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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 30 Dec 2010 01:00:37 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/30/t1293670688mg2de0euqhz2msc.htm/, Retrieved Fri, 03 May 2024 06:44:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=117208, Retrieved Fri, 03 May 2024 06:44:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi-Squared and McNemar Tests] [] [2010-11-16 14:33:59] [b98453cac15ba1066b407e146608df68]
- RMPD    [Multiple Regression] [] [2010-12-30 01:00:37] [393d554610c677f923bed472882d0fdb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13	360	3821	73	0	0
15	390	3850	70	0	0
17	304	3672	72	0	0
19.4	232	3210	78	0	0
24.3	151	3003	80	0	0
18.1	258	3410	78	0	0
20.2	232	3265	79	0	0
18	232	2789	73	0	0
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20	232	2914	75	0	0
21	199	2648	70	0	0
18	199	2774	70	0	0
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22.5	232	3085	76	0	0
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14	304	3672	73	0	0
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14	304	4257	74	0	0
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27.4	121	2670	79	0	0
24	107	2430	70	0	1
20	114	2582	73	0	1
23	115	2694	75	0	1
34.3	97	2188	80	0	1
20.3	131	2830	78	0	1
36.4	121	2950	80	0	1
29	98	2219	74	0	1
26	121	2234	70	0	1
21.5	121	2600	77	0	1
17	231	3907	75	0	0
22.4	231	3415	81	0	0
13	350	4100	73	0	0
25	181	2945	82	0	0
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12	455	4951	73	0	0
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30	111	2155	77	0	0
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22	140	2408	71	0	0
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24.5	98	2164	76	0	0
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10	307	4376	70	0	0
31	119	2720	82	0	0
15.5	400	4325	77	0	0
26	156	2585	82	0	0
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13	400	4422	72	0	0
35	72	1613	71	1	0
23.9	119	2405	78	1	0
32.9	119	2615	81	1	0
31.8	85	2020	79	1	0
40.8	85	2110	80	1	0
37	85	1975	81	1	0
32.7	168	2910	80	1	0
37.2	86	2019	80	1	0
38	91	1995	82	1	0
27.2	119	2300	78	1	0
28	97	2288	72	1	0
37	119	2434	80	1	0
22	108	2379	73	1	0
24	119	2545	75	1	0
32	83	2003	74	1	0
22	146	2815	77	1	0
24.2	146	2930	81	1	0
32	85	1990	76	1	0
31	79	1950	74	1	0
39.4	85	2070	78	1	0
33.5	85	1945	77	1	0
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20	225	3651	76	0	0
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36	135	2370	82	0	0
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27.9	156	2800	80	0	0
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34.4	98	2045	81	0	0
13	302	3870	76	0	0
10	360	4615	70	0	0
26.4	140	2870	80	0	0
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24	140	2865	82	0	0
36.1	98	1800	78	0	0
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16	302	4141	74	0	0
13	302	4294	72	0	0
14	302	4638	74	0	0
18.5	250	3525	77	0	0
18	250	3574	76	0	0
20.2	200	3060	81	0	0
22	232	2835	82	0	0
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14	351	4657	75	0	0
17.6	302	3725	79	0	0
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18	250	3021	73	0	0
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27	140	2790	82	0	0
13	302	3169	75	0	0
25.5	140	2755	77	0	0
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26	122	2451	74	0	0
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22	122	2395	72	0	0
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28	120	2625	82	0	0
16	351	4335	77	0	0
17	302	3449	70	0	0
19	250	3302	71	0	0
9	304	4732	70	0	0
32.4	107	2290	80	1	0
36	107	2205	82	1	0
31.5	98	2045	77	1	0
29.5	98	2135	78	1	0
24	120	2489	74	1	0
33	91	1795	76	1	0
38	91	1965	82	1	0
32	91	1965	82	1	0
35.1	81	1760	81	1	0
44.6	91	1850	80	1	0
33	91	1795	75	1	0
36.1	91	1800	78	1	0
33.7	107	2210	81	1	0
34.1	86	1975	79	1	0
18	70	2124	73	1	0
31.3	120	2542	80	1	0
31.6	120	2635	81	1	0
46.6	86	2110	80	1	0
34.1	91	1985	81	1	0
31	91	1970	82	1	0
37	91	2025	82	1	0
32.8	78	1985	78	1	0
21.5	80	2720	77	1	0
23.7	70	2420	80	1	0
19	70	2330	72	1	0
25.4	183	3530	79	0	1
30	146	3250	80	0	1
16.5	168	3820	76	0	1
23	122	2220	71	0	0
21	155	2472	73	0	0
15	302	4295	77	0	0
16.5	351	3955	79	0	0
36	98	2125	82	0	0
11	429	4633	72	0	0
12	429	4952	73	0	0
15	250	3432	75	0	0
20.2	302	3570	78	0	0
20.8	200	3070	78	0	0
19.8	200	2990	79	0	0
36	120	2160	82	1	0
38	262	3015	82	0	0
26.6	350	3725	81	0	0
19.9	260	3365	78	0	0
23.9	260	3420	79	0	0
17	260	4060	77	0	0
12	350	4456	72	0	0
11	350	3664	73	0	0
26.8	173	2700	79	0	0
23.8	151	2855	78	0	0
12	350	4499	73	0	0
25	116	2220	76	0	1
28	116	2123	71	0	1
24	116	2158	73	0	1
26	97	2300	74	0	1
30	79	2074	71	0	1
19	120	3270	76	0	1
23	120	2957	75	0	1
25	110	2672	70	0	1
27.2	141	3190	79	0	1
21	120	2979	72	0	1
28.1	141	3230	81	0	1
16.2	163	3410	78	0	1
14	340	3609	70	0	0
25.5	122	2300	77	0	0
39	86	1875	81	0	0
26	91	1955	71	0	0
13	360	4654	73	0	0
20	198	3102	74	0	0
22	198	2833	70	0	0
23	198	2904	73	0	0
18	225	3785	75	0	0
14	318	4237	73	0	0
14	318	4096	71	0	0
14	440	4312	70	0	0
15	318	4135	72	0	0
16	318	4498	75	0	0
34.2	105	2200	79	0	0
34.7	105	2215	81	0	0
38	105	2125	82	0	0
34.5	105	2150	79	0	0
27.2	135	2490	81	0	0
30	135	2385	81	0	0
23.2	156	2745	78	0	0
18	318	3436	70	0	0
16	225	3439	71	0	0
14	318	4077	72	0	0
18	225	3613	74	0	0
18	225	3121	73	0	0
22	225	3233	76	0	0
19	225	3264	75	0	0
20.5	225	3430	78	0	0
19	225	3630	77	0	0
13	318	3940	76	0	0
23	140	2592	75	0	0
14	400	4385	72	0	0
14	455	4425	70	0	0
16	400	4668	75	0	0
14	400	4464	71	0	0
19	250	3282	71	0	0
16	400	4278	73	0	0
16	400	4220	77	0	0
31	112	2575	82	0	0
21.5	231	3245	79	0	0
27	151	2735	82	0	0
33.5	151	2556	79	0	0
19.2	231	3535	78	0	0
13	400	5140	71	0	0
24.5	151	2740	77	0	0
18.5	250	3645	76	0	0
26	96	2189	72	0	1
27	101	2202	76	0	1
36	79	1825	77	0	1
25	104	2375	70	0	1
21.6	121	2795	78	0	1
24	121	2660	73	0	1
25	121	2671	75	0	1
26	108	2391	74	1	0
32.3	97	2065	81	1	0
30	97	1985	77	1	0
33.8	97	2145	80	1	0
20	97	2279	73	1	0
32	144	2665	82	1	0
21.1	134	2515	78	1	0
28	97	2155	76	1	0
29	97	2171	75	1	0
32.2	108	2265	80	1	0
32.4	108	2350	81	1	0
34	108	2245	82	1	0
31	71	1773	71	1	0
32	71	1836	74	1	0
27	97	2100	72	1	0
26	97	2265	77	1	0
38.1	89	1968	80	1	0
24	134	2702	75	1	0
25	113	2228	71	1	0
27.5	134	2560	78	1	0
31	76	1649	74	1	0
24	113	2278	72	1	0
29.8	134	2711	80	1	0
24	113	2372	70	1	0
25.4	168	2900	81	1	0
19	156	2930	76	1	0
20	156	2807	73	1	0
39.1	79	1755	81	1	0
37.7	89	2050	81	1	0
23	120	2506	72	1	0
35	122	2500	80	0	1
29.8	89	1845	80	0	1
26	97	1835	70	0	1
22	121	2511	72	0	1
25	90	2223	75	0	1
26	79	1963	74	0	1
30.5	97	2190	77	0	1
33	105	2190	81	0	1
27	97	1834	71	0	1
29	90	1937	75	0	1
29.5	97	1825	76	0	1
29	97	1940	77	0	1
43.1	90	1985	78	0	1
36	105	1980	82	0	1
31.5	89	1990	78	0	1
26	97	1950	73	0	1
23	97	2254	72	0	1
19	121	2868	73	0	1
18	121	2933	72	0	1
22	121	2945	75	0	1
20	130	3150	76	0	1
17	163	3140	78	0	1
30.7	145	3160	81	0	1
43.4	90	2335	80	0	1
44	97	2130	82	0	1
29	90	1937	76	0	1
41.5	98	2144	80	0	1
44.3	90	2085	80	0	1
31.9	89	1925	79	0	1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Herman Ole Andreas Wold' @ www.yougetit.org

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 15 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ www.yougetit.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117208&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]15 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ www.yougetit.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117208&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117208&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Herman Ole Andreas Wold' @ www.yougetit.org






Multiple Linear Regression - Estimated Regression Equation
MPG[t] = -19.5949213012208 + 0.00932120264360868Displ[t] -0.00681998045690182Weight[t] + 0.797990841371979Year[t] + 2.43807959073668OriginJapan[t] + 2.38304851707346OriginEurope[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
MPG[t] =  -19.5949213012208 +  0.00932120264360868Displ[t] -0.00681998045690182Weight[t] +  0.797990841371979Year[t] +  2.43807959073668OriginJapan[t] +  2.38304851707346OriginEurope[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117208&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]MPG[t] =  -19.5949213012208 +  0.00932120264360868Displ[t] -0.00681998045690182Weight[t] +  0.797990841371979Year[t] +  2.43807959073668OriginJapan[t] +  2.38304851707346OriginEurope[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117208&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117208&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
MPG[t] = -19.5949213012208 + 0.00932120264360868Displ[t] -0.00681998045690182Weight[t] + 0.797990841371979Year[t] + 2.43807959073668OriginJapan[t] + 2.38304851707346OriginEurope[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-19.59492130122084.063657-4.8222e-061e-06
Displ0.009321202643608680.0050011.86380.0631090.031555
Weight-0.006819980456901820.000564-12.099300
Year0.7979908413719790.05081115.705100
OriginJapan2.438079590736680.5308934.59246e-063e-06
OriginEurope2.383048517073460.560554.25132.7e-051.3e-05

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & -19.5949213012208 & 4.063657 & -4.822 & 2e-06 & 1e-06 \tabularnewline
Displ & 0.00932120264360868 & 0.005001 & 1.8638 & 0.063109 & 0.031555 \tabularnewline
Weight & -0.00681998045690182 & 0.000564 & -12.0993 & 0 & 0 \tabularnewline
Year & 0.797990841371979 & 0.050811 & 15.7051 & 0 & 0 \tabularnewline
OriginJapan & 2.43807959073668 & 0.530893 & 4.5924 & 6e-06 & 3e-06 \tabularnewline
OriginEurope & 2.38304851707346 & 0.56055 & 4.2513 & 2.7e-05 & 1.3e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117208&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]-19.5949213012208[/C][C]4.063657[/C][C]-4.822[/C][C]2e-06[/C][C]1e-06[/C][/ROW]
[ROW][C]Displ[/C][C]0.00932120264360868[/C][C]0.005001[/C][C]1.8638[/C][C]0.063109[/C][C]0.031555[/C][/ROW]
[ROW][C]Weight[/C][C]-0.00681998045690182[/C][C]0.000564[/C][C]-12.0993[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Year[/C][C]0.797990841371979[/C][C]0.050811[/C][C]15.7051[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]OriginJapan[/C][C]2.43807959073668[/C][C]0.530893[/C][C]4.5924[/C][C]6e-06[/C][C]3e-06[/C][/ROW]
[ROW][C]OriginEurope[/C][C]2.38304851707346[/C][C]0.56055[/C][C]4.2513[/C][C]2.7e-05[/C][C]1.3e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117208&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117208&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-19.59492130122084.063657-4.8222e-061e-06
Displ0.009321202643608680.0050011.86380.0631090.031555
Weight-0.006819980456901820.000564-12.099300
Year0.7979908413719790.05081115.705100
OriginJapan2.438079590736680.5308934.59246e-063e-06
OriginEurope2.383048517073460.560554.25132.7e-051.3e-05






Multiple Linear Regression - Regression Statistics
Multiple R0.905896689865256
R-squared0.820648812708828
Adjusted R-squared0.818325610800911
F-TEST (value)353.240417852756
F-TEST (DF numerator)5
F-TEST (DF denominator)386
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.32675009800069
Sum Squared Residuals4271.96475881537

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.905896689865256 \tabularnewline
R-squared & 0.820648812708828 \tabularnewline
Adjusted R-squared & 0.818325610800911 \tabularnewline
F-TEST (value) & 353.240417852756 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 386 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.32675009800069 \tabularnewline
Sum Squared Residuals & 4271.96475881537 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117208&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.905896689865256[/C][/ROW]
[ROW][C]R-squared[/C][C]0.820648812708828[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.818325610800911[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]353.240417852756[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]386[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.32675009800069[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]4271.96475881537[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117208&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117208&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.905896689865256
R-squared0.820648812708828
Adjusted R-squared0.818325610800911
F-TEST (value)353.240417852756
F-TEST (DF numerator)5
F-TEST (DF denominator)386
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.32675009800069
Sum Squared Residuals4271.96475881537






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.9548977448107-2.95489774481071
21513.6427818667531.357218133247
31715.65109664347521.34890335652482
419.422.9187460724559-3.5187460724559
524.325.1714462956462-0.87144629564624
618.121.7971012498094-3.69710124980935
720.223.3416379886983-3.14163798869828
81821.8000036379517-3.80000363795167
91921.2611189260275-2.26111892602749
102022.5434877635829-2.5434877635829
112120.06004867101980.939951328980195
121819.2007311334502-1.20073113345018
131820.736086686675-2.73608668667498
141921.8341566681506-2.83415666815064
1522.522.17526194682470.324738053175334
161819.2665166048975-1.26651660489752
171416.4490874848472-2.44908748484718
181517.2207349794848-2.22073497948484
1915.516.8652656764616-1.36526567646159
201617.0911022228892-1.09110222288924
211816.80085170721371.1991482927863
221413.25738975893160.742610241068404
231514.15070094295680.849299057043198
241920.5179535678831-1.51795356788306
2517.521.6810553262131-4.1810553262131
261615.68509028993080.314909710069219
2727.426.36487286711431.0351271328857
282423.07230228448590.927697715514132
292024.494886197658-4.49488619765799
302325.3363512718726-2.33635127187255
3134.332.60943394233981.69056605766019
3220.326.9519456961476-6.65194569614758
3336.427.63631769762728.76368230237277
342927.61939070258761.38060929741241
352624.53951529104911.46048470895085
3621.527.6293383334269-6.12933833342693
371715.76192596723581.23807403276422
3822.423.9053014002634-1.50530140026335
391313.9589111708992-0.9589111708992
402527.4426229241988-2.44262292419875
411310.6717337185872.32826628141301
4220.621.750028192139-1.15002819213898
43129.133834079654652.86616592034534
441419.4591251076606-5.45912510766062
4516.916.9736613003366-0.0736613003366014
461310.41928818585272.58071181414731
473028.18796909323871.81203090676131
4817.721.3067294624404-3.60672946244036
492121.6816690038266-0.681669003826563
5020.520.6451382302064-0.145138230206418
5126.628.4791899451581-1.87918994515808
521514.34067069274230.659329307257695
5328.426.64450894642261.75549105357744
542320.11085231051142.88914768948856
5516.514.44328916708262.05671083291737
562524.81636127800330.183638721996693
571616.0072286220334-0.00722862203336408
581513.23609949829651.76390050170346
592727.128886942606-0.128886942605986
601311.94249841676741.05750158323263
611720.1005970189632-3.10059701896316
6217.518.2318161179431-0.731816117943128
632829.1182532971364-1.11825329713638
643430.55044919308583.44955080691424
652728.8795539811448-1.87955398114481
661312.77374857676590.226251423234147
671716.68901415606570.310985843934316
681815.22883528542162.77116471457842
691616.000355513662-0.000355513661996265
7017.515.1491318235092.35086817649096
712927.96602463796111.03397536203889
723028.86478430024381.13521569975624
7330.528.77607142638961.72392857361043
7432.130.69946529897931.40053470102072
7523.528.0704581621963-4.57045816219631
762827.38793994413930.612060055860675
7728.827.36107393884961.43892606115041
7817.520.1743429370293-2.67434293702931
79118.30744883323872.6925511667613
801311.97424373002631.02575626997369
811411.61955161835292.38044838164706
821410.80206868566553.1979313143345
831314.7227489820722-1.7227489820722
8420.522.99556651299-2.49556651299002
8519.221.349086725878-2.14908672587796
861514.34297215385340.657027846146587
8715.516.7075758066885-1.2075758066885
8819.222.1328980672054-2.93289806720544
891514.08167081912340.918329180876566
902020.7293898426223-0.729389842622299
911519.0352468169833-4.03524681698331
921818.9943800621564-0.994380062156362
932220.51528883195991.48471116804007
941618.6328148421116-2.63281484211163
952022.7428747074473-2.74287470744729
962123.5886054120176-2.58860541201758
972523.42497900896641.5750209910336
982221.94488386607530.0551161339246882
992822.92696105186925.07303894813083
10024.527.2074227933877-2.70742279338769
1011316.6597828155757-3.65978281557572
102109.281812327003190.718187672996812
1033128.39920396309792.60079603690207
10415.516.0824390657646-0.582439065764638
1052629.6647858225932-3.66478582259319
10617.623.5083751615566-5.90837516155661
10718.519.9312651186715-1.43126511867145
1081310.46713181869132.53286818130868
1091311.43094675458531.56905324541473
1103529.17100614028365.82899385971645
11123.929.7936140322708-5.89361403227077
11232.930.75539066043732.14460933956268
11331.832.9003764596673-1.10037645966726
11440.833.08456905991817.71543094008193
1153734.80325726297182.1967427370282
11632.728.40224451381614.29775548618387
11737.233.71450848413973.48549151586026
1183835.52077571106742.47922428893261
11927.230.5097119802455-3.30971198024546
1202825.5985402393372.40145976066298
1213731.19181628176465.80818371823543
1222225.8784460882106-3.87844608821063
1232426.4448442441886-2.44484424418858
1243229.00771951528752.99228048471252
1252226.4511036749465-4.45110367494648
12624.228.8587692878907-4.65876928789068
1273230.71100334925841.28899665074163
1283129.33189366892881.66810633107116
12939.431.76138659545027.63861340454981
13033.531.81589331119091.68410668880907
1312725.08011546878351.91988453121645
1322725.87810631015551.12189368984447
1332929.8782393944915-0.878239394491522
13425.828.6280956652297-2.82809566522965
13518.620.0573056666209-1.45730566662089
13619.123.2832626785644-4.18326267856438
13720.622.6284914267873-2.02849142678734
1382018.2499045897131.75009541028703
1391515.5348678393786-0.534867839378627
1403630.93533636531135.06466363468869
1412626.5868045718096-0.586804571809622
14227.926.60250834161531.29749165838465
1432825.8028507273142.19714927268597
1442824.01545942789983.98454057210023
1452524.26995808394020.730041916059763
14635.731.29957045127224.40042954872783
14733.528.61239189542394.88760810457607
1481615.44080696929850.559193030701504
1491515.863486373883-0.863486373883012
1501412.02389050456181.97610949543825
1511318.4074984680508-5.40749846805079
152119.343425673341471.65657432665853
1531518.4414389865919-3.4414389865919
15419.420.1398797599328-0.739879759932783
15517.517.7869865023017-0.286986502301654
156126.839445884743275.16055411525673
15715.516.5797968335156-1.07979683351557
15830.928.41853418448142.48146581551861
1593231.44683489957890.553165100421058
16018.220.2899724578991-2.08997245789909
1612626.5076807601981-0.507680760198128
1622627.6030328778362-1.6030328778362
1633026.18248314239843.81751685760155
1642428.3018389121548-4.30183891215482
1652928.94239690273680.057603097263206
1662827.62836799718310.37163200281692
16737.332.15107475160655.14892524839351
1683128.93586357242052.06413642757947
169128.928067054816763.07193294518324
170138.42328224517714.5767177548229
17115.519.0698965227922-3.56989652279217
17229.929.72426122155680.17573877844321
17334.432.00895467461892.3910453253811
1741317.4740614732093-4.47406147320934
175108.14586073791491.85413926208509
17626.425.97597046733450.424029532665519
17720.224.2913627998014-4.09136279980137
17825.125.4029858531258-0.302985853125794
17922.325.0415800168245-2.74158001682446
1802427.6060520523629-3.60605205236295
18136.131.28587736244394.81412263755609
18218.123.605330159793-5.50533015979301
1831412.97246209892071.02753790107932
1841412.00397174612621.99602825387385
1851510.6576983655154.34230163448499
1861413.90705231050630.092947689493709
18714.515.577907145115-1.07790714511504
1881614.0298650866451.97013491335501
1891311.39042639399511.60957360600495
1901410.64033479956483.35966520043522
19118.520.1402430347448-1.6402430347448
1921819.0080731509846-1.00807315098463
19320.226.0374371805116-5.83743718051163
1942228.668202109282-6.66820210928199
1951312.17457751337760.82542248662237
1961411.76548494179252.23451505820755
19717.620.856931163576-3.25693116357604
1981521.0471941796838-6.04719417968381
1991820.3855498195354-2.3855498195354
2002120.48538868153440.514611318465575
2012422.3748420355831.62515796441698
2021817.9848104428770.0151895571229702
2032728.1175505866306-1.11755058663058
2041321.4568769321255-8.45687693212554
20525.524.36629569576231.13370430423775
2061821.4974957703396-3.49749577033965
2071924.0414419860107-5.04144198601069
2082323.5614317460189-0.561431746018907
2092623.87781558295952.12218441704049
21026.524.86410114120161.63589885879838
2112222.6637528058021-0.663752805802058
2122123.8163295030185-2.81632950301847
2132829.0564233091472-1.05642330914721
2141615.55750033165880.442499668341203
2151715.55732819733311.44267180266687
2161916.8731536284022.12684637159797
21796.825935676415312.17406432358469
21832.432.06203903583510.337960964164866
2193634.23771905741571.76228094258425
22031.531.25507089986770.244929100132335
22129.531.4392635001185-1.93926350011848
2222426.0380935110467-2.03809351104671
2233332.09682675421590.903173245784119
2243835.72537512477442.27462487522556
2253235.7253751247744-3.72537512477444
22635.136.2322682506313-1.13226825063125
22744.634.91369119457429.6863088054258
2283331.29883591284391.7011640871561
22936.133.65870853467532.44129146532467
23033.733.40562831375930.294371686240746
23134.133.21659678287140.883403217128556
2321827.2633354042635-9.26333540426346
23331.330.46457959506280.835420404937216
23431.630.62831225394290.971687746057106
23546.633.093890262561713.5061097374383
23634.134.7909846742644-0.690984674264428
2373135.6912752224899-4.69127522248993
2383735.31617629736031.68382370263967
23932.832.27583651578160.524163484218416
24021.526.483802443874-4.98380244387398
24123.730.8305570786244-7.13055707862438
2421925.0604285887697-6.06042858876971
24325.423.46065275515591.93934724484407
2443025.82335362664694.1766463733531
24516.518.9490678588843-2.44906785888434
2462323.0592585443879-0.0592585443878986
2472123.2442048392317-2.24420483923168
2481515.373560620398-0.373560620398045
24916.519.7450745880254-3.24507458802545
2503632.26134707943873.73865292056127
2511110.26224575484360.737754245156368
252128.884662830463933.11533716953607
2531519.1785195344927-4.17851953449271
25420.221.1160372930238-0.916037293023845
25520.823.5752648518267-2.77526485182667
25619.824.9188541297508-5.1188541297508
2573634.66579381234321.33420618765676
2583827.720241706347910.2797582936521
25926.622.90033057321323.69966942678679
26019.922.1226427756572-2.22264277565716
26123.922.54553469189951.35446530810046
2621716.58476551673840.415234483261589
2631210.73300728687021.26699271312983
2641116.9324226501084-5.9324226501084
26526.826.64497599087490.155024009125105
26623.824.5848217205237-0.784821720523743
2671211.23773896859540.762261031404626
2682529.3763340524596-4.3763340524596
2692826.04791794991921.95208205008082
2702427.4052003166716-3.40520031667158
2712627.0576510829349-1.05765108293493
2723026.03721249449393.96278750550615
2731922.2526393832871-3.25263938328712
2742323.5893024249254-0.589302424925415
2752521.44983062184653.55016937815355
27627.225.3879555994711.81204440052901
2772121.0452903307576-0.0452903307576384
27828.126.71113806393891.38886193606113
27916.223.29463551574-7.09463551574
2801414.820337024686-0.820337024685971
28125.527.3016051560676-1.80160515606763
2823933.05649692056895.94350307943109
2832624.5775960835151.42240391648499
2841310.27385402421172.72614597578832
2852020.1464197064307-0.146419706430684
2862218.78903108384943.21096891615064
2872320.69878499552532.30121500447473
2881816.53803636711621.46196363288385
2891412.72629536370821.27370463629183
2901412.09193092538741.90806907461263
2911410.95801102784493.04198897215514
2921512.62394252894022.37605747105982
2931612.54226214720083.45773785279924
29434.229.42112443956044.77887556043958
29534.730.91480641545083.78519358454915
2963832.3265954979445.67340450205601
29734.529.76212346240554.73787653759449
29827.229.3189478691111-2.11894786911111
2993030.0350458170858-0.0350458170857983
30023.225.381625584001-2.18162558400099
3011815.79512718557062.2048728144294
3021615.70578623971630.294213760283733
3031413.01950139544050.980498604559514
3041816.91308216433131.08691783566871
3051819.470521707755-1.470521707755
3062221.10065642069790.899343579302063
3071920.091246185162-1.091246185162
30820.521.3531019534322-0.853101953432235
3091919.1911150206799-0.191115020679893
3101317.145802083524-4.14580208352395
3112323.8819708274933-0.881970827493291
3121411.68328603149062.31671396850937
3131410.32717127586913.67282872413092
3141612.14720408630343.85279591369664
3151410.34651673402343.65348326597659
3161917.00955323754011.99044676245993
3171613.21101478175112.78898521824889
3181616.7985370137393-0.79853701373933
3193129.32285271084341.67714728915657
32021.523.4687163951927-1.9687163951927
3212728.5951827408399-1.59518274083988
32233.527.42198671850946.07801328149063
32319.220.6929312213192-1.4929312213192
324135.736209945157787.26379005484222
32524.524.5711286316955-0.0711286316954749
32618.518.5238545385446-0.0238545385446018
3272626.2093660282635-0.20936602826347
3282729.3592756610297-2.3592756610297
3293632.52333267649433.47666732350572
3302523.41943760168461.58056239831536
33121.627.0974329857031-5.49743298570305
3322424.0281761405249-0.0281761405249066
3332525.5491380382429-0.549138038242944
3342626.5945971640998-0.594597164099785
33532.334.3013134535739-2.00131345357394
3363031.6549485246382-1.65494852463816
33733.832.95772417564980.842275824350186
3382026.4579109048211-6.45791090482112
3393231.44541254505440.554587454945572
34021.129.1832342216657-8.0832342216657
3412829.6975610055929-1.69756100559288
3422928.79045047691050.209549523089532
34332.232.2418597499013-0.0418597499012848
34432.432.4601522524366-0.0601522524366136
3453433.97424104178330.0257589582167182
3463128.07048806453572.92951193546435
3473230.03480181986681.96519818013322
3482726.88069656523460.119303434765439
3492629.7453539967057-3.74535399670565
35038.134.09029109537264.00970890462744
3512425.5139253521091-1.51392535210912
3522525.3588874676769-0.358887467676887
35327.528.8763351011051-1.37633510110512
3543131.3567441785255-0.35674417852546
3552425.8158792862038-1.81587928620377
35629.829.44249973485690.357500265143102
3572423.5788194405110.421180559488953
35825.429.2684351597571-3.86843515975713
3591924.9620271074669-5.96202710746688
3602023.4069121795499-3.40691217954986
36139.136.24772574762852.85227425237146
36237.734.32904353927863.37095646072141
3632324.3261721605354-1.32617216053542
3643530.71463010587674.28536989412334
36529.834.8741176179083-5.07411761790827
3662627.0369786299064-1.03697862990637
3672224.2463623872313-2.2463623872313
3682528.3155320009831-3.31553200098309
3692629.1882028493259-3.18820284932589
37030.530.20182145731010.29817854268993
3713333.4683544439469-0.468354443946855
3722727.8417894517352-0.841789451735246
3732930.266046411657-1.26604641165701
37429.531.8931234827073-2.39312348270726
3752931.9068165715355-2.90681657153553
37643.132.332659873841710.7673401261583
3773635.69854118126820.301458818731784
37831.532.2892387689135-0.789238768913546
3792628.6466534014786-2.64665340147859
3802325.7753885012085-2.77538850120846
3811922.6096202054893-3.60962020548933
3821821.3683306344187-3.36833063441873
3832223.6804633930518-1.68046339305185
3842023.1642490645514-3.16424906455143
3851725.1360302391035-8.13603023910349
38630.727.22582150649643.47417849350357
38743.431.5416483966711.85835160333
3884434.60097449158419.39902550841592
3892931.064037253029-2.06403725302899
39041.532.91883428508718.5811657149129
39144.333.246643510895411.0533564891046
39231.933.5305283399841-1.63052833998414

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.9548977448107 & -2.95489774481071 \tabularnewline
2 & 15 & 13.642781866753 & 1.357218133247 \tabularnewline
3 & 17 & 15.6510966434752 & 1.34890335652482 \tabularnewline
4 & 19.4 & 22.9187460724559 & -3.5187460724559 \tabularnewline
5 & 24.3 & 25.1714462956462 & -0.87144629564624 \tabularnewline
6 & 18.1 & 21.7971012498094 & -3.69710124980935 \tabularnewline
7 & 20.2 & 23.3416379886983 & -3.14163798869828 \tabularnewline
8 & 18 & 21.8000036379517 & -3.80000363795167 \tabularnewline
9 & 19 & 21.2611189260275 & -2.26111892602749 \tabularnewline
10 & 20 & 22.5434877635829 & -2.5434877635829 \tabularnewline
11 & 21 & 20.0600486710198 & 0.939951328980195 \tabularnewline
12 & 18 & 19.2007311334502 & -1.20073113345018 \tabularnewline
13 & 18 & 20.736086686675 & -2.73608668667498 \tabularnewline
14 & 19 & 21.8341566681506 & -2.83415666815064 \tabularnewline
15 & 22.5 & 22.1752619468247 & 0.324738053175334 \tabularnewline
16 & 18 & 19.2665166048975 & -1.26651660489752 \tabularnewline
17 & 14 & 16.4490874848472 & -2.44908748484718 \tabularnewline
18 & 15 & 17.2207349794848 & -2.22073497948484 \tabularnewline
19 & 15.5 & 16.8652656764616 & -1.36526567646159 \tabularnewline
20 & 16 & 17.0911022228892 & -1.09110222288924 \tabularnewline
21 & 18 & 16.8008517072137 & 1.1991482927863 \tabularnewline
22 & 14 & 13.2573897589316 & 0.742610241068404 \tabularnewline
23 & 15 & 14.1507009429568 & 0.849299057043198 \tabularnewline
24 & 19 & 20.5179535678831 & -1.51795356788306 \tabularnewline
25 & 17.5 & 21.6810553262131 & -4.1810553262131 \tabularnewline
26 & 16 & 15.6850902899308 & 0.314909710069219 \tabularnewline
27 & 27.4 & 26.3648728671143 & 1.0351271328857 \tabularnewline
28 & 24 & 23.0723022844859 & 0.927697715514132 \tabularnewline
29 & 20 & 24.494886197658 & -4.49488619765799 \tabularnewline
30 & 23 & 25.3363512718726 & -2.33635127187255 \tabularnewline
31 & 34.3 & 32.6094339423398 & 1.69056605766019 \tabularnewline
32 & 20.3 & 26.9519456961476 & -6.65194569614758 \tabularnewline
33 & 36.4 & 27.6363176976272 & 8.76368230237277 \tabularnewline
34 & 29 & 27.6193907025876 & 1.38060929741241 \tabularnewline
35 & 26 & 24.5395152910491 & 1.46048470895085 \tabularnewline
36 & 21.5 & 27.6293383334269 & -6.12933833342693 \tabularnewline
37 & 17 & 15.7619259672358 & 1.23807403276422 \tabularnewline
38 & 22.4 & 23.9053014002634 & -1.50530140026335 \tabularnewline
39 & 13 & 13.9589111708992 & -0.9589111708992 \tabularnewline
40 & 25 & 27.4426229241988 & -2.44262292419875 \tabularnewline
41 & 13 & 10.671733718587 & 2.32826628141301 \tabularnewline
42 & 20.6 & 21.750028192139 & -1.15002819213898 \tabularnewline
43 & 12 & 9.13383407965465 & 2.86616592034534 \tabularnewline
44 & 14 & 19.4591251076606 & -5.45912510766062 \tabularnewline
45 & 16.9 & 16.9736613003366 & -0.0736613003366014 \tabularnewline
46 & 13 & 10.4192881858527 & 2.58071181414731 \tabularnewline
47 & 30 & 28.1879690932387 & 1.81203090676131 \tabularnewline
48 & 17.7 & 21.3067294624404 & -3.60672946244036 \tabularnewline
49 & 21 & 21.6816690038266 & -0.681669003826563 \tabularnewline
50 & 20.5 & 20.6451382302064 & -0.145138230206418 \tabularnewline
51 & 26.6 & 28.4791899451581 & -1.87918994515808 \tabularnewline
52 & 15 & 14.3406706927423 & 0.659329307257695 \tabularnewline
53 & 28.4 & 26.6445089464226 & 1.75549105357744 \tabularnewline
54 & 23 & 20.1108523105114 & 2.88914768948856 \tabularnewline
55 & 16.5 & 14.4432891670826 & 2.05671083291737 \tabularnewline
56 & 25 & 24.8163612780033 & 0.183638721996693 \tabularnewline
57 & 16 & 16.0072286220334 & -0.00722862203336408 \tabularnewline
58 & 15 & 13.2360994982965 & 1.76390050170346 \tabularnewline
59 & 27 & 27.128886942606 & -0.128886942605986 \tabularnewline
60 & 13 & 11.9424984167674 & 1.05750158323263 \tabularnewline
61 & 17 & 20.1005970189632 & -3.10059701896316 \tabularnewline
62 & 17.5 & 18.2318161179431 & -0.731816117943128 \tabularnewline
63 & 28 & 29.1182532971364 & -1.11825329713638 \tabularnewline
64 & 34 & 30.5504491930858 & 3.44955080691424 \tabularnewline
65 & 27 & 28.8795539811448 & -1.87955398114481 \tabularnewline
66 & 13 & 12.7737485767659 & 0.226251423234147 \tabularnewline
67 & 17 & 16.6890141560657 & 0.310985843934316 \tabularnewline
68 & 18 & 15.2288352854216 & 2.77116471457842 \tabularnewline
69 & 16 & 16.000355513662 & -0.000355513661996265 \tabularnewline
70 & 17.5 & 15.149131823509 & 2.35086817649096 \tabularnewline
71 & 29 & 27.9660246379611 & 1.03397536203889 \tabularnewline
72 & 30 & 28.8647843002438 & 1.13521569975624 \tabularnewline
73 & 30.5 & 28.7760714263896 & 1.72392857361043 \tabularnewline
74 & 32.1 & 30.6994652989793 & 1.40053470102072 \tabularnewline
75 & 23.5 & 28.0704581621963 & -4.57045816219631 \tabularnewline
76 & 28 & 27.3879399441393 & 0.612060055860675 \tabularnewline
77 & 28.8 & 27.3610739388496 & 1.43892606115041 \tabularnewline
78 & 17.5 & 20.1743429370293 & -2.67434293702931 \tabularnewline
79 & 11 & 8.3074488332387 & 2.6925511667613 \tabularnewline
80 & 13 & 11.9742437300263 & 1.02575626997369 \tabularnewline
81 & 14 & 11.6195516183529 & 2.38044838164706 \tabularnewline
82 & 14 & 10.8020686856655 & 3.1979313143345 \tabularnewline
83 & 13 & 14.7227489820722 & -1.7227489820722 \tabularnewline
84 & 20.5 & 22.99556651299 & -2.49556651299002 \tabularnewline
85 & 19.2 & 21.349086725878 & -2.14908672587796 \tabularnewline
86 & 15 & 14.3429721538534 & 0.657027846146587 \tabularnewline
87 & 15.5 & 16.7075758066885 & -1.2075758066885 \tabularnewline
88 & 19.2 & 22.1328980672054 & -2.93289806720544 \tabularnewline
89 & 15 & 14.0816708191234 & 0.918329180876566 \tabularnewline
90 & 20 & 20.7293898426223 & -0.729389842622299 \tabularnewline
91 & 15 & 19.0352468169833 & -4.03524681698331 \tabularnewline
92 & 18 & 18.9943800621564 & -0.994380062156362 \tabularnewline
93 & 22 & 20.5152888319599 & 1.48471116804007 \tabularnewline
94 & 16 & 18.6328148421116 & -2.63281484211163 \tabularnewline
95 & 20 & 22.7428747074473 & -2.74287470744729 \tabularnewline
96 & 21 & 23.5886054120176 & -2.58860541201758 \tabularnewline
97 & 25 & 23.4249790089664 & 1.5750209910336 \tabularnewline
98 & 22 & 21.9448838660753 & 0.0551161339246882 \tabularnewline
99 & 28 & 22.9269610518692 & 5.07303894813083 \tabularnewline
100 & 24.5 & 27.2074227933877 & -2.70742279338769 \tabularnewline
101 & 13 & 16.6597828155757 & -3.65978281557572 \tabularnewline
102 & 10 & 9.28181232700319 & 0.718187672996812 \tabularnewline
103 & 31 & 28.3992039630979 & 2.60079603690207 \tabularnewline
104 & 15.5 & 16.0824390657646 & -0.582439065764638 \tabularnewline
105 & 26 & 29.6647858225932 & -3.66478582259319 \tabularnewline
106 & 17.6 & 23.5083751615566 & -5.90837516155661 \tabularnewline
107 & 18.5 & 19.9312651186715 & -1.43126511867145 \tabularnewline
108 & 13 & 10.4671318186913 & 2.53286818130868 \tabularnewline
109 & 13 & 11.4309467545853 & 1.56905324541473 \tabularnewline
110 & 35 & 29.1710061402836 & 5.82899385971645 \tabularnewline
111 & 23.9 & 29.7936140322708 & -5.89361403227077 \tabularnewline
112 & 32.9 & 30.7553906604373 & 2.14460933956268 \tabularnewline
113 & 31.8 & 32.9003764596673 & -1.10037645966726 \tabularnewline
114 & 40.8 & 33.0845690599181 & 7.71543094008193 \tabularnewline
115 & 37 & 34.8032572629718 & 2.1967427370282 \tabularnewline
116 & 32.7 & 28.4022445138161 & 4.29775548618387 \tabularnewline
117 & 37.2 & 33.7145084841397 & 3.48549151586026 \tabularnewline
118 & 38 & 35.5207757110674 & 2.47922428893261 \tabularnewline
119 & 27.2 & 30.5097119802455 & -3.30971198024546 \tabularnewline
120 & 28 & 25.598540239337 & 2.40145976066298 \tabularnewline
121 & 37 & 31.1918162817646 & 5.80818371823543 \tabularnewline
122 & 22 & 25.8784460882106 & -3.87844608821063 \tabularnewline
123 & 24 & 26.4448442441886 & -2.44484424418858 \tabularnewline
124 & 32 & 29.0077195152875 & 2.99228048471252 \tabularnewline
125 & 22 & 26.4511036749465 & -4.45110367494648 \tabularnewline
126 & 24.2 & 28.8587692878907 & -4.65876928789068 \tabularnewline
127 & 32 & 30.7110033492584 & 1.28899665074163 \tabularnewline
128 & 31 & 29.3318936689288 & 1.66810633107116 \tabularnewline
129 & 39.4 & 31.7613865954502 & 7.63861340454981 \tabularnewline
130 & 33.5 & 31.8158933111909 & 1.68410668880907 \tabularnewline
131 & 27 & 25.0801154687835 & 1.91988453121645 \tabularnewline
132 & 27 & 25.8781063101555 & 1.12189368984447 \tabularnewline
133 & 29 & 29.8782393944915 & -0.878239394491522 \tabularnewline
134 & 25.8 & 28.6280956652297 & -2.82809566522965 \tabularnewline
135 & 18.6 & 20.0573056666209 & -1.45730566662089 \tabularnewline
136 & 19.1 & 23.2832626785644 & -4.18326267856438 \tabularnewline
137 & 20.6 & 22.6284914267873 & -2.02849142678734 \tabularnewline
138 & 20 & 18.249904589713 & 1.75009541028703 \tabularnewline
139 & 15 & 15.5348678393786 & -0.534867839378627 \tabularnewline
140 & 36 & 30.9353363653113 & 5.06466363468869 \tabularnewline
141 & 26 & 26.5868045718096 & -0.586804571809622 \tabularnewline
142 & 27.9 & 26.6025083416153 & 1.29749165838465 \tabularnewline
143 & 28 & 25.802850727314 & 2.19714927268597 \tabularnewline
144 & 28 & 24.0154594278998 & 3.98454057210023 \tabularnewline
145 & 25 & 24.2699580839402 & 0.730041916059763 \tabularnewline
146 & 35.7 & 31.2995704512722 & 4.40042954872783 \tabularnewline
147 & 33.5 & 28.6123918954239 & 4.88760810457607 \tabularnewline
148 & 16 & 15.4408069692985 & 0.559193030701504 \tabularnewline
149 & 15 & 15.863486373883 & -0.863486373883012 \tabularnewline
150 & 14 & 12.0238905045618 & 1.97610949543825 \tabularnewline
151 & 13 & 18.4074984680508 & -5.40749846805079 \tabularnewline
152 & 11 & 9.34342567334147 & 1.65657432665853 \tabularnewline
153 & 15 & 18.4414389865919 & -3.4414389865919 \tabularnewline
154 & 19.4 & 20.1398797599328 & -0.739879759932783 \tabularnewline
155 & 17.5 & 17.7869865023017 & -0.286986502301654 \tabularnewline
156 & 12 & 6.83944588474327 & 5.16055411525673 \tabularnewline
157 & 15.5 & 16.5797968335156 & -1.07979683351557 \tabularnewline
158 & 30.9 & 28.4185341844814 & 2.48146581551861 \tabularnewline
159 & 32 & 31.4468348995789 & 0.553165100421058 \tabularnewline
160 & 18.2 & 20.2899724578991 & -2.08997245789909 \tabularnewline
161 & 26 & 26.5076807601981 & -0.507680760198128 \tabularnewline
162 & 26 & 27.6030328778362 & -1.6030328778362 \tabularnewline
163 & 30 & 26.1824831423984 & 3.81751685760155 \tabularnewline
164 & 24 & 28.3018389121548 & -4.30183891215482 \tabularnewline
165 & 29 & 28.9423969027368 & 0.057603097263206 \tabularnewline
166 & 28 & 27.6283679971831 & 0.37163200281692 \tabularnewline
167 & 37.3 & 32.1510747516065 & 5.14892524839351 \tabularnewline
168 & 31 & 28.9358635724205 & 2.06413642757947 \tabularnewline
169 & 12 & 8.92806705481676 & 3.07193294518324 \tabularnewline
170 & 13 & 8.4232822451771 & 4.5767177548229 \tabularnewline
171 & 15.5 & 19.0698965227922 & -3.56989652279217 \tabularnewline
172 & 29.9 & 29.7242612215568 & 0.17573877844321 \tabularnewline
173 & 34.4 & 32.0089546746189 & 2.3910453253811 \tabularnewline
174 & 13 & 17.4740614732093 & -4.47406147320934 \tabularnewline
175 & 10 & 8.1458607379149 & 1.85413926208509 \tabularnewline
176 & 26.4 & 25.9759704673345 & 0.424029532665519 \tabularnewline
177 & 20.2 & 24.2913627998014 & -4.09136279980137 \tabularnewline
178 & 25.1 & 25.4029858531258 & -0.302985853125794 \tabularnewline
179 & 22.3 & 25.0415800168245 & -2.74158001682446 \tabularnewline
180 & 24 & 27.6060520523629 & -3.60605205236295 \tabularnewline
181 & 36.1 & 31.2858773624439 & 4.81412263755609 \tabularnewline
182 & 18.1 & 23.605330159793 & -5.50533015979301 \tabularnewline
183 & 14 & 12.9724620989207 & 1.02753790107932 \tabularnewline
184 & 14 & 12.0039717461262 & 1.99602825387385 \tabularnewline
185 & 15 & 10.657698365515 & 4.34230163448499 \tabularnewline
186 & 14 & 13.9070523105063 & 0.092947689493709 \tabularnewline
187 & 14.5 & 15.577907145115 & -1.07790714511504 \tabularnewline
188 & 16 & 14.029865086645 & 1.97013491335501 \tabularnewline
189 & 13 & 11.3904263939951 & 1.60957360600495 \tabularnewline
190 & 14 & 10.6403347995648 & 3.35966520043522 \tabularnewline
191 & 18.5 & 20.1402430347448 & -1.6402430347448 \tabularnewline
192 & 18 & 19.0080731509846 & -1.00807315098463 \tabularnewline
193 & 20.2 & 26.0374371805116 & -5.83743718051163 \tabularnewline
194 & 22 & 28.668202109282 & -6.66820210928199 \tabularnewline
195 & 13 & 12.1745775133776 & 0.82542248662237 \tabularnewline
196 & 14 & 11.7654849417925 & 2.23451505820755 \tabularnewline
197 & 17.6 & 20.856931163576 & -3.25693116357604 \tabularnewline
198 & 15 & 21.0471941796838 & -6.04719417968381 \tabularnewline
199 & 18 & 20.3855498195354 & -2.3855498195354 \tabularnewline
200 & 21 & 20.4853886815344 & 0.514611318465575 \tabularnewline
201 & 24 & 22.374842035583 & 1.62515796441698 \tabularnewline
202 & 18 & 17.984810442877 & 0.0151895571229702 \tabularnewline
203 & 27 & 28.1175505866306 & -1.11755058663058 \tabularnewline
204 & 13 & 21.4568769321255 & -8.45687693212554 \tabularnewline
205 & 25.5 & 24.3662956957623 & 1.13370430423775 \tabularnewline
206 & 18 & 21.4974957703396 & -3.49749577033965 \tabularnewline
207 & 19 & 24.0414419860107 & -5.04144198601069 \tabularnewline
208 & 23 & 23.5614317460189 & -0.561431746018907 \tabularnewline
209 & 26 & 23.8778155829595 & 2.12218441704049 \tabularnewline
210 & 26.5 & 24.8641011412016 & 1.63589885879838 \tabularnewline
211 & 22 & 22.6637528058021 & -0.663752805802058 \tabularnewline
212 & 21 & 23.8163295030185 & -2.81632950301847 \tabularnewline
213 & 28 & 29.0564233091472 & -1.05642330914721 \tabularnewline
214 & 16 & 15.5575003316588 & 0.442499668341203 \tabularnewline
215 & 17 & 15.5573281973331 & 1.44267180266687 \tabularnewline
216 & 19 & 16.873153628402 & 2.12684637159797 \tabularnewline
217 & 9 & 6.82593567641531 & 2.17406432358469 \tabularnewline
218 & 32.4 & 32.0620390358351 & 0.337960964164866 \tabularnewline
219 & 36 & 34.2377190574157 & 1.76228094258425 \tabularnewline
220 & 31.5 & 31.2550708998677 & 0.244929100132335 \tabularnewline
221 & 29.5 & 31.4392635001185 & -1.93926350011848 \tabularnewline
222 & 24 & 26.0380935110467 & -2.03809351104671 \tabularnewline
223 & 33 & 32.0968267542159 & 0.903173245784119 \tabularnewline
224 & 38 & 35.7253751247744 & 2.27462487522556 \tabularnewline
225 & 32 & 35.7253751247744 & -3.72537512477444 \tabularnewline
226 & 35.1 & 36.2322682506313 & -1.13226825063125 \tabularnewline
227 & 44.6 & 34.9136911945742 & 9.6863088054258 \tabularnewline
228 & 33 & 31.2988359128439 & 1.7011640871561 \tabularnewline
229 & 36.1 & 33.6587085346753 & 2.44129146532467 \tabularnewline
230 & 33.7 & 33.4056283137593 & 0.294371686240746 \tabularnewline
231 & 34.1 & 33.2165967828714 & 0.883403217128556 \tabularnewline
232 & 18 & 27.2633354042635 & -9.26333540426346 \tabularnewline
233 & 31.3 & 30.4645795950628 & 0.835420404937216 \tabularnewline
234 & 31.6 & 30.6283122539429 & 0.971687746057106 \tabularnewline
235 & 46.6 & 33.0938902625617 & 13.5061097374383 \tabularnewline
236 & 34.1 & 34.7909846742644 & -0.690984674264428 \tabularnewline
237 & 31 & 35.6912752224899 & -4.69127522248993 \tabularnewline
238 & 37 & 35.3161762973603 & 1.68382370263967 \tabularnewline
239 & 32.8 & 32.2758365157816 & 0.524163484218416 \tabularnewline
240 & 21.5 & 26.483802443874 & -4.98380244387398 \tabularnewline
241 & 23.7 & 30.8305570786244 & -7.13055707862438 \tabularnewline
242 & 19 & 25.0604285887697 & -6.06042858876971 \tabularnewline
243 & 25.4 & 23.4606527551559 & 1.93934724484407 \tabularnewline
244 & 30 & 25.8233536266469 & 4.1766463733531 \tabularnewline
245 & 16.5 & 18.9490678588843 & -2.44906785888434 \tabularnewline
246 & 23 & 23.0592585443879 & -0.0592585443878986 \tabularnewline
247 & 21 & 23.2442048392317 & -2.24420483923168 \tabularnewline
248 & 15 & 15.373560620398 & -0.373560620398045 \tabularnewline
249 & 16.5 & 19.7450745880254 & -3.24507458802545 \tabularnewline
250 & 36 & 32.2613470794387 & 3.73865292056127 \tabularnewline
251 & 11 & 10.2622457548436 & 0.737754245156368 \tabularnewline
252 & 12 & 8.88466283046393 & 3.11533716953607 \tabularnewline
253 & 15 & 19.1785195344927 & -4.17851953449271 \tabularnewline
254 & 20.2 & 21.1160372930238 & -0.916037293023845 \tabularnewline
255 & 20.8 & 23.5752648518267 & -2.77526485182667 \tabularnewline
256 & 19.8 & 24.9188541297508 & -5.1188541297508 \tabularnewline
257 & 36 & 34.6657938123432 & 1.33420618765676 \tabularnewline
258 & 38 & 27.7202417063479 & 10.2797582936521 \tabularnewline
259 & 26.6 & 22.9003305732132 & 3.69966942678679 \tabularnewline
260 & 19.9 & 22.1226427756572 & -2.22264277565716 \tabularnewline
261 & 23.9 & 22.5455346918995 & 1.35446530810046 \tabularnewline
262 & 17 & 16.5847655167384 & 0.415234483261589 \tabularnewline
263 & 12 & 10.7330072868702 & 1.26699271312983 \tabularnewline
264 & 11 & 16.9324226501084 & -5.9324226501084 \tabularnewline
265 & 26.8 & 26.6449759908749 & 0.155024009125105 \tabularnewline
266 & 23.8 & 24.5848217205237 & -0.784821720523743 \tabularnewline
267 & 12 & 11.2377389685954 & 0.762261031404626 \tabularnewline
268 & 25 & 29.3763340524596 & -4.3763340524596 \tabularnewline
269 & 28 & 26.0479179499192 & 1.95208205008082 \tabularnewline
270 & 24 & 27.4052003166716 & -3.40520031667158 \tabularnewline
271 & 26 & 27.0576510829349 & -1.05765108293493 \tabularnewline
272 & 30 & 26.0372124944939 & 3.96278750550615 \tabularnewline
273 & 19 & 22.2526393832871 & -3.25263938328712 \tabularnewline
274 & 23 & 23.5893024249254 & -0.589302424925415 \tabularnewline
275 & 25 & 21.4498306218465 & 3.55016937815355 \tabularnewline
276 & 27.2 & 25.387955599471 & 1.81204440052901 \tabularnewline
277 & 21 & 21.0452903307576 & -0.0452903307576384 \tabularnewline
278 & 28.1 & 26.7111380639389 & 1.38886193606113 \tabularnewline
279 & 16.2 & 23.29463551574 & -7.09463551574 \tabularnewline
280 & 14 & 14.820337024686 & -0.820337024685971 \tabularnewline
281 & 25.5 & 27.3016051560676 & -1.80160515606763 \tabularnewline
282 & 39 & 33.0564969205689 & 5.94350307943109 \tabularnewline
283 & 26 & 24.577596083515 & 1.42240391648499 \tabularnewline
284 & 13 & 10.2738540242117 & 2.72614597578832 \tabularnewline
285 & 20 & 20.1464197064307 & -0.146419706430684 \tabularnewline
286 & 22 & 18.7890310838494 & 3.21096891615064 \tabularnewline
287 & 23 & 20.6987849955253 & 2.30121500447473 \tabularnewline
288 & 18 & 16.5380363671162 & 1.46196363288385 \tabularnewline
289 & 14 & 12.7262953637082 & 1.27370463629183 \tabularnewline
290 & 14 & 12.0919309253874 & 1.90806907461263 \tabularnewline
291 & 14 & 10.9580110278449 & 3.04198897215514 \tabularnewline
292 & 15 & 12.6239425289402 & 2.37605747105982 \tabularnewline
293 & 16 & 12.5422621472008 & 3.45773785279924 \tabularnewline
294 & 34.2 & 29.4211244395604 & 4.77887556043958 \tabularnewline
295 & 34.7 & 30.9148064154508 & 3.78519358454915 \tabularnewline
296 & 38 & 32.326595497944 & 5.67340450205601 \tabularnewline
297 & 34.5 & 29.7621234624055 & 4.73787653759449 \tabularnewline
298 & 27.2 & 29.3189478691111 & -2.11894786911111 \tabularnewline
299 & 30 & 30.0350458170858 & -0.0350458170857983 \tabularnewline
300 & 23.2 & 25.381625584001 & -2.18162558400099 \tabularnewline
301 & 18 & 15.7951271855706 & 2.2048728144294 \tabularnewline
302 & 16 & 15.7057862397163 & 0.294213760283733 \tabularnewline
303 & 14 & 13.0195013954405 & 0.980498604559514 \tabularnewline
304 & 18 & 16.9130821643313 & 1.08691783566871 \tabularnewline
305 & 18 & 19.470521707755 & -1.470521707755 \tabularnewline
306 & 22 & 21.1006564206979 & 0.899343579302063 \tabularnewline
307 & 19 & 20.091246185162 & -1.091246185162 \tabularnewline
308 & 20.5 & 21.3531019534322 & -0.853101953432235 \tabularnewline
309 & 19 & 19.1911150206799 & -0.191115020679893 \tabularnewline
310 & 13 & 17.145802083524 & -4.14580208352395 \tabularnewline
311 & 23 & 23.8819708274933 & -0.881970827493291 \tabularnewline
312 & 14 & 11.6832860314906 & 2.31671396850937 \tabularnewline
313 & 14 & 10.3271712758691 & 3.67282872413092 \tabularnewline
314 & 16 & 12.1472040863034 & 3.85279591369664 \tabularnewline
315 & 14 & 10.3465167340234 & 3.65348326597659 \tabularnewline
316 & 19 & 17.0095532375401 & 1.99044676245993 \tabularnewline
317 & 16 & 13.2110147817511 & 2.78898521824889 \tabularnewline
318 & 16 & 16.7985370137393 & -0.79853701373933 \tabularnewline
319 & 31 & 29.3228527108434 & 1.67714728915657 \tabularnewline
320 & 21.5 & 23.4687163951927 & -1.9687163951927 \tabularnewline
321 & 27 & 28.5951827408399 & -1.59518274083988 \tabularnewline
322 & 33.5 & 27.4219867185094 & 6.07801328149063 \tabularnewline
323 & 19.2 & 20.6929312213192 & -1.4929312213192 \tabularnewline
324 & 13 & 5.73620994515778 & 7.26379005484222 \tabularnewline
325 & 24.5 & 24.5711286316955 & -0.0711286316954749 \tabularnewline
326 & 18.5 & 18.5238545385446 & -0.0238545385446018 \tabularnewline
327 & 26 & 26.2093660282635 & -0.20936602826347 \tabularnewline
328 & 27 & 29.3592756610297 & -2.3592756610297 \tabularnewline
329 & 36 & 32.5233326764943 & 3.47666732350572 \tabularnewline
330 & 25 & 23.4194376016846 & 1.58056239831536 \tabularnewline
331 & 21.6 & 27.0974329857031 & -5.49743298570305 \tabularnewline
332 & 24 & 24.0281761405249 & -0.0281761405249066 \tabularnewline
333 & 25 & 25.5491380382429 & -0.549138038242944 \tabularnewline
334 & 26 & 26.5945971640998 & -0.594597164099785 \tabularnewline
335 & 32.3 & 34.3013134535739 & -2.00131345357394 \tabularnewline
336 & 30 & 31.6549485246382 & -1.65494852463816 \tabularnewline
337 & 33.8 & 32.9577241756498 & 0.842275824350186 \tabularnewline
338 & 20 & 26.4579109048211 & -6.45791090482112 \tabularnewline
339 & 32 & 31.4454125450544 & 0.554587454945572 \tabularnewline
340 & 21.1 & 29.1832342216657 & -8.0832342216657 \tabularnewline
341 & 28 & 29.6975610055929 & -1.69756100559288 \tabularnewline
342 & 29 & 28.7904504769105 & 0.209549523089532 \tabularnewline
343 & 32.2 & 32.2418597499013 & -0.0418597499012848 \tabularnewline
344 & 32.4 & 32.4601522524366 & -0.0601522524366136 \tabularnewline
345 & 34 & 33.9742410417833 & 0.0257589582167182 \tabularnewline
346 & 31 & 28.0704880645357 & 2.92951193546435 \tabularnewline
347 & 32 & 30.0348018198668 & 1.96519818013322 \tabularnewline
348 & 27 & 26.8806965652346 & 0.119303434765439 \tabularnewline
349 & 26 & 29.7453539967057 & -3.74535399670565 \tabularnewline
350 & 38.1 & 34.0902910953726 & 4.00970890462744 \tabularnewline
351 & 24 & 25.5139253521091 & -1.51392535210912 \tabularnewline
352 & 25 & 25.3588874676769 & -0.358887467676887 \tabularnewline
353 & 27.5 & 28.8763351011051 & -1.37633510110512 \tabularnewline
354 & 31 & 31.3567441785255 & -0.35674417852546 \tabularnewline
355 & 24 & 25.8158792862038 & -1.81587928620377 \tabularnewline
356 & 29.8 & 29.4424997348569 & 0.357500265143102 \tabularnewline
357 & 24 & 23.578819440511 & 0.421180559488953 \tabularnewline
358 & 25.4 & 29.2684351597571 & -3.86843515975713 \tabularnewline
359 & 19 & 24.9620271074669 & -5.96202710746688 \tabularnewline
360 & 20 & 23.4069121795499 & -3.40691217954986 \tabularnewline
361 & 39.1 & 36.2477257476285 & 2.85227425237146 \tabularnewline
362 & 37.7 & 34.3290435392786 & 3.37095646072141 \tabularnewline
363 & 23 & 24.3261721605354 & -1.32617216053542 \tabularnewline
364 & 35 & 30.7146301058767 & 4.28536989412334 \tabularnewline
365 & 29.8 & 34.8741176179083 & -5.07411761790827 \tabularnewline
366 & 26 & 27.0369786299064 & -1.03697862990637 \tabularnewline
367 & 22 & 24.2463623872313 & -2.2463623872313 \tabularnewline
368 & 25 & 28.3155320009831 & -3.31553200098309 \tabularnewline
369 & 26 & 29.1882028493259 & -3.18820284932589 \tabularnewline
370 & 30.5 & 30.2018214573101 & 0.29817854268993 \tabularnewline
371 & 33 & 33.4683544439469 & -0.468354443946855 \tabularnewline
372 & 27 & 27.8417894517352 & -0.841789451735246 \tabularnewline
373 & 29 & 30.266046411657 & -1.26604641165701 \tabularnewline
374 & 29.5 & 31.8931234827073 & -2.39312348270726 \tabularnewline
375 & 29 & 31.9068165715355 & -2.90681657153553 \tabularnewline
376 & 43.1 & 32.3326598738417 & 10.7673401261583 \tabularnewline
377 & 36 & 35.6985411812682 & 0.301458818731784 \tabularnewline
378 & 31.5 & 32.2892387689135 & -0.789238768913546 \tabularnewline
379 & 26 & 28.6466534014786 & -2.64665340147859 \tabularnewline
380 & 23 & 25.7753885012085 & -2.77538850120846 \tabularnewline
381 & 19 & 22.6096202054893 & -3.60962020548933 \tabularnewline
382 & 18 & 21.3683306344187 & -3.36833063441873 \tabularnewline
383 & 22 & 23.6804633930518 & -1.68046339305185 \tabularnewline
384 & 20 & 23.1642490645514 & -3.16424906455143 \tabularnewline
385 & 17 & 25.1360302391035 & -8.13603023910349 \tabularnewline
386 & 30.7 & 27.2258215064964 & 3.47417849350357 \tabularnewline
387 & 43.4 & 31.54164839667 & 11.85835160333 \tabularnewline
388 & 44 & 34.6009744915841 & 9.39902550841592 \tabularnewline
389 & 29 & 31.064037253029 & -2.06403725302899 \tabularnewline
390 & 41.5 & 32.9188342850871 & 8.5811657149129 \tabularnewline
391 & 44.3 & 33.2466435108954 & 11.0533564891046 \tabularnewline
392 & 31.9 & 33.5305283399841 & -1.63052833998414 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117208&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]13[/C][C]15.9548977448107[/C][C]-2.95489774481071[/C][/ROW]
[ROW][C]2[/C][C]15[/C][C]13.642781866753[/C][C]1.357218133247[/C][/ROW]
[ROW][C]3[/C][C]17[/C][C]15.6510966434752[/C][C]1.34890335652482[/C][/ROW]
[ROW][C]4[/C][C]19.4[/C][C]22.9187460724559[/C][C]-3.5187460724559[/C][/ROW]
[ROW][C]5[/C][C]24.3[/C][C]25.1714462956462[/C][C]-0.87144629564624[/C][/ROW]
[ROW][C]6[/C][C]18.1[/C][C]21.7971012498094[/C][C]-3.69710124980935[/C][/ROW]
[ROW][C]7[/C][C]20.2[/C][C]23.3416379886983[/C][C]-3.14163798869828[/C][/ROW]
[ROW][C]8[/C][C]18[/C][C]21.8000036379517[/C][C]-3.80000363795167[/C][/ROW]
[ROW][C]9[/C][C]19[/C][C]21.2611189260275[/C][C]-2.26111892602749[/C][/ROW]
[ROW][C]10[/C][C]20[/C][C]22.5434877635829[/C][C]-2.5434877635829[/C][/ROW]
[ROW][C]11[/C][C]21[/C][C]20.0600486710198[/C][C]0.939951328980195[/C][/ROW]
[ROW][C]12[/C][C]18[/C][C]19.2007311334502[/C][C]-1.20073113345018[/C][/ROW]
[ROW][C]13[/C][C]18[/C][C]20.736086686675[/C][C]-2.73608668667498[/C][/ROW]
[ROW][C]14[/C][C]19[/C][C]21.8341566681506[/C][C]-2.83415666815064[/C][/ROW]
[ROW][C]15[/C][C]22.5[/C][C]22.1752619468247[/C][C]0.324738053175334[/C][/ROW]
[ROW][C]16[/C][C]18[/C][C]19.2665166048975[/C][C]-1.26651660489752[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]16.4490874848472[/C][C]-2.44908748484718[/C][/ROW]
[ROW][C]18[/C][C]15[/C][C]17.2207349794848[/C][C]-2.22073497948484[/C][/ROW]
[ROW][C]19[/C][C]15.5[/C][C]16.8652656764616[/C][C]-1.36526567646159[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]17.0911022228892[/C][C]-1.09110222288924[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]16.8008517072137[/C][C]1.1991482927863[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]13.2573897589316[/C][C]0.742610241068404[/C][/ROW]
[ROW][C]23[/C][C]15[/C][C]14.1507009429568[/C][C]0.849299057043198[/C][/ROW]
[ROW][C]24[/C][C]19[/C][C]20.5179535678831[/C][C]-1.51795356788306[/C][/ROW]
[ROW][C]25[/C][C]17.5[/C][C]21.6810553262131[/C][C]-4.1810553262131[/C][/ROW]
[ROW][C]26[/C][C]16[/C][C]15.6850902899308[/C][C]0.314909710069219[/C][/ROW]
[ROW][C]27[/C][C]27.4[/C][C]26.3648728671143[/C][C]1.0351271328857[/C][/ROW]
[ROW][C]28[/C][C]24[/C][C]23.0723022844859[/C][C]0.927697715514132[/C][/ROW]
[ROW][C]29[/C][C]20[/C][C]24.494886197658[/C][C]-4.49488619765799[/C][/ROW]
[ROW][C]30[/C][C]23[/C][C]25.3363512718726[/C][C]-2.33635127187255[/C][/ROW]
[ROW][C]31[/C][C]34.3[/C][C]32.6094339423398[/C][C]1.69056605766019[/C][/ROW]
[ROW][C]32[/C][C]20.3[/C][C]26.9519456961476[/C][C]-6.65194569614758[/C][/ROW]
[ROW][C]33[/C][C]36.4[/C][C]27.6363176976272[/C][C]8.76368230237277[/C][/ROW]
[ROW][C]34[/C][C]29[/C][C]27.6193907025876[/C][C]1.38060929741241[/C][/ROW]
[ROW][C]35[/C][C]26[/C][C]24.5395152910491[/C][C]1.46048470895085[/C][/ROW]
[ROW][C]36[/C][C]21.5[/C][C]27.6293383334269[/C][C]-6.12933833342693[/C][/ROW]
[ROW][C]37[/C][C]17[/C][C]15.7619259672358[/C][C]1.23807403276422[/C][/ROW]
[ROW][C]38[/C][C]22.4[/C][C]23.9053014002634[/C][C]-1.50530140026335[/C][/ROW]
[ROW][C]39[/C][C]13[/C][C]13.9589111708992[/C][C]-0.9589111708992[/C][/ROW]
[ROW][C]40[/C][C]25[/C][C]27.4426229241988[/C][C]-2.44262292419875[/C][/ROW]
[ROW][C]41[/C][C]13[/C][C]10.671733718587[/C][C]2.32826628141301[/C][/ROW]
[ROW][C]42[/C][C]20.6[/C][C]21.750028192139[/C][C]-1.15002819213898[/C][/ROW]
[ROW][C]43[/C][C]12[/C][C]9.13383407965465[/C][C]2.86616592034534[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]19.4591251076606[/C][C]-5.45912510766062[/C][/ROW]
[ROW][C]45[/C][C]16.9[/C][C]16.9736613003366[/C][C]-0.0736613003366014[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]10.4192881858527[/C][C]2.58071181414731[/C][/ROW]
[ROW][C]47[/C][C]30[/C][C]28.1879690932387[/C][C]1.81203090676131[/C][/ROW]
[ROW][C]48[/C][C]17.7[/C][C]21.3067294624404[/C][C]-3.60672946244036[/C][/ROW]
[ROW][C]49[/C][C]21[/C][C]21.6816690038266[/C][C]-0.681669003826563[/C][/ROW]
[ROW][C]50[/C][C]20.5[/C][C]20.6451382302064[/C][C]-0.145138230206418[/C][/ROW]
[ROW][C]51[/C][C]26.6[/C][C]28.4791899451581[/C][C]-1.87918994515808[/C][/ROW]
[ROW][C]52[/C][C]15[/C][C]14.3406706927423[/C][C]0.659329307257695[/C][/ROW]
[ROW][C]53[/C][C]28.4[/C][C]26.6445089464226[/C][C]1.75549105357744[/C][/ROW]
[ROW][C]54[/C][C]23[/C][C]20.1108523105114[/C][C]2.88914768948856[/C][/ROW]
[ROW][C]55[/C][C]16.5[/C][C]14.4432891670826[/C][C]2.05671083291737[/C][/ROW]
[ROW][C]56[/C][C]25[/C][C]24.8163612780033[/C][C]0.183638721996693[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]16.0072286220334[/C][C]-0.00722862203336408[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]13.2360994982965[/C][C]1.76390050170346[/C][/ROW]
[ROW][C]59[/C][C]27[/C][C]27.128886942606[/C][C]-0.128886942605986[/C][/ROW]
[ROW][C]60[/C][C]13[/C][C]11.9424984167674[/C][C]1.05750158323263[/C][/ROW]
[ROW][C]61[/C][C]17[/C][C]20.1005970189632[/C][C]-3.10059701896316[/C][/ROW]
[ROW][C]62[/C][C]17.5[/C][C]18.2318161179431[/C][C]-0.731816117943128[/C][/ROW]
[ROW][C]63[/C][C]28[/C][C]29.1182532971364[/C][C]-1.11825329713638[/C][/ROW]
[ROW][C]64[/C][C]34[/C][C]30.5504491930858[/C][C]3.44955080691424[/C][/ROW]
[ROW][C]65[/C][C]27[/C][C]28.8795539811448[/C][C]-1.87955398114481[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]12.7737485767659[/C][C]0.226251423234147[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]16.6890141560657[/C][C]0.310985843934316[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]15.2288352854216[/C][C]2.77116471457842[/C][/ROW]
[ROW][C]69[/C][C]16[/C][C]16.000355513662[/C][C]-0.000355513661996265[/C][/ROW]
[ROW][C]70[/C][C]17.5[/C][C]15.149131823509[/C][C]2.35086817649096[/C][/ROW]
[ROW][C]71[/C][C]29[/C][C]27.9660246379611[/C][C]1.03397536203889[/C][/ROW]
[ROW][C]72[/C][C]30[/C][C]28.8647843002438[/C][C]1.13521569975624[/C][/ROW]
[ROW][C]73[/C][C]30.5[/C][C]28.7760714263896[/C][C]1.72392857361043[/C][/ROW]
[ROW][C]74[/C][C]32.1[/C][C]30.6994652989793[/C][C]1.40053470102072[/C][/ROW]
[ROW][C]75[/C][C]23.5[/C][C]28.0704581621963[/C][C]-4.57045816219631[/C][/ROW]
[ROW][C]76[/C][C]28[/C][C]27.3879399441393[/C][C]0.612060055860675[/C][/ROW]
[ROW][C]77[/C][C]28.8[/C][C]27.3610739388496[/C][C]1.43892606115041[/C][/ROW]
[ROW][C]78[/C][C]17.5[/C][C]20.1743429370293[/C][C]-2.67434293702931[/C][/ROW]
[ROW][C]79[/C][C]11[/C][C]8.3074488332387[/C][C]2.6925511667613[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]11.9742437300263[/C][C]1.02575626997369[/C][/ROW]
[ROW][C]81[/C][C]14[/C][C]11.6195516183529[/C][C]2.38044838164706[/C][/ROW]
[ROW][C]82[/C][C]14[/C][C]10.8020686856655[/C][C]3.1979313143345[/C][/ROW]
[ROW][C]83[/C][C]13[/C][C]14.7227489820722[/C][C]-1.7227489820722[/C][/ROW]
[ROW][C]84[/C][C]20.5[/C][C]22.99556651299[/C][C]-2.49556651299002[/C][/ROW]
[ROW][C]85[/C][C]19.2[/C][C]21.349086725878[/C][C]-2.14908672587796[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]14.3429721538534[/C][C]0.657027846146587[/C][/ROW]
[ROW][C]87[/C][C]15.5[/C][C]16.7075758066885[/C][C]-1.2075758066885[/C][/ROW]
[ROW][C]88[/C][C]19.2[/C][C]22.1328980672054[/C][C]-2.93289806720544[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.0816708191234[/C][C]0.918329180876566[/C][/ROW]
[ROW][C]90[/C][C]20[/C][C]20.7293898426223[/C][C]-0.729389842622299[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]19.0352468169833[/C][C]-4.03524681698331[/C][/ROW]
[ROW][C]92[/C][C]18[/C][C]18.9943800621564[/C][C]-0.994380062156362[/C][/ROW]
[ROW][C]93[/C][C]22[/C][C]20.5152888319599[/C][C]1.48471116804007[/C][/ROW]
[ROW][C]94[/C][C]16[/C][C]18.6328148421116[/C][C]-2.63281484211163[/C][/ROW]
[ROW][C]95[/C][C]20[/C][C]22.7428747074473[/C][C]-2.74287470744729[/C][/ROW]
[ROW][C]96[/C][C]21[/C][C]23.5886054120176[/C][C]-2.58860541201758[/C][/ROW]
[ROW][C]97[/C][C]25[/C][C]23.4249790089664[/C][C]1.5750209910336[/C][/ROW]
[ROW][C]98[/C][C]22[/C][C]21.9448838660753[/C][C]0.0551161339246882[/C][/ROW]
[ROW][C]99[/C][C]28[/C][C]22.9269610518692[/C][C]5.07303894813083[/C][/ROW]
[ROW][C]100[/C][C]24.5[/C][C]27.2074227933877[/C][C]-2.70742279338769[/C][/ROW]
[ROW][C]101[/C][C]13[/C][C]16.6597828155757[/C][C]-3.65978281557572[/C][/ROW]
[ROW][C]102[/C][C]10[/C][C]9.28181232700319[/C][C]0.718187672996812[/C][/ROW]
[ROW][C]103[/C][C]31[/C][C]28.3992039630979[/C][C]2.60079603690207[/C][/ROW]
[ROW][C]104[/C][C]15.5[/C][C]16.0824390657646[/C][C]-0.582439065764638[/C][/ROW]
[ROW][C]105[/C][C]26[/C][C]29.6647858225932[/C][C]-3.66478582259319[/C][/ROW]
[ROW][C]106[/C][C]17.6[/C][C]23.5083751615566[/C][C]-5.90837516155661[/C][/ROW]
[ROW][C]107[/C][C]18.5[/C][C]19.9312651186715[/C][C]-1.43126511867145[/C][/ROW]
[ROW][C]108[/C][C]13[/C][C]10.4671318186913[/C][C]2.53286818130868[/C][/ROW]
[ROW][C]109[/C][C]13[/C][C]11.4309467545853[/C][C]1.56905324541473[/C][/ROW]
[ROW][C]110[/C][C]35[/C][C]29.1710061402836[/C][C]5.82899385971645[/C][/ROW]
[ROW][C]111[/C][C]23.9[/C][C]29.7936140322708[/C][C]-5.89361403227077[/C][/ROW]
[ROW][C]112[/C][C]32.9[/C][C]30.7553906604373[/C][C]2.14460933956268[/C][/ROW]
[ROW][C]113[/C][C]31.8[/C][C]32.9003764596673[/C][C]-1.10037645966726[/C][/ROW]
[ROW][C]114[/C][C]40.8[/C][C]33.0845690599181[/C][C]7.71543094008193[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]34.8032572629718[/C][C]2.1967427370282[/C][/ROW]
[ROW][C]116[/C][C]32.7[/C][C]28.4022445138161[/C][C]4.29775548618387[/C][/ROW]
[ROW][C]117[/C][C]37.2[/C][C]33.7145084841397[/C][C]3.48549151586026[/C][/ROW]
[ROW][C]118[/C][C]38[/C][C]35.5207757110674[/C][C]2.47922428893261[/C][/ROW]
[ROW][C]119[/C][C]27.2[/C][C]30.5097119802455[/C][C]-3.30971198024546[/C][/ROW]
[ROW][C]120[/C][C]28[/C][C]25.598540239337[/C][C]2.40145976066298[/C][/ROW]
[ROW][C]121[/C][C]37[/C][C]31.1918162817646[/C][C]5.80818371823543[/C][/ROW]
[ROW][C]122[/C][C]22[/C][C]25.8784460882106[/C][C]-3.87844608821063[/C][/ROW]
[ROW][C]123[/C][C]24[/C][C]26.4448442441886[/C][C]-2.44484424418858[/C][/ROW]
[ROW][C]124[/C][C]32[/C][C]29.0077195152875[/C][C]2.99228048471252[/C][/ROW]
[ROW][C]125[/C][C]22[/C][C]26.4511036749465[/C][C]-4.45110367494648[/C][/ROW]
[ROW][C]126[/C][C]24.2[/C][C]28.8587692878907[/C][C]-4.65876928789068[/C][/ROW]
[ROW][C]127[/C][C]32[/C][C]30.7110033492584[/C][C]1.28899665074163[/C][/ROW]
[ROW][C]128[/C][C]31[/C][C]29.3318936689288[/C][C]1.66810633107116[/C][/ROW]
[ROW][C]129[/C][C]39.4[/C][C]31.7613865954502[/C][C]7.63861340454981[/C][/ROW]
[ROW][C]130[/C][C]33.5[/C][C]31.8158933111909[/C][C]1.68410668880907[/C][/ROW]
[ROW][C]131[/C][C]27[/C][C]25.0801154687835[/C][C]1.91988453121645[/C][/ROW]
[ROW][C]132[/C][C]27[/C][C]25.8781063101555[/C][C]1.12189368984447[/C][/ROW]
[ROW][C]133[/C][C]29[/C][C]29.8782393944915[/C][C]-0.878239394491522[/C][/ROW]
[ROW][C]134[/C][C]25.8[/C][C]28.6280956652297[/C][C]-2.82809566522965[/C][/ROW]
[ROW][C]135[/C][C]18.6[/C][C]20.0573056666209[/C][C]-1.45730566662089[/C][/ROW]
[ROW][C]136[/C][C]19.1[/C][C]23.2832626785644[/C][C]-4.18326267856438[/C][/ROW]
[ROW][C]137[/C][C]20.6[/C][C]22.6284914267873[/C][C]-2.02849142678734[/C][/ROW]
[ROW][C]138[/C][C]20[/C][C]18.249904589713[/C][C]1.75009541028703[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]15.5348678393786[/C][C]-0.534867839378627[/C][/ROW]
[ROW][C]140[/C][C]36[/C][C]30.9353363653113[/C][C]5.06466363468869[/C][/ROW]
[ROW][C]141[/C][C]26[/C][C]26.5868045718096[/C][C]-0.586804571809622[/C][/ROW]
[ROW][C]142[/C][C]27.9[/C][C]26.6025083416153[/C][C]1.29749165838465[/C][/ROW]
[ROW][C]143[/C][C]28[/C][C]25.802850727314[/C][C]2.19714927268597[/C][/ROW]
[ROW][C]144[/C][C]28[/C][C]24.0154594278998[/C][C]3.98454057210023[/C][/ROW]
[ROW][C]145[/C][C]25[/C][C]24.2699580839402[/C][C]0.730041916059763[/C][/ROW]
[ROW][C]146[/C][C]35.7[/C][C]31.2995704512722[/C][C]4.40042954872783[/C][/ROW]
[ROW][C]147[/C][C]33.5[/C][C]28.6123918954239[/C][C]4.88760810457607[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]15.4408069692985[/C][C]0.559193030701504[/C][/ROW]
[ROW][C]149[/C][C]15[/C][C]15.863486373883[/C][C]-0.863486373883012[/C][/ROW]
[ROW][C]150[/C][C]14[/C][C]12.0238905045618[/C][C]1.97610949543825[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]18.4074984680508[/C][C]-5.40749846805079[/C][/ROW]
[ROW][C]152[/C][C]11[/C][C]9.34342567334147[/C][C]1.65657432665853[/C][/ROW]
[ROW][C]153[/C][C]15[/C][C]18.4414389865919[/C][C]-3.4414389865919[/C][/ROW]
[ROW][C]154[/C][C]19.4[/C][C]20.1398797599328[/C][C]-0.739879759932783[/C][/ROW]
[ROW][C]155[/C][C]17.5[/C][C]17.7869865023017[/C][C]-0.286986502301654[/C][/ROW]
[ROW][C]156[/C][C]12[/C][C]6.83944588474327[/C][C]5.16055411525673[/C][/ROW]
[ROW][C]157[/C][C]15.5[/C][C]16.5797968335156[/C][C]-1.07979683351557[/C][/ROW]
[ROW][C]158[/C][C]30.9[/C][C]28.4185341844814[/C][C]2.48146581551861[/C][/ROW]
[ROW][C]159[/C][C]32[/C][C]31.4468348995789[/C][C]0.553165100421058[/C][/ROW]
[ROW][C]160[/C][C]18.2[/C][C]20.2899724578991[/C][C]-2.08997245789909[/C][/ROW]
[ROW][C]161[/C][C]26[/C][C]26.5076807601981[/C][C]-0.507680760198128[/C][/ROW]
[ROW][C]162[/C][C]26[/C][C]27.6030328778362[/C][C]-1.6030328778362[/C][/ROW]
[ROW][C]163[/C][C]30[/C][C]26.1824831423984[/C][C]3.81751685760155[/C][/ROW]
[ROW][C]164[/C][C]24[/C][C]28.3018389121548[/C][C]-4.30183891215482[/C][/ROW]
[ROW][C]165[/C][C]29[/C][C]28.9423969027368[/C][C]0.057603097263206[/C][/ROW]
[ROW][C]166[/C][C]28[/C][C]27.6283679971831[/C][C]0.37163200281692[/C][/ROW]
[ROW][C]167[/C][C]37.3[/C][C]32.1510747516065[/C][C]5.14892524839351[/C][/ROW]
[ROW][C]168[/C][C]31[/C][C]28.9358635724205[/C][C]2.06413642757947[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]8.92806705481676[/C][C]3.07193294518324[/C][/ROW]
[ROW][C]170[/C][C]13[/C][C]8.4232822451771[/C][C]4.5767177548229[/C][/ROW]
[ROW][C]171[/C][C]15.5[/C][C]19.0698965227922[/C][C]-3.56989652279217[/C][/ROW]
[ROW][C]172[/C][C]29.9[/C][C]29.7242612215568[/C][C]0.17573877844321[/C][/ROW]
[ROW][C]173[/C][C]34.4[/C][C]32.0089546746189[/C][C]2.3910453253811[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]17.4740614732093[/C][C]-4.47406147320934[/C][/ROW]
[ROW][C]175[/C][C]10[/C][C]8.1458607379149[/C][C]1.85413926208509[/C][/ROW]
[ROW][C]176[/C][C]26.4[/C][C]25.9759704673345[/C][C]0.424029532665519[/C][/ROW]
[ROW][C]177[/C][C]20.2[/C][C]24.2913627998014[/C][C]-4.09136279980137[/C][/ROW]
[ROW][C]178[/C][C]25.1[/C][C]25.4029858531258[/C][C]-0.302985853125794[/C][/ROW]
[ROW][C]179[/C][C]22.3[/C][C]25.0415800168245[/C][C]-2.74158001682446[/C][/ROW]
[ROW][C]180[/C][C]24[/C][C]27.6060520523629[/C][C]-3.60605205236295[/C][/ROW]
[ROW][C]181[/C][C]36.1[/C][C]31.2858773624439[/C][C]4.81412263755609[/C][/ROW]
[ROW][C]182[/C][C]18.1[/C][C]23.605330159793[/C][C]-5.50533015979301[/C][/ROW]
[ROW][C]183[/C][C]14[/C][C]12.9724620989207[/C][C]1.02753790107932[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]12.0039717461262[/C][C]1.99602825387385[/C][/ROW]
[ROW][C]185[/C][C]15[/C][C]10.657698365515[/C][C]4.34230163448499[/C][/ROW]
[ROW][C]186[/C][C]14[/C][C]13.9070523105063[/C][C]0.092947689493709[/C][/ROW]
[ROW][C]187[/C][C]14.5[/C][C]15.577907145115[/C][C]-1.07790714511504[/C][/ROW]
[ROW][C]188[/C][C]16[/C][C]14.029865086645[/C][C]1.97013491335501[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]11.3904263939951[/C][C]1.60957360600495[/C][/ROW]
[ROW][C]190[/C][C]14[/C][C]10.6403347995648[/C][C]3.35966520043522[/C][/ROW]
[ROW][C]191[/C][C]18.5[/C][C]20.1402430347448[/C][C]-1.6402430347448[/C][/ROW]
[ROW][C]192[/C][C]18[/C][C]19.0080731509846[/C][C]-1.00807315098463[/C][/ROW]
[ROW][C]193[/C][C]20.2[/C][C]26.0374371805116[/C][C]-5.83743718051163[/C][/ROW]
[ROW][C]194[/C][C]22[/C][C]28.668202109282[/C][C]-6.66820210928199[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]12.1745775133776[/C][C]0.82542248662237[/C][/ROW]
[ROW][C]196[/C][C]14[/C][C]11.7654849417925[/C][C]2.23451505820755[/C][/ROW]
[ROW][C]197[/C][C]17.6[/C][C]20.856931163576[/C][C]-3.25693116357604[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]21.0471941796838[/C][C]-6.04719417968381[/C][/ROW]
[ROW][C]199[/C][C]18[/C][C]20.3855498195354[/C][C]-2.3855498195354[/C][/ROW]
[ROW][C]200[/C][C]21[/C][C]20.4853886815344[/C][C]0.514611318465575[/C][/ROW]
[ROW][C]201[/C][C]24[/C][C]22.374842035583[/C][C]1.62515796441698[/C][/ROW]
[ROW][C]202[/C][C]18[/C][C]17.984810442877[/C][C]0.0151895571229702[/C][/ROW]
[ROW][C]203[/C][C]27[/C][C]28.1175505866306[/C][C]-1.11755058663058[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]21.4568769321255[/C][C]-8.45687693212554[/C][/ROW]
[ROW][C]205[/C][C]25.5[/C][C]24.3662956957623[/C][C]1.13370430423775[/C][/ROW]
[ROW][C]206[/C][C]18[/C][C]21.4974957703396[/C][C]-3.49749577033965[/C][/ROW]
[ROW][C]207[/C][C]19[/C][C]24.0414419860107[/C][C]-5.04144198601069[/C][/ROW]
[ROW][C]208[/C][C]23[/C][C]23.5614317460189[/C][C]-0.561431746018907[/C][/ROW]
[ROW][C]209[/C][C]26[/C][C]23.8778155829595[/C][C]2.12218441704049[/C][/ROW]
[ROW][C]210[/C][C]26.5[/C][C]24.8641011412016[/C][C]1.63589885879838[/C][/ROW]
[ROW][C]211[/C][C]22[/C][C]22.6637528058021[/C][C]-0.663752805802058[/C][/ROW]
[ROW][C]212[/C][C]21[/C][C]23.8163295030185[/C][C]-2.81632950301847[/C][/ROW]
[ROW][C]213[/C][C]28[/C][C]29.0564233091472[/C][C]-1.05642330914721[/C][/ROW]
[ROW][C]214[/C][C]16[/C][C]15.5575003316588[/C][C]0.442499668341203[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.5573281973331[/C][C]1.44267180266687[/C][/ROW]
[ROW][C]216[/C][C]19[/C][C]16.873153628402[/C][C]2.12684637159797[/C][/ROW]
[ROW][C]217[/C][C]9[/C][C]6.82593567641531[/C][C]2.17406432358469[/C][/ROW]
[ROW][C]218[/C][C]32.4[/C][C]32.0620390358351[/C][C]0.337960964164866[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]34.2377190574157[/C][C]1.76228094258425[/C][/ROW]
[ROW][C]220[/C][C]31.5[/C][C]31.2550708998677[/C][C]0.244929100132335[/C][/ROW]
[ROW][C]221[/C][C]29.5[/C][C]31.4392635001185[/C][C]-1.93926350011848[/C][/ROW]
[ROW][C]222[/C][C]24[/C][C]26.0380935110467[/C][C]-2.03809351104671[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]32.0968267542159[/C][C]0.903173245784119[/C][/ROW]
[ROW][C]224[/C][C]38[/C][C]35.7253751247744[/C][C]2.27462487522556[/C][/ROW]
[ROW][C]225[/C][C]32[/C][C]35.7253751247744[/C][C]-3.72537512477444[/C][/ROW]
[ROW][C]226[/C][C]35.1[/C][C]36.2322682506313[/C][C]-1.13226825063125[/C][/ROW]
[ROW][C]227[/C][C]44.6[/C][C]34.9136911945742[/C][C]9.6863088054258[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]31.2988359128439[/C][C]1.7011640871561[/C][/ROW]
[ROW][C]229[/C][C]36.1[/C][C]33.6587085346753[/C][C]2.44129146532467[/C][/ROW]
[ROW][C]230[/C][C]33.7[/C][C]33.4056283137593[/C][C]0.294371686240746[/C][/ROW]
[ROW][C]231[/C][C]34.1[/C][C]33.2165967828714[/C][C]0.883403217128556[/C][/ROW]
[ROW][C]232[/C][C]18[/C][C]27.2633354042635[/C][C]-9.26333540426346[/C][/ROW]
[ROW][C]233[/C][C]31.3[/C][C]30.4645795950628[/C][C]0.835420404937216[/C][/ROW]
[ROW][C]234[/C][C]31.6[/C][C]30.6283122539429[/C][C]0.971687746057106[/C][/ROW]
[ROW][C]235[/C][C]46.6[/C][C]33.0938902625617[/C][C]13.5061097374383[/C][/ROW]
[ROW][C]236[/C][C]34.1[/C][C]34.7909846742644[/C][C]-0.690984674264428[/C][/ROW]
[ROW][C]237[/C][C]31[/C][C]35.6912752224899[/C][C]-4.69127522248993[/C][/ROW]
[ROW][C]238[/C][C]37[/C][C]35.3161762973603[/C][C]1.68382370263967[/C][/ROW]
[ROW][C]239[/C][C]32.8[/C][C]32.2758365157816[/C][C]0.524163484218416[/C][/ROW]
[ROW][C]240[/C][C]21.5[/C][C]26.483802443874[/C][C]-4.98380244387398[/C][/ROW]
[ROW][C]241[/C][C]23.7[/C][C]30.8305570786244[/C][C]-7.13055707862438[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]25.0604285887697[/C][C]-6.06042858876971[/C][/ROW]
[ROW][C]243[/C][C]25.4[/C][C]23.4606527551559[/C][C]1.93934724484407[/C][/ROW]
[ROW][C]244[/C][C]30[/C][C]25.8233536266469[/C][C]4.1766463733531[/C][/ROW]
[ROW][C]245[/C][C]16.5[/C][C]18.9490678588843[/C][C]-2.44906785888434[/C][/ROW]
[ROW][C]246[/C][C]23[/C][C]23.0592585443879[/C][C]-0.0592585443878986[/C][/ROW]
[ROW][C]247[/C][C]21[/C][C]23.2442048392317[/C][C]-2.24420483923168[/C][/ROW]
[ROW][C]248[/C][C]15[/C][C]15.373560620398[/C][C]-0.373560620398045[/C][/ROW]
[ROW][C]249[/C][C]16.5[/C][C]19.7450745880254[/C][C]-3.24507458802545[/C][/ROW]
[ROW][C]250[/C][C]36[/C][C]32.2613470794387[/C][C]3.73865292056127[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]10.2622457548436[/C][C]0.737754245156368[/C][/ROW]
[ROW][C]252[/C][C]12[/C][C]8.88466283046393[/C][C]3.11533716953607[/C][/ROW]
[ROW][C]253[/C][C]15[/C][C]19.1785195344927[/C][C]-4.17851953449271[/C][/ROW]
[ROW][C]254[/C][C]20.2[/C][C]21.1160372930238[/C][C]-0.916037293023845[/C][/ROW]
[ROW][C]255[/C][C]20.8[/C][C]23.5752648518267[/C][C]-2.77526485182667[/C][/ROW]
[ROW][C]256[/C][C]19.8[/C][C]24.9188541297508[/C][C]-5.1188541297508[/C][/ROW]
[ROW][C]257[/C][C]36[/C][C]34.6657938123432[/C][C]1.33420618765676[/C][/ROW]
[ROW][C]258[/C][C]38[/C][C]27.7202417063479[/C][C]10.2797582936521[/C][/ROW]
[ROW][C]259[/C][C]26.6[/C][C]22.9003305732132[/C][C]3.69966942678679[/C][/ROW]
[ROW][C]260[/C][C]19.9[/C][C]22.1226427756572[/C][C]-2.22264277565716[/C][/ROW]
[ROW][C]261[/C][C]23.9[/C][C]22.5455346918995[/C][C]1.35446530810046[/C][/ROW]
[ROW][C]262[/C][C]17[/C][C]16.5847655167384[/C][C]0.415234483261589[/C][/ROW]
[ROW][C]263[/C][C]12[/C][C]10.7330072868702[/C][C]1.26699271312983[/C][/ROW]
[ROW][C]264[/C][C]11[/C][C]16.9324226501084[/C][C]-5.9324226501084[/C][/ROW]
[ROW][C]265[/C][C]26.8[/C][C]26.6449759908749[/C][C]0.155024009125105[/C][/ROW]
[ROW][C]266[/C][C]23.8[/C][C]24.5848217205237[/C][C]-0.784821720523743[/C][/ROW]
[ROW][C]267[/C][C]12[/C][C]11.2377389685954[/C][C]0.762261031404626[/C][/ROW]
[ROW][C]268[/C][C]25[/C][C]29.3763340524596[/C][C]-4.3763340524596[/C][/ROW]
[ROW][C]269[/C][C]28[/C][C]26.0479179499192[/C][C]1.95208205008082[/C][/ROW]
[ROW][C]270[/C][C]24[/C][C]27.4052003166716[/C][C]-3.40520031667158[/C][/ROW]
[ROW][C]271[/C][C]26[/C][C]27.0576510829349[/C][C]-1.05765108293493[/C][/ROW]
[ROW][C]272[/C][C]30[/C][C]26.0372124944939[/C][C]3.96278750550615[/C][/ROW]
[ROW][C]273[/C][C]19[/C][C]22.2526393832871[/C][C]-3.25263938328712[/C][/ROW]
[ROW][C]274[/C][C]23[/C][C]23.5893024249254[/C][C]-0.589302424925415[/C][/ROW]
[ROW][C]275[/C][C]25[/C][C]21.4498306218465[/C][C]3.55016937815355[/C][/ROW]
[ROW][C]276[/C][C]27.2[/C][C]25.387955599471[/C][C]1.81204440052901[/C][/ROW]
[ROW][C]277[/C][C]21[/C][C]21.0452903307576[/C][C]-0.0452903307576384[/C][/ROW]
[ROW][C]278[/C][C]28.1[/C][C]26.7111380639389[/C][C]1.38886193606113[/C][/ROW]
[ROW][C]279[/C][C]16.2[/C][C]23.29463551574[/C][C]-7.09463551574[/C][/ROW]
[ROW][C]280[/C][C]14[/C][C]14.820337024686[/C][C]-0.820337024685971[/C][/ROW]
[ROW][C]281[/C][C]25.5[/C][C]27.3016051560676[/C][C]-1.80160515606763[/C][/ROW]
[ROW][C]282[/C][C]39[/C][C]33.0564969205689[/C][C]5.94350307943109[/C][/ROW]
[ROW][C]283[/C][C]26[/C][C]24.577596083515[/C][C]1.42240391648499[/C][/ROW]
[ROW][C]284[/C][C]13[/C][C]10.2738540242117[/C][C]2.72614597578832[/C][/ROW]
[ROW][C]285[/C][C]20[/C][C]20.1464197064307[/C][C]-0.146419706430684[/C][/ROW]
[ROW][C]286[/C][C]22[/C][C]18.7890310838494[/C][C]3.21096891615064[/C][/ROW]
[ROW][C]287[/C][C]23[/C][C]20.6987849955253[/C][C]2.30121500447473[/C][/ROW]
[ROW][C]288[/C][C]18[/C][C]16.5380363671162[/C][C]1.46196363288385[/C][/ROW]
[ROW][C]289[/C][C]14[/C][C]12.7262953637082[/C][C]1.27370463629183[/C][/ROW]
[ROW][C]290[/C][C]14[/C][C]12.0919309253874[/C][C]1.90806907461263[/C][/ROW]
[ROW][C]291[/C][C]14[/C][C]10.9580110278449[/C][C]3.04198897215514[/C][/ROW]
[ROW][C]292[/C][C]15[/C][C]12.6239425289402[/C][C]2.37605747105982[/C][/ROW]
[ROW][C]293[/C][C]16[/C][C]12.5422621472008[/C][C]3.45773785279924[/C][/ROW]
[ROW][C]294[/C][C]34.2[/C][C]29.4211244395604[/C][C]4.77887556043958[/C][/ROW]
[ROW][C]295[/C][C]34.7[/C][C]30.9148064154508[/C][C]3.78519358454915[/C][/ROW]
[ROW][C]296[/C][C]38[/C][C]32.326595497944[/C][C]5.67340450205601[/C][/ROW]
[ROW][C]297[/C][C]34.5[/C][C]29.7621234624055[/C][C]4.73787653759449[/C][/ROW]
[ROW][C]298[/C][C]27.2[/C][C]29.3189478691111[/C][C]-2.11894786911111[/C][/ROW]
[ROW][C]299[/C][C]30[/C][C]30.0350458170858[/C][C]-0.0350458170857983[/C][/ROW]
[ROW][C]300[/C][C]23.2[/C][C]25.381625584001[/C][C]-2.18162558400099[/C][/ROW]
[ROW][C]301[/C][C]18[/C][C]15.7951271855706[/C][C]2.2048728144294[/C][/ROW]
[ROW][C]302[/C][C]16[/C][C]15.7057862397163[/C][C]0.294213760283733[/C][/ROW]
[ROW][C]303[/C][C]14[/C][C]13.0195013954405[/C][C]0.980498604559514[/C][/ROW]
[ROW][C]304[/C][C]18[/C][C]16.9130821643313[/C][C]1.08691783566871[/C][/ROW]
[ROW][C]305[/C][C]18[/C][C]19.470521707755[/C][C]-1.470521707755[/C][/ROW]
[ROW][C]306[/C][C]22[/C][C]21.1006564206979[/C][C]0.899343579302063[/C][/ROW]
[ROW][C]307[/C][C]19[/C][C]20.091246185162[/C][C]-1.091246185162[/C][/ROW]
[ROW][C]308[/C][C]20.5[/C][C]21.3531019534322[/C][C]-0.853101953432235[/C][/ROW]
[ROW][C]309[/C][C]19[/C][C]19.1911150206799[/C][C]-0.191115020679893[/C][/ROW]
[ROW][C]310[/C][C]13[/C][C]17.145802083524[/C][C]-4.14580208352395[/C][/ROW]
[ROW][C]311[/C][C]23[/C][C]23.8819708274933[/C][C]-0.881970827493291[/C][/ROW]
[ROW][C]312[/C][C]14[/C][C]11.6832860314906[/C][C]2.31671396850937[/C][/ROW]
[ROW][C]313[/C][C]14[/C][C]10.3271712758691[/C][C]3.67282872413092[/C][/ROW]
[ROW][C]314[/C][C]16[/C][C]12.1472040863034[/C][C]3.85279591369664[/C][/ROW]
[ROW][C]315[/C][C]14[/C][C]10.3465167340234[/C][C]3.65348326597659[/C][/ROW]
[ROW][C]316[/C][C]19[/C][C]17.0095532375401[/C][C]1.99044676245993[/C][/ROW]
[ROW][C]317[/C][C]16[/C][C]13.2110147817511[/C][C]2.78898521824889[/C][/ROW]
[ROW][C]318[/C][C]16[/C][C]16.7985370137393[/C][C]-0.79853701373933[/C][/ROW]
[ROW][C]319[/C][C]31[/C][C]29.3228527108434[/C][C]1.67714728915657[/C][/ROW]
[ROW][C]320[/C][C]21.5[/C][C]23.4687163951927[/C][C]-1.9687163951927[/C][/ROW]
[ROW][C]321[/C][C]27[/C][C]28.5951827408399[/C][C]-1.59518274083988[/C][/ROW]
[ROW][C]322[/C][C]33.5[/C][C]27.4219867185094[/C][C]6.07801328149063[/C][/ROW]
[ROW][C]323[/C][C]19.2[/C][C]20.6929312213192[/C][C]-1.4929312213192[/C][/ROW]
[ROW][C]324[/C][C]13[/C][C]5.73620994515778[/C][C]7.26379005484222[/C][/ROW]
[ROW][C]325[/C][C]24.5[/C][C]24.5711286316955[/C][C]-0.0711286316954749[/C][/ROW]
[ROW][C]326[/C][C]18.5[/C][C]18.5238545385446[/C][C]-0.0238545385446018[/C][/ROW]
[ROW][C]327[/C][C]26[/C][C]26.2093660282635[/C][C]-0.20936602826347[/C][/ROW]
[ROW][C]328[/C][C]27[/C][C]29.3592756610297[/C][C]-2.3592756610297[/C][/ROW]
[ROW][C]329[/C][C]36[/C][C]32.5233326764943[/C][C]3.47666732350572[/C][/ROW]
[ROW][C]330[/C][C]25[/C][C]23.4194376016846[/C][C]1.58056239831536[/C][/ROW]
[ROW][C]331[/C][C]21.6[/C][C]27.0974329857031[/C][C]-5.49743298570305[/C][/ROW]
[ROW][C]332[/C][C]24[/C][C]24.0281761405249[/C][C]-0.0281761405249066[/C][/ROW]
[ROW][C]333[/C][C]25[/C][C]25.5491380382429[/C][C]-0.549138038242944[/C][/ROW]
[ROW][C]334[/C][C]26[/C][C]26.5945971640998[/C][C]-0.594597164099785[/C][/ROW]
[ROW][C]335[/C][C]32.3[/C][C]34.3013134535739[/C][C]-2.00131345357394[/C][/ROW]
[ROW][C]336[/C][C]30[/C][C]31.6549485246382[/C][C]-1.65494852463816[/C][/ROW]
[ROW][C]337[/C][C]33.8[/C][C]32.9577241756498[/C][C]0.842275824350186[/C][/ROW]
[ROW][C]338[/C][C]20[/C][C]26.4579109048211[/C][C]-6.45791090482112[/C][/ROW]
[ROW][C]339[/C][C]32[/C][C]31.4454125450544[/C][C]0.554587454945572[/C][/ROW]
[ROW][C]340[/C][C]21.1[/C][C]29.1832342216657[/C][C]-8.0832342216657[/C][/ROW]
[ROW][C]341[/C][C]28[/C][C]29.6975610055929[/C][C]-1.69756100559288[/C][/ROW]
[ROW][C]342[/C][C]29[/C][C]28.7904504769105[/C][C]0.209549523089532[/C][/ROW]
[ROW][C]343[/C][C]32.2[/C][C]32.2418597499013[/C][C]-0.0418597499012848[/C][/ROW]
[ROW][C]344[/C][C]32.4[/C][C]32.4601522524366[/C][C]-0.0601522524366136[/C][/ROW]
[ROW][C]345[/C][C]34[/C][C]33.9742410417833[/C][C]0.0257589582167182[/C][/ROW]
[ROW][C]346[/C][C]31[/C][C]28.0704880645357[/C][C]2.92951193546435[/C][/ROW]
[ROW][C]347[/C][C]32[/C][C]30.0348018198668[/C][C]1.96519818013322[/C][/ROW]
[ROW][C]348[/C][C]27[/C][C]26.8806965652346[/C][C]0.119303434765439[/C][/ROW]
[ROW][C]349[/C][C]26[/C][C]29.7453539967057[/C][C]-3.74535399670565[/C][/ROW]
[ROW][C]350[/C][C]38.1[/C][C]34.0902910953726[/C][C]4.00970890462744[/C][/ROW]
[ROW][C]351[/C][C]24[/C][C]25.5139253521091[/C][C]-1.51392535210912[/C][/ROW]
[ROW][C]352[/C][C]25[/C][C]25.3588874676769[/C][C]-0.358887467676887[/C][/ROW]
[ROW][C]353[/C][C]27.5[/C][C]28.8763351011051[/C][C]-1.37633510110512[/C][/ROW]
[ROW][C]354[/C][C]31[/C][C]31.3567441785255[/C][C]-0.35674417852546[/C][/ROW]
[ROW][C]355[/C][C]24[/C][C]25.8158792862038[/C][C]-1.81587928620377[/C][/ROW]
[ROW][C]356[/C][C]29.8[/C][C]29.4424997348569[/C][C]0.357500265143102[/C][/ROW]
[ROW][C]357[/C][C]24[/C][C]23.578819440511[/C][C]0.421180559488953[/C][/ROW]
[ROW][C]358[/C][C]25.4[/C][C]29.2684351597571[/C][C]-3.86843515975713[/C][/ROW]
[ROW][C]359[/C][C]19[/C][C]24.9620271074669[/C][C]-5.96202710746688[/C][/ROW]
[ROW][C]360[/C][C]20[/C][C]23.4069121795499[/C][C]-3.40691217954986[/C][/ROW]
[ROW][C]361[/C][C]39.1[/C][C]36.2477257476285[/C][C]2.85227425237146[/C][/ROW]
[ROW][C]362[/C][C]37.7[/C][C]34.3290435392786[/C][C]3.37095646072141[/C][/ROW]
[ROW][C]363[/C][C]23[/C][C]24.3261721605354[/C][C]-1.32617216053542[/C][/ROW]
[ROW][C]364[/C][C]35[/C][C]30.7146301058767[/C][C]4.28536989412334[/C][/ROW]
[ROW][C]365[/C][C]29.8[/C][C]34.8741176179083[/C][C]-5.07411761790827[/C][/ROW]
[ROW][C]366[/C][C]26[/C][C]27.0369786299064[/C][C]-1.03697862990637[/C][/ROW]
[ROW][C]367[/C][C]22[/C][C]24.2463623872313[/C][C]-2.2463623872313[/C][/ROW]
[ROW][C]368[/C][C]25[/C][C]28.3155320009831[/C][C]-3.31553200098309[/C][/ROW]
[ROW][C]369[/C][C]26[/C][C]29.1882028493259[/C][C]-3.18820284932589[/C][/ROW]
[ROW][C]370[/C][C]30.5[/C][C]30.2018214573101[/C][C]0.29817854268993[/C][/ROW]
[ROW][C]371[/C][C]33[/C][C]33.4683544439469[/C][C]-0.468354443946855[/C][/ROW]
[ROW][C]372[/C][C]27[/C][C]27.8417894517352[/C][C]-0.841789451735246[/C][/ROW]
[ROW][C]373[/C][C]29[/C][C]30.266046411657[/C][C]-1.26604641165701[/C][/ROW]
[ROW][C]374[/C][C]29.5[/C][C]31.8931234827073[/C][C]-2.39312348270726[/C][/ROW]
[ROW][C]375[/C][C]29[/C][C]31.9068165715355[/C][C]-2.90681657153553[/C][/ROW]
[ROW][C]376[/C][C]43.1[/C][C]32.3326598738417[/C][C]10.7673401261583[/C][/ROW]
[ROW][C]377[/C][C]36[/C][C]35.6985411812682[/C][C]0.301458818731784[/C][/ROW]
[ROW][C]378[/C][C]31.5[/C][C]32.2892387689135[/C][C]-0.789238768913546[/C][/ROW]
[ROW][C]379[/C][C]26[/C][C]28.6466534014786[/C][C]-2.64665340147859[/C][/ROW]
[ROW][C]380[/C][C]23[/C][C]25.7753885012085[/C][C]-2.77538850120846[/C][/ROW]
[ROW][C]381[/C][C]19[/C][C]22.6096202054893[/C][C]-3.60962020548933[/C][/ROW]
[ROW][C]382[/C][C]18[/C][C]21.3683306344187[/C][C]-3.36833063441873[/C][/ROW]
[ROW][C]383[/C][C]22[/C][C]23.6804633930518[/C][C]-1.68046339305185[/C][/ROW]
[ROW][C]384[/C][C]20[/C][C]23.1642490645514[/C][C]-3.16424906455143[/C][/ROW]
[ROW][C]385[/C][C]17[/C][C]25.1360302391035[/C][C]-8.13603023910349[/C][/ROW]
[ROW][C]386[/C][C]30.7[/C][C]27.2258215064964[/C][C]3.47417849350357[/C][/ROW]
[ROW][C]387[/C][C]43.4[/C][C]31.54164839667[/C][C]11.85835160333[/C][/ROW]
[ROW][C]388[/C][C]44[/C][C]34.6009744915841[/C][C]9.39902550841592[/C][/ROW]
[ROW][C]389[/C][C]29[/C][C]31.064037253029[/C][C]-2.06403725302899[/C][/ROW]
[ROW][C]390[/C][C]41.5[/C][C]32.9188342850871[/C][C]8.5811657149129[/C][/ROW]
[ROW][C]391[/C][C]44.3[/C][C]33.2466435108954[/C][C]11.0533564891046[/C][/ROW]
[ROW][C]392[/C][C]31.9[/C][C]33.5305283399841[/C][C]-1.63052833998414[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117208&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117208&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.9548977448107-2.95489774481071
21513.6427818667531.357218133247
31715.65109664347521.34890335652482
419.422.9187460724559-3.5187460724559
524.325.1714462956462-0.87144629564624
618.121.7971012498094-3.69710124980935
720.223.3416379886983-3.14163798869828
81821.8000036379517-3.80000363795167
91921.2611189260275-2.26111892602749
102022.5434877635829-2.5434877635829
112120.06004867101980.939951328980195
121819.2007311334502-1.20073113345018
131820.736086686675-2.73608668667498
141921.8341566681506-2.83415666815064
1522.522.17526194682470.324738053175334
161819.2665166048975-1.26651660489752
171416.4490874848472-2.44908748484718
181517.2207349794848-2.22073497948484
1915.516.8652656764616-1.36526567646159
201617.0911022228892-1.09110222288924
211816.80085170721371.1991482927863
221413.25738975893160.742610241068404
231514.15070094295680.849299057043198
241920.5179535678831-1.51795356788306
2517.521.6810553262131-4.1810553262131
261615.68509028993080.314909710069219
2727.426.36487286711431.0351271328857
282423.07230228448590.927697715514132
292024.494886197658-4.49488619765799
302325.3363512718726-2.33635127187255
3134.332.60943394233981.69056605766019
3220.326.9519456961476-6.65194569614758
3336.427.63631769762728.76368230237277
342927.61939070258761.38060929741241
352624.53951529104911.46048470895085
3621.527.6293383334269-6.12933833342693
371715.76192596723581.23807403276422
3822.423.9053014002634-1.50530140026335
391313.9589111708992-0.9589111708992
402527.4426229241988-2.44262292419875
411310.6717337185872.32826628141301
4220.621.750028192139-1.15002819213898
43129.133834079654652.86616592034534
441419.4591251076606-5.45912510766062
4516.916.9736613003366-0.0736613003366014
461310.41928818585272.58071181414731
473028.18796909323871.81203090676131
4817.721.3067294624404-3.60672946244036
492121.6816690038266-0.681669003826563
5020.520.6451382302064-0.145138230206418
5126.628.4791899451581-1.87918994515808
521514.34067069274230.659329307257695
5328.426.64450894642261.75549105357744
542320.11085231051142.88914768948856
5516.514.44328916708262.05671083291737
562524.81636127800330.183638721996693
571616.0072286220334-0.00722862203336408
581513.23609949829651.76390050170346
592727.128886942606-0.128886942605986
601311.94249841676741.05750158323263
611720.1005970189632-3.10059701896316
6217.518.2318161179431-0.731816117943128
632829.1182532971364-1.11825329713638
643430.55044919308583.44955080691424
652728.8795539811448-1.87955398114481
661312.77374857676590.226251423234147
671716.68901415606570.310985843934316
681815.22883528542162.77116471457842
691616.000355513662-0.000355513661996265
7017.515.1491318235092.35086817649096
712927.96602463796111.03397536203889
723028.86478430024381.13521569975624
7330.528.77607142638961.72392857361043
7432.130.69946529897931.40053470102072
7523.528.0704581621963-4.57045816219631
762827.38793994413930.612060055860675
7728.827.36107393884961.43892606115041
7817.520.1743429370293-2.67434293702931
79118.30744883323872.6925511667613
801311.97424373002631.02575626997369
811411.61955161835292.38044838164706
821410.80206868566553.1979313143345
831314.7227489820722-1.7227489820722
8420.522.99556651299-2.49556651299002
8519.221.349086725878-2.14908672587796
861514.34297215385340.657027846146587
8715.516.7075758066885-1.2075758066885
8819.222.1328980672054-2.93289806720544
891514.08167081912340.918329180876566
902020.7293898426223-0.729389842622299
911519.0352468169833-4.03524681698331
921818.9943800621564-0.994380062156362
932220.51528883195991.48471116804007
941618.6328148421116-2.63281484211163
952022.7428747074473-2.74287470744729
962123.5886054120176-2.58860541201758
972523.42497900896641.5750209910336
982221.94488386607530.0551161339246882
992822.92696105186925.07303894813083
10024.527.2074227933877-2.70742279338769
1011316.6597828155757-3.65978281557572
102109.281812327003190.718187672996812
1033128.39920396309792.60079603690207
10415.516.0824390657646-0.582439065764638
1052629.6647858225932-3.66478582259319
10617.623.5083751615566-5.90837516155661
10718.519.9312651186715-1.43126511867145
1081310.46713181869132.53286818130868
1091311.43094675458531.56905324541473
1103529.17100614028365.82899385971645
11123.929.7936140322708-5.89361403227077
11232.930.75539066043732.14460933956268
11331.832.9003764596673-1.10037645966726
11440.833.08456905991817.71543094008193
1153734.80325726297182.1967427370282
11632.728.40224451381614.29775548618387
11737.233.71450848413973.48549151586026
1183835.52077571106742.47922428893261
11927.230.5097119802455-3.30971198024546
1202825.5985402393372.40145976066298
1213731.19181628176465.80818371823543
1222225.8784460882106-3.87844608821063
1232426.4448442441886-2.44484424418858
1243229.00771951528752.99228048471252
1252226.4511036749465-4.45110367494648
12624.228.8587692878907-4.65876928789068
1273230.71100334925841.28899665074163
1283129.33189366892881.66810633107116
12939.431.76138659545027.63861340454981
13033.531.81589331119091.68410668880907
1312725.08011546878351.91988453121645
1322725.87810631015551.12189368984447
1332929.8782393944915-0.878239394491522
13425.828.6280956652297-2.82809566522965
13518.620.0573056666209-1.45730566662089
13619.123.2832626785644-4.18326267856438
13720.622.6284914267873-2.02849142678734
1382018.2499045897131.75009541028703
1391515.5348678393786-0.534867839378627
1403630.93533636531135.06466363468869
1412626.5868045718096-0.586804571809622
14227.926.60250834161531.29749165838465
1432825.8028507273142.19714927268597
1442824.01545942789983.98454057210023
1452524.26995808394020.730041916059763
14635.731.29957045127224.40042954872783
14733.528.61239189542394.88760810457607
1481615.44080696929850.559193030701504
1491515.863486373883-0.863486373883012
1501412.02389050456181.97610949543825
1511318.4074984680508-5.40749846805079
152119.343425673341471.65657432665853
1531518.4414389865919-3.4414389865919
15419.420.1398797599328-0.739879759932783
15517.517.7869865023017-0.286986502301654
156126.839445884743275.16055411525673
15715.516.5797968335156-1.07979683351557
15830.928.41853418448142.48146581551861
1593231.44683489957890.553165100421058
16018.220.2899724578991-2.08997245789909
1612626.5076807601981-0.507680760198128
1622627.6030328778362-1.6030328778362
1633026.18248314239843.81751685760155
1642428.3018389121548-4.30183891215482
1652928.94239690273680.057603097263206
1662827.62836799718310.37163200281692
16737.332.15107475160655.14892524839351
1683128.93586357242052.06413642757947
169128.928067054816763.07193294518324
170138.42328224517714.5767177548229
17115.519.0698965227922-3.56989652279217
17229.929.72426122155680.17573877844321
17334.432.00895467461892.3910453253811
1741317.4740614732093-4.47406147320934
175108.14586073791491.85413926208509
17626.425.97597046733450.424029532665519
17720.224.2913627998014-4.09136279980137
17825.125.4029858531258-0.302985853125794
17922.325.0415800168245-2.74158001682446
1802427.6060520523629-3.60605205236295
18136.131.28587736244394.81412263755609
18218.123.605330159793-5.50533015979301
1831412.97246209892071.02753790107932
1841412.00397174612621.99602825387385
1851510.6576983655154.34230163448499
1861413.90705231050630.092947689493709
18714.515.577907145115-1.07790714511504
1881614.0298650866451.97013491335501
1891311.39042639399511.60957360600495
1901410.64033479956483.35966520043522
19118.520.1402430347448-1.6402430347448
1921819.0080731509846-1.00807315098463
19320.226.0374371805116-5.83743718051163
1942228.668202109282-6.66820210928199
1951312.17457751337760.82542248662237
1961411.76548494179252.23451505820755
19717.620.856931163576-3.25693116357604
1981521.0471941796838-6.04719417968381
1991820.3855498195354-2.3855498195354
2002120.48538868153440.514611318465575
2012422.3748420355831.62515796441698
2021817.9848104428770.0151895571229702
2032728.1175505866306-1.11755058663058
2041321.4568769321255-8.45687693212554
20525.524.36629569576231.13370430423775
2061821.4974957703396-3.49749577033965
2071924.0414419860107-5.04144198601069
2082323.5614317460189-0.561431746018907
2092623.87781558295952.12218441704049
21026.524.86410114120161.63589885879838
2112222.6637528058021-0.663752805802058
2122123.8163295030185-2.81632950301847
2132829.0564233091472-1.05642330914721
2141615.55750033165880.442499668341203
2151715.55732819733311.44267180266687
2161916.8731536284022.12684637159797
21796.825935676415312.17406432358469
21832.432.06203903583510.337960964164866
2193634.23771905741571.76228094258425
22031.531.25507089986770.244929100132335
22129.531.4392635001185-1.93926350011848
2222426.0380935110467-2.03809351104671
2233332.09682675421590.903173245784119
2243835.72537512477442.27462487522556
2253235.7253751247744-3.72537512477444
22635.136.2322682506313-1.13226825063125
22744.634.91369119457429.6863088054258
2283331.29883591284391.7011640871561
22936.133.65870853467532.44129146532467
23033.733.40562831375930.294371686240746
23134.133.21659678287140.883403217128556
2321827.2633354042635-9.26333540426346
23331.330.46457959506280.835420404937216
23431.630.62831225394290.971687746057106
23546.633.093890262561713.5061097374383
23634.134.7909846742644-0.690984674264428
2373135.6912752224899-4.69127522248993
2383735.31617629736031.68382370263967
23932.832.27583651578160.524163484218416
24021.526.483802443874-4.98380244387398
24123.730.8305570786244-7.13055707862438
2421925.0604285887697-6.06042858876971
24325.423.46065275515591.93934724484407
2443025.82335362664694.1766463733531
24516.518.9490678588843-2.44906785888434
2462323.0592585443879-0.0592585443878986
2472123.2442048392317-2.24420483923168
2481515.373560620398-0.373560620398045
24916.519.7450745880254-3.24507458802545
2503632.26134707943873.73865292056127
2511110.26224575484360.737754245156368
252128.884662830463933.11533716953607
2531519.1785195344927-4.17851953449271
25420.221.1160372930238-0.916037293023845
25520.823.5752648518267-2.77526485182667
25619.824.9188541297508-5.1188541297508
2573634.66579381234321.33420618765676
2583827.720241706347910.2797582936521
25926.622.90033057321323.69966942678679
26019.922.1226427756572-2.22264277565716
26123.922.54553469189951.35446530810046
2621716.58476551673840.415234483261589
2631210.73300728687021.26699271312983
2641116.9324226501084-5.9324226501084
26526.826.64497599087490.155024009125105
26623.824.5848217205237-0.784821720523743
2671211.23773896859540.762261031404626
2682529.3763340524596-4.3763340524596
2692826.04791794991921.95208205008082
2702427.4052003166716-3.40520031667158
2712627.0576510829349-1.05765108293493
2723026.03721249449393.96278750550615
2731922.2526393832871-3.25263938328712
2742323.5893024249254-0.589302424925415
2752521.44983062184653.55016937815355
27627.225.3879555994711.81204440052901
2772121.0452903307576-0.0452903307576384
27828.126.71113806393891.38886193606113
27916.223.29463551574-7.09463551574
2801414.820337024686-0.820337024685971
28125.527.3016051560676-1.80160515606763
2823933.05649692056895.94350307943109
2832624.5775960835151.42240391648499
2841310.27385402421172.72614597578832
2852020.1464197064307-0.146419706430684
2862218.78903108384943.21096891615064
2872320.69878499552532.30121500447473
2881816.53803636711621.46196363288385
2891412.72629536370821.27370463629183
2901412.09193092538741.90806907461263
2911410.95801102784493.04198897215514
2921512.62394252894022.37605747105982
2931612.54226214720083.45773785279924
29434.229.42112443956044.77887556043958
29534.730.91480641545083.78519358454915
2963832.3265954979445.67340450205601
29734.529.76212346240554.73787653759449
29827.229.3189478691111-2.11894786911111
2993030.0350458170858-0.0350458170857983
30023.225.381625584001-2.18162558400099
3011815.79512718557062.2048728144294
3021615.70578623971630.294213760283733
3031413.01950139544050.980498604559514
3041816.91308216433131.08691783566871
3051819.470521707755-1.470521707755
3062221.10065642069790.899343579302063
3071920.091246185162-1.091246185162
30820.521.3531019534322-0.853101953432235
3091919.1911150206799-0.191115020679893
3101317.145802083524-4.14580208352395
3112323.8819708274933-0.881970827493291
3121411.68328603149062.31671396850937
3131410.32717127586913.67282872413092
3141612.14720408630343.85279591369664
3151410.34651673402343.65348326597659
3161917.00955323754011.99044676245993
3171613.21101478175112.78898521824889
3181616.7985370137393-0.79853701373933
3193129.32285271084341.67714728915657
32021.523.4687163951927-1.9687163951927
3212728.5951827408399-1.59518274083988
32233.527.42198671850946.07801328149063
32319.220.6929312213192-1.4929312213192
324135.736209945157787.26379005484222
32524.524.5711286316955-0.0711286316954749
32618.518.5238545385446-0.0238545385446018
3272626.2093660282635-0.20936602826347
3282729.3592756610297-2.3592756610297
3293632.52333267649433.47666732350572
3302523.41943760168461.58056239831536
33121.627.0974329857031-5.49743298570305
3322424.0281761405249-0.0281761405249066
3332525.5491380382429-0.549138038242944
3342626.5945971640998-0.594597164099785
33532.334.3013134535739-2.00131345357394
3363031.6549485246382-1.65494852463816
33733.832.95772417564980.842275824350186
3382026.4579109048211-6.45791090482112
3393231.44541254505440.554587454945572
34021.129.1832342216657-8.0832342216657
3412829.6975610055929-1.69756100559288
3422928.79045047691050.209549523089532
34332.232.2418597499013-0.0418597499012848
34432.432.4601522524366-0.0601522524366136
3453433.97424104178330.0257589582167182
3463128.07048806453572.92951193546435
3473230.03480181986681.96519818013322
3482726.88069656523460.119303434765439
3492629.7453539967057-3.74535399670565
35038.134.09029109537264.00970890462744
3512425.5139253521091-1.51392535210912
3522525.3588874676769-0.358887467676887
35327.528.8763351011051-1.37633510110512
3543131.3567441785255-0.35674417852546
3552425.8158792862038-1.81587928620377
35629.829.44249973485690.357500265143102
3572423.5788194405110.421180559488953
35825.429.2684351597571-3.86843515975713
3591924.9620271074669-5.96202710746688
3602023.4069121795499-3.40691217954986
36139.136.24772574762852.85227425237146
36237.734.32904353927863.37095646072141
3632324.3261721605354-1.32617216053542
3643530.71463010587674.28536989412334
36529.834.8741176179083-5.07411761790827
3662627.0369786299064-1.03697862990637
3672224.2463623872313-2.2463623872313
3682528.3155320009831-3.31553200098309
3692629.1882028493259-3.18820284932589
37030.530.20182145731010.29817854268993
3713333.4683544439469-0.468354443946855
3722727.8417894517352-0.841789451735246
3732930.266046411657-1.26604641165701
37429.531.8931234827073-2.39312348270726
3752931.9068165715355-2.90681657153553
37643.132.332659873841710.7673401261583
3773635.69854118126820.301458818731784
37831.532.2892387689135-0.789238768913546
3792628.6466534014786-2.64665340147859
3802325.7753885012085-2.77538850120846
3811922.6096202054893-3.60962020548933
3821821.3683306344187-3.36833063441873
3832223.6804633930518-1.68046339305185
3842023.1642490645514-3.16424906455143
3851725.1360302391035-8.13603023910349
38630.727.22582150649643.47417849350357
38743.431.5416483966711.85835160333
3884434.60097449158419.39902550841592
3892931.064037253029-2.06403725302899
39041.532.91883428508718.5811657149129
39144.333.246643510895411.0533564891046
39231.933.5305283399841-1.63052833998414






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.1300579852543090.2601159705086190.86994201474569
100.06008056448771290.1201611289754260.939919435512287
110.02223759162748350.04447518325496710.977762408372516
120.03229440864080540.06458881728161080.967705591359195
130.01641946136269070.03283892272538130.98358053863731
140.006707412691228460.01341482538245690.993292587308772
150.01251727974239990.02503455948479970.9874827202576
160.005649851255634490.0112997025112690.994350148744366
170.006381472010354730.01276294402070950.993618527989645
180.005750752872969630.01150150574593930.99424924712703
190.002727690714450020.005455381428900030.99727230928555
200.001302216773816720.002604433547633450.998697783226183
210.0006747295882395150.001349459176479030.99932527041176
220.0002951742794971030.0005903485589942070.999704825720503
230.0001314922256417030.0002629844512834060.999868507774358
245.46717347902289e-050.0001093434695804580.99994532826521
253.30385966657336e-056.60771933314673e-050.999966961403334
261.43529286318126e-052.87058572636252e-050.999985647071368
274.48058575885238e-058.96117151770476e-050.999955194142411
281.94153161257431e-053.88306322514862e-050.999980584683874
294.23230618242872e-058.46461236485744e-050.999957676938176
302.01849903895264e-054.03699807790528e-050.99997981500961
310.0008906214307438050.001781242861487610.999109378569256
320.002677544385300730.005355088770601470.9973224556147
330.1609344359488290.3218688718976580.83906556405117
340.1397933479683230.2795866959366460.860206652031677
350.1157415133738370.2314830267476750.884258486626162
360.1883404846712830.3766809693425670.811659515328717
370.1543412031354110.3086824062708210.84565879686459
380.1250034934639090.2500069869278190.87499650653609
390.09914632196063530.1982926439212710.900853678039365
400.07833148812887350.1566629762577470.921668511871127
410.06530391268838680.1306078253767740.934696087311613
420.05021195266533050.1004239053306610.94978804733467
430.04852389489305370.09704778978610750.951476105106946
440.04033541533524420.08067083067048850.959664584664756
450.03067150420258740.06134300840517480.969328495797413
460.02412662418090940.04825324836181870.97587337581909
470.03181127867381450.0636225573476290.968188721326185
480.03057637648718810.06115275297437630.969423623512812
490.02360826396580330.04721652793160660.976391736034197
500.01779227689372830.03558455378745660.982207723106272
510.01337212873754280.02674425747508560.986627871262457
520.01061419450674720.02122838901349440.989385805493253
530.01167537277626760.02335074555253520.988324627223732
540.01789659946220110.03579319892440220.9821034005378
550.01481233656140130.02962467312280260.985187663438599
560.01162019625159550.0232403925031910.988379803748405
570.008773710881493430.01754742176298690.991226289118507
580.006731831536750260.01346366307350050.99326816846325
590.005012565442297760.01002513088459550.994987434557702
600.003706020657036970.007412041314073950.996293979342963
610.003320503579663090.006641007159326180.996679496420337
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3540.01203998963420520.02407997926841040.987960010365795
3550.00897544524196650.0179508904839330.991024554758033
3560.006413093315547660.01282618663109530.993586906684452
3570.007023249715168230.01404649943033650.992976750284832
3580.005276863043290190.01055372608658040.99472313695671
3590.004652886482265730.009305772964531470.995347113517734
3600.00451259322380270.00902518644760540.995487406776197
3610.00370563135476820.007411262709536410.996294368645232
3620.003690022541448510.007380045082897020.996309977458552
3630.002458896304859850.004917792609719710.99754110369514
3640.002489054076675560.004978108153351120.997510945923324
3650.01338080927658610.02676161855317220.986619190723414
3660.02040440803809580.04080881607619160.979595591961904
3670.0251010955560140.05020219111202790.974898904443986
3680.03330080611127620.06660161222255240.966699193888724
3690.05017564293758990.100351285875180.94982435706241
3700.03917172484984350.0783434496996870.960828275150156
3710.04717391771481510.09434783542963010.952826082285185
3720.1379715252718220.2759430505436440.862028474728178
3730.1012982478387410.2025964956774810.89870175216126
3740.07379094475395230.1475818895079050.926209055246048
3750.05822779597522480.116455591950450.941772204024775
3760.2057361182090170.4114722364180340.794263881790983
3770.1929044385553740.3858088771107470.807095561444626
3780.2666268312717540.5332536625435080.733373168728246
3790.2741613455606890.5483226911213790.72583865443931
3800.24108941775070.48217883550140.7589105822493
3810.1754338223035120.3508676446070230.824566177696488
3820.2168434716508910.4336869433017810.78315652834911
3830.1366920225250040.2733840450500070.863307977474996

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.130057985254309 & 0.260115970508619 & 0.86994201474569 \tabularnewline
10 & 0.0600805644877129 & 0.120161128975426 & 0.939919435512287 \tabularnewline
11 & 0.0222375916274835 & 0.0444751832549671 & 0.977762408372516 \tabularnewline
12 & 0.0322944086408054 & 0.0645888172816108 & 0.967705591359195 \tabularnewline
13 & 0.0164194613626907 & 0.0328389227253813 & 0.98358053863731 \tabularnewline
14 & 0.00670741269122846 & 0.0134148253824569 & 0.993292587308772 \tabularnewline
15 & 0.0125172797423999 & 0.0250345594847997 & 0.9874827202576 \tabularnewline
16 & 0.00564985125563449 & 0.011299702511269 & 0.994350148744366 \tabularnewline
17 & 0.00638147201035473 & 0.0127629440207095 & 0.993618527989645 \tabularnewline
18 & 0.00575075287296963 & 0.0115015057459393 & 0.99424924712703 \tabularnewline
19 & 0.00272769071445002 & 0.00545538142890003 & 0.99727230928555 \tabularnewline
20 & 0.00130221677381672 & 0.00260443354763345 & 0.998697783226183 \tabularnewline
21 & 0.000674729588239515 & 0.00134945917647903 & 0.99932527041176 \tabularnewline
22 & 0.000295174279497103 & 0.000590348558994207 & 0.999704825720503 \tabularnewline
23 & 0.000131492225641703 & 0.000262984451283406 & 0.999868507774358 \tabularnewline
24 & 5.46717347902289e-05 & 0.000109343469580458 & 0.99994532826521 \tabularnewline
25 & 3.30385966657336e-05 & 6.60771933314673e-05 & 0.999966961403334 \tabularnewline
26 & 1.43529286318126e-05 & 2.87058572636252e-05 & 0.999985647071368 \tabularnewline
27 & 4.48058575885238e-05 & 8.96117151770476e-05 & 0.999955194142411 \tabularnewline
28 & 1.94153161257431e-05 & 3.88306322514862e-05 & 0.999980584683874 \tabularnewline
29 & 4.23230618242872e-05 & 8.46461236485744e-05 & 0.999957676938176 \tabularnewline
30 & 2.01849903895264e-05 & 4.03699807790528e-05 & 0.99997981500961 \tabularnewline
31 & 0.000890621430743805 & 0.00178124286148761 & 0.999109378569256 \tabularnewline
32 & 0.00267754438530073 & 0.00535508877060147 & 0.9973224556147 \tabularnewline
33 & 0.160934435948829 & 0.321868871897658 & 0.83906556405117 \tabularnewline
34 & 0.139793347968323 & 0.279586695936646 & 0.860206652031677 \tabularnewline
35 & 0.115741513373837 & 0.231483026747675 & 0.884258486626162 \tabularnewline
36 & 0.188340484671283 & 0.376680969342567 & 0.811659515328717 \tabularnewline
37 & 0.154341203135411 & 0.308682406270821 & 0.84565879686459 \tabularnewline
38 & 0.125003493463909 & 0.250006986927819 & 0.87499650653609 \tabularnewline
39 & 0.0991463219606353 & 0.198292643921271 & 0.900853678039365 \tabularnewline
40 & 0.0783314881288735 & 0.156662976257747 & 0.921668511871127 \tabularnewline
41 & 0.0653039126883868 & 0.130607825376774 & 0.934696087311613 \tabularnewline
42 & 0.0502119526653305 & 0.100423905330661 & 0.94978804733467 \tabularnewline
43 & 0.0485238948930537 & 0.0970477897861075 & 0.951476105106946 \tabularnewline
44 & 0.0403354153352442 & 0.0806708306704885 & 0.959664584664756 \tabularnewline
45 & 0.0306715042025874 & 0.0613430084051748 & 0.969328495797413 \tabularnewline
46 & 0.0241266241809094 & 0.0482532483618187 & 0.97587337581909 \tabularnewline
47 & 0.0318112786738145 & 0.063622557347629 & 0.968188721326185 \tabularnewline
48 & 0.0305763764871881 & 0.0611527529743763 & 0.969423623512812 \tabularnewline
49 & 0.0236082639658033 & 0.0472165279316066 & 0.976391736034197 \tabularnewline
50 & 0.0177922768937283 & 0.0355845537874566 & 0.982207723106272 \tabularnewline
51 & 0.0133721287375428 & 0.0267442574750856 & 0.986627871262457 \tabularnewline
52 & 0.0106141945067472 & 0.0212283890134944 & 0.989385805493253 \tabularnewline
53 & 0.0116753727762676 & 0.0233507455525352 & 0.988324627223732 \tabularnewline
54 & 0.0178965994622011 & 0.0357931989244022 & 0.9821034005378 \tabularnewline
55 & 0.0148123365614013 & 0.0296246731228026 & 0.985187663438599 \tabularnewline
56 & 0.0116201962515955 & 0.023240392503191 & 0.988379803748405 \tabularnewline
57 & 0.00877371088149343 & 0.0175474217629869 & 0.991226289118507 \tabularnewline
58 & 0.00673183153675026 & 0.0134636630735005 & 0.99326816846325 \tabularnewline
59 & 0.00501256544229776 & 0.0100251308845955 & 0.994987434557702 \tabularnewline
60 & 0.00370602065703697 & 0.00741204131407395 & 0.996293979342963 \tabularnewline
61 & 0.00332050357966309 & 0.00664100715932618 & 0.996679496420337 \tabularnewline
62 & 0.00237340150148982 & 0.00474680300297963 & 0.99762659849851 \tabularnewline
63 & 0.00168393402045813 & 0.00336786804091626 & 0.998316065979542 \tabularnewline
64 & 0.0032842349902198 & 0.00656846998043961 & 0.99671576500978 \tabularnewline
65 & 0.00248028832333056 & 0.00496057664666113 & 0.99751971167667 \tabularnewline
66 & 0.00178199351411365 & 0.0035639870282273 & 0.998218006485886 \tabularnewline
67 & 0.00126952196279785 & 0.00253904392559571 & 0.998730478037202 \tabularnewline
68 & 0.00137989043365175 & 0.0027597808673035 & 0.998620109566348 \tabularnewline
69 & 0.000990722255882249 & 0.0019814445117645 & 0.999009277744118 \tabularnewline
70 & 0.000790701463823593 & 0.00158140292764719 & 0.999209298536176 \tabularnewline
71 & 0.000664977461548181 & 0.00132995492309636 & 0.999335022538452 \tabularnewline
72 & 0.000569619618987669 & 0.00113923923797534 & 0.999430380381012 \tabularnewline
73 & 0.000543365160664825 & 0.00108673032132965 & 0.999456634839335 \tabularnewline
74 & 0.00048879425300658 & 0.00097758850601316 & 0.999511205746993 \tabularnewline
75 & 0.00056575658746674 & 0.00113151317493348 & 0.999434243412533 \tabularnewline
76 & 0.000428711289092044 & 0.000857422578184087 & 0.999571288710908 \tabularnewline
77 & 0.00039805947067199 & 0.000796118941343979 & 0.999601940529328 \tabularnewline
78 & 0.000359021277241981 & 0.000718042554483961 & 0.999640978722758 \tabularnewline
79 & 0.000288445198120478 & 0.000576890396240957 & 0.99971155480188 \tabularnewline
80 & 0.000202647349318801 & 0.000405294698637602 & 0.999797352650681 \tabularnewline
81 & 0.000164926501018985 & 0.00032985300203797 & 0.99983507349898 \tabularnewline
82 & 0.000225807570848716 & 0.000451615141697433 & 0.999774192429151 \tabularnewline
83 & 0.000173476012196855 & 0.000346952024393711 & 0.999826523987803 \tabularnewline
84 & 0.000147956731178358 & 0.000295913462356715 & 0.999852043268822 \tabularnewline
85 & 0.000113743603057394 & 0.000227487206114788 & 0.999886256396943 \tabularnewline
86 & 8.81519482070292e-05 & 0.000176303896414058 & 0.999911848051793 \tabularnewline
87 & 6.18240945030591e-05 & 0.000123648189006118 & 0.999938175905497 \tabularnewline
88 & 4.77612291328166e-05 & 9.55224582656332e-05 & 0.999952238770867 \tabularnewline
89 & 3.33518150987324e-05 & 6.67036301974648e-05 & 0.999966648184901 \tabularnewline
90 & 2.24263689294307e-05 & 4.48527378588614e-05 & 0.99997757363107 \tabularnewline
91 & 3.1284933147858e-05 & 6.2569866295716e-05 & 0.999968715066852 \tabularnewline
92 & 2.18332913135466e-05 & 4.36665826270932e-05 & 0.999978166708686 \tabularnewline
93 & 1.74322410343387e-05 & 3.48644820686775e-05 & 0.999982567758966 \tabularnewline
94 & 1.57412773009112e-05 & 3.14825546018224e-05 & 0.9999842587227 \tabularnewline
95 & 1.42737795454578e-05 & 2.85475590909157e-05 & 0.999985726220455 \tabularnewline
96 & 1.18126269097232e-05 & 2.36252538194464e-05 & 0.99998818737309 \tabularnewline
97 & 9.4242581155718e-06 & 1.88485162311436e-05 & 0.999990575741884 \tabularnewline
98 & 6.24954248974225e-06 & 1.24990849794845e-05 & 0.99999375045751 \tabularnewline
99 & 1.67974260462905e-05 & 3.3594852092581e-05 & 0.999983202573954 \tabularnewline
100 & 1.42485713530544e-05 & 2.84971427061088e-05 & 0.999985751428647 \tabularnewline
101 & 1.52037634462116e-05 & 3.04075268924231e-05 & 0.999984796236554 \tabularnewline
102 & 1.08295409717373e-05 & 2.16590819434745e-05 & 0.999989170459028 \tabularnewline
103 & 1.18360880895458e-05 & 2.36721761790915e-05 & 0.99998816391191 \tabularnewline
104 & 8.09562629960194e-06 & 1.61912525992039e-05 & 0.9999919043737 \tabularnewline
105 & 7.17205020317145e-06 & 1.43441004063429e-05 & 0.999992827949797 \tabularnewline
106 & 1.74058395158116e-05 & 3.48116790316232e-05 & 0.999982594160484 \tabularnewline
107 & 1.22831042637065e-05 & 2.4566208527413e-05 & 0.999987716895736 \tabularnewline
108 & 1.14201738951943e-05 & 2.28403477903885e-05 & 0.999988579826105 \tabularnewline
109 & 8.51375144236002e-06 & 1.702750288472e-05 & 0.999991486248558 \tabularnewline
110 & 7.29947994149277e-06 & 1.45989598829855e-05 & 0.999992700520059 \tabularnewline
111 & 6.11744940739954e-05 & 0.000122348988147991 & 0.999938825505926 \tabularnewline
112 & 5.21616701577746e-05 & 0.000104323340315549 & 0.999947838329842 \tabularnewline
113 & 3.82282805842277e-05 & 7.64565611684553e-05 & 0.999961771719416 \tabularnewline
114 & 0.000193006395035349 & 0.000386012790070698 & 0.999806993604965 \tabularnewline
115 & 0.000149697341512276 & 0.000299394683024552 & 0.999850302658488 \tabularnewline
116 & 0.000141083825190908 & 0.000282167650381815 & 0.99985891617481 \tabularnewline
117 & 0.000119761899950587 & 0.000239523799901175 & 0.99988023810005 \tabularnewline
118 & 9.2350003531587e-05 & 0.000184700007063174 & 0.999907649996468 \tabularnewline
119 & 0.00017355915975524 & 0.00034711831951048 & 0.999826440840245 \tabularnewline
120 & 0.000136837803572936 & 0.000273675607145872 & 0.999863162196427 \tabularnewline
121 & 0.000194553911482972 & 0.000389107822965943 & 0.999805446088517 \tabularnewline
122 & 0.000534198150493864 & 0.00106839630098773 & 0.999465801849506 \tabularnewline
123 & 0.000708870239517336 & 0.00141774047903467 & 0.999291129760483 \tabularnewline
124 & 0.000593002040641175 & 0.00118600408128235 & 0.99940699795936 \tabularnewline
125 & 0.00122223486328357 & 0.00244446972656714 & 0.998777765136716 \tabularnewline
126 & 0.00208322826560607 & 0.00416645653121213 & 0.997916771734394 \tabularnewline
127 & 0.00163893047788791 & 0.00327786095577582 & 0.998361069522112 \tabularnewline
128 & 0.00129875772240208 & 0.00259751544480417 & 0.998701242277598 \tabularnewline
129 & 0.00360801546717985 & 0.00721603093435969 & 0.99639198453282 \tabularnewline
130 & 0.00292584329782116 & 0.00585168659564232 & 0.997074156702179 \tabularnewline
131 & 0.00239249923085232 & 0.00478499846170465 & 0.997607500769148 \tabularnewline
132 & 0.00193419852085747 & 0.00386839704171494 & 0.998065801479143 \tabularnewline
133 & 0.0015227861118939 & 0.0030455722237878 & 0.998477213888106 \tabularnewline
134 & 0.00133413251192008 & 0.00266826502384017 & 0.99866586748808 \tabularnewline
135 & 0.00108090065420319 & 0.00216180130840637 & 0.998919099345797 \tabularnewline
136 & 0.00120822914641057 & 0.00241645829282114 & 0.99879177085359 \tabularnewline
137 & 0.00100155549710212 & 0.00200311099420423 & 0.998998444502898 \tabularnewline
138 & 0.000825942133046622 & 0.00165188426609324 & 0.999174057866953 \tabularnewline
139 & 0.00063696389843448 & 0.00127392779686896 & 0.999363036101566 \tabularnewline
140 & 0.00133272028822805 & 0.00266544057645609 & 0.998667279711772 \tabularnewline
141 & 0.00103423208546445 & 0.0020684641709289 & 0.998965767914536 \tabularnewline
142 & 0.000868279482681855 & 0.00173655896536371 & 0.999131720517318 \tabularnewline
143 & 0.000760873702648032 & 0.00152174740529606 & 0.999239126297352 \tabularnewline
144 & 0.000858380340783423 & 0.00171676068156685 & 0.999141619659217 \tabularnewline
145 & 0.000662229288989813 & 0.00132445857797963 & 0.99933777071101 \tabularnewline
146 & 0.00097392753253266 & 0.00194785506506532 & 0.999026072467467 \tabularnewline
147 & 0.00143148740014868 & 0.00286297480029736 & 0.998568512599851 \tabularnewline
148 & 0.00112551679701057 & 0.00225103359402114 & 0.99887448320299 \tabularnewline
149 & 0.00088353250858821 & 0.00176706501717642 & 0.999116467491412 \tabularnewline
150 & 0.000735983337908114 & 0.00147196667581623 & 0.999264016662092 \tabularnewline
151 & 0.00111158971717959 & 0.00222317943435918 & 0.99888841028282 \tabularnewline
152 & 0.000891914215944055 & 0.00178382843188811 & 0.999108085784056 \tabularnewline
153 & 0.000891194209418128 & 0.00178238841883626 & 0.999108805790582 \tabularnewline
154 & 0.000702777653275213 & 0.00140555530655043 & 0.999297222346725 \tabularnewline
155 & 0.000544022939269491 & 0.00108804587853898 & 0.99945597706073 \tabularnewline
156 & 0.000746919454303249 & 0.0014938389086065 & 0.999253080545697 \tabularnewline
157 & 0.000589602607495167 & 0.00117920521499033 & 0.999410397392505 \tabularnewline
158 & 0.000542223531284619 & 0.00108444706256924 & 0.999457776468715 \tabularnewline
159 & 0.000438293928604724 & 0.000876587857209448 & 0.999561706071395 \tabularnewline
160 & 0.000365688631258702 & 0.000731377262517404 & 0.999634311368741 \tabularnewline
161 & 0.000277446721923512 & 0.000554893443847024 & 0.999722553278076 \tabularnewline
162 & 0.000217134352548545 & 0.00043426870509709 & 0.999782865647451 \tabularnewline
163 & 0.00025627832875681 & 0.00051255665751362 & 0.999743721671243 \tabularnewline
164 & 0.000300042669646384 & 0.000600085339292769 & 0.999699957330354 \tabularnewline
165 & 0.000228302990974044 & 0.000456605981948089 & 0.999771697009026 \tabularnewline
166 & 0.000175770791465242 & 0.000351541582930483 & 0.999824229208535 \tabularnewline
167 & 0.000349210020886534 & 0.000698420041773069 & 0.999650789979113 \tabularnewline
168 & 0.000301272173686474 & 0.000602544347372949 & 0.999698727826314 \tabularnewline
169 & 0.000288096682543919 & 0.000576193365087838 & 0.999711903317456 \tabularnewline
170 & 0.000362624111859163 & 0.000725248223718325 & 0.99963737588814 \tabularnewline
171 & 0.0003679816826281 & 0.0007359633652562 & 0.999632018317372 \tabularnewline
172 & 0.000281352924185748 & 0.000562705848371495 & 0.999718647075814 \tabularnewline
173 & 0.000266786939441924 & 0.000533573878883849 & 0.999733213060558 \tabularnewline
174 & 0.000346243026932456 & 0.000692486053864911 & 0.999653756973067 \tabularnewline
175 & 0.000278343286310731 & 0.000556686572621462 & 0.99972165671369 \tabularnewline
176 & 0.000211867041123277 & 0.000423734082246554 & 0.999788132958877 \tabularnewline
177 & 0.000247129078948837 & 0.000494258157897675 & 0.999752870921051 \tabularnewline
178 & 0.000187581100432313 & 0.000375162200864626 & 0.999812418899568 \tabularnewline
179 & 0.000177164137128988 & 0.000354328274257977 & 0.999822835862871 \tabularnewline
180 & 0.000187286146092564 & 0.000374572292185127 & 0.999812713853907 \tabularnewline
181 & 0.000290185576924423 & 0.000580371153848846 & 0.999709814423076 \tabularnewline
182 & 0.000449421883738088 & 0.000898843767476177 & 0.999550578116262 \tabularnewline
183 & 0.000352621780311431 & 0.000705243560622861 & 0.999647378219689 \tabularnewline
184 & 0.000292928770061061 & 0.000585857540122121 & 0.99970707122994 \tabularnewline
185 & 0.000374687330248405 & 0.00074937466049681 & 0.999625312669752 \tabularnewline
186 & 0.000286846932800158 & 0.000573693865600316 & 0.9997131530672 \tabularnewline
187 & 0.000226726994071998 & 0.000453453988143997 & 0.999773273005928 \tabularnewline
188 & 0.000185885951786165 & 0.00037177190357233 & 0.999814114048214 \tabularnewline
189 & 0.000146998757526147 & 0.000293997515052293 & 0.999853001242474 \tabularnewline
190 & 0.000141217752352688 & 0.000282435504705375 & 0.999858782247647 \tabularnewline
191 & 0.000114667262788164 & 0.000229334525576328 & 0.999885332737212 \tabularnewline
192 & 8.8846600192852e-05 & 0.000177693200385704 & 0.999911153399807 \tabularnewline
193 & 0.000164174363272165 & 0.000328348726544329 & 0.999835825636728 \tabularnewline
194 & 0.000380542723954616 & 0.000761085447909233 & 0.999619457276045 \tabularnewline
195 & 0.00029380494797655 & 0.000587609895953099 & 0.999706195052023 \tabularnewline
196 & 0.000249077823916199 & 0.000498155647832398 & 0.999750922176084 \tabularnewline
197 & 0.000255743309914103 & 0.000511486619828206 & 0.999744256690086 \tabularnewline
198 & 0.000528040994824192 & 0.00105608198964838 & 0.999471959005176 \tabularnewline
199 & 0.000482203780460427 & 0.000964407560920854 & 0.99951779621954 \tabularnewline
200 & 0.000371497569107663 & 0.000742995138215326 & 0.999628502430892 \tabularnewline
201 & 0.00030333653739724 & 0.00060667307479448 & 0.999696663462603 \tabularnewline
202 & 0.000231750862142071 & 0.000463501724284142 & 0.999768249137858 \tabularnewline
203 & 0.000185762148920053 & 0.000371524297840106 & 0.99981423785108 \tabularnewline
204 & 0.000972888596140651 & 0.0019457771922813 & 0.99902711140386 \tabularnewline
205 & 0.000775314502638428 & 0.00155062900527686 & 0.999224685497362 \tabularnewline
206 & 0.00087227107676009 & 0.00174454215352018 & 0.99912772892324 \tabularnewline
207 & 0.00138116106542082 & 0.00276232213084164 & 0.99861883893458 \tabularnewline
208 & 0.00110396933091919 & 0.00220793866183838 & 0.99889603066908 \tabularnewline
209 & 0.000938678861727119 & 0.00187735772345424 & 0.999061321138273 \tabularnewline
210 & 0.0007723891673623 & 0.0015447783347246 & 0.999227610832638 \tabularnewline
211 & 0.000621384029641094 & 0.00124276805928219 & 0.99937861597036 \tabularnewline
212 & 0.00061747755253971 & 0.00123495510507942 & 0.99938252244746 \tabularnewline
213 & 0.000506278584778155 & 0.00101255716955631 & 0.999493721415222 \tabularnewline
214 & 0.000400103349754567 & 0.000800206699509135 & 0.999599896650246 \tabularnewline
215 & 0.000318767636085427 & 0.000637535272170854 & 0.999681232363915 \tabularnewline
216 & 0.000264544017430875 & 0.00052908803486175 & 0.99973545598257 \tabularnewline
217 & 0.000246690070049869 & 0.000493380140099737 & 0.99975330992995 \tabularnewline
218 & 0.000188106147118768 & 0.000376212294237537 & 0.999811893852881 \tabularnewline
219 & 0.000152198709927976 & 0.000304397419855951 & 0.999847801290072 \tabularnewline
220 & 0.000116206615836229 & 0.000232413231672458 & 0.999883793384164 \tabularnewline
221 & 0.000102201564204825 & 0.00020440312840965 & 0.999897798435795 \tabularnewline
222 & 9.89343861979609e-05 & 0.000197868772395922 & 0.999901065613802 \tabularnewline
223 & 7.51677055359884e-05 & 0.000150335411071977 & 0.999924832294464 \tabularnewline
224 & 6.4538301447028e-05 & 0.000129076602894056 & 0.999935461698553 \tabularnewline
225 & 7.46912776497657e-05 & 0.000149382555299531 & 0.99992530872235 \tabularnewline
226 & 5.88617529472472e-05 & 0.000117723505894494 & 0.999941138247053 \tabularnewline
227 & 0.000525460287100401 & 0.0010509205742008 & 0.9994745397129 \tabularnewline
228 & 0.000432833118783656 & 0.000865666237567312 & 0.999567166881216 \tabularnewline
229 & 0.000377090471237873 & 0.000754180942475747 & 0.999622909528762 \tabularnewline
230 & 0.00028880761609828 & 0.000577615232196559 & 0.999711192383902 \tabularnewline
231 & 0.000224077572902099 & 0.000448155145804197 & 0.999775922427098 \tabularnewline
232 & 0.00176112294838553 & 0.00352224589677106 & 0.998238877051614 \tabularnewline
233 & 0.00141857306477292 & 0.00283714612954583 & 0.998581426935227 \tabularnewline
234 & 0.00114554866290625 & 0.0022910973258125 & 0.998854451337094 \tabularnewline
235 & 0.0323726442773184 & 0.0647452885546368 & 0.967627355722682 \tabularnewline
236 & 0.0276738472940998 & 0.0553476945881997 & 0.9723261527059 \tabularnewline
237 & 0.0335939587030403 & 0.0671879174060805 & 0.96640604129696 \tabularnewline
238 & 0.0296847342716159 & 0.0593694685432318 & 0.970315265728384 \tabularnewline
239 & 0.0255652177307216 & 0.0511304354614431 & 0.974434782269278 \tabularnewline
240 & 0.033249996168908 & 0.066499992337816 & 0.966750003831092 \tabularnewline
241 & 0.058253948089001 & 0.116507896178002 & 0.941746051911 \tabularnewline
242 & 0.0812326302978718 & 0.162465260595744 & 0.918767369702128 \tabularnewline
243 & 0.0746608344978243 & 0.149321668995649 & 0.925339165502176 \tabularnewline
244 & 0.0824034698534177 & 0.164806939706835 & 0.917596530146582 \tabularnewline
245 & 0.0772118205963643 & 0.154423641192729 & 0.922788179403636 \tabularnewline
246 & 0.0670965177593107 & 0.134193035518621 & 0.93290348224069 \tabularnewline
247 & 0.0639754283961737 & 0.127950856792347 & 0.936024571603826 \tabularnewline
248 & 0.0553847866489916 & 0.110769573297983 & 0.944615213351008 \tabularnewline
249 & 0.0614849473412655 & 0.122969894682531 & 0.938515052658734 \tabularnewline
250 & 0.0620946569277033 & 0.124189313855407 & 0.937905343072297 \tabularnewline
251 & 0.0538808003865291 & 0.107761600773058 & 0.94611919961347 \tabularnewline
252 & 0.051388797903265 & 0.10277759580653 & 0.948611202096735 \tabularnewline
253 & 0.0596999595958053 & 0.119399919191611 & 0.940300040404195 \tabularnewline
254 & 0.0551533046988265 & 0.110306609397653 & 0.944846695301174 \tabularnewline
255 & 0.0561416266736028 & 0.112283253347206 & 0.943858373326397 \tabularnewline
256 & 0.0793452182516294 & 0.158690436503259 & 0.92065478174837 \tabularnewline
257 & 0.0700337842220561 & 0.140067568444112 & 0.929966215777944 \tabularnewline
258 & 0.169395815620673 & 0.338791631241345 & 0.830604184379327 \tabularnewline
259 & 0.166315183625145 & 0.33263036725029 & 0.833684816374855 \tabularnewline
260 & 0.165973699032407 & 0.331947398064813 & 0.834026300967593 \tabularnewline
261 & 0.150035909224942 & 0.300071818449884 & 0.849964090775058 \tabularnewline
262 & 0.132930452892089 & 0.265860905784179 & 0.86706954710791 \tabularnewline
263 & 0.118409639025098 & 0.236819278050196 & 0.881590360974902 \tabularnewline
264 & 0.184965132455927 & 0.369930264911853 & 0.815034867544073 \tabularnewline
265 & 0.169279302238055 & 0.33855860447611 & 0.830720697761945 \tabularnewline
266 & 0.154745176684136 & 0.309490353368271 & 0.845254823315864 \tabularnewline
267 & 0.137230767204971 & 0.274461534409941 & 0.86276923279503 \tabularnewline
268 & 0.154583881971779 & 0.309167763943558 & 0.845416118028221 \tabularnewline
269 & 0.142747484417153 & 0.285494968834306 & 0.857252515582847 \tabularnewline
270 & 0.145372122257721 & 0.290744244515443 & 0.854627877742279 \tabularnewline
271 & 0.129483010450545 & 0.25896602090109 & 0.870516989549455 \tabularnewline
272 & 0.141206546433512 & 0.282413092867023 & 0.858793453566488 \tabularnewline
273 & 0.134014338726655 & 0.26802867745331 & 0.865985661273345 \tabularnewline
274 & 0.118251277976328 & 0.236502555952655 & 0.881748722023672 \tabularnewline
275 & 0.133605545393011 & 0.267211090786023 & 0.866394454606989 \tabularnewline
276 & 0.125395313327221 & 0.250790626654442 & 0.874604686672779 \tabularnewline
277 & 0.114151265009131 & 0.228302530018262 & 0.885848734990869 \tabularnewline
278 & 0.104577698378106 & 0.209155396756213 & 0.895422301621894 \tabularnewline
279 & 0.149058861202036 & 0.298117722404073 & 0.850941138797964 \tabularnewline
280 & 0.140082061049147 & 0.280164122098293 & 0.859917938950853 \tabularnewline
281 & 0.137090766454543 & 0.274181532909086 & 0.862909233545457 \tabularnewline
282 & 0.154961560093778 & 0.309923120187557 & 0.845038439906222 \tabularnewline
283 & 0.138102109759393 & 0.276204219518785 & 0.861897890240607 \tabularnewline
284 & 0.129267454267758 & 0.258534908535516 & 0.870732545732242 \tabularnewline
285 & 0.113824552936613 & 0.227649105873225 & 0.886175447063387 \tabularnewline
286 & 0.108616999240883 & 0.217233998481766 & 0.891383000759117 \tabularnewline
287 & 0.0978068093109823 & 0.195613618621965 & 0.902193190689018 \tabularnewline
288 & 0.0872685851254905 & 0.174537170250981 & 0.91273141487451 \tabularnewline
289 & 0.075946864494994 & 0.151893728989988 & 0.924053135505006 \tabularnewline
290 & 0.0673973590448093 & 0.134794718089619 & 0.93260264095519 \tabularnewline
291 & 0.0603375113196672 & 0.120675022639334 & 0.939662488680333 \tabularnewline
292 & 0.0546027963083976 & 0.109205592616795 & 0.945397203691602 \tabularnewline
293 & 0.0558350466866502 & 0.1116700933733 & 0.94416495331335 \tabularnewline
294 & 0.0594477094620667 & 0.118895418924133 & 0.940552290537933 \tabularnewline
295 & 0.0571380489795277 & 0.114276097959055 & 0.942861951020472 \tabularnewline
296 & 0.0663810579683776 & 0.132762115936755 & 0.933618942031622 \tabularnewline
297 & 0.0731127214647829 & 0.146225442929566 & 0.926887278535217 \tabularnewline
298 & 0.0696846900879747 & 0.139369380175949 & 0.930315309912025 \tabularnewline
299 & 0.0607008740219916 & 0.121401748043983 & 0.939299125978008 \tabularnewline
300 & 0.0570836092792165 & 0.114167218558433 & 0.942916390720783 \tabularnewline
301 & 0.0492549215192221 & 0.0985098430384442 & 0.950745078480778 \tabularnewline
302 & 0.041693768731373 & 0.083387537462746 & 0.958306231268627 \tabularnewline
303 & 0.035004055261112 & 0.070008110522224 & 0.964995944738888 \tabularnewline
304 & 0.0301359193452402 & 0.0602718386904804 & 0.96986408065476 \tabularnewline
305 & 0.0261596419493003 & 0.0523192838986006 & 0.9738403580507 \tabularnewline
306 & 0.021436047543154 & 0.042872095086308 & 0.978563952456846 \tabularnewline
307 & 0.0181199286837924 & 0.0362398573675847 & 0.981880071316208 \tabularnewline
308 & 0.0152216163048321 & 0.0304432326096641 & 0.984778383695168 \tabularnewline
309 & 0.0122043524422931 & 0.0244087048845862 & 0.987795647557707 \tabularnewline
310 & 0.0169516622023251 & 0.0339033244046502 & 0.983048337797675 \tabularnewline
311 & 0.0141776323289271 & 0.0283552646578543 & 0.985822367671073 \tabularnewline
312 & 0.0116623953905472 & 0.0233247907810943 & 0.988337604609453 \tabularnewline
313 & 0.01012546509502 & 0.0202509301900399 & 0.98987453490498 \tabularnewline
314 & 0.0094217837330237 & 0.0188435674660474 & 0.990578216266976 \tabularnewline
315 & 0.0091364928908174 & 0.0182729857816348 & 0.990863507109183 \tabularnewline
316 & 0.0076031336822491 & 0.0152062673644982 & 0.992396866317751 \tabularnewline
317 & 0.00680420002883994 & 0.0136084000576799 & 0.99319579997116 \tabularnewline
318 & 0.00573485513270961 & 0.0114697102654192 & 0.99426514486729 \tabularnewline
319 & 0.00452600120692268 & 0.00905200241384536 & 0.995473998793077 \tabularnewline
320 & 0.00479799496661095 & 0.0095959899332219 & 0.99520200503339 \tabularnewline
321 & 0.00599310983273179 & 0.0119862196654636 & 0.994006890167268 \tabularnewline
322 & 0.00614110349138239 & 0.0122822069827648 & 0.993858896508618 \tabularnewline
323 & 0.00648942991211769 & 0.0129788598242354 & 0.993510570087882 \tabularnewline
324 & 0.0710867292536726 & 0.142173458507345 & 0.928913270746327 \tabularnewline
325 & 0.0916324868533088 & 0.183264973706618 & 0.908367513146691 \tabularnewline
326 & 0.076717327059686 & 0.153434654119372 & 0.923282672940314 \tabularnewline
327 & 0.0640569545816719 & 0.128113909163344 & 0.935943045418328 \tabularnewline
328 & 0.0584514855903043 & 0.116902971180609 & 0.941548514409696 \tabularnewline
329 & 0.052009616671434 & 0.104019233342868 & 0.947990383328566 \tabularnewline
330 & 0.0524599805045036 & 0.104919961009007 & 0.947540019495496 \tabularnewline
331 & 0.0759191215978241 & 0.151838243195648 & 0.924080878402176 \tabularnewline
332 & 0.0664608959605627 & 0.132921791921125 & 0.933539104039437 \tabularnewline
333 & 0.0548073949106267 & 0.109614789821253 & 0.945192605089373 \tabularnewline
334 & 0.0453529601817962 & 0.0907059203635924 & 0.954647039818204 \tabularnewline
335 & 0.0479956966608346 & 0.0959913933216692 & 0.952004303339165 \tabularnewline
336 & 0.0411849096981135 & 0.082369819396227 & 0.958815090301886 \tabularnewline
337 & 0.0337653653235563 & 0.0675307306471125 & 0.966234634676444 \tabularnewline
338 & 0.0557077105266597 & 0.111415421053319 & 0.94429228947334 \tabularnewline
339 & 0.0471409151255135 & 0.094281830251027 & 0.952859084874486 \tabularnewline
340 & 0.0809460812803347 & 0.161892162560669 & 0.919053918719665 \tabularnewline
341 & 0.0731211613006362 & 0.146242322601272 & 0.926878838699364 \tabularnewline
342 & 0.0592007697770172 & 0.118401539554034 & 0.940799230222983 \tabularnewline
343 & 0.0497829336340861 & 0.0995658672681722 & 0.950217066365914 \tabularnewline
344 & 0.0446935148301067 & 0.0893870296602135 & 0.955306485169893 \tabularnewline
345 & 0.041430122878437 & 0.082860245756874 & 0.958569877121563 \tabularnewline
346 & 0.0361661488764742 & 0.0723322977529485 & 0.963833851123526 \tabularnewline
347 & 0.0282826263848625 & 0.056565252769725 & 0.971717373615137 \tabularnewline
348 & 0.0224883149128296 & 0.0449766298256592 & 0.97751168508717 \tabularnewline
349 & 0.0362831488421758 & 0.0725662976843516 & 0.963716851157824 \tabularnewline
350 & 0.0294302515791603 & 0.0588605031583206 & 0.97056974842084 \tabularnewline
351 & 0.0227376540940906 & 0.0454753081881813 & 0.97726234590591 \tabularnewline
352 & 0.020577017316354 & 0.041154034632708 & 0.979422982683646 \tabularnewline
353 & 0.0154275603963594 & 0.0308551207927189 & 0.98457243960364 \tabularnewline
354 & 0.0120399896342052 & 0.0240799792684104 & 0.987960010365795 \tabularnewline
355 & 0.0089754452419665 & 0.017950890483933 & 0.991024554758033 \tabularnewline
356 & 0.00641309331554766 & 0.0128261866310953 & 0.993586906684452 \tabularnewline
357 & 0.00702324971516823 & 0.0140464994303365 & 0.992976750284832 \tabularnewline
358 & 0.00527686304329019 & 0.0105537260865804 & 0.99472313695671 \tabularnewline
359 & 0.00465288648226573 & 0.00930577296453147 & 0.995347113517734 \tabularnewline
360 & 0.0045125932238027 & 0.0090251864476054 & 0.995487406776197 \tabularnewline
361 & 0.0037056313547682 & 0.00741126270953641 & 0.996294368645232 \tabularnewline
362 & 0.00369002254144851 & 0.00738004508289702 & 0.996309977458552 \tabularnewline
363 & 0.00245889630485985 & 0.00491779260971971 & 0.99754110369514 \tabularnewline
364 & 0.00248905407667556 & 0.00497810815335112 & 0.997510945923324 \tabularnewline
365 & 0.0133808092765861 & 0.0267616185531722 & 0.986619190723414 \tabularnewline
366 & 0.0204044080380958 & 0.0408088160761916 & 0.979595591961904 \tabularnewline
367 & 0.025101095556014 & 0.0502021911120279 & 0.974898904443986 \tabularnewline
368 & 0.0333008061112762 & 0.0666016122225524 & 0.966699193888724 \tabularnewline
369 & 0.0501756429375899 & 0.10035128587518 & 0.94982435706241 \tabularnewline
370 & 0.0391717248498435 & 0.078343449699687 & 0.960828275150156 \tabularnewline
371 & 0.0471739177148151 & 0.0943478354296301 & 0.952826082285185 \tabularnewline
372 & 0.137971525271822 & 0.275943050543644 & 0.862028474728178 \tabularnewline
373 & 0.101298247838741 & 0.202596495677481 & 0.89870175216126 \tabularnewline
374 & 0.0737909447539523 & 0.147581889507905 & 0.926209055246048 \tabularnewline
375 & 0.0582277959752248 & 0.11645559195045 & 0.941772204024775 \tabularnewline
376 & 0.205736118209017 & 0.411472236418034 & 0.794263881790983 \tabularnewline
377 & 0.192904438555374 & 0.385808877110747 & 0.807095561444626 \tabularnewline
378 & 0.266626831271754 & 0.533253662543508 & 0.733373168728246 \tabularnewline
379 & 0.274161345560689 & 0.548322691121379 & 0.72583865443931 \tabularnewline
380 & 0.2410894177507 & 0.4821788355014 & 0.7589105822493 \tabularnewline
381 & 0.175433822303512 & 0.350867644607023 & 0.824566177696488 \tabularnewline
382 & 0.216843471650891 & 0.433686943301781 & 0.78315652834911 \tabularnewline
383 & 0.136692022525004 & 0.273384045050007 & 0.863307977474996 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117208&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]9[/C][C]0.130057985254309[/C][C]0.260115970508619[/C][C]0.86994201474569[/C][/ROW]
[ROW][C]10[/C][C]0.0600805644877129[/C][C]0.120161128975426[/C][C]0.939919435512287[/C][/ROW]
[ROW][C]11[/C][C]0.0222375916274835[/C][C]0.0444751832549671[/C][C]0.977762408372516[/C][/ROW]
[ROW][C]12[/C][C]0.0322944086408054[/C][C]0.0645888172816108[/C][C]0.967705591359195[/C][/ROW]
[ROW][C]13[/C][C]0.0164194613626907[/C][C]0.0328389227253813[/C][C]0.98358053863731[/C][/ROW]
[ROW][C]14[/C][C]0.00670741269122846[/C][C]0.0134148253824569[/C][C]0.993292587308772[/C][/ROW]
[ROW][C]15[/C][C]0.0125172797423999[/C][C]0.0250345594847997[/C][C]0.9874827202576[/C][/ROW]
[ROW][C]16[/C][C]0.00564985125563449[/C][C]0.011299702511269[/C][C]0.994350148744366[/C][/ROW]
[ROW][C]17[/C][C]0.00638147201035473[/C][C]0.0127629440207095[/C][C]0.993618527989645[/C][/ROW]
[ROW][C]18[/C][C]0.00575075287296963[/C][C]0.0115015057459393[/C][C]0.99424924712703[/C][/ROW]
[ROW][C]19[/C][C]0.00272769071445002[/C][C]0.00545538142890003[/C][C]0.99727230928555[/C][/ROW]
[ROW][C]20[/C][C]0.00130221677381672[/C][C]0.00260443354763345[/C][C]0.998697783226183[/C][/ROW]
[ROW][C]21[/C][C]0.000674729588239515[/C][C]0.00134945917647903[/C][C]0.99932527041176[/C][/ROW]
[ROW][C]22[/C][C]0.000295174279497103[/C][C]0.000590348558994207[/C][C]0.999704825720503[/C][/ROW]
[ROW][C]23[/C][C]0.000131492225641703[/C][C]0.000262984451283406[/C][C]0.999868507774358[/C][/ROW]
[ROW][C]24[/C][C]5.46717347902289e-05[/C][C]0.000109343469580458[/C][C]0.99994532826521[/C][/ROW]
[ROW][C]25[/C][C]3.30385966657336e-05[/C][C]6.60771933314673e-05[/C][C]0.999966961403334[/C][/ROW]
[ROW][C]26[/C][C]1.43529286318126e-05[/C][C]2.87058572636252e-05[/C][C]0.999985647071368[/C][/ROW]
[ROW][C]27[/C][C]4.48058575885238e-05[/C][C]8.96117151770476e-05[/C][C]0.999955194142411[/C][/ROW]
[ROW][C]28[/C][C]1.94153161257431e-05[/C][C]3.88306322514862e-05[/C][C]0.999980584683874[/C][/ROW]
[ROW][C]29[/C][C]4.23230618242872e-05[/C][C]8.46461236485744e-05[/C][C]0.999957676938176[/C][/ROW]
[ROW][C]30[/C][C]2.01849903895264e-05[/C][C]4.03699807790528e-05[/C][C]0.99997981500961[/C][/ROW]
[ROW][C]31[/C][C]0.000890621430743805[/C][C]0.00178124286148761[/C][C]0.999109378569256[/C][/ROW]
[ROW][C]32[/C][C]0.00267754438530073[/C][C]0.00535508877060147[/C][C]0.9973224556147[/C][/ROW]
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[ROW][C]110[/C][C]7.29947994149277e-06[/C][C]1.45989598829855e-05[/C][C]0.999992700520059[/C][/ROW]
[ROW][C]111[/C][C]6.11744940739954e-05[/C][C]0.000122348988147991[/C][C]0.999938825505926[/C][/ROW]
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[ROW][C]319[/C][C]0.00452600120692268[/C][C]0.00905200241384536[/C][C]0.995473998793077[/C][/ROW]
[ROW][C]320[/C][C]0.00479799496661095[/C][C]0.0095959899332219[/C][C]0.99520200503339[/C][/ROW]
[ROW][C]321[/C][C]0.00599310983273179[/C][C]0.0119862196654636[/C][C]0.994006890167268[/C][/ROW]
[ROW][C]322[/C][C]0.00614110349138239[/C][C]0.0122822069827648[/C][C]0.993858896508618[/C][/ROW]
[ROW][C]323[/C][C]0.00648942991211769[/C][C]0.0129788598242354[/C][C]0.993510570087882[/C][/ROW]
[ROW][C]324[/C][C]0.0710867292536726[/C][C]0.142173458507345[/C][C]0.928913270746327[/C][/ROW]
[ROW][C]325[/C][C]0.0916324868533088[/C][C]0.183264973706618[/C][C]0.908367513146691[/C][/ROW]
[ROW][C]326[/C][C]0.076717327059686[/C][C]0.153434654119372[/C][C]0.923282672940314[/C][/ROW]
[ROW][C]327[/C][C]0.0640569545816719[/C][C]0.128113909163344[/C][C]0.935943045418328[/C][/ROW]
[ROW][C]328[/C][C]0.0584514855903043[/C][C]0.116902971180609[/C][C]0.941548514409696[/C][/ROW]
[ROW][C]329[/C][C]0.052009616671434[/C][C]0.104019233342868[/C][C]0.947990383328566[/C][/ROW]
[ROW][C]330[/C][C]0.0524599805045036[/C][C]0.104919961009007[/C][C]0.947540019495496[/C][/ROW]
[ROW][C]331[/C][C]0.0759191215978241[/C][C]0.151838243195648[/C][C]0.924080878402176[/C][/ROW]
[ROW][C]332[/C][C]0.0664608959605627[/C][C]0.132921791921125[/C][C]0.933539104039437[/C][/ROW]
[ROW][C]333[/C][C]0.0548073949106267[/C][C]0.109614789821253[/C][C]0.945192605089373[/C][/ROW]
[ROW][C]334[/C][C]0.0453529601817962[/C][C]0.0907059203635924[/C][C]0.954647039818204[/C][/ROW]
[ROW][C]335[/C][C]0.0479956966608346[/C][C]0.0959913933216692[/C][C]0.952004303339165[/C][/ROW]
[ROW][C]336[/C][C]0.0411849096981135[/C][C]0.082369819396227[/C][C]0.958815090301886[/C][/ROW]
[ROW][C]337[/C][C]0.0337653653235563[/C][C]0.0675307306471125[/C][C]0.966234634676444[/C][/ROW]
[ROW][C]338[/C][C]0.0557077105266597[/C][C]0.111415421053319[/C][C]0.94429228947334[/C][/ROW]
[ROW][C]339[/C][C]0.0471409151255135[/C][C]0.094281830251027[/C][C]0.952859084874486[/C][/ROW]
[ROW][C]340[/C][C]0.0809460812803347[/C][C]0.161892162560669[/C][C]0.919053918719665[/C][/ROW]
[ROW][C]341[/C][C]0.0731211613006362[/C][C]0.146242322601272[/C][C]0.926878838699364[/C][/ROW]
[ROW][C]342[/C][C]0.0592007697770172[/C][C]0.118401539554034[/C][C]0.940799230222983[/C][/ROW]
[ROW][C]343[/C][C]0.0497829336340861[/C][C]0.0995658672681722[/C][C]0.950217066365914[/C][/ROW]
[ROW][C]344[/C][C]0.0446935148301067[/C][C]0.0893870296602135[/C][C]0.955306485169893[/C][/ROW]
[ROW][C]345[/C][C]0.041430122878437[/C][C]0.082860245756874[/C][C]0.958569877121563[/C][/ROW]
[ROW][C]346[/C][C]0.0361661488764742[/C][C]0.0723322977529485[/C][C]0.963833851123526[/C][/ROW]
[ROW][C]347[/C][C]0.0282826263848625[/C][C]0.056565252769725[/C][C]0.971717373615137[/C][/ROW]
[ROW][C]348[/C][C]0.0224883149128296[/C][C]0.0449766298256592[/C][C]0.97751168508717[/C][/ROW]
[ROW][C]349[/C][C]0.0362831488421758[/C][C]0.0725662976843516[/C][C]0.963716851157824[/C][/ROW]
[ROW][C]350[/C][C]0.0294302515791603[/C][C]0.0588605031583206[/C][C]0.97056974842084[/C][/ROW]
[ROW][C]351[/C][C]0.0227376540940906[/C][C]0.0454753081881813[/C][C]0.97726234590591[/C][/ROW]
[ROW][C]352[/C][C]0.020577017316354[/C][C]0.041154034632708[/C][C]0.979422982683646[/C][/ROW]
[ROW][C]353[/C][C]0.0154275603963594[/C][C]0.0308551207927189[/C][C]0.98457243960364[/C][/ROW]
[ROW][C]354[/C][C]0.0120399896342052[/C][C]0.0240799792684104[/C][C]0.987960010365795[/C][/ROW]
[ROW][C]355[/C][C]0.0089754452419665[/C][C]0.017950890483933[/C][C]0.991024554758033[/C][/ROW]
[ROW][C]356[/C][C]0.00641309331554766[/C][C]0.0128261866310953[/C][C]0.993586906684452[/C][/ROW]
[ROW][C]357[/C][C]0.00702324971516823[/C][C]0.0140464994303365[/C][C]0.992976750284832[/C][/ROW]
[ROW][C]358[/C][C]0.00527686304329019[/C][C]0.0105537260865804[/C][C]0.99472313695671[/C][/ROW]
[ROW][C]359[/C][C]0.00465288648226573[/C][C]0.00930577296453147[/C][C]0.995347113517734[/C][/ROW]
[ROW][C]360[/C][C]0.0045125932238027[/C][C]0.0090251864476054[/C][C]0.995487406776197[/C][/ROW]
[ROW][C]361[/C][C]0.0037056313547682[/C][C]0.00741126270953641[/C][C]0.996294368645232[/C][/ROW]
[ROW][C]362[/C][C]0.00369002254144851[/C][C]0.00738004508289702[/C][C]0.996309977458552[/C][/ROW]
[ROW][C]363[/C][C]0.00245889630485985[/C][C]0.00491779260971971[/C][C]0.99754110369514[/C][/ROW]
[ROW][C]364[/C][C]0.00248905407667556[/C][C]0.00497810815335112[/C][C]0.997510945923324[/C][/ROW]
[ROW][C]365[/C][C]0.0133808092765861[/C][C]0.0267616185531722[/C][C]0.986619190723414[/C][/ROW]
[ROW][C]366[/C][C]0.0204044080380958[/C][C]0.0408088160761916[/C][C]0.979595591961904[/C][/ROW]
[ROW][C]367[/C][C]0.025101095556014[/C][C]0.0502021911120279[/C][C]0.974898904443986[/C][/ROW]
[ROW][C]368[/C][C]0.0333008061112762[/C][C]0.0666016122225524[/C][C]0.966699193888724[/C][/ROW]
[ROW][C]369[/C][C]0.0501756429375899[/C][C]0.10035128587518[/C][C]0.94982435706241[/C][/ROW]
[ROW][C]370[/C][C]0.0391717248498435[/C][C]0.078343449699687[/C][C]0.960828275150156[/C][/ROW]
[ROW][C]371[/C][C]0.0471739177148151[/C][C]0.0943478354296301[/C][C]0.952826082285185[/C][/ROW]
[ROW][C]372[/C][C]0.137971525271822[/C][C]0.275943050543644[/C][C]0.862028474728178[/C][/ROW]
[ROW][C]373[/C][C]0.101298247838741[/C][C]0.202596495677481[/C][C]0.89870175216126[/C][/ROW]
[ROW][C]374[/C][C]0.0737909447539523[/C][C]0.147581889507905[/C][C]0.926209055246048[/C][/ROW]
[ROW][C]375[/C][C]0.0582277959752248[/C][C]0.11645559195045[/C][C]0.941772204024775[/C][/ROW]
[ROW][C]376[/C][C]0.205736118209017[/C][C]0.411472236418034[/C][C]0.794263881790983[/C][/ROW]
[ROW][C]377[/C][C]0.192904438555374[/C][C]0.385808877110747[/C][C]0.807095561444626[/C][/ROW]
[ROW][C]378[/C][C]0.266626831271754[/C][C]0.533253662543508[/C][C]0.733373168728246[/C][/ROW]
[ROW][C]379[/C][C]0.274161345560689[/C][C]0.548322691121379[/C][C]0.72583865443931[/C][/ROW]
[ROW][C]380[/C][C]0.2410894177507[/C][C]0.4821788355014[/C][C]0.7589105822493[/C][/ROW]
[ROW][C]381[/C][C]0.175433822303512[/C][C]0.350867644607023[/C][C]0.824566177696488[/C][/ROW]
[ROW][C]382[/C][C]0.216843471650891[/C][C]0.433686943301781[/C][C]0.78315652834911[/C][/ROW]
[ROW][C]383[/C][C]0.136692022525004[/C][C]0.273384045050007[/C][C]0.863307977474996[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117208&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117208&T=5

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.1300579852543090.2601159705086190.86994201474569
100.06008056448771290.1201611289754260.939919435512287
110.02223759162748350.04447518325496710.977762408372516
120.03229440864080540.06458881728161080.967705591359195
130.01641946136269070.03283892272538130.98358053863731
140.006707412691228460.01341482538245690.993292587308772
150.01251727974239990.02503455948479970.9874827202576
160.005649851255634490.0112997025112690.994350148744366
170.006381472010354730.01276294402070950.993618527989645
180.005750752872969630.01150150574593930.99424924712703
190.002727690714450020.005455381428900030.99727230928555
200.001302216773816720.002604433547633450.998697783226183
210.0006747295882395150.001349459176479030.99932527041176
220.0002951742794971030.0005903485589942070.999704825720503
230.0001314922256417030.0002629844512834060.999868507774358
245.46717347902289e-050.0001093434695804580.99994532826521
253.30385966657336e-056.60771933314673e-050.999966961403334
261.43529286318126e-052.87058572636252e-050.999985647071368
274.48058575885238e-058.96117151770476e-050.999955194142411
281.94153161257431e-053.88306322514862e-050.999980584683874
294.23230618242872e-058.46461236485744e-050.999957676938176
302.01849903895264e-054.03699807790528e-050.99997981500961
310.0008906214307438050.001781242861487610.999109378569256
320.002677544385300730.005355088770601470.9973224556147
330.1609344359488290.3218688718976580.83906556405117
340.1397933479683230.2795866959366460.860206652031677
350.1157415133738370.2314830267476750.884258486626162
360.1883404846712830.3766809693425670.811659515328717
370.1543412031354110.3086824062708210.84565879686459
380.1250034934639090.2500069869278190.87499650653609
390.09914632196063530.1982926439212710.900853678039365
400.07833148812887350.1566629762577470.921668511871127
410.06530391268838680.1306078253767740.934696087311613
420.05021195266533050.1004239053306610.94978804733467
430.04852389489305370.09704778978610750.951476105106946
440.04033541533524420.08067083067048850.959664584664756
450.03067150420258740.06134300840517480.969328495797413
460.02412662418090940.04825324836181870.97587337581909
470.03181127867381450.0636225573476290.968188721326185
480.03057637648718810.06115275297437630.969423623512812
490.02360826396580330.04721652793160660.976391736034197
500.01779227689372830.03558455378745660.982207723106272
510.01337212873754280.02674425747508560.986627871262457
520.01061419450674720.02122838901349440.989385805493253
530.01167537277626760.02335074555253520.988324627223732
540.01789659946220110.03579319892440220.9821034005378
550.01481233656140130.02962467312280260.985187663438599
560.01162019625159550.0232403925031910.988379803748405
570.008773710881493430.01754742176298690.991226289118507
580.006731831536750260.01346366307350050.99326816846325
590.005012565442297760.01002513088459550.994987434557702
600.003706020657036970.007412041314073950.996293979342963
610.003320503579663090.006641007159326180.996679496420337
620.002373401501489820.004746803002979630.99762659849851
630.001683934020458130.003367868040916260.998316065979542
640.00328423499021980.006568469980439610.99671576500978
650.002480288323330560.004960576646661130.99751971167667
660.001781993514113650.00356398702822730.998218006485886
670.001269521962797850.002539043925595710.998730478037202
680.001379890433651750.00275978086730350.998620109566348
690.0009907222558822490.00198144451176450.999009277744118
700.0007907014638235930.001581402927647190.999209298536176
710.0006649774615481810.001329954923096360.999335022538452
720.0005696196189876690.001139239237975340.999430380381012
730.0005433651606648250.001086730321329650.999456634839335
740.000488794253006580.000977588506013160.999511205746993
750.000565756587466740.001131513174933480.999434243412533
760.0004287112890920440.0008574225781840870.999571288710908
770.000398059470671990.0007961189413439790.999601940529328
780.0003590212772419810.0007180425544839610.999640978722758
790.0002884451981204780.0005768903962409570.99971155480188
800.0002026473493188010.0004052946986376020.999797352650681
810.0001649265010189850.000329853002037970.99983507349898
820.0002258075708487160.0004516151416974330.999774192429151
830.0001734760121968550.0003469520243937110.999826523987803
840.0001479567311783580.0002959134623567150.999852043268822
850.0001137436030573940.0002274872061147880.999886256396943
868.81519482070292e-050.0001763038964140580.999911848051793
876.18240945030591e-050.0001236481890061180.999938175905497
884.77612291328166e-059.55224582656332e-050.999952238770867
893.33518150987324e-056.67036301974648e-050.999966648184901
902.24263689294307e-054.48527378588614e-050.99997757363107
913.1284933147858e-056.2569866295716e-050.999968715066852
922.18332913135466e-054.36665826270932e-050.999978166708686
931.74322410343387e-053.48644820686775e-050.999982567758966
941.57412773009112e-053.14825546018224e-050.9999842587227
951.42737795454578e-052.85475590909157e-050.999985726220455
961.18126269097232e-052.36252538194464e-050.99998818737309
979.4242581155718e-061.88485162311436e-050.999990575741884
986.24954248974225e-061.24990849794845e-050.99999375045751
991.67974260462905e-053.3594852092581e-050.999983202573954
1001.42485713530544e-052.84971427061088e-050.999985751428647
1011.52037634462116e-053.04075268924231e-050.999984796236554
1021.08295409717373e-052.16590819434745e-050.999989170459028
1031.18360880895458e-052.36721761790915e-050.99998816391191
1048.09562629960194e-061.61912525992039e-050.9999919043737
1057.17205020317145e-061.43441004063429e-050.999992827949797
1061.74058395158116e-053.48116790316232e-050.999982594160484
1071.22831042637065e-052.4566208527413e-050.999987716895736
1081.14201738951943e-052.28403477903885e-050.999988579826105
1098.51375144236002e-061.702750288472e-050.999991486248558
1107.29947994149277e-061.45989598829855e-050.999992700520059
1116.11744940739954e-050.0001223489881479910.999938825505926
1125.21616701577746e-050.0001043233403155490.999947838329842
1133.82282805842277e-057.64565611684553e-050.999961771719416
1140.0001930063950353490.0003860127900706980.999806993604965
1150.0001496973415122760.0002993946830245520.999850302658488
1160.0001410838251909080.0002821676503818150.99985891617481
1170.0001197618999505870.0002395237999011750.99988023810005
1189.2350003531587e-050.0001847000070631740.999907649996468
1190.000173559159755240.000347118319510480.999826440840245
1200.0001368378035729360.0002736756071458720.999863162196427
1210.0001945539114829720.0003891078229659430.999805446088517
1220.0005341981504938640.001068396300987730.999465801849506
1230.0007088702395173360.001417740479034670.999291129760483
1240.0005930020406411750.001186004081282350.99940699795936
1250.001222234863283570.002444469726567140.998777765136716
1260.002083228265606070.004166456531212130.997916771734394
1270.001638930477887910.003277860955775820.998361069522112
1280.001298757722402080.002597515444804170.998701242277598
1290.003608015467179850.007216030934359690.99639198453282
1300.002925843297821160.005851686595642320.997074156702179
1310.002392499230852320.004784998461704650.997607500769148
1320.001934198520857470.003868397041714940.998065801479143
1330.00152278611189390.00304557222378780.998477213888106
1340.001334132511920080.002668265023840170.99866586748808
1350.001080900654203190.002161801308406370.998919099345797
1360.001208229146410570.002416458292821140.99879177085359
1370.001001555497102120.002003110994204230.998998444502898
1380.0008259421330466220.001651884266093240.999174057866953
1390.000636963898434480.001273927796868960.999363036101566
1400.001332720288228050.002665440576456090.998667279711772
1410.001034232085464450.00206846417092890.998965767914536
1420.0008682794826818550.001736558965363710.999131720517318
1430.0007608737026480320.001521747405296060.999239126297352
1440.0008583803407834230.001716760681566850.999141619659217
1450.0006622292889898130.001324458577979630.99933777071101
1460.000973927532532660.001947855065065320.999026072467467
1470.001431487400148680.002862974800297360.998568512599851
1480.001125516797010570.002251033594021140.99887448320299
1490.000883532508588210.001767065017176420.999116467491412
1500.0007359833379081140.001471966675816230.999264016662092
1510.001111589717179590.002223179434359180.99888841028282
1520.0008919142159440550.001783828431888110.999108085784056
1530.0008911942094181280.001782388418836260.999108805790582
1540.0007027776532752130.001405555306550430.999297222346725
1550.0005440229392694910.001088045878538980.99945597706073
1560.0007469194543032490.00149383890860650.999253080545697
1570.0005896026074951670.001179205214990330.999410397392505
1580.0005422235312846190.001084447062569240.999457776468715
1590.0004382939286047240.0008765878572094480.999561706071395
1600.0003656886312587020.0007313772625174040.999634311368741
1610.0002774467219235120.0005548934438470240.999722553278076
1620.0002171343525485450.000434268705097090.999782865647451
1630.000256278328756810.000512556657513620.999743721671243
1640.0003000426696463840.0006000853392927690.999699957330354
1650.0002283029909740440.0004566059819480890.999771697009026
1660.0001757707914652420.0003515415829304830.999824229208535
1670.0003492100208865340.0006984200417730690.999650789979113
1680.0003012721736864740.0006025443473729490.999698727826314
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3460.03616614887647420.07233229775294850.963833851123526
3470.02828262638486250.0565652527697250.971717373615137
3480.02248831491282960.04497662982565920.97751168508717
3490.03628314884217580.07256629768435160.963716851157824
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Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1970.525333333333333NOK
5% type I error level2430.648NOK
10% type I error level2760.736NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 197 & 0.525333333333333 & NOK \tabularnewline
5% type I error level & 243 & 0.648 & NOK \tabularnewline
10% type I error level & 276 & 0.736 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117208&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]197[/C][C]0.525333333333333[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]243[/C][C]0.648[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]276[/C][C]0.736[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117208&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117208&T=6

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1970.525333333333333NOK
5% type I error level2430.648NOK
10% type I error level2760.736NOK


Figures (Output of Computation)

Figure 1
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Figure 7
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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}