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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 computationSun, 12 Dec 2010 18:38:54 +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/12/t1292179006m4kafl8s7ugzr0e.htm/, Retrieved Wed, 08 May 2024 02:52:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108606, Retrieved Wed, 08 May 2024 02:52:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
F   PD    [Multiple Regression] [] [2010-12-12 18:38:54] [6b31f806e9ccc1f74a26091056f791cb] [Current]
-   PD      [Multiple Regression] [] [2010-12-21 13:53:35] [74be16979710d4c4e7c6647856088456]
-   PD      [Multiple Regression] [] [2010-12-21 19:18:27] [de55ccbf69577500a5f46ed42a101114]
-   PD        [Multiple Regression] [] [2010-12-22 14:46:32] [de55ccbf69577500a5f46ed42a101114]
-   PD        [Multiple Regression] [] [2010-12-22 14:46:32] [de55ccbf69577500a5f46ed42a101114]
-   PD        [Multiple Regression] [] [2010-12-22 16:12:32] [de55ccbf69577500a5f46ed42a101114]
-    D          [Multiple Regression] [] [2010-12-22 18:40:51] [de55ccbf69577500a5f46ed42a101114]
Feedback Forum
2010-12-19 08:35:30 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply] 
De student stelt hier een correct regressiemodel op en ook de interpretatie is -hoewel zeer beknopt - correct. Alle belangrijke elementen ('adjusted R squared', parameter waarden bihorende P waarden en assumpties), die nodig zijn voor de interpretatie van het model werden besproken.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8	350	165	3693	11,5
8	318	150	3436	11
8	302	140	3449	10,5
8	429	198	4341	10
8	440	215	4312	8,5
8	455	225	4425	10
8	383	170	3563	10
8	340	160	3609	8
8	455	225	3086	10
4	113	95	2372	15
6	199	97	2774	15,5
4	97	46	1835	20,5
4	110	87	2672	17,5
4	104	95	2375	17,5
4	121	113	2234	12,5
8	360	215	4615	14
8	307	200	4376	15
8	304	193	4732	18,5
4	97	88	2130	14,5
4	113	95	2228	14
6	250	100	3329	15,5
6	232	100	3288	15,5
8	350	165	4209	12
8	318	150	4096	13
8	400	170	4746	12
8	400	175	5140	12
4	140	72	2408	19
6	250	100	3282	15
4	122	86	2220	14
4	116	90	2123	14
4	88	76	2065	14,5
4	71	65	1773	19
4	97	60	1834	19
4	91	70	1955	20,5
4	97,5	80	2126	17
4	122	86	2226	16,5
8	350	165	4274	12
8	318	150	4135	13,5
8	351	153	4129	13
8	429	208	4633	11
8	350	155	4502	13,5
8	400	190	4422	12,5
3	70	97	2330	13,5
8	307	130	4098	14
8	302	140	4294	16
4	121	112	2933	14,5
4	121	76	2511	18
4	122	86	2395	16
4	120	97	2506	14,5
4	98	80	2164	15
8	350	175	4100	13
8	304	150	3672	11,5
8	302	137	4042	14,5
8	318	150	3777	12,5
8	400	150	4464	12
8	351	158	4363	13
8	440	215	4735	11
8	455	225	4951	11
6	225	105	3121	16,5
6	250	100	3278	18
6	250	88	3021	16,5
6	198	95	2904	16
8	400	150	4997	14
8	350	180	4499	12,5
6	232	100	2789	15
4	140	72	2401	19,5
4	108	94	2379	16,5
4	122	85	2310	18,5
6	155	107	2472	14
8	350	145	4082	13
8	400	230	4278	9,5
4	116	75	2158	15,5
4	114	91	2582	14
8	318	150	3399	11
4	121	110	2660	14
8	350	180	3664	11
6	198	95	3102	16,5
6	232	100	2901	16
4	122	80	2451	16,5
4	71	65	1836	21
6	250	100	3781	17
6	258	110	3632	18
8	302	140	4141	14
8	350	150	4699	14,5
8	302	140	4638	16
8	304	150	4257	15,5
4	79	67	1963	15,5
4	97	78	2300	14,5
4	83	61	2003	19
4	90	75	2125	14,5
4	116	75	2246	14
4	120	97	2489	15
4	79	67	2000	16
6	225	95	3264	16
6	250	72	3158	19,5
8	400	170	4668	11,5
8	350	145	4440	14
8	351	148	4657	13,5
6	231	110	3907	21
6	258	110	3730	19
6	225	95	3785	19
8	262	110	3221	13,5
8	302	129	3169	12
4	140	83	2639	17
6	232	100	2914	16
4	134	96	2702	13,5
4	90	71	2223	16,5
6	171	97	2984	14,5
4	115	95	2694	15
4	120	88	2957	17
4	121	115	2671	13,5
4	91	53	1795	17,5
4	116	81	2220	16,9
4	140	92	2572	14,9
4	101	83	2202	15,3
8	305	140	4215	13
8	304	120	3962	13,9
8	351	152	4215	12,8
6	250	105	3353	14,5
6	200	81	3012	17,6
4	85	52	2035	22,2
4	98	60	2164	22,1
6	225	100	3651	17,7
6	250	110	3645	16,2
6	258	95	3193	17,8
4	85	70	1990	17
4	97	75	2155	16,4
4	130	102	3150	15,7
8	318	150	3940	13,2
6	168	120	3820	16,7
8	350	180	4380	12,1
8	302	130	3870	15
8	318	150	3755	14
4	111	80	2155	14,8
4	79	58	1825	18,6
4	85	70	1945	16,8
8	305	145	3880	12,5
8	318	145	4140	13,7
6	231	105	3425	16,9
6	225	100	3630	17,7
8	400	180	4220	11,1
8	350	170	4165	11,4
8	351	149	4335	14,5
4	97	78	1940	14,5
4	97	75	2265	18,2
4	140	89	2755	15,8
4	98	83	2075	15,9
4	97	67	1985	16,4
6	146	97	2815	14,5
4	121	110	2600	12,8
4	90	48	1985	21,5
4	98	66	1800	14,4
4	85	70	2070	18,6
8	318	140	3735	13,2
8	302	139	3570	12,8
6	200	95	3155	18,2
6	200	85	2965	15,8
6	225	100	3430	17,2
6	232	90	3210	17,2
6	200	85	3070	16,7
6	225	110	3620	18,7
8	305	145	3425	13,2
6	231	165	3445	13,4
8	318	140	4080	13,7
4	98	68	2155	16,5
4	119	97	2300	14,7
4	105	75	2230	14,5
4	151	85	2855	17,6
5	131	103	2830	15,9
6	163	125	3140	13,6
6	163	133	3410	15,8
4	89	71	1990	14,9
4	98	68	2135	16,6
6	200	85	2990	18,2
4	140	88	2890	17,3
6	225	110	3360	16,6
8	305	130	3840	15,4
8	351	138	3955	13,2
8	318	135	3830	15,2
8	351	142	4054	14,3
8	267	125	3605	15
4	89	71	1925	14
4	86	65	1975	15,2
4	121	80	2670	15
4	141	71	3190	24,8
8	260	90	3420	22,2
4	105	70	2150	14,9
4	85	65	2020	19,2
4	151	90	2670	16
6	173	115	2595	11,3
4	151	90	2556	13,2
4	98	76	2144	14,7
4	98	70	2120	15,5
4	86	65	2019	16,4
4	140	88	2870	18,1
4	151	90	3003	20,1
4	97	78	2188	15,8
4	134	90	2711	15,5
4	119	92	2434	15
4	108	75	2265	15,2
4	156	105	2800	14,4
4	85	65	2110	19,2
5	121	67	2950	19,9
4	91	67	1850	13,8
4	89	62	1845	15,3
4	122	88	2500	15,1
4	135	84	2490	15,7
4	151	84	2635	16,4
6	173	110	2725	12,6
4	135	84	2385	12,9
4	86	64	1875	16,4
4	81	60	1760	16,1
4	85	65	1975	19,4
4	89	62	2050	17,3
4	105	63	2215	14,9
4	98	65	2045	16,2
4	105	74	2190	14,2
4	119	100	2615	14,8
4	141	80	3230	20,4
6	146	120	2930	13,8
6	231	110	3415	15,8
6	200	88	3060	17,1
6	225	85	3465	16,6
4	112	88	2640	18,6
4	112	88	2395	18
4	135	84	2525	16
4	151	90	2735	18
4	105	74	1980	15,3
4	91	68	1970	17,6
4	105	63	2125	14,7
4	120	88	2160	14,5
4	107	75	2205	14,5
4	91	67	1965	15,7
6	181	110	2945	16,4
6	262	85	3015	17
4	144	96	2665	13,9
4	151	90	2950	17,3
4	140	86	2790	15,6
4	135	84	2295	11,6
4	120	79	2625	18,6

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 13 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108606&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108606&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108606&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 time13 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






Multiple Linear Regression - Estimated Regression Equation
acceleration [t] = + 17.2587244715863 -0.184751272787248cylinders[t] -0.00730185636427856engine.displacement[t] -0.0732603848551417horsepower[t] + 0.00278578297645537weight[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
acceleration
[t] =  +  17.2587244715863 -0.184751272787248cylinders[t] -0.00730185636427856engine.displacement[t] -0.0732603848551417horsepower[t] +  0.00278578297645537weight[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108606&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]acceleration
[t] =  +  17.2587244715863 -0.184751272787248cylinders[t] -0.00730185636427856engine.displacement[t] -0.0732603848551417horsepower[t] +  0.00278578297645537weight[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108606&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108606&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
acceleration [t] = + 17.2587244715863 -0.184751272787248cylinders[t] -0.00730185636427856engine.displacement[t] -0.0732603848551417horsepower[t] + 0.00278578297645537weight[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)17.25872447158630.76421222.583700
cylinders-0.1847512727872480.206326-0.89540.3714720.185736
engine.displacement-0.007301856364278560.004611-1.58350.1146530.057326
horsepower-0.07326038485514170.006727-10.891100
weight0.002785782976455370.000367.747500

\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) & 17.2587244715863 & 0.764212 & 22.5837 & 0 & 0 \tabularnewline
cylinders & -0.184751272787248 & 0.206326 & -0.8954 & 0.371472 & 0.185736 \tabularnewline
engine.displacement & -0.00730185636427856 & 0.004611 & -1.5835 & 0.114653 & 0.057326 \tabularnewline
horsepower & -0.0732603848551417 & 0.006727 & -10.8911 & 0 & 0 \tabularnewline
weight & 0.00278578297645537 & 0.00036 & 7.7475 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108606&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]17.2587244715863[/C][C]0.764212[/C][C]22.5837[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]cylinders[/C][C]-0.184751272787248[/C][C]0.206326[/C][C]-0.8954[/C][C]0.371472[/C][C]0.185736[/C][/ROW]
[ROW][C]engine.displacement[/C][C]-0.00730185636427856[/C][C]0.004611[/C][C]-1.5835[/C][C]0.114653[/C][C]0.057326[/C][/ROW]
[ROW][C]horsepower[/C][C]-0.0732603848551417[/C][C]0.006727[/C][C]-10.8911[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]weight[/C][C]0.00278578297645537[/C][C]0.00036[/C][C]7.7475[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108606&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108606&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)17.25872447158630.76421222.583700
cylinders-0.1847512727872480.206326-0.89540.3714720.185736
engine.displacement-0.007301856364278560.004611-1.58350.1146530.057326
horsepower-0.07326038485514170.006727-10.891100
weight0.002785782976455370.000367.747500






Multiple Linear Regression - Regression Statistics
Multiple R0.768262915498146
R-squared0.590227907329712
Adjusted R-squared0.583253063199153
F-TEST (value)84.6223795516537
F-TEST (DF numerator)4
F-TEST (DF denominator)235
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.70721080842101
Sum Squared Residuals684.923654931535

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.768262915498146 \tabularnewline
R-squared & 0.590227907329712 \tabularnewline
Adjusted R-squared & 0.583253063199153 \tabularnewline
F-TEST (value) & 84.6223795516537 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 235 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.70721080842101 \tabularnewline
Sum Squared Residuals & 684.923654931535 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108606&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.768262915498146[/C][/ROW]
[ROW][C]R-squared[/C][C]0.590227907329712[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.583253063199153[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]84.6223795516537[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]235[/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]1.70721080842101[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]684.923654931535[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108606&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108606&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 R0.768262915498146
R-squared0.590227907329712
Adjusted R-squared0.583253063199153
F-TEST (value)84.6223795516537
F-TEST (DF numerator)4
F-TEST (DF denominator)235
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.70721080842101
Sum Squared Residuals684.923654931535






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
111.511.42499759274230.075002407257699
21112.0416165442772-1.0416165442772
310.512.9272652733510-2.42726527335098
41010.2357456084876-0.235745608487573
58.58.82921093962588-0.329210939625876
6108.301872721949741.69812727805026
71010.4555826215061-0.455582621506065
8811.6303123106384-3.63031231063841
9104.5717093164765.42829068352400
101515.3427502701875-0.342750270187548
1115.515.31865206410990.181347935890127
1220.517.55337337156142.94662662843859
1317.516.78647381105810.713526188941872
1417.515.41682432639542.08317567360458
1512.513.5812104411299-1.08121044112993
161410.25745169063413.74254830936585
171511.07755371939523.9224462806048
1818.512.60402072209215.89597927790786
1914.515.2982431856998-0.798243185699798
201414.9415975215780-0.941597521577975
2115.516.2725857868990-0.772585786898968
2215.516.2898020994213-0.789802099421313
231212.8624616085931-0.862461608593136
241313.8802333087377-0.880233308737719
251213.6270323244600-1.62703232446003
261214.3583288929077-2.35832889290774
271916.93087718717272.06912281282732
281516.1416539870056-1.14165398700557
291415.5129380141841-1.5129380141841
301414.9934866642330-0.993486664233034
3114.516.0620086177704-1.56200861777041
321916.17855578024472.82144421975527
331916.52494220061302.47505779938702
3420.516.17322923039834.32677076960167
351715.86953220445301.13046779554703
3616.515.52965271204280.970347287957169
371213.0435375020627-1.04353750206273
3813.513.9888788448195-0.488878844819479
391313.5114217323741-0.511421732374127
401110.31659038906110.68340961093889
4113.514.4112998692460-0.911299869245975
4212.511.25923094298571.24076905701434
4313.515.5779577119174-2.07795771191736
441415.4313329918005-1.43133299180053
451615.28125188845580.718748111544243
4614.515.6017331265274-1.10173312652737
471817.06350656524830.936493434751694
481616.0004500350638-0.000450035063788784
4914.515.5184114247723-1.01841142477233
501515.9717410293761-0.971741029376135
511311.82620741560811.17379258439192
5211.512.8012873158205-1.30128731582054
5314.514.7990157329544-0.299015732954429
5412.512.9915685392485-0.491568539248457
551214.3066492222024-2.30664922220245
561313.7969930245890-0.796993024588975
571110.00759713866650.992402861333498
58119.767194567565271.23280543243473
5916.515.50938741262750.99061258737249
601816.13051085509971.86948914490026
6116.516.29368924841240.206310751587585
621615.83462647712360.165373522876367
631415.7914715486532-1.79147154865316
6412.512.5714328989381-0.0714328989380675
651514.89969639417010.100303605829915
6619.516.91137670633752.58862329366251
6716.515.47202041769931.02797958230073
6818.515.83691886692022.66308113307978
691414.0660234366972-0.0660234366971941
701313.9738748676861-0.973874867686137
719.57.927662800170421.57233719982958
7215.516.1898948412361-0.689894841236096
731416.2135043782995-2.21350437829946
741111.9385425741483-0.938542574148328
751414.9877351436653-0.98773514366534
761110.24530411359780.754695886402165
7716.516.38621150646180.113788493538204
781615.21170408753310.788295912466914
7916.516.5960161908761-0.0960161908761392
802116.35406010776144.64593989223858
811717.5317596922568-0.531759692256794
821816.32565932929931.6743406707007
831414.8550270930581-0.855027093058085
8414.515.3264010398834-0.82640103988339
851616.2395612323564-0.239561232356403
8615.514.43097035704691.06902964295307
8715.516.5029189251467-1.00291892514674
8814.516.5044301402486-2.00443014024863
891917.02470512787871.97529487212131
9014.516.2878122684843-1.78781226848431
911416.4350437431642-2.43504374316417
921515.4710531141726-0.471053114172592
931616.6059928952756-0.60599289527559
941616.6403582268120-0.640358226812043
9519.517.84750767386911.65249232613093
9611.513.4097412522965-1.90974125229651
971414.9711851732572-0.971185173257158
9813.515.3486170682183-1.84861706821827
992117.28889976966003.71110023033995
1001916.59866606099192.40133393900808
1011918.09175115754530.90824884245471
10213.514.7819925549445-1.28199255494454
1031212.9531102733500-0.953110273350026
1041716.76852882132730.231471178672692
1051615.2479192662270.752080733772994
10613.516.0354592839128-2.53545928391283
10716.516.8538605395975-0.353860539597506
10814.516.1081184673653-1.60811846736530
1091516.2251686758776-1.22516867587762
1101717.4341430108500-0.434143010849979
11113.514.6520768321306-1.15207683213064
11217.516.97293049670290.527069503297121
11316.915.92305107664550.97694892335452
11414.915.9225378982085-1.02253789820852
11515.315.8359140588232-0.535914058823178
1161315.0392694642229-2.03926946422295
11713.915.8069759246468-1.90697592464685
11812.813.8242594532044-1.02425945320443
11914.515.9731426540582-1.47314265405819
12017.617.14653271382420.453467286175763
12122.217.75858993409304.44141006590702
12222.117.43694872647904.66305127352103
12317.717.35215431442460.347845685575438
12416.216.4202893589074-0.220289358907449
12517.816.20160637546251.59839362453748
1261716.31454277275990.68545722724006
12716.416.32027276322800.0797272367719747
12815.716.8731351736911-1.17313517369110
12913.213.4456511644107-0.245651164410682
13016.716.7739497531066-0.0739497531065677
13112.112.2399247247399-0.139924724739879
1321514.83268375499010.167316245009903
1331412.93028131376641.06971868623356
13414.815.8517448498524-1.05174484985241
13518.616.77782433809221.82217566190783
13616.816.18918253881940.610817461180553
13712.513.7397302428347-1.23973024283469
13813.714.3691096839775-0.669109683977464
13916.916.31245429928430.58754570071573
14017.717.2936528719190.406347128081
14111.111.4291066302931-0.32910663029309
14211.412.3735852333534-0.97358523335339
14314.514.37833456494450.121665435055500
14414.515.5015482687247-1.00154826872469
14518.216.62670889063811.57329110936189
14615.816.6521173374653-0.85211733746528
14715.915.50402518990620.395974810093818
14816.416.4327727360717-0.0327727360717458
14914.515.8198675534513-1.31986755345131
15012.814.8205881650780-2.02058816507802
15121.517.87583304286943.62416695713061
15214.415.9833614139184-1.58336141391836
15318.616.53740541087642.06259458912363
15413.213.6071695027887-0.407169502788748
15512.813.3376053983572-0.537605398357211
15618.216.51925429148541.68074570851463
15715.816.7225593745103-0.922559374510269
15817.216.73649627662790.463503723372074
15917.216.80511487580920.394885124190789
16016.717.0150665870381-0.315066587038084
16118.716.53319119360302.16680880639697
16213.212.47219898854750.727801011452502
16313.411.97254686750491.42745313249512
16413.714.5682646296658-0.86826462966585
16516.516.8257936008497-0.325793600849737
16614.714.9518419879868-0.251841987986807
16714.516.4707916355479-1.97079163554795
16817.617.14341675452430.456583245475682
16915.915.71637110721870.183628892781287
17013.614.5498246866626-0.949824686662602
17115.814.71590301146441.08409698853558
17214.916.2120749624477-1.31207496244768
17316.616.7700779413206-0.170077941320628
17418.216.79220394892171.40779605107835
17517.317.10145842414190.198541575858103
17616.615.80888761972460.791112380275368
17715.414.72720469660360.672795303396401
17813.214.1256012672980-0.925601267298019
17915.214.23812080982770.961879190172283
18014.314.10835224254650.191647757453468
1811514.71631816325490.283681836745116
1821416.0309990689781-2.03099906897808
18315.216.6317560960245-1.43175609602454
1841517.2134045190841-2.21340451908414
18524.819.17531800325165.62468199674836
18622.216.81617477709055.38382522290945
18714.916.6142309217072-1.71423092170723
18819.216.76441818632932.43558181367069
1891616.2617449796044-0.261744979604369
19011.313.6911582494031-2.39115824940305
19113.215.9441657202885-2.74416572028846
19214.716.2090669092676-1.50906690926760
19315.516.5817704269635-1.08177042696352
19416.416.7543305469886-0.354330546988576
19518.117.04574276461281.05425723538721
19620.117.1894107107642.91058928923600
19715.816.1924224468856-0.392422446885625
19815.516.5000936398318-1.00009363983178
1991515.6914388311075-0.691438831107534
20015.216.5463884706311-1.34638847063105
20114.415.4884817118950-1.08848171189505
20219.217.01513865421032.18486134578971
20319.918.76105748282121.13894251717876
20413.816.1005031724359-2.30050317243594
20515.316.4674798945579-1.16747989455793
20615.116.1464364778813-1.04643647788132
20715.716.3166960548017-0.616696054801711
20816.416.6038048845593-0.203804884559282
20912.614.4196119606180-1.81961196061796
21012.916.0241888422739-3.12418884227390
21116.416.4264381832341-0.0264381832341449
21216.116.4356239621837-0.335623962183735
21319.416.63905795238882.76094204761118
21417.317.03856540473130.261434595268720
21514.917.3081295091628-2.40812950916282
21616.216.7391386280051-0.539138628005072
21714.216.4326207013449-2.23262070134488
21814.815.6095824710048-0.809582471004822
21920.418.62740585861361.77259414138642
22013.814.4552437440754-0.655243744075418
22115.815.918294545244-0.118294545244007
22217.116.76742760270810.332572397291897
22316.617.932904453631-1.33290445363099
22418.616.60946465822791.99053534177214
2251815.92694782899632.07305217100371
2261616.4141984589776-0.414198458977648
2271816.44282087307401.55717912692603
22815.315.8476062762892-0.547606276289246
22917.616.36153674475541.23846325524456
23014.717.0574090412818-2.35740904128183
23114.515.2138739786151-0.713873978615051
23214.516.386543348408-1.88654334840801
23315.716.4208682147283-0.72086821472831
23416.414.97406936452391.42593063547608
2351716.40913342874780.590866571252236
23613.915.8593667501412-1.95936675014119
23717.317.04176421301190.258235786988129
23815.616.9694008962066-1.36940089620664
23911.615.7734683743929-4.17346837439291
24018.617.16860652636311.43139347363693

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 11.5 & 11.4249975927423 & 0.075002407257699 \tabularnewline
2 & 11 & 12.0416165442772 & -1.0416165442772 \tabularnewline
3 & 10.5 & 12.9272652733510 & -2.42726527335098 \tabularnewline
4 & 10 & 10.2357456084876 & -0.235745608487573 \tabularnewline
5 & 8.5 & 8.82921093962588 & -0.329210939625876 \tabularnewline
6 & 10 & 8.30187272194974 & 1.69812727805026 \tabularnewline
7 & 10 & 10.4555826215061 & -0.455582621506065 \tabularnewline
8 & 8 & 11.6303123106384 & -3.63031231063841 \tabularnewline
9 & 10 & 4.571709316476 & 5.42829068352400 \tabularnewline
10 & 15 & 15.3427502701875 & -0.342750270187548 \tabularnewline
11 & 15.5 & 15.3186520641099 & 0.181347935890127 \tabularnewline
12 & 20.5 & 17.5533733715614 & 2.94662662843859 \tabularnewline
13 & 17.5 & 16.7864738110581 & 0.713526188941872 \tabularnewline
14 & 17.5 & 15.4168243263954 & 2.08317567360458 \tabularnewline
15 & 12.5 & 13.5812104411299 & -1.08121044112993 \tabularnewline
16 & 14 & 10.2574516906341 & 3.74254830936585 \tabularnewline
17 & 15 & 11.0775537193952 & 3.9224462806048 \tabularnewline
18 & 18.5 & 12.6040207220921 & 5.89597927790786 \tabularnewline
19 & 14.5 & 15.2982431856998 & -0.798243185699798 \tabularnewline
20 & 14 & 14.9415975215780 & -0.941597521577975 \tabularnewline
21 & 15.5 & 16.2725857868990 & -0.772585786898968 \tabularnewline
22 & 15.5 & 16.2898020994213 & -0.789802099421313 \tabularnewline
23 & 12 & 12.8624616085931 & -0.862461608593136 \tabularnewline
24 & 13 & 13.8802333087377 & -0.880233308737719 \tabularnewline
25 & 12 & 13.6270323244600 & -1.62703232446003 \tabularnewline
26 & 12 & 14.3583288929077 & -2.35832889290774 \tabularnewline
27 & 19 & 16.9308771871727 & 2.06912281282732 \tabularnewline
28 & 15 & 16.1416539870056 & -1.14165398700557 \tabularnewline
29 & 14 & 15.5129380141841 & -1.5129380141841 \tabularnewline
30 & 14 & 14.9934866642330 & -0.993486664233034 \tabularnewline
31 & 14.5 & 16.0620086177704 & -1.56200861777041 \tabularnewline
32 & 19 & 16.1785557802447 & 2.82144421975527 \tabularnewline
33 & 19 & 16.5249422006130 & 2.47505779938702 \tabularnewline
34 & 20.5 & 16.1732292303983 & 4.32677076960167 \tabularnewline
35 & 17 & 15.8695322044530 & 1.13046779554703 \tabularnewline
36 & 16.5 & 15.5296527120428 & 0.970347287957169 \tabularnewline
37 & 12 & 13.0435375020627 & -1.04353750206273 \tabularnewline
38 & 13.5 & 13.9888788448195 & -0.488878844819479 \tabularnewline
39 & 13 & 13.5114217323741 & -0.511421732374127 \tabularnewline
40 & 11 & 10.3165903890611 & 0.68340961093889 \tabularnewline
41 & 13.5 & 14.4112998692460 & -0.911299869245975 \tabularnewline
42 & 12.5 & 11.2592309429857 & 1.24076905701434 \tabularnewline
43 & 13.5 & 15.5779577119174 & -2.07795771191736 \tabularnewline
44 & 14 & 15.4313329918005 & -1.43133299180053 \tabularnewline
45 & 16 & 15.2812518884558 & 0.718748111544243 \tabularnewline
46 & 14.5 & 15.6017331265274 & -1.10173312652737 \tabularnewline
47 & 18 & 17.0635065652483 & 0.936493434751694 \tabularnewline
48 & 16 & 16.0004500350638 & -0.000450035063788784 \tabularnewline
49 & 14.5 & 15.5184114247723 & -1.01841142477233 \tabularnewline
50 & 15 & 15.9717410293761 & -0.971741029376135 \tabularnewline
51 & 13 & 11.8262074156081 & 1.17379258439192 \tabularnewline
52 & 11.5 & 12.8012873158205 & -1.30128731582054 \tabularnewline
53 & 14.5 & 14.7990157329544 & -0.299015732954429 \tabularnewline
54 & 12.5 & 12.9915685392485 & -0.491568539248457 \tabularnewline
55 & 12 & 14.3066492222024 & -2.30664922220245 \tabularnewline
56 & 13 & 13.7969930245890 & -0.796993024588975 \tabularnewline
57 & 11 & 10.0075971386665 & 0.992402861333498 \tabularnewline
58 & 11 & 9.76719456756527 & 1.23280543243473 \tabularnewline
59 & 16.5 & 15.5093874126275 & 0.99061258737249 \tabularnewline
60 & 18 & 16.1305108550997 & 1.86948914490026 \tabularnewline
61 & 16.5 & 16.2936892484124 & 0.206310751587585 \tabularnewline
62 & 16 & 15.8346264771236 & 0.165373522876367 \tabularnewline
63 & 14 & 15.7914715486532 & -1.79147154865316 \tabularnewline
64 & 12.5 & 12.5714328989381 & -0.0714328989380675 \tabularnewline
65 & 15 & 14.8996963941701 & 0.100303605829915 \tabularnewline
66 & 19.5 & 16.9113767063375 & 2.58862329366251 \tabularnewline
67 & 16.5 & 15.4720204176993 & 1.02797958230073 \tabularnewline
68 & 18.5 & 15.8369188669202 & 2.66308113307978 \tabularnewline
69 & 14 & 14.0660234366972 & -0.0660234366971941 \tabularnewline
70 & 13 & 13.9738748676861 & -0.973874867686137 \tabularnewline
71 & 9.5 & 7.92766280017042 & 1.57233719982958 \tabularnewline
72 & 15.5 & 16.1898948412361 & -0.689894841236096 \tabularnewline
73 & 14 & 16.2135043782995 & -2.21350437829946 \tabularnewline
74 & 11 & 11.9385425741483 & -0.938542574148328 \tabularnewline
75 & 14 & 14.9877351436653 & -0.98773514366534 \tabularnewline
76 & 11 & 10.2453041135978 & 0.754695886402165 \tabularnewline
77 & 16.5 & 16.3862115064618 & 0.113788493538204 \tabularnewline
78 & 16 & 15.2117040875331 & 0.788295912466914 \tabularnewline
79 & 16.5 & 16.5960161908761 & -0.0960161908761392 \tabularnewline
80 & 21 & 16.3540601077614 & 4.64593989223858 \tabularnewline
81 & 17 & 17.5317596922568 & -0.531759692256794 \tabularnewline
82 & 18 & 16.3256593292993 & 1.6743406707007 \tabularnewline
83 & 14 & 14.8550270930581 & -0.855027093058085 \tabularnewline
84 & 14.5 & 15.3264010398834 & -0.82640103988339 \tabularnewline
85 & 16 & 16.2395612323564 & -0.239561232356403 \tabularnewline
86 & 15.5 & 14.4309703570469 & 1.06902964295307 \tabularnewline
87 & 15.5 & 16.5029189251467 & -1.00291892514674 \tabularnewline
88 & 14.5 & 16.5044301402486 & -2.00443014024863 \tabularnewline
89 & 19 & 17.0247051278787 & 1.97529487212131 \tabularnewline
90 & 14.5 & 16.2878122684843 & -1.78781226848431 \tabularnewline
91 & 14 & 16.4350437431642 & -2.43504374316417 \tabularnewline
92 & 15 & 15.4710531141726 & -0.471053114172592 \tabularnewline
93 & 16 & 16.6059928952756 & -0.60599289527559 \tabularnewline
94 & 16 & 16.6403582268120 & -0.640358226812043 \tabularnewline
95 & 19.5 & 17.8475076738691 & 1.65249232613093 \tabularnewline
96 & 11.5 & 13.4097412522965 & -1.90974125229651 \tabularnewline
97 & 14 & 14.9711851732572 & -0.971185173257158 \tabularnewline
98 & 13.5 & 15.3486170682183 & -1.84861706821827 \tabularnewline
99 & 21 & 17.2888997696600 & 3.71110023033995 \tabularnewline
100 & 19 & 16.5986660609919 & 2.40133393900808 \tabularnewline
101 & 19 & 18.0917511575453 & 0.90824884245471 \tabularnewline
102 & 13.5 & 14.7819925549445 & -1.28199255494454 \tabularnewline
103 & 12 & 12.9531102733500 & -0.953110273350026 \tabularnewline
104 & 17 & 16.7685288213273 & 0.231471178672692 \tabularnewline
105 & 16 & 15.247919266227 & 0.752080733772994 \tabularnewline
106 & 13.5 & 16.0354592839128 & -2.53545928391283 \tabularnewline
107 & 16.5 & 16.8538605395975 & -0.353860539597506 \tabularnewline
108 & 14.5 & 16.1081184673653 & -1.60811846736530 \tabularnewline
109 & 15 & 16.2251686758776 & -1.22516867587762 \tabularnewline
110 & 17 & 17.4341430108500 & -0.434143010849979 \tabularnewline
111 & 13.5 & 14.6520768321306 & -1.15207683213064 \tabularnewline
112 & 17.5 & 16.9729304967029 & 0.527069503297121 \tabularnewline
113 & 16.9 & 15.9230510766455 & 0.97694892335452 \tabularnewline
114 & 14.9 & 15.9225378982085 & -1.02253789820852 \tabularnewline
115 & 15.3 & 15.8359140588232 & -0.535914058823178 \tabularnewline
116 & 13 & 15.0392694642229 & -2.03926946422295 \tabularnewline
117 & 13.9 & 15.8069759246468 & -1.90697592464685 \tabularnewline
118 & 12.8 & 13.8242594532044 & -1.02425945320443 \tabularnewline
119 & 14.5 & 15.9731426540582 & -1.47314265405819 \tabularnewline
120 & 17.6 & 17.1465327138242 & 0.453467286175763 \tabularnewline
121 & 22.2 & 17.7585899340930 & 4.44141006590702 \tabularnewline
122 & 22.1 & 17.4369487264790 & 4.66305127352103 \tabularnewline
123 & 17.7 & 17.3521543144246 & 0.347845685575438 \tabularnewline
124 & 16.2 & 16.4202893589074 & -0.220289358907449 \tabularnewline
125 & 17.8 & 16.2016063754625 & 1.59839362453748 \tabularnewline
126 & 17 & 16.3145427727599 & 0.68545722724006 \tabularnewline
127 & 16.4 & 16.3202727632280 & 0.0797272367719747 \tabularnewline
128 & 15.7 & 16.8731351736911 & -1.17313517369110 \tabularnewline
129 & 13.2 & 13.4456511644107 & -0.245651164410682 \tabularnewline
130 & 16.7 & 16.7739497531066 & -0.0739497531065677 \tabularnewline
131 & 12.1 & 12.2399247247399 & -0.139924724739879 \tabularnewline
132 & 15 & 14.8326837549901 & 0.167316245009903 \tabularnewline
133 & 14 & 12.9302813137664 & 1.06971868623356 \tabularnewline
134 & 14.8 & 15.8517448498524 & -1.05174484985241 \tabularnewline
135 & 18.6 & 16.7778243380922 & 1.82217566190783 \tabularnewline
136 & 16.8 & 16.1891825388194 & 0.610817461180553 \tabularnewline
137 & 12.5 & 13.7397302428347 & -1.23973024283469 \tabularnewline
138 & 13.7 & 14.3691096839775 & -0.669109683977464 \tabularnewline
139 & 16.9 & 16.3124542992843 & 0.58754570071573 \tabularnewline
140 & 17.7 & 17.293652871919 & 0.406347128081 \tabularnewline
141 & 11.1 & 11.4291066302931 & -0.32910663029309 \tabularnewline
142 & 11.4 & 12.3735852333534 & -0.97358523335339 \tabularnewline
143 & 14.5 & 14.3783345649445 & 0.121665435055500 \tabularnewline
144 & 14.5 & 15.5015482687247 & -1.00154826872469 \tabularnewline
145 & 18.2 & 16.6267088906381 & 1.57329110936189 \tabularnewline
146 & 15.8 & 16.6521173374653 & -0.85211733746528 \tabularnewline
147 & 15.9 & 15.5040251899062 & 0.395974810093818 \tabularnewline
148 & 16.4 & 16.4327727360717 & -0.0327727360717458 \tabularnewline
149 & 14.5 & 15.8198675534513 & -1.31986755345131 \tabularnewline
150 & 12.8 & 14.8205881650780 & -2.02058816507802 \tabularnewline
151 & 21.5 & 17.8758330428694 & 3.62416695713061 \tabularnewline
152 & 14.4 & 15.9833614139184 & -1.58336141391836 \tabularnewline
153 & 18.6 & 16.5374054108764 & 2.06259458912363 \tabularnewline
154 & 13.2 & 13.6071695027887 & -0.407169502788748 \tabularnewline
155 & 12.8 & 13.3376053983572 & -0.537605398357211 \tabularnewline
156 & 18.2 & 16.5192542914854 & 1.68074570851463 \tabularnewline
157 & 15.8 & 16.7225593745103 & -0.922559374510269 \tabularnewline
158 & 17.2 & 16.7364962766279 & 0.463503723372074 \tabularnewline
159 & 17.2 & 16.8051148758092 & 0.394885124190789 \tabularnewline
160 & 16.7 & 17.0150665870381 & -0.315066587038084 \tabularnewline
161 & 18.7 & 16.5331911936030 & 2.16680880639697 \tabularnewline
162 & 13.2 & 12.4721989885475 & 0.727801011452502 \tabularnewline
163 & 13.4 & 11.9725468675049 & 1.42745313249512 \tabularnewline
164 & 13.7 & 14.5682646296658 & -0.86826462966585 \tabularnewline
165 & 16.5 & 16.8257936008497 & -0.325793600849737 \tabularnewline
166 & 14.7 & 14.9518419879868 & -0.251841987986807 \tabularnewline
167 & 14.5 & 16.4707916355479 & -1.97079163554795 \tabularnewline
168 & 17.6 & 17.1434167545243 & 0.456583245475682 \tabularnewline
169 & 15.9 & 15.7163711072187 & 0.183628892781287 \tabularnewline
170 & 13.6 & 14.5498246866626 & -0.949824686662602 \tabularnewline
171 & 15.8 & 14.7159030114644 & 1.08409698853558 \tabularnewline
172 & 14.9 & 16.2120749624477 & -1.31207496244768 \tabularnewline
173 & 16.6 & 16.7700779413206 & -0.170077941320628 \tabularnewline
174 & 18.2 & 16.7922039489217 & 1.40779605107835 \tabularnewline
175 & 17.3 & 17.1014584241419 & 0.198541575858103 \tabularnewline
176 & 16.6 & 15.8088876197246 & 0.791112380275368 \tabularnewline
177 & 15.4 & 14.7272046966036 & 0.672795303396401 \tabularnewline
178 & 13.2 & 14.1256012672980 & -0.925601267298019 \tabularnewline
179 & 15.2 & 14.2381208098277 & 0.961879190172283 \tabularnewline
180 & 14.3 & 14.1083522425465 & 0.191647757453468 \tabularnewline
181 & 15 & 14.7163181632549 & 0.283681836745116 \tabularnewline
182 & 14 & 16.0309990689781 & -2.03099906897808 \tabularnewline
183 & 15.2 & 16.6317560960245 & -1.43175609602454 \tabularnewline
184 & 15 & 17.2134045190841 & -2.21340451908414 \tabularnewline
185 & 24.8 & 19.1753180032516 & 5.62468199674836 \tabularnewline
186 & 22.2 & 16.8161747770905 & 5.38382522290945 \tabularnewline
187 & 14.9 & 16.6142309217072 & -1.71423092170723 \tabularnewline
188 & 19.2 & 16.7644181863293 & 2.43558181367069 \tabularnewline
189 & 16 & 16.2617449796044 & -0.261744979604369 \tabularnewline
190 & 11.3 & 13.6911582494031 & -2.39115824940305 \tabularnewline
191 & 13.2 & 15.9441657202885 & -2.74416572028846 \tabularnewline
192 & 14.7 & 16.2090669092676 & -1.50906690926760 \tabularnewline
193 & 15.5 & 16.5817704269635 & -1.08177042696352 \tabularnewline
194 & 16.4 & 16.7543305469886 & -0.354330546988576 \tabularnewline
195 & 18.1 & 17.0457427646128 & 1.05425723538721 \tabularnewline
196 & 20.1 & 17.189410710764 & 2.91058928923600 \tabularnewline
197 & 15.8 & 16.1924224468856 & -0.392422446885625 \tabularnewline
198 & 15.5 & 16.5000936398318 & -1.00009363983178 \tabularnewline
199 & 15 & 15.6914388311075 & -0.691438831107534 \tabularnewline
200 & 15.2 & 16.5463884706311 & -1.34638847063105 \tabularnewline
201 & 14.4 & 15.4884817118950 & -1.08848171189505 \tabularnewline
202 & 19.2 & 17.0151386542103 & 2.18486134578971 \tabularnewline
203 & 19.9 & 18.7610574828212 & 1.13894251717876 \tabularnewline
204 & 13.8 & 16.1005031724359 & -2.30050317243594 \tabularnewline
205 & 15.3 & 16.4674798945579 & -1.16747989455793 \tabularnewline
206 & 15.1 & 16.1464364778813 & -1.04643647788132 \tabularnewline
207 & 15.7 & 16.3166960548017 & -0.616696054801711 \tabularnewline
208 & 16.4 & 16.6038048845593 & -0.203804884559282 \tabularnewline
209 & 12.6 & 14.4196119606180 & -1.81961196061796 \tabularnewline
210 & 12.9 & 16.0241888422739 & -3.12418884227390 \tabularnewline
211 & 16.4 & 16.4264381832341 & -0.0264381832341449 \tabularnewline
212 & 16.1 & 16.4356239621837 & -0.335623962183735 \tabularnewline
213 & 19.4 & 16.6390579523888 & 2.76094204761118 \tabularnewline
214 & 17.3 & 17.0385654047313 & 0.261434595268720 \tabularnewline
215 & 14.9 & 17.3081295091628 & -2.40812950916282 \tabularnewline
216 & 16.2 & 16.7391386280051 & -0.539138628005072 \tabularnewline
217 & 14.2 & 16.4326207013449 & -2.23262070134488 \tabularnewline
218 & 14.8 & 15.6095824710048 & -0.809582471004822 \tabularnewline
219 & 20.4 & 18.6274058586136 & 1.77259414138642 \tabularnewline
220 & 13.8 & 14.4552437440754 & -0.655243744075418 \tabularnewline
221 & 15.8 & 15.918294545244 & -0.118294545244007 \tabularnewline
222 & 17.1 & 16.7674276027081 & 0.332572397291897 \tabularnewline
223 & 16.6 & 17.932904453631 & -1.33290445363099 \tabularnewline
224 & 18.6 & 16.6094646582279 & 1.99053534177214 \tabularnewline
225 & 18 & 15.9269478289963 & 2.07305217100371 \tabularnewline
226 & 16 & 16.4141984589776 & -0.414198458977648 \tabularnewline
227 & 18 & 16.4428208730740 & 1.55717912692603 \tabularnewline
228 & 15.3 & 15.8476062762892 & -0.547606276289246 \tabularnewline
229 & 17.6 & 16.3615367447554 & 1.23846325524456 \tabularnewline
230 & 14.7 & 17.0574090412818 & -2.35740904128183 \tabularnewline
231 & 14.5 & 15.2138739786151 & -0.713873978615051 \tabularnewline
232 & 14.5 & 16.386543348408 & -1.88654334840801 \tabularnewline
233 & 15.7 & 16.4208682147283 & -0.72086821472831 \tabularnewline
234 & 16.4 & 14.9740693645239 & 1.42593063547608 \tabularnewline
235 & 17 & 16.4091334287478 & 0.590866571252236 \tabularnewline
236 & 13.9 & 15.8593667501412 & -1.95936675014119 \tabularnewline
237 & 17.3 & 17.0417642130119 & 0.258235786988129 \tabularnewline
238 & 15.6 & 16.9694008962066 & -1.36940089620664 \tabularnewline
239 & 11.6 & 15.7734683743929 & -4.17346837439291 \tabularnewline
240 & 18.6 & 17.1686065263631 & 1.43139347363693 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108606&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]11.5[/C][C]11.4249975927423[/C][C]0.075002407257699[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]12.0416165442772[/C][C]-1.0416165442772[/C][/ROW]
[ROW][C]3[/C][C]10.5[/C][C]12.9272652733510[/C][C]-2.42726527335098[/C][/ROW]
[ROW][C]4[/C][C]10[/C][C]10.2357456084876[/C][C]-0.235745608487573[/C][/ROW]
[ROW][C]5[/C][C]8.5[/C][C]8.82921093962588[/C][C]-0.329210939625876[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]8.30187272194974[/C][C]1.69812727805026[/C][/ROW]
[ROW][C]7[/C][C]10[/C][C]10.4555826215061[/C][C]-0.455582621506065[/C][/ROW]
[ROW][C]8[/C][C]8[/C][C]11.6303123106384[/C][C]-3.63031231063841[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]4.571709316476[/C][C]5.42829068352400[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]15.3427502701875[/C][C]-0.342750270187548[/C][/ROW]
[ROW][C]11[/C][C]15.5[/C][C]15.3186520641099[/C][C]0.181347935890127[/C][/ROW]
[ROW][C]12[/C][C]20.5[/C][C]17.5533733715614[/C][C]2.94662662843859[/C][/ROW]
[ROW][C]13[/C][C]17.5[/C][C]16.7864738110581[/C][C]0.713526188941872[/C][/ROW]
[ROW][C]14[/C][C]17.5[/C][C]15.4168243263954[/C][C]2.08317567360458[/C][/ROW]
[ROW][C]15[/C][C]12.5[/C][C]13.5812104411299[/C][C]-1.08121044112993[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]10.2574516906341[/C][C]3.74254830936585[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]11.0775537193952[/C][C]3.9224462806048[/C][/ROW]
[ROW][C]18[/C][C]18.5[/C][C]12.6040207220921[/C][C]5.89597927790786[/C][/ROW]
[ROW][C]19[/C][C]14.5[/C][C]15.2982431856998[/C][C]-0.798243185699798[/C][/ROW]
[ROW][C]20[/C][C]14[/C][C]14.9415975215780[/C][C]-0.941597521577975[/C][/ROW]
[ROW][C]21[/C][C]15.5[/C][C]16.2725857868990[/C][C]-0.772585786898968[/C][/ROW]
[ROW][C]22[/C][C]15.5[/C][C]16.2898020994213[/C][C]-0.789802099421313[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]12.8624616085931[/C][C]-0.862461608593136[/C][/ROW]
[ROW][C]24[/C][C]13[/C][C]13.8802333087377[/C][C]-0.880233308737719[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]13.6270323244600[/C][C]-1.62703232446003[/C][/ROW]
[ROW][C]26[/C][C]12[/C][C]14.3583288929077[/C][C]-2.35832889290774[/C][/ROW]
[ROW][C]27[/C][C]19[/C][C]16.9308771871727[/C][C]2.06912281282732[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.1416539870056[/C][C]-1.14165398700557[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]15.5129380141841[/C][C]-1.5129380141841[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.9934866642330[/C][C]-0.993486664233034[/C][/ROW]
[ROW][C]31[/C][C]14.5[/C][C]16.0620086177704[/C][C]-1.56200861777041[/C][/ROW]
[ROW][C]32[/C][C]19[/C][C]16.1785557802447[/C][C]2.82144421975527[/C][/ROW]
[ROW][C]33[/C][C]19[/C][C]16.5249422006130[/C][C]2.47505779938702[/C][/ROW]
[ROW][C]34[/C][C]20.5[/C][C]16.1732292303983[/C][C]4.32677076960167[/C][/ROW]
[ROW][C]35[/C][C]17[/C][C]15.8695322044530[/C][C]1.13046779554703[/C][/ROW]
[ROW][C]36[/C][C]16.5[/C][C]15.5296527120428[/C][C]0.970347287957169[/C][/ROW]
[ROW][C]37[/C][C]12[/C][C]13.0435375020627[/C][C]-1.04353750206273[/C][/ROW]
[ROW][C]38[/C][C]13.5[/C][C]13.9888788448195[/C][C]-0.488878844819479[/C][/ROW]
[ROW][C]39[/C][C]13[/C][C]13.5114217323741[/C][C]-0.511421732374127[/C][/ROW]
[ROW][C]40[/C][C]11[/C][C]10.3165903890611[/C][C]0.68340961093889[/C][/ROW]
[ROW][C]41[/C][C]13.5[/C][C]14.4112998692460[/C][C]-0.911299869245975[/C][/ROW]
[ROW][C]42[/C][C]12.5[/C][C]11.2592309429857[/C][C]1.24076905701434[/C][/ROW]
[ROW][C]43[/C][C]13.5[/C][C]15.5779577119174[/C][C]-2.07795771191736[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]15.4313329918005[/C][C]-1.43133299180053[/C][/ROW]
[ROW][C]45[/C][C]16[/C][C]15.2812518884558[/C][C]0.718748111544243[/C][/ROW]
[ROW][C]46[/C][C]14.5[/C][C]15.6017331265274[/C][C]-1.10173312652737[/C][/ROW]
[ROW][C]47[/C][C]18[/C][C]17.0635065652483[/C][C]0.936493434751694[/C][/ROW]
[ROW][C]48[/C][C]16[/C][C]16.0004500350638[/C][C]-0.000450035063788784[/C][/ROW]
[ROW][C]49[/C][C]14.5[/C][C]15.5184114247723[/C][C]-1.01841142477233[/C][/ROW]
[ROW][C]50[/C][C]15[/C][C]15.9717410293761[/C][C]-0.971741029376135[/C][/ROW]
[ROW][C]51[/C][C]13[/C][C]11.8262074156081[/C][C]1.17379258439192[/C][/ROW]
[ROW][C]52[/C][C]11.5[/C][C]12.8012873158205[/C][C]-1.30128731582054[/C][/ROW]
[ROW][C]53[/C][C]14.5[/C][C]14.7990157329544[/C][C]-0.299015732954429[/C][/ROW]
[ROW][C]54[/C][C]12.5[/C][C]12.9915685392485[/C][C]-0.491568539248457[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.3066492222024[/C][C]-2.30664922220245[/C][/ROW]
[ROW][C]56[/C][C]13[/C][C]13.7969930245890[/C][C]-0.796993024588975[/C][/ROW]
[ROW][C]57[/C][C]11[/C][C]10.0075971386665[/C][C]0.992402861333498[/C][/ROW]
[ROW][C]58[/C][C]11[/C][C]9.76719456756527[/C][C]1.23280543243473[/C][/ROW]
[ROW][C]59[/C][C]16.5[/C][C]15.5093874126275[/C][C]0.99061258737249[/C][/ROW]
[ROW][C]60[/C][C]18[/C][C]16.1305108550997[/C][C]1.86948914490026[/C][/ROW]
[ROW][C]61[/C][C]16.5[/C][C]16.2936892484124[/C][C]0.206310751587585[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.8346264771236[/C][C]0.165373522876367[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]15.7914715486532[/C][C]-1.79147154865316[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]12.5714328989381[/C][C]-0.0714328989380675[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]14.8996963941701[/C][C]0.100303605829915[/C][/ROW]
[ROW][C]66[/C][C]19.5[/C][C]16.9113767063375[/C][C]2.58862329366251[/C][/ROW]
[ROW][C]67[/C][C]16.5[/C][C]15.4720204176993[/C][C]1.02797958230073[/C][/ROW]
[ROW][C]68[/C][C]18.5[/C][C]15.8369188669202[/C][C]2.66308113307978[/C][/ROW]
[ROW][C]69[/C][C]14[/C][C]14.0660234366972[/C][C]-0.0660234366971941[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]13.9738748676861[/C][C]-0.973874867686137[/C][/ROW]
[ROW][C]71[/C][C]9.5[/C][C]7.92766280017042[/C][C]1.57233719982958[/C][/ROW]
[ROW][C]72[/C][C]15.5[/C][C]16.1898948412361[/C][C]-0.689894841236096[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]16.2135043782995[/C][C]-2.21350437829946[/C][/ROW]
[ROW][C]74[/C][C]11[/C][C]11.9385425741483[/C][C]-0.938542574148328[/C][/ROW]
[ROW][C]75[/C][C]14[/C][C]14.9877351436653[/C][C]-0.98773514366534[/C][/ROW]
[ROW][C]76[/C][C]11[/C][C]10.2453041135978[/C][C]0.754695886402165[/C][/ROW]
[ROW][C]77[/C][C]16.5[/C][C]16.3862115064618[/C][C]0.113788493538204[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]15.2117040875331[/C][C]0.788295912466914[/C][/ROW]
[ROW][C]79[/C][C]16.5[/C][C]16.5960161908761[/C][C]-0.0960161908761392[/C][/ROW]
[ROW][C]80[/C][C]21[/C][C]16.3540601077614[/C][C]4.64593989223858[/C][/ROW]
[ROW][C]81[/C][C]17[/C][C]17.5317596922568[/C][C]-0.531759692256794[/C][/ROW]
[ROW][C]82[/C][C]18[/C][C]16.3256593292993[/C][C]1.6743406707007[/C][/ROW]
[ROW][C]83[/C][C]14[/C][C]14.8550270930581[/C][C]-0.855027093058085[/C][/ROW]
[ROW][C]84[/C][C]14.5[/C][C]15.3264010398834[/C][C]-0.82640103988339[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]16.2395612323564[/C][C]-0.239561232356403[/C][/ROW]
[ROW][C]86[/C][C]15.5[/C][C]14.4309703570469[/C][C]1.06902964295307[/C][/ROW]
[ROW][C]87[/C][C]15.5[/C][C]16.5029189251467[/C][C]-1.00291892514674[/C][/ROW]
[ROW][C]88[/C][C]14.5[/C][C]16.5044301402486[/C][C]-2.00443014024863[/C][/ROW]
[ROW][C]89[/C][C]19[/C][C]17.0247051278787[/C][C]1.97529487212131[/C][/ROW]
[ROW][C]90[/C][C]14.5[/C][C]16.2878122684843[/C][C]-1.78781226848431[/C][/ROW]
[ROW][C]91[/C][C]14[/C][C]16.4350437431642[/C][C]-2.43504374316417[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]15.4710531141726[/C][C]-0.471053114172592[/C][/ROW]
[ROW][C]93[/C][C]16[/C][C]16.6059928952756[/C][C]-0.60599289527559[/C][/ROW]
[ROW][C]94[/C][C]16[/C][C]16.6403582268120[/C][C]-0.640358226812043[/C][/ROW]
[ROW][C]95[/C][C]19.5[/C][C]17.8475076738691[/C][C]1.65249232613093[/C][/ROW]
[ROW][C]96[/C][C]11.5[/C][C]13.4097412522965[/C][C]-1.90974125229651[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.9711851732572[/C][C]-0.971185173257158[/C][/ROW]
[ROW][C]98[/C][C]13.5[/C][C]15.3486170682183[/C][C]-1.84861706821827[/C][/ROW]
[ROW][C]99[/C][C]21[/C][C]17.2888997696600[/C][C]3.71110023033995[/C][/ROW]
[ROW][C]100[/C][C]19[/C][C]16.5986660609919[/C][C]2.40133393900808[/C][/ROW]
[ROW][C]101[/C][C]19[/C][C]18.0917511575453[/C][C]0.90824884245471[/C][/ROW]
[ROW][C]102[/C][C]13.5[/C][C]14.7819925549445[/C][C]-1.28199255494454[/C][/ROW]
[ROW][C]103[/C][C]12[/C][C]12.9531102733500[/C][C]-0.953110273350026[/C][/ROW]
[ROW][C]104[/C][C]17[/C][C]16.7685288213273[/C][C]0.231471178672692[/C][/ROW]
[ROW][C]105[/C][C]16[/C][C]15.247919266227[/C][C]0.752080733772994[/C][/ROW]
[ROW][C]106[/C][C]13.5[/C][C]16.0354592839128[/C][C]-2.53545928391283[/C][/ROW]
[ROW][C]107[/C][C]16.5[/C][C]16.8538605395975[/C][C]-0.353860539597506[/C][/ROW]
[ROW][C]108[/C][C]14.5[/C][C]16.1081184673653[/C][C]-1.60811846736530[/C][/ROW]
[ROW][C]109[/C][C]15[/C][C]16.2251686758776[/C][C]-1.22516867587762[/C][/ROW]
[ROW][C]110[/C][C]17[/C][C]17.4341430108500[/C][C]-0.434143010849979[/C][/ROW]
[ROW][C]111[/C][C]13.5[/C][C]14.6520768321306[/C][C]-1.15207683213064[/C][/ROW]
[ROW][C]112[/C][C]17.5[/C][C]16.9729304967029[/C][C]0.527069503297121[/C][/ROW]
[ROW][C]113[/C][C]16.9[/C][C]15.9230510766455[/C][C]0.97694892335452[/C][/ROW]
[ROW][C]114[/C][C]14.9[/C][C]15.9225378982085[/C][C]-1.02253789820852[/C][/ROW]
[ROW][C]115[/C][C]15.3[/C][C]15.8359140588232[/C][C]-0.535914058823178[/C][/ROW]
[ROW][C]116[/C][C]13[/C][C]15.0392694642229[/C][C]-2.03926946422295[/C][/ROW]
[ROW][C]117[/C][C]13.9[/C][C]15.8069759246468[/C][C]-1.90697592464685[/C][/ROW]
[ROW][C]118[/C][C]12.8[/C][C]13.8242594532044[/C][C]-1.02425945320443[/C][/ROW]
[ROW][C]119[/C][C]14.5[/C][C]15.9731426540582[/C][C]-1.47314265405819[/C][/ROW]
[ROW][C]120[/C][C]17.6[/C][C]17.1465327138242[/C][C]0.453467286175763[/C][/ROW]
[ROW][C]121[/C][C]22.2[/C][C]17.7585899340930[/C][C]4.44141006590702[/C][/ROW]
[ROW][C]122[/C][C]22.1[/C][C]17.4369487264790[/C][C]4.66305127352103[/C][/ROW]
[ROW][C]123[/C][C]17.7[/C][C]17.3521543144246[/C][C]0.347845685575438[/C][/ROW]
[ROW][C]124[/C][C]16.2[/C][C]16.4202893589074[/C][C]-0.220289358907449[/C][/ROW]
[ROW][C]125[/C][C]17.8[/C][C]16.2016063754625[/C][C]1.59839362453748[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.3145427727599[/C][C]0.68545722724006[/C][/ROW]
[ROW][C]127[/C][C]16.4[/C][C]16.3202727632280[/C][C]0.0797272367719747[/C][/ROW]
[ROW][C]128[/C][C]15.7[/C][C]16.8731351736911[/C][C]-1.17313517369110[/C][/ROW]
[ROW][C]129[/C][C]13.2[/C][C]13.4456511644107[/C][C]-0.245651164410682[/C][/ROW]
[ROW][C]130[/C][C]16.7[/C][C]16.7739497531066[/C][C]-0.0739497531065677[/C][/ROW]
[ROW][C]131[/C][C]12.1[/C][C]12.2399247247399[/C][C]-0.139924724739879[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]14.8326837549901[/C][C]0.167316245009903[/C][/ROW]
[ROW][C]133[/C][C]14[/C][C]12.9302813137664[/C][C]1.06971868623356[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]15.8517448498524[/C][C]-1.05174484985241[/C][/ROW]
[ROW][C]135[/C][C]18.6[/C][C]16.7778243380922[/C][C]1.82217566190783[/C][/ROW]
[ROW][C]136[/C][C]16.8[/C][C]16.1891825388194[/C][C]0.610817461180553[/C][/ROW]
[ROW][C]137[/C][C]12.5[/C][C]13.7397302428347[/C][C]-1.23973024283469[/C][/ROW]
[ROW][C]138[/C][C]13.7[/C][C]14.3691096839775[/C][C]-0.669109683977464[/C][/ROW]
[ROW][C]139[/C][C]16.9[/C][C]16.3124542992843[/C][C]0.58754570071573[/C][/ROW]
[ROW][C]140[/C][C]17.7[/C][C]17.293652871919[/C][C]0.406347128081[/C][/ROW]
[ROW][C]141[/C][C]11.1[/C][C]11.4291066302931[/C][C]-0.32910663029309[/C][/ROW]
[ROW][C]142[/C][C]11.4[/C][C]12.3735852333534[/C][C]-0.97358523335339[/C][/ROW]
[ROW][C]143[/C][C]14.5[/C][C]14.3783345649445[/C][C]0.121665435055500[/C][/ROW]
[ROW][C]144[/C][C]14.5[/C][C]15.5015482687247[/C][C]-1.00154826872469[/C][/ROW]
[ROW][C]145[/C][C]18.2[/C][C]16.6267088906381[/C][C]1.57329110936189[/C][/ROW]
[ROW][C]146[/C][C]15.8[/C][C]16.6521173374653[/C][C]-0.85211733746528[/C][/ROW]
[ROW][C]147[/C][C]15.9[/C][C]15.5040251899062[/C][C]0.395974810093818[/C][/ROW]
[ROW][C]148[/C][C]16.4[/C][C]16.4327727360717[/C][C]-0.0327727360717458[/C][/ROW]
[ROW][C]149[/C][C]14.5[/C][C]15.8198675534513[/C][C]-1.31986755345131[/C][/ROW]
[ROW][C]150[/C][C]12.8[/C][C]14.8205881650780[/C][C]-2.02058816507802[/C][/ROW]
[ROW][C]151[/C][C]21.5[/C][C]17.8758330428694[/C][C]3.62416695713061[/C][/ROW]
[ROW][C]152[/C][C]14.4[/C][C]15.9833614139184[/C][C]-1.58336141391836[/C][/ROW]
[ROW][C]153[/C][C]18.6[/C][C]16.5374054108764[/C][C]2.06259458912363[/C][/ROW]
[ROW][C]154[/C][C]13.2[/C][C]13.6071695027887[/C][C]-0.407169502788748[/C][/ROW]
[ROW][C]155[/C][C]12.8[/C][C]13.3376053983572[/C][C]-0.537605398357211[/C][/ROW]
[ROW][C]156[/C][C]18.2[/C][C]16.5192542914854[/C][C]1.68074570851463[/C][/ROW]
[ROW][C]157[/C][C]15.8[/C][C]16.7225593745103[/C][C]-0.922559374510269[/C][/ROW]
[ROW][C]158[/C][C]17.2[/C][C]16.7364962766279[/C][C]0.463503723372074[/C][/ROW]
[ROW][C]159[/C][C]17.2[/C][C]16.8051148758092[/C][C]0.394885124190789[/C][/ROW]
[ROW][C]160[/C][C]16.7[/C][C]17.0150665870381[/C][C]-0.315066587038084[/C][/ROW]
[ROW][C]161[/C][C]18.7[/C][C]16.5331911936030[/C][C]2.16680880639697[/C][/ROW]
[ROW][C]162[/C][C]13.2[/C][C]12.4721989885475[/C][C]0.727801011452502[/C][/ROW]
[ROW][C]163[/C][C]13.4[/C][C]11.9725468675049[/C][C]1.42745313249512[/C][/ROW]
[ROW][C]164[/C][C]13.7[/C][C]14.5682646296658[/C][C]-0.86826462966585[/C][/ROW]
[ROW][C]165[/C][C]16.5[/C][C]16.8257936008497[/C][C]-0.325793600849737[/C][/ROW]
[ROW][C]166[/C][C]14.7[/C][C]14.9518419879868[/C][C]-0.251841987986807[/C][/ROW]
[ROW][C]167[/C][C]14.5[/C][C]16.4707916355479[/C][C]-1.97079163554795[/C][/ROW]
[ROW][C]168[/C][C]17.6[/C][C]17.1434167545243[/C][C]0.456583245475682[/C][/ROW]
[ROW][C]169[/C][C]15.9[/C][C]15.7163711072187[/C][C]0.183628892781287[/C][/ROW]
[ROW][C]170[/C][C]13.6[/C][C]14.5498246866626[/C][C]-0.949824686662602[/C][/ROW]
[ROW][C]171[/C][C]15.8[/C][C]14.7159030114644[/C][C]1.08409698853558[/C][/ROW]
[ROW][C]172[/C][C]14.9[/C][C]16.2120749624477[/C][C]-1.31207496244768[/C][/ROW]
[ROW][C]173[/C][C]16.6[/C][C]16.7700779413206[/C][C]-0.170077941320628[/C][/ROW]
[ROW][C]174[/C][C]18.2[/C][C]16.7922039489217[/C][C]1.40779605107835[/C][/ROW]
[ROW][C]175[/C][C]17.3[/C][C]17.1014584241419[/C][C]0.198541575858103[/C][/ROW]
[ROW][C]176[/C][C]16.6[/C][C]15.8088876197246[/C][C]0.791112380275368[/C][/ROW]
[ROW][C]177[/C][C]15.4[/C][C]14.7272046966036[/C][C]0.672795303396401[/C][/ROW]
[ROW][C]178[/C][C]13.2[/C][C]14.1256012672980[/C][C]-0.925601267298019[/C][/ROW]
[ROW][C]179[/C][C]15.2[/C][C]14.2381208098277[/C][C]0.961879190172283[/C][/ROW]
[ROW][C]180[/C][C]14.3[/C][C]14.1083522425465[/C][C]0.191647757453468[/C][/ROW]
[ROW][C]181[/C][C]15[/C][C]14.7163181632549[/C][C]0.283681836745116[/C][/ROW]
[ROW][C]182[/C][C]14[/C][C]16.0309990689781[/C][C]-2.03099906897808[/C][/ROW]
[ROW][C]183[/C][C]15.2[/C][C]16.6317560960245[/C][C]-1.43175609602454[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]17.2134045190841[/C][C]-2.21340451908414[/C][/ROW]
[ROW][C]185[/C][C]24.8[/C][C]19.1753180032516[/C][C]5.62468199674836[/C][/ROW]
[ROW][C]186[/C][C]22.2[/C][C]16.8161747770905[/C][C]5.38382522290945[/C][/ROW]
[ROW][C]187[/C][C]14.9[/C][C]16.6142309217072[/C][C]-1.71423092170723[/C][/ROW]
[ROW][C]188[/C][C]19.2[/C][C]16.7644181863293[/C][C]2.43558181367069[/C][/ROW]
[ROW][C]189[/C][C]16[/C][C]16.2617449796044[/C][C]-0.261744979604369[/C][/ROW]
[ROW][C]190[/C][C]11.3[/C][C]13.6911582494031[/C][C]-2.39115824940305[/C][/ROW]
[ROW][C]191[/C][C]13.2[/C][C]15.9441657202885[/C][C]-2.74416572028846[/C][/ROW]
[ROW][C]192[/C][C]14.7[/C][C]16.2090669092676[/C][C]-1.50906690926760[/C][/ROW]
[ROW][C]193[/C][C]15.5[/C][C]16.5817704269635[/C][C]-1.08177042696352[/C][/ROW]
[ROW][C]194[/C][C]16.4[/C][C]16.7543305469886[/C][C]-0.354330546988576[/C][/ROW]
[ROW][C]195[/C][C]18.1[/C][C]17.0457427646128[/C][C]1.05425723538721[/C][/ROW]
[ROW][C]196[/C][C]20.1[/C][C]17.189410710764[/C][C]2.91058928923600[/C][/ROW]
[ROW][C]197[/C][C]15.8[/C][C]16.1924224468856[/C][C]-0.392422446885625[/C][/ROW]
[ROW][C]198[/C][C]15.5[/C][C]16.5000936398318[/C][C]-1.00009363983178[/C][/ROW]
[ROW][C]199[/C][C]15[/C][C]15.6914388311075[/C][C]-0.691438831107534[/C][/ROW]
[ROW][C]200[/C][C]15.2[/C][C]16.5463884706311[/C][C]-1.34638847063105[/C][/ROW]
[ROW][C]201[/C][C]14.4[/C][C]15.4884817118950[/C][C]-1.08848171189505[/C][/ROW]
[ROW][C]202[/C][C]19.2[/C][C]17.0151386542103[/C][C]2.18486134578971[/C][/ROW]
[ROW][C]203[/C][C]19.9[/C][C]18.7610574828212[/C][C]1.13894251717876[/C][/ROW]
[ROW][C]204[/C][C]13.8[/C][C]16.1005031724359[/C][C]-2.30050317243594[/C][/ROW]
[ROW][C]205[/C][C]15.3[/C][C]16.4674798945579[/C][C]-1.16747989455793[/C][/ROW]
[ROW][C]206[/C][C]15.1[/C][C]16.1464364778813[/C][C]-1.04643647788132[/C][/ROW]
[ROW][C]207[/C][C]15.7[/C][C]16.3166960548017[/C][C]-0.616696054801711[/C][/ROW]
[ROW][C]208[/C][C]16.4[/C][C]16.6038048845593[/C][C]-0.203804884559282[/C][/ROW]
[ROW][C]209[/C][C]12.6[/C][C]14.4196119606180[/C][C]-1.81961196061796[/C][/ROW]
[ROW][C]210[/C][C]12.9[/C][C]16.0241888422739[/C][C]-3.12418884227390[/C][/ROW]
[ROW][C]211[/C][C]16.4[/C][C]16.4264381832341[/C][C]-0.0264381832341449[/C][/ROW]
[ROW][C]212[/C][C]16.1[/C][C]16.4356239621837[/C][C]-0.335623962183735[/C][/ROW]
[ROW][C]213[/C][C]19.4[/C][C]16.6390579523888[/C][C]2.76094204761118[/C][/ROW]
[ROW][C]214[/C][C]17.3[/C][C]17.0385654047313[/C][C]0.261434595268720[/C][/ROW]
[ROW][C]215[/C][C]14.9[/C][C]17.3081295091628[/C][C]-2.40812950916282[/C][/ROW]
[ROW][C]216[/C][C]16.2[/C][C]16.7391386280051[/C][C]-0.539138628005072[/C][/ROW]
[ROW][C]217[/C][C]14.2[/C][C]16.4326207013449[/C][C]-2.23262070134488[/C][/ROW]
[ROW][C]218[/C][C]14.8[/C][C]15.6095824710048[/C][C]-0.809582471004822[/C][/ROW]
[ROW][C]219[/C][C]20.4[/C][C]18.6274058586136[/C][C]1.77259414138642[/C][/ROW]
[ROW][C]220[/C][C]13.8[/C][C]14.4552437440754[/C][C]-0.655243744075418[/C][/ROW]
[ROW][C]221[/C][C]15.8[/C][C]15.918294545244[/C][C]-0.118294545244007[/C][/ROW]
[ROW][C]222[/C][C]17.1[/C][C]16.7674276027081[/C][C]0.332572397291897[/C][/ROW]
[ROW][C]223[/C][C]16.6[/C][C]17.932904453631[/C][C]-1.33290445363099[/C][/ROW]
[ROW][C]224[/C][C]18.6[/C][C]16.6094646582279[/C][C]1.99053534177214[/C][/ROW]
[ROW][C]225[/C][C]18[/C][C]15.9269478289963[/C][C]2.07305217100371[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]16.4141984589776[/C][C]-0.414198458977648[/C][/ROW]
[ROW][C]227[/C][C]18[/C][C]16.4428208730740[/C][C]1.55717912692603[/C][/ROW]
[ROW][C]228[/C][C]15.3[/C][C]15.8476062762892[/C][C]-0.547606276289246[/C][/ROW]
[ROW][C]229[/C][C]17.6[/C][C]16.3615367447554[/C][C]1.23846325524456[/C][/ROW]
[ROW][C]230[/C][C]14.7[/C][C]17.0574090412818[/C][C]-2.35740904128183[/C][/ROW]
[ROW][C]231[/C][C]14.5[/C][C]15.2138739786151[/C][C]-0.713873978615051[/C][/ROW]
[ROW][C]232[/C][C]14.5[/C][C]16.386543348408[/C][C]-1.88654334840801[/C][/ROW]
[ROW][C]233[/C][C]15.7[/C][C]16.4208682147283[/C][C]-0.72086821472831[/C][/ROW]
[ROW][C]234[/C][C]16.4[/C][C]14.9740693645239[/C][C]1.42593063547608[/C][/ROW]
[ROW][C]235[/C][C]17[/C][C]16.4091334287478[/C][C]0.590866571252236[/C][/ROW]
[ROW][C]236[/C][C]13.9[/C][C]15.8593667501412[/C][C]-1.95936675014119[/C][/ROW]
[ROW][C]237[/C][C]17.3[/C][C]17.0417642130119[/C][C]0.258235786988129[/C][/ROW]
[ROW][C]238[/C][C]15.6[/C][C]16.9694008962066[/C][C]-1.36940089620664[/C][/ROW]
[ROW][C]239[/C][C]11.6[/C][C]15.7734683743929[/C][C]-4.17346837439291[/C][/ROW]
[ROW][C]240[/C][C]18.6[/C][C]17.1686065263631[/C][C]1.43139347363693[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108606&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108606&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
111.511.42499759274230.075002407257699
21112.0416165442772-1.0416165442772
310.512.9272652733510-2.42726527335098
41010.2357456084876-0.235745608487573
58.58.82921093962588-0.329210939625876
6108.301872721949741.69812727805026
71010.4555826215061-0.455582621506065
8811.6303123106384-3.63031231063841
9104.5717093164765.42829068352400
101515.3427502701875-0.342750270187548
1115.515.31865206410990.181347935890127
1220.517.55337337156142.94662662843859
1317.516.78647381105810.713526188941872
1417.515.41682432639542.08317567360458
1512.513.5812104411299-1.08121044112993
161410.25745169063413.74254830936585
171511.07755371939523.9224462806048
1818.512.60402072209215.89597927790786
1914.515.2982431856998-0.798243185699798
201414.9415975215780-0.941597521577975
2115.516.2725857868990-0.772585786898968
2215.516.2898020994213-0.789802099421313
231212.8624616085931-0.862461608593136
241313.8802333087377-0.880233308737719
251213.6270323244600-1.62703232446003
261214.3583288929077-2.35832889290774
271916.93087718717272.06912281282732
281516.1416539870056-1.14165398700557
291415.5129380141841-1.5129380141841
301414.9934866642330-0.993486664233034
3114.516.0620086177704-1.56200861777041
321916.17855578024472.82144421975527
331916.52494220061302.47505779938702
3420.516.17322923039834.32677076960167
351715.86953220445301.13046779554703
3616.515.52965271204280.970347287957169
371213.0435375020627-1.04353750206273
3813.513.9888788448195-0.488878844819479
391313.5114217323741-0.511421732374127
401110.31659038906110.68340961093889
4113.514.4112998692460-0.911299869245975
4212.511.25923094298571.24076905701434
4313.515.5779577119174-2.07795771191736
441415.4313329918005-1.43133299180053
451615.28125188845580.718748111544243
4614.515.6017331265274-1.10173312652737
471817.06350656524830.936493434751694
481616.0004500350638-0.000450035063788784
4914.515.5184114247723-1.01841142477233
501515.9717410293761-0.971741029376135
511311.82620741560811.17379258439192
5211.512.8012873158205-1.30128731582054
5314.514.7990157329544-0.299015732954429
5412.512.9915685392485-0.491568539248457
551214.3066492222024-2.30664922220245
561313.7969930245890-0.796993024588975
571110.00759713866650.992402861333498
58119.767194567565271.23280543243473
5916.515.50938741262750.99061258737249
601816.13051085509971.86948914490026
6116.516.29368924841240.206310751587585
621615.83462647712360.165373522876367
631415.7914715486532-1.79147154865316
6412.512.5714328989381-0.0714328989380675
651514.89969639417010.100303605829915
6619.516.91137670633752.58862329366251
6716.515.47202041769931.02797958230073
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719.57.927662800170421.57233719982958
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751414.9877351436653-0.98773514366534
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7716.516.38621150646180.113788493538204
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851616.2395612323564-0.239561232356403
8615.514.43097035704691.06902964295307
8715.516.5029189251467-1.00291892514674
8814.516.5044301402486-2.00443014024863
891917.02470512787871.97529487212131
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941616.6403582268120-0.640358226812043
9519.517.84750767386911.65249232613093
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971414.9711851732572-0.971185173257158
9813.515.3486170682183-1.84861706821827
992117.28889976966003.71110023033995
1001916.59866606099192.40133393900808
1011918.09175115754530.90824884245471
10213.514.7819925549445-1.28199255494454
1031212.9531102733500-0.953110273350026
1041716.76852882132730.231471178672692
1051615.2479192662270.752080733772994
10613.516.0354592839128-2.53545928391283
10716.516.8538605395975-0.353860539597506
10814.516.1081184673653-1.60811846736530
1091516.2251686758776-1.22516867587762
1101717.4341430108500-0.434143010849979
11113.514.6520768321306-1.15207683213064
11217.516.97293049670290.527069503297121
11316.915.92305107664550.97694892335452
11414.915.9225378982085-1.02253789820852
11515.315.8359140588232-0.535914058823178
1161315.0392694642229-2.03926946422295
11713.915.8069759246468-1.90697592464685
11812.813.8242594532044-1.02425945320443
11914.515.9731426540582-1.47314265405819
12017.617.14653271382420.453467286175763
12122.217.75858993409304.44141006590702
12222.117.43694872647904.66305127352103
12317.717.35215431442460.347845685575438
12416.216.4202893589074-0.220289358907449
12517.816.20160637546251.59839362453748
1261716.31454277275990.68545722724006
12716.416.32027276322800.0797272367719747
12815.716.8731351736911-1.17313517369110
12913.213.4456511644107-0.245651164410682
13016.716.7739497531066-0.0739497531065677
13112.112.2399247247399-0.139924724739879
1321514.83268375499010.167316245009903
1331412.93028131376641.06971868623356
13414.815.8517448498524-1.05174484985241
13518.616.77782433809221.82217566190783
13616.816.18918253881940.610817461180553
13712.513.7397302428347-1.23973024283469
13813.714.3691096839775-0.669109683977464
13916.916.31245429928430.58754570071573
14017.717.2936528719190.406347128081
14111.111.4291066302931-0.32910663029309
14211.412.3735852333534-0.97358523335339
14314.514.37833456494450.121665435055500
14414.515.5015482687247-1.00154826872469
14518.216.62670889063811.57329110936189
14615.816.6521173374653-0.85211733746528
14715.915.50402518990620.395974810093818
14816.416.4327727360717-0.0327727360717458
14914.515.8198675534513-1.31986755345131
15012.814.8205881650780-2.02058816507802
15121.517.87583304286943.62416695713061
15214.415.9833614139184-1.58336141391836
15318.616.53740541087642.06259458912363
15413.213.6071695027887-0.407169502788748
15512.813.3376053983572-0.537605398357211
15618.216.51925429148541.68074570851463
15715.816.7225593745103-0.922559374510269
15817.216.73649627662790.463503723372074
15917.216.80511487580920.394885124190789
16016.717.0150665870381-0.315066587038084
16118.716.53319119360302.16680880639697
16213.212.47219898854750.727801011452502
16313.411.97254686750491.42745313249512
16413.714.5682646296658-0.86826462966585
16516.516.8257936008497-0.325793600849737
16614.714.9518419879868-0.251841987986807
16714.516.4707916355479-1.97079163554795
16817.617.14341675452430.456583245475682
16915.915.71637110721870.183628892781287
17013.614.5498246866626-0.949824686662602
17115.814.71590301146441.08409698853558
17214.916.2120749624477-1.31207496244768
17316.616.7700779413206-0.170077941320628
17418.216.79220394892171.40779605107835
17517.317.10145842414190.198541575858103
17616.615.80888761972460.791112380275368
17715.414.72720469660360.672795303396401
17813.214.1256012672980-0.925601267298019
17915.214.23812080982770.961879190172283
18014.314.10835224254650.191647757453468
1811514.71631816325490.283681836745116
1821416.0309990689781-2.03099906897808
18315.216.6317560960245-1.43175609602454
1841517.2134045190841-2.21340451908414
18524.819.17531800325165.62468199674836
18622.216.81617477709055.38382522290945
18714.916.6142309217072-1.71423092170723
18819.216.76441818632932.43558181367069
1891616.2617449796044-0.261744979604369
19011.313.6911582494031-2.39115824940305
19113.215.9441657202885-2.74416572028846
19214.716.2090669092676-1.50906690926760
19315.516.5817704269635-1.08177042696352
19416.416.7543305469886-0.354330546988576
19518.117.04574276461281.05425723538721
19620.117.1894107107642.91058928923600
19715.816.1924224468856-0.392422446885625
19815.516.5000936398318-1.00009363983178
1991515.6914388311075-0.691438831107534
20015.216.5463884706311-1.34638847063105
20114.415.4884817118950-1.08848171189505
20219.217.01513865421032.18486134578971
20319.918.76105748282121.13894251717876
20413.816.1005031724359-2.30050317243594
20515.316.4674798945579-1.16747989455793
20615.116.1464364778813-1.04643647788132
20715.716.3166960548017-0.616696054801711
20816.416.6038048845593-0.203804884559282
20912.614.4196119606180-1.81961196061796
21012.916.0241888422739-3.12418884227390
21116.416.4264381832341-0.0264381832341449
21216.116.4356239621837-0.335623962183735
21319.416.63905795238882.76094204761118
21417.317.03856540473130.261434595268720
21514.917.3081295091628-2.40812950916282
21616.216.7391386280051-0.539138628005072
21714.216.4326207013449-2.23262070134488
21814.815.6095824710048-0.809582471004822
21920.418.62740585861361.77259414138642
22013.814.4552437440754-0.655243744075418
22115.815.918294545244-0.118294545244007
22217.116.76742760270810.332572397291897
22316.617.932904453631-1.33290445363099
22418.616.60946465822791.99053534177214
2251815.92694782899632.07305217100371
2261616.4141984589776-0.414198458977648
2271816.44282087307401.55717912692603
22815.315.8476062762892-0.547606276289246
22917.616.36153674475541.23846325524456
23014.717.0574090412818-2.35740904128183
23114.515.2138739786151-0.713873978615051
23214.516.386543348408-1.88654334840801
23315.716.4208682147283-0.72086821472831
23416.414.97406936452391.42593063547608
2351716.40913342874780.590866571252236
23613.915.8593667501412-1.95936675014119
23717.317.04176421301190.258235786988129
23815.616.9694008962066-1.36940089620664
23911.615.7734683743929-4.17346837439291
24018.617.16860652636311.43139347363693






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.5974464076232320.8051071847535350.402553592376768
90.4667384944291240.9334769888582470.533261505570876
100.3218997447269420.6437994894538840.678100255273058
110.3508942885469050.7017885770938090.649105711453095
120.2699682612339950.5399365224679910.730031738766004
130.2214927201465260.4429854402930520.778507279853474
140.2006592598243170.4013185196486340.799340740175683
150.3492153127594810.6984306255189620.650784687240519
160.9445527251200530.1108945497598930.0554472748799466
170.9744938438455380.05101231230892360.0255061561544618
180.9965128415859810.006974316828037770.00348715841401889
190.9963117901009580.007376419798083450.00368820989904172
200.9959481776740560.00810364465188730.00405182232594365
210.9941779530175720.01164409396485560.00582204698242778
220.9911134480665260.01777310386694740.0088865519334737
230.987862432802040.02427513439592240.0121375671979612
240.9826477534252940.03470449314941230.0173522465747062
250.9774215450767470.04515690984650660.0225784549232533
260.9751880136675340.04962397266493210.0248119863324660
270.9854982232297460.02900355354050720.0145017767702536
280.980303585264310.03939282947137960.0196964147356898
290.980826941094550.03834611781090110.0191730589054505
300.9787628652811750.042474269437650.021237134718825
310.9776515035956050.04469699280878920.0223484964043946
320.9863357980546150.02732840389076910.0136642019453845
330.9917090820014220.01658183599715610.00829091799857804
340.9980930802846340.003813839430733150.00190691971536657
350.997301980998110.005396038003780310.00269801900189015
360.9962059415261330.007588116947733660.00379405847386683
370.994864668039450.01027066392110060.00513533196055029
380.9926998506715510.01460029865689720.0073001493284486
390.989897337851480.02020532429703890.0101026621485195
400.9867600490150060.02647990196998810.0132399509849940
410.9823366527948240.03532669441035180.0176633472051759
420.9798246784180270.04035064316394540.0201753215819727
430.9913270340316140.01734593193677120.00867296596838558
440.9890596815972370.02188063680552520.0109403184027626
450.9869724407602520.02605511847949510.0130275592397476
460.9869133999820490.02617320003590220.0130866000179511
470.984684565460460.03063086907907810.0153154345395391
480.9797339088089780.04053218238204400.0202660911910220
490.977607257155120.04478548568975850.0223927428448793
500.9745334560200510.05093308795989780.0254665439799489
510.9700836834840180.05983263303196340.0299163165159817
520.9688300387778150.06233992244437070.0311699612221853
530.9603349227997930.07933015440041330.0396650772002066
540.9508857815741460.09822843685170850.0491142184258542
550.9468780525495480.1062438949009050.0531219474504524
560.934746166774820.1305076664503590.0652538332251797
570.9271357246048170.1457285507903660.0728642753951829
580.9247014755015360.1505970489969280.0752985244984638
590.9199867148825340.1600265702349330.0800132851174663
600.940568327203770.1188633455924620.0594316727962309
610.933153038156460.1336939236870810.0668469618435407
620.9189801361422520.1620397277154960.081019863857748
630.9105202108755760.1789595782488480.0894797891244238
640.8935488487781910.2129023024436170.106451151221809
650.8738342211289050.2523315577421890.126165778871095
660.9068052965186430.1863894069627150.0931947034813575
670.8936670585096680.2126658829806630.106332941490332
680.9145567193918260.1708865612163480.0854432806081738
690.9010795926792310.1978408146415380.0989204073207688
700.884438143262580.2311237134748390.115561856737419
710.9102001366808540.1795997266382920.089799863319146
720.897721995202750.20455600959450.10227800479725
730.916461228055750.1670775438885010.0835387719442506
740.9064517889538030.1870964220923940.0935482110461972
750.9029259636711450.194148072657710.097074036328855
760.9069272766553360.1861454466893280.0930727233446642
770.8909091409486550.218181718102690.109090859051345
780.8797731961598840.2404536076802310.120226803840116
790.8589465869112950.2821068261774090.141053413088705
800.9538308364554880.09233832708902430.0461691635445121
810.9478059711621960.1043880576756090.0521940288378043
820.9528257033621350.09434859327573070.0471742966378653
830.9446506512683710.1106986974632570.0553493487316287
840.9356908820081040.1286182359837920.0643091179918961
850.9278538767158540.1442922465682910.0721461232841457
860.9214390576861640.1571218846276710.0785609423138356
870.9157572420540060.1684855158919880.084242757945994
880.9267055429543520.1465889140912960.073294457045648
890.9293071249091020.1413857501817960.070692875090898
900.934807505877260.1303849882454800.0651924941227401
910.9482266535843430.1035466928313140.0517733464156569
920.9396579700335650.120684059932870.060342029966435
930.9300893976199150.139821204760170.069910602380085
940.9197330963315460.1605338073369070.0802669036684537
950.927230616169620.1455387676607610.0727693838303806
960.9228323501797470.1543352996405060.077167649820253
970.9124958393571930.1750083212856140.0875041606428071
980.9164903595721310.1670192808557370.0835096404278687
990.9606478508314680.07870429833706350.0393521491685318
1000.9693065249296550.06138695014069060.0306934750703453
1010.9655562298756620.06888754024867650.0344437701243383
1020.9631270913773740.07374581724525130.0368729086226256
1030.9560743712977970.0878512574044060.043925628702203
1040.9468862889792740.1062274220414530.0531137110207263
1050.93968533114830.1206293377034010.0603146688517003
1060.9531437691405960.09371246171880860.0468562308594043
1070.9441406902646660.1117186194706680.0558593097353342
1080.9465524797703370.1068950404593270.0534475202296633
1090.9422187894158980.1155624211682040.0577812105841018
1100.932802699585910.1343946008281800.0671973004140901
1110.9267277238755220.1465445522489560.0732722761244782
1120.9139970709872340.1720058580255320.0860029290127659
1130.9071059846214080.1857880307571850.0928940153785925
1140.8958290757873840.2083418484252330.104170924212616
1150.880048134272070.2399037314558610.119951865727931
1160.8956501090501620.2086997818996770.104349890949838
1170.9135894952721540.1728210094556920.0864105047278458
1180.9017811682941940.1964376634116130.0982188317058065
1190.8987535503374050.2024928993251900.101246449662595
1200.885796035039170.2284079299216600.114203964960830
1210.9580139816433870.08397203671322560.0419860183566128
1220.9907995570411320.01840088591773650.00920044295886823
1230.9890100861375840.02197982772483160.0109899138624158
1240.9865380761117450.02692384777650940.0134619238882547
1250.986338255723270.02732348855345910.0136617442767295
1260.9838988740377820.03220225192443620.0161011259622181
1270.9800296193132080.03994076137358340.0199703806867917
1280.9790687151592680.04186256968146490.0209312848407325
1290.9738552397558480.05228952048830330.0261447602441516
1300.9738575173022040.05228496539559180.0261424826977959
1310.9679275838497160.06414483230056750.0320724161502837
1320.9613742813929820.07725143721403640.0386257186070182
1330.9604562536300030.07908749273999480.0395437463699974
1340.9546285474670870.09074290506582620.0453714525329131
1350.959018318456060.08196336308787890.0409816815439394
1360.9538146710317390.09237065793652280.0461853289682614
1370.9502370312624440.09952593747511150.0497629687375558
1380.9449326282238950.110134743552210.0550673717761051
1390.934480400342510.1310391993149810.0655195996574905
1400.927391977422440.1452160451551200.0726080225775599
1410.9243114697813210.1513770604373570.0756885302186787
1420.9115704510949180.1768590978101640.0884295489050819
1430.8960917674031650.207816465193670.103908232596835
1440.884081948833120.2318361023337580.115918051166879
1450.8840324232368720.2319351535262550.115967576763128
1460.8701984925645450.2596030148709110.129801507435455
1470.8620681430206840.2758637139586320.137931856979316
1480.8433371927496020.3133256145007960.156662807250398
1490.855604378541950.2887912429160990.144395621458050
1500.8558605792121180.2882788415757630.144139420787882
1510.9260372113420040.1479255773159910.0739627886579956
1520.9193902583822470.1612194832355060.0806097416177529
1530.9348932986647860.1302134026704290.0651067013352143
1540.921577542116230.1568449157675400.0784224578837699
1550.9065110967868480.1869778064263040.0934889032131521
1560.899093081688670.201813836622660.10090691831133
1570.8941793793500380.2116412412999240.105820620649962
1580.8779970507081260.2440058985837480.122002949291874
1590.8571848957226230.2856302085547540.142815104277377
1600.8461142815543120.3077714368913760.153885718445688
1610.8409221247898890.3181557504202220.159077875210111
1620.8457235944272260.3085528111455490.154276405572774
1630.9065439236563120.1869121526873760.0934560763436879
1640.902072636994070.195854726011860.09792736300593
1650.8838628488995470.2322743022009050.116137151100453
1660.8831109787913810.2337780424172370.116889021208619
1670.8858713215818640.2282573568362720.114128678418136
1680.8650878224363980.2698243551272040.134912177563602
1690.841041214635940.3179175707281210.158958785364060
1700.8286286894127210.3427426211745580.171371310587279
1710.8046350005173130.3907299989653740.195364999482687
1720.7844545064350720.4310909871298560.215545493564928
1730.7527949537112040.4944100925775910.247205046288796
1740.7267123960180730.5465752079638540.273287603981927
1750.6905503225775150.618899354844970.309449677422485
1760.6557209615829920.6885580768340160.344279038417008
1770.6180779387148120.7638441225703760.381922061285188
1780.5810124384740150.837975123051970.418987561525985
1790.5543367284667880.8913265430664240.445663271533212
1800.5203467151785940.9593065696428130.479653284821406
1810.4815564332518710.9631128665037430.518443566748129
1820.4717205178858080.9434410357716170.528279482114192
1830.4530038575817880.9060077151635760.546996142418212
1840.5343067483760690.9313865032478620.465693251623931
1850.7240857302588960.5518285394822090.275914269741104
1860.9027158284745770.1945683430508460.097284171525423
1870.897423164339190.2051536713216210.102576835660811
1880.9286946468826060.1426107062347890.0713053531173944
1890.9125402424864350.1749195150271300.0874597575135648
1900.904787282112240.1904254357755210.0952127178877603
1910.9137649052838650.172470189432270.086235094716135
1920.903057900983720.1938841980325610.0969420990162803
1930.885507655603370.2289846887932610.114492344396630
1940.8597284329950140.2805431340099720.140271567004986
1950.8370714300458140.3258571399083710.162928569954186
1960.8898208177455270.2203583645089470.110179182254473
1970.8637686861784840.2724626276430310.136231313821516
1980.8406244427065120.3187511145869760.159375557293488
1990.8076326992140820.3847346015718370.192367300785918
2000.7852722995128660.4294554009742690.214727700487134
2010.7471047991105470.5057904017789060.252895200889453
2020.780316047894210.439367904211580.21968395210579
2030.7448447247018080.5103105505963830.255155275298192
2040.7402197360579550.5195605278840910.259780263942045
2050.7001840115788120.5996319768423760.299815988421188
2060.6577354595948670.6845290808102670.342264540405133
2070.604335411706610.791329176586780.39566458829339
2080.5522335888542130.8955328222915740.447766411145787
2090.5358734131884910.9282531736230190.464126586811509
2100.592318665471430.815362669057140.40768133452857
2110.5352549923290440.9294900153419110.464745007670956
2120.4745710285949080.9491420571898170.525428971405092
2130.6401293173435460.7197413653129080.359870682656454
2140.5983982551185980.8032034897628040.401601744881402
2150.6143647132333380.7712705735333240.385635286766662
2160.5487707107808220.9024585784383570.451229289219178
2170.5523417067602130.8953165864795750.447658293239787
2180.4959966542412390.9919933084824770.504003345758761
2190.444558697669090.889117395338180.55544130233091
2200.4691344463069720.9382688926139440.530865553693028
2210.4100187743326040.8200375486652080.589981225667396
2220.3357256723315510.6714513446631010.66427432766845
2230.4508220294653170.9016440589306340.549177970534683
2240.4098777536516290.8197555073032570.590122246348371
2250.5062859125156650.9874281749686690.493714087484335
2260.4150974229498450.830194845899690.584902577050155
2270.5517443390447760.8965113219104470.448255660955224
2280.480506948336340.961013896672680.51949305166366
2290.598420516225080.803158967549840.40157948377492
2300.5831541081809120.8336917836381760.416845891819088
2310.8657047784103080.2685904431793850.134295221589692
2320.768852904952170.462294190095660.23114709504783

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.597446407623232 & 0.805107184753535 & 0.402553592376768 \tabularnewline
9 & 0.466738494429124 & 0.933476988858247 & 0.533261505570876 \tabularnewline
10 & 0.321899744726942 & 0.643799489453884 & 0.678100255273058 \tabularnewline
11 & 0.350894288546905 & 0.701788577093809 & 0.649105711453095 \tabularnewline
12 & 0.269968261233995 & 0.539936522467991 & 0.730031738766004 \tabularnewline
13 & 0.221492720146526 & 0.442985440293052 & 0.778507279853474 \tabularnewline
14 & 0.200659259824317 & 0.401318519648634 & 0.799340740175683 \tabularnewline
15 & 0.349215312759481 & 0.698430625518962 & 0.650784687240519 \tabularnewline
16 & 0.944552725120053 & 0.110894549759893 & 0.0554472748799466 \tabularnewline
17 & 0.974493843845538 & 0.0510123123089236 & 0.0255061561544618 \tabularnewline
18 & 0.996512841585981 & 0.00697431682803777 & 0.00348715841401889 \tabularnewline
19 & 0.996311790100958 & 0.00737641979808345 & 0.00368820989904172 \tabularnewline
20 & 0.995948177674056 & 0.0081036446518873 & 0.00405182232594365 \tabularnewline
21 & 0.994177953017572 & 0.0116440939648556 & 0.00582204698242778 \tabularnewline
22 & 0.991113448066526 & 0.0177731038669474 & 0.0088865519334737 \tabularnewline
23 & 0.98786243280204 & 0.0242751343959224 & 0.0121375671979612 \tabularnewline
24 & 0.982647753425294 & 0.0347044931494123 & 0.0173522465747062 \tabularnewline
25 & 0.977421545076747 & 0.0451569098465066 & 0.0225784549232533 \tabularnewline
26 & 0.975188013667534 & 0.0496239726649321 & 0.0248119863324660 \tabularnewline
27 & 0.985498223229746 & 0.0290035535405072 & 0.0145017767702536 \tabularnewline
28 & 0.98030358526431 & 0.0393928294713796 & 0.0196964147356898 \tabularnewline
29 & 0.98082694109455 & 0.0383461178109011 & 0.0191730589054505 \tabularnewline
30 & 0.978762865281175 & 0.04247426943765 & 0.021237134718825 \tabularnewline
31 & 0.977651503595605 & 0.0446969928087892 & 0.0223484964043946 \tabularnewline
32 & 0.986335798054615 & 0.0273284038907691 & 0.0136642019453845 \tabularnewline
33 & 0.991709082001422 & 0.0165818359971561 & 0.00829091799857804 \tabularnewline
34 & 0.998093080284634 & 0.00381383943073315 & 0.00190691971536657 \tabularnewline
35 & 0.99730198099811 & 0.00539603800378031 & 0.00269801900189015 \tabularnewline
36 & 0.996205941526133 & 0.00758811694773366 & 0.00379405847386683 \tabularnewline
37 & 0.99486466803945 & 0.0102706639211006 & 0.00513533196055029 \tabularnewline
38 & 0.992699850671551 & 0.0146002986568972 & 0.0073001493284486 \tabularnewline
39 & 0.98989733785148 & 0.0202053242970389 & 0.0101026621485195 \tabularnewline
40 & 0.986760049015006 & 0.0264799019699881 & 0.0132399509849940 \tabularnewline
41 & 0.982336652794824 & 0.0353266944103518 & 0.0176633472051759 \tabularnewline
42 & 0.979824678418027 & 0.0403506431639454 & 0.0201753215819727 \tabularnewline
43 & 0.991327034031614 & 0.0173459319367712 & 0.00867296596838558 \tabularnewline
44 & 0.989059681597237 & 0.0218806368055252 & 0.0109403184027626 \tabularnewline
45 & 0.986972440760252 & 0.0260551184794951 & 0.0130275592397476 \tabularnewline
46 & 0.986913399982049 & 0.0261732000359022 & 0.0130866000179511 \tabularnewline
47 & 0.98468456546046 & 0.0306308690790781 & 0.0153154345395391 \tabularnewline
48 & 0.979733908808978 & 0.0405321823820440 & 0.0202660911910220 \tabularnewline
49 & 0.97760725715512 & 0.0447854856897585 & 0.0223927428448793 \tabularnewline
50 & 0.974533456020051 & 0.0509330879598978 & 0.0254665439799489 \tabularnewline
51 & 0.970083683484018 & 0.0598326330319634 & 0.0299163165159817 \tabularnewline
52 & 0.968830038777815 & 0.0623399224443707 & 0.0311699612221853 \tabularnewline
53 & 0.960334922799793 & 0.0793301544004133 & 0.0396650772002066 \tabularnewline
54 & 0.950885781574146 & 0.0982284368517085 & 0.0491142184258542 \tabularnewline
55 & 0.946878052549548 & 0.106243894900905 & 0.0531219474504524 \tabularnewline
56 & 0.93474616677482 & 0.130507666450359 & 0.0652538332251797 \tabularnewline
57 & 0.927135724604817 & 0.145728550790366 & 0.0728642753951829 \tabularnewline
58 & 0.924701475501536 & 0.150597048996928 & 0.0752985244984638 \tabularnewline
59 & 0.919986714882534 & 0.160026570234933 & 0.0800132851174663 \tabularnewline
60 & 0.94056832720377 & 0.118863345592462 & 0.0594316727962309 \tabularnewline
61 & 0.93315303815646 & 0.133693923687081 & 0.0668469618435407 \tabularnewline
62 & 0.918980136142252 & 0.162039727715496 & 0.081019863857748 \tabularnewline
63 & 0.910520210875576 & 0.178959578248848 & 0.0894797891244238 \tabularnewline
64 & 0.893548848778191 & 0.212902302443617 & 0.106451151221809 \tabularnewline
65 & 0.873834221128905 & 0.252331557742189 & 0.126165778871095 \tabularnewline
66 & 0.906805296518643 & 0.186389406962715 & 0.0931947034813575 \tabularnewline
67 & 0.893667058509668 & 0.212665882980663 & 0.106332941490332 \tabularnewline
68 & 0.914556719391826 & 0.170886561216348 & 0.0854432806081738 \tabularnewline
69 & 0.901079592679231 & 0.197840814641538 & 0.0989204073207688 \tabularnewline
70 & 0.88443814326258 & 0.231123713474839 & 0.115561856737419 \tabularnewline
71 & 0.910200136680854 & 0.179599726638292 & 0.089799863319146 \tabularnewline
72 & 0.89772199520275 & 0.2045560095945 & 0.10227800479725 \tabularnewline
73 & 0.91646122805575 & 0.167077543888501 & 0.0835387719442506 \tabularnewline
74 & 0.906451788953803 & 0.187096422092394 & 0.0935482110461972 \tabularnewline
75 & 0.902925963671145 & 0.19414807265771 & 0.097074036328855 \tabularnewline
76 & 0.906927276655336 & 0.186145446689328 & 0.0930727233446642 \tabularnewline
77 & 0.890909140948655 & 0.21818171810269 & 0.109090859051345 \tabularnewline
78 & 0.879773196159884 & 0.240453607680231 & 0.120226803840116 \tabularnewline
79 & 0.858946586911295 & 0.282106826177409 & 0.141053413088705 \tabularnewline
80 & 0.953830836455488 & 0.0923383270890243 & 0.0461691635445121 \tabularnewline
81 & 0.947805971162196 & 0.104388057675609 & 0.0521940288378043 \tabularnewline
82 & 0.952825703362135 & 0.0943485932757307 & 0.0471742966378653 \tabularnewline
83 & 0.944650651268371 & 0.110698697463257 & 0.0553493487316287 \tabularnewline
84 & 0.935690882008104 & 0.128618235983792 & 0.0643091179918961 \tabularnewline
85 & 0.927853876715854 & 0.144292246568291 & 0.0721461232841457 \tabularnewline
86 & 0.921439057686164 & 0.157121884627671 & 0.0785609423138356 \tabularnewline
87 & 0.915757242054006 & 0.168485515891988 & 0.084242757945994 \tabularnewline
88 & 0.926705542954352 & 0.146588914091296 & 0.073294457045648 \tabularnewline
89 & 0.929307124909102 & 0.141385750181796 & 0.070692875090898 \tabularnewline
90 & 0.93480750587726 & 0.130384988245480 & 0.0651924941227401 \tabularnewline
91 & 0.948226653584343 & 0.103546692831314 & 0.0517733464156569 \tabularnewline
92 & 0.939657970033565 & 0.12068405993287 & 0.060342029966435 \tabularnewline
93 & 0.930089397619915 & 0.13982120476017 & 0.069910602380085 \tabularnewline
94 & 0.919733096331546 & 0.160533807336907 & 0.0802669036684537 \tabularnewline
95 & 0.92723061616962 & 0.145538767660761 & 0.0727693838303806 \tabularnewline
96 & 0.922832350179747 & 0.154335299640506 & 0.077167649820253 \tabularnewline
97 & 0.912495839357193 & 0.175008321285614 & 0.0875041606428071 \tabularnewline
98 & 0.916490359572131 & 0.167019280855737 & 0.0835096404278687 \tabularnewline
99 & 0.960647850831468 & 0.0787042983370635 & 0.0393521491685318 \tabularnewline
100 & 0.969306524929655 & 0.0613869501406906 & 0.0306934750703453 \tabularnewline
101 & 0.965556229875662 & 0.0688875402486765 & 0.0344437701243383 \tabularnewline
102 & 0.963127091377374 & 0.0737458172452513 & 0.0368729086226256 \tabularnewline
103 & 0.956074371297797 & 0.087851257404406 & 0.043925628702203 \tabularnewline
104 & 0.946886288979274 & 0.106227422041453 & 0.0531137110207263 \tabularnewline
105 & 0.9396853311483 & 0.120629337703401 & 0.0603146688517003 \tabularnewline
106 & 0.953143769140596 & 0.0937124617188086 & 0.0468562308594043 \tabularnewline
107 & 0.944140690264666 & 0.111718619470668 & 0.0558593097353342 \tabularnewline
108 & 0.946552479770337 & 0.106895040459327 & 0.0534475202296633 \tabularnewline
109 & 0.942218789415898 & 0.115562421168204 & 0.0577812105841018 \tabularnewline
110 & 0.93280269958591 & 0.134394600828180 & 0.0671973004140901 \tabularnewline
111 & 0.926727723875522 & 0.146544552248956 & 0.0732722761244782 \tabularnewline
112 & 0.913997070987234 & 0.172005858025532 & 0.0860029290127659 \tabularnewline
113 & 0.907105984621408 & 0.185788030757185 & 0.0928940153785925 \tabularnewline
114 & 0.895829075787384 & 0.208341848425233 & 0.104170924212616 \tabularnewline
115 & 0.88004813427207 & 0.239903731455861 & 0.119951865727931 \tabularnewline
116 & 0.895650109050162 & 0.208699781899677 & 0.104349890949838 \tabularnewline
117 & 0.913589495272154 & 0.172821009455692 & 0.0864105047278458 \tabularnewline
118 & 0.901781168294194 & 0.196437663411613 & 0.0982188317058065 \tabularnewline
119 & 0.898753550337405 & 0.202492899325190 & 0.101246449662595 \tabularnewline
120 & 0.88579603503917 & 0.228407929921660 & 0.114203964960830 \tabularnewline
121 & 0.958013981643387 & 0.0839720367132256 & 0.0419860183566128 \tabularnewline
122 & 0.990799557041132 & 0.0184008859177365 & 0.00920044295886823 \tabularnewline
123 & 0.989010086137584 & 0.0219798277248316 & 0.0109899138624158 \tabularnewline
124 & 0.986538076111745 & 0.0269238477765094 & 0.0134619238882547 \tabularnewline
125 & 0.98633825572327 & 0.0273234885534591 & 0.0136617442767295 \tabularnewline
126 & 0.983898874037782 & 0.0322022519244362 & 0.0161011259622181 \tabularnewline
127 & 0.980029619313208 & 0.0399407613735834 & 0.0199703806867917 \tabularnewline
128 & 0.979068715159268 & 0.0418625696814649 & 0.0209312848407325 \tabularnewline
129 & 0.973855239755848 & 0.0522895204883033 & 0.0261447602441516 \tabularnewline
130 & 0.973857517302204 & 0.0522849653955918 & 0.0261424826977959 \tabularnewline
131 & 0.967927583849716 & 0.0641448323005675 & 0.0320724161502837 \tabularnewline
132 & 0.961374281392982 & 0.0772514372140364 & 0.0386257186070182 \tabularnewline
133 & 0.960456253630003 & 0.0790874927399948 & 0.0395437463699974 \tabularnewline
134 & 0.954628547467087 & 0.0907429050658262 & 0.0453714525329131 \tabularnewline
135 & 0.95901831845606 & 0.0819633630878789 & 0.0409816815439394 \tabularnewline
136 & 0.953814671031739 & 0.0923706579365228 & 0.0461853289682614 \tabularnewline
137 & 0.950237031262444 & 0.0995259374751115 & 0.0497629687375558 \tabularnewline
138 & 0.944932628223895 & 0.11013474355221 & 0.0550673717761051 \tabularnewline
139 & 0.93448040034251 & 0.131039199314981 & 0.0655195996574905 \tabularnewline
140 & 0.92739197742244 & 0.145216045155120 & 0.0726080225775599 \tabularnewline
141 & 0.924311469781321 & 0.151377060437357 & 0.0756885302186787 \tabularnewline
142 & 0.911570451094918 & 0.176859097810164 & 0.0884295489050819 \tabularnewline
143 & 0.896091767403165 & 0.20781646519367 & 0.103908232596835 \tabularnewline
144 & 0.88408194883312 & 0.231836102333758 & 0.115918051166879 \tabularnewline
145 & 0.884032423236872 & 0.231935153526255 & 0.115967576763128 \tabularnewline
146 & 0.870198492564545 & 0.259603014870911 & 0.129801507435455 \tabularnewline
147 & 0.862068143020684 & 0.275863713958632 & 0.137931856979316 \tabularnewline
148 & 0.843337192749602 & 0.313325614500796 & 0.156662807250398 \tabularnewline
149 & 0.85560437854195 & 0.288791242916099 & 0.144395621458050 \tabularnewline
150 & 0.855860579212118 & 0.288278841575763 & 0.144139420787882 \tabularnewline
151 & 0.926037211342004 & 0.147925577315991 & 0.0739627886579956 \tabularnewline
152 & 0.919390258382247 & 0.161219483235506 & 0.0806097416177529 \tabularnewline
153 & 0.934893298664786 & 0.130213402670429 & 0.0651067013352143 \tabularnewline
154 & 0.92157754211623 & 0.156844915767540 & 0.0784224578837699 \tabularnewline
155 & 0.906511096786848 & 0.186977806426304 & 0.0934889032131521 \tabularnewline
156 & 0.89909308168867 & 0.20181383662266 & 0.10090691831133 \tabularnewline
157 & 0.894179379350038 & 0.211641241299924 & 0.105820620649962 \tabularnewline
158 & 0.877997050708126 & 0.244005898583748 & 0.122002949291874 \tabularnewline
159 & 0.857184895722623 & 0.285630208554754 & 0.142815104277377 \tabularnewline
160 & 0.846114281554312 & 0.307771436891376 & 0.153885718445688 \tabularnewline
161 & 0.840922124789889 & 0.318155750420222 & 0.159077875210111 \tabularnewline
162 & 0.845723594427226 & 0.308552811145549 & 0.154276405572774 \tabularnewline
163 & 0.906543923656312 & 0.186912152687376 & 0.0934560763436879 \tabularnewline
164 & 0.90207263699407 & 0.19585472601186 & 0.09792736300593 \tabularnewline
165 & 0.883862848899547 & 0.232274302200905 & 0.116137151100453 \tabularnewline
166 & 0.883110978791381 & 0.233778042417237 & 0.116889021208619 \tabularnewline
167 & 0.885871321581864 & 0.228257356836272 & 0.114128678418136 \tabularnewline
168 & 0.865087822436398 & 0.269824355127204 & 0.134912177563602 \tabularnewline
169 & 0.84104121463594 & 0.317917570728121 & 0.158958785364060 \tabularnewline
170 & 0.828628689412721 & 0.342742621174558 & 0.171371310587279 \tabularnewline
171 & 0.804635000517313 & 0.390729998965374 & 0.195364999482687 \tabularnewline
172 & 0.784454506435072 & 0.431090987129856 & 0.215545493564928 \tabularnewline
173 & 0.752794953711204 & 0.494410092577591 & 0.247205046288796 \tabularnewline
174 & 0.726712396018073 & 0.546575207963854 & 0.273287603981927 \tabularnewline
175 & 0.690550322577515 & 0.61889935484497 & 0.309449677422485 \tabularnewline
176 & 0.655720961582992 & 0.688558076834016 & 0.344279038417008 \tabularnewline
177 & 0.618077938714812 & 0.763844122570376 & 0.381922061285188 \tabularnewline
178 & 0.581012438474015 & 0.83797512305197 & 0.418987561525985 \tabularnewline
179 & 0.554336728466788 & 0.891326543066424 & 0.445663271533212 \tabularnewline
180 & 0.520346715178594 & 0.959306569642813 & 0.479653284821406 \tabularnewline
181 & 0.481556433251871 & 0.963112866503743 & 0.518443566748129 \tabularnewline
182 & 0.471720517885808 & 0.943441035771617 & 0.528279482114192 \tabularnewline
183 & 0.453003857581788 & 0.906007715163576 & 0.546996142418212 \tabularnewline
184 & 0.534306748376069 & 0.931386503247862 & 0.465693251623931 \tabularnewline
185 & 0.724085730258896 & 0.551828539482209 & 0.275914269741104 \tabularnewline
186 & 0.902715828474577 & 0.194568343050846 & 0.097284171525423 \tabularnewline
187 & 0.89742316433919 & 0.205153671321621 & 0.102576835660811 \tabularnewline
188 & 0.928694646882606 & 0.142610706234789 & 0.0713053531173944 \tabularnewline
189 & 0.912540242486435 & 0.174919515027130 & 0.0874597575135648 \tabularnewline
190 & 0.90478728211224 & 0.190425435775521 & 0.0952127178877603 \tabularnewline
191 & 0.913764905283865 & 0.17247018943227 & 0.086235094716135 \tabularnewline
192 & 0.90305790098372 & 0.193884198032561 & 0.0969420990162803 \tabularnewline
193 & 0.88550765560337 & 0.228984688793261 & 0.114492344396630 \tabularnewline
194 & 0.859728432995014 & 0.280543134009972 & 0.140271567004986 \tabularnewline
195 & 0.837071430045814 & 0.325857139908371 & 0.162928569954186 \tabularnewline
196 & 0.889820817745527 & 0.220358364508947 & 0.110179182254473 \tabularnewline
197 & 0.863768686178484 & 0.272462627643031 & 0.136231313821516 \tabularnewline
198 & 0.840624442706512 & 0.318751114586976 & 0.159375557293488 \tabularnewline
199 & 0.807632699214082 & 0.384734601571837 & 0.192367300785918 \tabularnewline
200 & 0.785272299512866 & 0.429455400974269 & 0.214727700487134 \tabularnewline
201 & 0.747104799110547 & 0.505790401778906 & 0.252895200889453 \tabularnewline
202 & 0.78031604789421 & 0.43936790421158 & 0.21968395210579 \tabularnewline
203 & 0.744844724701808 & 0.510310550596383 & 0.255155275298192 \tabularnewline
204 & 0.740219736057955 & 0.519560527884091 & 0.259780263942045 \tabularnewline
205 & 0.700184011578812 & 0.599631976842376 & 0.299815988421188 \tabularnewline
206 & 0.657735459594867 & 0.684529080810267 & 0.342264540405133 \tabularnewline
207 & 0.60433541170661 & 0.79132917658678 & 0.39566458829339 \tabularnewline
208 & 0.552233588854213 & 0.895532822291574 & 0.447766411145787 \tabularnewline
209 & 0.535873413188491 & 0.928253173623019 & 0.464126586811509 \tabularnewline
210 & 0.59231866547143 & 0.81536266905714 & 0.40768133452857 \tabularnewline
211 & 0.535254992329044 & 0.929490015341911 & 0.464745007670956 \tabularnewline
212 & 0.474571028594908 & 0.949142057189817 & 0.525428971405092 \tabularnewline
213 & 0.640129317343546 & 0.719741365312908 & 0.359870682656454 \tabularnewline
214 & 0.598398255118598 & 0.803203489762804 & 0.401601744881402 \tabularnewline
215 & 0.614364713233338 & 0.771270573533324 & 0.385635286766662 \tabularnewline
216 & 0.548770710780822 & 0.902458578438357 & 0.451229289219178 \tabularnewline
217 & 0.552341706760213 & 0.895316586479575 & 0.447658293239787 \tabularnewline
218 & 0.495996654241239 & 0.991993308482477 & 0.504003345758761 \tabularnewline
219 & 0.44455869766909 & 0.88911739533818 & 0.55544130233091 \tabularnewline
220 & 0.469134446306972 & 0.938268892613944 & 0.530865553693028 \tabularnewline
221 & 0.410018774332604 & 0.820037548665208 & 0.589981225667396 \tabularnewline
222 & 0.335725672331551 & 0.671451344663101 & 0.66427432766845 \tabularnewline
223 & 0.450822029465317 & 0.901644058930634 & 0.549177970534683 \tabularnewline
224 & 0.409877753651629 & 0.819755507303257 & 0.590122246348371 \tabularnewline
225 & 0.506285912515665 & 0.987428174968669 & 0.493714087484335 \tabularnewline
226 & 0.415097422949845 & 0.83019484589969 & 0.584902577050155 \tabularnewline
227 & 0.551744339044776 & 0.896511321910447 & 0.448255660955224 \tabularnewline
228 & 0.48050694833634 & 0.96101389667268 & 0.51949305166366 \tabularnewline
229 & 0.59842051622508 & 0.80315896754984 & 0.40157948377492 \tabularnewline
230 & 0.583154108180912 & 0.833691783638176 & 0.416845891819088 \tabularnewline
231 & 0.865704778410308 & 0.268590443179385 & 0.134295221589692 \tabularnewline
232 & 0.76885290495217 & 0.46229419009566 & 0.23114709504783 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108606&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]8[/C][C]0.597446407623232[/C][C]0.805107184753535[/C][C]0.402553592376768[/C][/ROW]
[ROW][C]9[/C][C]0.466738494429124[/C][C]0.933476988858247[/C][C]0.533261505570876[/C][/ROW]
[ROW][C]10[/C][C]0.321899744726942[/C][C]0.643799489453884[/C][C]0.678100255273058[/C][/ROW]
[ROW][C]11[/C][C]0.350894288546905[/C][C]0.701788577093809[/C][C]0.649105711453095[/C][/ROW]
[ROW][C]12[/C][C]0.269968261233995[/C][C]0.539936522467991[/C][C]0.730031738766004[/C][/ROW]
[ROW][C]13[/C][C]0.221492720146526[/C][C]0.442985440293052[/C][C]0.778507279853474[/C][/ROW]
[ROW][C]14[/C][C]0.200659259824317[/C][C]0.401318519648634[/C][C]0.799340740175683[/C][/ROW]
[ROW][C]15[/C][C]0.349215312759481[/C][C]0.698430625518962[/C][C]0.650784687240519[/C][/ROW]
[ROW][C]16[/C][C]0.944552725120053[/C][C]0.110894549759893[/C][C]0.0554472748799466[/C][/ROW]
[ROW][C]17[/C][C]0.974493843845538[/C][C]0.0510123123089236[/C][C]0.0255061561544618[/C][/ROW]
[ROW][C]18[/C][C]0.996512841585981[/C][C]0.00697431682803777[/C][C]0.00348715841401889[/C][/ROW]
[ROW][C]19[/C][C]0.996311790100958[/C][C]0.00737641979808345[/C][C]0.00368820989904172[/C][/ROW]
[ROW][C]20[/C][C]0.995948177674056[/C][C]0.0081036446518873[/C][C]0.00405182232594365[/C][/ROW]
[ROW][C]21[/C][C]0.994177953017572[/C][C]0.0116440939648556[/C][C]0.00582204698242778[/C][/ROW]
[ROW][C]22[/C][C]0.991113448066526[/C][C]0.0177731038669474[/C][C]0.0088865519334737[/C][/ROW]
[ROW][C]23[/C][C]0.98786243280204[/C][C]0.0242751343959224[/C][C]0.0121375671979612[/C][/ROW]
[ROW][C]24[/C][C]0.982647753425294[/C][C]0.0347044931494123[/C][C]0.0173522465747062[/C][/ROW]
[ROW][C]25[/C][C]0.977421545076747[/C][C]0.0451569098465066[/C][C]0.0225784549232533[/C][/ROW]
[ROW][C]26[/C][C]0.975188013667534[/C][C]0.0496239726649321[/C][C]0.0248119863324660[/C][/ROW]
[ROW][C]27[/C][C]0.985498223229746[/C][C]0.0290035535405072[/C][C]0.0145017767702536[/C][/ROW]
[ROW][C]28[/C][C]0.98030358526431[/C][C]0.0393928294713796[/C][C]0.0196964147356898[/C][/ROW]
[ROW][C]29[/C][C]0.98082694109455[/C][C]0.0383461178109011[/C][C]0.0191730589054505[/C][/ROW]
[ROW][C]30[/C][C]0.978762865281175[/C][C]0.04247426943765[/C][C]0.021237134718825[/C][/ROW]
[ROW][C]31[/C][C]0.977651503595605[/C][C]0.0446969928087892[/C][C]0.0223484964043946[/C][/ROW]
[ROW][C]32[/C][C]0.986335798054615[/C][C]0.0273284038907691[/C][C]0.0136642019453845[/C][/ROW]
[ROW][C]33[/C][C]0.991709082001422[/C][C]0.0165818359971561[/C][C]0.00829091799857804[/C][/ROW]
[ROW][C]34[/C][C]0.998093080284634[/C][C]0.00381383943073315[/C][C]0.00190691971536657[/C][/ROW]
[ROW][C]35[/C][C]0.99730198099811[/C][C]0.00539603800378031[/C][C]0.00269801900189015[/C][/ROW]
[ROW][C]36[/C][C]0.996205941526133[/C][C]0.00758811694773366[/C][C]0.00379405847386683[/C][/ROW]
[ROW][C]37[/C][C]0.99486466803945[/C][C]0.0102706639211006[/C][C]0.00513533196055029[/C][/ROW]
[ROW][C]38[/C][C]0.992699850671551[/C][C]0.0146002986568972[/C][C]0.0073001493284486[/C][/ROW]
[ROW][C]39[/C][C]0.98989733785148[/C][C]0.0202053242970389[/C][C]0.0101026621485195[/C][/ROW]
[ROW][C]40[/C][C]0.986760049015006[/C][C]0.0264799019699881[/C][C]0.0132399509849940[/C][/ROW]
[ROW][C]41[/C][C]0.982336652794824[/C][C]0.0353266944103518[/C][C]0.0176633472051759[/C][/ROW]
[ROW][C]42[/C][C]0.979824678418027[/C][C]0.0403506431639454[/C][C]0.0201753215819727[/C][/ROW]
[ROW][C]43[/C][C]0.991327034031614[/C][C]0.0173459319367712[/C][C]0.00867296596838558[/C][/ROW]
[ROW][C]44[/C][C]0.989059681597237[/C][C]0.0218806368055252[/C][C]0.0109403184027626[/C][/ROW]
[ROW][C]45[/C][C]0.986972440760252[/C][C]0.0260551184794951[/C][C]0.0130275592397476[/C][/ROW]
[ROW][C]46[/C][C]0.986913399982049[/C][C]0.0261732000359022[/C][C]0.0130866000179511[/C][/ROW]
[ROW][C]47[/C][C]0.98468456546046[/C][C]0.0306308690790781[/C][C]0.0153154345395391[/C][/ROW]
[ROW][C]48[/C][C]0.979733908808978[/C][C]0.0405321823820440[/C][C]0.0202660911910220[/C][/ROW]
[ROW][C]49[/C][C]0.97760725715512[/C][C]0.0447854856897585[/C][C]0.0223927428448793[/C][/ROW]
[ROW][C]50[/C][C]0.974533456020051[/C][C]0.0509330879598978[/C][C]0.0254665439799489[/C][/ROW]
[ROW][C]51[/C][C]0.970083683484018[/C][C]0.0598326330319634[/C][C]0.0299163165159817[/C][/ROW]
[ROW][C]52[/C][C]0.968830038777815[/C][C]0.0623399224443707[/C][C]0.0311699612221853[/C][/ROW]
[ROW][C]53[/C][C]0.960334922799793[/C][C]0.0793301544004133[/C][C]0.0396650772002066[/C][/ROW]
[ROW][C]54[/C][C]0.950885781574146[/C][C]0.0982284368517085[/C][C]0.0491142184258542[/C][/ROW]
[ROW][C]55[/C][C]0.946878052549548[/C][C]0.106243894900905[/C][C]0.0531219474504524[/C][/ROW]
[ROW][C]56[/C][C]0.93474616677482[/C][C]0.130507666450359[/C][C]0.0652538332251797[/C][/ROW]
[ROW][C]57[/C][C]0.927135724604817[/C][C]0.145728550790366[/C][C]0.0728642753951829[/C][/ROW]
[ROW][C]58[/C][C]0.924701475501536[/C][C]0.150597048996928[/C][C]0.0752985244984638[/C][/ROW]
[ROW][C]59[/C][C]0.919986714882534[/C][C]0.160026570234933[/C][C]0.0800132851174663[/C][/ROW]
[ROW][C]60[/C][C]0.94056832720377[/C][C]0.118863345592462[/C][C]0.0594316727962309[/C][/ROW]
[ROW][C]61[/C][C]0.93315303815646[/C][C]0.133693923687081[/C][C]0.0668469618435407[/C][/ROW]
[ROW][C]62[/C][C]0.918980136142252[/C][C]0.162039727715496[/C][C]0.081019863857748[/C][/ROW]
[ROW][C]63[/C][C]0.910520210875576[/C][C]0.178959578248848[/C][C]0.0894797891244238[/C][/ROW]
[ROW][C]64[/C][C]0.893548848778191[/C][C]0.212902302443617[/C][C]0.106451151221809[/C][/ROW]
[ROW][C]65[/C][C]0.873834221128905[/C][C]0.252331557742189[/C][C]0.126165778871095[/C][/ROW]
[ROW][C]66[/C][C]0.906805296518643[/C][C]0.186389406962715[/C][C]0.0931947034813575[/C][/ROW]
[ROW][C]67[/C][C]0.893667058509668[/C][C]0.212665882980663[/C][C]0.106332941490332[/C][/ROW]
[ROW][C]68[/C][C]0.914556719391826[/C][C]0.170886561216348[/C][C]0.0854432806081738[/C][/ROW]
[ROW][C]69[/C][C]0.901079592679231[/C][C]0.197840814641538[/C][C]0.0989204073207688[/C][/ROW]
[ROW][C]70[/C][C]0.88443814326258[/C][C]0.231123713474839[/C][C]0.115561856737419[/C][/ROW]
[ROW][C]71[/C][C]0.910200136680854[/C][C]0.179599726638292[/C][C]0.089799863319146[/C][/ROW]
[ROW][C]72[/C][C]0.89772199520275[/C][C]0.2045560095945[/C][C]0.10227800479725[/C][/ROW]
[ROW][C]73[/C][C]0.91646122805575[/C][C]0.167077543888501[/C][C]0.0835387719442506[/C][/ROW]
[ROW][C]74[/C][C]0.906451788953803[/C][C]0.187096422092394[/C][C]0.0935482110461972[/C][/ROW]
[ROW][C]75[/C][C]0.902925963671145[/C][C]0.19414807265771[/C][C]0.097074036328855[/C][/ROW]
[ROW][C]76[/C][C]0.906927276655336[/C][C]0.186145446689328[/C][C]0.0930727233446642[/C][/ROW]
[ROW][C]77[/C][C]0.890909140948655[/C][C]0.21818171810269[/C][C]0.109090859051345[/C][/ROW]
[ROW][C]78[/C][C]0.879773196159884[/C][C]0.240453607680231[/C][C]0.120226803840116[/C][/ROW]
[ROW][C]79[/C][C]0.858946586911295[/C][C]0.282106826177409[/C][C]0.141053413088705[/C][/ROW]
[ROW][C]80[/C][C]0.953830836455488[/C][C]0.0923383270890243[/C][C]0.0461691635445121[/C][/ROW]
[ROW][C]81[/C][C]0.947805971162196[/C][C]0.104388057675609[/C][C]0.0521940288378043[/C][/ROW]
[ROW][C]82[/C][C]0.952825703362135[/C][C]0.0943485932757307[/C][C]0.0471742966378653[/C][/ROW]
[ROW][C]83[/C][C]0.944650651268371[/C][C]0.110698697463257[/C][C]0.0553493487316287[/C][/ROW]
[ROW][C]84[/C][C]0.935690882008104[/C][C]0.128618235983792[/C][C]0.0643091179918961[/C][/ROW]
[ROW][C]85[/C][C]0.927853876715854[/C][C]0.144292246568291[/C][C]0.0721461232841457[/C][/ROW]
[ROW][C]86[/C][C]0.921439057686164[/C][C]0.157121884627671[/C][C]0.0785609423138356[/C][/ROW]
[ROW][C]87[/C][C]0.915757242054006[/C][C]0.168485515891988[/C][C]0.084242757945994[/C][/ROW]
[ROW][C]88[/C][C]0.926705542954352[/C][C]0.146588914091296[/C][C]0.073294457045648[/C][/ROW]
[ROW][C]89[/C][C]0.929307124909102[/C][C]0.141385750181796[/C][C]0.070692875090898[/C][/ROW]
[ROW][C]90[/C][C]0.93480750587726[/C][C]0.130384988245480[/C][C]0.0651924941227401[/C][/ROW]
[ROW][C]91[/C][C]0.948226653584343[/C][C]0.103546692831314[/C][C]0.0517733464156569[/C][/ROW]
[ROW][C]92[/C][C]0.939657970033565[/C][C]0.12068405993287[/C][C]0.060342029966435[/C][/ROW]
[ROW][C]93[/C][C]0.930089397619915[/C][C]0.13982120476017[/C][C]0.069910602380085[/C][/ROW]
[ROW][C]94[/C][C]0.919733096331546[/C][C]0.160533807336907[/C][C]0.0802669036684537[/C][/ROW]
[ROW][C]95[/C][C]0.92723061616962[/C][C]0.145538767660761[/C][C]0.0727693838303806[/C][/ROW]
[ROW][C]96[/C][C]0.922832350179747[/C][C]0.154335299640506[/C][C]0.077167649820253[/C][/ROW]
[ROW][C]97[/C][C]0.912495839357193[/C][C]0.175008321285614[/C][C]0.0875041606428071[/C][/ROW]
[ROW][C]98[/C][C]0.916490359572131[/C][C]0.167019280855737[/C][C]0.0835096404278687[/C][/ROW]
[ROW][C]99[/C][C]0.960647850831468[/C][C]0.0787042983370635[/C][C]0.0393521491685318[/C][/ROW]
[ROW][C]100[/C][C]0.969306524929655[/C][C]0.0613869501406906[/C][C]0.0306934750703453[/C][/ROW]
[ROW][C]101[/C][C]0.965556229875662[/C][C]0.0688875402486765[/C][C]0.0344437701243383[/C][/ROW]
[ROW][C]102[/C][C]0.963127091377374[/C][C]0.0737458172452513[/C][C]0.0368729086226256[/C][/ROW]
[ROW][C]103[/C][C]0.956074371297797[/C][C]0.087851257404406[/C][C]0.043925628702203[/C][/ROW]
[ROW][C]104[/C][C]0.946886288979274[/C][C]0.106227422041453[/C][C]0.0531137110207263[/C][/ROW]
[ROW][C]105[/C][C]0.9396853311483[/C][C]0.120629337703401[/C][C]0.0603146688517003[/C][/ROW]
[ROW][C]106[/C][C]0.953143769140596[/C][C]0.0937124617188086[/C][C]0.0468562308594043[/C][/ROW]
[ROW][C]107[/C][C]0.944140690264666[/C][C]0.111718619470668[/C][C]0.0558593097353342[/C][/ROW]
[ROW][C]108[/C][C]0.946552479770337[/C][C]0.106895040459327[/C][C]0.0534475202296633[/C][/ROW]
[ROW][C]109[/C][C]0.942218789415898[/C][C]0.115562421168204[/C][C]0.0577812105841018[/C][/ROW]
[ROW][C]110[/C][C]0.93280269958591[/C][C]0.134394600828180[/C][C]0.0671973004140901[/C][/ROW]
[ROW][C]111[/C][C]0.926727723875522[/C][C]0.146544552248956[/C][C]0.0732722761244782[/C][/ROW]
[ROW][C]112[/C][C]0.913997070987234[/C][C]0.172005858025532[/C][C]0.0860029290127659[/C][/ROW]
[ROW][C]113[/C][C]0.907105984621408[/C][C]0.185788030757185[/C][C]0.0928940153785925[/C][/ROW]
[ROW][C]114[/C][C]0.895829075787384[/C][C]0.208341848425233[/C][C]0.104170924212616[/C][/ROW]
[ROW][C]115[/C][C]0.88004813427207[/C][C]0.239903731455861[/C][C]0.119951865727931[/C][/ROW]
[ROW][C]116[/C][C]0.895650109050162[/C][C]0.208699781899677[/C][C]0.104349890949838[/C][/ROW]
[ROW][C]117[/C][C]0.913589495272154[/C][C]0.172821009455692[/C][C]0.0864105047278458[/C][/ROW]
[ROW][C]118[/C][C]0.901781168294194[/C][C]0.196437663411613[/C][C]0.0982188317058065[/C][/ROW]
[ROW][C]119[/C][C]0.898753550337405[/C][C]0.202492899325190[/C][C]0.101246449662595[/C][/ROW]
[ROW][C]120[/C][C]0.88579603503917[/C][C]0.228407929921660[/C][C]0.114203964960830[/C][/ROW]
[ROW][C]121[/C][C]0.958013981643387[/C][C]0.0839720367132256[/C][C]0.0419860183566128[/C][/ROW]
[ROW][C]122[/C][C]0.990799557041132[/C][C]0.0184008859177365[/C][C]0.00920044295886823[/C][/ROW]
[ROW][C]123[/C][C]0.989010086137584[/C][C]0.0219798277248316[/C][C]0.0109899138624158[/C][/ROW]
[ROW][C]124[/C][C]0.986538076111745[/C][C]0.0269238477765094[/C][C]0.0134619238882547[/C][/ROW]
[ROW][C]125[/C][C]0.98633825572327[/C][C]0.0273234885534591[/C][C]0.0136617442767295[/C][/ROW]
[ROW][C]126[/C][C]0.983898874037782[/C][C]0.0322022519244362[/C][C]0.0161011259622181[/C][/ROW]
[ROW][C]127[/C][C]0.980029619313208[/C][C]0.0399407613735834[/C][C]0.0199703806867917[/C][/ROW]
[ROW][C]128[/C][C]0.979068715159268[/C][C]0.0418625696814649[/C][C]0.0209312848407325[/C][/ROW]
[ROW][C]129[/C][C]0.973855239755848[/C][C]0.0522895204883033[/C][C]0.0261447602441516[/C][/ROW]
[ROW][C]130[/C][C]0.973857517302204[/C][C]0.0522849653955918[/C][C]0.0261424826977959[/C][/ROW]
[ROW][C]131[/C][C]0.967927583849716[/C][C]0.0641448323005675[/C][C]0.0320724161502837[/C][/ROW]
[ROW][C]132[/C][C]0.961374281392982[/C][C]0.0772514372140364[/C][C]0.0386257186070182[/C][/ROW]
[ROW][C]133[/C][C]0.960456253630003[/C][C]0.0790874927399948[/C][C]0.0395437463699974[/C][/ROW]
[ROW][C]134[/C][C]0.954628547467087[/C][C]0.0907429050658262[/C][C]0.0453714525329131[/C][/ROW]
[ROW][C]135[/C][C]0.95901831845606[/C][C]0.0819633630878789[/C][C]0.0409816815439394[/C][/ROW]
[ROW][C]136[/C][C]0.953814671031739[/C][C]0.0923706579365228[/C][C]0.0461853289682614[/C][/ROW]
[ROW][C]137[/C][C]0.950237031262444[/C][C]0.0995259374751115[/C][C]0.0497629687375558[/C][/ROW]
[ROW][C]138[/C][C]0.944932628223895[/C][C]0.11013474355221[/C][C]0.0550673717761051[/C][/ROW]
[ROW][C]139[/C][C]0.93448040034251[/C][C]0.131039199314981[/C][C]0.0655195996574905[/C][/ROW]
[ROW][C]140[/C][C]0.92739197742244[/C][C]0.145216045155120[/C][C]0.0726080225775599[/C][/ROW]
[ROW][C]141[/C][C]0.924311469781321[/C][C]0.151377060437357[/C][C]0.0756885302186787[/C][/ROW]
[ROW][C]142[/C][C]0.911570451094918[/C][C]0.176859097810164[/C][C]0.0884295489050819[/C][/ROW]
[ROW][C]143[/C][C]0.896091767403165[/C][C]0.20781646519367[/C][C]0.103908232596835[/C][/ROW]
[ROW][C]144[/C][C]0.88408194883312[/C][C]0.231836102333758[/C][C]0.115918051166879[/C][/ROW]
[ROW][C]145[/C][C]0.884032423236872[/C][C]0.231935153526255[/C][C]0.115967576763128[/C][/ROW]
[ROW][C]146[/C][C]0.870198492564545[/C][C]0.259603014870911[/C][C]0.129801507435455[/C][/ROW]
[ROW][C]147[/C][C]0.862068143020684[/C][C]0.275863713958632[/C][C]0.137931856979316[/C][/ROW]
[ROW][C]148[/C][C]0.843337192749602[/C][C]0.313325614500796[/C][C]0.156662807250398[/C][/ROW]
[ROW][C]149[/C][C]0.85560437854195[/C][C]0.288791242916099[/C][C]0.144395621458050[/C][/ROW]
[ROW][C]150[/C][C]0.855860579212118[/C][C]0.288278841575763[/C][C]0.144139420787882[/C][/ROW]
[ROW][C]151[/C][C]0.926037211342004[/C][C]0.147925577315991[/C][C]0.0739627886579956[/C][/ROW]
[ROW][C]152[/C][C]0.919390258382247[/C][C]0.161219483235506[/C][C]0.0806097416177529[/C][/ROW]
[ROW][C]153[/C][C]0.934893298664786[/C][C]0.130213402670429[/C][C]0.0651067013352143[/C][/ROW]
[ROW][C]154[/C][C]0.92157754211623[/C][C]0.156844915767540[/C][C]0.0784224578837699[/C][/ROW]
[ROW][C]155[/C][C]0.906511096786848[/C][C]0.186977806426304[/C][C]0.0934889032131521[/C][/ROW]
[ROW][C]156[/C][C]0.89909308168867[/C][C]0.20181383662266[/C][C]0.10090691831133[/C][/ROW]
[ROW][C]157[/C][C]0.894179379350038[/C][C]0.211641241299924[/C][C]0.105820620649962[/C][/ROW]
[ROW][C]158[/C][C]0.877997050708126[/C][C]0.244005898583748[/C][C]0.122002949291874[/C][/ROW]
[ROW][C]159[/C][C]0.857184895722623[/C][C]0.285630208554754[/C][C]0.142815104277377[/C][/ROW]
[ROW][C]160[/C][C]0.846114281554312[/C][C]0.307771436891376[/C][C]0.153885718445688[/C][/ROW]
[ROW][C]161[/C][C]0.840922124789889[/C][C]0.318155750420222[/C][C]0.159077875210111[/C][/ROW]
[ROW][C]162[/C][C]0.845723594427226[/C][C]0.308552811145549[/C][C]0.154276405572774[/C][/ROW]
[ROW][C]163[/C][C]0.906543923656312[/C][C]0.186912152687376[/C][C]0.0934560763436879[/C][/ROW]
[ROW][C]164[/C][C]0.90207263699407[/C][C]0.19585472601186[/C][C]0.09792736300593[/C][/ROW]
[ROW][C]165[/C][C]0.883862848899547[/C][C]0.232274302200905[/C][C]0.116137151100453[/C][/ROW]
[ROW][C]166[/C][C]0.883110978791381[/C][C]0.233778042417237[/C][C]0.116889021208619[/C][/ROW]
[ROW][C]167[/C][C]0.885871321581864[/C][C]0.228257356836272[/C][C]0.114128678418136[/C][/ROW]
[ROW][C]168[/C][C]0.865087822436398[/C][C]0.269824355127204[/C][C]0.134912177563602[/C][/ROW]
[ROW][C]169[/C][C]0.84104121463594[/C][C]0.317917570728121[/C][C]0.158958785364060[/C][/ROW]
[ROW][C]170[/C][C]0.828628689412721[/C][C]0.342742621174558[/C][C]0.171371310587279[/C][/ROW]
[ROW][C]171[/C][C]0.804635000517313[/C][C]0.390729998965374[/C][C]0.195364999482687[/C][/ROW]
[ROW][C]172[/C][C]0.784454506435072[/C][C]0.431090987129856[/C][C]0.215545493564928[/C][/ROW]
[ROW][C]173[/C][C]0.752794953711204[/C][C]0.494410092577591[/C][C]0.247205046288796[/C][/ROW]
[ROW][C]174[/C][C]0.726712396018073[/C][C]0.546575207963854[/C][C]0.273287603981927[/C][/ROW]
[ROW][C]175[/C][C]0.690550322577515[/C][C]0.61889935484497[/C][C]0.309449677422485[/C][/ROW]
[ROW][C]176[/C][C]0.655720961582992[/C][C]0.688558076834016[/C][C]0.344279038417008[/C][/ROW]
[ROW][C]177[/C][C]0.618077938714812[/C][C]0.763844122570376[/C][C]0.381922061285188[/C][/ROW]
[ROW][C]178[/C][C]0.581012438474015[/C][C]0.83797512305197[/C][C]0.418987561525985[/C][/ROW]
[ROW][C]179[/C][C]0.554336728466788[/C][C]0.891326543066424[/C][C]0.445663271533212[/C][/ROW]
[ROW][C]180[/C][C]0.520346715178594[/C][C]0.959306569642813[/C][C]0.479653284821406[/C][/ROW]
[ROW][C]181[/C][C]0.481556433251871[/C][C]0.963112866503743[/C][C]0.518443566748129[/C][/ROW]
[ROW][C]182[/C][C]0.471720517885808[/C][C]0.943441035771617[/C][C]0.528279482114192[/C][/ROW]
[ROW][C]183[/C][C]0.453003857581788[/C][C]0.906007715163576[/C][C]0.546996142418212[/C][/ROW]
[ROW][C]184[/C][C]0.534306748376069[/C][C]0.931386503247862[/C][C]0.465693251623931[/C][/ROW]
[ROW][C]185[/C][C]0.724085730258896[/C][C]0.551828539482209[/C][C]0.275914269741104[/C][/ROW]
[ROW][C]186[/C][C]0.902715828474577[/C][C]0.194568343050846[/C][C]0.097284171525423[/C][/ROW]
[ROW][C]187[/C][C]0.89742316433919[/C][C]0.205153671321621[/C][C]0.102576835660811[/C][/ROW]
[ROW][C]188[/C][C]0.928694646882606[/C][C]0.142610706234789[/C][C]0.0713053531173944[/C][/ROW]
[ROW][C]189[/C][C]0.912540242486435[/C][C]0.174919515027130[/C][C]0.0874597575135648[/C][/ROW]
[ROW][C]190[/C][C]0.90478728211224[/C][C]0.190425435775521[/C][C]0.0952127178877603[/C][/ROW]
[ROW][C]191[/C][C]0.913764905283865[/C][C]0.17247018943227[/C][C]0.086235094716135[/C][/ROW]
[ROW][C]192[/C][C]0.90305790098372[/C][C]0.193884198032561[/C][C]0.0969420990162803[/C][/ROW]
[ROW][C]193[/C][C]0.88550765560337[/C][C]0.228984688793261[/C][C]0.114492344396630[/C][/ROW]
[ROW][C]194[/C][C]0.859728432995014[/C][C]0.280543134009972[/C][C]0.140271567004986[/C][/ROW]
[ROW][C]195[/C][C]0.837071430045814[/C][C]0.325857139908371[/C][C]0.162928569954186[/C][/ROW]
[ROW][C]196[/C][C]0.889820817745527[/C][C]0.220358364508947[/C][C]0.110179182254473[/C][/ROW]
[ROW][C]197[/C][C]0.863768686178484[/C][C]0.272462627643031[/C][C]0.136231313821516[/C][/ROW]
[ROW][C]198[/C][C]0.840624442706512[/C][C]0.318751114586976[/C][C]0.159375557293488[/C][/ROW]
[ROW][C]199[/C][C]0.807632699214082[/C][C]0.384734601571837[/C][C]0.192367300785918[/C][/ROW]
[ROW][C]200[/C][C]0.785272299512866[/C][C]0.429455400974269[/C][C]0.214727700487134[/C][/ROW]
[ROW][C]201[/C][C]0.747104799110547[/C][C]0.505790401778906[/C][C]0.252895200889453[/C][/ROW]
[ROW][C]202[/C][C]0.78031604789421[/C][C]0.43936790421158[/C][C]0.21968395210579[/C][/ROW]
[ROW][C]203[/C][C]0.744844724701808[/C][C]0.510310550596383[/C][C]0.255155275298192[/C][/ROW]
[ROW][C]204[/C][C]0.740219736057955[/C][C]0.519560527884091[/C][C]0.259780263942045[/C][/ROW]
[ROW][C]205[/C][C]0.700184011578812[/C][C]0.599631976842376[/C][C]0.299815988421188[/C][/ROW]
[ROW][C]206[/C][C]0.657735459594867[/C][C]0.684529080810267[/C][C]0.342264540405133[/C][/ROW]
[ROW][C]207[/C][C]0.60433541170661[/C][C]0.79132917658678[/C][C]0.39566458829339[/C][/ROW]
[ROW][C]208[/C][C]0.552233588854213[/C][C]0.895532822291574[/C][C]0.447766411145787[/C][/ROW]
[ROW][C]209[/C][C]0.535873413188491[/C][C]0.928253173623019[/C][C]0.464126586811509[/C][/ROW]
[ROW][C]210[/C][C]0.59231866547143[/C][C]0.81536266905714[/C][C]0.40768133452857[/C][/ROW]
[ROW][C]211[/C][C]0.535254992329044[/C][C]0.929490015341911[/C][C]0.464745007670956[/C][/ROW]
[ROW][C]212[/C][C]0.474571028594908[/C][C]0.949142057189817[/C][C]0.525428971405092[/C][/ROW]
[ROW][C]213[/C][C]0.640129317343546[/C][C]0.719741365312908[/C][C]0.359870682656454[/C][/ROW]
[ROW][C]214[/C][C]0.598398255118598[/C][C]0.803203489762804[/C][C]0.401601744881402[/C][/ROW]
[ROW][C]215[/C][C]0.614364713233338[/C][C]0.771270573533324[/C][C]0.385635286766662[/C][/ROW]
[ROW][C]216[/C][C]0.548770710780822[/C][C]0.902458578438357[/C][C]0.451229289219178[/C][/ROW]
[ROW][C]217[/C][C]0.552341706760213[/C][C]0.895316586479575[/C][C]0.447658293239787[/C][/ROW]
[ROW][C]218[/C][C]0.495996654241239[/C][C]0.991993308482477[/C][C]0.504003345758761[/C][/ROW]
[ROW][C]219[/C][C]0.44455869766909[/C][C]0.88911739533818[/C][C]0.55544130233091[/C][/ROW]
[ROW][C]220[/C][C]0.469134446306972[/C][C]0.938268892613944[/C][C]0.530865553693028[/C][/ROW]
[ROW][C]221[/C][C]0.410018774332604[/C][C]0.820037548665208[/C][C]0.589981225667396[/C][/ROW]
[ROW][C]222[/C][C]0.335725672331551[/C][C]0.671451344663101[/C][C]0.66427432766845[/C][/ROW]
[ROW][C]223[/C][C]0.450822029465317[/C][C]0.901644058930634[/C][C]0.549177970534683[/C][/ROW]
[ROW][C]224[/C][C]0.409877753651629[/C][C]0.819755507303257[/C][C]0.590122246348371[/C][/ROW]
[ROW][C]225[/C][C]0.506285912515665[/C][C]0.987428174968669[/C][C]0.493714087484335[/C][/ROW]
[ROW][C]226[/C][C]0.415097422949845[/C][C]0.83019484589969[/C][C]0.584902577050155[/C][/ROW]
[ROW][C]227[/C][C]0.551744339044776[/C][C]0.896511321910447[/C][C]0.448255660955224[/C][/ROW]
[ROW][C]228[/C][C]0.48050694833634[/C][C]0.96101389667268[/C][C]0.51949305166366[/C][/ROW]
[ROW][C]229[/C][C]0.59842051622508[/C][C]0.80315896754984[/C][C]0.40157948377492[/C][/ROW]
[ROW][C]230[/C][C]0.583154108180912[/C][C]0.833691783638176[/C][C]0.416845891819088[/C][/ROW]
[ROW][C]231[/C][C]0.865704778410308[/C][C]0.268590443179385[/C][C]0.134295221589692[/C][/ROW]
[ROW][C]232[/C][C]0.76885290495217[/C][C]0.46229419009566[/C][C]0.23114709504783[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108606&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108606&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
80.5974464076232320.8051071847535350.402553592376768
90.4667384944291240.9334769888582470.533261505570876
100.3218997447269420.6437994894538840.678100255273058
110.3508942885469050.7017885770938090.649105711453095
120.2699682612339950.5399365224679910.730031738766004
130.2214927201465260.4429854402930520.778507279853474
140.2006592598243170.4013185196486340.799340740175683
150.3492153127594810.6984306255189620.650784687240519
160.9445527251200530.1108945497598930.0554472748799466
170.9744938438455380.05101231230892360.0255061561544618
180.9965128415859810.006974316828037770.00348715841401889
190.9963117901009580.007376419798083450.00368820989904172
200.9959481776740560.00810364465188730.00405182232594365
210.9941779530175720.01164409396485560.00582204698242778
220.9911134480665260.01777310386694740.0088865519334737
230.987862432802040.02427513439592240.0121375671979612
240.9826477534252940.03470449314941230.0173522465747062
250.9774215450767470.04515690984650660.0225784549232533
260.9751880136675340.04962397266493210.0248119863324660
270.9854982232297460.02900355354050720.0145017767702536
280.980303585264310.03939282947137960.0196964147356898
290.980826941094550.03834611781090110.0191730589054505
300.9787628652811750.042474269437650.021237134718825
310.9776515035956050.04469699280878920.0223484964043946
320.9863357980546150.02732840389076910.0136642019453845
330.9917090820014220.01658183599715610.00829091799857804
340.9980930802846340.003813839430733150.00190691971536657
350.997301980998110.005396038003780310.00269801900189015
360.9962059415261330.007588116947733660.00379405847386683
370.994864668039450.01027066392110060.00513533196055029
380.9926998506715510.01460029865689720.0073001493284486
390.989897337851480.02020532429703890.0101026621485195
400.9867600490150060.02647990196998810.0132399509849940
410.9823366527948240.03532669441035180.0176633472051759
420.9798246784180270.04035064316394540.0201753215819727
430.9913270340316140.01734593193677120.00867296596838558
440.9890596815972370.02188063680552520.0109403184027626
450.9869724407602520.02605511847949510.0130275592397476
460.9869133999820490.02617320003590220.0130866000179511
470.984684565460460.03063086907907810.0153154345395391
480.9797339088089780.04053218238204400.0202660911910220
490.977607257155120.04478548568975850.0223927428448793
500.9745334560200510.05093308795989780.0254665439799489
510.9700836834840180.05983263303196340.0299163165159817
520.9688300387778150.06233992244437070.0311699612221853
530.9603349227997930.07933015440041330.0396650772002066
540.9508857815741460.09822843685170850.0491142184258542
550.9468780525495480.1062438949009050.0531219474504524
560.934746166774820.1305076664503590.0652538332251797
570.9271357246048170.1457285507903660.0728642753951829
580.9247014755015360.1505970489969280.0752985244984638
590.9199867148825340.1600265702349330.0800132851174663
600.940568327203770.1188633455924620.0594316727962309
610.933153038156460.1336939236870810.0668469618435407
620.9189801361422520.1620397277154960.081019863857748
630.9105202108755760.1789595782488480.0894797891244238
640.8935488487781910.2129023024436170.106451151221809
650.8738342211289050.2523315577421890.126165778871095
660.9068052965186430.1863894069627150.0931947034813575
670.8936670585096680.2126658829806630.106332941490332
680.9145567193918260.1708865612163480.0854432806081738
690.9010795926792310.1978408146415380.0989204073207688
700.884438143262580.2311237134748390.115561856737419
710.9102001366808540.1795997266382920.089799863319146
720.897721995202750.20455600959450.10227800479725
730.916461228055750.1670775438885010.0835387719442506
740.9064517889538030.1870964220923940.0935482110461972
750.9029259636711450.194148072657710.097074036328855
760.9069272766553360.1861454466893280.0930727233446642
770.8909091409486550.218181718102690.109090859051345
780.8797731961598840.2404536076802310.120226803840116
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1080.9465524797703370.1068950404593270.0534475202296633
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1100.932802699585910.1343946008281800.0671973004140901
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1600.8461142815543120.3077714368913760.153885718445688
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1780.5810124384740150.837975123051970.418987561525985
1790.5543367284667880.8913265430664240.445663271533212
1800.5203467151785940.9593065696428130.479653284821406
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1820.4717205178858080.9434410357716170.528279482114192
1830.4530038575817880.9060077151635760.546996142418212
1840.5343067483760690.9313865032478620.465693251623931
1850.7240857302588960.5518285394822090.275914269741104
1860.9027158284745770.1945683430508460.097284171525423
1870.897423164339190.2051536713216210.102576835660811
1880.9286946468826060.1426107062347890.0713053531173944
1890.9125402424864350.1749195150271300.0874597575135648
1900.904787282112240.1904254357755210.0952127178877603
1910.9137649052838650.172470189432270.086235094716135
1920.903057900983720.1938841980325610.0969420990162803
1930.885507655603370.2289846887932610.114492344396630
1940.8597284329950140.2805431340099720.140271567004986
1950.8370714300458140.3258571399083710.162928569954186
1960.8898208177455270.2203583645089470.110179182254473
1970.8637686861784840.2724626276430310.136231313821516
1980.8406244427065120.3187511145869760.159375557293488
1990.8076326992140820.3847346015718370.192367300785918
2000.7852722995128660.4294554009742690.214727700487134
2010.7471047991105470.5057904017789060.252895200889453
2020.780316047894210.439367904211580.21968395210579
2030.7448447247018080.5103105505963830.255155275298192
2040.7402197360579550.5195605278840910.259780263942045
2050.7001840115788120.5996319768423760.299815988421188
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2100.592318665471430.815362669057140.40768133452857
2110.5352549923290440.9294900153419110.464745007670956
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2250.5062859125156650.9874281749686690.493714087484335
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2310.8657047784103080.2685904431793850.134295221589692
2320.768852904952170.462294190095660.23114709504783






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level60.0266666666666667NOK
5% type I error level390.173333333333333NOK
10% type I error level630.28NOK

\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 & 6 & 0.0266666666666667 & NOK \tabularnewline
5% type I error level & 39 & 0.173333333333333 & NOK \tabularnewline
10% type I error level & 63 & 0.28 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108606&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]6[/C][C]0.0266666666666667[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]39[/C][C]0.173333333333333[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]63[/C][C]0.28[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108606&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108606&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 level60.0266666666666667NOK
5% type I error level390.173333333333333NOK
10% type I error level630.28NOK


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 5 ; 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')
}