FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationWed, 10 Dec 2014 11:27:08 +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/2014/Dec/10/t1418210883jxsd2r4u6nim59k.htm/, Retrieved Sun, 19 May 2024 14:11:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264935, Retrieved Sun, 19 May 2024 14:11:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-10 11:27:08] [e2c8fd7ffb6898b7e37b86d31eb23523] [Current]
- R PD    [Multiple Regression] [] [2014-12-16 21:00:36] [69bf0eb8b9b38defaaf4848d8c317571]
- RMPD      [Multiple Regression] [] [2014-12-18 00:37:44] [69bf0eb8b9b38defaaf4848d8c317571]
- RMPD        [Multiple Regression] [] [2014-12-18 13:22:32] [69bf0eb8b9b38defaaf4848d8c317571]
- RMPD          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-18 17:04:58] [69bf0eb8b9b38defaaf4848d8c317571]
-   PD    [Multiple Regression] [] [2014-12-17 19:22:04] [69bf0eb8b9b38defaaf4848d8c317571]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
149	96	86	12,9
152	75	62	7,4
139	70	70	12,2
148	88	71	12,8
158	114	108	7,4
128	69	64	6,7
224	176	119	12,6
159	114	97	14,8
105	121	129	13,3
159	110	153	11,1
167	158	78	8,2
165	116	80	11,4
159	181	99	6,4
119	77	68	10,6
176	141	147	12,0
54	35	40	6,3
91	80	57	11,3
163	152	120	11,9
124	97	71	9,3
137	99	84	9,6
121	84	68	10,0
153	68	55	6,4
148	101	137	13,8
221	107	79	10,8
188	88	116	13,8
149	112	101	11,7
244	171	111	10,9
148	137	189	16,1
92	77	66	13,4
150	66	81	9,9
153	93	63	11,5
94	105	69	8,3
156	131	71	11,7
146	89	70	6,1
132	102	64	9,0
161	161	143	9,7
105	120	85	10,8
97	127	86	10,3
151	77	55	10,4
131	108	69	12,7
166	85	120	9,3
157	168	96	11,8
111	48	60	5,9
145	152	95	11,4
162	75	100	13,0
163	107	68	10,8
59	62	57	12,3
187	121	105	11,3
109	124	85	11,8
90	72	103	7,9
105	40	57	12,7
83	58	51	12,3
116	97	69	11,6
42	88	41	6,7
148	126	49	10,9
155	104	50	12,1
125	148	93	13,3
116	146	58	10,1
128	80	54	5,7
138	97	74	14,3
49	25	15	8,0
96	99	69	13,3
164	118	107	9,3
162	58	65	12,5
99	63	58	7,6
202	139	107	15,9
186	50	70	9,2
66	60	53	9,1
183	152	136	11,1
214	142	126	13,0
188	94	95	14,5
104	66	69	12,2
177	127	136	12,3
126	67	58	11,4
76	90	59	8,8
99	75	118	14,6
157	96	110	7,3
139	128	82	12,6
78	41	50	NA
162	146	102	13,0
108	69	65	12,6
159	186	90	13,2
74	81	64	9,9
110	85	83	7,7
96	54	70	10,5
116	46	50	13,4
87	106	77	10,9
97	34	37	4,3
127	60	81	10,3
106	95	101	11,8
80	57	79	11,2
74	62	71	11,4
91	36	60	8,6
133	56	55	13,2
74	54	44	12,6
114	64	40	5,6
140	76	56	9,9
95	98	43	8,8
98	88	45	7,7
121	35	32	9,0
126	102	56	7,3
98	61	40	11,4
95	80	34	13,6
110	49	89	7,9
70	78	50	10,7
102	90	56	10,3
86	45	46	8,3
130	55	76	9,6
96	96	64	14,2
102	43	74	8,5
100	52	57	13,5
94	60	45	4,9
52	54	30	6,4
98	51	62	9,6
118	51	51	11,6
99	38	36	11,1
48	41	34	4,35
50	146	61	12,7
150	182	70	18,1
154	192	69	17,85
109	263	145	16,6
68	35	23	12,6
194	439	120	17,1
158	214	147	19,1
159	341	215	16,1
67	58	24	13,35
147	292	84	18,4
39	85	30	14,7
100	200	77	10,6
111	158	46	12,6
138	199	61	16,2
101	297	178	13,6
131	227	160	18,9
101	108	57	14,1
114	86	42	14,5
165	302	163	16,15
114	148	75	14,75
111	178	94	14,8
75	120	45	12,45
82	207	78	12,65
121	157	47	17,35
32	128	29	8,6
150	296	97	18,4
117	323	116	16,1
71	79	32	11,6
165	70	50	17,75
154	146	118	15,25
126	246	66	17,65
138	145	48	15,6
149	196	86	16,35
145	199	89	17,65
120	127	76	13,6
138	91	39	11,7
109	153	75	14,35
132	299	57	14,75
172	228	72	18,25
169	190	60	9,9
114	180	109	16
156	212	76	18,25
172	269	65	16,85
68	130	40	14,6
89	179	58	13,85
167	243	123	18,95
113	190	71	15,6
115	299	102	14,85
78	121	80	11,75
118	137	97	18,45
87	305	46	15,9
173	157	93	17,1
2	96	19	16,1
162	183	140	19,9
49	52	78	10,95
122	238	98	18,45
96	40	40	15,1
100	226	80	15
82	190	76	11,35
100	214	79	15,95
115	145	87	18,1
141	119	95	14,6
165	222	49	15,4
165	222	49	15,4
110	159	80	17,6
118	165	86	13,35
158	249	69	19,1
146	125	79	15,35
49	122	52	7,6
90	186	120	13,4
121	148	69	13,9
155	274	94	19,1
104	172	72	15,25
147	84	43	12,9
110	168	87	16,1
108	102	52	17,35
113	106	71	13,15
115	2	61	12,15
61	139	51	12,6
60	95	50	10,35
109	130	67	15,4
68	72	30	9,6
111	141	70	18,2
77	113	52	13,6
73	206	75	14,85
151	268	87	14,75
89	175	69	14,1
78	77	72	14,9
110	125	79	16,25
220	255	121	19,25
65	111	43	13,6
141	132	58	13,6
117	211	57	15,65
122	92	50	12,75
63	76	69	14,6
44	171	64	9,85
52	83	38	12,65
62	119	53	11,9
131	266	90	19,2
101	186	96	16,6
42	50	49	11,2
152	117	56	15,25
107	219	102	11,9
77	246	40	13,2
154	279	100	16,35
103	148	67	12,4
96	137	78	15,85
154	130	62	14,35
175	181	55	18,15
57	98	59	11,15
112	226	96	15,65
143	234	86	17,75
49	138	38	7,65
110	85	43	12,35
131	66	23	15,6
167	236	77	19,3
56	106	48	15,2
137	135	26	17,1
86	122	91	15,6
121	218	94	18,4
149	199	62	19,05
168	112	74	18,55
140	278	114	19,1
88	94	52	13,1
168	113	64	12,85
94	84	31	9,5
51	86	38	4,5
48	62	27	11,85
145	222	105	13,6
66	167	64	11,7
85	82	62	12,4
109	207	65	13,35
63	184	58	11,4
102	83	76	14,9
162	183	140	19,9
128	85	48	17,75
86	89	68	11,2
114	225	80	14,6
164	237	71	17,6
119	102	76	14,05
126	221	63	16,1
132	128	46	13,35
142	91	53	11,85
83	198	74	11,95
94	204	70	14,75
81	158	78	15,15
166	138	56	13,2
110	226	100	16,85
64	44	51	7,85
93	196	52	7,7
104	83	102	12,6
105	79	78	7,85
49	52	78	10,95
88	105	55	12,35
95	116	98	9,95
102	83	76	14,9
99	196	73	16,65
63	153	47	13,4
76	157	45	13,95
109	75	83	15,7
117	106	60	16,85
57	58	48	10,95
120	75	50	15,35
73	74	56	12,2
91	185	77	15,1
108	265	91	17,75
105	131	76	15,2
117	139	68	14,6
119	196	74	16,65
31	78	29	8,1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264935&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264935&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264935&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 time9 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.31238 + 0.00978656LFM[t] + 0.027686B[t] -0.0025618H[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.31238 +  0.00978656LFM[t] +  0.027686B[t] -0.0025618H[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264935&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.31238 +  0.00978656LFM[t] +  0.027686B[t] -0.0025618H[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264935&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264935&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
TOT[t] = + 8.31238 + 0.00978656LFM[t] + 0.027686B[t] -0.0025618H[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.312380.54881315.152.49978e-381.24989e-38
LFM0.009786560.004793222.0420.04210660.0210533
B0.0276860.0026540310.439.25937e-224.62968e-22
H-0.00256180.006753-0.37940.7047090.352354

\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) & 8.31238 & 0.548813 & 15.15 & 2.49978e-38 & 1.24989e-38 \tabularnewline
LFM & 0.00978656 & 0.00479322 & 2.042 & 0.0421066 & 0.0210533 \tabularnewline
B & 0.027686 & 0.00265403 & 10.43 & 9.25937e-22 & 4.62968e-22 \tabularnewline
H & -0.0025618 & 0.006753 & -0.3794 & 0.704709 & 0.352354 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264935&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]8.31238[/C][C]0.548813[/C][C]15.15[/C][C]2.49978e-38[/C][C]1.24989e-38[/C][/ROW]
[ROW][C]LFM[/C][C]0.00978656[/C][C]0.00479322[/C][C]2.042[/C][C]0.0421066[/C][C]0.0210533[/C][/ROW]
[ROW][C]B[/C][C]0.027686[/C][C]0.00265403[/C][C]10.43[/C][C]9.25937e-22[/C][C]4.62968e-22[/C][/ROW]
[ROW][C]H[/C][C]-0.0025618[/C][C]0.006753[/C][C]-0.3794[/C][C]0.704709[/C][C]0.352354[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264935&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264935&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)8.312380.54881315.152.49978e-381.24989e-38
LFM0.009786560.004793222.0420.04210660.0210533
B0.0276860.0026540310.439.25937e-224.62968e-22
H-0.00256180.006753-0.37940.7047090.352354






Multiple Linear Regression - Regression Statistics
Multiple R0.599112
R-squared0.358935
Adjusted R-squared0.352115
F-TEST (value)52.631
F-TEST (DF numerator)3
F-TEST (DF denominator)282
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.75382
Sum Squared Residuals2138.55

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.599112 \tabularnewline
R-squared & 0.358935 \tabularnewline
Adjusted R-squared & 0.352115 \tabularnewline
F-TEST (value) & 52.631 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 282 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.75382 \tabularnewline
Sum Squared Residuals & 2138.55 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264935&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.599112[/C][/ROW]
[ROW][C]R-squared[/C][C]0.358935[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.352115[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]52.631[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]282[/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]2.75382[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2138.55[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264935&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264935&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 R0.599112
R-squared0.358935
Adjusted R-squared0.352115
F-TEST (value)52.631
F-TEST (DF numerator)3
F-TEST (DF denominator)282
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.75382
Sum Squared Residuals2138.55






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.20810.691872
27.411.7176-4.31756
312.211.43140.768586
412.812.01530.78472
57.412.7382-5.3382
66.711.3114-4.61145
712.615.0725-2.47246
814.812.77622.02384
913.312.35950.940487
1011.112.522-1.42196
118.214.1213-5.92131
1211.412.9338-1.5338
136.414.626-8.226
1410.611.4346-0.834609
151213.562-1.56197
166.39.7074-3.4074
1711.311.27180.0281773
1811.913.8085-1.90846
199.312.0296-2.72958
209.612.1789-2.57887
211011.648-1.64798
226.411.5515-5.15148
2313.812.20611.59388
2410.813.2352-2.43524
2513.812.29151.50854
2611.712.6127-0.912678
2710.915.1503-4.25026
2816.113.06963.0304
2913.411.17552.2245
309.911.4001-1.50014
3111.512.2231-0.723137
328.311.9626-3.66259
3311.713.2841-1.58407
346.112.026-5.92595
35912.2642-3.26423
369.713.9791-4.27914
3710.812.4445-1.64455
3810.312.5575-2.25749
3910.411.7811-1.38108
4012.712.40780.292247
419.311.9829-2.68285
4211.814.2542-2.4542
435.910.5739-4.67392
4411.413.6963-2.29634
451311.71811.28192
4610.812.6958-1.8958
4712.310.46031.8397
4811.313.2235-1.92349
4911.812.5944-0.794436
507.910.9227-3.02271
5112.710.30142.39861
5212.310.59981.70019
5311.611.9564-0.356408
546.711.0548-4.35476
5510.913.1237-2.22371
5612.112.5806-0.48056
5713.313.395-0.0949918
5810.113.3412-3.2412
595.711.6416-5.94161
6014.312.15892.1411
6189.44565-1.44565
6213.311.8161.48395
639.312.9102-3.61022
6412.511.33711.16292
657.610.8769-3.27689
6615.913.86352.03648
679.211.3377-2.13766
689.110.4837-1.38369
6911.113.9632-2.8632
701314.0153-1.01534
7114.512.51141.98862
7212.210.98071.2193
7312.313.2123-0.912329
7411.411.25190.148128
758.811.3968-2.59676
7614.611.05543.54458
777.312.2249-4.92494
7812.613.0065-0.406463
79NANA-0.678666
801311.51321.48685
8112.614.1875-1.58749
8213.214.4152-1.2152
839.913.7296-3.82959
847.77.76762-0.0676152
8510.57.693092.80691
8613.414.4013-1.00128
8710.916.7082-5.80822
884.35.00894-0.708935
8910.310.22120.0788073
9011.811.0710.728968
9111.210.37120.828763
9211.412.846-1.44595
938.66.423522.17648
9413.211.01892.18108
9512.618.0975-5.49749
965.67.34318-1.74318
979.912.9452-3.04518
988.812.6926-3.89256
997.79.08359-1.38359
100913.926-4.92601
1017.36.757840.542156
10211.49.169892.23011
10313.616.2175-2.61752
1047.98.22887-0.328865
10510.712.0589-1.3589
10610.312.2821-1.98206
1078.39.61267-1.31267
1089.67.14582.4542
10914.216.0115-1.81154
1108.55.584692.91531
11113.519.3782-5.8782
1124.98.73948-3.83948
1136.47.32462-0.924625
1149.68.748540.851464
11511.610.74110.858901
11611.116.5802-5.48017
1174.354.337610.0123949
11812.79.23993.4601
11918.115.20852.89153
12017.8517.53910.310912
12116.613.8882.71204
12212.617.5577-4.95773
12317.113.40693.69311
12419.121.7586-2.6586
12516.113.26242.83761
12613.3512.57010.779858
12718.414.67053.72948
12814.718.731-4.03099
12910.611.6552-1.05524
13012.611.41621.18382
13116.219.6676-3.46758
13213.610.16933.43073
13318.916.94491.9551
13414.111.30152.79854
13514.516.2208-1.72078
13616.1514.73351.41655
13714.7514.0360.714001
13814.814.60340.196579
13912.4514.4461-1.99607
14012.659.022863.62714
14117.3520.8451-3.49508
1428.67.926940.673058
14318.420.4028-2.00283
14416.115.61250.48755
14511.65.58716.0129
14617.7516.05941.69061
14715.2513.78721.46282
14817.6515.60442.04556
14915.614.22671.37327
15016.3513.7132.63704
15117.6516.85820.791797
15213.613.9824-0.38245
15311.710.77290.927051
15414.3517.3363-2.98631
15514.7512.62362.12636
15618.2523.423-5.17295
1579.98.03231.8677
1581613.26382.73617
15918.2518.6767-0.426701
16016.8514.72462.12542
16114.614.7406-0.140606
16213.8511.25932.59065
16318.9517.84671.10327
16415.618.2047-2.60466
16514.8515.3208-0.470804
16611.756.311695.43831
16718.4520.0402-1.59021
16815.912.91392.98608
16917.111.94115.15886
17016.110.80575.2943
17119.918.98180.91822
17210.958.344572.60543
17318.4513.60694.84314
17415.115.4431-0.343142
1751517.8305-2.83053
17611.3510.41350.936529
17715.9511.07944.87056
17818.116.24361.85644
17914.615.1479-0.54794
18015.415.9479-0.54794
18115.411.3864.01396
18217.618.0651-0.465081
18313.3510.82572.52428
18419.116.74962.3504
18515.3519.7864-4.43641
1867.68.23536-0.635363
18713.412.91730.482671
18813.911.97451.92553
18919.117.75771.34226
19015.2514.31650.933521
19112.910.61732.28272
19216.110.81015.2899
19317.3516.37110.978901
19413.1510.33692.81306
19512.1512.1771-0.0270729
19612.613.6517-1.05166
19710.357.756662.59334
19815.416.6944-1.29441
1999.64.52315.0769
20018.216.66131.53874
20113.613.2880.312007
20214.8517.0871-2.23714
20314.7514.50170.248318
20414.110.22313.87689
20514.911.29733.60272
20616.2514.21542.03461
20719.2517.56151.6885
20813.613.19830.401737
20913.613.10310.496856
21015.6514.82540.824629
21112.759.006313.74369
21214.618.0634-3.46335
2139.858.221881.62812
21412.6512.828-0.178015
21511.99.428352.47165
21619.216.80452.3955
21716.615.38221.21781
21811.28.845752.35425
21915.2518.5115-3.26149
22011.914.4742-2.57424
22113.214.1377-0.937741
22216.3517.1963-0.846294
22312.49.395063.00494
22415.8514.75991.09013
22514.3511.09533.25469
22618.1518.4323-0.282305
22711.1510.91960.230408
22815.6513.87011.77992
22917.7522.6153-4.86525
2307.656.932060.717937
23112.358.112784.23722
23215.612.58343.01661
23319.315.77223.52781
23415.211.42423.77585
23517.113.79863.3014
23615.612.49133.10869
23718.414.47133.92873
23819.0513.36785.68221
23918.5516.53722.01282
24019.117.64291.45712
24113.113.1711-0.0710947
24212.8514.8285-1.97853
2439.516.0952-6.59515
2444.53.079511.42049
24511.8513.8587-2.00875
24613.615.3179-1.71791
24711.710.55571.14433
24812.413.9936-1.59361
24913.3515.8246-2.47459
25011.47.913863.48614
25114.99.60575.2943
25219.913.94545.95459
25317.7517.9939-0.243885
25411.212.0525-0.852468
25514.613.29711.30292
25617.615.65631.94373
25714.0513.45270.597287
25816.115.78020.319819
25913.3513.5857-0.235731
26011.8514.3169-2.46693
26111.9511.90090.0490522
26214.7512.87971.87033
26315.1515.5642-0.414167
26413.211.73981.46023
26516.8519.0263-2.17626
2667.8514.6658-6.81579
2677.76.466831.23317
26812.616.0774-3.47735
2697.856.931780.91822
27010.9510.53970.410262
27112.3514.6026-2.25263
2729.956.463863.48614
27314.912.77072.12929
27416.6516.29450.355502
27513.412.73760.662409
27613.959.492944.45706
27715.711.08844.61158
27816.8516.2530.596957
27910.957.035143.91486
28015.3514.08211.26789
28112.211.22760.972379
28215.113.8231.27699
28317.7515.32212.42785
28415.213.73161.46843
28514.612.66391.93612
28616.6519.251-2.60099
2878.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.2081 & 0.691872 \tabularnewline
2 & 7.4 & 11.7176 & -4.31756 \tabularnewline
3 & 12.2 & 11.4314 & 0.768586 \tabularnewline
4 & 12.8 & 12.0153 & 0.78472 \tabularnewline
5 & 7.4 & 12.7382 & -5.3382 \tabularnewline
6 & 6.7 & 11.3114 & -4.61145 \tabularnewline
7 & 12.6 & 15.0725 & -2.47246 \tabularnewline
8 & 14.8 & 12.7762 & 2.02384 \tabularnewline
9 & 13.3 & 12.3595 & 0.940487 \tabularnewline
10 & 11.1 & 12.522 & -1.42196 \tabularnewline
11 & 8.2 & 14.1213 & -5.92131 \tabularnewline
12 & 11.4 & 12.9338 & -1.5338 \tabularnewline
13 & 6.4 & 14.626 & -8.226 \tabularnewline
14 & 10.6 & 11.4346 & -0.834609 \tabularnewline
15 & 12 & 13.562 & -1.56197 \tabularnewline
16 & 6.3 & 9.7074 & -3.4074 \tabularnewline
17 & 11.3 & 11.2718 & 0.0281773 \tabularnewline
18 & 11.9 & 13.8085 & -1.90846 \tabularnewline
19 & 9.3 & 12.0296 & -2.72958 \tabularnewline
20 & 9.6 & 12.1789 & -2.57887 \tabularnewline
21 & 10 & 11.648 & -1.64798 \tabularnewline
22 & 6.4 & 11.5515 & -5.15148 \tabularnewline
23 & 13.8 & 12.2061 & 1.59388 \tabularnewline
24 & 10.8 & 13.2352 & -2.43524 \tabularnewline
25 & 13.8 & 12.2915 & 1.50854 \tabularnewline
26 & 11.7 & 12.6127 & -0.912678 \tabularnewline
27 & 10.9 & 15.1503 & -4.25026 \tabularnewline
28 & 16.1 & 13.0696 & 3.0304 \tabularnewline
29 & 13.4 & 11.1755 & 2.2245 \tabularnewline
30 & 9.9 & 11.4001 & -1.50014 \tabularnewline
31 & 11.5 & 12.2231 & -0.723137 \tabularnewline
32 & 8.3 & 11.9626 & -3.66259 \tabularnewline
33 & 11.7 & 13.2841 & -1.58407 \tabularnewline
34 & 6.1 & 12.026 & -5.92595 \tabularnewline
35 & 9 & 12.2642 & -3.26423 \tabularnewline
36 & 9.7 & 13.9791 & -4.27914 \tabularnewline
37 & 10.8 & 12.4445 & -1.64455 \tabularnewline
38 & 10.3 & 12.5575 & -2.25749 \tabularnewline
39 & 10.4 & 11.7811 & -1.38108 \tabularnewline
40 & 12.7 & 12.4078 & 0.292247 \tabularnewline
41 & 9.3 & 11.9829 & -2.68285 \tabularnewline
42 & 11.8 & 14.2542 & -2.4542 \tabularnewline
43 & 5.9 & 10.5739 & -4.67392 \tabularnewline
44 & 11.4 & 13.6963 & -2.29634 \tabularnewline
45 & 13 & 11.7181 & 1.28192 \tabularnewline
46 & 10.8 & 12.6958 & -1.8958 \tabularnewline
47 & 12.3 & 10.4603 & 1.8397 \tabularnewline
48 & 11.3 & 13.2235 & -1.92349 \tabularnewline
49 & 11.8 & 12.5944 & -0.794436 \tabularnewline
50 & 7.9 & 10.9227 & -3.02271 \tabularnewline
51 & 12.7 & 10.3014 & 2.39861 \tabularnewline
52 & 12.3 & 10.5998 & 1.70019 \tabularnewline
53 & 11.6 & 11.9564 & -0.356408 \tabularnewline
54 & 6.7 & 11.0548 & -4.35476 \tabularnewline
55 & 10.9 & 13.1237 & -2.22371 \tabularnewline
56 & 12.1 & 12.5806 & -0.48056 \tabularnewline
57 & 13.3 & 13.395 & -0.0949918 \tabularnewline
58 & 10.1 & 13.3412 & -3.2412 \tabularnewline
59 & 5.7 & 11.6416 & -5.94161 \tabularnewline
60 & 14.3 & 12.1589 & 2.1411 \tabularnewline
61 & 8 & 9.44565 & -1.44565 \tabularnewline
62 & 13.3 & 11.816 & 1.48395 \tabularnewline
63 & 9.3 & 12.9102 & -3.61022 \tabularnewline
64 & 12.5 & 11.3371 & 1.16292 \tabularnewline
65 & 7.6 & 10.8769 & -3.27689 \tabularnewline
66 & 15.9 & 13.8635 & 2.03648 \tabularnewline
67 & 9.2 & 11.3377 & -2.13766 \tabularnewline
68 & 9.1 & 10.4837 & -1.38369 \tabularnewline
69 & 11.1 & 13.9632 & -2.8632 \tabularnewline
70 & 13 & 14.0153 & -1.01534 \tabularnewline
71 & 14.5 & 12.5114 & 1.98862 \tabularnewline
72 & 12.2 & 10.9807 & 1.2193 \tabularnewline
73 & 12.3 & 13.2123 & -0.912329 \tabularnewline
74 & 11.4 & 11.2519 & 0.148128 \tabularnewline
75 & 8.8 & 11.3968 & -2.59676 \tabularnewline
76 & 14.6 & 11.0554 & 3.54458 \tabularnewline
77 & 7.3 & 12.2249 & -4.92494 \tabularnewline
78 & 12.6 & 13.0065 & -0.406463 \tabularnewline
79 & NA & NA & -0.678666 \tabularnewline
80 & 13 & 11.5132 & 1.48685 \tabularnewline
81 & 12.6 & 14.1875 & -1.58749 \tabularnewline
82 & 13.2 & 14.4152 & -1.2152 \tabularnewline
83 & 9.9 & 13.7296 & -3.82959 \tabularnewline
84 & 7.7 & 7.76762 & -0.0676152 \tabularnewline
85 & 10.5 & 7.69309 & 2.80691 \tabularnewline
86 & 13.4 & 14.4013 & -1.00128 \tabularnewline
87 & 10.9 & 16.7082 & -5.80822 \tabularnewline
88 & 4.3 & 5.00894 & -0.708935 \tabularnewline
89 & 10.3 & 10.2212 & 0.0788073 \tabularnewline
90 & 11.8 & 11.071 & 0.728968 \tabularnewline
91 & 11.2 & 10.3712 & 0.828763 \tabularnewline
92 & 11.4 & 12.846 & -1.44595 \tabularnewline
93 & 8.6 & 6.42352 & 2.17648 \tabularnewline
94 & 13.2 & 11.0189 & 2.18108 \tabularnewline
95 & 12.6 & 18.0975 & -5.49749 \tabularnewline
96 & 5.6 & 7.34318 & -1.74318 \tabularnewline
97 & 9.9 & 12.9452 & -3.04518 \tabularnewline
98 & 8.8 & 12.6926 & -3.89256 \tabularnewline
99 & 7.7 & 9.08359 & -1.38359 \tabularnewline
100 & 9 & 13.926 & -4.92601 \tabularnewline
101 & 7.3 & 6.75784 & 0.542156 \tabularnewline
102 & 11.4 & 9.16989 & 2.23011 \tabularnewline
103 & 13.6 & 16.2175 & -2.61752 \tabularnewline
104 & 7.9 & 8.22887 & -0.328865 \tabularnewline
105 & 10.7 & 12.0589 & -1.3589 \tabularnewline
106 & 10.3 & 12.2821 & -1.98206 \tabularnewline
107 & 8.3 & 9.61267 & -1.31267 \tabularnewline
108 & 9.6 & 7.1458 & 2.4542 \tabularnewline
109 & 14.2 & 16.0115 & -1.81154 \tabularnewline
110 & 8.5 & 5.58469 & 2.91531 \tabularnewline
111 & 13.5 & 19.3782 & -5.8782 \tabularnewline
112 & 4.9 & 8.73948 & -3.83948 \tabularnewline
113 & 6.4 & 7.32462 & -0.924625 \tabularnewline
114 & 9.6 & 8.74854 & 0.851464 \tabularnewline
115 & 11.6 & 10.7411 & 0.858901 \tabularnewline
116 & 11.1 & 16.5802 & -5.48017 \tabularnewline
117 & 4.35 & 4.33761 & 0.0123949 \tabularnewline
118 & 12.7 & 9.2399 & 3.4601 \tabularnewline
119 & 18.1 & 15.2085 & 2.89153 \tabularnewline
120 & 17.85 & 17.5391 & 0.310912 \tabularnewline
121 & 16.6 & 13.888 & 2.71204 \tabularnewline
122 & 12.6 & 17.5577 & -4.95773 \tabularnewline
123 & 17.1 & 13.4069 & 3.69311 \tabularnewline
124 & 19.1 & 21.7586 & -2.6586 \tabularnewline
125 & 16.1 & 13.2624 & 2.83761 \tabularnewline
126 & 13.35 & 12.5701 & 0.779858 \tabularnewline
127 & 18.4 & 14.6705 & 3.72948 \tabularnewline
128 & 14.7 & 18.731 & -4.03099 \tabularnewline
129 & 10.6 & 11.6552 & -1.05524 \tabularnewline
130 & 12.6 & 11.4162 & 1.18382 \tabularnewline
131 & 16.2 & 19.6676 & -3.46758 \tabularnewline
132 & 13.6 & 10.1693 & 3.43073 \tabularnewline
133 & 18.9 & 16.9449 & 1.9551 \tabularnewline
134 & 14.1 & 11.3015 & 2.79854 \tabularnewline
135 & 14.5 & 16.2208 & -1.72078 \tabularnewline
136 & 16.15 & 14.7335 & 1.41655 \tabularnewline
137 & 14.75 & 14.036 & 0.714001 \tabularnewline
138 & 14.8 & 14.6034 & 0.196579 \tabularnewline
139 & 12.45 & 14.4461 & -1.99607 \tabularnewline
140 & 12.65 & 9.02286 & 3.62714 \tabularnewline
141 & 17.35 & 20.8451 & -3.49508 \tabularnewline
142 & 8.6 & 7.92694 & 0.673058 \tabularnewline
143 & 18.4 & 20.4028 & -2.00283 \tabularnewline
144 & 16.1 & 15.6125 & 0.48755 \tabularnewline
145 & 11.6 & 5.5871 & 6.0129 \tabularnewline
146 & 17.75 & 16.0594 & 1.69061 \tabularnewline
147 & 15.25 & 13.7872 & 1.46282 \tabularnewline
148 & 17.65 & 15.6044 & 2.04556 \tabularnewline
149 & 15.6 & 14.2267 & 1.37327 \tabularnewline
150 & 16.35 & 13.713 & 2.63704 \tabularnewline
151 & 17.65 & 16.8582 & 0.791797 \tabularnewline
152 & 13.6 & 13.9824 & -0.38245 \tabularnewline
153 & 11.7 & 10.7729 & 0.927051 \tabularnewline
154 & 14.35 & 17.3363 & -2.98631 \tabularnewline
155 & 14.75 & 12.6236 & 2.12636 \tabularnewline
156 & 18.25 & 23.423 & -5.17295 \tabularnewline
157 & 9.9 & 8.0323 & 1.8677 \tabularnewline
158 & 16 & 13.2638 & 2.73617 \tabularnewline
159 & 18.25 & 18.6767 & -0.426701 \tabularnewline
160 & 16.85 & 14.7246 & 2.12542 \tabularnewline
161 & 14.6 & 14.7406 & -0.140606 \tabularnewline
162 & 13.85 & 11.2593 & 2.59065 \tabularnewline
163 & 18.95 & 17.8467 & 1.10327 \tabularnewline
164 & 15.6 & 18.2047 & -2.60466 \tabularnewline
165 & 14.85 & 15.3208 & -0.470804 \tabularnewline
166 & 11.75 & 6.31169 & 5.43831 \tabularnewline
167 & 18.45 & 20.0402 & -1.59021 \tabularnewline
168 & 15.9 & 12.9139 & 2.98608 \tabularnewline
169 & 17.1 & 11.9411 & 5.15886 \tabularnewline
170 & 16.1 & 10.8057 & 5.2943 \tabularnewline
171 & 19.9 & 18.9818 & 0.91822 \tabularnewline
172 & 10.95 & 8.34457 & 2.60543 \tabularnewline
173 & 18.45 & 13.6069 & 4.84314 \tabularnewline
174 & 15.1 & 15.4431 & -0.343142 \tabularnewline
175 & 15 & 17.8305 & -2.83053 \tabularnewline
176 & 11.35 & 10.4135 & 0.936529 \tabularnewline
177 & 15.95 & 11.0794 & 4.87056 \tabularnewline
178 & 18.1 & 16.2436 & 1.85644 \tabularnewline
179 & 14.6 & 15.1479 & -0.54794 \tabularnewline
180 & 15.4 & 15.9479 & -0.54794 \tabularnewline
181 & 15.4 & 11.386 & 4.01396 \tabularnewline
182 & 17.6 & 18.0651 & -0.465081 \tabularnewline
183 & 13.35 & 10.8257 & 2.52428 \tabularnewline
184 & 19.1 & 16.7496 & 2.3504 \tabularnewline
185 & 15.35 & 19.7864 & -4.43641 \tabularnewline
186 & 7.6 & 8.23536 & -0.635363 \tabularnewline
187 & 13.4 & 12.9173 & 0.482671 \tabularnewline
188 & 13.9 & 11.9745 & 1.92553 \tabularnewline
189 & 19.1 & 17.7577 & 1.34226 \tabularnewline
190 & 15.25 & 14.3165 & 0.933521 \tabularnewline
191 & 12.9 & 10.6173 & 2.28272 \tabularnewline
192 & 16.1 & 10.8101 & 5.2899 \tabularnewline
193 & 17.35 & 16.3711 & 0.978901 \tabularnewline
194 & 13.15 & 10.3369 & 2.81306 \tabularnewline
195 & 12.15 & 12.1771 & -0.0270729 \tabularnewline
196 & 12.6 & 13.6517 & -1.05166 \tabularnewline
197 & 10.35 & 7.75666 & 2.59334 \tabularnewline
198 & 15.4 & 16.6944 & -1.29441 \tabularnewline
199 & 9.6 & 4.5231 & 5.0769 \tabularnewline
200 & 18.2 & 16.6613 & 1.53874 \tabularnewline
201 & 13.6 & 13.288 & 0.312007 \tabularnewline
202 & 14.85 & 17.0871 & -2.23714 \tabularnewline
203 & 14.75 & 14.5017 & 0.248318 \tabularnewline
204 & 14.1 & 10.2231 & 3.87689 \tabularnewline
205 & 14.9 & 11.2973 & 3.60272 \tabularnewline
206 & 16.25 & 14.2154 & 2.03461 \tabularnewline
207 & 19.25 & 17.5615 & 1.6885 \tabularnewline
208 & 13.6 & 13.1983 & 0.401737 \tabularnewline
209 & 13.6 & 13.1031 & 0.496856 \tabularnewline
210 & 15.65 & 14.8254 & 0.824629 \tabularnewline
211 & 12.75 & 9.00631 & 3.74369 \tabularnewline
212 & 14.6 & 18.0634 & -3.46335 \tabularnewline
213 & 9.85 & 8.22188 & 1.62812 \tabularnewline
214 & 12.65 & 12.828 & -0.178015 \tabularnewline
215 & 11.9 & 9.42835 & 2.47165 \tabularnewline
216 & 19.2 & 16.8045 & 2.3955 \tabularnewline
217 & 16.6 & 15.3822 & 1.21781 \tabularnewline
218 & 11.2 & 8.84575 & 2.35425 \tabularnewline
219 & 15.25 & 18.5115 & -3.26149 \tabularnewline
220 & 11.9 & 14.4742 & -2.57424 \tabularnewline
221 & 13.2 & 14.1377 & -0.937741 \tabularnewline
222 & 16.35 & 17.1963 & -0.846294 \tabularnewline
223 & 12.4 & 9.39506 & 3.00494 \tabularnewline
224 & 15.85 & 14.7599 & 1.09013 \tabularnewline
225 & 14.35 & 11.0953 & 3.25469 \tabularnewline
226 & 18.15 & 18.4323 & -0.282305 \tabularnewline
227 & 11.15 & 10.9196 & 0.230408 \tabularnewline
228 & 15.65 & 13.8701 & 1.77992 \tabularnewline
229 & 17.75 & 22.6153 & -4.86525 \tabularnewline
230 & 7.65 & 6.93206 & 0.717937 \tabularnewline
231 & 12.35 & 8.11278 & 4.23722 \tabularnewline
232 & 15.6 & 12.5834 & 3.01661 \tabularnewline
233 & 19.3 & 15.7722 & 3.52781 \tabularnewline
234 & 15.2 & 11.4242 & 3.77585 \tabularnewline
235 & 17.1 & 13.7986 & 3.3014 \tabularnewline
236 & 15.6 & 12.4913 & 3.10869 \tabularnewline
237 & 18.4 & 14.4713 & 3.92873 \tabularnewline
238 & 19.05 & 13.3678 & 5.68221 \tabularnewline
239 & 18.55 & 16.5372 & 2.01282 \tabularnewline
240 & 19.1 & 17.6429 & 1.45712 \tabularnewline
241 & 13.1 & 13.1711 & -0.0710947 \tabularnewline
242 & 12.85 & 14.8285 & -1.97853 \tabularnewline
243 & 9.5 & 16.0952 & -6.59515 \tabularnewline
244 & 4.5 & 3.07951 & 1.42049 \tabularnewline
245 & 11.85 & 13.8587 & -2.00875 \tabularnewline
246 & 13.6 & 15.3179 & -1.71791 \tabularnewline
247 & 11.7 & 10.5557 & 1.14433 \tabularnewline
248 & 12.4 & 13.9936 & -1.59361 \tabularnewline
249 & 13.35 & 15.8246 & -2.47459 \tabularnewline
250 & 11.4 & 7.91386 & 3.48614 \tabularnewline
251 & 14.9 & 9.6057 & 5.2943 \tabularnewline
252 & 19.9 & 13.9454 & 5.95459 \tabularnewline
253 & 17.75 & 17.9939 & -0.243885 \tabularnewline
254 & 11.2 & 12.0525 & -0.852468 \tabularnewline
255 & 14.6 & 13.2971 & 1.30292 \tabularnewline
256 & 17.6 & 15.6563 & 1.94373 \tabularnewline
257 & 14.05 & 13.4527 & 0.597287 \tabularnewline
258 & 16.1 & 15.7802 & 0.319819 \tabularnewline
259 & 13.35 & 13.5857 & -0.235731 \tabularnewline
260 & 11.85 & 14.3169 & -2.46693 \tabularnewline
261 & 11.95 & 11.9009 & 0.0490522 \tabularnewline
262 & 14.75 & 12.8797 & 1.87033 \tabularnewline
263 & 15.15 & 15.5642 & -0.414167 \tabularnewline
264 & 13.2 & 11.7398 & 1.46023 \tabularnewline
265 & 16.85 & 19.0263 & -2.17626 \tabularnewline
266 & 7.85 & 14.6658 & -6.81579 \tabularnewline
267 & 7.7 & 6.46683 & 1.23317 \tabularnewline
268 & 12.6 & 16.0774 & -3.47735 \tabularnewline
269 & 7.85 & 6.93178 & 0.91822 \tabularnewline
270 & 10.95 & 10.5397 & 0.410262 \tabularnewline
271 & 12.35 & 14.6026 & -2.25263 \tabularnewline
272 & 9.95 & 6.46386 & 3.48614 \tabularnewline
273 & 14.9 & 12.7707 & 2.12929 \tabularnewline
274 & 16.65 & 16.2945 & 0.355502 \tabularnewline
275 & 13.4 & 12.7376 & 0.662409 \tabularnewline
276 & 13.95 & 9.49294 & 4.45706 \tabularnewline
277 & 15.7 & 11.0884 & 4.61158 \tabularnewline
278 & 16.85 & 16.253 & 0.596957 \tabularnewline
279 & 10.95 & 7.03514 & 3.91486 \tabularnewline
280 & 15.35 & 14.0821 & 1.26789 \tabularnewline
281 & 12.2 & 11.2276 & 0.972379 \tabularnewline
282 & 15.1 & 13.823 & 1.27699 \tabularnewline
283 & 17.75 & 15.3221 & 2.42785 \tabularnewline
284 & 15.2 & 13.7316 & 1.46843 \tabularnewline
285 & 14.6 & 12.6639 & 1.93612 \tabularnewline
286 & 16.65 & 19.251 & -2.60099 \tabularnewline
287 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264935&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]12.9[/C][C]12.2081[/C][C]0.691872[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]11.7176[/C][C]-4.31756[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]11.4314[/C][C]0.768586[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]12.0153[/C][C]0.78472[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]12.7382[/C][C]-5.3382[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]11.3114[/C][C]-4.61145[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]15.0725[/C][C]-2.47246[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]12.7762[/C][C]2.02384[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]12.3595[/C][C]0.940487[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]12.522[/C][C]-1.42196[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]14.1213[/C][C]-5.92131[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]12.9338[/C][C]-1.5338[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]14.626[/C][C]-8.226[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]11.4346[/C][C]-0.834609[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]13.562[/C][C]-1.56197[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]9.7074[/C][C]-3.4074[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]11.2718[/C][C]0.0281773[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]13.8085[/C][C]-1.90846[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]12.0296[/C][C]-2.72958[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]12.1789[/C][C]-2.57887[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]11.648[/C][C]-1.64798[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]11.5515[/C][C]-5.15148[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]12.2061[/C][C]1.59388[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]13.2352[/C][C]-2.43524[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]12.2915[/C][C]1.50854[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]12.6127[/C][C]-0.912678[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]15.1503[/C][C]-4.25026[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]13.0696[/C][C]3.0304[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]11.1755[/C][C]2.2245[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]11.4001[/C][C]-1.50014[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]12.2231[/C][C]-0.723137[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]11.9626[/C][C]-3.66259[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]13.2841[/C][C]-1.58407[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]12.026[/C][C]-5.92595[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]12.2642[/C][C]-3.26423[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]13.9791[/C][C]-4.27914[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]12.4445[/C][C]-1.64455[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]12.5575[/C][C]-2.25749[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]11.7811[/C][C]-1.38108[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]12.4078[/C][C]0.292247[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]11.9829[/C][C]-2.68285[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]14.2542[/C][C]-2.4542[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]10.5739[/C][C]-4.67392[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]13.6963[/C][C]-2.29634[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]11.7181[/C][C]1.28192[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]12.6958[/C][C]-1.8958[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]10.4603[/C][C]1.8397[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]13.2235[/C][C]-1.92349[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]12.5944[/C][C]-0.794436[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]10.9227[/C][C]-3.02271[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]10.3014[/C][C]2.39861[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]10.5998[/C][C]1.70019[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]11.9564[/C][C]-0.356408[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]11.0548[/C][C]-4.35476[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]13.1237[/C][C]-2.22371[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]12.5806[/C][C]-0.48056[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]13.395[/C][C]-0.0949918[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]13.3412[/C][C]-3.2412[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]11.6416[/C][C]-5.94161[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]12.1589[/C][C]2.1411[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]9.44565[/C][C]-1.44565[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]11.816[/C][C]1.48395[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]12.9102[/C][C]-3.61022[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]11.3371[/C][C]1.16292[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]10.8769[/C][C]-3.27689[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]13.8635[/C][C]2.03648[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]11.3377[/C][C]-2.13766[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]10.4837[/C][C]-1.38369[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]13.9632[/C][C]-2.8632[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]14.0153[/C][C]-1.01534[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]12.5114[/C][C]1.98862[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]10.9807[/C][C]1.2193[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]13.2123[/C][C]-0.912329[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]11.2519[/C][C]0.148128[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]11.3968[/C][C]-2.59676[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]11.0554[/C][C]3.54458[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]12.2249[/C][C]-4.92494[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]13.0065[/C][C]-0.406463[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]-0.678666[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]11.5132[/C][C]1.48685[/C][/ROW]
[ROW][C]81[/C][C]12.6[/C][C]14.1875[/C][C]-1.58749[/C][/ROW]
[ROW][C]82[/C][C]13.2[/C][C]14.4152[/C][C]-1.2152[/C][/ROW]
[ROW][C]83[/C][C]9.9[/C][C]13.7296[/C][C]-3.82959[/C][/ROW]
[ROW][C]84[/C][C]7.7[/C][C]7.76762[/C][C]-0.0676152[/C][/ROW]
[ROW][C]85[/C][C]10.5[/C][C]7.69309[/C][C]2.80691[/C][/ROW]
[ROW][C]86[/C][C]13.4[/C][C]14.4013[/C][C]-1.00128[/C][/ROW]
[ROW][C]87[/C][C]10.9[/C][C]16.7082[/C][C]-5.80822[/C][/ROW]
[ROW][C]88[/C][C]4.3[/C][C]5.00894[/C][C]-0.708935[/C][/ROW]
[ROW][C]89[/C][C]10.3[/C][C]10.2212[/C][C]0.0788073[/C][/ROW]
[ROW][C]90[/C][C]11.8[/C][C]11.071[/C][C]0.728968[/C][/ROW]
[ROW][C]91[/C][C]11.2[/C][C]10.3712[/C][C]0.828763[/C][/ROW]
[ROW][C]92[/C][C]11.4[/C][C]12.846[/C][C]-1.44595[/C][/ROW]
[ROW][C]93[/C][C]8.6[/C][C]6.42352[/C][C]2.17648[/C][/ROW]
[ROW][C]94[/C][C]13.2[/C][C]11.0189[/C][C]2.18108[/C][/ROW]
[ROW][C]95[/C][C]12.6[/C][C]18.0975[/C][C]-5.49749[/C][/ROW]
[ROW][C]96[/C][C]5.6[/C][C]7.34318[/C][C]-1.74318[/C][/ROW]
[ROW][C]97[/C][C]9.9[/C][C]12.9452[/C][C]-3.04518[/C][/ROW]
[ROW][C]98[/C][C]8.8[/C][C]12.6926[/C][C]-3.89256[/C][/ROW]
[ROW][C]99[/C][C]7.7[/C][C]9.08359[/C][C]-1.38359[/C][/ROW]
[ROW][C]100[/C][C]9[/C][C]13.926[/C][C]-4.92601[/C][/ROW]
[ROW][C]101[/C][C]7.3[/C][C]6.75784[/C][C]0.542156[/C][/ROW]
[ROW][C]102[/C][C]11.4[/C][C]9.16989[/C][C]2.23011[/C][/ROW]
[ROW][C]103[/C][C]13.6[/C][C]16.2175[/C][C]-2.61752[/C][/ROW]
[ROW][C]104[/C][C]7.9[/C][C]8.22887[/C][C]-0.328865[/C][/ROW]
[ROW][C]105[/C][C]10.7[/C][C]12.0589[/C][C]-1.3589[/C][/ROW]
[ROW][C]106[/C][C]10.3[/C][C]12.2821[/C][C]-1.98206[/C][/ROW]
[ROW][C]107[/C][C]8.3[/C][C]9.61267[/C][C]-1.31267[/C][/ROW]
[ROW][C]108[/C][C]9.6[/C][C]7.1458[/C][C]2.4542[/C][/ROW]
[ROW][C]109[/C][C]14.2[/C][C]16.0115[/C][C]-1.81154[/C][/ROW]
[ROW][C]110[/C][C]8.5[/C][C]5.58469[/C][C]2.91531[/C][/ROW]
[ROW][C]111[/C][C]13.5[/C][C]19.3782[/C][C]-5.8782[/C][/ROW]
[ROW][C]112[/C][C]4.9[/C][C]8.73948[/C][C]-3.83948[/C][/ROW]
[ROW][C]113[/C][C]6.4[/C][C]7.32462[/C][C]-0.924625[/C][/ROW]
[ROW][C]114[/C][C]9.6[/C][C]8.74854[/C][C]0.851464[/C][/ROW]
[ROW][C]115[/C][C]11.6[/C][C]10.7411[/C][C]0.858901[/C][/ROW]
[ROW][C]116[/C][C]11.1[/C][C]16.5802[/C][C]-5.48017[/C][/ROW]
[ROW][C]117[/C][C]4.35[/C][C]4.33761[/C][C]0.0123949[/C][/ROW]
[ROW][C]118[/C][C]12.7[/C][C]9.2399[/C][C]3.4601[/C][/ROW]
[ROW][C]119[/C][C]18.1[/C][C]15.2085[/C][C]2.89153[/C][/ROW]
[ROW][C]120[/C][C]17.85[/C][C]17.5391[/C][C]0.310912[/C][/ROW]
[ROW][C]121[/C][C]16.6[/C][C]13.888[/C][C]2.71204[/C][/ROW]
[ROW][C]122[/C][C]12.6[/C][C]17.5577[/C][C]-4.95773[/C][/ROW]
[ROW][C]123[/C][C]17.1[/C][C]13.4069[/C][C]3.69311[/C][/ROW]
[ROW][C]124[/C][C]19.1[/C][C]21.7586[/C][C]-2.6586[/C][/ROW]
[ROW][C]125[/C][C]16.1[/C][C]13.2624[/C][C]2.83761[/C][/ROW]
[ROW][C]126[/C][C]13.35[/C][C]12.5701[/C][C]0.779858[/C][/ROW]
[ROW][C]127[/C][C]18.4[/C][C]14.6705[/C][C]3.72948[/C][/ROW]
[ROW][C]128[/C][C]14.7[/C][C]18.731[/C][C]-4.03099[/C][/ROW]
[ROW][C]129[/C][C]10.6[/C][C]11.6552[/C][C]-1.05524[/C][/ROW]
[ROW][C]130[/C][C]12.6[/C][C]11.4162[/C][C]1.18382[/C][/ROW]
[ROW][C]131[/C][C]16.2[/C][C]19.6676[/C][C]-3.46758[/C][/ROW]
[ROW][C]132[/C][C]13.6[/C][C]10.1693[/C][C]3.43073[/C][/ROW]
[ROW][C]133[/C][C]18.9[/C][C]16.9449[/C][C]1.9551[/C][/ROW]
[ROW][C]134[/C][C]14.1[/C][C]11.3015[/C][C]2.79854[/C][/ROW]
[ROW][C]135[/C][C]14.5[/C][C]16.2208[/C][C]-1.72078[/C][/ROW]
[ROW][C]136[/C][C]16.15[/C][C]14.7335[/C][C]1.41655[/C][/ROW]
[ROW][C]137[/C][C]14.75[/C][C]14.036[/C][C]0.714001[/C][/ROW]
[ROW][C]138[/C][C]14.8[/C][C]14.6034[/C][C]0.196579[/C][/ROW]
[ROW][C]139[/C][C]12.45[/C][C]14.4461[/C][C]-1.99607[/C][/ROW]
[ROW][C]140[/C][C]12.65[/C][C]9.02286[/C][C]3.62714[/C][/ROW]
[ROW][C]141[/C][C]17.35[/C][C]20.8451[/C][C]-3.49508[/C][/ROW]
[ROW][C]142[/C][C]8.6[/C][C]7.92694[/C][C]0.673058[/C][/ROW]
[ROW][C]143[/C][C]18.4[/C][C]20.4028[/C][C]-2.00283[/C][/ROW]
[ROW][C]144[/C][C]16.1[/C][C]15.6125[/C][C]0.48755[/C][/ROW]
[ROW][C]145[/C][C]11.6[/C][C]5.5871[/C][C]6.0129[/C][/ROW]
[ROW][C]146[/C][C]17.75[/C][C]16.0594[/C][C]1.69061[/C][/ROW]
[ROW][C]147[/C][C]15.25[/C][C]13.7872[/C][C]1.46282[/C][/ROW]
[ROW][C]148[/C][C]17.65[/C][C]15.6044[/C][C]2.04556[/C][/ROW]
[ROW][C]149[/C][C]15.6[/C][C]14.2267[/C][C]1.37327[/C][/ROW]
[ROW][C]150[/C][C]16.35[/C][C]13.713[/C][C]2.63704[/C][/ROW]
[ROW][C]151[/C][C]17.65[/C][C]16.8582[/C][C]0.791797[/C][/ROW]
[ROW][C]152[/C][C]13.6[/C][C]13.9824[/C][C]-0.38245[/C][/ROW]
[ROW][C]153[/C][C]11.7[/C][C]10.7729[/C][C]0.927051[/C][/ROW]
[ROW][C]154[/C][C]14.35[/C][C]17.3363[/C][C]-2.98631[/C][/ROW]
[ROW][C]155[/C][C]14.75[/C][C]12.6236[/C][C]2.12636[/C][/ROW]
[ROW][C]156[/C][C]18.25[/C][C]23.423[/C][C]-5.17295[/C][/ROW]
[ROW][C]157[/C][C]9.9[/C][C]8.0323[/C][C]1.8677[/C][/ROW]
[ROW][C]158[/C][C]16[/C][C]13.2638[/C][C]2.73617[/C][/ROW]
[ROW][C]159[/C][C]18.25[/C][C]18.6767[/C][C]-0.426701[/C][/ROW]
[ROW][C]160[/C][C]16.85[/C][C]14.7246[/C][C]2.12542[/C][/ROW]
[ROW][C]161[/C][C]14.6[/C][C]14.7406[/C][C]-0.140606[/C][/ROW]
[ROW][C]162[/C][C]13.85[/C][C]11.2593[/C][C]2.59065[/C][/ROW]
[ROW][C]163[/C][C]18.95[/C][C]17.8467[/C][C]1.10327[/C][/ROW]
[ROW][C]164[/C][C]15.6[/C][C]18.2047[/C][C]-2.60466[/C][/ROW]
[ROW][C]165[/C][C]14.85[/C][C]15.3208[/C][C]-0.470804[/C][/ROW]
[ROW][C]166[/C][C]11.75[/C][C]6.31169[/C][C]5.43831[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]20.0402[/C][C]-1.59021[/C][/ROW]
[ROW][C]168[/C][C]15.9[/C][C]12.9139[/C][C]2.98608[/C][/ROW]
[ROW][C]169[/C][C]17.1[/C][C]11.9411[/C][C]5.15886[/C][/ROW]
[ROW][C]170[/C][C]16.1[/C][C]10.8057[/C][C]5.2943[/C][/ROW]
[ROW][C]171[/C][C]19.9[/C][C]18.9818[/C][C]0.91822[/C][/ROW]
[ROW][C]172[/C][C]10.95[/C][C]8.34457[/C][C]2.60543[/C][/ROW]
[ROW][C]173[/C][C]18.45[/C][C]13.6069[/C][C]4.84314[/C][/ROW]
[ROW][C]174[/C][C]15.1[/C][C]15.4431[/C][C]-0.343142[/C][/ROW]
[ROW][C]175[/C][C]15[/C][C]17.8305[/C][C]-2.83053[/C][/ROW]
[ROW][C]176[/C][C]11.35[/C][C]10.4135[/C][C]0.936529[/C][/ROW]
[ROW][C]177[/C][C]15.95[/C][C]11.0794[/C][C]4.87056[/C][/ROW]
[ROW][C]178[/C][C]18.1[/C][C]16.2436[/C][C]1.85644[/C][/ROW]
[ROW][C]179[/C][C]14.6[/C][C]15.1479[/C][C]-0.54794[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]15.9479[/C][C]-0.54794[/C][/ROW]
[ROW][C]181[/C][C]15.4[/C][C]11.386[/C][C]4.01396[/C][/ROW]
[ROW][C]182[/C][C]17.6[/C][C]18.0651[/C][C]-0.465081[/C][/ROW]
[ROW][C]183[/C][C]13.35[/C][C]10.8257[/C][C]2.52428[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]16.7496[/C][C]2.3504[/C][/ROW]
[ROW][C]185[/C][C]15.35[/C][C]19.7864[/C][C]-4.43641[/C][/ROW]
[ROW][C]186[/C][C]7.6[/C][C]8.23536[/C][C]-0.635363[/C][/ROW]
[ROW][C]187[/C][C]13.4[/C][C]12.9173[/C][C]0.482671[/C][/ROW]
[ROW][C]188[/C][C]13.9[/C][C]11.9745[/C][C]1.92553[/C][/ROW]
[ROW][C]189[/C][C]19.1[/C][C]17.7577[/C][C]1.34226[/C][/ROW]
[ROW][C]190[/C][C]15.25[/C][C]14.3165[/C][C]0.933521[/C][/ROW]
[ROW][C]191[/C][C]12.9[/C][C]10.6173[/C][C]2.28272[/C][/ROW]
[ROW][C]192[/C][C]16.1[/C][C]10.8101[/C][C]5.2899[/C][/ROW]
[ROW][C]193[/C][C]17.35[/C][C]16.3711[/C][C]0.978901[/C][/ROW]
[ROW][C]194[/C][C]13.15[/C][C]10.3369[/C][C]2.81306[/C][/ROW]
[ROW][C]195[/C][C]12.15[/C][C]12.1771[/C][C]-0.0270729[/C][/ROW]
[ROW][C]196[/C][C]12.6[/C][C]13.6517[/C][C]-1.05166[/C][/ROW]
[ROW][C]197[/C][C]10.35[/C][C]7.75666[/C][C]2.59334[/C][/ROW]
[ROW][C]198[/C][C]15.4[/C][C]16.6944[/C][C]-1.29441[/C][/ROW]
[ROW][C]199[/C][C]9.6[/C][C]4.5231[/C][C]5.0769[/C][/ROW]
[ROW][C]200[/C][C]18.2[/C][C]16.6613[/C][C]1.53874[/C][/ROW]
[ROW][C]201[/C][C]13.6[/C][C]13.288[/C][C]0.312007[/C][/ROW]
[ROW][C]202[/C][C]14.85[/C][C]17.0871[/C][C]-2.23714[/C][/ROW]
[ROW][C]203[/C][C]14.75[/C][C]14.5017[/C][C]0.248318[/C][/ROW]
[ROW][C]204[/C][C]14.1[/C][C]10.2231[/C][C]3.87689[/C][/ROW]
[ROW][C]205[/C][C]14.9[/C][C]11.2973[/C][C]3.60272[/C][/ROW]
[ROW][C]206[/C][C]16.25[/C][C]14.2154[/C][C]2.03461[/C][/ROW]
[ROW][C]207[/C][C]19.25[/C][C]17.5615[/C][C]1.6885[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]13.1983[/C][C]0.401737[/C][/ROW]
[ROW][C]209[/C][C]13.6[/C][C]13.1031[/C][C]0.496856[/C][/ROW]
[ROW][C]210[/C][C]15.65[/C][C]14.8254[/C][C]0.824629[/C][/ROW]
[ROW][C]211[/C][C]12.75[/C][C]9.00631[/C][C]3.74369[/C][/ROW]
[ROW][C]212[/C][C]14.6[/C][C]18.0634[/C][C]-3.46335[/C][/ROW]
[ROW][C]213[/C][C]9.85[/C][C]8.22188[/C][C]1.62812[/C][/ROW]
[ROW][C]214[/C][C]12.65[/C][C]12.828[/C][C]-0.178015[/C][/ROW]
[ROW][C]215[/C][C]11.9[/C][C]9.42835[/C][C]2.47165[/C][/ROW]
[ROW][C]216[/C][C]19.2[/C][C]16.8045[/C][C]2.3955[/C][/ROW]
[ROW][C]217[/C][C]16.6[/C][C]15.3822[/C][C]1.21781[/C][/ROW]
[ROW][C]218[/C][C]11.2[/C][C]8.84575[/C][C]2.35425[/C][/ROW]
[ROW][C]219[/C][C]15.25[/C][C]18.5115[/C][C]-3.26149[/C][/ROW]
[ROW][C]220[/C][C]11.9[/C][C]14.4742[/C][C]-2.57424[/C][/ROW]
[ROW][C]221[/C][C]13.2[/C][C]14.1377[/C][C]-0.937741[/C][/ROW]
[ROW][C]222[/C][C]16.35[/C][C]17.1963[/C][C]-0.846294[/C][/ROW]
[ROW][C]223[/C][C]12.4[/C][C]9.39506[/C][C]3.00494[/C][/ROW]
[ROW][C]224[/C][C]15.85[/C][C]14.7599[/C][C]1.09013[/C][/ROW]
[ROW][C]225[/C][C]14.35[/C][C]11.0953[/C][C]3.25469[/C][/ROW]
[ROW][C]226[/C][C]18.15[/C][C]18.4323[/C][C]-0.282305[/C][/ROW]
[ROW][C]227[/C][C]11.15[/C][C]10.9196[/C][C]0.230408[/C][/ROW]
[ROW][C]228[/C][C]15.65[/C][C]13.8701[/C][C]1.77992[/C][/ROW]
[ROW][C]229[/C][C]17.75[/C][C]22.6153[/C][C]-4.86525[/C][/ROW]
[ROW][C]230[/C][C]7.65[/C][C]6.93206[/C][C]0.717937[/C][/ROW]
[ROW][C]231[/C][C]12.35[/C][C]8.11278[/C][C]4.23722[/C][/ROW]
[ROW][C]232[/C][C]15.6[/C][C]12.5834[/C][C]3.01661[/C][/ROW]
[ROW][C]233[/C][C]19.3[/C][C]15.7722[/C][C]3.52781[/C][/ROW]
[ROW][C]234[/C][C]15.2[/C][C]11.4242[/C][C]3.77585[/C][/ROW]
[ROW][C]235[/C][C]17.1[/C][C]13.7986[/C][C]3.3014[/C][/ROW]
[ROW][C]236[/C][C]15.6[/C][C]12.4913[/C][C]3.10869[/C][/ROW]
[ROW][C]237[/C][C]18.4[/C][C]14.4713[/C][C]3.92873[/C][/ROW]
[ROW][C]238[/C][C]19.05[/C][C]13.3678[/C][C]5.68221[/C][/ROW]
[ROW][C]239[/C][C]18.55[/C][C]16.5372[/C][C]2.01282[/C][/ROW]
[ROW][C]240[/C][C]19.1[/C][C]17.6429[/C][C]1.45712[/C][/ROW]
[ROW][C]241[/C][C]13.1[/C][C]13.1711[/C][C]-0.0710947[/C][/ROW]
[ROW][C]242[/C][C]12.85[/C][C]14.8285[/C][C]-1.97853[/C][/ROW]
[ROW][C]243[/C][C]9.5[/C][C]16.0952[/C][C]-6.59515[/C][/ROW]
[ROW][C]244[/C][C]4.5[/C][C]3.07951[/C][C]1.42049[/C][/ROW]
[ROW][C]245[/C][C]11.85[/C][C]13.8587[/C][C]-2.00875[/C][/ROW]
[ROW][C]246[/C][C]13.6[/C][C]15.3179[/C][C]-1.71791[/C][/ROW]
[ROW][C]247[/C][C]11.7[/C][C]10.5557[/C][C]1.14433[/C][/ROW]
[ROW][C]248[/C][C]12.4[/C][C]13.9936[/C][C]-1.59361[/C][/ROW]
[ROW][C]249[/C][C]13.35[/C][C]15.8246[/C][C]-2.47459[/C][/ROW]
[ROW][C]250[/C][C]11.4[/C][C]7.91386[/C][C]3.48614[/C][/ROW]
[ROW][C]251[/C][C]14.9[/C][C]9.6057[/C][C]5.2943[/C][/ROW]
[ROW][C]252[/C][C]19.9[/C][C]13.9454[/C][C]5.95459[/C][/ROW]
[ROW][C]253[/C][C]17.75[/C][C]17.9939[/C][C]-0.243885[/C][/ROW]
[ROW][C]254[/C][C]11.2[/C][C]12.0525[/C][C]-0.852468[/C][/ROW]
[ROW][C]255[/C][C]14.6[/C][C]13.2971[/C][C]1.30292[/C][/ROW]
[ROW][C]256[/C][C]17.6[/C][C]15.6563[/C][C]1.94373[/C][/ROW]
[ROW][C]257[/C][C]14.05[/C][C]13.4527[/C][C]0.597287[/C][/ROW]
[ROW][C]258[/C][C]16.1[/C][C]15.7802[/C][C]0.319819[/C][/ROW]
[ROW][C]259[/C][C]13.35[/C][C]13.5857[/C][C]-0.235731[/C][/ROW]
[ROW][C]260[/C][C]11.85[/C][C]14.3169[/C][C]-2.46693[/C][/ROW]
[ROW][C]261[/C][C]11.95[/C][C]11.9009[/C][C]0.0490522[/C][/ROW]
[ROW][C]262[/C][C]14.75[/C][C]12.8797[/C][C]1.87033[/C][/ROW]
[ROW][C]263[/C][C]15.15[/C][C]15.5642[/C][C]-0.414167[/C][/ROW]
[ROW][C]264[/C][C]13.2[/C][C]11.7398[/C][C]1.46023[/C][/ROW]
[ROW][C]265[/C][C]16.85[/C][C]19.0263[/C][C]-2.17626[/C][/ROW]
[ROW][C]266[/C][C]7.85[/C][C]14.6658[/C][C]-6.81579[/C][/ROW]
[ROW][C]267[/C][C]7.7[/C][C]6.46683[/C][C]1.23317[/C][/ROW]
[ROW][C]268[/C][C]12.6[/C][C]16.0774[/C][C]-3.47735[/C][/ROW]
[ROW][C]269[/C][C]7.85[/C][C]6.93178[/C][C]0.91822[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]10.5397[/C][C]0.410262[/C][/ROW]
[ROW][C]271[/C][C]12.35[/C][C]14.6026[/C][C]-2.25263[/C][/ROW]
[ROW][C]272[/C][C]9.95[/C][C]6.46386[/C][C]3.48614[/C][/ROW]
[ROW][C]273[/C][C]14.9[/C][C]12.7707[/C][C]2.12929[/C][/ROW]
[ROW][C]274[/C][C]16.65[/C][C]16.2945[/C][C]0.355502[/C][/ROW]
[ROW][C]275[/C][C]13.4[/C][C]12.7376[/C][C]0.662409[/C][/ROW]
[ROW][C]276[/C][C]13.95[/C][C]9.49294[/C][C]4.45706[/C][/ROW]
[ROW][C]277[/C][C]15.7[/C][C]11.0884[/C][C]4.61158[/C][/ROW]
[ROW][C]278[/C][C]16.85[/C][C]16.253[/C][C]0.596957[/C][/ROW]
[ROW][C]279[/C][C]10.95[/C][C]7.03514[/C][C]3.91486[/C][/ROW]
[ROW][C]280[/C][C]15.35[/C][C]14.0821[/C][C]1.26789[/C][/ROW]
[ROW][C]281[/C][C]12.2[/C][C]11.2276[/C][C]0.972379[/C][/ROW]
[ROW][C]282[/C][C]15.1[/C][C]13.823[/C][C]1.27699[/C][/ROW]
[ROW][C]283[/C][C]17.75[/C][C]15.3221[/C][C]2.42785[/C][/ROW]
[ROW][C]284[/C][C]15.2[/C][C]13.7316[/C][C]1.46843[/C][/ROW]
[ROW][C]285[/C][C]14.6[/C][C]12.6639[/C][C]1.93612[/C][/ROW]
[ROW][C]286[/C][C]16.65[/C][C]19.251[/C][C]-2.60099[/C][/ROW]
[ROW][C]287[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264935&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264935&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
112.912.20810.691872
27.411.7176-4.31756
312.211.43140.768586
412.812.01530.78472
57.412.7382-5.3382
66.711.3114-4.61145
712.615.0725-2.47246
814.812.77622.02384
913.312.35950.940487
1011.112.522-1.42196
118.214.1213-5.92131
1211.412.9338-1.5338
136.414.626-8.226
1410.611.4346-0.834609
151213.562-1.56197
166.39.7074-3.4074
1711.311.27180.0281773
1811.913.8085-1.90846
199.312.0296-2.72958
209.612.1789-2.57887
211011.648-1.64798
226.411.5515-5.15148
2313.812.20611.59388
2410.813.2352-2.43524
2513.812.29151.50854
2611.712.6127-0.912678
2710.915.1503-4.25026
2816.113.06963.0304
2913.411.17552.2245
309.911.4001-1.50014
3111.512.2231-0.723137
328.311.9626-3.66259
3311.713.2841-1.58407
346.112.026-5.92595
35912.2642-3.26423
369.713.9791-4.27914
3710.812.4445-1.64455
3810.312.5575-2.25749
3910.411.7811-1.38108
4012.712.40780.292247
419.311.9829-2.68285
4211.814.2542-2.4542
435.910.5739-4.67392
4411.413.6963-2.29634
451311.71811.28192
4610.812.6958-1.8958
4712.310.46031.8397
4811.313.2235-1.92349
4911.812.5944-0.794436
507.910.9227-3.02271
5112.710.30142.39861
5212.310.59981.70019
5311.611.9564-0.356408
546.711.0548-4.35476
5510.913.1237-2.22371
5612.112.5806-0.48056
5713.313.395-0.0949918
5810.113.3412-3.2412
595.711.6416-5.94161
6014.312.15892.1411
6189.44565-1.44565
6213.311.8161.48395
639.312.9102-3.61022
6412.511.33711.16292
657.610.8769-3.27689
6615.913.86352.03648
679.211.3377-2.13766
689.110.4837-1.38369
6911.113.9632-2.8632
701314.0153-1.01534
7114.512.51141.98862
7212.210.98071.2193
7312.313.2123-0.912329
7411.411.25190.148128
758.811.3968-2.59676
7614.611.05543.54458
777.312.2249-4.92494
7812.613.0065-0.406463
79NANA-0.678666
801311.51321.48685
8112.614.1875-1.58749
8213.214.4152-1.2152
839.913.7296-3.82959
847.77.76762-0.0676152
8510.57.693092.80691
8613.414.4013-1.00128
8710.916.7082-5.80822
884.35.00894-0.708935
8910.310.22120.0788073
9011.811.0710.728968
9111.210.37120.828763
9211.412.846-1.44595
938.66.423522.17648
9413.211.01892.18108
9512.618.0975-5.49749
965.67.34318-1.74318
979.912.9452-3.04518
988.812.6926-3.89256
997.79.08359-1.38359
100913.926-4.92601
1017.36.757840.542156
10211.49.169892.23011
10313.616.2175-2.61752
1047.98.22887-0.328865
10510.712.0589-1.3589
10610.312.2821-1.98206
1078.39.61267-1.31267
1089.67.14582.4542
10914.216.0115-1.81154
1108.55.584692.91531
11113.519.3782-5.8782
1124.98.73948-3.83948
1136.47.32462-0.924625
1149.68.748540.851464
11511.610.74110.858901
11611.116.5802-5.48017
1174.354.337610.0123949
11812.79.23993.4601
11918.115.20852.89153
12017.8517.53910.310912
12116.613.8882.71204
12212.617.5577-4.95773
12317.113.40693.69311
12419.121.7586-2.6586
12516.113.26242.83761
12613.3512.57010.779858
12718.414.67053.72948
12814.718.731-4.03099
12910.611.6552-1.05524
13012.611.41621.18382
13116.219.6676-3.46758
13213.610.16933.43073
13318.916.94491.9551
13414.111.30152.79854
13514.516.2208-1.72078
13616.1514.73351.41655
13714.7514.0360.714001
13814.814.60340.196579
13912.4514.4461-1.99607
14012.659.022863.62714
14117.3520.8451-3.49508
1428.67.926940.673058
14318.420.4028-2.00283
14416.115.61250.48755
14511.65.58716.0129
14617.7516.05941.69061
14715.2513.78721.46282
14817.6515.60442.04556
14915.614.22671.37327
15016.3513.7132.63704
15117.6516.85820.791797
15213.613.9824-0.38245
15311.710.77290.927051
15414.3517.3363-2.98631
15514.7512.62362.12636
15618.2523.423-5.17295
1579.98.03231.8677
1581613.26382.73617
15918.2518.6767-0.426701
16016.8514.72462.12542
16114.614.7406-0.140606
16213.8511.25932.59065
16318.9517.84671.10327
16415.618.2047-2.60466
16514.8515.3208-0.470804
16611.756.311695.43831
16718.4520.0402-1.59021
16815.912.91392.98608
16917.111.94115.15886
17016.110.80575.2943
17119.918.98180.91822
17210.958.344572.60543
17318.4513.60694.84314
17415.115.4431-0.343142
1751517.8305-2.83053
17611.3510.41350.936529
17715.9511.07944.87056
17818.116.24361.85644
17914.615.1479-0.54794
18015.415.9479-0.54794
18115.411.3864.01396
18217.618.0651-0.465081
18313.3510.82572.52428
18419.116.74962.3504
18515.3519.7864-4.43641
1867.68.23536-0.635363
18713.412.91730.482671
18813.911.97451.92553
18919.117.75771.34226
19015.2514.31650.933521
19112.910.61732.28272
19216.110.81015.2899
19317.3516.37110.978901
19413.1510.33692.81306
19512.1512.1771-0.0270729
19612.613.6517-1.05166
19710.357.756662.59334
19815.416.6944-1.29441
1999.64.52315.0769
20018.216.66131.53874
20113.613.2880.312007
20214.8517.0871-2.23714
20314.7514.50170.248318
20414.110.22313.87689
20514.911.29733.60272
20616.2514.21542.03461
20719.2517.56151.6885
20813.613.19830.401737
20913.613.10310.496856
21015.6514.82540.824629
21112.759.006313.74369
21214.618.0634-3.46335
2139.858.221881.62812
21412.6512.828-0.178015
21511.99.428352.47165
21619.216.80452.3955
21716.615.38221.21781
21811.28.845752.35425
21915.2518.5115-3.26149
22011.914.4742-2.57424
22113.214.1377-0.937741
22216.3517.1963-0.846294
22312.49.395063.00494
22415.8514.75991.09013
22514.3511.09533.25469
22618.1518.4323-0.282305
22711.1510.91960.230408
22815.6513.87011.77992
22917.7522.6153-4.86525
2307.656.932060.717937
23112.358.112784.23722
23215.612.58343.01661
23319.315.77223.52781
23415.211.42423.77585
23517.113.79863.3014
23615.612.49133.10869
23718.414.47133.92873
23819.0513.36785.68221
23918.5516.53722.01282
24019.117.64291.45712
24113.113.1711-0.0710947
24212.8514.8285-1.97853
2439.516.0952-6.59515
2444.53.079511.42049
24511.8513.8587-2.00875
24613.615.3179-1.71791
24711.710.55571.14433
24812.413.9936-1.59361
24913.3515.8246-2.47459
25011.47.913863.48614
25114.99.60575.2943
25219.913.94545.95459
25317.7517.9939-0.243885
25411.212.0525-0.852468
25514.613.29711.30292
25617.615.65631.94373
25714.0513.45270.597287
25816.115.78020.319819
25913.3513.5857-0.235731
26011.8514.3169-2.46693
26111.9511.90090.0490522
26214.7512.87971.87033
26315.1515.5642-0.414167
26413.211.73981.46023
26516.8519.0263-2.17626
2667.8514.6658-6.81579
2677.76.466831.23317
26812.616.0774-3.47735
2697.856.931780.91822
27010.9510.53970.410262
27112.3514.6026-2.25263
2729.956.463863.48614
27314.912.77072.12929
27416.6516.29450.355502
27513.412.73760.662409
27613.959.492944.45706
27715.711.08844.61158
27816.8516.2530.596957
27910.957.035143.91486
28015.3514.08211.26789
28112.211.22760.972379
28215.113.8231.27699
28317.7515.32212.42785
28415.213.73161.46843
28514.612.66391.93612
28616.6519.251-2.60099
2878.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.8807110.2385790.119289
80.891530.2169410.10847
90.8218680.3562630.178132
100.7496730.5006540.250327
110.7954710.4090580.204529
120.7235250.552950.276475
130.7767990.4464020.223201
140.7066780.5866450.293322
150.6286260.7427470.371374
160.5854030.8291940.414597
170.589130.8217390.41087
180.5220260.9559470.477974
190.4493070.8986140.550693
200.3835880.7671760.616412
210.3171690.6343380.682831
220.371670.743340.62833
230.318130.6362610.68187
240.2646520.5293040.735348
250.2228060.4456120.777194
260.1805090.3610180.819491
270.1514610.3029210.848539
280.1222050.244410.877795
290.1748190.3496380.825181
300.1453710.2907420.854629
310.1330970.2661930.866903
320.1123190.2246370.887681
330.110790.221580.88921
340.1680730.3361470.831927
350.1412670.2825340.858733
360.155530.311060.84447
370.1306670.2613350.869333
380.1069910.2139820.893009
390.08892390.1778480.911076
400.1009560.2019120.899044
410.1149290.2298570.885071
420.1025580.2051170.897442
430.1437170.2874340.856283
440.1232840.2465680.876716
450.1121070.2242130.887893
460.09708260.1941650.902917
470.1032860.2065710.896714
480.08750210.1750040.912498
490.07450360.1490070.925496
500.09239880.1847980.907601
510.1018520.2037040.898148
520.1045350.2090690.895465
530.09130050.1826010.9087
540.09544840.1908970.904552
550.08838120.1767620.911619
560.08836030.1767210.91164
570.08732290.1746460.912677
580.07626720.1525340.923733
590.1248410.2496810.875159
600.1551480.3102960.844852
610.1326680.2653350.867332
620.1413560.2827110.858644
630.1493450.2986910.850655
640.1438170.2876330.856183
650.148360.296720.85164
660.1870520.3741050.812948
670.1817870.3635730.818213
680.1584090.3168170.841591
690.1579110.3158220.842089
700.146470.292940.85353
710.1558220.3116430.844178
720.1452990.2905980.854701
730.1313670.2627330.868633
740.1172850.234570.882715
750.1058820.2117640.894118
760.1114380.2228760.888562
770.1906570.3813130.809343
780.1803630.3607260.819637
790.1703650.3407310.829635
800.1648630.3297260.835137
810.1627570.3255140.837243
820.1423990.2847970.857601
830.1715770.3431550.828423
840.1503410.3006820.849659
850.1678970.3357940.832103
860.1481330.2962650.851867
870.2610140.5220280.738986
880.2428320.4856630.757168
890.218660.437320.78134
900.1946260.3892520.805374
910.1745690.3491380.825431
920.1649380.3298760.835062
930.1734870.3469740.826513
940.1811960.3623910.818804
950.2703790.5407580.729621
960.2652720.5305430.734728
970.2599290.5198580.740071
980.2811630.5623270.718837
990.2731350.5462690.726865
1000.3499920.6999830.650008
1010.3369020.6738030.663098
1020.3838270.7676550.616173
1030.4400390.8800780.559961
1040.4114290.8228570.588571
1050.3941710.7883410.605829
1060.3939380.7878760.606062
1070.4061120.8122240.593888
1080.4379670.8759340.562033
1090.4610250.9220490.538975
1100.4804330.9608660.519567
1110.6716570.6566850.328343
1120.708630.5827390.29137
1130.7051840.5896320.294816
1140.6980870.6038260.301913
1150.6863840.6272320.313616
1160.8133380.3733230.186662
1170.8065690.3868630.193431
1180.8855330.2289340.114467
1190.9201630.1596750.0798374
1200.9098970.1802070.0901035
1210.9180460.1639090.0819544
1220.9185340.1629310.0814656
1230.9340270.1319460.0659728
1240.9381610.1236790.0618394
1250.9468420.1063160.0531578
1260.94870.10260.0513002
1270.9664950.06700980.0335049
1280.9725650.05486970.0274348
1290.9685240.06295170.0314759
1300.9679230.06415350.0320768
1310.9729960.05400890.0270045
1320.9762710.04745720.0237286
1330.9753520.04929670.0246484
1340.9774450.04510910.0225546
1350.9784320.04313580.0215679
1360.9762570.04748560.0237428
1370.9724750.05504910.0275245
1380.967230.06554020.0327701
1390.9626640.07467290.0373365
1400.9737830.0524340.026217
1410.9737930.05241340.0262067
1420.970790.05841930.0292096
1430.9660930.06781380.0339069
1440.9600970.07980530.0399027
1450.9803690.03926110.0196305
1460.9795930.04081320.0204066
1470.9790820.04183570.0209179
1480.9781230.04375410.0218771
1490.9754490.04910150.0245508
1500.9755150.04896940.0244847
1510.9718440.05631130.0281557
1520.9694580.06108330.0305416
1530.9643890.07122290.0356115
1540.9608390.07832210.039161
1550.9592730.08145490.0407275
1560.9849580.03008310.0150415
1570.9829620.03407510.0170376
1580.9832440.03351160.0167558
1590.9799940.04001120.0200056
1600.9803860.03922890.0196144
1610.9759440.04811110.0240556
1620.9745720.05085510.0254276
1630.9702630.05947470.0297374
1640.9686110.06277840.0313892
1650.9636840.07263240.0363162
1660.9767920.04641570.0232078
1670.9725040.05499270.0274964
1680.9717470.05650630.0282531
1690.9942310.01153730.00576863
1700.9955540.008891940.00444597
1710.9943340.01133210.00566605
1720.9942680.01146360.0057318
1730.9961670.007665040.00383252
1740.9950230.009954650.00497732
1750.99510.009799110.00489956
1760.9940120.0119750.00598752
1770.9959720.008056850.00402842
1780.9953820.009236660.00461833
1790.9944420.01111670.00555836
1800.9934080.01318420.00659208
1810.9947540.01049130.00524567
1820.9939250.01215070.00607537
1830.9936020.01279510.00639753
1840.9925860.01482880.00741442
1850.9949010.01019870.00509934
1860.994020.0119590.00597951
1870.9925580.01488480.00744242
1880.991270.01746090.00873047
1890.9893240.02135290.0106764
1900.9879320.02413610.0120681
1910.9861230.02775320.0138766
1920.9919370.01612610.00806306
1930.9900940.01981180.0099059
1940.988810.02237950.0111897
1950.9859460.02810870.0140544
1960.9828820.03423570.0171179
1970.9808760.03824870.0191244
1980.977580.044840.02242
1990.985690.0286210.0143105
2000.9831290.03374120.0168706
2010.9797710.04045870.0202294
2020.9804340.03913130.0195656
2030.9754430.04911370.0245569
2040.9775680.04486330.0224317
2050.9776040.04479140.0223957
2060.9763650.04726950.0236348
2070.9748790.05024130.0251206
2080.9711040.05779220.0288961
2090.964360.07127930.0356396
2100.9576650.08466910.0423345
2110.9641880.07162310.0358116
2120.9621810.07563760.0378188
2130.9606820.07863590.039318
2140.9515920.09681520.0484076
2150.9496770.1006470.0503234
2160.9452990.1094010.0547007
2170.9381440.1237120.0618558
2180.9281450.143710.071855
2190.9421270.1157460.0578732
2200.9314980.1370040.0685021
2210.9277250.1445490.0722746
2220.9173130.1653750.0826874
2230.9149040.1701920.0850961
2240.9054930.1890130.0945066
2250.894140.2117210.10586
2260.8731740.2536530.126826
2270.8494990.3010020.150501
2280.8256280.3487440.174372
2290.8459570.3080860.154043
2300.8202880.3594230.179712
2310.8262890.3474210.173711
2320.8079180.3841640.192082
2330.8591180.2817640.140882
2340.8737660.2524680.126234
2350.8702380.2595240.129762
2360.8654670.2690660.134533
2370.8760280.2479440.123972
2380.8890430.2219140.110957
2390.8694540.2610920.130546
2400.8489330.3021340.151067
2410.8502920.2994160.149708
2420.8387630.3224740.161237
2430.9349840.1300320.0650159
2440.9297070.1405850.0702925
2450.9484830.1030350.0515173
2460.9346660.1306680.0653342
2470.9165330.1669340.0834672
2480.9023220.1953560.0976779
2490.8831690.2336620.116831
2500.8725610.2548780.127439
2510.8630250.2739510.136975
2520.9245460.1509080.0754542
2530.9046150.190770.0953848
2540.8842980.2314030.115702
2550.8529560.2940870.147044
2560.8176530.3646930.182347
2570.7748960.4502080.225104
2580.726510.5469790.27349
2590.7010170.5979650.298983
2600.6880750.623850.311925
2610.62780.7443990.3722
2620.5857670.8284650.414233
2630.6373720.7252570.362628
2640.5770310.8459380.422969
2650.5646570.8706860.435343
2660.9495160.1009680.0504838
2670.92450.1509990.0754996
2680.9970670.00586620.0029331
2690.9973810.005238950.00261948
2700.9961450.007710280.00385514
2710.9999470.0001054295.27145e-05
2720.9998290.0003424850.000171243
2730.9996030.0007949390.00039747
2740.9993610.001277840.000638922
2750.9990210.001957830.000978916
2760.9965690.006861210.00343061
2770.9975270.004945970.00247298
2780.9906150.01877090.00938545
2790.9942950.01141030.00570517
2800.9739810.05203860.0260193

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.880711 & 0.238579 & 0.119289 \tabularnewline
8 & 0.89153 & 0.216941 & 0.10847 \tabularnewline
9 & 0.821868 & 0.356263 & 0.178132 \tabularnewline
10 & 0.749673 & 0.500654 & 0.250327 \tabularnewline
11 & 0.795471 & 0.409058 & 0.204529 \tabularnewline
12 & 0.723525 & 0.55295 & 0.276475 \tabularnewline
13 & 0.776799 & 0.446402 & 0.223201 \tabularnewline
14 & 0.706678 & 0.586645 & 0.293322 \tabularnewline
15 & 0.628626 & 0.742747 & 0.371374 \tabularnewline
16 & 0.585403 & 0.829194 & 0.414597 \tabularnewline
17 & 0.58913 & 0.821739 & 0.41087 \tabularnewline
18 & 0.522026 & 0.955947 & 0.477974 \tabularnewline
19 & 0.449307 & 0.898614 & 0.550693 \tabularnewline
20 & 0.383588 & 0.767176 & 0.616412 \tabularnewline
21 & 0.317169 & 0.634338 & 0.682831 \tabularnewline
22 & 0.37167 & 0.74334 & 0.62833 \tabularnewline
23 & 0.31813 & 0.636261 & 0.68187 \tabularnewline
24 & 0.264652 & 0.529304 & 0.735348 \tabularnewline
25 & 0.222806 & 0.445612 & 0.777194 \tabularnewline
26 & 0.180509 & 0.361018 & 0.819491 \tabularnewline
27 & 0.151461 & 0.302921 & 0.848539 \tabularnewline
28 & 0.122205 & 0.24441 & 0.877795 \tabularnewline
29 & 0.174819 & 0.349638 & 0.825181 \tabularnewline
30 & 0.145371 & 0.290742 & 0.854629 \tabularnewline
31 & 0.133097 & 0.266193 & 0.866903 \tabularnewline
32 & 0.112319 & 0.224637 & 0.887681 \tabularnewline
33 & 0.11079 & 0.22158 & 0.88921 \tabularnewline
34 & 0.168073 & 0.336147 & 0.831927 \tabularnewline
35 & 0.141267 & 0.282534 & 0.858733 \tabularnewline
36 & 0.15553 & 0.31106 & 0.84447 \tabularnewline
37 & 0.130667 & 0.261335 & 0.869333 \tabularnewline
38 & 0.106991 & 0.213982 & 0.893009 \tabularnewline
39 & 0.0889239 & 0.177848 & 0.911076 \tabularnewline
40 & 0.100956 & 0.201912 & 0.899044 \tabularnewline
41 & 0.114929 & 0.229857 & 0.885071 \tabularnewline
42 & 0.102558 & 0.205117 & 0.897442 \tabularnewline
43 & 0.143717 & 0.287434 & 0.856283 \tabularnewline
44 & 0.123284 & 0.246568 & 0.876716 \tabularnewline
45 & 0.112107 & 0.224213 & 0.887893 \tabularnewline
46 & 0.0970826 & 0.194165 & 0.902917 \tabularnewline
47 & 0.103286 & 0.206571 & 0.896714 \tabularnewline
48 & 0.0875021 & 0.175004 & 0.912498 \tabularnewline
49 & 0.0745036 & 0.149007 & 0.925496 \tabularnewline
50 & 0.0923988 & 0.184798 & 0.907601 \tabularnewline
51 & 0.101852 & 0.203704 & 0.898148 \tabularnewline
52 & 0.104535 & 0.209069 & 0.895465 \tabularnewline
53 & 0.0913005 & 0.182601 & 0.9087 \tabularnewline
54 & 0.0954484 & 0.190897 & 0.904552 \tabularnewline
55 & 0.0883812 & 0.176762 & 0.911619 \tabularnewline
56 & 0.0883603 & 0.176721 & 0.91164 \tabularnewline
57 & 0.0873229 & 0.174646 & 0.912677 \tabularnewline
58 & 0.0762672 & 0.152534 & 0.923733 \tabularnewline
59 & 0.124841 & 0.249681 & 0.875159 \tabularnewline
60 & 0.155148 & 0.310296 & 0.844852 \tabularnewline
61 & 0.132668 & 0.265335 & 0.867332 \tabularnewline
62 & 0.141356 & 0.282711 & 0.858644 \tabularnewline
63 & 0.149345 & 0.298691 & 0.850655 \tabularnewline
64 & 0.143817 & 0.287633 & 0.856183 \tabularnewline
65 & 0.14836 & 0.29672 & 0.85164 \tabularnewline
66 & 0.187052 & 0.374105 & 0.812948 \tabularnewline
67 & 0.181787 & 0.363573 & 0.818213 \tabularnewline
68 & 0.158409 & 0.316817 & 0.841591 \tabularnewline
69 & 0.157911 & 0.315822 & 0.842089 \tabularnewline
70 & 0.14647 & 0.29294 & 0.85353 \tabularnewline
71 & 0.155822 & 0.311643 & 0.844178 \tabularnewline
72 & 0.145299 & 0.290598 & 0.854701 \tabularnewline
73 & 0.131367 & 0.262733 & 0.868633 \tabularnewline
74 & 0.117285 & 0.23457 & 0.882715 \tabularnewline
75 & 0.105882 & 0.211764 & 0.894118 \tabularnewline
76 & 0.111438 & 0.222876 & 0.888562 \tabularnewline
77 & 0.190657 & 0.381313 & 0.809343 \tabularnewline
78 & 0.180363 & 0.360726 & 0.819637 \tabularnewline
79 & 0.170365 & 0.340731 & 0.829635 \tabularnewline
80 & 0.164863 & 0.329726 & 0.835137 \tabularnewline
81 & 0.162757 & 0.325514 & 0.837243 \tabularnewline
82 & 0.142399 & 0.284797 & 0.857601 \tabularnewline
83 & 0.171577 & 0.343155 & 0.828423 \tabularnewline
84 & 0.150341 & 0.300682 & 0.849659 \tabularnewline
85 & 0.167897 & 0.335794 & 0.832103 \tabularnewline
86 & 0.148133 & 0.296265 & 0.851867 \tabularnewline
87 & 0.261014 & 0.522028 & 0.738986 \tabularnewline
88 & 0.242832 & 0.485663 & 0.757168 \tabularnewline
89 & 0.21866 & 0.43732 & 0.78134 \tabularnewline
90 & 0.194626 & 0.389252 & 0.805374 \tabularnewline
91 & 0.174569 & 0.349138 & 0.825431 \tabularnewline
92 & 0.164938 & 0.329876 & 0.835062 \tabularnewline
93 & 0.173487 & 0.346974 & 0.826513 \tabularnewline
94 & 0.181196 & 0.362391 & 0.818804 \tabularnewline
95 & 0.270379 & 0.540758 & 0.729621 \tabularnewline
96 & 0.265272 & 0.530543 & 0.734728 \tabularnewline
97 & 0.259929 & 0.519858 & 0.740071 \tabularnewline
98 & 0.281163 & 0.562327 & 0.718837 \tabularnewline
99 & 0.273135 & 0.546269 & 0.726865 \tabularnewline
100 & 0.349992 & 0.699983 & 0.650008 \tabularnewline
101 & 0.336902 & 0.673803 & 0.663098 \tabularnewline
102 & 0.383827 & 0.767655 & 0.616173 \tabularnewline
103 & 0.440039 & 0.880078 & 0.559961 \tabularnewline
104 & 0.411429 & 0.822857 & 0.588571 \tabularnewline
105 & 0.394171 & 0.788341 & 0.605829 \tabularnewline
106 & 0.393938 & 0.787876 & 0.606062 \tabularnewline
107 & 0.406112 & 0.812224 & 0.593888 \tabularnewline
108 & 0.437967 & 0.875934 & 0.562033 \tabularnewline
109 & 0.461025 & 0.922049 & 0.538975 \tabularnewline
110 & 0.480433 & 0.960866 & 0.519567 \tabularnewline
111 & 0.671657 & 0.656685 & 0.328343 \tabularnewline
112 & 0.70863 & 0.582739 & 0.29137 \tabularnewline
113 & 0.705184 & 0.589632 & 0.294816 \tabularnewline
114 & 0.698087 & 0.603826 & 0.301913 \tabularnewline
115 & 0.686384 & 0.627232 & 0.313616 \tabularnewline
116 & 0.813338 & 0.373323 & 0.186662 \tabularnewline
117 & 0.806569 & 0.386863 & 0.193431 \tabularnewline
118 & 0.885533 & 0.228934 & 0.114467 \tabularnewline
119 & 0.920163 & 0.159675 & 0.0798374 \tabularnewline
120 & 0.909897 & 0.180207 & 0.0901035 \tabularnewline
121 & 0.918046 & 0.163909 & 0.0819544 \tabularnewline
122 & 0.918534 & 0.162931 & 0.0814656 \tabularnewline
123 & 0.934027 & 0.131946 & 0.0659728 \tabularnewline
124 & 0.938161 & 0.123679 & 0.0618394 \tabularnewline
125 & 0.946842 & 0.106316 & 0.0531578 \tabularnewline
126 & 0.9487 & 0.1026 & 0.0513002 \tabularnewline
127 & 0.966495 & 0.0670098 & 0.0335049 \tabularnewline
128 & 0.972565 & 0.0548697 & 0.0274348 \tabularnewline
129 & 0.968524 & 0.0629517 & 0.0314759 \tabularnewline
130 & 0.967923 & 0.0641535 & 0.0320768 \tabularnewline
131 & 0.972996 & 0.0540089 & 0.0270045 \tabularnewline
132 & 0.976271 & 0.0474572 & 0.0237286 \tabularnewline
133 & 0.975352 & 0.0492967 & 0.0246484 \tabularnewline
134 & 0.977445 & 0.0451091 & 0.0225546 \tabularnewline
135 & 0.978432 & 0.0431358 & 0.0215679 \tabularnewline
136 & 0.976257 & 0.0474856 & 0.0237428 \tabularnewline
137 & 0.972475 & 0.0550491 & 0.0275245 \tabularnewline
138 & 0.96723 & 0.0655402 & 0.0327701 \tabularnewline
139 & 0.962664 & 0.0746729 & 0.0373365 \tabularnewline
140 & 0.973783 & 0.052434 & 0.026217 \tabularnewline
141 & 0.973793 & 0.0524134 & 0.0262067 \tabularnewline
142 & 0.97079 & 0.0584193 & 0.0292096 \tabularnewline
143 & 0.966093 & 0.0678138 & 0.0339069 \tabularnewline
144 & 0.960097 & 0.0798053 & 0.0399027 \tabularnewline
145 & 0.980369 & 0.0392611 & 0.0196305 \tabularnewline
146 & 0.979593 & 0.0408132 & 0.0204066 \tabularnewline
147 & 0.979082 & 0.0418357 & 0.0209179 \tabularnewline
148 & 0.978123 & 0.0437541 & 0.0218771 \tabularnewline
149 & 0.975449 & 0.0491015 & 0.0245508 \tabularnewline
150 & 0.975515 & 0.0489694 & 0.0244847 \tabularnewline
151 & 0.971844 & 0.0563113 & 0.0281557 \tabularnewline
152 & 0.969458 & 0.0610833 & 0.0305416 \tabularnewline
153 & 0.964389 & 0.0712229 & 0.0356115 \tabularnewline
154 & 0.960839 & 0.0783221 & 0.039161 \tabularnewline
155 & 0.959273 & 0.0814549 & 0.0407275 \tabularnewline
156 & 0.984958 & 0.0300831 & 0.0150415 \tabularnewline
157 & 0.982962 & 0.0340751 & 0.0170376 \tabularnewline
158 & 0.983244 & 0.0335116 & 0.0167558 \tabularnewline
159 & 0.979994 & 0.0400112 & 0.0200056 \tabularnewline
160 & 0.980386 & 0.0392289 & 0.0196144 \tabularnewline
161 & 0.975944 & 0.0481111 & 0.0240556 \tabularnewline
162 & 0.974572 & 0.0508551 & 0.0254276 \tabularnewline
163 & 0.970263 & 0.0594747 & 0.0297374 \tabularnewline
164 & 0.968611 & 0.0627784 & 0.0313892 \tabularnewline
165 & 0.963684 & 0.0726324 & 0.0363162 \tabularnewline
166 & 0.976792 & 0.0464157 & 0.0232078 \tabularnewline
167 & 0.972504 & 0.0549927 & 0.0274964 \tabularnewline
168 & 0.971747 & 0.0565063 & 0.0282531 \tabularnewline
169 & 0.994231 & 0.0115373 & 0.00576863 \tabularnewline
170 & 0.995554 & 0.00889194 & 0.00444597 \tabularnewline
171 & 0.994334 & 0.0113321 & 0.00566605 \tabularnewline
172 & 0.994268 & 0.0114636 & 0.0057318 \tabularnewline
173 & 0.996167 & 0.00766504 & 0.00383252 \tabularnewline
174 & 0.995023 & 0.00995465 & 0.00497732 \tabularnewline
175 & 0.9951 & 0.00979911 & 0.00489956 \tabularnewline
176 & 0.994012 & 0.011975 & 0.00598752 \tabularnewline
177 & 0.995972 & 0.00805685 & 0.00402842 \tabularnewline
178 & 0.995382 & 0.00923666 & 0.00461833 \tabularnewline
179 & 0.994442 & 0.0111167 & 0.00555836 \tabularnewline
180 & 0.993408 & 0.0131842 & 0.00659208 \tabularnewline
181 & 0.994754 & 0.0104913 & 0.00524567 \tabularnewline
182 & 0.993925 & 0.0121507 & 0.00607537 \tabularnewline
183 & 0.993602 & 0.0127951 & 0.00639753 \tabularnewline
184 & 0.992586 & 0.0148288 & 0.00741442 \tabularnewline
185 & 0.994901 & 0.0101987 & 0.00509934 \tabularnewline
186 & 0.99402 & 0.011959 & 0.00597951 \tabularnewline
187 & 0.992558 & 0.0148848 & 0.00744242 \tabularnewline
188 & 0.99127 & 0.0174609 & 0.00873047 \tabularnewline
189 & 0.989324 & 0.0213529 & 0.0106764 \tabularnewline
190 & 0.987932 & 0.0241361 & 0.0120681 \tabularnewline
191 & 0.986123 & 0.0277532 & 0.0138766 \tabularnewline
192 & 0.991937 & 0.0161261 & 0.00806306 \tabularnewline
193 & 0.990094 & 0.0198118 & 0.0099059 \tabularnewline
194 & 0.98881 & 0.0223795 & 0.0111897 \tabularnewline
195 & 0.985946 & 0.0281087 & 0.0140544 \tabularnewline
196 & 0.982882 & 0.0342357 & 0.0171179 \tabularnewline
197 & 0.980876 & 0.0382487 & 0.0191244 \tabularnewline
198 & 0.97758 & 0.04484 & 0.02242 \tabularnewline
199 & 0.98569 & 0.028621 & 0.0143105 \tabularnewline
200 & 0.983129 & 0.0337412 & 0.0168706 \tabularnewline
201 & 0.979771 & 0.0404587 & 0.0202294 \tabularnewline
202 & 0.980434 & 0.0391313 & 0.0195656 \tabularnewline
203 & 0.975443 & 0.0491137 & 0.0245569 \tabularnewline
204 & 0.977568 & 0.0448633 & 0.0224317 \tabularnewline
205 & 0.977604 & 0.0447914 & 0.0223957 \tabularnewline
206 & 0.976365 & 0.0472695 & 0.0236348 \tabularnewline
207 & 0.974879 & 0.0502413 & 0.0251206 \tabularnewline
208 & 0.971104 & 0.0577922 & 0.0288961 \tabularnewline
209 & 0.96436 & 0.0712793 & 0.0356396 \tabularnewline
210 & 0.957665 & 0.0846691 & 0.0423345 \tabularnewline
211 & 0.964188 & 0.0716231 & 0.0358116 \tabularnewline
212 & 0.962181 & 0.0756376 & 0.0378188 \tabularnewline
213 & 0.960682 & 0.0786359 & 0.039318 \tabularnewline
214 & 0.951592 & 0.0968152 & 0.0484076 \tabularnewline
215 & 0.949677 & 0.100647 & 0.0503234 \tabularnewline
216 & 0.945299 & 0.109401 & 0.0547007 \tabularnewline
217 & 0.938144 & 0.123712 & 0.0618558 \tabularnewline
218 & 0.928145 & 0.14371 & 0.071855 \tabularnewline
219 & 0.942127 & 0.115746 & 0.0578732 \tabularnewline
220 & 0.931498 & 0.137004 & 0.0685021 \tabularnewline
221 & 0.927725 & 0.144549 & 0.0722746 \tabularnewline
222 & 0.917313 & 0.165375 & 0.0826874 \tabularnewline
223 & 0.914904 & 0.170192 & 0.0850961 \tabularnewline
224 & 0.905493 & 0.189013 & 0.0945066 \tabularnewline
225 & 0.89414 & 0.211721 & 0.10586 \tabularnewline
226 & 0.873174 & 0.253653 & 0.126826 \tabularnewline
227 & 0.849499 & 0.301002 & 0.150501 \tabularnewline
228 & 0.825628 & 0.348744 & 0.174372 \tabularnewline
229 & 0.845957 & 0.308086 & 0.154043 \tabularnewline
230 & 0.820288 & 0.359423 & 0.179712 \tabularnewline
231 & 0.826289 & 0.347421 & 0.173711 \tabularnewline
232 & 0.807918 & 0.384164 & 0.192082 \tabularnewline
233 & 0.859118 & 0.281764 & 0.140882 \tabularnewline
234 & 0.873766 & 0.252468 & 0.126234 \tabularnewline
235 & 0.870238 & 0.259524 & 0.129762 \tabularnewline
236 & 0.865467 & 0.269066 & 0.134533 \tabularnewline
237 & 0.876028 & 0.247944 & 0.123972 \tabularnewline
238 & 0.889043 & 0.221914 & 0.110957 \tabularnewline
239 & 0.869454 & 0.261092 & 0.130546 \tabularnewline
240 & 0.848933 & 0.302134 & 0.151067 \tabularnewline
241 & 0.850292 & 0.299416 & 0.149708 \tabularnewline
242 & 0.838763 & 0.322474 & 0.161237 \tabularnewline
243 & 0.934984 & 0.130032 & 0.0650159 \tabularnewline
244 & 0.929707 & 0.140585 & 0.0702925 \tabularnewline
245 & 0.948483 & 0.103035 & 0.0515173 \tabularnewline
246 & 0.934666 & 0.130668 & 0.0653342 \tabularnewline
247 & 0.916533 & 0.166934 & 0.0834672 \tabularnewline
248 & 0.902322 & 0.195356 & 0.0976779 \tabularnewline
249 & 0.883169 & 0.233662 & 0.116831 \tabularnewline
250 & 0.872561 & 0.254878 & 0.127439 \tabularnewline
251 & 0.863025 & 0.273951 & 0.136975 \tabularnewline
252 & 0.924546 & 0.150908 & 0.0754542 \tabularnewline
253 & 0.904615 & 0.19077 & 0.0953848 \tabularnewline
254 & 0.884298 & 0.231403 & 0.115702 \tabularnewline
255 & 0.852956 & 0.294087 & 0.147044 \tabularnewline
256 & 0.817653 & 0.364693 & 0.182347 \tabularnewline
257 & 0.774896 & 0.450208 & 0.225104 \tabularnewline
258 & 0.72651 & 0.546979 & 0.27349 \tabularnewline
259 & 0.701017 & 0.597965 & 0.298983 \tabularnewline
260 & 0.688075 & 0.62385 & 0.311925 \tabularnewline
261 & 0.6278 & 0.744399 & 0.3722 \tabularnewline
262 & 0.585767 & 0.828465 & 0.414233 \tabularnewline
263 & 0.637372 & 0.725257 & 0.362628 \tabularnewline
264 & 0.577031 & 0.845938 & 0.422969 \tabularnewline
265 & 0.564657 & 0.870686 & 0.435343 \tabularnewline
266 & 0.949516 & 0.100968 & 0.0504838 \tabularnewline
267 & 0.9245 & 0.150999 & 0.0754996 \tabularnewline
268 & 0.997067 & 0.0058662 & 0.0029331 \tabularnewline
269 & 0.997381 & 0.00523895 & 0.00261948 \tabularnewline
270 & 0.996145 & 0.00771028 & 0.00385514 \tabularnewline
271 & 0.999947 & 0.000105429 & 5.27145e-05 \tabularnewline
272 & 0.999829 & 0.000342485 & 0.000171243 \tabularnewline
273 & 0.999603 & 0.000794939 & 0.00039747 \tabularnewline
274 & 0.999361 & 0.00127784 & 0.000638922 \tabularnewline
275 & 0.999021 & 0.00195783 & 0.000978916 \tabularnewline
276 & 0.996569 & 0.00686121 & 0.00343061 \tabularnewline
277 & 0.997527 & 0.00494597 & 0.00247298 \tabularnewline
278 & 0.990615 & 0.0187709 & 0.00938545 \tabularnewline
279 & 0.994295 & 0.0114103 & 0.00570517 \tabularnewline
280 & 0.973981 & 0.0520386 & 0.0260193 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264935&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]7[/C][C]0.880711[/C][C]0.238579[/C][C]0.119289[/C][/ROW]
[ROW][C]8[/C][C]0.89153[/C][C]0.216941[/C][C]0.10847[/C][/ROW]
[ROW][C]9[/C][C]0.821868[/C][C]0.356263[/C][C]0.178132[/C][/ROW]
[ROW][C]10[/C][C]0.749673[/C][C]0.500654[/C][C]0.250327[/C][/ROW]
[ROW][C]11[/C][C]0.795471[/C][C]0.409058[/C][C]0.204529[/C][/ROW]
[ROW][C]12[/C][C]0.723525[/C][C]0.55295[/C][C]0.276475[/C][/ROW]
[ROW][C]13[/C][C]0.776799[/C][C]0.446402[/C][C]0.223201[/C][/ROW]
[ROW][C]14[/C][C]0.706678[/C][C]0.586645[/C][C]0.293322[/C][/ROW]
[ROW][C]15[/C][C]0.628626[/C][C]0.742747[/C][C]0.371374[/C][/ROW]
[ROW][C]16[/C][C]0.585403[/C][C]0.829194[/C][C]0.414597[/C][/ROW]
[ROW][C]17[/C][C]0.58913[/C][C]0.821739[/C][C]0.41087[/C][/ROW]
[ROW][C]18[/C][C]0.522026[/C][C]0.955947[/C][C]0.477974[/C][/ROW]
[ROW][C]19[/C][C]0.449307[/C][C]0.898614[/C][C]0.550693[/C][/ROW]
[ROW][C]20[/C][C]0.383588[/C][C]0.767176[/C][C]0.616412[/C][/ROW]
[ROW][C]21[/C][C]0.317169[/C][C]0.634338[/C][C]0.682831[/C][/ROW]
[ROW][C]22[/C][C]0.37167[/C][C]0.74334[/C][C]0.62833[/C][/ROW]
[ROW][C]23[/C][C]0.31813[/C][C]0.636261[/C][C]0.68187[/C][/ROW]
[ROW][C]24[/C][C]0.264652[/C][C]0.529304[/C][C]0.735348[/C][/ROW]
[ROW][C]25[/C][C]0.222806[/C][C]0.445612[/C][C]0.777194[/C][/ROW]
[ROW][C]26[/C][C]0.180509[/C][C]0.361018[/C][C]0.819491[/C][/ROW]
[ROW][C]27[/C][C]0.151461[/C][C]0.302921[/C][C]0.848539[/C][/ROW]
[ROW][C]28[/C][C]0.122205[/C][C]0.24441[/C][C]0.877795[/C][/ROW]
[ROW][C]29[/C][C]0.174819[/C][C]0.349638[/C][C]0.825181[/C][/ROW]
[ROW][C]30[/C][C]0.145371[/C][C]0.290742[/C][C]0.854629[/C][/ROW]
[ROW][C]31[/C][C]0.133097[/C][C]0.266193[/C][C]0.866903[/C][/ROW]
[ROW][C]32[/C][C]0.112319[/C][C]0.224637[/C][C]0.887681[/C][/ROW]
[ROW][C]33[/C][C]0.11079[/C][C]0.22158[/C][C]0.88921[/C][/ROW]
[ROW][C]34[/C][C]0.168073[/C][C]0.336147[/C][C]0.831927[/C][/ROW]
[ROW][C]35[/C][C]0.141267[/C][C]0.282534[/C][C]0.858733[/C][/ROW]
[ROW][C]36[/C][C]0.15553[/C][C]0.31106[/C][C]0.84447[/C][/ROW]
[ROW][C]37[/C][C]0.130667[/C][C]0.261335[/C][C]0.869333[/C][/ROW]
[ROW][C]38[/C][C]0.106991[/C][C]0.213982[/C][C]0.893009[/C][/ROW]
[ROW][C]39[/C][C]0.0889239[/C][C]0.177848[/C][C]0.911076[/C][/ROW]
[ROW][C]40[/C][C]0.100956[/C][C]0.201912[/C][C]0.899044[/C][/ROW]
[ROW][C]41[/C][C]0.114929[/C][C]0.229857[/C][C]0.885071[/C][/ROW]
[ROW][C]42[/C][C]0.102558[/C][C]0.205117[/C][C]0.897442[/C][/ROW]
[ROW][C]43[/C][C]0.143717[/C][C]0.287434[/C][C]0.856283[/C][/ROW]
[ROW][C]44[/C][C]0.123284[/C][C]0.246568[/C][C]0.876716[/C][/ROW]
[ROW][C]45[/C][C]0.112107[/C][C]0.224213[/C][C]0.887893[/C][/ROW]
[ROW][C]46[/C][C]0.0970826[/C][C]0.194165[/C][C]0.902917[/C][/ROW]
[ROW][C]47[/C][C]0.103286[/C][C]0.206571[/C][C]0.896714[/C][/ROW]
[ROW][C]48[/C][C]0.0875021[/C][C]0.175004[/C][C]0.912498[/C][/ROW]
[ROW][C]49[/C][C]0.0745036[/C][C]0.149007[/C][C]0.925496[/C][/ROW]
[ROW][C]50[/C][C]0.0923988[/C][C]0.184798[/C][C]0.907601[/C][/ROW]
[ROW][C]51[/C][C]0.101852[/C][C]0.203704[/C][C]0.898148[/C][/ROW]
[ROW][C]52[/C][C]0.104535[/C][C]0.209069[/C][C]0.895465[/C][/ROW]
[ROW][C]53[/C][C]0.0913005[/C][C]0.182601[/C][C]0.9087[/C][/ROW]
[ROW][C]54[/C][C]0.0954484[/C][C]0.190897[/C][C]0.904552[/C][/ROW]
[ROW][C]55[/C][C]0.0883812[/C][C]0.176762[/C][C]0.911619[/C][/ROW]
[ROW][C]56[/C][C]0.0883603[/C][C]0.176721[/C][C]0.91164[/C][/ROW]
[ROW][C]57[/C][C]0.0873229[/C][C]0.174646[/C][C]0.912677[/C][/ROW]
[ROW][C]58[/C][C]0.0762672[/C][C]0.152534[/C][C]0.923733[/C][/ROW]
[ROW][C]59[/C][C]0.124841[/C][C]0.249681[/C][C]0.875159[/C][/ROW]
[ROW][C]60[/C][C]0.155148[/C][C]0.310296[/C][C]0.844852[/C][/ROW]
[ROW][C]61[/C][C]0.132668[/C][C]0.265335[/C][C]0.867332[/C][/ROW]
[ROW][C]62[/C][C]0.141356[/C][C]0.282711[/C][C]0.858644[/C][/ROW]
[ROW][C]63[/C][C]0.149345[/C][C]0.298691[/C][C]0.850655[/C][/ROW]
[ROW][C]64[/C][C]0.143817[/C][C]0.287633[/C][C]0.856183[/C][/ROW]
[ROW][C]65[/C][C]0.14836[/C][C]0.29672[/C][C]0.85164[/C][/ROW]
[ROW][C]66[/C][C]0.187052[/C][C]0.374105[/C][C]0.812948[/C][/ROW]
[ROW][C]67[/C][C]0.181787[/C][C]0.363573[/C][C]0.818213[/C][/ROW]
[ROW][C]68[/C][C]0.158409[/C][C]0.316817[/C][C]0.841591[/C][/ROW]
[ROW][C]69[/C][C]0.157911[/C][C]0.315822[/C][C]0.842089[/C][/ROW]
[ROW][C]70[/C][C]0.14647[/C][C]0.29294[/C][C]0.85353[/C][/ROW]
[ROW][C]71[/C][C]0.155822[/C][C]0.311643[/C][C]0.844178[/C][/ROW]
[ROW][C]72[/C][C]0.145299[/C][C]0.290598[/C][C]0.854701[/C][/ROW]
[ROW][C]73[/C][C]0.131367[/C][C]0.262733[/C][C]0.868633[/C][/ROW]
[ROW][C]74[/C][C]0.117285[/C][C]0.23457[/C][C]0.882715[/C][/ROW]
[ROW][C]75[/C][C]0.105882[/C][C]0.211764[/C][C]0.894118[/C][/ROW]
[ROW][C]76[/C][C]0.111438[/C][C]0.222876[/C][C]0.888562[/C][/ROW]
[ROW][C]77[/C][C]0.190657[/C][C]0.381313[/C][C]0.809343[/C][/ROW]
[ROW][C]78[/C][C]0.180363[/C][C]0.360726[/C][C]0.819637[/C][/ROW]
[ROW][C]79[/C][C]0.170365[/C][C]0.340731[/C][C]0.829635[/C][/ROW]
[ROW][C]80[/C][C]0.164863[/C][C]0.329726[/C][C]0.835137[/C][/ROW]
[ROW][C]81[/C][C]0.162757[/C][C]0.325514[/C][C]0.837243[/C][/ROW]
[ROW][C]82[/C][C]0.142399[/C][C]0.284797[/C][C]0.857601[/C][/ROW]
[ROW][C]83[/C][C]0.171577[/C][C]0.343155[/C][C]0.828423[/C][/ROW]
[ROW][C]84[/C][C]0.150341[/C][C]0.300682[/C][C]0.849659[/C][/ROW]
[ROW][C]85[/C][C]0.167897[/C][C]0.335794[/C][C]0.832103[/C][/ROW]
[ROW][C]86[/C][C]0.148133[/C][C]0.296265[/C][C]0.851867[/C][/ROW]
[ROW][C]87[/C][C]0.261014[/C][C]0.522028[/C][C]0.738986[/C][/ROW]
[ROW][C]88[/C][C]0.242832[/C][C]0.485663[/C][C]0.757168[/C][/ROW]
[ROW][C]89[/C][C]0.21866[/C][C]0.43732[/C][C]0.78134[/C][/ROW]
[ROW][C]90[/C][C]0.194626[/C][C]0.389252[/C][C]0.805374[/C][/ROW]
[ROW][C]91[/C][C]0.174569[/C][C]0.349138[/C][C]0.825431[/C][/ROW]
[ROW][C]92[/C][C]0.164938[/C][C]0.329876[/C][C]0.835062[/C][/ROW]
[ROW][C]93[/C][C]0.173487[/C][C]0.346974[/C][C]0.826513[/C][/ROW]
[ROW][C]94[/C][C]0.181196[/C][C]0.362391[/C][C]0.818804[/C][/ROW]
[ROW][C]95[/C][C]0.270379[/C][C]0.540758[/C][C]0.729621[/C][/ROW]
[ROW][C]96[/C][C]0.265272[/C][C]0.530543[/C][C]0.734728[/C][/ROW]
[ROW][C]97[/C][C]0.259929[/C][C]0.519858[/C][C]0.740071[/C][/ROW]
[ROW][C]98[/C][C]0.281163[/C][C]0.562327[/C][C]0.718837[/C][/ROW]
[ROW][C]99[/C][C]0.273135[/C][C]0.546269[/C][C]0.726865[/C][/ROW]
[ROW][C]100[/C][C]0.349992[/C][C]0.699983[/C][C]0.650008[/C][/ROW]
[ROW][C]101[/C][C]0.336902[/C][C]0.673803[/C][C]0.663098[/C][/ROW]
[ROW][C]102[/C][C]0.383827[/C][C]0.767655[/C][C]0.616173[/C][/ROW]
[ROW][C]103[/C][C]0.440039[/C][C]0.880078[/C][C]0.559961[/C][/ROW]
[ROW][C]104[/C][C]0.411429[/C][C]0.822857[/C][C]0.588571[/C][/ROW]
[ROW][C]105[/C][C]0.394171[/C][C]0.788341[/C][C]0.605829[/C][/ROW]
[ROW][C]106[/C][C]0.393938[/C][C]0.787876[/C][C]0.606062[/C][/ROW]
[ROW][C]107[/C][C]0.406112[/C][C]0.812224[/C][C]0.593888[/C][/ROW]
[ROW][C]108[/C][C]0.437967[/C][C]0.875934[/C][C]0.562033[/C][/ROW]
[ROW][C]109[/C][C]0.461025[/C][C]0.922049[/C][C]0.538975[/C][/ROW]
[ROW][C]110[/C][C]0.480433[/C][C]0.960866[/C][C]0.519567[/C][/ROW]
[ROW][C]111[/C][C]0.671657[/C][C]0.656685[/C][C]0.328343[/C][/ROW]
[ROW][C]112[/C][C]0.70863[/C][C]0.582739[/C][C]0.29137[/C][/ROW]
[ROW][C]113[/C][C]0.705184[/C][C]0.589632[/C][C]0.294816[/C][/ROW]
[ROW][C]114[/C][C]0.698087[/C][C]0.603826[/C][C]0.301913[/C][/ROW]
[ROW][C]115[/C][C]0.686384[/C][C]0.627232[/C][C]0.313616[/C][/ROW]
[ROW][C]116[/C][C]0.813338[/C][C]0.373323[/C][C]0.186662[/C][/ROW]
[ROW][C]117[/C][C]0.806569[/C][C]0.386863[/C][C]0.193431[/C][/ROW]
[ROW][C]118[/C][C]0.885533[/C][C]0.228934[/C][C]0.114467[/C][/ROW]
[ROW][C]119[/C][C]0.920163[/C][C]0.159675[/C][C]0.0798374[/C][/ROW]
[ROW][C]120[/C][C]0.909897[/C][C]0.180207[/C][C]0.0901035[/C][/ROW]
[ROW][C]121[/C][C]0.918046[/C][C]0.163909[/C][C]0.0819544[/C][/ROW]
[ROW][C]122[/C][C]0.918534[/C][C]0.162931[/C][C]0.0814656[/C][/ROW]
[ROW][C]123[/C][C]0.934027[/C][C]0.131946[/C][C]0.0659728[/C][/ROW]
[ROW][C]124[/C][C]0.938161[/C][C]0.123679[/C][C]0.0618394[/C][/ROW]
[ROW][C]125[/C][C]0.946842[/C][C]0.106316[/C][C]0.0531578[/C][/ROW]
[ROW][C]126[/C][C]0.9487[/C][C]0.1026[/C][C]0.0513002[/C][/ROW]
[ROW][C]127[/C][C]0.966495[/C][C]0.0670098[/C][C]0.0335049[/C][/ROW]
[ROW][C]128[/C][C]0.972565[/C][C]0.0548697[/C][C]0.0274348[/C][/ROW]
[ROW][C]129[/C][C]0.968524[/C][C]0.0629517[/C][C]0.0314759[/C][/ROW]
[ROW][C]130[/C][C]0.967923[/C][C]0.0641535[/C][C]0.0320768[/C][/ROW]
[ROW][C]131[/C][C]0.972996[/C][C]0.0540089[/C][C]0.0270045[/C][/ROW]
[ROW][C]132[/C][C]0.976271[/C][C]0.0474572[/C][C]0.0237286[/C][/ROW]
[ROW][C]133[/C][C]0.975352[/C][C]0.0492967[/C][C]0.0246484[/C][/ROW]
[ROW][C]134[/C][C]0.977445[/C][C]0.0451091[/C][C]0.0225546[/C][/ROW]
[ROW][C]135[/C][C]0.978432[/C][C]0.0431358[/C][C]0.0215679[/C][/ROW]
[ROW][C]136[/C][C]0.976257[/C][C]0.0474856[/C][C]0.0237428[/C][/ROW]
[ROW][C]137[/C][C]0.972475[/C][C]0.0550491[/C][C]0.0275245[/C][/ROW]
[ROW][C]138[/C][C]0.96723[/C][C]0.0655402[/C][C]0.0327701[/C][/ROW]
[ROW][C]139[/C][C]0.962664[/C][C]0.0746729[/C][C]0.0373365[/C][/ROW]
[ROW][C]140[/C][C]0.973783[/C][C]0.052434[/C][C]0.026217[/C][/ROW]
[ROW][C]141[/C][C]0.973793[/C][C]0.0524134[/C][C]0.0262067[/C][/ROW]
[ROW][C]142[/C][C]0.97079[/C][C]0.0584193[/C][C]0.0292096[/C][/ROW]
[ROW][C]143[/C][C]0.966093[/C][C]0.0678138[/C][C]0.0339069[/C][/ROW]
[ROW][C]144[/C][C]0.960097[/C][C]0.0798053[/C][C]0.0399027[/C][/ROW]
[ROW][C]145[/C][C]0.980369[/C][C]0.0392611[/C][C]0.0196305[/C][/ROW]
[ROW][C]146[/C][C]0.979593[/C][C]0.0408132[/C][C]0.0204066[/C][/ROW]
[ROW][C]147[/C][C]0.979082[/C][C]0.0418357[/C][C]0.0209179[/C][/ROW]
[ROW][C]148[/C][C]0.978123[/C][C]0.0437541[/C][C]0.0218771[/C][/ROW]
[ROW][C]149[/C][C]0.975449[/C][C]0.0491015[/C][C]0.0245508[/C][/ROW]
[ROW][C]150[/C][C]0.975515[/C][C]0.0489694[/C][C]0.0244847[/C][/ROW]
[ROW][C]151[/C][C]0.971844[/C][C]0.0563113[/C][C]0.0281557[/C][/ROW]
[ROW][C]152[/C][C]0.969458[/C][C]0.0610833[/C][C]0.0305416[/C][/ROW]
[ROW][C]153[/C][C]0.964389[/C][C]0.0712229[/C][C]0.0356115[/C][/ROW]
[ROW][C]154[/C][C]0.960839[/C][C]0.0783221[/C][C]0.039161[/C][/ROW]
[ROW][C]155[/C][C]0.959273[/C][C]0.0814549[/C][C]0.0407275[/C][/ROW]
[ROW][C]156[/C][C]0.984958[/C][C]0.0300831[/C][C]0.0150415[/C][/ROW]
[ROW][C]157[/C][C]0.982962[/C][C]0.0340751[/C][C]0.0170376[/C][/ROW]
[ROW][C]158[/C][C]0.983244[/C][C]0.0335116[/C][C]0.0167558[/C][/ROW]
[ROW][C]159[/C][C]0.979994[/C][C]0.0400112[/C][C]0.0200056[/C][/ROW]
[ROW][C]160[/C][C]0.980386[/C][C]0.0392289[/C][C]0.0196144[/C][/ROW]
[ROW][C]161[/C][C]0.975944[/C][C]0.0481111[/C][C]0.0240556[/C][/ROW]
[ROW][C]162[/C][C]0.974572[/C][C]0.0508551[/C][C]0.0254276[/C][/ROW]
[ROW][C]163[/C][C]0.970263[/C][C]0.0594747[/C][C]0.0297374[/C][/ROW]
[ROW][C]164[/C][C]0.968611[/C][C]0.0627784[/C][C]0.0313892[/C][/ROW]
[ROW][C]165[/C][C]0.963684[/C][C]0.0726324[/C][C]0.0363162[/C][/ROW]
[ROW][C]166[/C][C]0.976792[/C][C]0.0464157[/C][C]0.0232078[/C][/ROW]
[ROW][C]167[/C][C]0.972504[/C][C]0.0549927[/C][C]0.0274964[/C][/ROW]
[ROW][C]168[/C][C]0.971747[/C][C]0.0565063[/C][C]0.0282531[/C][/ROW]
[ROW][C]169[/C][C]0.994231[/C][C]0.0115373[/C][C]0.00576863[/C][/ROW]
[ROW][C]170[/C][C]0.995554[/C][C]0.00889194[/C][C]0.00444597[/C][/ROW]
[ROW][C]171[/C][C]0.994334[/C][C]0.0113321[/C][C]0.00566605[/C][/ROW]
[ROW][C]172[/C][C]0.994268[/C][C]0.0114636[/C][C]0.0057318[/C][/ROW]
[ROW][C]173[/C][C]0.996167[/C][C]0.00766504[/C][C]0.00383252[/C][/ROW]
[ROW][C]174[/C][C]0.995023[/C][C]0.00995465[/C][C]0.00497732[/C][/ROW]
[ROW][C]175[/C][C]0.9951[/C][C]0.00979911[/C][C]0.00489956[/C][/ROW]
[ROW][C]176[/C][C]0.994012[/C][C]0.011975[/C][C]0.00598752[/C][/ROW]
[ROW][C]177[/C][C]0.995972[/C][C]0.00805685[/C][C]0.00402842[/C][/ROW]
[ROW][C]178[/C][C]0.995382[/C][C]0.00923666[/C][C]0.00461833[/C][/ROW]
[ROW][C]179[/C][C]0.994442[/C][C]0.0111167[/C][C]0.00555836[/C][/ROW]
[ROW][C]180[/C][C]0.993408[/C][C]0.0131842[/C][C]0.00659208[/C][/ROW]
[ROW][C]181[/C][C]0.994754[/C][C]0.0104913[/C][C]0.00524567[/C][/ROW]
[ROW][C]182[/C][C]0.993925[/C][C]0.0121507[/C][C]0.00607537[/C][/ROW]
[ROW][C]183[/C][C]0.993602[/C][C]0.0127951[/C][C]0.00639753[/C][/ROW]
[ROW][C]184[/C][C]0.992586[/C][C]0.0148288[/C][C]0.00741442[/C][/ROW]
[ROW][C]185[/C][C]0.994901[/C][C]0.0101987[/C][C]0.00509934[/C][/ROW]
[ROW][C]186[/C][C]0.99402[/C][C]0.011959[/C][C]0.00597951[/C][/ROW]
[ROW][C]187[/C][C]0.992558[/C][C]0.0148848[/C][C]0.00744242[/C][/ROW]
[ROW][C]188[/C][C]0.99127[/C][C]0.0174609[/C][C]0.00873047[/C][/ROW]
[ROW][C]189[/C][C]0.989324[/C][C]0.0213529[/C][C]0.0106764[/C][/ROW]
[ROW][C]190[/C][C]0.987932[/C][C]0.0241361[/C][C]0.0120681[/C][/ROW]
[ROW][C]191[/C][C]0.986123[/C][C]0.0277532[/C][C]0.0138766[/C][/ROW]
[ROW][C]192[/C][C]0.991937[/C][C]0.0161261[/C][C]0.00806306[/C][/ROW]
[ROW][C]193[/C][C]0.990094[/C][C]0.0198118[/C][C]0.0099059[/C][/ROW]
[ROW][C]194[/C][C]0.98881[/C][C]0.0223795[/C][C]0.0111897[/C][/ROW]
[ROW][C]195[/C][C]0.985946[/C][C]0.0281087[/C][C]0.0140544[/C][/ROW]
[ROW][C]196[/C][C]0.982882[/C][C]0.0342357[/C][C]0.0171179[/C][/ROW]
[ROW][C]197[/C][C]0.980876[/C][C]0.0382487[/C][C]0.0191244[/C][/ROW]
[ROW][C]198[/C][C]0.97758[/C][C]0.04484[/C][C]0.02242[/C][/ROW]
[ROW][C]199[/C][C]0.98569[/C][C]0.028621[/C][C]0.0143105[/C][/ROW]
[ROW][C]200[/C][C]0.983129[/C][C]0.0337412[/C][C]0.0168706[/C][/ROW]
[ROW][C]201[/C][C]0.979771[/C][C]0.0404587[/C][C]0.0202294[/C][/ROW]
[ROW][C]202[/C][C]0.980434[/C][C]0.0391313[/C][C]0.0195656[/C][/ROW]
[ROW][C]203[/C][C]0.975443[/C][C]0.0491137[/C][C]0.0245569[/C][/ROW]
[ROW][C]204[/C][C]0.977568[/C][C]0.0448633[/C][C]0.0224317[/C][/ROW]
[ROW][C]205[/C][C]0.977604[/C][C]0.0447914[/C][C]0.0223957[/C][/ROW]
[ROW][C]206[/C][C]0.976365[/C][C]0.0472695[/C][C]0.0236348[/C][/ROW]
[ROW][C]207[/C][C]0.974879[/C][C]0.0502413[/C][C]0.0251206[/C][/ROW]
[ROW][C]208[/C][C]0.971104[/C][C]0.0577922[/C][C]0.0288961[/C][/ROW]
[ROW][C]209[/C][C]0.96436[/C][C]0.0712793[/C][C]0.0356396[/C][/ROW]
[ROW][C]210[/C][C]0.957665[/C][C]0.0846691[/C][C]0.0423345[/C][/ROW]
[ROW][C]211[/C][C]0.964188[/C][C]0.0716231[/C][C]0.0358116[/C][/ROW]
[ROW][C]212[/C][C]0.962181[/C][C]0.0756376[/C][C]0.0378188[/C][/ROW]
[ROW][C]213[/C][C]0.960682[/C][C]0.0786359[/C][C]0.039318[/C][/ROW]
[ROW][C]214[/C][C]0.951592[/C][C]0.0968152[/C][C]0.0484076[/C][/ROW]
[ROW][C]215[/C][C]0.949677[/C][C]0.100647[/C][C]0.0503234[/C][/ROW]
[ROW][C]216[/C][C]0.945299[/C][C]0.109401[/C][C]0.0547007[/C][/ROW]
[ROW][C]217[/C][C]0.938144[/C][C]0.123712[/C][C]0.0618558[/C][/ROW]
[ROW][C]218[/C][C]0.928145[/C][C]0.14371[/C][C]0.071855[/C][/ROW]
[ROW][C]219[/C][C]0.942127[/C][C]0.115746[/C][C]0.0578732[/C][/ROW]
[ROW][C]220[/C][C]0.931498[/C][C]0.137004[/C][C]0.0685021[/C][/ROW]
[ROW][C]221[/C][C]0.927725[/C][C]0.144549[/C][C]0.0722746[/C][/ROW]
[ROW][C]222[/C][C]0.917313[/C][C]0.165375[/C][C]0.0826874[/C][/ROW]
[ROW][C]223[/C][C]0.914904[/C][C]0.170192[/C][C]0.0850961[/C][/ROW]
[ROW][C]224[/C][C]0.905493[/C][C]0.189013[/C][C]0.0945066[/C][/ROW]
[ROW][C]225[/C][C]0.89414[/C][C]0.211721[/C][C]0.10586[/C][/ROW]
[ROW][C]226[/C][C]0.873174[/C][C]0.253653[/C][C]0.126826[/C][/ROW]
[ROW][C]227[/C][C]0.849499[/C][C]0.301002[/C][C]0.150501[/C][/ROW]
[ROW][C]228[/C][C]0.825628[/C][C]0.348744[/C][C]0.174372[/C][/ROW]
[ROW][C]229[/C][C]0.845957[/C][C]0.308086[/C][C]0.154043[/C][/ROW]
[ROW][C]230[/C][C]0.820288[/C][C]0.359423[/C][C]0.179712[/C][/ROW]
[ROW][C]231[/C][C]0.826289[/C][C]0.347421[/C][C]0.173711[/C][/ROW]
[ROW][C]232[/C][C]0.807918[/C][C]0.384164[/C][C]0.192082[/C][/ROW]
[ROW][C]233[/C][C]0.859118[/C][C]0.281764[/C][C]0.140882[/C][/ROW]
[ROW][C]234[/C][C]0.873766[/C][C]0.252468[/C][C]0.126234[/C][/ROW]
[ROW][C]235[/C][C]0.870238[/C][C]0.259524[/C][C]0.129762[/C][/ROW]
[ROW][C]236[/C][C]0.865467[/C][C]0.269066[/C][C]0.134533[/C][/ROW]
[ROW][C]237[/C][C]0.876028[/C][C]0.247944[/C][C]0.123972[/C][/ROW]
[ROW][C]238[/C][C]0.889043[/C][C]0.221914[/C][C]0.110957[/C][/ROW]
[ROW][C]239[/C][C]0.869454[/C][C]0.261092[/C][C]0.130546[/C][/ROW]
[ROW][C]240[/C][C]0.848933[/C][C]0.302134[/C][C]0.151067[/C][/ROW]
[ROW][C]241[/C][C]0.850292[/C][C]0.299416[/C][C]0.149708[/C][/ROW]
[ROW][C]242[/C][C]0.838763[/C][C]0.322474[/C][C]0.161237[/C][/ROW]
[ROW][C]243[/C][C]0.934984[/C][C]0.130032[/C][C]0.0650159[/C][/ROW]
[ROW][C]244[/C][C]0.929707[/C][C]0.140585[/C][C]0.0702925[/C][/ROW]
[ROW][C]245[/C][C]0.948483[/C][C]0.103035[/C][C]0.0515173[/C][/ROW]
[ROW][C]246[/C][C]0.934666[/C][C]0.130668[/C][C]0.0653342[/C][/ROW]
[ROW][C]247[/C][C]0.916533[/C][C]0.166934[/C][C]0.0834672[/C][/ROW]
[ROW][C]248[/C][C]0.902322[/C][C]0.195356[/C][C]0.0976779[/C][/ROW]
[ROW][C]249[/C][C]0.883169[/C][C]0.233662[/C][C]0.116831[/C][/ROW]
[ROW][C]250[/C][C]0.872561[/C][C]0.254878[/C][C]0.127439[/C][/ROW]
[ROW][C]251[/C][C]0.863025[/C][C]0.273951[/C][C]0.136975[/C][/ROW]
[ROW][C]252[/C][C]0.924546[/C][C]0.150908[/C][C]0.0754542[/C][/ROW]
[ROW][C]253[/C][C]0.904615[/C][C]0.19077[/C][C]0.0953848[/C][/ROW]
[ROW][C]254[/C][C]0.884298[/C][C]0.231403[/C][C]0.115702[/C][/ROW]
[ROW][C]255[/C][C]0.852956[/C][C]0.294087[/C][C]0.147044[/C][/ROW]
[ROW][C]256[/C][C]0.817653[/C][C]0.364693[/C][C]0.182347[/C][/ROW]
[ROW][C]257[/C][C]0.774896[/C][C]0.450208[/C][C]0.225104[/C][/ROW]
[ROW][C]258[/C][C]0.72651[/C][C]0.546979[/C][C]0.27349[/C][/ROW]
[ROW][C]259[/C][C]0.701017[/C][C]0.597965[/C][C]0.298983[/C][/ROW]
[ROW][C]260[/C][C]0.688075[/C][C]0.62385[/C][C]0.311925[/C][/ROW]
[ROW][C]261[/C][C]0.6278[/C][C]0.744399[/C][C]0.3722[/C][/ROW]
[ROW][C]262[/C][C]0.585767[/C][C]0.828465[/C][C]0.414233[/C][/ROW]
[ROW][C]263[/C][C]0.637372[/C][C]0.725257[/C][C]0.362628[/C][/ROW]
[ROW][C]264[/C][C]0.577031[/C][C]0.845938[/C][C]0.422969[/C][/ROW]
[ROW][C]265[/C][C]0.564657[/C][C]0.870686[/C][C]0.435343[/C][/ROW]
[ROW][C]266[/C][C]0.949516[/C][C]0.100968[/C][C]0.0504838[/C][/ROW]
[ROW][C]267[/C][C]0.9245[/C][C]0.150999[/C][C]0.0754996[/C][/ROW]
[ROW][C]268[/C][C]0.997067[/C][C]0.0058662[/C][C]0.0029331[/C][/ROW]
[ROW][C]269[/C][C]0.997381[/C][C]0.00523895[/C][C]0.00261948[/C][/ROW]
[ROW][C]270[/C][C]0.996145[/C][C]0.00771028[/C][C]0.00385514[/C][/ROW]
[ROW][C]271[/C][C]0.999947[/C][C]0.000105429[/C][C]5.27145e-05[/C][/ROW]
[ROW][C]272[/C][C]0.999829[/C][C]0.000342485[/C][C]0.000171243[/C][/ROW]
[ROW][C]273[/C][C]0.999603[/C][C]0.000794939[/C][C]0.00039747[/C][/ROW]
[ROW][C]274[/C][C]0.999361[/C][C]0.00127784[/C][C]0.000638922[/C][/ROW]
[ROW][C]275[/C][C]0.999021[/C][C]0.00195783[/C][C]0.000978916[/C][/ROW]
[ROW][C]276[/C][C]0.996569[/C][C]0.00686121[/C][C]0.00343061[/C][/ROW]
[ROW][C]277[/C][C]0.997527[/C][C]0.00494597[/C][C]0.00247298[/C][/ROW]
[ROW][C]278[/C][C]0.990615[/C][C]0.0187709[/C][C]0.00938545[/C][/ROW]
[ROW][C]279[/C][C]0.994295[/C][C]0.0114103[/C][C]0.00570517[/C][/ROW]
[ROW][C]280[/C][C]0.973981[/C][C]0.0520386[/C][C]0.0260193[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264935&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264935&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
70.8807110.2385790.119289
80.891530.2169410.10847
90.8218680.3562630.178132
100.7496730.5006540.250327
110.7954710.4090580.204529
120.7235250.552950.276475
130.7767990.4464020.223201
140.7066780.5866450.293322
150.6286260.7427470.371374
160.5854030.8291940.414597
170.589130.8217390.41087
180.5220260.9559470.477974
190.4493070.8986140.550693
200.3835880.7671760.616412
210.3171690.6343380.682831
220.371670.743340.62833
230.318130.6362610.68187
240.2646520.5293040.735348
250.2228060.4456120.777194
260.1805090.3610180.819491
270.1514610.3029210.848539
280.1222050.244410.877795
290.1748190.3496380.825181
300.1453710.2907420.854629
310.1330970.2661930.866903
320.1123190.2246370.887681
330.110790.221580.88921
340.1680730.3361470.831927
350.1412670.2825340.858733
360.155530.311060.84447
370.1306670.2613350.869333
380.1069910.2139820.893009
390.08892390.1778480.911076
400.1009560.2019120.899044
410.1149290.2298570.885071
420.1025580.2051170.897442
430.1437170.2874340.856283
440.1232840.2465680.876716
450.1121070.2242130.887893
460.09708260.1941650.902917
470.1032860.2065710.896714
480.08750210.1750040.912498
490.07450360.1490070.925496
500.09239880.1847980.907601
510.1018520.2037040.898148
520.1045350.2090690.895465
530.09130050.1826010.9087
540.09544840.1908970.904552
550.08838120.1767620.911619
560.08836030.1767210.91164
570.08732290.1746460.912677
580.07626720.1525340.923733
590.1248410.2496810.875159
600.1551480.3102960.844852
610.1326680.2653350.867332
620.1413560.2827110.858644
630.1493450.2986910.850655
640.1438170.2876330.856183
650.148360.296720.85164
660.1870520.3741050.812948
670.1817870.3635730.818213
680.1584090.3168170.841591
690.1579110.3158220.842089
700.146470.292940.85353
710.1558220.3116430.844178
720.1452990.2905980.854701
730.1313670.2627330.868633
740.1172850.234570.882715
750.1058820.2117640.894118
760.1114380.2228760.888562
770.1906570.3813130.809343
780.1803630.3607260.819637
790.1703650.3407310.829635
800.1648630.3297260.835137
810.1627570.3255140.837243
820.1423990.2847970.857601
830.1715770.3431550.828423
840.1503410.3006820.849659
850.1678970.3357940.832103
860.1481330.2962650.851867
870.2610140.5220280.738986
880.2428320.4856630.757168
890.218660.437320.78134
900.1946260.3892520.805374
910.1745690.3491380.825431
920.1649380.3298760.835062
930.1734870.3469740.826513
940.1811960.3623910.818804
950.2703790.5407580.729621
960.2652720.5305430.734728
970.2599290.5198580.740071
980.2811630.5623270.718837
990.2731350.5462690.726865
1000.3499920.6999830.650008
1010.3369020.6738030.663098
1020.3838270.7676550.616173
1030.4400390.8800780.559961
1040.4114290.8228570.588571
1050.3941710.7883410.605829
1060.3939380.7878760.606062
1070.4061120.8122240.593888
1080.4379670.8759340.562033
1090.4610250.9220490.538975
1100.4804330.9608660.519567
1110.6716570.6566850.328343
1120.708630.5827390.29137
1130.7051840.5896320.294816
1140.6980870.6038260.301913
1150.6863840.6272320.313616
1160.8133380.3733230.186662
1170.8065690.3868630.193431
1180.8855330.2289340.114467
1190.9201630.1596750.0798374
1200.9098970.1802070.0901035
1210.9180460.1639090.0819544
1220.9185340.1629310.0814656
1230.9340270.1319460.0659728
1240.9381610.1236790.0618394
1250.9468420.1063160.0531578
1260.94870.10260.0513002
1270.9664950.06700980.0335049
1280.9725650.05486970.0274348
1290.9685240.06295170.0314759
1300.9679230.06415350.0320768
1310.9729960.05400890.0270045
1320.9762710.04745720.0237286
1330.9753520.04929670.0246484
1340.9774450.04510910.0225546
1350.9784320.04313580.0215679
1360.9762570.04748560.0237428
1370.9724750.05504910.0275245
1380.967230.06554020.0327701
1390.9626640.07467290.0373365
1400.9737830.0524340.026217
1410.9737930.05241340.0262067
1420.970790.05841930.0292096
1430.9660930.06781380.0339069
1440.9600970.07980530.0399027
1450.9803690.03926110.0196305
1460.9795930.04081320.0204066
1470.9790820.04183570.0209179
1480.9781230.04375410.0218771
1490.9754490.04910150.0245508
1500.9755150.04896940.0244847
1510.9718440.05631130.0281557
1520.9694580.06108330.0305416
1530.9643890.07122290.0356115
1540.9608390.07832210.039161
1550.9592730.08145490.0407275
1560.9849580.03008310.0150415
1570.9829620.03407510.0170376
1580.9832440.03351160.0167558
1590.9799940.04001120.0200056
1600.9803860.03922890.0196144
1610.9759440.04811110.0240556
1620.9745720.05085510.0254276
1630.9702630.05947470.0297374
1640.9686110.06277840.0313892
1650.9636840.07263240.0363162
1660.9767920.04641570.0232078
1670.9725040.05499270.0274964
1680.9717470.05650630.0282531
1690.9942310.01153730.00576863
1700.9955540.008891940.00444597
1710.9943340.01133210.00566605
1720.9942680.01146360.0057318
1730.9961670.007665040.00383252
1740.9950230.009954650.00497732
1750.99510.009799110.00489956
1760.9940120.0119750.00598752
1770.9959720.008056850.00402842
1780.9953820.009236660.00461833
1790.9944420.01111670.00555836
1800.9934080.01318420.00659208
1810.9947540.01049130.00524567
1820.9939250.01215070.00607537
1830.9936020.01279510.00639753
1840.9925860.01482880.00741442
1850.9949010.01019870.00509934
1860.994020.0119590.00597951
1870.9925580.01488480.00744242
1880.991270.01746090.00873047
1890.9893240.02135290.0106764
1900.9879320.02413610.0120681
1910.9861230.02775320.0138766
1920.9919370.01612610.00806306
1930.9900940.01981180.0099059
1940.988810.02237950.0111897
1950.9859460.02810870.0140544
1960.9828820.03423570.0171179
1970.9808760.03824870.0191244
1980.977580.044840.02242
1990.985690.0286210.0143105
2000.9831290.03374120.0168706
2010.9797710.04045870.0202294
2020.9804340.03913130.0195656
2030.9754430.04911370.0245569
2040.9775680.04486330.0224317
2050.9776040.04479140.0223957
2060.9763650.04726950.0236348
2070.9748790.05024130.0251206
2080.9711040.05779220.0288961
2090.964360.07127930.0356396
2100.9576650.08466910.0423345
2110.9641880.07162310.0358116
2120.9621810.07563760.0378188
2130.9606820.07863590.039318
2140.9515920.09681520.0484076
2150.9496770.1006470.0503234
2160.9452990.1094010.0547007
2170.9381440.1237120.0618558
2180.9281450.143710.071855
2190.9421270.1157460.0578732
2200.9314980.1370040.0685021
2210.9277250.1445490.0722746
2220.9173130.1653750.0826874
2230.9149040.1701920.0850961
2240.9054930.1890130.0945066
2250.894140.2117210.10586
2260.8731740.2536530.126826
2270.8494990.3010020.150501
2280.8256280.3487440.174372
2290.8459570.3080860.154043
2300.8202880.3594230.179712
2310.8262890.3474210.173711
2320.8079180.3841640.192082
2330.8591180.2817640.140882
2340.8737660.2524680.126234
2350.8702380.2595240.129762
2360.8654670.2690660.134533
2370.8760280.2479440.123972
2380.8890430.2219140.110957
2390.8694540.2610920.130546
2400.8489330.3021340.151067
2410.8502920.2994160.149708
2420.8387630.3224740.161237
2430.9349840.1300320.0650159
2440.9297070.1405850.0702925
2450.9484830.1030350.0515173
2460.9346660.1306680.0653342
2470.9165330.1669340.0834672
2480.9023220.1953560.0976779
2490.8831690.2336620.116831
2500.8725610.2548780.127439
2510.8630250.2739510.136975
2520.9245460.1509080.0754542
2530.9046150.190770.0953848
2540.8842980.2314030.115702
2550.8529560.2940870.147044
2560.8176530.3646930.182347
2570.7748960.4502080.225104
2580.726510.5469790.27349
2590.7010170.5979650.298983
2600.6880750.623850.311925
2610.62780.7443990.3722
2620.5857670.8284650.414233
2630.6373720.7252570.362628
2640.5770310.8459380.422969
2650.5646570.8706860.435343
2660.9495160.1009680.0504838
2670.92450.1509990.0754996
2680.9970670.00586620.0029331
2690.9973810.005238950.00261948
2700.9961450.007710280.00385514
2710.9999470.0001054295.27145e-05
2720.9998290.0003424850.000171243
2730.9996030.0007949390.00039747
2740.9993610.001277840.000638922
2750.9990210.001957830.000978916
2760.9965690.006861210.00343061
2770.9975270.004945970.00247298
2780.9906150.01877090.00938545
2790.9942950.01141030.00570517
2800.9739810.05203860.0260193






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level160.0583942NOK
5% type I error level680.248175NOK
10% type I error level1010.368613NOK

\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 & 16 & 0.0583942 & NOK \tabularnewline
5% type I error level & 68 & 0.248175 & NOK \tabularnewline
10% type I error level & 101 & 0.368613 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264935&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]16[/C][C]0.0583942[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]68[/C][C]0.248175[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]101[/C][C]0.368613[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264935&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264935&T=6

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


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 level160.0583942NOK
5% type I error level680.248175NOK
10% type I error level1010.368613NOK


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 5
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 6
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 7
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 8
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 9
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 10
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 4 ; 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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), 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,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
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, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
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,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
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,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
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,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
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,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
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')
}