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 computationTue, 11 Nov 2014 19:14:58 +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/Nov/11/t1415733378mumnpe32kzy15g6.htm/, Retrieved Sun, 19 May 2024 10:24:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=253714, Retrieved Sun, 19 May 2024 10:24:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-11-11 19:14:58] [c98c6a6156d025200627852118e8b268] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 12 12 53
39 32 16 11 11 83
30 35 19 15 14 66
31 33 15 6 12 67
34 37 14 13 21 76
35 29 13 10 12 78
39 31 19 12 22 53
34 36 15 14 11 80
36 35 14 12 10 74
37 38 15 9 13 76
38 31 16 10 10 79
36 34 16 12 8 54
38 35 16 12 15 67
39 38 16 11 14 54
33 37 17 15 10 87
32 33 15 12 14 58
36 32 15 10 14 75
38 38 20 12 11 88
39 38 18 11 10 64
32 32 16 12 13 57
32 33 16 11 9.5 66
31 31 16 12 14 68
39 38 19 13 12 54
37 39 16 11 14 56
39 32 17 12 11 86
41 32 17 13 9 80
36 35 16 10 11 76
33 37 15 14 15 69
33 33 16 12 14 78
34 33 14 10 13 67
31 31 15 12 9 80
27 32 12 8 15 54
37 31 14 10 10 71
34 37 16 12 11 84
34 30 14 12 13 74
32 33 10 7 8 71
29 31 10 9 20 63
36 33 14 12 12 71
29 31 16 10 10 76
35 33 16 10 10 69
37 32 16 10 9 74
34 33 14 12 14 75
38 32 20 15 8 54
35 33 14 10 14 52
38 28 14 10 11 69
37 35 11 12 13 68
38 39 14 13 9 65
33 34 15 11 11 75
36 38 16 11 15 74
38 32 14 12 11 75
32 38 16 14 10 72
32 30 14 10 14 67
32 33 12 12 18 63
34 38 16 13 14 62
32 32 9 5 11 63
37 35 14 6 14.5 76
39 34 16 12 13 74
29 34 16 12 9 67
37 36 15 11 10 73
35 34 16 10 15 70
30 28 12 7 20 53
38 34 16 12 12 77
34 35 16 14 12 80
31 35 14 11 14 52
34 31 16 12 13 54
35 37 17 13 11 80
36 35 18 14 17 66
30 27 18 11 12 73
39 40 12 12 13 63
35 37 16 12 14 69
38 36 10 8 13 67
31 38 14 11 15 54
34 39 18 14 13 81
38 41 18 14 10 69
34 27 16 12 11 84
39 30 17 9 19 80
37 37 16 13 13 70
34 31 16 11 17 69
28 31 13 12 13 77
37 27 16 12 9 54
33 36 16 12 11 79
35 37 16 12 9 71
37 33 15 12 12 73
32 34 15 11 12 72
33 31 16 10 13 77
38 39 14 9 13 75
33 34 16 12 12 69
29 32 16 12 15 54
33 33 15 12 22 70
31 36 12 9 13 73
36 32 17 15 15 54
35 41 16 12 13 77
32 28 15 12 15 82
29 30 13 12 12.5 80
39 36 16 10 11 80
37 35 16 13 16 69
35 31 16 9 11 78
37 34 16 12 11 81
32 36 14 10 10 76
38 36 16 14 10 76
37 35 16 11 16 73
36 37 20 15 12 85
32 28 15 11 11 66
33 39 16 11 16 79
40 32 13 12 19 68
38 35 17 12 11 76
41 39 16 12 16 71
36 35 16 11 15 54
43 42 12 7 24 46
30 34 16 12 14 85
31 33 16 14 15 74
32 41 17 11 11 88
32 33 13 11 15 38
37 34 12 10 12 76
37 32 18 13 10 86
33 40 14 13 14 54
34 40 14 8 13 67
33 35 13 11 9 69
38 36 16 12 15 90
33 37 13 11 15 54
31 27 16 13 14 76
38 39 13 12 11 89
37 38 16 14 8 76
36 31 15 13 11 73
31 33 16 15 11 79
39 32 15 10 8 90
44 39 17 11 10 74
33 36 15 9 11 81
35 33 12 11 13 72
32 33 16 10 11 71
28 32 10 11 20 66
40 37 16 8 10 77
27 30 12 11 15 65
37 38 14 12 12 74
32 29 15 12 14 85
28 22 13 9 23 54
34 35 15 11 14 63
30 35 11 10 16 54
35 34 12 8 11 64
31 35 11 9 12 69
32 34 16 8 10 54
30 37 15 9 14 84
30 35 17 15 12 86
31 23 16 11 12 77
40 31 10 8 11 89
32 27 18 13 12 76
36 36 13 12 13 60
32 31 16 12 11 75
35 32 13 9 19 73
38 39 10 7 12 85
42 37 15 13 17 79
34 38 16 9 9 71
35 39 16 6 12 72
38 34 14 8 19 69
33 31 10 8 18 78
36 32 17 15 15 54
32 37 13 6 14 69
33 36 15 9 11 81
34 32 16 11 9 84
32 38 12 8 18 84
34 36 13 8 16 69
27 26 13 10 24 66
31 26 12 8 14 81
38 33 17 14 20 82
34 39 15 10 18 72
24 30 10 8 23 54
30 33 14 11 12 78
26 25 11 12 14 74
34 38 13 12 16 82
27 37 16 12 18 73
37 31 12 5 20 55
36 37 16 12 12 72
41 35 12 10 12 78
29 25 9 7 17 59
36 28 12 12 13 72
32 35 15 11 9 78
37 33 12 8 16 68
30 30 12 9 18 69
31 31 14 10 10 67
38 37 12 9 14 74
36 36 16 12 11 54
35 30 11 6 9 67
31 36 19 15 11 70
38 32 15 12 10 80
22 28 8 12 11 89
32 36 16 12 19 76
36 34 17 11 14 74
39 31 12 7 12 87
28 28 11 7 14 54
32 36 11 5 21 61
32 36 14 12 13 38
38 40 16 12 10 75
32 33 12 3 15 69
35 37 16 11 16 62
32 32 13 10 14 72
37 38 15 12 12 70
34 31 16 9 19 79
33 37 16 12 15 87
33 33 14 9 19 62
26 32 16 12 13 77
30 30 16 12 17 69
24 30 14 10 12 69
34 31 11 9 11 75
34 32 12 12 14 54
33 34 15 8 11 72
34 36 15 11 13 74
35 37 16 11 12 85
35 36 16 12 15 52
36 33 11 10 14 70
34 33 15 10 12 84
34 33 12 12 17 64
41 44 12 12 11 84
32 39 15 11 18 87
30 32 15 8 13 79
35 35 16 12 17 67
28 25 14 10 13 65
33 35 17 11 11 85
39 34 14 10 12 83
36 35 13 8 22 61
36 39 15 12 14 82
35 33 13 12 12 76
38 36 14 10 12 58
33 32 15 12 17 72
31 32 12 9 9 72
34 36 13 9 21 38
32 36 8 6 10 78
31 32 14 10 11 54
33 34 14 9 12 63
34 33 11 9 23 66
34 35 12 9 13 70
34 30 13 6 12 71
33 38 10 10 16 67
32 34 16 6 9 58
41 33 18 14 17 72
34 32 13 10 9 72
36 31 11 10 14 70
37 30 4 6 17 76
36 27 13 12 13 50
29 31 16 12 11 72
37 30 10 7 12 72
27 32 12 8 10 88
35 35 12 11 19 53
28 28 10 3 16 58
35 33 13 6 16 66
37 31 15 10 14 82
29 35 12 8 20 69
32 35 14 9 15 68
36 32 10 9 23 44
19 21 12 8 20 56
21 20 12 9 16 53
31 34 11 7 14 70
33 32 10 7 17 78
36 34 12 6 11 71
33 32 16 9 13 72
37 33 12 10 17 68
34 33 14 11 15 67
35 37 16 12 21 75
31 32 14 8 18 62
37 34 13 11 15 67
35 30 4 3 8 83
27 30 15 11 12 64
34 38 11 12 12 68
40 36 11 7 22 62
29 32 14 9 12 72

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 8 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253714&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253714&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253714&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 time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
(1-B)Connected[t] = -0.0384626 + 0.413934`(1-B)Separate`[t] + 0.110394`(1-B)Learning`[t] -0.10077`(1-B)Software`[t] + 0.0569416`(1-B)Depression`[t] + 0.00981969`(1-B)Sport1`[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
(1-B)Connected[t] =  -0.0384626 +  0.413934`(1-B)Separate`[t] +  0.110394`(1-B)Learning`[t] -0.10077`(1-B)Software`[t] +  0.0569416`(1-B)Depression`[t] +  0.00981969`(1-B)Sport1`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253714&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C](1-B)Connected[t] =  -0.0384626 +  0.413934`(1-B)Separate`[t] +  0.110394`(1-B)Learning`[t] -0.10077`(1-B)Software`[t] +  0.0569416`(1-B)Depression`[t] +  0.00981969`(1-B)Sport1`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253714&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253714&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
(1-B)Connected[t] = -0.0384626 + 0.413934`(1-B)Separate`[t] + 0.110394`(1-B)Learning`[t] -0.10077`(1-B)Software`[t] + 0.0569416`(1-B)Depression`[t] + 0.00981969`(1-B)Sport1`[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-0.03846260.292767-0.13140.8955810.44779
`(1-B)Separate`0.4139340.05951026.9562.89905e-111.44953e-11
`(1-B)Learning`0.1103940.1141580.9670.3344390.16722
`(1-B)Software`-0.100770.115698-0.8710.3845810.192291
`(1-B)Depression`0.05694160.06722490.8470.3977660.198883
`(1-B)Sport1`0.009819690.02148990.45690.6480980.324049

\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) & -0.0384626 & 0.292767 & -0.1314 & 0.895581 & 0.44779 \tabularnewline
`(1-B)Separate` & 0.413934 & 0.0595102 & 6.956 & 2.89905e-11 & 1.44953e-11 \tabularnewline
`(1-B)Learning` & 0.110394 & 0.114158 & 0.967 & 0.334439 & 0.16722 \tabularnewline
`(1-B)Software` & -0.10077 & 0.115698 & -0.871 & 0.384581 & 0.192291 \tabularnewline
`(1-B)Depression` & 0.0569416 & 0.0672249 & 0.847 & 0.397766 & 0.198883 \tabularnewline
`(1-B)Sport1` & 0.00981969 & 0.0214899 & 0.4569 & 0.648098 & 0.324049 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253714&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]-0.0384626[/C][C]0.292767[/C][C]-0.1314[/C][C]0.895581[/C][C]0.44779[/C][/ROW]
[ROW][C]`(1-B)Separate`[/C][C]0.413934[/C][C]0.0595102[/C][C]6.956[/C][C]2.89905e-11[/C][C]1.44953e-11[/C][/ROW]
[ROW][C]`(1-B)Learning`[/C][C]0.110394[/C][C]0.114158[/C][C]0.967[/C][C]0.334439[/C][C]0.16722[/C][/ROW]
[ROW][C]`(1-B)Software`[/C][C]-0.10077[/C][C]0.115698[/C][C]-0.871[/C][C]0.384581[/C][C]0.192291[/C][/ROW]
[ROW][C]`(1-B)Depression`[/C][C]0.0569416[/C][C]0.0672249[/C][C]0.847[/C][C]0.397766[/C][C]0.198883[/C][/ROW]
[ROW][C]`(1-B)Sport1`[/C][C]0.00981969[/C][C]0.0214899[/C][C]0.4569[/C][C]0.648098[/C][C]0.324049[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253714&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253714&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)-0.03846260.292767-0.13140.8955810.44779
`(1-B)Separate`0.4139340.05951026.9562.89905e-111.44953e-11
`(1-B)Learning`0.1103940.1141580.9670.3344390.16722
`(1-B)Software`-0.100770.115698-0.8710.3845810.192291
`(1-B)Depression`0.05694160.06722490.8470.3977660.198883
`(1-B)Sport1`0.009819690.02148990.45690.6480980.324049






Multiple Linear Regression - Regression Statistics
Multiple R0.410282
R-squared0.168331
Adjusted R-squared0.152151
F-TEST (value)10.4034
F-TEST (DF numerator)5
F-TEST (DF denominator)257
p-value4.20252e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation4.7477
Sum Squared Residuals5792.95

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.410282 \tabularnewline
R-squared & 0.168331 \tabularnewline
Adjusted R-squared & 0.152151 \tabularnewline
F-TEST (value) & 10.4034 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 257 \tabularnewline
p-value & 4.20252e-09 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 4.7477 \tabularnewline
Sum Squared Residuals & 5792.95 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253714&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.410282[/C][/ROW]
[ROW][C]R-squared[/C][C]0.168331[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.152151[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]10.4034[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]257[/C][/ROW]
[ROW][C]p-value[/C][C]4.20252e-09[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]4.7477[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]5792.95[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253714&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253714&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 R0.410282
R-squared0.168331
Adjusted R-squared0.152151
F-TEST (value)10.4034
F-TEST (DF numerator)5
F-TEST (DF denominator)257
p-value4.20252e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation4.7477
Sum Squared Residuals5792.95






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1-2-1.85246-0.147536
2-91.13533-10.1353
31-0.5050451.50505
431.402341.59766
51-3.650854.65085
641.574162.42584
7-51.02686-6.02686
82-0.4771112.47711
911.80651-0.806506
101-3.067744.06774
11-20.642424-2.64242
1220.9017181.09828
1311.11951-0.119511
14-6-0.648797-5.3512
15-1-1.669680.669683
164-0.08392274.08392
1722.7524-0.752404
181-0.4510961.4511
19-7-2.74154-4.25846
2000.365323-0.365323
21-1-0.691223-0.308777
2282.838135.16187
23-20.37935-2.37935
242-2.802614.80261
252-0.3120342.31203
26-51.46986-6.46986
27-30.434961-3.43496
280-1.350831.35083
291-0.222671.22267
30-3-1.05759-1.94241
31-40.533704-4.5337
3210-0.5509210.5509
33-32.64899-5.64899
340-3.14113.1411
35-20.951443-2.95144
36-3-0.463128-2.53687
3770.5516996.4483
38-7-0.508787-6.49121
3960.7206675.27933
402-0.460242.46024
41-30.247671-3.24767
424-0.6402024.6402
43-30.538963-3.53896
443-2.112025.11202
45-12.43042-3.43042
4611.59046-0.590461
47-5-1.58412-3.41588
4831.945611.05439
492-3.061575.06157
50-62.37799-8.37799
510-2.988982.98898
5200.969499-0.969499
5322.13443-0.134429
54-2-2.649670.649675
5551.981493.01851
562-0.9412772.94128
57-10-0.334967-9.66503
5880.895647.10436
59-2-0.399918-1.60008
60-5-2.54356-2.45644
6182.163015.83699
62-40.203391-4.20339
63-3-0.118011-2.88199
643-1.611484.61148
6512.59619-1.59619
661-0.6525321.65253
67-6-3.2636-2.7364
6894.538294.46171
69-4-0.722827-3.27717
703-0.7882653.78827
71-70.914901-7.9149
7230.6659882.33401
7340.5007443.49926
74-4-5.648551.64855
7552.03232.9677
76-21.90576-3.90576
77-3-2.10258-0.89742
78-6-0.619624-5.38038
799-1.8166310.8166
80-44.04632-8.04632
8120.1830311.81697
822-1.614133.61413
83-50.466421-5.46642
841-0.963061.96306
8553.133351.86665
86-5-2.30551-2.69449
87-4-0.842801-3.1572
8840.8207833.17922
89-20.69145-2.69145
905-1.819536.81953
91-13.99083-4.99083
92-3-5.367022.36702
93-30.406623-3.40662
94102.892457.10755
95-2-0.578014-1.42199
96-2-1.48745-0.512549
9720.9304891.06951
98-50.664116-5.66412
996-0.2207526.22075
100-10.162103-1.1621
101-10.717974-1.71797
102-4-4.156280.156277
10315.03757-4.03757
1047-3.3051410.3051
105-21.26794-3.26794
10631.742491.25751
107-5-1.81731-3.18269
10873.254493.74551
109-13-3.59865-9.40135
1101-0.7050111.70501
11113.59542-2.59542
1120-4.054734.05473
11350.568174.43183
1140-0.5219590.521959
115-42.74497-6.74497
11610.53610.4639
117-1-2.728961.72896
11851.153753.84625
119-5-0.208451-4.79155
120-2-3.889071.88907
12174.655162.34484
122-1-0.621233-0.378767
123-1-2.804261.80426
124-50.757179-5.75718
1258-0.1217518.12175
12652.935862.06414
127-11-1.17383-9.82617
1282-1.787483.78748
129-30.380181-3.38018
130-4-0.752156-3.24784
131122.534489.46552
132-13-3.51301-9.48699
133103.310586.68942
134-5-3.43157-1.56843
135-4-2.64642-1.35358
13664.937831.06217
137-4-0.353764-3.64624
1385-0.3269745.32697
139-40.270347-4.27035
1401-0.06083391.06083
141-21.51453-3.51453
1420-1.34441.3444
1431-4.801365.80136
14492.973856.02615
145-8-1.38561-6.61439
14643.135570.864433
147-4-1.74354-2.25646
14830.782492.21751
14932.448680.551324
1504-0.6931864.69319
151-80.354854-8.35485
15210.8584240.141576
1533-2.161335.16133
154-5-1.69041-3.30959
15530.03634722.96365
156-42.58691-6.58691
1571-0.5869051.58691
1581-1.869772.86977
159-22.81835-4.81835
1602-1.017113.01711
161-7-3.95327-3.04673
1624-0.3694384.36944
16373.15793.8421
164-42.41535-6.41535
165-10-4.00635-5.99365
16660.9519235.04808
167-4-3.70728-0.292718
16885.755912.24409
169-7-0.0957076-6.90429
17010-2.3211312.3211
171-11.89273-2.89273
1725-1.047456.04745
173-12-4.10854-7.89146
17470.9305646.06944
175-43.12218-7.12218
1765-0.5948115.59481
177-7-1.25733-5.74267
17810.02031830.979682
17972.621634.37837
180-2-0.680347-1.31965
181-1-2.455651.45565
182-42.56471-6.56471
1837-1.792218.79221
184-16-2.32164-13.6784
185104.484045.51596
1864-0.9595144.95951
1873-1.415384.41538
188-11-1.60083-9.39917
18943.941880.0581234
1900-1.094051.09405
19162.030573.96943
192-6-2.24486-3.75514
19331.24091.7591
194-3-2.35423-0.645768
19552.330872.66913
196-3-2.03633-0.963671
197-11.99362-2.99362
1980-1.63041.6304
199-7-0.728271-6.27173
2004-0.7171224.71712
201-6-0.34242-5.65758
202100.1470349.85297
20300.148168-0.148168
204-11.5296-2.5296
20510.6206190.379381
20610.5369410.463059
2070-0.7063910.706391
2081-1.510882.51088
209-20.426707-2.42671
2100-0.4828710.482871
21174.369552.63045
212-9-1.24813-7.75187
213-2-2.996960.996957
21451.020593.97941
215-7-4.44446-2.55554
21654.41380.5862
2176-0.6455086.64551
218-30.819999-3.82
21901.18566-1.18566
220-1-2.915661.91566
22131.338521.66148
222-5-1.36316-3.63684
223-2-0.52287-1.47713
22432.07710.922903
225-2-0.521695-1.4783
226-1-1.613640.613642
22721.035490.964506
2281-0.1277631.12776
22900.369662-0.369662
2300-1.742551.74255
231-12.72723-3.72723
232-1-1.115720.115722
2339-0.4447569.44476
234-7-1.05682-5.94318
2352-0.4081172.40812
2361-0.5923361.59234
237-1-1.374410.374411
238-72.05061-9.05061
2398-0.5539738.55397
240-100.952656-10.9527
24181.069826.93018
242-7-2.47236-4.52764
24372.138644.86136
2442-1.005393.00539
245-81.70162-9.70162
2463-0.2129713.21297
2474-1.501985.50198
248-17-4.32317-12.6768
2492-0.8103922.81039
250105.900814.09919
2512-0.7273422.72734
25230.7005762.29942
253-3-0.603359-2.39664
25440.0216123.97839
255-3-0.0421464-2.95785
25612.1575-1.1575
257-4-2.22432-1.77568
25860.2549765.74502
259-2-2.123070.123067
260-80.410911-8.41091
26172.769944.23006
26260.1480155.85198
263-11-2.03577-8.96423
264-6NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & -2 & -1.85246 & -0.147536 \tabularnewline
2 & -9 & 1.13533 & -10.1353 \tabularnewline
3 & 1 & -0.505045 & 1.50505 \tabularnewline
4 & 3 & 1.40234 & 1.59766 \tabularnewline
5 & 1 & -3.65085 & 4.65085 \tabularnewline
6 & 4 & 1.57416 & 2.42584 \tabularnewline
7 & -5 & 1.02686 & -6.02686 \tabularnewline
8 & 2 & -0.477111 & 2.47711 \tabularnewline
9 & 1 & 1.80651 & -0.806506 \tabularnewline
10 & 1 & -3.06774 & 4.06774 \tabularnewline
11 & -2 & 0.642424 & -2.64242 \tabularnewline
12 & 2 & 0.901718 & 1.09828 \tabularnewline
13 & 1 & 1.11951 & -0.119511 \tabularnewline
14 & -6 & -0.648797 & -5.3512 \tabularnewline
15 & -1 & -1.66968 & 0.669683 \tabularnewline
16 & 4 & -0.0839227 & 4.08392 \tabularnewline
17 & 2 & 2.7524 & -0.752404 \tabularnewline
18 & 1 & -0.451096 & 1.4511 \tabularnewline
19 & -7 & -2.74154 & -4.25846 \tabularnewline
20 & 0 & 0.365323 & -0.365323 \tabularnewline
21 & -1 & -0.691223 & -0.308777 \tabularnewline
22 & 8 & 2.83813 & 5.16187 \tabularnewline
23 & -2 & 0.37935 & -2.37935 \tabularnewline
24 & 2 & -2.80261 & 4.80261 \tabularnewline
25 & 2 & -0.312034 & 2.31203 \tabularnewline
26 & -5 & 1.46986 & -6.46986 \tabularnewline
27 & -3 & 0.434961 & -3.43496 \tabularnewline
28 & 0 & -1.35083 & 1.35083 \tabularnewline
29 & 1 & -0.22267 & 1.22267 \tabularnewline
30 & -3 & -1.05759 & -1.94241 \tabularnewline
31 & -4 & 0.533704 & -4.5337 \tabularnewline
32 & 10 & -0.55092 & 10.5509 \tabularnewline
33 & -3 & 2.64899 & -5.64899 \tabularnewline
34 & 0 & -3.1411 & 3.1411 \tabularnewline
35 & -2 & 0.951443 & -2.95144 \tabularnewline
36 & -3 & -0.463128 & -2.53687 \tabularnewline
37 & 7 & 0.551699 & 6.4483 \tabularnewline
38 & -7 & -0.508787 & -6.49121 \tabularnewline
39 & 6 & 0.720667 & 5.27933 \tabularnewline
40 & 2 & -0.46024 & 2.46024 \tabularnewline
41 & -3 & 0.247671 & -3.24767 \tabularnewline
42 & 4 & -0.640202 & 4.6402 \tabularnewline
43 & -3 & 0.538963 & -3.53896 \tabularnewline
44 & 3 & -2.11202 & 5.11202 \tabularnewline
45 & -1 & 2.43042 & -3.43042 \tabularnewline
46 & 1 & 1.59046 & -0.590461 \tabularnewline
47 & -5 & -1.58412 & -3.41588 \tabularnewline
48 & 3 & 1.94561 & 1.05439 \tabularnewline
49 & 2 & -3.06157 & 5.06157 \tabularnewline
50 & -6 & 2.37799 & -8.37799 \tabularnewline
51 & 0 & -2.98898 & 2.98898 \tabularnewline
52 & 0 & 0.969499 & -0.969499 \tabularnewline
53 & 2 & 2.13443 & -0.134429 \tabularnewline
54 & -2 & -2.64967 & 0.649675 \tabularnewline
55 & 5 & 1.98149 & 3.01851 \tabularnewline
56 & 2 & -0.941277 & 2.94128 \tabularnewline
57 & -10 & -0.334967 & -9.66503 \tabularnewline
58 & 8 & 0.89564 & 7.10436 \tabularnewline
59 & -2 & -0.399918 & -1.60008 \tabularnewline
60 & -5 & -2.54356 & -2.45644 \tabularnewline
61 & 8 & 2.16301 & 5.83699 \tabularnewline
62 & -4 & 0.203391 & -4.20339 \tabularnewline
63 & -3 & -0.118011 & -2.88199 \tabularnewline
64 & 3 & -1.61148 & 4.61148 \tabularnewline
65 & 1 & 2.59619 & -1.59619 \tabularnewline
66 & 1 & -0.652532 & 1.65253 \tabularnewline
67 & -6 & -3.2636 & -2.7364 \tabularnewline
68 & 9 & 4.53829 & 4.46171 \tabularnewline
69 & -4 & -0.722827 & -3.27717 \tabularnewline
70 & 3 & -0.788265 & 3.78827 \tabularnewline
71 & -7 & 0.914901 & -7.9149 \tabularnewline
72 & 3 & 0.665988 & 2.33401 \tabularnewline
73 & 4 & 0.500744 & 3.49926 \tabularnewline
74 & -4 & -5.64855 & 1.64855 \tabularnewline
75 & 5 & 2.0323 & 2.9677 \tabularnewline
76 & -2 & 1.90576 & -3.90576 \tabularnewline
77 & -3 & -2.10258 & -0.89742 \tabularnewline
78 & -6 & -0.619624 & -5.38038 \tabularnewline
79 & 9 & -1.81663 & 10.8166 \tabularnewline
80 & -4 & 4.04632 & -8.04632 \tabularnewline
81 & 2 & 0.183031 & 1.81697 \tabularnewline
82 & 2 & -1.61413 & 3.61413 \tabularnewline
83 & -5 & 0.466421 & -5.46642 \tabularnewline
84 & 1 & -0.96306 & 1.96306 \tabularnewline
85 & 5 & 3.13335 & 1.86665 \tabularnewline
86 & -5 & -2.30551 & -2.69449 \tabularnewline
87 & -4 & -0.842801 & -3.1572 \tabularnewline
88 & 4 & 0.820783 & 3.17922 \tabularnewline
89 & -2 & 0.69145 & -2.69145 \tabularnewline
90 & 5 & -1.81953 & 6.81953 \tabularnewline
91 & -1 & 3.99083 & -4.99083 \tabularnewline
92 & -3 & -5.36702 & 2.36702 \tabularnewline
93 & -3 & 0.406623 & -3.40662 \tabularnewline
94 & 10 & 2.89245 & 7.10755 \tabularnewline
95 & -2 & -0.578014 & -1.42199 \tabularnewline
96 & -2 & -1.48745 & -0.512549 \tabularnewline
97 & 2 & 0.930489 & 1.06951 \tabularnewline
98 & -5 & 0.664116 & -5.66412 \tabularnewline
99 & 6 & -0.220752 & 6.22075 \tabularnewline
100 & -1 & 0.162103 & -1.1621 \tabularnewline
101 & -1 & 0.717974 & -1.71797 \tabularnewline
102 & -4 & -4.15628 & 0.156277 \tabularnewline
103 & 1 & 5.03757 & -4.03757 \tabularnewline
104 & 7 & -3.30514 & 10.3051 \tabularnewline
105 & -2 & 1.26794 & -3.26794 \tabularnewline
106 & 3 & 1.74249 & 1.25751 \tabularnewline
107 & -5 & -1.81731 & -3.18269 \tabularnewline
108 & 7 & 3.25449 & 3.74551 \tabularnewline
109 & -13 & -3.59865 & -9.40135 \tabularnewline
110 & 1 & -0.705011 & 1.70501 \tabularnewline
111 & 1 & 3.59542 & -2.59542 \tabularnewline
112 & 0 & -4.05473 & 4.05473 \tabularnewline
113 & 5 & 0.56817 & 4.43183 \tabularnewline
114 & 0 & -0.521959 & 0.521959 \tabularnewline
115 & -4 & 2.74497 & -6.74497 \tabularnewline
116 & 1 & 0.5361 & 0.4639 \tabularnewline
117 & -1 & -2.72896 & 1.72896 \tabularnewline
118 & 5 & 1.15375 & 3.84625 \tabularnewline
119 & -5 & -0.208451 & -4.79155 \tabularnewline
120 & -2 & -3.88907 & 1.88907 \tabularnewline
121 & 7 & 4.65516 & 2.34484 \tabularnewline
122 & -1 & -0.621233 & -0.378767 \tabularnewline
123 & -1 & -2.80426 & 1.80426 \tabularnewline
124 & -5 & 0.757179 & -5.75718 \tabularnewline
125 & 8 & -0.121751 & 8.12175 \tabularnewline
126 & 5 & 2.93586 & 2.06414 \tabularnewline
127 & -11 & -1.17383 & -9.82617 \tabularnewline
128 & 2 & -1.78748 & 3.78748 \tabularnewline
129 & -3 & 0.380181 & -3.38018 \tabularnewline
130 & -4 & -0.752156 & -3.24784 \tabularnewline
131 & 12 & 2.53448 & 9.46552 \tabularnewline
132 & -13 & -3.51301 & -9.48699 \tabularnewline
133 & 10 & 3.31058 & 6.68942 \tabularnewline
134 & -5 & -3.43157 & -1.56843 \tabularnewline
135 & -4 & -2.64642 & -1.35358 \tabularnewline
136 & 6 & 4.93783 & 1.06217 \tabularnewline
137 & -4 & -0.353764 & -3.64624 \tabularnewline
138 & 5 & -0.326974 & 5.32697 \tabularnewline
139 & -4 & 0.270347 & -4.27035 \tabularnewline
140 & 1 & -0.0608339 & 1.06083 \tabularnewline
141 & -2 & 1.51453 & -3.51453 \tabularnewline
142 & 0 & -1.3444 & 1.3444 \tabularnewline
143 & 1 & -4.80136 & 5.80136 \tabularnewline
144 & 9 & 2.97385 & 6.02615 \tabularnewline
145 & -8 & -1.38561 & -6.61439 \tabularnewline
146 & 4 & 3.13557 & 0.864433 \tabularnewline
147 & -4 & -1.74354 & -2.25646 \tabularnewline
148 & 3 & 0.78249 & 2.21751 \tabularnewline
149 & 3 & 2.44868 & 0.551324 \tabularnewline
150 & 4 & -0.693186 & 4.69319 \tabularnewline
151 & -8 & 0.354854 & -8.35485 \tabularnewline
152 & 1 & 0.858424 & 0.141576 \tabularnewline
153 & 3 & -2.16133 & 5.16133 \tabularnewline
154 & -5 & -1.69041 & -3.30959 \tabularnewline
155 & 3 & 0.0363472 & 2.96365 \tabularnewline
156 & -4 & 2.58691 & -6.58691 \tabularnewline
157 & 1 & -0.586905 & 1.58691 \tabularnewline
158 & 1 & -1.86977 & 2.86977 \tabularnewline
159 & -2 & 2.81835 & -4.81835 \tabularnewline
160 & 2 & -1.01711 & 3.01711 \tabularnewline
161 & -7 & -3.95327 & -3.04673 \tabularnewline
162 & 4 & -0.369438 & 4.36944 \tabularnewline
163 & 7 & 3.1579 & 3.8421 \tabularnewline
164 & -4 & 2.41535 & -6.41535 \tabularnewline
165 & -10 & -4.00635 & -5.99365 \tabularnewline
166 & 6 & 0.951923 & 5.04808 \tabularnewline
167 & -4 & -3.70728 & -0.292718 \tabularnewline
168 & 8 & 5.75591 & 2.24409 \tabularnewline
169 & -7 & -0.0957076 & -6.90429 \tabularnewline
170 & 10 & -2.32113 & 12.3211 \tabularnewline
171 & -1 & 1.89273 & -2.89273 \tabularnewline
172 & 5 & -1.04745 & 6.04745 \tabularnewline
173 & -12 & -4.10854 & -7.89146 \tabularnewline
174 & 7 & 0.930564 & 6.06944 \tabularnewline
175 & -4 & 3.12218 & -7.12218 \tabularnewline
176 & 5 & -0.594811 & 5.59481 \tabularnewline
177 & -7 & -1.25733 & -5.74267 \tabularnewline
178 & 1 & 0.0203183 & 0.979682 \tabularnewline
179 & 7 & 2.62163 & 4.37837 \tabularnewline
180 & -2 & -0.680347 & -1.31965 \tabularnewline
181 & -1 & -2.45565 & 1.45565 \tabularnewline
182 & -4 & 2.56471 & -6.56471 \tabularnewline
183 & 7 & -1.79221 & 8.79221 \tabularnewline
184 & -16 & -2.32164 & -13.6784 \tabularnewline
185 & 10 & 4.48404 & 5.51596 \tabularnewline
186 & 4 & -0.959514 & 4.95951 \tabularnewline
187 & 3 & -1.41538 & 4.41538 \tabularnewline
188 & -11 & -1.60083 & -9.39917 \tabularnewline
189 & 4 & 3.94188 & 0.0581234 \tabularnewline
190 & 0 & -1.09405 & 1.09405 \tabularnewline
191 & 6 & 2.03057 & 3.96943 \tabularnewline
192 & -6 & -2.24486 & -3.75514 \tabularnewline
193 & 3 & 1.2409 & 1.7591 \tabularnewline
194 & -3 & -2.35423 & -0.645768 \tabularnewline
195 & 5 & 2.33087 & 2.66913 \tabularnewline
196 & -3 & -2.03633 & -0.963671 \tabularnewline
197 & -1 & 1.99362 & -2.99362 \tabularnewline
198 & 0 & -1.6304 & 1.6304 \tabularnewline
199 & -7 & -0.728271 & -6.27173 \tabularnewline
200 & 4 & -0.717122 & 4.71712 \tabularnewline
201 & -6 & -0.34242 & -5.65758 \tabularnewline
202 & 10 & 0.147034 & 9.85297 \tabularnewline
203 & 0 & 0.148168 & -0.148168 \tabularnewline
204 & -1 & 1.5296 & -2.5296 \tabularnewline
205 & 1 & 0.620619 & 0.379381 \tabularnewline
206 & 1 & 0.536941 & 0.463059 \tabularnewline
207 & 0 & -0.706391 & 0.706391 \tabularnewline
208 & 1 & -1.51088 & 2.51088 \tabularnewline
209 & -2 & 0.426707 & -2.42671 \tabularnewline
210 & 0 & -0.482871 & 0.482871 \tabularnewline
211 & 7 & 4.36955 & 2.63045 \tabularnewline
212 & -9 & -1.24813 & -7.75187 \tabularnewline
213 & -2 & -2.99696 & 0.996957 \tabularnewline
214 & 5 & 1.02059 & 3.97941 \tabularnewline
215 & -7 & -4.44446 & -2.55554 \tabularnewline
216 & 5 & 4.4138 & 0.5862 \tabularnewline
217 & 6 & -0.645508 & 6.64551 \tabularnewline
218 & -3 & 0.819999 & -3.82 \tabularnewline
219 & 0 & 1.18566 & -1.18566 \tabularnewline
220 & -1 & -2.91566 & 1.91566 \tabularnewline
221 & 3 & 1.33852 & 1.66148 \tabularnewline
222 & -5 & -1.36316 & -3.63684 \tabularnewline
223 & -2 & -0.52287 & -1.47713 \tabularnewline
224 & 3 & 2.0771 & 0.922903 \tabularnewline
225 & -2 & -0.521695 & -1.4783 \tabularnewline
226 & -1 & -1.61364 & 0.613642 \tabularnewline
227 & 2 & 1.03549 & 0.964506 \tabularnewline
228 & 1 & -0.127763 & 1.12776 \tabularnewline
229 & 0 & 0.369662 & -0.369662 \tabularnewline
230 & 0 & -1.74255 & 1.74255 \tabularnewline
231 & -1 & 2.72723 & -3.72723 \tabularnewline
232 & -1 & -1.11572 & 0.115722 \tabularnewline
233 & 9 & -0.444756 & 9.44476 \tabularnewline
234 & -7 & -1.05682 & -5.94318 \tabularnewline
235 & 2 & -0.408117 & 2.40812 \tabularnewline
236 & 1 & -0.592336 & 1.59234 \tabularnewline
237 & -1 & -1.37441 & 0.374411 \tabularnewline
238 & -7 & 2.05061 & -9.05061 \tabularnewline
239 & 8 & -0.553973 & 8.55397 \tabularnewline
240 & -10 & 0.952656 & -10.9527 \tabularnewline
241 & 8 & 1.06982 & 6.93018 \tabularnewline
242 & -7 & -2.47236 & -4.52764 \tabularnewline
243 & 7 & 2.13864 & 4.86136 \tabularnewline
244 & 2 & -1.00539 & 3.00539 \tabularnewline
245 & -8 & 1.70162 & -9.70162 \tabularnewline
246 & 3 & -0.212971 & 3.21297 \tabularnewline
247 & 4 & -1.50198 & 5.50198 \tabularnewline
248 & -17 & -4.32317 & -12.6768 \tabularnewline
249 & 2 & -0.810392 & 2.81039 \tabularnewline
250 & 10 & 5.90081 & 4.09919 \tabularnewline
251 & 2 & -0.727342 & 2.72734 \tabularnewline
252 & 3 & 0.700576 & 2.29942 \tabularnewline
253 & -3 & -0.603359 & -2.39664 \tabularnewline
254 & 4 & 0.021612 & 3.97839 \tabularnewline
255 & -3 & -0.0421464 & -2.95785 \tabularnewline
256 & 1 & 2.1575 & -1.1575 \tabularnewline
257 & -4 & -2.22432 & -1.77568 \tabularnewline
258 & 6 & 0.254976 & 5.74502 \tabularnewline
259 & -2 & -2.12307 & 0.123067 \tabularnewline
260 & -8 & 0.410911 & -8.41091 \tabularnewline
261 & 7 & 2.76994 & 4.23006 \tabularnewline
262 & 6 & 0.148015 & 5.85198 \tabularnewline
263 & -11 & -2.03577 & -8.96423 \tabularnewline
264 & -6 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253714&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]-2[/C][C]-1.85246[/C][C]-0.147536[/C][/ROW]
[ROW][C]2[/C][C]-9[/C][C]1.13533[/C][C]-10.1353[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]-0.505045[/C][C]1.50505[/C][/ROW]
[ROW][C]4[/C][C]3[/C][C]1.40234[/C][C]1.59766[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]-3.65085[/C][C]4.65085[/C][/ROW]
[ROW][C]6[/C][C]4[/C][C]1.57416[/C][C]2.42584[/C][/ROW]
[ROW][C]7[/C][C]-5[/C][C]1.02686[/C][C]-6.02686[/C][/ROW]
[ROW][C]8[/C][C]2[/C][C]-0.477111[/C][C]2.47711[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]1.80651[/C][C]-0.806506[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]-3.06774[/C][C]4.06774[/C][/ROW]
[ROW][C]11[/C][C]-2[/C][C]0.642424[/C][C]-2.64242[/C][/ROW]
[ROW][C]12[/C][C]2[/C][C]0.901718[/C][C]1.09828[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]1.11951[/C][C]-0.119511[/C][/ROW]
[ROW][C]14[/C][C]-6[/C][C]-0.648797[/C][C]-5.3512[/C][/ROW]
[ROW][C]15[/C][C]-1[/C][C]-1.66968[/C][C]0.669683[/C][/ROW]
[ROW][C]16[/C][C]4[/C][C]-0.0839227[/C][C]4.08392[/C][/ROW]
[ROW][C]17[/C][C]2[/C][C]2.7524[/C][C]-0.752404[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]-0.451096[/C][C]1.4511[/C][/ROW]
[ROW][C]19[/C][C]-7[/C][C]-2.74154[/C][C]-4.25846[/C][/ROW]
[ROW][C]20[/C][C]0[/C][C]0.365323[/C][C]-0.365323[/C][/ROW]
[ROW][C]21[/C][C]-1[/C][C]-0.691223[/C][C]-0.308777[/C][/ROW]
[ROW][C]22[/C][C]8[/C][C]2.83813[/C][C]5.16187[/C][/ROW]
[ROW][C]23[/C][C]-2[/C][C]0.37935[/C][C]-2.37935[/C][/ROW]
[ROW][C]24[/C][C]2[/C][C]-2.80261[/C][C]4.80261[/C][/ROW]
[ROW][C]25[/C][C]2[/C][C]-0.312034[/C][C]2.31203[/C][/ROW]
[ROW][C]26[/C][C]-5[/C][C]1.46986[/C][C]-6.46986[/C][/ROW]
[ROW][C]27[/C][C]-3[/C][C]0.434961[/C][C]-3.43496[/C][/ROW]
[ROW][C]28[/C][C]0[/C][C]-1.35083[/C][C]1.35083[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]-0.22267[/C][C]1.22267[/C][/ROW]
[ROW][C]30[/C][C]-3[/C][C]-1.05759[/C][C]-1.94241[/C][/ROW]
[ROW][C]31[/C][C]-4[/C][C]0.533704[/C][C]-4.5337[/C][/ROW]
[ROW][C]32[/C][C]10[/C][C]-0.55092[/C][C]10.5509[/C][/ROW]
[ROW][C]33[/C][C]-3[/C][C]2.64899[/C][C]-5.64899[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]-3.1411[/C][C]3.1411[/C][/ROW]
[ROW][C]35[/C][C]-2[/C][C]0.951443[/C][C]-2.95144[/C][/ROW]
[ROW][C]36[/C][C]-3[/C][C]-0.463128[/C][C]-2.53687[/C][/ROW]
[ROW][C]37[/C][C]7[/C][C]0.551699[/C][C]6.4483[/C][/ROW]
[ROW][C]38[/C][C]-7[/C][C]-0.508787[/C][C]-6.49121[/C][/ROW]
[ROW][C]39[/C][C]6[/C][C]0.720667[/C][C]5.27933[/C][/ROW]
[ROW][C]40[/C][C]2[/C][C]-0.46024[/C][C]2.46024[/C][/ROW]
[ROW][C]41[/C][C]-3[/C][C]0.247671[/C][C]-3.24767[/C][/ROW]
[ROW][C]42[/C][C]4[/C][C]-0.640202[/C][C]4.6402[/C][/ROW]
[ROW][C]43[/C][C]-3[/C][C]0.538963[/C][C]-3.53896[/C][/ROW]
[ROW][C]44[/C][C]3[/C][C]-2.11202[/C][C]5.11202[/C][/ROW]
[ROW][C]45[/C][C]-1[/C][C]2.43042[/C][C]-3.43042[/C][/ROW]
[ROW][C]46[/C][C]1[/C][C]1.59046[/C][C]-0.590461[/C][/ROW]
[ROW][C]47[/C][C]-5[/C][C]-1.58412[/C][C]-3.41588[/C][/ROW]
[ROW][C]48[/C][C]3[/C][C]1.94561[/C][C]1.05439[/C][/ROW]
[ROW][C]49[/C][C]2[/C][C]-3.06157[/C][C]5.06157[/C][/ROW]
[ROW][C]50[/C][C]-6[/C][C]2.37799[/C][C]-8.37799[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]-2.98898[/C][C]2.98898[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.969499[/C][C]-0.969499[/C][/ROW]
[ROW][C]53[/C][C]2[/C][C]2.13443[/C][C]-0.134429[/C][/ROW]
[ROW][C]54[/C][C]-2[/C][C]-2.64967[/C][C]0.649675[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]1.98149[/C][C]3.01851[/C][/ROW]
[ROW][C]56[/C][C]2[/C][C]-0.941277[/C][C]2.94128[/C][/ROW]
[ROW][C]57[/C][C]-10[/C][C]-0.334967[/C][C]-9.66503[/C][/ROW]
[ROW][C]58[/C][C]8[/C][C]0.89564[/C][C]7.10436[/C][/ROW]
[ROW][C]59[/C][C]-2[/C][C]-0.399918[/C][C]-1.60008[/C][/ROW]
[ROW][C]60[/C][C]-5[/C][C]-2.54356[/C][C]-2.45644[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]2.16301[/C][C]5.83699[/C][/ROW]
[ROW][C]62[/C][C]-4[/C][C]0.203391[/C][C]-4.20339[/C][/ROW]
[ROW][C]63[/C][C]-3[/C][C]-0.118011[/C][C]-2.88199[/C][/ROW]
[ROW][C]64[/C][C]3[/C][C]-1.61148[/C][C]4.61148[/C][/ROW]
[ROW][C]65[/C][C]1[/C][C]2.59619[/C][C]-1.59619[/C][/ROW]
[ROW][C]66[/C][C]1[/C][C]-0.652532[/C][C]1.65253[/C][/ROW]
[ROW][C]67[/C][C]-6[/C][C]-3.2636[/C][C]-2.7364[/C][/ROW]
[ROW][C]68[/C][C]9[/C][C]4.53829[/C][C]4.46171[/C][/ROW]
[ROW][C]69[/C][C]-4[/C][C]-0.722827[/C][C]-3.27717[/C][/ROW]
[ROW][C]70[/C][C]3[/C][C]-0.788265[/C][C]3.78827[/C][/ROW]
[ROW][C]71[/C][C]-7[/C][C]0.914901[/C][C]-7.9149[/C][/ROW]
[ROW][C]72[/C][C]3[/C][C]0.665988[/C][C]2.33401[/C][/ROW]
[ROW][C]73[/C][C]4[/C][C]0.500744[/C][C]3.49926[/C][/ROW]
[ROW][C]74[/C][C]-4[/C][C]-5.64855[/C][C]1.64855[/C][/ROW]
[ROW][C]75[/C][C]5[/C][C]2.0323[/C][C]2.9677[/C][/ROW]
[ROW][C]76[/C][C]-2[/C][C]1.90576[/C][C]-3.90576[/C][/ROW]
[ROW][C]77[/C][C]-3[/C][C]-2.10258[/C][C]-0.89742[/C][/ROW]
[ROW][C]78[/C][C]-6[/C][C]-0.619624[/C][C]-5.38038[/C][/ROW]
[ROW][C]79[/C][C]9[/C][C]-1.81663[/C][C]10.8166[/C][/ROW]
[ROW][C]80[/C][C]-4[/C][C]4.04632[/C][C]-8.04632[/C][/ROW]
[ROW][C]81[/C][C]2[/C][C]0.183031[/C][C]1.81697[/C][/ROW]
[ROW][C]82[/C][C]2[/C][C]-1.61413[/C][C]3.61413[/C][/ROW]
[ROW][C]83[/C][C]-5[/C][C]0.466421[/C][C]-5.46642[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]-0.96306[/C][C]1.96306[/C][/ROW]
[ROW][C]85[/C][C]5[/C][C]3.13335[/C][C]1.86665[/C][/ROW]
[ROW][C]86[/C][C]-5[/C][C]-2.30551[/C][C]-2.69449[/C][/ROW]
[ROW][C]87[/C][C]-4[/C][C]-0.842801[/C][C]-3.1572[/C][/ROW]
[ROW][C]88[/C][C]4[/C][C]0.820783[/C][C]3.17922[/C][/ROW]
[ROW][C]89[/C][C]-2[/C][C]0.69145[/C][C]-2.69145[/C][/ROW]
[ROW][C]90[/C][C]5[/C][C]-1.81953[/C][C]6.81953[/C][/ROW]
[ROW][C]91[/C][C]-1[/C][C]3.99083[/C][C]-4.99083[/C][/ROW]
[ROW][C]92[/C][C]-3[/C][C]-5.36702[/C][C]2.36702[/C][/ROW]
[ROW][C]93[/C][C]-3[/C][C]0.406623[/C][C]-3.40662[/C][/ROW]
[ROW][C]94[/C][C]10[/C][C]2.89245[/C][C]7.10755[/C][/ROW]
[ROW][C]95[/C][C]-2[/C][C]-0.578014[/C][C]-1.42199[/C][/ROW]
[ROW][C]96[/C][C]-2[/C][C]-1.48745[/C][C]-0.512549[/C][/ROW]
[ROW][C]97[/C][C]2[/C][C]0.930489[/C][C]1.06951[/C][/ROW]
[ROW][C]98[/C][C]-5[/C][C]0.664116[/C][C]-5.66412[/C][/ROW]
[ROW][C]99[/C][C]6[/C][C]-0.220752[/C][C]6.22075[/C][/ROW]
[ROW][C]100[/C][C]-1[/C][C]0.162103[/C][C]-1.1621[/C][/ROW]
[ROW][C]101[/C][C]-1[/C][C]0.717974[/C][C]-1.71797[/C][/ROW]
[ROW][C]102[/C][C]-4[/C][C]-4.15628[/C][C]0.156277[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]5.03757[/C][C]-4.03757[/C][/ROW]
[ROW][C]104[/C][C]7[/C][C]-3.30514[/C][C]10.3051[/C][/ROW]
[ROW][C]105[/C][C]-2[/C][C]1.26794[/C][C]-3.26794[/C][/ROW]
[ROW][C]106[/C][C]3[/C][C]1.74249[/C][C]1.25751[/C][/ROW]
[ROW][C]107[/C][C]-5[/C][C]-1.81731[/C][C]-3.18269[/C][/ROW]
[ROW][C]108[/C][C]7[/C][C]3.25449[/C][C]3.74551[/C][/ROW]
[ROW][C]109[/C][C]-13[/C][C]-3.59865[/C][C]-9.40135[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]-0.705011[/C][C]1.70501[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]3.59542[/C][C]-2.59542[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]-4.05473[/C][C]4.05473[/C][/ROW]
[ROW][C]113[/C][C]5[/C][C]0.56817[/C][C]4.43183[/C][/ROW]
[ROW][C]114[/C][C]0[/C][C]-0.521959[/C][C]0.521959[/C][/ROW]
[ROW][C]115[/C][C]-4[/C][C]2.74497[/C][C]-6.74497[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.5361[/C][C]0.4639[/C][/ROW]
[ROW][C]117[/C][C]-1[/C][C]-2.72896[/C][C]1.72896[/C][/ROW]
[ROW][C]118[/C][C]5[/C][C]1.15375[/C][C]3.84625[/C][/ROW]
[ROW][C]119[/C][C]-5[/C][C]-0.208451[/C][C]-4.79155[/C][/ROW]
[ROW][C]120[/C][C]-2[/C][C]-3.88907[/C][C]1.88907[/C][/ROW]
[ROW][C]121[/C][C]7[/C][C]4.65516[/C][C]2.34484[/C][/ROW]
[ROW][C]122[/C][C]-1[/C][C]-0.621233[/C][C]-0.378767[/C][/ROW]
[ROW][C]123[/C][C]-1[/C][C]-2.80426[/C][C]1.80426[/C][/ROW]
[ROW][C]124[/C][C]-5[/C][C]0.757179[/C][C]-5.75718[/C][/ROW]
[ROW][C]125[/C][C]8[/C][C]-0.121751[/C][C]8.12175[/C][/ROW]
[ROW][C]126[/C][C]5[/C][C]2.93586[/C][C]2.06414[/C][/ROW]
[ROW][C]127[/C][C]-11[/C][C]-1.17383[/C][C]-9.82617[/C][/ROW]
[ROW][C]128[/C][C]2[/C][C]-1.78748[/C][C]3.78748[/C][/ROW]
[ROW][C]129[/C][C]-3[/C][C]0.380181[/C][C]-3.38018[/C][/ROW]
[ROW][C]130[/C][C]-4[/C][C]-0.752156[/C][C]-3.24784[/C][/ROW]
[ROW][C]131[/C][C]12[/C][C]2.53448[/C][C]9.46552[/C][/ROW]
[ROW][C]132[/C][C]-13[/C][C]-3.51301[/C][C]-9.48699[/C][/ROW]
[ROW][C]133[/C][C]10[/C][C]3.31058[/C][C]6.68942[/C][/ROW]
[ROW][C]134[/C][C]-5[/C][C]-3.43157[/C][C]-1.56843[/C][/ROW]
[ROW][C]135[/C][C]-4[/C][C]-2.64642[/C][C]-1.35358[/C][/ROW]
[ROW][C]136[/C][C]6[/C][C]4.93783[/C][C]1.06217[/C][/ROW]
[ROW][C]137[/C][C]-4[/C][C]-0.353764[/C][C]-3.64624[/C][/ROW]
[ROW][C]138[/C][C]5[/C][C]-0.326974[/C][C]5.32697[/C][/ROW]
[ROW][C]139[/C][C]-4[/C][C]0.270347[/C][C]-4.27035[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]-0.0608339[/C][C]1.06083[/C][/ROW]
[ROW][C]141[/C][C]-2[/C][C]1.51453[/C][C]-3.51453[/C][/ROW]
[ROW][C]142[/C][C]0[/C][C]-1.3444[/C][C]1.3444[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]-4.80136[/C][C]5.80136[/C][/ROW]
[ROW][C]144[/C][C]9[/C][C]2.97385[/C][C]6.02615[/C][/ROW]
[ROW][C]145[/C][C]-8[/C][C]-1.38561[/C][C]-6.61439[/C][/ROW]
[ROW][C]146[/C][C]4[/C][C]3.13557[/C][C]0.864433[/C][/ROW]
[ROW][C]147[/C][C]-4[/C][C]-1.74354[/C][C]-2.25646[/C][/ROW]
[ROW][C]148[/C][C]3[/C][C]0.78249[/C][C]2.21751[/C][/ROW]
[ROW][C]149[/C][C]3[/C][C]2.44868[/C][C]0.551324[/C][/ROW]
[ROW][C]150[/C][C]4[/C][C]-0.693186[/C][C]4.69319[/C][/ROW]
[ROW][C]151[/C][C]-8[/C][C]0.354854[/C][C]-8.35485[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]0.858424[/C][C]0.141576[/C][/ROW]
[ROW][C]153[/C][C]3[/C][C]-2.16133[/C][C]5.16133[/C][/ROW]
[ROW][C]154[/C][C]-5[/C][C]-1.69041[/C][C]-3.30959[/C][/ROW]
[ROW][C]155[/C][C]3[/C][C]0.0363472[/C][C]2.96365[/C][/ROW]
[ROW][C]156[/C][C]-4[/C][C]2.58691[/C][C]-6.58691[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]-0.586905[/C][C]1.58691[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]-1.86977[/C][C]2.86977[/C][/ROW]
[ROW][C]159[/C][C]-2[/C][C]2.81835[/C][C]-4.81835[/C][/ROW]
[ROW][C]160[/C][C]2[/C][C]-1.01711[/C][C]3.01711[/C][/ROW]
[ROW][C]161[/C][C]-7[/C][C]-3.95327[/C][C]-3.04673[/C][/ROW]
[ROW][C]162[/C][C]4[/C][C]-0.369438[/C][C]4.36944[/C][/ROW]
[ROW][C]163[/C][C]7[/C][C]3.1579[/C][C]3.8421[/C][/ROW]
[ROW][C]164[/C][C]-4[/C][C]2.41535[/C][C]-6.41535[/C][/ROW]
[ROW][C]165[/C][C]-10[/C][C]-4.00635[/C][C]-5.99365[/C][/ROW]
[ROW][C]166[/C][C]6[/C][C]0.951923[/C][C]5.04808[/C][/ROW]
[ROW][C]167[/C][C]-4[/C][C]-3.70728[/C][C]-0.292718[/C][/ROW]
[ROW][C]168[/C][C]8[/C][C]5.75591[/C][C]2.24409[/C][/ROW]
[ROW][C]169[/C][C]-7[/C][C]-0.0957076[/C][C]-6.90429[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]-2.32113[/C][C]12.3211[/C][/ROW]
[ROW][C]171[/C][C]-1[/C][C]1.89273[/C][C]-2.89273[/C][/ROW]
[ROW][C]172[/C][C]5[/C][C]-1.04745[/C][C]6.04745[/C][/ROW]
[ROW][C]173[/C][C]-12[/C][C]-4.10854[/C][C]-7.89146[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]0.930564[/C][C]6.06944[/C][/ROW]
[ROW][C]175[/C][C]-4[/C][C]3.12218[/C][C]-7.12218[/C][/ROW]
[ROW][C]176[/C][C]5[/C][C]-0.594811[/C][C]5.59481[/C][/ROW]
[ROW][C]177[/C][C]-7[/C][C]-1.25733[/C][C]-5.74267[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0.0203183[/C][C]0.979682[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]2.62163[/C][C]4.37837[/C][/ROW]
[ROW][C]180[/C][C]-2[/C][C]-0.680347[/C][C]-1.31965[/C][/ROW]
[ROW][C]181[/C][C]-1[/C][C]-2.45565[/C][C]1.45565[/C][/ROW]
[ROW][C]182[/C][C]-4[/C][C]2.56471[/C][C]-6.56471[/C][/ROW]
[ROW][C]183[/C][C]7[/C][C]-1.79221[/C][C]8.79221[/C][/ROW]
[ROW][C]184[/C][C]-16[/C][C]-2.32164[/C][C]-13.6784[/C][/ROW]
[ROW][C]185[/C][C]10[/C][C]4.48404[/C][C]5.51596[/C][/ROW]
[ROW][C]186[/C][C]4[/C][C]-0.959514[/C][C]4.95951[/C][/ROW]
[ROW][C]187[/C][C]3[/C][C]-1.41538[/C][C]4.41538[/C][/ROW]
[ROW][C]188[/C][C]-11[/C][C]-1.60083[/C][C]-9.39917[/C][/ROW]
[ROW][C]189[/C][C]4[/C][C]3.94188[/C][C]0.0581234[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]-1.09405[/C][C]1.09405[/C][/ROW]
[ROW][C]191[/C][C]6[/C][C]2.03057[/C][C]3.96943[/C][/ROW]
[ROW][C]192[/C][C]-6[/C][C]-2.24486[/C][C]-3.75514[/C][/ROW]
[ROW][C]193[/C][C]3[/C][C]1.2409[/C][C]1.7591[/C][/ROW]
[ROW][C]194[/C][C]-3[/C][C]-2.35423[/C][C]-0.645768[/C][/ROW]
[ROW][C]195[/C][C]5[/C][C]2.33087[/C][C]2.66913[/C][/ROW]
[ROW][C]196[/C][C]-3[/C][C]-2.03633[/C][C]-0.963671[/C][/ROW]
[ROW][C]197[/C][C]-1[/C][C]1.99362[/C][C]-2.99362[/C][/ROW]
[ROW][C]198[/C][C]0[/C][C]-1.6304[/C][C]1.6304[/C][/ROW]
[ROW][C]199[/C][C]-7[/C][C]-0.728271[/C][C]-6.27173[/C][/ROW]
[ROW][C]200[/C][C]4[/C][C]-0.717122[/C][C]4.71712[/C][/ROW]
[ROW][C]201[/C][C]-6[/C][C]-0.34242[/C][C]-5.65758[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]0.147034[/C][C]9.85297[/C][/ROW]
[ROW][C]203[/C][C]0[/C][C]0.148168[/C][C]-0.148168[/C][/ROW]
[ROW][C]204[/C][C]-1[/C][C]1.5296[/C][C]-2.5296[/C][/ROW]
[ROW][C]205[/C][C]1[/C][C]0.620619[/C][C]0.379381[/C][/ROW]
[ROW][C]206[/C][C]1[/C][C]0.536941[/C][C]0.463059[/C][/ROW]
[ROW][C]207[/C][C]0[/C][C]-0.706391[/C][C]0.706391[/C][/ROW]
[ROW][C]208[/C][C]1[/C][C]-1.51088[/C][C]2.51088[/C][/ROW]
[ROW][C]209[/C][C]-2[/C][C]0.426707[/C][C]-2.42671[/C][/ROW]
[ROW][C]210[/C][C]0[/C][C]-0.482871[/C][C]0.482871[/C][/ROW]
[ROW][C]211[/C][C]7[/C][C]4.36955[/C][C]2.63045[/C][/ROW]
[ROW][C]212[/C][C]-9[/C][C]-1.24813[/C][C]-7.75187[/C][/ROW]
[ROW][C]213[/C][C]-2[/C][C]-2.99696[/C][C]0.996957[/C][/ROW]
[ROW][C]214[/C][C]5[/C][C]1.02059[/C][C]3.97941[/C][/ROW]
[ROW][C]215[/C][C]-7[/C][C]-4.44446[/C][C]-2.55554[/C][/ROW]
[ROW][C]216[/C][C]5[/C][C]4.4138[/C][C]0.5862[/C][/ROW]
[ROW][C]217[/C][C]6[/C][C]-0.645508[/C][C]6.64551[/C][/ROW]
[ROW][C]218[/C][C]-3[/C][C]0.819999[/C][C]-3.82[/C][/ROW]
[ROW][C]219[/C][C]0[/C][C]1.18566[/C][C]-1.18566[/C][/ROW]
[ROW][C]220[/C][C]-1[/C][C]-2.91566[/C][C]1.91566[/C][/ROW]
[ROW][C]221[/C][C]3[/C][C]1.33852[/C][C]1.66148[/C][/ROW]
[ROW][C]222[/C][C]-5[/C][C]-1.36316[/C][C]-3.63684[/C][/ROW]
[ROW][C]223[/C][C]-2[/C][C]-0.52287[/C][C]-1.47713[/C][/ROW]
[ROW][C]224[/C][C]3[/C][C]2.0771[/C][C]0.922903[/C][/ROW]
[ROW][C]225[/C][C]-2[/C][C]-0.521695[/C][C]-1.4783[/C][/ROW]
[ROW][C]226[/C][C]-1[/C][C]-1.61364[/C][C]0.613642[/C][/ROW]
[ROW][C]227[/C][C]2[/C][C]1.03549[/C][C]0.964506[/C][/ROW]
[ROW][C]228[/C][C]1[/C][C]-0.127763[/C][C]1.12776[/C][/ROW]
[ROW][C]229[/C][C]0[/C][C]0.369662[/C][C]-0.369662[/C][/ROW]
[ROW][C]230[/C][C]0[/C][C]-1.74255[/C][C]1.74255[/C][/ROW]
[ROW][C]231[/C][C]-1[/C][C]2.72723[/C][C]-3.72723[/C][/ROW]
[ROW][C]232[/C][C]-1[/C][C]-1.11572[/C][C]0.115722[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]-0.444756[/C][C]9.44476[/C][/ROW]
[ROW][C]234[/C][C]-7[/C][C]-1.05682[/C][C]-5.94318[/C][/ROW]
[ROW][C]235[/C][C]2[/C][C]-0.408117[/C][C]2.40812[/C][/ROW]
[ROW][C]236[/C][C]1[/C][C]-0.592336[/C][C]1.59234[/C][/ROW]
[ROW][C]237[/C][C]-1[/C][C]-1.37441[/C][C]0.374411[/C][/ROW]
[ROW][C]238[/C][C]-7[/C][C]2.05061[/C][C]-9.05061[/C][/ROW]
[ROW][C]239[/C][C]8[/C][C]-0.553973[/C][C]8.55397[/C][/ROW]
[ROW][C]240[/C][C]-10[/C][C]0.952656[/C][C]-10.9527[/C][/ROW]
[ROW][C]241[/C][C]8[/C][C]1.06982[/C][C]6.93018[/C][/ROW]
[ROW][C]242[/C][C]-7[/C][C]-2.47236[/C][C]-4.52764[/C][/ROW]
[ROW][C]243[/C][C]7[/C][C]2.13864[/C][C]4.86136[/C][/ROW]
[ROW][C]244[/C][C]2[/C][C]-1.00539[/C][C]3.00539[/C][/ROW]
[ROW][C]245[/C][C]-8[/C][C]1.70162[/C][C]-9.70162[/C][/ROW]
[ROW][C]246[/C][C]3[/C][C]-0.212971[/C][C]3.21297[/C][/ROW]
[ROW][C]247[/C][C]4[/C][C]-1.50198[/C][C]5.50198[/C][/ROW]
[ROW][C]248[/C][C]-17[/C][C]-4.32317[/C][C]-12.6768[/C][/ROW]
[ROW][C]249[/C][C]2[/C][C]-0.810392[/C][C]2.81039[/C][/ROW]
[ROW][C]250[/C][C]10[/C][C]5.90081[/C][C]4.09919[/C][/ROW]
[ROW][C]251[/C][C]2[/C][C]-0.727342[/C][C]2.72734[/C][/ROW]
[ROW][C]252[/C][C]3[/C][C]0.700576[/C][C]2.29942[/C][/ROW]
[ROW][C]253[/C][C]-3[/C][C]-0.603359[/C][C]-2.39664[/C][/ROW]
[ROW][C]254[/C][C]4[/C][C]0.021612[/C][C]3.97839[/C][/ROW]
[ROW][C]255[/C][C]-3[/C][C]-0.0421464[/C][C]-2.95785[/C][/ROW]
[ROW][C]256[/C][C]1[/C][C]2.1575[/C][C]-1.1575[/C][/ROW]
[ROW][C]257[/C][C]-4[/C][C]-2.22432[/C][C]-1.77568[/C][/ROW]
[ROW][C]258[/C][C]6[/C][C]0.254976[/C][C]5.74502[/C][/ROW]
[ROW][C]259[/C][C]-2[/C][C]-2.12307[/C][C]0.123067[/C][/ROW]
[ROW][C]260[/C][C]-8[/C][C]0.410911[/C][C]-8.41091[/C][/ROW]
[ROW][C]261[/C][C]7[/C][C]2.76994[/C][C]4.23006[/C][/ROW]
[ROW][C]262[/C][C]6[/C][C]0.148015[/C][C]5.85198[/C][/ROW]
[ROW][C]263[/C][C]-11[/C][C]-2.03577[/C][C]-8.96423[/C][/ROW]
[ROW][C]264[/C][C]-6[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253714&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253714&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
1-2-1.85246-0.147536
2-91.13533-10.1353
31-0.5050451.50505
431.402341.59766
51-3.650854.65085
641.574162.42584
7-51.02686-6.02686
82-0.4771112.47711
911.80651-0.806506
101-3.067744.06774
11-20.642424-2.64242
1220.9017181.09828
1311.11951-0.119511
14-6-0.648797-5.3512
15-1-1.669680.669683
164-0.08392274.08392
1722.7524-0.752404
181-0.4510961.4511
19-7-2.74154-4.25846
2000.365323-0.365323
21-1-0.691223-0.308777
2282.838135.16187
23-20.37935-2.37935
242-2.802614.80261
252-0.3120342.31203
26-51.46986-6.46986
27-30.434961-3.43496
280-1.350831.35083
291-0.222671.22267
30-3-1.05759-1.94241
31-40.533704-4.5337
3210-0.5509210.5509
33-32.64899-5.64899
340-3.14113.1411
35-20.951443-2.95144
36-3-0.463128-2.53687
3770.5516996.4483
38-7-0.508787-6.49121
3960.7206675.27933
402-0.460242.46024
41-30.247671-3.24767
424-0.6402024.6402
43-30.538963-3.53896
443-2.112025.11202
45-12.43042-3.43042
4611.59046-0.590461
47-5-1.58412-3.41588
4831.945611.05439
492-3.061575.06157
50-62.37799-8.37799
510-2.988982.98898
5200.969499-0.969499
5322.13443-0.134429
54-2-2.649670.649675
5551.981493.01851
562-0.9412772.94128
57-10-0.334967-9.66503
5880.895647.10436
59-2-0.399918-1.60008
60-5-2.54356-2.45644
6182.163015.83699
62-40.203391-4.20339
63-3-0.118011-2.88199
643-1.611484.61148
6512.59619-1.59619
661-0.6525321.65253
67-6-3.2636-2.7364
6894.538294.46171
69-4-0.722827-3.27717
703-0.7882653.78827
71-70.914901-7.9149
7230.6659882.33401
7340.5007443.49926
74-4-5.648551.64855
7552.03232.9677
76-21.90576-3.90576
77-3-2.10258-0.89742
78-6-0.619624-5.38038
799-1.8166310.8166
80-44.04632-8.04632
8120.1830311.81697
822-1.614133.61413
83-50.466421-5.46642
841-0.963061.96306
8553.133351.86665
86-5-2.30551-2.69449
87-4-0.842801-3.1572
8840.8207833.17922
89-20.69145-2.69145
905-1.819536.81953
91-13.99083-4.99083
92-3-5.367022.36702
93-30.406623-3.40662
94102.892457.10755
95-2-0.578014-1.42199
96-2-1.48745-0.512549
9720.9304891.06951
98-50.664116-5.66412
996-0.2207526.22075
100-10.162103-1.1621
101-10.717974-1.71797
102-4-4.156280.156277
10315.03757-4.03757
1047-3.3051410.3051
105-21.26794-3.26794
10631.742491.25751
107-5-1.81731-3.18269
10873.254493.74551
109-13-3.59865-9.40135
1101-0.7050111.70501
11113.59542-2.59542
1120-4.054734.05473
11350.568174.43183
1140-0.5219590.521959
115-42.74497-6.74497
11610.53610.4639
117-1-2.728961.72896
11851.153753.84625
119-5-0.208451-4.79155
120-2-3.889071.88907
12174.655162.34484
122-1-0.621233-0.378767
123-1-2.804261.80426
124-50.757179-5.75718
1258-0.1217518.12175
12652.935862.06414
127-11-1.17383-9.82617
1282-1.787483.78748
129-30.380181-3.38018
130-4-0.752156-3.24784
131122.534489.46552
132-13-3.51301-9.48699
133103.310586.68942
134-5-3.43157-1.56843
135-4-2.64642-1.35358
13664.937831.06217
137-4-0.353764-3.64624
1385-0.3269745.32697
139-40.270347-4.27035
1401-0.06083391.06083
141-21.51453-3.51453
1420-1.34441.3444
1431-4.801365.80136
14492.973856.02615
145-8-1.38561-6.61439
14643.135570.864433
147-4-1.74354-2.25646
14830.782492.21751
14932.448680.551324
1504-0.6931864.69319
151-80.354854-8.35485
15210.8584240.141576
1533-2.161335.16133
154-5-1.69041-3.30959
15530.03634722.96365
156-42.58691-6.58691
1571-0.5869051.58691
1581-1.869772.86977
159-22.81835-4.81835
1602-1.017113.01711
161-7-3.95327-3.04673
1624-0.3694384.36944
16373.15793.8421
164-42.41535-6.41535
165-10-4.00635-5.99365
16660.9519235.04808
167-4-3.70728-0.292718
16885.755912.24409
169-7-0.0957076-6.90429
17010-2.3211312.3211
171-11.89273-2.89273
1725-1.047456.04745
173-12-4.10854-7.89146
17470.9305646.06944
175-43.12218-7.12218
1765-0.5948115.59481
177-7-1.25733-5.74267
17810.02031830.979682
17972.621634.37837
180-2-0.680347-1.31965
181-1-2.455651.45565
182-42.56471-6.56471
1837-1.792218.79221
184-16-2.32164-13.6784
185104.484045.51596
1864-0.9595144.95951
1873-1.415384.41538
188-11-1.60083-9.39917
18943.941880.0581234
1900-1.094051.09405
19162.030573.96943
192-6-2.24486-3.75514
19331.24091.7591
194-3-2.35423-0.645768
19552.330872.66913
196-3-2.03633-0.963671
197-11.99362-2.99362
1980-1.63041.6304
199-7-0.728271-6.27173
2004-0.7171224.71712
201-6-0.34242-5.65758
202100.1470349.85297
20300.148168-0.148168
204-11.5296-2.5296
20510.6206190.379381
20610.5369410.463059
2070-0.7063910.706391
2081-1.510882.51088
209-20.426707-2.42671
2100-0.4828710.482871
21174.369552.63045
212-9-1.24813-7.75187
213-2-2.996960.996957
21451.020593.97941
215-7-4.44446-2.55554
21654.41380.5862
2176-0.6455086.64551
218-30.819999-3.82
21901.18566-1.18566
220-1-2.915661.91566
22131.338521.66148
222-5-1.36316-3.63684
223-2-0.52287-1.47713
22432.07710.922903
225-2-0.521695-1.4783
226-1-1.613640.613642
22721.035490.964506
2281-0.1277631.12776
22900.369662-0.369662
2300-1.742551.74255
231-12.72723-3.72723
232-1-1.115720.115722
2339-0.4447569.44476
234-7-1.05682-5.94318
2352-0.4081172.40812
2361-0.5923361.59234
237-1-1.374410.374411
238-72.05061-9.05061
2398-0.5539738.55397
240-100.952656-10.9527
24181.069826.93018
242-7-2.47236-4.52764
24372.138644.86136
2442-1.005393.00539
245-81.70162-9.70162
2463-0.2129713.21297
2474-1.501985.50198
248-17-4.32317-12.6768
2492-0.8103922.81039
250105.900814.09919
2512-0.7273422.72734
25230.7005762.29942
253-3-0.603359-2.39664
25440.0216123.97839
255-3-0.0421464-2.95785
25612.1575-1.1575
257-4-2.22432-1.77568
25860.2549765.74502
259-2-2.123070.123067
260-80.410911-8.41091
26172.769944.23006
26260.1480155.85198
263-11-2.03577-8.96423
264-6NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.6503190.6993610.349681
100.4926940.9853880.507306
110.3508340.7016680.649166
120.2358120.4716240.764188
130.177440.3548790.82256
140.1218540.2437090.878146
150.1707310.3414610.829269
160.1547080.3094160.845292
170.1581880.3163750.841812
180.1153010.2306020.884699
190.1590020.3180050.840998
200.1120830.2241650.887917
210.07730050.1546010.9227
220.1293830.2587660.870617
230.1014120.2028240.898588
240.1002770.2005550.899723
250.08344680.1668940.916553
260.1225120.2450230.877488
270.09253920.1850780.907461
280.06753110.1350620.932469
290.05030730.1006150.949693
300.0377670.07553410.962233
310.03651750.07303490.963483
320.1277950.255590.872205
330.1243930.2487860.875607
340.1021850.2043710.897815
350.08005330.1601070.919947
360.06224570.1244910.937754
370.06476130.1295230.935239
380.1308740.2617490.869126
390.1552080.3104160.844792
400.1318080.2636170.868192
410.1069870.2139730.893013
420.08700210.1740040.912998
430.069470.138940.93053
440.06356720.1271340.936433
450.05080430.1016090.949196
460.03947820.07895640.960522
470.04203690.08407390.957963
480.03539110.07078230.964609
490.03215970.06431930.96784
500.05199030.1039810.94801
510.0416140.08322790.958386
520.03328980.06657950.96671
530.02523680.05047360.974763
540.01895030.03790070.98105
550.01685210.03370420.983148
560.01320510.02641010.986795
570.04519750.09039510.954802
580.07965670.1593130.920343
590.06706350.1341270.932937
600.05742320.1148460.942577
610.06360970.1272190.93639
620.06014070.1202810.939859
630.05007520.100150.949925
640.04418330.08836650.955817
650.03508050.07016090.96492
660.02838150.05676290.971619
670.03262480.06524960.967375
680.06322470.1264490.936775
690.06137960.1227590.93862
700.06090610.1218120.939094
710.08868060.1773610.911319
720.07535940.1507190.924641
730.06943110.1388620.930569
740.05743680.1148740.942563
750.05661940.1132390.943381
760.05207920.1041580.947921
770.04271310.08542620.957287
780.04656190.09312380.953438
790.09098570.1819710.909014
800.1079240.2158480.892076
810.09264810.1852960.907352
820.08636580.1727320.913634
830.09180580.1836120.908194
840.07835620.1567120.921644
850.07310160.1462030.926898
860.06930090.1386020.930699
870.06275730.1255150.937243
880.06193490.123870.938065
890.0547140.1094280.945286
900.06123320.1224660.938767
910.05744730.1148950.942553
920.04877290.09754580.951227
930.04364260.08728520.956357
940.05902970.1180590.94097
950.04929390.09858780.950706
960.04151660.08303320.958483
970.03464660.06929330.965353
980.03692450.07384910.963075
990.04212630.08425260.957874
1000.03457720.06915430.965423
1010.02982220.05964440.970178
1020.02410220.04820440.975898
1030.02141720.04283430.978583
1040.04721720.09443440.952783
1050.04439550.08879110.955604
1060.03835320.07670630.961647
1070.03643790.07287580.963562
1080.04098880.08197750.959011
1090.08390270.1678050.916097
1100.07190770.1438150.928092
1110.06265530.1253110.937345
1120.05780340.1156070.942197
1130.06068060.1213610.939319
1140.05070490.101410.949295
1150.05947840.1189570.940522
1160.04960460.09920920.950395
1170.04200460.08400920.957995
1180.03966920.07933840.960331
1190.04039030.08078070.95961
1200.03523010.07046020.96477
1210.03394140.06788270.966059
1220.02787340.05574680.972127
1230.02335380.04670750.976646
1240.02582070.05164130.974179
1250.0390570.07811390.960943
1260.03368050.06736110.966319
1270.06378280.1275660.936217
1280.06027090.1205420.939729
1290.05621990.112440.94378
1300.05077010.101540.94923
1310.08437060.1687410.915629
1320.134310.2686190.86569
1330.1564370.3128740.843563
1340.1393450.278690.860655
1350.1224670.2449340.877533
1360.1062720.2125440.893728
1370.1005530.2011070.899447
1380.1059010.2118020.894099
1390.1027180.2054350.897282
1400.0904640.1809280.909536
1410.08333780.1666760.916662
1420.07137750.1427550.928623
1430.0811990.1623980.918801
1440.09378050.1875610.906219
1450.1095950.219190.890405
1460.09717250.1943450.902828
1470.08625750.1725150.913742
1480.07609030.1521810.92391
1490.06416370.1283270.935836
1500.06552110.1310420.934479
1510.09575510.191510.904245
1520.08134890.1626980.918651
1530.08468440.1693690.915316
1540.07788260.1557650.922117
1550.07022290.1404460.929777
1560.0844230.1688460.915577
1570.07331170.1466230.926688
1580.06701170.1340230.932988
1590.07422310.1484460.925777
1600.06736280.1347260.932637
1610.05923430.1184690.940766
1620.05832140.1166430.941679
1630.05433890.1086780.945661
1640.07062340.1412470.929377
1650.07800770.1560150.921992
1660.08616720.1723340.913833
1670.07257090.1451420.927429
1680.06267720.1253540.937323
1690.07508560.1501710.924914
1700.1783260.3566520.821674
1710.1625060.3250110.837494
1720.1756430.3512870.824357
1730.2148710.4297410.785129
1740.2401460.4802930.759854
1750.2834390.5668790.716561
1760.2889110.5778220.711089
1770.2983840.5967690.701616
1780.2696330.5392670.730367
1790.2566580.5133150.743342
1800.2284610.4569230.771539
1810.2045670.4091330.795433
1820.2266710.4533420.773329
1830.3131980.6263960.686802
1840.6273060.7453870.372694
1850.6528460.6943080.347154
1860.6774540.6450930.322546
1870.6716680.6566640.328332
1880.7969270.4061470.203073
1890.7688740.4622520.231126
1900.7376550.5246890.262345
1910.753160.493680.24684
1920.7375250.524950.262475
1930.7057310.5885370.294269
1940.6693460.6613080.330654
1950.6418090.7163810.358191
1960.6056630.7886730.394337
1970.5926570.8146860.407343
1980.5531330.8937340.446867
1990.5673190.8653630.432681
2000.5657080.8685840.434292
2010.5930960.8138080.406904
2020.7073240.5853520.292676
2030.674230.6515390.32577
2040.6416590.7166830.358341
2050.6012140.7975710.398786
2060.561390.8772190.43861
2070.5211410.9577190.478859
2080.4871840.9743680.512816
2090.4478260.8956520.552174
2100.4239820.8479640.576018
2110.3919150.783830.608085
2120.4135230.8270470.586477
2130.3818880.7637770.618112
2140.3499060.6998130.650094
2150.313320.6266390.68668
2160.2791880.5583750.720812
2170.2953560.5907130.704644
2180.3121020.6242050.687898
2190.2711540.5423090.728846
2200.2356550.471310.764345
2210.2013960.4027910.798604
2220.1805450.3610890.819455
2230.1508890.3017770.849111
2240.1311480.2622950.868852
2250.107560.215120.89244
2260.08615170.1723030.913848
2270.068580.137160.93142
2280.05481620.1096320.945184
2290.0432580.08651590.956742
2300.03783160.07566320.962168
2310.06677170.1335430.933228
2320.1023230.2046470.897677
2330.1330840.2661670.866916
2340.1730090.3460180.826991
2350.1389330.2778660.861067
2360.1113290.2226580.888671
2370.1021430.2042860.897857
2380.1138860.2277720.886114
2390.1302860.2605720.869714
2400.2574530.5149060.742547
2410.2341820.4683640.765818
2420.1858550.371710.814145
2430.1724720.3449430.827528
2440.1673210.3346410.832679
2450.8664650.267070.133535
2460.90060.1988010.0994004
2470.8654750.269050.134525
2480.8687920.2624160.131208
2490.8600220.2799570.139978
2500.7889270.4221450.211073
2510.7358470.5283060.264153
2520.7701850.459630.229815
2530.6379360.7241280.362064
2540.7384350.523130.261565
2550.6015050.7969890.398495

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.650319 & 0.699361 & 0.349681 \tabularnewline
10 & 0.492694 & 0.985388 & 0.507306 \tabularnewline
11 & 0.350834 & 0.701668 & 0.649166 \tabularnewline
12 & 0.235812 & 0.471624 & 0.764188 \tabularnewline
13 & 0.17744 & 0.354879 & 0.82256 \tabularnewline
14 & 0.121854 & 0.243709 & 0.878146 \tabularnewline
15 & 0.170731 & 0.341461 & 0.829269 \tabularnewline
16 & 0.154708 & 0.309416 & 0.845292 \tabularnewline
17 & 0.158188 & 0.316375 & 0.841812 \tabularnewline
18 & 0.115301 & 0.230602 & 0.884699 \tabularnewline
19 & 0.159002 & 0.318005 & 0.840998 \tabularnewline
20 & 0.112083 & 0.224165 & 0.887917 \tabularnewline
21 & 0.0773005 & 0.154601 & 0.9227 \tabularnewline
22 & 0.129383 & 0.258766 & 0.870617 \tabularnewline
23 & 0.101412 & 0.202824 & 0.898588 \tabularnewline
24 & 0.100277 & 0.200555 & 0.899723 \tabularnewline
25 & 0.0834468 & 0.166894 & 0.916553 \tabularnewline
26 & 0.122512 & 0.245023 & 0.877488 \tabularnewline
27 & 0.0925392 & 0.185078 & 0.907461 \tabularnewline
28 & 0.0675311 & 0.135062 & 0.932469 \tabularnewline
29 & 0.0503073 & 0.100615 & 0.949693 \tabularnewline
30 & 0.037767 & 0.0755341 & 0.962233 \tabularnewline
31 & 0.0365175 & 0.0730349 & 0.963483 \tabularnewline
32 & 0.127795 & 0.25559 & 0.872205 \tabularnewline
33 & 0.124393 & 0.248786 & 0.875607 \tabularnewline
34 & 0.102185 & 0.204371 & 0.897815 \tabularnewline
35 & 0.0800533 & 0.160107 & 0.919947 \tabularnewline
36 & 0.0622457 & 0.124491 & 0.937754 \tabularnewline
37 & 0.0647613 & 0.129523 & 0.935239 \tabularnewline
38 & 0.130874 & 0.261749 & 0.869126 \tabularnewline
39 & 0.155208 & 0.310416 & 0.844792 \tabularnewline
40 & 0.131808 & 0.263617 & 0.868192 \tabularnewline
41 & 0.106987 & 0.213973 & 0.893013 \tabularnewline
42 & 0.0870021 & 0.174004 & 0.912998 \tabularnewline
43 & 0.06947 & 0.13894 & 0.93053 \tabularnewline
44 & 0.0635672 & 0.127134 & 0.936433 \tabularnewline
45 & 0.0508043 & 0.101609 & 0.949196 \tabularnewline
46 & 0.0394782 & 0.0789564 & 0.960522 \tabularnewline
47 & 0.0420369 & 0.0840739 & 0.957963 \tabularnewline
48 & 0.0353911 & 0.0707823 & 0.964609 \tabularnewline
49 & 0.0321597 & 0.0643193 & 0.96784 \tabularnewline
50 & 0.0519903 & 0.103981 & 0.94801 \tabularnewline
51 & 0.041614 & 0.0832279 & 0.958386 \tabularnewline
52 & 0.0332898 & 0.0665795 & 0.96671 \tabularnewline
53 & 0.0252368 & 0.0504736 & 0.974763 \tabularnewline
54 & 0.0189503 & 0.0379007 & 0.98105 \tabularnewline
55 & 0.0168521 & 0.0337042 & 0.983148 \tabularnewline
56 & 0.0132051 & 0.0264101 & 0.986795 \tabularnewline
57 & 0.0451975 & 0.0903951 & 0.954802 \tabularnewline
58 & 0.0796567 & 0.159313 & 0.920343 \tabularnewline
59 & 0.0670635 & 0.134127 & 0.932937 \tabularnewline
60 & 0.0574232 & 0.114846 & 0.942577 \tabularnewline
61 & 0.0636097 & 0.127219 & 0.93639 \tabularnewline
62 & 0.0601407 & 0.120281 & 0.939859 \tabularnewline
63 & 0.0500752 & 0.10015 & 0.949925 \tabularnewline
64 & 0.0441833 & 0.0883665 & 0.955817 \tabularnewline
65 & 0.0350805 & 0.0701609 & 0.96492 \tabularnewline
66 & 0.0283815 & 0.0567629 & 0.971619 \tabularnewline
67 & 0.0326248 & 0.0652496 & 0.967375 \tabularnewline
68 & 0.0632247 & 0.126449 & 0.936775 \tabularnewline
69 & 0.0613796 & 0.122759 & 0.93862 \tabularnewline
70 & 0.0609061 & 0.121812 & 0.939094 \tabularnewline
71 & 0.0886806 & 0.177361 & 0.911319 \tabularnewline
72 & 0.0753594 & 0.150719 & 0.924641 \tabularnewline
73 & 0.0694311 & 0.138862 & 0.930569 \tabularnewline
74 & 0.0574368 & 0.114874 & 0.942563 \tabularnewline
75 & 0.0566194 & 0.113239 & 0.943381 \tabularnewline
76 & 0.0520792 & 0.104158 & 0.947921 \tabularnewline
77 & 0.0427131 & 0.0854262 & 0.957287 \tabularnewline
78 & 0.0465619 & 0.0931238 & 0.953438 \tabularnewline
79 & 0.0909857 & 0.181971 & 0.909014 \tabularnewline
80 & 0.107924 & 0.215848 & 0.892076 \tabularnewline
81 & 0.0926481 & 0.185296 & 0.907352 \tabularnewline
82 & 0.0863658 & 0.172732 & 0.913634 \tabularnewline
83 & 0.0918058 & 0.183612 & 0.908194 \tabularnewline
84 & 0.0783562 & 0.156712 & 0.921644 \tabularnewline
85 & 0.0731016 & 0.146203 & 0.926898 \tabularnewline
86 & 0.0693009 & 0.138602 & 0.930699 \tabularnewline
87 & 0.0627573 & 0.125515 & 0.937243 \tabularnewline
88 & 0.0619349 & 0.12387 & 0.938065 \tabularnewline
89 & 0.054714 & 0.109428 & 0.945286 \tabularnewline
90 & 0.0612332 & 0.122466 & 0.938767 \tabularnewline
91 & 0.0574473 & 0.114895 & 0.942553 \tabularnewline
92 & 0.0487729 & 0.0975458 & 0.951227 \tabularnewline
93 & 0.0436426 & 0.0872852 & 0.956357 \tabularnewline
94 & 0.0590297 & 0.118059 & 0.94097 \tabularnewline
95 & 0.0492939 & 0.0985878 & 0.950706 \tabularnewline
96 & 0.0415166 & 0.0830332 & 0.958483 \tabularnewline
97 & 0.0346466 & 0.0692933 & 0.965353 \tabularnewline
98 & 0.0369245 & 0.0738491 & 0.963075 \tabularnewline
99 & 0.0421263 & 0.0842526 & 0.957874 \tabularnewline
100 & 0.0345772 & 0.0691543 & 0.965423 \tabularnewline
101 & 0.0298222 & 0.0596444 & 0.970178 \tabularnewline
102 & 0.0241022 & 0.0482044 & 0.975898 \tabularnewline
103 & 0.0214172 & 0.0428343 & 0.978583 \tabularnewline
104 & 0.0472172 & 0.0944344 & 0.952783 \tabularnewline
105 & 0.0443955 & 0.0887911 & 0.955604 \tabularnewline
106 & 0.0383532 & 0.0767063 & 0.961647 \tabularnewline
107 & 0.0364379 & 0.0728758 & 0.963562 \tabularnewline
108 & 0.0409888 & 0.0819775 & 0.959011 \tabularnewline
109 & 0.0839027 & 0.167805 & 0.916097 \tabularnewline
110 & 0.0719077 & 0.143815 & 0.928092 \tabularnewline
111 & 0.0626553 & 0.125311 & 0.937345 \tabularnewline
112 & 0.0578034 & 0.115607 & 0.942197 \tabularnewline
113 & 0.0606806 & 0.121361 & 0.939319 \tabularnewline
114 & 0.0507049 & 0.10141 & 0.949295 \tabularnewline
115 & 0.0594784 & 0.118957 & 0.940522 \tabularnewline
116 & 0.0496046 & 0.0992092 & 0.950395 \tabularnewline
117 & 0.0420046 & 0.0840092 & 0.957995 \tabularnewline
118 & 0.0396692 & 0.0793384 & 0.960331 \tabularnewline
119 & 0.0403903 & 0.0807807 & 0.95961 \tabularnewline
120 & 0.0352301 & 0.0704602 & 0.96477 \tabularnewline
121 & 0.0339414 & 0.0678827 & 0.966059 \tabularnewline
122 & 0.0278734 & 0.0557468 & 0.972127 \tabularnewline
123 & 0.0233538 & 0.0467075 & 0.976646 \tabularnewline
124 & 0.0258207 & 0.0516413 & 0.974179 \tabularnewline
125 & 0.039057 & 0.0781139 & 0.960943 \tabularnewline
126 & 0.0336805 & 0.0673611 & 0.966319 \tabularnewline
127 & 0.0637828 & 0.127566 & 0.936217 \tabularnewline
128 & 0.0602709 & 0.120542 & 0.939729 \tabularnewline
129 & 0.0562199 & 0.11244 & 0.94378 \tabularnewline
130 & 0.0507701 & 0.10154 & 0.94923 \tabularnewline
131 & 0.0843706 & 0.168741 & 0.915629 \tabularnewline
132 & 0.13431 & 0.268619 & 0.86569 \tabularnewline
133 & 0.156437 & 0.312874 & 0.843563 \tabularnewline
134 & 0.139345 & 0.27869 & 0.860655 \tabularnewline
135 & 0.122467 & 0.244934 & 0.877533 \tabularnewline
136 & 0.106272 & 0.212544 & 0.893728 \tabularnewline
137 & 0.100553 & 0.201107 & 0.899447 \tabularnewline
138 & 0.105901 & 0.211802 & 0.894099 \tabularnewline
139 & 0.102718 & 0.205435 & 0.897282 \tabularnewline
140 & 0.090464 & 0.180928 & 0.909536 \tabularnewline
141 & 0.0833378 & 0.166676 & 0.916662 \tabularnewline
142 & 0.0713775 & 0.142755 & 0.928623 \tabularnewline
143 & 0.081199 & 0.162398 & 0.918801 \tabularnewline
144 & 0.0937805 & 0.187561 & 0.906219 \tabularnewline
145 & 0.109595 & 0.21919 & 0.890405 \tabularnewline
146 & 0.0971725 & 0.194345 & 0.902828 \tabularnewline
147 & 0.0862575 & 0.172515 & 0.913742 \tabularnewline
148 & 0.0760903 & 0.152181 & 0.92391 \tabularnewline
149 & 0.0641637 & 0.128327 & 0.935836 \tabularnewline
150 & 0.0655211 & 0.131042 & 0.934479 \tabularnewline
151 & 0.0957551 & 0.19151 & 0.904245 \tabularnewline
152 & 0.0813489 & 0.162698 & 0.918651 \tabularnewline
153 & 0.0846844 & 0.169369 & 0.915316 \tabularnewline
154 & 0.0778826 & 0.155765 & 0.922117 \tabularnewline
155 & 0.0702229 & 0.140446 & 0.929777 \tabularnewline
156 & 0.084423 & 0.168846 & 0.915577 \tabularnewline
157 & 0.0733117 & 0.146623 & 0.926688 \tabularnewline
158 & 0.0670117 & 0.134023 & 0.932988 \tabularnewline
159 & 0.0742231 & 0.148446 & 0.925777 \tabularnewline
160 & 0.0673628 & 0.134726 & 0.932637 \tabularnewline
161 & 0.0592343 & 0.118469 & 0.940766 \tabularnewline
162 & 0.0583214 & 0.116643 & 0.941679 \tabularnewline
163 & 0.0543389 & 0.108678 & 0.945661 \tabularnewline
164 & 0.0706234 & 0.141247 & 0.929377 \tabularnewline
165 & 0.0780077 & 0.156015 & 0.921992 \tabularnewline
166 & 0.0861672 & 0.172334 & 0.913833 \tabularnewline
167 & 0.0725709 & 0.145142 & 0.927429 \tabularnewline
168 & 0.0626772 & 0.125354 & 0.937323 \tabularnewline
169 & 0.0750856 & 0.150171 & 0.924914 \tabularnewline
170 & 0.178326 & 0.356652 & 0.821674 \tabularnewline
171 & 0.162506 & 0.325011 & 0.837494 \tabularnewline
172 & 0.175643 & 0.351287 & 0.824357 \tabularnewline
173 & 0.214871 & 0.429741 & 0.785129 \tabularnewline
174 & 0.240146 & 0.480293 & 0.759854 \tabularnewline
175 & 0.283439 & 0.566879 & 0.716561 \tabularnewline
176 & 0.288911 & 0.577822 & 0.711089 \tabularnewline
177 & 0.298384 & 0.596769 & 0.701616 \tabularnewline
178 & 0.269633 & 0.539267 & 0.730367 \tabularnewline
179 & 0.256658 & 0.513315 & 0.743342 \tabularnewline
180 & 0.228461 & 0.456923 & 0.771539 \tabularnewline
181 & 0.204567 & 0.409133 & 0.795433 \tabularnewline
182 & 0.226671 & 0.453342 & 0.773329 \tabularnewline
183 & 0.313198 & 0.626396 & 0.686802 \tabularnewline
184 & 0.627306 & 0.745387 & 0.372694 \tabularnewline
185 & 0.652846 & 0.694308 & 0.347154 \tabularnewline
186 & 0.677454 & 0.645093 & 0.322546 \tabularnewline
187 & 0.671668 & 0.656664 & 0.328332 \tabularnewline
188 & 0.796927 & 0.406147 & 0.203073 \tabularnewline
189 & 0.768874 & 0.462252 & 0.231126 \tabularnewline
190 & 0.737655 & 0.524689 & 0.262345 \tabularnewline
191 & 0.75316 & 0.49368 & 0.24684 \tabularnewline
192 & 0.737525 & 0.52495 & 0.262475 \tabularnewline
193 & 0.705731 & 0.588537 & 0.294269 \tabularnewline
194 & 0.669346 & 0.661308 & 0.330654 \tabularnewline
195 & 0.641809 & 0.716381 & 0.358191 \tabularnewline
196 & 0.605663 & 0.788673 & 0.394337 \tabularnewline
197 & 0.592657 & 0.814686 & 0.407343 \tabularnewline
198 & 0.553133 & 0.893734 & 0.446867 \tabularnewline
199 & 0.567319 & 0.865363 & 0.432681 \tabularnewline
200 & 0.565708 & 0.868584 & 0.434292 \tabularnewline
201 & 0.593096 & 0.813808 & 0.406904 \tabularnewline
202 & 0.707324 & 0.585352 & 0.292676 \tabularnewline
203 & 0.67423 & 0.651539 & 0.32577 \tabularnewline
204 & 0.641659 & 0.716683 & 0.358341 \tabularnewline
205 & 0.601214 & 0.797571 & 0.398786 \tabularnewline
206 & 0.56139 & 0.877219 & 0.43861 \tabularnewline
207 & 0.521141 & 0.957719 & 0.478859 \tabularnewline
208 & 0.487184 & 0.974368 & 0.512816 \tabularnewline
209 & 0.447826 & 0.895652 & 0.552174 \tabularnewline
210 & 0.423982 & 0.847964 & 0.576018 \tabularnewline
211 & 0.391915 & 0.78383 & 0.608085 \tabularnewline
212 & 0.413523 & 0.827047 & 0.586477 \tabularnewline
213 & 0.381888 & 0.763777 & 0.618112 \tabularnewline
214 & 0.349906 & 0.699813 & 0.650094 \tabularnewline
215 & 0.31332 & 0.626639 & 0.68668 \tabularnewline
216 & 0.279188 & 0.558375 & 0.720812 \tabularnewline
217 & 0.295356 & 0.590713 & 0.704644 \tabularnewline
218 & 0.312102 & 0.624205 & 0.687898 \tabularnewline
219 & 0.271154 & 0.542309 & 0.728846 \tabularnewline
220 & 0.235655 & 0.47131 & 0.764345 \tabularnewline
221 & 0.201396 & 0.402791 & 0.798604 \tabularnewline
222 & 0.180545 & 0.361089 & 0.819455 \tabularnewline
223 & 0.150889 & 0.301777 & 0.849111 \tabularnewline
224 & 0.131148 & 0.262295 & 0.868852 \tabularnewline
225 & 0.10756 & 0.21512 & 0.89244 \tabularnewline
226 & 0.0861517 & 0.172303 & 0.913848 \tabularnewline
227 & 0.06858 & 0.13716 & 0.93142 \tabularnewline
228 & 0.0548162 & 0.109632 & 0.945184 \tabularnewline
229 & 0.043258 & 0.0865159 & 0.956742 \tabularnewline
230 & 0.0378316 & 0.0756632 & 0.962168 \tabularnewline
231 & 0.0667717 & 0.133543 & 0.933228 \tabularnewline
232 & 0.102323 & 0.204647 & 0.897677 \tabularnewline
233 & 0.133084 & 0.266167 & 0.866916 \tabularnewline
234 & 0.173009 & 0.346018 & 0.826991 \tabularnewline
235 & 0.138933 & 0.277866 & 0.861067 \tabularnewline
236 & 0.111329 & 0.222658 & 0.888671 \tabularnewline
237 & 0.102143 & 0.204286 & 0.897857 \tabularnewline
238 & 0.113886 & 0.227772 & 0.886114 \tabularnewline
239 & 0.130286 & 0.260572 & 0.869714 \tabularnewline
240 & 0.257453 & 0.514906 & 0.742547 \tabularnewline
241 & 0.234182 & 0.468364 & 0.765818 \tabularnewline
242 & 0.185855 & 0.37171 & 0.814145 \tabularnewline
243 & 0.172472 & 0.344943 & 0.827528 \tabularnewline
244 & 0.167321 & 0.334641 & 0.832679 \tabularnewline
245 & 0.866465 & 0.26707 & 0.133535 \tabularnewline
246 & 0.9006 & 0.198801 & 0.0994004 \tabularnewline
247 & 0.865475 & 0.26905 & 0.134525 \tabularnewline
248 & 0.868792 & 0.262416 & 0.131208 \tabularnewline
249 & 0.860022 & 0.279957 & 0.139978 \tabularnewline
250 & 0.788927 & 0.422145 & 0.211073 \tabularnewline
251 & 0.735847 & 0.528306 & 0.264153 \tabularnewline
252 & 0.770185 & 0.45963 & 0.229815 \tabularnewline
253 & 0.637936 & 0.724128 & 0.362064 \tabularnewline
254 & 0.738435 & 0.52313 & 0.261565 \tabularnewline
255 & 0.601505 & 0.796989 & 0.398495 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253714&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]9[/C][C]0.650319[/C][C]0.699361[/C][C]0.349681[/C][/ROW]
[ROW][C]10[/C][C]0.492694[/C][C]0.985388[/C][C]0.507306[/C][/ROW]
[ROW][C]11[/C][C]0.350834[/C][C]0.701668[/C][C]0.649166[/C][/ROW]
[ROW][C]12[/C][C]0.235812[/C][C]0.471624[/C][C]0.764188[/C][/ROW]
[ROW][C]13[/C][C]0.17744[/C][C]0.354879[/C][C]0.82256[/C][/ROW]
[ROW][C]14[/C][C]0.121854[/C][C]0.243709[/C][C]0.878146[/C][/ROW]
[ROW][C]15[/C][C]0.170731[/C][C]0.341461[/C][C]0.829269[/C][/ROW]
[ROW][C]16[/C][C]0.154708[/C][C]0.309416[/C][C]0.845292[/C][/ROW]
[ROW][C]17[/C][C]0.158188[/C][C]0.316375[/C][C]0.841812[/C][/ROW]
[ROW][C]18[/C][C]0.115301[/C][C]0.230602[/C][C]0.884699[/C][/ROW]
[ROW][C]19[/C][C]0.159002[/C][C]0.318005[/C][C]0.840998[/C][/ROW]
[ROW][C]20[/C][C]0.112083[/C][C]0.224165[/C][C]0.887917[/C][/ROW]
[ROW][C]21[/C][C]0.0773005[/C][C]0.154601[/C][C]0.9227[/C][/ROW]
[ROW][C]22[/C][C]0.129383[/C][C]0.258766[/C][C]0.870617[/C][/ROW]
[ROW][C]23[/C][C]0.101412[/C][C]0.202824[/C][C]0.898588[/C][/ROW]
[ROW][C]24[/C][C]0.100277[/C][C]0.200555[/C][C]0.899723[/C][/ROW]
[ROW][C]25[/C][C]0.0834468[/C][C]0.166894[/C][C]0.916553[/C][/ROW]
[ROW][C]26[/C][C]0.122512[/C][C]0.245023[/C][C]0.877488[/C][/ROW]
[ROW][C]27[/C][C]0.0925392[/C][C]0.185078[/C][C]0.907461[/C][/ROW]
[ROW][C]28[/C][C]0.0675311[/C][C]0.135062[/C][C]0.932469[/C][/ROW]
[ROW][C]29[/C][C]0.0503073[/C][C]0.100615[/C][C]0.949693[/C][/ROW]
[ROW][C]30[/C][C]0.037767[/C][C]0.0755341[/C][C]0.962233[/C][/ROW]
[ROW][C]31[/C][C]0.0365175[/C][C]0.0730349[/C][C]0.963483[/C][/ROW]
[ROW][C]32[/C][C]0.127795[/C][C]0.25559[/C][C]0.872205[/C][/ROW]
[ROW][C]33[/C][C]0.124393[/C][C]0.248786[/C][C]0.875607[/C][/ROW]
[ROW][C]34[/C][C]0.102185[/C][C]0.204371[/C][C]0.897815[/C][/ROW]
[ROW][C]35[/C][C]0.0800533[/C][C]0.160107[/C][C]0.919947[/C][/ROW]
[ROW][C]36[/C][C]0.0622457[/C][C]0.124491[/C][C]0.937754[/C][/ROW]
[ROW][C]37[/C][C]0.0647613[/C][C]0.129523[/C][C]0.935239[/C][/ROW]
[ROW][C]38[/C][C]0.130874[/C][C]0.261749[/C][C]0.869126[/C][/ROW]
[ROW][C]39[/C][C]0.155208[/C][C]0.310416[/C][C]0.844792[/C][/ROW]
[ROW][C]40[/C][C]0.131808[/C][C]0.263617[/C][C]0.868192[/C][/ROW]
[ROW][C]41[/C][C]0.106987[/C][C]0.213973[/C][C]0.893013[/C][/ROW]
[ROW][C]42[/C][C]0.0870021[/C][C]0.174004[/C][C]0.912998[/C][/ROW]
[ROW][C]43[/C][C]0.06947[/C][C]0.13894[/C][C]0.93053[/C][/ROW]
[ROW][C]44[/C][C]0.0635672[/C][C]0.127134[/C][C]0.936433[/C][/ROW]
[ROW][C]45[/C][C]0.0508043[/C][C]0.101609[/C][C]0.949196[/C][/ROW]
[ROW][C]46[/C][C]0.0394782[/C][C]0.0789564[/C][C]0.960522[/C][/ROW]
[ROW][C]47[/C][C]0.0420369[/C][C]0.0840739[/C][C]0.957963[/C][/ROW]
[ROW][C]48[/C][C]0.0353911[/C][C]0.0707823[/C][C]0.964609[/C][/ROW]
[ROW][C]49[/C][C]0.0321597[/C][C]0.0643193[/C][C]0.96784[/C][/ROW]
[ROW][C]50[/C][C]0.0519903[/C][C]0.103981[/C][C]0.94801[/C][/ROW]
[ROW][C]51[/C][C]0.041614[/C][C]0.0832279[/C][C]0.958386[/C][/ROW]
[ROW][C]52[/C][C]0.0332898[/C][C]0.0665795[/C][C]0.96671[/C][/ROW]
[ROW][C]53[/C][C]0.0252368[/C][C]0.0504736[/C][C]0.974763[/C][/ROW]
[ROW][C]54[/C][C]0.0189503[/C][C]0.0379007[/C][C]0.98105[/C][/ROW]
[ROW][C]55[/C][C]0.0168521[/C][C]0.0337042[/C][C]0.983148[/C][/ROW]
[ROW][C]56[/C][C]0.0132051[/C][C]0.0264101[/C][C]0.986795[/C][/ROW]
[ROW][C]57[/C][C]0.0451975[/C][C]0.0903951[/C][C]0.954802[/C][/ROW]
[ROW][C]58[/C][C]0.0796567[/C][C]0.159313[/C][C]0.920343[/C][/ROW]
[ROW][C]59[/C][C]0.0670635[/C][C]0.134127[/C][C]0.932937[/C][/ROW]
[ROW][C]60[/C][C]0.0574232[/C][C]0.114846[/C][C]0.942577[/C][/ROW]
[ROW][C]61[/C][C]0.0636097[/C][C]0.127219[/C][C]0.93639[/C][/ROW]
[ROW][C]62[/C][C]0.0601407[/C][C]0.120281[/C][C]0.939859[/C][/ROW]
[ROW][C]63[/C][C]0.0500752[/C][C]0.10015[/C][C]0.949925[/C][/ROW]
[ROW][C]64[/C][C]0.0441833[/C][C]0.0883665[/C][C]0.955817[/C][/ROW]
[ROW][C]65[/C][C]0.0350805[/C][C]0.0701609[/C][C]0.96492[/C][/ROW]
[ROW][C]66[/C][C]0.0283815[/C][C]0.0567629[/C][C]0.971619[/C][/ROW]
[ROW][C]67[/C][C]0.0326248[/C][C]0.0652496[/C][C]0.967375[/C][/ROW]
[ROW][C]68[/C][C]0.0632247[/C][C]0.126449[/C][C]0.936775[/C][/ROW]
[ROW][C]69[/C][C]0.0613796[/C][C]0.122759[/C][C]0.93862[/C][/ROW]
[ROW][C]70[/C][C]0.0609061[/C][C]0.121812[/C][C]0.939094[/C][/ROW]
[ROW][C]71[/C][C]0.0886806[/C][C]0.177361[/C][C]0.911319[/C][/ROW]
[ROW][C]72[/C][C]0.0753594[/C][C]0.150719[/C][C]0.924641[/C][/ROW]
[ROW][C]73[/C][C]0.0694311[/C][C]0.138862[/C][C]0.930569[/C][/ROW]
[ROW][C]74[/C][C]0.0574368[/C][C]0.114874[/C][C]0.942563[/C][/ROW]
[ROW][C]75[/C][C]0.0566194[/C][C]0.113239[/C][C]0.943381[/C][/ROW]
[ROW][C]76[/C][C]0.0520792[/C][C]0.104158[/C][C]0.947921[/C][/ROW]
[ROW][C]77[/C][C]0.0427131[/C][C]0.0854262[/C][C]0.957287[/C][/ROW]
[ROW][C]78[/C][C]0.0465619[/C][C]0.0931238[/C][C]0.953438[/C][/ROW]
[ROW][C]79[/C][C]0.0909857[/C][C]0.181971[/C][C]0.909014[/C][/ROW]
[ROW][C]80[/C][C]0.107924[/C][C]0.215848[/C][C]0.892076[/C][/ROW]
[ROW][C]81[/C][C]0.0926481[/C][C]0.185296[/C][C]0.907352[/C][/ROW]
[ROW][C]82[/C][C]0.0863658[/C][C]0.172732[/C][C]0.913634[/C][/ROW]
[ROW][C]83[/C][C]0.0918058[/C][C]0.183612[/C][C]0.908194[/C][/ROW]
[ROW][C]84[/C][C]0.0783562[/C][C]0.156712[/C][C]0.921644[/C][/ROW]
[ROW][C]85[/C][C]0.0731016[/C][C]0.146203[/C][C]0.926898[/C][/ROW]
[ROW][C]86[/C][C]0.0693009[/C][C]0.138602[/C][C]0.930699[/C][/ROW]
[ROW][C]87[/C][C]0.0627573[/C][C]0.125515[/C][C]0.937243[/C][/ROW]
[ROW][C]88[/C][C]0.0619349[/C][C]0.12387[/C][C]0.938065[/C][/ROW]
[ROW][C]89[/C][C]0.054714[/C][C]0.109428[/C][C]0.945286[/C][/ROW]
[ROW][C]90[/C][C]0.0612332[/C][C]0.122466[/C][C]0.938767[/C][/ROW]
[ROW][C]91[/C][C]0.0574473[/C][C]0.114895[/C][C]0.942553[/C][/ROW]
[ROW][C]92[/C][C]0.0487729[/C][C]0.0975458[/C][C]0.951227[/C][/ROW]
[ROW][C]93[/C][C]0.0436426[/C][C]0.0872852[/C][C]0.956357[/C][/ROW]
[ROW][C]94[/C][C]0.0590297[/C][C]0.118059[/C][C]0.94097[/C][/ROW]
[ROW][C]95[/C][C]0.0492939[/C][C]0.0985878[/C][C]0.950706[/C][/ROW]
[ROW][C]96[/C][C]0.0415166[/C][C]0.0830332[/C][C]0.958483[/C][/ROW]
[ROW][C]97[/C][C]0.0346466[/C][C]0.0692933[/C][C]0.965353[/C][/ROW]
[ROW][C]98[/C][C]0.0369245[/C][C]0.0738491[/C][C]0.963075[/C][/ROW]
[ROW][C]99[/C][C]0.0421263[/C][C]0.0842526[/C][C]0.957874[/C][/ROW]
[ROW][C]100[/C][C]0.0345772[/C][C]0.0691543[/C][C]0.965423[/C][/ROW]
[ROW][C]101[/C][C]0.0298222[/C][C]0.0596444[/C][C]0.970178[/C][/ROW]
[ROW][C]102[/C][C]0.0241022[/C][C]0.0482044[/C][C]0.975898[/C][/ROW]
[ROW][C]103[/C][C]0.0214172[/C][C]0.0428343[/C][C]0.978583[/C][/ROW]
[ROW][C]104[/C][C]0.0472172[/C][C]0.0944344[/C][C]0.952783[/C][/ROW]
[ROW][C]105[/C][C]0.0443955[/C][C]0.0887911[/C][C]0.955604[/C][/ROW]
[ROW][C]106[/C][C]0.0383532[/C][C]0.0767063[/C][C]0.961647[/C][/ROW]
[ROW][C]107[/C][C]0.0364379[/C][C]0.0728758[/C][C]0.963562[/C][/ROW]
[ROW][C]108[/C][C]0.0409888[/C][C]0.0819775[/C][C]0.959011[/C][/ROW]
[ROW][C]109[/C][C]0.0839027[/C][C]0.167805[/C][C]0.916097[/C][/ROW]
[ROW][C]110[/C][C]0.0719077[/C][C]0.143815[/C][C]0.928092[/C][/ROW]
[ROW][C]111[/C][C]0.0626553[/C][C]0.125311[/C][C]0.937345[/C][/ROW]
[ROW][C]112[/C][C]0.0578034[/C][C]0.115607[/C][C]0.942197[/C][/ROW]
[ROW][C]113[/C][C]0.0606806[/C][C]0.121361[/C][C]0.939319[/C][/ROW]
[ROW][C]114[/C][C]0.0507049[/C][C]0.10141[/C][C]0.949295[/C][/ROW]
[ROW][C]115[/C][C]0.0594784[/C][C]0.118957[/C][C]0.940522[/C][/ROW]
[ROW][C]116[/C][C]0.0496046[/C][C]0.0992092[/C][C]0.950395[/C][/ROW]
[ROW][C]117[/C][C]0.0420046[/C][C]0.0840092[/C][C]0.957995[/C][/ROW]
[ROW][C]118[/C][C]0.0396692[/C][C]0.0793384[/C][C]0.960331[/C][/ROW]
[ROW][C]119[/C][C]0.0403903[/C][C]0.0807807[/C][C]0.95961[/C][/ROW]
[ROW][C]120[/C][C]0.0352301[/C][C]0.0704602[/C][C]0.96477[/C][/ROW]
[ROW][C]121[/C][C]0.0339414[/C][C]0.0678827[/C][C]0.966059[/C][/ROW]
[ROW][C]122[/C][C]0.0278734[/C][C]0.0557468[/C][C]0.972127[/C][/ROW]
[ROW][C]123[/C][C]0.0233538[/C][C]0.0467075[/C][C]0.976646[/C][/ROW]
[ROW][C]124[/C][C]0.0258207[/C][C]0.0516413[/C][C]0.974179[/C][/ROW]
[ROW][C]125[/C][C]0.039057[/C][C]0.0781139[/C][C]0.960943[/C][/ROW]
[ROW][C]126[/C][C]0.0336805[/C][C]0.0673611[/C][C]0.966319[/C][/ROW]
[ROW][C]127[/C][C]0.0637828[/C][C]0.127566[/C][C]0.936217[/C][/ROW]
[ROW][C]128[/C][C]0.0602709[/C][C]0.120542[/C][C]0.939729[/C][/ROW]
[ROW][C]129[/C][C]0.0562199[/C][C]0.11244[/C][C]0.94378[/C][/ROW]
[ROW][C]130[/C][C]0.0507701[/C][C]0.10154[/C][C]0.94923[/C][/ROW]
[ROW][C]131[/C][C]0.0843706[/C][C]0.168741[/C][C]0.915629[/C][/ROW]
[ROW][C]132[/C][C]0.13431[/C][C]0.268619[/C][C]0.86569[/C][/ROW]
[ROW][C]133[/C][C]0.156437[/C][C]0.312874[/C][C]0.843563[/C][/ROW]
[ROW][C]134[/C][C]0.139345[/C][C]0.27869[/C][C]0.860655[/C][/ROW]
[ROW][C]135[/C][C]0.122467[/C][C]0.244934[/C][C]0.877533[/C][/ROW]
[ROW][C]136[/C][C]0.106272[/C][C]0.212544[/C][C]0.893728[/C][/ROW]
[ROW][C]137[/C][C]0.100553[/C][C]0.201107[/C][C]0.899447[/C][/ROW]
[ROW][C]138[/C][C]0.105901[/C][C]0.211802[/C][C]0.894099[/C][/ROW]
[ROW][C]139[/C][C]0.102718[/C][C]0.205435[/C][C]0.897282[/C][/ROW]
[ROW][C]140[/C][C]0.090464[/C][C]0.180928[/C][C]0.909536[/C][/ROW]
[ROW][C]141[/C][C]0.0833378[/C][C]0.166676[/C][C]0.916662[/C][/ROW]
[ROW][C]142[/C][C]0.0713775[/C][C]0.142755[/C][C]0.928623[/C][/ROW]
[ROW][C]143[/C][C]0.081199[/C][C]0.162398[/C][C]0.918801[/C][/ROW]
[ROW][C]144[/C][C]0.0937805[/C][C]0.187561[/C][C]0.906219[/C][/ROW]
[ROW][C]145[/C][C]0.109595[/C][C]0.21919[/C][C]0.890405[/C][/ROW]
[ROW][C]146[/C][C]0.0971725[/C][C]0.194345[/C][C]0.902828[/C][/ROW]
[ROW][C]147[/C][C]0.0862575[/C][C]0.172515[/C][C]0.913742[/C][/ROW]
[ROW][C]148[/C][C]0.0760903[/C][C]0.152181[/C][C]0.92391[/C][/ROW]
[ROW][C]149[/C][C]0.0641637[/C][C]0.128327[/C][C]0.935836[/C][/ROW]
[ROW][C]150[/C][C]0.0655211[/C][C]0.131042[/C][C]0.934479[/C][/ROW]
[ROW][C]151[/C][C]0.0957551[/C][C]0.19151[/C][C]0.904245[/C][/ROW]
[ROW][C]152[/C][C]0.0813489[/C][C]0.162698[/C][C]0.918651[/C][/ROW]
[ROW][C]153[/C][C]0.0846844[/C][C]0.169369[/C][C]0.915316[/C][/ROW]
[ROW][C]154[/C][C]0.0778826[/C][C]0.155765[/C][C]0.922117[/C][/ROW]
[ROW][C]155[/C][C]0.0702229[/C][C]0.140446[/C][C]0.929777[/C][/ROW]
[ROW][C]156[/C][C]0.084423[/C][C]0.168846[/C][C]0.915577[/C][/ROW]
[ROW][C]157[/C][C]0.0733117[/C][C]0.146623[/C][C]0.926688[/C][/ROW]
[ROW][C]158[/C][C]0.0670117[/C][C]0.134023[/C][C]0.932988[/C][/ROW]
[ROW][C]159[/C][C]0.0742231[/C][C]0.148446[/C][C]0.925777[/C][/ROW]
[ROW][C]160[/C][C]0.0673628[/C][C]0.134726[/C][C]0.932637[/C][/ROW]
[ROW][C]161[/C][C]0.0592343[/C][C]0.118469[/C][C]0.940766[/C][/ROW]
[ROW][C]162[/C][C]0.0583214[/C][C]0.116643[/C][C]0.941679[/C][/ROW]
[ROW][C]163[/C][C]0.0543389[/C][C]0.108678[/C][C]0.945661[/C][/ROW]
[ROW][C]164[/C][C]0.0706234[/C][C]0.141247[/C][C]0.929377[/C][/ROW]
[ROW][C]165[/C][C]0.0780077[/C][C]0.156015[/C][C]0.921992[/C][/ROW]
[ROW][C]166[/C][C]0.0861672[/C][C]0.172334[/C][C]0.913833[/C][/ROW]
[ROW][C]167[/C][C]0.0725709[/C][C]0.145142[/C][C]0.927429[/C][/ROW]
[ROW][C]168[/C][C]0.0626772[/C][C]0.125354[/C][C]0.937323[/C][/ROW]
[ROW][C]169[/C][C]0.0750856[/C][C]0.150171[/C][C]0.924914[/C][/ROW]
[ROW][C]170[/C][C]0.178326[/C][C]0.356652[/C][C]0.821674[/C][/ROW]
[ROW][C]171[/C][C]0.162506[/C][C]0.325011[/C][C]0.837494[/C][/ROW]
[ROW][C]172[/C][C]0.175643[/C][C]0.351287[/C][C]0.824357[/C][/ROW]
[ROW][C]173[/C][C]0.214871[/C][C]0.429741[/C][C]0.785129[/C][/ROW]
[ROW][C]174[/C][C]0.240146[/C][C]0.480293[/C][C]0.759854[/C][/ROW]
[ROW][C]175[/C][C]0.283439[/C][C]0.566879[/C][C]0.716561[/C][/ROW]
[ROW][C]176[/C][C]0.288911[/C][C]0.577822[/C][C]0.711089[/C][/ROW]
[ROW][C]177[/C][C]0.298384[/C][C]0.596769[/C][C]0.701616[/C][/ROW]
[ROW][C]178[/C][C]0.269633[/C][C]0.539267[/C][C]0.730367[/C][/ROW]
[ROW][C]179[/C][C]0.256658[/C][C]0.513315[/C][C]0.743342[/C][/ROW]
[ROW][C]180[/C][C]0.228461[/C][C]0.456923[/C][C]0.771539[/C][/ROW]
[ROW][C]181[/C][C]0.204567[/C][C]0.409133[/C][C]0.795433[/C][/ROW]
[ROW][C]182[/C][C]0.226671[/C][C]0.453342[/C][C]0.773329[/C][/ROW]
[ROW][C]183[/C][C]0.313198[/C][C]0.626396[/C][C]0.686802[/C][/ROW]
[ROW][C]184[/C][C]0.627306[/C][C]0.745387[/C][C]0.372694[/C][/ROW]
[ROW][C]185[/C][C]0.652846[/C][C]0.694308[/C][C]0.347154[/C][/ROW]
[ROW][C]186[/C][C]0.677454[/C][C]0.645093[/C][C]0.322546[/C][/ROW]
[ROW][C]187[/C][C]0.671668[/C][C]0.656664[/C][C]0.328332[/C][/ROW]
[ROW][C]188[/C][C]0.796927[/C][C]0.406147[/C][C]0.203073[/C][/ROW]
[ROW][C]189[/C][C]0.768874[/C][C]0.462252[/C][C]0.231126[/C][/ROW]
[ROW][C]190[/C][C]0.737655[/C][C]0.524689[/C][C]0.262345[/C][/ROW]
[ROW][C]191[/C][C]0.75316[/C][C]0.49368[/C][C]0.24684[/C][/ROW]
[ROW][C]192[/C][C]0.737525[/C][C]0.52495[/C][C]0.262475[/C][/ROW]
[ROW][C]193[/C][C]0.705731[/C][C]0.588537[/C][C]0.294269[/C][/ROW]
[ROW][C]194[/C][C]0.669346[/C][C]0.661308[/C][C]0.330654[/C][/ROW]
[ROW][C]195[/C][C]0.641809[/C][C]0.716381[/C][C]0.358191[/C][/ROW]
[ROW][C]196[/C][C]0.605663[/C][C]0.788673[/C][C]0.394337[/C][/ROW]
[ROW][C]197[/C][C]0.592657[/C][C]0.814686[/C][C]0.407343[/C][/ROW]
[ROW][C]198[/C][C]0.553133[/C][C]0.893734[/C][C]0.446867[/C][/ROW]
[ROW][C]199[/C][C]0.567319[/C][C]0.865363[/C][C]0.432681[/C][/ROW]
[ROW][C]200[/C][C]0.565708[/C][C]0.868584[/C][C]0.434292[/C][/ROW]
[ROW][C]201[/C][C]0.593096[/C][C]0.813808[/C][C]0.406904[/C][/ROW]
[ROW][C]202[/C][C]0.707324[/C][C]0.585352[/C][C]0.292676[/C][/ROW]
[ROW][C]203[/C][C]0.67423[/C][C]0.651539[/C][C]0.32577[/C][/ROW]
[ROW][C]204[/C][C]0.641659[/C][C]0.716683[/C][C]0.358341[/C][/ROW]
[ROW][C]205[/C][C]0.601214[/C][C]0.797571[/C][C]0.398786[/C][/ROW]
[ROW][C]206[/C][C]0.56139[/C][C]0.877219[/C][C]0.43861[/C][/ROW]
[ROW][C]207[/C][C]0.521141[/C][C]0.957719[/C][C]0.478859[/C][/ROW]
[ROW][C]208[/C][C]0.487184[/C][C]0.974368[/C][C]0.512816[/C][/ROW]
[ROW][C]209[/C][C]0.447826[/C][C]0.895652[/C][C]0.552174[/C][/ROW]
[ROW][C]210[/C][C]0.423982[/C][C]0.847964[/C][C]0.576018[/C][/ROW]
[ROW][C]211[/C][C]0.391915[/C][C]0.78383[/C][C]0.608085[/C][/ROW]
[ROW][C]212[/C][C]0.413523[/C][C]0.827047[/C][C]0.586477[/C][/ROW]
[ROW][C]213[/C][C]0.381888[/C][C]0.763777[/C][C]0.618112[/C][/ROW]
[ROW][C]214[/C][C]0.349906[/C][C]0.699813[/C][C]0.650094[/C][/ROW]
[ROW][C]215[/C][C]0.31332[/C][C]0.626639[/C][C]0.68668[/C][/ROW]
[ROW][C]216[/C][C]0.279188[/C][C]0.558375[/C][C]0.720812[/C][/ROW]
[ROW][C]217[/C][C]0.295356[/C][C]0.590713[/C][C]0.704644[/C][/ROW]
[ROW][C]218[/C][C]0.312102[/C][C]0.624205[/C][C]0.687898[/C][/ROW]
[ROW][C]219[/C][C]0.271154[/C][C]0.542309[/C][C]0.728846[/C][/ROW]
[ROW][C]220[/C][C]0.235655[/C][C]0.47131[/C][C]0.764345[/C][/ROW]
[ROW][C]221[/C][C]0.201396[/C][C]0.402791[/C][C]0.798604[/C][/ROW]
[ROW][C]222[/C][C]0.180545[/C][C]0.361089[/C][C]0.819455[/C][/ROW]
[ROW][C]223[/C][C]0.150889[/C][C]0.301777[/C][C]0.849111[/C][/ROW]
[ROW][C]224[/C][C]0.131148[/C][C]0.262295[/C][C]0.868852[/C][/ROW]
[ROW][C]225[/C][C]0.10756[/C][C]0.21512[/C][C]0.89244[/C][/ROW]
[ROW][C]226[/C][C]0.0861517[/C][C]0.172303[/C][C]0.913848[/C][/ROW]
[ROW][C]227[/C][C]0.06858[/C][C]0.13716[/C][C]0.93142[/C][/ROW]
[ROW][C]228[/C][C]0.0548162[/C][C]0.109632[/C][C]0.945184[/C][/ROW]
[ROW][C]229[/C][C]0.043258[/C][C]0.0865159[/C][C]0.956742[/C][/ROW]
[ROW][C]230[/C][C]0.0378316[/C][C]0.0756632[/C][C]0.962168[/C][/ROW]
[ROW][C]231[/C][C]0.0667717[/C][C]0.133543[/C][C]0.933228[/C][/ROW]
[ROW][C]232[/C][C]0.102323[/C][C]0.204647[/C][C]0.897677[/C][/ROW]
[ROW][C]233[/C][C]0.133084[/C][C]0.266167[/C][C]0.866916[/C][/ROW]
[ROW][C]234[/C][C]0.173009[/C][C]0.346018[/C][C]0.826991[/C][/ROW]
[ROW][C]235[/C][C]0.138933[/C][C]0.277866[/C][C]0.861067[/C][/ROW]
[ROW][C]236[/C][C]0.111329[/C][C]0.222658[/C][C]0.888671[/C][/ROW]
[ROW][C]237[/C][C]0.102143[/C][C]0.204286[/C][C]0.897857[/C][/ROW]
[ROW][C]238[/C][C]0.113886[/C][C]0.227772[/C][C]0.886114[/C][/ROW]
[ROW][C]239[/C][C]0.130286[/C][C]0.260572[/C][C]0.869714[/C][/ROW]
[ROW][C]240[/C][C]0.257453[/C][C]0.514906[/C][C]0.742547[/C][/ROW]
[ROW][C]241[/C][C]0.234182[/C][C]0.468364[/C][C]0.765818[/C][/ROW]
[ROW][C]242[/C][C]0.185855[/C][C]0.37171[/C][C]0.814145[/C][/ROW]
[ROW][C]243[/C][C]0.172472[/C][C]0.344943[/C][C]0.827528[/C][/ROW]
[ROW][C]244[/C][C]0.167321[/C][C]0.334641[/C][C]0.832679[/C][/ROW]
[ROW][C]245[/C][C]0.866465[/C][C]0.26707[/C][C]0.133535[/C][/ROW]
[ROW][C]246[/C][C]0.9006[/C][C]0.198801[/C][C]0.0994004[/C][/ROW]
[ROW][C]247[/C][C]0.865475[/C][C]0.26905[/C][C]0.134525[/C][/ROW]
[ROW][C]248[/C][C]0.868792[/C][C]0.262416[/C][C]0.131208[/C][/ROW]
[ROW][C]249[/C][C]0.860022[/C][C]0.279957[/C][C]0.139978[/C][/ROW]
[ROW][C]250[/C][C]0.788927[/C][C]0.422145[/C][C]0.211073[/C][/ROW]
[ROW][C]251[/C][C]0.735847[/C][C]0.528306[/C][C]0.264153[/C][/ROW]
[ROW][C]252[/C][C]0.770185[/C][C]0.45963[/C][C]0.229815[/C][/ROW]
[ROW][C]253[/C][C]0.637936[/C][C]0.724128[/C][C]0.362064[/C][/ROW]
[ROW][C]254[/C][C]0.738435[/C][C]0.52313[/C][C]0.261565[/C][/ROW]
[ROW][C]255[/C][C]0.601505[/C][C]0.796989[/C][C]0.398495[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253714&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253714&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.6503190.6993610.349681
100.4926940.9853880.507306
110.3508340.7016680.649166
120.2358120.4716240.764188
130.177440.3548790.82256
140.1218540.2437090.878146
150.1707310.3414610.829269
160.1547080.3094160.845292
170.1581880.3163750.841812
180.1153010.2306020.884699
190.1590020.3180050.840998
200.1120830.2241650.887917
210.07730050.1546010.9227
220.1293830.2587660.870617
230.1014120.2028240.898588
240.1002770.2005550.899723
250.08344680.1668940.916553
260.1225120.2450230.877488
270.09253920.1850780.907461
280.06753110.1350620.932469
290.05030730.1006150.949693
300.0377670.07553410.962233
310.03651750.07303490.963483
320.1277950.255590.872205
330.1243930.2487860.875607
340.1021850.2043710.897815
350.08005330.1601070.919947
360.06224570.1244910.937754
370.06476130.1295230.935239
380.1308740.2617490.869126
390.1552080.3104160.844792
400.1318080.2636170.868192
410.1069870.2139730.893013
420.08700210.1740040.912998
430.069470.138940.93053
440.06356720.1271340.936433
450.05080430.1016090.949196
460.03947820.07895640.960522
470.04203690.08407390.957963
480.03539110.07078230.964609
490.03215970.06431930.96784
500.05199030.1039810.94801
510.0416140.08322790.958386
520.03328980.06657950.96671
530.02523680.05047360.974763
540.01895030.03790070.98105
550.01685210.03370420.983148
560.01320510.02641010.986795
570.04519750.09039510.954802
580.07965670.1593130.920343
590.06706350.1341270.932937
600.05742320.1148460.942577
610.06360970.1272190.93639
620.06014070.1202810.939859
630.05007520.100150.949925
640.04418330.08836650.955817
650.03508050.07016090.96492
660.02838150.05676290.971619
670.03262480.06524960.967375
680.06322470.1264490.936775
690.06137960.1227590.93862
700.06090610.1218120.939094
710.08868060.1773610.911319
720.07535940.1507190.924641
730.06943110.1388620.930569
740.05743680.1148740.942563
750.05661940.1132390.943381
760.05207920.1041580.947921
770.04271310.08542620.957287
780.04656190.09312380.953438
790.09098570.1819710.909014
800.1079240.2158480.892076
810.09264810.1852960.907352
820.08636580.1727320.913634
830.09180580.1836120.908194
840.07835620.1567120.921644
850.07310160.1462030.926898
860.06930090.1386020.930699
870.06275730.1255150.937243
880.06193490.123870.938065
890.0547140.1094280.945286
900.06123320.1224660.938767
910.05744730.1148950.942553
920.04877290.09754580.951227
930.04364260.08728520.956357
940.05902970.1180590.94097
950.04929390.09858780.950706
960.04151660.08303320.958483
970.03464660.06929330.965353
980.03692450.07384910.963075
990.04212630.08425260.957874
1000.03457720.06915430.965423
1010.02982220.05964440.970178
1020.02410220.04820440.975898
1030.02141720.04283430.978583
1040.04721720.09443440.952783
1050.04439550.08879110.955604
1060.03835320.07670630.961647
1070.03643790.07287580.963562
1080.04098880.08197750.959011
1090.08390270.1678050.916097
1100.07190770.1438150.928092
1110.06265530.1253110.937345
1120.05780340.1156070.942197
1130.06068060.1213610.939319
1140.05070490.101410.949295
1150.05947840.1189570.940522
1160.04960460.09920920.950395
1170.04200460.08400920.957995
1180.03966920.07933840.960331
1190.04039030.08078070.95961
1200.03523010.07046020.96477
1210.03394140.06788270.966059
1220.02787340.05574680.972127
1230.02335380.04670750.976646
1240.02582070.05164130.974179
1250.0390570.07811390.960943
1260.03368050.06736110.966319
1270.06378280.1275660.936217
1280.06027090.1205420.939729
1290.05621990.112440.94378
1300.05077010.101540.94923
1310.08437060.1687410.915629
1320.134310.2686190.86569
1330.1564370.3128740.843563
1340.1393450.278690.860655
1350.1224670.2449340.877533
1360.1062720.2125440.893728
1370.1005530.2011070.899447
1380.1059010.2118020.894099
1390.1027180.2054350.897282
1400.0904640.1809280.909536
1410.08333780.1666760.916662
1420.07137750.1427550.928623
1430.0811990.1623980.918801
1440.09378050.1875610.906219
1450.1095950.219190.890405
1460.09717250.1943450.902828
1470.08625750.1725150.913742
1480.07609030.1521810.92391
1490.06416370.1283270.935836
1500.06552110.1310420.934479
1510.09575510.191510.904245
1520.08134890.1626980.918651
1530.08468440.1693690.915316
1540.07788260.1557650.922117
1550.07022290.1404460.929777
1560.0844230.1688460.915577
1570.07331170.1466230.926688
1580.06701170.1340230.932988
1590.07422310.1484460.925777
1600.06736280.1347260.932637
1610.05923430.1184690.940766
1620.05832140.1166430.941679
1630.05433890.1086780.945661
1640.07062340.1412470.929377
1650.07800770.1560150.921992
1660.08616720.1723340.913833
1670.07257090.1451420.927429
1680.06267720.1253540.937323
1690.07508560.1501710.924914
1700.1783260.3566520.821674
1710.1625060.3250110.837494
1720.1756430.3512870.824357
1730.2148710.4297410.785129
1740.2401460.4802930.759854
1750.2834390.5668790.716561
1760.2889110.5778220.711089
1770.2983840.5967690.701616
1780.2696330.5392670.730367
1790.2566580.5133150.743342
1800.2284610.4569230.771539
1810.2045670.4091330.795433
1820.2266710.4533420.773329
1830.3131980.6263960.686802
1840.6273060.7453870.372694
1850.6528460.6943080.347154
1860.6774540.6450930.322546
1870.6716680.6566640.328332
1880.7969270.4061470.203073
1890.7688740.4622520.231126
1900.7376550.5246890.262345
1910.753160.493680.24684
1920.7375250.524950.262475
1930.7057310.5885370.294269
1940.6693460.6613080.330654
1950.6418090.7163810.358191
1960.6056630.7886730.394337
1970.5926570.8146860.407343
1980.5531330.8937340.446867
1990.5673190.8653630.432681
2000.5657080.8685840.434292
2010.5930960.8138080.406904
2020.7073240.5853520.292676
2030.674230.6515390.32577
2040.6416590.7166830.358341
2050.6012140.7975710.398786
2060.561390.8772190.43861
2070.5211410.9577190.478859
2080.4871840.9743680.512816
2090.4478260.8956520.552174
2100.4239820.8479640.576018
2110.3919150.783830.608085
2120.4135230.8270470.586477
2130.3818880.7637770.618112
2140.3499060.6998130.650094
2150.313320.6266390.68668
2160.2791880.5583750.720812
2170.2953560.5907130.704644
2180.3121020.6242050.687898
2190.2711540.5423090.728846
2200.2356550.471310.764345
2210.2013960.4027910.798604
2220.1805450.3610890.819455
2230.1508890.3017770.849111
2240.1311480.2622950.868852
2250.107560.215120.89244
2260.08615170.1723030.913848
2270.068580.137160.93142
2280.05481620.1096320.945184
2290.0432580.08651590.956742
2300.03783160.07566320.962168
2310.06677170.1335430.933228
2320.1023230.2046470.897677
2330.1330840.2661670.866916
2340.1730090.3460180.826991
2350.1389330.2778660.861067
2360.1113290.2226580.888671
2370.1021430.2042860.897857
2380.1138860.2277720.886114
2390.1302860.2605720.869714
2400.2574530.5149060.742547
2410.2341820.4683640.765818
2420.1858550.371710.814145
2430.1724720.3449430.827528
2440.1673210.3346410.832679
2450.8664650.267070.133535
2460.90060.1988010.0994004
2470.8654750.269050.134525
2480.8687920.2624160.131208
2490.8600220.2799570.139978
2500.7889270.4221450.211073
2510.7358470.5283060.264153
2520.7701850.459630.229815
2530.6379360.7241280.362064
2540.7384350.523130.261565
2550.6015050.7969890.398495






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level60.0242915OK
10% type I error level480.194332NOK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 6 & 0.0242915 & OK \tabularnewline
10% type I error level & 48 & 0.194332 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253714&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]6[/C][C]0.0242915[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]48[/C][C]0.194332[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253714&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253714&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 level00OK
5% type I error level60.0242915OK
10% type I error level480.194332NOK


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 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = First Differences ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = First Differences ;
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')
}