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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 10 Dec 2014 11:15:54 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t14182105656mch69nnop4ko2p.htm/, Retrieved Tue, 28 May 2024 23:17:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264929, Retrieved Tue, 28 May 2024 23:17:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-10 11:15:54] [6398a3f6f1f2f5e55f0ec79c736f94f8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0 149 68 12.9 1.00
1 139 39 12.2 0.89
0 148 32 12.8 0.89
1 158 62 7.4 0.89
1 128 33 6.7 0.89
1 224 52 12.6 0.78
0 159 62 14.8 0.89
1 105 77 13.3 1.00
1 159 76 11.1 0.89
1 167 41 8.2 0.78
1 165 48 11.4 1.00
1 159 63 6.4 0.78
1 119 30 10.6 0.89
0 176 78 12.0 0.89
0 54 19 6.3 0.89
0 91 31 11.3 0.89
1 163 66 11.9 0.89
0 124 35 9.3 0.67
1 137 42 9.6 1.00
0 121 45 10.0 0.78
1 153 21 6.4 0.78
1 148 25 13.8 0.89
0 221 44 10.8 0.78
1 188 69 13.8 0.89
1 149 54 11.7 0.89
1 244 74 10.9 0.33
1 148 80 16.1 1.00
0 92 42 13.4 0.89
1 150 61 9.9 0.89
0 153 41 11.5 0.67
0 94 46 8.3 0.56
0 156 39 11.7 0.89
1 132 34 9.0 0.89
1 161 51 9.7 1.00
1 105 42 10.8 0.78
1 97 31 10.3 0.78
0 151 39 10.4 0.33
1 131 20 12.7 0.78
1 166 49 9.3 0.89
0 157 53 11.8 0.89
1 111 31 5.9 0.78
1 145 39 11.4 0.89
1 162 54 13.0 0.89
1 163 49 10.8 1.00
1 59 34 12.3 0.67
0 187 46 11.3 1.00
1 109 55 11.8 0.89
1 90 42 7.9 0.89
0 105 50 12.7 0.89
1 83 13 12.3 0.78
1 116 37 11.6 0.89
1 42 25 6.7 0.78
1 148 30 10.9 0.78
1 155 28 12.1 1.00
1 125 45 13.3 0.78
1 116 35 10.1 1.00
0 128 28 5.7 0.78
1 138 41 14.3 0.67
0 49 6 8.0 0.33
1 96 45 13.3 1.00
1 164 73 9.3 1.00
0 162 17 12.5 0.78
0 99 40 7.6 0.67
1 202 64 15.9 1.00
0 186 37 9.2 0.89
1 66 25 9.1 0.89
0 183 65 11.1 0.78
1 214 100 13.0 1.00
1 188 28 14.5 0.56
0 104 35 12.2 0.67
0 177 56 12.3 0.89
0 126 29 11.4 0.89
0 76 43 8.8 0.89
1 99 59 14.6 0.89
0 139 50 12.6 0.78
1 78 3 NA 0.89
0 162 59 13.0 1.00
1 108 27 12.6 1.00
0 159 61 13.2 0.89
0 74 28 9.9 0.44
1 110 51 7.7 0.78
0 96 35 10.5 0.89
0 116 29 13.4 0.67
0 87 48 10.9 0.78
1 97 25 4.3 0.78
0 127 44 10.3 0.33
1 106 64 11.8 0.89
1 80 32 11.2 0.89
0 74 20 11.4 0.89
0 91 28 8.6 0.89
0 133 34 13.2 0.56
1 74 31 12.6 0.67
1 114 26 5.6 0.67
1 140 58 9.9 0.78
0 95 23 8.8 0.78
1 98 21 7.7 0.78
0 121 21 9.0 0.89
1 126 33 7.3 1.00
1 98 16 11.4 0.89
1 95 20 13.6 0.89
1 110 37 7.9 0.78
1 70 35 10.7 1.00
0 102 33 10.3 0.78
1 86 27 8.3 0.67
1 130 41 9.6 0.78
1 96 40 14.2 0.89
0 102 35 8.5 0.67
0 100 28 13.5 0.22
0 94 32 4.9 0.44
0 52 22 6.4 0.89
0 98 44 9.6 0.67
0 118 27 11.6 0.89
1 99 17 11.1 0.67
1 48 12 4.35 0.78
1 50 45 12.7 0.78
1 150 37 18.1 0.78
1 154 37 17.85 1.00
0 109 108 16.6 0.78
1 68 10 12.6 0.67
1 194 68 17.1 0.89
0 158 72 19.1 0.89
1 159 143 16.1 1.00
0 67 9 13.35 0.78
0 147 55 18.4 0.67
1 39 17 14.7 0.89
1 100 37 10.6 0.67
1 111 27 12.6 0.67
1 138 37 16.2 1.00
1 101 58 13.6 0.67
1 131 66 18.9 1.00
1 101 21 14.1 0.89
1 114 19 14.5 0.89
0 165 78 16.15 1.00
1 114 35 14.75 0.67
1 111 48 14.8 0.44
1 75 27 12.45 0.89
1 82 43 12.65 0.56
1 121 30 17.35 0.78
1 32 25 8.6 1.00
0 150 69 18.4 1.00
1 117 72 16.1 0.89
1 71 23 11.6 0.67
1 165 13 17.75 0.89
1 154 61 15.25 0.33
1 126 43 17.65 0.89
0 149 51 16.35 0.78
0 145 67 17.65 1.00
1 120 36 13.6 0.44
0 109 44 14.35 0.67
0 132 45 14.75 0.33
1 172 34 18.25 0.89
0 169 36 9.9 0.89
1 114 72 16 1.00
1 156 39 18.25 0.89
0 172 43 16.85 0.89
1 68 25 14.6 1.00
1 89 56 13.85 0.89
1 167 80 18.95 1.00
0 113 40 15.6 0.78
0 115 73 14.85 0.78
0 78 34 11.75 0.67
0 118 72 18.45 0.89
1 87 42 15.9 0.67
0 173 61 17.1 0.78
1 2 23 16.1 0.89
0 162 74 19.9 0.89
1 49 16 10.95 0.78
0 122 66 18.45 1.00
1 96 9 15.1 1.00
0 100 41 15 1.00
0 82 57 11.35 0.67
1 100 48 15.95 0.89
0 115 51 18.1 1.00
1 141 53 14.6 1.00
1 165 29 15.4 0.89
1 165 29 15.4 0.89
1 110 55 17.6 0.89
1 118 54 13.35 0.89
0 158 43 19.1 0.89
1 146 51 15.35 1.00
0 49 20 7.6 0.67
0 90 79 13.4 1.00
0 121 39 13.9 0.89
1 155 61 19.1 0.89
0 104 55 15.25 0.89
1 147 30 12.9 0.89
0 110 55 16.1 1.00
0 108 22 17.35 1.00
0 113 37 13.15 1.00
0 115 2 12.15 0.89
1 61 38 12.6 0.89
1 60 27 10.35 0.89
1 109 56 15.4 0.33
1 68 25 9.6 0.67
0 111 39 18.2 0.56
0 77 33 13.6 0.44
1 73 43 14.85 1.00
0 151 57 14.75 0.89
0 89 43 14.1 0.33
0 78 23 14.9 0.67
0 110 44 16.25 0.67
1 220 54 19.25 1.00
1 65 28 13.6 0.78
0 141 36 13.6 0.67
0 117 39 15.65 1.00
1 122 16 12.75 0.78
0 63 23 14.6 0.89
1 44 40 9.85 0.89
1 52 24 12.65 0.89
0 131 78 19.2 0.00
1 101 57 16.6 0.67
1 42 37 11.2 1.00
1 152 27 15.25 1.00
0 107 61 11.9 0.67
0 77 27 13.2 0.89
0 154 69 16.35 0.89
1 103 34 12.4 0.56
1 96 44 15.85 0.67
1 175 34 18.15 1.00
1 57 39 11.15 1.00
0 112 51 15.65 1.00
0 143 34 17.75 0.67
0 49 31 7.65 0.44
1 110 13 12.35 0.89
1 131 12 15.6 0.44
0 167 51 19.3 0.56
0 56 24 15.2 0.89
0 137 19 17.1 0.67
1 86 30 15.6 0.89
1 121 81 18.4 1.00
0 149 42 19.05 0.78
0 168 22 18.55 0.44
0 140 85 19.1 0.89
1 88 27 13.1 0.89
1 168 25 12.85 0.89
1 94 22 9.5 0.44
1 51 19 4.5 1.00
0 48 14 11.85 0.89
1 145 45 13.6 0.67
1 66 45 11.7 0.33
1 85 28 12.4 0.78
0 109 51 13.35 0.89
0 63 41 11.4 0.78
1 102 31 14.9 0.78
0 162 74 19.9 0.89
1 86 19 11.2 0.78
1 114 51 14.6 0.78
0 164 73 17.6 0.67
1 119 24 14.05 0.89
0 126 61 16.1 0.89
1 132 23 13.35 0.78
1 142 14 11.85 1.00
0 83 54 11.95 1.00
1 94 51 14.75 0.78
0 81 62 15.15 0.78
1 166 36 13.2 0.89
0 110 59 16.85 0.89
1 64 24 7.85 0.67
0 93 26 7.7 1.00
0 104 54 12.6 0.67
1 105 39 7.85 0.56
1 49 16 10.95 0.78
0 88 36 12.35 1.00
1 95 31 9.95 0.67
1 102 31 14.9 0.78
0 99 42 16.65 0.56
1 63 39 13.4 1.00
0 76 25 13.95 0.89
0 109 31 15.7 0.44
1 117 38 16.85 1.00
1 57 31 10.95 0.89
0 120 17 15.35 0.78
1 73 22 12.2 0.89
0 91 55 15.1 0.11
0 108 62 17.75 0.89
1 105 51 15.2 0.89
0 117 30 14.6 1.00
0 119 49 16.65 0.89
1 31 16 8.1 1.00

Tables (Output of Computation)





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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264929&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264929&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264929&T=0

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


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

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






Multiple Linear Regression - Estimated Regression Equation
gender[t] = + 0.460746 + 0.000311645LFM[t] -0.00273085CH[t] -0.0168126TOT[t] + 0.498467Calculation[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
gender[t] =  +  0.460746 +  0.000311645LFM[t] -0.00273085CH[t] -0.0168126TOT[t] +  0.498467Calculation[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264929&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]gender[t] =  +  0.460746 +  0.000311645LFM[t] -0.00273085CH[t] -0.0168126TOT[t] +  0.498467Calculation[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264929&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264929&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
gender[t] = + 0.460746 + 0.000311645LFM[t] -0.00273085CH[t] -0.0168126TOT[t] + 0.498467Calculation[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)0.4607460.1740222.6480.008577220.00428861
LFM0.0003116450.0008313380.37490.7080470.354024
CH-0.002730850.00178144-1.5330.1264480.063224
TOT-0.01681260.00937523-1.7930.0740310.0370155
Calculation0.4984670.1633273.0520.002497650.00124883

\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) & 0.460746 & 0.174022 & 2.648 & 0.00857722 & 0.00428861 \tabularnewline
LFM & 0.000311645 & 0.000831338 & 0.3749 & 0.708047 & 0.354024 \tabularnewline
CH & -0.00273085 & 0.00178144 & -1.533 & 0.126448 & 0.063224 \tabularnewline
TOT & -0.0168126 & 0.00937523 & -1.793 & 0.074031 & 0.0370155 \tabularnewline
Calculation & 0.498467 & 0.163327 & 3.052 & 0.00249765 & 0.00124883 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264929&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]0.460746[/C][C]0.174022[/C][C]2.648[/C][C]0.00857722[/C][C]0.00428861[/C][/ROW]
[ROW][C]LFM[/C][C]0.000311645[/C][C]0.000831338[/C][C]0.3749[/C][C]0.708047[/C][C]0.354024[/C][/ROW]
[ROW][C]CH[/C][C]-0.00273085[/C][C]0.00178144[/C][C]-1.533[/C][C]0.126448[/C][C]0.063224[/C][/ROW]
[ROW][C]TOT[/C][C]-0.0168126[/C][C]0.00937523[/C][C]-1.793[/C][C]0.074031[/C][C]0.0370155[/C][/ROW]
[ROW][C]Calculation[/C][C]0.498467[/C][C]0.163327[/C][C]3.052[/C][C]0.00249765[/C][C]0.00124883[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264929&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264929&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)0.4607460.1740222.6480.008577220.00428861
LFM0.0003116450.0008313380.37490.7080470.354024
CH-0.002730850.00178144-1.5330.1264480.063224
TOT-0.01681260.00937523-1.7930.0740310.0370155
Calculation0.4984670.1633273.0520.002497650.00124883






Multiple Linear Regression - Regression Statistics
Multiple R0.235555
R-squared0.0554862
Adjusted R-squared0.0416472
F-TEST (value)4.0094
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value0.00354087
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.485758
Sum Squared Residuals64.4172

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.235555 \tabularnewline
R-squared & 0.0554862 \tabularnewline
Adjusted R-squared & 0.0416472 \tabularnewline
F-TEST (value) & 4.0094 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 273 \tabularnewline
p-value & 0.00354087 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.485758 \tabularnewline
Sum Squared Residuals & 64.4172 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264929&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.235555[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0554862[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0416472[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]4.0094[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]273[/C][/ROW]
[ROW][C]p-value[/C][C]0.00354087[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.485758[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]64.4172[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264929&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264929&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 R0.235555
R-squared0.0554862
Adjusted R-squared0.0416472
F-TEST (value)4.0094
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value0.00354087
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.485758
Sum Squared Residuals64.4172






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
100.603067-0.603067
210.6360830.363917
300.647916-0.647916
410.6598950.340105
510.7415090.258491
610.5655150.434485
700.535793-0.535793
810.5580520.441948
910.5597680.440232
1010.6517660.348234
1110.6878890.312111
1210.6194570.380543
1310.6813280.318672
1400.544473-0.544473
1500.763405-0.763405
1600.658102-0.658102
1710.5748730.425127
1800.581425-0.581425
1910.7258110.274189
2000.596245-0.596245
2110.7322830.267717
2210.6502190.349781
2300.61669-0.61669
2410.5425280.457472
2510.6066430.393357
2610.3159410.684059
2710.5161850.483815
2800.593068-0.593068
2910.6181010.381899
3000.53709-0.53709
3100.504018-0.504018
3200.649787-0.649787
3310.7013560.298644
3410.7070320.292968
3510.5860010.413999
3610.6219530.378047
3700.390944-0.390944
3810.6222380.377762
3910.6659450.334055
4000.610186-0.610186
4110.7002920.299708
4210.6514030.348597
4310.5888380.411162
4410.6946230.305377
4510.5134610.486539
4600.701888-0.701888
4710.5897650.410235
4810.6849140.315086
4900.587041-0.587041
5010.633120.36688
5110.6444640.355536
5210.6817230.318277
5310.630490.36951
5410.7276210.272379
5510.5420090.457991
5610.7299760.270024
5700.717145-0.717145
5810.485340.51466
5900.489625-0.489625
6010.6426340.357366
6110.6546130.345387
6200.643454-0.643454
6300.588562-0.588562
6410.580070.41993
6500.70663-0.70663
6610.7036840.296316
6700.542456-0.542456
6810.5342560.465744
6910.478230.52177
7000.526436-0.526436
7100.59982-0.59982
7200.67279-0.67279
7300.662689-0.662689
7410.528650.47135
7500.544487-0.544487
7611.63001-0.630015
770-0.2927020.292702
7811.56542-0.565424
7900.460224-0.460224
800-0.38490.3849
8111.66219-0.662187
8200.526386-0.526386
8300.562325-0.562325
840-0.2607860.260786
8511.37149-0.371491
860-0.4357480.435748
8710.6536240.346376
8811.68116-0.681162
8900.711689-0.711689
9000.46656-0.46656
910-0.4787150.478715
9210.6650930.334907
9310.5683460.431654
9411.6684-0.668396
950-0.3067140.306714
9611.73343-0.733429
970-0.214370.21437
9810.6995650.300435
9910.6507190.349281
10010.649970.35003
10110.7055530.294447
10211.61805-0.61805
1030-0.3917580.391758
10410.6166980.383302
10510.5863260.413674
10611.58802-0.588019
10700.298139-0.298139
10800.539597-0.539597
10900.752907-0.752907
11000.543701-0.543701
11100.672396-0.672396
1120-0.4074730.407473
11310.7586040.241396
11410.5287240.471276
11510.4909470.509053
11610.6060590.393941
11711.3095-0.309498
1180-0.4232370.423237
11910.4916470.508353
12011.43588-0.435879
1210-0.6524310.652431
12211.6214-0.621404
12300.380981-0.380981
1240-0.3770350.377035
12510.5466280.453372
12610.5437390.456261
12710.6288140.371186
12810.4391540.560846
12910.5020430.497957
13010.6414520.358548
13110.644240.35576
13211.5261-0.526104
1330-0.513320.51332
13410.3347560.665244
13510.6447050.355295
13610.4353360.564664
13710.5136340.486366
13810.7563250.243675
13911.50818-0.508178
1400-0.5264610.526461
14110.5590090.440991
14210.6218770.378123
14310.2502590.749741
14410.5294790.470521
14511.48183-0.481825
14600.524691-0.524691
1470-0.6094940.609494
14811.46727-0.467269
14900.295503-0.295503
1500-0.4416950.441695
15111.69229-0.692294
1520-0.4708830.470883
15310.5396640.460336
15411.55726-0.557265
1550-0.3333310.333331
15610.5463350.453665
15710.474190.52581
15811.51325-0.513255
15900.43637-0.43637
16000.52863-0.52863
16100.434341-0.434341
1620-0.5601850.560185
16311.44939-0.449387
1640-0.4284880.428488
16511.41821-0.418214
1660-0.3629710.362971
16711.5068-0.506804
1680-0.2893180.289318
16911.62622-0.626223
17000.473792-0.473792
1710-0.4636960.463696
17211.55147-0.55147
1730-0.3870450.387045
17410.6176940.382306
17510.6176940.382306
17610.4925630.507437
17710.5692410.430759
17811.51507-0.515073
1790-0.3926340.392634
18011.6276-0.627596
18100.546234-0.546234
18200.601892-0.601892
1830-0.5350170.535017
18411.5302-0.530203
1850-0.3486150.348615
18611.57261-0.572614
18700.641092-0.641092
18800.672301-0.672301
18900.730485-0.730485
1900-0.392220.39222
19110.6753360.324664
19210.2473670.752633
19310.5862380.413762
19411.36199-0.361987
19500.385298-0.385298
1960-0.3851310.385131
19711.54779-0.547795
19800.298492-0.298492
19900.505709-0.505709
20000.435637-0.435637
2010-0.4433350.443335
20210.5646910.435309
20311.5117-0.511698
20400.626054-0.626054
2050-0.3704840.370484
20611.61574-0.615741
2070-0.3567450.356745
20810.6423670.357633
20910.9657630.0342373
2100-0.6085530.608553
21110.6829590.317041
21210.6764570.323543
21311.46141-0.461413
21400.632718-0.632718
21500.48906-0.48906
2160-0.5293390.529339
21710.4379990.562001
21810.6157520.384248
21910.6830120.316988
22011.59173-0.591726
22100.448011-0.448011
22200.482069-0.482069
2230-0.3044750.304475
22410.425850.57415
22511.32817-0.328175
22600.600741-0.600741
22700.498032-0.498032
2280-0.413020.41302
22910.466370.53363
23011.46101-0.461009
23100.360475-0.360475
23200.394768-0.394768
2330-0.3621720.362172
23410.6724240.327576
23510.4895670.510433
23610.8475640.152436
23711.68188-0.681879
2380-0.5116330.511633
23910.3262130.673787
24010.5910990.408901
24111.57463-0.574629
24200.565555-0.565555
2430-0.4538270.453827
24411.41821-0.418214
2450-0.3638360.363836
24610.500340.49966
24711.35057-0.350574
2480-0.3602910.360291
24911.50638-0.506383
2500-0.3965710.396571
25110.7660050.233995
25211.6367-0.636702
2530-0.5084150.508415
25411.45077-0.450769
2550-0.3641230.364123
25611.49425-0.494249
2570-0.3828560.382856
25811.78774-0.787736
25900.467825-0.467825
2600-0.4658720.465872
26110.6370290.362971
26211.68069-0.680691
2630-0.4276170.427617
26410.5461730.453827
26511.37611-0.376114
2660-0.3529460.352946
26711.62526-0.625259
26800.365426-0.365426
2690-0.391390.39139
27010.653390.34661
27111.58245-0.582449
2720-0.3380610.338061
27311.13987-0.13987
27400.470302-0.470302
2750-0.4577210.457721
27611.66829-0.668285
27700.527725-0.527725
2780-0.2110020.211002
2791NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 0 & 0.603067 & -0.603067 \tabularnewline
2 & 1 & 0.636083 & 0.363917 \tabularnewline
3 & 0 & 0.647916 & -0.647916 \tabularnewline
4 & 1 & 0.659895 & 0.340105 \tabularnewline
5 & 1 & 0.741509 & 0.258491 \tabularnewline
6 & 1 & 0.565515 & 0.434485 \tabularnewline
7 & 0 & 0.535793 & -0.535793 \tabularnewline
8 & 1 & 0.558052 & 0.441948 \tabularnewline
9 & 1 & 0.559768 & 0.440232 \tabularnewline
10 & 1 & 0.651766 & 0.348234 \tabularnewline
11 & 1 & 0.687889 & 0.312111 \tabularnewline
12 & 1 & 0.619457 & 0.380543 \tabularnewline
13 & 1 & 0.681328 & 0.318672 \tabularnewline
14 & 0 & 0.544473 & -0.544473 \tabularnewline
15 & 0 & 0.763405 & -0.763405 \tabularnewline
16 & 0 & 0.658102 & -0.658102 \tabularnewline
17 & 1 & 0.574873 & 0.425127 \tabularnewline
18 & 0 & 0.581425 & -0.581425 \tabularnewline
19 & 1 & 0.725811 & 0.274189 \tabularnewline
20 & 0 & 0.596245 & -0.596245 \tabularnewline
21 & 1 & 0.732283 & 0.267717 \tabularnewline
22 & 1 & 0.650219 & 0.349781 \tabularnewline
23 & 0 & 0.61669 & -0.61669 \tabularnewline
24 & 1 & 0.542528 & 0.457472 \tabularnewline
25 & 1 & 0.606643 & 0.393357 \tabularnewline
26 & 1 & 0.315941 & 0.684059 \tabularnewline
27 & 1 & 0.516185 & 0.483815 \tabularnewline
28 & 0 & 0.593068 & -0.593068 \tabularnewline
29 & 1 & 0.618101 & 0.381899 \tabularnewline
30 & 0 & 0.53709 & -0.53709 \tabularnewline
31 & 0 & 0.504018 & -0.504018 \tabularnewline
32 & 0 & 0.649787 & -0.649787 \tabularnewline
33 & 1 & 0.701356 & 0.298644 \tabularnewline
34 & 1 & 0.707032 & 0.292968 \tabularnewline
35 & 1 & 0.586001 & 0.413999 \tabularnewline
36 & 1 & 0.621953 & 0.378047 \tabularnewline
37 & 0 & 0.390944 & -0.390944 \tabularnewline
38 & 1 & 0.622238 & 0.377762 \tabularnewline
39 & 1 & 0.665945 & 0.334055 \tabularnewline
40 & 0 & 0.610186 & -0.610186 \tabularnewline
41 & 1 & 0.700292 & 0.299708 \tabularnewline
42 & 1 & 0.651403 & 0.348597 \tabularnewline
43 & 1 & 0.588838 & 0.411162 \tabularnewline
44 & 1 & 0.694623 & 0.305377 \tabularnewline
45 & 1 & 0.513461 & 0.486539 \tabularnewline
46 & 0 & 0.701888 & -0.701888 \tabularnewline
47 & 1 & 0.589765 & 0.410235 \tabularnewline
48 & 1 & 0.684914 & 0.315086 \tabularnewline
49 & 0 & 0.587041 & -0.587041 \tabularnewline
50 & 1 & 0.63312 & 0.36688 \tabularnewline
51 & 1 & 0.644464 & 0.355536 \tabularnewline
52 & 1 & 0.681723 & 0.318277 \tabularnewline
53 & 1 & 0.63049 & 0.36951 \tabularnewline
54 & 1 & 0.727621 & 0.272379 \tabularnewline
55 & 1 & 0.542009 & 0.457991 \tabularnewline
56 & 1 & 0.729976 & 0.270024 \tabularnewline
57 & 0 & 0.717145 & -0.717145 \tabularnewline
58 & 1 & 0.48534 & 0.51466 \tabularnewline
59 & 0 & 0.489625 & -0.489625 \tabularnewline
60 & 1 & 0.642634 & 0.357366 \tabularnewline
61 & 1 & 0.654613 & 0.345387 \tabularnewline
62 & 0 & 0.643454 & -0.643454 \tabularnewline
63 & 0 & 0.588562 & -0.588562 \tabularnewline
64 & 1 & 0.58007 & 0.41993 \tabularnewline
65 & 0 & 0.70663 & -0.70663 \tabularnewline
66 & 1 & 0.703684 & 0.296316 \tabularnewline
67 & 0 & 0.542456 & -0.542456 \tabularnewline
68 & 1 & 0.534256 & 0.465744 \tabularnewline
69 & 1 & 0.47823 & 0.52177 \tabularnewline
70 & 0 & 0.526436 & -0.526436 \tabularnewline
71 & 0 & 0.59982 & -0.59982 \tabularnewline
72 & 0 & 0.67279 & -0.67279 \tabularnewline
73 & 0 & 0.662689 & -0.662689 \tabularnewline
74 & 1 & 0.52865 & 0.47135 \tabularnewline
75 & 0 & 0.544487 & -0.544487 \tabularnewline
76 & 1 & 1.63001 & -0.630015 \tabularnewline
77 & 0 & -0.292702 & 0.292702 \tabularnewline
78 & 1 & 1.56542 & -0.565424 \tabularnewline
79 & 0 & 0.460224 & -0.460224 \tabularnewline
80 & 0 & -0.3849 & 0.3849 \tabularnewline
81 & 1 & 1.66219 & -0.662187 \tabularnewline
82 & 0 & 0.526386 & -0.526386 \tabularnewline
83 & 0 & 0.562325 & -0.562325 \tabularnewline
84 & 0 & -0.260786 & 0.260786 \tabularnewline
85 & 1 & 1.37149 & -0.371491 \tabularnewline
86 & 0 & -0.435748 & 0.435748 \tabularnewline
87 & 1 & 0.653624 & 0.346376 \tabularnewline
88 & 1 & 1.68116 & -0.681162 \tabularnewline
89 & 0 & 0.711689 & -0.711689 \tabularnewline
90 & 0 & 0.46656 & -0.46656 \tabularnewline
91 & 0 & -0.478715 & 0.478715 \tabularnewline
92 & 1 & 0.665093 & 0.334907 \tabularnewline
93 & 1 & 0.568346 & 0.431654 \tabularnewline
94 & 1 & 1.6684 & -0.668396 \tabularnewline
95 & 0 & -0.306714 & 0.306714 \tabularnewline
96 & 1 & 1.73343 & -0.733429 \tabularnewline
97 & 0 & -0.21437 & 0.21437 \tabularnewline
98 & 1 & 0.699565 & 0.300435 \tabularnewline
99 & 1 & 0.650719 & 0.349281 \tabularnewline
100 & 1 & 0.64997 & 0.35003 \tabularnewline
101 & 1 & 0.705553 & 0.294447 \tabularnewline
102 & 1 & 1.61805 & -0.61805 \tabularnewline
103 & 0 & -0.391758 & 0.391758 \tabularnewline
104 & 1 & 0.616698 & 0.383302 \tabularnewline
105 & 1 & 0.586326 & 0.413674 \tabularnewline
106 & 1 & 1.58802 & -0.588019 \tabularnewline
107 & 0 & 0.298139 & -0.298139 \tabularnewline
108 & 0 & 0.539597 & -0.539597 \tabularnewline
109 & 0 & 0.752907 & -0.752907 \tabularnewline
110 & 0 & 0.543701 & -0.543701 \tabularnewline
111 & 0 & 0.672396 & -0.672396 \tabularnewline
112 & 0 & -0.407473 & 0.407473 \tabularnewline
113 & 1 & 0.758604 & 0.241396 \tabularnewline
114 & 1 & 0.528724 & 0.471276 \tabularnewline
115 & 1 & 0.490947 & 0.509053 \tabularnewline
116 & 1 & 0.606059 & 0.393941 \tabularnewline
117 & 1 & 1.3095 & -0.309498 \tabularnewline
118 & 0 & -0.423237 & 0.423237 \tabularnewline
119 & 1 & 0.491647 & 0.508353 \tabularnewline
120 & 1 & 1.43588 & -0.435879 \tabularnewline
121 & 0 & -0.652431 & 0.652431 \tabularnewline
122 & 1 & 1.6214 & -0.621404 \tabularnewline
123 & 0 & 0.380981 & -0.380981 \tabularnewline
124 & 0 & -0.377035 & 0.377035 \tabularnewline
125 & 1 & 0.546628 & 0.453372 \tabularnewline
126 & 1 & 0.543739 & 0.456261 \tabularnewline
127 & 1 & 0.628814 & 0.371186 \tabularnewline
128 & 1 & 0.439154 & 0.560846 \tabularnewline
129 & 1 & 0.502043 & 0.497957 \tabularnewline
130 & 1 & 0.641452 & 0.358548 \tabularnewline
131 & 1 & 0.64424 & 0.35576 \tabularnewline
132 & 1 & 1.5261 & -0.526104 \tabularnewline
133 & 0 & -0.51332 & 0.51332 \tabularnewline
134 & 1 & 0.334756 & 0.665244 \tabularnewline
135 & 1 & 0.644705 & 0.355295 \tabularnewline
136 & 1 & 0.435336 & 0.564664 \tabularnewline
137 & 1 & 0.513634 & 0.486366 \tabularnewline
138 & 1 & 0.756325 & 0.243675 \tabularnewline
139 & 1 & 1.50818 & -0.508178 \tabularnewline
140 & 0 & -0.526461 & 0.526461 \tabularnewline
141 & 1 & 0.559009 & 0.440991 \tabularnewline
142 & 1 & 0.621877 & 0.378123 \tabularnewline
143 & 1 & 0.250259 & 0.749741 \tabularnewline
144 & 1 & 0.529479 & 0.470521 \tabularnewline
145 & 1 & 1.48183 & -0.481825 \tabularnewline
146 & 0 & 0.524691 & -0.524691 \tabularnewline
147 & 0 & -0.609494 & 0.609494 \tabularnewline
148 & 1 & 1.46727 & -0.467269 \tabularnewline
149 & 0 & 0.295503 & -0.295503 \tabularnewline
150 & 0 & -0.441695 & 0.441695 \tabularnewline
151 & 1 & 1.69229 & -0.692294 \tabularnewline
152 & 0 & -0.470883 & 0.470883 \tabularnewline
153 & 1 & 0.539664 & 0.460336 \tabularnewline
154 & 1 & 1.55726 & -0.557265 \tabularnewline
155 & 0 & -0.333331 & 0.333331 \tabularnewline
156 & 1 & 0.546335 & 0.453665 \tabularnewline
157 & 1 & 0.47419 & 0.52581 \tabularnewline
158 & 1 & 1.51325 & -0.513255 \tabularnewline
159 & 0 & 0.43637 & -0.43637 \tabularnewline
160 & 0 & 0.52863 & -0.52863 \tabularnewline
161 & 0 & 0.434341 & -0.434341 \tabularnewline
162 & 0 & -0.560185 & 0.560185 \tabularnewline
163 & 1 & 1.44939 & -0.449387 \tabularnewline
164 & 0 & -0.428488 & 0.428488 \tabularnewline
165 & 1 & 1.41821 & -0.418214 \tabularnewline
166 & 0 & -0.362971 & 0.362971 \tabularnewline
167 & 1 & 1.5068 & -0.506804 \tabularnewline
168 & 0 & -0.289318 & 0.289318 \tabularnewline
169 & 1 & 1.62622 & -0.626223 \tabularnewline
170 & 0 & 0.473792 & -0.473792 \tabularnewline
171 & 0 & -0.463696 & 0.463696 \tabularnewline
172 & 1 & 1.55147 & -0.55147 \tabularnewline
173 & 0 & -0.387045 & 0.387045 \tabularnewline
174 & 1 & 0.617694 & 0.382306 \tabularnewline
175 & 1 & 0.617694 & 0.382306 \tabularnewline
176 & 1 & 0.492563 & 0.507437 \tabularnewline
177 & 1 & 0.569241 & 0.430759 \tabularnewline
178 & 1 & 1.51507 & -0.515073 \tabularnewline
179 & 0 & -0.392634 & 0.392634 \tabularnewline
180 & 1 & 1.6276 & -0.627596 \tabularnewline
181 & 0 & 0.546234 & -0.546234 \tabularnewline
182 & 0 & 0.601892 & -0.601892 \tabularnewline
183 & 0 & -0.535017 & 0.535017 \tabularnewline
184 & 1 & 1.5302 & -0.530203 \tabularnewline
185 & 0 & -0.348615 & 0.348615 \tabularnewline
186 & 1 & 1.57261 & -0.572614 \tabularnewline
187 & 0 & 0.641092 & -0.641092 \tabularnewline
188 & 0 & 0.672301 & -0.672301 \tabularnewline
189 & 0 & 0.730485 & -0.730485 \tabularnewline
190 & 0 & -0.39222 & 0.39222 \tabularnewline
191 & 1 & 0.675336 & 0.324664 \tabularnewline
192 & 1 & 0.247367 & 0.752633 \tabularnewline
193 & 1 & 0.586238 & 0.413762 \tabularnewline
194 & 1 & 1.36199 & -0.361987 \tabularnewline
195 & 0 & 0.385298 & -0.385298 \tabularnewline
196 & 0 & -0.385131 & 0.385131 \tabularnewline
197 & 1 & 1.54779 & -0.547795 \tabularnewline
198 & 0 & 0.298492 & -0.298492 \tabularnewline
199 & 0 & 0.505709 & -0.505709 \tabularnewline
200 & 0 & 0.435637 & -0.435637 \tabularnewline
201 & 0 & -0.443335 & 0.443335 \tabularnewline
202 & 1 & 0.564691 & 0.435309 \tabularnewline
203 & 1 & 1.5117 & -0.511698 \tabularnewline
204 & 0 & 0.626054 & -0.626054 \tabularnewline
205 & 0 & -0.370484 & 0.370484 \tabularnewline
206 & 1 & 1.61574 & -0.615741 \tabularnewline
207 & 0 & -0.356745 & 0.356745 \tabularnewline
208 & 1 & 0.642367 & 0.357633 \tabularnewline
209 & 1 & 0.965763 & 0.0342373 \tabularnewline
210 & 0 & -0.608553 & 0.608553 \tabularnewline
211 & 1 & 0.682959 & 0.317041 \tabularnewline
212 & 1 & 0.676457 & 0.323543 \tabularnewline
213 & 1 & 1.46141 & -0.461413 \tabularnewline
214 & 0 & 0.632718 & -0.632718 \tabularnewline
215 & 0 & 0.48906 & -0.48906 \tabularnewline
216 & 0 & -0.529339 & 0.529339 \tabularnewline
217 & 1 & 0.437999 & 0.562001 \tabularnewline
218 & 1 & 0.615752 & 0.384248 \tabularnewline
219 & 1 & 0.683012 & 0.316988 \tabularnewline
220 & 1 & 1.59173 & -0.591726 \tabularnewline
221 & 0 & 0.448011 & -0.448011 \tabularnewline
222 & 0 & 0.482069 & -0.482069 \tabularnewline
223 & 0 & -0.304475 & 0.304475 \tabularnewline
224 & 1 & 0.42585 & 0.57415 \tabularnewline
225 & 1 & 1.32817 & -0.328175 \tabularnewline
226 & 0 & 0.600741 & -0.600741 \tabularnewline
227 & 0 & 0.498032 & -0.498032 \tabularnewline
228 & 0 & -0.41302 & 0.41302 \tabularnewline
229 & 1 & 0.46637 & 0.53363 \tabularnewline
230 & 1 & 1.46101 & -0.461009 \tabularnewline
231 & 0 & 0.360475 & -0.360475 \tabularnewline
232 & 0 & 0.394768 & -0.394768 \tabularnewline
233 & 0 & -0.362172 & 0.362172 \tabularnewline
234 & 1 & 0.672424 & 0.327576 \tabularnewline
235 & 1 & 0.489567 & 0.510433 \tabularnewline
236 & 1 & 0.847564 & 0.152436 \tabularnewline
237 & 1 & 1.68188 & -0.681879 \tabularnewline
238 & 0 & -0.511633 & 0.511633 \tabularnewline
239 & 1 & 0.326213 & 0.673787 \tabularnewline
240 & 1 & 0.591099 & 0.408901 \tabularnewline
241 & 1 & 1.57463 & -0.574629 \tabularnewline
242 & 0 & 0.565555 & -0.565555 \tabularnewline
243 & 0 & -0.453827 & 0.453827 \tabularnewline
244 & 1 & 1.41821 & -0.418214 \tabularnewline
245 & 0 & -0.363836 & 0.363836 \tabularnewline
246 & 1 & 0.50034 & 0.49966 \tabularnewline
247 & 1 & 1.35057 & -0.350574 \tabularnewline
248 & 0 & -0.360291 & 0.360291 \tabularnewline
249 & 1 & 1.50638 & -0.506383 \tabularnewline
250 & 0 & -0.396571 & 0.396571 \tabularnewline
251 & 1 & 0.766005 & 0.233995 \tabularnewline
252 & 1 & 1.6367 & -0.636702 \tabularnewline
253 & 0 & -0.508415 & 0.508415 \tabularnewline
254 & 1 & 1.45077 & -0.450769 \tabularnewline
255 & 0 & -0.364123 & 0.364123 \tabularnewline
256 & 1 & 1.49425 & -0.494249 \tabularnewline
257 & 0 & -0.382856 & 0.382856 \tabularnewline
258 & 1 & 1.78774 & -0.787736 \tabularnewline
259 & 0 & 0.467825 & -0.467825 \tabularnewline
260 & 0 & -0.465872 & 0.465872 \tabularnewline
261 & 1 & 0.637029 & 0.362971 \tabularnewline
262 & 1 & 1.68069 & -0.680691 \tabularnewline
263 & 0 & -0.427617 & 0.427617 \tabularnewline
264 & 1 & 0.546173 & 0.453827 \tabularnewline
265 & 1 & 1.37611 & -0.376114 \tabularnewline
266 & 0 & -0.352946 & 0.352946 \tabularnewline
267 & 1 & 1.62526 & -0.625259 \tabularnewline
268 & 0 & 0.365426 & -0.365426 \tabularnewline
269 & 0 & -0.39139 & 0.39139 \tabularnewline
270 & 1 & 0.65339 & 0.34661 \tabularnewline
271 & 1 & 1.58245 & -0.582449 \tabularnewline
272 & 0 & -0.338061 & 0.338061 \tabularnewline
273 & 1 & 1.13987 & -0.13987 \tabularnewline
274 & 0 & 0.470302 & -0.470302 \tabularnewline
275 & 0 & -0.457721 & 0.457721 \tabularnewline
276 & 1 & 1.66829 & -0.668285 \tabularnewline
277 & 0 & 0.527725 & -0.527725 \tabularnewline
278 & 0 & -0.211002 & 0.211002 \tabularnewline
279 & 1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264929&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]0[/C][C]0.603067[/C][C]-0.603067[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]0.636083[/C][C]0.363917[/C][/ROW]
[ROW][C]3[/C][C]0[/C][C]0.647916[/C][C]-0.647916[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]0.659895[/C][C]0.340105[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.741509[/C][C]0.258491[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.565515[/C][C]0.434485[/C][/ROW]
[ROW][C]7[/C][C]0[/C][C]0.535793[/C][C]-0.535793[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.558052[/C][C]0.441948[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.559768[/C][C]0.440232[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.651766[/C][C]0.348234[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]0.687889[/C][C]0.312111[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.619457[/C][C]0.380543[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.681328[/C][C]0.318672[/C][/ROW]
[ROW][C]14[/C][C]0[/C][C]0.544473[/C][C]-0.544473[/C][/ROW]
[ROW][C]15[/C][C]0[/C][C]0.763405[/C][C]-0.763405[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0.658102[/C][C]-0.658102[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.574873[/C][C]0.425127[/C][/ROW]
[ROW][C]18[/C][C]0[/C][C]0.581425[/C][C]-0.581425[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]0.725811[/C][C]0.274189[/C][/ROW]
[ROW][C]20[/C][C]0[/C][C]0.596245[/C][C]-0.596245[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]0.732283[/C][C]0.267717[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.650219[/C][C]0.349781[/C][/ROW]
[ROW][C]23[/C][C]0[/C][C]0.61669[/C][C]-0.61669[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.542528[/C][C]0.457472[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.606643[/C][C]0.393357[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.315941[/C][C]0.684059[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.516185[/C][C]0.483815[/C][/ROW]
[ROW][C]28[/C][C]0[/C][C]0.593068[/C][C]-0.593068[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.618101[/C][C]0.381899[/C][/ROW]
[ROW][C]30[/C][C]0[/C][C]0.53709[/C][C]-0.53709[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0.504018[/C][C]-0.504018[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0.649787[/C][C]-0.649787[/C][/ROW]
[ROW][C]33[/C][C]1[/C][C]0.701356[/C][C]0.298644[/C][/ROW]
[ROW][C]34[/C][C]1[/C][C]0.707032[/C][C]0.292968[/C][/ROW]
[ROW][C]35[/C][C]1[/C][C]0.586001[/C][C]0.413999[/C][/ROW]
[ROW][C]36[/C][C]1[/C][C]0.621953[/C][C]0.378047[/C][/ROW]
[ROW][C]37[/C][C]0[/C][C]0.390944[/C][C]-0.390944[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.622238[/C][C]0.377762[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.665945[/C][C]0.334055[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]0.610186[/C][C]-0.610186[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.700292[/C][C]0.299708[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.651403[/C][C]0.348597[/C][/ROW]
[ROW][C]43[/C][C]1[/C][C]0.588838[/C][C]0.411162[/C][/ROW]
[ROW][C]44[/C][C]1[/C][C]0.694623[/C][C]0.305377[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]0.513461[/C][C]0.486539[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0.701888[/C][C]-0.701888[/C][/ROW]
[ROW][C]47[/C][C]1[/C][C]0.589765[/C][C]0.410235[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]0.684914[/C][C]0.315086[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0.587041[/C][C]-0.587041[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]0.63312[/C][C]0.36688[/C][/ROW]
[ROW][C]51[/C][C]1[/C][C]0.644464[/C][C]0.355536[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]0.681723[/C][C]0.318277[/C][/ROW]
[ROW][C]53[/C][C]1[/C][C]0.63049[/C][C]0.36951[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]0.727621[/C][C]0.272379[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.542009[/C][C]0.457991[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.729976[/C][C]0.270024[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]0.717145[/C][C]-0.717145[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.48534[/C][C]0.51466[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]0.489625[/C][C]-0.489625[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.642634[/C][C]0.357366[/C][/ROW]
[ROW][C]61[/C][C]1[/C][C]0.654613[/C][C]0.345387[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.643454[/C][C]-0.643454[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0.588562[/C][C]-0.588562[/C][/ROW]
[ROW][C]64[/C][C]1[/C][C]0.58007[/C][C]0.41993[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0.70663[/C][C]-0.70663[/C][/ROW]
[ROW][C]66[/C][C]1[/C][C]0.703684[/C][C]0.296316[/C][/ROW]
[ROW][C]67[/C][C]0[/C][C]0.542456[/C][C]-0.542456[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.534256[/C][C]0.465744[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.47823[/C][C]0.52177[/C][/ROW]
[ROW][C]70[/C][C]0[/C][C]0.526436[/C][C]-0.526436[/C][/ROW]
[ROW][C]71[/C][C]0[/C][C]0.59982[/C][C]-0.59982[/C][/ROW]
[ROW][C]72[/C][C]0[/C][C]0.67279[/C][C]-0.67279[/C][/ROW]
[ROW][C]73[/C][C]0[/C][C]0.662689[/C][C]-0.662689[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.52865[/C][C]0.47135[/C][/ROW]
[ROW][C]75[/C][C]0[/C][C]0.544487[/C][C]-0.544487[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]1.63001[/C][C]-0.630015[/C][/ROW]
[ROW][C]77[/C][C]0[/C][C]-0.292702[/C][C]0.292702[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]1.56542[/C][C]-0.565424[/C][/ROW]
[ROW][C]79[/C][C]0[/C][C]0.460224[/C][C]-0.460224[/C][/ROW]
[ROW][C]80[/C][C]0[/C][C]-0.3849[/C][C]0.3849[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]1.66219[/C][C]-0.662187[/C][/ROW]
[ROW][C]82[/C][C]0[/C][C]0.526386[/C][C]-0.526386[/C][/ROW]
[ROW][C]83[/C][C]0[/C][C]0.562325[/C][C]-0.562325[/C][/ROW]
[ROW][C]84[/C][C]0[/C][C]-0.260786[/C][C]0.260786[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]1.37149[/C][C]-0.371491[/C][/ROW]
[ROW][C]86[/C][C]0[/C][C]-0.435748[/C][C]0.435748[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.653624[/C][C]0.346376[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]1.68116[/C][C]-0.681162[/C][/ROW]
[ROW][C]89[/C][C]0[/C][C]0.711689[/C][C]-0.711689[/C][/ROW]
[ROW][C]90[/C][C]0[/C][C]0.46656[/C][C]-0.46656[/C][/ROW]
[ROW][C]91[/C][C]0[/C][C]-0.478715[/C][C]0.478715[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.665093[/C][C]0.334907[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.568346[/C][C]0.431654[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]1.6684[/C][C]-0.668396[/C][/ROW]
[ROW][C]95[/C][C]0[/C][C]-0.306714[/C][C]0.306714[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]1.73343[/C][C]-0.733429[/C][/ROW]
[ROW][C]97[/C][C]0[/C][C]-0.21437[/C][C]0.21437[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]0.699565[/C][C]0.300435[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.650719[/C][C]0.349281[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]0.64997[/C][C]0.35003[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]0.705553[/C][C]0.294447[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]1.61805[/C][C]-0.61805[/C][/ROW]
[ROW][C]103[/C][C]0[/C][C]-0.391758[/C][C]0.391758[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.616698[/C][C]0.383302[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.586326[/C][C]0.413674[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]1.58802[/C][C]-0.588019[/C][/ROW]
[ROW][C]107[/C][C]0[/C][C]0.298139[/C][C]-0.298139[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]0.539597[/C][C]-0.539597[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]0.752907[/C][C]-0.752907[/C][/ROW]
[ROW][C]110[/C][C]0[/C][C]0.543701[/C][C]-0.543701[/C][/ROW]
[ROW][C]111[/C][C]0[/C][C]0.672396[/C][C]-0.672396[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]-0.407473[/C][C]0.407473[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.758604[/C][C]0.241396[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.528724[/C][C]0.471276[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.490947[/C][C]0.509053[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.606059[/C][C]0.393941[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]1.3095[/C][C]-0.309498[/C][/ROW]
[ROW][C]118[/C][C]0[/C][C]-0.423237[/C][C]0.423237[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.491647[/C][C]0.508353[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]1.43588[/C][C]-0.435879[/C][/ROW]
[ROW][C]121[/C][C]0[/C][C]-0.652431[/C][C]0.652431[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]1.6214[/C][C]-0.621404[/C][/ROW]
[ROW][C]123[/C][C]0[/C][C]0.380981[/C][C]-0.380981[/C][/ROW]
[ROW][C]124[/C][C]0[/C][C]-0.377035[/C][C]0.377035[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.546628[/C][C]0.453372[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.543739[/C][C]0.456261[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.628814[/C][C]0.371186[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.439154[/C][C]0.560846[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.502043[/C][C]0.497957[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.641452[/C][C]0.358548[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.64424[/C][C]0.35576[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]1.5261[/C][C]-0.526104[/C][/ROW]
[ROW][C]133[/C][C]0[/C][C]-0.51332[/C][C]0.51332[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.334756[/C][C]0.665244[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]0.644705[/C][C]0.355295[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.435336[/C][C]0.564664[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]0.513634[/C][C]0.486366[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]0.756325[/C][C]0.243675[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]1.50818[/C][C]-0.508178[/C][/ROW]
[ROW][C]140[/C][C]0[/C][C]-0.526461[/C][C]0.526461[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.559009[/C][C]0.440991[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.621877[/C][C]0.378123[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.250259[/C][C]0.749741[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.529479[/C][C]0.470521[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]1.48183[/C][C]-0.481825[/C][/ROW]
[ROW][C]146[/C][C]0[/C][C]0.524691[/C][C]-0.524691[/C][/ROW]
[ROW][C]147[/C][C]0[/C][C]-0.609494[/C][C]0.609494[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]1.46727[/C][C]-0.467269[/C][/ROW]
[ROW][C]149[/C][C]0[/C][C]0.295503[/C][C]-0.295503[/C][/ROW]
[ROW][C]150[/C][C]0[/C][C]-0.441695[/C][C]0.441695[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]1.69229[/C][C]-0.692294[/C][/ROW]
[ROW][C]152[/C][C]0[/C][C]-0.470883[/C][C]0.470883[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]0.539664[/C][C]0.460336[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]1.55726[/C][C]-0.557265[/C][/ROW]
[ROW][C]155[/C][C]0[/C][C]-0.333331[/C][C]0.333331[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.546335[/C][C]0.453665[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.47419[/C][C]0.52581[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]1.51325[/C][C]-0.513255[/C][/ROW]
[ROW][C]159[/C][C]0[/C][C]0.43637[/C][C]-0.43637[/C][/ROW]
[ROW][C]160[/C][C]0[/C][C]0.52863[/C][C]-0.52863[/C][/ROW]
[ROW][C]161[/C][C]0[/C][C]0.434341[/C][C]-0.434341[/C][/ROW]
[ROW][C]162[/C][C]0[/C][C]-0.560185[/C][C]0.560185[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]1.44939[/C][C]-0.449387[/C][/ROW]
[ROW][C]164[/C][C]0[/C][C]-0.428488[/C][C]0.428488[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]1.41821[/C][C]-0.418214[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]-0.362971[/C][C]0.362971[/C][/ROW]
[ROW][C]167[/C][C]1[/C][C]1.5068[/C][C]-0.506804[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]-0.289318[/C][C]0.289318[/C][/ROW]
[ROW][C]169[/C][C]1[/C][C]1.62622[/C][C]-0.626223[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.473792[/C][C]-0.473792[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]-0.463696[/C][C]0.463696[/C][/ROW]
[ROW][C]172[/C][C]1[/C][C]1.55147[/C][C]-0.55147[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]-0.387045[/C][C]0.387045[/C][/ROW]
[ROW][C]174[/C][C]1[/C][C]0.617694[/C][C]0.382306[/C][/ROW]
[ROW][C]175[/C][C]1[/C][C]0.617694[/C][C]0.382306[/C][/ROW]
[ROW][C]176[/C][C]1[/C][C]0.492563[/C][C]0.507437[/C][/ROW]
[ROW][C]177[/C][C]1[/C][C]0.569241[/C][C]0.430759[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]1.51507[/C][C]-0.515073[/C][/ROW]
[ROW][C]179[/C][C]0[/C][C]-0.392634[/C][C]0.392634[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]1.6276[/C][C]-0.627596[/C][/ROW]
[ROW][C]181[/C][C]0[/C][C]0.546234[/C][C]-0.546234[/C][/ROW]
[ROW][C]182[/C][C]0[/C][C]0.601892[/C][C]-0.601892[/C][/ROW]
[ROW][C]183[/C][C]0[/C][C]-0.535017[/C][C]0.535017[/C][/ROW]
[ROW][C]184[/C][C]1[/C][C]1.5302[/C][C]-0.530203[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]-0.348615[/C][C]0.348615[/C][/ROW]
[ROW][C]186[/C][C]1[/C][C]1.57261[/C][C]-0.572614[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.641092[/C][C]-0.641092[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.672301[/C][C]-0.672301[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.730485[/C][C]-0.730485[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]-0.39222[/C][C]0.39222[/C][/ROW]
[ROW][C]191[/C][C]1[/C][C]0.675336[/C][C]0.324664[/C][/ROW]
[ROW][C]192[/C][C]1[/C][C]0.247367[/C][C]0.752633[/C][/ROW]
[ROW][C]193[/C][C]1[/C][C]0.586238[/C][C]0.413762[/C][/ROW]
[ROW][C]194[/C][C]1[/C][C]1.36199[/C][C]-0.361987[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.385298[/C][C]-0.385298[/C][/ROW]
[ROW][C]196[/C][C]0[/C][C]-0.385131[/C][C]0.385131[/C][/ROW]
[ROW][C]197[/C][C]1[/C][C]1.54779[/C][C]-0.547795[/C][/ROW]
[ROW][C]198[/C][C]0[/C][C]0.298492[/C][C]-0.298492[/C][/ROW]
[ROW][C]199[/C][C]0[/C][C]0.505709[/C][C]-0.505709[/C][/ROW]
[ROW][C]200[/C][C]0[/C][C]0.435637[/C][C]-0.435637[/C][/ROW]
[ROW][C]201[/C][C]0[/C][C]-0.443335[/C][C]0.443335[/C][/ROW]
[ROW][C]202[/C][C]1[/C][C]0.564691[/C][C]0.435309[/C][/ROW]
[ROW][C]203[/C][C]1[/C][C]1.5117[/C][C]-0.511698[/C][/ROW]
[ROW][C]204[/C][C]0[/C][C]0.626054[/C][C]-0.626054[/C][/ROW]
[ROW][C]205[/C][C]0[/C][C]-0.370484[/C][C]0.370484[/C][/ROW]
[ROW][C]206[/C][C]1[/C][C]1.61574[/C][C]-0.615741[/C][/ROW]
[ROW][C]207[/C][C]0[/C][C]-0.356745[/C][C]0.356745[/C][/ROW]
[ROW][C]208[/C][C]1[/C][C]0.642367[/C][C]0.357633[/C][/ROW]
[ROW][C]209[/C][C]1[/C][C]0.965763[/C][C]0.0342373[/C][/ROW]
[ROW][C]210[/C][C]0[/C][C]-0.608553[/C][C]0.608553[/C][/ROW]
[ROW][C]211[/C][C]1[/C][C]0.682959[/C][C]0.317041[/C][/ROW]
[ROW][C]212[/C][C]1[/C][C]0.676457[/C][C]0.323543[/C][/ROW]
[ROW][C]213[/C][C]1[/C][C]1.46141[/C][C]-0.461413[/C][/ROW]
[ROW][C]214[/C][C]0[/C][C]0.632718[/C][C]-0.632718[/C][/ROW]
[ROW][C]215[/C][C]0[/C][C]0.48906[/C][C]-0.48906[/C][/ROW]
[ROW][C]216[/C][C]0[/C][C]-0.529339[/C][C]0.529339[/C][/ROW]
[ROW][C]217[/C][C]1[/C][C]0.437999[/C][C]0.562001[/C][/ROW]
[ROW][C]218[/C][C]1[/C][C]0.615752[/C][C]0.384248[/C][/ROW]
[ROW][C]219[/C][C]1[/C][C]0.683012[/C][C]0.316988[/C][/ROW]
[ROW][C]220[/C][C]1[/C][C]1.59173[/C][C]-0.591726[/C][/ROW]
[ROW][C]221[/C][C]0[/C][C]0.448011[/C][C]-0.448011[/C][/ROW]
[ROW][C]222[/C][C]0[/C][C]0.482069[/C][C]-0.482069[/C][/ROW]
[ROW][C]223[/C][C]0[/C][C]-0.304475[/C][C]0.304475[/C][/ROW]
[ROW][C]224[/C][C]1[/C][C]0.42585[/C][C]0.57415[/C][/ROW]
[ROW][C]225[/C][C]1[/C][C]1.32817[/C][C]-0.328175[/C][/ROW]
[ROW][C]226[/C][C]0[/C][C]0.600741[/C][C]-0.600741[/C][/ROW]
[ROW][C]227[/C][C]0[/C][C]0.498032[/C][C]-0.498032[/C][/ROW]
[ROW][C]228[/C][C]0[/C][C]-0.41302[/C][C]0.41302[/C][/ROW]
[ROW][C]229[/C][C]1[/C][C]0.46637[/C][C]0.53363[/C][/ROW]
[ROW][C]230[/C][C]1[/C][C]1.46101[/C][C]-0.461009[/C][/ROW]
[ROW][C]231[/C][C]0[/C][C]0.360475[/C][C]-0.360475[/C][/ROW]
[ROW][C]232[/C][C]0[/C][C]0.394768[/C][C]-0.394768[/C][/ROW]
[ROW][C]233[/C][C]0[/C][C]-0.362172[/C][C]0.362172[/C][/ROW]
[ROW][C]234[/C][C]1[/C][C]0.672424[/C][C]0.327576[/C][/ROW]
[ROW][C]235[/C][C]1[/C][C]0.489567[/C][C]0.510433[/C][/ROW]
[ROW][C]236[/C][C]1[/C][C]0.847564[/C][C]0.152436[/C][/ROW]
[ROW][C]237[/C][C]1[/C][C]1.68188[/C][C]-0.681879[/C][/ROW]
[ROW][C]238[/C][C]0[/C][C]-0.511633[/C][C]0.511633[/C][/ROW]
[ROW][C]239[/C][C]1[/C][C]0.326213[/C][C]0.673787[/C][/ROW]
[ROW][C]240[/C][C]1[/C][C]0.591099[/C][C]0.408901[/C][/ROW]
[ROW][C]241[/C][C]1[/C][C]1.57463[/C][C]-0.574629[/C][/ROW]
[ROW][C]242[/C][C]0[/C][C]0.565555[/C][C]-0.565555[/C][/ROW]
[ROW][C]243[/C][C]0[/C][C]-0.453827[/C][C]0.453827[/C][/ROW]
[ROW][C]244[/C][C]1[/C][C]1.41821[/C][C]-0.418214[/C][/ROW]
[ROW][C]245[/C][C]0[/C][C]-0.363836[/C][C]0.363836[/C][/ROW]
[ROW][C]246[/C][C]1[/C][C]0.50034[/C][C]0.49966[/C][/ROW]
[ROW][C]247[/C][C]1[/C][C]1.35057[/C][C]-0.350574[/C][/ROW]
[ROW][C]248[/C][C]0[/C][C]-0.360291[/C][C]0.360291[/C][/ROW]
[ROW][C]249[/C][C]1[/C][C]1.50638[/C][C]-0.506383[/C][/ROW]
[ROW][C]250[/C][C]0[/C][C]-0.396571[/C][C]0.396571[/C][/ROW]
[ROW][C]251[/C][C]1[/C][C]0.766005[/C][C]0.233995[/C][/ROW]
[ROW][C]252[/C][C]1[/C][C]1.6367[/C][C]-0.636702[/C][/ROW]
[ROW][C]253[/C][C]0[/C][C]-0.508415[/C][C]0.508415[/C][/ROW]
[ROW][C]254[/C][C]1[/C][C]1.45077[/C][C]-0.450769[/C][/ROW]
[ROW][C]255[/C][C]0[/C][C]-0.364123[/C][C]0.364123[/C][/ROW]
[ROW][C]256[/C][C]1[/C][C]1.49425[/C][C]-0.494249[/C][/ROW]
[ROW][C]257[/C][C]0[/C][C]-0.382856[/C][C]0.382856[/C][/ROW]
[ROW][C]258[/C][C]1[/C][C]1.78774[/C][C]-0.787736[/C][/ROW]
[ROW][C]259[/C][C]0[/C][C]0.467825[/C][C]-0.467825[/C][/ROW]
[ROW][C]260[/C][C]0[/C][C]-0.465872[/C][C]0.465872[/C][/ROW]
[ROW][C]261[/C][C]1[/C][C]0.637029[/C][C]0.362971[/C][/ROW]
[ROW][C]262[/C][C]1[/C][C]1.68069[/C][C]-0.680691[/C][/ROW]
[ROW][C]263[/C][C]0[/C][C]-0.427617[/C][C]0.427617[/C][/ROW]
[ROW][C]264[/C][C]1[/C][C]0.546173[/C][C]0.453827[/C][/ROW]
[ROW][C]265[/C][C]1[/C][C]1.37611[/C][C]-0.376114[/C][/ROW]
[ROW][C]266[/C][C]0[/C][C]-0.352946[/C][C]0.352946[/C][/ROW]
[ROW][C]267[/C][C]1[/C][C]1.62526[/C][C]-0.625259[/C][/ROW]
[ROW][C]268[/C][C]0[/C][C]0.365426[/C][C]-0.365426[/C][/ROW]
[ROW][C]269[/C][C]0[/C][C]-0.39139[/C][C]0.39139[/C][/ROW]
[ROW][C]270[/C][C]1[/C][C]0.65339[/C][C]0.34661[/C][/ROW]
[ROW][C]271[/C][C]1[/C][C]1.58245[/C][C]-0.582449[/C][/ROW]
[ROW][C]272[/C][C]0[/C][C]-0.338061[/C][C]0.338061[/C][/ROW]
[ROW][C]273[/C][C]1[/C][C]1.13987[/C][C]-0.13987[/C][/ROW]
[ROW][C]274[/C][C]0[/C][C]0.470302[/C][C]-0.470302[/C][/ROW]
[ROW][C]275[/C][C]0[/C][C]-0.457721[/C][C]0.457721[/C][/ROW]
[ROW][C]276[/C][C]1[/C][C]1.66829[/C][C]-0.668285[/C][/ROW]
[ROW][C]277[/C][C]0[/C][C]0.527725[/C][C]-0.527725[/C][/ROW]
[ROW][C]278[/C][C]0[/C][C]-0.211002[/C][C]0.211002[/C][/ROW]
[ROW][C]279[/C][C]1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264929&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264929&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
100.603067-0.603067
210.6360830.363917
300.647916-0.647916
410.6598950.340105
510.7415090.258491
610.5655150.434485
700.535793-0.535793
810.5580520.441948
910.5597680.440232
1010.6517660.348234
1110.6878890.312111
1210.6194570.380543
1310.6813280.318672
1400.544473-0.544473
1500.763405-0.763405
1600.658102-0.658102
1710.5748730.425127
1800.581425-0.581425
1910.7258110.274189
2000.596245-0.596245
2110.7322830.267717
2210.6502190.349781
2300.61669-0.61669
2410.5425280.457472
2510.6066430.393357
2610.3159410.684059
2710.5161850.483815
2800.593068-0.593068
2910.6181010.381899
3000.53709-0.53709
3100.504018-0.504018
3200.649787-0.649787
3310.7013560.298644
3410.7070320.292968
3510.5860010.413999
3610.6219530.378047
3700.390944-0.390944
3810.6222380.377762
3910.6659450.334055
4000.610186-0.610186
4110.7002920.299708
4210.6514030.348597
4310.5888380.411162
4410.6946230.305377
4510.5134610.486539
4600.701888-0.701888
4710.5897650.410235
4810.6849140.315086
4900.587041-0.587041
5010.633120.36688
5110.6444640.355536
5210.6817230.318277
5310.630490.36951
5410.7276210.272379
5510.5420090.457991
5610.7299760.270024
5700.717145-0.717145
5810.485340.51466
5900.489625-0.489625
6010.6426340.357366
6110.6546130.345387
6200.643454-0.643454
6300.588562-0.588562
6410.580070.41993
6500.70663-0.70663
6610.7036840.296316
6700.542456-0.542456
6810.5342560.465744
6910.478230.52177
7000.526436-0.526436
7100.59982-0.59982
7200.67279-0.67279
7300.662689-0.662689
7410.528650.47135
7500.544487-0.544487
7611.63001-0.630015
770-0.2927020.292702
7811.56542-0.565424
7900.460224-0.460224
800-0.38490.3849
8111.66219-0.662187
8200.526386-0.526386
8300.562325-0.562325
840-0.2607860.260786
8511.37149-0.371491
860-0.4357480.435748
8710.6536240.346376
8811.68116-0.681162
8900.711689-0.711689
9000.46656-0.46656
910-0.4787150.478715
9210.6650930.334907
9310.5683460.431654
9411.6684-0.668396
950-0.3067140.306714
9611.73343-0.733429
970-0.214370.21437
9810.6995650.300435
9910.6507190.349281
10010.649970.35003
10110.7055530.294447
10211.61805-0.61805
1030-0.3917580.391758
10410.6166980.383302
10510.5863260.413674
10611.58802-0.588019
10700.298139-0.298139
10800.539597-0.539597
10900.752907-0.752907
11000.543701-0.543701
11100.672396-0.672396
1120-0.4074730.407473
11310.7586040.241396
11410.5287240.471276
11510.4909470.509053
11610.6060590.393941
11711.3095-0.309498
1180-0.4232370.423237
11910.4916470.508353
12011.43588-0.435879
1210-0.6524310.652431
12211.6214-0.621404
12300.380981-0.380981
1240-0.3770350.377035
12510.5466280.453372
12610.5437390.456261
12710.6288140.371186
12810.4391540.560846
12910.5020430.497957
13010.6414520.358548
13110.644240.35576
13211.5261-0.526104
1330-0.513320.51332
13410.3347560.665244
13510.6447050.355295
13610.4353360.564664
13710.5136340.486366
13810.7563250.243675
13911.50818-0.508178
1400-0.5264610.526461
14110.5590090.440991
14210.6218770.378123
14310.2502590.749741
14410.5294790.470521
14511.48183-0.481825
14600.524691-0.524691
1470-0.6094940.609494
14811.46727-0.467269
14900.295503-0.295503
1500-0.4416950.441695
15111.69229-0.692294
1520-0.4708830.470883
15310.5396640.460336
15411.55726-0.557265
1550-0.3333310.333331
15610.5463350.453665
15710.474190.52581
15811.51325-0.513255
15900.43637-0.43637
16000.52863-0.52863
16100.434341-0.434341
1620-0.5601850.560185
16311.44939-0.449387
1640-0.4284880.428488
16511.41821-0.418214
1660-0.3629710.362971
16711.5068-0.506804
1680-0.2893180.289318
16911.62622-0.626223
17000.473792-0.473792
1710-0.4636960.463696
17211.55147-0.55147
1730-0.3870450.387045
17410.6176940.382306
17510.6176940.382306
17610.4925630.507437
17710.5692410.430759
17811.51507-0.515073
1790-0.3926340.392634
18011.6276-0.627596
18100.546234-0.546234
18200.601892-0.601892
1830-0.5350170.535017
18411.5302-0.530203
1850-0.3486150.348615
18611.57261-0.572614
18700.641092-0.641092
18800.672301-0.672301
18900.730485-0.730485
1900-0.392220.39222
19110.6753360.324664
19210.2473670.752633
19310.5862380.413762
19411.36199-0.361987
19500.385298-0.385298
1960-0.3851310.385131
19711.54779-0.547795
19800.298492-0.298492
19900.505709-0.505709
20000.435637-0.435637
2010-0.4433350.443335
20210.5646910.435309
20311.5117-0.511698
20400.626054-0.626054
2050-0.3704840.370484
20611.61574-0.615741
2070-0.3567450.356745
20810.6423670.357633
20910.9657630.0342373
2100-0.6085530.608553
21110.6829590.317041
21210.6764570.323543
21311.46141-0.461413
21400.632718-0.632718
21500.48906-0.48906
2160-0.5293390.529339
21710.4379990.562001
21810.6157520.384248
21910.6830120.316988
22011.59173-0.591726
22100.448011-0.448011
22200.482069-0.482069
2230-0.3044750.304475
22410.425850.57415
22511.32817-0.328175
22600.600741-0.600741
22700.498032-0.498032
2280-0.413020.41302
22910.466370.53363
23011.46101-0.461009
23100.360475-0.360475
23200.394768-0.394768
2330-0.3621720.362172
23410.6724240.327576
23510.4895670.510433
23610.8475640.152436
23711.68188-0.681879
2380-0.5116330.511633
23910.3262130.673787
24010.5910990.408901
24111.57463-0.574629
24200.565555-0.565555
2430-0.4538270.453827
24411.41821-0.418214
2450-0.3638360.363836
24610.500340.49966
24711.35057-0.350574
2480-0.3602910.360291
24911.50638-0.506383
2500-0.3965710.396571
25110.7660050.233995
25211.6367-0.636702
2530-0.5084150.508415
25411.45077-0.450769
2550-0.3641230.364123
25611.49425-0.494249
2570-0.3828560.382856
25811.78774-0.787736
25900.467825-0.467825
2600-0.4658720.465872
26110.6370290.362971
26211.68069-0.680691
2630-0.4276170.427617
26410.5461730.453827
26511.37611-0.376114
2660-0.3529460.352946
26711.62526-0.625259
26800.365426-0.365426
2690-0.391390.39139
27010.653390.34661
27111.58245-0.582449
2720-0.3380610.338061
27311.13987-0.13987
27400.470302-0.470302
2750-0.4577210.457721
27611.66829-0.668285
27700.527725-0.527725
2780-0.2110020.211002
2791NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.657920.6841590.34208
90.5089250.9821510.491075
100.447420.8948390.55258
110.5596990.8806010.440301
120.4818920.9637840.518108
130.41980.8396010.5802
140.4862250.972450.513775
150.6566050.6867890.343395
160.5991260.8017470.400874
170.5576890.8846210.442311
180.4998390.9996790.500161
190.4220880.8441750.577912
200.3739370.7478730.626063
210.3065890.6131790.693411
220.333550.66710.66645
230.5125120.9749760.487488
240.4901350.980270.509865
250.4695440.9390880.530456
260.5304550.9390910.469545
270.5205450.958910.479455
280.4770310.9540620.522969
290.430650.86130.56935
300.4058710.8117420.594129
310.3541620.7083240.645838
320.3907750.7815490.609225
330.3676870.7353740.632313
340.3176190.6352380.682381
350.3797280.7594570.620272
360.4333620.8667230.566638
370.3843820.7687650.615618
380.4285680.8571370.571432
390.3850270.7700550.614973
400.4359470.8718940.564053
410.4065950.813190.593405
420.3849990.7699980.615001
430.3654780.7309560.634522
440.3249270.6498550.675073
450.4178740.8357470.582126
460.505070.989860.49493
470.4876580.9753160.512342
480.455140.9102810.54486
490.4717520.9435040.528248
500.4881450.9762910.511855
510.469450.93890.53055
520.4427940.8855890.557206
530.4259660.8519320.574034
540.3957360.7914730.604264
550.3923640.7847290.607636
560.3593460.7186920.640654
570.4212880.8425750.578712
580.4228840.8457680.577116
590.4062930.8125860.593707
600.3800550.760110.619945
610.3508780.7017550.649122
620.3704710.7409410.629529
630.3867680.7735360.613232
640.3624790.7249590.637521
650.406570.8131410.59343
660.3840710.7681420.615929
670.4075130.8150260.592487
680.3867330.7734660.613267
690.4058310.8116630.594169
700.4122290.8244570.587771
710.4469040.8938070.553096
720.4792750.958550.520725
730.5123610.9752780.487639
740.4971630.9943260.502837
750.5124850.975030.487515
760.55490.89020.4451
770.5309420.9381160.469058
780.5549730.8900540.445027
790.5385440.9229130.461456
800.5268050.9463910.473195
810.5537460.8925080.446254
820.5500060.8999880.449994
830.5579740.8840510.442026
840.5388720.9222550.461128
850.5132090.9735830.486791
860.5020720.9958550.497928
870.48750.9750.5125
880.5109590.9780830.489041
890.542710.914580.45729
900.5285450.9429110.471455
910.5434160.9131680.456584
920.534310.9313810.46569
930.5246180.9507630.475382
940.5436260.9127480.456374
950.5306910.9386180.469309
960.5641150.871770.435885
970.5358020.9283950.464198
980.5232990.9534010.476701
990.5137750.972450.486225
1000.4995220.9990430.500478
1010.4763060.9526130.523694
1020.4922440.9844870.507756
1030.4881050.9762090.511895
1040.4769580.9539150.523042
1050.4675770.9351540.532423
1060.4773930.9547860.522607
1070.4523560.9047120.547644
1080.4529610.9059220.547039
1090.4986930.9973850.501307
1100.5072150.985570.492785
1110.5389640.9220710.461036
1120.5401490.9197020.459851
1130.5220290.9559430.477971
1140.51970.9605990.4803
1150.5234370.9531260.476563
1160.5079960.9840090.492004
1170.5004480.9991040.499552
1180.4976440.9952890.502356
1190.4931310.9862620.506869
1200.4969150.993830.503085
1210.5248030.9503940.475197
1220.5500410.8999170.449959
1230.5364560.9270880.463544
1240.5227390.9545220.477261
1250.5211280.9577450.478872
1260.5191380.9617230.480862
1270.5021040.9957930.497896
1280.5143430.9713140.485657
1290.5166360.9667280.483364
1300.4977540.9955070.502246
1310.4781250.956250.521875
1320.4939760.9879510.506024
1330.4955620.9911240.504438
1340.5238560.9522870.476144
1350.504590.9908190.49541
1360.5133720.9732560.486628
1370.5067680.9864650.493232
1380.4793280.9586570.520672
1390.49430.9886010.5057
1400.5021580.9956830.497842
1410.4919150.983830.508085
1420.4727960.9455930.527204
1430.5167420.9665160.483258
1440.511670.976660.48833
1450.5175410.9649180.482459
1460.5304030.9391930.469597
1470.5444430.9111150.455557
1480.5464390.9071230.453561
1490.5277210.9445570.472279
1500.520270.959460.47973
1510.5590680.8818630.440932
1520.5627680.8744650.437232
1530.5597330.8805330.440267
1540.574840.850320.42516
1550.5565630.8868750.443437
1560.5544280.8911440.445572
1570.5772160.8455680.422784
1580.5858140.8283730.414186
1590.5802860.8394270.419714
1600.593510.812980.40649
1610.5878540.8242910.412146
1620.6010560.7978890.398944
1630.5963140.8073720.403686
1640.6034210.7931580.396579
1650.5939940.8120120.406006
1660.5767550.846490.423245
1670.5756370.8487270.424363
1680.555790.8884190.44421
1690.5750170.8499660.424983
1700.5778890.8442220.422111
1710.584460.831080.41554
1720.5860670.8278650.413933
1730.5736660.8526690.426334
1740.5574970.8850060.442503
1750.5421880.9156230.457812
1760.5638110.8723780.436189
1770.5579240.8841520.442076
1780.5555550.8888890.444445
1790.5496940.9006110.450306
1800.5970360.8059280.402964
1810.5979630.8040750.402037
1820.6168710.7662590.383129
1830.6507420.6985160.349258
1840.6494840.7010330.350516
1850.6295310.7409390.370469
1860.6307090.7385810.369291
1870.6413470.7173070.358653
1880.671330.6573410.32867
1890.7303350.5393310.269665
1900.7228310.5543380.277169
1910.7020690.5958620.297931
1920.7516040.4967920.248396
1930.735480.529040.26452
1940.7162750.5674490.283725
1950.7068030.5863940.293197
1960.7093090.5813820.290691
1970.7160020.5679970.283998
1980.6975110.6049780.302489
1990.6993630.6012750.300637
2000.6880560.6238880.311944
2010.6998960.6002080.300104
2020.6944850.6110310.305515
2030.7103840.5792320.289616
2040.7212210.5575590.278779
2050.6987040.6025920.301296
2060.7147270.5705460.285273
2070.6977140.6045720.302286
2080.6827480.6345040.317252
2090.647340.705320.35266
2100.6978410.6043180.302159
2110.6859330.6281330.314067
2120.6641930.6716140.335807
2130.661810.6763790.33819
2140.6850310.6299390.314969
2150.6722440.6555130.327756
2160.6675330.6649340.332467
2170.701760.5964790.29824
2180.6994550.6010890.300545
2190.6844430.6311130.315557
2200.6809850.6380290.319015
2210.6681260.6637490.331874
2220.7153510.5692980.284649
2230.6862240.6275520.313776
2240.690180.619640.30982
2250.6584910.6830190.341509
2260.6562440.6875120.343756
2270.6563040.6873930.343696
2280.6648180.6703630.335182
2290.7779480.4441040.222052
2300.7568150.486370.243185
2310.7763260.4473480.223674
2320.7466520.5066970.253348
2330.7317620.5364750.268238
2340.6937670.6124660.306233
2350.6573030.6853950.342697
2360.6104130.7791730.389587
2370.6791780.6416440.320822
2380.6794990.6410020.320501
2390.6976420.6047150.302358
2400.6755130.6489730.324487
2410.6648930.6702140.335107
2420.678040.643920.32196
2430.674240.6515210.32576
2440.6276070.7447860.372393
2450.5841980.8316050.415802
2460.6311790.7376410.368821
2470.5778180.8443630.422182
2480.5514150.897170.448585
2490.5042730.9914540.495727
2500.4783720.9567440.521628
2510.4314820.8629640.568518
2520.4452040.8904080.554796
2530.4946280.9892570.505372
2540.4505220.9010440.549478
2550.5407560.9184890.459244
2560.4883780.9767550.511622
2570.4279310.8558620.572069
2580.583750.8325010.41625
2590.6069270.7861460.393073
2600.5329440.9341110.467056
2610.4701790.9403570.529821
2620.6379640.7240710.362036
2630.5538760.8922480.446124
2640.6544060.6911870.345594
2650.556060.887880.44394
2660.4736740.9473480.526326
2670.5126560.9746890.487344
2680.3876710.7753410.612329
2690.5410330.9179330.458967
2700.3809630.7619270.619037
2710.221610.443220.77839

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.65792 & 0.684159 & 0.34208 \tabularnewline
9 & 0.508925 & 0.982151 & 0.491075 \tabularnewline
10 & 0.44742 & 0.894839 & 0.55258 \tabularnewline
11 & 0.559699 & 0.880601 & 0.440301 \tabularnewline
12 & 0.481892 & 0.963784 & 0.518108 \tabularnewline
13 & 0.4198 & 0.839601 & 0.5802 \tabularnewline
14 & 0.486225 & 0.97245 & 0.513775 \tabularnewline
15 & 0.656605 & 0.686789 & 0.343395 \tabularnewline
16 & 0.599126 & 0.801747 & 0.400874 \tabularnewline
17 & 0.557689 & 0.884621 & 0.442311 \tabularnewline
18 & 0.499839 & 0.999679 & 0.500161 \tabularnewline
19 & 0.422088 & 0.844175 & 0.577912 \tabularnewline
20 & 0.373937 & 0.747873 & 0.626063 \tabularnewline
21 & 0.306589 & 0.613179 & 0.693411 \tabularnewline
22 & 0.33355 & 0.6671 & 0.66645 \tabularnewline
23 & 0.512512 & 0.974976 & 0.487488 \tabularnewline
24 & 0.490135 & 0.98027 & 0.509865 \tabularnewline
25 & 0.469544 & 0.939088 & 0.530456 \tabularnewline
26 & 0.530455 & 0.939091 & 0.469545 \tabularnewline
27 & 0.520545 & 0.95891 & 0.479455 \tabularnewline
28 & 0.477031 & 0.954062 & 0.522969 \tabularnewline
29 & 0.43065 & 0.8613 & 0.56935 \tabularnewline
30 & 0.405871 & 0.811742 & 0.594129 \tabularnewline
31 & 0.354162 & 0.708324 & 0.645838 \tabularnewline
32 & 0.390775 & 0.781549 & 0.609225 \tabularnewline
33 & 0.367687 & 0.735374 & 0.632313 \tabularnewline
34 & 0.317619 & 0.635238 & 0.682381 \tabularnewline
35 & 0.379728 & 0.759457 & 0.620272 \tabularnewline
36 & 0.433362 & 0.866723 & 0.566638 \tabularnewline
37 & 0.384382 & 0.768765 & 0.615618 \tabularnewline
38 & 0.428568 & 0.857137 & 0.571432 \tabularnewline
39 & 0.385027 & 0.770055 & 0.614973 \tabularnewline
40 & 0.435947 & 0.871894 & 0.564053 \tabularnewline
41 & 0.406595 & 0.81319 & 0.593405 \tabularnewline
42 & 0.384999 & 0.769998 & 0.615001 \tabularnewline
43 & 0.365478 & 0.730956 & 0.634522 \tabularnewline
44 & 0.324927 & 0.649855 & 0.675073 \tabularnewline
45 & 0.417874 & 0.835747 & 0.582126 \tabularnewline
46 & 0.50507 & 0.98986 & 0.49493 \tabularnewline
47 & 0.487658 & 0.975316 & 0.512342 \tabularnewline
48 & 0.45514 & 0.910281 & 0.54486 \tabularnewline
49 & 0.471752 & 0.943504 & 0.528248 \tabularnewline
50 & 0.488145 & 0.976291 & 0.511855 \tabularnewline
51 & 0.46945 & 0.9389 & 0.53055 \tabularnewline
52 & 0.442794 & 0.885589 & 0.557206 \tabularnewline
53 & 0.425966 & 0.851932 & 0.574034 \tabularnewline
54 & 0.395736 & 0.791473 & 0.604264 \tabularnewline
55 & 0.392364 & 0.784729 & 0.607636 \tabularnewline
56 & 0.359346 & 0.718692 & 0.640654 \tabularnewline
57 & 0.421288 & 0.842575 & 0.578712 \tabularnewline
58 & 0.422884 & 0.845768 & 0.577116 \tabularnewline
59 & 0.406293 & 0.812586 & 0.593707 \tabularnewline
60 & 0.380055 & 0.76011 & 0.619945 \tabularnewline
61 & 0.350878 & 0.701755 & 0.649122 \tabularnewline
62 & 0.370471 & 0.740941 & 0.629529 \tabularnewline
63 & 0.386768 & 0.773536 & 0.613232 \tabularnewline
64 & 0.362479 & 0.724959 & 0.637521 \tabularnewline
65 & 0.40657 & 0.813141 & 0.59343 \tabularnewline
66 & 0.384071 & 0.768142 & 0.615929 \tabularnewline
67 & 0.407513 & 0.815026 & 0.592487 \tabularnewline
68 & 0.386733 & 0.773466 & 0.613267 \tabularnewline
69 & 0.405831 & 0.811663 & 0.594169 \tabularnewline
70 & 0.412229 & 0.824457 & 0.587771 \tabularnewline
71 & 0.446904 & 0.893807 & 0.553096 \tabularnewline
72 & 0.479275 & 0.95855 & 0.520725 \tabularnewline
73 & 0.512361 & 0.975278 & 0.487639 \tabularnewline
74 & 0.497163 & 0.994326 & 0.502837 \tabularnewline
75 & 0.512485 & 0.97503 & 0.487515 \tabularnewline
76 & 0.5549 & 0.8902 & 0.4451 \tabularnewline
77 & 0.530942 & 0.938116 & 0.469058 \tabularnewline
78 & 0.554973 & 0.890054 & 0.445027 \tabularnewline
79 & 0.538544 & 0.922913 & 0.461456 \tabularnewline
80 & 0.526805 & 0.946391 & 0.473195 \tabularnewline
81 & 0.553746 & 0.892508 & 0.446254 \tabularnewline
82 & 0.550006 & 0.899988 & 0.449994 \tabularnewline
83 & 0.557974 & 0.884051 & 0.442026 \tabularnewline
84 & 0.538872 & 0.922255 & 0.461128 \tabularnewline
85 & 0.513209 & 0.973583 & 0.486791 \tabularnewline
86 & 0.502072 & 0.995855 & 0.497928 \tabularnewline
87 & 0.4875 & 0.975 & 0.5125 \tabularnewline
88 & 0.510959 & 0.978083 & 0.489041 \tabularnewline
89 & 0.54271 & 0.91458 & 0.45729 \tabularnewline
90 & 0.528545 & 0.942911 & 0.471455 \tabularnewline
91 & 0.543416 & 0.913168 & 0.456584 \tabularnewline
92 & 0.53431 & 0.931381 & 0.46569 \tabularnewline
93 & 0.524618 & 0.950763 & 0.475382 \tabularnewline
94 & 0.543626 & 0.912748 & 0.456374 \tabularnewline
95 & 0.530691 & 0.938618 & 0.469309 \tabularnewline
96 & 0.564115 & 0.87177 & 0.435885 \tabularnewline
97 & 0.535802 & 0.928395 & 0.464198 \tabularnewline
98 & 0.523299 & 0.953401 & 0.476701 \tabularnewline
99 & 0.513775 & 0.97245 & 0.486225 \tabularnewline
100 & 0.499522 & 0.999043 & 0.500478 \tabularnewline
101 & 0.476306 & 0.952613 & 0.523694 \tabularnewline
102 & 0.492244 & 0.984487 & 0.507756 \tabularnewline
103 & 0.488105 & 0.976209 & 0.511895 \tabularnewline
104 & 0.476958 & 0.953915 & 0.523042 \tabularnewline
105 & 0.467577 & 0.935154 & 0.532423 \tabularnewline
106 & 0.477393 & 0.954786 & 0.522607 \tabularnewline
107 & 0.452356 & 0.904712 & 0.547644 \tabularnewline
108 & 0.452961 & 0.905922 & 0.547039 \tabularnewline
109 & 0.498693 & 0.997385 & 0.501307 \tabularnewline
110 & 0.507215 & 0.98557 & 0.492785 \tabularnewline
111 & 0.538964 & 0.922071 & 0.461036 \tabularnewline
112 & 0.540149 & 0.919702 & 0.459851 \tabularnewline
113 & 0.522029 & 0.955943 & 0.477971 \tabularnewline
114 & 0.5197 & 0.960599 & 0.4803 \tabularnewline
115 & 0.523437 & 0.953126 & 0.476563 \tabularnewline
116 & 0.507996 & 0.984009 & 0.492004 \tabularnewline
117 & 0.500448 & 0.999104 & 0.499552 \tabularnewline
118 & 0.497644 & 0.995289 & 0.502356 \tabularnewline
119 & 0.493131 & 0.986262 & 0.506869 \tabularnewline
120 & 0.496915 & 0.99383 & 0.503085 \tabularnewline
121 & 0.524803 & 0.950394 & 0.475197 \tabularnewline
122 & 0.550041 & 0.899917 & 0.449959 \tabularnewline
123 & 0.536456 & 0.927088 & 0.463544 \tabularnewline
124 & 0.522739 & 0.954522 & 0.477261 \tabularnewline
125 & 0.521128 & 0.957745 & 0.478872 \tabularnewline
126 & 0.519138 & 0.961723 & 0.480862 \tabularnewline
127 & 0.502104 & 0.995793 & 0.497896 \tabularnewline
128 & 0.514343 & 0.971314 & 0.485657 \tabularnewline
129 & 0.516636 & 0.966728 & 0.483364 \tabularnewline
130 & 0.497754 & 0.995507 & 0.502246 \tabularnewline
131 & 0.478125 & 0.95625 & 0.521875 \tabularnewline
132 & 0.493976 & 0.987951 & 0.506024 \tabularnewline
133 & 0.495562 & 0.991124 & 0.504438 \tabularnewline
134 & 0.523856 & 0.952287 & 0.476144 \tabularnewline
135 & 0.50459 & 0.990819 & 0.49541 \tabularnewline
136 & 0.513372 & 0.973256 & 0.486628 \tabularnewline
137 & 0.506768 & 0.986465 & 0.493232 \tabularnewline
138 & 0.479328 & 0.958657 & 0.520672 \tabularnewline
139 & 0.4943 & 0.988601 & 0.5057 \tabularnewline
140 & 0.502158 & 0.995683 & 0.497842 \tabularnewline
141 & 0.491915 & 0.98383 & 0.508085 \tabularnewline
142 & 0.472796 & 0.945593 & 0.527204 \tabularnewline
143 & 0.516742 & 0.966516 & 0.483258 \tabularnewline
144 & 0.51167 & 0.97666 & 0.48833 \tabularnewline
145 & 0.517541 & 0.964918 & 0.482459 \tabularnewline
146 & 0.530403 & 0.939193 & 0.469597 \tabularnewline
147 & 0.544443 & 0.911115 & 0.455557 \tabularnewline
148 & 0.546439 & 0.907123 & 0.453561 \tabularnewline
149 & 0.527721 & 0.944557 & 0.472279 \tabularnewline
150 & 0.52027 & 0.95946 & 0.47973 \tabularnewline
151 & 0.559068 & 0.881863 & 0.440932 \tabularnewline
152 & 0.562768 & 0.874465 & 0.437232 \tabularnewline
153 & 0.559733 & 0.880533 & 0.440267 \tabularnewline
154 & 0.57484 & 0.85032 & 0.42516 \tabularnewline
155 & 0.556563 & 0.886875 & 0.443437 \tabularnewline
156 & 0.554428 & 0.891144 & 0.445572 \tabularnewline
157 & 0.577216 & 0.845568 & 0.422784 \tabularnewline
158 & 0.585814 & 0.828373 & 0.414186 \tabularnewline
159 & 0.580286 & 0.839427 & 0.419714 \tabularnewline
160 & 0.59351 & 0.81298 & 0.40649 \tabularnewline
161 & 0.587854 & 0.824291 & 0.412146 \tabularnewline
162 & 0.601056 & 0.797889 & 0.398944 \tabularnewline
163 & 0.596314 & 0.807372 & 0.403686 \tabularnewline
164 & 0.603421 & 0.793158 & 0.396579 \tabularnewline
165 & 0.593994 & 0.812012 & 0.406006 \tabularnewline
166 & 0.576755 & 0.84649 & 0.423245 \tabularnewline
167 & 0.575637 & 0.848727 & 0.424363 \tabularnewline
168 & 0.55579 & 0.888419 & 0.44421 \tabularnewline
169 & 0.575017 & 0.849966 & 0.424983 \tabularnewline
170 & 0.577889 & 0.844222 & 0.422111 \tabularnewline
171 & 0.58446 & 0.83108 & 0.41554 \tabularnewline
172 & 0.586067 & 0.827865 & 0.413933 \tabularnewline
173 & 0.573666 & 0.852669 & 0.426334 \tabularnewline
174 & 0.557497 & 0.885006 & 0.442503 \tabularnewline
175 & 0.542188 & 0.915623 & 0.457812 \tabularnewline
176 & 0.563811 & 0.872378 & 0.436189 \tabularnewline
177 & 0.557924 & 0.884152 & 0.442076 \tabularnewline
178 & 0.555555 & 0.888889 & 0.444445 \tabularnewline
179 & 0.549694 & 0.900611 & 0.450306 \tabularnewline
180 & 0.597036 & 0.805928 & 0.402964 \tabularnewline
181 & 0.597963 & 0.804075 & 0.402037 \tabularnewline
182 & 0.616871 & 0.766259 & 0.383129 \tabularnewline
183 & 0.650742 & 0.698516 & 0.349258 \tabularnewline
184 & 0.649484 & 0.701033 & 0.350516 \tabularnewline
185 & 0.629531 & 0.740939 & 0.370469 \tabularnewline
186 & 0.630709 & 0.738581 & 0.369291 \tabularnewline
187 & 0.641347 & 0.717307 & 0.358653 \tabularnewline
188 & 0.67133 & 0.657341 & 0.32867 \tabularnewline
189 & 0.730335 & 0.539331 & 0.269665 \tabularnewline
190 & 0.722831 & 0.554338 & 0.277169 \tabularnewline
191 & 0.702069 & 0.595862 & 0.297931 \tabularnewline
192 & 0.751604 & 0.496792 & 0.248396 \tabularnewline
193 & 0.73548 & 0.52904 & 0.26452 \tabularnewline
194 & 0.716275 & 0.567449 & 0.283725 \tabularnewline
195 & 0.706803 & 0.586394 & 0.293197 \tabularnewline
196 & 0.709309 & 0.581382 & 0.290691 \tabularnewline
197 & 0.716002 & 0.567997 & 0.283998 \tabularnewline
198 & 0.697511 & 0.604978 & 0.302489 \tabularnewline
199 & 0.699363 & 0.601275 & 0.300637 \tabularnewline
200 & 0.688056 & 0.623888 & 0.311944 \tabularnewline
201 & 0.699896 & 0.600208 & 0.300104 \tabularnewline
202 & 0.694485 & 0.611031 & 0.305515 \tabularnewline
203 & 0.710384 & 0.579232 & 0.289616 \tabularnewline
204 & 0.721221 & 0.557559 & 0.278779 \tabularnewline
205 & 0.698704 & 0.602592 & 0.301296 \tabularnewline
206 & 0.714727 & 0.570546 & 0.285273 \tabularnewline
207 & 0.697714 & 0.604572 & 0.302286 \tabularnewline
208 & 0.682748 & 0.634504 & 0.317252 \tabularnewline
209 & 0.64734 & 0.70532 & 0.35266 \tabularnewline
210 & 0.697841 & 0.604318 & 0.302159 \tabularnewline
211 & 0.685933 & 0.628133 & 0.314067 \tabularnewline
212 & 0.664193 & 0.671614 & 0.335807 \tabularnewline
213 & 0.66181 & 0.676379 & 0.33819 \tabularnewline
214 & 0.685031 & 0.629939 & 0.314969 \tabularnewline
215 & 0.672244 & 0.655513 & 0.327756 \tabularnewline
216 & 0.667533 & 0.664934 & 0.332467 \tabularnewline
217 & 0.70176 & 0.596479 & 0.29824 \tabularnewline
218 & 0.699455 & 0.601089 & 0.300545 \tabularnewline
219 & 0.684443 & 0.631113 & 0.315557 \tabularnewline
220 & 0.680985 & 0.638029 & 0.319015 \tabularnewline
221 & 0.668126 & 0.663749 & 0.331874 \tabularnewline
222 & 0.715351 & 0.569298 & 0.284649 \tabularnewline
223 & 0.686224 & 0.627552 & 0.313776 \tabularnewline
224 & 0.69018 & 0.61964 & 0.30982 \tabularnewline
225 & 0.658491 & 0.683019 & 0.341509 \tabularnewline
226 & 0.656244 & 0.687512 & 0.343756 \tabularnewline
227 & 0.656304 & 0.687393 & 0.343696 \tabularnewline
228 & 0.664818 & 0.670363 & 0.335182 \tabularnewline
229 & 0.777948 & 0.444104 & 0.222052 \tabularnewline
230 & 0.756815 & 0.48637 & 0.243185 \tabularnewline
231 & 0.776326 & 0.447348 & 0.223674 \tabularnewline
232 & 0.746652 & 0.506697 & 0.253348 \tabularnewline
233 & 0.731762 & 0.536475 & 0.268238 \tabularnewline
234 & 0.693767 & 0.612466 & 0.306233 \tabularnewline
235 & 0.657303 & 0.685395 & 0.342697 \tabularnewline
236 & 0.610413 & 0.779173 & 0.389587 \tabularnewline
237 & 0.679178 & 0.641644 & 0.320822 \tabularnewline
238 & 0.679499 & 0.641002 & 0.320501 \tabularnewline
239 & 0.697642 & 0.604715 & 0.302358 \tabularnewline
240 & 0.675513 & 0.648973 & 0.324487 \tabularnewline
241 & 0.664893 & 0.670214 & 0.335107 \tabularnewline
242 & 0.67804 & 0.64392 & 0.32196 \tabularnewline
243 & 0.67424 & 0.651521 & 0.32576 \tabularnewline
244 & 0.627607 & 0.744786 & 0.372393 \tabularnewline
245 & 0.584198 & 0.831605 & 0.415802 \tabularnewline
246 & 0.631179 & 0.737641 & 0.368821 \tabularnewline
247 & 0.577818 & 0.844363 & 0.422182 \tabularnewline
248 & 0.551415 & 0.89717 & 0.448585 \tabularnewline
249 & 0.504273 & 0.991454 & 0.495727 \tabularnewline
250 & 0.478372 & 0.956744 & 0.521628 \tabularnewline
251 & 0.431482 & 0.862964 & 0.568518 \tabularnewline
252 & 0.445204 & 0.890408 & 0.554796 \tabularnewline
253 & 0.494628 & 0.989257 & 0.505372 \tabularnewline
254 & 0.450522 & 0.901044 & 0.549478 \tabularnewline
255 & 0.540756 & 0.918489 & 0.459244 \tabularnewline
256 & 0.488378 & 0.976755 & 0.511622 \tabularnewline
257 & 0.427931 & 0.855862 & 0.572069 \tabularnewline
258 & 0.58375 & 0.832501 & 0.41625 \tabularnewline
259 & 0.606927 & 0.786146 & 0.393073 \tabularnewline
260 & 0.532944 & 0.934111 & 0.467056 \tabularnewline
261 & 0.470179 & 0.940357 & 0.529821 \tabularnewline
262 & 0.637964 & 0.724071 & 0.362036 \tabularnewline
263 & 0.553876 & 0.892248 & 0.446124 \tabularnewline
264 & 0.654406 & 0.691187 & 0.345594 \tabularnewline
265 & 0.55606 & 0.88788 & 0.44394 \tabularnewline
266 & 0.473674 & 0.947348 & 0.526326 \tabularnewline
267 & 0.512656 & 0.974689 & 0.487344 \tabularnewline
268 & 0.387671 & 0.775341 & 0.612329 \tabularnewline
269 & 0.541033 & 0.917933 & 0.458967 \tabularnewline
270 & 0.380963 & 0.761927 & 0.619037 \tabularnewline
271 & 0.22161 & 0.44322 & 0.77839 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264929&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]8[/C][C]0.65792[/C][C]0.684159[/C][C]0.34208[/C][/ROW]
[ROW][C]9[/C][C]0.508925[/C][C]0.982151[/C][C]0.491075[/C][/ROW]
[ROW][C]10[/C][C]0.44742[/C][C]0.894839[/C][C]0.55258[/C][/ROW]
[ROW][C]11[/C][C]0.559699[/C][C]0.880601[/C][C]0.440301[/C][/ROW]
[ROW][C]12[/C][C]0.481892[/C][C]0.963784[/C][C]0.518108[/C][/ROW]
[ROW][C]13[/C][C]0.4198[/C][C]0.839601[/C][C]0.5802[/C][/ROW]
[ROW][C]14[/C][C]0.486225[/C][C]0.97245[/C][C]0.513775[/C][/ROW]
[ROW][C]15[/C][C]0.656605[/C][C]0.686789[/C][C]0.343395[/C][/ROW]
[ROW][C]16[/C][C]0.599126[/C][C]0.801747[/C][C]0.400874[/C][/ROW]
[ROW][C]17[/C][C]0.557689[/C][C]0.884621[/C][C]0.442311[/C][/ROW]
[ROW][C]18[/C][C]0.499839[/C][C]0.999679[/C][C]0.500161[/C][/ROW]
[ROW][C]19[/C][C]0.422088[/C][C]0.844175[/C][C]0.577912[/C][/ROW]
[ROW][C]20[/C][C]0.373937[/C][C]0.747873[/C][C]0.626063[/C][/ROW]
[ROW][C]21[/C][C]0.306589[/C][C]0.613179[/C][C]0.693411[/C][/ROW]
[ROW][C]22[/C][C]0.33355[/C][C]0.6671[/C][C]0.66645[/C][/ROW]
[ROW][C]23[/C][C]0.512512[/C][C]0.974976[/C][C]0.487488[/C][/ROW]
[ROW][C]24[/C][C]0.490135[/C][C]0.98027[/C][C]0.509865[/C][/ROW]
[ROW][C]25[/C][C]0.469544[/C][C]0.939088[/C][C]0.530456[/C][/ROW]
[ROW][C]26[/C][C]0.530455[/C][C]0.939091[/C][C]0.469545[/C][/ROW]
[ROW][C]27[/C][C]0.520545[/C][C]0.95891[/C][C]0.479455[/C][/ROW]
[ROW][C]28[/C][C]0.477031[/C][C]0.954062[/C][C]0.522969[/C][/ROW]
[ROW][C]29[/C][C]0.43065[/C][C]0.8613[/C][C]0.56935[/C][/ROW]
[ROW][C]30[/C][C]0.405871[/C][C]0.811742[/C][C]0.594129[/C][/ROW]
[ROW][C]31[/C][C]0.354162[/C][C]0.708324[/C][C]0.645838[/C][/ROW]
[ROW][C]32[/C][C]0.390775[/C][C]0.781549[/C][C]0.609225[/C][/ROW]
[ROW][C]33[/C][C]0.367687[/C][C]0.735374[/C][C]0.632313[/C][/ROW]
[ROW][C]34[/C][C]0.317619[/C][C]0.635238[/C][C]0.682381[/C][/ROW]
[ROW][C]35[/C][C]0.379728[/C][C]0.759457[/C][C]0.620272[/C][/ROW]
[ROW][C]36[/C][C]0.433362[/C][C]0.866723[/C][C]0.566638[/C][/ROW]
[ROW][C]37[/C][C]0.384382[/C][C]0.768765[/C][C]0.615618[/C][/ROW]
[ROW][C]38[/C][C]0.428568[/C][C]0.857137[/C][C]0.571432[/C][/ROW]
[ROW][C]39[/C][C]0.385027[/C][C]0.770055[/C][C]0.614973[/C][/ROW]
[ROW][C]40[/C][C]0.435947[/C][C]0.871894[/C][C]0.564053[/C][/ROW]
[ROW][C]41[/C][C]0.406595[/C][C]0.81319[/C][C]0.593405[/C][/ROW]
[ROW][C]42[/C][C]0.384999[/C][C]0.769998[/C][C]0.615001[/C][/ROW]
[ROW][C]43[/C][C]0.365478[/C][C]0.730956[/C][C]0.634522[/C][/ROW]
[ROW][C]44[/C][C]0.324927[/C][C]0.649855[/C][C]0.675073[/C][/ROW]
[ROW][C]45[/C][C]0.417874[/C][C]0.835747[/C][C]0.582126[/C][/ROW]
[ROW][C]46[/C][C]0.50507[/C][C]0.98986[/C][C]0.49493[/C][/ROW]
[ROW][C]47[/C][C]0.487658[/C][C]0.975316[/C][C]0.512342[/C][/ROW]
[ROW][C]48[/C][C]0.45514[/C][C]0.910281[/C][C]0.54486[/C][/ROW]
[ROW][C]49[/C][C]0.471752[/C][C]0.943504[/C][C]0.528248[/C][/ROW]
[ROW][C]50[/C][C]0.488145[/C][C]0.976291[/C][C]0.511855[/C][/ROW]
[ROW][C]51[/C][C]0.46945[/C][C]0.9389[/C][C]0.53055[/C][/ROW]
[ROW][C]52[/C][C]0.442794[/C][C]0.885589[/C][C]0.557206[/C][/ROW]
[ROW][C]53[/C][C]0.425966[/C][C]0.851932[/C][C]0.574034[/C][/ROW]
[ROW][C]54[/C][C]0.395736[/C][C]0.791473[/C][C]0.604264[/C][/ROW]
[ROW][C]55[/C][C]0.392364[/C][C]0.784729[/C][C]0.607636[/C][/ROW]
[ROW][C]56[/C][C]0.359346[/C][C]0.718692[/C][C]0.640654[/C][/ROW]
[ROW][C]57[/C][C]0.421288[/C][C]0.842575[/C][C]0.578712[/C][/ROW]
[ROW][C]58[/C][C]0.422884[/C][C]0.845768[/C][C]0.577116[/C][/ROW]
[ROW][C]59[/C][C]0.406293[/C][C]0.812586[/C][C]0.593707[/C][/ROW]
[ROW][C]60[/C][C]0.380055[/C][C]0.76011[/C][C]0.619945[/C][/ROW]
[ROW][C]61[/C][C]0.350878[/C][C]0.701755[/C][C]0.649122[/C][/ROW]
[ROW][C]62[/C][C]0.370471[/C][C]0.740941[/C][C]0.629529[/C][/ROW]
[ROW][C]63[/C][C]0.386768[/C][C]0.773536[/C][C]0.613232[/C][/ROW]
[ROW][C]64[/C][C]0.362479[/C][C]0.724959[/C][C]0.637521[/C][/ROW]
[ROW][C]65[/C][C]0.40657[/C][C]0.813141[/C][C]0.59343[/C][/ROW]
[ROW][C]66[/C][C]0.384071[/C][C]0.768142[/C][C]0.615929[/C][/ROW]
[ROW][C]67[/C][C]0.407513[/C][C]0.815026[/C][C]0.592487[/C][/ROW]
[ROW][C]68[/C][C]0.386733[/C][C]0.773466[/C][C]0.613267[/C][/ROW]
[ROW][C]69[/C][C]0.405831[/C][C]0.811663[/C][C]0.594169[/C][/ROW]
[ROW][C]70[/C][C]0.412229[/C][C]0.824457[/C][C]0.587771[/C][/ROW]
[ROW][C]71[/C][C]0.446904[/C][C]0.893807[/C][C]0.553096[/C][/ROW]
[ROW][C]72[/C][C]0.479275[/C][C]0.95855[/C][C]0.520725[/C][/ROW]
[ROW][C]73[/C][C]0.512361[/C][C]0.975278[/C][C]0.487639[/C][/ROW]
[ROW][C]74[/C][C]0.497163[/C][C]0.994326[/C][C]0.502837[/C][/ROW]
[ROW][C]75[/C][C]0.512485[/C][C]0.97503[/C][C]0.487515[/C][/ROW]
[ROW][C]76[/C][C]0.5549[/C][C]0.8902[/C][C]0.4451[/C][/ROW]
[ROW][C]77[/C][C]0.530942[/C][C]0.938116[/C][C]0.469058[/C][/ROW]
[ROW][C]78[/C][C]0.554973[/C][C]0.890054[/C][C]0.445027[/C][/ROW]
[ROW][C]79[/C][C]0.538544[/C][C]0.922913[/C][C]0.461456[/C][/ROW]
[ROW][C]80[/C][C]0.526805[/C][C]0.946391[/C][C]0.473195[/C][/ROW]
[ROW][C]81[/C][C]0.553746[/C][C]0.892508[/C][C]0.446254[/C][/ROW]
[ROW][C]82[/C][C]0.550006[/C][C]0.899988[/C][C]0.449994[/C][/ROW]
[ROW][C]83[/C][C]0.557974[/C][C]0.884051[/C][C]0.442026[/C][/ROW]
[ROW][C]84[/C][C]0.538872[/C][C]0.922255[/C][C]0.461128[/C][/ROW]
[ROW][C]85[/C][C]0.513209[/C][C]0.973583[/C][C]0.486791[/C][/ROW]
[ROW][C]86[/C][C]0.502072[/C][C]0.995855[/C][C]0.497928[/C][/ROW]
[ROW][C]87[/C][C]0.4875[/C][C]0.975[/C][C]0.5125[/C][/ROW]
[ROW][C]88[/C][C]0.510959[/C][C]0.978083[/C][C]0.489041[/C][/ROW]
[ROW][C]89[/C][C]0.54271[/C][C]0.91458[/C][C]0.45729[/C][/ROW]
[ROW][C]90[/C][C]0.528545[/C][C]0.942911[/C][C]0.471455[/C][/ROW]
[ROW][C]91[/C][C]0.543416[/C][C]0.913168[/C][C]0.456584[/C][/ROW]
[ROW][C]92[/C][C]0.53431[/C][C]0.931381[/C][C]0.46569[/C][/ROW]
[ROW][C]93[/C][C]0.524618[/C][C]0.950763[/C][C]0.475382[/C][/ROW]
[ROW][C]94[/C][C]0.543626[/C][C]0.912748[/C][C]0.456374[/C][/ROW]
[ROW][C]95[/C][C]0.530691[/C][C]0.938618[/C][C]0.469309[/C][/ROW]
[ROW][C]96[/C][C]0.564115[/C][C]0.87177[/C][C]0.435885[/C][/ROW]
[ROW][C]97[/C][C]0.535802[/C][C]0.928395[/C][C]0.464198[/C][/ROW]
[ROW][C]98[/C][C]0.523299[/C][C]0.953401[/C][C]0.476701[/C][/ROW]
[ROW][C]99[/C][C]0.513775[/C][C]0.97245[/C][C]0.486225[/C][/ROW]
[ROW][C]100[/C][C]0.499522[/C][C]0.999043[/C][C]0.500478[/C][/ROW]
[ROW][C]101[/C][C]0.476306[/C][C]0.952613[/C][C]0.523694[/C][/ROW]
[ROW][C]102[/C][C]0.492244[/C][C]0.984487[/C][C]0.507756[/C][/ROW]
[ROW][C]103[/C][C]0.488105[/C][C]0.976209[/C][C]0.511895[/C][/ROW]
[ROW][C]104[/C][C]0.476958[/C][C]0.953915[/C][C]0.523042[/C][/ROW]
[ROW][C]105[/C][C]0.467577[/C][C]0.935154[/C][C]0.532423[/C][/ROW]
[ROW][C]106[/C][C]0.477393[/C][C]0.954786[/C][C]0.522607[/C][/ROW]
[ROW][C]107[/C][C]0.452356[/C][C]0.904712[/C][C]0.547644[/C][/ROW]
[ROW][C]108[/C][C]0.452961[/C][C]0.905922[/C][C]0.547039[/C][/ROW]
[ROW][C]109[/C][C]0.498693[/C][C]0.997385[/C][C]0.501307[/C][/ROW]
[ROW][C]110[/C][C]0.507215[/C][C]0.98557[/C][C]0.492785[/C][/ROW]
[ROW][C]111[/C][C]0.538964[/C][C]0.922071[/C][C]0.461036[/C][/ROW]
[ROW][C]112[/C][C]0.540149[/C][C]0.919702[/C][C]0.459851[/C][/ROW]
[ROW][C]113[/C][C]0.522029[/C][C]0.955943[/C][C]0.477971[/C][/ROW]
[ROW][C]114[/C][C]0.5197[/C][C]0.960599[/C][C]0.4803[/C][/ROW]
[ROW][C]115[/C][C]0.523437[/C][C]0.953126[/C][C]0.476563[/C][/ROW]
[ROW][C]116[/C][C]0.507996[/C][C]0.984009[/C][C]0.492004[/C][/ROW]
[ROW][C]117[/C][C]0.500448[/C][C]0.999104[/C][C]0.499552[/C][/ROW]
[ROW][C]118[/C][C]0.497644[/C][C]0.995289[/C][C]0.502356[/C][/ROW]
[ROW][C]119[/C][C]0.493131[/C][C]0.986262[/C][C]0.506869[/C][/ROW]
[ROW][C]120[/C][C]0.496915[/C][C]0.99383[/C][C]0.503085[/C][/ROW]
[ROW][C]121[/C][C]0.524803[/C][C]0.950394[/C][C]0.475197[/C][/ROW]
[ROW][C]122[/C][C]0.550041[/C][C]0.899917[/C][C]0.449959[/C][/ROW]
[ROW][C]123[/C][C]0.536456[/C][C]0.927088[/C][C]0.463544[/C][/ROW]
[ROW][C]124[/C][C]0.522739[/C][C]0.954522[/C][C]0.477261[/C][/ROW]
[ROW][C]125[/C][C]0.521128[/C][C]0.957745[/C][C]0.478872[/C][/ROW]
[ROW][C]126[/C][C]0.519138[/C][C]0.961723[/C][C]0.480862[/C][/ROW]
[ROW][C]127[/C][C]0.502104[/C][C]0.995793[/C][C]0.497896[/C][/ROW]
[ROW][C]128[/C][C]0.514343[/C][C]0.971314[/C][C]0.485657[/C][/ROW]
[ROW][C]129[/C][C]0.516636[/C][C]0.966728[/C][C]0.483364[/C][/ROW]
[ROW][C]130[/C][C]0.497754[/C][C]0.995507[/C][C]0.502246[/C][/ROW]
[ROW][C]131[/C][C]0.478125[/C][C]0.95625[/C][C]0.521875[/C][/ROW]
[ROW][C]132[/C][C]0.493976[/C][C]0.987951[/C][C]0.506024[/C][/ROW]
[ROW][C]133[/C][C]0.495562[/C][C]0.991124[/C][C]0.504438[/C][/ROW]
[ROW][C]134[/C][C]0.523856[/C][C]0.952287[/C][C]0.476144[/C][/ROW]
[ROW][C]135[/C][C]0.50459[/C][C]0.990819[/C][C]0.49541[/C][/ROW]
[ROW][C]136[/C][C]0.513372[/C][C]0.973256[/C][C]0.486628[/C][/ROW]
[ROW][C]137[/C][C]0.506768[/C][C]0.986465[/C][C]0.493232[/C][/ROW]
[ROW][C]138[/C][C]0.479328[/C][C]0.958657[/C][C]0.520672[/C][/ROW]
[ROW][C]139[/C][C]0.4943[/C][C]0.988601[/C][C]0.5057[/C][/ROW]
[ROW][C]140[/C][C]0.502158[/C][C]0.995683[/C][C]0.497842[/C][/ROW]
[ROW][C]141[/C][C]0.491915[/C][C]0.98383[/C][C]0.508085[/C][/ROW]
[ROW][C]142[/C][C]0.472796[/C][C]0.945593[/C][C]0.527204[/C][/ROW]
[ROW][C]143[/C][C]0.516742[/C][C]0.966516[/C][C]0.483258[/C][/ROW]
[ROW][C]144[/C][C]0.51167[/C][C]0.97666[/C][C]0.48833[/C][/ROW]
[ROW][C]145[/C][C]0.517541[/C][C]0.964918[/C][C]0.482459[/C][/ROW]
[ROW][C]146[/C][C]0.530403[/C][C]0.939193[/C][C]0.469597[/C][/ROW]
[ROW][C]147[/C][C]0.544443[/C][C]0.911115[/C][C]0.455557[/C][/ROW]
[ROW][C]148[/C][C]0.546439[/C][C]0.907123[/C][C]0.453561[/C][/ROW]
[ROW][C]149[/C][C]0.527721[/C][C]0.944557[/C][C]0.472279[/C][/ROW]
[ROW][C]150[/C][C]0.52027[/C][C]0.95946[/C][C]0.47973[/C][/ROW]
[ROW][C]151[/C][C]0.559068[/C][C]0.881863[/C][C]0.440932[/C][/ROW]
[ROW][C]152[/C][C]0.562768[/C][C]0.874465[/C][C]0.437232[/C][/ROW]
[ROW][C]153[/C][C]0.559733[/C][C]0.880533[/C][C]0.440267[/C][/ROW]
[ROW][C]154[/C][C]0.57484[/C][C]0.85032[/C][C]0.42516[/C][/ROW]
[ROW][C]155[/C][C]0.556563[/C][C]0.886875[/C][C]0.443437[/C][/ROW]
[ROW][C]156[/C][C]0.554428[/C][C]0.891144[/C][C]0.445572[/C][/ROW]
[ROW][C]157[/C][C]0.577216[/C][C]0.845568[/C][C]0.422784[/C][/ROW]
[ROW][C]158[/C][C]0.585814[/C][C]0.828373[/C][C]0.414186[/C][/ROW]
[ROW][C]159[/C][C]0.580286[/C][C]0.839427[/C][C]0.419714[/C][/ROW]
[ROW][C]160[/C][C]0.59351[/C][C]0.81298[/C][C]0.40649[/C][/ROW]
[ROW][C]161[/C][C]0.587854[/C][C]0.824291[/C][C]0.412146[/C][/ROW]
[ROW][C]162[/C][C]0.601056[/C][C]0.797889[/C][C]0.398944[/C][/ROW]
[ROW][C]163[/C][C]0.596314[/C][C]0.807372[/C][C]0.403686[/C][/ROW]
[ROW][C]164[/C][C]0.603421[/C][C]0.793158[/C][C]0.396579[/C][/ROW]
[ROW][C]165[/C][C]0.593994[/C][C]0.812012[/C][C]0.406006[/C][/ROW]
[ROW][C]166[/C][C]0.576755[/C][C]0.84649[/C][C]0.423245[/C][/ROW]
[ROW][C]167[/C][C]0.575637[/C][C]0.848727[/C][C]0.424363[/C][/ROW]
[ROW][C]168[/C][C]0.55579[/C][C]0.888419[/C][C]0.44421[/C][/ROW]
[ROW][C]169[/C][C]0.575017[/C][C]0.849966[/C][C]0.424983[/C][/ROW]
[ROW][C]170[/C][C]0.577889[/C][C]0.844222[/C][C]0.422111[/C][/ROW]
[ROW][C]171[/C][C]0.58446[/C][C]0.83108[/C][C]0.41554[/C][/ROW]
[ROW][C]172[/C][C]0.586067[/C][C]0.827865[/C][C]0.413933[/C][/ROW]
[ROW][C]173[/C][C]0.573666[/C][C]0.852669[/C][C]0.426334[/C][/ROW]
[ROW][C]174[/C][C]0.557497[/C][C]0.885006[/C][C]0.442503[/C][/ROW]
[ROW][C]175[/C][C]0.542188[/C][C]0.915623[/C][C]0.457812[/C][/ROW]
[ROW][C]176[/C][C]0.563811[/C][C]0.872378[/C][C]0.436189[/C][/ROW]
[ROW][C]177[/C][C]0.557924[/C][C]0.884152[/C][C]0.442076[/C][/ROW]
[ROW][C]178[/C][C]0.555555[/C][C]0.888889[/C][C]0.444445[/C][/ROW]
[ROW][C]179[/C][C]0.549694[/C][C]0.900611[/C][C]0.450306[/C][/ROW]
[ROW][C]180[/C][C]0.597036[/C][C]0.805928[/C][C]0.402964[/C][/ROW]
[ROW][C]181[/C][C]0.597963[/C][C]0.804075[/C][C]0.402037[/C][/ROW]
[ROW][C]182[/C][C]0.616871[/C][C]0.766259[/C][C]0.383129[/C][/ROW]
[ROW][C]183[/C][C]0.650742[/C][C]0.698516[/C][C]0.349258[/C][/ROW]
[ROW][C]184[/C][C]0.649484[/C][C]0.701033[/C][C]0.350516[/C][/ROW]
[ROW][C]185[/C][C]0.629531[/C][C]0.740939[/C][C]0.370469[/C][/ROW]
[ROW][C]186[/C][C]0.630709[/C][C]0.738581[/C][C]0.369291[/C][/ROW]
[ROW][C]187[/C][C]0.641347[/C][C]0.717307[/C][C]0.358653[/C][/ROW]
[ROW][C]188[/C][C]0.67133[/C][C]0.657341[/C][C]0.32867[/C][/ROW]
[ROW][C]189[/C][C]0.730335[/C][C]0.539331[/C][C]0.269665[/C][/ROW]
[ROW][C]190[/C][C]0.722831[/C][C]0.554338[/C][C]0.277169[/C][/ROW]
[ROW][C]191[/C][C]0.702069[/C][C]0.595862[/C][C]0.297931[/C][/ROW]
[ROW][C]192[/C][C]0.751604[/C][C]0.496792[/C][C]0.248396[/C][/ROW]
[ROW][C]193[/C][C]0.73548[/C][C]0.52904[/C][C]0.26452[/C][/ROW]
[ROW][C]194[/C][C]0.716275[/C][C]0.567449[/C][C]0.283725[/C][/ROW]
[ROW][C]195[/C][C]0.706803[/C][C]0.586394[/C][C]0.293197[/C][/ROW]
[ROW][C]196[/C][C]0.709309[/C][C]0.581382[/C][C]0.290691[/C][/ROW]
[ROW][C]197[/C][C]0.716002[/C][C]0.567997[/C][C]0.283998[/C][/ROW]
[ROW][C]198[/C][C]0.697511[/C][C]0.604978[/C][C]0.302489[/C][/ROW]
[ROW][C]199[/C][C]0.699363[/C][C]0.601275[/C][C]0.300637[/C][/ROW]
[ROW][C]200[/C][C]0.688056[/C][C]0.623888[/C][C]0.311944[/C][/ROW]
[ROW][C]201[/C][C]0.699896[/C][C]0.600208[/C][C]0.300104[/C][/ROW]
[ROW][C]202[/C][C]0.694485[/C][C]0.611031[/C][C]0.305515[/C][/ROW]
[ROW][C]203[/C][C]0.710384[/C][C]0.579232[/C][C]0.289616[/C][/ROW]
[ROW][C]204[/C][C]0.721221[/C][C]0.557559[/C][C]0.278779[/C][/ROW]
[ROW][C]205[/C][C]0.698704[/C][C]0.602592[/C][C]0.301296[/C][/ROW]
[ROW][C]206[/C][C]0.714727[/C][C]0.570546[/C][C]0.285273[/C][/ROW]
[ROW][C]207[/C][C]0.697714[/C][C]0.604572[/C][C]0.302286[/C][/ROW]
[ROW][C]208[/C][C]0.682748[/C][C]0.634504[/C][C]0.317252[/C][/ROW]
[ROW][C]209[/C][C]0.64734[/C][C]0.70532[/C][C]0.35266[/C][/ROW]
[ROW][C]210[/C][C]0.697841[/C][C]0.604318[/C][C]0.302159[/C][/ROW]
[ROW][C]211[/C][C]0.685933[/C][C]0.628133[/C][C]0.314067[/C][/ROW]
[ROW][C]212[/C][C]0.664193[/C][C]0.671614[/C][C]0.335807[/C][/ROW]
[ROW][C]213[/C][C]0.66181[/C][C]0.676379[/C][C]0.33819[/C][/ROW]
[ROW][C]214[/C][C]0.685031[/C][C]0.629939[/C][C]0.314969[/C][/ROW]
[ROW][C]215[/C][C]0.672244[/C][C]0.655513[/C][C]0.327756[/C][/ROW]
[ROW][C]216[/C][C]0.667533[/C][C]0.664934[/C][C]0.332467[/C][/ROW]
[ROW][C]217[/C][C]0.70176[/C][C]0.596479[/C][C]0.29824[/C][/ROW]
[ROW][C]218[/C][C]0.699455[/C][C]0.601089[/C][C]0.300545[/C][/ROW]
[ROW][C]219[/C][C]0.684443[/C][C]0.631113[/C][C]0.315557[/C][/ROW]
[ROW][C]220[/C][C]0.680985[/C][C]0.638029[/C][C]0.319015[/C][/ROW]
[ROW][C]221[/C][C]0.668126[/C][C]0.663749[/C][C]0.331874[/C][/ROW]
[ROW][C]222[/C][C]0.715351[/C][C]0.569298[/C][C]0.284649[/C][/ROW]
[ROW][C]223[/C][C]0.686224[/C][C]0.627552[/C][C]0.313776[/C][/ROW]
[ROW][C]224[/C][C]0.69018[/C][C]0.61964[/C][C]0.30982[/C][/ROW]
[ROW][C]225[/C][C]0.658491[/C][C]0.683019[/C][C]0.341509[/C][/ROW]
[ROW][C]226[/C][C]0.656244[/C][C]0.687512[/C][C]0.343756[/C][/ROW]
[ROW][C]227[/C][C]0.656304[/C][C]0.687393[/C][C]0.343696[/C][/ROW]
[ROW][C]228[/C][C]0.664818[/C][C]0.670363[/C][C]0.335182[/C][/ROW]
[ROW][C]229[/C][C]0.777948[/C][C]0.444104[/C][C]0.222052[/C][/ROW]
[ROW][C]230[/C][C]0.756815[/C][C]0.48637[/C][C]0.243185[/C][/ROW]
[ROW][C]231[/C][C]0.776326[/C][C]0.447348[/C][C]0.223674[/C][/ROW]
[ROW][C]232[/C][C]0.746652[/C][C]0.506697[/C][C]0.253348[/C][/ROW]
[ROW][C]233[/C][C]0.731762[/C][C]0.536475[/C][C]0.268238[/C][/ROW]
[ROW][C]234[/C][C]0.693767[/C][C]0.612466[/C][C]0.306233[/C][/ROW]
[ROW][C]235[/C][C]0.657303[/C][C]0.685395[/C][C]0.342697[/C][/ROW]
[ROW][C]236[/C][C]0.610413[/C][C]0.779173[/C][C]0.389587[/C][/ROW]
[ROW][C]237[/C][C]0.679178[/C][C]0.641644[/C][C]0.320822[/C][/ROW]
[ROW][C]238[/C][C]0.679499[/C][C]0.641002[/C][C]0.320501[/C][/ROW]
[ROW][C]239[/C][C]0.697642[/C][C]0.604715[/C][C]0.302358[/C][/ROW]
[ROW][C]240[/C][C]0.675513[/C][C]0.648973[/C][C]0.324487[/C][/ROW]
[ROW][C]241[/C][C]0.664893[/C][C]0.670214[/C][C]0.335107[/C][/ROW]
[ROW][C]242[/C][C]0.67804[/C][C]0.64392[/C][C]0.32196[/C][/ROW]
[ROW][C]243[/C][C]0.67424[/C][C]0.651521[/C][C]0.32576[/C][/ROW]
[ROW][C]244[/C][C]0.627607[/C][C]0.744786[/C][C]0.372393[/C][/ROW]
[ROW][C]245[/C][C]0.584198[/C][C]0.831605[/C][C]0.415802[/C][/ROW]
[ROW][C]246[/C][C]0.631179[/C][C]0.737641[/C][C]0.368821[/C][/ROW]
[ROW][C]247[/C][C]0.577818[/C][C]0.844363[/C][C]0.422182[/C][/ROW]
[ROW][C]248[/C][C]0.551415[/C][C]0.89717[/C][C]0.448585[/C][/ROW]
[ROW][C]249[/C][C]0.504273[/C][C]0.991454[/C][C]0.495727[/C][/ROW]
[ROW][C]250[/C][C]0.478372[/C][C]0.956744[/C][C]0.521628[/C][/ROW]
[ROW][C]251[/C][C]0.431482[/C][C]0.862964[/C][C]0.568518[/C][/ROW]
[ROW][C]252[/C][C]0.445204[/C][C]0.890408[/C][C]0.554796[/C][/ROW]
[ROW][C]253[/C][C]0.494628[/C][C]0.989257[/C][C]0.505372[/C][/ROW]
[ROW][C]254[/C][C]0.450522[/C][C]0.901044[/C][C]0.549478[/C][/ROW]
[ROW][C]255[/C][C]0.540756[/C][C]0.918489[/C][C]0.459244[/C][/ROW]
[ROW][C]256[/C][C]0.488378[/C][C]0.976755[/C][C]0.511622[/C][/ROW]
[ROW][C]257[/C][C]0.427931[/C][C]0.855862[/C][C]0.572069[/C][/ROW]
[ROW][C]258[/C][C]0.58375[/C][C]0.832501[/C][C]0.41625[/C][/ROW]
[ROW][C]259[/C][C]0.606927[/C][C]0.786146[/C][C]0.393073[/C][/ROW]
[ROW][C]260[/C][C]0.532944[/C][C]0.934111[/C][C]0.467056[/C][/ROW]
[ROW][C]261[/C][C]0.470179[/C][C]0.940357[/C][C]0.529821[/C][/ROW]
[ROW][C]262[/C][C]0.637964[/C][C]0.724071[/C][C]0.362036[/C][/ROW]
[ROW][C]263[/C][C]0.553876[/C][C]0.892248[/C][C]0.446124[/C][/ROW]
[ROW][C]264[/C][C]0.654406[/C][C]0.691187[/C][C]0.345594[/C][/ROW]
[ROW][C]265[/C][C]0.55606[/C][C]0.88788[/C][C]0.44394[/C][/ROW]
[ROW][C]266[/C][C]0.473674[/C][C]0.947348[/C][C]0.526326[/C][/ROW]
[ROW][C]267[/C][C]0.512656[/C][C]0.974689[/C][C]0.487344[/C][/ROW]
[ROW][C]268[/C][C]0.387671[/C][C]0.775341[/C][C]0.612329[/C][/ROW]
[ROW][C]269[/C][C]0.541033[/C][C]0.917933[/C][C]0.458967[/C][/ROW]
[ROW][C]270[/C][C]0.380963[/C][C]0.761927[/C][C]0.619037[/C][/ROW]
[ROW][C]271[/C][C]0.22161[/C][C]0.44322[/C][C]0.77839[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264929&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264929&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.657920.6841590.34208
90.5089250.9821510.491075
100.447420.8948390.55258
110.5596990.8806010.440301
120.4818920.9637840.518108
130.41980.8396010.5802
140.4862250.972450.513775
150.6566050.6867890.343395
160.5991260.8017470.400874
170.5576890.8846210.442311
180.4998390.9996790.500161
190.4220880.8441750.577912
200.3739370.7478730.626063
210.3065890.6131790.693411
220.333550.66710.66645
230.5125120.9749760.487488
240.4901350.980270.509865
250.4695440.9390880.530456
260.5304550.9390910.469545
270.5205450.958910.479455
280.4770310.9540620.522969
290.430650.86130.56935
300.4058710.8117420.594129
310.3541620.7083240.645838
320.3907750.7815490.609225
330.3676870.7353740.632313
340.3176190.6352380.682381
350.3797280.7594570.620272
360.4333620.8667230.566638
370.3843820.7687650.615618
380.4285680.8571370.571432
390.3850270.7700550.614973
400.4359470.8718940.564053
410.4065950.813190.593405
420.3849990.7699980.615001
430.3654780.7309560.634522
440.3249270.6498550.675073
450.4178740.8357470.582126
460.505070.989860.49493
470.4876580.9753160.512342
480.455140.9102810.54486
490.4717520.9435040.528248
500.4881450.9762910.511855
510.469450.93890.53055
520.4427940.8855890.557206
530.4259660.8519320.574034
540.3957360.7914730.604264
550.3923640.7847290.607636
560.3593460.7186920.640654
570.4212880.8425750.578712
580.4228840.8457680.577116
590.4062930.8125860.593707
600.3800550.760110.619945
610.3508780.7017550.649122
620.3704710.7409410.629529
630.3867680.7735360.613232
640.3624790.7249590.637521
650.406570.8131410.59343
660.3840710.7681420.615929
670.4075130.8150260.592487
680.3867330.7734660.613267
690.4058310.8116630.594169
700.4122290.8244570.587771
710.4469040.8938070.553096
720.4792750.958550.520725
730.5123610.9752780.487639
740.4971630.9943260.502837
750.5124850.975030.487515
760.55490.89020.4451
770.5309420.9381160.469058
780.5549730.8900540.445027
790.5385440.9229130.461456
800.5268050.9463910.473195
810.5537460.8925080.446254
820.5500060.8999880.449994
830.5579740.8840510.442026
840.5388720.9222550.461128
850.5132090.9735830.486791
860.5020720.9958550.497928
870.48750.9750.5125
880.5109590.9780830.489041
890.542710.914580.45729
900.5285450.9429110.471455
910.5434160.9131680.456584
920.534310.9313810.46569
930.5246180.9507630.475382
940.5436260.9127480.456374
950.5306910.9386180.469309
960.5641150.871770.435885
970.5358020.9283950.464198
980.5232990.9534010.476701
990.5137750.972450.486225
1000.4995220.9990430.500478
1010.4763060.9526130.523694
1020.4922440.9844870.507756
1030.4881050.9762090.511895
1040.4769580.9539150.523042
1050.4675770.9351540.532423
1060.4773930.9547860.522607
1070.4523560.9047120.547644
1080.4529610.9059220.547039
1090.4986930.9973850.501307
1100.5072150.985570.492785
1110.5389640.9220710.461036
1120.5401490.9197020.459851
1130.5220290.9559430.477971
1140.51970.9605990.4803
1150.5234370.9531260.476563
1160.5079960.9840090.492004
1170.5004480.9991040.499552
1180.4976440.9952890.502356
1190.4931310.9862620.506869
1200.4969150.993830.503085
1210.5248030.9503940.475197
1220.5500410.8999170.449959
1230.5364560.9270880.463544
1240.5227390.9545220.477261
1250.5211280.9577450.478872
1260.5191380.9617230.480862
1270.5021040.9957930.497896
1280.5143430.9713140.485657
1290.5166360.9667280.483364
1300.4977540.9955070.502246
1310.4781250.956250.521875
1320.4939760.9879510.506024
1330.4955620.9911240.504438
1340.5238560.9522870.476144
1350.504590.9908190.49541
1360.5133720.9732560.486628
1370.5067680.9864650.493232
1380.4793280.9586570.520672
1390.49430.9886010.5057
1400.5021580.9956830.497842
1410.4919150.983830.508085
1420.4727960.9455930.527204
1430.5167420.9665160.483258
1440.511670.976660.48833
1450.5175410.9649180.482459
1460.5304030.9391930.469597
1470.5444430.9111150.455557
1480.5464390.9071230.453561
1490.5277210.9445570.472279
1500.520270.959460.47973
1510.5590680.8818630.440932
1520.5627680.8744650.437232
1530.5597330.8805330.440267
1540.574840.850320.42516
1550.5565630.8868750.443437
1560.5544280.8911440.445572
1570.5772160.8455680.422784
1580.5858140.8283730.414186
1590.5802860.8394270.419714
1600.593510.812980.40649
1610.5878540.8242910.412146
1620.6010560.7978890.398944
1630.5963140.8073720.403686
1640.6034210.7931580.396579
1650.5939940.8120120.406006
1660.5767550.846490.423245
1670.5756370.8487270.424363
1680.555790.8884190.44421
1690.5750170.8499660.424983
1700.5778890.8442220.422111
1710.584460.831080.41554
1720.5860670.8278650.413933
1730.5736660.8526690.426334
1740.5574970.8850060.442503
1750.5421880.9156230.457812
1760.5638110.8723780.436189
1770.5579240.8841520.442076
1780.5555550.8888890.444445
1790.5496940.9006110.450306
1800.5970360.8059280.402964
1810.5979630.8040750.402037
1820.6168710.7662590.383129
1830.6507420.6985160.349258
1840.6494840.7010330.350516
1850.6295310.7409390.370469
1860.6307090.7385810.369291
1870.6413470.7173070.358653
1880.671330.6573410.32867
1890.7303350.5393310.269665
1900.7228310.5543380.277169
1910.7020690.5958620.297931
1920.7516040.4967920.248396
1930.735480.529040.26452
1940.7162750.5674490.283725
1950.7068030.5863940.293197
1960.7093090.5813820.290691
1970.7160020.5679970.283998
1980.6975110.6049780.302489
1990.6993630.6012750.300637
2000.6880560.6238880.311944
2010.6998960.6002080.300104
2020.6944850.6110310.305515
2030.7103840.5792320.289616
2040.7212210.5575590.278779
2050.6987040.6025920.301296
2060.7147270.5705460.285273
2070.6977140.6045720.302286
2080.6827480.6345040.317252
2090.647340.705320.35266
2100.6978410.6043180.302159
2110.6859330.6281330.314067
2120.6641930.6716140.335807
2130.661810.6763790.33819
2140.6850310.6299390.314969
2150.6722440.6555130.327756
2160.6675330.6649340.332467
2170.701760.5964790.29824
2180.6994550.6010890.300545
2190.6844430.6311130.315557
2200.6809850.6380290.319015
2210.6681260.6637490.331874
2220.7153510.5692980.284649
2230.6862240.6275520.313776
2240.690180.619640.30982
2250.6584910.6830190.341509
2260.6562440.6875120.343756
2270.6563040.6873930.343696
2280.6648180.6703630.335182
2290.7779480.4441040.222052
2300.7568150.486370.243185
2310.7763260.4473480.223674
2320.7466520.5066970.253348
2330.7317620.5364750.268238
2340.6937670.6124660.306233
2350.6573030.6853950.342697
2360.6104130.7791730.389587
2370.6791780.6416440.320822
2380.6794990.6410020.320501
2390.6976420.6047150.302358
2400.6755130.6489730.324487
2410.6648930.6702140.335107
2420.678040.643920.32196
2430.674240.6515210.32576
2440.6276070.7447860.372393
2450.5841980.8316050.415802
2460.6311790.7376410.368821
2470.5778180.8443630.422182
2480.5514150.897170.448585
2490.5042730.9914540.495727
2500.4783720.9567440.521628
2510.4314820.8629640.568518
2520.4452040.8904080.554796
2530.4946280.9892570.505372
2540.4505220.9010440.549478
2550.5407560.9184890.459244
2560.4883780.9767550.511622
2570.4279310.8558620.572069
2580.583750.8325010.41625
2590.6069270.7861460.393073
2600.5329440.9341110.467056
2610.4701790.9403570.529821
2620.6379640.7240710.362036
2630.5538760.8922480.446124
2640.6544060.6911870.345594
2650.556060.887880.44394
2660.4736740.9473480.526326
2670.5126560.9746890.487344
2680.3876710.7753410.612329
2690.5410330.9179330.458967
2700.3809630.7619270.619037
2710.221610.443220.77839






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

\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 & 0 & 0 & OK \tabularnewline
10% type I error level & 0 & 0 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264929&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264929&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264929&T=6

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

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


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$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')
}