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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 09 Dec 2014 09:58:52 +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/09/t1418119205nn5zcdflhzo6q1z.htm/, Retrieved Thu, 31 Oct 2024 23:50:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264381, Retrieved Thu, 31 Oct 2024 23:50:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- RM D  [Multiple Regression] [] [2014-11-12 15:17:36] [dacad244957cb51472792888970d4390]
-   PD    [Multiple Regression] [] [2014-12-02 10:56:23] [dacad244957cb51472792888970d4390]
-   PD        [Multiple Regression] [] [2014-12-09 09:58:52] [a4daf178ee9972867aacc2039fa7f163] [Current]
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Dataseries X:
1 0 0 21 149 12.9
1 0 1 22 139 12.2
1 0 0 22 148 12.8
1 0 1 18 158 7.4
1 0 1 23 128 6.7
1 0 1 12 224 12.6
1 0 0 20 159 14.8
1 0 1 22 105 13.3
1 0 1 21 159 11.1
1 0 1 19 167 8.2
1 0 1 22 165 11.4
1 0 1 15 159 6.4
1 0 1 20 119 10.6
1 0 0 19 176 12.0
1 0 0 18 54 6.3
0 0 0 15 91 11.3
1 0 1 20 163 11.9
1 0 0 21 124 9.3
0 0 1 21 137 9.6
1 0 0 15 121 10.0
1 0 1 16 153 6.4
1 0 1 23 148 13.8
1 0 0 21 221 10.8
1 0 1 18 188 13.8
1 0 1 25 149 11.7
1 0 1 9 244 10.9
0 0 1 30 148 16.1
0 0 0 20 92 13.4
1 0 1 23 150 9.9
1 0 0 16 153 11.5
1 0 0 16 94 8.3
1 0 0 19 156 11.7
1 0 1 25 132 9.0
1 0 1 18 161 9.7
1 0 1 23 105 10.8
1 0 1 21 97 10.3
1 0 0 10 151 10.4
0 0 1 14 131 12.7
1 0 1 22 166 9.3
1 0 0 26 157 11.8
1 0 1 23 111 5.9
1 0 1 23 145 11.4
1 0 1 24 162 13.0
1 0 1 24 163 10.8
0 0 1 18 59 12.3
1 0 0 23 187 11.3
1 0 1 15 109 11.8
0 0 1 19 90 7.9
1 0 0 16 105 12.7
0 0 1 25 83 12.3
0 0 1 23 116 11.6
0 0 1 17 42 6.7
1 0 1 19 148 10.9
0 0 1 21 155 12.1
1 0 1 18 125 13.3
1 0 1 27 116 10.1
0 0 0 21 128 5.7
1 0 1 13 138 14.3
0 0 0 8 49 8.0
0 0 1 29 96 13.3
1 0 1 28 164 9.3
1 0 0 23 162 12.5
1 0 0 21 99 7.6
1 0 1 19 202 15.9
1 0 0 19 186 9.2
0 0 1 20 66 9.1
1 0 0 18 183 11.1
1 0 1 19 214 13.0
1 0 1 17 188 14.5
0 0 0 19 104 12.2
1 0 0 25 177 12.3
1 0 0 19 126 11.4
0 0 0 22 76 8.8
0 0 1 23 99 14.6
1 0 0 14 139 12.6
1 0 1 28 78 NA
1 0 0 16 162 13.0
0 0 1 24 108 12.6
1 0 0 20 159 13.2
0 0 0 12 74 9.9
1 0 1 24 110 7.7
0 0 0 22 96 10.5
0 0 0 12 116 13.4
0 0 0 22 87 10.9
0 0 1 20 97 4.3
0 0 0 10 127 10.3
0 0 1 23 106 11.8
0 0 1 17 80 11.2
0 0 0 22 74 11.4
0 0 0 24 91 8.6
0 0 0 18 133 13.2
0 0 1 21 74 12.6
0 0 1 20 114 5.6
0 0 1 20 140 9.9
0 0 0 22 95 8.8
0 0 1 19 98 7.7
0 0 0 20 121 9.0
0 0 1 26 126 7.3
0 0 1 23 98 11.4
0 0 1 24 95 13.6
0 0 1 21 110 7.9
0 0 1 21 70 10.7
0 0 0 19 102 10.3
0 0 1 8 86 8.3
0 0 1 17 130 9.6
0 0 1 20 96 14.2
0 0 0 11 102 8.5
0 0 0 8 100 13.5
0 0 0 15 94 4.9
0 0 0 18 52 6.4
0 0 0 18 98 9.6
0 0 0 19 118 11.6
0 0 1 19 99 11.1
1 1 1 23 48 4.35
1 1 1 22 50 12.7
1 1 1 21 150 18.1
1 1 1 25 154 17.85
0 1 0 30 109 16.6
0 1 1 17 68 12.6
1 1 1 27 194 17.1
1 1 0 23 158 19.1
1 1 1 23 159 16.1
1 1 0 18 67 13.35
1 1 0 18 147 18.4
1 1 1 23 39 14.7
1 1 1 19 100 10.6
1 1 1 15 111 12.6
1 1 1 20 138 16.2
1 1 1 16 101 13.6
0 1 1 24 131 18.9
1 1 1 25 101 14.1
1 1 1 25 114 14.5
1 1 0 19 165 16.15
1 1 1 19 114 14.75
1 1 1 16 111 14.8
1 1 1 19 75 12.45
1 1 1 19 82 12.65
1 1 1 23 121 17.35
1 1 1 21 32 8.6
1 1 0 22 150 18.4
1 1 1 19 117 16.1
0 1 1 20 71 11.6
1 1 1 20 165 17.75
1 1 1 3 154 15.25
1 1 1 23 126 17.65
1 1 0 23 149 16.35
1 1 0 20 145 17.65
1 1 1 15 120 13.6
1 1 0 16 109 14.35
1 1 0 7 132 14.75
1 1 1 24 172 18.25
1 1 0 17 169 9.9
1 1 1 24 114 16
1 1 1 24 156 18.25
1 1 0 19 172 16.85
0 1 1 25 68 14.6
0 1 1 20 89 13.85
1 1 1 28 167 18.95
1 1 0 23 113 15.6
0 1 0 27 115 14.85
0 1 0 18 78 11.75
0 1 0 28 118 18.45
0 1 1 21 87 15.9
1 1 0 19 173 17.1
1 1 1 23 2 16.1
0 1 0 27 162 19.9
0 1 1 22 49 10.95
0 1 0 28 122 18.45
0 1 1 25 96 15.1
0 1 0 21 100 15
0 1 0 22 82 11.35
0 1 1 28 100 15.95
0 1 0 20 115 18.1
0 1 1 29 141 14.6
1 1 1 25 165 15.4
1 1 1 25 165 15.4
0 1 1 20 110 17.6
1 1 1 20 118 13.35
1 1 0 16 158 19.1
0 1 1 20 146 15.35
1 1 0 20 49 7.6
0 1 0 23 90 13.4
0 1 0 18 121 13.9
1 1 1 25 155 19.1
0 1 0 18 104 15.25
0 1 1 19 147 12.9
0 1 0 25 110 16.1
0 1 0 25 108 17.35
0 1 0 25 113 13.15
0 1 0 24 115 12.15
0 1 1 19 61 12.6
0 1 1 26 60 10.35
0 1 1 10 109 15.4
0 1 1 17 68 9.6
0 1 0 13 111 18.2
0 1 0 17 77 13.6
0 1 1 30 73 14.85
1 1 0 25 151 14.75
0 1 0 4 89 14.1
0 1 0 16 78 14.9
0 1 0 21 110 16.25
1 1 1 23 220 19.25
0 1 1 22 65 13.6
1 1 0 17 141 13.6
0 1 0 20 117 15.65
1 1 1 20 122 12.75
0 1 0 22 63 14.6
1 1 1 16 44 9.85
0 1 1 23 52 12.65
0 1 0 0 131 19.2
0 1 1 18 101 16.6
0 1 1 25 42 11.2
1 1 1 23 152 15.25
1 1 0 12 107 11.9
0 1 0 18 77 13.2
1 1 0 24 154 16.35
1 1 1 11 103 12.4
0 1 1 18 96 15.85
1 1 1 23 175 18.15
0 1 1 24 57 11.15
0 1 0 29 112 15.65
1 1 0 18 143 17.75
0 1 0 15 49 7.65
1 1 1 29 110 12.35
1 1 1 16 131 15.6
1 1 0 19 167 19.3
0 1 0 22 56 15.2
1 1 0 16 137 17.1
0 1 1 23 86 15.6
1 1 1 23 121 18.4
1 1 0 19 149 19.05
1 1 0 4 168 18.55
1 1 0 20 140 19.1
0 1 1 24 88 13.1
1 1 1 20 168 12.85
1 1 1 4 94 9.5
1 1 1 24 51 4.5
0 1 0 22 48 11.85
1 1 1 16 145 13.6
1 1 1 3 66 11.7
0 1 1 15 85 12.4
1 1 0 24 109 13.35
0 1 0 17 63 11.4
0 1 1 20 102 14.9
0 1 0 27 162 19.9
0 1 1 26 86 11.2
0 1 1 23 114 14.6
1 1 0 17 164 17.6
1 1 1 20 119 14.05
1 1 0 22 126 16.1
1 1 1 19 132 13.35
1 1 1 24 142 11.85
1 1 0 19 83 11.95
0 1 1 23 94 14.75
0 1 0 15 81 15.15
1 1 1 27 166 13.2
0 1 0 26 110 16.85
0 1 1 22 64 7.85
1 1 0 22 93 7.7
0 1 0 18 104 12.6
0 1 1 15 105 7.85
0 1 1 22 49 10.95
0 1 0 27 88 12.35
0 1 1 10 95 9.95
0 1 1 20 102 14.9
0 1 0 17 99 16.65
0 1 1 23 63 13.4
0 1 0 19 76 13.95
0 1 0 13 109 15.7
0 1 1 27 117 16.85
0 1 1 23 57 10.95
0 1 0 16 120 15.35
0 1 1 25 73 12.2
0 1 0 2 91 15.1
0 1 0 26 108 17.75
0 1 1 20 105 15.2
1 1 0 23 117 14.6
0 1 0 22 119 16.65
0 1 1 24 31 8.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264381&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264381&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264381&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 5.03175 -1.07904groepn[t] + 4.49299jaarInd[t] -0.663961gender[t] + 0.0522913NUMERACYTOT[t] + 0.0441851LFM[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  5.03175 -1.07904groepn[t] +  4.49299jaarInd[t] -0.663961gender[t] +  0.0522913NUMERACYTOT[t] +  0.0441851LFM[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264381&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  5.03175 -1.07904groepn[t] +  4.49299jaarInd[t] -0.663961gender[t] +  0.0522913NUMERACYTOT[t] +  0.0441851LFM[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264381&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264381&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 5.03175 -1.07904groepn[t] + 4.49299jaarInd[t] -0.663961gender[t] + 0.0522913NUMERACYTOT[t] + 0.0441851LFM[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.031750.7457756.7479.06007e-114.53004e-11
groepn-1.079040.334622-3.2250.001415170.000707584
jaarInd4.492990.29673415.145.55359e-382.7768e-38
gender-0.6639610.292666-2.2690.02407280.0120364
NUMERACYTOT0.05229130.02822961.8520.06505750.0325288
LFM0.04418510.0042840110.312.87933e-211.43967e-21

\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) & 5.03175 & 0.745775 & 6.747 & 9.06007e-11 & 4.53004e-11 \tabularnewline
groepn & -1.07904 & 0.334622 & -3.225 & 0.00141517 & 0.000707584 \tabularnewline
jaarInd & 4.49299 & 0.296734 & 15.14 & 5.55359e-38 & 2.7768e-38 \tabularnewline
gender & -0.663961 & 0.292666 & -2.269 & 0.0240728 & 0.0120364 \tabularnewline
NUMERACYTOT & 0.0522913 & 0.0282296 & 1.852 & 0.0650575 & 0.0325288 \tabularnewline
LFM & 0.0441851 & 0.00428401 & 10.31 & 2.87933e-21 & 1.43967e-21 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264381&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]5.03175[/C][C]0.745775[/C][C]6.747[/C][C]9.06007e-11[/C][C]4.53004e-11[/C][/ROW]
[ROW][C]groepn[/C][C]-1.07904[/C][C]0.334622[/C][C]-3.225[/C][C]0.00141517[/C][C]0.000707584[/C][/ROW]
[ROW][C]jaarInd[/C][C]4.49299[/C][C]0.296734[/C][C]15.14[/C][C]5.55359e-38[/C][C]2.7768e-38[/C][/ROW]
[ROW][C]gender[/C][C]-0.663961[/C][C]0.292666[/C][C]-2.269[/C][C]0.0240728[/C][C]0.0120364[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0522913[/C][C]0.0282296[/C][C]1.852[/C][C]0.0650575[/C][C]0.0325288[/C][/ROW]
[ROW][C]LFM[/C][C]0.0441851[/C][C]0.00428401[/C][C]10.31[/C][C]2.87933e-21[/C][C]1.43967e-21[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264381&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264381&T=2

As an alternative you can also use a 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)5.031750.7457756.7479.06007e-114.53004e-11
groepn-1.079040.334622-3.2250.001415170.000707584
jaarInd4.492990.29673415.145.55359e-382.7768e-38
gender-0.6639610.292666-2.2690.02407280.0120364
NUMERACYTOT0.05229130.02822961.8520.06505750.0325288
LFM0.04418510.0042840110.312.87933e-211.43967e-21







Multiple Linear Regression - Regression Statistics
Multiple R0.727244
R-squared0.528884
Adjusted R-squared0.520224
F-TEST (value)61.0706
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.35113
Sum Squared Residuals1503.57

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.727244 \tabularnewline
R-squared & 0.528884 \tabularnewline
Adjusted R-squared & 0.520224 \tabularnewline
F-TEST (value) & 61.0706 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 272 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.35113 \tabularnewline
Sum Squared Residuals & 1503.57 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264381&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.727244[/C][/ROW]
[ROW][C]R-squared[/C][C]0.528884[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.520224[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]61.0706[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]272[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.35113[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1503.57[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264381&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264381&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.727244
R-squared0.528884
Adjusted R-squared0.520224
F-TEST (value)61.0706
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.35113
Sum Squared Residuals1503.57







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.63441.2656
212.210.58091.61912
312.811.64251.15749
47.411.2112-3.81123
56.710.1471-3.44714
612.613.8137-1.2137
714.812.0242.77604
813.39.078594.22141
911.111.4123-0.312293
108.211.6612-3.46119
1111.411.7297-0.329695
126.411.0985-4.69855
1310.69.59261.0074
141212.7228-0.722818
156.37.27994-0.979944
1611.39.836961.46304
1711.911.53670.363257
189.310.5298-1.22978
199.611.5193-1.91927
201010.0835-0.0834722
216.410.8857-4.48573
2213.811.03082.76916
2310.814.8157-4.01573
2413.812.53681.26321
2511.711.17960.520393
2610.914.5405-3.64053
2716.112.47593.62408
2813.410.14263.2574
299.911.1192-1.21921
3011.511.5497-0.0496869
318.38.94277-0.642766
3211.711.8391-0.139116
33910.4285-1.42846
349.711.3438-1.64379
3510.89.130881.66912
3610.38.672821.62718
3710.411.1476-0.747569
3812.710.88811.81188
399.311.7739-2.47388
4011.812.2493-0.44934
415.99.39599-3.49599
4211.410.89830.501716
431311.70171.29828
4410.811.7459-0.945908
4512.37.915954.38405
4611.313.418-2.11802
4711.88.889292.91071
487.99.33798-1.43798
4912.79.42883.2712
5012.39.342432.95757
5111.610.6960.904039
526.77.11251-0.412515
5310.910.82170.0783253
5412.112.3146-0.214597
5513.39.753133.54687
5610.19.826080.273919
575.711.7856-6.08556
5814.310.06614.23392
5987.615150.38485
6013.310.1263.17399
619.311.9993-2.69926
6212.512.31340.186608
637.69.42515-1.82515
6415.913.20772.69233
659.213.1647-3.96467
669.18.329830.770169
6711.112.9798-1.87982
681313.7379-0.737892
6914.512.48452.0155
7012.210.62051.57947
7112.313.0808-0.780751
7211.410.51360.886437
738.89.54023-0.740226
7414.69.944814.65519
7512.610.82651.77349
76NANA1.05265
771310.79482.20523
7812.611.4241.17604
7913.212.22890.971058
809.911.6041-1.7041
817.77.623930.0760724
8210.57.884722.61528
8313.412.52630.873738
8410.916.2996-5.39957
854.35.16617-0.866171
8610.38.754111.54589
8711.89.391552.40845
8811.29.251861.94814
8911.413.1076-1.70758
908.67.249611.35039
9113.29.33563.8644
9212.617.4507-4.85072
935.67.29953-1.69953
949.911.4797-1.57974
958.810.7915-1.99146
967.710.124-2.42397
97912.9947-3.99469
987.35.800631.49937
9911.47.620363.77964
10013.616.0263-2.42627
1017.95.758862.14114
10210.710.9322-0.232164
10310.310.586-0.286038
1048.39.7008-1.4008
1059.65.055384.54462
10614.215.8138-1.61383
1078.54.868593.63141
10813.518.5695-5.06952
1094.96.77062-1.87062
1106.47.10313-0.703133
1119.69.239130.360874
11211.610.23561.36435
11311.117.8553-6.75532
1144.352.79141.5586
11512.710.10762.59238
11618.116.14351.95648
11717.8517.15970.690345
11816.616.7543-0.154319
11912.613.2655-0.665511
12017.114.62962.47036
12119.119.00990.0901333
12216.115.09731.00266
12313.3510.83212.51785
12418.414.40773.99235
12514.717.2938-2.59378
12610.611.4707-0.870651
12712.611.32511.27489
12816.215.68110.518908
12913.610.6042.99598
13018.918.35170.548287
13114.113.72610.373881
13214.515.0798-0.579773
13316.1515.21240.937628
13414.7513.47291.27706
13514.814.43920.360847
13612.4512.19840.251552
13712.659.630833.01917
13817.3519.0438-1.69378
1398.66.423872.17613
14018.416.24492.15507
14116.117.5437-1.44375
14211.69.96811.6319
14317.7517.24310.506884
14415.2512.15183.09824
14517.6517.5320.118024
14616.3514.59841.75164
14717.6517.9183-0.268317
14813.613.34850.251467
14914.3514.24420.105831
15014.7513.13661.61344
15118.2525.1519-6.90193
1529.97.973831.92617
1531613.67962.3204
15418.2518.4391-0.189069
15516.8515.42261.42735
15614.614.58910.0109204
15713.8511.52482.3252
15818.9517.99130.958688
15915.616.7679-1.16789
16014.8517.0124-2.16242
16111.759.502742.24726
16218.4516.3532.097
16315.915.88330.0167464
16417.110.07287.0272
16516.114.29461.80541
16619.921.1263-1.22626
16710.958.879482.07052
16818.4517.75980.690168
16915.115.1414-0.0413676
1701517.9483-2.94833
17111.3510.14341.20655
17215.9513.50192.44815
17318.120.1073-2.00733
17414.615.5796-0.97956
17515.416.3796-0.97956
17615.412.5672.83303
17717.618.2914-0.691404
17813.3510.51362.8364
17919.120.1076-1.00763
18015.3519.4066-4.05659
1817.68.9041-1.3041
18213.415.3124-1.91238
18313.910.73773.16229
18419.118.91120.188766
18515.2518.6995-3.44952
18612.912.49240.407616
18716.114.3541.74599
18817.3520.0249-2.67494
18913.1516.861-3.71102
19012.1512.09960.0503947
19112.615.1215-2.52146
19210.359.149871.20013
19315.418.5543-3.15432
1949.66.509073.09093
19518.218.4159-0.215945
19613.612.4051.19497
19714.8516.5249-1.67493
19814.7514.31640.43362
19914.113.00781.09216
20014.914.13320.766781
20116.2515.70520.544842
20219.2518.53320.71678
20313.615.5647-1.96475
20413.613.6902-0.0902231
20515.6517.1181-1.46814
20612.7511.60881.14119
20714.615.3125-0.71254
2089.859.56110.288896
20912.658.762993.88701
21019.216.86472.33528
21116.617.4238-0.823836
21211.211.6506-0.450571
21315.2517.151-1.901
21411.912.5682-0.668236
21513.213.3552-0.155193
21616.3516.858-0.508005
21712.410.59381.80621
21815.8514.41681.43317
21918.1519.6343-1.48432
22011.1511.4899-0.339919
22115.6513.60542.04459
22217.7522.5742-4.82418
2237.659.45854-1.80854
22412.3511.15661.19336
22515.613.11812.48186
22619.317.24952.05049
22715.213.43571.76428
22817.115.36341.7366
22915.611.53084.06917
23018.415.37283.02719
23119.0516.5782.47204
23218.5515.12743.42256
23319.120.0041-0.90406
23413.116.5007-3.40066
23512.8515.4943-2.6443
2369.516.2902-6.79017
2374.55.44603-0.946033
23811.8513.2752-1.42524
23913.612.75480.845174
24011.712.7009-1.00088
24112.413.5669-1.16686
24213.3515.1474-1.79735
24311.410.91350.486514
24414.913.09461.80541
24519.922.7203-2.82027
24611.211.7006-0.500581
24714.613.5811.01899
24817.617.6356-0.0355886
24914.0513.11340.936573
25016.117.3577-1.2577
25113.3516.811-3.46101
25211.8513.0066-1.15659
25311.9511.41690.533121
25414.7513.48811.2619
25515.1518.4783-3.32833
25613.212.09471.10532
25716.8521.839-4.98903
2587.8513.8553-6.00532
2597.710.1612-2.46123
26012.619.0346-6.43458
2617.859.07626-1.22626
26210.9513.4249-2.47489
26312.3515.9813-3.63128
2649.959.463490.486514
26514.913.0381.86198
26616.6516.09710.552859
26713.413.32630.0736576
26813.9513.27070.679297
26915.714.29231.4077
27016.8518.482-1.63203
27110.9511.2636-0.313613
27215.3516.5436-1.19357
27312.210.75021.44983
27415.113.00632.0937
27517.7517.0960.653959
27615.215.4181-0.218053
27714.613.88320.716824
27816.6520.0355-3.38551
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 11.6344 & 1.2656 \tabularnewline
2 & 12.2 & 10.5809 & 1.61912 \tabularnewline
3 & 12.8 & 11.6425 & 1.15749 \tabularnewline
4 & 7.4 & 11.2112 & -3.81123 \tabularnewline
5 & 6.7 & 10.1471 & -3.44714 \tabularnewline
6 & 12.6 & 13.8137 & -1.2137 \tabularnewline
7 & 14.8 & 12.024 & 2.77604 \tabularnewline
8 & 13.3 & 9.07859 & 4.22141 \tabularnewline
9 & 11.1 & 11.4123 & -0.312293 \tabularnewline
10 & 8.2 & 11.6612 & -3.46119 \tabularnewline
11 & 11.4 & 11.7297 & -0.329695 \tabularnewline
12 & 6.4 & 11.0985 & -4.69855 \tabularnewline
13 & 10.6 & 9.5926 & 1.0074 \tabularnewline
14 & 12 & 12.7228 & -0.722818 \tabularnewline
15 & 6.3 & 7.27994 & -0.979944 \tabularnewline
16 & 11.3 & 9.83696 & 1.46304 \tabularnewline
17 & 11.9 & 11.5367 & 0.363257 \tabularnewline
18 & 9.3 & 10.5298 & -1.22978 \tabularnewline
19 & 9.6 & 11.5193 & -1.91927 \tabularnewline
20 & 10 & 10.0835 & -0.0834722 \tabularnewline
21 & 6.4 & 10.8857 & -4.48573 \tabularnewline
22 & 13.8 & 11.0308 & 2.76916 \tabularnewline
23 & 10.8 & 14.8157 & -4.01573 \tabularnewline
24 & 13.8 & 12.5368 & 1.26321 \tabularnewline
25 & 11.7 & 11.1796 & 0.520393 \tabularnewline
26 & 10.9 & 14.5405 & -3.64053 \tabularnewline
27 & 16.1 & 12.4759 & 3.62408 \tabularnewline
28 & 13.4 & 10.1426 & 3.2574 \tabularnewline
29 & 9.9 & 11.1192 & -1.21921 \tabularnewline
30 & 11.5 & 11.5497 & -0.0496869 \tabularnewline
31 & 8.3 & 8.94277 & -0.642766 \tabularnewline
32 & 11.7 & 11.8391 & -0.139116 \tabularnewline
33 & 9 & 10.4285 & -1.42846 \tabularnewline
34 & 9.7 & 11.3438 & -1.64379 \tabularnewline
35 & 10.8 & 9.13088 & 1.66912 \tabularnewline
36 & 10.3 & 8.67282 & 1.62718 \tabularnewline
37 & 10.4 & 11.1476 & -0.747569 \tabularnewline
38 & 12.7 & 10.8881 & 1.81188 \tabularnewline
39 & 9.3 & 11.7739 & -2.47388 \tabularnewline
40 & 11.8 & 12.2493 & -0.44934 \tabularnewline
41 & 5.9 & 9.39599 & -3.49599 \tabularnewline
42 & 11.4 & 10.8983 & 0.501716 \tabularnewline
43 & 13 & 11.7017 & 1.29828 \tabularnewline
44 & 10.8 & 11.7459 & -0.945908 \tabularnewline
45 & 12.3 & 7.91595 & 4.38405 \tabularnewline
46 & 11.3 & 13.418 & -2.11802 \tabularnewline
47 & 11.8 & 8.88929 & 2.91071 \tabularnewline
48 & 7.9 & 9.33798 & -1.43798 \tabularnewline
49 & 12.7 & 9.4288 & 3.2712 \tabularnewline
50 & 12.3 & 9.34243 & 2.95757 \tabularnewline
51 & 11.6 & 10.696 & 0.904039 \tabularnewline
52 & 6.7 & 7.11251 & -0.412515 \tabularnewline
53 & 10.9 & 10.8217 & 0.0783253 \tabularnewline
54 & 12.1 & 12.3146 & -0.214597 \tabularnewline
55 & 13.3 & 9.75313 & 3.54687 \tabularnewline
56 & 10.1 & 9.82608 & 0.273919 \tabularnewline
57 & 5.7 & 11.7856 & -6.08556 \tabularnewline
58 & 14.3 & 10.0661 & 4.23392 \tabularnewline
59 & 8 & 7.61515 & 0.38485 \tabularnewline
60 & 13.3 & 10.126 & 3.17399 \tabularnewline
61 & 9.3 & 11.9993 & -2.69926 \tabularnewline
62 & 12.5 & 12.3134 & 0.186608 \tabularnewline
63 & 7.6 & 9.42515 & -1.82515 \tabularnewline
64 & 15.9 & 13.2077 & 2.69233 \tabularnewline
65 & 9.2 & 13.1647 & -3.96467 \tabularnewline
66 & 9.1 & 8.32983 & 0.770169 \tabularnewline
67 & 11.1 & 12.9798 & -1.87982 \tabularnewline
68 & 13 & 13.7379 & -0.737892 \tabularnewline
69 & 14.5 & 12.4845 & 2.0155 \tabularnewline
70 & 12.2 & 10.6205 & 1.57947 \tabularnewline
71 & 12.3 & 13.0808 & -0.780751 \tabularnewline
72 & 11.4 & 10.5136 & 0.886437 \tabularnewline
73 & 8.8 & 9.54023 & -0.740226 \tabularnewline
74 & 14.6 & 9.94481 & 4.65519 \tabularnewline
75 & 12.6 & 10.8265 & 1.77349 \tabularnewline
76 & NA & NA & 1.05265 \tabularnewline
77 & 13 & 10.7948 & 2.20523 \tabularnewline
78 & 12.6 & 11.424 & 1.17604 \tabularnewline
79 & 13.2 & 12.2289 & 0.971058 \tabularnewline
80 & 9.9 & 11.6041 & -1.7041 \tabularnewline
81 & 7.7 & 7.62393 & 0.0760724 \tabularnewline
82 & 10.5 & 7.88472 & 2.61528 \tabularnewline
83 & 13.4 & 12.5263 & 0.873738 \tabularnewline
84 & 10.9 & 16.2996 & -5.39957 \tabularnewline
85 & 4.3 & 5.16617 & -0.866171 \tabularnewline
86 & 10.3 & 8.75411 & 1.54589 \tabularnewline
87 & 11.8 & 9.39155 & 2.40845 \tabularnewline
88 & 11.2 & 9.25186 & 1.94814 \tabularnewline
89 & 11.4 & 13.1076 & -1.70758 \tabularnewline
90 & 8.6 & 7.24961 & 1.35039 \tabularnewline
91 & 13.2 & 9.3356 & 3.8644 \tabularnewline
92 & 12.6 & 17.4507 & -4.85072 \tabularnewline
93 & 5.6 & 7.29953 & -1.69953 \tabularnewline
94 & 9.9 & 11.4797 & -1.57974 \tabularnewline
95 & 8.8 & 10.7915 & -1.99146 \tabularnewline
96 & 7.7 & 10.124 & -2.42397 \tabularnewline
97 & 9 & 12.9947 & -3.99469 \tabularnewline
98 & 7.3 & 5.80063 & 1.49937 \tabularnewline
99 & 11.4 & 7.62036 & 3.77964 \tabularnewline
100 & 13.6 & 16.0263 & -2.42627 \tabularnewline
101 & 7.9 & 5.75886 & 2.14114 \tabularnewline
102 & 10.7 & 10.9322 & -0.232164 \tabularnewline
103 & 10.3 & 10.586 & -0.286038 \tabularnewline
104 & 8.3 & 9.7008 & -1.4008 \tabularnewline
105 & 9.6 & 5.05538 & 4.54462 \tabularnewline
106 & 14.2 & 15.8138 & -1.61383 \tabularnewline
107 & 8.5 & 4.86859 & 3.63141 \tabularnewline
108 & 13.5 & 18.5695 & -5.06952 \tabularnewline
109 & 4.9 & 6.77062 & -1.87062 \tabularnewline
110 & 6.4 & 7.10313 & -0.703133 \tabularnewline
111 & 9.6 & 9.23913 & 0.360874 \tabularnewline
112 & 11.6 & 10.2356 & 1.36435 \tabularnewline
113 & 11.1 & 17.8553 & -6.75532 \tabularnewline
114 & 4.35 & 2.7914 & 1.5586 \tabularnewline
115 & 12.7 & 10.1076 & 2.59238 \tabularnewline
116 & 18.1 & 16.1435 & 1.95648 \tabularnewline
117 & 17.85 & 17.1597 & 0.690345 \tabularnewline
118 & 16.6 & 16.7543 & -0.154319 \tabularnewline
119 & 12.6 & 13.2655 & -0.665511 \tabularnewline
120 & 17.1 & 14.6296 & 2.47036 \tabularnewline
121 & 19.1 & 19.0099 & 0.0901333 \tabularnewline
122 & 16.1 & 15.0973 & 1.00266 \tabularnewline
123 & 13.35 & 10.8321 & 2.51785 \tabularnewline
124 & 18.4 & 14.4077 & 3.99235 \tabularnewline
125 & 14.7 & 17.2938 & -2.59378 \tabularnewline
126 & 10.6 & 11.4707 & -0.870651 \tabularnewline
127 & 12.6 & 11.3251 & 1.27489 \tabularnewline
128 & 16.2 & 15.6811 & 0.518908 \tabularnewline
129 & 13.6 & 10.604 & 2.99598 \tabularnewline
130 & 18.9 & 18.3517 & 0.548287 \tabularnewline
131 & 14.1 & 13.7261 & 0.373881 \tabularnewline
132 & 14.5 & 15.0798 & -0.579773 \tabularnewline
133 & 16.15 & 15.2124 & 0.937628 \tabularnewline
134 & 14.75 & 13.4729 & 1.27706 \tabularnewline
135 & 14.8 & 14.4392 & 0.360847 \tabularnewline
136 & 12.45 & 12.1984 & 0.251552 \tabularnewline
137 & 12.65 & 9.63083 & 3.01917 \tabularnewline
138 & 17.35 & 19.0438 & -1.69378 \tabularnewline
139 & 8.6 & 6.42387 & 2.17613 \tabularnewline
140 & 18.4 & 16.2449 & 2.15507 \tabularnewline
141 & 16.1 & 17.5437 & -1.44375 \tabularnewline
142 & 11.6 & 9.9681 & 1.6319 \tabularnewline
143 & 17.75 & 17.2431 & 0.506884 \tabularnewline
144 & 15.25 & 12.1518 & 3.09824 \tabularnewline
145 & 17.65 & 17.532 & 0.118024 \tabularnewline
146 & 16.35 & 14.5984 & 1.75164 \tabularnewline
147 & 17.65 & 17.9183 & -0.268317 \tabularnewline
148 & 13.6 & 13.3485 & 0.251467 \tabularnewline
149 & 14.35 & 14.2442 & 0.105831 \tabularnewline
150 & 14.75 & 13.1366 & 1.61344 \tabularnewline
151 & 18.25 & 25.1519 & -6.90193 \tabularnewline
152 & 9.9 & 7.97383 & 1.92617 \tabularnewline
153 & 16 & 13.6796 & 2.3204 \tabularnewline
154 & 18.25 & 18.4391 & -0.189069 \tabularnewline
155 & 16.85 & 15.4226 & 1.42735 \tabularnewline
156 & 14.6 & 14.5891 & 0.0109204 \tabularnewline
157 & 13.85 & 11.5248 & 2.3252 \tabularnewline
158 & 18.95 & 17.9913 & 0.958688 \tabularnewline
159 & 15.6 & 16.7679 & -1.16789 \tabularnewline
160 & 14.85 & 17.0124 & -2.16242 \tabularnewline
161 & 11.75 & 9.50274 & 2.24726 \tabularnewline
162 & 18.45 & 16.353 & 2.097 \tabularnewline
163 & 15.9 & 15.8833 & 0.0167464 \tabularnewline
164 & 17.1 & 10.0728 & 7.0272 \tabularnewline
165 & 16.1 & 14.2946 & 1.80541 \tabularnewline
166 & 19.9 & 21.1263 & -1.22626 \tabularnewline
167 & 10.95 & 8.87948 & 2.07052 \tabularnewline
168 & 18.45 & 17.7598 & 0.690168 \tabularnewline
169 & 15.1 & 15.1414 & -0.0413676 \tabularnewline
170 & 15 & 17.9483 & -2.94833 \tabularnewline
171 & 11.35 & 10.1434 & 1.20655 \tabularnewline
172 & 15.95 & 13.5019 & 2.44815 \tabularnewline
173 & 18.1 & 20.1073 & -2.00733 \tabularnewline
174 & 14.6 & 15.5796 & -0.97956 \tabularnewline
175 & 15.4 & 16.3796 & -0.97956 \tabularnewline
176 & 15.4 & 12.567 & 2.83303 \tabularnewline
177 & 17.6 & 18.2914 & -0.691404 \tabularnewline
178 & 13.35 & 10.5136 & 2.8364 \tabularnewline
179 & 19.1 & 20.1076 & -1.00763 \tabularnewline
180 & 15.35 & 19.4066 & -4.05659 \tabularnewline
181 & 7.6 & 8.9041 & -1.3041 \tabularnewline
182 & 13.4 & 15.3124 & -1.91238 \tabularnewline
183 & 13.9 & 10.7377 & 3.16229 \tabularnewline
184 & 19.1 & 18.9112 & 0.188766 \tabularnewline
185 & 15.25 & 18.6995 & -3.44952 \tabularnewline
186 & 12.9 & 12.4924 & 0.407616 \tabularnewline
187 & 16.1 & 14.354 & 1.74599 \tabularnewline
188 & 17.35 & 20.0249 & -2.67494 \tabularnewline
189 & 13.15 & 16.861 & -3.71102 \tabularnewline
190 & 12.15 & 12.0996 & 0.0503947 \tabularnewline
191 & 12.6 & 15.1215 & -2.52146 \tabularnewline
192 & 10.35 & 9.14987 & 1.20013 \tabularnewline
193 & 15.4 & 18.5543 & -3.15432 \tabularnewline
194 & 9.6 & 6.50907 & 3.09093 \tabularnewline
195 & 18.2 & 18.4159 & -0.215945 \tabularnewline
196 & 13.6 & 12.405 & 1.19497 \tabularnewline
197 & 14.85 & 16.5249 & -1.67493 \tabularnewline
198 & 14.75 & 14.3164 & 0.43362 \tabularnewline
199 & 14.1 & 13.0078 & 1.09216 \tabularnewline
200 & 14.9 & 14.1332 & 0.766781 \tabularnewline
201 & 16.25 & 15.7052 & 0.544842 \tabularnewline
202 & 19.25 & 18.5332 & 0.71678 \tabularnewline
203 & 13.6 & 15.5647 & -1.96475 \tabularnewline
204 & 13.6 & 13.6902 & -0.0902231 \tabularnewline
205 & 15.65 & 17.1181 & -1.46814 \tabularnewline
206 & 12.75 & 11.6088 & 1.14119 \tabularnewline
207 & 14.6 & 15.3125 & -0.71254 \tabularnewline
208 & 9.85 & 9.5611 & 0.288896 \tabularnewline
209 & 12.65 & 8.76299 & 3.88701 \tabularnewline
210 & 19.2 & 16.8647 & 2.33528 \tabularnewline
211 & 16.6 & 17.4238 & -0.823836 \tabularnewline
212 & 11.2 & 11.6506 & -0.450571 \tabularnewline
213 & 15.25 & 17.151 & -1.901 \tabularnewline
214 & 11.9 & 12.5682 & -0.668236 \tabularnewline
215 & 13.2 & 13.3552 & -0.155193 \tabularnewline
216 & 16.35 & 16.858 & -0.508005 \tabularnewline
217 & 12.4 & 10.5938 & 1.80621 \tabularnewline
218 & 15.85 & 14.4168 & 1.43317 \tabularnewline
219 & 18.15 & 19.6343 & -1.48432 \tabularnewline
220 & 11.15 & 11.4899 & -0.339919 \tabularnewline
221 & 15.65 & 13.6054 & 2.04459 \tabularnewline
222 & 17.75 & 22.5742 & -4.82418 \tabularnewline
223 & 7.65 & 9.45854 & -1.80854 \tabularnewline
224 & 12.35 & 11.1566 & 1.19336 \tabularnewline
225 & 15.6 & 13.1181 & 2.48186 \tabularnewline
226 & 19.3 & 17.2495 & 2.05049 \tabularnewline
227 & 15.2 & 13.4357 & 1.76428 \tabularnewline
228 & 17.1 & 15.3634 & 1.7366 \tabularnewline
229 & 15.6 & 11.5308 & 4.06917 \tabularnewline
230 & 18.4 & 15.3728 & 3.02719 \tabularnewline
231 & 19.05 & 16.578 & 2.47204 \tabularnewline
232 & 18.55 & 15.1274 & 3.42256 \tabularnewline
233 & 19.1 & 20.0041 & -0.90406 \tabularnewline
234 & 13.1 & 16.5007 & -3.40066 \tabularnewline
235 & 12.85 & 15.4943 & -2.6443 \tabularnewline
236 & 9.5 & 16.2902 & -6.79017 \tabularnewline
237 & 4.5 & 5.44603 & -0.946033 \tabularnewline
238 & 11.85 & 13.2752 & -1.42524 \tabularnewline
239 & 13.6 & 12.7548 & 0.845174 \tabularnewline
240 & 11.7 & 12.7009 & -1.00088 \tabularnewline
241 & 12.4 & 13.5669 & -1.16686 \tabularnewline
242 & 13.35 & 15.1474 & -1.79735 \tabularnewline
243 & 11.4 & 10.9135 & 0.486514 \tabularnewline
244 & 14.9 & 13.0946 & 1.80541 \tabularnewline
245 & 19.9 & 22.7203 & -2.82027 \tabularnewline
246 & 11.2 & 11.7006 & -0.500581 \tabularnewline
247 & 14.6 & 13.581 & 1.01899 \tabularnewline
248 & 17.6 & 17.6356 & -0.0355886 \tabularnewline
249 & 14.05 & 13.1134 & 0.936573 \tabularnewline
250 & 16.1 & 17.3577 & -1.2577 \tabularnewline
251 & 13.35 & 16.811 & -3.46101 \tabularnewline
252 & 11.85 & 13.0066 & -1.15659 \tabularnewline
253 & 11.95 & 11.4169 & 0.533121 \tabularnewline
254 & 14.75 & 13.4881 & 1.2619 \tabularnewline
255 & 15.15 & 18.4783 & -3.32833 \tabularnewline
256 & 13.2 & 12.0947 & 1.10532 \tabularnewline
257 & 16.85 & 21.839 & -4.98903 \tabularnewline
258 & 7.85 & 13.8553 & -6.00532 \tabularnewline
259 & 7.7 & 10.1612 & -2.46123 \tabularnewline
260 & 12.6 & 19.0346 & -6.43458 \tabularnewline
261 & 7.85 & 9.07626 & -1.22626 \tabularnewline
262 & 10.95 & 13.4249 & -2.47489 \tabularnewline
263 & 12.35 & 15.9813 & -3.63128 \tabularnewline
264 & 9.95 & 9.46349 & 0.486514 \tabularnewline
265 & 14.9 & 13.038 & 1.86198 \tabularnewline
266 & 16.65 & 16.0971 & 0.552859 \tabularnewline
267 & 13.4 & 13.3263 & 0.0736576 \tabularnewline
268 & 13.95 & 13.2707 & 0.679297 \tabularnewline
269 & 15.7 & 14.2923 & 1.4077 \tabularnewline
270 & 16.85 & 18.482 & -1.63203 \tabularnewline
271 & 10.95 & 11.2636 & -0.313613 \tabularnewline
272 & 15.35 & 16.5436 & -1.19357 \tabularnewline
273 & 12.2 & 10.7502 & 1.44983 \tabularnewline
274 & 15.1 & 13.0063 & 2.0937 \tabularnewline
275 & 17.75 & 17.096 & 0.653959 \tabularnewline
276 & 15.2 & 15.4181 & -0.218053 \tabularnewline
277 & 14.6 & 13.8832 & 0.716824 \tabularnewline
278 & 16.65 & 20.0355 & -3.38551 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264381&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]11.6344[/C][C]1.2656[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.5809[/C][C]1.61912[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.6425[/C][C]1.15749[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.2112[/C][C]-3.81123[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.1471[/C][C]-3.44714[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.8137[/C][C]-1.2137[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.024[/C][C]2.77604[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]9.07859[/C][C]4.22141[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.4123[/C][C]-0.312293[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]11.6612[/C][C]-3.46119[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]11.7297[/C][C]-0.329695[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.0985[/C][C]-4.69855[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.5926[/C][C]1.0074[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.7228[/C][C]-0.722818[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]7.27994[/C][C]-0.979944[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.83696[/C][C]1.46304[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]11.5367[/C][C]0.363257[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.5298[/C][C]-1.22978[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.5193[/C][C]-1.91927[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]10.0835[/C][C]-0.0834722[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]10.8857[/C][C]-4.48573[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]11.0308[/C][C]2.76916[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]14.8157[/C][C]-4.01573[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.5368[/C][C]1.26321[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]11.1796[/C][C]0.520393[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]14.5405[/C][C]-3.64053[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.4759[/C][C]3.62408[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.1426[/C][C]3.2574[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.1192[/C][C]-1.21921[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]11.5497[/C][C]-0.0496869[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]8.94277[/C][C]-0.642766[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.8391[/C][C]-0.139116[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]10.4285[/C][C]-1.42846[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]11.3438[/C][C]-1.64379[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]9.13088[/C][C]1.66912[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]8.67282[/C][C]1.62718[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.1476[/C][C]-0.747569[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]10.8881[/C][C]1.81188[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]11.7739[/C][C]-2.47388[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.2493[/C][C]-0.44934[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]9.39599[/C][C]-3.49599[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]10.8983[/C][C]0.501716[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.7017[/C][C]1.29828[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.7459[/C][C]-0.945908[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]7.91595[/C][C]4.38405[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.418[/C][C]-2.11802[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]8.88929[/C][C]2.91071[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]9.33798[/C][C]-1.43798[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]9.4288[/C][C]3.2712[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]9.34243[/C][C]2.95757[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.696[/C][C]0.904039[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]7.11251[/C][C]-0.412515[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.8217[/C][C]0.0783253[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.3146[/C][C]-0.214597[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]9.75313[/C][C]3.54687[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]9.82608[/C][C]0.273919[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.7856[/C][C]-6.08556[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]10.0661[/C][C]4.23392[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]7.61515[/C][C]0.38485[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.126[/C][C]3.17399[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]11.9993[/C][C]-2.69926[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]12.3134[/C][C]0.186608[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]9.42515[/C][C]-1.82515[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.2077[/C][C]2.69233[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.1647[/C][C]-3.96467[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]8.32983[/C][C]0.770169[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.9798[/C][C]-1.87982[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.7379[/C][C]-0.737892[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.4845[/C][C]2.0155[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.6205[/C][C]1.57947[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.0808[/C][C]-0.780751[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.5136[/C][C]0.886437[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]9.54023[/C][C]-0.740226[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]9.94481[/C][C]4.65519[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]10.8265[/C][C]1.77349[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]1.05265[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.7948[/C][C]2.20523[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]11.424[/C][C]1.17604[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]12.2289[/C][C]0.971058[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]11.6041[/C][C]-1.7041[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]7.62393[/C][C]0.0760724[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]7.88472[/C][C]2.61528[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]12.5263[/C][C]0.873738[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]16.2996[/C][C]-5.39957[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]5.16617[/C][C]-0.866171[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]8.75411[/C][C]1.54589[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]9.39155[/C][C]2.40845[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]9.25186[/C][C]1.94814[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]13.1076[/C][C]-1.70758[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]7.24961[/C][C]1.35039[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]9.3356[/C][C]3.8644[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]17.4507[/C][C]-4.85072[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]7.29953[/C][C]-1.69953[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]11.4797[/C][C]-1.57974[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]10.7915[/C][C]-1.99146[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]10.124[/C][C]-2.42397[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]12.9947[/C][C]-3.99469[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]5.80063[/C][C]1.49937[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]7.62036[/C][C]3.77964[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]16.0263[/C][C]-2.42627[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]5.75886[/C][C]2.14114[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]10.9322[/C][C]-0.232164[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]10.586[/C][C]-0.286038[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]9.7008[/C][C]-1.4008[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]5.05538[/C][C]4.54462[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]15.8138[/C][C]-1.61383[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]4.86859[/C][C]3.63141[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]18.5695[/C][C]-5.06952[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]6.77062[/C][C]-1.87062[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]7.10313[/C][C]-0.703133[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]9.23913[/C][C]0.360874[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]10.2356[/C][C]1.36435[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]17.8553[/C][C]-6.75532[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]2.7914[/C][C]1.5586[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]10.1076[/C][C]2.59238[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]16.1435[/C][C]1.95648[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]17.1597[/C][C]0.690345[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]16.7543[/C][C]-0.154319[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]13.2655[/C][C]-0.665511[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]14.6296[/C][C]2.47036[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]19.0099[/C][C]0.0901333[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]15.0973[/C][C]1.00266[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]10.8321[/C][C]2.51785[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]14.4077[/C][C]3.99235[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.2938[/C][C]-2.59378[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.4707[/C][C]-0.870651[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]11.3251[/C][C]1.27489[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]15.6811[/C][C]0.518908[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]10.604[/C][C]2.99598[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]18.3517[/C][C]0.548287[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]13.7261[/C][C]0.373881[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]15.0798[/C][C]-0.579773[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]15.2124[/C][C]0.937628[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.4729[/C][C]1.27706[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]14.4392[/C][C]0.360847[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.1984[/C][C]0.251552[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.63083[/C][C]3.01917[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]19.0438[/C][C]-1.69378[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]6.42387[/C][C]2.17613[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]16.2449[/C][C]2.15507[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]17.5437[/C][C]-1.44375[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]9.9681[/C][C]1.6319[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]17.2431[/C][C]0.506884[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]12.1518[/C][C]3.09824[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]17.532[/C][C]0.118024[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]14.5984[/C][C]1.75164[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]17.9183[/C][C]-0.268317[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]13.3485[/C][C]0.251467[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]14.2442[/C][C]0.105831[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]13.1366[/C][C]1.61344[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]25.1519[/C][C]-6.90193[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]7.97383[/C][C]1.92617[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]13.6796[/C][C]2.3204[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]18.4391[/C][C]-0.189069[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]15.4226[/C][C]1.42735[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]14.5891[/C][C]0.0109204[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]11.5248[/C][C]2.3252[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]17.9913[/C][C]0.958688[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]16.7679[/C][C]-1.16789[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]17.0124[/C][C]-2.16242[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]9.50274[/C][C]2.24726[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]16.353[/C][C]2.097[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]15.8833[/C][C]0.0167464[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]10.0728[/C][C]7.0272[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]14.2946[/C][C]1.80541[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]21.1263[/C][C]-1.22626[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]8.87948[/C][C]2.07052[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]17.7598[/C][C]0.690168[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]15.1414[/C][C]-0.0413676[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]17.9483[/C][C]-2.94833[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]10.1434[/C][C]1.20655[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]13.5019[/C][C]2.44815[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]20.1073[/C][C]-2.00733[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]15.5796[/C][C]-0.97956[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.3796[/C][C]-0.97956[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]12.567[/C][C]2.83303[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]18.2914[/C][C]-0.691404[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]10.5136[/C][C]2.8364[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]20.1076[/C][C]-1.00763[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]19.4066[/C][C]-4.05659[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]8.9041[/C][C]-1.3041[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]15.3124[/C][C]-1.91238[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]10.7377[/C][C]3.16229[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]18.9112[/C][C]0.188766[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]18.6995[/C][C]-3.44952[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]12.4924[/C][C]0.407616[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]14.354[/C][C]1.74599[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]20.0249[/C][C]-2.67494[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]16.861[/C][C]-3.71102[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]12.0996[/C][C]0.0503947[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]15.1215[/C][C]-2.52146[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]9.14987[/C][C]1.20013[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]18.5543[/C][C]-3.15432[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]6.50907[/C][C]3.09093[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]18.4159[/C][C]-0.215945[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.405[/C][C]1.19497[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]16.5249[/C][C]-1.67493[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]14.3164[/C][C]0.43362[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]13.0078[/C][C]1.09216[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]14.1332[/C][C]0.766781[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]15.7052[/C][C]0.544842[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]18.5332[/C][C]0.71678[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]15.5647[/C][C]-1.96475[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]13.6902[/C][C]-0.0902231[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]17.1181[/C][C]-1.46814[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]11.6088[/C][C]1.14119[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]15.3125[/C][C]-0.71254[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]9.5611[/C][C]0.288896[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]8.76299[/C][C]3.88701[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]16.8647[/C][C]2.33528[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]17.4238[/C][C]-0.823836[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]11.6506[/C][C]-0.450571[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]17.151[/C][C]-1.901[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]12.5682[/C][C]-0.668236[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]13.3552[/C][C]-0.155193[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]16.858[/C][C]-0.508005[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]10.5938[/C][C]1.80621[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]14.4168[/C][C]1.43317[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]19.6343[/C][C]-1.48432[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]11.4899[/C][C]-0.339919[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]13.6054[/C][C]2.04459[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]22.5742[/C][C]-4.82418[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]9.45854[/C][C]-1.80854[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]11.1566[/C][C]1.19336[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]13.1181[/C][C]2.48186[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]17.2495[/C][C]2.05049[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]13.4357[/C][C]1.76428[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]15.3634[/C][C]1.7366[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]11.5308[/C][C]4.06917[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]15.3728[/C][C]3.02719[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]16.578[/C][C]2.47204[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]15.1274[/C][C]3.42256[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]20.0041[/C][C]-0.90406[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]16.5007[/C][C]-3.40066[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]15.4943[/C][C]-2.6443[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]16.2902[/C][C]-6.79017[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]5.44603[/C][C]-0.946033[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]13.2752[/C][C]-1.42524[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]12.7548[/C][C]0.845174[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]12.7009[/C][C]-1.00088[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.5669[/C][C]-1.16686[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]15.1474[/C][C]-1.79735[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]10.9135[/C][C]0.486514[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]13.0946[/C][C]1.80541[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]22.7203[/C][C]-2.82027[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]11.7006[/C][C]-0.500581[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]13.581[/C][C]1.01899[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]17.6356[/C][C]-0.0355886[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]13.1134[/C][C]0.936573[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]17.3577[/C][C]-1.2577[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]16.811[/C][C]-3.46101[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]13.0066[/C][C]-1.15659[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.4169[/C][C]0.533121[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]13.4881[/C][C]1.2619[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]18.4783[/C][C]-3.32833[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]12.0947[/C][C]1.10532[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.839[/C][C]-4.98903[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]13.8553[/C][C]-6.00532[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]10.1612[/C][C]-2.46123[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]19.0346[/C][C]-6.43458[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]9.07626[/C][C]-1.22626[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]13.4249[/C][C]-2.47489[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]15.9813[/C][C]-3.63128[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]9.46349[/C][C]0.486514[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]13.038[/C][C]1.86198[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.0971[/C][C]0.552859[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]13.3263[/C][C]0.0736576[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]13.2707[/C][C]0.679297[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]14.2923[/C][C]1.4077[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]18.482[/C][C]-1.63203[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]11.2636[/C][C]-0.313613[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]16.5436[/C][C]-1.19357[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]10.7502[/C][C]1.44983[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]13.0063[/C][C]2.0937[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]17.096[/C][C]0.653959[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]15.4181[/C][C]-0.218053[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]13.8832[/C][C]0.716824[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]20.0355[/C][C]-3.38551[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264381&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264381&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.63441.2656
212.210.58091.61912
312.811.64251.15749
47.411.2112-3.81123
56.710.1471-3.44714
612.613.8137-1.2137
714.812.0242.77604
813.39.078594.22141
911.111.4123-0.312293
108.211.6612-3.46119
1111.411.7297-0.329695
126.411.0985-4.69855
1310.69.59261.0074
141212.7228-0.722818
156.37.27994-0.979944
1611.39.836961.46304
1711.911.53670.363257
189.310.5298-1.22978
199.611.5193-1.91927
201010.0835-0.0834722
216.410.8857-4.48573
2213.811.03082.76916
2310.814.8157-4.01573
2413.812.53681.26321
2511.711.17960.520393
2610.914.5405-3.64053
2716.112.47593.62408
2813.410.14263.2574
299.911.1192-1.21921
3011.511.5497-0.0496869
318.38.94277-0.642766
3211.711.8391-0.139116
33910.4285-1.42846
349.711.3438-1.64379
3510.89.130881.66912
3610.38.672821.62718
3710.411.1476-0.747569
3812.710.88811.81188
399.311.7739-2.47388
4011.812.2493-0.44934
415.99.39599-3.49599
4211.410.89830.501716
431311.70171.29828
4410.811.7459-0.945908
4512.37.915954.38405
4611.313.418-2.11802
4711.88.889292.91071
487.99.33798-1.43798
4912.79.42883.2712
5012.39.342432.95757
5111.610.6960.904039
526.77.11251-0.412515
5310.910.82170.0783253
5412.112.3146-0.214597
5513.39.753133.54687
5610.19.826080.273919
575.711.7856-6.08556
5814.310.06614.23392
5987.615150.38485
6013.310.1263.17399
619.311.9993-2.69926
6212.512.31340.186608
637.69.42515-1.82515
6415.913.20772.69233
659.213.1647-3.96467
669.18.329830.770169
6711.112.9798-1.87982
681313.7379-0.737892
6914.512.48452.0155
7012.210.62051.57947
7112.313.0808-0.780751
7211.410.51360.886437
738.89.54023-0.740226
7414.69.944814.65519
7512.610.82651.77349
76NANA1.05265
771310.79482.20523
7812.611.4241.17604
7913.212.22890.971058
809.911.6041-1.7041
817.77.623930.0760724
8210.57.884722.61528
8313.412.52630.873738
8410.916.2996-5.39957
854.35.16617-0.866171
8610.38.754111.54589
8711.89.391552.40845
8811.29.251861.94814
8911.413.1076-1.70758
908.67.249611.35039
9113.29.33563.8644
9212.617.4507-4.85072
935.67.29953-1.69953
949.911.4797-1.57974
958.810.7915-1.99146
967.710.124-2.42397
97912.9947-3.99469
987.35.800631.49937
9911.47.620363.77964
10013.616.0263-2.42627
1017.95.758862.14114
10210.710.9322-0.232164
10310.310.586-0.286038
1048.39.7008-1.4008
1059.65.055384.54462
10614.215.8138-1.61383
1078.54.868593.63141
10813.518.5695-5.06952
1094.96.77062-1.87062
1106.47.10313-0.703133
1119.69.239130.360874
11211.610.23561.36435
11311.117.8553-6.75532
1144.352.79141.5586
11512.710.10762.59238
11618.116.14351.95648
11717.8517.15970.690345
11816.616.7543-0.154319
11912.613.2655-0.665511
12017.114.62962.47036
12119.119.00990.0901333
12216.115.09731.00266
12313.3510.83212.51785
12418.414.40773.99235
12514.717.2938-2.59378
12610.611.4707-0.870651
12712.611.32511.27489
12816.215.68110.518908
12913.610.6042.99598
13018.918.35170.548287
13114.113.72610.373881
13214.515.0798-0.579773
13316.1515.21240.937628
13414.7513.47291.27706
13514.814.43920.360847
13612.4512.19840.251552
13712.659.630833.01917
13817.3519.0438-1.69378
1398.66.423872.17613
14018.416.24492.15507
14116.117.5437-1.44375
14211.69.96811.6319
14317.7517.24310.506884
14415.2512.15183.09824
14517.6517.5320.118024
14616.3514.59841.75164
14717.6517.9183-0.268317
14813.613.34850.251467
14914.3514.24420.105831
15014.7513.13661.61344
15118.2525.1519-6.90193
1529.97.973831.92617
1531613.67962.3204
15418.2518.4391-0.189069
15516.8515.42261.42735
15614.614.58910.0109204
15713.8511.52482.3252
15818.9517.99130.958688
15915.616.7679-1.16789
16014.8517.0124-2.16242
16111.759.502742.24726
16218.4516.3532.097
16315.915.88330.0167464
16417.110.07287.0272
16516.114.29461.80541
16619.921.1263-1.22626
16710.958.879482.07052
16818.4517.75980.690168
16915.115.1414-0.0413676
1701517.9483-2.94833
17111.3510.14341.20655
17215.9513.50192.44815
17318.120.1073-2.00733
17414.615.5796-0.97956
17515.416.3796-0.97956
17615.412.5672.83303
17717.618.2914-0.691404
17813.3510.51362.8364
17919.120.1076-1.00763
18015.3519.4066-4.05659
1817.68.9041-1.3041
18213.415.3124-1.91238
18313.910.73773.16229
18419.118.91120.188766
18515.2518.6995-3.44952
18612.912.49240.407616
18716.114.3541.74599
18817.3520.0249-2.67494
18913.1516.861-3.71102
19012.1512.09960.0503947
19112.615.1215-2.52146
19210.359.149871.20013
19315.418.5543-3.15432
1949.66.509073.09093
19518.218.4159-0.215945
19613.612.4051.19497
19714.8516.5249-1.67493
19814.7514.31640.43362
19914.113.00781.09216
20014.914.13320.766781
20116.2515.70520.544842
20219.2518.53320.71678
20313.615.5647-1.96475
20413.613.6902-0.0902231
20515.6517.1181-1.46814
20612.7511.60881.14119
20714.615.3125-0.71254
2089.859.56110.288896
20912.658.762993.88701
21019.216.86472.33528
21116.617.4238-0.823836
21211.211.6506-0.450571
21315.2517.151-1.901
21411.912.5682-0.668236
21513.213.3552-0.155193
21616.3516.858-0.508005
21712.410.59381.80621
21815.8514.41681.43317
21918.1519.6343-1.48432
22011.1511.4899-0.339919
22115.6513.60542.04459
22217.7522.5742-4.82418
2237.659.45854-1.80854
22412.3511.15661.19336
22515.613.11812.48186
22619.317.24952.05049
22715.213.43571.76428
22817.115.36341.7366
22915.611.53084.06917
23018.415.37283.02719
23119.0516.5782.47204
23218.5515.12743.42256
23319.120.0041-0.90406
23413.116.5007-3.40066
23512.8515.4943-2.6443
2369.516.2902-6.79017
2374.55.44603-0.946033
23811.8513.2752-1.42524
23913.612.75480.845174
24011.712.7009-1.00088
24112.413.5669-1.16686
24213.3515.1474-1.79735
24311.410.91350.486514
24414.913.09461.80541
24519.922.7203-2.82027
24611.211.7006-0.500581
24714.613.5811.01899
24817.617.6356-0.0355886
24914.0513.11340.936573
25016.117.3577-1.2577
25113.3516.811-3.46101
25211.8513.0066-1.15659
25311.9511.41690.533121
25414.7513.48811.2619
25515.1518.4783-3.32833
25613.212.09471.10532
25716.8521.839-4.98903
2587.8513.8553-6.00532
2597.710.1612-2.46123
26012.619.0346-6.43458
2617.859.07626-1.22626
26210.9513.4249-2.47489
26312.3515.9813-3.63128
2649.959.463490.486514
26514.913.0381.86198
26616.6516.09710.552859
26713.413.32630.0736576
26813.9513.27070.679297
26915.714.29231.4077
27016.8518.482-1.63203
27110.9511.2636-0.313613
27215.3516.5436-1.19357
27312.210.75021.44983
27415.113.00632.0937
27517.7517.0960.653959
27615.215.4181-0.218053
27714.613.88320.716824
27816.6520.0355-3.38551
2798.1NANA







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9256680.1486630.0743316
100.8950120.2099750.104988
110.8661070.2677860.133893
120.8992530.2014950.100747
130.8596460.2807070.140354
140.8127210.3745580.187279
150.785260.429480.21474
160.7129050.5741890.287095
170.6488640.7022720.351136
180.6249380.7501250.375062
190.6420910.7158170.357909
200.5673870.8652250.432613
210.5816550.836690.418345
220.6064590.7870830.393541
230.7070640.5858710.292936
240.7371630.5256740.262837
250.6793040.6413920.320696
260.6418760.7162480.358124
270.6088550.7822890.391145
280.5851890.8296230.414811
290.5426010.9147980.457399
300.4885480.9770960.511452
310.4303420.8606850.569658
320.3722140.7444270.627786
330.3582880.7165760.641712
340.3098950.6197890.690105
350.2775410.5550820.722459
360.250760.501520.74924
370.2222310.4444620.777769
380.2114020.4228050.788598
390.2044990.4089990.795501
400.1772080.3544150.822792
410.2461970.4923950.753803
420.2117930.4235870.788207
430.1941210.3882420.805879
440.1640870.3281740.835913
450.174280.3485610.82572
460.1623190.3246380.837681
470.2022140.4044290.797786
480.2460160.4920310.753984
490.2772120.5544240.722788
500.2497860.4995720.750214
510.2169980.4339950.783002
520.2274530.4549060.772547
530.1973420.3946830.802658
540.1683680.3367360.831632
550.2259820.4519640.774018
560.1948110.3896230.805189
570.4937030.9874070.506297
580.6101650.7796710.389835
590.5744090.8511820.425591
600.56850.8630.4315
610.578860.8422790.42114
620.5414540.9170920.458546
630.542850.91430.45715
640.6058650.7882710.394135
650.6361510.7276980.363849
660.6035540.7928920.396446
670.5763760.8472470.423624
680.5454580.9090840.454542
690.5582170.8835660.441783
700.5309720.9380560.469028
710.4953030.9906060.504697
720.4622520.9245050.537748
730.4390590.8781170.560941
740.5091470.9817050.490853
750.5039950.9920110.496005
760.4856630.9713270.514337
770.4640520.9281040.535948
780.4450690.8901380.554931
790.4098380.8196770.590162
800.4083690.8167380.591631
810.3739150.747830.626085
820.3751150.750230.624885
830.3422690.6845380.657731
840.5679530.8640950.432047
850.5363510.9272980.463649
860.5071450.985710.492855
870.4930560.9861130.506944
880.4726520.9453040.527348
890.4683330.9366670.531667
900.4443990.8887970.555601
910.48260.96520.5174
920.6299660.7400680.370034
930.6141980.7716030.385802
940.6013550.7972910.398645
950.6039580.7920840.396042
960.6058650.7882710.394135
970.6777330.6445340.322267
980.6522310.6955390.347769
990.6902870.6194260.309713
1000.7001890.5996230.299811
1010.6858470.6283050.314153
1020.6537430.6925140.346257
1030.624620.7507590.37538
1040.6036780.7926450.396322
1050.6857620.6284760.314238
1060.6679490.6641010.332051
1070.7200260.5599470.279974
1080.8182450.363510.181755
1090.8197750.360450.180225
1100.7998910.4002180.200109
1110.7775860.4448280.222414
1120.7524960.4950090.247504
1130.8062450.387510.193755
1140.8701760.2596480.129824
1150.9132060.1735880.0867941
1160.9173260.1653480.0826739
1170.9061980.1876040.0938021
1180.8912170.2175650.108783
1190.8773630.2452730.122637
1200.8828860.2342290.117114
1210.8651160.2697690.134884
1220.8487430.3025150.151257
1230.850270.2994590.14973
1240.8810340.2379320.118966
1250.8911710.2176570.108829
1260.8779510.2440980.122049
1270.8634960.2730070.136504
1280.8444650.311070.155535
1290.8517080.2965840.148292
1300.8323210.3353580.167679
1310.8104610.3790770.189539
1320.7895050.4209890.210495
1330.7665470.4669060.233453
1340.7454760.5090470.254524
1350.7207120.5585760.279288
1360.6939610.6120780.306039
1370.7091050.581790.290895
1380.7061430.5877140.293857
1390.6975610.6048770.302439
1400.6906950.6186110.309305
1410.6796420.6407170.320358
1420.6596790.6806420.340321
1430.6280230.7439530.371977
1440.6492820.7014360.350718
1450.6166010.7667970.383399
1460.5975270.8049450.402473
1470.5657270.8685450.434273
1480.5322730.9354530.467727
1490.4975370.9950740.502463
1500.4750110.9500210.524989
1510.7533910.4932180.246609
1520.7469790.5060410.253021
1530.7444820.5110370.255518
1540.7177270.5645460.282273
1550.7055680.5888650.294432
1560.6778330.6443350.322167
1570.675920.648160.32408
1580.6496370.7007270.350363
1590.6304810.7390380.369519
1600.6319870.7360260.368013
1610.6238340.7523330.376166
1620.6211430.7577130.378857
1630.5886980.8226040.411302
1640.918530.1629390.0814696
1650.9079460.1841080.0920539
1660.9012260.1975490.0987744
1670.8947030.2105940.105297
1680.8828280.2343440.117172
1690.8647170.2705670.135283
1700.8803530.2392940.119647
1710.8729670.2540670.127033
1720.8700580.2598840.129942
1730.8701440.2597120.129856
1740.8543270.2913460.145673
1750.8372790.3254430.162721
1760.8504890.2990230.149511
1770.8313770.3372450.168623
1780.8360790.3278420.163921
1790.8232870.3534260.176713
1800.8515860.2968280.148414
1810.8376240.3247510.162376
1820.8423320.3153360.157668
1830.8713990.2572020.128601
1840.8509380.2981240.149062
1850.8942660.2114680.105734
1860.8761090.2477810.123891
1870.8658310.2683380.134169
1880.8815990.2368020.118401
1890.9235260.1529480.0764741
1900.9131780.1736440.0868218
1910.9099780.1800440.090022
1920.896270.207460.10373
1930.9043420.1913150.0956576
1940.9078520.1842950.0921477
1950.8909440.2181120.109056
1960.8921760.2156470.107824
1970.8862070.2275860.113793
1980.8673510.2652970.132649
1990.8495410.3009190.150459
2000.8259430.3481140.174057
2010.8028790.3942420.197121
2020.7938570.4122860.206143
2030.7964130.4071750.203587
2040.7716110.4567790.228389
2050.746710.5065790.25329
2060.7315390.5369230.268461
2070.7330790.5338430.266921
2080.7297020.5405950.270298
2090.7364040.5271930.263596
2100.7485020.5029960.251498
2110.7361710.5276580.263829
2120.7016290.5967410.298371
2130.6868850.626230.313115
2140.6506840.6986310.349316
2150.6166540.7666920.383346
2160.5813830.8372340.418617
2170.5873930.8252130.412607
2180.5555450.888910.444455
2190.5252480.9495030.474752
2200.4862390.9724780.513761
2210.4614510.9229020.538549
2220.5716490.8567020.428351
2230.5358040.9283920.464196
2240.527080.9458390.47292
2250.5049230.9901540.495077
2260.518750.9624990.48125
2270.4909990.9819990.509001
2280.522330.9553410.47767
2290.7652330.4695350.234767
2300.7885590.4228820.211441
2310.7663890.4672230.233611
2320.8368740.3262520.163126
2330.8080270.3839460.191973
2340.8178340.3643330.182166
2350.7943120.4113750.205688
2360.8573660.2852680.142634
2370.8264310.3471370.173569
2380.7926420.4147150.207358
2390.8510330.2979330.148967
2400.8197220.3605570.180278
2410.7822490.4355020.217751
2420.7531690.4936620.246831
2430.7277540.5444920.272246
2440.6806880.6386230.319312
2450.6571240.6857520.342876
2460.6020670.7958670.397933
2470.5592180.8815640.440782
2480.5867430.8265150.413257
2490.5899430.8201140.410057
2500.5882240.8235530.411776
2510.5364230.9271550.463577
2520.5335910.9328170.466409
2530.5011760.9976480.498824
2540.465250.9305010.53475
2550.4080180.8160350.591982
2560.3405710.6811420.659429
2570.3994390.7988780.600561
2580.5279980.9440040.472002
2590.5675640.8648710.432436
2600.9331250.1337510.0668754
2610.9003010.1993990.0996993
2620.9540670.09186690.0459334
2630.9900030.01999440.00999722
2640.9780830.04383390.0219169
2650.9679280.06414440.0320722
2660.9711360.05772880.0288644
2670.9405710.1188580.0594292
2680.8739250.2521510.126075
2690.7670880.4658240.232912
2700.5662080.8675840.433792

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.925668 & 0.148663 & 0.0743316 \tabularnewline
10 & 0.895012 & 0.209975 & 0.104988 \tabularnewline
11 & 0.866107 & 0.267786 & 0.133893 \tabularnewline
12 & 0.899253 & 0.201495 & 0.100747 \tabularnewline
13 & 0.859646 & 0.280707 & 0.140354 \tabularnewline
14 & 0.812721 & 0.374558 & 0.187279 \tabularnewline
15 & 0.78526 & 0.42948 & 0.21474 \tabularnewline
16 & 0.712905 & 0.574189 & 0.287095 \tabularnewline
17 & 0.648864 & 0.702272 & 0.351136 \tabularnewline
18 & 0.624938 & 0.750125 & 0.375062 \tabularnewline
19 & 0.642091 & 0.715817 & 0.357909 \tabularnewline
20 & 0.567387 & 0.865225 & 0.432613 \tabularnewline
21 & 0.581655 & 0.83669 & 0.418345 \tabularnewline
22 & 0.606459 & 0.787083 & 0.393541 \tabularnewline
23 & 0.707064 & 0.585871 & 0.292936 \tabularnewline
24 & 0.737163 & 0.525674 & 0.262837 \tabularnewline
25 & 0.679304 & 0.641392 & 0.320696 \tabularnewline
26 & 0.641876 & 0.716248 & 0.358124 \tabularnewline
27 & 0.608855 & 0.782289 & 0.391145 \tabularnewline
28 & 0.585189 & 0.829623 & 0.414811 \tabularnewline
29 & 0.542601 & 0.914798 & 0.457399 \tabularnewline
30 & 0.488548 & 0.977096 & 0.511452 \tabularnewline
31 & 0.430342 & 0.860685 & 0.569658 \tabularnewline
32 & 0.372214 & 0.744427 & 0.627786 \tabularnewline
33 & 0.358288 & 0.716576 & 0.641712 \tabularnewline
34 & 0.309895 & 0.619789 & 0.690105 \tabularnewline
35 & 0.277541 & 0.555082 & 0.722459 \tabularnewline
36 & 0.25076 & 0.50152 & 0.74924 \tabularnewline
37 & 0.222231 & 0.444462 & 0.777769 \tabularnewline
38 & 0.211402 & 0.422805 & 0.788598 \tabularnewline
39 & 0.204499 & 0.408999 & 0.795501 \tabularnewline
40 & 0.177208 & 0.354415 & 0.822792 \tabularnewline
41 & 0.246197 & 0.492395 & 0.753803 \tabularnewline
42 & 0.211793 & 0.423587 & 0.788207 \tabularnewline
43 & 0.194121 & 0.388242 & 0.805879 \tabularnewline
44 & 0.164087 & 0.328174 & 0.835913 \tabularnewline
45 & 0.17428 & 0.348561 & 0.82572 \tabularnewline
46 & 0.162319 & 0.324638 & 0.837681 \tabularnewline
47 & 0.202214 & 0.404429 & 0.797786 \tabularnewline
48 & 0.246016 & 0.492031 & 0.753984 \tabularnewline
49 & 0.277212 & 0.554424 & 0.722788 \tabularnewline
50 & 0.249786 & 0.499572 & 0.750214 \tabularnewline
51 & 0.216998 & 0.433995 & 0.783002 \tabularnewline
52 & 0.227453 & 0.454906 & 0.772547 \tabularnewline
53 & 0.197342 & 0.394683 & 0.802658 \tabularnewline
54 & 0.168368 & 0.336736 & 0.831632 \tabularnewline
55 & 0.225982 & 0.451964 & 0.774018 \tabularnewline
56 & 0.194811 & 0.389623 & 0.805189 \tabularnewline
57 & 0.493703 & 0.987407 & 0.506297 \tabularnewline
58 & 0.610165 & 0.779671 & 0.389835 \tabularnewline
59 & 0.574409 & 0.851182 & 0.425591 \tabularnewline
60 & 0.5685 & 0.863 & 0.4315 \tabularnewline
61 & 0.57886 & 0.842279 & 0.42114 \tabularnewline
62 & 0.541454 & 0.917092 & 0.458546 \tabularnewline
63 & 0.54285 & 0.9143 & 0.45715 \tabularnewline
64 & 0.605865 & 0.788271 & 0.394135 \tabularnewline
65 & 0.636151 & 0.727698 & 0.363849 \tabularnewline
66 & 0.603554 & 0.792892 & 0.396446 \tabularnewline
67 & 0.576376 & 0.847247 & 0.423624 \tabularnewline
68 & 0.545458 & 0.909084 & 0.454542 \tabularnewline
69 & 0.558217 & 0.883566 & 0.441783 \tabularnewline
70 & 0.530972 & 0.938056 & 0.469028 \tabularnewline
71 & 0.495303 & 0.990606 & 0.504697 \tabularnewline
72 & 0.462252 & 0.924505 & 0.537748 \tabularnewline
73 & 0.439059 & 0.878117 & 0.560941 \tabularnewline
74 & 0.509147 & 0.981705 & 0.490853 \tabularnewline
75 & 0.503995 & 0.992011 & 0.496005 \tabularnewline
76 & 0.485663 & 0.971327 & 0.514337 \tabularnewline
77 & 0.464052 & 0.928104 & 0.535948 \tabularnewline
78 & 0.445069 & 0.890138 & 0.554931 \tabularnewline
79 & 0.409838 & 0.819677 & 0.590162 \tabularnewline
80 & 0.408369 & 0.816738 & 0.591631 \tabularnewline
81 & 0.373915 & 0.74783 & 0.626085 \tabularnewline
82 & 0.375115 & 0.75023 & 0.624885 \tabularnewline
83 & 0.342269 & 0.684538 & 0.657731 \tabularnewline
84 & 0.567953 & 0.864095 & 0.432047 \tabularnewline
85 & 0.536351 & 0.927298 & 0.463649 \tabularnewline
86 & 0.507145 & 0.98571 & 0.492855 \tabularnewline
87 & 0.493056 & 0.986113 & 0.506944 \tabularnewline
88 & 0.472652 & 0.945304 & 0.527348 \tabularnewline
89 & 0.468333 & 0.936667 & 0.531667 \tabularnewline
90 & 0.444399 & 0.888797 & 0.555601 \tabularnewline
91 & 0.4826 & 0.9652 & 0.5174 \tabularnewline
92 & 0.629966 & 0.740068 & 0.370034 \tabularnewline
93 & 0.614198 & 0.771603 & 0.385802 \tabularnewline
94 & 0.601355 & 0.797291 & 0.398645 \tabularnewline
95 & 0.603958 & 0.792084 & 0.396042 \tabularnewline
96 & 0.605865 & 0.788271 & 0.394135 \tabularnewline
97 & 0.677733 & 0.644534 & 0.322267 \tabularnewline
98 & 0.652231 & 0.695539 & 0.347769 \tabularnewline
99 & 0.690287 & 0.619426 & 0.309713 \tabularnewline
100 & 0.700189 & 0.599623 & 0.299811 \tabularnewline
101 & 0.685847 & 0.628305 & 0.314153 \tabularnewline
102 & 0.653743 & 0.692514 & 0.346257 \tabularnewline
103 & 0.62462 & 0.750759 & 0.37538 \tabularnewline
104 & 0.603678 & 0.792645 & 0.396322 \tabularnewline
105 & 0.685762 & 0.628476 & 0.314238 \tabularnewline
106 & 0.667949 & 0.664101 & 0.332051 \tabularnewline
107 & 0.720026 & 0.559947 & 0.279974 \tabularnewline
108 & 0.818245 & 0.36351 & 0.181755 \tabularnewline
109 & 0.819775 & 0.36045 & 0.180225 \tabularnewline
110 & 0.799891 & 0.400218 & 0.200109 \tabularnewline
111 & 0.777586 & 0.444828 & 0.222414 \tabularnewline
112 & 0.752496 & 0.495009 & 0.247504 \tabularnewline
113 & 0.806245 & 0.38751 & 0.193755 \tabularnewline
114 & 0.870176 & 0.259648 & 0.129824 \tabularnewline
115 & 0.913206 & 0.173588 & 0.0867941 \tabularnewline
116 & 0.917326 & 0.165348 & 0.0826739 \tabularnewline
117 & 0.906198 & 0.187604 & 0.0938021 \tabularnewline
118 & 0.891217 & 0.217565 & 0.108783 \tabularnewline
119 & 0.877363 & 0.245273 & 0.122637 \tabularnewline
120 & 0.882886 & 0.234229 & 0.117114 \tabularnewline
121 & 0.865116 & 0.269769 & 0.134884 \tabularnewline
122 & 0.848743 & 0.302515 & 0.151257 \tabularnewline
123 & 0.85027 & 0.299459 & 0.14973 \tabularnewline
124 & 0.881034 & 0.237932 & 0.118966 \tabularnewline
125 & 0.891171 & 0.217657 & 0.108829 \tabularnewline
126 & 0.877951 & 0.244098 & 0.122049 \tabularnewline
127 & 0.863496 & 0.273007 & 0.136504 \tabularnewline
128 & 0.844465 & 0.31107 & 0.155535 \tabularnewline
129 & 0.851708 & 0.296584 & 0.148292 \tabularnewline
130 & 0.832321 & 0.335358 & 0.167679 \tabularnewline
131 & 0.810461 & 0.379077 & 0.189539 \tabularnewline
132 & 0.789505 & 0.420989 & 0.210495 \tabularnewline
133 & 0.766547 & 0.466906 & 0.233453 \tabularnewline
134 & 0.745476 & 0.509047 & 0.254524 \tabularnewline
135 & 0.720712 & 0.558576 & 0.279288 \tabularnewline
136 & 0.693961 & 0.612078 & 0.306039 \tabularnewline
137 & 0.709105 & 0.58179 & 0.290895 \tabularnewline
138 & 0.706143 & 0.587714 & 0.293857 \tabularnewline
139 & 0.697561 & 0.604877 & 0.302439 \tabularnewline
140 & 0.690695 & 0.618611 & 0.309305 \tabularnewline
141 & 0.679642 & 0.640717 & 0.320358 \tabularnewline
142 & 0.659679 & 0.680642 & 0.340321 \tabularnewline
143 & 0.628023 & 0.743953 & 0.371977 \tabularnewline
144 & 0.649282 & 0.701436 & 0.350718 \tabularnewline
145 & 0.616601 & 0.766797 & 0.383399 \tabularnewline
146 & 0.597527 & 0.804945 & 0.402473 \tabularnewline
147 & 0.565727 & 0.868545 & 0.434273 \tabularnewline
148 & 0.532273 & 0.935453 & 0.467727 \tabularnewline
149 & 0.497537 & 0.995074 & 0.502463 \tabularnewline
150 & 0.475011 & 0.950021 & 0.524989 \tabularnewline
151 & 0.753391 & 0.493218 & 0.246609 \tabularnewline
152 & 0.746979 & 0.506041 & 0.253021 \tabularnewline
153 & 0.744482 & 0.511037 & 0.255518 \tabularnewline
154 & 0.717727 & 0.564546 & 0.282273 \tabularnewline
155 & 0.705568 & 0.588865 & 0.294432 \tabularnewline
156 & 0.677833 & 0.644335 & 0.322167 \tabularnewline
157 & 0.67592 & 0.64816 & 0.32408 \tabularnewline
158 & 0.649637 & 0.700727 & 0.350363 \tabularnewline
159 & 0.630481 & 0.739038 & 0.369519 \tabularnewline
160 & 0.631987 & 0.736026 & 0.368013 \tabularnewline
161 & 0.623834 & 0.752333 & 0.376166 \tabularnewline
162 & 0.621143 & 0.757713 & 0.378857 \tabularnewline
163 & 0.588698 & 0.822604 & 0.411302 \tabularnewline
164 & 0.91853 & 0.162939 & 0.0814696 \tabularnewline
165 & 0.907946 & 0.184108 & 0.0920539 \tabularnewline
166 & 0.901226 & 0.197549 & 0.0987744 \tabularnewline
167 & 0.894703 & 0.210594 & 0.105297 \tabularnewline
168 & 0.882828 & 0.234344 & 0.117172 \tabularnewline
169 & 0.864717 & 0.270567 & 0.135283 \tabularnewline
170 & 0.880353 & 0.239294 & 0.119647 \tabularnewline
171 & 0.872967 & 0.254067 & 0.127033 \tabularnewline
172 & 0.870058 & 0.259884 & 0.129942 \tabularnewline
173 & 0.870144 & 0.259712 & 0.129856 \tabularnewline
174 & 0.854327 & 0.291346 & 0.145673 \tabularnewline
175 & 0.837279 & 0.325443 & 0.162721 \tabularnewline
176 & 0.850489 & 0.299023 & 0.149511 \tabularnewline
177 & 0.831377 & 0.337245 & 0.168623 \tabularnewline
178 & 0.836079 & 0.327842 & 0.163921 \tabularnewline
179 & 0.823287 & 0.353426 & 0.176713 \tabularnewline
180 & 0.851586 & 0.296828 & 0.148414 \tabularnewline
181 & 0.837624 & 0.324751 & 0.162376 \tabularnewline
182 & 0.842332 & 0.315336 & 0.157668 \tabularnewline
183 & 0.871399 & 0.257202 & 0.128601 \tabularnewline
184 & 0.850938 & 0.298124 & 0.149062 \tabularnewline
185 & 0.894266 & 0.211468 & 0.105734 \tabularnewline
186 & 0.876109 & 0.247781 & 0.123891 \tabularnewline
187 & 0.865831 & 0.268338 & 0.134169 \tabularnewline
188 & 0.881599 & 0.236802 & 0.118401 \tabularnewline
189 & 0.923526 & 0.152948 & 0.0764741 \tabularnewline
190 & 0.913178 & 0.173644 & 0.0868218 \tabularnewline
191 & 0.909978 & 0.180044 & 0.090022 \tabularnewline
192 & 0.89627 & 0.20746 & 0.10373 \tabularnewline
193 & 0.904342 & 0.191315 & 0.0956576 \tabularnewline
194 & 0.907852 & 0.184295 & 0.0921477 \tabularnewline
195 & 0.890944 & 0.218112 & 0.109056 \tabularnewline
196 & 0.892176 & 0.215647 & 0.107824 \tabularnewline
197 & 0.886207 & 0.227586 & 0.113793 \tabularnewline
198 & 0.867351 & 0.265297 & 0.132649 \tabularnewline
199 & 0.849541 & 0.300919 & 0.150459 \tabularnewline
200 & 0.825943 & 0.348114 & 0.174057 \tabularnewline
201 & 0.802879 & 0.394242 & 0.197121 \tabularnewline
202 & 0.793857 & 0.412286 & 0.206143 \tabularnewline
203 & 0.796413 & 0.407175 & 0.203587 \tabularnewline
204 & 0.771611 & 0.456779 & 0.228389 \tabularnewline
205 & 0.74671 & 0.506579 & 0.25329 \tabularnewline
206 & 0.731539 & 0.536923 & 0.268461 \tabularnewline
207 & 0.733079 & 0.533843 & 0.266921 \tabularnewline
208 & 0.729702 & 0.540595 & 0.270298 \tabularnewline
209 & 0.736404 & 0.527193 & 0.263596 \tabularnewline
210 & 0.748502 & 0.502996 & 0.251498 \tabularnewline
211 & 0.736171 & 0.527658 & 0.263829 \tabularnewline
212 & 0.701629 & 0.596741 & 0.298371 \tabularnewline
213 & 0.686885 & 0.62623 & 0.313115 \tabularnewline
214 & 0.650684 & 0.698631 & 0.349316 \tabularnewline
215 & 0.616654 & 0.766692 & 0.383346 \tabularnewline
216 & 0.581383 & 0.837234 & 0.418617 \tabularnewline
217 & 0.587393 & 0.825213 & 0.412607 \tabularnewline
218 & 0.555545 & 0.88891 & 0.444455 \tabularnewline
219 & 0.525248 & 0.949503 & 0.474752 \tabularnewline
220 & 0.486239 & 0.972478 & 0.513761 \tabularnewline
221 & 0.461451 & 0.922902 & 0.538549 \tabularnewline
222 & 0.571649 & 0.856702 & 0.428351 \tabularnewline
223 & 0.535804 & 0.928392 & 0.464196 \tabularnewline
224 & 0.52708 & 0.945839 & 0.47292 \tabularnewline
225 & 0.504923 & 0.990154 & 0.495077 \tabularnewline
226 & 0.51875 & 0.962499 & 0.48125 \tabularnewline
227 & 0.490999 & 0.981999 & 0.509001 \tabularnewline
228 & 0.52233 & 0.955341 & 0.47767 \tabularnewline
229 & 0.765233 & 0.469535 & 0.234767 \tabularnewline
230 & 0.788559 & 0.422882 & 0.211441 \tabularnewline
231 & 0.766389 & 0.467223 & 0.233611 \tabularnewline
232 & 0.836874 & 0.326252 & 0.163126 \tabularnewline
233 & 0.808027 & 0.383946 & 0.191973 \tabularnewline
234 & 0.817834 & 0.364333 & 0.182166 \tabularnewline
235 & 0.794312 & 0.411375 & 0.205688 \tabularnewline
236 & 0.857366 & 0.285268 & 0.142634 \tabularnewline
237 & 0.826431 & 0.347137 & 0.173569 \tabularnewline
238 & 0.792642 & 0.414715 & 0.207358 \tabularnewline
239 & 0.851033 & 0.297933 & 0.148967 \tabularnewline
240 & 0.819722 & 0.360557 & 0.180278 \tabularnewline
241 & 0.782249 & 0.435502 & 0.217751 \tabularnewline
242 & 0.753169 & 0.493662 & 0.246831 \tabularnewline
243 & 0.727754 & 0.544492 & 0.272246 \tabularnewline
244 & 0.680688 & 0.638623 & 0.319312 \tabularnewline
245 & 0.657124 & 0.685752 & 0.342876 \tabularnewline
246 & 0.602067 & 0.795867 & 0.397933 \tabularnewline
247 & 0.559218 & 0.881564 & 0.440782 \tabularnewline
248 & 0.586743 & 0.826515 & 0.413257 \tabularnewline
249 & 0.589943 & 0.820114 & 0.410057 \tabularnewline
250 & 0.588224 & 0.823553 & 0.411776 \tabularnewline
251 & 0.536423 & 0.927155 & 0.463577 \tabularnewline
252 & 0.533591 & 0.932817 & 0.466409 \tabularnewline
253 & 0.501176 & 0.997648 & 0.498824 \tabularnewline
254 & 0.46525 & 0.930501 & 0.53475 \tabularnewline
255 & 0.408018 & 0.816035 & 0.591982 \tabularnewline
256 & 0.340571 & 0.681142 & 0.659429 \tabularnewline
257 & 0.399439 & 0.798878 & 0.600561 \tabularnewline
258 & 0.527998 & 0.944004 & 0.472002 \tabularnewline
259 & 0.567564 & 0.864871 & 0.432436 \tabularnewline
260 & 0.933125 & 0.133751 & 0.0668754 \tabularnewline
261 & 0.900301 & 0.199399 & 0.0996993 \tabularnewline
262 & 0.954067 & 0.0918669 & 0.0459334 \tabularnewline
263 & 0.990003 & 0.0199944 & 0.00999722 \tabularnewline
264 & 0.978083 & 0.0438339 & 0.0219169 \tabularnewline
265 & 0.967928 & 0.0641444 & 0.0320722 \tabularnewline
266 & 0.971136 & 0.0577288 & 0.0288644 \tabularnewline
267 & 0.940571 & 0.118858 & 0.0594292 \tabularnewline
268 & 0.873925 & 0.252151 & 0.126075 \tabularnewline
269 & 0.767088 & 0.465824 & 0.232912 \tabularnewline
270 & 0.566208 & 0.867584 & 0.433792 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264381&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]9[/C][C]0.925668[/C][C]0.148663[/C][C]0.0743316[/C][/ROW]
[ROW][C]10[/C][C]0.895012[/C][C]0.209975[/C][C]0.104988[/C][/ROW]
[ROW][C]11[/C][C]0.866107[/C][C]0.267786[/C][C]0.133893[/C][/ROW]
[ROW][C]12[/C][C]0.899253[/C][C]0.201495[/C][C]0.100747[/C][/ROW]
[ROW][C]13[/C][C]0.859646[/C][C]0.280707[/C][C]0.140354[/C][/ROW]
[ROW][C]14[/C][C]0.812721[/C][C]0.374558[/C][C]0.187279[/C][/ROW]
[ROW][C]15[/C][C]0.78526[/C][C]0.42948[/C][C]0.21474[/C][/ROW]
[ROW][C]16[/C][C]0.712905[/C][C]0.574189[/C][C]0.287095[/C][/ROW]
[ROW][C]17[/C][C]0.648864[/C][C]0.702272[/C][C]0.351136[/C][/ROW]
[ROW][C]18[/C][C]0.624938[/C][C]0.750125[/C][C]0.375062[/C][/ROW]
[ROW][C]19[/C][C]0.642091[/C][C]0.715817[/C][C]0.357909[/C][/ROW]
[ROW][C]20[/C][C]0.567387[/C][C]0.865225[/C][C]0.432613[/C][/ROW]
[ROW][C]21[/C][C]0.581655[/C][C]0.83669[/C][C]0.418345[/C][/ROW]
[ROW][C]22[/C][C]0.606459[/C][C]0.787083[/C][C]0.393541[/C][/ROW]
[ROW][C]23[/C][C]0.707064[/C][C]0.585871[/C][C]0.292936[/C][/ROW]
[ROW][C]24[/C][C]0.737163[/C][C]0.525674[/C][C]0.262837[/C][/ROW]
[ROW][C]25[/C][C]0.679304[/C][C]0.641392[/C][C]0.320696[/C][/ROW]
[ROW][C]26[/C][C]0.641876[/C][C]0.716248[/C][C]0.358124[/C][/ROW]
[ROW][C]27[/C][C]0.608855[/C][C]0.782289[/C][C]0.391145[/C][/ROW]
[ROW][C]28[/C][C]0.585189[/C][C]0.829623[/C][C]0.414811[/C][/ROW]
[ROW][C]29[/C][C]0.542601[/C][C]0.914798[/C][C]0.457399[/C][/ROW]
[ROW][C]30[/C][C]0.488548[/C][C]0.977096[/C][C]0.511452[/C][/ROW]
[ROW][C]31[/C][C]0.430342[/C][C]0.860685[/C][C]0.569658[/C][/ROW]
[ROW][C]32[/C][C]0.372214[/C][C]0.744427[/C][C]0.627786[/C][/ROW]
[ROW][C]33[/C][C]0.358288[/C][C]0.716576[/C][C]0.641712[/C][/ROW]
[ROW][C]34[/C][C]0.309895[/C][C]0.619789[/C][C]0.690105[/C][/ROW]
[ROW][C]35[/C][C]0.277541[/C][C]0.555082[/C][C]0.722459[/C][/ROW]
[ROW][C]36[/C][C]0.25076[/C][C]0.50152[/C][C]0.74924[/C][/ROW]
[ROW][C]37[/C][C]0.222231[/C][C]0.444462[/C][C]0.777769[/C][/ROW]
[ROW][C]38[/C][C]0.211402[/C][C]0.422805[/C][C]0.788598[/C][/ROW]
[ROW][C]39[/C][C]0.204499[/C][C]0.408999[/C][C]0.795501[/C][/ROW]
[ROW][C]40[/C][C]0.177208[/C][C]0.354415[/C][C]0.822792[/C][/ROW]
[ROW][C]41[/C][C]0.246197[/C][C]0.492395[/C][C]0.753803[/C][/ROW]
[ROW][C]42[/C][C]0.211793[/C][C]0.423587[/C][C]0.788207[/C][/ROW]
[ROW][C]43[/C][C]0.194121[/C][C]0.388242[/C][C]0.805879[/C][/ROW]
[ROW][C]44[/C][C]0.164087[/C][C]0.328174[/C][C]0.835913[/C][/ROW]
[ROW][C]45[/C][C]0.17428[/C][C]0.348561[/C][C]0.82572[/C][/ROW]
[ROW][C]46[/C][C]0.162319[/C][C]0.324638[/C][C]0.837681[/C][/ROW]
[ROW][C]47[/C][C]0.202214[/C][C]0.404429[/C][C]0.797786[/C][/ROW]
[ROW][C]48[/C][C]0.246016[/C][C]0.492031[/C][C]0.753984[/C][/ROW]
[ROW][C]49[/C][C]0.277212[/C][C]0.554424[/C][C]0.722788[/C][/ROW]
[ROW][C]50[/C][C]0.249786[/C][C]0.499572[/C][C]0.750214[/C][/ROW]
[ROW][C]51[/C][C]0.216998[/C][C]0.433995[/C][C]0.783002[/C][/ROW]
[ROW][C]52[/C][C]0.227453[/C][C]0.454906[/C][C]0.772547[/C][/ROW]
[ROW][C]53[/C][C]0.197342[/C][C]0.394683[/C][C]0.802658[/C][/ROW]
[ROW][C]54[/C][C]0.168368[/C][C]0.336736[/C][C]0.831632[/C][/ROW]
[ROW][C]55[/C][C]0.225982[/C][C]0.451964[/C][C]0.774018[/C][/ROW]
[ROW][C]56[/C][C]0.194811[/C][C]0.389623[/C][C]0.805189[/C][/ROW]
[ROW][C]57[/C][C]0.493703[/C][C]0.987407[/C][C]0.506297[/C][/ROW]
[ROW][C]58[/C][C]0.610165[/C][C]0.779671[/C][C]0.389835[/C][/ROW]
[ROW][C]59[/C][C]0.574409[/C][C]0.851182[/C][C]0.425591[/C][/ROW]
[ROW][C]60[/C][C]0.5685[/C][C]0.863[/C][C]0.4315[/C][/ROW]
[ROW][C]61[/C][C]0.57886[/C][C]0.842279[/C][C]0.42114[/C][/ROW]
[ROW][C]62[/C][C]0.541454[/C][C]0.917092[/C][C]0.458546[/C][/ROW]
[ROW][C]63[/C][C]0.54285[/C][C]0.9143[/C][C]0.45715[/C][/ROW]
[ROW][C]64[/C][C]0.605865[/C][C]0.788271[/C][C]0.394135[/C][/ROW]
[ROW][C]65[/C][C]0.636151[/C][C]0.727698[/C][C]0.363849[/C][/ROW]
[ROW][C]66[/C][C]0.603554[/C][C]0.792892[/C][C]0.396446[/C][/ROW]
[ROW][C]67[/C][C]0.576376[/C][C]0.847247[/C][C]0.423624[/C][/ROW]
[ROW][C]68[/C][C]0.545458[/C][C]0.909084[/C][C]0.454542[/C][/ROW]
[ROW][C]69[/C][C]0.558217[/C][C]0.883566[/C][C]0.441783[/C][/ROW]
[ROW][C]70[/C][C]0.530972[/C][C]0.938056[/C][C]0.469028[/C][/ROW]
[ROW][C]71[/C][C]0.495303[/C][C]0.990606[/C][C]0.504697[/C][/ROW]
[ROW][C]72[/C][C]0.462252[/C][C]0.924505[/C][C]0.537748[/C][/ROW]
[ROW][C]73[/C][C]0.439059[/C][C]0.878117[/C][C]0.560941[/C][/ROW]
[ROW][C]74[/C][C]0.509147[/C][C]0.981705[/C][C]0.490853[/C][/ROW]
[ROW][C]75[/C][C]0.503995[/C][C]0.992011[/C][C]0.496005[/C][/ROW]
[ROW][C]76[/C][C]0.485663[/C][C]0.971327[/C][C]0.514337[/C][/ROW]
[ROW][C]77[/C][C]0.464052[/C][C]0.928104[/C][C]0.535948[/C][/ROW]
[ROW][C]78[/C][C]0.445069[/C][C]0.890138[/C][C]0.554931[/C][/ROW]
[ROW][C]79[/C][C]0.409838[/C][C]0.819677[/C][C]0.590162[/C][/ROW]
[ROW][C]80[/C][C]0.408369[/C][C]0.816738[/C][C]0.591631[/C][/ROW]
[ROW][C]81[/C][C]0.373915[/C][C]0.74783[/C][C]0.626085[/C][/ROW]
[ROW][C]82[/C][C]0.375115[/C][C]0.75023[/C][C]0.624885[/C][/ROW]
[ROW][C]83[/C][C]0.342269[/C][C]0.684538[/C][C]0.657731[/C][/ROW]
[ROW][C]84[/C][C]0.567953[/C][C]0.864095[/C][C]0.432047[/C][/ROW]
[ROW][C]85[/C][C]0.536351[/C][C]0.927298[/C][C]0.463649[/C][/ROW]
[ROW][C]86[/C][C]0.507145[/C][C]0.98571[/C][C]0.492855[/C][/ROW]
[ROW][C]87[/C][C]0.493056[/C][C]0.986113[/C][C]0.506944[/C][/ROW]
[ROW][C]88[/C][C]0.472652[/C][C]0.945304[/C][C]0.527348[/C][/ROW]
[ROW][C]89[/C][C]0.468333[/C][C]0.936667[/C][C]0.531667[/C][/ROW]
[ROW][C]90[/C][C]0.444399[/C][C]0.888797[/C][C]0.555601[/C][/ROW]
[ROW][C]91[/C][C]0.4826[/C][C]0.9652[/C][C]0.5174[/C][/ROW]
[ROW][C]92[/C][C]0.629966[/C][C]0.740068[/C][C]0.370034[/C][/ROW]
[ROW][C]93[/C][C]0.614198[/C][C]0.771603[/C][C]0.385802[/C][/ROW]
[ROW][C]94[/C][C]0.601355[/C][C]0.797291[/C][C]0.398645[/C][/ROW]
[ROW][C]95[/C][C]0.603958[/C][C]0.792084[/C][C]0.396042[/C][/ROW]
[ROW][C]96[/C][C]0.605865[/C][C]0.788271[/C][C]0.394135[/C][/ROW]
[ROW][C]97[/C][C]0.677733[/C][C]0.644534[/C][C]0.322267[/C][/ROW]
[ROW][C]98[/C][C]0.652231[/C][C]0.695539[/C][C]0.347769[/C][/ROW]
[ROW][C]99[/C][C]0.690287[/C][C]0.619426[/C][C]0.309713[/C][/ROW]
[ROW][C]100[/C][C]0.700189[/C][C]0.599623[/C][C]0.299811[/C][/ROW]
[ROW][C]101[/C][C]0.685847[/C][C]0.628305[/C][C]0.314153[/C][/ROW]
[ROW][C]102[/C][C]0.653743[/C][C]0.692514[/C][C]0.346257[/C][/ROW]
[ROW][C]103[/C][C]0.62462[/C][C]0.750759[/C][C]0.37538[/C][/ROW]
[ROW][C]104[/C][C]0.603678[/C][C]0.792645[/C][C]0.396322[/C][/ROW]
[ROW][C]105[/C][C]0.685762[/C][C]0.628476[/C][C]0.314238[/C][/ROW]
[ROW][C]106[/C][C]0.667949[/C][C]0.664101[/C][C]0.332051[/C][/ROW]
[ROW][C]107[/C][C]0.720026[/C][C]0.559947[/C][C]0.279974[/C][/ROW]
[ROW][C]108[/C][C]0.818245[/C][C]0.36351[/C][C]0.181755[/C][/ROW]
[ROW][C]109[/C][C]0.819775[/C][C]0.36045[/C][C]0.180225[/C][/ROW]
[ROW][C]110[/C][C]0.799891[/C][C]0.400218[/C][C]0.200109[/C][/ROW]
[ROW][C]111[/C][C]0.777586[/C][C]0.444828[/C][C]0.222414[/C][/ROW]
[ROW][C]112[/C][C]0.752496[/C][C]0.495009[/C][C]0.247504[/C][/ROW]
[ROW][C]113[/C][C]0.806245[/C][C]0.38751[/C][C]0.193755[/C][/ROW]
[ROW][C]114[/C][C]0.870176[/C][C]0.259648[/C][C]0.129824[/C][/ROW]
[ROW][C]115[/C][C]0.913206[/C][C]0.173588[/C][C]0.0867941[/C][/ROW]
[ROW][C]116[/C][C]0.917326[/C][C]0.165348[/C][C]0.0826739[/C][/ROW]
[ROW][C]117[/C][C]0.906198[/C][C]0.187604[/C][C]0.0938021[/C][/ROW]
[ROW][C]118[/C][C]0.891217[/C][C]0.217565[/C][C]0.108783[/C][/ROW]
[ROW][C]119[/C][C]0.877363[/C][C]0.245273[/C][C]0.122637[/C][/ROW]
[ROW][C]120[/C][C]0.882886[/C][C]0.234229[/C][C]0.117114[/C][/ROW]
[ROW][C]121[/C][C]0.865116[/C][C]0.269769[/C][C]0.134884[/C][/ROW]
[ROW][C]122[/C][C]0.848743[/C][C]0.302515[/C][C]0.151257[/C][/ROW]
[ROW][C]123[/C][C]0.85027[/C][C]0.299459[/C][C]0.14973[/C][/ROW]
[ROW][C]124[/C][C]0.881034[/C][C]0.237932[/C][C]0.118966[/C][/ROW]
[ROW][C]125[/C][C]0.891171[/C][C]0.217657[/C][C]0.108829[/C][/ROW]
[ROW][C]126[/C][C]0.877951[/C][C]0.244098[/C][C]0.122049[/C][/ROW]
[ROW][C]127[/C][C]0.863496[/C][C]0.273007[/C][C]0.136504[/C][/ROW]
[ROW][C]128[/C][C]0.844465[/C][C]0.31107[/C][C]0.155535[/C][/ROW]
[ROW][C]129[/C][C]0.851708[/C][C]0.296584[/C][C]0.148292[/C][/ROW]
[ROW][C]130[/C][C]0.832321[/C][C]0.335358[/C][C]0.167679[/C][/ROW]
[ROW][C]131[/C][C]0.810461[/C][C]0.379077[/C][C]0.189539[/C][/ROW]
[ROW][C]132[/C][C]0.789505[/C][C]0.420989[/C][C]0.210495[/C][/ROW]
[ROW][C]133[/C][C]0.766547[/C][C]0.466906[/C][C]0.233453[/C][/ROW]
[ROW][C]134[/C][C]0.745476[/C][C]0.509047[/C][C]0.254524[/C][/ROW]
[ROW][C]135[/C][C]0.720712[/C][C]0.558576[/C][C]0.279288[/C][/ROW]
[ROW][C]136[/C][C]0.693961[/C][C]0.612078[/C][C]0.306039[/C][/ROW]
[ROW][C]137[/C][C]0.709105[/C][C]0.58179[/C][C]0.290895[/C][/ROW]
[ROW][C]138[/C][C]0.706143[/C][C]0.587714[/C][C]0.293857[/C][/ROW]
[ROW][C]139[/C][C]0.697561[/C][C]0.604877[/C][C]0.302439[/C][/ROW]
[ROW][C]140[/C][C]0.690695[/C][C]0.618611[/C][C]0.309305[/C][/ROW]
[ROW][C]141[/C][C]0.679642[/C][C]0.640717[/C][C]0.320358[/C][/ROW]
[ROW][C]142[/C][C]0.659679[/C][C]0.680642[/C][C]0.340321[/C][/ROW]
[ROW][C]143[/C][C]0.628023[/C][C]0.743953[/C][C]0.371977[/C][/ROW]
[ROW][C]144[/C][C]0.649282[/C][C]0.701436[/C][C]0.350718[/C][/ROW]
[ROW][C]145[/C][C]0.616601[/C][C]0.766797[/C][C]0.383399[/C][/ROW]
[ROW][C]146[/C][C]0.597527[/C][C]0.804945[/C][C]0.402473[/C][/ROW]
[ROW][C]147[/C][C]0.565727[/C][C]0.868545[/C][C]0.434273[/C][/ROW]
[ROW][C]148[/C][C]0.532273[/C][C]0.935453[/C][C]0.467727[/C][/ROW]
[ROW][C]149[/C][C]0.497537[/C][C]0.995074[/C][C]0.502463[/C][/ROW]
[ROW][C]150[/C][C]0.475011[/C][C]0.950021[/C][C]0.524989[/C][/ROW]
[ROW][C]151[/C][C]0.753391[/C][C]0.493218[/C][C]0.246609[/C][/ROW]
[ROW][C]152[/C][C]0.746979[/C][C]0.506041[/C][C]0.253021[/C][/ROW]
[ROW][C]153[/C][C]0.744482[/C][C]0.511037[/C][C]0.255518[/C][/ROW]
[ROW][C]154[/C][C]0.717727[/C][C]0.564546[/C][C]0.282273[/C][/ROW]
[ROW][C]155[/C][C]0.705568[/C][C]0.588865[/C][C]0.294432[/C][/ROW]
[ROW][C]156[/C][C]0.677833[/C][C]0.644335[/C][C]0.322167[/C][/ROW]
[ROW][C]157[/C][C]0.67592[/C][C]0.64816[/C][C]0.32408[/C][/ROW]
[ROW][C]158[/C][C]0.649637[/C][C]0.700727[/C][C]0.350363[/C][/ROW]
[ROW][C]159[/C][C]0.630481[/C][C]0.739038[/C][C]0.369519[/C][/ROW]
[ROW][C]160[/C][C]0.631987[/C][C]0.736026[/C][C]0.368013[/C][/ROW]
[ROW][C]161[/C][C]0.623834[/C][C]0.752333[/C][C]0.376166[/C][/ROW]
[ROW][C]162[/C][C]0.621143[/C][C]0.757713[/C][C]0.378857[/C][/ROW]
[ROW][C]163[/C][C]0.588698[/C][C]0.822604[/C][C]0.411302[/C][/ROW]
[ROW][C]164[/C][C]0.91853[/C][C]0.162939[/C][C]0.0814696[/C][/ROW]
[ROW][C]165[/C][C]0.907946[/C][C]0.184108[/C][C]0.0920539[/C][/ROW]
[ROW][C]166[/C][C]0.901226[/C][C]0.197549[/C][C]0.0987744[/C][/ROW]
[ROW][C]167[/C][C]0.894703[/C][C]0.210594[/C][C]0.105297[/C][/ROW]
[ROW][C]168[/C][C]0.882828[/C][C]0.234344[/C][C]0.117172[/C][/ROW]
[ROW][C]169[/C][C]0.864717[/C][C]0.270567[/C][C]0.135283[/C][/ROW]
[ROW][C]170[/C][C]0.880353[/C][C]0.239294[/C][C]0.119647[/C][/ROW]
[ROW][C]171[/C][C]0.872967[/C][C]0.254067[/C][C]0.127033[/C][/ROW]
[ROW][C]172[/C][C]0.870058[/C][C]0.259884[/C][C]0.129942[/C][/ROW]
[ROW][C]173[/C][C]0.870144[/C][C]0.259712[/C][C]0.129856[/C][/ROW]
[ROW][C]174[/C][C]0.854327[/C][C]0.291346[/C][C]0.145673[/C][/ROW]
[ROW][C]175[/C][C]0.837279[/C][C]0.325443[/C][C]0.162721[/C][/ROW]
[ROW][C]176[/C][C]0.850489[/C][C]0.299023[/C][C]0.149511[/C][/ROW]
[ROW][C]177[/C][C]0.831377[/C][C]0.337245[/C][C]0.168623[/C][/ROW]
[ROW][C]178[/C][C]0.836079[/C][C]0.327842[/C][C]0.163921[/C][/ROW]
[ROW][C]179[/C][C]0.823287[/C][C]0.353426[/C][C]0.176713[/C][/ROW]
[ROW][C]180[/C][C]0.851586[/C][C]0.296828[/C][C]0.148414[/C][/ROW]
[ROW][C]181[/C][C]0.837624[/C][C]0.324751[/C][C]0.162376[/C][/ROW]
[ROW][C]182[/C][C]0.842332[/C][C]0.315336[/C][C]0.157668[/C][/ROW]
[ROW][C]183[/C][C]0.871399[/C][C]0.257202[/C][C]0.128601[/C][/ROW]
[ROW][C]184[/C][C]0.850938[/C][C]0.298124[/C][C]0.149062[/C][/ROW]
[ROW][C]185[/C][C]0.894266[/C][C]0.211468[/C][C]0.105734[/C][/ROW]
[ROW][C]186[/C][C]0.876109[/C][C]0.247781[/C][C]0.123891[/C][/ROW]
[ROW][C]187[/C][C]0.865831[/C][C]0.268338[/C][C]0.134169[/C][/ROW]
[ROW][C]188[/C][C]0.881599[/C][C]0.236802[/C][C]0.118401[/C][/ROW]
[ROW][C]189[/C][C]0.923526[/C][C]0.152948[/C][C]0.0764741[/C][/ROW]
[ROW][C]190[/C][C]0.913178[/C][C]0.173644[/C][C]0.0868218[/C][/ROW]
[ROW][C]191[/C][C]0.909978[/C][C]0.180044[/C][C]0.090022[/C][/ROW]
[ROW][C]192[/C][C]0.89627[/C][C]0.20746[/C][C]0.10373[/C][/ROW]
[ROW][C]193[/C][C]0.904342[/C][C]0.191315[/C][C]0.0956576[/C][/ROW]
[ROW][C]194[/C][C]0.907852[/C][C]0.184295[/C][C]0.0921477[/C][/ROW]
[ROW][C]195[/C][C]0.890944[/C][C]0.218112[/C][C]0.109056[/C][/ROW]
[ROW][C]196[/C][C]0.892176[/C][C]0.215647[/C][C]0.107824[/C][/ROW]
[ROW][C]197[/C][C]0.886207[/C][C]0.227586[/C][C]0.113793[/C][/ROW]
[ROW][C]198[/C][C]0.867351[/C][C]0.265297[/C][C]0.132649[/C][/ROW]
[ROW][C]199[/C][C]0.849541[/C][C]0.300919[/C][C]0.150459[/C][/ROW]
[ROW][C]200[/C][C]0.825943[/C][C]0.348114[/C][C]0.174057[/C][/ROW]
[ROW][C]201[/C][C]0.802879[/C][C]0.394242[/C][C]0.197121[/C][/ROW]
[ROW][C]202[/C][C]0.793857[/C][C]0.412286[/C][C]0.206143[/C][/ROW]
[ROW][C]203[/C][C]0.796413[/C][C]0.407175[/C][C]0.203587[/C][/ROW]
[ROW][C]204[/C][C]0.771611[/C][C]0.456779[/C][C]0.228389[/C][/ROW]
[ROW][C]205[/C][C]0.74671[/C][C]0.506579[/C][C]0.25329[/C][/ROW]
[ROW][C]206[/C][C]0.731539[/C][C]0.536923[/C][C]0.268461[/C][/ROW]
[ROW][C]207[/C][C]0.733079[/C][C]0.533843[/C][C]0.266921[/C][/ROW]
[ROW][C]208[/C][C]0.729702[/C][C]0.540595[/C][C]0.270298[/C][/ROW]
[ROW][C]209[/C][C]0.736404[/C][C]0.527193[/C][C]0.263596[/C][/ROW]
[ROW][C]210[/C][C]0.748502[/C][C]0.502996[/C][C]0.251498[/C][/ROW]
[ROW][C]211[/C][C]0.736171[/C][C]0.527658[/C][C]0.263829[/C][/ROW]
[ROW][C]212[/C][C]0.701629[/C][C]0.596741[/C][C]0.298371[/C][/ROW]
[ROW][C]213[/C][C]0.686885[/C][C]0.62623[/C][C]0.313115[/C][/ROW]
[ROW][C]214[/C][C]0.650684[/C][C]0.698631[/C][C]0.349316[/C][/ROW]
[ROW][C]215[/C][C]0.616654[/C][C]0.766692[/C][C]0.383346[/C][/ROW]
[ROW][C]216[/C][C]0.581383[/C][C]0.837234[/C][C]0.418617[/C][/ROW]
[ROW][C]217[/C][C]0.587393[/C][C]0.825213[/C][C]0.412607[/C][/ROW]
[ROW][C]218[/C][C]0.555545[/C][C]0.88891[/C][C]0.444455[/C][/ROW]
[ROW][C]219[/C][C]0.525248[/C][C]0.949503[/C][C]0.474752[/C][/ROW]
[ROW][C]220[/C][C]0.486239[/C][C]0.972478[/C][C]0.513761[/C][/ROW]
[ROW][C]221[/C][C]0.461451[/C][C]0.922902[/C][C]0.538549[/C][/ROW]
[ROW][C]222[/C][C]0.571649[/C][C]0.856702[/C][C]0.428351[/C][/ROW]
[ROW][C]223[/C][C]0.535804[/C][C]0.928392[/C][C]0.464196[/C][/ROW]
[ROW][C]224[/C][C]0.52708[/C][C]0.945839[/C][C]0.47292[/C][/ROW]
[ROW][C]225[/C][C]0.504923[/C][C]0.990154[/C][C]0.495077[/C][/ROW]
[ROW][C]226[/C][C]0.51875[/C][C]0.962499[/C][C]0.48125[/C][/ROW]
[ROW][C]227[/C][C]0.490999[/C][C]0.981999[/C][C]0.509001[/C][/ROW]
[ROW][C]228[/C][C]0.52233[/C][C]0.955341[/C][C]0.47767[/C][/ROW]
[ROW][C]229[/C][C]0.765233[/C][C]0.469535[/C][C]0.234767[/C][/ROW]
[ROW][C]230[/C][C]0.788559[/C][C]0.422882[/C][C]0.211441[/C][/ROW]
[ROW][C]231[/C][C]0.766389[/C][C]0.467223[/C][C]0.233611[/C][/ROW]
[ROW][C]232[/C][C]0.836874[/C][C]0.326252[/C][C]0.163126[/C][/ROW]
[ROW][C]233[/C][C]0.808027[/C][C]0.383946[/C][C]0.191973[/C][/ROW]
[ROW][C]234[/C][C]0.817834[/C][C]0.364333[/C][C]0.182166[/C][/ROW]
[ROW][C]235[/C][C]0.794312[/C][C]0.411375[/C][C]0.205688[/C][/ROW]
[ROW][C]236[/C][C]0.857366[/C][C]0.285268[/C][C]0.142634[/C][/ROW]
[ROW][C]237[/C][C]0.826431[/C][C]0.347137[/C][C]0.173569[/C][/ROW]
[ROW][C]238[/C][C]0.792642[/C][C]0.414715[/C][C]0.207358[/C][/ROW]
[ROW][C]239[/C][C]0.851033[/C][C]0.297933[/C][C]0.148967[/C][/ROW]
[ROW][C]240[/C][C]0.819722[/C][C]0.360557[/C][C]0.180278[/C][/ROW]
[ROW][C]241[/C][C]0.782249[/C][C]0.435502[/C][C]0.217751[/C][/ROW]
[ROW][C]242[/C][C]0.753169[/C][C]0.493662[/C][C]0.246831[/C][/ROW]
[ROW][C]243[/C][C]0.727754[/C][C]0.544492[/C][C]0.272246[/C][/ROW]
[ROW][C]244[/C][C]0.680688[/C][C]0.638623[/C][C]0.319312[/C][/ROW]
[ROW][C]245[/C][C]0.657124[/C][C]0.685752[/C][C]0.342876[/C][/ROW]
[ROW][C]246[/C][C]0.602067[/C][C]0.795867[/C][C]0.397933[/C][/ROW]
[ROW][C]247[/C][C]0.559218[/C][C]0.881564[/C][C]0.440782[/C][/ROW]
[ROW][C]248[/C][C]0.586743[/C][C]0.826515[/C][C]0.413257[/C][/ROW]
[ROW][C]249[/C][C]0.589943[/C][C]0.820114[/C][C]0.410057[/C][/ROW]
[ROW][C]250[/C][C]0.588224[/C][C]0.823553[/C][C]0.411776[/C][/ROW]
[ROW][C]251[/C][C]0.536423[/C][C]0.927155[/C][C]0.463577[/C][/ROW]
[ROW][C]252[/C][C]0.533591[/C][C]0.932817[/C][C]0.466409[/C][/ROW]
[ROW][C]253[/C][C]0.501176[/C][C]0.997648[/C][C]0.498824[/C][/ROW]
[ROW][C]254[/C][C]0.46525[/C][C]0.930501[/C][C]0.53475[/C][/ROW]
[ROW][C]255[/C][C]0.408018[/C][C]0.816035[/C][C]0.591982[/C][/ROW]
[ROW][C]256[/C][C]0.340571[/C][C]0.681142[/C][C]0.659429[/C][/ROW]
[ROW][C]257[/C][C]0.399439[/C][C]0.798878[/C][C]0.600561[/C][/ROW]
[ROW][C]258[/C][C]0.527998[/C][C]0.944004[/C][C]0.472002[/C][/ROW]
[ROW][C]259[/C][C]0.567564[/C][C]0.864871[/C][C]0.432436[/C][/ROW]
[ROW][C]260[/C][C]0.933125[/C][C]0.133751[/C][C]0.0668754[/C][/ROW]
[ROW][C]261[/C][C]0.900301[/C][C]0.199399[/C][C]0.0996993[/C][/ROW]
[ROW][C]262[/C][C]0.954067[/C][C]0.0918669[/C][C]0.0459334[/C][/ROW]
[ROW][C]263[/C][C]0.990003[/C][C]0.0199944[/C][C]0.00999722[/C][/ROW]
[ROW][C]264[/C][C]0.978083[/C][C]0.0438339[/C][C]0.0219169[/C][/ROW]
[ROW][C]265[/C][C]0.967928[/C][C]0.0641444[/C][C]0.0320722[/C][/ROW]
[ROW][C]266[/C][C]0.971136[/C][C]0.0577288[/C][C]0.0288644[/C][/ROW]
[ROW][C]267[/C][C]0.940571[/C][C]0.118858[/C][C]0.0594292[/C][/ROW]
[ROW][C]268[/C][C]0.873925[/C][C]0.252151[/C][C]0.126075[/C][/ROW]
[ROW][C]269[/C][C]0.767088[/C][C]0.465824[/C][C]0.232912[/C][/ROW]
[ROW][C]270[/C][C]0.566208[/C][C]0.867584[/C][C]0.433792[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264381&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264381&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9256680.1486630.0743316
100.8950120.2099750.104988
110.8661070.2677860.133893
120.8992530.2014950.100747
130.8596460.2807070.140354
140.8127210.3745580.187279
150.785260.429480.21474
160.7129050.5741890.287095
170.6488640.7022720.351136
180.6249380.7501250.375062
190.6420910.7158170.357909
200.5673870.8652250.432613
210.5816550.836690.418345
220.6064590.7870830.393541
230.7070640.5858710.292936
240.7371630.5256740.262837
250.6793040.6413920.320696
260.6418760.7162480.358124
270.6088550.7822890.391145
280.5851890.8296230.414811
290.5426010.9147980.457399
300.4885480.9770960.511452
310.4303420.8606850.569658
320.3722140.7444270.627786
330.3582880.7165760.641712
340.3098950.6197890.690105
350.2775410.5550820.722459
360.250760.501520.74924
370.2222310.4444620.777769
380.2114020.4228050.788598
390.2044990.4089990.795501
400.1772080.3544150.822792
410.2461970.4923950.753803
420.2117930.4235870.788207
430.1941210.3882420.805879
440.1640870.3281740.835913
450.174280.3485610.82572
460.1623190.3246380.837681
470.2022140.4044290.797786
480.2460160.4920310.753984
490.2772120.5544240.722788
500.2497860.4995720.750214
510.2169980.4339950.783002
520.2274530.4549060.772547
530.1973420.3946830.802658
540.1683680.3367360.831632
550.2259820.4519640.774018
560.1948110.3896230.805189
570.4937030.9874070.506297
580.6101650.7796710.389835
590.5744090.8511820.425591
600.56850.8630.4315
610.578860.8422790.42114
620.5414540.9170920.458546
630.542850.91430.45715
640.6058650.7882710.394135
650.6361510.7276980.363849
660.6035540.7928920.396446
670.5763760.8472470.423624
680.5454580.9090840.454542
690.5582170.8835660.441783
700.5309720.9380560.469028
710.4953030.9906060.504697
720.4622520.9245050.537748
730.4390590.8781170.560941
740.5091470.9817050.490853
750.5039950.9920110.496005
760.4856630.9713270.514337
770.4640520.9281040.535948
780.4450690.8901380.554931
790.4098380.8196770.590162
800.4083690.8167380.591631
810.3739150.747830.626085
820.3751150.750230.624885
830.3422690.6845380.657731
840.5679530.8640950.432047
850.5363510.9272980.463649
860.5071450.985710.492855
870.4930560.9861130.506944
880.4726520.9453040.527348
890.4683330.9366670.531667
900.4443990.8887970.555601
910.48260.96520.5174
920.6299660.7400680.370034
930.6141980.7716030.385802
940.6013550.7972910.398645
950.6039580.7920840.396042
960.6058650.7882710.394135
970.6777330.6445340.322267
980.6522310.6955390.347769
990.6902870.6194260.309713
1000.7001890.5996230.299811
1010.6858470.6283050.314153
1020.6537430.6925140.346257
1030.624620.7507590.37538
1040.6036780.7926450.396322
1050.6857620.6284760.314238
1060.6679490.6641010.332051
1070.7200260.5599470.279974
1080.8182450.363510.181755
1090.8197750.360450.180225
1100.7998910.4002180.200109
1110.7775860.4448280.222414
1120.7524960.4950090.247504
1130.8062450.387510.193755
1140.8701760.2596480.129824
1150.9132060.1735880.0867941
1160.9173260.1653480.0826739
1170.9061980.1876040.0938021
1180.8912170.2175650.108783
1190.8773630.2452730.122637
1200.8828860.2342290.117114
1210.8651160.2697690.134884
1220.8487430.3025150.151257
1230.850270.2994590.14973
1240.8810340.2379320.118966
1250.8911710.2176570.108829
1260.8779510.2440980.122049
1270.8634960.2730070.136504
1280.8444650.311070.155535
1290.8517080.2965840.148292
1300.8323210.3353580.167679
1310.8104610.3790770.189539
1320.7895050.4209890.210495
1330.7665470.4669060.233453
1340.7454760.5090470.254524
1350.7207120.5585760.279288
1360.6939610.6120780.306039
1370.7091050.581790.290895
1380.7061430.5877140.293857
1390.6975610.6048770.302439
1400.6906950.6186110.309305
1410.6796420.6407170.320358
1420.6596790.6806420.340321
1430.6280230.7439530.371977
1440.6492820.7014360.350718
1450.6166010.7667970.383399
1460.5975270.8049450.402473
1470.5657270.8685450.434273
1480.5322730.9354530.467727
1490.4975370.9950740.502463
1500.4750110.9500210.524989
1510.7533910.4932180.246609
1520.7469790.5060410.253021
1530.7444820.5110370.255518
1540.7177270.5645460.282273
1550.7055680.5888650.294432
1560.6778330.6443350.322167
1570.675920.648160.32408
1580.6496370.7007270.350363
1590.6304810.7390380.369519
1600.6319870.7360260.368013
1610.6238340.7523330.376166
1620.6211430.7577130.378857
1630.5886980.8226040.411302
1640.918530.1629390.0814696
1650.9079460.1841080.0920539
1660.9012260.1975490.0987744
1670.8947030.2105940.105297
1680.8828280.2343440.117172
1690.8647170.2705670.135283
1700.8803530.2392940.119647
1710.8729670.2540670.127033
1720.8700580.2598840.129942
1730.8701440.2597120.129856
1740.8543270.2913460.145673
1750.8372790.3254430.162721
1760.8504890.2990230.149511
1770.8313770.3372450.168623
1780.8360790.3278420.163921
1790.8232870.3534260.176713
1800.8515860.2968280.148414
1810.8376240.3247510.162376
1820.8423320.3153360.157668
1830.8713990.2572020.128601
1840.8509380.2981240.149062
1850.8942660.2114680.105734
1860.8761090.2477810.123891
1870.8658310.2683380.134169
1880.8815990.2368020.118401
1890.9235260.1529480.0764741
1900.9131780.1736440.0868218
1910.9099780.1800440.090022
1920.896270.207460.10373
1930.9043420.1913150.0956576
1940.9078520.1842950.0921477
1950.8909440.2181120.109056
1960.8921760.2156470.107824
1970.8862070.2275860.113793
1980.8673510.2652970.132649
1990.8495410.3009190.150459
2000.8259430.3481140.174057
2010.8028790.3942420.197121
2020.7938570.4122860.206143
2030.7964130.4071750.203587
2040.7716110.4567790.228389
2050.746710.5065790.25329
2060.7315390.5369230.268461
2070.7330790.5338430.266921
2080.7297020.5405950.270298
2090.7364040.5271930.263596
2100.7485020.5029960.251498
2110.7361710.5276580.263829
2120.7016290.5967410.298371
2130.6868850.626230.313115
2140.6506840.6986310.349316
2150.6166540.7666920.383346
2160.5813830.8372340.418617
2170.5873930.8252130.412607
2180.5555450.888910.444455
2190.5252480.9495030.474752
2200.4862390.9724780.513761
2210.4614510.9229020.538549
2220.5716490.8567020.428351
2230.5358040.9283920.464196
2240.527080.9458390.47292
2250.5049230.9901540.495077
2260.518750.9624990.48125
2270.4909990.9819990.509001
2280.522330.9553410.47767
2290.7652330.4695350.234767
2300.7885590.4228820.211441
2310.7663890.4672230.233611
2320.8368740.3262520.163126
2330.8080270.3839460.191973
2340.8178340.3643330.182166
2350.7943120.4113750.205688
2360.8573660.2852680.142634
2370.8264310.3471370.173569
2380.7926420.4147150.207358
2390.8510330.2979330.148967
2400.8197220.3605570.180278
2410.7822490.4355020.217751
2420.7531690.4936620.246831
2430.7277540.5444920.272246
2440.6806880.6386230.319312
2450.6571240.6857520.342876
2460.6020670.7958670.397933
2470.5592180.8815640.440782
2480.5867430.8265150.413257
2490.5899430.8201140.410057
2500.5882240.8235530.411776
2510.5364230.9271550.463577
2520.5335910.9328170.466409
2530.5011760.9976480.498824
2540.465250.9305010.53475
2550.4080180.8160350.591982
2560.3405710.6811420.659429
2570.3994390.7988780.600561
2580.5279980.9440040.472002
2590.5675640.8648710.432436
2600.9331250.1337510.0668754
2610.9003010.1993990.0996993
2620.9540670.09186690.0459334
2630.9900030.01999440.00999722
2640.9780830.04383390.0219169
2650.9679280.06414440.0320722
2660.9711360.05772880.0288644
2670.9405710.1188580.0594292
2680.8739250.2521510.126075
2690.7670880.4658240.232912
2700.5662080.8675840.433792







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00763359OK
10% type I error level50.019084OK

\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 & 2 & 0.00763359 & OK \tabularnewline
10% type I error level & 5 & 0.019084 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264381&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]2[/C][C]0.00763359[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]5[/C][C]0.019084[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264381&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264381&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00763359OK
10% type I error level50.019084OK



Parameters (Session):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 6 ; 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')
}