FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 16 Dec 2014 12:10:26 +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/16/t1418732011nhuty9i3mtfftym.htm/, Retrieved Thu, 16 May 2024 22:25:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269393, Retrieved Thu, 16 May 2024 22:25:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact62

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-16 12:10:26] [6e8ac1d1765f9a3eaeef7407a694f46f] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.67 2 149 12.9
0.83 1 139 12.2
1 2 148 12.8
0.83 0 158 7.4
0.67 0 128 6.7
0 0 224 12.6
0.83 2 159 14.8
0.5 2 105 13.3
0.83 0 159 11.1
0.33 2 167 8.2
0.5 3 165 11.4
0.67 0 159 6.4
1 0 119 10.6
0.5 2 176 12
0.67 1 54 6.3
0.17 2 91 11.3
0.83 1 163 11.9
0.67 1 124 9.3
0.67 1 137 9.6
0.67 0 121 10
0.5 2 153 6.4
1 1 148 13.8
0.83 1 221 10.8
0.83 1 188 13.8
1 2 149 11.7
0.67 0 244 10.9
1 1 148 16.1
0.83 2 92 13.4
1 3 150 9.9
0.83 2 153 11.5
0.67 1 94 8.3
0.67 0 156 11.7
1 2 132 9
0.67 2 161 9.7
1 3 105 10.8
1 3 97 10.3
0.5 1 151 10.4
0.67 0 131 12.7
0.83 2 166 9.3
1 2 157 11.8
1 2 111 5.9
1 2 145 11.4
1 1 162 13
1 3 163 10.8
0.83 2 59 12.3
0.83 2 187 11.3
0.5 0 109 11.8
0.83 0 90 7.9
0.17 0 105 12.7
0.83 3 83 12.3
1 2 116 11.6
1 0 42 6.7
0.67 2 148 10.9
1 0 155 12.1
1 0 125 13.3
1 2 116 10.1
0.83 3 128 5.7
0.33 0 138 14.3
0.33 1 49 8
1 2 96 13.3
1 2 164 9.3
0.83 0 162 12.5
1 3 99 7.6
0.83 2 202 15.9
0.67 0 186 9.2
0.83 3 66 9.1
0.67 2 183 11.1
0.83 2 214 13
0.67 3 188 14.5
1 0 104 12.2
0.83 1 177 12.3
0.67 2 126 11.4
0.83 1 76 8.8
0.83 2 99 14.6
0.67 0 139 12.6
1 3 78 NA
0.33 0 162 13
0.83 2 108 12.6
1 1 159 13.2
0.83 0 74 9.9
0.83 0 110 7.7
0.5 1 96 10.5
0.5 0 116 13.4
0.83 2 87 10.9
1 1 97 4.3
0.33 2 127 10.3
1 1 106 11.8
0.67 1 80 11.2
0.83 3 74 11.4
1 2 91 8.6
0.83 0 133 13.2
0.83 2 74 12.6
1 1 114 5.6
0.83 0 140 9.9
1 1 95 8.8
0.83 0 98 7.7
0.67 0 121 9
0.83 1 126 7.3
0.83 2 98 11.4
0.83 2 95 13.6
0.83 2 110 7.9
0.67 2 70 10.7
0.83 3 102 10.3
0 0 86 8.3
0.83 0 130 9.6
1 0 96 14.2
0.17 0 102 8.5
0.17 0 100 13.5
0.5 3 94 4.9
0.5 2 52 6.4
1 0 98 9.6
0.67 2 118 11.6
0.83 2 99 11.1
1 0 48 4.35
1 2 50 12.7
1 1 150 18.1
1 3 154 17.85
1 3 109 16.6
1 0 68 12.6
0.83 3 194 17.1
1 2 158 19.1
0.83 2 159 16.1
1 0 67 13.35
0.83 2 147 18.4
0.83 3 39 14.7
1 2 100 10.6
0.67 0 111 12.6
0.83 0 138 16.2
1 0 101 13.6
1 1 131 18.9
0.83 2 101 14.1
1 3 114 14.5
1 0 165 16.15
1 2 114 14.75
0.67 2 111 14.8
1 1 75 12.45
0.83 2 82 12.65
1 2 121 17.35
1 2 32 8.6
0.83 2 150 18.4
0.67 2 117 16.1
0.83 2 71 11.6
1 1 165 17.75
0 0 154 15.25
1 2 126 17.65
1 0 149 16.35
0.67 2 145 17.65
1 0 120 13.6
0.83 0 109 14.35
0.17 0 132 14.75
0.83 3 172 18.25
0.83 0 169 9.9
0.83 2 114 16
0.83 3 156 18.25
0.83 0 172 16.85
1 2 68 14.6
0.83 0 89 13.85
1 3 167 18.95
0.83 2 113 15.6
1 2 115 14.85
0.83 2 78 11.75
1 3 118 18.45
0.83 3 87 15.9
0.83 3 173 17.1
1 2 2 16.1
1 3 162 19.9
1 1 49 10.95
1 2 122 18.45
1 3 96 15.1
1 2 100 15
1 2 82 11.35
1 2 100 15.95
0.83 1 115 18.1
1 3 141 14.6
1 2 165 15.4
1 2 165 15.4
1 1 110 17.6
0.83 1 118 13.35
0.5 0 158 19.1
0.67 1 146 15.35
1 1 49 7.6
0.67 2 90 13.4
1 0 121 13.9
1 3 155 19.1
0.5 1 104 15.25
0.67 1 147 12.9
0.67 3 110 16.1
0.67 3 108 17.35
0.67 3 113 13.15
0.67 3 115 12.15
0.67 0 61 12.6
1 2 60 10.35
0.67 1 109 15.4
0.67 2 68 9.6
0.33 1 111 18.2
0.83 1 77 13.6
1 3 73 14.85
1 1 151 14.75
0.17 0 89 14.1
0.67 1 78 14.9
0.83 1 110 16.25
0.83 2 220 19.25
1 1 65 13.6
0.83 0 141 13.6
1 2 117 15.65
1 2 122 12.75
0.83 3 63 14.6
0.83 0 44 9.85
1 2 52 12.65
0 0 131 19.2
1 1 101 16.6
0.83 2 42 11.2
1 1 152 15.25
0.33 0 107 11.9
0.83 0 77 13.2
0.83 2 154 16.35
0.17 0 103 12.4
0.83 1 96 15.85
0.83 2 175 18.15
0.67 2 57 11.15
1 3 112 15.65
0.83 0 143 17.75
1 0 49 7.65
1 2 110 12.35
1 0 131 15.6
1 3 167 19.3
0.83 2 56 15.2
1 1 137 17.1
0.83 3 86 15.6
0.83 2 121 18.4
0.83 2 149 19.05
0 0 168 18.55
1 1 140 19.1
1 2 88 13.1
1 2 168 12.85
0 0 94 9.5
0.83 3 51 4.5
0.83 1 48 11.85
0.83 0 145 13.6
0 0 66 11.7
0.67 0 85 12.4
1 2 109 13.35
0.67 0 63 11.4
0.83 2 102 14.9
1 3 162 19.9
1 2 86 11.2
1 1 114 14.6
0.83 1 164 17.6
0.83 1 119 14.05
1 0 126 16.1
1 1 132 13.35
1 0 142 11.85
0.67 2 83 11.95
0.83 3 94 14.75
0.33 1 81 15.15
1 2 166 13.2
1 3 110 16.85
0.67 3 64 7.85
1 1 93 7.7
0.83 1 104 12.6
0.67 0 105 7.85
1 1 49 10.95
1 3 88 12.35
0.17 0 95 9.95
0.83 2 102 14.9
0.83 2 99 16.65
1 2 63 13.4
0.67 2 76 13.95
0.5 0 109 15.7
0.67 3 117 16.85
0.83 2 57 10.95
0.83 0 120 15.35
1 2 73 12.2
0.17 0 91 15.1
1 2 108 17.75
0.67 2 105 15.2
0.67 3 117 14.6
0.83 2 119 16.65
0.5 2 31 8.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269393&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269393&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269393&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.44309 + 0.926903Graphical_Interpretation[t] + 0.516591Proportionality_and_Ratio[t] + 0.0263424LFM[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.44309 +  0.926903Graphical_Interpretation[t] +  0.516591Proportionality_and_Ratio[t] +  0.0263424LFM[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269393&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.44309 +  0.926903Graphical_Interpretation[t] +  0.516591Proportionality_and_Ratio[t] +  0.0263424LFM[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269393&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269393&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.44309 + 0.926903Graphical_Interpretation[t] + 0.516591Proportionality_and_Ratio[t] + 0.0263424LFM[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.443090.8768869.6284.33181e-192.16591e-19
Graphical_Interpretation0.9269030.8319081.1140.2661740.133087
Proportionality_and_Ratio0.5165910.1898252.7210.006916760.00345838
LFM0.02634240.004809655.4779.79191e-084.89596e-08

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 8.44309 & 0.876886 & 9.628 & 4.33181e-19 & 2.16591e-19 \tabularnewline
Graphical_Interpretation & 0.926903 & 0.831908 & 1.114 & 0.266174 & 0.133087 \tabularnewline
Proportionality_and_Ratio & 0.516591 & 0.189825 & 2.721 & 0.00691676 & 0.00345838 \tabularnewline
LFM & 0.0263424 & 0.00480965 & 5.477 & 9.79191e-08 & 4.89596e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269393&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]8.44309[/C][C]0.876886[/C][C]9.628[/C][C]4.33181e-19[/C][C]2.16591e-19[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]0.926903[/C][C]0.831908[/C][C]1.114[/C][C]0.266174[/C][C]0.133087[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]0.516591[/C][C]0.189825[/C][C]2.721[/C][C]0.00691676[/C][C]0.00345838[/C][/ROW]
[ROW][C]LFM[/C][C]0.0263424[/C][C]0.00480965[/C][C]5.477[/C][C]9.79191e-08[/C][C]4.89596e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269393&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269393&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.443090.8768869.6284.33181e-192.16591e-19
Graphical_Interpretation0.9269030.8319081.1140.2661740.133087
Proportionality_and_Ratio0.5165910.1898252.7210.006916760.00345838
LFM0.02634240.004809655.4779.79191e-084.89596e-08






Multiple Linear Regression - Regression Statistics
Multiple R0.357876
R-squared0.128075
Adjusted R-squared0.118529
F-TEST (value)13.4158
F-TEST (DF numerator)3
F-TEST (DF denominator)274
p-value3.40179e-08
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.18685
Sum Squared Residuals2782.75

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.357876 \tabularnewline
R-squared & 0.128075 \tabularnewline
Adjusted R-squared & 0.118529 \tabularnewline
F-TEST (value) & 13.4158 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 274 \tabularnewline
p-value & 3.40179e-08 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.18685 \tabularnewline
Sum Squared Residuals & 2782.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269393&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.357876[/C][/ROW]
[ROW][C]R-squared[/C][C]0.128075[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.118529[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]13.4158[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]274[/C][/ROW]
[ROW][C]p-value[/C][C]3.40179e-08[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.18685[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2782.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269393&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269393&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.357876
R-squared0.128075
Adjusted R-squared0.118529
F-TEST (value)13.4158
F-TEST (DF numerator)3
F-TEST (DF denominator)274
p-value3.40179e-08
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.18685
Sum Squared Residuals2782.75






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.0223-1.12232
212.213.3906-1.19061
312.814.3019-1.50185
47.413.3745-5.97452
56.712.4359-5.73594
612.614.3438-1.74379
714.814.4340.365955
813.312.70570.594322
911.113.4009-2.30086
108.214.1813-5.98133
1111.414.8028-3.40281
126.413.2526-6.85256
1310.612.5047-1.90474
141214.576-2.57599
156.311.0032-4.7032
1611.312.031-0.731007
1711.914.0228-2.12282
189.312.8472-3.54717
199.613.1896-3.58962
201012.2515-2.25155
216.413.9701-7.57011
2213.813.78530.0147384
2310.815.5507-4.75068
2413.814.6814-0.881384
2511.714.3282-2.6282
2610.915.4917-4.59166
2716.113.78532.31474
2813.412.66910.730895
299.914.8711-4.97113
3011.514.276-2.77599
318.312.0569-3.75689
3211.713.1735-1.47353
33913.8804-4.88037
349.714.3384-4.63843
3510.813.6857-2.88572
3610.313.475-3.17498
3710.413.4008-3.00084
3812.712.5150.185028
399.314.6184-5.31844
4011.814.5389-2.73893
415.913.3272-7.42718
4211.414.2228-2.82283
431314.1541-1.15406
4410.815.2136-4.41358
4512.311.79980.500194
4611.315.1716-3.87163
4711.811.77790.0221343
487.911.5832-3.68324
4912.711.36661.33338
5012.312.9486-0.648615
5111.613.4589-1.8589
526.710.4764-3.77638
5310.913.996-3.09597
5412.113.4531-1.35307
5513.312.66280.637204
5610.113.4589-3.3589
575.714.134-8.43402
5814.312.38421.91578
59810.5563-2.55634
6013.312.9320.367952
619.314.7233-5.42333
6212.513.4799-0.979891
637.613.5277-5.92767
6415.915.56680.333232
659.213.9638-4.7638
669.112.5008-3.40079
6711.114.918-3.81796
681315.8829-2.88288
6914.515.5663-1.06626
7012.212.10960.0903945
7112.314.3916-2.09162
7211.413.4164-2.01644
738.811.731-2.93104
7414.612.85351.7465
7512.612.7257-0.125711
76NANA-0.0164389
771313.4906-0.490583
7812.613.475-0.875028
7913.214.4618-1.26176
809.914.3101-4.41009
817.79.15201-1.45201
8210.59.062261.43774
8313.415.0374-1.63739
8410.919.0418-8.1418
854.37.12764-2.82764
8610.311.1789-0.878881
8711.812.2881-0.488101
8811.212.5115-1.31153
8911.415.6003-4.20034
908.68.115960.484039
9113.212.79490.405058
9212.619.8896-7.28962
935.68.60036-3.00036
949.913.4891-3.58911
958.812.894-4.09398
967.710.9515-3.25155
97914.7482-5.74816
987.38.72716-1.42716
9911.410.54810.851868
10013.618.8433-5.24327
1017.99.14127-1.24127
10210.713.8491-3.14912
10310.312.7085-2.40854
1048.311.3369-3.03693
1059.67.298872.30113
10614.216.9876-2.78759
1078.56.234912.26509
10813.521.5325-8.0325
1094.99.80953-4.90953
1106.48.75155-2.35155
1119.611.2057-1.6057
11211.613.3535-1.7535
11311.117.3844-6.28443
1144.353.37030.979702
11512.78.437954.26205
11618.115.22652.8735
11717.8515.04112.80891
11816.615.16131.43872
11912.611.37261.22738
12017.112.56534.53472
12119.117.4341.66595
12216.113.88492.21506
12313.359.067944.28206
12418.415.48952.91045
12514.717.1374-2.43742
12610.69.988120.611876
12712.69.247673.35233
12816.214.63061.56942
12913.68.037445.56256
13018.917.70621.19381
13114.113.52280.577198
13214.512.06652.43351
13316.1514.80621.34379
13414.7512.97131.77869
13514.814.21230.587733
13612.4512.20570.244319
13712.658.890613.75939
13817.3519.9961-2.64614
1398.64.396964.20304
14018.415.47942.92064
14116.116.6159-0.515915
14211.68.083083.51692
14317.7514.99982.75018
14415.2511.32233.92768
14517.6514.5953.05499
14616.3512.61693.73305
14717.6516.58111.06892
14813.611.33372.26626
14914.3511.67792.67214
15014.7511.79312.95691
15118.2522.0143-3.76429
1529.97.148642.75136
1531612.62163.37839
15418.2515.14333.10669
15516.8514.44452.40554
15614.612.30692.2931
15713.8510.21893.63105
15818.9516.57232.3777
15915.614.18261.41745
16014.8515.4003-0.550312
16111.757.328174.42183
16218.4515.6042.84602
16315.914.11941.78057
16417.111.45595.64414
16516.111.38724.71276
16619.920.1274-0.227365
16710.956.116954.83305
16818.4516.79861.65136
16915.113.13741.96258
1701516.2133-1.21325
17111.358.437422.91258
17215.9510.60845.34161
17318.118.134-0.0340469
17414.613.94970.650327
17515.414.74970.650327
17615.410.58434.81575
17717.617.08740.512584
17813.357.318646.03136
17919.117.17671.9233
18015.3518.9274-3.57736
1817.66.668120.931884
18213.412.05741.34257
18313.99.802844.09716
18419.116.01273.08726
18515.2515.803-0.553041
18612.910.31162.58845
18716.112.20893.89113
18817.3517.7906-0.440582
18913.1514.6433-1.49327
19012.1510.2211.929
19112.614.2337-1.63372
19210.357.402032.94797
19315.417.6886-2.28858
1949.63.589576.01043
19518.216.35741.84262
19613.611.59282.00724
19714.8513.96430.885711
19814.7511.59513.15486
19914.110.83543.26458
20014.911.27673.62332
20116.2513.04093.20907
20219.2517.24882.00116
20313.612.92670.6733
20413.611.43522.16476
20515.6516.517-0.86695
20612.7510.57182.17823
20714.615.1215-0.521488
2089.858.972980.877017
20912.655.343957.30605
21019.215.14724.05283
21116.616.752-0.151986
21211.29.840631.35937
21315.2514.91760.332393
21411.99.940791.95921
21513.211.15232.04767
21616.3515.26391.08607
21712.48.807883.59212
21815.8512.55553.29448
21918.1518.5988-0.448817
22011.159.370121.77988
22115.6510.87944.77061
22217.7520.7608-3.01077
2237.658.60084-0.950842
22412.359.570852.77915
22515.611.61893.98105
22619.315.82083.47922
22715.211.59553.6045
22817.114.52762.57236
22915.610.6334.96697
23018.413.52064.87938
23119.0513.36865.68138
23218.5513.02455.52548
23319.118.72130.378691
23413.115.0787-1.9787
23512.8514.2693-1.41928
2369.517.1057-7.60566
2374.53.643450.856551
23811.8511.28210.56793
23913.612.08171.51831
24011.710.60321.09678
24112.412.32450.0755006
24213.3512.67370.676311
24311.49.432531.96747
24414.910.18724.71276
24519.921.3686-1.46862
24611.29.489621.71038
24714.611.04923.55083
24817.616.41381.18624
24914.0510.63913.41086
25016.116.1138-0.0137834
25113.3514.6106-1.26062
25211.8512.1837-0.333719
25311.9510.43841.51162
25414.7510.99933.7507
25515.1516.726-1.57602
25613.210.16743.03257
25716.8521.2998-4.4498
2587.8512.4864-4.63643
2597.77.568620.131377
26012.616.5801-3.98007
2617.858.07736-0.227365
26210.9511.8379-0.8879
26312.3513.5032-1.15319
2649.957.982531.96747
26514.911.10353.7965
26616.6515.31271.33725
26713.411.54931.85068
26813.9510.02793.92213
26915.712.5463.15405
27016.8517.6471-0.797121
27110.957.973512.97649
27215.3515.4762-0.126173
27312.28.097824.10218
27415.110.59824.50184
27517.7515.41332.33675
27615.214.2960.904049
27714.611.33033.26965
27816.6519.3063-2.65634
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 & 14.0223 & -1.12232 \tabularnewline
2 & 12.2 & 13.3906 & -1.19061 \tabularnewline
3 & 12.8 & 14.3019 & -1.50185 \tabularnewline
4 & 7.4 & 13.3745 & -5.97452 \tabularnewline
5 & 6.7 & 12.4359 & -5.73594 \tabularnewline
6 & 12.6 & 14.3438 & -1.74379 \tabularnewline
7 & 14.8 & 14.434 & 0.365955 \tabularnewline
8 & 13.3 & 12.7057 & 0.594322 \tabularnewline
9 & 11.1 & 13.4009 & -2.30086 \tabularnewline
10 & 8.2 & 14.1813 & -5.98133 \tabularnewline
11 & 11.4 & 14.8028 & -3.40281 \tabularnewline
12 & 6.4 & 13.2526 & -6.85256 \tabularnewline
13 & 10.6 & 12.5047 & -1.90474 \tabularnewline
14 & 12 & 14.576 & -2.57599 \tabularnewline
15 & 6.3 & 11.0032 & -4.7032 \tabularnewline
16 & 11.3 & 12.031 & -0.731007 \tabularnewline
17 & 11.9 & 14.0228 & -2.12282 \tabularnewline
18 & 9.3 & 12.8472 & -3.54717 \tabularnewline
19 & 9.6 & 13.1896 & -3.58962 \tabularnewline
20 & 10 & 12.2515 & -2.25155 \tabularnewline
21 & 6.4 & 13.9701 & -7.57011 \tabularnewline
22 & 13.8 & 13.7853 & 0.0147384 \tabularnewline
23 & 10.8 & 15.5507 & -4.75068 \tabularnewline
24 & 13.8 & 14.6814 & -0.881384 \tabularnewline
25 & 11.7 & 14.3282 & -2.6282 \tabularnewline
26 & 10.9 & 15.4917 & -4.59166 \tabularnewline
27 & 16.1 & 13.7853 & 2.31474 \tabularnewline
28 & 13.4 & 12.6691 & 0.730895 \tabularnewline
29 & 9.9 & 14.8711 & -4.97113 \tabularnewline
30 & 11.5 & 14.276 & -2.77599 \tabularnewline
31 & 8.3 & 12.0569 & -3.75689 \tabularnewline
32 & 11.7 & 13.1735 & -1.47353 \tabularnewline
33 & 9 & 13.8804 & -4.88037 \tabularnewline
34 & 9.7 & 14.3384 & -4.63843 \tabularnewline
35 & 10.8 & 13.6857 & -2.88572 \tabularnewline
36 & 10.3 & 13.475 & -3.17498 \tabularnewline
37 & 10.4 & 13.4008 & -3.00084 \tabularnewline
38 & 12.7 & 12.515 & 0.185028 \tabularnewline
39 & 9.3 & 14.6184 & -5.31844 \tabularnewline
40 & 11.8 & 14.5389 & -2.73893 \tabularnewline
41 & 5.9 & 13.3272 & -7.42718 \tabularnewline
42 & 11.4 & 14.2228 & -2.82283 \tabularnewline
43 & 13 & 14.1541 & -1.15406 \tabularnewline
44 & 10.8 & 15.2136 & -4.41358 \tabularnewline
45 & 12.3 & 11.7998 & 0.500194 \tabularnewline
46 & 11.3 & 15.1716 & -3.87163 \tabularnewline
47 & 11.8 & 11.7779 & 0.0221343 \tabularnewline
48 & 7.9 & 11.5832 & -3.68324 \tabularnewline
49 & 12.7 & 11.3666 & 1.33338 \tabularnewline
50 & 12.3 & 12.9486 & -0.648615 \tabularnewline
51 & 11.6 & 13.4589 & -1.8589 \tabularnewline
52 & 6.7 & 10.4764 & -3.77638 \tabularnewline
53 & 10.9 & 13.996 & -3.09597 \tabularnewline
54 & 12.1 & 13.4531 & -1.35307 \tabularnewline
55 & 13.3 & 12.6628 & 0.637204 \tabularnewline
56 & 10.1 & 13.4589 & -3.3589 \tabularnewline
57 & 5.7 & 14.134 & -8.43402 \tabularnewline
58 & 14.3 & 12.3842 & 1.91578 \tabularnewline
59 & 8 & 10.5563 & -2.55634 \tabularnewline
60 & 13.3 & 12.932 & 0.367952 \tabularnewline
61 & 9.3 & 14.7233 & -5.42333 \tabularnewline
62 & 12.5 & 13.4799 & -0.979891 \tabularnewline
63 & 7.6 & 13.5277 & -5.92767 \tabularnewline
64 & 15.9 & 15.5668 & 0.333232 \tabularnewline
65 & 9.2 & 13.9638 & -4.7638 \tabularnewline
66 & 9.1 & 12.5008 & -3.40079 \tabularnewline
67 & 11.1 & 14.918 & -3.81796 \tabularnewline
68 & 13 & 15.8829 & -2.88288 \tabularnewline
69 & 14.5 & 15.5663 & -1.06626 \tabularnewline
70 & 12.2 & 12.1096 & 0.0903945 \tabularnewline
71 & 12.3 & 14.3916 & -2.09162 \tabularnewline
72 & 11.4 & 13.4164 & -2.01644 \tabularnewline
73 & 8.8 & 11.731 & -2.93104 \tabularnewline
74 & 14.6 & 12.8535 & 1.7465 \tabularnewline
75 & 12.6 & 12.7257 & -0.125711 \tabularnewline
76 & NA & NA & -0.0164389 \tabularnewline
77 & 13 & 13.4906 & -0.490583 \tabularnewline
78 & 12.6 & 13.475 & -0.875028 \tabularnewline
79 & 13.2 & 14.4618 & -1.26176 \tabularnewline
80 & 9.9 & 14.3101 & -4.41009 \tabularnewline
81 & 7.7 & 9.15201 & -1.45201 \tabularnewline
82 & 10.5 & 9.06226 & 1.43774 \tabularnewline
83 & 13.4 & 15.0374 & -1.63739 \tabularnewline
84 & 10.9 & 19.0418 & -8.1418 \tabularnewline
85 & 4.3 & 7.12764 & -2.82764 \tabularnewline
86 & 10.3 & 11.1789 & -0.878881 \tabularnewline
87 & 11.8 & 12.2881 & -0.488101 \tabularnewline
88 & 11.2 & 12.5115 & -1.31153 \tabularnewline
89 & 11.4 & 15.6003 & -4.20034 \tabularnewline
90 & 8.6 & 8.11596 & 0.484039 \tabularnewline
91 & 13.2 & 12.7949 & 0.405058 \tabularnewline
92 & 12.6 & 19.8896 & -7.28962 \tabularnewline
93 & 5.6 & 8.60036 & -3.00036 \tabularnewline
94 & 9.9 & 13.4891 & -3.58911 \tabularnewline
95 & 8.8 & 12.894 & -4.09398 \tabularnewline
96 & 7.7 & 10.9515 & -3.25155 \tabularnewline
97 & 9 & 14.7482 & -5.74816 \tabularnewline
98 & 7.3 & 8.72716 & -1.42716 \tabularnewline
99 & 11.4 & 10.5481 & 0.851868 \tabularnewline
100 & 13.6 & 18.8433 & -5.24327 \tabularnewline
101 & 7.9 & 9.14127 & -1.24127 \tabularnewline
102 & 10.7 & 13.8491 & -3.14912 \tabularnewline
103 & 10.3 & 12.7085 & -2.40854 \tabularnewline
104 & 8.3 & 11.3369 & -3.03693 \tabularnewline
105 & 9.6 & 7.29887 & 2.30113 \tabularnewline
106 & 14.2 & 16.9876 & -2.78759 \tabularnewline
107 & 8.5 & 6.23491 & 2.26509 \tabularnewline
108 & 13.5 & 21.5325 & -8.0325 \tabularnewline
109 & 4.9 & 9.80953 & -4.90953 \tabularnewline
110 & 6.4 & 8.75155 & -2.35155 \tabularnewline
111 & 9.6 & 11.2057 & -1.6057 \tabularnewline
112 & 11.6 & 13.3535 & -1.7535 \tabularnewline
113 & 11.1 & 17.3844 & -6.28443 \tabularnewline
114 & 4.35 & 3.3703 & 0.979702 \tabularnewline
115 & 12.7 & 8.43795 & 4.26205 \tabularnewline
116 & 18.1 & 15.2265 & 2.8735 \tabularnewline
117 & 17.85 & 15.0411 & 2.80891 \tabularnewline
118 & 16.6 & 15.1613 & 1.43872 \tabularnewline
119 & 12.6 & 11.3726 & 1.22738 \tabularnewline
120 & 17.1 & 12.5653 & 4.53472 \tabularnewline
121 & 19.1 & 17.434 & 1.66595 \tabularnewline
122 & 16.1 & 13.8849 & 2.21506 \tabularnewline
123 & 13.35 & 9.06794 & 4.28206 \tabularnewline
124 & 18.4 & 15.4895 & 2.91045 \tabularnewline
125 & 14.7 & 17.1374 & -2.43742 \tabularnewline
126 & 10.6 & 9.98812 & 0.611876 \tabularnewline
127 & 12.6 & 9.24767 & 3.35233 \tabularnewline
128 & 16.2 & 14.6306 & 1.56942 \tabularnewline
129 & 13.6 & 8.03744 & 5.56256 \tabularnewline
130 & 18.9 & 17.7062 & 1.19381 \tabularnewline
131 & 14.1 & 13.5228 & 0.577198 \tabularnewline
132 & 14.5 & 12.0665 & 2.43351 \tabularnewline
133 & 16.15 & 14.8062 & 1.34379 \tabularnewline
134 & 14.75 & 12.9713 & 1.77869 \tabularnewline
135 & 14.8 & 14.2123 & 0.587733 \tabularnewline
136 & 12.45 & 12.2057 & 0.244319 \tabularnewline
137 & 12.65 & 8.89061 & 3.75939 \tabularnewline
138 & 17.35 & 19.9961 & -2.64614 \tabularnewline
139 & 8.6 & 4.39696 & 4.20304 \tabularnewline
140 & 18.4 & 15.4794 & 2.92064 \tabularnewline
141 & 16.1 & 16.6159 & -0.515915 \tabularnewline
142 & 11.6 & 8.08308 & 3.51692 \tabularnewline
143 & 17.75 & 14.9998 & 2.75018 \tabularnewline
144 & 15.25 & 11.3223 & 3.92768 \tabularnewline
145 & 17.65 & 14.595 & 3.05499 \tabularnewline
146 & 16.35 & 12.6169 & 3.73305 \tabularnewline
147 & 17.65 & 16.5811 & 1.06892 \tabularnewline
148 & 13.6 & 11.3337 & 2.26626 \tabularnewline
149 & 14.35 & 11.6779 & 2.67214 \tabularnewline
150 & 14.75 & 11.7931 & 2.95691 \tabularnewline
151 & 18.25 & 22.0143 & -3.76429 \tabularnewline
152 & 9.9 & 7.14864 & 2.75136 \tabularnewline
153 & 16 & 12.6216 & 3.37839 \tabularnewline
154 & 18.25 & 15.1433 & 3.10669 \tabularnewline
155 & 16.85 & 14.4445 & 2.40554 \tabularnewline
156 & 14.6 & 12.3069 & 2.2931 \tabularnewline
157 & 13.85 & 10.2189 & 3.63105 \tabularnewline
158 & 18.95 & 16.5723 & 2.3777 \tabularnewline
159 & 15.6 & 14.1826 & 1.41745 \tabularnewline
160 & 14.85 & 15.4003 & -0.550312 \tabularnewline
161 & 11.75 & 7.32817 & 4.42183 \tabularnewline
162 & 18.45 & 15.604 & 2.84602 \tabularnewline
163 & 15.9 & 14.1194 & 1.78057 \tabularnewline
164 & 17.1 & 11.4559 & 5.64414 \tabularnewline
165 & 16.1 & 11.3872 & 4.71276 \tabularnewline
166 & 19.9 & 20.1274 & -0.227365 \tabularnewline
167 & 10.95 & 6.11695 & 4.83305 \tabularnewline
168 & 18.45 & 16.7986 & 1.65136 \tabularnewline
169 & 15.1 & 13.1374 & 1.96258 \tabularnewline
170 & 15 & 16.2133 & -1.21325 \tabularnewline
171 & 11.35 & 8.43742 & 2.91258 \tabularnewline
172 & 15.95 & 10.6084 & 5.34161 \tabularnewline
173 & 18.1 & 18.134 & -0.0340469 \tabularnewline
174 & 14.6 & 13.9497 & 0.650327 \tabularnewline
175 & 15.4 & 14.7497 & 0.650327 \tabularnewline
176 & 15.4 & 10.5843 & 4.81575 \tabularnewline
177 & 17.6 & 17.0874 & 0.512584 \tabularnewline
178 & 13.35 & 7.31864 & 6.03136 \tabularnewline
179 & 19.1 & 17.1767 & 1.9233 \tabularnewline
180 & 15.35 & 18.9274 & -3.57736 \tabularnewline
181 & 7.6 & 6.66812 & 0.931884 \tabularnewline
182 & 13.4 & 12.0574 & 1.34257 \tabularnewline
183 & 13.9 & 9.80284 & 4.09716 \tabularnewline
184 & 19.1 & 16.0127 & 3.08726 \tabularnewline
185 & 15.25 & 15.803 & -0.553041 \tabularnewline
186 & 12.9 & 10.3116 & 2.58845 \tabularnewline
187 & 16.1 & 12.2089 & 3.89113 \tabularnewline
188 & 17.35 & 17.7906 & -0.440582 \tabularnewline
189 & 13.15 & 14.6433 & -1.49327 \tabularnewline
190 & 12.15 & 10.221 & 1.929 \tabularnewline
191 & 12.6 & 14.2337 & -1.63372 \tabularnewline
192 & 10.35 & 7.40203 & 2.94797 \tabularnewline
193 & 15.4 & 17.6886 & -2.28858 \tabularnewline
194 & 9.6 & 3.58957 & 6.01043 \tabularnewline
195 & 18.2 & 16.3574 & 1.84262 \tabularnewline
196 & 13.6 & 11.5928 & 2.00724 \tabularnewline
197 & 14.85 & 13.9643 & 0.885711 \tabularnewline
198 & 14.75 & 11.5951 & 3.15486 \tabularnewline
199 & 14.1 & 10.8354 & 3.26458 \tabularnewline
200 & 14.9 & 11.2767 & 3.62332 \tabularnewline
201 & 16.25 & 13.0409 & 3.20907 \tabularnewline
202 & 19.25 & 17.2488 & 2.00116 \tabularnewline
203 & 13.6 & 12.9267 & 0.6733 \tabularnewline
204 & 13.6 & 11.4352 & 2.16476 \tabularnewline
205 & 15.65 & 16.517 & -0.86695 \tabularnewline
206 & 12.75 & 10.5718 & 2.17823 \tabularnewline
207 & 14.6 & 15.1215 & -0.521488 \tabularnewline
208 & 9.85 & 8.97298 & 0.877017 \tabularnewline
209 & 12.65 & 5.34395 & 7.30605 \tabularnewline
210 & 19.2 & 15.1472 & 4.05283 \tabularnewline
211 & 16.6 & 16.752 & -0.151986 \tabularnewline
212 & 11.2 & 9.84063 & 1.35937 \tabularnewline
213 & 15.25 & 14.9176 & 0.332393 \tabularnewline
214 & 11.9 & 9.94079 & 1.95921 \tabularnewline
215 & 13.2 & 11.1523 & 2.04767 \tabularnewline
216 & 16.35 & 15.2639 & 1.08607 \tabularnewline
217 & 12.4 & 8.80788 & 3.59212 \tabularnewline
218 & 15.85 & 12.5555 & 3.29448 \tabularnewline
219 & 18.15 & 18.5988 & -0.448817 \tabularnewline
220 & 11.15 & 9.37012 & 1.77988 \tabularnewline
221 & 15.65 & 10.8794 & 4.77061 \tabularnewline
222 & 17.75 & 20.7608 & -3.01077 \tabularnewline
223 & 7.65 & 8.60084 & -0.950842 \tabularnewline
224 & 12.35 & 9.57085 & 2.77915 \tabularnewline
225 & 15.6 & 11.6189 & 3.98105 \tabularnewline
226 & 19.3 & 15.8208 & 3.47922 \tabularnewline
227 & 15.2 & 11.5955 & 3.6045 \tabularnewline
228 & 17.1 & 14.5276 & 2.57236 \tabularnewline
229 & 15.6 & 10.633 & 4.96697 \tabularnewline
230 & 18.4 & 13.5206 & 4.87938 \tabularnewline
231 & 19.05 & 13.3686 & 5.68138 \tabularnewline
232 & 18.55 & 13.0245 & 5.52548 \tabularnewline
233 & 19.1 & 18.7213 & 0.378691 \tabularnewline
234 & 13.1 & 15.0787 & -1.9787 \tabularnewline
235 & 12.85 & 14.2693 & -1.41928 \tabularnewline
236 & 9.5 & 17.1057 & -7.60566 \tabularnewline
237 & 4.5 & 3.64345 & 0.856551 \tabularnewline
238 & 11.85 & 11.2821 & 0.56793 \tabularnewline
239 & 13.6 & 12.0817 & 1.51831 \tabularnewline
240 & 11.7 & 10.6032 & 1.09678 \tabularnewline
241 & 12.4 & 12.3245 & 0.0755006 \tabularnewline
242 & 13.35 & 12.6737 & 0.676311 \tabularnewline
243 & 11.4 & 9.43253 & 1.96747 \tabularnewline
244 & 14.9 & 10.1872 & 4.71276 \tabularnewline
245 & 19.9 & 21.3686 & -1.46862 \tabularnewline
246 & 11.2 & 9.48962 & 1.71038 \tabularnewline
247 & 14.6 & 11.0492 & 3.55083 \tabularnewline
248 & 17.6 & 16.4138 & 1.18624 \tabularnewline
249 & 14.05 & 10.6391 & 3.41086 \tabularnewline
250 & 16.1 & 16.1138 & -0.0137834 \tabularnewline
251 & 13.35 & 14.6106 & -1.26062 \tabularnewline
252 & 11.85 & 12.1837 & -0.333719 \tabularnewline
253 & 11.95 & 10.4384 & 1.51162 \tabularnewline
254 & 14.75 & 10.9993 & 3.7507 \tabularnewline
255 & 15.15 & 16.726 & -1.57602 \tabularnewline
256 & 13.2 & 10.1674 & 3.03257 \tabularnewline
257 & 16.85 & 21.2998 & -4.4498 \tabularnewline
258 & 7.85 & 12.4864 & -4.63643 \tabularnewline
259 & 7.7 & 7.56862 & 0.131377 \tabularnewline
260 & 12.6 & 16.5801 & -3.98007 \tabularnewline
261 & 7.85 & 8.07736 & -0.227365 \tabularnewline
262 & 10.95 & 11.8379 & -0.8879 \tabularnewline
263 & 12.35 & 13.5032 & -1.15319 \tabularnewline
264 & 9.95 & 7.98253 & 1.96747 \tabularnewline
265 & 14.9 & 11.1035 & 3.7965 \tabularnewline
266 & 16.65 & 15.3127 & 1.33725 \tabularnewline
267 & 13.4 & 11.5493 & 1.85068 \tabularnewline
268 & 13.95 & 10.0279 & 3.92213 \tabularnewline
269 & 15.7 & 12.546 & 3.15405 \tabularnewline
270 & 16.85 & 17.6471 & -0.797121 \tabularnewline
271 & 10.95 & 7.97351 & 2.97649 \tabularnewline
272 & 15.35 & 15.4762 & -0.126173 \tabularnewline
273 & 12.2 & 8.09782 & 4.10218 \tabularnewline
274 & 15.1 & 10.5982 & 4.50184 \tabularnewline
275 & 17.75 & 15.4133 & 2.33675 \tabularnewline
276 & 15.2 & 14.296 & 0.904049 \tabularnewline
277 & 14.6 & 11.3303 & 3.26965 \tabularnewline
278 & 16.65 & 19.3063 & -2.65634 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269393&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]14.0223[/C][C]-1.12232[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]13.3906[/C][C]-1.19061[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]14.3019[/C][C]-1.50185[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]13.3745[/C][C]-5.97452[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]12.4359[/C][C]-5.73594[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]14.3438[/C][C]-1.74379[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]14.434[/C][C]0.365955[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]12.7057[/C][C]0.594322[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]13.4009[/C][C]-2.30086[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.1813[/C][C]-5.98133[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]14.8028[/C][C]-3.40281[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]13.2526[/C][C]-6.85256[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]12.5047[/C][C]-1.90474[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]14.576[/C][C]-2.57599[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]11.0032[/C][C]-4.7032[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.031[/C][C]-0.731007[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]14.0228[/C][C]-2.12282[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.8472[/C][C]-3.54717[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]13.1896[/C][C]-3.58962[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.2515[/C][C]-2.25155[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]13.9701[/C][C]-7.57011[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]13.7853[/C][C]0.0147384[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]15.5507[/C][C]-4.75068[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]14.6814[/C][C]-0.881384[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]14.3282[/C][C]-2.6282[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]15.4917[/C][C]-4.59166[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.7853[/C][C]2.31474[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]12.6691[/C][C]0.730895[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]14.8711[/C][C]-4.97113[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]14.276[/C][C]-2.77599[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.0569[/C][C]-3.75689[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.1735[/C][C]-1.47353[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]13.8804[/C][C]-4.88037[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]14.3384[/C][C]-4.63843[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]13.6857[/C][C]-2.88572[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]13.475[/C][C]-3.17498[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]13.4008[/C][C]-3.00084[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.515[/C][C]0.185028[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]14.6184[/C][C]-5.31844[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.5389[/C][C]-2.73893[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.3272[/C][C]-7.42718[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]14.2228[/C][C]-2.82283[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]14.1541[/C][C]-1.15406[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]15.2136[/C][C]-4.41358[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]11.7998[/C][C]0.500194[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]15.1716[/C][C]-3.87163[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]11.7779[/C][C]0.0221343[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]11.5832[/C][C]-3.68324[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]11.3666[/C][C]1.33338[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]12.9486[/C][C]-0.648615[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]13.4589[/C][C]-1.8589[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.4764[/C][C]-3.77638[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.996[/C][C]-3.09597[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]13.4531[/C][C]-1.35307[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]12.6628[/C][C]0.637204[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.4589[/C][C]-3.3589[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]14.134[/C][C]-8.43402[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.3842[/C][C]1.91578[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]10.5563[/C][C]-2.55634[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.932[/C][C]0.367952[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]14.7233[/C][C]-5.42333[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]13.4799[/C][C]-0.979891[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]13.5277[/C][C]-5.92767[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]15.5668[/C][C]0.333232[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.9638[/C][C]-4.7638[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]12.5008[/C][C]-3.40079[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]14.918[/C][C]-3.81796[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]15.8829[/C][C]-2.88288[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]15.5663[/C][C]-1.06626[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.1096[/C][C]0.0903945[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]14.3916[/C][C]-2.09162[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]13.4164[/C][C]-2.01644[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.731[/C][C]-2.93104[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]12.8535[/C][C]1.7465[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.7257[/C][C]-0.125711[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]-0.0164389[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]13.4906[/C][C]-0.490583[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]13.475[/C][C]-0.875028[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]14.4618[/C][C]-1.26176[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]14.3101[/C][C]-4.41009[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]9.15201[/C][C]-1.45201[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]9.06226[/C][C]1.43774[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]15.0374[/C][C]-1.63739[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]19.0418[/C][C]-8.1418[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]7.12764[/C][C]-2.82764[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]11.1789[/C][C]-0.878881[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]12.2881[/C][C]-0.488101[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]12.5115[/C][C]-1.31153[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]15.6003[/C][C]-4.20034[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]8.11596[/C][C]0.484039[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]12.7949[/C][C]0.405058[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]19.8896[/C][C]-7.28962[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]8.60036[/C][C]-3.00036[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]13.4891[/C][C]-3.58911[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]12.894[/C][C]-4.09398[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]10.9515[/C][C]-3.25155[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]14.7482[/C][C]-5.74816[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]8.72716[/C][C]-1.42716[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]10.5481[/C][C]0.851868[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]18.8433[/C][C]-5.24327[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]9.14127[/C][C]-1.24127[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]13.8491[/C][C]-3.14912[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]12.7085[/C][C]-2.40854[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]11.3369[/C][C]-3.03693[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]7.29887[/C][C]2.30113[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]16.9876[/C][C]-2.78759[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]6.23491[/C][C]2.26509[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]21.5325[/C][C]-8.0325[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]9.80953[/C][C]-4.90953[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]8.75155[/C][C]-2.35155[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]11.2057[/C][C]-1.6057[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]13.3535[/C][C]-1.7535[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]17.3844[/C][C]-6.28443[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]3.3703[/C][C]0.979702[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]8.43795[/C][C]4.26205[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]15.2265[/C][C]2.8735[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]15.0411[/C][C]2.80891[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]15.1613[/C][C]1.43872[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]11.3726[/C][C]1.22738[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]12.5653[/C][C]4.53472[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]17.434[/C][C]1.66595[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]13.8849[/C][C]2.21506[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]9.06794[/C][C]4.28206[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]15.4895[/C][C]2.91045[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.1374[/C][C]-2.43742[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]9.98812[/C][C]0.611876[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]9.24767[/C][C]3.35233[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]14.6306[/C][C]1.56942[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]8.03744[/C][C]5.56256[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]17.7062[/C][C]1.19381[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]13.5228[/C][C]0.577198[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]12.0665[/C][C]2.43351[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.8062[/C][C]1.34379[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]12.9713[/C][C]1.77869[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]14.2123[/C][C]0.587733[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.2057[/C][C]0.244319[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]8.89061[/C][C]3.75939[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]19.9961[/C][C]-2.64614[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]4.39696[/C][C]4.20304[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]15.4794[/C][C]2.92064[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]16.6159[/C][C]-0.515915[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]8.08308[/C][C]3.51692[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]14.9998[/C][C]2.75018[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]11.3223[/C][C]3.92768[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]14.595[/C][C]3.05499[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]12.6169[/C][C]3.73305[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]16.5811[/C][C]1.06892[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]11.3337[/C][C]2.26626[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]11.6779[/C][C]2.67214[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]11.7931[/C][C]2.95691[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]22.0143[/C][C]-3.76429[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]7.14864[/C][C]2.75136[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]12.6216[/C][C]3.37839[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]15.1433[/C][C]3.10669[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]14.4445[/C][C]2.40554[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]12.3069[/C][C]2.2931[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]10.2189[/C][C]3.63105[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]16.5723[/C][C]2.3777[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]14.1826[/C][C]1.41745[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.4003[/C][C]-0.550312[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]7.32817[/C][C]4.42183[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.604[/C][C]2.84602[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]14.1194[/C][C]1.78057[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]11.4559[/C][C]5.64414[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]11.3872[/C][C]4.71276[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]20.1274[/C][C]-0.227365[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]6.11695[/C][C]4.83305[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]16.7986[/C][C]1.65136[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]13.1374[/C][C]1.96258[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]16.2133[/C][C]-1.21325[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]8.43742[/C][C]2.91258[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]10.6084[/C][C]5.34161[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]18.134[/C][C]-0.0340469[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]13.9497[/C][C]0.650327[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]14.7497[/C][C]0.650327[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]10.5843[/C][C]4.81575[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]17.0874[/C][C]0.512584[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]7.31864[/C][C]6.03136[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]17.1767[/C][C]1.9233[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]18.9274[/C][C]-3.57736[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]6.66812[/C][C]0.931884[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]12.0574[/C][C]1.34257[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]9.80284[/C][C]4.09716[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]16.0127[/C][C]3.08726[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]15.803[/C][C]-0.553041[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]10.3116[/C][C]2.58845[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]12.2089[/C][C]3.89113[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]17.7906[/C][C]-0.440582[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]14.6433[/C][C]-1.49327[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]10.221[/C][C]1.929[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]14.2337[/C][C]-1.63372[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]7.40203[/C][C]2.94797[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]17.6886[/C][C]-2.28858[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]3.58957[/C][C]6.01043[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]16.3574[/C][C]1.84262[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]11.5928[/C][C]2.00724[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]13.9643[/C][C]0.885711[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]11.5951[/C][C]3.15486[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]10.8354[/C][C]3.26458[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.2767[/C][C]3.62332[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]13.0409[/C][C]3.20907[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]17.2488[/C][C]2.00116[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]12.9267[/C][C]0.6733[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]11.4352[/C][C]2.16476[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]16.517[/C][C]-0.86695[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]10.5718[/C][C]2.17823[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]15.1215[/C][C]-0.521488[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]8.97298[/C][C]0.877017[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]5.34395[/C][C]7.30605[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]15.1472[/C][C]4.05283[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]16.752[/C][C]-0.151986[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]9.84063[/C][C]1.35937[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]14.9176[/C][C]0.332393[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]9.94079[/C][C]1.95921[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]11.1523[/C][C]2.04767[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]15.2639[/C][C]1.08607[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]8.80788[/C][C]3.59212[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]12.5555[/C][C]3.29448[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]18.5988[/C][C]-0.448817[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]9.37012[/C][C]1.77988[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]10.8794[/C][C]4.77061[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]20.7608[/C][C]-3.01077[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]8.60084[/C][C]-0.950842[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]9.57085[/C][C]2.77915[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]11.6189[/C][C]3.98105[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]15.8208[/C][C]3.47922[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]11.5955[/C][C]3.6045[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]14.5276[/C][C]2.57236[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]10.633[/C][C]4.96697[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]13.5206[/C][C]4.87938[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]13.3686[/C][C]5.68138[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]13.0245[/C][C]5.52548[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]18.7213[/C][C]0.378691[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]15.0787[/C][C]-1.9787[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]14.2693[/C][C]-1.41928[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]17.1057[/C][C]-7.60566[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]3.64345[/C][C]0.856551[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]11.2821[/C][C]0.56793[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]12.0817[/C][C]1.51831[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]10.6032[/C][C]1.09678[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]12.3245[/C][C]0.0755006[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]12.6737[/C][C]0.676311[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]9.43253[/C][C]1.96747[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]10.1872[/C][C]4.71276[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]21.3686[/C][C]-1.46862[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]9.48962[/C][C]1.71038[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]11.0492[/C][C]3.55083[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]16.4138[/C][C]1.18624[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]10.6391[/C][C]3.41086[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]16.1138[/C][C]-0.0137834[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]14.6106[/C][C]-1.26062[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]12.1837[/C][C]-0.333719[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]10.4384[/C][C]1.51162[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]10.9993[/C][C]3.7507[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]16.726[/C][C]-1.57602[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]10.1674[/C][C]3.03257[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.2998[/C][C]-4.4498[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]12.4864[/C][C]-4.63643[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]7.56862[/C][C]0.131377[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]16.5801[/C][C]-3.98007[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]8.07736[/C][C]-0.227365[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]11.8379[/C][C]-0.8879[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]13.5032[/C][C]-1.15319[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]7.98253[/C][C]1.96747[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]11.1035[/C][C]3.7965[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]15.3127[/C][C]1.33725[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]11.5493[/C][C]1.85068[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]10.0279[/C][C]3.92213[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]12.546[/C][C]3.15405[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]17.6471[/C][C]-0.797121[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]7.97351[/C][C]2.97649[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]15.4762[/C][C]-0.126173[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]8.09782[/C][C]4.10218[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]10.5982[/C][C]4.50184[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.4133[/C][C]2.33675[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]14.296[/C][C]0.904049[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]11.3303[/C][C]3.26965[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]19.3063[/C][C]-2.65634[/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=269393&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269393&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.0223-1.12232
212.213.3906-1.19061
312.814.3019-1.50185
47.413.3745-5.97452
56.712.4359-5.73594
612.614.3438-1.74379
714.814.4340.365955
813.312.70570.594322
911.113.4009-2.30086
108.214.1813-5.98133
1111.414.8028-3.40281
126.413.2526-6.85256
1310.612.5047-1.90474
141214.576-2.57599
156.311.0032-4.7032
1611.312.031-0.731007
1711.914.0228-2.12282
189.312.8472-3.54717
199.613.1896-3.58962
201012.2515-2.25155
216.413.9701-7.57011
2213.813.78530.0147384
2310.815.5507-4.75068
2413.814.6814-0.881384
2511.714.3282-2.6282
2610.915.4917-4.59166
2716.113.78532.31474
2813.412.66910.730895
299.914.8711-4.97113
3011.514.276-2.77599
318.312.0569-3.75689
3211.713.1735-1.47353
33913.8804-4.88037
349.714.3384-4.63843
3510.813.6857-2.88572
3610.313.475-3.17498
3710.413.4008-3.00084
3812.712.5150.185028
399.314.6184-5.31844
4011.814.5389-2.73893
415.913.3272-7.42718
4211.414.2228-2.82283
431314.1541-1.15406
4410.815.2136-4.41358
4512.311.79980.500194
4611.315.1716-3.87163
4711.811.77790.0221343
487.911.5832-3.68324
4912.711.36661.33338
5012.312.9486-0.648615
5111.613.4589-1.8589
526.710.4764-3.77638
5310.913.996-3.09597
5412.113.4531-1.35307
5513.312.66280.637204
5610.113.4589-3.3589
575.714.134-8.43402
5814.312.38421.91578
59810.5563-2.55634
6013.312.9320.367952
619.314.7233-5.42333
6212.513.4799-0.979891
637.613.5277-5.92767
6415.915.56680.333232
659.213.9638-4.7638
669.112.5008-3.40079
6711.114.918-3.81796
681315.8829-2.88288
6914.515.5663-1.06626
7012.212.10960.0903945
7112.314.3916-2.09162
7211.413.4164-2.01644
738.811.731-2.93104
7414.612.85351.7465
7512.612.7257-0.125711
76NANA-0.0164389
771313.4906-0.490583
7812.613.475-0.875028
7913.214.4618-1.26176
809.914.3101-4.41009
817.79.15201-1.45201
8210.59.062261.43774
8313.415.0374-1.63739
8410.919.0418-8.1418
854.37.12764-2.82764
8610.311.1789-0.878881
8711.812.2881-0.488101
8811.212.5115-1.31153
8911.415.6003-4.20034
908.68.115960.484039
9113.212.79490.405058
9212.619.8896-7.28962
935.68.60036-3.00036
949.913.4891-3.58911
958.812.894-4.09398
967.710.9515-3.25155
97914.7482-5.74816
987.38.72716-1.42716
9911.410.54810.851868
10013.618.8433-5.24327
1017.99.14127-1.24127
10210.713.8491-3.14912
10310.312.7085-2.40854
1048.311.3369-3.03693
1059.67.298872.30113
10614.216.9876-2.78759
1078.56.234912.26509
10813.521.5325-8.0325
1094.99.80953-4.90953
1106.48.75155-2.35155
1119.611.2057-1.6057
11211.613.3535-1.7535
11311.117.3844-6.28443
1144.353.37030.979702
11512.78.437954.26205
11618.115.22652.8735
11717.8515.04112.80891
11816.615.16131.43872
11912.611.37261.22738
12017.112.56534.53472
12119.117.4341.66595
12216.113.88492.21506
12313.359.067944.28206
12418.415.48952.91045
12514.717.1374-2.43742
12610.69.988120.611876
12712.69.247673.35233
12816.214.63061.56942
12913.68.037445.56256
13018.917.70621.19381
13114.113.52280.577198
13214.512.06652.43351
13316.1514.80621.34379
13414.7512.97131.77869
13514.814.21230.587733
13612.4512.20570.244319
13712.658.890613.75939
13817.3519.9961-2.64614
1398.64.396964.20304
14018.415.47942.92064
14116.116.6159-0.515915
14211.68.083083.51692
14317.7514.99982.75018
14415.2511.32233.92768
14517.6514.5953.05499
14616.3512.61693.73305
14717.6516.58111.06892
14813.611.33372.26626
14914.3511.67792.67214
15014.7511.79312.95691
15118.2522.0143-3.76429
1529.97.148642.75136
1531612.62163.37839
15418.2515.14333.10669
15516.8514.44452.40554
15614.612.30692.2931
15713.8510.21893.63105
15818.9516.57232.3777
15915.614.18261.41745
16014.8515.4003-0.550312
16111.757.328174.42183
16218.4515.6042.84602
16315.914.11941.78057
16417.111.45595.64414
16516.111.38724.71276
16619.920.1274-0.227365
16710.956.116954.83305
16818.4516.79861.65136
16915.113.13741.96258
1701516.2133-1.21325
17111.358.437422.91258
17215.9510.60845.34161
17318.118.134-0.0340469
17414.613.94970.650327
17515.414.74970.650327
17615.410.58434.81575
17717.617.08740.512584
17813.357.318646.03136
17919.117.17671.9233
18015.3518.9274-3.57736
1817.66.668120.931884
18213.412.05741.34257
18313.99.802844.09716
18419.116.01273.08726
18515.2515.803-0.553041
18612.910.31162.58845
18716.112.20893.89113
18817.3517.7906-0.440582
18913.1514.6433-1.49327
19012.1510.2211.929
19112.614.2337-1.63372
19210.357.402032.94797
19315.417.6886-2.28858
1949.63.589576.01043
19518.216.35741.84262
19613.611.59282.00724
19714.8513.96430.885711
19814.7511.59513.15486
19914.110.83543.26458
20014.911.27673.62332
20116.2513.04093.20907
20219.2517.24882.00116
20313.612.92670.6733
20413.611.43522.16476
20515.6516.517-0.86695
20612.7510.57182.17823
20714.615.1215-0.521488
2089.858.972980.877017
20912.655.343957.30605
21019.215.14724.05283
21116.616.752-0.151986
21211.29.840631.35937
21315.2514.91760.332393
21411.99.940791.95921
21513.211.15232.04767
21616.3515.26391.08607
21712.48.807883.59212
21815.8512.55553.29448
21918.1518.5988-0.448817
22011.159.370121.77988
22115.6510.87944.77061
22217.7520.7608-3.01077
2237.658.60084-0.950842
22412.359.570852.77915
22515.611.61893.98105
22619.315.82083.47922
22715.211.59553.6045
22817.114.52762.57236
22915.610.6334.96697
23018.413.52064.87938
23119.0513.36865.68138
23218.5513.02455.52548
23319.118.72130.378691
23413.115.0787-1.9787
23512.8514.2693-1.41928
2369.517.1057-7.60566
2374.53.643450.856551
23811.8511.28210.56793
23913.612.08171.51831
24011.710.60321.09678
24112.412.32450.0755006
24213.3512.67370.676311
24311.49.432531.96747
24414.910.18724.71276
24519.921.3686-1.46862
24611.29.489621.71038
24714.611.04923.55083
24817.616.41381.18624
24914.0510.63913.41086
25016.116.1138-0.0137834
25113.3514.6106-1.26062
25211.8512.1837-0.333719
25311.9510.43841.51162
25414.7510.99933.7507
25515.1516.726-1.57602
25613.210.16743.03257
25716.8521.2998-4.4498
2587.8512.4864-4.63643
2597.77.568620.131377
26012.616.5801-3.98007
2617.858.07736-0.227365
26210.9511.8379-0.8879
26312.3513.5032-1.15319
2649.957.982531.96747
26514.911.10353.7965
26616.6515.31271.33725
26713.411.54931.85068
26813.9510.02793.92213
26915.712.5463.15405
27016.8517.6471-0.797121
27110.957.973512.97649
27215.3515.4762-0.126173
27312.28.097824.10218
27415.110.59824.50184
27517.7515.41332.33675
27615.214.2960.904049
27714.611.33033.26965
27816.6519.3063-2.65634
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.1089050.217810.891095
80.04198610.08397220.958014
90.06522080.1304420.934779
100.383970.767940.61603
110.3525260.7050520.647474
120.3688710.7377420.631129
130.3005810.6011620.699419
140.2206810.4413620.779319
150.1758450.351690.824155
160.1492860.2985710.850714
170.1060350.2120710.893965
180.07414670.1482930.925853
190.05094520.101890.949055
200.0388930.07778590.961107
210.1175490.2350990.882451
220.1119190.2238370.888081
230.09664180.1932840.903358
240.0837980.1675960.916202
250.06254420.1250880.937456
260.0486110.09722190.951389
270.0871740.1743480.912826
280.07642090.1528420.923579
290.1051910.2103820.894809
300.08231990.164640.91768
310.06830460.1366090.931695
320.05790570.1158110.942094
330.06338180.1267640.936618
340.05832330.1166470.941677
350.0460180.09203590.953982
360.03675550.07351110.963244
370.02825670.05651350.971743
380.02935550.0587110.970644
390.03108430.06216860.968916
400.02377470.04754950.976225
410.05527650.1105530.944724
420.04411480.08822950.955885
430.03759410.07518830.962406
440.03358460.06716930.966415
450.03284940.06569870.967151
460.02825210.05650430.971748
470.0251150.05022990.974885
480.02310860.04621720.976891
490.02538740.05077470.974613
500.02123420.04246840.978766
510.01657020.03314050.98343
520.01661820.03323650.983382
530.01357430.02714860.986426
540.01127330.02254650.988727
550.01166420.02332830.988336
560.009582350.01916470.990418
570.03205010.06410020.96795
580.03908150.0781630.960918
590.03328160.06656320.966718
600.03399230.06798460.966008
610.03894710.07789420.961053
620.03334230.06668460.966658
630.04128110.08256220.958719
640.05300340.1060070.946997
650.06377380.1275480.936226
660.05565830.1113170.944342
670.05617130.1123430.943829
680.05736450.1147290.942635
690.06243670.1248730.937563
700.05595930.1119190.944041
710.05217670.1043530.947823
720.04636280.09272560.953637
730.04049590.08099170.959504
740.05391790.1078360.946082
750.0482880.09657610.951712
760.04435440.08870870.955646
770.0406860.08137210.959314
780.03768910.07537830.962311
790.0304770.0609540.969523
800.03678030.07356060.96322
810.0308040.0616080.969196
820.03108020.06216030.96892
830.02607080.05214170.973929
840.08710630.1742130.912894
850.08542530.1708510.914575
860.0762740.1525480.923726
870.06616840.1323370.933832
880.05841450.1168290.941585
890.06116410.1223280.938836
900.057940.115880.94206
910.05586730.1117350.944133
920.128640.257280.87136
930.1325190.2650380.867481
940.1343350.268670.865665
950.1521060.3042130.847894
960.1617010.3234020.838299
970.2432910.4865820.756709
980.228180.456360.77182
990.2351560.4703130.764844
1000.3011820.6023630.698818
1010.2769780.5539560.723022
1020.2800610.5601220.719939
1030.282440.564880.71756
1040.3022310.6044620.697769
1050.3395340.6790690.660466
1060.3578570.7157130.642143
1070.3671990.7343980.632801
1080.6503620.6992760.349638
1090.7148450.5703090.285155
1100.7108620.5782760.289138
1110.7149720.5700550.285028
1120.7106970.5786060.289303
1130.8264380.3471240.173562
1140.8332560.3334880.166744
1150.9051070.1897860.0948928
1160.9371060.1257890.0628944
1170.9557230.08855460.0442773
1180.9548060.09038750.0451938
1190.9630770.07384580.0369229
1200.9811780.03764490.0188225
1210.982780.03443990.0172199
1220.9842710.0314580.015729
1230.9910490.0179010.0089505
1240.9937090.01258230.00629117
1250.9939790.01204270.00602135
1260.9932530.01349360.00674678
1270.9946140.01077150.00538577
1280.9940860.01182720.00591358
1290.9977330.004534910.00226746
1300.9974910.005017410.00250871
1310.997160.005679150.00283957
1320.9971270.005745670.00287284
1330.9967960.006408280.00320414
1340.9966960.006607280.00330364
1350.995930.008139640.00406982
1360.99510.009800110.00490006
1370.9963060.007388880.00369444
1380.9959090.008182480.00409124
1390.9971490.005701090.00285055
1400.9974110.005178280.00258914
1410.9968020.006396890.00319845
1420.9971420.005716480.00285824
1430.997410.005179490.00258974
1440.9980070.003986880.00199344
1450.9979720.004055240.00202762
1460.9982970.003405310.00170266
1470.9978760.004248950.00212448
1480.9976130.004774660.00238733
1490.9975370.004925530.00246276
1500.9976020.00479550.00239775
1510.9991120.001775250.000887624
1520.9990850.001830710.000915354
1530.999130.001740840.000870419
1540.9990670.001865290.000932647
1550.9990490.001901450.000950726
1560.9989160.002167980.00108399
1570.9989590.00208280.0010414
1580.9988240.002352720.00117636
1590.9985340.00293160.0014658
1600.9981540.003692290.00184615
1610.998630.00274020.0013701
1620.9986150.002769260.00138463
1630.9983890.003221360.00161068
1640.9997180.0005644170.000282208
1650.9997690.0004620850.000231043
1660.9996780.0006446470.000322323
1670.9997860.0004279970.000213999
1680.9997260.0005484470.000274224
1690.9996590.0006820520.000341026
1700.9995630.0008730750.000436537
1710.9995410.0009174660.000458733
1720.999740.000520210.000260105
1730.9996780.0006443030.000322151
1740.9996170.0007669160.000383458
1750.999550.0009003960.000450198
1760.9997090.0005827890.000291394
1770.9996180.0007647270.000382363
1780.9997610.0004789130.000239456
1790.9996990.0006020110.000301005
1800.9997240.0005524230.000276212
1810.9996230.0007535190.000376759
1820.9994890.001022620.000511311
1830.9994750.001049940.00052497
1840.9994110.001178240.000589118
1850.9994480.001103420.000551712
1860.9993270.001345610.000672805
1870.9993650.001269820.00063491
1880.9992370.001525050.000762524
1890.9992860.001427480.000713739
1900.9991420.001715520.00085776
1910.9989010.002198310.00109916
1920.998710.002579690.00128985
1930.9987010.002597070.00129854
1940.9992470.001506310.000753154
1950.9990480.001904560.000952279
1960.9988680.002264440.00113222
1970.9985690.002862930.00143146
1980.9983540.003292960.00164648
1990.9983530.003294970.00164748
2000.9982970.003406520.00170326
2010.9980910.003818780.00190939
2020.9978840.004231020.00211551
2030.9973980.005203150.00260157
2040.9966410.00671780.0033589
2050.9962680.007463070.00373154
2060.9958860.008228570.00411428
2070.9944410.01111720.00555861
2080.9932640.0134710.00673551
2090.9964470.007106530.00355326
2100.9969590.006082280.00304114
2110.995910.008179940.00408997
2120.9947930.01041320.00520658
2130.9934790.01304240.0065212
2140.9923040.01539210.00769607
2150.9902860.01942710.00971353
2160.9875170.02496650.0124833
2170.9878870.02422550.0121127
2180.9851530.02969360.0148468
2190.9803950.03921080.0196054
2200.9749930.05001490.0250075
2210.975170.04966060.0248303
2220.9710620.05787530.0289377
2230.9666350.06673010.0333651
2240.959850.08029930.0401496
2250.9528130.09437330.0471867
2260.9629710.07405820.0370291
2270.9581020.08379510.0418975
2280.9536410.09271820.0463591
2290.9603690.07926110.0396306
2300.9603250.079350.039675
2310.9574120.08517540.0425877
2320.9678370.06432690.0321635
2330.9577960.08440710.0422035
2340.9704420.05911520.0295576
2350.973190.05361970.0268099
2360.9957610.008477260.00423863
2370.9946420.01071520.00535759
2380.9927990.01440130.00720063
2390.9896090.02078290.0103914
2400.9854910.02901870.0145094
2410.9799080.04018350.0200918
2420.9735490.0529030.0264515
2430.9649210.07015820.0350791
2440.9597280.08054340.0402717
2450.9494440.1011110.0505556
2460.9344780.1310450.0655224
2470.9178310.1643390.0821693
2480.8921130.2157730.107887
2490.8940020.2119960.105998
2500.8640420.2719170.135958
2510.8482080.3035850.151792
2520.8115990.3768030.188401
2530.7654250.469150.234575
2540.7587940.4824120.241206
2550.8600830.2798340.139917
2560.8237170.3525670.176283
2570.8834920.2330170.116508
2580.9583090.08338280.0416914
2590.9453880.1092230.0546116
2600.9981590.003682850.00184143
2610.9961250.007750830.00387541
2620.996250.007500450.00375023
2630.9992450.001509510.000754753
2640.9981370.003725980.00186299
2650.9974470.005105530.00255277
2660.9960630.007873720.00393686
2670.99290.01419990.00709997
2680.9814280.03714460.0185723
2690.9592150.0815690.0407845
2700.9033190.1933610.0966807
2710.9619980.07600320.0380016
2720.9683810.06323850.0316193

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.108905 & 0.21781 & 0.891095 \tabularnewline
8 & 0.0419861 & 0.0839722 & 0.958014 \tabularnewline
9 & 0.0652208 & 0.130442 & 0.934779 \tabularnewline
10 & 0.38397 & 0.76794 & 0.61603 \tabularnewline
11 & 0.352526 & 0.705052 & 0.647474 \tabularnewline
12 & 0.368871 & 0.737742 & 0.631129 \tabularnewline
13 & 0.300581 & 0.601162 & 0.699419 \tabularnewline
14 & 0.220681 & 0.441362 & 0.779319 \tabularnewline
15 & 0.175845 & 0.35169 & 0.824155 \tabularnewline
16 & 0.149286 & 0.298571 & 0.850714 \tabularnewline
17 & 0.106035 & 0.212071 & 0.893965 \tabularnewline
18 & 0.0741467 & 0.148293 & 0.925853 \tabularnewline
19 & 0.0509452 & 0.10189 & 0.949055 \tabularnewline
20 & 0.038893 & 0.0777859 & 0.961107 \tabularnewline
21 & 0.117549 & 0.235099 & 0.882451 \tabularnewline
22 & 0.111919 & 0.223837 & 0.888081 \tabularnewline
23 & 0.0966418 & 0.193284 & 0.903358 \tabularnewline
24 & 0.083798 & 0.167596 & 0.916202 \tabularnewline
25 & 0.0625442 & 0.125088 & 0.937456 \tabularnewline
26 & 0.048611 & 0.0972219 & 0.951389 \tabularnewline
27 & 0.087174 & 0.174348 & 0.912826 \tabularnewline
28 & 0.0764209 & 0.152842 & 0.923579 \tabularnewline
29 & 0.105191 & 0.210382 & 0.894809 \tabularnewline
30 & 0.0823199 & 0.16464 & 0.91768 \tabularnewline
31 & 0.0683046 & 0.136609 & 0.931695 \tabularnewline
32 & 0.0579057 & 0.115811 & 0.942094 \tabularnewline
33 & 0.0633818 & 0.126764 & 0.936618 \tabularnewline
34 & 0.0583233 & 0.116647 & 0.941677 \tabularnewline
35 & 0.046018 & 0.0920359 & 0.953982 \tabularnewline
36 & 0.0367555 & 0.0735111 & 0.963244 \tabularnewline
37 & 0.0282567 & 0.0565135 & 0.971743 \tabularnewline
38 & 0.0293555 & 0.058711 & 0.970644 \tabularnewline
39 & 0.0310843 & 0.0621686 & 0.968916 \tabularnewline
40 & 0.0237747 & 0.0475495 & 0.976225 \tabularnewline
41 & 0.0552765 & 0.110553 & 0.944724 \tabularnewline
42 & 0.0441148 & 0.0882295 & 0.955885 \tabularnewline
43 & 0.0375941 & 0.0751883 & 0.962406 \tabularnewline
44 & 0.0335846 & 0.0671693 & 0.966415 \tabularnewline
45 & 0.0328494 & 0.0656987 & 0.967151 \tabularnewline
46 & 0.0282521 & 0.0565043 & 0.971748 \tabularnewline
47 & 0.025115 & 0.0502299 & 0.974885 \tabularnewline
48 & 0.0231086 & 0.0462172 & 0.976891 \tabularnewline
49 & 0.0253874 & 0.0507747 & 0.974613 \tabularnewline
50 & 0.0212342 & 0.0424684 & 0.978766 \tabularnewline
51 & 0.0165702 & 0.0331405 & 0.98343 \tabularnewline
52 & 0.0166182 & 0.0332365 & 0.983382 \tabularnewline
53 & 0.0135743 & 0.0271486 & 0.986426 \tabularnewline
54 & 0.0112733 & 0.0225465 & 0.988727 \tabularnewline
55 & 0.0116642 & 0.0233283 & 0.988336 \tabularnewline
56 & 0.00958235 & 0.0191647 & 0.990418 \tabularnewline
57 & 0.0320501 & 0.0641002 & 0.96795 \tabularnewline
58 & 0.0390815 & 0.078163 & 0.960918 \tabularnewline
59 & 0.0332816 & 0.0665632 & 0.966718 \tabularnewline
60 & 0.0339923 & 0.0679846 & 0.966008 \tabularnewline
61 & 0.0389471 & 0.0778942 & 0.961053 \tabularnewline
62 & 0.0333423 & 0.0666846 & 0.966658 \tabularnewline
63 & 0.0412811 & 0.0825622 & 0.958719 \tabularnewline
64 & 0.0530034 & 0.106007 & 0.946997 \tabularnewline
65 & 0.0637738 & 0.127548 & 0.936226 \tabularnewline
66 & 0.0556583 & 0.111317 & 0.944342 \tabularnewline
67 & 0.0561713 & 0.112343 & 0.943829 \tabularnewline
68 & 0.0573645 & 0.114729 & 0.942635 \tabularnewline
69 & 0.0624367 & 0.124873 & 0.937563 \tabularnewline
70 & 0.0559593 & 0.111919 & 0.944041 \tabularnewline
71 & 0.0521767 & 0.104353 & 0.947823 \tabularnewline
72 & 0.0463628 & 0.0927256 & 0.953637 \tabularnewline
73 & 0.0404959 & 0.0809917 & 0.959504 \tabularnewline
74 & 0.0539179 & 0.107836 & 0.946082 \tabularnewline
75 & 0.048288 & 0.0965761 & 0.951712 \tabularnewline
76 & 0.0443544 & 0.0887087 & 0.955646 \tabularnewline
77 & 0.040686 & 0.0813721 & 0.959314 \tabularnewline
78 & 0.0376891 & 0.0753783 & 0.962311 \tabularnewline
79 & 0.030477 & 0.060954 & 0.969523 \tabularnewline
80 & 0.0367803 & 0.0735606 & 0.96322 \tabularnewline
81 & 0.030804 & 0.061608 & 0.969196 \tabularnewline
82 & 0.0310802 & 0.0621603 & 0.96892 \tabularnewline
83 & 0.0260708 & 0.0521417 & 0.973929 \tabularnewline
84 & 0.0871063 & 0.174213 & 0.912894 \tabularnewline
85 & 0.0854253 & 0.170851 & 0.914575 \tabularnewline
86 & 0.076274 & 0.152548 & 0.923726 \tabularnewline
87 & 0.0661684 & 0.132337 & 0.933832 \tabularnewline
88 & 0.0584145 & 0.116829 & 0.941585 \tabularnewline
89 & 0.0611641 & 0.122328 & 0.938836 \tabularnewline
90 & 0.05794 & 0.11588 & 0.94206 \tabularnewline
91 & 0.0558673 & 0.111735 & 0.944133 \tabularnewline
92 & 0.12864 & 0.25728 & 0.87136 \tabularnewline
93 & 0.132519 & 0.265038 & 0.867481 \tabularnewline
94 & 0.134335 & 0.26867 & 0.865665 \tabularnewline
95 & 0.152106 & 0.304213 & 0.847894 \tabularnewline
96 & 0.161701 & 0.323402 & 0.838299 \tabularnewline
97 & 0.243291 & 0.486582 & 0.756709 \tabularnewline
98 & 0.22818 & 0.45636 & 0.77182 \tabularnewline
99 & 0.235156 & 0.470313 & 0.764844 \tabularnewline
100 & 0.301182 & 0.602363 & 0.698818 \tabularnewline
101 & 0.276978 & 0.553956 & 0.723022 \tabularnewline
102 & 0.280061 & 0.560122 & 0.719939 \tabularnewline
103 & 0.28244 & 0.56488 & 0.71756 \tabularnewline
104 & 0.302231 & 0.604462 & 0.697769 \tabularnewline
105 & 0.339534 & 0.679069 & 0.660466 \tabularnewline
106 & 0.357857 & 0.715713 & 0.642143 \tabularnewline
107 & 0.367199 & 0.734398 & 0.632801 \tabularnewline
108 & 0.650362 & 0.699276 & 0.349638 \tabularnewline
109 & 0.714845 & 0.570309 & 0.285155 \tabularnewline
110 & 0.710862 & 0.578276 & 0.289138 \tabularnewline
111 & 0.714972 & 0.570055 & 0.285028 \tabularnewline
112 & 0.710697 & 0.578606 & 0.289303 \tabularnewline
113 & 0.826438 & 0.347124 & 0.173562 \tabularnewline
114 & 0.833256 & 0.333488 & 0.166744 \tabularnewline
115 & 0.905107 & 0.189786 & 0.0948928 \tabularnewline
116 & 0.937106 & 0.125789 & 0.0628944 \tabularnewline
117 & 0.955723 & 0.0885546 & 0.0442773 \tabularnewline
118 & 0.954806 & 0.0903875 & 0.0451938 \tabularnewline
119 & 0.963077 & 0.0738458 & 0.0369229 \tabularnewline
120 & 0.981178 & 0.0376449 & 0.0188225 \tabularnewline
121 & 0.98278 & 0.0344399 & 0.0172199 \tabularnewline
122 & 0.984271 & 0.031458 & 0.015729 \tabularnewline
123 & 0.991049 & 0.017901 & 0.0089505 \tabularnewline
124 & 0.993709 & 0.0125823 & 0.00629117 \tabularnewline
125 & 0.993979 & 0.0120427 & 0.00602135 \tabularnewline
126 & 0.993253 & 0.0134936 & 0.00674678 \tabularnewline
127 & 0.994614 & 0.0107715 & 0.00538577 \tabularnewline
128 & 0.994086 & 0.0118272 & 0.00591358 \tabularnewline
129 & 0.997733 & 0.00453491 & 0.00226746 \tabularnewline
130 & 0.997491 & 0.00501741 & 0.00250871 \tabularnewline
131 & 0.99716 & 0.00567915 & 0.00283957 \tabularnewline
132 & 0.997127 & 0.00574567 & 0.00287284 \tabularnewline
133 & 0.996796 & 0.00640828 & 0.00320414 \tabularnewline
134 & 0.996696 & 0.00660728 & 0.00330364 \tabularnewline
135 & 0.99593 & 0.00813964 & 0.00406982 \tabularnewline
136 & 0.9951 & 0.00980011 & 0.00490006 \tabularnewline
137 & 0.996306 & 0.00738888 & 0.00369444 \tabularnewline
138 & 0.995909 & 0.00818248 & 0.00409124 \tabularnewline
139 & 0.997149 & 0.00570109 & 0.00285055 \tabularnewline
140 & 0.997411 & 0.00517828 & 0.00258914 \tabularnewline
141 & 0.996802 & 0.00639689 & 0.00319845 \tabularnewline
142 & 0.997142 & 0.00571648 & 0.00285824 \tabularnewline
143 & 0.99741 & 0.00517949 & 0.00258974 \tabularnewline
144 & 0.998007 & 0.00398688 & 0.00199344 \tabularnewline
145 & 0.997972 & 0.00405524 & 0.00202762 \tabularnewline
146 & 0.998297 & 0.00340531 & 0.00170266 \tabularnewline
147 & 0.997876 & 0.00424895 & 0.00212448 \tabularnewline
148 & 0.997613 & 0.00477466 & 0.00238733 \tabularnewline
149 & 0.997537 & 0.00492553 & 0.00246276 \tabularnewline
150 & 0.997602 & 0.0047955 & 0.00239775 \tabularnewline
151 & 0.999112 & 0.00177525 & 0.000887624 \tabularnewline
152 & 0.999085 & 0.00183071 & 0.000915354 \tabularnewline
153 & 0.99913 & 0.00174084 & 0.000870419 \tabularnewline
154 & 0.999067 & 0.00186529 & 0.000932647 \tabularnewline
155 & 0.999049 & 0.00190145 & 0.000950726 \tabularnewline
156 & 0.998916 & 0.00216798 & 0.00108399 \tabularnewline
157 & 0.998959 & 0.0020828 & 0.0010414 \tabularnewline
158 & 0.998824 & 0.00235272 & 0.00117636 \tabularnewline
159 & 0.998534 & 0.0029316 & 0.0014658 \tabularnewline
160 & 0.998154 & 0.00369229 & 0.00184615 \tabularnewline
161 & 0.99863 & 0.0027402 & 0.0013701 \tabularnewline
162 & 0.998615 & 0.00276926 & 0.00138463 \tabularnewline
163 & 0.998389 & 0.00322136 & 0.00161068 \tabularnewline
164 & 0.999718 & 0.000564417 & 0.000282208 \tabularnewline
165 & 0.999769 & 0.000462085 & 0.000231043 \tabularnewline
166 & 0.999678 & 0.000644647 & 0.000322323 \tabularnewline
167 & 0.999786 & 0.000427997 & 0.000213999 \tabularnewline
168 & 0.999726 & 0.000548447 & 0.000274224 \tabularnewline
169 & 0.999659 & 0.000682052 & 0.000341026 \tabularnewline
170 & 0.999563 & 0.000873075 & 0.000436537 \tabularnewline
171 & 0.999541 & 0.000917466 & 0.000458733 \tabularnewline
172 & 0.99974 & 0.00052021 & 0.000260105 \tabularnewline
173 & 0.999678 & 0.000644303 & 0.000322151 \tabularnewline
174 & 0.999617 & 0.000766916 & 0.000383458 \tabularnewline
175 & 0.99955 & 0.000900396 & 0.000450198 \tabularnewline
176 & 0.999709 & 0.000582789 & 0.000291394 \tabularnewline
177 & 0.999618 & 0.000764727 & 0.000382363 \tabularnewline
178 & 0.999761 & 0.000478913 & 0.000239456 \tabularnewline
179 & 0.999699 & 0.000602011 & 0.000301005 \tabularnewline
180 & 0.999724 & 0.000552423 & 0.000276212 \tabularnewline
181 & 0.999623 & 0.000753519 & 0.000376759 \tabularnewline
182 & 0.999489 & 0.00102262 & 0.000511311 \tabularnewline
183 & 0.999475 & 0.00104994 & 0.00052497 \tabularnewline
184 & 0.999411 & 0.00117824 & 0.000589118 \tabularnewline
185 & 0.999448 & 0.00110342 & 0.000551712 \tabularnewline
186 & 0.999327 & 0.00134561 & 0.000672805 \tabularnewline
187 & 0.999365 & 0.00126982 & 0.00063491 \tabularnewline
188 & 0.999237 & 0.00152505 & 0.000762524 \tabularnewline
189 & 0.999286 & 0.00142748 & 0.000713739 \tabularnewline
190 & 0.999142 & 0.00171552 & 0.00085776 \tabularnewline
191 & 0.998901 & 0.00219831 & 0.00109916 \tabularnewline
192 & 0.99871 & 0.00257969 & 0.00128985 \tabularnewline
193 & 0.998701 & 0.00259707 & 0.00129854 \tabularnewline
194 & 0.999247 & 0.00150631 & 0.000753154 \tabularnewline
195 & 0.999048 & 0.00190456 & 0.000952279 \tabularnewline
196 & 0.998868 & 0.00226444 & 0.00113222 \tabularnewline
197 & 0.998569 & 0.00286293 & 0.00143146 \tabularnewline
198 & 0.998354 & 0.00329296 & 0.00164648 \tabularnewline
199 & 0.998353 & 0.00329497 & 0.00164748 \tabularnewline
200 & 0.998297 & 0.00340652 & 0.00170326 \tabularnewline
201 & 0.998091 & 0.00381878 & 0.00190939 \tabularnewline
202 & 0.997884 & 0.00423102 & 0.00211551 \tabularnewline
203 & 0.997398 & 0.00520315 & 0.00260157 \tabularnewline
204 & 0.996641 & 0.0067178 & 0.0033589 \tabularnewline
205 & 0.996268 & 0.00746307 & 0.00373154 \tabularnewline
206 & 0.995886 & 0.00822857 & 0.00411428 \tabularnewline
207 & 0.994441 & 0.0111172 & 0.00555861 \tabularnewline
208 & 0.993264 & 0.013471 & 0.00673551 \tabularnewline
209 & 0.996447 & 0.00710653 & 0.00355326 \tabularnewline
210 & 0.996959 & 0.00608228 & 0.00304114 \tabularnewline
211 & 0.99591 & 0.00817994 & 0.00408997 \tabularnewline
212 & 0.994793 & 0.0104132 & 0.00520658 \tabularnewline
213 & 0.993479 & 0.0130424 & 0.0065212 \tabularnewline
214 & 0.992304 & 0.0153921 & 0.00769607 \tabularnewline
215 & 0.990286 & 0.0194271 & 0.00971353 \tabularnewline
216 & 0.987517 & 0.0249665 & 0.0124833 \tabularnewline
217 & 0.987887 & 0.0242255 & 0.0121127 \tabularnewline
218 & 0.985153 & 0.0296936 & 0.0148468 \tabularnewline
219 & 0.980395 & 0.0392108 & 0.0196054 \tabularnewline
220 & 0.974993 & 0.0500149 & 0.0250075 \tabularnewline
221 & 0.97517 & 0.0496606 & 0.0248303 \tabularnewline
222 & 0.971062 & 0.0578753 & 0.0289377 \tabularnewline
223 & 0.966635 & 0.0667301 & 0.0333651 \tabularnewline
224 & 0.95985 & 0.0802993 & 0.0401496 \tabularnewline
225 & 0.952813 & 0.0943733 & 0.0471867 \tabularnewline
226 & 0.962971 & 0.0740582 & 0.0370291 \tabularnewline
227 & 0.958102 & 0.0837951 & 0.0418975 \tabularnewline
228 & 0.953641 & 0.0927182 & 0.0463591 \tabularnewline
229 & 0.960369 & 0.0792611 & 0.0396306 \tabularnewline
230 & 0.960325 & 0.07935 & 0.039675 \tabularnewline
231 & 0.957412 & 0.0851754 & 0.0425877 \tabularnewline
232 & 0.967837 & 0.0643269 & 0.0321635 \tabularnewline
233 & 0.957796 & 0.0844071 & 0.0422035 \tabularnewline
234 & 0.970442 & 0.0591152 & 0.0295576 \tabularnewline
235 & 0.97319 & 0.0536197 & 0.0268099 \tabularnewline
236 & 0.995761 & 0.00847726 & 0.00423863 \tabularnewline
237 & 0.994642 & 0.0107152 & 0.00535759 \tabularnewline
238 & 0.992799 & 0.0144013 & 0.00720063 \tabularnewline
239 & 0.989609 & 0.0207829 & 0.0103914 \tabularnewline
240 & 0.985491 & 0.0290187 & 0.0145094 \tabularnewline
241 & 0.979908 & 0.0401835 & 0.0200918 \tabularnewline
242 & 0.973549 & 0.052903 & 0.0264515 \tabularnewline
243 & 0.964921 & 0.0701582 & 0.0350791 \tabularnewline
244 & 0.959728 & 0.0805434 & 0.0402717 \tabularnewline
245 & 0.949444 & 0.101111 & 0.0505556 \tabularnewline
246 & 0.934478 & 0.131045 & 0.0655224 \tabularnewline
247 & 0.917831 & 0.164339 & 0.0821693 \tabularnewline
248 & 0.892113 & 0.215773 & 0.107887 \tabularnewline
249 & 0.894002 & 0.211996 & 0.105998 \tabularnewline
250 & 0.864042 & 0.271917 & 0.135958 \tabularnewline
251 & 0.848208 & 0.303585 & 0.151792 \tabularnewline
252 & 0.811599 & 0.376803 & 0.188401 \tabularnewline
253 & 0.765425 & 0.46915 & 0.234575 \tabularnewline
254 & 0.758794 & 0.482412 & 0.241206 \tabularnewline
255 & 0.860083 & 0.279834 & 0.139917 \tabularnewline
256 & 0.823717 & 0.352567 & 0.176283 \tabularnewline
257 & 0.883492 & 0.233017 & 0.116508 \tabularnewline
258 & 0.958309 & 0.0833828 & 0.0416914 \tabularnewline
259 & 0.945388 & 0.109223 & 0.0546116 \tabularnewline
260 & 0.998159 & 0.00368285 & 0.00184143 \tabularnewline
261 & 0.996125 & 0.00775083 & 0.00387541 \tabularnewline
262 & 0.99625 & 0.00750045 & 0.00375023 \tabularnewline
263 & 0.999245 & 0.00150951 & 0.000754753 \tabularnewline
264 & 0.998137 & 0.00372598 & 0.00186299 \tabularnewline
265 & 0.997447 & 0.00510553 & 0.00255277 \tabularnewline
266 & 0.996063 & 0.00787372 & 0.00393686 \tabularnewline
267 & 0.9929 & 0.0141999 & 0.00709997 \tabularnewline
268 & 0.981428 & 0.0371446 & 0.0185723 \tabularnewline
269 & 0.959215 & 0.081569 & 0.0407845 \tabularnewline
270 & 0.903319 & 0.193361 & 0.0966807 \tabularnewline
271 & 0.961998 & 0.0760032 & 0.0380016 \tabularnewline
272 & 0.968381 & 0.0632385 & 0.0316193 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269393&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]7[/C][C]0.108905[/C][C]0.21781[/C][C]0.891095[/C][/ROW]
[ROW][C]8[/C][C]0.0419861[/C][C]0.0839722[/C][C]0.958014[/C][/ROW]
[ROW][C]9[/C][C]0.0652208[/C][C]0.130442[/C][C]0.934779[/C][/ROW]
[ROW][C]10[/C][C]0.38397[/C][C]0.76794[/C][C]0.61603[/C][/ROW]
[ROW][C]11[/C][C]0.352526[/C][C]0.705052[/C][C]0.647474[/C][/ROW]
[ROW][C]12[/C][C]0.368871[/C][C]0.737742[/C][C]0.631129[/C][/ROW]
[ROW][C]13[/C][C]0.300581[/C][C]0.601162[/C][C]0.699419[/C][/ROW]
[ROW][C]14[/C][C]0.220681[/C][C]0.441362[/C][C]0.779319[/C][/ROW]
[ROW][C]15[/C][C]0.175845[/C][C]0.35169[/C][C]0.824155[/C][/ROW]
[ROW][C]16[/C][C]0.149286[/C][C]0.298571[/C][C]0.850714[/C][/ROW]
[ROW][C]17[/C][C]0.106035[/C][C]0.212071[/C][C]0.893965[/C][/ROW]
[ROW][C]18[/C][C]0.0741467[/C][C]0.148293[/C][C]0.925853[/C][/ROW]
[ROW][C]19[/C][C]0.0509452[/C][C]0.10189[/C][C]0.949055[/C][/ROW]
[ROW][C]20[/C][C]0.038893[/C][C]0.0777859[/C][C]0.961107[/C][/ROW]
[ROW][C]21[/C][C]0.117549[/C][C]0.235099[/C][C]0.882451[/C][/ROW]
[ROW][C]22[/C][C]0.111919[/C][C]0.223837[/C][C]0.888081[/C][/ROW]
[ROW][C]23[/C][C]0.0966418[/C][C]0.193284[/C][C]0.903358[/C][/ROW]
[ROW][C]24[/C][C]0.083798[/C][C]0.167596[/C][C]0.916202[/C][/ROW]
[ROW][C]25[/C][C]0.0625442[/C][C]0.125088[/C][C]0.937456[/C][/ROW]
[ROW][C]26[/C][C]0.048611[/C][C]0.0972219[/C][C]0.951389[/C][/ROW]
[ROW][C]27[/C][C]0.087174[/C][C]0.174348[/C][C]0.912826[/C][/ROW]
[ROW][C]28[/C][C]0.0764209[/C][C]0.152842[/C][C]0.923579[/C][/ROW]
[ROW][C]29[/C][C]0.105191[/C][C]0.210382[/C][C]0.894809[/C][/ROW]
[ROW][C]30[/C][C]0.0823199[/C][C]0.16464[/C][C]0.91768[/C][/ROW]
[ROW][C]31[/C][C]0.0683046[/C][C]0.136609[/C][C]0.931695[/C][/ROW]
[ROW][C]32[/C][C]0.0579057[/C][C]0.115811[/C][C]0.942094[/C][/ROW]
[ROW][C]33[/C][C]0.0633818[/C][C]0.126764[/C][C]0.936618[/C][/ROW]
[ROW][C]34[/C][C]0.0583233[/C][C]0.116647[/C][C]0.941677[/C][/ROW]
[ROW][C]35[/C][C]0.046018[/C][C]0.0920359[/C][C]0.953982[/C][/ROW]
[ROW][C]36[/C][C]0.0367555[/C][C]0.0735111[/C][C]0.963244[/C][/ROW]
[ROW][C]37[/C][C]0.0282567[/C][C]0.0565135[/C][C]0.971743[/C][/ROW]
[ROW][C]38[/C][C]0.0293555[/C][C]0.058711[/C][C]0.970644[/C][/ROW]
[ROW][C]39[/C][C]0.0310843[/C][C]0.0621686[/C][C]0.968916[/C][/ROW]
[ROW][C]40[/C][C]0.0237747[/C][C]0.0475495[/C][C]0.976225[/C][/ROW]
[ROW][C]41[/C][C]0.0552765[/C][C]0.110553[/C][C]0.944724[/C][/ROW]
[ROW][C]42[/C][C]0.0441148[/C][C]0.0882295[/C][C]0.955885[/C][/ROW]
[ROW][C]43[/C][C]0.0375941[/C][C]0.0751883[/C][C]0.962406[/C][/ROW]
[ROW][C]44[/C][C]0.0335846[/C][C]0.0671693[/C][C]0.966415[/C][/ROW]
[ROW][C]45[/C][C]0.0328494[/C][C]0.0656987[/C][C]0.967151[/C][/ROW]
[ROW][C]46[/C][C]0.0282521[/C][C]0.0565043[/C][C]0.971748[/C][/ROW]
[ROW][C]47[/C][C]0.025115[/C][C]0.0502299[/C][C]0.974885[/C][/ROW]
[ROW][C]48[/C][C]0.0231086[/C][C]0.0462172[/C][C]0.976891[/C][/ROW]
[ROW][C]49[/C][C]0.0253874[/C][C]0.0507747[/C][C]0.974613[/C][/ROW]
[ROW][C]50[/C][C]0.0212342[/C][C]0.0424684[/C][C]0.978766[/C][/ROW]
[ROW][C]51[/C][C]0.0165702[/C][C]0.0331405[/C][C]0.98343[/C][/ROW]
[ROW][C]52[/C][C]0.0166182[/C][C]0.0332365[/C][C]0.983382[/C][/ROW]
[ROW][C]53[/C][C]0.0135743[/C][C]0.0271486[/C][C]0.986426[/C][/ROW]
[ROW][C]54[/C][C]0.0112733[/C][C]0.0225465[/C][C]0.988727[/C][/ROW]
[ROW][C]55[/C][C]0.0116642[/C][C]0.0233283[/C][C]0.988336[/C][/ROW]
[ROW][C]56[/C][C]0.00958235[/C][C]0.0191647[/C][C]0.990418[/C][/ROW]
[ROW][C]57[/C][C]0.0320501[/C][C]0.0641002[/C][C]0.96795[/C][/ROW]
[ROW][C]58[/C][C]0.0390815[/C][C]0.078163[/C][C]0.960918[/C][/ROW]
[ROW][C]59[/C][C]0.0332816[/C][C]0.0665632[/C][C]0.966718[/C][/ROW]
[ROW][C]60[/C][C]0.0339923[/C][C]0.0679846[/C][C]0.966008[/C][/ROW]
[ROW][C]61[/C][C]0.0389471[/C][C]0.0778942[/C][C]0.961053[/C][/ROW]
[ROW][C]62[/C][C]0.0333423[/C][C]0.0666846[/C][C]0.966658[/C][/ROW]
[ROW][C]63[/C][C]0.0412811[/C][C]0.0825622[/C][C]0.958719[/C][/ROW]
[ROW][C]64[/C][C]0.0530034[/C][C]0.106007[/C][C]0.946997[/C][/ROW]
[ROW][C]65[/C][C]0.0637738[/C][C]0.127548[/C][C]0.936226[/C][/ROW]
[ROW][C]66[/C][C]0.0556583[/C][C]0.111317[/C][C]0.944342[/C][/ROW]
[ROW][C]67[/C][C]0.0561713[/C][C]0.112343[/C][C]0.943829[/C][/ROW]
[ROW][C]68[/C][C]0.0573645[/C][C]0.114729[/C][C]0.942635[/C][/ROW]
[ROW][C]69[/C][C]0.0624367[/C][C]0.124873[/C][C]0.937563[/C][/ROW]
[ROW][C]70[/C][C]0.0559593[/C][C]0.111919[/C][C]0.944041[/C][/ROW]
[ROW][C]71[/C][C]0.0521767[/C][C]0.104353[/C][C]0.947823[/C][/ROW]
[ROW][C]72[/C][C]0.0463628[/C][C]0.0927256[/C][C]0.953637[/C][/ROW]
[ROW][C]73[/C][C]0.0404959[/C][C]0.0809917[/C][C]0.959504[/C][/ROW]
[ROW][C]74[/C][C]0.0539179[/C][C]0.107836[/C][C]0.946082[/C][/ROW]
[ROW][C]75[/C][C]0.048288[/C][C]0.0965761[/C][C]0.951712[/C][/ROW]
[ROW][C]76[/C][C]0.0443544[/C][C]0.0887087[/C][C]0.955646[/C][/ROW]
[ROW][C]77[/C][C]0.040686[/C][C]0.0813721[/C][C]0.959314[/C][/ROW]
[ROW][C]78[/C][C]0.0376891[/C][C]0.0753783[/C][C]0.962311[/C][/ROW]
[ROW][C]79[/C][C]0.030477[/C][C]0.060954[/C][C]0.969523[/C][/ROW]
[ROW][C]80[/C][C]0.0367803[/C][C]0.0735606[/C][C]0.96322[/C][/ROW]
[ROW][C]81[/C][C]0.030804[/C][C]0.061608[/C][C]0.969196[/C][/ROW]
[ROW][C]82[/C][C]0.0310802[/C][C]0.0621603[/C][C]0.96892[/C][/ROW]
[ROW][C]83[/C][C]0.0260708[/C][C]0.0521417[/C][C]0.973929[/C][/ROW]
[ROW][C]84[/C][C]0.0871063[/C][C]0.174213[/C][C]0.912894[/C][/ROW]
[ROW][C]85[/C][C]0.0854253[/C][C]0.170851[/C][C]0.914575[/C][/ROW]
[ROW][C]86[/C][C]0.076274[/C][C]0.152548[/C][C]0.923726[/C][/ROW]
[ROW][C]87[/C][C]0.0661684[/C][C]0.132337[/C][C]0.933832[/C][/ROW]
[ROW][C]88[/C][C]0.0584145[/C][C]0.116829[/C][C]0.941585[/C][/ROW]
[ROW][C]89[/C][C]0.0611641[/C][C]0.122328[/C][C]0.938836[/C][/ROW]
[ROW][C]90[/C][C]0.05794[/C][C]0.11588[/C][C]0.94206[/C][/ROW]
[ROW][C]91[/C][C]0.0558673[/C][C]0.111735[/C][C]0.944133[/C][/ROW]
[ROW][C]92[/C][C]0.12864[/C][C]0.25728[/C][C]0.87136[/C][/ROW]
[ROW][C]93[/C][C]0.132519[/C][C]0.265038[/C][C]0.867481[/C][/ROW]
[ROW][C]94[/C][C]0.134335[/C][C]0.26867[/C][C]0.865665[/C][/ROW]
[ROW][C]95[/C][C]0.152106[/C][C]0.304213[/C][C]0.847894[/C][/ROW]
[ROW][C]96[/C][C]0.161701[/C][C]0.323402[/C][C]0.838299[/C][/ROW]
[ROW][C]97[/C][C]0.243291[/C][C]0.486582[/C][C]0.756709[/C][/ROW]
[ROW][C]98[/C][C]0.22818[/C][C]0.45636[/C][C]0.77182[/C][/ROW]
[ROW][C]99[/C][C]0.235156[/C][C]0.470313[/C][C]0.764844[/C][/ROW]
[ROW][C]100[/C][C]0.301182[/C][C]0.602363[/C][C]0.698818[/C][/ROW]
[ROW][C]101[/C][C]0.276978[/C][C]0.553956[/C][C]0.723022[/C][/ROW]
[ROW][C]102[/C][C]0.280061[/C][C]0.560122[/C][C]0.719939[/C][/ROW]
[ROW][C]103[/C][C]0.28244[/C][C]0.56488[/C][C]0.71756[/C][/ROW]
[ROW][C]104[/C][C]0.302231[/C][C]0.604462[/C][C]0.697769[/C][/ROW]
[ROW][C]105[/C][C]0.339534[/C][C]0.679069[/C][C]0.660466[/C][/ROW]
[ROW][C]106[/C][C]0.357857[/C][C]0.715713[/C][C]0.642143[/C][/ROW]
[ROW][C]107[/C][C]0.367199[/C][C]0.734398[/C][C]0.632801[/C][/ROW]
[ROW][C]108[/C][C]0.650362[/C][C]0.699276[/C][C]0.349638[/C][/ROW]
[ROW][C]109[/C][C]0.714845[/C][C]0.570309[/C][C]0.285155[/C][/ROW]
[ROW][C]110[/C][C]0.710862[/C][C]0.578276[/C][C]0.289138[/C][/ROW]
[ROW][C]111[/C][C]0.714972[/C][C]0.570055[/C][C]0.285028[/C][/ROW]
[ROW][C]112[/C][C]0.710697[/C][C]0.578606[/C][C]0.289303[/C][/ROW]
[ROW][C]113[/C][C]0.826438[/C][C]0.347124[/C][C]0.173562[/C][/ROW]
[ROW][C]114[/C][C]0.833256[/C][C]0.333488[/C][C]0.166744[/C][/ROW]
[ROW][C]115[/C][C]0.905107[/C][C]0.189786[/C][C]0.0948928[/C][/ROW]
[ROW][C]116[/C][C]0.937106[/C][C]0.125789[/C][C]0.0628944[/C][/ROW]
[ROW][C]117[/C][C]0.955723[/C][C]0.0885546[/C][C]0.0442773[/C][/ROW]
[ROW][C]118[/C][C]0.954806[/C][C]0.0903875[/C][C]0.0451938[/C][/ROW]
[ROW][C]119[/C][C]0.963077[/C][C]0.0738458[/C][C]0.0369229[/C][/ROW]
[ROW][C]120[/C][C]0.981178[/C][C]0.0376449[/C][C]0.0188225[/C][/ROW]
[ROW][C]121[/C][C]0.98278[/C][C]0.0344399[/C][C]0.0172199[/C][/ROW]
[ROW][C]122[/C][C]0.984271[/C][C]0.031458[/C][C]0.015729[/C][/ROW]
[ROW][C]123[/C][C]0.991049[/C][C]0.017901[/C][C]0.0089505[/C][/ROW]
[ROW][C]124[/C][C]0.993709[/C][C]0.0125823[/C][C]0.00629117[/C][/ROW]
[ROW][C]125[/C][C]0.993979[/C][C]0.0120427[/C][C]0.00602135[/C][/ROW]
[ROW][C]126[/C][C]0.993253[/C][C]0.0134936[/C][C]0.00674678[/C][/ROW]
[ROW][C]127[/C][C]0.994614[/C][C]0.0107715[/C][C]0.00538577[/C][/ROW]
[ROW][C]128[/C][C]0.994086[/C][C]0.0118272[/C][C]0.00591358[/C][/ROW]
[ROW][C]129[/C][C]0.997733[/C][C]0.00453491[/C][C]0.00226746[/C][/ROW]
[ROW][C]130[/C][C]0.997491[/C][C]0.00501741[/C][C]0.00250871[/C][/ROW]
[ROW][C]131[/C][C]0.99716[/C][C]0.00567915[/C][C]0.00283957[/C][/ROW]
[ROW][C]132[/C][C]0.997127[/C][C]0.00574567[/C][C]0.00287284[/C][/ROW]
[ROW][C]133[/C][C]0.996796[/C][C]0.00640828[/C][C]0.00320414[/C][/ROW]
[ROW][C]134[/C][C]0.996696[/C][C]0.00660728[/C][C]0.00330364[/C][/ROW]
[ROW][C]135[/C][C]0.99593[/C][C]0.00813964[/C][C]0.00406982[/C][/ROW]
[ROW][C]136[/C][C]0.9951[/C][C]0.00980011[/C][C]0.00490006[/C][/ROW]
[ROW][C]137[/C][C]0.996306[/C][C]0.00738888[/C][C]0.00369444[/C][/ROW]
[ROW][C]138[/C][C]0.995909[/C][C]0.00818248[/C][C]0.00409124[/C][/ROW]
[ROW][C]139[/C][C]0.997149[/C][C]0.00570109[/C][C]0.00285055[/C][/ROW]
[ROW][C]140[/C][C]0.997411[/C][C]0.00517828[/C][C]0.00258914[/C][/ROW]
[ROW][C]141[/C][C]0.996802[/C][C]0.00639689[/C][C]0.00319845[/C][/ROW]
[ROW][C]142[/C][C]0.997142[/C][C]0.00571648[/C][C]0.00285824[/C][/ROW]
[ROW][C]143[/C][C]0.99741[/C][C]0.00517949[/C][C]0.00258974[/C][/ROW]
[ROW][C]144[/C][C]0.998007[/C][C]0.00398688[/C][C]0.00199344[/C][/ROW]
[ROW][C]145[/C][C]0.997972[/C][C]0.00405524[/C][C]0.00202762[/C][/ROW]
[ROW][C]146[/C][C]0.998297[/C][C]0.00340531[/C][C]0.00170266[/C][/ROW]
[ROW][C]147[/C][C]0.997876[/C][C]0.00424895[/C][C]0.00212448[/C][/ROW]
[ROW][C]148[/C][C]0.997613[/C][C]0.00477466[/C][C]0.00238733[/C][/ROW]
[ROW][C]149[/C][C]0.997537[/C][C]0.00492553[/C][C]0.00246276[/C][/ROW]
[ROW][C]150[/C][C]0.997602[/C][C]0.0047955[/C][C]0.00239775[/C][/ROW]
[ROW][C]151[/C][C]0.999112[/C][C]0.00177525[/C][C]0.000887624[/C][/ROW]
[ROW][C]152[/C][C]0.999085[/C][C]0.00183071[/C][C]0.000915354[/C][/ROW]
[ROW][C]153[/C][C]0.99913[/C][C]0.00174084[/C][C]0.000870419[/C][/ROW]
[ROW][C]154[/C][C]0.999067[/C][C]0.00186529[/C][C]0.000932647[/C][/ROW]
[ROW][C]155[/C][C]0.999049[/C][C]0.00190145[/C][C]0.000950726[/C][/ROW]
[ROW][C]156[/C][C]0.998916[/C][C]0.00216798[/C][C]0.00108399[/C][/ROW]
[ROW][C]157[/C][C]0.998959[/C][C]0.0020828[/C][C]0.0010414[/C][/ROW]
[ROW][C]158[/C][C]0.998824[/C][C]0.00235272[/C][C]0.00117636[/C][/ROW]
[ROW][C]159[/C][C]0.998534[/C][C]0.0029316[/C][C]0.0014658[/C][/ROW]
[ROW][C]160[/C][C]0.998154[/C][C]0.00369229[/C][C]0.00184615[/C][/ROW]
[ROW][C]161[/C][C]0.99863[/C][C]0.0027402[/C][C]0.0013701[/C][/ROW]
[ROW][C]162[/C][C]0.998615[/C][C]0.00276926[/C][C]0.00138463[/C][/ROW]
[ROW][C]163[/C][C]0.998389[/C][C]0.00322136[/C][C]0.00161068[/C][/ROW]
[ROW][C]164[/C][C]0.999718[/C][C]0.000564417[/C][C]0.000282208[/C][/ROW]
[ROW][C]165[/C][C]0.999769[/C][C]0.000462085[/C][C]0.000231043[/C][/ROW]
[ROW][C]166[/C][C]0.999678[/C][C]0.000644647[/C][C]0.000322323[/C][/ROW]
[ROW][C]167[/C][C]0.999786[/C][C]0.000427997[/C][C]0.000213999[/C][/ROW]
[ROW][C]168[/C][C]0.999726[/C][C]0.000548447[/C][C]0.000274224[/C][/ROW]
[ROW][C]169[/C][C]0.999659[/C][C]0.000682052[/C][C]0.000341026[/C][/ROW]
[ROW][C]170[/C][C]0.999563[/C][C]0.000873075[/C][C]0.000436537[/C][/ROW]
[ROW][C]171[/C][C]0.999541[/C][C]0.000917466[/C][C]0.000458733[/C][/ROW]
[ROW][C]172[/C][C]0.99974[/C][C]0.00052021[/C][C]0.000260105[/C][/ROW]
[ROW][C]173[/C][C]0.999678[/C][C]0.000644303[/C][C]0.000322151[/C][/ROW]
[ROW][C]174[/C][C]0.999617[/C][C]0.000766916[/C][C]0.000383458[/C][/ROW]
[ROW][C]175[/C][C]0.99955[/C][C]0.000900396[/C][C]0.000450198[/C][/ROW]
[ROW][C]176[/C][C]0.999709[/C][C]0.000582789[/C][C]0.000291394[/C][/ROW]
[ROW][C]177[/C][C]0.999618[/C][C]0.000764727[/C][C]0.000382363[/C][/ROW]
[ROW][C]178[/C][C]0.999761[/C][C]0.000478913[/C][C]0.000239456[/C][/ROW]
[ROW][C]179[/C][C]0.999699[/C][C]0.000602011[/C][C]0.000301005[/C][/ROW]
[ROW][C]180[/C][C]0.999724[/C][C]0.000552423[/C][C]0.000276212[/C][/ROW]
[ROW][C]181[/C][C]0.999623[/C][C]0.000753519[/C][C]0.000376759[/C][/ROW]
[ROW][C]182[/C][C]0.999489[/C][C]0.00102262[/C][C]0.000511311[/C][/ROW]
[ROW][C]183[/C][C]0.999475[/C][C]0.00104994[/C][C]0.00052497[/C][/ROW]
[ROW][C]184[/C][C]0.999411[/C][C]0.00117824[/C][C]0.000589118[/C][/ROW]
[ROW][C]185[/C][C]0.999448[/C][C]0.00110342[/C][C]0.000551712[/C][/ROW]
[ROW][C]186[/C][C]0.999327[/C][C]0.00134561[/C][C]0.000672805[/C][/ROW]
[ROW][C]187[/C][C]0.999365[/C][C]0.00126982[/C][C]0.00063491[/C][/ROW]
[ROW][C]188[/C][C]0.999237[/C][C]0.00152505[/C][C]0.000762524[/C][/ROW]
[ROW][C]189[/C][C]0.999286[/C][C]0.00142748[/C][C]0.000713739[/C][/ROW]
[ROW][C]190[/C][C]0.999142[/C][C]0.00171552[/C][C]0.00085776[/C][/ROW]
[ROW][C]191[/C][C]0.998901[/C][C]0.00219831[/C][C]0.00109916[/C][/ROW]
[ROW][C]192[/C][C]0.99871[/C][C]0.00257969[/C][C]0.00128985[/C][/ROW]
[ROW][C]193[/C][C]0.998701[/C][C]0.00259707[/C][C]0.00129854[/C][/ROW]
[ROW][C]194[/C][C]0.999247[/C][C]0.00150631[/C][C]0.000753154[/C][/ROW]
[ROW][C]195[/C][C]0.999048[/C][C]0.00190456[/C][C]0.000952279[/C][/ROW]
[ROW][C]196[/C][C]0.998868[/C][C]0.00226444[/C][C]0.00113222[/C][/ROW]
[ROW][C]197[/C][C]0.998569[/C][C]0.00286293[/C][C]0.00143146[/C][/ROW]
[ROW][C]198[/C][C]0.998354[/C][C]0.00329296[/C][C]0.00164648[/C][/ROW]
[ROW][C]199[/C][C]0.998353[/C][C]0.00329497[/C][C]0.00164748[/C][/ROW]
[ROW][C]200[/C][C]0.998297[/C][C]0.00340652[/C][C]0.00170326[/C][/ROW]
[ROW][C]201[/C][C]0.998091[/C][C]0.00381878[/C][C]0.00190939[/C][/ROW]
[ROW][C]202[/C][C]0.997884[/C][C]0.00423102[/C][C]0.00211551[/C][/ROW]
[ROW][C]203[/C][C]0.997398[/C][C]0.00520315[/C][C]0.00260157[/C][/ROW]
[ROW][C]204[/C][C]0.996641[/C][C]0.0067178[/C][C]0.0033589[/C][/ROW]
[ROW][C]205[/C][C]0.996268[/C][C]0.00746307[/C][C]0.00373154[/C][/ROW]
[ROW][C]206[/C][C]0.995886[/C][C]0.00822857[/C][C]0.00411428[/C][/ROW]
[ROW][C]207[/C][C]0.994441[/C][C]0.0111172[/C][C]0.00555861[/C][/ROW]
[ROW][C]208[/C][C]0.993264[/C][C]0.013471[/C][C]0.00673551[/C][/ROW]
[ROW][C]209[/C][C]0.996447[/C][C]0.00710653[/C][C]0.00355326[/C][/ROW]
[ROW][C]210[/C][C]0.996959[/C][C]0.00608228[/C][C]0.00304114[/C][/ROW]
[ROW][C]211[/C][C]0.99591[/C][C]0.00817994[/C][C]0.00408997[/C][/ROW]
[ROW][C]212[/C][C]0.994793[/C][C]0.0104132[/C][C]0.00520658[/C][/ROW]
[ROW][C]213[/C][C]0.993479[/C][C]0.0130424[/C][C]0.0065212[/C][/ROW]
[ROW][C]214[/C][C]0.992304[/C][C]0.0153921[/C][C]0.00769607[/C][/ROW]
[ROW][C]215[/C][C]0.990286[/C][C]0.0194271[/C][C]0.00971353[/C][/ROW]
[ROW][C]216[/C][C]0.987517[/C][C]0.0249665[/C][C]0.0124833[/C][/ROW]
[ROW][C]217[/C][C]0.987887[/C][C]0.0242255[/C][C]0.0121127[/C][/ROW]
[ROW][C]218[/C][C]0.985153[/C][C]0.0296936[/C][C]0.0148468[/C][/ROW]
[ROW][C]219[/C][C]0.980395[/C][C]0.0392108[/C][C]0.0196054[/C][/ROW]
[ROW][C]220[/C][C]0.974993[/C][C]0.0500149[/C][C]0.0250075[/C][/ROW]
[ROW][C]221[/C][C]0.97517[/C][C]0.0496606[/C][C]0.0248303[/C][/ROW]
[ROW][C]222[/C][C]0.971062[/C][C]0.0578753[/C][C]0.0289377[/C][/ROW]
[ROW][C]223[/C][C]0.966635[/C][C]0.0667301[/C][C]0.0333651[/C][/ROW]
[ROW][C]224[/C][C]0.95985[/C][C]0.0802993[/C][C]0.0401496[/C][/ROW]
[ROW][C]225[/C][C]0.952813[/C][C]0.0943733[/C][C]0.0471867[/C][/ROW]
[ROW][C]226[/C][C]0.962971[/C][C]0.0740582[/C][C]0.0370291[/C][/ROW]
[ROW][C]227[/C][C]0.958102[/C][C]0.0837951[/C][C]0.0418975[/C][/ROW]
[ROW][C]228[/C][C]0.953641[/C][C]0.0927182[/C][C]0.0463591[/C][/ROW]
[ROW][C]229[/C][C]0.960369[/C][C]0.0792611[/C][C]0.0396306[/C][/ROW]
[ROW][C]230[/C][C]0.960325[/C][C]0.07935[/C][C]0.039675[/C][/ROW]
[ROW][C]231[/C][C]0.957412[/C][C]0.0851754[/C][C]0.0425877[/C][/ROW]
[ROW][C]232[/C][C]0.967837[/C][C]0.0643269[/C][C]0.0321635[/C][/ROW]
[ROW][C]233[/C][C]0.957796[/C][C]0.0844071[/C][C]0.0422035[/C][/ROW]
[ROW][C]234[/C][C]0.970442[/C][C]0.0591152[/C][C]0.0295576[/C][/ROW]
[ROW][C]235[/C][C]0.97319[/C][C]0.0536197[/C][C]0.0268099[/C][/ROW]
[ROW][C]236[/C][C]0.995761[/C][C]0.00847726[/C][C]0.00423863[/C][/ROW]
[ROW][C]237[/C][C]0.994642[/C][C]0.0107152[/C][C]0.00535759[/C][/ROW]
[ROW][C]238[/C][C]0.992799[/C][C]0.0144013[/C][C]0.00720063[/C][/ROW]
[ROW][C]239[/C][C]0.989609[/C][C]0.0207829[/C][C]0.0103914[/C][/ROW]
[ROW][C]240[/C][C]0.985491[/C][C]0.0290187[/C][C]0.0145094[/C][/ROW]
[ROW][C]241[/C][C]0.979908[/C][C]0.0401835[/C][C]0.0200918[/C][/ROW]
[ROW][C]242[/C][C]0.973549[/C][C]0.052903[/C][C]0.0264515[/C][/ROW]
[ROW][C]243[/C][C]0.964921[/C][C]0.0701582[/C][C]0.0350791[/C][/ROW]
[ROW][C]244[/C][C]0.959728[/C][C]0.0805434[/C][C]0.0402717[/C][/ROW]
[ROW][C]245[/C][C]0.949444[/C][C]0.101111[/C][C]0.0505556[/C][/ROW]
[ROW][C]246[/C][C]0.934478[/C][C]0.131045[/C][C]0.0655224[/C][/ROW]
[ROW][C]247[/C][C]0.917831[/C][C]0.164339[/C][C]0.0821693[/C][/ROW]
[ROW][C]248[/C][C]0.892113[/C][C]0.215773[/C][C]0.107887[/C][/ROW]
[ROW][C]249[/C][C]0.894002[/C][C]0.211996[/C][C]0.105998[/C][/ROW]
[ROW][C]250[/C][C]0.864042[/C][C]0.271917[/C][C]0.135958[/C][/ROW]
[ROW][C]251[/C][C]0.848208[/C][C]0.303585[/C][C]0.151792[/C][/ROW]
[ROW][C]252[/C][C]0.811599[/C][C]0.376803[/C][C]0.188401[/C][/ROW]
[ROW][C]253[/C][C]0.765425[/C][C]0.46915[/C][C]0.234575[/C][/ROW]
[ROW][C]254[/C][C]0.758794[/C][C]0.482412[/C][C]0.241206[/C][/ROW]
[ROW][C]255[/C][C]0.860083[/C][C]0.279834[/C][C]0.139917[/C][/ROW]
[ROW][C]256[/C][C]0.823717[/C][C]0.352567[/C][C]0.176283[/C][/ROW]
[ROW][C]257[/C][C]0.883492[/C][C]0.233017[/C][C]0.116508[/C][/ROW]
[ROW][C]258[/C][C]0.958309[/C][C]0.0833828[/C][C]0.0416914[/C][/ROW]
[ROW][C]259[/C][C]0.945388[/C][C]0.109223[/C][C]0.0546116[/C][/ROW]
[ROW][C]260[/C][C]0.998159[/C][C]0.00368285[/C][C]0.00184143[/C][/ROW]
[ROW][C]261[/C][C]0.996125[/C][C]0.00775083[/C][C]0.00387541[/C][/ROW]
[ROW][C]262[/C][C]0.99625[/C][C]0.00750045[/C][C]0.00375023[/C][/ROW]
[ROW][C]263[/C][C]0.999245[/C][C]0.00150951[/C][C]0.000754753[/C][/ROW]
[ROW][C]264[/C][C]0.998137[/C][C]0.00372598[/C][C]0.00186299[/C][/ROW]
[ROW][C]265[/C][C]0.997447[/C][C]0.00510553[/C][C]0.00255277[/C][/ROW]
[ROW][C]266[/C][C]0.996063[/C][C]0.00787372[/C][C]0.00393686[/C][/ROW]
[ROW][C]267[/C][C]0.9929[/C][C]0.0141999[/C][C]0.00709997[/C][/ROW]
[ROW][C]268[/C][C]0.981428[/C][C]0.0371446[/C][C]0.0185723[/C][/ROW]
[ROW][C]269[/C][C]0.959215[/C][C]0.081569[/C][C]0.0407845[/C][/ROW]
[ROW][C]270[/C][C]0.903319[/C][C]0.193361[/C][C]0.0966807[/C][/ROW]
[ROW][C]271[/C][C]0.961998[/C][C]0.0760032[/C][C]0.0380016[/C][/ROW]
[ROW][C]272[/C][C]0.968381[/C][C]0.0632385[/C][C]0.0316193[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269393&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269393&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.1089050.217810.891095
80.04198610.08397220.958014
90.06522080.1304420.934779
100.383970.767940.61603
110.3525260.7050520.647474
120.3688710.7377420.631129
130.3005810.6011620.699419
140.2206810.4413620.779319
150.1758450.351690.824155
160.1492860.2985710.850714
170.1060350.2120710.893965
180.07414670.1482930.925853
190.05094520.101890.949055
200.0388930.07778590.961107
210.1175490.2350990.882451
220.1119190.2238370.888081
230.09664180.1932840.903358
240.0837980.1675960.916202
250.06254420.1250880.937456
260.0486110.09722190.951389
270.0871740.1743480.912826
280.07642090.1528420.923579
290.1051910.2103820.894809
300.08231990.164640.91768
310.06830460.1366090.931695
320.05790570.1158110.942094
330.06338180.1267640.936618
340.05832330.1166470.941677
350.0460180.09203590.953982
360.03675550.07351110.963244
370.02825670.05651350.971743
380.02935550.0587110.970644
390.03108430.06216860.968916
400.02377470.04754950.976225
410.05527650.1105530.944724
420.04411480.08822950.955885
430.03759410.07518830.962406
440.03358460.06716930.966415
450.03284940.06569870.967151
460.02825210.05650430.971748
470.0251150.05022990.974885
480.02310860.04621720.976891
490.02538740.05077470.974613
500.02123420.04246840.978766
510.01657020.03314050.98343
520.01661820.03323650.983382
530.01357430.02714860.986426
540.01127330.02254650.988727
550.01166420.02332830.988336
560.009582350.01916470.990418
570.03205010.06410020.96795
580.03908150.0781630.960918
590.03328160.06656320.966718
600.03399230.06798460.966008
610.03894710.07789420.961053
620.03334230.06668460.966658
630.04128110.08256220.958719
640.05300340.1060070.946997
650.06377380.1275480.936226
660.05565830.1113170.944342
670.05617130.1123430.943829
680.05736450.1147290.942635
690.06243670.1248730.937563
700.05595930.1119190.944041
710.05217670.1043530.947823
720.04636280.09272560.953637
730.04049590.08099170.959504
740.05391790.1078360.946082
750.0482880.09657610.951712
760.04435440.08870870.955646
770.0406860.08137210.959314
780.03768910.07537830.962311
790.0304770.0609540.969523
800.03678030.07356060.96322
810.0308040.0616080.969196
820.03108020.06216030.96892
830.02607080.05214170.973929
840.08710630.1742130.912894
850.08542530.1708510.914575
860.0762740.1525480.923726
870.06616840.1323370.933832
880.05841450.1168290.941585
890.06116410.1223280.938836
900.057940.115880.94206
910.05586730.1117350.944133
920.128640.257280.87136
930.1325190.2650380.867481
940.1343350.268670.865665
950.1521060.3042130.847894
960.1617010.3234020.838299
970.2432910.4865820.756709
980.228180.456360.77182
990.2351560.4703130.764844
1000.3011820.6023630.698818
1010.2769780.5539560.723022
1020.2800610.5601220.719939
1030.282440.564880.71756
1040.3022310.6044620.697769
1050.3395340.6790690.660466
1060.3578570.7157130.642143
1070.3671990.7343980.632801
1080.6503620.6992760.349638
1090.7148450.5703090.285155
1100.7108620.5782760.289138
1110.7149720.5700550.285028
1120.7106970.5786060.289303
1130.8264380.3471240.173562
1140.8332560.3334880.166744
1150.9051070.1897860.0948928
1160.9371060.1257890.0628944
1170.9557230.08855460.0442773
1180.9548060.09038750.0451938
1190.9630770.07384580.0369229
1200.9811780.03764490.0188225
1210.982780.03443990.0172199
1220.9842710.0314580.015729
1230.9910490.0179010.0089505
1240.9937090.01258230.00629117
1250.9939790.01204270.00602135
1260.9932530.01349360.00674678
1270.9946140.01077150.00538577
1280.9940860.01182720.00591358
1290.9977330.004534910.00226746
1300.9974910.005017410.00250871
1310.997160.005679150.00283957
1320.9971270.005745670.00287284
1330.9967960.006408280.00320414
1340.9966960.006607280.00330364
1350.995930.008139640.00406982
1360.99510.009800110.00490006
1370.9963060.007388880.00369444
1380.9959090.008182480.00409124
1390.9971490.005701090.00285055
1400.9974110.005178280.00258914
1410.9968020.006396890.00319845
1420.9971420.005716480.00285824
1430.997410.005179490.00258974
1440.9980070.003986880.00199344
1450.9979720.004055240.00202762
1460.9982970.003405310.00170266
1470.9978760.004248950.00212448
1480.9976130.004774660.00238733
1490.9975370.004925530.00246276
1500.9976020.00479550.00239775
1510.9991120.001775250.000887624
1520.9990850.001830710.000915354
1530.999130.001740840.000870419
1540.9990670.001865290.000932647
1550.9990490.001901450.000950726
1560.9989160.002167980.00108399
1570.9989590.00208280.0010414
1580.9988240.002352720.00117636
1590.9985340.00293160.0014658
1600.9981540.003692290.00184615
1610.998630.00274020.0013701
1620.9986150.002769260.00138463
1630.9983890.003221360.00161068
1640.9997180.0005644170.000282208
1650.9997690.0004620850.000231043
1660.9996780.0006446470.000322323
1670.9997860.0004279970.000213999
1680.9997260.0005484470.000274224
1690.9996590.0006820520.000341026
1700.9995630.0008730750.000436537
1710.9995410.0009174660.000458733
1720.999740.000520210.000260105
1730.9996780.0006443030.000322151
1740.9996170.0007669160.000383458
1750.999550.0009003960.000450198
1760.9997090.0005827890.000291394
1770.9996180.0007647270.000382363
1780.9997610.0004789130.000239456
1790.9996990.0006020110.000301005
1800.9997240.0005524230.000276212
1810.9996230.0007535190.000376759
1820.9994890.001022620.000511311
1830.9994750.001049940.00052497
1840.9994110.001178240.000589118
1850.9994480.001103420.000551712
1860.9993270.001345610.000672805
1870.9993650.001269820.00063491
1880.9992370.001525050.000762524
1890.9992860.001427480.000713739
1900.9991420.001715520.00085776
1910.9989010.002198310.00109916
1920.998710.002579690.00128985
1930.9987010.002597070.00129854
1940.9992470.001506310.000753154
1950.9990480.001904560.000952279
1960.9988680.002264440.00113222
1970.9985690.002862930.00143146
1980.9983540.003292960.00164648
1990.9983530.003294970.00164748
2000.9982970.003406520.00170326
2010.9980910.003818780.00190939
2020.9978840.004231020.00211551
2030.9973980.005203150.00260157
2040.9966410.00671780.0033589
2050.9962680.007463070.00373154
2060.9958860.008228570.00411428
2070.9944410.01111720.00555861
2080.9932640.0134710.00673551
2090.9964470.007106530.00355326
2100.9969590.006082280.00304114
2110.995910.008179940.00408997
2120.9947930.01041320.00520658
2130.9934790.01304240.0065212
2140.9923040.01539210.00769607
2150.9902860.01942710.00971353
2160.9875170.02496650.0124833
2170.9878870.02422550.0121127
2180.9851530.02969360.0148468
2190.9803950.03921080.0196054
2200.9749930.05001490.0250075
2210.975170.04966060.0248303
2220.9710620.05787530.0289377
2230.9666350.06673010.0333651
2240.959850.08029930.0401496
2250.9528130.09437330.0471867
2260.9629710.07405820.0370291
2270.9581020.08379510.0418975
2280.9536410.09271820.0463591
2290.9603690.07926110.0396306
2300.9603250.079350.039675
2310.9574120.08517540.0425877
2320.9678370.06432690.0321635
2330.9577960.08440710.0422035
2340.9704420.05911520.0295576
2350.973190.05361970.0268099
2360.9957610.008477260.00423863
2370.9946420.01071520.00535759
2380.9927990.01440130.00720063
2390.9896090.02078290.0103914
2400.9854910.02901870.0145094
2410.9799080.04018350.0200918
2420.9735490.0529030.0264515
2430.9649210.07015820.0350791
2440.9597280.08054340.0402717
2450.9494440.1011110.0505556
2460.9344780.1310450.0655224
2470.9178310.1643390.0821693
2480.8921130.2157730.107887
2490.8940020.2119960.105998
2500.8640420.2719170.135958
2510.8482080.3035850.151792
2520.8115990.3768030.188401
2530.7654250.469150.234575
2540.7587940.4824120.241206
2550.8600830.2798340.139917
2560.8237170.3525670.176283
2570.8834920.2330170.116508
2580.9583090.08338280.0416914
2590.9453880.1092230.0546116
2600.9981590.003682850.00184143
2610.9961250.007750830.00387541
2620.996250.007500450.00375023
2630.9992450.001509510.000754753
2640.9981370.003725980.00186299
2650.9974470.005105530.00255277
2660.9960630.007873720.00393686
2670.99290.01419990.00709997
2680.9814280.03714460.0185723
2690.9592150.0815690.0407845
2700.9033190.1933610.0966807
2710.9619980.07600320.0380016
2720.9683810.06323850.0316193






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level890.334586NOK
5% type I error level1250.469925NOK
10% type I error level1830.68797NOK

\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 & 89 & 0.334586 & NOK \tabularnewline
5% type I error level & 125 & 0.469925 & NOK \tabularnewline
10% type I error level & 183 & 0.68797 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269393&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]89[/C][C]0.334586[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]125[/C][C]0.469925[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]183[/C][C]0.68797[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269393&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269393&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level890.334586NOK
5% type I error level1250.469925NOK
10% type I error level1830.68797NOK


Figures (Output of Computation)

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


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


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


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


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


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


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


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


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


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


Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}