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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 08 Dec 2014 14:35:30 +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/08/t1418049413yis89cdwbvqgu77.htm/, Retrieved Fri, 17 May 2024 10:36:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264028, Retrieved Fri, 17 May 2024 10:36:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [multiple regressi...] [2014-12-08 14:35:30] [d71ad52285d92a63edfc83f9fb1da7a1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2.1 0 26 21 149 68
1.5 0 51 26 152 55
2 1 57 22 139 39
2 0 37 22 148 32
2.1 1 67 18 158 62
2 1 43 23 128 33
2.3 1 52 12 224 52
2.1 0 52 20 159 62
2.1 1 43 22 105 77
2.2 1 84 21 159 76
2.1 1 67 19 167 41
2.1 1 49 22 165 48
2.1 1 70 15 159 63
2 1 52 20 119 30
2.3 0 58 19 176 78
1.8 0 68 18 54 19
2 0 62 15 91 31
2.2 1 43 20 163 66
2 0 56 21 124 35
2.1 1 56 21 137 42
2 0 74 15 121 45
1.8 1 65 16 153 21
2.2 1 63 23 148 25
2.2 0 58 21 221 44
1.7 1 57 18 188 69
2.1 1 63 25 149 54
2.3 1 53 9 244 74
2.7 1 57 30 148 80
1.9 0 51 20 92 42
2 1 64 23 150 61
2 0 53 16 153 41
1.9 0 29 16 94 46
2 0 54 19 156 39
2 1 51 25 146 63
2 1 58 25 132 34
2.1 1 43 18 161 51
2 1 51 23 105 42
1.8 1 53 21 97 31
2 0 54 10 151 39
2.2 1 56 14 131 20
2.2 1 61 22 166 49
2.1 0 47 26 157 53
1.8 1 39 23 111 31
1.9 1 48 23 145 39
2.1 1 50 24 162 54
2 1 35 24 163 49
1.9 1 30 18 59 34
2.2 0 68 23 187 46
2 1 49 15 109 55
2 1 61 19 90 42
1.7 0 67 16 105 50
2 1 47 25 83 13
2.2 1 56 23 116 37
1.7 1 50 17 42 25
2 1 43 19 148 30
2.2 1 67 21 155 28
2 1 62 18 125 45
1.9 1 57 27 116 35
2 0 41 21 128 28
2 1 54 13 138 41
1.6 0 45 8 49 6
2.1 1 48 29 96 45
2.1 1 61 28 164 73
2 0 56 23 162 17
1.9 0 41 21 99 40
2.2 1 43 19 202 64
2.1 0 53 19 186 37
1.8 1 44 20 66 25
2.3 0 66 18 183 65
2.3 1 58 19 214 100
2.2 1 46 17 188 28
2.1 0 37 19 104 35
2.2 0 51 25 177 56
1.9 0 51 19 126 29
1.8 0 56 22 76 43
2.1 1 66 23 99 59
1.8 1 45 26 157 52
2 0 37 14 139 50
1.7 1 59 28 78 3
2.1 0 42 16 162 59
2.1 1 38 24 108 27
2.1 0 66 20 159 61
1.8 0 34 12 74 28
2 1 53 24 110 51
2.1 0 49 22 96 35
1.9 0 55 12 116 29
2.1 0 49 22 87 48
1 1 59 20 97 25
2.2 0 40 10 127 44
2.1 1 58 23 106 64
1.9 1 60 17 80 32
2 0 63 22 74 20
1.9 0 56 24 91 28
2 0 54 18 133 34
1.8 1 52 21 74 31
2 1 34 20 114 26
2 1 69 20 140 58
2 0 32 22 95 23
1.8 1 48 19 98 21
2 0 67 20 121 21
1.1 1 58 26 126 33
1.8 1 57 23 98 16
1.8 1 42 24 95 20
2 1 64 21 110 37
1.9 1 58 21 70 35
2.1 0 66 19 102 33
1.6 1 26 8 86 27
2.2 1 61 17 130 41
1.9 1 52 20 96 40
2 0 51 11 102 35
2.1 0 55 8 100 28
1.3 0 50 15 94 32
1.8 0 60 18 52 22
1.9 0 56 18 98 44
2.1 0 63 19 118 27
1.8 1 61 19 99 17
0.75 1 52 23 48 12
1.5 1 16 22 50 45
3 1 46 21 150 37
2.25 1 56 25 154 37
3 0 52 30 109 108
1.5 1 55 17 68 10
3 1 50 27 194 68
3 0 59 23 158 72
3 1 60 23 159 143
0.75 0 52 18 67 9
3 0 44 18 147 55
2.25 1 67 23 39 17
1.5 1 52 19 100 37
1.5 1 55 15 111 27
2.25 1 37 20 138 37
3 1 54 16 101 58
3 1 72 24 131 66
1.5 1 51 25 101 21
2.25 1 48 25 114 19
2.25 0 60 19 165 78
1.5 1 50 19 114 35
2.25 1 63 16 111 48
1.5 1 33 19 75 27
2.25 1 67 19 82 43
2.25 1 46 23 121 30
3 1 54 21 32 25
3 0 59 22 150 69
3 1 61 19 117 72
1.5 1 33 20 71 23
3 1 47 20 165 13
3 1 69 3 154 61
2.25 1 52 23 126 43
1.5 0 55 14 138 22
2.25 0 55 23 149 51
2.25 0 41 20 145 67
3 1 73 15 120 36
0.75 0 51 13 138 21
2.25 0 52 16 109 44
3 0 50 7 132 45
3 1 51 24 172 34
1.5 0 60 17 169 36
2.25 1 56 24 114 72
3 1 56 24 156 39
2.25 0 29 19 172 43
1.5 1 66 25 68 25
2.25 1 66 20 89 56
2.25 1 73 28 167 80
1.5 0 55 23 113 40
2.25 0 64 27 115 73
1.5 0 40 18 78 34
2.25 0 46 28 118 72
3 1 58 21 87 42
3 0 43 19 173 61
3 1 61 23 2 23
3 0 51 27 162 74
1.5 1 50 22 49 16
2.25 0 52 28 122 66
1.5 1 54 25 96 9
2.25 0 66 21 100 41
2.25 0 61 22 82 57
2.25 1 80 28 100 48
3 0 51 20 115 51
1.5 1 56 29 141 53
2.25 1 56 25 165 29
2.25 1 56 25 165 29
3 1 53 20 110 55
2.25 1 47 20 118 54
3 0 25 16 158 43
2.25 1 47 20 146 51
1.5 0 46 20 49 20
3 0 50 23 90 79
1.5 0 39 18 121 39
3 1 51 25 155 61
3 0 58 18 104 55
3 1 35 19 147 30
3 0 58 25 110 55
2.25 0 60 25 108 22
2.25 0 62 25 113 37
0.75 0 63 24 115 2
3 1 53 19 61 38
0.75 1 46 26 60 27
1.5 1 67 10 109 56
1.5 1 59 17 68 25
3 0 64 13 111 39
1.5 0 38 17 77 33
2.25 1 50 30 73 43
3 0 48 25 151 57
3 0 48 4 89 43
1.5 0 47 16 78 23
3 0 66 21 110 44
3 1 47 23 220 54
1.5 1 63 22 65 28
1.5 0 58 17 141 36
2.25 0 44 20 117 39
1.5 1 51 20 122 16
1.5 0 43 22 63 23
2.25 1 55 16 44 40
1.5 1 38 23 52 24
2.25 1 56 16 62 29
3 0 45 0 131 78
3 1 50 18 101 57
0.75 1 54 25 42 37
1.5 1 57 23 152 27
1.5 0 60 12 107 61
2.25 0 55 18 77 27
2.25 0 56 24 154 69
1.5 1 49 11 103 34
2.25 1 37 18 96 44
0.75 0 43 14 154 21
2.25 1 59 23 175 34
0.75 1 46 24 57 39
2.25 0 51 29 112 51
3 0 58 18 143 34
0.75 0 64 15 49 31
0.75 1 53 29 110 13
3 1 48 16 131 12
3 0 51 19 167 51
3 0 47 22 56 24
3 0 59 16 137 19
1.5 1 62 23 86 30
3 1 62 23 121 81
3 0 51 19 149 42
3 0 64 4 168 22
3 0 52 20 140 85
1.5 1 67 24 88 27
2.25 1 50 20 168 25
0.75 1 54 4 94 22
0.75 1 58 24 51 19
2.25 0 56 22 48 14
3 1 63 16 145 45
2.25 1 31 3 66 45
3 1 65 15 85 28
2.25 0 71 24 109 51
3 0 50 17 63 41
1.5 1 57 20 102 31
3 0 47 27 162 74
3 1 54 23 128 24
0.75 1 47 26 86 19
1.5 1 57 23 114 51
3 0 43 17 164 73
3 1 41 20 119 24
3 0 63 22 126 61
2.25 1 63 19 132 23
2.25 1 56 24 142 14
3 0 51 19 83 54
1.5 1 50 23 94 51
2.25 0 22 15 81 62
2.25 1 41 27 166 36
2.25 0 59 26 110 59
0.75 1 56 22 64 24
2.25 0 66 22 93 26
1.5 0 53 18 104 54
2.25 1 42 15 105 39
1.5 1 52 22 49 16
0.75 0 54 27 88 36
1.5 1 44 10 95 31
1.5 1 62 20 102 31
2.25 0 53 17 99 42
1.5 1 50 23 63 39
1.5 0 36 19 76 25
3 0 76 13 109 31
2.25 1 66 27 117 38
1.5 1 62 23 57 31
0.75 0 59 16 120 17
2.25 1 47 25 73 22
3 0 55 2 91 55
3 0 58 26 108 62
1.5 1 60 20 105 51
1.5 0 44 23 117 30
2.25 0 57 22 119 49
0.75 1 45 24 31 16

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 11 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264028&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]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264028&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264028&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 time11 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
PE[t] = + 1.40506 -0.0675157gender[t] + 0.00275816AMS.I[t] -0.00982324NUMERACYTOT[t] + 0.00261785LFM[t] + 0.0113957CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
PE[t] =  +  1.40506 -0.0675157gender[t] +  0.00275816AMS.I[t] -0.00982324NUMERACYTOT[t] +  0.00261785LFM[t] +  0.0113957CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264028&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]PE[t] =  +  1.40506 -0.0675157gender[t] +  0.00275816AMS.I[t] -0.00982324NUMERACYTOT[t] +  0.00261785LFM[t] +  0.0113957CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264028&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264028&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
PE[t] = + 1.40506 -0.0675157gender[t] + 0.00275816AMS.I[t] -0.00982324NUMERACYTOT[t] + 0.00261785LFM[t] + 0.0113957CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.405060.2135156.5812.28684e-101.14342e-10
gender-0.06751570.0644832-1.0470.2959870.147993
AMS.I0.002758160.003087890.89320.3725040.186252
NUMERACYTOT-0.009823240.0062185-1.580.1153050.0576524
LFM0.002617850.000876042.9880.003053490.00152675
CH0.01139570.001838416.1992.024e-091.012e-09

\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) & 1.40506 & 0.213515 & 6.581 & 2.28684e-10 & 1.14342e-10 \tabularnewline
gender & -0.0675157 & 0.0644832 & -1.047 & 0.295987 & 0.147993 \tabularnewline
AMS.I & 0.00275816 & 0.00308789 & 0.8932 & 0.372504 & 0.186252 \tabularnewline
NUMERACYTOT & -0.00982324 & 0.0062185 & -1.58 & 0.115305 & 0.0576524 \tabularnewline
LFM & 0.00261785 & 0.00087604 & 2.988 & 0.00305349 & 0.00152675 \tabularnewline
CH & 0.0113957 & 0.00183841 & 6.199 & 2.024e-09 & 1.012e-09 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264028&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]1.40506[/C][C]0.213515[/C][C]6.581[/C][C]2.28684e-10[/C][C]1.14342e-10[/C][/ROW]
[ROW][C]gender[/C][C]-0.0675157[/C][C]0.0644832[/C][C]-1.047[/C][C]0.295987[/C][C]0.147993[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.00275816[/C][C]0.00308789[/C][C]0.8932[/C][C]0.372504[/C][C]0.186252[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]-0.00982324[/C][C]0.0062185[/C][C]-1.58[/C][C]0.115305[/C][C]0.0576524[/C][/ROW]
[ROW][C]LFM[/C][C]0.00261785[/C][C]0.00087604[/C][C]2.988[/C][C]0.00305349[/C][C]0.00152675[/C][/ROW]
[ROW][C]CH[/C][C]0.0113957[/C][C]0.00183841[/C][C]6.199[/C][C]2.024e-09[/C][C]1.012e-09[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264028&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264028&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)1.405060.2135156.5812.28684e-101.14342e-10
gender-0.06751570.0644832-1.0470.2959870.147993
AMS.I0.002758160.003087890.89320.3725040.186252
NUMERACYTOT-0.009823240.0062185-1.580.1153050.0576524
LFM0.002617850.000876042.9880.003053490.00152675
CH0.01139570.001838416.1992.024e-091.012e-09






Multiple Linear Regression - Regression Statistics
Multiple R0.486208
R-squared0.236398
Adjusted R-squared0.222811
F-TEST (value)17.3985
F-TEST (DF numerator)5
F-TEST (DF denominator)281
p-value5.32907e-15
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.526762
Sum Squared Residuals77.9713

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.486208 \tabularnewline
R-squared & 0.236398 \tabularnewline
Adjusted R-squared & 0.222811 \tabularnewline
F-TEST (value) & 17.3985 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 5.32907e-15 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.526762 \tabularnewline
Sum Squared Residuals & 77.9713 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264028&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.486208[/C][/ROW]
[ROW][C]R-squared[/C][C]0.236398[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.222811[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]17.3985[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]281[/C][/ROW]
[ROW][C]p-value[/C][C]5.32907e-15[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.526762[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]77.9713[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264028&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264028&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 R0.486208
R-squared0.236398
Adjusted R-squared0.222811
F-TEST (value)17.3985
F-TEST (DF numerator)5
F-TEST (DF denominator)281
p-value5.32907e-15
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.526762
Sum Squared Residuals77.9713






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
12.12.43545-0.335453
21.52.315-0.815001
322.08696-0.0869641
422.04311-0.0431076
52.12.46568-0.365678
621.941360.0586437
72.32.54207-0.242066
82.12.47479-0.374793
92.12.39238-0.292378
102.22.64525-0.445254
112.12.24011-0.140106
122.12.23552-0.135524
132.12.51744-0.417436
1421.93790.0620981
152.32.728-0.427999
161.81.773680.0263176
1722.02021-0.0202114
182.22.43851-0.238508
1922.07669-0.0766946
202.12.12298-0.0229805
2122.29138-0.291384
221.81.9995-0.199497
232.21.957710.242289
242.22.4387-0.238703
251.72.5964-0.896401
262.12.27116-0.171157
272.32.87736-0.577356
282.72.499160.200839
291.92.06873-0.168726
3022.37595-0.375949
3122.26183-0.261828
321.92.09816-0.198157
3322.22018-0.220178
3422.33277-0.332766
3521.984950.0150507
362.12.28198-0.181983
3722.00577-0.00577217
381.81.88464-0.0846399
3922.2955-0.295498
402.21.925330.274668
412.22.28264-0.0826352
422.12.29427-0.194266
431.81.86303-0.063029
441.92.06802-0.168025
452.12.27916-0.179156
4622.18342-0.183423
471.91.785380.114619
482.22.38042-0.180423
4922.23746-0.237457
5022.03338-0.0333791
511.72.27735-0.577346
5221.587030.412974
532.21.991380.208619
541.71.7033-0.00330293
5521.998820.00118077
562.22.04090.159098
5722.17177-0.171772
581.91.93205-0.0320548
5921.966020.0339761
6022.18727-0.187272
611.61.64724-0.0472443
622.11.949180.150815
632.12.49196-0.391956
6421.95140.0485958
651.92.02685-0.126854
662.22.52764-0.327635
672.12.27316-0.173164
681.81.720110.0798875
692.32.63007-0.330069
702.33.01067-0.710666
712.22.108660.0913373
722.11.991580.108421
732.22.40167-0.201666
741.92.01941-0.119412
751.82.03238-0.23238
762.12.22516-0.125164
771.82.20984-0.409838
7822.30325-0.303255
791.71.463610.236392
802.12.46017-0.360171
812.11.797010.302989
822.12.50201-0.402011
831.81.89376-0.0937623
8422.11712-0.117115
852.11.974260.125735
861.92.07303-0.173029
872.12.098850.00115241
8811.84264-0.842638
892.22.25103-0.0510342
902.12.2784-0.178402
911.91.91013-0.0101323
9221.784350.215649
931.91.881070.0189337
9422.11281-0.112813
951.81.82167-0.0216713
9621.829580.170417
9722.35884-0.358844
9821.788010.21199
991.81.779160.0208432
10021.949460.0505353
1011.11.94802-0.848023
1021.81.707710.0922911
1031.81.694240.105758
10422.01739-0.0173856
1051.91.873330.0266685
1062.12.043540.0564613
1071.61.86349-0.263493
1082.22.146340.0536563
1091.91.99165-0.0916481
11022.10354-0.103544
1112.12.059040.0409593
1121.32.00636-0.706363
1131.81.780570.0194315
1141.92.14066-0.240661
1152.12.008780.0912242
1161.81.772050.0279519
1170.751.51744-0.767443
1181.51.80927-0.309265
11932.072450.927547
1202.252.071210.178787
12132.769870.230131
1221.51.61422-0.114223
12332.4930.507003
12432.575970.424031
12533.32292-0.322921
1260.751.64963-0.899627
12732.361190.63881
1282.251.592230.657767
1291.51.97776-0.477756
1301.51.94016-0.440163
1312.252.026040.223962
13232.254670.745331
13332.395430.60457
1341.51.73635-0.236345
1352.251.739310.510688
1362.252.70472-0.454719
1371.51.9861-0.486098
1382.252.191710.0582861
1391.51.74595-0.245948
1402.252.040380.209619
1412.251.897120.352881
14231.648861.35114
14332.530660.469338
14432.445930.554069
1451.51.68007-0.180071
14631.850811.14919
14732.596680.403324
1482.252.07490.175099
1491.52.03121-0.531205
1502.252.30207-0.0520667
1512.252.46478-0.214781
15232.115930.884069
1530.752.0186-1.2686
1542.252.178070.0719285
15532.332570.66743
15632.080180.919821
1571.52.25622-0.756219
1582.252.37517-0.12517
15932.109060.890937
1602.252.238690.0113074
1611.51.73691-0.236912
1622.252.194270.0557319
1632.252.61268-0.362677
1641.52.08247-0.582472
1652.252.4493-0.199295
1661.51.93022-0.430217
1672.252.38628-0.136283
16831.99761.0024
16932.485050.514953
17031.54721.4528
17132.547870.452127
1721.51.56995-0.0699506
1732.252.34493-0.0949291
1741.51.59478-0.0947826
1752.252.109820.140178
1762.252.221420.0285827
1772.252.091930.158073
17832.23150.768503
1791.52.18022-0.680218
1802.252.008840.241156
1812.252.008840.241156
18232.201990.798009
1832.252.194990.0550108
18432.220480.77952
1852.252.23410.0158981
1861.51.69166-0.191663
18732.45290.547098
1881.52.097-0.597005
18932.333540.666464
19032.287240.712763
19131.974141.02586
19232.234180.765819
1932.251.858410.391595
1942.252.047950.202054
1950.751.66691-0.916914
19631.889811.11019
1970.751.67377-0.923774
1981.52.34762-0.847616
1991.51.79619-0.29619
20032.18890.811104
2011.51.92051-0.420511
2022.251.861880.388124
20332.336720.663277
20432.221170.778835
2051.51.84382-0.343818
20632.170190.829813
20732.432540.56746
2081.51.78444-0.28444
2091.52.1774-0.677403
2102.252.080680.169322
2111.51.78346-0.283458
2121.51.73458-0.234579
2132.251.903090.346912
2141.51.62605-0.126048
2152.251.827610.422385
21632.760980.239019
21732.212590.787406
2180.751.7725-1.0225
2191.51.97442-0.474425
2201.52.42792-0.92792
2212.251.88920.360798
2222.252.51321-0.263213
2231.52.02173-0.521734
2242.252.01550.234495
2250.752.0286-1.2786
2262.252.119920.130079
2270.751.82231-1.07231
2282.252.135230.114766
22932.150020.849976
2300.751.91578-1.16578
2310.751.63496-0.884964
23231.792451.20755
23332.377450.622552
23431.738681.26132
23531.985791.01421
2361.51.84962-0.349625
23732.522430.477572
23832.227770.772234
23932.23280.767203
24032.687150.312846
2411.51.82464-0.324641
2422.252.003680.246318
2430.751.94398-1.19398
2440.751.61179-0.861792
2452.251.628610.621394
24632.246530.753466
2472.252.079160.170835
24831.911081.08892
2492.252.231660.0183398
25032.008120.991876
2511.51.91859-0.418585
25232.536840.463159
25331.869141.13086
2540.751.65343-0.90343
2551.52.14844-0.648443
25632.617880.382119
25731.839191.16081
25832.38770.612299
2592.251.932330.317673
2602.251.787520.462479
26132.191740.808264
2621.52.07678-0.576779
2632.252.236970.0130278
2642.252.030210.219788
2652.252.2727-0.022699
2660.751.71693-0.966933
2672.251.910740.339261
2681.52.26205-0.762051
2692.252.025350.224652
2701.51.57547-0.075467
2710.751.92939-1.17939
2721.51.96264-0.462636
2731.51.93238-0.432376
2742.252.122040.127963
2751.51.85888-0.358878
2761.51.80156-0.301565
27732.125590.874407
2782.251.993680.256317
2791.51.7851-0.285103
2800.751.91849-1.16849
2812.251.663410.586591
28232.40210.597898
28332.298890.701108
2841.52.16263-0.662626
2851.51.94865-0.448647
2862.252.216080.0339204
2870.751.48939-0.739392

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 2.1 & 2.43545 & -0.335453 \tabularnewline
2 & 1.5 & 2.315 & -0.815001 \tabularnewline
3 & 2 & 2.08696 & -0.0869641 \tabularnewline
4 & 2 & 2.04311 & -0.0431076 \tabularnewline
5 & 2.1 & 2.46568 & -0.365678 \tabularnewline
6 & 2 & 1.94136 & 0.0586437 \tabularnewline
7 & 2.3 & 2.54207 & -0.242066 \tabularnewline
8 & 2.1 & 2.47479 & -0.374793 \tabularnewline
9 & 2.1 & 2.39238 & -0.292378 \tabularnewline
10 & 2.2 & 2.64525 & -0.445254 \tabularnewline
11 & 2.1 & 2.24011 & -0.140106 \tabularnewline
12 & 2.1 & 2.23552 & -0.135524 \tabularnewline
13 & 2.1 & 2.51744 & -0.417436 \tabularnewline
14 & 2 & 1.9379 & 0.0620981 \tabularnewline
15 & 2.3 & 2.728 & -0.427999 \tabularnewline
16 & 1.8 & 1.77368 & 0.0263176 \tabularnewline
17 & 2 & 2.02021 & -0.0202114 \tabularnewline
18 & 2.2 & 2.43851 & -0.238508 \tabularnewline
19 & 2 & 2.07669 & -0.0766946 \tabularnewline
20 & 2.1 & 2.12298 & -0.0229805 \tabularnewline
21 & 2 & 2.29138 & -0.291384 \tabularnewline
22 & 1.8 & 1.9995 & -0.199497 \tabularnewline
23 & 2.2 & 1.95771 & 0.242289 \tabularnewline
24 & 2.2 & 2.4387 & -0.238703 \tabularnewline
25 & 1.7 & 2.5964 & -0.896401 \tabularnewline
26 & 2.1 & 2.27116 & -0.171157 \tabularnewline
27 & 2.3 & 2.87736 & -0.577356 \tabularnewline
28 & 2.7 & 2.49916 & 0.200839 \tabularnewline
29 & 1.9 & 2.06873 & -0.168726 \tabularnewline
30 & 2 & 2.37595 & -0.375949 \tabularnewline
31 & 2 & 2.26183 & -0.261828 \tabularnewline
32 & 1.9 & 2.09816 & -0.198157 \tabularnewline
33 & 2 & 2.22018 & -0.220178 \tabularnewline
34 & 2 & 2.33277 & -0.332766 \tabularnewline
35 & 2 & 1.98495 & 0.0150507 \tabularnewline
36 & 2.1 & 2.28198 & -0.181983 \tabularnewline
37 & 2 & 2.00577 & -0.00577217 \tabularnewline
38 & 1.8 & 1.88464 & -0.0846399 \tabularnewline
39 & 2 & 2.2955 & -0.295498 \tabularnewline
40 & 2.2 & 1.92533 & 0.274668 \tabularnewline
41 & 2.2 & 2.28264 & -0.0826352 \tabularnewline
42 & 2.1 & 2.29427 & -0.194266 \tabularnewline
43 & 1.8 & 1.86303 & -0.063029 \tabularnewline
44 & 1.9 & 2.06802 & -0.168025 \tabularnewline
45 & 2.1 & 2.27916 & -0.179156 \tabularnewline
46 & 2 & 2.18342 & -0.183423 \tabularnewline
47 & 1.9 & 1.78538 & 0.114619 \tabularnewline
48 & 2.2 & 2.38042 & -0.180423 \tabularnewline
49 & 2 & 2.23746 & -0.237457 \tabularnewline
50 & 2 & 2.03338 & -0.0333791 \tabularnewline
51 & 1.7 & 2.27735 & -0.577346 \tabularnewline
52 & 2 & 1.58703 & 0.412974 \tabularnewline
53 & 2.2 & 1.99138 & 0.208619 \tabularnewline
54 & 1.7 & 1.7033 & -0.00330293 \tabularnewline
55 & 2 & 1.99882 & 0.00118077 \tabularnewline
56 & 2.2 & 2.0409 & 0.159098 \tabularnewline
57 & 2 & 2.17177 & -0.171772 \tabularnewline
58 & 1.9 & 1.93205 & -0.0320548 \tabularnewline
59 & 2 & 1.96602 & 0.0339761 \tabularnewline
60 & 2 & 2.18727 & -0.187272 \tabularnewline
61 & 1.6 & 1.64724 & -0.0472443 \tabularnewline
62 & 2.1 & 1.94918 & 0.150815 \tabularnewline
63 & 2.1 & 2.49196 & -0.391956 \tabularnewline
64 & 2 & 1.9514 & 0.0485958 \tabularnewline
65 & 1.9 & 2.02685 & -0.126854 \tabularnewline
66 & 2.2 & 2.52764 & -0.327635 \tabularnewline
67 & 2.1 & 2.27316 & -0.173164 \tabularnewline
68 & 1.8 & 1.72011 & 0.0798875 \tabularnewline
69 & 2.3 & 2.63007 & -0.330069 \tabularnewline
70 & 2.3 & 3.01067 & -0.710666 \tabularnewline
71 & 2.2 & 2.10866 & 0.0913373 \tabularnewline
72 & 2.1 & 1.99158 & 0.108421 \tabularnewline
73 & 2.2 & 2.40167 & -0.201666 \tabularnewline
74 & 1.9 & 2.01941 & -0.119412 \tabularnewline
75 & 1.8 & 2.03238 & -0.23238 \tabularnewline
76 & 2.1 & 2.22516 & -0.125164 \tabularnewline
77 & 1.8 & 2.20984 & -0.409838 \tabularnewline
78 & 2 & 2.30325 & -0.303255 \tabularnewline
79 & 1.7 & 1.46361 & 0.236392 \tabularnewline
80 & 2.1 & 2.46017 & -0.360171 \tabularnewline
81 & 2.1 & 1.79701 & 0.302989 \tabularnewline
82 & 2.1 & 2.50201 & -0.402011 \tabularnewline
83 & 1.8 & 1.89376 & -0.0937623 \tabularnewline
84 & 2 & 2.11712 & -0.117115 \tabularnewline
85 & 2.1 & 1.97426 & 0.125735 \tabularnewline
86 & 1.9 & 2.07303 & -0.173029 \tabularnewline
87 & 2.1 & 2.09885 & 0.00115241 \tabularnewline
88 & 1 & 1.84264 & -0.842638 \tabularnewline
89 & 2.2 & 2.25103 & -0.0510342 \tabularnewline
90 & 2.1 & 2.2784 & -0.178402 \tabularnewline
91 & 1.9 & 1.91013 & -0.0101323 \tabularnewline
92 & 2 & 1.78435 & 0.215649 \tabularnewline
93 & 1.9 & 1.88107 & 0.0189337 \tabularnewline
94 & 2 & 2.11281 & -0.112813 \tabularnewline
95 & 1.8 & 1.82167 & -0.0216713 \tabularnewline
96 & 2 & 1.82958 & 0.170417 \tabularnewline
97 & 2 & 2.35884 & -0.358844 \tabularnewline
98 & 2 & 1.78801 & 0.21199 \tabularnewline
99 & 1.8 & 1.77916 & 0.0208432 \tabularnewline
100 & 2 & 1.94946 & 0.0505353 \tabularnewline
101 & 1.1 & 1.94802 & -0.848023 \tabularnewline
102 & 1.8 & 1.70771 & 0.0922911 \tabularnewline
103 & 1.8 & 1.69424 & 0.105758 \tabularnewline
104 & 2 & 2.01739 & -0.0173856 \tabularnewline
105 & 1.9 & 1.87333 & 0.0266685 \tabularnewline
106 & 2.1 & 2.04354 & 0.0564613 \tabularnewline
107 & 1.6 & 1.86349 & -0.263493 \tabularnewline
108 & 2.2 & 2.14634 & 0.0536563 \tabularnewline
109 & 1.9 & 1.99165 & -0.0916481 \tabularnewline
110 & 2 & 2.10354 & -0.103544 \tabularnewline
111 & 2.1 & 2.05904 & 0.0409593 \tabularnewline
112 & 1.3 & 2.00636 & -0.706363 \tabularnewline
113 & 1.8 & 1.78057 & 0.0194315 \tabularnewline
114 & 1.9 & 2.14066 & -0.240661 \tabularnewline
115 & 2.1 & 2.00878 & 0.0912242 \tabularnewline
116 & 1.8 & 1.77205 & 0.0279519 \tabularnewline
117 & 0.75 & 1.51744 & -0.767443 \tabularnewline
118 & 1.5 & 1.80927 & -0.309265 \tabularnewline
119 & 3 & 2.07245 & 0.927547 \tabularnewline
120 & 2.25 & 2.07121 & 0.178787 \tabularnewline
121 & 3 & 2.76987 & 0.230131 \tabularnewline
122 & 1.5 & 1.61422 & -0.114223 \tabularnewline
123 & 3 & 2.493 & 0.507003 \tabularnewline
124 & 3 & 2.57597 & 0.424031 \tabularnewline
125 & 3 & 3.32292 & -0.322921 \tabularnewline
126 & 0.75 & 1.64963 & -0.899627 \tabularnewline
127 & 3 & 2.36119 & 0.63881 \tabularnewline
128 & 2.25 & 1.59223 & 0.657767 \tabularnewline
129 & 1.5 & 1.97776 & -0.477756 \tabularnewline
130 & 1.5 & 1.94016 & -0.440163 \tabularnewline
131 & 2.25 & 2.02604 & 0.223962 \tabularnewline
132 & 3 & 2.25467 & 0.745331 \tabularnewline
133 & 3 & 2.39543 & 0.60457 \tabularnewline
134 & 1.5 & 1.73635 & -0.236345 \tabularnewline
135 & 2.25 & 1.73931 & 0.510688 \tabularnewline
136 & 2.25 & 2.70472 & -0.454719 \tabularnewline
137 & 1.5 & 1.9861 & -0.486098 \tabularnewline
138 & 2.25 & 2.19171 & 0.0582861 \tabularnewline
139 & 1.5 & 1.74595 & -0.245948 \tabularnewline
140 & 2.25 & 2.04038 & 0.209619 \tabularnewline
141 & 2.25 & 1.89712 & 0.352881 \tabularnewline
142 & 3 & 1.64886 & 1.35114 \tabularnewline
143 & 3 & 2.53066 & 0.469338 \tabularnewline
144 & 3 & 2.44593 & 0.554069 \tabularnewline
145 & 1.5 & 1.68007 & -0.180071 \tabularnewline
146 & 3 & 1.85081 & 1.14919 \tabularnewline
147 & 3 & 2.59668 & 0.403324 \tabularnewline
148 & 2.25 & 2.0749 & 0.175099 \tabularnewline
149 & 1.5 & 2.03121 & -0.531205 \tabularnewline
150 & 2.25 & 2.30207 & -0.0520667 \tabularnewline
151 & 2.25 & 2.46478 & -0.214781 \tabularnewline
152 & 3 & 2.11593 & 0.884069 \tabularnewline
153 & 0.75 & 2.0186 & -1.2686 \tabularnewline
154 & 2.25 & 2.17807 & 0.0719285 \tabularnewline
155 & 3 & 2.33257 & 0.66743 \tabularnewline
156 & 3 & 2.08018 & 0.919821 \tabularnewline
157 & 1.5 & 2.25622 & -0.756219 \tabularnewline
158 & 2.25 & 2.37517 & -0.12517 \tabularnewline
159 & 3 & 2.10906 & 0.890937 \tabularnewline
160 & 2.25 & 2.23869 & 0.0113074 \tabularnewline
161 & 1.5 & 1.73691 & -0.236912 \tabularnewline
162 & 2.25 & 2.19427 & 0.0557319 \tabularnewline
163 & 2.25 & 2.61268 & -0.362677 \tabularnewline
164 & 1.5 & 2.08247 & -0.582472 \tabularnewline
165 & 2.25 & 2.4493 & -0.199295 \tabularnewline
166 & 1.5 & 1.93022 & -0.430217 \tabularnewline
167 & 2.25 & 2.38628 & -0.136283 \tabularnewline
168 & 3 & 1.9976 & 1.0024 \tabularnewline
169 & 3 & 2.48505 & 0.514953 \tabularnewline
170 & 3 & 1.5472 & 1.4528 \tabularnewline
171 & 3 & 2.54787 & 0.452127 \tabularnewline
172 & 1.5 & 1.56995 & -0.0699506 \tabularnewline
173 & 2.25 & 2.34493 & -0.0949291 \tabularnewline
174 & 1.5 & 1.59478 & -0.0947826 \tabularnewline
175 & 2.25 & 2.10982 & 0.140178 \tabularnewline
176 & 2.25 & 2.22142 & 0.0285827 \tabularnewline
177 & 2.25 & 2.09193 & 0.158073 \tabularnewline
178 & 3 & 2.2315 & 0.768503 \tabularnewline
179 & 1.5 & 2.18022 & -0.680218 \tabularnewline
180 & 2.25 & 2.00884 & 0.241156 \tabularnewline
181 & 2.25 & 2.00884 & 0.241156 \tabularnewline
182 & 3 & 2.20199 & 0.798009 \tabularnewline
183 & 2.25 & 2.19499 & 0.0550108 \tabularnewline
184 & 3 & 2.22048 & 0.77952 \tabularnewline
185 & 2.25 & 2.2341 & 0.0158981 \tabularnewline
186 & 1.5 & 1.69166 & -0.191663 \tabularnewline
187 & 3 & 2.4529 & 0.547098 \tabularnewline
188 & 1.5 & 2.097 & -0.597005 \tabularnewline
189 & 3 & 2.33354 & 0.666464 \tabularnewline
190 & 3 & 2.28724 & 0.712763 \tabularnewline
191 & 3 & 1.97414 & 1.02586 \tabularnewline
192 & 3 & 2.23418 & 0.765819 \tabularnewline
193 & 2.25 & 1.85841 & 0.391595 \tabularnewline
194 & 2.25 & 2.04795 & 0.202054 \tabularnewline
195 & 0.75 & 1.66691 & -0.916914 \tabularnewline
196 & 3 & 1.88981 & 1.11019 \tabularnewline
197 & 0.75 & 1.67377 & -0.923774 \tabularnewline
198 & 1.5 & 2.34762 & -0.847616 \tabularnewline
199 & 1.5 & 1.79619 & -0.29619 \tabularnewline
200 & 3 & 2.1889 & 0.811104 \tabularnewline
201 & 1.5 & 1.92051 & -0.420511 \tabularnewline
202 & 2.25 & 1.86188 & 0.388124 \tabularnewline
203 & 3 & 2.33672 & 0.663277 \tabularnewline
204 & 3 & 2.22117 & 0.778835 \tabularnewline
205 & 1.5 & 1.84382 & -0.343818 \tabularnewline
206 & 3 & 2.17019 & 0.829813 \tabularnewline
207 & 3 & 2.43254 & 0.56746 \tabularnewline
208 & 1.5 & 1.78444 & -0.28444 \tabularnewline
209 & 1.5 & 2.1774 & -0.677403 \tabularnewline
210 & 2.25 & 2.08068 & 0.169322 \tabularnewline
211 & 1.5 & 1.78346 & -0.283458 \tabularnewline
212 & 1.5 & 1.73458 & -0.234579 \tabularnewline
213 & 2.25 & 1.90309 & 0.346912 \tabularnewline
214 & 1.5 & 1.62605 & -0.126048 \tabularnewline
215 & 2.25 & 1.82761 & 0.422385 \tabularnewline
216 & 3 & 2.76098 & 0.239019 \tabularnewline
217 & 3 & 2.21259 & 0.787406 \tabularnewline
218 & 0.75 & 1.7725 & -1.0225 \tabularnewline
219 & 1.5 & 1.97442 & -0.474425 \tabularnewline
220 & 1.5 & 2.42792 & -0.92792 \tabularnewline
221 & 2.25 & 1.8892 & 0.360798 \tabularnewline
222 & 2.25 & 2.51321 & -0.263213 \tabularnewline
223 & 1.5 & 2.02173 & -0.521734 \tabularnewline
224 & 2.25 & 2.0155 & 0.234495 \tabularnewline
225 & 0.75 & 2.0286 & -1.2786 \tabularnewline
226 & 2.25 & 2.11992 & 0.130079 \tabularnewline
227 & 0.75 & 1.82231 & -1.07231 \tabularnewline
228 & 2.25 & 2.13523 & 0.114766 \tabularnewline
229 & 3 & 2.15002 & 0.849976 \tabularnewline
230 & 0.75 & 1.91578 & -1.16578 \tabularnewline
231 & 0.75 & 1.63496 & -0.884964 \tabularnewline
232 & 3 & 1.79245 & 1.20755 \tabularnewline
233 & 3 & 2.37745 & 0.622552 \tabularnewline
234 & 3 & 1.73868 & 1.26132 \tabularnewline
235 & 3 & 1.98579 & 1.01421 \tabularnewline
236 & 1.5 & 1.84962 & -0.349625 \tabularnewline
237 & 3 & 2.52243 & 0.477572 \tabularnewline
238 & 3 & 2.22777 & 0.772234 \tabularnewline
239 & 3 & 2.2328 & 0.767203 \tabularnewline
240 & 3 & 2.68715 & 0.312846 \tabularnewline
241 & 1.5 & 1.82464 & -0.324641 \tabularnewline
242 & 2.25 & 2.00368 & 0.246318 \tabularnewline
243 & 0.75 & 1.94398 & -1.19398 \tabularnewline
244 & 0.75 & 1.61179 & -0.861792 \tabularnewline
245 & 2.25 & 1.62861 & 0.621394 \tabularnewline
246 & 3 & 2.24653 & 0.753466 \tabularnewline
247 & 2.25 & 2.07916 & 0.170835 \tabularnewline
248 & 3 & 1.91108 & 1.08892 \tabularnewline
249 & 2.25 & 2.23166 & 0.0183398 \tabularnewline
250 & 3 & 2.00812 & 0.991876 \tabularnewline
251 & 1.5 & 1.91859 & -0.418585 \tabularnewline
252 & 3 & 2.53684 & 0.463159 \tabularnewline
253 & 3 & 1.86914 & 1.13086 \tabularnewline
254 & 0.75 & 1.65343 & -0.90343 \tabularnewline
255 & 1.5 & 2.14844 & -0.648443 \tabularnewline
256 & 3 & 2.61788 & 0.382119 \tabularnewline
257 & 3 & 1.83919 & 1.16081 \tabularnewline
258 & 3 & 2.3877 & 0.612299 \tabularnewline
259 & 2.25 & 1.93233 & 0.317673 \tabularnewline
260 & 2.25 & 1.78752 & 0.462479 \tabularnewline
261 & 3 & 2.19174 & 0.808264 \tabularnewline
262 & 1.5 & 2.07678 & -0.576779 \tabularnewline
263 & 2.25 & 2.23697 & 0.0130278 \tabularnewline
264 & 2.25 & 2.03021 & 0.219788 \tabularnewline
265 & 2.25 & 2.2727 & -0.022699 \tabularnewline
266 & 0.75 & 1.71693 & -0.966933 \tabularnewline
267 & 2.25 & 1.91074 & 0.339261 \tabularnewline
268 & 1.5 & 2.26205 & -0.762051 \tabularnewline
269 & 2.25 & 2.02535 & 0.224652 \tabularnewline
270 & 1.5 & 1.57547 & -0.075467 \tabularnewline
271 & 0.75 & 1.92939 & -1.17939 \tabularnewline
272 & 1.5 & 1.96264 & -0.462636 \tabularnewline
273 & 1.5 & 1.93238 & -0.432376 \tabularnewline
274 & 2.25 & 2.12204 & 0.127963 \tabularnewline
275 & 1.5 & 1.85888 & -0.358878 \tabularnewline
276 & 1.5 & 1.80156 & -0.301565 \tabularnewline
277 & 3 & 2.12559 & 0.874407 \tabularnewline
278 & 2.25 & 1.99368 & 0.256317 \tabularnewline
279 & 1.5 & 1.7851 & -0.285103 \tabularnewline
280 & 0.75 & 1.91849 & -1.16849 \tabularnewline
281 & 2.25 & 1.66341 & 0.586591 \tabularnewline
282 & 3 & 2.4021 & 0.597898 \tabularnewline
283 & 3 & 2.29889 & 0.701108 \tabularnewline
284 & 1.5 & 2.16263 & -0.662626 \tabularnewline
285 & 1.5 & 1.94865 & -0.448647 \tabularnewline
286 & 2.25 & 2.21608 & 0.0339204 \tabularnewline
287 & 0.75 & 1.48939 & -0.739392 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264028&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]2.1[/C][C]2.43545[/C][C]-0.335453[/C][/ROW]
[ROW][C]2[/C][C]1.5[/C][C]2.315[/C][C]-0.815001[/C][/ROW]
[ROW][C]3[/C][C]2[/C][C]2.08696[/C][C]-0.0869641[/C][/ROW]
[ROW][C]4[/C][C]2[/C][C]2.04311[/C][C]-0.0431076[/C][/ROW]
[ROW][C]5[/C][C]2.1[/C][C]2.46568[/C][C]-0.365678[/C][/ROW]
[ROW][C]6[/C][C]2[/C][C]1.94136[/C][C]0.0586437[/C][/ROW]
[ROW][C]7[/C][C]2.3[/C][C]2.54207[/C][C]-0.242066[/C][/ROW]
[ROW][C]8[/C][C]2.1[/C][C]2.47479[/C][C]-0.374793[/C][/ROW]
[ROW][C]9[/C][C]2.1[/C][C]2.39238[/C][C]-0.292378[/C][/ROW]
[ROW][C]10[/C][C]2.2[/C][C]2.64525[/C][C]-0.445254[/C][/ROW]
[ROW][C]11[/C][C]2.1[/C][C]2.24011[/C][C]-0.140106[/C][/ROW]
[ROW][C]12[/C][C]2.1[/C][C]2.23552[/C][C]-0.135524[/C][/ROW]
[ROW][C]13[/C][C]2.1[/C][C]2.51744[/C][C]-0.417436[/C][/ROW]
[ROW][C]14[/C][C]2[/C][C]1.9379[/C][C]0.0620981[/C][/ROW]
[ROW][C]15[/C][C]2.3[/C][C]2.728[/C][C]-0.427999[/C][/ROW]
[ROW][C]16[/C][C]1.8[/C][C]1.77368[/C][C]0.0263176[/C][/ROW]
[ROW][C]17[/C][C]2[/C][C]2.02021[/C][C]-0.0202114[/C][/ROW]
[ROW][C]18[/C][C]2.2[/C][C]2.43851[/C][C]-0.238508[/C][/ROW]
[ROW][C]19[/C][C]2[/C][C]2.07669[/C][C]-0.0766946[/C][/ROW]
[ROW][C]20[/C][C]2.1[/C][C]2.12298[/C][C]-0.0229805[/C][/ROW]
[ROW][C]21[/C][C]2[/C][C]2.29138[/C][C]-0.291384[/C][/ROW]
[ROW][C]22[/C][C]1.8[/C][C]1.9995[/C][C]-0.199497[/C][/ROW]
[ROW][C]23[/C][C]2.2[/C][C]1.95771[/C][C]0.242289[/C][/ROW]
[ROW][C]24[/C][C]2.2[/C][C]2.4387[/C][C]-0.238703[/C][/ROW]
[ROW][C]25[/C][C]1.7[/C][C]2.5964[/C][C]-0.896401[/C][/ROW]
[ROW][C]26[/C][C]2.1[/C][C]2.27116[/C][C]-0.171157[/C][/ROW]
[ROW][C]27[/C][C]2.3[/C][C]2.87736[/C][C]-0.577356[/C][/ROW]
[ROW][C]28[/C][C]2.7[/C][C]2.49916[/C][C]0.200839[/C][/ROW]
[ROW][C]29[/C][C]1.9[/C][C]2.06873[/C][C]-0.168726[/C][/ROW]
[ROW][C]30[/C][C]2[/C][C]2.37595[/C][C]-0.375949[/C][/ROW]
[ROW][C]31[/C][C]2[/C][C]2.26183[/C][C]-0.261828[/C][/ROW]
[ROW][C]32[/C][C]1.9[/C][C]2.09816[/C][C]-0.198157[/C][/ROW]
[ROW][C]33[/C][C]2[/C][C]2.22018[/C][C]-0.220178[/C][/ROW]
[ROW][C]34[/C][C]2[/C][C]2.33277[/C][C]-0.332766[/C][/ROW]
[ROW][C]35[/C][C]2[/C][C]1.98495[/C][C]0.0150507[/C][/ROW]
[ROW][C]36[/C][C]2.1[/C][C]2.28198[/C][C]-0.181983[/C][/ROW]
[ROW][C]37[/C][C]2[/C][C]2.00577[/C][C]-0.00577217[/C][/ROW]
[ROW][C]38[/C][C]1.8[/C][C]1.88464[/C][C]-0.0846399[/C][/ROW]
[ROW][C]39[/C][C]2[/C][C]2.2955[/C][C]-0.295498[/C][/ROW]
[ROW][C]40[/C][C]2.2[/C][C]1.92533[/C][C]0.274668[/C][/ROW]
[ROW][C]41[/C][C]2.2[/C][C]2.28264[/C][C]-0.0826352[/C][/ROW]
[ROW][C]42[/C][C]2.1[/C][C]2.29427[/C][C]-0.194266[/C][/ROW]
[ROW][C]43[/C][C]1.8[/C][C]1.86303[/C][C]-0.063029[/C][/ROW]
[ROW][C]44[/C][C]1.9[/C][C]2.06802[/C][C]-0.168025[/C][/ROW]
[ROW][C]45[/C][C]2.1[/C][C]2.27916[/C][C]-0.179156[/C][/ROW]
[ROW][C]46[/C][C]2[/C][C]2.18342[/C][C]-0.183423[/C][/ROW]
[ROW][C]47[/C][C]1.9[/C][C]1.78538[/C][C]0.114619[/C][/ROW]
[ROW][C]48[/C][C]2.2[/C][C]2.38042[/C][C]-0.180423[/C][/ROW]
[ROW][C]49[/C][C]2[/C][C]2.23746[/C][C]-0.237457[/C][/ROW]
[ROW][C]50[/C][C]2[/C][C]2.03338[/C][C]-0.0333791[/C][/ROW]
[ROW][C]51[/C][C]1.7[/C][C]2.27735[/C][C]-0.577346[/C][/ROW]
[ROW][C]52[/C][C]2[/C][C]1.58703[/C][C]0.412974[/C][/ROW]
[ROW][C]53[/C][C]2.2[/C][C]1.99138[/C][C]0.208619[/C][/ROW]
[ROW][C]54[/C][C]1.7[/C][C]1.7033[/C][C]-0.00330293[/C][/ROW]
[ROW][C]55[/C][C]2[/C][C]1.99882[/C][C]0.00118077[/C][/ROW]
[ROW][C]56[/C][C]2.2[/C][C]2.0409[/C][C]0.159098[/C][/ROW]
[ROW][C]57[/C][C]2[/C][C]2.17177[/C][C]-0.171772[/C][/ROW]
[ROW][C]58[/C][C]1.9[/C][C]1.93205[/C][C]-0.0320548[/C][/ROW]
[ROW][C]59[/C][C]2[/C][C]1.96602[/C][C]0.0339761[/C][/ROW]
[ROW][C]60[/C][C]2[/C][C]2.18727[/C][C]-0.187272[/C][/ROW]
[ROW][C]61[/C][C]1.6[/C][C]1.64724[/C][C]-0.0472443[/C][/ROW]
[ROW][C]62[/C][C]2.1[/C][C]1.94918[/C][C]0.150815[/C][/ROW]
[ROW][C]63[/C][C]2.1[/C][C]2.49196[/C][C]-0.391956[/C][/ROW]
[ROW][C]64[/C][C]2[/C][C]1.9514[/C][C]0.0485958[/C][/ROW]
[ROW][C]65[/C][C]1.9[/C][C]2.02685[/C][C]-0.126854[/C][/ROW]
[ROW][C]66[/C][C]2.2[/C][C]2.52764[/C][C]-0.327635[/C][/ROW]
[ROW][C]67[/C][C]2.1[/C][C]2.27316[/C][C]-0.173164[/C][/ROW]
[ROW][C]68[/C][C]1.8[/C][C]1.72011[/C][C]0.0798875[/C][/ROW]
[ROW][C]69[/C][C]2.3[/C][C]2.63007[/C][C]-0.330069[/C][/ROW]
[ROW][C]70[/C][C]2.3[/C][C]3.01067[/C][C]-0.710666[/C][/ROW]
[ROW][C]71[/C][C]2.2[/C][C]2.10866[/C][C]0.0913373[/C][/ROW]
[ROW][C]72[/C][C]2.1[/C][C]1.99158[/C][C]0.108421[/C][/ROW]
[ROW][C]73[/C][C]2.2[/C][C]2.40167[/C][C]-0.201666[/C][/ROW]
[ROW][C]74[/C][C]1.9[/C][C]2.01941[/C][C]-0.119412[/C][/ROW]
[ROW][C]75[/C][C]1.8[/C][C]2.03238[/C][C]-0.23238[/C][/ROW]
[ROW][C]76[/C][C]2.1[/C][C]2.22516[/C][C]-0.125164[/C][/ROW]
[ROW][C]77[/C][C]1.8[/C][C]2.20984[/C][C]-0.409838[/C][/ROW]
[ROW][C]78[/C][C]2[/C][C]2.30325[/C][C]-0.303255[/C][/ROW]
[ROW][C]79[/C][C]1.7[/C][C]1.46361[/C][C]0.236392[/C][/ROW]
[ROW][C]80[/C][C]2.1[/C][C]2.46017[/C][C]-0.360171[/C][/ROW]
[ROW][C]81[/C][C]2.1[/C][C]1.79701[/C][C]0.302989[/C][/ROW]
[ROW][C]82[/C][C]2.1[/C][C]2.50201[/C][C]-0.402011[/C][/ROW]
[ROW][C]83[/C][C]1.8[/C][C]1.89376[/C][C]-0.0937623[/C][/ROW]
[ROW][C]84[/C][C]2[/C][C]2.11712[/C][C]-0.117115[/C][/ROW]
[ROW][C]85[/C][C]2.1[/C][C]1.97426[/C][C]0.125735[/C][/ROW]
[ROW][C]86[/C][C]1.9[/C][C]2.07303[/C][C]-0.173029[/C][/ROW]
[ROW][C]87[/C][C]2.1[/C][C]2.09885[/C][C]0.00115241[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]1.84264[/C][C]-0.842638[/C][/ROW]
[ROW][C]89[/C][C]2.2[/C][C]2.25103[/C][C]-0.0510342[/C][/ROW]
[ROW][C]90[/C][C]2.1[/C][C]2.2784[/C][C]-0.178402[/C][/ROW]
[ROW][C]91[/C][C]1.9[/C][C]1.91013[/C][C]-0.0101323[/C][/ROW]
[ROW][C]92[/C][C]2[/C][C]1.78435[/C][C]0.215649[/C][/ROW]
[ROW][C]93[/C][C]1.9[/C][C]1.88107[/C][C]0.0189337[/C][/ROW]
[ROW][C]94[/C][C]2[/C][C]2.11281[/C][C]-0.112813[/C][/ROW]
[ROW][C]95[/C][C]1.8[/C][C]1.82167[/C][C]-0.0216713[/C][/ROW]
[ROW][C]96[/C][C]2[/C][C]1.82958[/C][C]0.170417[/C][/ROW]
[ROW][C]97[/C][C]2[/C][C]2.35884[/C][C]-0.358844[/C][/ROW]
[ROW][C]98[/C][C]2[/C][C]1.78801[/C][C]0.21199[/C][/ROW]
[ROW][C]99[/C][C]1.8[/C][C]1.77916[/C][C]0.0208432[/C][/ROW]
[ROW][C]100[/C][C]2[/C][C]1.94946[/C][C]0.0505353[/C][/ROW]
[ROW][C]101[/C][C]1.1[/C][C]1.94802[/C][C]-0.848023[/C][/ROW]
[ROW][C]102[/C][C]1.8[/C][C]1.70771[/C][C]0.0922911[/C][/ROW]
[ROW][C]103[/C][C]1.8[/C][C]1.69424[/C][C]0.105758[/C][/ROW]
[ROW][C]104[/C][C]2[/C][C]2.01739[/C][C]-0.0173856[/C][/ROW]
[ROW][C]105[/C][C]1.9[/C][C]1.87333[/C][C]0.0266685[/C][/ROW]
[ROW][C]106[/C][C]2.1[/C][C]2.04354[/C][C]0.0564613[/C][/ROW]
[ROW][C]107[/C][C]1.6[/C][C]1.86349[/C][C]-0.263493[/C][/ROW]
[ROW][C]108[/C][C]2.2[/C][C]2.14634[/C][C]0.0536563[/C][/ROW]
[ROW][C]109[/C][C]1.9[/C][C]1.99165[/C][C]-0.0916481[/C][/ROW]
[ROW][C]110[/C][C]2[/C][C]2.10354[/C][C]-0.103544[/C][/ROW]
[ROW][C]111[/C][C]2.1[/C][C]2.05904[/C][C]0.0409593[/C][/ROW]
[ROW][C]112[/C][C]1.3[/C][C]2.00636[/C][C]-0.706363[/C][/ROW]
[ROW][C]113[/C][C]1.8[/C][C]1.78057[/C][C]0.0194315[/C][/ROW]
[ROW][C]114[/C][C]1.9[/C][C]2.14066[/C][C]-0.240661[/C][/ROW]
[ROW][C]115[/C][C]2.1[/C][C]2.00878[/C][C]0.0912242[/C][/ROW]
[ROW][C]116[/C][C]1.8[/C][C]1.77205[/C][C]0.0279519[/C][/ROW]
[ROW][C]117[/C][C]0.75[/C][C]1.51744[/C][C]-0.767443[/C][/ROW]
[ROW][C]118[/C][C]1.5[/C][C]1.80927[/C][C]-0.309265[/C][/ROW]
[ROW][C]119[/C][C]3[/C][C]2.07245[/C][C]0.927547[/C][/ROW]
[ROW][C]120[/C][C]2.25[/C][C]2.07121[/C][C]0.178787[/C][/ROW]
[ROW][C]121[/C][C]3[/C][C]2.76987[/C][C]0.230131[/C][/ROW]
[ROW][C]122[/C][C]1.5[/C][C]1.61422[/C][C]-0.114223[/C][/ROW]
[ROW][C]123[/C][C]3[/C][C]2.493[/C][C]0.507003[/C][/ROW]
[ROW][C]124[/C][C]3[/C][C]2.57597[/C][C]0.424031[/C][/ROW]
[ROW][C]125[/C][C]3[/C][C]3.32292[/C][C]-0.322921[/C][/ROW]
[ROW][C]126[/C][C]0.75[/C][C]1.64963[/C][C]-0.899627[/C][/ROW]
[ROW][C]127[/C][C]3[/C][C]2.36119[/C][C]0.63881[/C][/ROW]
[ROW][C]128[/C][C]2.25[/C][C]1.59223[/C][C]0.657767[/C][/ROW]
[ROW][C]129[/C][C]1.5[/C][C]1.97776[/C][C]-0.477756[/C][/ROW]
[ROW][C]130[/C][C]1.5[/C][C]1.94016[/C][C]-0.440163[/C][/ROW]
[ROW][C]131[/C][C]2.25[/C][C]2.02604[/C][C]0.223962[/C][/ROW]
[ROW][C]132[/C][C]3[/C][C]2.25467[/C][C]0.745331[/C][/ROW]
[ROW][C]133[/C][C]3[/C][C]2.39543[/C][C]0.60457[/C][/ROW]
[ROW][C]134[/C][C]1.5[/C][C]1.73635[/C][C]-0.236345[/C][/ROW]
[ROW][C]135[/C][C]2.25[/C][C]1.73931[/C][C]0.510688[/C][/ROW]
[ROW][C]136[/C][C]2.25[/C][C]2.70472[/C][C]-0.454719[/C][/ROW]
[ROW][C]137[/C][C]1.5[/C][C]1.9861[/C][C]-0.486098[/C][/ROW]
[ROW][C]138[/C][C]2.25[/C][C]2.19171[/C][C]0.0582861[/C][/ROW]
[ROW][C]139[/C][C]1.5[/C][C]1.74595[/C][C]-0.245948[/C][/ROW]
[ROW][C]140[/C][C]2.25[/C][C]2.04038[/C][C]0.209619[/C][/ROW]
[ROW][C]141[/C][C]2.25[/C][C]1.89712[/C][C]0.352881[/C][/ROW]
[ROW][C]142[/C][C]3[/C][C]1.64886[/C][C]1.35114[/C][/ROW]
[ROW][C]143[/C][C]3[/C][C]2.53066[/C][C]0.469338[/C][/ROW]
[ROW][C]144[/C][C]3[/C][C]2.44593[/C][C]0.554069[/C][/ROW]
[ROW][C]145[/C][C]1.5[/C][C]1.68007[/C][C]-0.180071[/C][/ROW]
[ROW][C]146[/C][C]3[/C][C]1.85081[/C][C]1.14919[/C][/ROW]
[ROW][C]147[/C][C]3[/C][C]2.59668[/C][C]0.403324[/C][/ROW]
[ROW][C]148[/C][C]2.25[/C][C]2.0749[/C][C]0.175099[/C][/ROW]
[ROW][C]149[/C][C]1.5[/C][C]2.03121[/C][C]-0.531205[/C][/ROW]
[ROW][C]150[/C][C]2.25[/C][C]2.30207[/C][C]-0.0520667[/C][/ROW]
[ROW][C]151[/C][C]2.25[/C][C]2.46478[/C][C]-0.214781[/C][/ROW]
[ROW][C]152[/C][C]3[/C][C]2.11593[/C][C]0.884069[/C][/ROW]
[ROW][C]153[/C][C]0.75[/C][C]2.0186[/C][C]-1.2686[/C][/ROW]
[ROW][C]154[/C][C]2.25[/C][C]2.17807[/C][C]0.0719285[/C][/ROW]
[ROW][C]155[/C][C]3[/C][C]2.33257[/C][C]0.66743[/C][/ROW]
[ROW][C]156[/C][C]3[/C][C]2.08018[/C][C]0.919821[/C][/ROW]
[ROW][C]157[/C][C]1.5[/C][C]2.25622[/C][C]-0.756219[/C][/ROW]
[ROW][C]158[/C][C]2.25[/C][C]2.37517[/C][C]-0.12517[/C][/ROW]
[ROW][C]159[/C][C]3[/C][C]2.10906[/C][C]0.890937[/C][/ROW]
[ROW][C]160[/C][C]2.25[/C][C]2.23869[/C][C]0.0113074[/C][/ROW]
[ROW][C]161[/C][C]1.5[/C][C]1.73691[/C][C]-0.236912[/C][/ROW]
[ROW][C]162[/C][C]2.25[/C][C]2.19427[/C][C]0.0557319[/C][/ROW]
[ROW][C]163[/C][C]2.25[/C][C]2.61268[/C][C]-0.362677[/C][/ROW]
[ROW][C]164[/C][C]1.5[/C][C]2.08247[/C][C]-0.582472[/C][/ROW]
[ROW][C]165[/C][C]2.25[/C][C]2.4493[/C][C]-0.199295[/C][/ROW]
[ROW][C]166[/C][C]1.5[/C][C]1.93022[/C][C]-0.430217[/C][/ROW]
[ROW][C]167[/C][C]2.25[/C][C]2.38628[/C][C]-0.136283[/C][/ROW]
[ROW][C]168[/C][C]3[/C][C]1.9976[/C][C]1.0024[/C][/ROW]
[ROW][C]169[/C][C]3[/C][C]2.48505[/C][C]0.514953[/C][/ROW]
[ROW][C]170[/C][C]3[/C][C]1.5472[/C][C]1.4528[/C][/ROW]
[ROW][C]171[/C][C]3[/C][C]2.54787[/C][C]0.452127[/C][/ROW]
[ROW][C]172[/C][C]1.5[/C][C]1.56995[/C][C]-0.0699506[/C][/ROW]
[ROW][C]173[/C][C]2.25[/C][C]2.34493[/C][C]-0.0949291[/C][/ROW]
[ROW][C]174[/C][C]1.5[/C][C]1.59478[/C][C]-0.0947826[/C][/ROW]
[ROW][C]175[/C][C]2.25[/C][C]2.10982[/C][C]0.140178[/C][/ROW]
[ROW][C]176[/C][C]2.25[/C][C]2.22142[/C][C]0.0285827[/C][/ROW]
[ROW][C]177[/C][C]2.25[/C][C]2.09193[/C][C]0.158073[/C][/ROW]
[ROW][C]178[/C][C]3[/C][C]2.2315[/C][C]0.768503[/C][/ROW]
[ROW][C]179[/C][C]1.5[/C][C]2.18022[/C][C]-0.680218[/C][/ROW]
[ROW][C]180[/C][C]2.25[/C][C]2.00884[/C][C]0.241156[/C][/ROW]
[ROW][C]181[/C][C]2.25[/C][C]2.00884[/C][C]0.241156[/C][/ROW]
[ROW][C]182[/C][C]3[/C][C]2.20199[/C][C]0.798009[/C][/ROW]
[ROW][C]183[/C][C]2.25[/C][C]2.19499[/C][C]0.0550108[/C][/ROW]
[ROW][C]184[/C][C]3[/C][C]2.22048[/C][C]0.77952[/C][/ROW]
[ROW][C]185[/C][C]2.25[/C][C]2.2341[/C][C]0.0158981[/C][/ROW]
[ROW][C]186[/C][C]1.5[/C][C]1.69166[/C][C]-0.191663[/C][/ROW]
[ROW][C]187[/C][C]3[/C][C]2.4529[/C][C]0.547098[/C][/ROW]
[ROW][C]188[/C][C]1.5[/C][C]2.097[/C][C]-0.597005[/C][/ROW]
[ROW][C]189[/C][C]3[/C][C]2.33354[/C][C]0.666464[/C][/ROW]
[ROW][C]190[/C][C]3[/C][C]2.28724[/C][C]0.712763[/C][/ROW]
[ROW][C]191[/C][C]3[/C][C]1.97414[/C][C]1.02586[/C][/ROW]
[ROW][C]192[/C][C]3[/C][C]2.23418[/C][C]0.765819[/C][/ROW]
[ROW][C]193[/C][C]2.25[/C][C]1.85841[/C][C]0.391595[/C][/ROW]
[ROW][C]194[/C][C]2.25[/C][C]2.04795[/C][C]0.202054[/C][/ROW]
[ROW][C]195[/C][C]0.75[/C][C]1.66691[/C][C]-0.916914[/C][/ROW]
[ROW][C]196[/C][C]3[/C][C]1.88981[/C][C]1.11019[/C][/ROW]
[ROW][C]197[/C][C]0.75[/C][C]1.67377[/C][C]-0.923774[/C][/ROW]
[ROW][C]198[/C][C]1.5[/C][C]2.34762[/C][C]-0.847616[/C][/ROW]
[ROW][C]199[/C][C]1.5[/C][C]1.79619[/C][C]-0.29619[/C][/ROW]
[ROW][C]200[/C][C]3[/C][C]2.1889[/C][C]0.811104[/C][/ROW]
[ROW][C]201[/C][C]1.5[/C][C]1.92051[/C][C]-0.420511[/C][/ROW]
[ROW][C]202[/C][C]2.25[/C][C]1.86188[/C][C]0.388124[/C][/ROW]
[ROW][C]203[/C][C]3[/C][C]2.33672[/C][C]0.663277[/C][/ROW]
[ROW][C]204[/C][C]3[/C][C]2.22117[/C][C]0.778835[/C][/ROW]
[ROW][C]205[/C][C]1.5[/C][C]1.84382[/C][C]-0.343818[/C][/ROW]
[ROW][C]206[/C][C]3[/C][C]2.17019[/C][C]0.829813[/C][/ROW]
[ROW][C]207[/C][C]3[/C][C]2.43254[/C][C]0.56746[/C][/ROW]
[ROW][C]208[/C][C]1.5[/C][C]1.78444[/C][C]-0.28444[/C][/ROW]
[ROW][C]209[/C][C]1.5[/C][C]2.1774[/C][C]-0.677403[/C][/ROW]
[ROW][C]210[/C][C]2.25[/C][C]2.08068[/C][C]0.169322[/C][/ROW]
[ROW][C]211[/C][C]1.5[/C][C]1.78346[/C][C]-0.283458[/C][/ROW]
[ROW][C]212[/C][C]1.5[/C][C]1.73458[/C][C]-0.234579[/C][/ROW]
[ROW][C]213[/C][C]2.25[/C][C]1.90309[/C][C]0.346912[/C][/ROW]
[ROW][C]214[/C][C]1.5[/C][C]1.62605[/C][C]-0.126048[/C][/ROW]
[ROW][C]215[/C][C]2.25[/C][C]1.82761[/C][C]0.422385[/C][/ROW]
[ROW][C]216[/C][C]3[/C][C]2.76098[/C][C]0.239019[/C][/ROW]
[ROW][C]217[/C][C]3[/C][C]2.21259[/C][C]0.787406[/C][/ROW]
[ROW][C]218[/C][C]0.75[/C][C]1.7725[/C][C]-1.0225[/C][/ROW]
[ROW][C]219[/C][C]1.5[/C][C]1.97442[/C][C]-0.474425[/C][/ROW]
[ROW][C]220[/C][C]1.5[/C][C]2.42792[/C][C]-0.92792[/C][/ROW]
[ROW][C]221[/C][C]2.25[/C][C]1.8892[/C][C]0.360798[/C][/ROW]
[ROW][C]222[/C][C]2.25[/C][C]2.51321[/C][C]-0.263213[/C][/ROW]
[ROW][C]223[/C][C]1.5[/C][C]2.02173[/C][C]-0.521734[/C][/ROW]
[ROW][C]224[/C][C]2.25[/C][C]2.0155[/C][C]0.234495[/C][/ROW]
[ROW][C]225[/C][C]0.75[/C][C]2.0286[/C][C]-1.2786[/C][/ROW]
[ROW][C]226[/C][C]2.25[/C][C]2.11992[/C][C]0.130079[/C][/ROW]
[ROW][C]227[/C][C]0.75[/C][C]1.82231[/C][C]-1.07231[/C][/ROW]
[ROW][C]228[/C][C]2.25[/C][C]2.13523[/C][C]0.114766[/C][/ROW]
[ROW][C]229[/C][C]3[/C][C]2.15002[/C][C]0.849976[/C][/ROW]
[ROW][C]230[/C][C]0.75[/C][C]1.91578[/C][C]-1.16578[/C][/ROW]
[ROW][C]231[/C][C]0.75[/C][C]1.63496[/C][C]-0.884964[/C][/ROW]
[ROW][C]232[/C][C]3[/C][C]1.79245[/C][C]1.20755[/C][/ROW]
[ROW][C]233[/C][C]3[/C][C]2.37745[/C][C]0.622552[/C][/ROW]
[ROW][C]234[/C][C]3[/C][C]1.73868[/C][C]1.26132[/C][/ROW]
[ROW][C]235[/C][C]3[/C][C]1.98579[/C][C]1.01421[/C][/ROW]
[ROW][C]236[/C][C]1.5[/C][C]1.84962[/C][C]-0.349625[/C][/ROW]
[ROW][C]237[/C][C]3[/C][C]2.52243[/C][C]0.477572[/C][/ROW]
[ROW][C]238[/C][C]3[/C][C]2.22777[/C][C]0.772234[/C][/ROW]
[ROW][C]239[/C][C]3[/C][C]2.2328[/C][C]0.767203[/C][/ROW]
[ROW][C]240[/C][C]3[/C][C]2.68715[/C][C]0.312846[/C][/ROW]
[ROW][C]241[/C][C]1.5[/C][C]1.82464[/C][C]-0.324641[/C][/ROW]
[ROW][C]242[/C][C]2.25[/C][C]2.00368[/C][C]0.246318[/C][/ROW]
[ROW][C]243[/C][C]0.75[/C][C]1.94398[/C][C]-1.19398[/C][/ROW]
[ROW][C]244[/C][C]0.75[/C][C]1.61179[/C][C]-0.861792[/C][/ROW]
[ROW][C]245[/C][C]2.25[/C][C]1.62861[/C][C]0.621394[/C][/ROW]
[ROW][C]246[/C][C]3[/C][C]2.24653[/C][C]0.753466[/C][/ROW]
[ROW][C]247[/C][C]2.25[/C][C]2.07916[/C][C]0.170835[/C][/ROW]
[ROW][C]248[/C][C]3[/C][C]1.91108[/C][C]1.08892[/C][/ROW]
[ROW][C]249[/C][C]2.25[/C][C]2.23166[/C][C]0.0183398[/C][/ROW]
[ROW][C]250[/C][C]3[/C][C]2.00812[/C][C]0.991876[/C][/ROW]
[ROW][C]251[/C][C]1.5[/C][C]1.91859[/C][C]-0.418585[/C][/ROW]
[ROW][C]252[/C][C]3[/C][C]2.53684[/C][C]0.463159[/C][/ROW]
[ROW][C]253[/C][C]3[/C][C]1.86914[/C][C]1.13086[/C][/ROW]
[ROW][C]254[/C][C]0.75[/C][C]1.65343[/C][C]-0.90343[/C][/ROW]
[ROW][C]255[/C][C]1.5[/C][C]2.14844[/C][C]-0.648443[/C][/ROW]
[ROW][C]256[/C][C]3[/C][C]2.61788[/C][C]0.382119[/C][/ROW]
[ROW][C]257[/C][C]3[/C][C]1.83919[/C][C]1.16081[/C][/ROW]
[ROW][C]258[/C][C]3[/C][C]2.3877[/C][C]0.612299[/C][/ROW]
[ROW][C]259[/C][C]2.25[/C][C]1.93233[/C][C]0.317673[/C][/ROW]
[ROW][C]260[/C][C]2.25[/C][C]1.78752[/C][C]0.462479[/C][/ROW]
[ROW][C]261[/C][C]3[/C][C]2.19174[/C][C]0.808264[/C][/ROW]
[ROW][C]262[/C][C]1.5[/C][C]2.07678[/C][C]-0.576779[/C][/ROW]
[ROW][C]263[/C][C]2.25[/C][C]2.23697[/C][C]0.0130278[/C][/ROW]
[ROW][C]264[/C][C]2.25[/C][C]2.03021[/C][C]0.219788[/C][/ROW]
[ROW][C]265[/C][C]2.25[/C][C]2.2727[/C][C]-0.022699[/C][/ROW]
[ROW][C]266[/C][C]0.75[/C][C]1.71693[/C][C]-0.966933[/C][/ROW]
[ROW][C]267[/C][C]2.25[/C][C]1.91074[/C][C]0.339261[/C][/ROW]
[ROW][C]268[/C][C]1.5[/C][C]2.26205[/C][C]-0.762051[/C][/ROW]
[ROW][C]269[/C][C]2.25[/C][C]2.02535[/C][C]0.224652[/C][/ROW]
[ROW][C]270[/C][C]1.5[/C][C]1.57547[/C][C]-0.075467[/C][/ROW]
[ROW][C]271[/C][C]0.75[/C][C]1.92939[/C][C]-1.17939[/C][/ROW]
[ROW][C]272[/C][C]1.5[/C][C]1.96264[/C][C]-0.462636[/C][/ROW]
[ROW][C]273[/C][C]1.5[/C][C]1.93238[/C][C]-0.432376[/C][/ROW]
[ROW][C]274[/C][C]2.25[/C][C]2.12204[/C][C]0.127963[/C][/ROW]
[ROW][C]275[/C][C]1.5[/C][C]1.85888[/C][C]-0.358878[/C][/ROW]
[ROW][C]276[/C][C]1.5[/C][C]1.80156[/C][C]-0.301565[/C][/ROW]
[ROW][C]277[/C][C]3[/C][C]2.12559[/C][C]0.874407[/C][/ROW]
[ROW][C]278[/C][C]2.25[/C][C]1.99368[/C][C]0.256317[/C][/ROW]
[ROW][C]279[/C][C]1.5[/C][C]1.7851[/C][C]-0.285103[/C][/ROW]
[ROW][C]280[/C][C]0.75[/C][C]1.91849[/C][C]-1.16849[/C][/ROW]
[ROW][C]281[/C][C]2.25[/C][C]1.66341[/C][C]0.586591[/C][/ROW]
[ROW][C]282[/C][C]3[/C][C]2.4021[/C][C]0.597898[/C][/ROW]
[ROW][C]283[/C][C]3[/C][C]2.29889[/C][C]0.701108[/C][/ROW]
[ROW][C]284[/C][C]1.5[/C][C]2.16263[/C][C]-0.662626[/C][/ROW]
[ROW][C]285[/C][C]1.5[/C][C]1.94865[/C][C]-0.448647[/C][/ROW]
[ROW][C]286[/C][C]2.25[/C][C]2.21608[/C][C]0.0339204[/C][/ROW]
[ROW][C]287[/C][C]0.75[/C][C]1.48939[/C][C]-0.739392[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264028&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264028&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
12.12.43545-0.335453
21.52.315-0.815001
322.08696-0.0869641
422.04311-0.0431076
52.12.46568-0.365678
621.941360.0586437
72.32.54207-0.242066
82.12.47479-0.374793
92.12.39238-0.292378
102.22.64525-0.445254
112.12.24011-0.140106
122.12.23552-0.135524
132.12.51744-0.417436
1421.93790.0620981
152.32.728-0.427999
161.81.773680.0263176
1722.02021-0.0202114
182.22.43851-0.238508
1922.07669-0.0766946
202.12.12298-0.0229805
2122.29138-0.291384
221.81.9995-0.199497
232.21.957710.242289
242.22.4387-0.238703
251.72.5964-0.896401
262.12.27116-0.171157
272.32.87736-0.577356
282.72.499160.200839
291.92.06873-0.168726
3022.37595-0.375949
3122.26183-0.261828
321.92.09816-0.198157
3322.22018-0.220178
3422.33277-0.332766
3521.984950.0150507
362.12.28198-0.181983
3722.00577-0.00577217
381.81.88464-0.0846399
3922.2955-0.295498
402.21.925330.274668
412.22.28264-0.0826352
422.12.29427-0.194266
431.81.86303-0.063029
441.92.06802-0.168025
452.12.27916-0.179156
4622.18342-0.183423
471.91.785380.114619
482.22.38042-0.180423
4922.23746-0.237457
5022.03338-0.0333791
511.72.27735-0.577346
5221.587030.412974
532.21.991380.208619
541.71.7033-0.00330293
5521.998820.00118077
562.22.04090.159098
5722.17177-0.171772
581.91.93205-0.0320548
5921.966020.0339761
6022.18727-0.187272
611.61.64724-0.0472443
622.11.949180.150815
632.12.49196-0.391956
6421.95140.0485958
651.92.02685-0.126854
662.22.52764-0.327635
672.12.27316-0.173164
681.81.720110.0798875
692.32.63007-0.330069
702.33.01067-0.710666
712.22.108660.0913373
722.11.991580.108421
732.22.40167-0.201666
741.92.01941-0.119412
751.82.03238-0.23238
762.12.22516-0.125164
771.82.20984-0.409838
7822.30325-0.303255
791.71.463610.236392
802.12.46017-0.360171
812.11.797010.302989
822.12.50201-0.402011
831.81.89376-0.0937623
8422.11712-0.117115
852.11.974260.125735
861.92.07303-0.173029
872.12.098850.00115241
8811.84264-0.842638
892.22.25103-0.0510342
902.12.2784-0.178402
911.91.91013-0.0101323
9221.784350.215649
931.91.881070.0189337
9422.11281-0.112813
951.81.82167-0.0216713
9621.829580.170417
9722.35884-0.358844
9821.788010.21199
991.81.779160.0208432
10021.949460.0505353
1011.11.94802-0.848023
1021.81.707710.0922911
1031.81.694240.105758
10422.01739-0.0173856
1051.91.873330.0266685
1062.12.043540.0564613
1071.61.86349-0.263493
1082.22.146340.0536563
1091.91.99165-0.0916481
11022.10354-0.103544
1112.12.059040.0409593
1121.32.00636-0.706363
1131.81.780570.0194315
1141.92.14066-0.240661
1152.12.008780.0912242
1161.81.772050.0279519
1170.751.51744-0.767443
1181.51.80927-0.309265
11932.072450.927547
1202.252.071210.178787
12132.769870.230131
1221.51.61422-0.114223
12332.4930.507003
12432.575970.424031
12533.32292-0.322921
1260.751.64963-0.899627
12732.361190.63881
1282.251.592230.657767
1291.51.97776-0.477756
1301.51.94016-0.440163
1312.252.026040.223962
13232.254670.745331
13332.395430.60457
1341.51.73635-0.236345
1352.251.739310.510688
1362.252.70472-0.454719
1371.51.9861-0.486098
1382.252.191710.0582861
1391.51.74595-0.245948
1402.252.040380.209619
1412.251.897120.352881
14231.648861.35114
14332.530660.469338
14432.445930.554069
1451.51.68007-0.180071
14631.850811.14919
14732.596680.403324
1482.252.07490.175099
1491.52.03121-0.531205
1502.252.30207-0.0520667
1512.252.46478-0.214781
15232.115930.884069
1530.752.0186-1.2686
1542.252.178070.0719285
15532.332570.66743
15632.080180.919821
1571.52.25622-0.756219
1582.252.37517-0.12517
15932.109060.890937
1602.252.238690.0113074
1611.51.73691-0.236912
1622.252.194270.0557319
1632.252.61268-0.362677
1641.52.08247-0.582472
1652.252.4493-0.199295
1661.51.93022-0.430217
1672.252.38628-0.136283
16831.99761.0024
16932.485050.514953
17031.54721.4528
17132.547870.452127
1721.51.56995-0.0699506
1732.252.34493-0.0949291
1741.51.59478-0.0947826
1752.252.109820.140178
1762.252.221420.0285827
1772.252.091930.158073
17832.23150.768503
1791.52.18022-0.680218
1802.252.008840.241156
1812.252.008840.241156
18232.201990.798009
1832.252.194990.0550108
18432.220480.77952
1852.252.23410.0158981
1861.51.69166-0.191663
18732.45290.547098
1881.52.097-0.597005
18932.333540.666464
19032.287240.712763
19131.974141.02586
19232.234180.765819
1932.251.858410.391595
1942.252.047950.202054
1950.751.66691-0.916914
19631.889811.11019
1970.751.67377-0.923774
1981.52.34762-0.847616
1991.51.79619-0.29619
20032.18890.811104
2011.51.92051-0.420511
2022.251.861880.388124
20332.336720.663277
20432.221170.778835
2051.51.84382-0.343818
20632.170190.829813
20732.432540.56746
2081.51.78444-0.28444
2091.52.1774-0.677403
2102.252.080680.169322
2111.51.78346-0.283458
2121.51.73458-0.234579
2132.251.903090.346912
2141.51.62605-0.126048
2152.251.827610.422385
21632.760980.239019
21732.212590.787406
2180.751.7725-1.0225
2191.51.97442-0.474425
2201.52.42792-0.92792
2212.251.88920.360798
2222.252.51321-0.263213
2231.52.02173-0.521734
2242.252.01550.234495
2250.752.0286-1.2786
2262.252.119920.130079
2270.751.82231-1.07231
2282.252.135230.114766
22932.150020.849976
2300.751.91578-1.16578
2310.751.63496-0.884964
23231.792451.20755
23332.377450.622552
23431.738681.26132
23531.985791.01421
2361.51.84962-0.349625
23732.522430.477572
23832.227770.772234
23932.23280.767203
24032.687150.312846
2411.51.82464-0.324641
2422.252.003680.246318
2430.751.94398-1.19398
2440.751.61179-0.861792
2452.251.628610.621394
24632.246530.753466
2472.252.079160.170835
24831.911081.08892
2492.252.231660.0183398
25032.008120.991876
2511.51.91859-0.418585
25232.536840.463159
25331.869141.13086
2540.751.65343-0.90343
2551.52.14844-0.648443
25632.617880.382119
25731.839191.16081
25832.38770.612299
2592.251.932330.317673
2602.251.787520.462479
26132.191740.808264
2621.52.07678-0.576779
2632.252.236970.0130278
2642.252.030210.219788
2652.252.2727-0.022699
2660.751.71693-0.966933
2672.251.910740.339261
2681.52.26205-0.762051
2692.252.025350.224652
2701.51.57547-0.075467
2710.751.92939-1.17939
2721.51.96264-0.462636
2731.51.93238-0.432376
2742.252.122040.127963
2751.51.85888-0.358878
2761.51.80156-0.301565
27732.125590.874407
2782.251.993680.256317
2791.51.7851-0.285103
2800.751.91849-1.16849
2812.251.663410.586591
28232.40210.597898
28332.298890.701108
2841.52.16263-0.662626
2851.51.94865-0.448647
2862.252.216080.0339204
2870.751.48939-0.739392






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.001904770.003809550.998095
100.01043660.02087320.989563
110.002426570.004853130.997573
120.001436150.00287230.998564
130.0008808870.001761770.999119
140.0002428060.0004856120.999757
150.000164920.000329840.999835
164.52746e-059.05492e-050.999955
171.13944e-052.27889e-050.999989
182.77687e-065.55374e-060.999997
199.6302e-071.92604e-060.999999
202.68242e-075.36483e-071
216.4994e-081.29988e-071
227.46548e-081.4931e-071
231.47154e-072.94308e-071
245.9399e-081.18798e-071
251.07543e-062.15086e-060.999999
263.91444e-077.82889e-071
271.34705e-072.69409e-071
281.46701e-062.93401e-060.999999
295.43258e-071.08652e-060.999999
302.60395e-075.20791e-071
319.48048e-081.8961e-071
323.33166e-086.66332e-081
331.15652e-082.31305e-081
345.17063e-091.03413e-081
351.73343e-093.46686e-091
365.77851e-101.1557e-091
371.85887e-103.71775e-101
387.81608e-111.56322e-101
392.59897e-115.19795e-111
402.10314e-114.20627e-111
417.46919e-121.49384e-111
422.44995e-124.8999e-121
431.10605e-122.21211e-121
444.42105e-138.8421e-131
451.36537e-132.73073e-131
464.4299e-148.8598e-141
471.3495e-142.699e-141
484.85047e-159.70095e-151
491.445e-152.89e-151
504.17965e-168.35931e-161
514.70644e-169.41288e-161
521.90016e-163.80032e-161
531.04458e-162.08916e-161
543.88731e-177.77462e-171
551.11247e-172.22493e-171
564.39498e-188.78997e-181
571.27845e-182.55689e-181
584.57081e-199.14161e-191
591.40088e-192.80176e-191
603.95456e-207.90912e-201
611.1929e-202.38579e-201
623.82017e-217.64034e-211
631.40378e-212.80757e-211
643.71814e-227.43628e-221
659.79183e-231.95837e-221
662.8485e-235.69699e-231
677.86047e-241.57209e-231
682.1391e-244.27819e-241
691.08227e-242.16455e-241
704.53505e-259.0701e-251
711.51546e-253.03093e-251
729.61883e-261.92377e-251
732.86074e-265.72148e-261
747.59697e-271.51939e-261
752.25838e-274.51676e-271
766.59069e-281.31814e-271
771.57665e-273.15331e-271
784.38369e-288.76737e-281
791.93851e-283.87702e-281
805.83887e-291.16777e-281
812.70364e-295.40729e-291
828.23978e-301.64796e-291
832.03121e-304.06242e-301
845.08624e-311.01725e-301
852.87652e-315.75304e-311
867.23754e-321.44751e-311
873.37045e-326.7409e-321
882.52296e-265.04591e-261
891.67072e-263.34145e-261
905.56426e-271.11285e-261
911.65368e-273.30736e-271
927.76202e-281.5524e-271
932.23984e-284.47969e-281
946.61289e-291.32258e-281
951.98939e-293.97879e-291
966.20045e-301.24009e-291
972.32247e-304.64493e-301
988.19059e-311.63812e-301
992.47468e-314.94937e-311
1007.44451e-321.4889e-311
1011.31018e-272.62036e-271
1024.13553e-288.27106e-281
1031.32999e-282.65997e-281
1044.3881e-298.77619e-291
1051.37059e-292.74117e-291
1066.19218e-301.23844e-291
1073.92521e-307.85043e-301
1082.22524e-304.45048e-301
1096.79889e-311.35978e-301
1102.2202e-314.4404e-311
1111.07467e-312.14934e-311
1123.87185e-307.74369e-301
1131.20844e-302.41687e-301
1144.05008e-318.10015e-311
1151.67936e-313.35872e-311
1165.20325e-321.04065e-311
1173.09305e-286.18611e-281
1182.01681e-284.03361e-281
1194.445e-258.89e-251
1202.24486e-254.48971e-251
1214.54021e-249.08042e-241
1222.09863e-244.19726e-241
1232.12537e-234.25075e-231
1241.79683e-223.59367e-221
1252.17248e-224.34496e-221
1261.29423e-202.58846e-201
1272.00117e-194.00234e-191
1287.81984e-191.56397e-181
1298.36897e-191.67379e-181
1306.97605e-191.39521e-181
1314.36573e-198.73147e-191
1321.21554e-172.43108e-171
1335.6112e-171.12224e-161
1343.83721e-177.67443e-171
1354.2574e-178.5148e-171
1363.42485e-176.8497e-171
1373.86329e-177.72657e-171
1382.25243e-174.50487e-171
1391.35224e-172.70448e-171
1408.78359e-181.75672e-171
1416.59909e-181.31982e-171
1423.23739e-156.47479e-151
1436.28526e-151.25705e-141
1441.39145e-142.78289e-141
1458.24984e-151.64997e-141
1463.36138e-136.72276e-131
1477.10784e-131.42157e-121
1484.10225e-138.20449e-131
1494.18759e-138.37518e-131
1502.34224e-134.68447e-131
1511.44692e-132.89385e-131
1528.19889e-131.63978e-121
1532.421e-114.842e-111
1541.51657e-113.03315e-111
1555.02308e-111.00462e-101
1562.10148e-104.20296e-101
1574.59739e-109.19478e-101
1582.84612e-105.69224e-101
1598.95432e-101.79086e-091
1605.93033e-101.18607e-091
1614.35476e-108.70952e-101
1622.547e-105.09399e-101
1632.40373e-104.80746e-101
1642.90345e-105.80689e-101
1651.96506e-103.93012e-101
1661.5527e-103.1054e-101
1679.89871e-111.97974e-101
1685.34816e-101.06963e-091
1697.44458e-101.48892e-091
1704.68775e-089.3755e-081
1714.83387e-089.66774e-081
1723.40273e-086.80546e-081
1732.29371e-084.58741e-081
1741.5374e-083.07479e-081
1759.88666e-091.97733e-081
1766.07518e-091.21504e-081
1773.75663e-097.51326e-091
1787.78603e-091.55721e-081
1791.54502e-083.09005e-081
1801.00832e-082.01664e-081
1816.51345e-091.30269e-081
1821.24235e-082.48471e-081
1837.59481e-091.51896e-081
1841.56539e-083.13079e-081
1859.87176e-091.97435e-081
1866.35587e-091.27117e-081
1876.57834e-091.31567e-081
1888.73403e-091.74681e-081
1891.00679e-082.01358e-081
1901.5517e-083.1034e-081
1915.44394e-081.08879e-071
1928.54459e-081.70892e-071
1936.81864e-081.36373e-071
1944.43176e-088.86351e-081
1951.22868e-072.45736e-071
1967.48425e-071.49685e-060.999999
1971.7601e-063.52021e-060.999998
1983.87827e-067.75655e-060.999996
1992.85216e-065.70432e-060.999997
2004.61796e-069.23591e-060.999995
2013.83187e-067.66374e-060.999996
2023.57384e-067.14767e-060.999996
2033.86676e-067.73352e-060.999996
2045.89111e-061.17822e-050.999994
2054.5071e-069.0142e-060.999995
2067.16772e-061.43354e-050.999993
2076.38454e-061.27691e-050.999994
2084.62996e-069.25992e-060.999995
2097.72247e-061.54449e-050.999992
2105.19888e-061.03978e-050.999995
2113.86448e-067.72897e-060.999996
2122.64978e-065.29956e-060.999997
2132.47764e-064.95528e-060.999998
2141.74613e-063.49226e-060.999998
2151.76788e-063.53576e-060.999998
2161.28068e-062.56137e-060.999999
2172.25264e-064.50528e-060.999998
2184.38969e-068.77938e-060.999996
2194.50571e-069.01142e-060.999995
2201.38391e-052.76781e-050.999986
2211.08772e-052.17545e-050.999989
2221.06712e-052.13425e-050.999989
2231.04192e-052.08385e-050.99999
2247.60255e-061.52051e-050.999992
2250.0001731120.0003462240.999827
2260.0001285020.0002570050.999871
2270.000227650.0004553010.999772
2280.0001558680.0003117370.999844
2290.0001716310.0003432620.999828
2300.0005518360.001103670.999448
2310.0009001050.001800210.9991
2320.002327480.004654970.997673
2330.001957940.003915890.998042
2340.008980280.01796060.99102
2350.01173620.02347240.988264
2360.009379120.01875820.990621
2370.007959870.01591970.99204
2380.007681660.01536330.992318
2390.006757120.01351420.993243
2400.005087570.01017510.994912
2410.003885550.00777110.996114
2420.002793230.005586450.997207
2430.0132310.0264620.986769
2440.01416440.02832870.985836
2450.02028920.04057840.979711
2460.01780320.03560650.982197
2470.01319060.02638110.986809
2480.02692950.0538590.973071
2490.02011280.04022570.979887
2500.04858310.09716620.951417
2510.04266310.08532620.957337
2520.03339840.06679670.966602
2530.06861550.1372310.931385
2540.07396810.1479360.926032
2550.08641280.1728260.913587
2560.06870250.1374050.931297
2570.1722510.3445010.827749
2580.1525880.3051750.847412
2590.127150.2542990.87285
2600.1420780.2841570.857922
2610.1846360.3692710.815364
2620.1770940.3541880.822906
2630.1417470.2834940.858253
2640.1368690.2737380.863131
2650.1027160.2054330.897284
2660.1265470.2530950.873453
2670.1141180.2282350.885882
2680.1597880.3195770.840212
2690.1447960.2895910.855204
2700.1167980.2335970.883202
2710.2869810.5739620.713019
2720.2282460.4564920.771754
2730.1651040.3302080.834896
2740.1102340.2204680.889766
2750.07486970.1497390.92513
2760.0436310.08726190.956369
2770.08745880.1749180.912541
2780.1019980.2039950.898002

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.00190477 & 0.00380955 & 0.998095 \tabularnewline
10 & 0.0104366 & 0.0208732 & 0.989563 \tabularnewline
11 & 0.00242657 & 0.00485313 & 0.997573 \tabularnewline
12 & 0.00143615 & 0.0028723 & 0.998564 \tabularnewline
13 & 0.000880887 & 0.00176177 & 0.999119 \tabularnewline
14 & 0.000242806 & 0.000485612 & 0.999757 \tabularnewline
15 & 0.00016492 & 0.00032984 & 0.999835 \tabularnewline
16 & 4.52746e-05 & 9.05492e-05 & 0.999955 \tabularnewline
17 & 1.13944e-05 & 2.27889e-05 & 0.999989 \tabularnewline
18 & 2.77687e-06 & 5.55374e-06 & 0.999997 \tabularnewline
19 & 9.6302e-07 & 1.92604e-06 & 0.999999 \tabularnewline
20 & 2.68242e-07 & 5.36483e-07 & 1 \tabularnewline
21 & 6.4994e-08 & 1.29988e-07 & 1 \tabularnewline
22 & 7.46548e-08 & 1.4931e-07 & 1 \tabularnewline
23 & 1.47154e-07 & 2.94308e-07 & 1 \tabularnewline
24 & 5.9399e-08 & 1.18798e-07 & 1 \tabularnewline
25 & 1.07543e-06 & 2.15086e-06 & 0.999999 \tabularnewline
26 & 3.91444e-07 & 7.82889e-07 & 1 \tabularnewline
27 & 1.34705e-07 & 2.69409e-07 & 1 \tabularnewline
28 & 1.46701e-06 & 2.93401e-06 & 0.999999 \tabularnewline
29 & 5.43258e-07 & 1.08652e-06 & 0.999999 \tabularnewline
30 & 2.60395e-07 & 5.20791e-07 & 1 \tabularnewline
31 & 9.48048e-08 & 1.8961e-07 & 1 \tabularnewline
32 & 3.33166e-08 & 6.66332e-08 & 1 \tabularnewline
33 & 1.15652e-08 & 2.31305e-08 & 1 \tabularnewline
34 & 5.17063e-09 & 1.03413e-08 & 1 \tabularnewline
35 & 1.73343e-09 & 3.46686e-09 & 1 \tabularnewline
36 & 5.77851e-10 & 1.1557e-09 & 1 \tabularnewline
37 & 1.85887e-10 & 3.71775e-10 & 1 \tabularnewline
38 & 7.81608e-11 & 1.56322e-10 & 1 \tabularnewline
39 & 2.59897e-11 & 5.19795e-11 & 1 \tabularnewline
40 & 2.10314e-11 & 4.20627e-11 & 1 \tabularnewline
41 & 7.46919e-12 & 1.49384e-11 & 1 \tabularnewline
42 & 2.44995e-12 & 4.8999e-12 & 1 \tabularnewline
43 & 1.10605e-12 & 2.21211e-12 & 1 \tabularnewline
44 & 4.42105e-13 & 8.8421e-13 & 1 \tabularnewline
45 & 1.36537e-13 & 2.73073e-13 & 1 \tabularnewline
46 & 4.4299e-14 & 8.8598e-14 & 1 \tabularnewline
47 & 1.3495e-14 & 2.699e-14 & 1 \tabularnewline
48 & 4.85047e-15 & 9.70095e-15 & 1 \tabularnewline
49 & 1.445e-15 & 2.89e-15 & 1 \tabularnewline
50 & 4.17965e-16 & 8.35931e-16 & 1 \tabularnewline
51 & 4.70644e-16 & 9.41288e-16 & 1 \tabularnewline
52 & 1.90016e-16 & 3.80032e-16 & 1 \tabularnewline
53 & 1.04458e-16 & 2.08916e-16 & 1 \tabularnewline
54 & 3.88731e-17 & 7.77462e-17 & 1 \tabularnewline
55 & 1.11247e-17 & 2.22493e-17 & 1 \tabularnewline
56 & 4.39498e-18 & 8.78997e-18 & 1 \tabularnewline
57 & 1.27845e-18 & 2.55689e-18 & 1 \tabularnewline
58 & 4.57081e-19 & 9.14161e-19 & 1 \tabularnewline
59 & 1.40088e-19 & 2.80176e-19 & 1 \tabularnewline
60 & 3.95456e-20 & 7.90912e-20 & 1 \tabularnewline
61 & 1.1929e-20 & 2.38579e-20 & 1 \tabularnewline
62 & 3.82017e-21 & 7.64034e-21 & 1 \tabularnewline
63 & 1.40378e-21 & 2.80757e-21 & 1 \tabularnewline
64 & 3.71814e-22 & 7.43628e-22 & 1 \tabularnewline
65 & 9.79183e-23 & 1.95837e-22 & 1 \tabularnewline
66 & 2.8485e-23 & 5.69699e-23 & 1 \tabularnewline
67 & 7.86047e-24 & 1.57209e-23 & 1 \tabularnewline
68 & 2.1391e-24 & 4.27819e-24 & 1 \tabularnewline
69 & 1.08227e-24 & 2.16455e-24 & 1 \tabularnewline
70 & 4.53505e-25 & 9.0701e-25 & 1 \tabularnewline
71 & 1.51546e-25 & 3.03093e-25 & 1 \tabularnewline
72 & 9.61883e-26 & 1.92377e-25 & 1 \tabularnewline
73 & 2.86074e-26 & 5.72148e-26 & 1 \tabularnewline
74 & 7.59697e-27 & 1.51939e-26 & 1 \tabularnewline
75 & 2.25838e-27 & 4.51676e-27 & 1 \tabularnewline
76 & 6.59069e-28 & 1.31814e-27 & 1 \tabularnewline
77 & 1.57665e-27 & 3.15331e-27 & 1 \tabularnewline
78 & 4.38369e-28 & 8.76737e-28 & 1 \tabularnewline
79 & 1.93851e-28 & 3.87702e-28 & 1 \tabularnewline
80 & 5.83887e-29 & 1.16777e-28 & 1 \tabularnewline
81 & 2.70364e-29 & 5.40729e-29 & 1 \tabularnewline
82 & 8.23978e-30 & 1.64796e-29 & 1 \tabularnewline
83 & 2.03121e-30 & 4.06242e-30 & 1 \tabularnewline
84 & 5.08624e-31 & 1.01725e-30 & 1 \tabularnewline
85 & 2.87652e-31 & 5.75304e-31 & 1 \tabularnewline
86 & 7.23754e-32 & 1.44751e-31 & 1 \tabularnewline
87 & 3.37045e-32 & 6.7409e-32 & 1 \tabularnewline
88 & 2.52296e-26 & 5.04591e-26 & 1 \tabularnewline
89 & 1.67072e-26 & 3.34145e-26 & 1 \tabularnewline
90 & 5.56426e-27 & 1.11285e-26 & 1 \tabularnewline
91 & 1.65368e-27 & 3.30736e-27 & 1 \tabularnewline
92 & 7.76202e-28 & 1.5524e-27 & 1 \tabularnewline
93 & 2.23984e-28 & 4.47969e-28 & 1 \tabularnewline
94 & 6.61289e-29 & 1.32258e-28 & 1 \tabularnewline
95 & 1.98939e-29 & 3.97879e-29 & 1 \tabularnewline
96 & 6.20045e-30 & 1.24009e-29 & 1 \tabularnewline
97 & 2.32247e-30 & 4.64493e-30 & 1 \tabularnewline
98 & 8.19059e-31 & 1.63812e-30 & 1 \tabularnewline
99 & 2.47468e-31 & 4.94937e-31 & 1 \tabularnewline
100 & 7.44451e-32 & 1.4889e-31 & 1 \tabularnewline
101 & 1.31018e-27 & 2.62036e-27 & 1 \tabularnewline
102 & 4.13553e-28 & 8.27106e-28 & 1 \tabularnewline
103 & 1.32999e-28 & 2.65997e-28 & 1 \tabularnewline
104 & 4.3881e-29 & 8.77619e-29 & 1 \tabularnewline
105 & 1.37059e-29 & 2.74117e-29 & 1 \tabularnewline
106 & 6.19218e-30 & 1.23844e-29 & 1 \tabularnewline
107 & 3.92521e-30 & 7.85043e-30 & 1 \tabularnewline
108 & 2.22524e-30 & 4.45048e-30 & 1 \tabularnewline
109 & 6.79889e-31 & 1.35978e-30 & 1 \tabularnewline
110 & 2.2202e-31 & 4.4404e-31 & 1 \tabularnewline
111 & 1.07467e-31 & 2.14934e-31 & 1 \tabularnewline
112 & 3.87185e-30 & 7.74369e-30 & 1 \tabularnewline
113 & 1.20844e-30 & 2.41687e-30 & 1 \tabularnewline
114 & 4.05008e-31 & 8.10015e-31 & 1 \tabularnewline
115 & 1.67936e-31 & 3.35872e-31 & 1 \tabularnewline
116 & 5.20325e-32 & 1.04065e-31 & 1 \tabularnewline
117 & 3.09305e-28 & 6.18611e-28 & 1 \tabularnewline
118 & 2.01681e-28 & 4.03361e-28 & 1 \tabularnewline
119 & 4.445e-25 & 8.89e-25 & 1 \tabularnewline
120 & 2.24486e-25 & 4.48971e-25 & 1 \tabularnewline
121 & 4.54021e-24 & 9.08042e-24 & 1 \tabularnewline
122 & 2.09863e-24 & 4.19726e-24 & 1 \tabularnewline
123 & 2.12537e-23 & 4.25075e-23 & 1 \tabularnewline
124 & 1.79683e-22 & 3.59367e-22 & 1 \tabularnewline
125 & 2.17248e-22 & 4.34496e-22 & 1 \tabularnewline
126 & 1.29423e-20 & 2.58846e-20 & 1 \tabularnewline
127 & 2.00117e-19 & 4.00234e-19 & 1 \tabularnewline
128 & 7.81984e-19 & 1.56397e-18 & 1 \tabularnewline
129 & 8.36897e-19 & 1.67379e-18 & 1 \tabularnewline
130 & 6.97605e-19 & 1.39521e-18 & 1 \tabularnewline
131 & 4.36573e-19 & 8.73147e-19 & 1 \tabularnewline
132 & 1.21554e-17 & 2.43108e-17 & 1 \tabularnewline
133 & 5.6112e-17 & 1.12224e-16 & 1 \tabularnewline
134 & 3.83721e-17 & 7.67443e-17 & 1 \tabularnewline
135 & 4.2574e-17 & 8.5148e-17 & 1 \tabularnewline
136 & 3.42485e-17 & 6.8497e-17 & 1 \tabularnewline
137 & 3.86329e-17 & 7.72657e-17 & 1 \tabularnewline
138 & 2.25243e-17 & 4.50487e-17 & 1 \tabularnewline
139 & 1.35224e-17 & 2.70448e-17 & 1 \tabularnewline
140 & 8.78359e-18 & 1.75672e-17 & 1 \tabularnewline
141 & 6.59909e-18 & 1.31982e-17 & 1 \tabularnewline
142 & 3.23739e-15 & 6.47479e-15 & 1 \tabularnewline
143 & 6.28526e-15 & 1.25705e-14 & 1 \tabularnewline
144 & 1.39145e-14 & 2.78289e-14 & 1 \tabularnewline
145 & 8.24984e-15 & 1.64997e-14 & 1 \tabularnewline
146 & 3.36138e-13 & 6.72276e-13 & 1 \tabularnewline
147 & 7.10784e-13 & 1.42157e-12 & 1 \tabularnewline
148 & 4.10225e-13 & 8.20449e-13 & 1 \tabularnewline
149 & 4.18759e-13 & 8.37518e-13 & 1 \tabularnewline
150 & 2.34224e-13 & 4.68447e-13 & 1 \tabularnewline
151 & 1.44692e-13 & 2.89385e-13 & 1 \tabularnewline
152 & 8.19889e-13 & 1.63978e-12 & 1 \tabularnewline
153 & 2.421e-11 & 4.842e-11 & 1 \tabularnewline
154 & 1.51657e-11 & 3.03315e-11 & 1 \tabularnewline
155 & 5.02308e-11 & 1.00462e-10 & 1 \tabularnewline
156 & 2.10148e-10 & 4.20296e-10 & 1 \tabularnewline
157 & 4.59739e-10 & 9.19478e-10 & 1 \tabularnewline
158 & 2.84612e-10 & 5.69224e-10 & 1 \tabularnewline
159 & 8.95432e-10 & 1.79086e-09 & 1 \tabularnewline
160 & 5.93033e-10 & 1.18607e-09 & 1 \tabularnewline
161 & 4.35476e-10 & 8.70952e-10 & 1 \tabularnewline
162 & 2.547e-10 & 5.09399e-10 & 1 \tabularnewline
163 & 2.40373e-10 & 4.80746e-10 & 1 \tabularnewline
164 & 2.90345e-10 & 5.80689e-10 & 1 \tabularnewline
165 & 1.96506e-10 & 3.93012e-10 & 1 \tabularnewline
166 & 1.5527e-10 & 3.1054e-10 & 1 \tabularnewline
167 & 9.89871e-11 & 1.97974e-10 & 1 \tabularnewline
168 & 5.34816e-10 & 1.06963e-09 & 1 \tabularnewline
169 & 7.44458e-10 & 1.48892e-09 & 1 \tabularnewline
170 & 4.68775e-08 & 9.3755e-08 & 1 \tabularnewline
171 & 4.83387e-08 & 9.66774e-08 & 1 \tabularnewline
172 & 3.40273e-08 & 6.80546e-08 & 1 \tabularnewline
173 & 2.29371e-08 & 4.58741e-08 & 1 \tabularnewline
174 & 1.5374e-08 & 3.07479e-08 & 1 \tabularnewline
175 & 9.88666e-09 & 1.97733e-08 & 1 \tabularnewline
176 & 6.07518e-09 & 1.21504e-08 & 1 \tabularnewline
177 & 3.75663e-09 & 7.51326e-09 & 1 \tabularnewline
178 & 7.78603e-09 & 1.55721e-08 & 1 \tabularnewline
179 & 1.54502e-08 & 3.09005e-08 & 1 \tabularnewline
180 & 1.00832e-08 & 2.01664e-08 & 1 \tabularnewline
181 & 6.51345e-09 & 1.30269e-08 & 1 \tabularnewline
182 & 1.24235e-08 & 2.48471e-08 & 1 \tabularnewline
183 & 7.59481e-09 & 1.51896e-08 & 1 \tabularnewline
184 & 1.56539e-08 & 3.13079e-08 & 1 \tabularnewline
185 & 9.87176e-09 & 1.97435e-08 & 1 \tabularnewline
186 & 6.35587e-09 & 1.27117e-08 & 1 \tabularnewline
187 & 6.57834e-09 & 1.31567e-08 & 1 \tabularnewline
188 & 8.73403e-09 & 1.74681e-08 & 1 \tabularnewline
189 & 1.00679e-08 & 2.01358e-08 & 1 \tabularnewline
190 & 1.5517e-08 & 3.1034e-08 & 1 \tabularnewline
191 & 5.44394e-08 & 1.08879e-07 & 1 \tabularnewline
192 & 8.54459e-08 & 1.70892e-07 & 1 \tabularnewline
193 & 6.81864e-08 & 1.36373e-07 & 1 \tabularnewline
194 & 4.43176e-08 & 8.86351e-08 & 1 \tabularnewline
195 & 1.22868e-07 & 2.45736e-07 & 1 \tabularnewline
196 & 7.48425e-07 & 1.49685e-06 & 0.999999 \tabularnewline
197 & 1.7601e-06 & 3.52021e-06 & 0.999998 \tabularnewline
198 & 3.87827e-06 & 7.75655e-06 & 0.999996 \tabularnewline
199 & 2.85216e-06 & 5.70432e-06 & 0.999997 \tabularnewline
200 & 4.61796e-06 & 9.23591e-06 & 0.999995 \tabularnewline
201 & 3.83187e-06 & 7.66374e-06 & 0.999996 \tabularnewline
202 & 3.57384e-06 & 7.14767e-06 & 0.999996 \tabularnewline
203 & 3.86676e-06 & 7.73352e-06 & 0.999996 \tabularnewline
204 & 5.89111e-06 & 1.17822e-05 & 0.999994 \tabularnewline
205 & 4.5071e-06 & 9.0142e-06 & 0.999995 \tabularnewline
206 & 7.16772e-06 & 1.43354e-05 & 0.999993 \tabularnewline
207 & 6.38454e-06 & 1.27691e-05 & 0.999994 \tabularnewline
208 & 4.62996e-06 & 9.25992e-06 & 0.999995 \tabularnewline
209 & 7.72247e-06 & 1.54449e-05 & 0.999992 \tabularnewline
210 & 5.19888e-06 & 1.03978e-05 & 0.999995 \tabularnewline
211 & 3.86448e-06 & 7.72897e-06 & 0.999996 \tabularnewline
212 & 2.64978e-06 & 5.29956e-06 & 0.999997 \tabularnewline
213 & 2.47764e-06 & 4.95528e-06 & 0.999998 \tabularnewline
214 & 1.74613e-06 & 3.49226e-06 & 0.999998 \tabularnewline
215 & 1.76788e-06 & 3.53576e-06 & 0.999998 \tabularnewline
216 & 1.28068e-06 & 2.56137e-06 & 0.999999 \tabularnewline
217 & 2.25264e-06 & 4.50528e-06 & 0.999998 \tabularnewline
218 & 4.38969e-06 & 8.77938e-06 & 0.999996 \tabularnewline
219 & 4.50571e-06 & 9.01142e-06 & 0.999995 \tabularnewline
220 & 1.38391e-05 & 2.76781e-05 & 0.999986 \tabularnewline
221 & 1.08772e-05 & 2.17545e-05 & 0.999989 \tabularnewline
222 & 1.06712e-05 & 2.13425e-05 & 0.999989 \tabularnewline
223 & 1.04192e-05 & 2.08385e-05 & 0.99999 \tabularnewline
224 & 7.60255e-06 & 1.52051e-05 & 0.999992 \tabularnewline
225 & 0.000173112 & 0.000346224 & 0.999827 \tabularnewline
226 & 0.000128502 & 0.000257005 & 0.999871 \tabularnewline
227 & 0.00022765 & 0.000455301 & 0.999772 \tabularnewline
228 & 0.000155868 & 0.000311737 & 0.999844 \tabularnewline
229 & 0.000171631 & 0.000343262 & 0.999828 \tabularnewline
230 & 0.000551836 & 0.00110367 & 0.999448 \tabularnewline
231 & 0.000900105 & 0.00180021 & 0.9991 \tabularnewline
232 & 0.00232748 & 0.00465497 & 0.997673 \tabularnewline
233 & 0.00195794 & 0.00391589 & 0.998042 \tabularnewline
234 & 0.00898028 & 0.0179606 & 0.99102 \tabularnewline
235 & 0.0117362 & 0.0234724 & 0.988264 \tabularnewline
236 & 0.00937912 & 0.0187582 & 0.990621 \tabularnewline
237 & 0.00795987 & 0.0159197 & 0.99204 \tabularnewline
238 & 0.00768166 & 0.0153633 & 0.992318 \tabularnewline
239 & 0.00675712 & 0.0135142 & 0.993243 \tabularnewline
240 & 0.00508757 & 0.0101751 & 0.994912 \tabularnewline
241 & 0.00388555 & 0.0077711 & 0.996114 \tabularnewline
242 & 0.00279323 & 0.00558645 & 0.997207 \tabularnewline
243 & 0.013231 & 0.026462 & 0.986769 \tabularnewline
244 & 0.0141644 & 0.0283287 & 0.985836 \tabularnewline
245 & 0.0202892 & 0.0405784 & 0.979711 \tabularnewline
246 & 0.0178032 & 0.0356065 & 0.982197 \tabularnewline
247 & 0.0131906 & 0.0263811 & 0.986809 \tabularnewline
248 & 0.0269295 & 0.053859 & 0.973071 \tabularnewline
249 & 0.0201128 & 0.0402257 & 0.979887 \tabularnewline
250 & 0.0485831 & 0.0971662 & 0.951417 \tabularnewline
251 & 0.0426631 & 0.0853262 & 0.957337 \tabularnewline
252 & 0.0333984 & 0.0667967 & 0.966602 \tabularnewline
253 & 0.0686155 & 0.137231 & 0.931385 \tabularnewline
254 & 0.0739681 & 0.147936 & 0.926032 \tabularnewline
255 & 0.0864128 & 0.172826 & 0.913587 \tabularnewline
256 & 0.0687025 & 0.137405 & 0.931297 \tabularnewline
257 & 0.172251 & 0.344501 & 0.827749 \tabularnewline
258 & 0.152588 & 0.305175 & 0.847412 \tabularnewline
259 & 0.12715 & 0.254299 & 0.87285 \tabularnewline
260 & 0.142078 & 0.284157 & 0.857922 \tabularnewline
261 & 0.184636 & 0.369271 & 0.815364 \tabularnewline
262 & 0.177094 & 0.354188 & 0.822906 \tabularnewline
263 & 0.141747 & 0.283494 & 0.858253 \tabularnewline
264 & 0.136869 & 0.273738 & 0.863131 \tabularnewline
265 & 0.102716 & 0.205433 & 0.897284 \tabularnewline
266 & 0.126547 & 0.253095 & 0.873453 \tabularnewline
267 & 0.114118 & 0.228235 & 0.885882 \tabularnewline
268 & 0.159788 & 0.319577 & 0.840212 \tabularnewline
269 & 0.144796 & 0.289591 & 0.855204 \tabularnewline
270 & 0.116798 & 0.233597 & 0.883202 \tabularnewline
271 & 0.286981 & 0.573962 & 0.713019 \tabularnewline
272 & 0.228246 & 0.456492 & 0.771754 \tabularnewline
273 & 0.165104 & 0.330208 & 0.834896 \tabularnewline
274 & 0.110234 & 0.220468 & 0.889766 \tabularnewline
275 & 0.0748697 & 0.149739 & 0.92513 \tabularnewline
276 & 0.043631 & 0.0872619 & 0.956369 \tabularnewline
277 & 0.0874588 & 0.174918 & 0.912541 \tabularnewline
278 & 0.101998 & 0.203995 & 0.898002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264028&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]9[/C][C]0.00190477[/C][C]0.00380955[/C][C]0.998095[/C][/ROW]
[ROW][C]10[/C][C]0.0104366[/C][C]0.0208732[/C][C]0.989563[/C][/ROW]
[ROW][C]11[/C][C]0.00242657[/C][C]0.00485313[/C][C]0.997573[/C][/ROW]
[ROW][C]12[/C][C]0.00143615[/C][C]0.0028723[/C][C]0.998564[/C][/ROW]
[ROW][C]13[/C][C]0.000880887[/C][C]0.00176177[/C][C]0.999119[/C][/ROW]
[ROW][C]14[/C][C]0.000242806[/C][C]0.000485612[/C][C]0.999757[/C][/ROW]
[ROW][C]15[/C][C]0.00016492[/C][C]0.00032984[/C][C]0.999835[/C][/ROW]
[ROW][C]16[/C][C]4.52746e-05[/C][C]9.05492e-05[/C][C]0.999955[/C][/ROW]
[ROW][C]17[/C][C]1.13944e-05[/C][C]2.27889e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]18[/C][C]2.77687e-06[/C][C]5.55374e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]19[/C][C]9.6302e-07[/C][C]1.92604e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]20[/C][C]2.68242e-07[/C][C]5.36483e-07[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]6.4994e-08[/C][C]1.29988e-07[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]7.46548e-08[/C][C]1.4931e-07[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]1.47154e-07[/C][C]2.94308e-07[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]5.9399e-08[/C][C]1.18798e-07[/C][C]1[/C][/ROW]
[ROW][C]25[/C][C]1.07543e-06[/C][C]2.15086e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]26[/C][C]3.91444e-07[/C][C]7.82889e-07[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]1.34705e-07[/C][C]2.69409e-07[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]1.46701e-06[/C][C]2.93401e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]29[/C][C]5.43258e-07[/C][C]1.08652e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]30[/C][C]2.60395e-07[/C][C]5.20791e-07[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]9.48048e-08[/C][C]1.8961e-07[/C][C]1[/C][/ROW]
[ROW][C]32[/C][C]3.33166e-08[/C][C]6.66332e-08[/C][C]1[/C][/ROW]
[ROW][C]33[/C][C]1.15652e-08[/C][C]2.31305e-08[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]5.17063e-09[/C][C]1.03413e-08[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]1.73343e-09[/C][C]3.46686e-09[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]5.77851e-10[/C][C]1.1557e-09[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]1.85887e-10[/C][C]3.71775e-10[/C][C]1[/C][/ROW]
[ROW][C]38[/C][C]7.81608e-11[/C][C]1.56322e-10[/C][C]1[/C][/ROW]
[ROW][C]39[/C][C]2.59897e-11[/C][C]5.19795e-11[/C][C]1[/C][/ROW]
[ROW][C]40[/C][C]2.10314e-11[/C][C]4.20627e-11[/C][C]1[/C][/ROW]
[ROW][C]41[/C][C]7.46919e-12[/C][C]1.49384e-11[/C][C]1[/C][/ROW]
[ROW][C]42[/C][C]2.44995e-12[/C][C]4.8999e-12[/C][C]1[/C][/ROW]
[ROW][C]43[/C][C]1.10605e-12[/C][C]2.21211e-12[/C][C]1[/C][/ROW]
[ROW][C]44[/C][C]4.42105e-13[/C][C]8.8421e-13[/C][C]1[/C][/ROW]
[ROW][C]45[/C][C]1.36537e-13[/C][C]2.73073e-13[/C][C]1[/C][/ROW]
[ROW][C]46[/C][C]4.4299e-14[/C][C]8.8598e-14[/C][C]1[/C][/ROW]
[ROW][C]47[/C][C]1.3495e-14[/C][C]2.699e-14[/C][C]1[/C][/ROW]
[ROW][C]48[/C][C]4.85047e-15[/C][C]9.70095e-15[/C][C]1[/C][/ROW]
[ROW][C]49[/C][C]1.445e-15[/C][C]2.89e-15[/C][C]1[/C][/ROW]
[ROW][C]50[/C][C]4.17965e-16[/C][C]8.35931e-16[/C][C]1[/C][/ROW]
[ROW][C]51[/C][C]4.70644e-16[/C][C]9.41288e-16[/C][C]1[/C][/ROW]
[ROW][C]52[/C][C]1.90016e-16[/C][C]3.80032e-16[/C][C]1[/C][/ROW]
[ROW][C]53[/C][C]1.04458e-16[/C][C]2.08916e-16[/C][C]1[/C][/ROW]
[ROW][C]54[/C][C]3.88731e-17[/C][C]7.77462e-17[/C][C]1[/C][/ROW]
[ROW][C]55[/C][C]1.11247e-17[/C][C]2.22493e-17[/C][C]1[/C][/ROW]
[ROW][C]56[/C][C]4.39498e-18[/C][C]8.78997e-18[/C][C]1[/C][/ROW]
[ROW][C]57[/C][C]1.27845e-18[/C][C]2.55689e-18[/C][C]1[/C][/ROW]
[ROW][C]58[/C][C]4.57081e-19[/C][C]9.14161e-19[/C][C]1[/C][/ROW]
[ROW][C]59[/C][C]1.40088e-19[/C][C]2.80176e-19[/C][C]1[/C][/ROW]
[ROW][C]60[/C][C]3.95456e-20[/C][C]7.90912e-20[/C][C]1[/C][/ROW]
[ROW][C]61[/C][C]1.1929e-20[/C][C]2.38579e-20[/C][C]1[/C][/ROW]
[ROW][C]62[/C][C]3.82017e-21[/C][C]7.64034e-21[/C][C]1[/C][/ROW]
[ROW][C]63[/C][C]1.40378e-21[/C][C]2.80757e-21[/C][C]1[/C][/ROW]
[ROW][C]64[/C][C]3.71814e-22[/C][C]7.43628e-22[/C][C]1[/C][/ROW]
[ROW][C]65[/C][C]9.79183e-23[/C][C]1.95837e-22[/C][C]1[/C][/ROW]
[ROW][C]66[/C][C]2.8485e-23[/C][C]5.69699e-23[/C][C]1[/C][/ROW]
[ROW][C]67[/C][C]7.86047e-24[/C][C]1.57209e-23[/C][C]1[/C][/ROW]
[ROW][C]68[/C][C]2.1391e-24[/C][C]4.27819e-24[/C][C]1[/C][/ROW]
[ROW][C]69[/C][C]1.08227e-24[/C][C]2.16455e-24[/C][C]1[/C][/ROW]
[ROW][C]70[/C][C]4.53505e-25[/C][C]9.0701e-25[/C][C]1[/C][/ROW]
[ROW][C]71[/C][C]1.51546e-25[/C][C]3.03093e-25[/C][C]1[/C][/ROW]
[ROW][C]72[/C][C]9.61883e-26[/C][C]1.92377e-25[/C][C]1[/C][/ROW]
[ROW][C]73[/C][C]2.86074e-26[/C][C]5.72148e-26[/C][C]1[/C][/ROW]
[ROW][C]74[/C][C]7.59697e-27[/C][C]1.51939e-26[/C][C]1[/C][/ROW]
[ROW][C]75[/C][C]2.25838e-27[/C][C]4.51676e-27[/C][C]1[/C][/ROW]
[ROW][C]76[/C][C]6.59069e-28[/C][C]1.31814e-27[/C][C]1[/C][/ROW]
[ROW][C]77[/C][C]1.57665e-27[/C][C]3.15331e-27[/C][C]1[/C][/ROW]
[ROW][C]78[/C][C]4.38369e-28[/C][C]8.76737e-28[/C][C]1[/C][/ROW]
[ROW][C]79[/C][C]1.93851e-28[/C][C]3.87702e-28[/C][C]1[/C][/ROW]
[ROW][C]80[/C][C]5.83887e-29[/C][C]1.16777e-28[/C][C]1[/C][/ROW]
[ROW][C]81[/C][C]2.70364e-29[/C][C]5.40729e-29[/C][C]1[/C][/ROW]
[ROW][C]82[/C][C]8.23978e-30[/C][C]1.64796e-29[/C][C]1[/C][/ROW]
[ROW][C]83[/C][C]2.03121e-30[/C][C]4.06242e-30[/C][C]1[/C][/ROW]
[ROW][C]84[/C][C]5.08624e-31[/C][C]1.01725e-30[/C][C]1[/C][/ROW]
[ROW][C]85[/C][C]2.87652e-31[/C][C]5.75304e-31[/C][C]1[/C][/ROW]
[ROW][C]86[/C][C]7.23754e-32[/C][C]1.44751e-31[/C][C]1[/C][/ROW]
[ROW][C]87[/C][C]3.37045e-32[/C][C]6.7409e-32[/C][C]1[/C][/ROW]
[ROW][C]88[/C][C]2.52296e-26[/C][C]5.04591e-26[/C][C]1[/C][/ROW]
[ROW][C]89[/C][C]1.67072e-26[/C][C]3.34145e-26[/C][C]1[/C][/ROW]
[ROW][C]90[/C][C]5.56426e-27[/C][C]1.11285e-26[/C][C]1[/C][/ROW]
[ROW][C]91[/C][C]1.65368e-27[/C][C]3.30736e-27[/C][C]1[/C][/ROW]
[ROW][C]92[/C][C]7.76202e-28[/C][C]1.5524e-27[/C][C]1[/C][/ROW]
[ROW][C]93[/C][C]2.23984e-28[/C][C]4.47969e-28[/C][C]1[/C][/ROW]
[ROW][C]94[/C][C]6.61289e-29[/C][C]1.32258e-28[/C][C]1[/C][/ROW]
[ROW][C]95[/C][C]1.98939e-29[/C][C]3.97879e-29[/C][C]1[/C][/ROW]
[ROW][C]96[/C][C]6.20045e-30[/C][C]1.24009e-29[/C][C]1[/C][/ROW]
[ROW][C]97[/C][C]2.32247e-30[/C][C]4.64493e-30[/C][C]1[/C][/ROW]
[ROW][C]98[/C][C]8.19059e-31[/C][C]1.63812e-30[/C][C]1[/C][/ROW]
[ROW][C]99[/C][C]2.47468e-31[/C][C]4.94937e-31[/C][C]1[/C][/ROW]
[ROW][C]100[/C][C]7.44451e-32[/C][C]1.4889e-31[/C][C]1[/C][/ROW]
[ROW][C]101[/C][C]1.31018e-27[/C][C]2.62036e-27[/C][C]1[/C][/ROW]
[ROW][C]102[/C][C]4.13553e-28[/C][C]8.27106e-28[/C][C]1[/C][/ROW]
[ROW][C]103[/C][C]1.32999e-28[/C][C]2.65997e-28[/C][C]1[/C][/ROW]
[ROW][C]104[/C][C]4.3881e-29[/C][C]8.77619e-29[/C][C]1[/C][/ROW]
[ROW][C]105[/C][C]1.37059e-29[/C][C]2.74117e-29[/C][C]1[/C][/ROW]
[ROW][C]106[/C][C]6.19218e-30[/C][C]1.23844e-29[/C][C]1[/C][/ROW]
[ROW][C]107[/C][C]3.92521e-30[/C][C]7.85043e-30[/C][C]1[/C][/ROW]
[ROW][C]108[/C][C]2.22524e-30[/C][C]4.45048e-30[/C][C]1[/C][/ROW]
[ROW][C]109[/C][C]6.79889e-31[/C][C]1.35978e-30[/C][C]1[/C][/ROW]
[ROW][C]110[/C][C]2.2202e-31[/C][C]4.4404e-31[/C][C]1[/C][/ROW]
[ROW][C]111[/C][C]1.07467e-31[/C][C]2.14934e-31[/C][C]1[/C][/ROW]
[ROW][C]112[/C][C]3.87185e-30[/C][C]7.74369e-30[/C][C]1[/C][/ROW]
[ROW][C]113[/C][C]1.20844e-30[/C][C]2.41687e-30[/C][C]1[/C][/ROW]
[ROW][C]114[/C][C]4.05008e-31[/C][C]8.10015e-31[/C][C]1[/C][/ROW]
[ROW][C]115[/C][C]1.67936e-31[/C][C]3.35872e-31[/C][C]1[/C][/ROW]
[ROW][C]116[/C][C]5.20325e-32[/C][C]1.04065e-31[/C][C]1[/C][/ROW]
[ROW][C]117[/C][C]3.09305e-28[/C][C]6.18611e-28[/C][C]1[/C][/ROW]
[ROW][C]118[/C][C]2.01681e-28[/C][C]4.03361e-28[/C][C]1[/C][/ROW]
[ROW][C]119[/C][C]4.445e-25[/C][C]8.89e-25[/C][C]1[/C][/ROW]
[ROW][C]120[/C][C]2.24486e-25[/C][C]4.48971e-25[/C][C]1[/C][/ROW]
[ROW][C]121[/C][C]4.54021e-24[/C][C]9.08042e-24[/C][C]1[/C][/ROW]
[ROW][C]122[/C][C]2.09863e-24[/C][C]4.19726e-24[/C][C]1[/C][/ROW]
[ROW][C]123[/C][C]2.12537e-23[/C][C]4.25075e-23[/C][C]1[/C][/ROW]
[ROW][C]124[/C][C]1.79683e-22[/C][C]3.59367e-22[/C][C]1[/C][/ROW]
[ROW][C]125[/C][C]2.17248e-22[/C][C]4.34496e-22[/C][C]1[/C][/ROW]
[ROW][C]126[/C][C]1.29423e-20[/C][C]2.58846e-20[/C][C]1[/C][/ROW]
[ROW][C]127[/C][C]2.00117e-19[/C][C]4.00234e-19[/C][C]1[/C][/ROW]
[ROW][C]128[/C][C]7.81984e-19[/C][C]1.56397e-18[/C][C]1[/C][/ROW]
[ROW][C]129[/C][C]8.36897e-19[/C][C]1.67379e-18[/C][C]1[/C][/ROW]
[ROW][C]130[/C][C]6.97605e-19[/C][C]1.39521e-18[/C][C]1[/C][/ROW]
[ROW][C]131[/C][C]4.36573e-19[/C][C]8.73147e-19[/C][C]1[/C][/ROW]
[ROW][C]132[/C][C]1.21554e-17[/C][C]2.43108e-17[/C][C]1[/C][/ROW]
[ROW][C]133[/C][C]5.6112e-17[/C][C]1.12224e-16[/C][C]1[/C][/ROW]
[ROW][C]134[/C][C]3.83721e-17[/C][C]7.67443e-17[/C][C]1[/C][/ROW]
[ROW][C]135[/C][C]4.2574e-17[/C][C]8.5148e-17[/C][C]1[/C][/ROW]
[ROW][C]136[/C][C]3.42485e-17[/C][C]6.8497e-17[/C][C]1[/C][/ROW]
[ROW][C]137[/C][C]3.86329e-17[/C][C]7.72657e-17[/C][C]1[/C][/ROW]
[ROW][C]138[/C][C]2.25243e-17[/C][C]4.50487e-17[/C][C]1[/C][/ROW]
[ROW][C]139[/C][C]1.35224e-17[/C][C]2.70448e-17[/C][C]1[/C][/ROW]
[ROW][C]140[/C][C]8.78359e-18[/C][C]1.75672e-17[/C][C]1[/C][/ROW]
[ROW][C]141[/C][C]6.59909e-18[/C][C]1.31982e-17[/C][C]1[/C][/ROW]
[ROW][C]142[/C][C]3.23739e-15[/C][C]6.47479e-15[/C][C]1[/C][/ROW]
[ROW][C]143[/C][C]6.28526e-15[/C][C]1.25705e-14[/C][C]1[/C][/ROW]
[ROW][C]144[/C][C]1.39145e-14[/C][C]2.78289e-14[/C][C]1[/C][/ROW]
[ROW][C]145[/C][C]8.24984e-15[/C][C]1.64997e-14[/C][C]1[/C][/ROW]
[ROW][C]146[/C][C]3.36138e-13[/C][C]6.72276e-13[/C][C]1[/C][/ROW]
[ROW][C]147[/C][C]7.10784e-13[/C][C]1.42157e-12[/C][C]1[/C][/ROW]
[ROW][C]148[/C][C]4.10225e-13[/C][C]8.20449e-13[/C][C]1[/C][/ROW]
[ROW][C]149[/C][C]4.18759e-13[/C][C]8.37518e-13[/C][C]1[/C][/ROW]
[ROW][C]150[/C][C]2.34224e-13[/C][C]4.68447e-13[/C][C]1[/C][/ROW]
[ROW][C]151[/C][C]1.44692e-13[/C][C]2.89385e-13[/C][C]1[/C][/ROW]
[ROW][C]152[/C][C]8.19889e-13[/C][C]1.63978e-12[/C][C]1[/C][/ROW]
[ROW][C]153[/C][C]2.421e-11[/C][C]4.842e-11[/C][C]1[/C][/ROW]
[ROW][C]154[/C][C]1.51657e-11[/C][C]3.03315e-11[/C][C]1[/C][/ROW]
[ROW][C]155[/C][C]5.02308e-11[/C][C]1.00462e-10[/C][C]1[/C][/ROW]
[ROW][C]156[/C][C]2.10148e-10[/C][C]4.20296e-10[/C][C]1[/C][/ROW]
[ROW][C]157[/C][C]4.59739e-10[/C][C]9.19478e-10[/C][C]1[/C][/ROW]
[ROW][C]158[/C][C]2.84612e-10[/C][C]5.69224e-10[/C][C]1[/C][/ROW]
[ROW][C]159[/C][C]8.95432e-10[/C][C]1.79086e-09[/C][C]1[/C][/ROW]
[ROW][C]160[/C][C]5.93033e-10[/C][C]1.18607e-09[/C][C]1[/C][/ROW]
[ROW][C]161[/C][C]4.35476e-10[/C][C]8.70952e-10[/C][C]1[/C][/ROW]
[ROW][C]162[/C][C]2.547e-10[/C][C]5.09399e-10[/C][C]1[/C][/ROW]
[ROW][C]163[/C][C]2.40373e-10[/C][C]4.80746e-10[/C][C]1[/C][/ROW]
[ROW][C]164[/C][C]2.90345e-10[/C][C]5.80689e-10[/C][C]1[/C][/ROW]
[ROW][C]165[/C][C]1.96506e-10[/C][C]3.93012e-10[/C][C]1[/C][/ROW]
[ROW][C]166[/C][C]1.5527e-10[/C][C]3.1054e-10[/C][C]1[/C][/ROW]
[ROW][C]167[/C][C]9.89871e-11[/C][C]1.97974e-10[/C][C]1[/C][/ROW]
[ROW][C]168[/C][C]5.34816e-10[/C][C]1.06963e-09[/C][C]1[/C][/ROW]
[ROW][C]169[/C][C]7.44458e-10[/C][C]1.48892e-09[/C][C]1[/C][/ROW]
[ROW][C]170[/C][C]4.68775e-08[/C][C]9.3755e-08[/C][C]1[/C][/ROW]
[ROW][C]171[/C][C]4.83387e-08[/C][C]9.66774e-08[/C][C]1[/C][/ROW]
[ROW][C]172[/C][C]3.40273e-08[/C][C]6.80546e-08[/C][C]1[/C][/ROW]
[ROW][C]173[/C][C]2.29371e-08[/C][C]4.58741e-08[/C][C]1[/C][/ROW]
[ROW][C]174[/C][C]1.5374e-08[/C][C]3.07479e-08[/C][C]1[/C][/ROW]
[ROW][C]175[/C][C]9.88666e-09[/C][C]1.97733e-08[/C][C]1[/C][/ROW]
[ROW][C]176[/C][C]6.07518e-09[/C][C]1.21504e-08[/C][C]1[/C][/ROW]
[ROW][C]177[/C][C]3.75663e-09[/C][C]7.51326e-09[/C][C]1[/C][/ROW]
[ROW][C]178[/C][C]7.78603e-09[/C][C]1.55721e-08[/C][C]1[/C][/ROW]
[ROW][C]179[/C][C]1.54502e-08[/C][C]3.09005e-08[/C][C]1[/C][/ROW]
[ROW][C]180[/C][C]1.00832e-08[/C][C]2.01664e-08[/C][C]1[/C][/ROW]
[ROW][C]181[/C][C]6.51345e-09[/C][C]1.30269e-08[/C][C]1[/C][/ROW]
[ROW][C]182[/C][C]1.24235e-08[/C][C]2.48471e-08[/C][C]1[/C][/ROW]
[ROW][C]183[/C][C]7.59481e-09[/C][C]1.51896e-08[/C][C]1[/C][/ROW]
[ROW][C]184[/C][C]1.56539e-08[/C][C]3.13079e-08[/C][C]1[/C][/ROW]
[ROW][C]185[/C][C]9.87176e-09[/C][C]1.97435e-08[/C][C]1[/C][/ROW]
[ROW][C]186[/C][C]6.35587e-09[/C][C]1.27117e-08[/C][C]1[/C][/ROW]
[ROW][C]187[/C][C]6.57834e-09[/C][C]1.31567e-08[/C][C]1[/C][/ROW]
[ROW][C]188[/C][C]8.73403e-09[/C][C]1.74681e-08[/C][C]1[/C][/ROW]
[ROW][C]189[/C][C]1.00679e-08[/C][C]2.01358e-08[/C][C]1[/C][/ROW]
[ROW][C]190[/C][C]1.5517e-08[/C][C]3.1034e-08[/C][C]1[/C][/ROW]
[ROW][C]191[/C][C]5.44394e-08[/C][C]1.08879e-07[/C][C]1[/C][/ROW]
[ROW][C]192[/C][C]8.54459e-08[/C][C]1.70892e-07[/C][C]1[/C][/ROW]
[ROW][C]193[/C][C]6.81864e-08[/C][C]1.36373e-07[/C][C]1[/C][/ROW]
[ROW][C]194[/C][C]4.43176e-08[/C][C]8.86351e-08[/C][C]1[/C][/ROW]
[ROW][C]195[/C][C]1.22868e-07[/C][C]2.45736e-07[/C][C]1[/C][/ROW]
[ROW][C]196[/C][C]7.48425e-07[/C][C]1.49685e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]197[/C][C]1.7601e-06[/C][C]3.52021e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]198[/C][C]3.87827e-06[/C][C]7.75655e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]199[/C][C]2.85216e-06[/C][C]5.70432e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]200[/C][C]4.61796e-06[/C][C]9.23591e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]201[/C][C]3.83187e-06[/C][C]7.66374e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]202[/C][C]3.57384e-06[/C][C]7.14767e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]203[/C][C]3.86676e-06[/C][C]7.73352e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]204[/C][C]5.89111e-06[/C][C]1.17822e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]205[/C][C]4.5071e-06[/C][C]9.0142e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]206[/C][C]7.16772e-06[/C][C]1.43354e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]207[/C][C]6.38454e-06[/C][C]1.27691e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]208[/C][C]4.62996e-06[/C][C]9.25992e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]209[/C][C]7.72247e-06[/C][C]1.54449e-05[/C][C]0.999992[/C][/ROW]
[ROW][C]210[/C][C]5.19888e-06[/C][C]1.03978e-05[/C][C]0.999995[/C][/ROW]
[ROW][C]211[/C][C]3.86448e-06[/C][C]7.72897e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]212[/C][C]2.64978e-06[/C][C]5.29956e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]213[/C][C]2.47764e-06[/C][C]4.95528e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]214[/C][C]1.74613e-06[/C][C]3.49226e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]215[/C][C]1.76788e-06[/C][C]3.53576e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]216[/C][C]1.28068e-06[/C][C]2.56137e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]217[/C][C]2.25264e-06[/C][C]4.50528e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]218[/C][C]4.38969e-06[/C][C]8.77938e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]219[/C][C]4.50571e-06[/C][C]9.01142e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]220[/C][C]1.38391e-05[/C][C]2.76781e-05[/C][C]0.999986[/C][/ROW]
[ROW][C]221[/C][C]1.08772e-05[/C][C]2.17545e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]222[/C][C]1.06712e-05[/C][C]2.13425e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]223[/C][C]1.04192e-05[/C][C]2.08385e-05[/C][C]0.99999[/C][/ROW]
[ROW][C]224[/C][C]7.60255e-06[/C][C]1.52051e-05[/C][C]0.999992[/C][/ROW]
[ROW][C]225[/C][C]0.000173112[/C][C]0.000346224[/C][C]0.999827[/C][/ROW]
[ROW][C]226[/C][C]0.000128502[/C][C]0.000257005[/C][C]0.999871[/C][/ROW]
[ROW][C]227[/C][C]0.00022765[/C][C]0.000455301[/C][C]0.999772[/C][/ROW]
[ROW][C]228[/C][C]0.000155868[/C][C]0.000311737[/C][C]0.999844[/C][/ROW]
[ROW][C]229[/C][C]0.000171631[/C][C]0.000343262[/C][C]0.999828[/C][/ROW]
[ROW][C]230[/C][C]0.000551836[/C][C]0.00110367[/C][C]0.999448[/C][/ROW]
[ROW][C]231[/C][C]0.000900105[/C][C]0.00180021[/C][C]0.9991[/C][/ROW]
[ROW][C]232[/C][C]0.00232748[/C][C]0.00465497[/C][C]0.997673[/C][/ROW]
[ROW][C]233[/C][C]0.00195794[/C][C]0.00391589[/C][C]0.998042[/C][/ROW]
[ROW][C]234[/C][C]0.00898028[/C][C]0.0179606[/C][C]0.99102[/C][/ROW]
[ROW][C]235[/C][C]0.0117362[/C][C]0.0234724[/C][C]0.988264[/C][/ROW]
[ROW][C]236[/C][C]0.00937912[/C][C]0.0187582[/C][C]0.990621[/C][/ROW]
[ROW][C]237[/C][C]0.00795987[/C][C]0.0159197[/C][C]0.99204[/C][/ROW]
[ROW][C]238[/C][C]0.00768166[/C][C]0.0153633[/C][C]0.992318[/C][/ROW]
[ROW][C]239[/C][C]0.00675712[/C][C]0.0135142[/C][C]0.993243[/C][/ROW]
[ROW][C]240[/C][C]0.00508757[/C][C]0.0101751[/C][C]0.994912[/C][/ROW]
[ROW][C]241[/C][C]0.00388555[/C][C]0.0077711[/C][C]0.996114[/C][/ROW]
[ROW][C]242[/C][C]0.00279323[/C][C]0.00558645[/C][C]0.997207[/C][/ROW]
[ROW][C]243[/C][C]0.013231[/C][C]0.026462[/C][C]0.986769[/C][/ROW]
[ROW][C]244[/C][C]0.0141644[/C][C]0.0283287[/C][C]0.985836[/C][/ROW]
[ROW][C]245[/C][C]0.0202892[/C][C]0.0405784[/C][C]0.979711[/C][/ROW]
[ROW][C]246[/C][C]0.0178032[/C][C]0.0356065[/C][C]0.982197[/C][/ROW]
[ROW][C]247[/C][C]0.0131906[/C][C]0.0263811[/C][C]0.986809[/C][/ROW]
[ROW][C]248[/C][C]0.0269295[/C][C]0.053859[/C][C]0.973071[/C][/ROW]
[ROW][C]249[/C][C]0.0201128[/C][C]0.0402257[/C][C]0.979887[/C][/ROW]
[ROW][C]250[/C][C]0.0485831[/C][C]0.0971662[/C][C]0.951417[/C][/ROW]
[ROW][C]251[/C][C]0.0426631[/C][C]0.0853262[/C][C]0.957337[/C][/ROW]
[ROW][C]252[/C][C]0.0333984[/C][C]0.0667967[/C][C]0.966602[/C][/ROW]
[ROW][C]253[/C][C]0.0686155[/C][C]0.137231[/C][C]0.931385[/C][/ROW]
[ROW][C]254[/C][C]0.0739681[/C][C]0.147936[/C][C]0.926032[/C][/ROW]
[ROW][C]255[/C][C]0.0864128[/C][C]0.172826[/C][C]0.913587[/C][/ROW]
[ROW][C]256[/C][C]0.0687025[/C][C]0.137405[/C][C]0.931297[/C][/ROW]
[ROW][C]257[/C][C]0.172251[/C][C]0.344501[/C][C]0.827749[/C][/ROW]
[ROW][C]258[/C][C]0.152588[/C][C]0.305175[/C][C]0.847412[/C][/ROW]
[ROW][C]259[/C][C]0.12715[/C][C]0.254299[/C][C]0.87285[/C][/ROW]
[ROW][C]260[/C][C]0.142078[/C][C]0.284157[/C][C]0.857922[/C][/ROW]
[ROW][C]261[/C][C]0.184636[/C][C]0.369271[/C][C]0.815364[/C][/ROW]
[ROW][C]262[/C][C]0.177094[/C][C]0.354188[/C][C]0.822906[/C][/ROW]
[ROW][C]263[/C][C]0.141747[/C][C]0.283494[/C][C]0.858253[/C][/ROW]
[ROW][C]264[/C][C]0.136869[/C][C]0.273738[/C][C]0.863131[/C][/ROW]
[ROW][C]265[/C][C]0.102716[/C][C]0.205433[/C][C]0.897284[/C][/ROW]
[ROW][C]266[/C][C]0.126547[/C][C]0.253095[/C][C]0.873453[/C][/ROW]
[ROW][C]267[/C][C]0.114118[/C][C]0.228235[/C][C]0.885882[/C][/ROW]
[ROW][C]268[/C][C]0.159788[/C][C]0.319577[/C][C]0.840212[/C][/ROW]
[ROW][C]269[/C][C]0.144796[/C][C]0.289591[/C][C]0.855204[/C][/ROW]
[ROW][C]270[/C][C]0.116798[/C][C]0.233597[/C][C]0.883202[/C][/ROW]
[ROW][C]271[/C][C]0.286981[/C][C]0.573962[/C][C]0.713019[/C][/ROW]
[ROW][C]272[/C][C]0.228246[/C][C]0.456492[/C][C]0.771754[/C][/ROW]
[ROW][C]273[/C][C]0.165104[/C][C]0.330208[/C][C]0.834896[/C][/ROW]
[ROW][C]274[/C][C]0.110234[/C][C]0.220468[/C][C]0.889766[/C][/ROW]
[ROW][C]275[/C][C]0.0748697[/C][C]0.149739[/C][C]0.92513[/C][/ROW]
[ROW][C]276[/C][C]0.043631[/C][C]0.0872619[/C][C]0.956369[/C][/ROW]
[ROW][C]277[/C][C]0.0874588[/C][C]0.174918[/C][C]0.912541[/C][/ROW]
[ROW][C]278[/C][C]0.101998[/C][C]0.203995[/C][C]0.898002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264028&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264028&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.001904770.003809550.998095
100.01043660.02087320.989563
110.002426570.004853130.997573
120.001436150.00287230.998564
130.0008808870.001761770.999119
140.0002428060.0004856120.999757
150.000164920.000329840.999835
164.52746e-059.05492e-050.999955
171.13944e-052.27889e-050.999989
182.77687e-065.55374e-060.999997
199.6302e-071.92604e-060.999999
202.68242e-075.36483e-071
216.4994e-081.29988e-071
227.46548e-081.4931e-071
231.47154e-072.94308e-071
245.9399e-081.18798e-071
251.07543e-062.15086e-060.999999
263.91444e-077.82889e-071
271.34705e-072.69409e-071
281.46701e-062.93401e-060.999999
295.43258e-071.08652e-060.999999
302.60395e-075.20791e-071
319.48048e-081.8961e-071
323.33166e-086.66332e-081
331.15652e-082.31305e-081
345.17063e-091.03413e-081
351.73343e-093.46686e-091
365.77851e-101.1557e-091
371.85887e-103.71775e-101
387.81608e-111.56322e-101
392.59897e-115.19795e-111
402.10314e-114.20627e-111
417.46919e-121.49384e-111
422.44995e-124.8999e-121
431.10605e-122.21211e-121
444.42105e-138.8421e-131
451.36537e-132.73073e-131
464.4299e-148.8598e-141
471.3495e-142.699e-141
484.85047e-159.70095e-151
491.445e-152.89e-151
504.17965e-168.35931e-161
514.70644e-169.41288e-161
521.90016e-163.80032e-161
531.04458e-162.08916e-161
543.88731e-177.77462e-171
551.11247e-172.22493e-171
564.39498e-188.78997e-181
571.27845e-182.55689e-181
584.57081e-199.14161e-191
591.40088e-192.80176e-191
603.95456e-207.90912e-201
611.1929e-202.38579e-201
623.82017e-217.64034e-211
631.40378e-212.80757e-211
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677.86047e-241.57209e-231
682.1391e-244.27819e-241
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704.53505e-259.0701e-251
711.51546e-253.03093e-251
729.61883e-261.92377e-251
732.86074e-265.72148e-261
747.59697e-271.51939e-261
752.25838e-274.51676e-271
766.59069e-281.31814e-271
771.57665e-273.15331e-271
784.38369e-288.76737e-281
791.93851e-283.87702e-281
805.83887e-291.16777e-281
812.70364e-295.40729e-291
828.23978e-301.64796e-291
832.03121e-304.06242e-301
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852.87652e-315.75304e-311
867.23754e-321.44751e-311
873.37045e-326.7409e-321
882.52296e-265.04591e-261
891.67072e-263.34145e-261
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911.65368e-273.30736e-271
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951.98939e-293.97879e-291
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988.19059e-311.63812e-301
992.47468e-314.94937e-311
1007.44451e-321.4889e-311
1011.31018e-272.62036e-271
1024.13553e-288.27106e-281
1031.32999e-282.65997e-281
1044.3881e-298.77619e-291
1051.37059e-292.74117e-291
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1073.92521e-307.85043e-301
1082.22524e-304.45048e-301
1096.79889e-311.35978e-301
1102.2202e-314.4404e-311
1111.07467e-312.14934e-311
1123.87185e-307.74369e-301
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1697.44458e-101.48892e-091
1704.68775e-089.3755e-081
1714.83387e-089.66774e-081
1723.40273e-086.80546e-081
1732.29371e-084.58741e-081
1741.5374e-083.07479e-081
1759.88666e-091.97733e-081
1766.07518e-091.21504e-081
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1787.78603e-091.55721e-081
1791.54502e-083.09005e-081
1801.00832e-082.01664e-081
1816.51345e-091.30269e-081
1821.24235e-082.48471e-081
1837.59481e-091.51896e-081
1841.56539e-083.13079e-081
1859.87176e-091.97435e-081
1866.35587e-091.27117e-081
1876.57834e-091.31567e-081
1888.73403e-091.74681e-081
1891.00679e-082.01358e-081
1901.5517e-083.1034e-081
1915.44394e-081.08879e-071
1928.54459e-081.70892e-071
1936.81864e-081.36373e-071
1944.43176e-088.86351e-081
1951.22868e-072.45736e-071
1967.48425e-071.49685e-060.999999
1971.7601e-063.52021e-060.999998
1983.87827e-067.75655e-060.999996
1992.85216e-065.70432e-060.999997
2004.61796e-069.23591e-060.999995
2013.83187e-067.66374e-060.999996
2023.57384e-067.14767e-060.999996
2033.86676e-067.73352e-060.999996
2045.89111e-061.17822e-050.999994
2054.5071e-069.0142e-060.999995
2067.16772e-061.43354e-050.999993
2076.38454e-061.27691e-050.999994
2084.62996e-069.25992e-060.999995
2097.72247e-061.54449e-050.999992
2105.19888e-061.03978e-050.999995
2113.86448e-067.72897e-060.999996
2122.64978e-065.29956e-060.999997
2132.47764e-064.95528e-060.999998
2141.74613e-063.49226e-060.999998
2151.76788e-063.53576e-060.999998
2161.28068e-062.56137e-060.999999
2172.25264e-064.50528e-060.999998
2184.38969e-068.77938e-060.999996
2194.50571e-069.01142e-060.999995
2201.38391e-052.76781e-050.999986
2211.08772e-052.17545e-050.999989
2221.06712e-052.13425e-050.999989
2231.04192e-052.08385e-050.99999
2247.60255e-061.52051e-050.999992
2250.0001731120.0003462240.999827
2260.0001285020.0002570050.999871
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2280.0001558680.0003117370.999844
2290.0001716310.0003432620.999828
2300.0005518360.001103670.999448
2310.0009001050.001800210.9991
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2330.001957940.003915890.998042
2340.008980280.01796060.99102
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2360.009379120.01875820.990621
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2390.006757120.01351420.993243
2400.005087570.01017510.994912
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2500.04858310.09716620.951417
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2620.1770940.3541880.822906
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2660.1265470.2530950.873453
2670.1141180.2282350.885882
2680.1597880.3195770.840212
2690.1447960.2895910.855204
2700.1167980.2335970.883202
2710.2869810.5739620.713019
2720.2282460.4564920.771754
2730.1651040.3302080.834896
2740.1102340.2204680.889766
2750.07486970.1497390.92513
2760.0436310.08726190.956369
2770.08745880.1749180.912541
2780.1019980.2039950.898002






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level2260.837037NOK
5% type I error level2400.888889NOK
10% type I error level2450.907407NOK

\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 & 226 & 0.837037 & NOK \tabularnewline
5% type I error level & 240 & 0.888889 & NOK \tabularnewline
10% type I error level & 245 & 0.907407 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264028&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]226[/C][C]0.837037[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]240[/C][C]0.888889[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]245[/C][C]0.907407[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264028&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264028&T=6

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level2260.837037NOK
5% type I error level2400.888889NOK
10% type I error level2450.907407NOK


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- ''
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')
}