FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 09 Dec 2014 19:09:53 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/09/t1418152270772r563fay3g3hg.htm/, Retrieved Thu, 16 May 2024 11:35:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264817, Retrieved Thu, 16 May 2024 11:35:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-09 19:09:53] [a4daf178ee9972867aacc2039fa7f163] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 149 18 68 86 96
12.2 139 31 39 70 70
12.8 148 39 32 71 88
7.4 158 46 62 108 114
6.7 128 31 33 64 69
12.6 224 67 52 119 176
14.8 159 35 62 97 114
13.3 105 52 77 129 121
11.1 159 77 76 153 110
8.2 167 37 41 78 158
11.4 165 32 48 80 116
6.4 159 36 63 99 181
10.6 119 38 30 68 77
12.0 176 69 78 147 141
6.3 54 21 19 40 35
11.3 91 26 31 57 80
11.9 163 54 66 120 152
9.3 124 36 35 71 97
9.6 137 42 42 84 99
10.0 121 23 45 68 84
6.4 153 34 21 55 68
13.8 148 112 25 137 101
10.8 221 35 44 79 107
13.8 188 47 69 116 88
11.7 149 47 54 101 112
10.9 244 37 74 111 171
16.1 148 109 80 189 137
13.4 92 24 42 66 77
9.9 150 20 61 81 66
11.5 153 22 41 63 93
8.3 94 23 46 69 105
11.7 156 32 39 71 131
9.0 132 30 34 64 102
9.7 161 92 51 143 161
10.8 105 43 42 85 120
10.3 97 55 31 86 127
10.4 151 16 39 55 77
12.7 131 49 20 69 108
9.3 166 71 49 120 85
11.8 157 43 53 96 168
5.9 111 29 31 60 48
11.4 145 56 39 95 152
13.0 162 46 54 100 75
10.8 163 19 49 68 107
12.3 59 23 34 57 62
11.3 187 59 46 105 121
11.8 109 30 55 85 124
7.9 90 61 42 103 72
12.7 105 7 50 57 40
12.3 83 38 13 51 58
11.6 116 32 37 69 97
6.7 42 16 25 41 88
10.9 148 19 30 49 126
12.1 155 22 28 50 104
13.3 125 48 45 93 148
10.1 116 23 35 58 146
5.7 128 26 28 54 80
14.3 138 33 41 74 97
8.0 49 9 6 15 25
13.3 96 24 45 69 99
9.3 164 34 73 107 118
12.5 162 48 17 65 58
7.6 99 18 40 58 63
15.9 202 43 64 107 139
9.2 186 33 37 70 50
9.1 66 28 25 53 60
11.1 183 71 65 136 152
13.0 214 26 100 126 142
14.5 188 67 28 95 94
12.2 104 34 35 69 66
12.3 177 80 56 136 127
11.4 126 29 29 58 67
8.8 76 16 43 59 90
14.6 99 59 59 118 75
12.6 139 32 50 82 128
NA 78 47 3 50 41
13.0 162 43 59 102 146
12.6 108 38 27 65 69
13.2 159 29 61 90 186
9.9 74 36 28 64 81
7.7 110 32 51 83 85
10.5 96 35 35 70 54
13.4 116 21 29 50 46
10.9 87 29 48 77 106
4.3 97 12 25 37 34
10.3 127 37 44 81 60
11.8 106 37 64 101 95
11.2 80 47 32 79 57
11.4 74 51 20 71 62
8.6 91 32 28 60 36
13.2 133 21 34 55 56
12.6 74 13 31 44 54
5.6 114 14 26 40 64
9.9 140 -2 58 56 76
8.8 95 20 23 43 98
7.7 98 24 21 45 88
9.0 121 11 21 32 35
7.3 126 23 33 56 102
11.4 98 24 16 40 61
13.6 95 14 20 34 80
7.9 110 52 37 89 49
10.7 70 15 35 50 78
10.3 102 23 33 56 90
8.3 86 19 27 46 45
9.6 130 35 41 76 55
14.2 96 24 40 64 96
8.5 102 39 35 74 43
13.5 100 29 28 57 52
4.9 94 13 32 45 60
6.4 52 8 22 30 54
9.6 98 18 44 62 51
11.6 118 24 27 51 51
11.1 99 19 17 36 38
4.35 48 23 12 34 41
12.7 50 16 45 61 146
18.1 150 33 37 70 182
17.85 154 32 37 69 192
16.6 109 37 108 145 263
12.6 68 14 10 23 35
17.1 194 52 68 120 439
19.1 158 75 72 147 214
16.1 159 72 143 215 341
13.35 67 15 9 24 58
18.4 147 29 55 84 292
14.7 39 13 17 30 85
10.6 100 40 37 77 200
12.6 111 19 27 46 158
16.2 138 24 37 61 199
13.6 101 121 58 178 297
18.9 131 93 66 160 227
14.1 101 36 21 57 108
14.5 114 23 19 42 86
16.15 165 85 78 163 302
14.75 114 41 35 75 148
14.8 111 46 48 94 178
12.45 75 18 27 45 120
12.65 82 35 43 78 207
17.35 121 17 30 47 157
8.6 32 4 25 29 128
18.4 150 28 69 97 296
16.1 117 44 72 116 323
11.6 71 10 23 32 79
17.75 165 38 13 50 70
15.25 154 57 61 118 146
17.65 126 23 43 66 246
16.35 149 36 51 86 196
17.65 145 22 67 89 199
13.6 120 40 36 76 127
14.35 109 31 44 75 153
14.75 132 11 45 57 299
18.25 172 38 34 72 228
9.9 169 24 36 60 190
16 114 37 72 109 180
18.25 156 37 39 76 212
16.85 172 22 43 65 269
14.6 68 15 25 40 130
13.85 89 2 56 58 179
18.95 167 43 80 123 243
15.6 113 31 40 71 190
14.85 115 29 73 102 299
11.75 78 45 34 80 121
18.45 118 25 72 97 137
15.9 87 4 42 46 305
17.1 173 31 61 93 157
16.1 2 -4 23 19 96
19.9 162 66 74 140 183
10.95 49 61 16 78 52
18.45 122 32 66 98 238
15.1 96 31 9 40 40
15 100 39 41 80 226
11.35 82 19 57 76 190
15.95 100 31 48 79 214
18.1 115 36 51 87 145
14.6 141 42 53 95 119
15.4 165 21 29 49 222
15.4 165 21 29 49 222
17.6 110 25 55 80 159
13.35 118 32 54 86 165
19.1 158 26 43 69 249
15.35 146 28 51 79 125
7.6 49 32 20 52 122
13.4 90 41 79 120 186
13.9 121 29 39 69 148
19.1 155 33 61 94 274
15.25 104 17 55 72 172
12.9 147 13 30 43 84
16.1 110 32 55 87 168
17.35 108 30 22 52 102
13.15 113 34 37 71 106
12.15 115 59 2 61 2
12.6 61 13 38 51 139
10.35 60 23 27 50 95
15.4 109 10 56 67 130
9.6 68 5 25 30 72
18.2 111 31 39 70 141
13.6 77 19 33 52 113
14.85 73 32 43 75 206
14.75 151 30 57 87 268
14.1 89 25 43 69 175
14.9 78 48 23 72 77
16.25 110 35 44 79 125
19.25 220 67 54 121 255
13.6 65 15 28 43 111
13.6 141 22 36 58 132
15.65 117 18 39 57 211
12.75 122 33 16 50 92
14.6 63 46 23 69 76
9.85 44 24 40 64 171
12.65 52 14 24 38 83
19.2 131 12 78 90 266
16.6 101 38 57 96 186
11.2 42 12 37 49 50
15.25 152 28 27 56 117
11.9 107 41 61 102 219
13.2 77 12 27 40 246
16.35 154 31 69 100 279
12.4 103 33 34 67 148
15.85 96 34 44 78 137
18.15 175 21 34 55 181
11.15 57 20 39 59 98
15.65 112 44 51 96 226
17.75 143 52 34 86 234
7.65 49 7 31 38 138
12.35 110 29 13 43 85
15.6 131 11 12 23 66
19.3 167 26 51 77 236
15.2 56 24 24 48 106
17.1 137 7 19 26 135
15.6 86 60 30 91 122
18.4 121 13 81 94 218
19.05 149 20 42 62 199
18.55 168 52 22 74 112
19.1 140 28 85 114 278
13.1 88 25 27 52 94
12.85 168 39 25 64 113
9.5 94 9 22 31 84
4.5 51 19 19 38 86
11.85 48 13 14 27 62
13.6 145 60 45 105 222
11.7 66 19 45 64 167
12.4 85 34 28 62 82
13.35 109 14 51 65 207
11.4 63 17 41 58 184
14.9 102 45 31 76 83
19.9 162 66 74 140 183
11.2 86 48 19 68 89
14.6 114 29 51 80 225
17.6 164 -2 73 71 237
14.05 119 51 24 76 102
16.1 126 2 61 63 221
13.35 132 24 23 46 128
11.85 142 40 14 53 91
11.95 83 20 54 74 198
14.75 94 19 51 70 204
15.15 81 16 62 78 158
13.2 166 20 36 56 138
16.85 110 40 59 100 226
7.85 64 27 24 51 44
7.7 93 25 26 52 196
12.6 104 49 54 102 83
7.85 105 39 39 78 79
10.95 49 61 16 78 52
12.35 88 19 36 55 105
9.95 95 67 31 98 116
14.9 102 45 31 76 83
16.65 99 30 42 73 196
13.4 63 8 39 47 153
13.95 76 19 25 45 157
15.7 109 52 31 83 75
16.85 117 22 38 60 106
10.95 57 17 31 48 58
15.35 120 33 17 50 75
12.2 73 34 22 56 74
15.1 91 22 55 77 185
17.75 108 30 62 91 265
15.2 105 25 51 76 131
14.6 117 38 30 68 139
16.65 119 26 49 74 196
8.1 31 13 16 29 78

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264817&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264817&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264817&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.21356 + 0.0110085LFM[t] -0.359242PRH[t] -0.370158CH[t] + 0.362366Hours[t] + 0.0276791Blog[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.21356 +  0.0110085LFM[t] -0.359242PRH[t] -0.370158CH[t] +  0.362366Hours[t] +  0.0276791Blog[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264817&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.21356 +  0.0110085LFM[t] -0.359242PRH[t] -0.370158CH[t] +  0.362366Hours[t] +  0.0276791Blog[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264817&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264817&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.21356 + 0.0110085LFM[t] -0.359242PRH[t] -0.370158CH[t] + 0.362366Hours[t] + 0.0276791Blog[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.213560.54546815.061.10722e-375.53612e-38
LFM0.01100850.004855022.2670.02414730.0120736
PRH-0.3592420.44797-0.80190.4232920.211646
CH-0.3701580.447322-0.82750.4086810.20434
Hours0.3623660.4471560.81040.4184310.209215
Blog0.02767910.002923379.4681.43585e-187.17927e-19

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 8.21356 & 0.545468 & 15.06 & 1.10722e-37 & 5.53612e-38 \tabularnewline
LFM & 0.0110085 & 0.00485502 & 2.267 & 0.0241473 & 0.0120736 \tabularnewline
PRH & -0.359242 & 0.44797 & -0.8019 & 0.423292 & 0.211646 \tabularnewline
CH & -0.370158 & 0.447322 & -0.8275 & 0.408681 & 0.20434 \tabularnewline
Hours & 0.362366 & 0.447156 & 0.8104 & 0.418431 & 0.209215 \tabularnewline
Blog & 0.0276791 & 0.00292337 & 9.468 & 1.43585e-18 & 7.17927e-19 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264817&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]8.21356[/C][C]0.545468[/C][C]15.06[/C][C]1.10722e-37[/C][C]5.53612e-38[/C][/ROW]
[ROW][C]LFM[/C][C]0.0110085[/C][C]0.00485502[/C][C]2.267[/C][C]0.0241473[/C][C]0.0120736[/C][/ROW]
[ROW][C]PRH[/C][C]-0.359242[/C][C]0.44797[/C][C]-0.8019[/C][C]0.423292[/C][C]0.211646[/C][/ROW]
[ROW][C]CH[/C][C]-0.370158[/C][C]0.447322[/C][C]-0.8275[/C][C]0.408681[/C][C]0.20434[/C][/ROW]
[ROW][C]Hours[/C][C]0.362366[/C][C]0.447156[/C][C]0.8104[/C][C]0.418431[/C][C]0.209215[/C][/ROW]
[ROW][C]Blog[/C][C]0.0276791[/C][C]0.00292337[/C][C]9.468[/C][C]1.43585e-18[/C][C]7.17927e-19[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264817&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264817&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.213560.54546815.061.10722e-375.53612e-38
LFM0.01100850.004855022.2670.02414730.0120736
PRH-0.3592420.44797-0.80190.4232920.211646
CH-0.3701580.447322-0.82750.4086810.20434
Hours0.3623660.4471560.81040.4184310.209215
Blog0.02767910.002923379.4681.43585e-187.17927e-19






Multiple Linear Regression - Regression Statistics
Multiple R0.608557
R-squared0.370342
Adjusted R-squared0.358767
F-TEST (value)31.9961
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.7181
Sum Squared Residuals2009.56

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.608557 \tabularnewline
R-squared & 0.370342 \tabularnewline
Adjusted R-squared & 0.358767 \tabularnewline
F-TEST (value) & 31.9961 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 272 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.7181 \tabularnewline
Sum Squared Residuals & 2009.56 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264817&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.608557[/C][/ROW]
[ROW][C]R-squared[/C][C]0.370342[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.358767[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]31.9961[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]272[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.7181[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2009.56[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264817&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264817&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 R0.608557
R-squared0.370342
Adjusted R-squared0.358767
F-TEST (value)31.9961
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.7181
Sum Squared Residuals2009.56






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.03740.862594
212.211.47420.725754
312.812.15110.648917
47.412.7689-5.36894
56.711.3722-4.67222
612.615.3551-2.75513
714.812.74562.05442
813.312.28111.0189
911.112.657-1.55699
108.214.2214-6.02141
1111.412.9667-1.5667
126.414.5954-8.19541
1310.611.5398-0.939825
141213.6616-1.66161
156.39.69435-3.39435
1611.311.26930.0306585
1711.913.8696-1.96961
189.312.1032-2.80324
199.612.2659-2.66591
201011.5919-1.59185
216.411.7226-5.32264
2213.812.79351.00648
2310.813.3746-2.57461
2413.812.32811.47188
2511.712.68-0.97996
2610.915.1718-4.27176
2716.113.3522.74796
2813.411.10542.29465
299.911.2788-1.37883
3011.512.2213-0.721283
318.311.8681-3.56809
3211.713.3529-1.65294
33912.3188-3.31875
349.714.3323-4.6323
3510.812.498-1.69802
3610.312.7269-2.42691
3710.411.7532-1.35324
3812.712.64230.0577352
399.312.2337-2.93371
4011.814.3134-2.51335
415.910.6132-4.71315
4211.413.8881-2.48809
431311.79581.20418
4410.812.6472-1.84717
4512.310.38611.9139
4611.313.4472-2.14722
4711.812.5109-0.710864
487.911.0605-3.16053
4912.710.10892.59111
5012.310.75011.54992
5111.611.9871-0.387093
526.710.9669-4.26687
5310.913.156-2.25599
5412.112.6491-0.549065
5513.313.4855-0.185454
5610.113.3308-3.23083
575.711.7-6.00003
5814.312.20122.09876
5989.42632-1.42632
6013.311.7351.56505
619.312.8225-3.5225
6212.511.61980.880173
637.610.7917-3.19174
6415.913.92031.97967
659.211.4599-2.2599
669.110.4935-1.39355
6711.114.1507-3.05068
681313.8018-0.80185
6914.512.87611.62386
7012.211.01881.18123
7112.313.4909-1.1909
7211.411.31980.0802311
738.811.2563-2.45626
7414.611.10393.49606
7512.612.997-0.397045
76NANA-0.712703
771311.62071.37933
7812.614.1275-1.52752
7913.214.4645-1.26449
809.913.6798-3.7798
817.77.80168-0.101678
8210.57.703432.79657
8313.414.3219-0.921873
8410.916.6652-5.76517
854.35.04514-0.745138
8610.310.12690.173113
8711.811.16940.630556
8811.210.54780.652211
8911.412.8936-1.49358
908.66.428412.17159
9113.210.92192.27807
9212.618.0811-5.48114
935.67.10018-1.50018
949.912.9552-3.05519
958.812.7395-3.93951
967.79.0851-1.3851
97913.9386-4.93862
987.36.831130.46887
9911.49.16162.2384
10013.616.3549-2.75493
1017.98.11727-0.21727
10210.712.0423-1.34227
10310.312.2548-1.95483
1048.39.6569-1.3569
1059.67.090872.50913
10614.216.0758-1.87576
1078.55.626152.87385
10813.519.3004-5.80038
1094.98.63424-3.73424
1106.47.21742-0.817419
1119.68.78880.811202
11211.610.78210.817893
11311.116.2428-5.1428
1144.354.154480.195519
11512.79.317233.38277
11618.115.28492.81507
11717.8517.21720.632849
11816.613.53443.06564
11912.617.6329-5.03294
12017.113.54953.55048
12119.121.5132-2.41317
12216.113.28332.81675
12313.3512.52620.82385
12418.414.60383.79623
12514.718.7869-4.08689
12610.611.6578-1.05778
12712.611.42761.17245
12816.219.7098-3.50983
12913.610.77752.82253
13018.917.06361.8364
13114.111.37272.72726
13214.516.3968-1.89683
13316.1514.4581.69196
13414.7514.08210.667918
13514.814.55650.243458
13612.4514.4201-1.97012
13712.659.010563.63944
13817.3520.6765-3.32645
1398.67.807680.79232
14018.420.3183-1.91834
14116.115.17150.928526
14211.65.472566.12744
14317.7516.15281.59721
14415.2513.74651.50351
14517.6515.93161.71835
14616.3513.56462.78539
14717.6516.94430.705716
14813.612.65240.947607
14914.3517.5888-3.23883
15014.7512.77171.97835
15118.2523.4775-5.2275
1529.97.905341.99466
1531613.36062.63943
15418.2518.6864-0.436379
15516.8514.66252.18752
15614.614.46780.132226
15713.8511.1892.66101
15818.9517.85171.09828
15915.618.0274-2.42737
16014.8515.7594-0.909422
16111.756.121695.62831
16218.4519.8487-1.39866
16315.913.24762.65244
16417.111.70115.39894
16516.110.89185.20819
16619.919.57060.32944
16710.958.229932.72007
16818.4513.75434.69573
16915.115.4723-0.372258
1701517.6405-2.6405
17111.3510.36060.989428
17215.9511.05814.89191
17318.116.27781.82218
17414.614.852-0.252
17515.415.652-0.252
17615.411.2754.12498
17717.618.0088-0.408824
17813.3510.84122.50883
17919.116.72082.37922
18015.3519.824-4.47396
1817.68.06516-0.465164
18213.413.29120.108822
18313.911.93171.96826
18419.117.59381.5062
18515.2514.31370.936286
18612.910.5462.354
18716.110.89815.20195
18817.3516.40940.940573
18913.1510.70362.44636
19012.1512.0270.123007
19112.613.6151-1.01506
19210.357.919032.43097
19315.416.5759-1.17586
1949.64.531225.06878
19518.216.59121.60882
19613.613.2340.366007
19714.8517.0434-2.19343
19814.7514.7926-0.0425754
19914.110.73663.36337
20014.911.30093.59912
20116.2514.48221.76784
20219.2517.48021.76982
20313.613.20760.392376
20413.613.04420.555806
20515.6515.34390.30613
20612.759.125213.62479
20714.617.9444-3.34436
2089.858.14011.7099
20912.659.898032.75197
21019.217.11072.08933
21116.615.20911.39094
21211.29.314771.88523
21315.2518.456-3.20597
21411.914.7597-2.85974
21513.214.0405-0.840543
21616.3517.2321-0.882115
21712.49.375793.02421
21815.8512.65063.19935
21918.1518.3122-0.162194
22011.1511.3044-0.154428
22115.6514.06221.58778
22217.7522.453-4.70301
2237.657.428890.221107
22412.358.173364.17664
22515.612.56813.03191
22619.315.7523.54801
22715.211.43223.76777
22817.114.35322.7468
22915.612.18913.4109
23018.414.44723.95281
23119.0513.65415.39591
23218.5516.68711.86293
23319.117.65191.44813
23413.113.3678-0.267775
23512.8514.7801-1.9301
2369.516.0667-6.56671
2374.53.03961.4604
23811.8514.0414-2.19137
23913.615.1713-1.57125
24011.710.6071.09298
24112.413.8394-1.43941
24213.3515.6837-2.33369
24311.48.032833.36717
24414.99.691815.20819
24519.920.688-0.788012
24611.211.9895-0.789538
24714.613.00381.59616
24817.616.23151.36847
24914.0513.19870.851348
25016.115.4930.606991
25113.3513.4491-0.0990825
25211.8514.1494-2.29944
25311.9511.75690.193136
25414.7512.64542.10457
25515.1515.5927-0.442664
25613.212.05761.14242
25716.8519.0333-2.18333
2587.8515.0503-7.20033
2597.76.125761.57424
26012.616.1241-3.52406
2617.857.520560.32944
26210.9510.46750.482536
26312.3514.8379-2.48791
2649.956.582833.36717
26514.913.10731.79267
26616.6516.11310.536896
26713.413.07280.327249
26813.959.660334.28967
26915.711.05824.64182
27016.8516.1580.692006
27110.957.181153.76885
27215.3514.15021.19977
27312.211.07611.12386
27415.113.33571.7643
27517.7515.22612.52387
27615.213.83391.36609
27714.612.23572.36427
27816.6519.1797-2.52974
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.0374 & 0.862594 \tabularnewline
2 & 12.2 & 11.4742 & 0.725754 \tabularnewline
3 & 12.8 & 12.1511 & 0.648917 \tabularnewline
4 & 7.4 & 12.7689 & -5.36894 \tabularnewline
5 & 6.7 & 11.3722 & -4.67222 \tabularnewline
6 & 12.6 & 15.3551 & -2.75513 \tabularnewline
7 & 14.8 & 12.7456 & 2.05442 \tabularnewline
8 & 13.3 & 12.2811 & 1.0189 \tabularnewline
9 & 11.1 & 12.657 & -1.55699 \tabularnewline
10 & 8.2 & 14.2214 & -6.02141 \tabularnewline
11 & 11.4 & 12.9667 & -1.5667 \tabularnewline
12 & 6.4 & 14.5954 & -8.19541 \tabularnewline
13 & 10.6 & 11.5398 & -0.939825 \tabularnewline
14 & 12 & 13.6616 & -1.66161 \tabularnewline
15 & 6.3 & 9.69435 & -3.39435 \tabularnewline
16 & 11.3 & 11.2693 & 0.0306585 \tabularnewline
17 & 11.9 & 13.8696 & -1.96961 \tabularnewline
18 & 9.3 & 12.1032 & -2.80324 \tabularnewline
19 & 9.6 & 12.2659 & -2.66591 \tabularnewline
20 & 10 & 11.5919 & -1.59185 \tabularnewline
21 & 6.4 & 11.7226 & -5.32264 \tabularnewline
22 & 13.8 & 12.7935 & 1.00648 \tabularnewline
23 & 10.8 & 13.3746 & -2.57461 \tabularnewline
24 & 13.8 & 12.3281 & 1.47188 \tabularnewline
25 & 11.7 & 12.68 & -0.97996 \tabularnewline
26 & 10.9 & 15.1718 & -4.27176 \tabularnewline
27 & 16.1 & 13.352 & 2.74796 \tabularnewline
28 & 13.4 & 11.1054 & 2.29465 \tabularnewline
29 & 9.9 & 11.2788 & -1.37883 \tabularnewline
30 & 11.5 & 12.2213 & -0.721283 \tabularnewline
31 & 8.3 & 11.8681 & -3.56809 \tabularnewline
32 & 11.7 & 13.3529 & -1.65294 \tabularnewline
33 & 9 & 12.3188 & -3.31875 \tabularnewline
34 & 9.7 & 14.3323 & -4.6323 \tabularnewline
35 & 10.8 & 12.498 & -1.69802 \tabularnewline
36 & 10.3 & 12.7269 & -2.42691 \tabularnewline
37 & 10.4 & 11.7532 & -1.35324 \tabularnewline
38 & 12.7 & 12.6423 & 0.0577352 \tabularnewline
39 & 9.3 & 12.2337 & -2.93371 \tabularnewline
40 & 11.8 & 14.3134 & -2.51335 \tabularnewline
41 & 5.9 & 10.6132 & -4.71315 \tabularnewline
42 & 11.4 & 13.8881 & -2.48809 \tabularnewline
43 & 13 & 11.7958 & 1.20418 \tabularnewline
44 & 10.8 & 12.6472 & -1.84717 \tabularnewline
45 & 12.3 & 10.3861 & 1.9139 \tabularnewline
46 & 11.3 & 13.4472 & -2.14722 \tabularnewline
47 & 11.8 & 12.5109 & -0.710864 \tabularnewline
48 & 7.9 & 11.0605 & -3.16053 \tabularnewline
49 & 12.7 & 10.1089 & 2.59111 \tabularnewline
50 & 12.3 & 10.7501 & 1.54992 \tabularnewline
51 & 11.6 & 11.9871 & -0.387093 \tabularnewline
52 & 6.7 & 10.9669 & -4.26687 \tabularnewline
53 & 10.9 & 13.156 & -2.25599 \tabularnewline
54 & 12.1 & 12.6491 & -0.549065 \tabularnewline
55 & 13.3 & 13.4855 & -0.185454 \tabularnewline
56 & 10.1 & 13.3308 & -3.23083 \tabularnewline
57 & 5.7 & 11.7 & -6.00003 \tabularnewline
58 & 14.3 & 12.2012 & 2.09876 \tabularnewline
59 & 8 & 9.42632 & -1.42632 \tabularnewline
60 & 13.3 & 11.735 & 1.56505 \tabularnewline
61 & 9.3 & 12.8225 & -3.5225 \tabularnewline
62 & 12.5 & 11.6198 & 0.880173 \tabularnewline
63 & 7.6 & 10.7917 & -3.19174 \tabularnewline
64 & 15.9 & 13.9203 & 1.97967 \tabularnewline
65 & 9.2 & 11.4599 & -2.2599 \tabularnewline
66 & 9.1 & 10.4935 & -1.39355 \tabularnewline
67 & 11.1 & 14.1507 & -3.05068 \tabularnewline
68 & 13 & 13.8018 & -0.80185 \tabularnewline
69 & 14.5 & 12.8761 & 1.62386 \tabularnewline
70 & 12.2 & 11.0188 & 1.18123 \tabularnewline
71 & 12.3 & 13.4909 & -1.1909 \tabularnewline
72 & 11.4 & 11.3198 & 0.0802311 \tabularnewline
73 & 8.8 & 11.2563 & -2.45626 \tabularnewline
74 & 14.6 & 11.1039 & 3.49606 \tabularnewline
75 & 12.6 & 12.997 & -0.397045 \tabularnewline
76 & NA & NA & -0.712703 \tabularnewline
77 & 13 & 11.6207 & 1.37933 \tabularnewline
78 & 12.6 & 14.1275 & -1.52752 \tabularnewline
79 & 13.2 & 14.4645 & -1.26449 \tabularnewline
80 & 9.9 & 13.6798 & -3.7798 \tabularnewline
81 & 7.7 & 7.80168 & -0.101678 \tabularnewline
82 & 10.5 & 7.70343 & 2.79657 \tabularnewline
83 & 13.4 & 14.3219 & -0.921873 \tabularnewline
84 & 10.9 & 16.6652 & -5.76517 \tabularnewline
85 & 4.3 & 5.04514 & -0.745138 \tabularnewline
86 & 10.3 & 10.1269 & 0.173113 \tabularnewline
87 & 11.8 & 11.1694 & 0.630556 \tabularnewline
88 & 11.2 & 10.5478 & 0.652211 \tabularnewline
89 & 11.4 & 12.8936 & -1.49358 \tabularnewline
90 & 8.6 & 6.42841 & 2.17159 \tabularnewline
91 & 13.2 & 10.9219 & 2.27807 \tabularnewline
92 & 12.6 & 18.0811 & -5.48114 \tabularnewline
93 & 5.6 & 7.10018 & -1.50018 \tabularnewline
94 & 9.9 & 12.9552 & -3.05519 \tabularnewline
95 & 8.8 & 12.7395 & -3.93951 \tabularnewline
96 & 7.7 & 9.0851 & -1.3851 \tabularnewline
97 & 9 & 13.9386 & -4.93862 \tabularnewline
98 & 7.3 & 6.83113 & 0.46887 \tabularnewline
99 & 11.4 & 9.1616 & 2.2384 \tabularnewline
100 & 13.6 & 16.3549 & -2.75493 \tabularnewline
101 & 7.9 & 8.11727 & -0.21727 \tabularnewline
102 & 10.7 & 12.0423 & -1.34227 \tabularnewline
103 & 10.3 & 12.2548 & -1.95483 \tabularnewline
104 & 8.3 & 9.6569 & -1.3569 \tabularnewline
105 & 9.6 & 7.09087 & 2.50913 \tabularnewline
106 & 14.2 & 16.0758 & -1.87576 \tabularnewline
107 & 8.5 & 5.62615 & 2.87385 \tabularnewline
108 & 13.5 & 19.3004 & -5.80038 \tabularnewline
109 & 4.9 & 8.63424 & -3.73424 \tabularnewline
110 & 6.4 & 7.21742 & -0.817419 \tabularnewline
111 & 9.6 & 8.7888 & 0.811202 \tabularnewline
112 & 11.6 & 10.7821 & 0.817893 \tabularnewline
113 & 11.1 & 16.2428 & -5.1428 \tabularnewline
114 & 4.35 & 4.15448 & 0.195519 \tabularnewline
115 & 12.7 & 9.31723 & 3.38277 \tabularnewline
116 & 18.1 & 15.2849 & 2.81507 \tabularnewline
117 & 17.85 & 17.2172 & 0.632849 \tabularnewline
118 & 16.6 & 13.5344 & 3.06564 \tabularnewline
119 & 12.6 & 17.6329 & -5.03294 \tabularnewline
120 & 17.1 & 13.5495 & 3.55048 \tabularnewline
121 & 19.1 & 21.5132 & -2.41317 \tabularnewline
122 & 16.1 & 13.2833 & 2.81675 \tabularnewline
123 & 13.35 & 12.5262 & 0.82385 \tabularnewline
124 & 18.4 & 14.6038 & 3.79623 \tabularnewline
125 & 14.7 & 18.7869 & -4.08689 \tabularnewline
126 & 10.6 & 11.6578 & -1.05778 \tabularnewline
127 & 12.6 & 11.4276 & 1.17245 \tabularnewline
128 & 16.2 & 19.7098 & -3.50983 \tabularnewline
129 & 13.6 & 10.7775 & 2.82253 \tabularnewline
130 & 18.9 & 17.0636 & 1.8364 \tabularnewline
131 & 14.1 & 11.3727 & 2.72726 \tabularnewline
132 & 14.5 & 16.3968 & -1.89683 \tabularnewline
133 & 16.15 & 14.458 & 1.69196 \tabularnewline
134 & 14.75 & 14.0821 & 0.667918 \tabularnewline
135 & 14.8 & 14.5565 & 0.243458 \tabularnewline
136 & 12.45 & 14.4201 & -1.97012 \tabularnewline
137 & 12.65 & 9.01056 & 3.63944 \tabularnewline
138 & 17.35 & 20.6765 & -3.32645 \tabularnewline
139 & 8.6 & 7.80768 & 0.79232 \tabularnewline
140 & 18.4 & 20.3183 & -1.91834 \tabularnewline
141 & 16.1 & 15.1715 & 0.928526 \tabularnewline
142 & 11.6 & 5.47256 & 6.12744 \tabularnewline
143 & 17.75 & 16.1528 & 1.59721 \tabularnewline
144 & 15.25 & 13.7465 & 1.50351 \tabularnewline
145 & 17.65 & 15.9316 & 1.71835 \tabularnewline
146 & 16.35 & 13.5646 & 2.78539 \tabularnewline
147 & 17.65 & 16.9443 & 0.705716 \tabularnewline
148 & 13.6 & 12.6524 & 0.947607 \tabularnewline
149 & 14.35 & 17.5888 & -3.23883 \tabularnewline
150 & 14.75 & 12.7717 & 1.97835 \tabularnewline
151 & 18.25 & 23.4775 & -5.2275 \tabularnewline
152 & 9.9 & 7.90534 & 1.99466 \tabularnewline
153 & 16 & 13.3606 & 2.63943 \tabularnewline
154 & 18.25 & 18.6864 & -0.436379 \tabularnewline
155 & 16.85 & 14.6625 & 2.18752 \tabularnewline
156 & 14.6 & 14.4678 & 0.132226 \tabularnewline
157 & 13.85 & 11.189 & 2.66101 \tabularnewline
158 & 18.95 & 17.8517 & 1.09828 \tabularnewline
159 & 15.6 & 18.0274 & -2.42737 \tabularnewline
160 & 14.85 & 15.7594 & -0.909422 \tabularnewline
161 & 11.75 & 6.12169 & 5.62831 \tabularnewline
162 & 18.45 & 19.8487 & -1.39866 \tabularnewline
163 & 15.9 & 13.2476 & 2.65244 \tabularnewline
164 & 17.1 & 11.7011 & 5.39894 \tabularnewline
165 & 16.1 & 10.8918 & 5.20819 \tabularnewline
166 & 19.9 & 19.5706 & 0.32944 \tabularnewline
167 & 10.95 & 8.22993 & 2.72007 \tabularnewline
168 & 18.45 & 13.7543 & 4.69573 \tabularnewline
169 & 15.1 & 15.4723 & -0.372258 \tabularnewline
170 & 15 & 17.6405 & -2.6405 \tabularnewline
171 & 11.35 & 10.3606 & 0.989428 \tabularnewline
172 & 15.95 & 11.0581 & 4.89191 \tabularnewline
173 & 18.1 & 16.2778 & 1.82218 \tabularnewline
174 & 14.6 & 14.852 & -0.252 \tabularnewline
175 & 15.4 & 15.652 & -0.252 \tabularnewline
176 & 15.4 & 11.275 & 4.12498 \tabularnewline
177 & 17.6 & 18.0088 & -0.408824 \tabularnewline
178 & 13.35 & 10.8412 & 2.50883 \tabularnewline
179 & 19.1 & 16.7208 & 2.37922 \tabularnewline
180 & 15.35 & 19.824 & -4.47396 \tabularnewline
181 & 7.6 & 8.06516 & -0.465164 \tabularnewline
182 & 13.4 & 13.2912 & 0.108822 \tabularnewline
183 & 13.9 & 11.9317 & 1.96826 \tabularnewline
184 & 19.1 & 17.5938 & 1.5062 \tabularnewline
185 & 15.25 & 14.3137 & 0.936286 \tabularnewline
186 & 12.9 & 10.546 & 2.354 \tabularnewline
187 & 16.1 & 10.8981 & 5.20195 \tabularnewline
188 & 17.35 & 16.4094 & 0.940573 \tabularnewline
189 & 13.15 & 10.7036 & 2.44636 \tabularnewline
190 & 12.15 & 12.027 & 0.123007 \tabularnewline
191 & 12.6 & 13.6151 & -1.01506 \tabularnewline
192 & 10.35 & 7.91903 & 2.43097 \tabularnewline
193 & 15.4 & 16.5759 & -1.17586 \tabularnewline
194 & 9.6 & 4.53122 & 5.06878 \tabularnewline
195 & 18.2 & 16.5912 & 1.60882 \tabularnewline
196 & 13.6 & 13.234 & 0.366007 \tabularnewline
197 & 14.85 & 17.0434 & -2.19343 \tabularnewline
198 & 14.75 & 14.7926 & -0.0425754 \tabularnewline
199 & 14.1 & 10.7366 & 3.36337 \tabularnewline
200 & 14.9 & 11.3009 & 3.59912 \tabularnewline
201 & 16.25 & 14.4822 & 1.76784 \tabularnewline
202 & 19.25 & 17.4802 & 1.76982 \tabularnewline
203 & 13.6 & 13.2076 & 0.392376 \tabularnewline
204 & 13.6 & 13.0442 & 0.555806 \tabularnewline
205 & 15.65 & 15.3439 & 0.30613 \tabularnewline
206 & 12.75 & 9.12521 & 3.62479 \tabularnewline
207 & 14.6 & 17.9444 & -3.34436 \tabularnewline
208 & 9.85 & 8.1401 & 1.7099 \tabularnewline
209 & 12.65 & 9.89803 & 2.75197 \tabularnewline
210 & 19.2 & 17.1107 & 2.08933 \tabularnewline
211 & 16.6 & 15.2091 & 1.39094 \tabularnewline
212 & 11.2 & 9.31477 & 1.88523 \tabularnewline
213 & 15.25 & 18.456 & -3.20597 \tabularnewline
214 & 11.9 & 14.7597 & -2.85974 \tabularnewline
215 & 13.2 & 14.0405 & -0.840543 \tabularnewline
216 & 16.35 & 17.2321 & -0.882115 \tabularnewline
217 & 12.4 & 9.37579 & 3.02421 \tabularnewline
218 & 15.85 & 12.6506 & 3.19935 \tabularnewline
219 & 18.15 & 18.3122 & -0.162194 \tabularnewline
220 & 11.15 & 11.3044 & -0.154428 \tabularnewline
221 & 15.65 & 14.0622 & 1.58778 \tabularnewline
222 & 17.75 & 22.453 & -4.70301 \tabularnewline
223 & 7.65 & 7.42889 & 0.221107 \tabularnewline
224 & 12.35 & 8.17336 & 4.17664 \tabularnewline
225 & 15.6 & 12.5681 & 3.03191 \tabularnewline
226 & 19.3 & 15.752 & 3.54801 \tabularnewline
227 & 15.2 & 11.4322 & 3.76777 \tabularnewline
228 & 17.1 & 14.3532 & 2.7468 \tabularnewline
229 & 15.6 & 12.1891 & 3.4109 \tabularnewline
230 & 18.4 & 14.4472 & 3.95281 \tabularnewline
231 & 19.05 & 13.6541 & 5.39591 \tabularnewline
232 & 18.55 & 16.6871 & 1.86293 \tabularnewline
233 & 19.1 & 17.6519 & 1.44813 \tabularnewline
234 & 13.1 & 13.3678 & -0.267775 \tabularnewline
235 & 12.85 & 14.7801 & -1.9301 \tabularnewline
236 & 9.5 & 16.0667 & -6.56671 \tabularnewline
237 & 4.5 & 3.0396 & 1.4604 \tabularnewline
238 & 11.85 & 14.0414 & -2.19137 \tabularnewline
239 & 13.6 & 15.1713 & -1.57125 \tabularnewline
240 & 11.7 & 10.607 & 1.09298 \tabularnewline
241 & 12.4 & 13.8394 & -1.43941 \tabularnewline
242 & 13.35 & 15.6837 & -2.33369 \tabularnewline
243 & 11.4 & 8.03283 & 3.36717 \tabularnewline
244 & 14.9 & 9.69181 & 5.20819 \tabularnewline
245 & 19.9 & 20.688 & -0.788012 \tabularnewline
246 & 11.2 & 11.9895 & -0.789538 \tabularnewline
247 & 14.6 & 13.0038 & 1.59616 \tabularnewline
248 & 17.6 & 16.2315 & 1.36847 \tabularnewline
249 & 14.05 & 13.1987 & 0.851348 \tabularnewline
250 & 16.1 & 15.493 & 0.606991 \tabularnewline
251 & 13.35 & 13.4491 & -0.0990825 \tabularnewline
252 & 11.85 & 14.1494 & -2.29944 \tabularnewline
253 & 11.95 & 11.7569 & 0.193136 \tabularnewline
254 & 14.75 & 12.6454 & 2.10457 \tabularnewline
255 & 15.15 & 15.5927 & -0.442664 \tabularnewline
256 & 13.2 & 12.0576 & 1.14242 \tabularnewline
257 & 16.85 & 19.0333 & -2.18333 \tabularnewline
258 & 7.85 & 15.0503 & -7.20033 \tabularnewline
259 & 7.7 & 6.12576 & 1.57424 \tabularnewline
260 & 12.6 & 16.1241 & -3.52406 \tabularnewline
261 & 7.85 & 7.52056 & 0.32944 \tabularnewline
262 & 10.95 & 10.4675 & 0.482536 \tabularnewline
263 & 12.35 & 14.8379 & -2.48791 \tabularnewline
264 & 9.95 & 6.58283 & 3.36717 \tabularnewline
265 & 14.9 & 13.1073 & 1.79267 \tabularnewline
266 & 16.65 & 16.1131 & 0.536896 \tabularnewline
267 & 13.4 & 13.0728 & 0.327249 \tabularnewline
268 & 13.95 & 9.66033 & 4.28967 \tabularnewline
269 & 15.7 & 11.0582 & 4.64182 \tabularnewline
270 & 16.85 & 16.158 & 0.692006 \tabularnewline
271 & 10.95 & 7.18115 & 3.76885 \tabularnewline
272 & 15.35 & 14.1502 & 1.19977 \tabularnewline
273 & 12.2 & 11.0761 & 1.12386 \tabularnewline
274 & 15.1 & 13.3357 & 1.7643 \tabularnewline
275 & 17.75 & 15.2261 & 2.52387 \tabularnewline
276 & 15.2 & 13.8339 & 1.36609 \tabularnewline
277 & 14.6 & 12.2357 & 2.36427 \tabularnewline
278 & 16.65 & 19.1797 & -2.52974 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264817&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]12.0374[/C][C]0.862594[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]11.4742[/C][C]0.725754[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]12.1511[/C][C]0.648917[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.7689[/C][C]-5.36894[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]11.3722[/C][C]-4.67222[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]15.3551[/C][C]-2.75513[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.7456[/C][C]2.05442[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]12.2811[/C][C]1.0189[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.657[/C][C]-1.55699[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.2214[/C][C]-6.02141[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.9667[/C][C]-1.5667[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.5954[/C][C]-8.19541[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.5398[/C][C]-0.939825[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.6616[/C][C]-1.66161[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]9.69435[/C][C]-3.39435[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.2693[/C][C]0.0306585[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]13.8696[/C][C]-1.96961[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.1032[/C][C]-2.80324[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.2659[/C][C]-2.66591[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]11.5919[/C][C]-1.59185[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]11.7226[/C][C]-5.32264[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.7935[/C][C]1.00648[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]13.3746[/C][C]-2.57461[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.3281[/C][C]1.47188[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]12.68[/C][C]-0.97996[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]15.1718[/C][C]-4.27176[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.352[/C][C]2.74796[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]11.1054[/C][C]2.29465[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.2788[/C][C]-1.37883[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.2213[/C][C]-0.721283[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.8681[/C][C]-3.56809[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.3529[/C][C]-1.65294[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.3188[/C][C]-3.31875[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]14.3323[/C][C]-4.6323[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.498[/C][C]-1.69802[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.7269[/C][C]-2.42691[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.7532[/C][C]-1.35324[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.6423[/C][C]0.0577352[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]12.2337[/C][C]-2.93371[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.3134[/C][C]-2.51335[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.6132[/C][C]-4.71315[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.8881[/C][C]-2.48809[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.7958[/C][C]1.20418[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.6472[/C][C]-1.84717[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]10.3861[/C][C]1.9139[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.4472[/C][C]-2.14722[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.5109[/C][C]-0.710864[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]11.0605[/C][C]-3.16053[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.1089[/C][C]2.59111[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]10.7501[/C][C]1.54992[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]11.9871[/C][C]-0.387093[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.9669[/C][C]-4.26687[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.156[/C][C]-2.25599[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.6491[/C][C]-0.549065[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.4855[/C][C]-0.185454[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.3308[/C][C]-3.23083[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.7[/C][C]-6.00003[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.2012[/C][C]2.09876[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]9.42632[/C][C]-1.42632[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]11.735[/C][C]1.56505[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.8225[/C][C]-3.5225[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.6198[/C][C]0.880173[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]10.7917[/C][C]-3.19174[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.9203[/C][C]1.97967[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.4599[/C][C]-2.2599[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]10.4935[/C][C]-1.39355[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]14.1507[/C][C]-3.05068[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.8018[/C][C]-0.80185[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.8761[/C][C]1.62386[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.0188[/C][C]1.18123[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.4909[/C][C]-1.1909[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]11.3198[/C][C]0.0802311[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.2563[/C][C]-2.45626[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.1039[/C][C]3.49606[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.997[/C][C]-0.397045[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]-0.712703[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.6207[/C][C]1.37933[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]14.1275[/C][C]-1.52752[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]14.4645[/C][C]-1.26449[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]13.6798[/C][C]-3.7798[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]7.80168[/C][C]-0.101678[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]7.70343[/C][C]2.79657[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]14.3219[/C][C]-0.921873[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]16.6652[/C][C]-5.76517[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]5.04514[/C][C]-0.745138[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]10.1269[/C][C]0.173113[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]11.1694[/C][C]0.630556[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]10.5478[/C][C]0.652211[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]12.8936[/C][C]-1.49358[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]6.42841[/C][C]2.17159[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]10.9219[/C][C]2.27807[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]18.0811[/C][C]-5.48114[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]7.10018[/C][C]-1.50018[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]12.9552[/C][C]-3.05519[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]12.7395[/C][C]-3.93951[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]9.0851[/C][C]-1.3851[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]13.9386[/C][C]-4.93862[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]6.83113[/C][C]0.46887[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]9.1616[/C][C]2.2384[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]16.3549[/C][C]-2.75493[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]8.11727[/C][C]-0.21727[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]12.0423[/C][C]-1.34227[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]12.2548[/C][C]-1.95483[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]9.6569[/C][C]-1.3569[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]7.09087[/C][C]2.50913[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]16.0758[/C][C]-1.87576[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]5.62615[/C][C]2.87385[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]19.3004[/C][C]-5.80038[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]8.63424[/C][C]-3.73424[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]7.21742[/C][C]-0.817419[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]8.7888[/C][C]0.811202[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]10.7821[/C][C]0.817893[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]16.2428[/C][C]-5.1428[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]4.15448[/C][C]0.195519[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]9.31723[/C][C]3.38277[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]15.2849[/C][C]2.81507[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]17.2172[/C][C]0.632849[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]13.5344[/C][C]3.06564[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]17.6329[/C][C]-5.03294[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]13.5495[/C][C]3.55048[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]21.5132[/C][C]-2.41317[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]13.2833[/C][C]2.81675[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]12.5262[/C][C]0.82385[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]14.6038[/C][C]3.79623[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]18.7869[/C][C]-4.08689[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.6578[/C][C]-1.05778[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]11.4276[/C][C]1.17245[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]19.7098[/C][C]-3.50983[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]10.7775[/C][C]2.82253[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]17.0636[/C][C]1.8364[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]11.3727[/C][C]2.72726[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]16.3968[/C][C]-1.89683[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.458[/C][C]1.69196[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]14.0821[/C][C]0.667918[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]14.5565[/C][C]0.243458[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]14.4201[/C][C]-1.97012[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.01056[/C][C]3.63944[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]20.6765[/C][C]-3.32645[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]7.80768[/C][C]0.79232[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]20.3183[/C][C]-1.91834[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]15.1715[/C][C]0.928526[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]5.47256[/C][C]6.12744[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]16.1528[/C][C]1.59721[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]13.7465[/C][C]1.50351[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]15.9316[/C][C]1.71835[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]13.5646[/C][C]2.78539[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]16.9443[/C][C]0.705716[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.6524[/C][C]0.947607[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]17.5888[/C][C]-3.23883[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]12.7717[/C][C]1.97835[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]23.4775[/C][C]-5.2275[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]7.90534[/C][C]1.99466[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]13.3606[/C][C]2.63943[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]18.6864[/C][C]-0.436379[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]14.6625[/C][C]2.18752[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]14.4678[/C][C]0.132226[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]11.189[/C][C]2.66101[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]17.8517[/C][C]1.09828[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]18.0274[/C][C]-2.42737[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.7594[/C][C]-0.909422[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]6.12169[/C][C]5.62831[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]19.8487[/C][C]-1.39866[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]13.2476[/C][C]2.65244[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]11.7011[/C][C]5.39894[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]10.8918[/C][C]5.20819[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]19.5706[/C][C]0.32944[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]8.22993[/C][C]2.72007[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]13.7543[/C][C]4.69573[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]15.4723[/C][C]-0.372258[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]17.6405[/C][C]-2.6405[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]10.3606[/C][C]0.989428[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]11.0581[/C][C]4.89191[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]16.2778[/C][C]1.82218[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]14.852[/C][C]-0.252[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]15.652[/C][C]-0.252[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]11.275[/C][C]4.12498[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]18.0088[/C][C]-0.408824[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]10.8412[/C][C]2.50883[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]16.7208[/C][C]2.37922[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]19.824[/C][C]-4.47396[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]8.06516[/C][C]-0.465164[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]13.2912[/C][C]0.108822[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]11.9317[/C][C]1.96826[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]17.5938[/C][C]1.5062[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]14.3137[/C][C]0.936286[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]10.546[/C][C]2.354[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]10.8981[/C][C]5.20195[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]16.4094[/C][C]0.940573[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]10.7036[/C][C]2.44636[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]12.027[/C][C]0.123007[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]13.6151[/C][C]-1.01506[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]7.91903[/C][C]2.43097[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]16.5759[/C][C]-1.17586[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]4.53122[/C][C]5.06878[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]16.5912[/C][C]1.60882[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]13.234[/C][C]0.366007[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]17.0434[/C][C]-2.19343[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]14.7926[/C][C]-0.0425754[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]10.7366[/C][C]3.36337[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.3009[/C][C]3.59912[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]14.4822[/C][C]1.76784[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]17.4802[/C][C]1.76982[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.2076[/C][C]0.392376[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]13.0442[/C][C]0.555806[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]15.3439[/C][C]0.30613[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]9.12521[/C][C]3.62479[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]17.9444[/C][C]-3.34436[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]8.1401[/C][C]1.7099[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]9.89803[/C][C]2.75197[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]17.1107[/C][C]2.08933[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]15.2091[/C][C]1.39094[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]9.31477[/C][C]1.88523[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]18.456[/C][C]-3.20597[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]14.7597[/C][C]-2.85974[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]14.0405[/C][C]-0.840543[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]17.2321[/C][C]-0.882115[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.37579[/C][C]3.02421[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]12.6506[/C][C]3.19935[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]18.3122[/C][C]-0.162194[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]11.3044[/C][C]-0.154428[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]14.0622[/C][C]1.58778[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]22.453[/C][C]-4.70301[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]7.42889[/C][C]0.221107[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]8.17336[/C][C]4.17664[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]12.5681[/C][C]3.03191[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]15.752[/C][C]3.54801[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]11.4322[/C][C]3.76777[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]14.3532[/C][C]2.7468[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]12.1891[/C][C]3.4109[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]14.4472[/C][C]3.95281[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]13.6541[/C][C]5.39591[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]16.6871[/C][C]1.86293[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]17.6519[/C][C]1.44813[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]13.3678[/C][C]-0.267775[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]14.7801[/C][C]-1.9301[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]16.0667[/C][C]-6.56671[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]3.0396[/C][C]1.4604[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]14.0414[/C][C]-2.19137[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]15.1713[/C][C]-1.57125[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]10.607[/C][C]1.09298[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.8394[/C][C]-1.43941[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]15.6837[/C][C]-2.33369[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]8.03283[/C][C]3.36717[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]9.69181[/C][C]5.20819[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]20.688[/C][C]-0.788012[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]11.9895[/C][C]-0.789538[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]13.0038[/C][C]1.59616[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]16.2315[/C][C]1.36847[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]13.1987[/C][C]0.851348[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]15.493[/C][C]0.606991[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]13.4491[/C][C]-0.0990825[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]14.1494[/C][C]-2.29944[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.7569[/C][C]0.193136[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]12.6454[/C][C]2.10457[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]15.5927[/C][C]-0.442664[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]12.0576[/C][C]1.14242[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]19.0333[/C][C]-2.18333[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]15.0503[/C][C]-7.20033[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]6.12576[/C][C]1.57424[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]16.1241[/C][C]-3.52406[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]7.52056[/C][C]0.32944[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]10.4675[/C][C]0.482536[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]14.8379[/C][C]-2.48791[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]6.58283[/C][C]3.36717[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]13.1073[/C][C]1.79267[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.1131[/C][C]0.536896[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]13.0728[/C][C]0.327249[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]9.66033[/C][C]4.28967[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]11.0582[/C][C]4.64182[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]16.158[/C][C]0.692006[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]7.18115[/C][C]3.76885[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]14.1502[/C][C]1.19977[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]11.0761[/C][C]1.12386[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]13.3357[/C][C]1.7643[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.2261[/C][C]2.52387[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]13.8339[/C][C]1.36609[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]12.2357[/C][C]2.36427[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]19.1797[/C][C]-2.52974[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264817&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264817&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.03740.862594
212.211.47420.725754
312.812.15110.648917
47.412.7689-5.36894
56.711.3722-4.67222
612.615.3551-2.75513
714.812.74562.05442
813.312.28111.0189
911.112.657-1.55699
108.214.2214-6.02141
1111.412.9667-1.5667
126.414.5954-8.19541
1310.611.5398-0.939825
141213.6616-1.66161
156.39.69435-3.39435
1611.311.26930.0306585
1711.913.8696-1.96961
189.312.1032-2.80324
199.612.2659-2.66591
201011.5919-1.59185
216.411.7226-5.32264
2213.812.79351.00648
2310.813.3746-2.57461
2413.812.32811.47188
2511.712.68-0.97996
2610.915.1718-4.27176
2716.113.3522.74796
2813.411.10542.29465
299.911.2788-1.37883
3011.512.2213-0.721283
318.311.8681-3.56809
3211.713.3529-1.65294
33912.3188-3.31875
349.714.3323-4.6323
3510.812.498-1.69802
3610.312.7269-2.42691
3710.411.7532-1.35324
3812.712.64230.0577352
399.312.2337-2.93371
4011.814.3134-2.51335
415.910.6132-4.71315
4211.413.8881-2.48809
431311.79581.20418
4410.812.6472-1.84717
4512.310.38611.9139
4611.313.4472-2.14722
4711.812.5109-0.710864
487.911.0605-3.16053
4912.710.10892.59111
5012.310.75011.54992
5111.611.9871-0.387093
526.710.9669-4.26687
5310.913.156-2.25599
5412.112.6491-0.549065
5513.313.4855-0.185454
5610.113.3308-3.23083
575.711.7-6.00003
5814.312.20122.09876
5989.42632-1.42632
6013.311.7351.56505
619.312.8225-3.5225
6212.511.61980.880173
637.610.7917-3.19174
6415.913.92031.97967
659.211.4599-2.2599
669.110.4935-1.39355
6711.114.1507-3.05068
681313.8018-0.80185
6914.512.87611.62386
7012.211.01881.18123
7112.313.4909-1.1909
7211.411.31980.0802311
738.811.2563-2.45626
7414.611.10393.49606
7512.612.997-0.397045
76NANA-0.712703
771311.62071.37933
7812.614.1275-1.52752
7913.214.4645-1.26449
809.913.6798-3.7798
817.77.80168-0.101678
8210.57.703432.79657
8313.414.3219-0.921873
8410.916.6652-5.76517
854.35.04514-0.745138
8610.310.12690.173113
8711.811.16940.630556
8811.210.54780.652211
8911.412.8936-1.49358
908.66.428412.17159
9113.210.92192.27807
9212.618.0811-5.48114
935.67.10018-1.50018
949.912.9552-3.05519
958.812.7395-3.93951
967.79.0851-1.3851
97913.9386-4.93862
987.36.831130.46887
9911.49.16162.2384
10013.616.3549-2.75493
1017.98.11727-0.21727
10210.712.0423-1.34227
10310.312.2548-1.95483
1048.39.6569-1.3569
1059.67.090872.50913
10614.216.0758-1.87576
1078.55.626152.87385
10813.519.3004-5.80038
1094.98.63424-3.73424
1106.47.21742-0.817419
1119.68.78880.811202
11211.610.78210.817893
11311.116.2428-5.1428
1144.354.154480.195519
11512.79.317233.38277
11618.115.28492.81507
11717.8517.21720.632849
11816.613.53443.06564
11912.617.6329-5.03294
12017.113.54953.55048
12119.121.5132-2.41317
12216.113.28332.81675
12313.3512.52620.82385
12418.414.60383.79623
12514.718.7869-4.08689
12610.611.6578-1.05778
12712.611.42761.17245
12816.219.7098-3.50983
12913.610.77752.82253
13018.917.06361.8364
13114.111.37272.72726
13214.516.3968-1.89683
13316.1514.4581.69196
13414.7514.08210.667918
13514.814.55650.243458
13612.4514.4201-1.97012
13712.659.010563.63944
13817.3520.6765-3.32645
1398.67.807680.79232
14018.420.3183-1.91834
14116.115.17150.928526
14211.65.472566.12744
14317.7516.15281.59721
14415.2513.74651.50351
14517.6515.93161.71835
14616.3513.56462.78539
14717.6516.94430.705716
14813.612.65240.947607
14914.3517.5888-3.23883
15014.7512.77171.97835
15118.2523.4775-5.2275
1529.97.905341.99466
1531613.36062.63943
15418.2518.6864-0.436379
15516.8514.66252.18752
15614.614.46780.132226
15713.8511.1892.66101
15818.9517.85171.09828
15915.618.0274-2.42737
16014.8515.7594-0.909422
16111.756.121695.62831
16218.4519.8487-1.39866
16315.913.24762.65244
16417.111.70115.39894
16516.110.89185.20819
16619.919.57060.32944
16710.958.229932.72007
16818.4513.75434.69573
16915.115.4723-0.372258
1701517.6405-2.6405
17111.3510.36060.989428
17215.9511.05814.89191
17318.116.27781.82218
17414.614.852-0.252
17515.415.652-0.252
17615.411.2754.12498
17717.618.0088-0.408824
17813.3510.84122.50883
17919.116.72082.37922
18015.3519.824-4.47396
1817.68.06516-0.465164
18213.413.29120.108822
18313.911.93171.96826
18419.117.59381.5062
18515.2514.31370.936286
18612.910.5462.354
18716.110.89815.20195
18817.3516.40940.940573
18913.1510.70362.44636
19012.1512.0270.123007
19112.613.6151-1.01506
19210.357.919032.43097
19315.416.5759-1.17586
1949.64.531225.06878
19518.216.59121.60882
19613.613.2340.366007
19714.8517.0434-2.19343
19814.7514.7926-0.0425754
19914.110.73663.36337
20014.911.30093.59912
20116.2514.48221.76784
20219.2517.48021.76982
20313.613.20760.392376
20413.613.04420.555806
20515.6515.34390.30613
20612.759.125213.62479
20714.617.9444-3.34436
2089.858.14011.7099
20912.659.898032.75197
21019.217.11072.08933
21116.615.20911.39094
21211.29.314771.88523
21315.2518.456-3.20597
21411.914.7597-2.85974
21513.214.0405-0.840543
21616.3517.2321-0.882115
21712.49.375793.02421
21815.8512.65063.19935
21918.1518.3122-0.162194
22011.1511.3044-0.154428
22115.6514.06221.58778
22217.7522.453-4.70301
2237.657.428890.221107
22412.358.173364.17664
22515.612.56813.03191
22619.315.7523.54801
22715.211.43223.76777
22817.114.35322.7468
22915.612.18913.4109
23018.414.44723.95281
23119.0513.65415.39591
23218.5516.68711.86293
23319.117.65191.44813
23413.113.3678-0.267775
23512.8514.7801-1.9301
2369.516.0667-6.56671
2374.53.03961.4604
23811.8514.0414-2.19137
23913.615.1713-1.57125
24011.710.6071.09298
24112.413.8394-1.43941
24213.3515.6837-2.33369
24311.48.032833.36717
24414.99.691815.20819
24519.920.688-0.788012
24611.211.9895-0.789538
24714.613.00381.59616
24817.616.23151.36847
24914.0513.19870.851348
25016.115.4930.606991
25113.3513.4491-0.0990825
25211.8514.1494-2.29944
25311.9511.75690.193136
25414.7512.64542.10457
25515.1515.5927-0.442664
25613.212.05761.14242
25716.8519.0333-2.18333
2587.8515.0503-7.20033
2597.76.125761.57424
26012.616.1241-3.52406
2617.857.520560.32944
26210.9510.46750.482536
26312.3514.8379-2.48791
2649.956.582833.36717
26514.913.10731.79267
26616.6516.11310.536896
26713.413.07280.327249
26813.959.660334.28967
26915.711.05824.64182
27016.8516.1580.692006
27110.957.181153.76885
27215.3514.15021.19977
27312.211.07611.12386
27415.113.33571.7643
27517.7515.22612.52387
27615.213.83391.36609
27714.612.23572.36427
27816.6519.1797-2.52974
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9072230.1855540.0927769
100.9051520.1896950.0948477
110.8388140.3223720.161186
120.8692030.2615930.130797
130.8126360.3747290.187364
140.7371120.5257750.262888
150.6757320.6485350.324268
160.6889160.6221680.311084
170.624280.751440.37572
180.5444350.9111310.455565
190.4694350.9388710.530565
200.3927520.7855050.607248
210.46630.9326010.5337
220.4804090.9608180.519591
230.4152770.8305550.584723
240.3508670.7017340.649133
250.2925570.5851130.707443
260.2547050.509410.745295
270.2156420.4312850.784358
280.2754570.5509140.724543
290.2464510.4929020.753549
300.2221230.4442450.777877
310.1921770.3843540.807823
320.1895050.379010.810495
330.1587190.3174380.841281
340.1623020.3246050.837698
350.1360040.2720080.863996
360.1121710.2243430.887829
370.08940580.1788120.910594
380.1040590.2081180.895941
390.1251180.2502360.874882
400.1116620.2233240.888338
410.1706660.3413330.829334
420.1479190.2958390.852081
430.130470.260940.86953
440.1102080.2204170.889792
450.1138640.2277280.886136
460.09648370.1929670.903516
470.08056880.1611380.919431
480.1003030.2006060.899697
490.09877730.1975550.901223
500.1058180.2116370.894182
510.09113630.1822730.908864
520.09596980.191940.90403
530.08733190.1746640.912668
540.08534560.1706910.914654
550.08628370.1725670.913716
560.07467680.1493540.925323
570.1303420.2606840.869658
580.1590540.3181070.840946
590.135580.2711590.86442
600.141170.282340.85883
610.1566080.3132160.843392
620.1496810.2993620.850319
630.1579610.3159220.842039
640.1940130.3880250.805987
650.1932920.3865840.806708
660.1683720.3367440.831628
670.1697060.3394120.830294
680.1562710.3125410.843729
690.1664960.3329920.833504
700.1538780.3077550.846122
710.1406110.2812230.859389
720.1243290.2486580.875671
730.1123120.2246240.887688
740.1185590.2371170.881441
750.1102470.2204950.889753
760.1021330.2042650.897867
770.09708970.1941790.90291
780.09620530.1924110.903795
790.08163660.1632730.918363
800.1046160.2092310.895384
810.08889040.1777810.91111
820.09851280.1970260.901487
830.0845010.1690020.915499
840.1787370.3574740.821263
850.1641480.3282960.835852
860.1446540.2893080.855346
870.1253930.2507870.874607
880.1098750.2197490.890125
890.103520.207040.89648
900.1073510.2147020.892649
910.1126210.2252420.887379
920.1876630.3753270.812337
930.1887030.3774070.811297
940.1832590.3665180.816741
950.2000390.4000770.799961
960.1950.390.805
970.2657020.5314030.734298
980.2529990.5059980.747001
990.2974820.5949640.702518
1000.354210.7084210.64579
1010.3275930.6551870.672407
1020.3119860.6239720.688014
1030.3149550.6299110.685045
1040.3325670.6651350.667433
1050.3640480.7280950.635952
1060.3911090.7822180.608891
1070.4087230.8174460.591277
1080.6288490.7423020.371151
1090.674130.651740.32587
1100.6840540.6318930.315946
1110.6786280.6427440.321372
1120.6667360.6665270.333264
1130.7282230.5435540.271777
1140.7213690.5572620.278631
1150.8325060.3349880.167494
1160.8829670.2340660.117033
1170.8717580.2564850.128242
1180.914750.17050.08525
1190.9091990.1816010.0908007
1200.9272040.1455920.0727961
1210.939640.1207190.0603597
1220.948690.102620.0513099
1230.951390.09721910.0486096
1240.9699720.06005610.030028
1250.9740840.05183180.0259159
1260.969770.06045910.0302296
1270.9691110.06177750.0308888
1280.9659950.06801040.0340052
1290.9646910.07061780.0353089
1300.9630580.07388480.0369424
1310.965340.06932030.0346602
1320.9635930.07281470.0364074
1330.9666430.06671320.0333566
1340.9612410.07751730.0387586
1350.9540770.0918470.0459235
1360.947060.1058810.0529404
1370.9620150.07597090.0379855
1380.9620790.07584250.0379213
1390.9584310.08313750.0415687
1400.9511160.09776880.0488844
1410.9459810.1080380.0540188
1420.973390.05321970.0266098
1430.9723090.05538280.0276914
1440.9723750.05525030.0276251
1450.9685140.06297170.0314858
1460.9691280.06174370.0308718
1470.9642330.07153350.0357668
1480.9585140.08297130.0414856
1490.9531220.09375540.0468777
1500.951920.09616050.0480802
1510.982090.03581970.0179098
1520.980110.0397810.0198905
1530.9809350.03812950.0190647
1540.9769450.04610980.0230549
1550.9780250.043950.021975
1560.9734710.05305870.0265294
1570.9723310.05533770.0276688
1580.9679480.06410350.0320518
1590.9658590.06828190.034141
1600.9602450.07950940.0397547
1610.9727280.05454490.0272725
1620.9682260.06354890.0317745
1630.9692030.06159480.0307974
1640.9939310.01213760.00606879
1650.9952470.009506570.00475329
1660.9939050.01218960.0060948
1670.9938210.01235780.00617892
1680.9960940.00781250.00390625
1690.9949660.01006840.00503422
1700.9952170.00956650.00478325
1710.9942690.01146230.00573116
1720.9961090.007781820.00389091
1730.9956520.008695740.00434787
1740.99440.01119920.00559962
1750.9928590.01428170.00714085
1760.9940510.01189710.00594856
1770.9932830.01343470.00671734
1780.993290.013420.00671002
1790.9923790.01524110.00762054
1800.9940230.01195410.00597706
1810.9935350.01293070.00646534
1820.9921380.01572490.00786243
1830.9909050.01819060.00909528
1840.9886870.0226260.011313
1850.987920.02416010.0120801
1860.9858520.02829690.0141484
1870.9925690.01486160.00743079
1880.9908630.01827360.00913678
1890.9891870.02162610.0108131
1900.9862740.02745180.0137259
1910.9830440.03391260.0169563
1920.9799810.04003770.0200189
1930.9772610.04547750.0227387
1940.9858870.02822630.0141131
1950.9831960.03360740.0168037
1960.981010.03797980.0189899
1970.980850.03830080.0191504
1980.9756720.04865640.0243282
1990.977430.04513920.0225696
2000.9769050.04619080.0230954
2010.9734050.0531890.0265945
2020.97190.05620030.0281002
2030.9683030.06339350.0316968
2040.9614010.0771990.0385995
2050.9537520.09249660.0462483
2060.9654230.06915360.0345768
2070.9618250.07634980.0381749
2080.9604580.07908440.0395422
2090.9560250.08795040.0439752
2100.9488290.1023420.0511711
2110.9388130.1223730.0611867
2120.9279780.1440440.0720219
2130.9415240.1169510.0584757
2140.9321710.1356580.0678292
2150.9286970.1426070.0713035
2160.9162840.1674310.0837156
2170.9133680.1732630.0866317
2180.9028690.1942620.0971311
2190.8822510.2354970.117749
2200.8589120.2821760.141088
2210.8445070.3109860.155493
2220.8634050.273190.136595
2230.8381240.3237530.161876
2240.8442980.3114040.155702
2250.8303920.3392160.169608
2260.8894390.2211230.110561
2270.9112030.1775940.0887972
2280.9133680.1732630.0866315
2290.899730.200540.10027
2300.9162350.167530.0837649
2310.9431930.1136150.0568073
2320.9282110.1435770.0717886
2330.9153390.1693210.0846607
2340.9040660.1918680.0959339
2350.8952010.2095980.104799
2360.9628380.0743240.037162
2370.961690.07661970.0383099
2380.9631090.07378290.0368914
2390.9526610.09467750.0473387
2400.9378570.1242850.0621426
2410.9264780.1470450.0735223
2420.9098450.180310.090155
2430.9041850.191630.0958149
2440.8916480.2167050.108352
2450.8625420.2749150.137458
2460.8313460.3373090.168654
2470.7987020.4025960.201298
2480.7565480.4869040.243452
2490.7074760.5850480.292524
2500.6502420.6995160.349758
2510.5990430.8019140.400957
2520.5976720.8046560.402328
2530.5315310.9369390.468469
2540.466620.9332390.53338
2550.5222890.9554220.477711
2560.4539390.9078780.546061
2570.4532230.9064450.546777
2580.8927250.214550.107275
2590.8512250.297550.148775
2600.9954340.009131150.00456557
2610.9965910.006818230.00340912
2620.9970250.005949530.00297476
2630.9997990.00040110.00020055
2640.9993490.001301640.000650819
2650.9978660.004267660.00213383
2660.9956320.008735480.00436774
2670.9941620.0116770.00583848
2680.9818050.03638930.0181947
2690.9703860.05922790.0296139
2700.8854750.2290490.114525

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.907223 & 0.185554 & 0.0927769 \tabularnewline
10 & 0.905152 & 0.189695 & 0.0948477 \tabularnewline
11 & 0.838814 & 0.322372 & 0.161186 \tabularnewline
12 & 0.869203 & 0.261593 & 0.130797 \tabularnewline
13 & 0.812636 & 0.374729 & 0.187364 \tabularnewline
14 & 0.737112 & 0.525775 & 0.262888 \tabularnewline
15 & 0.675732 & 0.648535 & 0.324268 \tabularnewline
16 & 0.688916 & 0.622168 & 0.311084 \tabularnewline
17 & 0.62428 & 0.75144 & 0.37572 \tabularnewline
18 & 0.544435 & 0.911131 & 0.455565 \tabularnewline
19 & 0.469435 & 0.938871 & 0.530565 \tabularnewline
20 & 0.392752 & 0.785505 & 0.607248 \tabularnewline
21 & 0.4663 & 0.932601 & 0.5337 \tabularnewline
22 & 0.480409 & 0.960818 & 0.519591 \tabularnewline
23 & 0.415277 & 0.830555 & 0.584723 \tabularnewline
24 & 0.350867 & 0.701734 & 0.649133 \tabularnewline
25 & 0.292557 & 0.585113 & 0.707443 \tabularnewline
26 & 0.254705 & 0.50941 & 0.745295 \tabularnewline
27 & 0.215642 & 0.431285 & 0.784358 \tabularnewline
28 & 0.275457 & 0.550914 & 0.724543 \tabularnewline
29 & 0.246451 & 0.492902 & 0.753549 \tabularnewline
30 & 0.222123 & 0.444245 & 0.777877 \tabularnewline
31 & 0.192177 & 0.384354 & 0.807823 \tabularnewline
32 & 0.189505 & 0.37901 & 0.810495 \tabularnewline
33 & 0.158719 & 0.317438 & 0.841281 \tabularnewline
34 & 0.162302 & 0.324605 & 0.837698 \tabularnewline
35 & 0.136004 & 0.272008 & 0.863996 \tabularnewline
36 & 0.112171 & 0.224343 & 0.887829 \tabularnewline
37 & 0.0894058 & 0.178812 & 0.910594 \tabularnewline
38 & 0.104059 & 0.208118 & 0.895941 \tabularnewline
39 & 0.125118 & 0.250236 & 0.874882 \tabularnewline
40 & 0.111662 & 0.223324 & 0.888338 \tabularnewline
41 & 0.170666 & 0.341333 & 0.829334 \tabularnewline
42 & 0.147919 & 0.295839 & 0.852081 \tabularnewline
43 & 0.13047 & 0.26094 & 0.86953 \tabularnewline
44 & 0.110208 & 0.220417 & 0.889792 \tabularnewline
45 & 0.113864 & 0.227728 & 0.886136 \tabularnewline
46 & 0.0964837 & 0.192967 & 0.903516 \tabularnewline
47 & 0.0805688 & 0.161138 & 0.919431 \tabularnewline
48 & 0.100303 & 0.200606 & 0.899697 \tabularnewline
49 & 0.0987773 & 0.197555 & 0.901223 \tabularnewline
50 & 0.105818 & 0.211637 & 0.894182 \tabularnewline
51 & 0.0911363 & 0.182273 & 0.908864 \tabularnewline
52 & 0.0959698 & 0.19194 & 0.90403 \tabularnewline
53 & 0.0873319 & 0.174664 & 0.912668 \tabularnewline
54 & 0.0853456 & 0.170691 & 0.914654 \tabularnewline
55 & 0.0862837 & 0.172567 & 0.913716 \tabularnewline
56 & 0.0746768 & 0.149354 & 0.925323 \tabularnewline
57 & 0.130342 & 0.260684 & 0.869658 \tabularnewline
58 & 0.159054 & 0.318107 & 0.840946 \tabularnewline
59 & 0.13558 & 0.271159 & 0.86442 \tabularnewline
60 & 0.14117 & 0.28234 & 0.85883 \tabularnewline
61 & 0.156608 & 0.313216 & 0.843392 \tabularnewline
62 & 0.149681 & 0.299362 & 0.850319 \tabularnewline
63 & 0.157961 & 0.315922 & 0.842039 \tabularnewline
64 & 0.194013 & 0.388025 & 0.805987 \tabularnewline
65 & 0.193292 & 0.386584 & 0.806708 \tabularnewline
66 & 0.168372 & 0.336744 & 0.831628 \tabularnewline
67 & 0.169706 & 0.339412 & 0.830294 \tabularnewline
68 & 0.156271 & 0.312541 & 0.843729 \tabularnewline
69 & 0.166496 & 0.332992 & 0.833504 \tabularnewline
70 & 0.153878 & 0.307755 & 0.846122 \tabularnewline
71 & 0.140611 & 0.281223 & 0.859389 \tabularnewline
72 & 0.124329 & 0.248658 & 0.875671 \tabularnewline
73 & 0.112312 & 0.224624 & 0.887688 \tabularnewline
74 & 0.118559 & 0.237117 & 0.881441 \tabularnewline
75 & 0.110247 & 0.220495 & 0.889753 \tabularnewline
76 & 0.102133 & 0.204265 & 0.897867 \tabularnewline
77 & 0.0970897 & 0.194179 & 0.90291 \tabularnewline
78 & 0.0962053 & 0.192411 & 0.903795 \tabularnewline
79 & 0.0816366 & 0.163273 & 0.918363 \tabularnewline
80 & 0.104616 & 0.209231 & 0.895384 \tabularnewline
81 & 0.0888904 & 0.177781 & 0.91111 \tabularnewline
82 & 0.0985128 & 0.197026 & 0.901487 \tabularnewline
83 & 0.084501 & 0.169002 & 0.915499 \tabularnewline
84 & 0.178737 & 0.357474 & 0.821263 \tabularnewline
85 & 0.164148 & 0.328296 & 0.835852 \tabularnewline
86 & 0.144654 & 0.289308 & 0.855346 \tabularnewline
87 & 0.125393 & 0.250787 & 0.874607 \tabularnewline
88 & 0.109875 & 0.219749 & 0.890125 \tabularnewline
89 & 0.10352 & 0.20704 & 0.89648 \tabularnewline
90 & 0.107351 & 0.214702 & 0.892649 \tabularnewline
91 & 0.112621 & 0.225242 & 0.887379 \tabularnewline
92 & 0.187663 & 0.375327 & 0.812337 \tabularnewline
93 & 0.188703 & 0.377407 & 0.811297 \tabularnewline
94 & 0.183259 & 0.366518 & 0.816741 \tabularnewline
95 & 0.200039 & 0.400077 & 0.799961 \tabularnewline
96 & 0.195 & 0.39 & 0.805 \tabularnewline
97 & 0.265702 & 0.531403 & 0.734298 \tabularnewline
98 & 0.252999 & 0.505998 & 0.747001 \tabularnewline
99 & 0.297482 & 0.594964 & 0.702518 \tabularnewline
100 & 0.35421 & 0.708421 & 0.64579 \tabularnewline
101 & 0.327593 & 0.655187 & 0.672407 \tabularnewline
102 & 0.311986 & 0.623972 & 0.688014 \tabularnewline
103 & 0.314955 & 0.629911 & 0.685045 \tabularnewline
104 & 0.332567 & 0.665135 & 0.667433 \tabularnewline
105 & 0.364048 & 0.728095 & 0.635952 \tabularnewline
106 & 0.391109 & 0.782218 & 0.608891 \tabularnewline
107 & 0.408723 & 0.817446 & 0.591277 \tabularnewline
108 & 0.628849 & 0.742302 & 0.371151 \tabularnewline
109 & 0.67413 & 0.65174 & 0.32587 \tabularnewline
110 & 0.684054 & 0.631893 & 0.315946 \tabularnewline
111 & 0.678628 & 0.642744 & 0.321372 \tabularnewline
112 & 0.666736 & 0.666527 & 0.333264 \tabularnewline
113 & 0.728223 & 0.543554 & 0.271777 \tabularnewline
114 & 0.721369 & 0.557262 & 0.278631 \tabularnewline
115 & 0.832506 & 0.334988 & 0.167494 \tabularnewline
116 & 0.882967 & 0.234066 & 0.117033 \tabularnewline
117 & 0.871758 & 0.256485 & 0.128242 \tabularnewline
118 & 0.91475 & 0.1705 & 0.08525 \tabularnewline
119 & 0.909199 & 0.181601 & 0.0908007 \tabularnewline
120 & 0.927204 & 0.145592 & 0.0727961 \tabularnewline
121 & 0.93964 & 0.120719 & 0.0603597 \tabularnewline
122 & 0.94869 & 0.10262 & 0.0513099 \tabularnewline
123 & 0.95139 & 0.0972191 & 0.0486096 \tabularnewline
124 & 0.969972 & 0.0600561 & 0.030028 \tabularnewline
125 & 0.974084 & 0.0518318 & 0.0259159 \tabularnewline
126 & 0.96977 & 0.0604591 & 0.0302296 \tabularnewline
127 & 0.969111 & 0.0617775 & 0.0308888 \tabularnewline
128 & 0.965995 & 0.0680104 & 0.0340052 \tabularnewline
129 & 0.964691 & 0.0706178 & 0.0353089 \tabularnewline
130 & 0.963058 & 0.0738848 & 0.0369424 \tabularnewline
131 & 0.96534 & 0.0693203 & 0.0346602 \tabularnewline
132 & 0.963593 & 0.0728147 & 0.0364074 \tabularnewline
133 & 0.966643 & 0.0667132 & 0.0333566 \tabularnewline
134 & 0.961241 & 0.0775173 & 0.0387586 \tabularnewline
135 & 0.954077 & 0.091847 & 0.0459235 \tabularnewline
136 & 0.94706 & 0.105881 & 0.0529404 \tabularnewline
137 & 0.962015 & 0.0759709 & 0.0379855 \tabularnewline
138 & 0.962079 & 0.0758425 & 0.0379213 \tabularnewline
139 & 0.958431 & 0.0831375 & 0.0415687 \tabularnewline
140 & 0.951116 & 0.0977688 & 0.0488844 \tabularnewline
141 & 0.945981 & 0.108038 & 0.0540188 \tabularnewline
142 & 0.97339 & 0.0532197 & 0.0266098 \tabularnewline
143 & 0.972309 & 0.0553828 & 0.0276914 \tabularnewline
144 & 0.972375 & 0.0552503 & 0.0276251 \tabularnewline
145 & 0.968514 & 0.0629717 & 0.0314858 \tabularnewline
146 & 0.969128 & 0.0617437 & 0.0308718 \tabularnewline
147 & 0.964233 & 0.0715335 & 0.0357668 \tabularnewline
148 & 0.958514 & 0.0829713 & 0.0414856 \tabularnewline
149 & 0.953122 & 0.0937554 & 0.0468777 \tabularnewline
150 & 0.95192 & 0.0961605 & 0.0480802 \tabularnewline
151 & 0.98209 & 0.0358197 & 0.0179098 \tabularnewline
152 & 0.98011 & 0.039781 & 0.0198905 \tabularnewline
153 & 0.980935 & 0.0381295 & 0.0190647 \tabularnewline
154 & 0.976945 & 0.0461098 & 0.0230549 \tabularnewline
155 & 0.978025 & 0.04395 & 0.021975 \tabularnewline
156 & 0.973471 & 0.0530587 & 0.0265294 \tabularnewline
157 & 0.972331 & 0.0553377 & 0.0276688 \tabularnewline
158 & 0.967948 & 0.0641035 & 0.0320518 \tabularnewline
159 & 0.965859 & 0.0682819 & 0.034141 \tabularnewline
160 & 0.960245 & 0.0795094 & 0.0397547 \tabularnewline
161 & 0.972728 & 0.0545449 & 0.0272725 \tabularnewline
162 & 0.968226 & 0.0635489 & 0.0317745 \tabularnewline
163 & 0.969203 & 0.0615948 & 0.0307974 \tabularnewline
164 & 0.993931 & 0.0121376 & 0.00606879 \tabularnewline
165 & 0.995247 & 0.00950657 & 0.00475329 \tabularnewline
166 & 0.993905 & 0.0121896 & 0.0060948 \tabularnewline
167 & 0.993821 & 0.0123578 & 0.00617892 \tabularnewline
168 & 0.996094 & 0.0078125 & 0.00390625 \tabularnewline
169 & 0.994966 & 0.0100684 & 0.00503422 \tabularnewline
170 & 0.995217 & 0.0095665 & 0.00478325 \tabularnewline
171 & 0.994269 & 0.0114623 & 0.00573116 \tabularnewline
172 & 0.996109 & 0.00778182 & 0.00389091 \tabularnewline
173 & 0.995652 & 0.00869574 & 0.00434787 \tabularnewline
174 & 0.9944 & 0.0111992 & 0.00559962 \tabularnewline
175 & 0.992859 & 0.0142817 & 0.00714085 \tabularnewline
176 & 0.994051 & 0.0118971 & 0.00594856 \tabularnewline
177 & 0.993283 & 0.0134347 & 0.00671734 \tabularnewline
178 & 0.99329 & 0.01342 & 0.00671002 \tabularnewline
179 & 0.992379 & 0.0152411 & 0.00762054 \tabularnewline
180 & 0.994023 & 0.0119541 & 0.00597706 \tabularnewline
181 & 0.993535 & 0.0129307 & 0.00646534 \tabularnewline
182 & 0.992138 & 0.0157249 & 0.00786243 \tabularnewline
183 & 0.990905 & 0.0181906 & 0.00909528 \tabularnewline
184 & 0.988687 & 0.022626 & 0.011313 \tabularnewline
185 & 0.98792 & 0.0241601 & 0.0120801 \tabularnewline
186 & 0.985852 & 0.0282969 & 0.0141484 \tabularnewline
187 & 0.992569 & 0.0148616 & 0.00743079 \tabularnewline
188 & 0.990863 & 0.0182736 & 0.00913678 \tabularnewline
189 & 0.989187 & 0.0216261 & 0.0108131 \tabularnewline
190 & 0.986274 & 0.0274518 & 0.0137259 \tabularnewline
191 & 0.983044 & 0.0339126 & 0.0169563 \tabularnewline
192 & 0.979981 & 0.0400377 & 0.0200189 \tabularnewline
193 & 0.977261 & 0.0454775 & 0.0227387 \tabularnewline
194 & 0.985887 & 0.0282263 & 0.0141131 \tabularnewline
195 & 0.983196 & 0.0336074 & 0.0168037 \tabularnewline
196 & 0.98101 & 0.0379798 & 0.0189899 \tabularnewline
197 & 0.98085 & 0.0383008 & 0.0191504 \tabularnewline
198 & 0.975672 & 0.0486564 & 0.0243282 \tabularnewline
199 & 0.97743 & 0.0451392 & 0.0225696 \tabularnewline
200 & 0.976905 & 0.0461908 & 0.0230954 \tabularnewline
201 & 0.973405 & 0.053189 & 0.0265945 \tabularnewline
202 & 0.9719 & 0.0562003 & 0.0281002 \tabularnewline
203 & 0.968303 & 0.0633935 & 0.0316968 \tabularnewline
204 & 0.961401 & 0.077199 & 0.0385995 \tabularnewline
205 & 0.953752 & 0.0924966 & 0.0462483 \tabularnewline
206 & 0.965423 & 0.0691536 & 0.0345768 \tabularnewline
207 & 0.961825 & 0.0763498 & 0.0381749 \tabularnewline
208 & 0.960458 & 0.0790844 & 0.0395422 \tabularnewline
209 & 0.956025 & 0.0879504 & 0.0439752 \tabularnewline
210 & 0.948829 & 0.102342 & 0.0511711 \tabularnewline
211 & 0.938813 & 0.122373 & 0.0611867 \tabularnewline
212 & 0.927978 & 0.144044 & 0.0720219 \tabularnewline
213 & 0.941524 & 0.116951 & 0.0584757 \tabularnewline
214 & 0.932171 & 0.135658 & 0.0678292 \tabularnewline
215 & 0.928697 & 0.142607 & 0.0713035 \tabularnewline
216 & 0.916284 & 0.167431 & 0.0837156 \tabularnewline
217 & 0.913368 & 0.173263 & 0.0866317 \tabularnewline
218 & 0.902869 & 0.194262 & 0.0971311 \tabularnewline
219 & 0.882251 & 0.235497 & 0.117749 \tabularnewline
220 & 0.858912 & 0.282176 & 0.141088 \tabularnewline
221 & 0.844507 & 0.310986 & 0.155493 \tabularnewline
222 & 0.863405 & 0.27319 & 0.136595 \tabularnewline
223 & 0.838124 & 0.323753 & 0.161876 \tabularnewline
224 & 0.844298 & 0.311404 & 0.155702 \tabularnewline
225 & 0.830392 & 0.339216 & 0.169608 \tabularnewline
226 & 0.889439 & 0.221123 & 0.110561 \tabularnewline
227 & 0.911203 & 0.177594 & 0.0887972 \tabularnewline
228 & 0.913368 & 0.173263 & 0.0866315 \tabularnewline
229 & 0.89973 & 0.20054 & 0.10027 \tabularnewline
230 & 0.916235 & 0.16753 & 0.0837649 \tabularnewline
231 & 0.943193 & 0.113615 & 0.0568073 \tabularnewline
232 & 0.928211 & 0.143577 & 0.0717886 \tabularnewline
233 & 0.915339 & 0.169321 & 0.0846607 \tabularnewline
234 & 0.904066 & 0.191868 & 0.0959339 \tabularnewline
235 & 0.895201 & 0.209598 & 0.104799 \tabularnewline
236 & 0.962838 & 0.074324 & 0.037162 \tabularnewline
237 & 0.96169 & 0.0766197 & 0.0383099 \tabularnewline
238 & 0.963109 & 0.0737829 & 0.0368914 \tabularnewline
239 & 0.952661 & 0.0946775 & 0.0473387 \tabularnewline
240 & 0.937857 & 0.124285 & 0.0621426 \tabularnewline
241 & 0.926478 & 0.147045 & 0.0735223 \tabularnewline
242 & 0.909845 & 0.18031 & 0.090155 \tabularnewline
243 & 0.904185 & 0.19163 & 0.0958149 \tabularnewline
244 & 0.891648 & 0.216705 & 0.108352 \tabularnewline
245 & 0.862542 & 0.274915 & 0.137458 \tabularnewline
246 & 0.831346 & 0.337309 & 0.168654 \tabularnewline
247 & 0.798702 & 0.402596 & 0.201298 \tabularnewline
248 & 0.756548 & 0.486904 & 0.243452 \tabularnewline
249 & 0.707476 & 0.585048 & 0.292524 \tabularnewline
250 & 0.650242 & 0.699516 & 0.349758 \tabularnewline
251 & 0.599043 & 0.801914 & 0.400957 \tabularnewline
252 & 0.597672 & 0.804656 & 0.402328 \tabularnewline
253 & 0.531531 & 0.936939 & 0.468469 \tabularnewline
254 & 0.46662 & 0.933239 & 0.53338 \tabularnewline
255 & 0.522289 & 0.955422 & 0.477711 \tabularnewline
256 & 0.453939 & 0.907878 & 0.546061 \tabularnewline
257 & 0.453223 & 0.906445 & 0.546777 \tabularnewline
258 & 0.892725 & 0.21455 & 0.107275 \tabularnewline
259 & 0.851225 & 0.29755 & 0.148775 \tabularnewline
260 & 0.995434 & 0.00913115 & 0.00456557 \tabularnewline
261 & 0.996591 & 0.00681823 & 0.00340912 \tabularnewline
262 & 0.997025 & 0.00594953 & 0.00297476 \tabularnewline
263 & 0.999799 & 0.0004011 & 0.00020055 \tabularnewline
264 & 0.999349 & 0.00130164 & 0.000650819 \tabularnewline
265 & 0.997866 & 0.00426766 & 0.00213383 \tabularnewline
266 & 0.995632 & 0.00873548 & 0.00436774 \tabularnewline
267 & 0.994162 & 0.011677 & 0.00583848 \tabularnewline
268 & 0.981805 & 0.0363893 & 0.0181947 \tabularnewline
269 & 0.970386 & 0.0592279 & 0.0296139 \tabularnewline
270 & 0.885475 & 0.229049 & 0.114525 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264817&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]0.907223[/C][C]0.185554[/C][C]0.0927769[/C][/ROW]
[ROW][C]10[/C][C]0.905152[/C][C]0.189695[/C][C]0.0948477[/C][/ROW]
[ROW][C]11[/C][C]0.838814[/C][C]0.322372[/C][C]0.161186[/C][/ROW]
[ROW][C]12[/C][C]0.869203[/C][C]0.261593[/C][C]0.130797[/C][/ROW]
[ROW][C]13[/C][C]0.812636[/C][C]0.374729[/C][C]0.187364[/C][/ROW]
[ROW][C]14[/C][C]0.737112[/C][C]0.525775[/C][C]0.262888[/C][/ROW]
[ROW][C]15[/C][C]0.675732[/C][C]0.648535[/C][C]0.324268[/C][/ROW]
[ROW][C]16[/C][C]0.688916[/C][C]0.622168[/C][C]0.311084[/C][/ROW]
[ROW][C]17[/C][C]0.62428[/C][C]0.75144[/C][C]0.37572[/C][/ROW]
[ROW][C]18[/C][C]0.544435[/C][C]0.911131[/C][C]0.455565[/C][/ROW]
[ROW][C]19[/C][C]0.469435[/C][C]0.938871[/C][C]0.530565[/C][/ROW]
[ROW][C]20[/C][C]0.392752[/C][C]0.785505[/C][C]0.607248[/C][/ROW]
[ROW][C]21[/C][C]0.4663[/C][C]0.932601[/C][C]0.5337[/C][/ROW]
[ROW][C]22[/C][C]0.480409[/C][C]0.960818[/C][C]0.519591[/C][/ROW]
[ROW][C]23[/C][C]0.415277[/C][C]0.830555[/C][C]0.584723[/C][/ROW]
[ROW][C]24[/C][C]0.350867[/C][C]0.701734[/C][C]0.649133[/C][/ROW]
[ROW][C]25[/C][C]0.292557[/C][C]0.585113[/C][C]0.707443[/C][/ROW]
[ROW][C]26[/C][C]0.254705[/C][C]0.50941[/C][C]0.745295[/C][/ROW]
[ROW][C]27[/C][C]0.215642[/C][C]0.431285[/C][C]0.784358[/C][/ROW]
[ROW][C]28[/C][C]0.275457[/C][C]0.550914[/C][C]0.724543[/C][/ROW]
[ROW][C]29[/C][C]0.246451[/C][C]0.492902[/C][C]0.753549[/C][/ROW]
[ROW][C]30[/C][C]0.222123[/C][C]0.444245[/C][C]0.777877[/C][/ROW]
[ROW][C]31[/C][C]0.192177[/C][C]0.384354[/C][C]0.807823[/C][/ROW]
[ROW][C]32[/C][C]0.189505[/C][C]0.37901[/C][C]0.810495[/C][/ROW]
[ROW][C]33[/C][C]0.158719[/C][C]0.317438[/C][C]0.841281[/C][/ROW]
[ROW][C]34[/C][C]0.162302[/C][C]0.324605[/C][C]0.837698[/C][/ROW]
[ROW][C]35[/C][C]0.136004[/C][C]0.272008[/C][C]0.863996[/C][/ROW]
[ROW][C]36[/C][C]0.112171[/C][C]0.224343[/C][C]0.887829[/C][/ROW]
[ROW][C]37[/C][C]0.0894058[/C][C]0.178812[/C][C]0.910594[/C][/ROW]
[ROW][C]38[/C][C]0.104059[/C][C]0.208118[/C][C]0.895941[/C][/ROW]
[ROW][C]39[/C][C]0.125118[/C][C]0.250236[/C][C]0.874882[/C][/ROW]
[ROW][C]40[/C][C]0.111662[/C][C]0.223324[/C][C]0.888338[/C][/ROW]
[ROW][C]41[/C][C]0.170666[/C][C]0.341333[/C][C]0.829334[/C][/ROW]
[ROW][C]42[/C][C]0.147919[/C][C]0.295839[/C][C]0.852081[/C][/ROW]
[ROW][C]43[/C][C]0.13047[/C][C]0.26094[/C][C]0.86953[/C][/ROW]
[ROW][C]44[/C][C]0.110208[/C][C]0.220417[/C][C]0.889792[/C][/ROW]
[ROW][C]45[/C][C]0.113864[/C][C]0.227728[/C][C]0.886136[/C][/ROW]
[ROW][C]46[/C][C]0.0964837[/C][C]0.192967[/C][C]0.903516[/C][/ROW]
[ROW][C]47[/C][C]0.0805688[/C][C]0.161138[/C][C]0.919431[/C][/ROW]
[ROW][C]48[/C][C]0.100303[/C][C]0.200606[/C][C]0.899697[/C][/ROW]
[ROW][C]49[/C][C]0.0987773[/C][C]0.197555[/C][C]0.901223[/C][/ROW]
[ROW][C]50[/C][C]0.105818[/C][C]0.211637[/C][C]0.894182[/C][/ROW]
[ROW][C]51[/C][C]0.0911363[/C][C]0.182273[/C][C]0.908864[/C][/ROW]
[ROW][C]52[/C][C]0.0959698[/C][C]0.19194[/C][C]0.90403[/C][/ROW]
[ROW][C]53[/C][C]0.0873319[/C][C]0.174664[/C][C]0.912668[/C][/ROW]
[ROW][C]54[/C][C]0.0853456[/C][C]0.170691[/C][C]0.914654[/C][/ROW]
[ROW][C]55[/C][C]0.0862837[/C][C]0.172567[/C][C]0.913716[/C][/ROW]
[ROW][C]56[/C][C]0.0746768[/C][C]0.149354[/C][C]0.925323[/C][/ROW]
[ROW][C]57[/C][C]0.130342[/C][C]0.260684[/C][C]0.869658[/C][/ROW]
[ROW][C]58[/C][C]0.159054[/C][C]0.318107[/C][C]0.840946[/C][/ROW]
[ROW][C]59[/C][C]0.13558[/C][C]0.271159[/C][C]0.86442[/C][/ROW]
[ROW][C]60[/C][C]0.14117[/C][C]0.28234[/C][C]0.85883[/C][/ROW]
[ROW][C]61[/C][C]0.156608[/C][C]0.313216[/C][C]0.843392[/C][/ROW]
[ROW][C]62[/C][C]0.149681[/C][C]0.299362[/C][C]0.850319[/C][/ROW]
[ROW][C]63[/C][C]0.157961[/C][C]0.315922[/C][C]0.842039[/C][/ROW]
[ROW][C]64[/C][C]0.194013[/C][C]0.388025[/C][C]0.805987[/C][/ROW]
[ROW][C]65[/C][C]0.193292[/C][C]0.386584[/C][C]0.806708[/C][/ROW]
[ROW][C]66[/C][C]0.168372[/C][C]0.336744[/C][C]0.831628[/C][/ROW]
[ROW][C]67[/C][C]0.169706[/C][C]0.339412[/C][C]0.830294[/C][/ROW]
[ROW][C]68[/C][C]0.156271[/C][C]0.312541[/C][C]0.843729[/C][/ROW]
[ROW][C]69[/C][C]0.166496[/C][C]0.332992[/C][C]0.833504[/C][/ROW]
[ROW][C]70[/C][C]0.153878[/C][C]0.307755[/C][C]0.846122[/C][/ROW]
[ROW][C]71[/C][C]0.140611[/C][C]0.281223[/C][C]0.859389[/C][/ROW]
[ROW][C]72[/C][C]0.124329[/C][C]0.248658[/C][C]0.875671[/C][/ROW]
[ROW][C]73[/C][C]0.112312[/C][C]0.224624[/C][C]0.887688[/C][/ROW]
[ROW][C]74[/C][C]0.118559[/C][C]0.237117[/C][C]0.881441[/C][/ROW]
[ROW][C]75[/C][C]0.110247[/C][C]0.220495[/C][C]0.889753[/C][/ROW]
[ROW][C]76[/C][C]0.102133[/C][C]0.204265[/C][C]0.897867[/C][/ROW]
[ROW][C]77[/C][C]0.0970897[/C][C]0.194179[/C][C]0.90291[/C][/ROW]
[ROW][C]78[/C][C]0.0962053[/C][C]0.192411[/C][C]0.903795[/C][/ROW]
[ROW][C]79[/C][C]0.0816366[/C][C]0.163273[/C][C]0.918363[/C][/ROW]
[ROW][C]80[/C][C]0.104616[/C][C]0.209231[/C][C]0.895384[/C][/ROW]
[ROW][C]81[/C][C]0.0888904[/C][C]0.177781[/C][C]0.91111[/C][/ROW]
[ROW][C]82[/C][C]0.0985128[/C][C]0.197026[/C][C]0.901487[/C][/ROW]
[ROW][C]83[/C][C]0.084501[/C][C]0.169002[/C][C]0.915499[/C][/ROW]
[ROW][C]84[/C][C]0.178737[/C][C]0.357474[/C][C]0.821263[/C][/ROW]
[ROW][C]85[/C][C]0.164148[/C][C]0.328296[/C][C]0.835852[/C][/ROW]
[ROW][C]86[/C][C]0.144654[/C][C]0.289308[/C][C]0.855346[/C][/ROW]
[ROW][C]87[/C][C]0.125393[/C][C]0.250787[/C][C]0.874607[/C][/ROW]
[ROW][C]88[/C][C]0.109875[/C][C]0.219749[/C][C]0.890125[/C][/ROW]
[ROW][C]89[/C][C]0.10352[/C][C]0.20704[/C][C]0.89648[/C][/ROW]
[ROW][C]90[/C][C]0.107351[/C][C]0.214702[/C][C]0.892649[/C][/ROW]
[ROW][C]91[/C][C]0.112621[/C][C]0.225242[/C][C]0.887379[/C][/ROW]
[ROW][C]92[/C][C]0.187663[/C][C]0.375327[/C][C]0.812337[/C][/ROW]
[ROW][C]93[/C][C]0.188703[/C][C]0.377407[/C][C]0.811297[/C][/ROW]
[ROW][C]94[/C][C]0.183259[/C][C]0.366518[/C][C]0.816741[/C][/ROW]
[ROW][C]95[/C][C]0.200039[/C][C]0.400077[/C][C]0.799961[/C][/ROW]
[ROW][C]96[/C][C]0.195[/C][C]0.39[/C][C]0.805[/C][/ROW]
[ROW][C]97[/C][C]0.265702[/C][C]0.531403[/C][C]0.734298[/C][/ROW]
[ROW][C]98[/C][C]0.252999[/C][C]0.505998[/C][C]0.747001[/C][/ROW]
[ROW][C]99[/C][C]0.297482[/C][C]0.594964[/C][C]0.702518[/C][/ROW]
[ROW][C]100[/C][C]0.35421[/C][C]0.708421[/C][C]0.64579[/C][/ROW]
[ROW][C]101[/C][C]0.327593[/C][C]0.655187[/C][C]0.672407[/C][/ROW]
[ROW][C]102[/C][C]0.311986[/C][C]0.623972[/C][C]0.688014[/C][/ROW]
[ROW][C]103[/C][C]0.314955[/C][C]0.629911[/C][C]0.685045[/C][/ROW]
[ROW][C]104[/C][C]0.332567[/C][C]0.665135[/C][C]0.667433[/C][/ROW]
[ROW][C]105[/C][C]0.364048[/C][C]0.728095[/C][C]0.635952[/C][/ROW]
[ROW][C]106[/C][C]0.391109[/C][C]0.782218[/C][C]0.608891[/C][/ROW]
[ROW][C]107[/C][C]0.408723[/C][C]0.817446[/C][C]0.591277[/C][/ROW]
[ROW][C]108[/C][C]0.628849[/C][C]0.742302[/C][C]0.371151[/C][/ROW]
[ROW][C]109[/C][C]0.67413[/C][C]0.65174[/C][C]0.32587[/C][/ROW]
[ROW][C]110[/C][C]0.684054[/C][C]0.631893[/C][C]0.315946[/C][/ROW]
[ROW][C]111[/C][C]0.678628[/C][C]0.642744[/C][C]0.321372[/C][/ROW]
[ROW][C]112[/C][C]0.666736[/C][C]0.666527[/C][C]0.333264[/C][/ROW]
[ROW][C]113[/C][C]0.728223[/C][C]0.543554[/C][C]0.271777[/C][/ROW]
[ROW][C]114[/C][C]0.721369[/C][C]0.557262[/C][C]0.278631[/C][/ROW]
[ROW][C]115[/C][C]0.832506[/C][C]0.334988[/C][C]0.167494[/C][/ROW]
[ROW][C]116[/C][C]0.882967[/C][C]0.234066[/C][C]0.117033[/C][/ROW]
[ROW][C]117[/C][C]0.871758[/C][C]0.256485[/C][C]0.128242[/C][/ROW]
[ROW][C]118[/C][C]0.91475[/C][C]0.1705[/C][C]0.08525[/C][/ROW]
[ROW][C]119[/C][C]0.909199[/C][C]0.181601[/C][C]0.0908007[/C][/ROW]
[ROW][C]120[/C][C]0.927204[/C][C]0.145592[/C][C]0.0727961[/C][/ROW]
[ROW][C]121[/C][C]0.93964[/C][C]0.120719[/C][C]0.0603597[/C][/ROW]
[ROW][C]122[/C][C]0.94869[/C][C]0.10262[/C][C]0.0513099[/C][/ROW]
[ROW][C]123[/C][C]0.95139[/C][C]0.0972191[/C][C]0.0486096[/C][/ROW]
[ROW][C]124[/C][C]0.969972[/C][C]0.0600561[/C][C]0.030028[/C][/ROW]
[ROW][C]125[/C][C]0.974084[/C][C]0.0518318[/C][C]0.0259159[/C][/ROW]
[ROW][C]126[/C][C]0.96977[/C][C]0.0604591[/C][C]0.0302296[/C][/ROW]
[ROW][C]127[/C][C]0.969111[/C][C]0.0617775[/C][C]0.0308888[/C][/ROW]
[ROW][C]128[/C][C]0.965995[/C][C]0.0680104[/C][C]0.0340052[/C][/ROW]
[ROW][C]129[/C][C]0.964691[/C][C]0.0706178[/C][C]0.0353089[/C][/ROW]
[ROW][C]130[/C][C]0.963058[/C][C]0.0738848[/C][C]0.0369424[/C][/ROW]
[ROW][C]131[/C][C]0.96534[/C][C]0.0693203[/C][C]0.0346602[/C][/ROW]
[ROW][C]132[/C][C]0.963593[/C][C]0.0728147[/C][C]0.0364074[/C][/ROW]
[ROW][C]133[/C][C]0.966643[/C][C]0.0667132[/C][C]0.0333566[/C][/ROW]
[ROW][C]134[/C][C]0.961241[/C][C]0.0775173[/C][C]0.0387586[/C][/ROW]
[ROW][C]135[/C][C]0.954077[/C][C]0.091847[/C][C]0.0459235[/C][/ROW]
[ROW][C]136[/C][C]0.94706[/C][C]0.105881[/C][C]0.0529404[/C][/ROW]
[ROW][C]137[/C][C]0.962015[/C][C]0.0759709[/C][C]0.0379855[/C][/ROW]
[ROW][C]138[/C][C]0.962079[/C][C]0.0758425[/C][C]0.0379213[/C][/ROW]
[ROW][C]139[/C][C]0.958431[/C][C]0.0831375[/C][C]0.0415687[/C][/ROW]
[ROW][C]140[/C][C]0.951116[/C][C]0.0977688[/C][C]0.0488844[/C][/ROW]
[ROW][C]141[/C][C]0.945981[/C][C]0.108038[/C][C]0.0540188[/C][/ROW]
[ROW][C]142[/C][C]0.97339[/C][C]0.0532197[/C][C]0.0266098[/C][/ROW]
[ROW][C]143[/C][C]0.972309[/C][C]0.0553828[/C][C]0.0276914[/C][/ROW]
[ROW][C]144[/C][C]0.972375[/C][C]0.0552503[/C][C]0.0276251[/C][/ROW]
[ROW][C]145[/C][C]0.968514[/C][C]0.0629717[/C][C]0.0314858[/C][/ROW]
[ROW][C]146[/C][C]0.969128[/C][C]0.0617437[/C][C]0.0308718[/C][/ROW]
[ROW][C]147[/C][C]0.964233[/C][C]0.0715335[/C][C]0.0357668[/C][/ROW]
[ROW][C]148[/C][C]0.958514[/C][C]0.0829713[/C][C]0.0414856[/C][/ROW]
[ROW][C]149[/C][C]0.953122[/C][C]0.0937554[/C][C]0.0468777[/C][/ROW]
[ROW][C]150[/C][C]0.95192[/C][C]0.0961605[/C][C]0.0480802[/C][/ROW]
[ROW][C]151[/C][C]0.98209[/C][C]0.0358197[/C][C]0.0179098[/C][/ROW]
[ROW][C]152[/C][C]0.98011[/C][C]0.039781[/C][C]0.0198905[/C][/ROW]
[ROW][C]153[/C][C]0.980935[/C][C]0.0381295[/C][C]0.0190647[/C][/ROW]
[ROW][C]154[/C][C]0.976945[/C][C]0.0461098[/C][C]0.0230549[/C][/ROW]
[ROW][C]155[/C][C]0.978025[/C][C]0.04395[/C][C]0.021975[/C][/ROW]
[ROW][C]156[/C][C]0.973471[/C][C]0.0530587[/C][C]0.0265294[/C][/ROW]
[ROW][C]157[/C][C]0.972331[/C][C]0.0553377[/C][C]0.0276688[/C][/ROW]
[ROW][C]158[/C][C]0.967948[/C][C]0.0641035[/C][C]0.0320518[/C][/ROW]
[ROW][C]159[/C][C]0.965859[/C][C]0.0682819[/C][C]0.034141[/C][/ROW]
[ROW][C]160[/C][C]0.960245[/C][C]0.0795094[/C][C]0.0397547[/C][/ROW]
[ROW][C]161[/C][C]0.972728[/C][C]0.0545449[/C][C]0.0272725[/C][/ROW]
[ROW][C]162[/C][C]0.968226[/C][C]0.0635489[/C][C]0.0317745[/C][/ROW]
[ROW][C]163[/C][C]0.969203[/C][C]0.0615948[/C][C]0.0307974[/C][/ROW]
[ROW][C]164[/C][C]0.993931[/C][C]0.0121376[/C][C]0.00606879[/C][/ROW]
[ROW][C]165[/C][C]0.995247[/C][C]0.00950657[/C][C]0.00475329[/C][/ROW]
[ROW][C]166[/C][C]0.993905[/C][C]0.0121896[/C][C]0.0060948[/C][/ROW]
[ROW][C]167[/C][C]0.993821[/C][C]0.0123578[/C][C]0.00617892[/C][/ROW]
[ROW][C]168[/C][C]0.996094[/C][C]0.0078125[/C][C]0.00390625[/C][/ROW]
[ROW][C]169[/C][C]0.994966[/C][C]0.0100684[/C][C]0.00503422[/C][/ROW]
[ROW][C]170[/C][C]0.995217[/C][C]0.0095665[/C][C]0.00478325[/C][/ROW]
[ROW][C]171[/C][C]0.994269[/C][C]0.0114623[/C][C]0.00573116[/C][/ROW]
[ROW][C]172[/C][C]0.996109[/C][C]0.00778182[/C][C]0.00389091[/C][/ROW]
[ROW][C]173[/C][C]0.995652[/C][C]0.00869574[/C][C]0.00434787[/C][/ROW]
[ROW][C]174[/C][C]0.9944[/C][C]0.0111992[/C][C]0.00559962[/C][/ROW]
[ROW][C]175[/C][C]0.992859[/C][C]0.0142817[/C][C]0.00714085[/C][/ROW]
[ROW][C]176[/C][C]0.994051[/C][C]0.0118971[/C][C]0.00594856[/C][/ROW]
[ROW][C]177[/C][C]0.993283[/C][C]0.0134347[/C][C]0.00671734[/C][/ROW]
[ROW][C]178[/C][C]0.99329[/C][C]0.01342[/C][C]0.00671002[/C][/ROW]
[ROW][C]179[/C][C]0.992379[/C][C]0.0152411[/C][C]0.00762054[/C][/ROW]
[ROW][C]180[/C][C]0.994023[/C][C]0.0119541[/C][C]0.00597706[/C][/ROW]
[ROW][C]181[/C][C]0.993535[/C][C]0.0129307[/C][C]0.00646534[/C][/ROW]
[ROW][C]182[/C][C]0.992138[/C][C]0.0157249[/C][C]0.00786243[/C][/ROW]
[ROW][C]183[/C][C]0.990905[/C][C]0.0181906[/C][C]0.00909528[/C][/ROW]
[ROW][C]184[/C][C]0.988687[/C][C]0.022626[/C][C]0.011313[/C][/ROW]
[ROW][C]185[/C][C]0.98792[/C][C]0.0241601[/C][C]0.0120801[/C][/ROW]
[ROW][C]186[/C][C]0.985852[/C][C]0.0282969[/C][C]0.0141484[/C][/ROW]
[ROW][C]187[/C][C]0.992569[/C][C]0.0148616[/C][C]0.00743079[/C][/ROW]
[ROW][C]188[/C][C]0.990863[/C][C]0.0182736[/C][C]0.00913678[/C][/ROW]
[ROW][C]189[/C][C]0.989187[/C][C]0.0216261[/C][C]0.0108131[/C][/ROW]
[ROW][C]190[/C][C]0.986274[/C][C]0.0274518[/C][C]0.0137259[/C][/ROW]
[ROW][C]191[/C][C]0.983044[/C][C]0.0339126[/C][C]0.0169563[/C][/ROW]
[ROW][C]192[/C][C]0.979981[/C][C]0.0400377[/C][C]0.0200189[/C][/ROW]
[ROW][C]193[/C][C]0.977261[/C][C]0.0454775[/C][C]0.0227387[/C][/ROW]
[ROW][C]194[/C][C]0.985887[/C][C]0.0282263[/C][C]0.0141131[/C][/ROW]
[ROW][C]195[/C][C]0.983196[/C][C]0.0336074[/C][C]0.0168037[/C][/ROW]
[ROW][C]196[/C][C]0.98101[/C][C]0.0379798[/C][C]0.0189899[/C][/ROW]
[ROW][C]197[/C][C]0.98085[/C][C]0.0383008[/C][C]0.0191504[/C][/ROW]
[ROW][C]198[/C][C]0.975672[/C][C]0.0486564[/C][C]0.0243282[/C][/ROW]
[ROW][C]199[/C][C]0.97743[/C][C]0.0451392[/C][C]0.0225696[/C][/ROW]
[ROW][C]200[/C][C]0.976905[/C][C]0.0461908[/C][C]0.0230954[/C][/ROW]
[ROW][C]201[/C][C]0.973405[/C][C]0.053189[/C][C]0.0265945[/C][/ROW]
[ROW][C]202[/C][C]0.9719[/C][C]0.0562003[/C][C]0.0281002[/C][/ROW]
[ROW][C]203[/C][C]0.968303[/C][C]0.0633935[/C][C]0.0316968[/C][/ROW]
[ROW][C]204[/C][C]0.961401[/C][C]0.077199[/C][C]0.0385995[/C][/ROW]
[ROW][C]205[/C][C]0.953752[/C][C]0.0924966[/C][C]0.0462483[/C][/ROW]
[ROW][C]206[/C][C]0.965423[/C][C]0.0691536[/C][C]0.0345768[/C][/ROW]
[ROW][C]207[/C][C]0.961825[/C][C]0.0763498[/C][C]0.0381749[/C][/ROW]
[ROW][C]208[/C][C]0.960458[/C][C]0.0790844[/C][C]0.0395422[/C][/ROW]
[ROW][C]209[/C][C]0.956025[/C][C]0.0879504[/C][C]0.0439752[/C][/ROW]
[ROW][C]210[/C][C]0.948829[/C][C]0.102342[/C][C]0.0511711[/C][/ROW]
[ROW][C]211[/C][C]0.938813[/C][C]0.122373[/C][C]0.0611867[/C][/ROW]
[ROW][C]212[/C][C]0.927978[/C][C]0.144044[/C][C]0.0720219[/C][/ROW]
[ROW][C]213[/C][C]0.941524[/C][C]0.116951[/C][C]0.0584757[/C][/ROW]
[ROW][C]214[/C][C]0.932171[/C][C]0.135658[/C][C]0.0678292[/C][/ROW]
[ROW][C]215[/C][C]0.928697[/C][C]0.142607[/C][C]0.0713035[/C][/ROW]
[ROW][C]216[/C][C]0.916284[/C][C]0.167431[/C][C]0.0837156[/C][/ROW]
[ROW][C]217[/C][C]0.913368[/C][C]0.173263[/C][C]0.0866317[/C][/ROW]
[ROW][C]218[/C][C]0.902869[/C][C]0.194262[/C][C]0.0971311[/C][/ROW]
[ROW][C]219[/C][C]0.882251[/C][C]0.235497[/C][C]0.117749[/C][/ROW]
[ROW][C]220[/C][C]0.858912[/C][C]0.282176[/C][C]0.141088[/C][/ROW]
[ROW][C]221[/C][C]0.844507[/C][C]0.310986[/C][C]0.155493[/C][/ROW]
[ROW][C]222[/C][C]0.863405[/C][C]0.27319[/C][C]0.136595[/C][/ROW]
[ROW][C]223[/C][C]0.838124[/C][C]0.323753[/C][C]0.161876[/C][/ROW]
[ROW][C]224[/C][C]0.844298[/C][C]0.311404[/C][C]0.155702[/C][/ROW]
[ROW][C]225[/C][C]0.830392[/C][C]0.339216[/C][C]0.169608[/C][/ROW]
[ROW][C]226[/C][C]0.889439[/C][C]0.221123[/C][C]0.110561[/C][/ROW]
[ROW][C]227[/C][C]0.911203[/C][C]0.177594[/C][C]0.0887972[/C][/ROW]
[ROW][C]228[/C][C]0.913368[/C][C]0.173263[/C][C]0.0866315[/C][/ROW]
[ROW][C]229[/C][C]0.89973[/C][C]0.20054[/C][C]0.10027[/C][/ROW]
[ROW][C]230[/C][C]0.916235[/C][C]0.16753[/C][C]0.0837649[/C][/ROW]
[ROW][C]231[/C][C]0.943193[/C][C]0.113615[/C][C]0.0568073[/C][/ROW]
[ROW][C]232[/C][C]0.928211[/C][C]0.143577[/C][C]0.0717886[/C][/ROW]
[ROW][C]233[/C][C]0.915339[/C][C]0.169321[/C][C]0.0846607[/C][/ROW]
[ROW][C]234[/C][C]0.904066[/C][C]0.191868[/C][C]0.0959339[/C][/ROW]
[ROW][C]235[/C][C]0.895201[/C][C]0.209598[/C][C]0.104799[/C][/ROW]
[ROW][C]236[/C][C]0.962838[/C][C]0.074324[/C][C]0.037162[/C][/ROW]
[ROW][C]237[/C][C]0.96169[/C][C]0.0766197[/C][C]0.0383099[/C][/ROW]
[ROW][C]238[/C][C]0.963109[/C][C]0.0737829[/C][C]0.0368914[/C][/ROW]
[ROW][C]239[/C][C]0.952661[/C][C]0.0946775[/C][C]0.0473387[/C][/ROW]
[ROW][C]240[/C][C]0.937857[/C][C]0.124285[/C][C]0.0621426[/C][/ROW]
[ROW][C]241[/C][C]0.926478[/C][C]0.147045[/C][C]0.0735223[/C][/ROW]
[ROW][C]242[/C][C]0.909845[/C][C]0.18031[/C][C]0.090155[/C][/ROW]
[ROW][C]243[/C][C]0.904185[/C][C]0.19163[/C][C]0.0958149[/C][/ROW]
[ROW][C]244[/C][C]0.891648[/C][C]0.216705[/C][C]0.108352[/C][/ROW]
[ROW][C]245[/C][C]0.862542[/C][C]0.274915[/C][C]0.137458[/C][/ROW]
[ROW][C]246[/C][C]0.831346[/C][C]0.337309[/C][C]0.168654[/C][/ROW]
[ROW][C]247[/C][C]0.798702[/C][C]0.402596[/C][C]0.201298[/C][/ROW]
[ROW][C]248[/C][C]0.756548[/C][C]0.486904[/C][C]0.243452[/C][/ROW]
[ROW][C]249[/C][C]0.707476[/C][C]0.585048[/C][C]0.292524[/C][/ROW]
[ROW][C]250[/C][C]0.650242[/C][C]0.699516[/C][C]0.349758[/C][/ROW]
[ROW][C]251[/C][C]0.599043[/C][C]0.801914[/C][C]0.400957[/C][/ROW]
[ROW][C]252[/C][C]0.597672[/C][C]0.804656[/C][C]0.402328[/C][/ROW]
[ROW][C]253[/C][C]0.531531[/C][C]0.936939[/C][C]0.468469[/C][/ROW]
[ROW][C]254[/C][C]0.46662[/C][C]0.933239[/C][C]0.53338[/C][/ROW]
[ROW][C]255[/C][C]0.522289[/C][C]0.955422[/C][C]0.477711[/C][/ROW]
[ROW][C]256[/C][C]0.453939[/C][C]0.907878[/C][C]0.546061[/C][/ROW]
[ROW][C]257[/C][C]0.453223[/C][C]0.906445[/C][C]0.546777[/C][/ROW]
[ROW][C]258[/C][C]0.892725[/C][C]0.21455[/C][C]0.107275[/C][/ROW]
[ROW][C]259[/C][C]0.851225[/C][C]0.29755[/C][C]0.148775[/C][/ROW]
[ROW][C]260[/C][C]0.995434[/C][C]0.00913115[/C][C]0.00456557[/C][/ROW]
[ROW][C]261[/C][C]0.996591[/C][C]0.00681823[/C][C]0.00340912[/C][/ROW]
[ROW][C]262[/C][C]0.997025[/C][C]0.00594953[/C][C]0.00297476[/C][/ROW]
[ROW][C]263[/C][C]0.999799[/C][C]0.0004011[/C][C]0.00020055[/C][/ROW]
[ROW][C]264[/C][C]0.999349[/C][C]0.00130164[/C][C]0.000650819[/C][/ROW]
[ROW][C]265[/C][C]0.997866[/C][C]0.00426766[/C][C]0.00213383[/C][/ROW]
[ROW][C]266[/C][C]0.995632[/C][C]0.00873548[/C][C]0.00436774[/C][/ROW]
[ROW][C]267[/C][C]0.994162[/C][C]0.011677[/C][C]0.00583848[/C][/ROW]
[ROW][C]268[/C][C]0.981805[/C][C]0.0363893[/C][C]0.0181947[/C][/ROW]
[ROW][C]269[/C][C]0.970386[/C][C]0.0592279[/C][C]0.0296139[/C][/ROW]
[ROW][C]270[/C][C]0.885475[/C][C]0.229049[/C][C]0.114525[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264817&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264817&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
90.9072230.1855540.0927769
100.9051520.1896950.0948477
110.8388140.3223720.161186
120.8692030.2615930.130797
130.8126360.3747290.187364
140.7371120.5257750.262888
150.6757320.6485350.324268
160.6889160.6221680.311084
170.624280.751440.37572
180.5444350.9111310.455565
190.4694350.9388710.530565
200.3927520.7855050.607248
210.46630.9326010.5337
220.4804090.9608180.519591
230.4152770.8305550.584723
240.3508670.7017340.649133
250.2925570.5851130.707443
260.2547050.509410.745295
270.2156420.4312850.784358
280.2754570.5509140.724543
290.2464510.4929020.753549
300.2221230.4442450.777877
310.1921770.3843540.807823
320.1895050.379010.810495
330.1587190.3174380.841281
340.1623020.3246050.837698
350.1360040.2720080.863996
360.1121710.2243430.887829
370.08940580.1788120.910594
380.1040590.2081180.895941
390.1251180.2502360.874882
400.1116620.2233240.888338
410.1706660.3413330.829334
420.1479190.2958390.852081
430.130470.260940.86953
440.1102080.2204170.889792
450.1138640.2277280.886136
460.09648370.1929670.903516
470.08056880.1611380.919431
480.1003030.2006060.899697
490.09877730.1975550.901223
500.1058180.2116370.894182
510.09113630.1822730.908864
520.09596980.191940.90403
530.08733190.1746640.912668
540.08534560.1706910.914654
550.08628370.1725670.913716
560.07467680.1493540.925323
570.1303420.2606840.869658
580.1590540.3181070.840946
590.135580.2711590.86442
600.141170.282340.85883
610.1566080.3132160.843392
620.1496810.2993620.850319
630.1579610.3159220.842039
640.1940130.3880250.805987
650.1932920.3865840.806708
660.1683720.3367440.831628
670.1697060.3394120.830294
680.1562710.3125410.843729
690.1664960.3329920.833504
700.1538780.3077550.846122
710.1406110.2812230.859389
720.1243290.2486580.875671
730.1123120.2246240.887688
740.1185590.2371170.881441
750.1102470.2204950.889753
760.1021330.2042650.897867
770.09708970.1941790.90291
780.09620530.1924110.903795
790.08163660.1632730.918363
800.1046160.2092310.895384
810.08889040.1777810.91111
820.09851280.1970260.901487
830.0845010.1690020.915499
840.1787370.3574740.821263
850.1641480.3282960.835852
860.1446540.2893080.855346
870.1253930.2507870.874607
880.1098750.2197490.890125
890.103520.207040.89648
900.1073510.2147020.892649
910.1126210.2252420.887379
920.1876630.3753270.812337
930.1887030.3774070.811297
940.1832590.3665180.816741
950.2000390.4000770.799961
960.1950.390.805
970.2657020.5314030.734298
980.2529990.5059980.747001
990.2974820.5949640.702518
1000.354210.7084210.64579
1010.3275930.6551870.672407
1020.3119860.6239720.688014
1030.3149550.6299110.685045
1040.3325670.6651350.667433
1050.3640480.7280950.635952
1060.3911090.7822180.608891
1070.4087230.8174460.591277
1080.6288490.7423020.371151
1090.674130.651740.32587
1100.6840540.6318930.315946
1110.6786280.6427440.321372
1120.6667360.6665270.333264
1130.7282230.5435540.271777
1140.7213690.5572620.278631
1150.8325060.3349880.167494
1160.8829670.2340660.117033
1170.8717580.2564850.128242
1180.914750.17050.08525
1190.9091990.1816010.0908007
1200.9272040.1455920.0727961
1210.939640.1207190.0603597
1220.948690.102620.0513099
1230.951390.09721910.0486096
1240.9699720.06005610.030028
1250.9740840.05183180.0259159
1260.969770.06045910.0302296
1270.9691110.06177750.0308888
1280.9659950.06801040.0340052
1290.9646910.07061780.0353089
1300.9630580.07388480.0369424
1310.965340.06932030.0346602
1320.9635930.07281470.0364074
1330.9666430.06671320.0333566
1340.9612410.07751730.0387586
1350.9540770.0918470.0459235
1360.947060.1058810.0529404
1370.9620150.07597090.0379855
1380.9620790.07584250.0379213
1390.9584310.08313750.0415687
1400.9511160.09776880.0488844
1410.9459810.1080380.0540188
1420.973390.05321970.0266098
1430.9723090.05538280.0276914
1440.9723750.05525030.0276251
1450.9685140.06297170.0314858
1460.9691280.06174370.0308718
1470.9642330.07153350.0357668
1480.9585140.08297130.0414856
1490.9531220.09375540.0468777
1500.951920.09616050.0480802
1510.982090.03581970.0179098
1520.980110.0397810.0198905
1530.9809350.03812950.0190647
1540.9769450.04610980.0230549
1550.9780250.043950.021975
1560.9734710.05305870.0265294
1570.9723310.05533770.0276688
1580.9679480.06410350.0320518
1590.9658590.06828190.034141
1600.9602450.07950940.0397547
1610.9727280.05454490.0272725
1620.9682260.06354890.0317745
1630.9692030.06159480.0307974
1640.9939310.01213760.00606879
1650.9952470.009506570.00475329
1660.9939050.01218960.0060948
1670.9938210.01235780.00617892
1680.9960940.00781250.00390625
1690.9949660.01006840.00503422
1700.9952170.00956650.00478325
1710.9942690.01146230.00573116
1720.9961090.007781820.00389091
1730.9956520.008695740.00434787
1740.99440.01119920.00559962
1750.9928590.01428170.00714085
1760.9940510.01189710.00594856
1770.9932830.01343470.00671734
1780.993290.013420.00671002
1790.9923790.01524110.00762054
1800.9940230.01195410.00597706
1810.9935350.01293070.00646534
1820.9921380.01572490.00786243
1830.9909050.01819060.00909528
1840.9886870.0226260.011313
1850.987920.02416010.0120801
1860.9858520.02829690.0141484
1870.9925690.01486160.00743079
1880.9908630.01827360.00913678
1890.9891870.02162610.0108131
1900.9862740.02745180.0137259
1910.9830440.03391260.0169563
1920.9799810.04003770.0200189
1930.9772610.04547750.0227387
1940.9858870.02822630.0141131
1950.9831960.03360740.0168037
1960.981010.03797980.0189899
1970.980850.03830080.0191504
1980.9756720.04865640.0243282
1990.977430.04513920.0225696
2000.9769050.04619080.0230954
2010.9734050.0531890.0265945
2020.97190.05620030.0281002
2030.9683030.06339350.0316968
2040.9614010.0771990.0385995
2050.9537520.09249660.0462483
2060.9654230.06915360.0345768
2070.9618250.07634980.0381749
2080.9604580.07908440.0395422
2090.9560250.08795040.0439752
2100.9488290.1023420.0511711
2110.9388130.1223730.0611867
2120.9279780.1440440.0720219
2130.9415240.1169510.0584757
2140.9321710.1356580.0678292
2150.9286970.1426070.0713035
2160.9162840.1674310.0837156
2170.9133680.1732630.0866317
2180.9028690.1942620.0971311
2190.8822510.2354970.117749
2200.8589120.2821760.141088
2210.8445070.3109860.155493
2220.8634050.273190.136595
2230.8381240.3237530.161876
2240.8442980.3114040.155702
2250.8303920.3392160.169608
2260.8894390.2211230.110561
2270.9112030.1775940.0887972
2280.9133680.1732630.0866315
2290.899730.200540.10027
2300.9162350.167530.0837649
2310.9431930.1136150.0568073
2320.9282110.1435770.0717886
2330.9153390.1693210.0846607
2340.9040660.1918680.0959339
2350.8952010.2095980.104799
2360.9628380.0743240.037162
2370.961690.07661970.0383099
2380.9631090.07378290.0368914
2390.9526610.09467750.0473387
2400.9378570.1242850.0621426
2410.9264780.1470450.0735223
2420.9098450.180310.090155
2430.9041850.191630.0958149
2440.8916480.2167050.108352
2450.8625420.2749150.137458
2460.8313460.3373090.168654
2470.7987020.4025960.201298
2480.7565480.4869040.243452
2490.7074760.5850480.292524
2500.6502420.6995160.349758
2510.5990430.8019140.400957
2520.5976720.8046560.402328
2530.5315310.9369390.468469
2540.466620.9332390.53338
2550.5222890.9554220.477711
2560.4539390.9078780.546061
2570.4532230.9064450.546777
2580.8927250.214550.107275
2590.8512250.297550.148775
2600.9954340.009131150.00456557
2610.9965910.006818230.00340912
2620.9970250.005949530.00297476
2630.9997990.00040110.00020055
2640.9993490.001301640.000650819
2650.9978660.004267660.00213383
2660.9956320.008735480.00436774
2670.9941620.0116770.00583848
2680.9818050.03638930.0181947
2690.9703860.05922790.0296139
2700.8854750.2290490.114525






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level120.0458015NOK
5% type I error level510.194656NOK
10% type I error level990.377863NOK

\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 & 12 & 0.0458015 & NOK \tabularnewline
5% type I error level & 51 & 0.194656 & NOK \tabularnewline
10% type I error level & 99 & 0.377863 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264817&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]12[/C][C]0.0458015[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]51[/C][C]0.194656[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]99[/C][C]0.377863[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264817&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264817&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level120.0458015NOK
5% type I error level510.194656NOK
10% type I error level990.377863NOK


Figures (Output of Computation)

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


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


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


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


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


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


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


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


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


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


Input Parameters & R Code

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