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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 10 Dec 2014 13:34:01 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t1418218498x0s7s9932k6jci8.htm/, Retrieved Sun, 19 May 2024 15:53:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265155, Retrieved Sun, 19 May 2024 15:53:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-10 13:34:01] [cb9023b84cdbf59fe6647357de544f7b] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265155&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265155&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265155&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 time7 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.55807 -0.0137131CH[t] + 0.00975692PRH[t] + 0.0263895Blogged[t] + 0.0119389LFM[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.55807 -0.0137131CH[t] +  0.00975692PRH[t] +  0.0263895Blogged[t] +  0.0119389LFM[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265155&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.55807 -0.0137131CH[t] +  0.00975692PRH[t] +  0.0263895Blogged[t] +  0.0119389LFM[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265155&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265155&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] = + 8.55807 -0.0137131CH[t] + 0.00975692PRH[t] + 0.0263895Blogged[t] + 0.0119389LFM[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.558070.60130614.232.35661e-331.17831e-33
CH-0.01371310.0123255-1.1130.2670560.133528
PRH0.009756920.01027780.94930.3434570.171728
Blogged0.02638950.003252648.1132.99802e-141.49901e-14
LFM0.01193890.005031052.3730.01846880.00923442

\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) & 8.55807 & 0.601306 & 14.23 & 2.35661e-33 & 1.17831e-33 \tabularnewline
CH & -0.0137131 & 0.0123255 & -1.113 & 0.267056 & 0.133528 \tabularnewline
PRH & 0.00975692 & 0.0102778 & 0.9493 & 0.343457 & 0.171728 \tabularnewline
Blogged & 0.0263895 & 0.00325264 & 8.113 & 2.99802e-14 & 1.49901e-14 \tabularnewline
LFM & 0.0119389 & 0.00503105 & 2.373 & 0.0184688 & 0.00923442 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265155&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]8.55807[/C][C]0.601306[/C][C]14.23[/C][C]2.35661e-33[/C][C]1.17831e-33[/C][/ROW]
[ROW][C]CH[/C][C]-0.0137131[/C][C]0.0123255[/C][C]-1.113[/C][C]0.267056[/C][C]0.133528[/C][/ROW]
[ROW][C]PRH[/C][C]0.00975692[/C][C]0.0102778[/C][C]0.9493[/C][C]0.343457[/C][C]0.171728[/C][/ROW]
[ROW][C]Blogged[/C][C]0.0263895[/C][C]0.00325264[/C][C]8.113[/C][C]2.99802e-14[/C][C]1.49901e-14[/C][/ROW]
[ROW][C]LFM[/C][C]0.0119389[/C][C]0.00503105[/C][C]2.373[/C][C]0.0184688[/C][C]0.00923442[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265155&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265155&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)8.558070.60130614.232.35661e-331.17831e-33
CH-0.01371310.0123255-1.1130.2670560.133528
PRH0.009756920.01027780.94930.3434570.171728
Blogged0.02638950.003252648.1132.99802e-141.49901e-14
LFM0.01193890.005031052.3730.01846880.00923442






Multiple Linear Regression - Regression Statistics
Multiple R0.586208
R-squared0.343639
Adjusted R-squared0.332174
F-TEST (value)29.9734
F-TEST (DF numerator)4
F-TEST (DF denominator)229
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.70355
Sum Squared Residuals1673.81

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.586208 \tabularnewline
R-squared & 0.343639 \tabularnewline
Adjusted R-squared & 0.332174 \tabularnewline
F-TEST (value) & 29.9734 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 229 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.70355 \tabularnewline
Sum Squared Residuals & 1673.81 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265155&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.586208[/C][/ROW]
[ROW][C]R-squared[/C][C]0.343639[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.332174[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]29.9734[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]229[/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]2.70355[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1673.81[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265155&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265155&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 R0.586208
R-squared0.343639
Adjusted R-squared0.332174
F-TEST (value)29.9734
F-TEST (DF numerator)4
F-TEST (DF denominator)229
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.70355
Sum Squared Residuals1673.81






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.11350.786499
212.812.5890.210986
37.413.0514-5.65144
46.711.7571-5.05707
512.615.8176-3.21758
614.812.9561.84395
713.312.45620.843756
811.113.0683-1.9683
98.214.5202-6.32019
1011.413.2432-1.84317
116.414.7202-8.32019
121213.9839-1.98385
136.310.0708-3.77075
1411.311.5843-0.284252
1511.914.1371-2.23714
169.312.4696-3.16958
171011.8267-1.82672
1813.813.74030.0596755
1910.813.7584-2.95837
2011.713.0107-1.31067
2110.915.33-4.43002
2216.113.90692.19314
239.911.4493-1.54926
2411.512.4914-0.99137
258.312.0448-3.74484
2611.713.655-1.95499
27912.6522-3.65221
2810.812.822-2.022
2910.412.0141-1.61414
3012.713.176-0.475969
3111.814.5587-2.75868
321312.17970.820296
3310.812.8412-2.04124
3412.310.65681.64322
3511.313.9286-2.62864
3611.612.3076-0.70761
3710.913.4241-2.5241
3812.112.9838-0.883804
3913.313.8073-0.507332
4010.113.5403-3.44031
4114.312.52521.77483
429.312.9607-3.6607
4312.512.2580.242018
447.611.0297-3.42967
459.211.9128-2.71278
4614.513.5530.947046
4712.314.0354-1.73535
4812.613.222-0.62201
491313.9555-0.955525
5012.611.66890.931136
5113.214.8113-1.61127
527.711.7273-4.02732
5310.510.9908-0.490778
5410.912.0188-1.11877
554.310.3876-6.08765
5610.311.4153-1.11532
5711.411.3010.0989546
585.611.3881-5.7881
598.812.1582-3.35818
60910.7457-1.74567
619.611.3408-1.74081
626.410.3803-3.9803
6311.611.17660.423355
644.3510.273-5.92296
6512.712.54690.153088
6618.114.96643.1336
6717.8515.26832.5817
6816.615.67990.920146
6912.610.2932.30698
7017.122.0341-4.9341
7119.115.83623.26379
7216.118.1967-2.09672
7313.3510.91152.43849
7418.417.54760.85243
7514.711.16053.53948
7610.614.9128-4.31276
7712.613.868-1.26797
7816.215.18391.01606
7913.617.9868-4.38682
8018.916.11482.78517
8114.112.67721.42275
8214.512.15252.34753
8316.1518.2574-2.10735
8414.7513.74481.00516
8514.814.37120.42878
8612.4512.42560.0243924
8712.6514.7515-2.10153
8817.3513.90033.44969
898.612.0142-3.41418
9018.417.48720.912796
9116.117.9207-1.82071
9211.611.27270.327322
9317.7512.56785.18224
9415.2513.96921.28082
9517.6516.18891.46105
9615.613.98411.61588
9716.3515.16121.1888
9817.6514.83662.81339
9913.613.23880.36118
10011.712.4947-0.794742
10114.3513.59610.753897
10214.7517.5147-2.76472
10318.2516.53291.7171
1049.915.3303-5.43026
1051614.04291.95711
10618.2515.84132.40868
10716.8517.3353-0.485343
10814.612.60411.99591
10913.8513.59590.254056
11018.9516.2872.66297
11115.614.67510.924876
11214.8517.1034-2.25341
11311.7512.6553-0.905259
11418.4512.83885.61119
11515.917.1086-1.20865
11617.114.23262.86737
11716.110.76095.33908
11819.914.95074.94935
11910.9510.89110.0589016
12018.4515.70252.74751
12115.110.93884.16116
1221515.5343-0.534284
12311.3513.9548-2.60481
12415.9515.04360.906438
12518.113.40944.69059
12614.613.06481.53519
12715.416.1937-0.793689
12815.416.1937-0.793689
12917.613.5574.04301
13013.3513.8929-0.542853
13119.116.67942.42057
13215.3513.17372.17633
1337.612.4006-4.80056
13413.413.8577-0.457728
13513.913.65650.243526
13619.117.12481.97518
13715.2513.75041.49963
13812.912.24530.654737
13916.113.86282.2372
14017.3512.53024.81977
14113.1512.52880.621187
14212.1510.53211.61794
14312.612.56020.0397651
14410.3511.6356-1.28557
14515.412.61972.78031
1469.610.9759-1.37592
14718.213.37194.82813
14813.612.19221.40776
14914.8514.58840.261583
15014.7516.9443-2.19431
15114.113.89310.206934
15214.911.67423.22577
15316.2512.90823.34184
15419.2517.82721.42283
15513.612.02571.57427
15613.613.44590.154139
15715.6515.16390.486067
15812.7512.5450.204972
15914.611.44923.15075
1609.8513.2816-3.43164
16112.6511.17671.47329
16211.912.2654-0.36537
16319.216.18913.01085
16416.614.26152.33853
16511.29.988681.21132
16615.2513.36331.88669
16711.915.1784-3.27838
16813.215.716-2.51603
16916.3517.1156-0.765609
17012.413.5492-1.14917
17115.8513.04792.80207
17214.3513.93940.410634
17318.1515.16252.98746
17411.1511.4851-0.335093
17515.6515.58920.0607959
17617.7516.48161.26839
1777.6512.428-4.77803
17812.3512.21910.130854
17915.611.80663.79345
18019.316.33412.96588
18115.211.9293.271
18217.113.5643.53596
18315.612.97842.62163
18418.414.77173.62832
18519.0515.20773.84232
18618.5513.72514.82489
18719.116.67342.42661
18813.111.9631.13702
18912.8513.5835-0.733523
1909.511.6832-2.18318
1914.511.3613-6.86129
19211.8510.70211.14785
19313.616.116-2.51602
19411.713.3214-1.62139
19512.411.68460.715408
19613.3514.7593-1.40928
19711.413.7695-2.36953
19814.911.98012.91987
19919.914.95074.94935
20017.7512.23445.51558
20111.212.1413-0.941272
20214.615.4403-0.840339
20317.615.74981.85019
20414.0512.8391.21097
20516.115.07751.02252
20613.3513.4306-0.0806368
20711.8512.8531-1.00314
20811.9514.2288-2.27876
20914.7514.54980.200189
21015.1513.00062.14943
21113.213.8832-0.683157
21216.8515.41661.43341
2137.8510.4176-2.56763
2147.714.7281-7.02812
21512.611.72760.872366
2167.8511.7421-3.89214
21710.9510.89110.0589016
21812.3512.07130.278691
2199.9512.9821-3.03206
22014.911.98012.91987
22116.6514.62912.02087
22213.412.89110.508931
22313.9513.45110.498857
22415.711.92093.77912
22516.8512.44584.40423
22610.9510.50990.440054
22715.3512.05883.29119
22812.211.41250.787513
22915.113.9871.11299
23017.7516.28321.4668
23115.212.81322.38676
23214.613.58241.01756
23316.6514.73291.91711
2348.110.894-2.79399

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.1135 & 0.786499 \tabularnewline
2 & 12.8 & 12.589 & 0.210986 \tabularnewline
3 & 7.4 & 13.0514 & -5.65144 \tabularnewline
4 & 6.7 & 11.7571 & -5.05707 \tabularnewline
5 & 12.6 & 15.8176 & -3.21758 \tabularnewline
6 & 14.8 & 12.956 & 1.84395 \tabularnewline
7 & 13.3 & 12.4562 & 0.843756 \tabularnewline
8 & 11.1 & 13.0683 & -1.9683 \tabularnewline
9 & 8.2 & 14.5202 & -6.32019 \tabularnewline
10 & 11.4 & 13.2432 & -1.84317 \tabularnewline
11 & 6.4 & 14.7202 & -8.32019 \tabularnewline
12 & 12 & 13.9839 & -1.98385 \tabularnewline
13 & 6.3 & 10.0708 & -3.77075 \tabularnewline
14 & 11.3 & 11.5843 & -0.284252 \tabularnewline
15 & 11.9 & 14.1371 & -2.23714 \tabularnewline
16 & 9.3 & 12.4696 & -3.16958 \tabularnewline
17 & 10 & 11.8267 & -1.82672 \tabularnewline
18 & 13.8 & 13.7403 & 0.0596755 \tabularnewline
19 & 10.8 & 13.7584 & -2.95837 \tabularnewline
20 & 11.7 & 13.0107 & -1.31067 \tabularnewline
21 & 10.9 & 15.33 & -4.43002 \tabularnewline
22 & 16.1 & 13.9069 & 2.19314 \tabularnewline
23 & 9.9 & 11.4493 & -1.54926 \tabularnewline
24 & 11.5 & 12.4914 & -0.99137 \tabularnewline
25 & 8.3 & 12.0448 & -3.74484 \tabularnewline
26 & 11.7 & 13.655 & -1.95499 \tabularnewline
27 & 9 & 12.6522 & -3.65221 \tabularnewline
28 & 10.8 & 12.822 & -2.022 \tabularnewline
29 & 10.4 & 12.0141 & -1.61414 \tabularnewline
30 & 12.7 & 13.176 & -0.475969 \tabularnewline
31 & 11.8 & 14.5587 & -2.75868 \tabularnewline
32 & 13 & 12.1797 & 0.820296 \tabularnewline
33 & 10.8 & 12.8412 & -2.04124 \tabularnewline
34 & 12.3 & 10.6568 & 1.64322 \tabularnewline
35 & 11.3 & 13.9286 & -2.62864 \tabularnewline
36 & 11.6 & 12.3076 & -0.70761 \tabularnewline
37 & 10.9 & 13.4241 & -2.5241 \tabularnewline
38 & 12.1 & 12.9838 & -0.883804 \tabularnewline
39 & 13.3 & 13.8073 & -0.507332 \tabularnewline
40 & 10.1 & 13.5403 & -3.44031 \tabularnewline
41 & 14.3 & 12.5252 & 1.77483 \tabularnewline
42 & 9.3 & 12.9607 & -3.6607 \tabularnewline
43 & 12.5 & 12.258 & 0.242018 \tabularnewline
44 & 7.6 & 11.0297 & -3.42967 \tabularnewline
45 & 9.2 & 11.9128 & -2.71278 \tabularnewline
46 & 14.5 & 13.553 & 0.947046 \tabularnewline
47 & 12.3 & 14.0354 & -1.73535 \tabularnewline
48 & 12.6 & 13.222 & -0.62201 \tabularnewline
49 & 13 & 13.9555 & -0.955525 \tabularnewline
50 & 12.6 & 11.6689 & 0.931136 \tabularnewline
51 & 13.2 & 14.8113 & -1.61127 \tabularnewline
52 & 7.7 & 11.7273 & -4.02732 \tabularnewline
53 & 10.5 & 10.9908 & -0.490778 \tabularnewline
54 & 10.9 & 12.0188 & -1.11877 \tabularnewline
55 & 4.3 & 10.3876 & -6.08765 \tabularnewline
56 & 10.3 & 11.4153 & -1.11532 \tabularnewline
57 & 11.4 & 11.301 & 0.0989546 \tabularnewline
58 & 5.6 & 11.3881 & -5.7881 \tabularnewline
59 & 8.8 & 12.1582 & -3.35818 \tabularnewline
60 & 9 & 10.7457 & -1.74567 \tabularnewline
61 & 9.6 & 11.3408 & -1.74081 \tabularnewline
62 & 6.4 & 10.3803 & -3.9803 \tabularnewline
63 & 11.6 & 11.1766 & 0.423355 \tabularnewline
64 & 4.35 & 10.273 & -5.92296 \tabularnewline
65 & 12.7 & 12.5469 & 0.153088 \tabularnewline
66 & 18.1 & 14.9664 & 3.1336 \tabularnewline
67 & 17.85 & 15.2683 & 2.5817 \tabularnewline
68 & 16.6 & 15.6799 & 0.920146 \tabularnewline
69 & 12.6 & 10.293 & 2.30698 \tabularnewline
70 & 17.1 & 22.0341 & -4.9341 \tabularnewline
71 & 19.1 & 15.8362 & 3.26379 \tabularnewline
72 & 16.1 & 18.1967 & -2.09672 \tabularnewline
73 & 13.35 & 10.9115 & 2.43849 \tabularnewline
74 & 18.4 & 17.5476 & 0.85243 \tabularnewline
75 & 14.7 & 11.1605 & 3.53948 \tabularnewline
76 & 10.6 & 14.9128 & -4.31276 \tabularnewline
77 & 12.6 & 13.868 & -1.26797 \tabularnewline
78 & 16.2 & 15.1839 & 1.01606 \tabularnewline
79 & 13.6 & 17.9868 & -4.38682 \tabularnewline
80 & 18.9 & 16.1148 & 2.78517 \tabularnewline
81 & 14.1 & 12.6772 & 1.42275 \tabularnewline
82 & 14.5 & 12.1525 & 2.34753 \tabularnewline
83 & 16.15 & 18.2574 & -2.10735 \tabularnewline
84 & 14.75 & 13.7448 & 1.00516 \tabularnewline
85 & 14.8 & 14.3712 & 0.42878 \tabularnewline
86 & 12.45 & 12.4256 & 0.0243924 \tabularnewline
87 & 12.65 & 14.7515 & -2.10153 \tabularnewline
88 & 17.35 & 13.9003 & 3.44969 \tabularnewline
89 & 8.6 & 12.0142 & -3.41418 \tabularnewline
90 & 18.4 & 17.4872 & 0.912796 \tabularnewline
91 & 16.1 & 17.9207 & -1.82071 \tabularnewline
92 & 11.6 & 11.2727 & 0.327322 \tabularnewline
93 & 17.75 & 12.5678 & 5.18224 \tabularnewline
94 & 15.25 & 13.9692 & 1.28082 \tabularnewline
95 & 17.65 & 16.1889 & 1.46105 \tabularnewline
96 & 15.6 & 13.9841 & 1.61588 \tabularnewline
97 & 16.35 & 15.1612 & 1.1888 \tabularnewline
98 & 17.65 & 14.8366 & 2.81339 \tabularnewline
99 & 13.6 & 13.2388 & 0.36118 \tabularnewline
100 & 11.7 & 12.4947 & -0.794742 \tabularnewline
101 & 14.35 & 13.5961 & 0.753897 \tabularnewline
102 & 14.75 & 17.5147 & -2.76472 \tabularnewline
103 & 18.25 & 16.5329 & 1.7171 \tabularnewline
104 & 9.9 & 15.3303 & -5.43026 \tabularnewline
105 & 16 & 14.0429 & 1.95711 \tabularnewline
106 & 18.25 & 15.8413 & 2.40868 \tabularnewline
107 & 16.85 & 17.3353 & -0.485343 \tabularnewline
108 & 14.6 & 12.6041 & 1.99591 \tabularnewline
109 & 13.85 & 13.5959 & 0.254056 \tabularnewline
110 & 18.95 & 16.287 & 2.66297 \tabularnewline
111 & 15.6 & 14.6751 & 0.924876 \tabularnewline
112 & 14.85 & 17.1034 & -2.25341 \tabularnewline
113 & 11.75 & 12.6553 & -0.905259 \tabularnewline
114 & 18.45 & 12.8388 & 5.61119 \tabularnewline
115 & 15.9 & 17.1086 & -1.20865 \tabularnewline
116 & 17.1 & 14.2326 & 2.86737 \tabularnewline
117 & 16.1 & 10.7609 & 5.33908 \tabularnewline
118 & 19.9 & 14.9507 & 4.94935 \tabularnewline
119 & 10.95 & 10.8911 & 0.0589016 \tabularnewline
120 & 18.45 & 15.7025 & 2.74751 \tabularnewline
121 & 15.1 & 10.9388 & 4.16116 \tabularnewline
122 & 15 & 15.5343 & -0.534284 \tabularnewline
123 & 11.35 & 13.9548 & -2.60481 \tabularnewline
124 & 15.95 & 15.0436 & 0.906438 \tabularnewline
125 & 18.1 & 13.4094 & 4.69059 \tabularnewline
126 & 14.6 & 13.0648 & 1.53519 \tabularnewline
127 & 15.4 & 16.1937 & -0.793689 \tabularnewline
128 & 15.4 & 16.1937 & -0.793689 \tabularnewline
129 & 17.6 & 13.557 & 4.04301 \tabularnewline
130 & 13.35 & 13.8929 & -0.542853 \tabularnewline
131 & 19.1 & 16.6794 & 2.42057 \tabularnewline
132 & 15.35 & 13.1737 & 2.17633 \tabularnewline
133 & 7.6 & 12.4006 & -4.80056 \tabularnewline
134 & 13.4 & 13.8577 & -0.457728 \tabularnewline
135 & 13.9 & 13.6565 & 0.243526 \tabularnewline
136 & 19.1 & 17.1248 & 1.97518 \tabularnewline
137 & 15.25 & 13.7504 & 1.49963 \tabularnewline
138 & 12.9 & 12.2453 & 0.654737 \tabularnewline
139 & 16.1 & 13.8628 & 2.2372 \tabularnewline
140 & 17.35 & 12.5302 & 4.81977 \tabularnewline
141 & 13.15 & 12.5288 & 0.621187 \tabularnewline
142 & 12.15 & 10.5321 & 1.61794 \tabularnewline
143 & 12.6 & 12.5602 & 0.0397651 \tabularnewline
144 & 10.35 & 11.6356 & -1.28557 \tabularnewline
145 & 15.4 & 12.6197 & 2.78031 \tabularnewline
146 & 9.6 & 10.9759 & -1.37592 \tabularnewline
147 & 18.2 & 13.3719 & 4.82813 \tabularnewline
148 & 13.6 & 12.1922 & 1.40776 \tabularnewline
149 & 14.85 & 14.5884 & 0.261583 \tabularnewline
150 & 14.75 & 16.9443 & -2.19431 \tabularnewline
151 & 14.1 & 13.8931 & 0.206934 \tabularnewline
152 & 14.9 & 11.6742 & 3.22577 \tabularnewline
153 & 16.25 & 12.9082 & 3.34184 \tabularnewline
154 & 19.25 & 17.8272 & 1.42283 \tabularnewline
155 & 13.6 & 12.0257 & 1.57427 \tabularnewline
156 & 13.6 & 13.4459 & 0.154139 \tabularnewline
157 & 15.65 & 15.1639 & 0.486067 \tabularnewline
158 & 12.75 & 12.545 & 0.204972 \tabularnewline
159 & 14.6 & 11.4492 & 3.15075 \tabularnewline
160 & 9.85 & 13.2816 & -3.43164 \tabularnewline
161 & 12.65 & 11.1767 & 1.47329 \tabularnewline
162 & 11.9 & 12.2654 & -0.36537 \tabularnewline
163 & 19.2 & 16.1891 & 3.01085 \tabularnewline
164 & 16.6 & 14.2615 & 2.33853 \tabularnewline
165 & 11.2 & 9.98868 & 1.21132 \tabularnewline
166 & 15.25 & 13.3633 & 1.88669 \tabularnewline
167 & 11.9 & 15.1784 & -3.27838 \tabularnewline
168 & 13.2 & 15.716 & -2.51603 \tabularnewline
169 & 16.35 & 17.1156 & -0.765609 \tabularnewline
170 & 12.4 & 13.5492 & -1.14917 \tabularnewline
171 & 15.85 & 13.0479 & 2.80207 \tabularnewline
172 & 14.35 & 13.9394 & 0.410634 \tabularnewline
173 & 18.15 & 15.1625 & 2.98746 \tabularnewline
174 & 11.15 & 11.4851 & -0.335093 \tabularnewline
175 & 15.65 & 15.5892 & 0.0607959 \tabularnewline
176 & 17.75 & 16.4816 & 1.26839 \tabularnewline
177 & 7.65 & 12.428 & -4.77803 \tabularnewline
178 & 12.35 & 12.2191 & 0.130854 \tabularnewline
179 & 15.6 & 11.8066 & 3.79345 \tabularnewline
180 & 19.3 & 16.3341 & 2.96588 \tabularnewline
181 & 15.2 & 11.929 & 3.271 \tabularnewline
182 & 17.1 & 13.564 & 3.53596 \tabularnewline
183 & 15.6 & 12.9784 & 2.62163 \tabularnewline
184 & 18.4 & 14.7717 & 3.62832 \tabularnewline
185 & 19.05 & 15.2077 & 3.84232 \tabularnewline
186 & 18.55 & 13.7251 & 4.82489 \tabularnewline
187 & 19.1 & 16.6734 & 2.42661 \tabularnewline
188 & 13.1 & 11.963 & 1.13702 \tabularnewline
189 & 12.85 & 13.5835 & -0.733523 \tabularnewline
190 & 9.5 & 11.6832 & -2.18318 \tabularnewline
191 & 4.5 & 11.3613 & -6.86129 \tabularnewline
192 & 11.85 & 10.7021 & 1.14785 \tabularnewline
193 & 13.6 & 16.116 & -2.51602 \tabularnewline
194 & 11.7 & 13.3214 & -1.62139 \tabularnewline
195 & 12.4 & 11.6846 & 0.715408 \tabularnewline
196 & 13.35 & 14.7593 & -1.40928 \tabularnewline
197 & 11.4 & 13.7695 & -2.36953 \tabularnewline
198 & 14.9 & 11.9801 & 2.91987 \tabularnewline
199 & 19.9 & 14.9507 & 4.94935 \tabularnewline
200 & 17.75 & 12.2344 & 5.51558 \tabularnewline
201 & 11.2 & 12.1413 & -0.941272 \tabularnewline
202 & 14.6 & 15.4403 & -0.840339 \tabularnewline
203 & 17.6 & 15.7498 & 1.85019 \tabularnewline
204 & 14.05 & 12.839 & 1.21097 \tabularnewline
205 & 16.1 & 15.0775 & 1.02252 \tabularnewline
206 & 13.35 & 13.4306 & -0.0806368 \tabularnewline
207 & 11.85 & 12.8531 & -1.00314 \tabularnewline
208 & 11.95 & 14.2288 & -2.27876 \tabularnewline
209 & 14.75 & 14.5498 & 0.200189 \tabularnewline
210 & 15.15 & 13.0006 & 2.14943 \tabularnewline
211 & 13.2 & 13.8832 & -0.683157 \tabularnewline
212 & 16.85 & 15.4166 & 1.43341 \tabularnewline
213 & 7.85 & 10.4176 & -2.56763 \tabularnewline
214 & 7.7 & 14.7281 & -7.02812 \tabularnewline
215 & 12.6 & 11.7276 & 0.872366 \tabularnewline
216 & 7.85 & 11.7421 & -3.89214 \tabularnewline
217 & 10.95 & 10.8911 & 0.0589016 \tabularnewline
218 & 12.35 & 12.0713 & 0.278691 \tabularnewline
219 & 9.95 & 12.9821 & -3.03206 \tabularnewline
220 & 14.9 & 11.9801 & 2.91987 \tabularnewline
221 & 16.65 & 14.6291 & 2.02087 \tabularnewline
222 & 13.4 & 12.8911 & 0.508931 \tabularnewline
223 & 13.95 & 13.4511 & 0.498857 \tabularnewline
224 & 15.7 & 11.9209 & 3.77912 \tabularnewline
225 & 16.85 & 12.4458 & 4.40423 \tabularnewline
226 & 10.95 & 10.5099 & 0.440054 \tabularnewline
227 & 15.35 & 12.0588 & 3.29119 \tabularnewline
228 & 12.2 & 11.4125 & 0.787513 \tabularnewline
229 & 15.1 & 13.987 & 1.11299 \tabularnewline
230 & 17.75 & 16.2832 & 1.4668 \tabularnewline
231 & 15.2 & 12.8132 & 2.38676 \tabularnewline
232 & 14.6 & 13.5824 & 1.01756 \tabularnewline
233 & 16.65 & 14.7329 & 1.91711 \tabularnewline
234 & 8.1 & 10.894 & -2.79399 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265155&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]12.1135[/C][C]0.786499[/C][/ROW]
[ROW][C]2[/C][C]12.8[/C][C]12.589[/C][C]0.210986[/C][/ROW]
[ROW][C]3[/C][C]7.4[/C][C]13.0514[/C][C]-5.65144[/C][/ROW]
[ROW][C]4[/C][C]6.7[/C][C]11.7571[/C][C]-5.05707[/C][/ROW]
[ROW][C]5[/C][C]12.6[/C][C]15.8176[/C][C]-3.21758[/C][/ROW]
[ROW][C]6[/C][C]14.8[/C][C]12.956[/C][C]1.84395[/C][/ROW]
[ROW][C]7[/C][C]13.3[/C][C]12.4562[/C][C]0.843756[/C][/ROW]
[ROW][C]8[/C][C]11.1[/C][C]13.0683[/C][C]-1.9683[/C][/ROW]
[ROW][C]9[/C][C]8.2[/C][C]14.5202[/C][C]-6.32019[/C][/ROW]
[ROW][C]10[/C][C]11.4[/C][C]13.2432[/C][C]-1.84317[/C][/ROW]
[ROW][C]11[/C][C]6.4[/C][C]14.7202[/C][C]-8.32019[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]13.9839[/C][C]-1.98385[/C][/ROW]
[ROW][C]13[/C][C]6.3[/C][C]10.0708[/C][C]-3.77075[/C][/ROW]
[ROW][C]14[/C][C]11.3[/C][C]11.5843[/C][C]-0.284252[/C][/ROW]
[ROW][C]15[/C][C]11.9[/C][C]14.1371[/C][C]-2.23714[/C][/ROW]
[ROW][C]16[/C][C]9.3[/C][C]12.4696[/C][C]-3.16958[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]11.8267[/C][C]-1.82672[/C][/ROW]
[ROW][C]18[/C][C]13.8[/C][C]13.7403[/C][C]0.0596755[/C][/ROW]
[ROW][C]19[/C][C]10.8[/C][C]13.7584[/C][C]-2.95837[/C][/ROW]
[ROW][C]20[/C][C]11.7[/C][C]13.0107[/C][C]-1.31067[/C][/ROW]
[ROW][C]21[/C][C]10.9[/C][C]15.33[/C][C]-4.43002[/C][/ROW]
[ROW][C]22[/C][C]16.1[/C][C]13.9069[/C][C]2.19314[/C][/ROW]
[ROW][C]23[/C][C]9.9[/C][C]11.4493[/C][C]-1.54926[/C][/ROW]
[ROW][C]24[/C][C]11.5[/C][C]12.4914[/C][C]-0.99137[/C][/ROW]
[ROW][C]25[/C][C]8.3[/C][C]12.0448[/C][C]-3.74484[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]13.655[/C][C]-1.95499[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]12.6522[/C][C]-3.65221[/C][/ROW]
[ROW][C]28[/C][C]10.8[/C][C]12.822[/C][C]-2.022[/C][/ROW]
[ROW][C]29[/C][C]10.4[/C][C]12.0141[/C][C]-1.61414[/C][/ROW]
[ROW][C]30[/C][C]12.7[/C][C]13.176[/C][C]-0.475969[/C][/ROW]
[ROW][C]31[/C][C]11.8[/C][C]14.5587[/C][C]-2.75868[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.1797[/C][C]0.820296[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]12.8412[/C][C]-2.04124[/C][/ROW]
[ROW][C]34[/C][C]12.3[/C][C]10.6568[/C][C]1.64322[/C][/ROW]
[ROW][C]35[/C][C]11.3[/C][C]13.9286[/C][C]-2.62864[/C][/ROW]
[ROW][C]36[/C][C]11.6[/C][C]12.3076[/C][C]-0.70761[/C][/ROW]
[ROW][C]37[/C][C]10.9[/C][C]13.4241[/C][C]-2.5241[/C][/ROW]
[ROW][C]38[/C][C]12.1[/C][C]12.9838[/C][C]-0.883804[/C][/ROW]
[ROW][C]39[/C][C]13.3[/C][C]13.8073[/C][C]-0.507332[/C][/ROW]
[ROW][C]40[/C][C]10.1[/C][C]13.5403[/C][C]-3.44031[/C][/ROW]
[ROW][C]41[/C][C]14.3[/C][C]12.5252[/C][C]1.77483[/C][/ROW]
[ROW][C]42[/C][C]9.3[/C][C]12.9607[/C][C]-3.6607[/C][/ROW]
[ROW][C]43[/C][C]12.5[/C][C]12.258[/C][C]0.242018[/C][/ROW]
[ROW][C]44[/C][C]7.6[/C][C]11.0297[/C][C]-3.42967[/C][/ROW]
[ROW][C]45[/C][C]9.2[/C][C]11.9128[/C][C]-2.71278[/C][/ROW]
[ROW][C]46[/C][C]14.5[/C][C]13.553[/C][C]0.947046[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]14.0354[/C][C]-1.73535[/C][/ROW]
[ROW][C]48[/C][C]12.6[/C][C]13.222[/C][C]-0.62201[/C][/ROW]
[ROW][C]49[/C][C]13[/C][C]13.9555[/C][C]-0.955525[/C][/ROW]
[ROW][C]50[/C][C]12.6[/C][C]11.6689[/C][C]0.931136[/C][/ROW]
[ROW][C]51[/C][C]13.2[/C][C]14.8113[/C][C]-1.61127[/C][/ROW]
[ROW][C]52[/C][C]7.7[/C][C]11.7273[/C][C]-4.02732[/C][/ROW]
[ROW][C]53[/C][C]10.5[/C][C]10.9908[/C][C]-0.490778[/C][/ROW]
[ROW][C]54[/C][C]10.9[/C][C]12.0188[/C][C]-1.11877[/C][/ROW]
[ROW][C]55[/C][C]4.3[/C][C]10.3876[/C][C]-6.08765[/C][/ROW]
[ROW][C]56[/C][C]10.3[/C][C]11.4153[/C][C]-1.11532[/C][/ROW]
[ROW][C]57[/C][C]11.4[/C][C]11.301[/C][C]0.0989546[/C][/ROW]
[ROW][C]58[/C][C]5.6[/C][C]11.3881[/C][C]-5.7881[/C][/ROW]
[ROW][C]59[/C][C]8.8[/C][C]12.1582[/C][C]-3.35818[/C][/ROW]
[ROW][C]60[/C][C]9[/C][C]10.7457[/C][C]-1.74567[/C][/ROW]
[ROW][C]61[/C][C]9.6[/C][C]11.3408[/C][C]-1.74081[/C][/ROW]
[ROW][C]62[/C][C]6.4[/C][C]10.3803[/C][C]-3.9803[/C][/ROW]
[ROW][C]63[/C][C]11.6[/C][C]11.1766[/C][C]0.423355[/C][/ROW]
[ROW][C]64[/C][C]4.35[/C][C]10.273[/C][C]-5.92296[/C][/ROW]
[ROW][C]65[/C][C]12.7[/C][C]12.5469[/C][C]0.153088[/C][/ROW]
[ROW][C]66[/C][C]18.1[/C][C]14.9664[/C][C]3.1336[/C][/ROW]
[ROW][C]67[/C][C]17.85[/C][C]15.2683[/C][C]2.5817[/C][/ROW]
[ROW][C]68[/C][C]16.6[/C][C]15.6799[/C][C]0.920146[/C][/ROW]
[ROW][C]69[/C][C]12.6[/C][C]10.293[/C][C]2.30698[/C][/ROW]
[ROW][C]70[/C][C]17.1[/C][C]22.0341[/C][C]-4.9341[/C][/ROW]
[ROW][C]71[/C][C]19.1[/C][C]15.8362[/C][C]3.26379[/C][/ROW]
[ROW][C]72[/C][C]16.1[/C][C]18.1967[/C][C]-2.09672[/C][/ROW]
[ROW][C]73[/C][C]13.35[/C][C]10.9115[/C][C]2.43849[/C][/ROW]
[ROW][C]74[/C][C]18.4[/C][C]17.5476[/C][C]0.85243[/C][/ROW]
[ROW][C]75[/C][C]14.7[/C][C]11.1605[/C][C]3.53948[/C][/ROW]
[ROW][C]76[/C][C]10.6[/C][C]14.9128[/C][C]-4.31276[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]13.868[/C][C]-1.26797[/C][/ROW]
[ROW][C]78[/C][C]16.2[/C][C]15.1839[/C][C]1.01606[/C][/ROW]
[ROW][C]79[/C][C]13.6[/C][C]17.9868[/C][C]-4.38682[/C][/ROW]
[ROW][C]80[/C][C]18.9[/C][C]16.1148[/C][C]2.78517[/C][/ROW]
[ROW][C]81[/C][C]14.1[/C][C]12.6772[/C][C]1.42275[/C][/ROW]
[ROW][C]82[/C][C]14.5[/C][C]12.1525[/C][C]2.34753[/C][/ROW]
[ROW][C]83[/C][C]16.15[/C][C]18.2574[/C][C]-2.10735[/C][/ROW]
[ROW][C]84[/C][C]14.75[/C][C]13.7448[/C][C]1.00516[/C][/ROW]
[ROW][C]85[/C][C]14.8[/C][C]14.3712[/C][C]0.42878[/C][/ROW]
[ROW][C]86[/C][C]12.45[/C][C]12.4256[/C][C]0.0243924[/C][/ROW]
[ROW][C]87[/C][C]12.65[/C][C]14.7515[/C][C]-2.10153[/C][/ROW]
[ROW][C]88[/C][C]17.35[/C][C]13.9003[/C][C]3.44969[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]12.0142[/C][C]-3.41418[/C][/ROW]
[ROW][C]90[/C][C]18.4[/C][C]17.4872[/C][C]0.912796[/C][/ROW]
[ROW][C]91[/C][C]16.1[/C][C]17.9207[/C][C]-1.82071[/C][/ROW]
[ROW][C]92[/C][C]11.6[/C][C]11.2727[/C][C]0.327322[/C][/ROW]
[ROW][C]93[/C][C]17.75[/C][C]12.5678[/C][C]5.18224[/C][/ROW]
[ROW][C]94[/C][C]15.25[/C][C]13.9692[/C][C]1.28082[/C][/ROW]
[ROW][C]95[/C][C]17.65[/C][C]16.1889[/C][C]1.46105[/C][/ROW]
[ROW][C]96[/C][C]15.6[/C][C]13.9841[/C][C]1.61588[/C][/ROW]
[ROW][C]97[/C][C]16.35[/C][C]15.1612[/C][C]1.1888[/C][/ROW]
[ROW][C]98[/C][C]17.65[/C][C]14.8366[/C][C]2.81339[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]13.2388[/C][C]0.36118[/C][/ROW]
[ROW][C]100[/C][C]11.7[/C][C]12.4947[/C][C]-0.794742[/C][/ROW]
[ROW][C]101[/C][C]14.35[/C][C]13.5961[/C][C]0.753897[/C][/ROW]
[ROW][C]102[/C][C]14.75[/C][C]17.5147[/C][C]-2.76472[/C][/ROW]
[ROW][C]103[/C][C]18.25[/C][C]16.5329[/C][C]1.7171[/C][/ROW]
[ROW][C]104[/C][C]9.9[/C][C]15.3303[/C][C]-5.43026[/C][/ROW]
[ROW][C]105[/C][C]16[/C][C]14.0429[/C][C]1.95711[/C][/ROW]
[ROW][C]106[/C][C]18.25[/C][C]15.8413[/C][C]2.40868[/C][/ROW]
[ROW][C]107[/C][C]16.85[/C][C]17.3353[/C][C]-0.485343[/C][/ROW]
[ROW][C]108[/C][C]14.6[/C][C]12.6041[/C][C]1.99591[/C][/ROW]
[ROW][C]109[/C][C]13.85[/C][C]13.5959[/C][C]0.254056[/C][/ROW]
[ROW][C]110[/C][C]18.95[/C][C]16.287[/C][C]2.66297[/C][/ROW]
[ROW][C]111[/C][C]15.6[/C][C]14.6751[/C][C]0.924876[/C][/ROW]
[ROW][C]112[/C][C]14.85[/C][C]17.1034[/C][C]-2.25341[/C][/ROW]
[ROW][C]113[/C][C]11.75[/C][C]12.6553[/C][C]-0.905259[/C][/ROW]
[ROW][C]114[/C][C]18.45[/C][C]12.8388[/C][C]5.61119[/C][/ROW]
[ROW][C]115[/C][C]15.9[/C][C]17.1086[/C][C]-1.20865[/C][/ROW]
[ROW][C]116[/C][C]17.1[/C][C]14.2326[/C][C]2.86737[/C][/ROW]
[ROW][C]117[/C][C]16.1[/C][C]10.7609[/C][C]5.33908[/C][/ROW]
[ROW][C]118[/C][C]19.9[/C][C]14.9507[/C][C]4.94935[/C][/ROW]
[ROW][C]119[/C][C]10.95[/C][C]10.8911[/C][C]0.0589016[/C][/ROW]
[ROW][C]120[/C][C]18.45[/C][C]15.7025[/C][C]2.74751[/C][/ROW]
[ROW][C]121[/C][C]15.1[/C][C]10.9388[/C][C]4.16116[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]15.5343[/C][C]-0.534284[/C][/ROW]
[ROW][C]123[/C][C]11.35[/C][C]13.9548[/C][C]-2.60481[/C][/ROW]
[ROW][C]124[/C][C]15.95[/C][C]15.0436[/C][C]0.906438[/C][/ROW]
[ROW][C]125[/C][C]18.1[/C][C]13.4094[/C][C]4.69059[/C][/ROW]
[ROW][C]126[/C][C]14.6[/C][C]13.0648[/C][C]1.53519[/C][/ROW]
[ROW][C]127[/C][C]15.4[/C][C]16.1937[/C][C]-0.793689[/C][/ROW]
[ROW][C]128[/C][C]15.4[/C][C]16.1937[/C][C]-0.793689[/C][/ROW]
[ROW][C]129[/C][C]17.6[/C][C]13.557[/C][C]4.04301[/C][/ROW]
[ROW][C]130[/C][C]13.35[/C][C]13.8929[/C][C]-0.542853[/C][/ROW]
[ROW][C]131[/C][C]19.1[/C][C]16.6794[/C][C]2.42057[/C][/ROW]
[ROW][C]132[/C][C]15.35[/C][C]13.1737[/C][C]2.17633[/C][/ROW]
[ROW][C]133[/C][C]7.6[/C][C]12.4006[/C][C]-4.80056[/C][/ROW]
[ROW][C]134[/C][C]13.4[/C][C]13.8577[/C][C]-0.457728[/C][/ROW]
[ROW][C]135[/C][C]13.9[/C][C]13.6565[/C][C]0.243526[/C][/ROW]
[ROW][C]136[/C][C]19.1[/C][C]17.1248[/C][C]1.97518[/C][/ROW]
[ROW][C]137[/C][C]15.25[/C][C]13.7504[/C][C]1.49963[/C][/ROW]
[ROW][C]138[/C][C]12.9[/C][C]12.2453[/C][C]0.654737[/C][/ROW]
[ROW][C]139[/C][C]16.1[/C][C]13.8628[/C][C]2.2372[/C][/ROW]
[ROW][C]140[/C][C]17.35[/C][C]12.5302[/C][C]4.81977[/C][/ROW]
[ROW][C]141[/C][C]13.15[/C][C]12.5288[/C][C]0.621187[/C][/ROW]
[ROW][C]142[/C][C]12.15[/C][C]10.5321[/C][C]1.61794[/C][/ROW]
[ROW][C]143[/C][C]12.6[/C][C]12.5602[/C][C]0.0397651[/C][/ROW]
[ROW][C]144[/C][C]10.35[/C][C]11.6356[/C][C]-1.28557[/C][/ROW]
[ROW][C]145[/C][C]15.4[/C][C]12.6197[/C][C]2.78031[/C][/ROW]
[ROW][C]146[/C][C]9.6[/C][C]10.9759[/C][C]-1.37592[/C][/ROW]
[ROW][C]147[/C][C]18.2[/C][C]13.3719[/C][C]4.82813[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.1922[/C][C]1.40776[/C][/ROW]
[ROW][C]149[/C][C]14.85[/C][C]14.5884[/C][C]0.261583[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]16.9443[/C][C]-2.19431[/C][/ROW]
[ROW][C]151[/C][C]14.1[/C][C]13.8931[/C][C]0.206934[/C][/ROW]
[ROW][C]152[/C][C]14.9[/C][C]11.6742[/C][C]3.22577[/C][/ROW]
[ROW][C]153[/C][C]16.25[/C][C]12.9082[/C][C]3.34184[/C][/ROW]
[ROW][C]154[/C][C]19.25[/C][C]17.8272[/C][C]1.42283[/C][/ROW]
[ROW][C]155[/C][C]13.6[/C][C]12.0257[/C][C]1.57427[/C][/ROW]
[ROW][C]156[/C][C]13.6[/C][C]13.4459[/C][C]0.154139[/C][/ROW]
[ROW][C]157[/C][C]15.65[/C][C]15.1639[/C][C]0.486067[/C][/ROW]
[ROW][C]158[/C][C]12.75[/C][C]12.545[/C][C]0.204972[/C][/ROW]
[ROW][C]159[/C][C]14.6[/C][C]11.4492[/C][C]3.15075[/C][/ROW]
[ROW][C]160[/C][C]9.85[/C][C]13.2816[/C][C]-3.43164[/C][/ROW]
[ROW][C]161[/C][C]12.65[/C][C]11.1767[/C][C]1.47329[/C][/ROW]
[ROW][C]162[/C][C]11.9[/C][C]12.2654[/C][C]-0.36537[/C][/ROW]
[ROW][C]163[/C][C]19.2[/C][C]16.1891[/C][C]3.01085[/C][/ROW]
[ROW][C]164[/C][C]16.6[/C][C]14.2615[/C][C]2.33853[/C][/ROW]
[ROW][C]165[/C][C]11.2[/C][C]9.98868[/C][C]1.21132[/C][/ROW]
[ROW][C]166[/C][C]15.25[/C][C]13.3633[/C][C]1.88669[/C][/ROW]
[ROW][C]167[/C][C]11.9[/C][C]15.1784[/C][C]-3.27838[/C][/ROW]
[ROW][C]168[/C][C]13.2[/C][C]15.716[/C][C]-2.51603[/C][/ROW]
[ROW][C]169[/C][C]16.35[/C][C]17.1156[/C][C]-0.765609[/C][/ROW]
[ROW][C]170[/C][C]12.4[/C][C]13.5492[/C][C]-1.14917[/C][/ROW]
[ROW][C]171[/C][C]15.85[/C][C]13.0479[/C][C]2.80207[/C][/ROW]
[ROW][C]172[/C][C]14.35[/C][C]13.9394[/C][C]0.410634[/C][/ROW]
[ROW][C]173[/C][C]18.15[/C][C]15.1625[/C][C]2.98746[/C][/ROW]
[ROW][C]174[/C][C]11.15[/C][C]11.4851[/C][C]-0.335093[/C][/ROW]
[ROW][C]175[/C][C]15.65[/C][C]15.5892[/C][C]0.0607959[/C][/ROW]
[ROW][C]176[/C][C]17.75[/C][C]16.4816[/C][C]1.26839[/C][/ROW]
[ROW][C]177[/C][C]7.65[/C][C]12.428[/C][C]-4.77803[/C][/ROW]
[ROW][C]178[/C][C]12.35[/C][C]12.2191[/C][C]0.130854[/C][/ROW]
[ROW][C]179[/C][C]15.6[/C][C]11.8066[/C][C]3.79345[/C][/ROW]
[ROW][C]180[/C][C]19.3[/C][C]16.3341[/C][C]2.96588[/C][/ROW]
[ROW][C]181[/C][C]15.2[/C][C]11.929[/C][C]3.271[/C][/ROW]
[ROW][C]182[/C][C]17.1[/C][C]13.564[/C][C]3.53596[/C][/ROW]
[ROW][C]183[/C][C]15.6[/C][C]12.9784[/C][C]2.62163[/C][/ROW]
[ROW][C]184[/C][C]18.4[/C][C]14.7717[/C][C]3.62832[/C][/ROW]
[ROW][C]185[/C][C]19.05[/C][C]15.2077[/C][C]3.84232[/C][/ROW]
[ROW][C]186[/C][C]18.55[/C][C]13.7251[/C][C]4.82489[/C][/ROW]
[ROW][C]187[/C][C]19.1[/C][C]16.6734[/C][C]2.42661[/C][/ROW]
[ROW][C]188[/C][C]13.1[/C][C]11.963[/C][C]1.13702[/C][/ROW]
[ROW][C]189[/C][C]12.85[/C][C]13.5835[/C][C]-0.733523[/C][/ROW]
[ROW][C]190[/C][C]9.5[/C][C]11.6832[/C][C]-2.18318[/C][/ROW]
[ROW][C]191[/C][C]4.5[/C][C]11.3613[/C][C]-6.86129[/C][/ROW]
[ROW][C]192[/C][C]11.85[/C][C]10.7021[/C][C]1.14785[/C][/ROW]
[ROW][C]193[/C][C]13.6[/C][C]16.116[/C][C]-2.51602[/C][/ROW]
[ROW][C]194[/C][C]11.7[/C][C]13.3214[/C][C]-1.62139[/C][/ROW]
[ROW][C]195[/C][C]12.4[/C][C]11.6846[/C][C]0.715408[/C][/ROW]
[ROW][C]196[/C][C]13.35[/C][C]14.7593[/C][C]-1.40928[/C][/ROW]
[ROW][C]197[/C][C]11.4[/C][C]13.7695[/C][C]-2.36953[/C][/ROW]
[ROW][C]198[/C][C]14.9[/C][C]11.9801[/C][C]2.91987[/C][/ROW]
[ROW][C]199[/C][C]19.9[/C][C]14.9507[/C][C]4.94935[/C][/ROW]
[ROW][C]200[/C][C]17.75[/C][C]12.2344[/C][C]5.51558[/C][/ROW]
[ROW][C]201[/C][C]11.2[/C][C]12.1413[/C][C]-0.941272[/C][/ROW]
[ROW][C]202[/C][C]14.6[/C][C]15.4403[/C][C]-0.840339[/C][/ROW]
[ROW][C]203[/C][C]17.6[/C][C]15.7498[/C][C]1.85019[/C][/ROW]
[ROW][C]204[/C][C]14.05[/C][C]12.839[/C][C]1.21097[/C][/ROW]
[ROW][C]205[/C][C]16.1[/C][C]15.0775[/C][C]1.02252[/C][/ROW]
[ROW][C]206[/C][C]13.35[/C][C]13.4306[/C][C]-0.0806368[/C][/ROW]
[ROW][C]207[/C][C]11.85[/C][C]12.8531[/C][C]-1.00314[/C][/ROW]
[ROW][C]208[/C][C]11.95[/C][C]14.2288[/C][C]-2.27876[/C][/ROW]
[ROW][C]209[/C][C]14.75[/C][C]14.5498[/C][C]0.200189[/C][/ROW]
[ROW][C]210[/C][C]15.15[/C][C]13.0006[/C][C]2.14943[/C][/ROW]
[ROW][C]211[/C][C]13.2[/C][C]13.8832[/C][C]-0.683157[/C][/ROW]
[ROW][C]212[/C][C]16.85[/C][C]15.4166[/C][C]1.43341[/C][/ROW]
[ROW][C]213[/C][C]7.85[/C][C]10.4176[/C][C]-2.56763[/C][/ROW]
[ROW][C]214[/C][C]7.7[/C][C]14.7281[/C][C]-7.02812[/C][/ROW]
[ROW][C]215[/C][C]12.6[/C][C]11.7276[/C][C]0.872366[/C][/ROW]
[ROW][C]216[/C][C]7.85[/C][C]11.7421[/C][C]-3.89214[/C][/ROW]
[ROW][C]217[/C][C]10.95[/C][C]10.8911[/C][C]0.0589016[/C][/ROW]
[ROW][C]218[/C][C]12.35[/C][C]12.0713[/C][C]0.278691[/C][/ROW]
[ROW][C]219[/C][C]9.95[/C][C]12.9821[/C][C]-3.03206[/C][/ROW]
[ROW][C]220[/C][C]14.9[/C][C]11.9801[/C][C]2.91987[/C][/ROW]
[ROW][C]221[/C][C]16.65[/C][C]14.6291[/C][C]2.02087[/C][/ROW]
[ROW][C]222[/C][C]13.4[/C][C]12.8911[/C][C]0.508931[/C][/ROW]
[ROW][C]223[/C][C]13.95[/C][C]13.4511[/C][C]0.498857[/C][/ROW]
[ROW][C]224[/C][C]15.7[/C][C]11.9209[/C][C]3.77912[/C][/ROW]
[ROW][C]225[/C][C]16.85[/C][C]12.4458[/C][C]4.40423[/C][/ROW]
[ROW][C]226[/C][C]10.95[/C][C]10.5099[/C][C]0.440054[/C][/ROW]
[ROW][C]227[/C][C]15.35[/C][C]12.0588[/C][C]3.29119[/C][/ROW]
[ROW][C]228[/C][C]12.2[/C][C]11.4125[/C][C]0.787513[/C][/ROW]
[ROW][C]229[/C][C]15.1[/C][C]13.987[/C][C]1.11299[/C][/ROW]
[ROW][C]230[/C][C]17.75[/C][C]16.2832[/C][C]1.4668[/C][/ROW]
[ROW][C]231[/C][C]15.2[/C][C]12.8132[/C][C]2.38676[/C][/ROW]
[ROW][C]232[/C][C]14.6[/C][C]13.5824[/C][C]1.01756[/C][/ROW]
[ROW][C]233[/C][C]16.65[/C][C]14.7329[/C][C]1.91711[/C][/ROW]
[ROW][C]234[/C][C]8.1[/C][C]10.894[/C][C]-2.79399[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265155&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265155&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
112.912.11350.786499
212.812.5890.210986
37.413.0514-5.65144
46.711.7571-5.05707
512.615.8176-3.21758
614.812.9561.84395
713.312.45620.843756
811.113.0683-1.9683
98.214.5202-6.32019
1011.413.2432-1.84317
116.414.7202-8.32019
121213.9839-1.98385
136.310.0708-3.77075
1411.311.5843-0.284252
1511.914.1371-2.23714
169.312.4696-3.16958
171011.8267-1.82672
1813.813.74030.0596755
1910.813.7584-2.95837
2011.713.0107-1.31067
2110.915.33-4.43002
2216.113.90692.19314
239.911.4493-1.54926
2411.512.4914-0.99137
258.312.0448-3.74484
2611.713.655-1.95499
27912.6522-3.65221
2810.812.822-2.022
2910.412.0141-1.61414
3012.713.176-0.475969
3111.814.5587-2.75868
321312.17970.820296
3310.812.8412-2.04124
3412.310.65681.64322
3511.313.9286-2.62864
3611.612.3076-0.70761
3710.913.4241-2.5241
3812.112.9838-0.883804
3913.313.8073-0.507332
4010.113.5403-3.44031
4114.312.52521.77483
429.312.9607-3.6607
4312.512.2580.242018
447.611.0297-3.42967
459.211.9128-2.71278
4614.513.5530.947046
4712.314.0354-1.73535
4812.613.222-0.62201
491313.9555-0.955525
5012.611.66890.931136
5113.214.8113-1.61127
527.711.7273-4.02732
5310.510.9908-0.490778
5410.912.0188-1.11877
554.310.3876-6.08765
5610.311.4153-1.11532
5711.411.3010.0989546
585.611.3881-5.7881
598.812.1582-3.35818
60910.7457-1.74567
619.611.3408-1.74081
626.410.3803-3.9803
6311.611.17660.423355
644.3510.273-5.92296
6512.712.54690.153088
6618.114.96643.1336
6717.8515.26832.5817
6816.615.67990.920146
6912.610.2932.30698
7017.122.0341-4.9341
7119.115.83623.26379
7216.118.1967-2.09672
7313.3510.91152.43849
7418.417.54760.85243
7514.711.16053.53948
7610.614.9128-4.31276
7712.613.868-1.26797
7816.215.18391.01606
7913.617.9868-4.38682
8018.916.11482.78517
8114.112.67721.42275
8214.512.15252.34753
8316.1518.2574-2.10735
8414.7513.74481.00516
8514.814.37120.42878
8612.4512.42560.0243924
8712.6514.7515-2.10153
8817.3513.90033.44969
898.612.0142-3.41418
9018.417.48720.912796
9116.117.9207-1.82071
9211.611.27270.327322
9317.7512.56785.18224
9415.2513.96921.28082
9517.6516.18891.46105
9615.613.98411.61588
9716.3515.16121.1888
9817.6514.83662.81339
9913.613.23880.36118
10011.712.4947-0.794742
10114.3513.59610.753897
10214.7517.5147-2.76472
10318.2516.53291.7171
1049.915.3303-5.43026
1051614.04291.95711
10618.2515.84132.40868
10716.8517.3353-0.485343
10814.612.60411.99591
10913.8513.59590.254056
11018.9516.2872.66297
11115.614.67510.924876
11214.8517.1034-2.25341
11311.7512.6553-0.905259
11418.4512.83885.61119
11515.917.1086-1.20865
11617.114.23262.86737
11716.110.76095.33908
11819.914.95074.94935
11910.9510.89110.0589016
12018.4515.70252.74751
12115.110.93884.16116
1221515.5343-0.534284
12311.3513.9548-2.60481
12415.9515.04360.906438
12518.113.40944.69059
12614.613.06481.53519
12715.416.1937-0.793689
12815.416.1937-0.793689
12917.613.5574.04301
13013.3513.8929-0.542853
13119.116.67942.42057
13215.3513.17372.17633
1337.612.4006-4.80056
13413.413.8577-0.457728
13513.913.65650.243526
13619.117.12481.97518
13715.2513.75041.49963
13812.912.24530.654737
13916.113.86282.2372
14017.3512.53024.81977
14113.1512.52880.621187
14212.1510.53211.61794
14312.612.56020.0397651
14410.3511.6356-1.28557
14515.412.61972.78031
1469.610.9759-1.37592
14718.213.37194.82813
14813.612.19221.40776
14914.8514.58840.261583
15014.7516.9443-2.19431
15114.113.89310.206934
15214.911.67423.22577
15316.2512.90823.34184
15419.2517.82721.42283
15513.612.02571.57427
15613.613.44590.154139
15715.6515.16390.486067
15812.7512.5450.204972
15914.611.44923.15075
1609.8513.2816-3.43164
16112.6511.17671.47329
16211.912.2654-0.36537
16319.216.18913.01085
16416.614.26152.33853
16511.29.988681.21132
16615.2513.36331.88669
16711.915.1784-3.27838
16813.215.716-2.51603
16916.3517.1156-0.765609
17012.413.5492-1.14917
17115.8513.04792.80207
17214.3513.93940.410634
17318.1515.16252.98746
17411.1511.4851-0.335093
17515.6515.58920.0607959
17617.7516.48161.26839
1777.6512.428-4.77803
17812.3512.21910.130854
17915.611.80663.79345
18019.316.33412.96588
18115.211.9293.271
18217.113.5643.53596
18315.612.97842.62163
18418.414.77173.62832
18519.0515.20773.84232
18618.5513.72514.82489
18719.116.67342.42661
18813.111.9631.13702
18912.8513.5835-0.733523
1909.511.6832-2.18318
1914.511.3613-6.86129
19211.8510.70211.14785
19313.616.116-2.51602
19411.713.3214-1.62139
19512.411.68460.715408
19613.3514.7593-1.40928
19711.413.7695-2.36953
19814.911.98012.91987
19919.914.95074.94935
20017.7512.23445.51558
20111.212.1413-0.941272
20214.615.4403-0.840339
20317.615.74981.85019
20414.0512.8391.21097
20516.115.07751.02252
20613.3513.4306-0.0806368
20711.8512.8531-1.00314
20811.9514.2288-2.27876
20914.7514.54980.200189
21015.1513.00062.14943
21113.213.8832-0.683157
21216.8515.41661.43341
2137.8510.4176-2.56763
2147.714.7281-7.02812
21512.611.72760.872366
2167.8511.7421-3.89214
21710.9510.89110.0589016
21812.3512.07130.278691
2199.9512.9821-3.03206
22014.911.98012.91987
22116.6514.62912.02087
22213.412.89110.508931
22313.9513.45110.498857
22415.711.92093.77912
22516.8512.44584.40423
22610.9510.50990.440054
22715.3512.05883.29119
22812.211.41250.787513
22915.113.9871.11299
23017.7516.28321.4668
23115.212.81322.38676
23214.613.58241.01756
23316.6514.73291.91711
2348.110.894-2.79399






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.8792030.2415950.120797
90.8905950.218810.109405
100.8188130.3623750.181187
110.8756190.2487610.124381
120.8143870.3712250.185613
130.7449180.5101640.255082
140.7738780.4522440.226122
150.7155980.5688040.284402
160.6424790.7150430.357521
170.5626170.8747660.437383
180.5503280.8993450.449672
190.4936270.9872550.506373
200.4232690.8465380.576731
210.3796690.7593380.620331
220.3344740.6689480.665526
230.2900290.5800580.709971
240.2640550.528110.735945
250.2221730.4443470.777827
260.2187460.4374920.781254
270.1840480.3680950.815952
280.1536490.3072970.846351
290.1237930.2475850.876207
300.1294590.2589190.870541
310.1155050.2310110.884495
320.09344010.186880.90656
330.07651290.1530260.923487
340.08626910.1725380.913731
350.07222740.1444550.927773
360.06032650.1206530.939674
370.05417070.1083410.945829
380.0523290.1046580.947671
390.05311090.1062220.946889
400.04354260.08708520.956457
410.05978240.1195650.940218
420.06520790.1304160.934792
430.05147870.1029570.948521
440.05984780.1196960.940152
450.06670020.13340.9333
460.06082320.1216460.939177
470.05404630.1080930.945954
480.05157980.103160.94842
490.04861490.09722980.951385
500.04223790.08447570.957762
510.04632310.09264630.953677
520.06640560.1328110.933594
530.05380470.1076090.946195
540.04401530.08803050.955985
550.1366940.2733880.863306
560.1257990.2515970.874201
570.103890.207780.89611
580.1995580.3991160.800442
590.1947080.3894160.805292
600.1926110.3852220.807389
610.2008380.4016760.799162
620.2238570.4477140.776143
630.2252010.4504020.774799
640.3870680.7741360.612932
650.4169110.8338220.583089
660.6187330.7625340.381267
670.7113070.5773860.288693
680.6959420.6081150.304058
690.7503640.4992720.249636
700.7677420.4645160.232258
710.8035250.3929510.196475
720.8199120.3601750.180088
730.8524780.2950450.147522
740.8587090.2825820.141291
750.9079950.184010.092005
760.9278250.1443510.0721754
770.9155930.1688130.0844066
780.9156890.1686230.0843113
790.9444440.1111130.0555565
800.9508740.09825170.0491258
810.9482940.1034120.051706
820.9538420.09231650.0461583
830.9507220.09855590.0492779
840.9451330.1097340.0548671
850.9361180.1277630.0638817
860.9244130.1511740.0755869
870.9136350.1727310.0863654
880.9423090.1153820.0576912
890.9428450.114310.0571549
900.9399530.1200930.0600467
910.929120.1417610.0708803
920.917880.1642410.0821205
930.9575770.08484640.0424232
940.9564840.0870320.043516
950.9564680.08706340.0435317
960.9533950.09321090.0466054
970.9487440.1025130.0512565
980.9559130.08817410.044087
990.9482880.1034230.0517116
1000.943590.1128210.0564103
1010.9350050.129990.064995
1020.9280620.1438760.0719379
1030.9238410.1523170.0761587
1040.9701170.05976650.0298832
1050.9692520.06149660.0307483
1060.9701540.05969180.0298459
1070.9637240.07255220.0362761
1080.9646360.07072820.0353641
1090.9583650.08326910.0416346
1100.9602330.07953380.0397669
1110.9535840.09283290.0464165
1120.9498220.1003560.0501778
1130.9408630.1182740.0591368
1140.9676220.06475590.032378
1150.9620950.0758090.0379045
1160.964230.07153910.0357696
1170.99220.01559930.00779966
1180.9945490.01090260.0054513
1190.9929070.01418670.00709334
1200.9929910.01401840.00700921
1210.9953050.009389750.00469488
1220.9938980.01220440.00610221
1230.9941650.01166910.00583454
1240.992890.014220.00711
1250.9953660.009268510.00463425
1260.9948530.01029460.00514732
1270.9934940.01301140.00650572
1280.9918830.01623330.00811666
1290.9935480.01290470.00645233
1300.992630.01474050.00737027
1310.9925940.01481130.00740565
1320.9918030.01639380.00819688
1330.9943970.01120640.00560319
1340.993790.01241920.00620959
1350.992150.01570010.00785006
1360.9909520.01809510.00904757
1370.9888090.02238230.0111911
1380.9880370.0239260.011963
1390.9860660.02786740.0139337
1400.9923660.01526760.0076338
1410.9905650.01886940.00943468
1420.98840.02320060.0116003
1430.985150.02970020.0148501
1440.9819060.03618820.0180941
1450.9795540.04089250.0204462
1460.9769470.04610550.0230528
1470.9855430.02891330.0144567
1480.9825180.03496480.0174824
1490.9796550.04068930.0203447
1500.9796070.04078540.0203927
1510.9741880.05162420.0258121
1520.9772940.04541260.0227063
1530.9767640.04647220.0232361
1540.9732540.0534930.0267465
1550.9709350.05813010.029065
1560.9672950.06540910.0327046
1570.9598420.08031650.0401582
1580.9509130.09817470.0490873
1590.9603440.07931290.0396564
1600.9585390.0829210.0414605
1610.9555780.08884460.0444223
1620.9454560.1090890.0545444
1630.9417140.1165730.0582864
1640.9363780.1272440.063622
1650.9240570.1518850.0759426
1660.9115020.1769950.0884976
1670.9283740.1432510.0716257
1680.9180880.1638230.0819117
1690.9132670.1734660.0867328
1700.8997420.2005150.100258
1710.8954830.2090340.104517
1720.8793310.2413370.120669
1730.8668380.2663250.133162
1740.8413690.3172630.158631
1750.8125550.3748910.187445
1760.7917240.4165510.208276
1770.8208280.3583450.179172
1780.7896440.4207120.210356
1790.7928110.4143790.207189
1800.7768690.4462630.223131
1810.8393130.3213740.160687
1820.8600030.2799940.139997
1830.8700520.2598970.129948
1840.8564620.2870760.143538
1850.8730570.2538850.126943
1860.9001890.1996230.0998114
1870.8807130.2385750.119287
1880.8597120.2805750.140288
1890.8517940.2964120.148206
1900.8472650.305470.152735
1910.9443590.1112810.0556406
1920.9389710.1220590.0610293
1930.940850.11830.0591501
1940.9259550.1480910.0740454
1950.9050870.1898270.0949134
1960.890430.2191390.10957
1970.8689660.2620680.131034
1980.8573130.2853740.142687
1990.8460560.3078880.153944
2000.9134430.1731140.0865568
2010.8881170.2237650.111883
2020.861430.277140.13857
2030.8317860.3364290.168214
2040.7969850.4060290.203015
2050.7523220.4953560.247678
2060.6991510.6016970.300849
2070.6546330.6907350.345367
2080.6546690.6906630.345331
2090.5915080.8169840.408492
2100.5288350.942330.471165
2110.5845280.8309440.415472
2120.5198140.9603710.480186
2130.5218740.9562510.478126
2140.916440.167120.0835602
2150.8798050.2403910.120195
2160.9952650.009469770.00473489
2170.9976990.004602930.00230147
2180.9979250.004150190.00207509
2190.9998250.0003502070.000175103
2200.9994730.00105330.000526648
2210.9990190.001961050.000980526
2220.9980040.003991860.00199593
2230.9980270.00394560.0019728
2240.9943460.01130820.00565411
2250.9905440.01891190.00945594
2260.9633240.07335170.0366758

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.879203 & 0.241595 & 0.120797 \tabularnewline
9 & 0.890595 & 0.21881 & 0.109405 \tabularnewline
10 & 0.818813 & 0.362375 & 0.181187 \tabularnewline
11 & 0.875619 & 0.248761 & 0.124381 \tabularnewline
12 & 0.814387 & 0.371225 & 0.185613 \tabularnewline
13 & 0.744918 & 0.510164 & 0.255082 \tabularnewline
14 & 0.773878 & 0.452244 & 0.226122 \tabularnewline
15 & 0.715598 & 0.568804 & 0.284402 \tabularnewline
16 & 0.642479 & 0.715043 & 0.357521 \tabularnewline
17 & 0.562617 & 0.874766 & 0.437383 \tabularnewline
18 & 0.550328 & 0.899345 & 0.449672 \tabularnewline
19 & 0.493627 & 0.987255 & 0.506373 \tabularnewline
20 & 0.423269 & 0.846538 & 0.576731 \tabularnewline
21 & 0.379669 & 0.759338 & 0.620331 \tabularnewline
22 & 0.334474 & 0.668948 & 0.665526 \tabularnewline
23 & 0.290029 & 0.580058 & 0.709971 \tabularnewline
24 & 0.264055 & 0.52811 & 0.735945 \tabularnewline
25 & 0.222173 & 0.444347 & 0.777827 \tabularnewline
26 & 0.218746 & 0.437492 & 0.781254 \tabularnewline
27 & 0.184048 & 0.368095 & 0.815952 \tabularnewline
28 & 0.153649 & 0.307297 & 0.846351 \tabularnewline
29 & 0.123793 & 0.247585 & 0.876207 \tabularnewline
30 & 0.129459 & 0.258919 & 0.870541 \tabularnewline
31 & 0.115505 & 0.231011 & 0.884495 \tabularnewline
32 & 0.0934401 & 0.18688 & 0.90656 \tabularnewline
33 & 0.0765129 & 0.153026 & 0.923487 \tabularnewline
34 & 0.0862691 & 0.172538 & 0.913731 \tabularnewline
35 & 0.0722274 & 0.144455 & 0.927773 \tabularnewline
36 & 0.0603265 & 0.120653 & 0.939674 \tabularnewline
37 & 0.0541707 & 0.108341 & 0.945829 \tabularnewline
38 & 0.052329 & 0.104658 & 0.947671 \tabularnewline
39 & 0.0531109 & 0.106222 & 0.946889 \tabularnewline
40 & 0.0435426 & 0.0870852 & 0.956457 \tabularnewline
41 & 0.0597824 & 0.119565 & 0.940218 \tabularnewline
42 & 0.0652079 & 0.130416 & 0.934792 \tabularnewline
43 & 0.0514787 & 0.102957 & 0.948521 \tabularnewline
44 & 0.0598478 & 0.119696 & 0.940152 \tabularnewline
45 & 0.0667002 & 0.1334 & 0.9333 \tabularnewline
46 & 0.0608232 & 0.121646 & 0.939177 \tabularnewline
47 & 0.0540463 & 0.108093 & 0.945954 \tabularnewline
48 & 0.0515798 & 0.10316 & 0.94842 \tabularnewline
49 & 0.0486149 & 0.0972298 & 0.951385 \tabularnewline
50 & 0.0422379 & 0.0844757 & 0.957762 \tabularnewline
51 & 0.0463231 & 0.0926463 & 0.953677 \tabularnewline
52 & 0.0664056 & 0.132811 & 0.933594 \tabularnewline
53 & 0.0538047 & 0.107609 & 0.946195 \tabularnewline
54 & 0.0440153 & 0.0880305 & 0.955985 \tabularnewline
55 & 0.136694 & 0.273388 & 0.863306 \tabularnewline
56 & 0.125799 & 0.251597 & 0.874201 \tabularnewline
57 & 0.10389 & 0.20778 & 0.89611 \tabularnewline
58 & 0.199558 & 0.399116 & 0.800442 \tabularnewline
59 & 0.194708 & 0.389416 & 0.805292 \tabularnewline
60 & 0.192611 & 0.385222 & 0.807389 \tabularnewline
61 & 0.200838 & 0.401676 & 0.799162 \tabularnewline
62 & 0.223857 & 0.447714 & 0.776143 \tabularnewline
63 & 0.225201 & 0.450402 & 0.774799 \tabularnewline
64 & 0.387068 & 0.774136 & 0.612932 \tabularnewline
65 & 0.416911 & 0.833822 & 0.583089 \tabularnewline
66 & 0.618733 & 0.762534 & 0.381267 \tabularnewline
67 & 0.711307 & 0.577386 & 0.288693 \tabularnewline
68 & 0.695942 & 0.608115 & 0.304058 \tabularnewline
69 & 0.750364 & 0.499272 & 0.249636 \tabularnewline
70 & 0.767742 & 0.464516 & 0.232258 \tabularnewline
71 & 0.803525 & 0.392951 & 0.196475 \tabularnewline
72 & 0.819912 & 0.360175 & 0.180088 \tabularnewline
73 & 0.852478 & 0.295045 & 0.147522 \tabularnewline
74 & 0.858709 & 0.282582 & 0.141291 \tabularnewline
75 & 0.907995 & 0.18401 & 0.092005 \tabularnewline
76 & 0.927825 & 0.144351 & 0.0721754 \tabularnewline
77 & 0.915593 & 0.168813 & 0.0844066 \tabularnewline
78 & 0.915689 & 0.168623 & 0.0843113 \tabularnewline
79 & 0.944444 & 0.111113 & 0.0555565 \tabularnewline
80 & 0.950874 & 0.0982517 & 0.0491258 \tabularnewline
81 & 0.948294 & 0.103412 & 0.051706 \tabularnewline
82 & 0.953842 & 0.0923165 & 0.0461583 \tabularnewline
83 & 0.950722 & 0.0985559 & 0.0492779 \tabularnewline
84 & 0.945133 & 0.109734 & 0.0548671 \tabularnewline
85 & 0.936118 & 0.127763 & 0.0638817 \tabularnewline
86 & 0.924413 & 0.151174 & 0.0755869 \tabularnewline
87 & 0.913635 & 0.172731 & 0.0863654 \tabularnewline
88 & 0.942309 & 0.115382 & 0.0576912 \tabularnewline
89 & 0.942845 & 0.11431 & 0.0571549 \tabularnewline
90 & 0.939953 & 0.120093 & 0.0600467 \tabularnewline
91 & 0.92912 & 0.141761 & 0.0708803 \tabularnewline
92 & 0.91788 & 0.164241 & 0.0821205 \tabularnewline
93 & 0.957577 & 0.0848464 & 0.0424232 \tabularnewline
94 & 0.956484 & 0.087032 & 0.043516 \tabularnewline
95 & 0.956468 & 0.0870634 & 0.0435317 \tabularnewline
96 & 0.953395 & 0.0932109 & 0.0466054 \tabularnewline
97 & 0.948744 & 0.102513 & 0.0512565 \tabularnewline
98 & 0.955913 & 0.0881741 & 0.044087 \tabularnewline
99 & 0.948288 & 0.103423 & 0.0517116 \tabularnewline
100 & 0.94359 & 0.112821 & 0.0564103 \tabularnewline
101 & 0.935005 & 0.12999 & 0.064995 \tabularnewline
102 & 0.928062 & 0.143876 & 0.0719379 \tabularnewline
103 & 0.923841 & 0.152317 & 0.0761587 \tabularnewline
104 & 0.970117 & 0.0597665 & 0.0298832 \tabularnewline
105 & 0.969252 & 0.0614966 & 0.0307483 \tabularnewline
106 & 0.970154 & 0.0596918 & 0.0298459 \tabularnewline
107 & 0.963724 & 0.0725522 & 0.0362761 \tabularnewline
108 & 0.964636 & 0.0707282 & 0.0353641 \tabularnewline
109 & 0.958365 & 0.0832691 & 0.0416346 \tabularnewline
110 & 0.960233 & 0.0795338 & 0.0397669 \tabularnewline
111 & 0.953584 & 0.0928329 & 0.0464165 \tabularnewline
112 & 0.949822 & 0.100356 & 0.0501778 \tabularnewline
113 & 0.940863 & 0.118274 & 0.0591368 \tabularnewline
114 & 0.967622 & 0.0647559 & 0.032378 \tabularnewline
115 & 0.962095 & 0.075809 & 0.0379045 \tabularnewline
116 & 0.96423 & 0.0715391 & 0.0357696 \tabularnewline
117 & 0.9922 & 0.0155993 & 0.00779966 \tabularnewline
118 & 0.994549 & 0.0109026 & 0.0054513 \tabularnewline
119 & 0.992907 & 0.0141867 & 0.00709334 \tabularnewline
120 & 0.992991 & 0.0140184 & 0.00700921 \tabularnewline
121 & 0.995305 & 0.00938975 & 0.00469488 \tabularnewline
122 & 0.993898 & 0.0122044 & 0.00610221 \tabularnewline
123 & 0.994165 & 0.0116691 & 0.00583454 \tabularnewline
124 & 0.99289 & 0.01422 & 0.00711 \tabularnewline
125 & 0.995366 & 0.00926851 & 0.00463425 \tabularnewline
126 & 0.994853 & 0.0102946 & 0.00514732 \tabularnewline
127 & 0.993494 & 0.0130114 & 0.00650572 \tabularnewline
128 & 0.991883 & 0.0162333 & 0.00811666 \tabularnewline
129 & 0.993548 & 0.0129047 & 0.00645233 \tabularnewline
130 & 0.99263 & 0.0147405 & 0.00737027 \tabularnewline
131 & 0.992594 & 0.0148113 & 0.00740565 \tabularnewline
132 & 0.991803 & 0.0163938 & 0.00819688 \tabularnewline
133 & 0.994397 & 0.0112064 & 0.00560319 \tabularnewline
134 & 0.99379 & 0.0124192 & 0.00620959 \tabularnewline
135 & 0.99215 & 0.0157001 & 0.00785006 \tabularnewline
136 & 0.990952 & 0.0180951 & 0.00904757 \tabularnewline
137 & 0.988809 & 0.0223823 & 0.0111911 \tabularnewline
138 & 0.988037 & 0.023926 & 0.011963 \tabularnewline
139 & 0.986066 & 0.0278674 & 0.0139337 \tabularnewline
140 & 0.992366 & 0.0152676 & 0.0076338 \tabularnewline
141 & 0.990565 & 0.0188694 & 0.00943468 \tabularnewline
142 & 0.9884 & 0.0232006 & 0.0116003 \tabularnewline
143 & 0.98515 & 0.0297002 & 0.0148501 \tabularnewline
144 & 0.981906 & 0.0361882 & 0.0180941 \tabularnewline
145 & 0.979554 & 0.0408925 & 0.0204462 \tabularnewline
146 & 0.976947 & 0.0461055 & 0.0230528 \tabularnewline
147 & 0.985543 & 0.0289133 & 0.0144567 \tabularnewline
148 & 0.982518 & 0.0349648 & 0.0174824 \tabularnewline
149 & 0.979655 & 0.0406893 & 0.0203447 \tabularnewline
150 & 0.979607 & 0.0407854 & 0.0203927 \tabularnewline
151 & 0.974188 & 0.0516242 & 0.0258121 \tabularnewline
152 & 0.977294 & 0.0454126 & 0.0227063 \tabularnewline
153 & 0.976764 & 0.0464722 & 0.0232361 \tabularnewline
154 & 0.973254 & 0.053493 & 0.0267465 \tabularnewline
155 & 0.970935 & 0.0581301 & 0.029065 \tabularnewline
156 & 0.967295 & 0.0654091 & 0.0327046 \tabularnewline
157 & 0.959842 & 0.0803165 & 0.0401582 \tabularnewline
158 & 0.950913 & 0.0981747 & 0.0490873 \tabularnewline
159 & 0.960344 & 0.0793129 & 0.0396564 \tabularnewline
160 & 0.958539 & 0.082921 & 0.0414605 \tabularnewline
161 & 0.955578 & 0.0888446 & 0.0444223 \tabularnewline
162 & 0.945456 & 0.109089 & 0.0545444 \tabularnewline
163 & 0.941714 & 0.116573 & 0.0582864 \tabularnewline
164 & 0.936378 & 0.127244 & 0.063622 \tabularnewline
165 & 0.924057 & 0.151885 & 0.0759426 \tabularnewline
166 & 0.911502 & 0.176995 & 0.0884976 \tabularnewline
167 & 0.928374 & 0.143251 & 0.0716257 \tabularnewline
168 & 0.918088 & 0.163823 & 0.0819117 \tabularnewline
169 & 0.913267 & 0.173466 & 0.0867328 \tabularnewline
170 & 0.899742 & 0.200515 & 0.100258 \tabularnewline
171 & 0.895483 & 0.209034 & 0.104517 \tabularnewline
172 & 0.879331 & 0.241337 & 0.120669 \tabularnewline
173 & 0.866838 & 0.266325 & 0.133162 \tabularnewline
174 & 0.841369 & 0.317263 & 0.158631 \tabularnewline
175 & 0.812555 & 0.374891 & 0.187445 \tabularnewline
176 & 0.791724 & 0.416551 & 0.208276 \tabularnewline
177 & 0.820828 & 0.358345 & 0.179172 \tabularnewline
178 & 0.789644 & 0.420712 & 0.210356 \tabularnewline
179 & 0.792811 & 0.414379 & 0.207189 \tabularnewline
180 & 0.776869 & 0.446263 & 0.223131 \tabularnewline
181 & 0.839313 & 0.321374 & 0.160687 \tabularnewline
182 & 0.860003 & 0.279994 & 0.139997 \tabularnewline
183 & 0.870052 & 0.259897 & 0.129948 \tabularnewline
184 & 0.856462 & 0.287076 & 0.143538 \tabularnewline
185 & 0.873057 & 0.253885 & 0.126943 \tabularnewline
186 & 0.900189 & 0.199623 & 0.0998114 \tabularnewline
187 & 0.880713 & 0.238575 & 0.119287 \tabularnewline
188 & 0.859712 & 0.280575 & 0.140288 \tabularnewline
189 & 0.851794 & 0.296412 & 0.148206 \tabularnewline
190 & 0.847265 & 0.30547 & 0.152735 \tabularnewline
191 & 0.944359 & 0.111281 & 0.0556406 \tabularnewline
192 & 0.938971 & 0.122059 & 0.0610293 \tabularnewline
193 & 0.94085 & 0.1183 & 0.0591501 \tabularnewline
194 & 0.925955 & 0.148091 & 0.0740454 \tabularnewline
195 & 0.905087 & 0.189827 & 0.0949134 \tabularnewline
196 & 0.89043 & 0.219139 & 0.10957 \tabularnewline
197 & 0.868966 & 0.262068 & 0.131034 \tabularnewline
198 & 0.857313 & 0.285374 & 0.142687 \tabularnewline
199 & 0.846056 & 0.307888 & 0.153944 \tabularnewline
200 & 0.913443 & 0.173114 & 0.0865568 \tabularnewline
201 & 0.888117 & 0.223765 & 0.111883 \tabularnewline
202 & 0.86143 & 0.27714 & 0.13857 \tabularnewline
203 & 0.831786 & 0.336429 & 0.168214 \tabularnewline
204 & 0.796985 & 0.406029 & 0.203015 \tabularnewline
205 & 0.752322 & 0.495356 & 0.247678 \tabularnewline
206 & 0.699151 & 0.601697 & 0.300849 \tabularnewline
207 & 0.654633 & 0.690735 & 0.345367 \tabularnewline
208 & 0.654669 & 0.690663 & 0.345331 \tabularnewline
209 & 0.591508 & 0.816984 & 0.408492 \tabularnewline
210 & 0.528835 & 0.94233 & 0.471165 \tabularnewline
211 & 0.584528 & 0.830944 & 0.415472 \tabularnewline
212 & 0.519814 & 0.960371 & 0.480186 \tabularnewline
213 & 0.521874 & 0.956251 & 0.478126 \tabularnewline
214 & 0.91644 & 0.16712 & 0.0835602 \tabularnewline
215 & 0.879805 & 0.240391 & 0.120195 \tabularnewline
216 & 0.995265 & 0.00946977 & 0.00473489 \tabularnewline
217 & 0.997699 & 0.00460293 & 0.00230147 \tabularnewline
218 & 0.997925 & 0.00415019 & 0.00207509 \tabularnewline
219 & 0.999825 & 0.000350207 & 0.000175103 \tabularnewline
220 & 0.999473 & 0.0010533 & 0.000526648 \tabularnewline
221 & 0.999019 & 0.00196105 & 0.000980526 \tabularnewline
222 & 0.998004 & 0.00399186 & 0.00199593 \tabularnewline
223 & 0.998027 & 0.0039456 & 0.0019728 \tabularnewline
224 & 0.994346 & 0.0113082 & 0.00565411 \tabularnewline
225 & 0.990544 & 0.0189119 & 0.00945594 \tabularnewline
226 & 0.963324 & 0.0733517 & 0.0366758 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265155&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]8[/C][C]0.879203[/C][C]0.241595[/C][C]0.120797[/C][/ROW]
[ROW][C]9[/C][C]0.890595[/C][C]0.21881[/C][C]0.109405[/C][/ROW]
[ROW][C]10[/C][C]0.818813[/C][C]0.362375[/C][C]0.181187[/C][/ROW]
[ROW][C]11[/C][C]0.875619[/C][C]0.248761[/C][C]0.124381[/C][/ROW]
[ROW][C]12[/C][C]0.814387[/C][C]0.371225[/C][C]0.185613[/C][/ROW]
[ROW][C]13[/C][C]0.744918[/C][C]0.510164[/C][C]0.255082[/C][/ROW]
[ROW][C]14[/C][C]0.773878[/C][C]0.452244[/C][C]0.226122[/C][/ROW]
[ROW][C]15[/C][C]0.715598[/C][C]0.568804[/C][C]0.284402[/C][/ROW]
[ROW][C]16[/C][C]0.642479[/C][C]0.715043[/C][C]0.357521[/C][/ROW]
[ROW][C]17[/C][C]0.562617[/C][C]0.874766[/C][C]0.437383[/C][/ROW]
[ROW][C]18[/C][C]0.550328[/C][C]0.899345[/C][C]0.449672[/C][/ROW]
[ROW][C]19[/C][C]0.493627[/C][C]0.987255[/C][C]0.506373[/C][/ROW]
[ROW][C]20[/C][C]0.423269[/C][C]0.846538[/C][C]0.576731[/C][/ROW]
[ROW][C]21[/C][C]0.379669[/C][C]0.759338[/C][C]0.620331[/C][/ROW]
[ROW][C]22[/C][C]0.334474[/C][C]0.668948[/C][C]0.665526[/C][/ROW]
[ROW][C]23[/C][C]0.290029[/C][C]0.580058[/C][C]0.709971[/C][/ROW]
[ROW][C]24[/C][C]0.264055[/C][C]0.52811[/C][C]0.735945[/C][/ROW]
[ROW][C]25[/C][C]0.222173[/C][C]0.444347[/C][C]0.777827[/C][/ROW]
[ROW][C]26[/C][C]0.218746[/C][C]0.437492[/C][C]0.781254[/C][/ROW]
[ROW][C]27[/C][C]0.184048[/C][C]0.368095[/C][C]0.815952[/C][/ROW]
[ROW][C]28[/C][C]0.153649[/C][C]0.307297[/C][C]0.846351[/C][/ROW]
[ROW][C]29[/C][C]0.123793[/C][C]0.247585[/C][C]0.876207[/C][/ROW]
[ROW][C]30[/C][C]0.129459[/C][C]0.258919[/C][C]0.870541[/C][/ROW]
[ROW][C]31[/C][C]0.115505[/C][C]0.231011[/C][C]0.884495[/C][/ROW]
[ROW][C]32[/C][C]0.0934401[/C][C]0.18688[/C][C]0.90656[/C][/ROW]
[ROW][C]33[/C][C]0.0765129[/C][C]0.153026[/C][C]0.923487[/C][/ROW]
[ROW][C]34[/C][C]0.0862691[/C][C]0.172538[/C][C]0.913731[/C][/ROW]
[ROW][C]35[/C][C]0.0722274[/C][C]0.144455[/C][C]0.927773[/C][/ROW]
[ROW][C]36[/C][C]0.0603265[/C][C]0.120653[/C][C]0.939674[/C][/ROW]
[ROW][C]37[/C][C]0.0541707[/C][C]0.108341[/C][C]0.945829[/C][/ROW]
[ROW][C]38[/C][C]0.052329[/C][C]0.104658[/C][C]0.947671[/C][/ROW]
[ROW][C]39[/C][C]0.0531109[/C][C]0.106222[/C][C]0.946889[/C][/ROW]
[ROW][C]40[/C][C]0.0435426[/C][C]0.0870852[/C][C]0.956457[/C][/ROW]
[ROW][C]41[/C][C]0.0597824[/C][C]0.119565[/C][C]0.940218[/C][/ROW]
[ROW][C]42[/C][C]0.0652079[/C][C]0.130416[/C][C]0.934792[/C][/ROW]
[ROW][C]43[/C][C]0.0514787[/C][C]0.102957[/C][C]0.948521[/C][/ROW]
[ROW][C]44[/C][C]0.0598478[/C][C]0.119696[/C][C]0.940152[/C][/ROW]
[ROW][C]45[/C][C]0.0667002[/C][C]0.1334[/C][C]0.9333[/C][/ROW]
[ROW][C]46[/C][C]0.0608232[/C][C]0.121646[/C][C]0.939177[/C][/ROW]
[ROW][C]47[/C][C]0.0540463[/C][C]0.108093[/C][C]0.945954[/C][/ROW]
[ROW][C]48[/C][C]0.0515798[/C][C]0.10316[/C][C]0.94842[/C][/ROW]
[ROW][C]49[/C][C]0.0486149[/C][C]0.0972298[/C][C]0.951385[/C][/ROW]
[ROW][C]50[/C][C]0.0422379[/C][C]0.0844757[/C][C]0.957762[/C][/ROW]
[ROW][C]51[/C][C]0.0463231[/C][C]0.0926463[/C][C]0.953677[/C][/ROW]
[ROW][C]52[/C][C]0.0664056[/C][C]0.132811[/C][C]0.933594[/C][/ROW]
[ROW][C]53[/C][C]0.0538047[/C][C]0.107609[/C][C]0.946195[/C][/ROW]
[ROW][C]54[/C][C]0.0440153[/C][C]0.0880305[/C][C]0.955985[/C][/ROW]
[ROW][C]55[/C][C]0.136694[/C][C]0.273388[/C][C]0.863306[/C][/ROW]
[ROW][C]56[/C][C]0.125799[/C][C]0.251597[/C][C]0.874201[/C][/ROW]
[ROW][C]57[/C][C]0.10389[/C][C]0.20778[/C][C]0.89611[/C][/ROW]
[ROW][C]58[/C][C]0.199558[/C][C]0.399116[/C][C]0.800442[/C][/ROW]
[ROW][C]59[/C][C]0.194708[/C][C]0.389416[/C][C]0.805292[/C][/ROW]
[ROW][C]60[/C][C]0.192611[/C][C]0.385222[/C][C]0.807389[/C][/ROW]
[ROW][C]61[/C][C]0.200838[/C][C]0.401676[/C][C]0.799162[/C][/ROW]
[ROW][C]62[/C][C]0.223857[/C][C]0.447714[/C][C]0.776143[/C][/ROW]
[ROW][C]63[/C][C]0.225201[/C][C]0.450402[/C][C]0.774799[/C][/ROW]
[ROW][C]64[/C][C]0.387068[/C][C]0.774136[/C][C]0.612932[/C][/ROW]
[ROW][C]65[/C][C]0.416911[/C][C]0.833822[/C][C]0.583089[/C][/ROW]
[ROW][C]66[/C][C]0.618733[/C][C]0.762534[/C][C]0.381267[/C][/ROW]
[ROW][C]67[/C][C]0.711307[/C][C]0.577386[/C][C]0.288693[/C][/ROW]
[ROW][C]68[/C][C]0.695942[/C][C]0.608115[/C][C]0.304058[/C][/ROW]
[ROW][C]69[/C][C]0.750364[/C][C]0.499272[/C][C]0.249636[/C][/ROW]
[ROW][C]70[/C][C]0.767742[/C][C]0.464516[/C][C]0.232258[/C][/ROW]
[ROW][C]71[/C][C]0.803525[/C][C]0.392951[/C][C]0.196475[/C][/ROW]
[ROW][C]72[/C][C]0.819912[/C][C]0.360175[/C][C]0.180088[/C][/ROW]
[ROW][C]73[/C][C]0.852478[/C][C]0.295045[/C][C]0.147522[/C][/ROW]
[ROW][C]74[/C][C]0.858709[/C][C]0.282582[/C][C]0.141291[/C][/ROW]
[ROW][C]75[/C][C]0.907995[/C][C]0.18401[/C][C]0.092005[/C][/ROW]
[ROW][C]76[/C][C]0.927825[/C][C]0.144351[/C][C]0.0721754[/C][/ROW]
[ROW][C]77[/C][C]0.915593[/C][C]0.168813[/C][C]0.0844066[/C][/ROW]
[ROW][C]78[/C][C]0.915689[/C][C]0.168623[/C][C]0.0843113[/C][/ROW]
[ROW][C]79[/C][C]0.944444[/C][C]0.111113[/C][C]0.0555565[/C][/ROW]
[ROW][C]80[/C][C]0.950874[/C][C]0.0982517[/C][C]0.0491258[/C][/ROW]
[ROW][C]81[/C][C]0.948294[/C][C]0.103412[/C][C]0.051706[/C][/ROW]
[ROW][C]82[/C][C]0.953842[/C][C]0.0923165[/C][C]0.0461583[/C][/ROW]
[ROW][C]83[/C][C]0.950722[/C][C]0.0985559[/C][C]0.0492779[/C][/ROW]
[ROW][C]84[/C][C]0.945133[/C][C]0.109734[/C][C]0.0548671[/C][/ROW]
[ROW][C]85[/C][C]0.936118[/C][C]0.127763[/C][C]0.0638817[/C][/ROW]
[ROW][C]86[/C][C]0.924413[/C][C]0.151174[/C][C]0.0755869[/C][/ROW]
[ROW][C]87[/C][C]0.913635[/C][C]0.172731[/C][C]0.0863654[/C][/ROW]
[ROW][C]88[/C][C]0.942309[/C][C]0.115382[/C][C]0.0576912[/C][/ROW]
[ROW][C]89[/C][C]0.942845[/C][C]0.11431[/C][C]0.0571549[/C][/ROW]
[ROW][C]90[/C][C]0.939953[/C][C]0.120093[/C][C]0.0600467[/C][/ROW]
[ROW][C]91[/C][C]0.92912[/C][C]0.141761[/C][C]0.0708803[/C][/ROW]
[ROW][C]92[/C][C]0.91788[/C][C]0.164241[/C][C]0.0821205[/C][/ROW]
[ROW][C]93[/C][C]0.957577[/C][C]0.0848464[/C][C]0.0424232[/C][/ROW]
[ROW][C]94[/C][C]0.956484[/C][C]0.087032[/C][C]0.043516[/C][/ROW]
[ROW][C]95[/C][C]0.956468[/C][C]0.0870634[/C][C]0.0435317[/C][/ROW]
[ROW][C]96[/C][C]0.953395[/C][C]0.0932109[/C][C]0.0466054[/C][/ROW]
[ROW][C]97[/C][C]0.948744[/C][C]0.102513[/C][C]0.0512565[/C][/ROW]
[ROW][C]98[/C][C]0.955913[/C][C]0.0881741[/C][C]0.044087[/C][/ROW]
[ROW][C]99[/C][C]0.948288[/C][C]0.103423[/C][C]0.0517116[/C][/ROW]
[ROW][C]100[/C][C]0.94359[/C][C]0.112821[/C][C]0.0564103[/C][/ROW]
[ROW][C]101[/C][C]0.935005[/C][C]0.12999[/C][C]0.064995[/C][/ROW]
[ROW][C]102[/C][C]0.928062[/C][C]0.143876[/C][C]0.0719379[/C][/ROW]
[ROW][C]103[/C][C]0.923841[/C][C]0.152317[/C][C]0.0761587[/C][/ROW]
[ROW][C]104[/C][C]0.970117[/C][C]0.0597665[/C][C]0.0298832[/C][/ROW]
[ROW][C]105[/C][C]0.969252[/C][C]0.0614966[/C][C]0.0307483[/C][/ROW]
[ROW][C]106[/C][C]0.970154[/C][C]0.0596918[/C][C]0.0298459[/C][/ROW]
[ROW][C]107[/C][C]0.963724[/C][C]0.0725522[/C][C]0.0362761[/C][/ROW]
[ROW][C]108[/C][C]0.964636[/C][C]0.0707282[/C][C]0.0353641[/C][/ROW]
[ROW][C]109[/C][C]0.958365[/C][C]0.0832691[/C][C]0.0416346[/C][/ROW]
[ROW][C]110[/C][C]0.960233[/C][C]0.0795338[/C][C]0.0397669[/C][/ROW]
[ROW][C]111[/C][C]0.953584[/C][C]0.0928329[/C][C]0.0464165[/C][/ROW]
[ROW][C]112[/C][C]0.949822[/C][C]0.100356[/C][C]0.0501778[/C][/ROW]
[ROW][C]113[/C][C]0.940863[/C][C]0.118274[/C][C]0.0591368[/C][/ROW]
[ROW][C]114[/C][C]0.967622[/C][C]0.0647559[/C][C]0.032378[/C][/ROW]
[ROW][C]115[/C][C]0.962095[/C][C]0.075809[/C][C]0.0379045[/C][/ROW]
[ROW][C]116[/C][C]0.96423[/C][C]0.0715391[/C][C]0.0357696[/C][/ROW]
[ROW][C]117[/C][C]0.9922[/C][C]0.0155993[/C][C]0.00779966[/C][/ROW]
[ROW][C]118[/C][C]0.994549[/C][C]0.0109026[/C][C]0.0054513[/C][/ROW]
[ROW][C]119[/C][C]0.992907[/C][C]0.0141867[/C][C]0.00709334[/C][/ROW]
[ROW][C]120[/C][C]0.992991[/C][C]0.0140184[/C][C]0.00700921[/C][/ROW]
[ROW][C]121[/C][C]0.995305[/C][C]0.00938975[/C][C]0.00469488[/C][/ROW]
[ROW][C]122[/C][C]0.993898[/C][C]0.0122044[/C][C]0.00610221[/C][/ROW]
[ROW][C]123[/C][C]0.994165[/C][C]0.0116691[/C][C]0.00583454[/C][/ROW]
[ROW][C]124[/C][C]0.99289[/C][C]0.01422[/C][C]0.00711[/C][/ROW]
[ROW][C]125[/C][C]0.995366[/C][C]0.00926851[/C][C]0.00463425[/C][/ROW]
[ROW][C]126[/C][C]0.994853[/C][C]0.0102946[/C][C]0.00514732[/C][/ROW]
[ROW][C]127[/C][C]0.993494[/C][C]0.0130114[/C][C]0.00650572[/C][/ROW]
[ROW][C]128[/C][C]0.991883[/C][C]0.0162333[/C][C]0.00811666[/C][/ROW]
[ROW][C]129[/C][C]0.993548[/C][C]0.0129047[/C][C]0.00645233[/C][/ROW]
[ROW][C]130[/C][C]0.99263[/C][C]0.0147405[/C][C]0.00737027[/C][/ROW]
[ROW][C]131[/C][C]0.992594[/C][C]0.0148113[/C][C]0.00740565[/C][/ROW]
[ROW][C]132[/C][C]0.991803[/C][C]0.0163938[/C][C]0.00819688[/C][/ROW]
[ROW][C]133[/C][C]0.994397[/C][C]0.0112064[/C][C]0.00560319[/C][/ROW]
[ROW][C]134[/C][C]0.99379[/C][C]0.0124192[/C][C]0.00620959[/C][/ROW]
[ROW][C]135[/C][C]0.99215[/C][C]0.0157001[/C][C]0.00785006[/C][/ROW]
[ROW][C]136[/C][C]0.990952[/C][C]0.0180951[/C][C]0.00904757[/C][/ROW]
[ROW][C]137[/C][C]0.988809[/C][C]0.0223823[/C][C]0.0111911[/C][/ROW]
[ROW][C]138[/C][C]0.988037[/C][C]0.023926[/C][C]0.011963[/C][/ROW]
[ROW][C]139[/C][C]0.986066[/C][C]0.0278674[/C][C]0.0139337[/C][/ROW]
[ROW][C]140[/C][C]0.992366[/C][C]0.0152676[/C][C]0.0076338[/C][/ROW]
[ROW][C]141[/C][C]0.990565[/C][C]0.0188694[/C][C]0.00943468[/C][/ROW]
[ROW][C]142[/C][C]0.9884[/C][C]0.0232006[/C][C]0.0116003[/C][/ROW]
[ROW][C]143[/C][C]0.98515[/C][C]0.0297002[/C][C]0.0148501[/C][/ROW]
[ROW][C]144[/C][C]0.981906[/C][C]0.0361882[/C][C]0.0180941[/C][/ROW]
[ROW][C]145[/C][C]0.979554[/C][C]0.0408925[/C][C]0.0204462[/C][/ROW]
[ROW][C]146[/C][C]0.976947[/C][C]0.0461055[/C][C]0.0230528[/C][/ROW]
[ROW][C]147[/C][C]0.985543[/C][C]0.0289133[/C][C]0.0144567[/C][/ROW]
[ROW][C]148[/C][C]0.982518[/C][C]0.0349648[/C][C]0.0174824[/C][/ROW]
[ROW][C]149[/C][C]0.979655[/C][C]0.0406893[/C][C]0.0203447[/C][/ROW]
[ROW][C]150[/C][C]0.979607[/C][C]0.0407854[/C][C]0.0203927[/C][/ROW]
[ROW][C]151[/C][C]0.974188[/C][C]0.0516242[/C][C]0.0258121[/C][/ROW]
[ROW][C]152[/C][C]0.977294[/C][C]0.0454126[/C][C]0.0227063[/C][/ROW]
[ROW][C]153[/C][C]0.976764[/C][C]0.0464722[/C][C]0.0232361[/C][/ROW]
[ROW][C]154[/C][C]0.973254[/C][C]0.053493[/C][C]0.0267465[/C][/ROW]
[ROW][C]155[/C][C]0.970935[/C][C]0.0581301[/C][C]0.029065[/C][/ROW]
[ROW][C]156[/C][C]0.967295[/C][C]0.0654091[/C][C]0.0327046[/C][/ROW]
[ROW][C]157[/C][C]0.959842[/C][C]0.0803165[/C][C]0.0401582[/C][/ROW]
[ROW][C]158[/C][C]0.950913[/C][C]0.0981747[/C][C]0.0490873[/C][/ROW]
[ROW][C]159[/C][C]0.960344[/C][C]0.0793129[/C][C]0.0396564[/C][/ROW]
[ROW][C]160[/C][C]0.958539[/C][C]0.082921[/C][C]0.0414605[/C][/ROW]
[ROW][C]161[/C][C]0.955578[/C][C]0.0888446[/C][C]0.0444223[/C][/ROW]
[ROW][C]162[/C][C]0.945456[/C][C]0.109089[/C][C]0.0545444[/C][/ROW]
[ROW][C]163[/C][C]0.941714[/C][C]0.116573[/C][C]0.0582864[/C][/ROW]
[ROW][C]164[/C][C]0.936378[/C][C]0.127244[/C][C]0.063622[/C][/ROW]
[ROW][C]165[/C][C]0.924057[/C][C]0.151885[/C][C]0.0759426[/C][/ROW]
[ROW][C]166[/C][C]0.911502[/C][C]0.176995[/C][C]0.0884976[/C][/ROW]
[ROW][C]167[/C][C]0.928374[/C][C]0.143251[/C][C]0.0716257[/C][/ROW]
[ROW][C]168[/C][C]0.918088[/C][C]0.163823[/C][C]0.0819117[/C][/ROW]
[ROW][C]169[/C][C]0.913267[/C][C]0.173466[/C][C]0.0867328[/C][/ROW]
[ROW][C]170[/C][C]0.899742[/C][C]0.200515[/C][C]0.100258[/C][/ROW]
[ROW][C]171[/C][C]0.895483[/C][C]0.209034[/C][C]0.104517[/C][/ROW]
[ROW][C]172[/C][C]0.879331[/C][C]0.241337[/C][C]0.120669[/C][/ROW]
[ROW][C]173[/C][C]0.866838[/C][C]0.266325[/C][C]0.133162[/C][/ROW]
[ROW][C]174[/C][C]0.841369[/C][C]0.317263[/C][C]0.158631[/C][/ROW]
[ROW][C]175[/C][C]0.812555[/C][C]0.374891[/C][C]0.187445[/C][/ROW]
[ROW][C]176[/C][C]0.791724[/C][C]0.416551[/C][C]0.208276[/C][/ROW]
[ROW][C]177[/C][C]0.820828[/C][C]0.358345[/C][C]0.179172[/C][/ROW]
[ROW][C]178[/C][C]0.789644[/C][C]0.420712[/C][C]0.210356[/C][/ROW]
[ROW][C]179[/C][C]0.792811[/C][C]0.414379[/C][C]0.207189[/C][/ROW]
[ROW][C]180[/C][C]0.776869[/C][C]0.446263[/C][C]0.223131[/C][/ROW]
[ROW][C]181[/C][C]0.839313[/C][C]0.321374[/C][C]0.160687[/C][/ROW]
[ROW][C]182[/C][C]0.860003[/C][C]0.279994[/C][C]0.139997[/C][/ROW]
[ROW][C]183[/C][C]0.870052[/C][C]0.259897[/C][C]0.129948[/C][/ROW]
[ROW][C]184[/C][C]0.856462[/C][C]0.287076[/C][C]0.143538[/C][/ROW]
[ROW][C]185[/C][C]0.873057[/C][C]0.253885[/C][C]0.126943[/C][/ROW]
[ROW][C]186[/C][C]0.900189[/C][C]0.199623[/C][C]0.0998114[/C][/ROW]
[ROW][C]187[/C][C]0.880713[/C][C]0.238575[/C][C]0.119287[/C][/ROW]
[ROW][C]188[/C][C]0.859712[/C][C]0.280575[/C][C]0.140288[/C][/ROW]
[ROW][C]189[/C][C]0.851794[/C][C]0.296412[/C][C]0.148206[/C][/ROW]
[ROW][C]190[/C][C]0.847265[/C][C]0.30547[/C][C]0.152735[/C][/ROW]
[ROW][C]191[/C][C]0.944359[/C][C]0.111281[/C][C]0.0556406[/C][/ROW]
[ROW][C]192[/C][C]0.938971[/C][C]0.122059[/C][C]0.0610293[/C][/ROW]
[ROW][C]193[/C][C]0.94085[/C][C]0.1183[/C][C]0.0591501[/C][/ROW]
[ROW][C]194[/C][C]0.925955[/C][C]0.148091[/C][C]0.0740454[/C][/ROW]
[ROW][C]195[/C][C]0.905087[/C][C]0.189827[/C][C]0.0949134[/C][/ROW]
[ROW][C]196[/C][C]0.89043[/C][C]0.219139[/C][C]0.10957[/C][/ROW]
[ROW][C]197[/C][C]0.868966[/C][C]0.262068[/C][C]0.131034[/C][/ROW]
[ROW][C]198[/C][C]0.857313[/C][C]0.285374[/C][C]0.142687[/C][/ROW]
[ROW][C]199[/C][C]0.846056[/C][C]0.307888[/C][C]0.153944[/C][/ROW]
[ROW][C]200[/C][C]0.913443[/C][C]0.173114[/C][C]0.0865568[/C][/ROW]
[ROW][C]201[/C][C]0.888117[/C][C]0.223765[/C][C]0.111883[/C][/ROW]
[ROW][C]202[/C][C]0.86143[/C][C]0.27714[/C][C]0.13857[/C][/ROW]
[ROW][C]203[/C][C]0.831786[/C][C]0.336429[/C][C]0.168214[/C][/ROW]
[ROW][C]204[/C][C]0.796985[/C][C]0.406029[/C][C]0.203015[/C][/ROW]
[ROW][C]205[/C][C]0.752322[/C][C]0.495356[/C][C]0.247678[/C][/ROW]
[ROW][C]206[/C][C]0.699151[/C][C]0.601697[/C][C]0.300849[/C][/ROW]
[ROW][C]207[/C][C]0.654633[/C][C]0.690735[/C][C]0.345367[/C][/ROW]
[ROW][C]208[/C][C]0.654669[/C][C]0.690663[/C][C]0.345331[/C][/ROW]
[ROW][C]209[/C][C]0.591508[/C][C]0.816984[/C][C]0.408492[/C][/ROW]
[ROW][C]210[/C][C]0.528835[/C][C]0.94233[/C][C]0.471165[/C][/ROW]
[ROW][C]211[/C][C]0.584528[/C][C]0.830944[/C][C]0.415472[/C][/ROW]
[ROW][C]212[/C][C]0.519814[/C][C]0.960371[/C][C]0.480186[/C][/ROW]
[ROW][C]213[/C][C]0.521874[/C][C]0.956251[/C][C]0.478126[/C][/ROW]
[ROW][C]214[/C][C]0.91644[/C][C]0.16712[/C][C]0.0835602[/C][/ROW]
[ROW][C]215[/C][C]0.879805[/C][C]0.240391[/C][C]0.120195[/C][/ROW]
[ROW][C]216[/C][C]0.995265[/C][C]0.00946977[/C][C]0.00473489[/C][/ROW]
[ROW][C]217[/C][C]0.997699[/C][C]0.00460293[/C][C]0.00230147[/C][/ROW]
[ROW][C]218[/C][C]0.997925[/C][C]0.00415019[/C][C]0.00207509[/C][/ROW]
[ROW][C]219[/C][C]0.999825[/C][C]0.000350207[/C][C]0.000175103[/C][/ROW]
[ROW][C]220[/C][C]0.999473[/C][C]0.0010533[/C][C]0.000526648[/C][/ROW]
[ROW][C]221[/C][C]0.999019[/C][C]0.00196105[/C][C]0.000980526[/C][/ROW]
[ROW][C]222[/C][C]0.998004[/C][C]0.00399186[/C][C]0.00199593[/C][/ROW]
[ROW][C]223[/C][C]0.998027[/C][C]0.0039456[/C][C]0.0019728[/C][/ROW]
[ROW][C]224[/C][C]0.994346[/C][C]0.0113082[/C][C]0.00565411[/C][/ROW]
[ROW][C]225[/C][C]0.990544[/C][C]0.0189119[/C][C]0.00945594[/C][/ROW]
[ROW][C]226[/C][C]0.963324[/C][C]0.0733517[/C][C]0.0366758[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265155&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265155&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.8792030.2415950.120797
90.8905950.218810.109405
100.8188130.3623750.181187
110.8756190.2487610.124381
120.8143870.3712250.185613
130.7449180.5101640.255082
140.7738780.4522440.226122
150.7155980.5688040.284402
160.6424790.7150430.357521
170.5626170.8747660.437383
180.5503280.8993450.449672
190.4936270.9872550.506373
200.4232690.8465380.576731
210.3796690.7593380.620331
220.3344740.6689480.665526
230.2900290.5800580.709971
240.2640550.528110.735945
250.2221730.4443470.777827
260.2187460.4374920.781254
270.1840480.3680950.815952
280.1536490.3072970.846351
290.1237930.2475850.876207
300.1294590.2589190.870541
310.1155050.2310110.884495
320.09344010.186880.90656
330.07651290.1530260.923487
340.08626910.1725380.913731
350.07222740.1444550.927773
360.06032650.1206530.939674
370.05417070.1083410.945829
380.0523290.1046580.947671
390.05311090.1062220.946889
400.04354260.08708520.956457
410.05978240.1195650.940218
420.06520790.1304160.934792
430.05147870.1029570.948521
440.05984780.1196960.940152
450.06670020.13340.9333
460.06082320.1216460.939177
470.05404630.1080930.945954
480.05157980.103160.94842
490.04861490.09722980.951385
500.04223790.08447570.957762
510.04632310.09264630.953677
520.06640560.1328110.933594
530.05380470.1076090.946195
540.04401530.08803050.955985
550.1366940.2733880.863306
560.1257990.2515970.874201
570.103890.207780.89611
580.1995580.3991160.800442
590.1947080.3894160.805292
600.1926110.3852220.807389
610.2008380.4016760.799162
620.2238570.4477140.776143
630.2252010.4504020.774799
640.3870680.7741360.612932
650.4169110.8338220.583089
660.6187330.7625340.381267
670.7113070.5773860.288693
680.6959420.6081150.304058
690.7503640.4992720.249636
700.7677420.4645160.232258
710.8035250.3929510.196475
720.8199120.3601750.180088
730.8524780.2950450.147522
740.8587090.2825820.141291
750.9079950.184010.092005
760.9278250.1443510.0721754
770.9155930.1688130.0844066
780.9156890.1686230.0843113
790.9444440.1111130.0555565
800.9508740.09825170.0491258
810.9482940.1034120.051706
820.9538420.09231650.0461583
830.9507220.09855590.0492779
840.9451330.1097340.0548671
850.9361180.1277630.0638817
860.9244130.1511740.0755869
870.9136350.1727310.0863654
880.9423090.1153820.0576912
890.9428450.114310.0571549
900.9399530.1200930.0600467
910.929120.1417610.0708803
920.917880.1642410.0821205
930.9575770.08484640.0424232
940.9564840.0870320.043516
950.9564680.08706340.0435317
960.9533950.09321090.0466054
970.9487440.1025130.0512565
980.9559130.08817410.044087
990.9482880.1034230.0517116
1000.943590.1128210.0564103
1010.9350050.129990.064995
1020.9280620.1438760.0719379
1030.9238410.1523170.0761587
1040.9701170.05976650.0298832
1050.9692520.06149660.0307483
1060.9701540.05969180.0298459
1070.9637240.07255220.0362761
1080.9646360.07072820.0353641
1090.9583650.08326910.0416346
1100.9602330.07953380.0397669
1110.9535840.09283290.0464165
1120.9498220.1003560.0501778
1130.9408630.1182740.0591368
1140.9676220.06475590.032378
1150.9620950.0758090.0379045
1160.964230.07153910.0357696
1170.99220.01559930.00779966
1180.9945490.01090260.0054513
1190.9929070.01418670.00709334
1200.9929910.01401840.00700921
1210.9953050.009389750.00469488
1220.9938980.01220440.00610221
1230.9941650.01166910.00583454
1240.992890.014220.00711
1250.9953660.009268510.00463425
1260.9948530.01029460.00514732
1270.9934940.01301140.00650572
1280.9918830.01623330.00811666
1290.9935480.01290470.00645233
1300.992630.01474050.00737027
1310.9925940.01481130.00740565
1320.9918030.01639380.00819688
1330.9943970.01120640.00560319
1340.993790.01241920.00620959
1350.992150.01570010.00785006
1360.9909520.01809510.00904757
1370.9888090.02238230.0111911
1380.9880370.0239260.011963
1390.9860660.02786740.0139337
1400.9923660.01526760.0076338
1410.9905650.01886940.00943468
1420.98840.02320060.0116003
1430.985150.02970020.0148501
1440.9819060.03618820.0180941
1450.9795540.04089250.0204462
1460.9769470.04610550.0230528
1470.9855430.02891330.0144567
1480.9825180.03496480.0174824
1490.9796550.04068930.0203447
1500.9796070.04078540.0203927
1510.9741880.05162420.0258121
1520.9772940.04541260.0227063
1530.9767640.04647220.0232361
1540.9732540.0534930.0267465
1550.9709350.05813010.029065
1560.9672950.06540910.0327046
1570.9598420.08031650.0401582
1580.9509130.09817470.0490873
1590.9603440.07931290.0396564
1600.9585390.0829210.0414605
1610.9555780.08884460.0444223
1620.9454560.1090890.0545444
1630.9417140.1165730.0582864
1640.9363780.1272440.063622
1650.9240570.1518850.0759426
1660.9115020.1769950.0884976
1670.9283740.1432510.0716257
1680.9180880.1638230.0819117
1690.9132670.1734660.0867328
1700.8997420.2005150.100258
1710.8954830.2090340.104517
1720.8793310.2413370.120669
1730.8668380.2663250.133162
1740.8413690.3172630.158631
1750.8125550.3748910.187445
1760.7917240.4165510.208276
1770.8208280.3583450.179172
1780.7896440.4207120.210356
1790.7928110.4143790.207189
1800.7768690.4462630.223131
1810.8393130.3213740.160687
1820.8600030.2799940.139997
1830.8700520.2598970.129948
1840.8564620.2870760.143538
1850.8730570.2538850.126943
1860.9001890.1996230.0998114
1870.8807130.2385750.119287
1880.8597120.2805750.140288
1890.8517940.2964120.148206
1900.8472650.305470.152735
1910.9443590.1112810.0556406
1920.9389710.1220590.0610293
1930.940850.11830.0591501
1940.9259550.1480910.0740454
1950.9050870.1898270.0949134
1960.890430.2191390.10957
1970.8689660.2620680.131034
1980.8573130.2853740.142687
1990.8460560.3078880.153944
2000.9134430.1731140.0865568
2010.8881170.2237650.111883
2020.861430.277140.13857
2030.8317860.3364290.168214
2040.7969850.4060290.203015
2050.7523220.4953560.247678
2060.6991510.6016970.300849
2070.6546330.6907350.345367
2080.6546690.6906630.345331
2090.5915080.8169840.408492
2100.5288350.942330.471165
2110.5845280.8309440.415472
2120.5198140.9603710.480186
2130.5218740.9562510.478126
2140.916440.167120.0835602
2150.8798050.2403910.120195
2160.9952650.009469770.00473489
2170.9976990.004602930.00230147
2180.9979250.004150190.00207509
2190.9998250.0003502070.000175103
2200.9994730.00105330.000526648
2210.9990190.001961050.000980526
2220.9980040.003991860.00199593
2230.9980270.00394560.0019728
2240.9943460.01130820.00565411
2250.9905440.01891190.00945594
2260.9633240.07335170.0366758






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0456621NOK
5% type I error level460.210046NOK
10% type I error level800.365297NOK

\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 & 10 & 0.0456621 & NOK \tabularnewline
5% type I error level & 46 & 0.210046 & NOK \tabularnewline
10% type I error level & 80 & 0.365297 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265155&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]10[/C][C]0.0456621[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]46[/C][C]0.210046[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]80[/C][C]0.365297[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265155&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265155&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0456621NOK
5% type I error level460.210046NOK
10% type I error level800.365297NOK


Figures (Output of Computation)

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Input Parameters & R Code

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