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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 13:52:55 +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/t1418219618pmfxosm4kc0f1s3.htm/, Retrieved Fri, 17 May 2024 11:00:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265188, Retrieved Fri, 17 May 2024 11:00:04 +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 13:52:55] [cb9023b84cdbf59fe6647357de544f7b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 18 96 149
12.8 39 88 148
7.4 46 114 158
6.7 31 69 128
12.6 67 176 224
14.8 35 114 159
13.3 52 121 105
11.1 77 110 159
8.2 37 158 167
11.4 32 116 165
6.4 36 181 159
12 69 141 176
6.3 21 35 54
11.3 26 80 91
11.9 54 152 163
9.3 36 97 124
10 23 84 121
13.8 112 101 148
10.8 35 107 221
11.7 47 112 149
10.9 37 171 244
16.1 109 137 148
9.9 20 66 150
11.5 22 93 153
8.3 23 105 94
11.7 32 131 156
9 30 102 132
10.8 43 120 105
10.4 16 77 151
12.7 49 108 131
11.8 43 168 157
13 46 75 162
10.8 19 107 163
12.3 23 62 59
11.3 59 121 187
11.6 32 97 116
10.9 19 126 148
12.1 22 104 155
13.3 48 148 125
10.1 23 146 116
14.3 33 97 138
9.3 34 118 164
12.5 48 58 162
7.6 18 63 99
9.2 33 50 186
14.5 67 94 188
12.3 80 127 177
12.6 32 128 139
13 43 146 162
12.6 38 69 108
13.2 29 186 159
7.7 32 85 110
10.5 35 54 96
10.9 29 106 87
4.3 12 34 97
10.3 37 60 127
11.4 51 62 74
5.6 14 64 114
8.8 20 98 95
9 11 35 121
9.6 35 55 130
6.4 8 54 52
11.6 24 51 118
4.35 23 41 48
12.7 16 146 50
18.1 33 182 150
17.85 32 192 154
16.6 37 263 109
12.6 14 35 68
17.1 52 439 194
19.1 75 214 158
16.1 72 341 159
13.35 15 58 67
18.4 29 292 147
14.7 13 85 39
10.6 40 200 100
12.6 19 158 111
16.2 24 199 138
13.6 121 297 101
18.9 93 227 131
14.1 36 108 101
14.5 23 86 114
16.15 85 302 165
14.75 41 148 114
14.8 46 178 111
12.45 18 120 75
12.65 35 207 82
17.35 17 157 121
8.6 4 128 32
18.4 28 296 150
16.1 44 323 117
11.6 10 79 71
17.75 38 70 165
15.25 57 146 154
17.65 23 246 126
15.6 26 145 138
16.35 36 196 149
17.65 22 199 145
13.6 40 127 120
11.7 18 91 138
14.35 31 153 109
14.75 11 299 132
18.25 38 228 172
9.9 24 190 169
16 37 180 114
18.25 37 212 156
16.85 22 269 172
14.6 15 130 68
13.85 2 179 89
18.95 43 243 167
15.6 31 190 113
14.85 29 299 115
11.75 45 121 78
18.45 25 137 118
15.9 4 305 87
17.1 31 157 173
16.1 -4 96 2
19.9 66 183 162
10.95 61 52 49
18.45 32 238 122
15.1 31 40 96
15 39 226 100
11.35 19 190 82
15.95 31 214 100
18.1 36 145 115
14.6 42 119 141
15.4 21 222 165
15.4 21 222 165
17.6 25 159 110
13.35 32 165 118
19.1 26 249 158
15.35 28 125 146
7.6 32 122 49
13.4 41 186 90
13.9 29 148 121
19.1 33 274 155
15.25 17 172 104
12.9 13 84 147
16.1 32 168 110
17.35 30 102 108
13.15 34 106 113
12.15 59 2 115
12.6 13 139 61
10.35 23 95 60
15.4 10 130 109
9.6 5 72 68
18.2 31 141 111
13.6 19 113 77
14.85 32 206 73
14.75 30 268 151
14.1 25 175 89
14.9 48 77 78
16.25 35 125 110
19.25 67 255 220
13.6 15 111 65
13.6 22 132 141
15.65 18 211 117
12.75 33 92 122
14.6 46 76 63
9.85 24 171 44
12.65 14 83 52
11.9 23 119 62
19.2 12 266 131
16.6 38 186 101
11.2 12 50 42
15.25 28 117 152
11.9 41 219 107
13.2 12 246 77
16.35 31 279 154
12.4 33 148 103
15.85 34 137 96
14.35 41 130 154
18.15 21 181 175
11.15 20 98 57
15.65 44 226 112
17.75 52 234 143
7.65 7 138 49
12.35 29 85 110
15.6 11 66 131
19.3 26 236 167
15.2 24 106 56
17.1 7 135 137
15.6 60 122 86
18.4 13 218 121
19.05 20 199 149
18.55 52 112 168
19.1 28 278 140
13.1 25 94 88
12.85 39 113 168
9.5 9 84 94
4.5 19 86 51
11.85 13 62 48
13.6 60 222 145
11.7 19 167 66
12.4 34 82 85
13.35 14 207 109
11.4 17 184 63
14.9 45 83 102
19.9 66 183 162
17.75 24 85 128
11.2 48 89 86
14.6 29 225 114
17.6 -2 237 164
14.05 51 102 119
16.1 2 221 126
13.35 24 128 132
11.85 40 91 142
11.95 20 198 83
14.75 19 204 94
15.15 16 158 81
13.2 20 138 166
16.85 40 226 110
7.85 27 44 64
7.7 25 196 93
12.6 49 83 104
7.85 39 79 105
10.95 61 52 49
12.35 19 105 88
9.95 67 116 95
14.9 45 83 102
16.65 30 196 99
13.4 8 153 63
13.95 19 157 76
15.7 52 75 109
16.85 22 106 117
10.95 17 58 57
15.35 33 75 120
12.2 34 74 73
15.1 22 185 91
17.75 30 265 108
15.2 25 131 105
14.6 38 139 117
16.65 26 196 119
8.1 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 time14 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 14 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265188&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]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265188&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265188&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 time14 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.48454 + 0.00765414PRH[t] + 0.0242834Blogged[t] + 0.0108515LFM[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.48454 +  0.00765414PRH[t] +  0.0242834Blogged[t] +  0.0108515LFM[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265188&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.48454 +  0.00765414PRH[t] +  0.0242834Blogged[t] +  0.0108515LFM[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265188&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265188&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] = + 8.48454 + 0.00765414PRH[t] + 0.0242834Blogged[t] + 0.0108515LFM[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.484540.59797214.193.02189e-331.51095e-33
PRH0.007654140.01010770.75730.449670.224835
Blogged0.02428340.002646389.1762.63924e-171.31962e-17
LFM0.01085150.004937752.1980.02897090.0144855

\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) & 8.48454 & 0.597972 & 14.19 & 3.02189e-33 & 1.51095e-33 \tabularnewline
PRH & 0.00765414 & 0.0101077 & 0.7573 & 0.44967 & 0.224835 \tabularnewline
Blogged & 0.0242834 & 0.00264638 & 9.176 & 2.63924e-17 & 1.31962e-17 \tabularnewline
LFM & 0.0108515 & 0.00493775 & 2.198 & 0.0289709 & 0.0144855 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265188&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]8.48454[/C][C]0.597972[/C][C]14.19[/C][C]3.02189e-33[/C][C]1.51095e-33[/C][/ROW]
[ROW][C]PRH[/C][C]0.00765414[/C][C]0.0101077[/C][C]0.7573[/C][C]0.44967[/C][C]0.224835[/C][/ROW]
[ROW][C]Blogged[/C][C]0.0242834[/C][C]0.00264638[/C][C]9.176[/C][C]2.63924e-17[/C][C]1.31962e-17[/C][/ROW]
[ROW][C]LFM[/C][C]0.0108515[/C][C]0.00493775[/C][C]2.198[/C][C]0.0289709[/C][C]0.0144855[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265188&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265188&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)8.484540.59797214.193.02189e-331.51095e-33
PRH0.007654140.01010770.75730.449670.224835
Blogged0.02428340.002646389.1762.63924e-171.31962e-17
LFM0.01085150.004937752.1980.02897090.0144855






Multiple Linear Regression - Regression Statistics
Multiple R0.583174
R-squared0.340091
Adjusted R-squared0.331484
F-TEST (value)39.511
F-TEST (DF numerator)3
F-TEST (DF denominator)230
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.70495
Sum Squared Residuals1682.85

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.583174 \tabularnewline
R-squared & 0.340091 \tabularnewline
Adjusted R-squared & 0.331484 \tabularnewline
F-TEST (value) & 39.511 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 230 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.70495 \tabularnewline
Sum Squared Residuals & 1682.85 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265188&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.583174[/C][/ROW]
[ROW][C]R-squared[/C][C]0.340091[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.331484[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]39.511[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]230[/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]2.70495[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1682.85[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265188&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265188&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 R0.583174
R-squared0.340091
Adjusted R-squared0.331484
F-TEST (value)39.511
F-TEST (DF numerator)3
F-TEST (DF denominator)230
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.70495
Sum Squared Residuals1682.85






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.57040.329604
212.812.5260.273986
37.413.3195-5.91948
46.711.7864-5.08637
512.615.702-3.10198
614.813.24611.55387
713.312.96030.339744
811.113.4705-2.37047
98.214.4167-6.21672
1011.413.3368-1.93685
116.414.8808-8.48077
121214.3465-2.3465
136.310.0812-3.78118
1411.311.6137-0.313708
1511.914.3577-2.45774
169.312.4612-3.16117
171012.0134-2.01342
1813.813.40050.399549
1910.813.7489-2.94894
2011.713.1809-1.4809
2110.915.568-4.66797
2216.114.25171.84831
239.911.8681-1.96805
2411.512.5716-1.07157
258.312.2304-3.93038
2611.713.6034-1.90343
27912.6235-3.62347
2810.812.8671-2.06708
2910.412.1154-1.71541
3012.712.9037-0.203748
3111.814.597-2.79697
321312.41580.58417
3310.812.9971-2.19709
3412.310.80641.4936
3511.313.9037-2.60366
3611.612.3437-0.743738
3710.913.2957-2.3957
3812.112.8604-0.760388
3913.313.8023-0.502321
4010.113.4647-3.36474
4114.312.59011.70988
429.313.3899-4.08987
4312.512.01830.48168
447.611.2265-3.62647
459.211.9697-2.76968
4614.513.32011.17991
4712.314.1016-1.80158
4812.613.3461-0.746107
491314.117-1.11699
5012.611.62290.977084
5113.214.9486-1.74861
527.711.9872-4.28723
5310.511.1055-0.605484
5410.912.2246-1.32463
554.310.4546-6.15462
5610.311.6029-1.30289
5711.411.18350.216515
585.611.3829-5.78291
598.812.0483-3.24829
60910.7317-1.73169
619.611.4987-1.89872
626.410.4214-4.02136
6311.611.18720.412829
644.3510.1771-5.82708
6512.712.6950.00504107
6618.114.78443.31557
6717.8515.0632.78698
6816.616.33710.262909
6912.610.17952.42048
7017.121.6482-4.54816
7119.115.96983.13021
7216.119.0417-2.94167
7313.3510.73482.61516
7418.417.39241.00757
7514.711.07133.62866
7610.614.7325-4.13254
7712.613.6713-1.07126
7816.214.99811.20186
7913.617.7189-4.11886
8018.916.13032.76975
8114.112.47871.6213
8214.511.9862.51397
8316.1518.2592-2.10923
8414.7513.62941.12062
8514.814.36360.436407
8612.4512.35020.0998136
8712.6514.6689-2.01892
8817.3513.74023.60981
898.611.9707-3.37068
9018.417.51450.885533
9116.117.9345-1.83449
9211.611.24990.350072
9317.7512.26575.48427
9415.2514.13731.11267
9517.6516.00161.64841
9615.613.70211.89785
9716.3515.13651.21349
9817.6515.05882.5912
9913.613.17690.423121
10011.712.3296-0.629612
10114.3513.620.730007
10214.7517.2619-2.51187
10318.2516.17852.07153
1049.915.116-5.21599
1051614.37581.62417
10618.2515.60872.64134
10716.8517.0516-0.201624
10814.612.49412.1059
10913.8513.81240.0376387
11018.9516.52672.42326
11115.614.56191.03812
11214.8517.2152-2.36517
11311.7512.6137-0.863686
11418.4513.28325.1668
11515.916.8657-0.965674
11617.114.41162.68838
11716.110.80685.29317
11819.915.19154.70848
11910.9510.74590.204095
12018.4515.83282.61719
12115.110.73494.3651
1221515.3563-0.356251
12311.3514.1336-2.78364
12415.9515.00360.946383
12518.113.52914.57089
12614.613.22581.3742
12715.415.8267-0.42669
12815.415.8267-0.42669
12917.613.73063.86938
13013.3514.0167-0.666711
13119.116.44472.65535
13215.3513.31862.0314
1337.612.2238-4.62377
13413.414.2917-0.891708
13513.913.61350.286514
13619.117.07282.02724
13715.2513.921.33004
13812.912.2190.680979
13916.114.00272.09725
14017.3512.3634.98697
14113.1512.5450.604958
14212.1510.23261.91737
14312.612.6214-0.0213792
14410.3511.6186-1.2686
14515.412.90072.49926
1469.611.0091-1.40912
14718.213.35034.8497
14813.612.20961.39044
14914.8514.5240.325987
15014.7516.8607-2.11069
15114.113.89130.208727
15214.911.56823.33182
15316.2512.98153.26847
15419.2517.5771.67304
15513.612.00021.59984
15613.613.38840.211598
15715.6515.01570.634262
15812.7512.29510.454916
15914.611.36583.23418
1609.8513.2982-3.44817
16112.6511.17151.4785
16211.912.2231-0.323104
16319.216.45732.74268
16416.614.38812.21189
16511.210.24630.953675
16615.2513.18942.06056
16711.915.2775-3.37754
16813.215.3857-2.18567
16916.3517.168-0.818018
17012.413.4488-1.04878
17115.8513.11342.73665
17214.3513.62630.723666
17318.1514.93963.21041
17411.1511.6359-0.485933
17515.6515.52470.125261
17617.7516.11661.63336
1777.6512.421-4.77095
17812.3511.96430.385734
17915.611.5934.00701
18019.316.22663.07337
18115.211.853.35003
18217.113.3033.79697
18315.612.83962.76041
18418.415.19093.20914
18519.0515.08693.96311
18618.5513.42535.12465
18719.116.96892.13115
18813.111.91351.18653
18912.8513.3501-0.500129
1909.511.6133-2.11328
1914.511.2718-6.77177
19211.8510.61051.23951
19313.615.9082-2.30817
19411.713.4015-1.7015
19512.411.65840.741601
19613.3514.8012-1.45118
19711.413.7665-2.36645
19814.911.95142.94865
19919.915.19154.70848
20017.7512.12135.62868
20111.211.9464-0.746392
20214.615.4073-0.807347
20317.616.0041.59596
20414.0512.64311.40686
20516.115.23380.866231
20613.3513.20890.141086
20711.8512.5414-0.691409
20811.9514.3464-2.39641
20914.7514.60380.146176
21015.1513.32281.82724
21113.213.7901-0.590082
21216.8515.47241.37758
2137.8510.4542-2.60417
2147.714.4446-6.74463
21512.612.00370.596327
2167.8511.8408-3.99085
21710.9510.74590.204095
21812.3512.13470.215341
2199.9512.8451-2.89514
22014.911.95142.94865
22116.6514.5482.10199
22213.412.94480.455221
22313.9513.26720.682822
22415.711.88663.81337
22516.8512.49664.3534
22610.9510.64160.308365
22715.3511.86063.48944
22812.211.33390.866086
22915.114.13280.967152
23017.7516.32121.42877
23115.212.99642.20357
23214.613.42041.17958
23316.6514.73441.91558
2348.110.8145-2.71455

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.5704 & 0.329604 \tabularnewline
2 & 12.8 & 12.526 & 0.273986 \tabularnewline
3 & 7.4 & 13.3195 & -5.91948 \tabularnewline
4 & 6.7 & 11.7864 & -5.08637 \tabularnewline
5 & 12.6 & 15.702 & -3.10198 \tabularnewline
6 & 14.8 & 13.2461 & 1.55387 \tabularnewline
7 & 13.3 & 12.9603 & 0.339744 \tabularnewline
8 & 11.1 & 13.4705 & -2.37047 \tabularnewline
9 & 8.2 & 14.4167 & -6.21672 \tabularnewline
10 & 11.4 & 13.3368 & -1.93685 \tabularnewline
11 & 6.4 & 14.8808 & -8.48077 \tabularnewline
12 & 12 & 14.3465 & -2.3465 \tabularnewline
13 & 6.3 & 10.0812 & -3.78118 \tabularnewline
14 & 11.3 & 11.6137 & -0.313708 \tabularnewline
15 & 11.9 & 14.3577 & -2.45774 \tabularnewline
16 & 9.3 & 12.4612 & -3.16117 \tabularnewline
17 & 10 & 12.0134 & -2.01342 \tabularnewline
18 & 13.8 & 13.4005 & 0.399549 \tabularnewline
19 & 10.8 & 13.7489 & -2.94894 \tabularnewline
20 & 11.7 & 13.1809 & -1.4809 \tabularnewline
21 & 10.9 & 15.568 & -4.66797 \tabularnewline
22 & 16.1 & 14.2517 & 1.84831 \tabularnewline
23 & 9.9 & 11.8681 & -1.96805 \tabularnewline
24 & 11.5 & 12.5716 & -1.07157 \tabularnewline
25 & 8.3 & 12.2304 & -3.93038 \tabularnewline
26 & 11.7 & 13.6034 & -1.90343 \tabularnewline
27 & 9 & 12.6235 & -3.62347 \tabularnewline
28 & 10.8 & 12.8671 & -2.06708 \tabularnewline
29 & 10.4 & 12.1154 & -1.71541 \tabularnewline
30 & 12.7 & 12.9037 & -0.203748 \tabularnewline
31 & 11.8 & 14.597 & -2.79697 \tabularnewline
32 & 13 & 12.4158 & 0.58417 \tabularnewline
33 & 10.8 & 12.9971 & -2.19709 \tabularnewline
34 & 12.3 & 10.8064 & 1.4936 \tabularnewline
35 & 11.3 & 13.9037 & -2.60366 \tabularnewline
36 & 11.6 & 12.3437 & -0.743738 \tabularnewline
37 & 10.9 & 13.2957 & -2.3957 \tabularnewline
38 & 12.1 & 12.8604 & -0.760388 \tabularnewline
39 & 13.3 & 13.8023 & -0.502321 \tabularnewline
40 & 10.1 & 13.4647 & -3.36474 \tabularnewline
41 & 14.3 & 12.5901 & 1.70988 \tabularnewline
42 & 9.3 & 13.3899 & -4.08987 \tabularnewline
43 & 12.5 & 12.0183 & 0.48168 \tabularnewline
44 & 7.6 & 11.2265 & -3.62647 \tabularnewline
45 & 9.2 & 11.9697 & -2.76968 \tabularnewline
46 & 14.5 & 13.3201 & 1.17991 \tabularnewline
47 & 12.3 & 14.1016 & -1.80158 \tabularnewline
48 & 12.6 & 13.3461 & -0.746107 \tabularnewline
49 & 13 & 14.117 & -1.11699 \tabularnewline
50 & 12.6 & 11.6229 & 0.977084 \tabularnewline
51 & 13.2 & 14.9486 & -1.74861 \tabularnewline
52 & 7.7 & 11.9872 & -4.28723 \tabularnewline
53 & 10.5 & 11.1055 & -0.605484 \tabularnewline
54 & 10.9 & 12.2246 & -1.32463 \tabularnewline
55 & 4.3 & 10.4546 & -6.15462 \tabularnewline
56 & 10.3 & 11.6029 & -1.30289 \tabularnewline
57 & 11.4 & 11.1835 & 0.216515 \tabularnewline
58 & 5.6 & 11.3829 & -5.78291 \tabularnewline
59 & 8.8 & 12.0483 & -3.24829 \tabularnewline
60 & 9 & 10.7317 & -1.73169 \tabularnewline
61 & 9.6 & 11.4987 & -1.89872 \tabularnewline
62 & 6.4 & 10.4214 & -4.02136 \tabularnewline
63 & 11.6 & 11.1872 & 0.412829 \tabularnewline
64 & 4.35 & 10.1771 & -5.82708 \tabularnewline
65 & 12.7 & 12.695 & 0.00504107 \tabularnewline
66 & 18.1 & 14.7844 & 3.31557 \tabularnewline
67 & 17.85 & 15.063 & 2.78698 \tabularnewline
68 & 16.6 & 16.3371 & 0.262909 \tabularnewline
69 & 12.6 & 10.1795 & 2.42048 \tabularnewline
70 & 17.1 & 21.6482 & -4.54816 \tabularnewline
71 & 19.1 & 15.9698 & 3.13021 \tabularnewline
72 & 16.1 & 19.0417 & -2.94167 \tabularnewline
73 & 13.35 & 10.7348 & 2.61516 \tabularnewline
74 & 18.4 & 17.3924 & 1.00757 \tabularnewline
75 & 14.7 & 11.0713 & 3.62866 \tabularnewline
76 & 10.6 & 14.7325 & -4.13254 \tabularnewline
77 & 12.6 & 13.6713 & -1.07126 \tabularnewline
78 & 16.2 & 14.9981 & 1.20186 \tabularnewline
79 & 13.6 & 17.7189 & -4.11886 \tabularnewline
80 & 18.9 & 16.1303 & 2.76975 \tabularnewline
81 & 14.1 & 12.4787 & 1.6213 \tabularnewline
82 & 14.5 & 11.986 & 2.51397 \tabularnewline
83 & 16.15 & 18.2592 & -2.10923 \tabularnewline
84 & 14.75 & 13.6294 & 1.12062 \tabularnewline
85 & 14.8 & 14.3636 & 0.436407 \tabularnewline
86 & 12.45 & 12.3502 & 0.0998136 \tabularnewline
87 & 12.65 & 14.6689 & -2.01892 \tabularnewline
88 & 17.35 & 13.7402 & 3.60981 \tabularnewline
89 & 8.6 & 11.9707 & -3.37068 \tabularnewline
90 & 18.4 & 17.5145 & 0.885533 \tabularnewline
91 & 16.1 & 17.9345 & -1.83449 \tabularnewline
92 & 11.6 & 11.2499 & 0.350072 \tabularnewline
93 & 17.75 & 12.2657 & 5.48427 \tabularnewline
94 & 15.25 & 14.1373 & 1.11267 \tabularnewline
95 & 17.65 & 16.0016 & 1.64841 \tabularnewline
96 & 15.6 & 13.7021 & 1.89785 \tabularnewline
97 & 16.35 & 15.1365 & 1.21349 \tabularnewline
98 & 17.65 & 15.0588 & 2.5912 \tabularnewline
99 & 13.6 & 13.1769 & 0.423121 \tabularnewline
100 & 11.7 & 12.3296 & -0.629612 \tabularnewline
101 & 14.35 & 13.62 & 0.730007 \tabularnewline
102 & 14.75 & 17.2619 & -2.51187 \tabularnewline
103 & 18.25 & 16.1785 & 2.07153 \tabularnewline
104 & 9.9 & 15.116 & -5.21599 \tabularnewline
105 & 16 & 14.3758 & 1.62417 \tabularnewline
106 & 18.25 & 15.6087 & 2.64134 \tabularnewline
107 & 16.85 & 17.0516 & -0.201624 \tabularnewline
108 & 14.6 & 12.4941 & 2.1059 \tabularnewline
109 & 13.85 & 13.8124 & 0.0376387 \tabularnewline
110 & 18.95 & 16.5267 & 2.42326 \tabularnewline
111 & 15.6 & 14.5619 & 1.03812 \tabularnewline
112 & 14.85 & 17.2152 & -2.36517 \tabularnewline
113 & 11.75 & 12.6137 & -0.863686 \tabularnewline
114 & 18.45 & 13.2832 & 5.1668 \tabularnewline
115 & 15.9 & 16.8657 & -0.965674 \tabularnewline
116 & 17.1 & 14.4116 & 2.68838 \tabularnewline
117 & 16.1 & 10.8068 & 5.29317 \tabularnewline
118 & 19.9 & 15.1915 & 4.70848 \tabularnewline
119 & 10.95 & 10.7459 & 0.204095 \tabularnewline
120 & 18.45 & 15.8328 & 2.61719 \tabularnewline
121 & 15.1 & 10.7349 & 4.3651 \tabularnewline
122 & 15 & 15.3563 & -0.356251 \tabularnewline
123 & 11.35 & 14.1336 & -2.78364 \tabularnewline
124 & 15.95 & 15.0036 & 0.946383 \tabularnewline
125 & 18.1 & 13.5291 & 4.57089 \tabularnewline
126 & 14.6 & 13.2258 & 1.3742 \tabularnewline
127 & 15.4 & 15.8267 & -0.42669 \tabularnewline
128 & 15.4 & 15.8267 & -0.42669 \tabularnewline
129 & 17.6 & 13.7306 & 3.86938 \tabularnewline
130 & 13.35 & 14.0167 & -0.666711 \tabularnewline
131 & 19.1 & 16.4447 & 2.65535 \tabularnewline
132 & 15.35 & 13.3186 & 2.0314 \tabularnewline
133 & 7.6 & 12.2238 & -4.62377 \tabularnewline
134 & 13.4 & 14.2917 & -0.891708 \tabularnewline
135 & 13.9 & 13.6135 & 0.286514 \tabularnewline
136 & 19.1 & 17.0728 & 2.02724 \tabularnewline
137 & 15.25 & 13.92 & 1.33004 \tabularnewline
138 & 12.9 & 12.219 & 0.680979 \tabularnewline
139 & 16.1 & 14.0027 & 2.09725 \tabularnewline
140 & 17.35 & 12.363 & 4.98697 \tabularnewline
141 & 13.15 & 12.545 & 0.604958 \tabularnewline
142 & 12.15 & 10.2326 & 1.91737 \tabularnewline
143 & 12.6 & 12.6214 & -0.0213792 \tabularnewline
144 & 10.35 & 11.6186 & -1.2686 \tabularnewline
145 & 15.4 & 12.9007 & 2.49926 \tabularnewline
146 & 9.6 & 11.0091 & -1.40912 \tabularnewline
147 & 18.2 & 13.3503 & 4.8497 \tabularnewline
148 & 13.6 & 12.2096 & 1.39044 \tabularnewline
149 & 14.85 & 14.524 & 0.325987 \tabularnewline
150 & 14.75 & 16.8607 & -2.11069 \tabularnewline
151 & 14.1 & 13.8913 & 0.208727 \tabularnewline
152 & 14.9 & 11.5682 & 3.33182 \tabularnewline
153 & 16.25 & 12.9815 & 3.26847 \tabularnewline
154 & 19.25 & 17.577 & 1.67304 \tabularnewline
155 & 13.6 & 12.0002 & 1.59984 \tabularnewline
156 & 13.6 & 13.3884 & 0.211598 \tabularnewline
157 & 15.65 & 15.0157 & 0.634262 \tabularnewline
158 & 12.75 & 12.2951 & 0.454916 \tabularnewline
159 & 14.6 & 11.3658 & 3.23418 \tabularnewline
160 & 9.85 & 13.2982 & -3.44817 \tabularnewline
161 & 12.65 & 11.1715 & 1.4785 \tabularnewline
162 & 11.9 & 12.2231 & -0.323104 \tabularnewline
163 & 19.2 & 16.4573 & 2.74268 \tabularnewline
164 & 16.6 & 14.3881 & 2.21189 \tabularnewline
165 & 11.2 & 10.2463 & 0.953675 \tabularnewline
166 & 15.25 & 13.1894 & 2.06056 \tabularnewline
167 & 11.9 & 15.2775 & -3.37754 \tabularnewline
168 & 13.2 & 15.3857 & -2.18567 \tabularnewline
169 & 16.35 & 17.168 & -0.818018 \tabularnewline
170 & 12.4 & 13.4488 & -1.04878 \tabularnewline
171 & 15.85 & 13.1134 & 2.73665 \tabularnewline
172 & 14.35 & 13.6263 & 0.723666 \tabularnewline
173 & 18.15 & 14.9396 & 3.21041 \tabularnewline
174 & 11.15 & 11.6359 & -0.485933 \tabularnewline
175 & 15.65 & 15.5247 & 0.125261 \tabularnewline
176 & 17.75 & 16.1166 & 1.63336 \tabularnewline
177 & 7.65 & 12.421 & -4.77095 \tabularnewline
178 & 12.35 & 11.9643 & 0.385734 \tabularnewline
179 & 15.6 & 11.593 & 4.00701 \tabularnewline
180 & 19.3 & 16.2266 & 3.07337 \tabularnewline
181 & 15.2 & 11.85 & 3.35003 \tabularnewline
182 & 17.1 & 13.303 & 3.79697 \tabularnewline
183 & 15.6 & 12.8396 & 2.76041 \tabularnewline
184 & 18.4 & 15.1909 & 3.20914 \tabularnewline
185 & 19.05 & 15.0869 & 3.96311 \tabularnewline
186 & 18.55 & 13.4253 & 5.12465 \tabularnewline
187 & 19.1 & 16.9689 & 2.13115 \tabularnewline
188 & 13.1 & 11.9135 & 1.18653 \tabularnewline
189 & 12.85 & 13.3501 & -0.500129 \tabularnewline
190 & 9.5 & 11.6133 & -2.11328 \tabularnewline
191 & 4.5 & 11.2718 & -6.77177 \tabularnewline
192 & 11.85 & 10.6105 & 1.23951 \tabularnewline
193 & 13.6 & 15.9082 & -2.30817 \tabularnewline
194 & 11.7 & 13.4015 & -1.7015 \tabularnewline
195 & 12.4 & 11.6584 & 0.741601 \tabularnewline
196 & 13.35 & 14.8012 & -1.45118 \tabularnewline
197 & 11.4 & 13.7665 & -2.36645 \tabularnewline
198 & 14.9 & 11.9514 & 2.94865 \tabularnewline
199 & 19.9 & 15.1915 & 4.70848 \tabularnewline
200 & 17.75 & 12.1213 & 5.62868 \tabularnewline
201 & 11.2 & 11.9464 & -0.746392 \tabularnewline
202 & 14.6 & 15.4073 & -0.807347 \tabularnewline
203 & 17.6 & 16.004 & 1.59596 \tabularnewline
204 & 14.05 & 12.6431 & 1.40686 \tabularnewline
205 & 16.1 & 15.2338 & 0.866231 \tabularnewline
206 & 13.35 & 13.2089 & 0.141086 \tabularnewline
207 & 11.85 & 12.5414 & -0.691409 \tabularnewline
208 & 11.95 & 14.3464 & -2.39641 \tabularnewline
209 & 14.75 & 14.6038 & 0.146176 \tabularnewline
210 & 15.15 & 13.3228 & 1.82724 \tabularnewline
211 & 13.2 & 13.7901 & -0.590082 \tabularnewline
212 & 16.85 & 15.4724 & 1.37758 \tabularnewline
213 & 7.85 & 10.4542 & -2.60417 \tabularnewline
214 & 7.7 & 14.4446 & -6.74463 \tabularnewline
215 & 12.6 & 12.0037 & 0.596327 \tabularnewline
216 & 7.85 & 11.8408 & -3.99085 \tabularnewline
217 & 10.95 & 10.7459 & 0.204095 \tabularnewline
218 & 12.35 & 12.1347 & 0.215341 \tabularnewline
219 & 9.95 & 12.8451 & -2.89514 \tabularnewline
220 & 14.9 & 11.9514 & 2.94865 \tabularnewline
221 & 16.65 & 14.548 & 2.10199 \tabularnewline
222 & 13.4 & 12.9448 & 0.455221 \tabularnewline
223 & 13.95 & 13.2672 & 0.682822 \tabularnewline
224 & 15.7 & 11.8866 & 3.81337 \tabularnewline
225 & 16.85 & 12.4966 & 4.3534 \tabularnewline
226 & 10.95 & 10.6416 & 0.308365 \tabularnewline
227 & 15.35 & 11.8606 & 3.48944 \tabularnewline
228 & 12.2 & 11.3339 & 0.866086 \tabularnewline
229 & 15.1 & 14.1328 & 0.967152 \tabularnewline
230 & 17.75 & 16.3212 & 1.42877 \tabularnewline
231 & 15.2 & 12.9964 & 2.20357 \tabularnewline
232 & 14.6 & 13.4204 & 1.17958 \tabularnewline
233 & 16.65 & 14.7344 & 1.91558 \tabularnewline
234 & 8.1 & 10.8145 & -2.71455 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265188&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]12.5704[/C][C]0.329604[/C][/ROW]
[ROW][C]2[/C][C]12.8[/C][C]12.526[/C][C]0.273986[/C][/ROW]
[ROW][C]3[/C][C]7.4[/C][C]13.3195[/C][C]-5.91948[/C][/ROW]
[ROW][C]4[/C][C]6.7[/C][C]11.7864[/C][C]-5.08637[/C][/ROW]
[ROW][C]5[/C][C]12.6[/C][C]15.702[/C][C]-3.10198[/C][/ROW]
[ROW][C]6[/C][C]14.8[/C][C]13.2461[/C][C]1.55387[/C][/ROW]
[ROW][C]7[/C][C]13.3[/C][C]12.9603[/C][C]0.339744[/C][/ROW]
[ROW][C]8[/C][C]11.1[/C][C]13.4705[/C][C]-2.37047[/C][/ROW]
[ROW][C]9[/C][C]8.2[/C][C]14.4167[/C][C]-6.21672[/C][/ROW]
[ROW][C]10[/C][C]11.4[/C][C]13.3368[/C][C]-1.93685[/C][/ROW]
[ROW][C]11[/C][C]6.4[/C][C]14.8808[/C][C]-8.48077[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]14.3465[/C][C]-2.3465[/C][/ROW]
[ROW][C]13[/C][C]6.3[/C][C]10.0812[/C][C]-3.78118[/C][/ROW]
[ROW][C]14[/C][C]11.3[/C][C]11.6137[/C][C]-0.313708[/C][/ROW]
[ROW][C]15[/C][C]11.9[/C][C]14.3577[/C][C]-2.45774[/C][/ROW]
[ROW][C]16[/C][C]9.3[/C][C]12.4612[/C][C]-3.16117[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]12.0134[/C][C]-2.01342[/C][/ROW]
[ROW][C]18[/C][C]13.8[/C][C]13.4005[/C][C]0.399549[/C][/ROW]
[ROW][C]19[/C][C]10.8[/C][C]13.7489[/C][C]-2.94894[/C][/ROW]
[ROW][C]20[/C][C]11.7[/C][C]13.1809[/C][C]-1.4809[/C][/ROW]
[ROW][C]21[/C][C]10.9[/C][C]15.568[/C][C]-4.66797[/C][/ROW]
[ROW][C]22[/C][C]16.1[/C][C]14.2517[/C][C]1.84831[/C][/ROW]
[ROW][C]23[/C][C]9.9[/C][C]11.8681[/C][C]-1.96805[/C][/ROW]
[ROW][C]24[/C][C]11.5[/C][C]12.5716[/C][C]-1.07157[/C][/ROW]
[ROW][C]25[/C][C]8.3[/C][C]12.2304[/C][C]-3.93038[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]13.6034[/C][C]-1.90343[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]12.6235[/C][C]-3.62347[/C][/ROW]
[ROW][C]28[/C][C]10.8[/C][C]12.8671[/C][C]-2.06708[/C][/ROW]
[ROW][C]29[/C][C]10.4[/C][C]12.1154[/C][C]-1.71541[/C][/ROW]
[ROW][C]30[/C][C]12.7[/C][C]12.9037[/C][C]-0.203748[/C][/ROW]
[ROW][C]31[/C][C]11.8[/C][C]14.597[/C][C]-2.79697[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.4158[/C][C]0.58417[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]12.9971[/C][C]-2.19709[/C][/ROW]
[ROW][C]34[/C][C]12.3[/C][C]10.8064[/C][C]1.4936[/C][/ROW]
[ROW][C]35[/C][C]11.3[/C][C]13.9037[/C][C]-2.60366[/C][/ROW]
[ROW][C]36[/C][C]11.6[/C][C]12.3437[/C][C]-0.743738[/C][/ROW]
[ROW][C]37[/C][C]10.9[/C][C]13.2957[/C][C]-2.3957[/C][/ROW]
[ROW][C]38[/C][C]12.1[/C][C]12.8604[/C][C]-0.760388[/C][/ROW]
[ROW][C]39[/C][C]13.3[/C][C]13.8023[/C][C]-0.502321[/C][/ROW]
[ROW][C]40[/C][C]10.1[/C][C]13.4647[/C][C]-3.36474[/C][/ROW]
[ROW][C]41[/C][C]14.3[/C][C]12.5901[/C][C]1.70988[/C][/ROW]
[ROW][C]42[/C][C]9.3[/C][C]13.3899[/C][C]-4.08987[/C][/ROW]
[ROW][C]43[/C][C]12.5[/C][C]12.0183[/C][C]0.48168[/C][/ROW]
[ROW][C]44[/C][C]7.6[/C][C]11.2265[/C][C]-3.62647[/C][/ROW]
[ROW][C]45[/C][C]9.2[/C][C]11.9697[/C][C]-2.76968[/C][/ROW]
[ROW][C]46[/C][C]14.5[/C][C]13.3201[/C][C]1.17991[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]14.1016[/C][C]-1.80158[/C][/ROW]
[ROW][C]48[/C][C]12.6[/C][C]13.3461[/C][C]-0.746107[/C][/ROW]
[ROW][C]49[/C][C]13[/C][C]14.117[/C][C]-1.11699[/C][/ROW]
[ROW][C]50[/C][C]12.6[/C][C]11.6229[/C][C]0.977084[/C][/ROW]
[ROW][C]51[/C][C]13.2[/C][C]14.9486[/C][C]-1.74861[/C][/ROW]
[ROW][C]52[/C][C]7.7[/C][C]11.9872[/C][C]-4.28723[/C][/ROW]
[ROW][C]53[/C][C]10.5[/C][C]11.1055[/C][C]-0.605484[/C][/ROW]
[ROW][C]54[/C][C]10.9[/C][C]12.2246[/C][C]-1.32463[/C][/ROW]
[ROW][C]55[/C][C]4.3[/C][C]10.4546[/C][C]-6.15462[/C][/ROW]
[ROW][C]56[/C][C]10.3[/C][C]11.6029[/C][C]-1.30289[/C][/ROW]
[ROW][C]57[/C][C]11.4[/C][C]11.1835[/C][C]0.216515[/C][/ROW]
[ROW][C]58[/C][C]5.6[/C][C]11.3829[/C][C]-5.78291[/C][/ROW]
[ROW][C]59[/C][C]8.8[/C][C]12.0483[/C][C]-3.24829[/C][/ROW]
[ROW][C]60[/C][C]9[/C][C]10.7317[/C][C]-1.73169[/C][/ROW]
[ROW][C]61[/C][C]9.6[/C][C]11.4987[/C][C]-1.89872[/C][/ROW]
[ROW][C]62[/C][C]6.4[/C][C]10.4214[/C][C]-4.02136[/C][/ROW]
[ROW][C]63[/C][C]11.6[/C][C]11.1872[/C][C]0.412829[/C][/ROW]
[ROW][C]64[/C][C]4.35[/C][C]10.1771[/C][C]-5.82708[/C][/ROW]
[ROW][C]65[/C][C]12.7[/C][C]12.695[/C][C]0.00504107[/C][/ROW]
[ROW][C]66[/C][C]18.1[/C][C]14.7844[/C][C]3.31557[/C][/ROW]
[ROW][C]67[/C][C]17.85[/C][C]15.063[/C][C]2.78698[/C][/ROW]
[ROW][C]68[/C][C]16.6[/C][C]16.3371[/C][C]0.262909[/C][/ROW]
[ROW][C]69[/C][C]12.6[/C][C]10.1795[/C][C]2.42048[/C][/ROW]
[ROW][C]70[/C][C]17.1[/C][C]21.6482[/C][C]-4.54816[/C][/ROW]
[ROW][C]71[/C][C]19.1[/C][C]15.9698[/C][C]3.13021[/C][/ROW]
[ROW][C]72[/C][C]16.1[/C][C]19.0417[/C][C]-2.94167[/C][/ROW]
[ROW][C]73[/C][C]13.35[/C][C]10.7348[/C][C]2.61516[/C][/ROW]
[ROW][C]74[/C][C]18.4[/C][C]17.3924[/C][C]1.00757[/C][/ROW]
[ROW][C]75[/C][C]14.7[/C][C]11.0713[/C][C]3.62866[/C][/ROW]
[ROW][C]76[/C][C]10.6[/C][C]14.7325[/C][C]-4.13254[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]13.6713[/C][C]-1.07126[/C][/ROW]
[ROW][C]78[/C][C]16.2[/C][C]14.9981[/C][C]1.20186[/C][/ROW]
[ROW][C]79[/C][C]13.6[/C][C]17.7189[/C][C]-4.11886[/C][/ROW]
[ROW][C]80[/C][C]18.9[/C][C]16.1303[/C][C]2.76975[/C][/ROW]
[ROW][C]81[/C][C]14.1[/C][C]12.4787[/C][C]1.6213[/C][/ROW]
[ROW][C]82[/C][C]14.5[/C][C]11.986[/C][C]2.51397[/C][/ROW]
[ROW][C]83[/C][C]16.15[/C][C]18.2592[/C][C]-2.10923[/C][/ROW]
[ROW][C]84[/C][C]14.75[/C][C]13.6294[/C][C]1.12062[/C][/ROW]
[ROW][C]85[/C][C]14.8[/C][C]14.3636[/C][C]0.436407[/C][/ROW]
[ROW][C]86[/C][C]12.45[/C][C]12.3502[/C][C]0.0998136[/C][/ROW]
[ROW][C]87[/C][C]12.65[/C][C]14.6689[/C][C]-2.01892[/C][/ROW]
[ROW][C]88[/C][C]17.35[/C][C]13.7402[/C][C]3.60981[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]11.9707[/C][C]-3.37068[/C][/ROW]
[ROW][C]90[/C][C]18.4[/C][C]17.5145[/C][C]0.885533[/C][/ROW]
[ROW][C]91[/C][C]16.1[/C][C]17.9345[/C][C]-1.83449[/C][/ROW]
[ROW][C]92[/C][C]11.6[/C][C]11.2499[/C][C]0.350072[/C][/ROW]
[ROW][C]93[/C][C]17.75[/C][C]12.2657[/C][C]5.48427[/C][/ROW]
[ROW][C]94[/C][C]15.25[/C][C]14.1373[/C][C]1.11267[/C][/ROW]
[ROW][C]95[/C][C]17.65[/C][C]16.0016[/C][C]1.64841[/C][/ROW]
[ROW][C]96[/C][C]15.6[/C][C]13.7021[/C][C]1.89785[/C][/ROW]
[ROW][C]97[/C][C]16.35[/C][C]15.1365[/C][C]1.21349[/C][/ROW]
[ROW][C]98[/C][C]17.65[/C][C]15.0588[/C][C]2.5912[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]13.1769[/C][C]0.423121[/C][/ROW]
[ROW][C]100[/C][C]11.7[/C][C]12.3296[/C][C]-0.629612[/C][/ROW]
[ROW][C]101[/C][C]14.35[/C][C]13.62[/C][C]0.730007[/C][/ROW]
[ROW][C]102[/C][C]14.75[/C][C]17.2619[/C][C]-2.51187[/C][/ROW]
[ROW][C]103[/C][C]18.25[/C][C]16.1785[/C][C]2.07153[/C][/ROW]
[ROW][C]104[/C][C]9.9[/C][C]15.116[/C][C]-5.21599[/C][/ROW]
[ROW][C]105[/C][C]16[/C][C]14.3758[/C][C]1.62417[/C][/ROW]
[ROW][C]106[/C][C]18.25[/C][C]15.6087[/C][C]2.64134[/C][/ROW]
[ROW][C]107[/C][C]16.85[/C][C]17.0516[/C][C]-0.201624[/C][/ROW]
[ROW][C]108[/C][C]14.6[/C][C]12.4941[/C][C]2.1059[/C][/ROW]
[ROW][C]109[/C][C]13.85[/C][C]13.8124[/C][C]0.0376387[/C][/ROW]
[ROW][C]110[/C][C]18.95[/C][C]16.5267[/C][C]2.42326[/C][/ROW]
[ROW][C]111[/C][C]15.6[/C][C]14.5619[/C][C]1.03812[/C][/ROW]
[ROW][C]112[/C][C]14.85[/C][C]17.2152[/C][C]-2.36517[/C][/ROW]
[ROW][C]113[/C][C]11.75[/C][C]12.6137[/C][C]-0.863686[/C][/ROW]
[ROW][C]114[/C][C]18.45[/C][C]13.2832[/C][C]5.1668[/C][/ROW]
[ROW][C]115[/C][C]15.9[/C][C]16.8657[/C][C]-0.965674[/C][/ROW]
[ROW][C]116[/C][C]17.1[/C][C]14.4116[/C][C]2.68838[/C][/ROW]
[ROW][C]117[/C][C]16.1[/C][C]10.8068[/C][C]5.29317[/C][/ROW]
[ROW][C]118[/C][C]19.9[/C][C]15.1915[/C][C]4.70848[/C][/ROW]
[ROW][C]119[/C][C]10.95[/C][C]10.7459[/C][C]0.204095[/C][/ROW]
[ROW][C]120[/C][C]18.45[/C][C]15.8328[/C][C]2.61719[/C][/ROW]
[ROW][C]121[/C][C]15.1[/C][C]10.7349[/C][C]4.3651[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]15.3563[/C][C]-0.356251[/C][/ROW]
[ROW][C]123[/C][C]11.35[/C][C]14.1336[/C][C]-2.78364[/C][/ROW]
[ROW][C]124[/C][C]15.95[/C][C]15.0036[/C][C]0.946383[/C][/ROW]
[ROW][C]125[/C][C]18.1[/C][C]13.5291[/C][C]4.57089[/C][/ROW]
[ROW][C]126[/C][C]14.6[/C][C]13.2258[/C][C]1.3742[/C][/ROW]
[ROW][C]127[/C][C]15.4[/C][C]15.8267[/C][C]-0.42669[/C][/ROW]
[ROW][C]128[/C][C]15.4[/C][C]15.8267[/C][C]-0.42669[/C][/ROW]
[ROW][C]129[/C][C]17.6[/C][C]13.7306[/C][C]3.86938[/C][/ROW]
[ROW][C]130[/C][C]13.35[/C][C]14.0167[/C][C]-0.666711[/C][/ROW]
[ROW][C]131[/C][C]19.1[/C][C]16.4447[/C][C]2.65535[/C][/ROW]
[ROW][C]132[/C][C]15.35[/C][C]13.3186[/C][C]2.0314[/C][/ROW]
[ROW][C]133[/C][C]7.6[/C][C]12.2238[/C][C]-4.62377[/C][/ROW]
[ROW][C]134[/C][C]13.4[/C][C]14.2917[/C][C]-0.891708[/C][/ROW]
[ROW][C]135[/C][C]13.9[/C][C]13.6135[/C][C]0.286514[/C][/ROW]
[ROW][C]136[/C][C]19.1[/C][C]17.0728[/C][C]2.02724[/C][/ROW]
[ROW][C]137[/C][C]15.25[/C][C]13.92[/C][C]1.33004[/C][/ROW]
[ROW][C]138[/C][C]12.9[/C][C]12.219[/C][C]0.680979[/C][/ROW]
[ROW][C]139[/C][C]16.1[/C][C]14.0027[/C][C]2.09725[/C][/ROW]
[ROW][C]140[/C][C]17.35[/C][C]12.363[/C][C]4.98697[/C][/ROW]
[ROW][C]141[/C][C]13.15[/C][C]12.545[/C][C]0.604958[/C][/ROW]
[ROW][C]142[/C][C]12.15[/C][C]10.2326[/C][C]1.91737[/C][/ROW]
[ROW][C]143[/C][C]12.6[/C][C]12.6214[/C][C]-0.0213792[/C][/ROW]
[ROW][C]144[/C][C]10.35[/C][C]11.6186[/C][C]-1.2686[/C][/ROW]
[ROW][C]145[/C][C]15.4[/C][C]12.9007[/C][C]2.49926[/C][/ROW]
[ROW][C]146[/C][C]9.6[/C][C]11.0091[/C][C]-1.40912[/C][/ROW]
[ROW][C]147[/C][C]18.2[/C][C]13.3503[/C][C]4.8497[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.2096[/C][C]1.39044[/C][/ROW]
[ROW][C]149[/C][C]14.85[/C][C]14.524[/C][C]0.325987[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]16.8607[/C][C]-2.11069[/C][/ROW]
[ROW][C]151[/C][C]14.1[/C][C]13.8913[/C][C]0.208727[/C][/ROW]
[ROW][C]152[/C][C]14.9[/C][C]11.5682[/C][C]3.33182[/C][/ROW]
[ROW][C]153[/C][C]16.25[/C][C]12.9815[/C][C]3.26847[/C][/ROW]
[ROW][C]154[/C][C]19.25[/C][C]17.577[/C][C]1.67304[/C][/ROW]
[ROW][C]155[/C][C]13.6[/C][C]12.0002[/C][C]1.59984[/C][/ROW]
[ROW][C]156[/C][C]13.6[/C][C]13.3884[/C][C]0.211598[/C][/ROW]
[ROW][C]157[/C][C]15.65[/C][C]15.0157[/C][C]0.634262[/C][/ROW]
[ROW][C]158[/C][C]12.75[/C][C]12.2951[/C][C]0.454916[/C][/ROW]
[ROW][C]159[/C][C]14.6[/C][C]11.3658[/C][C]3.23418[/C][/ROW]
[ROW][C]160[/C][C]9.85[/C][C]13.2982[/C][C]-3.44817[/C][/ROW]
[ROW][C]161[/C][C]12.65[/C][C]11.1715[/C][C]1.4785[/C][/ROW]
[ROW][C]162[/C][C]11.9[/C][C]12.2231[/C][C]-0.323104[/C][/ROW]
[ROW][C]163[/C][C]19.2[/C][C]16.4573[/C][C]2.74268[/C][/ROW]
[ROW][C]164[/C][C]16.6[/C][C]14.3881[/C][C]2.21189[/C][/ROW]
[ROW][C]165[/C][C]11.2[/C][C]10.2463[/C][C]0.953675[/C][/ROW]
[ROW][C]166[/C][C]15.25[/C][C]13.1894[/C][C]2.06056[/C][/ROW]
[ROW][C]167[/C][C]11.9[/C][C]15.2775[/C][C]-3.37754[/C][/ROW]
[ROW][C]168[/C][C]13.2[/C][C]15.3857[/C][C]-2.18567[/C][/ROW]
[ROW][C]169[/C][C]16.35[/C][C]17.168[/C][C]-0.818018[/C][/ROW]
[ROW][C]170[/C][C]12.4[/C][C]13.4488[/C][C]-1.04878[/C][/ROW]
[ROW][C]171[/C][C]15.85[/C][C]13.1134[/C][C]2.73665[/C][/ROW]
[ROW][C]172[/C][C]14.35[/C][C]13.6263[/C][C]0.723666[/C][/ROW]
[ROW][C]173[/C][C]18.15[/C][C]14.9396[/C][C]3.21041[/C][/ROW]
[ROW][C]174[/C][C]11.15[/C][C]11.6359[/C][C]-0.485933[/C][/ROW]
[ROW][C]175[/C][C]15.65[/C][C]15.5247[/C][C]0.125261[/C][/ROW]
[ROW][C]176[/C][C]17.75[/C][C]16.1166[/C][C]1.63336[/C][/ROW]
[ROW][C]177[/C][C]7.65[/C][C]12.421[/C][C]-4.77095[/C][/ROW]
[ROW][C]178[/C][C]12.35[/C][C]11.9643[/C][C]0.385734[/C][/ROW]
[ROW][C]179[/C][C]15.6[/C][C]11.593[/C][C]4.00701[/C][/ROW]
[ROW][C]180[/C][C]19.3[/C][C]16.2266[/C][C]3.07337[/C][/ROW]
[ROW][C]181[/C][C]15.2[/C][C]11.85[/C][C]3.35003[/C][/ROW]
[ROW][C]182[/C][C]17.1[/C][C]13.303[/C][C]3.79697[/C][/ROW]
[ROW][C]183[/C][C]15.6[/C][C]12.8396[/C][C]2.76041[/C][/ROW]
[ROW][C]184[/C][C]18.4[/C][C]15.1909[/C][C]3.20914[/C][/ROW]
[ROW][C]185[/C][C]19.05[/C][C]15.0869[/C][C]3.96311[/C][/ROW]
[ROW][C]186[/C][C]18.55[/C][C]13.4253[/C][C]5.12465[/C][/ROW]
[ROW][C]187[/C][C]19.1[/C][C]16.9689[/C][C]2.13115[/C][/ROW]
[ROW][C]188[/C][C]13.1[/C][C]11.9135[/C][C]1.18653[/C][/ROW]
[ROW][C]189[/C][C]12.85[/C][C]13.3501[/C][C]-0.500129[/C][/ROW]
[ROW][C]190[/C][C]9.5[/C][C]11.6133[/C][C]-2.11328[/C][/ROW]
[ROW][C]191[/C][C]4.5[/C][C]11.2718[/C][C]-6.77177[/C][/ROW]
[ROW][C]192[/C][C]11.85[/C][C]10.6105[/C][C]1.23951[/C][/ROW]
[ROW][C]193[/C][C]13.6[/C][C]15.9082[/C][C]-2.30817[/C][/ROW]
[ROW][C]194[/C][C]11.7[/C][C]13.4015[/C][C]-1.7015[/C][/ROW]
[ROW][C]195[/C][C]12.4[/C][C]11.6584[/C][C]0.741601[/C][/ROW]
[ROW][C]196[/C][C]13.35[/C][C]14.8012[/C][C]-1.45118[/C][/ROW]
[ROW][C]197[/C][C]11.4[/C][C]13.7665[/C][C]-2.36645[/C][/ROW]
[ROW][C]198[/C][C]14.9[/C][C]11.9514[/C][C]2.94865[/C][/ROW]
[ROW][C]199[/C][C]19.9[/C][C]15.1915[/C][C]4.70848[/C][/ROW]
[ROW][C]200[/C][C]17.75[/C][C]12.1213[/C][C]5.62868[/C][/ROW]
[ROW][C]201[/C][C]11.2[/C][C]11.9464[/C][C]-0.746392[/C][/ROW]
[ROW][C]202[/C][C]14.6[/C][C]15.4073[/C][C]-0.807347[/C][/ROW]
[ROW][C]203[/C][C]17.6[/C][C]16.004[/C][C]1.59596[/C][/ROW]
[ROW][C]204[/C][C]14.05[/C][C]12.6431[/C][C]1.40686[/C][/ROW]
[ROW][C]205[/C][C]16.1[/C][C]15.2338[/C][C]0.866231[/C][/ROW]
[ROW][C]206[/C][C]13.35[/C][C]13.2089[/C][C]0.141086[/C][/ROW]
[ROW][C]207[/C][C]11.85[/C][C]12.5414[/C][C]-0.691409[/C][/ROW]
[ROW][C]208[/C][C]11.95[/C][C]14.3464[/C][C]-2.39641[/C][/ROW]
[ROW][C]209[/C][C]14.75[/C][C]14.6038[/C][C]0.146176[/C][/ROW]
[ROW][C]210[/C][C]15.15[/C][C]13.3228[/C][C]1.82724[/C][/ROW]
[ROW][C]211[/C][C]13.2[/C][C]13.7901[/C][C]-0.590082[/C][/ROW]
[ROW][C]212[/C][C]16.85[/C][C]15.4724[/C][C]1.37758[/C][/ROW]
[ROW][C]213[/C][C]7.85[/C][C]10.4542[/C][C]-2.60417[/C][/ROW]
[ROW][C]214[/C][C]7.7[/C][C]14.4446[/C][C]-6.74463[/C][/ROW]
[ROW][C]215[/C][C]12.6[/C][C]12.0037[/C][C]0.596327[/C][/ROW]
[ROW][C]216[/C][C]7.85[/C][C]11.8408[/C][C]-3.99085[/C][/ROW]
[ROW][C]217[/C][C]10.95[/C][C]10.7459[/C][C]0.204095[/C][/ROW]
[ROW][C]218[/C][C]12.35[/C][C]12.1347[/C][C]0.215341[/C][/ROW]
[ROW][C]219[/C][C]9.95[/C][C]12.8451[/C][C]-2.89514[/C][/ROW]
[ROW][C]220[/C][C]14.9[/C][C]11.9514[/C][C]2.94865[/C][/ROW]
[ROW][C]221[/C][C]16.65[/C][C]14.548[/C][C]2.10199[/C][/ROW]
[ROW][C]222[/C][C]13.4[/C][C]12.9448[/C][C]0.455221[/C][/ROW]
[ROW][C]223[/C][C]13.95[/C][C]13.2672[/C][C]0.682822[/C][/ROW]
[ROW][C]224[/C][C]15.7[/C][C]11.8866[/C][C]3.81337[/C][/ROW]
[ROW][C]225[/C][C]16.85[/C][C]12.4966[/C][C]4.3534[/C][/ROW]
[ROW][C]226[/C][C]10.95[/C][C]10.6416[/C][C]0.308365[/C][/ROW]
[ROW][C]227[/C][C]15.35[/C][C]11.8606[/C][C]3.48944[/C][/ROW]
[ROW][C]228[/C][C]12.2[/C][C]11.3339[/C][C]0.866086[/C][/ROW]
[ROW][C]229[/C][C]15.1[/C][C]14.1328[/C][C]0.967152[/C][/ROW]
[ROW][C]230[/C][C]17.75[/C][C]16.3212[/C][C]1.42877[/C][/ROW]
[ROW][C]231[/C][C]15.2[/C][C]12.9964[/C][C]2.20357[/C][/ROW]
[ROW][C]232[/C][C]14.6[/C][C]13.4204[/C][C]1.17958[/C][/ROW]
[ROW][C]233[/C][C]16.65[/C][C]14.7344[/C][C]1.91558[/C][/ROW]
[ROW][C]234[/C][C]8.1[/C][C]10.8145[/C][C]-2.71455[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265188&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265188&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
112.912.57040.329604
212.812.5260.273986
37.413.3195-5.91948
46.711.7864-5.08637
512.615.702-3.10198
614.813.24611.55387
713.312.96030.339744
811.113.4705-2.37047
98.214.4167-6.21672
1011.413.3368-1.93685
116.414.8808-8.48077
121214.3465-2.3465
136.310.0812-3.78118
1411.311.6137-0.313708
1511.914.3577-2.45774
169.312.4612-3.16117
171012.0134-2.01342
1813.813.40050.399549
1910.813.7489-2.94894
2011.713.1809-1.4809
2110.915.568-4.66797
2216.114.25171.84831
239.911.8681-1.96805
2411.512.5716-1.07157
258.312.2304-3.93038
2611.713.6034-1.90343
27912.6235-3.62347
2810.812.8671-2.06708
2910.412.1154-1.71541
3012.712.9037-0.203748
3111.814.597-2.79697
321312.41580.58417
3310.812.9971-2.19709
3412.310.80641.4936
3511.313.9037-2.60366
3611.612.3437-0.743738
3710.913.2957-2.3957
3812.112.8604-0.760388
3913.313.8023-0.502321
4010.113.4647-3.36474
4114.312.59011.70988
429.313.3899-4.08987
4312.512.01830.48168
447.611.2265-3.62647
459.211.9697-2.76968
4614.513.32011.17991
4712.314.1016-1.80158
4812.613.3461-0.746107
491314.117-1.11699
5012.611.62290.977084
5113.214.9486-1.74861
527.711.9872-4.28723
5310.511.1055-0.605484
5410.912.2246-1.32463
554.310.4546-6.15462
5610.311.6029-1.30289
5711.411.18350.216515
585.611.3829-5.78291
598.812.0483-3.24829
60910.7317-1.73169
619.611.4987-1.89872
626.410.4214-4.02136
6311.611.18720.412829
644.3510.1771-5.82708
6512.712.6950.00504107
6618.114.78443.31557
6717.8515.0632.78698
6816.616.33710.262909
6912.610.17952.42048
7017.121.6482-4.54816
7119.115.96983.13021
7216.119.0417-2.94167
7313.3510.73482.61516
7418.417.39241.00757
7514.711.07133.62866
7610.614.7325-4.13254
7712.613.6713-1.07126
7816.214.99811.20186
7913.617.7189-4.11886
8018.916.13032.76975
8114.112.47871.6213
8214.511.9862.51397
8316.1518.2592-2.10923
8414.7513.62941.12062
8514.814.36360.436407
8612.4512.35020.0998136
8712.6514.6689-2.01892
8817.3513.74023.60981
898.611.9707-3.37068
9018.417.51450.885533
9116.117.9345-1.83449
9211.611.24990.350072
9317.7512.26575.48427
9415.2514.13731.11267
9517.6516.00161.64841
9615.613.70211.89785
9716.3515.13651.21349
9817.6515.05882.5912
9913.613.17690.423121
10011.712.3296-0.629612
10114.3513.620.730007
10214.7517.2619-2.51187
10318.2516.17852.07153
1049.915.116-5.21599
1051614.37581.62417
10618.2515.60872.64134
10716.8517.0516-0.201624
10814.612.49412.1059
10913.8513.81240.0376387
11018.9516.52672.42326
11115.614.56191.03812
11214.8517.2152-2.36517
11311.7512.6137-0.863686
11418.4513.28325.1668
11515.916.8657-0.965674
11617.114.41162.68838
11716.110.80685.29317
11819.915.19154.70848
11910.9510.74590.204095
12018.4515.83282.61719
12115.110.73494.3651
1221515.3563-0.356251
12311.3514.1336-2.78364
12415.9515.00360.946383
12518.113.52914.57089
12614.613.22581.3742
12715.415.8267-0.42669
12815.415.8267-0.42669
12917.613.73063.86938
13013.3514.0167-0.666711
13119.116.44472.65535
13215.3513.31862.0314
1337.612.2238-4.62377
13413.414.2917-0.891708
13513.913.61350.286514
13619.117.07282.02724
13715.2513.921.33004
13812.912.2190.680979
13916.114.00272.09725
14017.3512.3634.98697
14113.1512.5450.604958
14212.1510.23261.91737
14312.612.6214-0.0213792
14410.3511.6186-1.2686
14515.412.90072.49926
1469.611.0091-1.40912
14718.213.35034.8497
14813.612.20961.39044
14914.8514.5240.325987
15014.7516.8607-2.11069
15114.113.89130.208727
15214.911.56823.33182
15316.2512.98153.26847
15419.2517.5771.67304
15513.612.00021.59984
15613.613.38840.211598
15715.6515.01570.634262
15812.7512.29510.454916
15914.611.36583.23418
1609.8513.2982-3.44817
16112.6511.17151.4785
16211.912.2231-0.323104
16319.216.45732.74268
16416.614.38812.21189
16511.210.24630.953675
16615.2513.18942.06056
16711.915.2775-3.37754
16813.215.3857-2.18567
16916.3517.168-0.818018
17012.413.4488-1.04878
17115.8513.11342.73665
17214.3513.62630.723666
17318.1514.93963.21041
17411.1511.6359-0.485933
17515.6515.52470.125261
17617.7516.11661.63336
1777.6512.421-4.77095
17812.3511.96430.385734
17915.611.5934.00701
18019.316.22663.07337
18115.211.853.35003
18217.113.3033.79697
18315.612.83962.76041
18418.415.19093.20914
18519.0515.08693.96311
18618.5513.42535.12465
18719.116.96892.13115
18813.111.91351.18653
18912.8513.3501-0.500129
1909.511.6133-2.11328
1914.511.2718-6.77177
19211.8510.61051.23951
19313.615.9082-2.30817
19411.713.4015-1.7015
19512.411.65840.741601
19613.3514.8012-1.45118
19711.413.7665-2.36645
19814.911.95142.94865
19919.915.19154.70848
20017.7512.12135.62868
20111.211.9464-0.746392
20214.615.4073-0.807347
20317.616.0041.59596
20414.0512.64311.40686
20516.115.23380.866231
20613.3513.20890.141086
20711.8512.5414-0.691409
20811.9514.3464-2.39641
20914.7514.60380.146176
21015.1513.32281.82724
21113.213.7901-0.590082
21216.8515.47241.37758
2137.8510.4542-2.60417
2147.714.4446-6.74463
21512.612.00370.596327
2167.8511.8408-3.99085
21710.9510.74590.204095
21812.3512.13470.215341
2199.9512.8451-2.89514
22014.911.95142.94865
22116.6514.5482.10199
22213.412.94480.455221
22313.9513.26720.682822
22415.711.88663.81337
22516.8512.49664.3534
22610.9510.64160.308365
22715.3511.86063.48944
22812.211.33390.866086
22915.114.13280.967152
23017.7516.32121.42877
23115.212.99642.20357
23214.613.42041.17958
23316.6514.73441.91558
2348.110.8145-2.71455






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.8174470.3651050.182553
80.8069560.3860880.193044
90.9049970.1900070.0950034
100.8477070.3045860.152293
110.8937610.2124770.106239
120.8453350.3093310.154665
130.8364070.3271850.163593
140.8187290.3625420.181271
150.7720410.4559190.227959
160.7155880.5688240.284412
170.6458080.7083840.354192
180.5716930.8566130.428307
190.524380.9512410.47562
200.4595630.9191260.540437
210.4152150.830430.584785
220.4071460.8142930.592854
230.3459250.6918510.654075
240.3097330.6194660.690267
250.267070.5341410.73293
260.2401790.4803580.759821
270.2105230.4210470.789477
280.1739940.3479890.826006
290.1418090.2836180.858191
300.1252660.2505310.874734
310.1094380.2188770.890562
320.09087040.1817410.90913
330.07474530.1494910.925255
340.08554230.1710850.914458
350.07331540.1466310.926685
360.06013630.1202730.939864
370.05113280.1022660.948867
380.04634840.09269680.953652
390.04592130.09184250.954079
400.03746970.07493940.96253
410.05153050.1030610.94847
420.0537630.1075260.946237
430.04184760.08369520.958152
440.04840020.09680030.9516
450.05385870.1077170.946141
460.04897960.09795920.95102
470.04302170.08604340.956978
480.04083120.08166240.959169
490.03798260.07596520.962017
500.03291820.06583640.967082
510.03590920.07181840.964091
520.05106380.1021280.948936
530.04059230.08118460.959408
540.0323940.06478790.967606
550.1044340.2088670.895566
560.09243960.1848790.90756
570.07534360.1506870.924656
580.148420.2968410.85158
590.1450070.2900150.854993
600.1407150.281430.859285
610.1396520.2793040.860348
620.1549790.3099580.845021
630.1541610.3083230.845839
640.2912670.5825340.708733
650.3189750.637950.681025
660.5183960.9632090.481604
670.6324310.7351370.367569
680.6071190.7857610.392881
690.6742920.6514160.325708
700.6938920.6122170.306108
710.7374790.5250420.262521
720.7285110.5429770.271489
730.7732660.4534680.226734
740.787490.4250190.21251
750.8520810.2958380.147919
760.877980.244040.12202
770.8638650.2722710.136135
780.8685930.2628140.131407
790.9040420.1919160.0959582
800.9149940.1700110.0850056
810.9126230.1747540.087377
820.9234740.1530530.0765264
830.9170610.1658780.082939
840.9102030.1795950.0897974
850.8974470.2051060.102553
860.8815510.2368980.118449
870.8672440.2655130.132756
880.9085430.1829140.0914572
890.9104950.179010.0895049
900.9063420.1873160.0936578
910.8914750.2170490.108525
920.8765040.2469910.123496
930.9391720.1216560.0608279
940.9336110.1327770.0663887
950.9339260.1321480.0660742
960.933330.133340.06667
970.9277240.1445520.0722758
980.9337960.1324070.0662036
990.9239460.1521090.0760544
1000.9196080.1607840.0803918
1010.908140.183720.0918602
1020.9013990.1972020.098601
1030.9007540.1984920.0992462
1040.9584020.08319620.0415981
1050.9547320.09053590.0452679
1060.9570010.08599890.0429994
1070.9510520.09789660.0489483
1080.950890.09822080.0491104
1090.9411320.1177350.0588677
1100.9408510.1182980.0591492
1110.9319620.1360760.0680382
1120.9265450.1469110.0734555
1130.9144330.1711330.0855667
1140.9511830.09763320.0488166
1150.9411730.1176550.0588274
1160.9420230.1159550.0579774
1170.9828730.03425390.017127
1180.9884580.0230840.011542
1190.9852880.02942430.0147122
1200.9858270.02834540.0141727
1210.9898590.02028210.0101411
1220.9870010.02599840.0129992
1230.9868820.02623590.0131179
1240.9841260.03174750.0158738
1250.9899760.02004830.0100241
1260.9880990.02380150.0119007
1270.9867460.02650710.0132535
1280.985450.02910010.01455
1290.9889270.02214640.0110732
1300.986750.02649990.01325
1310.9860630.02787480.0139374
1320.9840830.03183460.0159173
1330.9897770.02044610.010223
1340.9871410.02571820.0128591
1350.9840770.03184660.0159233
1360.9817550.03649060.0182453
1370.9781160.04376850.0218842
1380.9759980.04800470.0240023
1390.9732750.05345020.0267251
1400.983350.03330070.0166503
1410.979420.04116070.0205804
1420.9760150.04797070.0239853
1430.9701240.05975270.0298763
1440.9644380.07112340.0355617
1450.9615320.07693680.0384684
1460.956620.08676090.0433805
1470.9717990.05640220.0282011
1480.9667010.06659750.0332988
1490.9604050.07919070.0395953
1500.9615320.0769360.038468
1510.9524910.09501880.0475094
1520.9572170.0855650.0427825
1530.9585260.08294830.0414742
1540.9544860.09102710.0455136
1550.950.09999950.0499998
1560.9436990.1126010.0563005
1570.9314710.1370580.0685288
1580.920490.159020.0795101
1590.9330650.133870.066935
1600.931680.1366390.0683197
1610.9263060.1473870.0736936
1620.9110160.1779690.0889845
1630.9100460.1799080.0899539
1640.9065380.1869240.093462
1650.895690.208620.10431
1660.881520.2369590.11848
1670.8959870.2080270.104013
1680.881280.237440.11872
1690.8728090.2543820.127191
1700.8571470.2857060.142853
1710.8564320.2871350.143568
1720.8438440.3123120.156156
1730.8300480.3399040.169952
1740.801590.3968190.19841
1750.7691850.4616290.230815
1760.7378430.5243140.262157
1770.7770080.4459840.222992
1780.7460330.5079330.253967
1790.7444080.5111850.255592
1800.722520.5549590.27748
1810.7780640.4438720.221936
1820.7764430.4471150.223557
1830.7816620.4366760.218338
1840.7856480.4287040.214352
1850.789380.421240.21062
1860.8034270.3931470.196573
1870.783680.432640.21632
1880.7524830.4950340.247517
1890.765760.468480.23424
1900.7678750.4642510.232125
1910.9094970.1810050.0905025
1920.8953880.2092230.104612
1930.9118290.1763410.0881707
1940.8912810.2174370.108719
1950.8647810.2704380.135219
1960.8471980.3056050.152802
1970.8236110.3527770.176389
1980.8127650.374470.187235
1990.8293110.3413770.170689
2000.8888330.2223350.111167
2010.8618620.2762750.138138
2020.8339380.3321230.166062
2030.7954760.4090490.204524
2040.7530420.4939160.246958
2050.7024330.5951340.297567
2060.6550820.6898350.344918
2070.6437560.7124870.356244
2080.6268750.746250.373125
2090.5633240.8733520.436676
2100.5266290.9467420.473371
2110.6199110.7601790.380089
2120.5636470.8727050.436353
2130.5630870.8738260.436913
2140.9344990.1310010.0655006
2150.905750.18850.0942499
2160.9975180.004963630.00248181
2170.9989190.002161220.00108061
2180.9989860.002028960.00101448
2190.9999150.0001700318.50153e-05
2200.999760.0004790290.000239514
2210.9994840.001032820.00051641
2220.9989520.002095260.00104763
2230.9972780.005443080.00272154
2240.9968420.006316840.00315842
2250.9941480.01170330.00585165
2260.9836390.03272110.0163605
2270.9535120.09297620.0464881

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.817447 & 0.365105 & 0.182553 \tabularnewline
8 & 0.806956 & 0.386088 & 0.193044 \tabularnewline
9 & 0.904997 & 0.190007 & 0.0950034 \tabularnewline
10 & 0.847707 & 0.304586 & 0.152293 \tabularnewline
11 & 0.893761 & 0.212477 & 0.106239 \tabularnewline
12 & 0.845335 & 0.309331 & 0.154665 \tabularnewline
13 & 0.836407 & 0.327185 & 0.163593 \tabularnewline
14 & 0.818729 & 0.362542 & 0.181271 \tabularnewline
15 & 0.772041 & 0.455919 & 0.227959 \tabularnewline
16 & 0.715588 & 0.568824 & 0.284412 \tabularnewline
17 & 0.645808 & 0.708384 & 0.354192 \tabularnewline
18 & 0.571693 & 0.856613 & 0.428307 \tabularnewline
19 & 0.52438 & 0.951241 & 0.47562 \tabularnewline
20 & 0.459563 & 0.919126 & 0.540437 \tabularnewline
21 & 0.415215 & 0.83043 & 0.584785 \tabularnewline
22 & 0.407146 & 0.814293 & 0.592854 \tabularnewline
23 & 0.345925 & 0.691851 & 0.654075 \tabularnewline
24 & 0.309733 & 0.619466 & 0.690267 \tabularnewline
25 & 0.26707 & 0.534141 & 0.73293 \tabularnewline
26 & 0.240179 & 0.480358 & 0.759821 \tabularnewline
27 & 0.210523 & 0.421047 & 0.789477 \tabularnewline
28 & 0.173994 & 0.347989 & 0.826006 \tabularnewline
29 & 0.141809 & 0.283618 & 0.858191 \tabularnewline
30 & 0.125266 & 0.250531 & 0.874734 \tabularnewline
31 & 0.109438 & 0.218877 & 0.890562 \tabularnewline
32 & 0.0908704 & 0.181741 & 0.90913 \tabularnewline
33 & 0.0747453 & 0.149491 & 0.925255 \tabularnewline
34 & 0.0855423 & 0.171085 & 0.914458 \tabularnewline
35 & 0.0733154 & 0.146631 & 0.926685 \tabularnewline
36 & 0.0601363 & 0.120273 & 0.939864 \tabularnewline
37 & 0.0511328 & 0.102266 & 0.948867 \tabularnewline
38 & 0.0463484 & 0.0926968 & 0.953652 \tabularnewline
39 & 0.0459213 & 0.0918425 & 0.954079 \tabularnewline
40 & 0.0374697 & 0.0749394 & 0.96253 \tabularnewline
41 & 0.0515305 & 0.103061 & 0.94847 \tabularnewline
42 & 0.053763 & 0.107526 & 0.946237 \tabularnewline
43 & 0.0418476 & 0.0836952 & 0.958152 \tabularnewline
44 & 0.0484002 & 0.0968003 & 0.9516 \tabularnewline
45 & 0.0538587 & 0.107717 & 0.946141 \tabularnewline
46 & 0.0489796 & 0.0979592 & 0.95102 \tabularnewline
47 & 0.0430217 & 0.0860434 & 0.956978 \tabularnewline
48 & 0.0408312 & 0.0816624 & 0.959169 \tabularnewline
49 & 0.0379826 & 0.0759652 & 0.962017 \tabularnewline
50 & 0.0329182 & 0.0658364 & 0.967082 \tabularnewline
51 & 0.0359092 & 0.0718184 & 0.964091 \tabularnewline
52 & 0.0510638 & 0.102128 & 0.948936 \tabularnewline
53 & 0.0405923 & 0.0811846 & 0.959408 \tabularnewline
54 & 0.032394 & 0.0647879 & 0.967606 \tabularnewline
55 & 0.104434 & 0.208867 & 0.895566 \tabularnewline
56 & 0.0924396 & 0.184879 & 0.90756 \tabularnewline
57 & 0.0753436 & 0.150687 & 0.924656 \tabularnewline
58 & 0.14842 & 0.296841 & 0.85158 \tabularnewline
59 & 0.145007 & 0.290015 & 0.854993 \tabularnewline
60 & 0.140715 & 0.28143 & 0.859285 \tabularnewline
61 & 0.139652 & 0.279304 & 0.860348 \tabularnewline
62 & 0.154979 & 0.309958 & 0.845021 \tabularnewline
63 & 0.154161 & 0.308323 & 0.845839 \tabularnewline
64 & 0.291267 & 0.582534 & 0.708733 \tabularnewline
65 & 0.318975 & 0.63795 & 0.681025 \tabularnewline
66 & 0.518396 & 0.963209 & 0.481604 \tabularnewline
67 & 0.632431 & 0.735137 & 0.367569 \tabularnewline
68 & 0.607119 & 0.785761 & 0.392881 \tabularnewline
69 & 0.674292 & 0.651416 & 0.325708 \tabularnewline
70 & 0.693892 & 0.612217 & 0.306108 \tabularnewline
71 & 0.737479 & 0.525042 & 0.262521 \tabularnewline
72 & 0.728511 & 0.542977 & 0.271489 \tabularnewline
73 & 0.773266 & 0.453468 & 0.226734 \tabularnewline
74 & 0.78749 & 0.425019 & 0.21251 \tabularnewline
75 & 0.852081 & 0.295838 & 0.147919 \tabularnewline
76 & 0.87798 & 0.24404 & 0.12202 \tabularnewline
77 & 0.863865 & 0.272271 & 0.136135 \tabularnewline
78 & 0.868593 & 0.262814 & 0.131407 \tabularnewline
79 & 0.904042 & 0.191916 & 0.0959582 \tabularnewline
80 & 0.914994 & 0.170011 & 0.0850056 \tabularnewline
81 & 0.912623 & 0.174754 & 0.087377 \tabularnewline
82 & 0.923474 & 0.153053 & 0.0765264 \tabularnewline
83 & 0.917061 & 0.165878 & 0.082939 \tabularnewline
84 & 0.910203 & 0.179595 & 0.0897974 \tabularnewline
85 & 0.897447 & 0.205106 & 0.102553 \tabularnewline
86 & 0.881551 & 0.236898 & 0.118449 \tabularnewline
87 & 0.867244 & 0.265513 & 0.132756 \tabularnewline
88 & 0.908543 & 0.182914 & 0.0914572 \tabularnewline
89 & 0.910495 & 0.17901 & 0.0895049 \tabularnewline
90 & 0.906342 & 0.187316 & 0.0936578 \tabularnewline
91 & 0.891475 & 0.217049 & 0.108525 \tabularnewline
92 & 0.876504 & 0.246991 & 0.123496 \tabularnewline
93 & 0.939172 & 0.121656 & 0.0608279 \tabularnewline
94 & 0.933611 & 0.132777 & 0.0663887 \tabularnewline
95 & 0.933926 & 0.132148 & 0.0660742 \tabularnewline
96 & 0.93333 & 0.13334 & 0.06667 \tabularnewline
97 & 0.927724 & 0.144552 & 0.0722758 \tabularnewline
98 & 0.933796 & 0.132407 & 0.0662036 \tabularnewline
99 & 0.923946 & 0.152109 & 0.0760544 \tabularnewline
100 & 0.919608 & 0.160784 & 0.0803918 \tabularnewline
101 & 0.90814 & 0.18372 & 0.0918602 \tabularnewline
102 & 0.901399 & 0.197202 & 0.098601 \tabularnewline
103 & 0.900754 & 0.198492 & 0.0992462 \tabularnewline
104 & 0.958402 & 0.0831962 & 0.0415981 \tabularnewline
105 & 0.954732 & 0.0905359 & 0.0452679 \tabularnewline
106 & 0.957001 & 0.0859989 & 0.0429994 \tabularnewline
107 & 0.951052 & 0.0978966 & 0.0489483 \tabularnewline
108 & 0.95089 & 0.0982208 & 0.0491104 \tabularnewline
109 & 0.941132 & 0.117735 & 0.0588677 \tabularnewline
110 & 0.940851 & 0.118298 & 0.0591492 \tabularnewline
111 & 0.931962 & 0.136076 & 0.0680382 \tabularnewline
112 & 0.926545 & 0.146911 & 0.0734555 \tabularnewline
113 & 0.914433 & 0.171133 & 0.0855667 \tabularnewline
114 & 0.951183 & 0.0976332 & 0.0488166 \tabularnewline
115 & 0.941173 & 0.117655 & 0.0588274 \tabularnewline
116 & 0.942023 & 0.115955 & 0.0579774 \tabularnewline
117 & 0.982873 & 0.0342539 & 0.017127 \tabularnewline
118 & 0.988458 & 0.023084 & 0.011542 \tabularnewline
119 & 0.985288 & 0.0294243 & 0.0147122 \tabularnewline
120 & 0.985827 & 0.0283454 & 0.0141727 \tabularnewline
121 & 0.989859 & 0.0202821 & 0.0101411 \tabularnewline
122 & 0.987001 & 0.0259984 & 0.0129992 \tabularnewline
123 & 0.986882 & 0.0262359 & 0.0131179 \tabularnewline
124 & 0.984126 & 0.0317475 & 0.0158738 \tabularnewline
125 & 0.989976 & 0.0200483 & 0.0100241 \tabularnewline
126 & 0.988099 & 0.0238015 & 0.0119007 \tabularnewline
127 & 0.986746 & 0.0265071 & 0.0132535 \tabularnewline
128 & 0.98545 & 0.0291001 & 0.01455 \tabularnewline
129 & 0.988927 & 0.0221464 & 0.0110732 \tabularnewline
130 & 0.98675 & 0.0264999 & 0.01325 \tabularnewline
131 & 0.986063 & 0.0278748 & 0.0139374 \tabularnewline
132 & 0.984083 & 0.0318346 & 0.0159173 \tabularnewline
133 & 0.989777 & 0.0204461 & 0.010223 \tabularnewline
134 & 0.987141 & 0.0257182 & 0.0128591 \tabularnewline
135 & 0.984077 & 0.0318466 & 0.0159233 \tabularnewline
136 & 0.981755 & 0.0364906 & 0.0182453 \tabularnewline
137 & 0.978116 & 0.0437685 & 0.0218842 \tabularnewline
138 & 0.975998 & 0.0480047 & 0.0240023 \tabularnewline
139 & 0.973275 & 0.0534502 & 0.0267251 \tabularnewline
140 & 0.98335 & 0.0333007 & 0.0166503 \tabularnewline
141 & 0.97942 & 0.0411607 & 0.0205804 \tabularnewline
142 & 0.976015 & 0.0479707 & 0.0239853 \tabularnewline
143 & 0.970124 & 0.0597527 & 0.0298763 \tabularnewline
144 & 0.964438 & 0.0711234 & 0.0355617 \tabularnewline
145 & 0.961532 & 0.0769368 & 0.0384684 \tabularnewline
146 & 0.95662 & 0.0867609 & 0.0433805 \tabularnewline
147 & 0.971799 & 0.0564022 & 0.0282011 \tabularnewline
148 & 0.966701 & 0.0665975 & 0.0332988 \tabularnewline
149 & 0.960405 & 0.0791907 & 0.0395953 \tabularnewline
150 & 0.961532 & 0.076936 & 0.038468 \tabularnewline
151 & 0.952491 & 0.0950188 & 0.0475094 \tabularnewline
152 & 0.957217 & 0.085565 & 0.0427825 \tabularnewline
153 & 0.958526 & 0.0829483 & 0.0414742 \tabularnewline
154 & 0.954486 & 0.0910271 & 0.0455136 \tabularnewline
155 & 0.95 & 0.0999995 & 0.0499998 \tabularnewline
156 & 0.943699 & 0.112601 & 0.0563005 \tabularnewline
157 & 0.931471 & 0.137058 & 0.0685288 \tabularnewline
158 & 0.92049 & 0.15902 & 0.0795101 \tabularnewline
159 & 0.933065 & 0.13387 & 0.066935 \tabularnewline
160 & 0.93168 & 0.136639 & 0.0683197 \tabularnewline
161 & 0.926306 & 0.147387 & 0.0736936 \tabularnewline
162 & 0.911016 & 0.177969 & 0.0889845 \tabularnewline
163 & 0.910046 & 0.179908 & 0.0899539 \tabularnewline
164 & 0.906538 & 0.186924 & 0.093462 \tabularnewline
165 & 0.89569 & 0.20862 & 0.10431 \tabularnewline
166 & 0.88152 & 0.236959 & 0.11848 \tabularnewline
167 & 0.895987 & 0.208027 & 0.104013 \tabularnewline
168 & 0.88128 & 0.23744 & 0.11872 \tabularnewline
169 & 0.872809 & 0.254382 & 0.127191 \tabularnewline
170 & 0.857147 & 0.285706 & 0.142853 \tabularnewline
171 & 0.856432 & 0.287135 & 0.143568 \tabularnewline
172 & 0.843844 & 0.312312 & 0.156156 \tabularnewline
173 & 0.830048 & 0.339904 & 0.169952 \tabularnewline
174 & 0.80159 & 0.396819 & 0.19841 \tabularnewline
175 & 0.769185 & 0.461629 & 0.230815 \tabularnewline
176 & 0.737843 & 0.524314 & 0.262157 \tabularnewline
177 & 0.777008 & 0.445984 & 0.222992 \tabularnewline
178 & 0.746033 & 0.507933 & 0.253967 \tabularnewline
179 & 0.744408 & 0.511185 & 0.255592 \tabularnewline
180 & 0.72252 & 0.554959 & 0.27748 \tabularnewline
181 & 0.778064 & 0.443872 & 0.221936 \tabularnewline
182 & 0.776443 & 0.447115 & 0.223557 \tabularnewline
183 & 0.781662 & 0.436676 & 0.218338 \tabularnewline
184 & 0.785648 & 0.428704 & 0.214352 \tabularnewline
185 & 0.78938 & 0.42124 & 0.21062 \tabularnewline
186 & 0.803427 & 0.393147 & 0.196573 \tabularnewline
187 & 0.78368 & 0.43264 & 0.21632 \tabularnewline
188 & 0.752483 & 0.495034 & 0.247517 \tabularnewline
189 & 0.76576 & 0.46848 & 0.23424 \tabularnewline
190 & 0.767875 & 0.464251 & 0.232125 \tabularnewline
191 & 0.909497 & 0.181005 & 0.0905025 \tabularnewline
192 & 0.895388 & 0.209223 & 0.104612 \tabularnewline
193 & 0.911829 & 0.176341 & 0.0881707 \tabularnewline
194 & 0.891281 & 0.217437 & 0.108719 \tabularnewline
195 & 0.864781 & 0.270438 & 0.135219 \tabularnewline
196 & 0.847198 & 0.305605 & 0.152802 \tabularnewline
197 & 0.823611 & 0.352777 & 0.176389 \tabularnewline
198 & 0.812765 & 0.37447 & 0.187235 \tabularnewline
199 & 0.829311 & 0.341377 & 0.170689 \tabularnewline
200 & 0.888833 & 0.222335 & 0.111167 \tabularnewline
201 & 0.861862 & 0.276275 & 0.138138 \tabularnewline
202 & 0.833938 & 0.332123 & 0.166062 \tabularnewline
203 & 0.795476 & 0.409049 & 0.204524 \tabularnewline
204 & 0.753042 & 0.493916 & 0.246958 \tabularnewline
205 & 0.702433 & 0.595134 & 0.297567 \tabularnewline
206 & 0.655082 & 0.689835 & 0.344918 \tabularnewline
207 & 0.643756 & 0.712487 & 0.356244 \tabularnewline
208 & 0.626875 & 0.74625 & 0.373125 \tabularnewline
209 & 0.563324 & 0.873352 & 0.436676 \tabularnewline
210 & 0.526629 & 0.946742 & 0.473371 \tabularnewline
211 & 0.619911 & 0.760179 & 0.380089 \tabularnewline
212 & 0.563647 & 0.872705 & 0.436353 \tabularnewline
213 & 0.563087 & 0.873826 & 0.436913 \tabularnewline
214 & 0.934499 & 0.131001 & 0.0655006 \tabularnewline
215 & 0.90575 & 0.1885 & 0.0942499 \tabularnewline
216 & 0.997518 & 0.00496363 & 0.00248181 \tabularnewline
217 & 0.998919 & 0.00216122 & 0.00108061 \tabularnewline
218 & 0.998986 & 0.00202896 & 0.00101448 \tabularnewline
219 & 0.999915 & 0.000170031 & 8.50153e-05 \tabularnewline
220 & 0.99976 & 0.000479029 & 0.000239514 \tabularnewline
221 & 0.999484 & 0.00103282 & 0.00051641 \tabularnewline
222 & 0.998952 & 0.00209526 & 0.00104763 \tabularnewline
223 & 0.997278 & 0.00544308 & 0.00272154 \tabularnewline
224 & 0.996842 & 0.00631684 & 0.00315842 \tabularnewline
225 & 0.994148 & 0.0117033 & 0.00585165 \tabularnewline
226 & 0.983639 & 0.0327211 & 0.0163605 \tabularnewline
227 & 0.953512 & 0.0929762 & 0.0464881 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265188&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]7[/C][C]0.817447[/C][C]0.365105[/C][C]0.182553[/C][/ROW]
[ROW][C]8[/C][C]0.806956[/C][C]0.386088[/C][C]0.193044[/C][/ROW]
[ROW][C]9[/C][C]0.904997[/C][C]0.190007[/C][C]0.0950034[/C][/ROW]
[ROW][C]10[/C][C]0.847707[/C][C]0.304586[/C][C]0.152293[/C][/ROW]
[ROW][C]11[/C][C]0.893761[/C][C]0.212477[/C][C]0.106239[/C][/ROW]
[ROW][C]12[/C][C]0.845335[/C][C]0.309331[/C][C]0.154665[/C][/ROW]
[ROW][C]13[/C][C]0.836407[/C][C]0.327185[/C][C]0.163593[/C][/ROW]
[ROW][C]14[/C][C]0.818729[/C][C]0.362542[/C][C]0.181271[/C][/ROW]
[ROW][C]15[/C][C]0.772041[/C][C]0.455919[/C][C]0.227959[/C][/ROW]
[ROW][C]16[/C][C]0.715588[/C][C]0.568824[/C][C]0.284412[/C][/ROW]
[ROW][C]17[/C][C]0.645808[/C][C]0.708384[/C][C]0.354192[/C][/ROW]
[ROW][C]18[/C][C]0.571693[/C][C]0.856613[/C][C]0.428307[/C][/ROW]
[ROW][C]19[/C][C]0.52438[/C][C]0.951241[/C][C]0.47562[/C][/ROW]
[ROW][C]20[/C][C]0.459563[/C][C]0.919126[/C][C]0.540437[/C][/ROW]
[ROW][C]21[/C][C]0.415215[/C][C]0.83043[/C][C]0.584785[/C][/ROW]
[ROW][C]22[/C][C]0.407146[/C][C]0.814293[/C][C]0.592854[/C][/ROW]
[ROW][C]23[/C][C]0.345925[/C][C]0.691851[/C][C]0.654075[/C][/ROW]
[ROW][C]24[/C][C]0.309733[/C][C]0.619466[/C][C]0.690267[/C][/ROW]
[ROW][C]25[/C][C]0.26707[/C][C]0.534141[/C][C]0.73293[/C][/ROW]
[ROW][C]26[/C][C]0.240179[/C][C]0.480358[/C][C]0.759821[/C][/ROW]
[ROW][C]27[/C][C]0.210523[/C][C]0.421047[/C][C]0.789477[/C][/ROW]
[ROW][C]28[/C][C]0.173994[/C][C]0.347989[/C][C]0.826006[/C][/ROW]
[ROW][C]29[/C][C]0.141809[/C][C]0.283618[/C][C]0.858191[/C][/ROW]
[ROW][C]30[/C][C]0.125266[/C][C]0.250531[/C][C]0.874734[/C][/ROW]
[ROW][C]31[/C][C]0.109438[/C][C]0.218877[/C][C]0.890562[/C][/ROW]
[ROW][C]32[/C][C]0.0908704[/C][C]0.181741[/C][C]0.90913[/C][/ROW]
[ROW][C]33[/C][C]0.0747453[/C][C]0.149491[/C][C]0.925255[/C][/ROW]
[ROW][C]34[/C][C]0.0855423[/C][C]0.171085[/C][C]0.914458[/C][/ROW]
[ROW][C]35[/C][C]0.0733154[/C][C]0.146631[/C][C]0.926685[/C][/ROW]
[ROW][C]36[/C][C]0.0601363[/C][C]0.120273[/C][C]0.939864[/C][/ROW]
[ROW][C]37[/C][C]0.0511328[/C][C]0.102266[/C][C]0.948867[/C][/ROW]
[ROW][C]38[/C][C]0.0463484[/C][C]0.0926968[/C][C]0.953652[/C][/ROW]
[ROW][C]39[/C][C]0.0459213[/C][C]0.0918425[/C][C]0.954079[/C][/ROW]
[ROW][C]40[/C][C]0.0374697[/C][C]0.0749394[/C][C]0.96253[/C][/ROW]
[ROW][C]41[/C][C]0.0515305[/C][C]0.103061[/C][C]0.94847[/C][/ROW]
[ROW][C]42[/C][C]0.053763[/C][C]0.107526[/C][C]0.946237[/C][/ROW]
[ROW][C]43[/C][C]0.0418476[/C][C]0.0836952[/C][C]0.958152[/C][/ROW]
[ROW][C]44[/C][C]0.0484002[/C][C]0.0968003[/C][C]0.9516[/C][/ROW]
[ROW][C]45[/C][C]0.0538587[/C][C]0.107717[/C][C]0.946141[/C][/ROW]
[ROW][C]46[/C][C]0.0489796[/C][C]0.0979592[/C][C]0.95102[/C][/ROW]
[ROW][C]47[/C][C]0.0430217[/C][C]0.0860434[/C][C]0.956978[/C][/ROW]
[ROW][C]48[/C][C]0.0408312[/C][C]0.0816624[/C][C]0.959169[/C][/ROW]
[ROW][C]49[/C][C]0.0379826[/C][C]0.0759652[/C][C]0.962017[/C][/ROW]
[ROW][C]50[/C][C]0.0329182[/C][C]0.0658364[/C][C]0.967082[/C][/ROW]
[ROW][C]51[/C][C]0.0359092[/C][C]0.0718184[/C][C]0.964091[/C][/ROW]
[ROW][C]52[/C][C]0.0510638[/C][C]0.102128[/C][C]0.948936[/C][/ROW]
[ROW][C]53[/C][C]0.0405923[/C][C]0.0811846[/C][C]0.959408[/C][/ROW]
[ROW][C]54[/C][C]0.032394[/C][C]0.0647879[/C][C]0.967606[/C][/ROW]
[ROW][C]55[/C][C]0.104434[/C][C]0.208867[/C][C]0.895566[/C][/ROW]
[ROW][C]56[/C][C]0.0924396[/C][C]0.184879[/C][C]0.90756[/C][/ROW]
[ROW][C]57[/C][C]0.0753436[/C][C]0.150687[/C][C]0.924656[/C][/ROW]
[ROW][C]58[/C][C]0.14842[/C][C]0.296841[/C][C]0.85158[/C][/ROW]
[ROW][C]59[/C][C]0.145007[/C][C]0.290015[/C][C]0.854993[/C][/ROW]
[ROW][C]60[/C][C]0.140715[/C][C]0.28143[/C][C]0.859285[/C][/ROW]
[ROW][C]61[/C][C]0.139652[/C][C]0.279304[/C][C]0.860348[/C][/ROW]
[ROW][C]62[/C][C]0.154979[/C][C]0.309958[/C][C]0.845021[/C][/ROW]
[ROW][C]63[/C][C]0.154161[/C][C]0.308323[/C][C]0.845839[/C][/ROW]
[ROW][C]64[/C][C]0.291267[/C][C]0.582534[/C][C]0.708733[/C][/ROW]
[ROW][C]65[/C][C]0.318975[/C][C]0.63795[/C][C]0.681025[/C][/ROW]
[ROW][C]66[/C][C]0.518396[/C][C]0.963209[/C][C]0.481604[/C][/ROW]
[ROW][C]67[/C][C]0.632431[/C][C]0.735137[/C][C]0.367569[/C][/ROW]
[ROW][C]68[/C][C]0.607119[/C][C]0.785761[/C][C]0.392881[/C][/ROW]
[ROW][C]69[/C][C]0.674292[/C][C]0.651416[/C][C]0.325708[/C][/ROW]
[ROW][C]70[/C][C]0.693892[/C][C]0.612217[/C][C]0.306108[/C][/ROW]
[ROW][C]71[/C][C]0.737479[/C][C]0.525042[/C][C]0.262521[/C][/ROW]
[ROW][C]72[/C][C]0.728511[/C][C]0.542977[/C][C]0.271489[/C][/ROW]
[ROW][C]73[/C][C]0.773266[/C][C]0.453468[/C][C]0.226734[/C][/ROW]
[ROW][C]74[/C][C]0.78749[/C][C]0.425019[/C][C]0.21251[/C][/ROW]
[ROW][C]75[/C][C]0.852081[/C][C]0.295838[/C][C]0.147919[/C][/ROW]
[ROW][C]76[/C][C]0.87798[/C][C]0.24404[/C][C]0.12202[/C][/ROW]
[ROW][C]77[/C][C]0.863865[/C][C]0.272271[/C][C]0.136135[/C][/ROW]
[ROW][C]78[/C][C]0.868593[/C][C]0.262814[/C][C]0.131407[/C][/ROW]
[ROW][C]79[/C][C]0.904042[/C][C]0.191916[/C][C]0.0959582[/C][/ROW]
[ROW][C]80[/C][C]0.914994[/C][C]0.170011[/C][C]0.0850056[/C][/ROW]
[ROW][C]81[/C][C]0.912623[/C][C]0.174754[/C][C]0.087377[/C][/ROW]
[ROW][C]82[/C][C]0.923474[/C][C]0.153053[/C][C]0.0765264[/C][/ROW]
[ROW][C]83[/C][C]0.917061[/C][C]0.165878[/C][C]0.082939[/C][/ROW]
[ROW][C]84[/C][C]0.910203[/C][C]0.179595[/C][C]0.0897974[/C][/ROW]
[ROW][C]85[/C][C]0.897447[/C][C]0.205106[/C][C]0.102553[/C][/ROW]
[ROW][C]86[/C][C]0.881551[/C][C]0.236898[/C][C]0.118449[/C][/ROW]
[ROW][C]87[/C][C]0.867244[/C][C]0.265513[/C][C]0.132756[/C][/ROW]
[ROW][C]88[/C][C]0.908543[/C][C]0.182914[/C][C]0.0914572[/C][/ROW]
[ROW][C]89[/C][C]0.910495[/C][C]0.17901[/C][C]0.0895049[/C][/ROW]
[ROW][C]90[/C][C]0.906342[/C][C]0.187316[/C][C]0.0936578[/C][/ROW]
[ROW][C]91[/C][C]0.891475[/C][C]0.217049[/C][C]0.108525[/C][/ROW]
[ROW][C]92[/C][C]0.876504[/C][C]0.246991[/C][C]0.123496[/C][/ROW]
[ROW][C]93[/C][C]0.939172[/C][C]0.121656[/C][C]0.0608279[/C][/ROW]
[ROW][C]94[/C][C]0.933611[/C][C]0.132777[/C][C]0.0663887[/C][/ROW]
[ROW][C]95[/C][C]0.933926[/C][C]0.132148[/C][C]0.0660742[/C][/ROW]
[ROW][C]96[/C][C]0.93333[/C][C]0.13334[/C][C]0.06667[/C][/ROW]
[ROW][C]97[/C][C]0.927724[/C][C]0.144552[/C][C]0.0722758[/C][/ROW]
[ROW][C]98[/C][C]0.933796[/C][C]0.132407[/C][C]0.0662036[/C][/ROW]
[ROW][C]99[/C][C]0.923946[/C][C]0.152109[/C][C]0.0760544[/C][/ROW]
[ROW][C]100[/C][C]0.919608[/C][C]0.160784[/C][C]0.0803918[/C][/ROW]
[ROW][C]101[/C][C]0.90814[/C][C]0.18372[/C][C]0.0918602[/C][/ROW]
[ROW][C]102[/C][C]0.901399[/C][C]0.197202[/C][C]0.098601[/C][/ROW]
[ROW][C]103[/C][C]0.900754[/C][C]0.198492[/C][C]0.0992462[/C][/ROW]
[ROW][C]104[/C][C]0.958402[/C][C]0.0831962[/C][C]0.0415981[/C][/ROW]
[ROW][C]105[/C][C]0.954732[/C][C]0.0905359[/C][C]0.0452679[/C][/ROW]
[ROW][C]106[/C][C]0.957001[/C][C]0.0859989[/C][C]0.0429994[/C][/ROW]
[ROW][C]107[/C][C]0.951052[/C][C]0.0978966[/C][C]0.0489483[/C][/ROW]
[ROW][C]108[/C][C]0.95089[/C][C]0.0982208[/C][C]0.0491104[/C][/ROW]
[ROW][C]109[/C][C]0.941132[/C][C]0.117735[/C][C]0.0588677[/C][/ROW]
[ROW][C]110[/C][C]0.940851[/C][C]0.118298[/C][C]0.0591492[/C][/ROW]
[ROW][C]111[/C][C]0.931962[/C][C]0.136076[/C][C]0.0680382[/C][/ROW]
[ROW][C]112[/C][C]0.926545[/C][C]0.146911[/C][C]0.0734555[/C][/ROW]
[ROW][C]113[/C][C]0.914433[/C][C]0.171133[/C][C]0.0855667[/C][/ROW]
[ROW][C]114[/C][C]0.951183[/C][C]0.0976332[/C][C]0.0488166[/C][/ROW]
[ROW][C]115[/C][C]0.941173[/C][C]0.117655[/C][C]0.0588274[/C][/ROW]
[ROW][C]116[/C][C]0.942023[/C][C]0.115955[/C][C]0.0579774[/C][/ROW]
[ROW][C]117[/C][C]0.982873[/C][C]0.0342539[/C][C]0.017127[/C][/ROW]
[ROW][C]118[/C][C]0.988458[/C][C]0.023084[/C][C]0.011542[/C][/ROW]
[ROW][C]119[/C][C]0.985288[/C][C]0.0294243[/C][C]0.0147122[/C][/ROW]
[ROW][C]120[/C][C]0.985827[/C][C]0.0283454[/C][C]0.0141727[/C][/ROW]
[ROW][C]121[/C][C]0.989859[/C][C]0.0202821[/C][C]0.0101411[/C][/ROW]
[ROW][C]122[/C][C]0.987001[/C][C]0.0259984[/C][C]0.0129992[/C][/ROW]
[ROW][C]123[/C][C]0.986882[/C][C]0.0262359[/C][C]0.0131179[/C][/ROW]
[ROW][C]124[/C][C]0.984126[/C][C]0.0317475[/C][C]0.0158738[/C][/ROW]
[ROW][C]125[/C][C]0.989976[/C][C]0.0200483[/C][C]0.0100241[/C][/ROW]
[ROW][C]126[/C][C]0.988099[/C][C]0.0238015[/C][C]0.0119007[/C][/ROW]
[ROW][C]127[/C][C]0.986746[/C][C]0.0265071[/C][C]0.0132535[/C][/ROW]
[ROW][C]128[/C][C]0.98545[/C][C]0.0291001[/C][C]0.01455[/C][/ROW]
[ROW][C]129[/C][C]0.988927[/C][C]0.0221464[/C][C]0.0110732[/C][/ROW]
[ROW][C]130[/C][C]0.98675[/C][C]0.0264999[/C][C]0.01325[/C][/ROW]
[ROW][C]131[/C][C]0.986063[/C][C]0.0278748[/C][C]0.0139374[/C][/ROW]
[ROW][C]132[/C][C]0.984083[/C][C]0.0318346[/C][C]0.0159173[/C][/ROW]
[ROW][C]133[/C][C]0.989777[/C][C]0.0204461[/C][C]0.010223[/C][/ROW]
[ROW][C]134[/C][C]0.987141[/C][C]0.0257182[/C][C]0.0128591[/C][/ROW]
[ROW][C]135[/C][C]0.984077[/C][C]0.0318466[/C][C]0.0159233[/C][/ROW]
[ROW][C]136[/C][C]0.981755[/C][C]0.0364906[/C][C]0.0182453[/C][/ROW]
[ROW][C]137[/C][C]0.978116[/C][C]0.0437685[/C][C]0.0218842[/C][/ROW]
[ROW][C]138[/C][C]0.975998[/C][C]0.0480047[/C][C]0.0240023[/C][/ROW]
[ROW][C]139[/C][C]0.973275[/C][C]0.0534502[/C][C]0.0267251[/C][/ROW]
[ROW][C]140[/C][C]0.98335[/C][C]0.0333007[/C][C]0.0166503[/C][/ROW]
[ROW][C]141[/C][C]0.97942[/C][C]0.0411607[/C][C]0.0205804[/C][/ROW]
[ROW][C]142[/C][C]0.976015[/C][C]0.0479707[/C][C]0.0239853[/C][/ROW]
[ROW][C]143[/C][C]0.970124[/C][C]0.0597527[/C][C]0.0298763[/C][/ROW]
[ROW][C]144[/C][C]0.964438[/C][C]0.0711234[/C][C]0.0355617[/C][/ROW]
[ROW][C]145[/C][C]0.961532[/C][C]0.0769368[/C][C]0.0384684[/C][/ROW]
[ROW][C]146[/C][C]0.95662[/C][C]0.0867609[/C][C]0.0433805[/C][/ROW]
[ROW][C]147[/C][C]0.971799[/C][C]0.0564022[/C][C]0.0282011[/C][/ROW]
[ROW][C]148[/C][C]0.966701[/C][C]0.0665975[/C][C]0.0332988[/C][/ROW]
[ROW][C]149[/C][C]0.960405[/C][C]0.0791907[/C][C]0.0395953[/C][/ROW]
[ROW][C]150[/C][C]0.961532[/C][C]0.076936[/C][C]0.038468[/C][/ROW]
[ROW][C]151[/C][C]0.952491[/C][C]0.0950188[/C][C]0.0475094[/C][/ROW]
[ROW][C]152[/C][C]0.957217[/C][C]0.085565[/C][C]0.0427825[/C][/ROW]
[ROW][C]153[/C][C]0.958526[/C][C]0.0829483[/C][C]0.0414742[/C][/ROW]
[ROW][C]154[/C][C]0.954486[/C][C]0.0910271[/C][C]0.0455136[/C][/ROW]
[ROW][C]155[/C][C]0.95[/C][C]0.0999995[/C][C]0.0499998[/C][/ROW]
[ROW][C]156[/C][C]0.943699[/C][C]0.112601[/C][C]0.0563005[/C][/ROW]
[ROW][C]157[/C][C]0.931471[/C][C]0.137058[/C][C]0.0685288[/C][/ROW]
[ROW][C]158[/C][C]0.92049[/C][C]0.15902[/C][C]0.0795101[/C][/ROW]
[ROW][C]159[/C][C]0.933065[/C][C]0.13387[/C][C]0.066935[/C][/ROW]
[ROW][C]160[/C][C]0.93168[/C][C]0.136639[/C][C]0.0683197[/C][/ROW]
[ROW][C]161[/C][C]0.926306[/C][C]0.147387[/C][C]0.0736936[/C][/ROW]
[ROW][C]162[/C][C]0.911016[/C][C]0.177969[/C][C]0.0889845[/C][/ROW]
[ROW][C]163[/C][C]0.910046[/C][C]0.179908[/C][C]0.0899539[/C][/ROW]
[ROW][C]164[/C][C]0.906538[/C][C]0.186924[/C][C]0.093462[/C][/ROW]
[ROW][C]165[/C][C]0.89569[/C][C]0.20862[/C][C]0.10431[/C][/ROW]
[ROW][C]166[/C][C]0.88152[/C][C]0.236959[/C][C]0.11848[/C][/ROW]
[ROW][C]167[/C][C]0.895987[/C][C]0.208027[/C][C]0.104013[/C][/ROW]
[ROW][C]168[/C][C]0.88128[/C][C]0.23744[/C][C]0.11872[/C][/ROW]
[ROW][C]169[/C][C]0.872809[/C][C]0.254382[/C][C]0.127191[/C][/ROW]
[ROW][C]170[/C][C]0.857147[/C][C]0.285706[/C][C]0.142853[/C][/ROW]
[ROW][C]171[/C][C]0.856432[/C][C]0.287135[/C][C]0.143568[/C][/ROW]
[ROW][C]172[/C][C]0.843844[/C][C]0.312312[/C][C]0.156156[/C][/ROW]
[ROW][C]173[/C][C]0.830048[/C][C]0.339904[/C][C]0.169952[/C][/ROW]
[ROW][C]174[/C][C]0.80159[/C][C]0.396819[/C][C]0.19841[/C][/ROW]
[ROW][C]175[/C][C]0.769185[/C][C]0.461629[/C][C]0.230815[/C][/ROW]
[ROW][C]176[/C][C]0.737843[/C][C]0.524314[/C][C]0.262157[/C][/ROW]
[ROW][C]177[/C][C]0.777008[/C][C]0.445984[/C][C]0.222992[/C][/ROW]
[ROW][C]178[/C][C]0.746033[/C][C]0.507933[/C][C]0.253967[/C][/ROW]
[ROW][C]179[/C][C]0.744408[/C][C]0.511185[/C][C]0.255592[/C][/ROW]
[ROW][C]180[/C][C]0.72252[/C][C]0.554959[/C][C]0.27748[/C][/ROW]
[ROW][C]181[/C][C]0.778064[/C][C]0.443872[/C][C]0.221936[/C][/ROW]
[ROW][C]182[/C][C]0.776443[/C][C]0.447115[/C][C]0.223557[/C][/ROW]
[ROW][C]183[/C][C]0.781662[/C][C]0.436676[/C][C]0.218338[/C][/ROW]
[ROW][C]184[/C][C]0.785648[/C][C]0.428704[/C][C]0.214352[/C][/ROW]
[ROW][C]185[/C][C]0.78938[/C][C]0.42124[/C][C]0.21062[/C][/ROW]
[ROW][C]186[/C][C]0.803427[/C][C]0.393147[/C][C]0.196573[/C][/ROW]
[ROW][C]187[/C][C]0.78368[/C][C]0.43264[/C][C]0.21632[/C][/ROW]
[ROW][C]188[/C][C]0.752483[/C][C]0.495034[/C][C]0.247517[/C][/ROW]
[ROW][C]189[/C][C]0.76576[/C][C]0.46848[/C][C]0.23424[/C][/ROW]
[ROW][C]190[/C][C]0.767875[/C][C]0.464251[/C][C]0.232125[/C][/ROW]
[ROW][C]191[/C][C]0.909497[/C][C]0.181005[/C][C]0.0905025[/C][/ROW]
[ROW][C]192[/C][C]0.895388[/C][C]0.209223[/C][C]0.104612[/C][/ROW]
[ROW][C]193[/C][C]0.911829[/C][C]0.176341[/C][C]0.0881707[/C][/ROW]
[ROW][C]194[/C][C]0.891281[/C][C]0.217437[/C][C]0.108719[/C][/ROW]
[ROW][C]195[/C][C]0.864781[/C][C]0.270438[/C][C]0.135219[/C][/ROW]
[ROW][C]196[/C][C]0.847198[/C][C]0.305605[/C][C]0.152802[/C][/ROW]
[ROW][C]197[/C][C]0.823611[/C][C]0.352777[/C][C]0.176389[/C][/ROW]
[ROW][C]198[/C][C]0.812765[/C][C]0.37447[/C][C]0.187235[/C][/ROW]
[ROW][C]199[/C][C]0.829311[/C][C]0.341377[/C][C]0.170689[/C][/ROW]
[ROW][C]200[/C][C]0.888833[/C][C]0.222335[/C][C]0.111167[/C][/ROW]
[ROW][C]201[/C][C]0.861862[/C][C]0.276275[/C][C]0.138138[/C][/ROW]
[ROW][C]202[/C][C]0.833938[/C][C]0.332123[/C][C]0.166062[/C][/ROW]
[ROW][C]203[/C][C]0.795476[/C][C]0.409049[/C][C]0.204524[/C][/ROW]
[ROW][C]204[/C][C]0.753042[/C][C]0.493916[/C][C]0.246958[/C][/ROW]
[ROW][C]205[/C][C]0.702433[/C][C]0.595134[/C][C]0.297567[/C][/ROW]
[ROW][C]206[/C][C]0.655082[/C][C]0.689835[/C][C]0.344918[/C][/ROW]
[ROW][C]207[/C][C]0.643756[/C][C]0.712487[/C][C]0.356244[/C][/ROW]
[ROW][C]208[/C][C]0.626875[/C][C]0.74625[/C][C]0.373125[/C][/ROW]
[ROW][C]209[/C][C]0.563324[/C][C]0.873352[/C][C]0.436676[/C][/ROW]
[ROW][C]210[/C][C]0.526629[/C][C]0.946742[/C][C]0.473371[/C][/ROW]
[ROW][C]211[/C][C]0.619911[/C][C]0.760179[/C][C]0.380089[/C][/ROW]
[ROW][C]212[/C][C]0.563647[/C][C]0.872705[/C][C]0.436353[/C][/ROW]
[ROW][C]213[/C][C]0.563087[/C][C]0.873826[/C][C]0.436913[/C][/ROW]
[ROW][C]214[/C][C]0.934499[/C][C]0.131001[/C][C]0.0655006[/C][/ROW]
[ROW][C]215[/C][C]0.90575[/C][C]0.1885[/C][C]0.0942499[/C][/ROW]
[ROW][C]216[/C][C]0.997518[/C][C]0.00496363[/C][C]0.00248181[/C][/ROW]
[ROW][C]217[/C][C]0.998919[/C][C]0.00216122[/C][C]0.00108061[/C][/ROW]
[ROW][C]218[/C][C]0.998986[/C][C]0.00202896[/C][C]0.00101448[/C][/ROW]
[ROW][C]219[/C][C]0.999915[/C][C]0.000170031[/C][C]8.50153e-05[/C][/ROW]
[ROW][C]220[/C][C]0.99976[/C][C]0.000479029[/C][C]0.000239514[/C][/ROW]
[ROW][C]221[/C][C]0.999484[/C][C]0.00103282[/C][C]0.00051641[/C][/ROW]
[ROW][C]222[/C][C]0.998952[/C][C]0.00209526[/C][C]0.00104763[/C][/ROW]
[ROW][C]223[/C][C]0.997278[/C][C]0.00544308[/C][C]0.00272154[/C][/ROW]
[ROW][C]224[/C][C]0.996842[/C][C]0.00631684[/C][C]0.00315842[/C][/ROW]
[ROW][C]225[/C][C]0.994148[/C][C]0.0117033[/C][C]0.00585165[/C][/ROW]
[ROW][C]226[/C][C]0.983639[/C][C]0.0327211[/C][C]0.0163605[/C][/ROW]
[ROW][C]227[/C][C]0.953512[/C][C]0.0929762[/C][C]0.0464881[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265188&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265188&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.8174470.3651050.182553
80.8069560.3860880.193044
90.9049970.1900070.0950034
100.8477070.3045860.152293
110.8937610.2124770.106239
120.8453350.3093310.154665
130.8364070.3271850.163593
140.8187290.3625420.181271
150.7720410.4559190.227959
160.7155880.5688240.284412
170.6458080.7083840.354192
180.5716930.8566130.428307
190.524380.9512410.47562
200.4595630.9191260.540437
210.4152150.830430.584785
220.4071460.8142930.592854
230.3459250.6918510.654075
240.3097330.6194660.690267
250.267070.5341410.73293
260.2401790.4803580.759821
270.2105230.4210470.789477
280.1739940.3479890.826006
290.1418090.2836180.858191
300.1252660.2505310.874734
310.1094380.2188770.890562
320.09087040.1817410.90913
330.07474530.1494910.925255
340.08554230.1710850.914458
350.07331540.1466310.926685
360.06013630.1202730.939864
370.05113280.1022660.948867
380.04634840.09269680.953652
390.04592130.09184250.954079
400.03746970.07493940.96253
410.05153050.1030610.94847
420.0537630.1075260.946237
430.04184760.08369520.958152
440.04840020.09680030.9516
450.05385870.1077170.946141
460.04897960.09795920.95102
470.04302170.08604340.956978
480.04083120.08166240.959169
490.03798260.07596520.962017
500.03291820.06583640.967082
510.03590920.07181840.964091
520.05106380.1021280.948936
530.04059230.08118460.959408
540.0323940.06478790.967606
550.1044340.2088670.895566
560.09243960.1848790.90756
570.07534360.1506870.924656
580.148420.2968410.85158
590.1450070.2900150.854993
600.1407150.281430.859285
610.1396520.2793040.860348
620.1549790.3099580.845021
630.1541610.3083230.845839
640.2912670.5825340.708733
650.3189750.637950.681025
660.5183960.9632090.481604
670.6324310.7351370.367569
680.6071190.7857610.392881
690.6742920.6514160.325708
700.6938920.6122170.306108
710.7374790.5250420.262521
720.7285110.5429770.271489
730.7732660.4534680.226734
740.787490.4250190.21251
750.8520810.2958380.147919
760.877980.244040.12202
770.8638650.2722710.136135
780.8685930.2628140.131407
790.9040420.1919160.0959582
800.9149940.1700110.0850056
810.9126230.1747540.087377
820.9234740.1530530.0765264
830.9170610.1658780.082939
840.9102030.1795950.0897974
850.8974470.2051060.102553
860.8815510.2368980.118449
870.8672440.2655130.132756
880.9085430.1829140.0914572
890.9104950.179010.0895049
900.9063420.1873160.0936578
910.8914750.2170490.108525
920.8765040.2469910.123496
930.9391720.1216560.0608279
940.9336110.1327770.0663887
950.9339260.1321480.0660742
960.933330.133340.06667
970.9277240.1445520.0722758
980.9337960.1324070.0662036
990.9239460.1521090.0760544
1000.9196080.1607840.0803918
1010.908140.183720.0918602
1020.9013990.1972020.098601
1030.9007540.1984920.0992462
1040.9584020.08319620.0415981
1050.9547320.09053590.0452679
1060.9570010.08599890.0429994
1070.9510520.09789660.0489483
1080.950890.09822080.0491104
1090.9411320.1177350.0588677
1100.9408510.1182980.0591492
1110.9319620.1360760.0680382
1120.9265450.1469110.0734555
1130.9144330.1711330.0855667
1140.9511830.09763320.0488166
1150.9411730.1176550.0588274
1160.9420230.1159550.0579774
1170.9828730.03425390.017127
1180.9884580.0230840.011542
1190.9852880.02942430.0147122
1200.9858270.02834540.0141727
1210.9898590.02028210.0101411
1220.9870010.02599840.0129992
1230.9868820.02623590.0131179
1240.9841260.03174750.0158738
1250.9899760.02004830.0100241
1260.9880990.02380150.0119007
1270.9867460.02650710.0132535
1280.985450.02910010.01455
1290.9889270.02214640.0110732
1300.986750.02649990.01325
1310.9860630.02787480.0139374
1320.9840830.03183460.0159173
1330.9897770.02044610.010223
1340.9871410.02571820.0128591
1350.9840770.03184660.0159233
1360.9817550.03649060.0182453
1370.9781160.04376850.0218842
1380.9759980.04800470.0240023
1390.9732750.05345020.0267251
1400.983350.03330070.0166503
1410.979420.04116070.0205804
1420.9760150.04797070.0239853
1430.9701240.05975270.0298763
1440.9644380.07112340.0355617
1450.9615320.07693680.0384684
1460.956620.08676090.0433805
1470.9717990.05640220.0282011
1480.9667010.06659750.0332988
1490.9604050.07919070.0395953
1500.9615320.0769360.038468
1510.9524910.09501880.0475094
1520.9572170.0855650.0427825
1530.9585260.08294830.0414742
1540.9544860.09102710.0455136
1550.950.09999950.0499998
1560.9436990.1126010.0563005
1570.9314710.1370580.0685288
1580.920490.159020.0795101
1590.9330650.133870.066935
1600.931680.1366390.0683197
1610.9263060.1473870.0736936
1620.9110160.1779690.0889845
1630.9100460.1799080.0899539
1640.9065380.1869240.093462
1650.895690.208620.10431
1660.881520.2369590.11848
1670.8959870.2080270.104013
1680.881280.237440.11872
1690.8728090.2543820.127191
1700.8571470.2857060.142853
1710.8564320.2871350.143568
1720.8438440.3123120.156156
1730.8300480.3399040.169952
1740.801590.3968190.19841
1750.7691850.4616290.230815
1760.7378430.5243140.262157
1770.7770080.4459840.222992
1780.7460330.5079330.253967
1790.7444080.5111850.255592
1800.722520.5549590.27748
1810.7780640.4438720.221936
1820.7764430.4471150.223557
1830.7816620.4366760.218338
1840.7856480.4287040.214352
1850.789380.421240.21062
1860.8034270.3931470.196573
1870.783680.432640.21632
1880.7524830.4950340.247517
1890.765760.468480.23424
1900.7678750.4642510.232125
1910.9094970.1810050.0905025
1920.8953880.2092230.104612
1930.9118290.1763410.0881707
1940.8912810.2174370.108719
1950.8647810.2704380.135219
1960.8471980.3056050.152802
1970.8236110.3527770.176389
1980.8127650.374470.187235
1990.8293110.3413770.170689
2000.8888330.2223350.111167
2010.8618620.2762750.138138
2020.8339380.3321230.166062
2030.7954760.4090490.204524
2040.7530420.4939160.246958
2050.7024330.5951340.297567
2060.6550820.6898350.344918
2070.6437560.7124870.356244
2080.6268750.746250.373125
2090.5633240.8733520.436676
2100.5266290.9467420.473371
2110.6199110.7601790.380089
2120.5636470.8727050.436353
2130.5630870.8738260.436913
2140.9344990.1310010.0655006
2150.905750.18850.0942499
2160.9975180.004963630.00248181
2170.9989190.002161220.00108061
2180.9989860.002028960.00101448
2190.9999150.0001700318.50153e-05
2200.999760.0004790290.000239514
2210.9994840.001032820.00051641
2220.9989520.002095260.00104763
2230.9972780.005443080.00272154
2240.9968420.006316840.00315842
2250.9941480.01170330.00585165
2260.9836390.03272110.0163605
2270.9535120.09297620.0464881






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level90.040724NOK
5% type I error level360.162896NOK
10% type I error level700.316742NOK

\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 & 9 & 0.040724 & NOK \tabularnewline
5% type I error level & 36 & 0.162896 & NOK \tabularnewline
10% type I error level & 70 & 0.316742 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265188&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]9[/C][C]0.040724[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]36[/C][C]0.162896[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]70[/C][C]0.316742[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265188&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265188&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 level90.040724NOK
5% type I error level360.162896NOK
10% type I error level700.316742NOK


Figures (Output of Computation)

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Input Parameters & R Code

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