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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 13:48:37 +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/t1418219346f27tmne7jvm85zu.htm/, Retrieved Sun, 19 May 2024 13:54:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265184, Retrieved Sun, 19 May 2024 13:54:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact60

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 13:48:37] [cb9023b84cdbf59fe6647357de544f7b] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 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 & 12 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265184&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]12 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=265184&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265184&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 time12 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.66111 -0.0115614CH[t] + 0.0260742Blogged[t] + 0.0133786LFM[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.66111 -0.0115614CH[t] +  0.0260742Blogged[t] +  0.0133786LFM[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265184&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.66111 -0.0115614CH[t] +  0.0260742Blogged[t] +  0.0133786LFM[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265184&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265184&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] = + 8.66111 -0.0115614CH[t] + 0.0260742Blogged[t] + 0.0133786LFM[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.661110.59130214.659.21835e-354.60918e-35
CH-0.01156140.0121127-0.95450.3408410.17042
Blogged0.02607420.003234948.064.14538e-142.07269e-14
LFM0.01337860.004796012.790.005720970.00286049

\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) & 8.66111 & 0.591302 & 14.65 & 9.21835e-35 & 4.60918e-35 \tabularnewline
CH & -0.0115614 & 0.0121127 & -0.9545 & 0.340841 & 0.17042 \tabularnewline
Blogged & 0.0260742 & 0.00323494 & 8.06 & 4.14538e-14 & 2.07269e-14 \tabularnewline
LFM & 0.0133786 & 0.00479601 & 2.79 & 0.00572097 & 0.00286049 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265184&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]8.66111[/C][C]0.591302[/C][C]14.65[/C][C]9.21835e-35[/C][C]4.60918e-35[/C][/ROW]
[ROW][C]CH[/C][C]-0.0115614[/C][C]0.0121127[/C][C]-0.9545[/C][C]0.340841[/C][C]0.17042[/C][/ROW]
[ROW][C]Blogged[/C][C]0.0260742[/C][C]0.00323494[/C][C]8.06[/C][C]4.14538e-14[/C][C]2.07269e-14[/C][/ROW]
[ROW][C]LFM[/C][C]0.0133786[/C][C]0.00479601[/C][C]2.79[/C][C]0.00572097[/C][C]0.00286049[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265184&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265184&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)8.661110.59130214.659.21835e-354.60918e-35
CH-0.01156140.0121127-0.95450.3408410.17042
Blogged0.02607420.003234948.064.14538e-142.07269e-14
LFM0.01337860.004796012.790.005720970.00286049






Multiple Linear Regression - Regression Statistics
Multiple R0.584
R-squared0.341056
Adjusted R-squared0.332461
F-TEST (value)39.6811
F-TEST (DF numerator)3
F-TEST (DF denominator)230
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.70297
Sum Squared Residuals1680.39

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.584 \tabularnewline
R-squared & 0.341056 \tabularnewline
Adjusted R-squared & 0.332461 \tabularnewline
F-TEST (value) & 39.6811 \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 & 2.70297 \tabularnewline
Sum Squared Residuals & 1680.39 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265184&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.584[/C][/ROW]
[ROW][C]R-squared[/C][C]0.341056[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.332461[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]39.6811[/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]2.70297[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1680.39[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265184&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265184&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 R0.584
R-squared0.341056
Adjusted R-squared0.332461
F-TEST (value)39.6811
F-TEST (DF numerator)3
F-TEST (DF denominator)230
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.70297
Sum Squared Residuals1680.39






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.37150.528523
212.812.56570.234285
37.413.0306-5.63059
46.711.7912-5.09117
512.615.6458-3.04579
614.813.0441.75603
713.312.33060.969378
811.112.7778-1.67781
98.214.5411-6.34105
1011.413.3382-1.93825
116.414.7794-8.37938
121213.7904-1.79043
136.310.0765-3.77649
1411.311.6061-0.306102
1511.914.0421-2.14206
169.312.4446-3.14461
171011.9499-1.9499
1813.812.98560.81439
1910.813.899-3.09903
2011.712.9505-1.25052
2110.915.5286-4.62864
2216.113.28842.81159
239.911.6836-1.78356
2411.512.6589-1.15893
258.312.1247-3.82467
2611.713.713-2.01301
27912.6936-3.69357
2810.812.7092-1.9092
2910.412.2381-1.8381
3012.712.9985-0.298501
3111.814.5293-2.72927
321312.15970.840301
3310.813.0653-2.26526
3412.310.6741.62603
3511.313.7861-2.48607
3611.612.3145-0.714461
3710.913.5797-2.67966
3812.113.1228-1.0228
3913.313.6722-0.372163
4010.113.6152-3.51522
4114.312.56251.73746
429.313.088-3.78798
4312.512.14420.355791
447.611.1658-3.56582
459.212.0255-2.82547
4614.513.30361.19645
4712.313.6931-1.39312
4812.613.2802-0.680172
491313.9532-0.953164
5012.611.5931.00703
5113.214.9329-1.73287
527.711.7594-4.05944
5310.510.9488-0.448819
5410.912.034-1.13397
554.310.5563-6.25633
5610.311.4159-1.11595
5711.411.03650.363495
585.611.5544-5.95443
598.812.2214-3.42144
60910.9497-1.94973
619.611.3604-1.7604
626.410.5105-4.11046
6311.611.25740.342583
644.3510.2336-5.88359
6512.712.61660.0833806
6618.114.98563.11436
6717.8515.29992.5501
6816.615.72830.871725
6912.610.36782.23216
7017.121.917-4.81698
7119.115.52243.5776
7216.118.0263-1.92635
7313.3510.96572.38427
7418.417.60560.79443
7514.711.20263.49735
7610.614.7861-4.18605
7712.613.9537-1.35371
7816.215.26840.931637
7913.617.0858-3.48584
8018.915.56953.33049
8114.112.58561.51442
8214.512.2092.29101
8316.1517.8412-1.69121
8414.7513.64061.10939
8514.814.23240.567594
8612.4512.4813-0.0312596
8712.6514.6584-2.00839
8817.3514.02673.32326
898.612.1377-3.5377
9018.417.58810.811857
9116.117.816-1.71597
9211.611.40490.195053
9317.7512.54355.20652
9415.2513.8231.42699
9517.6516.26391.38606
9615.614.03381.56622
9716.3515.17541.17455
9817.6515.01522.63483
9913.613.16180.438236
10011.712.6373-0.937327
10114.3513.60.749962
10214.7517.703-2.95302
10318.2516.51411.73593
1049.915.46-5.55999
1051614.04721.95278
10618.2515.8252.42498
10716.8517.4791-0.629064
10814.612.67151.92853
10913.8513.8717-0.0216597
11018.9516.30652.64353
11115.614.66450.935455
11214.8517.1519-2.30187
11311.7512.4665-0.71654
11418.4512.97955.47046
11515.917.2921-1.39212
11617.114.3642.73598
11716.110.92515.17492
11819.914.74455.15551
11910.9510.48750.462457
12018.4515.73592.71408
12115.110.88444.21562
1221515.4177-0.417735
12311.3514.0533-2.70326
12415.9515.02390.926086
12518.113.39084.70921
12614.613.03761.56242
12715.416.3218-0.921784
12815.416.3218-0.921784
12917.613.64273.95731
13013.3513.9177-0.567723
13119.116.77032.32972
13215.3513.2842.06596
1337.612.2665-4.66649
13413.413.8016-0.401646
13513.913.6880.211982
13619.117.17391.92611
13715.2513.90141.34862
13812.912.47120.428838
13916.113.87742.22264
14017.3512.51124.83878
14113.1512.5090.641007
14212.1510.22871.92132
14312.612.6622-0.0621942
14410.3511.6287-1.27872
14515.412.86162.53841
1469.611.1592-1.55917
14718.213.37174.82829
14813.612.25611.34387
14914.8514.51190.338095
15014.7517.0102-2.26018
15114.113.91770.182339
15214.911.44643.45355
15316.2512.88333.36666
15419.2517.6291.62098
15513.612.10121.49876
15613.613.57310.026914
15715.6515.27720.37282
15812.7512.50720.242849
15914.611.21973.3803
1609.8513.246-3.39601
16112.6511.24351.40651
16211.912.2581-0.358141
16319.216.44772.75233
16416.614.20322.39684
16511.210.0991.10105
16615.2513.43321.81681
16711.915.0976-3.19764
16813.215.7934-2.59337
16916.3517.1984-0.848395
17012.413.505-1.10501
17115.8513.00892.84107
17214.3513.86830.481719
17318.1515.32872.82128
17411.1511.5281-0.378074
17515.6515.46270.187336
17617.7516.28251.46746
1777.6512.5565-4.90651
17812.3512.19880.151228
17915.611.99593.60413
18019.316.45922.84077
18115.211.89673.30329
18217.113.79433.30566
18315.612.64592.95411
18418.415.02763.37236
18519.0515.35773.69228
18618.5513.57474.97532
18719.116.82.29996
18813.111.97731.12275
18912.8513.5661-0.716073
1909.511.8546-2.35459
1914.511.3661-6.86614
19211.8510.7581.09197
19313.615.8692-2.26923
19411.713.3782-1.67824
19512.411.61270.787337
19613.3514.9271-1.57712
19711.413.8276-2.42761
19814.911.83153.06851
19919.914.74455.15551
20017.7512.31245.43759
20111.211.9126-0.712614
20214.615.4633-0.863347
20317.616.19081.40918
20414.0512.63531.41473
20516.115.4040.696021
20613.3513.4987-0.14868
20711.8512.7718-0.921772
20811.9514.3099-2.35992
20914.7514.64820.101784
21015.1513.14772.0023
21113.214.064-0.863997
21216.8515.34341.50658
2137.8510.3871-2.53714
2147.714.7153-7.01528
21512.611.59231.00767
2167.8511.6748-3.82484
21710.9510.48750.462457
21812.3512.160.189985
2199.9512.5983-2.64829
22014.911.83153.06851
22116.6514.61062.03943
22213.413.04240.357571
22313.9513.48250.467492
22415.711.71653.98345
22516.8512.55094.29905
22610.9510.57760.372404
22715.3512.02563.32443
22812.211.31290.887106
22915.114.06641.03358
23017.7516.29891.45113
23115.212.8922.30804
23214.613.50391.09611
23316.6514.79721.85279
2348.110.9247-2.82466

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.3715 & 0.528523 \tabularnewline
2 & 12.8 & 12.5657 & 0.234285 \tabularnewline
3 & 7.4 & 13.0306 & -5.63059 \tabularnewline
4 & 6.7 & 11.7912 & -5.09117 \tabularnewline
5 & 12.6 & 15.6458 & -3.04579 \tabularnewline
6 & 14.8 & 13.044 & 1.75603 \tabularnewline
7 & 13.3 & 12.3306 & 0.969378 \tabularnewline
8 & 11.1 & 12.7778 & -1.67781 \tabularnewline
9 & 8.2 & 14.5411 & -6.34105 \tabularnewline
10 & 11.4 & 13.3382 & -1.93825 \tabularnewline
11 & 6.4 & 14.7794 & -8.37938 \tabularnewline
12 & 12 & 13.7904 & -1.79043 \tabularnewline
13 & 6.3 & 10.0765 & -3.77649 \tabularnewline
14 & 11.3 & 11.6061 & -0.306102 \tabularnewline
15 & 11.9 & 14.0421 & -2.14206 \tabularnewline
16 & 9.3 & 12.4446 & -3.14461 \tabularnewline
17 & 10 & 11.9499 & -1.9499 \tabularnewline
18 & 13.8 & 12.9856 & 0.81439 \tabularnewline
19 & 10.8 & 13.899 & -3.09903 \tabularnewline
20 & 11.7 & 12.9505 & -1.25052 \tabularnewline
21 & 10.9 & 15.5286 & -4.62864 \tabularnewline
22 & 16.1 & 13.2884 & 2.81159 \tabularnewline
23 & 9.9 & 11.6836 & -1.78356 \tabularnewline
24 & 11.5 & 12.6589 & -1.15893 \tabularnewline
25 & 8.3 & 12.1247 & -3.82467 \tabularnewline
26 & 11.7 & 13.713 & -2.01301 \tabularnewline
27 & 9 & 12.6936 & -3.69357 \tabularnewline
28 & 10.8 & 12.7092 & -1.9092 \tabularnewline
29 & 10.4 & 12.2381 & -1.8381 \tabularnewline
30 & 12.7 & 12.9985 & -0.298501 \tabularnewline
31 & 11.8 & 14.5293 & -2.72927 \tabularnewline
32 & 13 & 12.1597 & 0.840301 \tabularnewline
33 & 10.8 & 13.0653 & -2.26526 \tabularnewline
34 & 12.3 & 10.674 & 1.62603 \tabularnewline
35 & 11.3 & 13.7861 & -2.48607 \tabularnewline
36 & 11.6 & 12.3145 & -0.714461 \tabularnewline
37 & 10.9 & 13.5797 & -2.67966 \tabularnewline
38 & 12.1 & 13.1228 & -1.0228 \tabularnewline
39 & 13.3 & 13.6722 & -0.372163 \tabularnewline
40 & 10.1 & 13.6152 & -3.51522 \tabularnewline
41 & 14.3 & 12.5625 & 1.73746 \tabularnewline
42 & 9.3 & 13.088 & -3.78798 \tabularnewline
43 & 12.5 & 12.1442 & 0.355791 \tabularnewline
44 & 7.6 & 11.1658 & -3.56582 \tabularnewline
45 & 9.2 & 12.0255 & -2.82547 \tabularnewline
46 & 14.5 & 13.3036 & 1.19645 \tabularnewline
47 & 12.3 & 13.6931 & -1.39312 \tabularnewline
48 & 12.6 & 13.2802 & -0.680172 \tabularnewline
49 & 13 & 13.9532 & -0.953164 \tabularnewline
50 & 12.6 & 11.593 & 1.00703 \tabularnewline
51 & 13.2 & 14.9329 & -1.73287 \tabularnewline
52 & 7.7 & 11.7594 & -4.05944 \tabularnewline
53 & 10.5 & 10.9488 & -0.448819 \tabularnewline
54 & 10.9 & 12.034 & -1.13397 \tabularnewline
55 & 4.3 & 10.5563 & -6.25633 \tabularnewline
56 & 10.3 & 11.4159 & -1.11595 \tabularnewline
57 & 11.4 & 11.0365 & 0.363495 \tabularnewline
58 & 5.6 & 11.5544 & -5.95443 \tabularnewline
59 & 8.8 & 12.2214 & -3.42144 \tabularnewline
60 & 9 & 10.9497 & -1.94973 \tabularnewline
61 & 9.6 & 11.3604 & -1.7604 \tabularnewline
62 & 6.4 & 10.5105 & -4.11046 \tabularnewline
63 & 11.6 & 11.2574 & 0.342583 \tabularnewline
64 & 4.35 & 10.2336 & -5.88359 \tabularnewline
65 & 12.7 & 12.6166 & 0.0833806 \tabularnewline
66 & 18.1 & 14.9856 & 3.11436 \tabularnewline
67 & 17.85 & 15.2999 & 2.5501 \tabularnewline
68 & 16.6 & 15.7283 & 0.871725 \tabularnewline
69 & 12.6 & 10.3678 & 2.23216 \tabularnewline
70 & 17.1 & 21.917 & -4.81698 \tabularnewline
71 & 19.1 & 15.5224 & 3.5776 \tabularnewline
72 & 16.1 & 18.0263 & -1.92635 \tabularnewline
73 & 13.35 & 10.9657 & 2.38427 \tabularnewline
74 & 18.4 & 17.6056 & 0.79443 \tabularnewline
75 & 14.7 & 11.2026 & 3.49735 \tabularnewline
76 & 10.6 & 14.7861 & -4.18605 \tabularnewline
77 & 12.6 & 13.9537 & -1.35371 \tabularnewline
78 & 16.2 & 15.2684 & 0.931637 \tabularnewline
79 & 13.6 & 17.0858 & -3.48584 \tabularnewline
80 & 18.9 & 15.5695 & 3.33049 \tabularnewline
81 & 14.1 & 12.5856 & 1.51442 \tabularnewline
82 & 14.5 & 12.209 & 2.29101 \tabularnewline
83 & 16.15 & 17.8412 & -1.69121 \tabularnewline
84 & 14.75 & 13.6406 & 1.10939 \tabularnewline
85 & 14.8 & 14.2324 & 0.567594 \tabularnewline
86 & 12.45 & 12.4813 & -0.0312596 \tabularnewline
87 & 12.65 & 14.6584 & -2.00839 \tabularnewline
88 & 17.35 & 14.0267 & 3.32326 \tabularnewline
89 & 8.6 & 12.1377 & -3.5377 \tabularnewline
90 & 18.4 & 17.5881 & 0.811857 \tabularnewline
91 & 16.1 & 17.816 & -1.71597 \tabularnewline
92 & 11.6 & 11.4049 & 0.195053 \tabularnewline
93 & 17.75 & 12.5435 & 5.20652 \tabularnewline
94 & 15.25 & 13.823 & 1.42699 \tabularnewline
95 & 17.65 & 16.2639 & 1.38606 \tabularnewline
96 & 15.6 & 14.0338 & 1.56622 \tabularnewline
97 & 16.35 & 15.1754 & 1.17455 \tabularnewline
98 & 17.65 & 15.0152 & 2.63483 \tabularnewline
99 & 13.6 & 13.1618 & 0.438236 \tabularnewline
100 & 11.7 & 12.6373 & -0.937327 \tabularnewline
101 & 14.35 & 13.6 & 0.749962 \tabularnewline
102 & 14.75 & 17.703 & -2.95302 \tabularnewline
103 & 18.25 & 16.5141 & 1.73593 \tabularnewline
104 & 9.9 & 15.46 & -5.55999 \tabularnewline
105 & 16 & 14.0472 & 1.95278 \tabularnewline
106 & 18.25 & 15.825 & 2.42498 \tabularnewline
107 & 16.85 & 17.4791 & -0.629064 \tabularnewline
108 & 14.6 & 12.6715 & 1.92853 \tabularnewline
109 & 13.85 & 13.8717 & -0.0216597 \tabularnewline
110 & 18.95 & 16.3065 & 2.64353 \tabularnewline
111 & 15.6 & 14.6645 & 0.935455 \tabularnewline
112 & 14.85 & 17.1519 & -2.30187 \tabularnewline
113 & 11.75 & 12.4665 & -0.71654 \tabularnewline
114 & 18.45 & 12.9795 & 5.47046 \tabularnewline
115 & 15.9 & 17.2921 & -1.39212 \tabularnewline
116 & 17.1 & 14.364 & 2.73598 \tabularnewline
117 & 16.1 & 10.9251 & 5.17492 \tabularnewline
118 & 19.9 & 14.7445 & 5.15551 \tabularnewline
119 & 10.95 & 10.4875 & 0.462457 \tabularnewline
120 & 18.45 & 15.7359 & 2.71408 \tabularnewline
121 & 15.1 & 10.8844 & 4.21562 \tabularnewline
122 & 15 & 15.4177 & -0.417735 \tabularnewline
123 & 11.35 & 14.0533 & -2.70326 \tabularnewline
124 & 15.95 & 15.0239 & 0.926086 \tabularnewline
125 & 18.1 & 13.3908 & 4.70921 \tabularnewline
126 & 14.6 & 13.0376 & 1.56242 \tabularnewline
127 & 15.4 & 16.3218 & -0.921784 \tabularnewline
128 & 15.4 & 16.3218 & -0.921784 \tabularnewline
129 & 17.6 & 13.6427 & 3.95731 \tabularnewline
130 & 13.35 & 13.9177 & -0.567723 \tabularnewline
131 & 19.1 & 16.7703 & 2.32972 \tabularnewline
132 & 15.35 & 13.284 & 2.06596 \tabularnewline
133 & 7.6 & 12.2665 & -4.66649 \tabularnewline
134 & 13.4 & 13.8016 & -0.401646 \tabularnewline
135 & 13.9 & 13.688 & 0.211982 \tabularnewline
136 & 19.1 & 17.1739 & 1.92611 \tabularnewline
137 & 15.25 & 13.9014 & 1.34862 \tabularnewline
138 & 12.9 & 12.4712 & 0.428838 \tabularnewline
139 & 16.1 & 13.8774 & 2.22264 \tabularnewline
140 & 17.35 & 12.5112 & 4.83878 \tabularnewline
141 & 13.15 & 12.509 & 0.641007 \tabularnewline
142 & 12.15 & 10.2287 & 1.92132 \tabularnewline
143 & 12.6 & 12.6622 & -0.0621942 \tabularnewline
144 & 10.35 & 11.6287 & -1.27872 \tabularnewline
145 & 15.4 & 12.8616 & 2.53841 \tabularnewline
146 & 9.6 & 11.1592 & -1.55917 \tabularnewline
147 & 18.2 & 13.3717 & 4.82829 \tabularnewline
148 & 13.6 & 12.2561 & 1.34387 \tabularnewline
149 & 14.85 & 14.5119 & 0.338095 \tabularnewline
150 & 14.75 & 17.0102 & -2.26018 \tabularnewline
151 & 14.1 & 13.9177 & 0.182339 \tabularnewline
152 & 14.9 & 11.4464 & 3.45355 \tabularnewline
153 & 16.25 & 12.8833 & 3.36666 \tabularnewline
154 & 19.25 & 17.629 & 1.62098 \tabularnewline
155 & 13.6 & 12.1012 & 1.49876 \tabularnewline
156 & 13.6 & 13.5731 & 0.026914 \tabularnewline
157 & 15.65 & 15.2772 & 0.37282 \tabularnewline
158 & 12.75 & 12.5072 & 0.242849 \tabularnewline
159 & 14.6 & 11.2197 & 3.3803 \tabularnewline
160 & 9.85 & 13.246 & -3.39601 \tabularnewline
161 & 12.65 & 11.2435 & 1.40651 \tabularnewline
162 & 11.9 & 12.2581 & -0.358141 \tabularnewline
163 & 19.2 & 16.4477 & 2.75233 \tabularnewline
164 & 16.6 & 14.2032 & 2.39684 \tabularnewline
165 & 11.2 & 10.099 & 1.10105 \tabularnewline
166 & 15.25 & 13.4332 & 1.81681 \tabularnewline
167 & 11.9 & 15.0976 & -3.19764 \tabularnewline
168 & 13.2 & 15.7934 & -2.59337 \tabularnewline
169 & 16.35 & 17.1984 & -0.848395 \tabularnewline
170 & 12.4 & 13.505 & -1.10501 \tabularnewline
171 & 15.85 & 13.0089 & 2.84107 \tabularnewline
172 & 14.35 & 13.8683 & 0.481719 \tabularnewline
173 & 18.15 & 15.3287 & 2.82128 \tabularnewline
174 & 11.15 & 11.5281 & -0.378074 \tabularnewline
175 & 15.65 & 15.4627 & 0.187336 \tabularnewline
176 & 17.75 & 16.2825 & 1.46746 \tabularnewline
177 & 7.65 & 12.5565 & -4.90651 \tabularnewline
178 & 12.35 & 12.1988 & 0.151228 \tabularnewline
179 & 15.6 & 11.9959 & 3.60413 \tabularnewline
180 & 19.3 & 16.4592 & 2.84077 \tabularnewline
181 & 15.2 & 11.8967 & 3.30329 \tabularnewline
182 & 17.1 & 13.7943 & 3.30566 \tabularnewline
183 & 15.6 & 12.6459 & 2.95411 \tabularnewline
184 & 18.4 & 15.0276 & 3.37236 \tabularnewline
185 & 19.05 & 15.3577 & 3.69228 \tabularnewline
186 & 18.55 & 13.5747 & 4.97532 \tabularnewline
187 & 19.1 & 16.8 & 2.29996 \tabularnewline
188 & 13.1 & 11.9773 & 1.12275 \tabularnewline
189 & 12.85 & 13.5661 & -0.716073 \tabularnewline
190 & 9.5 & 11.8546 & -2.35459 \tabularnewline
191 & 4.5 & 11.3661 & -6.86614 \tabularnewline
192 & 11.85 & 10.758 & 1.09197 \tabularnewline
193 & 13.6 & 15.8692 & -2.26923 \tabularnewline
194 & 11.7 & 13.3782 & -1.67824 \tabularnewline
195 & 12.4 & 11.6127 & 0.787337 \tabularnewline
196 & 13.35 & 14.9271 & -1.57712 \tabularnewline
197 & 11.4 & 13.8276 & -2.42761 \tabularnewline
198 & 14.9 & 11.8315 & 3.06851 \tabularnewline
199 & 19.9 & 14.7445 & 5.15551 \tabularnewline
200 & 17.75 & 12.3124 & 5.43759 \tabularnewline
201 & 11.2 & 11.9126 & -0.712614 \tabularnewline
202 & 14.6 & 15.4633 & -0.863347 \tabularnewline
203 & 17.6 & 16.1908 & 1.40918 \tabularnewline
204 & 14.05 & 12.6353 & 1.41473 \tabularnewline
205 & 16.1 & 15.404 & 0.696021 \tabularnewline
206 & 13.35 & 13.4987 & -0.14868 \tabularnewline
207 & 11.85 & 12.7718 & -0.921772 \tabularnewline
208 & 11.95 & 14.3099 & -2.35992 \tabularnewline
209 & 14.75 & 14.6482 & 0.101784 \tabularnewline
210 & 15.15 & 13.1477 & 2.0023 \tabularnewline
211 & 13.2 & 14.064 & -0.863997 \tabularnewline
212 & 16.85 & 15.3434 & 1.50658 \tabularnewline
213 & 7.85 & 10.3871 & -2.53714 \tabularnewline
214 & 7.7 & 14.7153 & -7.01528 \tabularnewline
215 & 12.6 & 11.5923 & 1.00767 \tabularnewline
216 & 7.85 & 11.6748 & -3.82484 \tabularnewline
217 & 10.95 & 10.4875 & 0.462457 \tabularnewline
218 & 12.35 & 12.16 & 0.189985 \tabularnewline
219 & 9.95 & 12.5983 & -2.64829 \tabularnewline
220 & 14.9 & 11.8315 & 3.06851 \tabularnewline
221 & 16.65 & 14.6106 & 2.03943 \tabularnewline
222 & 13.4 & 13.0424 & 0.357571 \tabularnewline
223 & 13.95 & 13.4825 & 0.467492 \tabularnewline
224 & 15.7 & 11.7165 & 3.98345 \tabularnewline
225 & 16.85 & 12.5509 & 4.29905 \tabularnewline
226 & 10.95 & 10.5776 & 0.372404 \tabularnewline
227 & 15.35 & 12.0256 & 3.32443 \tabularnewline
228 & 12.2 & 11.3129 & 0.887106 \tabularnewline
229 & 15.1 & 14.0664 & 1.03358 \tabularnewline
230 & 17.75 & 16.2989 & 1.45113 \tabularnewline
231 & 15.2 & 12.892 & 2.30804 \tabularnewline
232 & 14.6 & 13.5039 & 1.09611 \tabularnewline
233 & 16.65 & 14.7972 & 1.85279 \tabularnewline
234 & 8.1 & 10.9247 & -2.82466 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265184&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]12.3715[/C][C]0.528523[/C][/ROW]
[ROW][C]2[/C][C]12.8[/C][C]12.5657[/C][C]0.234285[/C][/ROW]
[ROW][C]3[/C][C]7.4[/C][C]13.0306[/C][C]-5.63059[/C][/ROW]
[ROW][C]4[/C][C]6.7[/C][C]11.7912[/C][C]-5.09117[/C][/ROW]
[ROW][C]5[/C][C]12.6[/C][C]15.6458[/C][C]-3.04579[/C][/ROW]
[ROW][C]6[/C][C]14.8[/C][C]13.044[/C][C]1.75603[/C][/ROW]
[ROW][C]7[/C][C]13.3[/C][C]12.3306[/C][C]0.969378[/C][/ROW]
[ROW][C]8[/C][C]11.1[/C][C]12.7778[/C][C]-1.67781[/C][/ROW]
[ROW][C]9[/C][C]8.2[/C][C]14.5411[/C][C]-6.34105[/C][/ROW]
[ROW][C]10[/C][C]11.4[/C][C]13.3382[/C][C]-1.93825[/C][/ROW]
[ROW][C]11[/C][C]6.4[/C][C]14.7794[/C][C]-8.37938[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]13.7904[/C][C]-1.79043[/C][/ROW]
[ROW][C]13[/C][C]6.3[/C][C]10.0765[/C][C]-3.77649[/C][/ROW]
[ROW][C]14[/C][C]11.3[/C][C]11.6061[/C][C]-0.306102[/C][/ROW]
[ROW][C]15[/C][C]11.9[/C][C]14.0421[/C][C]-2.14206[/C][/ROW]
[ROW][C]16[/C][C]9.3[/C][C]12.4446[/C][C]-3.14461[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]11.9499[/C][C]-1.9499[/C][/ROW]
[ROW][C]18[/C][C]13.8[/C][C]12.9856[/C][C]0.81439[/C][/ROW]
[ROW][C]19[/C][C]10.8[/C][C]13.899[/C][C]-3.09903[/C][/ROW]
[ROW][C]20[/C][C]11.7[/C][C]12.9505[/C][C]-1.25052[/C][/ROW]
[ROW][C]21[/C][C]10.9[/C][C]15.5286[/C][C]-4.62864[/C][/ROW]
[ROW][C]22[/C][C]16.1[/C][C]13.2884[/C][C]2.81159[/C][/ROW]
[ROW][C]23[/C][C]9.9[/C][C]11.6836[/C][C]-1.78356[/C][/ROW]
[ROW][C]24[/C][C]11.5[/C][C]12.6589[/C][C]-1.15893[/C][/ROW]
[ROW][C]25[/C][C]8.3[/C][C]12.1247[/C][C]-3.82467[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]13.713[/C][C]-2.01301[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]12.6936[/C][C]-3.69357[/C][/ROW]
[ROW][C]28[/C][C]10.8[/C][C]12.7092[/C][C]-1.9092[/C][/ROW]
[ROW][C]29[/C][C]10.4[/C][C]12.2381[/C][C]-1.8381[/C][/ROW]
[ROW][C]30[/C][C]12.7[/C][C]12.9985[/C][C]-0.298501[/C][/ROW]
[ROW][C]31[/C][C]11.8[/C][C]14.5293[/C][C]-2.72927[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.1597[/C][C]0.840301[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]13.0653[/C][C]-2.26526[/C][/ROW]
[ROW][C]34[/C][C]12.3[/C][C]10.674[/C][C]1.62603[/C][/ROW]
[ROW][C]35[/C][C]11.3[/C][C]13.7861[/C][C]-2.48607[/C][/ROW]
[ROW][C]36[/C][C]11.6[/C][C]12.3145[/C][C]-0.714461[/C][/ROW]
[ROW][C]37[/C][C]10.9[/C][C]13.5797[/C][C]-2.67966[/C][/ROW]
[ROW][C]38[/C][C]12.1[/C][C]13.1228[/C][C]-1.0228[/C][/ROW]
[ROW][C]39[/C][C]13.3[/C][C]13.6722[/C][C]-0.372163[/C][/ROW]
[ROW][C]40[/C][C]10.1[/C][C]13.6152[/C][C]-3.51522[/C][/ROW]
[ROW][C]41[/C][C]14.3[/C][C]12.5625[/C][C]1.73746[/C][/ROW]
[ROW][C]42[/C][C]9.3[/C][C]13.088[/C][C]-3.78798[/C][/ROW]
[ROW][C]43[/C][C]12.5[/C][C]12.1442[/C][C]0.355791[/C][/ROW]
[ROW][C]44[/C][C]7.6[/C][C]11.1658[/C][C]-3.56582[/C][/ROW]
[ROW][C]45[/C][C]9.2[/C][C]12.0255[/C][C]-2.82547[/C][/ROW]
[ROW][C]46[/C][C]14.5[/C][C]13.3036[/C][C]1.19645[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]13.6931[/C][C]-1.39312[/C][/ROW]
[ROW][C]48[/C][C]12.6[/C][C]13.2802[/C][C]-0.680172[/C][/ROW]
[ROW][C]49[/C][C]13[/C][C]13.9532[/C][C]-0.953164[/C][/ROW]
[ROW][C]50[/C][C]12.6[/C][C]11.593[/C][C]1.00703[/C][/ROW]
[ROW][C]51[/C][C]13.2[/C][C]14.9329[/C][C]-1.73287[/C][/ROW]
[ROW][C]52[/C][C]7.7[/C][C]11.7594[/C][C]-4.05944[/C][/ROW]
[ROW][C]53[/C][C]10.5[/C][C]10.9488[/C][C]-0.448819[/C][/ROW]
[ROW][C]54[/C][C]10.9[/C][C]12.034[/C][C]-1.13397[/C][/ROW]
[ROW][C]55[/C][C]4.3[/C][C]10.5563[/C][C]-6.25633[/C][/ROW]
[ROW][C]56[/C][C]10.3[/C][C]11.4159[/C][C]-1.11595[/C][/ROW]
[ROW][C]57[/C][C]11.4[/C][C]11.0365[/C][C]0.363495[/C][/ROW]
[ROW][C]58[/C][C]5.6[/C][C]11.5544[/C][C]-5.95443[/C][/ROW]
[ROW][C]59[/C][C]8.8[/C][C]12.2214[/C][C]-3.42144[/C][/ROW]
[ROW][C]60[/C][C]9[/C][C]10.9497[/C][C]-1.94973[/C][/ROW]
[ROW][C]61[/C][C]9.6[/C][C]11.3604[/C][C]-1.7604[/C][/ROW]
[ROW][C]62[/C][C]6.4[/C][C]10.5105[/C][C]-4.11046[/C][/ROW]
[ROW][C]63[/C][C]11.6[/C][C]11.2574[/C][C]0.342583[/C][/ROW]
[ROW][C]64[/C][C]4.35[/C][C]10.2336[/C][C]-5.88359[/C][/ROW]
[ROW][C]65[/C][C]12.7[/C][C]12.6166[/C][C]0.0833806[/C][/ROW]
[ROW][C]66[/C][C]18.1[/C][C]14.9856[/C][C]3.11436[/C][/ROW]
[ROW][C]67[/C][C]17.85[/C][C]15.2999[/C][C]2.5501[/C][/ROW]
[ROW][C]68[/C][C]16.6[/C][C]15.7283[/C][C]0.871725[/C][/ROW]
[ROW][C]69[/C][C]12.6[/C][C]10.3678[/C][C]2.23216[/C][/ROW]
[ROW][C]70[/C][C]17.1[/C][C]21.917[/C][C]-4.81698[/C][/ROW]
[ROW][C]71[/C][C]19.1[/C][C]15.5224[/C][C]3.5776[/C][/ROW]
[ROW][C]72[/C][C]16.1[/C][C]18.0263[/C][C]-1.92635[/C][/ROW]
[ROW][C]73[/C][C]13.35[/C][C]10.9657[/C][C]2.38427[/C][/ROW]
[ROW][C]74[/C][C]18.4[/C][C]17.6056[/C][C]0.79443[/C][/ROW]
[ROW][C]75[/C][C]14.7[/C][C]11.2026[/C][C]3.49735[/C][/ROW]
[ROW][C]76[/C][C]10.6[/C][C]14.7861[/C][C]-4.18605[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]13.9537[/C][C]-1.35371[/C][/ROW]
[ROW][C]78[/C][C]16.2[/C][C]15.2684[/C][C]0.931637[/C][/ROW]
[ROW][C]79[/C][C]13.6[/C][C]17.0858[/C][C]-3.48584[/C][/ROW]
[ROW][C]80[/C][C]18.9[/C][C]15.5695[/C][C]3.33049[/C][/ROW]
[ROW][C]81[/C][C]14.1[/C][C]12.5856[/C][C]1.51442[/C][/ROW]
[ROW][C]82[/C][C]14.5[/C][C]12.209[/C][C]2.29101[/C][/ROW]
[ROW][C]83[/C][C]16.15[/C][C]17.8412[/C][C]-1.69121[/C][/ROW]
[ROW][C]84[/C][C]14.75[/C][C]13.6406[/C][C]1.10939[/C][/ROW]
[ROW][C]85[/C][C]14.8[/C][C]14.2324[/C][C]0.567594[/C][/ROW]
[ROW][C]86[/C][C]12.45[/C][C]12.4813[/C][C]-0.0312596[/C][/ROW]
[ROW][C]87[/C][C]12.65[/C][C]14.6584[/C][C]-2.00839[/C][/ROW]
[ROW][C]88[/C][C]17.35[/C][C]14.0267[/C][C]3.32326[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]12.1377[/C][C]-3.5377[/C][/ROW]
[ROW][C]90[/C][C]18.4[/C][C]17.5881[/C][C]0.811857[/C][/ROW]
[ROW][C]91[/C][C]16.1[/C][C]17.816[/C][C]-1.71597[/C][/ROW]
[ROW][C]92[/C][C]11.6[/C][C]11.4049[/C][C]0.195053[/C][/ROW]
[ROW][C]93[/C][C]17.75[/C][C]12.5435[/C][C]5.20652[/C][/ROW]
[ROW][C]94[/C][C]15.25[/C][C]13.823[/C][C]1.42699[/C][/ROW]
[ROW][C]95[/C][C]17.65[/C][C]16.2639[/C][C]1.38606[/C][/ROW]
[ROW][C]96[/C][C]15.6[/C][C]14.0338[/C][C]1.56622[/C][/ROW]
[ROW][C]97[/C][C]16.35[/C][C]15.1754[/C][C]1.17455[/C][/ROW]
[ROW][C]98[/C][C]17.65[/C][C]15.0152[/C][C]2.63483[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]13.1618[/C][C]0.438236[/C][/ROW]
[ROW][C]100[/C][C]11.7[/C][C]12.6373[/C][C]-0.937327[/C][/ROW]
[ROW][C]101[/C][C]14.35[/C][C]13.6[/C][C]0.749962[/C][/ROW]
[ROW][C]102[/C][C]14.75[/C][C]17.703[/C][C]-2.95302[/C][/ROW]
[ROW][C]103[/C][C]18.25[/C][C]16.5141[/C][C]1.73593[/C][/ROW]
[ROW][C]104[/C][C]9.9[/C][C]15.46[/C][C]-5.55999[/C][/ROW]
[ROW][C]105[/C][C]16[/C][C]14.0472[/C][C]1.95278[/C][/ROW]
[ROW][C]106[/C][C]18.25[/C][C]15.825[/C][C]2.42498[/C][/ROW]
[ROW][C]107[/C][C]16.85[/C][C]17.4791[/C][C]-0.629064[/C][/ROW]
[ROW][C]108[/C][C]14.6[/C][C]12.6715[/C][C]1.92853[/C][/ROW]
[ROW][C]109[/C][C]13.85[/C][C]13.8717[/C][C]-0.0216597[/C][/ROW]
[ROW][C]110[/C][C]18.95[/C][C]16.3065[/C][C]2.64353[/C][/ROW]
[ROW][C]111[/C][C]15.6[/C][C]14.6645[/C][C]0.935455[/C][/ROW]
[ROW][C]112[/C][C]14.85[/C][C]17.1519[/C][C]-2.30187[/C][/ROW]
[ROW][C]113[/C][C]11.75[/C][C]12.4665[/C][C]-0.71654[/C][/ROW]
[ROW][C]114[/C][C]18.45[/C][C]12.9795[/C][C]5.47046[/C][/ROW]
[ROW][C]115[/C][C]15.9[/C][C]17.2921[/C][C]-1.39212[/C][/ROW]
[ROW][C]116[/C][C]17.1[/C][C]14.364[/C][C]2.73598[/C][/ROW]
[ROW][C]117[/C][C]16.1[/C][C]10.9251[/C][C]5.17492[/C][/ROW]
[ROW][C]118[/C][C]19.9[/C][C]14.7445[/C][C]5.15551[/C][/ROW]
[ROW][C]119[/C][C]10.95[/C][C]10.4875[/C][C]0.462457[/C][/ROW]
[ROW][C]120[/C][C]18.45[/C][C]15.7359[/C][C]2.71408[/C][/ROW]
[ROW][C]121[/C][C]15.1[/C][C]10.8844[/C][C]4.21562[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]15.4177[/C][C]-0.417735[/C][/ROW]
[ROW][C]123[/C][C]11.35[/C][C]14.0533[/C][C]-2.70326[/C][/ROW]
[ROW][C]124[/C][C]15.95[/C][C]15.0239[/C][C]0.926086[/C][/ROW]
[ROW][C]125[/C][C]18.1[/C][C]13.3908[/C][C]4.70921[/C][/ROW]
[ROW][C]126[/C][C]14.6[/C][C]13.0376[/C][C]1.56242[/C][/ROW]
[ROW][C]127[/C][C]15.4[/C][C]16.3218[/C][C]-0.921784[/C][/ROW]
[ROW][C]128[/C][C]15.4[/C][C]16.3218[/C][C]-0.921784[/C][/ROW]
[ROW][C]129[/C][C]17.6[/C][C]13.6427[/C][C]3.95731[/C][/ROW]
[ROW][C]130[/C][C]13.35[/C][C]13.9177[/C][C]-0.567723[/C][/ROW]
[ROW][C]131[/C][C]19.1[/C][C]16.7703[/C][C]2.32972[/C][/ROW]
[ROW][C]132[/C][C]15.35[/C][C]13.284[/C][C]2.06596[/C][/ROW]
[ROW][C]133[/C][C]7.6[/C][C]12.2665[/C][C]-4.66649[/C][/ROW]
[ROW][C]134[/C][C]13.4[/C][C]13.8016[/C][C]-0.401646[/C][/ROW]
[ROW][C]135[/C][C]13.9[/C][C]13.688[/C][C]0.211982[/C][/ROW]
[ROW][C]136[/C][C]19.1[/C][C]17.1739[/C][C]1.92611[/C][/ROW]
[ROW][C]137[/C][C]15.25[/C][C]13.9014[/C][C]1.34862[/C][/ROW]
[ROW][C]138[/C][C]12.9[/C][C]12.4712[/C][C]0.428838[/C][/ROW]
[ROW][C]139[/C][C]16.1[/C][C]13.8774[/C][C]2.22264[/C][/ROW]
[ROW][C]140[/C][C]17.35[/C][C]12.5112[/C][C]4.83878[/C][/ROW]
[ROW][C]141[/C][C]13.15[/C][C]12.509[/C][C]0.641007[/C][/ROW]
[ROW][C]142[/C][C]12.15[/C][C]10.2287[/C][C]1.92132[/C][/ROW]
[ROW][C]143[/C][C]12.6[/C][C]12.6622[/C][C]-0.0621942[/C][/ROW]
[ROW][C]144[/C][C]10.35[/C][C]11.6287[/C][C]-1.27872[/C][/ROW]
[ROW][C]145[/C][C]15.4[/C][C]12.8616[/C][C]2.53841[/C][/ROW]
[ROW][C]146[/C][C]9.6[/C][C]11.1592[/C][C]-1.55917[/C][/ROW]
[ROW][C]147[/C][C]18.2[/C][C]13.3717[/C][C]4.82829[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.2561[/C][C]1.34387[/C][/ROW]
[ROW][C]149[/C][C]14.85[/C][C]14.5119[/C][C]0.338095[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]17.0102[/C][C]-2.26018[/C][/ROW]
[ROW][C]151[/C][C]14.1[/C][C]13.9177[/C][C]0.182339[/C][/ROW]
[ROW][C]152[/C][C]14.9[/C][C]11.4464[/C][C]3.45355[/C][/ROW]
[ROW][C]153[/C][C]16.25[/C][C]12.8833[/C][C]3.36666[/C][/ROW]
[ROW][C]154[/C][C]19.25[/C][C]17.629[/C][C]1.62098[/C][/ROW]
[ROW][C]155[/C][C]13.6[/C][C]12.1012[/C][C]1.49876[/C][/ROW]
[ROW][C]156[/C][C]13.6[/C][C]13.5731[/C][C]0.026914[/C][/ROW]
[ROW][C]157[/C][C]15.65[/C][C]15.2772[/C][C]0.37282[/C][/ROW]
[ROW][C]158[/C][C]12.75[/C][C]12.5072[/C][C]0.242849[/C][/ROW]
[ROW][C]159[/C][C]14.6[/C][C]11.2197[/C][C]3.3803[/C][/ROW]
[ROW][C]160[/C][C]9.85[/C][C]13.246[/C][C]-3.39601[/C][/ROW]
[ROW][C]161[/C][C]12.65[/C][C]11.2435[/C][C]1.40651[/C][/ROW]
[ROW][C]162[/C][C]11.9[/C][C]12.2581[/C][C]-0.358141[/C][/ROW]
[ROW][C]163[/C][C]19.2[/C][C]16.4477[/C][C]2.75233[/C][/ROW]
[ROW][C]164[/C][C]16.6[/C][C]14.2032[/C][C]2.39684[/C][/ROW]
[ROW][C]165[/C][C]11.2[/C][C]10.099[/C][C]1.10105[/C][/ROW]
[ROW][C]166[/C][C]15.25[/C][C]13.4332[/C][C]1.81681[/C][/ROW]
[ROW][C]167[/C][C]11.9[/C][C]15.0976[/C][C]-3.19764[/C][/ROW]
[ROW][C]168[/C][C]13.2[/C][C]15.7934[/C][C]-2.59337[/C][/ROW]
[ROW][C]169[/C][C]16.35[/C][C]17.1984[/C][C]-0.848395[/C][/ROW]
[ROW][C]170[/C][C]12.4[/C][C]13.505[/C][C]-1.10501[/C][/ROW]
[ROW][C]171[/C][C]15.85[/C][C]13.0089[/C][C]2.84107[/C][/ROW]
[ROW][C]172[/C][C]14.35[/C][C]13.8683[/C][C]0.481719[/C][/ROW]
[ROW][C]173[/C][C]18.15[/C][C]15.3287[/C][C]2.82128[/C][/ROW]
[ROW][C]174[/C][C]11.15[/C][C]11.5281[/C][C]-0.378074[/C][/ROW]
[ROW][C]175[/C][C]15.65[/C][C]15.4627[/C][C]0.187336[/C][/ROW]
[ROW][C]176[/C][C]17.75[/C][C]16.2825[/C][C]1.46746[/C][/ROW]
[ROW][C]177[/C][C]7.65[/C][C]12.5565[/C][C]-4.90651[/C][/ROW]
[ROW][C]178[/C][C]12.35[/C][C]12.1988[/C][C]0.151228[/C][/ROW]
[ROW][C]179[/C][C]15.6[/C][C]11.9959[/C][C]3.60413[/C][/ROW]
[ROW][C]180[/C][C]19.3[/C][C]16.4592[/C][C]2.84077[/C][/ROW]
[ROW][C]181[/C][C]15.2[/C][C]11.8967[/C][C]3.30329[/C][/ROW]
[ROW][C]182[/C][C]17.1[/C][C]13.7943[/C][C]3.30566[/C][/ROW]
[ROW][C]183[/C][C]15.6[/C][C]12.6459[/C][C]2.95411[/C][/ROW]
[ROW][C]184[/C][C]18.4[/C][C]15.0276[/C][C]3.37236[/C][/ROW]
[ROW][C]185[/C][C]19.05[/C][C]15.3577[/C][C]3.69228[/C][/ROW]
[ROW][C]186[/C][C]18.55[/C][C]13.5747[/C][C]4.97532[/C][/ROW]
[ROW][C]187[/C][C]19.1[/C][C]16.8[/C][C]2.29996[/C][/ROW]
[ROW][C]188[/C][C]13.1[/C][C]11.9773[/C][C]1.12275[/C][/ROW]
[ROW][C]189[/C][C]12.85[/C][C]13.5661[/C][C]-0.716073[/C][/ROW]
[ROW][C]190[/C][C]9.5[/C][C]11.8546[/C][C]-2.35459[/C][/ROW]
[ROW][C]191[/C][C]4.5[/C][C]11.3661[/C][C]-6.86614[/C][/ROW]
[ROW][C]192[/C][C]11.85[/C][C]10.758[/C][C]1.09197[/C][/ROW]
[ROW][C]193[/C][C]13.6[/C][C]15.8692[/C][C]-2.26923[/C][/ROW]
[ROW][C]194[/C][C]11.7[/C][C]13.3782[/C][C]-1.67824[/C][/ROW]
[ROW][C]195[/C][C]12.4[/C][C]11.6127[/C][C]0.787337[/C][/ROW]
[ROW][C]196[/C][C]13.35[/C][C]14.9271[/C][C]-1.57712[/C][/ROW]
[ROW][C]197[/C][C]11.4[/C][C]13.8276[/C][C]-2.42761[/C][/ROW]
[ROW][C]198[/C][C]14.9[/C][C]11.8315[/C][C]3.06851[/C][/ROW]
[ROW][C]199[/C][C]19.9[/C][C]14.7445[/C][C]5.15551[/C][/ROW]
[ROW][C]200[/C][C]17.75[/C][C]12.3124[/C][C]5.43759[/C][/ROW]
[ROW][C]201[/C][C]11.2[/C][C]11.9126[/C][C]-0.712614[/C][/ROW]
[ROW][C]202[/C][C]14.6[/C][C]15.4633[/C][C]-0.863347[/C][/ROW]
[ROW][C]203[/C][C]17.6[/C][C]16.1908[/C][C]1.40918[/C][/ROW]
[ROW][C]204[/C][C]14.05[/C][C]12.6353[/C][C]1.41473[/C][/ROW]
[ROW][C]205[/C][C]16.1[/C][C]15.404[/C][C]0.696021[/C][/ROW]
[ROW][C]206[/C][C]13.35[/C][C]13.4987[/C][C]-0.14868[/C][/ROW]
[ROW][C]207[/C][C]11.85[/C][C]12.7718[/C][C]-0.921772[/C][/ROW]
[ROW][C]208[/C][C]11.95[/C][C]14.3099[/C][C]-2.35992[/C][/ROW]
[ROW][C]209[/C][C]14.75[/C][C]14.6482[/C][C]0.101784[/C][/ROW]
[ROW][C]210[/C][C]15.15[/C][C]13.1477[/C][C]2.0023[/C][/ROW]
[ROW][C]211[/C][C]13.2[/C][C]14.064[/C][C]-0.863997[/C][/ROW]
[ROW][C]212[/C][C]16.85[/C][C]15.3434[/C][C]1.50658[/C][/ROW]
[ROW][C]213[/C][C]7.85[/C][C]10.3871[/C][C]-2.53714[/C][/ROW]
[ROW][C]214[/C][C]7.7[/C][C]14.7153[/C][C]-7.01528[/C][/ROW]
[ROW][C]215[/C][C]12.6[/C][C]11.5923[/C][C]1.00767[/C][/ROW]
[ROW][C]216[/C][C]7.85[/C][C]11.6748[/C][C]-3.82484[/C][/ROW]
[ROW][C]217[/C][C]10.95[/C][C]10.4875[/C][C]0.462457[/C][/ROW]
[ROW][C]218[/C][C]12.35[/C][C]12.16[/C][C]0.189985[/C][/ROW]
[ROW][C]219[/C][C]9.95[/C][C]12.5983[/C][C]-2.64829[/C][/ROW]
[ROW][C]220[/C][C]14.9[/C][C]11.8315[/C][C]3.06851[/C][/ROW]
[ROW][C]221[/C][C]16.65[/C][C]14.6106[/C][C]2.03943[/C][/ROW]
[ROW][C]222[/C][C]13.4[/C][C]13.0424[/C][C]0.357571[/C][/ROW]
[ROW][C]223[/C][C]13.95[/C][C]13.4825[/C][C]0.467492[/C][/ROW]
[ROW][C]224[/C][C]15.7[/C][C]11.7165[/C][C]3.98345[/C][/ROW]
[ROW][C]225[/C][C]16.85[/C][C]12.5509[/C][C]4.29905[/C][/ROW]
[ROW][C]226[/C][C]10.95[/C][C]10.5776[/C][C]0.372404[/C][/ROW]
[ROW][C]227[/C][C]15.35[/C][C]12.0256[/C][C]3.32443[/C][/ROW]
[ROW][C]228[/C][C]12.2[/C][C]11.3129[/C][C]0.887106[/C][/ROW]
[ROW][C]229[/C][C]15.1[/C][C]14.0664[/C][C]1.03358[/C][/ROW]
[ROW][C]230[/C][C]17.75[/C][C]16.2989[/C][C]1.45113[/C][/ROW]
[ROW][C]231[/C][C]15.2[/C][C]12.892[/C][C]2.30804[/C][/ROW]
[ROW][C]232[/C][C]14.6[/C][C]13.5039[/C][C]1.09611[/C][/ROW]
[ROW][C]233[/C][C]16.65[/C][C]14.7972[/C][C]1.85279[/C][/ROW]
[ROW][C]234[/C][C]8.1[/C][C]10.9247[/C][C]-2.82466[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265184&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265184&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
112.912.37150.528523
212.812.56570.234285
37.413.0306-5.63059
46.711.7912-5.09117
512.615.6458-3.04579
614.813.0441.75603
713.312.33060.969378
811.112.7778-1.67781
98.214.5411-6.34105
1011.413.3382-1.93825
116.414.7794-8.37938
121213.7904-1.79043
136.310.0765-3.77649
1411.311.6061-0.306102
1511.914.0421-2.14206
169.312.4446-3.14461
171011.9499-1.9499
1813.812.98560.81439
1910.813.899-3.09903
2011.712.9505-1.25052
2110.915.5286-4.62864
2216.113.28842.81159
239.911.6836-1.78356
2411.512.6589-1.15893
258.312.1247-3.82467
2611.713.713-2.01301
27912.6936-3.69357
2810.812.7092-1.9092
2910.412.2381-1.8381
3012.712.9985-0.298501
3111.814.5293-2.72927
321312.15970.840301
3310.813.0653-2.26526
3412.310.6741.62603
3511.313.7861-2.48607
3611.612.3145-0.714461
3710.913.5797-2.67966
3812.113.1228-1.0228
3913.313.6722-0.372163
4010.113.6152-3.51522
4114.312.56251.73746
429.313.088-3.78798
4312.512.14420.355791
447.611.1658-3.56582
459.212.0255-2.82547
4614.513.30361.19645
4712.313.6931-1.39312
4812.613.2802-0.680172
491313.9532-0.953164
5012.611.5931.00703
5113.214.9329-1.73287
527.711.7594-4.05944
5310.510.9488-0.448819
5410.912.034-1.13397
554.310.5563-6.25633
5610.311.4159-1.11595
5711.411.03650.363495
585.611.5544-5.95443
598.812.2214-3.42144
60910.9497-1.94973
619.611.3604-1.7604
626.410.5105-4.11046
6311.611.25740.342583
644.3510.2336-5.88359
6512.712.61660.0833806
6618.114.98563.11436
6717.8515.29992.5501
6816.615.72830.871725
6912.610.36782.23216
7017.121.917-4.81698
7119.115.52243.5776
7216.118.0263-1.92635
7313.3510.96572.38427
7418.417.60560.79443
7514.711.20263.49735
7610.614.7861-4.18605
7712.613.9537-1.35371
7816.215.26840.931637
7913.617.0858-3.48584
8018.915.56953.33049
8114.112.58561.51442
8214.512.2092.29101
8316.1517.8412-1.69121
8414.7513.64061.10939
8514.814.23240.567594
8612.4512.4813-0.0312596
8712.6514.6584-2.00839
8817.3514.02673.32326
898.612.1377-3.5377
9018.417.58810.811857
9116.117.816-1.71597
9211.611.40490.195053
9317.7512.54355.20652
9415.2513.8231.42699
9517.6516.26391.38606
9615.614.03381.56622
9716.3515.17541.17455
9817.6515.01522.63483
9913.613.16180.438236
10011.712.6373-0.937327
10114.3513.60.749962
10214.7517.703-2.95302
10318.2516.51411.73593
1049.915.46-5.55999
1051614.04721.95278
10618.2515.8252.42498
10716.8517.4791-0.629064
10814.612.67151.92853
10913.8513.8717-0.0216597
11018.9516.30652.64353
11115.614.66450.935455
11214.8517.1519-2.30187
11311.7512.4665-0.71654
11418.4512.97955.47046
11515.917.2921-1.39212
11617.114.3642.73598
11716.110.92515.17492
11819.914.74455.15551
11910.9510.48750.462457
12018.4515.73592.71408
12115.110.88444.21562
1221515.4177-0.417735
12311.3514.0533-2.70326
12415.9515.02390.926086
12518.113.39084.70921
12614.613.03761.56242
12715.416.3218-0.921784
12815.416.3218-0.921784
12917.613.64273.95731
13013.3513.9177-0.567723
13119.116.77032.32972
13215.3513.2842.06596
1337.612.2665-4.66649
13413.413.8016-0.401646
13513.913.6880.211982
13619.117.17391.92611
13715.2513.90141.34862
13812.912.47120.428838
13916.113.87742.22264
14017.3512.51124.83878
14113.1512.5090.641007
14212.1510.22871.92132
14312.612.6622-0.0621942
14410.3511.6287-1.27872
14515.412.86162.53841
1469.611.1592-1.55917
14718.213.37174.82829
14813.612.25611.34387
14914.8514.51190.338095
15014.7517.0102-2.26018
15114.113.91770.182339
15214.911.44643.45355
15316.2512.88333.36666
15419.2517.6291.62098
15513.612.10121.49876
15613.613.57310.026914
15715.6515.27720.37282
15812.7512.50720.242849
15914.611.21973.3803
1609.8513.246-3.39601
16112.6511.24351.40651
16211.912.2581-0.358141
16319.216.44772.75233
16416.614.20322.39684
16511.210.0991.10105
16615.2513.43321.81681
16711.915.0976-3.19764
16813.215.7934-2.59337
16916.3517.1984-0.848395
17012.413.505-1.10501
17115.8513.00892.84107
17214.3513.86830.481719
17318.1515.32872.82128
17411.1511.5281-0.378074
17515.6515.46270.187336
17617.7516.28251.46746
1777.6512.5565-4.90651
17812.3512.19880.151228
17915.611.99593.60413
18019.316.45922.84077
18115.211.89673.30329
18217.113.79433.30566
18315.612.64592.95411
18418.415.02763.37236
18519.0515.35773.69228
18618.5513.57474.97532
18719.116.82.29996
18813.111.97731.12275
18912.8513.5661-0.716073
1909.511.8546-2.35459
1914.511.3661-6.86614
19211.8510.7581.09197
19313.615.8692-2.26923
19411.713.3782-1.67824
19512.411.61270.787337
19613.3514.9271-1.57712
19711.413.8276-2.42761
19814.911.83153.06851
19919.914.74455.15551
20017.7512.31245.43759
20111.211.9126-0.712614
20214.615.4633-0.863347
20317.616.19081.40918
20414.0512.63531.41473
20516.115.4040.696021
20613.3513.4987-0.14868
20711.8512.7718-0.921772
20811.9514.3099-2.35992
20914.7514.64820.101784
21015.1513.14772.0023
21113.214.064-0.863997
21216.8515.34341.50658
2137.8510.3871-2.53714
2147.714.7153-7.01528
21512.611.59231.00767
2167.8511.6748-3.82484
21710.9510.48750.462457
21812.3512.160.189985
2199.9512.5983-2.64829
22014.911.83153.06851
22116.6514.61062.03943
22213.413.04240.357571
22313.9513.48250.467492
22415.711.71653.98345
22516.8512.55094.29905
22610.9510.57760.372404
22715.3512.02563.32443
22812.211.31290.887106
22915.114.06641.03358
23017.7516.29891.45113
23115.212.8922.30804
23214.613.50391.09611
23316.6514.79721.85279
2348.110.9247-2.82466






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.9052690.1894610.0947305
80.8362940.3274120.163706
90.8307720.3384560.169228
100.7502860.4994290.249714
110.8132490.3735020.186751
120.7404680.5190650.259532
130.6642260.6715480.335774
140.7016630.5966730.298337
150.638140.723720.36186
160.5617570.8764850.438243
170.4819420.9638840.518058
180.5913990.8172020.408601
190.5688150.862370.431185
200.5026740.9946520.497326
210.4873710.9747420.512629
220.592970.814060.40703
230.5754890.8490230.424511
240.5206280.9587450.479372
250.4930130.9860260.506987
260.4589680.9179360.541032
270.4190520.8381030.580948
280.3737490.7474990.626251
290.324050.6480990.67595
300.3577590.7155190.642241
310.3204030.6408060.679597
320.2892240.5784480.710776
330.25270.5053990.7473
340.2519760.5039530.748024
350.2219330.4438670.778067
360.191880.3837610.80812
370.1663770.3327540.833623
380.1496360.2992720.850364
390.150070.300140.84993
400.131020.262040.86898
410.1547140.3094280.845286
420.1805160.3610320.819484
430.1633120.3266250.836688
440.1955220.3910450.804478
450.2099510.4199030.790049
460.2355610.4711220.764439
470.2173980.4347960.782602
480.199140.398280.80086
490.1861690.3723380.813831
500.1751780.3503560.824822
510.1652980.3305960.834702
520.2134610.4269230.786539
530.1852390.3704790.814761
540.1605890.3211780.839411
550.3744930.7489850.625507
560.3573210.7146420.642679
570.3331240.6662470.666876
580.5277320.9445360.472268
590.5294990.9410030.470501
600.5293860.9412280.470614
610.5431050.913790.456895
620.5885380.8229230.411462
630.5808830.8382340.419117
640.719680.5606410.28032
650.7167630.5664740.283237
660.8260650.3478690.173935
670.8650680.2698640.134932
680.8478430.3043130.152157
690.8748650.2502690.125135
700.8874850.2250290.112515
710.9262830.1474350.0737173
720.9349510.1300980.0650488
730.9471690.1056620.052831
740.9444290.1111430.0555715
750.9659330.06813370.0340669
760.9723770.0552460.027623
770.9664780.06704370.0335218
780.9638090.07238180.0361909
790.9629660.07406720.0370336
800.9741580.05168430.0258421
810.973220.05356010.0267801
820.9754390.04912170.0245609
830.9730550.05389030.0269452
840.9699170.06016510.0300826
850.9645720.07085570.0354278
860.9567120.08657570.0432878
870.9499890.1000220.0500109
880.9635630.07287350.0364367
890.9661360.06772880.0338644
900.9611650.07766920.0388346
910.9537990.09240140.0462007
920.9449390.1101220.0550608
930.9737580.05248310.0262416
940.9736170.05276620.0263831
950.9720760.05584840.0279242
960.9692650.06147040.0307352
970.9651620.06967630.0348382
980.9669360.06612880.0330644
990.9610780.07784330.0389217
1000.9577710.08445810.042229
1010.9506470.09870660.0493533
1020.948070.1038590.0519297
1030.9443870.1112250.0556126
1040.9809510.03809820.0190491
1050.979780.04043920.0202196
1060.9801570.03968590.0198429
1070.9754570.04908510.0245426
1080.9756890.04862160.0243108
1090.9702670.05946550.0297328
1100.9706010.05879810.029399
1110.9653270.0693460.034673
1120.9630520.07389570.0369478
1130.9557910.08841730.0442087
1140.974260.05148020.0257401
1150.9701290.05974150.0298707
1160.9707870.05842550.0292127
1170.9932860.01342880.00671442
1180.9956680.008663550.00433177
1190.9944370.01112560.00556279
1200.9944240.01115250.00557627
1210.9963980.007203940.00360197
1220.99530.009399310.00469965
1230.9956330.008733450.00436672
1240.9946610.01067870.00533934
1250.9965730.006854270.00342713
1260.9961750.007649940.00382497
1270.9951570.009685010.0048425
1280.9939490.0121020.00605098
1290.9950590.0098810.0049405
1300.9943340.01133280.0056664
1310.9941750.0116510.0058255
1320.9934380.0131240.00656201
1330.9953450.009309780.00465489
1340.9947310.01053890.00526946
1350.9933170.01336690.00668344
1360.9922290.01554270.00777136
1370.9902330.01953410.00976703
1380.9897410.02051810.010259
1390.9880.02400030.0120001
1400.9935420.01291660.00645831
1410.9919980.0160050.00800248
1420.9904120.01917620.00958809
1430.9876430.02471370.0123568
1440.9848820.03023610.0151181
1450.9823970.03520690.0176034
1460.9805420.03891690.0194584
1470.9879660.02406890.0120344
1480.985320.02935960.0146798
1490.9829720.03405580.0170279
1500.9830430.03391430.0169572
1510.9784130.04317330.0215866
1520.9817570.03648670.0182434
1530.9813820.03723690.0186184
1540.9787020.04259640.0212982
1550.9766410.0467180.023359
1560.9737040.05259160.0262958
1570.9673920.06521530.0326076
1580.9599180.0801640.040082
1590.9687880.06242480.0312124
1600.9672220.06555570.0327778
1610.9647560.07048710.0352435
1620.9563620.08727680.0436384
1630.9519710.09605790.048029
1640.947650.10470.0523499
1650.9369130.1261730.0630867
1660.9258410.1483190.0741593
1670.9397720.1204560.0602281
1680.931080.1378410.0689203
1690.9268180.1463650.0731823
1700.9147290.1705420.0852712
1710.9115520.1768970.0884483
1720.8972890.2054220.102711
1730.8847370.2305260.115263
1740.8618230.2763540.138177
1750.8357850.328430.164215
1760.8192120.3615760.180788
1770.848160.303680.15184
1780.8201920.3596160.179808
1790.820230.3595410.17977
1800.8043990.3912030.195601
1810.8620170.2759660.137983
1820.87410.25180.1259
1830.8908530.2182940.109147
1840.8768430.2463140.123157
1850.88950.2210010.1105
1860.9163160.1673690.0836843
1870.8988660.2022680.101134
1880.879990.240020.12001
1890.8736770.2526450.126323
1900.8719760.2560470.128024
1910.9558340.08833130.0441656
1920.9518040.09639110.0481956
1930.9517180.09656480.0482824
1940.9393240.1213530.0606764
1950.9215520.1568960.0784482
1960.910090.179820.0899102
1970.8920260.2159480.107974
1980.8835380.2329230.116462
1990.8763330.2473350.123667
2000.9321480.1357030.0678517
2010.9107740.1784510.0892257
2020.8876570.2246850.112343
2030.8633850.273230.136615
2040.8346460.3307090.165354
2050.7955480.4089040.204452
2060.7480560.5038880.251944
2070.707690.5846190.29231
2080.7093680.5812630.290632
2090.6508330.6983330.349167
2100.5910470.8179060.408953
2110.631160.737680.36884
2120.5660470.8679060.433953
2130.5595840.8808320.440416
2140.926770.1464590.0732296
2150.8940620.2118770.105938
2160.9961530.007694470.00384724
2170.9940540.01189120.00594559
2180.9909990.01800120.00900062
2190.9999470.0001059155.29577e-05
2200.9998380.0003241710.000162086
2210.9996990.0006011380.000300569
2220.9994030.001193740.000596869
2230.9994190.001161360.00058068
2240.9984620.003075640.00153782
2250.9976160.004767280.00238364
2260.9900090.01998260.00999129
2270.9819390.03612270.0180614

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.905269 & 0.189461 & 0.0947305 \tabularnewline
8 & 0.836294 & 0.327412 & 0.163706 \tabularnewline
9 & 0.830772 & 0.338456 & 0.169228 \tabularnewline
10 & 0.750286 & 0.499429 & 0.249714 \tabularnewline
11 & 0.813249 & 0.373502 & 0.186751 \tabularnewline
12 & 0.740468 & 0.519065 & 0.259532 \tabularnewline
13 & 0.664226 & 0.671548 & 0.335774 \tabularnewline
14 & 0.701663 & 0.596673 & 0.298337 \tabularnewline
15 & 0.63814 & 0.72372 & 0.36186 \tabularnewline
16 & 0.561757 & 0.876485 & 0.438243 \tabularnewline
17 & 0.481942 & 0.963884 & 0.518058 \tabularnewline
18 & 0.591399 & 0.817202 & 0.408601 \tabularnewline
19 & 0.568815 & 0.86237 & 0.431185 \tabularnewline
20 & 0.502674 & 0.994652 & 0.497326 \tabularnewline
21 & 0.487371 & 0.974742 & 0.512629 \tabularnewline
22 & 0.59297 & 0.81406 & 0.40703 \tabularnewline
23 & 0.575489 & 0.849023 & 0.424511 \tabularnewline
24 & 0.520628 & 0.958745 & 0.479372 \tabularnewline
25 & 0.493013 & 0.986026 & 0.506987 \tabularnewline
26 & 0.458968 & 0.917936 & 0.541032 \tabularnewline
27 & 0.419052 & 0.838103 & 0.580948 \tabularnewline
28 & 0.373749 & 0.747499 & 0.626251 \tabularnewline
29 & 0.32405 & 0.648099 & 0.67595 \tabularnewline
30 & 0.357759 & 0.715519 & 0.642241 \tabularnewline
31 & 0.320403 & 0.640806 & 0.679597 \tabularnewline
32 & 0.289224 & 0.578448 & 0.710776 \tabularnewline
33 & 0.2527 & 0.505399 & 0.7473 \tabularnewline
34 & 0.251976 & 0.503953 & 0.748024 \tabularnewline
35 & 0.221933 & 0.443867 & 0.778067 \tabularnewline
36 & 0.19188 & 0.383761 & 0.80812 \tabularnewline
37 & 0.166377 & 0.332754 & 0.833623 \tabularnewline
38 & 0.149636 & 0.299272 & 0.850364 \tabularnewline
39 & 0.15007 & 0.30014 & 0.84993 \tabularnewline
40 & 0.13102 & 0.26204 & 0.86898 \tabularnewline
41 & 0.154714 & 0.309428 & 0.845286 \tabularnewline
42 & 0.180516 & 0.361032 & 0.819484 \tabularnewline
43 & 0.163312 & 0.326625 & 0.836688 \tabularnewline
44 & 0.195522 & 0.391045 & 0.804478 \tabularnewline
45 & 0.209951 & 0.419903 & 0.790049 \tabularnewline
46 & 0.235561 & 0.471122 & 0.764439 \tabularnewline
47 & 0.217398 & 0.434796 & 0.782602 \tabularnewline
48 & 0.19914 & 0.39828 & 0.80086 \tabularnewline
49 & 0.186169 & 0.372338 & 0.813831 \tabularnewline
50 & 0.175178 & 0.350356 & 0.824822 \tabularnewline
51 & 0.165298 & 0.330596 & 0.834702 \tabularnewline
52 & 0.213461 & 0.426923 & 0.786539 \tabularnewline
53 & 0.185239 & 0.370479 & 0.814761 \tabularnewline
54 & 0.160589 & 0.321178 & 0.839411 \tabularnewline
55 & 0.374493 & 0.748985 & 0.625507 \tabularnewline
56 & 0.357321 & 0.714642 & 0.642679 \tabularnewline
57 & 0.333124 & 0.666247 & 0.666876 \tabularnewline
58 & 0.527732 & 0.944536 & 0.472268 \tabularnewline
59 & 0.529499 & 0.941003 & 0.470501 \tabularnewline
60 & 0.529386 & 0.941228 & 0.470614 \tabularnewline
61 & 0.543105 & 0.91379 & 0.456895 \tabularnewline
62 & 0.588538 & 0.822923 & 0.411462 \tabularnewline
63 & 0.580883 & 0.838234 & 0.419117 \tabularnewline
64 & 0.71968 & 0.560641 & 0.28032 \tabularnewline
65 & 0.716763 & 0.566474 & 0.283237 \tabularnewline
66 & 0.826065 & 0.347869 & 0.173935 \tabularnewline
67 & 0.865068 & 0.269864 & 0.134932 \tabularnewline
68 & 0.847843 & 0.304313 & 0.152157 \tabularnewline
69 & 0.874865 & 0.250269 & 0.125135 \tabularnewline
70 & 0.887485 & 0.225029 & 0.112515 \tabularnewline
71 & 0.926283 & 0.147435 & 0.0737173 \tabularnewline
72 & 0.934951 & 0.130098 & 0.0650488 \tabularnewline
73 & 0.947169 & 0.105662 & 0.052831 \tabularnewline
74 & 0.944429 & 0.111143 & 0.0555715 \tabularnewline
75 & 0.965933 & 0.0681337 & 0.0340669 \tabularnewline
76 & 0.972377 & 0.055246 & 0.027623 \tabularnewline
77 & 0.966478 & 0.0670437 & 0.0335218 \tabularnewline
78 & 0.963809 & 0.0723818 & 0.0361909 \tabularnewline
79 & 0.962966 & 0.0740672 & 0.0370336 \tabularnewline
80 & 0.974158 & 0.0516843 & 0.0258421 \tabularnewline
81 & 0.97322 & 0.0535601 & 0.0267801 \tabularnewline
82 & 0.975439 & 0.0491217 & 0.0245609 \tabularnewline
83 & 0.973055 & 0.0538903 & 0.0269452 \tabularnewline
84 & 0.969917 & 0.0601651 & 0.0300826 \tabularnewline
85 & 0.964572 & 0.0708557 & 0.0354278 \tabularnewline
86 & 0.956712 & 0.0865757 & 0.0432878 \tabularnewline
87 & 0.949989 & 0.100022 & 0.0500109 \tabularnewline
88 & 0.963563 & 0.0728735 & 0.0364367 \tabularnewline
89 & 0.966136 & 0.0677288 & 0.0338644 \tabularnewline
90 & 0.961165 & 0.0776692 & 0.0388346 \tabularnewline
91 & 0.953799 & 0.0924014 & 0.0462007 \tabularnewline
92 & 0.944939 & 0.110122 & 0.0550608 \tabularnewline
93 & 0.973758 & 0.0524831 & 0.0262416 \tabularnewline
94 & 0.973617 & 0.0527662 & 0.0263831 \tabularnewline
95 & 0.972076 & 0.0558484 & 0.0279242 \tabularnewline
96 & 0.969265 & 0.0614704 & 0.0307352 \tabularnewline
97 & 0.965162 & 0.0696763 & 0.0348382 \tabularnewline
98 & 0.966936 & 0.0661288 & 0.0330644 \tabularnewline
99 & 0.961078 & 0.0778433 & 0.0389217 \tabularnewline
100 & 0.957771 & 0.0844581 & 0.042229 \tabularnewline
101 & 0.950647 & 0.0987066 & 0.0493533 \tabularnewline
102 & 0.94807 & 0.103859 & 0.0519297 \tabularnewline
103 & 0.944387 & 0.111225 & 0.0556126 \tabularnewline
104 & 0.980951 & 0.0380982 & 0.0190491 \tabularnewline
105 & 0.97978 & 0.0404392 & 0.0202196 \tabularnewline
106 & 0.980157 & 0.0396859 & 0.0198429 \tabularnewline
107 & 0.975457 & 0.0490851 & 0.0245426 \tabularnewline
108 & 0.975689 & 0.0486216 & 0.0243108 \tabularnewline
109 & 0.970267 & 0.0594655 & 0.0297328 \tabularnewline
110 & 0.970601 & 0.0587981 & 0.029399 \tabularnewline
111 & 0.965327 & 0.069346 & 0.034673 \tabularnewline
112 & 0.963052 & 0.0738957 & 0.0369478 \tabularnewline
113 & 0.955791 & 0.0884173 & 0.0442087 \tabularnewline
114 & 0.97426 & 0.0514802 & 0.0257401 \tabularnewline
115 & 0.970129 & 0.0597415 & 0.0298707 \tabularnewline
116 & 0.970787 & 0.0584255 & 0.0292127 \tabularnewline
117 & 0.993286 & 0.0134288 & 0.00671442 \tabularnewline
118 & 0.995668 & 0.00866355 & 0.00433177 \tabularnewline
119 & 0.994437 & 0.0111256 & 0.00556279 \tabularnewline
120 & 0.994424 & 0.0111525 & 0.00557627 \tabularnewline
121 & 0.996398 & 0.00720394 & 0.00360197 \tabularnewline
122 & 0.9953 & 0.00939931 & 0.00469965 \tabularnewline
123 & 0.995633 & 0.00873345 & 0.00436672 \tabularnewline
124 & 0.994661 & 0.0106787 & 0.00533934 \tabularnewline
125 & 0.996573 & 0.00685427 & 0.00342713 \tabularnewline
126 & 0.996175 & 0.00764994 & 0.00382497 \tabularnewline
127 & 0.995157 & 0.00968501 & 0.0048425 \tabularnewline
128 & 0.993949 & 0.012102 & 0.00605098 \tabularnewline
129 & 0.995059 & 0.009881 & 0.0049405 \tabularnewline
130 & 0.994334 & 0.0113328 & 0.0056664 \tabularnewline
131 & 0.994175 & 0.011651 & 0.0058255 \tabularnewline
132 & 0.993438 & 0.013124 & 0.00656201 \tabularnewline
133 & 0.995345 & 0.00930978 & 0.00465489 \tabularnewline
134 & 0.994731 & 0.0105389 & 0.00526946 \tabularnewline
135 & 0.993317 & 0.0133669 & 0.00668344 \tabularnewline
136 & 0.992229 & 0.0155427 & 0.00777136 \tabularnewline
137 & 0.990233 & 0.0195341 & 0.00976703 \tabularnewline
138 & 0.989741 & 0.0205181 & 0.010259 \tabularnewline
139 & 0.988 & 0.0240003 & 0.0120001 \tabularnewline
140 & 0.993542 & 0.0129166 & 0.00645831 \tabularnewline
141 & 0.991998 & 0.016005 & 0.00800248 \tabularnewline
142 & 0.990412 & 0.0191762 & 0.00958809 \tabularnewline
143 & 0.987643 & 0.0247137 & 0.0123568 \tabularnewline
144 & 0.984882 & 0.0302361 & 0.0151181 \tabularnewline
145 & 0.982397 & 0.0352069 & 0.0176034 \tabularnewline
146 & 0.980542 & 0.0389169 & 0.0194584 \tabularnewline
147 & 0.987966 & 0.0240689 & 0.0120344 \tabularnewline
148 & 0.98532 & 0.0293596 & 0.0146798 \tabularnewline
149 & 0.982972 & 0.0340558 & 0.0170279 \tabularnewline
150 & 0.983043 & 0.0339143 & 0.0169572 \tabularnewline
151 & 0.978413 & 0.0431733 & 0.0215866 \tabularnewline
152 & 0.981757 & 0.0364867 & 0.0182434 \tabularnewline
153 & 0.981382 & 0.0372369 & 0.0186184 \tabularnewline
154 & 0.978702 & 0.0425964 & 0.0212982 \tabularnewline
155 & 0.976641 & 0.046718 & 0.023359 \tabularnewline
156 & 0.973704 & 0.0525916 & 0.0262958 \tabularnewline
157 & 0.967392 & 0.0652153 & 0.0326076 \tabularnewline
158 & 0.959918 & 0.080164 & 0.040082 \tabularnewline
159 & 0.968788 & 0.0624248 & 0.0312124 \tabularnewline
160 & 0.967222 & 0.0655557 & 0.0327778 \tabularnewline
161 & 0.964756 & 0.0704871 & 0.0352435 \tabularnewline
162 & 0.956362 & 0.0872768 & 0.0436384 \tabularnewline
163 & 0.951971 & 0.0960579 & 0.048029 \tabularnewline
164 & 0.94765 & 0.1047 & 0.0523499 \tabularnewline
165 & 0.936913 & 0.126173 & 0.0630867 \tabularnewline
166 & 0.925841 & 0.148319 & 0.0741593 \tabularnewline
167 & 0.939772 & 0.120456 & 0.0602281 \tabularnewline
168 & 0.93108 & 0.137841 & 0.0689203 \tabularnewline
169 & 0.926818 & 0.146365 & 0.0731823 \tabularnewline
170 & 0.914729 & 0.170542 & 0.0852712 \tabularnewline
171 & 0.911552 & 0.176897 & 0.0884483 \tabularnewline
172 & 0.897289 & 0.205422 & 0.102711 \tabularnewline
173 & 0.884737 & 0.230526 & 0.115263 \tabularnewline
174 & 0.861823 & 0.276354 & 0.138177 \tabularnewline
175 & 0.835785 & 0.32843 & 0.164215 \tabularnewline
176 & 0.819212 & 0.361576 & 0.180788 \tabularnewline
177 & 0.84816 & 0.30368 & 0.15184 \tabularnewline
178 & 0.820192 & 0.359616 & 0.179808 \tabularnewline
179 & 0.82023 & 0.359541 & 0.17977 \tabularnewline
180 & 0.804399 & 0.391203 & 0.195601 \tabularnewline
181 & 0.862017 & 0.275966 & 0.137983 \tabularnewline
182 & 0.8741 & 0.2518 & 0.1259 \tabularnewline
183 & 0.890853 & 0.218294 & 0.109147 \tabularnewline
184 & 0.876843 & 0.246314 & 0.123157 \tabularnewline
185 & 0.8895 & 0.221001 & 0.1105 \tabularnewline
186 & 0.916316 & 0.167369 & 0.0836843 \tabularnewline
187 & 0.898866 & 0.202268 & 0.101134 \tabularnewline
188 & 0.87999 & 0.24002 & 0.12001 \tabularnewline
189 & 0.873677 & 0.252645 & 0.126323 \tabularnewline
190 & 0.871976 & 0.256047 & 0.128024 \tabularnewline
191 & 0.955834 & 0.0883313 & 0.0441656 \tabularnewline
192 & 0.951804 & 0.0963911 & 0.0481956 \tabularnewline
193 & 0.951718 & 0.0965648 & 0.0482824 \tabularnewline
194 & 0.939324 & 0.121353 & 0.0606764 \tabularnewline
195 & 0.921552 & 0.156896 & 0.0784482 \tabularnewline
196 & 0.91009 & 0.17982 & 0.0899102 \tabularnewline
197 & 0.892026 & 0.215948 & 0.107974 \tabularnewline
198 & 0.883538 & 0.232923 & 0.116462 \tabularnewline
199 & 0.876333 & 0.247335 & 0.123667 \tabularnewline
200 & 0.932148 & 0.135703 & 0.0678517 \tabularnewline
201 & 0.910774 & 0.178451 & 0.0892257 \tabularnewline
202 & 0.887657 & 0.224685 & 0.112343 \tabularnewline
203 & 0.863385 & 0.27323 & 0.136615 \tabularnewline
204 & 0.834646 & 0.330709 & 0.165354 \tabularnewline
205 & 0.795548 & 0.408904 & 0.204452 \tabularnewline
206 & 0.748056 & 0.503888 & 0.251944 \tabularnewline
207 & 0.70769 & 0.584619 & 0.29231 \tabularnewline
208 & 0.709368 & 0.581263 & 0.290632 \tabularnewline
209 & 0.650833 & 0.698333 & 0.349167 \tabularnewline
210 & 0.591047 & 0.817906 & 0.408953 \tabularnewline
211 & 0.63116 & 0.73768 & 0.36884 \tabularnewline
212 & 0.566047 & 0.867906 & 0.433953 \tabularnewline
213 & 0.559584 & 0.880832 & 0.440416 \tabularnewline
214 & 0.92677 & 0.146459 & 0.0732296 \tabularnewline
215 & 0.894062 & 0.211877 & 0.105938 \tabularnewline
216 & 0.996153 & 0.00769447 & 0.00384724 \tabularnewline
217 & 0.994054 & 0.0118912 & 0.00594559 \tabularnewline
218 & 0.990999 & 0.0180012 & 0.00900062 \tabularnewline
219 & 0.999947 & 0.000105915 & 5.29577e-05 \tabularnewline
220 & 0.999838 & 0.000324171 & 0.000162086 \tabularnewline
221 & 0.999699 & 0.000601138 & 0.000300569 \tabularnewline
222 & 0.999403 & 0.00119374 & 0.000596869 \tabularnewline
223 & 0.999419 & 0.00116136 & 0.00058068 \tabularnewline
224 & 0.998462 & 0.00307564 & 0.00153782 \tabularnewline
225 & 0.997616 & 0.00476728 & 0.00238364 \tabularnewline
226 & 0.990009 & 0.0199826 & 0.00999129 \tabularnewline
227 & 0.981939 & 0.0361227 & 0.0180614 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265184&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]0.905269[/C][C]0.189461[/C][C]0.0947305[/C][/ROW]
[ROW][C]8[/C][C]0.836294[/C][C]0.327412[/C][C]0.163706[/C][/ROW]
[ROW][C]9[/C][C]0.830772[/C][C]0.338456[/C][C]0.169228[/C][/ROW]
[ROW][C]10[/C][C]0.750286[/C][C]0.499429[/C][C]0.249714[/C][/ROW]
[ROW][C]11[/C][C]0.813249[/C][C]0.373502[/C][C]0.186751[/C][/ROW]
[ROW][C]12[/C][C]0.740468[/C][C]0.519065[/C][C]0.259532[/C][/ROW]
[ROW][C]13[/C][C]0.664226[/C][C]0.671548[/C][C]0.335774[/C][/ROW]
[ROW][C]14[/C][C]0.701663[/C][C]0.596673[/C][C]0.298337[/C][/ROW]
[ROW][C]15[/C][C]0.63814[/C][C]0.72372[/C][C]0.36186[/C][/ROW]
[ROW][C]16[/C][C]0.561757[/C][C]0.876485[/C][C]0.438243[/C][/ROW]
[ROW][C]17[/C][C]0.481942[/C][C]0.963884[/C][C]0.518058[/C][/ROW]
[ROW][C]18[/C][C]0.591399[/C][C]0.817202[/C][C]0.408601[/C][/ROW]
[ROW][C]19[/C][C]0.568815[/C][C]0.86237[/C][C]0.431185[/C][/ROW]
[ROW][C]20[/C][C]0.502674[/C][C]0.994652[/C][C]0.497326[/C][/ROW]
[ROW][C]21[/C][C]0.487371[/C][C]0.974742[/C][C]0.512629[/C][/ROW]
[ROW][C]22[/C][C]0.59297[/C][C]0.81406[/C][C]0.40703[/C][/ROW]
[ROW][C]23[/C][C]0.575489[/C][C]0.849023[/C][C]0.424511[/C][/ROW]
[ROW][C]24[/C][C]0.520628[/C][C]0.958745[/C][C]0.479372[/C][/ROW]
[ROW][C]25[/C][C]0.493013[/C][C]0.986026[/C][C]0.506987[/C][/ROW]
[ROW][C]26[/C][C]0.458968[/C][C]0.917936[/C][C]0.541032[/C][/ROW]
[ROW][C]27[/C][C]0.419052[/C][C]0.838103[/C][C]0.580948[/C][/ROW]
[ROW][C]28[/C][C]0.373749[/C][C]0.747499[/C][C]0.626251[/C][/ROW]
[ROW][C]29[/C][C]0.32405[/C][C]0.648099[/C][C]0.67595[/C][/ROW]
[ROW][C]30[/C][C]0.357759[/C][C]0.715519[/C][C]0.642241[/C][/ROW]
[ROW][C]31[/C][C]0.320403[/C][C]0.640806[/C][C]0.679597[/C][/ROW]
[ROW][C]32[/C][C]0.289224[/C][C]0.578448[/C][C]0.710776[/C][/ROW]
[ROW][C]33[/C][C]0.2527[/C][C]0.505399[/C][C]0.7473[/C][/ROW]
[ROW][C]34[/C][C]0.251976[/C][C]0.503953[/C][C]0.748024[/C][/ROW]
[ROW][C]35[/C][C]0.221933[/C][C]0.443867[/C][C]0.778067[/C][/ROW]
[ROW][C]36[/C][C]0.19188[/C][C]0.383761[/C][C]0.80812[/C][/ROW]
[ROW][C]37[/C][C]0.166377[/C][C]0.332754[/C][C]0.833623[/C][/ROW]
[ROW][C]38[/C][C]0.149636[/C][C]0.299272[/C][C]0.850364[/C][/ROW]
[ROW][C]39[/C][C]0.15007[/C][C]0.30014[/C][C]0.84993[/C][/ROW]
[ROW][C]40[/C][C]0.13102[/C][C]0.26204[/C][C]0.86898[/C][/ROW]
[ROW][C]41[/C][C]0.154714[/C][C]0.309428[/C][C]0.845286[/C][/ROW]
[ROW][C]42[/C][C]0.180516[/C][C]0.361032[/C][C]0.819484[/C][/ROW]
[ROW][C]43[/C][C]0.163312[/C][C]0.326625[/C][C]0.836688[/C][/ROW]
[ROW][C]44[/C][C]0.195522[/C][C]0.391045[/C][C]0.804478[/C][/ROW]
[ROW][C]45[/C][C]0.209951[/C][C]0.419903[/C][C]0.790049[/C][/ROW]
[ROW][C]46[/C][C]0.235561[/C][C]0.471122[/C][C]0.764439[/C][/ROW]
[ROW][C]47[/C][C]0.217398[/C][C]0.434796[/C][C]0.782602[/C][/ROW]
[ROW][C]48[/C][C]0.19914[/C][C]0.39828[/C][C]0.80086[/C][/ROW]
[ROW][C]49[/C][C]0.186169[/C][C]0.372338[/C][C]0.813831[/C][/ROW]
[ROW][C]50[/C][C]0.175178[/C][C]0.350356[/C][C]0.824822[/C][/ROW]
[ROW][C]51[/C][C]0.165298[/C][C]0.330596[/C][C]0.834702[/C][/ROW]
[ROW][C]52[/C][C]0.213461[/C][C]0.426923[/C][C]0.786539[/C][/ROW]
[ROW][C]53[/C][C]0.185239[/C][C]0.370479[/C][C]0.814761[/C][/ROW]
[ROW][C]54[/C][C]0.160589[/C][C]0.321178[/C][C]0.839411[/C][/ROW]
[ROW][C]55[/C][C]0.374493[/C][C]0.748985[/C][C]0.625507[/C][/ROW]
[ROW][C]56[/C][C]0.357321[/C][C]0.714642[/C][C]0.642679[/C][/ROW]
[ROW][C]57[/C][C]0.333124[/C][C]0.666247[/C][C]0.666876[/C][/ROW]
[ROW][C]58[/C][C]0.527732[/C][C]0.944536[/C][C]0.472268[/C][/ROW]
[ROW][C]59[/C][C]0.529499[/C][C]0.941003[/C][C]0.470501[/C][/ROW]
[ROW][C]60[/C][C]0.529386[/C][C]0.941228[/C][C]0.470614[/C][/ROW]
[ROW][C]61[/C][C]0.543105[/C][C]0.91379[/C][C]0.456895[/C][/ROW]
[ROW][C]62[/C][C]0.588538[/C][C]0.822923[/C][C]0.411462[/C][/ROW]
[ROW][C]63[/C][C]0.580883[/C][C]0.838234[/C][C]0.419117[/C][/ROW]
[ROW][C]64[/C][C]0.71968[/C][C]0.560641[/C][C]0.28032[/C][/ROW]
[ROW][C]65[/C][C]0.716763[/C][C]0.566474[/C][C]0.283237[/C][/ROW]
[ROW][C]66[/C][C]0.826065[/C][C]0.347869[/C][C]0.173935[/C][/ROW]
[ROW][C]67[/C][C]0.865068[/C][C]0.269864[/C][C]0.134932[/C][/ROW]
[ROW][C]68[/C][C]0.847843[/C][C]0.304313[/C][C]0.152157[/C][/ROW]
[ROW][C]69[/C][C]0.874865[/C][C]0.250269[/C][C]0.125135[/C][/ROW]
[ROW][C]70[/C][C]0.887485[/C][C]0.225029[/C][C]0.112515[/C][/ROW]
[ROW][C]71[/C][C]0.926283[/C][C]0.147435[/C][C]0.0737173[/C][/ROW]
[ROW][C]72[/C][C]0.934951[/C][C]0.130098[/C][C]0.0650488[/C][/ROW]
[ROW][C]73[/C][C]0.947169[/C][C]0.105662[/C][C]0.052831[/C][/ROW]
[ROW][C]74[/C][C]0.944429[/C][C]0.111143[/C][C]0.0555715[/C][/ROW]
[ROW][C]75[/C][C]0.965933[/C][C]0.0681337[/C][C]0.0340669[/C][/ROW]
[ROW][C]76[/C][C]0.972377[/C][C]0.055246[/C][C]0.027623[/C][/ROW]
[ROW][C]77[/C][C]0.966478[/C][C]0.0670437[/C][C]0.0335218[/C][/ROW]
[ROW][C]78[/C][C]0.963809[/C][C]0.0723818[/C][C]0.0361909[/C][/ROW]
[ROW][C]79[/C][C]0.962966[/C][C]0.0740672[/C][C]0.0370336[/C][/ROW]
[ROW][C]80[/C][C]0.974158[/C][C]0.0516843[/C][C]0.0258421[/C][/ROW]
[ROW][C]81[/C][C]0.97322[/C][C]0.0535601[/C][C]0.0267801[/C][/ROW]
[ROW][C]82[/C][C]0.975439[/C][C]0.0491217[/C][C]0.0245609[/C][/ROW]
[ROW][C]83[/C][C]0.973055[/C][C]0.0538903[/C][C]0.0269452[/C][/ROW]
[ROW][C]84[/C][C]0.969917[/C][C]0.0601651[/C][C]0.0300826[/C][/ROW]
[ROW][C]85[/C][C]0.964572[/C][C]0.0708557[/C][C]0.0354278[/C][/ROW]
[ROW][C]86[/C][C]0.956712[/C][C]0.0865757[/C][C]0.0432878[/C][/ROW]
[ROW][C]87[/C][C]0.949989[/C][C]0.100022[/C][C]0.0500109[/C][/ROW]
[ROW][C]88[/C][C]0.963563[/C][C]0.0728735[/C][C]0.0364367[/C][/ROW]
[ROW][C]89[/C][C]0.966136[/C][C]0.0677288[/C][C]0.0338644[/C][/ROW]
[ROW][C]90[/C][C]0.961165[/C][C]0.0776692[/C][C]0.0388346[/C][/ROW]
[ROW][C]91[/C][C]0.953799[/C][C]0.0924014[/C][C]0.0462007[/C][/ROW]
[ROW][C]92[/C][C]0.944939[/C][C]0.110122[/C][C]0.0550608[/C][/ROW]
[ROW][C]93[/C][C]0.973758[/C][C]0.0524831[/C][C]0.0262416[/C][/ROW]
[ROW][C]94[/C][C]0.973617[/C][C]0.0527662[/C][C]0.0263831[/C][/ROW]
[ROW][C]95[/C][C]0.972076[/C][C]0.0558484[/C][C]0.0279242[/C][/ROW]
[ROW][C]96[/C][C]0.969265[/C][C]0.0614704[/C][C]0.0307352[/C][/ROW]
[ROW][C]97[/C][C]0.965162[/C][C]0.0696763[/C][C]0.0348382[/C][/ROW]
[ROW][C]98[/C][C]0.966936[/C][C]0.0661288[/C][C]0.0330644[/C][/ROW]
[ROW][C]99[/C][C]0.961078[/C][C]0.0778433[/C][C]0.0389217[/C][/ROW]
[ROW][C]100[/C][C]0.957771[/C][C]0.0844581[/C][C]0.042229[/C][/ROW]
[ROW][C]101[/C][C]0.950647[/C][C]0.0987066[/C][C]0.0493533[/C][/ROW]
[ROW][C]102[/C][C]0.94807[/C][C]0.103859[/C][C]0.0519297[/C][/ROW]
[ROW][C]103[/C][C]0.944387[/C][C]0.111225[/C][C]0.0556126[/C][/ROW]
[ROW][C]104[/C][C]0.980951[/C][C]0.0380982[/C][C]0.0190491[/C][/ROW]
[ROW][C]105[/C][C]0.97978[/C][C]0.0404392[/C][C]0.0202196[/C][/ROW]
[ROW][C]106[/C][C]0.980157[/C][C]0.0396859[/C][C]0.0198429[/C][/ROW]
[ROW][C]107[/C][C]0.975457[/C][C]0.0490851[/C][C]0.0245426[/C][/ROW]
[ROW][C]108[/C][C]0.975689[/C][C]0.0486216[/C][C]0.0243108[/C][/ROW]
[ROW][C]109[/C][C]0.970267[/C][C]0.0594655[/C][C]0.0297328[/C][/ROW]
[ROW][C]110[/C][C]0.970601[/C][C]0.0587981[/C][C]0.029399[/C][/ROW]
[ROW][C]111[/C][C]0.965327[/C][C]0.069346[/C][C]0.034673[/C][/ROW]
[ROW][C]112[/C][C]0.963052[/C][C]0.0738957[/C][C]0.0369478[/C][/ROW]
[ROW][C]113[/C][C]0.955791[/C][C]0.0884173[/C][C]0.0442087[/C][/ROW]
[ROW][C]114[/C][C]0.97426[/C][C]0.0514802[/C][C]0.0257401[/C][/ROW]
[ROW][C]115[/C][C]0.970129[/C][C]0.0597415[/C][C]0.0298707[/C][/ROW]
[ROW][C]116[/C][C]0.970787[/C][C]0.0584255[/C][C]0.0292127[/C][/ROW]
[ROW][C]117[/C][C]0.993286[/C][C]0.0134288[/C][C]0.00671442[/C][/ROW]
[ROW][C]118[/C][C]0.995668[/C][C]0.00866355[/C][C]0.00433177[/C][/ROW]
[ROW][C]119[/C][C]0.994437[/C][C]0.0111256[/C][C]0.00556279[/C][/ROW]
[ROW][C]120[/C][C]0.994424[/C][C]0.0111525[/C][C]0.00557627[/C][/ROW]
[ROW][C]121[/C][C]0.996398[/C][C]0.00720394[/C][C]0.00360197[/C][/ROW]
[ROW][C]122[/C][C]0.9953[/C][C]0.00939931[/C][C]0.00469965[/C][/ROW]
[ROW][C]123[/C][C]0.995633[/C][C]0.00873345[/C][C]0.00436672[/C][/ROW]
[ROW][C]124[/C][C]0.994661[/C][C]0.0106787[/C][C]0.00533934[/C][/ROW]
[ROW][C]125[/C][C]0.996573[/C][C]0.00685427[/C][C]0.00342713[/C][/ROW]
[ROW][C]126[/C][C]0.996175[/C][C]0.00764994[/C][C]0.00382497[/C][/ROW]
[ROW][C]127[/C][C]0.995157[/C][C]0.00968501[/C][C]0.0048425[/C][/ROW]
[ROW][C]128[/C][C]0.993949[/C][C]0.012102[/C][C]0.00605098[/C][/ROW]
[ROW][C]129[/C][C]0.995059[/C][C]0.009881[/C][C]0.0049405[/C][/ROW]
[ROW][C]130[/C][C]0.994334[/C][C]0.0113328[/C][C]0.0056664[/C][/ROW]
[ROW][C]131[/C][C]0.994175[/C][C]0.011651[/C][C]0.0058255[/C][/ROW]
[ROW][C]132[/C][C]0.993438[/C][C]0.013124[/C][C]0.00656201[/C][/ROW]
[ROW][C]133[/C][C]0.995345[/C][C]0.00930978[/C][C]0.00465489[/C][/ROW]
[ROW][C]134[/C][C]0.994731[/C][C]0.0105389[/C][C]0.00526946[/C][/ROW]
[ROW][C]135[/C][C]0.993317[/C][C]0.0133669[/C][C]0.00668344[/C][/ROW]
[ROW][C]136[/C][C]0.992229[/C][C]0.0155427[/C][C]0.00777136[/C][/ROW]
[ROW][C]137[/C][C]0.990233[/C][C]0.0195341[/C][C]0.00976703[/C][/ROW]
[ROW][C]138[/C][C]0.989741[/C][C]0.0205181[/C][C]0.010259[/C][/ROW]
[ROW][C]139[/C][C]0.988[/C][C]0.0240003[/C][C]0.0120001[/C][/ROW]
[ROW][C]140[/C][C]0.993542[/C][C]0.0129166[/C][C]0.00645831[/C][/ROW]
[ROW][C]141[/C][C]0.991998[/C][C]0.016005[/C][C]0.00800248[/C][/ROW]
[ROW][C]142[/C][C]0.990412[/C][C]0.0191762[/C][C]0.00958809[/C][/ROW]
[ROW][C]143[/C][C]0.987643[/C][C]0.0247137[/C][C]0.0123568[/C][/ROW]
[ROW][C]144[/C][C]0.984882[/C][C]0.0302361[/C][C]0.0151181[/C][/ROW]
[ROW][C]145[/C][C]0.982397[/C][C]0.0352069[/C][C]0.0176034[/C][/ROW]
[ROW][C]146[/C][C]0.980542[/C][C]0.0389169[/C][C]0.0194584[/C][/ROW]
[ROW][C]147[/C][C]0.987966[/C][C]0.0240689[/C][C]0.0120344[/C][/ROW]
[ROW][C]148[/C][C]0.98532[/C][C]0.0293596[/C][C]0.0146798[/C][/ROW]
[ROW][C]149[/C][C]0.982972[/C][C]0.0340558[/C][C]0.0170279[/C][/ROW]
[ROW][C]150[/C][C]0.983043[/C][C]0.0339143[/C][C]0.0169572[/C][/ROW]
[ROW][C]151[/C][C]0.978413[/C][C]0.0431733[/C][C]0.0215866[/C][/ROW]
[ROW][C]152[/C][C]0.981757[/C][C]0.0364867[/C][C]0.0182434[/C][/ROW]
[ROW][C]153[/C][C]0.981382[/C][C]0.0372369[/C][C]0.0186184[/C][/ROW]
[ROW][C]154[/C][C]0.978702[/C][C]0.0425964[/C][C]0.0212982[/C][/ROW]
[ROW][C]155[/C][C]0.976641[/C][C]0.046718[/C][C]0.023359[/C][/ROW]
[ROW][C]156[/C][C]0.973704[/C][C]0.0525916[/C][C]0.0262958[/C][/ROW]
[ROW][C]157[/C][C]0.967392[/C][C]0.0652153[/C][C]0.0326076[/C][/ROW]
[ROW][C]158[/C][C]0.959918[/C][C]0.080164[/C][C]0.040082[/C][/ROW]
[ROW][C]159[/C][C]0.968788[/C][C]0.0624248[/C][C]0.0312124[/C][/ROW]
[ROW][C]160[/C][C]0.967222[/C][C]0.0655557[/C][C]0.0327778[/C][/ROW]
[ROW][C]161[/C][C]0.964756[/C][C]0.0704871[/C][C]0.0352435[/C][/ROW]
[ROW][C]162[/C][C]0.956362[/C][C]0.0872768[/C][C]0.0436384[/C][/ROW]
[ROW][C]163[/C][C]0.951971[/C][C]0.0960579[/C][C]0.048029[/C][/ROW]
[ROW][C]164[/C][C]0.94765[/C][C]0.1047[/C][C]0.0523499[/C][/ROW]
[ROW][C]165[/C][C]0.936913[/C][C]0.126173[/C][C]0.0630867[/C][/ROW]
[ROW][C]166[/C][C]0.925841[/C][C]0.148319[/C][C]0.0741593[/C][/ROW]
[ROW][C]167[/C][C]0.939772[/C][C]0.120456[/C][C]0.0602281[/C][/ROW]
[ROW][C]168[/C][C]0.93108[/C][C]0.137841[/C][C]0.0689203[/C][/ROW]
[ROW][C]169[/C][C]0.926818[/C][C]0.146365[/C][C]0.0731823[/C][/ROW]
[ROW][C]170[/C][C]0.914729[/C][C]0.170542[/C][C]0.0852712[/C][/ROW]
[ROW][C]171[/C][C]0.911552[/C][C]0.176897[/C][C]0.0884483[/C][/ROW]
[ROW][C]172[/C][C]0.897289[/C][C]0.205422[/C][C]0.102711[/C][/ROW]
[ROW][C]173[/C][C]0.884737[/C][C]0.230526[/C][C]0.115263[/C][/ROW]
[ROW][C]174[/C][C]0.861823[/C][C]0.276354[/C][C]0.138177[/C][/ROW]
[ROW][C]175[/C][C]0.835785[/C][C]0.32843[/C][C]0.164215[/C][/ROW]
[ROW][C]176[/C][C]0.819212[/C][C]0.361576[/C][C]0.180788[/C][/ROW]
[ROW][C]177[/C][C]0.84816[/C][C]0.30368[/C][C]0.15184[/C][/ROW]
[ROW][C]178[/C][C]0.820192[/C][C]0.359616[/C][C]0.179808[/C][/ROW]
[ROW][C]179[/C][C]0.82023[/C][C]0.359541[/C][C]0.17977[/C][/ROW]
[ROW][C]180[/C][C]0.804399[/C][C]0.391203[/C][C]0.195601[/C][/ROW]
[ROW][C]181[/C][C]0.862017[/C][C]0.275966[/C][C]0.137983[/C][/ROW]
[ROW][C]182[/C][C]0.8741[/C][C]0.2518[/C][C]0.1259[/C][/ROW]
[ROW][C]183[/C][C]0.890853[/C][C]0.218294[/C][C]0.109147[/C][/ROW]
[ROW][C]184[/C][C]0.876843[/C][C]0.246314[/C][C]0.123157[/C][/ROW]
[ROW][C]185[/C][C]0.8895[/C][C]0.221001[/C][C]0.1105[/C][/ROW]
[ROW][C]186[/C][C]0.916316[/C][C]0.167369[/C][C]0.0836843[/C][/ROW]
[ROW][C]187[/C][C]0.898866[/C][C]0.202268[/C][C]0.101134[/C][/ROW]
[ROW][C]188[/C][C]0.87999[/C][C]0.24002[/C][C]0.12001[/C][/ROW]
[ROW][C]189[/C][C]0.873677[/C][C]0.252645[/C][C]0.126323[/C][/ROW]
[ROW][C]190[/C][C]0.871976[/C][C]0.256047[/C][C]0.128024[/C][/ROW]
[ROW][C]191[/C][C]0.955834[/C][C]0.0883313[/C][C]0.0441656[/C][/ROW]
[ROW][C]192[/C][C]0.951804[/C][C]0.0963911[/C][C]0.0481956[/C][/ROW]
[ROW][C]193[/C][C]0.951718[/C][C]0.0965648[/C][C]0.0482824[/C][/ROW]
[ROW][C]194[/C][C]0.939324[/C][C]0.121353[/C][C]0.0606764[/C][/ROW]
[ROW][C]195[/C][C]0.921552[/C][C]0.156896[/C][C]0.0784482[/C][/ROW]
[ROW][C]196[/C][C]0.91009[/C][C]0.17982[/C][C]0.0899102[/C][/ROW]
[ROW][C]197[/C][C]0.892026[/C][C]0.215948[/C][C]0.107974[/C][/ROW]
[ROW][C]198[/C][C]0.883538[/C][C]0.232923[/C][C]0.116462[/C][/ROW]
[ROW][C]199[/C][C]0.876333[/C][C]0.247335[/C][C]0.123667[/C][/ROW]
[ROW][C]200[/C][C]0.932148[/C][C]0.135703[/C][C]0.0678517[/C][/ROW]
[ROW][C]201[/C][C]0.910774[/C][C]0.178451[/C][C]0.0892257[/C][/ROW]
[ROW][C]202[/C][C]0.887657[/C][C]0.224685[/C][C]0.112343[/C][/ROW]
[ROW][C]203[/C][C]0.863385[/C][C]0.27323[/C][C]0.136615[/C][/ROW]
[ROW][C]204[/C][C]0.834646[/C][C]0.330709[/C][C]0.165354[/C][/ROW]
[ROW][C]205[/C][C]0.795548[/C][C]0.408904[/C][C]0.204452[/C][/ROW]
[ROW][C]206[/C][C]0.748056[/C][C]0.503888[/C][C]0.251944[/C][/ROW]
[ROW][C]207[/C][C]0.70769[/C][C]0.584619[/C][C]0.29231[/C][/ROW]
[ROW][C]208[/C][C]0.709368[/C][C]0.581263[/C][C]0.290632[/C][/ROW]
[ROW][C]209[/C][C]0.650833[/C][C]0.698333[/C][C]0.349167[/C][/ROW]
[ROW][C]210[/C][C]0.591047[/C][C]0.817906[/C][C]0.408953[/C][/ROW]
[ROW][C]211[/C][C]0.63116[/C][C]0.73768[/C][C]0.36884[/C][/ROW]
[ROW][C]212[/C][C]0.566047[/C][C]0.867906[/C][C]0.433953[/C][/ROW]
[ROW][C]213[/C][C]0.559584[/C][C]0.880832[/C][C]0.440416[/C][/ROW]
[ROW][C]214[/C][C]0.92677[/C][C]0.146459[/C][C]0.0732296[/C][/ROW]
[ROW][C]215[/C][C]0.894062[/C][C]0.211877[/C][C]0.105938[/C][/ROW]
[ROW][C]216[/C][C]0.996153[/C][C]0.00769447[/C][C]0.00384724[/C][/ROW]
[ROW][C]217[/C][C]0.994054[/C][C]0.0118912[/C][C]0.00594559[/C][/ROW]
[ROW][C]218[/C][C]0.990999[/C][C]0.0180012[/C][C]0.00900062[/C][/ROW]
[ROW][C]219[/C][C]0.999947[/C][C]0.000105915[/C][C]5.29577e-05[/C][/ROW]
[ROW][C]220[/C][C]0.999838[/C][C]0.000324171[/C][C]0.000162086[/C][/ROW]
[ROW][C]221[/C][C]0.999699[/C][C]0.000601138[/C][C]0.000300569[/C][/ROW]
[ROW][C]222[/C][C]0.999403[/C][C]0.00119374[/C][C]0.000596869[/C][/ROW]
[ROW][C]223[/C][C]0.999419[/C][C]0.00116136[/C][C]0.00058068[/C][/ROW]
[ROW][C]224[/C][C]0.998462[/C][C]0.00307564[/C][C]0.00153782[/C][/ROW]
[ROW][C]225[/C][C]0.997616[/C][C]0.00476728[/C][C]0.00238364[/C][/ROW]
[ROW][C]226[/C][C]0.990009[/C][C]0.0199826[/C][C]0.00999129[/C][/ROW]
[ROW][C]227[/C][C]0.981939[/C][C]0.0361227[/C][C]0.0180614[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265184&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265184&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
70.9052690.1894610.0947305
80.8362940.3274120.163706
90.8307720.3384560.169228
100.7502860.4994290.249714
110.8132490.3735020.186751
120.7404680.5190650.259532
130.6642260.6715480.335774
140.7016630.5966730.298337
150.638140.723720.36186
160.5617570.8764850.438243
170.4819420.9638840.518058
180.5913990.8172020.408601
190.5688150.862370.431185
200.5026740.9946520.497326
210.4873710.9747420.512629
220.592970.814060.40703
230.5754890.8490230.424511
240.5206280.9587450.479372
250.4930130.9860260.506987
260.4589680.9179360.541032
270.4190520.8381030.580948
280.3737490.7474990.626251
290.324050.6480990.67595
300.3577590.7155190.642241
310.3204030.6408060.679597
320.2892240.5784480.710776
330.25270.5053990.7473
340.2519760.5039530.748024
350.2219330.4438670.778067
360.191880.3837610.80812
370.1663770.3327540.833623
380.1496360.2992720.850364
390.150070.300140.84993
400.131020.262040.86898
410.1547140.3094280.845286
420.1805160.3610320.819484
430.1633120.3266250.836688
440.1955220.3910450.804478
450.2099510.4199030.790049
460.2355610.4711220.764439
470.2173980.4347960.782602
480.199140.398280.80086
490.1861690.3723380.813831
500.1751780.3503560.824822
510.1652980.3305960.834702
520.2134610.4269230.786539
530.1852390.3704790.814761
540.1605890.3211780.839411
550.3744930.7489850.625507
560.3573210.7146420.642679
570.3331240.6662470.666876
580.5277320.9445360.472268
590.5294990.9410030.470501
600.5293860.9412280.470614
610.5431050.913790.456895
620.5885380.8229230.411462
630.5808830.8382340.419117
640.719680.5606410.28032
650.7167630.5664740.283237
660.8260650.3478690.173935
670.8650680.2698640.134932
680.8478430.3043130.152157
690.8748650.2502690.125135
700.8874850.2250290.112515
710.9262830.1474350.0737173
720.9349510.1300980.0650488
730.9471690.1056620.052831
740.9444290.1111430.0555715
750.9659330.06813370.0340669
760.9723770.0552460.027623
770.9664780.06704370.0335218
780.9638090.07238180.0361909
790.9629660.07406720.0370336
800.9741580.05168430.0258421
810.973220.05356010.0267801
820.9754390.04912170.0245609
830.9730550.05389030.0269452
840.9699170.06016510.0300826
850.9645720.07085570.0354278
860.9567120.08657570.0432878
870.9499890.1000220.0500109
880.9635630.07287350.0364367
890.9661360.06772880.0338644
900.9611650.07766920.0388346
910.9537990.09240140.0462007
920.9449390.1101220.0550608
930.9737580.05248310.0262416
940.9736170.05276620.0263831
950.9720760.05584840.0279242
960.9692650.06147040.0307352
970.9651620.06967630.0348382
980.9669360.06612880.0330644
990.9610780.07784330.0389217
1000.9577710.08445810.042229
1010.9506470.09870660.0493533
1020.948070.1038590.0519297
1030.9443870.1112250.0556126
1040.9809510.03809820.0190491
1050.979780.04043920.0202196
1060.9801570.03968590.0198429
1070.9754570.04908510.0245426
1080.9756890.04862160.0243108
1090.9702670.05946550.0297328
1100.9706010.05879810.029399
1110.9653270.0693460.034673
1120.9630520.07389570.0369478
1130.9557910.08841730.0442087
1140.974260.05148020.0257401
1150.9701290.05974150.0298707
1160.9707870.05842550.0292127
1170.9932860.01342880.00671442
1180.9956680.008663550.00433177
1190.9944370.01112560.00556279
1200.9944240.01115250.00557627
1210.9963980.007203940.00360197
1220.99530.009399310.00469965
1230.9956330.008733450.00436672
1240.9946610.01067870.00533934
1250.9965730.006854270.00342713
1260.9961750.007649940.00382497
1270.9951570.009685010.0048425
1280.9939490.0121020.00605098
1290.9950590.0098810.0049405
1300.9943340.01133280.0056664
1310.9941750.0116510.0058255
1320.9934380.0131240.00656201
1330.9953450.009309780.00465489
1340.9947310.01053890.00526946
1350.9933170.01336690.00668344
1360.9922290.01554270.00777136
1370.9902330.01953410.00976703
1380.9897410.02051810.010259
1390.9880.02400030.0120001
1400.9935420.01291660.00645831
1410.9919980.0160050.00800248
1420.9904120.01917620.00958809
1430.9876430.02471370.0123568
1440.9848820.03023610.0151181
1450.9823970.03520690.0176034
1460.9805420.03891690.0194584
1470.9879660.02406890.0120344
1480.985320.02935960.0146798
1490.9829720.03405580.0170279
1500.9830430.03391430.0169572
1510.9784130.04317330.0215866
1520.9817570.03648670.0182434
1530.9813820.03723690.0186184
1540.9787020.04259640.0212982
1550.9766410.0467180.023359
1560.9737040.05259160.0262958
1570.9673920.06521530.0326076
1580.9599180.0801640.040082
1590.9687880.06242480.0312124
1600.9672220.06555570.0327778
1610.9647560.07048710.0352435
1620.9563620.08727680.0436384
1630.9519710.09605790.048029
1640.947650.10470.0523499
1650.9369130.1261730.0630867
1660.9258410.1483190.0741593
1670.9397720.1204560.0602281
1680.931080.1378410.0689203
1690.9268180.1463650.0731823
1700.9147290.1705420.0852712
1710.9115520.1768970.0884483
1720.8972890.2054220.102711
1730.8847370.2305260.115263
1740.8618230.2763540.138177
1750.8357850.328430.164215
1760.8192120.3615760.180788
1770.848160.303680.15184
1780.8201920.3596160.179808
1790.820230.3595410.17977
1800.8043990.3912030.195601
1810.8620170.2759660.137983
1820.87410.25180.1259
1830.8908530.2182940.109147
1840.8768430.2463140.123157
1850.88950.2210010.1105
1860.9163160.1673690.0836843
1870.8988660.2022680.101134
1880.879990.240020.12001
1890.8736770.2526450.126323
1900.8719760.2560470.128024
1910.9558340.08833130.0441656
1920.9518040.09639110.0481956
1930.9517180.09656480.0482824
1940.9393240.1213530.0606764
1950.9215520.1568960.0784482
1960.910090.179820.0899102
1970.8920260.2159480.107974
1980.8835380.2329230.116462
1990.8763330.2473350.123667
2000.9321480.1357030.0678517
2010.9107740.1784510.0892257
2020.8876570.2246850.112343
2030.8633850.273230.136615
2040.8346460.3307090.165354
2050.7955480.4089040.204452
2060.7480560.5038880.251944
2070.707690.5846190.29231
2080.7093680.5812630.290632
2090.6508330.6983330.349167
2100.5910470.8179060.408953
2110.631160.737680.36884
2120.5660470.8679060.433953
2130.5595840.8808320.440416
2140.926770.1464590.0732296
2150.8940620.2118770.105938
2160.9961530.007694470.00384724
2170.9940540.01189120.00594559
2180.9909990.01800120.00900062
2190.9999470.0001059155.29577e-05
2200.9998380.0003241710.000162086
2210.9996990.0006011380.000300569
2220.9994030.001193740.000596869
2230.9994190.001161360.00058068
2240.9984620.003075640.00153782
2250.9976160.004767280.00238364
2260.9900090.01998260.00999129
2270.9819390.03612270.0180614






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level170.0769231NOK
5% type I error level570.257919NOK
10% type I error level1000.452489NOK

\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 & 17 & 0.0769231 & NOK \tabularnewline
5% type I error level & 57 & 0.257919 & NOK \tabularnewline
10% type I error level & 100 & 0.452489 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265184&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]17[/C][C]0.0769231[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]57[/C][C]0.257919[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]100[/C][C]0.452489[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265184&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265184&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 level170.0769231NOK
5% type I error level570.257919NOK
10% type I error level1000.452489NOK


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')
}