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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 15 Dec 2014 13:05:02 +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/15/t1418648768guezocpff9eoal4.htm/, Retrieved Thu, 16 May 2024 17:28:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268302, Retrieved Thu, 16 May 2024 17:28:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact50

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Invloed van CH en...] [2014-12-15 13:05:02] [5848e943dc403117a4a7bf00dc78acfc] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'George Udny Yule' @ yule.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 & 8 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268302&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268302&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268302&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 time8 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 9.12431 + 0.0148375LFM[t] + 0.0512547CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  9.12431 +  0.0148375LFM[t] +  0.0512547CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268302&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  9.12431 +  0.0148375LFM[t] +  0.0512547CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268302&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268302&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] = + 9.12431 + 0.0148375LFM[t] + 0.0512547CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.124310.60795615.011.32982e-376.6491e-38
LFM0.01483750.005269512.8160.005218920.00260946
CH0.05125470.01100884.6565.02737e-062.51368e-06

\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) & 9.12431 & 0.607956 & 15.01 & 1.32982e-37 & 6.6491e-38 \tabularnewline
LFM & 0.0148375 & 0.00526951 & 2.816 & 0.00521892 & 0.00260946 \tabularnewline
CH & 0.0512547 & 0.0110088 & 4.656 & 5.02737e-06 & 2.51368e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268302&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]9.12431[/C][C]0.607956[/C][C]15.01[/C][C]1.32982e-37[/C][C]6.6491e-38[/C][/ROW]
[ROW][C]LFM[/C][C]0.0148375[/C][C]0.00526951[/C][C]2.816[/C][C]0.00521892[/C][C]0.00260946[/C][/ROW]
[ROW][C]CH[/C][C]0.0512547[/C][C]0.0110088[/C][C]4.656[/C][C]5.02737e-06[/C][C]2.51368e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268302&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268302&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)9.124310.60795615.011.32982e-376.6491e-38
LFM0.01483750.005269512.8160.005218920.00260946
CH0.05125470.01100884.6565.02737e-062.51368e-06






Multiple Linear Regression - Regression Statistics
Multiple R0.397467
R-squared0.15798
Adjusted R-squared0.151856
F-TEST (value)25.7978
F-TEST (DF numerator)2
F-TEST (DF denominator)275
p-value5.3928e-11
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.12603
Sum Squared Residuals2687.31

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.397467 \tabularnewline
R-squared & 0.15798 \tabularnewline
Adjusted R-squared & 0.151856 \tabularnewline
F-TEST (value) & 25.7978 \tabularnewline
F-TEST (DF numerator) & 2 \tabularnewline
F-TEST (DF denominator) & 275 \tabularnewline
p-value & 5.3928e-11 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.12603 \tabularnewline
Sum Squared Residuals & 2687.31 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268302&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.397467[/C][/ROW]
[ROW][C]R-squared[/C][C]0.15798[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.151856[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]25.7978[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]2[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]275[/C][/ROW]
[ROW][C]p-value[/C][C]5.3928e-11[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.12603[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2687.31[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268302&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268302&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 R0.397467
R-squared0.15798
Adjusted R-squared0.151856
F-TEST (value)25.7978
F-TEST (DF numerator)2
F-TEST (DF denominator)275
p-value5.3928e-11
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.12603
Sum Squared Residuals2687.31






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.8204-1.92041
212.213.1857-0.98565
312.812.9604-0.160405
47.414.6464-7.24642
56.712.7149-6.01491
612.615.1131-2.51315
714.814.66130.138743
813.314.6289-1.32885
911.115.3788-4.27882
108.213.7036-5.50361
1111.414.0327-2.63272
126.414.7125-8.31251
1310.612.4276-1.82761
141215.7336-3.73357
156.310.8994-4.59937
1611.312.0634-0.763415
1711.914.9256-3.02563
189.312.7581-3.45807
199.613.3097-3.70974
201013.2261-3.2261
216.412.4708-6.07079
2213.812.60161.19838
2310.814.6586-3.8586
2413.815.4503-1.65033
2511.714.1028-2.40284
2610.916.5375-5.6375
2716.115.42060.679371
2813.412.64210.757946
299.914.4765-4.57647
3011.513.4959-1.99588
318.312.8767-4.57675
3211.713.4379-1.73789
33912.8255-3.82551
349.714.1271-4.42713
3510.812.8349-2.03494
3610.312.1524-1.85244
3710.413.3637-2.9637
3812.712.09310.606888
399.314.0988-4.79881
4011.814.1703-2.37029
415.912.3602-6.46016
4211.413.2747-1.87468
431314.2957-1.29573
4410.814.0543-3.2543
4512.311.74240.55762
4611.314.2566-2.95663
4711.813.5606-1.7606
487.912.6124-4.71238
4912.713.245-0.544978
5012.311.02211.27787
5111.612.7419-1.14188
526.711.0289-4.32885
5310.912.8579-1.9579
5412.112.8592-0.759248
5513.313.28550.0145462
5610.112.6394-2.53937
575.712.4586-6.75864
5814.313.27331.02668
59810.1589-2.15887
6013.312.85520.444833
619.315.2992-5.99925
6212.512.39930.100691
637.612.6434-5.04341
6415.915.40180.498223
659.213.7805-4.5805
669.111.385-2.28495
6711.115.1711-4.07112
681317.425-4.42499
6914.513.34891.15112
7012.212.4613-0.26132
7112.314.6208-2.3208
7211.412.4802-1.08022
738.812.4559-3.65591
7414.613.61720.982755
7512.613.7495-1.14945
76NANA-1.55201
771312.51060.489367
7812.614.01-1.41
7913.214.9574-1.75741
809.915.5704-5.67042
817.79.54262-1.84262
8210.59.431841.06816
8313.415.3754-1.97539
8410.918.4449-7.54491
854.37.26387-2.96387
8610.312.4774-2.17738
8711.812.5515-0.751457
8811.211.04740.152623
8911.414.7097-3.30965
908.68.240350.359648
9113.212.41120.788822
9212.619.1484-6.5484
935.69.87433-4.27433
949.912.8127-2.91273
958.812.7547-3.95473
967.710.696-2.99599
97914.3852-5.38524
987.37.298460.00154303
9911.49.358962.04104
10013.618.3529-4.75285
1017.99.15685-1.25685
10210.712.7291-2.02914
10310.313.7842-3.48421
1048.311.8546-3.55462
1059.67.998891.60111
10614.218.1316-3.93165
1078.57.043191.45681
10813.520.7592-7.25918
1094.99.52346-4.62346
1106.49.63359-3.23359
1119.610.259-0.659008
11211.611.9645-0.364549
11311.117.2016-6.10157
1144.353.822640.527356
11512.77.846354.85365
11618.113.55574.5443
11717.8517.52710.322901
11816.614.64581.95419
11912.610.98811.6119
12017.113.1593.94103
12119.121.8129-2.71289
12216.113.32972.77029
12313.359.074424.27558
12418.414.27434.1257
12514.716.6045-1.90448
12610.610.15510.444855
12712.69.46833.1317
12816.216.19570.00433456
12913.69.150834.44917
13018.916.49922.40076
13114.111.38962.71038
13214.513.92040.579644
13316.1514.00972.1403
13414.7513.18151.56851
13514.813.9710.829003
13612.4512.34490.105066
13712.657.757284.89272
13817.3519.6305-2.28048
1398.65.08653.5135
14018.416.85061.54937
14116.115.85660.243372
14211.66.08885.5112
14317.7517.03580.714185
14415.2510.79784.45222
14517.6515.24912.40092
14616.3513.40982.94019
14717.6516.80.850025
14813.612.24681.3532
14914.3512.98931.36068
15014.759.919014.83099
15118.2521.827-3.57701
1529.98.406121.49388
1531611.18794.81211
15418.2515.28032.96969
15516.8513.66463.18537
15614.614.06510.534893
15713.8510.60253.24746
15818.9516.20112.74887
15915.615.32220.27779
16014.8515.1243-0.274292
16111.757.865473.88453
16218.4515.11793.33213
16315.913.61772.28227
16417.111.33285.76716
16516.111.52084.57917
16619.919.62140.278579
16710.956.817294.13271
16818.4514.364.09
16915.112.80952.2905
1701516.9125-1.9125
17111.358.468282.88172
17215.9511.29464.65539
17318.117.43290.667109
17414.612.25892.34112
17515.413.05892.34112
17615.411.37544.02456
17717.617.8929-0.292884
17813.357.922585.42742
17919.117.65461.44543
18015.3518.6264-3.27644
1817.68.7088-1.1088
18213.412.41860.981424
18313.99.350654.54935
18419.117.33641.76359
18515.2515.19310.056942
18612.910.37542.52456
18716.110.60445.49564
18817.3516.89740.452633
18913.1511.93311.21687
19012.1511.52710.622926
19112.613.6484-1.04843
19210.358.561861.78814
19315.417.2146-1.81463
1949.64.17025.4298
19518.216.55821.6418
19613.611.16142.4386
19714.8514.38630.463716
19814.7513.29881.4512
19914.110.66053.43951
20014.911.66163.23836
20116.2512.15634.0937
20219.2517.17392.07612
20313.613.06160.538439
20413.610.80922.79077
20515.6514.65460.995444
20612.759.387933.36207
20714.616.5773-1.97735
2089.858.325971.52403
20912.658.515884.13412
21019.216.14443.05559
21116.617.0439-0.443907
21211.28.713482.48652
21315.2517.1885-1.93845
21411.910.35071.54933
21513.211.79591.40415
21616.3516.34520.00477168
21712.49.353913.04609
21815.8511.16354.68647
21918.1518.969-0.818978
22011.158.900092.24991
22115.6510.88874.76127
22217.7521.5402-3.79024
2237.656.722740.927257
22412.358.433073.91693
22515.610.51625.08384
22619.315.28534.01468
22715.210.23094.96912
22817.113.4383.66203
22915.612.27133.32873
23018.412.83785.56221
23119.0513.24465.80539
23218.5515.00823.5418
23319.117.81391.28612
23413.113.1484-0.0483713
23512.8514.9966-2.14664
2369.515.8549-6.35486
2374.53.204071.29593
23811.8511.83220.0177969
23913.614.31-0.710044
24011.711.12060.579374
24112.412.4056-0.00558245
24213.3514.1105-0.760513
24311.48.726632.67337
24414.910.32084.57917
24519.920.0742-0.174171
24611.210.02981.17023
24714.612.29922.30075
24817.615.67011.92992
24914.0512.07041.97963
25016.115.01171.08829
25113.3513.4488-0.098796
25211.8513.0236-1.17357
25311.9510.3331.61698
25414.7513.10391.64607
25515.1515.3825-0.232498
25613.210.13053.06954
25716.8520.304-3.45402
2587.8511.9868-4.13682
2597.78.53516-0.835159
26012.617.4312-4.83118
2617.857.571420.278579
26210.9510.87520.0748243
26312.3514.5228-2.17276
2649.957.276632.67337
26514.910.99593.90408
26616.6515.3081.342
26713.410.98332.41668
26813.9510.58053.36951
26915.711.6584.04203
27016.8517.4589-0.608941
27110.957.376143.57386
27215.3514.4850.864952
27312.210.39351.80647
27415.111.25453.84545
27517.7515.84621.90377
27615.212.99792.20207
27714.611.35143.24855
27816.6518.9543-2.30435
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 14.8204 & -1.92041 \tabularnewline
2 & 12.2 & 13.1857 & -0.98565 \tabularnewline
3 & 12.8 & 12.9604 & -0.160405 \tabularnewline
4 & 7.4 & 14.6464 & -7.24642 \tabularnewline
5 & 6.7 & 12.7149 & -6.01491 \tabularnewline
6 & 12.6 & 15.1131 & -2.51315 \tabularnewline
7 & 14.8 & 14.6613 & 0.138743 \tabularnewline
8 & 13.3 & 14.6289 & -1.32885 \tabularnewline
9 & 11.1 & 15.3788 & -4.27882 \tabularnewline
10 & 8.2 & 13.7036 & -5.50361 \tabularnewline
11 & 11.4 & 14.0327 & -2.63272 \tabularnewline
12 & 6.4 & 14.7125 & -8.31251 \tabularnewline
13 & 10.6 & 12.4276 & -1.82761 \tabularnewline
14 & 12 & 15.7336 & -3.73357 \tabularnewline
15 & 6.3 & 10.8994 & -4.59937 \tabularnewline
16 & 11.3 & 12.0634 & -0.763415 \tabularnewline
17 & 11.9 & 14.9256 & -3.02563 \tabularnewline
18 & 9.3 & 12.7581 & -3.45807 \tabularnewline
19 & 9.6 & 13.3097 & -3.70974 \tabularnewline
20 & 10 & 13.2261 & -3.2261 \tabularnewline
21 & 6.4 & 12.4708 & -6.07079 \tabularnewline
22 & 13.8 & 12.6016 & 1.19838 \tabularnewline
23 & 10.8 & 14.6586 & -3.8586 \tabularnewline
24 & 13.8 & 15.4503 & -1.65033 \tabularnewline
25 & 11.7 & 14.1028 & -2.40284 \tabularnewline
26 & 10.9 & 16.5375 & -5.6375 \tabularnewline
27 & 16.1 & 15.4206 & 0.679371 \tabularnewline
28 & 13.4 & 12.6421 & 0.757946 \tabularnewline
29 & 9.9 & 14.4765 & -4.57647 \tabularnewline
30 & 11.5 & 13.4959 & -1.99588 \tabularnewline
31 & 8.3 & 12.8767 & -4.57675 \tabularnewline
32 & 11.7 & 13.4379 & -1.73789 \tabularnewline
33 & 9 & 12.8255 & -3.82551 \tabularnewline
34 & 9.7 & 14.1271 & -4.42713 \tabularnewline
35 & 10.8 & 12.8349 & -2.03494 \tabularnewline
36 & 10.3 & 12.1524 & -1.85244 \tabularnewline
37 & 10.4 & 13.3637 & -2.9637 \tabularnewline
38 & 12.7 & 12.0931 & 0.606888 \tabularnewline
39 & 9.3 & 14.0988 & -4.79881 \tabularnewline
40 & 11.8 & 14.1703 & -2.37029 \tabularnewline
41 & 5.9 & 12.3602 & -6.46016 \tabularnewline
42 & 11.4 & 13.2747 & -1.87468 \tabularnewline
43 & 13 & 14.2957 & -1.29573 \tabularnewline
44 & 10.8 & 14.0543 & -3.2543 \tabularnewline
45 & 12.3 & 11.7424 & 0.55762 \tabularnewline
46 & 11.3 & 14.2566 & -2.95663 \tabularnewline
47 & 11.8 & 13.5606 & -1.7606 \tabularnewline
48 & 7.9 & 12.6124 & -4.71238 \tabularnewline
49 & 12.7 & 13.245 & -0.544978 \tabularnewline
50 & 12.3 & 11.0221 & 1.27787 \tabularnewline
51 & 11.6 & 12.7419 & -1.14188 \tabularnewline
52 & 6.7 & 11.0289 & -4.32885 \tabularnewline
53 & 10.9 & 12.8579 & -1.9579 \tabularnewline
54 & 12.1 & 12.8592 & -0.759248 \tabularnewline
55 & 13.3 & 13.2855 & 0.0145462 \tabularnewline
56 & 10.1 & 12.6394 & -2.53937 \tabularnewline
57 & 5.7 & 12.4586 & -6.75864 \tabularnewline
58 & 14.3 & 13.2733 & 1.02668 \tabularnewline
59 & 8 & 10.1589 & -2.15887 \tabularnewline
60 & 13.3 & 12.8552 & 0.444833 \tabularnewline
61 & 9.3 & 15.2992 & -5.99925 \tabularnewline
62 & 12.5 & 12.3993 & 0.100691 \tabularnewline
63 & 7.6 & 12.6434 & -5.04341 \tabularnewline
64 & 15.9 & 15.4018 & 0.498223 \tabularnewline
65 & 9.2 & 13.7805 & -4.5805 \tabularnewline
66 & 9.1 & 11.385 & -2.28495 \tabularnewline
67 & 11.1 & 15.1711 & -4.07112 \tabularnewline
68 & 13 & 17.425 & -4.42499 \tabularnewline
69 & 14.5 & 13.3489 & 1.15112 \tabularnewline
70 & 12.2 & 12.4613 & -0.26132 \tabularnewline
71 & 12.3 & 14.6208 & -2.3208 \tabularnewline
72 & 11.4 & 12.4802 & -1.08022 \tabularnewline
73 & 8.8 & 12.4559 & -3.65591 \tabularnewline
74 & 14.6 & 13.6172 & 0.982755 \tabularnewline
75 & 12.6 & 13.7495 & -1.14945 \tabularnewline
76 & NA & NA & -1.55201 \tabularnewline
77 & 13 & 12.5106 & 0.489367 \tabularnewline
78 & 12.6 & 14.01 & -1.41 \tabularnewline
79 & 13.2 & 14.9574 & -1.75741 \tabularnewline
80 & 9.9 & 15.5704 & -5.67042 \tabularnewline
81 & 7.7 & 9.54262 & -1.84262 \tabularnewline
82 & 10.5 & 9.43184 & 1.06816 \tabularnewline
83 & 13.4 & 15.3754 & -1.97539 \tabularnewline
84 & 10.9 & 18.4449 & -7.54491 \tabularnewline
85 & 4.3 & 7.26387 & -2.96387 \tabularnewline
86 & 10.3 & 12.4774 & -2.17738 \tabularnewline
87 & 11.8 & 12.5515 & -0.751457 \tabularnewline
88 & 11.2 & 11.0474 & 0.152623 \tabularnewline
89 & 11.4 & 14.7097 & -3.30965 \tabularnewline
90 & 8.6 & 8.24035 & 0.359648 \tabularnewline
91 & 13.2 & 12.4112 & 0.788822 \tabularnewline
92 & 12.6 & 19.1484 & -6.5484 \tabularnewline
93 & 5.6 & 9.87433 & -4.27433 \tabularnewline
94 & 9.9 & 12.8127 & -2.91273 \tabularnewline
95 & 8.8 & 12.7547 & -3.95473 \tabularnewline
96 & 7.7 & 10.696 & -2.99599 \tabularnewline
97 & 9 & 14.3852 & -5.38524 \tabularnewline
98 & 7.3 & 7.29846 & 0.00154303 \tabularnewline
99 & 11.4 & 9.35896 & 2.04104 \tabularnewline
100 & 13.6 & 18.3529 & -4.75285 \tabularnewline
101 & 7.9 & 9.15685 & -1.25685 \tabularnewline
102 & 10.7 & 12.7291 & -2.02914 \tabularnewline
103 & 10.3 & 13.7842 & -3.48421 \tabularnewline
104 & 8.3 & 11.8546 & -3.55462 \tabularnewline
105 & 9.6 & 7.99889 & 1.60111 \tabularnewline
106 & 14.2 & 18.1316 & -3.93165 \tabularnewline
107 & 8.5 & 7.04319 & 1.45681 \tabularnewline
108 & 13.5 & 20.7592 & -7.25918 \tabularnewline
109 & 4.9 & 9.52346 & -4.62346 \tabularnewline
110 & 6.4 & 9.63359 & -3.23359 \tabularnewline
111 & 9.6 & 10.259 & -0.659008 \tabularnewline
112 & 11.6 & 11.9645 & -0.364549 \tabularnewline
113 & 11.1 & 17.2016 & -6.10157 \tabularnewline
114 & 4.35 & 3.82264 & 0.527356 \tabularnewline
115 & 12.7 & 7.84635 & 4.85365 \tabularnewline
116 & 18.1 & 13.5557 & 4.5443 \tabularnewline
117 & 17.85 & 17.5271 & 0.322901 \tabularnewline
118 & 16.6 & 14.6458 & 1.95419 \tabularnewline
119 & 12.6 & 10.9881 & 1.6119 \tabularnewline
120 & 17.1 & 13.159 & 3.94103 \tabularnewline
121 & 19.1 & 21.8129 & -2.71289 \tabularnewline
122 & 16.1 & 13.3297 & 2.77029 \tabularnewline
123 & 13.35 & 9.07442 & 4.27558 \tabularnewline
124 & 18.4 & 14.2743 & 4.1257 \tabularnewline
125 & 14.7 & 16.6045 & -1.90448 \tabularnewline
126 & 10.6 & 10.1551 & 0.444855 \tabularnewline
127 & 12.6 & 9.4683 & 3.1317 \tabularnewline
128 & 16.2 & 16.1957 & 0.00433456 \tabularnewline
129 & 13.6 & 9.15083 & 4.44917 \tabularnewline
130 & 18.9 & 16.4992 & 2.40076 \tabularnewline
131 & 14.1 & 11.3896 & 2.71038 \tabularnewline
132 & 14.5 & 13.9204 & 0.579644 \tabularnewline
133 & 16.15 & 14.0097 & 2.1403 \tabularnewline
134 & 14.75 & 13.1815 & 1.56851 \tabularnewline
135 & 14.8 & 13.971 & 0.829003 \tabularnewline
136 & 12.45 & 12.3449 & 0.105066 \tabularnewline
137 & 12.65 & 7.75728 & 4.89272 \tabularnewline
138 & 17.35 & 19.6305 & -2.28048 \tabularnewline
139 & 8.6 & 5.0865 & 3.5135 \tabularnewline
140 & 18.4 & 16.8506 & 1.54937 \tabularnewline
141 & 16.1 & 15.8566 & 0.243372 \tabularnewline
142 & 11.6 & 6.0888 & 5.5112 \tabularnewline
143 & 17.75 & 17.0358 & 0.714185 \tabularnewline
144 & 15.25 & 10.7978 & 4.45222 \tabularnewline
145 & 17.65 & 15.2491 & 2.40092 \tabularnewline
146 & 16.35 & 13.4098 & 2.94019 \tabularnewline
147 & 17.65 & 16.8 & 0.850025 \tabularnewline
148 & 13.6 & 12.2468 & 1.3532 \tabularnewline
149 & 14.35 & 12.9893 & 1.36068 \tabularnewline
150 & 14.75 & 9.91901 & 4.83099 \tabularnewline
151 & 18.25 & 21.827 & -3.57701 \tabularnewline
152 & 9.9 & 8.40612 & 1.49388 \tabularnewline
153 & 16 & 11.1879 & 4.81211 \tabularnewline
154 & 18.25 & 15.2803 & 2.96969 \tabularnewline
155 & 16.85 & 13.6646 & 3.18537 \tabularnewline
156 & 14.6 & 14.0651 & 0.534893 \tabularnewline
157 & 13.85 & 10.6025 & 3.24746 \tabularnewline
158 & 18.95 & 16.2011 & 2.74887 \tabularnewline
159 & 15.6 & 15.3222 & 0.27779 \tabularnewline
160 & 14.85 & 15.1243 & -0.274292 \tabularnewline
161 & 11.75 & 7.86547 & 3.88453 \tabularnewline
162 & 18.45 & 15.1179 & 3.33213 \tabularnewline
163 & 15.9 & 13.6177 & 2.28227 \tabularnewline
164 & 17.1 & 11.3328 & 5.76716 \tabularnewline
165 & 16.1 & 11.5208 & 4.57917 \tabularnewline
166 & 19.9 & 19.6214 & 0.278579 \tabularnewline
167 & 10.95 & 6.81729 & 4.13271 \tabularnewline
168 & 18.45 & 14.36 & 4.09 \tabularnewline
169 & 15.1 & 12.8095 & 2.2905 \tabularnewline
170 & 15 & 16.9125 & -1.9125 \tabularnewline
171 & 11.35 & 8.46828 & 2.88172 \tabularnewline
172 & 15.95 & 11.2946 & 4.65539 \tabularnewline
173 & 18.1 & 17.4329 & 0.667109 \tabularnewline
174 & 14.6 & 12.2589 & 2.34112 \tabularnewline
175 & 15.4 & 13.0589 & 2.34112 \tabularnewline
176 & 15.4 & 11.3754 & 4.02456 \tabularnewline
177 & 17.6 & 17.8929 & -0.292884 \tabularnewline
178 & 13.35 & 7.92258 & 5.42742 \tabularnewline
179 & 19.1 & 17.6546 & 1.44543 \tabularnewline
180 & 15.35 & 18.6264 & -3.27644 \tabularnewline
181 & 7.6 & 8.7088 & -1.1088 \tabularnewline
182 & 13.4 & 12.4186 & 0.981424 \tabularnewline
183 & 13.9 & 9.35065 & 4.54935 \tabularnewline
184 & 19.1 & 17.3364 & 1.76359 \tabularnewline
185 & 15.25 & 15.1931 & 0.056942 \tabularnewline
186 & 12.9 & 10.3754 & 2.52456 \tabularnewline
187 & 16.1 & 10.6044 & 5.49564 \tabularnewline
188 & 17.35 & 16.8974 & 0.452633 \tabularnewline
189 & 13.15 & 11.9331 & 1.21687 \tabularnewline
190 & 12.15 & 11.5271 & 0.622926 \tabularnewline
191 & 12.6 & 13.6484 & -1.04843 \tabularnewline
192 & 10.35 & 8.56186 & 1.78814 \tabularnewline
193 & 15.4 & 17.2146 & -1.81463 \tabularnewline
194 & 9.6 & 4.1702 & 5.4298 \tabularnewline
195 & 18.2 & 16.5582 & 1.6418 \tabularnewline
196 & 13.6 & 11.1614 & 2.4386 \tabularnewline
197 & 14.85 & 14.3863 & 0.463716 \tabularnewline
198 & 14.75 & 13.2988 & 1.4512 \tabularnewline
199 & 14.1 & 10.6605 & 3.43951 \tabularnewline
200 & 14.9 & 11.6616 & 3.23836 \tabularnewline
201 & 16.25 & 12.1563 & 4.0937 \tabularnewline
202 & 19.25 & 17.1739 & 2.07612 \tabularnewline
203 & 13.6 & 13.0616 & 0.538439 \tabularnewline
204 & 13.6 & 10.8092 & 2.79077 \tabularnewline
205 & 15.65 & 14.6546 & 0.995444 \tabularnewline
206 & 12.75 & 9.38793 & 3.36207 \tabularnewline
207 & 14.6 & 16.5773 & -1.97735 \tabularnewline
208 & 9.85 & 8.32597 & 1.52403 \tabularnewline
209 & 12.65 & 8.51588 & 4.13412 \tabularnewline
210 & 19.2 & 16.1444 & 3.05559 \tabularnewline
211 & 16.6 & 17.0439 & -0.443907 \tabularnewline
212 & 11.2 & 8.71348 & 2.48652 \tabularnewline
213 & 15.25 & 17.1885 & -1.93845 \tabularnewline
214 & 11.9 & 10.3507 & 1.54933 \tabularnewline
215 & 13.2 & 11.7959 & 1.40415 \tabularnewline
216 & 16.35 & 16.3452 & 0.00477168 \tabularnewline
217 & 12.4 & 9.35391 & 3.04609 \tabularnewline
218 & 15.85 & 11.1635 & 4.68647 \tabularnewline
219 & 18.15 & 18.969 & -0.818978 \tabularnewline
220 & 11.15 & 8.90009 & 2.24991 \tabularnewline
221 & 15.65 & 10.8887 & 4.76127 \tabularnewline
222 & 17.75 & 21.5402 & -3.79024 \tabularnewline
223 & 7.65 & 6.72274 & 0.927257 \tabularnewline
224 & 12.35 & 8.43307 & 3.91693 \tabularnewline
225 & 15.6 & 10.5162 & 5.08384 \tabularnewline
226 & 19.3 & 15.2853 & 4.01468 \tabularnewline
227 & 15.2 & 10.2309 & 4.96912 \tabularnewline
228 & 17.1 & 13.438 & 3.66203 \tabularnewline
229 & 15.6 & 12.2713 & 3.32873 \tabularnewline
230 & 18.4 & 12.8378 & 5.56221 \tabularnewline
231 & 19.05 & 13.2446 & 5.80539 \tabularnewline
232 & 18.55 & 15.0082 & 3.5418 \tabularnewline
233 & 19.1 & 17.8139 & 1.28612 \tabularnewline
234 & 13.1 & 13.1484 & -0.0483713 \tabularnewline
235 & 12.85 & 14.9966 & -2.14664 \tabularnewline
236 & 9.5 & 15.8549 & -6.35486 \tabularnewline
237 & 4.5 & 3.20407 & 1.29593 \tabularnewline
238 & 11.85 & 11.8322 & 0.0177969 \tabularnewline
239 & 13.6 & 14.31 & -0.710044 \tabularnewline
240 & 11.7 & 11.1206 & 0.579374 \tabularnewline
241 & 12.4 & 12.4056 & -0.00558245 \tabularnewline
242 & 13.35 & 14.1105 & -0.760513 \tabularnewline
243 & 11.4 & 8.72663 & 2.67337 \tabularnewline
244 & 14.9 & 10.3208 & 4.57917 \tabularnewline
245 & 19.9 & 20.0742 & -0.174171 \tabularnewline
246 & 11.2 & 10.0298 & 1.17023 \tabularnewline
247 & 14.6 & 12.2992 & 2.30075 \tabularnewline
248 & 17.6 & 15.6701 & 1.92992 \tabularnewline
249 & 14.05 & 12.0704 & 1.97963 \tabularnewline
250 & 16.1 & 15.0117 & 1.08829 \tabularnewline
251 & 13.35 & 13.4488 & -0.098796 \tabularnewline
252 & 11.85 & 13.0236 & -1.17357 \tabularnewline
253 & 11.95 & 10.333 & 1.61698 \tabularnewline
254 & 14.75 & 13.1039 & 1.64607 \tabularnewline
255 & 15.15 & 15.3825 & -0.232498 \tabularnewline
256 & 13.2 & 10.1305 & 3.06954 \tabularnewline
257 & 16.85 & 20.304 & -3.45402 \tabularnewline
258 & 7.85 & 11.9868 & -4.13682 \tabularnewline
259 & 7.7 & 8.53516 & -0.835159 \tabularnewline
260 & 12.6 & 17.4312 & -4.83118 \tabularnewline
261 & 7.85 & 7.57142 & 0.278579 \tabularnewline
262 & 10.95 & 10.8752 & 0.0748243 \tabularnewline
263 & 12.35 & 14.5228 & -2.17276 \tabularnewline
264 & 9.95 & 7.27663 & 2.67337 \tabularnewline
265 & 14.9 & 10.9959 & 3.90408 \tabularnewline
266 & 16.65 & 15.308 & 1.342 \tabularnewline
267 & 13.4 & 10.9833 & 2.41668 \tabularnewline
268 & 13.95 & 10.5805 & 3.36951 \tabularnewline
269 & 15.7 & 11.658 & 4.04203 \tabularnewline
270 & 16.85 & 17.4589 & -0.608941 \tabularnewline
271 & 10.95 & 7.37614 & 3.57386 \tabularnewline
272 & 15.35 & 14.485 & 0.864952 \tabularnewline
273 & 12.2 & 10.3935 & 1.80647 \tabularnewline
274 & 15.1 & 11.2545 & 3.84545 \tabularnewline
275 & 17.75 & 15.8462 & 1.90377 \tabularnewline
276 & 15.2 & 12.9979 & 2.20207 \tabularnewline
277 & 14.6 & 11.3514 & 3.24855 \tabularnewline
278 & 16.65 & 18.9543 & -2.30435 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268302&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]14.8204[/C][C]-1.92041[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]13.1857[/C][C]-0.98565[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]12.9604[/C][C]-0.160405[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]14.6464[/C][C]-7.24642[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]12.7149[/C][C]-6.01491[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]15.1131[/C][C]-2.51315[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]14.6613[/C][C]0.138743[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]14.6289[/C][C]-1.32885[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]15.3788[/C][C]-4.27882[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]13.7036[/C][C]-5.50361[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]14.0327[/C][C]-2.63272[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.7125[/C][C]-8.31251[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]12.4276[/C][C]-1.82761[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]15.7336[/C][C]-3.73357[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]10.8994[/C][C]-4.59937[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.0634[/C][C]-0.763415[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]14.9256[/C][C]-3.02563[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.7581[/C][C]-3.45807[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]13.3097[/C][C]-3.70974[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]13.2261[/C][C]-3.2261[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]12.4708[/C][C]-6.07079[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.6016[/C][C]1.19838[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]14.6586[/C][C]-3.8586[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]15.4503[/C][C]-1.65033[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]14.1028[/C][C]-2.40284[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]16.5375[/C][C]-5.6375[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]15.4206[/C][C]0.679371[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]12.6421[/C][C]0.757946[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]14.4765[/C][C]-4.57647[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]13.4959[/C][C]-1.99588[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.8767[/C][C]-4.57675[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.4379[/C][C]-1.73789[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.8255[/C][C]-3.82551[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]14.1271[/C][C]-4.42713[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.8349[/C][C]-2.03494[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.1524[/C][C]-1.85244[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]13.3637[/C][C]-2.9637[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.0931[/C][C]0.606888[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]14.0988[/C][C]-4.79881[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.1703[/C][C]-2.37029[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]12.3602[/C][C]-6.46016[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.2747[/C][C]-1.87468[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]14.2957[/C][C]-1.29573[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]14.0543[/C][C]-3.2543[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]11.7424[/C][C]0.55762[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]14.2566[/C][C]-2.95663[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]13.5606[/C][C]-1.7606[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.6124[/C][C]-4.71238[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]13.245[/C][C]-0.544978[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]11.0221[/C][C]1.27787[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.7419[/C][C]-1.14188[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]11.0289[/C][C]-4.32885[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]12.8579[/C][C]-1.9579[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.8592[/C][C]-0.759248[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.2855[/C][C]0.0145462[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]12.6394[/C][C]-2.53937[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.4586[/C][C]-6.75864[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]13.2733[/C][C]1.02668[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]10.1589[/C][C]-2.15887[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.8552[/C][C]0.444833[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]15.2992[/C][C]-5.99925[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]12.3993[/C][C]0.100691[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]12.6434[/C][C]-5.04341[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]15.4018[/C][C]0.498223[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.7805[/C][C]-4.5805[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]11.385[/C][C]-2.28495[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]15.1711[/C][C]-4.07112[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]17.425[/C][C]-4.42499[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]13.3489[/C][C]1.15112[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.4613[/C][C]-0.26132[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]14.6208[/C][C]-2.3208[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.4802[/C][C]-1.08022[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]12.4559[/C][C]-3.65591[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.6172[/C][C]0.982755[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]13.7495[/C][C]-1.14945[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]-1.55201[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]12.5106[/C][C]0.489367[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]14.01[/C][C]-1.41[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]14.9574[/C][C]-1.75741[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]15.5704[/C][C]-5.67042[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]9.54262[/C][C]-1.84262[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]9.43184[/C][C]1.06816[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]15.3754[/C][C]-1.97539[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]18.4449[/C][C]-7.54491[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]7.26387[/C][C]-2.96387[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]12.4774[/C][C]-2.17738[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]12.5515[/C][C]-0.751457[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]11.0474[/C][C]0.152623[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]14.7097[/C][C]-3.30965[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]8.24035[/C][C]0.359648[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]12.4112[/C][C]0.788822[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]19.1484[/C][C]-6.5484[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]9.87433[/C][C]-4.27433[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]12.8127[/C][C]-2.91273[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]12.7547[/C][C]-3.95473[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]10.696[/C][C]-2.99599[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]14.3852[/C][C]-5.38524[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]7.29846[/C][C]0.00154303[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]9.35896[/C][C]2.04104[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]18.3529[/C][C]-4.75285[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]9.15685[/C][C]-1.25685[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]12.7291[/C][C]-2.02914[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]13.7842[/C][C]-3.48421[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]11.8546[/C][C]-3.55462[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]7.99889[/C][C]1.60111[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]18.1316[/C][C]-3.93165[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]7.04319[/C][C]1.45681[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]20.7592[/C][C]-7.25918[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]9.52346[/C][C]-4.62346[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]9.63359[/C][C]-3.23359[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]10.259[/C][C]-0.659008[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]11.9645[/C][C]-0.364549[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]17.2016[/C][C]-6.10157[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]3.82264[/C][C]0.527356[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]7.84635[/C][C]4.85365[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]13.5557[/C][C]4.5443[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]17.5271[/C][C]0.322901[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]14.6458[/C][C]1.95419[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]10.9881[/C][C]1.6119[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]13.159[/C][C]3.94103[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]21.8129[/C][C]-2.71289[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]13.3297[/C][C]2.77029[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]9.07442[/C][C]4.27558[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]14.2743[/C][C]4.1257[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]16.6045[/C][C]-1.90448[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]10.1551[/C][C]0.444855[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]9.4683[/C][C]3.1317[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]16.1957[/C][C]0.00433456[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]9.15083[/C][C]4.44917[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]16.4992[/C][C]2.40076[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]11.3896[/C][C]2.71038[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]13.9204[/C][C]0.579644[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.0097[/C][C]2.1403[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.1815[/C][C]1.56851[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]13.971[/C][C]0.829003[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.3449[/C][C]0.105066[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]7.75728[/C][C]4.89272[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]19.6305[/C][C]-2.28048[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]5.0865[/C][C]3.5135[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]16.8506[/C][C]1.54937[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]15.8566[/C][C]0.243372[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]6.0888[/C][C]5.5112[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]17.0358[/C][C]0.714185[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]10.7978[/C][C]4.45222[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]15.2491[/C][C]2.40092[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]13.4098[/C][C]2.94019[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]16.8[/C][C]0.850025[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.2468[/C][C]1.3532[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]12.9893[/C][C]1.36068[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]9.91901[/C][C]4.83099[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]21.827[/C][C]-3.57701[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]8.40612[/C][C]1.49388[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.1879[/C][C]4.81211[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]15.2803[/C][C]2.96969[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]13.6646[/C][C]3.18537[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]14.0651[/C][C]0.534893[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]10.6025[/C][C]3.24746[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]16.2011[/C][C]2.74887[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]15.3222[/C][C]0.27779[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.1243[/C][C]-0.274292[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]7.86547[/C][C]3.88453[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.1179[/C][C]3.33213[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]13.6177[/C][C]2.28227[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]11.3328[/C][C]5.76716[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]11.5208[/C][C]4.57917[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]19.6214[/C][C]0.278579[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]6.81729[/C][C]4.13271[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]14.36[/C][C]4.09[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]12.8095[/C][C]2.2905[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]16.9125[/C][C]-1.9125[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]8.46828[/C][C]2.88172[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]11.2946[/C][C]4.65539[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]17.4329[/C][C]0.667109[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]12.2589[/C][C]2.34112[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.0589[/C][C]2.34112[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]11.3754[/C][C]4.02456[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]17.8929[/C][C]-0.292884[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]7.92258[/C][C]5.42742[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]17.6546[/C][C]1.44543[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]18.6264[/C][C]-3.27644[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]8.7088[/C][C]-1.1088[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]12.4186[/C][C]0.981424[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]9.35065[/C][C]4.54935[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]17.3364[/C][C]1.76359[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]15.1931[/C][C]0.056942[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]10.3754[/C][C]2.52456[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]10.6044[/C][C]5.49564[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]16.8974[/C][C]0.452633[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]11.9331[/C][C]1.21687[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]11.5271[/C][C]0.622926[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]13.6484[/C][C]-1.04843[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]8.56186[/C][C]1.78814[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]17.2146[/C][C]-1.81463[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]4.1702[/C][C]5.4298[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]16.5582[/C][C]1.6418[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]11.1614[/C][C]2.4386[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]14.3863[/C][C]0.463716[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]13.2988[/C][C]1.4512[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]10.6605[/C][C]3.43951[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.6616[/C][C]3.23836[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]12.1563[/C][C]4.0937[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]17.1739[/C][C]2.07612[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.0616[/C][C]0.538439[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]10.8092[/C][C]2.79077[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]14.6546[/C][C]0.995444[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]9.38793[/C][C]3.36207[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]16.5773[/C][C]-1.97735[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]8.32597[/C][C]1.52403[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]8.51588[/C][C]4.13412[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]16.1444[/C][C]3.05559[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]17.0439[/C][C]-0.443907[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]8.71348[/C][C]2.48652[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]17.1885[/C][C]-1.93845[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]10.3507[/C][C]1.54933[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]11.7959[/C][C]1.40415[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]16.3452[/C][C]0.00477168[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.35391[/C][C]3.04609[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]11.1635[/C][C]4.68647[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]18.969[/C][C]-0.818978[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]8.90009[/C][C]2.24991[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]10.8887[/C][C]4.76127[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]21.5402[/C][C]-3.79024[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]6.72274[/C][C]0.927257[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]8.43307[/C][C]3.91693[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]10.5162[/C][C]5.08384[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]15.2853[/C][C]4.01468[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]10.2309[/C][C]4.96912[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]13.438[/C][C]3.66203[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]12.2713[/C][C]3.32873[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]12.8378[/C][C]5.56221[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]13.2446[/C][C]5.80539[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]15.0082[/C][C]3.5418[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]17.8139[/C][C]1.28612[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]13.1484[/C][C]-0.0483713[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]14.9966[/C][C]-2.14664[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]15.8549[/C][C]-6.35486[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]3.20407[/C][C]1.29593[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]11.8322[/C][C]0.0177969[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]14.31[/C][C]-0.710044[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]11.1206[/C][C]0.579374[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]12.4056[/C][C]-0.00558245[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]14.1105[/C][C]-0.760513[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]8.72663[/C][C]2.67337[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]10.3208[/C][C]4.57917[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]20.0742[/C][C]-0.174171[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]10.0298[/C][C]1.17023[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]12.2992[/C][C]2.30075[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]15.6701[/C][C]1.92992[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]12.0704[/C][C]1.97963[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]15.0117[/C][C]1.08829[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]13.4488[/C][C]-0.098796[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]13.0236[/C][C]-1.17357[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]10.333[/C][C]1.61698[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]13.1039[/C][C]1.64607[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]15.3825[/C][C]-0.232498[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]10.1305[/C][C]3.06954[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]20.304[/C][C]-3.45402[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]11.9868[/C][C]-4.13682[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]8.53516[/C][C]-0.835159[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]17.4312[/C][C]-4.83118[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]7.57142[/C][C]0.278579[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]10.8752[/C][C]0.0748243[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]14.5228[/C][C]-2.17276[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]7.27663[/C][C]2.67337[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]10.9959[/C][C]3.90408[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]15.308[/C][C]1.342[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]10.9833[/C][C]2.41668[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]10.5805[/C][C]3.36951[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]11.658[/C][C]4.04203[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]17.4589[/C][C]-0.608941[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]7.37614[/C][C]3.57386[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]14.485[/C][C]0.864952[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]10.3935[/C][C]1.80647[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]11.2545[/C][C]3.84545[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.8462[/C][C]1.90377[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]12.9979[/C][C]2.20207[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]11.3514[/C][C]3.24855[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]18.9543[/C][C]-2.30435[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268302&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268302&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
112.914.8204-1.92041
212.213.1857-0.98565
312.812.9604-0.160405
47.414.6464-7.24642
56.712.7149-6.01491
612.615.1131-2.51315
714.814.66130.138743
813.314.6289-1.32885
911.115.3788-4.27882
108.213.7036-5.50361
1111.414.0327-2.63272
126.414.7125-8.31251
1310.612.4276-1.82761
141215.7336-3.73357
156.310.8994-4.59937
1611.312.0634-0.763415
1711.914.9256-3.02563
189.312.7581-3.45807
199.613.3097-3.70974
201013.2261-3.2261
216.412.4708-6.07079
2213.812.60161.19838
2310.814.6586-3.8586
2413.815.4503-1.65033
2511.714.1028-2.40284
2610.916.5375-5.6375
2716.115.42060.679371
2813.412.64210.757946
299.914.4765-4.57647
3011.513.4959-1.99588
318.312.8767-4.57675
3211.713.4379-1.73789
33912.8255-3.82551
349.714.1271-4.42713
3510.812.8349-2.03494
3610.312.1524-1.85244
3710.413.3637-2.9637
3812.712.09310.606888
399.314.0988-4.79881
4011.814.1703-2.37029
415.912.3602-6.46016
4211.413.2747-1.87468
431314.2957-1.29573
4410.814.0543-3.2543
4512.311.74240.55762
4611.314.2566-2.95663
4711.813.5606-1.7606
487.912.6124-4.71238
4912.713.245-0.544978
5012.311.02211.27787
5111.612.7419-1.14188
526.711.0289-4.32885
5310.912.8579-1.9579
5412.112.8592-0.759248
5513.313.28550.0145462
5610.112.6394-2.53937
575.712.4586-6.75864
5814.313.27331.02668
59810.1589-2.15887
6013.312.85520.444833
619.315.2992-5.99925
6212.512.39930.100691
637.612.6434-5.04341
6415.915.40180.498223
659.213.7805-4.5805
669.111.385-2.28495
6711.115.1711-4.07112
681317.425-4.42499
6914.513.34891.15112
7012.212.4613-0.26132
7112.314.6208-2.3208
7211.412.4802-1.08022
738.812.4559-3.65591
7414.613.61720.982755
7512.613.7495-1.14945
76NANA-1.55201
771312.51060.489367
7812.614.01-1.41
7913.214.9574-1.75741
809.915.5704-5.67042
817.79.54262-1.84262
8210.59.431841.06816
8313.415.3754-1.97539
8410.918.4449-7.54491
854.37.26387-2.96387
8610.312.4774-2.17738
8711.812.5515-0.751457
8811.211.04740.152623
8911.414.7097-3.30965
908.68.240350.359648
9113.212.41120.788822
9212.619.1484-6.5484
935.69.87433-4.27433
949.912.8127-2.91273
958.812.7547-3.95473
967.710.696-2.99599
97914.3852-5.38524
987.37.298460.00154303
9911.49.358962.04104
10013.618.3529-4.75285
1017.99.15685-1.25685
10210.712.7291-2.02914
10310.313.7842-3.48421
1048.311.8546-3.55462
1059.67.998891.60111
10614.218.1316-3.93165
1078.57.043191.45681
10813.520.7592-7.25918
1094.99.52346-4.62346
1106.49.63359-3.23359
1119.610.259-0.659008
11211.611.9645-0.364549
11311.117.2016-6.10157
1144.353.822640.527356
11512.77.846354.85365
11618.113.55574.5443
11717.8517.52710.322901
11816.614.64581.95419
11912.610.98811.6119
12017.113.1593.94103
12119.121.8129-2.71289
12216.113.32972.77029
12313.359.074424.27558
12418.414.27434.1257
12514.716.6045-1.90448
12610.610.15510.444855
12712.69.46833.1317
12816.216.19570.00433456
12913.69.150834.44917
13018.916.49922.40076
13114.111.38962.71038
13214.513.92040.579644
13316.1514.00972.1403
13414.7513.18151.56851
13514.813.9710.829003
13612.4512.34490.105066
13712.657.757284.89272
13817.3519.6305-2.28048
1398.65.08653.5135
14018.416.85061.54937
14116.115.85660.243372
14211.66.08885.5112
14317.7517.03580.714185
14415.2510.79784.45222
14517.6515.24912.40092
14616.3513.40982.94019
14717.6516.80.850025
14813.612.24681.3532
14914.3512.98931.36068
15014.759.919014.83099
15118.2521.827-3.57701
1529.98.406121.49388
1531611.18794.81211
15418.2515.28032.96969
15516.8513.66463.18537
15614.614.06510.534893
15713.8510.60253.24746
15818.9516.20112.74887
15915.615.32220.27779
16014.8515.1243-0.274292
16111.757.865473.88453
16218.4515.11793.33213
16315.913.61772.28227
16417.111.33285.76716
16516.111.52084.57917
16619.919.62140.278579
16710.956.817294.13271
16818.4514.364.09
16915.112.80952.2905
1701516.9125-1.9125
17111.358.468282.88172
17215.9511.29464.65539
17318.117.43290.667109
17414.612.25892.34112
17515.413.05892.34112
17615.411.37544.02456
17717.617.8929-0.292884
17813.357.922585.42742
17919.117.65461.44543
18015.3518.6264-3.27644
1817.68.7088-1.1088
18213.412.41860.981424
18313.99.350654.54935
18419.117.33641.76359
18515.2515.19310.056942
18612.910.37542.52456
18716.110.60445.49564
18817.3516.89740.452633
18913.1511.93311.21687
19012.1511.52710.622926
19112.613.6484-1.04843
19210.358.561861.78814
19315.417.2146-1.81463
1949.64.17025.4298
19518.216.55821.6418
19613.611.16142.4386
19714.8514.38630.463716
19814.7513.29881.4512
19914.110.66053.43951
20014.911.66163.23836
20116.2512.15634.0937
20219.2517.17392.07612
20313.613.06160.538439
20413.610.80922.79077
20515.6514.65460.995444
20612.759.387933.36207
20714.616.5773-1.97735
2089.858.325971.52403
20912.658.515884.13412
21019.216.14443.05559
21116.617.0439-0.443907
21211.28.713482.48652
21315.2517.1885-1.93845
21411.910.35071.54933
21513.211.79591.40415
21616.3516.34520.00477168
21712.49.353913.04609
21815.8511.16354.68647
21918.1518.969-0.818978
22011.158.900092.24991
22115.6510.88874.76127
22217.7521.5402-3.79024
2237.656.722740.927257
22412.358.433073.91693
22515.610.51625.08384
22619.315.28534.01468
22715.210.23094.96912
22817.113.4383.66203
22915.612.27133.32873
23018.412.83785.56221
23119.0513.24465.80539
23218.5515.00823.5418
23319.117.81391.28612
23413.113.1484-0.0483713
23512.8514.9966-2.14664
2369.515.8549-6.35486
2374.53.204071.29593
23811.8511.83220.0177969
23913.614.31-0.710044
24011.711.12060.579374
24112.412.4056-0.00558245
24213.3514.1105-0.760513
24311.48.726632.67337
24414.910.32084.57917
24519.920.0742-0.174171
24611.210.02981.17023
24714.612.29922.30075
24817.615.67011.92992
24914.0512.07041.97963
25016.115.01171.08829
25113.3513.4488-0.098796
25211.8513.0236-1.17357
25311.9510.3331.61698
25414.7513.10391.64607
25515.1515.3825-0.232498
25613.210.13053.06954
25716.8520.304-3.45402
2587.8511.9868-4.13682
2597.78.53516-0.835159
26012.617.4312-4.83118
2617.857.571420.278579
26210.9510.87520.0748243
26312.3514.5228-2.17276
2649.957.276632.67337
26514.910.99593.90408
26616.6515.3081.342
26713.410.98332.41668
26813.9510.58053.36951
26915.711.6584.04203
27016.8517.4589-0.608941
27110.957.376143.57386
27215.3514.4850.864952
27312.210.39351.80647
27415.111.25453.84545
27517.7515.84621.90377
27615.212.99792.20207
27714.611.35143.24855
27816.6518.9543-2.30435
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.7143150.571370.285685
70.7171670.5656670.282833
80.6156050.768790.384395
90.5279030.9441950.472097
100.4988020.9976030.501198
110.3934690.7869370.606531
120.5862070.8275850.413793
130.4974590.9949190.502541
140.4124490.8248970.587551
150.3744140.7488280.625586
160.339770.679540.66023
170.2722270.5444540.727773
180.2143870.4287750.785613
190.1669790.3339570.833021
200.1254920.2509840.874508
210.1317460.2634910.868254
220.2009830.4019670.799017
230.1621090.3242190.837891
240.1407440.2814870.859256
250.110430.220860.88957
260.1039840.2079670.896016
270.1289860.2579730.871014
280.1340160.2680330.865984
290.1215620.2431250.878438
300.09912390.1982480.900876
310.09667450.1933490.903325
320.08028980.160580.91971
330.06637170.1327430.933628
340.05784690.1156940.942153
350.04427420.08854830.955726
360.0335190.06703790.966481
370.02569690.05139380.974303
380.03058130.06116250.969419
390.02873870.05747740.971261
400.02247880.04495770.977521
410.0386190.07723790.961381
420.03133270.06266550.968667
430.02747920.05495850.972521
440.02227180.04454360.977728
450.02113670.04227340.978863
460.01742110.03484210.982579
470.01324350.0264870.986756
480.01460410.02920820.985396
490.0124840.0249680.987516
500.01436860.02873720.985631
510.01137810.02275620.988622
520.01323960.02647910.98676
530.01054610.02109230.989454
540.009350730.01870150.990649
550.009114130.01822830.990886
560.007096080.01419220.992904
570.01631580.03263160.983684
580.02054560.04109120.979454
590.01616750.0323350.983833
600.01582380.03164760.984176
610.02296050.0459210.977039
620.02293690.04587380.977063
630.02785010.05570020.97215
640.03543330.07086670.964567
650.0406880.0813760.959312
660.03341640.06683290.966584
670.03478960.06957920.96521
680.04011460.08022930.959885
690.04916980.09833960.95083
700.04457460.08914910.955425
710.04240890.08481790.957591
720.03663660.07327320.963363
730.03402970.06805940.96597
740.04015330.08030660.959847
750.03625430.07250850.963746
760.03399910.06799830.966001
770.03257370.06514740.967426
780.03065260.06130510.969347
790.02503290.05006590.974967
800.03846690.07693390.961533
810.03263270.06526540.967367
820.03436850.06873710.965631
830.02906360.05812720.970936
840.08878810.1775760.911212
850.08684760.1736950.913152
860.07913010.158260.92087
870.06919290.1383860.930807
880.06241880.1248380.937581
890.06140550.1228110.938595
900.06060820.1212160.939392
910.05922090.1184420.940779
920.123980.2479590.87602
930.1485610.2971210.851439
940.1452120.2904240.854788
950.1617380.3234760.838262
960.167560.335120.83244
970.2455820.4911630.754418
980.2324760.4649530.767524
990.2581770.5163530.741823
1000.3196380.6392750.680362
1010.2945890.5891780.705411
1020.2840880.5681770.715912
1030.2983470.5966950.701653
1040.3355160.6710320.664484
1050.3594190.7188370.640581
1060.4010880.8021760.598912
1070.4146620.8293250.585338
1080.6628070.6743860.337193
1090.7143980.5712040.285602
1100.7343020.5313960.265698
1110.7291940.5416120.270806
1120.7166920.5666170.283308
1130.8359850.328030.164015
1140.8325420.3349160.167458
1150.9168970.1662060.0831028
1160.9565180.08696410.043482
1170.9580730.08385310.0419265
1180.9603860.0792280.039614
1190.9676010.06479790.0323989
1200.981430.03714050.0185703
1210.9859770.02804630.0140232
1220.989040.02191950.0109597
1230.9941520.01169560.00584779
1240.997390.005219380.00260969
1250.9974340.005131130.00256557
1260.9971040.005792140.00289607
1270.9977790.004441610.00222081
1280.9974490.005101040.00255052
1290.998710.002579070.00128953
1300.9987830.002433670.00121683
1310.9989010.002197680.00109884
1320.9989670.002066160.00103308
1330.9989570.002085580.00104279
1340.9988610.002278960.00113948
1350.9986080.002783380.00139169
1360.9982690.003461990.001731
1370.9991530.001693480.000846738
1380.9990120.001976780.00098839
1390.999230.001540820.000770412
1400.9991370.001725460.00086273
1410.9988890.002221310.00111065
1420.9994920.001015080.000507541
1430.9994640.001072690.000536343
1440.9996650.0006707950.000335397
1450.999650.0006994980.000349749
1460.9996630.0006748080.000337404
1470.9995870.0008268580.000413429
1480.9994980.001003030.000501517
1490.9994090.001181120.00059056
1500.9995990.0008024860.000401243
1510.999890.000220960.00011048
1520.9998660.0002670610.00013353
1530.9999110.0001782228.91109e-05
1540.9999060.0001873439.36717e-05
1550.9999230.0001544697.72343e-05
1560.9998970.0002052410.00010262
1570.9998970.0002057680.000102884
1580.9998880.0002248070.000112404
1590.9998640.000272670.000136335
1600.9998180.0003647260.000182363
1610.999840.0003205680.000160284
1620.9998540.0002913830.000145691
1630.9998360.0003272710.000163636
1640.9999852.98975e-051.49488e-05
1650.9999872.57457e-051.28729e-05
1660.9999813.70667e-051.85334e-05
1670.9999843.22698e-051.61349e-05
1680.9999892.1421e-051.07105e-05
1690.9999872.68835e-051.34417e-05
1700.9999862.73052e-051.36526e-05
1710.9999853.07145e-051.53573e-05
1720.9999892.10231e-051.05116e-05
1730.9999872.5412e-051.2706e-05
1740.9999843.10717e-051.55358e-05
1750.9999813.81793e-051.90897e-05
1760.9999833.32838e-051.66419e-05
1770.999983.93554e-051.96777e-05
1780.9999862.73167e-051.36584e-05
1790.9999823.54212e-051.77106e-05
1800.9999843.27385e-051.63692e-05
1810.9999823.64555e-051.82278e-05
1820.9999755.0631e-052.53155e-05
1830.9999754.95547e-052.47774e-05
1840.9999656.98119e-053.49059e-05
1850.9999637.49748e-053.74874e-05
1860.9999519.79391e-054.89695e-05
1870.9999794.23899e-052.1195e-05
1880.9999715.89607e-052.94804e-05
1890.9999578.53484e-054.26742e-05
1900.9999380.000124916.24552e-05
1910.9999120.00017568.78001e-05
1920.9998770.000245520.00012276
1930.9998540.0002912940.000145647
1940.9999230.0001536877.68437e-05
1950.9998960.000207830.000103915
1960.999880.0002397950.000119897
1970.9998710.000258770.000129385
1980.9998170.0003667840.000183392
1990.9998470.0003062820.000153141
2000.9998240.000352350.000176175
2010.9998060.0003886350.000194318
2020.999780.0004399780.000219989
2030.9997360.0005282510.000264126
2040.9996610.0006785130.000339257
2050.9995260.0009488960.000474448
2060.9996620.000676170.000338085
2070.9995490.0009020920.000451046
2080.9994920.001016350.000508177
2090.9994250.0011510.000575499
2100.9993290.001342740.000671369
2110.9990460.001907020.000953511
2120.9987290.002542350.00127118
2130.9989690.002062220.00103111
2140.998670.00265920.0013296
2150.9984950.003009610.0015048
2160.9979810.004037590.00201879
2170.9977320.004535580.00226779
2180.9973630.005273780.00263689
2190.9963110.007377880.00368894
2200.9950770.009845780.00492289
2210.9950820.009836770.00491839
2220.9955890.008821440.00441072
2230.9938820.01223540.00611769
2240.9936680.01266410.00633204
2250.99320.01360060.00680031
2260.9964870.007026310.00351316
2270.9973450.005309190.0026546
2280.9979680.004063870.00203194
2290.9972520.005495320.00274766
2300.9979280.004143260.00207163
2310.9988530.002293250.00114663
2320.998380.003239740.00161987
2330.9977760.004448250.00222413
2340.9972020.00559660.0027983
2350.9968270.006346090.00317305
2360.9993370.001325870.000662936
2370.9992380.001523590.000761795
2380.9991010.00179820.000899102
2390.9986510.002697410.00134871
2400.9978860.00422760.0021138
2410.997160.005680240.00284012
2420.9958410.008318080.00415904
2430.9950050.00998970.00499485
2440.9934590.01308220.00654112
2450.9901320.01973550.00986774
2460.9855480.02890310.0144515
2470.9807250.03854960.0192748
2480.9738910.05221760.0261088
2490.9634550.07308980.0365449
2500.9487950.102410.0512051
2510.9328880.1342250.0671123
2520.9263630.1472740.0736372
2530.900510.1989810.0994903
2540.8679840.2640310.132016
2550.8832660.2334680.116734
2560.850430.2991410.14957
2570.8560470.2879050.143953
2580.9393450.1213090.0606546
2590.9402170.1195660.0597828
2600.999460.001080910.000540457
2610.9990270.00194580.000972902
2620.9985720.00285620.0014281
2630.9999892.1455e-051.07275e-05
2640.9999617.77152e-053.88576e-05
2650.9999549.22914e-054.61457e-05
2660.999910.0001799728.99861e-05
2670.9999549.25342e-054.62671e-05
2680.9998470.0003067890.000153395
2690.9996360.0007283890.000364195
2700.998240.003520910.00176046
2710.9961360.007727860.00386393
2720.9919580.0160830.00804152
2730.9586170.08276620.0413831

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
6 & 0.714315 & 0.57137 & 0.285685 \tabularnewline
7 & 0.717167 & 0.565667 & 0.282833 \tabularnewline
8 & 0.615605 & 0.76879 & 0.384395 \tabularnewline
9 & 0.527903 & 0.944195 & 0.472097 \tabularnewline
10 & 0.498802 & 0.997603 & 0.501198 \tabularnewline
11 & 0.393469 & 0.786937 & 0.606531 \tabularnewline
12 & 0.586207 & 0.827585 & 0.413793 \tabularnewline
13 & 0.497459 & 0.994919 & 0.502541 \tabularnewline
14 & 0.412449 & 0.824897 & 0.587551 \tabularnewline
15 & 0.374414 & 0.748828 & 0.625586 \tabularnewline
16 & 0.33977 & 0.67954 & 0.66023 \tabularnewline
17 & 0.272227 & 0.544454 & 0.727773 \tabularnewline
18 & 0.214387 & 0.428775 & 0.785613 \tabularnewline
19 & 0.166979 & 0.333957 & 0.833021 \tabularnewline
20 & 0.125492 & 0.250984 & 0.874508 \tabularnewline
21 & 0.131746 & 0.263491 & 0.868254 \tabularnewline
22 & 0.200983 & 0.401967 & 0.799017 \tabularnewline
23 & 0.162109 & 0.324219 & 0.837891 \tabularnewline
24 & 0.140744 & 0.281487 & 0.859256 \tabularnewline
25 & 0.11043 & 0.22086 & 0.88957 \tabularnewline
26 & 0.103984 & 0.207967 & 0.896016 \tabularnewline
27 & 0.128986 & 0.257973 & 0.871014 \tabularnewline
28 & 0.134016 & 0.268033 & 0.865984 \tabularnewline
29 & 0.121562 & 0.243125 & 0.878438 \tabularnewline
30 & 0.0991239 & 0.198248 & 0.900876 \tabularnewline
31 & 0.0966745 & 0.193349 & 0.903325 \tabularnewline
32 & 0.0802898 & 0.16058 & 0.91971 \tabularnewline
33 & 0.0663717 & 0.132743 & 0.933628 \tabularnewline
34 & 0.0578469 & 0.115694 & 0.942153 \tabularnewline
35 & 0.0442742 & 0.0885483 & 0.955726 \tabularnewline
36 & 0.033519 & 0.0670379 & 0.966481 \tabularnewline
37 & 0.0256969 & 0.0513938 & 0.974303 \tabularnewline
38 & 0.0305813 & 0.0611625 & 0.969419 \tabularnewline
39 & 0.0287387 & 0.0574774 & 0.971261 \tabularnewline
40 & 0.0224788 & 0.0449577 & 0.977521 \tabularnewline
41 & 0.038619 & 0.0772379 & 0.961381 \tabularnewline
42 & 0.0313327 & 0.0626655 & 0.968667 \tabularnewline
43 & 0.0274792 & 0.0549585 & 0.972521 \tabularnewline
44 & 0.0222718 & 0.0445436 & 0.977728 \tabularnewline
45 & 0.0211367 & 0.0422734 & 0.978863 \tabularnewline
46 & 0.0174211 & 0.0348421 & 0.982579 \tabularnewline
47 & 0.0132435 & 0.026487 & 0.986756 \tabularnewline
48 & 0.0146041 & 0.0292082 & 0.985396 \tabularnewline
49 & 0.012484 & 0.024968 & 0.987516 \tabularnewline
50 & 0.0143686 & 0.0287372 & 0.985631 \tabularnewline
51 & 0.0113781 & 0.0227562 & 0.988622 \tabularnewline
52 & 0.0132396 & 0.0264791 & 0.98676 \tabularnewline
53 & 0.0105461 & 0.0210923 & 0.989454 \tabularnewline
54 & 0.00935073 & 0.0187015 & 0.990649 \tabularnewline
55 & 0.00911413 & 0.0182283 & 0.990886 \tabularnewline
56 & 0.00709608 & 0.0141922 & 0.992904 \tabularnewline
57 & 0.0163158 & 0.0326316 & 0.983684 \tabularnewline
58 & 0.0205456 & 0.0410912 & 0.979454 \tabularnewline
59 & 0.0161675 & 0.032335 & 0.983833 \tabularnewline
60 & 0.0158238 & 0.0316476 & 0.984176 \tabularnewline
61 & 0.0229605 & 0.045921 & 0.977039 \tabularnewline
62 & 0.0229369 & 0.0458738 & 0.977063 \tabularnewline
63 & 0.0278501 & 0.0557002 & 0.97215 \tabularnewline
64 & 0.0354333 & 0.0708667 & 0.964567 \tabularnewline
65 & 0.040688 & 0.081376 & 0.959312 \tabularnewline
66 & 0.0334164 & 0.0668329 & 0.966584 \tabularnewline
67 & 0.0347896 & 0.0695792 & 0.96521 \tabularnewline
68 & 0.0401146 & 0.0802293 & 0.959885 \tabularnewline
69 & 0.0491698 & 0.0983396 & 0.95083 \tabularnewline
70 & 0.0445746 & 0.0891491 & 0.955425 \tabularnewline
71 & 0.0424089 & 0.0848179 & 0.957591 \tabularnewline
72 & 0.0366366 & 0.0732732 & 0.963363 \tabularnewline
73 & 0.0340297 & 0.0680594 & 0.96597 \tabularnewline
74 & 0.0401533 & 0.0803066 & 0.959847 \tabularnewline
75 & 0.0362543 & 0.0725085 & 0.963746 \tabularnewline
76 & 0.0339991 & 0.0679983 & 0.966001 \tabularnewline
77 & 0.0325737 & 0.0651474 & 0.967426 \tabularnewline
78 & 0.0306526 & 0.0613051 & 0.969347 \tabularnewline
79 & 0.0250329 & 0.0500659 & 0.974967 \tabularnewline
80 & 0.0384669 & 0.0769339 & 0.961533 \tabularnewline
81 & 0.0326327 & 0.0652654 & 0.967367 \tabularnewline
82 & 0.0343685 & 0.0687371 & 0.965631 \tabularnewline
83 & 0.0290636 & 0.0581272 & 0.970936 \tabularnewline
84 & 0.0887881 & 0.177576 & 0.911212 \tabularnewline
85 & 0.0868476 & 0.173695 & 0.913152 \tabularnewline
86 & 0.0791301 & 0.15826 & 0.92087 \tabularnewline
87 & 0.0691929 & 0.138386 & 0.930807 \tabularnewline
88 & 0.0624188 & 0.124838 & 0.937581 \tabularnewline
89 & 0.0614055 & 0.122811 & 0.938595 \tabularnewline
90 & 0.0606082 & 0.121216 & 0.939392 \tabularnewline
91 & 0.0592209 & 0.118442 & 0.940779 \tabularnewline
92 & 0.12398 & 0.247959 & 0.87602 \tabularnewline
93 & 0.148561 & 0.297121 & 0.851439 \tabularnewline
94 & 0.145212 & 0.290424 & 0.854788 \tabularnewline
95 & 0.161738 & 0.323476 & 0.838262 \tabularnewline
96 & 0.16756 & 0.33512 & 0.83244 \tabularnewline
97 & 0.245582 & 0.491163 & 0.754418 \tabularnewline
98 & 0.232476 & 0.464953 & 0.767524 \tabularnewline
99 & 0.258177 & 0.516353 & 0.741823 \tabularnewline
100 & 0.319638 & 0.639275 & 0.680362 \tabularnewline
101 & 0.294589 & 0.589178 & 0.705411 \tabularnewline
102 & 0.284088 & 0.568177 & 0.715912 \tabularnewline
103 & 0.298347 & 0.596695 & 0.701653 \tabularnewline
104 & 0.335516 & 0.671032 & 0.664484 \tabularnewline
105 & 0.359419 & 0.718837 & 0.640581 \tabularnewline
106 & 0.401088 & 0.802176 & 0.598912 \tabularnewline
107 & 0.414662 & 0.829325 & 0.585338 \tabularnewline
108 & 0.662807 & 0.674386 & 0.337193 \tabularnewline
109 & 0.714398 & 0.571204 & 0.285602 \tabularnewline
110 & 0.734302 & 0.531396 & 0.265698 \tabularnewline
111 & 0.729194 & 0.541612 & 0.270806 \tabularnewline
112 & 0.716692 & 0.566617 & 0.283308 \tabularnewline
113 & 0.835985 & 0.32803 & 0.164015 \tabularnewline
114 & 0.832542 & 0.334916 & 0.167458 \tabularnewline
115 & 0.916897 & 0.166206 & 0.0831028 \tabularnewline
116 & 0.956518 & 0.0869641 & 0.043482 \tabularnewline
117 & 0.958073 & 0.0838531 & 0.0419265 \tabularnewline
118 & 0.960386 & 0.079228 & 0.039614 \tabularnewline
119 & 0.967601 & 0.0647979 & 0.0323989 \tabularnewline
120 & 0.98143 & 0.0371405 & 0.0185703 \tabularnewline
121 & 0.985977 & 0.0280463 & 0.0140232 \tabularnewline
122 & 0.98904 & 0.0219195 & 0.0109597 \tabularnewline
123 & 0.994152 & 0.0116956 & 0.00584779 \tabularnewline
124 & 0.99739 & 0.00521938 & 0.00260969 \tabularnewline
125 & 0.997434 & 0.00513113 & 0.00256557 \tabularnewline
126 & 0.997104 & 0.00579214 & 0.00289607 \tabularnewline
127 & 0.997779 & 0.00444161 & 0.00222081 \tabularnewline
128 & 0.997449 & 0.00510104 & 0.00255052 \tabularnewline
129 & 0.99871 & 0.00257907 & 0.00128953 \tabularnewline
130 & 0.998783 & 0.00243367 & 0.00121683 \tabularnewline
131 & 0.998901 & 0.00219768 & 0.00109884 \tabularnewline
132 & 0.998967 & 0.00206616 & 0.00103308 \tabularnewline
133 & 0.998957 & 0.00208558 & 0.00104279 \tabularnewline
134 & 0.998861 & 0.00227896 & 0.00113948 \tabularnewline
135 & 0.998608 & 0.00278338 & 0.00139169 \tabularnewline
136 & 0.998269 & 0.00346199 & 0.001731 \tabularnewline
137 & 0.999153 & 0.00169348 & 0.000846738 \tabularnewline
138 & 0.999012 & 0.00197678 & 0.00098839 \tabularnewline
139 & 0.99923 & 0.00154082 & 0.000770412 \tabularnewline
140 & 0.999137 & 0.00172546 & 0.00086273 \tabularnewline
141 & 0.998889 & 0.00222131 & 0.00111065 \tabularnewline
142 & 0.999492 & 0.00101508 & 0.000507541 \tabularnewline
143 & 0.999464 & 0.00107269 & 0.000536343 \tabularnewline
144 & 0.999665 & 0.000670795 & 0.000335397 \tabularnewline
145 & 0.99965 & 0.000699498 & 0.000349749 \tabularnewline
146 & 0.999663 & 0.000674808 & 0.000337404 \tabularnewline
147 & 0.999587 & 0.000826858 & 0.000413429 \tabularnewline
148 & 0.999498 & 0.00100303 & 0.000501517 \tabularnewline
149 & 0.999409 & 0.00118112 & 0.00059056 \tabularnewline
150 & 0.999599 & 0.000802486 & 0.000401243 \tabularnewline
151 & 0.99989 & 0.00022096 & 0.00011048 \tabularnewline
152 & 0.999866 & 0.000267061 & 0.00013353 \tabularnewline
153 & 0.999911 & 0.000178222 & 8.91109e-05 \tabularnewline
154 & 0.999906 & 0.000187343 & 9.36717e-05 \tabularnewline
155 & 0.999923 & 0.000154469 & 7.72343e-05 \tabularnewline
156 & 0.999897 & 0.000205241 & 0.00010262 \tabularnewline
157 & 0.999897 & 0.000205768 & 0.000102884 \tabularnewline
158 & 0.999888 & 0.000224807 & 0.000112404 \tabularnewline
159 & 0.999864 & 0.00027267 & 0.000136335 \tabularnewline
160 & 0.999818 & 0.000364726 & 0.000182363 \tabularnewline
161 & 0.99984 & 0.000320568 & 0.000160284 \tabularnewline
162 & 0.999854 & 0.000291383 & 0.000145691 \tabularnewline
163 & 0.999836 & 0.000327271 & 0.000163636 \tabularnewline
164 & 0.999985 & 2.98975e-05 & 1.49488e-05 \tabularnewline
165 & 0.999987 & 2.57457e-05 & 1.28729e-05 \tabularnewline
166 & 0.999981 & 3.70667e-05 & 1.85334e-05 \tabularnewline
167 & 0.999984 & 3.22698e-05 & 1.61349e-05 \tabularnewline
168 & 0.999989 & 2.1421e-05 & 1.07105e-05 \tabularnewline
169 & 0.999987 & 2.68835e-05 & 1.34417e-05 \tabularnewline
170 & 0.999986 & 2.73052e-05 & 1.36526e-05 \tabularnewline
171 & 0.999985 & 3.07145e-05 & 1.53573e-05 \tabularnewline
172 & 0.999989 & 2.10231e-05 & 1.05116e-05 \tabularnewline
173 & 0.999987 & 2.5412e-05 & 1.2706e-05 \tabularnewline
174 & 0.999984 & 3.10717e-05 & 1.55358e-05 \tabularnewline
175 & 0.999981 & 3.81793e-05 & 1.90897e-05 \tabularnewline
176 & 0.999983 & 3.32838e-05 & 1.66419e-05 \tabularnewline
177 & 0.99998 & 3.93554e-05 & 1.96777e-05 \tabularnewline
178 & 0.999986 & 2.73167e-05 & 1.36584e-05 \tabularnewline
179 & 0.999982 & 3.54212e-05 & 1.77106e-05 \tabularnewline
180 & 0.999984 & 3.27385e-05 & 1.63692e-05 \tabularnewline
181 & 0.999982 & 3.64555e-05 & 1.82278e-05 \tabularnewline
182 & 0.999975 & 5.0631e-05 & 2.53155e-05 \tabularnewline
183 & 0.999975 & 4.95547e-05 & 2.47774e-05 \tabularnewline
184 & 0.999965 & 6.98119e-05 & 3.49059e-05 \tabularnewline
185 & 0.999963 & 7.49748e-05 & 3.74874e-05 \tabularnewline
186 & 0.999951 & 9.79391e-05 & 4.89695e-05 \tabularnewline
187 & 0.999979 & 4.23899e-05 & 2.1195e-05 \tabularnewline
188 & 0.999971 & 5.89607e-05 & 2.94804e-05 \tabularnewline
189 & 0.999957 & 8.53484e-05 & 4.26742e-05 \tabularnewline
190 & 0.999938 & 0.00012491 & 6.24552e-05 \tabularnewline
191 & 0.999912 & 0.0001756 & 8.78001e-05 \tabularnewline
192 & 0.999877 & 0.00024552 & 0.00012276 \tabularnewline
193 & 0.999854 & 0.000291294 & 0.000145647 \tabularnewline
194 & 0.999923 & 0.000153687 & 7.68437e-05 \tabularnewline
195 & 0.999896 & 0.00020783 & 0.000103915 \tabularnewline
196 & 0.99988 & 0.000239795 & 0.000119897 \tabularnewline
197 & 0.999871 & 0.00025877 & 0.000129385 \tabularnewline
198 & 0.999817 & 0.000366784 & 0.000183392 \tabularnewline
199 & 0.999847 & 0.000306282 & 0.000153141 \tabularnewline
200 & 0.999824 & 0.00035235 & 0.000176175 \tabularnewline
201 & 0.999806 & 0.000388635 & 0.000194318 \tabularnewline
202 & 0.99978 & 0.000439978 & 0.000219989 \tabularnewline
203 & 0.999736 & 0.000528251 & 0.000264126 \tabularnewline
204 & 0.999661 & 0.000678513 & 0.000339257 \tabularnewline
205 & 0.999526 & 0.000948896 & 0.000474448 \tabularnewline
206 & 0.999662 & 0.00067617 & 0.000338085 \tabularnewline
207 & 0.999549 & 0.000902092 & 0.000451046 \tabularnewline
208 & 0.999492 & 0.00101635 & 0.000508177 \tabularnewline
209 & 0.999425 & 0.001151 & 0.000575499 \tabularnewline
210 & 0.999329 & 0.00134274 & 0.000671369 \tabularnewline
211 & 0.999046 & 0.00190702 & 0.000953511 \tabularnewline
212 & 0.998729 & 0.00254235 & 0.00127118 \tabularnewline
213 & 0.998969 & 0.00206222 & 0.00103111 \tabularnewline
214 & 0.99867 & 0.0026592 & 0.0013296 \tabularnewline
215 & 0.998495 & 0.00300961 & 0.0015048 \tabularnewline
216 & 0.997981 & 0.00403759 & 0.00201879 \tabularnewline
217 & 0.997732 & 0.00453558 & 0.00226779 \tabularnewline
218 & 0.997363 & 0.00527378 & 0.00263689 \tabularnewline
219 & 0.996311 & 0.00737788 & 0.00368894 \tabularnewline
220 & 0.995077 & 0.00984578 & 0.00492289 \tabularnewline
221 & 0.995082 & 0.00983677 & 0.00491839 \tabularnewline
222 & 0.995589 & 0.00882144 & 0.00441072 \tabularnewline
223 & 0.993882 & 0.0122354 & 0.00611769 \tabularnewline
224 & 0.993668 & 0.0126641 & 0.00633204 \tabularnewline
225 & 0.9932 & 0.0136006 & 0.00680031 \tabularnewline
226 & 0.996487 & 0.00702631 & 0.00351316 \tabularnewline
227 & 0.997345 & 0.00530919 & 0.0026546 \tabularnewline
228 & 0.997968 & 0.00406387 & 0.00203194 \tabularnewline
229 & 0.997252 & 0.00549532 & 0.00274766 \tabularnewline
230 & 0.997928 & 0.00414326 & 0.00207163 \tabularnewline
231 & 0.998853 & 0.00229325 & 0.00114663 \tabularnewline
232 & 0.99838 & 0.00323974 & 0.00161987 \tabularnewline
233 & 0.997776 & 0.00444825 & 0.00222413 \tabularnewline
234 & 0.997202 & 0.0055966 & 0.0027983 \tabularnewline
235 & 0.996827 & 0.00634609 & 0.00317305 \tabularnewline
236 & 0.999337 & 0.00132587 & 0.000662936 \tabularnewline
237 & 0.999238 & 0.00152359 & 0.000761795 \tabularnewline
238 & 0.999101 & 0.0017982 & 0.000899102 \tabularnewline
239 & 0.998651 & 0.00269741 & 0.00134871 \tabularnewline
240 & 0.997886 & 0.0042276 & 0.0021138 \tabularnewline
241 & 0.99716 & 0.00568024 & 0.00284012 \tabularnewline
242 & 0.995841 & 0.00831808 & 0.00415904 \tabularnewline
243 & 0.995005 & 0.0099897 & 0.00499485 \tabularnewline
244 & 0.993459 & 0.0130822 & 0.00654112 \tabularnewline
245 & 0.990132 & 0.0197355 & 0.00986774 \tabularnewline
246 & 0.985548 & 0.0289031 & 0.0144515 \tabularnewline
247 & 0.980725 & 0.0385496 & 0.0192748 \tabularnewline
248 & 0.973891 & 0.0522176 & 0.0261088 \tabularnewline
249 & 0.963455 & 0.0730898 & 0.0365449 \tabularnewline
250 & 0.948795 & 0.10241 & 0.0512051 \tabularnewline
251 & 0.932888 & 0.134225 & 0.0671123 \tabularnewline
252 & 0.926363 & 0.147274 & 0.0736372 \tabularnewline
253 & 0.90051 & 0.198981 & 0.0994903 \tabularnewline
254 & 0.867984 & 0.264031 & 0.132016 \tabularnewline
255 & 0.883266 & 0.233468 & 0.116734 \tabularnewline
256 & 0.85043 & 0.299141 & 0.14957 \tabularnewline
257 & 0.856047 & 0.287905 & 0.143953 \tabularnewline
258 & 0.939345 & 0.121309 & 0.0606546 \tabularnewline
259 & 0.940217 & 0.119566 & 0.0597828 \tabularnewline
260 & 0.99946 & 0.00108091 & 0.000540457 \tabularnewline
261 & 0.999027 & 0.0019458 & 0.000972902 \tabularnewline
262 & 0.998572 & 0.0028562 & 0.0014281 \tabularnewline
263 & 0.999989 & 2.1455e-05 & 1.07275e-05 \tabularnewline
264 & 0.999961 & 7.77152e-05 & 3.88576e-05 \tabularnewline
265 & 0.999954 & 9.22914e-05 & 4.61457e-05 \tabularnewline
266 & 0.99991 & 0.000179972 & 8.99861e-05 \tabularnewline
267 & 0.999954 & 9.25342e-05 & 4.62671e-05 \tabularnewline
268 & 0.999847 & 0.000306789 & 0.000153395 \tabularnewline
269 & 0.999636 & 0.000728389 & 0.000364195 \tabularnewline
270 & 0.99824 & 0.00352091 & 0.00176046 \tabularnewline
271 & 0.996136 & 0.00772786 & 0.00386393 \tabularnewline
272 & 0.991958 & 0.016083 & 0.00804152 \tabularnewline
273 & 0.958617 & 0.0827662 & 0.0413831 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268302&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]6[/C][C]0.714315[/C][C]0.57137[/C][C]0.285685[/C][/ROW]
[ROW][C]7[/C][C]0.717167[/C][C]0.565667[/C][C]0.282833[/C][/ROW]
[ROW][C]8[/C][C]0.615605[/C][C]0.76879[/C][C]0.384395[/C][/ROW]
[ROW][C]9[/C][C]0.527903[/C][C]0.944195[/C][C]0.472097[/C][/ROW]
[ROW][C]10[/C][C]0.498802[/C][C]0.997603[/C][C]0.501198[/C][/ROW]
[ROW][C]11[/C][C]0.393469[/C][C]0.786937[/C][C]0.606531[/C][/ROW]
[ROW][C]12[/C][C]0.586207[/C][C]0.827585[/C][C]0.413793[/C][/ROW]
[ROW][C]13[/C][C]0.497459[/C][C]0.994919[/C][C]0.502541[/C][/ROW]
[ROW][C]14[/C][C]0.412449[/C][C]0.824897[/C][C]0.587551[/C][/ROW]
[ROW][C]15[/C][C]0.374414[/C][C]0.748828[/C][C]0.625586[/C][/ROW]
[ROW][C]16[/C][C]0.33977[/C][C]0.67954[/C][C]0.66023[/C][/ROW]
[ROW][C]17[/C][C]0.272227[/C][C]0.544454[/C][C]0.727773[/C][/ROW]
[ROW][C]18[/C][C]0.214387[/C][C]0.428775[/C][C]0.785613[/C][/ROW]
[ROW][C]19[/C][C]0.166979[/C][C]0.333957[/C][C]0.833021[/C][/ROW]
[ROW][C]20[/C][C]0.125492[/C][C]0.250984[/C][C]0.874508[/C][/ROW]
[ROW][C]21[/C][C]0.131746[/C][C]0.263491[/C][C]0.868254[/C][/ROW]
[ROW][C]22[/C][C]0.200983[/C][C]0.401967[/C][C]0.799017[/C][/ROW]
[ROW][C]23[/C][C]0.162109[/C][C]0.324219[/C][C]0.837891[/C][/ROW]
[ROW][C]24[/C][C]0.140744[/C][C]0.281487[/C][C]0.859256[/C][/ROW]
[ROW][C]25[/C][C]0.11043[/C][C]0.22086[/C][C]0.88957[/C][/ROW]
[ROW][C]26[/C][C]0.103984[/C][C]0.207967[/C][C]0.896016[/C][/ROW]
[ROW][C]27[/C][C]0.128986[/C][C]0.257973[/C][C]0.871014[/C][/ROW]
[ROW][C]28[/C][C]0.134016[/C][C]0.268033[/C][C]0.865984[/C][/ROW]
[ROW][C]29[/C][C]0.121562[/C][C]0.243125[/C][C]0.878438[/C][/ROW]
[ROW][C]30[/C][C]0.0991239[/C][C]0.198248[/C][C]0.900876[/C][/ROW]
[ROW][C]31[/C][C]0.0966745[/C][C]0.193349[/C][C]0.903325[/C][/ROW]
[ROW][C]32[/C][C]0.0802898[/C][C]0.16058[/C][C]0.91971[/C][/ROW]
[ROW][C]33[/C][C]0.0663717[/C][C]0.132743[/C][C]0.933628[/C][/ROW]
[ROW][C]34[/C][C]0.0578469[/C][C]0.115694[/C][C]0.942153[/C][/ROW]
[ROW][C]35[/C][C]0.0442742[/C][C]0.0885483[/C][C]0.955726[/C][/ROW]
[ROW][C]36[/C][C]0.033519[/C][C]0.0670379[/C][C]0.966481[/C][/ROW]
[ROW][C]37[/C][C]0.0256969[/C][C]0.0513938[/C][C]0.974303[/C][/ROW]
[ROW][C]38[/C][C]0.0305813[/C][C]0.0611625[/C][C]0.969419[/C][/ROW]
[ROW][C]39[/C][C]0.0287387[/C][C]0.0574774[/C][C]0.971261[/C][/ROW]
[ROW][C]40[/C][C]0.0224788[/C][C]0.0449577[/C][C]0.977521[/C][/ROW]
[ROW][C]41[/C][C]0.038619[/C][C]0.0772379[/C][C]0.961381[/C][/ROW]
[ROW][C]42[/C][C]0.0313327[/C][C]0.0626655[/C][C]0.968667[/C][/ROW]
[ROW][C]43[/C][C]0.0274792[/C][C]0.0549585[/C][C]0.972521[/C][/ROW]
[ROW][C]44[/C][C]0.0222718[/C][C]0.0445436[/C][C]0.977728[/C][/ROW]
[ROW][C]45[/C][C]0.0211367[/C][C]0.0422734[/C][C]0.978863[/C][/ROW]
[ROW][C]46[/C][C]0.0174211[/C][C]0.0348421[/C][C]0.982579[/C][/ROW]
[ROW][C]47[/C][C]0.0132435[/C][C]0.026487[/C][C]0.986756[/C][/ROW]
[ROW][C]48[/C][C]0.0146041[/C][C]0.0292082[/C][C]0.985396[/C][/ROW]
[ROW][C]49[/C][C]0.012484[/C][C]0.024968[/C][C]0.987516[/C][/ROW]
[ROW][C]50[/C][C]0.0143686[/C][C]0.0287372[/C][C]0.985631[/C][/ROW]
[ROW][C]51[/C][C]0.0113781[/C][C]0.0227562[/C][C]0.988622[/C][/ROW]
[ROW][C]52[/C][C]0.0132396[/C][C]0.0264791[/C][C]0.98676[/C][/ROW]
[ROW][C]53[/C][C]0.0105461[/C][C]0.0210923[/C][C]0.989454[/C][/ROW]
[ROW][C]54[/C][C]0.00935073[/C][C]0.0187015[/C][C]0.990649[/C][/ROW]
[ROW][C]55[/C][C]0.00911413[/C][C]0.0182283[/C][C]0.990886[/C][/ROW]
[ROW][C]56[/C][C]0.00709608[/C][C]0.0141922[/C][C]0.992904[/C][/ROW]
[ROW][C]57[/C][C]0.0163158[/C][C]0.0326316[/C][C]0.983684[/C][/ROW]
[ROW][C]58[/C][C]0.0205456[/C][C]0.0410912[/C][C]0.979454[/C][/ROW]
[ROW][C]59[/C][C]0.0161675[/C][C]0.032335[/C][C]0.983833[/C][/ROW]
[ROW][C]60[/C][C]0.0158238[/C][C]0.0316476[/C][C]0.984176[/C][/ROW]
[ROW][C]61[/C][C]0.0229605[/C][C]0.045921[/C][C]0.977039[/C][/ROW]
[ROW][C]62[/C][C]0.0229369[/C][C]0.0458738[/C][C]0.977063[/C][/ROW]
[ROW][C]63[/C][C]0.0278501[/C][C]0.0557002[/C][C]0.97215[/C][/ROW]
[ROW][C]64[/C][C]0.0354333[/C][C]0.0708667[/C][C]0.964567[/C][/ROW]
[ROW][C]65[/C][C]0.040688[/C][C]0.081376[/C][C]0.959312[/C][/ROW]
[ROW][C]66[/C][C]0.0334164[/C][C]0.0668329[/C][C]0.966584[/C][/ROW]
[ROW][C]67[/C][C]0.0347896[/C][C]0.0695792[/C][C]0.96521[/C][/ROW]
[ROW][C]68[/C][C]0.0401146[/C][C]0.0802293[/C][C]0.959885[/C][/ROW]
[ROW][C]69[/C][C]0.0491698[/C][C]0.0983396[/C][C]0.95083[/C][/ROW]
[ROW][C]70[/C][C]0.0445746[/C][C]0.0891491[/C][C]0.955425[/C][/ROW]
[ROW][C]71[/C][C]0.0424089[/C][C]0.0848179[/C][C]0.957591[/C][/ROW]
[ROW][C]72[/C][C]0.0366366[/C][C]0.0732732[/C][C]0.963363[/C][/ROW]
[ROW][C]73[/C][C]0.0340297[/C][C]0.0680594[/C][C]0.96597[/C][/ROW]
[ROW][C]74[/C][C]0.0401533[/C][C]0.0803066[/C][C]0.959847[/C][/ROW]
[ROW][C]75[/C][C]0.0362543[/C][C]0.0725085[/C][C]0.963746[/C][/ROW]
[ROW][C]76[/C][C]0.0339991[/C][C]0.0679983[/C][C]0.966001[/C][/ROW]
[ROW][C]77[/C][C]0.0325737[/C][C]0.0651474[/C][C]0.967426[/C][/ROW]
[ROW][C]78[/C][C]0.0306526[/C][C]0.0613051[/C][C]0.969347[/C][/ROW]
[ROW][C]79[/C][C]0.0250329[/C][C]0.0500659[/C][C]0.974967[/C][/ROW]
[ROW][C]80[/C][C]0.0384669[/C][C]0.0769339[/C][C]0.961533[/C][/ROW]
[ROW][C]81[/C][C]0.0326327[/C][C]0.0652654[/C][C]0.967367[/C][/ROW]
[ROW][C]82[/C][C]0.0343685[/C][C]0.0687371[/C][C]0.965631[/C][/ROW]
[ROW][C]83[/C][C]0.0290636[/C][C]0.0581272[/C][C]0.970936[/C][/ROW]
[ROW][C]84[/C][C]0.0887881[/C][C]0.177576[/C][C]0.911212[/C][/ROW]
[ROW][C]85[/C][C]0.0868476[/C][C]0.173695[/C][C]0.913152[/C][/ROW]
[ROW][C]86[/C][C]0.0791301[/C][C]0.15826[/C][C]0.92087[/C][/ROW]
[ROW][C]87[/C][C]0.0691929[/C][C]0.138386[/C][C]0.930807[/C][/ROW]
[ROW][C]88[/C][C]0.0624188[/C][C]0.124838[/C][C]0.937581[/C][/ROW]
[ROW][C]89[/C][C]0.0614055[/C][C]0.122811[/C][C]0.938595[/C][/ROW]
[ROW][C]90[/C][C]0.0606082[/C][C]0.121216[/C][C]0.939392[/C][/ROW]
[ROW][C]91[/C][C]0.0592209[/C][C]0.118442[/C][C]0.940779[/C][/ROW]
[ROW][C]92[/C][C]0.12398[/C][C]0.247959[/C][C]0.87602[/C][/ROW]
[ROW][C]93[/C][C]0.148561[/C][C]0.297121[/C][C]0.851439[/C][/ROW]
[ROW][C]94[/C][C]0.145212[/C][C]0.290424[/C][C]0.854788[/C][/ROW]
[ROW][C]95[/C][C]0.161738[/C][C]0.323476[/C][C]0.838262[/C][/ROW]
[ROW][C]96[/C][C]0.16756[/C][C]0.33512[/C][C]0.83244[/C][/ROW]
[ROW][C]97[/C][C]0.245582[/C][C]0.491163[/C][C]0.754418[/C][/ROW]
[ROW][C]98[/C][C]0.232476[/C][C]0.464953[/C][C]0.767524[/C][/ROW]
[ROW][C]99[/C][C]0.258177[/C][C]0.516353[/C][C]0.741823[/C][/ROW]
[ROW][C]100[/C][C]0.319638[/C][C]0.639275[/C][C]0.680362[/C][/ROW]
[ROW][C]101[/C][C]0.294589[/C][C]0.589178[/C][C]0.705411[/C][/ROW]
[ROW][C]102[/C][C]0.284088[/C][C]0.568177[/C][C]0.715912[/C][/ROW]
[ROW][C]103[/C][C]0.298347[/C][C]0.596695[/C][C]0.701653[/C][/ROW]
[ROW][C]104[/C][C]0.335516[/C][C]0.671032[/C][C]0.664484[/C][/ROW]
[ROW][C]105[/C][C]0.359419[/C][C]0.718837[/C][C]0.640581[/C][/ROW]
[ROW][C]106[/C][C]0.401088[/C][C]0.802176[/C][C]0.598912[/C][/ROW]
[ROW][C]107[/C][C]0.414662[/C][C]0.829325[/C][C]0.585338[/C][/ROW]
[ROW][C]108[/C][C]0.662807[/C][C]0.674386[/C][C]0.337193[/C][/ROW]
[ROW][C]109[/C][C]0.714398[/C][C]0.571204[/C][C]0.285602[/C][/ROW]
[ROW][C]110[/C][C]0.734302[/C][C]0.531396[/C][C]0.265698[/C][/ROW]
[ROW][C]111[/C][C]0.729194[/C][C]0.541612[/C][C]0.270806[/C][/ROW]
[ROW][C]112[/C][C]0.716692[/C][C]0.566617[/C][C]0.283308[/C][/ROW]
[ROW][C]113[/C][C]0.835985[/C][C]0.32803[/C][C]0.164015[/C][/ROW]
[ROW][C]114[/C][C]0.832542[/C][C]0.334916[/C][C]0.167458[/C][/ROW]
[ROW][C]115[/C][C]0.916897[/C][C]0.166206[/C][C]0.0831028[/C][/ROW]
[ROW][C]116[/C][C]0.956518[/C][C]0.0869641[/C][C]0.043482[/C][/ROW]
[ROW][C]117[/C][C]0.958073[/C][C]0.0838531[/C][C]0.0419265[/C][/ROW]
[ROW][C]118[/C][C]0.960386[/C][C]0.079228[/C][C]0.039614[/C][/ROW]
[ROW][C]119[/C][C]0.967601[/C][C]0.0647979[/C][C]0.0323989[/C][/ROW]
[ROW][C]120[/C][C]0.98143[/C][C]0.0371405[/C][C]0.0185703[/C][/ROW]
[ROW][C]121[/C][C]0.985977[/C][C]0.0280463[/C][C]0.0140232[/C][/ROW]
[ROW][C]122[/C][C]0.98904[/C][C]0.0219195[/C][C]0.0109597[/C][/ROW]
[ROW][C]123[/C][C]0.994152[/C][C]0.0116956[/C][C]0.00584779[/C][/ROW]
[ROW][C]124[/C][C]0.99739[/C][C]0.00521938[/C][C]0.00260969[/C][/ROW]
[ROW][C]125[/C][C]0.997434[/C][C]0.00513113[/C][C]0.00256557[/C][/ROW]
[ROW][C]126[/C][C]0.997104[/C][C]0.00579214[/C][C]0.00289607[/C][/ROW]
[ROW][C]127[/C][C]0.997779[/C][C]0.00444161[/C][C]0.00222081[/C][/ROW]
[ROW][C]128[/C][C]0.997449[/C][C]0.00510104[/C][C]0.00255052[/C][/ROW]
[ROW][C]129[/C][C]0.99871[/C][C]0.00257907[/C][C]0.00128953[/C][/ROW]
[ROW][C]130[/C][C]0.998783[/C][C]0.00243367[/C][C]0.00121683[/C][/ROW]
[ROW][C]131[/C][C]0.998901[/C][C]0.00219768[/C][C]0.00109884[/C][/ROW]
[ROW][C]132[/C][C]0.998967[/C][C]0.00206616[/C][C]0.00103308[/C][/ROW]
[ROW][C]133[/C][C]0.998957[/C][C]0.00208558[/C][C]0.00104279[/C][/ROW]
[ROW][C]134[/C][C]0.998861[/C][C]0.00227896[/C][C]0.00113948[/C][/ROW]
[ROW][C]135[/C][C]0.998608[/C][C]0.00278338[/C][C]0.00139169[/C][/ROW]
[ROW][C]136[/C][C]0.998269[/C][C]0.00346199[/C][C]0.001731[/C][/ROW]
[ROW][C]137[/C][C]0.999153[/C][C]0.00169348[/C][C]0.000846738[/C][/ROW]
[ROW][C]138[/C][C]0.999012[/C][C]0.00197678[/C][C]0.00098839[/C][/ROW]
[ROW][C]139[/C][C]0.99923[/C][C]0.00154082[/C][C]0.000770412[/C][/ROW]
[ROW][C]140[/C][C]0.999137[/C][C]0.00172546[/C][C]0.00086273[/C][/ROW]
[ROW][C]141[/C][C]0.998889[/C][C]0.00222131[/C][C]0.00111065[/C][/ROW]
[ROW][C]142[/C][C]0.999492[/C][C]0.00101508[/C][C]0.000507541[/C][/ROW]
[ROW][C]143[/C][C]0.999464[/C][C]0.00107269[/C][C]0.000536343[/C][/ROW]
[ROW][C]144[/C][C]0.999665[/C][C]0.000670795[/C][C]0.000335397[/C][/ROW]
[ROW][C]145[/C][C]0.99965[/C][C]0.000699498[/C][C]0.000349749[/C][/ROW]
[ROW][C]146[/C][C]0.999663[/C][C]0.000674808[/C][C]0.000337404[/C][/ROW]
[ROW][C]147[/C][C]0.999587[/C][C]0.000826858[/C][C]0.000413429[/C][/ROW]
[ROW][C]148[/C][C]0.999498[/C][C]0.00100303[/C][C]0.000501517[/C][/ROW]
[ROW][C]149[/C][C]0.999409[/C][C]0.00118112[/C][C]0.00059056[/C][/ROW]
[ROW][C]150[/C][C]0.999599[/C][C]0.000802486[/C][C]0.000401243[/C][/ROW]
[ROW][C]151[/C][C]0.99989[/C][C]0.00022096[/C][C]0.00011048[/C][/ROW]
[ROW][C]152[/C][C]0.999866[/C][C]0.000267061[/C][C]0.00013353[/C][/ROW]
[ROW][C]153[/C][C]0.999911[/C][C]0.000178222[/C][C]8.91109e-05[/C][/ROW]
[ROW][C]154[/C][C]0.999906[/C][C]0.000187343[/C][C]9.36717e-05[/C][/ROW]
[ROW][C]155[/C][C]0.999923[/C][C]0.000154469[/C][C]7.72343e-05[/C][/ROW]
[ROW][C]156[/C][C]0.999897[/C][C]0.000205241[/C][C]0.00010262[/C][/ROW]
[ROW][C]157[/C][C]0.999897[/C][C]0.000205768[/C][C]0.000102884[/C][/ROW]
[ROW][C]158[/C][C]0.999888[/C][C]0.000224807[/C][C]0.000112404[/C][/ROW]
[ROW][C]159[/C][C]0.999864[/C][C]0.00027267[/C][C]0.000136335[/C][/ROW]
[ROW][C]160[/C][C]0.999818[/C][C]0.000364726[/C][C]0.000182363[/C][/ROW]
[ROW][C]161[/C][C]0.99984[/C][C]0.000320568[/C][C]0.000160284[/C][/ROW]
[ROW][C]162[/C][C]0.999854[/C][C]0.000291383[/C][C]0.000145691[/C][/ROW]
[ROW][C]163[/C][C]0.999836[/C][C]0.000327271[/C][C]0.000163636[/C][/ROW]
[ROW][C]164[/C][C]0.999985[/C][C]2.98975e-05[/C][C]1.49488e-05[/C][/ROW]
[ROW][C]165[/C][C]0.999987[/C][C]2.57457e-05[/C][C]1.28729e-05[/C][/ROW]
[ROW][C]166[/C][C]0.999981[/C][C]3.70667e-05[/C][C]1.85334e-05[/C][/ROW]
[ROW][C]167[/C][C]0.999984[/C][C]3.22698e-05[/C][C]1.61349e-05[/C][/ROW]
[ROW][C]168[/C][C]0.999989[/C][C]2.1421e-05[/C][C]1.07105e-05[/C][/ROW]
[ROW][C]169[/C][C]0.999987[/C][C]2.68835e-05[/C][C]1.34417e-05[/C][/ROW]
[ROW][C]170[/C][C]0.999986[/C][C]2.73052e-05[/C][C]1.36526e-05[/C][/ROW]
[ROW][C]171[/C][C]0.999985[/C][C]3.07145e-05[/C][C]1.53573e-05[/C][/ROW]
[ROW][C]172[/C][C]0.999989[/C][C]2.10231e-05[/C][C]1.05116e-05[/C][/ROW]
[ROW][C]173[/C][C]0.999987[/C][C]2.5412e-05[/C][C]1.2706e-05[/C][/ROW]
[ROW][C]174[/C][C]0.999984[/C][C]3.10717e-05[/C][C]1.55358e-05[/C][/ROW]
[ROW][C]175[/C][C]0.999981[/C][C]3.81793e-05[/C][C]1.90897e-05[/C][/ROW]
[ROW][C]176[/C][C]0.999983[/C][C]3.32838e-05[/C][C]1.66419e-05[/C][/ROW]
[ROW][C]177[/C][C]0.99998[/C][C]3.93554e-05[/C][C]1.96777e-05[/C][/ROW]
[ROW][C]178[/C][C]0.999986[/C][C]2.73167e-05[/C][C]1.36584e-05[/C][/ROW]
[ROW][C]179[/C][C]0.999982[/C][C]3.54212e-05[/C][C]1.77106e-05[/C][/ROW]
[ROW][C]180[/C][C]0.999984[/C][C]3.27385e-05[/C][C]1.63692e-05[/C][/ROW]
[ROW][C]181[/C][C]0.999982[/C][C]3.64555e-05[/C][C]1.82278e-05[/C][/ROW]
[ROW][C]182[/C][C]0.999975[/C][C]5.0631e-05[/C][C]2.53155e-05[/C][/ROW]
[ROW][C]183[/C][C]0.999975[/C][C]4.95547e-05[/C][C]2.47774e-05[/C][/ROW]
[ROW][C]184[/C][C]0.999965[/C][C]6.98119e-05[/C][C]3.49059e-05[/C][/ROW]
[ROW][C]185[/C][C]0.999963[/C][C]7.49748e-05[/C][C]3.74874e-05[/C][/ROW]
[ROW][C]186[/C][C]0.999951[/C][C]9.79391e-05[/C][C]4.89695e-05[/C][/ROW]
[ROW][C]187[/C][C]0.999979[/C][C]4.23899e-05[/C][C]2.1195e-05[/C][/ROW]
[ROW][C]188[/C][C]0.999971[/C][C]5.89607e-05[/C][C]2.94804e-05[/C][/ROW]
[ROW][C]189[/C][C]0.999957[/C][C]8.53484e-05[/C][C]4.26742e-05[/C][/ROW]
[ROW][C]190[/C][C]0.999938[/C][C]0.00012491[/C][C]6.24552e-05[/C][/ROW]
[ROW][C]191[/C][C]0.999912[/C][C]0.0001756[/C][C]8.78001e-05[/C][/ROW]
[ROW][C]192[/C][C]0.999877[/C][C]0.00024552[/C][C]0.00012276[/C][/ROW]
[ROW][C]193[/C][C]0.999854[/C][C]0.000291294[/C][C]0.000145647[/C][/ROW]
[ROW][C]194[/C][C]0.999923[/C][C]0.000153687[/C][C]7.68437e-05[/C][/ROW]
[ROW][C]195[/C][C]0.999896[/C][C]0.00020783[/C][C]0.000103915[/C][/ROW]
[ROW][C]196[/C][C]0.99988[/C][C]0.000239795[/C][C]0.000119897[/C][/ROW]
[ROW][C]197[/C][C]0.999871[/C][C]0.00025877[/C][C]0.000129385[/C][/ROW]
[ROW][C]198[/C][C]0.999817[/C][C]0.000366784[/C][C]0.000183392[/C][/ROW]
[ROW][C]199[/C][C]0.999847[/C][C]0.000306282[/C][C]0.000153141[/C][/ROW]
[ROW][C]200[/C][C]0.999824[/C][C]0.00035235[/C][C]0.000176175[/C][/ROW]
[ROW][C]201[/C][C]0.999806[/C][C]0.000388635[/C][C]0.000194318[/C][/ROW]
[ROW][C]202[/C][C]0.99978[/C][C]0.000439978[/C][C]0.000219989[/C][/ROW]
[ROW][C]203[/C][C]0.999736[/C][C]0.000528251[/C][C]0.000264126[/C][/ROW]
[ROW][C]204[/C][C]0.999661[/C][C]0.000678513[/C][C]0.000339257[/C][/ROW]
[ROW][C]205[/C][C]0.999526[/C][C]0.000948896[/C][C]0.000474448[/C][/ROW]
[ROW][C]206[/C][C]0.999662[/C][C]0.00067617[/C][C]0.000338085[/C][/ROW]
[ROW][C]207[/C][C]0.999549[/C][C]0.000902092[/C][C]0.000451046[/C][/ROW]
[ROW][C]208[/C][C]0.999492[/C][C]0.00101635[/C][C]0.000508177[/C][/ROW]
[ROW][C]209[/C][C]0.999425[/C][C]0.001151[/C][C]0.000575499[/C][/ROW]
[ROW][C]210[/C][C]0.999329[/C][C]0.00134274[/C][C]0.000671369[/C][/ROW]
[ROW][C]211[/C][C]0.999046[/C][C]0.00190702[/C][C]0.000953511[/C][/ROW]
[ROW][C]212[/C][C]0.998729[/C][C]0.00254235[/C][C]0.00127118[/C][/ROW]
[ROW][C]213[/C][C]0.998969[/C][C]0.00206222[/C][C]0.00103111[/C][/ROW]
[ROW][C]214[/C][C]0.99867[/C][C]0.0026592[/C][C]0.0013296[/C][/ROW]
[ROW][C]215[/C][C]0.998495[/C][C]0.00300961[/C][C]0.0015048[/C][/ROW]
[ROW][C]216[/C][C]0.997981[/C][C]0.00403759[/C][C]0.00201879[/C][/ROW]
[ROW][C]217[/C][C]0.997732[/C][C]0.00453558[/C][C]0.00226779[/C][/ROW]
[ROW][C]218[/C][C]0.997363[/C][C]0.00527378[/C][C]0.00263689[/C][/ROW]
[ROW][C]219[/C][C]0.996311[/C][C]0.00737788[/C][C]0.00368894[/C][/ROW]
[ROW][C]220[/C][C]0.995077[/C][C]0.00984578[/C][C]0.00492289[/C][/ROW]
[ROW][C]221[/C][C]0.995082[/C][C]0.00983677[/C][C]0.00491839[/C][/ROW]
[ROW][C]222[/C][C]0.995589[/C][C]0.00882144[/C][C]0.00441072[/C][/ROW]
[ROW][C]223[/C][C]0.993882[/C][C]0.0122354[/C][C]0.00611769[/C][/ROW]
[ROW][C]224[/C][C]0.993668[/C][C]0.0126641[/C][C]0.00633204[/C][/ROW]
[ROW][C]225[/C][C]0.9932[/C][C]0.0136006[/C][C]0.00680031[/C][/ROW]
[ROW][C]226[/C][C]0.996487[/C][C]0.00702631[/C][C]0.00351316[/C][/ROW]
[ROW][C]227[/C][C]0.997345[/C][C]0.00530919[/C][C]0.0026546[/C][/ROW]
[ROW][C]228[/C][C]0.997968[/C][C]0.00406387[/C][C]0.00203194[/C][/ROW]
[ROW][C]229[/C][C]0.997252[/C][C]0.00549532[/C][C]0.00274766[/C][/ROW]
[ROW][C]230[/C][C]0.997928[/C][C]0.00414326[/C][C]0.00207163[/C][/ROW]
[ROW][C]231[/C][C]0.998853[/C][C]0.00229325[/C][C]0.00114663[/C][/ROW]
[ROW][C]232[/C][C]0.99838[/C][C]0.00323974[/C][C]0.00161987[/C][/ROW]
[ROW][C]233[/C][C]0.997776[/C][C]0.00444825[/C][C]0.00222413[/C][/ROW]
[ROW][C]234[/C][C]0.997202[/C][C]0.0055966[/C][C]0.0027983[/C][/ROW]
[ROW][C]235[/C][C]0.996827[/C][C]0.00634609[/C][C]0.00317305[/C][/ROW]
[ROW][C]236[/C][C]0.999337[/C][C]0.00132587[/C][C]0.000662936[/C][/ROW]
[ROW][C]237[/C][C]0.999238[/C][C]0.00152359[/C][C]0.000761795[/C][/ROW]
[ROW][C]238[/C][C]0.999101[/C][C]0.0017982[/C][C]0.000899102[/C][/ROW]
[ROW][C]239[/C][C]0.998651[/C][C]0.00269741[/C][C]0.00134871[/C][/ROW]
[ROW][C]240[/C][C]0.997886[/C][C]0.0042276[/C][C]0.0021138[/C][/ROW]
[ROW][C]241[/C][C]0.99716[/C][C]0.00568024[/C][C]0.00284012[/C][/ROW]
[ROW][C]242[/C][C]0.995841[/C][C]0.00831808[/C][C]0.00415904[/C][/ROW]
[ROW][C]243[/C][C]0.995005[/C][C]0.0099897[/C][C]0.00499485[/C][/ROW]
[ROW][C]244[/C][C]0.993459[/C][C]0.0130822[/C][C]0.00654112[/C][/ROW]
[ROW][C]245[/C][C]0.990132[/C][C]0.0197355[/C][C]0.00986774[/C][/ROW]
[ROW][C]246[/C][C]0.985548[/C][C]0.0289031[/C][C]0.0144515[/C][/ROW]
[ROW][C]247[/C][C]0.980725[/C][C]0.0385496[/C][C]0.0192748[/C][/ROW]
[ROW][C]248[/C][C]0.973891[/C][C]0.0522176[/C][C]0.0261088[/C][/ROW]
[ROW][C]249[/C][C]0.963455[/C][C]0.0730898[/C][C]0.0365449[/C][/ROW]
[ROW][C]250[/C][C]0.948795[/C][C]0.10241[/C][C]0.0512051[/C][/ROW]
[ROW][C]251[/C][C]0.932888[/C][C]0.134225[/C][C]0.0671123[/C][/ROW]
[ROW][C]252[/C][C]0.926363[/C][C]0.147274[/C][C]0.0736372[/C][/ROW]
[ROW][C]253[/C][C]0.90051[/C][C]0.198981[/C][C]0.0994903[/C][/ROW]
[ROW][C]254[/C][C]0.867984[/C][C]0.264031[/C][C]0.132016[/C][/ROW]
[ROW][C]255[/C][C]0.883266[/C][C]0.233468[/C][C]0.116734[/C][/ROW]
[ROW][C]256[/C][C]0.85043[/C][C]0.299141[/C][C]0.14957[/C][/ROW]
[ROW][C]257[/C][C]0.856047[/C][C]0.287905[/C][C]0.143953[/C][/ROW]
[ROW][C]258[/C][C]0.939345[/C][C]0.121309[/C][C]0.0606546[/C][/ROW]
[ROW][C]259[/C][C]0.940217[/C][C]0.119566[/C][C]0.0597828[/C][/ROW]
[ROW][C]260[/C][C]0.99946[/C][C]0.00108091[/C][C]0.000540457[/C][/ROW]
[ROW][C]261[/C][C]0.999027[/C][C]0.0019458[/C][C]0.000972902[/C][/ROW]
[ROW][C]262[/C][C]0.998572[/C][C]0.0028562[/C][C]0.0014281[/C][/ROW]
[ROW][C]263[/C][C]0.999989[/C][C]2.1455e-05[/C][C]1.07275e-05[/C][/ROW]
[ROW][C]264[/C][C]0.999961[/C][C]7.77152e-05[/C][C]3.88576e-05[/C][/ROW]
[ROW][C]265[/C][C]0.999954[/C][C]9.22914e-05[/C][C]4.61457e-05[/C][/ROW]
[ROW][C]266[/C][C]0.99991[/C][C]0.000179972[/C][C]8.99861e-05[/C][/ROW]
[ROW][C]267[/C][C]0.999954[/C][C]9.25342e-05[/C][C]4.62671e-05[/C][/ROW]
[ROW][C]268[/C][C]0.999847[/C][C]0.000306789[/C][C]0.000153395[/C][/ROW]
[ROW][C]269[/C][C]0.999636[/C][C]0.000728389[/C][C]0.000364195[/C][/ROW]
[ROW][C]270[/C][C]0.99824[/C][C]0.00352091[/C][C]0.00176046[/C][/ROW]
[ROW][C]271[/C][C]0.996136[/C][C]0.00772786[/C][C]0.00386393[/C][/ROW]
[ROW][C]272[/C][C]0.991958[/C][C]0.016083[/C][C]0.00804152[/C][/ROW]
[ROW][C]273[/C][C]0.958617[/C][C]0.0827662[/C][C]0.0413831[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268302&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268302&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
60.7143150.571370.285685
70.7171670.5656670.282833
80.6156050.768790.384395
90.5279030.9441950.472097
100.4988020.9976030.501198
110.3934690.7869370.606531
120.5862070.8275850.413793
130.4974590.9949190.502541
140.4124490.8248970.587551
150.3744140.7488280.625586
160.339770.679540.66023
170.2722270.5444540.727773
180.2143870.4287750.785613
190.1669790.3339570.833021
200.1254920.2509840.874508
210.1317460.2634910.868254
220.2009830.4019670.799017
230.1621090.3242190.837891
240.1407440.2814870.859256
250.110430.220860.88957
260.1039840.2079670.896016
270.1289860.2579730.871014
280.1340160.2680330.865984
290.1215620.2431250.878438
300.09912390.1982480.900876
310.09667450.1933490.903325
320.08028980.160580.91971
330.06637170.1327430.933628
340.05784690.1156940.942153
350.04427420.08854830.955726
360.0335190.06703790.966481
370.02569690.05139380.974303
380.03058130.06116250.969419
390.02873870.05747740.971261
400.02247880.04495770.977521
410.0386190.07723790.961381
420.03133270.06266550.968667
430.02747920.05495850.972521
440.02227180.04454360.977728
450.02113670.04227340.978863
460.01742110.03484210.982579
470.01324350.0264870.986756
480.01460410.02920820.985396
490.0124840.0249680.987516
500.01436860.02873720.985631
510.01137810.02275620.988622
520.01323960.02647910.98676
530.01054610.02109230.989454
540.009350730.01870150.990649
550.009114130.01822830.990886
560.007096080.01419220.992904
570.01631580.03263160.983684
580.02054560.04109120.979454
590.01616750.0323350.983833
600.01582380.03164760.984176
610.02296050.0459210.977039
620.02293690.04587380.977063
630.02785010.05570020.97215
640.03543330.07086670.964567
650.0406880.0813760.959312
660.03341640.06683290.966584
670.03478960.06957920.96521
680.04011460.08022930.959885
690.04916980.09833960.95083
700.04457460.08914910.955425
710.04240890.08481790.957591
720.03663660.07327320.963363
730.03402970.06805940.96597
740.04015330.08030660.959847
750.03625430.07250850.963746
760.03399910.06799830.966001
770.03257370.06514740.967426
780.03065260.06130510.969347
790.02503290.05006590.974967
800.03846690.07693390.961533
810.03263270.06526540.967367
820.03436850.06873710.965631
830.02906360.05812720.970936
840.08878810.1775760.911212
850.08684760.1736950.913152
860.07913010.158260.92087
870.06919290.1383860.930807
880.06241880.1248380.937581
890.06140550.1228110.938595
900.06060820.1212160.939392
910.05922090.1184420.940779
920.123980.2479590.87602
930.1485610.2971210.851439
940.1452120.2904240.854788
950.1617380.3234760.838262
960.167560.335120.83244
970.2455820.4911630.754418
980.2324760.4649530.767524
990.2581770.5163530.741823
1000.3196380.6392750.680362
1010.2945890.5891780.705411
1020.2840880.5681770.715912
1030.2983470.5966950.701653
1040.3355160.6710320.664484
1050.3594190.7188370.640581
1060.4010880.8021760.598912
1070.4146620.8293250.585338
1080.6628070.6743860.337193
1090.7143980.5712040.285602
1100.7343020.5313960.265698
1110.7291940.5416120.270806
1120.7166920.5666170.283308
1130.8359850.328030.164015
1140.8325420.3349160.167458
1150.9168970.1662060.0831028
1160.9565180.08696410.043482
1170.9580730.08385310.0419265
1180.9603860.0792280.039614
1190.9676010.06479790.0323989
1200.981430.03714050.0185703
1210.9859770.02804630.0140232
1220.989040.02191950.0109597
1230.9941520.01169560.00584779
1240.997390.005219380.00260969
1250.9974340.005131130.00256557
1260.9971040.005792140.00289607
1270.9977790.004441610.00222081
1280.9974490.005101040.00255052
1290.998710.002579070.00128953
1300.9987830.002433670.00121683
1310.9989010.002197680.00109884
1320.9989670.002066160.00103308
1330.9989570.002085580.00104279
1340.9988610.002278960.00113948
1350.9986080.002783380.00139169
1360.9982690.003461990.001731
1370.9991530.001693480.000846738
1380.9990120.001976780.00098839
1390.999230.001540820.000770412
1400.9991370.001725460.00086273
1410.9988890.002221310.00111065
1420.9994920.001015080.000507541
1430.9994640.001072690.000536343
1440.9996650.0006707950.000335397
1450.999650.0006994980.000349749
1460.9996630.0006748080.000337404
1470.9995870.0008268580.000413429
1480.9994980.001003030.000501517
1490.9994090.001181120.00059056
1500.9995990.0008024860.000401243
1510.999890.000220960.00011048
1520.9998660.0002670610.00013353
1530.9999110.0001782228.91109e-05
1540.9999060.0001873439.36717e-05
1550.9999230.0001544697.72343e-05
1560.9998970.0002052410.00010262
1570.9998970.0002057680.000102884
1580.9998880.0002248070.000112404
1590.9998640.000272670.000136335
1600.9998180.0003647260.000182363
1610.999840.0003205680.000160284
1620.9998540.0002913830.000145691
1630.9998360.0003272710.000163636
1640.9999852.98975e-051.49488e-05
1650.9999872.57457e-051.28729e-05
1660.9999813.70667e-051.85334e-05
1670.9999843.22698e-051.61349e-05
1680.9999892.1421e-051.07105e-05
1690.9999872.68835e-051.34417e-05
1700.9999862.73052e-051.36526e-05
1710.9999853.07145e-051.53573e-05
1720.9999892.10231e-051.05116e-05
1730.9999872.5412e-051.2706e-05
1740.9999843.10717e-051.55358e-05
1750.9999813.81793e-051.90897e-05
1760.9999833.32838e-051.66419e-05
1770.999983.93554e-051.96777e-05
1780.9999862.73167e-051.36584e-05
1790.9999823.54212e-051.77106e-05
1800.9999843.27385e-051.63692e-05
1810.9999823.64555e-051.82278e-05
1820.9999755.0631e-052.53155e-05
1830.9999754.95547e-052.47774e-05
1840.9999656.98119e-053.49059e-05
1850.9999637.49748e-053.74874e-05
1860.9999519.79391e-054.89695e-05
1870.9999794.23899e-052.1195e-05
1880.9999715.89607e-052.94804e-05
1890.9999578.53484e-054.26742e-05
1900.9999380.000124916.24552e-05
1910.9999120.00017568.78001e-05
1920.9998770.000245520.00012276
1930.9998540.0002912940.000145647
1940.9999230.0001536877.68437e-05
1950.9998960.000207830.000103915
1960.999880.0002397950.000119897
1970.9998710.000258770.000129385
1980.9998170.0003667840.000183392
1990.9998470.0003062820.000153141
2000.9998240.000352350.000176175
2010.9998060.0003886350.000194318
2020.999780.0004399780.000219989
2030.9997360.0005282510.000264126
2040.9996610.0006785130.000339257
2050.9995260.0009488960.000474448
2060.9996620.000676170.000338085
2070.9995490.0009020920.000451046
2080.9994920.001016350.000508177
2090.9994250.0011510.000575499
2100.9993290.001342740.000671369
2110.9990460.001907020.000953511
2120.9987290.002542350.00127118
2130.9989690.002062220.00103111
2140.998670.00265920.0013296
2150.9984950.003009610.0015048
2160.9979810.004037590.00201879
2170.9977320.004535580.00226779
2180.9973630.005273780.00263689
2190.9963110.007377880.00368894
2200.9950770.009845780.00492289
2210.9950820.009836770.00491839
2220.9955890.008821440.00441072
2230.9938820.01223540.00611769
2240.9936680.01266410.00633204
2250.99320.01360060.00680031
2260.9964870.007026310.00351316
2270.9973450.005309190.0026546
2280.9979680.004063870.00203194
2290.9972520.005495320.00274766
2300.9979280.004143260.00207163
2310.9988530.002293250.00114663
2320.998380.003239740.00161987
2330.9977760.004448250.00222413
2340.9972020.00559660.0027983
2350.9968270.006346090.00317305
2360.9993370.001325870.000662936
2370.9992380.001523590.000761795
2380.9991010.00179820.000899102
2390.9986510.002697410.00134871
2400.9978860.00422760.0021138
2410.997160.005680240.00284012
2420.9958410.008318080.00415904
2430.9950050.00998970.00499485
2440.9934590.01308220.00654112
2450.9901320.01973550.00986774
2460.9855480.02890310.0144515
2470.9807250.03854960.0192748
2480.9738910.05221760.0261088
2490.9634550.07308980.0365449
2500.9487950.102410.0512051
2510.9328880.1342250.0671123
2520.9263630.1472740.0736372
2530.900510.1989810.0994903
2540.8679840.2640310.132016
2550.8832660.2334680.116734
2560.850430.2991410.14957
2570.8560470.2879050.143953
2580.9393450.1213090.0606546
2590.9402170.1195660.0597828
2600.999460.001080910.000540457
2610.9990270.00194580.000972902
2620.9985720.00285620.0014281
2630.9999892.1455e-051.07275e-05
2640.9999617.77152e-053.88576e-05
2650.9999549.22914e-054.61457e-05
2660.999910.0001799728.99861e-05
2670.9999549.25342e-054.62671e-05
2680.9998470.0003067890.000153395
2690.9996360.0007283890.000364195
2700.998240.003520910.00176046
2710.9961360.007727860.00386393
2720.9919580.0160830.00804152
2730.9586170.08276620.0413831






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1290.481343NOK
5% type I error level1610.600746NOK
10% type I error level1970.735075NOK

\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 & 129 & 0.481343 & NOK \tabularnewline
5% type I error level & 161 & 0.600746 & NOK \tabularnewline
10% type I error level & 197 & 0.735075 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268302&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]129[/C][C]0.481343[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]161[/C][C]0.600746[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]197[/C][C]0.735075[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268302&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268302&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 level1290.481343NOK
5% type I error level1610.600746NOK
10% type I error level1970.735075NOK


Figures (Output of Computation)

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Input Parameters & R Code

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