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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 computationSat, 13 Dec 2014 11:28:03 +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/13/t1418470165z0fy4i98elx8cue.htm/, Retrieved Thu, 16 May 2024 12:31:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266995, Retrieved Thu, 16 May 2024 12:31:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Multiple Regressi...] [2014-12-13 11:28:03] [56a3e0974002d1c8d48b4dd203e70051] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.8 149 96 18 68
2.1 139 70 31 39
2.2 148 88 39 32
2.3 158 114 46 62
2.1 128 69 31 33
2.7 224 176 67 52
2.1 159 114 35 62
2.4 105 121 52 77
2.9 159 110 77 76
2.2 167 158 37 41
2.1 165 116 32 48
2.2 159 181 36 63
2.2 119 77 38 30
2.7 176 141 69 78
1.9 54 35 21 19
2 91 80 26 31
2.5 163 152 54 66
2.2 124 97 36 35
2.3 137 99 42 42
1.9 121 84 23 45
2.1 153 68 34 21
3.5 148 101 112 25
2.1 221 107 35 44
2.3 188 88 47 69
2.3 149 112 47 54
2.2 244 171 37 74
3.5 148 137 109 80
1.9 92 77 24 42
1.9 150 66 20 61
1.9 153 93 22 41
1.9 94 105 23 46
2.1 156 131 32 39
2 132 102 30 34
3.2 161 161 92 51
2.3 105 120 43 42
2.5 97 127 55 31
1.8 151 77 16 39
2.4 131 108 49 20
2.8 166 85 71 49
2.3 157 168 43 53
2 111 48 29 31
2.5 145 152 56 39
2.3 162 75 46 54
1.8 163 107 19 49
1.9 59 62 23 34
2.6 187 121 59 46
2 109 124 30 55
2.6 90 72 61 42
1.6 105 40 7 50
2.2 83 58 38 13
2.1 116 97 32 37
1.8 42 88 16 25
1.8 148 126 19 30
1.9 155 104 22 28
2.4 125 148 48 45
1.9 116 146 23 35
2 128 80 26 28
2.1 138 97 33 41
1.7 49 25 9 6
1.9 96 99 24 45
2.1 164 118 34 73
2.4 162 58 48 17
1.8 99 63 18 40
2.3 202 139 43 64
2.1 186 50 33 37
2 66 60 28 25
2.8 183 152 71 65
2 214 142 26 100
2.7 188 94 67 28
2.1 104 66 34 35
2.9 177 127 80 56
2 126 67 29 29
1.8 76 90 16 43
2.6 99 75 59 59
2.1 139 128 32 50
2.3 162 146 43 59
2.2 108 69 38 27
2 159 186 29 61
2.2 74 81 36 28
2.1 110 85 32 51
2.1 96 54 35 35
1.9 116 46 21 29
2 87 106 29 48
1.7 97 34 12 25
2.2 127 60 37 44
2.2 106 95 37 64
2.3 80 57 47 32
2.4 74 62 51 20
2.1 91 36 32 28
1.9 133 56 21 34
1.7 74 54 13 31
1.8 114 64 14 26
1.5 140 76 -2 58
1.9 95 98 20 23
1.9 98 88 24 21
1.7 121 35 11 21
1.9 126 102 23 33
1.9 98 61 24 16
1.8 95 80 14 20
2.4 110 49 52 37
1.8 70 78 15 35
1.9 102 90 23 33
1.8 86 45 19 27
2.1 130 55 35 41
1.9 96 96 24 40
2.2 102 43 39 35
2 100 52 29 28
1.7 94 60 13 32
1.7 52 54 8 22
1.8 98 51 18 44
1.9 118 51 24 27
1.8 99 38 19 17
1 48 41 23 12
1 50 146 16 45
4 150 182 33 37
4 154 192 32 37
3 109 263 37 108
2 68 35 14 10
4 194 439 52 68
4 158 214 75 72
4 159 341 72 143
2 67 58 15 9
4 147 292 29 55
1 39 85 13 17
3 100 200 40 37
3 111 158 19 27
4 138 199 24 37
3 101 297 121 58
4 131 227 93 66
3 101 108 36 21
3 114 86 23 19
4 165 302 85 78
3 114 148 41 35
3 111 178 46 48
2 75 120 18 27
2 82 207 35 43
3 121 157 17 30
1 32 128 4 25
4 150 296 28 69
3 117 323 44 72
2 71 79 10 23
4 165 70 38 13
4 154 146 57 61
4 126 246 23 43
4 149 196 36 51
4 145 199 22 67
3 120 127 40 36
3 109 153 31 44
4 132 299 11 45
4 172 228 38 34
4 169 190 24 36
3 114 180 37 72
4 156 212 37 39
4 172 269 22 43
2 68 130 15 25
2 89 179 2 56
4 167 243 43 80
3 113 190 31 40
3 115 299 29 73
2 78 121 45 34
3 118 137 25 72
2 87 305 4 42
4 173 157 31 61
1 2 96 -4 23
4 162 183 66 74
1 49 52 61 16
4 122 238 32 66
3 96 40 31 9
3 100 226 39 41
2 82 190 19 57
3 100 214 31 48
3 115 145 36 51
4 141 119 42 53
4 165 222 21 29
4 165 222 21 29
3 110 159 25 55
3 118 165 32 54
4 158 249 26 43
4 146 125 28 51
1 49 122 32 20
2 90 186 41 79
3 121 148 29 39
4 155 274 33 61
3 104 172 17 55
4 147 84 13 30
3 110 168 32 55
3 108 102 30 22
3 113 106 34 37
3 115 2 59 2
1 61 139 13 38
1 60 95 23 27
3 109 130 10 56
2 68 72 5 25
3 111 141 31 39
2 77 113 19 33
2 73 206 32 43
4 151 268 30 57
2 89 175 25 43
2 78 77 48 23
3 110 125 35 44
4 220 255 67 54
2 65 111 15 28
4 141 132 22 36
3 117 211 18 39
4 122 92 33 16
2 63 76 46 23
1 44 171 24 40
1 52 83 14 24
4 131 266 12 78
3 101 186 38 57
1 42 50 12 37
4 152 117 28 27
3 107 219 41 61
2 77 246 12 27
4 154 279 31 69
3 103 148 33 34
3 96 137 34 44
4 175 181 21 34
1 57 98 20 39
3 112 226 44 51
4 143 234 52 34
1 49 138 7 31
3 110 85 29 13
4 131 66 11 12
4 167 236 26 51
1 56 106 24 24
4 137 135 7 19
2 86 122 60 30
3 121 218 13 81
4 149 199 20 42
4 168 112 52 22
4 140 278 28 85
2 88 94 25 27
4 168 113 39 25
2 94 84 9 22
1 51 86 19 19
1 48 62 13 14
4 145 222 60 45
2 66 167 19 45
2 85 82 34 28
3 109 207 14 51
2 63 184 17 41
3 102 83 45 31
4 162 183 66 74
2 86 89 48 19
3 114 225 29 51
4 164 237 -2 73
3 119 102 51 24
4 126 221 2 61
4 132 128 24 23
4 142 91 40 14
2 83 198 20 54
2 94 204 19 51
2 81 158 16 62
4 166 138 20 36
3 110 226 40 59
2 64 44 27 24
2 93 196 25 26
3 104 83 49 54
3 105 79 39 39
1 49 52 61 16
2 88 105 19 36
2 95 116 67 31
3 102 83 45 31
3 99 196 30 42
2 63 153 8 39
2 76 157 19 25
3 109 75 52 31
3 117 106 22 38
1 57 58 17 31
3 120 75 33 17
2 73 74 34 22
2 91 185 22 55
3 108 265 30 62
3 105 131 25 51
3 117 139 38 30
3 119 196 26 49
1 31 78 13 16

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'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 & 9 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266995&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266995&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266995&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
PR[t] = + 0.699602 + 0.0107783LFM[t] + 0.00684764Blogs[t] + 0.00547875PRH[t] -0.0114757CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
PR[t] =  +  0.699602 +  0.0107783LFM[t] +  0.00684764Blogs[t] +  0.00547875PRH[t] -0.0114757CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266995&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]PR[t] =  +  0.699602 +  0.0107783LFM[t] +  0.00684764Blogs[t] +  0.00547875PRH[t] -0.0114757CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266995&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266995&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
PR[t] = + 0.699602 + 0.0107783LFM[t] + 0.00684764Blogs[t] + 0.00547875PRH[t] -0.0114757CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)0.6996020.1189185.8831.1757e-085.87848e-09
LFM0.01077830.0010530510.245.05607e-212.52804e-21
Blogs0.006847640.00063716110.751.06527e-225.32635e-23
PRH0.005478750.002065942.6520.008471070.00423554
CH-0.01147570.00250776-4.5767.19944e-063.59972e-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) & 0.699602 & 0.118918 & 5.883 & 1.1757e-08 & 5.87848e-09 \tabularnewline
LFM & 0.0107783 & 0.00105305 & 10.24 & 5.05607e-21 & 2.52804e-21 \tabularnewline
Blogs & 0.00684764 & 0.000637161 & 10.75 & 1.06527e-22 & 5.32635e-23 \tabularnewline
PRH & 0.00547875 & 0.00206594 & 2.652 & 0.00847107 & 0.00423554 \tabularnewline
CH & -0.0114757 & 0.00250776 & -4.576 & 7.19944e-06 & 3.59972e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266995&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]0.699602[/C][C]0.118918[/C][C]5.883[/C][C]1.1757e-08[/C][C]5.87848e-09[/C][/ROW]
[ROW][C]LFM[/C][C]0.0107783[/C][C]0.00105305[/C][C]10.24[/C][C]5.05607e-21[/C][C]2.52804e-21[/C][/ROW]
[ROW][C]Blogs[/C][C]0.00684764[/C][C]0.000637161[/C][C]10.75[/C][C]1.06527e-22[/C][C]5.32635e-23[/C][/ROW]
[ROW][C]PRH[/C][C]0.00547875[/C][C]0.00206594[/C][C]2.652[/C][C]0.00847107[/C][C]0.00423554[/C][/ROW]
[ROW][C]CH[/C][C]-0.0114757[/C][C]0.00250776[/C][C]-4.576[/C][C]7.19944e-06[/C][C]3.59972e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266995&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266995&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)0.6996020.1189185.8831.1757e-085.87848e-09
LFM0.01077830.0010530510.245.05607e-212.52804e-21
Blogs0.006847640.00063716110.751.06527e-225.32635e-23
PRH0.005478750.002065942.6520.008471070.00423554
CH-0.01147570.00250776-4.5767.19944e-063.59972e-06






Multiple Linear Regression - Regression Statistics
Multiple R0.746279
R-squared0.556933
Adjusted R-squared0.550441
F-TEST (value)85.7899
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.593681
Sum Squared Residuals96.2209

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.746279 \tabularnewline
R-squared & 0.556933 \tabularnewline
Adjusted R-squared & 0.550441 \tabularnewline
F-TEST (value) & 85.7899 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 273 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.593681 \tabularnewline
Sum Squared Residuals & 96.2209 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266995&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.746279[/C][/ROW]
[ROW][C]R-squared[/C][C]0.556933[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.550441[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]85.7899[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]273[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.593681[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]96.2209[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266995&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266995&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 R0.746279
R-squared0.556933
Adjusted R-squared0.550441
F-TEST (value)85.7899
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.593681
Sum Squared Residuals96.2209






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11.82.28121-0.481214
22.12.39941-0.299411
32.22.74383-0.543834
42.32.72374-0.423736
52.12.34286-0.242857
62.74.08947-1.38947
72.12.67425-0.574248
82.42.061160.338844
92.92.716310.183694
102.23.31372-1.11372
112.12.89684-0.796837
122.23.12704-0.927043
132.22.37341-0.173411
142.73.04503-0.345032
151.91.418310.481686
1622.01494-0.0149406
172.53.03577-0.535765
182.22.49592-0.29592
192.32.60228-0.302276
201.92.18858-0.288585
212.12.75961-0.659611
223.53.313130.186868
232.13.50113-1.40113
242.32.7942-0.494196
252.32.71032-0.41032
262.23.85397-1.65397
273.52.912050.587952
281.91.867990.0320141
291.92.17785-0.277851
301.92.63554-0.735543
311.92.02989-0.129895
322.13.00583-0.905828
3322.59499-0.594987
343.23.45617-0.256165
352.32.40665-0.106649
362.52.56033-0.0603335
371.82.4945-0.694503
382.42.89005-0.490051
392.82.89753-0.0975338
402.33.16958-0.869575
4122.02782-0.0278186
422.53.16256-0.662557
432.32.5916-0.291597
441.82.73095-0.930952
451.91.495910.404086
462.63.33908-0.739076
4722.25674-0.256745
482.62.01490.585095
491.61.56980.0302031
502.22.050370.149627
512.12.36483-0.264827
521.81.555650.244349
531.82.91742-1.11742
541.92.88161-0.981608
552.42.80692-0.406916
561.92.674-0.774004
5722.44817-0.448165
582.12.56153-0.461526
591.71.379380.320615
601.92.02732-0.12732
612.12.62382-0.523819
622.42.91075-0.510745
631.81.83765-0.0376459
642.33.32979-1.02979
652.12.80295-0.702948
6621.688340.311658
672.83.35595-0.555946
6822.9734-0.973404
692.73.41536-0.71536
702.12.057120.042881
712.93.27268-0.372675
7222.34255-0.34255
731.81.729250.0707536
742.61.926410.673592
752.12.67582-0.575821
762.33.00396-0.703965
772.22.2345-0.0344957
7823.14588-1.14588
792.21.927770.272228
802.12.057330.0426745
812.11.89420.2058
821.92.04714-0.147136
8321.971220.0287845
841.71.75677-0.0567705
852.22.177090.0229106
862.21.96090.239102
872.31.842460.457538
882.41.971650.428347
892.11.780940.319056
901.92.24147-0.341466
911.71.582450.117553
921.82.14491-0.344913
931.52.05244-0.552439
941.92.24024-0.340244
951.92.24897-0.348969
961.72.06272-0.362722
971.92.50344-0.603442
981.92.12146-0.221461
991.82.11854-0.318541
1002.42.081050.318955
1011.81.668730.131268
1021.92.16259-0.262591
1031.81.728930.0710669
1042.12.19866-0.0986557
1051.92.06416-0.164156
1062.21.905460.29454
10721.971070.0289252
1081.71.82762-0.127623
1091.71.421210.278789
1101.81.698790.101207
1111.92.14232-0.242319
1121.81.93587-0.135875
11311.48602-0.486017
11411.80953-0.809527
11543.318820.681182
11643.424930.575071
11732.638710.361293
11821.634140.36586
11945.30126-1.30126
12043.452630.547373
12143.501850.498154
12221.797810.202188
12343.811250.188754
12411.57814-0.578142
12532.941510.0584892
12632.772170.227826
12743.256580.743421
12833.8193-0.8193
12943.41810.581896
13032.4840.515998
13132.42520.5748
13244.1166-0.116601
13332.764760.23524
13432.816060.183936
13522.11847-0.118466
13622.69919-0.699187
13732.827730.172275
13811.65603-0.656028
13943.704830.295167
14033.58727-0.587268
14121.796670.203328
14243.016370.983633
14342.971491.02851
14443.374750.625255
14543.259680.740317
14642.97681.0232
14732.668670.331325
14832.587040.412962
14943.713640.286356
15043.932750.0672471
15143.540550.459446
15232.537370.462631
15343.587880.41212
15444.02256-0.0225648
15522.11801-0.118009
15622.25292-0.252918
15743.481090.518912
15832.929420.0705834
15933.30771-0.307711
16022.22525-0.225245
16132.220290.779711
16223.26578-1.26578
16343.109150.890846
16411.09268-0.0926758
16543.21120.788797
16611.73441-0.734409
16743.062220.937781
16832.074790.925215
16933.06817-0.0681679
17022.33446-0.334457
17132.861840.138164
17232.543990.456009
17342.656111.34389
17443.780460.219542
17543.780460.219542
17632.47980.520203
17732.656940.343064
17843.756630.243369
17942.697341.30266
18012.00896-1.00896
18122.26136-0.26136
18232.728560.27144
18343.727280.272724
18432.460320.539684
18542.586171.41383
18632.579780.420223
18732.474020.525984
18832.405080.594922
18932.25310.746902
19011.94405-0.944048
19111.81299-0.812994
19232.176780.82322
19321.666060.333941
19432.58380.416199
19522.02871-0.0287137
19622.5789-0.578898
19743.672540.327457
19822.50072-0.500723
19922.06662-0.0666177
20032.4280.572003
20144.56437-0.564368
20221.921140.0788579
20342.830641.16936
20433.05658-0.0565822
20542.641731.35827
20621.887140.112862
20712.01726-1.01726
20811.62971-0.629714
20943.103670.896326
21032.615950.384049
21111.13582-0.135817
21242.982641.01736
21332.877130.122874
21422.96995-0.969953
21543.647970.352028
21632.613840.386156
21732.353790.646206
21843.550110.44989
21911.64706-0.647057
22033.11014-0.110145
22143.737970.26203
22211.85532-0.855318
22332.476970.523035
22442.486061.51394
22543.672810.327189
22611.88511-0.885111
22742.920981.07902
22822.4464-0.446403
22932.638260.361744
23043.295850.704153
23143.309720.690276
23243.290180.709819
23322.1189-0.118897
23443.210920.789079
23522.08481-0.0848085
23611.72425-0.724251
23711.55208-0.552078
23843.594950.405047
23922.14222-0.142217
24022.04222-0.0422231
24132.783340.216658
24222.26124-0.261237
24332.258140.741859
24443.21120.788797
24522.28092-0.280919
24633.04267-0.0426722
24743.241450.758547
24832.684680.31532
24942.881941.11806
25042.866391.13361
25142.911751.08825
25222.43992-0.439922
25322.62852-0.628518
25422.03074-0.0307395
25543.130230.869774
25632.974870.0251326
25721.563220.43678
25822.88272-0.882723
25932.037670.962328
26032.138410.861592
26111.73441-0.734409
26222.05807-0.0580669
26322.5292-0.529198
26432.258140.741859
26532.791180.208824
26622.0226-0.0226025
26722.41104-0.411037
26832.317160.68284
26932.370970.629029
27011.44852-0.448521
27132.492280.507716
27221.926960.0730436
27322.43661-0.436611
27433.13115-0.131154
27532.280070.719926
27632.776410.223592
27732.90450.0955027
27811.45546-0.455458

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1.8 & 2.28121 & -0.481214 \tabularnewline
2 & 2.1 & 2.39941 & -0.299411 \tabularnewline
3 & 2.2 & 2.74383 & -0.543834 \tabularnewline
4 & 2.3 & 2.72374 & -0.423736 \tabularnewline
5 & 2.1 & 2.34286 & -0.242857 \tabularnewline
6 & 2.7 & 4.08947 & -1.38947 \tabularnewline
7 & 2.1 & 2.67425 & -0.574248 \tabularnewline
8 & 2.4 & 2.06116 & 0.338844 \tabularnewline
9 & 2.9 & 2.71631 & 0.183694 \tabularnewline
10 & 2.2 & 3.31372 & -1.11372 \tabularnewline
11 & 2.1 & 2.89684 & -0.796837 \tabularnewline
12 & 2.2 & 3.12704 & -0.927043 \tabularnewline
13 & 2.2 & 2.37341 & -0.173411 \tabularnewline
14 & 2.7 & 3.04503 & -0.345032 \tabularnewline
15 & 1.9 & 1.41831 & 0.481686 \tabularnewline
16 & 2 & 2.01494 & -0.0149406 \tabularnewline
17 & 2.5 & 3.03577 & -0.535765 \tabularnewline
18 & 2.2 & 2.49592 & -0.29592 \tabularnewline
19 & 2.3 & 2.60228 & -0.302276 \tabularnewline
20 & 1.9 & 2.18858 & -0.288585 \tabularnewline
21 & 2.1 & 2.75961 & -0.659611 \tabularnewline
22 & 3.5 & 3.31313 & 0.186868 \tabularnewline
23 & 2.1 & 3.50113 & -1.40113 \tabularnewline
24 & 2.3 & 2.7942 & -0.494196 \tabularnewline
25 & 2.3 & 2.71032 & -0.41032 \tabularnewline
26 & 2.2 & 3.85397 & -1.65397 \tabularnewline
27 & 3.5 & 2.91205 & 0.587952 \tabularnewline
28 & 1.9 & 1.86799 & 0.0320141 \tabularnewline
29 & 1.9 & 2.17785 & -0.277851 \tabularnewline
30 & 1.9 & 2.63554 & -0.735543 \tabularnewline
31 & 1.9 & 2.02989 & -0.129895 \tabularnewline
32 & 2.1 & 3.00583 & -0.905828 \tabularnewline
33 & 2 & 2.59499 & -0.594987 \tabularnewline
34 & 3.2 & 3.45617 & -0.256165 \tabularnewline
35 & 2.3 & 2.40665 & -0.106649 \tabularnewline
36 & 2.5 & 2.56033 & -0.0603335 \tabularnewline
37 & 1.8 & 2.4945 & -0.694503 \tabularnewline
38 & 2.4 & 2.89005 & -0.490051 \tabularnewline
39 & 2.8 & 2.89753 & -0.0975338 \tabularnewline
40 & 2.3 & 3.16958 & -0.869575 \tabularnewline
41 & 2 & 2.02782 & -0.0278186 \tabularnewline
42 & 2.5 & 3.16256 & -0.662557 \tabularnewline
43 & 2.3 & 2.5916 & -0.291597 \tabularnewline
44 & 1.8 & 2.73095 & -0.930952 \tabularnewline
45 & 1.9 & 1.49591 & 0.404086 \tabularnewline
46 & 2.6 & 3.33908 & -0.739076 \tabularnewline
47 & 2 & 2.25674 & -0.256745 \tabularnewline
48 & 2.6 & 2.0149 & 0.585095 \tabularnewline
49 & 1.6 & 1.5698 & 0.0302031 \tabularnewline
50 & 2.2 & 2.05037 & 0.149627 \tabularnewline
51 & 2.1 & 2.36483 & -0.264827 \tabularnewline
52 & 1.8 & 1.55565 & 0.244349 \tabularnewline
53 & 1.8 & 2.91742 & -1.11742 \tabularnewline
54 & 1.9 & 2.88161 & -0.981608 \tabularnewline
55 & 2.4 & 2.80692 & -0.406916 \tabularnewline
56 & 1.9 & 2.674 & -0.774004 \tabularnewline
57 & 2 & 2.44817 & -0.448165 \tabularnewline
58 & 2.1 & 2.56153 & -0.461526 \tabularnewline
59 & 1.7 & 1.37938 & 0.320615 \tabularnewline
60 & 1.9 & 2.02732 & -0.12732 \tabularnewline
61 & 2.1 & 2.62382 & -0.523819 \tabularnewline
62 & 2.4 & 2.91075 & -0.510745 \tabularnewline
63 & 1.8 & 1.83765 & -0.0376459 \tabularnewline
64 & 2.3 & 3.32979 & -1.02979 \tabularnewline
65 & 2.1 & 2.80295 & -0.702948 \tabularnewline
66 & 2 & 1.68834 & 0.311658 \tabularnewline
67 & 2.8 & 3.35595 & -0.555946 \tabularnewline
68 & 2 & 2.9734 & -0.973404 \tabularnewline
69 & 2.7 & 3.41536 & -0.71536 \tabularnewline
70 & 2.1 & 2.05712 & 0.042881 \tabularnewline
71 & 2.9 & 3.27268 & -0.372675 \tabularnewline
72 & 2 & 2.34255 & -0.34255 \tabularnewline
73 & 1.8 & 1.72925 & 0.0707536 \tabularnewline
74 & 2.6 & 1.92641 & 0.673592 \tabularnewline
75 & 2.1 & 2.67582 & -0.575821 \tabularnewline
76 & 2.3 & 3.00396 & -0.703965 \tabularnewline
77 & 2.2 & 2.2345 & -0.0344957 \tabularnewline
78 & 2 & 3.14588 & -1.14588 \tabularnewline
79 & 2.2 & 1.92777 & 0.272228 \tabularnewline
80 & 2.1 & 2.05733 & 0.0426745 \tabularnewline
81 & 2.1 & 1.8942 & 0.2058 \tabularnewline
82 & 1.9 & 2.04714 & -0.147136 \tabularnewline
83 & 2 & 1.97122 & 0.0287845 \tabularnewline
84 & 1.7 & 1.75677 & -0.0567705 \tabularnewline
85 & 2.2 & 2.17709 & 0.0229106 \tabularnewline
86 & 2.2 & 1.9609 & 0.239102 \tabularnewline
87 & 2.3 & 1.84246 & 0.457538 \tabularnewline
88 & 2.4 & 1.97165 & 0.428347 \tabularnewline
89 & 2.1 & 1.78094 & 0.319056 \tabularnewline
90 & 1.9 & 2.24147 & -0.341466 \tabularnewline
91 & 1.7 & 1.58245 & 0.117553 \tabularnewline
92 & 1.8 & 2.14491 & -0.344913 \tabularnewline
93 & 1.5 & 2.05244 & -0.552439 \tabularnewline
94 & 1.9 & 2.24024 & -0.340244 \tabularnewline
95 & 1.9 & 2.24897 & -0.348969 \tabularnewline
96 & 1.7 & 2.06272 & -0.362722 \tabularnewline
97 & 1.9 & 2.50344 & -0.603442 \tabularnewline
98 & 1.9 & 2.12146 & -0.221461 \tabularnewline
99 & 1.8 & 2.11854 & -0.318541 \tabularnewline
100 & 2.4 & 2.08105 & 0.318955 \tabularnewline
101 & 1.8 & 1.66873 & 0.131268 \tabularnewline
102 & 1.9 & 2.16259 & -0.262591 \tabularnewline
103 & 1.8 & 1.72893 & 0.0710669 \tabularnewline
104 & 2.1 & 2.19866 & -0.0986557 \tabularnewline
105 & 1.9 & 2.06416 & -0.164156 \tabularnewline
106 & 2.2 & 1.90546 & 0.29454 \tabularnewline
107 & 2 & 1.97107 & 0.0289252 \tabularnewline
108 & 1.7 & 1.82762 & -0.127623 \tabularnewline
109 & 1.7 & 1.42121 & 0.278789 \tabularnewline
110 & 1.8 & 1.69879 & 0.101207 \tabularnewline
111 & 1.9 & 2.14232 & -0.242319 \tabularnewline
112 & 1.8 & 1.93587 & -0.135875 \tabularnewline
113 & 1 & 1.48602 & -0.486017 \tabularnewline
114 & 1 & 1.80953 & -0.809527 \tabularnewline
115 & 4 & 3.31882 & 0.681182 \tabularnewline
116 & 4 & 3.42493 & 0.575071 \tabularnewline
117 & 3 & 2.63871 & 0.361293 \tabularnewline
118 & 2 & 1.63414 & 0.36586 \tabularnewline
119 & 4 & 5.30126 & -1.30126 \tabularnewline
120 & 4 & 3.45263 & 0.547373 \tabularnewline
121 & 4 & 3.50185 & 0.498154 \tabularnewline
122 & 2 & 1.79781 & 0.202188 \tabularnewline
123 & 4 & 3.81125 & 0.188754 \tabularnewline
124 & 1 & 1.57814 & -0.578142 \tabularnewline
125 & 3 & 2.94151 & 0.0584892 \tabularnewline
126 & 3 & 2.77217 & 0.227826 \tabularnewline
127 & 4 & 3.25658 & 0.743421 \tabularnewline
128 & 3 & 3.8193 & -0.8193 \tabularnewline
129 & 4 & 3.4181 & 0.581896 \tabularnewline
130 & 3 & 2.484 & 0.515998 \tabularnewline
131 & 3 & 2.4252 & 0.5748 \tabularnewline
132 & 4 & 4.1166 & -0.116601 \tabularnewline
133 & 3 & 2.76476 & 0.23524 \tabularnewline
134 & 3 & 2.81606 & 0.183936 \tabularnewline
135 & 2 & 2.11847 & -0.118466 \tabularnewline
136 & 2 & 2.69919 & -0.699187 \tabularnewline
137 & 3 & 2.82773 & 0.172275 \tabularnewline
138 & 1 & 1.65603 & -0.656028 \tabularnewline
139 & 4 & 3.70483 & 0.295167 \tabularnewline
140 & 3 & 3.58727 & -0.587268 \tabularnewline
141 & 2 & 1.79667 & 0.203328 \tabularnewline
142 & 4 & 3.01637 & 0.983633 \tabularnewline
143 & 4 & 2.97149 & 1.02851 \tabularnewline
144 & 4 & 3.37475 & 0.625255 \tabularnewline
145 & 4 & 3.25968 & 0.740317 \tabularnewline
146 & 4 & 2.9768 & 1.0232 \tabularnewline
147 & 3 & 2.66867 & 0.331325 \tabularnewline
148 & 3 & 2.58704 & 0.412962 \tabularnewline
149 & 4 & 3.71364 & 0.286356 \tabularnewline
150 & 4 & 3.93275 & 0.0672471 \tabularnewline
151 & 4 & 3.54055 & 0.459446 \tabularnewline
152 & 3 & 2.53737 & 0.462631 \tabularnewline
153 & 4 & 3.58788 & 0.41212 \tabularnewline
154 & 4 & 4.02256 & -0.0225648 \tabularnewline
155 & 2 & 2.11801 & -0.118009 \tabularnewline
156 & 2 & 2.25292 & -0.252918 \tabularnewline
157 & 4 & 3.48109 & 0.518912 \tabularnewline
158 & 3 & 2.92942 & 0.0705834 \tabularnewline
159 & 3 & 3.30771 & -0.307711 \tabularnewline
160 & 2 & 2.22525 & -0.225245 \tabularnewline
161 & 3 & 2.22029 & 0.779711 \tabularnewline
162 & 2 & 3.26578 & -1.26578 \tabularnewline
163 & 4 & 3.10915 & 0.890846 \tabularnewline
164 & 1 & 1.09268 & -0.0926758 \tabularnewline
165 & 4 & 3.2112 & 0.788797 \tabularnewline
166 & 1 & 1.73441 & -0.734409 \tabularnewline
167 & 4 & 3.06222 & 0.937781 \tabularnewline
168 & 3 & 2.07479 & 0.925215 \tabularnewline
169 & 3 & 3.06817 & -0.0681679 \tabularnewline
170 & 2 & 2.33446 & -0.334457 \tabularnewline
171 & 3 & 2.86184 & 0.138164 \tabularnewline
172 & 3 & 2.54399 & 0.456009 \tabularnewline
173 & 4 & 2.65611 & 1.34389 \tabularnewline
174 & 4 & 3.78046 & 0.219542 \tabularnewline
175 & 4 & 3.78046 & 0.219542 \tabularnewline
176 & 3 & 2.4798 & 0.520203 \tabularnewline
177 & 3 & 2.65694 & 0.343064 \tabularnewline
178 & 4 & 3.75663 & 0.243369 \tabularnewline
179 & 4 & 2.69734 & 1.30266 \tabularnewline
180 & 1 & 2.00896 & -1.00896 \tabularnewline
181 & 2 & 2.26136 & -0.26136 \tabularnewline
182 & 3 & 2.72856 & 0.27144 \tabularnewline
183 & 4 & 3.72728 & 0.272724 \tabularnewline
184 & 3 & 2.46032 & 0.539684 \tabularnewline
185 & 4 & 2.58617 & 1.41383 \tabularnewline
186 & 3 & 2.57978 & 0.420223 \tabularnewline
187 & 3 & 2.47402 & 0.525984 \tabularnewline
188 & 3 & 2.40508 & 0.594922 \tabularnewline
189 & 3 & 2.2531 & 0.746902 \tabularnewline
190 & 1 & 1.94405 & -0.944048 \tabularnewline
191 & 1 & 1.81299 & -0.812994 \tabularnewline
192 & 3 & 2.17678 & 0.82322 \tabularnewline
193 & 2 & 1.66606 & 0.333941 \tabularnewline
194 & 3 & 2.5838 & 0.416199 \tabularnewline
195 & 2 & 2.02871 & -0.0287137 \tabularnewline
196 & 2 & 2.5789 & -0.578898 \tabularnewline
197 & 4 & 3.67254 & 0.327457 \tabularnewline
198 & 2 & 2.50072 & -0.500723 \tabularnewline
199 & 2 & 2.06662 & -0.0666177 \tabularnewline
200 & 3 & 2.428 & 0.572003 \tabularnewline
201 & 4 & 4.56437 & -0.564368 \tabularnewline
202 & 2 & 1.92114 & 0.0788579 \tabularnewline
203 & 4 & 2.83064 & 1.16936 \tabularnewline
204 & 3 & 3.05658 & -0.0565822 \tabularnewline
205 & 4 & 2.64173 & 1.35827 \tabularnewline
206 & 2 & 1.88714 & 0.112862 \tabularnewline
207 & 1 & 2.01726 & -1.01726 \tabularnewline
208 & 1 & 1.62971 & -0.629714 \tabularnewline
209 & 4 & 3.10367 & 0.896326 \tabularnewline
210 & 3 & 2.61595 & 0.384049 \tabularnewline
211 & 1 & 1.13582 & -0.135817 \tabularnewline
212 & 4 & 2.98264 & 1.01736 \tabularnewline
213 & 3 & 2.87713 & 0.122874 \tabularnewline
214 & 2 & 2.96995 & -0.969953 \tabularnewline
215 & 4 & 3.64797 & 0.352028 \tabularnewline
216 & 3 & 2.61384 & 0.386156 \tabularnewline
217 & 3 & 2.35379 & 0.646206 \tabularnewline
218 & 4 & 3.55011 & 0.44989 \tabularnewline
219 & 1 & 1.64706 & -0.647057 \tabularnewline
220 & 3 & 3.11014 & -0.110145 \tabularnewline
221 & 4 & 3.73797 & 0.26203 \tabularnewline
222 & 1 & 1.85532 & -0.855318 \tabularnewline
223 & 3 & 2.47697 & 0.523035 \tabularnewline
224 & 4 & 2.48606 & 1.51394 \tabularnewline
225 & 4 & 3.67281 & 0.327189 \tabularnewline
226 & 1 & 1.88511 & -0.885111 \tabularnewline
227 & 4 & 2.92098 & 1.07902 \tabularnewline
228 & 2 & 2.4464 & -0.446403 \tabularnewline
229 & 3 & 2.63826 & 0.361744 \tabularnewline
230 & 4 & 3.29585 & 0.704153 \tabularnewline
231 & 4 & 3.30972 & 0.690276 \tabularnewline
232 & 4 & 3.29018 & 0.709819 \tabularnewline
233 & 2 & 2.1189 & -0.118897 \tabularnewline
234 & 4 & 3.21092 & 0.789079 \tabularnewline
235 & 2 & 2.08481 & -0.0848085 \tabularnewline
236 & 1 & 1.72425 & -0.724251 \tabularnewline
237 & 1 & 1.55208 & -0.552078 \tabularnewline
238 & 4 & 3.59495 & 0.405047 \tabularnewline
239 & 2 & 2.14222 & -0.142217 \tabularnewline
240 & 2 & 2.04222 & -0.0422231 \tabularnewline
241 & 3 & 2.78334 & 0.216658 \tabularnewline
242 & 2 & 2.26124 & -0.261237 \tabularnewline
243 & 3 & 2.25814 & 0.741859 \tabularnewline
244 & 4 & 3.2112 & 0.788797 \tabularnewline
245 & 2 & 2.28092 & -0.280919 \tabularnewline
246 & 3 & 3.04267 & -0.0426722 \tabularnewline
247 & 4 & 3.24145 & 0.758547 \tabularnewline
248 & 3 & 2.68468 & 0.31532 \tabularnewline
249 & 4 & 2.88194 & 1.11806 \tabularnewline
250 & 4 & 2.86639 & 1.13361 \tabularnewline
251 & 4 & 2.91175 & 1.08825 \tabularnewline
252 & 2 & 2.43992 & -0.439922 \tabularnewline
253 & 2 & 2.62852 & -0.628518 \tabularnewline
254 & 2 & 2.03074 & -0.0307395 \tabularnewline
255 & 4 & 3.13023 & 0.869774 \tabularnewline
256 & 3 & 2.97487 & 0.0251326 \tabularnewline
257 & 2 & 1.56322 & 0.43678 \tabularnewline
258 & 2 & 2.88272 & -0.882723 \tabularnewline
259 & 3 & 2.03767 & 0.962328 \tabularnewline
260 & 3 & 2.13841 & 0.861592 \tabularnewline
261 & 1 & 1.73441 & -0.734409 \tabularnewline
262 & 2 & 2.05807 & -0.0580669 \tabularnewline
263 & 2 & 2.5292 & -0.529198 \tabularnewline
264 & 3 & 2.25814 & 0.741859 \tabularnewline
265 & 3 & 2.79118 & 0.208824 \tabularnewline
266 & 2 & 2.0226 & -0.0226025 \tabularnewline
267 & 2 & 2.41104 & -0.411037 \tabularnewline
268 & 3 & 2.31716 & 0.68284 \tabularnewline
269 & 3 & 2.37097 & 0.629029 \tabularnewline
270 & 1 & 1.44852 & -0.448521 \tabularnewline
271 & 3 & 2.49228 & 0.507716 \tabularnewline
272 & 2 & 1.92696 & 0.0730436 \tabularnewline
273 & 2 & 2.43661 & -0.436611 \tabularnewline
274 & 3 & 3.13115 & -0.131154 \tabularnewline
275 & 3 & 2.28007 & 0.719926 \tabularnewline
276 & 3 & 2.77641 & 0.223592 \tabularnewline
277 & 3 & 2.9045 & 0.0955027 \tabularnewline
278 & 1 & 1.45546 & -0.455458 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266995&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]1.8[/C][C]2.28121[/C][C]-0.481214[/C][/ROW]
[ROW][C]2[/C][C]2.1[/C][C]2.39941[/C][C]-0.299411[/C][/ROW]
[ROW][C]3[/C][C]2.2[/C][C]2.74383[/C][C]-0.543834[/C][/ROW]
[ROW][C]4[/C][C]2.3[/C][C]2.72374[/C][C]-0.423736[/C][/ROW]
[ROW][C]5[/C][C]2.1[/C][C]2.34286[/C][C]-0.242857[/C][/ROW]
[ROW][C]6[/C][C]2.7[/C][C]4.08947[/C][C]-1.38947[/C][/ROW]
[ROW][C]7[/C][C]2.1[/C][C]2.67425[/C][C]-0.574248[/C][/ROW]
[ROW][C]8[/C][C]2.4[/C][C]2.06116[/C][C]0.338844[/C][/ROW]
[ROW][C]9[/C][C]2.9[/C][C]2.71631[/C][C]0.183694[/C][/ROW]
[ROW][C]10[/C][C]2.2[/C][C]3.31372[/C][C]-1.11372[/C][/ROW]
[ROW][C]11[/C][C]2.1[/C][C]2.89684[/C][C]-0.796837[/C][/ROW]
[ROW][C]12[/C][C]2.2[/C][C]3.12704[/C][C]-0.927043[/C][/ROW]
[ROW][C]13[/C][C]2.2[/C][C]2.37341[/C][C]-0.173411[/C][/ROW]
[ROW][C]14[/C][C]2.7[/C][C]3.04503[/C][C]-0.345032[/C][/ROW]
[ROW][C]15[/C][C]1.9[/C][C]1.41831[/C][C]0.481686[/C][/ROW]
[ROW][C]16[/C][C]2[/C][C]2.01494[/C][C]-0.0149406[/C][/ROW]
[ROW][C]17[/C][C]2.5[/C][C]3.03577[/C][C]-0.535765[/C][/ROW]
[ROW][C]18[/C][C]2.2[/C][C]2.49592[/C][C]-0.29592[/C][/ROW]
[ROW][C]19[/C][C]2.3[/C][C]2.60228[/C][C]-0.302276[/C][/ROW]
[ROW][C]20[/C][C]1.9[/C][C]2.18858[/C][C]-0.288585[/C][/ROW]
[ROW][C]21[/C][C]2.1[/C][C]2.75961[/C][C]-0.659611[/C][/ROW]
[ROW][C]22[/C][C]3.5[/C][C]3.31313[/C][C]0.186868[/C][/ROW]
[ROW][C]23[/C][C]2.1[/C][C]3.50113[/C][C]-1.40113[/C][/ROW]
[ROW][C]24[/C][C]2.3[/C][C]2.7942[/C][C]-0.494196[/C][/ROW]
[ROW][C]25[/C][C]2.3[/C][C]2.71032[/C][C]-0.41032[/C][/ROW]
[ROW][C]26[/C][C]2.2[/C][C]3.85397[/C][C]-1.65397[/C][/ROW]
[ROW][C]27[/C][C]3.5[/C][C]2.91205[/C][C]0.587952[/C][/ROW]
[ROW][C]28[/C][C]1.9[/C][C]1.86799[/C][C]0.0320141[/C][/ROW]
[ROW][C]29[/C][C]1.9[/C][C]2.17785[/C][C]-0.277851[/C][/ROW]
[ROW][C]30[/C][C]1.9[/C][C]2.63554[/C][C]-0.735543[/C][/ROW]
[ROW][C]31[/C][C]1.9[/C][C]2.02989[/C][C]-0.129895[/C][/ROW]
[ROW][C]32[/C][C]2.1[/C][C]3.00583[/C][C]-0.905828[/C][/ROW]
[ROW][C]33[/C][C]2[/C][C]2.59499[/C][C]-0.594987[/C][/ROW]
[ROW][C]34[/C][C]3.2[/C][C]3.45617[/C][C]-0.256165[/C][/ROW]
[ROW][C]35[/C][C]2.3[/C][C]2.40665[/C][C]-0.106649[/C][/ROW]
[ROW][C]36[/C][C]2.5[/C][C]2.56033[/C][C]-0.0603335[/C][/ROW]
[ROW][C]37[/C][C]1.8[/C][C]2.4945[/C][C]-0.694503[/C][/ROW]
[ROW][C]38[/C][C]2.4[/C][C]2.89005[/C][C]-0.490051[/C][/ROW]
[ROW][C]39[/C][C]2.8[/C][C]2.89753[/C][C]-0.0975338[/C][/ROW]
[ROW][C]40[/C][C]2.3[/C][C]3.16958[/C][C]-0.869575[/C][/ROW]
[ROW][C]41[/C][C]2[/C][C]2.02782[/C][C]-0.0278186[/C][/ROW]
[ROW][C]42[/C][C]2.5[/C][C]3.16256[/C][C]-0.662557[/C][/ROW]
[ROW][C]43[/C][C]2.3[/C][C]2.5916[/C][C]-0.291597[/C][/ROW]
[ROW][C]44[/C][C]1.8[/C][C]2.73095[/C][C]-0.930952[/C][/ROW]
[ROW][C]45[/C][C]1.9[/C][C]1.49591[/C][C]0.404086[/C][/ROW]
[ROW][C]46[/C][C]2.6[/C][C]3.33908[/C][C]-0.739076[/C][/ROW]
[ROW][C]47[/C][C]2[/C][C]2.25674[/C][C]-0.256745[/C][/ROW]
[ROW][C]48[/C][C]2.6[/C][C]2.0149[/C][C]0.585095[/C][/ROW]
[ROW][C]49[/C][C]1.6[/C][C]1.5698[/C][C]0.0302031[/C][/ROW]
[ROW][C]50[/C][C]2.2[/C][C]2.05037[/C][C]0.149627[/C][/ROW]
[ROW][C]51[/C][C]2.1[/C][C]2.36483[/C][C]-0.264827[/C][/ROW]
[ROW][C]52[/C][C]1.8[/C][C]1.55565[/C][C]0.244349[/C][/ROW]
[ROW][C]53[/C][C]1.8[/C][C]2.91742[/C][C]-1.11742[/C][/ROW]
[ROW][C]54[/C][C]1.9[/C][C]2.88161[/C][C]-0.981608[/C][/ROW]
[ROW][C]55[/C][C]2.4[/C][C]2.80692[/C][C]-0.406916[/C][/ROW]
[ROW][C]56[/C][C]1.9[/C][C]2.674[/C][C]-0.774004[/C][/ROW]
[ROW][C]57[/C][C]2[/C][C]2.44817[/C][C]-0.448165[/C][/ROW]
[ROW][C]58[/C][C]2.1[/C][C]2.56153[/C][C]-0.461526[/C][/ROW]
[ROW][C]59[/C][C]1.7[/C][C]1.37938[/C][C]0.320615[/C][/ROW]
[ROW][C]60[/C][C]1.9[/C][C]2.02732[/C][C]-0.12732[/C][/ROW]
[ROW][C]61[/C][C]2.1[/C][C]2.62382[/C][C]-0.523819[/C][/ROW]
[ROW][C]62[/C][C]2.4[/C][C]2.91075[/C][C]-0.510745[/C][/ROW]
[ROW][C]63[/C][C]1.8[/C][C]1.83765[/C][C]-0.0376459[/C][/ROW]
[ROW][C]64[/C][C]2.3[/C][C]3.32979[/C][C]-1.02979[/C][/ROW]
[ROW][C]65[/C][C]2.1[/C][C]2.80295[/C][C]-0.702948[/C][/ROW]
[ROW][C]66[/C][C]2[/C][C]1.68834[/C][C]0.311658[/C][/ROW]
[ROW][C]67[/C][C]2.8[/C][C]3.35595[/C][C]-0.555946[/C][/ROW]
[ROW][C]68[/C][C]2[/C][C]2.9734[/C][C]-0.973404[/C][/ROW]
[ROW][C]69[/C][C]2.7[/C][C]3.41536[/C][C]-0.71536[/C][/ROW]
[ROW][C]70[/C][C]2.1[/C][C]2.05712[/C][C]0.042881[/C][/ROW]
[ROW][C]71[/C][C]2.9[/C][C]3.27268[/C][C]-0.372675[/C][/ROW]
[ROW][C]72[/C][C]2[/C][C]2.34255[/C][C]-0.34255[/C][/ROW]
[ROW][C]73[/C][C]1.8[/C][C]1.72925[/C][C]0.0707536[/C][/ROW]
[ROW][C]74[/C][C]2.6[/C][C]1.92641[/C][C]0.673592[/C][/ROW]
[ROW][C]75[/C][C]2.1[/C][C]2.67582[/C][C]-0.575821[/C][/ROW]
[ROW][C]76[/C][C]2.3[/C][C]3.00396[/C][C]-0.703965[/C][/ROW]
[ROW][C]77[/C][C]2.2[/C][C]2.2345[/C][C]-0.0344957[/C][/ROW]
[ROW][C]78[/C][C]2[/C][C]3.14588[/C][C]-1.14588[/C][/ROW]
[ROW][C]79[/C][C]2.2[/C][C]1.92777[/C][C]0.272228[/C][/ROW]
[ROW][C]80[/C][C]2.1[/C][C]2.05733[/C][C]0.0426745[/C][/ROW]
[ROW][C]81[/C][C]2.1[/C][C]1.8942[/C][C]0.2058[/C][/ROW]
[ROW][C]82[/C][C]1.9[/C][C]2.04714[/C][C]-0.147136[/C][/ROW]
[ROW][C]83[/C][C]2[/C][C]1.97122[/C][C]0.0287845[/C][/ROW]
[ROW][C]84[/C][C]1.7[/C][C]1.75677[/C][C]-0.0567705[/C][/ROW]
[ROW][C]85[/C][C]2.2[/C][C]2.17709[/C][C]0.0229106[/C][/ROW]
[ROW][C]86[/C][C]2.2[/C][C]1.9609[/C][C]0.239102[/C][/ROW]
[ROW][C]87[/C][C]2.3[/C][C]1.84246[/C][C]0.457538[/C][/ROW]
[ROW][C]88[/C][C]2.4[/C][C]1.97165[/C][C]0.428347[/C][/ROW]
[ROW][C]89[/C][C]2.1[/C][C]1.78094[/C][C]0.319056[/C][/ROW]
[ROW][C]90[/C][C]1.9[/C][C]2.24147[/C][C]-0.341466[/C][/ROW]
[ROW][C]91[/C][C]1.7[/C][C]1.58245[/C][C]0.117553[/C][/ROW]
[ROW][C]92[/C][C]1.8[/C][C]2.14491[/C][C]-0.344913[/C][/ROW]
[ROW][C]93[/C][C]1.5[/C][C]2.05244[/C][C]-0.552439[/C][/ROW]
[ROW][C]94[/C][C]1.9[/C][C]2.24024[/C][C]-0.340244[/C][/ROW]
[ROW][C]95[/C][C]1.9[/C][C]2.24897[/C][C]-0.348969[/C][/ROW]
[ROW][C]96[/C][C]1.7[/C][C]2.06272[/C][C]-0.362722[/C][/ROW]
[ROW][C]97[/C][C]1.9[/C][C]2.50344[/C][C]-0.603442[/C][/ROW]
[ROW][C]98[/C][C]1.9[/C][C]2.12146[/C][C]-0.221461[/C][/ROW]
[ROW][C]99[/C][C]1.8[/C][C]2.11854[/C][C]-0.318541[/C][/ROW]
[ROW][C]100[/C][C]2.4[/C][C]2.08105[/C][C]0.318955[/C][/ROW]
[ROW][C]101[/C][C]1.8[/C][C]1.66873[/C][C]0.131268[/C][/ROW]
[ROW][C]102[/C][C]1.9[/C][C]2.16259[/C][C]-0.262591[/C][/ROW]
[ROW][C]103[/C][C]1.8[/C][C]1.72893[/C][C]0.0710669[/C][/ROW]
[ROW][C]104[/C][C]2.1[/C][C]2.19866[/C][C]-0.0986557[/C][/ROW]
[ROW][C]105[/C][C]1.9[/C][C]2.06416[/C][C]-0.164156[/C][/ROW]
[ROW][C]106[/C][C]2.2[/C][C]1.90546[/C][C]0.29454[/C][/ROW]
[ROW][C]107[/C][C]2[/C][C]1.97107[/C][C]0.0289252[/C][/ROW]
[ROW][C]108[/C][C]1.7[/C][C]1.82762[/C][C]-0.127623[/C][/ROW]
[ROW][C]109[/C][C]1.7[/C][C]1.42121[/C][C]0.278789[/C][/ROW]
[ROW][C]110[/C][C]1.8[/C][C]1.69879[/C][C]0.101207[/C][/ROW]
[ROW][C]111[/C][C]1.9[/C][C]2.14232[/C][C]-0.242319[/C][/ROW]
[ROW][C]112[/C][C]1.8[/C][C]1.93587[/C][C]-0.135875[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]1.48602[/C][C]-0.486017[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]1.80953[/C][C]-0.809527[/C][/ROW]
[ROW][C]115[/C][C]4[/C][C]3.31882[/C][C]0.681182[/C][/ROW]
[ROW][C]116[/C][C]4[/C][C]3.42493[/C][C]0.575071[/C][/ROW]
[ROW][C]117[/C][C]3[/C][C]2.63871[/C][C]0.361293[/C][/ROW]
[ROW][C]118[/C][C]2[/C][C]1.63414[/C][C]0.36586[/C][/ROW]
[ROW][C]119[/C][C]4[/C][C]5.30126[/C][C]-1.30126[/C][/ROW]
[ROW][C]120[/C][C]4[/C][C]3.45263[/C][C]0.547373[/C][/ROW]
[ROW][C]121[/C][C]4[/C][C]3.50185[/C][C]0.498154[/C][/ROW]
[ROW][C]122[/C][C]2[/C][C]1.79781[/C][C]0.202188[/C][/ROW]
[ROW][C]123[/C][C]4[/C][C]3.81125[/C][C]0.188754[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]1.57814[/C][C]-0.578142[/C][/ROW]
[ROW][C]125[/C][C]3[/C][C]2.94151[/C][C]0.0584892[/C][/ROW]
[ROW][C]126[/C][C]3[/C][C]2.77217[/C][C]0.227826[/C][/ROW]
[ROW][C]127[/C][C]4[/C][C]3.25658[/C][C]0.743421[/C][/ROW]
[ROW][C]128[/C][C]3[/C][C]3.8193[/C][C]-0.8193[/C][/ROW]
[ROW][C]129[/C][C]4[/C][C]3.4181[/C][C]0.581896[/C][/ROW]
[ROW][C]130[/C][C]3[/C][C]2.484[/C][C]0.515998[/C][/ROW]
[ROW][C]131[/C][C]3[/C][C]2.4252[/C][C]0.5748[/C][/ROW]
[ROW][C]132[/C][C]4[/C][C]4.1166[/C][C]-0.116601[/C][/ROW]
[ROW][C]133[/C][C]3[/C][C]2.76476[/C][C]0.23524[/C][/ROW]
[ROW][C]134[/C][C]3[/C][C]2.81606[/C][C]0.183936[/C][/ROW]
[ROW][C]135[/C][C]2[/C][C]2.11847[/C][C]-0.118466[/C][/ROW]
[ROW][C]136[/C][C]2[/C][C]2.69919[/C][C]-0.699187[/C][/ROW]
[ROW][C]137[/C][C]3[/C][C]2.82773[/C][C]0.172275[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]1.65603[/C][C]-0.656028[/C][/ROW]
[ROW][C]139[/C][C]4[/C][C]3.70483[/C][C]0.295167[/C][/ROW]
[ROW][C]140[/C][C]3[/C][C]3.58727[/C][C]-0.587268[/C][/ROW]
[ROW][C]141[/C][C]2[/C][C]1.79667[/C][C]0.203328[/C][/ROW]
[ROW][C]142[/C][C]4[/C][C]3.01637[/C][C]0.983633[/C][/ROW]
[ROW][C]143[/C][C]4[/C][C]2.97149[/C][C]1.02851[/C][/ROW]
[ROW][C]144[/C][C]4[/C][C]3.37475[/C][C]0.625255[/C][/ROW]
[ROW][C]145[/C][C]4[/C][C]3.25968[/C][C]0.740317[/C][/ROW]
[ROW][C]146[/C][C]4[/C][C]2.9768[/C][C]1.0232[/C][/ROW]
[ROW][C]147[/C][C]3[/C][C]2.66867[/C][C]0.331325[/C][/ROW]
[ROW][C]148[/C][C]3[/C][C]2.58704[/C][C]0.412962[/C][/ROW]
[ROW][C]149[/C][C]4[/C][C]3.71364[/C][C]0.286356[/C][/ROW]
[ROW][C]150[/C][C]4[/C][C]3.93275[/C][C]0.0672471[/C][/ROW]
[ROW][C]151[/C][C]4[/C][C]3.54055[/C][C]0.459446[/C][/ROW]
[ROW][C]152[/C][C]3[/C][C]2.53737[/C][C]0.462631[/C][/ROW]
[ROW][C]153[/C][C]4[/C][C]3.58788[/C][C]0.41212[/C][/ROW]
[ROW][C]154[/C][C]4[/C][C]4.02256[/C][C]-0.0225648[/C][/ROW]
[ROW][C]155[/C][C]2[/C][C]2.11801[/C][C]-0.118009[/C][/ROW]
[ROW][C]156[/C][C]2[/C][C]2.25292[/C][C]-0.252918[/C][/ROW]
[ROW][C]157[/C][C]4[/C][C]3.48109[/C][C]0.518912[/C][/ROW]
[ROW][C]158[/C][C]3[/C][C]2.92942[/C][C]0.0705834[/C][/ROW]
[ROW][C]159[/C][C]3[/C][C]3.30771[/C][C]-0.307711[/C][/ROW]
[ROW][C]160[/C][C]2[/C][C]2.22525[/C][C]-0.225245[/C][/ROW]
[ROW][C]161[/C][C]3[/C][C]2.22029[/C][C]0.779711[/C][/ROW]
[ROW][C]162[/C][C]2[/C][C]3.26578[/C][C]-1.26578[/C][/ROW]
[ROW][C]163[/C][C]4[/C][C]3.10915[/C][C]0.890846[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]1.09268[/C][C]-0.0926758[/C][/ROW]
[ROW][C]165[/C][C]4[/C][C]3.2112[/C][C]0.788797[/C][/ROW]
[ROW][C]166[/C][C]1[/C][C]1.73441[/C][C]-0.734409[/C][/ROW]
[ROW][C]167[/C][C]4[/C][C]3.06222[/C][C]0.937781[/C][/ROW]
[ROW][C]168[/C][C]3[/C][C]2.07479[/C][C]0.925215[/C][/ROW]
[ROW][C]169[/C][C]3[/C][C]3.06817[/C][C]-0.0681679[/C][/ROW]
[ROW][C]170[/C][C]2[/C][C]2.33446[/C][C]-0.334457[/C][/ROW]
[ROW][C]171[/C][C]3[/C][C]2.86184[/C][C]0.138164[/C][/ROW]
[ROW][C]172[/C][C]3[/C][C]2.54399[/C][C]0.456009[/C][/ROW]
[ROW][C]173[/C][C]4[/C][C]2.65611[/C][C]1.34389[/C][/ROW]
[ROW][C]174[/C][C]4[/C][C]3.78046[/C][C]0.219542[/C][/ROW]
[ROW][C]175[/C][C]4[/C][C]3.78046[/C][C]0.219542[/C][/ROW]
[ROW][C]176[/C][C]3[/C][C]2.4798[/C][C]0.520203[/C][/ROW]
[ROW][C]177[/C][C]3[/C][C]2.65694[/C][C]0.343064[/C][/ROW]
[ROW][C]178[/C][C]4[/C][C]3.75663[/C][C]0.243369[/C][/ROW]
[ROW][C]179[/C][C]4[/C][C]2.69734[/C][C]1.30266[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]2.00896[/C][C]-1.00896[/C][/ROW]
[ROW][C]181[/C][C]2[/C][C]2.26136[/C][C]-0.26136[/C][/ROW]
[ROW][C]182[/C][C]3[/C][C]2.72856[/C][C]0.27144[/C][/ROW]
[ROW][C]183[/C][C]4[/C][C]3.72728[/C][C]0.272724[/C][/ROW]
[ROW][C]184[/C][C]3[/C][C]2.46032[/C][C]0.539684[/C][/ROW]
[ROW][C]185[/C][C]4[/C][C]2.58617[/C][C]1.41383[/C][/ROW]
[ROW][C]186[/C][C]3[/C][C]2.57978[/C][C]0.420223[/C][/ROW]
[ROW][C]187[/C][C]3[/C][C]2.47402[/C][C]0.525984[/C][/ROW]
[ROW][C]188[/C][C]3[/C][C]2.40508[/C][C]0.594922[/C][/ROW]
[ROW][C]189[/C][C]3[/C][C]2.2531[/C][C]0.746902[/C][/ROW]
[ROW][C]190[/C][C]1[/C][C]1.94405[/C][C]-0.944048[/C][/ROW]
[ROW][C]191[/C][C]1[/C][C]1.81299[/C][C]-0.812994[/C][/ROW]
[ROW][C]192[/C][C]3[/C][C]2.17678[/C][C]0.82322[/C][/ROW]
[ROW][C]193[/C][C]2[/C][C]1.66606[/C][C]0.333941[/C][/ROW]
[ROW][C]194[/C][C]3[/C][C]2.5838[/C][C]0.416199[/C][/ROW]
[ROW][C]195[/C][C]2[/C][C]2.02871[/C][C]-0.0287137[/C][/ROW]
[ROW][C]196[/C][C]2[/C][C]2.5789[/C][C]-0.578898[/C][/ROW]
[ROW][C]197[/C][C]4[/C][C]3.67254[/C][C]0.327457[/C][/ROW]
[ROW][C]198[/C][C]2[/C][C]2.50072[/C][C]-0.500723[/C][/ROW]
[ROW][C]199[/C][C]2[/C][C]2.06662[/C][C]-0.0666177[/C][/ROW]
[ROW][C]200[/C][C]3[/C][C]2.428[/C][C]0.572003[/C][/ROW]
[ROW][C]201[/C][C]4[/C][C]4.56437[/C][C]-0.564368[/C][/ROW]
[ROW][C]202[/C][C]2[/C][C]1.92114[/C][C]0.0788579[/C][/ROW]
[ROW][C]203[/C][C]4[/C][C]2.83064[/C][C]1.16936[/C][/ROW]
[ROW][C]204[/C][C]3[/C][C]3.05658[/C][C]-0.0565822[/C][/ROW]
[ROW][C]205[/C][C]4[/C][C]2.64173[/C][C]1.35827[/C][/ROW]
[ROW][C]206[/C][C]2[/C][C]1.88714[/C][C]0.112862[/C][/ROW]
[ROW][C]207[/C][C]1[/C][C]2.01726[/C][C]-1.01726[/C][/ROW]
[ROW][C]208[/C][C]1[/C][C]1.62971[/C][C]-0.629714[/C][/ROW]
[ROW][C]209[/C][C]4[/C][C]3.10367[/C][C]0.896326[/C][/ROW]
[ROW][C]210[/C][C]3[/C][C]2.61595[/C][C]0.384049[/C][/ROW]
[ROW][C]211[/C][C]1[/C][C]1.13582[/C][C]-0.135817[/C][/ROW]
[ROW][C]212[/C][C]4[/C][C]2.98264[/C][C]1.01736[/C][/ROW]
[ROW][C]213[/C][C]3[/C][C]2.87713[/C][C]0.122874[/C][/ROW]
[ROW][C]214[/C][C]2[/C][C]2.96995[/C][C]-0.969953[/C][/ROW]
[ROW][C]215[/C][C]4[/C][C]3.64797[/C][C]0.352028[/C][/ROW]
[ROW][C]216[/C][C]3[/C][C]2.61384[/C][C]0.386156[/C][/ROW]
[ROW][C]217[/C][C]3[/C][C]2.35379[/C][C]0.646206[/C][/ROW]
[ROW][C]218[/C][C]4[/C][C]3.55011[/C][C]0.44989[/C][/ROW]
[ROW][C]219[/C][C]1[/C][C]1.64706[/C][C]-0.647057[/C][/ROW]
[ROW][C]220[/C][C]3[/C][C]3.11014[/C][C]-0.110145[/C][/ROW]
[ROW][C]221[/C][C]4[/C][C]3.73797[/C][C]0.26203[/C][/ROW]
[ROW][C]222[/C][C]1[/C][C]1.85532[/C][C]-0.855318[/C][/ROW]
[ROW][C]223[/C][C]3[/C][C]2.47697[/C][C]0.523035[/C][/ROW]
[ROW][C]224[/C][C]4[/C][C]2.48606[/C][C]1.51394[/C][/ROW]
[ROW][C]225[/C][C]4[/C][C]3.67281[/C][C]0.327189[/C][/ROW]
[ROW][C]226[/C][C]1[/C][C]1.88511[/C][C]-0.885111[/C][/ROW]
[ROW][C]227[/C][C]4[/C][C]2.92098[/C][C]1.07902[/C][/ROW]
[ROW][C]228[/C][C]2[/C][C]2.4464[/C][C]-0.446403[/C][/ROW]
[ROW][C]229[/C][C]3[/C][C]2.63826[/C][C]0.361744[/C][/ROW]
[ROW][C]230[/C][C]4[/C][C]3.29585[/C][C]0.704153[/C][/ROW]
[ROW][C]231[/C][C]4[/C][C]3.30972[/C][C]0.690276[/C][/ROW]
[ROW][C]232[/C][C]4[/C][C]3.29018[/C][C]0.709819[/C][/ROW]
[ROW][C]233[/C][C]2[/C][C]2.1189[/C][C]-0.118897[/C][/ROW]
[ROW][C]234[/C][C]4[/C][C]3.21092[/C][C]0.789079[/C][/ROW]
[ROW][C]235[/C][C]2[/C][C]2.08481[/C][C]-0.0848085[/C][/ROW]
[ROW][C]236[/C][C]1[/C][C]1.72425[/C][C]-0.724251[/C][/ROW]
[ROW][C]237[/C][C]1[/C][C]1.55208[/C][C]-0.552078[/C][/ROW]
[ROW][C]238[/C][C]4[/C][C]3.59495[/C][C]0.405047[/C][/ROW]
[ROW][C]239[/C][C]2[/C][C]2.14222[/C][C]-0.142217[/C][/ROW]
[ROW][C]240[/C][C]2[/C][C]2.04222[/C][C]-0.0422231[/C][/ROW]
[ROW][C]241[/C][C]3[/C][C]2.78334[/C][C]0.216658[/C][/ROW]
[ROW][C]242[/C][C]2[/C][C]2.26124[/C][C]-0.261237[/C][/ROW]
[ROW][C]243[/C][C]3[/C][C]2.25814[/C][C]0.741859[/C][/ROW]
[ROW][C]244[/C][C]4[/C][C]3.2112[/C][C]0.788797[/C][/ROW]
[ROW][C]245[/C][C]2[/C][C]2.28092[/C][C]-0.280919[/C][/ROW]
[ROW][C]246[/C][C]3[/C][C]3.04267[/C][C]-0.0426722[/C][/ROW]
[ROW][C]247[/C][C]4[/C][C]3.24145[/C][C]0.758547[/C][/ROW]
[ROW][C]248[/C][C]3[/C][C]2.68468[/C][C]0.31532[/C][/ROW]
[ROW][C]249[/C][C]4[/C][C]2.88194[/C][C]1.11806[/C][/ROW]
[ROW][C]250[/C][C]4[/C][C]2.86639[/C][C]1.13361[/C][/ROW]
[ROW][C]251[/C][C]4[/C][C]2.91175[/C][C]1.08825[/C][/ROW]
[ROW][C]252[/C][C]2[/C][C]2.43992[/C][C]-0.439922[/C][/ROW]
[ROW][C]253[/C][C]2[/C][C]2.62852[/C][C]-0.628518[/C][/ROW]
[ROW][C]254[/C][C]2[/C][C]2.03074[/C][C]-0.0307395[/C][/ROW]
[ROW][C]255[/C][C]4[/C][C]3.13023[/C][C]0.869774[/C][/ROW]
[ROW][C]256[/C][C]3[/C][C]2.97487[/C][C]0.0251326[/C][/ROW]
[ROW][C]257[/C][C]2[/C][C]1.56322[/C][C]0.43678[/C][/ROW]
[ROW][C]258[/C][C]2[/C][C]2.88272[/C][C]-0.882723[/C][/ROW]
[ROW][C]259[/C][C]3[/C][C]2.03767[/C][C]0.962328[/C][/ROW]
[ROW][C]260[/C][C]3[/C][C]2.13841[/C][C]0.861592[/C][/ROW]
[ROW][C]261[/C][C]1[/C][C]1.73441[/C][C]-0.734409[/C][/ROW]
[ROW][C]262[/C][C]2[/C][C]2.05807[/C][C]-0.0580669[/C][/ROW]
[ROW][C]263[/C][C]2[/C][C]2.5292[/C][C]-0.529198[/C][/ROW]
[ROW][C]264[/C][C]3[/C][C]2.25814[/C][C]0.741859[/C][/ROW]
[ROW][C]265[/C][C]3[/C][C]2.79118[/C][C]0.208824[/C][/ROW]
[ROW][C]266[/C][C]2[/C][C]2.0226[/C][C]-0.0226025[/C][/ROW]
[ROW][C]267[/C][C]2[/C][C]2.41104[/C][C]-0.411037[/C][/ROW]
[ROW][C]268[/C][C]3[/C][C]2.31716[/C][C]0.68284[/C][/ROW]
[ROW][C]269[/C][C]3[/C][C]2.37097[/C][C]0.629029[/C][/ROW]
[ROW][C]270[/C][C]1[/C][C]1.44852[/C][C]-0.448521[/C][/ROW]
[ROW][C]271[/C][C]3[/C][C]2.49228[/C][C]0.507716[/C][/ROW]
[ROW][C]272[/C][C]2[/C][C]1.92696[/C][C]0.0730436[/C][/ROW]
[ROW][C]273[/C][C]2[/C][C]2.43661[/C][C]-0.436611[/C][/ROW]
[ROW][C]274[/C][C]3[/C][C]3.13115[/C][C]-0.131154[/C][/ROW]
[ROW][C]275[/C][C]3[/C][C]2.28007[/C][C]0.719926[/C][/ROW]
[ROW][C]276[/C][C]3[/C][C]2.77641[/C][C]0.223592[/C][/ROW]
[ROW][C]277[/C][C]3[/C][C]2.9045[/C][C]0.0955027[/C][/ROW]
[ROW][C]278[/C][C]1[/C][C]1.45546[/C][C]-0.455458[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266995&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266995&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
11.82.28121-0.481214
22.12.39941-0.299411
32.22.74383-0.543834
42.32.72374-0.423736
52.12.34286-0.242857
62.74.08947-1.38947
72.12.67425-0.574248
82.42.061160.338844
92.92.716310.183694
102.23.31372-1.11372
112.12.89684-0.796837
122.23.12704-0.927043
132.22.37341-0.173411
142.73.04503-0.345032
151.91.418310.481686
1622.01494-0.0149406
172.53.03577-0.535765
182.22.49592-0.29592
192.32.60228-0.302276
201.92.18858-0.288585
212.12.75961-0.659611
223.53.313130.186868
232.13.50113-1.40113
242.32.7942-0.494196
252.32.71032-0.41032
262.23.85397-1.65397
273.52.912050.587952
281.91.867990.0320141
291.92.17785-0.277851
301.92.63554-0.735543
311.92.02989-0.129895
322.13.00583-0.905828
3322.59499-0.594987
343.23.45617-0.256165
352.32.40665-0.106649
362.52.56033-0.0603335
371.82.4945-0.694503
382.42.89005-0.490051
392.82.89753-0.0975338
402.33.16958-0.869575
4122.02782-0.0278186
422.53.16256-0.662557
432.32.5916-0.291597
441.82.73095-0.930952
451.91.495910.404086
462.63.33908-0.739076
4722.25674-0.256745
482.62.01490.585095
491.61.56980.0302031
502.22.050370.149627
512.12.36483-0.264827
521.81.555650.244349
531.82.91742-1.11742
541.92.88161-0.981608
552.42.80692-0.406916
561.92.674-0.774004
5722.44817-0.448165
582.12.56153-0.461526
591.71.379380.320615
601.92.02732-0.12732
612.12.62382-0.523819
622.42.91075-0.510745
631.81.83765-0.0376459
642.33.32979-1.02979
652.12.80295-0.702948
6621.688340.311658
672.83.35595-0.555946
6822.9734-0.973404
692.73.41536-0.71536
702.12.057120.042881
712.93.27268-0.372675
7222.34255-0.34255
731.81.729250.0707536
742.61.926410.673592
752.12.67582-0.575821
762.33.00396-0.703965
772.22.2345-0.0344957
7823.14588-1.14588
792.21.927770.272228
802.12.057330.0426745
812.11.89420.2058
821.92.04714-0.147136
8321.971220.0287845
841.71.75677-0.0567705
852.22.177090.0229106
862.21.96090.239102
872.31.842460.457538
882.41.971650.428347
892.11.780940.319056
901.92.24147-0.341466
911.71.582450.117553
921.82.14491-0.344913
931.52.05244-0.552439
941.92.24024-0.340244
951.92.24897-0.348969
961.72.06272-0.362722
971.92.50344-0.603442
981.92.12146-0.221461
991.82.11854-0.318541
1002.42.081050.318955
1011.81.668730.131268
1021.92.16259-0.262591
1031.81.728930.0710669
1042.12.19866-0.0986557
1051.92.06416-0.164156
1062.21.905460.29454
10721.971070.0289252
1081.71.82762-0.127623
1091.71.421210.278789
1101.81.698790.101207
1111.92.14232-0.242319
1121.81.93587-0.135875
11311.48602-0.486017
11411.80953-0.809527
11543.318820.681182
11643.424930.575071
11732.638710.361293
11821.634140.36586
11945.30126-1.30126
12043.452630.547373
12143.501850.498154
12221.797810.202188
12343.811250.188754
12411.57814-0.578142
12532.941510.0584892
12632.772170.227826
12743.256580.743421
12833.8193-0.8193
12943.41810.581896
13032.4840.515998
13132.42520.5748
13244.1166-0.116601
13332.764760.23524
13432.816060.183936
13522.11847-0.118466
13622.69919-0.699187
13732.827730.172275
13811.65603-0.656028
13943.704830.295167
14033.58727-0.587268
14121.796670.203328
14243.016370.983633
14342.971491.02851
14443.374750.625255
14543.259680.740317
14642.97681.0232
14732.668670.331325
14832.587040.412962
14943.713640.286356
15043.932750.0672471
15143.540550.459446
15232.537370.462631
15343.587880.41212
15444.02256-0.0225648
15522.11801-0.118009
15622.25292-0.252918
15743.481090.518912
15832.929420.0705834
15933.30771-0.307711
16022.22525-0.225245
16132.220290.779711
16223.26578-1.26578
16343.109150.890846
16411.09268-0.0926758
16543.21120.788797
16611.73441-0.734409
16743.062220.937781
16832.074790.925215
16933.06817-0.0681679
17022.33446-0.334457
17132.861840.138164
17232.543990.456009
17342.656111.34389
17443.780460.219542
17543.780460.219542
17632.47980.520203
17732.656940.343064
17843.756630.243369
17942.697341.30266
18012.00896-1.00896
18122.26136-0.26136
18232.728560.27144
18343.727280.272724
18432.460320.539684
18542.586171.41383
18632.579780.420223
18732.474020.525984
18832.405080.594922
18932.25310.746902
19011.94405-0.944048
19111.81299-0.812994
19232.176780.82322
19321.666060.333941
19432.58380.416199
19522.02871-0.0287137
19622.5789-0.578898
19743.672540.327457
19822.50072-0.500723
19922.06662-0.0666177
20032.4280.572003
20144.56437-0.564368
20221.921140.0788579
20342.830641.16936
20433.05658-0.0565822
20542.641731.35827
20621.887140.112862
20712.01726-1.01726
20811.62971-0.629714
20943.103670.896326
21032.615950.384049
21111.13582-0.135817
21242.982641.01736
21332.877130.122874
21422.96995-0.969953
21543.647970.352028
21632.613840.386156
21732.353790.646206
21843.550110.44989
21911.64706-0.647057
22033.11014-0.110145
22143.737970.26203
22211.85532-0.855318
22332.476970.523035
22442.486061.51394
22543.672810.327189
22611.88511-0.885111
22742.920981.07902
22822.4464-0.446403
22932.638260.361744
23043.295850.704153
23143.309720.690276
23243.290180.709819
23322.1189-0.118897
23443.210920.789079
23522.08481-0.0848085
23611.72425-0.724251
23711.55208-0.552078
23843.594950.405047
23922.14222-0.142217
24022.04222-0.0422231
24132.783340.216658
24222.26124-0.261237
24332.258140.741859
24443.21120.788797
24522.28092-0.280919
24633.04267-0.0426722
24743.241450.758547
24832.684680.31532
24942.881941.11806
25042.866391.13361
25142.911751.08825
25222.43992-0.439922
25322.62852-0.628518
25422.03074-0.0307395
25543.130230.869774
25632.974870.0251326
25721.563220.43678
25822.88272-0.882723
25932.037670.962328
26032.138410.861592
26111.73441-0.734409
26222.05807-0.0580669
26322.5292-0.529198
26432.258140.741859
26532.791180.208824
26622.0226-0.0226025
26722.41104-0.411037
26832.317160.68284
26932.370970.629029
27011.44852-0.448521
27132.492280.507716
27221.926960.0730436
27322.43661-0.436611
27433.13115-0.131154
27532.280070.719926
27632.776410.223592
27732.90450.0955027
27811.45546-0.455458






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
89.42891e-050.0001885780.999906
93.20244e-066.40488e-060.999997
106.94323e-071.38865e-060.999999
114.0701e-088.14019e-081
129.73351e-091.9467e-081
135.65022e-101.13004e-091
143.34458e-116.68917e-111
151.90707e-123.81415e-121
168.591e-141.7182e-131
176.38825e-151.27765e-141
184.25844e-168.51689e-161
192.92021e-175.84042e-171
202.0108e-184.0216e-181
212.24231e-194.48462e-191
221.7688e-203.5376e-201
231.29471e-212.58941e-211
246.09368e-231.21874e-221
251.22085e-232.4417e-231
263.38568e-246.77136e-241
271.38017e-242.76034e-241
282.09998e-254.19995e-251
296.95798e-261.3916e-251
304.56833e-279.13666e-271
314.3801e-288.76021e-281
323.02115e-296.04229e-291
337.60973e-301.52195e-291
346.18253e-311.23651e-301
353.55927e-327.11853e-321
362.32687e-334.65375e-331
371.67185e-343.34369e-341
389.86412e-361.97282e-351
397.91558e-371.58312e-361
405.61944e-381.12389e-371
413.83896e-397.67791e-391
424.04784e-408.09569e-401
432.89338e-415.78677e-411
446.69741e-421.33948e-411
454.59013e-439.18026e-431
466.27703e-441.25541e-431
471.03441e-442.06883e-441
486.17088e-461.23418e-451
493.44116e-476.88231e-471
501.86623e-483.73247e-481
511.24062e-492.48123e-491
526.86542e-511.37308e-501
534.15574e-518.31149e-511
544.42576e-528.85153e-521
553.37721e-536.75443e-531
563.97224e-547.94448e-541
574.18571e-558.37141e-551
582.91124e-565.82248e-561
592.99741e-575.99481e-571
603.05248e-586.10497e-581
612.60779e-595.21558e-591
622.91944e-605.83889e-601
631.97982e-613.95965e-611
647.84422e-621.56884e-611
651.57733e-623.15465e-621
669.71229e-641.94246e-631
671.33421e-642.66842e-641
687.96291e-641.59258e-631
693.18153e-646.36305e-641
702.17755e-654.3551e-651
711.55377e-653.10754e-651
722.33655e-664.6731e-661
731.58564e-673.17127e-671
743.07207e-686.14413e-681
756.42049e-691.2841e-681
763.17517e-696.35033e-691
772.40646e-704.81293e-701
786.15073e-701.23015e-691
791.46448e-702.92896e-701
801.63504e-713.27009e-711
812.01484e-724.02967e-721
823.06652e-736.13304e-731
833.01676e-746.03352e-741
842.88734e-755.77467e-751
857.0044e-761.40088e-751
861.08254e-762.16508e-761
873.87842e-777.75684e-771
885.14188e-781.02838e-771
894.77028e-799.54056e-791
902.17665e-794.35331e-791
912.86384e-805.72769e-801
921.7768e-803.5536e-801
932.21953e-794.43906e-791
943.91004e-807.82007e-801
951.134e-802.268e-801
968.18834e-811.63767e-801
971.02089e-802.04177e-801
982.95102e-815.90203e-811
991.21031e-812.42062e-811
1002.31734e-824.63467e-821
1012.68015e-835.36031e-831
1026.15636e-841.23127e-831
1031.70477e-843.40955e-841
1042.7488e-845.4976e-841
1058.74977e-851.74995e-841
1069.49912e-861.89982e-851
1071.93077e-863.86155e-861
1089.69336e-871.93867e-861
1095.33887e-871.06777e-861
1102.02539e-874.05078e-871
1117.87585e-871.57517e-861
1129.13729e-871.82746e-861
1131.07637e-372.15274e-371
1141.09248e-282.18496e-281
1151.60466e-083.20932e-081
1160.0005605940.001121190.999439
1170.0008377790.001675560.999162
1180.0007864980.0015730.999214
1190.001769030.003538050.998231
1200.004784890.009569780.995215
1210.005576430.01115290.994424
1220.004907810.009815620.995092
1230.01944840.03889670.980552
1240.04096630.08193260.959034
1250.03868480.07736960.961315
1260.05434970.1086990.94565
1270.2286890.4573780.771311
1280.5208590.9582810.479141
1290.5902690.8194610.409731
1300.6396170.7207670.360383
1310.7157460.5685080.284254
1320.6896360.6207280.310364
1330.679680.640640.32032
1340.6581970.6836050.341803
1350.6286050.7427910.371395
1360.671080.6578390.32892
1370.6918830.6162330.308117
1380.7525240.4949530.247476
1390.7997890.4004210.200211
1400.789490.4210210.21051
1410.7677990.4644030.232201
1420.9168770.1662450.0831225
1430.9559550.088090.044045
1440.9809950.03801030.0190051
1450.989220.0215610.0107805
1460.9958920.008216950.00410848
1470.9953760.009247070.00462353
1480.9949750.01005080.00502542
1490.9966430.006714630.00335731
1500.9969050.006190420.00309521
1510.9980520.003895520.00194776
1520.9977010.004597070.00229853
1530.9978290.004341750.00217087
1540.99790.004200510.00210025
1550.9974110.005177830.00258892
1560.997320.005359950.00267997
1570.9977160.004568920.00228446
1580.9970350.005930170.00296509
1590.9963610.007277220.00363861
1600.9956940.008611950.00430598
1610.9961510.007698150.00384908
1620.9978810.004237710.00211886
1630.9991280.001743070.000871535
1640.9995590.0008827340.000441367
1650.9996180.0007639610.000381981
1660.9997220.000555550.000277775
1670.999910.0001797878.98935e-05
1680.9999519.86455e-054.93228e-05
1690.9999519.78692e-054.89346e-05
1700.9999390.0001229936.14963e-05
1710.9999360.000128816.44048e-05
1720.9999170.0001654528.27259e-05
1730.9999656.93358e-053.46679e-05
1740.9999637.32934e-053.66467e-05
1750.9999617.80925e-053.90462e-05
1760.9999519.85338e-054.92669e-05
1770.9999330.0001339726.69861e-05
1780.9999150.0001695158.47574e-05
1790.9999568.73679e-054.36839e-05
1800.9999686.33493e-053.16746e-05
1810.9999656.95543e-053.47772e-05
1820.9999539.36752e-054.68376e-05
1830.9999360.0001283786.41892e-05
1840.9999230.0001543787.7189e-05
1850.9999647.14474e-053.57237e-05
1860.9999519.82854e-054.91427e-05
1870.999940.0001192625.96308e-05
1880.9999240.000151737.58648e-05
1890.9999140.0001721818.60904e-05
1900.9999568.76162e-054.38081e-05
1910.9999745.29577e-052.64788e-05
1920.9999696.16151e-053.08075e-05
1930.9999568.84112e-054.42056e-05
1940.9999390.0001224066.12028e-05
1950.9999090.0001827049.1352e-05
1960.9998850.0002290140.000114507
1970.9998440.0003114180.000155709
1980.9998230.0003530120.000176506
1990.9997420.00051670.00025835
2000.9996670.0006664780.000333239
2010.9999983.65582e-061.82791e-06
2020.9999984.65799e-062.32899e-06
2030.9999983.44423e-061.72211e-06
2040.9999975.65617e-062.82809e-06
20517.12955e-073.56478e-07
20617.38972e-073.69486e-07
20717.82001e-073.91e-07
20819.13836e-074.56918e-07
20916.27915e-073.13958e-07
21017.56925e-073.78462e-07
2110.9999991.31814e-066.59071e-07
2120.9999991.5329e-067.66448e-07
2130.9999992.44744e-061.22372e-06
2140.9999983.32459e-061.66229e-06
2150.9999975.41942e-062.70971e-06
2160.9999976.73645e-063.36823e-06
2170.9999984.96911e-062.48456e-06
2180.9999992.39204e-061.19602e-06
2190.9999992.19175e-061.09588e-06
2200.9999983.88873e-061.94437e-06
2210.9999975.35883e-062.67941e-06
2220.9999976.34855e-063.17428e-06
2230.9999959.80087e-064.90043e-06
2240.9999983.2429e-061.62145e-06
2250.9999983.35562e-061.67781e-06
2260.9999992.91872e-061.45936e-06
2270.9999992.03426e-061.01713e-06
2280.9999983.19117e-061.59558e-06
2290.9999984.56198e-062.28099e-06
2300.9999967.33146e-063.66573e-06
2310.9999959.40772e-064.70386e-06
2320.9999931.38533e-056.92663e-06
2330.999992.08828e-051.04414e-05
2340.9999892.2178e-051.1089e-05
2350.999992.0655e-051.03275e-05
2360.9999882.49097e-051.24549e-05
2370.9999833.36204e-051.68102e-05
2380.9999764.81483e-052.40741e-05
2390.9999637.36125e-053.68062e-05
2400.9999430.0001131965.65978e-05
2410.99990.0002002130.000100107
2420.999880.0002390370.000119519
2430.9998570.0002863620.000143181
2440.9997790.0004417220.000220861
2450.9996530.0006943480.000347174
2460.9993770.001245060.000622528
2470.9994470.001105750.000552876
2480.999040.001919440.00095972
2490.9995440.0009118840.000455942
2500.9997350.0005291040.000264552
2510.9997220.0005553730.000277686
2520.9995030.0009933830.000496692
2530.9995560.0008884610.00044423
2540.9993760.001248630.000624315
2550.9991280.001744430.000872215
2560.9982960.003408850.00170443
2570.9977030.004594310.00229715
2580.9973170.005366070.00268304
2590.9964590.007081080.00354054
2600.9957580.008484780.00424239
2610.9919660.01606860.00803432
2620.9883170.02336660.0116833
2630.9942370.01152620.00576311
2640.9910110.01797870.00898937
2650.9864080.02718460.0135923
2660.9874170.02516550.0125828
2670.969580.06083910.0304195
2680.9327420.1345160.0672581
2690.8691780.2616450.130822
2700.8625080.2749850.137492

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 9.42891e-05 & 0.000188578 & 0.999906 \tabularnewline
9 & 3.20244e-06 & 6.40488e-06 & 0.999997 \tabularnewline
10 & 6.94323e-07 & 1.38865e-06 & 0.999999 \tabularnewline
11 & 4.0701e-08 & 8.14019e-08 & 1 \tabularnewline
12 & 9.73351e-09 & 1.9467e-08 & 1 \tabularnewline
13 & 5.65022e-10 & 1.13004e-09 & 1 \tabularnewline
14 & 3.34458e-11 & 6.68917e-11 & 1 \tabularnewline
15 & 1.90707e-12 & 3.81415e-12 & 1 \tabularnewline
16 & 8.591e-14 & 1.7182e-13 & 1 \tabularnewline
17 & 6.38825e-15 & 1.27765e-14 & 1 \tabularnewline
18 & 4.25844e-16 & 8.51689e-16 & 1 \tabularnewline
19 & 2.92021e-17 & 5.84042e-17 & 1 \tabularnewline
20 & 2.0108e-18 & 4.0216e-18 & 1 \tabularnewline
21 & 2.24231e-19 & 4.48462e-19 & 1 \tabularnewline
22 & 1.7688e-20 & 3.5376e-20 & 1 \tabularnewline
23 & 1.29471e-21 & 2.58941e-21 & 1 \tabularnewline
24 & 6.09368e-23 & 1.21874e-22 & 1 \tabularnewline
25 & 1.22085e-23 & 2.4417e-23 & 1 \tabularnewline
26 & 3.38568e-24 & 6.77136e-24 & 1 \tabularnewline
27 & 1.38017e-24 & 2.76034e-24 & 1 \tabularnewline
28 & 2.09998e-25 & 4.19995e-25 & 1 \tabularnewline
29 & 6.95798e-26 & 1.3916e-25 & 1 \tabularnewline
30 & 4.56833e-27 & 9.13666e-27 & 1 \tabularnewline
31 & 4.3801e-28 & 8.76021e-28 & 1 \tabularnewline
32 & 3.02115e-29 & 6.04229e-29 & 1 \tabularnewline
33 & 7.60973e-30 & 1.52195e-29 & 1 \tabularnewline
34 & 6.18253e-31 & 1.23651e-30 & 1 \tabularnewline
35 & 3.55927e-32 & 7.11853e-32 & 1 \tabularnewline
36 & 2.32687e-33 & 4.65375e-33 & 1 \tabularnewline
37 & 1.67185e-34 & 3.34369e-34 & 1 \tabularnewline
38 & 9.86412e-36 & 1.97282e-35 & 1 \tabularnewline
39 & 7.91558e-37 & 1.58312e-36 & 1 \tabularnewline
40 & 5.61944e-38 & 1.12389e-37 & 1 \tabularnewline
41 & 3.83896e-39 & 7.67791e-39 & 1 \tabularnewline
42 & 4.04784e-40 & 8.09569e-40 & 1 \tabularnewline
43 & 2.89338e-41 & 5.78677e-41 & 1 \tabularnewline
44 & 6.69741e-42 & 1.33948e-41 & 1 \tabularnewline
45 & 4.59013e-43 & 9.18026e-43 & 1 \tabularnewline
46 & 6.27703e-44 & 1.25541e-43 & 1 \tabularnewline
47 & 1.03441e-44 & 2.06883e-44 & 1 \tabularnewline
48 & 6.17088e-46 & 1.23418e-45 & 1 \tabularnewline
49 & 3.44116e-47 & 6.88231e-47 & 1 \tabularnewline
50 & 1.86623e-48 & 3.73247e-48 & 1 \tabularnewline
51 & 1.24062e-49 & 2.48123e-49 & 1 \tabularnewline
52 & 6.86542e-51 & 1.37308e-50 & 1 \tabularnewline
53 & 4.15574e-51 & 8.31149e-51 & 1 \tabularnewline
54 & 4.42576e-52 & 8.85153e-52 & 1 \tabularnewline
55 & 3.37721e-53 & 6.75443e-53 & 1 \tabularnewline
56 & 3.97224e-54 & 7.94448e-54 & 1 \tabularnewline
57 & 4.18571e-55 & 8.37141e-55 & 1 \tabularnewline
58 & 2.91124e-56 & 5.82248e-56 & 1 \tabularnewline
59 & 2.99741e-57 & 5.99481e-57 & 1 \tabularnewline
60 & 3.05248e-58 & 6.10497e-58 & 1 \tabularnewline
61 & 2.60779e-59 & 5.21558e-59 & 1 \tabularnewline
62 & 2.91944e-60 & 5.83889e-60 & 1 \tabularnewline
63 & 1.97982e-61 & 3.95965e-61 & 1 \tabularnewline
64 & 7.84422e-62 & 1.56884e-61 & 1 \tabularnewline
65 & 1.57733e-62 & 3.15465e-62 & 1 \tabularnewline
66 & 9.71229e-64 & 1.94246e-63 & 1 \tabularnewline
67 & 1.33421e-64 & 2.66842e-64 & 1 \tabularnewline
68 & 7.96291e-64 & 1.59258e-63 & 1 \tabularnewline
69 & 3.18153e-64 & 6.36305e-64 & 1 \tabularnewline
70 & 2.17755e-65 & 4.3551e-65 & 1 \tabularnewline
71 & 1.55377e-65 & 3.10754e-65 & 1 \tabularnewline
72 & 2.33655e-66 & 4.6731e-66 & 1 \tabularnewline
73 & 1.58564e-67 & 3.17127e-67 & 1 \tabularnewline
74 & 3.07207e-68 & 6.14413e-68 & 1 \tabularnewline
75 & 6.42049e-69 & 1.2841e-68 & 1 \tabularnewline
76 & 3.17517e-69 & 6.35033e-69 & 1 \tabularnewline
77 & 2.40646e-70 & 4.81293e-70 & 1 \tabularnewline
78 & 6.15073e-70 & 1.23015e-69 & 1 \tabularnewline
79 & 1.46448e-70 & 2.92896e-70 & 1 \tabularnewline
80 & 1.63504e-71 & 3.27009e-71 & 1 \tabularnewline
81 & 2.01484e-72 & 4.02967e-72 & 1 \tabularnewline
82 & 3.06652e-73 & 6.13304e-73 & 1 \tabularnewline
83 & 3.01676e-74 & 6.03352e-74 & 1 \tabularnewline
84 & 2.88734e-75 & 5.77467e-75 & 1 \tabularnewline
85 & 7.0044e-76 & 1.40088e-75 & 1 \tabularnewline
86 & 1.08254e-76 & 2.16508e-76 & 1 \tabularnewline
87 & 3.87842e-77 & 7.75684e-77 & 1 \tabularnewline
88 & 5.14188e-78 & 1.02838e-77 & 1 \tabularnewline
89 & 4.77028e-79 & 9.54056e-79 & 1 \tabularnewline
90 & 2.17665e-79 & 4.35331e-79 & 1 \tabularnewline
91 & 2.86384e-80 & 5.72769e-80 & 1 \tabularnewline
92 & 1.7768e-80 & 3.5536e-80 & 1 \tabularnewline
93 & 2.21953e-79 & 4.43906e-79 & 1 \tabularnewline
94 & 3.91004e-80 & 7.82007e-80 & 1 \tabularnewline
95 & 1.134e-80 & 2.268e-80 & 1 \tabularnewline
96 & 8.18834e-81 & 1.63767e-80 & 1 \tabularnewline
97 & 1.02089e-80 & 2.04177e-80 & 1 \tabularnewline
98 & 2.95102e-81 & 5.90203e-81 & 1 \tabularnewline
99 & 1.21031e-81 & 2.42062e-81 & 1 \tabularnewline
100 & 2.31734e-82 & 4.63467e-82 & 1 \tabularnewline
101 & 2.68015e-83 & 5.36031e-83 & 1 \tabularnewline
102 & 6.15636e-84 & 1.23127e-83 & 1 \tabularnewline
103 & 1.70477e-84 & 3.40955e-84 & 1 \tabularnewline
104 & 2.7488e-84 & 5.4976e-84 & 1 \tabularnewline
105 & 8.74977e-85 & 1.74995e-84 & 1 \tabularnewline
106 & 9.49912e-86 & 1.89982e-85 & 1 \tabularnewline
107 & 1.93077e-86 & 3.86155e-86 & 1 \tabularnewline
108 & 9.69336e-87 & 1.93867e-86 & 1 \tabularnewline
109 & 5.33887e-87 & 1.06777e-86 & 1 \tabularnewline
110 & 2.02539e-87 & 4.05078e-87 & 1 \tabularnewline
111 & 7.87585e-87 & 1.57517e-86 & 1 \tabularnewline
112 & 9.13729e-87 & 1.82746e-86 & 1 \tabularnewline
113 & 1.07637e-37 & 2.15274e-37 & 1 \tabularnewline
114 & 1.09248e-28 & 2.18496e-28 & 1 \tabularnewline
115 & 1.60466e-08 & 3.20932e-08 & 1 \tabularnewline
116 & 0.000560594 & 0.00112119 & 0.999439 \tabularnewline
117 & 0.000837779 & 0.00167556 & 0.999162 \tabularnewline
118 & 0.000786498 & 0.001573 & 0.999214 \tabularnewline
119 & 0.00176903 & 0.00353805 & 0.998231 \tabularnewline
120 & 0.00478489 & 0.00956978 & 0.995215 \tabularnewline
121 & 0.00557643 & 0.0111529 & 0.994424 \tabularnewline
122 & 0.00490781 & 0.00981562 & 0.995092 \tabularnewline
123 & 0.0194484 & 0.0388967 & 0.980552 \tabularnewline
124 & 0.0409663 & 0.0819326 & 0.959034 \tabularnewline
125 & 0.0386848 & 0.0773696 & 0.961315 \tabularnewline
126 & 0.0543497 & 0.108699 & 0.94565 \tabularnewline
127 & 0.228689 & 0.457378 & 0.771311 \tabularnewline
128 & 0.520859 & 0.958281 & 0.479141 \tabularnewline
129 & 0.590269 & 0.819461 & 0.409731 \tabularnewline
130 & 0.639617 & 0.720767 & 0.360383 \tabularnewline
131 & 0.715746 & 0.568508 & 0.284254 \tabularnewline
132 & 0.689636 & 0.620728 & 0.310364 \tabularnewline
133 & 0.67968 & 0.64064 & 0.32032 \tabularnewline
134 & 0.658197 & 0.683605 & 0.341803 \tabularnewline
135 & 0.628605 & 0.742791 & 0.371395 \tabularnewline
136 & 0.67108 & 0.657839 & 0.32892 \tabularnewline
137 & 0.691883 & 0.616233 & 0.308117 \tabularnewline
138 & 0.752524 & 0.494953 & 0.247476 \tabularnewline
139 & 0.799789 & 0.400421 & 0.200211 \tabularnewline
140 & 0.78949 & 0.421021 & 0.21051 \tabularnewline
141 & 0.767799 & 0.464403 & 0.232201 \tabularnewline
142 & 0.916877 & 0.166245 & 0.0831225 \tabularnewline
143 & 0.955955 & 0.08809 & 0.044045 \tabularnewline
144 & 0.980995 & 0.0380103 & 0.0190051 \tabularnewline
145 & 0.98922 & 0.021561 & 0.0107805 \tabularnewline
146 & 0.995892 & 0.00821695 & 0.00410848 \tabularnewline
147 & 0.995376 & 0.00924707 & 0.00462353 \tabularnewline
148 & 0.994975 & 0.0100508 & 0.00502542 \tabularnewline
149 & 0.996643 & 0.00671463 & 0.00335731 \tabularnewline
150 & 0.996905 & 0.00619042 & 0.00309521 \tabularnewline
151 & 0.998052 & 0.00389552 & 0.00194776 \tabularnewline
152 & 0.997701 & 0.00459707 & 0.00229853 \tabularnewline
153 & 0.997829 & 0.00434175 & 0.00217087 \tabularnewline
154 & 0.9979 & 0.00420051 & 0.00210025 \tabularnewline
155 & 0.997411 & 0.00517783 & 0.00258892 \tabularnewline
156 & 0.99732 & 0.00535995 & 0.00267997 \tabularnewline
157 & 0.997716 & 0.00456892 & 0.00228446 \tabularnewline
158 & 0.997035 & 0.00593017 & 0.00296509 \tabularnewline
159 & 0.996361 & 0.00727722 & 0.00363861 \tabularnewline
160 & 0.995694 & 0.00861195 & 0.00430598 \tabularnewline
161 & 0.996151 & 0.00769815 & 0.00384908 \tabularnewline
162 & 0.997881 & 0.00423771 & 0.00211886 \tabularnewline
163 & 0.999128 & 0.00174307 & 0.000871535 \tabularnewline
164 & 0.999559 & 0.000882734 & 0.000441367 \tabularnewline
165 & 0.999618 & 0.000763961 & 0.000381981 \tabularnewline
166 & 0.999722 & 0.00055555 & 0.000277775 \tabularnewline
167 & 0.99991 & 0.000179787 & 8.98935e-05 \tabularnewline
168 & 0.999951 & 9.86455e-05 & 4.93228e-05 \tabularnewline
169 & 0.999951 & 9.78692e-05 & 4.89346e-05 \tabularnewline
170 & 0.999939 & 0.000122993 & 6.14963e-05 \tabularnewline
171 & 0.999936 & 0.00012881 & 6.44048e-05 \tabularnewline
172 & 0.999917 & 0.000165452 & 8.27259e-05 \tabularnewline
173 & 0.999965 & 6.93358e-05 & 3.46679e-05 \tabularnewline
174 & 0.999963 & 7.32934e-05 & 3.66467e-05 \tabularnewline
175 & 0.999961 & 7.80925e-05 & 3.90462e-05 \tabularnewline
176 & 0.999951 & 9.85338e-05 & 4.92669e-05 \tabularnewline
177 & 0.999933 & 0.000133972 & 6.69861e-05 \tabularnewline
178 & 0.999915 & 0.000169515 & 8.47574e-05 \tabularnewline
179 & 0.999956 & 8.73679e-05 & 4.36839e-05 \tabularnewline
180 & 0.999968 & 6.33493e-05 & 3.16746e-05 \tabularnewline
181 & 0.999965 & 6.95543e-05 & 3.47772e-05 \tabularnewline
182 & 0.999953 & 9.36752e-05 & 4.68376e-05 \tabularnewline
183 & 0.999936 & 0.000128378 & 6.41892e-05 \tabularnewline
184 & 0.999923 & 0.000154378 & 7.7189e-05 \tabularnewline
185 & 0.999964 & 7.14474e-05 & 3.57237e-05 \tabularnewline
186 & 0.999951 & 9.82854e-05 & 4.91427e-05 \tabularnewline
187 & 0.99994 & 0.000119262 & 5.96308e-05 \tabularnewline
188 & 0.999924 & 0.00015173 & 7.58648e-05 \tabularnewline
189 & 0.999914 & 0.000172181 & 8.60904e-05 \tabularnewline
190 & 0.999956 & 8.76162e-05 & 4.38081e-05 \tabularnewline
191 & 0.999974 & 5.29577e-05 & 2.64788e-05 \tabularnewline
192 & 0.999969 & 6.16151e-05 & 3.08075e-05 \tabularnewline
193 & 0.999956 & 8.84112e-05 & 4.42056e-05 \tabularnewline
194 & 0.999939 & 0.000122406 & 6.12028e-05 \tabularnewline
195 & 0.999909 & 0.000182704 & 9.1352e-05 \tabularnewline
196 & 0.999885 & 0.000229014 & 0.000114507 \tabularnewline
197 & 0.999844 & 0.000311418 & 0.000155709 \tabularnewline
198 & 0.999823 & 0.000353012 & 0.000176506 \tabularnewline
199 & 0.999742 & 0.0005167 & 0.00025835 \tabularnewline
200 & 0.999667 & 0.000666478 & 0.000333239 \tabularnewline
201 & 0.999998 & 3.65582e-06 & 1.82791e-06 \tabularnewline
202 & 0.999998 & 4.65799e-06 & 2.32899e-06 \tabularnewline
203 & 0.999998 & 3.44423e-06 & 1.72211e-06 \tabularnewline
204 & 0.999997 & 5.65617e-06 & 2.82809e-06 \tabularnewline
205 & 1 & 7.12955e-07 & 3.56478e-07 \tabularnewline
206 & 1 & 7.38972e-07 & 3.69486e-07 \tabularnewline
207 & 1 & 7.82001e-07 & 3.91e-07 \tabularnewline
208 & 1 & 9.13836e-07 & 4.56918e-07 \tabularnewline
209 & 1 & 6.27915e-07 & 3.13958e-07 \tabularnewline
210 & 1 & 7.56925e-07 & 3.78462e-07 \tabularnewline
211 & 0.999999 & 1.31814e-06 & 6.59071e-07 \tabularnewline
212 & 0.999999 & 1.5329e-06 & 7.66448e-07 \tabularnewline
213 & 0.999999 & 2.44744e-06 & 1.22372e-06 \tabularnewline
214 & 0.999998 & 3.32459e-06 & 1.66229e-06 \tabularnewline
215 & 0.999997 & 5.41942e-06 & 2.70971e-06 \tabularnewline
216 & 0.999997 & 6.73645e-06 & 3.36823e-06 \tabularnewline
217 & 0.999998 & 4.96911e-06 & 2.48456e-06 \tabularnewline
218 & 0.999999 & 2.39204e-06 & 1.19602e-06 \tabularnewline
219 & 0.999999 & 2.19175e-06 & 1.09588e-06 \tabularnewline
220 & 0.999998 & 3.88873e-06 & 1.94437e-06 \tabularnewline
221 & 0.999997 & 5.35883e-06 & 2.67941e-06 \tabularnewline
222 & 0.999997 & 6.34855e-06 & 3.17428e-06 \tabularnewline
223 & 0.999995 & 9.80087e-06 & 4.90043e-06 \tabularnewline
224 & 0.999998 & 3.2429e-06 & 1.62145e-06 \tabularnewline
225 & 0.999998 & 3.35562e-06 & 1.67781e-06 \tabularnewline
226 & 0.999999 & 2.91872e-06 & 1.45936e-06 \tabularnewline
227 & 0.999999 & 2.03426e-06 & 1.01713e-06 \tabularnewline
228 & 0.999998 & 3.19117e-06 & 1.59558e-06 \tabularnewline
229 & 0.999998 & 4.56198e-06 & 2.28099e-06 \tabularnewline
230 & 0.999996 & 7.33146e-06 & 3.66573e-06 \tabularnewline
231 & 0.999995 & 9.40772e-06 & 4.70386e-06 \tabularnewline
232 & 0.999993 & 1.38533e-05 & 6.92663e-06 \tabularnewline
233 & 0.99999 & 2.08828e-05 & 1.04414e-05 \tabularnewline
234 & 0.999989 & 2.2178e-05 & 1.1089e-05 \tabularnewline
235 & 0.99999 & 2.0655e-05 & 1.03275e-05 \tabularnewline
236 & 0.999988 & 2.49097e-05 & 1.24549e-05 \tabularnewline
237 & 0.999983 & 3.36204e-05 & 1.68102e-05 \tabularnewline
238 & 0.999976 & 4.81483e-05 & 2.40741e-05 \tabularnewline
239 & 0.999963 & 7.36125e-05 & 3.68062e-05 \tabularnewline
240 & 0.999943 & 0.000113196 & 5.65978e-05 \tabularnewline
241 & 0.9999 & 0.000200213 & 0.000100107 \tabularnewline
242 & 0.99988 & 0.000239037 & 0.000119519 \tabularnewline
243 & 0.999857 & 0.000286362 & 0.000143181 \tabularnewline
244 & 0.999779 & 0.000441722 & 0.000220861 \tabularnewline
245 & 0.999653 & 0.000694348 & 0.000347174 \tabularnewline
246 & 0.999377 & 0.00124506 & 0.000622528 \tabularnewline
247 & 0.999447 & 0.00110575 & 0.000552876 \tabularnewline
248 & 0.99904 & 0.00191944 & 0.00095972 \tabularnewline
249 & 0.999544 & 0.000911884 & 0.000455942 \tabularnewline
250 & 0.999735 & 0.000529104 & 0.000264552 \tabularnewline
251 & 0.999722 & 0.000555373 & 0.000277686 \tabularnewline
252 & 0.999503 & 0.000993383 & 0.000496692 \tabularnewline
253 & 0.999556 & 0.000888461 & 0.00044423 \tabularnewline
254 & 0.999376 & 0.00124863 & 0.000624315 \tabularnewline
255 & 0.999128 & 0.00174443 & 0.000872215 \tabularnewline
256 & 0.998296 & 0.00340885 & 0.00170443 \tabularnewline
257 & 0.997703 & 0.00459431 & 0.00229715 \tabularnewline
258 & 0.997317 & 0.00536607 & 0.00268304 \tabularnewline
259 & 0.996459 & 0.00708108 & 0.00354054 \tabularnewline
260 & 0.995758 & 0.00848478 & 0.00424239 \tabularnewline
261 & 0.991966 & 0.0160686 & 0.00803432 \tabularnewline
262 & 0.988317 & 0.0233666 & 0.0116833 \tabularnewline
263 & 0.994237 & 0.0115262 & 0.00576311 \tabularnewline
264 & 0.991011 & 0.0179787 & 0.00898937 \tabularnewline
265 & 0.986408 & 0.0271846 & 0.0135923 \tabularnewline
266 & 0.987417 & 0.0251655 & 0.0125828 \tabularnewline
267 & 0.96958 & 0.0608391 & 0.0304195 \tabularnewline
268 & 0.932742 & 0.134516 & 0.0672581 \tabularnewline
269 & 0.869178 & 0.261645 & 0.130822 \tabularnewline
270 & 0.862508 & 0.274985 & 0.137492 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266995&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]8[/C][C]9.42891e-05[/C][C]0.000188578[/C][C]0.999906[/C][/ROW]
[ROW][C]9[/C][C]3.20244e-06[/C][C]6.40488e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]10[/C][C]6.94323e-07[/C][C]1.38865e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]11[/C][C]4.0701e-08[/C][C]8.14019e-08[/C][C]1[/C][/ROW]
[ROW][C]12[/C][C]9.73351e-09[/C][C]1.9467e-08[/C][C]1[/C][/ROW]
[ROW][C]13[/C][C]5.65022e-10[/C][C]1.13004e-09[/C][C]1[/C][/ROW]
[ROW][C]14[/C][C]3.34458e-11[/C][C]6.68917e-11[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]1.90707e-12[/C][C]3.81415e-12[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]8.591e-14[/C][C]1.7182e-13[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]6.38825e-15[/C][C]1.27765e-14[/C][C]1[/C][/ROW]
[ROW][C]18[/C][C]4.25844e-16[/C][C]8.51689e-16[/C][C]1[/C][/ROW]
[ROW][C]19[/C][C]2.92021e-17[/C][C]5.84042e-17[/C][C]1[/C][/ROW]
[ROW][C]20[/C][C]2.0108e-18[/C][C]4.0216e-18[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]2.24231e-19[/C][C]4.48462e-19[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]1.7688e-20[/C][C]3.5376e-20[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]1.29471e-21[/C][C]2.58941e-21[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]6.09368e-23[/C][C]1.21874e-22[/C][C]1[/C][/ROW]
[ROW][C]25[/C][C]1.22085e-23[/C][C]2.4417e-23[/C][C]1[/C][/ROW]
[ROW][C]26[/C][C]3.38568e-24[/C][C]6.77136e-24[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]1.38017e-24[/C][C]2.76034e-24[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]2.09998e-25[/C][C]4.19995e-25[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]6.95798e-26[/C][C]1.3916e-25[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]4.56833e-27[/C][C]9.13666e-27[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]4.3801e-28[/C][C]8.76021e-28[/C][C]1[/C][/ROW]
[ROW][C]32[/C][C]3.02115e-29[/C][C]6.04229e-29[/C][C]1[/C][/ROW]
[ROW][C]33[/C][C]7.60973e-30[/C][C]1.52195e-29[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]6.18253e-31[/C][C]1.23651e-30[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]3.55927e-32[/C][C]7.11853e-32[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]2.32687e-33[/C][C]4.65375e-33[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]1.67185e-34[/C][C]3.34369e-34[/C][C]1[/C][/ROW]
[ROW][C]38[/C][C]9.86412e-36[/C][C]1.97282e-35[/C][C]1[/C][/ROW]
[ROW][C]39[/C][C]7.91558e-37[/C][C]1.58312e-36[/C][C]1[/C][/ROW]
[ROW][C]40[/C][C]5.61944e-38[/C][C]1.12389e-37[/C][C]1[/C][/ROW]
[ROW][C]41[/C][C]3.83896e-39[/C][C]7.67791e-39[/C][C]1[/C][/ROW]
[ROW][C]42[/C][C]4.04784e-40[/C][C]8.09569e-40[/C][C]1[/C][/ROW]
[ROW][C]43[/C][C]2.89338e-41[/C][C]5.78677e-41[/C][C]1[/C][/ROW]
[ROW][C]44[/C][C]6.69741e-42[/C][C]1.33948e-41[/C][C]1[/C][/ROW]
[ROW][C]45[/C][C]4.59013e-43[/C][C]9.18026e-43[/C][C]1[/C][/ROW]
[ROW][C]46[/C][C]6.27703e-44[/C][C]1.25541e-43[/C][C]1[/C][/ROW]
[ROW][C]47[/C][C]1.03441e-44[/C][C]2.06883e-44[/C][C]1[/C][/ROW]
[ROW][C]48[/C][C]6.17088e-46[/C][C]1.23418e-45[/C][C]1[/C][/ROW]
[ROW][C]49[/C][C]3.44116e-47[/C][C]6.88231e-47[/C][C]1[/C][/ROW]
[ROW][C]50[/C][C]1.86623e-48[/C][C]3.73247e-48[/C][C]1[/C][/ROW]
[ROW][C]51[/C][C]1.24062e-49[/C][C]2.48123e-49[/C][C]1[/C][/ROW]
[ROW][C]52[/C][C]6.86542e-51[/C][C]1.37308e-50[/C][C]1[/C][/ROW]
[ROW][C]53[/C][C]4.15574e-51[/C][C]8.31149e-51[/C][C]1[/C][/ROW]
[ROW][C]54[/C][C]4.42576e-52[/C][C]8.85153e-52[/C][C]1[/C][/ROW]
[ROW][C]55[/C][C]3.37721e-53[/C][C]6.75443e-53[/C][C]1[/C][/ROW]
[ROW][C]56[/C][C]3.97224e-54[/C][C]7.94448e-54[/C][C]1[/C][/ROW]
[ROW][C]57[/C][C]4.18571e-55[/C][C]8.37141e-55[/C][C]1[/C][/ROW]
[ROW][C]58[/C][C]2.91124e-56[/C][C]5.82248e-56[/C][C]1[/C][/ROW]
[ROW][C]59[/C][C]2.99741e-57[/C][C]5.99481e-57[/C][C]1[/C][/ROW]
[ROW][C]60[/C][C]3.05248e-58[/C][C]6.10497e-58[/C][C]1[/C][/ROW]
[ROW][C]61[/C][C]2.60779e-59[/C][C]5.21558e-59[/C][C]1[/C][/ROW]
[ROW][C]62[/C][C]2.91944e-60[/C][C]5.83889e-60[/C][C]1[/C][/ROW]
[ROW][C]63[/C][C]1.97982e-61[/C][C]3.95965e-61[/C][C]1[/C][/ROW]
[ROW][C]64[/C][C]7.84422e-62[/C][C]1.56884e-61[/C][C]1[/C][/ROW]
[ROW][C]65[/C][C]1.57733e-62[/C][C]3.15465e-62[/C][C]1[/C][/ROW]
[ROW][C]66[/C][C]9.71229e-64[/C][C]1.94246e-63[/C][C]1[/C][/ROW]
[ROW][C]67[/C][C]1.33421e-64[/C][C]2.66842e-64[/C][C]1[/C][/ROW]
[ROW][C]68[/C][C]7.96291e-64[/C][C]1.59258e-63[/C][C]1[/C][/ROW]
[ROW][C]69[/C][C]3.18153e-64[/C][C]6.36305e-64[/C][C]1[/C][/ROW]
[ROW][C]70[/C][C]2.17755e-65[/C][C]4.3551e-65[/C][C]1[/C][/ROW]
[ROW][C]71[/C][C]1.55377e-65[/C][C]3.10754e-65[/C][C]1[/C][/ROW]
[ROW][C]72[/C][C]2.33655e-66[/C][C]4.6731e-66[/C][C]1[/C][/ROW]
[ROW][C]73[/C][C]1.58564e-67[/C][C]3.17127e-67[/C][C]1[/C][/ROW]
[ROW][C]74[/C][C]3.07207e-68[/C][C]6.14413e-68[/C][C]1[/C][/ROW]
[ROW][C]75[/C][C]6.42049e-69[/C][C]1.2841e-68[/C][C]1[/C][/ROW]
[ROW][C]76[/C][C]3.17517e-69[/C][C]6.35033e-69[/C][C]1[/C][/ROW]
[ROW][C]77[/C][C]2.40646e-70[/C][C]4.81293e-70[/C][C]1[/C][/ROW]
[ROW][C]78[/C][C]6.15073e-70[/C][C]1.23015e-69[/C][C]1[/C][/ROW]
[ROW][C]79[/C][C]1.46448e-70[/C][C]2.92896e-70[/C][C]1[/C][/ROW]
[ROW][C]80[/C][C]1.63504e-71[/C][C]3.27009e-71[/C][C]1[/C][/ROW]
[ROW][C]81[/C][C]2.01484e-72[/C][C]4.02967e-72[/C][C]1[/C][/ROW]
[ROW][C]82[/C][C]3.06652e-73[/C][C]6.13304e-73[/C][C]1[/C][/ROW]
[ROW][C]83[/C][C]3.01676e-74[/C][C]6.03352e-74[/C][C]1[/C][/ROW]
[ROW][C]84[/C][C]2.88734e-75[/C][C]5.77467e-75[/C][C]1[/C][/ROW]
[ROW][C]85[/C][C]7.0044e-76[/C][C]1.40088e-75[/C][C]1[/C][/ROW]
[ROW][C]86[/C][C]1.08254e-76[/C][C]2.16508e-76[/C][C]1[/C][/ROW]
[ROW][C]87[/C][C]3.87842e-77[/C][C]7.75684e-77[/C][C]1[/C][/ROW]
[ROW][C]88[/C][C]5.14188e-78[/C][C]1.02838e-77[/C][C]1[/C][/ROW]
[ROW][C]89[/C][C]4.77028e-79[/C][C]9.54056e-79[/C][C]1[/C][/ROW]
[ROW][C]90[/C][C]2.17665e-79[/C][C]4.35331e-79[/C][C]1[/C][/ROW]
[ROW][C]91[/C][C]2.86384e-80[/C][C]5.72769e-80[/C][C]1[/C][/ROW]
[ROW][C]92[/C][C]1.7768e-80[/C][C]3.5536e-80[/C][C]1[/C][/ROW]
[ROW][C]93[/C][C]2.21953e-79[/C][C]4.43906e-79[/C][C]1[/C][/ROW]
[ROW][C]94[/C][C]3.91004e-80[/C][C]7.82007e-80[/C][C]1[/C][/ROW]
[ROW][C]95[/C][C]1.134e-80[/C][C]2.268e-80[/C][C]1[/C][/ROW]
[ROW][C]96[/C][C]8.18834e-81[/C][C]1.63767e-80[/C][C]1[/C][/ROW]
[ROW][C]97[/C][C]1.02089e-80[/C][C]2.04177e-80[/C][C]1[/C][/ROW]
[ROW][C]98[/C][C]2.95102e-81[/C][C]5.90203e-81[/C][C]1[/C][/ROW]
[ROW][C]99[/C][C]1.21031e-81[/C][C]2.42062e-81[/C][C]1[/C][/ROW]
[ROW][C]100[/C][C]2.31734e-82[/C][C]4.63467e-82[/C][C]1[/C][/ROW]
[ROW][C]101[/C][C]2.68015e-83[/C][C]5.36031e-83[/C][C]1[/C][/ROW]
[ROW][C]102[/C][C]6.15636e-84[/C][C]1.23127e-83[/C][C]1[/C][/ROW]
[ROW][C]103[/C][C]1.70477e-84[/C][C]3.40955e-84[/C][C]1[/C][/ROW]
[ROW][C]104[/C][C]2.7488e-84[/C][C]5.4976e-84[/C][C]1[/C][/ROW]
[ROW][C]105[/C][C]8.74977e-85[/C][C]1.74995e-84[/C][C]1[/C][/ROW]
[ROW][C]106[/C][C]9.49912e-86[/C][C]1.89982e-85[/C][C]1[/C][/ROW]
[ROW][C]107[/C][C]1.93077e-86[/C][C]3.86155e-86[/C][C]1[/C][/ROW]
[ROW][C]108[/C][C]9.69336e-87[/C][C]1.93867e-86[/C][C]1[/C][/ROW]
[ROW][C]109[/C][C]5.33887e-87[/C][C]1.06777e-86[/C][C]1[/C][/ROW]
[ROW][C]110[/C][C]2.02539e-87[/C][C]4.05078e-87[/C][C]1[/C][/ROW]
[ROW][C]111[/C][C]7.87585e-87[/C][C]1.57517e-86[/C][C]1[/C][/ROW]
[ROW][C]112[/C][C]9.13729e-87[/C][C]1.82746e-86[/C][C]1[/C][/ROW]
[ROW][C]113[/C][C]1.07637e-37[/C][C]2.15274e-37[/C][C]1[/C][/ROW]
[ROW][C]114[/C][C]1.09248e-28[/C][C]2.18496e-28[/C][C]1[/C][/ROW]
[ROW][C]115[/C][C]1.60466e-08[/C][C]3.20932e-08[/C][C]1[/C][/ROW]
[ROW][C]116[/C][C]0.000560594[/C][C]0.00112119[/C][C]0.999439[/C][/ROW]
[ROW][C]117[/C][C]0.000837779[/C][C]0.00167556[/C][C]0.999162[/C][/ROW]
[ROW][C]118[/C][C]0.000786498[/C][C]0.001573[/C][C]0.999214[/C][/ROW]
[ROW][C]119[/C][C]0.00176903[/C][C]0.00353805[/C][C]0.998231[/C][/ROW]
[ROW][C]120[/C][C]0.00478489[/C][C]0.00956978[/C][C]0.995215[/C][/ROW]
[ROW][C]121[/C][C]0.00557643[/C][C]0.0111529[/C][C]0.994424[/C][/ROW]
[ROW][C]122[/C][C]0.00490781[/C][C]0.00981562[/C][C]0.995092[/C][/ROW]
[ROW][C]123[/C][C]0.0194484[/C][C]0.0388967[/C][C]0.980552[/C][/ROW]
[ROW][C]124[/C][C]0.0409663[/C][C]0.0819326[/C][C]0.959034[/C][/ROW]
[ROW][C]125[/C][C]0.0386848[/C][C]0.0773696[/C][C]0.961315[/C][/ROW]
[ROW][C]126[/C][C]0.0543497[/C][C]0.108699[/C][C]0.94565[/C][/ROW]
[ROW][C]127[/C][C]0.228689[/C][C]0.457378[/C][C]0.771311[/C][/ROW]
[ROW][C]128[/C][C]0.520859[/C][C]0.958281[/C][C]0.479141[/C][/ROW]
[ROW][C]129[/C][C]0.590269[/C][C]0.819461[/C][C]0.409731[/C][/ROW]
[ROW][C]130[/C][C]0.639617[/C][C]0.720767[/C][C]0.360383[/C][/ROW]
[ROW][C]131[/C][C]0.715746[/C][C]0.568508[/C][C]0.284254[/C][/ROW]
[ROW][C]132[/C][C]0.689636[/C][C]0.620728[/C][C]0.310364[/C][/ROW]
[ROW][C]133[/C][C]0.67968[/C][C]0.64064[/C][C]0.32032[/C][/ROW]
[ROW][C]134[/C][C]0.658197[/C][C]0.683605[/C][C]0.341803[/C][/ROW]
[ROW][C]135[/C][C]0.628605[/C][C]0.742791[/C][C]0.371395[/C][/ROW]
[ROW][C]136[/C][C]0.67108[/C][C]0.657839[/C][C]0.32892[/C][/ROW]
[ROW][C]137[/C][C]0.691883[/C][C]0.616233[/C][C]0.308117[/C][/ROW]
[ROW][C]138[/C][C]0.752524[/C][C]0.494953[/C][C]0.247476[/C][/ROW]
[ROW][C]139[/C][C]0.799789[/C][C]0.400421[/C][C]0.200211[/C][/ROW]
[ROW][C]140[/C][C]0.78949[/C][C]0.421021[/C][C]0.21051[/C][/ROW]
[ROW][C]141[/C][C]0.767799[/C][C]0.464403[/C][C]0.232201[/C][/ROW]
[ROW][C]142[/C][C]0.916877[/C][C]0.166245[/C][C]0.0831225[/C][/ROW]
[ROW][C]143[/C][C]0.955955[/C][C]0.08809[/C][C]0.044045[/C][/ROW]
[ROW][C]144[/C][C]0.980995[/C][C]0.0380103[/C][C]0.0190051[/C][/ROW]
[ROW][C]145[/C][C]0.98922[/C][C]0.021561[/C][C]0.0107805[/C][/ROW]
[ROW][C]146[/C][C]0.995892[/C][C]0.00821695[/C][C]0.00410848[/C][/ROW]
[ROW][C]147[/C][C]0.995376[/C][C]0.00924707[/C][C]0.00462353[/C][/ROW]
[ROW][C]148[/C][C]0.994975[/C][C]0.0100508[/C][C]0.00502542[/C][/ROW]
[ROW][C]149[/C][C]0.996643[/C][C]0.00671463[/C][C]0.00335731[/C][/ROW]
[ROW][C]150[/C][C]0.996905[/C][C]0.00619042[/C][C]0.00309521[/C][/ROW]
[ROW][C]151[/C][C]0.998052[/C][C]0.00389552[/C][C]0.00194776[/C][/ROW]
[ROW][C]152[/C][C]0.997701[/C][C]0.00459707[/C][C]0.00229853[/C][/ROW]
[ROW][C]153[/C][C]0.997829[/C][C]0.00434175[/C][C]0.00217087[/C][/ROW]
[ROW][C]154[/C][C]0.9979[/C][C]0.00420051[/C][C]0.00210025[/C][/ROW]
[ROW][C]155[/C][C]0.997411[/C][C]0.00517783[/C][C]0.00258892[/C][/ROW]
[ROW][C]156[/C][C]0.99732[/C][C]0.00535995[/C][C]0.00267997[/C][/ROW]
[ROW][C]157[/C][C]0.997716[/C][C]0.00456892[/C][C]0.00228446[/C][/ROW]
[ROW][C]158[/C][C]0.997035[/C][C]0.00593017[/C][C]0.00296509[/C][/ROW]
[ROW][C]159[/C][C]0.996361[/C][C]0.00727722[/C][C]0.00363861[/C][/ROW]
[ROW][C]160[/C][C]0.995694[/C][C]0.00861195[/C][C]0.00430598[/C][/ROW]
[ROW][C]161[/C][C]0.996151[/C][C]0.00769815[/C][C]0.00384908[/C][/ROW]
[ROW][C]162[/C][C]0.997881[/C][C]0.00423771[/C][C]0.00211886[/C][/ROW]
[ROW][C]163[/C][C]0.999128[/C][C]0.00174307[/C][C]0.000871535[/C][/ROW]
[ROW][C]164[/C][C]0.999559[/C][C]0.000882734[/C][C]0.000441367[/C][/ROW]
[ROW][C]165[/C][C]0.999618[/C][C]0.000763961[/C][C]0.000381981[/C][/ROW]
[ROW][C]166[/C][C]0.999722[/C][C]0.00055555[/C][C]0.000277775[/C][/ROW]
[ROW][C]167[/C][C]0.99991[/C][C]0.000179787[/C][C]8.98935e-05[/C][/ROW]
[ROW][C]168[/C][C]0.999951[/C][C]9.86455e-05[/C][C]4.93228e-05[/C][/ROW]
[ROW][C]169[/C][C]0.999951[/C][C]9.78692e-05[/C][C]4.89346e-05[/C][/ROW]
[ROW][C]170[/C][C]0.999939[/C][C]0.000122993[/C][C]6.14963e-05[/C][/ROW]
[ROW][C]171[/C][C]0.999936[/C][C]0.00012881[/C][C]6.44048e-05[/C][/ROW]
[ROW][C]172[/C][C]0.999917[/C][C]0.000165452[/C][C]8.27259e-05[/C][/ROW]
[ROW][C]173[/C][C]0.999965[/C][C]6.93358e-05[/C][C]3.46679e-05[/C][/ROW]
[ROW][C]174[/C][C]0.999963[/C][C]7.32934e-05[/C][C]3.66467e-05[/C][/ROW]
[ROW][C]175[/C][C]0.999961[/C][C]7.80925e-05[/C][C]3.90462e-05[/C][/ROW]
[ROW][C]176[/C][C]0.999951[/C][C]9.85338e-05[/C][C]4.92669e-05[/C][/ROW]
[ROW][C]177[/C][C]0.999933[/C][C]0.000133972[/C][C]6.69861e-05[/C][/ROW]
[ROW][C]178[/C][C]0.999915[/C][C]0.000169515[/C][C]8.47574e-05[/C][/ROW]
[ROW][C]179[/C][C]0.999956[/C][C]8.73679e-05[/C][C]4.36839e-05[/C][/ROW]
[ROW][C]180[/C][C]0.999968[/C][C]6.33493e-05[/C][C]3.16746e-05[/C][/ROW]
[ROW][C]181[/C][C]0.999965[/C][C]6.95543e-05[/C][C]3.47772e-05[/C][/ROW]
[ROW][C]182[/C][C]0.999953[/C][C]9.36752e-05[/C][C]4.68376e-05[/C][/ROW]
[ROW][C]183[/C][C]0.999936[/C][C]0.000128378[/C][C]6.41892e-05[/C][/ROW]
[ROW][C]184[/C][C]0.999923[/C][C]0.000154378[/C][C]7.7189e-05[/C][/ROW]
[ROW][C]185[/C][C]0.999964[/C][C]7.14474e-05[/C][C]3.57237e-05[/C][/ROW]
[ROW][C]186[/C][C]0.999951[/C][C]9.82854e-05[/C][C]4.91427e-05[/C][/ROW]
[ROW][C]187[/C][C]0.99994[/C][C]0.000119262[/C][C]5.96308e-05[/C][/ROW]
[ROW][C]188[/C][C]0.999924[/C][C]0.00015173[/C][C]7.58648e-05[/C][/ROW]
[ROW][C]189[/C][C]0.999914[/C][C]0.000172181[/C][C]8.60904e-05[/C][/ROW]
[ROW][C]190[/C][C]0.999956[/C][C]8.76162e-05[/C][C]4.38081e-05[/C][/ROW]
[ROW][C]191[/C][C]0.999974[/C][C]5.29577e-05[/C][C]2.64788e-05[/C][/ROW]
[ROW][C]192[/C][C]0.999969[/C][C]6.16151e-05[/C][C]3.08075e-05[/C][/ROW]
[ROW][C]193[/C][C]0.999956[/C][C]8.84112e-05[/C][C]4.42056e-05[/C][/ROW]
[ROW][C]194[/C][C]0.999939[/C][C]0.000122406[/C][C]6.12028e-05[/C][/ROW]
[ROW][C]195[/C][C]0.999909[/C][C]0.000182704[/C][C]9.1352e-05[/C][/ROW]
[ROW][C]196[/C][C]0.999885[/C][C]0.000229014[/C][C]0.000114507[/C][/ROW]
[ROW][C]197[/C][C]0.999844[/C][C]0.000311418[/C][C]0.000155709[/C][/ROW]
[ROW][C]198[/C][C]0.999823[/C][C]0.000353012[/C][C]0.000176506[/C][/ROW]
[ROW][C]199[/C][C]0.999742[/C][C]0.0005167[/C][C]0.00025835[/C][/ROW]
[ROW][C]200[/C][C]0.999667[/C][C]0.000666478[/C][C]0.000333239[/C][/ROW]
[ROW][C]201[/C][C]0.999998[/C][C]3.65582e-06[/C][C]1.82791e-06[/C][/ROW]
[ROW][C]202[/C][C]0.999998[/C][C]4.65799e-06[/C][C]2.32899e-06[/C][/ROW]
[ROW][C]203[/C][C]0.999998[/C][C]3.44423e-06[/C][C]1.72211e-06[/C][/ROW]
[ROW][C]204[/C][C]0.999997[/C][C]5.65617e-06[/C][C]2.82809e-06[/C][/ROW]
[ROW][C]205[/C][C]1[/C][C]7.12955e-07[/C][C]3.56478e-07[/C][/ROW]
[ROW][C]206[/C][C]1[/C][C]7.38972e-07[/C][C]3.69486e-07[/C][/ROW]
[ROW][C]207[/C][C]1[/C][C]7.82001e-07[/C][C]3.91e-07[/C][/ROW]
[ROW][C]208[/C][C]1[/C][C]9.13836e-07[/C][C]4.56918e-07[/C][/ROW]
[ROW][C]209[/C][C]1[/C][C]6.27915e-07[/C][C]3.13958e-07[/C][/ROW]
[ROW][C]210[/C][C]1[/C][C]7.56925e-07[/C][C]3.78462e-07[/C][/ROW]
[ROW][C]211[/C][C]0.999999[/C][C]1.31814e-06[/C][C]6.59071e-07[/C][/ROW]
[ROW][C]212[/C][C]0.999999[/C][C]1.5329e-06[/C][C]7.66448e-07[/C][/ROW]
[ROW][C]213[/C][C]0.999999[/C][C]2.44744e-06[/C][C]1.22372e-06[/C][/ROW]
[ROW][C]214[/C][C]0.999998[/C][C]3.32459e-06[/C][C]1.66229e-06[/C][/ROW]
[ROW][C]215[/C][C]0.999997[/C][C]5.41942e-06[/C][C]2.70971e-06[/C][/ROW]
[ROW][C]216[/C][C]0.999997[/C][C]6.73645e-06[/C][C]3.36823e-06[/C][/ROW]
[ROW][C]217[/C][C]0.999998[/C][C]4.96911e-06[/C][C]2.48456e-06[/C][/ROW]
[ROW][C]218[/C][C]0.999999[/C][C]2.39204e-06[/C][C]1.19602e-06[/C][/ROW]
[ROW][C]219[/C][C]0.999999[/C][C]2.19175e-06[/C][C]1.09588e-06[/C][/ROW]
[ROW][C]220[/C][C]0.999998[/C][C]3.88873e-06[/C][C]1.94437e-06[/C][/ROW]
[ROW][C]221[/C][C]0.999997[/C][C]5.35883e-06[/C][C]2.67941e-06[/C][/ROW]
[ROW][C]222[/C][C]0.999997[/C][C]6.34855e-06[/C][C]3.17428e-06[/C][/ROW]
[ROW][C]223[/C][C]0.999995[/C][C]9.80087e-06[/C][C]4.90043e-06[/C][/ROW]
[ROW][C]224[/C][C]0.999998[/C][C]3.2429e-06[/C][C]1.62145e-06[/C][/ROW]
[ROW][C]225[/C][C]0.999998[/C][C]3.35562e-06[/C][C]1.67781e-06[/C][/ROW]
[ROW][C]226[/C][C]0.999999[/C][C]2.91872e-06[/C][C]1.45936e-06[/C][/ROW]
[ROW][C]227[/C][C]0.999999[/C][C]2.03426e-06[/C][C]1.01713e-06[/C][/ROW]
[ROW][C]228[/C][C]0.999998[/C][C]3.19117e-06[/C][C]1.59558e-06[/C][/ROW]
[ROW][C]229[/C][C]0.999998[/C][C]4.56198e-06[/C][C]2.28099e-06[/C][/ROW]
[ROW][C]230[/C][C]0.999996[/C][C]7.33146e-06[/C][C]3.66573e-06[/C][/ROW]
[ROW][C]231[/C][C]0.999995[/C][C]9.40772e-06[/C][C]4.70386e-06[/C][/ROW]
[ROW][C]232[/C][C]0.999993[/C][C]1.38533e-05[/C][C]6.92663e-06[/C][/ROW]
[ROW][C]233[/C][C]0.99999[/C][C]2.08828e-05[/C][C]1.04414e-05[/C][/ROW]
[ROW][C]234[/C][C]0.999989[/C][C]2.2178e-05[/C][C]1.1089e-05[/C][/ROW]
[ROW][C]235[/C][C]0.99999[/C][C]2.0655e-05[/C][C]1.03275e-05[/C][/ROW]
[ROW][C]236[/C][C]0.999988[/C][C]2.49097e-05[/C][C]1.24549e-05[/C][/ROW]
[ROW][C]237[/C][C]0.999983[/C][C]3.36204e-05[/C][C]1.68102e-05[/C][/ROW]
[ROW][C]238[/C][C]0.999976[/C][C]4.81483e-05[/C][C]2.40741e-05[/C][/ROW]
[ROW][C]239[/C][C]0.999963[/C][C]7.36125e-05[/C][C]3.68062e-05[/C][/ROW]
[ROW][C]240[/C][C]0.999943[/C][C]0.000113196[/C][C]5.65978e-05[/C][/ROW]
[ROW][C]241[/C][C]0.9999[/C][C]0.000200213[/C][C]0.000100107[/C][/ROW]
[ROW][C]242[/C][C]0.99988[/C][C]0.000239037[/C][C]0.000119519[/C][/ROW]
[ROW][C]243[/C][C]0.999857[/C][C]0.000286362[/C][C]0.000143181[/C][/ROW]
[ROW][C]244[/C][C]0.999779[/C][C]0.000441722[/C][C]0.000220861[/C][/ROW]
[ROW][C]245[/C][C]0.999653[/C][C]0.000694348[/C][C]0.000347174[/C][/ROW]
[ROW][C]246[/C][C]0.999377[/C][C]0.00124506[/C][C]0.000622528[/C][/ROW]
[ROW][C]247[/C][C]0.999447[/C][C]0.00110575[/C][C]0.000552876[/C][/ROW]
[ROW][C]248[/C][C]0.99904[/C][C]0.00191944[/C][C]0.00095972[/C][/ROW]
[ROW][C]249[/C][C]0.999544[/C][C]0.000911884[/C][C]0.000455942[/C][/ROW]
[ROW][C]250[/C][C]0.999735[/C][C]0.000529104[/C][C]0.000264552[/C][/ROW]
[ROW][C]251[/C][C]0.999722[/C][C]0.000555373[/C][C]0.000277686[/C][/ROW]
[ROW][C]252[/C][C]0.999503[/C][C]0.000993383[/C][C]0.000496692[/C][/ROW]
[ROW][C]253[/C][C]0.999556[/C][C]0.000888461[/C][C]0.00044423[/C][/ROW]
[ROW][C]254[/C][C]0.999376[/C][C]0.00124863[/C][C]0.000624315[/C][/ROW]
[ROW][C]255[/C][C]0.999128[/C][C]0.00174443[/C][C]0.000872215[/C][/ROW]
[ROW][C]256[/C][C]0.998296[/C][C]0.00340885[/C][C]0.00170443[/C][/ROW]
[ROW][C]257[/C][C]0.997703[/C][C]0.00459431[/C][C]0.00229715[/C][/ROW]
[ROW][C]258[/C][C]0.997317[/C][C]0.00536607[/C][C]0.00268304[/C][/ROW]
[ROW][C]259[/C][C]0.996459[/C][C]0.00708108[/C][C]0.00354054[/C][/ROW]
[ROW][C]260[/C][C]0.995758[/C][C]0.00848478[/C][C]0.00424239[/C][/ROW]
[ROW][C]261[/C][C]0.991966[/C][C]0.0160686[/C][C]0.00803432[/C][/ROW]
[ROW][C]262[/C][C]0.988317[/C][C]0.0233666[/C][C]0.0116833[/C][/ROW]
[ROW][C]263[/C][C]0.994237[/C][C]0.0115262[/C][C]0.00576311[/C][/ROW]
[ROW][C]264[/C][C]0.991011[/C][C]0.0179787[/C][C]0.00898937[/C][/ROW]
[ROW][C]265[/C][C]0.986408[/C][C]0.0271846[/C][C]0.0135923[/C][/ROW]
[ROW][C]266[/C][C]0.987417[/C][C]0.0251655[/C][C]0.0125828[/C][/ROW]
[ROW][C]267[/C][C]0.96958[/C][C]0.0608391[/C][C]0.0304195[/C][/ROW]
[ROW][C]268[/C][C]0.932742[/C][C]0.134516[/C][C]0.0672581[/C][/ROW]
[ROW][C]269[/C][C]0.869178[/C][C]0.261645[/C][C]0.130822[/C][/ROW]
[ROW][C]270[/C][C]0.862508[/C][C]0.274985[/C][C]0.137492[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266995&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266995&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
89.42891e-050.0001885780.999906
93.20244e-066.40488e-060.999997
106.94323e-071.38865e-060.999999
114.0701e-088.14019e-081
129.73351e-091.9467e-081
135.65022e-101.13004e-091
143.34458e-116.68917e-111
151.90707e-123.81415e-121
168.591e-141.7182e-131
176.38825e-151.27765e-141
184.25844e-168.51689e-161
192.92021e-175.84042e-171
202.0108e-184.0216e-181
212.24231e-194.48462e-191
221.7688e-203.5376e-201
231.29471e-212.58941e-211
246.09368e-231.21874e-221
251.22085e-232.4417e-231
263.38568e-246.77136e-241
271.38017e-242.76034e-241
282.09998e-254.19995e-251
296.95798e-261.3916e-251
304.56833e-279.13666e-271
314.3801e-288.76021e-281
323.02115e-296.04229e-291
337.60973e-301.52195e-291
346.18253e-311.23651e-301
353.55927e-327.11853e-321
362.32687e-334.65375e-331
371.67185e-343.34369e-341
389.86412e-361.97282e-351
397.91558e-371.58312e-361
405.61944e-381.12389e-371
413.83896e-397.67791e-391
424.04784e-408.09569e-401
432.89338e-415.78677e-411
446.69741e-421.33948e-411
454.59013e-439.18026e-431
466.27703e-441.25541e-431
471.03441e-442.06883e-441
486.17088e-461.23418e-451
493.44116e-476.88231e-471
501.86623e-483.73247e-481
511.24062e-492.48123e-491
526.86542e-511.37308e-501
534.15574e-518.31149e-511
544.42576e-528.85153e-521
553.37721e-536.75443e-531
563.97224e-547.94448e-541
574.18571e-558.37141e-551
582.91124e-565.82248e-561
592.99741e-575.99481e-571
603.05248e-586.10497e-581
612.60779e-595.21558e-591
622.91944e-605.83889e-601
631.97982e-613.95965e-611
647.84422e-621.56884e-611
651.57733e-623.15465e-621
669.71229e-641.94246e-631
671.33421e-642.66842e-641
687.96291e-641.59258e-631
693.18153e-646.36305e-641
702.17755e-654.3551e-651
711.55377e-653.10754e-651
722.33655e-664.6731e-661
731.58564e-673.17127e-671
743.07207e-686.14413e-681
756.42049e-691.2841e-681
763.17517e-696.35033e-691
772.40646e-704.81293e-701
786.15073e-701.23015e-691
791.46448e-702.92896e-701
801.63504e-713.27009e-711
812.01484e-724.02967e-721
823.06652e-736.13304e-731
833.01676e-746.03352e-741
842.88734e-755.77467e-751
857.0044e-761.40088e-751
861.08254e-762.16508e-761
873.87842e-777.75684e-771
885.14188e-781.02838e-771
894.77028e-799.54056e-791
902.17665e-794.35331e-791
912.86384e-805.72769e-801
921.7768e-803.5536e-801
932.21953e-794.43906e-791
943.91004e-807.82007e-801
951.134e-802.268e-801
968.18834e-811.63767e-801
971.02089e-802.04177e-801
982.95102e-815.90203e-811
991.21031e-812.42062e-811
1002.31734e-824.63467e-821
1012.68015e-835.36031e-831
1026.15636e-841.23127e-831
1031.70477e-843.40955e-841
1042.7488e-845.4976e-841
1058.74977e-851.74995e-841
1069.49912e-861.89982e-851
1071.93077e-863.86155e-861
1089.69336e-871.93867e-861
1095.33887e-871.06777e-861
1102.02539e-874.05078e-871
1117.87585e-871.57517e-861
1129.13729e-871.82746e-861
1131.07637e-372.15274e-371
1141.09248e-282.18496e-281
1151.60466e-083.20932e-081
1160.0005605940.001121190.999439
1170.0008377790.001675560.999162
1180.0007864980.0015730.999214
1190.001769030.003538050.998231
1200.004784890.009569780.995215
1210.005576430.01115290.994424
1220.004907810.009815620.995092
1230.01944840.03889670.980552
1240.04096630.08193260.959034
1250.03868480.07736960.961315
1260.05434970.1086990.94565
1270.2286890.4573780.771311
1280.5208590.9582810.479141
1290.5902690.8194610.409731
1300.6396170.7207670.360383
1310.7157460.5685080.284254
1320.6896360.6207280.310364
1330.679680.640640.32032
1340.6581970.6836050.341803
1350.6286050.7427910.371395
1360.671080.6578390.32892
1370.6918830.6162330.308117
1380.7525240.4949530.247476
1390.7997890.4004210.200211
1400.789490.4210210.21051
1410.7677990.4644030.232201
1420.9168770.1662450.0831225
1430.9559550.088090.044045
1440.9809950.03801030.0190051
1450.989220.0215610.0107805
1460.9958920.008216950.00410848
1470.9953760.009247070.00462353
1480.9949750.01005080.00502542
1490.9966430.006714630.00335731
1500.9969050.006190420.00309521
1510.9980520.003895520.00194776
1520.9977010.004597070.00229853
1530.9978290.004341750.00217087
1540.99790.004200510.00210025
1550.9974110.005177830.00258892
1560.997320.005359950.00267997
1570.9977160.004568920.00228446
1580.9970350.005930170.00296509
1590.9963610.007277220.00363861
1600.9956940.008611950.00430598
1610.9961510.007698150.00384908
1620.9978810.004237710.00211886
1630.9991280.001743070.000871535
1640.9995590.0008827340.000441367
1650.9996180.0007639610.000381981
1660.9997220.000555550.000277775
1670.999910.0001797878.98935e-05
1680.9999519.86455e-054.93228e-05
1690.9999519.78692e-054.89346e-05
1700.9999390.0001229936.14963e-05
1710.9999360.000128816.44048e-05
1720.9999170.0001654528.27259e-05
1730.9999656.93358e-053.46679e-05
1740.9999637.32934e-053.66467e-05
1750.9999617.80925e-053.90462e-05
1760.9999519.85338e-054.92669e-05
1770.9999330.0001339726.69861e-05
1780.9999150.0001695158.47574e-05
1790.9999568.73679e-054.36839e-05
1800.9999686.33493e-053.16746e-05
1810.9999656.95543e-053.47772e-05
1820.9999539.36752e-054.68376e-05
1830.9999360.0001283786.41892e-05
1840.9999230.0001543787.7189e-05
1850.9999647.14474e-053.57237e-05
1860.9999519.82854e-054.91427e-05
1870.999940.0001192625.96308e-05
1880.9999240.000151737.58648e-05
1890.9999140.0001721818.60904e-05
1900.9999568.76162e-054.38081e-05
1910.9999745.29577e-052.64788e-05
1920.9999696.16151e-053.08075e-05
1930.9999568.84112e-054.42056e-05
1940.9999390.0001224066.12028e-05
1950.9999090.0001827049.1352e-05
1960.9998850.0002290140.000114507
1970.9998440.0003114180.000155709
1980.9998230.0003530120.000176506
1990.9997420.00051670.00025835
2000.9996670.0006664780.000333239
2010.9999983.65582e-061.82791e-06
2020.9999984.65799e-062.32899e-06
2030.9999983.44423e-061.72211e-06
2040.9999975.65617e-062.82809e-06
20517.12955e-073.56478e-07
20617.38972e-073.69486e-07
20717.82001e-073.91e-07
20819.13836e-074.56918e-07
20916.27915e-073.13958e-07
21017.56925e-073.78462e-07
2110.9999991.31814e-066.59071e-07
2120.9999991.5329e-067.66448e-07
2130.9999992.44744e-061.22372e-06
2140.9999983.32459e-061.66229e-06
2150.9999975.41942e-062.70971e-06
2160.9999976.73645e-063.36823e-06
2170.9999984.96911e-062.48456e-06
2180.9999992.39204e-061.19602e-06
2190.9999992.19175e-061.09588e-06
2200.9999983.88873e-061.94437e-06
2210.9999975.35883e-062.67941e-06
2220.9999976.34855e-063.17428e-06
2230.9999959.80087e-064.90043e-06
2240.9999983.2429e-061.62145e-06
2250.9999983.35562e-061.67781e-06
2260.9999992.91872e-061.45936e-06
2270.9999992.03426e-061.01713e-06
2280.9999983.19117e-061.59558e-06
2290.9999984.56198e-062.28099e-06
2300.9999967.33146e-063.66573e-06
2310.9999959.40772e-064.70386e-06
2320.9999931.38533e-056.92663e-06
2330.999992.08828e-051.04414e-05
2340.9999892.2178e-051.1089e-05
2350.999992.0655e-051.03275e-05
2360.9999882.49097e-051.24549e-05
2370.9999833.36204e-051.68102e-05
2380.9999764.81483e-052.40741e-05
2390.9999637.36125e-053.68062e-05
2400.9999430.0001131965.65978e-05
2410.99990.0002002130.000100107
2420.999880.0002390370.000119519
2430.9998570.0002863620.000143181
2440.9997790.0004417220.000220861
2450.9996530.0006943480.000347174
2460.9993770.001245060.000622528
2470.9994470.001105750.000552876
2480.999040.001919440.00095972
2490.9995440.0009118840.000455942
2500.9997350.0005291040.000264552
2510.9997220.0005553730.000277686
2520.9995030.0009933830.000496692
2530.9995560.0008884610.00044423
2540.9993760.001248630.000624315
2550.9991280.001744430.000872215
2560.9982960.003408850.00170443
2570.9977030.004594310.00229715
2580.9973170.005366070.00268304
2590.9964590.007081080.00354054
2600.9957580.008484780.00424239
2610.9919660.01606860.00803432
2620.9883170.02336660.0116833
2630.9942370.01152620.00576311
2640.9910110.01797870.00898937
2650.9864080.02718460.0135923
2660.9874170.02516550.0125828
2670.969580.06083910.0304195
2680.9327420.1345160.0672581
2690.8691780.2616450.130822
2700.8625080.2749850.137492






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level2280.86692NOK
5% type I error level2390.908745NOK
10% type I error level2430.923954NOK

\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 & 228 & 0.86692 & NOK \tabularnewline
5% type I error level & 239 & 0.908745 & NOK \tabularnewline
10% type I error level & 243 & 0.923954 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266995&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]228[/C][C]0.86692[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]239[/C][C]0.908745[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]243[/C][C]0.923954[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266995&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266995&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 level2280.86692NOK
5% type I error level2390.908745NOK
10% type I error level2430.923954NOK


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')
}