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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 11:19:27 +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/t1418469956lw54rg85k32cnr3.htm/, Retrieved Thu, 16 May 2024 13:34:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266991, Retrieved Thu, 16 May 2024 13:34:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89

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 11:19:27] [56a3e0974002d1c8d48b4dd203e70051] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.5 149 96 18 68
6 139 70 31 39
6.5 148 88 39 32
1 158 114 46 62
1 128 69 31 33
5.5 224 176 67 52
8.5 159 114 35 62
6.5 105 121 52 77
4.5 159 110 77 76
2 167 158 37 41
5 165 116 32 48
0.5 159 181 36 63
5 119 77 38 30
5 176 141 69 78
2.5 54 35 21 19
5 91 80 26 31
5.5 163 152 54 66
3.5 124 97 36 35
3 137 99 42 42
4 121 84 23 45
0.5 153 68 34 21
6.5 148 101 112 25
4.5 221 107 35 44
7.5 188 88 47 69
5.5 149 112 47 54
4 244 171 37 74
7.5 148 137 109 80
7 92 77 24 42
4 150 66 20 61
5.5 153 93 22 41
2.5 94 105 23 46
5.5 156 131 32 39
3.5 132 102 30 34
2.5 161 161 92 51
4.5 105 120 43 42
4.5 97 127 55 31
4.5 151 77 16 39
6 131 108 49 20
2.5 166 85 71 49
5 157 168 43 53
0 111 48 29 31
5 145 152 56 39
6.5 162 75 46 54
5 163 107 19 49
6 59 62 23 34
4.5 187 121 59 46
5.5 109 124 30 55
1 90 72 61 42
7.5 105 40 7 50
6 83 58 38 13
5 116 97 32 37
1 42 88 16 25
5 148 126 19 30
6.5 155 104 22 28
7 125 148 48 45
4.5 116 146 23 35
0 128 80 26 28
8.5 138 97 33 41
3.5 49 25 9 6
7.5 96 99 24 45
3.5 164 118 34 73
6 162 58 48 17
1.5 99 63 18 40
9 202 139 43 64
3.5 186 50 33 37
3.5 66 60 28 25
4 183 152 71 65
6.5 214 142 26 100
7.5 188 94 67 28
6 104 66 34 35
5 177 127 80 56
5.5 126 67 29 29
3.5 76 90 16 43
7.5 99 75 59 59
6.5 139 128 32 50
6.5 162 146 43 59
6.5 108 69 38 27
7 159 186 29 61
3.5 74 81 36 28
1.5 110 85 32 51
4 96 54 35 35
7.5 116 46 21 29
4.5 87 106 29 48
0 97 34 12 25
3.5 127 60 37 44
5.5 106 95 37 64
5 80 57 47 32
4.5 74 62 51 20
2.5 91 36 32 28
7.5 133 56 21 34
7 74 54 13 31
0 114 64 14 26
4.5 140 76 -2 58
3 95 98 20 23
1.5 98 88 24 21
3.5 121 35 11 21
2.5 126 102 23 33
5.5 98 61 24 16
8 95 80 14 20
1 110 49 52 37
5 70 78 15 35
4.5 102 90 23 33
3 86 45 19 27
3 130 55 35 41
8 96 96 24 40
2.5 102 43 39 35
7 100 52 29 28
0 94 60 13 32
1 52 54 8 22
3.5 98 51 18 44
5.5 118 51 24 27
5.5 99 38 19 17
0.5 48 41 23 12
7.5 50 146 16 45
9 150 182 33 37
9.5 154 192 32 37
8.5 109 263 37 108
7 68 35 14 10
8 194 439 52 68
10 158 214 75 72
7 159 341 72 143
8.5 67 58 15 9
9 147 292 29 55
9.5 39 85 13 17
4 100 200 40 37
6 111 158 19 27
8 138 199 24 37
5.5 101 297 121 58
9.5 131 227 93 66
7.5 101 108 36 21
7 114 86 23 19
7.5 165 302 85 78
8 114 148 41 35
7 111 178 46 48
7 75 120 18 27
6 82 207 35 43
10 121 157 17 30
2.5 32 128 4 25
9 150 296 28 69
8 117 323 44 72
6 71 79 10 23
8.5 165 70 38 13
6 154 146 57 61
9 126 246 23 43
8 149 196 36 51
9 145 199 22 67
5.5 120 127 40 36
7 109 153 31 44
5.5 132 299 11 45
9 172 228 38 34
2 169 190 24 36
8.5 114 180 37 72
9 156 212 37 39
8.5 172 269 22 43
9 68 130 15 25
7.5 89 179 2 56
10 167 243 43 80
9 113 190 31 40
7.5 115 299 29 73
6 78 121 45 34
10.5 118 137 25 72
8.5 87 305 4 42
8 173 157 31 61
10 2 96 -4 23
10.5 162 183 66 74
6.5 49 52 61 16
9.5 122 238 32 66
8.5 96 40 31 9
7.5 100 226 39 41
5 82 190 19 57
8 100 214 31 48
10 115 145 36 51
7 141 119 42 53
7.5 165 222 21 29
7.5 165 222 21 29
9.5 110 159 25 55
6 118 165 32 54
10 158 249 26 43
7 146 125 28 51
3 49 122 32 20
6 90 186 41 79
7 121 148 29 39
10 155 274 33 61
7 104 172 17 55
3.5 147 84 13 30
8 110 168 32 55
10 108 102 30 22
5.5 113 106 34 37
6 115 2 59 2
6.5 61 139 13 38
6.5 60 95 23 27
8.5 109 130 10 56
4 68 72 5 25
9.5 111 141 31 39
8 77 113 19 33
8.5 73 206 32 43
5.5 151 268 30 57
7 89 175 25 43
9 78 77 48 23
8 110 125 35 44
10 220 255 67 54
8 65 111 15 28
6 141 132 22 36
8 117 211 18 39
5 122 92 33 16
9 63 76 46 23
4.5 44 171 24 40
8.5 52 83 14 24
9.5 131 266 12 78
8.5 101 186 38 57
7.5 42 50 12 37
7.5 152 117 28 27
5 107 219 41 61
7 77 246 12 27
8 154 279 31 69
5.5 103 148 33 34
8.5 96 137 34 44
9.5 175 181 21 34
7 57 98 20 39
8 112 226 44 51
8.5 143 234 52 34
3.5 49 138 7 31
6.5 110 85 29 13
6.5 131 66 11 12
10.5 167 236 26 51
8.5 56 106 24 24
8 137 135 7 19
10 86 122 60 30
10 121 218 13 81
9.5 149 199 20 42
9 168 112 52 22
10 140 278 28 85
7.5 88 94 25 27
4.5 168 113 39 25
4.5 94 84 9 22
0.5 51 86 19 19
6.5 48 62 13 14
4.5 145 222 60 45
5.5 66 167 19 45
5 85 82 34 28
6 109 207 14 51
4 63 184 17 41
8 102 83 45 31
10.5 162 183 66 74
6.5 86 89 48 19
8 114 225 29 51
8.5 164 237 -2 73
5.5 119 102 51 24
7 126 221 2 61
5 132 128 24 23
3.5 142 91 40 14
5 83 198 20 54
9 94 204 19 51
8.5 81 158 16 62
5 166 138 20 36
9.5 110 226 40 59
3 64 44 27 24
1.5 93 196 25 26
6 104 83 49 54
0.5 105 79 39 39
6.5 49 52 61 16
7.5 88 105 19 36
4.5 95 116 67 31
8 102 83 45 31
9 99 196 30 42
7.5 63 153 8 39
8.5 76 157 19 25
7 109 75 52 31
9.5 117 106 22 38
6.5 57 58 17 31
9.5 120 75 33 17
6 73 74 34 22
8 91 185 22 55
9.5 108 265 30 62
8 105 131 25 51
8 117 139 38 30
9 119 196 26 49
5 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 time8 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266991&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266991&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266991&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.34992 -0.00210667LFM[t] + 0.016826Blogs[t] -0.0027329PRH[t] -0.00179536CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  4.34992 -0.00210667LFM[t] +  0.016826Blogs[t] -0.0027329PRH[t] -0.00179536CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266991&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  4.34992 -0.00210667LFM[t] +  0.016826Blogs[t] -0.0027329PRH[t] -0.00179536CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266991&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266991&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
Ex[t] = + 4.34992 -0.00210667LFM[t] + 0.016826Blogs[t] -0.0027329PRH[t] -0.00179536CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.349920.4567679.5239.46926e-194.73463e-19
LFM-0.002106670.00404478-0.52080.6029030.301451
Blogs0.0168260.002447346.8754.20496e-112.10248e-11
PRH-0.00273290.0079353-0.34440.7308120.365406
CH-0.001795360.00963234-0.18640.8522780.426139

\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) & 4.34992 & 0.456767 & 9.523 & 9.46926e-19 & 4.73463e-19 \tabularnewline
LFM & -0.00210667 & 0.00404478 & -0.5208 & 0.602903 & 0.301451 \tabularnewline
Blogs & 0.016826 & 0.00244734 & 6.875 & 4.20496e-11 & 2.10248e-11 \tabularnewline
PRH & -0.0027329 & 0.0079353 & -0.3444 & 0.730812 & 0.365406 \tabularnewline
CH & -0.00179536 & 0.00963234 & -0.1864 & 0.852278 & 0.426139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266991&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]4.34992[/C][C]0.456767[/C][C]9.523[/C][C]9.46926e-19[/C][C]4.73463e-19[/C][/ROW]
[ROW][C]LFM[/C][C]-0.00210667[/C][C]0.00404478[/C][C]-0.5208[/C][C]0.602903[/C][C]0.301451[/C][/ROW]
[ROW][C]Blogs[/C][C]0.016826[/C][C]0.00244734[/C][C]6.875[/C][C]4.20496e-11[/C][C]2.10248e-11[/C][/ROW]
[ROW][C]PRH[/C][C]-0.0027329[/C][C]0.0079353[/C][C]-0.3444[/C][C]0.730812[/C][C]0.365406[/C][/ROW]
[ROW][C]CH[/C][C]-0.00179536[/C][C]0.00963234[/C][C]-0.1864[/C][C]0.852278[/C][C]0.426139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266991&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266991&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)4.349920.4567679.5239.46926e-194.73463e-19
LFM-0.002106670.00404478-0.52080.6029030.301451
Blogs0.0168260.002447346.8754.20496e-112.10248e-11
PRH-0.00273290.0079353-0.34440.7308120.365406
CH-0.001795360.00963234-0.18640.8522780.426139






Multiple Linear Regression - Regression Statistics
Multiple R0.449052
R-squared0.201647
Adjusted R-squared0.18995
F-TEST (value)17.2385
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value1.27298e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.28034
Sum Squared Residuals1419.59

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.449052 \tabularnewline
R-squared & 0.201647 \tabularnewline
Adjusted R-squared & 0.18995 \tabularnewline
F-TEST (value) & 17.2385 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 273 \tabularnewline
p-value & 1.27298e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.28034 \tabularnewline
Sum Squared Residuals & 1419.59 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266991&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.449052[/C][/ROW]
[ROW][C]R-squared[/C][C]0.201647[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.18995[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]17.2385[/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]1.27298e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.28034[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1419.59[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266991&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266991&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 R0.449052
R-squared0.201647
Adjusted R-squared0.18995
F-TEST (value)17.2385
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value1.27298e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.28034
Sum Squared Residuals1419.59






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.55.480052.01995
265.080180.919822
36.55.354791.14521
415.69821-4.69821
515.0973-4.0973
65.56.56294-1.06294
78.55.726162.77384
86.55.884320.615684
94.55.51894-1.01894
1026.48189-4.48189
1155.78051-0.78051
120.56.84898-6.34898
1355.23712-0.237121
1456.02301-1.02301
152.54.73357-2.23357
1655.37759-0.377586
175.56.29802-0.798019
183.55.5596-2.0596
1935.5369-2.5369
2045.36475-1.36475
210.55.04115-4.54115
226.55.386591.11341
234.55.51008-1.01008
247.55.182232.31777
255.55.69515-0.195147
2646.47917-2.47917
277.55.901781.59822
2875.310721.68928
2944.98026-0.980265
305.55.458690.0413119
312.55.77318-3.27318
325.56.06802-0.568018
333.55.64507-2.14507
342.56.37675-3.87675
354.55.95492-1.45492
364.56.07651-1.57651
374.55.21367-0.713674
3865.721340.278661
392.55.14842-2.64842
4056.63328-1.63328
4104.78882-4.78882
4256.37895-1.37895
436.55.047931.45207
4455.66702-0.667021
4565.144940.855057
464.55.7481-1.2481
475.56.02599-0.525989
4815.12968-4.12968
497.54.692872.80713
5065.023790.976211
5155.58379-0.583791
5215.65352-4.65352
5356.05243-1.05243
546.55.66290.8371
5576.364870.635132
564.56.43645-1.93645
5705.30502-5.30502
588.55.527532.97247
593.54.63198-1.13198
607.55.667081.83292
613.55.76592-2.26592
6264.822851.17715
631.55.0804-3.5804
6496.030772.96923
653.54.64277-1.14277
663.55.09904-1.59904
6746.21122-2.21122
686.56.03780.462203
697.55.302142.19786
7065.085590.91441
7155.79477-0.794774
725.55.080510.419494
733.55.58323-2.08323
747.55.136152.36385
756.56.03360.466396
766.56.24180.258201
776.55.131071.36893
7876.955830.0441715
793.55.40828-1.90828
801.55.36938-3.86938
8144.8978-0.897799
827.54.770092.72991
834.55.78477-1.28477
8404.63998-4.63998
853.54.91182-1.41182
865.55.50907-0.00906667
8754.954570.0454254
884.55.06196-0.561957
892.54.62623-2.12623
907.54.893562.60644
9175.011451.98855
9205.10169-5.10169
934.55.2351-0.735101
9435.70279-2.70279
951.55.52087-4.02087
963.54.61616-1.11616
972.55.67863-3.17863
985.55.075540.424459
9985.42172.5783
10014.73413-3.73413
10155.41105-0.411054
1024.55.52728-1.02728
10334.82552-1.82552
10434.83223-1.83223
10585.625582.37442
1062.54.68914-2.18914
10774.884682.11532
10805.06848-5.06848
10915.08762-4.08762
1103.54.87341-1.37341
1115.54.84540.654601
1125.54.698310.801694
1130.54.85427-4.35427
1147.56.576670.923331
11596.939642.06036
1169.57.102212.39779
1178.58.250520.249481
11874.739372.26063
119811.0636-3.06365
120107.28362.7164
12179.29912-2.29912
1228.55.127533.37247
12398.775440.224563
1249.55.631923.86808
12547.32871-3.32871
12666.67419-0.674192
12787.275560.72444
1285.58.69966-3.19966
1299.57.52081.9792
1307.55.818271.68173
13175.459831.54017
1327.58.71144-1.21144
13386.425131.57487
13476.899220.100779
13576.113380.886623
13667.48731-1.48731
137106.636383.36362
1382.56.38042-3.88042
13998.814020.185981
14089.28873-1.28873
14165.460980.539018
1428.55.052953.44705
14366.2168-0.216801
14498.083620.916378
14587.143980.856021
14697.212421.78758
1475.56.06008-0.560077
14876.530960.469041
1495.58.99196-3.49196
15097.659011.34099
15127.06061-5.06061
1528.56.908061.59194
15397.417261.58274
1548.58.376450.123553
15596.308172.69183
1567.57.068280.431722
157107.825682.17432
15897.152281.84772
1597.58.92832-1.42832
16066.03753-0.037527
16110.56.208914.29109
1628.59.21224-0.712237
16386.432921.56708
164105.930644.06936
16510.56.774573.72543
1666.54.926221.57378
1679.57.891551.60845
1688.54.719853.78015
1697.57.76174-0.26174
17057.21986-2.21986
17187.569120.430876
172106.357483.64252
17375.845241.15476
1747.57.62824-0.128239
1757.57.62824-0.128239
1769.56.626462.87354
17766.69322-0.693225
178108.058491.94151
17975.977521.02248
18036.17611-3.17611
18167.03608-1.03608
18276.435990.564008
183108.434011.56599
18476.87970.120302
1853.55.36424-1.86424
18686.758761.24124
187105.717174.28283
1885.55.73608-0.236079
18963.976482.02352
1906.56.456480.0435203
1916.55.710660.789338
1928.56.179812.32019
19345.35959-1.35959
1949.56.333813.16619
19585.977882.02212
1968.57.497641.00236
1975.58.35686-2.85686
19876.961460.0385426
19995.308733.69127
20086.046791.95321
201107.897032.10297
20285.989412.01059
20366.14916-0.149159
20487.534520.465482
20555.52199-0.521991
20695.328973.67103
2074.56.99707-2.49707
2088.55.555592.94441
2099.58.376831.12317
2108.57.06061.4394
2117.55.003522.49648
2127.55.873361.62664
21357.58784-2.58784
21478.24564-1.24564
21588.51135-0.511351
2165.56.47196-0.971957
2178.56.280932.21907
2189.56.908332.59167
21975.754111.24589
22087.704840.295158
2218.57.78280.717199
2223.56.4939-2.9939
2236.55.445811.05419
2246.55.132861.36714
22510.57.806432.69357
2268.55.906832.59317
22786.279581.72042
228106.003693.99631
229107.582132.41787
2309.57.254342.24566
23195.698913.30109
232108.503491.49651
2337.55.629381.87062
2344.55.74587-1.24587
2354.55.50119-1.00119
2360.55.60348-5.10348
2376.55.231351.26865
2384.57.53506-3.03506
2395.56.88811-1.38811
24055.4074-0.4074
24167.47346-1.47346
24247.19312-3.19312
24385.352972.64703
24410.56.774573.72543
2456.55.500970.999027
24687.72480.275204
2478.57.86660.633403
2485.55.63302-0.133016
24977.68805-0.688047
25056.11869-1.11869
2513.55.44749-1.94749
25257.35501-2.35501
25397.440911.55909
2548.56.682751.81725
25556.20291-1.20291
2569.57.705621.79438
25734.83856-1.83856
2581.57.3369-5.8369
25965.296530.703473
2600.55.28138-4.78138
2616.54.926221.57378
2627.55.814711.68529
2634.55.86285-1.36285
26485.352972.64703
26597.281871.71813
2667.56.69970.800301
2678.56.734691.76531
26875.184481.81552
2699.55.758653.74135
2706.55.103641.39636
2719.55.238374.26163
27265.308840.691155
27387.112160.887842
2749.58.387991.11201
27586.173041.82696
27686.284551.71545
27797.23811.7619
27855.53279-0.532792

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 5.48005 & 2.01995 \tabularnewline
2 & 6 & 5.08018 & 0.919822 \tabularnewline
3 & 6.5 & 5.35479 & 1.14521 \tabularnewline
4 & 1 & 5.69821 & -4.69821 \tabularnewline
5 & 1 & 5.0973 & -4.0973 \tabularnewline
6 & 5.5 & 6.56294 & -1.06294 \tabularnewline
7 & 8.5 & 5.72616 & 2.77384 \tabularnewline
8 & 6.5 & 5.88432 & 0.615684 \tabularnewline
9 & 4.5 & 5.51894 & -1.01894 \tabularnewline
10 & 2 & 6.48189 & -4.48189 \tabularnewline
11 & 5 & 5.78051 & -0.78051 \tabularnewline
12 & 0.5 & 6.84898 & -6.34898 \tabularnewline
13 & 5 & 5.23712 & -0.237121 \tabularnewline
14 & 5 & 6.02301 & -1.02301 \tabularnewline
15 & 2.5 & 4.73357 & -2.23357 \tabularnewline
16 & 5 & 5.37759 & -0.377586 \tabularnewline
17 & 5.5 & 6.29802 & -0.798019 \tabularnewline
18 & 3.5 & 5.5596 & -2.0596 \tabularnewline
19 & 3 & 5.5369 & -2.5369 \tabularnewline
20 & 4 & 5.36475 & -1.36475 \tabularnewline
21 & 0.5 & 5.04115 & -4.54115 \tabularnewline
22 & 6.5 & 5.38659 & 1.11341 \tabularnewline
23 & 4.5 & 5.51008 & -1.01008 \tabularnewline
24 & 7.5 & 5.18223 & 2.31777 \tabularnewline
25 & 5.5 & 5.69515 & -0.195147 \tabularnewline
26 & 4 & 6.47917 & -2.47917 \tabularnewline
27 & 7.5 & 5.90178 & 1.59822 \tabularnewline
28 & 7 & 5.31072 & 1.68928 \tabularnewline
29 & 4 & 4.98026 & -0.980265 \tabularnewline
30 & 5.5 & 5.45869 & 0.0413119 \tabularnewline
31 & 2.5 & 5.77318 & -3.27318 \tabularnewline
32 & 5.5 & 6.06802 & -0.568018 \tabularnewline
33 & 3.5 & 5.64507 & -2.14507 \tabularnewline
34 & 2.5 & 6.37675 & -3.87675 \tabularnewline
35 & 4.5 & 5.95492 & -1.45492 \tabularnewline
36 & 4.5 & 6.07651 & -1.57651 \tabularnewline
37 & 4.5 & 5.21367 & -0.713674 \tabularnewline
38 & 6 & 5.72134 & 0.278661 \tabularnewline
39 & 2.5 & 5.14842 & -2.64842 \tabularnewline
40 & 5 & 6.63328 & -1.63328 \tabularnewline
41 & 0 & 4.78882 & -4.78882 \tabularnewline
42 & 5 & 6.37895 & -1.37895 \tabularnewline
43 & 6.5 & 5.04793 & 1.45207 \tabularnewline
44 & 5 & 5.66702 & -0.667021 \tabularnewline
45 & 6 & 5.14494 & 0.855057 \tabularnewline
46 & 4.5 & 5.7481 & -1.2481 \tabularnewline
47 & 5.5 & 6.02599 & -0.525989 \tabularnewline
48 & 1 & 5.12968 & -4.12968 \tabularnewline
49 & 7.5 & 4.69287 & 2.80713 \tabularnewline
50 & 6 & 5.02379 & 0.976211 \tabularnewline
51 & 5 & 5.58379 & -0.583791 \tabularnewline
52 & 1 & 5.65352 & -4.65352 \tabularnewline
53 & 5 & 6.05243 & -1.05243 \tabularnewline
54 & 6.5 & 5.6629 & 0.8371 \tabularnewline
55 & 7 & 6.36487 & 0.635132 \tabularnewline
56 & 4.5 & 6.43645 & -1.93645 \tabularnewline
57 & 0 & 5.30502 & -5.30502 \tabularnewline
58 & 8.5 & 5.52753 & 2.97247 \tabularnewline
59 & 3.5 & 4.63198 & -1.13198 \tabularnewline
60 & 7.5 & 5.66708 & 1.83292 \tabularnewline
61 & 3.5 & 5.76592 & -2.26592 \tabularnewline
62 & 6 & 4.82285 & 1.17715 \tabularnewline
63 & 1.5 & 5.0804 & -3.5804 \tabularnewline
64 & 9 & 6.03077 & 2.96923 \tabularnewline
65 & 3.5 & 4.64277 & -1.14277 \tabularnewline
66 & 3.5 & 5.09904 & -1.59904 \tabularnewline
67 & 4 & 6.21122 & -2.21122 \tabularnewline
68 & 6.5 & 6.0378 & 0.462203 \tabularnewline
69 & 7.5 & 5.30214 & 2.19786 \tabularnewline
70 & 6 & 5.08559 & 0.91441 \tabularnewline
71 & 5 & 5.79477 & -0.794774 \tabularnewline
72 & 5.5 & 5.08051 & 0.419494 \tabularnewline
73 & 3.5 & 5.58323 & -2.08323 \tabularnewline
74 & 7.5 & 5.13615 & 2.36385 \tabularnewline
75 & 6.5 & 6.0336 & 0.466396 \tabularnewline
76 & 6.5 & 6.2418 & 0.258201 \tabularnewline
77 & 6.5 & 5.13107 & 1.36893 \tabularnewline
78 & 7 & 6.95583 & 0.0441715 \tabularnewline
79 & 3.5 & 5.40828 & -1.90828 \tabularnewline
80 & 1.5 & 5.36938 & -3.86938 \tabularnewline
81 & 4 & 4.8978 & -0.897799 \tabularnewline
82 & 7.5 & 4.77009 & 2.72991 \tabularnewline
83 & 4.5 & 5.78477 & -1.28477 \tabularnewline
84 & 0 & 4.63998 & -4.63998 \tabularnewline
85 & 3.5 & 4.91182 & -1.41182 \tabularnewline
86 & 5.5 & 5.50907 & -0.00906667 \tabularnewline
87 & 5 & 4.95457 & 0.0454254 \tabularnewline
88 & 4.5 & 5.06196 & -0.561957 \tabularnewline
89 & 2.5 & 4.62623 & -2.12623 \tabularnewline
90 & 7.5 & 4.89356 & 2.60644 \tabularnewline
91 & 7 & 5.01145 & 1.98855 \tabularnewline
92 & 0 & 5.10169 & -5.10169 \tabularnewline
93 & 4.5 & 5.2351 & -0.735101 \tabularnewline
94 & 3 & 5.70279 & -2.70279 \tabularnewline
95 & 1.5 & 5.52087 & -4.02087 \tabularnewline
96 & 3.5 & 4.61616 & -1.11616 \tabularnewline
97 & 2.5 & 5.67863 & -3.17863 \tabularnewline
98 & 5.5 & 5.07554 & 0.424459 \tabularnewline
99 & 8 & 5.4217 & 2.5783 \tabularnewline
100 & 1 & 4.73413 & -3.73413 \tabularnewline
101 & 5 & 5.41105 & -0.411054 \tabularnewline
102 & 4.5 & 5.52728 & -1.02728 \tabularnewline
103 & 3 & 4.82552 & -1.82552 \tabularnewline
104 & 3 & 4.83223 & -1.83223 \tabularnewline
105 & 8 & 5.62558 & 2.37442 \tabularnewline
106 & 2.5 & 4.68914 & -2.18914 \tabularnewline
107 & 7 & 4.88468 & 2.11532 \tabularnewline
108 & 0 & 5.06848 & -5.06848 \tabularnewline
109 & 1 & 5.08762 & -4.08762 \tabularnewline
110 & 3.5 & 4.87341 & -1.37341 \tabularnewline
111 & 5.5 & 4.8454 & 0.654601 \tabularnewline
112 & 5.5 & 4.69831 & 0.801694 \tabularnewline
113 & 0.5 & 4.85427 & -4.35427 \tabularnewline
114 & 7.5 & 6.57667 & 0.923331 \tabularnewline
115 & 9 & 6.93964 & 2.06036 \tabularnewline
116 & 9.5 & 7.10221 & 2.39779 \tabularnewline
117 & 8.5 & 8.25052 & 0.249481 \tabularnewline
118 & 7 & 4.73937 & 2.26063 \tabularnewline
119 & 8 & 11.0636 & -3.06365 \tabularnewline
120 & 10 & 7.2836 & 2.7164 \tabularnewline
121 & 7 & 9.29912 & -2.29912 \tabularnewline
122 & 8.5 & 5.12753 & 3.37247 \tabularnewline
123 & 9 & 8.77544 & 0.224563 \tabularnewline
124 & 9.5 & 5.63192 & 3.86808 \tabularnewline
125 & 4 & 7.32871 & -3.32871 \tabularnewline
126 & 6 & 6.67419 & -0.674192 \tabularnewline
127 & 8 & 7.27556 & 0.72444 \tabularnewline
128 & 5.5 & 8.69966 & -3.19966 \tabularnewline
129 & 9.5 & 7.5208 & 1.9792 \tabularnewline
130 & 7.5 & 5.81827 & 1.68173 \tabularnewline
131 & 7 & 5.45983 & 1.54017 \tabularnewline
132 & 7.5 & 8.71144 & -1.21144 \tabularnewline
133 & 8 & 6.42513 & 1.57487 \tabularnewline
134 & 7 & 6.89922 & 0.100779 \tabularnewline
135 & 7 & 6.11338 & 0.886623 \tabularnewline
136 & 6 & 7.48731 & -1.48731 \tabularnewline
137 & 10 & 6.63638 & 3.36362 \tabularnewline
138 & 2.5 & 6.38042 & -3.88042 \tabularnewline
139 & 9 & 8.81402 & 0.185981 \tabularnewline
140 & 8 & 9.28873 & -1.28873 \tabularnewline
141 & 6 & 5.46098 & 0.539018 \tabularnewline
142 & 8.5 & 5.05295 & 3.44705 \tabularnewline
143 & 6 & 6.2168 & -0.216801 \tabularnewline
144 & 9 & 8.08362 & 0.916378 \tabularnewline
145 & 8 & 7.14398 & 0.856021 \tabularnewline
146 & 9 & 7.21242 & 1.78758 \tabularnewline
147 & 5.5 & 6.06008 & -0.560077 \tabularnewline
148 & 7 & 6.53096 & 0.469041 \tabularnewline
149 & 5.5 & 8.99196 & -3.49196 \tabularnewline
150 & 9 & 7.65901 & 1.34099 \tabularnewline
151 & 2 & 7.06061 & -5.06061 \tabularnewline
152 & 8.5 & 6.90806 & 1.59194 \tabularnewline
153 & 9 & 7.41726 & 1.58274 \tabularnewline
154 & 8.5 & 8.37645 & 0.123553 \tabularnewline
155 & 9 & 6.30817 & 2.69183 \tabularnewline
156 & 7.5 & 7.06828 & 0.431722 \tabularnewline
157 & 10 & 7.82568 & 2.17432 \tabularnewline
158 & 9 & 7.15228 & 1.84772 \tabularnewline
159 & 7.5 & 8.92832 & -1.42832 \tabularnewline
160 & 6 & 6.03753 & -0.037527 \tabularnewline
161 & 10.5 & 6.20891 & 4.29109 \tabularnewline
162 & 8.5 & 9.21224 & -0.712237 \tabularnewline
163 & 8 & 6.43292 & 1.56708 \tabularnewline
164 & 10 & 5.93064 & 4.06936 \tabularnewline
165 & 10.5 & 6.77457 & 3.72543 \tabularnewline
166 & 6.5 & 4.92622 & 1.57378 \tabularnewline
167 & 9.5 & 7.89155 & 1.60845 \tabularnewline
168 & 8.5 & 4.71985 & 3.78015 \tabularnewline
169 & 7.5 & 7.76174 & -0.26174 \tabularnewline
170 & 5 & 7.21986 & -2.21986 \tabularnewline
171 & 8 & 7.56912 & 0.430876 \tabularnewline
172 & 10 & 6.35748 & 3.64252 \tabularnewline
173 & 7 & 5.84524 & 1.15476 \tabularnewline
174 & 7.5 & 7.62824 & -0.128239 \tabularnewline
175 & 7.5 & 7.62824 & -0.128239 \tabularnewline
176 & 9.5 & 6.62646 & 2.87354 \tabularnewline
177 & 6 & 6.69322 & -0.693225 \tabularnewline
178 & 10 & 8.05849 & 1.94151 \tabularnewline
179 & 7 & 5.97752 & 1.02248 \tabularnewline
180 & 3 & 6.17611 & -3.17611 \tabularnewline
181 & 6 & 7.03608 & -1.03608 \tabularnewline
182 & 7 & 6.43599 & 0.564008 \tabularnewline
183 & 10 & 8.43401 & 1.56599 \tabularnewline
184 & 7 & 6.8797 & 0.120302 \tabularnewline
185 & 3.5 & 5.36424 & -1.86424 \tabularnewline
186 & 8 & 6.75876 & 1.24124 \tabularnewline
187 & 10 & 5.71717 & 4.28283 \tabularnewline
188 & 5.5 & 5.73608 & -0.236079 \tabularnewline
189 & 6 & 3.97648 & 2.02352 \tabularnewline
190 & 6.5 & 6.45648 & 0.0435203 \tabularnewline
191 & 6.5 & 5.71066 & 0.789338 \tabularnewline
192 & 8.5 & 6.17981 & 2.32019 \tabularnewline
193 & 4 & 5.35959 & -1.35959 \tabularnewline
194 & 9.5 & 6.33381 & 3.16619 \tabularnewline
195 & 8 & 5.97788 & 2.02212 \tabularnewline
196 & 8.5 & 7.49764 & 1.00236 \tabularnewline
197 & 5.5 & 8.35686 & -2.85686 \tabularnewline
198 & 7 & 6.96146 & 0.0385426 \tabularnewline
199 & 9 & 5.30873 & 3.69127 \tabularnewline
200 & 8 & 6.04679 & 1.95321 \tabularnewline
201 & 10 & 7.89703 & 2.10297 \tabularnewline
202 & 8 & 5.98941 & 2.01059 \tabularnewline
203 & 6 & 6.14916 & -0.149159 \tabularnewline
204 & 8 & 7.53452 & 0.465482 \tabularnewline
205 & 5 & 5.52199 & -0.521991 \tabularnewline
206 & 9 & 5.32897 & 3.67103 \tabularnewline
207 & 4.5 & 6.99707 & -2.49707 \tabularnewline
208 & 8.5 & 5.55559 & 2.94441 \tabularnewline
209 & 9.5 & 8.37683 & 1.12317 \tabularnewline
210 & 8.5 & 7.0606 & 1.4394 \tabularnewline
211 & 7.5 & 5.00352 & 2.49648 \tabularnewline
212 & 7.5 & 5.87336 & 1.62664 \tabularnewline
213 & 5 & 7.58784 & -2.58784 \tabularnewline
214 & 7 & 8.24564 & -1.24564 \tabularnewline
215 & 8 & 8.51135 & -0.511351 \tabularnewline
216 & 5.5 & 6.47196 & -0.971957 \tabularnewline
217 & 8.5 & 6.28093 & 2.21907 \tabularnewline
218 & 9.5 & 6.90833 & 2.59167 \tabularnewline
219 & 7 & 5.75411 & 1.24589 \tabularnewline
220 & 8 & 7.70484 & 0.295158 \tabularnewline
221 & 8.5 & 7.7828 & 0.717199 \tabularnewline
222 & 3.5 & 6.4939 & -2.9939 \tabularnewline
223 & 6.5 & 5.44581 & 1.05419 \tabularnewline
224 & 6.5 & 5.13286 & 1.36714 \tabularnewline
225 & 10.5 & 7.80643 & 2.69357 \tabularnewline
226 & 8.5 & 5.90683 & 2.59317 \tabularnewline
227 & 8 & 6.27958 & 1.72042 \tabularnewline
228 & 10 & 6.00369 & 3.99631 \tabularnewline
229 & 10 & 7.58213 & 2.41787 \tabularnewline
230 & 9.5 & 7.25434 & 2.24566 \tabularnewline
231 & 9 & 5.69891 & 3.30109 \tabularnewline
232 & 10 & 8.50349 & 1.49651 \tabularnewline
233 & 7.5 & 5.62938 & 1.87062 \tabularnewline
234 & 4.5 & 5.74587 & -1.24587 \tabularnewline
235 & 4.5 & 5.50119 & -1.00119 \tabularnewline
236 & 0.5 & 5.60348 & -5.10348 \tabularnewline
237 & 6.5 & 5.23135 & 1.26865 \tabularnewline
238 & 4.5 & 7.53506 & -3.03506 \tabularnewline
239 & 5.5 & 6.88811 & -1.38811 \tabularnewline
240 & 5 & 5.4074 & -0.4074 \tabularnewline
241 & 6 & 7.47346 & -1.47346 \tabularnewline
242 & 4 & 7.19312 & -3.19312 \tabularnewline
243 & 8 & 5.35297 & 2.64703 \tabularnewline
244 & 10.5 & 6.77457 & 3.72543 \tabularnewline
245 & 6.5 & 5.50097 & 0.999027 \tabularnewline
246 & 8 & 7.7248 & 0.275204 \tabularnewline
247 & 8.5 & 7.8666 & 0.633403 \tabularnewline
248 & 5.5 & 5.63302 & -0.133016 \tabularnewline
249 & 7 & 7.68805 & -0.688047 \tabularnewline
250 & 5 & 6.11869 & -1.11869 \tabularnewline
251 & 3.5 & 5.44749 & -1.94749 \tabularnewline
252 & 5 & 7.35501 & -2.35501 \tabularnewline
253 & 9 & 7.44091 & 1.55909 \tabularnewline
254 & 8.5 & 6.68275 & 1.81725 \tabularnewline
255 & 5 & 6.20291 & -1.20291 \tabularnewline
256 & 9.5 & 7.70562 & 1.79438 \tabularnewline
257 & 3 & 4.83856 & -1.83856 \tabularnewline
258 & 1.5 & 7.3369 & -5.8369 \tabularnewline
259 & 6 & 5.29653 & 0.703473 \tabularnewline
260 & 0.5 & 5.28138 & -4.78138 \tabularnewline
261 & 6.5 & 4.92622 & 1.57378 \tabularnewline
262 & 7.5 & 5.81471 & 1.68529 \tabularnewline
263 & 4.5 & 5.86285 & -1.36285 \tabularnewline
264 & 8 & 5.35297 & 2.64703 \tabularnewline
265 & 9 & 7.28187 & 1.71813 \tabularnewline
266 & 7.5 & 6.6997 & 0.800301 \tabularnewline
267 & 8.5 & 6.73469 & 1.76531 \tabularnewline
268 & 7 & 5.18448 & 1.81552 \tabularnewline
269 & 9.5 & 5.75865 & 3.74135 \tabularnewline
270 & 6.5 & 5.10364 & 1.39636 \tabularnewline
271 & 9.5 & 5.23837 & 4.26163 \tabularnewline
272 & 6 & 5.30884 & 0.691155 \tabularnewline
273 & 8 & 7.11216 & 0.887842 \tabularnewline
274 & 9.5 & 8.38799 & 1.11201 \tabularnewline
275 & 8 & 6.17304 & 1.82696 \tabularnewline
276 & 8 & 6.28455 & 1.71545 \tabularnewline
277 & 9 & 7.2381 & 1.7619 \tabularnewline
278 & 5 & 5.53279 & -0.532792 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266991&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]7.5[/C][C]5.48005[/C][C]2.01995[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]5.08018[/C][C]0.919822[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]5.35479[/C][C]1.14521[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]5.69821[/C][C]-4.69821[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.0973[/C][C]-4.0973[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]6.56294[/C][C]-1.06294[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]5.72616[/C][C]2.77384[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]5.88432[/C][C]0.615684[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]5.51894[/C][C]-1.01894[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]6.48189[/C][C]-4.48189[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]5.78051[/C][C]-0.78051[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]6.84898[/C][C]-6.34898[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]5.23712[/C][C]-0.237121[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]6.02301[/C][C]-1.02301[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]4.73357[/C][C]-2.23357[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]5.37759[/C][C]-0.377586[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]6.29802[/C][C]-0.798019[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]5.5596[/C][C]-2.0596[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]5.5369[/C][C]-2.5369[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]5.36475[/C][C]-1.36475[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]5.04115[/C][C]-4.54115[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]5.38659[/C][C]1.11341[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]5.51008[/C][C]-1.01008[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]5.18223[/C][C]2.31777[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]5.69515[/C][C]-0.195147[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]6.47917[/C][C]-2.47917[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]5.90178[/C][C]1.59822[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]5.31072[/C][C]1.68928[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]4.98026[/C][C]-0.980265[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]5.45869[/C][C]0.0413119[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]5.77318[/C][C]-3.27318[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]6.06802[/C][C]-0.568018[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]5.64507[/C][C]-2.14507[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]6.37675[/C][C]-3.87675[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]5.95492[/C][C]-1.45492[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]6.07651[/C][C]-1.57651[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.21367[/C][C]-0.713674[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]5.72134[/C][C]0.278661[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]5.14842[/C][C]-2.64842[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]6.63328[/C][C]-1.63328[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]4.78882[/C][C]-4.78882[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.37895[/C][C]-1.37895[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]5.04793[/C][C]1.45207[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]5.66702[/C][C]-0.667021[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]5.14494[/C][C]0.855057[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]5.7481[/C][C]-1.2481[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]6.02599[/C][C]-0.525989[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]5.12968[/C][C]-4.12968[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]4.69287[/C][C]2.80713[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]5.02379[/C][C]0.976211[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]5.58379[/C][C]-0.583791[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]5.65352[/C][C]-4.65352[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]6.05243[/C][C]-1.05243[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]5.6629[/C][C]0.8371[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]6.36487[/C][C]0.635132[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]6.43645[/C][C]-1.93645[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]5.30502[/C][C]-5.30502[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]5.52753[/C][C]2.97247[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]4.63198[/C][C]-1.13198[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]5.66708[/C][C]1.83292[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]5.76592[/C][C]-2.26592[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]4.82285[/C][C]1.17715[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]5.0804[/C][C]-3.5804[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]6.03077[/C][C]2.96923[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]4.64277[/C][C]-1.14277[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]5.09904[/C][C]-1.59904[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]6.21122[/C][C]-2.21122[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]6.0378[/C][C]0.462203[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]5.30214[/C][C]2.19786[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]5.08559[/C][C]0.91441[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]5.79477[/C][C]-0.794774[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]5.08051[/C][C]0.419494[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]5.58323[/C][C]-2.08323[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]5.13615[/C][C]2.36385[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]6.0336[/C][C]0.466396[/C][/ROW]
[ROW][C]76[/C][C]6.5[/C][C]6.2418[/C][C]0.258201[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]5.13107[/C][C]1.36893[/C][/ROW]
[ROW][C]78[/C][C]7[/C][C]6.95583[/C][C]0.0441715[/C][/ROW]
[ROW][C]79[/C][C]3.5[/C][C]5.40828[/C][C]-1.90828[/C][/ROW]
[ROW][C]80[/C][C]1.5[/C][C]5.36938[/C][C]-3.86938[/C][/ROW]
[ROW][C]81[/C][C]4[/C][C]4.8978[/C][C]-0.897799[/C][/ROW]
[ROW][C]82[/C][C]7.5[/C][C]4.77009[/C][C]2.72991[/C][/ROW]
[ROW][C]83[/C][C]4.5[/C][C]5.78477[/C][C]-1.28477[/C][/ROW]
[ROW][C]84[/C][C]0[/C][C]4.63998[/C][C]-4.63998[/C][/ROW]
[ROW][C]85[/C][C]3.5[/C][C]4.91182[/C][C]-1.41182[/C][/ROW]
[ROW][C]86[/C][C]5.5[/C][C]5.50907[/C][C]-0.00906667[/C][/ROW]
[ROW][C]87[/C][C]5[/C][C]4.95457[/C][C]0.0454254[/C][/ROW]
[ROW][C]88[/C][C]4.5[/C][C]5.06196[/C][C]-0.561957[/C][/ROW]
[ROW][C]89[/C][C]2.5[/C][C]4.62623[/C][C]-2.12623[/C][/ROW]
[ROW][C]90[/C][C]7.5[/C][C]4.89356[/C][C]2.60644[/C][/ROW]
[ROW][C]91[/C][C]7[/C][C]5.01145[/C][C]1.98855[/C][/ROW]
[ROW][C]92[/C][C]0[/C][C]5.10169[/C][C]-5.10169[/C][/ROW]
[ROW][C]93[/C][C]4.5[/C][C]5.2351[/C][C]-0.735101[/C][/ROW]
[ROW][C]94[/C][C]3[/C][C]5.70279[/C][C]-2.70279[/C][/ROW]
[ROW][C]95[/C][C]1.5[/C][C]5.52087[/C][C]-4.02087[/C][/ROW]
[ROW][C]96[/C][C]3.5[/C][C]4.61616[/C][C]-1.11616[/C][/ROW]
[ROW][C]97[/C][C]2.5[/C][C]5.67863[/C][C]-3.17863[/C][/ROW]
[ROW][C]98[/C][C]5.5[/C][C]5.07554[/C][C]0.424459[/C][/ROW]
[ROW][C]99[/C][C]8[/C][C]5.4217[/C][C]2.5783[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]4.73413[/C][C]-3.73413[/C][/ROW]
[ROW][C]101[/C][C]5[/C][C]5.41105[/C][C]-0.411054[/C][/ROW]
[ROW][C]102[/C][C]4.5[/C][C]5.52728[/C][C]-1.02728[/C][/ROW]
[ROW][C]103[/C][C]3[/C][C]4.82552[/C][C]-1.82552[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]4.83223[/C][C]-1.83223[/C][/ROW]
[ROW][C]105[/C][C]8[/C][C]5.62558[/C][C]2.37442[/C][/ROW]
[ROW][C]106[/C][C]2.5[/C][C]4.68914[/C][C]-2.18914[/C][/ROW]
[ROW][C]107[/C][C]7[/C][C]4.88468[/C][C]2.11532[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]5.06848[/C][C]-5.06848[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]5.08762[/C][C]-4.08762[/C][/ROW]
[ROW][C]110[/C][C]3.5[/C][C]4.87341[/C][C]-1.37341[/C][/ROW]
[ROW][C]111[/C][C]5.5[/C][C]4.8454[/C][C]0.654601[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]4.69831[/C][C]0.801694[/C][/ROW]
[ROW][C]113[/C][C]0.5[/C][C]4.85427[/C][C]-4.35427[/C][/ROW]
[ROW][C]114[/C][C]7.5[/C][C]6.57667[/C][C]0.923331[/C][/ROW]
[ROW][C]115[/C][C]9[/C][C]6.93964[/C][C]2.06036[/C][/ROW]
[ROW][C]116[/C][C]9.5[/C][C]7.10221[/C][C]2.39779[/C][/ROW]
[ROW][C]117[/C][C]8.5[/C][C]8.25052[/C][C]0.249481[/C][/ROW]
[ROW][C]118[/C][C]7[/C][C]4.73937[/C][C]2.26063[/C][/ROW]
[ROW][C]119[/C][C]8[/C][C]11.0636[/C][C]-3.06365[/C][/ROW]
[ROW][C]120[/C][C]10[/C][C]7.2836[/C][C]2.7164[/C][/ROW]
[ROW][C]121[/C][C]7[/C][C]9.29912[/C][C]-2.29912[/C][/ROW]
[ROW][C]122[/C][C]8.5[/C][C]5.12753[/C][C]3.37247[/C][/ROW]
[ROW][C]123[/C][C]9[/C][C]8.77544[/C][C]0.224563[/C][/ROW]
[ROW][C]124[/C][C]9.5[/C][C]5.63192[/C][C]3.86808[/C][/ROW]
[ROW][C]125[/C][C]4[/C][C]7.32871[/C][C]-3.32871[/C][/ROW]
[ROW][C]126[/C][C]6[/C][C]6.67419[/C][C]-0.674192[/C][/ROW]
[ROW][C]127[/C][C]8[/C][C]7.27556[/C][C]0.72444[/C][/ROW]
[ROW][C]128[/C][C]5.5[/C][C]8.69966[/C][C]-3.19966[/C][/ROW]
[ROW][C]129[/C][C]9.5[/C][C]7.5208[/C][C]1.9792[/C][/ROW]
[ROW][C]130[/C][C]7.5[/C][C]5.81827[/C][C]1.68173[/C][/ROW]
[ROW][C]131[/C][C]7[/C][C]5.45983[/C][C]1.54017[/C][/ROW]
[ROW][C]132[/C][C]7.5[/C][C]8.71144[/C][C]-1.21144[/C][/ROW]
[ROW][C]133[/C][C]8[/C][C]6.42513[/C][C]1.57487[/C][/ROW]
[ROW][C]134[/C][C]7[/C][C]6.89922[/C][C]0.100779[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]6.11338[/C][C]0.886623[/C][/ROW]
[ROW][C]136[/C][C]6[/C][C]7.48731[/C][C]-1.48731[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]6.63638[/C][C]3.36362[/C][/ROW]
[ROW][C]138[/C][C]2.5[/C][C]6.38042[/C][C]-3.88042[/C][/ROW]
[ROW][C]139[/C][C]9[/C][C]8.81402[/C][C]0.185981[/C][/ROW]
[ROW][C]140[/C][C]8[/C][C]9.28873[/C][C]-1.28873[/C][/ROW]
[ROW][C]141[/C][C]6[/C][C]5.46098[/C][C]0.539018[/C][/ROW]
[ROW][C]142[/C][C]8.5[/C][C]5.05295[/C][C]3.44705[/C][/ROW]
[ROW][C]143[/C][C]6[/C][C]6.2168[/C][C]-0.216801[/C][/ROW]
[ROW][C]144[/C][C]9[/C][C]8.08362[/C][C]0.916378[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]7.14398[/C][C]0.856021[/C][/ROW]
[ROW][C]146[/C][C]9[/C][C]7.21242[/C][C]1.78758[/C][/ROW]
[ROW][C]147[/C][C]5.5[/C][C]6.06008[/C][C]-0.560077[/C][/ROW]
[ROW][C]148[/C][C]7[/C][C]6.53096[/C][C]0.469041[/C][/ROW]
[ROW][C]149[/C][C]5.5[/C][C]8.99196[/C][C]-3.49196[/C][/ROW]
[ROW][C]150[/C][C]9[/C][C]7.65901[/C][C]1.34099[/C][/ROW]
[ROW][C]151[/C][C]2[/C][C]7.06061[/C][C]-5.06061[/C][/ROW]
[ROW][C]152[/C][C]8.5[/C][C]6.90806[/C][C]1.59194[/C][/ROW]
[ROW][C]153[/C][C]9[/C][C]7.41726[/C][C]1.58274[/C][/ROW]
[ROW][C]154[/C][C]8.5[/C][C]8.37645[/C][C]0.123553[/C][/ROW]
[ROW][C]155[/C][C]9[/C][C]6.30817[/C][C]2.69183[/C][/ROW]
[ROW][C]156[/C][C]7.5[/C][C]7.06828[/C][C]0.431722[/C][/ROW]
[ROW][C]157[/C][C]10[/C][C]7.82568[/C][C]2.17432[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]7.15228[/C][C]1.84772[/C][/ROW]
[ROW][C]159[/C][C]7.5[/C][C]8.92832[/C][C]-1.42832[/C][/ROW]
[ROW][C]160[/C][C]6[/C][C]6.03753[/C][C]-0.037527[/C][/ROW]
[ROW][C]161[/C][C]10.5[/C][C]6.20891[/C][C]4.29109[/C][/ROW]
[ROW][C]162[/C][C]8.5[/C][C]9.21224[/C][C]-0.712237[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]6.43292[/C][C]1.56708[/C][/ROW]
[ROW][C]164[/C][C]10[/C][C]5.93064[/C][C]4.06936[/C][/ROW]
[ROW][C]165[/C][C]10.5[/C][C]6.77457[/C][C]3.72543[/C][/ROW]
[ROW][C]166[/C][C]6.5[/C][C]4.92622[/C][C]1.57378[/C][/ROW]
[ROW][C]167[/C][C]9.5[/C][C]7.89155[/C][C]1.60845[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]4.71985[/C][C]3.78015[/C][/ROW]
[ROW][C]169[/C][C]7.5[/C][C]7.76174[/C][C]-0.26174[/C][/ROW]
[ROW][C]170[/C][C]5[/C][C]7.21986[/C][C]-2.21986[/C][/ROW]
[ROW][C]171[/C][C]8[/C][C]7.56912[/C][C]0.430876[/C][/ROW]
[ROW][C]172[/C][C]10[/C][C]6.35748[/C][C]3.64252[/C][/ROW]
[ROW][C]173[/C][C]7[/C][C]5.84524[/C][C]1.15476[/C][/ROW]
[ROW][C]174[/C][C]7.5[/C][C]7.62824[/C][C]-0.128239[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]7.62824[/C][C]-0.128239[/C][/ROW]
[ROW][C]176[/C][C]9.5[/C][C]6.62646[/C][C]2.87354[/C][/ROW]
[ROW][C]177[/C][C]6[/C][C]6.69322[/C][C]-0.693225[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]8.05849[/C][C]1.94151[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]5.97752[/C][C]1.02248[/C][/ROW]
[ROW][C]180[/C][C]3[/C][C]6.17611[/C][C]-3.17611[/C][/ROW]
[ROW][C]181[/C][C]6[/C][C]7.03608[/C][C]-1.03608[/C][/ROW]
[ROW][C]182[/C][C]7[/C][C]6.43599[/C][C]0.564008[/C][/ROW]
[ROW][C]183[/C][C]10[/C][C]8.43401[/C][C]1.56599[/C][/ROW]
[ROW][C]184[/C][C]7[/C][C]6.8797[/C][C]0.120302[/C][/ROW]
[ROW][C]185[/C][C]3.5[/C][C]5.36424[/C][C]-1.86424[/C][/ROW]
[ROW][C]186[/C][C]8[/C][C]6.75876[/C][C]1.24124[/C][/ROW]
[ROW][C]187[/C][C]10[/C][C]5.71717[/C][C]4.28283[/C][/ROW]
[ROW][C]188[/C][C]5.5[/C][C]5.73608[/C][C]-0.236079[/C][/ROW]
[ROW][C]189[/C][C]6[/C][C]3.97648[/C][C]2.02352[/C][/ROW]
[ROW][C]190[/C][C]6.5[/C][C]6.45648[/C][C]0.0435203[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]5.71066[/C][C]0.789338[/C][/ROW]
[ROW][C]192[/C][C]8.5[/C][C]6.17981[/C][C]2.32019[/C][/ROW]
[ROW][C]193[/C][C]4[/C][C]5.35959[/C][C]-1.35959[/C][/ROW]
[ROW][C]194[/C][C]9.5[/C][C]6.33381[/C][C]3.16619[/C][/ROW]
[ROW][C]195[/C][C]8[/C][C]5.97788[/C][C]2.02212[/C][/ROW]
[ROW][C]196[/C][C]8.5[/C][C]7.49764[/C][C]1.00236[/C][/ROW]
[ROW][C]197[/C][C]5.5[/C][C]8.35686[/C][C]-2.85686[/C][/ROW]
[ROW][C]198[/C][C]7[/C][C]6.96146[/C][C]0.0385426[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]5.30873[/C][C]3.69127[/C][/ROW]
[ROW][C]200[/C][C]8[/C][C]6.04679[/C][C]1.95321[/C][/ROW]
[ROW][C]201[/C][C]10[/C][C]7.89703[/C][C]2.10297[/C][/ROW]
[ROW][C]202[/C][C]8[/C][C]5.98941[/C][C]2.01059[/C][/ROW]
[ROW][C]203[/C][C]6[/C][C]6.14916[/C][C]-0.149159[/C][/ROW]
[ROW][C]204[/C][C]8[/C][C]7.53452[/C][C]0.465482[/C][/ROW]
[ROW][C]205[/C][C]5[/C][C]5.52199[/C][C]-0.521991[/C][/ROW]
[ROW][C]206[/C][C]9[/C][C]5.32897[/C][C]3.67103[/C][/ROW]
[ROW][C]207[/C][C]4.5[/C][C]6.99707[/C][C]-2.49707[/C][/ROW]
[ROW][C]208[/C][C]8.5[/C][C]5.55559[/C][C]2.94441[/C][/ROW]
[ROW][C]209[/C][C]9.5[/C][C]8.37683[/C][C]1.12317[/C][/ROW]
[ROW][C]210[/C][C]8.5[/C][C]7.0606[/C][C]1.4394[/C][/ROW]
[ROW][C]211[/C][C]7.5[/C][C]5.00352[/C][C]2.49648[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]5.87336[/C][C]1.62664[/C][/ROW]
[ROW][C]213[/C][C]5[/C][C]7.58784[/C][C]-2.58784[/C][/ROW]
[ROW][C]214[/C][C]7[/C][C]8.24564[/C][C]-1.24564[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]8.51135[/C][C]-0.511351[/C][/ROW]
[ROW][C]216[/C][C]5.5[/C][C]6.47196[/C][C]-0.971957[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]6.28093[/C][C]2.21907[/C][/ROW]
[ROW][C]218[/C][C]9.5[/C][C]6.90833[/C][C]2.59167[/C][/ROW]
[ROW][C]219[/C][C]7[/C][C]5.75411[/C][C]1.24589[/C][/ROW]
[ROW][C]220[/C][C]8[/C][C]7.70484[/C][C]0.295158[/C][/ROW]
[ROW][C]221[/C][C]8.5[/C][C]7.7828[/C][C]0.717199[/C][/ROW]
[ROW][C]222[/C][C]3.5[/C][C]6.4939[/C][C]-2.9939[/C][/ROW]
[ROW][C]223[/C][C]6.5[/C][C]5.44581[/C][C]1.05419[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]5.13286[/C][C]1.36714[/C][/ROW]
[ROW][C]225[/C][C]10.5[/C][C]7.80643[/C][C]2.69357[/C][/ROW]
[ROW][C]226[/C][C]8.5[/C][C]5.90683[/C][C]2.59317[/C][/ROW]
[ROW][C]227[/C][C]8[/C][C]6.27958[/C][C]1.72042[/C][/ROW]
[ROW][C]228[/C][C]10[/C][C]6.00369[/C][C]3.99631[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]7.58213[/C][C]2.41787[/C][/ROW]
[ROW][C]230[/C][C]9.5[/C][C]7.25434[/C][C]2.24566[/C][/ROW]
[ROW][C]231[/C][C]9[/C][C]5.69891[/C][C]3.30109[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.50349[/C][C]1.49651[/C][/ROW]
[ROW][C]233[/C][C]7.5[/C][C]5.62938[/C][C]1.87062[/C][/ROW]
[ROW][C]234[/C][C]4.5[/C][C]5.74587[/C][C]-1.24587[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]5.50119[/C][C]-1.00119[/C][/ROW]
[ROW][C]236[/C][C]0.5[/C][C]5.60348[/C][C]-5.10348[/C][/ROW]
[ROW][C]237[/C][C]6.5[/C][C]5.23135[/C][C]1.26865[/C][/ROW]
[ROW][C]238[/C][C]4.5[/C][C]7.53506[/C][C]-3.03506[/C][/ROW]
[ROW][C]239[/C][C]5.5[/C][C]6.88811[/C][C]-1.38811[/C][/ROW]
[ROW][C]240[/C][C]5[/C][C]5.4074[/C][C]-0.4074[/C][/ROW]
[ROW][C]241[/C][C]6[/C][C]7.47346[/C][C]-1.47346[/C][/ROW]
[ROW][C]242[/C][C]4[/C][C]7.19312[/C][C]-3.19312[/C][/ROW]
[ROW][C]243[/C][C]8[/C][C]5.35297[/C][C]2.64703[/C][/ROW]
[ROW][C]244[/C][C]10.5[/C][C]6.77457[/C][C]3.72543[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]5.50097[/C][C]0.999027[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]7.7248[/C][C]0.275204[/C][/ROW]
[ROW][C]247[/C][C]8.5[/C][C]7.8666[/C][C]0.633403[/C][/ROW]
[ROW][C]248[/C][C]5.5[/C][C]5.63302[/C][C]-0.133016[/C][/ROW]
[ROW][C]249[/C][C]7[/C][C]7.68805[/C][C]-0.688047[/C][/ROW]
[ROW][C]250[/C][C]5[/C][C]6.11869[/C][C]-1.11869[/C][/ROW]
[ROW][C]251[/C][C]3.5[/C][C]5.44749[/C][C]-1.94749[/C][/ROW]
[ROW][C]252[/C][C]5[/C][C]7.35501[/C][C]-2.35501[/C][/ROW]
[ROW][C]253[/C][C]9[/C][C]7.44091[/C][C]1.55909[/C][/ROW]
[ROW][C]254[/C][C]8.5[/C][C]6.68275[/C][C]1.81725[/C][/ROW]
[ROW][C]255[/C][C]5[/C][C]6.20291[/C][C]-1.20291[/C][/ROW]
[ROW][C]256[/C][C]9.5[/C][C]7.70562[/C][C]1.79438[/C][/ROW]
[ROW][C]257[/C][C]3[/C][C]4.83856[/C][C]-1.83856[/C][/ROW]
[ROW][C]258[/C][C]1.5[/C][C]7.3369[/C][C]-5.8369[/C][/ROW]
[ROW][C]259[/C][C]6[/C][C]5.29653[/C][C]0.703473[/C][/ROW]
[ROW][C]260[/C][C]0.5[/C][C]5.28138[/C][C]-4.78138[/C][/ROW]
[ROW][C]261[/C][C]6.5[/C][C]4.92622[/C][C]1.57378[/C][/ROW]
[ROW][C]262[/C][C]7.5[/C][C]5.81471[/C][C]1.68529[/C][/ROW]
[ROW][C]263[/C][C]4.5[/C][C]5.86285[/C][C]-1.36285[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]5.35297[/C][C]2.64703[/C][/ROW]
[ROW][C]265[/C][C]9[/C][C]7.28187[/C][C]1.71813[/C][/ROW]
[ROW][C]266[/C][C]7.5[/C][C]6.6997[/C][C]0.800301[/C][/ROW]
[ROW][C]267[/C][C]8.5[/C][C]6.73469[/C][C]1.76531[/C][/ROW]
[ROW][C]268[/C][C]7[/C][C]5.18448[/C][C]1.81552[/C][/ROW]
[ROW][C]269[/C][C]9.5[/C][C]5.75865[/C][C]3.74135[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]5.10364[/C][C]1.39636[/C][/ROW]
[ROW][C]271[/C][C]9.5[/C][C]5.23837[/C][C]4.26163[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]5.30884[/C][C]0.691155[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]7.11216[/C][C]0.887842[/C][/ROW]
[ROW][C]274[/C][C]9.5[/C][C]8.38799[/C][C]1.11201[/C][/ROW]
[ROW][C]275[/C][C]8[/C][C]6.17304[/C][C]1.82696[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]6.28455[/C][C]1.71545[/C][/ROW]
[ROW][C]277[/C][C]9[/C][C]7.2381[/C][C]1.7619[/C][/ROW]
[ROW][C]278[/C][C]5[/C][C]5.53279[/C][C]-0.532792[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266991&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266991&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
17.55.480052.01995
265.080180.919822
36.55.354791.14521
415.69821-4.69821
515.0973-4.0973
65.56.56294-1.06294
78.55.726162.77384
86.55.884320.615684
94.55.51894-1.01894
1026.48189-4.48189
1155.78051-0.78051
120.56.84898-6.34898
1355.23712-0.237121
1456.02301-1.02301
152.54.73357-2.23357
1655.37759-0.377586
175.56.29802-0.798019
183.55.5596-2.0596
1935.5369-2.5369
2045.36475-1.36475
210.55.04115-4.54115
226.55.386591.11341
234.55.51008-1.01008
247.55.182232.31777
255.55.69515-0.195147
2646.47917-2.47917
277.55.901781.59822
2875.310721.68928
2944.98026-0.980265
305.55.458690.0413119
312.55.77318-3.27318
325.56.06802-0.568018
333.55.64507-2.14507
342.56.37675-3.87675
354.55.95492-1.45492
364.56.07651-1.57651
374.55.21367-0.713674
3865.721340.278661
392.55.14842-2.64842
4056.63328-1.63328
4104.78882-4.78882
4256.37895-1.37895
436.55.047931.45207
4455.66702-0.667021
4565.144940.855057
464.55.7481-1.2481
475.56.02599-0.525989
4815.12968-4.12968
497.54.692872.80713
5065.023790.976211
5155.58379-0.583791
5215.65352-4.65352
5356.05243-1.05243
546.55.66290.8371
5576.364870.635132
564.56.43645-1.93645
5705.30502-5.30502
588.55.527532.97247
593.54.63198-1.13198
607.55.667081.83292
613.55.76592-2.26592
6264.822851.17715
631.55.0804-3.5804
6496.030772.96923
653.54.64277-1.14277
663.55.09904-1.59904
6746.21122-2.21122
686.56.03780.462203
697.55.302142.19786
7065.085590.91441
7155.79477-0.794774
725.55.080510.419494
733.55.58323-2.08323
747.55.136152.36385
756.56.03360.466396
766.56.24180.258201
776.55.131071.36893
7876.955830.0441715
793.55.40828-1.90828
801.55.36938-3.86938
8144.8978-0.897799
827.54.770092.72991
834.55.78477-1.28477
8404.63998-4.63998
853.54.91182-1.41182
865.55.50907-0.00906667
8754.954570.0454254
884.55.06196-0.561957
892.54.62623-2.12623
907.54.893562.60644
9175.011451.98855
9205.10169-5.10169
934.55.2351-0.735101
9435.70279-2.70279
951.55.52087-4.02087
963.54.61616-1.11616
972.55.67863-3.17863
985.55.075540.424459
9985.42172.5783
10014.73413-3.73413
10155.41105-0.411054
1024.55.52728-1.02728
10334.82552-1.82552
10434.83223-1.83223
10585.625582.37442
1062.54.68914-2.18914
10774.884682.11532
10805.06848-5.06848
10915.08762-4.08762
1103.54.87341-1.37341
1115.54.84540.654601
1125.54.698310.801694
1130.54.85427-4.35427
1147.56.576670.923331
11596.939642.06036
1169.57.102212.39779
1178.58.250520.249481
11874.739372.26063
119811.0636-3.06365
120107.28362.7164
12179.29912-2.29912
1228.55.127533.37247
12398.775440.224563
1249.55.631923.86808
12547.32871-3.32871
12666.67419-0.674192
12787.275560.72444
1285.58.69966-3.19966
1299.57.52081.9792
1307.55.818271.68173
13175.459831.54017
1327.58.71144-1.21144
13386.425131.57487
13476.899220.100779
13576.113380.886623
13667.48731-1.48731
137106.636383.36362
1382.56.38042-3.88042
13998.814020.185981
14089.28873-1.28873
14165.460980.539018
1428.55.052953.44705
14366.2168-0.216801
14498.083620.916378
14587.143980.856021
14697.212421.78758
1475.56.06008-0.560077
14876.530960.469041
1495.58.99196-3.49196
15097.659011.34099
15127.06061-5.06061
1528.56.908061.59194
15397.417261.58274
1548.58.376450.123553
15596.308172.69183
1567.57.068280.431722
157107.825682.17432
15897.152281.84772
1597.58.92832-1.42832
16066.03753-0.037527
16110.56.208914.29109
1628.59.21224-0.712237
16386.432921.56708
164105.930644.06936
16510.56.774573.72543
1666.54.926221.57378
1679.57.891551.60845
1688.54.719853.78015
1697.57.76174-0.26174
17057.21986-2.21986
17187.569120.430876
172106.357483.64252
17375.845241.15476
1747.57.62824-0.128239
1757.57.62824-0.128239
1769.56.626462.87354
17766.69322-0.693225
178108.058491.94151
17975.977521.02248
18036.17611-3.17611
18167.03608-1.03608
18276.435990.564008
183108.434011.56599
18476.87970.120302
1853.55.36424-1.86424
18686.758761.24124
187105.717174.28283
1885.55.73608-0.236079
18963.976482.02352
1906.56.456480.0435203
1916.55.710660.789338
1928.56.179812.32019
19345.35959-1.35959
1949.56.333813.16619
19585.977882.02212
1968.57.497641.00236
1975.58.35686-2.85686
19876.961460.0385426
19995.308733.69127
20086.046791.95321
201107.897032.10297
20285.989412.01059
20366.14916-0.149159
20487.534520.465482
20555.52199-0.521991
20695.328973.67103
2074.56.99707-2.49707
2088.55.555592.94441
2099.58.376831.12317
2108.57.06061.4394
2117.55.003522.49648
2127.55.873361.62664
21357.58784-2.58784
21478.24564-1.24564
21588.51135-0.511351
2165.56.47196-0.971957
2178.56.280932.21907
2189.56.908332.59167
21975.754111.24589
22087.704840.295158
2218.57.78280.717199
2223.56.4939-2.9939
2236.55.445811.05419
2246.55.132861.36714
22510.57.806432.69357
2268.55.906832.59317
22786.279581.72042
228106.003693.99631
229107.582132.41787
2309.57.254342.24566
23195.698913.30109
232108.503491.49651
2337.55.629381.87062
2344.55.74587-1.24587
2354.55.50119-1.00119
2360.55.60348-5.10348
2376.55.231351.26865
2384.57.53506-3.03506
2395.56.88811-1.38811
24055.4074-0.4074
24167.47346-1.47346
24247.19312-3.19312
24385.352972.64703
24410.56.774573.72543
2456.55.500970.999027
24687.72480.275204
2478.57.86660.633403
2485.55.63302-0.133016
24977.68805-0.688047
25056.11869-1.11869
2513.55.44749-1.94749
25257.35501-2.35501
25397.440911.55909
2548.56.682751.81725
25556.20291-1.20291
2569.57.705621.79438
25734.83856-1.83856
2581.57.3369-5.8369
25965.296530.703473
2600.55.28138-4.78138
2616.54.926221.57378
2627.55.814711.68529
2634.55.86285-1.36285
26485.352972.64703
26597.281871.71813
2667.56.69970.800301
2678.56.734691.76531
26875.184481.81552
2699.55.758653.74135
2706.55.103641.39636
2719.55.238374.26163
27265.308840.691155
27387.112160.887842
2749.58.387991.11201
27586.173041.82696
27686.284551.71545
27797.23811.7619
27855.53279-0.532792






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.9178170.1643660.082183
90.9252440.1495120.0747559
100.9264490.1471030.0735515
110.8775340.2449320.122466
120.9029040.1941930.0970963
130.8737930.2524150.126207
140.819050.36190.18095
150.7564220.4871560.243578
160.7317810.5364380.268219
170.685170.629660.31483
180.6124930.7750140.387507
190.559590.8808190.44041
200.4928790.9857570.507121
210.6009330.7981340.399067
220.6338590.7322810.366141
230.567990.864020.43201
240.5128640.9742730.487136
250.4528660.9057310.547134
260.4038210.8076420.596179
270.3446320.6892650.655368
280.380930.7618610.61907
290.3593120.7186240.640688
300.329170.658340.67083
310.3007730.6015470.699227
320.3017890.6035770.698211
330.2577040.5154080.742296
340.263550.5270990.73645
350.2278260.4556520.772174
360.2020110.4040220.797989
370.1661540.3323080.833846
380.1782570.3565130.821743
390.2213670.4427330.778633
400.1966790.3933580.803321
410.3330130.6660260.666987
420.3002020.6004030.699798
430.2756960.5513910.724304
440.2410340.4820690.758966
450.2275380.4550770.772462
460.1959480.3918960.804052
470.1684680.3369360.831532
480.2497930.4995860.750207
490.2669040.5338080.733096
500.2700730.5401460.729927
510.237220.4744410.76278
520.273730.547460.72627
530.2528610.5057230.747139
540.2606030.5212060.739397
550.2763010.5526020.723699
560.2477720.4955440.752228
570.3727590.7455180.627241
580.460160.9203190.53984
590.4198760.8397520.580124
600.4423160.8846320.557684
610.4441540.8883070.555846
620.4282620.8565240.571738
630.4774990.9549970.522501
640.5379750.9240510.462025
650.516820.966360.48318
660.4830290.9660590.516971
670.4736170.9472340.526383
680.434370.868740.56563
690.4506660.9013330.549334
700.42780.8556010.5722
710.3966980.7933970.603302
720.3663230.7326470.633677
730.3419310.6838620.658069
740.3431920.6863840.656808
750.3268180.6536370.673182
760.3044020.6088050.695598
770.2966190.5932390.703381
780.2875150.5750290.712485
790.2653980.5307970.734602
800.3278340.6556680.672166
810.2992790.5985570.700721
820.3238640.6477270.676136
830.2956770.5913540.704323
840.411560.8231190.58844
850.397290.7945810.60271
860.364780.729560.63522
870.3337220.6674430.666278
880.303910.6078210.69609
890.3037210.6074420.696279
900.3223050.6446110.677695
910.3354730.6709460.664527
920.4730.9460010.527
930.4483550.8967110.551645
940.4416340.8832680.558366
950.4898640.9797290.510136
960.4703270.9406540.529673
970.496740.9934810.50326
980.4779660.9559320.522034
990.5434460.9131080.456554
1000.64530.7094010.3547
1010.6185020.7629950.381498
1020.5954430.8091130.404557
1030.5918390.8163230.408161
1040.610410.7791810.38959
1050.6410180.7179650.358982
1060.6663940.6672110.333606
1070.6714740.6570510.328526
1080.8161550.367690.183845
1090.8655440.2689110.134456
1100.8715560.2568880.128444
1110.8616980.2766040.138302
1120.8518060.2963880.148194
1130.9058420.1883160.094158
1140.9096890.1806220.090311
1150.9232320.1535350.0767675
1160.9363740.1272510.0636255
1170.926030.147940.0739702
1180.9331950.133610.0668048
1190.9243230.1513540.0756771
1200.9326940.1346130.0673065
1210.9399890.1200220.0600112
1220.9594650.08107090.0405354
1230.9547120.09057690.0452885
1240.9761650.04766950.0238347
1250.9788390.04232190.0211609
1260.9746070.05078640.0253932
1270.9711990.05760180.0288009
1280.9712970.05740610.028703
1290.9717740.0564510.0282255
1300.9706950.0586110.0293055
1310.968170.06366030.0318302
1320.9645340.07093250.0354663
1330.9622940.07541220.0377061
1340.9557860.08842720.0442136
1350.9502090.09958210.0497911
1360.9428620.1142770.0571385
1370.9586980.08260410.0413021
1380.9679640.06407220.0320361
1390.9619650.07606980.0380349
1400.9550450.089910.044955
1410.9477480.1045040.0522522
1420.9551880.08962430.0448122
1430.9530030.09399430.0469971
1440.9484790.1030420.051521
1450.9405640.1188730.0594364
1460.9358150.128370.064185
1470.9286930.1426150.0713075
1480.9178780.1642440.0821222
1490.9235390.1529220.0764608
1500.9169460.1661080.0830541
1510.9667270.06654690.0332734
1520.9631580.0736850.0368425
1530.9600920.07981520.0399076
1540.9523760.09524740.0476237
1550.9603390.07932230.0396612
1560.953060.09388060.0469403
1570.9498450.100310.0501551
1580.9482350.103530.051765
1590.9412840.1174320.058716
1600.9318050.1363910.0681953
1610.9477540.1044930.0522463
1620.9390830.1218340.0609171
1630.9310210.1379590.0689793
1640.9665720.06685620.0334281
1650.9695270.06094610.030473
1660.9658080.06838440.0341922
1670.9618330.07633310.0381665
1680.9711630.05767390.028837
1690.9647130.07057360.0352868
1700.9657290.06854230.0342712
1710.9588490.08230190.0411509
1720.965740.06852040.0342602
1730.9602820.07943530.0397177
1740.9518790.09624140.0481207
1750.9420890.1158220.0579112
1760.9439370.1121250.0560627
1770.9381410.1237170.0618587
1780.9371410.1257180.0628589
1790.927470.1450610.0725305
1800.9363260.1273470.0636736
1810.9374770.1250460.0625228
1820.9259570.1480860.0740429
1830.9186820.1626350.0813175
1840.9047320.1905360.095268
1850.9184030.1631940.0815971
1860.9054630.1890750.0945373
1870.9367150.126570.0632848
1880.9296880.1406230.0703117
1890.9211680.1576640.0788322
1900.9062990.1874030.0937014
1910.8909930.2180150.109007
1920.8807270.2385460.119273
1930.874210.251580.12579
1940.8834720.2330570.116528
1950.8762690.2474610.123731
1960.8651090.2697820.134891
1970.8792090.2415820.120791
1980.8584540.2830920.141546
1990.8813320.2373360.118668
2000.867080.265840.13292
2010.8530910.2938180.146909
2020.849410.3011790.15059
2030.8315930.3368140.168407
2040.8084850.3830310.191515
2050.7873190.4253620.212681
2060.8248790.3502420.175121
2070.8188150.362370.181185
2080.8400450.3199110.159955
2090.8161160.3677680.183884
2100.7930850.413830.206915
2110.7867050.4265890.213295
2120.7604620.4790750.239538
2130.7882890.4234220.211711
2140.7609910.4780170.239009
2150.7375830.5248330.262417
2160.7128220.5743560.287178
2170.6955390.6089220.304461
2180.6880630.6238740.311937
2190.6563420.6873170.343658
2200.615480.769040.38452
2210.5784370.8431270.421563
2220.5846620.8306750.415338
2230.5478490.9043020.452151
2240.5128990.9742010.487101
2250.5161830.9676340.483817
2260.5446690.9106620.455331
2270.5439120.9121770.456088
2280.62190.7561990.3781
2290.5892740.8214510.410726
2300.5930070.8139860.406993
2310.6335230.7329540.366477
2320.5909790.8180410.409021
2330.5742390.8515230.425761
2340.5430750.9138510.456925
2350.5007280.9985440.499272
2360.6702880.6594230.329712
2370.6419610.7160790.358039
2380.6821460.6357080.317854
2390.652260.695480.34774
2400.6104380.7791240.389562
2410.5811840.8376330.418816
2420.624090.7518190.37591
2430.6078940.7842120.392106
2440.5962760.8074480.403724
2450.5487360.9025280.451264
2460.491460.9829190.50854
2470.4346810.8693630.565319
2480.3780720.7561440.621928
2490.3422470.6844940.657753
2500.3000650.600130.699935
2510.2940470.5880940.705953
2520.3280170.6560330.671983
2530.279370.558740.72063
2540.2312090.4624190.768791
2550.271760.5435210.72824
2560.236360.4727190.76364
2570.2525980.5051970.747402
2580.8250480.3499050.174952
2590.7914620.4170760.208538
2600.9995480.0009046830.000452342
2610.9999931.38105e-056.90523e-06
2620.9999813.74244e-051.87122e-05
2630.9999774.62276e-052.31138e-05
2640.9999715.83285e-052.91642e-05
2650.9999190.0001627398.13696e-05
2660.9996420.0007150010.0003575
2670.9991910.001617920.000808962
2680.9966420.006715180.00335759
2690.987170.02566070.0128303
2700.9656290.06874110.0343706

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.917817 & 0.164366 & 0.082183 \tabularnewline
9 & 0.925244 & 0.149512 & 0.0747559 \tabularnewline
10 & 0.926449 & 0.147103 & 0.0735515 \tabularnewline
11 & 0.877534 & 0.244932 & 0.122466 \tabularnewline
12 & 0.902904 & 0.194193 & 0.0970963 \tabularnewline
13 & 0.873793 & 0.252415 & 0.126207 \tabularnewline
14 & 0.81905 & 0.3619 & 0.18095 \tabularnewline
15 & 0.756422 & 0.487156 & 0.243578 \tabularnewline
16 & 0.731781 & 0.536438 & 0.268219 \tabularnewline
17 & 0.68517 & 0.62966 & 0.31483 \tabularnewline
18 & 0.612493 & 0.775014 & 0.387507 \tabularnewline
19 & 0.55959 & 0.880819 & 0.44041 \tabularnewline
20 & 0.492879 & 0.985757 & 0.507121 \tabularnewline
21 & 0.600933 & 0.798134 & 0.399067 \tabularnewline
22 & 0.633859 & 0.732281 & 0.366141 \tabularnewline
23 & 0.56799 & 0.86402 & 0.43201 \tabularnewline
24 & 0.512864 & 0.974273 & 0.487136 \tabularnewline
25 & 0.452866 & 0.905731 & 0.547134 \tabularnewline
26 & 0.403821 & 0.807642 & 0.596179 \tabularnewline
27 & 0.344632 & 0.689265 & 0.655368 \tabularnewline
28 & 0.38093 & 0.761861 & 0.61907 \tabularnewline
29 & 0.359312 & 0.718624 & 0.640688 \tabularnewline
30 & 0.32917 & 0.65834 & 0.67083 \tabularnewline
31 & 0.300773 & 0.601547 & 0.699227 \tabularnewline
32 & 0.301789 & 0.603577 & 0.698211 \tabularnewline
33 & 0.257704 & 0.515408 & 0.742296 \tabularnewline
34 & 0.26355 & 0.527099 & 0.73645 \tabularnewline
35 & 0.227826 & 0.455652 & 0.772174 \tabularnewline
36 & 0.202011 & 0.404022 & 0.797989 \tabularnewline
37 & 0.166154 & 0.332308 & 0.833846 \tabularnewline
38 & 0.178257 & 0.356513 & 0.821743 \tabularnewline
39 & 0.221367 & 0.442733 & 0.778633 \tabularnewline
40 & 0.196679 & 0.393358 & 0.803321 \tabularnewline
41 & 0.333013 & 0.666026 & 0.666987 \tabularnewline
42 & 0.300202 & 0.600403 & 0.699798 \tabularnewline
43 & 0.275696 & 0.551391 & 0.724304 \tabularnewline
44 & 0.241034 & 0.482069 & 0.758966 \tabularnewline
45 & 0.227538 & 0.455077 & 0.772462 \tabularnewline
46 & 0.195948 & 0.391896 & 0.804052 \tabularnewline
47 & 0.168468 & 0.336936 & 0.831532 \tabularnewline
48 & 0.249793 & 0.499586 & 0.750207 \tabularnewline
49 & 0.266904 & 0.533808 & 0.733096 \tabularnewline
50 & 0.270073 & 0.540146 & 0.729927 \tabularnewline
51 & 0.23722 & 0.474441 & 0.76278 \tabularnewline
52 & 0.27373 & 0.54746 & 0.72627 \tabularnewline
53 & 0.252861 & 0.505723 & 0.747139 \tabularnewline
54 & 0.260603 & 0.521206 & 0.739397 \tabularnewline
55 & 0.276301 & 0.552602 & 0.723699 \tabularnewline
56 & 0.247772 & 0.495544 & 0.752228 \tabularnewline
57 & 0.372759 & 0.745518 & 0.627241 \tabularnewline
58 & 0.46016 & 0.920319 & 0.53984 \tabularnewline
59 & 0.419876 & 0.839752 & 0.580124 \tabularnewline
60 & 0.442316 & 0.884632 & 0.557684 \tabularnewline
61 & 0.444154 & 0.888307 & 0.555846 \tabularnewline
62 & 0.428262 & 0.856524 & 0.571738 \tabularnewline
63 & 0.477499 & 0.954997 & 0.522501 \tabularnewline
64 & 0.537975 & 0.924051 & 0.462025 \tabularnewline
65 & 0.51682 & 0.96636 & 0.48318 \tabularnewline
66 & 0.483029 & 0.966059 & 0.516971 \tabularnewline
67 & 0.473617 & 0.947234 & 0.526383 \tabularnewline
68 & 0.43437 & 0.86874 & 0.56563 \tabularnewline
69 & 0.450666 & 0.901333 & 0.549334 \tabularnewline
70 & 0.4278 & 0.855601 & 0.5722 \tabularnewline
71 & 0.396698 & 0.793397 & 0.603302 \tabularnewline
72 & 0.366323 & 0.732647 & 0.633677 \tabularnewline
73 & 0.341931 & 0.683862 & 0.658069 \tabularnewline
74 & 0.343192 & 0.686384 & 0.656808 \tabularnewline
75 & 0.326818 & 0.653637 & 0.673182 \tabularnewline
76 & 0.304402 & 0.608805 & 0.695598 \tabularnewline
77 & 0.296619 & 0.593239 & 0.703381 \tabularnewline
78 & 0.287515 & 0.575029 & 0.712485 \tabularnewline
79 & 0.265398 & 0.530797 & 0.734602 \tabularnewline
80 & 0.327834 & 0.655668 & 0.672166 \tabularnewline
81 & 0.299279 & 0.598557 & 0.700721 \tabularnewline
82 & 0.323864 & 0.647727 & 0.676136 \tabularnewline
83 & 0.295677 & 0.591354 & 0.704323 \tabularnewline
84 & 0.41156 & 0.823119 & 0.58844 \tabularnewline
85 & 0.39729 & 0.794581 & 0.60271 \tabularnewline
86 & 0.36478 & 0.72956 & 0.63522 \tabularnewline
87 & 0.333722 & 0.667443 & 0.666278 \tabularnewline
88 & 0.30391 & 0.607821 & 0.69609 \tabularnewline
89 & 0.303721 & 0.607442 & 0.696279 \tabularnewline
90 & 0.322305 & 0.644611 & 0.677695 \tabularnewline
91 & 0.335473 & 0.670946 & 0.664527 \tabularnewline
92 & 0.473 & 0.946001 & 0.527 \tabularnewline
93 & 0.448355 & 0.896711 & 0.551645 \tabularnewline
94 & 0.441634 & 0.883268 & 0.558366 \tabularnewline
95 & 0.489864 & 0.979729 & 0.510136 \tabularnewline
96 & 0.470327 & 0.940654 & 0.529673 \tabularnewline
97 & 0.49674 & 0.993481 & 0.50326 \tabularnewline
98 & 0.477966 & 0.955932 & 0.522034 \tabularnewline
99 & 0.543446 & 0.913108 & 0.456554 \tabularnewline
100 & 0.6453 & 0.709401 & 0.3547 \tabularnewline
101 & 0.618502 & 0.762995 & 0.381498 \tabularnewline
102 & 0.595443 & 0.809113 & 0.404557 \tabularnewline
103 & 0.591839 & 0.816323 & 0.408161 \tabularnewline
104 & 0.61041 & 0.779181 & 0.38959 \tabularnewline
105 & 0.641018 & 0.717965 & 0.358982 \tabularnewline
106 & 0.666394 & 0.667211 & 0.333606 \tabularnewline
107 & 0.671474 & 0.657051 & 0.328526 \tabularnewline
108 & 0.816155 & 0.36769 & 0.183845 \tabularnewline
109 & 0.865544 & 0.268911 & 0.134456 \tabularnewline
110 & 0.871556 & 0.256888 & 0.128444 \tabularnewline
111 & 0.861698 & 0.276604 & 0.138302 \tabularnewline
112 & 0.851806 & 0.296388 & 0.148194 \tabularnewline
113 & 0.905842 & 0.188316 & 0.094158 \tabularnewline
114 & 0.909689 & 0.180622 & 0.090311 \tabularnewline
115 & 0.923232 & 0.153535 & 0.0767675 \tabularnewline
116 & 0.936374 & 0.127251 & 0.0636255 \tabularnewline
117 & 0.92603 & 0.14794 & 0.0739702 \tabularnewline
118 & 0.933195 & 0.13361 & 0.0668048 \tabularnewline
119 & 0.924323 & 0.151354 & 0.0756771 \tabularnewline
120 & 0.932694 & 0.134613 & 0.0673065 \tabularnewline
121 & 0.939989 & 0.120022 & 0.0600112 \tabularnewline
122 & 0.959465 & 0.0810709 & 0.0405354 \tabularnewline
123 & 0.954712 & 0.0905769 & 0.0452885 \tabularnewline
124 & 0.976165 & 0.0476695 & 0.0238347 \tabularnewline
125 & 0.978839 & 0.0423219 & 0.0211609 \tabularnewline
126 & 0.974607 & 0.0507864 & 0.0253932 \tabularnewline
127 & 0.971199 & 0.0576018 & 0.0288009 \tabularnewline
128 & 0.971297 & 0.0574061 & 0.028703 \tabularnewline
129 & 0.971774 & 0.056451 & 0.0282255 \tabularnewline
130 & 0.970695 & 0.058611 & 0.0293055 \tabularnewline
131 & 0.96817 & 0.0636603 & 0.0318302 \tabularnewline
132 & 0.964534 & 0.0709325 & 0.0354663 \tabularnewline
133 & 0.962294 & 0.0754122 & 0.0377061 \tabularnewline
134 & 0.955786 & 0.0884272 & 0.0442136 \tabularnewline
135 & 0.950209 & 0.0995821 & 0.0497911 \tabularnewline
136 & 0.942862 & 0.114277 & 0.0571385 \tabularnewline
137 & 0.958698 & 0.0826041 & 0.0413021 \tabularnewline
138 & 0.967964 & 0.0640722 & 0.0320361 \tabularnewline
139 & 0.961965 & 0.0760698 & 0.0380349 \tabularnewline
140 & 0.955045 & 0.08991 & 0.044955 \tabularnewline
141 & 0.947748 & 0.104504 & 0.0522522 \tabularnewline
142 & 0.955188 & 0.0896243 & 0.0448122 \tabularnewline
143 & 0.953003 & 0.0939943 & 0.0469971 \tabularnewline
144 & 0.948479 & 0.103042 & 0.051521 \tabularnewline
145 & 0.940564 & 0.118873 & 0.0594364 \tabularnewline
146 & 0.935815 & 0.12837 & 0.064185 \tabularnewline
147 & 0.928693 & 0.142615 & 0.0713075 \tabularnewline
148 & 0.917878 & 0.164244 & 0.0821222 \tabularnewline
149 & 0.923539 & 0.152922 & 0.0764608 \tabularnewline
150 & 0.916946 & 0.166108 & 0.0830541 \tabularnewline
151 & 0.966727 & 0.0665469 & 0.0332734 \tabularnewline
152 & 0.963158 & 0.073685 & 0.0368425 \tabularnewline
153 & 0.960092 & 0.0798152 & 0.0399076 \tabularnewline
154 & 0.952376 & 0.0952474 & 0.0476237 \tabularnewline
155 & 0.960339 & 0.0793223 & 0.0396612 \tabularnewline
156 & 0.95306 & 0.0938806 & 0.0469403 \tabularnewline
157 & 0.949845 & 0.10031 & 0.0501551 \tabularnewline
158 & 0.948235 & 0.10353 & 0.051765 \tabularnewline
159 & 0.941284 & 0.117432 & 0.058716 \tabularnewline
160 & 0.931805 & 0.136391 & 0.0681953 \tabularnewline
161 & 0.947754 & 0.104493 & 0.0522463 \tabularnewline
162 & 0.939083 & 0.121834 & 0.0609171 \tabularnewline
163 & 0.931021 & 0.137959 & 0.0689793 \tabularnewline
164 & 0.966572 & 0.0668562 & 0.0334281 \tabularnewline
165 & 0.969527 & 0.0609461 & 0.030473 \tabularnewline
166 & 0.965808 & 0.0683844 & 0.0341922 \tabularnewline
167 & 0.961833 & 0.0763331 & 0.0381665 \tabularnewline
168 & 0.971163 & 0.0576739 & 0.028837 \tabularnewline
169 & 0.964713 & 0.0705736 & 0.0352868 \tabularnewline
170 & 0.965729 & 0.0685423 & 0.0342712 \tabularnewline
171 & 0.958849 & 0.0823019 & 0.0411509 \tabularnewline
172 & 0.96574 & 0.0685204 & 0.0342602 \tabularnewline
173 & 0.960282 & 0.0794353 & 0.0397177 \tabularnewline
174 & 0.951879 & 0.0962414 & 0.0481207 \tabularnewline
175 & 0.942089 & 0.115822 & 0.0579112 \tabularnewline
176 & 0.943937 & 0.112125 & 0.0560627 \tabularnewline
177 & 0.938141 & 0.123717 & 0.0618587 \tabularnewline
178 & 0.937141 & 0.125718 & 0.0628589 \tabularnewline
179 & 0.92747 & 0.145061 & 0.0725305 \tabularnewline
180 & 0.936326 & 0.127347 & 0.0636736 \tabularnewline
181 & 0.937477 & 0.125046 & 0.0625228 \tabularnewline
182 & 0.925957 & 0.148086 & 0.0740429 \tabularnewline
183 & 0.918682 & 0.162635 & 0.0813175 \tabularnewline
184 & 0.904732 & 0.190536 & 0.095268 \tabularnewline
185 & 0.918403 & 0.163194 & 0.0815971 \tabularnewline
186 & 0.905463 & 0.189075 & 0.0945373 \tabularnewline
187 & 0.936715 & 0.12657 & 0.0632848 \tabularnewline
188 & 0.929688 & 0.140623 & 0.0703117 \tabularnewline
189 & 0.921168 & 0.157664 & 0.0788322 \tabularnewline
190 & 0.906299 & 0.187403 & 0.0937014 \tabularnewline
191 & 0.890993 & 0.218015 & 0.109007 \tabularnewline
192 & 0.880727 & 0.238546 & 0.119273 \tabularnewline
193 & 0.87421 & 0.25158 & 0.12579 \tabularnewline
194 & 0.883472 & 0.233057 & 0.116528 \tabularnewline
195 & 0.876269 & 0.247461 & 0.123731 \tabularnewline
196 & 0.865109 & 0.269782 & 0.134891 \tabularnewline
197 & 0.879209 & 0.241582 & 0.120791 \tabularnewline
198 & 0.858454 & 0.283092 & 0.141546 \tabularnewline
199 & 0.881332 & 0.237336 & 0.118668 \tabularnewline
200 & 0.86708 & 0.26584 & 0.13292 \tabularnewline
201 & 0.853091 & 0.293818 & 0.146909 \tabularnewline
202 & 0.84941 & 0.301179 & 0.15059 \tabularnewline
203 & 0.831593 & 0.336814 & 0.168407 \tabularnewline
204 & 0.808485 & 0.383031 & 0.191515 \tabularnewline
205 & 0.787319 & 0.425362 & 0.212681 \tabularnewline
206 & 0.824879 & 0.350242 & 0.175121 \tabularnewline
207 & 0.818815 & 0.36237 & 0.181185 \tabularnewline
208 & 0.840045 & 0.319911 & 0.159955 \tabularnewline
209 & 0.816116 & 0.367768 & 0.183884 \tabularnewline
210 & 0.793085 & 0.41383 & 0.206915 \tabularnewline
211 & 0.786705 & 0.426589 & 0.213295 \tabularnewline
212 & 0.760462 & 0.479075 & 0.239538 \tabularnewline
213 & 0.788289 & 0.423422 & 0.211711 \tabularnewline
214 & 0.760991 & 0.478017 & 0.239009 \tabularnewline
215 & 0.737583 & 0.524833 & 0.262417 \tabularnewline
216 & 0.712822 & 0.574356 & 0.287178 \tabularnewline
217 & 0.695539 & 0.608922 & 0.304461 \tabularnewline
218 & 0.688063 & 0.623874 & 0.311937 \tabularnewline
219 & 0.656342 & 0.687317 & 0.343658 \tabularnewline
220 & 0.61548 & 0.76904 & 0.38452 \tabularnewline
221 & 0.578437 & 0.843127 & 0.421563 \tabularnewline
222 & 0.584662 & 0.830675 & 0.415338 \tabularnewline
223 & 0.547849 & 0.904302 & 0.452151 \tabularnewline
224 & 0.512899 & 0.974201 & 0.487101 \tabularnewline
225 & 0.516183 & 0.967634 & 0.483817 \tabularnewline
226 & 0.544669 & 0.910662 & 0.455331 \tabularnewline
227 & 0.543912 & 0.912177 & 0.456088 \tabularnewline
228 & 0.6219 & 0.756199 & 0.3781 \tabularnewline
229 & 0.589274 & 0.821451 & 0.410726 \tabularnewline
230 & 0.593007 & 0.813986 & 0.406993 \tabularnewline
231 & 0.633523 & 0.732954 & 0.366477 \tabularnewline
232 & 0.590979 & 0.818041 & 0.409021 \tabularnewline
233 & 0.574239 & 0.851523 & 0.425761 \tabularnewline
234 & 0.543075 & 0.913851 & 0.456925 \tabularnewline
235 & 0.500728 & 0.998544 & 0.499272 \tabularnewline
236 & 0.670288 & 0.659423 & 0.329712 \tabularnewline
237 & 0.641961 & 0.716079 & 0.358039 \tabularnewline
238 & 0.682146 & 0.635708 & 0.317854 \tabularnewline
239 & 0.65226 & 0.69548 & 0.34774 \tabularnewline
240 & 0.610438 & 0.779124 & 0.389562 \tabularnewline
241 & 0.581184 & 0.837633 & 0.418816 \tabularnewline
242 & 0.62409 & 0.751819 & 0.37591 \tabularnewline
243 & 0.607894 & 0.784212 & 0.392106 \tabularnewline
244 & 0.596276 & 0.807448 & 0.403724 \tabularnewline
245 & 0.548736 & 0.902528 & 0.451264 \tabularnewline
246 & 0.49146 & 0.982919 & 0.50854 \tabularnewline
247 & 0.434681 & 0.869363 & 0.565319 \tabularnewline
248 & 0.378072 & 0.756144 & 0.621928 \tabularnewline
249 & 0.342247 & 0.684494 & 0.657753 \tabularnewline
250 & 0.300065 & 0.60013 & 0.699935 \tabularnewline
251 & 0.294047 & 0.588094 & 0.705953 \tabularnewline
252 & 0.328017 & 0.656033 & 0.671983 \tabularnewline
253 & 0.27937 & 0.55874 & 0.72063 \tabularnewline
254 & 0.231209 & 0.462419 & 0.768791 \tabularnewline
255 & 0.27176 & 0.543521 & 0.72824 \tabularnewline
256 & 0.23636 & 0.472719 & 0.76364 \tabularnewline
257 & 0.252598 & 0.505197 & 0.747402 \tabularnewline
258 & 0.825048 & 0.349905 & 0.174952 \tabularnewline
259 & 0.791462 & 0.417076 & 0.208538 \tabularnewline
260 & 0.999548 & 0.000904683 & 0.000452342 \tabularnewline
261 & 0.999993 & 1.38105e-05 & 6.90523e-06 \tabularnewline
262 & 0.999981 & 3.74244e-05 & 1.87122e-05 \tabularnewline
263 & 0.999977 & 4.62276e-05 & 2.31138e-05 \tabularnewline
264 & 0.999971 & 5.83285e-05 & 2.91642e-05 \tabularnewline
265 & 0.999919 & 0.000162739 & 8.13696e-05 \tabularnewline
266 & 0.999642 & 0.000715001 & 0.0003575 \tabularnewline
267 & 0.999191 & 0.00161792 & 0.000808962 \tabularnewline
268 & 0.996642 & 0.00671518 & 0.00335759 \tabularnewline
269 & 0.98717 & 0.0256607 & 0.0128303 \tabularnewline
270 & 0.965629 & 0.0687411 & 0.0343706 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266991&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]8[/C][C]0.917817[/C][C]0.164366[/C][C]0.082183[/C][/ROW]
[ROW][C]9[/C][C]0.925244[/C][C]0.149512[/C][C]0.0747559[/C][/ROW]
[ROW][C]10[/C][C]0.926449[/C][C]0.147103[/C][C]0.0735515[/C][/ROW]
[ROW][C]11[/C][C]0.877534[/C][C]0.244932[/C][C]0.122466[/C][/ROW]
[ROW][C]12[/C][C]0.902904[/C][C]0.194193[/C][C]0.0970963[/C][/ROW]
[ROW][C]13[/C][C]0.873793[/C][C]0.252415[/C][C]0.126207[/C][/ROW]
[ROW][C]14[/C][C]0.81905[/C][C]0.3619[/C][C]0.18095[/C][/ROW]
[ROW][C]15[/C][C]0.756422[/C][C]0.487156[/C][C]0.243578[/C][/ROW]
[ROW][C]16[/C][C]0.731781[/C][C]0.536438[/C][C]0.268219[/C][/ROW]
[ROW][C]17[/C][C]0.68517[/C][C]0.62966[/C][C]0.31483[/C][/ROW]
[ROW][C]18[/C][C]0.612493[/C][C]0.775014[/C][C]0.387507[/C][/ROW]
[ROW][C]19[/C][C]0.55959[/C][C]0.880819[/C][C]0.44041[/C][/ROW]
[ROW][C]20[/C][C]0.492879[/C][C]0.985757[/C][C]0.507121[/C][/ROW]
[ROW][C]21[/C][C]0.600933[/C][C]0.798134[/C][C]0.399067[/C][/ROW]
[ROW][C]22[/C][C]0.633859[/C][C]0.732281[/C][C]0.366141[/C][/ROW]
[ROW][C]23[/C][C]0.56799[/C][C]0.86402[/C][C]0.43201[/C][/ROW]
[ROW][C]24[/C][C]0.512864[/C][C]0.974273[/C][C]0.487136[/C][/ROW]
[ROW][C]25[/C][C]0.452866[/C][C]0.905731[/C][C]0.547134[/C][/ROW]
[ROW][C]26[/C][C]0.403821[/C][C]0.807642[/C][C]0.596179[/C][/ROW]
[ROW][C]27[/C][C]0.344632[/C][C]0.689265[/C][C]0.655368[/C][/ROW]
[ROW][C]28[/C][C]0.38093[/C][C]0.761861[/C][C]0.61907[/C][/ROW]
[ROW][C]29[/C][C]0.359312[/C][C]0.718624[/C][C]0.640688[/C][/ROW]
[ROW][C]30[/C][C]0.32917[/C][C]0.65834[/C][C]0.67083[/C][/ROW]
[ROW][C]31[/C][C]0.300773[/C][C]0.601547[/C][C]0.699227[/C][/ROW]
[ROW][C]32[/C][C]0.301789[/C][C]0.603577[/C][C]0.698211[/C][/ROW]
[ROW][C]33[/C][C]0.257704[/C][C]0.515408[/C][C]0.742296[/C][/ROW]
[ROW][C]34[/C][C]0.26355[/C][C]0.527099[/C][C]0.73645[/C][/ROW]
[ROW][C]35[/C][C]0.227826[/C][C]0.455652[/C][C]0.772174[/C][/ROW]
[ROW][C]36[/C][C]0.202011[/C][C]0.404022[/C][C]0.797989[/C][/ROW]
[ROW][C]37[/C][C]0.166154[/C][C]0.332308[/C][C]0.833846[/C][/ROW]
[ROW][C]38[/C][C]0.178257[/C][C]0.356513[/C][C]0.821743[/C][/ROW]
[ROW][C]39[/C][C]0.221367[/C][C]0.442733[/C][C]0.778633[/C][/ROW]
[ROW][C]40[/C][C]0.196679[/C][C]0.393358[/C][C]0.803321[/C][/ROW]
[ROW][C]41[/C][C]0.333013[/C][C]0.666026[/C][C]0.666987[/C][/ROW]
[ROW][C]42[/C][C]0.300202[/C][C]0.600403[/C][C]0.699798[/C][/ROW]
[ROW][C]43[/C][C]0.275696[/C][C]0.551391[/C][C]0.724304[/C][/ROW]
[ROW][C]44[/C][C]0.241034[/C][C]0.482069[/C][C]0.758966[/C][/ROW]
[ROW][C]45[/C][C]0.227538[/C][C]0.455077[/C][C]0.772462[/C][/ROW]
[ROW][C]46[/C][C]0.195948[/C][C]0.391896[/C][C]0.804052[/C][/ROW]
[ROW][C]47[/C][C]0.168468[/C][C]0.336936[/C][C]0.831532[/C][/ROW]
[ROW][C]48[/C][C]0.249793[/C][C]0.499586[/C][C]0.750207[/C][/ROW]
[ROW][C]49[/C][C]0.266904[/C][C]0.533808[/C][C]0.733096[/C][/ROW]
[ROW][C]50[/C][C]0.270073[/C][C]0.540146[/C][C]0.729927[/C][/ROW]
[ROW][C]51[/C][C]0.23722[/C][C]0.474441[/C][C]0.76278[/C][/ROW]
[ROW][C]52[/C][C]0.27373[/C][C]0.54746[/C][C]0.72627[/C][/ROW]
[ROW][C]53[/C][C]0.252861[/C][C]0.505723[/C][C]0.747139[/C][/ROW]
[ROW][C]54[/C][C]0.260603[/C][C]0.521206[/C][C]0.739397[/C][/ROW]
[ROW][C]55[/C][C]0.276301[/C][C]0.552602[/C][C]0.723699[/C][/ROW]
[ROW][C]56[/C][C]0.247772[/C][C]0.495544[/C][C]0.752228[/C][/ROW]
[ROW][C]57[/C][C]0.372759[/C][C]0.745518[/C][C]0.627241[/C][/ROW]
[ROW][C]58[/C][C]0.46016[/C][C]0.920319[/C][C]0.53984[/C][/ROW]
[ROW][C]59[/C][C]0.419876[/C][C]0.839752[/C][C]0.580124[/C][/ROW]
[ROW][C]60[/C][C]0.442316[/C][C]0.884632[/C][C]0.557684[/C][/ROW]
[ROW][C]61[/C][C]0.444154[/C][C]0.888307[/C][C]0.555846[/C][/ROW]
[ROW][C]62[/C][C]0.428262[/C][C]0.856524[/C][C]0.571738[/C][/ROW]
[ROW][C]63[/C][C]0.477499[/C][C]0.954997[/C][C]0.522501[/C][/ROW]
[ROW][C]64[/C][C]0.537975[/C][C]0.924051[/C][C]0.462025[/C][/ROW]
[ROW][C]65[/C][C]0.51682[/C][C]0.96636[/C][C]0.48318[/C][/ROW]
[ROW][C]66[/C][C]0.483029[/C][C]0.966059[/C][C]0.516971[/C][/ROW]
[ROW][C]67[/C][C]0.473617[/C][C]0.947234[/C][C]0.526383[/C][/ROW]
[ROW][C]68[/C][C]0.43437[/C][C]0.86874[/C][C]0.56563[/C][/ROW]
[ROW][C]69[/C][C]0.450666[/C][C]0.901333[/C][C]0.549334[/C][/ROW]
[ROW][C]70[/C][C]0.4278[/C][C]0.855601[/C][C]0.5722[/C][/ROW]
[ROW][C]71[/C][C]0.396698[/C][C]0.793397[/C][C]0.603302[/C][/ROW]
[ROW][C]72[/C][C]0.366323[/C][C]0.732647[/C][C]0.633677[/C][/ROW]
[ROW][C]73[/C][C]0.341931[/C][C]0.683862[/C][C]0.658069[/C][/ROW]
[ROW][C]74[/C][C]0.343192[/C][C]0.686384[/C][C]0.656808[/C][/ROW]
[ROW][C]75[/C][C]0.326818[/C][C]0.653637[/C][C]0.673182[/C][/ROW]
[ROW][C]76[/C][C]0.304402[/C][C]0.608805[/C][C]0.695598[/C][/ROW]
[ROW][C]77[/C][C]0.296619[/C][C]0.593239[/C][C]0.703381[/C][/ROW]
[ROW][C]78[/C][C]0.287515[/C][C]0.575029[/C][C]0.712485[/C][/ROW]
[ROW][C]79[/C][C]0.265398[/C][C]0.530797[/C][C]0.734602[/C][/ROW]
[ROW][C]80[/C][C]0.327834[/C][C]0.655668[/C][C]0.672166[/C][/ROW]
[ROW][C]81[/C][C]0.299279[/C][C]0.598557[/C][C]0.700721[/C][/ROW]
[ROW][C]82[/C][C]0.323864[/C][C]0.647727[/C][C]0.676136[/C][/ROW]
[ROW][C]83[/C][C]0.295677[/C][C]0.591354[/C][C]0.704323[/C][/ROW]
[ROW][C]84[/C][C]0.41156[/C][C]0.823119[/C][C]0.58844[/C][/ROW]
[ROW][C]85[/C][C]0.39729[/C][C]0.794581[/C][C]0.60271[/C][/ROW]
[ROW][C]86[/C][C]0.36478[/C][C]0.72956[/C][C]0.63522[/C][/ROW]
[ROW][C]87[/C][C]0.333722[/C][C]0.667443[/C][C]0.666278[/C][/ROW]
[ROW][C]88[/C][C]0.30391[/C][C]0.607821[/C][C]0.69609[/C][/ROW]
[ROW][C]89[/C][C]0.303721[/C][C]0.607442[/C][C]0.696279[/C][/ROW]
[ROW][C]90[/C][C]0.322305[/C][C]0.644611[/C][C]0.677695[/C][/ROW]
[ROW][C]91[/C][C]0.335473[/C][C]0.670946[/C][C]0.664527[/C][/ROW]
[ROW][C]92[/C][C]0.473[/C][C]0.946001[/C][C]0.527[/C][/ROW]
[ROW][C]93[/C][C]0.448355[/C][C]0.896711[/C][C]0.551645[/C][/ROW]
[ROW][C]94[/C][C]0.441634[/C][C]0.883268[/C][C]0.558366[/C][/ROW]
[ROW][C]95[/C][C]0.489864[/C][C]0.979729[/C][C]0.510136[/C][/ROW]
[ROW][C]96[/C][C]0.470327[/C][C]0.940654[/C][C]0.529673[/C][/ROW]
[ROW][C]97[/C][C]0.49674[/C][C]0.993481[/C][C]0.50326[/C][/ROW]
[ROW][C]98[/C][C]0.477966[/C][C]0.955932[/C][C]0.522034[/C][/ROW]
[ROW][C]99[/C][C]0.543446[/C][C]0.913108[/C][C]0.456554[/C][/ROW]
[ROW][C]100[/C][C]0.6453[/C][C]0.709401[/C][C]0.3547[/C][/ROW]
[ROW][C]101[/C][C]0.618502[/C][C]0.762995[/C][C]0.381498[/C][/ROW]
[ROW][C]102[/C][C]0.595443[/C][C]0.809113[/C][C]0.404557[/C][/ROW]
[ROW][C]103[/C][C]0.591839[/C][C]0.816323[/C][C]0.408161[/C][/ROW]
[ROW][C]104[/C][C]0.61041[/C][C]0.779181[/C][C]0.38959[/C][/ROW]
[ROW][C]105[/C][C]0.641018[/C][C]0.717965[/C][C]0.358982[/C][/ROW]
[ROW][C]106[/C][C]0.666394[/C][C]0.667211[/C][C]0.333606[/C][/ROW]
[ROW][C]107[/C][C]0.671474[/C][C]0.657051[/C][C]0.328526[/C][/ROW]
[ROW][C]108[/C][C]0.816155[/C][C]0.36769[/C][C]0.183845[/C][/ROW]
[ROW][C]109[/C][C]0.865544[/C][C]0.268911[/C][C]0.134456[/C][/ROW]
[ROW][C]110[/C][C]0.871556[/C][C]0.256888[/C][C]0.128444[/C][/ROW]
[ROW][C]111[/C][C]0.861698[/C][C]0.276604[/C][C]0.138302[/C][/ROW]
[ROW][C]112[/C][C]0.851806[/C][C]0.296388[/C][C]0.148194[/C][/ROW]
[ROW][C]113[/C][C]0.905842[/C][C]0.188316[/C][C]0.094158[/C][/ROW]
[ROW][C]114[/C][C]0.909689[/C][C]0.180622[/C][C]0.090311[/C][/ROW]
[ROW][C]115[/C][C]0.923232[/C][C]0.153535[/C][C]0.0767675[/C][/ROW]
[ROW][C]116[/C][C]0.936374[/C][C]0.127251[/C][C]0.0636255[/C][/ROW]
[ROW][C]117[/C][C]0.92603[/C][C]0.14794[/C][C]0.0739702[/C][/ROW]
[ROW][C]118[/C][C]0.933195[/C][C]0.13361[/C][C]0.0668048[/C][/ROW]
[ROW][C]119[/C][C]0.924323[/C][C]0.151354[/C][C]0.0756771[/C][/ROW]
[ROW][C]120[/C][C]0.932694[/C][C]0.134613[/C][C]0.0673065[/C][/ROW]
[ROW][C]121[/C][C]0.939989[/C][C]0.120022[/C][C]0.0600112[/C][/ROW]
[ROW][C]122[/C][C]0.959465[/C][C]0.0810709[/C][C]0.0405354[/C][/ROW]
[ROW][C]123[/C][C]0.954712[/C][C]0.0905769[/C][C]0.0452885[/C][/ROW]
[ROW][C]124[/C][C]0.976165[/C][C]0.0476695[/C][C]0.0238347[/C][/ROW]
[ROW][C]125[/C][C]0.978839[/C][C]0.0423219[/C][C]0.0211609[/C][/ROW]
[ROW][C]126[/C][C]0.974607[/C][C]0.0507864[/C][C]0.0253932[/C][/ROW]
[ROW][C]127[/C][C]0.971199[/C][C]0.0576018[/C][C]0.0288009[/C][/ROW]
[ROW][C]128[/C][C]0.971297[/C][C]0.0574061[/C][C]0.028703[/C][/ROW]
[ROW][C]129[/C][C]0.971774[/C][C]0.056451[/C][C]0.0282255[/C][/ROW]
[ROW][C]130[/C][C]0.970695[/C][C]0.058611[/C][C]0.0293055[/C][/ROW]
[ROW][C]131[/C][C]0.96817[/C][C]0.0636603[/C][C]0.0318302[/C][/ROW]
[ROW][C]132[/C][C]0.964534[/C][C]0.0709325[/C][C]0.0354663[/C][/ROW]
[ROW][C]133[/C][C]0.962294[/C][C]0.0754122[/C][C]0.0377061[/C][/ROW]
[ROW][C]134[/C][C]0.955786[/C][C]0.0884272[/C][C]0.0442136[/C][/ROW]
[ROW][C]135[/C][C]0.950209[/C][C]0.0995821[/C][C]0.0497911[/C][/ROW]
[ROW][C]136[/C][C]0.942862[/C][C]0.114277[/C][C]0.0571385[/C][/ROW]
[ROW][C]137[/C][C]0.958698[/C][C]0.0826041[/C][C]0.0413021[/C][/ROW]
[ROW][C]138[/C][C]0.967964[/C][C]0.0640722[/C][C]0.0320361[/C][/ROW]
[ROW][C]139[/C][C]0.961965[/C][C]0.0760698[/C][C]0.0380349[/C][/ROW]
[ROW][C]140[/C][C]0.955045[/C][C]0.08991[/C][C]0.044955[/C][/ROW]
[ROW][C]141[/C][C]0.947748[/C][C]0.104504[/C][C]0.0522522[/C][/ROW]
[ROW][C]142[/C][C]0.955188[/C][C]0.0896243[/C][C]0.0448122[/C][/ROW]
[ROW][C]143[/C][C]0.953003[/C][C]0.0939943[/C][C]0.0469971[/C][/ROW]
[ROW][C]144[/C][C]0.948479[/C][C]0.103042[/C][C]0.051521[/C][/ROW]
[ROW][C]145[/C][C]0.940564[/C][C]0.118873[/C][C]0.0594364[/C][/ROW]
[ROW][C]146[/C][C]0.935815[/C][C]0.12837[/C][C]0.064185[/C][/ROW]
[ROW][C]147[/C][C]0.928693[/C][C]0.142615[/C][C]0.0713075[/C][/ROW]
[ROW][C]148[/C][C]0.917878[/C][C]0.164244[/C][C]0.0821222[/C][/ROW]
[ROW][C]149[/C][C]0.923539[/C][C]0.152922[/C][C]0.0764608[/C][/ROW]
[ROW][C]150[/C][C]0.916946[/C][C]0.166108[/C][C]0.0830541[/C][/ROW]
[ROW][C]151[/C][C]0.966727[/C][C]0.0665469[/C][C]0.0332734[/C][/ROW]
[ROW][C]152[/C][C]0.963158[/C][C]0.073685[/C][C]0.0368425[/C][/ROW]
[ROW][C]153[/C][C]0.960092[/C][C]0.0798152[/C][C]0.0399076[/C][/ROW]
[ROW][C]154[/C][C]0.952376[/C][C]0.0952474[/C][C]0.0476237[/C][/ROW]
[ROW][C]155[/C][C]0.960339[/C][C]0.0793223[/C][C]0.0396612[/C][/ROW]
[ROW][C]156[/C][C]0.95306[/C][C]0.0938806[/C][C]0.0469403[/C][/ROW]
[ROW][C]157[/C][C]0.949845[/C][C]0.10031[/C][C]0.0501551[/C][/ROW]
[ROW][C]158[/C][C]0.948235[/C][C]0.10353[/C][C]0.051765[/C][/ROW]
[ROW][C]159[/C][C]0.941284[/C][C]0.117432[/C][C]0.058716[/C][/ROW]
[ROW][C]160[/C][C]0.931805[/C][C]0.136391[/C][C]0.0681953[/C][/ROW]
[ROW][C]161[/C][C]0.947754[/C][C]0.104493[/C][C]0.0522463[/C][/ROW]
[ROW][C]162[/C][C]0.939083[/C][C]0.121834[/C][C]0.0609171[/C][/ROW]
[ROW][C]163[/C][C]0.931021[/C][C]0.137959[/C][C]0.0689793[/C][/ROW]
[ROW][C]164[/C][C]0.966572[/C][C]0.0668562[/C][C]0.0334281[/C][/ROW]
[ROW][C]165[/C][C]0.969527[/C][C]0.0609461[/C][C]0.030473[/C][/ROW]
[ROW][C]166[/C][C]0.965808[/C][C]0.0683844[/C][C]0.0341922[/C][/ROW]
[ROW][C]167[/C][C]0.961833[/C][C]0.0763331[/C][C]0.0381665[/C][/ROW]
[ROW][C]168[/C][C]0.971163[/C][C]0.0576739[/C][C]0.028837[/C][/ROW]
[ROW][C]169[/C][C]0.964713[/C][C]0.0705736[/C][C]0.0352868[/C][/ROW]
[ROW][C]170[/C][C]0.965729[/C][C]0.0685423[/C][C]0.0342712[/C][/ROW]
[ROW][C]171[/C][C]0.958849[/C][C]0.0823019[/C][C]0.0411509[/C][/ROW]
[ROW][C]172[/C][C]0.96574[/C][C]0.0685204[/C][C]0.0342602[/C][/ROW]
[ROW][C]173[/C][C]0.960282[/C][C]0.0794353[/C][C]0.0397177[/C][/ROW]
[ROW][C]174[/C][C]0.951879[/C][C]0.0962414[/C][C]0.0481207[/C][/ROW]
[ROW][C]175[/C][C]0.942089[/C][C]0.115822[/C][C]0.0579112[/C][/ROW]
[ROW][C]176[/C][C]0.943937[/C][C]0.112125[/C][C]0.0560627[/C][/ROW]
[ROW][C]177[/C][C]0.938141[/C][C]0.123717[/C][C]0.0618587[/C][/ROW]
[ROW][C]178[/C][C]0.937141[/C][C]0.125718[/C][C]0.0628589[/C][/ROW]
[ROW][C]179[/C][C]0.92747[/C][C]0.145061[/C][C]0.0725305[/C][/ROW]
[ROW][C]180[/C][C]0.936326[/C][C]0.127347[/C][C]0.0636736[/C][/ROW]
[ROW][C]181[/C][C]0.937477[/C][C]0.125046[/C][C]0.0625228[/C][/ROW]
[ROW][C]182[/C][C]0.925957[/C][C]0.148086[/C][C]0.0740429[/C][/ROW]
[ROW][C]183[/C][C]0.918682[/C][C]0.162635[/C][C]0.0813175[/C][/ROW]
[ROW][C]184[/C][C]0.904732[/C][C]0.190536[/C][C]0.095268[/C][/ROW]
[ROW][C]185[/C][C]0.918403[/C][C]0.163194[/C][C]0.0815971[/C][/ROW]
[ROW][C]186[/C][C]0.905463[/C][C]0.189075[/C][C]0.0945373[/C][/ROW]
[ROW][C]187[/C][C]0.936715[/C][C]0.12657[/C][C]0.0632848[/C][/ROW]
[ROW][C]188[/C][C]0.929688[/C][C]0.140623[/C][C]0.0703117[/C][/ROW]
[ROW][C]189[/C][C]0.921168[/C][C]0.157664[/C][C]0.0788322[/C][/ROW]
[ROW][C]190[/C][C]0.906299[/C][C]0.187403[/C][C]0.0937014[/C][/ROW]
[ROW][C]191[/C][C]0.890993[/C][C]0.218015[/C][C]0.109007[/C][/ROW]
[ROW][C]192[/C][C]0.880727[/C][C]0.238546[/C][C]0.119273[/C][/ROW]
[ROW][C]193[/C][C]0.87421[/C][C]0.25158[/C][C]0.12579[/C][/ROW]
[ROW][C]194[/C][C]0.883472[/C][C]0.233057[/C][C]0.116528[/C][/ROW]
[ROW][C]195[/C][C]0.876269[/C][C]0.247461[/C][C]0.123731[/C][/ROW]
[ROW][C]196[/C][C]0.865109[/C][C]0.269782[/C][C]0.134891[/C][/ROW]
[ROW][C]197[/C][C]0.879209[/C][C]0.241582[/C][C]0.120791[/C][/ROW]
[ROW][C]198[/C][C]0.858454[/C][C]0.283092[/C][C]0.141546[/C][/ROW]
[ROW][C]199[/C][C]0.881332[/C][C]0.237336[/C][C]0.118668[/C][/ROW]
[ROW][C]200[/C][C]0.86708[/C][C]0.26584[/C][C]0.13292[/C][/ROW]
[ROW][C]201[/C][C]0.853091[/C][C]0.293818[/C][C]0.146909[/C][/ROW]
[ROW][C]202[/C][C]0.84941[/C][C]0.301179[/C][C]0.15059[/C][/ROW]
[ROW][C]203[/C][C]0.831593[/C][C]0.336814[/C][C]0.168407[/C][/ROW]
[ROW][C]204[/C][C]0.808485[/C][C]0.383031[/C][C]0.191515[/C][/ROW]
[ROW][C]205[/C][C]0.787319[/C][C]0.425362[/C][C]0.212681[/C][/ROW]
[ROW][C]206[/C][C]0.824879[/C][C]0.350242[/C][C]0.175121[/C][/ROW]
[ROW][C]207[/C][C]0.818815[/C][C]0.36237[/C][C]0.181185[/C][/ROW]
[ROW][C]208[/C][C]0.840045[/C][C]0.319911[/C][C]0.159955[/C][/ROW]
[ROW][C]209[/C][C]0.816116[/C][C]0.367768[/C][C]0.183884[/C][/ROW]
[ROW][C]210[/C][C]0.793085[/C][C]0.41383[/C][C]0.206915[/C][/ROW]
[ROW][C]211[/C][C]0.786705[/C][C]0.426589[/C][C]0.213295[/C][/ROW]
[ROW][C]212[/C][C]0.760462[/C][C]0.479075[/C][C]0.239538[/C][/ROW]
[ROW][C]213[/C][C]0.788289[/C][C]0.423422[/C][C]0.211711[/C][/ROW]
[ROW][C]214[/C][C]0.760991[/C][C]0.478017[/C][C]0.239009[/C][/ROW]
[ROW][C]215[/C][C]0.737583[/C][C]0.524833[/C][C]0.262417[/C][/ROW]
[ROW][C]216[/C][C]0.712822[/C][C]0.574356[/C][C]0.287178[/C][/ROW]
[ROW][C]217[/C][C]0.695539[/C][C]0.608922[/C][C]0.304461[/C][/ROW]
[ROW][C]218[/C][C]0.688063[/C][C]0.623874[/C][C]0.311937[/C][/ROW]
[ROW][C]219[/C][C]0.656342[/C][C]0.687317[/C][C]0.343658[/C][/ROW]
[ROW][C]220[/C][C]0.61548[/C][C]0.76904[/C][C]0.38452[/C][/ROW]
[ROW][C]221[/C][C]0.578437[/C][C]0.843127[/C][C]0.421563[/C][/ROW]
[ROW][C]222[/C][C]0.584662[/C][C]0.830675[/C][C]0.415338[/C][/ROW]
[ROW][C]223[/C][C]0.547849[/C][C]0.904302[/C][C]0.452151[/C][/ROW]
[ROW][C]224[/C][C]0.512899[/C][C]0.974201[/C][C]0.487101[/C][/ROW]
[ROW][C]225[/C][C]0.516183[/C][C]0.967634[/C][C]0.483817[/C][/ROW]
[ROW][C]226[/C][C]0.544669[/C][C]0.910662[/C][C]0.455331[/C][/ROW]
[ROW][C]227[/C][C]0.543912[/C][C]0.912177[/C][C]0.456088[/C][/ROW]
[ROW][C]228[/C][C]0.6219[/C][C]0.756199[/C][C]0.3781[/C][/ROW]
[ROW][C]229[/C][C]0.589274[/C][C]0.821451[/C][C]0.410726[/C][/ROW]
[ROW][C]230[/C][C]0.593007[/C][C]0.813986[/C][C]0.406993[/C][/ROW]
[ROW][C]231[/C][C]0.633523[/C][C]0.732954[/C][C]0.366477[/C][/ROW]
[ROW][C]232[/C][C]0.590979[/C][C]0.818041[/C][C]0.409021[/C][/ROW]
[ROW][C]233[/C][C]0.574239[/C][C]0.851523[/C][C]0.425761[/C][/ROW]
[ROW][C]234[/C][C]0.543075[/C][C]0.913851[/C][C]0.456925[/C][/ROW]
[ROW][C]235[/C][C]0.500728[/C][C]0.998544[/C][C]0.499272[/C][/ROW]
[ROW][C]236[/C][C]0.670288[/C][C]0.659423[/C][C]0.329712[/C][/ROW]
[ROW][C]237[/C][C]0.641961[/C][C]0.716079[/C][C]0.358039[/C][/ROW]
[ROW][C]238[/C][C]0.682146[/C][C]0.635708[/C][C]0.317854[/C][/ROW]
[ROW][C]239[/C][C]0.65226[/C][C]0.69548[/C][C]0.34774[/C][/ROW]
[ROW][C]240[/C][C]0.610438[/C][C]0.779124[/C][C]0.389562[/C][/ROW]
[ROW][C]241[/C][C]0.581184[/C][C]0.837633[/C][C]0.418816[/C][/ROW]
[ROW][C]242[/C][C]0.62409[/C][C]0.751819[/C][C]0.37591[/C][/ROW]
[ROW][C]243[/C][C]0.607894[/C][C]0.784212[/C][C]0.392106[/C][/ROW]
[ROW][C]244[/C][C]0.596276[/C][C]0.807448[/C][C]0.403724[/C][/ROW]
[ROW][C]245[/C][C]0.548736[/C][C]0.902528[/C][C]0.451264[/C][/ROW]
[ROW][C]246[/C][C]0.49146[/C][C]0.982919[/C][C]0.50854[/C][/ROW]
[ROW][C]247[/C][C]0.434681[/C][C]0.869363[/C][C]0.565319[/C][/ROW]
[ROW][C]248[/C][C]0.378072[/C][C]0.756144[/C][C]0.621928[/C][/ROW]
[ROW][C]249[/C][C]0.342247[/C][C]0.684494[/C][C]0.657753[/C][/ROW]
[ROW][C]250[/C][C]0.300065[/C][C]0.60013[/C][C]0.699935[/C][/ROW]
[ROW][C]251[/C][C]0.294047[/C][C]0.588094[/C][C]0.705953[/C][/ROW]
[ROW][C]252[/C][C]0.328017[/C][C]0.656033[/C][C]0.671983[/C][/ROW]
[ROW][C]253[/C][C]0.27937[/C][C]0.55874[/C][C]0.72063[/C][/ROW]
[ROW][C]254[/C][C]0.231209[/C][C]0.462419[/C][C]0.768791[/C][/ROW]
[ROW][C]255[/C][C]0.27176[/C][C]0.543521[/C][C]0.72824[/C][/ROW]
[ROW][C]256[/C][C]0.23636[/C][C]0.472719[/C][C]0.76364[/C][/ROW]
[ROW][C]257[/C][C]0.252598[/C][C]0.505197[/C][C]0.747402[/C][/ROW]
[ROW][C]258[/C][C]0.825048[/C][C]0.349905[/C][C]0.174952[/C][/ROW]
[ROW][C]259[/C][C]0.791462[/C][C]0.417076[/C][C]0.208538[/C][/ROW]
[ROW][C]260[/C][C]0.999548[/C][C]0.000904683[/C][C]0.000452342[/C][/ROW]
[ROW][C]261[/C][C]0.999993[/C][C]1.38105e-05[/C][C]6.90523e-06[/C][/ROW]
[ROW][C]262[/C][C]0.999981[/C][C]3.74244e-05[/C][C]1.87122e-05[/C][/ROW]
[ROW][C]263[/C][C]0.999977[/C][C]4.62276e-05[/C][C]2.31138e-05[/C][/ROW]
[ROW][C]264[/C][C]0.999971[/C][C]5.83285e-05[/C][C]2.91642e-05[/C][/ROW]
[ROW][C]265[/C][C]0.999919[/C][C]0.000162739[/C][C]8.13696e-05[/C][/ROW]
[ROW][C]266[/C][C]0.999642[/C][C]0.000715001[/C][C]0.0003575[/C][/ROW]
[ROW][C]267[/C][C]0.999191[/C][C]0.00161792[/C][C]0.000808962[/C][/ROW]
[ROW][C]268[/C][C]0.996642[/C][C]0.00671518[/C][C]0.00335759[/C][/ROW]
[ROW][C]269[/C][C]0.98717[/C][C]0.0256607[/C][C]0.0128303[/C][/ROW]
[ROW][C]270[/C][C]0.965629[/C][C]0.0687411[/C][C]0.0343706[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266991&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266991&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.9178170.1643660.082183
90.9252440.1495120.0747559
100.9264490.1471030.0735515
110.8775340.2449320.122466
120.9029040.1941930.0970963
130.8737930.2524150.126207
140.819050.36190.18095
150.7564220.4871560.243578
160.7317810.5364380.268219
170.685170.629660.31483
180.6124930.7750140.387507
190.559590.8808190.44041
200.4928790.9857570.507121
210.6009330.7981340.399067
220.6338590.7322810.366141
230.567990.864020.43201
240.5128640.9742730.487136
250.4528660.9057310.547134
260.4038210.8076420.596179
270.3446320.6892650.655368
280.380930.7618610.61907
290.3593120.7186240.640688
300.329170.658340.67083
310.3007730.6015470.699227
320.3017890.6035770.698211
330.2577040.5154080.742296
340.263550.5270990.73645
350.2278260.4556520.772174
360.2020110.4040220.797989
370.1661540.3323080.833846
380.1782570.3565130.821743
390.2213670.4427330.778633
400.1966790.3933580.803321
410.3330130.6660260.666987
420.3002020.6004030.699798
430.2756960.5513910.724304
440.2410340.4820690.758966
450.2275380.4550770.772462
460.1959480.3918960.804052
470.1684680.3369360.831532
480.2497930.4995860.750207
490.2669040.5338080.733096
500.2700730.5401460.729927
510.237220.4744410.76278
520.273730.547460.72627
530.2528610.5057230.747139
540.2606030.5212060.739397
550.2763010.5526020.723699
560.2477720.4955440.752228
570.3727590.7455180.627241
580.460160.9203190.53984
590.4198760.8397520.580124
600.4423160.8846320.557684
610.4441540.8883070.555846
620.4282620.8565240.571738
630.4774990.9549970.522501
640.5379750.9240510.462025
650.516820.966360.48318
660.4830290.9660590.516971
670.4736170.9472340.526383
680.434370.868740.56563
690.4506660.9013330.549334
700.42780.8556010.5722
710.3966980.7933970.603302
720.3663230.7326470.633677
730.3419310.6838620.658069
740.3431920.6863840.656808
750.3268180.6536370.673182
760.3044020.6088050.695598
770.2966190.5932390.703381
780.2875150.5750290.712485
790.2653980.5307970.734602
800.3278340.6556680.672166
810.2992790.5985570.700721
820.3238640.6477270.676136
830.2956770.5913540.704323
840.411560.8231190.58844
850.397290.7945810.60271
860.364780.729560.63522
870.3337220.6674430.666278
880.303910.6078210.69609
890.3037210.6074420.696279
900.3223050.6446110.677695
910.3354730.6709460.664527
920.4730.9460010.527
930.4483550.8967110.551645
940.4416340.8832680.558366
950.4898640.9797290.510136
960.4703270.9406540.529673
970.496740.9934810.50326
980.4779660.9559320.522034
990.5434460.9131080.456554
1000.64530.7094010.3547
1010.6185020.7629950.381498
1020.5954430.8091130.404557
1030.5918390.8163230.408161
1040.610410.7791810.38959
1050.6410180.7179650.358982
1060.6663940.6672110.333606
1070.6714740.6570510.328526
1080.8161550.367690.183845
1090.8655440.2689110.134456
1100.8715560.2568880.128444
1110.8616980.2766040.138302
1120.8518060.2963880.148194
1130.9058420.1883160.094158
1140.9096890.1806220.090311
1150.9232320.1535350.0767675
1160.9363740.1272510.0636255
1170.926030.147940.0739702
1180.9331950.133610.0668048
1190.9243230.1513540.0756771
1200.9326940.1346130.0673065
1210.9399890.1200220.0600112
1220.9594650.08107090.0405354
1230.9547120.09057690.0452885
1240.9761650.04766950.0238347
1250.9788390.04232190.0211609
1260.9746070.05078640.0253932
1270.9711990.05760180.0288009
1280.9712970.05740610.028703
1290.9717740.0564510.0282255
1300.9706950.0586110.0293055
1310.968170.06366030.0318302
1320.9645340.07093250.0354663
1330.9622940.07541220.0377061
1340.9557860.08842720.0442136
1350.9502090.09958210.0497911
1360.9428620.1142770.0571385
1370.9586980.08260410.0413021
1380.9679640.06407220.0320361
1390.9619650.07606980.0380349
1400.9550450.089910.044955
1410.9477480.1045040.0522522
1420.9551880.08962430.0448122
1430.9530030.09399430.0469971
1440.9484790.1030420.051521
1450.9405640.1188730.0594364
1460.9358150.128370.064185
1470.9286930.1426150.0713075
1480.9178780.1642440.0821222
1490.9235390.1529220.0764608
1500.9169460.1661080.0830541
1510.9667270.06654690.0332734
1520.9631580.0736850.0368425
1530.9600920.07981520.0399076
1540.9523760.09524740.0476237
1550.9603390.07932230.0396612
1560.953060.09388060.0469403
1570.9498450.100310.0501551
1580.9482350.103530.051765
1590.9412840.1174320.058716
1600.9318050.1363910.0681953
1610.9477540.1044930.0522463
1620.9390830.1218340.0609171
1630.9310210.1379590.0689793
1640.9665720.06685620.0334281
1650.9695270.06094610.030473
1660.9658080.06838440.0341922
1670.9618330.07633310.0381665
1680.9711630.05767390.028837
1690.9647130.07057360.0352868
1700.9657290.06854230.0342712
1710.9588490.08230190.0411509
1720.965740.06852040.0342602
1730.9602820.07943530.0397177
1740.9518790.09624140.0481207
1750.9420890.1158220.0579112
1760.9439370.1121250.0560627
1770.9381410.1237170.0618587
1780.9371410.1257180.0628589
1790.927470.1450610.0725305
1800.9363260.1273470.0636736
1810.9374770.1250460.0625228
1820.9259570.1480860.0740429
1830.9186820.1626350.0813175
1840.9047320.1905360.095268
1850.9184030.1631940.0815971
1860.9054630.1890750.0945373
1870.9367150.126570.0632848
1880.9296880.1406230.0703117
1890.9211680.1576640.0788322
1900.9062990.1874030.0937014
1910.8909930.2180150.109007
1920.8807270.2385460.119273
1930.874210.251580.12579
1940.8834720.2330570.116528
1950.8762690.2474610.123731
1960.8651090.2697820.134891
1970.8792090.2415820.120791
1980.8584540.2830920.141546
1990.8813320.2373360.118668
2000.867080.265840.13292
2010.8530910.2938180.146909
2020.849410.3011790.15059
2030.8315930.3368140.168407
2040.8084850.3830310.191515
2050.7873190.4253620.212681
2060.8248790.3502420.175121
2070.8188150.362370.181185
2080.8400450.3199110.159955
2090.8161160.3677680.183884
2100.7930850.413830.206915
2110.7867050.4265890.213295
2120.7604620.4790750.239538
2130.7882890.4234220.211711
2140.7609910.4780170.239009
2150.7375830.5248330.262417
2160.7128220.5743560.287178
2170.6955390.6089220.304461
2180.6880630.6238740.311937
2190.6563420.6873170.343658
2200.615480.769040.38452
2210.5784370.8431270.421563
2220.5846620.8306750.415338
2230.5478490.9043020.452151
2240.5128990.9742010.487101
2250.5161830.9676340.483817
2260.5446690.9106620.455331
2270.5439120.9121770.456088
2280.62190.7561990.3781
2290.5892740.8214510.410726
2300.5930070.8139860.406993
2310.6335230.7329540.366477
2320.5909790.8180410.409021
2330.5742390.8515230.425761
2340.5430750.9138510.456925
2350.5007280.9985440.499272
2360.6702880.6594230.329712
2370.6419610.7160790.358039
2380.6821460.6357080.317854
2390.652260.695480.34774
2400.6104380.7791240.389562
2410.5811840.8376330.418816
2420.624090.7518190.37591
2430.6078940.7842120.392106
2440.5962760.8074480.403724
2450.5487360.9025280.451264
2460.491460.9829190.50854
2470.4346810.8693630.565319
2480.3780720.7561440.621928
2490.3422470.6844940.657753
2500.3000650.600130.699935
2510.2940470.5880940.705953
2520.3280170.6560330.671983
2530.279370.558740.72063
2540.2312090.4624190.768791
2550.271760.5435210.72824
2560.236360.4727190.76364
2570.2525980.5051970.747402
2580.8250480.3499050.174952
2590.7914620.4170760.208538
2600.9995480.0009046830.000452342
2610.9999931.38105e-056.90523e-06
2620.9999813.74244e-051.87122e-05
2630.9999774.62276e-052.31138e-05
2640.9999715.83285e-052.91642e-05
2650.9999190.0001627398.13696e-05
2660.9996420.0007150010.0003575
2670.9991910.001617920.000808962
2680.9966420.006715180.00335759
2690.987170.02566070.0128303
2700.9656290.06874110.0343706






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level90.0342205NOK
5% type I error level120.0456274OK
10% type I error level480.18251NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 9 & 0.0342205 & NOK \tabularnewline
5% type I error level & 12 & 0.0456274 & OK \tabularnewline
10% type I error level & 48 & 0.18251 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266991&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]9[/C][C]0.0342205[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]12[/C][C]0.0456274[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]48[/C][C]0.18251[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266991&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266991&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level90.0342205NOK
5% type I error level120.0456274OK
10% type I error level480.18251NOK


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
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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')
}