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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 10 Dec 2014 13:41:18 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t1418218999w7nhyzgyj1kgqe7.htm/, Retrieved Sun, 19 May 2024 14:32:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265170, Retrieved Sun, 19 May 2024 14:32:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-10 13:41:18] [cb9023b84cdbf59fe6647357de544f7b] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265170&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265170&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265170&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'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 5.5795 + 0.0135911PRH[t] + 0.0200465Blogged[t] + 0.0220808LFM[t] + 0.0170477t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  5.5795 +  0.0135911PRH[t] +  0.0200465Blogged[t] +  0.0220808LFM[t] +  0.0170477t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265170&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  5.5795 +  0.0135911PRH[t] +  0.0200465Blogged[t] +  0.0220808LFM[t] +  0.0170477t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265170&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265170&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 5.5795 + 0.0135911PRH[t] + 0.0200465Blogged[t] + 0.0220808LFM[t] + 0.0170477t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.57950.7175627.7762.53478e-131.26739e-13
PRH0.01359110.009388081.4480.1490680.0745339
Blogged0.02004650.00253527.9071.10941e-135.54705e-14
LFM0.02208080.004894344.5121.02881e-055.14407e-06
t0.01704770.002685926.3471.1637e-095.8185e-10

\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) & 5.5795 & 0.717562 & 7.776 & 2.53478e-13 & 1.26739e-13 \tabularnewline
PRH & 0.0135911 & 0.00938808 & 1.448 & 0.149068 & 0.0745339 \tabularnewline
Blogged & 0.0200465 & 0.0025352 & 7.907 & 1.10941e-13 & 5.54705e-14 \tabularnewline
LFM & 0.0220808 & 0.00489434 & 4.512 & 1.02881e-05 & 5.14407e-06 \tabularnewline
t & 0.0170477 & 0.00268592 & 6.347 & 1.1637e-09 & 5.8185e-10 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265170&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]5.5795[/C][C]0.717562[/C][C]7.776[/C][C]2.53478e-13[/C][C]1.26739e-13[/C][/ROW]
[ROW][C]PRH[/C][C]0.0135911[/C][C]0.00938808[/C][C]1.448[/C][C]0.149068[/C][C]0.0745339[/C][/ROW]
[ROW][C]Blogged[/C][C]0.0200465[/C][C]0.0025352[/C][C]7.907[/C][C]1.10941e-13[/C][C]5.54705e-14[/C][/ROW]
[ROW][C]LFM[/C][C]0.0220808[/C][C]0.00489434[/C][C]4.512[/C][C]1.02881e-05[/C][C]5.14407e-06[/C][/ROW]
[ROW][C]t[/C][C]0.0170477[/C][C]0.00268592[/C][C]6.347[/C][C]1.1637e-09[/C][C]5.8185e-10[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265170&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265170&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)5.57950.7175627.7762.53478e-131.26739e-13
PRH0.01359110.009388081.4480.1490680.0745339
Blogged0.02004650.00253527.9071.10941e-135.54705e-14
LFM0.02208080.004894344.5121.02881e-055.14407e-06
t0.01704770.002685926.3471.1637e-095.8185e-10






Multiple Linear Regression - Regression Statistics
Multiple R0.66243
R-squared0.438814
Adjusted R-squared0.429011
F-TEST (value)44.766
F-TEST (DF numerator)4
F-TEST (DF denominator)229
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.49987
Sum Squared Residuals1431.1

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.66243 \tabularnewline
R-squared & 0.438814 \tabularnewline
Adjusted R-squared & 0.429011 \tabularnewline
F-TEST (value) & 44.766 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 229 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.49987 \tabularnewline
Sum Squared Residuals & 1431.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265170&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.66243[/C][/ROW]
[ROW][C]R-squared[/C][C]0.438814[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.429011[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]44.766[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]229[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.49987[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1431.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265170&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265170&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 R0.66243
R-squared0.438814
Adjusted R-squared0.429011
F-TEST (value)44.766
F-TEST (DF numerator)4
F-TEST (DF denominator)229
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.49987
Sum Squared Residuals1431.1






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.05571.84431
212.811.17571.6243
37.412.0299-4.6299
46.710.2786-3.57857
512.615.0496-2.44963
614.811.95362.84637
713.311.14972.15032
811.112.4784-1.37836
98.213.0906-4.89064
1011.412.1536-0.753621
116.413.3956-6.99557
121213.4346-1.43464
136.37.98052-1.68052
1411.39.784611.51539
1511.913.2154-1.31537
169.311.0241-1.72407
171010.5376-0.537591
1813.812.70121.09878
1910.813.4039-2.60393
2011.712.0945-0.394485
2110.915.256-4.35604
2216.113.45032.64969
239.910.8786-0.978611
2411.511.5303-0.030338
258.310.4988-2.19876
2611.712.5284-0.828353
27911.4069-2.40693
2810.811.3653-0.565317
2910.411.1691-0.769125
3012.711.81450.885497
3111.813.5269-1.72689
321311.83081.1692
3310.812.1445-1.34445
3412.39.017373.28263
3511.313.5328-2.23278
3611.611.1340.465984
3710.912.2623-1.36231
3812.112.03370.066322
3913.312.62370.676286
4010.112.0622-1.96216
4114.311.71862.58138
429.312.7443-3.44434
4312.511.70470.795285
447.610.0232-2.42317
459.211.9045-2.70451
4614.513.30991.19014
4712.313.9222-1.62224
4812.612.46790.132112
491313.5031-0.503133
5012.610.71631.88372
5113.214.0826-0.882568
527.711.0337-3.33374
5310.510.1610.339014
5410.910.9402-0.0401744
554.39.50364-5.20364
5610.311.0441-0.744096
5711.410.12121.27877
585.610.5587-4.95873
598.810.9194-2.11937
60910.1253-1.12527
619.611.0682-1.46816
626.48.9759-2.5759
6311.610.60760.992401
644.358.86493-4.51493
6512.710.93591.76412
6618.114.11373.98627
6717.8514.4063.44402
6816.614.92061.67936
6912.69.149193.45081
7017.120.5637-3.46365
7119.115.58793.51207
7216.118.1322-2.03219
7313.359.669963.68004
7418.416.33462.06538
7514.79.599865.10014
7610.613.6361-3.03614
7712.612.7687-0.168715
7816.214.27181.92819
7913.616.7548-3.15476
8018.915.65043.24957
8114.111.84482.25518
8214.511.53122.96878
8316.1517.8471-1.69707
8414.7513.05281.69717
8514.813.6731.12701
8612.4511.35191.09812
8712.6513.4986-0.848582
8817.3513.12984.22018
898.610.4236-1.82364
9018.416.74021.65978
9116.116.7873-0.687311
9211.610.43521.16479
9317.7512.7285.02201
9415.2514.28390.966092
9517.6515.22522.42476
9615.613.52332.07666
9716.3514.94161.40844
9817.6514.74012.90986
9913.613.00650.593535
10011.712.4003-0.700291
10114.3513.19661.15344
10214.7516.3764-1.62643
10318.2516.22042.02963
1049.915.2191-5.31913
1051613.9982.00205
10618.2515.58392.66612
10716.8516.893-0.0430061
10814.611.73212.86795
10913.8513.01840.831612
11018.9516.5982.35205
11115.614.19711.40292
11214.8516.4162-1.56617
11311.7512.2654-0.515414
11418.4513.21465.23538
11515.915.62950.270452
11617.114.94562.15437
11716.19.488336.61167
11819.915.73374.16626
11910.9510.56160.388391
12018.4515.52512.92494
12115.110.98524.11479
1221514.9280.0720475
12311.3513.554-2.20405
12415.9514.61281.33724
12518.113.64584.45423
12614.613.79730.802739
12715.416.1236-0.723619
12815.416.1407-0.740667
12917.613.73473.86529
13013.3514.1438-0.793817
13119.116.64652.45355
13215.3513.941.41005
1337.611.8094-4.20938
13413.414.137-0.73704
13513.913.9137-0.013735
13619.117.26171.83825
13715.2513.89051.35952
13812.913.0385-0.138548
13916.114.18071.91926
14017.3512.80344.54662
14113.1513.06540.0846211
14212.1511.38150.768464
14312.612.32740.272611
14410.3511.5762-1.22622
14515.413.20022.19983
1469.611.0813-1.48126
14718.213.78444.41564
14813.612.32631.27374
14914.8514.2960.55401
15014.7517.251-2.50104
15114.113.96680.1332
15214.912.0892.811
15316.2513.59822.65182
15419.2519.08510.164922
15513.612.08621.51383
15613.614.2975-0.697472
15715.6515.31390.336116
15812.7513.2597-0.509675
15914.611.82992.7701
1609.8513.0328-3.18281
16112.6511.32651.32349
16211.912.4084-0.508358
16319.216.74632.45369
16416.614.85061.74941
16511.210.48520.714823
16615.2514.49170.758313
16711.915.7365-3.83652
16813.215.2383-2.03825
16916.3517.8753-1.52529
17012.414.1673-1.76731
17115.8513.82292.02713
17214.3515.0754-0.725424
17318.1516.30671.84328
17411.1512.0408-0.890777
17515.6516.1644-0.514405
17617.7517.13510.614941
1777.6512.5404-4.89045
17812.3513.141-0.790969
17915.612.99622.60381
18019.317.41991.88009
18115.212.35282.84723
18217.114.50872.59134
18315.613.85931.74069
18418.415.93492.46514
18519.0516.28442.76557
18618.5515.41193.13811
18719.117.81221.2878
18813.112.95170.14828
18912.8515.3064-2.45639
1909.512.7004-3.20038
1914.511.944-7.44395
19211.8511.33210.517903
19313.617.3372-3.7372
19411.713.9501-2.25007
19512.412.8866-0.486574
19613.3515.6675-2.31755
19711.414.2486-2.84858
19814.913.48261.41736
19919.917.11462.7854
20017.7513.84553.90448
20111.213.3415-2.14154
20214.616.4449-1.84494
20317.617.38530.214739
20414.0514.4227-0.372731
20516.116.3139-0.213906
20613.3514.8981-1.54812
20711.8514.6117-2.76172
20811.9515.1991-3.24914
20914.7515.5658-0.815769
21015.1514.33290.817144
21113.215.8802-2.68021
21216.8516.69660.153358
2137.8511.8728-4.02283
2147.715.5501-7.8501
21512.613.871-1.27098
2167.8513.694-5.84401
21710.9512.2323-1.28228
21812.3513.6021-1.25211
2199.9514.6466-4.69661
22014.913.85771.04231
22116.6515.86990.780123
22213.413.931-0.531011
22313.9514.4648-0.514798
22415.714.01521.68479
22516.8514.42262.42739
22610.9512.0846-1.13462
22715.3514.0511.29899
22812.213.0238-0.823806
22915.115.5004-0.400371
23017.7517.60520.144761
23115.214.80190.398137
23214.615.4209-0.820937
23316.6516.46170.188299
2348.111.9935-3.89347

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 11.0557 & 1.84431 \tabularnewline
2 & 12.8 & 11.1757 & 1.6243 \tabularnewline
3 & 7.4 & 12.0299 & -4.6299 \tabularnewline
4 & 6.7 & 10.2786 & -3.57857 \tabularnewline
5 & 12.6 & 15.0496 & -2.44963 \tabularnewline
6 & 14.8 & 11.9536 & 2.84637 \tabularnewline
7 & 13.3 & 11.1497 & 2.15032 \tabularnewline
8 & 11.1 & 12.4784 & -1.37836 \tabularnewline
9 & 8.2 & 13.0906 & -4.89064 \tabularnewline
10 & 11.4 & 12.1536 & -0.753621 \tabularnewline
11 & 6.4 & 13.3956 & -6.99557 \tabularnewline
12 & 12 & 13.4346 & -1.43464 \tabularnewline
13 & 6.3 & 7.98052 & -1.68052 \tabularnewline
14 & 11.3 & 9.78461 & 1.51539 \tabularnewline
15 & 11.9 & 13.2154 & -1.31537 \tabularnewline
16 & 9.3 & 11.0241 & -1.72407 \tabularnewline
17 & 10 & 10.5376 & -0.537591 \tabularnewline
18 & 13.8 & 12.7012 & 1.09878 \tabularnewline
19 & 10.8 & 13.4039 & -2.60393 \tabularnewline
20 & 11.7 & 12.0945 & -0.394485 \tabularnewline
21 & 10.9 & 15.256 & -4.35604 \tabularnewline
22 & 16.1 & 13.4503 & 2.64969 \tabularnewline
23 & 9.9 & 10.8786 & -0.978611 \tabularnewline
24 & 11.5 & 11.5303 & -0.030338 \tabularnewline
25 & 8.3 & 10.4988 & -2.19876 \tabularnewline
26 & 11.7 & 12.5284 & -0.828353 \tabularnewline
27 & 9 & 11.4069 & -2.40693 \tabularnewline
28 & 10.8 & 11.3653 & -0.565317 \tabularnewline
29 & 10.4 & 11.1691 & -0.769125 \tabularnewline
30 & 12.7 & 11.8145 & 0.885497 \tabularnewline
31 & 11.8 & 13.5269 & -1.72689 \tabularnewline
32 & 13 & 11.8308 & 1.1692 \tabularnewline
33 & 10.8 & 12.1445 & -1.34445 \tabularnewline
34 & 12.3 & 9.01737 & 3.28263 \tabularnewline
35 & 11.3 & 13.5328 & -2.23278 \tabularnewline
36 & 11.6 & 11.134 & 0.465984 \tabularnewline
37 & 10.9 & 12.2623 & -1.36231 \tabularnewline
38 & 12.1 & 12.0337 & 0.066322 \tabularnewline
39 & 13.3 & 12.6237 & 0.676286 \tabularnewline
40 & 10.1 & 12.0622 & -1.96216 \tabularnewline
41 & 14.3 & 11.7186 & 2.58138 \tabularnewline
42 & 9.3 & 12.7443 & -3.44434 \tabularnewline
43 & 12.5 & 11.7047 & 0.795285 \tabularnewline
44 & 7.6 & 10.0232 & -2.42317 \tabularnewline
45 & 9.2 & 11.9045 & -2.70451 \tabularnewline
46 & 14.5 & 13.3099 & 1.19014 \tabularnewline
47 & 12.3 & 13.9222 & -1.62224 \tabularnewline
48 & 12.6 & 12.4679 & 0.132112 \tabularnewline
49 & 13 & 13.5031 & -0.503133 \tabularnewline
50 & 12.6 & 10.7163 & 1.88372 \tabularnewline
51 & 13.2 & 14.0826 & -0.882568 \tabularnewline
52 & 7.7 & 11.0337 & -3.33374 \tabularnewline
53 & 10.5 & 10.161 & 0.339014 \tabularnewline
54 & 10.9 & 10.9402 & -0.0401744 \tabularnewline
55 & 4.3 & 9.50364 & -5.20364 \tabularnewline
56 & 10.3 & 11.0441 & -0.744096 \tabularnewline
57 & 11.4 & 10.1212 & 1.27877 \tabularnewline
58 & 5.6 & 10.5587 & -4.95873 \tabularnewline
59 & 8.8 & 10.9194 & -2.11937 \tabularnewline
60 & 9 & 10.1253 & -1.12527 \tabularnewline
61 & 9.6 & 11.0682 & -1.46816 \tabularnewline
62 & 6.4 & 8.9759 & -2.5759 \tabularnewline
63 & 11.6 & 10.6076 & 0.992401 \tabularnewline
64 & 4.35 & 8.86493 & -4.51493 \tabularnewline
65 & 12.7 & 10.9359 & 1.76412 \tabularnewline
66 & 18.1 & 14.1137 & 3.98627 \tabularnewline
67 & 17.85 & 14.406 & 3.44402 \tabularnewline
68 & 16.6 & 14.9206 & 1.67936 \tabularnewline
69 & 12.6 & 9.14919 & 3.45081 \tabularnewline
70 & 17.1 & 20.5637 & -3.46365 \tabularnewline
71 & 19.1 & 15.5879 & 3.51207 \tabularnewline
72 & 16.1 & 18.1322 & -2.03219 \tabularnewline
73 & 13.35 & 9.66996 & 3.68004 \tabularnewline
74 & 18.4 & 16.3346 & 2.06538 \tabularnewline
75 & 14.7 & 9.59986 & 5.10014 \tabularnewline
76 & 10.6 & 13.6361 & -3.03614 \tabularnewline
77 & 12.6 & 12.7687 & -0.168715 \tabularnewline
78 & 16.2 & 14.2718 & 1.92819 \tabularnewline
79 & 13.6 & 16.7548 & -3.15476 \tabularnewline
80 & 18.9 & 15.6504 & 3.24957 \tabularnewline
81 & 14.1 & 11.8448 & 2.25518 \tabularnewline
82 & 14.5 & 11.5312 & 2.96878 \tabularnewline
83 & 16.15 & 17.8471 & -1.69707 \tabularnewline
84 & 14.75 & 13.0528 & 1.69717 \tabularnewline
85 & 14.8 & 13.673 & 1.12701 \tabularnewline
86 & 12.45 & 11.3519 & 1.09812 \tabularnewline
87 & 12.65 & 13.4986 & -0.848582 \tabularnewline
88 & 17.35 & 13.1298 & 4.22018 \tabularnewline
89 & 8.6 & 10.4236 & -1.82364 \tabularnewline
90 & 18.4 & 16.7402 & 1.65978 \tabularnewline
91 & 16.1 & 16.7873 & -0.687311 \tabularnewline
92 & 11.6 & 10.4352 & 1.16479 \tabularnewline
93 & 17.75 & 12.728 & 5.02201 \tabularnewline
94 & 15.25 & 14.2839 & 0.966092 \tabularnewline
95 & 17.65 & 15.2252 & 2.42476 \tabularnewline
96 & 15.6 & 13.5233 & 2.07666 \tabularnewline
97 & 16.35 & 14.9416 & 1.40844 \tabularnewline
98 & 17.65 & 14.7401 & 2.90986 \tabularnewline
99 & 13.6 & 13.0065 & 0.593535 \tabularnewline
100 & 11.7 & 12.4003 & -0.700291 \tabularnewline
101 & 14.35 & 13.1966 & 1.15344 \tabularnewline
102 & 14.75 & 16.3764 & -1.62643 \tabularnewline
103 & 18.25 & 16.2204 & 2.02963 \tabularnewline
104 & 9.9 & 15.2191 & -5.31913 \tabularnewline
105 & 16 & 13.998 & 2.00205 \tabularnewline
106 & 18.25 & 15.5839 & 2.66612 \tabularnewline
107 & 16.85 & 16.893 & -0.0430061 \tabularnewline
108 & 14.6 & 11.7321 & 2.86795 \tabularnewline
109 & 13.85 & 13.0184 & 0.831612 \tabularnewline
110 & 18.95 & 16.598 & 2.35205 \tabularnewline
111 & 15.6 & 14.1971 & 1.40292 \tabularnewline
112 & 14.85 & 16.4162 & -1.56617 \tabularnewline
113 & 11.75 & 12.2654 & -0.515414 \tabularnewline
114 & 18.45 & 13.2146 & 5.23538 \tabularnewline
115 & 15.9 & 15.6295 & 0.270452 \tabularnewline
116 & 17.1 & 14.9456 & 2.15437 \tabularnewline
117 & 16.1 & 9.48833 & 6.61167 \tabularnewline
118 & 19.9 & 15.7337 & 4.16626 \tabularnewline
119 & 10.95 & 10.5616 & 0.388391 \tabularnewline
120 & 18.45 & 15.5251 & 2.92494 \tabularnewline
121 & 15.1 & 10.9852 & 4.11479 \tabularnewline
122 & 15 & 14.928 & 0.0720475 \tabularnewline
123 & 11.35 & 13.554 & -2.20405 \tabularnewline
124 & 15.95 & 14.6128 & 1.33724 \tabularnewline
125 & 18.1 & 13.6458 & 4.45423 \tabularnewline
126 & 14.6 & 13.7973 & 0.802739 \tabularnewline
127 & 15.4 & 16.1236 & -0.723619 \tabularnewline
128 & 15.4 & 16.1407 & -0.740667 \tabularnewline
129 & 17.6 & 13.7347 & 3.86529 \tabularnewline
130 & 13.35 & 14.1438 & -0.793817 \tabularnewline
131 & 19.1 & 16.6465 & 2.45355 \tabularnewline
132 & 15.35 & 13.94 & 1.41005 \tabularnewline
133 & 7.6 & 11.8094 & -4.20938 \tabularnewline
134 & 13.4 & 14.137 & -0.73704 \tabularnewline
135 & 13.9 & 13.9137 & -0.013735 \tabularnewline
136 & 19.1 & 17.2617 & 1.83825 \tabularnewline
137 & 15.25 & 13.8905 & 1.35952 \tabularnewline
138 & 12.9 & 13.0385 & -0.138548 \tabularnewline
139 & 16.1 & 14.1807 & 1.91926 \tabularnewline
140 & 17.35 & 12.8034 & 4.54662 \tabularnewline
141 & 13.15 & 13.0654 & 0.0846211 \tabularnewline
142 & 12.15 & 11.3815 & 0.768464 \tabularnewline
143 & 12.6 & 12.3274 & 0.272611 \tabularnewline
144 & 10.35 & 11.5762 & -1.22622 \tabularnewline
145 & 15.4 & 13.2002 & 2.19983 \tabularnewline
146 & 9.6 & 11.0813 & -1.48126 \tabularnewline
147 & 18.2 & 13.7844 & 4.41564 \tabularnewline
148 & 13.6 & 12.3263 & 1.27374 \tabularnewline
149 & 14.85 & 14.296 & 0.55401 \tabularnewline
150 & 14.75 & 17.251 & -2.50104 \tabularnewline
151 & 14.1 & 13.9668 & 0.1332 \tabularnewline
152 & 14.9 & 12.089 & 2.811 \tabularnewline
153 & 16.25 & 13.5982 & 2.65182 \tabularnewline
154 & 19.25 & 19.0851 & 0.164922 \tabularnewline
155 & 13.6 & 12.0862 & 1.51383 \tabularnewline
156 & 13.6 & 14.2975 & -0.697472 \tabularnewline
157 & 15.65 & 15.3139 & 0.336116 \tabularnewline
158 & 12.75 & 13.2597 & -0.509675 \tabularnewline
159 & 14.6 & 11.8299 & 2.7701 \tabularnewline
160 & 9.85 & 13.0328 & -3.18281 \tabularnewline
161 & 12.65 & 11.3265 & 1.32349 \tabularnewline
162 & 11.9 & 12.4084 & -0.508358 \tabularnewline
163 & 19.2 & 16.7463 & 2.45369 \tabularnewline
164 & 16.6 & 14.8506 & 1.74941 \tabularnewline
165 & 11.2 & 10.4852 & 0.714823 \tabularnewline
166 & 15.25 & 14.4917 & 0.758313 \tabularnewline
167 & 11.9 & 15.7365 & -3.83652 \tabularnewline
168 & 13.2 & 15.2383 & -2.03825 \tabularnewline
169 & 16.35 & 17.8753 & -1.52529 \tabularnewline
170 & 12.4 & 14.1673 & -1.76731 \tabularnewline
171 & 15.85 & 13.8229 & 2.02713 \tabularnewline
172 & 14.35 & 15.0754 & -0.725424 \tabularnewline
173 & 18.15 & 16.3067 & 1.84328 \tabularnewline
174 & 11.15 & 12.0408 & -0.890777 \tabularnewline
175 & 15.65 & 16.1644 & -0.514405 \tabularnewline
176 & 17.75 & 17.1351 & 0.614941 \tabularnewline
177 & 7.65 & 12.5404 & -4.89045 \tabularnewline
178 & 12.35 & 13.141 & -0.790969 \tabularnewline
179 & 15.6 & 12.9962 & 2.60381 \tabularnewline
180 & 19.3 & 17.4199 & 1.88009 \tabularnewline
181 & 15.2 & 12.3528 & 2.84723 \tabularnewline
182 & 17.1 & 14.5087 & 2.59134 \tabularnewline
183 & 15.6 & 13.8593 & 1.74069 \tabularnewline
184 & 18.4 & 15.9349 & 2.46514 \tabularnewline
185 & 19.05 & 16.2844 & 2.76557 \tabularnewline
186 & 18.55 & 15.4119 & 3.13811 \tabularnewline
187 & 19.1 & 17.8122 & 1.2878 \tabularnewline
188 & 13.1 & 12.9517 & 0.14828 \tabularnewline
189 & 12.85 & 15.3064 & -2.45639 \tabularnewline
190 & 9.5 & 12.7004 & -3.20038 \tabularnewline
191 & 4.5 & 11.944 & -7.44395 \tabularnewline
192 & 11.85 & 11.3321 & 0.517903 \tabularnewline
193 & 13.6 & 17.3372 & -3.7372 \tabularnewline
194 & 11.7 & 13.9501 & -2.25007 \tabularnewline
195 & 12.4 & 12.8866 & -0.486574 \tabularnewline
196 & 13.35 & 15.6675 & -2.31755 \tabularnewline
197 & 11.4 & 14.2486 & -2.84858 \tabularnewline
198 & 14.9 & 13.4826 & 1.41736 \tabularnewline
199 & 19.9 & 17.1146 & 2.7854 \tabularnewline
200 & 17.75 & 13.8455 & 3.90448 \tabularnewline
201 & 11.2 & 13.3415 & -2.14154 \tabularnewline
202 & 14.6 & 16.4449 & -1.84494 \tabularnewline
203 & 17.6 & 17.3853 & 0.214739 \tabularnewline
204 & 14.05 & 14.4227 & -0.372731 \tabularnewline
205 & 16.1 & 16.3139 & -0.213906 \tabularnewline
206 & 13.35 & 14.8981 & -1.54812 \tabularnewline
207 & 11.85 & 14.6117 & -2.76172 \tabularnewline
208 & 11.95 & 15.1991 & -3.24914 \tabularnewline
209 & 14.75 & 15.5658 & -0.815769 \tabularnewline
210 & 15.15 & 14.3329 & 0.817144 \tabularnewline
211 & 13.2 & 15.8802 & -2.68021 \tabularnewline
212 & 16.85 & 16.6966 & 0.153358 \tabularnewline
213 & 7.85 & 11.8728 & -4.02283 \tabularnewline
214 & 7.7 & 15.5501 & -7.8501 \tabularnewline
215 & 12.6 & 13.871 & -1.27098 \tabularnewline
216 & 7.85 & 13.694 & -5.84401 \tabularnewline
217 & 10.95 & 12.2323 & -1.28228 \tabularnewline
218 & 12.35 & 13.6021 & -1.25211 \tabularnewline
219 & 9.95 & 14.6466 & -4.69661 \tabularnewline
220 & 14.9 & 13.8577 & 1.04231 \tabularnewline
221 & 16.65 & 15.8699 & 0.780123 \tabularnewline
222 & 13.4 & 13.931 & -0.531011 \tabularnewline
223 & 13.95 & 14.4648 & -0.514798 \tabularnewline
224 & 15.7 & 14.0152 & 1.68479 \tabularnewline
225 & 16.85 & 14.4226 & 2.42739 \tabularnewline
226 & 10.95 & 12.0846 & -1.13462 \tabularnewline
227 & 15.35 & 14.051 & 1.29899 \tabularnewline
228 & 12.2 & 13.0238 & -0.823806 \tabularnewline
229 & 15.1 & 15.5004 & -0.400371 \tabularnewline
230 & 17.75 & 17.6052 & 0.144761 \tabularnewline
231 & 15.2 & 14.8019 & 0.398137 \tabularnewline
232 & 14.6 & 15.4209 & -0.820937 \tabularnewline
233 & 16.65 & 16.4617 & 0.188299 \tabularnewline
234 & 8.1 & 11.9935 & -3.89347 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265170&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]11.0557[/C][C]1.84431[/C][/ROW]
[ROW][C]2[/C][C]12.8[/C][C]11.1757[/C][C]1.6243[/C][/ROW]
[ROW][C]3[/C][C]7.4[/C][C]12.0299[/C][C]-4.6299[/C][/ROW]
[ROW][C]4[/C][C]6.7[/C][C]10.2786[/C][C]-3.57857[/C][/ROW]
[ROW][C]5[/C][C]12.6[/C][C]15.0496[/C][C]-2.44963[/C][/ROW]
[ROW][C]6[/C][C]14.8[/C][C]11.9536[/C][C]2.84637[/C][/ROW]
[ROW][C]7[/C][C]13.3[/C][C]11.1497[/C][C]2.15032[/C][/ROW]
[ROW][C]8[/C][C]11.1[/C][C]12.4784[/C][C]-1.37836[/C][/ROW]
[ROW][C]9[/C][C]8.2[/C][C]13.0906[/C][C]-4.89064[/C][/ROW]
[ROW][C]10[/C][C]11.4[/C][C]12.1536[/C][C]-0.753621[/C][/ROW]
[ROW][C]11[/C][C]6.4[/C][C]13.3956[/C][C]-6.99557[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]13.4346[/C][C]-1.43464[/C][/ROW]
[ROW][C]13[/C][C]6.3[/C][C]7.98052[/C][C]-1.68052[/C][/ROW]
[ROW][C]14[/C][C]11.3[/C][C]9.78461[/C][C]1.51539[/C][/ROW]
[ROW][C]15[/C][C]11.9[/C][C]13.2154[/C][C]-1.31537[/C][/ROW]
[ROW][C]16[/C][C]9.3[/C][C]11.0241[/C][C]-1.72407[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]10.5376[/C][C]-0.537591[/C][/ROW]
[ROW][C]18[/C][C]13.8[/C][C]12.7012[/C][C]1.09878[/C][/ROW]
[ROW][C]19[/C][C]10.8[/C][C]13.4039[/C][C]-2.60393[/C][/ROW]
[ROW][C]20[/C][C]11.7[/C][C]12.0945[/C][C]-0.394485[/C][/ROW]
[ROW][C]21[/C][C]10.9[/C][C]15.256[/C][C]-4.35604[/C][/ROW]
[ROW][C]22[/C][C]16.1[/C][C]13.4503[/C][C]2.64969[/C][/ROW]
[ROW][C]23[/C][C]9.9[/C][C]10.8786[/C][C]-0.978611[/C][/ROW]
[ROW][C]24[/C][C]11.5[/C][C]11.5303[/C][C]-0.030338[/C][/ROW]
[ROW][C]25[/C][C]8.3[/C][C]10.4988[/C][C]-2.19876[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]12.5284[/C][C]-0.828353[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]11.4069[/C][C]-2.40693[/C][/ROW]
[ROW][C]28[/C][C]10.8[/C][C]11.3653[/C][C]-0.565317[/C][/ROW]
[ROW][C]29[/C][C]10.4[/C][C]11.1691[/C][C]-0.769125[/C][/ROW]
[ROW][C]30[/C][C]12.7[/C][C]11.8145[/C][C]0.885497[/C][/ROW]
[ROW][C]31[/C][C]11.8[/C][C]13.5269[/C][C]-1.72689[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]11.8308[/C][C]1.1692[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]12.1445[/C][C]-1.34445[/C][/ROW]
[ROW][C]34[/C][C]12.3[/C][C]9.01737[/C][C]3.28263[/C][/ROW]
[ROW][C]35[/C][C]11.3[/C][C]13.5328[/C][C]-2.23278[/C][/ROW]
[ROW][C]36[/C][C]11.6[/C][C]11.134[/C][C]0.465984[/C][/ROW]
[ROW][C]37[/C][C]10.9[/C][C]12.2623[/C][C]-1.36231[/C][/ROW]
[ROW][C]38[/C][C]12.1[/C][C]12.0337[/C][C]0.066322[/C][/ROW]
[ROW][C]39[/C][C]13.3[/C][C]12.6237[/C][C]0.676286[/C][/ROW]
[ROW][C]40[/C][C]10.1[/C][C]12.0622[/C][C]-1.96216[/C][/ROW]
[ROW][C]41[/C][C]14.3[/C][C]11.7186[/C][C]2.58138[/C][/ROW]
[ROW][C]42[/C][C]9.3[/C][C]12.7443[/C][C]-3.44434[/C][/ROW]
[ROW][C]43[/C][C]12.5[/C][C]11.7047[/C][C]0.795285[/C][/ROW]
[ROW][C]44[/C][C]7.6[/C][C]10.0232[/C][C]-2.42317[/C][/ROW]
[ROW][C]45[/C][C]9.2[/C][C]11.9045[/C][C]-2.70451[/C][/ROW]
[ROW][C]46[/C][C]14.5[/C][C]13.3099[/C][C]1.19014[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]13.9222[/C][C]-1.62224[/C][/ROW]
[ROW][C]48[/C][C]12.6[/C][C]12.4679[/C][C]0.132112[/C][/ROW]
[ROW][C]49[/C][C]13[/C][C]13.5031[/C][C]-0.503133[/C][/ROW]
[ROW][C]50[/C][C]12.6[/C][C]10.7163[/C][C]1.88372[/C][/ROW]
[ROW][C]51[/C][C]13.2[/C][C]14.0826[/C][C]-0.882568[/C][/ROW]
[ROW][C]52[/C][C]7.7[/C][C]11.0337[/C][C]-3.33374[/C][/ROW]
[ROW][C]53[/C][C]10.5[/C][C]10.161[/C][C]0.339014[/C][/ROW]
[ROW][C]54[/C][C]10.9[/C][C]10.9402[/C][C]-0.0401744[/C][/ROW]
[ROW][C]55[/C][C]4.3[/C][C]9.50364[/C][C]-5.20364[/C][/ROW]
[ROW][C]56[/C][C]10.3[/C][C]11.0441[/C][C]-0.744096[/C][/ROW]
[ROW][C]57[/C][C]11.4[/C][C]10.1212[/C][C]1.27877[/C][/ROW]
[ROW][C]58[/C][C]5.6[/C][C]10.5587[/C][C]-4.95873[/C][/ROW]
[ROW][C]59[/C][C]8.8[/C][C]10.9194[/C][C]-2.11937[/C][/ROW]
[ROW][C]60[/C][C]9[/C][C]10.1253[/C][C]-1.12527[/C][/ROW]
[ROW][C]61[/C][C]9.6[/C][C]11.0682[/C][C]-1.46816[/C][/ROW]
[ROW][C]62[/C][C]6.4[/C][C]8.9759[/C][C]-2.5759[/C][/ROW]
[ROW][C]63[/C][C]11.6[/C][C]10.6076[/C][C]0.992401[/C][/ROW]
[ROW][C]64[/C][C]4.35[/C][C]8.86493[/C][C]-4.51493[/C][/ROW]
[ROW][C]65[/C][C]12.7[/C][C]10.9359[/C][C]1.76412[/C][/ROW]
[ROW][C]66[/C][C]18.1[/C][C]14.1137[/C][C]3.98627[/C][/ROW]
[ROW][C]67[/C][C]17.85[/C][C]14.406[/C][C]3.44402[/C][/ROW]
[ROW][C]68[/C][C]16.6[/C][C]14.9206[/C][C]1.67936[/C][/ROW]
[ROW][C]69[/C][C]12.6[/C][C]9.14919[/C][C]3.45081[/C][/ROW]
[ROW][C]70[/C][C]17.1[/C][C]20.5637[/C][C]-3.46365[/C][/ROW]
[ROW][C]71[/C][C]19.1[/C][C]15.5879[/C][C]3.51207[/C][/ROW]
[ROW][C]72[/C][C]16.1[/C][C]18.1322[/C][C]-2.03219[/C][/ROW]
[ROW][C]73[/C][C]13.35[/C][C]9.66996[/C][C]3.68004[/C][/ROW]
[ROW][C]74[/C][C]18.4[/C][C]16.3346[/C][C]2.06538[/C][/ROW]
[ROW][C]75[/C][C]14.7[/C][C]9.59986[/C][C]5.10014[/C][/ROW]
[ROW][C]76[/C][C]10.6[/C][C]13.6361[/C][C]-3.03614[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]12.7687[/C][C]-0.168715[/C][/ROW]
[ROW][C]78[/C][C]16.2[/C][C]14.2718[/C][C]1.92819[/C][/ROW]
[ROW][C]79[/C][C]13.6[/C][C]16.7548[/C][C]-3.15476[/C][/ROW]
[ROW][C]80[/C][C]18.9[/C][C]15.6504[/C][C]3.24957[/C][/ROW]
[ROW][C]81[/C][C]14.1[/C][C]11.8448[/C][C]2.25518[/C][/ROW]
[ROW][C]82[/C][C]14.5[/C][C]11.5312[/C][C]2.96878[/C][/ROW]
[ROW][C]83[/C][C]16.15[/C][C]17.8471[/C][C]-1.69707[/C][/ROW]
[ROW][C]84[/C][C]14.75[/C][C]13.0528[/C][C]1.69717[/C][/ROW]
[ROW][C]85[/C][C]14.8[/C][C]13.673[/C][C]1.12701[/C][/ROW]
[ROW][C]86[/C][C]12.45[/C][C]11.3519[/C][C]1.09812[/C][/ROW]
[ROW][C]87[/C][C]12.65[/C][C]13.4986[/C][C]-0.848582[/C][/ROW]
[ROW][C]88[/C][C]17.35[/C][C]13.1298[/C][C]4.22018[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.4236[/C][C]-1.82364[/C][/ROW]
[ROW][C]90[/C][C]18.4[/C][C]16.7402[/C][C]1.65978[/C][/ROW]
[ROW][C]91[/C][C]16.1[/C][C]16.7873[/C][C]-0.687311[/C][/ROW]
[ROW][C]92[/C][C]11.6[/C][C]10.4352[/C][C]1.16479[/C][/ROW]
[ROW][C]93[/C][C]17.75[/C][C]12.728[/C][C]5.02201[/C][/ROW]
[ROW][C]94[/C][C]15.25[/C][C]14.2839[/C][C]0.966092[/C][/ROW]
[ROW][C]95[/C][C]17.65[/C][C]15.2252[/C][C]2.42476[/C][/ROW]
[ROW][C]96[/C][C]15.6[/C][C]13.5233[/C][C]2.07666[/C][/ROW]
[ROW][C]97[/C][C]16.35[/C][C]14.9416[/C][C]1.40844[/C][/ROW]
[ROW][C]98[/C][C]17.65[/C][C]14.7401[/C][C]2.90986[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]13.0065[/C][C]0.593535[/C][/ROW]
[ROW][C]100[/C][C]11.7[/C][C]12.4003[/C][C]-0.700291[/C][/ROW]
[ROW][C]101[/C][C]14.35[/C][C]13.1966[/C][C]1.15344[/C][/ROW]
[ROW][C]102[/C][C]14.75[/C][C]16.3764[/C][C]-1.62643[/C][/ROW]
[ROW][C]103[/C][C]18.25[/C][C]16.2204[/C][C]2.02963[/C][/ROW]
[ROW][C]104[/C][C]9.9[/C][C]15.2191[/C][C]-5.31913[/C][/ROW]
[ROW][C]105[/C][C]16[/C][C]13.998[/C][C]2.00205[/C][/ROW]
[ROW][C]106[/C][C]18.25[/C][C]15.5839[/C][C]2.66612[/C][/ROW]
[ROW][C]107[/C][C]16.85[/C][C]16.893[/C][C]-0.0430061[/C][/ROW]
[ROW][C]108[/C][C]14.6[/C][C]11.7321[/C][C]2.86795[/C][/ROW]
[ROW][C]109[/C][C]13.85[/C][C]13.0184[/C][C]0.831612[/C][/ROW]
[ROW][C]110[/C][C]18.95[/C][C]16.598[/C][C]2.35205[/C][/ROW]
[ROW][C]111[/C][C]15.6[/C][C]14.1971[/C][C]1.40292[/C][/ROW]
[ROW][C]112[/C][C]14.85[/C][C]16.4162[/C][C]-1.56617[/C][/ROW]
[ROW][C]113[/C][C]11.75[/C][C]12.2654[/C][C]-0.515414[/C][/ROW]
[ROW][C]114[/C][C]18.45[/C][C]13.2146[/C][C]5.23538[/C][/ROW]
[ROW][C]115[/C][C]15.9[/C][C]15.6295[/C][C]0.270452[/C][/ROW]
[ROW][C]116[/C][C]17.1[/C][C]14.9456[/C][C]2.15437[/C][/ROW]
[ROW][C]117[/C][C]16.1[/C][C]9.48833[/C][C]6.61167[/C][/ROW]
[ROW][C]118[/C][C]19.9[/C][C]15.7337[/C][C]4.16626[/C][/ROW]
[ROW][C]119[/C][C]10.95[/C][C]10.5616[/C][C]0.388391[/C][/ROW]
[ROW][C]120[/C][C]18.45[/C][C]15.5251[/C][C]2.92494[/C][/ROW]
[ROW][C]121[/C][C]15.1[/C][C]10.9852[/C][C]4.11479[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.928[/C][C]0.0720475[/C][/ROW]
[ROW][C]123[/C][C]11.35[/C][C]13.554[/C][C]-2.20405[/C][/ROW]
[ROW][C]124[/C][C]15.95[/C][C]14.6128[/C][C]1.33724[/C][/ROW]
[ROW][C]125[/C][C]18.1[/C][C]13.6458[/C][C]4.45423[/C][/ROW]
[ROW][C]126[/C][C]14.6[/C][C]13.7973[/C][C]0.802739[/C][/ROW]
[ROW][C]127[/C][C]15.4[/C][C]16.1236[/C][C]-0.723619[/C][/ROW]
[ROW][C]128[/C][C]15.4[/C][C]16.1407[/C][C]-0.740667[/C][/ROW]
[ROW][C]129[/C][C]17.6[/C][C]13.7347[/C][C]3.86529[/C][/ROW]
[ROW][C]130[/C][C]13.35[/C][C]14.1438[/C][C]-0.793817[/C][/ROW]
[ROW][C]131[/C][C]19.1[/C][C]16.6465[/C][C]2.45355[/C][/ROW]
[ROW][C]132[/C][C]15.35[/C][C]13.94[/C][C]1.41005[/C][/ROW]
[ROW][C]133[/C][C]7.6[/C][C]11.8094[/C][C]-4.20938[/C][/ROW]
[ROW][C]134[/C][C]13.4[/C][C]14.137[/C][C]-0.73704[/C][/ROW]
[ROW][C]135[/C][C]13.9[/C][C]13.9137[/C][C]-0.013735[/C][/ROW]
[ROW][C]136[/C][C]19.1[/C][C]17.2617[/C][C]1.83825[/C][/ROW]
[ROW][C]137[/C][C]15.25[/C][C]13.8905[/C][C]1.35952[/C][/ROW]
[ROW][C]138[/C][C]12.9[/C][C]13.0385[/C][C]-0.138548[/C][/ROW]
[ROW][C]139[/C][C]16.1[/C][C]14.1807[/C][C]1.91926[/C][/ROW]
[ROW][C]140[/C][C]17.35[/C][C]12.8034[/C][C]4.54662[/C][/ROW]
[ROW][C]141[/C][C]13.15[/C][C]13.0654[/C][C]0.0846211[/C][/ROW]
[ROW][C]142[/C][C]12.15[/C][C]11.3815[/C][C]0.768464[/C][/ROW]
[ROW][C]143[/C][C]12.6[/C][C]12.3274[/C][C]0.272611[/C][/ROW]
[ROW][C]144[/C][C]10.35[/C][C]11.5762[/C][C]-1.22622[/C][/ROW]
[ROW][C]145[/C][C]15.4[/C][C]13.2002[/C][C]2.19983[/C][/ROW]
[ROW][C]146[/C][C]9.6[/C][C]11.0813[/C][C]-1.48126[/C][/ROW]
[ROW][C]147[/C][C]18.2[/C][C]13.7844[/C][C]4.41564[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.3263[/C][C]1.27374[/C][/ROW]
[ROW][C]149[/C][C]14.85[/C][C]14.296[/C][C]0.55401[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]17.251[/C][C]-2.50104[/C][/ROW]
[ROW][C]151[/C][C]14.1[/C][C]13.9668[/C][C]0.1332[/C][/ROW]
[ROW][C]152[/C][C]14.9[/C][C]12.089[/C][C]2.811[/C][/ROW]
[ROW][C]153[/C][C]16.25[/C][C]13.5982[/C][C]2.65182[/C][/ROW]
[ROW][C]154[/C][C]19.25[/C][C]19.0851[/C][C]0.164922[/C][/ROW]
[ROW][C]155[/C][C]13.6[/C][C]12.0862[/C][C]1.51383[/C][/ROW]
[ROW][C]156[/C][C]13.6[/C][C]14.2975[/C][C]-0.697472[/C][/ROW]
[ROW][C]157[/C][C]15.65[/C][C]15.3139[/C][C]0.336116[/C][/ROW]
[ROW][C]158[/C][C]12.75[/C][C]13.2597[/C][C]-0.509675[/C][/ROW]
[ROW][C]159[/C][C]14.6[/C][C]11.8299[/C][C]2.7701[/C][/ROW]
[ROW][C]160[/C][C]9.85[/C][C]13.0328[/C][C]-3.18281[/C][/ROW]
[ROW][C]161[/C][C]12.65[/C][C]11.3265[/C][C]1.32349[/C][/ROW]
[ROW][C]162[/C][C]11.9[/C][C]12.4084[/C][C]-0.508358[/C][/ROW]
[ROW][C]163[/C][C]19.2[/C][C]16.7463[/C][C]2.45369[/C][/ROW]
[ROW][C]164[/C][C]16.6[/C][C]14.8506[/C][C]1.74941[/C][/ROW]
[ROW][C]165[/C][C]11.2[/C][C]10.4852[/C][C]0.714823[/C][/ROW]
[ROW][C]166[/C][C]15.25[/C][C]14.4917[/C][C]0.758313[/C][/ROW]
[ROW][C]167[/C][C]11.9[/C][C]15.7365[/C][C]-3.83652[/C][/ROW]
[ROW][C]168[/C][C]13.2[/C][C]15.2383[/C][C]-2.03825[/C][/ROW]
[ROW][C]169[/C][C]16.35[/C][C]17.8753[/C][C]-1.52529[/C][/ROW]
[ROW][C]170[/C][C]12.4[/C][C]14.1673[/C][C]-1.76731[/C][/ROW]
[ROW][C]171[/C][C]15.85[/C][C]13.8229[/C][C]2.02713[/C][/ROW]
[ROW][C]172[/C][C]14.35[/C][C]15.0754[/C][C]-0.725424[/C][/ROW]
[ROW][C]173[/C][C]18.15[/C][C]16.3067[/C][C]1.84328[/C][/ROW]
[ROW][C]174[/C][C]11.15[/C][C]12.0408[/C][C]-0.890777[/C][/ROW]
[ROW][C]175[/C][C]15.65[/C][C]16.1644[/C][C]-0.514405[/C][/ROW]
[ROW][C]176[/C][C]17.75[/C][C]17.1351[/C][C]0.614941[/C][/ROW]
[ROW][C]177[/C][C]7.65[/C][C]12.5404[/C][C]-4.89045[/C][/ROW]
[ROW][C]178[/C][C]12.35[/C][C]13.141[/C][C]-0.790969[/C][/ROW]
[ROW][C]179[/C][C]15.6[/C][C]12.9962[/C][C]2.60381[/C][/ROW]
[ROW][C]180[/C][C]19.3[/C][C]17.4199[/C][C]1.88009[/C][/ROW]
[ROW][C]181[/C][C]15.2[/C][C]12.3528[/C][C]2.84723[/C][/ROW]
[ROW][C]182[/C][C]17.1[/C][C]14.5087[/C][C]2.59134[/C][/ROW]
[ROW][C]183[/C][C]15.6[/C][C]13.8593[/C][C]1.74069[/C][/ROW]
[ROW][C]184[/C][C]18.4[/C][C]15.9349[/C][C]2.46514[/C][/ROW]
[ROW][C]185[/C][C]19.05[/C][C]16.2844[/C][C]2.76557[/C][/ROW]
[ROW][C]186[/C][C]18.55[/C][C]15.4119[/C][C]3.13811[/C][/ROW]
[ROW][C]187[/C][C]19.1[/C][C]17.8122[/C][C]1.2878[/C][/ROW]
[ROW][C]188[/C][C]13.1[/C][C]12.9517[/C][C]0.14828[/C][/ROW]
[ROW][C]189[/C][C]12.85[/C][C]15.3064[/C][C]-2.45639[/C][/ROW]
[ROW][C]190[/C][C]9.5[/C][C]12.7004[/C][C]-3.20038[/C][/ROW]
[ROW][C]191[/C][C]4.5[/C][C]11.944[/C][C]-7.44395[/C][/ROW]
[ROW][C]192[/C][C]11.85[/C][C]11.3321[/C][C]0.517903[/C][/ROW]
[ROW][C]193[/C][C]13.6[/C][C]17.3372[/C][C]-3.7372[/C][/ROW]
[ROW][C]194[/C][C]11.7[/C][C]13.9501[/C][C]-2.25007[/C][/ROW]
[ROW][C]195[/C][C]12.4[/C][C]12.8866[/C][C]-0.486574[/C][/ROW]
[ROW][C]196[/C][C]13.35[/C][C]15.6675[/C][C]-2.31755[/C][/ROW]
[ROW][C]197[/C][C]11.4[/C][C]14.2486[/C][C]-2.84858[/C][/ROW]
[ROW][C]198[/C][C]14.9[/C][C]13.4826[/C][C]1.41736[/C][/ROW]
[ROW][C]199[/C][C]19.9[/C][C]17.1146[/C][C]2.7854[/C][/ROW]
[ROW][C]200[/C][C]17.75[/C][C]13.8455[/C][C]3.90448[/C][/ROW]
[ROW][C]201[/C][C]11.2[/C][C]13.3415[/C][C]-2.14154[/C][/ROW]
[ROW][C]202[/C][C]14.6[/C][C]16.4449[/C][C]-1.84494[/C][/ROW]
[ROW][C]203[/C][C]17.6[/C][C]17.3853[/C][C]0.214739[/C][/ROW]
[ROW][C]204[/C][C]14.05[/C][C]14.4227[/C][C]-0.372731[/C][/ROW]
[ROW][C]205[/C][C]16.1[/C][C]16.3139[/C][C]-0.213906[/C][/ROW]
[ROW][C]206[/C][C]13.35[/C][C]14.8981[/C][C]-1.54812[/C][/ROW]
[ROW][C]207[/C][C]11.85[/C][C]14.6117[/C][C]-2.76172[/C][/ROW]
[ROW][C]208[/C][C]11.95[/C][C]15.1991[/C][C]-3.24914[/C][/ROW]
[ROW][C]209[/C][C]14.75[/C][C]15.5658[/C][C]-0.815769[/C][/ROW]
[ROW][C]210[/C][C]15.15[/C][C]14.3329[/C][C]0.817144[/C][/ROW]
[ROW][C]211[/C][C]13.2[/C][C]15.8802[/C][C]-2.68021[/C][/ROW]
[ROW][C]212[/C][C]16.85[/C][C]16.6966[/C][C]0.153358[/C][/ROW]
[ROW][C]213[/C][C]7.85[/C][C]11.8728[/C][C]-4.02283[/C][/ROW]
[ROW][C]214[/C][C]7.7[/C][C]15.5501[/C][C]-7.8501[/C][/ROW]
[ROW][C]215[/C][C]12.6[/C][C]13.871[/C][C]-1.27098[/C][/ROW]
[ROW][C]216[/C][C]7.85[/C][C]13.694[/C][C]-5.84401[/C][/ROW]
[ROW][C]217[/C][C]10.95[/C][C]12.2323[/C][C]-1.28228[/C][/ROW]
[ROW][C]218[/C][C]12.35[/C][C]13.6021[/C][C]-1.25211[/C][/ROW]
[ROW][C]219[/C][C]9.95[/C][C]14.6466[/C][C]-4.69661[/C][/ROW]
[ROW][C]220[/C][C]14.9[/C][C]13.8577[/C][C]1.04231[/C][/ROW]
[ROW][C]221[/C][C]16.65[/C][C]15.8699[/C][C]0.780123[/C][/ROW]
[ROW][C]222[/C][C]13.4[/C][C]13.931[/C][C]-0.531011[/C][/ROW]
[ROW][C]223[/C][C]13.95[/C][C]14.4648[/C][C]-0.514798[/C][/ROW]
[ROW][C]224[/C][C]15.7[/C][C]14.0152[/C][C]1.68479[/C][/ROW]
[ROW][C]225[/C][C]16.85[/C][C]14.4226[/C][C]2.42739[/C][/ROW]
[ROW][C]226[/C][C]10.95[/C][C]12.0846[/C][C]-1.13462[/C][/ROW]
[ROW][C]227[/C][C]15.35[/C][C]14.051[/C][C]1.29899[/C][/ROW]
[ROW][C]228[/C][C]12.2[/C][C]13.0238[/C][C]-0.823806[/C][/ROW]
[ROW][C]229[/C][C]15.1[/C][C]15.5004[/C][C]-0.400371[/C][/ROW]
[ROW][C]230[/C][C]17.75[/C][C]17.6052[/C][C]0.144761[/C][/ROW]
[ROW][C]231[/C][C]15.2[/C][C]14.8019[/C][C]0.398137[/C][/ROW]
[ROW][C]232[/C][C]14.6[/C][C]15.4209[/C][C]-0.820937[/C][/ROW]
[ROW][C]233[/C][C]16.65[/C][C]16.4617[/C][C]0.188299[/C][/ROW]
[ROW][C]234[/C][C]8.1[/C][C]11.9935[/C][C]-3.89347[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265170&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265170&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.05571.84431
212.811.17571.6243
37.412.0299-4.6299
46.710.2786-3.57857
512.615.0496-2.44963
614.811.95362.84637
713.311.14972.15032
811.112.4784-1.37836
98.213.0906-4.89064
1011.412.1536-0.753621
116.413.3956-6.99557
121213.4346-1.43464
136.37.98052-1.68052
1411.39.784611.51539
1511.913.2154-1.31537
169.311.0241-1.72407
171010.5376-0.537591
1813.812.70121.09878
1910.813.4039-2.60393
2011.712.0945-0.394485
2110.915.256-4.35604
2216.113.45032.64969
239.910.8786-0.978611
2411.511.5303-0.030338
258.310.4988-2.19876
2611.712.5284-0.828353
27911.4069-2.40693
2810.811.3653-0.565317
2910.411.1691-0.769125
3012.711.81450.885497
3111.813.5269-1.72689
321311.83081.1692
3310.812.1445-1.34445
3412.39.017373.28263
3511.313.5328-2.23278
3611.611.1340.465984
3710.912.2623-1.36231
3812.112.03370.066322
3913.312.62370.676286
4010.112.0622-1.96216
4114.311.71862.58138
429.312.7443-3.44434
4312.511.70470.795285
447.610.0232-2.42317
459.211.9045-2.70451
4614.513.30991.19014
4712.313.9222-1.62224
4812.612.46790.132112
491313.5031-0.503133
5012.610.71631.88372
5113.214.0826-0.882568
527.711.0337-3.33374
5310.510.1610.339014
5410.910.9402-0.0401744
554.39.50364-5.20364
5610.311.0441-0.744096
5711.410.12121.27877
585.610.5587-4.95873
598.810.9194-2.11937
60910.1253-1.12527
619.611.0682-1.46816
626.48.9759-2.5759
6311.610.60760.992401
644.358.86493-4.51493
6512.710.93591.76412
6618.114.11373.98627
6717.8514.4063.44402
6816.614.92061.67936
6912.69.149193.45081
7017.120.5637-3.46365
7119.115.58793.51207
7216.118.1322-2.03219
7313.359.669963.68004
7418.416.33462.06538
7514.79.599865.10014
7610.613.6361-3.03614
7712.612.7687-0.168715
7816.214.27181.92819
7913.616.7548-3.15476
8018.915.65043.24957
8114.111.84482.25518
8214.511.53122.96878
8316.1517.8471-1.69707
8414.7513.05281.69717
8514.813.6731.12701
8612.4511.35191.09812
8712.6513.4986-0.848582
8817.3513.12984.22018
898.610.4236-1.82364
9018.416.74021.65978
9116.116.7873-0.687311
9211.610.43521.16479
9317.7512.7285.02201
9415.2514.28390.966092
9517.6515.22522.42476
9615.613.52332.07666
9716.3514.94161.40844
9817.6514.74012.90986
9913.613.00650.593535
10011.712.4003-0.700291
10114.3513.19661.15344
10214.7516.3764-1.62643
10318.2516.22042.02963
1049.915.2191-5.31913
1051613.9982.00205
10618.2515.58392.66612
10716.8516.893-0.0430061
10814.611.73212.86795
10913.8513.01840.831612
11018.9516.5982.35205
11115.614.19711.40292
11214.8516.4162-1.56617
11311.7512.2654-0.515414
11418.4513.21465.23538
11515.915.62950.270452
11617.114.94562.15437
11716.19.488336.61167
11819.915.73374.16626
11910.9510.56160.388391
12018.4515.52512.92494
12115.110.98524.11479
1221514.9280.0720475
12311.3513.554-2.20405
12415.9514.61281.33724
12518.113.64584.45423
12614.613.79730.802739
12715.416.1236-0.723619
12815.416.1407-0.740667
12917.613.73473.86529
13013.3514.1438-0.793817
13119.116.64652.45355
13215.3513.941.41005
1337.611.8094-4.20938
13413.414.137-0.73704
13513.913.9137-0.013735
13619.117.26171.83825
13715.2513.89051.35952
13812.913.0385-0.138548
13916.114.18071.91926
14017.3512.80344.54662
14113.1513.06540.0846211
14212.1511.38150.768464
14312.612.32740.272611
14410.3511.5762-1.22622
14515.413.20022.19983
1469.611.0813-1.48126
14718.213.78444.41564
14813.612.32631.27374
14914.8514.2960.55401
15014.7517.251-2.50104
15114.113.96680.1332
15214.912.0892.811
15316.2513.59822.65182
15419.2519.08510.164922
15513.612.08621.51383
15613.614.2975-0.697472
15715.6515.31390.336116
15812.7513.2597-0.509675
15914.611.82992.7701
1609.8513.0328-3.18281
16112.6511.32651.32349
16211.912.4084-0.508358
16319.216.74632.45369
16416.614.85061.74941
16511.210.48520.714823
16615.2514.49170.758313
16711.915.7365-3.83652
16813.215.2383-2.03825
16916.3517.8753-1.52529
17012.414.1673-1.76731
17115.8513.82292.02713
17214.3515.0754-0.725424
17318.1516.30671.84328
17411.1512.0408-0.890777
17515.6516.1644-0.514405
17617.7517.13510.614941
1777.6512.5404-4.89045
17812.3513.141-0.790969
17915.612.99622.60381
18019.317.41991.88009
18115.212.35282.84723
18217.114.50872.59134
18315.613.85931.74069
18418.415.93492.46514
18519.0516.28442.76557
18618.5515.41193.13811
18719.117.81221.2878
18813.112.95170.14828
18912.8515.3064-2.45639
1909.512.7004-3.20038
1914.511.944-7.44395
19211.8511.33210.517903
19313.617.3372-3.7372
19411.713.9501-2.25007
19512.412.8866-0.486574
19613.3515.6675-2.31755
19711.414.2486-2.84858
19814.913.48261.41736
19919.917.11462.7854
20017.7513.84553.90448
20111.213.3415-2.14154
20214.616.4449-1.84494
20317.617.38530.214739
20414.0514.4227-0.372731
20516.116.3139-0.213906
20613.3514.8981-1.54812
20711.8514.6117-2.76172
20811.9515.1991-3.24914
20914.7515.5658-0.815769
21015.1514.33290.817144
21113.215.8802-2.68021
21216.8516.69660.153358
2137.8511.8728-4.02283
2147.715.5501-7.8501
21512.613.871-1.27098
2167.8513.694-5.84401
21710.9512.2323-1.28228
21812.3513.6021-1.25211
2199.9514.6466-4.69661
22014.913.85771.04231
22116.6515.86990.780123
22213.413.931-0.531011
22313.9514.4648-0.514798
22415.714.01521.68479
22516.8514.42262.42739
22610.9512.0846-1.13462
22715.3514.0511.29899
22812.213.0238-0.823806
22915.115.5004-0.400371
23017.7517.60520.144761
23115.214.80190.398137
23214.615.4209-0.820937
23316.6516.46170.188299
2348.111.9935-3.89347






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.9087480.1825030.0912515
90.9631370.07372510.0368625
100.9406340.1187320.0593659
110.9575710.08485710.0424285
120.9350350.1299310.0649655
130.9096760.1806490.0903243
140.9166450.166710.0833548
150.8919780.2160440.108022
160.8496370.3007250.150363
170.7988320.4023350.201168
180.7416170.5167660.258383
190.6871480.6257050.312852
200.6336590.7326820.366341
210.5854030.8291940.414597
220.5901030.8197940.409897
230.5224010.9551980.477599
240.4798530.9597060.520147
250.4234640.8469280.576536
260.3835740.7671470.616426
270.3431040.6862090.656896
280.2902610.5805220.709739
290.2415210.4830410.758479
300.2108840.4217680.789116
310.1786050.357210.821395
320.1449270.2898530.855073
330.1164450.2328910.883555
340.1195180.2390360.880482
350.1113050.222610.888695
360.08743630.1748730.912564
370.06946730.1389350.930533
380.05587740.1117550.944123
390.04653990.09307970.95346
400.03695240.07390480.963048
410.03824560.07649130.961754
420.04998070.09996140.950019
430.03843340.07686680.961567
440.05362970.1072590.94637
450.06644290.1328860.933557
460.0545430.1090860.945457
470.05129110.1025820.948709
480.04286940.08573880.957131
490.0350420.07008410.964958
500.02748590.05497180.972514
510.0240720.04814390.975928
520.04486240.08972480.955138
530.03581580.07163170.964184
540.02764330.05528660.972357
550.1077330.2154670.892267
560.09464220.1892840.905358
570.07648710.1529740.923513
580.157290.314580.84271
590.1537730.3075460.846227
600.1470680.2941360.852932
610.1466480.2932970.853352
620.1653480.3306950.834652
630.1613240.3226490.838676
640.3157020.6314050.684298
650.3349210.6698420.665079
660.4874930.9749870.512507
670.5525270.8949470.447473
680.5152880.9694250.484712
690.5585740.8828530.441426
700.6102770.7794470.389723
710.6198080.7603840.380192
720.626410.7471790.37359
730.6502960.6994070.349704
740.6531630.6936750.346837
750.7219310.5561390.278069
760.7832160.4335680.216784
770.7620520.4758970.237948
780.7507690.4984610.249231
790.8310670.3378670.168933
800.8306020.3387960.169398
810.8113870.3772260.188613
820.8021910.3956170.197809
830.8014370.3971270.198563
840.7759450.448110.224055
850.7461480.5077040.253852
860.7141270.5717450.285873
870.6975260.6049480.302474
880.7319070.5361870.268093
890.7478850.504230.252115
900.7294710.5410580.270529
910.7029050.5941910.297095
920.6696150.6607690.330385
930.6947250.610550.305275
940.6651530.6696940.334847
950.6487090.7025830.351291
960.6152160.7695680.384784
970.5788440.8423110.421156
980.5604650.879070.439535
990.532960.934080.46704
1000.5464880.9070250.453512
1010.5094110.9811780.490589
1020.5050170.9899660.494983
1030.4719350.9438710.528065
1040.753180.4936390.24682
1050.7242420.5515150.275758
1060.7029230.5941540.297077
1070.6830020.6339950.316998
1080.6609090.6781820.339091
1090.6268320.7463350.373168
1100.59790.8041990.4021
1110.5607940.8784130.439206
1120.559890.8802190.44011
1130.561750.8764990.43825
1140.6067180.7865650.393282
1150.5699470.8601060.430053
1160.534280.931440.46572
1170.7115620.5768760.288438
1180.7058290.5883410.294171
1190.704330.591340.29567
1200.6923410.6153180.307659
1210.6861630.6276730.313837
1220.6619450.6761090.338055
1230.6983620.6032770.301638
1240.667730.6645410.33227
1250.6894460.6211070.310554
1260.6662440.6675120.333756
1270.6648930.6702140.335107
1280.6657010.6685990.334299
1290.673340.6533190.32666
1300.6742970.6514050.325703
1310.6481660.7036670.351834
1320.6144210.7711580.385579
1330.7638610.4722780.236139
1340.754690.4906190.24531
1350.7380150.523970.261985
1360.7086530.5826940.291347
1370.6763140.6473710.323686
1380.6752010.6495970.324799
1390.6445060.7109880.355494
1400.6702390.6595220.329761
1410.6515070.6969860.348493
1420.6311860.7376270.368814
1430.6022380.7955240.397762
1440.6043270.7913460.395673
1450.5729070.8541870.427093
1460.5863420.8273160.413658
1470.6232530.7534940.376747
1480.5911190.8177620.408881
1490.5631870.8736250.436813
1500.6033950.793210.396605
1510.5707720.8584550.429228
1520.5680440.8639120.431956
1530.5537820.8924350.446218
1540.5306360.9387290.469364
1550.5100890.9798210.489911
1560.5009910.9980180.499009
1570.463280.926560.53672
1580.4475490.8950980.552451
1590.4707760.9415510.529224
1600.5022690.9954630.497731
1610.4871940.9743880.512806
1620.4603880.9207750.539612
1630.4529460.9058920.547054
1640.4452380.8904760.554762
1650.4355980.8711970.564402
1660.3964860.7929730.603514
1670.4622530.9245050.537747
1680.4429750.885950.557025
1690.4361330.8722660.563867
1700.4270630.8541250.572937
1710.4214280.8428560.578572
1720.4054630.8109270.594537
1730.365550.73110.63445
1740.3394060.6788120.660594
1750.3053690.6107380.694631
1760.2688220.5376440.731178
1770.3463180.6926360.653682
1780.3187550.637510.681245
1790.2973010.5946020.702699
1800.2640830.5281660.735917
1810.3319560.6639110.668044
1820.3245050.649010.675495
1830.3509560.7019120.649044
1840.3755410.7510810.624459
1850.3933760.7867530.606624
1860.4167670.8335350.583233
1870.420530.8410590.57947
1880.4185590.8371180.581441
1890.4295070.8590140.570493
1900.4305450.8610910.569455
1910.668870.6622590.33113
1920.674590.6508190.32541
1930.7133130.5733740.286687
1940.6794970.6410060.320503
1950.6471070.7057850.352893
1960.613140.7737210.38686
1970.576510.8469790.42349
1980.5897640.8204720.410236
1990.6299420.7401150.370058
2000.8036630.3926750.196337
2010.7770160.4459680.222984
2020.7361320.5277360.263868
2030.6889890.6220230.311011
2040.6745560.6508890.325444
2050.6373160.7253680.362684
2060.5844790.8310420.415521
2070.542930.9141390.45707
2080.4966770.9933550.503323
2090.4552710.9105420.544729
2100.5578580.8842830.442142
2110.5435480.9129040.456452
2120.5829110.8341780.417089
2130.5351510.9296980.464849
2140.8463460.3073090.153654
2150.7935010.4129980.206499
2160.9917120.01657650.00828824
2170.9956670.008665240.00433262
2180.9982760.003447430.00172372
2190.9999975.06608e-062.53304e-06
2200.9999911.73487e-058.67435e-06
2210.9999657.03053e-053.51527e-05
2220.9998480.0003038090.000151905
2230.9998570.0002861110.000143055
2240.9995820.000836520.00041826
2250.9977680.004464850.00223242
2260.9909310.01813840.00906922

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.908748 & 0.182503 & 0.0912515 \tabularnewline
9 & 0.963137 & 0.0737251 & 0.0368625 \tabularnewline
10 & 0.940634 & 0.118732 & 0.0593659 \tabularnewline
11 & 0.957571 & 0.0848571 & 0.0424285 \tabularnewline
12 & 0.935035 & 0.129931 & 0.0649655 \tabularnewline
13 & 0.909676 & 0.180649 & 0.0903243 \tabularnewline
14 & 0.916645 & 0.16671 & 0.0833548 \tabularnewline
15 & 0.891978 & 0.216044 & 0.108022 \tabularnewline
16 & 0.849637 & 0.300725 & 0.150363 \tabularnewline
17 & 0.798832 & 0.402335 & 0.201168 \tabularnewline
18 & 0.741617 & 0.516766 & 0.258383 \tabularnewline
19 & 0.687148 & 0.625705 & 0.312852 \tabularnewline
20 & 0.633659 & 0.732682 & 0.366341 \tabularnewline
21 & 0.585403 & 0.829194 & 0.414597 \tabularnewline
22 & 0.590103 & 0.819794 & 0.409897 \tabularnewline
23 & 0.522401 & 0.955198 & 0.477599 \tabularnewline
24 & 0.479853 & 0.959706 & 0.520147 \tabularnewline
25 & 0.423464 & 0.846928 & 0.576536 \tabularnewline
26 & 0.383574 & 0.767147 & 0.616426 \tabularnewline
27 & 0.343104 & 0.686209 & 0.656896 \tabularnewline
28 & 0.290261 & 0.580522 & 0.709739 \tabularnewline
29 & 0.241521 & 0.483041 & 0.758479 \tabularnewline
30 & 0.210884 & 0.421768 & 0.789116 \tabularnewline
31 & 0.178605 & 0.35721 & 0.821395 \tabularnewline
32 & 0.144927 & 0.289853 & 0.855073 \tabularnewline
33 & 0.116445 & 0.232891 & 0.883555 \tabularnewline
34 & 0.119518 & 0.239036 & 0.880482 \tabularnewline
35 & 0.111305 & 0.22261 & 0.888695 \tabularnewline
36 & 0.0874363 & 0.174873 & 0.912564 \tabularnewline
37 & 0.0694673 & 0.138935 & 0.930533 \tabularnewline
38 & 0.0558774 & 0.111755 & 0.944123 \tabularnewline
39 & 0.0465399 & 0.0930797 & 0.95346 \tabularnewline
40 & 0.0369524 & 0.0739048 & 0.963048 \tabularnewline
41 & 0.0382456 & 0.0764913 & 0.961754 \tabularnewline
42 & 0.0499807 & 0.0999614 & 0.950019 \tabularnewline
43 & 0.0384334 & 0.0768668 & 0.961567 \tabularnewline
44 & 0.0536297 & 0.107259 & 0.94637 \tabularnewline
45 & 0.0664429 & 0.132886 & 0.933557 \tabularnewline
46 & 0.054543 & 0.109086 & 0.945457 \tabularnewline
47 & 0.0512911 & 0.102582 & 0.948709 \tabularnewline
48 & 0.0428694 & 0.0857388 & 0.957131 \tabularnewline
49 & 0.035042 & 0.0700841 & 0.964958 \tabularnewline
50 & 0.0274859 & 0.0549718 & 0.972514 \tabularnewline
51 & 0.024072 & 0.0481439 & 0.975928 \tabularnewline
52 & 0.0448624 & 0.0897248 & 0.955138 \tabularnewline
53 & 0.0358158 & 0.0716317 & 0.964184 \tabularnewline
54 & 0.0276433 & 0.0552866 & 0.972357 \tabularnewline
55 & 0.107733 & 0.215467 & 0.892267 \tabularnewline
56 & 0.0946422 & 0.189284 & 0.905358 \tabularnewline
57 & 0.0764871 & 0.152974 & 0.923513 \tabularnewline
58 & 0.15729 & 0.31458 & 0.84271 \tabularnewline
59 & 0.153773 & 0.307546 & 0.846227 \tabularnewline
60 & 0.147068 & 0.294136 & 0.852932 \tabularnewline
61 & 0.146648 & 0.293297 & 0.853352 \tabularnewline
62 & 0.165348 & 0.330695 & 0.834652 \tabularnewline
63 & 0.161324 & 0.322649 & 0.838676 \tabularnewline
64 & 0.315702 & 0.631405 & 0.684298 \tabularnewline
65 & 0.334921 & 0.669842 & 0.665079 \tabularnewline
66 & 0.487493 & 0.974987 & 0.512507 \tabularnewline
67 & 0.552527 & 0.894947 & 0.447473 \tabularnewline
68 & 0.515288 & 0.969425 & 0.484712 \tabularnewline
69 & 0.558574 & 0.882853 & 0.441426 \tabularnewline
70 & 0.610277 & 0.779447 & 0.389723 \tabularnewline
71 & 0.619808 & 0.760384 & 0.380192 \tabularnewline
72 & 0.62641 & 0.747179 & 0.37359 \tabularnewline
73 & 0.650296 & 0.699407 & 0.349704 \tabularnewline
74 & 0.653163 & 0.693675 & 0.346837 \tabularnewline
75 & 0.721931 & 0.556139 & 0.278069 \tabularnewline
76 & 0.783216 & 0.433568 & 0.216784 \tabularnewline
77 & 0.762052 & 0.475897 & 0.237948 \tabularnewline
78 & 0.750769 & 0.498461 & 0.249231 \tabularnewline
79 & 0.831067 & 0.337867 & 0.168933 \tabularnewline
80 & 0.830602 & 0.338796 & 0.169398 \tabularnewline
81 & 0.811387 & 0.377226 & 0.188613 \tabularnewline
82 & 0.802191 & 0.395617 & 0.197809 \tabularnewline
83 & 0.801437 & 0.397127 & 0.198563 \tabularnewline
84 & 0.775945 & 0.44811 & 0.224055 \tabularnewline
85 & 0.746148 & 0.507704 & 0.253852 \tabularnewline
86 & 0.714127 & 0.571745 & 0.285873 \tabularnewline
87 & 0.697526 & 0.604948 & 0.302474 \tabularnewline
88 & 0.731907 & 0.536187 & 0.268093 \tabularnewline
89 & 0.747885 & 0.50423 & 0.252115 \tabularnewline
90 & 0.729471 & 0.541058 & 0.270529 \tabularnewline
91 & 0.702905 & 0.594191 & 0.297095 \tabularnewline
92 & 0.669615 & 0.660769 & 0.330385 \tabularnewline
93 & 0.694725 & 0.61055 & 0.305275 \tabularnewline
94 & 0.665153 & 0.669694 & 0.334847 \tabularnewline
95 & 0.648709 & 0.702583 & 0.351291 \tabularnewline
96 & 0.615216 & 0.769568 & 0.384784 \tabularnewline
97 & 0.578844 & 0.842311 & 0.421156 \tabularnewline
98 & 0.560465 & 0.87907 & 0.439535 \tabularnewline
99 & 0.53296 & 0.93408 & 0.46704 \tabularnewline
100 & 0.546488 & 0.907025 & 0.453512 \tabularnewline
101 & 0.509411 & 0.981178 & 0.490589 \tabularnewline
102 & 0.505017 & 0.989966 & 0.494983 \tabularnewline
103 & 0.471935 & 0.943871 & 0.528065 \tabularnewline
104 & 0.75318 & 0.493639 & 0.24682 \tabularnewline
105 & 0.724242 & 0.551515 & 0.275758 \tabularnewline
106 & 0.702923 & 0.594154 & 0.297077 \tabularnewline
107 & 0.683002 & 0.633995 & 0.316998 \tabularnewline
108 & 0.660909 & 0.678182 & 0.339091 \tabularnewline
109 & 0.626832 & 0.746335 & 0.373168 \tabularnewline
110 & 0.5979 & 0.804199 & 0.4021 \tabularnewline
111 & 0.560794 & 0.878413 & 0.439206 \tabularnewline
112 & 0.55989 & 0.880219 & 0.44011 \tabularnewline
113 & 0.56175 & 0.876499 & 0.43825 \tabularnewline
114 & 0.606718 & 0.786565 & 0.393282 \tabularnewline
115 & 0.569947 & 0.860106 & 0.430053 \tabularnewline
116 & 0.53428 & 0.93144 & 0.46572 \tabularnewline
117 & 0.711562 & 0.576876 & 0.288438 \tabularnewline
118 & 0.705829 & 0.588341 & 0.294171 \tabularnewline
119 & 0.70433 & 0.59134 & 0.29567 \tabularnewline
120 & 0.692341 & 0.615318 & 0.307659 \tabularnewline
121 & 0.686163 & 0.627673 & 0.313837 \tabularnewline
122 & 0.661945 & 0.676109 & 0.338055 \tabularnewline
123 & 0.698362 & 0.603277 & 0.301638 \tabularnewline
124 & 0.66773 & 0.664541 & 0.33227 \tabularnewline
125 & 0.689446 & 0.621107 & 0.310554 \tabularnewline
126 & 0.666244 & 0.667512 & 0.333756 \tabularnewline
127 & 0.664893 & 0.670214 & 0.335107 \tabularnewline
128 & 0.665701 & 0.668599 & 0.334299 \tabularnewline
129 & 0.67334 & 0.653319 & 0.32666 \tabularnewline
130 & 0.674297 & 0.651405 & 0.325703 \tabularnewline
131 & 0.648166 & 0.703667 & 0.351834 \tabularnewline
132 & 0.614421 & 0.771158 & 0.385579 \tabularnewline
133 & 0.763861 & 0.472278 & 0.236139 \tabularnewline
134 & 0.75469 & 0.490619 & 0.24531 \tabularnewline
135 & 0.738015 & 0.52397 & 0.261985 \tabularnewline
136 & 0.708653 & 0.582694 & 0.291347 \tabularnewline
137 & 0.676314 & 0.647371 & 0.323686 \tabularnewline
138 & 0.675201 & 0.649597 & 0.324799 \tabularnewline
139 & 0.644506 & 0.710988 & 0.355494 \tabularnewline
140 & 0.670239 & 0.659522 & 0.329761 \tabularnewline
141 & 0.651507 & 0.696986 & 0.348493 \tabularnewline
142 & 0.631186 & 0.737627 & 0.368814 \tabularnewline
143 & 0.602238 & 0.795524 & 0.397762 \tabularnewline
144 & 0.604327 & 0.791346 & 0.395673 \tabularnewline
145 & 0.572907 & 0.854187 & 0.427093 \tabularnewline
146 & 0.586342 & 0.827316 & 0.413658 \tabularnewline
147 & 0.623253 & 0.753494 & 0.376747 \tabularnewline
148 & 0.591119 & 0.817762 & 0.408881 \tabularnewline
149 & 0.563187 & 0.873625 & 0.436813 \tabularnewline
150 & 0.603395 & 0.79321 & 0.396605 \tabularnewline
151 & 0.570772 & 0.858455 & 0.429228 \tabularnewline
152 & 0.568044 & 0.863912 & 0.431956 \tabularnewline
153 & 0.553782 & 0.892435 & 0.446218 \tabularnewline
154 & 0.530636 & 0.938729 & 0.469364 \tabularnewline
155 & 0.510089 & 0.979821 & 0.489911 \tabularnewline
156 & 0.500991 & 0.998018 & 0.499009 \tabularnewline
157 & 0.46328 & 0.92656 & 0.53672 \tabularnewline
158 & 0.447549 & 0.895098 & 0.552451 \tabularnewline
159 & 0.470776 & 0.941551 & 0.529224 \tabularnewline
160 & 0.502269 & 0.995463 & 0.497731 \tabularnewline
161 & 0.487194 & 0.974388 & 0.512806 \tabularnewline
162 & 0.460388 & 0.920775 & 0.539612 \tabularnewline
163 & 0.452946 & 0.905892 & 0.547054 \tabularnewline
164 & 0.445238 & 0.890476 & 0.554762 \tabularnewline
165 & 0.435598 & 0.871197 & 0.564402 \tabularnewline
166 & 0.396486 & 0.792973 & 0.603514 \tabularnewline
167 & 0.462253 & 0.924505 & 0.537747 \tabularnewline
168 & 0.442975 & 0.88595 & 0.557025 \tabularnewline
169 & 0.436133 & 0.872266 & 0.563867 \tabularnewline
170 & 0.427063 & 0.854125 & 0.572937 \tabularnewline
171 & 0.421428 & 0.842856 & 0.578572 \tabularnewline
172 & 0.405463 & 0.810927 & 0.594537 \tabularnewline
173 & 0.36555 & 0.7311 & 0.63445 \tabularnewline
174 & 0.339406 & 0.678812 & 0.660594 \tabularnewline
175 & 0.305369 & 0.610738 & 0.694631 \tabularnewline
176 & 0.268822 & 0.537644 & 0.731178 \tabularnewline
177 & 0.346318 & 0.692636 & 0.653682 \tabularnewline
178 & 0.318755 & 0.63751 & 0.681245 \tabularnewline
179 & 0.297301 & 0.594602 & 0.702699 \tabularnewline
180 & 0.264083 & 0.528166 & 0.735917 \tabularnewline
181 & 0.331956 & 0.663911 & 0.668044 \tabularnewline
182 & 0.324505 & 0.64901 & 0.675495 \tabularnewline
183 & 0.350956 & 0.701912 & 0.649044 \tabularnewline
184 & 0.375541 & 0.751081 & 0.624459 \tabularnewline
185 & 0.393376 & 0.786753 & 0.606624 \tabularnewline
186 & 0.416767 & 0.833535 & 0.583233 \tabularnewline
187 & 0.42053 & 0.841059 & 0.57947 \tabularnewline
188 & 0.418559 & 0.837118 & 0.581441 \tabularnewline
189 & 0.429507 & 0.859014 & 0.570493 \tabularnewline
190 & 0.430545 & 0.861091 & 0.569455 \tabularnewline
191 & 0.66887 & 0.662259 & 0.33113 \tabularnewline
192 & 0.67459 & 0.650819 & 0.32541 \tabularnewline
193 & 0.713313 & 0.573374 & 0.286687 \tabularnewline
194 & 0.679497 & 0.641006 & 0.320503 \tabularnewline
195 & 0.647107 & 0.705785 & 0.352893 \tabularnewline
196 & 0.61314 & 0.773721 & 0.38686 \tabularnewline
197 & 0.57651 & 0.846979 & 0.42349 \tabularnewline
198 & 0.589764 & 0.820472 & 0.410236 \tabularnewline
199 & 0.629942 & 0.740115 & 0.370058 \tabularnewline
200 & 0.803663 & 0.392675 & 0.196337 \tabularnewline
201 & 0.777016 & 0.445968 & 0.222984 \tabularnewline
202 & 0.736132 & 0.527736 & 0.263868 \tabularnewline
203 & 0.688989 & 0.622023 & 0.311011 \tabularnewline
204 & 0.674556 & 0.650889 & 0.325444 \tabularnewline
205 & 0.637316 & 0.725368 & 0.362684 \tabularnewline
206 & 0.584479 & 0.831042 & 0.415521 \tabularnewline
207 & 0.54293 & 0.914139 & 0.45707 \tabularnewline
208 & 0.496677 & 0.993355 & 0.503323 \tabularnewline
209 & 0.455271 & 0.910542 & 0.544729 \tabularnewline
210 & 0.557858 & 0.884283 & 0.442142 \tabularnewline
211 & 0.543548 & 0.912904 & 0.456452 \tabularnewline
212 & 0.582911 & 0.834178 & 0.417089 \tabularnewline
213 & 0.535151 & 0.929698 & 0.464849 \tabularnewline
214 & 0.846346 & 0.307309 & 0.153654 \tabularnewline
215 & 0.793501 & 0.412998 & 0.206499 \tabularnewline
216 & 0.991712 & 0.0165765 & 0.00828824 \tabularnewline
217 & 0.995667 & 0.00866524 & 0.00433262 \tabularnewline
218 & 0.998276 & 0.00344743 & 0.00172372 \tabularnewline
219 & 0.999997 & 5.06608e-06 & 2.53304e-06 \tabularnewline
220 & 0.999991 & 1.73487e-05 & 8.67435e-06 \tabularnewline
221 & 0.999965 & 7.03053e-05 & 3.51527e-05 \tabularnewline
222 & 0.999848 & 0.000303809 & 0.000151905 \tabularnewline
223 & 0.999857 & 0.000286111 & 0.000143055 \tabularnewline
224 & 0.999582 & 0.00083652 & 0.00041826 \tabularnewline
225 & 0.997768 & 0.00446485 & 0.00223242 \tabularnewline
226 & 0.990931 & 0.0181384 & 0.00906922 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265170&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]0.908748[/C][C]0.182503[/C][C]0.0912515[/C][/ROW]
[ROW][C]9[/C][C]0.963137[/C][C]0.0737251[/C][C]0.0368625[/C][/ROW]
[ROW][C]10[/C][C]0.940634[/C][C]0.118732[/C][C]0.0593659[/C][/ROW]
[ROW][C]11[/C][C]0.957571[/C][C]0.0848571[/C][C]0.0424285[/C][/ROW]
[ROW][C]12[/C][C]0.935035[/C][C]0.129931[/C][C]0.0649655[/C][/ROW]
[ROW][C]13[/C][C]0.909676[/C][C]0.180649[/C][C]0.0903243[/C][/ROW]
[ROW][C]14[/C][C]0.916645[/C][C]0.16671[/C][C]0.0833548[/C][/ROW]
[ROW][C]15[/C][C]0.891978[/C][C]0.216044[/C][C]0.108022[/C][/ROW]
[ROW][C]16[/C][C]0.849637[/C][C]0.300725[/C][C]0.150363[/C][/ROW]
[ROW][C]17[/C][C]0.798832[/C][C]0.402335[/C][C]0.201168[/C][/ROW]
[ROW][C]18[/C][C]0.741617[/C][C]0.516766[/C][C]0.258383[/C][/ROW]
[ROW][C]19[/C][C]0.687148[/C][C]0.625705[/C][C]0.312852[/C][/ROW]
[ROW][C]20[/C][C]0.633659[/C][C]0.732682[/C][C]0.366341[/C][/ROW]
[ROW][C]21[/C][C]0.585403[/C][C]0.829194[/C][C]0.414597[/C][/ROW]
[ROW][C]22[/C][C]0.590103[/C][C]0.819794[/C][C]0.409897[/C][/ROW]
[ROW][C]23[/C][C]0.522401[/C][C]0.955198[/C][C]0.477599[/C][/ROW]
[ROW][C]24[/C][C]0.479853[/C][C]0.959706[/C][C]0.520147[/C][/ROW]
[ROW][C]25[/C][C]0.423464[/C][C]0.846928[/C][C]0.576536[/C][/ROW]
[ROW][C]26[/C][C]0.383574[/C][C]0.767147[/C][C]0.616426[/C][/ROW]
[ROW][C]27[/C][C]0.343104[/C][C]0.686209[/C][C]0.656896[/C][/ROW]
[ROW][C]28[/C][C]0.290261[/C][C]0.580522[/C][C]0.709739[/C][/ROW]
[ROW][C]29[/C][C]0.241521[/C][C]0.483041[/C][C]0.758479[/C][/ROW]
[ROW][C]30[/C][C]0.210884[/C][C]0.421768[/C][C]0.789116[/C][/ROW]
[ROW][C]31[/C][C]0.178605[/C][C]0.35721[/C][C]0.821395[/C][/ROW]
[ROW][C]32[/C][C]0.144927[/C][C]0.289853[/C][C]0.855073[/C][/ROW]
[ROW][C]33[/C][C]0.116445[/C][C]0.232891[/C][C]0.883555[/C][/ROW]
[ROW][C]34[/C][C]0.119518[/C][C]0.239036[/C][C]0.880482[/C][/ROW]
[ROW][C]35[/C][C]0.111305[/C][C]0.22261[/C][C]0.888695[/C][/ROW]
[ROW][C]36[/C][C]0.0874363[/C][C]0.174873[/C][C]0.912564[/C][/ROW]
[ROW][C]37[/C][C]0.0694673[/C][C]0.138935[/C][C]0.930533[/C][/ROW]
[ROW][C]38[/C][C]0.0558774[/C][C]0.111755[/C][C]0.944123[/C][/ROW]
[ROW][C]39[/C][C]0.0465399[/C][C]0.0930797[/C][C]0.95346[/C][/ROW]
[ROW][C]40[/C][C]0.0369524[/C][C]0.0739048[/C][C]0.963048[/C][/ROW]
[ROW][C]41[/C][C]0.0382456[/C][C]0.0764913[/C][C]0.961754[/C][/ROW]
[ROW][C]42[/C][C]0.0499807[/C][C]0.0999614[/C][C]0.950019[/C][/ROW]
[ROW][C]43[/C][C]0.0384334[/C][C]0.0768668[/C][C]0.961567[/C][/ROW]
[ROW][C]44[/C][C]0.0536297[/C][C]0.107259[/C][C]0.94637[/C][/ROW]
[ROW][C]45[/C][C]0.0664429[/C][C]0.132886[/C][C]0.933557[/C][/ROW]
[ROW][C]46[/C][C]0.054543[/C][C]0.109086[/C][C]0.945457[/C][/ROW]
[ROW][C]47[/C][C]0.0512911[/C][C]0.102582[/C][C]0.948709[/C][/ROW]
[ROW][C]48[/C][C]0.0428694[/C][C]0.0857388[/C][C]0.957131[/C][/ROW]
[ROW][C]49[/C][C]0.035042[/C][C]0.0700841[/C][C]0.964958[/C][/ROW]
[ROW][C]50[/C][C]0.0274859[/C][C]0.0549718[/C][C]0.972514[/C][/ROW]
[ROW][C]51[/C][C]0.024072[/C][C]0.0481439[/C][C]0.975928[/C][/ROW]
[ROW][C]52[/C][C]0.0448624[/C][C]0.0897248[/C][C]0.955138[/C][/ROW]
[ROW][C]53[/C][C]0.0358158[/C][C]0.0716317[/C][C]0.964184[/C][/ROW]
[ROW][C]54[/C][C]0.0276433[/C][C]0.0552866[/C][C]0.972357[/C][/ROW]
[ROW][C]55[/C][C]0.107733[/C][C]0.215467[/C][C]0.892267[/C][/ROW]
[ROW][C]56[/C][C]0.0946422[/C][C]0.189284[/C][C]0.905358[/C][/ROW]
[ROW][C]57[/C][C]0.0764871[/C][C]0.152974[/C][C]0.923513[/C][/ROW]
[ROW][C]58[/C][C]0.15729[/C][C]0.31458[/C][C]0.84271[/C][/ROW]
[ROW][C]59[/C][C]0.153773[/C][C]0.307546[/C][C]0.846227[/C][/ROW]
[ROW][C]60[/C][C]0.147068[/C][C]0.294136[/C][C]0.852932[/C][/ROW]
[ROW][C]61[/C][C]0.146648[/C][C]0.293297[/C][C]0.853352[/C][/ROW]
[ROW][C]62[/C][C]0.165348[/C][C]0.330695[/C][C]0.834652[/C][/ROW]
[ROW][C]63[/C][C]0.161324[/C][C]0.322649[/C][C]0.838676[/C][/ROW]
[ROW][C]64[/C][C]0.315702[/C][C]0.631405[/C][C]0.684298[/C][/ROW]
[ROW][C]65[/C][C]0.334921[/C][C]0.669842[/C][C]0.665079[/C][/ROW]
[ROW][C]66[/C][C]0.487493[/C][C]0.974987[/C][C]0.512507[/C][/ROW]
[ROW][C]67[/C][C]0.552527[/C][C]0.894947[/C][C]0.447473[/C][/ROW]
[ROW][C]68[/C][C]0.515288[/C][C]0.969425[/C][C]0.484712[/C][/ROW]
[ROW][C]69[/C][C]0.558574[/C][C]0.882853[/C][C]0.441426[/C][/ROW]
[ROW][C]70[/C][C]0.610277[/C][C]0.779447[/C][C]0.389723[/C][/ROW]
[ROW][C]71[/C][C]0.619808[/C][C]0.760384[/C][C]0.380192[/C][/ROW]
[ROW][C]72[/C][C]0.62641[/C][C]0.747179[/C][C]0.37359[/C][/ROW]
[ROW][C]73[/C][C]0.650296[/C][C]0.699407[/C][C]0.349704[/C][/ROW]
[ROW][C]74[/C][C]0.653163[/C][C]0.693675[/C][C]0.346837[/C][/ROW]
[ROW][C]75[/C][C]0.721931[/C][C]0.556139[/C][C]0.278069[/C][/ROW]
[ROW][C]76[/C][C]0.783216[/C][C]0.433568[/C][C]0.216784[/C][/ROW]
[ROW][C]77[/C][C]0.762052[/C][C]0.475897[/C][C]0.237948[/C][/ROW]
[ROW][C]78[/C][C]0.750769[/C][C]0.498461[/C][C]0.249231[/C][/ROW]
[ROW][C]79[/C][C]0.831067[/C][C]0.337867[/C][C]0.168933[/C][/ROW]
[ROW][C]80[/C][C]0.830602[/C][C]0.338796[/C][C]0.169398[/C][/ROW]
[ROW][C]81[/C][C]0.811387[/C][C]0.377226[/C][C]0.188613[/C][/ROW]
[ROW][C]82[/C][C]0.802191[/C][C]0.395617[/C][C]0.197809[/C][/ROW]
[ROW][C]83[/C][C]0.801437[/C][C]0.397127[/C][C]0.198563[/C][/ROW]
[ROW][C]84[/C][C]0.775945[/C][C]0.44811[/C][C]0.224055[/C][/ROW]
[ROW][C]85[/C][C]0.746148[/C][C]0.507704[/C][C]0.253852[/C][/ROW]
[ROW][C]86[/C][C]0.714127[/C][C]0.571745[/C][C]0.285873[/C][/ROW]
[ROW][C]87[/C][C]0.697526[/C][C]0.604948[/C][C]0.302474[/C][/ROW]
[ROW][C]88[/C][C]0.731907[/C][C]0.536187[/C][C]0.268093[/C][/ROW]
[ROW][C]89[/C][C]0.747885[/C][C]0.50423[/C][C]0.252115[/C][/ROW]
[ROW][C]90[/C][C]0.729471[/C][C]0.541058[/C][C]0.270529[/C][/ROW]
[ROW][C]91[/C][C]0.702905[/C][C]0.594191[/C][C]0.297095[/C][/ROW]
[ROW][C]92[/C][C]0.669615[/C][C]0.660769[/C][C]0.330385[/C][/ROW]
[ROW][C]93[/C][C]0.694725[/C][C]0.61055[/C][C]0.305275[/C][/ROW]
[ROW][C]94[/C][C]0.665153[/C][C]0.669694[/C][C]0.334847[/C][/ROW]
[ROW][C]95[/C][C]0.648709[/C][C]0.702583[/C][C]0.351291[/C][/ROW]
[ROW][C]96[/C][C]0.615216[/C][C]0.769568[/C][C]0.384784[/C][/ROW]
[ROW][C]97[/C][C]0.578844[/C][C]0.842311[/C][C]0.421156[/C][/ROW]
[ROW][C]98[/C][C]0.560465[/C][C]0.87907[/C][C]0.439535[/C][/ROW]
[ROW][C]99[/C][C]0.53296[/C][C]0.93408[/C][C]0.46704[/C][/ROW]
[ROW][C]100[/C][C]0.546488[/C][C]0.907025[/C][C]0.453512[/C][/ROW]
[ROW][C]101[/C][C]0.509411[/C][C]0.981178[/C][C]0.490589[/C][/ROW]
[ROW][C]102[/C][C]0.505017[/C][C]0.989966[/C][C]0.494983[/C][/ROW]
[ROW][C]103[/C][C]0.471935[/C][C]0.943871[/C][C]0.528065[/C][/ROW]
[ROW][C]104[/C][C]0.75318[/C][C]0.493639[/C][C]0.24682[/C][/ROW]
[ROW][C]105[/C][C]0.724242[/C][C]0.551515[/C][C]0.275758[/C][/ROW]
[ROW][C]106[/C][C]0.702923[/C][C]0.594154[/C][C]0.297077[/C][/ROW]
[ROW][C]107[/C][C]0.683002[/C][C]0.633995[/C][C]0.316998[/C][/ROW]
[ROW][C]108[/C][C]0.660909[/C][C]0.678182[/C][C]0.339091[/C][/ROW]
[ROW][C]109[/C][C]0.626832[/C][C]0.746335[/C][C]0.373168[/C][/ROW]
[ROW][C]110[/C][C]0.5979[/C][C]0.804199[/C][C]0.4021[/C][/ROW]
[ROW][C]111[/C][C]0.560794[/C][C]0.878413[/C][C]0.439206[/C][/ROW]
[ROW][C]112[/C][C]0.55989[/C][C]0.880219[/C][C]0.44011[/C][/ROW]
[ROW][C]113[/C][C]0.56175[/C][C]0.876499[/C][C]0.43825[/C][/ROW]
[ROW][C]114[/C][C]0.606718[/C][C]0.786565[/C][C]0.393282[/C][/ROW]
[ROW][C]115[/C][C]0.569947[/C][C]0.860106[/C][C]0.430053[/C][/ROW]
[ROW][C]116[/C][C]0.53428[/C][C]0.93144[/C][C]0.46572[/C][/ROW]
[ROW][C]117[/C][C]0.711562[/C][C]0.576876[/C][C]0.288438[/C][/ROW]
[ROW][C]118[/C][C]0.705829[/C][C]0.588341[/C][C]0.294171[/C][/ROW]
[ROW][C]119[/C][C]0.70433[/C][C]0.59134[/C][C]0.29567[/C][/ROW]
[ROW][C]120[/C][C]0.692341[/C][C]0.615318[/C][C]0.307659[/C][/ROW]
[ROW][C]121[/C][C]0.686163[/C][C]0.627673[/C][C]0.313837[/C][/ROW]
[ROW][C]122[/C][C]0.661945[/C][C]0.676109[/C][C]0.338055[/C][/ROW]
[ROW][C]123[/C][C]0.698362[/C][C]0.603277[/C][C]0.301638[/C][/ROW]
[ROW][C]124[/C][C]0.66773[/C][C]0.664541[/C][C]0.33227[/C][/ROW]
[ROW][C]125[/C][C]0.689446[/C][C]0.621107[/C][C]0.310554[/C][/ROW]
[ROW][C]126[/C][C]0.666244[/C][C]0.667512[/C][C]0.333756[/C][/ROW]
[ROW][C]127[/C][C]0.664893[/C][C]0.670214[/C][C]0.335107[/C][/ROW]
[ROW][C]128[/C][C]0.665701[/C][C]0.668599[/C][C]0.334299[/C][/ROW]
[ROW][C]129[/C][C]0.67334[/C][C]0.653319[/C][C]0.32666[/C][/ROW]
[ROW][C]130[/C][C]0.674297[/C][C]0.651405[/C][C]0.325703[/C][/ROW]
[ROW][C]131[/C][C]0.648166[/C][C]0.703667[/C][C]0.351834[/C][/ROW]
[ROW][C]132[/C][C]0.614421[/C][C]0.771158[/C][C]0.385579[/C][/ROW]
[ROW][C]133[/C][C]0.763861[/C][C]0.472278[/C][C]0.236139[/C][/ROW]
[ROW][C]134[/C][C]0.75469[/C][C]0.490619[/C][C]0.24531[/C][/ROW]
[ROW][C]135[/C][C]0.738015[/C][C]0.52397[/C][C]0.261985[/C][/ROW]
[ROW][C]136[/C][C]0.708653[/C][C]0.582694[/C][C]0.291347[/C][/ROW]
[ROW][C]137[/C][C]0.676314[/C][C]0.647371[/C][C]0.323686[/C][/ROW]
[ROW][C]138[/C][C]0.675201[/C][C]0.649597[/C][C]0.324799[/C][/ROW]
[ROW][C]139[/C][C]0.644506[/C][C]0.710988[/C][C]0.355494[/C][/ROW]
[ROW][C]140[/C][C]0.670239[/C][C]0.659522[/C][C]0.329761[/C][/ROW]
[ROW][C]141[/C][C]0.651507[/C][C]0.696986[/C][C]0.348493[/C][/ROW]
[ROW][C]142[/C][C]0.631186[/C][C]0.737627[/C][C]0.368814[/C][/ROW]
[ROW][C]143[/C][C]0.602238[/C][C]0.795524[/C][C]0.397762[/C][/ROW]
[ROW][C]144[/C][C]0.604327[/C][C]0.791346[/C][C]0.395673[/C][/ROW]
[ROW][C]145[/C][C]0.572907[/C][C]0.854187[/C][C]0.427093[/C][/ROW]
[ROW][C]146[/C][C]0.586342[/C][C]0.827316[/C][C]0.413658[/C][/ROW]
[ROW][C]147[/C][C]0.623253[/C][C]0.753494[/C][C]0.376747[/C][/ROW]
[ROW][C]148[/C][C]0.591119[/C][C]0.817762[/C][C]0.408881[/C][/ROW]
[ROW][C]149[/C][C]0.563187[/C][C]0.873625[/C][C]0.436813[/C][/ROW]
[ROW][C]150[/C][C]0.603395[/C][C]0.79321[/C][C]0.396605[/C][/ROW]
[ROW][C]151[/C][C]0.570772[/C][C]0.858455[/C][C]0.429228[/C][/ROW]
[ROW][C]152[/C][C]0.568044[/C][C]0.863912[/C][C]0.431956[/C][/ROW]
[ROW][C]153[/C][C]0.553782[/C][C]0.892435[/C][C]0.446218[/C][/ROW]
[ROW][C]154[/C][C]0.530636[/C][C]0.938729[/C][C]0.469364[/C][/ROW]
[ROW][C]155[/C][C]0.510089[/C][C]0.979821[/C][C]0.489911[/C][/ROW]
[ROW][C]156[/C][C]0.500991[/C][C]0.998018[/C][C]0.499009[/C][/ROW]
[ROW][C]157[/C][C]0.46328[/C][C]0.92656[/C][C]0.53672[/C][/ROW]
[ROW][C]158[/C][C]0.447549[/C][C]0.895098[/C][C]0.552451[/C][/ROW]
[ROW][C]159[/C][C]0.470776[/C][C]0.941551[/C][C]0.529224[/C][/ROW]
[ROW][C]160[/C][C]0.502269[/C][C]0.995463[/C][C]0.497731[/C][/ROW]
[ROW][C]161[/C][C]0.487194[/C][C]0.974388[/C][C]0.512806[/C][/ROW]
[ROW][C]162[/C][C]0.460388[/C][C]0.920775[/C][C]0.539612[/C][/ROW]
[ROW][C]163[/C][C]0.452946[/C][C]0.905892[/C][C]0.547054[/C][/ROW]
[ROW][C]164[/C][C]0.445238[/C][C]0.890476[/C][C]0.554762[/C][/ROW]
[ROW][C]165[/C][C]0.435598[/C][C]0.871197[/C][C]0.564402[/C][/ROW]
[ROW][C]166[/C][C]0.396486[/C][C]0.792973[/C][C]0.603514[/C][/ROW]
[ROW][C]167[/C][C]0.462253[/C][C]0.924505[/C][C]0.537747[/C][/ROW]
[ROW][C]168[/C][C]0.442975[/C][C]0.88595[/C][C]0.557025[/C][/ROW]
[ROW][C]169[/C][C]0.436133[/C][C]0.872266[/C][C]0.563867[/C][/ROW]
[ROW][C]170[/C][C]0.427063[/C][C]0.854125[/C][C]0.572937[/C][/ROW]
[ROW][C]171[/C][C]0.421428[/C][C]0.842856[/C][C]0.578572[/C][/ROW]
[ROW][C]172[/C][C]0.405463[/C][C]0.810927[/C][C]0.594537[/C][/ROW]
[ROW][C]173[/C][C]0.36555[/C][C]0.7311[/C][C]0.63445[/C][/ROW]
[ROW][C]174[/C][C]0.339406[/C][C]0.678812[/C][C]0.660594[/C][/ROW]
[ROW][C]175[/C][C]0.305369[/C][C]0.610738[/C][C]0.694631[/C][/ROW]
[ROW][C]176[/C][C]0.268822[/C][C]0.537644[/C][C]0.731178[/C][/ROW]
[ROW][C]177[/C][C]0.346318[/C][C]0.692636[/C][C]0.653682[/C][/ROW]
[ROW][C]178[/C][C]0.318755[/C][C]0.63751[/C][C]0.681245[/C][/ROW]
[ROW][C]179[/C][C]0.297301[/C][C]0.594602[/C][C]0.702699[/C][/ROW]
[ROW][C]180[/C][C]0.264083[/C][C]0.528166[/C][C]0.735917[/C][/ROW]
[ROW][C]181[/C][C]0.331956[/C][C]0.663911[/C][C]0.668044[/C][/ROW]
[ROW][C]182[/C][C]0.324505[/C][C]0.64901[/C][C]0.675495[/C][/ROW]
[ROW][C]183[/C][C]0.350956[/C][C]0.701912[/C][C]0.649044[/C][/ROW]
[ROW][C]184[/C][C]0.375541[/C][C]0.751081[/C][C]0.624459[/C][/ROW]
[ROW][C]185[/C][C]0.393376[/C][C]0.786753[/C][C]0.606624[/C][/ROW]
[ROW][C]186[/C][C]0.416767[/C][C]0.833535[/C][C]0.583233[/C][/ROW]
[ROW][C]187[/C][C]0.42053[/C][C]0.841059[/C][C]0.57947[/C][/ROW]
[ROW][C]188[/C][C]0.418559[/C][C]0.837118[/C][C]0.581441[/C][/ROW]
[ROW][C]189[/C][C]0.429507[/C][C]0.859014[/C][C]0.570493[/C][/ROW]
[ROW][C]190[/C][C]0.430545[/C][C]0.861091[/C][C]0.569455[/C][/ROW]
[ROW][C]191[/C][C]0.66887[/C][C]0.662259[/C][C]0.33113[/C][/ROW]
[ROW][C]192[/C][C]0.67459[/C][C]0.650819[/C][C]0.32541[/C][/ROW]
[ROW][C]193[/C][C]0.713313[/C][C]0.573374[/C][C]0.286687[/C][/ROW]
[ROW][C]194[/C][C]0.679497[/C][C]0.641006[/C][C]0.320503[/C][/ROW]
[ROW][C]195[/C][C]0.647107[/C][C]0.705785[/C][C]0.352893[/C][/ROW]
[ROW][C]196[/C][C]0.61314[/C][C]0.773721[/C][C]0.38686[/C][/ROW]
[ROW][C]197[/C][C]0.57651[/C][C]0.846979[/C][C]0.42349[/C][/ROW]
[ROW][C]198[/C][C]0.589764[/C][C]0.820472[/C][C]0.410236[/C][/ROW]
[ROW][C]199[/C][C]0.629942[/C][C]0.740115[/C][C]0.370058[/C][/ROW]
[ROW][C]200[/C][C]0.803663[/C][C]0.392675[/C][C]0.196337[/C][/ROW]
[ROW][C]201[/C][C]0.777016[/C][C]0.445968[/C][C]0.222984[/C][/ROW]
[ROW][C]202[/C][C]0.736132[/C][C]0.527736[/C][C]0.263868[/C][/ROW]
[ROW][C]203[/C][C]0.688989[/C][C]0.622023[/C][C]0.311011[/C][/ROW]
[ROW][C]204[/C][C]0.674556[/C][C]0.650889[/C][C]0.325444[/C][/ROW]
[ROW][C]205[/C][C]0.637316[/C][C]0.725368[/C][C]0.362684[/C][/ROW]
[ROW][C]206[/C][C]0.584479[/C][C]0.831042[/C][C]0.415521[/C][/ROW]
[ROW][C]207[/C][C]0.54293[/C][C]0.914139[/C][C]0.45707[/C][/ROW]
[ROW][C]208[/C][C]0.496677[/C][C]0.993355[/C][C]0.503323[/C][/ROW]
[ROW][C]209[/C][C]0.455271[/C][C]0.910542[/C][C]0.544729[/C][/ROW]
[ROW][C]210[/C][C]0.557858[/C][C]0.884283[/C][C]0.442142[/C][/ROW]
[ROW][C]211[/C][C]0.543548[/C][C]0.912904[/C][C]0.456452[/C][/ROW]
[ROW][C]212[/C][C]0.582911[/C][C]0.834178[/C][C]0.417089[/C][/ROW]
[ROW][C]213[/C][C]0.535151[/C][C]0.929698[/C][C]0.464849[/C][/ROW]
[ROW][C]214[/C][C]0.846346[/C][C]0.307309[/C][C]0.153654[/C][/ROW]
[ROW][C]215[/C][C]0.793501[/C][C]0.412998[/C][C]0.206499[/C][/ROW]
[ROW][C]216[/C][C]0.991712[/C][C]0.0165765[/C][C]0.00828824[/C][/ROW]
[ROW][C]217[/C][C]0.995667[/C][C]0.00866524[/C][C]0.00433262[/C][/ROW]
[ROW][C]218[/C][C]0.998276[/C][C]0.00344743[/C][C]0.00172372[/C][/ROW]
[ROW][C]219[/C][C]0.999997[/C][C]5.06608e-06[/C][C]2.53304e-06[/C][/ROW]
[ROW][C]220[/C][C]0.999991[/C][C]1.73487e-05[/C][C]8.67435e-06[/C][/ROW]
[ROW][C]221[/C][C]0.999965[/C][C]7.03053e-05[/C][C]3.51527e-05[/C][/ROW]
[ROW][C]222[/C][C]0.999848[/C][C]0.000303809[/C][C]0.000151905[/C][/ROW]
[ROW][C]223[/C][C]0.999857[/C][C]0.000286111[/C][C]0.000143055[/C][/ROW]
[ROW][C]224[/C][C]0.999582[/C][C]0.00083652[/C][C]0.00041826[/C][/ROW]
[ROW][C]225[/C][C]0.997768[/C][C]0.00446485[/C][C]0.00223242[/C][/ROW]
[ROW][C]226[/C][C]0.990931[/C][C]0.0181384[/C][C]0.00906922[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265170&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265170&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
80.9087480.1825030.0912515
90.9631370.07372510.0368625
100.9406340.1187320.0593659
110.9575710.08485710.0424285
120.9350350.1299310.0649655
130.9096760.1806490.0903243
140.9166450.166710.0833548
150.8919780.2160440.108022
160.8496370.3007250.150363
170.7988320.4023350.201168
180.7416170.5167660.258383
190.6871480.6257050.312852
200.6336590.7326820.366341
210.5854030.8291940.414597
220.5901030.8197940.409897
230.5224010.9551980.477599
240.4798530.9597060.520147
250.4234640.8469280.576536
260.3835740.7671470.616426
270.3431040.6862090.656896
280.2902610.5805220.709739
290.2415210.4830410.758479
300.2108840.4217680.789116
310.1786050.357210.821395
320.1449270.2898530.855073
330.1164450.2328910.883555
340.1195180.2390360.880482
350.1113050.222610.888695
360.08743630.1748730.912564
370.06946730.1389350.930533
380.05587740.1117550.944123
390.04653990.09307970.95346
400.03695240.07390480.963048
410.03824560.07649130.961754
420.04998070.09996140.950019
430.03843340.07686680.961567
440.05362970.1072590.94637
450.06644290.1328860.933557
460.0545430.1090860.945457
470.05129110.1025820.948709
480.04286940.08573880.957131
490.0350420.07008410.964958
500.02748590.05497180.972514
510.0240720.04814390.975928
520.04486240.08972480.955138
530.03581580.07163170.964184
540.02764330.05528660.972357
550.1077330.2154670.892267
560.09464220.1892840.905358
570.07648710.1529740.923513
580.157290.314580.84271
590.1537730.3075460.846227
600.1470680.2941360.852932
610.1466480.2932970.853352
620.1653480.3306950.834652
630.1613240.3226490.838676
640.3157020.6314050.684298
650.3349210.6698420.665079
660.4874930.9749870.512507
670.5525270.8949470.447473
680.5152880.9694250.484712
690.5585740.8828530.441426
700.6102770.7794470.389723
710.6198080.7603840.380192
720.626410.7471790.37359
730.6502960.6994070.349704
740.6531630.6936750.346837
750.7219310.5561390.278069
760.7832160.4335680.216784
770.7620520.4758970.237948
780.7507690.4984610.249231
790.8310670.3378670.168933
800.8306020.3387960.169398
810.8113870.3772260.188613
820.8021910.3956170.197809
830.8014370.3971270.198563
840.7759450.448110.224055
850.7461480.5077040.253852
860.7141270.5717450.285873
870.6975260.6049480.302474
880.7319070.5361870.268093
890.7478850.504230.252115
900.7294710.5410580.270529
910.7029050.5941910.297095
920.6696150.6607690.330385
930.6947250.610550.305275
940.6651530.6696940.334847
950.6487090.7025830.351291
960.6152160.7695680.384784
970.5788440.8423110.421156
980.5604650.879070.439535
990.532960.934080.46704
1000.5464880.9070250.453512
1010.5094110.9811780.490589
1020.5050170.9899660.494983
1030.4719350.9438710.528065
1040.753180.4936390.24682
1050.7242420.5515150.275758
1060.7029230.5941540.297077
1070.6830020.6339950.316998
1080.6609090.6781820.339091
1090.6268320.7463350.373168
1100.59790.8041990.4021
1110.5607940.8784130.439206
1120.559890.8802190.44011
1130.561750.8764990.43825
1140.6067180.7865650.393282
1150.5699470.8601060.430053
1160.534280.931440.46572
1170.7115620.5768760.288438
1180.7058290.5883410.294171
1190.704330.591340.29567
1200.6923410.6153180.307659
1210.6861630.6276730.313837
1220.6619450.6761090.338055
1230.6983620.6032770.301638
1240.667730.6645410.33227
1250.6894460.6211070.310554
1260.6662440.6675120.333756
1270.6648930.6702140.335107
1280.6657010.6685990.334299
1290.673340.6533190.32666
1300.6742970.6514050.325703
1310.6481660.7036670.351834
1320.6144210.7711580.385579
1330.7638610.4722780.236139
1340.754690.4906190.24531
1350.7380150.523970.261985
1360.7086530.5826940.291347
1370.6763140.6473710.323686
1380.6752010.6495970.324799
1390.6445060.7109880.355494
1400.6702390.6595220.329761
1410.6515070.6969860.348493
1420.6311860.7376270.368814
1430.6022380.7955240.397762
1440.6043270.7913460.395673
1450.5729070.8541870.427093
1460.5863420.8273160.413658
1470.6232530.7534940.376747
1480.5911190.8177620.408881
1490.5631870.8736250.436813
1500.6033950.793210.396605
1510.5707720.8584550.429228
1520.5680440.8639120.431956
1530.5537820.8924350.446218
1540.5306360.9387290.469364
1550.5100890.9798210.489911
1560.5009910.9980180.499009
1570.463280.926560.53672
1580.4475490.8950980.552451
1590.4707760.9415510.529224
1600.5022690.9954630.497731
1610.4871940.9743880.512806
1620.4603880.9207750.539612
1630.4529460.9058920.547054
1640.4452380.8904760.554762
1650.4355980.8711970.564402
1660.3964860.7929730.603514
1670.4622530.9245050.537747
1680.4429750.885950.557025
1690.4361330.8722660.563867
1700.4270630.8541250.572937
1710.4214280.8428560.578572
1720.4054630.8109270.594537
1730.365550.73110.63445
1740.3394060.6788120.660594
1750.3053690.6107380.694631
1760.2688220.5376440.731178
1770.3463180.6926360.653682
1780.3187550.637510.681245
1790.2973010.5946020.702699
1800.2640830.5281660.735917
1810.3319560.6639110.668044
1820.3245050.649010.675495
1830.3509560.7019120.649044
1840.3755410.7510810.624459
1850.3933760.7867530.606624
1860.4167670.8335350.583233
1870.420530.8410590.57947
1880.4185590.8371180.581441
1890.4295070.8590140.570493
1900.4305450.8610910.569455
1910.668870.6622590.33113
1920.674590.6508190.32541
1930.7133130.5733740.286687
1940.6794970.6410060.320503
1950.6471070.7057850.352893
1960.613140.7737210.38686
1970.576510.8469790.42349
1980.5897640.8204720.410236
1990.6299420.7401150.370058
2000.8036630.3926750.196337
2010.7770160.4459680.222984
2020.7361320.5277360.263868
2030.6889890.6220230.311011
2040.6745560.6508890.325444
2050.6373160.7253680.362684
2060.5844790.8310420.415521
2070.542930.9141390.45707
2080.4966770.9933550.503323
2090.4552710.9105420.544729
2100.5578580.8842830.442142
2110.5435480.9129040.456452
2120.5829110.8341780.417089
2130.5351510.9296980.464849
2140.8463460.3073090.153654
2150.7935010.4129980.206499
2160.9917120.01657650.00828824
2170.9956670.008665240.00433262
2180.9982760.003447430.00172372
2190.9999975.06608e-062.53304e-06
2200.9999911.73487e-058.67435e-06
2210.9999657.03053e-053.51527e-05
2220.9998480.0003038090.000151905
2230.9998570.0002861110.000143055
2240.9995820.000836520.00041826
2250.9977680.004464850.00223242
2260.9909310.01813840.00906922






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level90.0410959NOK
5% type I error level120.0547945NOK
10% type I error level250.114155NOK

\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 & 0.0410959 & NOK \tabularnewline
5% type I error level & 12 & 0.0547945 & NOK \tabularnewline
10% type I error level & 25 & 0.114155 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265170&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]0.0410959[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]12[/C][C]0.0547945[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]25[/C][C]0.114155[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265170&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265170&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level90.0410959NOK
5% type I error level120.0547945NOK
10% type I error level250.114155NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = 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')
}