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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 computationThu, 11 Dec 2014 10:32:23 +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/11/t1418294066krmysdaju9zyd2p.htm/, Retrieved Thu, 16 May 2024 15:34:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265691, Retrieved Thu, 16 May 2024 15:34:25 +0000
QR Codes:

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

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataset

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

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

\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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265691&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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265691&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265691&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






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.30523 -0.00282747LFM[t] + 0.0165657Blogs[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  4.30523 -0.00282747LFM[t] +  0.0165657Blogs[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265691&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  4.30523 -0.00282747LFM[t] +  0.0165657Blogs[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265691&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265691&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.30523 -0.00282747LFM[t] + 0.0165657Blogs[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.305230.442449.7312.01586e-191.00793e-19
LFM-0.002827470.00363106-0.77870.4368320.218416
Blogs0.01656570.002050698.0782.08487e-141.04244e-14

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 4.30523 & 0.44244 & 9.731 & 2.01586e-19 & 1.00793e-19 \tabularnewline
LFM & -0.00282747 & 0.00363106 & -0.7787 & 0.436832 & 0.218416 \tabularnewline
Blogs & 0.0165657 & 0.00205069 & 8.078 & 2.08487e-14 & 1.04244e-14 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265691&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]4.30523[/C][C]0.44244[/C][C]9.731[/C][C]2.01586e-19[/C][C]1.00793e-19[/C][/ROW]
[ROW][C]LFM[/C][C]-0.00282747[/C][C]0.00363106[/C][C]-0.7787[/C][C]0.436832[/C][C]0.218416[/C][/ROW]
[ROW][C]Blogs[/C][C]0.0165657[/C][C]0.00205069[/C][C]8.078[/C][C]2.08487e-14[/C][C]1.04244e-14[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265691&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265691&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.305230.442449.7312.01586e-191.00793e-19
LFM-0.002827470.00363106-0.77870.4368320.218416
Blogs0.01656570.002050698.0782.08487e-141.04244e-14






Multiple Linear Regression - Regression Statistics
Multiple R0.44848
R-squared0.201135
Adjusted R-squared0.195325
F-TEST (value)34.6191
F-TEST (DF numerator)2
F-TEST (DF denominator)275
p-value3.88578e-14
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.27276
Sum Squared Residuals1420.5

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.44848 \tabularnewline
R-squared & 0.201135 \tabularnewline
Adjusted R-squared & 0.195325 \tabularnewline
F-TEST (value) & 34.6191 \tabularnewline
F-TEST (DF numerator) & 2 \tabularnewline
F-TEST (DF denominator) & 275 \tabularnewline
p-value & 3.88578e-14 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.27276 \tabularnewline
Sum Squared Residuals & 1420.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265691&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.44848[/C][/ROW]
[ROW][C]R-squared[/C][C]0.201135[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.195325[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]34.6191[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]2[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]275[/C][/ROW]
[ROW][C]p-value[/C][C]3.88578e-14[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.27276[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1420.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265691&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265691&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 R0.44848
R-squared0.201135
Adjusted R-squared0.195325
F-TEST (value)34.6191
F-TEST (DF numerator)2
F-TEST (DF denominator)275
p-value3.88578e-14
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.27276
Sum Squared Residuals1420.5






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.55.474242.02576
265.071810.928189
36.55.344551.15545
415.74698-4.74698
515.08635-4.08635
65.56.58744-1.08744
78.55.744152.75585
86.56.012790.487205
94.55.67789-1.17789
1026.45042-4.45042
1155.76032-0.760318
120.56.85405-6.35405
1355.24432-0.244321
1456.14336-1.14336
152.54.73235-2.23235
1655.37319-0.373187
175.56.36234-0.862338
183.55.5615-2.0615
1935.55787-2.55787
2045.35463-1.35463
210.54.9991-4.4991
226.55.55990.9401
234.55.45289-0.952889
247.55.231452.26855
255.55.7393-0.239295
2646.44806-2.44806
277.56.156261.34374
2875.320661.67934
2944.97445-0.974447
305.55.413240.0867625
312.55.77885-3.27885
325.56.03425-0.534251
333.55.62171-2.12171
342.56.51708-4.01708
354.55.99623-1.49623
364.56.13481-1.63481
374.55.15384-0.653842
3865.723930.276073
392.55.24396-2.74396
4056.64435-1.64435
4104.78654-4.78654
4256.41323-1.41323
436.55.089611.41039
4455.61688-0.616882
4565.165480.834517
464.55.78094-1.28094
475.56.05118-0.551182
4815.24349-4.24349
497.54.670982.82902
5065.031360.968639
5155.58412-0.584116
5215.64426-4.64426
5355.97404-0.974042
546.55.58980.910195
5576.403520.596481
564.56.39583-1.89583
5705.26857-5.26857
588.55.521912.97809
593.54.58083-1.08083
607.55.67381.8262
613.55.79628-2.29628
6264.807991.19201
631.55.06895-3.56895
6496.036712.96329
653.54.60761-1.10761
663.55.11256-1.61256
6746.30579-2.30579
686.56.052480.44752
697.55.330842.16916
7065.104510.89549
7155.90861-0.908611
725.55.058870.441129
733.55.58126-2.08126
747.55.267742.23226
756.56.032620.467379
766.56.265770.234229
776.55.14291.3571
7876.936880.0631195
793.55.43782-1.93782
801.55.40229-3.90229
8144.92834-0.928342
827.54.739272.76073
834.55.8152-1.3152
8404.5942-4.5942
853.54.94008-1.44008
865.55.57926-0.0792597
8755.02328-0.0232782
884.55.12307-0.623071
892.54.6443-2.1443
907.54.856862.64314
9174.990552.00945
9205.0431-5.0431
934.55.16838-0.668378
9435.66006-2.66006
951.55.48592-3.98592
963.54.54291-1.04291
972.55.63867-3.13867
985.55.038650.461354
9985.361882.63812
10014.80593-3.80593
10155.39943-0.399432
1024.55.50774-1.00774
10334.80753-1.80753
10434.84877-1.84877
10585.62412.3759
1062.54.72915-2.22915
10774.88392.1161
10805.03339-5.03339
10915.05275-4.05275
1103.54.87299-1.37299
1115.54.816440.68356
1125.54.654810.845192
1130.54.84871-4.34871
1147.56.582450.917553
11596.896072.10393
1169.57.050412.44959
1178.58.353810.146189
11874.692762.30724
119811.029-3.02904
120107.403552.59645
12179.50456-2.50456
1228.55.07663.4234
12398.726770.273228
1249.55.603043.89696
12547.33562-3.33562
12666.60876-0.60876
12787.211610.788389
1285.58.93966-3.43966
1299.57.695241.80476
1307.55.808751.69125
13175.407551.59245
1327.58.84153-1.34153
13386.434621.56538
13476.940070.0599265
13576.081050.918947
13667.50247-1.50247
137106.563923.43608
1382.56.33516-3.83516
13998.784550.215448
14089.32513-1.32513
14165.413170.58683
1428.54.99833.5017
14366.28839-0.288391
14498.024130.975873
14587.130810.869188
14697.191821.80818
1475.56.06978-0.569777
14876.531590.468413
1495.58.88514-3.38514
15097.595881.40412
15126.97487-4.97487
1528.56.964721.53528
15397.376071.62393
1548.58.275070.224925
15596.26652.7335
1567.57.018840.481157
157107.85852.1415
15897.133211.86679
1597.58.93321-1.43321
16066.08914-0.0891363
16110.56.241094.25891
1628.59.11177-0.611773
16386.416891.58311
164105.889884.11012
16510.56.87873.6213
1666.55.02811.4719
1679.57.902911.59709
1688.54.696423.80358
1697.57.76633-0.266328
17057.22086-2.22086
17187.567540.43246
172106.38213.6179
17375.877871.12213
1747.57.51628-0.0162801
1757.57.51628-0.0162801
1769.56.628152.87185
17766.70493-0.704927
178107.983352.01665
17975.963131.03687
18036.1877-3.1877
18167.13198-1.13198
18276.414830.585171
183108.405971.59403
18476.860470.139528
1853.55.28111-1.78111
18686.777241.22276
187105.689564.31044
1885.55.74169-0.24169
18964.01321.9868
1906.56.435390.0646146
1916.55.709320.790677
1928.56.150582.34942
19345.30569-1.30569
1949.56.327143.17286
19585.959442.04056
1968.57.511360.988644
1975.58.31789-2.81789
19876.952580.0474193
19995.360253.63975
20086.064921.93508
201107.907442.09256
20285.960242.03976
20366.09323-0.0932284
20487.469780.530224
20555.48432-0.484323
20695.386093.61391
2074.57.01355-2.51355
2088.55.533152.96685
2099.58.34131.1587
2108.57.100871.39913
2117.55.014762.48524
2127.55.813641.68636
21357.63058-2.63058
21478.16267-1.16267
21588.49163-0.491626
2165.56.46572-0.965723
2178.56.303292.19671
2189.56.808812.69119
21975.76751.2325
22087.73240.267602
2218.57.777270.722728
2223.56.45275-2.95275
2236.55.402291.09771
2246.55.028171.47183
22510.57.742542.75746
2268.55.902862.59714
22786.154241.84576
228106.083083.91692
229107.574432.42557
2309.57.180512.31949
23195.685573.31443
232108.514641.48536
2337.55.613591.88641
2344.55.70214-1.20214
2354.55.43097-0.930967
2360.55.58568-5.08568
2376.55.196591.30341
2384.57.57283-3.07283
2395.56.88509-1.38509
24055.42328-0.423283
24167.42613-1.42613
24247.17519-3.17519
24385.391782.60822
24410.56.87873.6213
2456.55.536410.963585
24687.710180.289822
2478.57.767590.732407
2485.55.65846-0.158462
24977.60999-0.609986
25056.05241-1.05241
2513.55.41121-1.91121
25257.35056-2.35056
25397.418851.58115
2548.56.693581.80642
25556.12194-1.12194
2569.57.738051.76195
25734.85316-1.85316
2581.57.28915-5.78915
25965.386130.613873
2600.55.31704-4.81704
2616.55.02811.4719
2627.55.795811.70419
2634.55.95824-1.45824
26485.391782.60822
26597.272191.72781
2667.56.661650.83835
2678.56.691161.80884
26875.239461.76054
2699.55.730383.76962
2706.55.104881.39512
2719.55.208364.29164
27265.324690.675313
27387.112580.887417
2749.58.389771.11023
27586.178451.82155
27686.277051.72295
27797.215641.78436
27855.5097-0.509703

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 5.47424 & 2.02576 \tabularnewline
2 & 6 & 5.07181 & 0.928189 \tabularnewline
3 & 6.5 & 5.34455 & 1.15545 \tabularnewline
4 & 1 & 5.74698 & -4.74698 \tabularnewline
5 & 1 & 5.08635 & -4.08635 \tabularnewline
6 & 5.5 & 6.58744 & -1.08744 \tabularnewline
7 & 8.5 & 5.74415 & 2.75585 \tabularnewline
8 & 6.5 & 6.01279 & 0.487205 \tabularnewline
9 & 4.5 & 5.67789 & -1.17789 \tabularnewline
10 & 2 & 6.45042 & -4.45042 \tabularnewline
11 & 5 & 5.76032 & -0.760318 \tabularnewline
12 & 0.5 & 6.85405 & -6.35405 \tabularnewline
13 & 5 & 5.24432 & -0.244321 \tabularnewline
14 & 5 & 6.14336 & -1.14336 \tabularnewline
15 & 2.5 & 4.73235 & -2.23235 \tabularnewline
16 & 5 & 5.37319 & -0.373187 \tabularnewline
17 & 5.5 & 6.36234 & -0.862338 \tabularnewline
18 & 3.5 & 5.5615 & -2.0615 \tabularnewline
19 & 3 & 5.55787 & -2.55787 \tabularnewline
20 & 4 & 5.35463 & -1.35463 \tabularnewline
21 & 0.5 & 4.9991 & -4.4991 \tabularnewline
22 & 6.5 & 5.5599 & 0.9401 \tabularnewline
23 & 4.5 & 5.45289 & -0.952889 \tabularnewline
24 & 7.5 & 5.23145 & 2.26855 \tabularnewline
25 & 5.5 & 5.7393 & -0.239295 \tabularnewline
26 & 4 & 6.44806 & -2.44806 \tabularnewline
27 & 7.5 & 6.15626 & 1.34374 \tabularnewline
28 & 7 & 5.32066 & 1.67934 \tabularnewline
29 & 4 & 4.97445 & -0.974447 \tabularnewline
30 & 5.5 & 5.41324 & 0.0867625 \tabularnewline
31 & 2.5 & 5.77885 & -3.27885 \tabularnewline
32 & 5.5 & 6.03425 & -0.534251 \tabularnewline
33 & 3.5 & 5.62171 & -2.12171 \tabularnewline
34 & 2.5 & 6.51708 & -4.01708 \tabularnewline
35 & 4.5 & 5.99623 & -1.49623 \tabularnewline
36 & 4.5 & 6.13481 & -1.63481 \tabularnewline
37 & 4.5 & 5.15384 & -0.653842 \tabularnewline
38 & 6 & 5.72393 & 0.276073 \tabularnewline
39 & 2.5 & 5.24396 & -2.74396 \tabularnewline
40 & 5 & 6.64435 & -1.64435 \tabularnewline
41 & 0 & 4.78654 & -4.78654 \tabularnewline
42 & 5 & 6.41323 & -1.41323 \tabularnewline
43 & 6.5 & 5.08961 & 1.41039 \tabularnewline
44 & 5 & 5.61688 & -0.616882 \tabularnewline
45 & 6 & 5.16548 & 0.834517 \tabularnewline
46 & 4.5 & 5.78094 & -1.28094 \tabularnewline
47 & 5.5 & 6.05118 & -0.551182 \tabularnewline
48 & 1 & 5.24349 & -4.24349 \tabularnewline
49 & 7.5 & 4.67098 & 2.82902 \tabularnewline
50 & 6 & 5.03136 & 0.968639 \tabularnewline
51 & 5 & 5.58412 & -0.584116 \tabularnewline
52 & 1 & 5.64426 & -4.64426 \tabularnewline
53 & 5 & 5.97404 & -0.974042 \tabularnewline
54 & 6.5 & 5.5898 & 0.910195 \tabularnewline
55 & 7 & 6.40352 & 0.596481 \tabularnewline
56 & 4.5 & 6.39583 & -1.89583 \tabularnewline
57 & 0 & 5.26857 & -5.26857 \tabularnewline
58 & 8.5 & 5.52191 & 2.97809 \tabularnewline
59 & 3.5 & 4.58083 & -1.08083 \tabularnewline
60 & 7.5 & 5.6738 & 1.8262 \tabularnewline
61 & 3.5 & 5.79628 & -2.29628 \tabularnewline
62 & 6 & 4.80799 & 1.19201 \tabularnewline
63 & 1.5 & 5.06895 & -3.56895 \tabularnewline
64 & 9 & 6.03671 & 2.96329 \tabularnewline
65 & 3.5 & 4.60761 & -1.10761 \tabularnewline
66 & 3.5 & 5.11256 & -1.61256 \tabularnewline
67 & 4 & 6.30579 & -2.30579 \tabularnewline
68 & 6.5 & 6.05248 & 0.44752 \tabularnewline
69 & 7.5 & 5.33084 & 2.16916 \tabularnewline
70 & 6 & 5.10451 & 0.89549 \tabularnewline
71 & 5 & 5.90861 & -0.908611 \tabularnewline
72 & 5.5 & 5.05887 & 0.441129 \tabularnewline
73 & 3.5 & 5.58126 & -2.08126 \tabularnewline
74 & 7.5 & 5.26774 & 2.23226 \tabularnewline
75 & 6.5 & 6.03262 & 0.467379 \tabularnewline
76 & 6.5 & 6.26577 & 0.234229 \tabularnewline
77 & 6.5 & 5.1429 & 1.3571 \tabularnewline
78 & 7 & 6.93688 & 0.0631195 \tabularnewline
79 & 3.5 & 5.43782 & -1.93782 \tabularnewline
80 & 1.5 & 5.40229 & -3.90229 \tabularnewline
81 & 4 & 4.92834 & -0.928342 \tabularnewline
82 & 7.5 & 4.73927 & 2.76073 \tabularnewline
83 & 4.5 & 5.8152 & -1.3152 \tabularnewline
84 & 0 & 4.5942 & -4.5942 \tabularnewline
85 & 3.5 & 4.94008 & -1.44008 \tabularnewline
86 & 5.5 & 5.57926 & -0.0792597 \tabularnewline
87 & 5 & 5.02328 & -0.0232782 \tabularnewline
88 & 4.5 & 5.12307 & -0.623071 \tabularnewline
89 & 2.5 & 4.6443 & -2.1443 \tabularnewline
90 & 7.5 & 4.85686 & 2.64314 \tabularnewline
91 & 7 & 4.99055 & 2.00945 \tabularnewline
92 & 0 & 5.0431 & -5.0431 \tabularnewline
93 & 4.5 & 5.16838 & -0.668378 \tabularnewline
94 & 3 & 5.66006 & -2.66006 \tabularnewline
95 & 1.5 & 5.48592 & -3.98592 \tabularnewline
96 & 3.5 & 4.54291 & -1.04291 \tabularnewline
97 & 2.5 & 5.63867 & -3.13867 \tabularnewline
98 & 5.5 & 5.03865 & 0.461354 \tabularnewline
99 & 8 & 5.36188 & 2.63812 \tabularnewline
100 & 1 & 4.80593 & -3.80593 \tabularnewline
101 & 5 & 5.39943 & -0.399432 \tabularnewline
102 & 4.5 & 5.50774 & -1.00774 \tabularnewline
103 & 3 & 4.80753 & -1.80753 \tabularnewline
104 & 3 & 4.84877 & -1.84877 \tabularnewline
105 & 8 & 5.6241 & 2.3759 \tabularnewline
106 & 2.5 & 4.72915 & -2.22915 \tabularnewline
107 & 7 & 4.8839 & 2.1161 \tabularnewline
108 & 0 & 5.03339 & -5.03339 \tabularnewline
109 & 1 & 5.05275 & -4.05275 \tabularnewline
110 & 3.5 & 4.87299 & -1.37299 \tabularnewline
111 & 5.5 & 4.81644 & 0.68356 \tabularnewline
112 & 5.5 & 4.65481 & 0.845192 \tabularnewline
113 & 0.5 & 4.84871 & -4.34871 \tabularnewline
114 & 7.5 & 6.58245 & 0.917553 \tabularnewline
115 & 9 & 6.89607 & 2.10393 \tabularnewline
116 & 9.5 & 7.05041 & 2.44959 \tabularnewline
117 & 8.5 & 8.35381 & 0.146189 \tabularnewline
118 & 7 & 4.69276 & 2.30724 \tabularnewline
119 & 8 & 11.029 & -3.02904 \tabularnewline
120 & 10 & 7.40355 & 2.59645 \tabularnewline
121 & 7 & 9.50456 & -2.50456 \tabularnewline
122 & 8.5 & 5.0766 & 3.4234 \tabularnewline
123 & 9 & 8.72677 & 0.273228 \tabularnewline
124 & 9.5 & 5.60304 & 3.89696 \tabularnewline
125 & 4 & 7.33562 & -3.33562 \tabularnewline
126 & 6 & 6.60876 & -0.60876 \tabularnewline
127 & 8 & 7.21161 & 0.788389 \tabularnewline
128 & 5.5 & 8.93966 & -3.43966 \tabularnewline
129 & 9.5 & 7.69524 & 1.80476 \tabularnewline
130 & 7.5 & 5.80875 & 1.69125 \tabularnewline
131 & 7 & 5.40755 & 1.59245 \tabularnewline
132 & 7.5 & 8.84153 & -1.34153 \tabularnewline
133 & 8 & 6.43462 & 1.56538 \tabularnewline
134 & 7 & 6.94007 & 0.0599265 \tabularnewline
135 & 7 & 6.08105 & 0.918947 \tabularnewline
136 & 6 & 7.50247 & -1.50247 \tabularnewline
137 & 10 & 6.56392 & 3.43608 \tabularnewline
138 & 2.5 & 6.33516 & -3.83516 \tabularnewline
139 & 9 & 8.78455 & 0.215448 \tabularnewline
140 & 8 & 9.32513 & -1.32513 \tabularnewline
141 & 6 & 5.41317 & 0.58683 \tabularnewline
142 & 8.5 & 4.9983 & 3.5017 \tabularnewline
143 & 6 & 6.28839 & -0.288391 \tabularnewline
144 & 9 & 8.02413 & 0.975873 \tabularnewline
145 & 8 & 7.13081 & 0.869188 \tabularnewline
146 & 9 & 7.19182 & 1.80818 \tabularnewline
147 & 5.5 & 6.06978 & -0.569777 \tabularnewline
148 & 7 & 6.53159 & 0.468413 \tabularnewline
149 & 5.5 & 8.88514 & -3.38514 \tabularnewline
150 & 9 & 7.59588 & 1.40412 \tabularnewline
151 & 2 & 6.97487 & -4.97487 \tabularnewline
152 & 8.5 & 6.96472 & 1.53528 \tabularnewline
153 & 9 & 7.37607 & 1.62393 \tabularnewline
154 & 8.5 & 8.27507 & 0.224925 \tabularnewline
155 & 9 & 6.2665 & 2.7335 \tabularnewline
156 & 7.5 & 7.01884 & 0.481157 \tabularnewline
157 & 10 & 7.8585 & 2.1415 \tabularnewline
158 & 9 & 7.13321 & 1.86679 \tabularnewline
159 & 7.5 & 8.93321 & -1.43321 \tabularnewline
160 & 6 & 6.08914 & -0.0891363 \tabularnewline
161 & 10.5 & 6.24109 & 4.25891 \tabularnewline
162 & 8.5 & 9.11177 & -0.611773 \tabularnewline
163 & 8 & 6.41689 & 1.58311 \tabularnewline
164 & 10 & 5.88988 & 4.11012 \tabularnewline
165 & 10.5 & 6.8787 & 3.6213 \tabularnewline
166 & 6.5 & 5.0281 & 1.4719 \tabularnewline
167 & 9.5 & 7.90291 & 1.59709 \tabularnewline
168 & 8.5 & 4.69642 & 3.80358 \tabularnewline
169 & 7.5 & 7.76633 & -0.266328 \tabularnewline
170 & 5 & 7.22086 & -2.22086 \tabularnewline
171 & 8 & 7.56754 & 0.43246 \tabularnewline
172 & 10 & 6.3821 & 3.6179 \tabularnewline
173 & 7 & 5.87787 & 1.12213 \tabularnewline
174 & 7.5 & 7.51628 & -0.0162801 \tabularnewline
175 & 7.5 & 7.51628 & -0.0162801 \tabularnewline
176 & 9.5 & 6.62815 & 2.87185 \tabularnewline
177 & 6 & 6.70493 & -0.704927 \tabularnewline
178 & 10 & 7.98335 & 2.01665 \tabularnewline
179 & 7 & 5.96313 & 1.03687 \tabularnewline
180 & 3 & 6.1877 & -3.1877 \tabularnewline
181 & 6 & 7.13198 & -1.13198 \tabularnewline
182 & 7 & 6.41483 & 0.585171 \tabularnewline
183 & 10 & 8.40597 & 1.59403 \tabularnewline
184 & 7 & 6.86047 & 0.139528 \tabularnewline
185 & 3.5 & 5.28111 & -1.78111 \tabularnewline
186 & 8 & 6.77724 & 1.22276 \tabularnewline
187 & 10 & 5.68956 & 4.31044 \tabularnewline
188 & 5.5 & 5.74169 & -0.24169 \tabularnewline
189 & 6 & 4.0132 & 1.9868 \tabularnewline
190 & 6.5 & 6.43539 & 0.0646146 \tabularnewline
191 & 6.5 & 5.70932 & 0.790677 \tabularnewline
192 & 8.5 & 6.15058 & 2.34942 \tabularnewline
193 & 4 & 5.30569 & -1.30569 \tabularnewline
194 & 9.5 & 6.32714 & 3.17286 \tabularnewline
195 & 8 & 5.95944 & 2.04056 \tabularnewline
196 & 8.5 & 7.51136 & 0.988644 \tabularnewline
197 & 5.5 & 8.31789 & -2.81789 \tabularnewline
198 & 7 & 6.95258 & 0.0474193 \tabularnewline
199 & 9 & 5.36025 & 3.63975 \tabularnewline
200 & 8 & 6.06492 & 1.93508 \tabularnewline
201 & 10 & 7.90744 & 2.09256 \tabularnewline
202 & 8 & 5.96024 & 2.03976 \tabularnewline
203 & 6 & 6.09323 & -0.0932284 \tabularnewline
204 & 8 & 7.46978 & 0.530224 \tabularnewline
205 & 5 & 5.48432 & -0.484323 \tabularnewline
206 & 9 & 5.38609 & 3.61391 \tabularnewline
207 & 4.5 & 7.01355 & -2.51355 \tabularnewline
208 & 8.5 & 5.53315 & 2.96685 \tabularnewline
209 & 9.5 & 8.3413 & 1.1587 \tabularnewline
210 & 8.5 & 7.10087 & 1.39913 \tabularnewline
211 & 7.5 & 5.01476 & 2.48524 \tabularnewline
212 & 7.5 & 5.81364 & 1.68636 \tabularnewline
213 & 5 & 7.63058 & -2.63058 \tabularnewline
214 & 7 & 8.16267 & -1.16267 \tabularnewline
215 & 8 & 8.49163 & -0.491626 \tabularnewline
216 & 5.5 & 6.46572 & -0.965723 \tabularnewline
217 & 8.5 & 6.30329 & 2.19671 \tabularnewline
218 & 9.5 & 6.80881 & 2.69119 \tabularnewline
219 & 7 & 5.7675 & 1.2325 \tabularnewline
220 & 8 & 7.7324 & 0.267602 \tabularnewline
221 & 8.5 & 7.77727 & 0.722728 \tabularnewline
222 & 3.5 & 6.45275 & -2.95275 \tabularnewline
223 & 6.5 & 5.40229 & 1.09771 \tabularnewline
224 & 6.5 & 5.02817 & 1.47183 \tabularnewline
225 & 10.5 & 7.74254 & 2.75746 \tabularnewline
226 & 8.5 & 5.90286 & 2.59714 \tabularnewline
227 & 8 & 6.15424 & 1.84576 \tabularnewline
228 & 10 & 6.08308 & 3.91692 \tabularnewline
229 & 10 & 7.57443 & 2.42557 \tabularnewline
230 & 9.5 & 7.18051 & 2.31949 \tabularnewline
231 & 9 & 5.68557 & 3.31443 \tabularnewline
232 & 10 & 8.51464 & 1.48536 \tabularnewline
233 & 7.5 & 5.61359 & 1.88641 \tabularnewline
234 & 4.5 & 5.70214 & -1.20214 \tabularnewline
235 & 4.5 & 5.43097 & -0.930967 \tabularnewline
236 & 0.5 & 5.58568 & -5.08568 \tabularnewline
237 & 6.5 & 5.19659 & 1.30341 \tabularnewline
238 & 4.5 & 7.57283 & -3.07283 \tabularnewline
239 & 5.5 & 6.88509 & -1.38509 \tabularnewline
240 & 5 & 5.42328 & -0.423283 \tabularnewline
241 & 6 & 7.42613 & -1.42613 \tabularnewline
242 & 4 & 7.17519 & -3.17519 \tabularnewline
243 & 8 & 5.39178 & 2.60822 \tabularnewline
244 & 10.5 & 6.8787 & 3.6213 \tabularnewline
245 & 6.5 & 5.53641 & 0.963585 \tabularnewline
246 & 8 & 7.71018 & 0.289822 \tabularnewline
247 & 8.5 & 7.76759 & 0.732407 \tabularnewline
248 & 5.5 & 5.65846 & -0.158462 \tabularnewline
249 & 7 & 7.60999 & -0.609986 \tabularnewline
250 & 5 & 6.05241 & -1.05241 \tabularnewline
251 & 3.5 & 5.41121 & -1.91121 \tabularnewline
252 & 5 & 7.35056 & -2.35056 \tabularnewline
253 & 9 & 7.41885 & 1.58115 \tabularnewline
254 & 8.5 & 6.69358 & 1.80642 \tabularnewline
255 & 5 & 6.12194 & -1.12194 \tabularnewline
256 & 9.5 & 7.73805 & 1.76195 \tabularnewline
257 & 3 & 4.85316 & -1.85316 \tabularnewline
258 & 1.5 & 7.28915 & -5.78915 \tabularnewline
259 & 6 & 5.38613 & 0.613873 \tabularnewline
260 & 0.5 & 5.31704 & -4.81704 \tabularnewline
261 & 6.5 & 5.0281 & 1.4719 \tabularnewline
262 & 7.5 & 5.79581 & 1.70419 \tabularnewline
263 & 4.5 & 5.95824 & -1.45824 \tabularnewline
264 & 8 & 5.39178 & 2.60822 \tabularnewline
265 & 9 & 7.27219 & 1.72781 \tabularnewline
266 & 7.5 & 6.66165 & 0.83835 \tabularnewline
267 & 8.5 & 6.69116 & 1.80884 \tabularnewline
268 & 7 & 5.23946 & 1.76054 \tabularnewline
269 & 9.5 & 5.73038 & 3.76962 \tabularnewline
270 & 6.5 & 5.10488 & 1.39512 \tabularnewline
271 & 9.5 & 5.20836 & 4.29164 \tabularnewline
272 & 6 & 5.32469 & 0.675313 \tabularnewline
273 & 8 & 7.11258 & 0.887417 \tabularnewline
274 & 9.5 & 8.38977 & 1.11023 \tabularnewline
275 & 8 & 6.17845 & 1.82155 \tabularnewline
276 & 8 & 6.27705 & 1.72295 \tabularnewline
277 & 9 & 7.21564 & 1.78436 \tabularnewline
278 & 5 & 5.5097 & -0.509703 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265691&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]7.5[/C][C]5.47424[/C][C]2.02576[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]5.07181[/C][C]0.928189[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]5.34455[/C][C]1.15545[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]5.74698[/C][C]-4.74698[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.08635[/C][C]-4.08635[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]6.58744[/C][C]-1.08744[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]5.74415[/C][C]2.75585[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]6.01279[/C][C]0.487205[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]5.67789[/C][C]-1.17789[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]6.45042[/C][C]-4.45042[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]5.76032[/C][C]-0.760318[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]6.85405[/C][C]-6.35405[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]5.24432[/C][C]-0.244321[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]6.14336[/C][C]-1.14336[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]4.73235[/C][C]-2.23235[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]5.37319[/C][C]-0.373187[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]6.36234[/C][C]-0.862338[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]5.5615[/C][C]-2.0615[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]5.55787[/C][C]-2.55787[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]5.35463[/C][C]-1.35463[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]4.9991[/C][C]-4.4991[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]5.5599[/C][C]0.9401[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]5.45289[/C][C]-0.952889[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]5.23145[/C][C]2.26855[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]5.7393[/C][C]-0.239295[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]6.44806[/C][C]-2.44806[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]6.15626[/C][C]1.34374[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]5.32066[/C][C]1.67934[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]4.97445[/C][C]-0.974447[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]5.41324[/C][C]0.0867625[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]5.77885[/C][C]-3.27885[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]6.03425[/C][C]-0.534251[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]5.62171[/C][C]-2.12171[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]6.51708[/C][C]-4.01708[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]5.99623[/C][C]-1.49623[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]6.13481[/C][C]-1.63481[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.15384[/C][C]-0.653842[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]5.72393[/C][C]0.276073[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]5.24396[/C][C]-2.74396[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]6.64435[/C][C]-1.64435[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]4.78654[/C][C]-4.78654[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.41323[/C][C]-1.41323[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]5.08961[/C][C]1.41039[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]5.61688[/C][C]-0.616882[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]5.16548[/C][C]0.834517[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]5.78094[/C][C]-1.28094[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]6.05118[/C][C]-0.551182[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]5.24349[/C][C]-4.24349[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]4.67098[/C][C]2.82902[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]5.03136[/C][C]0.968639[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]5.58412[/C][C]-0.584116[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]5.64426[/C][C]-4.64426[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]5.97404[/C][C]-0.974042[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]5.5898[/C][C]0.910195[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]6.40352[/C][C]0.596481[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]6.39583[/C][C]-1.89583[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]5.26857[/C][C]-5.26857[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]5.52191[/C][C]2.97809[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]4.58083[/C][C]-1.08083[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]5.6738[/C][C]1.8262[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]5.79628[/C][C]-2.29628[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]4.80799[/C][C]1.19201[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]5.06895[/C][C]-3.56895[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]6.03671[/C][C]2.96329[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]4.60761[/C][C]-1.10761[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]5.11256[/C][C]-1.61256[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]6.30579[/C][C]-2.30579[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]6.05248[/C][C]0.44752[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]5.33084[/C][C]2.16916[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]5.10451[/C][C]0.89549[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]5.90861[/C][C]-0.908611[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]5.05887[/C][C]0.441129[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]5.58126[/C][C]-2.08126[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]5.26774[/C][C]2.23226[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]6.03262[/C][C]0.467379[/C][/ROW]
[ROW][C]76[/C][C]6.5[/C][C]6.26577[/C][C]0.234229[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]5.1429[/C][C]1.3571[/C][/ROW]
[ROW][C]78[/C][C]7[/C][C]6.93688[/C][C]0.0631195[/C][/ROW]
[ROW][C]79[/C][C]3.5[/C][C]5.43782[/C][C]-1.93782[/C][/ROW]
[ROW][C]80[/C][C]1.5[/C][C]5.40229[/C][C]-3.90229[/C][/ROW]
[ROW][C]81[/C][C]4[/C][C]4.92834[/C][C]-0.928342[/C][/ROW]
[ROW][C]82[/C][C]7.5[/C][C]4.73927[/C][C]2.76073[/C][/ROW]
[ROW][C]83[/C][C]4.5[/C][C]5.8152[/C][C]-1.3152[/C][/ROW]
[ROW][C]84[/C][C]0[/C][C]4.5942[/C][C]-4.5942[/C][/ROW]
[ROW][C]85[/C][C]3.5[/C][C]4.94008[/C][C]-1.44008[/C][/ROW]
[ROW][C]86[/C][C]5.5[/C][C]5.57926[/C][C]-0.0792597[/C][/ROW]
[ROW][C]87[/C][C]5[/C][C]5.02328[/C][C]-0.0232782[/C][/ROW]
[ROW][C]88[/C][C]4.5[/C][C]5.12307[/C][C]-0.623071[/C][/ROW]
[ROW][C]89[/C][C]2.5[/C][C]4.6443[/C][C]-2.1443[/C][/ROW]
[ROW][C]90[/C][C]7.5[/C][C]4.85686[/C][C]2.64314[/C][/ROW]
[ROW][C]91[/C][C]7[/C][C]4.99055[/C][C]2.00945[/C][/ROW]
[ROW][C]92[/C][C]0[/C][C]5.0431[/C][C]-5.0431[/C][/ROW]
[ROW][C]93[/C][C]4.5[/C][C]5.16838[/C][C]-0.668378[/C][/ROW]
[ROW][C]94[/C][C]3[/C][C]5.66006[/C][C]-2.66006[/C][/ROW]
[ROW][C]95[/C][C]1.5[/C][C]5.48592[/C][C]-3.98592[/C][/ROW]
[ROW][C]96[/C][C]3.5[/C][C]4.54291[/C][C]-1.04291[/C][/ROW]
[ROW][C]97[/C][C]2.5[/C][C]5.63867[/C][C]-3.13867[/C][/ROW]
[ROW][C]98[/C][C]5.5[/C][C]5.03865[/C][C]0.461354[/C][/ROW]
[ROW][C]99[/C][C]8[/C][C]5.36188[/C][C]2.63812[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]4.80593[/C][C]-3.80593[/C][/ROW]
[ROW][C]101[/C][C]5[/C][C]5.39943[/C][C]-0.399432[/C][/ROW]
[ROW][C]102[/C][C]4.5[/C][C]5.50774[/C][C]-1.00774[/C][/ROW]
[ROW][C]103[/C][C]3[/C][C]4.80753[/C][C]-1.80753[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]4.84877[/C][C]-1.84877[/C][/ROW]
[ROW][C]105[/C][C]8[/C][C]5.6241[/C][C]2.3759[/C][/ROW]
[ROW][C]106[/C][C]2.5[/C][C]4.72915[/C][C]-2.22915[/C][/ROW]
[ROW][C]107[/C][C]7[/C][C]4.8839[/C][C]2.1161[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]5.03339[/C][C]-5.03339[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]5.05275[/C][C]-4.05275[/C][/ROW]
[ROW][C]110[/C][C]3.5[/C][C]4.87299[/C][C]-1.37299[/C][/ROW]
[ROW][C]111[/C][C]5.5[/C][C]4.81644[/C][C]0.68356[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]4.65481[/C][C]0.845192[/C][/ROW]
[ROW][C]113[/C][C]0.5[/C][C]4.84871[/C][C]-4.34871[/C][/ROW]
[ROW][C]114[/C][C]7.5[/C][C]6.58245[/C][C]0.917553[/C][/ROW]
[ROW][C]115[/C][C]9[/C][C]6.89607[/C][C]2.10393[/C][/ROW]
[ROW][C]116[/C][C]9.5[/C][C]7.05041[/C][C]2.44959[/C][/ROW]
[ROW][C]117[/C][C]8.5[/C][C]8.35381[/C][C]0.146189[/C][/ROW]
[ROW][C]118[/C][C]7[/C][C]4.69276[/C][C]2.30724[/C][/ROW]
[ROW][C]119[/C][C]8[/C][C]11.029[/C][C]-3.02904[/C][/ROW]
[ROW][C]120[/C][C]10[/C][C]7.40355[/C][C]2.59645[/C][/ROW]
[ROW][C]121[/C][C]7[/C][C]9.50456[/C][C]-2.50456[/C][/ROW]
[ROW][C]122[/C][C]8.5[/C][C]5.0766[/C][C]3.4234[/C][/ROW]
[ROW][C]123[/C][C]9[/C][C]8.72677[/C][C]0.273228[/C][/ROW]
[ROW][C]124[/C][C]9.5[/C][C]5.60304[/C][C]3.89696[/C][/ROW]
[ROW][C]125[/C][C]4[/C][C]7.33562[/C][C]-3.33562[/C][/ROW]
[ROW][C]126[/C][C]6[/C][C]6.60876[/C][C]-0.60876[/C][/ROW]
[ROW][C]127[/C][C]8[/C][C]7.21161[/C][C]0.788389[/C][/ROW]
[ROW][C]128[/C][C]5.5[/C][C]8.93966[/C][C]-3.43966[/C][/ROW]
[ROW][C]129[/C][C]9.5[/C][C]7.69524[/C][C]1.80476[/C][/ROW]
[ROW][C]130[/C][C]7.5[/C][C]5.80875[/C][C]1.69125[/C][/ROW]
[ROW][C]131[/C][C]7[/C][C]5.40755[/C][C]1.59245[/C][/ROW]
[ROW][C]132[/C][C]7.5[/C][C]8.84153[/C][C]-1.34153[/C][/ROW]
[ROW][C]133[/C][C]8[/C][C]6.43462[/C][C]1.56538[/C][/ROW]
[ROW][C]134[/C][C]7[/C][C]6.94007[/C][C]0.0599265[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]6.08105[/C][C]0.918947[/C][/ROW]
[ROW][C]136[/C][C]6[/C][C]7.50247[/C][C]-1.50247[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]6.56392[/C][C]3.43608[/C][/ROW]
[ROW][C]138[/C][C]2.5[/C][C]6.33516[/C][C]-3.83516[/C][/ROW]
[ROW][C]139[/C][C]9[/C][C]8.78455[/C][C]0.215448[/C][/ROW]
[ROW][C]140[/C][C]8[/C][C]9.32513[/C][C]-1.32513[/C][/ROW]
[ROW][C]141[/C][C]6[/C][C]5.41317[/C][C]0.58683[/C][/ROW]
[ROW][C]142[/C][C]8.5[/C][C]4.9983[/C][C]3.5017[/C][/ROW]
[ROW][C]143[/C][C]6[/C][C]6.28839[/C][C]-0.288391[/C][/ROW]
[ROW][C]144[/C][C]9[/C][C]8.02413[/C][C]0.975873[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]7.13081[/C][C]0.869188[/C][/ROW]
[ROW][C]146[/C][C]9[/C][C]7.19182[/C][C]1.80818[/C][/ROW]
[ROW][C]147[/C][C]5.5[/C][C]6.06978[/C][C]-0.569777[/C][/ROW]
[ROW][C]148[/C][C]7[/C][C]6.53159[/C][C]0.468413[/C][/ROW]
[ROW][C]149[/C][C]5.5[/C][C]8.88514[/C][C]-3.38514[/C][/ROW]
[ROW][C]150[/C][C]9[/C][C]7.59588[/C][C]1.40412[/C][/ROW]
[ROW][C]151[/C][C]2[/C][C]6.97487[/C][C]-4.97487[/C][/ROW]
[ROW][C]152[/C][C]8.5[/C][C]6.96472[/C][C]1.53528[/C][/ROW]
[ROW][C]153[/C][C]9[/C][C]7.37607[/C][C]1.62393[/C][/ROW]
[ROW][C]154[/C][C]8.5[/C][C]8.27507[/C][C]0.224925[/C][/ROW]
[ROW][C]155[/C][C]9[/C][C]6.2665[/C][C]2.7335[/C][/ROW]
[ROW][C]156[/C][C]7.5[/C][C]7.01884[/C][C]0.481157[/C][/ROW]
[ROW][C]157[/C][C]10[/C][C]7.8585[/C][C]2.1415[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]7.13321[/C][C]1.86679[/C][/ROW]
[ROW][C]159[/C][C]7.5[/C][C]8.93321[/C][C]-1.43321[/C][/ROW]
[ROW][C]160[/C][C]6[/C][C]6.08914[/C][C]-0.0891363[/C][/ROW]
[ROW][C]161[/C][C]10.5[/C][C]6.24109[/C][C]4.25891[/C][/ROW]
[ROW][C]162[/C][C]8.5[/C][C]9.11177[/C][C]-0.611773[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]6.41689[/C][C]1.58311[/C][/ROW]
[ROW][C]164[/C][C]10[/C][C]5.88988[/C][C]4.11012[/C][/ROW]
[ROW][C]165[/C][C]10.5[/C][C]6.8787[/C][C]3.6213[/C][/ROW]
[ROW][C]166[/C][C]6.5[/C][C]5.0281[/C][C]1.4719[/C][/ROW]
[ROW][C]167[/C][C]9.5[/C][C]7.90291[/C][C]1.59709[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]4.69642[/C][C]3.80358[/C][/ROW]
[ROW][C]169[/C][C]7.5[/C][C]7.76633[/C][C]-0.266328[/C][/ROW]
[ROW][C]170[/C][C]5[/C][C]7.22086[/C][C]-2.22086[/C][/ROW]
[ROW][C]171[/C][C]8[/C][C]7.56754[/C][C]0.43246[/C][/ROW]
[ROW][C]172[/C][C]10[/C][C]6.3821[/C][C]3.6179[/C][/ROW]
[ROW][C]173[/C][C]7[/C][C]5.87787[/C][C]1.12213[/C][/ROW]
[ROW][C]174[/C][C]7.5[/C][C]7.51628[/C][C]-0.0162801[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]7.51628[/C][C]-0.0162801[/C][/ROW]
[ROW][C]176[/C][C]9.5[/C][C]6.62815[/C][C]2.87185[/C][/ROW]
[ROW][C]177[/C][C]6[/C][C]6.70493[/C][C]-0.704927[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]7.98335[/C][C]2.01665[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]5.96313[/C][C]1.03687[/C][/ROW]
[ROW][C]180[/C][C]3[/C][C]6.1877[/C][C]-3.1877[/C][/ROW]
[ROW][C]181[/C][C]6[/C][C]7.13198[/C][C]-1.13198[/C][/ROW]
[ROW][C]182[/C][C]7[/C][C]6.41483[/C][C]0.585171[/C][/ROW]
[ROW][C]183[/C][C]10[/C][C]8.40597[/C][C]1.59403[/C][/ROW]
[ROW][C]184[/C][C]7[/C][C]6.86047[/C][C]0.139528[/C][/ROW]
[ROW][C]185[/C][C]3.5[/C][C]5.28111[/C][C]-1.78111[/C][/ROW]
[ROW][C]186[/C][C]8[/C][C]6.77724[/C][C]1.22276[/C][/ROW]
[ROW][C]187[/C][C]10[/C][C]5.68956[/C][C]4.31044[/C][/ROW]
[ROW][C]188[/C][C]5.5[/C][C]5.74169[/C][C]-0.24169[/C][/ROW]
[ROW][C]189[/C][C]6[/C][C]4.0132[/C][C]1.9868[/C][/ROW]
[ROW][C]190[/C][C]6.5[/C][C]6.43539[/C][C]0.0646146[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]5.70932[/C][C]0.790677[/C][/ROW]
[ROW][C]192[/C][C]8.5[/C][C]6.15058[/C][C]2.34942[/C][/ROW]
[ROW][C]193[/C][C]4[/C][C]5.30569[/C][C]-1.30569[/C][/ROW]
[ROW][C]194[/C][C]9.5[/C][C]6.32714[/C][C]3.17286[/C][/ROW]
[ROW][C]195[/C][C]8[/C][C]5.95944[/C][C]2.04056[/C][/ROW]
[ROW][C]196[/C][C]8.5[/C][C]7.51136[/C][C]0.988644[/C][/ROW]
[ROW][C]197[/C][C]5.5[/C][C]8.31789[/C][C]-2.81789[/C][/ROW]
[ROW][C]198[/C][C]7[/C][C]6.95258[/C][C]0.0474193[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]5.36025[/C][C]3.63975[/C][/ROW]
[ROW][C]200[/C][C]8[/C][C]6.06492[/C][C]1.93508[/C][/ROW]
[ROW][C]201[/C][C]10[/C][C]7.90744[/C][C]2.09256[/C][/ROW]
[ROW][C]202[/C][C]8[/C][C]5.96024[/C][C]2.03976[/C][/ROW]
[ROW][C]203[/C][C]6[/C][C]6.09323[/C][C]-0.0932284[/C][/ROW]
[ROW][C]204[/C][C]8[/C][C]7.46978[/C][C]0.530224[/C][/ROW]
[ROW][C]205[/C][C]5[/C][C]5.48432[/C][C]-0.484323[/C][/ROW]
[ROW][C]206[/C][C]9[/C][C]5.38609[/C][C]3.61391[/C][/ROW]
[ROW][C]207[/C][C]4.5[/C][C]7.01355[/C][C]-2.51355[/C][/ROW]
[ROW][C]208[/C][C]8.5[/C][C]5.53315[/C][C]2.96685[/C][/ROW]
[ROW][C]209[/C][C]9.5[/C][C]8.3413[/C][C]1.1587[/C][/ROW]
[ROW][C]210[/C][C]8.5[/C][C]7.10087[/C][C]1.39913[/C][/ROW]
[ROW][C]211[/C][C]7.5[/C][C]5.01476[/C][C]2.48524[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]5.81364[/C][C]1.68636[/C][/ROW]
[ROW][C]213[/C][C]5[/C][C]7.63058[/C][C]-2.63058[/C][/ROW]
[ROW][C]214[/C][C]7[/C][C]8.16267[/C][C]-1.16267[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]8.49163[/C][C]-0.491626[/C][/ROW]
[ROW][C]216[/C][C]5.5[/C][C]6.46572[/C][C]-0.965723[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]6.30329[/C][C]2.19671[/C][/ROW]
[ROW][C]218[/C][C]9.5[/C][C]6.80881[/C][C]2.69119[/C][/ROW]
[ROW][C]219[/C][C]7[/C][C]5.7675[/C][C]1.2325[/C][/ROW]
[ROW][C]220[/C][C]8[/C][C]7.7324[/C][C]0.267602[/C][/ROW]
[ROW][C]221[/C][C]8.5[/C][C]7.77727[/C][C]0.722728[/C][/ROW]
[ROW][C]222[/C][C]3.5[/C][C]6.45275[/C][C]-2.95275[/C][/ROW]
[ROW][C]223[/C][C]6.5[/C][C]5.40229[/C][C]1.09771[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]5.02817[/C][C]1.47183[/C][/ROW]
[ROW][C]225[/C][C]10.5[/C][C]7.74254[/C][C]2.75746[/C][/ROW]
[ROW][C]226[/C][C]8.5[/C][C]5.90286[/C][C]2.59714[/C][/ROW]
[ROW][C]227[/C][C]8[/C][C]6.15424[/C][C]1.84576[/C][/ROW]
[ROW][C]228[/C][C]10[/C][C]6.08308[/C][C]3.91692[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]7.57443[/C][C]2.42557[/C][/ROW]
[ROW][C]230[/C][C]9.5[/C][C]7.18051[/C][C]2.31949[/C][/ROW]
[ROW][C]231[/C][C]9[/C][C]5.68557[/C][C]3.31443[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.51464[/C][C]1.48536[/C][/ROW]
[ROW][C]233[/C][C]7.5[/C][C]5.61359[/C][C]1.88641[/C][/ROW]
[ROW][C]234[/C][C]4.5[/C][C]5.70214[/C][C]-1.20214[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]5.43097[/C][C]-0.930967[/C][/ROW]
[ROW][C]236[/C][C]0.5[/C][C]5.58568[/C][C]-5.08568[/C][/ROW]
[ROW][C]237[/C][C]6.5[/C][C]5.19659[/C][C]1.30341[/C][/ROW]
[ROW][C]238[/C][C]4.5[/C][C]7.57283[/C][C]-3.07283[/C][/ROW]
[ROW][C]239[/C][C]5.5[/C][C]6.88509[/C][C]-1.38509[/C][/ROW]
[ROW][C]240[/C][C]5[/C][C]5.42328[/C][C]-0.423283[/C][/ROW]
[ROW][C]241[/C][C]6[/C][C]7.42613[/C][C]-1.42613[/C][/ROW]
[ROW][C]242[/C][C]4[/C][C]7.17519[/C][C]-3.17519[/C][/ROW]
[ROW][C]243[/C][C]8[/C][C]5.39178[/C][C]2.60822[/C][/ROW]
[ROW][C]244[/C][C]10.5[/C][C]6.8787[/C][C]3.6213[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]5.53641[/C][C]0.963585[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]7.71018[/C][C]0.289822[/C][/ROW]
[ROW][C]247[/C][C]8.5[/C][C]7.76759[/C][C]0.732407[/C][/ROW]
[ROW][C]248[/C][C]5.5[/C][C]5.65846[/C][C]-0.158462[/C][/ROW]
[ROW][C]249[/C][C]7[/C][C]7.60999[/C][C]-0.609986[/C][/ROW]
[ROW][C]250[/C][C]5[/C][C]6.05241[/C][C]-1.05241[/C][/ROW]
[ROW][C]251[/C][C]3.5[/C][C]5.41121[/C][C]-1.91121[/C][/ROW]
[ROW][C]252[/C][C]5[/C][C]7.35056[/C][C]-2.35056[/C][/ROW]
[ROW][C]253[/C][C]9[/C][C]7.41885[/C][C]1.58115[/C][/ROW]
[ROW][C]254[/C][C]8.5[/C][C]6.69358[/C][C]1.80642[/C][/ROW]
[ROW][C]255[/C][C]5[/C][C]6.12194[/C][C]-1.12194[/C][/ROW]
[ROW][C]256[/C][C]9.5[/C][C]7.73805[/C][C]1.76195[/C][/ROW]
[ROW][C]257[/C][C]3[/C][C]4.85316[/C][C]-1.85316[/C][/ROW]
[ROW][C]258[/C][C]1.5[/C][C]7.28915[/C][C]-5.78915[/C][/ROW]
[ROW][C]259[/C][C]6[/C][C]5.38613[/C][C]0.613873[/C][/ROW]
[ROW][C]260[/C][C]0.5[/C][C]5.31704[/C][C]-4.81704[/C][/ROW]
[ROW][C]261[/C][C]6.5[/C][C]5.0281[/C][C]1.4719[/C][/ROW]
[ROW][C]262[/C][C]7.5[/C][C]5.79581[/C][C]1.70419[/C][/ROW]
[ROW][C]263[/C][C]4.5[/C][C]5.95824[/C][C]-1.45824[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]5.39178[/C][C]2.60822[/C][/ROW]
[ROW][C]265[/C][C]9[/C][C]7.27219[/C][C]1.72781[/C][/ROW]
[ROW][C]266[/C][C]7.5[/C][C]6.66165[/C][C]0.83835[/C][/ROW]
[ROW][C]267[/C][C]8.5[/C][C]6.69116[/C][C]1.80884[/C][/ROW]
[ROW][C]268[/C][C]7[/C][C]5.23946[/C][C]1.76054[/C][/ROW]
[ROW][C]269[/C][C]9.5[/C][C]5.73038[/C][C]3.76962[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]5.10488[/C][C]1.39512[/C][/ROW]
[ROW][C]271[/C][C]9.5[/C][C]5.20836[/C][C]4.29164[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]5.32469[/C][C]0.675313[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]7.11258[/C][C]0.887417[/C][/ROW]
[ROW][C]274[/C][C]9.5[/C][C]8.38977[/C][C]1.11023[/C][/ROW]
[ROW][C]275[/C][C]8[/C][C]6.17845[/C][C]1.82155[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]6.27705[/C][C]1.72295[/C][/ROW]
[ROW][C]277[/C][C]9[/C][C]7.21564[/C][C]1.78436[/C][/ROW]
[ROW][C]278[/C][C]5[/C][C]5.5097[/C][C]-0.509703[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265691&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265691&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.55.474242.02576
265.071810.928189
36.55.344551.15545
415.74698-4.74698
515.08635-4.08635
65.56.58744-1.08744
78.55.744152.75585
86.56.012790.487205
94.55.67789-1.17789
1026.45042-4.45042
1155.76032-0.760318
120.56.85405-6.35405
1355.24432-0.244321
1456.14336-1.14336
152.54.73235-2.23235
1655.37319-0.373187
175.56.36234-0.862338
183.55.5615-2.0615
1935.55787-2.55787
2045.35463-1.35463
210.54.9991-4.4991
226.55.55990.9401
234.55.45289-0.952889
247.55.231452.26855
255.55.7393-0.239295
2646.44806-2.44806
277.56.156261.34374
2875.320661.67934
2944.97445-0.974447
305.55.413240.0867625
312.55.77885-3.27885
325.56.03425-0.534251
333.55.62171-2.12171
342.56.51708-4.01708
354.55.99623-1.49623
364.56.13481-1.63481
374.55.15384-0.653842
3865.723930.276073
392.55.24396-2.74396
4056.64435-1.64435
4104.78654-4.78654
4256.41323-1.41323
436.55.089611.41039
4455.61688-0.616882
4565.165480.834517
464.55.78094-1.28094
475.56.05118-0.551182
4815.24349-4.24349
497.54.670982.82902
5065.031360.968639
5155.58412-0.584116
5215.64426-4.64426
5355.97404-0.974042
546.55.58980.910195
5576.403520.596481
564.56.39583-1.89583
5705.26857-5.26857
588.55.521912.97809
593.54.58083-1.08083
607.55.67381.8262
613.55.79628-2.29628
6264.807991.19201
631.55.06895-3.56895
6496.036712.96329
653.54.60761-1.10761
663.55.11256-1.61256
6746.30579-2.30579
686.56.052480.44752
697.55.330842.16916
7065.104510.89549
7155.90861-0.908611
725.55.058870.441129
733.55.58126-2.08126
747.55.267742.23226
756.56.032620.467379
766.56.265770.234229
776.55.14291.3571
7876.936880.0631195
793.55.43782-1.93782
801.55.40229-3.90229
8144.92834-0.928342
827.54.739272.76073
834.55.8152-1.3152
8404.5942-4.5942
853.54.94008-1.44008
865.55.57926-0.0792597
8755.02328-0.0232782
884.55.12307-0.623071
892.54.6443-2.1443
907.54.856862.64314
9174.990552.00945
9205.0431-5.0431
934.55.16838-0.668378
9435.66006-2.66006
951.55.48592-3.98592
963.54.54291-1.04291
972.55.63867-3.13867
985.55.038650.461354
9985.361882.63812
10014.80593-3.80593
10155.39943-0.399432
1024.55.50774-1.00774
10334.80753-1.80753
10434.84877-1.84877
10585.62412.3759
1062.54.72915-2.22915
10774.88392.1161
10805.03339-5.03339
10915.05275-4.05275
1103.54.87299-1.37299
1115.54.816440.68356
1125.54.654810.845192
1130.54.84871-4.34871
1147.56.582450.917553
11596.896072.10393
1169.57.050412.44959
1178.58.353810.146189
11874.692762.30724
119811.029-3.02904
120107.403552.59645
12179.50456-2.50456
1228.55.07663.4234
12398.726770.273228
1249.55.603043.89696
12547.33562-3.33562
12666.60876-0.60876
12787.211610.788389
1285.58.93966-3.43966
1299.57.695241.80476
1307.55.808751.69125
13175.407551.59245
1327.58.84153-1.34153
13386.434621.56538
13476.940070.0599265
13576.081050.918947
13667.50247-1.50247
137106.563923.43608
1382.56.33516-3.83516
13998.784550.215448
14089.32513-1.32513
14165.413170.58683
1428.54.99833.5017
14366.28839-0.288391
14498.024130.975873
14587.130810.869188
14697.191821.80818
1475.56.06978-0.569777
14876.531590.468413
1495.58.88514-3.38514
15097.595881.40412
15126.97487-4.97487
1528.56.964721.53528
15397.376071.62393
1548.58.275070.224925
15596.26652.7335
1567.57.018840.481157
157107.85852.1415
15897.133211.86679
1597.58.93321-1.43321
16066.08914-0.0891363
16110.56.241094.25891
1628.59.11177-0.611773
16386.416891.58311
164105.889884.11012
16510.56.87873.6213
1666.55.02811.4719
1679.57.902911.59709
1688.54.696423.80358
1697.57.76633-0.266328
17057.22086-2.22086
17187.567540.43246
172106.38213.6179
17375.877871.12213
1747.57.51628-0.0162801
1757.57.51628-0.0162801
1769.56.628152.87185
17766.70493-0.704927
178107.983352.01665
17975.963131.03687
18036.1877-3.1877
18167.13198-1.13198
18276.414830.585171
183108.405971.59403
18476.860470.139528
1853.55.28111-1.78111
18686.777241.22276
187105.689564.31044
1885.55.74169-0.24169
18964.01321.9868
1906.56.435390.0646146
1916.55.709320.790677
1928.56.150582.34942
19345.30569-1.30569
1949.56.327143.17286
19585.959442.04056
1968.57.511360.988644
1975.58.31789-2.81789
19876.952580.0474193
19995.360253.63975
20086.064921.93508
201107.907442.09256
20285.960242.03976
20366.09323-0.0932284
20487.469780.530224
20555.48432-0.484323
20695.386093.61391
2074.57.01355-2.51355
2088.55.533152.96685
2099.58.34131.1587
2108.57.100871.39913
2117.55.014762.48524
2127.55.813641.68636
21357.63058-2.63058
21478.16267-1.16267
21588.49163-0.491626
2165.56.46572-0.965723
2178.56.303292.19671
2189.56.808812.69119
21975.76751.2325
22087.73240.267602
2218.57.777270.722728
2223.56.45275-2.95275
2236.55.402291.09771
2246.55.028171.47183
22510.57.742542.75746
2268.55.902862.59714
22786.154241.84576
228106.083083.91692
229107.574432.42557
2309.57.180512.31949
23195.685573.31443
232108.514641.48536
2337.55.613591.88641
2344.55.70214-1.20214
2354.55.43097-0.930967
2360.55.58568-5.08568
2376.55.196591.30341
2384.57.57283-3.07283
2395.56.88509-1.38509
24055.42328-0.423283
24167.42613-1.42613
24247.17519-3.17519
24385.391782.60822
24410.56.87873.6213
2456.55.536410.963585
24687.710180.289822
2478.57.767590.732407
2485.55.65846-0.158462
24977.60999-0.609986
25056.05241-1.05241
2513.55.41121-1.91121
25257.35056-2.35056
25397.418851.58115
2548.56.693581.80642
25556.12194-1.12194
2569.57.738051.76195
25734.85316-1.85316
2581.57.28915-5.78915
25965.386130.613873
2600.55.31704-4.81704
2616.55.02811.4719
2627.55.795811.70419
2634.55.95824-1.45824
26485.391782.60822
26597.272191.72781
2667.56.661650.83835
2678.56.691161.80884
26875.239461.76054
2699.55.730383.76962
2706.55.104881.39512
2719.55.208364.29164
27265.324690.675313
27387.112580.887417
2749.58.389771.11023
27586.178451.82155
27686.277051.72295
27797.215641.78436
27855.5097-0.509703






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.8512570.2974870.148743
70.9563250.08735020.0436751
80.933110.1337810.0668903
90.8917080.2165840.108292
100.9195720.1608550.0804276
110.8758850.248230.124115
120.9017410.1965190.0982593
130.8572220.2855560.142778
140.8079560.3840890.192044
150.7759430.4481150.224057
160.7310230.5379530.268977
170.6923680.6152650.307632
180.6344930.7310150.365507
190.6000840.7998310.399916
200.5327370.9345260.467263
210.7259820.5480360.274018
220.7133240.5733510.286676
230.6603260.6793470.339674
240.6655010.6689980.334499
250.61810.7638010.3819
260.5809980.8380050.419002
270.6307450.738510.369255
280.643660.712680.35634
290.5963260.8073470.403674
300.545070.9098590.45493
310.5327060.9345870.467294
320.4861780.9723570.513822
330.4475540.8951080.552446
340.4474910.8949810.552509
350.3995040.7990090.600496
360.3545380.7090770.645462
370.3084270.6168550.691573
380.2835090.5670180.716491
390.2962660.5925320.703734
400.260830.521660.73917
410.4081050.8162110.591895
420.3664530.7329050.633547
430.3546920.7093830.645308
440.3132620.6265250.686738
450.3011220.6022440.698878
460.2658030.5316050.734197
470.2362410.4724810.763759
480.2982870.5965730.701713
490.341330.6826590.65867
500.3197330.6394650.680267
510.282680.5653590.71732
520.3352860.6705710.664714
530.3000420.6000850.699958
540.2844580.5689170.715542
550.2950960.5901920.704904
560.2645210.5290420.735479
570.418270.8365410.58173
580.4979140.9958270.502086
590.459410.918820.54059
600.4917290.9834570.508271
610.4774620.9549240.522538
620.4467150.893430.553285
630.4903340.9806680.509666
640.5545580.8908830.445442
650.5367640.9264720.463236
660.5039630.9920750.496037
670.4908170.9816350.509183
680.460760.921520.53924
690.4602490.9204990.539751
700.4392210.8784430.560779
710.4070330.8140650.592967
720.3745130.7490250.625487
730.3493590.6987180.650641
740.3780780.7561560.621922
750.3592130.7184250.640787
760.3364390.6728780.663561
770.3248160.6496310.675184
780.3103130.6206270.689687
790.2881570.5763140.711843
800.3402870.6805730.659713
810.3107230.6214460.689277
820.3322980.6645960.667702
830.3037480.6074970.696252
840.4257540.8515070.574246
850.4075360.8150720.592464
860.3787360.7574730.621264
870.3488860.6977730.651114
880.31850.6370010.6815
890.316270.632540.68373
900.3317350.663470.668265
910.3451230.6902460.654877
920.4982110.9964230.501789
930.4705570.9411140.529443
940.4714330.9428660.528567
950.5351040.9297910.464896
960.5180530.9638940.481947
970.5521070.8957850.447893
980.5260570.9478850.473943
990.5692620.8614760.430738
1000.6563190.6873630.343681
1010.6297970.7404050.370203
1020.6064020.7871960.393598
1030.601520.7969610.39848
1040.612360.775280.38764
1050.6446910.7106180.355309
1060.6621820.6756370.337818
1070.6665210.6669570.333479
1080.8062490.3875020.193751
1090.8565790.2868430.143421
1100.8547290.2905420.145271
1110.8418930.3162130.158107
1120.8287450.342510.171255
1130.8919790.2160420.108021
1140.8971410.2057170.102859
1150.9050640.1898730.0949365
1160.9153110.1693770.0846887
1170.9052670.1894660.0947329
1180.9121320.1757360.0878679
1190.9067670.1864660.0932332
1200.9191010.1617980.0808989
1210.9126750.1746510.0873253
1220.9351840.1296320.0648161
1230.927110.145780.0728898
1240.9570840.08583190.0429159
1250.9635810.07283710.0364185
1260.9577650.08447090.0422354
1270.9522570.09548630.0477432
1280.9543420.09131520.0456576
1290.9555820.08883580.0444179
1300.9532210.0935580.046779
1310.9493080.1013850.0506924
1320.9420570.1158860.0579432
1330.9385870.1228270.0614135
1340.9288110.1423790.0711894
1350.9206510.1586990.0793493
1360.9106260.1787480.089374
1370.9306850.138630.0693148
1380.9471940.1056110.0528056
1390.938740.122520.0612598
1400.9282930.1434140.0717072
1410.9183910.1632170.0816086
1420.9275140.1449710.0724856
1430.9188030.1623930.0811966
1440.9110570.1778860.0889429
1450.8997420.2005150.100258
1460.8953390.2093210.104661
1470.8844360.2311280.115564
1480.8692380.2615250.130762
1490.8838920.2322170.116108
1500.8735930.2528140.126407
1510.9488060.1023870.0511935
1520.9448260.1103470.0551736
1530.9399760.1200480.0600238
1540.9298780.1402430.0701217
1550.9384310.1231380.0615692
1560.928630.142740.0713698
1570.9268780.1462430.0731215
1580.9239320.1521370.0760683
1590.9134830.1730340.0865171
1600.9003150.1993690.0996847
1610.9315930.1368130.0684067
1620.9192410.1615180.0807591
1630.9096770.1806450.0903226
1640.9497330.1005330.0502667
1650.9586320.08273680.0413684
1660.9535440.09291290.0464565
1670.9498810.1002380.050119
1680.9595080.08098390.040492
1690.9511830.09763370.0488169
1700.9506750.09865030.0493252
1710.9415430.1169130.0584565
1720.9537950.09241030.0462051
1730.9459280.1081440.054072
1740.9367090.1265810.0632906
1750.9264040.1471920.0735961
1760.9318210.1363570.0681787
1770.9228760.1542480.0771239
1780.9180150.163970.0819852
1790.9053630.1892730.0946366
1800.9210660.1578680.0789341
1810.911190.1776190.0888097
1820.8965370.2069270.103463
1830.8871090.2257820.112891
1840.8689830.2620340.131017
1850.8865030.2269930.113497
1860.8717430.2565140.128257
1870.9053040.1893920.0946958
1880.8932520.2134960.106748
1890.8810660.2378680.118934
1900.8615280.2769440.138472
1910.8416480.3167040.158352
1920.8357430.3285150.164257
1930.8289070.3421850.171093
1940.8417360.3165290.158264
1950.8332350.3335290.166765
1960.8168150.3663690.183185
1970.838050.3239010.16195
1980.8133960.3732080.186604
1990.8406510.3186990.159349
2000.8268610.3462780.173139
2010.8097740.3804510.190226
2020.8028670.3942670.197133
2030.7819120.4361760.218088
2040.7526170.4947670.247383
2050.7356040.5287910.264396
2060.7759980.4480050.224002
2070.7724420.4551170.227558
2080.7938620.4122760.206138
2090.7707380.4585240.229262
2100.7497710.5004570.250229
2110.7578650.4842710.242135
2120.7300320.5399370.269968
2130.7461560.5076870.253844
2140.7160720.5678560.283928
2150.6887960.6224070.311204
2160.665380.6692410.33462
2170.6544230.6911550.345577
2180.6365990.7268010.363401
2190.6098330.7803330.390167
2200.5682550.8634890.431745
2210.5267360.9465280.473264
2220.5447390.9105230.455261
2230.5041010.9917990.495899
2240.4650140.9300280.534986
2250.4554160.9108330.544584
2260.4704880.9409760.529512
2270.4375980.8751960.562402
2280.5149010.9701990.485099
2290.5117510.9764980.488249
2300.493840.9876790.50616
2310.4993820.9987640.500618
2320.4722610.9445230.527739
2330.4508110.9016220.549189
2340.4453040.8906090.554696
2350.413140.826280.58686
2360.6083170.7833660.391683
2370.5700290.8599420.429971
2380.6334150.733170.366585
2390.5992940.8014120.400706
2400.5566460.8867090.443354
2410.532520.9349590.46748
2420.5864610.8270780.413539
2430.577240.8455190.42276
2440.6233210.7533590.376679
2450.572950.8541010.42705
2460.5176470.9647060.482353
2470.463680.927360.53632
2480.4109730.8219450.589027
2490.3649520.7299040.635048
2500.335560.671120.66444
2510.3622580.7245150.637742
2520.3862430.7724870.613757
2530.3389990.6779980.661001
2540.3013270.6026550.698673
2550.3357840.6715680.664216
2560.2907310.5814610.709269
2570.2953260.5906520.704674
2580.7792170.4415660.220783
2590.7275980.5448030.272402
2600.9990710.001858260.00092913
2610.9983870.003225930.00161296
2620.9966060.006788740.00339437
2630.9999578.58074e-054.29037e-05
2640.9998660.0002671920.000133596
2650.9996190.0007618520.000380926
2660.9990250.001949780.000974888
2670.9988720.002255510.00112776
2680.9990060.001988950.000994475
2690.9980350.003929430.00196472
2700.9951690.009661120.00483056
2710.9999390.0001224296.12146e-05
2720.9993070.001385560.000692779

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
6 & 0.851257 & 0.297487 & 0.148743 \tabularnewline
7 & 0.956325 & 0.0873502 & 0.0436751 \tabularnewline
8 & 0.93311 & 0.133781 & 0.0668903 \tabularnewline
9 & 0.891708 & 0.216584 & 0.108292 \tabularnewline
10 & 0.919572 & 0.160855 & 0.0804276 \tabularnewline
11 & 0.875885 & 0.24823 & 0.124115 \tabularnewline
12 & 0.901741 & 0.196519 & 0.0982593 \tabularnewline
13 & 0.857222 & 0.285556 & 0.142778 \tabularnewline
14 & 0.807956 & 0.384089 & 0.192044 \tabularnewline
15 & 0.775943 & 0.448115 & 0.224057 \tabularnewline
16 & 0.731023 & 0.537953 & 0.268977 \tabularnewline
17 & 0.692368 & 0.615265 & 0.307632 \tabularnewline
18 & 0.634493 & 0.731015 & 0.365507 \tabularnewline
19 & 0.600084 & 0.799831 & 0.399916 \tabularnewline
20 & 0.532737 & 0.934526 & 0.467263 \tabularnewline
21 & 0.725982 & 0.548036 & 0.274018 \tabularnewline
22 & 0.713324 & 0.573351 & 0.286676 \tabularnewline
23 & 0.660326 & 0.679347 & 0.339674 \tabularnewline
24 & 0.665501 & 0.668998 & 0.334499 \tabularnewline
25 & 0.6181 & 0.763801 & 0.3819 \tabularnewline
26 & 0.580998 & 0.838005 & 0.419002 \tabularnewline
27 & 0.630745 & 0.73851 & 0.369255 \tabularnewline
28 & 0.64366 & 0.71268 & 0.35634 \tabularnewline
29 & 0.596326 & 0.807347 & 0.403674 \tabularnewline
30 & 0.54507 & 0.909859 & 0.45493 \tabularnewline
31 & 0.532706 & 0.934587 & 0.467294 \tabularnewline
32 & 0.486178 & 0.972357 & 0.513822 \tabularnewline
33 & 0.447554 & 0.895108 & 0.552446 \tabularnewline
34 & 0.447491 & 0.894981 & 0.552509 \tabularnewline
35 & 0.399504 & 0.799009 & 0.600496 \tabularnewline
36 & 0.354538 & 0.709077 & 0.645462 \tabularnewline
37 & 0.308427 & 0.616855 & 0.691573 \tabularnewline
38 & 0.283509 & 0.567018 & 0.716491 \tabularnewline
39 & 0.296266 & 0.592532 & 0.703734 \tabularnewline
40 & 0.26083 & 0.52166 & 0.73917 \tabularnewline
41 & 0.408105 & 0.816211 & 0.591895 \tabularnewline
42 & 0.366453 & 0.732905 & 0.633547 \tabularnewline
43 & 0.354692 & 0.709383 & 0.645308 \tabularnewline
44 & 0.313262 & 0.626525 & 0.686738 \tabularnewline
45 & 0.301122 & 0.602244 & 0.698878 \tabularnewline
46 & 0.265803 & 0.531605 & 0.734197 \tabularnewline
47 & 0.236241 & 0.472481 & 0.763759 \tabularnewline
48 & 0.298287 & 0.596573 & 0.701713 \tabularnewline
49 & 0.34133 & 0.682659 & 0.65867 \tabularnewline
50 & 0.319733 & 0.639465 & 0.680267 \tabularnewline
51 & 0.28268 & 0.565359 & 0.71732 \tabularnewline
52 & 0.335286 & 0.670571 & 0.664714 \tabularnewline
53 & 0.300042 & 0.600085 & 0.699958 \tabularnewline
54 & 0.284458 & 0.568917 & 0.715542 \tabularnewline
55 & 0.295096 & 0.590192 & 0.704904 \tabularnewline
56 & 0.264521 & 0.529042 & 0.735479 \tabularnewline
57 & 0.41827 & 0.836541 & 0.58173 \tabularnewline
58 & 0.497914 & 0.995827 & 0.502086 \tabularnewline
59 & 0.45941 & 0.91882 & 0.54059 \tabularnewline
60 & 0.491729 & 0.983457 & 0.508271 \tabularnewline
61 & 0.477462 & 0.954924 & 0.522538 \tabularnewline
62 & 0.446715 & 0.89343 & 0.553285 \tabularnewline
63 & 0.490334 & 0.980668 & 0.509666 \tabularnewline
64 & 0.554558 & 0.890883 & 0.445442 \tabularnewline
65 & 0.536764 & 0.926472 & 0.463236 \tabularnewline
66 & 0.503963 & 0.992075 & 0.496037 \tabularnewline
67 & 0.490817 & 0.981635 & 0.509183 \tabularnewline
68 & 0.46076 & 0.92152 & 0.53924 \tabularnewline
69 & 0.460249 & 0.920499 & 0.539751 \tabularnewline
70 & 0.439221 & 0.878443 & 0.560779 \tabularnewline
71 & 0.407033 & 0.814065 & 0.592967 \tabularnewline
72 & 0.374513 & 0.749025 & 0.625487 \tabularnewline
73 & 0.349359 & 0.698718 & 0.650641 \tabularnewline
74 & 0.378078 & 0.756156 & 0.621922 \tabularnewline
75 & 0.359213 & 0.718425 & 0.640787 \tabularnewline
76 & 0.336439 & 0.672878 & 0.663561 \tabularnewline
77 & 0.324816 & 0.649631 & 0.675184 \tabularnewline
78 & 0.310313 & 0.620627 & 0.689687 \tabularnewline
79 & 0.288157 & 0.576314 & 0.711843 \tabularnewline
80 & 0.340287 & 0.680573 & 0.659713 \tabularnewline
81 & 0.310723 & 0.621446 & 0.689277 \tabularnewline
82 & 0.332298 & 0.664596 & 0.667702 \tabularnewline
83 & 0.303748 & 0.607497 & 0.696252 \tabularnewline
84 & 0.425754 & 0.851507 & 0.574246 \tabularnewline
85 & 0.407536 & 0.815072 & 0.592464 \tabularnewline
86 & 0.378736 & 0.757473 & 0.621264 \tabularnewline
87 & 0.348886 & 0.697773 & 0.651114 \tabularnewline
88 & 0.3185 & 0.637001 & 0.6815 \tabularnewline
89 & 0.31627 & 0.63254 & 0.68373 \tabularnewline
90 & 0.331735 & 0.66347 & 0.668265 \tabularnewline
91 & 0.345123 & 0.690246 & 0.654877 \tabularnewline
92 & 0.498211 & 0.996423 & 0.501789 \tabularnewline
93 & 0.470557 & 0.941114 & 0.529443 \tabularnewline
94 & 0.471433 & 0.942866 & 0.528567 \tabularnewline
95 & 0.535104 & 0.929791 & 0.464896 \tabularnewline
96 & 0.518053 & 0.963894 & 0.481947 \tabularnewline
97 & 0.552107 & 0.895785 & 0.447893 \tabularnewline
98 & 0.526057 & 0.947885 & 0.473943 \tabularnewline
99 & 0.569262 & 0.861476 & 0.430738 \tabularnewline
100 & 0.656319 & 0.687363 & 0.343681 \tabularnewline
101 & 0.629797 & 0.740405 & 0.370203 \tabularnewline
102 & 0.606402 & 0.787196 & 0.393598 \tabularnewline
103 & 0.60152 & 0.796961 & 0.39848 \tabularnewline
104 & 0.61236 & 0.77528 & 0.38764 \tabularnewline
105 & 0.644691 & 0.710618 & 0.355309 \tabularnewline
106 & 0.662182 & 0.675637 & 0.337818 \tabularnewline
107 & 0.666521 & 0.666957 & 0.333479 \tabularnewline
108 & 0.806249 & 0.387502 & 0.193751 \tabularnewline
109 & 0.856579 & 0.286843 & 0.143421 \tabularnewline
110 & 0.854729 & 0.290542 & 0.145271 \tabularnewline
111 & 0.841893 & 0.316213 & 0.158107 \tabularnewline
112 & 0.828745 & 0.34251 & 0.171255 \tabularnewline
113 & 0.891979 & 0.216042 & 0.108021 \tabularnewline
114 & 0.897141 & 0.205717 & 0.102859 \tabularnewline
115 & 0.905064 & 0.189873 & 0.0949365 \tabularnewline
116 & 0.915311 & 0.169377 & 0.0846887 \tabularnewline
117 & 0.905267 & 0.189466 & 0.0947329 \tabularnewline
118 & 0.912132 & 0.175736 & 0.0878679 \tabularnewline
119 & 0.906767 & 0.186466 & 0.0932332 \tabularnewline
120 & 0.919101 & 0.161798 & 0.0808989 \tabularnewline
121 & 0.912675 & 0.174651 & 0.0873253 \tabularnewline
122 & 0.935184 & 0.129632 & 0.0648161 \tabularnewline
123 & 0.92711 & 0.14578 & 0.0728898 \tabularnewline
124 & 0.957084 & 0.0858319 & 0.0429159 \tabularnewline
125 & 0.963581 & 0.0728371 & 0.0364185 \tabularnewline
126 & 0.957765 & 0.0844709 & 0.0422354 \tabularnewline
127 & 0.952257 & 0.0954863 & 0.0477432 \tabularnewline
128 & 0.954342 & 0.0913152 & 0.0456576 \tabularnewline
129 & 0.955582 & 0.0888358 & 0.0444179 \tabularnewline
130 & 0.953221 & 0.093558 & 0.046779 \tabularnewline
131 & 0.949308 & 0.101385 & 0.0506924 \tabularnewline
132 & 0.942057 & 0.115886 & 0.0579432 \tabularnewline
133 & 0.938587 & 0.122827 & 0.0614135 \tabularnewline
134 & 0.928811 & 0.142379 & 0.0711894 \tabularnewline
135 & 0.920651 & 0.158699 & 0.0793493 \tabularnewline
136 & 0.910626 & 0.178748 & 0.089374 \tabularnewline
137 & 0.930685 & 0.13863 & 0.0693148 \tabularnewline
138 & 0.947194 & 0.105611 & 0.0528056 \tabularnewline
139 & 0.93874 & 0.12252 & 0.0612598 \tabularnewline
140 & 0.928293 & 0.143414 & 0.0717072 \tabularnewline
141 & 0.918391 & 0.163217 & 0.0816086 \tabularnewline
142 & 0.927514 & 0.144971 & 0.0724856 \tabularnewline
143 & 0.918803 & 0.162393 & 0.0811966 \tabularnewline
144 & 0.911057 & 0.177886 & 0.0889429 \tabularnewline
145 & 0.899742 & 0.200515 & 0.100258 \tabularnewline
146 & 0.895339 & 0.209321 & 0.104661 \tabularnewline
147 & 0.884436 & 0.231128 & 0.115564 \tabularnewline
148 & 0.869238 & 0.261525 & 0.130762 \tabularnewline
149 & 0.883892 & 0.232217 & 0.116108 \tabularnewline
150 & 0.873593 & 0.252814 & 0.126407 \tabularnewline
151 & 0.948806 & 0.102387 & 0.0511935 \tabularnewline
152 & 0.944826 & 0.110347 & 0.0551736 \tabularnewline
153 & 0.939976 & 0.120048 & 0.0600238 \tabularnewline
154 & 0.929878 & 0.140243 & 0.0701217 \tabularnewline
155 & 0.938431 & 0.123138 & 0.0615692 \tabularnewline
156 & 0.92863 & 0.14274 & 0.0713698 \tabularnewline
157 & 0.926878 & 0.146243 & 0.0731215 \tabularnewline
158 & 0.923932 & 0.152137 & 0.0760683 \tabularnewline
159 & 0.913483 & 0.173034 & 0.0865171 \tabularnewline
160 & 0.900315 & 0.199369 & 0.0996847 \tabularnewline
161 & 0.931593 & 0.136813 & 0.0684067 \tabularnewline
162 & 0.919241 & 0.161518 & 0.0807591 \tabularnewline
163 & 0.909677 & 0.180645 & 0.0903226 \tabularnewline
164 & 0.949733 & 0.100533 & 0.0502667 \tabularnewline
165 & 0.958632 & 0.0827368 & 0.0413684 \tabularnewline
166 & 0.953544 & 0.0929129 & 0.0464565 \tabularnewline
167 & 0.949881 & 0.100238 & 0.050119 \tabularnewline
168 & 0.959508 & 0.0809839 & 0.040492 \tabularnewline
169 & 0.951183 & 0.0976337 & 0.0488169 \tabularnewline
170 & 0.950675 & 0.0986503 & 0.0493252 \tabularnewline
171 & 0.941543 & 0.116913 & 0.0584565 \tabularnewline
172 & 0.953795 & 0.0924103 & 0.0462051 \tabularnewline
173 & 0.945928 & 0.108144 & 0.054072 \tabularnewline
174 & 0.936709 & 0.126581 & 0.0632906 \tabularnewline
175 & 0.926404 & 0.147192 & 0.0735961 \tabularnewline
176 & 0.931821 & 0.136357 & 0.0681787 \tabularnewline
177 & 0.922876 & 0.154248 & 0.0771239 \tabularnewline
178 & 0.918015 & 0.16397 & 0.0819852 \tabularnewline
179 & 0.905363 & 0.189273 & 0.0946366 \tabularnewline
180 & 0.921066 & 0.157868 & 0.0789341 \tabularnewline
181 & 0.91119 & 0.177619 & 0.0888097 \tabularnewline
182 & 0.896537 & 0.206927 & 0.103463 \tabularnewline
183 & 0.887109 & 0.225782 & 0.112891 \tabularnewline
184 & 0.868983 & 0.262034 & 0.131017 \tabularnewline
185 & 0.886503 & 0.226993 & 0.113497 \tabularnewline
186 & 0.871743 & 0.256514 & 0.128257 \tabularnewline
187 & 0.905304 & 0.189392 & 0.0946958 \tabularnewline
188 & 0.893252 & 0.213496 & 0.106748 \tabularnewline
189 & 0.881066 & 0.237868 & 0.118934 \tabularnewline
190 & 0.861528 & 0.276944 & 0.138472 \tabularnewline
191 & 0.841648 & 0.316704 & 0.158352 \tabularnewline
192 & 0.835743 & 0.328515 & 0.164257 \tabularnewline
193 & 0.828907 & 0.342185 & 0.171093 \tabularnewline
194 & 0.841736 & 0.316529 & 0.158264 \tabularnewline
195 & 0.833235 & 0.333529 & 0.166765 \tabularnewline
196 & 0.816815 & 0.366369 & 0.183185 \tabularnewline
197 & 0.83805 & 0.323901 & 0.16195 \tabularnewline
198 & 0.813396 & 0.373208 & 0.186604 \tabularnewline
199 & 0.840651 & 0.318699 & 0.159349 \tabularnewline
200 & 0.826861 & 0.346278 & 0.173139 \tabularnewline
201 & 0.809774 & 0.380451 & 0.190226 \tabularnewline
202 & 0.802867 & 0.394267 & 0.197133 \tabularnewline
203 & 0.781912 & 0.436176 & 0.218088 \tabularnewline
204 & 0.752617 & 0.494767 & 0.247383 \tabularnewline
205 & 0.735604 & 0.528791 & 0.264396 \tabularnewline
206 & 0.775998 & 0.448005 & 0.224002 \tabularnewline
207 & 0.772442 & 0.455117 & 0.227558 \tabularnewline
208 & 0.793862 & 0.412276 & 0.206138 \tabularnewline
209 & 0.770738 & 0.458524 & 0.229262 \tabularnewline
210 & 0.749771 & 0.500457 & 0.250229 \tabularnewline
211 & 0.757865 & 0.484271 & 0.242135 \tabularnewline
212 & 0.730032 & 0.539937 & 0.269968 \tabularnewline
213 & 0.746156 & 0.507687 & 0.253844 \tabularnewline
214 & 0.716072 & 0.567856 & 0.283928 \tabularnewline
215 & 0.688796 & 0.622407 & 0.311204 \tabularnewline
216 & 0.66538 & 0.669241 & 0.33462 \tabularnewline
217 & 0.654423 & 0.691155 & 0.345577 \tabularnewline
218 & 0.636599 & 0.726801 & 0.363401 \tabularnewline
219 & 0.609833 & 0.780333 & 0.390167 \tabularnewline
220 & 0.568255 & 0.863489 & 0.431745 \tabularnewline
221 & 0.526736 & 0.946528 & 0.473264 \tabularnewline
222 & 0.544739 & 0.910523 & 0.455261 \tabularnewline
223 & 0.504101 & 0.991799 & 0.495899 \tabularnewline
224 & 0.465014 & 0.930028 & 0.534986 \tabularnewline
225 & 0.455416 & 0.910833 & 0.544584 \tabularnewline
226 & 0.470488 & 0.940976 & 0.529512 \tabularnewline
227 & 0.437598 & 0.875196 & 0.562402 \tabularnewline
228 & 0.514901 & 0.970199 & 0.485099 \tabularnewline
229 & 0.511751 & 0.976498 & 0.488249 \tabularnewline
230 & 0.49384 & 0.987679 & 0.50616 \tabularnewline
231 & 0.499382 & 0.998764 & 0.500618 \tabularnewline
232 & 0.472261 & 0.944523 & 0.527739 \tabularnewline
233 & 0.450811 & 0.901622 & 0.549189 \tabularnewline
234 & 0.445304 & 0.890609 & 0.554696 \tabularnewline
235 & 0.41314 & 0.82628 & 0.58686 \tabularnewline
236 & 0.608317 & 0.783366 & 0.391683 \tabularnewline
237 & 0.570029 & 0.859942 & 0.429971 \tabularnewline
238 & 0.633415 & 0.73317 & 0.366585 \tabularnewline
239 & 0.599294 & 0.801412 & 0.400706 \tabularnewline
240 & 0.556646 & 0.886709 & 0.443354 \tabularnewline
241 & 0.53252 & 0.934959 & 0.46748 \tabularnewline
242 & 0.586461 & 0.827078 & 0.413539 \tabularnewline
243 & 0.57724 & 0.845519 & 0.42276 \tabularnewline
244 & 0.623321 & 0.753359 & 0.376679 \tabularnewline
245 & 0.57295 & 0.854101 & 0.42705 \tabularnewline
246 & 0.517647 & 0.964706 & 0.482353 \tabularnewline
247 & 0.46368 & 0.92736 & 0.53632 \tabularnewline
248 & 0.410973 & 0.821945 & 0.589027 \tabularnewline
249 & 0.364952 & 0.729904 & 0.635048 \tabularnewline
250 & 0.33556 & 0.67112 & 0.66444 \tabularnewline
251 & 0.362258 & 0.724515 & 0.637742 \tabularnewline
252 & 0.386243 & 0.772487 & 0.613757 \tabularnewline
253 & 0.338999 & 0.677998 & 0.661001 \tabularnewline
254 & 0.301327 & 0.602655 & 0.698673 \tabularnewline
255 & 0.335784 & 0.671568 & 0.664216 \tabularnewline
256 & 0.290731 & 0.581461 & 0.709269 \tabularnewline
257 & 0.295326 & 0.590652 & 0.704674 \tabularnewline
258 & 0.779217 & 0.441566 & 0.220783 \tabularnewline
259 & 0.727598 & 0.544803 & 0.272402 \tabularnewline
260 & 0.999071 & 0.00185826 & 0.00092913 \tabularnewline
261 & 0.998387 & 0.00322593 & 0.00161296 \tabularnewline
262 & 0.996606 & 0.00678874 & 0.00339437 \tabularnewline
263 & 0.999957 & 8.58074e-05 & 4.29037e-05 \tabularnewline
264 & 0.999866 & 0.000267192 & 0.000133596 \tabularnewline
265 & 0.999619 & 0.000761852 & 0.000380926 \tabularnewline
266 & 0.999025 & 0.00194978 & 0.000974888 \tabularnewline
267 & 0.998872 & 0.00225551 & 0.00112776 \tabularnewline
268 & 0.999006 & 0.00198895 & 0.000994475 \tabularnewline
269 & 0.998035 & 0.00392943 & 0.00196472 \tabularnewline
270 & 0.995169 & 0.00966112 & 0.00483056 \tabularnewline
271 & 0.999939 & 0.000122429 & 6.12146e-05 \tabularnewline
272 & 0.999307 & 0.00138556 & 0.000692779 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265691&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]6[/C][C]0.851257[/C][C]0.297487[/C][C]0.148743[/C][/ROW]
[ROW][C]7[/C][C]0.956325[/C][C]0.0873502[/C][C]0.0436751[/C][/ROW]
[ROW][C]8[/C][C]0.93311[/C][C]0.133781[/C][C]0.0668903[/C][/ROW]
[ROW][C]9[/C][C]0.891708[/C][C]0.216584[/C][C]0.108292[/C][/ROW]
[ROW][C]10[/C][C]0.919572[/C][C]0.160855[/C][C]0.0804276[/C][/ROW]
[ROW][C]11[/C][C]0.875885[/C][C]0.24823[/C][C]0.124115[/C][/ROW]
[ROW][C]12[/C][C]0.901741[/C][C]0.196519[/C][C]0.0982593[/C][/ROW]
[ROW][C]13[/C][C]0.857222[/C][C]0.285556[/C][C]0.142778[/C][/ROW]
[ROW][C]14[/C][C]0.807956[/C][C]0.384089[/C][C]0.192044[/C][/ROW]
[ROW][C]15[/C][C]0.775943[/C][C]0.448115[/C][C]0.224057[/C][/ROW]
[ROW][C]16[/C][C]0.731023[/C][C]0.537953[/C][C]0.268977[/C][/ROW]
[ROW][C]17[/C][C]0.692368[/C][C]0.615265[/C][C]0.307632[/C][/ROW]
[ROW][C]18[/C][C]0.634493[/C][C]0.731015[/C][C]0.365507[/C][/ROW]
[ROW][C]19[/C][C]0.600084[/C][C]0.799831[/C][C]0.399916[/C][/ROW]
[ROW][C]20[/C][C]0.532737[/C][C]0.934526[/C][C]0.467263[/C][/ROW]
[ROW][C]21[/C][C]0.725982[/C][C]0.548036[/C][C]0.274018[/C][/ROW]
[ROW][C]22[/C][C]0.713324[/C][C]0.573351[/C][C]0.286676[/C][/ROW]
[ROW][C]23[/C][C]0.660326[/C][C]0.679347[/C][C]0.339674[/C][/ROW]
[ROW][C]24[/C][C]0.665501[/C][C]0.668998[/C][C]0.334499[/C][/ROW]
[ROW][C]25[/C][C]0.6181[/C][C]0.763801[/C][C]0.3819[/C][/ROW]
[ROW][C]26[/C][C]0.580998[/C][C]0.838005[/C][C]0.419002[/C][/ROW]
[ROW][C]27[/C][C]0.630745[/C][C]0.73851[/C][C]0.369255[/C][/ROW]
[ROW][C]28[/C][C]0.64366[/C][C]0.71268[/C][C]0.35634[/C][/ROW]
[ROW][C]29[/C][C]0.596326[/C][C]0.807347[/C][C]0.403674[/C][/ROW]
[ROW][C]30[/C][C]0.54507[/C][C]0.909859[/C][C]0.45493[/C][/ROW]
[ROW][C]31[/C][C]0.532706[/C][C]0.934587[/C][C]0.467294[/C][/ROW]
[ROW][C]32[/C][C]0.486178[/C][C]0.972357[/C][C]0.513822[/C][/ROW]
[ROW][C]33[/C][C]0.447554[/C][C]0.895108[/C][C]0.552446[/C][/ROW]
[ROW][C]34[/C][C]0.447491[/C][C]0.894981[/C][C]0.552509[/C][/ROW]
[ROW][C]35[/C][C]0.399504[/C][C]0.799009[/C][C]0.600496[/C][/ROW]
[ROW][C]36[/C][C]0.354538[/C][C]0.709077[/C][C]0.645462[/C][/ROW]
[ROW][C]37[/C][C]0.308427[/C][C]0.616855[/C][C]0.691573[/C][/ROW]
[ROW][C]38[/C][C]0.283509[/C][C]0.567018[/C][C]0.716491[/C][/ROW]
[ROW][C]39[/C][C]0.296266[/C][C]0.592532[/C][C]0.703734[/C][/ROW]
[ROW][C]40[/C][C]0.26083[/C][C]0.52166[/C][C]0.73917[/C][/ROW]
[ROW][C]41[/C][C]0.408105[/C][C]0.816211[/C][C]0.591895[/C][/ROW]
[ROW][C]42[/C][C]0.366453[/C][C]0.732905[/C][C]0.633547[/C][/ROW]
[ROW][C]43[/C][C]0.354692[/C][C]0.709383[/C][C]0.645308[/C][/ROW]
[ROW][C]44[/C][C]0.313262[/C][C]0.626525[/C][C]0.686738[/C][/ROW]
[ROW][C]45[/C][C]0.301122[/C][C]0.602244[/C][C]0.698878[/C][/ROW]
[ROW][C]46[/C][C]0.265803[/C][C]0.531605[/C][C]0.734197[/C][/ROW]
[ROW][C]47[/C][C]0.236241[/C][C]0.472481[/C][C]0.763759[/C][/ROW]
[ROW][C]48[/C][C]0.298287[/C][C]0.596573[/C][C]0.701713[/C][/ROW]
[ROW][C]49[/C][C]0.34133[/C][C]0.682659[/C][C]0.65867[/C][/ROW]
[ROW][C]50[/C][C]0.319733[/C][C]0.639465[/C][C]0.680267[/C][/ROW]
[ROW][C]51[/C][C]0.28268[/C][C]0.565359[/C][C]0.71732[/C][/ROW]
[ROW][C]52[/C][C]0.335286[/C][C]0.670571[/C][C]0.664714[/C][/ROW]
[ROW][C]53[/C][C]0.300042[/C][C]0.600085[/C][C]0.699958[/C][/ROW]
[ROW][C]54[/C][C]0.284458[/C][C]0.568917[/C][C]0.715542[/C][/ROW]
[ROW][C]55[/C][C]0.295096[/C][C]0.590192[/C][C]0.704904[/C][/ROW]
[ROW][C]56[/C][C]0.264521[/C][C]0.529042[/C][C]0.735479[/C][/ROW]
[ROW][C]57[/C][C]0.41827[/C][C]0.836541[/C][C]0.58173[/C][/ROW]
[ROW][C]58[/C][C]0.497914[/C][C]0.995827[/C][C]0.502086[/C][/ROW]
[ROW][C]59[/C][C]0.45941[/C][C]0.91882[/C][C]0.54059[/C][/ROW]
[ROW][C]60[/C][C]0.491729[/C][C]0.983457[/C][C]0.508271[/C][/ROW]
[ROW][C]61[/C][C]0.477462[/C][C]0.954924[/C][C]0.522538[/C][/ROW]
[ROW][C]62[/C][C]0.446715[/C][C]0.89343[/C][C]0.553285[/C][/ROW]
[ROW][C]63[/C][C]0.490334[/C][C]0.980668[/C][C]0.509666[/C][/ROW]
[ROW][C]64[/C][C]0.554558[/C][C]0.890883[/C][C]0.445442[/C][/ROW]
[ROW][C]65[/C][C]0.536764[/C][C]0.926472[/C][C]0.463236[/C][/ROW]
[ROW][C]66[/C][C]0.503963[/C][C]0.992075[/C][C]0.496037[/C][/ROW]
[ROW][C]67[/C][C]0.490817[/C][C]0.981635[/C][C]0.509183[/C][/ROW]
[ROW][C]68[/C][C]0.46076[/C][C]0.92152[/C][C]0.53924[/C][/ROW]
[ROW][C]69[/C][C]0.460249[/C][C]0.920499[/C][C]0.539751[/C][/ROW]
[ROW][C]70[/C][C]0.439221[/C][C]0.878443[/C][C]0.560779[/C][/ROW]
[ROW][C]71[/C][C]0.407033[/C][C]0.814065[/C][C]0.592967[/C][/ROW]
[ROW][C]72[/C][C]0.374513[/C][C]0.749025[/C][C]0.625487[/C][/ROW]
[ROW][C]73[/C][C]0.349359[/C][C]0.698718[/C][C]0.650641[/C][/ROW]
[ROW][C]74[/C][C]0.378078[/C][C]0.756156[/C][C]0.621922[/C][/ROW]
[ROW][C]75[/C][C]0.359213[/C][C]0.718425[/C][C]0.640787[/C][/ROW]
[ROW][C]76[/C][C]0.336439[/C][C]0.672878[/C][C]0.663561[/C][/ROW]
[ROW][C]77[/C][C]0.324816[/C][C]0.649631[/C][C]0.675184[/C][/ROW]
[ROW][C]78[/C][C]0.310313[/C][C]0.620627[/C][C]0.689687[/C][/ROW]
[ROW][C]79[/C][C]0.288157[/C][C]0.576314[/C][C]0.711843[/C][/ROW]
[ROW][C]80[/C][C]0.340287[/C][C]0.680573[/C][C]0.659713[/C][/ROW]
[ROW][C]81[/C][C]0.310723[/C][C]0.621446[/C][C]0.689277[/C][/ROW]
[ROW][C]82[/C][C]0.332298[/C][C]0.664596[/C][C]0.667702[/C][/ROW]
[ROW][C]83[/C][C]0.303748[/C][C]0.607497[/C][C]0.696252[/C][/ROW]
[ROW][C]84[/C][C]0.425754[/C][C]0.851507[/C][C]0.574246[/C][/ROW]
[ROW][C]85[/C][C]0.407536[/C][C]0.815072[/C][C]0.592464[/C][/ROW]
[ROW][C]86[/C][C]0.378736[/C][C]0.757473[/C][C]0.621264[/C][/ROW]
[ROW][C]87[/C][C]0.348886[/C][C]0.697773[/C][C]0.651114[/C][/ROW]
[ROW][C]88[/C][C]0.3185[/C][C]0.637001[/C][C]0.6815[/C][/ROW]
[ROW][C]89[/C][C]0.31627[/C][C]0.63254[/C][C]0.68373[/C][/ROW]
[ROW][C]90[/C][C]0.331735[/C][C]0.66347[/C][C]0.668265[/C][/ROW]
[ROW][C]91[/C][C]0.345123[/C][C]0.690246[/C][C]0.654877[/C][/ROW]
[ROW][C]92[/C][C]0.498211[/C][C]0.996423[/C][C]0.501789[/C][/ROW]
[ROW][C]93[/C][C]0.470557[/C][C]0.941114[/C][C]0.529443[/C][/ROW]
[ROW][C]94[/C][C]0.471433[/C][C]0.942866[/C][C]0.528567[/C][/ROW]
[ROW][C]95[/C][C]0.535104[/C][C]0.929791[/C][C]0.464896[/C][/ROW]
[ROW][C]96[/C][C]0.518053[/C][C]0.963894[/C][C]0.481947[/C][/ROW]
[ROW][C]97[/C][C]0.552107[/C][C]0.895785[/C][C]0.447893[/C][/ROW]
[ROW][C]98[/C][C]0.526057[/C][C]0.947885[/C][C]0.473943[/C][/ROW]
[ROW][C]99[/C][C]0.569262[/C][C]0.861476[/C][C]0.430738[/C][/ROW]
[ROW][C]100[/C][C]0.656319[/C][C]0.687363[/C][C]0.343681[/C][/ROW]
[ROW][C]101[/C][C]0.629797[/C][C]0.740405[/C][C]0.370203[/C][/ROW]
[ROW][C]102[/C][C]0.606402[/C][C]0.787196[/C][C]0.393598[/C][/ROW]
[ROW][C]103[/C][C]0.60152[/C][C]0.796961[/C][C]0.39848[/C][/ROW]
[ROW][C]104[/C][C]0.61236[/C][C]0.77528[/C][C]0.38764[/C][/ROW]
[ROW][C]105[/C][C]0.644691[/C][C]0.710618[/C][C]0.355309[/C][/ROW]
[ROW][C]106[/C][C]0.662182[/C][C]0.675637[/C][C]0.337818[/C][/ROW]
[ROW][C]107[/C][C]0.666521[/C][C]0.666957[/C][C]0.333479[/C][/ROW]
[ROW][C]108[/C][C]0.806249[/C][C]0.387502[/C][C]0.193751[/C][/ROW]
[ROW][C]109[/C][C]0.856579[/C][C]0.286843[/C][C]0.143421[/C][/ROW]
[ROW][C]110[/C][C]0.854729[/C][C]0.290542[/C][C]0.145271[/C][/ROW]
[ROW][C]111[/C][C]0.841893[/C][C]0.316213[/C][C]0.158107[/C][/ROW]
[ROW][C]112[/C][C]0.828745[/C][C]0.34251[/C][C]0.171255[/C][/ROW]
[ROW][C]113[/C][C]0.891979[/C][C]0.216042[/C][C]0.108021[/C][/ROW]
[ROW][C]114[/C][C]0.897141[/C][C]0.205717[/C][C]0.102859[/C][/ROW]
[ROW][C]115[/C][C]0.905064[/C][C]0.189873[/C][C]0.0949365[/C][/ROW]
[ROW][C]116[/C][C]0.915311[/C][C]0.169377[/C][C]0.0846887[/C][/ROW]
[ROW][C]117[/C][C]0.905267[/C][C]0.189466[/C][C]0.0947329[/C][/ROW]
[ROW][C]118[/C][C]0.912132[/C][C]0.175736[/C][C]0.0878679[/C][/ROW]
[ROW][C]119[/C][C]0.906767[/C][C]0.186466[/C][C]0.0932332[/C][/ROW]
[ROW][C]120[/C][C]0.919101[/C][C]0.161798[/C][C]0.0808989[/C][/ROW]
[ROW][C]121[/C][C]0.912675[/C][C]0.174651[/C][C]0.0873253[/C][/ROW]
[ROW][C]122[/C][C]0.935184[/C][C]0.129632[/C][C]0.0648161[/C][/ROW]
[ROW][C]123[/C][C]0.92711[/C][C]0.14578[/C][C]0.0728898[/C][/ROW]
[ROW][C]124[/C][C]0.957084[/C][C]0.0858319[/C][C]0.0429159[/C][/ROW]
[ROW][C]125[/C][C]0.963581[/C][C]0.0728371[/C][C]0.0364185[/C][/ROW]
[ROW][C]126[/C][C]0.957765[/C][C]0.0844709[/C][C]0.0422354[/C][/ROW]
[ROW][C]127[/C][C]0.952257[/C][C]0.0954863[/C][C]0.0477432[/C][/ROW]
[ROW][C]128[/C][C]0.954342[/C][C]0.0913152[/C][C]0.0456576[/C][/ROW]
[ROW][C]129[/C][C]0.955582[/C][C]0.0888358[/C][C]0.0444179[/C][/ROW]
[ROW][C]130[/C][C]0.953221[/C][C]0.093558[/C][C]0.046779[/C][/ROW]
[ROW][C]131[/C][C]0.949308[/C][C]0.101385[/C][C]0.0506924[/C][/ROW]
[ROW][C]132[/C][C]0.942057[/C][C]0.115886[/C][C]0.0579432[/C][/ROW]
[ROW][C]133[/C][C]0.938587[/C][C]0.122827[/C][C]0.0614135[/C][/ROW]
[ROW][C]134[/C][C]0.928811[/C][C]0.142379[/C][C]0.0711894[/C][/ROW]
[ROW][C]135[/C][C]0.920651[/C][C]0.158699[/C][C]0.0793493[/C][/ROW]
[ROW][C]136[/C][C]0.910626[/C][C]0.178748[/C][C]0.089374[/C][/ROW]
[ROW][C]137[/C][C]0.930685[/C][C]0.13863[/C][C]0.0693148[/C][/ROW]
[ROW][C]138[/C][C]0.947194[/C][C]0.105611[/C][C]0.0528056[/C][/ROW]
[ROW][C]139[/C][C]0.93874[/C][C]0.12252[/C][C]0.0612598[/C][/ROW]
[ROW][C]140[/C][C]0.928293[/C][C]0.143414[/C][C]0.0717072[/C][/ROW]
[ROW][C]141[/C][C]0.918391[/C][C]0.163217[/C][C]0.0816086[/C][/ROW]
[ROW][C]142[/C][C]0.927514[/C][C]0.144971[/C][C]0.0724856[/C][/ROW]
[ROW][C]143[/C][C]0.918803[/C][C]0.162393[/C][C]0.0811966[/C][/ROW]
[ROW][C]144[/C][C]0.911057[/C][C]0.177886[/C][C]0.0889429[/C][/ROW]
[ROW][C]145[/C][C]0.899742[/C][C]0.200515[/C][C]0.100258[/C][/ROW]
[ROW][C]146[/C][C]0.895339[/C][C]0.209321[/C][C]0.104661[/C][/ROW]
[ROW][C]147[/C][C]0.884436[/C][C]0.231128[/C][C]0.115564[/C][/ROW]
[ROW][C]148[/C][C]0.869238[/C][C]0.261525[/C][C]0.130762[/C][/ROW]
[ROW][C]149[/C][C]0.883892[/C][C]0.232217[/C][C]0.116108[/C][/ROW]
[ROW][C]150[/C][C]0.873593[/C][C]0.252814[/C][C]0.126407[/C][/ROW]
[ROW][C]151[/C][C]0.948806[/C][C]0.102387[/C][C]0.0511935[/C][/ROW]
[ROW][C]152[/C][C]0.944826[/C][C]0.110347[/C][C]0.0551736[/C][/ROW]
[ROW][C]153[/C][C]0.939976[/C][C]0.120048[/C][C]0.0600238[/C][/ROW]
[ROW][C]154[/C][C]0.929878[/C][C]0.140243[/C][C]0.0701217[/C][/ROW]
[ROW][C]155[/C][C]0.938431[/C][C]0.123138[/C][C]0.0615692[/C][/ROW]
[ROW][C]156[/C][C]0.92863[/C][C]0.14274[/C][C]0.0713698[/C][/ROW]
[ROW][C]157[/C][C]0.926878[/C][C]0.146243[/C][C]0.0731215[/C][/ROW]
[ROW][C]158[/C][C]0.923932[/C][C]0.152137[/C][C]0.0760683[/C][/ROW]
[ROW][C]159[/C][C]0.913483[/C][C]0.173034[/C][C]0.0865171[/C][/ROW]
[ROW][C]160[/C][C]0.900315[/C][C]0.199369[/C][C]0.0996847[/C][/ROW]
[ROW][C]161[/C][C]0.931593[/C][C]0.136813[/C][C]0.0684067[/C][/ROW]
[ROW][C]162[/C][C]0.919241[/C][C]0.161518[/C][C]0.0807591[/C][/ROW]
[ROW][C]163[/C][C]0.909677[/C][C]0.180645[/C][C]0.0903226[/C][/ROW]
[ROW][C]164[/C][C]0.949733[/C][C]0.100533[/C][C]0.0502667[/C][/ROW]
[ROW][C]165[/C][C]0.958632[/C][C]0.0827368[/C][C]0.0413684[/C][/ROW]
[ROW][C]166[/C][C]0.953544[/C][C]0.0929129[/C][C]0.0464565[/C][/ROW]
[ROW][C]167[/C][C]0.949881[/C][C]0.100238[/C][C]0.050119[/C][/ROW]
[ROW][C]168[/C][C]0.959508[/C][C]0.0809839[/C][C]0.040492[/C][/ROW]
[ROW][C]169[/C][C]0.951183[/C][C]0.0976337[/C][C]0.0488169[/C][/ROW]
[ROW][C]170[/C][C]0.950675[/C][C]0.0986503[/C][C]0.0493252[/C][/ROW]
[ROW][C]171[/C][C]0.941543[/C][C]0.116913[/C][C]0.0584565[/C][/ROW]
[ROW][C]172[/C][C]0.953795[/C][C]0.0924103[/C][C]0.0462051[/C][/ROW]
[ROW][C]173[/C][C]0.945928[/C][C]0.108144[/C][C]0.054072[/C][/ROW]
[ROW][C]174[/C][C]0.936709[/C][C]0.126581[/C][C]0.0632906[/C][/ROW]
[ROW][C]175[/C][C]0.926404[/C][C]0.147192[/C][C]0.0735961[/C][/ROW]
[ROW][C]176[/C][C]0.931821[/C][C]0.136357[/C][C]0.0681787[/C][/ROW]
[ROW][C]177[/C][C]0.922876[/C][C]0.154248[/C][C]0.0771239[/C][/ROW]
[ROW][C]178[/C][C]0.918015[/C][C]0.16397[/C][C]0.0819852[/C][/ROW]
[ROW][C]179[/C][C]0.905363[/C][C]0.189273[/C][C]0.0946366[/C][/ROW]
[ROW][C]180[/C][C]0.921066[/C][C]0.157868[/C][C]0.0789341[/C][/ROW]
[ROW][C]181[/C][C]0.91119[/C][C]0.177619[/C][C]0.0888097[/C][/ROW]
[ROW][C]182[/C][C]0.896537[/C][C]0.206927[/C][C]0.103463[/C][/ROW]
[ROW][C]183[/C][C]0.887109[/C][C]0.225782[/C][C]0.112891[/C][/ROW]
[ROW][C]184[/C][C]0.868983[/C][C]0.262034[/C][C]0.131017[/C][/ROW]
[ROW][C]185[/C][C]0.886503[/C][C]0.226993[/C][C]0.113497[/C][/ROW]
[ROW][C]186[/C][C]0.871743[/C][C]0.256514[/C][C]0.128257[/C][/ROW]
[ROW][C]187[/C][C]0.905304[/C][C]0.189392[/C][C]0.0946958[/C][/ROW]
[ROW][C]188[/C][C]0.893252[/C][C]0.213496[/C][C]0.106748[/C][/ROW]
[ROW][C]189[/C][C]0.881066[/C][C]0.237868[/C][C]0.118934[/C][/ROW]
[ROW][C]190[/C][C]0.861528[/C][C]0.276944[/C][C]0.138472[/C][/ROW]
[ROW][C]191[/C][C]0.841648[/C][C]0.316704[/C][C]0.158352[/C][/ROW]
[ROW][C]192[/C][C]0.835743[/C][C]0.328515[/C][C]0.164257[/C][/ROW]
[ROW][C]193[/C][C]0.828907[/C][C]0.342185[/C][C]0.171093[/C][/ROW]
[ROW][C]194[/C][C]0.841736[/C][C]0.316529[/C][C]0.158264[/C][/ROW]
[ROW][C]195[/C][C]0.833235[/C][C]0.333529[/C][C]0.166765[/C][/ROW]
[ROW][C]196[/C][C]0.816815[/C][C]0.366369[/C][C]0.183185[/C][/ROW]
[ROW][C]197[/C][C]0.83805[/C][C]0.323901[/C][C]0.16195[/C][/ROW]
[ROW][C]198[/C][C]0.813396[/C][C]0.373208[/C][C]0.186604[/C][/ROW]
[ROW][C]199[/C][C]0.840651[/C][C]0.318699[/C][C]0.159349[/C][/ROW]
[ROW][C]200[/C][C]0.826861[/C][C]0.346278[/C][C]0.173139[/C][/ROW]
[ROW][C]201[/C][C]0.809774[/C][C]0.380451[/C][C]0.190226[/C][/ROW]
[ROW][C]202[/C][C]0.802867[/C][C]0.394267[/C][C]0.197133[/C][/ROW]
[ROW][C]203[/C][C]0.781912[/C][C]0.436176[/C][C]0.218088[/C][/ROW]
[ROW][C]204[/C][C]0.752617[/C][C]0.494767[/C][C]0.247383[/C][/ROW]
[ROW][C]205[/C][C]0.735604[/C][C]0.528791[/C][C]0.264396[/C][/ROW]
[ROW][C]206[/C][C]0.775998[/C][C]0.448005[/C][C]0.224002[/C][/ROW]
[ROW][C]207[/C][C]0.772442[/C][C]0.455117[/C][C]0.227558[/C][/ROW]
[ROW][C]208[/C][C]0.793862[/C][C]0.412276[/C][C]0.206138[/C][/ROW]
[ROW][C]209[/C][C]0.770738[/C][C]0.458524[/C][C]0.229262[/C][/ROW]
[ROW][C]210[/C][C]0.749771[/C][C]0.500457[/C][C]0.250229[/C][/ROW]
[ROW][C]211[/C][C]0.757865[/C][C]0.484271[/C][C]0.242135[/C][/ROW]
[ROW][C]212[/C][C]0.730032[/C][C]0.539937[/C][C]0.269968[/C][/ROW]
[ROW][C]213[/C][C]0.746156[/C][C]0.507687[/C][C]0.253844[/C][/ROW]
[ROW][C]214[/C][C]0.716072[/C][C]0.567856[/C][C]0.283928[/C][/ROW]
[ROW][C]215[/C][C]0.688796[/C][C]0.622407[/C][C]0.311204[/C][/ROW]
[ROW][C]216[/C][C]0.66538[/C][C]0.669241[/C][C]0.33462[/C][/ROW]
[ROW][C]217[/C][C]0.654423[/C][C]0.691155[/C][C]0.345577[/C][/ROW]
[ROW][C]218[/C][C]0.636599[/C][C]0.726801[/C][C]0.363401[/C][/ROW]
[ROW][C]219[/C][C]0.609833[/C][C]0.780333[/C][C]0.390167[/C][/ROW]
[ROW][C]220[/C][C]0.568255[/C][C]0.863489[/C][C]0.431745[/C][/ROW]
[ROW][C]221[/C][C]0.526736[/C][C]0.946528[/C][C]0.473264[/C][/ROW]
[ROW][C]222[/C][C]0.544739[/C][C]0.910523[/C][C]0.455261[/C][/ROW]
[ROW][C]223[/C][C]0.504101[/C][C]0.991799[/C][C]0.495899[/C][/ROW]
[ROW][C]224[/C][C]0.465014[/C][C]0.930028[/C][C]0.534986[/C][/ROW]
[ROW][C]225[/C][C]0.455416[/C][C]0.910833[/C][C]0.544584[/C][/ROW]
[ROW][C]226[/C][C]0.470488[/C][C]0.940976[/C][C]0.529512[/C][/ROW]
[ROW][C]227[/C][C]0.437598[/C][C]0.875196[/C][C]0.562402[/C][/ROW]
[ROW][C]228[/C][C]0.514901[/C][C]0.970199[/C][C]0.485099[/C][/ROW]
[ROW][C]229[/C][C]0.511751[/C][C]0.976498[/C][C]0.488249[/C][/ROW]
[ROW][C]230[/C][C]0.49384[/C][C]0.987679[/C][C]0.50616[/C][/ROW]
[ROW][C]231[/C][C]0.499382[/C][C]0.998764[/C][C]0.500618[/C][/ROW]
[ROW][C]232[/C][C]0.472261[/C][C]0.944523[/C][C]0.527739[/C][/ROW]
[ROW][C]233[/C][C]0.450811[/C][C]0.901622[/C][C]0.549189[/C][/ROW]
[ROW][C]234[/C][C]0.445304[/C][C]0.890609[/C][C]0.554696[/C][/ROW]
[ROW][C]235[/C][C]0.41314[/C][C]0.82628[/C][C]0.58686[/C][/ROW]
[ROW][C]236[/C][C]0.608317[/C][C]0.783366[/C][C]0.391683[/C][/ROW]
[ROW][C]237[/C][C]0.570029[/C][C]0.859942[/C][C]0.429971[/C][/ROW]
[ROW][C]238[/C][C]0.633415[/C][C]0.73317[/C][C]0.366585[/C][/ROW]
[ROW][C]239[/C][C]0.599294[/C][C]0.801412[/C][C]0.400706[/C][/ROW]
[ROW][C]240[/C][C]0.556646[/C][C]0.886709[/C][C]0.443354[/C][/ROW]
[ROW][C]241[/C][C]0.53252[/C][C]0.934959[/C][C]0.46748[/C][/ROW]
[ROW][C]242[/C][C]0.586461[/C][C]0.827078[/C][C]0.413539[/C][/ROW]
[ROW][C]243[/C][C]0.57724[/C][C]0.845519[/C][C]0.42276[/C][/ROW]
[ROW][C]244[/C][C]0.623321[/C][C]0.753359[/C][C]0.376679[/C][/ROW]
[ROW][C]245[/C][C]0.57295[/C][C]0.854101[/C][C]0.42705[/C][/ROW]
[ROW][C]246[/C][C]0.517647[/C][C]0.964706[/C][C]0.482353[/C][/ROW]
[ROW][C]247[/C][C]0.46368[/C][C]0.92736[/C][C]0.53632[/C][/ROW]
[ROW][C]248[/C][C]0.410973[/C][C]0.821945[/C][C]0.589027[/C][/ROW]
[ROW][C]249[/C][C]0.364952[/C][C]0.729904[/C][C]0.635048[/C][/ROW]
[ROW][C]250[/C][C]0.33556[/C][C]0.67112[/C][C]0.66444[/C][/ROW]
[ROW][C]251[/C][C]0.362258[/C][C]0.724515[/C][C]0.637742[/C][/ROW]
[ROW][C]252[/C][C]0.386243[/C][C]0.772487[/C][C]0.613757[/C][/ROW]
[ROW][C]253[/C][C]0.338999[/C][C]0.677998[/C][C]0.661001[/C][/ROW]
[ROW][C]254[/C][C]0.301327[/C][C]0.602655[/C][C]0.698673[/C][/ROW]
[ROW][C]255[/C][C]0.335784[/C][C]0.671568[/C][C]0.664216[/C][/ROW]
[ROW][C]256[/C][C]0.290731[/C][C]0.581461[/C][C]0.709269[/C][/ROW]
[ROW][C]257[/C][C]0.295326[/C][C]0.590652[/C][C]0.704674[/C][/ROW]
[ROW][C]258[/C][C]0.779217[/C][C]0.441566[/C][C]0.220783[/C][/ROW]
[ROW][C]259[/C][C]0.727598[/C][C]0.544803[/C][C]0.272402[/C][/ROW]
[ROW][C]260[/C][C]0.999071[/C][C]0.00185826[/C][C]0.00092913[/C][/ROW]
[ROW][C]261[/C][C]0.998387[/C][C]0.00322593[/C][C]0.00161296[/C][/ROW]
[ROW][C]262[/C][C]0.996606[/C][C]0.00678874[/C][C]0.00339437[/C][/ROW]
[ROW][C]263[/C][C]0.999957[/C][C]8.58074e-05[/C][C]4.29037e-05[/C][/ROW]
[ROW][C]264[/C][C]0.999866[/C][C]0.000267192[/C][C]0.000133596[/C][/ROW]
[ROW][C]265[/C][C]0.999619[/C][C]0.000761852[/C][C]0.000380926[/C][/ROW]
[ROW][C]266[/C][C]0.999025[/C][C]0.00194978[/C][C]0.000974888[/C][/ROW]
[ROW][C]267[/C][C]0.998872[/C][C]0.00225551[/C][C]0.00112776[/C][/ROW]
[ROW][C]268[/C][C]0.999006[/C][C]0.00198895[/C][C]0.000994475[/C][/ROW]
[ROW][C]269[/C][C]0.998035[/C][C]0.00392943[/C][C]0.00196472[/C][/ROW]
[ROW][C]270[/C][C]0.995169[/C][C]0.00966112[/C][C]0.00483056[/C][/ROW]
[ROW][C]271[/C][C]0.999939[/C][C]0.000122429[/C][C]6.12146e-05[/C][/ROW]
[ROW][C]272[/C][C]0.999307[/C][C]0.00138556[/C][C]0.000692779[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265691&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265691&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.8512570.2974870.148743
70.9563250.08735020.0436751
80.933110.1337810.0668903
90.8917080.2165840.108292
100.9195720.1608550.0804276
110.8758850.248230.124115
120.9017410.1965190.0982593
130.8572220.2855560.142778
140.8079560.3840890.192044
150.7759430.4481150.224057
160.7310230.5379530.268977
170.6923680.6152650.307632
180.6344930.7310150.365507
190.6000840.7998310.399916
200.5327370.9345260.467263
210.7259820.5480360.274018
220.7133240.5733510.286676
230.6603260.6793470.339674
240.6655010.6689980.334499
250.61810.7638010.3819
260.5809980.8380050.419002
270.6307450.738510.369255
280.643660.712680.35634
290.5963260.8073470.403674
300.545070.9098590.45493
310.5327060.9345870.467294
320.4861780.9723570.513822
330.4475540.8951080.552446
340.4474910.8949810.552509
350.3995040.7990090.600496
360.3545380.7090770.645462
370.3084270.6168550.691573
380.2835090.5670180.716491
390.2962660.5925320.703734
400.260830.521660.73917
410.4081050.8162110.591895
420.3664530.7329050.633547
430.3546920.7093830.645308
440.3132620.6265250.686738
450.3011220.6022440.698878
460.2658030.5316050.734197
470.2362410.4724810.763759
480.2982870.5965730.701713
490.341330.6826590.65867
500.3197330.6394650.680267
510.282680.5653590.71732
520.3352860.6705710.664714
530.3000420.6000850.699958
540.2844580.5689170.715542
550.2950960.5901920.704904
560.2645210.5290420.735479
570.418270.8365410.58173
580.4979140.9958270.502086
590.459410.918820.54059
600.4917290.9834570.508271
610.4774620.9549240.522538
620.4467150.893430.553285
630.4903340.9806680.509666
640.5545580.8908830.445442
650.5367640.9264720.463236
660.5039630.9920750.496037
670.4908170.9816350.509183
680.460760.921520.53924
690.4602490.9204990.539751
700.4392210.8784430.560779
710.4070330.8140650.592967
720.3745130.7490250.625487
730.3493590.6987180.650641
740.3780780.7561560.621922
750.3592130.7184250.640787
760.3364390.6728780.663561
770.3248160.6496310.675184
780.3103130.6206270.689687
790.2881570.5763140.711843
800.3402870.6805730.659713
810.3107230.6214460.689277
820.3322980.6645960.667702
830.3037480.6074970.696252
840.4257540.8515070.574246
850.4075360.8150720.592464
860.3787360.7574730.621264
870.3488860.6977730.651114
880.31850.6370010.6815
890.316270.632540.68373
900.3317350.663470.668265
910.3451230.6902460.654877
920.4982110.9964230.501789
930.4705570.9411140.529443
940.4714330.9428660.528567
950.5351040.9297910.464896
960.5180530.9638940.481947
970.5521070.8957850.447893
980.5260570.9478850.473943
990.5692620.8614760.430738
1000.6563190.6873630.343681
1010.6297970.7404050.370203
1020.6064020.7871960.393598
1030.601520.7969610.39848
1040.612360.775280.38764
1050.6446910.7106180.355309
1060.6621820.6756370.337818
1070.6665210.6669570.333479
1080.8062490.3875020.193751
1090.8565790.2868430.143421
1100.8547290.2905420.145271
1110.8418930.3162130.158107
1120.8287450.342510.171255
1130.8919790.2160420.108021
1140.8971410.2057170.102859
1150.9050640.1898730.0949365
1160.9153110.1693770.0846887
1170.9052670.1894660.0947329
1180.9121320.1757360.0878679
1190.9067670.1864660.0932332
1200.9191010.1617980.0808989
1210.9126750.1746510.0873253
1220.9351840.1296320.0648161
1230.927110.145780.0728898
1240.9570840.08583190.0429159
1250.9635810.07283710.0364185
1260.9577650.08447090.0422354
1270.9522570.09548630.0477432
1280.9543420.09131520.0456576
1290.9555820.08883580.0444179
1300.9532210.0935580.046779
1310.9493080.1013850.0506924
1320.9420570.1158860.0579432
1330.9385870.1228270.0614135
1340.9288110.1423790.0711894
1350.9206510.1586990.0793493
1360.9106260.1787480.089374
1370.9306850.138630.0693148
1380.9471940.1056110.0528056
1390.938740.122520.0612598
1400.9282930.1434140.0717072
1410.9183910.1632170.0816086
1420.9275140.1449710.0724856
1430.9188030.1623930.0811966
1440.9110570.1778860.0889429
1450.8997420.2005150.100258
1460.8953390.2093210.104661
1470.8844360.2311280.115564
1480.8692380.2615250.130762
1490.8838920.2322170.116108
1500.8735930.2528140.126407
1510.9488060.1023870.0511935
1520.9448260.1103470.0551736
1530.9399760.1200480.0600238
1540.9298780.1402430.0701217
1550.9384310.1231380.0615692
1560.928630.142740.0713698
1570.9268780.1462430.0731215
1580.9239320.1521370.0760683
1590.9134830.1730340.0865171
1600.9003150.1993690.0996847
1610.9315930.1368130.0684067
1620.9192410.1615180.0807591
1630.9096770.1806450.0903226
1640.9497330.1005330.0502667
1650.9586320.08273680.0413684
1660.9535440.09291290.0464565
1670.9498810.1002380.050119
1680.9595080.08098390.040492
1690.9511830.09763370.0488169
1700.9506750.09865030.0493252
1710.9415430.1169130.0584565
1720.9537950.09241030.0462051
1730.9459280.1081440.054072
1740.9367090.1265810.0632906
1750.9264040.1471920.0735961
1760.9318210.1363570.0681787
1770.9228760.1542480.0771239
1780.9180150.163970.0819852
1790.9053630.1892730.0946366
1800.9210660.1578680.0789341
1810.911190.1776190.0888097
1820.8965370.2069270.103463
1830.8871090.2257820.112891
1840.8689830.2620340.131017
1850.8865030.2269930.113497
1860.8717430.2565140.128257
1870.9053040.1893920.0946958
1880.8932520.2134960.106748
1890.8810660.2378680.118934
1900.8615280.2769440.138472
1910.8416480.3167040.158352
1920.8357430.3285150.164257
1930.8289070.3421850.171093
1940.8417360.3165290.158264
1950.8332350.3335290.166765
1960.8168150.3663690.183185
1970.838050.3239010.16195
1980.8133960.3732080.186604
1990.8406510.3186990.159349
2000.8268610.3462780.173139
2010.8097740.3804510.190226
2020.8028670.3942670.197133
2030.7819120.4361760.218088
2040.7526170.4947670.247383
2050.7356040.5287910.264396
2060.7759980.4480050.224002
2070.7724420.4551170.227558
2080.7938620.4122760.206138
2090.7707380.4585240.229262
2100.7497710.5004570.250229
2110.7578650.4842710.242135
2120.7300320.5399370.269968
2130.7461560.5076870.253844
2140.7160720.5678560.283928
2150.6887960.6224070.311204
2160.665380.6692410.33462
2170.6544230.6911550.345577
2180.6365990.7268010.363401
2190.6098330.7803330.390167
2200.5682550.8634890.431745
2210.5267360.9465280.473264
2220.5447390.9105230.455261
2230.5041010.9917990.495899
2240.4650140.9300280.534986
2250.4554160.9108330.544584
2260.4704880.9409760.529512
2270.4375980.8751960.562402
2280.5149010.9701990.485099
2290.5117510.9764980.488249
2300.493840.9876790.50616
2310.4993820.9987640.500618
2320.4722610.9445230.527739
2330.4508110.9016220.549189
2340.4453040.8906090.554696
2350.413140.826280.58686
2360.6083170.7833660.391683
2370.5700290.8599420.429971
2380.6334150.733170.366585
2390.5992940.8014120.400706
2400.5566460.8867090.443354
2410.532520.9349590.46748
2420.5864610.8270780.413539
2430.577240.8455190.42276
2440.6233210.7533590.376679
2450.572950.8541010.42705
2460.5176470.9647060.482353
2470.463680.927360.53632
2480.4109730.8219450.589027
2490.3649520.7299040.635048
2500.335560.671120.66444
2510.3622580.7245150.637742
2520.3862430.7724870.613757
2530.3389990.6779980.661001
2540.3013270.6026550.698673
2550.3357840.6715680.664216
2560.2907310.5814610.709269
2570.2953260.5906520.704674
2580.7792170.4415660.220783
2590.7275980.5448030.272402
2600.9990710.001858260.00092913
2610.9983870.003225930.00161296
2620.9966060.006788740.00339437
2630.9999578.58074e-054.29037e-05
2640.9998660.0002671920.000133596
2650.9996190.0007618520.000380926
2660.9990250.001949780.000974888
2670.9988720.002255510.00112776
2680.9990060.001988950.000994475
2690.9980350.003929430.00196472
2700.9951690.009661120.00483056
2710.9999390.0001224296.12146e-05
2720.9993070.001385560.000692779






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level130.0486891NOK
5% type I error level130.0486891OK
10% type I error level270.101124NOK

\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 & 13 & 0.0486891 & NOK \tabularnewline
5% type I error level & 13 & 0.0486891 & OK \tabularnewline
10% type I error level & 27 & 0.101124 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265691&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]13[/C][C]0.0486891[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]13[/C][C]0.0486891[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]27[/C][C]0.101124[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265691&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265691&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level130.0486891NOK
5% type I error level130.0486891OK
10% type I error level270.101124NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

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