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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 10 Nov 2014 16:41:45 +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/Nov/10/t1415637863brwqmvqgnfldf6c.htm/, Retrieved Sun, 19 May 2024 14:07:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=253397, Retrieved Sun, 19 May 2024 14:07:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [WS6: Vraag1] [2014-11-10 16:41:45] [58179e1d3a5a39b9daf58e365d8a3352] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 13 14 53 38
39 16 18 83 32
30 19 11 66 35
31 15 12 67 33
34 14 16 76 37
35 13 18 78 29
39 19 14 53 31
34 15 14 80 36
36 14 15 74 35
37 15 15 76 38
38 16 17 79 31
36 16 19 54 34
38 16 10 67 35
39 16 16 54 38
33 17 18 87 37
32 15 14 58 33
36 15 14 75 32
38 20 17 88 38
39 18 14 64 38
32 16 16 57 32
32 16 18 66 33
31 16 11 68 31
39 19 14 54 38
37 16 12 56 39
39 17 17 86 32
41 17 9 80 32
36 16 16 76 35
33 15 14 69 37
33 16 15 78 33
34 14 11 67 33
31 15 16 80 31
27 12 13 54 32
37 14 17 71 31
34 16 15 84 37
34 14 14 74 30
32 10 16 71 33
29 10 9 63 31
36 14 15 71 33
29 16 17 76 31
35 16 13 69 33
37 16 15 74 32
34 14 16 75 33
38 20 16 54 32
35 14 12 52 33
38 14 15 69 28
37 11 11 68 35
38 14 15 65 39
33 15 15 75 34
36 16 17 74 38
38 14 13 75 32
32 16 16 72 38
32 14 14 67 30
32 12 11 63 33
34 16 12 62 38
32 9 12 63 32
37 14 15 76 35
39 16 16 74 34
29 16 15 67 34
37 15 12 73 36
35 16 12 70 34
30 12 8 53 28
38 16 13 77 34
34 16 11 80 35
31 14 14 52 35
34 16 15 54 31
35 17 10 80 37
36 18 11 66 35
30 18 12 73 27
39 12 15 63 40
35 16 15 69 37
38 10 14 67 36
31 14 16 54 38
34 18 15 81 39
38 18 15 69 41
34 16 13 84 27
39 17 12 80 30
37 16 17 70 37
34 16 13 69 31
28 13 15 77 31
37 16 13 54 27
33 16 15 79 36
35 16 15 71 37
37 15 16 73 33
32 15 15 72 34
33 16 14 77 31
38 14 15 75 39
33 16 14 69 34
29 16 13 54 32
33 15 7 70 33
31 12 17 73 36
36 17 13 54 32
35 16 15 77 41
32 15 14 82 28
29 13 13 80 30
39 16 16 80 36
37 16 12 69 35
35 16 14 78 31
37 16 17 81 34
32 14 15 76 36
38 16 17 76 36
37 16 12 73 35
36 20 16 85 37
32 15 11 66 28
33 16 15 79 39
40 13 9 68 32
38 17 16 76 35
41 16 15 71 39
36 16 10 54 35
43 12 10 46 42
30 16 15 85 34
31 16 11 74 33
32 17 13 88 41
32 13 14 38 33
37 12 18 76 34
37 18 16 86 32
33 14 14 54 40
34 14 14 67 40
33 13 14 69 35
38 16 14 90 36
33 13 12 54 37
31 16 14 76 27
38 13 15 89 39
37 16 15 76 38
36 15 15 73 31
31 16 13 79 33
39 15 17 90 32
44 17 17 74 39
33 15 19 81 36
35 12 15 72 33
32 16 13 71 33
28 10 9 66 32
40 16 15 77 37
27 12 15 65 30
37 14 15 74 38
32 15 16 85 29
28 13 11 54 22
34 15 14 63 35
30 11 11 54 35
35 12 15 64 34
31 11 13 69 35
32 16 15 54 34
30 15 16 84 37
30 17 14 86 35
31 16 15 77 23
40 10 16 89 31
32 18 16 76 27
36 13 11 60 36
32 16 12 75 31
35 13 9 73 32
38 10 16 85 39
42 15 13 79 37
34 16 16 71 38
35 16 12 72 39
38 14 9 69 34
33 10 13 78 31
36 17 13 54 32
32 13 14 69 37
33 15 19 81 36
34 16 13 84 32
32 12 12 84 38
34 13 13 69 36
27 13 10 66 26
31 12 14 81 26
38 17 16 82 33
34 15 10 72 39
24 10 11 54 30
30 14 14 78 33
26 11 12 74 25
34 13 9 82 38
27 16 9 73 37
37 12 11 55 31
36 16 16 72 37
41 12 9 78 35
29 9 13 59 25
36 12 16 72 28
32 15 13 78 35
37 12 9 68 33
30 12 12 69 30
31 14 16 67 31
38 12 11 74 37
36 16 14 54 36
35 11 13 67 30
31 19 15 70 36
38 15 14 80 32
22 8 16 89 28
32 16 13 76 36
36 17 14 74 34
39 12 15 87 31
28 11 13 54 28
32 11 11 61 36
32 14 11 38 36
38 16 14 75 40
32 12 15 69 33
35 16 11 62 37
32 13 15 72 32
37 15 12 70 38
34 16 14 79 31
33 16 14 87 37
33 14 8 62 33
26 16 13 77 32
30 16 9 69 30
24 14 15 69 30
34 11 17 75 31
34 12 13 54 32
33 15 15 72 34
34 15 15 74 36
35 16 14 85 37
35 16 16 52 36
36 11 13 70 33
34 15 16 84 33
34 12 9 64 33
41 12 16 84 44
32 15 11 87 39
30 15 10 79 32
35 16 11 67 35
28 14 15 65 25
33 17 17 85 35
39 14 14 83 34
36 13 8 61 35
36 15 15 82 39
35 13 11 76 33
38 14 16 58 36
33 15 10 72 32
31 12 15 72 32
34 13 9 38 36
32 8 16 78 36
31 14 19 54 32
33 14 12 63 34
34 11 8 66 33
34 12 11 70 35
34 13 14 71 30
33 10 9 67 38
32 16 15 58 34
41 18 13 72 33
34 13 16 72 32
36 11 11 70 31
37 4 12 76 30
36 13 13 50 27
29 16 10 72 31
37 10 11 72 30
27 12 12 88 32
35 12 8 53 35
28 10 12 58 28
35 13 12 66 33
37 15 15 82 31
29 12 11 69 35
32 14 13 68 35
36 10 14 44 32
19 12 10 56 21
21 12 12 53 20
31 11 15 70 34
33 10 13 78 32
36 12 13 71 34
33 16 13 72 32
37 12 12 68 33
34 14 12 67 33
35 16 9 75 37
31 14 9 62 32
37 13 15 67 34
35 4 10 83 30
27 15 14 64 30
34 11 15 68 38
40 11 7 62 36
29 14 14 72 32

Tables (Output of Computation)





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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253397&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253397&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253397&T=0

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


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

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






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 15.0596 + 0.131127Learning[t] + 0.0747413Happiness[t] + 0.0201308Sport1[t] + 0.43586Separate[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  15.0596 +  0.131127Learning[t] +  0.0747413Happiness[t] +  0.0201308Sport1[t] +  0.43586Separate[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253397&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  15.0596 +  0.131127Learning[t] +  0.0747413Happiness[t] +  0.0201308Sport1[t] +  0.43586Separate[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253397&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253397&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
Connected[t] = + 15.0596 + 0.131127Learning[t] + 0.0747413Happiness[t] + 0.0201308Sport1[t] + 0.43586Separate[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.05962.403476.2661.53856e-097.69282e-10
Learning0.1311270.08940681.4670.143690.0718449
Happiness0.07474130.08906540.83920.4021460.201073
Sport10.02013080.02096860.960.337930.168965
Separate0.435860.0577477.5487.55156e-133.77578e-13

\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) & 15.0596 & 2.40347 & 6.266 & 1.53856e-09 & 7.69282e-10 \tabularnewline
Learning & 0.131127 & 0.0894068 & 1.467 & 0.14369 & 0.0718449 \tabularnewline
Happiness & 0.0747413 & 0.0890654 & 0.8392 & 0.402146 & 0.201073 \tabularnewline
Sport1 & 0.0201308 & 0.0209686 & 0.96 & 0.33793 & 0.168965 \tabularnewline
Separate & 0.43586 & 0.057747 & 7.548 & 7.55156e-13 & 3.77578e-13 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253397&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]15.0596[/C][C]2.40347[/C][C]6.266[/C][C]1.53856e-09[/C][C]7.69282e-10[/C][/ROW]
[ROW][C]Learning[/C][C]0.131127[/C][C]0.0894068[/C][C]1.467[/C][C]0.14369[/C][C]0.0718449[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0747413[/C][C]0.0890654[/C][C]0.8392[/C][C]0.402146[/C][C]0.201073[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0201308[/C][C]0.0209686[/C][C]0.96[/C][C]0.33793[/C][C]0.168965[/C][/ROW]
[ROW][C]Separate[/C][C]0.43586[/C][C]0.057747[/C][C]7.548[/C][C]7.55156e-13[/C][C]3.77578e-13[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253397&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253397&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)15.05962.403476.2661.53856e-097.69282e-10
Learning0.1311270.08940681.4670.143690.0718449
Happiness0.07474130.08906540.83920.4021460.201073
Sport10.02013080.02096860.960.337930.168965
Separate0.435860.0577477.5487.55156e-133.77578e-13






Multiple Linear Regression - Regression Statistics
Multiple R0.473085
R-squared0.22381
Adjusted R-squared0.211822
F-TEST (value)18.6703
F-TEST (DF numerator)4
F-TEST (DF denominator)259
p-value1.68976e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.37049
Sum Squared Residuals2942.3

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.473085 \tabularnewline
R-squared & 0.22381 \tabularnewline
Adjusted R-squared & 0.211822 \tabularnewline
F-TEST (value) & 18.6703 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 259 \tabularnewline
p-value & 1.68976e-13 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.37049 \tabularnewline
Sum Squared Residuals & 2942.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253397&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.473085[/C][/ROW]
[ROW][C]R-squared[/C][C]0.22381[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.211822[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]18.6703[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]259[/C][/ROW]
[ROW][C]p-value[/C][C]1.68976e-13[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.37049[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2942.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253397&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253397&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 R0.473085
R-squared0.22381
Adjusted R-squared0.211822
F-TEST (value)18.6703
F-TEST (DF numerator)4
F-TEST (DF denominator)259
p-value1.68976e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.37049
Sum Squared Residuals2942.3






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14135.44035.55973
23934.12144.87863
33034.9569-4.95692
43133.6556-2.65557
53435.748-1.74802
63532.31982.68024
73933.1765.824
83435.3743-1.37433
93634.76131.2387
103736.24030.759731
113833.53024.46975
123634.4841.51596
133834.50893.49107
143936.00332.99674
153336.5123-3.51232
163233.6239-1.62387
173633.53022.46977
183837.2870.713046
193936.31732.68266
203233.4485-1.44849
213234.215-2.21501
223132.8604-1.86036
233936.24722.75284
243736.18040.819583
253934.23824.76185
264133.51947.48056
273635.13860.861444
283335.5888-2.58875
293334.2324-1.23236
303433.44970.550302
313133.3445-2.34451
322732.6394-5.63937
333733.10693.89305
343436.0966-2.09658
353432.50731.49274
363233.3794-1.37942
372931.8235-2.82346
383633.82922.17081
392933.4699-4.46986
403533.90171.0983
413733.7163.28403
423433.98450.0155493
433833.91264.08739
443533.22251.77752
453831.60966.39038
463733.94823.05183
473836.32361.67644
483334.4767-1.4767
493636.4806-0.480617
503833.32444.67563
513236.3656-4.36561
523232.3663-0.366341
533233.1069-1.10692
543435.8653-1.86534
553232.3524-0.352422
563734.80162.19844
573934.66244.33757
582934.4468-5.44678
593735.08391.91607
603534.28290.717054
613030.5021-0.502088
623834.49863.5014
633434.8454-0.845372
643134.2437-3.24368
653432.87751.1225
663535.7735-0.773478
673634.82581.1742
683031.5546-1.55457
693936.45692.54309
703535.7946-0.79462
713834.4573.543
723135.741-4.74101
733437.1702-3.17016
743837.80030.199685
753431.58852.4115
763932.87196.12806
773735.96421.03577
783433.030.970025
792832.9471-4.94712
803730.98466.01543
813335.5601-2.56007
823535.8349-0.834881
833734.07532.92468
843234.4163-2.4163
853333.2658-0.265762
863836.52491.47513
873334.4123-1.4123
882933.1639-4.16387
893333.3423-0.342252
903135.0643-4.06426
913633.2952.705
923537.6991-2.69911
933231.92770.0722916
942932.4222-3.42217
953935.65493.34506
963734.69872.30132
973533.28591.71411
983734.87812.12191
993235.2374-3.23742
1003835.64922.35084
1013734.77922.2208
1023636.716-0.71596
1033231.38140.618608
1043336.8676-3.86765
1054032.75347.24664
1063835.26972.73032
1074136.70664.2934
1083634.24721.75277
1094336.61276.3873
1103034.8091-4.80913
1113133.8529-2.85287
1123237.9022-5.90219
1133232.959-0.959003
1143734.32772.67233
1153734.29452.70546
1163336.4632-3.46324
1173436.7249-2.72494
1183334.4548-1.45478
1193835.70682.29324
1203334.8751-1.87505
1213131.5022-0.50219
1223836.67561.32442
1233736.37140.628605
1243633.12892.87115
1253134.103-3.103
1263934.05644.94358
1274437.04766.9524
1283335.7682-2.76817
1293533.58711.41294
1303233.942-1.94196
1312832.3197-4.31972
1324035.95574.04433
1332732.1386-5.13857
1343736.06890.93112
1353232.5734-0.573444
1362828.2624-0.262408
1373434.5962-0.596246
1383033.6663-3.66634
1393533.86191.13812
1403134.1178-3.11778
1413234.1851-2.18508
1423036.0402-6.0402
1433035.3215-5.32151
1443129.85361.14638
1454032.87017.12995
1463231.91390.0860736
1473634.48521.51476
1483233.076-1.07602
1493532.8542.14599
1503836.27641.72359
1514235.71536.28468
1523436.3455-2.34548
1533536.5025-1.50251
1543833.77634.22366
1553332.42440.575609
1563633.2952.705
1573235.3265-3.3265
1583335.7682-2.76817
1593433.76780.232203
1603235.7837-3.78371
1613434.8159-0.815896
1622730.1727-3.17268
1633130.64250.357523
1643834.51873.48125
1653436.2219-2.2219
1662431.3559-7.35591
1673033.8954-3.89536
1682629.7851-3.78509
1693435.6504-1.65035
1702735.4267-8.42669
1713732.07424.92585
1723635.92980.0702466
1734134.13116.86888
1742929.2956-0.295618
1753631.48254.5175
1763234.8235-2.82347
1773733.05813.94191
1783031.9949-1.99487
1793132.9517-1.95168
1803835.07182.9282
1813634.98211.01794
1823531.89823.10178
1833135.7723-4.77227
1843833.63094.36911
1852231.3002-9.30022
1863235.3502-3.35019
1873634.64411.35592
1883933.01735.9827
1892830.7648-2.7648
1903234.2431-2.24311
1913234.1735-2.17349
1923837.14820.851756
1933233.5267-1.52667
1943535.3547-0.354739
1953233.2823-1.28233
1963735.89531.10474
1973433.3060.693976
1983336.0822-3.08223
1993333.1248-0.12482
2002633.6269-7.62688
2013032.2951-2.29515
2022432.4813-8.48134
2033432.79411.20591
2043432.63941.36063
2053334.4163-1.4163
2063435.3283-1.32829
2073536.042-1.04197
2083535.0913-0.0912778
2093633.26622.73381
2103434.2968-0.296754
2113432.97761.02243
2124138.69782.30216
2133236.5986-4.5986
2143033.3118-3.31179
2153534.58370.416328
2162830.2215-2.22152
2173335.5256-2.5256
2183934.43194.56813
2193633.84532.15472
2203636.7969-0.796914
2213533.49971.50025
2223834.94983.05019
2233333.1709-0.170877
2243133.1512-2.1512
2253433.89290.107122
2263234.5657-2.56566
2273133.3501-2.35007
2283333.8798-0.879777
2293432.8121.18804
2303434.1196-0.119557
2313432.31571.68426
2323334.955-1.95501
2333234.2656-2.2656
2344134.22436.77566
2353433.35710.642929
2363632.2453.75501
2373731.08685.91323
2383630.51075.48933
2392932.8661-3.86614
2403731.71835.28174
2412733.2491-6.24907
2423533.55311.44689
2432830.6395-2.63945
2443533.37321.62682
2453733.313.68997
2462934.0994-5.09943
2473234.491-2.49103
2483632.25053.74945
2491927.6609-8.66094
2502127.3142-6.31417
2513133.8515-2.85154
2523332.86030.139748
2533633.85332.14669
2543333.5262-0.526228
2553733.28233.71768
2563433.52440.475561
2573535.467-0.466957
2583132.7637-1.7637
2593734.05342.9466
2603531.07823.9218
2612732.4371-5.43708
2623435.5547-1.55472
2634033.96436.03572
2642933.3387-4.33872

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 35.4403 & 5.55973 \tabularnewline
2 & 39 & 34.1214 & 4.87863 \tabularnewline
3 & 30 & 34.9569 & -4.95692 \tabularnewline
4 & 31 & 33.6556 & -2.65557 \tabularnewline
5 & 34 & 35.748 & -1.74802 \tabularnewline
6 & 35 & 32.3198 & 2.68024 \tabularnewline
7 & 39 & 33.176 & 5.824 \tabularnewline
8 & 34 & 35.3743 & -1.37433 \tabularnewline
9 & 36 & 34.7613 & 1.2387 \tabularnewline
10 & 37 & 36.2403 & 0.759731 \tabularnewline
11 & 38 & 33.5302 & 4.46975 \tabularnewline
12 & 36 & 34.484 & 1.51596 \tabularnewline
13 & 38 & 34.5089 & 3.49107 \tabularnewline
14 & 39 & 36.0033 & 2.99674 \tabularnewline
15 & 33 & 36.5123 & -3.51232 \tabularnewline
16 & 32 & 33.6239 & -1.62387 \tabularnewline
17 & 36 & 33.5302 & 2.46977 \tabularnewline
18 & 38 & 37.287 & 0.713046 \tabularnewline
19 & 39 & 36.3173 & 2.68266 \tabularnewline
20 & 32 & 33.4485 & -1.44849 \tabularnewline
21 & 32 & 34.215 & -2.21501 \tabularnewline
22 & 31 & 32.8604 & -1.86036 \tabularnewline
23 & 39 & 36.2472 & 2.75284 \tabularnewline
24 & 37 & 36.1804 & 0.819583 \tabularnewline
25 & 39 & 34.2382 & 4.76185 \tabularnewline
26 & 41 & 33.5194 & 7.48056 \tabularnewline
27 & 36 & 35.1386 & 0.861444 \tabularnewline
28 & 33 & 35.5888 & -2.58875 \tabularnewline
29 & 33 & 34.2324 & -1.23236 \tabularnewline
30 & 34 & 33.4497 & 0.550302 \tabularnewline
31 & 31 & 33.3445 & -2.34451 \tabularnewline
32 & 27 & 32.6394 & -5.63937 \tabularnewline
33 & 37 & 33.1069 & 3.89305 \tabularnewline
34 & 34 & 36.0966 & -2.09658 \tabularnewline
35 & 34 & 32.5073 & 1.49274 \tabularnewline
36 & 32 & 33.3794 & -1.37942 \tabularnewline
37 & 29 & 31.8235 & -2.82346 \tabularnewline
38 & 36 & 33.8292 & 2.17081 \tabularnewline
39 & 29 & 33.4699 & -4.46986 \tabularnewline
40 & 35 & 33.9017 & 1.0983 \tabularnewline
41 & 37 & 33.716 & 3.28403 \tabularnewline
42 & 34 & 33.9845 & 0.0155493 \tabularnewline
43 & 38 & 33.9126 & 4.08739 \tabularnewline
44 & 35 & 33.2225 & 1.77752 \tabularnewline
45 & 38 & 31.6096 & 6.39038 \tabularnewline
46 & 37 & 33.9482 & 3.05183 \tabularnewline
47 & 38 & 36.3236 & 1.67644 \tabularnewline
48 & 33 & 34.4767 & -1.4767 \tabularnewline
49 & 36 & 36.4806 & -0.480617 \tabularnewline
50 & 38 & 33.3244 & 4.67563 \tabularnewline
51 & 32 & 36.3656 & -4.36561 \tabularnewline
52 & 32 & 32.3663 & -0.366341 \tabularnewline
53 & 32 & 33.1069 & -1.10692 \tabularnewline
54 & 34 & 35.8653 & -1.86534 \tabularnewline
55 & 32 & 32.3524 & -0.352422 \tabularnewline
56 & 37 & 34.8016 & 2.19844 \tabularnewline
57 & 39 & 34.6624 & 4.33757 \tabularnewline
58 & 29 & 34.4468 & -5.44678 \tabularnewline
59 & 37 & 35.0839 & 1.91607 \tabularnewline
60 & 35 & 34.2829 & 0.717054 \tabularnewline
61 & 30 & 30.5021 & -0.502088 \tabularnewline
62 & 38 & 34.4986 & 3.5014 \tabularnewline
63 & 34 & 34.8454 & -0.845372 \tabularnewline
64 & 31 & 34.2437 & -3.24368 \tabularnewline
65 & 34 & 32.8775 & 1.1225 \tabularnewline
66 & 35 & 35.7735 & -0.773478 \tabularnewline
67 & 36 & 34.8258 & 1.1742 \tabularnewline
68 & 30 & 31.5546 & -1.55457 \tabularnewline
69 & 39 & 36.4569 & 2.54309 \tabularnewline
70 & 35 & 35.7946 & -0.79462 \tabularnewline
71 & 38 & 34.457 & 3.543 \tabularnewline
72 & 31 & 35.741 & -4.74101 \tabularnewline
73 & 34 & 37.1702 & -3.17016 \tabularnewline
74 & 38 & 37.8003 & 0.199685 \tabularnewline
75 & 34 & 31.5885 & 2.4115 \tabularnewline
76 & 39 & 32.8719 & 6.12806 \tabularnewline
77 & 37 & 35.9642 & 1.03577 \tabularnewline
78 & 34 & 33.03 & 0.970025 \tabularnewline
79 & 28 & 32.9471 & -4.94712 \tabularnewline
80 & 37 & 30.9846 & 6.01543 \tabularnewline
81 & 33 & 35.5601 & -2.56007 \tabularnewline
82 & 35 & 35.8349 & -0.834881 \tabularnewline
83 & 37 & 34.0753 & 2.92468 \tabularnewline
84 & 32 & 34.4163 & -2.4163 \tabularnewline
85 & 33 & 33.2658 & -0.265762 \tabularnewline
86 & 38 & 36.5249 & 1.47513 \tabularnewline
87 & 33 & 34.4123 & -1.4123 \tabularnewline
88 & 29 & 33.1639 & -4.16387 \tabularnewline
89 & 33 & 33.3423 & -0.342252 \tabularnewline
90 & 31 & 35.0643 & -4.06426 \tabularnewline
91 & 36 & 33.295 & 2.705 \tabularnewline
92 & 35 & 37.6991 & -2.69911 \tabularnewline
93 & 32 & 31.9277 & 0.0722916 \tabularnewline
94 & 29 & 32.4222 & -3.42217 \tabularnewline
95 & 39 & 35.6549 & 3.34506 \tabularnewline
96 & 37 & 34.6987 & 2.30132 \tabularnewline
97 & 35 & 33.2859 & 1.71411 \tabularnewline
98 & 37 & 34.8781 & 2.12191 \tabularnewline
99 & 32 & 35.2374 & -3.23742 \tabularnewline
100 & 38 & 35.6492 & 2.35084 \tabularnewline
101 & 37 & 34.7792 & 2.2208 \tabularnewline
102 & 36 & 36.716 & -0.71596 \tabularnewline
103 & 32 & 31.3814 & 0.618608 \tabularnewline
104 & 33 & 36.8676 & -3.86765 \tabularnewline
105 & 40 & 32.7534 & 7.24664 \tabularnewline
106 & 38 & 35.2697 & 2.73032 \tabularnewline
107 & 41 & 36.7066 & 4.2934 \tabularnewline
108 & 36 & 34.2472 & 1.75277 \tabularnewline
109 & 43 & 36.6127 & 6.3873 \tabularnewline
110 & 30 & 34.8091 & -4.80913 \tabularnewline
111 & 31 & 33.8529 & -2.85287 \tabularnewline
112 & 32 & 37.9022 & -5.90219 \tabularnewline
113 & 32 & 32.959 & -0.959003 \tabularnewline
114 & 37 & 34.3277 & 2.67233 \tabularnewline
115 & 37 & 34.2945 & 2.70546 \tabularnewline
116 & 33 & 36.4632 & -3.46324 \tabularnewline
117 & 34 & 36.7249 & -2.72494 \tabularnewline
118 & 33 & 34.4548 & -1.45478 \tabularnewline
119 & 38 & 35.7068 & 2.29324 \tabularnewline
120 & 33 & 34.8751 & -1.87505 \tabularnewline
121 & 31 & 31.5022 & -0.50219 \tabularnewline
122 & 38 & 36.6756 & 1.32442 \tabularnewline
123 & 37 & 36.3714 & 0.628605 \tabularnewline
124 & 36 & 33.1289 & 2.87115 \tabularnewline
125 & 31 & 34.103 & -3.103 \tabularnewline
126 & 39 & 34.0564 & 4.94358 \tabularnewline
127 & 44 & 37.0476 & 6.9524 \tabularnewline
128 & 33 & 35.7682 & -2.76817 \tabularnewline
129 & 35 & 33.5871 & 1.41294 \tabularnewline
130 & 32 & 33.942 & -1.94196 \tabularnewline
131 & 28 & 32.3197 & -4.31972 \tabularnewline
132 & 40 & 35.9557 & 4.04433 \tabularnewline
133 & 27 & 32.1386 & -5.13857 \tabularnewline
134 & 37 & 36.0689 & 0.93112 \tabularnewline
135 & 32 & 32.5734 & -0.573444 \tabularnewline
136 & 28 & 28.2624 & -0.262408 \tabularnewline
137 & 34 & 34.5962 & -0.596246 \tabularnewline
138 & 30 & 33.6663 & -3.66634 \tabularnewline
139 & 35 & 33.8619 & 1.13812 \tabularnewline
140 & 31 & 34.1178 & -3.11778 \tabularnewline
141 & 32 & 34.1851 & -2.18508 \tabularnewline
142 & 30 & 36.0402 & -6.0402 \tabularnewline
143 & 30 & 35.3215 & -5.32151 \tabularnewline
144 & 31 & 29.8536 & 1.14638 \tabularnewline
145 & 40 & 32.8701 & 7.12995 \tabularnewline
146 & 32 & 31.9139 & 0.0860736 \tabularnewline
147 & 36 & 34.4852 & 1.51476 \tabularnewline
148 & 32 & 33.076 & -1.07602 \tabularnewline
149 & 35 & 32.854 & 2.14599 \tabularnewline
150 & 38 & 36.2764 & 1.72359 \tabularnewline
151 & 42 & 35.7153 & 6.28468 \tabularnewline
152 & 34 & 36.3455 & -2.34548 \tabularnewline
153 & 35 & 36.5025 & -1.50251 \tabularnewline
154 & 38 & 33.7763 & 4.22366 \tabularnewline
155 & 33 & 32.4244 & 0.575609 \tabularnewline
156 & 36 & 33.295 & 2.705 \tabularnewline
157 & 32 & 35.3265 & -3.3265 \tabularnewline
158 & 33 & 35.7682 & -2.76817 \tabularnewline
159 & 34 & 33.7678 & 0.232203 \tabularnewline
160 & 32 & 35.7837 & -3.78371 \tabularnewline
161 & 34 & 34.8159 & -0.815896 \tabularnewline
162 & 27 & 30.1727 & -3.17268 \tabularnewline
163 & 31 & 30.6425 & 0.357523 \tabularnewline
164 & 38 & 34.5187 & 3.48125 \tabularnewline
165 & 34 & 36.2219 & -2.2219 \tabularnewline
166 & 24 & 31.3559 & -7.35591 \tabularnewline
167 & 30 & 33.8954 & -3.89536 \tabularnewline
168 & 26 & 29.7851 & -3.78509 \tabularnewline
169 & 34 & 35.6504 & -1.65035 \tabularnewline
170 & 27 & 35.4267 & -8.42669 \tabularnewline
171 & 37 & 32.0742 & 4.92585 \tabularnewline
172 & 36 & 35.9298 & 0.0702466 \tabularnewline
173 & 41 & 34.1311 & 6.86888 \tabularnewline
174 & 29 & 29.2956 & -0.295618 \tabularnewline
175 & 36 & 31.4825 & 4.5175 \tabularnewline
176 & 32 & 34.8235 & -2.82347 \tabularnewline
177 & 37 & 33.0581 & 3.94191 \tabularnewline
178 & 30 & 31.9949 & -1.99487 \tabularnewline
179 & 31 & 32.9517 & -1.95168 \tabularnewline
180 & 38 & 35.0718 & 2.9282 \tabularnewline
181 & 36 & 34.9821 & 1.01794 \tabularnewline
182 & 35 & 31.8982 & 3.10178 \tabularnewline
183 & 31 & 35.7723 & -4.77227 \tabularnewline
184 & 38 & 33.6309 & 4.36911 \tabularnewline
185 & 22 & 31.3002 & -9.30022 \tabularnewline
186 & 32 & 35.3502 & -3.35019 \tabularnewline
187 & 36 & 34.6441 & 1.35592 \tabularnewline
188 & 39 & 33.0173 & 5.9827 \tabularnewline
189 & 28 & 30.7648 & -2.7648 \tabularnewline
190 & 32 & 34.2431 & -2.24311 \tabularnewline
191 & 32 & 34.1735 & -2.17349 \tabularnewline
192 & 38 & 37.1482 & 0.851756 \tabularnewline
193 & 32 & 33.5267 & -1.52667 \tabularnewline
194 & 35 & 35.3547 & -0.354739 \tabularnewline
195 & 32 & 33.2823 & -1.28233 \tabularnewline
196 & 37 & 35.8953 & 1.10474 \tabularnewline
197 & 34 & 33.306 & 0.693976 \tabularnewline
198 & 33 & 36.0822 & -3.08223 \tabularnewline
199 & 33 & 33.1248 & -0.12482 \tabularnewline
200 & 26 & 33.6269 & -7.62688 \tabularnewline
201 & 30 & 32.2951 & -2.29515 \tabularnewline
202 & 24 & 32.4813 & -8.48134 \tabularnewline
203 & 34 & 32.7941 & 1.20591 \tabularnewline
204 & 34 & 32.6394 & 1.36063 \tabularnewline
205 & 33 & 34.4163 & -1.4163 \tabularnewline
206 & 34 & 35.3283 & -1.32829 \tabularnewline
207 & 35 & 36.042 & -1.04197 \tabularnewline
208 & 35 & 35.0913 & -0.0912778 \tabularnewline
209 & 36 & 33.2662 & 2.73381 \tabularnewline
210 & 34 & 34.2968 & -0.296754 \tabularnewline
211 & 34 & 32.9776 & 1.02243 \tabularnewline
212 & 41 & 38.6978 & 2.30216 \tabularnewline
213 & 32 & 36.5986 & -4.5986 \tabularnewline
214 & 30 & 33.3118 & -3.31179 \tabularnewline
215 & 35 & 34.5837 & 0.416328 \tabularnewline
216 & 28 & 30.2215 & -2.22152 \tabularnewline
217 & 33 & 35.5256 & -2.5256 \tabularnewline
218 & 39 & 34.4319 & 4.56813 \tabularnewline
219 & 36 & 33.8453 & 2.15472 \tabularnewline
220 & 36 & 36.7969 & -0.796914 \tabularnewline
221 & 35 & 33.4997 & 1.50025 \tabularnewline
222 & 38 & 34.9498 & 3.05019 \tabularnewline
223 & 33 & 33.1709 & -0.170877 \tabularnewline
224 & 31 & 33.1512 & -2.1512 \tabularnewline
225 & 34 & 33.8929 & 0.107122 \tabularnewline
226 & 32 & 34.5657 & -2.56566 \tabularnewline
227 & 31 & 33.3501 & -2.35007 \tabularnewline
228 & 33 & 33.8798 & -0.879777 \tabularnewline
229 & 34 & 32.812 & 1.18804 \tabularnewline
230 & 34 & 34.1196 & -0.119557 \tabularnewline
231 & 34 & 32.3157 & 1.68426 \tabularnewline
232 & 33 & 34.955 & -1.95501 \tabularnewline
233 & 32 & 34.2656 & -2.2656 \tabularnewline
234 & 41 & 34.2243 & 6.77566 \tabularnewline
235 & 34 & 33.3571 & 0.642929 \tabularnewline
236 & 36 & 32.245 & 3.75501 \tabularnewline
237 & 37 & 31.0868 & 5.91323 \tabularnewline
238 & 36 & 30.5107 & 5.48933 \tabularnewline
239 & 29 & 32.8661 & -3.86614 \tabularnewline
240 & 37 & 31.7183 & 5.28174 \tabularnewline
241 & 27 & 33.2491 & -6.24907 \tabularnewline
242 & 35 & 33.5531 & 1.44689 \tabularnewline
243 & 28 & 30.6395 & -2.63945 \tabularnewline
244 & 35 & 33.3732 & 1.62682 \tabularnewline
245 & 37 & 33.31 & 3.68997 \tabularnewline
246 & 29 & 34.0994 & -5.09943 \tabularnewline
247 & 32 & 34.491 & -2.49103 \tabularnewline
248 & 36 & 32.2505 & 3.74945 \tabularnewline
249 & 19 & 27.6609 & -8.66094 \tabularnewline
250 & 21 & 27.3142 & -6.31417 \tabularnewline
251 & 31 & 33.8515 & -2.85154 \tabularnewline
252 & 33 & 32.8603 & 0.139748 \tabularnewline
253 & 36 & 33.8533 & 2.14669 \tabularnewline
254 & 33 & 33.5262 & -0.526228 \tabularnewline
255 & 37 & 33.2823 & 3.71768 \tabularnewline
256 & 34 & 33.5244 & 0.475561 \tabularnewline
257 & 35 & 35.467 & -0.466957 \tabularnewline
258 & 31 & 32.7637 & -1.7637 \tabularnewline
259 & 37 & 34.0534 & 2.9466 \tabularnewline
260 & 35 & 31.0782 & 3.9218 \tabularnewline
261 & 27 & 32.4371 & -5.43708 \tabularnewline
262 & 34 & 35.5547 & -1.55472 \tabularnewline
263 & 40 & 33.9643 & 6.03572 \tabularnewline
264 & 29 & 33.3387 & -4.33872 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253397&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]41[/C][C]35.4403[/C][C]5.55973[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]34.1214[/C][C]4.87863[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]34.9569[/C][C]-4.95692[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]33.6556[/C][C]-2.65557[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]35.748[/C][C]-1.74802[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]32.3198[/C][C]2.68024[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]33.176[/C][C]5.824[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]35.3743[/C][C]-1.37433[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]34.7613[/C][C]1.2387[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]36.2403[/C][C]0.759731[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]33.5302[/C][C]4.46975[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]34.484[/C][C]1.51596[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]34.5089[/C][C]3.49107[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]36.0033[/C][C]2.99674[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]36.5123[/C][C]-3.51232[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]33.6239[/C][C]-1.62387[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]33.5302[/C][C]2.46977[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]37.287[/C][C]0.713046[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]36.3173[/C][C]2.68266[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.4485[/C][C]-1.44849[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.215[/C][C]-2.21501[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]32.8604[/C][C]-1.86036[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]36.2472[/C][C]2.75284[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]36.1804[/C][C]0.819583[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]34.2382[/C][C]4.76185[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]33.5194[/C][C]7.48056[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]35.1386[/C][C]0.861444[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]35.5888[/C][C]-2.58875[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]34.2324[/C][C]-1.23236[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]33.4497[/C][C]0.550302[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]33.3445[/C][C]-2.34451[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]32.6394[/C][C]-5.63937[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]33.1069[/C][C]3.89305[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]36.0966[/C][C]-2.09658[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]32.5073[/C][C]1.49274[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]33.3794[/C][C]-1.37942[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]31.8235[/C][C]-2.82346[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]33.8292[/C][C]2.17081[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]33.4699[/C][C]-4.46986[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]33.9017[/C][C]1.0983[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]33.716[/C][C]3.28403[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]33.9845[/C][C]0.0155493[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]33.9126[/C][C]4.08739[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]33.2225[/C][C]1.77752[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]31.6096[/C][C]6.39038[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]33.9482[/C][C]3.05183[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]36.3236[/C][C]1.67644[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]34.4767[/C][C]-1.4767[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]36.4806[/C][C]-0.480617[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]33.3244[/C][C]4.67563[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]36.3656[/C][C]-4.36561[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.3663[/C][C]-0.366341[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]33.1069[/C][C]-1.10692[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]35.8653[/C][C]-1.86534[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]32.3524[/C][C]-0.352422[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]34.8016[/C][C]2.19844[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]34.6624[/C][C]4.33757[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]34.4468[/C][C]-5.44678[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]35.0839[/C][C]1.91607[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]34.2829[/C][C]0.717054[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]30.5021[/C][C]-0.502088[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]34.4986[/C][C]3.5014[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]34.8454[/C][C]-0.845372[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]34.2437[/C][C]-3.24368[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]32.8775[/C][C]1.1225[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]35.7735[/C][C]-0.773478[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]34.8258[/C][C]1.1742[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]31.5546[/C][C]-1.55457[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]36.4569[/C][C]2.54309[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]35.7946[/C][C]-0.79462[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]34.457[/C][C]3.543[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]35.741[/C][C]-4.74101[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]37.1702[/C][C]-3.17016[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]37.8003[/C][C]0.199685[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]31.5885[/C][C]2.4115[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.8719[/C][C]6.12806[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.9642[/C][C]1.03577[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]33.03[/C][C]0.970025[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]32.9471[/C][C]-4.94712[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]30.9846[/C][C]6.01543[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]35.5601[/C][C]-2.56007[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]35.8349[/C][C]-0.834881[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]34.0753[/C][C]2.92468[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.4163[/C][C]-2.4163[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]33.2658[/C][C]-0.265762[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]36.5249[/C][C]1.47513[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]34.4123[/C][C]-1.4123[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]33.1639[/C][C]-4.16387[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.3423[/C][C]-0.342252[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]35.0643[/C][C]-4.06426[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]33.295[/C][C]2.705[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]37.6991[/C][C]-2.69911[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.9277[/C][C]0.0722916[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]32.4222[/C][C]-3.42217[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]35.6549[/C][C]3.34506[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.6987[/C][C]2.30132[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]33.2859[/C][C]1.71411[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]34.8781[/C][C]2.12191[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]35.2374[/C][C]-3.23742[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]35.6492[/C][C]2.35084[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]34.7792[/C][C]2.2208[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]36.716[/C][C]-0.71596[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]31.3814[/C][C]0.618608[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]36.8676[/C][C]-3.86765[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]32.7534[/C][C]7.24664[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]35.2697[/C][C]2.73032[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]36.7066[/C][C]4.2934[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]34.2472[/C][C]1.75277[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]36.6127[/C][C]6.3873[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]34.8091[/C][C]-4.80913[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]33.8529[/C][C]-2.85287[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]37.9022[/C][C]-5.90219[/C][/ROW]
[ROW][C]113[/C][C]32[/C][C]32.959[/C][C]-0.959003[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.3277[/C][C]2.67233[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]34.2945[/C][C]2.70546[/C][/ROW]
[ROW][C]116[/C][C]33[/C][C]36.4632[/C][C]-3.46324[/C][/ROW]
[ROW][C]117[/C][C]34[/C][C]36.7249[/C][C]-2.72494[/C][/ROW]
[ROW][C]118[/C][C]33[/C][C]34.4548[/C][C]-1.45478[/C][/ROW]
[ROW][C]119[/C][C]38[/C][C]35.7068[/C][C]2.29324[/C][/ROW]
[ROW][C]120[/C][C]33[/C][C]34.8751[/C][C]-1.87505[/C][/ROW]
[ROW][C]121[/C][C]31[/C][C]31.5022[/C][C]-0.50219[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]36.6756[/C][C]1.32442[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]36.3714[/C][C]0.628605[/C][/ROW]
[ROW][C]124[/C][C]36[/C][C]33.1289[/C][C]2.87115[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]34.103[/C][C]-3.103[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]34.0564[/C][C]4.94358[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]37.0476[/C][C]6.9524[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]35.7682[/C][C]-2.76817[/C][/ROW]
[ROW][C]129[/C][C]35[/C][C]33.5871[/C][C]1.41294[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]33.942[/C][C]-1.94196[/C][/ROW]
[ROW][C]131[/C][C]28[/C][C]32.3197[/C][C]-4.31972[/C][/ROW]
[ROW][C]132[/C][C]40[/C][C]35.9557[/C][C]4.04433[/C][/ROW]
[ROW][C]133[/C][C]27[/C][C]32.1386[/C][C]-5.13857[/C][/ROW]
[ROW][C]134[/C][C]37[/C][C]36.0689[/C][C]0.93112[/C][/ROW]
[ROW][C]135[/C][C]32[/C][C]32.5734[/C][C]-0.573444[/C][/ROW]
[ROW][C]136[/C][C]28[/C][C]28.2624[/C][C]-0.262408[/C][/ROW]
[ROW][C]137[/C][C]34[/C][C]34.5962[/C][C]-0.596246[/C][/ROW]
[ROW][C]138[/C][C]30[/C][C]33.6663[/C][C]-3.66634[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]33.8619[/C][C]1.13812[/C][/ROW]
[ROW][C]140[/C][C]31[/C][C]34.1178[/C][C]-3.11778[/C][/ROW]
[ROW][C]141[/C][C]32[/C][C]34.1851[/C][C]-2.18508[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]36.0402[/C][C]-6.0402[/C][/ROW]
[ROW][C]143[/C][C]30[/C][C]35.3215[/C][C]-5.32151[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]29.8536[/C][C]1.14638[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]32.8701[/C][C]7.12995[/C][/ROW]
[ROW][C]146[/C][C]32[/C][C]31.9139[/C][C]0.0860736[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.4852[/C][C]1.51476[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]33.076[/C][C]-1.07602[/C][/ROW]
[ROW][C]149[/C][C]35[/C][C]32.854[/C][C]2.14599[/C][/ROW]
[ROW][C]150[/C][C]38[/C][C]36.2764[/C][C]1.72359[/C][/ROW]
[ROW][C]151[/C][C]42[/C][C]35.7153[/C][C]6.28468[/C][/ROW]
[ROW][C]152[/C][C]34[/C][C]36.3455[/C][C]-2.34548[/C][/ROW]
[ROW][C]153[/C][C]35[/C][C]36.5025[/C][C]-1.50251[/C][/ROW]
[ROW][C]154[/C][C]38[/C][C]33.7763[/C][C]4.22366[/C][/ROW]
[ROW][C]155[/C][C]33[/C][C]32.4244[/C][C]0.575609[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]33.295[/C][C]2.705[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]35.3265[/C][C]-3.3265[/C][/ROW]
[ROW][C]158[/C][C]33[/C][C]35.7682[/C][C]-2.76817[/C][/ROW]
[ROW][C]159[/C][C]34[/C][C]33.7678[/C][C]0.232203[/C][/ROW]
[ROW][C]160[/C][C]32[/C][C]35.7837[/C][C]-3.78371[/C][/ROW]
[ROW][C]161[/C][C]34[/C][C]34.8159[/C][C]-0.815896[/C][/ROW]
[ROW][C]162[/C][C]27[/C][C]30.1727[/C][C]-3.17268[/C][/ROW]
[ROW][C]163[/C][C]31[/C][C]30.6425[/C][C]0.357523[/C][/ROW]
[ROW][C]164[/C][C]38[/C][C]34.5187[/C][C]3.48125[/C][/ROW]
[ROW][C]165[/C][C]34[/C][C]36.2219[/C][C]-2.2219[/C][/ROW]
[ROW][C]166[/C][C]24[/C][C]31.3559[/C][C]-7.35591[/C][/ROW]
[ROW][C]167[/C][C]30[/C][C]33.8954[/C][C]-3.89536[/C][/ROW]
[ROW][C]168[/C][C]26[/C][C]29.7851[/C][C]-3.78509[/C][/ROW]
[ROW][C]169[/C][C]34[/C][C]35.6504[/C][C]-1.65035[/C][/ROW]
[ROW][C]170[/C][C]27[/C][C]35.4267[/C][C]-8.42669[/C][/ROW]
[ROW][C]171[/C][C]37[/C][C]32.0742[/C][C]4.92585[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]35.9298[/C][C]0.0702466[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]34.1311[/C][C]6.86888[/C][/ROW]
[ROW][C]174[/C][C]29[/C][C]29.2956[/C][C]-0.295618[/C][/ROW]
[ROW][C]175[/C][C]36[/C][C]31.4825[/C][C]4.5175[/C][/ROW]
[ROW][C]176[/C][C]32[/C][C]34.8235[/C][C]-2.82347[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]33.0581[/C][C]3.94191[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.9949[/C][C]-1.99487[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]32.9517[/C][C]-1.95168[/C][/ROW]
[ROW][C]180[/C][C]38[/C][C]35.0718[/C][C]2.9282[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.9821[/C][C]1.01794[/C][/ROW]
[ROW][C]182[/C][C]35[/C][C]31.8982[/C][C]3.10178[/C][/ROW]
[ROW][C]183[/C][C]31[/C][C]35.7723[/C][C]-4.77227[/C][/ROW]
[ROW][C]184[/C][C]38[/C][C]33.6309[/C][C]4.36911[/C][/ROW]
[ROW][C]185[/C][C]22[/C][C]31.3002[/C][C]-9.30022[/C][/ROW]
[ROW][C]186[/C][C]32[/C][C]35.3502[/C][C]-3.35019[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]34.6441[/C][C]1.35592[/C][/ROW]
[ROW][C]188[/C][C]39[/C][C]33.0173[/C][C]5.9827[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.7648[/C][C]-2.7648[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]34.2431[/C][C]-2.24311[/C][/ROW]
[ROW][C]191[/C][C]32[/C][C]34.1735[/C][C]-2.17349[/C][/ROW]
[ROW][C]192[/C][C]38[/C][C]37.1482[/C][C]0.851756[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]33.5267[/C][C]-1.52667[/C][/ROW]
[ROW][C]194[/C][C]35[/C][C]35.3547[/C][C]-0.354739[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]33.2823[/C][C]-1.28233[/C][/ROW]
[ROW][C]196[/C][C]37[/C][C]35.8953[/C][C]1.10474[/C][/ROW]
[ROW][C]197[/C][C]34[/C][C]33.306[/C][C]0.693976[/C][/ROW]
[ROW][C]198[/C][C]33[/C][C]36.0822[/C][C]-3.08223[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]33.1248[/C][C]-0.12482[/C][/ROW]
[ROW][C]200[/C][C]26[/C][C]33.6269[/C][C]-7.62688[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]32.2951[/C][C]-2.29515[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]32.4813[/C][C]-8.48134[/C][/ROW]
[ROW][C]203[/C][C]34[/C][C]32.7941[/C][C]1.20591[/C][/ROW]
[ROW][C]204[/C][C]34[/C][C]32.6394[/C][C]1.36063[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]34.4163[/C][C]-1.4163[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]35.3283[/C][C]-1.32829[/C][/ROW]
[ROW][C]207[/C][C]35[/C][C]36.042[/C][C]-1.04197[/C][/ROW]
[ROW][C]208[/C][C]35[/C][C]35.0913[/C][C]-0.0912778[/C][/ROW]
[ROW][C]209[/C][C]36[/C][C]33.2662[/C][C]2.73381[/C][/ROW]
[ROW][C]210[/C][C]34[/C][C]34.2968[/C][C]-0.296754[/C][/ROW]
[ROW][C]211[/C][C]34[/C][C]32.9776[/C][C]1.02243[/C][/ROW]
[ROW][C]212[/C][C]41[/C][C]38.6978[/C][C]2.30216[/C][/ROW]
[ROW][C]213[/C][C]32[/C][C]36.5986[/C][C]-4.5986[/C][/ROW]
[ROW][C]214[/C][C]30[/C][C]33.3118[/C][C]-3.31179[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]34.5837[/C][C]0.416328[/C][/ROW]
[ROW][C]216[/C][C]28[/C][C]30.2215[/C][C]-2.22152[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]35.5256[/C][C]-2.5256[/C][/ROW]
[ROW][C]218[/C][C]39[/C][C]34.4319[/C][C]4.56813[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]33.8453[/C][C]2.15472[/C][/ROW]
[ROW][C]220[/C][C]36[/C][C]36.7969[/C][C]-0.796914[/C][/ROW]
[ROW][C]221[/C][C]35[/C][C]33.4997[/C][C]1.50025[/C][/ROW]
[ROW][C]222[/C][C]38[/C][C]34.9498[/C][C]3.05019[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]33.1709[/C][C]-0.170877[/C][/ROW]
[ROW][C]224[/C][C]31[/C][C]33.1512[/C][C]-2.1512[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]33.8929[/C][C]0.107122[/C][/ROW]
[ROW][C]226[/C][C]32[/C][C]34.5657[/C][C]-2.56566[/C][/ROW]
[ROW][C]227[/C][C]31[/C][C]33.3501[/C][C]-2.35007[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]33.8798[/C][C]-0.879777[/C][/ROW]
[ROW][C]229[/C][C]34[/C][C]32.812[/C][C]1.18804[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]34.1196[/C][C]-0.119557[/C][/ROW]
[ROW][C]231[/C][C]34[/C][C]32.3157[/C][C]1.68426[/C][/ROW]
[ROW][C]232[/C][C]33[/C][C]34.955[/C][C]-1.95501[/C][/ROW]
[ROW][C]233[/C][C]32[/C][C]34.2656[/C][C]-2.2656[/C][/ROW]
[ROW][C]234[/C][C]41[/C][C]34.2243[/C][C]6.77566[/C][/ROW]
[ROW][C]235[/C][C]34[/C][C]33.3571[/C][C]0.642929[/C][/ROW]
[ROW][C]236[/C][C]36[/C][C]32.245[/C][C]3.75501[/C][/ROW]
[ROW][C]237[/C][C]37[/C][C]31.0868[/C][C]5.91323[/C][/ROW]
[ROW][C]238[/C][C]36[/C][C]30.5107[/C][C]5.48933[/C][/ROW]
[ROW][C]239[/C][C]29[/C][C]32.8661[/C][C]-3.86614[/C][/ROW]
[ROW][C]240[/C][C]37[/C][C]31.7183[/C][C]5.28174[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]33.2491[/C][C]-6.24907[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.5531[/C][C]1.44689[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]30.6395[/C][C]-2.63945[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]33.3732[/C][C]1.62682[/C][/ROW]
[ROW][C]245[/C][C]37[/C][C]33.31[/C][C]3.68997[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]34.0994[/C][C]-5.09943[/C][/ROW]
[ROW][C]247[/C][C]32[/C][C]34.491[/C][C]-2.49103[/C][/ROW]
[ROW][C]248[/C][C]36[/C][C]32.2505[/C][C]3.74945[/C][/ROW]
[ROW][C]249[/C][C]19[/C][C]27.6609[/C][C]-8.66094[/C][/ROW]
[ROW][C]250[/C][C]21[/C][C]27.3142[/C][C]-6.31417[/C][/ROW]
[ROW][C]251[/C][C]31[/C][C]33.8515[/C][C]-2.85154[/C][/ROW]
[ROW][C]252[/C][C]33[/C][C]32.8603[/C][C]0.139748[/C][/ROW]
[ROW][C]253[/C][C]36[/C][C]33.8533[/C][C]2.14669[/C][/ROW]
[ROW][C]254[/C][C]33[/C][C]33.5262[/C][C]-0.526228[/C][/ROW]
[ROW][C]255[/C][C]37[/C][C]33.2823[/C][C]3.71768[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]33.5244[/C][C]0.475561[/C][/ROW]
[ROW][C]257[/C][C]35[/C][C]35.467[/C][C]-0.466957[/C][/ROW]
[ROW][C]258[/C][C]31[/C][C]32.7637[/C][C]-1.7637[/C][/ROW]
[ROW][C]259[/C][C]37[/C][C]34.0534[/C][C]2.9466[/C][/ROW]
[ROW][C]260[/C][C]35[/C][C]31.0782[/C][C]3.9218[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]32.4371[/C][C]-5.43708[/C][/ROW]
[ROW][C]262[/C][C]34[/C][C]35.5547[/C][C]-1.55472[/C][/ROW]
[ROW][C]263[/C][C]40[/C][C]33.9643[/C][C]6.03572[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]33.3387[/C][C]-4.33872[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253397&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253397&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
14135.44035.55973
23934.12144.87863
33034.9569-4.95692
43133.6556-2.65557
53435.748-1.74802
63532.31982.68024
73933.1765.824
83435.3743-1.37433
93634.76131.2387
103736.24030.759731
113833.53024.46975
123634.4841.51596
133834.50893.49107
143936.00332.99674
153336.5123-3.51232
163233.6239-1.62387
173633.53022.46977
183837.2870.713046
193936.31732.68266
203233.4485-1.44849
213234.215-2.21501
223132.8604-1.86036
233936.24722.75284
243736.18040.819583
253934.23824.76185
264133.51947.48056
273635.13860.861444
283335.5888-2.58875
293334.2324-1.23236
303433.44970.550302
313133.3445-2.34451
322732.6394-5.63937
333733.10693.89305
343436.0966-2.09658
353432.50731.49274
363233.3794-1.37942
372931.8235-2.82346
383633.82922.17081
392933.4699-4.46986
403533.90171.0983
413733.7163.28403
423433.98450.0155493
433833.91264.08739
443533.22251.77752
453831.60966.39038
463733.94823.05183
473836.32361.67644
483334.4767-1.4767
493636.4806-0.480617
503833.32444.67563
513236.3656-4.36561
523232.3663-0.366341
533233.1069-1.10692
543435.8653-1.86534
553232.3524-0.352422
563734.80162.19844
573934.66244.33757
582934.4468-5.44678
593735.08391.91607
603534.28290.717054
613030.5021-0.502088
623834.49863.5014
633434.8454-0.845372
643134.2437-3.24368
653432.87751.1225
663535.7735-0.773478
673634.82581.1742
683031.5546-1.55457
693936.45692.54309
703535.7946-0.79462
713834.4573.543
723135.741-4.74101
733437.1702-3.17016
743837.80030.199685
753431.58852.4115
763932.87196.12806
773735.96421.03577
783433.030.970025
792832.9471-4.94712
803730.98466.01543
813335.5601-2.56007
823535.8349-0.834881
833734.07532.92468
843234.4163-2.4163
853333.2658-0.265762
863836.52491.47513
873334.4123-1.4123
882933.1639-4.16387
893333.3423-0.342252
903135.0643-4.06426
913633.2952.705
923537.6991-2.69911
933231.92770.0722916
942932.4222-3.42217
953935.65493.34506
963734.69872.30132
973533.28591.71411
983734.87812.12191
993235.2374-3.23742
1003835.64922.35084
1013734.77922.2208
1023636.716-0.71596
1033231.38140.618608
1043336.8676-3.86765
1054032.75347.24664
1063835.26972.73032
1074136.70664.2934
1083634.24721.75277
1094336.61276.3873
1103034.8091-4.80913
1113133.8529-2.85287
1123237.9022-5.90219
1133232.959-0.959003
1143734.32772.67233
1153734.29452.70546
1163336.4632-3.46324
1173436.7249-2.72494
1183334.4548-1.45478
1193835.70682.29324
1203334.8751-1.87505
1213131.5022-0.50219
1223836.67561.32442
1233736.37140.628605
1243633.12892.87115
1253134.103-3.103
1263934.05644.94358
1274437.04766.9524
1283335.7682-2.76817
1293533.58711.41294
1303233.942-1.94196
1312832.3197-4.31972
1324035.95574.04433
1332732.1386-5.13857
1343736.06890.93112
1353232.5734-0.573444
1362828.2624-0.262408
1373434.5962-0.596246
1383033.6663-3.66634
1393533.86191.13812
1403134.1178-3.11778
1413234.1851-2.18508
1423036.0402-6.0402
1433035.3215-5.32151
1443129.85361.14638
1454032.87017.12995
1463231.91390.0860736
1473634.48521.51476
1483233.076-1.07602
1493532.8542.14599
1503836.27641.72359
1514235.71536.28468
1523436.3455-2.34548
1533536.5025-1.50251
1543833.77634.22366
1553332.42440.575609
1563633.2952.705
1573235.3265-3.3265
1583335.7682-2.76817
1593433.76780.232203
1603235.7837-3.78371
1613434.8159-0.815896
1622730.1727-3.17268
1633130.64250.357523
1643834.51873.48125
1653436.2219-2.2219
1662431.3559-7.35591
1673033.8954-3.89536
1682629.7851-3.78509
1693435.6504-1.65035
1702735.4267-8.42669
1713732.07424.92585
1723635.92980.0702466
1734134.13116.86888
1742929.2956-0.295618
1753631.48254.5175
1763234.8235-2.82347
1773733.05813.94191
1783031.9949-1.99487
1793132.9517-1.95168
1803835.07182.9282
1813634.98211.01794
1823531.89823.10178
1833135.7723-4.77227
1843833.63094.36911
1852231.3002-9.30022
1863235.3502-3.35019
1873634.64411.35592
1883933.01735.9827
1892830.7648-2.7648
1903234.2431-2.24311
1913234.1735-2.17349
1923837.14820.851756
1933233.5267-1.52667
1943535.3547-0.354739
1953233.2823-1.28233
1963735.89531.10474
1973433.3060.693976
1983336.0822-3.08223
1993333.1248-0.12482
2002633.6269-7.62688
2013032.2951-2.29515
2022432.4813-8.48134
2033432.79411.20591
2043432.63941.36063
2053334.4163-1.4163
2063435.3283-1.32829
2073536.042-1.04197
2083535.0913-0.0912778
2093633.26622.73381
2103434.2968-0.296754
2113432.97761.02243
2124138.69782.30216
2133236.5986-4.5986
2143033.3118-3.31179
2153534.58370.416328
2162830.2215-2.22152
2173335.5256-2.5256
2183934.43194.56813
2193633.84532.15472
2203636.7969-0.796914
2213533.49971.50025
2223834.94983.05019
2233333.1709-0.170877
2243133.1512-2.1512
2253433.89290.107122
2263234.5657-2.56566
2273133.3501-2.35007
2283333.8798-0.879777
2293432.8121.18804
2303434.1196-0.119557
2313432.31571.68426
2323334.955-1.95501
2333234.2656-2.2656
2344134.22436.77566
2353433.35710.642929
2363632.2453.75501
2373731.08685.91323
2383630.51075.48933
2392932.8661-3.86614
2403731.71835.28174
2412733.2491-6.24907
2423533.55311.44689
2432830.6395-2.63945
2443533.37321.62682
2453733.313.68997
2462934.0994-5.09943
2473234.491-2.49103
2483632.25053.74945
2491927.6609-8.66094
2502127.3142-6.31417
2513133.8515-2.85154
2523332.86030.139748
2533633.85332.14669
2543333.5262-0.526228
2553733.28233.71768
2563433.52440.475561
2573535.467-0.466957
2583132.7637-1.7637
2593734.05342.9466
2603531.07823.9218
2612732.4371-5.43708
2623435.5547-1.55472
2634033.96436.03572
2642933.3387-4.33872






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.3975460.7950930.602454
90.2584710.5169420.741529
100.1529150.305830.847085
110.1053970.2107950.894603
120.5628160.8743690.437184
130.6444410.7111190.355559
140.5553240.8893530.444676
150.4908420.9816840.509158
160.5768310.8463390.423169
170.5028310.9943390.497169
180.4751780.9503550.524822
190.4355580.8711170.564442
200.489910.9798190.51009
210.5286380.9427250.471362
220.4886840.9773680.511316
230.4377680.8755360.562232
240.3700350.7400690.629965
250.4085410.8170820.591459
260.6133310.7733380.386669
270.5514990.8970020.448501
280.5414460.9171080.458554
290.5116410.9767180.488359
300.4528310.9056630.547169
310.4576290.9152570.542371
320.5724290.8551420.427571
330.5704140.8591710.429586
340.539910.9201790.46009
350.487530.975060.51247
360.4340840.8681680.565916
370.3955580.7911160.604442
380.3619390.7238770.638061
390.4592050.918410.540795
400.4088550.8177090.591145
410.3863350.7726710.613665
420.3380760.6761530.661924
430.3090040.6180080.690996
440.2738670.5477340.726133
450.3428960.6857930.657104
460.364140.728280.63586
470.337150.6743010.66285
480.3089360.6178710.691064
490.2690520.5381030.730948
500.2920130.5840270.707987
510.3213190.6426370.678681
520.2906410.5812830.709359
530.2579140.5158280.742086
540.2339420.4678840.766058
550.200440.4008810.79956
560.1844220.3688430.815578
570.1938980.3877950.806102
580.2813650.562730.718635
590.2563530.5127050.743647
600.2228090.4456190.777191
610.1986840.3973680.801316
620.1922950.3845910.807705
630.168750.3375010.83125
640.1684670.3369340.831533
650.1443420.2886850.855658
660.1239740.2479470.876026
670.104480.2089590.89552
680.1104380.2208770.889562
690.1102450.2204910.889755
700.09363080.1872620.906369
710.1000170.2000330.899983
720.1204860.2409710.879514
730.1203280.2406570.879672
740.1014130.2028250.898587
750.08791480.175830.912085
760.1151550.230310.884845
770.09833910.1966780.901661
780.08292120.1658420.917079
790.1156180.2312370.884382
800.1418280.2836560.858172
810.1344480.2688970.865552
820.1153690.2307390.884631
830.1083940.2167880.891606
840.1027990.2055980.897201
850.08892140.1778430.911079
860.07990690.1598140.920093
870.07053150.1410630.929469
880.08685940.1737190.913141
890.07321160.1464230.926788
900.07788130.1557630.922119
910.07101560.1420310.928984
920.06382980.127660.93617
930.05447990.108960.94552
940.05815170.1163030.941848
950.05901110.1180220.940989
960.05328570.1065710.946714
970.04558590.09117180.954414
980.04017280.08034550.959827
990.03904580.07809160.960954
1000.03544940.07089870.964551
1010.03159870.06319740.968401
1020.02652530.05305060.973475
1030.02189120.04378240.978109
1040.02268630.04537260.977314
1050.04926620.09853240.950734
1060.04637890.09275770.953621
1070.05610920.1122180.943891
1080.0489880.09797590.951012
1090.08695160.1739030.913048
1100.1040950.208190.895905
1110.103130.2062590.89687
1120.1322210.2644430.867779
1130.1200870.2401740.879913
1140.1153430.2306860.884657
1150.1101490.2202970.889851
1160.1097710.2195420.890229
1170.1019490.2038990.898051
1180.08938520.178770.910615
1190.08384320.1676860.916157
1200.07466370.1493270.925336
1210.06602960.1320590.93397
1220.05891980.117840.94108
1230.04971840.09943670.950282
1240.04731240.09462480.952688
1250.04675320.09350630.953247
1260.05934040.1186810.94066
1270.1117330.2234670.888267
1280.1051560.2103120.894844
1290.09247470.1849490.907525
1300.08393470.1678690.916065
1310.09503860.1900770.904961
1320.1062810.2125610.893719
1330.1320370.2640750.867963
1340.116260.232520.88374
1350.1015690.2031390.898431
1360.08907080.1781420.910929
1370.07611960.1522390.92388
1380.07862290.1572460.921377
1390.06809940.1361990.931901
1400.06595410.1319080.934046
1410.06006380.1201280.939936
1420.08399710.1679940.916003
1430.1032790.2065570.896721
1440.09576810.1915360.904232
1450.1677560.3355130.832244
1460.1557910.3115820.844209
1470.1394080.2788160.860592
1480.1228620.2457240.877138
1490.1134330.2268660.886567
1500.1019660.2039320.898034
1510.1534870.3069750.846513
1520.1408130.2816270.859187
1530.1245170.2490340.875483
1540.1372480.2744960.862752
1550.1188890.2377790.881111
1560.1187760.2375510.881224
1570.1190140.2380280.880986
1580.1109290.2218580.889071
1590.0975930.1951860.902407
1600.1041690.2083370.895831
1610.08975510.179510.910245
1620.08653870.1730770.913461
1630.07528790.1505760.924712
1640.08595820.1719160.914042
1650.07822650.1564530.921774
1660.14970.29940.8503
1670.1510170.3020340.848983
1680.1493480.2986950.850652
1690.1353070.2706130.864693
1700.2633110.5266220.736689
1710.3002390.6004770.699761
1720.2697010.5394010.730299
1730.3692950.738590.630705
1740.3347480.6694950.665252
1750.390070.7801390.60993
1760.3731820.7463640.626818
1770.3842350.7684710.615765
1780.3571630.7143270.642837
1790.3290040.6580090.670996
1800.3150670.6301350.684933
1810.2867130.5734260.713287
1820.2867750.5735490.713225
1830.299520.5990410.70048
1840.3524570.7049150.647543
1850.5989970.8020070.401003
1860.5888570.8222870.411143
1870.5735790.8528420.426421
1880.6808730.6382540.319127
1890.66470.6705990.3353
1900.6632660.6734690.336734
1910.6557420.6885160.344258
1920.6205670.7588660.379433
1930.5892650.821470.410735
1940.5493840.9012330.450616
1950.5110360.9779280.488964
1960.4740060.9480110.525994
1970.461120.9222410.53888
1980.4381920.8763840.561808
1990.3975220.7950440.602478
2000.5049980.9900030.495002
2010.4699920.9399830.530008
2020.644590.710820.35541
2030.6104670.7790660.389533
2040.5729440.8541130.427056
2050.5331110.9337770.466889
2060.4939660.9879310.506034
2070.4514460.9028920.548554
2080.4080560.8161130.591944
2090.3872750.7745510.612725
2100.3479810.6959610.652019
2110.3094320.6188640.690568
2120.2777160.5554330.722284
2130.3194130.6388250.680587
2140.3059160.6118320.694084
2150.2673810.5347610.732619
2160.234950.4698990.76505
2170.2101250.420250.789875
2180.2419980.4839950.758002
2190.2130030.4260050.786997
2200.1836090.3672180.816391
2210.158840.3176810.84116
2220.1501210.3002420.849879
2230.1236350.247270.876365
2240.1062590.2125180.893741
2250.08626420.1725280.913736
2260.09722830.1944570.902772
2270.08452990.169060.91547
2280.06729910.1345980.932701
2290.05263820.1052760.947362
2300.04072040.08144080.95928
2310.03411570.06823140.965884
2320.04123910.08247820.958761
2330.03378880.06757760.966211
2340.1440860.2881720.855914
2350.1181510.2363020.881849
2360.1204380.2408760.879562
2370.118070.2361390.88193
2380.2674630.5349250.732537
2390.2268610.4537220.773139
2400.3253830.6507660.674617
2410.435230.870460.56477
2420.36830.73660.6317
2430.3122860.6245710.687714
2440.270570.5411390.72943
2450.5236990.9526030.476301
2460.7673850.4652310.232615
2470.7387910.5224180.261209
2480.7213040.5573930.278696
2490.7591260.4817480.240874
2500.7028270.5943460.297173
2510.6822010.6355990.317799
2520.577370.8452610.42263
2530.4915060.9830120.508494
2540.4500830.9001660.549917
2550.4573730.9147470.542627
2560.3476880.6953760.652312

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.397546 & 0.795093 & 0.602454 \tabularnewline
9 & 0.258471 & 0.516942 & 0.741529 \tabularnewline
10 & 0.152915 & 0.30583 & 0.847085 \tabularnewline
11 & 0.105397 & 0.210795 & 0.894603 \tabularnewline
12 & 0.562816 & 0.874369 & 0.437184 \tabularnewline
13 & 0.644441 & 0.711119 & 0.355559 \tabularnewline
14 & 0.555324 & 0.889353 & 0.444676 \tabularnewline
15 & 0.490842 & 0.981684 & 0.509158 \tabularnewline
16 & 0.576831 & 0.846339 & 0.423169 \tabularnewline
17 & 0.502831 & 0.994339 & 0.497169 \tabularnewline
18 & 0.475178 & 0.950355 & 0.524822 \tabularnewline
19 & 0.435558 & 0.871117 & 0.564442 \tabularnewline
20 & 0.48991 & 0.979819 & 0.51009 \tabularnewline
21 & 0.528638 & 0.942725 & 0.471362 \tabularnewline
22 & 0.488684 & 0.977368 & 0.511316 \tabularnewline
23 & 0.437768 & 0.875536 & 0.562232 \tabularnewline
24 & 0.370035 & 0.740069 & 0.629965 \tabularnewline
25 & 0.408541 & 0.817082 & 0.591459 \tabularnewline
26 & 0.613331 & 0.773338 & 0.386669 \tabularnewline
27 & 0.551499 & 0.897002 & 0.448501 \tabularnewline
28 & 0.541446 & 0.917108 & 0.458554 \tabularnewline
29 & 0.511641 & 0.976718 & 0.488359 \tabularnewline
30 & 0.452831 & 0.905663 & 0.547169 \tabularnewline
31 & 0.457629 & 0.915257 & 0.542371 \tabularnewline
32 & 0.572429 & 0.855142 & 0.427571 \tabularnewline
33 & 0.570414 & 0.859171 & 0.429586 \tabularnewline
34 & 0.53991 & 0.920179 & 0.46009 \tabularnewline
35 & 0.48753 & 0.97506 & 0.51247 \tabularnewline
36 & 0.434084 & 0.868168 & 0.565916 \tabularnewline
37 & 0.395558 & 0.791116 & 0.604442 \tabularnewline
38 & 0.361939 & 0.723877 & 0.638061 \tabularnewline
39 & 0.459205 & 0.91841 & 0.540795 \tabularnewline
40 & 0.408855 & 0.817709 & 0.591145 \tabularnewline
41 & 0.386335 & 0.772671 & 0.613665 \tabularnewline
42 & 0.338076 & 0.676153 & 0.661924 \tabularnewline
43 & 0.309004 & 0.618008 & 0.690996 \tabularnewline
44 & 0.273867 & 0.547734 & 0.726133 \tabularnewline
45 & 0.342896 & 0.685793 & 0.657104 \tabularnewline
46 & 0.36414 & 0.72828 & 0.63586 \tabularnewline
47 & 0.33715 & 0.674301 & 0.66285 \tabularnewline
48 & 0.308936 & 0.617871 & 0.691064 \tabularnewline
49 & 0.269052 & 0.538103 & 0.730948 \tabularnewline
50 & 0.292013 & 0.584027 & 0.707987 \tabularnewline
51 & 0.321319 & 0.642637 & 0.678681 \tabularnewline
52 & 0.290641 & 0.581283 & 0.709359 \tabularnewline
53 & 0.257914 & 0.515828 & 0.742086 \tabularnewline
54 & 0.233942 & 0.467884 & 0.766058 \tabularnewline
55 & 0.20044 & 0.400881 & 0.79956 \tabularnewline
56 & 0.184422 & 0.368843 & 0.815578 \tabularnewline
57 & 0.193898 & 0.387795 & 0.806102 \tabularnewline
58 & 0.281365 & 0.56273 & 0.718635 \tabularnewline
59 & 0.256353 & 0.512705 & 0.743647 \tabularnewline
60 & 0.222809 & 0.445619 & 0.777191 \tabularnewline
61 & 0.198684 & 0.397368 & 0.801316 \tabularnewline
62 & 0.192295 & 0.384591 & 0.807705 \tabularnewline
63 & 0.16875 & 0.337501 & 0.83125 \tabularnewline
64 & 0.168467 & 0.336934 & 0.831533 \tabularnewline
65 & 0.144342 & 0.288685 & 0.855658 \tabularnewline
66 & 0.123974 & 0.247947 & 0.876026 \tabularnewline
67 & 0.10448 & 0.208959 & 0.89552 \tabularnewline
68 & 0.110438 & 0.220877 & 0.889562 \tabularnewline
69 & 0.110245 & 0.220491 & 0.889755 \tabularnewline
70 & 0.0936308 & 0.187262 & 0.906369 \tabularnewline
71 & 0.100017 & 0.200033 & 0.899983 \tabularnewline
72 & 0.120486 & 0.240971 & 0.879514 \tabularnewline
73 & 0.120328 & 0.240657 & 0.879672 \tabularnewline
74 & 0.101413 & 0.202825 & 0.898587 \tabularnewline
75 & 0.0879148 & 0.17583 & 0.912085 \tabularnewline
76 & 0.115155 & 0.23031 & 0.884845 \tabularnewline
77 & 0.0983391 & 0.196678 & 0.901661 \tabularnewline
78 & 0.0829212 & 0.165842 & 0.917079 \tabularnewline
79 & 0.115618 & 0.231237 & 0.884382 \tabularnewline
80 & 0.141828 & 0.283656 & 0.858172 \tabularnewline
81 & 0.134448 & 0.268897 & 0.865552 \tabularnewline
82 & 0.115369 & 0.230739 & 0.884631 \tabularnewline
83 & 0.108394 & 0.216788 & 0.891606 \tabularnewline
84 & 0.102799 & 0.205598 & 0.897201 \tabularnewline
85 & 0.0889214 & 0.177843 & 0.911079 \tabularnewline
86 & 0.0799069 & 0.159814 & 0.920093 \tabularnewline
87 & 0.0705315 & 0.141063 & 0.929469 \tabularnewline
88 & 0.0868594 & 0.173719 & 0.913141 \tabularnewline
89 & 0.0732116 & 0.146423 & 0.926788 \tabularnewline
90 & 0.0778813 & 0.155763 & 0.922119 \tabularnewline
91 & 0.0710156 & 0.142031 & 0.928984 \tabularnewline
92 & 0.0638298 & 0.12766 & 0.93617 \tabularnewline
93 & 0.0544799 & 0.10896 & 0.94552 \tabularnewline
94 & 0.0581517 & 0.116303 & 0.941848 \tabularnewline
95 & 0.0590111 & 0.118022 & 0.940989 \tabularnewline
96 & 0.0532857 & 0.106571 & 0.946714 \tabularnewline
97 & 0.0455859 & 0.0911718 & 0.954414 \tabularnewline
98 & 0.0401728 & 0.0803455 & 0.959827 \tabularnewline
99 & 0.0390458 & 0.0780916 & 0.960954 \tabularnewline
100 & 0.0354494 & 0.0708987 & 0.964551 \tabularnewline
101 & 0.0315987 & 0.0631974 & 0.968401 \tabularnewline
102 & 0.0265253 & 0.0530506 & 0.973475 \tabularnewline
103 & 0.0218912 & 0.0437824 & 0.978109 \tabularnewline
104 & 0.0226863 & 0.0453726 & 0.977314 \tabularnewline
105 & 0.0492662 & 0.0985324 & 0.950734 \tabularnewline
106 & 0.0463789 & 0.0927577 & 0.953621 \tabularnewline
107 & 0.0561092 & 0.112218 & 0.943891 \tabularnewline
108 & 0.048988 & 0.0979759 & 0.951012 \tabularnewline
109 & 0.0869516 & 0.173903 & 0.913048 \tabularnewline
110 & 0.104095 & 0.20819 & 0.895905 \tabularnewline
111 & 0.10313 & 0.206259 & 0.89687 \tabularnewline
112 & 0.132221 & 0.264443 & 0.867779 \tabularnewline
113 & 0.120087 & 0.240174 & 0.879913 \tabularnewline
114 & 0.115343 & 0.230686 & 0.884657 \tabularnewline
115 & 0.110149 & 0.220297 & 0.889851 \tabularnewline
116 & 0.109771 & 0.219542 & 0.890229 \tabularnewline
117 & 0.101949 & 0.203899 & 0.898051 \tabularnewline
118 & 0.0893852 & 0.17877 & 0.910615 \tabularnewline
119 & 0.0838432 & 0.167686 & 0.916157 \tabularnewline
120 & 0.0746637 & 0.149327 & 0.925336 \tabularnewline
121 & 0.0660296 & 0.132059 & 0.93397 \tabularnewline
122 & 0.0589198 & 0.11784 & 0.94108 \tabularnewline
123 & 0.0497184 & 0.0994367 & 0.950282 \tabularnewline
124 & 0.0473124 & 0.0946248 & 0.952688 \tabularnewline
125 & 0.0467532 & 0.0935063 & 0.953247 \tabularnewline
126 & 0.0593404 & 0.118681 & 0.94066 \tabularnewline
127 & 0.111733 & 0.223467 & 0.888267 \tabularnewline
128 & 0.105156 & 0.210312 & 0.894844 \tabularnewline
129 & 0.0924747 & 0.184949 & 0.907525 \tabularnewline
130 & 0.0839347 & 0.167869 & 0.916065 \tabularnewline
131 & 0.0950386 & 0.190077 & 0.904961 \tabularnewline
132 & 0.106281 & 0.212561 & 0.893719 \tabularnewline
133 & 0.132037 & 0.264075 & 0.867963 \tabularnewline
134 & 0.11626 & 0.23252 & 0.88374 \tabularnewline
135 & 0.101569 & 0.203139 & 0.898431 \tabularnewline
136 & 0.0890708 & 0.178142 & 0.910929 \tabularnewline
137 & 0.0761196 & 0.152239 & 0.92388 \tabularnewline
138 & 0.0786229 & 0.157246 & 0.921377 \tabularnewline
139 & 0.0680994 & 0.136199 & 0.931901 \tabularnewline
140 & 0.0659541 & 0.131908 & 0.934046 \tabularnewline
141 & 0.0600638 & 0.120128 & 0.939936 \tabularnewline
142 & 0.0839971 & 0.167994 & 0.916003 \tabularnewline
143 & 0.103279 & 0.206557 & 0.896721 \tabularnewline
144 & 0.0957681 & 0.191536 & 0.904232 \tabularnewline
145 & 0.167756 & 0.335513 & 0.832244 \tabularnewline
146 & 0.155791 & 0.311582 & 0.844209 \tabularnewline
147 & 0.139408 & 0.278816 & 0.860592 \tabularnewline
148 & 0.122862 & 0.245724 & 0.877138 \tabularnewline
149 & 0.113433 & 0.226866 & 0.886567 \tabularnewline
150 & 0.101966 & 0.203932 & 0.898034 \tabularnewline
151 & 0.153487 & 0.306975 & 0.846513 \tabularnewline
152 & 0.140813 & 0.281627 & 0.859187 \tabularnewline
153 & 0.124517 & 0.249034 & 0.875483 \tabularnewline
154 & 0.137248 & 0.274496 & 0.862752 \tabularnewline
155 & 0.118889 & 0.237779 & 0.881111 \tabularnewline
156 & 0.118776 & 0.237551 & 0.881224 \tabularnewline
157 & 0.119014 & 0.238028 & 0.880986 \tabularnewline
158 & 0.110929 & 0.221858 & 0.889071 \tabularnewline
159 & 0.097593 & 0.195186 & 0.902407 \tabularnewline
160 & 0.104169 & 0.208337 & 0.895831 \tabularnewline
161 & 0.0897551 & 0.17951 & 0.910245 \tabularnewline
162 & 0.0865387 & 0.173077 & 0.913461 \tabularnewline
163 & 0.0752879 & 0.150576 & 0.924712 \tabularnewline
164 & 0.0859582 & 0.171916 & 0.914042 \tabularnewline
165 & 0.0782265 & 0.156453 & 0.921774 \tabularnewline
166 & 0.1497 & 0.2994 & 0.8503 \tabularnewline
167 & 0.151017 & 0.302034 & 0.848983 \tabularnewline
168 & 0.149348 & 0.298695 & 0.850652 \tabularnewline
169 & 0.135307 & 0.270613 & 0.864693 \tabularnewline
170 & 0.263311 & 0.526622 & 0.736689 \tabularnewline
171 & 0.300239 & 0.600477 & 0.699761 \tabularnewline
172 & 0.269701 & 0.539401 & 0.730299 \tabularnewline
173 & 0.369295 & 0.73859 & 0.630705 \tabularnewline
174 & 0.334748 & 0.669495 & 0.665252 \tabularnewline
175 & 0.39007 & 0.780139 & 0.60993 \tabularnewline
176 & 0.373182 & 0.746364 & 0.626818 \tabularnewline
177 & 0.384235 & 0.768471 & 0.615765 \tabularnewline
178 & 0.357163 & 0.714327 & 0.642837 \tabularnewline
179 & 0.329004 & 0.658009 & 0.670996 \tabularnewline
180 & 0.315067 & 0.630135 & 0.684933 \tabularnewline
181 & 0.286713 & 0.573426 & 0.713287 \tabularnewline
182 & 0.286775 & 0.573549 & 0.713225 \tabularnewline
183 & 0.29952 & 0.599041 & 0.70048 \tabularnewline
184 & 0.352457 & 0.704915 & 0.647543 \tabularnewline
185 & 0.598997 & 0.802007 & 0.401003 \tabularnewline
186 & 0.588857 & 0.822287 & 0.411143 \tabularnewline
187 & 0.573579 & 0.852842 & 0.426421 \tabularnewline
188 & 0.680873 & 0.638254 & 0.319127 \tabularnewline
189 & 0.6647 & 0.670599 & 0.3353 \tabularnewline
190 & 0.663266 & 0.673469 & 0.336734 \tabularnewline
191 & 0.655742 & 0.688516 & 0.344258 \tabularnewline
192 & 0.620567 & 0.758866 & 0.379433 \tabularnewline
193 & 0.589265 & 0.82147 & 0.410735 \tabularnewline
194 & 0.549384 & 0.901233 & 0.450616 \tabularnewline
195 & 0.511036 & 0.977928 & 0.488964 \tabularnewline
196 & 0.474006 & 0.948011 & 0.525994 \tabularnewline
197 & 0.46112 & 0.922241 & 0.53888 \tabularnewline
198 & 0.438192 & 0.876384 & 0.561808 \tabularnewline
199 & 0.397522 & 0.795044 & 0.602478 \tabularnewline
200 & 0.504998 & 0.990003 & 0.495002 \tabularnewline
201 & 0.469992 & 0.939983 & 0.530008 \tabularnewline
202 & 0.64459 & 0.71082 & 0.35541 \tabularnewline
203 & 0.610467 & 0.779066 & 0.389533 \tabularnewline
204 & 0.572944 & 0.854113 & 0.427056 \tabularnewline
205 & 0.533111 & 0.933777 & 0.466889 \tabularnewline
206 & 0.493966 & 0.987931 & 0.506034 \tabularnewline
207 & 0.451446 & 0.902892 & 0.548554 \tabularnewline
208 & 0.408056 & 0.816113 & 0.591944 \tabularnewline
209 & 0.387275 & 0.774551 & 0.612725 \tabularnewline
210 & 0.347981 & 0.695961 & 0.652019 \tabularnewline
211 & 0.309432 & 0.618864 & 0.690568 \tabularnewline
212 & 0.277716 & 0.555433 & 0.722284 \tabularnewline
213 & 0.319413 & 0.638825 & 0.680587 \tabularnewline
214 & 0.305916 & 0.611832 & 0.694084 \tabularnewline
215 & 0.267381 & 0.534761 & 0.732619 \tabularnewline
216 & 0.23495 & 0.469899 & 0.76505 \tabularnewline
217 & 0.210125 & 0.42025 & 0.789875 \tabularnewline
218 & 0.241998 & 0.483995 & 0.758002 \tabularnewline
219 & 0.213003 & 0.426005 & 0.786997 \tabularnewline
220 & 0.183609 & 0.367218 & 0.816391 \tabularnewline
221 & 0.15884 & 0.317681 & 0.84116 \tabularnewline
222 & 0.150121 & 0.300242 & 0.849879 \tabularnewline
223 & 0.123635 & 0.24727 & 0.876365 \tabularnewline
224 & 0.106259 & 0.212518 & 0.893741 \tabularnewline
225 & 0.0862642 & 0.172528 & 0.913736 \tabularnewline
226 & 0.0972283 & 0.194457 & 0.902772 \tabularnewline
227 & 0.0845299 & 0.16906 & 0.91547 \tabularnewline
228 & 0.0672991 & 0.134598 & 0.932701 \tabularnewline
229 & 0.0526382 & 0.105276 & 0.947362 \tabularnewline
230 & 0.0407204 & 0.0814408 & 0.95928 \tabularnewline
231 & 0.0341157 & 0.0682314 & 0.965884 \tabularnewline
232 & 0.0412391 & 0.0824782 & 0.958761 \tabularnewline
233 & 0.0337888 & 0.0675776 & 0.966211 \tabularnewline
234 & 0.144086 & 0.288172 & 0.855914 \tabularnewline
235 & 0.118151 & 0.236302 & 0.881849 \tabularnewline
236 & 0.120438 & 0.240876 & 0.879562 \tabularnewline
237 & 0.11807 & 0.236139 & 0.88193 \tabularnewline
238 & 0.267463 & 0.534925 & 0.732537 \tabularnewline
239 & 0.226861 & 0.453722 & 0.773139 \tabularnewline
240 & 0.325383 & 0.650766 & 0.674617 \tabularnewline
241 & 0.43523 & 0.87046 & 0.56477 \tabularnewline
242 & 0.3683 & 0.7366 & 0.6317 \tabularnewline
243 & 0.312286 & 0.624571 & 0.687714 \tabularnewline
244 & 0.27057 & 0.541139 & 0.72943 \tabularnewline
245 & 0.523699 & 0.952603 & 0.476301 \tabularnewline
246 & 0.767385 & 0.465231 & 0.232615 \tabularnewline
247 & 0.738791 & 0.522418 & 0.261209 \tabularnewline
248 & 0.721304 & 0.557393 & 0.278696 \tabularnewline
249 & 0.759126 & 0.481748 & 0.240874 \tabularnewline
250 & 0.702827 & 0.594346 & 0.297173 \tabularnewline
251 & 0.682201 & 0.635599 & 0.317799 \tabularnewline
252 & 0.57737 & 0.845261 & 0.42263 \tabularnewline
253 & 0.491506 & 0.983012 & 0.508494 \tabularnewline
254 & 0.450083 & 0.900166 & 0.549917 \tabularnewline
255 & 0.457373 & 0.914747 & 0.542627 \tabularnewline
256 & 0.347688 & 0.695376 & 0.652312 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253397&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]8[/C][C]0.397546[/C][C]0.795093[/C][C]0.602454[/C][/ROW]
[ROW][C]9[/C][C]0.258471[/C][C]0.516942[/C][C]0.741529[/C][/ROW]
[ROW][C]10[/C][C]0.152915[/C][C]0.30583[/C][C]0.847085[/C][/ROW]
[ROW][C]11[/C][C]0.105397[/C][C]0.210795[/C][C]0.894603[/C][/ROW]
[ROW][C]12[/C][C]0.562816[/C][C]0.874369[/C][C]0.437184[/C][/ROW]
[ROW][C]13[/C][C]0.644441[/C][C]0.711119[/C][C]0.355559[/C][/ROW]
[ROW][C]14[/C][C]0.555324[/C][C]0.889353[/C][C]0.444676[/C][/ROW]
[ROW][C]15[/C][C]0.490842[/C][C]0.981684[/C][C]0.509158[/C][/ROW]
[ROW][C]16[/C][C]0.576831[/C][C]0.846339[/C][C]0.423169[/C][/ROW]
[ROW][C]17[/C][C]0.502831[/C][C]0.994339[/C][C]0.497169[/C][/ROW]
[ROW][C]18[/C][C]0.475178[/C][C]0.950355[/C][C]0.524822[/C][/ROW]
[ROW][C]19[/C][C]0.435558[/C][C]0.871117[/C][C]0.564442[/C][/ROW]
[ROW][C]20[/C][C]0.48991[/C][C]0.979819[/C][C]0.51009[/C][/ROW]
[ROW][C]21[/C][C]0.528638[/C][C]0.942725[/C][C]0.471362[/C][/ROW]
[ROW][C]22[/C][C]0.488684[/C][C]0.977368[/C][C]0.511316[/C][/ROW]
[ROW][C]23[/C][C]0.437768[/C][C]0.875536[/C][C]0.562232[/C][/ROW]
[ROW][C]24[/C][C]0.370035[/C][C]0.740069[/C][C]0.629965[/C][/ROW]
[ROW][C]25[/C][C]0.408541[/C][C]0.817082[/C][C]0.591459[/C][/ROW]
[ROW][C]26[/C][C]0.613331[/C][C]0.773338[/C][C]0.386669[/C][/ROW]
[ROW][C]27[/C][C]0.551499[/C][C]0.897002[/C][C]0.448501[/C][/ROW]
[ROW][C]28[/C][C]0.541446[/C][C]0.917108[/C][C]0.458554[/C][/ROW]
[ROW][C]29[/C][C]0.511641[/C][C]0.976718[/C][C]0.488359[/C][/ROW]
[ROW][C]30[/C][C]0.452831[/C][C]0.905663[/C][C]0.547169[/C][/ROW]
[ROW][C]31[/C][C]0.457629[/C][C]0.915257[/C][C]0.542371[/C][/ROW]
[ROW][C]32[/C][C]0.572429[/C][C]0.855142[/C][C]0.427571[/C][/ROW]
[ROW][C]33[/C][C]0.570414[/C][C]0.859171[/C][C]0.429586[/C][/ROW]
[ROW][C]34[/C][C]0.53991[/C][C]0.920179[/C][C]0.46009[/C][/ROW]
[ROW][C]35[/C][C]0.48753[/C][C]0.97506[/C][C]0.51247[/C][/ROW]
[ROW][C]36[/C][C]0.434084[/C][C]0.868168[/C][C]0.565916[/C][/ROW]
[ROW][C]37[/C][C]0.395558[/C][C]0.791116[/C][C]0.604442[/C][/ROW]
[ROW][C]38[/C][C]0.361939[/C][C]0.723877[/C][C]0.638061[/C][/ROW]
[ROW][C]39[/C][C]0.459205[/C][C]0.91841[/C][C]0.540795[/C][/ROW]
[ROW][C]40[/C][C]0.408855[/C][C]0.817709[/C][C]0.591145[/C][/ROW]
[ROW][C]41[/C][C]0.386335[/C][C]0.772671[/C][C]0.613665[/C][/ROW]
[ROW][C]42[/C][C]0.338076[/C][C]0.676153[/C][C]0.661924[/C][/ROW]
[ROW][C]43[/C][C]0.309004[/C][C]0.618008[/C][C]0.690996[/C][/ROW]
[ROW][C]44[/C][C]0.273867[/C][C]0.547734[/C][C]0.726133[/C][/ROW]
[ROW][C]45[/C][C]0.342896[/C][C]0.685793[/C][C]0.657104[/C][/ROW]
[ROW][C]46[/C][C]0.36414[/C][C]0.72828[/C][C]0.63586[/C][/ROW]
[ROW][C]47[/C][C]0.33715[/C][C]0.674301[/C][C]0.66285[/C][/ROW]
[ROW][C]48[/C][C]0.308936[/C][C]0.617871[/C][C]0.691064[/C][/ROW]
[ROW][C]49[/C][C]0.269052[/C][C]0.538103[/C][C]0.730948[/C][/ROW]
[ROW][C]50[/C][C]0.292013[/C][C]0.584027[/C][C]0.707987[/C][/ROW]
[ROW][C]51[/C][C]0.321319[/C][C]0.642637[/C][C]0.678681[/C][/ROW]
[ROW][C]52[/C][C]0.290641[/C][C]0.581283[/C][C]0.709359[/C][/ROW]
[ROW][C]53[/C][C]0.257914[/C][C]0.515828[/C][C]0.742086[/C][/ROW]
[ROW][C]54[/C][C]0.233942[/C][C]0.467884[/C][C]0.766058[/C][/ROW]
[ROW][C]55[/C][C]0.20044[/C][C]0.400881[/C][C]0.79956[/C][/ROW]
[ROW][C]56[/C][C]0.184422[/C][C]0.368843[/C][C]0.815578[/C][/ROW]
[ROW][C]57[/C][C]0.193898[/C][C]0.387795[/C][C]0.806102[/C][/ROW]
[ROW][C]58[/C][C]0.281365[/C][C]0.56273[/C][C]0.718635[/C][/ROW]
[ROW][C]59[/C][C]0.256353[/C][C]0.512705[/C][C]0.743647[/C][/ROW]
[ROW][C]60[/C][C]0.222809[/C][C]0.445619[/C][C]0.777191[/C][/ROW]
[ROW][C]61[/C][C]0.198684[/C][C]0.397368[/C][C]0.801316[/C][/ROW]
[ROW][C]62[/C][C]0.192295[/C][C]0.384591[/C][C]0.807705[/C][/ROW]
[ROW][C]63[/C][C]0.16875[/C][C]0.337501[/C][C]0.83125[/C][/ROW]
[ROW][C]64[/C][C]0.168467[/C][C]0.336934[/C][C]0.831533[/C][/ROW]
[ROW][C]65[/C][C]0.144342[/C][C]0.288685[/C][C]0.855658[/C][/ROW]
[ROW][C]66[/C][C]0.123974[/C][C]0.247947[/C][C]0.876026[/C][/ROW]
[ROW][C]67[/C][C]0.10448[/C][C]0.208959[/C][C]0.89552[/C][/ROW]
[ROW][C]68[/C][C]0.110438[/C][C]0.220877[/C][C]0.889562[/C][/ROW]
[ROW][C]69[/C][C]0.110245[/C][C]0.220491[/C][C]0.889755[/C][/ROW]
[ROW][C]70[/C][C]0.0936308[/C][C]0.187262[/C][C]0.906369[/C][/ROW]
[ROW][C]71[/C][C]0.100017[/C][C]0.200033[/C][C]0.899983[/C][/ROW]
[ROW][C]72[/C][C]0.120486[/C][C]0.240971[/C][C]0.879514[/C][/ROW]
[ROW][C]73[/C][C]0.120328[/C][C]0.240657[/C][C]0.879672[/C][/ROW]
[ROW][C]74[/C][C]0.101413[/C][C]0.202825[/C][C]0.898587[/C][/ROW]
[ROW][C]75[/C][C]0.0879148[/C][C]0.17583[/C][C]0.912085[/C][/ROW]
[ROW][C]76[/C][C]0.115155[/C][C]0.23031[/C][C]0.884845[/C][/ROW]
[ROW][C]77[/C][C]0.0983391[/C][C]0.196678[/C][C]0.901661[/C][/ROW]
[ROW][C]78[/C][C]0.0829212[/C][C]0.165842[/C][C]0.917079[/C][/ROW]
[ROW][C]79[/C][C]0.115618[/C][C]0.231237[/C][C]0.884382[/C][/ROW]
[ROW][C]80[/C][C]0.141828[/C][C]0.283656[/C][C]0.858172[/C][/ROW]
[ROW][C]81[/C][C]0.134448[/C][C]0.268897[/C][C]0.865552[/C][/ROW]
[ROW][C]82[/C][C]0.115369[/C][C]0.230739[/C][C]0.884631[/C][/ROW]
[ROW][C]83[/C][C]0.108394[/C][C]0.216788[/C][C]0.891606[/C][/ROW]
[ROW][C]84[/C][C]0.102799[/C][C]0.205598[/C][C]0.897201[/C][/ROW]
[ROW][C]85[/C][C]0.0889214[/C][C]0.177843[/C][C]0.911079[/C][/ROW]
[ROW][C]86[/C][C]0.0799069[/C][C]0.159814[/C][C]0.920093[/C][/ROW]
[ROW][C]87[/C][C]0.0705315[/C][C]0.141063[/C][C]0.929469[/C][/ROW]
[ROW][C]88[/C][C]0.0868594[/C][C]0.173719[/C][C]0.913141[/C][/ROW]
[ROW][C]89[/C][C]0.0732116[/C][C]0.146423[/C][C]0.926788[/C][/ROW]
[ROW][C]90[/C][C]0.0778813[/C][C]0.155763[/C][C]0.922119[/C][/ROW]
[ROW][C]91[/C][C]0.0710156[/C][C]0.142031[/C][C]0.928984[/C][/ROW]
[ROW][C]92[/C][C]0.0638298[/C][C]0.12766[/C][C]0.93617[/C][/ROW]
[ROW][C]93[/C][C]0.0544799[/C][C]0.10896[/C][C]0.94552[/C][/ROW]
[ROW][C]94[/C][C]0.0581517[/C][C]0.116303[/C][C]0.941848[/C][/ROW]
[ROW][C]95[/C][C]0.0590111[/C][C]0.118022[/C][C]0.940989[/C][/ROW]
[ROW][C]96[/C][C]0.0532857[/C][C]0.106571[/C][C]0.946714[/C][/ROW]
[ROW][C]97[/C][C]0.0455859[/C][C]0.0911718[/C][C]0.954414[/C][/ROW]
[ROW][C]98[/C][C]0.0401728[/C][C]0.0803455[/C][C]0.959827[/C][/ROW]
[ROW][C]99[/C][C]0.0390458[/C][C]0.0780916[/C][C]0.960954[/C][/ROW]
[ROW][C]100[/C][C]0.0354494[/C][C]0.0708987[/C][C]0.964551[/C][/ROW]
[ROW][C]101[/C][C]0.0315987[/C][C]0.0631974[/C][C]0.968401[/C][/ROW]
[ROW][C]102[/C][C]0.0265253[/C][C]0.0530506[/C][C]0.973475[/C][/ROW]
[ROW][C]103[/C][C]0.0218912[/C][C]0.0437824[/C][C]0.978109[/C][/ROW]
[ROW][C]104[/C][C]0.0226863[/C][C]0.0453726[/C][C]0.977314[/C][/ROW]
[ROW][C]105[/C][C]0.0492662[/C][C]0.0985324[/C][C]0.950734[/C][/ROW]
[ROW][C]106[/C][C]0.0463789[/C][C]0.0927577[/C][C]0.953621[/C][/ROW]
[ROW][C]107[/C][C]0.0561092[/C][C]0.112218[/C][C]0.943891[/C][/ROW]
[ROW][C]108[/C][C]0.048988[/C][C]0.0979759[/C][C]0.951012[/C][/ROW]
[ROW][C]109[/C][C]0.0869516[/C][C]0.173903[/C][C]0.913048[/C][/ROW]
[ROW][C]110[/C][C]0.104095[/C][C]0.20819[/C][C]0.895905[/C][/ROW]
[ROW][C]111[/C][C]0.10313[/C][C]0.206259[/C][C]0.89687[/C][/ROW]
[ROW][C]112[/C][C]0.132221[/C][C]0.264443[/C][C]0.867779[/C][/ROW]
[ROW][C]113[/C][C]0.120087[/C][C]0.240174[/C][C]0.879913[/C][/ROW]
[ROW][C]114[/C][C]0.115343[/C][C]0.230686[/C][C]0.884657[/C][/ROW]
[ROW][C]115[/C][C]0.110149[/C][C]0.220297[/C][C]0.889851[/C][/ROW]
[ROW][C]116[/C][C]0.109771[/C][C]0.219542[/C][C]0.890229[/C][/ROW]
[ROW][C]117[/C][C]0.101949[/C][C]0.203899[/C][C]0.898051[/C][/ROW]
[ROW][C]118[/C][C]0.0893852[/C][C]0.17877[/C][C]0.910615[/C][/ROW]
[ROW][C]119[/C][C]0.0838432[/C][C]0.167686[/C][C]0.916157[/C][/ROW]
[ROW][C]120[/C][C]0.0746637[/C][C]0.149327[/C][C]0.925336[/C][/ROW]
[ROW][C]121[/C][C]0.0660296[/C][C]0.132059[/C][C]0.93397[/C][/ROW]
[ROW][C]122[/C][C]0.0589198[/C][C]0.11784[/C][C]0.94108[/C][/ROW]
[ROW][C]123[/C][C]0.0497184[/C][C]0.0994367[/C][C]0.950282[/C][/ROW]
[ROW][C]124[/C][C]0.0473124[/C][C]0.0946248[/C][C]0.952688[/C][/ROW]
[ROW][C]125[/C][C]0.0467532[/C][C]0.0935063[/C][C]0.953247[/C][/ROW]
[ROW][C]126[/C][C]0.0593404[/C][C]0.118681[/C][C]0.94066[/C][/ROW]
[ROW][C]127[/C][C]0.111733[/C][C]0.223467[/C][C]0.888267[/C][/ROW]
[ROW][C]128[/C][C]0.105156[/C][C]0.210312[/C][C]0.894844[/C][/ROW]
[ROW][C]129[/C][C]0.0924747[/C][C]0.184949[/C][C]0.907525[/C][/ROW]
[ROW][C]130[/C][C]0.0839347[/C][C]0.167869[/C][C]0.916065[/C][/ROW]
[ROW][C]131[/C][C]0.0950386[/C][C]0.190077[/C][C]0.904961[/C][/ROW]
[ROW][C]132[/C][C]0.106281[/C][C]0.212561[/C][C]0.893719[/C][/ROW]
[ROW][C]133[/C][C]0.132037[/C][C]0.264075[/C][C]0.867963[/C][/ROW]
[ROW][C]134[/C][C]0.11626[/C][C]0.23252[/C][C]0.88374[/C][/ROW]
[ROW][C]135[/C][C]0.101569[/C][C]0.203139[/C][C]0.898431[/C][/ROW]
[ROW][C]136[/C][C]0.0890708[/C][C]0.178142[/C][C]0.910929[/C][/ROW]
[ROW][C]137[/C][C]0.0761196[/C][C]0.152239[/C][C]0.92388[/C][/ROW]
[ROW][C]138[/C][C]0.0786229[/C][C]0.157246[/C][C]0.921377[/C][/ROW]
[ROW][C]139[/C][C]0.0680994[/C][C]0.136199[/C][C]0.931901[/C][/ROW]
[ROW][C]140[/C][C]0.0659541[/C][C]0.131908[/C][C]0.934046[/C][/ROW]
[ROW][C]141[/C][C]0.0600638[/C][C]0.120128[/C][C]0.939936[/C][/ROW]
[ROW][C]142[/C][C]0.0839971[/C][C]0.167994[/C][C]0.916003[/C][/ROW]
[ROW][C]143[/C][C]0.103279[/C][C]0.206557[/C][C]0.896721[/C][/ROW]
[ROW][C]144[/C][C]0.0957681[/C][C]0.191536[/C][C]0.904232[/C][/ROW]
[ROW][C]145[/C][C]0.167756[/C][C]0.335513[/C][C]0.832244[/C][/ROW]
[ROW][C]146[/C][C]0.155791[/C][C]0.311582[/C][C]0.844209[/C][/ROW]
[ROW][C]147[/C][C]0.139408[/C][C]0.278816[/C][C]0.860592[/C][/ROW]
[ROW][C]148[/C][C]0.122862[/C][C]0.245724[/C][C]0.877138[/C][/ROW]
[ROW][C]149[/C][C]0.113433[/C][C]0.226866[/C][C]0.886567[/C][/ROW]
[ROW][C]150[/C][C]0.101966[/C][C]0.203932[/C][C]0.898034[/C][/ROW]
[ROW][C]151[/C][C]0.153487[/C][C]0.306975[/C][C]0.846513[/C][/ROW]
[ROW][C]152[/C][C]0.140813[/C][C]0.281627[/C][C]0.859187[/C][/ROW]
[ROW][C]153[/C][C]0.124517[/C][C]0.249034[/C][C]0.875483[/C][/ROW]
[ROW][C]154[/C][C]0.137248[/C][C]0.274496[/C][C]0.862752[/C][/ROW]
[ROW][C]155[/C][C]0.118889[/C][C]0.237779[/C][C]0.881111[/C][/ROW]
[ROW][C]156[/C][C]0.118776[/C][C]0.237551[/C][C]0.881224[/C][/ROW]
[ROW][C]157[/C][C]0.119014[/C][C]0.238028[/C][C]0.880986[/C][/ROW]
[ROW][C]158[/C][C]0.110929[/C][C]0.221858[/C][C]0.889071[/C][/ROW]
[ROW][C]159[/C][C]0.097593[/C][C]0.195186[/C][C]0.902407[/C][/ROW]
[ROW][C]160[/C][C]0.104169[/C][C]0.208337[/C][C]0.895831[/C][/ROW]
[ROW][C]161[/C][C]0.0897551[/C][C]0.17951[/C][C]0.910245[/C][/ROW]
[ROW][C]162[/C][C]0.0865387[/C][C]0.173077[/C][C]0.913461[/C][/ROW]
[ROW][C]163[/C][C]0.0752879[/C][C]0.150576[/C][C]0.924712[/C][/ROW]
[ROW][C]164[/C][C]0.0859582[/C][C]0.171916[/C][C]0.914042[/C][/ROW]
[ROW][C]165[/C][C]0.0782265[/C][C]0.156453[/C][C]0.921774[/C][/ROW]
[ROW][C]166[/C][C]0.1497[/C][C]0.2994[/C][C]0.8503[/C][/ROW]
[ROW][C]167[/C][C]0.151017[/C][C]0.302034[/C][C]0.848983[/C][/ROW]
[ROW][C]168[/C][C]0.149348[/C][C]0.298695[/C][C]0.850652[/C][/ROW]
[ROW][C]169[/C][C]0.135307[/C][C]0.270613[/C][C]0.864693[/C][/ROW]
[ROW][C]170[/C][C]0.263311[/C][C]0.526622[/C][C]0.736689[/C][/ROW]
[ROW][C]171[/C][C]0.300239[/C][C]0.600477[/C][C]0.699761[/C][/ROW]
[ROW][C]172[/C][C]0.269701[/C][C]0.539401[/C][C]0.730299[/C][/ROW]
[ROW][C]173[/C][C]0.369295[/C][C]0.73859[/C][C]0.630705[/C][/ROW]
[ROW][C]174[/C][C]0.334748[/C][C]0.669495[/C][C]0.665252[/C][/ROW]
[ROW][C]175[/C][C]0.39007[/C][C]0.780139[/C][C]0.60993[/C][/ROW]
[ROW][C]176[/C][C]0.373182[/C][C]0.746364[/C][C]0.626818[/C][/ROW]
[ROW][C]177[/C][C]0.384235[/C][C]0.768471[/C][C]0.615765[/C][/ROW]
[ROW][C]178[/C][C]0.357163[/C][C]0.714327[/C][C]0.642837[/C][/ROW]
[ROW][C]179[/C][C]0.329004[/C][C]0.658009[/C][C]0.670996[/C][/ROW]
[ROW][C]180[/C][C]0.315067[/C][C]0.630135[/C][C]0.684933[/C][/ROW]
[ROW][C]181[/C][C]0.286713[/C][C]0.573426[/C][C]0.713287[/C][/ROW]
[ROW][C]182[/C][C]0.286775[/C][C]0.573549[/C][C]0.713225[/C][/ROW]
[ROW][C]183[/C][C]0.29952[/C][C]0.599041[/C][C]0.70048[/C][/ROW]
[ROW][C]184[/C][C]0.352457[/C][C]0.704915[/C][C]0.647543[/C][/ROW]
[ROW][C]185[/C][C]0.598997[/C][C]0.802007[/C][C]0.401003[/C][/ROW]
[ROW][C]186[/C][C]0.588857[/C][C]0.822287[/C][C]0.411143[/C][/ROW]
[ROW][C]187[/C][C]0.573579[/C][C]0.852842[/C][C]0.426421[/C][/ROW]
[ROW][C]188[/C][C]0.680873[/C][C]0.638254[/C][C]0.319127[/C][/ROW]
[ROW][C]189[/C][C]0.6647[/C][C]0.670599[/C][C]0.3353[/C][/ROW]
[ROW][C]190[/C][C]0.663266[/C][C]0.673469[/C][C]0.336734[/C][/ROW]
[ROW][C]191[/C][C]0.655742[/C][C]0.688516[/C][C]0.344258[/C][/ROW]
[ROW][C]192[/C][C]0.620567[/C][C]0.758866[/C][C]0.379433[/C][/ROW]
[ROW][C]193[/C][C]0.589265[/C][C]0.82147[/C][C]0.410735[/C][/ROW]
[ROW][C]194[/C][C]0.549384[/C][C]0.901233[/C][C]0.450616[/C][/ROW]
[ROW][C]195[/C][C]0.511036[/C][C]0.977928[/C][C]0.488964[/C][/ROW]
[ROW][C]196[/C][C]0.474006[/C][C]0.948011[/C][C]0.525994[/C][/ROW]
[ROW][C]197[/C][C]0.46112[/C][C]0.922241[/C][C]0.53888[/C][/ROW]
[ROW][C]198[/C][C]0.438192[/C][C]0.876384[/C][C]0.561808[/C][/ROW]
[ROW][C]199[/C][C]0.397522[/C][C]0.795044[/C][C]0.602478[/C][/ROW]
[ROW][C]200[/C][C]0.504998[/C][C]0.990003[/C][C]0.495002[/C][/ROW]
[ROW][C]201[/C][C]0.469992[/C][C]0.939983[/C][C]0.530008[/C][/ROW]
[ROW][C]202[/C][C]0.64459[/C][C]0.71082[/C][C]0.35541[/C][/ROW]
[ROW][C]203[/C][C]0.610467[/C][C]0.779066[/C][C]0.389533[/C][/ROW]
[ROW][C]204[/C][C]0.572944[/C][C]0.854113[/C][C]0.427056[/C][/ROW]
[ROW][C]205[/C][C]0.533111[/C][C]0.933777[/C][C]0.466889[/C][/ROW]
[ROW][C]206[/C][C]0.493966[/C][C]0.987931[/C][C]0.506034[/C][/ROW]
[ROW][C]207[/C][C]0.451446[/C][C]0.902892[/C][C]0.548554[/C][/ROW]
[ROW][C]208[/C][C]0.408056[/C][C]0.816113[/C][C]0.591944[/C][/ROW]
[ROW][C]209[/C][C]0.387275[/C][C]0.774551[/C][C]0.612725[/C][/ROW]
[ROW][C]210[/C][C]0.347981[/C][C]0.695961[/C][C]0.652019[/C][/ROW]
[ROW][C]211[/C][C]0.309432[/C][C]0.618864[/C][C]0.690568[/C][/ROW]
[ROW][C]212[/C][C]0.277716[/C][C]0.555433[/C][C]0.722284[/C][/ROW]
[ROW][C]213[/C][C]0.319413[/C][C]0.638825[/C][C]0.680587[/C][/ROW]
[ROW][C]214[/C][C]0.305916[/C][C]0.611832[/C][C]0.694084[/C][/ROW]
[ROW][C]215[/C][C]0.267381[/C][C]0.534761[/C][C]0.732619[/C][/ROW]
[ROW][C]216[/C][C]0.23495[/C][C]0.469899[/C][C]0.76505[/C][/ROW]
[ROW][C]217[/C][C]0.210125[/C][C]0.42025[/C][C]0.789875[/C][/ROW]
[ROW][C]218[/C][C]0.241998[/C][C]0.483995[/C][C]0.758002[/C][/ROW]
[ROW][C]219[/C][C]0.213003[/C][C]0.426005[/C][C]0.786997[/C][/ROW]
[ROW][C]220[/C][C]0.183609[/C][C]0.367218[/C][C]0.816391[/C][/ROW]
[ROW][C]221[/C][C]0.15884[/C][C]0.317681[/C][C]0.84116[/C][/ROW]
[ROW][C]222[/C][C]0.150121[/C][C]0.300242[/C][C]0.849879[/C][/ROW]
[ROW][C]223[/C][C]0.123635[/C][C]0.24727[/C][C]0.876365[/C][/ROW]
[ROW][C]224[/C][C]0.106259[/C][C]0.212518[/C][C]0.893741[/C][/ROW]
[ROW][C]225[/C][C]0.0862642[/C][C]0.172528[/C][C]0.913736[/C][/ROW]
[ROW][C]226[/C][C]0.0972283[/C][C]0.194457[/C][C]0.902772[/C][/ROW]
[ROW][C]227[/C][C]0.0845299[/C][C]0.16906[/C][C]0.91547[/C][/ROW]
[ROW][C]228[/C][C]0.0672991[/C][C]0.134598[/C][C]0.932701[/C][/ROW]
[ROW][C]229[/C][C]0.0526382[/C][C]0.105276[/C][C]0.947362[/C][/ROW]
[ROW][C]230[/C][C]0.0407204[/C][C]0.0814408[/C][C]0.95928[/C][/ROW]
[ROW][C]231[/C][C]0.0341157[/C][C]0.0682314[/C][C]0.965884[/C][/ROW]
[ROW][C]232[/C][C]0.0412391[/C][C]0.0824782[/C][C]0.958761[/C][/ROW]
[ROW][C]233[/C][C]0.0337888[/C][C]0.0675776[/C][C]0.966211[/C][/ROW]
[ROW][C]234[/C][C]0.144086[/C][C]0.288172[/C][C]0.855914[/C][/ROW]
[ROW][C]235[/C][C]0.118151[/C][C]0.236302[/C][C]0.881849[/C][/ROW]
[ROW][C]236[/C][C]0.120438[/C][C]0.240876[/C][C]0.879562[/C][/ROW]
[ROW][C]237[/C][C]0.11807[/C][C]0.236139[/C][C]0.88193[/C][/ROW]
[ROW][C]238[/C][C]0.267463[/C][C]0.534925[/C][C]0.732537[/C][/ROW]
[ROW][C]239[/C][C]0.226861[/C][C]0.453722[/C][C]0.773139[/C][/ROW]
[ROW][C]240[/C][C]0.325383[/C][C]0.650766[/C][C]0.674617[/C][/ROW]
[ROW][C]241[/C][C]0.43523[/C][C]0.87046[/C][C]0.56477[/C][/ROW]
[ROW][C]242[/C][C]0.3683[/C][C]0.7366[/C][C]0.6317[/C][/ROW]
[ROW][C]243[/C][C]0.312286[/C][C]0.624571[/C][C]0.687714[/C][/ROW]
[ROW][C]244[/C][C]0.27057[/C][C]0.541139[/C][C]0.72943[/C][/ROW]
[ROW][C]245[/C][C]0.523699[/C][C]0.952603[/C][C]0.476301[/C][/ROW]
[ROW][C]246[/C][C]0.767385[/C][C]0.465231[/C][C]0.232615[/C][/ROW]
[ROW][C]247[/C][C]0.738791[/C][C]0.522418[/C][C]0.261209[/C][/ROW]
[ROW][C]248[/C][C]0.721304[/C][C]0.557393[/C][C]0.278696[/C][/ROW]
[ROW][C]249[/C][C]0.759126[/C][C]0.481748[/C][C]0.240874[/C][/ROW]
[ROW][C]250[/C][C]0.702827[/C][C]0.594346[/C][C]0.297173[/C][/ROW]
[ROW][C]251[/C][C]0.682201[/C][C]0.635599[/C][C]0.317799[/C][/ROW]
[ROW][C]252[/C][C]0.57737[/C][C]0.845261[/C][C]0.42263[/C][/ROW]
[ROW][C]253[/C][C]0.491506[/C][C]0.983012[/C][C]0.508494[/C][/ROW]
[ROW][C]254[/C][C]0.450083[/C][C]0.900166[/C][C]0.549917[/C][/ROW]
[ROW][C]255[/C][C]0.457373[/C][C]0.914747[/C][C]0.542627[/C][/ROW]
[ROW][C]256[/C][C]0.347688[/C][C]0.695376[/C][C]0.652312[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253397&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253397&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.3975460.7950930.602454
90.2584710.5169420.741529
100.1529150.305830.847085
110.1053970.2107950.894603
120.5628160.8743690.437184
130.6444410.7111190.355559
140.5553240.8893530.444676
150.4908420.9816840.509158
160.5768310.8463390.423169
170.5028310.9943390.497169
180.4751780.9503550.524822
190.4355580.8711170.564442
200.489910.9798190.51009
210.5286380.9427250.471362
220.4886840.9773680.511316
230.4377680.8755360.562232
240.3700350.7400690.629965
250.4085410.8170820.591459
260.6133310.7733380.386669
270.5514990.8970020.448501
280.5414460.9171080.458554
290.5116410.9767180.488359
300.4528310.9056630.547169
310.4576290.9152570.542371
320.5724290.8551420.427571
330.5704140.8591710.429586
340.539910.9201790.46009
350.487530.975060.51247
360.4340840.8681680.565916
370.3955580.7911160.604442
380.3619390.7238770.638061
390.4592050.918410.540795
400.4088550.8177090.591145
410.3863350.7726710.613665
420.3380760.6761530.661924
430.3090040.6180080.690996
440.2738670.5477340.726133
450.3428960.6857930.657104
460.364140.728280.63586
470.337150.6743010.66285
480.3089360.6178710.691064
490.2690520.5381030.730948
500.2920130.5840270.707987
510.3213190.6426370.678681
520.2906410.5812830.709359
530.2579140.5158280.742086
540.2339420.4678840.766058
550.200440.4008810.79956
560.1844220.3688430.815578
570.1938980.3877950.806102
580.2813650.562730.718635
590.2563530.5127050.743647
600.2228090.4456190.777191
610.1986840.3973680.801316
620.1922950.3845910.807705
630.168750.3375010.83125
640.1684670.3369340.831533
650.1443420.2886850.855658
660.1239740.2479470.876026
670.104480.2089590.89552
680.1104380.2208770.889562
690.1102450.2204910.889755
700.09363080.1872620.906369
710.1000170.2000330.899983
720.1204860.2409710.879514
730.1203280.2406570.879672
740.1014130.2028250.898587
750.08791480.175830.912085
760.1151550.230310.884845
770.09833910.1966780.901661
780.08292120.1658420.917079
790.1156180.2312370.884382
800.1418280.2836560.858172
810.1344480.2688970.865552
820.1153690.2307390.884631
830.1083940.2167880.891606
840.1027990.2055980.897201
850.08892140.1778430.911079
860.07990690.1598140.920093
870.07053150.1410630.929469
880.08685940.1737190.913141
890.07321160.1464230.926788
900.07788130.1557630.922119
910.07101560.1420310.928984
920.06382980.127660.93617
930.05447990.108960.94552
940.05815170.1163030.941848
950.05901110.1180220.940989
960.05328570.1065710.946714
970.04558590.09117180.954414
980.04017280.08034550.959827
990.03904580.07809160.960954
1000.03544940.07089870.964551
1010.03159870.06319740.968401
1020.02652530.05305060.973475
1030.02189120.04378240.978109
1040.02268630.04537260.977314
1050.04926620.09853240.950734
1060.04637890.09275770.953621
1070.05610920.1122180.943891
1080.0489880.09797590.951012
1090.08695160.1739030.913048
1100.1040950.208190.895905
1110.103130.2062590.89687
1120.1322210.2644430.867779
1130.1200870.2401740.879913
1140.1153430.2306860.884657
1150.1101490.2202970.889851
1160.1097710.2195420.890229
1170.1019490.2038990.898051
1180.08938520.178770.910615
1190.08384320.1676860.916157
1200.07466370.1493270.925336
1210.06602960.1320590.93397
1220.05891980.117840.94108
1230.04971840.09943670.950282
1240.04731240.09462480.952688
1250.04675320.09350630.953247
1260.05934040.1186810.94066
1270.1117330.2234670.888267
1280.1051560.2103120.894844
1290.09247470.1849490.907525
1300.08393470.1678690.916065
1310.09503860.1900770.904961
1320.1062810.2125610.893719
1330.1320370.2640750.867963
1340.116260.232520.88374
1350.1015690.2031390.898431
1360.08907080.1781420.910929
1370.07611960.1522390.92388
1380.07862290.1572460.921377
1390.06809940.1361990.931901
1400.06595410.1319080.934046
1410.06006380.1201280.939936
1420.08399710.1679940.916003
1430.1032790.2065570.896721
1440.09576810.1915360.904232
1450.1677560.3355130.832244
1460.1557910.3115820.844209
1470.1394080.2788160.860592
1480.1228620.2457240.877138
1490.1134330.2268660.886567
1500.1019660.2039320.898034
1510.1534870.3069750.846513
1520.1408130.2816270.859187
1530.1245170.2490340.875483
1540.1372480.2744960.862752
1550.1188890.2377790.881111
1560.1187760.2375510.881224
1570.1190140.2380280.880986
1580.1109290.2218580.889071
1590.0975930.1951860.902407
1600.1041690.2083370.895831
1610.08975510.179510.910245
1620.08653870.1730770.913461
1630.07528790.1505760.924712
1640.08595820.1719160.914042
1650.07822650.1564530.921774
1660.14970.29940.8503
1670.1510170.3020340.848983
1680.1493480.2986950.850652
1690.1353070.2706130.864693
1700.2633110.5266220.736689
1710.3002390.6004770.699761
1720.2697010.5394010.730299
1730.3692950.738590.630705
1740.3347480.6694950.665252
1750.390070.7801390.60993
1760.3731820.7463640.626818
1770.3842350.7684710.615765
1780.3571630.7143270.642837
1790.3290040.6580090.670996
1800.3150670.6301350.684933
1810.2867130.5734260.713287
1820.2867750.5735490.713225
1830.299520.5990410.70048
1840.3524570.7049150.647543
1850.5989970.8020070.401003
1860.5888570.8222870.411143
1870.5735790.8528420.426421
1880.6808730.6382540.319127
1890.66470.6705990.3353
1900.6632660.6734690.336734
1910.6557420.6885160.344258
1920.6205670.7588660.379433
1930.5892650.821470.410735
1940.5493840.9012330.450616
1950.5110360.9779280.488964
1960.4740060.9480110.525994
1970.461120.9222410.53888
1980.4381920.8763840.561808
1990.3975220.7950440.602478
2000.5049980.9900030.495002
2010.4699920.9399830.530008
2020.644590.710820.35541
2030.6104670.7790660.389533
2040.5729440.8541130.427056
2050.5331110.9337770.466889
2060.4939660.9879310.506034
2070.4514460.9028920.548554
2080.4080560.8161130.591944
2090.3872750.7745510.612725
2100.3479810.6959610.652019
2110.3094320.6188640.690568
2120.2777160.5554330.722284
2130.3194130.6388250.680587
2140.3059160.6118320.694084
2150.2673810.5347610.732619
2160.234950.4698990.76505
2170.2101250.420250.789875
2180.2419980.4839950.758002
2190.2130030.4260050.786997
2200.1836090.3672180.816391
2210.158840.3176810.84116
2220.1501210.3002420.849879
2230.1236350.247270.876365
2240.1062590.2125180.893741
2250.08626420.1725280.913736
2260.09722830.1944570.902772
2270.08452990.169060.91547
2280.06729910.1345980.932701
2290.05263820.1052760.947362
2300.04072040.08144080.95928
2310.03411570.06823140.965884
2320.04123910.08247820.958761
2330.03378880.06757760.966211
2340.1440860.2881720.855914
2350.1181510.2363020.881849
2360.1204380.2408760.879562
2370.118070.2361390.88193
2380.2674630.5349250.732537
2390.2268610.4537220.773139
2400.3253830.6507660.674617
2410.435230.870460.56477
2420.36830.73660.6317
2430.3122860.6245710.687714
2440.270570.5411390.72943
2450.5236990.9526030.476301
2460.7673850.4652310.232615
2470.7387910.5224180.261209
2480.7213040.5573930.278696
2490.7591260.4817480.240874
2500.7028270.5943460.297173
2510.6822010.6355990.317799
2520.577370.8452610.42263
2530.4915060.9830120.508494
2540.4500830.9001660.549917
2550.4573730.9147470.542627
2560.3476880.6953760.652312






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00803213OK
10% type I error level180.0722892OK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 2 & 0.00803213 & OK \tabularnewline
10% type I error level & 18 & 0.0722892 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253397&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]2[/C][C]0.00803213[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]18[/C][C]0.0722892[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253397&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253397&T=6

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00803213OK
10% type I error level180.0722892OK


Figures (Output of Computation)

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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')
}