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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 12 Dec 2014 11:18:34 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/12/t1418383224s0wmc3cdsthqbck.htm/, Retrieved Thu, 31 Oct 2024 22:56:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266521, Retrieved Thu, 31 Oct 2024 22:56:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-12 11:18:34] [d3a85ea23f6d8881e8b5a834ebd3a404] [Current]
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Dataseries X:
13 50
8 62
14 54
16 71
14 54
13 65
15 73
13 52
20 84
17 42
15 66
16 65
12 78
17 73
11 75
16 72
16 66
15 70
13 61
14 81
19 71
16 69
17 71
10 72
15 68
14 70
14 68
16 61
15 67
17 76
14 70
16 60
15 72
16 69
16 71
10 62
8 70
17 64
14 58
10 76
14 52
12 59
16 68
16 76
16 65
8 67
16 59
15 69
8 76
13 63
14 75
13 63
16 60
19 73
19 63
14 70
15 75
13 66
10 63
16 63
15 64
11 70
9 75
16 61
12 60
12 62
14 73
14 61
13 66
15 64
17 59
14 64
11 60
9 56
7 78
13 53
15 67
12 59
15 66
14 68
16 71
14 66
13 73
16 72
13 71
16 59
16 64
16 66
10 78
12 68
12 73
12 62
12 65
19 68
14 65
13 60
16 71
15 65
12 68
8 64
10 74
16 69
16 76
10 68
18 72
12 67
16 63
10 59
14 73
12 66
11 62
15 69
7 66
16 51
16 56
16 67
16 69
12 57
15 56
14 55
15 63
16 67
13 65
10 47
17 76
15 64
18 68
16 64
20 65
16 71
17 63
16 60
15 68
13 72
16 70
16 61
16 61
17 62
20 71
14 71
17 51
6 56
16 70
15 73
16 76
16 68
14 48
16 52
16 60
16 59
14 57
14 79
16 60
16 60
15 59
16 62
16 59
18 61
15 71
16 57
16 66
16 63
17 69
14 58
18 59
9 48
15 66
14 73
15 67
13 61
16 68
20 75
14 62
12 69
15 58
15 60
15 74
16 55
11 62
16 63
7 69
11 58
9 58
15 68
16 72
14 62
15 62
13 65
13 69
12 66
16 72
14 62
16 75
14 58
15 66
10 55
16 47
14 72
16 62
12 64
16 64
16 19
15 50
14 68
16 70
11 79
15 69
18 71
13 48
7 73
7 74
17 66
18 71
15 74
8 78
13 75
13 53
15 60
18 70
16 69
14 65
15 78
19 78
16 59
12 72
16 70
11 63
16 63
15 71
19 74
15 67
14 66
14 62
17 80
16 73
20 67
16 61
9 73
13 74
15 32
19 69
16 69
17 84
16 64
9 58
11 59
14 78
19 57
13 60
14 68
15 68
15 73
14 69
16 67
17 60
12 65
15 66
17 74
15 81
10 72
16 55
15 49
11 74
16 53
16 64
16 65
14 57
14 51
16 80
16 67
18 70
14 74
20 75
15 70
16 69
16 65
16 55
12 71




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266521&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266521&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266521&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
AMS.E[t] = + 64.0974 + 0.0983802CONFSTATTOT[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
AMS.E[t] =  +  64.0974 +  0.0983802CONFSTATTOT[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266521&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]AMS.E[t] =  +  64.0974 +  0.0983802CONFSTATTOT[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266521&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266521&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
AMS.E[t] = + 64.0974 + 0.0983802CONFSTATTOT[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)64.09742.6610624.098.23036e-704.11518e-70
CONFSTATTOT0.09838020.181580.54180.5883930.294196

\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) & 64.0974 & 2.66106 & 24.09 & 8.23036e-70 & 4.11518e-70 \tabularnewline
CONFSTATTOT & 0.0983802 & 0.18158 & 0.5418 & 0.588393 & 0.294196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266521&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]64.0974[/C][C]2.66106[/C][C]24.09[/C][C]8.23036e-70[/C][C]4.11518e-70[/C][/ROW]
[ROW][C]CONFSTATTOT[/C][C]0.0983802[/C][C]0.18158[/C][C]0.5418[/C][C]0.588393[/C][C]0.294196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266521&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266521&T=2

As an alternative you can also use a 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)64.09742.6610624.098.23036e-704.11518e-70
CONFSTATTOT0.09838020.181580.54180.5883930.294196







Multiple Linear Regression - Regression Statistics
Multiple R0.0325953
R-squared0.00106245
Adjusted R-squared-0.00255689
F-TEST (value)0.293549
F-TEST (DF numerator)1
F-TEST (DF denominator)276
p-value0.588393
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation8.19503
Sum Squared Residuals18535.7

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.0325953 \tabularnewline
R-squared & 0.00106245 \tabularnewline
Adjusted R-squared & -0.00255689 \tabularnewline
F-TEST (value) & 0.293549 \tabularnewline
F-TEST (DF numerator) & 1 \tabularnewline
F-TEST (DF denominator) & 276 \tabularnewline
p-value & 0.588393 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 8.19503 \tabularnewline
Sum Squared Residuals & 18535.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266521&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.0325953[/C][/ROW]
[ROW][C]R-squared[/C][C]0.00106245[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]-0.00255689[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]0.293549[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]1[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]276[/C][/ROW]
[ROW][C]p-value[/C][C]0.588393[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]8.19503[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]18535.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266521&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266521&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.0325953
R-squared0.00106245
Adjusted R-squared-0.00255689
F-TEST (value)0.293549
F-TEST (DF numerator)1
F-TEST (DF denominator)276
p-value0.588393
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation8.19503
Sum Squared Residuals18535.7







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
15065.3764-15.3764
26264.8845-2.88447
35465.4748-11.4748
47165.67155.32849
55465.4748-11.4748
66565.3764-0.376373
77365.57317.42687
85265.3764-13.3764
98466.06517.935
104265.7699-23.7699
116665.57310.426866
126565.6715-0.671514
137865.27812.722
147365.76997.23011
157565.17969.82039
167265.67156.32849
176665.67150.328486
187065.57314.42687
196165.3764-4.37637
208165.474815.5252
217165.96675.03335
226965.67153.32849
237165.76995.23011
247265.08126.91877
256865.57312.42687
267065.47484.52525
276865.47482.52525
286165.6715-4.67151
296765.57311.42687
307665.769910.2301
317065.47484.52525
326065.6715-5.67151
337265.57316.42687
346965.67153.32849
357165.67155.32849
366265.0812-3.08123
377064.88455.11553
386465.7699-1.76989
395865.4748-7.47475
407665.081210.9188
415265.4748-13.4748
425965.278-6.27799
436865.67152.32849
447665.671510.3285
456565.6715-0.671514
466764.88452.11553
475965.6715-6.67151
486965.57313.42687
497664.884511.1155
506365.3764-2.37637
517565.47489.52525
526365.3764-2.37637
536065.6715-5.67151
547365.96677.03335
556365.9667-2.96665
567065.47484.52525
577565.57319.42687
586665.37640.623627
596365.0812-2.08123
606365.6715-2.67151
616465.5731-1.57313
627065.17964.82039
637564.982910.0171
646165.6715-4.67151
656065.278-5.27799
666265.278-3.27799
677365.47487.52525
686165.4748-4.47475
696665.37640.623627
706465.5731-1.57313
715965.7699-6.76989
726465.4748-1.47475
736065.1796-5.17961
745664.9829-8.98285
757864.786113.2139
765365.3764-12.3764
776765.57311.42687
785965.278-6.27799
796665.57310.426866
806865.47482.52525
817165.67155.32849
826665.47480.525247
837365.37647.62363
847265.67156.32849
857165.37645.62363
865965.6715-6.67151
876465.6715-1.67151
886665.67150.328486
897865.081212.9188
906865.2782.72201
917365.2787.72201
926265.278-3.27799
936565.278-0.277993
946865.96672.03335
956565.4748-0.474753
966065.3764-5.37637
977165.67155.32849
986565.5731-0.573134
996865.2782.72201
1006464.8845-0.884472
1017465.08128.91877
1026965.67153.32849
1037665.671510.3285
1046865.08122.91877
1057265.86836.13173
1066765.2781.72201
1076365.6715-2.67151
1085965.0812-6.08123
1097365.47487.52525
1106665.2780.722007
1116265.1796-3.17961
1126965.57313.42687
1136664.78611.21391
1145165.6715-14.6715
1155665.6715-9.67151
1166765.67151.32849
1176965.67153.32849
1185765.278-8.27799
1195665.5731-9.57313
1205565.4748-10.4748
1216365.5731-2.57313
1226765.67151.32849
1236565.3764-0.376373
1244765.0812-18.0812
1257665.769910.2301
1266465.5731-1.57313
1276865.86832.13173
1286465.6715-1.67151
1296566.065-1.06503
1307165.67155.32849
1316365.7699-2.76989
1326065.6715-5.67151
1336865.57312.42687
1347265.37646.62363
1357065.67154.32849
1366165.6715-4.67151
1376165.6715-4.67151
1386265.7699-3.76989
1397166.0654.93497
1407165.47485.52525
1415165.7699-14.7699
1425664.6877-8.68771
1437065.67154.32849
1447365.57317.42687
1457665.671510.3285
1466865.67152.32849
1474865.4748-17.4748
1485265.6715-13.6715
1496065.6715-5.67151
1505965.6715-6.67151
1515765.4748-8.47475
1527965.474813.5252
1536065.6715-5.67151
1546065.6715-5.67151
1555965.5731-6.57313
1566265.6715-3.67151
1575965.6715-6.67151
1586165.8683-4.86827
1597165.57315.42687
1605765.6715-8.67151
1616665.67150.328486
1626365.6715-2.67151
1636965.76993.23011
1645865.4748-7.47475
1655965.8683-6.86827
1664864.9829-16.9829
1676665.57310.426866
1687365.47487.52525
1696765.57311.42687
1706165.3764-4.37637
1716865.67152.32849
1727566.0658.93497
1736265.4748-3.47475
1746965.2783.72201
1755865.5731-7.57313
1766065.5731-5.57313
1777465.57318.42687
1785565.6715-10.6715
1796265.1796-3.17961
1806365.6715-2.67151
1816964.78614.21391
1825865.1796-7.17961
1835864.9829-6.98285
1846865.57312.42687
1857265.67156.32849
1866265.4748-3.47475
1876265.5731-3.57313
1886565.3764-0.376373
1896965.37643.62363
1906665.2780.722007
1917265.67156.32849
1926265.4748-3.47475
1937565.67159.32849
1945865.4748-7.47475
1956665.57310.426866
1965565.0812-10.0812
1974765.6715-18.6715
1987265.47486.52525
1996265.6715-3.67151
2006465.278-1.27799
2016465.6715-1.67151
2021965.6715-46.6715
2035065.5731-15.5731
2046865.47482.52525
2057065.67154.32849
2067965.179613.8204
2076965.57313.42687
2087165.86835.13173
2094865.3764-17.3764
2107364.78618.21391
2117464.78619.21391
2126665.76990.230106
2137165.86835.13173
2147465.57318.42687
2157864.884513.1155
2167565.37649.62363
2175365.3764-12.3764
2186065.5731-5.57313
2197065.86834.13173
2206965.67153.32849
2216565.4748-0.474753
2227865.573112.4269
2237865.966712.0333
2245965.6715-6.67151
2257265.2786.72201
2267065.67154.32849
2276365.1796-2.17961
2286365.6715-2.67151
2297165.57315.42687
2307465.96678.03335
2316765.57311.42687
2326665.47480.525247
2336265.4748-3.47475
2348065.769914.2301
2357365.67157.32849
2366766.0650.934965
2376165.6715-4.67151
2387364.98298.01715
2397465.37648.62363
2403265.5731-33.5731
2416965.96673.03335
2426965.67153.32849
2438465.769918.2301
2446465.6715-1.67151
2455864.9829-6.98285
2465965.1796-6.17961
2477865.474812.5252
2485765.9667-8.96665
2496065.3764-5.37637
2506865.47482.52525
2516865.57312.42687
2527365.57317.42687
2536965.47483.52525
2546765.67151.32849
2556065.7699-5.76989
2566565.278-0.277993
2576665.57310.426866
2587465.76998.23011
2598165.573115.4269
2607265.08126.91877
2615565.6715-10.6715
2624965.5731-16.5731
2637465.17968.82039
2645365.6715-12.6715
2656465.6715-1.67151
2666565.6715-0.671514
2675765.4748-8.47475
2685165.4748-14.4748
2698065.671514.3285
2706765.67151.32849
2717065.86834.13173
2727465.47488.52525
2737566.0658.93497
2747065.57314.42687
2756965.67153.32849
2766565.6715-0.671514
2775565.6715-10.6715
2787165.2785.72201

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 50 & 65.3764 & -15.3764 \tabularnewline
2 & 62 & 64.8845 & -2.88447 \tabularnewline
3 & 54 & 65.4748 & -11.4748 \tabularnewline
4 & 71 & 65.6715 & 5.32849 \tabularnewline
5 & 54 & 65.4748 & -11.4748 \tabularnewline
6 & 65 & 65.3764 & -0.376373 \tabularnewline
7 & 73 & 65.5731 & 7.42687 \tabularnewline
8 & 52 & 65.3764 & -13.3764 \tabularnewline
9 & 84 & 66.065 & 17.935 \tabularnewline
10 & 42 & 65.7699 & -23.7699 \tabularnewline
11 & 66 & 65.5731 & 0.426866 \tabularnewline
12 & 65 & 65.6715 & -0.671514 \tabularnewline
13 & 78 & 65.278 & 12.722 \tabularnewline
14 & 73 & 65.7699 & 7.23011 \tabularnewline
15 & 75 & 65.1796 & 9.82039 \tabularnewline
16 & 72 & 65.6715 & 6.32849 \tabularnewline
17 & 66 & 65.6715 & 0.328486 \tabularnewline
18 & 70 & 65.5731 & 4.42687 \tabularnewline
19 & 61 & 65.3764 & -4.37637 \tabularnewline
20 & 81 & 65.4748 & 15.5252 \tabularnewline
21 & 71 & 65.9667 & 5.03335 \tabularnewline
22 & 69 & 65.6715 & 3.32849 \tabularnewline
23 & 71 & 65.7699 & 5.23011 \tabularnewline
24 & 72 & 65.0812 & 6.91877 \tabularnewline
25 & 68 & 65.5731 & 2.42687 \tabularnewline
26 & 70 & 65.4748 & 4.52525 \tabularnewline
27 & 68 & 65.4748 & 2.52525 \tabularnewline
28 & 61 & 65.6715 & -4.67151 \tabularnewline
29 & 67 & 65.5731 & 1.42687 \tabularnewline
30 & 76 & 65.7699 & 10.2301 \tabularnewline
31 & 70 & 65.4748 & 4.52525 \tabularnewline
32 & 60 & 65.6715 & -5.67151 \tabularnewline
33 & 72 & 65.5731 & 6.42687 \tabularnewline
34 & 69 & 65.6715 & 3.32849 \tabularnewline
35 & 71 & 65.6715 & 5.32849 \tabularnewline
36 & 62 & 65.0812 & -3.08123 \tabularnewline
37 & 70 & 64.8845 & 5.11553 \tabularnewline
38 & 64 & 65.7699 & -1.76989 \tabularnewline
39 & 58 & 65.4748 & -7.47475 \tabularnewline
40 & 76 & 65.0812 & 10.9188 \tabularnewline
41 & 52 & 65.4748 & -13.4748 \tabularnewline
42 & 59 & 65.278 & -6.27799 \tabularnewline
43 & 68 & 65.6715 & 2.32849 \tabularnewline
44 & 76 & 65.6715 & 10.3285 \tabularnewline
45 & 65 & 65.6715 & -0.671514 \tabularnewline
46 & 67 & 64.8845 & 2.11553 \tabularnewline
47 & 59 & 65.6715 & -6.67151 \tabularnewline
48 & 69 & 65.5731 & 3.42687 \tabularnewline
49 & 76 & 64.8845 & 11.1155 \tabularnewline
50 & 63 & 65.3764 & -2.37637 \tabularnewline
51 & 75 & 65.4748 & 9.52525 \tabularnewline
52 & 63 & 65.3764 & -2.37637 \tabularnewline
53 & 60 & 65.6715 & -5.67151 \tabularnewline
54 & 73 & 65.9667 & 7.03335 \tabularnewline
55 & 63 & 65.9667 & -2.96665 \tabularnewline
56 & 70 & 65.4748 & 4.52525 \tabularnewline
57 & 75 & 65.5731 & 9.42687 \tabularnewline
58 & 66 & 65.3764 & 0.623627 \tabularnewline
59 & 63 & 65.0812 & -2.08123 \tabularnewline
60 & 63 & 65.6715 & -2.67151 \tabularnewline
61 & 64 & 65.5731 & -1.57313 \tabularnewline
62 & 70 & 65.1796 & 4.82039 \tabularnewline
63 & 75 & 64.9829 & 10.0171 \tabularnewline
64 & 61 & 65.6715 & -4.67151 \tabularnewline
65 & 60 & 65.278 & -5.27799 \tabularnewline
66 & 62 & 65.278 & -3.27799 \tabularnewline
67 & 73 & 65.4748 & 7.52525 \tabularnewline
68 & 61 & 65.4748 & -4.47475 \tabularnewline
69 & 66 & 65.3764 & 0.623627 \tabularnewline
70 & 64 & 65.5731 & -1.57313 \tabularnewline
71 & 59 & 65.7699 & -6.76989 \tabularnewline
72 & 64 & 65.4748 & -1.47475 \tabularnewline
73 & 60 & 65.1796 & -5.17961 \tabularnewline
74 & 56 & 64.9829 & -8.98285 \tabularnewline
75 & 78 & 64.7861 & 13.2139 \tabularnewline
76 & 53 & 65.3764 & -12.3764 \tabularnewline
77 & 67 & 65.5731 & 1.42687 \tabularnewline
78 & 59 & 65.278 & -6.27799 \tabularnewline
79 & 66 & 65.5731 & 0.426866 \tabularnewline
80 & 68 & 65.4748 & 2.52525 \tabularnewline
81 & 71 & 65.6715 & 5.32849 \tabularnewline
82 & 66 & 65.4748 & 0.525247 \tabularnewline
83 & 73 & 65.3764 & 7.62363 \tabularnewline
84 & 72 & 65.6715 & 6.32849 \tabularnewline
85 & 71 & 65.3764 & 5.62363 \tabularnewline
86 & 59 & 65.6715 & -6.67151 \tabularnewline
87 & 64 & 65.6715 & -1.67151 \tabularnewline
88 & 66 & 65.6715 & 0.328486 \tabularnewline
89 & 78 & 65.0812 & 12.9188 \tabularnewline
90 & 68 & 65.278 & 2.72201 \tabularnewline
91 & 73 & 65.278 & 7.72201 \tabularnewline
92 & 62 & 65.278 & -3.27799 \tabularnewline
93 & 65 & 65.278 & -0.277993 \tabularnewline
94 & 68 & 65.9667 & 2.03335 \tabularnewline
95 & 65 & 65.4748 & -0.474753 \tabularnewline
96 & 60 & 65.3764 & -5.37637 \tabularnewline
97 & 71 & 65.6715 & 5.32849 \tabularnewline
98 & 65 & 65.5731 & -0.573134 \tabularnewline
99 & 68 & 65.278 & 2.72201 \tabularnewline
100 & 64 & 64.8845 & -0.884472 \tabularnewline
101 & 74 & 65.0812 & 8.91877 \tabularnewline
102 & 69 & 65.6715 & 3.32849 \tabularnewline
103 & 76 & 65.6715 & 10.3285 \tabularnewline
104 & 68 & 65.0812 & 2.91877 \tabularnewline
105 & 72 & 65.8683 & 6.13173 \tabularnewline
106 & 67 & 65.278 & 1.72201 \tabularnewline
107 & 63 & 65.6715 & -2.67151 \tabularnewline
108 & 59 & 65.0812 & -6.08123 \tabularnewline
109 & 73 & 65.4748 & 7.52525 \tabularnewline
110 & 66 & 65.278 & 0.722007 \tabularnewline
111 & 62 & 65.1796 & -3.17961 \tabularnewline
112 & 69 & 65.5731 & 3.42687 \tabularnewline
113 & 66 & 64.7861 & 1.21391 \tabularnewline
114 & 51 & 65.6715 & -14.6715 \tabularnewline
115 & 56 & 65.6715 & -9.67151 \tabularnewline
116 & 67 & 65.6715 & 1.32849 \tabularnewline
117 & 69 & 65.6715 & 3.32849 \tabularnewline
118 & 57 & 65.278 & -8.27799 \tabularnewline
119 & 56 & 65.5731 & -9.57313 \tabularnewline
120 & 55 & 65.4748 & -10.4748 \tabularnewline
121 & 63 & 65.5731 & -2.57313 \tabularnewline
122 & 67 & 65.6715 & 1.32849 \tabularnewline
123 & 65 & 65.3764 & -0.376373 \tabularnewline
124 & 47 & 65.0812 & -18.0812 \tabularnewline
125 & 76 & 65.7699 & 10.2301 \tabularnewline
126 & 64 & 65.5731 & -1.57313 \tabularnewline
127 & 68 & 65.8683 & 2.13173 \tabularnewline
128 & 64 & 65.6715 & -1.67151 \tabularnewline
129 & 65 & 66.065 & -1.06503 \tabularnewline
130 & 71 & 65.6715 & 5.32849 \tabularnewline
131 & 63 & 65.7699 & -2.76989 \tabularnewline
132 & 60 & 65.6715 & -5.67151 \tabularnewline
133 & 68 & 65.5731 & 2.42687 \tabularnewline
134 & 72 & 65.3764 & 6.62363 \tabularnewline
135 & 70 & 65.6715 & 4.32849 \tabularnewline
136 & 61 & 65.6715 & -4.67151 \tabularnewline
137 & 61 & 65.6715 & -4.67151 \tabularnewline
138 & 62 & 65.7699 & -3.76989 \tabularnewline
139 & 71 & 66.065 & 4.93497 \tabularnewline
140 & 71 & 65.4748 & 5.52525 \tabularnewline
141 & 51 & 65.7699 & -14.7699 \tabularnewline
142 & 56 & 64.6877 & -8.68771 \tabularnewline
143 & 70 & 65.6715 & 4.32849 \tabularnewline
144 & 73 & 65.5731 & 7.42687 \tabularnewline
145 & 76 & 65.6715 & 10.3285 \tabularnewline
146 & 68 & 65.6715 & 2.32849 \tabularnewline
147 & 48 & 65.4748 & -17.4748 \tabularnewline
148 & 52 & 65.6715 & -13.6715 \tabularnewline
149 & 60 & 65.6715 & -5.67151 \tabularnewline
150 & 59 & 65.6715 & -6.67151 \tabularnewline
151 & 57 & 65.4748 & -8.47475 \tabularnewline
152 & 79 & 65.4748 & 13.5252 \tabularnewline
153 & 60 & 65.6715 & -5.67151 \tabularnewline
154 & 60 & 65.6715 & -5.67151 \tabularnewline
155 & 59 & 65.5731 & -6.57313 \tabularnewline
156 & 62 & 65.6715 & -3.67151 \tabularnewline
157 & 59 & 65.6715 & -6.67151 \tabularnewline
158 & 61 & 65.8683 & -4.86827 \tabularnewline
159 & 71 & 65.5731 & 5.42687 \tabularnewline
160 & 57 & 65.6715 & -8.67151 \tabularnewline
161 & 66 & 65.6715 & 0.328486 \tabularnewline
162 & 63 & 65.6715 & -2.67151 \tabularnewline
163 & 69 & 65.7699 & 3.23011 \tabularnewline
164 & 58 & 65.4748 & -7.47475 \tabularnewline
165 & 59 & 65.8683 & -6.86827 \tabularnewline
166 & 48 & 64.9829 & -16.9829 \tabularnewline
167 & 66 & 65.5731 & 0.426866 \tabularnewline
168 & 73 & 65.4748 & 7.52525 \tabularnewline
169 & 67 & 65.5731 & 1.42687 \tabularnewline
170 & 61 & 65.3764 & -4.37637 \tabularnewline
171 & 68 & 65.6715 & 2.32849 \tabularnewline
172 & 75 & 66.065 & 8.93497 \tabularnewline
173 & 62 & 65.4748 & -3.47475 \tabularnewline
174 & 69 & 65.278 & 3.72201 \tabularnewline
175 & 58 & 65.5731 & -7.57313 \tabularnewline
176 & 60 & 65.5731 & -5.57313 \tabularnewline
177 & 74 & 65.5731 & 8.42687 \tabularnewline
178 & 55 & 65.6715 & -10.6715 \tabularnewline
179 & 62 & 65.1796 & -3.17961 \tabularnewline
180 & 63 & 65.6715 & -2.67151 \tabularnewline
181 & 69 & 64.7861 & 4.21391 \tabularnewline
182 & 58 & 65.1796 & -7.17961 \tabularnewline
183 & 58 & 64.9829 & -6.98285 \tabularnewline
184 & 68 & 65.5731 & 2.42687 \tabularnewline
185 & 72 & 65.6715 & 6.32849 \tabularnewline
186 & 62 & 65.4748 & -3.47475 \tabularnewline
187 & 62 & 65.5731 & -3.57313 \tabularnewline
188 & 65 & 65.3764 & -0.376373 \tabularnewline
189 & 69 & 65.3764 & 3.62363 \tabularnewline
190 & 66 & 65.278 & 0.722007 \tabularnewline
191 & 72 & 65.6715 & 6.32849 \tabularnewline
192 & 62 & 65.4748 & -3.47475 \tabularnewline
193 & 75 & 65.6715 & 9.32849 \tabularnewline
194 & 58 & 65.4748 & -7.47475 \tabularnewline
195 & 66 & 65.5731 & 0.426866 \tabularnewline
196 & 55 & 65.0812 & -10.0812 \tabularnewline
197 & 47 & 65.6715 & -18.6715 \tabularnewline
198 & 72 & 65.4748 & 6.52525 \tabularnewline
199 & 62 & 65.6715 & -3.67151 \tabularnewline
200 & 64 & 65.278 & -1.27799 \tabularnewline
201 & 64 & 65.6715 & -1.67151 \tabularnewline
202 & 19 & 65.6715 & -46.6715 \tabularnewline
203 & 50 & 65.5731 & -15.5731 \tabularnewline
204 & 68 & 65.4748 & 2.52525 \tabularnewline
205 & 70 & 65.6715 & 4.32849 \tabularnewline
206 & 79 & 65.1796 & 13.8204 \tabularnewline
207 & 69 & 65.5731 & 3.42687 \tabularnewline
208 & 71 & 65.8683 & 5.13173 \tabularnewline
209 & 48 & 65.3764 & -17.3764 \tabularnewline
210 & 73 & 64.7861 & 8.21391 \tabularnewline
211 & 74 & 64.7861 & 9.21391 \tabularnewline
212 & 66 & 65.7699 & 0.230106 \tabularnewline
213 & 71 & 65.8683 & 5.13173 \tabularnewline
214 & 74 & 65.5731 & 8.42687 \tabularnewline
215 & 78 & 64.8845 & 13.1155 \tabularnewline
216 & 75 & 65.3764 & 9.62363 \tabularnewline
217 & 53 & 65.3764 & -12.3764 \tabularnewline
218 & 60 & 65.5731 & -5.57313 \tabularnewline
219 & 70 & 65.8683 & 4.13173 \tabularnewline
220 & 69 & 65.6715 & 3.32849 \tabularnewline
221 & 65 & 65.4748 & -0.474753 \tabularnewline
222 & 78 & 65.5731 & 12.4269 \tabularnewline
223 & 78 & 65.9667 & 12.0333 \tabularnewline
224 & 59 & 65.6715 & -6.67151 \tabularnewline
225 & 72 & 65.278 & 6.72201 \tabularnewline
226 & 70 & 65.6715 & 4.32849 \tabularnewline
227 & 63 & 65.1796 & -2.17961 \tabularnewline
228 & 63 & 65.6715 & -2.67151 \tabularnewline
229 & 71 & 65.5731 & 5.42687 \tabularnewline
230 & 74 & 65.9667 & 8.03335 \tabularnewline
231 & 67 & 65.5731 & 1.42687 \tabularnewline
232 & 66 & 65.4748 & 0.525247 \tabularnewline
233 & 62 & 65.4748 & -3.47475 \tabularnewline
234 & 80 & 65.7699 & 14.2301 \tabularnewline
235 & 73 & 65.6715 & 7.32849 \tabularnewline
236 & 67 & 66.065 & 0.934965 \tabularnewline
237 & 61 & 65.6715 & -4.67151 \tabularnewline
238 & 73 & 64.9829 & 8.01715 \tabularnewline
239 & 74 & 65.3764 & 8.62363 \tabularnewline
240 & 32 & 65.5731 & -33.5731 \tabularnewline
241 & 69 & 65.9667 & 3.03335 \tabularnewline
242 & 69 & 65.6715 & 3.32849 \tabularnewline
243 & 84 & 65.7699 & 18.2301 \tabularnewline
244 & 64 & 65.6715 & -1.67151 \tabularnewline
245 & 58 & 64.9829 & -6.98285 \tabularnewline
246 & 59 & 65.1796 & -6.17961 \tabularnewline
247 & 78 & 65.4748 & 12.5252 \tabularnewline
248 & 57 & 65.9667 & -8.96665 \tabularnewline
249 & 60 & 65.3764 & -5.37637 \tabularnewline
250 & 68 & 65.4748 & 2.52525 \tabularnewline
251 & 68 & 65.5731 & 2.42687 \tabularnewline
252 & 73 & 65.5731 & 7.42687 \tabularnewline
253 & 69 & 65.4748 & 3.52525 \tabularnewline
254 & 67 & 65.6715 & 1.32849 \tabularnewline
255 & 60 & 65.7699 & -5.76989 \tabularnewline
256 & 65 & 65.278 & -0.277993 \tabularnewline
257 & 66 & 65.5731 & 0.426866 \tabularnewline
258 & 74 & 65.7699 & 8.23011 \tabularnewline
259 & 81 & 65.5731 & 15.4269 \tabularnewline
260 & 72 & 65.0812 & 6.91877 \tabularnewline
261 & 55 & 65.6715 & -10.6715 \tabularnewline
262 & 49 & 65.5731 & -16.5731 \tabularnewline
263 & 74 & 65.1796 & 8.82039 \tabularnewline
264 & 53 & 65.6715 & -12.6715 \tabularnewline
265 & 64 & 65.6715 & -1.67151 \tabularnewline
266 & 65 & 65.6715 & -0.671514 \tabularnewline
267 & 57 & 65.4748 & -8.47475 \tabularnewline
268 & 51 & 65.4748 & -14.4748 \tabularnewline
269 & 80 & 65.6715 & 14.3285 \tabularnewline
270 & 67 & 65.6715 & 1.32849 \tabularnewline
271 & 70 & 65.8683 & 4.13173 \tabularnewline
272 & 74 & 65.4748 & 8.52525 \tabularnewline
273 & 75 & 66.065 & 8.93497 \tabularnewline
274 & 70 & 65.5731 & 4.42687 \tabularnewline
275 & 69 & 65.6715 & 3.32849 \tabularnewline
276 & 65 & 65.6715 & -0.671514 \tabularnewline
277 & 55 & 65.6715 & -10.6715 \tabularnewline
278 & 71 & 65.278 & 5.72201 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266521&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]50[/C][C]65.3764[/C][C]-15.3764[/C][/ROW]
[ROW][C]2[/C][C]62[/C][C]64.8845[/C][C]-2.88447[/C][/ROW]
[ROW][C]3[/C][C]54[/C][C]65.4748[/C][C]-11.4748[/C][/ROW]
[ROW][C]4[/C][C]71[/C][C]65.6715[/C][C]5.32849[/C][/ROW]
[ROW][C]5[/C][C]54[/C][C]65.4748[/C][C]-11.4748[/C][/ROW]
[ROW][C]6[/C][C]65[/C][C]65.3764[/C][C]-0.376373[/C][/ROW]
[ROW][C]7[/C][C]73[/C][C]65.5731[/C][C]7.42687[/C][/ROW]
[ROW][C]8[/C][C]52[/C][C]65.3764[/C][C]-13.3764[/C][/ROW]
[ROW][C]9[/C][C]84[/C][C]66.065[/C][C]17.935[/C][/ROW]
[ROW][C]10[/C][C]42[/C][C]65.7699[/C][C]-23.7699[/C][/ROW]
[ROW][C]11[/C][C]66[/C][C]65.5731[/C][C]0.426866[/C][/ROW]
[ROW][C]12[/C][C]65[/C][C]65.6715[/C][C]-0.671514[/C][/ROW]
[ROW][C]13[/C][C]78[/C][C]65.278[/C][C]12.722[/C][/ROW]
[ROW][C]14[/C][C]73[/C][C]65.7699[/C][C]7.23011[/C][/ROW]
[ROW][C]15[/C][C]75[/C][C]65.1796[/C][C]9.82039[/C][/ROW]
[ROW][C]16[/C][C]72[/C][C]65.6715[/C][C]6.32849[/C][/ROW]
[ROW][C]17[/C][C]66[/C][C]65.6715[/C][C]0.328486[/C][/ROW]
[ROW][C]18[/C][C]70[/C][C]65.5731[/C][C]4.42687[/C][/ROW]
[ROW][C]19[/C][C]61[/C][C]65.3764[/C][C]-4.37637[/C][/ROW]
[ROW][C]20[/C][C]81[/C][C]65.4748[/C][C]15.5252[/C][/ROW]
[ROW][C]21[/C][C]71[/C][C]65.9667[/C][C]5.03335[/C][/ROW]
[ROW][C]22[/C][C]69[/C][C]65.6715[/C][C]3.32849[/C][/ROW]
[ROW][C]23[/C][C]71[/C][C]65.7699[/C][C]5.23011[/C][/ROW]
[ROW][C]24[/C][C]72[/C][C]65.0812[/C][C]6.91877[/C][/ROW]
[ROW][C]25[/C][C]68[/C][C]65.5731[/C][C]2.42687[/C][/ROW]
[ROW][C]26[/C][C]70[/C][C]65.4748[/C][C]4.52525[/C][/ROW]
[ROW][C]27[/C][C]68[/C][C]65.4748[/C][C]2.52525[/C][/ROW]
[ROW][C]28[/C][C]61[/C][C]65.6715[/C][C]-4.67151[/C][/ROW]
[ROW][C]29[/C][C]67[/C][C]65.5731[/C][C]1.42687[/C][/ROW]
[ROW][C]30[/C][C]76[/C][C]65.7699[/C][C]10.2301[/C][/ROW]
[ROW][C]31[/C][C]70[/C][C]65.4748[/C][C]4.52525[/C][/ROW]
[ROW][C]32[/C][C]60[/C][C]65.6715[/C][C]-5.67151[/C][/ROW]
[ROW][C]33[/C][C]72[/C][C]65.5731[/C][C]6.42687[/C][/ROW]
[ROW][C]34[/C][C]69[/C][C]65.6715[/C][C]3.32849[/C][/ROW]
[ROW][C]35[/C][C]71[/C][C]65.6715[/C][C]5.32849[/C][/ROW]
[ROW][C]36[/C][C]62[/C][C]65.0812[/C][C]-3.08123[/C][/ROW]
[ROW][C]37[/C][C]70[/C][C]64.8845[/C][C]5.11553[/C][/ROW]
[ROW][C]38[/C][C]64[/C][C]65.7699[/C][C]-1.76989[/C][/ROW]
[ROW][C]39[/C][C]58[/C][C]65.4748[/C][C]-7.47475[/C][/ROW]
[ROW][C]40[/C][C]76[/C][C]65.0812[/C][C]10.9188[/C][/ROW]
[ROW][C]41[/C][C]52[/C][C]65.4748[/C][C]-13.4748[/C][/ROW]
[ROW][C]42[/C][C]59[/C][C]65.278[/C][C]-6.27799[/C][/ROW]
[ROW][C]43[/C][C]68[/C][C]65.6715[/C][C]2.32849[/C][/ROW]
[ROW][C]44[/C][C]76[/C][C]65.6715[/C][C]10.3285[/C][/ROW]
[ROW][C]45[/C][C]65[/C][C]65.6715[/C][C]-0.671514[/C][/ROW]
[ROW][C]46[/C][C]67[/C][C]64.8845[/C][C]2.11553[/C][/ROW]
[ROW][C]47[/C][C]59[/C][C]65.6715[/C][C]-6.67151[/C][/ROW]
[ROW][C]48[/C][C]69[/C][C]65.5731[/C][C]3.42687[/C][/ROW]
[ROW][C]49[/C][C]76[/C][C]64.8845[/C][C]11.1155[/C][/ROW]
[ROW][C]50[/C][C]63[/C][C]65.3764[/C][C]-2.37637[/C][/ROW]
[ROW][C]51[/C][C]75[/C][C]65.4748[/C][C]9.52525[/C][/ROW]
[ROW][C]52[/C][C]63[/C][C]65.3764[/C][C]-2.37637[/C][/ROW]
[ROW][C]53[/C][C]60[/C][C]65.6715[/C][C]-5.67151[/C][/ROW]
[ROW][C]54[/C][C]73[/C][C]65.9667[/C][C]7.03335[/C][/ROW]
[ROW][C]55[/C][C]63[/C][C]65.9667[/C][C]-2.96665[/C][/ROW]
[ROW][C]56[/C][C]70[/C][C]65.4748[/C][C]4.52525[/C][/ROW]
[ROW][C]57[/C][C]75[/C][C]65.5731[/C][C]9.42687[/C][/ROW]
[ROW][C]58[/C][C]66[/C][C]65.3764[/C][C]0.623627[/C][/ROW]
[ROW][C]59[/C][C]63[/C][C]65.0812[/C][C]-2.08123[/C][/ROW]
[ROW][C]60[/C][C]63[/C][C]65.6715[/C][C]-2.67151[/C][/ROW]
[ROW][C]61[/C][C]64[/C][C]65.5731[/C][C]-1.57313[/C][/ROW]
[ROW][C]62[/C][C]70[/C][C]65.1796[/C][C]4.82039[/C][/ROW]
[ROW][C]63[/C][C]75[/C][C]64.9829[/C][C]10.0171[/C][/ROW]
[ROW][C]64[/C][C]61[/C][C]65.6715[/C][C]-4.67151[/C][/ROW]
[ROW][C]65[/C][C]60[/C][C]65.278[/C][C]-5.27799[/C][/ROW]
[ROW][C]66[/C][C]62[/C][C]65.278[/C][C]-3.27799[/C][/ROW]
[ROW][C]67[/C][C]73[/C][C]65.4748[/C][C]7.52525[/C][/ROW]
[ROW][C]68[/C][C]61[/C][C]65.4748[/C][C]-4.47475[/C][/ROW]
[ROW][C]69[/C][C]66[/C][C]65.3764[/C][C]0.623627[/C][/ROW]
[ROW][C]70[/C][C]64[/C][C]65.5731[/C][C]-1.57313[/C][/ROW]
[ROW][C]71[/C][C]59[/C][C]65.7699[/C][C]-6.76989[/C][/ROW]
[ROW][C]72[/C][C]64[/C][C]65.4748[/C][C]-1.47475[/C][/ROW]
[ROW][C]73[/C][C]60[/C][C]65.1796[/C][C]-5.17961[/C][/ROW]
[ROW][C]74[/C][C]56[/C][C]64.9829[/C][C]-8.98285[/C][/ROW]
[ROW][C]75[/C][C]78[/C][C]64.7861[/C][C]13.2139[/C][/ROW]
[ROW][C]76[/C][C]53[/C][C]65.3764[/C][C]-12.3764[/C][/ROW]
[ROW][C]77[/C][C]67[/C][C]65.5731[/C][C]1.42687[/C][/ROW]
[ROW][C]78[/C][C]59[/C][C]65.278[/C][C]-6.27799[/C][/ROW]
[ROW][C]79[/C][C]66[/C][C]65.5731[/C][C]0.426866[/C][/ROW]
[ROW][C]80[/C][C]68[/C][C]65.4748[/C][C]2.52525[/C][/ROW]
[ROW][C]81[/C][C]71[/C][C]65.6715[/C][C]5.32849[/C][/ROW]
[ROW][C]82[/C][C]66[/C][C]65.4748[/C][C]0.525247[/C][/ROW]
[ROW][C]83[/C][C]73[/C][C]65.3764[/C][C]7.62363[/C][/ROW]
[ROW][C]84[/C][C]72[/C][C]65.6715[/C][C]6.32849[/C][/ROW]
[ROW][C]85[/C][C]71[/C][C]65.3764[/C][C]5.62363[/C][/ROW]
[ROW][C]86[/C][C]59[/C][C]65.6715[/C][C]-6.67151[/C][/ROW]
[ROW][C]87[/C][C]64[/C][C]65.6715[/C][C]-1.67151[/C][/ROW]
[ROW][C]88[/C][C]66[/C][C]65.6715[/C][C]0.328486[/C][/ROW]
[ROW][C]89[/C][C]78[/C][C]65.0812[/C][C]12.9188[/C][/ROW]
[ROW][C]90[/C][C]68[/C][C]65.278[/C][C]2.72201[/C][/ROW]
[ROW][C]91[/C][C]73[/C][C]65.278[/C][C]7.72201[/C][/ROW]
[ROW][C]92[/C][C]62[/C][C]65.278[/C][C]-3.27799[/C][/ROW]
[ROW][C]93[/C][C]65[/C][C]65.278[/C][C]-0.277993[/C][/ROW]
[ROW][C]94[/C][C]68[/C][C]65.9667[/C][C]2.03335[/C][/ROW]
[ROW][C]95[/C][C]65[/C][C]65.4748[/C][C]-0.474753[/C][/ROW]
[ROW][C]96[/C][C]60[/C][C]65.3764[/C][C]-5.37637[/C][/ROW]
[ROW][C]97[/C][C]71[/C][C]65.6715[/C][C]5.32849[/C][/ROW]
[ROW][C]98[/C][C]65[/C][C]65.5731[/C][C]-0.573134[/C][/ROW]
[ROW][C]99[/C][C]68[/C][C]65.278[/C][C]2.72201[/C][/ROW]
[ROW][C]100[/C][C]64[/C][C]64.8845[/C][C]-0.884472[/C][/ROW]
[ROW][C]101[/C][C]74[/C][C]65.0812[/C][C]8.91877[/C][/ROW]
[ROW][C]102[/C][C]69[/C][C]65.6715[/C][C]3.32849[/C][/ROW]
[ROW][C]103[/C][C]76[/C][C]65.6715[/C][C]10.3285[/C][/ROW]
[ROW][C]104[/C][C]68[/C][C]65.0812[/C][C]2.91877[/C][/ROW]
[ROW][C]105[/C][C]72[/C][C]65.8683[/C][C]6.13173[/C][/ROW]
[ROW][C]106[/C][C]67[/C][C]65.278[/C][C]1.72201[/C][/ROW]
[ROW][C]107[/C][C]63[/C][C]65.6715[/C][C]-2.67151[/C][/ROW]
[ROW][C]108[/C][C]59[/C][C]65.0812[/C][C]-6.08123[/C][/ROW]
[ROW][C]109[/C][C]73[/C][C]65.4748[/C][C]7.52525[/C][/ROW]
[ROW][C]110[/C][C]66[/C][C]65.278[/C][C]0.722007[/C][/ROW]
[ROW][C]111[/C][C]62[/C][C]65.1796[/C][C]-3.17961[/C][/ROW]
[ROW][C]112[/C][C]69[/C][C]65.5731[/C][C]3.42687[/C][/ROW]
[ROW][C]113[/C][C]66[/C][C]64.7861[/C][C]1.21391[/C][/ROW]
[ROW][C]114[/C][C]51[/C][C]65.6715[/C][C]-14.6715[/C][/ROW]
[ROW][C]115[/C][C]56[/C][C]65.6715[/C][C]-9.67151[/C][/ROW]
[ROW][C]116[/C][C]67[/C][C]65.6715[/C][C]1.32849[/C][/ROW]
[ROW][C]117[/C][C]69[/C][C]65.6715[/C][C]3.32849[/C][/ROW]
[ROW][C]118[/C][C]57[/C][C]65.278[/C][C]-8.27799[/C][/ROW]
[ROW][C]119[/C][C]56[/C][C]65.5731[/C][C]-9.57313[/C][/ROW]
[ROW][C]120[/C][C]55[/C][C]65.4748[/C][C]-10.4748[/C][/ROW]
[ROW][C]121[/C][C]63[/C][C]65.5731[/C][C]-2.57313[/C][/ROW]
[ROW][C]122[/C][C]67[/C][C]65.6715[/C][C]1.32849[/C][/ROW]
[ROW][C]123[/C][C]65[/C][C]65.3764[/C][C]-0.376373[/C][/ROW]
[ROW][C]124[/C][C]47[/C][C]65.0812[/C][C]-18.0812[/C][/ROW]
[ROW][C]125[/C][C]76[/C][C]65.7699[/C][C]10.2301[/C][/ROW]
[ROW][C]126[/C][C]64[/C][C]65.5731[/C][C]-1.57313[/C][/ROW]
[ROW][C]127[/C][C]68[/C][C]65.8683[/C][C]2.13173[/C][/ROW]
[ROW][C]128[/C][C]64[/C][C]65.6715[/C][C]-1.67151[/C][/ROW]
[ROW][C]129[/C][C]65[/C][C]66.065[/C][C]-1.06503[/C][/ROW]
[ROW][C]130[/C][C]71[/C][C]65.6715[/C][C]5.32849[/C][/ROW]
[ROW][C]131[/C][C]63[/C][C]65.7699[/C][C]-2.76989[/C][/ROW]
[ROW][C]132[/C][C]60[/C][C]65.6715[/C][C]-5.67151[/C][/ROW]
[ROW][C]133[/C][C]68[/C][C]65.5731[/C][C]2.42687[/C][/ROW]
[ROW][C]134[/C][C]72[/C][C]65.3764[/C][C]6.62363[/C][/ROW]
[ROW][C]135[/C][C]70[/C][C]65.6715[/C][C]4.32849[/C][/ROW]
[ROW][C]136[/C][C]61[/C][C]65.6715[/C][C]-4.67151[/C][/ROW]
[ROW][C]137[/C][C]61[/C][C]65.6715[/C][C]-4.67151[/C][/ROW]
[ROW][C]138[/C][C]62[/C][C]65.7699[/C][C]-3.76989[/C][/ROW]
[ROW][C]139[/C][C]71[/C][C]66.065[/C][C]4.93497[/C][/ROW]
[ROW][C]140[/C][C]71[/C][C]65.4748[/C][C]5.52525[/C][/ROW]
[ROW][C]141[/C][C]51[/C][C]65.7699[/C][C]-14.7699[/C][/ROW]
[ROW][C]142[/C][C]56[/C][C]64.6877[/C][C]-8.68771[/C][/ROW]
[ROW][C]143[/C][C]70[/C][C]65.6715[/C][C]4.32849[/C][/ROW]
[ROW][C]144[/C][C]73[/C][C]65.5731[/C][C]7.42687[/C][/ROW]
[ROW][C]145[/C][C]76[/C][C]65.6715[/C][C]10.3285[/C][/ROW]
[ROW][C]146[/C][C]68[/C][C]65.6715[/C][C]2.32849[/C][/ROW]
[ROW][C]147[/C][C]48[/C][C]65.4748[/C][C]-17.4748[/C][/ROW]
[ROW][C]148[/C][C]52[/C][C]65.6715[/C][C]-13.6715[/C][/ROW]
[ROW][C]149[/C][C]60[/C][C]65.6715[/C][C]-5.67151[/C][/ROW]
[ROW][C]150[/C][C]59[/C][C]65.6715[/C][C]-6.67151[/C][/ROW]
[ROW][C]151[/C][C]57[/C][C]65.4748[/C][C]-8.47475[/C][/ROW]
[ROW][C]152[/C][C]79[/C][C]65.4748[/C][C]13.5252[/C][/ROW]
[ROW][C]153[/C][C]60[/C][C]65.6715[/C][C]-5.67151[/C][/ROW]
[ROW][C]154[/C][C]60[/C][C]65.6715[/C][C]-5.67151[/C][/ROW]
[ROW][C]155[/C][C]59[/C][C]65.5731[/C][C]-6.57313[/C][/ROW]
[ROW][C]156[/C][C]62[/C][C]65.6715[/C][C]-3.67151[/C][/ROW]
[ROW][C]157[/C][C]59[/C][C]65.6715[/C][C]-6.67151[/C][/ROW]
[ROW][C]158[/C][C]61[/C][C]65.8683[/C][C]-4.86827[/C][/ROW]
[ROW][C]159[/C][C]71[/C][C]65.5731[/C][C]5.42687[/C][/ROW]
[ROW][C]160[/C][C]57[/C][C]65.6715[/C][C]-8.67151[/C][/ROW]
[ROW][C]161[/C][C]66[/C][C]65.6715[/C][C]0.328486[/C][/ROW]
[ROW][C]162[/C][C]63[/C][C]65.6715[/C][C]-2.67151[/C][/ROW]
[ROW][C]163[/C][C]69[/C][C]65.7699[/C][C]3.23011[/C][/ROW]
[ROW][C]164[/C][C]58[/C][C]65.4748[/C][C]-7.47475[/C][/ROW]
[ROW][C]165[/C][C]59[/C][C]65.8683[/C][C]-6.86827[/C][/ROW]
[ROW][C]166[/C][C]48[/C][C]64.9829[/C][C]-16.9829[/C][/ROW]
[ROW][C]167[/C][C]66[/C][C]65.5731[/C][C]0.426866[/C][/ROW]
[ROW][C]168[/C][C]73[/C][C]65.4748[/C][C]7.52525[/C][/ROW]
[ROW][C]169[/C][C]67[/C][C]65.5731[/C][C]1.42687[/C][/ROW]
[ROW][C]170[/C][C]61[/C][C]65.3764[/C][C]-4.37637[/C][/ROW]
[ROW][C]171[/C][C]68[/C][C]65.6715[/C][C]2.32849[/C][/ROW]
[ROW][C]172[/C][C]75[/C][C]66.065[/C][C]8.93497[/C][/ROW]
[ROW][C]173[/C][C]62[/C][C]65.4748[/C][C]-3.47475[/C][/ROW]
[ROW][C]174[/C][C]69[/C][C]65.278[/C][C]3.72201[/C][/ROW]
[ROW][C]175[/C][C]58[/C][C]65.5731[/C][C]-7.57313[/C][/ROW]
[ROW][C]176[/C][C]60[/C][C]65.5731[/C][C]-5.57313[/C][/ROW]
[ROW][C]177[/C][C]74[/C][C]65.5731[/C][C]8.42687[/C][/ROW]
[ROW][C]178[/C][C]55[/C][C]65.6715[/C][C]-10.6715[/C][/ROW]
[ROW][C]179[/C][C]62[/C][C]65.1796[/C][C]-3.17961[/C][/ROW]
[ROW][C]180[/C][C]63[/C][C]65.6715[/C][C]-2.67151[/C][/ROW]
[ROW][C]181[/C][C]69[/C][C]64.7861[/C][C]4.21391[/C][/ROW]
[ROW][C]182[/C][C]58[/C][C]65.1796[/C][C]-7.17961[/C][/ROW]
[ROW][C]183[/C][C]58[/C][C]64.9829[/C][C]-6.98285[/C][/ROW]
[ROW][C]184[/C][C]68[/C][C]65.5731[/C][C]2.42687[/C][/ROW]
[ROW][C]185[/C][C]72[/C][C]65.6715[/C][C]6.32849[/C][/ROW]
[ROW][C]186[/C][C]62[/C][C]65.4748[/C][C]-3.47475[/C][/ROW]
[ROW][C]187[/C][C]62[/C][C]65.5731[/C][C]-3.57313[/C][/ROW]
[ROW][C]188[/C][C]65[/C][C]65.3764[/C][C]-0.376373[/C][/ROW]
[ROW][C]189[/C][C]69[/C][C]65.3764[/C][C]3.62363[/C][/ROW]
[ROW][C]190[/C][C]66[/C][C]65.278[/C][C]0.722007[/C][/ROW]
[ROW][C]191[/C][C]72[/C][C]65.6715[/C][C]6.32849[/C][/ROW]
[ROW][C]192[/C][C]62[/C][C]65.4748[/C][C]-3.47475[/C][/ROW]
[ROW][C]193[/C][C]75[/C][C]65.6715[/C][C]9.32849[/C][/ROW]
[ROW][C]194[/C][C]58[/C][C]65.4748[/C][C]-7.47475[/C][/ROW]
[ROW][C]195[/C][C]66[/C][C]65.5731[/C][C]0.426866[/C][/ROW]
[ROW][C]196[/C][C]55[/C][C]65.0812[/C][C]-10.0812[/C][/ROW]
[ROW][C]197[/C][C]47[/C][C]65.6715[/C][C]-18.6715[/C][/ROW]
[ROW][C]198[/C][C]72[/C][C]65.4748[/C][C]6.52525[/C][/ROW]
[ROW][C]199[/C][C]62[/C][C]65.6715[/C][C]-3.67151[/C][/ROW]
[ROW][C]200[/C][C]64[/C][C]65.278[/C][C]-1.27799[/C][/ROW]
[ROW][C]201[/C][C]64[/C][C]65.6715[/C][C]-1.67151[/C][/ROW]
[ROW][C]202[/C][C]19[/C][C]65.6715[/C][C]-46.6715[/C][/ROW]
[ROW][C]203[/C][C]50[/C][C]65.5731[/C][C]-15.5731[/C][/ROW]
[ROW][C]204[/C][C]68[/C][C]65.4748[/C][C]2.52525[/C][/ROW]
[ROW][C]205[/C][C]70[/C][C]65.6715[/C][C]4.32849[/C][/ROW]
[ROW][C]206[/C][C]79[/C][C]65.1796[/C][C]13.8204[/C][/ROW]
[ROW][C]207[/C][C]69[/C][C]65.5731[/C][C]3.42687[/C][/ROW]
[ROW][C]208[/C][C]71[/C][C]65.8683[/C][C]5.13173[/C][/ROW]
[ROW][C]209[/C][C]48[/C][C]65.3764[/C][C]-17.3764[/C][/ROW]
[ROW][C]210[/C][C]73[/C][C]64.7861[/C][C]8.21391[/C][/ROW]
[ROW][C]211[/C][C]74[/C][C]64.7861[/C][C]9.21391[/C][/ROW]
[ROW][C]212[/C][C]66[/C][C]65.7699[/C][C]0.230106[/C][/ROW]
[ROW][C]213[/C][C]71[/C][C]65.8683[/C][C]5.13173[/C][/ROW]
[ROW][C]214[/C][C]74[/C][C]65.5731[/C][C]8.42687[/C][/ROW]
[ROW][C]215[/C][C]78[/C][C]64.8845[/C][C]13.1155[/C][/ROW]
[ROW][C]216[/C][C]75[/C][C]65.3764[/C][C]9.62363[/C][/ROW]
[ROW][C]217[/C][C]53[/C][C]65.3764[/C][C]-12.3764[/C][/ROW]
[ROW][C]218[/C][C]60[/C][C]65.5731[/C][C]-5.57313[/C][/ROW]
[ROW][C]219[/C][C]70[/C][C]65.8683[/C][C]4.13173[/C][/ROW]
[ROW][C]220[/C][C]69[/C][C]65.6715[/C][C]3.32849[/C][/ROW]
[ROW][C]221[/C][C]65[/C][C]65.4748[/C][C]-0.474753[/C][/ROW]
[ROW][C]222[/C][C]78[/C][C]65.5731[/C][C]12.4269[/C][/ROW]
[ROW][C]223[/C][C]78[/C][C]65.9667[/C][C]12.0333[/C][/ROW]
[ROW][C]224[/C][C]59[/C][C]65.6715[/C][C]-6.67151[/C][/ROW]
[ROW][C]225[/C][C]72[/C][C]65.278[/C][C]6.72201[/C][/ROW]
[ROW][C]226[/C][C]70[/C][C]65.6715[/C][C]4.32849[/C][/ROW]
[ROW][C]227[/C][C]63[/C][C]65.1796[/C][C]-2.17961[/C][/ROW]
[ROW][C]228[/C][C]63[/C][C]65.6715[/C][C]-2.67151[/C][/ROW]
[ROW][C]229[/C][C]71[/C][C]65.5731[/C][C]5.42687[/C][/ROW]
[ROW][C]230[/C][C]74[/C][C]65.9667[/C][C]8.03335[/C][/ROW]
[ROW][C]231[/C][C]67[/C][C]65.5731[/C][C]1.42687[/C][/ROW]
[ROW][C]232[/C][C]66[/C][C]65.4748[/C][C]0.525247[/C][/ROW]
[ROW][C]233[/C][C]62[/C][C]65.4748[/C][C]-3.47475[/C][/ROW]
[ROW][C]234[/C][C]80[/C][C]65.7699[/C][C]14.2301[/C][/ROW]
[ROW][C]235[/C][C]73[/C][C]65.6715[/C][C]7.32849[/C][/ROW]
[ROW][C]236[/C][C]67[/C][C]66.065[/C][C]0.934965[/C][/ROW]
[ROW][C]237[/C][C]61[/C][C]65.6715[/C][C]-4.67151[/C][/ROW]
[ROW][C]238[/C][C]73[/C][C]64.9829[/C][C]8.01715[/C][/ROW]
[ROW][C]239[/C][C]74[/C][C]65.3764[/C][C]8.62363[/C][/ROW]
[ROW][C]240[/C][C]32[/C][C]65.5731[/C][C]-33.5731[/C][/ROW]
[ROW][C]241[/C][C]69[/C][C]65.9667[/C][C]3.03335[/C][/ROW]
[ROW][C]242[/C][C]69[/C][C]65.6715[/C][C]3.32849[/C][/ROW]
[ROW][C]243[/C][C]84[/C][C]65.7699[/C][C]18.2301[/C][/ROW]
[ROW][C]244[/C][C]64[/C][C]65.6715[/C][C]-1.67151[/C][/ROW]
[ROW][C]245[/C][C]58[/C][C]64.9829[/C][C]-6.98285[/C][/ROW]
[ROW][C]246[/C][C]59[/C][C]65.1796[/C][C]-6.17961[/C][/ROW]
[ROW][C]247[/C][C]78[/C][C]65.4748[/C][C]12.5252[/C][/ROW]
[ROW][C]248[/C][C]57[/C][C]65.9667[/C][C]-8.96665[/C][/ROW]
[ROW][C]249[/C][C]60[/C][C]65.3764[/C][C]-5.37637[/C][/ROW]
[ROW][C]250[/C][C]68[/C][C]65.4748[/C][C]2.52525[/C][/ROW]
[ROW][C]251[/C][C]68[/C][C]65.5731[/C][C]2.42687[/C][/ROW]
[ROW][C]252[/C][C]73[/C][C]65.5731[/C][C]7.42687[/C][/ROW]
[ROW][C]253[/C][C]69[/C][C]65.4748[/C][C]3.52525[/C][/ROW]
[ROW][C]254[/C][C]67[/C][C]65.6715[/C][C]1.32849[/C][/ROW]
[ROW][C]255[/C][C]60[/C][C]65.7699[/C][C]-5.76989[/C][/ROW]
[ROW][C]256[/C][C]65[/C][C]65.278[/C][C]-0.277993[/C][/ROW]
[ROW][C]257[/C][C]66[/C][C]65.5731[/C][C]0.426866[/C][/ROW]
[ROW][C]258[/C][C]74[/C][C]65.7699[/C][C]8.23011[/C][/ROW]
[ROW][C]259[/C][C]81[/C][C]65.5731[/C][C]15.4269[/C][/ROW]
[ROW][C]260[/C][C]72[/C][C]65.0812[/C][C]6.91877[/C][/ROW]
[ROW][C]261[/C][C]55[/C][C]65.6715[/C][C]-10.6715[/C][/ROW]
[ROW][C]262[/C][C]49[/C][C]65.5731[/C][C]-16.5731[/C][/ROW]
[ROW][C]263[/C][C]74[/C][C]65.1796[/C][C]8.82039[/C][/ROW]
[ROW][C]264[/C][C]53[/C][C]65.6715[/C][C]-12.6715[/C][/ROW]
[ROW][C]265[/C][C]64[/C][C]65.6715[/C][C]-1.67151[/C][/ROW]
[ROW][C]266[/C][C]65[/C][C]65.6715[/C][C]-0.671514[/C][/ROW]
[ROW][C]267[/C][C]57[/C][C]65.4748[/C][C]-8.47475[/C][/ROW]
[ROW][C]268[/C][C]51[/C][C]65.4748[/C][C]-14.4748[/C][/ROW]
[ROW][C]269[/C][C]80[/C][C]65.6715[/C][C]14.3285[/C][/ROW]
[ROW][C]270[/C][C]67[/C][C]65.6715[/C][C]1.32849[/C][/ROW]
[ROW][C]271[/C][C]70[/C][C]65.8683[/C][C]4.13173[/C][/ROW]
[ROW][C]272[/C][C]74[/C][C]65.4748[/C][C]8.52525[/C][/ROW]
[ROW][C]273[/C][C]75[/C][C]66.065[/C][C]8.93497[/C][/ROW]
[ROW][C]274[/C][C]70[/C][C]65.5731[/C][C]4.42687[/C][/ROW]
[ROW][C]275[/C][C]69[/C][C]65.6715[/C][C]3.32849[/C][/ROW]
[ROW][C]276[/C][C]65[/C][C]65.6715[/C][C]-0.671514[/C][/ROW]
[ROW][C]277[/C][C]55[/C][C]65.6715[/C][C]-10.6715[/C][/ROW]
[ROW][C]278[/C][C]71[/C][C]65.278[/C][C]5.72201[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266521&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266521&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
15065.3764-15.3764
26264.8845-2.88447
35465.4748-11.4748
47165.67155.32849
55465.4748-11.4748
66565.3764-0.376373
77365.57317.42687
85265.3764-13.3764
98466.06517.935
104265.7699-23.7699
116665.57310.426866
126565.6715-0.671514
137865.27812.722
147365.76997.23011
157565.17969.82039
167265.67156.32849
176665.67150.328486
187065.57314.42687
196165.3764-4.37637
208165.474815.5252
217165.96675.03335
226965.67153.32849
237165.76995.23011
247265.08126.91877
256865.57312.42687
267065.47484.52525
276865.47482.52525
286165.6715-4.67151
296765.57311.42687
307665.769910.2301
317065.47484.52525
326065.6715-5.67151
337265.57316.42687
346965.67153.32849
357165.67155.32849
366265.0812-3.08123
377064.88455.11553
386465.7699-1.76989
395865.4748-7.47475
407665.081210.9188
415265.4748-13.4748
425965.278-6.27799
436865.67152.32849
447665.671510.3285
456565.6715-0.671514
466764.88452.11553
475965.6715-6.67151
486965.57313.42687
497664.884511.1155
506365.3764-2.37637
517565.47489.52525
526365.3764-2.37637
536065.6715-5.67151
547365.96677.03335
556365.9667-2.96665
567065.47484.52525
577565.57319.42687
586665.37640.623627
596365.0812-2.08123
606365.6715-2.67151
616465.5731-1.57313
627065.17964.82039
637564.982910.0171
646165.6715-4.67151
656065.278-5.27799
666265.278-3.27799
677365.47487.52525
686165.4748-4.47475
696665.37640.623627
706465.5731-1.57313
715965.7699-6.76989
726465.4748-1.47475
736065.1796-5.17961
745664.9829-8.98285
757864.786113.2139
765365.3764-12.3764
776765.57311.42687
785965.278-6.27799
796665.57310.426866
806865.47482.52525
817165.67155.32849
826665.47480.525247
837365.37647.62363
847265.67156.32849
857165.37645.62363
865965.6715-6.67151
876465.6715-1.67151
886665.67150.328486
897865.081212.9188
906865.2782.72201
917365.2787.72201
926265.278-3.27799
936565.278-0.277993
946865.96672.03335
956565.4748-0.474753
966065.3764-5.37637
977165.67155.32849
986565.5731-0.573134
996865.2782.72201
1006464.8845-0.884472
1017465.08128.91877
1026965.67153.32849
1037665.671510.3285
1046865.08122.91877
1057265.86836.13173
1066765.2781.72201
1076365.6715-2.67151
1085965.0812-6.08123
1097365.47487.52525
1106665.2780.722007
1116265.1796-3.17961
1126965.57313.42687
1136664.78611.21391
1145165.6715-14.6715
1155665.6715-9.67151
1166765.67151.32849
1176965.67153.32849
1185765.278-8.27799
1195665.5731-9.57313
1205565.4748-10.4748
1216365.5731-2.57313
1226765.67151.32849
1236565.3764-0.376373
1244765.0812-18.0812
1257665.769910.2301
1266465.5731-1.57313
1276865.86832.13173
1286465.6715-1.67151
1296566.065-1.06503
1307165.67155.32849
1316365.7699-2.76989
1326065.6715-5.67151
1336865.57312.42687
1347265.37646.62363
1357065.67154.32849
1366165.6715-4.67151
1376165.6715-4.67151
1386265.7699-3.76989
1397166.0654.93497
1407165.47485.52525
1415165.7699-14.7699
1425664.6877-8.68771
1437065.67154.32849
1447365.57317.42687
1457665.671510.3285
1466865.67152.32849
1474865.4748-17.4748
1485265.6715-13.6715
1496065.6715-5.67151
1505965.6715-6.67151
1515765.4748-8.47475
1527965.474813.5252
1536065.6715-5.67151
1546065.6715-5.67151
1555965.5731-6.57313
1566265.6715-3.67151
1575965.6715-6.67151
1586165.8683-4.86827
1597165.57315.42687
1605765.6715-8.67151
1616665.67150.328486
1626365.6715-2.67151
1636965.76993.23011
1645865.4748-7.47475
1655965.8683-6.86827
1664864.9829-16.9829
1676665.57310.426866
1687365.47487.52525
1696765.57311.42687
1706165.3764-4.37637
1716865.67152.32849
1727566.0658.93497
1736265.4748-3.47475
1746965.2783.72201
1755865.5731-7.57313
1766065.5731-5.57313
1777465.57318.42687
1785565.6715-10.6715
1796265.1796-3.17961
1806365.6715-2.67151
1816964.78614.21391
1825865.1796-7.17961
1835864.9829-6.98285
1846865.57312.42687
1857265.67156.32849
1866265.4748-3.47475
1876265.5731-3.57313
1886565.3764-0.376373
1896965.37643.62363
1906665.2780.722007
1917265.67156.32849
1926265.4748-3.47475
1937565.67159.32849
1945865.4748-7.47475
1956665.57310.426866
1965565.0812-10.0812
1974765.6715-18.6715
1987265.47486.52525
1996265.6715-3.67151
2006465.278-1.27799
2016465.6715-1.67151
2021965.6715-46.6715
2035065.5731-15.5731
2046865.47482.52525
2057065.67154.32849
2067965.179613.8204
2076965.57313.42687
2087165.86835.13173
2094865.3764-17.3764
2107364.78618.21391
2117464.78619.21391
2126665.76990.230106
2137165.86835.13173
2147465.57318.42687
2157864.884513.1155
2167565.37649.62363
2175365.3764-12.3764
2186065.5731-5.57313
2197065.86834.13173
2206965.67153.32849
2216565.4748-0.474753
2227865.573112.4269
2237865.966712.0333
2245965.6715-6.67151
2257265.2786.72201
2267065.67154.32849
2276365.1796-2.17961
2286365.6715-2.67151
2297165.57315.42687
2307465.96678.03335
2316765.57311.42687
2326665.47480.525247
2336265.4748-3.47475
2348065.769914.2301
2357365.67157.32849
2366766.0650.934965
2376165.6715-4.67151
2387364.98298.01715
2397465.37648.62363
2403265.5731-33.5731
2416965.96673.03335
2426965.67153.32849
2438465.769918.2301
2446465.6715-1.67151
2455864.9829-6.98285
2465965.1796-6.17961
2477865.474812.5252
2485765.9667-8.96665
2496065.3764-5.37637
2506865.47482.52525
2516865.57312.42687
2527365.57317.42687
2536965.47483.52525
2546765.67151.32849
2556065.7699-5.76989
2566565.278-0.277993
2576665.57310.426866
2587465.76998.23011
2598165.573115.4269
2607265.08126.91877
2615565.6715-10.6715
2624965.5731-16.5731
2637465.17968.82039
2645365.6715-12.6715
2656465.6715-1.67151
2666565.6715-0.671514
2675765.4748-8.47475
2685165.4748-14.4748
2698065.671514.3285
2706765.67151.32849
2717065.86834.13173
2727465.47488.52525
2737566.0658.93497
2747065.57314.42687
2756965.67153.32849
2766565.6715-0.671514
2775565.6715-10.6715
2787165.2785.72201







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
50.7547340.4905320.245266
60.6824980.6350030.317502
70.7554570.4890870.244543
80.7471740.5056530.252826
90.8095920.3808150.190408
100.9881180.02376320.0118816
110.9810120.03797530.0189876
120.9690190.06196240.0309812
130.9913280.01734450.00867227
140.9889260.02214840.0110742
150.9933440.01331260.00665629
160.9911030.01779330.00889666
170.9859670.02806560.0140328
180.9805980.03880450.0194023
190.972370.05525910.0276296
200.9869840.02603160.0130158
210.9811310.03773850.0188692
220.9732390.05352160.0267608
230.9638380.07232430.0361621
240.9634350.07312950.0365648
250.9503560.09928890.0496444
260.936940.1261190.0630597
270.9180070.1639850.0819926
280.9069630.1860740.0930372
290.8816240.2367530.118376
300.8782950.243410.121705
310.8542660.2914680.145734
320.8461940.3076110.153806
330.8254340.3491320.174566
340.7911440.4177120.208856
350.759150.4816990.24085
360.719840.5603210.28016
370.7032930.5934150.296707
380.66820.66360.3318
390.66870.66260.3313
400.6984520.6030950.301548
410.7747580.4504840.225242
420.7604170.4791660.239583
430.7229030.5541940.277097
440.7296870.5406260.270313
450.6921870.6156250.307813
460.6545480.6909040.345452
470.6496210.7007590.350379
480.6104840.7790310.389516
490.6405210.7189580.359479
500.6044980.7910030.395502
510.6075040.7849930.392496
520.5714820.8570370.428518
530.5561830.8876330.443817
540.5355230.9289540.464477
550.5030740.9938530.496926
560.4684880.9369760.531512
570.4712790.9425570.528721
580.4291990.8583970.570801
590.3930310.7860620.606969
600.3613320.7226650.638668
610.3263760.6527510.673624
620.2985350.5970690.701465
630.3074610.6149220.692539
640.2886390.5772780.711361
650.275190.5503810.72481
660.2508620.5017240.749138
670.2409820.4819650.759018
680.2236420.4472840.776358
690.1946650.3893290.805335
700.1703160.3406330.829684
710.1666030.3332070.833397
720.1445120.2890240.855488
730.1347370.2694730.865263
740.1439310.2878630.856069
750.1792340.3584680.820766
760.2230440.4460870.776956
770.195480.390960.80452
780.187910.3758190.81209
790.1629470.3258930.837053
800.1418120.2836250.858188
810.1288370.2576750.871163
820.1097770.2195530.890223
830.1061630.2123250.893837
840.09829150.1965830.901708
850.08884020.177680.91116
860.08597540.1719510.914025
870.07301760.1460350.926982
880.06084020.121680.93916
890.07753660.1550730.922463
900.06571470.1314290.934285
910.06312790.1262560.936872
920.05514570.1102910.944854
930.0457930.0915860.954207
940.03797290.07594580.962027
950.03109240.06218480.968908
960.02846530.05693070.971535
970.0250070.0500140.974993
980.02019960.04039920.9798
990.01642730.03285470.983573
1000.01325370.02650750.986746
1010.01357370.02714750.986426
1020.01107860.02215730.988921
1030.01269210.02538420.987308
1040.01025770.02051530.989742
1050.009135320.01827060.990865
1060.007203070.01440610.992797
1070.005846620.01169320.994153
1080.005495130.01099030.994505
1090.005217310.01043460.994783
1100.004036140.008072270.995964
1110.00329890.006597810.996701
1120.002612250.005224490.997388
1130.001999770.003999530.998
1140.004206970.008413940.995793
1150.004945360.009890710.995055
1160.003833620.007667230.996166
1170.003055570.006111130.996944
1180.00323770.00647540.996762
1190.003755470.007510930.996245
1200.004661060.009322120.995339
1210.003717620.007435240.996282
1220.002868870.005737740.997131
1230.002193990.004387980.997806
1240.00662320.01324640.993377
1250.007573350.01514670.992427
1260.006015170.01203030.993985
1270.004751470.009502930.995249
1280.003735660.007471320.996264
1290.002898060.005796120.997102
1300.002474860.004949730.997525
1310.001960680.003921350.998039
1320.001726090.003452180.998274
1330.001333440.002666870.998667
1340.001210320.002420650.99879
1350.0009801210.001960240.99902
1360.000815090.001630180.999185
1370.0006751110.001350220.999325
1380.0005365950.001073190.999463
1390.0004399760.0008799530.99956
1400.0003716020.0007432040.999628
1410.000782540.001565080.999217
1420.000822880.001645760.999177
1430.0006636470.001327290.999336
1440.0006301480.00126030.99937
1450.0007534640.001506930.999247
1460.0005718650.001143730.999428
1470.001669960.003339930.99833
1480.002760190.005520390.99724
1490.002413540.004827070.997586
1500.002213620.004427230.997786
1510.002262820.004525640.997737
1520.003569080.007138150.996431
1530.003122770.006245530.996877
1540.002725620.005451240.997274
1550.002479410.004958810.997521
1560.001998750.003997510.998001
1570.001821530.003643060.998178
1580.001522130.003044250.998478
1590.001299350.002598690.998701
1600.001341040.002682090.998659
1610.001007760.002015530.998992
1620.0007754770.001550950.999225
1630.0006021040.001204210.999398
1640.0005705020.0011410.999429
1650.0005205370.001041070.999479
1660.001349380.002698760.998651
1670.00101330.00202660.998987
1680.0009613410.001922680.999039
1690.0007212730.001442550.999279
1700.0005810230.001162050.999419
1710.0004372830.0008745650.999563
1720.00046060.0009211990.999539
1730.0003560020.0007120040.999644
1740.0002751120.0005502250.999725
1750.0002607010.0005214010.999739
1760.0002181370.0004362740.999782
1770.0002190210.0004380430.999781
1780.0002701890.0005403780.99973
1790.0002050160.0004100320.999795
1800.0001519870.0003039730.999848
1810.0001170580.0002341150.999883
1820.0001080260.0002160510.999892
1839.95597e-050.0001991190.9999
1847.19168e-050.0001438340.999928
1856.13925e-050.0001227850.999939
1864.5704e-059.14081e-050.999954
1873.39064e-056.78129e-050.999966
1882.33306e-054.66613e-050.999977
1891.69239e-053.38478e-050.999983
1901.14678e-052.29355e-050.999989
1919.58351e-061.9167e-050.99999
1926.90099e-061.3802e-050.999993
1937.48124e-061.49625e-050.999993
1946.93229e-061.38646e-050.999993
1954.588e-069.176e-060.999995
1965.86113e-061.17223e-050.999994
1972.75352e-055.50704e-050.999972
1982.29086e-054.58172e-050.999977
1991.67228e-053.34455e-050.999983
2001.1456e-052.2912e-050.999989
2017.75012e-061.55002e-050.999992
2020.0565010.1130020.943499
2030.09397750.1879550.906022
2040.07966670.1593330.920333
2050.06874920.1374980.931251
2060.08649920.1729980.913501
2070.07367170.1473430.926328
2080.06454250.1290850.935457
2090.1255640.2511280.874436
2100.1184080.2368170.881592
2110.1174210.2348420.882579
2120.09939530.1987910.900605
2130.08707970.1741590.91292
2140.08409170.1681830.915908
2150.1073530.2147050.892647
2160.1116910.2233810.888309
2170.1375250.2750510.862475
2180.1281110.2562230.871889
2190.1102650.220530.889735
2200.09347280.1869460.906527
2210.07758960.1551790.92241
2220.091780.183560.90822
2230.1036270.2072530.896373
2240.09892230.1978450.901078
2250.09102890.1820580.908971
2260.07744950.1548990.922551
2270.06388260.1277650.936117
2280.0532120.1064240.946788
2290.04553360.09106720.954466
2300.04231420.08462830.957686
2310.03334290.06668590.966657
2320.0258820.05176390.974118
2330.02095030.04190050.97905
2340.03075270.06150540.969247
2350.0280760.05615190.971924
2360.02150820.04301640.978492
2370.01765530.03531060.982345
2380.01664210.03328420.983358
2390.01654990.03309990.98345
2400.3508270.7016550.649173
2410.3070890.6141790.692911
2420.2675080.5350160.732492
2430.4306330.8612660.569367
2440.3819140.7638270.618086
2450.3784880.7569750.621512
2460.3764240.7528480.623576
2470.4258920.8517840.574108
2480.4258540.8517090.574146
2490.403970.8079410.59603
2500.3508940.7017890.649106
2510.300390.600780.69961
2520.2824110.5648220.717589
2530.2390160.4780330.760984
2540.195050.39010.80495
2550.172240.344480.82776
2560.1357950.271590.864205
2570.1039030.2078060.896097
2580.09964820.1992960.900352
2590.1736910.3473810.826309
2600.1570970.3141940.842903
2610.1708430.3416860.829157
2620.3246040.6492080.675396
2630.3650440.7300880.634956
2640.4965480.9930960.503452
2650.4221670.8443350.577833
2660.3427560.6855130.657244
2670.3446980.6893950.655302
2680.6577790.6844410.342221
2690.7674250.465150.232575
2700.6660430.6679130.333957
2710.5405570.9188860.459443
2720.4860230.9720460.513977
2730.6089220.7821570.391078

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
5 & 0.754734 & 0.490532 & 0.245266 \tabularnewline
6 & 0.682498 & 0.635003 & 0.317502 \tabularnewline
7 & 0.755457 & 0.489087 & 0.244543 \tabularnewline
8 & 0.747174 & 0.505653 & 0.252826 \tabularnewline
9 & 0.809592 & 0.380815 & 0.190408 \tabularnewline
10 & 0.988118 & 0.0237632 & 0.0118816 \tabularnewline
11 & 0.981012 & 0.0379753 & 0.0189876 \tabularnewline
12 & 0.969019 & 0.0619624 & 0.0309812 \tabularnewline
13 & 0.991328 & 0.0173445 & 0.00867227 \tabularnewline
14 & 0.988926 & 0.0221484 & 0.0110742 \tabularnewline
15 & 0.993344 & 0.0133126 & 0.00665629 \tabularnewline
16 & 0.991103 & 0.0177933 & 0.00889666 \tabularnewline
17 & 0.985967 & 0.0280656 & 0.0140328 \tabularnewline
18 & 0.980598 & 0.0388045 & 0.0194023 \tabularnewline
19 & 0.97237 & 0.0552591 & 0.0276296 \tabularnewline
20 & 0.986984 & 0.0260316 & 0.0130158 \tabularnewline
21 & 0.981131 & 0.0377385 & 0.0188692 \tabularnewline
22 & 0.973239 & 0.0535216 & 0.0267608 \tabularnewline
23 & 0.963838 & 0.0723243 & 0.0361621 \tabularnewline
24 & 0.963435 & 0.0731295 & 0.0365648 \tabularnewline
25 & 0.950356 & 0.0992889 & 0.0496444 \tabularnewline
26 & 0.93694 & 0.126119 & 0.0630597 \tabularnewline
27 & 0.918007 & 0.163985 & 0.0819926 \tabularnewline
28 & 0.906963 & 0.186074 & 0.0930372 \tabularnewline
29 & 0.881624 & 0.236753 & 0.118376 \tabularnewline
30 & 0.878295 & 0.24341 & 0.121705 \tabularnewline
31 & 0.854266 & 0.291468 & 0.145734 \tabularnewline
32 & 0.846194 & 0.307611 & 0.153806 \tabularnewline
33 & 0.825434 & 0.349132 & 0.174566 \tabularnewline
34 & 0.791144 & 0.417712 & 0.208856 \tabularnewline
35 & 0.75915 & 0.481699 & 0.24085 \tabularnewline
36 & 0.71984 & 0.560321 & 0.28016 \tabularnewline
37 & 0.703293 & 0.593415 & 0.296707 \tabularnewline
38 & 0.6682 & 0.6636 & 0.3318 \tabularnewline
39 & 0.6687 & 0.6626 & 0.3313 \tabularnewline
40 & 0.698452 & 0.603095 & 0.301548 \tabularnewline
41 & 0.774758 & 0.450484 & 0.225242 \tabularnewline
42 & 0.760417 & 0.479166 & 0.239583 \tabularnewline
43 & 0.722903 & 0.554194 & 0.277097 \tabularnewline
44 & 0.729687 & 0.540626 & 0.270313 \tabularnewline
45 & 0.692187 & 0.615625 & 0.307813 \tabularnewline
46 & 0.654548 & 0.690904 & 0.345452 \tabularnewline
47 & 0.649621 & 0.700759 & 0.350379 \tabularnewline
48 & 0.610484 & 0.779031 & 0.389516 \tabularnewline
49 & 0.640521 & 0.718958 & 0.359479 \tabularnewline
50 & 0.604498 & 0.791003 & 0.395502 \tabularnewline
51 & 0.607504 & 0.784993 & 0.392496 \tabularnewline
52 & 0.571482 & 0.857037 & 0.428518 \tabularnewline
53 & 0.556183 & 0.887633 & 0.443817 \tabularnewline
54 & 0.535523 & 0.928954 & 0.464477 \tabularnewline
55 & 0.503074 & 0.993853 & 0.496926 \tabularnewline
56 & 0.468488 & 0.936976 & 0.531512 \tabularnewline
57 & 0.471279 & 0.942557 & 0.528721 \tabularnewline
58 & 0.429199 & 0.858397 & 0.570801 \tabularnewline
59 & 0.393031 & 0.786062 & 0.606969 \tabularnewline
60 & 0.361332 & 0.722665 & 0.638668 \tabularnewline
61 & 0.326376 & 0.652751 & 0.673624 \tabularnewline
62 & 0.298535 & 0.597069 & 0.701465 \tabularnewline
63 & 0.307461 & 0.614922 & 0.692539 \tabularnewline
64 & 0.288639 & 0.577278 & 0.711361 \tabularnewline
65 & 0.27519 & 0.550381 & 0.72481 \tabularnewline
66 & 0.250862 & 0.501724 & 0.749138 \tabularnewline
67 & 0.240982 & 0.481965 & 0.759018 \tabularnewline
68 & 0.223642 & 0.447284 & 0.776358 \tabularnewline
69 & 0.194665 & 0.389329 & 0.805335 \tabularnewline
70 & 0.170316 & 0.340633 & 0.829684 \tabularnewline
71 & 0.166603 & 0.333207 & 0.833397 \tabularnewline
72 & 0.144512 & 0.289024 & 0.855488 \tabularnewline
73 & 0.134737 & 0.269473 & 0.865263 \tabularnewline
74 & 0.143931 & 0.287863 & 0.856069 \tabularnewline
75 & 0.179234 & 0.358468 & 0.820766 \tabularnewline
76 & 0.223044 & 0.446087 & 0.776956 \tabularnewline
77 & 0.19548 & 0.39096 & 0.80452 \tabularnewline
78 & 0.18791 & 0.375819 & 0.81209 \tabularnewline
79 & 0.162947 & 0.325893 & 0.837053 \tabularnewline
80 & 0.141812 & 0.283625 & 0.858188 \tabularnewline
81 & 0.128837 & 0.257675 & 0.871163 \tabularnewline
82 & 0.109777 & 0.219553 & 0.890223 \tabularnewline
83 & 0.106163 & 0.212325 & 0.893837 \tabularnewline
84 & 0.0982915 & 0.196583 & 0.901708 \tabularnewline
85 & 0.0888402 & 0.17768 & 0.91116 \tabularnewline
86 & 0.0859754 & 0.171951 & 0.914025 \tabularnewline
87 & 0.0730176 & 0.146035 & 0.926982 \tabularnewline
88 & 0.0608402 & 0.12168 & 0.93916 \tabularnewline
89 & 0.0775366 & 0.155073 & 0.922463 \tabularnewline
90 & 0.0657147 & 0.131429 & 0.934285 \tabularnewline
91 & 0.0631279 & 0.126256 & 0.936872 \tabularnewline
92 & 0.0551457 & 0.110291 & 0.944854 \tabularnewline
93 & 0.045793 & 0.091586 & 0.954207 \tabularnewline
94 & 0.0379729 & 0.0759458 & 0.962027 \tabularnewline
95 & 0.0310924 & 0.0621848 & 0.968908 \tabularnewline
96 & 0.0284653 & 0.0569307 & 0.971535 \tabularnewline
97 & 0.025007 & 0.050014 & 0.974993 \tabularnewline
98 & 0.0201996 & 0.0403992 & 0.9798 \tabularnewline
99 & 0.0164273 & 0.0328547 & 0.983573 \tabularnewline
100 & 0.0132537 & 0.0265075 & 0.986746 \tabularnewline
101 & 0.0135737 & 0.0271475 & 0.986426 \tabularnewline
102 & 0.0110786 & 0.0221573 & 0.988921 \tabularnewline
103 & 0.0126921 & 0.0253842 & 0.987308 \tabularnewline
104 & 0.0102577 & 0.0205153 & 0.989742 \tabularnewline
105 & 0.00913532 & 0.0182706 & 0.990865 \tabularnewline
106 & 0.00720307 & 0.0144061 & 0.992797 \tabularnewline
107 & 0.00584662 & 0.0116932 & 0.994153 \tabularnewline
108 & 0.00549513 & 0.0109903 & 0.994505 \tabularnewline
109 & 0.00521731 & 0.0104346 & 0.994783 \tabularnewline
110 & 0.00403614 & 0.00807227 & 0.995964 \tabularnewline
111 & 0.0032989 & 0.00659781 & 0.996701 \tabularnewline
112 & 0.00261225 & 0.00522449 & 0.997388 \tabularnewline
113 & 0.00199977 & 0.00399953 & 0.998 \tabularnewline
114 & 0.00420697 & 0.00841394 & 0.995793 \tabularnewline
115 & 0.00494536 & 0.00989071 & 0.995055 \tabularnewline
116 & 0.00383362 & 0.00766723 & 0.996166 \tabularnewline
117 & 0.00305557 & 0.00611113 & 0.996944 \tabularnewline
118 & 0.0032377 & 0.0064754 & 0.996762 \tabularnewline
119 & 0.00375547 & 0.00751093 & 0.996245 \tabularnewline
120 & 0.00466106 & 0.00932212 & 0.995339 \tabularnewline
121 & 0.00371762 & 0.00743524 & 0.996282 \tabularnewline
122 & 0.00286887 & 0.00573774 & 0.997131 \tabularnewline
123 & 0.00219399 & 0.00438798 & 0.997806 \tabularnewline
124 & 0.0066232 & 0.0132464 & 0.993377 \tabularnewline
125 & 0.00757335 & 0.0151467 & 0.992427 \tabularnewline
126 & 0.00601517 & 0.0120303 & 0.993985 \tabularnewline
127 & 0.00475147 & 0.00950293 & 0.995249 \tabularnewline
128 & 0.00373566 & 0.00747132 & 0.996264 \tabularnewline
129 & 0.00289806 & 0.00579612 & 0.997102 \tabularnewline
130 & 0.00247486 & 0.00494973 & 0.997525 \tabularnewline
131 & 0.00196068 & 0.00392135 & 0.998039 \tabularnewline
132 & 0.00172609 & 0.00345218 & 0.998274 \tabularnewline
133 & 0.00133344 & 0.00266687 & 0.998667 \tabularnewline
134 & 0.00121032 & 0.00242065 & 0.99879 \tabularnewline
135 & 0.000980121 & 0.00196024 & 0.99902 \tabularnewline
136 & 0.00081509 & 0.00163018 & 0.999185 \tabularnewline
137 & 0.000675111 & 0.00135022 & 0.999325 \tabularnewline
138 & 0.000536595 & 0.00107319 & 0.999463 \tabularnewline
139 & 0.000439976 & 0.000879953 & 0.99956 \tabularnewline
140 & 0.000371602 & 0.000743204 & 0.999628 \tabularnewline
141 & 0.00078254 & 0.00156508 & 0.999217 \tabularnewline
142 & 0.00082288 & 0.00164576 & 0.999177 \tabularnewline
143 & 0.000663647 & 0.00132729 & 0.999336 \tabularnewline
144 & 0.000630148 & 0.0012603 & 0.99937 \tabularnewline
145 & 0.000753464 & 0.00150693 & 0.999247 \tabularnewline
146 & 0.000571865 & 0.00114373 & 0.999428 \tabularnewline
147 & 0.00166996 & 0.00333993 & 0.99833 \tabularnewline
148 & 0.00276019 & 0.00552039 & 0.99724 \tabularnewline
149 & 0.00241354 & 0.00482707 & 0.997586 \tabularnewline
150 & 0.00221362 & 0.00442723 & 0.997786 \tabularnewline
151 & 0.00226282 & 0.00452564 & 0.997737 \tabularnewline
152 & 0.00356908 & 0.00713815 & 0.996431 \tabularnewline
153 & 0.00312277 & 0.00624553 & 0.996877 \tabularnewline
154 & 0.00272562 & 0.00545124 & 0.997274 \tabularnewline
155 & 0.00247941 & 0.00495881 & 0.997521 \tabularnewline
156 & 0.00199875 & 0.00399751 & 0.998001 \tabularnewline
157 & 0.00182153 & 0.00364306 & 0.998178 \tabularnewline
158 & 0.00152213 & 0.00304425 & 0.998478 \tabularnewline
159 & 0.00129935 & 0.00259869 & 0.998701 \tabularnewline
160 & 0.00134104 & 0.00268209 & 0.998659 \tabularnewline
161 & 0.00100776 & 0.00201553 & 0.998992 \tabularnewline
162 & 0.000775477 & 0.00155095 & 0.999225 \tabularnewline
163 & 0.000602104 & 0.00120421 & 0.999398 \tabularnewline
164 & 0.000570502 & 0.001141 & 0.999429 \tabularnewline
165 & 0.000520537 & 0.00104107 & 0.999479 \tabularnewline
166 & 0.00134938 & 0.00269876 & 0.998651 \tabularnewline
167 & 0.0010133 & 0.0020266 & 0.998987 \tabularnewline
168 & 0.000961341 & 0.00192268 & 0.999039 \tabularnewline
169 & 0.000721273 & 0.00144255 & 0.999279 \tabularnewline
170 & 0.000581023 & 0.00116205 & 0.999419 \tabularnewline
171 & 0.000437283 & 0.000874565 & 0.999563 \tabularnewline
172 & 0.0004606 & 0.000921199 & 0.999539 \tabularnewline
173 & 0.000356002 & 0.000712004 & 0.999644 \tabularnewline
174 & 0.000275112 & 0.000550225 & 0.999725 \tabularnewline
175 & 0.000260701 & 0.000521401 & 0.999739 \tabularnewline
176 & 0.000218137 & 0.000436274 & 0.999782 \tabularnewline
177 & 0.000219021 & 0.000438043 & 0.999781 \tabularnewline
178 & 0.000270189 & 0.000540378 & 0.99973 \tabularnewline
179 & 0.000205016 & 0.000410032 & 0.999795 \tabularnewline
180 & 0.000151987 & 0.000303973 & 0.999848 \tabularnewline
181 & 0.000117058 & 0.000234115 & 0.999883 \tabularnewline
182 & 0.000108026 & 0.000216051 & 0.999892 \tabularnewline
183 & 9.95597e-05 & 0.000199119 & 0.9999 \tabularnewline
184 & 7.19168e-05 & 0.000143834 & 0.999928 \tabularnewline
185 & 6.13925e-05 & 0.000122785 & 0.999939 \tabularnewline
186 & 4.5704e-05 & 9.14081e-05 & 0.999954 \tabularnewline
187 & 3.39064e-05 & 6.78129e-05 & 0.999966 \tabularnewline
188 & 2.33306e-05 & 4.66613e-05 & 0.999977 \tabularnewline
189 & 1.69239e-05 & 3.38478e-05 & 0.999983 \tabularnewline
190 & 1.14678e-05 & 2.29355e-05 & 0.999989 \tabularnewline
191 & 9.58351e-06 & 1.9167e-05 & 0.99999 \tabularnewline
192 & 6.90099e-06 & 1.3802e-05 & 0.999993 \tabularnewline
193 & 7.48124e-06 & 1.49625e-05 & 0.999993 \tabularnewline
194 & 6.93229e-06 & 1.38646e-05 & 0.999993 \tabularnewline
195 & 4.588e-06 & 9.176e-06 & 0.999995 \tabularnewline
196 & 5.86113e-06 & 1.17223e-05 & 0.999994 \tabularnewline
197 & 2.75352e-05 & 5.50704e-05 & 0.999972 \tabularnewline
198 & 2.29086e-05 & 4.58172e-05 & 0.999977 \tabularnewline
199 & 1.67228e-05 & 3.34455e-05 & 0.999983 \tabularnewline
200 & 1.1456e-05 & 2.2912e-05 & 0.999989 \tabularnewline
201 & 7.75012e-06 & 1.55002e-05 & 0.999992 \tabularnewline
202 & 0.056501 & 0.113002 & 0.943499 \tabularnewline
203 & 0.0939775 & 0.187955 & 0.906022 \tabularnewline
204 & 0.0796667 & 0.159333 & 0.920333 \tabularnewline
205 & 0.0687492 & 0.137498 & 0.931251 \tabularnewline
206 & 0.0864992 & 0.172998 & 0.913501 \tabularnewline
207 & 0.0736717 & 0.147343 & 0.926328 \tabularnewline
208 & 0.0645425 & 0.129085 & 0.935457 \tabularnewline
209 & 0.125564 & 0.251128 & 0.874436 \tabularnewline
210 & 0.118408 & 0.236817 & 0.881592 \tabularnewline
211 & 0.117421 & 0.234842 & 0.882579 \tabularnewline
212 & 0.0993953 & 0.198791 & 0.900605 \tabularnewline
213 & 0.0870797 & 0.174159 & 0.91292 \tabularnewline
214 & 0.0840917 & 0.168183 & 0.915908 \tabularnewline
215 & 0.107353 & 0.214705 & 0.892647 \tabularnewline
216 & 0.111691 & 0.223381 & 0.888309 \tabularnewline
217 & 0.137525 & 0.275051 & 0.862475 \tabularnewline
218 & 0.128111 & 0.256223 & 0.871889 \tabularnewline
219 & 0.110265 & 0.22053 & 0.889735 \tabularnewline
220 & 0.0934728 & 0.186946 & 0.906527 \tabularnewline
221 & 0.0775896 & 0.155179 & 0.92241 \tabularnewline
222 & 0.09178 & 0.18356 & 0.90822 \tabularnewline
223 & 0.103627 & 0.207253 & 0.896373 \tabularnewline
224 & 0.0989223 & 0.197845 & 0.901078 \tabularnewline
225 & 0.0910289 & 0.182058 & 0.908971 \tabularnewline
226 & 0.0774495 & 0.154899 & 0.922551 \tabularnewline
227 & 0.0638826 & 0.127765 & 0.936117 \tabularnewline
228 & 0.053212 & 0.106424 & 0.946788 \tabularnewline
229 & 0.0455336 & 0.0910672 & 0.954466 \tabularnewline
230 & 0.0423142 & 0.0846283 & 0.957686 \tabularnewline
231 & 0.0333429 & 0.0666859 & 0.966657 \tabularnewline
232 & 0.025882 & 0.0517639 & 0.974118 \tabularnewline
233 & 0.0209503 & 0.0419005 & 0.97905 \tabularnewline
234 & 0.0307527 & 0.0615054 & 0.969247 \tabularnewline
235 & 0.028076 & 0.0561519 & 0.971924 \tabularnewline
236 & 0.0215082 & 0.0430164 & 0.978492 \tabularnewline
237 & 0.0176553 & 0.0353106 & 0.982345 \tabularnewline
238 & 0.0166421 & 0.0332842 & 0.983358 \tabularnewline
239 & 0.0165499 & 0.0330999 & 0.98345 \tabularnewline
240 & 0.350827 & 0.701655 & 0.649173 \tabularnewline
241 & 0.307089 & 0.614179 & 0.692911 \tabularnewline
242 & 0.267508 & 0.535016 & 0.732492 \tabularnewline
243 & 0.430633 & 0.861266 & 0.569367 \tabularnewline
244 & 0.381914 & 0.763827 & 0.618086 \tabularnewline
245 & 0.378488 & 0.756975 & 0.621512 \tabularnewline
246 & 0.376424 & 0.752848 & 0.623576 \tabularnewline
247 & 0.425892 & 0.851784 & 0.574108 \tabularnewline
248 & 0.425854 & 0.851709 & 0.574146 \tabularnewline
249 & 0.40397 & 0.807941 & 0.59603 \tabularnewline
250 & 0.350894 & 0.701789 & 0.649106 \tabularnewline
251 & 0.30039 & 0.60078 & 0.69961 \tabularnewline
252 & 0.282411 & 0.564822 & 0.717589 \tabularnewline
253 & 0.239016 & 0.478033 & 0.760984 \tabularnewline
254 & 0.19505 & 0.3901 & 0.80495 \tabularnewline
255 & 0.17224 & 0.34448 & 0.82776 \tabularnewline
256 & 0.135795 & 0.27159 & 0.864205 \tabularnewline
257 & 0.103903 & 0.207806 & 0.896097 \tabularnewline
258 & 0.0996482 & 0.199296 & 0.900352 \tabularnewline
259 & 0.173691 & 0.347381 & 0.826309 \tabularnewline
260 & 0.157097 & 0.314194 & 0.842903 \tabularnewline
261 & 0.170843 & 0.341686 & 0.829157 \tabularnewline
262 & 0.324604 & 0.649208 & 0.675396 \tabularnewline
263 & 0.365044 & 0.730088 & 0.634956 \tabularnewline
264 & 0.496548 & 0.993096 & 0.503452 \tabularnewline
265 & 0.422167 & 0.844335 & 0.577833 \tabularnewline
266 & 0.342756 & 0.685513 & 0.657244 \tabularnewline
267 & 0.344698 & 0.689395 & 0.655302 \tabularnewline
268 & 0.657779 & 0.684441 & 0.342221 \tabularnewline
269 & 0.767425 & 0.46515 & 0.232575 \tabularnewline
270 & 0.666043 & 0.667913 & 0.333957 \tabularnewline
271 & 0.540557 & 0.918886 & 0.459443 \tabularnewline
272 & 0.486023 & 0.972046 & 0.513977 \tabularnewline
273 & 0.608922 & 0.782157 & 0.391078 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266521&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]5[/C][C]0.754734[/C][C]0.490532[/C][C]0.245266[/C][/ROW]
[ROW][C]6[/C][C]0.682498[/C][C]0.635003[/C][C]0.317502[/C][/ROW]
[ROW][C]7[/C][C]0.755457[/C][C]0.489087[/C][C]0.244543[/C][/ROW]
[ROW][C]8[/C][C]0.747174[/C][C]0.505653[/C][C]0.252826[/C][/ROW]
[ROW][C]9[/C][C]0.809592[/C][C]0.380815[/C][C]0.190408[/C][/ROW]
[ROW][C]10[/C][C]0.988118[/C][C]0.0237632[/C][C]0.0118816[/C][/ROW]
[ROW][C]11[/C][C]0.981012[/C][C]0.0379753[/C][C]0.0189876[/C][/ROW]
[ROW][C]12[/C][C]0.969019[/C][C]0.0619624[/C][C]0.0309812[/C][/ROW]
[ROW][C]13[/C][C]0.991328[/C][C]0.0173445[/C][C]0.00867227[/C][/ROW]
[ROW][C]14[/C][C]0.988926[/C][C]0.0221484[/C][C]0.0110742[/C][/ROW]
[ROW][C]15[/C][C]0.993344[/C][C]0.0133126[/C][C]0.00665629[/C][/ROW]
[ROW][C]16[/C][C]0.991103[/C][C]0.0177933[/C][C]0.00889666[/C][/ROW]
[ROW][C]17[/C][C]0.985967[/C][C]0.0280656[/C][C]0.0140328[/C][/ROW]
[ROW][C]18[/C][C]0.980598[/C][C]0.0388045[/C][C]0.0194023[/C][/ROW]
[ROW][C]19[/C][C]0.97237[/C][C]0.0552591[/C][C]0.0276296[/C][/ROW]
[ROW][C]20[/C][C]0.986984[/C][C]0.0260316[/C][C]0.0130158[/C][/ROW]
[ROW][C]21[/C][C]0.981131[/C][C]0.0377385[/C][C]0.0188692[/C][/ROW]
[ROW][C]22[/C][C]0.973239[/C][C]0.0535216[/C][C]0.0267608[/C][/ROW]
[ROW][C]23[/C][C]0.963838[/C][C]0.0723243[/C][C]0.0361621[/C][/ROW]
[ROW][C]24[/C][C]0.963435[/C][C]0.0731295[/C][C]0.0365648[/C][/ROW]
[ROW][C]25[/C][C]0.950356[/C][C]0.0992889[/C][C]0.0496444[/C][/ROW]
[ROW][C]26[/C][C]0.93694[/C][C]0.126119[/C][C]0.0630597[/C][/ROW]
[ROW][C]27[/C][C]0.918007[/C][C]0.163985[/C][C]0.0819926[/C][/ROW]
[ROW][C]28[/C][C]0.906963[/C][C]0.186074[/C][C]0.0930372[/C][/ROW]
[ROW][C]29[/C][C]0.881624[/C][C]0.236753[/C][C]0.118376[/C][/ROW]
[ROW][C]30[/C][C]0.878295[/C][C]0.24341[/C][C]0.121705[/C][/ROW]
[ROW][C]31[/C][C]0.854266[/C][C]0.291468[/C][C]0.145734[/C][/ROW]
[ROW][C]32[/C][C]0.846194[/C][C]0.307611[/C][C]0.153806[/C][/ROW]
[ROW][C]33[/C][C]0.825434[/C][C]0.349132[/C][C]0.174566[/C][/ROW]
[ROW][C]34[/C][C]0.791144[/C][C]0.417712[/C][C]0.208856[/C][/ROW]
[ROW][C]35[/C][C]0.75915[/C][C]0.481699[/C][C]0.24085[/C][/ROW]
[ROW][C]36[/C][C]0.71984[/C][C]0.560321[/C][C]0.28016[/C][/ROW]
[ROW][C]37[/C][C]0.703293[/C][C]0.593415[/C][C]0.296707[/C][/ROW]
[ROW][C]38[/C][C]0.6682[/C][C]0.6636[/C][C]0.3318[/C][/ROW]
[ROW][C]39[/C][C]0.6687[/C][C]0.6626[/C][C]0.3313[/C][/ROW]
[ROW][C]40[/C][C]0.698452[/C][C]0.603095[/C][C]0.301548[/C][/ROW]
[ROW][C]41[/C][C]0.774758[/C][C]0.450484[/C][C]0.225242[/C][/ROW]
[ROW][C]42[/C][C]0.760417[/C][C]0.479166[/C][C]0.239583[/C][/ROW]
[ROW][C]43[/C][C]0.722903[/C][C]0.554194[/C][C]0.277097[/C][/ROW]
[ROW][C]44[/C][C]0.729687[/C][C]0.540626[/C][C]0.270313[/C][/ROW]
[ROW][C]45[/C][C]0.692187[/C][C]0.615625[/C][C]0.307813[/C][/ROW]
[ROW][C]46[/C][C]0.654548[/C][C]0.690904[/C][C]0.345452[/C][/ROW]
[ROW][C]47[/C][C]0.649621[/C][C]0.700759[/C][C]0.350379[/C][/ROW]
[ROW][C]48[/C][C]0.610484[/C][C]0.779031[/C][C]0.389516[/C][/ROW]
[ROW][C]49[/C][C]0.640521[/C][C]0.718958[/C][C]0.359479[/C][/ROW]
[ROW][C]50[/C][C]0.604498[/C][C]0.791003[/C][C]0.395502[/C][/ROW]
[ROW][C]51[/C][C]0.607504[/C][C]0.784993[/C][C]0.392496[/C][/ROW]
[ROW][C]52[/C][C]0.571482[/C][C]0.857037[/C][C]0.428518[/C][/ROW]
[ROW][C]53[/C][C]0.556183[/C][C]0.887633[/C][C]0.443817[/C][/ROW]
[ROW][C]54[/C][C]0.535523[/C][C]0.928954[/C][C]0.464477[/C][/ROW]
[ROW][C]55[/C][C]0.503074[/C][C]0.993853[/C][C]0.496926[/C][/ROW]
[ROW][C]56[/C][C]0.468488[/C][C]0.936976[/C][C]0.531512[/C][/ROW]
[ROW][C]57[/C][C]0.471279[/C][C]0.942557[/C][C]0.528721[/C][/ROW]
[ROW][C]58[/C][C]0.429199[/C][C]0.858397[/C][C]0.570801[/C][/ROW]
[ROW][C]59[/C][C]0.393031[/C][C]0.786062[/C][C]0.606969[/C][/ROW]
[ROW][C]60[/C][C]0.361332[/C][C]0.722665[/C][C]0.638668[/C][/ROW]
[ROW][C]61[/C][C]0.326376[/C][C]0.652751[/C][C]0.673624[/C][/ROW]
[ROW][C]62[/C][C]0.298535[/C][C]0.597069[/C][C]0.701465[/C][/ROW]
[ROW][C]63[/C][C]0.307461[/C][C]0.614922[/C][C]0.692539[/C][/ROW]
[ROW][C]64[/C][C]0.288639[/C][C]0.577278[/C][C]0.711361[/C][/ROW]
[ROW][C]65[/C][C]0.27519[/C][C]0.550381[/C][C]0.72481[/C][/ROW]
[ROW][C]66[/C][C]0.250862[/C][C]0.501724[/C][C]0.749138[/C][/ROW]
[ROW][C]67[/C][C]0.240982[/C][C]0.481965[/C][C]0.759018[/C][/ROW]
[ROW][C]68[/C][C]0.223642[/C][C]0.447284[/C][C]0.776358[/C][/ROW]
[ROW][C]69[/C][C]0.194665[/C][C]0.389329[/C][C]0.805335[/C][/ROW]
[ROW][C]70[/C][C]0.170316[/C][C]0.340633[/C][C]0.829684[/C][/ROW]
[ROW][C]71[/C][C]0.166603[/C][C]0.333207[/C][C]0.833397[/C][/ROW]
[ROW][C]72[/C][C]0.144512[/C][C]0.289024[/C][C]0.855488[/C][/ROW]
[ROW][C]73[/C][C]0.134737[/C][C]0.269473[/C][C]0.865263[/C][/ROW]
[ROW][C]74[/C][C]0.143931[/C][C]0.287863[/C][C]0.856069[/C][/ROW]
[ROW][C]75[/C][C]0.179234[/C][C]0.358468[/C][C]0.820766[/C][/ROW]
[ROW][C]76[/C][C]0.223044[/C][C]0.446087[/C][C]0.776956[/C][/ROW]
[ROW][C]77[/C][C]0.19548[/C][C]0.39096[/C][C]0.80452[/C][/ROW]
[ROW][C]78[/C][C]0.18791[/C][C]0.375819[/C][C]0.81209[/C][/ROW]
[ROW][C]79[/C][C]0.162947[/C][C]0.325893[/C][C]0.837053[/C][/ROW]
[ROW][C]80[/C][C]0.141812[/C][C]0.283625[/C][C]0.858188[/C][/ROW]
[ROW][C]81[/C][C]0.128837[/C][C]0.257675[/C][C]0.871163[/C][/ROW]
[ROW][C]82[/C][C]0.109777[/C][C]0.219553[/C][C]0.890223[/C][/ROW]
[ROW][C]83[/C][C]0.106163[/C][C]0.212325[/C][C]0.893837[/C][/ROW]
[ROW][C]84[/C][C]0.0982915[/C][C]0.196583[/C][C]0.901708[/C][/ROW]
[ROW][C]85[/C][C]0.0888402[/C][C]0.17768[/C][C]0.91116[/C][/ROW]
[ROW][C]86[/C][C]0.0859754[/C][C]0.171951[/C][C]0.914025[/C][/ROW]
[ROW][C]87[/C][C]0.0730176[/C][C]0.146035[/C][C]0.926982[/C][/ROW]
[ROW][C]88[/C][C]0.0608402[/C][C]0.12168[/C][C]0.93916[/C][/ROW]
[ROW][C]89[/C][C]0.0775366[/C][C]0.155073[/C][C]0.922463[/C][/ROW]
[ROW][C]90[/C][C]0.0657147[/C][C]0.131429[/C][C]0.934285[/C][/ROW]
[ROW][C]91[/C][C]0.0631279[/C][C]0.126256[/C][C]0.936872[/C][/ROW]
[ROW][C]92[/C][C]0.0551457[/C][C]0.110291[/C][C]0.944854[/C][/ROW]
[ROW][C]93[/C][C]0.045793[/C][C]0.091586[/C][C]0.954207[/C][/ROW]
[ROW][C]94[/C][C]0.0379729[/C][C]0.0759458[/C][C]0.962027[/C][/ROW]
[ROW][C]95[/C][C]0.0310924[/C][C]0.0621848[/C][C]0.968908[/C][/ROW]
[ROW][C]96[/C][C]0.0284653[/C][C]0.0569307[/C][C]0.971535[/C][/ROW]
[ROW][C]97[/C][C]0.025007[/C][C]0.050014[/C][C]0.974993[/C][/ROW]
[ROW][C]98[/C][C]0.0201996[/C][C]0.0403992[/C][C]0.9798[/C][/ROW]
[ROW][C]99[/C][C]0.0164273[/C][C]0.0328547[/C][C]0.983573[/C][/ROW]
[ROW][C]100[/C][C]0.0132537[/C][C]0.0265075[/C][C]0.986746[/C][/ROW]
[ROW][C]101[/C][C]0.0135737[/C][C]0.0271475[/C][C]0.986426[/C][/ROW]
[ROW][C]102[/C][C]0.0110786[/C][C]0.0221573[/C][C]0.988921[/C][/ROW]
[ROW][C]103[/C][C]0.0126921[/C][C]0.0253842[/C][C]0.987308[/C][/ROW]
[ROW][C]104[/C][C]0.0102577[/C][C]0.0205153[/C][C]0.989742[/C][/ROW]
[ROW][C]105[/C][C]0.00913532[/C][C]0.0182706[/C][C]0.990865[/C][/ROW]
[ROW][C]106[/C][C]0.00720307[/C][C]0.0144061[/C][C]0.992797[/C][/ROW]
[ROW][C]107[/C][C]0.00584662[/C][C]0.0116932[/C][C]0.994153[/C][/ROW]
[ROW][C]108[/C][C]0.00549513[/C][C]0.0109903[/C][C]0.994505[/C][/ROW]
[ROW][C]109[/C][C]0.00521731[/C][C]0.0104346[/C][C]0.994783[/C][/ROW]
[ROW][C]110[/C][C]0.00403614[/C][C]0.00807227[/C][C]0.995964[/C][/ROW]
[ROW][C]111[/C][C]0.0032989[/C][C]0.00659781[/C][C]0.996701[/C][/ROW]
[ROW][C]112[/C][C]0.00261225[/C][C]0.00522449[/C][C]0.997388[/C][/ROW]
[ROW][C]113[/C][C]0.00199977[/C][C]0.00399953[/C][C]0.998[/C][/ROW]
[ROW][C]114[/C][C]0.00420697[/C][C]0.00841394[/C][C]0.995793[/C][/ROW]
[ROW][C]115[/C][C]0.00494536[/C][C]0.00989071[/C][C]0.995055[/C][/ROW]
[ROW][C]116[/C][C]0.00383362[/C][C]0.00766723[/C][C]0.996166[/C][/ROW]
[ROW][C]117[/C][C]0.00305557[/C][C]0.00611113[/C][C]0.996944[/C][/ROW]
[ROW][C]118[/C][C]0.0032377[/C][C]0.0064754[/C][C]0.996762[/C][/ROW]
[ROW][C]119[/C][C]0.00375547[/C][C]0.00751093[/C][C]0.996245[/C][/ROW]
[ROW][C]120[/C][C]0.00466106[/C][C]0.00932212[/C][C]0.995339[/C][/ROW]
[ROW][C]121[/C][C]0.00371762[/C][C]0.00743524[/C][C]0.996282[/C][/ROW]
[ROW][C]122[/C][C]0.00286887[/C][C]0.00573774[/C][C]0.997131[/C][/ROW]
[ROW][C]123[/C][C]0.00219399[/C][C]0.00438798[/C][C]0.997806[/C][/ROW]
[ROW][C]124[/C][C]0.0066232[/C][C]0.0132464[/C][C]0.993377[/C][/ROW]
[ROW][C]125[/C][C]0.00757335[/C][C]0.0151467[/C][C]0.992427[/C][/ROW]
[ROW][C]126[/C][C]0.00601517[/C][C]0.0120303[/C][C]0.993985[/C][/ROW]
[ROW][C]127[/C][C]0.00475147[/C][C]0.00950293[/C][C]0.995249[/C][/ROW]
[ROW][C]128[/C][C]0.00373566[/C][C]0.00747132[/C][C]0.996264[/C][/ROW]
[ROW][C]129[/C][C]0.00289806[/C][C]0.00579612[/C][C]0.997102[/C][/ROW]
[ROW][C]130[/C][C]0.00247486[/C][C]0.00494973[/C][C]0.997525[/C][/ROW]
[ROW][C]131[/C][C]0.00196068[/C][C]0.00392135[/C][C]0.998039[/C][/ROW]
[ROW][C]132[/C][C]0.00172609[/C][C]0.00345218[/C][C]0.998274[/C][/ROW]
[ROW][C]133[/C][C]0.00133344[/C][C]0.00266687[/C][C]0.998667[/C][/ROW]
[ROW][C]134[/C][C]0.00121032[/C][C]0.00242065[/C][C]0.99879[/C][/ROW]
[ROW][C]135[/C][C]0.000980121[/C][C]0.00196024[/C][C]0.99902[/C][/ROW]
[ROW][C]136[/C][C]0.00081509[/C][C]0.00163018[/C][C]0.999185[/C][/ROW]
[ROW][C]137[/C][C]0.000675111[/C][C]0.00135022[/C][C]0.999325[/C][/ROW]
[ROW][C]138[/C][C]0.000536595[/C][C]0.00107319[/C][C]0.999463[/C][/ROW]
[ROW][C]139[/C][C]0.000439976[/C][C]0.000879953[/C][C]0.99956[/C][/ROW]
[ROW][C]140[/C][C]0.000371602[/C][C]0.000743204[/C][C]0.999628[/C][/ROW]
[ROW][C]141[/C][C]0.00078254[/C][C]0.00156508[/C][C]0.999217[/C][/ROW]
[ROW][C]142[/C][C]0.00082288[/C][C]0.00164576[/C][C]0.999177[/C][/ROW]
[ROW][C]143[/C][C]0.000663647[/C][C]0.00132729[/C][C]0.999336[/C][/ROW]
[ROW][C]144[/C][C]0.000630148[/C][C]0.0012603[/C][C]0.99937[/C][/ROW]
[ROW][C]145[/C][C]0.000753464[/C][C]0.00150693[/C][C]0.999247[/C][/ROW]
[ROW][C]146[/C][C]0.000571865[/C][C]0.00114373[/C][C]0.999428[/C][/ROW]
[ROW][C]147[/C][C]0.00166996[/C][C]0.00333993[/C][C]0.99833[/C][/ROW]
[ROW][C]148[/C][C]0.00276019[/C][C]0.00552039[/C][C]0.99724[/C][/ROW]
[ROW][C]149[/C][C]0.00241354[/C][C]0.00482707[/C][C]0.997586[/C][/ROW]
[ROW][C]150[/C][C]0.00221362[/C][C]0.00442723[/C][C]0.997786[/C][/ROW]
[ROW][C]151[/C][C]0.00226282[/C][C]0.00452564[/C][C]0.997737[/C][/ROW]
[ROW][C]152[/C][C]0.00356908[/C][C]0.00713815[/C][C]0.996431[/C][/ROW]
[ROW][C]153[/C][C]0.00312277[/C][C]0.00624553[/C][C]0.996877[/C][/ROW]
[ROW][C]154[/C][C]0.00272562[/C][C]0.00545124[/C][C]0.997274[/C][/ROW]
[ROW][C]155[/C][C]0.00247941[/C][C]0.00495881[/C][C]0.997521[/C][/ROW]
[ROW][C]156[/C][C]0.00199875[/C][C]0.00399751[/C][C]0.998001[/C][/ROW]
[ROW][C]157[/C][C]0.00182153[/C][C]0.00364306[/C][C]0.998178[/C][/ROW]
[ROW][C]158[/C][C]0.00152213[/C][C]0.00304425[/C][C]0.998478[/C][/ROW]
[ROW][C]159[/C][C]0.00129935[/C][C]0.00259869[/C][C]0.998701[/C][/ROW]
[ROW][C]160[/C][C]0.00134104[/C][C]0.00268209[/C][C]0.998659[/C][/ROW]
[ROW][C]161[/C][C]0.00100776[/C][C]0.00201553[/C][C]0.998992[/C][/ROW]
[ROW][C]162[/C][C]0.000775477[/C][C]0.00155095[/C][C]0.999225[/C][/ROW]
[ROW][C]163[/C][C]0.000602104[/C][C]0.00120421[/C][C]0.999398[/C][/ROW]
[ROW][C]164[/C][C]0.000570502[/C][C]0.001141[/C][C]0.999429[/C][/ROW]
[ROW][C]165[/C][C]0.000520537[/C][C]0.00104107[/C][C]0.999479[/C][/ROW]
[ROW][C]166[/C][C]0.00134938[/C][C]0.00269876[/C][C]0.998651[/C][/ROW]
[ROW][C]167[/C][C]0.0010133[/C][C]0.0020266[/C][C]0.998987[/C][/ROW]
[ROW][C]168[/C][C]0.000961341[/C][C]0.00192268[/C][C]0.999039[/C][/ROW]
[ROW][C]169[/C][C]0.000721273[/C][C]0.00144255[/C][C]0.999279[/C][/ROW]
[ROW][C]170[/C][C]0.000581023[/C][C]0.00116205[/C][C]0.999419[/C][/ROW]
[ROW][C]171[/C][C]0.000437283[/C][C]0.000874565[/C][C]0.999563[/C][/ROW]
[ROW][C]172[/C][C]0.0004606[/C][C]0.000921199[/C][C]0.999539[/C][/ROW]
[ROW][C]173[/C][C]0.000356002[/C][C]0.000712004[/C][C]0.999644[/C][/ROW]
[ROW][C]174[/C][C]0.000275112[/C][C]0.000550225[/C][C]0.999725[/C][/ROW]
[ROW][C]175[/C][C]0.000260701[/C][C]0.000521401[/C][C]0.999739[/C][/ROW]
[ROW][C]176[/C][C]0.000218137[/C][C]0.000436274[/C][C]0.999782[/C][/ROW]
[ROW][C]177[/C][C]0.000219021[/C][C]0.000438043[/C][C]0.999781[/C][/ROW]
[ROW][C]178[/C][C]0.000270189[/C][C]0.000540378[/C][C]0.99973[/C][/ROW]
[ROW][C]179[/C][C]0.000205016[/C][C]0.000410032[/C][C]0.999795[/C][/ROW]
[ROW][C]180[/C][C]0.000151987[/C][C]0.000303973[/C][C]0.999848[/C][/ROW]
[ROW][C]181[/C][C]0.000117058[/C][C]0.000234115[/C][C]0.999883[/C][/ROW]
[ROW][C]182[/C][C]0.000108026[/C][C]0.000216051[/C][C]0.999892[/C][/ROW]
[ROW][C]183[/C][C]9.95597e-05[/C][C]0.000199119[/C][C]0.9999[/C][/ROW]
[ROW][C]184[/C][C]7.19168e-05[/C][C]0.000143834[/C][C]0.999928[/C][/ROW]
[ROW][C]185[/C][C]6.13925e-05[/C][C]0.000122785[/C][C]0.999939[/C][/ROW]
[ROW][C]186[/C][C]4.5704e-05[/C][C]9.14081e-05[/C][C]0.999954[/C][/ROW]
[ROW][C]187[/C][C]3.39064e-05[/C][C]6.78129e-05[/C][C]0.999966[/C][/ROW]
[ROW][C]188[/C][C]2.33306e-05[/C][C]4.66613e-05[/C][C]0.999977[/C][/ROW]
[ROW][C]189[/C][C]1.69239e-05[/C][C]3.38478e-05[/C][C]0.999983[/C][/ROW]
[ROW][C]190[/C][C]1.14678e-05[/C][C]2.29355e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]191[/C][C]9.58351e-06[/C][C]1.9167e-05[/C][C]0.99999[/C][/ROW]
[ROW][C]192[/C][C]6.90099e-06[/C][C]1.3802e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]193[/C][C]7.48124e-06[/C][C]1.49625e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]194[/C][C]6.93229e-06[/C][C]1.38646e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]195[/C][C]4.588e-06[/C][C]9.176e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]196[/C][C]5.86113e-06[/C][C]1.17223e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]197[/C][C]2.75352e-05[/C][C]5.50704e-05[/C][C]0.999972[/C][/ROW]
[ROW][C]198[/C][C]2.29086e-05[/C][C]4.58172e-05[/C][C]0.999977[/C][/ROW]
[ROW][C]199[/C][C]1.67228e-05[/C][C]3.34455e-05[/C][C]0.999983[/C][/ROW]
[ROW][C]200[/C][C]1.1456e-05[/C][C]2.2912e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]201[/C][C]7.75012e-06[/C][C]1.55002e-05[/C][C]0.999992[/C][/ROW]
[ROW][C]202[/C][C]0.056501[/C][C]0.113002[/C][C]0.943499[/C][/ROW]
[ROW][C]203[/C][C]0.0939775[/C][C]0.187955[/C][C]0.906022[/C][/ROW]
[ROW][C]204[/C][C]0.0796667[/C][C]0.159333[/C][C]0.920333[/C][/ROW]
[ROW][C]205[/C][C]0.0687492[/C][C]0.137498[/C][C]0.931251[/C][/ROW]
[ROW][C]206[/C][C]0.0864992[/C][C]0.172998[/C][C]0.913501[/C][/ROW]
[ROW][C]207[/C][C]0.0736717[/C][C]0.147343[/C][C]0.926328[/C][/ROW]
[ROW][C]208[/C][C]0.0645425[/C][C]0.129085[/C][C]0.935457[/C][/ROW]
[ROW][C]209[/C][C]0.125564[/C][C]0.251128[/C][C]0.874436[/C][/ROW]
[ROW][C]210[/C][C]0.118408[/C][C]0.236817[/C][C]0.881592[/C][/ROW]
[ROW][C]211[/C][C]0.117421[/C][C]0.234842[/C][C]0.882579[/C][/ROW]
[ROW][C]212[/C][C]0.0993953[/C][C]0.198791[/C][C]0.900605[/C][/ROW]
[ROW][C]213[/C][C]0.0870797[/C][C]0.174159[/C][C]0.91292[/C][/ROW]
[ROW][C]214[/C][C]0.0840917[/C][C]0.168183[/C][C]0.915908[/C][/ROW]
[ROW][C]215[/C][C]0.107353[/C][C]0.214705[/C][C]0.892647[/C][/ROW]
[ROW][C]216[/C][C]0.111691[/C][C]0.223381[/C][C]0.888309[/C][/ROW]
[ROW][C]217[/C][C]0.137525[/C][C]0.275051[/C][C]0.862475[/C][/ROW]
[ROW][C]218[/C][C]0.128111[/C][C]0.256223[/C][C]0.871889[/C][/ROW]
[ROW][C]219[/C][C]0.110265[/C][C]0.22053[/C][C]0.889735[/C][/ROW]
[ROW][C]220[/C][C]0.0934728[/C][C]0.186946[/C][C]0.906527[/C][/ROW]
[ROW][C]221[/C][C]0.0775896[/C][C]0.155179[/C][C]0.92241[/C][/ROW]
[ROW][C]222[/C][C]0.09178[/C][C]0.18356[/C][C]0.90822[/C][/ROW]
[ROW][C]223[/C][C]0.103627[/C][C]0.207253[/C][C]0.896373[/C][/ROW]
[ROW][C]224[/C][C]0.0989223[/C][C]0.197845[/C][C]0.901078[/C][/ROW]
[ROW][C]225[/C][C]0.0910289[/C][C]0.182058[/C][C]0.908971[/C][/ROW]
[ROW][C]226[/C][C]0.0774495[/C][C]0.154899[/C][C]0.922551[/C][/ROW]
[ROW][C]227[/C][C]0.0638826[/C][C]0.127765[/C][C]0.936117[/C][/ROW]
[ROW][C]228[/C][C]0.053212[/C][C]0.106424[/C][C]0.946788[/C][/ROW]
[ROW][C]229[/C][C]0.0455336[/C][C]0.0910672[/C][C]0.954466[/C][/ROW]
[ROW][C]230[/C][C]0.0423142[/C][C]0.0846283[/C][C]0.957686[/C][/ROW]
[ROW][C]231[/C][C]0.0333429[/C][C]0.0666859[/C][C]0.966657[/C][/ROW]
[ROW][C]232[/C][C]0.025882[/C][C]0.0517639[/C][C]0.974118[/C][/ROW]
[ROW][C]233[/C][C]0.0209503[/C][C]0.0419005[/C][C]0.97905[/C][/ROW]
[ROW][C]234[/C][C]0.0307527[/C][C]0.0615054[/C][C]0.969247[/C][/ROW]
[ROW][C]235[/C][C]0.028076[/C][C]0.0561519[/C][C]0.971924[/C][/ROW]
[ROW][C]236[/C][C]0.0215082[/C][C]0.0430164[/C][C]0.978492[/C][/ROW]
[ROW][C]237[/C][C]0.0176553[/C][C]0.0353106[/C][C]0.982345[/C][/ROW]
[ROW][C]238[/C][C]0.0166421[/C][C]0.0332842[/C][C]0.983358[/C][/ROW]
[ROW][C]239[/C][C]0.0165499[/C][C]0.0330999[/C][C]0.98345[/C][/ROW]
[ROW][C]240[/C][C]0.350827[/C][C]0.701655[/C][C]0.649173[/C][/ROW]
[ROW][C]241[/C][C]0.307089[/C][C]0.614179[/C][C]0.692911[/C][/ROW]
[ROW][C]242[/C][C]0.267508[/C][C]0.535016[/C][C]0.732492[/C][/ROW]
[ROW][C]243[/C][C]0.430633[/C][C]0.861266[/C][C]0.569367[/C][/ROW]
[ROW][C]244[/C][C]0.381914[/C][C]0.763827[/C][C]0.618086[/C][/ROW]
[ROW][C]245[/C][C]0.378488[/C][C]0.756975[/C][C]0.621512[/C][/ROW]
[ROW][C]246[/C][C]0.376424[/C][C]0.752848[/C][C]0.623576[/C][/ROW]
[ROW][C]247[/C][C]0.425892[/C][C]0.851784[/C][C]0.574108[/C][/ROW]
[ROW][C]248[/C][C]0.425854[/C][C]0.851709[/C][C]0.574146[/C][/ROW]
[ROW][C]249[/C][C]0.40397[/C][C]0.807941[/C][C]0.59603[/C][/ROW]
[ROW][C]250[/C][C]0.350894[/C][C]0.701789[/C][C]0.649106[/C][/ROW]
[ROW][C]251[/C][C]0.30039[/C][C]0.60078[/C][C]0.69961[/C][/ROW]
[ROW][C]252[/C][C]0.282411[/C][C]0.564822[/C][C]0.717589[/C][/ROW]
[ROW][C]253[/C][C]0.239016[/C][C]0.478033[/C][C]0.760984[/C][/ROW]
[ROW][C]254[/C][C]0.19505[/C][C]0.3901[/C][C]0.80495[/C][/ROW]
[ROW][C]255[/C][C]0.17224[/C][C]0.34448[/C][C]0.82776[/C][/ROW]
[ROW][C]256[/C][C]0.135795[/C][C]0.27159[/C][C]0.864205[/C][/ROW]
[ROW][C]257[/C][C]0.103903[/C][C]0.207806[/C][C]0.896097[/C][/ROW]
[ROW][C]258[/C][C]0.0996482[/C][C]0.199296[/C][C]0.900352[/C][/ROW]
[ROW][C]259[/C][C]0.173691[/C][C]0.347381[/C][C]0.826309[/C][/ROW]
[ROW][C]260[/C][C]0.157097[/C][C]0.314194[/C][C]0.842903[/C][/ROW]
[ROW][C]261[/C][C]0.170843[/C][C]0.341686[/C][C]0.829157[/C][/ROW]
[ROW][C]262[/C][C]0.324604[/C][C]0.649208[/C][C]0.675396[/C][/ROW]
[ROW][C]263[/C][C]0.365044[/C][C]0.730088[/C][C]0.634956[/C][/ROW]
[ROW][C]264[/C][C]0.496548[/C][C]0.993096[/C][C]0.503452[/C][/ROW]
[ROW][C]265[/C][C]0.422167[/C][C]0.844335[/C][C]0.577833[/C][/ROW]
[ROW][C]266[/C][C]0.342756[/C][C]0.685513[/C][C]0.657244[/C][/ROW]
[ROW][C]267[/C][C]0.344698[/C][C]0.689395[/C][C]0.655302[/C][/ROW]
[ROW][C]268[/C][C]0.657779[/C][C]0.684441[/C][C]0.342221[/C][/ROW]
[ROW][C]269[/C][C]0.767425[/C][C]0.46515[/C][C]0.232575[/C][/ROW]
[ROW][C]270[/C][C]0.666043[/C][C]0.667913[/C][C]0.333957[/C][/ROW]
[ROW][C]271[/C][C]0.540557[/C][C]0.918886[/C][C]0.459443[/C][/ROW]
[ROW][C]272[/C][C]0.486023[/C][C]0.972046[/C][C]0.513977[/C][/ROW]
[ROW][C]273[/C][C]0.608922[/C][C]0.782157[/C][C]0.391078[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266521&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266521&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
50.7547340.4905320.245266
60.6824980.6350030.317502
70.7554570.4890870.244543
80.7471740.5056530.252826
90.8095920.3808150.190408
100.9881180.02376320.0118816
110.9810120.03797530.0189876
120.9690190.06196240.0309812
130.9913280.01734450.00867227
140.9889260.02214840.0110742
150.9933440.01331260.00665629
160.9911030.01779330.00889666
170.9859670.02806560.0140328
180.9805980.03880450.0194023
190.972370.05525910.0276296
200.9869840.02603160.0130158
210.9811310.03773850.0188692
220.9732390.05352160.0267608
230.9638380.07232430.0361621
240.9634350.07312950.0365648
250.9503560.09928890.0496444
260.936940.1261190.0630597
270.9180070.1639850.0819926
280.9069630.1860740.0930372
290.8816240.2367530.118376
300.8782950.243410.121705
310.8542660.2914680.145734
320.8461940.3076110.153806
330.8254340.3491320.174566
340.7911440.4177120.208856
350.759150.4816990.24085
360.719840.5603210.28016
370.7032930.5934150.296707
380.66820.66360.3318
390.66870.66260.3313
400.6984520.6030950.301548
410.7747580.4504840.225242
420.7604170.4791660.239583
430.7229030.5541940.277097
440.7296870.5406260.270313
450.6921870.6156250.307813
460.6545480.6909040.345452
470.6496210.7007590.350379
480.6104840.7790310.389516
490.6405210.7189580.359479
500.6044980.7910030.395502
510.6075040.7849930.392496
520.5714820.8570370.428518
530.5561830.8876330.443817
540.5355230.9289540.464477
550.5030740.9938530.496926
560.4684880.9369760.531512
570.4712790.9425570.528721
580.4291990.8583970.570801
590.3930310.7860620.606969
600.3613320.7226650.638668
610.3263760.6527510.673624
620.2985350.5970690.701465
630.3074610.6149220.692539
640.2886390.5772780.711361
650.275190.5503810.72481
660.2508620.5017240.749138
670.2409820.4819650.759018
680.2236420.4472840.776358
690.1946650.3893290.805335
700.1703160.3406330.829684
710.1666030.3332070.833397
720.1445120.2890240.855488
730.1347370.2694730.865263
740.1439310.2878630.856069
750.1792340.3584680.820766
760.2230440.4460870.776956
770.195480.390960.80452
780.187910.3758190.81209
790.1629470.3258930.837053
800.1418120.2836250.858188
810.1288370.2576750.871163
820.1097770.2195530.890223
830.1061630.2123250.893837
840.09829150.1965830.901708
850.08884020.177680.91116
860.08597540.1719510.914025
870.07301760.1460350.926982
880.06084020.121680.93916
890.07753660.1550730.922463
900.06571470.1314290.934285
910.06312790.1262560.936872
920.05514570.1102910.944854
930.0457930.0915860.954207
940.03797290.07594580.962027
950.03109240.06218480.968908
960.02846530.05693070.971535
970.0250070.0500140.974993
980.02019960.04039920.9798
990.01642730.03285470.983573
1000.01325370.02650750.986746
1010.01357370.02714750.986426
1020.01107860.02215730.988921
1030.01269210.02538420.987308
1040.01025770.02051530.989742
1050.009135320.01827060.990865
1060.007203070.01440610.992797
1070.005846620.01169320.994153
1080.005495130.01099030.994505
1090.005217310.01043460.994783
1100.004036140.008072270.995964
1110.00329890.006597810.996701
1120.002612250.005224490.997388
1130.001999770.003999530.998
1140.004206970.008413940.995793
1150.004945360.009890710.995055
1160.003833620.007667230.996166
1170.003055570.006111130.996944
1180.00323770.00647540.996762
1190.003755470.007510930.996245
1200.004661060.009322120.995339
1210.003717620.007435240.996282
1220.002868870.005737740.997131
1230.002193990.004387980.997806
1240.00662320.01324640.993377
1250.007573350.01514670.992427
1260.006015170.01203030.993985
1270.004751470.009502930.995249
1280.003735660.007471320.996264
1290.002898060.005796120.997102
1300.002474860.004949730.997525
1310.001960680.003921350.998039
1320.001726090.003452180.998274
1330.001333440.002666870.998667
1340.001210320.002420650.99879
1350.0009801210.001960240.99902
1360.000815090.001630180.999185
1370.0006751110.001350220.999325
1380.0005365950.001073190.999463
1390.0004399760.0008799530.99956
1400.0003716020.0007432040.999628
1410.000782540.001565080.999217
1420.000822880.001645760.999177
1430.0006636470.001327290.999336
1440.0006301480.00126030.99937
1450.0007534640.001506930.999247
1460.0005718650.001143730.999428
1470.001669960.003339930.99833
1480.002760190.005520390.99724
1490.002413540.004827070.997586
1500.002213620.004427230.997786
1510.002262820.004525640.997737
1520.003569080.007138150.996431
1530.003122770.006245530.996877
1540.002725620.005451240.997274
1550.002479410.004958810.997521
1560.001998750.003997510.998001
1570.001821530.003643060.998178
1580.001522130.003044250.998478
1590.001299350.002598690.998701
1600.001341040.002682090.998659
1610.001007760.002015530.998992
1620.0007754770.001550950.999225
1630.0006021040.001204210.999398
1640.0005705020.0011410.999429
1650.0005205370.001041070.999479
1660.001349380.002698760.998651
1670.00101330.00202660.998987
1680.0009613410.001922680.999039
1690.0007212730.001442550.999279
1700.0005810230.001162050.999419
1710.0004372830.0008745650.999563
1720.00046060.0009211990.999539
1730.0003560020.0007120040.999644
1740.0002751120.0005502250.999725
1750.0002607010.0005214010.999739
1760.0002181370.0004362740.999782
1770.0002190210.0004380430.999781
1780.0002701890.0005403780.99973
1790.0002050160.0004100320.999795
1800.0001519870.0003039730.999848
1810.0001170580.0002341150.999883
1820.0001080260.0002160510.999892
1839.95597e-050.0001991190.9999
1847.19168e-050.0001438340.999928
1856.13925e-050.0001227850.999939
1864.5704e-059.14081e-050.999954
1873.39064e-056.78129e-050.999966
1882.33306e-054.66613e-050.999977
1891.69239e-053.38478e-050.999983
1901.14678e-052.29355e-050.999989
1919.58351e-061.9167e-050.99999
1926.90099e-061.3802e-050.999993
1937.48124e-061.49625e-050.999993
1946.93229e-061.38646e-050.999993
1954.588e-069.176e-060.999995
1965.86113e-061.17223e-050.999994
1972.75352e-055.50704e-050.999972
1982.29086e-054.58172e-050.999977
1991.67228e-053.34455e-050.999983
2001.1456e-052.2912e-050.999989
2017.75012e-061.55002e-050.999992
2020.0565010.1130020.943499
2030.09397750.1879550.906022
2040.07966670.1593330.920333
2050.06874920.1374980.931251
2060.08649920.1729980.913501
2070.07367170.1473430.926328
2080.06454250.1290850.935457
2090.1255640.2511280.874436
2100.1184080.2368170.881592
2110.1174210.2348420.882579
2120.09939530.1987910.900605
2130.08707970.1741590.91292
2140.08409170.1681830.915908
2150.1073530.2147050.892647
2160.1116910.2233810.888309
2170.1375250.2750510.862475
2180.1281110.2562230.871889
2190.1102650.220530.889735
2200.09347280.1869460.906527
2210.07758960.1551790.92241
2220.091780.183560.90822
2230.1036270.2072530.896373
2240.09892230.1978450.901078
2250.09102890.1820580.908971
2260.07744950.1548990.922551
2270.06388260.1277650.936117
2280.0532120.1064240.946788
2290.04553360.09106720.954466
2300.04231420.08462830.957686
2310.03334290.06668590.966657
2320.0258820.05176390.974118
2330.02095030.04190050.97905
2340.03075270.06150540.969247
2350.0280760.05615190.971924
2360.02150820.04301640.978492
2370.01765530.03531060.982345
2380.01664210.03328420.983358
2390.01654990.03309990.98345
2400.3508270.7016550.649173
2410.3070890.6141790.692911
2420.2675080.5350160.732492
2430.4306330.8612660.569367
2440.3819140.7638270.618086
2450.3784880.7569750.621512
2460.3764240.7528480.623576
2470.4258920.8517840.574108
2480.4258540.8517090.574146
2490.403970.8079410.59603
2500.3508940.7017890.649106
2510.300390.600780.69961
2520.2824110.5648220.717589
2530.2390160.4780330.760984
2540.195050.39010.80495
2550.172240.344480.82776
2560.1357950.271590.864205
2570.1039030.2078060.896097
2580.09964820.1992960.900352
2590.1736910.3473810.826309
2600.1570970.3141940.842903
2610.1708430.3416860.829157
2620.3246040.6492080.675396
2630.3650440.7300880.634956
2640.4965480.9930960.503452
2650.4221670.8443350.577833
2660.3427560.6855130.657244
2670.3446980.6893950.655302
2680.6577790.6844410.342221
2690.7674250.465150.232575
2700.6660430.6679130.333957
2710.5405570.9188860.459443
2720.4860230.9720460.513977
2730.6089220.7821570.391078







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level890.330855NOK
5% type I error level1190.442379NOK
10% type I error level1360.505576NOK

\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 & 89 & 0.330855 & NOK \tabularnewline
5% type I error level & 119 & 0.442379 & NOK \tabularnewline
10% type I error level & 136 & 0.505576 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266521&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]89[/C][C]0.330855[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]119[/C][C]0.442379[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]136[/C][C]0.505576[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266521&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266521&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level890.330855NOK
5% type I error level1190.442379NOK
10% type I error level1360.505576NOK



Parameters (Session):
par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '1'
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')
}