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Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 09 Dec 2014 19:09:22 +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/09/t1418152179z10swkj86e41dd9.htm/, Retrieved Thu, 31 Oct 2024 23:27:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264816, Retrieved Thu, 31 Oct 2024 23:27:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-09 19:09:22] [61a57b1a717662ce9f6e819e563a5fa9] [Current]
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Dataseries X:
12.9 0
12.8 0
7.4 1
6.7 1
12.6 1
14.8 0
13.3 1
11.1 1
8.2 1
11.4 1
6.4 1
12 0
6.3 0
11.3 0
11.9 1
9.3 0
10 0
13.8 1
10.8 0
11.7 1
10.9 1
16.1 1
9.9 1
11.5 0
8.3 0
11.7 0
9 1
10.8 1
10.4 0
12.7 1
11.8 0
13 1
10.8 1
12.3 1
11.3 0
11.6 1
10.9 1
12.1 1
13.3 1
10.1 1
14.3 1
9.3 1
12.5 0
7.6 0
9.2 0
14.5 1
12.3 0
12.6 0
13 0
12.6 1
13.2 0
7.7 1
10.5 0
10.9 0
4.3 1
10.3 0
11.4 0
5.6 1
8.8 0
9 0
9.6 1
6.4 0
11.6 0
4.35 1
12.7 1
18.1 1
17.85 1
16.6 0
12.6 1
17.1 1
19.1 0
16.1 1
13.35 0
18.4 0
14.7 1
10.6 1
12.6 1
16.2 1
13.6 1
18.9 1
14.1 1
14.5 1
16.15 0
14.75 1
14.8 1
12.45 1
12.65 1
17.35 1
8.6 1
18.4 0
16.1 1
11.6 1
17.75 1
15.25 1
17.65 1
16.35 0
17.65 0
13.6 1
14.35 0
14.75 0
18.25 1
9.9 0
16 1
18.25 1
16.85 0
14.6 1
13.85 1
18.95 1
15.6 0
14.85 0
11.75 0
18.45 0
15.9 1
17.1 0
16.1 1
19.9 0
10.95 1
18.45 0
15.1 1
15 0
11.35 0
15.95 1
18.1 0
14.6 1
15.4 1
15.4 1
17.6 1
13.35 1
19.1 0
15.35 1
7.6 0
13.4 0
13.9 0
19.1 1
15.25 0
12.9 1
16.1 0
17.35 0
13.15 0
12.15 0
12.6 1
10.35 1
15.4 1
9.6 1
18.2 0
13.6 0
14.85 1
14.75 0
14.1 0
14.9 0
16.25 0
19.25 1
13.6 1
13.6 0
15.65 0
12.75 1
14.6 0
9.85 1
12.65 1
19.2 0
16.6 1
11.2 1
15.25 1
11.9 0
13.2 0
16.35 0
12.4 1
15.85 1
18.15 1
11.15 1
15.65 0
17.75 0
7.65 0
12.35 1
15.6 1
19.3 0
15.2 0
17.1 0
15.6 1
18.4 1
19.05 0
18.55 0
19.1 0
13.1 1
12.85 1
9.5 1
4.5 1
11.85 0
13.6 1
11.7 1
12.4 1
13.35 0
11.4 0
14.9 1
19.9 0
11.2 1
14.6 1
17.6 0
14.05 1
16.1 0
13.35 1
11.85 1
11.95 0
14.75 1
15.15 0
13.2 1
16.85 0
7.85 1
7.7 0
12.6 0
7.85 1
10.95 1
12.35 0
9.95 1
14.9 1
16.65 0
13.4 1
13.95 0
15.7 0
16.85 1
10.95 1
15.35 0
12.2 1
15.1 0
17.75 0
15.2 1
14.6 0
16.65 0
8.1 1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264816&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264816&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264816&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 time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 14.0107 -0.937267gender[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  14.0107 -0.937267gender[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264816&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  14.0107 -0.937267gender[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264816&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264816&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
TOT[t] = + 14.0107 -0.937267gender[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)14.01070.32511643.092.87875e-1111.43938e-111
gender-0.9372670.438299-2.1380.03355090.0167755

\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) & 14.0107 & 0.325116 & 43.09 & 2.87875e-111 & 1.43938e-111 \tabularnewline
gender & -0.937267 & 0.438299 & -2.138 & 0.0335509 & 0.0167755 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264816&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]14.0107[/C][C]0.325116[/C][C]43.09[/C][C]2.87875e-111[/C][C]1.43938e-111[/C][/ROW]
[ROW][C]gender[/C][C]-0.937267[/C][C]0.438299[/C][C]-2.138[/C][C]0.0335509[/C][C]0.0167755[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264816&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264816&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)14.01070.32511643.092.87875e-1111.43938e-111
gender-0.9372670.438299-2.1380.03355090.0167755







Multiple Linear Regression - Regression Statistics
Multiple R0.140524
R-squared0.0197469
Adjusted R-squared0.0154286
F-TEST (value)4.57284
F-TEST (DF numerator)1
F-TEST (DF denominator)227
p-value0.0335509
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.29956
Sum Squared Residuals2471.38

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.140524 \tabularnewline
R-squared & 0.0197469 \tabularnewline
Adjusted R-squared & 0.0154286 \tabularnewline
F-TEST (value) & 4.57284 \tabularnewline
F-TEST (DF numerator) & 1 \tabularnewline
F-TEST (DF denominator) & 227 \tabularnewline
p-value & 0.0335509 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.29956 \tabularnewline
Sum Squared Residuals & 2471.38 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264816&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.140524[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0197469[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0154286[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]4.57284[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]1[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]227[/C][/ROW]
[ROW][C]p-value[/C][C]0.0335509[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.29956[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2471.38[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264816&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264816&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 R0.140524
R-squared0.0197469
Adjusted R-squared0.0154286
F-TEST (value)4.57284
F-TEST (DF numerator)1
F-TEST (DF denominator)227
p-value0.0335509
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.29956
Sum Squared Residuals2471.38







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.0107-1.11068
212.814.0107-1.21068
37.413.0734-5.67341
46.713.0734-6.37341
512.613.0734-0.473413
614.814.01070.78932
713.313.07340.226587
811.113.0734-1.97341
98.213.0734-4.87341
1011.413.0734-1.67341
116.413.0734-6.67341
121214.0107-2.01068
136.314.0107-7.71068
1411.314.0107-2.71068
1511.913.0734-1.17341
169.314.0107-4.71068
171014.0107-4.01068
1813.813.07340.726587
1910.814.0107-3.21068
2011.713.0734-1.37341
2110.913.0734-2.17341
2216.113.07343.02659
239.913.0734-3.17341
2411.514.0107-2.51068
258.314.0107-5.71068
2611.714.0107-2.31068
27913.0734-4.07341
2810.813.0734-2.27341
2910.414.0107-3.61068
3012.713.0734-0.373413
3111.814.0107-2.21068
321313.0734-0.0734127
3310.813.0734-2.27341
3412.313.0734-0.773413
3511.314.0107-2.71068
3611.613.0734-1.47341
3710.913.0734-2.17341
3812.113.0734-0.973413
3913.313.07340.226587
4010.113.0734-2.97341
4114.313.07341.22659
429.313.0734-3.77341
4312.514.0107-1.51068
447.614.0107-6.41068
459.214.0107-4.81068
4614.513.07341.42659
4712.314.0107-1.71068
4812.614.0107-1.41068
491314.0107-1.01068
5012.613.0734-0.473413
5113.214.0107-0.81068
527.713.0734-5.37341
5310.514.0107-3.51068
5410.914.0107-3.11068
554.313.0734-8.77341
5610.314.0107-3.71068
5711.414.0107-2.61068
585.613.0734-7.47341
598.814.0107-5.21068
60914.0107-5.01068
619.613.0734-3.47341
626.414.0107-7.61068
6311.614.0107-2.41068
644.3513.0734-8.72341
6512.713.0734-0.373413
6618.113.07345.02659
6717.8513.07344.77659
6816.614.01072.58932
6912.613.0734-0.473413
7017.113.07344.02659
7119.114.01075.08932
7216.113.07343.02659
7313.3514.0107-0.66068
7418.414.01074.38932
7514.713.07341.62659
7610.613.0734-2.47341
7712.613.0734-0.473413
7816.213.07343.12659
7913.613.07340.526587
8018.913.07345.82659
8114.113.07341.02659
8214.513.07341.42659
8316.1514.01072.13932
8414.7513.07341.67659
8514.813.07341.72659
8612.4513.0734-0.623413
8712.6513.0734-0.423413
8817.3513.07344.27659
898.613.0734-4.47341
9018.414.01074.38932
9116.113.07343.02659
9211.613.0734-1.47341
9317.7513.07344.67659
9415.2513.07342.17659
9517.6513.07344.57659
9616.3514.01072.33932
9717.6514.01073.63932
9813.613.07340.526587
9914.3514.01070.33932
10014.7514.01070.73932
10118.2513.07345.17659
1029.914.0107-4.11068
1031613.07342.92659
10418.2513.07345.17659
10516.8514.01072.83932
10614.613.07341.52659
10713.8513.07340.776587
10818.9513.07345.87659
10915.614.01071.58932
11014.8514.01070.83932
11111.7514.0107-2.26068
11218.4514.01074.43932
11315.913.07342.82659
11417.114.01073.08932
11516.113.07343.02659
11619.914.01075.88932
11710.9513.0734-2.12341
11818.4514.01074.43932
11915.113.07342.02659
1201514.01070.98932
12111.3514.0107-2.66068
12215.9513.07342.87659
12318.114.01074.08932
12414.613.07341.52659
12515.413.07342.32659
12615.413.07342.32659
12717.613.07344.52659
12813.3513.07340.276587
12919.114.01075.08932
13015.3513.07342.27659
1317.614.0107-6.41068
13213.414.0107-0.61068
13313.914.0107-0.11068
13419.113.07346.02659
13515.2514.01071.23932
13612.913.0734-0.173413
13716.114.01072.08932
13817.3514.01073.33932
13913.1514.0107-0.86068
14012.1514.0107-1.86068
14112.613.0734-0.473413
14210.3513.0734-2.72341
14315.413.07342.32659
1449.613.0734-3.47341
14518.214.01074.18932
14613.614.0107-0.41068
14714.8513.07341.77659
14814.7514.01070.73932
14914.114.01070.0893204
15014.914.01070.88932
15116.2514.01072.23932
15219.2513.07346.17659
15313.613.07340.526587
15413.614.0107-0.41068
15515.6514.01071.63932
15612.7513.0734-0.323413
15714.614.01070.58932
1589.8513.0734-3.22341
15912.6513.0734-0.423413
16019.214.01075.18932
16116.613.07343.52659
16211.213.0734-1.87341
16315.2513.07342.17659
16411.914.0107-2.11068
16513.214.0107-0.81068
16616.3514.01072.33932
16712.413.0734-0.673413
16815.8513.07342.77659
16918.1513.07345.07659
17011.1513.0734-1.92341
17115.6514.01071.63932
17217.7514.01073.73932
1737.6514.0107-6.36068
17412.3513.0734-0.723413
17515.613.07342.52659
17619.314.01075.28932
17715.214.01071.18932
17817.114.01073.08932
17915.613.07342.52659
18018.413.07345.32659
18119.0514.01075.03932
18218.5514.01074.53932
18319.114.01075.08932
18413.113.07340.0265873
18512.8513.0734-0.223413
1869.513.0734-3.57341
1874.513.0734-8.57341
18811.8514.0107-2.16068
18913.613.07340.526587
19011.713.0734-1.37341
19112.413.0734-0.673413
19213.3514.0107-0.66068
19311.414.0107-2.61068
19414.913.07341.82659
19519.914.01075.88932
19611.213.0734-1.87341
19714.613.07341.52659
19817.614.01073.58932
19914.0513.07340.976587
20016.114.01072.08932
20113.3513.07340.276587
20211.8513.0734-1.22341
20311.9514.0107-2.06068
20414.7513.07341.67659
20515.1514.01071.13932
20613.213.07340.126587
20716.8514.01072.83932
2087.8513.0734-5.22341
2097.714.0107-6.31068
21012.614.0107-1.41068
2117.8513.0734-5.22341
21210.9513.0734-2.12341
21312.3514.0107-1.66068
2149.9513.0734-3.12341
21514.913.07341.82659
21616.6514.01072.63932
21713.413.07340.326587
21813.9514.0107-0.0606796
21915.714.01071.68932
22016.8513.07343.77659
22110.9513.0734-2.12341
22215.3514.01071.33932
22312.213.0734-0.873413
22415.114.01071.08932
22517.7514.01073.73932
22615.213.07342.12659
22714.614.01070.58932
22816.6514.01072.63932
2298.113.0734-4.97341

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 14.0107 & -1.11068 \tabularnewline
2 & 12.8 & 14.0107 & -1.21068 \tabularnewline
3 & 7.4 & 13.0734 & -5.67341 \tabularnewline
4 & 6.7 & 13.0734 & -6.37341 \tabularnewline
5 & 12.6 & 13.0734 & -0.473413 \tabularnewline
6 & 14.8 & 14.0107 & 0.78932 \tabularnewline
7 & 13.3 & 13.0734 & 0.226587 \tabularnewline
8 & 11.1 & 13.0734 & -1.97341 \tabularnewline
9 & 8.2 & 13.0734 & -4.87341 \tabularnewline
10 & 11.4 & 13.0734 & -1.67341 \tabularnewline
11 & 6.4 & 13.0734 & -6.67341 \tabularnewline
12 & 12 & 14.0107 & -2.01068 \tabularnewline
13 & 6.3 & 14.0107 & -7.71068 \tabularnewline
14 & 11.3 & 14.0107 & -2.71068 \tabularnewline
15 & 11.9 & 13.0734 & -1.17341 \tabularnewline
16 & 9.3 & 14.0107 & -4.71068 \tabularnewline
17 & 10 & 14.0107 & -4.01068 \tabularnewline
18 & 13.8 & 13.0734 & 0.726587 \tabularnewline
19 & 10.8 & 14.0107 & -3.21068 \tabularnewline
20 & 11.7 & 13.0734 & -1.37341 \tabularnewline
21 & 10.9 & 13.0734 & -2.17341 \tabularnewline
22 & 16.1 & 13.0734 & 3.02659 \tabularnewline
23 & 9.9 & 13.0734 & -3.17341 \tabularnewline
24 & 11.5 & 14.0107 & -2.51068 \tabularnewline
25 & 8.3 & 14.0107 & -5.71068 \tabularnewline
26 & 11.7 & 14.0107 & -2.31068 \tabularnewline
27 & 9 & 13.0734 & -4.07341 \tabularnewline
28 & 10.8 & 13.0734 & -2.27341 \tabularnewline
29 & 10.4 & 14.0107 & -3.61068 \tabularnewline
30 & 12.7 & 13.0734 & -0.373413 \tabularnewline
31 & 11.8 & 14.0107 & -2.21068 \tabularnewline
32 & 13 & 13.0734 & -0.0734127 \tabularnewline
33 & 10.8 & 13.0734 & -2.27341 \tabularnewline
34 & 12.3 & 13.0734 & -0.773413 \tabularnewline
35 & 11.3 & 14.0107 & -2.71068 \tabularnewline
36 & 11.6 & 13.0734 & -1.47341 \tabularnewline
37 & 10.9 & 13.0734 & -2.17341 \tabularnewline
38 & 12.1 & 13.0734 & -0.973413 \tabularnewline
39 & 13.3 & 13.0734 & 0.226587 \tabularnewline
40 & 10.1 & 13.0734 & -2.97341 \tabularnewline
41 & 14.3 & 13.0734 & 1.22659 \tabularnewline
42 & 9.3 & 13.0734 & -3.77341 \tabularnewline
43 & 12.5 & 14.0107 & -1.51068 \tabularnewline
44 & 7.6 & 14.0107 & -6.41068 \tabularnewline
45 & 9.2 & 14.0107 & -4.81068 \tabularnewline
46 & 14.5 & 13.0734 & 1.42659 \tabularnewline
47 & 12.3 & 14.0107 & -1.71068 \tabularnewline
48 & 12.6 & 14.0107 & -1.41068 \tabularnewline
49 & 13 & 14.0107 & -1.01068 \tabularnewline
50 & 12.6 & 13.0734 & -0.473413 \tabularnewline
51 & 13.2 & 14.0107 & -0.81068 \tabularnewline
52 & 7.7 & 13.0734 & -5.37341 \tabularnewline
53 & 10.5 & 14.0107 & -3.51068 \tabularnewline
54 & 10.9 & 14.0107 & -3.11068 \tabularnewline
55 & 4.3 & 13.0734 & -8.77341 \tabularnewline
56 & 10.3 & 14.0107 & -3.71068 \tabularnewline
57 & 11.4 & 14.0107 & -2.61068 \tabularnewline
58 & 5.6 & 13.0734 & -7.47341 \tabularnewline
59 & 8.8 & 14.0107 & -5.21068 \tabularnewline
60 & 9 & 14.0107 & -5.01068 \tabularnewline
61 & 9.6 & 13.0734 & -3.47341 \tabularnewline
62 & 6.4 & 14.0107 & -7.61068 \tabularnewline
63 & 11.6 & 14.0107 & -2.41068 \tabularnewline
64 & 4.35 & 13.0734 & -8.72341 \tabularnewline
65 & 12.7 & 13.0734 & -0.373413 \tabularnewline
66 & 18.1 & 13.0734 & 5.02659 \tabularnewline
67 & 17.85 & 13.0734 & 4.77659 \tabularnewline
68 & 16.6 & 14.0107 & 2.58932 \tabularnewline
69 & 12.6 & 13.0734 & -0.473413 \tabularnewline
70 & 17.1 & 13.0734 & 4.02659 \tabularnewline
71 & 19.1 & 14.0107 & 5.08932 \tabularnewline
72 & 16.1 & 13.0734 & 3.02659 \tabularnewline
73 & 13.35 & 14.0107 & -0.66068 \tabularnewline
74 & 18.4 & 14.0107 & 4.38932 \tabularnewline
75 & 14.7 & 13.0734 & 1.62659 \tabularnewline
76 & 10.6 & 13.0734 & -2.47341 \tabularnewline
77 & 12.6 & 13.0734 & -0.473413 \tabularnewline
78 & 16.2 & 13.0734 & 3.12659 \tabularnewline
79 & 13.6 & 13.0734 & 0.526587 \tabularnewline
80 & 18.9 & 13.0734 & 5.82659 \tabularnewline
81 & 14.1 & 13.0734 & 1.02659 \tabularnewline
82 & 14.5 & 13.0734 & 1.42659 \tabularnewline
83 & 16.15 & 14.0107 & 2.13932 \tabularnewline
84 & 14.75 & 13.0734 & 1.67659 \tabularnewline
85 & 14.8 & 13.0734 & 1.72659 \tabularnewline
86 & 12.45 & 13.0734 & -0.623413 \tabularnewline
87 & 12.65 & 13.0734 & -0.423413 \tabularnewline
88 & 17.35 & 13.0734 & 4.27659 \tabularnewline
89 & 8.6 & 13.0734 & -4.47341 \tabularnewline
90 & 18.4 & 14.0107 & 4.38932 \tabularnewline
91 & 16.1 & 13.0734 & 3.02659 \tabularnewline
92 & 11.6 & 13.0734 & -1.47341 \tabularnewline
93 & 17.75 & 13.0734 & 4.67659 \tabularnewline
94 & 15.25 & 13.0734 & 2.17659 \tabularnewline
95 & 17.65 & 13.0734 & 4.57659 \tabularnewline
96 & 16.35 & 14.0107 & 2.33932 \tabularnewline
97 & 17.65 & 14.0107 & 3.63932 \tabularnewline
98 & 13.6 & 13.0734 & 0.526587 \tabularnewline
99 & 14.35 & 14.0107 & 0.33932 \tabularnewline
100 & 14.75 & 14.0107 & 0.73932 \tabularnewline
101 & 18.25 & 13.0734 & 5.17659 \tabularnewline
102 & 9.9 & 14.0107 & -4.11068 \tabularnewline
103 & 16 & 13.0734 & 2.92659 \tabularnewline
104 & 18.25 & 13.0734 & 5.17659 \tabularnewline
105 & 16.85 & 14.0107 & 2.83932 \tabularnewline
106 & 14.6 & 13.0734 & 1.52659 \tabularnewline
107 & 13.85 & 13.0734 & 0.776587 \tabularnewline
108 & 18.95 & 13.0734 & 5.87659 \tabularnewline
109 & 15.6 & 14.0107 & 1.58932 \tabularnewline
110 & 14.85 & 14.0107 & 0.83932 \tabularnewline
111 & 11.75 & 14.0107 & -2.26068 \tabularnewline
112 & 18.45 & 14.0107 & 4.43932 \tabularnewline
113 & 15.9 & 13.0734 & 2.82659 \tabularnewline
114 & 17.1 & 14.0107 & 3.08932 \tabularnewline
115 & 16.1 & 13.0734 & 3.02659 \tabularnewline
116 & 19.9 & 14.0107 & 5.88932 \tabularnewline
117 & 10.95 & 13.0734 & -2.12341 \tabularnewline
118 & 18.45 & 14.0107 & 4.43932 \tabularnewline
119 & 15.1 & 13.0734 & 2.02659 \tabularnewline
120 & 15 & 14.0107 & 0.98932 \tabularnewline
121 & 11.35 & 14.0107 & -2.66068 \tabularnewline
122 & 15.95 & 13.0734 & 2.87659 \tabularnewline
123 & 18.1 & 14.0107 & 4.08932 \tabularnewline
124 & 14.6 & 13.0734 & 1.52659 \tabularnewline
125 & 15.4 & 13.0734 & 2.32659 \tabularnewline
126 & 15.4 & 13.0734 & 2.32659 \tabularnewline
127 & 17.6 & 13.0734 & 4.52659 \tabularnewline
128 & 13.35 & 13.0734 & 0.276587 \tabularnewline
129 & 19.1 & 14.0107 & 5.08932 \tabularnewline
130 & 15.35 & 13.0734 & 2.27659 \tabularnewline
131 & 7.6 & 14.0107 & -6.41068 \tabularnewline
132 & 13.4 & 14.0107 & -0.61068 \tabularnewline
133 & 13.9 & 14.0107 & -0.11068 \tabularnewline
134 & 19.1 & 13.0734 & 6.02659 \tabularnewline
135 & 15.25 & 14.0107 & 1.23932 \tabularnewline
136 & 12.9 & 13.0734 & -0.173413 \tabularnewline
137 & 16.1 & 14.0107 & 2.08932 \tabularnewline
138 & 17.35 & 14.0107 & 3.33932 \tabularnewline
139 & 13.15 & 14.0107 & -0.86068 \tabularnewline
140 & 12.15 & 14.0107 & -1.86068 \tabularnewline
141 & 12.6 & 13.0734 & -0.473413 \tabularnewline
142 & 10.35 & 13.0734 & -2.72341 \tabularnewline
143 & 15.4 & 13.0734 & 2.32659 \tabularnewline
144 & 9.6 & 13.0734 & -3.47341 \tabularnewline
145 & 18.2 & 14.0107 & 4.18932 \tabularnewline
146 & 13.6 & 14.0107 & -0.41068 \tabularnewline
147 & 14.85 & 13.0734 & 1.77659 \tabularnewline
148 & 14.75 & 14.0107 & 0.73932 \tabularnewline
149 & 14.1 & 14.0107 & 0.0893204 \tabularnewline
150 & 14.9 & 14.0107 & 0.88932 \tabularnewline
151 & 16.25 & 14.0107 & 2.23932 \tabularnewline
152 & 19.25 & 13.0734 & 6.17659 \tabularnewline
153 & 13.6 & 13.0734 & 0.526587 \tabularnewline
154 & 13.6 & 14.0107 & -0.41068 \tabularnewline
155 & 15.65 & 14.0107 & 1.63932 \tabularnewline
156 & 12.75 & 13.0734 & -0.323413 \tabularnewline
157 & 14.6 & 14.0107 & 0.58932 \tabularnewline
158 & 9.85 & 13.0734 & -3.22341 \tabularnewline
159 & 12.65 & 13.0734 & -0.423413 \tabularnewline
160 & 19.2 & 14.0107 & 5.18932 \tabularnewline
161 & 16.6 & 13.0734 & 3.52659 \tabularnewline
162 & 11.2 & 13.0734 & -1.87341 \tabularnewline
163 & 15.25 & 13.0734 & 2.17659 \tabularnewline
164 & 11.9 & 14.0107 & -2.11068 \tabularnewline
165 & 13.2 & 14.0107 & -0.81068 \tabularnewline
166 & 16.35 & 14.0107 & 2.33932 \tabularnewline
167 & 12.4 & 13.0734 & -0.673413 \tabularnewline
168 & 15.85 & 13.0734 & 2.77659 \tabularnewline
169 & 18.15 & 13.0734 & 5.07659 \tabularnewline
170 & 11.15 & 13.0734 & -1.92341 \tabularnewline
171 & 15.65 & 14.0107 & 1.63932 \tabularnewline
172 & 17.75 & 14.0107 & 3.73932 \tabularnewline
173 & 7.65 & 14.0107 & -6.36068 \tabularnewline
174 & 12.35 & 13.0734 & -0.723413 \tabularnewline
175 & 15.6 & 13.0734 & 2.52659 \tabularnewline
176 & 19.3 & 14.0107 & 5.28932 \tabularnewline
177 & 15.2 & 14.0107 & 1.18932 \tabularnewline
178 & 17.1 & 14.0107 & 3.08932 \tabularnewline
179 & 15.6 & 13.0734 & 2.52659 \tabularnewline
180 & 18.4 & 13.0734 & 5.32659 \tabularnewline
181 & 19.05 & 14.0107 & 5.03932 \tabularnewline
182 & 18.55 & 14.0107 & 4.53932 \tabularnewline
183 & 19.1 & 14.0107 & 5.08932 \tabularnewline
184 & 13.1 & 13.0734 & 0.0265873 \tabularnewline
185 & 12.85 & 13.0734 & -0.223413 \tabularnewline
186 & 9.5 & 13.0734 & -3.57341 \tabularnewline
187 & 4.5 & 13.0734 & -8.57341 \tabularnewline
188 & 11.85 & 14.0107 & -2.16068 \tabularnewline
189 & 13.6 & 13.0734 & 0.526587 \tabularnewline
190 & 11.7 & 13.0734 & -1.37341 \tabularnewline
191 & 12.4 & 13.0734 & -0.673413 \tabularnewline
192 & 13.35 & 14.0107 & -0.66068 \tabularnewline
193 & 11.4 & 14.0107 & -2.61068 \tabularnewline
194 & 14.9 & 13.0734 & 1.82659 \tabularnewline
195 & 19.9 & 14.0107 & 5.88932 \tabularnewline
196 & 11.2 & 13.0734 & -1.87341 \tabularnewline
197 & 14.6 & 13.0734 & 1.52659 \tabularnewline
198 & 17.6 & 14.0107 & 3.58932 \tabularnewline
199 & 14.05 & 13.0734 & 0.976587 \tabularnewline
200 & 16.1 & 14.0107 & 2.08932 \tabularnewline
201 & 13.35 & 13.0734 & 0.276587 \tabularnewline
202 & 11.85 & 13.0734 & -1.22341 \tabularnewline
203 & 11.95 & 14.0107 & -2.06068 \tabularnewline
204 & 14.75 & 13.0734 & 1.67659 \tabularnewline
205 & 15.15 & 14.0107 & 1.13932 \tabularnewline
206 & 13.2 & 13.0734 & 0.126587 \tabularnewline
207 & 16.85 & 14.0107 & 2.83932 \tabularnewline
208 & 7.85 & 13.0734 & -5.22341 \tabularnewline
209 & 7.7 & 14.0107 & -6.31068 \tabularnewline
210 & 12.6 & 14.0107 & -1.41068 \tabularnewline
211 & 7.85 & 13.0734 & -5.22341 \tabularnewline
212 & 10.95 & 13.0734 & -2.12341 \tabularnewline
213 & 12.35 & 14.0107 & -1.66068 \tabularnewline
214 & 9.95 & 13.0734 & -3.12341 \tabularnewline
215 & 14.9 & 13.0734 & 1.82659 \tabularnewline
216 & 16.65 & 14.0107 & 2.63932 \tabularnewline
217 & 13.4 & 13.0734 & 0.326587 \tabularnewline
218 & 13.95 & 14.0107 & -0.0606796 \tabularnewline
219 & 15.7 & 14.0107 & 1.68932 \tabularnewline
220 & 16.85 & 13.0734 & 3.77659 \tabularnewline
221 & 10.95 & 13.0734 & -2.12341 \tabularnewline
222 & 15.35 & 14.0107 & 1.33932 \tabularnewline
223 & 12.2 & 13.0734 & -0.873413 \tabularnewline
224 & 15.1 & 14.0107 & 1.08932 \tabularnewline
225 & 17.75 & 14.0107 & 3.73932 \tabularnewline
226 & 15.2 & 13.0734 & 2.12659 \tabularnewline
227 & 14.6 & 14.0107 & 0.58932 \tabularnewline
228 & 16.65 & 14.0107 & 2.63932 \tabularnewline
229 & 8.1 & 13.0734 & -4.97341 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264816&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]14.0107[/C][C]-1.11068[/C][/ROW]
[ROW][C]2[/C][C]12.8[/C][C]14.0107[/C][C]-1.21068[/C][/ROW]
[ROW][C]3[/C][C]7.4[/C][C]13.0734[/C][C]-5.67341[/C][/ROW]
[ROW][C]4[/C][C]6.7[/C][C]13.0734[/C][C]-6.37341[/C][/ROW]
[ROW][C]5[/C][C]12.6[/C][C]13.0734[/C][C]-0.473413[/C][/ROW]
[ROW][C]6[/C][C]14.8[/C][C]14.0107[/C][C]0.78932[/C][/ROW]
[ROW][C]7[/C][C]13.3[/C][C]13.0734[/C][C]0.226587[/C][/ROW]
[ROW][C]8[/C][C]11.1[/C][C]13.0734[/C][C]-1.97341[/C][/ROW]
[ROW][C]9[/C][C]8.2[/C][C]13.0734[/C][C]-4.87341[/C][/ROW]
[ROW][C]10[/C][C]11.4[/C][C]13.0734[/C][C]-1.67341[/C][/ROW]
[ROW][C]11[/C][C]6.4[/C][C]13.0734[/C][C]-6.67341[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]14.0107[/C][C]-2.01068[/C][/ROW]
[ROW][C]13[/C][C]6.3[/C][C]14.0107[/C][C]-7.71068[/C][/ROW]
[ROW][C]14[/C][C]11.3[/C][C]14.0107[/C][C]-2.71068[/C][/ROW]
[ROW][C]15[/C][C]11.9[/C][C]13.0734[/C][C]-1.17341[/C][/ROW]
[ROW][C]16[/C][C]9.3[/C][C]14.0107[/C][C]-4.71068[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]14.0107[/C][C]-4.01068[/C][/ROW]
[ROW][C]18[/C][C]13.8[/C][C]13.0734[/C][C]0.726587[/C][/ROW]
[ROW][C]19[/C][C]10.8[/C][C]14.0107[/C][C]-3.21068[/C][/ROW]
[ROW][C]20[/C][C]11.7[/C][C]13.0734[/C][C]-1.37341[/C][/ROW]
[ROW][C]21[/C][C]10.9[/C][C]13.0734[/C][C]-2.17341[/C][/ROW]
[ROW][C]22[/C][C]16.1[/C][C]13.0734[/C][C]3.02659[/C][/ROW]
[ROW][C]23[/C][C]9.9[/C][C]13.0734[/C][C]-3.17341[/C][/ROW]
[ROW][C]24[/C][C]11.5[/C][C]14.0107[/C][C]-2.51068[/C][/ROW]
[ROW][C]25[/C][C]8.3[/C][C]14.0107[/C][C]-5.71068[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]14.0107[/C][C]-2.31068[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]13.0734[/C][C]-4.07341[/C][/ROW]
[ROW][C]28[/C][C]10.8[/C][C]13.0734[/C][C]-2.27341[/C][/ROW]
[ROW][C]29[/C][C]10.4[/C][C]14.0107[/C][C]-3.61068[/C][/ROW]
[ROW][C]30[/C][C]12.7[/C][C]13.0734[/C][C]-0.373413[/C][/ROW]
[ROW][C]31[/C][C]11.8[/C][C]14.0107[/C][C]-2.21068[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]13.0734[/C][C]-0.0734127[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]13.0734[/C][C]-2.27341[/C][/ROW]
[ROW][C]34[/C][C]12.3[/C][C]13.0734[/C][C]-0.773413[/C][/ROW]
[ROW][C]35[/C][C]11.3[/C][C]14.0107[/C][C]-2.71068[/C][/ROW]
[ROW][C]36[/C][C]11.6[/C][C]13.0734[/C][C]-1.47341[/C][/ROW]
[ROW][C]37[/C][C]10.9[/C][C]13.0734[/C][C]-2.17341[/C][/ROW]
[ROW][C]38[/C][C]12.1[/C][C]13.0734[/C][C]-0.973413[/C][/ROW]
[ROW][C]39[/C][C]13.3[/C][C]13.0734[/C][C]0.226587[/C][/ROW]
[ROW][C]40[/C][C]10.1[/C][C]13.0734[/C][C]-2.97341[/C][/ROW]
[ROW][C]41[/C][C]14.3[/C][C]13.0734[/C][C]1.22659[/C][/ROW]
[ROW][C]42[/C][C]9.3[/C][C]13.0734[/C][C]-3.77341[/C][/ROW]
[ROW][C]43[/C][C]12.5[/C][C]14.0107[/C][C]-1.51068[/C][/ROW]
[ROW][C]44[/C][C]7.6[/C][C]14.0107[/C][C]-6.41068[/C][/ROW]
[ROW][C]45[/C][C]9.2[/C][C]14.0107[/C][C]-4.81068[/C][/ROW]
[ROW][C]46[/C][C]14.5[/C][C]13.0734[/C][C]1.42659[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]14.0107[/C][C]-1.71068[/C][/ROW]
[ROW][C]48[/C][C]12.6[/C][C]14.0107[/C][C]-1.41068[/C][/ROW]
[ROW][C]49[/C][C]13[/C][C]14.0107[/C][C]-1.01068[/C][/ROW]
[ROW][C]50[/C][C]12.6[/C][C]13.0734[/C][C]-0.473413[/C][/ROW]
[ROW][C]51[/C][C]13.2[/C][C]14.0107[/C][C]-0.81068[/C][/ROW]
[ROW][C]52[/C][C]7.7[/C][C]13.0734[/C][C]-5.37341[/C][/ROW]
[ROW][C]53[/C][C]10.5[/C][C]14.0107[/C][C]-3.51068[/C][/ROW]
[ROW][C]54[/C][C]10.9[/C][C]14.0107[/C][C]-3.11068[/C][/ROW]
[ROW][C]55[/C][C]4.3[/C][C]13.0734[/C][C]-8.77341[/C][/ROW]
[ROW][C]56[/C][C]10.3[/C][C]14.0107[/C][C]-3.71068[/C][/ROW]
[ROW][C]57[/C][C]11.4[/C][C]14.0107[/C][C]-2.61068[/C][/ROW]
[ROW][C]58[/C][C]5.6[/C][C]13.0734[/C][C]-7.47341[/C][/ROW]
[ROW][C]59[/C][C]8.8[/C][C]14.0107[/C][C]-5.21068[/C][/ROW]
[ROW][C]60[/C][C]9[/C][C]14.0107[/C][C]-5.01068[/C][/ROW]
[ROW][C]61[/C][C]9.6[/C][C]13.0734[/C][C]-3.47341[/C][/ROW]
[ROW][C]62[/C][C]6.4[/C][C]14.0107[/C][C]-7.61068[/C][/ROW]
[ROW][C]63[/C][C]11.6[/C][C]14.0107[/C][C]-2.41068[/C][/ROW]
[ROW][C]64[/C][C]4.35[/C][C]13.0734[/C][C]-8.72341[/C][/ROW]
[ROW][C]65[/C][C]12.7[/C][C]13.0734[/C][C]-0.373413[/C][/ROW]
[ROW][C]66[/C][C]18.1[/C][C]13.0734[/C][C]5.02659[/C][/ROW]
[ROW][C]67[/C][C]17.85[/C][C]13.0734[/C][C]4.77659[/C][/ROW]
[ROW][C]68[/C][C]16.6[/C][C]14.0107[/C][C]2.58932[/C][/ROW]
[ROW][C]69[/C][C]12.6[/C][C]13.0734[/C][C]-0.473413[/C][/ROW]
[ROW][C]70[/C][C]17.1[/C][C]13.0734[/C][C]4.02659[/C][/ROW]
[ROW][C]71[/C][C]19.1[/C][C]14.0107[/C][C]5.08932[/C][/ROW]
[ROW][C]72[/C][C]16.1[/C][C]13.0734[/C][C]3.02659[/C][/ROW]
[ROW][C]73[/C][C]13.35[/C][C]14.0107[/C][C]-0.66068[/C][/ROW]
[ROW][C]74[/C][C]18.4[/C][C]14.0107[/C][C]4.38932[/C][/ROW]
[ROW][C]75[/C][C]14.7[/C][C]13.0734[/C][C]1.62659[/C][/ROW]
[ROW][C]76[/C][C]10.6[/C][C]13.0734[/C][C]-2.47341[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]13.0734[/C][C]-0.473413[/C][/ROW]
[ROW][C]78[/C][C]16.2[/C][C]13.0734[/C][C]3.12659[/C][/ROW]
[ROW][C]79[/C][C]13.6[/C][C]13.0734[/C][C]0.526587[/C][/ROW]
[ROW][C]80[/C][C]18.9[/C][C]13.0734[/C][C]5.82659[/C][/ROW]
[ROW][C]81[/C][C]14.1[/C][C]13.0734[/C][C]1.02659[/C][/ROW]
[ROW][C]82[/C][C]14.5[/C][C]13.0734[/C][C]1.42659[/C][/ROW]
[ROW][C]83[/C][C]16.15[/C][C]14.0107[/C][C]2.13932[/C][/ROW]
[ROW][C]84[/C][C]14.75[/C][C]13.0734[/C][C]1.67659[/C][/ROW]
[ROW][C]85[/C][C]14.8[/C][C]13.0734[/C][C]1.72659[/C][/ROW]
[ROW][C]86[/C][C]12.45[/C][C]13.0734[/C][C]-0.623413[/C][/ROW]
[ROW][C]87[/C][C]12.65[/C][C]13.0734[/C][C]-0.423413[/C][/ROW]
[ROW][C]88[/C][C]17.35[/C][C]13.0734[/C][C]4.27659[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]13.0734[/C][C]-4.47341[/C][/ROW]
[ROW][C]90[/C][C]18.4[/C][C]14.0107[/C][C]4.38932[/C][/ROW]
[ROW][C]91[/C][C]16.1[/C][C]13.0734[/C][C]3.02659[/C][/ROW]
[ROW][C]92[/C][C]11.6[/C][C]13.0734[/C][C]-1.47341[/C][/ROW]
[ROW][C]93[/C][C]17.75[/C][C]13.0734[/C][C]4.67659[/C][/ROW]
[ROW][C]94[/C][C]15.25[/C][C]13.0734[/C][C]2.17659[/C][/ROW]
[ROW][C]95[/C][C]17.65[/C][C]13.0734[/C][C]4.57659[/C][/ROW]
[ROW][C]96[/C][C]16.35[/C][C]14.0107[/C][C]2.33932[/C][/ROW]
[ROW][C]97[/C][C]17.65[/C][C]14.0107[/C][C]3.63932[/C][/ROW]
[ROW][C]98[/C][C]13.6[/C][C]13.0734[/C][C]0.526587[/C][/ROW]
[ROW][C]99[/C][C]14.35[/C][C]14.0107[/C][C]0.33932[/C][/ROW]
[ROW][C]100[/C][C]14.75[/C][C]14.0107[/C][C]0.73932[/C][/ROW]
[ROW][C]101[/C][C]18.25[/C][C]13.0734[/C][C]5.17659[/C][/ROW]
[ROW][C]102[/C][C]9.9[/C][C]14.0107[/C][C]-4.11068[/C][/ROW]
[ROW][C]103[/C][C]16[/C][C]13.0734[/C][C]2.92659[/C][/ROW]
[ROW][C]104[/C][C]18.25[/C][C]13.0734[/C][C]5.17659[/C][/ROW]
[ROW][C]105[/C][C]16.85[/C][C]14.0107[/C][C]2.83932[/C][/ROW]
[ROW][C]106[/C][C]14.6[/C][C]13.0734[/C][C]1.52659[/C][/ROW]
[ROW][C]107[/C][C]13.85[/C][C]13.0734[/C][C]0.776587[/C][/ROW]
[ROW][C]108[/C][C]18.95[/C][C]13.0734[/C][C]5.87659[/C][/ROW]
[ROW][C]109[/C][C]15.6[/C][C]14.0107[/C][C]1.58932[/C][/ROW]
[ROW][C]110[/C][C]14.85[/C][C]14.0107[/C][C]0.83932[/C][/ROW]
[ROW][C]111[/C][C]11.75[/C][C]14.0107[/C][C]-2.26068[/C][/ROW]
[ROW][C]112[/C][C]18.45[/C][C]14.0107[/C][C]4.43932[/C][/ROW]
[ROW][C]113[/C][C]15.9[/C][C]13.0734[/C][C]2.82659[/C][/ROW]
[ROW][C]114[/C][C]17.1[/C][C]14.0107[/C][C]3.08932[/C][/ROW]
[ROW][C]115[/C][C]16.1[/C][C]13.0734[/C][C]3.02659[/C][/ROW]
[ROW][C]116[/C][C]19.9[/C][C]14.0107[/C][C]5.88932[/C][/ROW]
[ROW][C]117[/C][C]10.95[/C][C]13.0734[/C][C]-2.12341[/C][/ROW]
[ROW][C]118[/C][C]18.45[/C][C]14.0107[/C][C]4.43932[/C][/ROW]
[ROW][C]119[/C][C]15.1[/C][C]13.0734[/C][C]2.02659[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]14.0107[/C][C]0.98932[/C][/ROW]
[ROW][C]121[/C][C]11.35[/C][C]14.0107[/C][C]-2.66068[/C][/ROW]
[ROW][C]122[/C][C]15.95[/C][C]13.0734[/C][C]2.87659[/C][/ROW]
[ROW][C]123[/C][C]18.1[/C][C]14.0107[/C][C]4.08932[/C][/ROW]
[ROW][C]124[/C][C]14.6[/C][C]13.0734[/C][C]1.52659[/C][/ROW]
[ROW][C]125[/C][C]15.4[/C][C]13.0734[/C][C]2.32659[/C][/ROW]
[ROW][C]126[/C][C]15.4[/C][C]13.0734[/C][C]2.32659[/C][/ROW]
[ROW][C]127[/C][C]17.6[/C][C]13.0734[/C][C]4.52659[/C][/ROW]
[ROW][C]128[/C][C]13.35[/C][C]13.0734[/C][C]0.276587[/C][/ROW]
[ROW][C]129[/C][C]19.1[/C][C]14.0107[/C][C]5.08932[/C][/ROW]
[ROW][C]130[/C][C]15.35[/C][C]13.0734[/C][C]2.27659[/C][/ROW]
[ROW][C]131[/C][C]7.6[/C][C]14.0107[/C][C]-6.41068[/C][/ROW]
[ROW][C]132[/C][C]13.4[/C][C]14.0107[/C][C]-0.61068[/C][/ROW]
[ROW][C]133[/C][C]13.9[/C][C]14.0107[/C][C]-0.11068[/C][/ROW]
[ROW][C]134[/C][C]19.1[/C][C]13.0734[/C][C]6.02659[/C][/ROW]
[ROW][C]135[/C][C]15.25[/C][C]14.0107[/C][C]1.23932[/C][/ROW]
[ROW][C]136[/C][C]12.9[/C][C]13.0734[/C][C]-0.173413[/C][/ROW]
[ROW][C]137[/C][C]16.1[/C][C]14.0107[/C][C]2.08932[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]14.0107[/C][C]3.33932[/C][/ROW]
[ROW][C]139[/C][C]13.15[/C][C]14.0107[/C][C]-0.86068[/C][/ROW]
[ROW][C]140[/C][C]12.15[/C][C]14.0107[/C][C]-1.86068[/C][/ROW]
[ROW][C]141[/C][C]12.6[/C][C]13.0734[/C][C]-0.473413[/C][/ROW]
[ROW][C]142[/C][C]10.35[/C][C]13.0734[/C][C]-2.72341[/C][/ROW]
[ROW][C]143[/C][C]15.4[/C][C]13.0734[/C][C]2.32659[/C][/ROW]
[ROW][C]144[/C][C]9.6[/C][C]13.0734[/C][C]-3.47341[/C][/ROW]
[ROW][C]145[/C][C]18.2[/C][C]14.0107[/C][C]4.18932[/C][/ROW]
[ROW][C]146[/C][C]13.6[/C][C]14.0107[/C][C]-0.41068[/C][/ROW]
[ROW][C]147[/C][C]14.85[/C][C]13.0734[/C][C]1.77659[/C][/ROW]
[ROW][C]148[/C][C]14.75[/C][C]14.0107[/C][C]0.73932[/C][/ROW]
[ROW][C]149[/C][C]14.1[/C][C]14.0107[/C][C]0.0893204[/C][/ROW]
[ROW][C]150[/C][C]14.9[/C][C]14.0107[/C][C]0.88932[/C][/ROW]
[ROW][C]151[/C][C]16.25[/C][C]14.0107[/C][C]2.23932[/C][/ROW]
[ROW][C]152[/C][C]19.25[/C][C]13.0734[/C][C]6.17659[/C][/ROW]
[ROW][C]153[/C][C]13.6[/C][C]13.0734[/C][C]0.526587[/C][/ROW]
[ROW][C]154[/C][C]13.6[/C][C]14.0107[/C][C]-0.41068[/C][/ROW]
[ROW][C]155[/C][C]15.65[/C][C]14.0107[/C][C]1.63932[/C][/ROW]
[ROW][C]156[/C][C]12.75[/C][C]13.0734[/C][C]-0.323413[/C][/ROW]
[ROW][C]157[/C][C]14.6[/C][C]14.0107[/C][C]0.58932[/C][/ROW]
[ROW][C]158[/C][C]9.85[/C][C]13.0734[/C][C]-3.22341[/C][/ROW]
[ROW][C]159[/C][C]12.65[/C][C]13.0734[/C][C]-0.423413[/C][/ROW]
[ROW][C]160[/C][C]19.2[/C][C]14.0107[/C][C]5.18932[/C][/ROW]
[ROW][C]161[/C][C]16.6[/C][C]13.0734[/C][C]3.52659[/C][/ROW]
[ROW][C]162[/C][C]11.2[/C][C]13.0734[/C][C]-1.87341[/C][/ROW]
[ROW][C]163[/C][C]15.25[/C][C]13.0734[/C][C]2.17659[/C][/ROW]
[ROW][C]164[/C][C]11.9[/C][C]14.0107[/C][C]-2.11068[/C][/ROW]
[ROW][C]165[/C][C]13.2[/C][C]14.0107[/C][C]-0.81068[/C][/ROW]
[ROW][C]166[/C][C]16.35[/C][C]14.0107[/C][C]2.33932[/C][/ROW]
[ROW][C]167[/C][C]12.4[/C][C]13.0734[/C][C]-0.673413[/C][/ROW]
[ROW][C]168[/C][C]15.85[/C][C]13.0734[/C][C]2.77659[/C][/ROW]
[ROW][C]169[/C][C]18.15[/C][C]13.0734[/C][C]5.07659[/C][/ROW]
[ROW][C]170[/C][C]11.15[/C][C]13.0734[/C][C]-1.92341[/C][/ROW]
[ROW][C]171[/C][C]15.65[/C][C]14.0107[/C][C]1.63932[/C][/ROW]
[ROW][C]172[/C][C]17.75[/C][C]14.0107[/C][C]3.73932[/C][/ROW]
[ROW][C]173[/C][C]7.65[/C][C]14.0107[/C][C]-6.36068[/C][/ROW]
[ROW][C]174[/C][C]12.35[/C][C]13.0734[/C][C]-0.723413[/C][/ROW]
[ROW][C]175[/C][C]15.6[/C][C]13.0734[/C][C]2.52659[/C][/ROW]
[ROW][C]176[/C][C]19.3[/C][C]14.0107[/C][C]5.28932[/C][/ROW]
[ROW][C]177[/C][C]15.2[/C][C]14.0107[/C][C]1.18932[/C][/ROW]
[ROW][C]178[/C][C]17.1[/C][C]14.0107[/C][C]3.08932[/C][/ROW]
[ROW][C]179[/C][C]15.6[/C][C]13.0734[/C][C]2.52659[/C][/ROW]
[ROW][C]180[/C][C]18.4[/C][C]13.0734[/C][C]5.32659[/C][/ROW]
[ROW][C]181[/C][C]19.05[/C][C]14.0107[/C][C]5.03932[/C][/ROW]
[ROW][C]182[/C][C]18.55[/C][C]14.0107[/C][C]4.53932[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]14.0107[/C][C]5.08932[/C][/ROW]
[ROW][C]184[/C][C]13.1[/C][C]13.0734[/C][C]0.0265873[/C][/ROW]
[ROW][C]185[/C][C]12.85[/C][C]13.0734[/C][C]-0.223413[/C][/ROW]
[ROW][C]186[/C][C]9.5[/C][C]13.0734[/C][C]-3.57341[/C][/ROW]
[ROW][C]187[/C][C]4.5[/C][C]13.0734[/C][C]-8.57341[/C][/ROW]
[ROW][C]188[/C][C]11.85[/C][C]14.0107[/C][C]-2.16068[/C][/ROW]
[ROW][C]189[/C][C]13.6[/C][C]13.0734[/C][C]0.526587[/C][/ROW]
[ROW][C]190[/C][C]11.7[/C][C]13.0734[/C][C]-1.37341[/C][/ROW]
[ROW][C]191[/C][C]12.4[/C][C]13.0734[/C][C]-0.673413[/C][/ROW]
[ROW][C]192[/C][C]13.35[/C][C]14.0107[/C][C]-0.66068[/C][/ROW]
[ROW][C]193[/C][C]11.4[/C][C]14.0107[/C][C]-2.61068[/C][/ROW]
[ROW][C]194[/C][C]14.9[/C][C]13.0734[/C][C]1.82659[/C][/ROW]
[ROW][C]195[/C][C]19.9[/C][C]14.0107[/C][C]5.88932[/C][/ROW]
[ROW][C]196[/C][C]11.2[/C][C]13.0734[/C][C]-1.87341[/C][/ROW]
[ROW][C]197[/C][C]14.6[/C][C]13.0734[/C][C]1.52659[/C][/ROW]
[ROW][C]198[/C][C]17.6[/C][C]14.0107[/C][C]3.58932[/C][/ROW]
[ROW][C]199[/C][C]14.05[/C][C]13.0734[/C][C]0.976587[/C][/ROW]
[ROW][C]200[/C][C]16.1[/C][C]14.0107[/C][C]2.08932[/C][/ROW]
[ROW][C]201[/C][C]13.35[/C][C]13.0734[/C][C]0.276587[/C][/ROW]
[ROW][C]202[/C][C]11.85[/C][C]13.0734[/C][C]-1.22341[/C][/ROW]
[ROW][C]203[/C][C]11.95[/C][C]14.0107[/C][C]-2.06068[/C][/ROW]
[ROW][C]204[/C][C]14.75[/C][C]13.0734[/C][C]1.67659[/C][/ROW]
[ROW][C]205[/C][C]15.15[/C][C]14.0107[/C][C]1.13932[/C][/ROW]
[ROW][C]206[/C][C]13.2[/C][C]13.0734[/C][C]0.126587[/C][/ROW]
[ROW][C]207[/C][C]16.85[/C][C]14.0107[/C][C]2.83932[/C][/ROW]
[ROW][C]208[/C][C]7.85[/C][C]13.0734[/C][C]-5.22341[/C][/ROW]
[ROW][C]209[/C][C]7.7[/C][C]14.0107[/C][C]-6.31068[/C][/ROW]
[ROW][C]210[/C][C]12.6[/C][C]14.0107[/C][C]-1.41068[/C][/ROW]
[ROW][C]211[/C][C]7.85[/C][C]13.0734[/C][C]-5.22341[/C][/ROW]
[ROW][C]212[/C][C]10.95[/C][C]13.0734[/C][C]-2.12341[/C][/ROW]
[ROW][C]213[/C][C]12.35[/C][C]14.0107[/C][C]-1.66068[/C][/ROW]
[ROW][C]214[/C][C]9.95[/C][C]13.0734[/C][C]-3.12341[/C][/ROW]
[ROW][C]215[/C][C]14.9[/C][C]13.0734[/C][C]1.82659[/C][/ROW]
[ROW][C]216[/C][C]16.65[/C][C]14.0107[/C][C]2.63932[/C][/ROW]
[ROW][C]217[/C][C]13.4[/C][C]13.0734[/C][C]0.326587[/C][/ROW]
[ROW][C]218[/C][C]13.95[/C][C]14.0107[/C][C]-0.0606796[/C][/ROW]
[ROW][C]219[/C][C]15.7[/C][C]14.0107[/C][C]1.68932[/C][/ROW]
[ROW][C]220[/C][C]16.85[/C][C]13.0734[/C][C]3.77659[/C][/ROW]
[ROW][C]221[/C][C]10.95[/C][C]13.0734[/C][C]-2.12341[/C][/ROW]
[ROW][C]222[/C][C]15.35[/C][C]14.0107[/C][C]1.33932[/C][/ROW]
[ROW][C]223[/C][C]12.2[/C][C]13.0734[/C][C]-0.873413[/C][/ROW]
[ROW][C]224[/C][C]15.1[/C][C]14.0107[/C][C]1.08932[/C][/ROW]
[ROW][C]225[/C][C]17.75[/C][C]14.0107[/C][C]3.73932[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]13.0734[/C][C]2.12659[/C][/ROW]
[ROW][C]227[/C][C]14.6[/C][C]14.0107[/C][C]0.58932[/C][/ROW]
[ROW][C]228[/C][C]16.65[/C][C]14.0107[/C][C]2.63932[/C][/ROW]
[ROW][C]229[/C][C]8.1[/C][C]13.0734[/C][C]-4.97341[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264816&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264816&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
112.914.0107-1.11068
212.814.0107-1.21068
37.413.0734-5.67341
46.713.0734-6.37341
512.613.0734-0.473413
614.814.01070.78932
713.313.07340.226587
811.113.0734-1.97341
98.213.0734-4.87341
1011.413.0734-1.67341
116.413.0734-6.67341
121214.0107-2.01068
136.314.0107-7.71068
1411.314.0107-2.71068
1511.913.0734-1.17341
169.314.0107-4.71068
171014.0107-4.01068
1813.813.07340.726587
1910.814.0107-3.21068
2011.713.0734-1.37341
2110.913.0734-2.17341
2216.113.07343.02659
239.913.0734-3.17341
2411.514.0107-2.51068
258.314.0107-5.71068
2611.714.0107-2.31068
27913.0734-4.07341
2810.813.0734-2.27341
2910.414.0107-3.61068
3012.713.0734-0.373413
3111.814.0107-2.21068
321313.0734-0.0734127
3310.813.0734-2.27341
3412.313.0734-0.773413
3511.314.0107-2.71068
3611.613.0734-1.47341
3710.913.0734-2.17341
3812.113.0734-0.973413
3913.313.07340.226587
4010.113.0734-2.97341
4114.313.07341.22659
429.313.0734-3.77341
4312.514.0107-1.51068
447.614.0107-6.41068
459.214.0107-4.81068
4614.513.07341.42659
4712.314.0107-1.71068
4812.614.0107-1.41068
491314.0107-1.01068
5012.613.0734-0.473413
5113.214.0107-0.81068
527.713.0734-5.37341
5310.514.0107-3.51068
5410.914.0107-3.11068
554.313.0734-8.77341
5610.314.0107-3.71068
5711.414.0107-2.61068
585.613.0734-7.47341
598.814.0107-5.21068
60914.0107-5.01068
619.613.0734-3.47341
626.414.0107-7.61068
6311.614.0107-2.41068
644.3513.0734-8.72341
6512.713.0734-0.373413
6618.113.07345.02659
6717.8513.07344.77659
6816.614.01072.58932
6912.613.0734-0.473413
7017.113.07344.02659
7119.114.01075.08932
7216.113.07343.02659
7313.3514.0107-0.66068
7418.414.01074.38932
7514.713.07341.62659
7610.613.0734-2.47341
7712.613.0734-0.473413
7816.213.07343.12659
7913.613.07340.526587
8018.913.07345.82659
8114.113.07341.02659
8214.513.07341.42659
8316.1514.01072.13932
8414.7513.07341.67659
8514.813.07341.72659
8612.4513.0734-0.623413
8712.6513.0734-0.423413
8817.3513.07344.27659
898.613.0734-4.47341
9018.414.01074.38932
9116.113.07343.02659
9211.613.0734-1.47341
9317.7513.07344.67659
9415.2513.07342.17659
9517.6513.07344.57659
9616.3514.01072.33932
9717.6514.01073.63932
9813.613.07340.526587
9914.3514.01070.33932
10014.7514.01070.73932
10118.2513.07345.17659
1029.914.0107-4.11068
1031613.07342.92659
10418.2513.07345.17659
10516.8514.01072.83932
10614.613.07341.52659
10713.8513.07340.776587
10818.9513.07345.87659
10915.614.01071.58932
11014.8514.01070.83932
11111.7514.0107-2.26068
11218.4514.01074.43932
11315.913.07342.82659
11417.114.01073.08932
11516.113.07343.02659
11619.914.01075.88932
11710.9513.0734-2.12341
11818.4514.01074.43932
11915.113.07342.02659
1201514.01070.98932
12111.3514.0107-2.66068
12215.9513.07342.87659
12318.114.01074.08932
12414.613.07341.52659
12515.413.07342.32659
12615.413.07342.32659
12717.613.07344.52659
12813.3513.07340.276587
12919.114.01075.08932
13015.3513.07342.27659
1317.614.0107-6.41068
13213.414.0107-0.61068
13313.914.0107-0.11068
13419.113.07346.02659
13515.2514.01071.23932
13612.913.0734-0.173413
13716.114.01072.08932
13817.3514.01073.33932
13913.1514.0107-0.86068
14012.1514.0107-1.86068
14112.613.0734-0.473413
14210.3513.0734-2.72341
14315.413.07342.32659
1449.613.0734-3.47341
14518.214.01074.18932
14613.614.0107-0.41068
14714.8513.07341.77659
14814.7514.01070.73932
14914.114.01070.0893204
15014.914.01070.88932
15116.2514.01072.23932
15219.2513.07346.17659
15313.613.07340.526587
15413.614.0107-0.41068
15515.6514.01071.63932
15612.7513.0734-0.323413
15714.614.01070.58932
1589.8513.0734-3.22341
15912.6513.0734-0.423413
16019.214.01075.18932
16116.613.07343.52659
16211.213.0734-1.87341
16315.2513.07342.17659
16411.914.0107-2.11068
16513.214.0107-0.81068
16616.3514.01072.33932
16712.413.0734-0.673413
16815.8513.07342.77659
16918.1513.07345.07659
17011.1513.0734-1.92341
17115.6514.01071.63932
17217.7514.01073.73932
1737.6514.0107-6.36068
17412.3513.0734-0.723413
17515.613.07342.52659
17619.314.01075.28932
17715.214.01071.18932
17817.114.01073.08932
17915.613.07342.52659
18018.413.07345.32659
18119.0514.01075.03932
18218.5514.01074.53932
18319.114.01075.08932
18413.113.07340.0265873
18512.8513.0734-0.223413
1869.513.0734-3.57341
1874.513.0734-8.57341
18811.8514.0107-2.16068
18913.613.07340.526587
19011.713.0734-1.37341
19112.413.0734-0.673413
19213.3514.0107-0.66068
19311.414.0107-2.61068
19414.913.07341.82659
19519.914.01075.88932
19611.213.0734-1.87341
19714.613.07341.52659
19817.614.01073.58932
19914.0513.07340.976587
20016.114.01072.08932
20113.3513.07340.276587
20211.8513.0734-1.22341
20311.9514.0107-2.06068
20414.7513.07341.67659
20515.1514.01071.13932
20613.213.07340.126587
20716.8514.01072.83932
2087.8513.0734-5.22341
2097.714.0107-6.31068
21012.614.0107-1.41068
2117.8513.0734-5.22341
21210.9513.0734-2.12341
21312.3514.0107-1.66068
2149.9513.0734-3.12341
21514.913.07341.82659
21616.6514.01072.63932
21713.413.07340.326587
21813.9514.0107-0.0606796
21915.714.01071.68932
22016.8513.07343.77659
22110.9513.0734-2.12341
22215.3514.01071.33932
22312.213.0734-0.873413
22415.114.01071.08932
22517.7514.01073.73932
22615.213.07342.12659
22714.614.01070.58932
22816.6514.01072.63932
2298.113.0734-4.97341







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
50.4114950.8229890.588505
60.2922210.5844430.707779
70.3726770.7453540.627323
80.2640950.5281890.735905
90.208960.4179190.79104
100.1500390.3000790.849961
110.1892780.3785560.810722
120.138380.276760.86162
130.3826850.7653710.617315
140.3036520.6073040.696348
150.2647650.5295290.735235
160.2393070.4786150.760693
170.1946250.3892490.805375
180.2216170.4432330.778383
190.1725270.3450540.827473
200.1372590.2745190.862741
210.1025790.2051590.897421
220.1936090.3872180.806391
230.1568540.3137090.843146
240.1217120.2434230.878288
250.1250710.2501430.874929
260.0977080.1954160.902292
270.08454010.169080.91546
280.06358280.1271660.936417
290.04902390.09804780.950976
300.04082850.0816570.959172
310.03062530.06125070.969375
320.0260530.05210610.973947
330.01870380.03740750.981296
340.01406220.02812430.985938
350.01004080.02008160.989959
360.006978240.01395650.993022
370.004779740.009559480.99522
380.003359750.006719490.99664
390.00284660.005693190.997153
400.002079860.004159710.99792
410.002322880.004645760.997677
420.002031160.004062330.997969
430.001511260.003022520.998489
440.002421280.004842550.997579
450.002190840.004381670.997809
460.002529110.005058230.997471
470.001942790.003885580.998057
480.001529170.003058350.998471
490.001261910.002523830.998738
500.0009096210.001819240.99909
510.0007614450.001522890.999239
520.001229540.002459080.99877
530.0009470860.001894170.999053
540.0007002570.001400510.9993
550.006982070.01396410.993018
560.005911880.01182380.994088
570.004621120.009242230.995379
580.01454370.02908750.985456
590.01656090.03312180.983439
600.01814060.03628130.981859
610.01625880.03251760.983741
620.03780190.07560380.962198
630.03300880.06601760.966991
640.1191750.238350.880825
650.1088730.2177460.891127
660.2415660.4831310.758434
670.3875950.7751910.612405
680.4656050.931210.534395
690.4352340.8704670.564766
700.5309180.9381650.469082
710.7074020.5851960.292598
720.7385160.5229690.261484
730.7202530.5594940.279747
740.8093970.3812050.190603
750.8034870.3930250.196513
760.7886290.4227430.211371
770.7636270.4727460.236373
780.7856430.4287140.214357
790.7642510.4714970.235749
800.8572030.2855940.142797
810.8422370.3155270.157763
820.8294740.3410520.170526
830.8382250.3235510.161775
840.827170.3456610.17283
850.8156550.3686910.184345
860.7911710.4176590.208829
870.7647120.4705750.235288
880.801180.397640.19882
890.8258570.3482860.174143
900.8726360.2547280.127364
910.8759770.2480460.124023
920.8605430.2789150.139457
930.8899430.2201140.110057
940.8827140.2345720.117286
950.905360.189280.0946398
960.9073270.1853470.0926735
970.9215160.1569680.078484
980.9078540.1842920.0921459
990.8959950.208010.104005
1000.8841780.2316440.115822
1010.9135760.1728480.0864238
1020.923430.1531390.0765696
1030.9220270.1559460.0779732
1040.9431010.1137980.0568988
1050.9446950.110610.0553049
1060.9362150.127570.0637849
1070.9244860.1510280.075514
1080.9520430.09591330.0479566
1090.9470190.1059620.0529812
1100.9391770.1216460.0608232
1110.9355250.128950.0644748
1120.9481040.1037910.0518956
1130.9457550.108490.0542452
1140.94650.1070.0534998
1150.9452180.1095640.054782
1160.966390.06722020.0336101
1170.9625120.07497540.0374877
1180.9690880.06182460.0309123
1190.9647190.07056220.0352811
1200.9580830.08383440.0419172
1210.9572910.08541850.0427092
1220.9553060.08938780.0446939
1230.9600330.07993350.0399668
1240.9530970.09380570.0469029
1250.9482560.1034880.0517439
1260.9430680.1138640.0569319
1270.9530280.09394450.0469723
1280.9428990.1142010.0571007
1290.9561940.08761240.0438062
1300.9515930.09681360.0484068
1310.9775730.04485430.0224272
1320.9730930.05381450.0269072
1330.9673750.06525010.0326251
1340.9824070.0351870.0175935
1350.9784880.04302390.0215119
1360.9729420.05411510.0270576
1370.9686850.06262920.0313146
1380.9679220.06415660.0320783
1390.9623340.07533210.037666
1400.9594870.08102560.0405128
1410.9502890.09942150.0497107
1420.9472410.1055170.0527585
1430.9424840.1150320.0575159
1440.9443510.1112980.0556491
1450.9484350.1031310.0515654
1460.9390430.1219140.0609571
1470.9305290.1389420.0694711
1480.9172030.1655950.0827973
1490.9024760.1950480.0975242
1500.885410.2291810.11459
1510.8713760.2572490.128624
1520.923350.1533010.0766503
1530.908370.183260.0916301
1540.8938460.2123080.106154
1550.8768780.2462440.123122
1560.8547110.2905790.145289
1570.8314490.3371020.168551
1580.8294360.3411280.170564
1590.8019820.3960350.198018
1600.8297330.3405350.170267
1610.8382850.323430.161715
1620.8189310.3621390.181069
1630.8060150.387970.193985
1640.8012490.3975010.198751
1650.7799330.4401340.220067
1660.7561870.4876250.243813
1670.721910.556180.27809
1680.7176690.5646620.282331
1690.7821670.4356660.217833
1700.7565450.4869110.243455
1710.7246270.5507460.275373
1720.7196310.5607380.280369
1730.8549050.290190.145095
1740.8279340.3441330.172066
1750.8247510.3504980.175249
1760.8500410.2999180.149959
1770.8227270.3545470.177273
1780.8071580.3856830.192842
1790.8053810.3892370.194619
1800.88070.2385990.1193
1810.8992250.201550.100775
1820.9097760.1804480.0902239
1830.9301860.1396280.069814
1840.9138410.1723180.0861588
1850.8938750.2122510.106125
1860.8887090.2225810.111291
1870.9744010.05119750.0255988
1880.9731980.05360340.0268017
1890.9652460.06950850.0347542
1900.9545510.09089820.0454491
1910.9401390.1197210.0598607
1920.92610.1478010.0739004
1930.9313190.1373620.0686809
1940.9247180.1505630.0752815
1950.955750.08850030.0442502
1960.9431840.1136310.0568157
1970.9353550.1292890.0646447
1980.9353550.1292910.0646455
1990.9223730.1552540.077627
2000.9053790.1892410.0946206
2010.8816480.2367040.118352
2020.8481180.3037640.151882
2030.8358280.3283440.164172
2040.8277420.3445160.172258
2050.7839830.4320340.216017
2060.742770.514460.25723
2070.7185710.5628580.281429
2080.7579760.4840480.242024
2090.9338080.1323830.0661917
2100.9282590.1434820.0717409
2110.9607360.07852790.0392639
2120.9477950.1044090.0522047
2130.9539010.09219870.0460993
2140.9572330.08553360.0427668
2150.9457690.1084620.0542312
2160.9187710.1624590.0812293
2170.8763420.2473160.123658
2180.8388440.3223110.161156
2190.7629310.4741380.237069
2200.8885270.2229470.111473
2210.8200690.3598610.179931
2220.718310.5633810.28169
2230.5800830.8398350.419917
2240.4285060.8570120.571494

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
5 & 0.411495 & 0.822989 & 0.588505 \tabularnewline
6 & 0.292221 & 0.584443 & 0.707779 \tabularnewline
7 & 0.372677 & 0.745354 & 0.627323 \tabularnewline
8 & 0.264095 & 0.528189 & 0.735905 \tabularnewline
9 & 0.20896 & 0.417919 & 0.79104 \tabularnewline
10 & 0.150039 & 0.300079 & 0.849961 \tabularnewline
11 & 0.189278 & 0.378556 & 0.810722 \tabularnewline
12 & 0.13838 & 0.27676 & 0.86162 \tabularnewline
13 & 0.382685 & 0.765371 & 0.617315 \tabularnewline
14 & 0.303652 & 0.607304 & 0.696348 \tabularnewline
15 & 0.264765 & 0.529529 & 0.735235 \tabularnewline
16 & 0.239307 & 0.478615 & 0.760693 \tabularnewline
17 & 0.194625 & 0.389249 & 0.805375 \tabularnewline
18 & 0.221617 & 0.443233 & 0.778383 \tabularnewline
19 & 0.172527 & 0.345054 & 0.827473 \tabularnewline
20 & 0.137259 & 0.274519 & 0.862741 \tabularnewline
21 & 0.102579 & 0.205159 & 0.897421 \tabularnewline
22 & 0.193609 & 0.387218 & 0.806391 \tabularnewline
23 & 0.156854 & 0.313709 & 0.843146 \tabularnewline
24 & 0.121712 & 0.243423 & 0.878288 \tabularnewline
25 & 0.125071 & 0.250143 & 0.874929 \tabularnewline
26 & 0.097708 & 0.195416 & 0.902292 \tabularnewline
27 & 0.0845401 & 0.16908 & 0.91546 \tabularnewline
28 & 0.0635828 & 0.127166 & 0.936417 \tabularnewline
29 & 0.0490239 & 0.0980478 & 0.950976 \tabularnewline
30 & 0.0408285 & 0.081657 & 0.959172 \tabularnewline
31 & 0.0306253 & 0.0612507 & 0.969375 \tabularnewline
32 & 0.026053 & 0.0521061 & 0.973947 \tabularnewline
33 & 0.0187038 & 0.0374075 & 0.981296 \tabularnewline
34 & 0.0140622 & 0.0281243 & 0.985938 \tabularnewline
35 & 0.0100408 & 0.0200816 & 0.989959 \tabularnewline
36 & 0.00697824 & 0.0139565 & 0.993022 \tabularnewline
37 & 0.00477974 & 0.00955948 & 0.99522 \tabularnewline
38 & 0.00335975 & 0.00671949 & 0.99664 \tabularnewline
39 & 0.0028466 & 0.00569319 & 0.997153 \tabularnewline
40 & 0.00207986 & 0.00415971 & 0.99792 \tabularnewline
41 & 0.00232288 & 0.00464576 & 0.997677 \tabularnewline
42 & 0.00203116 & 0.00406233 & 0.997969 \tabularnewline
43 & 0.00151126 & 0.00302252 & 0.998489 \tabularnewline
44 & 0.00242128 & 0.00484255 & 0.997579 \tabularnewline
45 & 0.00219084 & 0.00438167 & 0.997809 \tabularnewline
46 & 0.00252911 & 0.00505823 & 0.997471 \tabularnewline
47 & 0.00194279 & 0.00388558 & 0.998057 \tabularnewline
48 & 0.00152917 & 0.00305835 & 0.998471 \tabularnewline
49 & 0.00126191 & 0.00252383 & 0.998738 \tabularnewline
50 & 0.000909621 & 0.00181924 & 0.99909 \tabularnewline
51 & 0.000761445 & 0.00152289 & 0.999239 \tabularnewline
52 & 0.00122954 & 0.00245908 & 0.99877 \tabularnewline
53 & 0.000947086 & 0.00189417 & 0.999053 \tabularnewline
54 & 0.000700257 & 0.00140051 & 0.9993 \tabularnewline
55 & 0.00698207 & 0.0139641 & 0.993018 \tabularnewline
56 & 0.00591188 & 0.0118238 & 0.994088 \tabularnewline
57 & 0.00462112 & 0.00924223 & 0.995379 \tabularnewline
58 & 0.0145437 & 0.0290875 & 0.985456 \tabularnewline
59 & 0.0165609 & 0.0331218 & 0.983439 \tabularnewline
60 & 0.0181406 & 0.0362813 & 0.981859 \tabularnewline
61 & 0.0162588 & 0.0325176 & 0.983741 \tabularnewline
62 & 0.0378019 & 0.0756038 & 0.962198 \tabularnewline
63 & 0.0330088 & 0.0660176 & 0.966991 \tabularnewline
64 & 0.119175 & 0.23835 & 0.880825 \tabularnewline
65 & 0.108873 & 0.217746 & 0.891127 \tabularnewline
66 & 0.241566 & 0.483131 & 0.758434 \tabularnewline
67 & 0.387595 & 0.775191 & 0.612405 \tabularnewline
68 & 0.465605 & 0.93121 & 0.534395 \tabularnewline
69 & 0.435234 & 0.870467 & 0.564766 \tabularnewline
70 & 0.530918 & 0.938165 & 0.469082 \tabularnewline
71 & 0.707402 & 0.585196 & 0.292598 \tabularnewline
72 & 0.738516 & 0.522969 & 0.261484 \tabularnewline
73 & 0.720253 & 0.559494 & 0.279747 \tabularnewline
74 & 0.809397 & 0.381205 & 0.190603 \tabularnewline
75 & 0.803487 & 0.393025 & 0.196513 \tabularnewline
76 & 0.788629 & 0.422743 & 0.211371 \tabularnewline
77 & 0.763627 & 0.472746 & 0.236373 \tabularnewline
78 & 0.785643 & 0.428714 & 0.214357 \tabularnewline
79 & 0.764251 & 0.471497 & 0.235749 \tabularnewline
80 & 0.857203 & 0.285594 & 0.142797 \tabularnewline
81 & 0.842237 & 0.315527 & 0.157763 \tabularnewline
82 & 0.829474 & 0.341052 & 0.170526 \tabularnewline
83 & 0.838225 & 0.323551 & 0.161775 \tabularnewline
84 & 0.82717 & 0.345661 & 0.17283 \tabularnewline
85 & 0.815655 & 0.368691 & 0.184345 \tabularnewline
86 & 0.791171 & 0.417659 & 0.208829 \tabularnewline
87 & 0.764712 & 0.470575 & 0.235288 \tabularnewline
88 & 0.80118 & 0.39764 & 0.19882 \tabularnewline
89 & 0.825857 & 0.348286 & 0.174143 \tabularnewline
90 & 0.872636 & 0.254728 & 0.127364 \tabularnewline
91 & 0.875977 & 0.248046 & 0.124023 \tabularnewline
92 & 0.860543 & 0.278915 & 0.139457 \tabularnewline
93 & 0.889943 & 0.220114 & 0.110057 \tabularnewline
94 & 0.882714 & 0.234572 & 0.117286 \tabularnewline
95 & 0.90536 & 0.18928 & 0.0946398 \tabularnewline
96 & 0.907327 & 0.185347 & 0.0926735 \tabularnewline
97 & 0.921516 & 0.156968 & 0.078484 \tabularnewline
98 & 0.907854 & 0.184292 & 0.0921459 \tabularnewline
99 & 0.895995 & 0.20801 & 0.104005 \tabularnewline
100 & 0.884178 & 0.231644 & 0.115822 \tabularnewline
101 & 0.913576 & 0.172848 & 0.0864238 \tabularnewline
102 & 0.92343 & 0.153139 & 0.0765696 \tabularnewline
103 & 0.922027 & 0.155946 & 0.0779732 \tabularnewline
104 & 0.943101 & 0.113798 & 0.0568988 \tabularnewline
105 & 0.944695 & 0.11061 & 0.0553049 \tabularnewline
106 & 0.936215 & 0.12757 & 0.0637849 \tabularnewline
107 & 0.924486 & 0.151028 & 0.075514 \tabularnewline
108 & 0.952043 & 0.0959133 & 0.0479566 \tabularnewline
109 & 0.947019 & 0.105962 & 0.0529812 \tabularnewline
110 & 0.939177 & 0.121646 & 0.0608232 \tabularnewline
111 & 0.935525 & 0.12895 & 0.0644748 \tabularnewline
112 & 0.948104 & 0.103791 & 0.0518956 \tabularnewline
113 & 0.945755 & 0.10849 & 0.0542452 \tabularnewline
114 & 0.9465 & 0.107 & 0.0534998 \tabularnewline
115 & 0.945218 & 0.109564 & 0.054782 \tabularnewline
116 & 0.96639 & 0.0672202 & 0.0336101 \tabularnewline
117 & 0.962512 & 0.0749754 & 0.0374877 \tabularnewline
118 & 0.969088 & 0.0618246 & 0.0309123 \tabularnewline
119 & 0.964719 & 0.0705622 & 0.0352811 \tabularnewline
120 & 0.958083 & 0.0838344 & 0.0419172 \tabularnewline
121 & 0.957291 & 0.0854185 & 0.0427092 \tabularnewline
122 & 0.955306 & 0.0893878 & 0.0446939 \tabularnewline
123 & 0.960033 & 0.0799335 & 0.0399668 \tabularnewline
124 & 0.953097 & 0.0938057 & 0.0469029 \tabularnewline
125 & 0.948256 & 0.103488 & 0.0517439 \tabularnewline
126 & 0.943068 & 0.113864 & 0.0569319 \tabularnewline
127 & 0.953028 & 0.0939445 & 0.0469723 \tabularnewline
128 & 0.942899 & 0.114201 & 0.0571007 \tabularnewline
129 & 0.956194 & 0.0876124 & 0.0438062 \tabularnewline
130 & 0.951593 & 0.0968136 & 0.0484068 \tabularnewline
131 & 0.977573 & 0.0448543 & 0.0224272 \tabularnewline
132 & 0.973093 & 0.0538145 & 0.0269072 \tabularnewline
133 & 0.967375 & 0.0652501 & 0.0326251 \tabularnewline
134 & 0.982407 & 0.035187 & 0.0175935 \tabularnewline
135 & 0.978488 & 0.0430239 & 0.0215119 \tabularnewline
136 & 0.972942 & 0.0541151 & 0.0270576 \tabularnewline
137 & 0.968685 & 0.0626292 & 0.0313146 \tabularnewline
138 & 0.967922 & 0.0641566 & 0.0320783 \tabularnewline
139 & 0.962334 & 0.0753321 & 0.037666 \tabularnewline
140 & 0.959487 & 0.0810256 & 0.0405128 \tabularnewline
141 & 0.950289 & 0.0994215 & 0.0497107 \tabularnewline
142 & 0.947241 & 0.105517 & 0.0527585 \tabularnewline
143 & 0.942484 & 0.115032 & 0.0575159 \tabularnewline
144 & 0.944351 & 0.111298 & 0.0556491 \tabularnewline
145 & 0.948435 & 0.103131 & 0.0515654 \tabularnewline
146 & 0.939043 & 0.121914 & 0.0609571 \tabularnewline
147 & 0.930529 & 0.138942 & 0.0694711 \tabularnewline
148 & 0.917203 & 0.165595 & 0.0827973 \tabularnewline
149 & 0.902476 & 0.195048 & 0.0975242 \tabularnewline
150 & 0.88541 & 0.229181 & 0.11459 \tabularnewline
151 & 0.871376 & 0.257249 & 0.128624 \tabularnewline
152 & 0.92335 & 0.153301 & 0.0766503 \tabularnewline
153 & 0.90837 & 0.18326 & 0.0916301 \tabularnewline
154 & 0.893846 & 0.212308 & 0.106154 \tabularnewline
155 & 0.876878 & 0.246244 & 0.123122 \tabularnewline
156 & 0.854711 & 0.290579 & 0.145289 \tabularnewline
157 & 0.831449 & 0.337102 & 0.168551 \tabularnewline
158 & 0.829436 & 0.341128 & 0.170564 \tabularnewline
159 & 0.801982 & 0.396035 & 0.198018 \tabularnewline
160 & 0.829733 & 0.340535 & 0.170267 \tabularnewline
161 & 0.838285 & 0.32343 & 0.161715 \tabularnewline
162 & 0.818931 & 0.362139 & 0.181069 \tabularnewline
163 & 0.806015 & 0.38797 & 0.193985 \tabularnewline
164 & 0.801249 & 0.397501 & 0.198751 \tabularnewline
165 & 0.779933 & 0.440134 & 0.220067 \tabularnewline
166 & 0.756187 & 0.487625 & 0.243813 \tabularnewline
167 & 0.72191 & 0.55618 & 0.27809 \tabularnewline
168 & 0.717669 & 0.564662 & 0.282331 \tabularnewline
169 & 0.782167 & 0.435666 & 0.217833 \tabularnewline
170 & 0.756545 & 0.486911 & 0.243455 \tabularnewline
171 & 0.724627 & 0.550746 & 0.275373 \tabularnewline
172 & 0.719631 & 0.560738 & 0.280369 \tabularnewline
173 & 0.854905 & 0.29019 & 0.145095 \tabularnewline
174 & 0.827934 & 0.344133 & 0.172066 \tabularnewline
175 & 0.824751 & 0.350498 & 0.175249 \tabularnewline
176 & 0.850041 & 0.299918 & 0.149959 \tabularnewline
177 & 0.822727 & 0.354547 & 0.177273 \tabularnewline
178 & 0.807158 & 0.385683 & 0.192842 \tabularnewline
179 & 0.805381 & 0.389237 & 0.194619 \tabularnewline
180 & 0.8807 & 0.238599 & 0.1193 \tabularnewline
181 & 0.899225 & 0.20155 & 0.100775 \tabularnewline
182 & 0.909776 & 0.180448 & 0.0902239 \tabularnewline
183 & 0.930186 & 0.139628 & 0.069814 \tabularnewline
184 & 0.913841 & 0.172318 & 0.0861588 \tabularnewline
185 & 0.893875 & 0.212251 & 0.106125 \tabularnewline
186 & 0.888709 & 0.222581 & 0.111291 \tabularnewline
187 & 0.974401 & 0.0511975 & 0.0255988 \tabularnewline
188 & 0.973198 & 0.0536034 & 0.0268017 \tabularnewline
189 & 0.965246 & 0.0695085 & 0.0347542 \tabularnewline
190 & 0.954551 & 0.0908982 & 0.0454491 \tabularnewline
191 & 0.940139 & 0.119721 & 0.0598607 \tabularnewline
192 & 0.9261 & 0.147801 & 0.0739004 \tabularnewline
193 & 0.931319 & 0.137362 & 0.0686809 \tabularnewline
194 & 0.924718 & 0.150563 & 0.0752815 \tabularnewline
195 & 0.95575 & 0.0885003 & 0.0442502 \tabularnewline
196 & 0.943184 & 0.113631 & 0.0568157 \tabularnewline
197 & 0.935355 & 0.129289 & 0.0646447 \tabularnewline
198 & 0.935355 & 0.129291 & 0.0646455 \tabularnewline
199 & 0.922373 & 0.155254 & 0.077627 \tabularnewline
200 & 0.905379 & 0.189241 & 0.0946206 \tabularnewline
201 & 0.881648 & 0.236704 & 0.118352 \tabularnewline
202 & 0.848118 & 0.303764 & 0.151882 \tabularnewline
203 & 0.835828 & 0.328344 & 0.164172 \tabularnewline
204 & 0.827742 & 0.344516 & 0.172258 \tabularnewline
205 & 0.783983 & 0.432034 & 0.216017 \tabularnewline
206 & 0.74277 & 0.51446 & 0.25723 \tabularnewline
207 & 0.718571 & 0.562858 & 0.281429 \tabularnewline
208 & 0.757976 & 0.484048 & 0.242024 \tabularnewline
209 & 0.933808 & 0.132383 & 0.0661917 \tabularnewline
210 & 0.928259 & 0.143482 & 0.0717409 \tabularnewline
211 & 0.960736 & 0.0785279 & 0.0392639 \tabularnewline
212 & 0.947795 & 0.104409 & 0.0522047 \tabularnewline
213 & 0.953901 & 0.0921987 & 0.0460993 \tabularnewline
214 & 0.957233 & 0.0855336 & 0.0427668 \tabularnewline
215 & 0.945769 & 0.108462 & 0.0542312 \tabularnewline
216 & 0.918771 & 0.162459 & 0.0812293 \tabularnewline
217 & 0.876342 & 0.247316 & 0.123658 \tabularnewline
218 & 0.838844 & 0.322311 & 0.161156 \tabularnewline
219 & 0.762931 & 0.474138 & 0.237069 \tabularnewline
220 & 0.888527 & 0.222947 & 0.111473 \tabularnewline
221 & 0.820069 & 0.359861 & 0.179931 \tabularnewline
222 & 0.71831 & 0.563381 & 0.28169 \tabularnewline
223 & 0.580083 & 0.839835 & 0.419917 \tabularnewline
224 & 0.428506 & 0.857012 & 0.571494 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264816&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]0.411495[/C][C]0.822989[/C][C]0.588505[/C][/ROW]
[ROW][C]6[/C][C]0.292221[/C][C]0.584443[/C][C]0.707779[/C][/ROW]
[ROW][C]7[/C][C]0.372677[/C][C]0.745354[/C][C]0.627323[/C][/ROW]
[ROW][C]8[/C][C]0.264095[/C][C]0.528189[/C][C]0.735905[/C][/ROW]
[ROW][C]9[/C][C]0.20896[/C][C]0.417919[/C][C]0.79104[/C][/ROW]
[ROW][C]10[/C][C]0.150039[/C][C]0.300079[/C][C]0.849961[/C][/ROW]
[ROW][C]11[/C][C]0.189278[/C][C]0.378556[/C][C]0.810722[/C][/ROW]
[ROW][C]12[/C][C]0.13838[/C][C]0.27676[/C][C]0.86162[/C][/ROW]
[ROW][C]13[/C][C]0.382685[/C][C]0.765371[/C][C]0.617315[/C][/ROW]
[ROW][C]14[/C][C]0.303652[/C][C]0.607304[/C][C]0.696348[/C][/ROW]
[ROW][C]15[/C][C]0.264765[/C][C]0.529529[/C][C]0.735235[/C][/ROW]
[ROW][C]16[/C][C]0.239307[/C][C]0.478615[/C][C]0.760693[/C][/ROW]
[ROW][C]17[/C][C]0.194625[/C][C]0.389249[/C][C]0.805375[/C][/ROW]
[ROW][C]18[/C][C]0.221617[/C][C]0.443233[/C][C]0.778383[/C][/ROW]
[ROW][C]19[/C][C]0.172527[/C][C]0.345054[/C][C]0.827473[/C][/ROW]
[ROW][C]20[/C][C]0.137259[/C][C]0.274519[/C][C]0.862741[/C][/ROW]
[ROW][C]21[/C][C]0.102579[/C][C]0.205159[/C][C]0.897421[/C][/ROW]
[ROW][C]22[/C][C]0.193609[/C][C]0.387218[/C][C]0.806391[/C][/ROW]
[ROW][C]23[/C][C]0.156854[/C][C]0.313709[/C][C]0.843146[/C][/ROW]
[ROW][C]24[/C][C]0.121712[/C][C]0.243423[/C][C]0.878288[/C][/ROW]
[ROW][C]25[/C][C]0.125071[/C][C]0.250143[/C][C]0.874929[/C][/ROW]
[ROW][C]26[/C][C]0.097708[/C][C]0.195416[/C][C]0.902292[/C][/ROW]
[ROW][C]27[/C][C]0.0845401[/C][C]0.16908[/C][C]0.91546[/C][/ROW]
[ROW][C]28[/C][C]0.0635828[/C][C]0.127166[/C][C]0.936417[/C][/ROW]
[ROW][C]29[/C][C]0.0490239[/C][C]0.0980478[/C][C]0.950976[/C][/ROW]
[ROW][C]30[/C][C]0.0408285[/C][C]0.081657[/C][C]0.959172[/C][/ROW]
[ROW][C]31[/C][C]0.0306253[/C][C]0.0612507[/C][C]0.969375[/C][/ROW]
[ROW][C]32[/C][C]0.026053[/C][C]0.0521061[/C][C]0.973947[/C][/ROW]
[ROW][C]33[/C][C]0.0187038[/C][C]0.0374075[/C][C]0.981296[/C][/ROW]
[ROW][C]34[/C][C]0.0140622[/C][C]0.0281243[/C][C]0.985938[/C][/ROW]
[ROW][C]35[/C][C]0.0100408[/C][C]0.0200816[/C][C]0.989959[/C][/ROW]
[ROW][C]36[/C][C]0.00697824[/C][C]0.0139565[/C][C]0.993022[/C][/ROW]
[ROW][C]37[/C][C]0.00477974[/C][C]0.00955948[/C][C]0.99522[/C][/ROW]
[ROW][C]38[/C][C]0.00335975[/C][C]0.00671949[/C][C]0.99664[/C][/ROW]
[ROW][C]39[/C][C]0.0028466[/C][C]0.00569319[/C][C]0.997153[/C][/ROW]
[ROW][C]40[/C][C]0.00207986[/C][C]0.00415971[/C][C]0.99792[/C][/ROW]
[ROW][C]41[/C][C]0.00232288[/C][C]0.00464576[/C][C]0.997677[/C][/ROW]
[ROW][C]42[/C][C]0.00203116[/C][C]0.00406233[/C][C]0.997969[/C][/ROW]
[ROW][C]43[/C][C]0.00151126[/C][C]0.00302252[/C][C]0.998489[/C][/ROW]
[ROW][C]44[/C][C]0.00242128[/C][C]0.00484255[/C][C]0.997579[/C][/ROW]
[ROW][C]45[/C][C]0.00219084[/C][C]0.00438167[/C][C]0.997809[/C][/ROW]
[ROW][C]46[/C][C]0.00252911[/C][C]0.00505823[/C][C]0.997471[/C][/ROW]
[ROW][C]47[/C][C]0.00194279[/C][C]0.00388558[/C][C]0.998057[/C][/ROW]
[ROW][C]48[/C][C]0.00152917[/C][C]0.00305835[/C][C]0.998471[/C][/ROW]
[ROW][C]49[/C][C]0.00126191[/C][C]0.00252383[/C][C]0.998738[/C][/ROW]
[ROW][C]50[/C][C]0.000909621[/C][C]0.00181924[/C][C]0.99909[/C][/ROW]
[ROW][C]51[/C][C]0.000761445[/C][C]0.00152289[/C][C]0.999239[/C][/ROW]
[ROW][C]52[/C][C]0.00122954[/C][C]0.00245908[/C][C]0.99877[/C][/ROW]
[ROW][C]53[/C][C]0.000947086[/C][C]0.00189417[/C][C]0.999053[/C][/ROW]
[ROW][C]54[/C][C]0.000700257[/C][C]0.00140051[/C][C]0.9993[/C][/ROW]
[ROW][C]55[/C][C]0.00698207[/C][C]0.0139641[/C][C]0.993018[/C][/ROW]
[ROW][C]56[/C][C]0.00591188[/C][C]0.0118238[/C][C]0.994088[/C][/ROW]
[ROW][C]57[/C][C]0.00462112[/C][C]0.00924223[/C][C]0.995379[/C][/ROW]
[ROW][C]58[/C][C]0.0145437[/C][C]0.0290875[/C][C]0.985456[/C][/ROW]
[ROW][C]59[/C][C]0.0165609[/C][C]0.0331218[/C][C]0.983439[/C][/ROW]
[ROW][C]60[/C][C]0.0181406[/C][C]0.0362813[/C][C]0.981859[/C][/ROW]
[ROW][C]61[/C][C]0.0162588[/C][C]0.0325176[/C][C]0.983741[/C][/ROW]
[ROW][C]62[/C][C]0.0378019[/C][C]0.0756038[/C][C]0.962198[/C][/ROW]
[ROW][C]63[/C][C]0.0330088[/C][C]0.0660176[/C][C]0.966991[/C][/ROW]
[ROW][C]64[/C][C]0.119175[/C][C]0.23835[/C][C]0.880825[/C][/ROW]
[ROW][C]65[/C][C]0.108873[/C][C]0.217746[/C][C]0.891127[/C][/ROW]
[ROW][C]66[/C][C]0.241566[/C][C]0.483131[/C][C]0.758434[/C][/ROW]
[ROW][C]67[/C][C]0.387595[/C][C]0.775191[/C][C]0.612405[/C][/ROW]
[ROW][C]68[/C][C]0.465605[/C][C]0.93121[/C][C]0.534395[/C][/ROW]
[ROW][C]69[/C][C]0.435234[/C][C]0.870467[/C][C]0.564766[/C][/ROW]
[ROW][C]70[/C][C]0.530918[/C][C]0.938165[/C][C]0.469082[/C][/ROW]
[ROW][C]71[/C][C]0.707402[/C][C]0.585196[/C][C]0.292598[/C][/ROW]
[ROW][C]72[/C][C]0.738516[/C][C]0.522969[/C][C]0.261484[/C][/ROW]
[ROW][C]73[/C][C]0.720253[/C][C]0.559494[/C][C]0.279747[/C][/ROW]
[ROW][C]74[/C][C]0.809397[/C][C]0.381205[/C][C]0.190603[/C][/ROW]
[ROW][C]75[/C][C]0.803487[/C][C]0.393025[/C][C]0.196513[/C][/ROW]
[ROW][C]76[/C][C]0.788629[/C][C]0.422743[/C][C]0.211371[/C][/ROW]
[ROW][C]77[/C][C]0.763627[/C][C]0.472746[/C][C]0.236373[/C][/ROW]
[ROW][C]78[/C][C]0.785643[/C][C]0.428714[/C][C]0.214357[/C][/ROW]
[ROW][C]79[/C][C]0.764251[/C][C]0.471497[/C][C]0.235749[/C][/ROW]
[ROW][C]80[/C][C]0.857203[/C][C]0.285594[/C][C]0.142797[/C][/ROW]
[ROW][C]81[/C][C]0.842237[/C][C]0.315527[/C][C]0.157763[/C][/ROW]
[ROW][C]82[/C][C]0.829474[/C][C]0.341052[/C][C]0.170526[/C][/ROW]
[ROW][C]83[/C][C]0.838225[/C][C]0.323551[/C][C]0.161775[/C][/ROW]
[ROW][C]84[/C][C]0.82717[/C][C]0.345661[/C][C]0.17283[/C][/ROW]
[ROW][C]85[/C][C]0.815655[/C][C]0.368691[/C][C]0.184345[/C][/ROW]
[ROW][C]86[/C][C]0.791171[/C][C]0.417659[/C][C]0.208829[/C][/ROW]
[ROW][C]87[/C][C]0.764712[/C][C]0.470575[/C][C]0.235288[/C][/ROW]
[ROW][C]88[/C][C]0.80118[/C][C]0.39764[/C][C]0.19882[/C][/ROW]
[ROW][C]89[/C][C]0.825857[/C][C]0.348286[/C][C]0.174143[/C][/ROW]
[ROW][C]90[/C][C]0.872636[/C][C]0.254728[/C][C]0.127364[/C][/ROW]
[ROW][C]91[/C][C]0.875977[/C][C]0.248046[/C][C]0.124023[/C][/ROW]
[ROW][C]92[/C][C]0.860543[/C][C]0.278915[/C][C]0.139457[/C][/ROW]
[ROW][C]93[/C][C]0.889943[/C][C]0.220114[/C][C]0.110057[/C][/ROW]
[ROW][C]94[/C][C]0.882714[/C][C]0.234572[/C][C]0.117286[/C][/ROW]
[ROW][C]95[/C][C]0.90536[/C][C]0.18928[/C][C]0.0946398[/C][/ROW]
[ROW][C]96[/C][C]0.907327[/C][C]0.185347[/C][C]0.0926735[/C][/ROW]
[ROW][C]97[/C][C]0.921516[/C][C]0.156968[/C][C]0.078484[/C][/ROW]
[ROW][C]98[/C][C]0.907854[/C][C]0.184292[/C][C]0.0921459[/C][/ROW]
[ROW][C]99[/C][C]0.895995[/C][C]0.20801[/C][C]0.104005[/C][/ROW]
[ROW][C]100[/C][C]0.884178[/C][C]0.231644[/C][C]0.115822[/C][/ROW]
[ROW][C]101[/C][C]0.913576[/C][C]0.172848[/C][C]0.0864238[/C][/ROW]
[ROW][C]102[/C][C]0.92343[/C][C]0.153139[/C][C]0.0765696[/C][/ROW]
[ROW][C]103[/C][C]0.922027[/C][C]0.155946[/C][C]0.0779732[/C][/ROW]
[ROW][C]104[/C][C]0.943101[/C][C]0.113798[/C][C]0.0568988[/C][/ROW]
[ROW][C]105[/C][C]0.944695[/C][C]0.11061[/C][C]0.0553049[/C][/ROW]
[ROW][C]106[/C][C]0.936215[/C][C]0.12757[/C][C]0.0637849[/C][/ROW]
[ROW][C]107[/C][C]0.924486[/C][C]0.151028[/C][C]0.075514[/C][/ROW]
[ROW][C]108[/C][C]0.952043[/C][C]0.0959133[/C][C]0.0479566[/C][/ROW]
[ROW][C]109[/C][C]0.947019[/C][C]0.105962[/C][C]0.0529812[/C][/ROW]
[ROW][C]110[/C][C]0.939177[/C][C]0.121646[/C][C]0.0608232[/C][/ROW]
[ROW][C]111[/C][C]0.935525[/C][C]0.12895[/C][C]0.0644748[/C][/ROW]
[ROW][C]112[/C][C]0.948104[/C][C]0.103791[/C][C]0.0518956[/C][/ROW]
[ROW][C]113[/C][C]0.945755[/C][C]0.10849[/C][C]0.0542452[/C][/ROW]
[ROW][C]114[/C][C]0.9465[/C][C]0.107[/C][C]0.0534998[/C][/ROW]
[ROW][C]115[/C][C]0.945218[/C][C]0.109564[/C][C]0.054782[/C][/ROW]
[ROW][C]116[/C][C]0.96639[/C][C]0.0672202[/C][C]0.0336101[/C][/ROW]
[ROW][C]117[/C][C]0.962512[/C][C]0.0749754[/C][C]0.0374877[/C][/ROW]
[ROW][C]118[/C][C]0.969088[/C][C]0.0618246[/C][C]0.0309123[/C][/ROW]
[ROW][C]119[/C][C]0.964719[/C][C]0.0705622[/C][C]0.0352811[/C][/ROW]
[ROW][C]120[/C][C]0.958083[/C][C]0.0838344[/C][C]0.0419172[/C][/ROW]
[ROW][C]121[/C][C]0.957291[/C][C]0.0854185[/C][C]0.0427092[/C][/ROW]
[ROW][C]122[/C][C]0.955306[/C][C]0.0893878[/C][C]0.0446939[/C][/ROW]
[ROW][C]123[/C][C]0.960033[/C][C]0.0799335[/C][C]0.0399668[/C][/ROW]
[ROW][C]124[/C][C]0.953097[/C][C]0.0938057[/C][C]0.0469029[/C][/ROW]
[ROW][C]125[/C][C]0.948256[/C][C]0.103488[/C][C]0.0517439[/C][/ROW]
[ROW][C]126[/C][C]0.943068[/C][C]0.113864[/C][C]0.0569319[/C][/ROW]
[ROW][C]127[/C][C]0.953028[/C][C]0.0939445[/C][C]0.0469723[/C][/ROW]
[ROW][C]128[/C][C]0.942899[/C][C]0.114201[/C][C]0.0571007[/C][/ROW]
[ROW][C]129[/C][C]0.956194[/C][C]0.0876124[/C][C]0.0438062[/C][/ROW]
[ROW][C]130[/C][C]0.951593[/C][C]0.0968136[/C][C]0.0484068[/C][/ROW]
[ROW][C]131[/C][C]0.977573[/C][C]0.0448543[/C][C]0.0224272[/C][/ROW]
[ROW][C]132[/C][C]0.973093[/C][C]0.0538145[/C][C]0.0269072[/C][/ROW]
[ROW][C]133[/C][C]0.967375[/C][C]0.0652501[/C][C]0.0326251[/C][/ROW]
[ROW][C]134[/C][C]0.982407[/C][C]0.035187[/C][C]0.0175935[/C][/ROW]
[ROW][C]135[/C][C]0.978488[/C][C]0.0430239[/C][C]0.0215119[/C][/ROW]
[ROW][C]136[/C][C]0.972942[/C][C]0.0541151[/C][C]0.0270576[/C][/ROW]
[ROW][C]137[/C][C]0.968685[/C][C]0.0626292[/C][C]0.0313146[/C][/ROW]
[ROW][C]138[/C][C]0.967922[/C][C]0.0641566[/C][C]0.0320783[/C][/ROW]
[ROW][C]139[/C][C]0.962334[/C][C]0.0753321[/C][C]0.037666[/C][/ROW]
[ROW][C]140[/C][C]0.959487[/C][C]0.0810256[/C][C]0.0405128[/C][/ROW]
[ROW][C]141[/C][C]0.950289[/C][C]0.0994215[/C][C]0.0497107[/C][/ROW]
[ROW][C]142[/C][C]0.947241[/C][C]0.105517[/C][C]0.0527585[/C][/ROW]
[ROW][C]143[/C][C]0.942484[/C][C]0.115032[/C][C]0.0575159[/C][/ROW]
[ROW][C]144[/C][C]0.944351[/C][C]0.111298[/C][C]0.0556491[/C][/ROW]
[ROW][C]145[/C][C]0.948435[/C][C]0.103131[/C][C]0.0515654[/C][/ROW]
[ROW][C]146[/C][C]0.939043[/C][C]0.121914[/C][C]0.0609571[/C][/ROW]
[ROW][C]147[/C][C]0.930529[/C][C]0.138942[/C][C]0.0694711[/C][/ROW]
[ROW][C]148[/C][C]0.917203[/C][C]0.165595[/C][C]0.0827973[/C][/ROW]
[ROW][C]149[/C][C]0.902476[/C][C]0.195048[/C][C]0.0975242[/C][/ROW]
[ROW][C]150[/C][C]0.88541[/C][C]0.229181[/C][C]0.11459[/C][/ROW]
[ROW][C]151[/C][C]0.871376[/C][C]0.257249[/C][C]0.128624[/C][/ROW]
[ROW][C]152[/C][C]0.92335[/C][C]0.153301[/C][C]0.0766503[/C][/ROW]
[ROW][C]153[/C][C]0.90837[/C][C]0.18326[/C][C]0.0916301[/C][/ROW]
[ROW][C]154[/C][C]0.893846[/C][C]0.212308[/C][C]0.106154[/C][/ROW]
[ROW][C]155[/C][C]0.876878[/C][C]0.246244[/C][C]0.123122[/C][/ROW]
[ROW][C]156[/C][C]0.854711[/C][C]0.290579[/C][C]0.145289[/C][/ROW]
[ROW][C]157[/C][C]0.831449[/C][C]0.337102[/C][C]0.168551[/C][/ROW]
[ROW][C]158[/C][C]0.829436[/C][C]0.341128[/C][C]0.170564[/C][/ROW]
[ROW][C]159[/C][C]0.801982[/C][C]0.396035[/C][C]0.198018[/C][/ROW]
[ROW][C]160[/C][C]0.829733[/C][C]0.340535[/C][C]0.170267[/C][/ROW]
[ROW][C]161[/C][C]0.838285[/C][C]0.32343[/C][C]0.161715[/C][/ROW]
[ROW][C]162[/C][C]0.818931[/C][C]0.362139[/C][C]0.181069[/C][/ROW]
[ROW][C]163[/C][C]0.806015[/C][C]0.38797[/C][C]0.193985[/C][/ROW]
[ROW][C]164[/C][C]0.801249[/C][C]0.397501[/C][C]0.198751[/C][/ROW]
[ROW][C]165[/C][C]0.779933[/C][C]0.440134[/C][C]0.220067[/C][/ROW]
[ROW][C]166[/C][C]0.756187[/C][C]0.487625[/C][C]0.243813[/C][/ROW]
[ROW][C]167[/C][C]0.72191[/C][C]0.55618[/C][C]0.27809[/C][/ROW]
[ROW][C]168[/C][C]0.717669[/C][C]0.564662[/C][C]0.282331[/C][/ROW]
[ROW][C]169[/C][C]0.782167[/C][C]0.435666[/C][C]0.217833[/C][/ROW]
[ROW][C]170[/C][C]0.756545[/C][C]0.486911[/C][C]0.243455[/C][/ROW]
[ROW][C]171[/C][C]0.724627[/C][C]0.550746[/C][C]0.275373[/C][/ROW]
[ROW][C]172[/C][C]0.719631[/C][C]0.560738[/C][C]0.280369[/C][/ROW]
[ROW][C]173[/C][C]0.854905[/C][C]0.29019[/C][C]0.145095[/C][/ROW]
[ROW][C]174[/C][C]0.827934[/C][C]0.344133[/C][C]0.172066[/C][/ROW]
[ROW][C]175[/C][C]0.824751[/C][C]0.350498[/C][C]0.175249[/C][/ROW]
[ROW][C]176[/C][C]0.850041[/C][C]0.299918[/C][C]0.149959[/C][/ROW]
[ROW][C]177[/C][C]0.822727[/C][C]0.354547[/C][C]0.177273[/C][/ROW]
[ROW][C]178[/C][C]0.807158[/C][C]0.385683[/C][C]0.192842[/C][/ROW]
[ROW][C]179[/C][C]0.805381[/C][C]0.389237[/C][C]0.194619[/C][/ROW]
[ROW][C]180[/C][C]0.8807[/C][C]0.238599[/C][C]0.1193[/C][/ROW]
[ROW][C]181[/C][C]0.899225[/C][C]0.20155[/C][C]0.100775[/C][/ROW]
[ROW][C]182[/C][C]0.909776[/C][C]0.180448[/C][C]0.0902239[/C][/ROW]
[ROW][C]183[/C][C]0.930186[/C][C]0.139628[/C][C]0.069814[/C][/ROW]
[ROW][C]184[/C][C]0.913841[/C][C]0.172318[/C][C]0.0861588[/C][/ROW]
[ROW][C]185[/C][C]0.893875[/C][C]0.212251[/C][C]0.106125[/C][/ROW]
[ROW][C]186[/C][C]0.888709[/C][C]0.222581[/C][C]0.111291[/C][/ROW]
[ROW][C]187[/C][C]0.974401[/C][C]0.0511975[/C][C]0.0255988[/C][/ROW]
[ROW][C]188[/C][C]0.973198[/C][C]0.0536034[/C][C]0.0268017[/C][/ROW]
[ROW][C]189[/C][C]0.965246[/C][C]0.0695085[/C][C]0.0347542[/C][/ROW]
[ROW][C]190[/C][C]0.954551[/C][C]0.0908982[/C][C]0.0454491[/C][/ROW]
[ROW][C]191[/C][C]0.940139[/C][C]0.119721[/C][C]0.0598607[/C][/ROW]
[ROW][C]192[/C][C]0.9261[/C][C]0.147801[/C][C]0.0739004[/C][/ROW]
[ROW][C]193[/C][C]0.931319[/C][C]0.137362[/C][C]0.0686809[/C][/ROW]
[ROW][C]194[/C][C]0.924718[/C][C]0.150563[/C][C]0.0752815[/C][/ROW]
[ROW][C]195[/C][C]0.95575[/C][C]0.0885003[/C][C]0.0442502[/C][/ROW]
[ROW][C]196[/C][C]0.943184[/C][C]0.113631[/C][C]0.0568157[/C][/ROW]
[ROW][C]197[/C][C]0.935355[/C][C]0.129289[/C][C]0.0646447[/C][/ROW]
[ROW][C]198[/C][C]0.935355[/C][C]0.129291[/C][C]0.0646455[/C][/ROW]
[ROW][C]199[/C][C]0.922373[/C][C]0.155254[/C][C]0.077627[/C][/ROW]
[ROW][C]200[/C][C]0.905379[/C][C]0.189241[/C][C]0.0946206[/C][/ROW]
[ROW][C]201[/C][C]0.881648[/C][C]0.236704[/C][C]0.118352[/C][/ROW]
[ROW][C]202[/C][C]0.848118[/C][C]0.303764[/C][C]0.151882[/C][/ROW]
[ROW][C]203[/C][C]0.835828[/C][C]0.328344[/C][C]0.164172[/C][/ROW]
[ROW][C]204[/C][C]0.827742[/C][C]0.344516[/C][C]0.172258[/C][/ROW]
[ROW][C]205[/C][C]0.783983[/C][C]0.432034[/C][C]0.216017[/C][/ROW]
[ROW][C]206[/C][C]0.74277[/C][C]0.51446[/C][C]0.25723[/C][/ROW]
[ROW][C]207[/C][C]0.718571[/C][C]0.562858[/C][C]0.281429[/C][/ROW]
[ROW][C]208[/C][C]0.757976[/C][C]0.484048[/C][C]0.242024[/C][/ROW]
[ROW][C]209[/C][C]0.933808[/C][C]0.132383[/C][C]0.0661917[/C][/ROW]
[ROW][C]210[/C][C]0.928259[/C][C]0.143482[/C][C]0.0717409[/C][/ROW]
[ROW][C]211[/C][C]0.960736[/C][C]0.0785279[/C][C]0.0392639[/C][/ROW]
[ROW][C]212[/C][C]0.947795[/C][C]0.104409[/C][C]0.0522047[/C][/ROW]
[ROW][C]213[/C][C]0.953901[/C][C]0.0921987[/C][C]0.0460993[/C][/ROW]
[ROW][C]214[/C][C]0.957233[/C][C]0.0855336[/C][C]0.0427668[/C][/ROW]
[ROW][C]215[/C][C]0.945769[/C][C]0.108462[/C][C]0.0542312[/C][/ROW]
[ROW][C]216[/C][C]0.918771[/C][C]0.162459[/C][C]0.0812293[/C][/ROW]
[ROW][C]217[/C][C]0.876342[/C][C]0.247316[/C][C]0.123658[/C][/ROW]
[ROW][C]218[/C][C]0.838844[/C][C]0.322311[/C][C]0.161156[/C][/ROW]
[ROW][C]219[/C][C]0.762931[/C][C]0.474138[/C][C]0.237069[/C][/ROW]
[ROW][C]220[/C][C]0.888527[/C][C]0.222947[/C][C]0.111473[/C][/ROW]
[ROW][C]221[/C][C]0.820069[/C][C]0.359861[/C][C]0.179931[/C][/ROW]
[ROW][C]222[/C][C]0.71831[/C][C]0.563381[/C][C]0.28169[/C][/ROW]
[ROW][C]223[/C][C]0.580083[/C][C]0.839835[/C][C]0.419917[/C][/ROW]
[ROW][C]224[/C][C]0.428506[/C][C]0.857012[/C][C]0.571494[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264816&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264816&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
50.4114950.8229890.588505
60.2922210.5844430.707779
70.3726770.7453540.627323
80.2640950.5281890.735905
90.208960.4179190.79104
100.1500390.3000790.849961
110.1892780.3785560.810722
120.138380.276760.86162
130.3826850.7653710.617315
140.3036520.6073040.696348
150.2647650.5295290.735235
160.2393070.4786150.760693
170.1946250.3892490.805375
180.2216170.4432330.778383
190.1725270.3450540.827473
200.1372590.2745190.862741
210.1025790.2051590.897421
220.1936090.3872180.806391
230.1568540.3137090.843146
240.1217120.2434230.878288
250.1250710.2501430.874929
260.0977080.1954160.902292
270.08454010.169080.91546
280.06358280.1271660.936417
290.04902390.09804780.950976
300.04082850.0816570.959172
310.03062530.06125070.969375
320.0260530.05210610.973947
330.01870380.03740750.981296
340.01406220.02812430.985938
350.01004080.02008160.989959
360.006978240.01395650.993022
370.004779740.009559480.99522
380.003359750.006719490.99664
390.00284660.005693190.997153
400.002079860.004159710.99792
410.002322880.004645760.997677
420.002031160.004062330.997969
430.001511260.003022520.998489
440.002421280.004842550.997579
450.002190840.004381670.997809
460.002529110.005058230.997471
470.001942790.003885580.998057
480.001529170.003058350.998471
490.001261910.002523830.998738
500.0009096210.001819240.99909
510.0007614450.001522890.999239
520.001229540.002459080.99877
530.0009470860.001894170.999053
540.0007002570.001400510.9993
550.006982070.01396410.993018
560.005911880.01182380.994088
570.004621120.009242230.995379
580.01454370.02908750.985456
590.01656090.03312180.983439
600.01814060.03628130.981859
610.01625880.03251760.983741
620.03780190.07560380.962198
630.03300880.06601760.966991
640.1191750.238350.880825
650.1088730.2177460.891127
660.2415660.4831310.758434
670.3875950.7751910.612405
680.4656050.931210.534395
690.4352340.8704670.564766
700.5309180.9381650.469082
710.7074020.5851960.292598
720.7385160.5229690.261484
730.7202530.5594940.279747
740.8093970.3812050.190603
750.8034870.3930250.196513
760.7886290.4227430.211371
770.7636270.4727460.236373
780.7856430.4287140.214357
790.7642510.4714970.235749
800.8572030.2855940.142797
810.8422370.3155270.157763
820.8294740.3410520.170526
830.8382250.3235510.161775
840.827170.3456610.17283
850.8156550.3686910.184345
860.7911710.4176590.208829
870.7647120.4705750.235288
880.801180.397640.19882
890.8258570.3482860.174143
900.8726360.2547280.127364
910.8759770.2480460.124023
920.8605430.2789150.139457
930.8899430.2201140.110057
940.8827140.2345720.117286
950.905360.189280.0946398
960.9073270.1853470.0926735
970.9215160.1569680.078484
980.9078540.1842920.0921459
990.8959950.208010.104005
1000.8841780.2316440.115822
1010.9135760.1728480.0864238
1020.923430.1531390.0765696
1030.9220270.1559460.0779732
1040.9431010.1137980.0568988
1050.9446950.110610.0553049
1060.9362150.127570.0637849
1070.9244860.1510280.075514
1080.9520430.09591330.0479566
1090.9470190.1059620.0529812
1100.9391770.1216460.0608232
1110.9355250.128950.0644748
1120.9481040.1037910.0518956
1130.9457550.108490.0542452
1140.94650.1070.0534998
1150.9452180.1095640.054782
1160.966390.06722020.0336101
1170.9625120.07497540.0374877
1180.9690880.06182460.0309123
1190.9647190.07056220.0352811
1200.9580830.08383440.0419172
1210.9572910.08541850.0427092
1220.9553060.08938780.0446939
1230.9600330.07993350.0399668
1240.9530970.09380570.0469029
1250.9482560.1034880.0517439
1260.9430680.1138640.0569319
1270.9530280.09394450.0469723
1280.9428990.1142010.0571007
1290.9561940.08761240.0438062
1300.9515930.09681360.0484068
1310.9775730.04485430.0224272
1320.9730930.05381450.0269072
1330.9673750.06525010.0326251
1340.9824070.0351870.0175935
1350.9784880.04302390.0215119
1360.9729420.05411510.0270576
1370.9686850.06262920.0313146
1380.9679220.06415660.0320783
1390.9623340.07533210.037666
1400.9594870.08102560.0405128
1410.9502890.09942150.0497107
1420.9472410.1055170.0527585
1430.9424840.1150320.0575159
1440.9443510.1112980.0556491
1450.9484350.1031310.0515654
1460.9390430.1219140.0609571
1470.9305290.1389420.0694711
1480.9172030.1655950.0827973
1490.9024760.1950480.0975242
1500.885410.2291810.11459
1510.8713760.2572490.128624
1520.923350.1533010.0766503
1530.908370.183260.0916301
1540.8938460.2123080.106154
1550.8768780.2462440.123122
1560.8547110.2905790.145289
1570.8314490.3371020.168551
1580.8294360.3411280.170564
1590.8019820.3960350.198018
1600.8297330.3405350.170267
1610.8382850.323430.161715
1620.8189310.3621390.181069
1630.8060150.387970.193985
1640.8012490.3975010.198751
1650.7799330.4401340.220067
1660.7561870.4876250.243813
1670.721910.556180.27809
1680.7176690.5646620.282331
1690.7821670.4356660.217833
1700.7565450.4869110.243455
1710.7246270.5507460.275373
1720.7196310.5607380.280369
1730.8549050.290190.145095
1740.8279340.3441330.172066
1750.8247510.3504980.175249
1760.8500410.2999180.149959
1770.8227270.3545470.177273
1780.8071580.3856830.192842
1790.8053810.3892370.194619
1800.88070.2385990.1193
1810.8992250.201550.100775
1820.9097760.1804480.0902239
1830.9301860.1396280.069814
1840.9138410.1723180.0861588
1850.8938750.2122510.106125
1860.8887090.2225810.111291
1870.9744010.05119750.0255988
1880.9731980.05360340.0268017
1890.9652460.06950850.0347542
1900.9545510.09089820.0454491
1910.9401390.1197210.0598607
1920.92610.1478010.0739004
1930.9313190.1373620.0686809
1940.9247180.1505630.0752815
1950.955750.08850030.0442502
1960.9431840.1136310.0568157
1970.9353550.1292890.0646447
1980.9353550.1292910.0646455
1990.9223730.1552540.077627
2000.9053790.1892410.0946206
2010.8816480.2367040.118352
2020.8481180.3037640.151882
2030.8358280.3283440.164172
2040.8277420.3445160.172258
2050.7839830.4320340.216017
2060.742770.514460.25723
2070.7185710.5628580.281429
2080.7579760.4840480.242024
2090.9338080.1323830.0661917
2100.9282590.1434820.0717409
2110.9607360.07852790.0392639
2120.9477950.1044090.0522047
2130.9539010.09219870.0460993
2140.9572330.08553360.0427668
2150.9457690.1084620.0542312
2160.9187710.1624590.0812293
2170.8763420.2473160.123658
2180.8388440.3223110.161156
2190.7629310.4741380.237069
2200.8885270.2229470.111473
2210.8200690.3598610.179931
2220.718310.5633810.28169
2230.5800830.8398350.419917
2240.4285060.8570120.571494







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level190.0863636NOK
5% type I error level320.145455NOK
10% type I error level670.304545NOK

\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 & 19 & 0.0863636 & NOK \tabularnewline
5% type I error level & 32 & 0.145455 & NOK \tabularnewline
10% type I error level & 67 & 0.304545 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264816&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]19[/C][C]0.0863636[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]32[/C][C]0.145455[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]67[/C][C]0.304545[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264816&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264816&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 level190.0863636NOK
5% type I error level320.145455NOK
10% type I error level670.304545NOK



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