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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 20 Nov 2013 08:02:26 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/20/t1384952559s0wm5h2ej4kekv3.htm/, Retrieved Wed, 01 May 2024 22:16:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226597, Retrieved Wed, 01 May 2024 22:16:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [time effect in su...] [2010-11-17 08:55:33] [b98453cac15ba1066b407e146608df68]
- R  D  [Univariate Explorative Data Analysis] [WS 7] [2013-11-18 16:53:53] [d1af3aceda32c4de5f8ef20fdfdffdc9]
- RMPD    [Multiple Regression] [] [2013-11-19 20:42:56] [50191575d7f9c958084e7e760a37a7f0]
- R PD        [Multiple Regression] [] [2013-11-20 13:02:26] [0968a8b67fc621ded3325342a6e4b095] [Current]
- RMPD          [Multiple Regression] [] [2014-12-14 14:45:58] [69bf0eb8b9b38defaaf4848d8c317571]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 12 14 12 53 32 9
39 32 16 11 18 11 83 51 9
30 35 19 15 11 14 66 42 9
31 33 15 6 12 12 67 41 9
34 37 14 13 16 21 76 46 9
35 29 13 10 18 12 78 47 9
39 31 19 12 14 22 53 37 9
34 36 15 14 14 11 80 49 9
36 35 14 12 15 10 74 45 9
37 38 15 9 15 13 76 47 9
38 31 16 10 17 10 79 49 9
36 34 16 12 19 8 54 33 9
38 35 16 12 10 15 67 42 9
39 38 16 11 16 14 54 33 9
33 37 17 15 18 10 87 53 9
32 33 15 12 14 14 58 36 9
36 32 15 10 14 14 75 45 9
38 38 20 12 17 11 88 54 9
39 38 18 11 14 10 64 41 9
32 32 16 12 16 13 57 36 9
32 33 16 11 18 9.5 66 41 9
31 31 16 12 11 14 68 44 9
39 38 19 13 14 12 54 33 9
37 39 16 11 12 14 56 37 9
39 32 17 12 17 11 86 52 9
41 32 17 13 9 9 80 47 9
36 35 16 10 16 11 76 43 9
33 37 15 14 14 15 69 44 9
33 33 16 12 15 14 78 45 9
34 33 14 10 11 13 67 44 9
31 31 15 12 16 9 80 49 9
27 32 12 8 13 15 54 33 9
37 31 14 10 17 10 71 43 9
34 37 16 12 15 11 84 54 9
34 30 14 12 14 13 74 42 9
32 33 10 7 16 8 71 44 9
29 31 10 9 9 20 63 37 9
36 33 14 12 15 12 71 43 9
29 31 16 10 17 10 76 46 9
35 33 16 10 13 10 69 42 9
37 32 16 10 15 9 74 45 9
34 33 14 12 16 14 75 44 9
38 32 20 15 16 8 54 33 9
35 33 14 10 12 14 52 31 9
38 28 14 10 15 11 69 42 9
37 35 11 12 11 13 68 40 9
38 39 14 13 15 9 65 43 9
33 34 15 11 15 11 75 46 9
36 38 16 11 17 15 74 42 9
38 32 14 12 13 11 75 45 9
32 38 16 14 16 10 72 44 9
32 30 14 10 14 14 67 40 9
32 33 12 12 11 18 63 37 9
34 38 16 13 12 14 62 46 9
32 32 9 5 12 11 63 36 9
37 35 14 6 15 14.5 76 47 9
39 34 16 12 16 13 74 45 9
29 34 16 12 15 9 67 42 9
37 36 15 11 12 10 73 43 9
35 34 16 10 12 15 70 43 9
30 28 12 7 8 20 53 32 9
38 34 16 12 13 12 77 45 9
34 35 16 14 11 12 80 48 9
31 35 14 11 14 14 52 31 9
34 31 16 12 15 13 54 33 9
35 37 17 13 10 11 80 49 10
36 35 18 14 11 17 66 42 10
30 27 18 11 12 12 73 41 10
39 40 12 12 15 13 63 38 10
35 37 16 12 15 14 69 42 10
38 36 10 8 14 13 67 44 10
31 38 14 11 16 15 54 33 10
34 39 18 14 15 13 81 48 10
38 41 18 14 15 10 69 40 10
34 27 16 12 13 11 84 50 10
39 30 17 9 12 19 80 49 10
37 37 16 13 17 13 70 43 10
34 31 16 11 13 17 69 44 10
28 31 13 12 15 13 77 47 10
37 27 16 12 13 9 54 33 10
33 36 16 12 15 11 79 46 10
35 37 16 12 15 9 71 45 10
37 33 15 12 16 12 73 43 10
32 34 15 11 15 12 72 44 10
33 31 16 10 14 13 77 47 10
38 39 14 9 15 13 75 45 10
33 34 16 12 14 12 69 42 10
29 32 16 12 13 15 54 33 10
33 33 15 12 7 22 70 43 10
31 36 12 9 17 13 73 46 10
36 32 17 15 13 15 54 33 10
35 41 16 12 15 13 77 46 10
32 28 15 12 14 15 82 48 10
29 30 13 12 13 12.5 80 47 10
39 36 16 10 16 11 80 47 10
37 35 16 13 12 16 69 43 10
35 31 16 9 14 11 78 46 10
37 34 16 12 17 11 81 48 10
32 36 14 10 15 10 76 46 10
38 36 16 14 17 10 76 45 10
37 35 16 11 12 16 73 45 10
36 37 20 15 16 12 85 52 10
32 28 15 11 11 11 66 42 10
33 39 16 11 15 16 79 47 10
40 32 13 12 9 19 68 41 10
38 35 17 12 16 11 76 47 10
41 39 16 12 15 16 71 43 10
36 35 16 11 10 15 54 33 10
43 42 12 7 10 24 46 30 10
30 34 16 12 15 14 85 52 10
31 33 16 14 11 15 74 44 10
32 41 17 11 13 11 88 55 10
32 33 13 11 14 15 38 11 10
37 34 12 10 18 12 76 47 10
37 32 18 13 16 10 86 53 10
33 40 14 13 14 14 54 33 10
34 40 14 8 14 13 67 44 10
33 35 13 11 14 9 69 42 10
38 36 16 12 14 15 90 55 10
33 37 13 11 12 15 54 33 10
31 27 16 13 14 14 76 46 10
38 39 13 12 15 11 89 54 10
37 38 16 14 15 8 76 47 10
36 31 15 13 15 11 73 45 10
31 33 16 15 13 11 79 47 10
39 32 15 10 17 8 90 55 10
44 39 17 11 17 10 74 44 10
33 36 15 9 19 11 81 53 10
35 33 12 11 15 13 72 44 10
32 33 16 10 13 11 71 42 10
28 32 10 11 9 20 66 40 10
40 37 16 8 15 10 77 46 10
27 30 12 11 15 15 65 40 10
37 38 14 12 15 12 74 46 10
32 29 15 12 16 14 85 53 10
28 22 13 9 11 23 54 33 10
34 35 15 11 14 14 63 42 10
30 35 11 10 11 16 54 35 10
35 34 12 8 15 11 64 40 10
31 35 11 9 13 12 69 41 10
32 34 16 8 15 10 54 33 10
30 37 15 9 16 14 84 51 10
30 35 17 15 14 12 86 53 10
31 23 16 11 15 12 77 46 10
40 31 10 8 16 11 89 55 10
32 27 18 13 16 12 76 47 10
36 36 13 12 11 13 60 38 10
32 31 16 12 12 11 75 46 10
35 32 13 9 9 19 73 46 10
38 39 10 7 16 12 85 53 10
42 37 15 13 13 17 79 47 10
34 38 16 9 16 9 71 41 10
35 39 16 6 12 12 72 44 10
38 34 14 8 9 19 69 43 9
33 31 10 8 13 18 78 51 10
36 32 17 15 13 15 54 33 10
32 37 13 6 14 14 69 43 10
33 36 15 9 19 11 81 53 10
34 32 16 11 13 9 84 51 10
32 38 12 8 12 18 84 50 10
34 36 13 8 13 16 69 46 10
27 26 13 10 10 24 66 43 11
31 26 12 8 14 14 81 47 11
38 33 17 14 16 20 82 50 11
34 39 15 10 10 18 72 43 11
24 30 10 8 11 23 54 33 11
30 33 14 11 14 12 78 48 11
26 25 11 12 12 14 74 44 11
34 38 13 12 9 16 82 50 11
27 37 16 12 9 18 73 41 11
37 31 12 5 11 20 55 34 11
36 37 16 12 16 12 72 44 11
41 35 12 10 9 12 78 47 11
29 25 9 7 13 17 59 35 11
36 28 12 12 16 13 72 44 11
32 35 15 11 13 9 78 44 11
37 33 12 8 9 16 68 43 11
30 30 12 9 12 18 69 41 11
31 31 14 10 16 10 67 41 11
38 37 12 9 11 14 74 42 11
36 36 16 12 14 11 54 33 11
35 30 11 6 13 9 67 41 11
31 36 19 15 15 11 70 44 11
38 32 15 12 14 10 80 48 11
22 28 8 12 16 11 89 55 11
32 36 16 12 13 19 76 44 11
36 34 17 11 14 14 74 43 11
39 31 12 7 15 12 87 52 11
28 28 11 7 13 14 54 30 11
32 36 11 5 11 21 61 39 11
32 36 14 12 11 13 38 11 11
38 40 16 12 14 10 75 44 11
32 33 12 3 15 15 69 42 11
35 37 16 11 11 16 62 41 11
32 32 13 10 15 14 72 44 11
37 38 15 12 12 12 70 44 11
34 31 16 9 14 19 79 48 11
33 37 16 12 14 15 87 53 11
33 33 14 9 8 19 62 37 11
26 32 16 12 13 13 77 44 11
30 30 16 12 9 17 69 44 11
24 30 14 10 15 12 69 40 11
34 31 11 9 17 11 75 42 11
34 32 12 12 13 14 54 35 11
33 34 15 8 15 11 72 43 11
34 36 15 11 15 13 74 45 11
35 37 16 11 14 12 85 55 11
35 36 16 12 16 15 52 31 11
36 33 11 10 13 14 70 44 11
34 33 15 10 16 12 84 50 11
34 33 12 12 9 17 64 40 11
41 44 12 12 16 11 84 53 11
32 39 15 11 11 18 87 54 11
30 32 15 8 10 13 79 49 11
35 35 16 12 11 17 67 40 11
28 25 14 10 15 13 65 41 11
33 35 17 11 17 11 85 52 11
39 34 14 10 14 12 83 52 11
36 35 13 8 8 22 61 36 11
36 39 15 12 15 14 82 52 11
35 33 13 12 11 12 76 46 11
38 36 14 10 16 12 58 31 11
33 32 15 12 10 17 72 44 11
31 32 12 9 15 9 72 44 11
34 36 13 9 9 21 38 11 11
32 36 8 6 16 10 78 46 11
31 32 14 10 19 11 54 33 11
33 34 14 9 12 12 63 34 11
34 33 11 9 8 23 66 42 11
34 35 12 9 11 13 70 43 11
34 30 13 6 14 12 71 43 11
33 38 10 10 9 16 67 44 11
32 34 16 6 15 9 58 36 11
41 33 18 14 13 17 72 46 11
34 32 13 10 16 9 72 44 11
36 31 11 10 11 14 70 43 11
37 30 4 6 12 17 76 50 11
36 27 13 12 13 13 50 33 11
29 31 16 12 10 11 72 43 11
37 30 10 7 11 12 72 44 11
27 32 12 8 12 10 88 53 11
35 35 12 11 8 19 53 34 11
28 28 10 3 12 16 58 35 11
35 33 13 6 12 16 66 40 11
37 31 15 10 15 14 82 53 11
29 35 12 8 11 20 69 42 11
32 35 14 9 13 15 68 43 11
36 32 10 9 14 23 44 29 11
19 21 12 8 10 20 56 36 11
21 20 12 9 12 16 53 30 11
31 34 11 7 15 14 70 42 11
33 32 10 7 13 17 78 47 11
36 34 12 6 13 11 71 44 11
33 32 16 9 13 13 72 45 11
37 33 12 10 12 17 68 44 11
34 33 14 11 12 15 67 43 11
35 37 16 12 9 21 75 43 11
31 32 14 8 9 18 62 40 11
37 34 13 11 15 15 67 41 11
35 30 4 3 10 8 83 52 11
27 30 15 11 14 12 64 38 11
34 38 11 12 15 12 68 41 11
40 36 11 7 7 22 62 39 11
29 32 14 9 14 12 72 43 11

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time20 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 & 20 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226597&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]20 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=226597&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226597&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time20 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 18.9394 -0.0282513Connected[t] + 0.0029614Separate[t] -0.0675091Learning[t] -0.026789Software[t] -0.687128Happiness[t] -0.165979Sport1[t] + 0.168248Sport2[t] + 1.14577Month[t] -0.00820559t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Depression[t] =  +  18.9394 -0.0282513Connected[t] +  0.0029614Separate[t] -0.0675091Learning[t] -0.026789Software[t] -0.687128Happiness[t] -0.165979Sport1[t] +  0.168248Sport2[t] +  1.14577Month[t] -0.00820559t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226597&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Depression[t] =  +  18.9394 -0.0282513Connected[t] +  0.0029614Separate[t] -0.0675091Learning[t] -0.026789Software[t] -0.687128Happiness[t] -0.165979Sport1[t] +  0.168248Sport2[t] +  1.14577Month[t] -0.00820559t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226597&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226597&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 18.9394 -0.0282513Connected[t] + 0.0029614Separate[t] -0.0675091Learning[t] -0.026789Software[t] -0.687128Happiness[t] -0.165979Sport1[t] + 0.168248Sport2[t] + 1.14577Month[t] -0.00820559t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.93945.636633.360.0008991080.000449554
Connected-0.02825130.0512583-0.55120.5820110.291005
Separate0.00296140.05211170.056830.9547270.477363
Learning-0.06750910.0925384-0.72950.4663530.233176
Software-0.0267890.095616-0.28020.7795730.389787
Happiness-0.6871280.0744356-9.2311.09082e-175.45411e-18
Sport1-0.1659790.0551293-3.0110.002868990.0014345
Sport20.1682480.08264832.0360.04281740.0214087
Month1.145770.5993361.9120.05703480.0285174
t-0.008205590.00640395-1.2810.2012460.100623

\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) & 18.9394 & 5.63663 & 3.36 & 0.000899108 & 0.000449554 \tabularnewline
Connected & -0.0282513 & 0.0512583 & -0.5512 & 0.582011 & 0.291005 \tabularnewline
Separate & 0.0029614 & 0.0521117 & 0.05683 & 0.954727 & 0.477363 \tabularnewline
Learning & -0.0675091 & 0.0925384 & -0.7295 & 0.466353 & 0.233176 \tabularnewline
Software & -0.026789 & 0.095616 & -0.2802 & 0.779573 & 0.389787 \tabularnewline
Happiness & -0.687128 & 0.0744356 & -9.231 & 1.09082e-17 & 5.45411e-18 \tabularnewline
Sport1 & -0.165979 & 0.0551293 & -3.011 & 0.00286899 & 0.0014345 \tabularnewline
Sport2 & 0.168248 & 0.0826483 & 2.036 & 0.0428174 & 0.0214087 \tabularnewline
Month & 1.14577 & 0.599336 & 1.912 & 0.0570348 & 0.0285174 \tabularnewline
t & -0.00820559 & 0.00640395 & -1.281 & 0.201246 & 0.100623 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226597&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]18.9394[/C][C]5.63663[/C][C]3.36[/C][C]0.000899108[/C][C]0.000449554[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0282513[/C][C]0.0512583[/C][C]-0.5512[/C][C]0.582011[/C][C]0.291005[/C][/ROW]
[ROW][C]Separate[/C][C]0.0029614[/C][C]0.0521117[/C][C]0.05683[/C][C]0.954727[/C][C]0.477363[/C][/ROW]
[ROW][C]Learning[/C][C]-0.0675091[/C][C]0.0925384[/C][C]-0.7295[/C][C]0.466353[/C][C]0.233176[/C][/ROW]
[ROW][C]Software[/C][C]-0.026789[/C][C]0.095616[/C][C]-0.2802[/C][C]0.779573[/C][C]0.389787[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.687128[/C][C]0.0744356[/C][C]-9.231[/C][C]1.09082e-17[/C][C]5.45411e-18[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.165979[/C][C]0.0551293[/C][C]-3.011[/C][C]0.00286899[/C][C]0.0014345[/C][/ROW]
[ROW][C]Sport2[/C][C]0.168248[/C][C]0.0826483[/C][C]2.036[/C][C]0.0428174[/C][C]0.0214087[/C][/ROW]
[ROW][C]Month[/C][C]1.14577[/C][C]0.599336[/C][C]1.912[/C][C]0.0570348[/C][C]0.0285174[/C][/ROW]
[ROW][C]t[/C][C]-0.00820559[/C][C]0.00640395[/C][C]-1.281[/C][C]0.201246[/C][C]0.100623[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226597&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226597&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.93945.636633.360.0008991080.000449554
Connected-0.02825130.0512583-0.55120.5820110.291005
Separate0.00296140.05211170.056830.9547270.477363
Learning-0.06750910.0925384-0.72950.4663530.233176
Software-0.0267890.095616-0.28020.7795730.389787
Happiness-0.6871280.0744356-9.2311.09082e-175.45411e-18
Sport1-0.1659790.0551293-3.0110.002868990.0014345
Sport20.1682480.08264832.0360.04281740.0214087
Month1.145770.5993361.9120.05703480.0285174
t-0.008205590.00640395-1.2810.2012460.100623






Multiple Linear Regression - Regression Statistics
Multiple R0.628414
R-squared0.394905
Adjusted R-squared0.373464
F-TEST (value)18.4187
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.7463
Sum Squared Residuals1915.7

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.628414 \tabularnewline
R-squared & 0.394905 \tabularnewline
Adjusted R-squared & 0.373464 \tabularnewline
F-TEST (value) & 18.4187 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 254 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.7463 \tabularnewline
Sum Squared Residuals & 1915.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226597&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.628414[/C][/ROW]
[ROW][C]R-squared[/C][C]0.394905[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.373464[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]18.4187[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]254[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.7463[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1915.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226597&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226597&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.628414
R-squared0.394905
Adjusted R-squared0.373464
F-TEST (value)18.4187
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.7463
Sum Squared Residuals1915.7






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.9655-1.96554
2119.289171.71083
31415.3517-1.35173
41214.7991-2.79913
52111.19699.80308
6129.746682.25332
72214.38837.61174
81112.2901-1.29013
91011.9793-1.9793
101311.96911.03088
111010.2819-0.281943
12810.3688-2.36879
131515.8477-0.847707
141412.36761.63236
15108.864731.13527
161413.790.210009
171412.4121.58801
18119.269051.73095
191013.2521-3.25205
201312.47840.52158
219.510.4731-0.973139
221415.4432-1.44316
231213.4119-1.41194
241415.4346-1.4346
25119.363581.63642
26914.9237-5.92374
271110.39460.605422
281513.14181.85824
291411.09512.90491
301315.6533-2.65326
31910.8507-1.85067
321514.9530.0470209
331010.583-0.583031
341111.556-0.556013
351311.991.00996
36811.9114-3.91137
372016.88843.11159
381211.89690.103144
391010.2996-0.29964
401013.3652-3.36522
41911.5981-2.59815
421410.73773.26226
43811.763-3.76297
441415.1255-1.12546
451111.9854-0.985395
461314.7531-1.75312
47912.7534-3.75335
481111.7026-0.702625
49159.672735.32727
501112.7858-1.78576
511011.0445-1.04454
521412.7861.21402
531815.08872.91135
541415.735-1.73501
551114.604-3.60395
5614.511.73072.76934
571310.67562.32443
58912.2941-3.29411
591013.3939-3.39388
601513.89351.10653
612018.07861.92142
621212.2262-0.226243
631213.6615-1.66149
641413.67920.320773
651312.730.269975
661115.575-4.57498
671715.89711.10286
681214.0979-2.09789
691313.3458-0.34584
701412.84881.15116
711314.6207-1.62071
721513.39851.60148
731311.68751.31246
741012.218-2.21802
751113.037-2.03701
761914.09214.90792
771311.33611.66388
781714.53122.46878
791312.67090.329082
80915.0304-6.03037
811111.8253-0.825324
82912.9232-3.92316
831211.55850.441468
841212.7427-0.742689
851313.0186-0.0186067
861312.3630.637024
871213.4441-1.44409
881515.2055-0.205545
892218.30443.6956
901311.781.22
911514.83530.164707
921312.02530.974675
931512.32462.67539
9412.513.3929-0.892942
951110.90970.0903431
961614.77591.22409
971112.5562-1.5562
981110.19720.802817
991012.3924-2.39241
1001010.43-0.430015
1011614.4611.53896
1021210.54731.4527
1031115.9769-4.9769
1041611.84054.15948
1051916.72862.27139
1061111.3875-0.387513
1071612.21793.78206
1081516.9407-1.94073
1092417.95586.04422
1101411.67982.32019
1111514.81510.184892
1121112.968-1.96797
1131513.4151.585
1141210.3641.63598
1151010.5884-0.588433
1161414.3076-0.307576
1171314.0981-1.09807
118913.422-4.422
1191511.74783.25215
1201515.7612-0.761213
1211412.68521.31477
1221111.2452-0.245247
123811.9862-3.98621
1241112.2413-1.24127
1251112.974-1.97403
12689.71002-1.71002
1271010.2244-0.224408
128119.68481.3152
1291312.48820.51175
1301113.5253-2.52529
1312017.24732.75269
1321011.6512-1.65115
1331513.16141.83859
1341212.2483-0.248257
1351410.9523.04801
1362316.46756.53253
1371414.0987-0.0986926
1381616.8778-0.877775
1391113.1444-2.14436
1401214.0055-2.00545
1411013.4247-3.42472
1421410.88463.11541
1431211.95350.0464921
1441211.68510.314877
1451110.76710.232873
1461211.11080.889191
1471315.9577-2.95765
1481114.0143-3.01429
1491916.60052.39947
1501211.16050.839499
1511712.58294.41714
152911.1002-2.10023
1531214.2344-2.23438
1541915.45343.54665
1551814.0973.90301
1561514.30190.69807
1571413.43830.561655
158119.438641.56136
159912.5576-3.55758
1601813.49294.50707
1611614.48441.51565
1622417.79116.20893
1631413.22570.77426
1642011.50678.49327
1651816.47631.5237
1662317.73315.26692
1671213.6927-1.6927
1681415.3147-1.31472
1691616.727-0.727032
1701816.69071.30933
1712017.27542.72463
1721212.2808-0.280824
1731216.7678-4.76782
1741715.7381.26198
1751312.49960.500409
176913.5149-4.5149
1771617.8825-1.88246
1781815.47252.52752
1791012.8606-2.86062
1801415.2763-1.27627
1811114.7152-3.71516
182915.0911-6.0911
1831113.065-2.06505
1841012.898-2.89798
1851112.1122-1.11218
1861913.67355.32654
1871412.98221.01781
1881211.99440.00557473
1891415.5057-1.50571
1902117.18843.8116
1911315.8967-2.89671
1921012.9454-2.94541
1931513.56941.43063
1941616.746-0.746027
1951413.13350.866473
1961215.2066-3.20658
1971913.08025.91982
1981512.5512.44896
1991918.32660.673355
2001313.5503-0.550266
2011717.4995-0.499475
2021213.0536-1.05361
2031110.96150.0384632
2041415.8647-1.86475
2051112.7795-1.77945
2061312.67310.326908
2071213.1159-1.11593
2081513.14311.85694
2091414.7498-0.749838
2101211.15250.847501
2111717.7402-0.740236
2121111.6246-0.624597
2131814.78613.21394
2141316.0677-3.06772
2151715.54291.45714
2161313.6431-0.643084
2171110.45080.549184
2181212.8928-0.8928
2192218.17573.82427
2201412.33371.66629
2211215.2059-3.20591
2221212.1362-0.136155
2231716.12260.877434
224913.0181-4.01811
2252117.08343.91665
2261011.9892-1.9892
2271111.2201-0.220066
2281214.6724-2.67241
2292318.43214.56792
2301315.8052-2.80523
2311213.5677-1.56772
2321617.9746-1.97463
233913.71-4.70998
2341713.82833.17174
235912.0617-3.06167
2361415.7284-1.72837
2371715.76341.23659
2381315.7744-2.77436
2391115.8656-4.86556
2401215.6485-3.6485
2411013.9384-3.93837
2421918.99370.00627027
2431616.1017-0.101725
2441615.14110.858917
2451412.29851.70154
2462015.83974.16028
2471514.54490.455075
2482315.62587.37425
2492017.89152.10848
2501615.91130.0887451
2511412.9191.08096
2521713.80363.19642
2531114.2654-3.26542
2541313.9879-0.987913
2551715.29571.70429
2561515.2082-0.208178
2572115.75535.24468
2581817.74050.259538
2591512.77142.2286
260816.2605-8.26045
2611213.571-1.57096
2621212.7856-0.78563
2632218.89233.10766
2641213.1303-1.13026

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 13.9655 & -1.96554 \tabularnewline
2 & 11 & 9.28917 & 1.71083 \tabularnewline
3 & 14 & 15.3517 & -1.35173 \tabularnewline
4 & 12 & 14.7991 & -2.79913 \tabularnewline
5 & 21 & 11.1969 & 9.80308 \tabularnewline
6 & 12 & 9.74668 & 2.25332 \tabularnewline
7 & 22 & 14.3883 & 7.61174 \tabularnewline
8 & 11 & 12.2901 & -1.29013 \tabularnewline
9 & 10 & 11.9793 & -1.9793 \tabularnewline
10 & 13 & 11.9691 & 1.03088 \tabularnewline
11 & 10 & 10.2819 & -0.281943 \tabularnewline
12 & 8 & 10.3688 & -2.36879 \tabularnewline
13 & 15 & 15.8477 & -0.847707 \tabularnewline
14 & 14 & 12.3676 & 1.63236 \tabularnewline
15 & 10 & 8.86473 & 1.13527 \tabularnewline
16 & 14 & 13.79 & 0.210009 \tabularnewline
17 & 14 & 12.412 & 1.58801 \tabularnewline
18 & 11 & 9.26905 & 1.73095 \tabularnewline
19 & 10 & 13.2521 & -3.25205 \tabularnewline
20 & 13 & 12.4784 & 0.52158 \tabularnewline
21 & 9.5 & 10.4731 & -0.973139 \tabularnewline
22 & 14 & 15.4432 & -1.44316 \tabularnewline
23 & 12 & 13.4119 & -1.41194 \tabularnewline
24 & 14 & 15.4346 & -1.4346 \tabularnewline
25 & 11 & 9.36358 & 1.63642 \tabularnewline
26 & 9 & 14.9237 & -5.92374 \tabularnewline
27 & 11 & 10.3946 & 0.605422 \tabularnewline
28 & 15 & 13.1418 & 1.85824 \tabularnewline
29 & 14 & 11.0951 & 2.90491 \tabularnewline
30 & 13 & 15.6533 & -2.65326 \tabularnewline
31 & 9 & 10.8507 & -1.85067 \tabularnewline
32 & 15 & 14.953 & 0.0470209 \tabularnewline
33 & 10 & 10.583 & -0.583031 \tabularnewline
34 & 11 & 11.556 & -0.556013 \tabularnewline
35 & 13 & 11.99 & 1.00996 \tabularnewline
36 & 8 & 11.9114 & -3.91137 \tabularnewline
37 & 20 & 16.8884 & 3.11159 \tabularnewline
38 & 12 & 11.8969 & 0.103144 \tabularnewline
39 & 10 & 10.2996 & -0.29964 \tabularnewline
40 & 10 & 13.3652 & -3.36522 \tabularnewline
41 & 9 & 11.5981 & -2.59815 \tabularnewline
42 & 14 & 10.7377 & 3.26226 \tabularnewline
43 & 8 & 11.763 & -3.76297 \tabularnewline
44 & 14 & 15.1255 & -1.12546 \tabularnewline
45 & 11 & 11.9854 & -0.985395 \tabularnewline
46 & 13 & 14.7531 & -1.75312 \tabularnewline
47 & 9 & 12.7534 & -3.75335 \tabularnewline
48 & 11 & 11.7026 & -0.702625 \tabularnewline
49 & 15 & 9.67273 & 5.32727 \tabularnewline
50 & 11 & 12.7858 & -1.78576 \tabularnewline
51 & 10 & 11.0445 & -1.04454 \tabularnewline
52 & 14 & 12.786 & 1.21402 \tabularnewline
53 & 18 & 15.0887 & 2.91135 \tabularnewline
54 & 14 & 15.735 & -1.73501 \tabularnewline
55 & 11 & 14.604 & -3.60395 \tabularnewline
56 & 14.5 & 11.7307 & 2.76934 \tabularnewline
57 & 13 & 10.6756 & 2.32443 \tabularnewline
58 & 9 & 12.2941 & -3.29411 \tabularnewline
59 & 10 & 13.3939 & -3.39388 \tabularnewline
60 & 15 & 13.8935 & 1.10653 \tabularnewline
61 & 20 & 18.0786 & 1.92142 \tabularnewline
62 & 12 & 12.2262 & -0.226243 \tabularnewline
63 & 12 & 13.6615 & -1.66149 \tabularnewline
64 & 14 & 13.6792 & 0.320773 \tabularnewline
65 & 13 & 12.73 & 0.269975 \tabularnewline
66 & 11 & 15.575 & -4.57498 \tabularnewline
67 & 17 & 15.8971 & 1.10286 \tabularnewline
68 & 12 & 14.0979 & -2.09789 \tabularnewline
69 & 13 & 13.3458 & -0.34584 \tabularnewline
70 & 14 & 12.8488 & 1.15116 \tabularnewline
71 & 13 & 14.6207 & -1.62071 \tabularnewline
72 & 15 & 13.3985 & 1.60148 \tabularnewline
73 & 13 & 11.6875 & 1.31246 \tabularnewline
74 & 10 & 12.218 & -2.21802 \tabularnewline
75 & 11 & 13.037 & -2.03701 \tabularnewline
76 & 19 & 14.0921 & 4.90792 \tabularnewline
77 & 13 & 11.3361 & 1.66388 \tabularnewline
78 & 17 & 14.5312 & 2.46878 \tabularnewline
79 & 13 & 12.6709 & 0.329082 \tabularnewline
80 & 9 & 15.0304 & -6.03037 \tabularnewline
81 & 11 & 11.8253 & -0.825324 \tabularnewline
82 & 9 & 12.9232 & -3.92316 \tabularnewline
83 & 12 & 11.5585 & 0.441468 \tabularnewline
84 & 12 & 12.7427 & -0.742689 \tabularnewline
85 & 13 & 13.0186 & -0.0186067 \tabularnewline
86 & 13 & 12.363 & 0.637024 \tabularnewline
87 & 12 & 13.4441 & -1.44409 \tabularnewline
88 & 15 & 15.2055 & -0.205545 \tabularnewline
89 & 22 & 18.3044 & 3.6956 \tabularnewline
90 & 13 & 11.78 & 1.22 \tabularnewline
91 & 15 & 14.8353 & 0.164707 \tabularnewline
92 & 13 & 12.0253 & 0.974675 \tabularnewline
93 & 15 & 12.3246 & 2.67539 \tabularnewline
94 & 12.5 & 13.3929 & -0.892942 \tabularnewline
95 & 11 & 10.9097 & 0.0903431 \tabularnewline
96 & 16 & 14.7759 & 1.22409 \tabularnewline
97 & 11 & 12.5562 & -1.5562 \tabularnewline
98 & 11 & 10.1972 & 0.802817 \tabularnewline
99 & 10 & 12.3924 & -2.39241 \tabularnewline
100 & 10 & 10.43 & -0.430015 \tabularnewline
101 & 16 & 14.461 & 1.53896 \tabularnewline
102 & 12 & 10.5473 & 1.4527 \tabularnewline
103 & 11 & 15.9769 & -4.9769 \tabularnewline
104 & 16 & 11.8405 & 4.15948 \tabularnewline
105 & 19 & 16.7286 & 2.27139 \tabularnewline
106 & 11 & 11.3875 & -0.387513 \tabularnewline
107 & 16 & 12.2179 & 3.78206 \tabularnewline
108 & 15 & 16.9407 & -1.94073 \tabularnewline
109 & 24 & 17.9558 & 6.04422 \tabularnewline
110 & 14 & 11.6798 & 2.32019 \tabularnewline
111 & 15 & 14.8151 & 0.184892 \tabularnewline
112 & 11 & 12.968 & -1.96797 \tabularnewline
113 & 15 & 13.415 & 1.585 \tabularnewline
114 & 12 & 10.364 & 1.63598 \tabularnewline
115 & 10 & 10.5884 & -0.588433 \tabularnewline
116 & 14 & 14.3076 & -0.307576 \tabularnewline
117 & 13 & 14.0981 & -1.09807 \tabularnewline
118 & 9 & 13.422 & -4.422 \tabularnewline
119 & 15 & 11.7478 & 3.25215 \tabularnewline
120 & 15 & 15.7612 & -0.761213 \tabularnewline
121 & 14 & 12.6852 & 1.31477 \tabularnewline
122 & 11 & 11.2452 & -0.245247 \tabularnewline
123 & 8 & 11.9862 & -3.98621 \tabularnewline
124 & 11 & 12.2413 & -1.24127 \tabularnewline
125 & 11 & 12.974 & -1.97403 \tabularnewline
126 & 8 & 9.71002 & -1.71002 \tabularnewline
127 & 10 & 10.2244 & -0.224408 \tabularnewline
128 & 11 & 9.6848 & 1.3152 \tabularnewline
129 & 13 & 12.4882 & 0.51175 \tabularnewline
130 & 11 & 13.5253 & -2.52529 \tabularnewline
131 & 20 & 17.2473 & 2.75269 \tabularnewline
132 & 10 & 11.6512 & -1.65115 \tabularnewline
133 & 15 & 13.1614 & 1.83859 \tabularnewline
134 & 12 & 12.2483 & -0.248257 \tabularnewline
135 & 14 & 10.952 & 3.04801 \tabularnewline
136 & 23 & 16.4675 & 6.53253 \tabularnewline
137 & 14 & 14.0987 & -0.0986926 \tabularnewline
138 & 16 & 16.8778 & -0.877775 \tabularnewline
139 & 11 & 13.1444 & -2.14436 \tabularnewline
140 & 12 & 14.0055 & -2.00545 \tabularnewline
141 & 10 & 13.4247 & -3.42472 \tabularnewline
142 & 14 & 10.8846 & 3.11541 \tabularnewline
143 & 12 & 11.9535 & 0.0464921 \tabularnewline
144 & 12 & 11.6851 & 0.314877 \tabularnewline
145 & 11 & 10.7671 & 0.232873 \tabularnewline
146 & 12 & 11.1108 & 0.889191 \tabularnewline
147 & 13 & 15.9577 & -2.95765 \tabularnewline
148 & 11 & 14.0143 & -3.01429 \tabularnewline
149 & 19 & 16.6005 & 2.39947 \tabularnewline
150 & 12 & 11.1605 & 0.839499 \tabularnewline
151 & 17 & 12.5829 & 4.41714 \tabularnewline
152 & 9 & 11.1002 & -2.10023 \tabularnewline
153 & 12 & 14.2344 & -2.23438 \tabularnewline
154 & 19 & 15.4534 & 3.54665 \tabularnewline
155 & 18 & 14.097 & 3.90301 \tabularnewline
156 & 15 & 14.3019 & 0.69807 \tabularnewline
157 & 14 & 13.4383 & 0.561655 \tabularnewline
158 & 11 & 9.43864 & 1.56136 \tabularnewline
159 & 9 & 12.5576 & -3.55758 \tabularnewline
160 & 18 & 13.4929 & 4.50707 \tabularnewline
161 & 16 & 14.4844 & 1.51565 \tabularnewline
162 & 24 & 17.7911 & 6.20893 \tabularnewline
163 & 14 & 13.2257 & 0.77426 \tabularnewline
164 & 20 & 11.5067 & 8.49327 \tabularnewline
165 & 18 & 16.4763 & 1.5237 \tabularnewline
166 & 23 & 17.7331 & 5.26692 \tabularnewline
167 & 12 & 13.6927 & -1.6927 \tabularnewline
168 & 14 & 15.3147 & -1.31472 \tabularnewline
169 & 16 & 16.727 & -0.727032 \tabularnewline
170 & 18 & 16.6907 & 1.30933 \tabularnewline
171 & 20 & 17.2754 & 2.72463 \tabularnewline
172 & 12 & 12.2808 & -0.280824 \tabularnewline
173 & 12 & 16.7678 & -4.76782 \tabularnewline
174 & 17 & 15.738 & 1.26198 \tabularnewline
175 & 13 & 12.4996 & 0.500409 \tabularnewline
176 & 9 & 13.5149 & -4.5149 \tabularnewline
177 & 16 & 17.8825 & -1.88246 \tabularnewline
178 & 18 & 15.4725 & 2.52752 \tabularnewline
179 & 10 & 12.8606 & -2.86062 \tabularnewline
180 & 14 & 15.2763 & -1.27627 \tabularnewline
181 & 11 & 14.7152 & -3.71516 \tabularnewline
182 & 9 & 15.0911 & -6.0911 \tabularnewline
183 & 11 & 13.065 & -2.06505 \tabularnewline
184 & 10 & 12.898 & -2.89798 \tabularnewline
185 & 11 & 12.1122 & -1.11218 \tabularnewline
186 & 19 & 13.6735 & 5.32654 \tabularnewline
187 & 14 & 12.9822 & 1.01781 \tabularnewline
188 & 12 & 11.9944 & 0.00557473 \tabularnewline
189 & 14 & 15.5057 & -1.50571 \tabularnewline
190 & 21 & 17.1884 & 3.8116 \tabularnewline
191 & 13 & 15.8967 & -2.89671 \tabularnewline
192 & 10 & 12.9454 & -2.94541 \tabularnewline
193 & 15 & 13.5694 & 1.43063 \tabularnewline
194 & 16 & 16.746 & -0.746027 \tabularnewline
195 & 14 & 13.1335 & 0.866473 \tabularnewline
196 & 12 & 15.2066 & -3.20658 \tabularnewline
197 & 19 & 13.0802 & 5.91982 \tabularnewline
198 & 15 & 12.551 & 2.44896 \tabularnewline
199 & 19 & 18.3266 & 0.673355 \tabularnewline
200 & 13 & 13.5503 & -0.550266 \tabularnewline
201 & 17 & 17.4995 & -0.499475 \tabularnewline
202 & 12 & 13.0536 & -1.05361 \tabularnewline
203 & 11 & 10.9615 & 0.0384632 \tabularnewline
204 & 14 & 15.8647 & -1.86475 \tabularnewline
205 & 11 & 12.7795 & -1.77945 \tabularnewline
206 & 13 & 12.6731 & 0.326908 \tabularnewline
207 & 12 & 13.1159 & -1.11593 \tabularnewline
208 & 15 & 13.1431 & 1.85694 \tabularnewline
209 & 14 & 14.7498 & -0.749838 \tabularnewline
210 & 12 & 11.1525 & 0.847501 \tabularnewline
211 & 17 & 17.7402 & -0.740236 \tabularnewline
212 & 11 & 11.6246 & -0.624597 \tabularnewline
213 & 18 & 14.7861 & 3.21394 \tabularnewline
214 & 13 & 16.0677 & -3.06772 \tabularnewline
215 & 17 & 15.5429 & 1.45714 \tabularnewline
216 & 13 & 13.6431 & -0.643084 \tabularnewline
217 & 11 & 10.4508 & 0.549184 \tabularnewline
218 & 12 & 12.8928 & -0.8928 \tabularnewline
219 & 22 & 18.1757 & 3.82427 \tabularnewline
220 & 14 & 12.3337 & 1.66629 \tabularnewline
221 & 12 & 15.2059 & -3.20591 \tabularnewline
222 & 12 & 12.1362 & -0.136155 \tabularnewline
223 & 17 & 16.1226 & 0.877434 \tabularnewline
224 & 9 & 13.0181 & -4.01811 \tabularnewline
225 & 21 & 17.0834 & 3.91665 \tabularnewline
226 & 10 & 11.9892 & -1.9892 \tabularnewline
227 & 11 & 11.2201 & -0.220066 \tabularnewline
228 & 12 & 14.6724 & -2.67241 \tabularnewline
229 & 23 & 18.4321 & 4.56792 \tabularnewline
230 & 13 & 15.8052 & -2.80523 \tabularnewline
231 & 12 & 13.5677 & -1.56772 \tabularnewline
232 & 16 & 17.9746 & -1.97463 \tabularnewline
233 & 9 & 13.71 & -4.70998 \tabularnewline
234 & 17 & 13.8283 & 3.17174 \tabularnewline
235 & 9 & 12.0617 & -3.06167 \tabularnewline
236 & 14 & 15.7284 & -1.72837 \tabularnewline
237 & 17 & 15.7634 & 1.23659 \tabularnewline
238 & 13 & 15.7744 & -2.77436 \tabularnewline
239 & 11 & 15.8656 & -4.86556 \tabularnewline
240 & 12 & 15.6485 & -3.6485 \tabularnewline
241 & 10 & 13.9384 & -3.93837 \tabularnewline
242 & 19 & 18.9937 & 0.00627027 \tabularnewline
243 & 16 & 16.1017 & -0.101725 \tabularnewline
244 & 16 & 15.1411 & 0.858917 \tabularnewline
245 & 14 & 12.2985 & 1.70154 \tabularnewline
246 & 20 & 15.8397 & 4.16028 \tabularnewline
247 & 15 & 14.5449 & 0.455075 \tabularnewline
248 & 23 & 15.6258 & 7.37425 \tabularnewline
249 & 20 & 17.8915 & 2.10848 \tabularnewline
250 & 16 & 15.9113 & 0.0887451 \tabularnewline
251 & 14 & 12.919 & 1.08096 \tabularnewline
252 & 17 & 13.8036 & 3.19642 \tabularnewline
253 & 11 & 14.2654 & -3.26542 \tabularnewline
254 & 13 & 13.9879 & -0.987913 \tabularnewline
255 & 17 & 15.2957 & 1.70429 \tabularnewline
256 & 15 & 15.2082 & -0.208178 \tabularnewline
257 & 21 & 15.7553 & 5.24468 \tabularnewline
258 & 18 & 17.7405 & 0.259538 \tabularnewline
259 & 15 & 12.7714 & 2.2286 \tabularnewline
260 & 8 & 16.2605 & -8.26045 \tabularnewline
261 & 12 & 13.571 & -1.57096 \tabularnewline
262 & 12 & 12.7856 & -0.78563 \tabularnewline
263 & 22 & 18.8923 & 3.10766 \tabularnewline
264 & 12 & 13.1303 & -1.13026 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226597&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[/C][C]13.9655[/C][C]-1.96554[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]9.28917[/C][C]1.71083[/C][/ROW]
[ROW][C]3[/C][C]14[/C][C]15.3517[/C][C]-1.35173[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.7991[/C][C]-2.79913[/C][/ROW]
[ROW][C]5[/C][C]21[/C][C]11.1969[/C][C]9.80308[/C][/ROW]
[ROW][C]6[/C][C]12[/C][C]9.74668[/C][C]2.25332[/C][/ROW]
[ROW][C]7[/C][C]22[/C][C]14.3883[/C][C]7.61174[/C][/ROW]
[ROW][C]8[/C][C]11[/C][C]12.2901[/C][C]-1.29013[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]11.9793[/C][C]-1.9793[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]11.9691[/C][C]1.03088[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.2819[/C][C]-0.281943[/C][/ROW]
[ROW][C]12[/C][C]8[/C][C]10.3688[/C][C]-2.36879[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]15.8477[/C][C]-0.847707[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]12.3676[/C][C]1.63236[/C][/ROW]
[ROW][C]15[/C][C]10[/C][C]8.86473[/C][C]1.13527[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.79[/C][C]0.210009[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]12.412[/C][C]1.58801[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]9.26905[/C][C]1.73095[/C][/ROW]
[ROW][C]19[/C][C]10[/C][C]13.2521[/C][C]-3.25205[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]12.4784[/C][C]0.52158[/C][/ROW]
[ROW][C]21[/C][C]9.5[/C][C]10.4731[/C][C]-0.973139[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]15.4432[/C][C]-1.44316[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]13.4119[/C][C]-1.41194[/C][/ROW]
[ROW][C]24[/C][C]14[/C][C]15.4346[/C][C]-1.4346[/C][/ROW]
[ROW][C]25[/C][C]11[/C][C]9.36358[/C][C]1.63642[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]14.9237[/C][C]-5.92374[/C][/ROW]
[ROW][C]27[/C][C]11[/C][C]10.3946[/C][C]0.605422[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]13.1418[/C][C]1.85824[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]11.0951[/C][C]2.90491[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]15.6533[/C][C]-2.65326[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]10.8507[/C][C]-1.85067[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]14.953[/C][C]0.0470209[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.583[/C][C]-0.583031[/C][/ROW]
[ROW][C]34[/C][C]11[/C][C]11.556[/C][C]-0.556013[/C][/ROW]
[ROW][C]35[/C][C]13[/C][C]11.99[/C][C]1.00996[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]11.9114[/C][C]-3.91137[/C][/ROW]
[ROW][C]37[/C][C]20[/C][C]16.8884[/C][C]3.11159[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]11.8969[/C][C]0.103144[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.2996[/C][C]-0.29964[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]13.3652[/C][C]-3.36522[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]11.5981[/C][C]-2.59815[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]10.7377[/C][C]3.26226[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]11.763[/C][C]-3.76297[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]15.1255[/C][C]-1.12546[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]11.9854[/C][C]-0.985395[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]14.7531[/C][C]-1.75312[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]12.7534[/C][C]-3.75335[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.7026[/C][C]-0.702625[/C][/ROW]
[ROW][C]49[/C][C]15[/C][C]9.67273[/C][C]5.32727[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]12.7858[/C][C]-1.78576[/C][/ROW]
[ROW][C]51[/C][C]10[/C][C]11.0445[/C][C]-1.04454[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]12.786[/C][C]1.21402[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]15.0887[/C][C]2.91135[/C][/ROW]
[ROW][C]54[/C][C]14[/C][C]15.735[/C][C]-1.73501[/C][/ROW]
[ROW][C]55[/C][C]11[/C][C]14.604[/C][C]-3.60395[/C][/ROW]
[ROW][C]56[/C][C]14.5[/C][C]11.7307[/C][C]2.76934[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]10.6756[/C][C]2.32443[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]12.2941[/C][C]-3.29411[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]13.3939[/C][C]-3.39388[/C][/ROW]
[ROW][C]60[/C][C]15[/C][C]13.8935[/C][C]1.10653[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]18.0786[/C][C]1.92142[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]12.2262[/C][C]-0.226243[/C][/ROW]
[ROW][C]63[/C][C]12[/C][C]13.6615[/C][C]-1.66149[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.6792[/C][C]0.320773[/C][/ROW]
[ROW][C]65[/C][C]13[/C][C]12.73[/C][C]0.269975[/C][/ROW]
[ROW][C]66[/C][C]11[/C][C]15.575[/C][C]-4.57498[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]15.8971[/C][C]1.10286[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.0979[/C][C]-2.09789[/C][/ROW]
[ROW][C]69[/C][C]13[/C][C]13.3458[/C][C]-0.34584[/C][/ROW]
[ROW][C]70[/C][C]14[/C][C]12.8488[/C][C]1.15116[/C][/ROW]
[ROW][C]71[/C][C]13[/C][C]14.6207[/C][C]-1.62071[/C][/ROW]
[ROW][C]72[/C][C]15[/C][C]13.3985[/C][C]1.60148[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]11.6875[/C][C]1.31246[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]12.218[/C][C]-2.21802[/C][/ROW]
[ROW][C]75[/C][C]11[/C][C]13.037[/C][C]-2.03701[/C][/ROW]
[ROW][C]76[/C][C]19[/C][C]14.0921[/C][C]4.90792[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.3361[/C][C]1.66388[/C][/ROW]
[ROW][C]78[/C][C]17[/C][C]14.5312[/C][C]2.46878[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.6709[/C][C]0.329082[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]15.0304[/C][C]-6.03037[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]11.8253[/C][C]-0.825324[/C][/ROW]
[ROW][C]82[/C][C]9[/C][C]12.9232[/C][C]-3.92316[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.5585[/C][C]0.441468[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.7427[/C][C]-0.742689[/C][/ROW]
[ROW][C]85[/C][C]13[/C][C]13.0186[/C][C]-0.0186067[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]12.363[/C][C]0.637024[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]13.4441[/C][C]-1.44409[/C][/ROW]
[ROW][C]88[/C][C]15[/C][C]15.2055[/C][C]-0.205545[/C][/ROW]
[ROW][C]89[/C][C]22[/C][C]18.3044[/C][C]3.6956[/C][/ROW]
[ROW][C]90[/C][C]13[/C][C]11.78[/C][C]1.22[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]14.8353[/C][C]0.164707[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]12.0253[/C][C]0.974675[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]12.3246[/C][C]2.67539[/C][/ROW]
[ROW][C]94[/C][C]12.5[/C][C]13.3929[/C][C]-0.892942[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]10.9097[/C][C]0.0903431[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.7759[/C][C]1.22409[/C][/ROW]
[ROW][C]97[/C][C]11[/C][C]12.5562[/C][C]-1.5562[/C][/ROW]
[ROW][C]98[/C][C]11[/C][C]10.1972[/C][C]0.802817[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]12.3924[/C][C]-2.39241[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]10.43[/C][C]-0.430015[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.461[/C][C]1.53896[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]10.5473[/C][C]1.4527[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]15.9769[/C][C]-4.9769[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]11.8405[/C][C]4.15948[/C][/ROW]
[ROW][C]105[/C][C]19[/C][C]16.7286[/C][C]2.27139[/C][/ROW]
[ROW][C]106[/C][C]11[/C][C]11.3875[/C][C]-0.387513[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]12.2179[/C][C]3.78206[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]16.9407[/C][C]-1.94073[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]17.9558[/C][C]6.04422[/C][/ROW]
[ROW][C]110[/C][C]14[/C][C]11.6798[/C][C]2.32019[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]14.8151[/C][C]0.184892[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.968[/C][C]-1.96797[/C][/ROW]
[ROW][C]113[/C][C]15[/C][C]13.415[/C][C]1.585[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]10.364[/C][C]1.63598[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]10.5884[/C][C]-0.588433[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.3076[/C][C]-0.307576[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]14.0981[/C][C]-1.09807[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]13.422[/C][C]-4.422[/C][/ROW]
[ROW][C]119[/C][C]15[/C][C]11.7478[/C][C]3.25215[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]15.7612[/C][C]-0.761213[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]12.6852[/C][C]1.31477[/C][/ROW]
[ROW][C]122[/C][C]11[/C][C]11.2452[/C][C]-0.245247[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]11.9862[/C][C]-3.98621[/C][/ROW]
[ROW][C]124[/C][C]11[/C][C]12.2413[/C][C]-1.24127[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]12.974[/C][C]-1.97403[/C][/ROW]
[ROW][C]126[/C][C]8[/C][C]9.71002[/C][C]-1.71002[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.2244[/C][C]-0.224408[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.6848[/C][C]1.3152[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]12.4882[/C][C]0.51175[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]13.5253[/C][C]-2.52529[/C][/ROW]
[ROW][C]131[/C][C]20[/C][C]17.2473[/C][C]2.75269[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]11.6512[/C][C]-1.65115[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.1614[/C][C]1.83859[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]12.2483[/C][C]-0.248257[/C][/ROW]
[ROW][C]135[/C][C]14[/C][C]10.952[/C][C]3.04801[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]16.4675[/C][C]6.53253[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]14.0987[/C][C]-0.0986926[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]16.8778[/C][C]-0.877775[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]13.1444[/C][C]-2.14436[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]14.0055[/C][C]-2.00545[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.4247[/C][C]-3.42472[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]10.8846[/C][C]3.11541[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]11.9535[/C][C]0.0464921[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]11.6851[/C][C]0.314877[/C][/ROW]
[ROW][C]145[/C][C]11[/C][C]10.7671[/C][C]0.232873[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.1108[/C][C]0.889191[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.9577[/C][C]-2.95765[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.0143[/C][C]-3.01429[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]16.6005[/C][C]2.39947[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]11.1605[/C][C]0.839499[/C][/ROW]
[ROW][C]151[/C][C]17[/C][C]12.5829[/C][C]4.41714[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.1002[/C][C]-2.10023[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.2344[/C][C]-2.23438[/C][/ROW]
[ROW][C]154[/C][C]19[/C][C]15.4534[/C][C]3.54665[/C][/ROW]
[ROW][C]155[/C][C]18[/C][C]14.097[/C][C]3.90301[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]14.3019[/C][C]0.69807[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.4383[/C][C]0.561655[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]9.43864[/C][C]1.56136[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]12.5576[/C][C]-3.55758[/C][/ROW]
[ROW][C]160[/C][C]18[/C][C]13.4929[/C][C]4.50707[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]14.4844[/C][C]1.51565[/C][/ROW]
[ROW][C]162[/C][C]24[/C][C]17.7911[/C][C]6.20893[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.2257[/C][C]0.77426[/C][/ROW]
[ROW][C]164[/C][C]20[/C][C]11.5067[/C][C]8.49327[/C][/ROW]
[ROW][C]165[/C][C]18[/C][C]16.4763[/C][C]1.5237[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]17.7331[/C][C]5.26692[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]13.6927[/C][C]-1.6927[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]15.3147[/C][C]-1.31472[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]16.727[/C][C]-0.727032[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]16.6907[/C][C]1.30933[/C][/ROW]
[ROW][C]171[/C][C]20[/C][C]17.2754[/C][C]2.72463[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]12.2808[/C][C]-0.280824[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]16.7678[/C][C]-4.76782[/C][/ROW]
[ROW][C]174[/C][C]17[/C][C]15.738[/C][C]1.26198[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]12.4996[/C][C]0.500409[/C][/ROW]
[ROW][C]176[/C][C]9[/C][C]13.5149[/C][C]-4.5149[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]17.8825[/C][C]-1.88246[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]15.4725[/C][C]2.52752[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]12.8606[/C][C]-2.86062[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]15.2763[/C][C]-1.27627[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]14.7152[/C][C]-3.71516[/C][/ROW]
[ROW][C]182[/C][C]9[/C][C]15.0911[/C][C]-6.0911[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]13.065[/C][C]-2.06505[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]12.898[/C][C]-2.89798[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]12.1122[/C][C]-1.11218[/C][/ROW]
[ROW][C]186[/C][C]19[/C][C]13.6735[/C][C]5.32654[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]12.9822[/C][C]1.01781[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]11.9944[/C][C]0.00557473[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]15.5057[/C][C]-1.50571[/C][/ROW]
[ROW][C]190[/C][C]21[/C][C]17.1884[/C][C]3.8116[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]15.8967[/C][C]-2.89671[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]12.9454[/C][C]-2.94541[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]13.5694[/C][C]1.43063[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]16.746[/C][C]-0.746027[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]13.1335[/C][C]0.866473[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]15.2066[/C][C]-3.20658[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]13.0802[/C][C]5.91982[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]12.551[/C][C]2.44896[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]18.3266[/C][C]0.673355[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.5503[/C][C]-0.550266[/C][/ROW]
[ROW][C]201[/C][C]17[/C][C]17.4995[/C][C]-0.499475[/C][/ROW]
[ROW][C]202[/C][C]12[/C][C]13.0536[/C][C]-1.05361[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]10.9615[/C][C]0.0384632[/C][/ROW]
[ROW][C]204[/C][C]14[/C][C]15.8647[/C][C]-1.86475[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]12.7795[/C][C]-1.77945[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]12.6731[/C][C]0.326908[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]13.1159[/C][C]-1.11593[/C][/ROW]
[ROW][C]208[/C][C]15[/C][C]13.1431[/C][C]1.85694[/C][/ROW]
[ROW][C]209[/C][C]14[/C][C]14.7498[/C][C]-0.749838[/C][/ROW]
[ROW][C]210[/C][C]12[/C][C]11.1525[/C][C]0.847501[/C][/ROW]
[ROW][C]211[/C][C]17[/C][C]17.7402[/C][C]-0.740236[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]11.6246[/C][C]-0.624597[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]14.7861[/C][C]3.21394[/C][/ROW]
[ROW][C]214[/C][C]13[/C][C]16.0677[/C][C]-3.06772[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.5429[/C][C]1.45714[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]13.6431[/C][C]-0.643084[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]10.4508[/C][C]0.549184[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]12.8928[/C][C]-0.8928[/C][/ROW]
[ROW][C]219[/C][C]22[/C][C]18.1757[/C][C]3.82427[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]12.3337[/C][C]1.66629[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]15.2059[/C][C]-3.20591[/C][/ROW]
[ROW][C]222[/C][C]12[/C][C]12.1362[/C][C]-0.136155[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]16.1226[/C][C]0.877434[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]13.0181[/C][C]-4.01811[/C][/ROW]
[ROW][C]225[/C][C]21[/C][C]17.0834[/C][C]3.91665[/C][/ROW]
[ROW][C]226[/C][C]10[/C][C]11.9892[/C][C]-1.9892[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]11.2201[/C][C]-0.220066[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]14.6724[/C][C]-2.67241[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]18.4321[/C][C]4.56792[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]15.8052[/C][C]-2.80523[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]13.5677[/C][C]-1.56772[/C][/ROW]
[ROW][C]232[/C][C]16[/C][C]17.9746[/C][C]-1.97463[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]13.71[/C][C]-4.70998[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]13.8283[/C][C]3.17174[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]12.0617[/C][C]-3.06167[/C][/ROW]
[ROW][C]236[/C][C]14[/C][C]15.7284[/C][C]-1.72837[/C][/ROW]
[ROW][C]237[/C][C]17[/C][C]15.7634[/C][C]1.23659[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]15.7744[/C][C]-2.77436[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]15.8656[/C][C]-4.86556[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]15.6485[/C][C]-3.6485[/C][/ROW]
[ROW][C]241[/C][C]10[/C][C]13.9384[/C][C]-3.93837[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]18.9937[/C][C]0.00627027[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]16.1017[/C][C]-0.101725[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]15.1411[/C][C]0.858917[/C][/ROW]
[ROW][C]245[/C][C]14[/C][C]12.2985[/C][C]1.70154[/C][/ROW]
[ROW][C]246[/C][C]20[/C][C]15.8397[/C][C]4.16028[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]14.5449[/C][C]0.455075[/C][/ROW]
[ROW][C]248[/C][C]23[/C][C]15.6258[/C][C]7.37425[/C][/ROW]
[ROW][C]249[/C][C]20[/C][C]17.8915[/C][C]2.10848[/C][/ROW]
[ROW][C]250[/C][C]16[/C][C]15.9113[/C][C]0.0887451[/C][/ROW]
[ROW][C]251[/C][C]14[/C][C]12.919[/C][C]1.08096[/C][/ROW]
[ROW][C]252[/C][C]17[/C][C]13.8036[/C][C]3.19642[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]14.2654[/C][C]-3.26542[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.9879[/C][C]-0.987913[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]15.2957[/C][C]1.70429[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]15.2082[/C][C]-0.208178[/C][/ROW]
[ROW][C]257[/C][C]21[/C][C]15.7553[/C][C]5.24468[/C][/ROW]
[ROW][C]258[/C][C]18[/C][C]17.7405[/C][C]0.259538[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.7714[/C][C]2.2286[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]16.2605[/C][C]-8.26045[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]13.571[/C][C]-1.57096[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]12.7856[/C][C]-0.78563[/C][/ROW]
[ROW][C]263[/C][C]22[/C][C]18.8923[/C][C]3.10766[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]13.1303[/C][C]-1.13026[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226597&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226597&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.9655-1.96554
2119.289171.71083
31415.3517-1.35173
41214.7991-2.79913
52111.19699.80308
6129.746682.25332
72214.38837.61174
81112.2901-1.29013
91011.9793-1.9793
101311.96911.03088
111010.2819-0.281943
12810.3688-2.36879
131515.8477-0.847707
141412.36761.63236
15108.864731.13527
161413.790.210009
171412.4121.58801
18119.269051.73095
191013.2521-3.25205
201312.47840.52158
219.510.4731-0.973139
221415.4432-1.44316
231213.4119-1.41194
241415.4346-1.4346
25119.363581.63642
26914.9237-5.92374
271110.39460.605422
281513.14181.85824
291411.09512.90491
301315.6533-2.65326
31910.8507-1.85067
321514.9530.0470209
331010.583-0.583031
341111.556-0.556013
351311.991.00996
36811.9114-3.91137
372016.88843.11159
381211.89690.103144
391010.2996-0.29964
401013.3652-3.36522
41911.5981-2.59815
421410.73773.26226
43811.763-3.76297
441415.1255-1.12546
451111.9854-0.985395
461314.7531-1.75312
47912.7534-3.75335
481111.7026-0.702625
49159.672735.32727
501112.7858-1.78576
511011.0445-1.04454
521412.7861.21402
531815.08872.91135
541415.735-1.73501
551114.604-3.60395
5614.511.73072.76934
571310.67562.32443
58912.2941-3.29411
591013.3939-3.39388
601513.89351.10653
612018.07861.92142
621212.2262-0.226243
631213.6615-1.66149
641413.67920.320773
651312.730.269975
661115.575-4.57498
671715.89711.10286
681214.0979-2.09789
691313.3458-0.34584
701412.84881.15116
711314.6207-1.62071
721513.39851.60148
731311.68751.31246
741012.218-2.21802
751113.037-2.03701
761914.09214.90792
771311.33611.66388
781714.53122.46878
791312.67090.329082
80915.0304-6.03037
811111.8253-0.825324
82912.9232-3.92316
831211.55850.441468
841212.7427-0.742689
851313.0186-0.0186067
861312.3630.637024
871213.4441-1.44409
881515.2055-0.205545
892218.30443.6956
901311.781.22
911514.83530.164707
921312.02530.974675
931512.32462.67539
9412.513.3929-0.892942
951110.90970.0903431
961614.77591.22409
971112.5562-1.5562
981110.19720.802817
991012.3924-2.39241
1001010.43-0.430015
1011614.4611.53896
1021210.54731.4527
1031115.9769-4.9769
1041611.84054.15948
1051916.72862.27139
1061111.3875-0.387513
1071612.21793.78206
1081516.9407-1.94073
1092417.95586.04422
1101411.67982.32019
1111514.81510.184892
1121112.968-1.96797
1131513.4151.585
1141210.3641.63598
1151010.5884-0.588433
1161414.3076-0.307576
1171314.0981-1.09807
118913.422-4.422
1191511.74783.25215
1201515.7612-0.761213
1211412.68521.31477
1221111.2452-0.245247
123811.9862-3.98621
1241112.2413-1.24127
1251112.974-1.97403
12689.71002-1.71002
1271010.2244-0.224408
128119.68481.3152
1291312.48820.51175
1301113.5253-2.52529
1312017.24732.75269
1321011.6512-1.65115
1331513.16141.83859
1341212.2483-0.248257
1351410.9523.04801
1362316.46756.53253
1371414.0987-0.0986926
1381616.8778-0.877775
1391113.1444-2.14436
1401214.0055-2.00545
1411013.4247-3.42472
1421410.88463.11541
1431211.95350.0464921
1441211.68510.314877
1451110.76710.232873
1461211.11080.889191
1471315.9577-2.95765
1481114.0143-3.01429
1491916.60052.39947
1501211.16050.839499
1511712.58294.41714
152911.1002-2.10023
1531214.2344-2.23438
1541915.45343.54665
1551814.0973.90301
1561514.30190.69807
1571413.43830.561655
158119.438641.56136
159912.5576-3.55758
1601813.49294.50707
1611614.48441.51565
1622417.79116.20893
1631413.22570.77426
1642011.50678.49327
1651816.47631.5237
1662317.73315.26692
1671213.6927-1.6927
1681415.3147-1.31472
1691616.727-0.727032
1701816.69071.30933
1712017.27542.72463
1721212.2808-0.280824
1731216.7678-4.76782
1741715.7381.26198
1751312.49960.500409
176913.5149-4.5149
1771617.8825-1.88246
1781815.47252.52752
1791012.8606-2.86062
1801415.2763-1.27627
1811114.7152-3.71516
182915.0911-6.0911
1831113.065-2.06505
1841012.898-2.89798
1851112.1122-1.11218
1861913.67355.32654
1871412.98221.01781
1881211.99440.00557473
1891415.5057-1.50571
1902117.18843.8116
1911315.8967-2.89671
1921012.9454-2.94541
1931513.56941.43063
1941616.746-0.746027
1951413.13350.866473
1961215.2066-3.20658
1971913.08025.91982
1981512.5512.44896
1991918.32660.673355
2001313.5503-0.550266
2011717.4995-0.499475
2021213.0536-1.05361
2031110.96150.0384632
2041415.8647-1.86475
2051112.7795-1.77945
2061312.67310.326908
2071213.1159-1.11593
2081513.14311.85694
2091414.7498-0.749838
2101211.15250.847501
2111717.7402-0.740236
2121111.6246-0.624597
2131814.78613.21394
2141316.0677-3.06772
2151715.54291.45714
2161313.6431-0.643084
2171110.45080.549184
2181212.8928-0.8928
2192218.17573.82427
2201412.33371.66629
2211215.2059-3.20591
2221212.1362-0.136155
2231716.12260.877434
224913.0181-4.01811
2252117.08343.91665
2261011.9892-1.9892
2271111.2201-0.220066
2281214.6724-2.67241
2292318.43214.56792
2301315.8052-2.80523
2311213.5677-1.56772
2321617.9746-1.97463
233913.71-4.70998
2341713.82833.17174
235912.0617-3.06167
2361415.7284-1.72837
2371715.76341.23659
2381315.7744-2.77436
2391115.8656-4.86556
2401215.6485-3.6485
2411013.9384-3.93837
2421918.99370.00627027
2431616.1017-0.101725
2441615.14110.858917
2451412.29851.70154
2462015.83974.16028
2471514.54490.455075
2482315.62587.37425
2492017.89152.10848
2501615.91130.0887451
2511412.9191.08096
2521713.80363.19642
2531114.2654-3.26542
2541313.9879-0.987913
2551715.29571.70429
2561515.2082-0.208178
2572115.75535.24468
2581817.74050.259538
2591512.77142.2286
260816.2605-8.26045
2611213.571-1.57096
2621212.7856-0.78563
2632218.89233.10766
2641213.1303-1.13026






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.9822780.03544340.0177217
140.9894630.02107440.0105372
150.9787050.042590.021295
160.960160.07967990.0398399
170.9830760.03384840.0169242
180.9742080.05158420.0257921
190.9837090.0325820.016291
200.9731030.05379370.0268968
210.9631880.07362490.0368125
220.9496230.1007550.0503773
230.9324520.1350960.0675481
240.9071220.1857560.0928782
250.880620.2387610.11938
260.8653220.2693570.134678
270.8916790.2166420.108321
280.8672980.2654050.132702
290.9025120.1949760.097488
300.8827890.2344220.117211
310.8694320.2611350.130568
320.8515950.296810.148405
330.814560.3708790.18544
340.7753550.4492890.224645
350.759820.480360.24018
360.7610480.4779040.238952
370.8588420.2823160.141158
380.8260810.3478370.173919
390.7887840.4224310.211216
400.766260.467480.23374
410.7329490.5341010.267051
420.7503060.4993880.249694
430.7560590.4878820.243941
440.7214620.5570770.278538
450.6784120.6431760.321588
460.6355560.7288890.364444
470.6249690.7500620.375031
480.5802810.8394390.419719
490.7287050.542590.271295
500.6909310.6181380.309069
510.6526380.6947240.347362
520.6336840.7326310.366316
530.6627640.6744730.337236
540.6390170.7219670.360983
550.6306890.7386210.369311
560.6935690.6128630.306431
570.6932950.6134110.306705
580.7007110.5985770.299289
590.6930220.6139570.306978
600.6885830.6228330.311417
610.7151540.5696920.284846
620.6784150.643170.321585
630.646060.7078810.35394
640.6077030.7845940.392297
650.5684320.8631350.431568
660.5591290.8817420.440871
670.586090.827820.41391
680.5604420.8791150.439558
690.5198660.9602690.480134
700.4925930.9851870.507407
710.4566330.9132650.543367
720.4258850.8517710.574115
730.3943770.7887550.605623
740.3777250.755450.622275
750.3518340.7036680.648166
760.4906840.9813680.509316
770.4604320.9208640.539568
780.4532730.9065450.546727
790.4145670.8291340.585433
800.5501520.8996960.449848
810.5161380.9677230.483862
820.5499950.9000110.450005
830.5118860.9762290.488114
840.4751640.9503280.524836
850.4367890.8735780.563211
860.4012990.8025970.598701
870.3718320.7436640.628168
880.3384940.6769890.661506
890.41450.8290.5855
900.3812740.7625480.618726
910.3513320.7026630.648668
920.3200520.6401050.679948
930.3131020.6262030.686898
940.2855770.5711530.714423
950.2538330.5076660.746167
960.2359020.4718040.764098
970.217470.4349390.78253
980.191680.3833610.80832
990.1876510.3753020.812349
1000.1639320.3278640.836068
1010.1529210.3058430.847079
1020.1366210.2732430.863379
1030.1831110.3662220.816889
1040.2113880.4227750.788612
1050.2151730.4303460.784827
1060.1896970.3793940.810303
1070.2096830.4193650.790317
1080.1975740.3951470.802426
1090.2989130.5978260.701087
1100.2870980.5741970.712902
1110.2575370.5150750.742463
1120.2487660.4975310.751234
1130.2260130.4520260.773987
1140.2059310.4118610.794069
1150.1823220.3646440.817678
1160.1598090.3196190.840191
1170.1434350.286870.856565
1180.1827670.3655340.817233
1190.1882220.3764430.811778
1200.1672370.3344730.832763
1210.1522480.3044950.847752
1220.1336430.2672860.866357
1230.1598540.3197080.840146
1240.1432650.286530.856735
1250.133970.2679410.86603
1260.1238180.2476360.876182
1270.1070510.2141030.892949
1280.09462370.1892470.905376
1290.08069520.161390.919305
1300.07973960.1594790.92026
1310.0811830.1623660.918817
1320.07402150.1480430.925978
1330.06721220.1344240.932788
1340.05645160.1129030.943548
1350.05845030.1169010.94155
1360.1174040.2348080.882596
1370.1011380.2022760.898862
1380.08919950.1783990.9108
1390.08664630.1732930.913354
1400.08268640.1653730.917314
1410.09617490.192350.903825
1420.09768730.1953750.902313
1430.08333770.1666750.916662
1440.07026090.1405220.929739
1450.05905610.1181120.940944
1460.04974760.09949520.950252
1470.05654720.1130940.943453
1480.06344910.1268980.936551
1490.05948230.1189650.940518
1500.04963710.09927410.950363
1510.06182790.1236560.938172
1520.05963320.1192660.940367
1530.06119250.1223850.938808
1540.06315940.1263190.936841
1550.06722610.1344520.932774
1560.05730270.1146050.942697
1570.04799510.09599020.952005
1580.04038550.0807710.959615
1590.05571960.1114390.94428
1600.06135770.1227150.938642
1610.05191240.1038250.948088
1620.09075410.1815080.909246
1630.08056480.161130.919435
1640.2762660.5525320.723734
1650.2511350.5022710.748865
1660.3161770.6323540.683823
1670.3000940.6001880.699906
1680.2830550.566110.716945
1690.2556930.5113870.744307
1700.2332440.4664880.766756
1710.2312870.4625740.768713
1720.2051470.4102940.794853
1730.2574590.5149180.742541
1740.2481490.4962990.751851
1750.2325860.4651720.767414
1760.2743270.5486540.725673
1770.2559480.5118950.744052
1780.2654060.5308120.734594
1790.260640.5212810.73936
1800.2343950.4687890.765605
1810.2648840.5297680.735116
1820.3821750.764350.617825
1830.3737230.7474470.626277
1840.3721390.7442780.627861
1850.3533620.7067250.646638
1860.4625450.925090.537455
1870.4270480.8540960.572952
1880.3940230.7880450.605977
1890.3619250.723850.638075
1900.3917890.7835790.608211
1910.4203560.8407120.579644
1920.4412950.8825910.558705
1930.4289990.8579980.571001
1940.3985720.7971430.601428
1950.3705580.7411160.629442
1960.4084230.8168460.591577
1970.6128640.7742720.387136
1980.6221810.7556380.377819
1990.5815840.8368320.418416
2000.5401810.9196370.459819
2010.4969730.9939450.503027
2020.457270.9145390.54273
2030.4379550.8759090.562045
2040.4263650.8527310.573635
2050.3900040.7800090.609996
2060.3493680.6987370.650632
2070.3110520.6221050.688948
2080.2778760.5557520.722124
2090.2414520.4829050.758548
2100.2379120.4758240.762088
2110.2121980.4243960.787802
2120.1825330.3650660.817467
2130.2097590.4195180.790241
2140.1919230.3838470.808077
2150.1645850.329170.835415
2160.1403570.2807140.859643
2170.1371030.2742060.862897
2180.1154890.2309770.884511
2190.1281990.2563990.871801
2200.1346020.2692040.865398
2210.1226670.2453340.877333
2220.0984710.1969420.901529
2230.08483530.1696710.915165
2240.07822410.1564480.921776
2250.07234870.1446970.927651
2260.06031430.1206290.939686
2270.04583350.09166690.954167
2280.03782690.07565370.962173
2290.06740710.1348140.932593
2300.05550370.1110070.944496
2310.04269890.08539780.957301
2320.036130.07225990.96387
2330.0689260.1378520.931074
2340.07476550.1495310.925234
2350.06785870.1357170.932141
2360.05018720.1003740.949813
2370.07007410.1401480.929926
2380.09432160.1886430.905678
2390.1839280.3678570.816072
2400.2258930.4517850.774107
2410.2091850.418370.790815
2420.6362880.7274250.363712
2430.5519330.8961350.448067
2440.5430920.9138160.456908
2450.4755880.9511760.524412
2460.3892030.7784060.610797
2470.3750710.7501430.624929
2480.3233030.6466050.676697
2490.327870.655740.67213
2500.2791810.5583620.720819
2510.1728510.3457020.827149

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.982278 & 0.0354434 & 0.0177217 \tabularnewline
14 & 0.989463 & 0.0210744 & 0.0105372 \tabularnewline
15 & 0.978705 & 0.04259 & 0.021295 \tabularnewline
16 & 0.96016 & 0.0796799 & 0.0398399 \tabularnewline
17 & 0.983076 & 0.0338484 & 0.0169242 \tabularnewline
18 & 0.974208 & 0.0515842 & 0.0257921 \tabularnewline
19 & 0.983709 & 0.032582 & 0.016291 \tabularnewline
20 & 0.973103 & 0.0537937 & 0.0268968 \tabularnewline
21 & 0.963188 & 0.0736249 & 0.0368125 \tabularnewline
22 & 0.949623 & 0.100755 & 0.0503773 \tabularnewline
23 & 0.932452 & 0.135096 & 0.0675481 \tabularnewline
24 & 0.907122 & 0.185756 & 0.0928782 \tabularnewline
25 & 0.88062 & 0.238761 & 0.11938 \tabularnewline
26 & 0.865322 & 0.269357 & 0.134678 \tabularnewline
27 & 0.891679 & 0.216642 & 0.108321 \tabularnewline
28 & 0.867298 & 0.265405 & 0.132702 \tabularnewline
29 & 0.902512 & 0.194976 & 0.097488 \tabularnewline
30 & 0.882789 & 0.234422 & 0.117211 \tabularnewline
31 & 0.869432 & 0.261135 & 0.130568 \tabularnewline
32 & 0.851595 & 0.29681 & 0.148405 \tabularnewline
33 & 0.81456 & 0.370879 & 0.18544 \tabularnewline
34 & 0.775355 & 0.449289 & 0.224645 \tabularnewline
35 & 0.75982 & 0.48036 & 0.24018 \tabularnewline
36 & 0.761048 & 0.477904 & 0.238952 \tabularnewline
37 & 0.858842 & 0.282316 & 0.141158 \tabularnewline
38 & 0.826081 & 0.347837 & 0.173919 \tabularnewline
39 & 0.788784 & 0.422431 & 0.211216 \tabularnewline
40 & 0.76626 & 0.46748 & 0.23374 \tabularnewline
41 & 0.732949 & 0.534101 & 0.267051 \tabularnewline
42 & 0.750306 & 0.499388 & 0.249694 \tabularnewline
43 & 0.756059 & 0.487882 & 0.243941 \tabularnewline
44 & 0.721462 & 0.557077 & 0.278538 \tabularnewline
45 & 0.678412 & 0.643176 & 0.321588 \tabularnewline
46 & 0.635556 & 0.728889 & 0.364444 \tabularnewline
47 & 0.624969 & 0.750062 & 0.375031 \tabularnewline
48 & 0.580281 & 0.839439 & 0.419719 \tabularnewline
49 & 0.728705 & 0.54259 & 0.271295 \tabularnewline
50 & 0.690931 & 0.618138 & 0.309069 \tabularnewline
51 & 0.652638 & 0.694724 & 0.347362 \tabularnewline
52 & 0.633684 & 0.732631 & 0.366316 \tabularnewline
53 & 0.662764 & 0.674473 & 0.337236 \tabularnewline
54 & 0.639017 & 0.721967 & 0.360983 \tabularnewline
55 & 0.630689 & 0.738621 & 0.369311 \tabularnewline
56 & 0.693569 & 0.612863 & 0.306431 \tabularnewline
57 & 0.693295 & 0.613411 & 0.306705 \tabularnewline
58 & 0.700711 & 0.598577 & 0.299289 \tabularnewline
59 & 0.693022 & 0.613957 & 0.306978 \tabularnewline
60 & 0.688583 & 0.622833 & 0.311417 \tabularnewline
61 & 0.715154 & 0.569692 & 0.284846 \tabularnewline
62 & 0.678415 & 0.64317 & 0.321585 \tabularnewline
63 & 0.64606 & 0.707881 & 0.35394 \tabularnewline
64 & 0.607703 & 0.784594 & 0.392297 \tabularnewline
65 & 0.568432 & 0.863135 & 0.431568 \tabularnewline
66 & 0.559129 & 0.881742 & 0.440871 \tabularnewline
67 & 0.58609 & 0.82782 & 0.41391 \tabularnewline
68 & 0.560442 & 0.879115 & 0.439558 \tabularnewline
69 & 0.519866 & 0.960269 & 0.480134 \tabularnewline
70 & 0.492593 & 0.985187 & 0.507407 \tabularnewline
71 & 0.456633 & 0.913265 & 0.543367 \tabularnewline
72 & 0.425885 & 0.851771 & 0.574115 \tabularnewline
73 & 0.394377 & 0.788755 & 0.605623 \tabularnewline
74 & 0.377725 & 0.75545 & 0.622275 \tabularnewline
75 & 0.351834 & 0.703668 & 0.648166 \tabularnewline
76 & 0.490684 & 0.981368 & 0.509316 \tabularnewline
77 & 0.460432 & 0.920864 & 0.539568 \tabularnewline
78 & 0.453273 & 0.906545 & 0.546727 \tabularnewline
79 & 0.414567 & 0.829134 & 0.585433 \tabularnewline
80 & 0.550152 & 0.899696 & 0.449848 \tabularnewline
81 & 0.516138 & 0.967723 & 0.483862 \tabularnewline
82 & 0.549995 & 0.900011 & 0.450005 \tabularnewline
83 & 0.511886 & 0.976229 & 0.488114 \tabularnewline
84 & 0.475164 & 0.950328 & 0.524836 \tabularnewline
85 & 0.436789 & 0.873578 & 0.563211 \tabularnewline
86 & 0.401299 & 0.802597 & 0.598701 \tabularnewline
87 & 0.371832 & 0.743664 & 0.628168 \tabularnewline
88 & 0.338494 & 0.676989 & 0.661506 \tabularnewline
89 & 0.4145 & 0.829 & 0.5855 \tabularnewline
90 & 0.381274 & 0.762548 & 0.618726 \tabularnewline
91 & 0.351332 & 0.702663 & 0.648668 \tabularnewline
92 & 0.320052 & 0.640105 & 0.679948 \tabularnewline
93 & 0.313102 & 0.626203 & 0.686898 \tabularnewline
94 & 0.285577 & 0.571153 & 0.714423 \tabularnewline
95 & 0.253833 & 0.507666 & 0.746167 \tabularnewline
96 & 0.235902 & 0.471804 & 0.764098 \tabularnewline
97 & 0.21747 & 0.434939 & 0.78253 \tabularnewline
98 & 0.19168 & 0.383361 & 0.80832 \tabularnewline
99 & 0.187651 & 0.375302 & 0.812349 \tabularnewline
100 & 0.163932 & 0.327864 & 0.836068 \tabularnewline
101 & 0.152921 & 0.305843 & 0.847079 \tabularnewline
102 & 0.136621 & 0.273243 & 0.863379 \tabularnewline
103 & 0.183111 & 0.366222 & 0.816889 \tabularnewline
104 & 0.211388 & 0.422775 & 0.788612 \tabularnewline
105 & 0.215173 & 0.430346 & 0.784827 \tabularnewline
106 & 0.189697 & 0.379394 & 0.810303 \tabularnewline
107 & 0.209683 & 0.419365 & 0.790317 \tabularnewline
108 & 0.197574 & 0.395147 & 0.802426 \tabularnewline
109 & 0.298913 & 0.597826 & 0.701087 \tabularnewline
110 & 0.287098 & 0.574197 & 0.712902 \tabularnewline
111 & 0.257537 & 0.515075 & 0.742463 \tabularnewline
112 & 0.248766 & 0.497531 & 0.751234 \tabularnewline
113 & 0.226013 & 0.452026 & 0.773987 \tabularnewline
114 & 0.205931 & 0.411861 & 0.794069 \tabularnewline
115 & 0.182322 & 0.364644 & 0.817678 \tabularnewline
116 & 0.159809 & 0.319619 & 0.840191 \tabularnewline
117 & 0.143435 & 0.28687 & 0.856565 \tabularnewline
118 & 0.182767 & 0.365534 & 0.817233 \tabularnewline
119 & 0.188222 & 0.376443 & 0.811778 \tabularnewline
120 & 0.167237 & 0.334473 & 0.832763 \tabularnewline
121 & 0.152248 & 0.304495 & 0.847752 \tabularnewline
122 & 0.133643 & 0.267286 & 0.866357 \tabularnewline
123 & 0.159854 & 0.319708 & 0.840146 \tabularnewline
124 & 0.143265 & 0.28653 & 0.856735 \tabularnewline
125 & 0.13397 & 0.267941 & 0.86603 \tabularnewline
126 & 0.123818 & 0.247636 & 0.876182 \tabularnewline
127 & 0.107051 & 0.214103 & 0.892949 \tabularnewline
128 & 0.0946237 & 0.189247 & 0.905376 \tabularnewline
129 & 0.0806952 & 0.16139 & 0.919305 \tabularnewline
130 & 0.0797396 & 0.159479 & 0.92026 \tabularnewline
131 & 0.081183 & 0.162366 & 0.918817 \tabularnewline
132 & 0.0740215 & 0.148043 & 0.925978 \tabularnewline
133 & 0.0672122 & 0.134424 & 0.932788 \tabularnewline
134 & 0.0564516 & 0.112903 & 0.943548 \tabularnewline
135 & 0.0584503 & 0.116901 & 0.94155 \tabularnewline
136 & 0.117404 & 0.234808 & 0.882596 \tabularnewline
137 & 0.101138 & 0.202276 & 0.898862 \tabularnewline
138 & 0.0891995 & 0.178399 & 0.9108 \tabularnewline
139 & 0.0866463 & 0.173293 & 0.913354 \tabularnewline
140 & 0.0826864 & 0.165373 & 0.917314 \tabularnewline
141 & 0.0961749 & 0.19235 & 0.903825 \tabularnewline
142 & 0.0976873 & 0.195375 & 0.902313 \tabularnewline
143 & 0.0833377 & 0.166675 & 0.916662 \tabularnewline
144 & 0.0702609 & 0.140522 & 0.929739 \tabularnewline
145 & 0.0590561 & 0.118112 & 0.940944 \tabularnewline
146 & 0.0497476 & 0.0994952 & 0.950252 \tabularnewline
147 & 0.0565472 & 0.113094 & 0.943453 \tabularnewline
148 & 0.0634491 & 0.126898 & 0.936551 \tabularnewline
149 & 0.0594823 & 0.118965 & 0.940518 \tabularnewline
150 & 0.0496371 & 0.0992741 & 0.950363 \tabularnewline
151 & 0.0618279 & 0.123656 & 0.938172 \tabularnewline
152 & 0.0596332 & 0.119266 & 0.940367 \tabularnewline
153 & 0.0611925 & 0.122385 & 0.938808 \tabularnewline
154 & 0.0631594 & 0.126319 & 0.936841 \tabularnewline
155 & 0.0672261 & 0.134452 & 0.932774 \tabularnewline
156 & 0.0573027 & 0.114605 & 0.942697 \tabularnewline
157 & 0.0479951 & 0.0959902 & 0.952005 \tabularnewline
158 & 0.0403855 & 0.080771 & 0.959615 \tabularnewline
159 & 0.0557196 & 0.111439 & 0.94428 \tabularnewline
160 & 0.0613577 & 0.122715 & 0.938642 \tabularnewline
161 & 0.0519124 & 0.103825 & 0.948088 \tabularnewline
162 & 0.0907541 & 0.181508 & 0.909246 \tabularnewline
163 & 0.0805648 & 0.16113 & 0.919435 \tabularnewline
164 & 0.276266 & 0.552532 & 0.723734 \tabularnewline
165 & 0.251135 & 0.502271 & 0.748865 \tabularnewline
166 & 0.316177 & 0.632354 & 0.683823 \tabularnewline
167 & 0.300094 & 0.600188 & 0.699906 \tabularnewline
168 & 0.283055 & 0.56611 & 0.716945 \tabularnewline
169 & 0.255693 & 0.511387 & 0.744307 \tabularnewline
170 & 0.233244 & 0.466488 & 0.766756 \tabularnewline
171 & 0.231287 & 0.462574 & 0.768713 \tabularnewline
172 & 0.205147 & 0.410294 & 0.794853 \tabularnewline
173 & 0.257459 & 0.514918 & 0.742541 \tabularnewline
174 & 0.248149 & 0.496299 & 0.751851 \tabularnewline
175 & 0.232586 & 0.465172 & 0.767414 \tabularnewline
176 & 0.274327 & 0.548654 & 0.725673 \tabularnewline
177 & 0.255948 & 0.511895 & 0.744052 \tabularnewline
178 & 0.265406 & 0.530812 & 0.734594 \tabularnewline
179 & 0.26064 & 0.521281 & 0.73936 \tabularnewline
180 & 0.234395 & 0.468789 & 0.765605 \tabularnewline
181 & 0.264884 & 0.529768 & 0.735116 \tabularnewline
182 & 0.382175 & 0.76435 & 0.617825 \tabularnewline
183 & 0.373723 & 0.747447 & 0.626277 \tabularnewline
184 & 0.372139 & 0.744278 & 0.627861 \tabularnewline
185 & 0.353362 & 0.706725 & 0.646638 \tabularnewline
186 & 0.462545 & 0.92509 & 0.537455 \tabularnewline
187 & 0.427048 & 0.854096 & 0.572952 \tabularnewline
188 & 0.394023 & 0.788045 & 0.605977 \tabularnewline
189 & 0.361925 & 0.72385 & 0.638075 \tabularnewline
190 & 0.391789 & 0.783579 & 0.608211 \tabularnewline
191 & 0.420356 & 0.840712 & 0.579644 \tabularnewline
192 & 0.441295 & 0.882591 & 0.558705 \tabularnewline
193 & 0.428999 & 0.857998 & 0.571001 \tabularnewline
194 & 0.398572 & 0.797143 & 0.601428 \tabularnewline
195 & 0.370558 & 0.741116 & 0.629442 \tabularnewline
196 & 0.408423 & 0.816846 & 0.591577 \tabularnewline
197 & 0.612864 & 0.774272 & 0.387136 \tabularnewline
198 & 0.622181 & 0.755638 & 0.377819 \tabularnewline
199 & 0.581584 & 0.836832 & 0.418416 \tabularnewline
200 & 0.540181 & 0.919637 & 0.459819 \tabularnewline
201 & 0.496973 & 0.993945 & 0.503027 \tabularnewline
202 & 0.45727 & 0.914539 & 0.54273 \tabularnewline
203 & 0.437955 & 0.875909 & 0.562045 \tabularnewline
204 & 0.426365 & 0.852731 & 0.573635 \tabularnewline
205 & 0.390004 & 0.780009 & 0.609996 \tabularnewline
206 & 0.349368 & 0.698737 & 0.650632 \tabularnewline
207 & 0.311052 & 0.622105 & 0.688948 \tabularnewline
208 & 0.277876 & 0.555752 & 0.722124 \tabularnewline
209 & 0.241452 & 0.482905 & 0.758548 \tabularnewline
210 & 0.237912 & 0.475824 & 0.762088 \tabularnewline
211 & 0.212198 & 0.424396 & 0.787802 \tabularnewline
212 & 0.182533 & 0.365066 & 0.817467 \tabularnewline
213 & 0.209759 & 0.419518 & 0.790241 \tabularnewline
214 & 0.191923 & 0.383847 & 0.808077 \tabularnewline
215 & 0.164585 & 0.32917 & 0.835415 \tabularnewline
216 & 0.140357 & 0.280714 & 0.859643 \tabularnewline
217 & 0.137103 & 0.274206 & 0.862897 \tabularnewline
218 & 0.115489 & 0.230977 & 0.884511 \tabularnewline
219 & 0.128199 & 0.256399 & 0.871801 \tabularnewline
220 & 0.134602 & 0.269204 & 0.865398 \tabularnewline
221 & 0.122667 & 0.245334 & 0.877333 \tabularnewline
222 & 0.098471 & 0.196942 & 0.901529 \tabularnewline
223 & 0.0848353 & 0.169671 & 0.915165 \tabularnewline
224 & 0.0782241 & 0.156448 & 0.921776 \tabularnewline
225 & 0.0723487 & 0.144697 & 0.927651 \tabularnewline
226 & 0.0603143 & 0.120629 & 0.939686 \tabularnewline
227 & 0.0458335 & 0.0916669 & 0.954167 \tabularnewline
228 & 0.0378269 & 0.0756537 & 0.962173 \tabularnewline
229 & 0.0674071 & 0.134814 & 0.932593 \tabularnewline
230 & 0.0555037 & 0.111007 & 0.944496 \tabularnewline
231 & 0.0426989 & 0.0853978 & 0.957301 \tabularnewline
232 & 0.03613 & 0.0722599 & 0.96387 \tabularnewline
233 & 0.068926 & 0.137852 & 0.931074 \tabularnewline
234 & 0.0747655 & 0.149531 & 0.925234 \tabularnewline
235 & 0.0678587 & 0.135717 & 0.932141 \tabularnewline
236 & 0.0501872 & 0.100374 & 0.949813 \tabularnewline
237 & 0.0700741 & 0.140148 & 0.929926 \tabularnewline
238 & 0.0943216 & 0.188643 & 0.905678 \tabularnewline
239 & 0.183928 & 0.367857 & 0.816072 \tabularnewline
240 & 0.225893 & 0.451785 & 0.774107 \tabularnewline
241 & 0.209185 & 0.41837 & 0.790815 \tabularnewline
242 & 0.636288 & 0.727425 & 0.363712 \tabularnewline
243 & 0.551933 & 0.896135 & 0.448067 \tabularnewline
244 & 0.543092 & 0.913816 & 0.456908 \tabularnewline
245 & 0.475588 & 0.951176 & 0.524412 \tabularnewline
246 & 0.389203 & 0.778406 & 0.610797 \tabularnewline
247 & 0.375071 & 0.750143 & 0.624929 \tabularnewline
248 & 0.323303 & 0.646605 & 0.676697 \tabularnewline
249 & 0.32787 & 0.65574 & 0.67213 \tabularnewline
250 & 0.279181 & 0.558362 & 0.720819 \tabularnewline
251 & 0.172851 & 0.345702 & 0.827149 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226597&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]13[/C][C]0.982278[/C][C]0.0354434[/C][C]0.0177217[/C][/ROW]
[ROW][C]14[/C][C]0.989463[/C][C]0.0210744[/C][C]0.0105372[/C][/ROW]
[ROW][C]15[/C][C]0.978705[/C][C]0.04259[/C][C]0.021295[/C][/ROW]
[ROW][C]16[/C][C]0.96016[/C][C]0.0796799[/C][C]0.0398399[/C][/ROW]
[ROW][C]17[/C][C]0.983076[/C][C]0.0338484[/C][C]0.0169242[/C][/ROW]
[ROW][C]18[/C][C]0.974208[/C][C]0.0515842[/C][C]0.0257921[/C][/ROW]
[ROW][C]19[/C][C]0.983709[/C][C]0.032582[/C][C]0.016291[/C][/ROW]
[ROW][C]20[/C][C]0.973103[/C][C]0.0537937[/C][C]0.0268968[/C][/ROW]
[ROW][C]21[/C][C]0.963188[/C][C]0.0736249[/C][C]0.0368125[/C][/ROW]
[ROW][C]22[/C][C]0.949623[/C][C]0.100755[/C][C]0.0503773[/C][/ROW]
[ROW][C]23[/C][C]0.932452[/C][C]0.135096[/C][C]0.0675481[/C][/ROW]
[ROW][C]24[/C][C]0.907122[/C][C]0.185756[/C][C]0.0928782[/C][/ROW]
[ROW][C]25[/C][C]0.88062[/C][C]0.238761[/C][C]0.11938[/C][/ROW]
[ROW][C]26[/C][C]0.865322[/C][C]0.269357[/C][C]0.134678[/C][/ROW]
[ROW][C]27[/C][C]0.891679[/C][C]0.216642[/C][C]0.108321[/C][/ROW]
[ROW][C]28[/C][C]0.867298[/C][C]0.265405[/C][C]0.132702[/C][/ROW]
[ROW][C]29[/C][C]0.902512[/C][C]0.194976[/C][C]0.097488[/C][/ROW]
[ROW][C]30[/C][C]0.882789[/C][C]0.234422[/C][C]0.117211[/C][/ROW]
[ROW][C]31[/C][C]0.869432[/C][C]0.261135[/C][C]0.130568[/C][/ROW]
[ROW][C]32[/C][C]0.851595[/C][C]0.29681[/C][C]0.148405[/C][/ROW]
[ROW][C]33[/C][C]0.81456[/C][C]0.370879[/C][C]0.18544[/C][/ROW]
[ROW][C]34[/C][C]0.775355[/C][C]0.449289[/C][C]0.224645[/C][/ROW]
[ROW][C]35[/C][C]0.75982[/C][C]0.48036[/C][C]0.24018[/C][/ROW]
[ROW][C]36[/C][C]0.761048[/C][C]0.477904[/C][C]0.238952[/C][/ROW]
[ROW][C]37[/C][C]0.858842[/C][C]0.282316[/C][C]0.141158[/C][/ROW]
[ROW][C]38[/C][C]0.826081[/C][C]0.347837[/C][C]0.173919[/C][/ROW]
[ROW][C]39[/C][C]0.788784[/C][C]0.422431[/C][C]0.211216[/C][/ROW]
[ROW][C]40[/C][C]0.76626[/C][C]0.46748[/C][C]0.23374[/C][/ROW]
[ROW][C]41[/C][C]0.732949[/C][C]0.534101[/C][C]0.267051[/C][/ROW]
[ROW][C]42[/C][C]0.750306[/C][C]0.499388[/C][C]0.249694[/C][/ROW]
[ROW][C]43[/C][C]0.756059[/C][C]0.487882[/C][C]0.243941[/C][/ROW]
[ROW][C]44[/C][C]0.721462[/C][C]0.557077[/C][C]0.278538[/C][/ROW]
[ROW][C]45[/C][C]0.678412[/C][C]0.643176[/C][C]0.321588[/C][/ROW]
[ROW][C]46[/C][C]0.635556[/C][C]0.728889[/C][C]0.364444[/C][/ROW]
[ROW][C]47[/C][C]0.624969[/C][C]0.750062[/C][C]0.375031[/C][/ROW]
[ROW][C]48[/C][C]0.580281[/C][C]0.839439[/C][C]0.419719[/C][/ROW]
[ROW][C]49[/C][C]0.728705[/C][C]0.54259[/C][C]0.271295[/C][/ROW]
[ROW][C]50[/C][C]0.690931[/C][C]0.618138[/C][C]0.309069[/C][/ROW]
[ROW][C]51[/C][C]0.652638[/C][C]0.694724[/C][C]0.347362[/C][/ROW]
[ROW][C]52[/C][C]0.633684[/C][C]0.732631[/C][C]0.366316[/C][/ROW]
[ROW][C]53[/C][C]0.662764[/C][C]0.674473[/C][C]0.337236[/C][/ROW]
[ROW][C]54[/C][C]0.639017[/C][C]0.721967[/C][C]0.360983[/C][/ROW]
[ROW][C]55[/C][C]0.630689[/C][C]0.738621[/C][C]0.369311[/C][/ROW]
[ROW][C]56[/C][C]0.693569[/C][C]0.612863[/C][C]0.306431[/C][/ROW]
[ROW][C]57[/C][C]0.693295[/C][C]0.613411[/C][C]0.306705[/C][/ROW]
[ROW][C]58[/C][C]0.700711[/C][C]0.598577[/C][C]0.299289[/C][/ROW]
[ROW][C]59[/C][C]0.693022[/C][C]0.613957[/C][C]0.306978[/C][/ROW]
[ROW][C]60[/C][C]0.688583[/C][C]0.622833[/C][C]0.311417[/C][/ROW]
[ROW][C]61[/C][C]0.715154[/C][C]0.569692[/C][C]0.284846[/C][/ROW]
[ROW][C]62[/C][C]0.678415[/C][C]0.64317[/C][C]0.321585[/C][/ROW]
[ROW][C]63[/C][C]0.64606[/C][C]0.707881[/C][C]0.35394[/C][/ROW]
[ROW][C]64[/C][C]0.607703[/C][C]0.784594[/C][C]0.392297[/C][/ROW]
[ROW][C]65[/C][C]0.568432[/C][C]0.863135[/C][C]0.431568[/C][/ROW]
[ROW][C]66[/C][C]0.559129[/C][C]0.881742[/C][C]0.440871[/C][/ROW]
[ROW][C]67[/C][C]0.58609[/C][C]0.82782[/C][C]0.41391[/C][/ROW]
[ROW][C]68[/C][C]0.560442[/C][C]0.879115[/C][C]0.439558[/C][/ROW]
[ROW][C]69[/C][C]0.519866[/C][C]0.960269[/C][C]0.480134[/C][/ROW]
[ROW][C]70[/C][C]0.492593[/C][C]0.985187[/C][C]0.507407[/C][/ROW]
[ROW][C]71[/C][C]0.456633[/C][C]0.913265[/C][C]0.543367[/C][/ROW]
[ROW][C]72[/C][C]0.425885[/C][C]0.851771[/C][C]0.574115[/C][/ROW]
[ROW][C]73[/C][C]0.394377[/C][C]0.788755[/C][C]0.605623[/C][/ROW]
[ROW][C]74[/C][C]0.377725[/C][C]0.75545[/C][C]0.622275[/C][/ROW]
[ROW][C]75[/C][C]0.351834[/C][C]0.703668[/C][C]0.648166[/C][/ROW]
[ROW][C]76[/C][C]0.490684[/C][C]0.981368[/C][C]0.509316[/C][/ROW]
[ROW][C]77[/C][C]0.460432[/C][C]0.920864[/C][C]0.539568[/C][/ROW]
[ROW][C]78[/C][C]0.453273[/C][C]0.906545[/C][C]0.546727[/C][/ROW]
[ROW][C]79[/C][C]0.414567[/C][C]0.829134[/C][C]0.585433[/C][/ROW]
[ROW][C]80[/C][C]0.550152[/C][C]0.899696[/C][C]0.449848[/C][/ROW]
[ROW][C]81[/C][C]0.516138[/C][C]0.967723[/C][C]0.483862[/C][/ROW]
[ROW][C]82[/C][C]0.549995[/C][C]0.900011[/C][C]0.450005[/C][/ROW]
[ROW][C]83[/C][C]0.511886[/C][C]0.976229[/C][C]0.488114[/C][/ROW]
[ROW][C]84[/C][C]0.475164[/C][C]0.950328[/C][C]0.524836[/C][/ROW]
[ROW][C]85[/C][C]0.436789[/C][C]0.873578[/C][C]0.563211[/C][/ROW]
[ROW][C]86[/C][C]0.401299[/C][C]0.802597[/C][C]0.598701[/C][/ROW]
[ROW][C]87[/C][C]0.371832[/C][C]0.743664[/C][C]0.628168[/C][/ROW]
[ROW][C]88[/C][C]0.338494[/C][C]0.676989[/C][C]0.661506[/C][/ROW]
[ROW][C]89[/C][C]0.4145[/C][C]0.829[/C][C]0.5855[/C][/ROW]
[ROW][C]90[/C][C]0.381274[/C][C]0.762548[/C][C]0.618726[/C][/ROW]
[ROW][C]91[/C][C]0.351332[/C][C]0.702663[/C][C]0.648668[/C][/ROW]
[ROW][C]92[/C][C]0.320052[/C][C]0.640105[/C][C]0.679948[/C][/ROW]
[ROW][C]93[/C][C]0.313102[/C][C]0.626203[/C][C]0.686898[/C][/ROW]
[ROW][C]94[/C][C]0.285577[/C][C]0.571153[/C][C]0.714423[/C][/ROW]
[ROW][C]95[/C][C]0.253833[/C][C]0.507666[/C][C]0.746167[/C][/ROW]
[ROW][C]96[/C][C]0.235902[/C][C]0.471804[/C][C]0.764098[/C][/ROW]
[ROW][C]97[/C][C]0.21747[/C][C]0.434939[/C][C]0.78253[/C][/ROW]
[ROW][C]98[/C][C]0.19168[/C][C]0.383361[/C][C]0.80832[/C][/ROW]
[ROW][C]99[/C][C]0.187651[/C][C]0.375302[/C][C]0.812349[/C][/ROW]
[ROW][C]100[/C][C]0.163932[/C][C]0.327864[/C][C]0.836068[/C][/ROW]
[ROW][C]101[/C][C]0.152921[/C][C]0.305843[/C][C]0.847079[/C][/ROW]
[ROW][C]102[/C][C]0.136621[/C][C]0.273243[/C][C]0.863379[/C][/ROW]
[ROW][C]103[/C][C]0.183111[/C][C]0.366222[/C][C]0.816889[/C][/ROW]
[ROW][C]104[/C][C]0.211388[/C][C]0.422775[/C][C]0.788612[/C][/ROW]
[ROW][C]105[/C][C]0.215173[/C][C]0.430346[/C][C]0.784827[/C][/ROW]
[ROW][C]106[/C][C]0.189697[/C][C]0.379394[/C][C]0.810303[/C][/ROW]
[ROW][C]107[/C][C]0.209683[/C][C]0.419365[/C][C]0.790317[/C][/ROW]
[ROW][C]108[/C][C]0.197574[/C][C]0.395147[/C][C]0.802426[/C][/ROW]
[ROW][C]109[/C][C]0.298913[/C][C]0.597826[/C][C]0.701087[/C][/ROW]
[ROW][C]110[/C][C]0.287098[/C][C]0.574197[/C][C]0.712902[/C][/ROW]
[ROW][C]111[/C][C]0.257537[/C][C]0.515075[/C][C]0.742463[/C][/ROW]
[ROW][C]112[/C][C]0.248766[/C][C]0.497531[/C][C]0.751234[/C][/ROW]
[ROW][C]113[/C][C]0.226013[/C][C]0.452026[/C][C]0.773987[/C][/ROW]
[ROW][C]114[/C][C]0.205931[/C][C]0.411861[/C][C]0.794069[/C][/ROW]
[ROW][C]115[/C][C]0.182322[/C][C]0.364644[/C][C]0.817678[/C][/ROW]
[ROW][C]116[/C][C]0.159809[/C][C]0.319619[/C][C]0.840191[/C][/ROW]
[ROW][C]117[/C][C]0.143435[/C][C]0.28687[/C][C]0.856565[/C][/ROW]
[ROW][C]118[/C][C]0.182767[/C][C]0.365534[/C][C]0.817233[/C][/ROW]
[ROW][C]119[/C][C]0.188222[/C][C]0.376443[/C][C]0.811778[/C][/ROW]
[ROW][C]120[/C][C]0.167237[/C][C]0.334473[/C][C]0.832763[/C][/ROW]
[ROW][C]121[/C][C]0.152248[/C][C]0.304495[/C][C]0.847752[/C][/ROW]
[ROW][C]122[/C][C]0.133643[/C][C]0.267286[/C][C]0.866357[/C][/ROW]
[ROW][C]123[/C][C]0.159854[/C][C]0.319708[/C][C]0.840146[/C][/ROW]
[ROW][C]124[/C][C]0.143265[/C][C]0.28653[/C][C]0.856735[/C][/ROW]
[ROW][C]125[/C][C]0.13397[/C][C]0.267941[/C][C]0.86603[/C][/ROW]
[ROW][C]126[/C][C]0.123818[/C][C]0.247636[/C][C]0.876182[/C][/ROW]
[ROW][C]127[/C][C]0.107051[/C][C]0.214103[/C][C]0.892949[/C][/ROW]
[ROW][C]128[/C][C]0.0946237[/C][C]0.189247[/C][C]0.905376[/C][/ROW]
[ROW][C]129[/C][C]0.0806952[/C][C]0.16139[/C][C]0.919305[/C][/ROW]
[ROW][C]130[/C][C]0.0797396[/C][C]0.159479[/C][C]0.92026[/C][/ROW]
[ROW][C]131[/C][C]0.081183[/C][C]0.162366[/C][C]0.918817[/C][/ROW]
[ROW][C]132[/C][C]0.0740215[/C][C]0.148043[/C][C]0.925978[/C][/ROW]
[ROW][C]133[/C][C]0.0672122[/C][C]0.134424[/C][C]0.932788[/C][/ROW]
[ROW][C]134[/C][C]0.0564516[/C][C]0.112903[/C][C]0.943548[/C][/ROW]
[ROW][C]135[/C][C]0.0584503[/C][C]0.116901[/C][C]0.94155[/C][/ROW]
[ROW][C]136[/C][C]0.117404[/C][C]0.234808[/C][C]0.882596[/C][/ROW]
[ROW][C]137[/C][C]0.101138[/C][C]0.202276[/C][C]0.898862[/C][/ROW]
[ROW][C]138[/C][C]0.0891995[/C][C]0.178399[/C][C]0.9108[/C][/ROW]
[ROW][C]139[/C][C]0.0866463[/C][C]0.173293[/C][C]0.913354[/C][/ROW]
[ROW][C]140[/C][C]0.0826864[/C][C]0.165373[/C][C]0.917314[/C][/ROW]
[ROW][C]141[/C][C]0.0961749[/C][C]0.19235[/C][C]0.903825[/C][/ROW]
[ROW][C]142[/C][C]0.0976873[/C][C]0.195375[/C][C]0.902313[/C][/ROW]
[ROW][C]143[/C][C]0.0833377[/C][C]0.166675[/C][C]0.916662[/C][/ROW]
[ROW][C]144[/C][C]0.0702609[/C][C]0.140522[/C][C]0.929739[/C][/ROW]
[ROW][C]145[/C][C]0.0590561[/C][C]0.118112[/C][C]0.940944[/C][/ROW]
[ROW][C]146[/C][C]0.0497476[/C][C]0.0994952[/C][C]0.950252[/C][/ROW]
[ROW][C]147[/C][C]0.0565472[/C][C]0.113094[/C][C]0.943453[/C][/ROW]
[ROW][C]148[/C][C]0.0634491[/C][C]0.126898[/C][C]0.936551[/C][/ROW]
[ROW][C]149[/C][C]0.0594823[/C][C]0.118965[/C][C]0.940518[/C][/ROW]
[ROW][C]150[/C][C]0.0496371[/C][C]0.0992741[/C][C]0.950363[/C][/ROW]
[ROW][C]151[/C][C]0.0618279[/C][C]0.123656[/C][C]0.938172[/C][/ROW]
[ROW][C]152[/C][C]0.0596332[/C][C]0.119266[/C][C]0.940367[/C][/ROW]
[ROW][C]153[/C][C]0.0611925[/C][C]0.122385[/C][C]0.938808[/C][/ROW]
[ROW][C]154[/C][C]0.0631594[/C][C]0.126319[/C][C]0.936841[/C][/ROW]
[ROW][C]155[/C][C]0.0672261[/C][C]0.134452[/C][C]0.932774[/C][/ROW]
[ROW][C]156[/C][C]0.0573027[/C][C]0.114605[/C][C]0.942697[/C][/ROW]
[ROW][C]157[/C][C]0.0479951[/C][C]0.0959902[/C][C]0.952005[/C][/ROW]
[ROW][C]158[/C][C]0.0403855[/C][C]0.080771[/C][C]0.959615[/C][/ROW]
[ROW][C]159[/C][C]0.0557196[/C][C]0.111439[/C][C]0.94428[/C][/ROW]
[ROW][C]160[/C][C]0.0613577[/C][C]0.122715[/C][C]0.938642[/C][/ROW]
[ROW][C]161[/C][C]0.0519124[/C][C]0.103825[/C][C]0.948088[/C][/ROW]
[ROW][C]162[/C][C]0.0907541[/C][C]0.181508[/C][C]0.909246[/C][/ROW]
[ROW][C]163[/C][C]0.0805648[/C][C]0.16113[/C][C]0.919435[/C][/ROW]
[ROW][C]164[/C][C]0.276266[/C][C]0.552532[/C][C]0.723734[/C][/ROW]
[ROW][C]165[/C][C]0.251135[/C][C]0.502271[/C][C]0.748865[/C][/ROW]
[ROW][C]166[/C][C]0.316177[/C][C]0.632354[/C][C]0.683823[/C][/ROW]
[ROW][C]167[/C][C]0.300094[/C][C]0.600188[/C][C]0.699906[/C][/ROW]
[ROW][C]168[/C][C]0.283055[/C][C]0.56611[/C][C]0.716945[/C][/ROW]
[ROW][C]169[/C][C]0.255693[/C][C]0.511387[/C][C]0.744307[/C][/ROW]
[ROW][C]170[/C][C]0.233244[/C][C]0.466488[/C][C]0.766756[/C][/ROW]
[ROW][C]171[/C][C]0.231287[/C][C]0.462574[/C][C]0.768713[/C][/ROW]
[ROW][C]172[/C][C]0.205147[/C][C]0.410294[/C][C]0.794853[/C][/ROW]
[ROW][C]173[/C][C]0.257459[/C][C]0.514918[/C][C]0.742541[/C][/ROW]
[ROW][C]174[/C][C]0.248149[/C][C]0.496299[/C][C]0.751851[/C][/ROW]
[ROW][C]175[/C][C]0.232586[/C][C]0.465172[/C][C]0.767414[/C][/ROW]
[ROW][C]176[/C][C]0.274327[/C][C]0.548654[/C][C]0.725673[/C][/ROW]
[ROW][C]177[/C][C]0.255948[/C][C]0.511895[/C][C]0.744052[/C][/ROW]
[ROW][C]178[/C][C]0.265406[/C][C]0.530812[/C][C]0.734594[/C][/ROW]
[ROW][C]179[/C][C]0.26064[/C][C]0.521281[/C][C]0.73936[/C][/ROW]
[ROW][C]180[/C][C]0.234395[/C][C]0.468789[/C][C]0.765605[/C][/ROW]
[ROW][C]181[/C][C]0.264884[/C][C]0.529768[/C][C]0.735116[/C][/ROW]
[ROW][C]182[/C][C]0.382175[/C][C]0.76435[/C][C]0.617825[/C][/ROW]
[ROW][C]183[/C][C]0.373723[/C][C]0.747447[/C][C]0.626277[/C][/ROW]
[ROW][C]184[/C][C]0.372139[/C][C]0.744278[/C][C]0.627861[/C][/ROW]
[ROW][C]185[/C][C]0.353362[/C][C]0.706725[/C][C]0.646638[/C][/ROW]
[ROW][C]186[/C][C]0.462545[/C][C]0.92509[/C][C]0.537455[/C][/ROW]
[ROW][C]187[/C][C]0.427048[/C][C]0.854096[/C][C]0.572952[/C][/ROW]
[ROW][C]188[/C][C]0.394023[/C][C]0.788045[/C][C]0.605977[/C][/ROW]
[ROW][C]189[/C][C]0.361925[/C][C]0.72385[/C][C]0.638075[/C][/ROW]
[ROW][C]190[/C][C]0.391789[/C][C]0.783579[/C][C]0.608211[/C][/ROW]
[ROW][C]191[/C][C]0.420356[/C][C]0.840712[/C][C]0.579644[/C][/ROW]
[ROW][C]192[/C][C]0.441295[/C][C]0.882591[/C][C]0.558705[/C][/ROW]
[ROW][C]193[/C][C]0.428999[/C][C]0.857998[/C][C]0.571001[/C][/ROW]
[ROW][C]194[/C][C]0.398572[/C][C]0.797143[/C][C]0.601428[/C][/ROW]
[ROW][C]195[/C][C]0.370558[/C][C]0.741116[/C][C]0.629442[/C][/ROW]
[ROW][C]196[/C][C]0.408423[/C][C]0.816846[/C][C]0.591577[/C][/ROW]
[ROW][C]197[/C][C]0.612864[/C][C]0.774272[/C][C]0.387136[/C][/ROW]
[ROW][C]198[/C][C]0.622181[/C][C]0.755638[/C][C]0.377819[/C][/ROW]
[ROW][C]199[/C][C]0.581584[/C][C]0.836832[/C][C]0.418416[/C][/ROW]
[ROW][C]200[/C][C]0.540181[/C][C]0.919637[/C][C]0.459819[/C][/ROW]
[ROW][C]201[/C][C]0.496973[/C][C]0.993945[/C][C]0.503027[/C][/ROW]
[ROW][C]202[/C][C]0.45727[/C][C]0.914539[/C][C]0.54273[/C][/ROW]
[ROW][C]203[/C][C]0.437955[/C][C]0.875909[/C][C]0.562045[/C][/ROW]
[ROW][C]204[/C][C]0.426365[/C][C]0.852731[/C][C]0.573635[/C][/ROW]
[ROW][C]205[/C][C]0.390004[/C][C]0.780009[/C][C]0.609996[/C][/ROW]
[ROW][C]206[/C][C]0.349368[/C][C]0.698737[/C][C]0.650632[/C][/ROW]
[ROW][C]207[/C][C]0.311052[/C][C]0.622105[/C][C]0.688948[/C][/ROW]
[ROW][C]208[/C][C]0.277876[/C][C]0.555752[/C][C]0.722124[/C][/ROW]
[ROW][C]209[/C][C]0.241452[/C][C]0.482905[/C][C]0.758548[/C][/ROW]
[ROW][C]210[/C][C]0.237912[/C][C]0.475824[/C][C]0.762088[/C][/ROW]
[ROW][C]211[/C][C]0.212198[/C][C]0.424396[/C][C]0.787802[/C][/ROW]
[ROW][C]212[/C][C]0.182533[/C][C]0.365066[/C][C]0.817467[/C][/ROW]
[ROW][C]213[/C][C]0.209759[/C][C]0.419518[/C][C]0.790241[/C][/ROW]
[ROW][C]214[/C][C]0.191923[/C][C]0.383847[/C][C]0.808077[/C][/ROW]
[ROW][C]215[/C][C]0.164585[/C][C]0.32917[/C][C]0.835415[/C][/ROW]
[ROW][C]216[/C][C]0.140357[/C][C]0.280714[/C][C]0.859643[/C][/ROW]
[ROW][C]217[/C][C]0.137103[/C][C]0.274206[/C][C]0.862897[/C][/ROW]
[ROW][C]218[/C][C]0.115489[/C][C]0.230977[/C][C]0.884511[/C][/ROW]
[ROW][C]219[/C][C]0.128199[/C][C]0.256399[/C][C]0.871801[/C][/ROW]
[ROW][C]220[/C][C]0.134602[/C][C]0.269204[/C][C]0.865398[/C][/ROW]
[ROW][C]221[/C][C]0.122667[/C][C]0.245334[/C][C]0.877333[/C][/ROW]
[ROW][C]222[/C][C]0.098471[/C][C]0.196942[/C][C]0.901529[/C][/ROW]
[ROW][C]223[/C][C]0.0848353[/C][C]0.169671[/C][C]0.915165[/C][/ROW]
[ROW][C]224[/C][C]0.0782241[/C][C]0.156448[/C][C]0.921776[/C][/ROW]
[ROW][C]225[/C][C]0.0723487[/C][C]0.144697[/C][C]0.927651[/C][/ROW]
[ROW][C]226[/C][C]0.0603143[/C][C]0.120629[/C][C]0.939686[/C][/ROW]
[ROW][C]227[/C][C]0.0458335[/C][C]0.0916669[/C][C]0.954167[/C][/ROW]
[ROW][C]228[/C][C]0.0378269[/C][C]0.0756537[/C][C]0.962173[/C][/ROW]
[ROW][C]229[/C][C]0.0674071[/C][C]0.134814[/C][C]0.932593[/C][/ROW]
[ROW][C]230[/C][C]0.0555037[/C][C]0.111007[/C][C]0.944496[/C][/ROW]
[ROW][C]231[/C][C]0.0426989[/C][C]0.0853978[/C][C]0.957301[/C][/ROW]
[ROW][C]232[/C][C]0.03613[/C][C]0.0722599[/C][C]0.96387[/C][/ROW]
[ROW][C]233[/C][C]0.068926[/C][C]0.137852[/C][C]0.931074[/C][/ROW]
[ROW][C]234[/C][C]0.0747655[/C][C]0.149531[/C][C]0.925234[/C][/ROW]
[ROW][C]235[/C][C]0.0678587[/C][C]0.135717[/C][C]0.932141[/C][/ROW]
[ROW][C]236[/C][C]0.0501872[/C][C]0.100374[/C][C]0.949813[/C][/ROW]
[ROW][C]237[/C][C]0.0700741[/C][C]0.140148[/C][C]0.929926[/C][/ROW]
[ROW][C]238[/C][C]0.0943216[/C][C]0.188643[/C][C]0.905678[/C][/ROW]
[ROW][C]239[/C][C]0.183928[/C][C]0.367857[/C][C]0.816072[/C][/ROW]
[ROW][C]240[/C][C]0.225893[/C][C]0.451785[/C][C]0.774107[/C][/ROW]
[ROW][C]241[/C][C]0.209185[/C][C]0.41837[/C][C]0.790815[/C][/ROW]
[ROW][C]242[/C][C]0.636288[/C][C]0.727425[/C][C]0.363712[/C][/ROW]
[ROW][C]243[/C][C]0.551933[/C][C]0.896135[/C][C]0.448067[/C][/ROW]
[ROW][C]244[/C][C]0.543092[/C][C]0.913816[/C][C]0.456908[/C][/ROW]
[ROW][C]245[/C][C]0.475588[/C][C]0.951176[/C][C]0.524412[/C][/ROW]
[ROW][C]246[/C][C]0.389203[/C][C]0.778406[/C][C]0.610797[/C][/ROW]
[ROW][C]247[/C][C]0.375071[/C][C]0.750143[/C][C]0.624929[/C][/ROW]
[ROW][C]248[/C][C]0.323303[/C][C]0.646605[/C][C]0.676697[/C][/ROW]
[ROW][C]249[/C][C]0.32787[/C][C]0.65574[/C][C]0.67213[/C][/ROW]
[ROW][C]250[/C][C]0.279181[/C][C]0.558362[/C][C]0.720819[/C][/ROW]
[ROW][C]251[/C][C]0.172851[/C][C]0.345702[/C][C]0.827149[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226597&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226597&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.9822780.03544340.0177217
140.9894630.02107440.0105372
150.9787050.042590.021295
160.960160.07967990.0398399
170.9830760.03384840.0169242
180.9742080.05158420.0257921
190.9837090.0325820.016291
200.9731030.05379370.0268968
210.9631880.07362490.0368125
220.9496230.1007550.0503773
230.9324520.1350960.0675481
240.9071220.1857560.0928782
250.880620.2387610.11938
260.8653220.2693570.134678
270.8916790.2166420.108321
280.8672980.2654050.132702
290.9025120.1949760.097488
300.8827890.2344220.117211
310.8694320.2611350.130568
320.8515950.296810.148405
330.814560.3708790.18544
340.7753550.4492890.224645
350.759820.480360.24018
360.7610480.4779040.238952
370.8588420.2823160.141158
380.8260810.3478370.173919
390.7887840.4224310.211216
400.766260.467480.23374
410.7329490.5341010.267051
420.7503060.4993880.249694
430.7560590.4878820.243941
440.7214620.5570770.278538
450.6784120.6431760.321588
460.6355560.7288890.364444
470.6249690.7500620.375031
480.5802810.8394390.419719
490.7287050.542590.271295
500.6909310.6181380.309069
510.6526380.6947240.347362
520.6336840.7326310.366316
530.6627640.6744730.337236
540.6390170.7219670.360983
550.6306890.7386210.369311
560.6935690.6128630.306431
570.6932950.6134110.306705
580.7007110.5985770.299289
590.6930220.6139570.306978
600.6885830.6228330.311417
610.7151540.5696920.284846
620.6784150.643170.321585
630.646060.7078810.35394
640.6077030.7845940.392297
650.5684320.8631350.431568
660.5591290.8817420.440871
670.586090.827820.41391
680.5604420.8791150.439558
690.5198660.9602690.480134
700.4925930.9851870.507407
710.4566330.9132650.543367
720.4258850.8517710.574115
730.3943770.7887550.605623
740.3777250.755450.622275
750.3518340.7036680.648166
760.4906840.9813680.509316
770.4604320.9208640.539568
780.4532730.9065450.546727
790.4145670.8291340.585433
800.5501520.8996960.449848
810.5161380.9677230.483862
820.5499950.9000110.450005
830.5118860.9762290.488114
840.4751640.9503280.524836
850.4367890.8735780.563211
860.4012990.8025970.598701
870.3718320.7436640.628168
880.3384940.6769890.661506
890.41450.8290.5855
900.3812740.7625480.618726
910.3513320.7026630.648668
920.3200520.6401050.679948
930.3131020.6262030.686898
940.2855770.5711530.714423
950.2538330.5076660.746167
960.2359020.4718040.764098
970.217470.4349390.78253
980.191680.3833610.80832
990.1876510.3753020.812349
1000.1639320.3278640.836068
1010.1529210.3058430.847079
1020.1366210.2732430.863379
1030.1831110.3662220.816889
1040.2113880.4227750.788612
1050.2151730.4303460.784827
1060.1896970.3793940.810303
1070.2096830.4193650.790317
1080.1975740.3951470.802426
1090.2989130.5978260.701087
1100.2870980.5741970.712902
1110.2575370.5150750.742463
1120.2487660.4975310.751234
1130.2260130.4520260.773987
1140.2059310.4118610.794069
1150.1823220.3646440.817678
1160.1598090.3196190.840191
1170.1434350.286870.856565
1180.1827670.3655340.817233
1190.1882220.3764430.811778
1200.1672370.3344730.832763
1210.1522480.3044950.847752
1220.1336430.2672860.866357
1230.1598540.3197080.840146
1240.1432650.286530.856735
1250.133970.2679410.86603
1260.1238180.2476360.876182
1270.1070510.2141030.892949
1280.09462370.1892470.905376
1290.08069520.161390.919305
1300.07973960.1594790.92026
1310.0811830.1623660.918817
1320.07402150.1480430.925978
1330.06721220.1344240.932788
1340.05645160.1129030.943548
1350.05845030.1169010.94155
1360.1174040.2348080.882596
1370.1011380.2022760.898862
1380.08919950.1783990.9108
1390.08664630.1732930.913354
1400.08268640.1653730.917314
1410.09617490.192350.903825
1420.09768730.1953750.902313
1430.08333770.1666750.916662
1440.07026090.1405220.929739
1450.05905610.1181120.940944
1460.04974760.09949520.950252
1470.05654720.1130940.943453
1480.06344910.1268980.936551
1490.05948230.1189650.940518
1500.04963710.09927410.950363
1510.06182790.1236560.938172
1520.05963320.1192660.940367
1530.06119250.1223850.938808
1540.06315940.1263190.936841
1550.06722610.1344520.932774
1560.05730270.1146050.942697
1570.04799510.09599020.952005
1580.04038550.0807710.959615
1590.05571960.1114390.94428
1600.06135770.1227150.938642
1610.05191240.1038250.948088
1620.09075410.1815080.909246
1630.08056480.161130.919435
1640.2762660.5525320.723734
1650.2511350.5022710.748865
1660.3161770.6323540.683823
1670.3000940.6001880.699906
1680.2830550.566110.716945
1690.2556930.5113870.744307
1700.2332440.4664880.766756
1710.2312870.4625740.768713
1720.2051470.4102940.794853
1730.2574590.5149180.742541
1740.2481490.4962990.751851
1750.2325860.4651720.767414
1760.2743270.5486540.725673
1770.2559480.5118950.744052
1780.2654060.5308120.734594
1790.260640.5212810.73936
1800.2343950.4687890.765605
1810.2648840.5297680.735116
1820.3821750.764350.617825
1830.3737230.7474470.626277
1840.3721390.7442780.627861
1850.3533620.7067250.646638
1860.4625450.925090.537455
1870.4270480.8540960.572952
1880.3940230.7880450.605977
1890.3619250.723850.638075
1900.3917890.7835790.608211
1910.4203560.8407120.579644
1920.4412950.8825910.558705
1930.4289990.8579980.571001
1940.3985720.7971430.601428
1950.3705580.7411160.629442
1960.4084230.8168460.591577
1970.6128640.7742720.387136
1980.6221810.7556380.377819
1990.5815840.8368320.418416
2000.5401810.9196370.459819
2010.4969730.9939450.503027
2020.457270.9145390.54273
2030.4379550.8759090.562045
2040.4263650.8527310.573635
2050.3900040.7800090.609996
2060.3493680.6987370.650632
2070.3110520.6221050.688948
2080.2778760.5557520.722124
2090.2414520.4829050.758548
2100.2379120.4758240.762088
2110.2121980.4243960.787802
2120.1825330.3650660.817467
2130.2097590.4195180.790241
2140.1919230.3838470.808077
2150.1645850.329170.835415
2160.1403570.2807140.859643
2170.1371030.2742060.862897
2180.1154890.2309770.884511
2190.1281990.2563990.871801
2200.1346020.2692040.865398
2210.1226670.2453340.877333
2220.0984710.1969420.901529
2230.08483530.1696710.915165
2240.07822410.1564480.921776
2250.07234870.1446970.927651
2260.06031430.1206290.939686
2270.04583350.09166690.954167
2280.03782690.07565370.962173
2290.06740710.1348140.932593
2300.05550370.1110070.944496
2310.04269890.08539780.957301
2320.036130.07225990.96387
2330.0689260.1378520.931074
2340.07476550.1495310.925234
2350.06785870.1357170.932141
2360.05018720.1003740.949813
2370.07007410.1401480.929926
2380.09432160.1886430.905678
2390.1839280.3678570.816072
2400.2258930.4517850.774107
2410.2091850.418370.790815
2420.6362880.7274250.363712
2430.5519330.8961350.448067
2440.5430920.9138160.456908
2450.4755880.9511760.524412
2460.3892030.7784060.610797
2470.3750710.7501430.624929
2480.3233030.6466050.676697
2490.327870.655740.67213
2500.2791810.5583620.720819
2510.1728510.3457020.827149






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level50.0209205OK
10% type I error level170.0711297OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 5 & 0.0209205 & OK \tabularnewline
10% type I error level & 17 & 0.0711297 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226597&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]5[/C][C]0.0209205[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]17[/C][C]0.0711297[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226597&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226597&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level50.0209205OK
10% type I error level170.0711297OK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}