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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 computationSat, 02 Nov 2013 17:02:57 -0400
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/02/t1383426224xz6tpmjjlnjiqn5.htm/, Retrieved Tue, 14 May 2024 01:26:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221816, Retrieved Tue, 14 May 2024 01:26:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [WORKSHOP 7 ] [2013-11-02 19:41:02] [69bf0eb8b9b38defaaf4848d8c317571]
-   PD    [Multiple Regression] [w7] [2013-11-02 21:02:57] [4c6743e926d608f4adf2160fecf92c6f] [Current]
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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 time22 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 22 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221816&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]22 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221816&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221816&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 time22 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 8.39956 + 0.0298601Connected[t] + 0.047894Separate[t] + 0.564804Software[t] + 0.0848059Happiness[t] -0.02627Depression[t] + 0.035671Sport1[t] -0.0469853Sport2[t] -0.404736Month[t] + 0.267616M1[t] + 0.305546M2[t] + 0.528643M3[t] + 0.481157M4[t] -0.0950095M5[t] + 0.224825M6[t] + 0.431912M7[t] -0.28801M8[t] -0.0135655M9[t] -0.16161M10[t] -0.327338M11[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  8.39956 +  0.0298601Connected[t] +  0.047894Separate[t] +  0.564804Software[t] +  0.0848059Happiness[t] -0.02627Depression[t] +  0.035671Sport1[t] -0.0469853Sport2[t] -0.404736Month[t] +  0.267616M1[t] +  0.305546M2[t] +  0.528643M3[t] +  0.481157M4[t] -0.0950095M5[t] +  0.224825M6[t] +  0.431912M7[t] -0.28801M8[t] -0.0135655M9[t] -0.16161M10[t] -0.327338M11[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221816&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  8.39956 +  0.0298601Connected[t] +  0.047894Separate[t] +  0.564804Software[t] +  0.0848059Happiness[t] -0.02627Depression[t] +  0.035671Sport1[t] -0.0469853Sport2[t] -0.404736Month[t] +  0.267616M1[t] +  0.305546M2[t] +  0.528643M3[t] +  0.481157M4[t] -0.0950095M5[t] +  0.224825M6[t] +  0.431912M7[t] -0.28801M8[t] -0.0135655M9[t] -0.16161M10[t] -0.327338M11[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221816&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221816&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
Learning[t] = + 8.39956 + 0.0298601Connected[t] + 0.047894Separate[t] + 0.564804Software[t] + 0.0848059Happiness[t] -0.02627Depression[t] + 0.035671Sport1[t] -0.0469853Sport2[t] -0.404736Month[t] + 0.267616M1[t] + 0.305546M2[t] + 0.528643M3[t] + 0.481157M4[t] -0.0950095M5[t] + 0.224825M6[t] + 0.431912M7[t] -0.28801M8[t] -0.0135655M9[t] -0.16161M10[t] -0.327338M11[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.399562.699653.1110.002084030.00104201
Connected0.02986010.03641810.81990.4130590.20653
Separate0.0478940.0362281.3220.1874010.0937007
Software0.5648040.054714810.325.79849e-212.89925e-21
Happiness0.08480590.05896021.4380.1516140.075807
Depression-0.026270.0441143-0.59550.5520620.276031
Sport10.0356710.03865590.92280.3570310.178516
Sport2-0.04698530.0574565-0.81780.4142950.207148
Month-0.4047360.162482-2.4910.01340590.00670293
M10.2676160.5788050.46240.6442350.322118
M20.3055460.5771870.52940.5970290.298515
M30.5286430.5751690.91910.3589460.179473
M40.4811570.5727710.84010.4017010.200851
M5-0.09500950.579414-0.1640.8698860.434943
M60.2248250.5836840.38520.7004380.350219
M70.4319120.5748460.75140.4531640.226582
M8-0.288010.572037-0.50350.615080.30754
M9-0.01356550.571728-0.023730.981090.490545
M10-0.161610.576083-0.28050.7793060.389653
M11-0.3273380.571969-0.57230.5676450.283822

\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) & 8.39956 & 2.69965 & 3.111 & 0.00208403 & 0.00104201 \tabularnewline
Connected & 0.0298601 & 0.0364181 & 0.8199 & 0.413059 & 0.20653 \tabularnewline
Separate & 0.047894 & 0.036228 & 1.322 & 0.187401 & 0.0937007 \tabularnewline
Software & 0.564804 & 0.0547148 & 10.32 & 5.79849e-21 & 2.89925e-21 \tabularnewline
Happiness & 0.0848059 & 0.0589602 & 1.438 & 0.151614 & 0.075807 \tabularnewline
Depression & -0.02627 & 0.0441143 & -0.5955 & 0.552062 & 0.276031 \tabularnewline
Sport1 & 0.035671 & 0.0386559 & 0.9228 & 0.357031 & 0.178516 \tabularnewline
Sport2 & -0.0469853 & 0.0574565 & -0.8178 & 0.414295 & 0.207148 \tabularnewline
Month & -0.404736 & 0.162482 & -2.491 & 0.0134059 & 0.00670293 \tabularnewline
M1 & 0.267616 & 0.578805 & 0.4624 & 0.644235 & 0.322118 \tabularnewline
M2 & 0.305546 & 0.577187 & 0.5294 & 0.597029 & 0.298515 \tabularnewline
M3 & 0.528643 & 0.575169 & 0.9191 & 0.358946 & 0.179473 \tabularnewline
M4 & 0.481157 & 0.572771 & 0.8401 & 0.401701 & 0.200851 \tabularnewline
M5 & -0.0950095 & 0.579414 & -0.164 & 0.869886 & 0.434943 \tabularnewline
M6 & 0.224825 & 0.583684 & 0.3852 & 0.700438 & 0.350219 \tabularnewline
M7 & 0.431912 & 0.574846 & 0.7514 & 0.453164 & 0.226582 \tabularnewline
M8 & -0.28801 & 0.572037 & -0.5035 & 0.61508 & 0.30754 \tabularnewline
M9 & -0.0135655 & 0.571728 & -0.02373 & 0.98109 & 0.490545 \tabularnewline
M10 & -0.16161 & 0.576083 & -0.2805 & 0.779306 & 0.389653 \tabularnewline
M11 & -0.327338 & 0.571969 & -0.5723 & 0.567645 & 0.283822 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221816&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]8.39956[/C][C]2.69965[/C][C]3.111[/C][C]0.00208403[/C][C]0.00104201[/C][/ROW]
[ROW][C]Connected[/C][C]0.0298601[/C][C]0.0364181[/C][C]0.8199[/C][C]0.413059[/C][C]0.20653[/C][/ROW]
[ROW][C]Separate[/C][C]0.047894[/C][C]0.036228[/C][C]1.322[/C][C]0.187401[/C][C]0.0937007[/C][/ROW]
[ROW][C]Software[/C][C]0.564804[/C][C]0.0547148[/C][C]10.32[/C][C]5.79849e-21[/C][C]2.89925e-21[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0848059[/C][C]0.0589602[/C][C]1.438[/C][C]0.151614[/C][C]0.075807[/C][/ROW]
[ROW][C]Depression[/C][C]-0.02627[/C][C]0.0441143[/C][C]-0.5955[/C][C]0.552062[/C][C]0.276031[/C][/ROW]
[ROW][C]Sport1[/C][C]0.035671[/C][C]0.0386559[/C][C]0.9228[/C][C]0.357031[/C][C]0.178516[/C][/ROW]
[ROW][C]Sport2[/C][C]-0.0469853[/C][C]0.0574565[/C][C]-0.8178[/C][C]0.414295[/C][C]0.207148[/C][/ROW]
[ROW][C]Month[/C][C]-0.404736[/C][C]0.162482[/C][C]-2.491[/C][C]0.0134059[/C][C]0.00670293[/C][/ROW]
[ROW][C]M1[/C][C]0.267616[/C][C]0.578805[/C][C]0.4624[/C][C]0.644235[/C][C]0.322118[/C][/ROW]
[ROW][C]M2[/C][C]0.305546[/C][C]0.577187[/C][C]0.5294[/C][C]0.597029[/C][C]0.298515[/C][/ROW]
[ROW][C]M3[/C][C]0.528643[/C][C]0.575169[/C][C]0.9191[/C][C]0.358946[/C][C]0.179473[/C][/ROW]
[ROW][C]M4[/C][C]0.481157[/C][C]0.572771[/C][C]0.8401[/C][C]0.401701[/C][C]0.200851[/C][/ROW]
[ROW][C]M5[/C][C]-0.0950095[/C][C]0.579414[/C][C]-0.164[/C][C]0.869886[/C][C]0.434943[/C][/ROW]
[ROW][C]M6[/C][C]0.224825[/C][C]0.583684[/C][C]0.3852[/C][C]0.700438[/C][C]0.350219[/C][/ROW]
[ROW][C]M7[/C][C]0.431912[/C][C]0.574846[/C][C]0.7514[/C][C]0.453164[/C][C]0.226582[/C][/ROW]
[ROW][C]M8[/C][C]-0.28801[/C][C]0.572037[/C][C]-0.5035[/C][C]0.61508[/C][C]0.30754[/C][/ROW]
[ROW][C]M9[/C][C]-0.0135655[/C][C]0.571728[/C][C]-0.02373[/C][C]0.98109[/C][C]0.490545[/C][/ROW]
[ROW][C]M10[/C][C]-0.16161[/C][C]0.576083[/C][C]-0.2805[/C][C]0.779306[/C][C]0.389653[/C][/ROW]
[ROW][C]M11[/C][C]-0.327338[/C][C]0.571969[/C][C]-0.5723[/C][C]0.567645[/C][C]0.283822[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221816&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221816&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)8.399562.699653.1110.002084030.00104201
Connected0.02986010.03641810.81990.4130590.20653
Separate0.0478940.0362281.3220.1874010.0937007
Software0.5648040.054714810.325.79849e-212.89925e-21
Happiness0.08480590.05896021.4380.1516140.075807
Depression-0.026270.0441143-0.59550.5520620.276031
Sport10.0356710.03865590.92280.3570310.178516
Sport2-0.04698530.0574565-0.81780.4142950.207148
Month-0.4047360.162482-2.4910.01340590.00670293
M10.2676160.5788050.46240.6442350.322118
M20.3055460.5771870.52940.5970290.298515
M30.5286430.5751690.91910.3589460.179473
M40.4811570.5727710.84010.4017010.200851
M5-0.09500950.579414-0.1640.8698860.434943
M60.2248250.5836840.38520.7004380.350219
M70.4319120.5748460.75140.4531640.226582
M8-0.288010.572037-0.50350.615080.30754
M9-0.01356550.571728-0.023730.981090.490545
M10-0.161610.576083-0.28050.7793060.389653
M11-0.3273380.571969-0.57230.5676450.283822






Multiple Linear Regression - Regression Statistics
Multiple R0.674036
R-squared0.454324
Adjusted R-squared0.411833
F-TEST (value)10.6922
F-TEST (DF numerator)19
F-TEST (DF denominator)244
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.88354
Sum Squared Residuals865.64

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.674036 \tabularnewline
R-squared & 0.454324 \tabularnewline
Adjusted R-squared & 0.411833 \tabularnewline
F-TEST (value) & 10.6922 \tabularnewline
F-TEST (DF numerator) & 19 \tabularnewline
F-TEST (DF denominator) & 244 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.88354 \tabularnewline
Sum Squared Residuals & 865.64 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221816&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.674036[/C][/ROW]
[ROW][C]R-squared[/C][C]0.454324[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.411833[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]10.6922[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]19[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]244[/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]1.88354[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]865.64[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221816&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221816&T=3

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

Multiple Linear Regression - Regression Statistics
Multiple R0.674036
R-squared0.454324
Adjusted R-squared0.411833
F-TEST (value)10.6922
F-TEST (DF numerator)19
F-TEST (DF denominator)244
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.88354
Sum Squared Residuals865.64






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.1055-3.10552
21615.77450.225535
31917.27571.72427
41512.29912.70092
51416.1466-2.1466
61314.8491-1.84913
71915.37723.62279
81516.5653-1.56533
91415.807-1.80698
101514.03660.96337
111614.39181.60823
121616.0148-0.0148222
131615.48380.516235
141615.62470.375317
151718.3921-1.39207
161515.7487-0.748724
171514.2980.701965
182016.46863.53136
191815.66732.33266
201615.09190.908127
211615.19710.802923
221614.70671.29328
231916.00432.99567
241614.85151.14851
251716.27660.723439
261716.3340.665992
271615.44340.556567
281517.09-2.09
291615.57780.422224
301414.1395-0.139512
311516.0487-1.04875
321212.4103-0.410341
331414.6722-0.672229
341615.60260.397421
351415.1714-1.17136
361012.8586-2.85862
371013.2051-3.20512
381415.9647-1.96473
391615.0130.987043
401614.83941.16056
411614.50841.49162
421415.9522-1.95225
432017.85072.14934
441413.79080.209183
451414.3382-0.338169
461115.2917-4.29167
471416.1085-2.10851
481515.0807-0.0806867
491615.84630.153739
501415.8819-1.88192
511617.5635-1.56349
521414.6085-0.608532
531214.9444-2.94443
541615.85960.140395
55911.7855-2.78551
561412.03271.96727
571615.85470.145334
581615.31960.680447
591514.810.189957
601614.17871.82129
611211.75510.244897
621616.0228-0.0227832
631617.1004-1.10039
641415.2707-1.27075
651615.24580.754163
661715.84721.15284
671816.30981.69019
681813.8464.154
691215.589-3.589
701615.17770.822348
711012.5705-2.57055
721414.6493-0.64925
731816.97481.02517
741817.25460.745376
751615.42750.572513
761713.58793.41209
771616.0533-0.0533448
781614.33971.66033
791315.3515-2.3515
801614.48161.51843
811615.46570.534338
821615.23940.760612
831515.1131-0.113113
841514.60680.393221
851614.12211.87791
861414.2351-0.235105
871615.63220.367762
881615.09370.90629
891514.0930.906965
901213.853-1.85297
911716.94790.0521022
921615.36650.633475
931514.87580.124193
941314.6905-1.69048
951614.27491.72507
961615.51410.485944
971613.75222.2478
981615.95540.0445906
991414.7677-0.767659
1001617.3751-1.37515
1011614.33821.66185
1022017.52662.47341
1031514.31830.681682
1041614.59181.40824
1051314.6067-1.60666
1061715.34981.65017
1071615.25870.741311
1081614.1461.85397
1091212.3179-0.317869
1101615.45270.54729
1111616.4054-0.405389
1121715.33381.66625
1131314.638-1.63796
1141214.6722-2.67225
1151816.43571.56432
1161415.503-1.50301
1171412.95651.04355
1181314.5039-1.50388
1191615.08080.919183
1201314.3219-1.32185
1211615.55030.449747
1221316.0586-3.05858
1231617.2775-1.27752
1241516.2083-1.20826
1251616.6586-0.658631
1261514.780.220036
1271715.931.07002
1281513.57851.42153
1291214.6086-2.60863
1301613.74742.25257
1311013.3191-3.31913
1321613.43192.56815
1331214.393-2.39295
1341415.7954-1.79538
1351515.5339-0.533878
1361312.51070.489274
1371514.2550.745031
1381113.5915-2.59146
1391213.3627-1.3627
1401113.0715-2.07152
1411612.82613.1739
1421513.53091.46906
1431716.51860.481449
1441614.13451.86553
1451013.4758-3.47583
1461815.79322.20679
1471315.4038-2.40382
1481615.2940.706047
1491312.62490.375072
1501013.1167-3.11668
1511516.4184-1.41836
1521613.70942.29064
1531611.84384.15618
1541412.58191.4181
1551012.0291-2.0291
1561716.5160.484014
1571311.99671.00332
1581514.1720.82797
1591615.10770.892292
1601213.3192-1.3192
1611312.49720.502811
1621312.42330.576699
1631212.5693-0.569269
1641715.68921.31084
1651513.38821.6118
1661011.1621-1.16213
1671413.70840.29163
1681113.921-2.92103
1691314.7466-1.74664
1701614.57691.42305
1711210.66151.33846
1721615.59590.404067
1731213.4231-1.4231
174911.3052-2.30521
1751215.0894-3.08937
1761514.08520.914849
1771211.88590.114143
1781212.2814-0.281433
1791413.23630.763695
1801213.1688-1.16883
1811615.06590.934084
1821111.4534-0.453372
1831917.01081.98924
1841515.3965-0.396538
185814.2865-6.28652
1861614.87661.12336
1871714.73442.26562
1881211.87930.120662
1891111.316-0.316021
1901110.01430.985713
1911414.5075-0.507503
1921615.30810.691881
193129.811482.18852
1941614.08081.91921
1951314.0176-1.01755
1961515.2631-0.263121
1971612.68653.31348
1981615.11380.886205
1991412.6811.31903
2001614.18641.81364
2011613.75482.24521
2021413.12610.8739
2031113.058-2.058
2041214.2894-2.28942
2051512.87842.12164
2061514.66120.338816
2071614.8261.17397
2081615.33680.663243
2091113.3203-2.32028
2101514.10480.895164
2111214.473-2.47297
2121215.3428-3.34278
2131513.99631.00368
2141511.7553.24502
2151614.1161.884
2161412.95171.04826
2171714.83112.16886
2181414.0835-0.0834989
2191312.33080.669232
2201515.5352-0.535203
2211314.423-1.42301
2221414.3332-0.333232
2231514.57750.422548
2241212.7376-0.737586
2251312.80680.193188
226811.5696-3.5696
2271413.42450.575494
2281412.99671.00331
2291112.3492-1.34921
2301213.0957-1.09575
2311311.70131.29868
2321013.5476-3.54756
2331611.23834.76169
2341815.94722.05281
2351314.1967-1.1967
2361112.9089-1.90887
237410.7972-6.79719
2381313.9256-0.925613
2391613.85552.14453
2401011.5613-1.56133
2411212.4761-0.47615
2421213.6596-1.65964
243109.369430.630575
2441311.51531.48472
2451513.42921.57085
2461212.1283-0.128343
2471413.20810.791879
2481012.1403-2.14029
2491210.65421.34578
2501211.53240.467605
2511111.5557-0.555717
2521011.649-1.64901
2531211.58610.413934
2541613.06922.93081
2551213.7388-1.73884
2561414.2304-0.230429
2571614.31381.68617
2581411.77162.22842
2591314.667-1.66705
26048.99115-4.99115
2611513.75931.24066
2621114.8548-3.8548
2631110.88720.112774
2641412.84921.15075

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.1055 & -3.10552 \tabularnewline
2 & 16 & 15.7745 & 0.225535 \tabularnewline
3 & 19 & 17.2757 & 1.72427 \tabularnewline
4 & 15 & 12.2991 & 2.70092 \tabularnewline
5 & 14 & 16.1466 & -2.1466 \tabularnewline
6 & 13 & 14.8491 & -1.84913 \tabularnewline
7 & 19 & 15.3772 & 3.62279 \tabularnewline
8 & 15 & 16.5653 & -1.56533 \tabularnewline
9 & 14 & 15.807 & -1.80698 \tabularnewline
10 & 15 & 14.0366 & 0.96337 \tabularnewline
11 & 16 & 14.3918 & 1.60823 \tabularnewline
12 & 16 & 16.0148 & -0.0148222 \tabularnewline
13 & 16 & 15.4838 & 0.516235 \tabularnewline
14 & 16 & 15.6247 & 0.375317 \tabularnewline
15 & 17 & 18.3921 & -1.39207 \tabularnewline
16 & 15 & 15.7487 & -0.748724 \tabularnewline
17 & 15 & 14.298 & 0.701965 \tabularnewline
18 & 20 & 16.4686 & 3.53136 \tabularnewline
19 & 18 & 15.6673 & 2.33266 \tabularnewline
20 & 16 & 15.0919 & 0.908127 \tabularnewline
21 & 16 & 15.1971 & 0.802923 \tabularnewline
22 & 16 & 14.7067 & 1.29328 \tabularnewline
23 & 19 & 16.0043 & 2.99567 \tabularnewline
24 & 16 & 14.8515 & 1.14851 \tabularnewline
25 & 17 & 16.2766 & 0.723439 \tabularnewline
26 & 17 & 16.334 & 0.665992 \tabularnewline
27 & 16 & 15.4434 & 0.556567 \tabularnewline
28 & 15 & 17.09 & -2.09 \tabularnewline
29 & 16 & 15.5778 & 0.422224 \tabularnewline
30 & 14 & 14.1395 & -0.139512 \tabularnewline
31 & 15 & 16.0487 & -1.04875 \tabularnewline
32 & 12 & 12.4103 & -0.410341 \tabularnewline
33 & 14 & 14.6722 & -0.672229 \tabularnewline
34 & 16 & 15.6026 & 0.397421 \tabularnewline
35 & 14 & 15.1714 & -1.17136 \tabularnewline
36 & 10 & 12.8586 & -2.85862 \tabularnewline
37 & 10 & 13.2051 & -3.20512 \tabularnewline
38 & 14 & 15.9647 & -1.96473 \tabularnewline
39 & 16 & 15.013 & 0.987043 \tabularnewline
40 & 16 & 14.8394 & 1.16056 \tabularnewline
41 & 16 & 14.5084 & 1.49162 \tabularnewline
42 & 14 & 15.9522 & -1.95225 \tabularnewline
43 & 20 & 17.8507 & 2.14934 \tabularnewline
44 & 14 & 13.7908 & 0.209183 \tabularnewline
45 & 14 & 14.3382 & -0.338169 \tabularnewline
46 & 11 & 15.2917 & -4.29167 \tabularnewline
47 & 14 & 16.1085 & -2.10851 \tabularnewline
48 & 15 & 15.0807 & -0.0806867 \tabularnewline
49 & 16 & 15.8463 & 0.153739 \tabularnewline
50 & 14 & 15.8819 & -1.88192 \tabularnewline
51 & 16 & 17.5635 & -1.56349 \tabularnewline
52 & 14 & 14.6085 & -0.608532 \tabularnewline
53 & 12 & 14.9444 & -2.94443 \tabularnewline
54 & 16 & 15.8596 & 0.140395 \tabularnewline
55 & 9 & 11.7855 & -2.78551 \tabularnewline
56 & 14 & 12.0327 & 1.96727 \tabularnewline
57 & 16 & 15.8547 & 0.145334 \tabularnewline
58 & 16 & 15.3196 & 0.680447 \tabularnewline
59 & 15 & 14.81 & 0.189957 \tabularnewline
60 & 16 & 14.1787 & 1.82129 \tabularnewline
61 & 12 & 11.7551 & 0.244897 \tabularnewline
62 & 16 & 16.0228 & -0.0227832 \tabularnewline
63 & 16 & 17.1004 & -1.10039 \tabularnewline
64 & 14 & 15.2707 & -1.27075 \tabularnewline
65 & 16 & 15.2458 & 0.754163 \tabularnewline
66 & 17 & 15.8472 & 1.15284 \tabularnewline
67 & 18 & 16.3098 & 1.69019 \tabularnewline
68 & 18 & 13.846 & 4.154 \tabularnewline
69 & 12 & 15.589 & -3.589 \tabularnewline
70 & 16 & 15.1777 & 0.822348 \tabularnewline
71 & 10 & 12.5705 & -2.57055 \tabularnewline
72 & 14 & 14.6493 & -0.64925 \tabularnewline
73 & 18 & 16.9748 & 1.02517 \tabularnewline
74 & 18 & 17.2546 & 0.745376 \tabularnewline
75 & 16 & 15.4275 & 0.572513 \tabularnewline
76 & 17 & 13.5879 & 3.41209 \tabularnewline
77 & 16 & 16.0533 & -0.0533448 \tabularnewline
78 & 16 & 14.3397 & 1.66033 \tabularnewline
79 & 13 & 15.3515 & -2.3515 \tabularnewline
80 & 16 & 14.4816 & 1.51843 \tabularnewline
81 & 16 & 15.4657 & 0.534338 \tabularnewline
82 & 16 & 15.2394 & 0.760612 \tabularnewline
83 & 15 & 15.1131 & -0.113113 \tabularnewline
84 & 15 & 14.6068 & 0.393221 \tabularnewline
85 & 16 & 14.1221 & 1.87791 \tabularnewline
86 & 14 & 14.2351 & -0.235105 \tabularnewline
87 & 16 & 15.6322 & 0.367762 \tabularnewline
88 & 16 & 15.0937 & 0.90629 \tabularnewline
89 & 15 & 14.093 & 0.906965 \tabularnewline
90 & 12 & 13.853 & -1.85297 \tabularnewline
91 & 17 & 16.9479 & 0.0521022 \tabularnewline
92 & 16 & 15.3665 & 0.633475 \tabularnewline
93 & 15 & 14.8758 & 0.124193 \tabularnewline
94 & 13 & 14.6905 & -1.69048 \tabularnewline
95 & 16 & 14.2749 & 1.72507 \tabularnewline
96 & 16 & 15.5141 & 0.485944 \tabularnewline
97 & 16 & 13.7522 & 2.2478 \tabularnewline
98 & 16 & 15.9554 & 0.0445906 \tabularnewline
99 & 14 & 14.7677 & -0.767659 \tabularnewline
100 & 16 & 17.3751 & -1.37515 \tabularnewline
101 & 16 & 14.3382 & 1.66185 \tabularnewline
102 & 20 & 17.5266 & 2.47341 \tabularnewline
103 & 15 & 14.3183 & 0.681682 \tabularnewline
104 & 16 & 14.5918 & 1.40824 \tabularnewline
105 & 13 & 14.6067 & -1.60666 \tabularnewline
106 & 17 & 15.3498 & 1.65017 \tabularnewline
107 & 16 & 15.2587 & 0.741311 \tabularnewline
108 & 16 & 14.146 & 1.85397 \tabularnewline
109 & 12 & 12.3179 & -0.317869 \tabularnewline
110 & 16 & 15.4527 & 0.54729 \tabularnewline
111 & 16 & 16.4054 & -0.405389 \tabularnewline
112 & 17 & 15.3338 & 1.66625 \tabularnewline
113 & 13 & 14.638 & -1.63796 \tabularnewline
114 & 12 & 14.6722 & -2.67225 \tabularnewline
115 & 18 & 16.4357 & 1.56432 \tabularnewline
116 & 14 & 15.503 & -1.50301 \tabularnewline
117 & 14 & 12.9565 & 1.04355 \tabularnewline
118 & 13 & 14.5039 & -1.50388 \tabularnewline
119 & 16 & 15.0808 & 0.919183 \tabularnewline
120 & 13 & 14.3219 & -1.32185 \tabularnewline
121 & 16 & 15.5503 & 0.449747 \tabularnewline
122 & 13 & 16.0586 & -3.05858 \tabularnewline
123 & 16 & 17.2775 & -1.27752 \tabularnewline
124 & 15 & 16.2083 & -1.20826 \tabularnewline
125 & 16 & 16.6586 & -0.658631 \tabularnewline
126 & 15 & 14.78 & 0.220036 \tabularnewline
127 & 17 & 15.93 & 1.07002 \tabularnewline
128 & 15 & 13.5785 & 1.42153 \tabularnewline
129 & 12 & 14.6086 & -2.60863 \tabularnewline
130 & 16 & 13.7474 & 2.25257 \tabularnewline
131 & 10 & 13.3191 & -3.31913 \tabularnewline
132 & 16 & 13.4319 & 2.56815 \tabularnewline
133 & 12 & 14.393 & -2.39295 \tabularnewline
134 & 14 & 15.7954 & -1.79538 \tabularnewline
135 & 15 & 15.5339 & -0.533878 \tabularnewline
136 & 13 & 12.5107 & 0.489274 \tabularnewline
137 & 15 & 14.255 & 0.745031 \tabularnewline
138 & 11 & 13.5915 & -2.59146 \tabularnewline
139 & 12 & 13.3627 & -1.3627 \tabularnewline
140 & 11 & 13.0715 & -2.07152 \tabularnewline
141 & 16 & 12.8261 & 3.1739 \tabularnewline
142 & 15 & 13.5309 & 1.46906 \tabularnewline
143 & 17 & 16.5186 & 0.481449 \tabularnewline
144 & 16 & 14.1345 & 1.86553 \tabularnewline
145 & 10 & 13.4758 & -3.47583 \tabularnewline
146 & 18 & 15.7932 & 2.20679 \tabularnewline
147 & 13 & 15.4038 & -2.40382 \tabularnewline
148 & 16 & 15.294 & 0.706047 \tabularnewline
149 & 13 & 12.6249 & 0.375072 \tabularnewline
150 & 10 & 13.1167 & -3.11668 \tabularnewline
151 & 15 & 16.4184 & -1.41836 \tabularnewline
152 & 16 & 13.7094 & 2.29064 \tabularnewline
153 & 16 & 11.8438 & 4.15618 \tabularnewline
154 & 14 & 12.5819 & 1.4181 \tabularnewline
155 & 10 & 12.0291 & -2.0291 \tabularnewline
156 & 17 & 16.516 & 0.484014 \tabularnewline
157 & 13 & 11.9967 & 1.00332 \tabularnewline
158 & 15 & 14.172 & 0.82797 \tabularnewline
159 & 16 & 15.1077 & 0.892292 \tabularnewline
160 & 12 & 13.3192 & -1.3192 \tabularnewline
161 & 13 & 12.4972 & 0.502811 \tabularnewline
162 & 13 & 12.4233 & 0.576699 \tabularnewline
163 & 12 & 12.5693 & -0.569269 \tabularnewline
164 & 17 & 15.6892 & 1.31084 \tabularnewline
165 & 15 & 13.3882 & 1.6118 \tabularnewline
166 & 10 & 11.1621 & -1.16213 \tabularnewline
167 & 14 & 13.7084 & 0.29163 \tabularnewline
168 & 11 & 13.921 & -2.92103 \tabularnewline
169 & 13 & 14.7466 & -1.74664 \tabularnewline
170 & 16 & 14.5769 & 1.42305 \tabularnewline
171 & 12 & 10.6615 & 1.33846 \tabularnewline
172 & 16 & 15.5959 & 0.404067 \tabularnewline
173 & 12 & 13.4231 & -1.4231 \tabularnewline
174 & 9 & 11.3052 & -2.30521 \tabularnewline
175 & 12 & 15.0894 & -3.08937 \tabularnewline
176 & 15 & 14.0852 & 0.914849 \tabularnewline
177 & 12 & 11.8859 & 0.114143 \tabularnewline
178 & 12 & 12.2814 & -0.281433 \tabularnewline
179 & 14 & 13.2363 & 0.763695 \tabularnewline
180 & 12 & 13.1688 & -1.16883 \tabularnewline
181 & 16 & 15.0659 & 0.934084 \tabularnewline
182 & 11 & 11.4534 & -0.453372 \tabularnewline
183 & 19 & 17.0108 & 1.98924 \tabularnewline
184 & 15 & 15.3965 & -0.396538 \tabularnewline
185 & 8 & 14.2865 & -6.28652 \tabularnewline
186 & 16 & 14.8766 & 1.12336 \tabularnewline
187 & 17 & 14.7344 & 2.26562 \tabularnewline
188 & 12 & 11.8793 & 0.120662 \tabularnewline
189 & 11 & 11.316 & -0.316021 \tabularnewline
190 & 11 & 10.0143 & 0.985713 \tabularnewline
191 & 14 & 14.5075 & -0.507503 \tabularnewline
192 & 16 & 15.3081 & 0.691881 \tabularnewline
193 & 12 & 9.81148 & 2.18852 \tabularnewline
194 & 16 & 14.0808 & 1.91921 \tabularnewline
195 & 13 & 14.0176 & -1.01755 \tabularnewline
196 & 15 & 15.2631 & -0.263121 \tabularnewline
197 & 16 & 12.6865 & 3.31348 \tabularnewline
198 & 16 & 15.1138 & 0.886205 \tabularnewline
199 & 14 & 12.681 & 1.31903 \tabularnewline
200 & 16 & 14.1864 & 1.81364 \tabularnewline
201 & 16 & 13.7548 & 2.24521 \tabularnewline
202 & 14 & 13.1261 & 0.8739 \tabularnewline
203 & 11 & 13.058 & -2.058 \tabularnewline
204 & 12 & 14.2894 & -2.28942 \tabularnewline
205 & 15 & 12.8784 & 2.12164 \tabularnewline
206 & 15 & 14.6612 & 0.338816 \tabularnewline
207 & 16 & 14.826 & 1.17397 \tabularnewline
208 & 16 & 15.3368 & 0.663243 \tabularnewline
209 & 11 & 13.3203 & -2.32028 \tabularnewline
210 & 15 & 14.1048 & 0.895164 \tabularnewline
211 & 12 & 14.473 & -2.47297 \tabularnewline
212 & 12 & 15.3428 & -3.34278 \tabularnewline
213 & 15 & 13.9963 & 1.00368 \tabularnewline
214 & 15 & 11.755 & 3.24502 \tabularnewline
215 & 16 & 14.116 & 1.884 \tabularnewline
216 & 14 & 12.9517 & 1.04826 \tabularnewline
217 & 17 & 14.8311 & 2.16886 \tabularnewline
218 & 14 & 14.0835 & -0.0834989 \tabularnewline
219 & 13 & 12.3308 & 0.669232 \tabularnewline
220 & 15 & 15.5352 & -0.535203 \tabularnewline
221 & 13 & 14.423 & -1.42301 \tabularnewline
222 & 14 & 14.3332 & -0.333232 \tabularnewline
223 & 15 & 14.5775 & 0.422548 \tabularnewline
224 & 12 & 12.7376 & -0.737586 \tabularnewline
225 & 13 & 12.8068 & 0.193188 \tabularnewline
226 & 8 & 11.5696 & -3.5696 \tabularnewline
227 & 14 & 13.4245 & 0.575494 \tabularnewline
228 & 14 & 12.9967 & 1.00331 \tabularnewline
229 & 11 & 12.3492 & -1.34921 \tabularnewline
230 & 12 & 13.0957 & -1.09575 \tabularnewline
231 & 13 & 11.7013 & 1.29868 \tabularnewline
232 & 10 & 13.5476 & -3.54756 \tabularnewline
233 & 16 & 11.2383 & 4.76169 \tabularnewline
234 & 18 & 15.9472 & 2.05281 \tabularnewline
235 & 13 & 14.1967 & -1.1967 \tabularnewline
236 & 11 & 12.9089 & -1.90887 \tabularnewline
237 & 4 & 10.7972 & -6.79719 \tabularnewline
238 & 13 & 13.9256 & -0.925613 \tabularnewline
239 & 16 & 13.8555 & 2.14453 \tabularnewline
240 & 10 & 11.5613 & -1.56133 \tabularnewline
241 & 12 & 12.4761 & -0.47615 \tabularnewline
242 & 12 & 13.6596 & -1.65964 \tabularnewline
243 & 10 & 9.36943 & 0.630575 \tabularnewline
244 & 13 & 11.5153 & 1.48472 \tabularnewline
245 & 15 & 13.4292 & 1.57085 \tabularnewline
246 & 12 & 12.1283 & -0.128343 \tabularnewline
247 & 14 & 13.2081 & 0.791879 \tabularnewline
248 & 10 & 12.1403 & -2.14029 \tabularnewline
249 & 12 & 10.6542 & 1.34578 \tabularnewline
250 & 12 & 11.5324 & 0.467605 \tabularnewline
251 & 11 & 11.5557 & -0.555717 \tabularnewline
252 & 10 & 11.649 & -1.64901 \tabularnewline
253 & 12 & 11.5861 & 0.413934 \tabularnewline
254 & 16 & 13.0692 & 2.93081 \tabularnewline
255 & 12 & 13.7388 & -1.73884 \tabularnewline
256 & 14 & 14.2304 & -0.230429 \tabularnewline
257 & 16 & 14.3138 & 1.68617 \tabularnewline
258 & 14 & 11.7716 & 2.22842 \tabularnewline
259 & 13 & 14.667 & -1.66705 \tabularnewline
260 & 4 & 8.99115 & -4.99115 \tabularnewline
261 & 15 & 13.7593 & 1.24066 \tabularnewline
262 & 11 & 14.8548 & -3.8548 \tabularnewline
263 & 11 & 10.8872 & 0.112774 \tabularnewline
264 & 14 & 12.8492 & 1.15075 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221816&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]13[/C][C]16.1055[/C][C]-3.10552[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.7745[/C][C]0.225535[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]17.2757[/C][C]1.72427[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.2991[/C][C]2.70092[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.1466[/C][C]-2.1466[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.8491[/C][C]-1.84913[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.3772[/C][C]3.62279[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.5653[/C][C]-1.56533[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.807[/C][C]-1.80698[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.0366[/C][C]0.96337[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.3918[/C][C]1.60823[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.0148[/C][C]-0.0148222[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.4838[/C][C]0.516235[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.6247[/C][C]0.375317[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]18.3921[/C][C]-1.39207[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.7487[/C][C]-0.748724[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.298[/C][C]0.701965[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.4686[/C][C]3.53136[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.6673[/C][C]2.33266[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.0919[/C][C]0.908127[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.1971[/C][C]0.802923[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]14.7067[/C][C]1.29328[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.0043[/C][C]2.99567[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.8515[/C][C]1.14851[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.2766[/C][C]0.723439[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.334[/C][C]0.665992[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.4434[/C][C]0.556567[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]17.09[/C][C]-2.09[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.5778[/C][C]0.422224[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.1395[/C][C]-0.139512[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]16.0487[/C][C]-1.04875[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.4103[/C][C]-0.410341[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.6722[/C][C]-0.672229[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.6026[/C][C]0.397421[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.1714[/C][C]-1.17136[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.8586[/C][C]-2.85862[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.2051[/C][C]-3.20512[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.9647[/C][C]-1.96473[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]15.013[/C][C]0.987043[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.8394[/C][C]1.16056[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.5084[/C][C]1.49162[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.9522[/C][C]-1.95225[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.8507[/C][C]2.14934[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]13.7908[/C][C]0.209183[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.3382[/C][C]-0.338169[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.2917[/C][C]-4.29167[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.1085[/C][C]-2.10851[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.0807[/C][C]-0.0806867[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.8463[/C][C]0.153739[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.8819[/C][C]-1.88192[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]17.5635[/C][C]-1.56349[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.6085[/C][C]-0.608532[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.9444[/C][C]-2.94443[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.8596[/C][C]0.140395[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.7855[/C][C]-2.78551[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.0327[/C][C]1.96727[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.8547[/C][C]0.145334[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.3196[/C][C]0.680447[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.81[/C][C]0.189957[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.1787[/C][C]1.82129[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.7551[/C][C]0.244897[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]16.0228[/C][C]-0.0227832[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]17.1004[/C][C]-1.10039[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]15.2707[/C][C]-1.27075[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.2458[/C][C]0.754163[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]15.8472[/C][C]1.15284[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.3098[/C][C]1.69019[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]13.846[/C][C]4.154[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.589[/C][C]-3.589[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.1777[/C][C]0.822348[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]12.5705[/C][C]-2.57055[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.6493[/C][C]-0.64925[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.9748[/C][C]1.02517[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.2546[/C][C]0.745376[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.4275[/C][C]0.572513[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.5879[/C][C]3.41209[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.0533[/C][C]-0.0533448[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.3397[/C][C]1.66033[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.3515[/C][C]-2.3515[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]14.4816[/C][C]1.51843[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.4657[/C][C]0.534338[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.2394[/C][C]0.760612[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.1131[/C][C]-0.113113[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.6068[/C][C]0.393221[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.1221[/C][C]1.87791[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.2351[/C][C]-0.235105[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.6322[/C][C]0.367762[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]15.0937[/C][C]0.90629[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.093[/C][C]0.906965[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.853[/C][C]-1.85297[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.9479[/C][C]0.0521022[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.3665[/C][C]0.633475[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]14.8758[/C][C]0.124193[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.6905[/C][C]-1.69048[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.2749[/C][C]1.72507[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.5141[/C][C]0.485944[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.7522[/C][C]2.2478[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.9554[/C][C]0.0445906[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.7677[/C][C]-0.767659[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.3751[/C][C]-1.37515[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.3382[/C][C]1.66185[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.5266[/C][C]2.47341[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.3183[/C][C]0.681682[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.5918[/C][C]1.40824[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.6067[/C][C]-1.60666[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.3498[/C][C]1.65017[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.2587[/C][C]0.741311[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.146[/C][C]1.85397[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.3179[/C][C]-0.317869[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.4527[/C][C]0.54729[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.4054[/C][C]-0.405389[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.3338[/C][C]1.66625[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.638[/C][C]-1.63796[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.6722[/C][C]-2.67225[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.4357[/C][C]1.56432[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.503[/C][C]-1.50301[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]12.9565[/C][C]1.04355[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.5039[/C][C]-1.50388[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.0808[/C][C]0.919183[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.3219[/C][C]-1.32185[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.5503[/C][C]0.449747[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]16.0586[/C][C]-3.05858[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]17.2775[/C][C]-1.27752[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]16.2083[/C][C]-1.20826[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.6586[/C][C]-0.658631[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.78[/C][C]0.220036[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.93[/C][C]1.07002[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.5785[/C][C]1.42153[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.6086[/C][C]-2.60863[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.7474[/C][C]2.25257[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.3191[/C][C]-3.31913[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4319[/C][C]2.56815[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.393[/C][C]-2.39295[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.7954[/C][C]-1.79538[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.5339[/C][C]-0.533878[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.5107[/C][C]0.489274[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.255[/C][C]0.745031[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.5915[/C][C]-2.59146[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.3627[/C][C]-1.3627[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.0715[/C][C]-2.07152[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8261[/C][C]3.1739[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.5309[/C][C]1.46906[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.5186[/C][C]0.481449[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.1345[/C][C]1.86553[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.4758[/C][C]-3.47583[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.7932[/C][C]2.20679[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.4038[/C][C]-2.40382[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]15.294[/C][C]0.706047[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.6249[/C][C]0.375072[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]13.1167[/C][C]-3.11668[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.4184[/C][C]-1.41836[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.7094[/C][C]2.29064[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.8438[/C][C]4.15618[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.5819[/C][C]1.4181[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.0291[/C][C]-2.0291[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.516[/C][C]0.484014[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.9967[/C][C]1.00332[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]14.172[/C][C]0.82797[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]15.1077[/C][C]0.892292[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]13.3192[/C][C]-1.3192[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.4972[/C][C]0.502811[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.4233[/C][C]0.576699[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.5693[/C][C]-0.569269[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]15.6892[/C][C]1.31084[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.3882[/C][C]1.6118[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.1621[/C][C]-1.16213[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]13.7084[/C][C]0.29163[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]13.921[/C][C]-2.92103[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.7466[/C][C]-1.74664[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.5769[/C][C]1.42305[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.6615[/C][C]1.33846[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.5959[/C][C]0.404067[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.4231[/C][C]-1.4231[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.3052[/C][C]-2.30521[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]15.0894[/C][C]-3.08937[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.0852[/C][C]0.914849[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]11.8859[/C][C]0.114143[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.2814[/C][C]-0.281433[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.2363[/C][C]0.763695[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.1688[/C][C]-1.16883[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.0659[/C][C]0.934084[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.4534[/C][C]-0.453372[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]17.0108[/C][C]1.98924[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.3965[/C][C]-0.396538[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.2865[/C][C]-6.28652[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.8766[/C][C]1.12336[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.7344[/C][C]2.26562[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]11.8793[/C][C]0.120662[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.316[/C][C]-0.316021[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.0143[/C][C]0.985713[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.5075[/C][C]-0.507503[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.3081[/C][C]0.691881[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.81148[/C][C]2.18852[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.0808[/C][C]1.91921[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]14.0176[/C][C]-1.01755[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.2631[/C][C]-0.263121[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.6865[/C][C]3.31348[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.1138[/C][C]0.886205[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.681[/C][C]1.31903[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.1864[/C][C]1.81364[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]13.7548[/C][C]2.24521[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.1261[/C][C]0.8739[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.058[/C][C]-2.058[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.2894[/C][C]-2.28942[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.8784[/C][C]2.12164[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.6612[/C][C]0.338816[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.826[/C][C]1.17397[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]15.3368[/C][C]0.663243[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.3203[/C][C]-2.32028[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]14.1048[/C][C]0.895164[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.473[/C][C]-2.47297[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.3428[/C][C]-3.34278[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]13.9963[/C][C]1.00368[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]11.755[/C][C]3.24502[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.116[/C][C]1.884[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]12.9517[/C][C]1.04826[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.8311[/C][C]2.16886[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.0835[/C][C]-0.0834989[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]12.3308[/C][C]0.669232[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.5352[/C][C]-0.535203[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.423[/C][C]-1.42301[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.3332[/C][C]-0.333232[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.5775[/C][C]0.422548[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]12.7376[/C][C]-0.737586[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.8068[/C][C]0.193188[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.5696[/C][C]-3.5696[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.4245[/C][C]0.575494[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.9967[/C][C]1.00331[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.3492[/C][C]-1.34921[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]13.0957[/C][C]-1.09575[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.7013[/C][C]1.29868[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.5476[/C][C]-3.54756[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.2383[/C][C]4.76169[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.9472[/C][C]2.05281[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]14.1967[/C][C]-1.1967[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.9089[/C][C]-1.90887[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.7972[/C][C]-6.79719[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.9256[/C][C]-0.925613[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]13.8555[/C][C]2.14453[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.5613[/C][C]-1.56133[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.4761[/C][C]-0.47615[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.6596[/C][C]-1.65964[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]9.36943[/C][C]0.630575[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]11.5153[/C][C]1.48472[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.4292[/C][C]1.57085[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]12.1283[/C][C]-0.128343[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]13.2081[/C][C]0.791879[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.1403[/C][C]-2.14029[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.6542[/C][C]1.34578[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5324[/C][C]0.467605[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.5557[/C][C]-0.555717[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.649[/C][C]-1.64901[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.5861[/C][C]0.413934[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]13.0692[/C][C]2.93081[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.7388[/C][C]-1.73884[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]14.2304[/C][C]-0.230429[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.3138[/C][C]1.68617[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.7716[/C][C]2.22842[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.667[/C][C]-1.66705[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]8.99115[/C][C]-4.99115[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.7593[/C][C]1.24066[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.8548[/C][C]-3.8548[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]10.8872[/C][C]0.112774[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.8492[/C][C]1.15075[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221816&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221816&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
11316.1055-3.10552
21615.77450.225535
31917.27571.72427
41512.29912.70092
51416.1466-2.1466
61314.8491-1.84913
71915.37723.62279
81516.5653-1.56533
91415.807-1.80698
101514.03660.96337
111614.39181.60823
121616.0148-0.0148222
131615.48380.516235
141615.62470.375317
151718.3921-1.39207
161515.7487-0.748724
171514.2980.701965
182016.46863.53136
191815.66732.33266
201615.09190.908127
211615.19710.802923
221614.70671.29328
231916.00432.99567
241614.85151.14851
251716.27660.723439
261716.3340.665992
271615.44340.556567
281517.09-2.09
291615.57780.422224
301414.1395-0.139512
311516.0487-1.04875
321212.4103-0.410341
331414.6722-0.672229
341615.60260.397421
351415.1714-1.17136
361012.8586-2.85862
371013.2051-3.20512
381415.9647-1.96473
391615.0130.987043
401614.83941.16056
411614.50841.49162
421415.9522-1.95225
432017.85072.14934
441413.79080.209183
451414.3382-0.338169
461115.2917-4.29167
471416.1085-2.10851
481515.0807-0.0806867
491615.84630.153739
501415.8819-1.88192
511617.5635-1.56349
521414.6085-0.608532
531214.9444-2.94443
541615.85960.140395
55911.7855-2.78551
561412.03271.96727
571615.85470.145334
581615.31960.680447
591514.810.189957
601614.17871.82129
611211.75510.244897
621616.0228-0.0227832
631617.1004-1.10039
641415.2707-1.27075
651615.24580.754163
661715.84721.15284
671816.30981.69019
681813.8464.154
691215.589-3.589
701615.17770.822348
711012.5705-2.57055
721414.6493-0.64925
731816.97481.02517
741817.25460.745376
751615.42750.572513
761713.58793.41209
771616.0533-0.0533448
781614.33971.66033
791315.3515-2.3515
801614.48161.51843
811615.46570.534338
821615.23940.760612
831515.1131-0.113113
841514.60680.393221
851614.12211.87791
861414.2351-0.235105
871615.63220.367762
881615.09370.90629
891514.0930.906965
901213.853-1.85297
911716.94790.0521022
921615.36650.633475
931514.87580.124193
941314.6905-1.69048
951614.27491.72507
961615.51410.485944
971613.75222.2478
981615.95540.0445906
991414.7677-0.767659
1001617.3751-1.37515
1011614.33821.66185
1022017.52662.47341
1031514.31830.681682
1041614.59181.40824
1051314.6067-1.60666
1061715.34981.65017
1071615.25870.741311
1081614.1461.85397
1091212.3179-0.317869
1101615.45270.54729
1111616.4054-0.405389
1121715.33381.66625
1131314.638-1.63796
1141214.6722-2.67225
1151816.43571.56432
1161415.503-1.50301
1171412.95651.04355
1181314.5039-1.50388
1191615.08080.919183
1201314.3219-1.32185
1211615.55030.449747
1221316.0586-3.05858
1231617.2775-1.27752
1241516.2083-1.20826
1251616.6586-0.658631
1261514.780.220036
1271715.931.07002
1281513.57851.42153
1291214.6086-2.60863
1301613.74742.25257
1311013.3191-3.31913
1321613.43192.56815
1331214.393-2.39295
1341415.7954-1.79538
1351515.5339-0.533878
1361312.51070.489274
1371514.2550.745031
1381113.5915-2.59146
1391213.3627-1.3627
1401113.0715-2.07152
1411612.82613.1739
1421513.53091.46906
1431716.51860.481449
1441614.13451.86553
1451013.4758-3.47583
1461815.79322.20679
1471315.4038-2.40382
1481615.2940.706047
1491312.62490.375072
1501013.1167-3.11668
1511516.4184-1.41836
1521613.70942.29064
1531611.84384.15618
1541412.58191.4181
1551012.0291-2.0291
1561716.5160.484014
1571311.99671.00332
1581514.1720.82797
1591615.10770.892292
1601213.3192-1.3192
1611312.49720.502811
1621312.42330.576699
1631212.5693-0.569269
1641715.68921.31084
1651513.38821.6118
1661011.1621-1.16213
1671413.70840.29163
1681113.921-2.92103
1691314.7466-1.74664
1701614.57691.42305
1711210.66151.33846
1721615.59590.404067
1731213.4231-1.4231
174911.3052-2.30521
1751215.0894-3.08937
1761514.08520.914849
1771211.88590.114143
1781212.2814-0.281433
1791413.23630.763695
1801213.1688-1.16883
1811615.06590.934084
1821111.4534-0.453372
1831917.01081.98924
1841515.3965-0.396538
185814.2865-6.28652
1861614.87661.12336
1871714.73442.26562
1881211.87930.120662
1891111.316-0.316021
1901110.01430.985713
1911414.5075-0.507503
1921615.30810.691881
193129.811482.18852
1941614.08081.91921
1951314.0176-1.01755
1961515.2631-0.263121
1971612.68653.31348
1981615.11380.886205
1991412.6811.31903
2001614.18641.81364
2011613.75482.24521
2021413.12610.8739
2031113.058-2.058
2041214.2894-2.28942
2051512.87842.12164
2061514.66120.338816
2071614.8261.17397
2081615.33680.663243
2091113.3203-2.32028
2101514.10480.895164
2111214.473-2.47297
2121215.3428-3.34278
2131513.99631.00368
2141511.7553.24502
2151614.1161.884
2161412.95171.04826
2171714.83112.16886
2181414.0835-0.0834989
2191312.33080.669232
2201515.5352-0.535203
2211314.423-1.42301
2221414.3332-0.333232
2231514.57750.422548
2241212.7376-0.737586
2251312.80680.193188
226811.5696-3.5696
2271413.42450.575494
2281412.99671.00331
2291112.3492-1.34921
2301213.0957-1.09575
2311311.70131.29868
2321013.5476-3.54756
2331611.23834.76169
2341815.94722.05281
2351314.1967-1.1967
2361112.9089-1.90887
237410.7972-6.79719
2381313.9256-0.925613
2391613.85552.14453
2401011.5613-1.56133
2411212.4761-0.47615
2421213.6596-1.65964
243109.369430.630575
2441311.51531.48472
2451513.42921.57085
2461212.1283-0.128343
2471413.20810.791879
2481012.1403-2.14029
2491210.65421.34578
2501211.53240.467605
2511111.5557-0.555717
2521011.649-1.64901
2531211.58610.413934
2541613.06922.93081
2551213.7388-1.73884
2561414.2304-0.230429
2571614.31381.68617
2581411.77162.22842
2591314.667-1.66705
26048.99115-4.99115
2611513.75931.24066
2621114.8548-3.8548
2631110.88720.112774
2641412.84921.15075






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
230.4018630.8037260.598137
240.781490.437020.21851
250.8592350.281530.140765
260.829170.341660.17083
270.7993570.4012860.200643
280.7511740.4976520.248826
290.7003830.5992350.299617
300.724740.5505190.27526
310.769170.4616590.23083
320.7068410.5863180.293159
330.6424440.7151120.357556
340.5693070.8613850.430693
350.5143060.9713890.485694
360.598570.8028590.40143
370.5435940.9128130.456406
380.5037930.9924150.496207
390.4428260.8856520.557174
400.3799070.7598130.620093
410.3236650.6473310.676335
420.2732530.5465070.726747
430.2417640.4835280.758236
440.1985060.3970120.801494
450.1644180.3288370.835582
460.3067620.6135250.693238
470.5477980.9044030.452202
480.515410.969180.48459
490.5509120.8981770.449088
500.5253510.9492980.474649
510.5068380.9863240.493162
520.4561140.9122290.543886
530.4642010.9284030.535799
540.421740.843480.57826
550.5030670.9938670.496933
560.4579520.9159040.542048
570.4073960.8147920.592604
580.410250.82050.58975
590.3678550.7357110.632145
600.3821120.7642250.617888
610.3583340.7166670.641666
620.3276710.6553410.672329
630.3000520.6001030.699948
640.265490.5309810.73451
650.2325030.4650050.767497
660.1988930.3977850.801107
670.1785930.3571860.821407
680.2217060.4434120.778294
690.3644260.7288520.635574
700.3230880.6461760.676912
710.4831250.966250.516875
720.4422390.8844780.557761
730.4373350.874670.562665
740.418940.8378810.58106
750.3935620.7871240.606438
760.3986930.7973850.601307
770.3630.7260.637
780.3345480.6690960.665452
790.3653960.7307920.634604
800.3575290.7150590.642471
810.3527120.7054240.647288
820.3154680.6309350.684532
830.2794940.5589890.720506
840.2450240.4900470.754976
850.2336210.4672430.766379
860.2033420.4066830.796658
870.1753540.3507080.824646
880.1538510.3077030.846149
890.133270.266540.86673
900.13170.26340.8683
910.1148850.229770.885115
920.09688570.1937710.903114
930.08103010.162060.91897
940.07729130.1545830.922709
950.07202910.1440580.927971
960.06055470.1211090.939445
970.05943370.1188670.940566
980.04839180.09678370.951608
990.04187920.08375830.958121
1000.04676290.09352580.953237
1010.04079790.08159580.959202
1020.04514780.09029550.954852
1030.03814420.07628840.961856
1040.03288970.06577940.96711
1050.03330320.06660630.966697
1060.02900740.05801480.970993
1070.0235480.04709590.976452
1080.02260660.04521310.977393
1090.01885640.03771280.981144
1100.01557320.03114630.984427
1110.01229910.02459820.987701
1120.01075710.02151410.989243
1130.01039690.02079390.989603
1140.01747520.03495050.982525
1150.01541410.03082820.984586
1160.01477040.02954070.98523
1170.0134780.0269560.986522
1180.01240810.02481620.987592
1190.01017260.02034510.989827
1200.008934080.01786820.991066
1210.006981370.01396270.993019
1220.01244080.02488170.987559
1230.01208550.0241710.987915
1240.01279420.02558830.987206
1250.01052820.02105640.989472
1260.008475240.01695050.991525
1270.006900250.01380050.9931
1280.005953540.01190710.994046
1290.007696840.01539370.992303
1300.008961820.01792360.991038
1310.01324850.02649690.986752
1320.01417380.02834770.985826
1330.0165170.0330340.983483
1340.01703810.03407620.982962
1350.01459330.02918660.985407
1360.01151870.02303730.988481
1370.009012630.01802530.990987
1380.01084550.02169110.989154
1390.01033240.02066470.989668
1400.01240050.02480110.987599
1410.02416840.04833690.975832
1420.02231330.04462660.977687
1430.01858270.03716530.981417
1440.01794230.03588450.982058
1450.0419650.08392990.958035
1460.04310470.08620950.956895
1470.057380.114760.94262
1480.04793750.0958750.952063
1490.03929050.07858090.96071
1500.06282790.1256560.937172
1510.06217350.1243470.937826
1520.0617640.1235280.938236
1530.1150330.2300660.884967
1540.109260.2185210.89074
1550.1119770.2239550.888023
1560.0961130.1922260.903887
1570.08507770.1701550.914922
1580.07264940.1452990.927351
1590.06231280.1246260.937687
1600.05601860.1120370.943981
1610.04589580.09179170.954104
1620.03815180.07630370.961848
1630.03184610.06369220.968154
1640.03140710.06281410.968593
1650.02947190.05894380.970528
1660.0255990.05119790.974401
1670.02036610.04073210.979634
1680.02813480.05626960.971865
1690.03065160.06130330.969348
1700.02968730.05937460.970313
1710.02556430.05112850.974436
1720.02058480.04116960.979415
1730.01972320.03944640.980277
1740.0243830.04876610.975617
1750.03271270.06542550.967287
1760.02990670.05981340.970093
1770.02515350.05030690.974847
1780.01980210.03960420.980198
1790.01619630.03239270.983804
1800.01343020.02686040.98657
1810.01079120.02158240.989209
1820.008401120.01680220.991599
1830.007996330.01599270.992004
1840.006229830.01245970.99377
1850.1769010.3538010.823099
1860.1630380.3260750.836962
1870.1847770.3695540.815223
1880.2086910.4173820.791309
1890.1795360.3590710.820464
1900.1787980.3575960.821202
1910.1797890.3595770.820211
1920.1685040.3370080.831496
1930.1763760.3527510.823624
1940.1726240.3452480.827376
1950.1742240.3484470.825776
1960.1492510.2985020.850749
1970.1724030.3448070.827597
1980.1493280.2986550.850672
1990.1459860.2919720.854014
2000.133080.2661610.86692
2010.1505730.3011450.849427
2020.1269890.2539780.873011
2030.1616450.3232910.838355
2040.1659980.3319970.834002
2050.1614020.3228050.838598
2060.1340370.2680740.865963
2070.1142510.2285030.885749
2080.09317860.1863570.906821
2090.1341560.2683130.865844
2100.1111040.2222070.888896
2110.1156990.2313990.884301
2120.1171250.234250.882875
2130.1586690.3173390.841331
2140.5450950.909810.454905
2150.5285090.9429820.471491
2160.4810910.9621820.518909
2170.4947620.9895240.505238
2180.4519690.9039380.548031
2190.4232070.8464140.576793
2200.3933620.7867240.606638
2210.6085520.7828950.391448
2220.7027040.5945910.297296
2230.6610060.6779890.338994
2240.621610.756780.37839
2250.5920720.8158560.407928
2260.5690670.8618660.430933
2270.6650260.6699470.334974
2280.6043630.7912740.395637
2290.5338970.9322060.466103
2300.4831950.9663910.516805
2310.4318670.8637340.568133
2320.4649270.9298540.535073
2330.4114670.8229340.588533
2340.3796470.7592950.620353
2350.3461560.6923120.653844
2360.3085910.6171820.691409
2370.4338830.8677670.566117
2380.3330250.6660510.666975
2390.26660.5331990.7334
2400.1916040.3832080.808396
2410.106410.2128190.89359

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
23 & 0.401863 & 0.803726 & 0.598137 \tabularnewline
24 & 0.78149 & 0.43702 & 0.21851 \tabularnewline
25 & 0.859235 & 0.28153 & 0.140765 \tabularnewline
26 & 0.82917 & 0.34166 & 0.17083 \tabularnewline
27 & 0.799357 & 0.401286 & 0.200643 \tabularnewline
28 & 0.751174 & 0.497652 & 0.248826 \tabularnewline
29 & 0.700383 & 0.599235 & 0.299617 \tabularnewline
30 & 0.72474 & 0.550519 & 0.27526 \tabularnewline
31 & 0.76917 & 0.461659 & 0.23083 \tabularnewline
32 & 0.706841 & 0.586318 & 0.293159 \tabularnewline
33 & 0.642444 & 0.715112 & 0.357556 \tabularnewline
34 & 0.569307 & 0.861385 & 0.430693 \tabularnewline
35 & 0.514306 & 0.971389 & 0.485694 \tabularnewline
36 & 0.59857 & 0.802859 & 0.40143 \tabularnewline
37 & 0.543594 & 0.912813 & 0.456406 \tabularnewline
38 & 0.503793 & 0.992415 & 0.496207 \tabularnewline
39 & 0.442826 & 0.885652 & 0.557174 \tabularnewline
40 & 0.379907 & 0.759813 & 0.620093 \tabularnewline
41 & 0.323665 & 0.647331 & 0.676335 \tabularnewline
42 & 0.273253 & 0.546507 & 0.726747 \tabularnewline
43 & 0.241764 & 0.483528 & 0.758236 \tabularnewline
44 & 0.198506 & 0.397012 & 0.801494 \tabularnewline
45 & 0.164418 & 0.328837 & 0.835582 \tabularnewline
46 & 0.306762 & 0.613525 & 0.693238 \tabularnewline
47 & 0.547798 & 0.904403 & 0.452202 \tabularnewline
48 & 0.51541 & 0.96918 & 0.48459 \tabularnewline
49 & 0.550912 & 0.898177 & 0.449088 \tabularnewline
50 & 0.525351 & 0.949298 & 0.474649 \tabularnewline
51 & 0.506838 & 0.986324 & 0.493162 \tabularnewline
52 & 0.456114 & 0.912229 & 0.543886 \tabularnewline
53 & 0.464201 & 0.928403 & 0.535799 \tabularnewline
54 & 0.42174 & 0.84348 & 0.57826 \tabularnewline
55 & 0.503067 & 0.993867 & 0.496933 \tabularnewline
56 & 0.457952 & 0.915904 & 0.542048 \tabularnewline
57 & 0.407396 & 0.814792 & 0.592604 \tabularnewline
58 & 0.41025 & 0.8205 & 0.58975 \tabularnewline
59 & 0.367855 & 0.735711 & 0.632145 \tabularnewline
60 & 0.382112 & 0.764225 & 0.617888 \tabularnewline
61 & 0.358334 & 0.716667 & 0.641666 \tabularnewline
62 & 0.327671 & 0.655341 & 0.672329 \tabularnewline
63 & 0.300052 & 0.600103 & 0.699948 \tabularnewline
64 & 0.26549 & 0.530981 & 0.73451 \tabularnewline
65 & 0.232503 & 0.465005 & 0.767497 \tabularnewline
66 & 0.198893 & 0.397785 & 0.801107 \tabularnewline
67 & 0.178593 & 0.357186 & 0.821407 \tabularnewline
68 & 0.221706 & 0.443412 & 0.778294 \tabularnewline
69 & 0.364426 & 0.728852 & 0.635574 \tabularnewline
70 & 0.323088 & 0.646176 & 0.676912 \tabularnewline
71 & 0.483125 & 0.96625 & 0.516875 \tabularnewline
72 & 0.442239 & 0.884478 & 0.557761 \tabularnewline
73 & 0.437335 & 0.87467 & 0.562665 \tabularnewline
74 & 0.41894 & 0.837881 & 0.58106 \tabularnewline
75 & 0.393562 & 0.787124 & 0.606438 \tabularnewline
76 & 0.398693 & 0.797385 & 0.601307 \tabularnewline
77 & 0.363 & 0.726 & 0.637 \tabularnewline
78 & 0.334548 & 0.669096 & 0.665452 \tabularnewline
79 & 0.365396 & 0.730792 & 0.634604 \tabularnewline
80 & 0.357529 & 0.715059 & 0.642471 \tabularnewline
81 & 0.352712 & 0.705424 & 0.647288 \tabularnewline
82 & 0.315468 & 0.630935 & 0.684532 \tabularnewline
83 & 0.279494 & 0.558989 & 0.720506 \tabularnewline
84 & 0.245024 & 0.490047 & 0.754976 \tabularnewline
85 & 0.233621 & 0.467243 & 0.766379 \tabularnewline
86 & 0.203342 & 0.406683 & 0.796658 \tabularnewline
87 & 0.175354 & 0.350708 & 0.824646 \tabularnewline
88 & 0.153851 & 0.307703 & 0.846149 \tabularnewline
89 & 0.13327 & 0.26654 & 0.86673 \tabularnewline
90 & 0.1317 & 0.2634 & 0.8683 \tabularnewline
91 & 0.114885 & 0.22977 & 0.885115 \tabularnewline
92 & 0.0968857 & 0.193771 & 0.903114 \tabularnewline
93 & 0.0810301 & 0.16206 & 0.91897 \tabularnewline
94 & 0.0772913 & 0.154583 & 0.922709 \tabularnewline
95 & 0.0720291 & 0.144058 & 0.927971 \tabularnewline
96 & 0.0605547 & 0.121109 & 0.939445 \tabularnewline
97 & 0.0594337 & 0.118867 & 0.940566 \tabularnewline
98 & 0.0483918 & 0.0967837 & 0.951608 \tabularnewline
99 & 0.0418792 & 0.0837583 & 0.958121 \tabularnewline
100 & 0.0467629 & 0.0935258 & 0.953237 \tabularnewline
101 & 0.0407979 & 0.0815958 & 0.959202 \tabularnewline
102 & 0.0451478 & 0.0902955 & 0.954852 \tabularnewline
103 & 0.0381442 & 0.0762884 & 0.961856 \tabularnewline
104 & 0.0328897 & 0.0657794 & 0.96711 \tabularnewline
105 & 0.0333032 & 0.0666063 & 0.966697 \tabularnewline
106 & 0.0290074 & 0.0580148 & 0.970993 \tabularnewline
107 & 0.023548 & 0.0470959 & 0.976452 \tabularnewline
108 & 0.0226066 & 0.0452131 & 0.977393 \tabularnewline
109 & 0.0188564 & 0.0377128 & 0.981144 \tabularnewline
110 & 0.0155732 & 0.0311463 & 0.984427 \tabularnewline
111 & 0.0122991 & 0.0245982 & 0.987701 \tabularnewline
112 & 0.0107571 & 0.0215141 & 0.989243 \tabularnewline
113 & 0.0103969 & 0.0207939 & 0.989603 \tabularnewline
114 & 0.0174752 & 0.0349505 & 0.982525 \tabularnewline
115 & 0.0154141 & 0.0308282 & 0.984586 \tabularnewline
116 & 0.0147704 & 0.0295407 & 0.98523 \tabularnewline
117 & 0.013478 & 0.026956 & 0.986522 \tabularnewline
118 & 0.0124081 & 0.0248162 & 0.987592 \tabularnewline
119 & 0.0101726 & 0.0203451 & 0.989827 \tabularnewline
120 & 0.00893408 & 0.0178682 & 0.991066 \tabularnewline
121 & 0.00698137 & 0.0139627 & 0.993019 \tabularnewline
122 & 0.0124408 & 0.0248817 & 0.987559 \tabularnewline
123 & 0.0120855 & 0.024171 & 0.987915 \tabularnewline
124 & 0.0127942 & 0.0255883 & 0.987206 \tabularnewline
125 & 0.0105282 & 0.0210564 & 0.989472 \tabularnewline
126 & 0.00847524 & 0.0169505 & 0.991525 \tabularnewline
127 & 0.00690025 & 0.0138005 & 0.9931 \tabularnewline
128 & 0.00595354 & 0.0119071 & 0.994046 \tabularnewline
129 & 0.00769684 & 0.0153937 & 0.992303 \tabularnewline
130 & 0.00896182 & 0.0179236 & 0.991038 \tabularnewline
131 & 0.0132485 & 0.0264969 & 0.986752 \tabularnewline
132 & 0.0141738 & 0.0283477 & 0.985826 \tabularnewline
133 & 0.016517 & 0.033034 & 0.983483 \tabularnewline
134 & 0.0170381 & 0.0340762 & 0.982962 \tabularnewline
135 & 0.0145933 & 0.0291866 & 0.985407 \tabularnewline
136 & 0.0115187 & 0.0230373 & 0.988481 \tabularnewline
137 & 0.00901263 & 0.0180253 & 0.990987 \tabularnewline
138 & 0.0108455 & 0.0216911 & 0.989154 \tabularnewline
139 & 0.0103324 & 0.0206647 & 0.989668 \tabularnewline
140 & 0.0124005 & 0.0248011 & 0.987599 \tabularnewline
141 & 0.0241684 & 0.0483369 & 0.975832 \tabularnewline
142 & 0.0223133 & 0.0446266 & 0.977687 \tabularnewline
143 & 0.0185827 & 0.0371653 & 0.981417 \tabularnewline
144 & 0.0179423 & 0.0358845 & 0.982058 \tabularnewline
145 & 0.041965 & 0.0839299 & 0.958035 \tabularnewline
146 & 0.0431047 & 0.0862095 & 0.956895 \tabularnewline
147 & 0.05738 & 0.11476 & 0.94262 \tabularnewline
148 & 0.0479375 & 0.095875 & 0.952063 \tabularnewline
149 & 0.0392905 & 0.0785809 & 0.96071 \tabularnewline
150 & 0.0628279 & 0.125656 & 0.937172 \tabularnewline
151 & 0.0621735 & 0.124347 & 0.937826 \tabularnewline
152 & 0.061764 & 0.123528 & 0.938236 \tabularnewline
153 & 0.115033 & 0.230066 & 0.884967 \tabularnewline
154 & 0.10926 & 0.218521 & 0.89074 \tabularnewline
155 & 0.111977 & 0.223955 & 0.888023 \tabularnewline
156 & 0.096113 & 0.192226 & 0.903887 \tabularnewline
157 & 0.0850777 & 0.170155 & 0.914922 \tabularnewline
158 & 0.0726494 & 0.145299 & 0.927351 \tabularnewline
159 & 0.0623128 & 0.124626 & 0.937687 \tabularnewline
160 & 0.0560186 & 0.112037 & 0.943981 \tabularnewline
161 & 0.0458958 & 0.0917917 & 0.954104 \tabularnewline
162 & 0.0381518 & 0.0763037 & 0.961848 \tabularnewline
163 & 0.0318461 & 0.0636922 & 0.968154 \tabularnewline
164 & 0.0314071 & 0.0628141 & 0.968593 \tabularnewline
165 & 0.0294719 & 0.0589438 & 0.970528 \tabularnewline
166 & 0.025599 & 0.0511979 & 0.974401 \tabularnewline
167 & 0.0203661 & 0.0407321 & 0.979634 \tabularnewline
168 & 0.0281348 & 0.0562696 & 0.971865 \tabularnewline
169 & 0.0306516 & 0.0613033 & 0.969348 \tabularnewline
170 & 0.0296873 & 0.0593746 & 0.970313 \tabularnewline
171 & 0.0255643 & 0.0511285 & 0.974436 \tabularnewline
172 & 0.0205848 & 0.0411696 & 0.979415 \tabularnewline
173 & 0.0197232 & 0.0394464 & 0.980277 \tabularnewline
174 & 0.024383 & 0.0487661 & 0.975617 \tabularnewline
175 & 0.0327127 & 0.0654255 & 0.967287 \tabularnewline
176 & 0.0299067 & 0.0598134 & 0.970093 \tabularnewline
177 & 0.0251535 & 0.0503069 & 0.974847 \tabularnewline
178 & 0.0198021 & 0.0396042 & 0.980198 \tabularnewline
179 & 0.0161963 & 0.0323927 & 0.983804 \tabularnewline
180 & 0.0134302 & 0.0268604 & 0.98657 \tabularnewline
181 & 0.0107912 & 0.0215824 & 0.989209 \tabularnewline
182 & 0.00840112 & 0.0168022 & 0.991599 \tabularnewline
183 & 0.00799633 & 0.0159927 & 0.992004 \tabularnewline
184 & 0.00622983 & 0.0124597 & 0.99377 \tabularnewline
185 & 0.176901 & 0.353801 & 0.823099 \tabularnewline
186 & 0.163038 & 0.326075 & 0.836962 \tabularnewline
187 & 0.184777 & 0.369554 & 0.815223 \tabularnewline
188 & 0.208691 & 0.417382 & 0.791309 \tabularnewline
189 & 0.179536 & 0.359071 & 0.820464 \tabularnewline
190 & 0.178798 & 0.357596 & 0.821202 \tabularnewline
191 & 0.179789 & 0.359577 & 0.820211 \tabularnewline
192 & 0.168504 & 0.337008 & 0.831496 \tabularnewline
193 & 0.176376 & 0.352751 & 0.823624 \tabularnewline
194 & 0.172624 & 0.345248 & 0.827376 \tabularnewline
195 & 0.174224 & 0.348447 & 0.825776 \tabularnewline
196 & 0.149251 & 0.298502 & 0.850749 \tabularnewline
197 & 0.172403 & 0.344807 & 0.827597 \tabularnewline
198 & 0.149328 & 0.298655 & 0.850672 \tabularnewline
199 & 0.145986 & 0.291972 & 0.854014 \tabularnewline
200 & 0.13308 & 0.266161 & 0.86692 \tabularnewline
201 & 0.150573 & 0.301145 & 0.849427 \tabularnewline
202 & 0.126989 & 0.253978 & 0.873011 \tabularnewline
203 & 0.161645 & 0.323291 & 0.838355 \tabularnewline
204 & 0.165998 & 0.331997 & 0.834002 \tabularnewline
205 & 0.161402 & 0.322805 & 0.838598 \tabularnewline
206 & 0.134037 & 0.268074 & 0.865963 \tabularnewline
207 & 0.114251 & 0.228503 & 0.885749 \tabularnewline
208 & 0.0931786 & 0.186357 & 0.906821 \tabularnewline
209 & 0.134156 & 0.268313 & 0.865844 \tabularnewline
210 & 0.111104 & 0.222207 & 0.888896 \tabularnewline
211 & 0.115699 & 0.231399 & 0.884301 \tabularnewline
212 & 0.117125 & 0.23425 & 0.882875 \tabularnewline
213 & 0.158669 & 0.317339 & 0.841331 \tabularnewline
214 & 0.545095 & 0.90981 & 0.454905 \tabularnewline
215 & 0.528509 & 0.942982 & 0.471491 \tabularnewline
216 & 0.481091 & 0.962182 & 0.518909 \tabularnewline
217 & 0.494762 & 0.989524 & 0.505238 \tabularnewline
218 & 0.451969 & 0.903938 & 0.548031 \tabularnewline
219 & 0.423207 & 0.846414 & 0.576793 \tabularnewline
220 & 0.393362 & 0.786724 & 0.606638 \tabularnewline
221 & 0.608552 & 0.782895 & 0.391448 \tabularnewline
222 & 0.702704 & 0.594591 & 0.297296 \tabularnewline
223 & 0.661006 & 0.677989 & 0.338994 \tabularnewline
224 & 0.62161 & 0.75678 & 0.37839 \tabularnewline
225 & 0.592072 & 0.815856 & 0.407928 \tabularnewline
226 & 0.569067 & 0.861866 & 0.430933 \tabularnewline
227 & 0.665026 & 0.669947 & 0.334974 \tabularnewline
228 & 0.604363 & 0.791274 & 0.395637 \tabularnewline
229 & 0.533897 & 0.932206 & 0.466103 \tabularnewline
230 & 0.483195 & 0.966391 & 0.516805 \tabularnewline
231 & 0.431867 & 0.863734 & 0.568133 \tabularnewline
232 & 0.464927 & 0.929854 & 0.535073 \tabularnewline
233 & 0.411467 & 0.822934 & 0.588533 \tabularnewline
234 & 0.379647 & 0.759295 & 0.620353 \tabularnewline
235 & 0.346156 & 0.692312 & 0.653844 \tabularnewline
236 & 0.308591 & 0.617182 & 0.691409 \tabularnewline
237 & 0.433883 & 0.867767 & 0.566117 \tabularnewline
238 & 0.333025 & 0.666051 & 0.666975 \tabularnewline
239 & 0.2666 & 0.533199 & 0.7334 \tabularnewline
240 & 0.191604 & 0.383208 & 0.808396 \tabularnewline
241 & 0.10641 & 0.212819 & 0.89359 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221816&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]23[/C][C]0.401863[/C][C]0.803726[/C][C]0.598137[/C][/ROW]
[ROW][C]24[/C][C]0.78149[/C][C]0.43702[/C][C]0.21851[/C][/ROW]
[ROW][C]25[/C][C]0.859235[/C][C]0.28153[/C][C]0.140765[/C][/ROW]
[ROW][C]26[/C][C]0.82917[/C][C]0.34166[/C][C]0.17083[/C][/ROW]
[ROW][C]27[/C][C]0.799357[/C][C]0.401286[/C][C]0.200643[/C][/ROW]
[ROW][C]28[/C][C]0.751174[/C][C]0.497652[/C][C]0.248826[/C][/ROW]
[ROW][C]29[/C][C]0.700383[/C][C]0.599235[/C][C]0.299617[/C][/ROW]
[ROW][C]30[/C][C]0.72474[/C][C]0.550519[/C][C]0.27526[/C][/ROW]
[ROW][C]31[/C][C]0.76917[/C][C]0.461659[/C][C]0.23083[/C][/ROW]
[ROW][C]32[/C][C]0.706841[/C][C]0.586318[/C][C]0.293159[/C][/ROW]
[ROW][C]33[/C][C]0.642444[/C][C]0.715112[/C][C]0.357556[/C][/ROW]
[ROW][C]34[/C][C]0.569307[/C][C]0.861385[/C][C]0.430693[/C][/ROW]
[ROW][C]35[/C][C]0.514306[/C][C]0.971389[/C][C]0.485694[/C][/ROW]
[ROW][C]36[/C][C]0.59857[/C][C]0.802859[/C][C]0.40143[/C][/ROW]
[ROW][C]37[/C][C]0.543594[/C][C]0.912813[/C][C]0.456406[/C][/ROW]
[ROW][C]38[/C][C]0.503793[/C][C]0.992415[/C][C]0.496207[/C][/ROW]
[ROW][C]39[/C][C]0.442826[/C][C]0.885652[/C][C]0.557174[/C][/ROW]
[ROW][C]40[/C][C]0.379907[/C][C]0.759813[/C][C]0.620093[/C][/ROW]
[ROW][C]41[/C][C]0.323665[/C][C]0.647331[/C][C]0.676335[/C][/ROW]
[ROW][C]42[/C][C]0.273253[/C][C]0.546507[/C][C]0.726747[/C][/ROW]
[ROW][C]43[/C][C]0.241764[/C][C]0.483528[/C][C]0.758236[/C][/ROW]
[ROW][C]44[/C][C]0.198506[/C][C]0.397012[/C][C]0.801494[/C][/ROW]
[ROW][C]45[/C][C]0.164418[/C][C]0.328837[/C][C]0.835582[/C][/ROW]
[ROW][C]46[/C][C]0.306762[/C][C]0.613525[/C][C]0.693238[/C][/ROW]
[ROW][C]47[/C][C]0.547798[/C][C]0.904403[/C][C]0.452202[/C][/ROW]
[ROW][C]48[/C][C]0.51541[/C][C]0.96918[/C][C]0.48459[/C][/ROW]
[ROW][C]49[/C][C]0.550912[/C][C]0.898177[/C][C]0.449088[/C][/ROW]
[ROW][C]50[/C][C]0.525351[/C][C]0.949298[/C][C]0.474649[/C][/ROW]
[ROW][C]51[/C][C]0.506838[/C][C]0.986324[/C][C]0.493162[/C][/ROW]
[ROW][C]52[/C][C]0.456114[/C][C]0.912229[/C][C]0.543886[/C][/ROW]
[ROW][C]53[/C][C]0.464201[/C][C]0.928403[/C][C]0.535799[/C][/ROW]
[ROW][C]54[/C][C]0.42174[/C][C]0.84348[/C][C]0.57826[/C][/ROW]
[ROW][C]55[/C][C]0.503067[/C][C]0.993867[/C][C]0.496933[/C][/ROW]
[ROW][C]56[/C][C]0.457952[/C][C]0.915904[/C][C]0.542048[/C][/ROW]
[ROW][C]57[/C][C]0.407396[/C][C]0.814792[/C][C]0.592604[/C][/ROW]
[ROW][C]58[/C][C]0.41025[/C][C]0.8205[/C][C]0.58975[/C][/ROW]
[ROW][C]59[/C][C]0.367855[/C][C]0.735711[/C][C]0.632145[/C][/ROW]
[ROW][C]60[/C][C]0.382112[/C][C]0.764225[/C][C]0.617888[/C][/ROW]
[ROW][C]61[/C][C]0.358334[/C][C]0.716667[/C][C]0.641666[/C][/ROW]
[ROW][C]62[/C][C]0.327671[/C][C]0.655341[/C][C]0.672329[/C][/ROW]
[ROW][C]63[/C][C]0.300052[/C][C]0.600103[/C][C]0.699948[/C][/ROW]
[ROW][C]64[/C][C]0.26549[/C][C]0.530981[/C][C]0.73451[/C][/ROW]
[ROW][C]65[/C][C]0.232503[/C][C]0.465005[/C][C]0.767497[/C][/ROW]
[ROW][C]66[/C][C]0.198893[/C][C]0.397785[/C][C]0.801107[/C][/ROW]
[ROW][C]67[/C][C]0.178593[/C][C]0.357186[/C][C]0.821407[/C][/ROW]
[ROW][C]68[/C][C]0.221706[/C][C]0.443412[/C][C]0.778294[/C][/ROW]
[ROW][C]69[/C][C]0.364426[/C][C]0.728852[/C][C]0.635574[/C][/ROW]
[ROW][C]70[/C][C]0.323088[/C][C]0.646176[/C][C]0.676912[/C][/ROW]
[ROW][C]71[/C][C]0.483125[/C][C]0.96625[/C][C]0.516875[/C][/ROW]
[ROW][C]72[/C][C]0.442239[/C][C]0.884478[/C][C]0.557761[/C][/ROW]
[ROW][C]73[/C][C]0.437335[/C][C]0.87467[/C][C]0.562665[/C][/ROW]
[ROW][C]74[/C][C]0.41894[/C][C]0.837881[/C][C]0.58106[/C][/ROW]
[ROW][C]75[/C][C]0.393562[/C][C]0.787124[/C][C]0.606438[/C][/ROW]
[ROW][C]76[/C][C]0.398693[/C][C]0.797385[/C][C]0.601307[/C][/ROW]
[ROW][C]77[/C][C]0.363[/C][C]0.726[/C][C]0.637[/C][/ROW]
[ROW][C]78[/C][C]0.334548[/C][C]0.669096[/C][C]0.665452[/C][/ROW]
[ROW][C]79[/C][C]0.365396[/C][C]0.730792[/C][C]0.634604[/C][/ROW]
[ROW][C]80[/C][C]0.357529[/C][C]0.715059[/C][C]0.642471[/C][/ROW]
[ROW][C]81[/C][C]0.352712[/C][C]0.705424[/C][C]0.647288[/C][/ROW]
[ROW][C]82[/C][C]0.315468[/C][C]0.630935[/C][C]0.684532[/C][/ROW]
[ROW][C]83[/C][C]0.279494[/C][C]0.558989[/C][C]0.720506[/C][/ROW]
[ROW][C]84[/C][C]0.245024[/C][C]0.490047[/C][C]0.754976[/C][/ROW]
[ROW][C]85[/C][C]0.233621[/C][C]0.467243[/C][C]0.766379[/C][/ROW]
[ROW][C]86[/C][C]0.203342[/C][C]0.406683[/C][C]0.796658[/C][/ROW]
[ROW][C]87[/C][C]0.175354[/C][C]0.350708[/C][C]0.824646[/C][/ROW]
[ROW][C]88[/C][C]0.153851[/C][C]0.307703[/C][C]0.846149[/C][/ROW]
[ROW][C]89[/C][C]0.13327[/C][C]0.26654[/C][C]0.86673[/C][/ROW]
[ROW][C]90[/C][C]0.1317[/C][C]0.2634[/C][C]0.8683[/C][/ROW]
[ROW][C]91[/C][C]0.114885[/C][C]0.22977[/C][C]0.885115[/C][/ROW]
[ROW][C]92[/C][C]0.0968857[/C][C]0.193771[/C][C]0.903114[/C][/ROW]
[ROW][C]93[/C][C]0.0810301[/C][C]0.16206[/C][C]0.91897[/C][/ROW]
[ROW][C]94[/C][C]0.0772913[/C][C]0.154583[/C][C]0.922709[/C][/ROW]
[ROW][C]95[/C][C]0.0720291[/C][C]0.144058[/C][C]0.927971[/C][/ROW]
[ROW][C]96[/C][C]0.0605547[/C][C]0.121109[/C][C]0.939445[/C][/ROW]
[ROW][C]97[/C][C]0.0594337[/C][C]0.118867[/C][C]0.940566[/C][/ROW]
[ROW][C]98[/C][C]0.0483918[/C][C]0.0967837[/C][C]0.951608[/C][/ROW]
[ROW][C]99[/C][C]0.0418792[/C][C]0.0837583[/C][C]0.958121[/C][/ROW]
[ROW][C]100[/C][C]0.0467629[/C][C]0.0935258[/C][C]0.953237[/C][/ROW]
[ROW][C]101[/C][C]0.0407979[/C][C]0.0815958[/C][C]0.959202[/C][/ROW]
[ROW][C]102[/C][C]0.0451478[/C][C]0.0902955[/C][C]0.954852[/C][/ROW]
[ROW][C]103[/C][C]0.0381442[/C][C]0.0762884[/C][C]0.961856[/C][/ROW]
[ROW][C]104[/C][C]0.0328897[/C][C]0.0657794[/C][C]0.96711[/C][/ROW]
[ROW][C]105[/C][C]0.0333032[/C][C]0.0666063[/C][C]0.966697[/C][/ROW]
[ROW][C]106[/C][C]0.0290074[/C][C]0.0580148[/C][C]0.970993[/C][/ROW]
[ROW][C]107[/C][C]0.023548[/C][C]0.0470959[/C][C]0.976452[/C][/ROW]
[ROW][C]108[/C][C]0.0226066[/C][C]0.0452131[/C][C]0.977393[/C][/ROW]
[ROW][C]109[/C][C]0.0188564[/C][C]0.0377128[/C][C]0.981144[/C][/ROW]
[ROW][C]110[/C][C]0.0155732[/C][C]0.0311463[/C][C]0.984427[/C][/ROW]
[ROW][C]111[/C][C]0.0122991[/C][C]0.0245982[/C][C]0.987701[/C][/ROW]
[ROW][C]112[/C][C]0.0107571[/C][C]0.0215141[/C][C]0.989243[/C][/ROW]
[ROW][C]113[/C][C]0.0103969[/C][C]0.0207939[/C][C]0.989603[/C][/ROW]
[ROW][C]114[/C][C]0.0174752[/C][C]0.0349505[/C][C]0.982525[/C][/ROW]
[ROW][C]115[/C][C]0.0154141[/C][C]0.0308282[/C][C]0.984586[/C][/ROW]
[ROW][C]116[/C][C]0.0147704[/C][C]0.0295407[/C][C]0.98523[/C][/ROW]
[ROW][C]117[/C][C]0.013478[/C][C]0.026956[/C][C]0.986522[/C][/ROW]
[ROW][C]118[/C][C]0.0124081[/C][C]0.0248162[/C][C]0.987592[/C][/ROW]
[ROW][C]119[/C][C]0.0101726[/C][C]0.0203451[/C][C]0.989827[/C][/ROW]
[ROW][C]120[/C][C]0.00893408[/C][C]0.0178682[/C][C]0.991066[/C][/ROW]
[ROW][C]121[/C][C]0.00698137[/C][C]0.0139627[/C][C]0.993019[/C][/ROW]
[ROW][C]122[/C][C]0.0124408[/C][C]0.0248817[/C][C]0.987559[/C][/ROW]
[ROW][C]123[/C][C]0.0120855[/C][C]0.024171[/C][C]0.987915[/C][/ROW]
[ROW][C]124[/C][C]0.0127942[/C][C]0.0255883[/C][C]0.987206[/C][/ROW]
[ROW][C]125[/C][C]0.0105282[/C][C]0.0210564[/C][C]0.989472[/C][/ROW]
[ROW][C]126[/C][C]0.00847524[/C][C]0.0169505[/C][C]0.991525[/C][/ROW]
[ROW][C]127[/C][C]0.00690025[/C][C]0.0138005[/C][C]0.9931[/C][/ROW]
[ROW][C]128[/C][C]0.00595354[/C][C]0.0119071[/C][C]0.994046[/C][/ROW]
[ROW][C]129[/C][C]0.00769684[/C][C]0.0153937[/C][C]0.992303[/C][/ROW]
[ROW][C]130[/C][C]0.00896182[/C][C]0.0179236[/C][C]0.991038[/C][/ROW]
[ROW][C]131[/C][C]0.0132485[/C][C]0.0264969[/C][C]0.986752[/C][/ROW]
[ROW][C]132[/C][C]0.0141738[/C][C]0.0283477[/C][C]0.985826[/C][/ROW]
[ROW][C]133[/C][C]0.016517[/C][C]0.033034[/C][C]0.983483[/C][/ROW]
[ROW][C]134[/C][C]0.0170381[/C][C]0.0340762[/C][C]0.982962[/C][/ROW]
[ROW][C]135[/C][C]0.0145933[/C][C]0.0291866[/C][C]0.985407[/C][/ROW]
[ROW][C]136[/C][C]0.0115187[/C][C]0.0230373[/C][C]0.988481[/C][/ROW]
[ROW][C]137[/C][C]0.00901263[/C][C]0.0180253[/C][C]0.990987[/C][/ROW]
[ROW][C]138[/C][C]0.0108455[/C][C]0.0216911[/C][C]0.989154[/C][/ROW]
[ROW][C]139[/C][C]0.0103324[/C][C]0.0206647[/C][C]0.989668[/C][/ROW]
[ROW][C]140[/C][C]0.0124005[/C][C]0.0248011[/C][C]0.987599[/C][/ROW]
[ROW][C]141[/C][C]0.0241684[/C][C]0.0483369[/C][C]0.975832[/C][/ROW]
[ROW][C]142[/C][C]0.0223133[/C][C]0.0446266[/C][C]0.977687[/C][/ROW]
[ROW][C]143[/C][C]0.0185827[/C][C]0.0371653[/C][C]0.981417[/C][/ROW]
[ROW][C]144[/C][C]0.0179423[/C][C]0.0358845[/C][C]0.982058[/C][/ROW]
[ROW][C]145[/C][C]0.041965[/C][C]0.0839299[/C][C]0.958035[/C][/ROW]
[ROW][C]146[/C][C]0.0431047[/C][C]0.0862095[/C][C]0.956895[/C][/ROW]
[ROW][C]147[/C][C]0.05738[/C][C]0.11476[/C][C]0.94262[/C][/ROW]
[ROW][C]148[/C][C]0.0479375[/C][C]0.095875[/C][C]0.952063[/C][/ROW]
[ROW][C]149[/C][C]0.0392905[/C][C]0.0785809[/C][C]0.96071[/C][/ROW]
[ROW][C]150[/C][C]0.0628279[/C][C]0.125656[/C][C]0.937172[/C][/ROW]
[ROW][C]151[/C][C]0.0621735[/C][C]0.124347[/C][C]0.937826[/C][/ROW]
[ROW][C]152[/C][C]0.061764[/C][C]0.123528[/C][C]0.938236[/C][/ROW]
[ROW][C]153[/C][C]0.115033[/C][C]0.230066[/C][C]0.884967[/C][/ROW]
[ROW][C]154[/C][C]0.10926[/C][C]0.218521[/C][C]0.89074[/C][/ROW]
[ROW][C]155[/C][C]0.111977[/C][C]0.223955[/C][C]0.888023[/C][/ROW]
[ROW][C]156[/C][C]0.096113[/C][C]0.192226[/C][C]0.903887[/C][/ROW]
[ROW][C]157[/C][C]0.0850777[/C][C]0.170155[/C][C]0.914922[/C][/ROW]
[ROW][C]158[/C][C]0.0726494[/C][C]0.145299[/C][C]0.927351[/C][/ROW]
[ROW][C]159[/C][C]0.0623128[/C][C]0.124626[/C][C]0.937687[/C][/ROW]
[ROW][C]160[/C][C]0.0560186[/C][C]0.112037[/C][C]0.943981[/C][/ROW]
[ROW][C]161[/C][C]0.0458958[/C][C]0.0917917[/C][C]0.954104[/C][/ROW]
[ROW][C]162[/C][C]0.0381518[/C][C]0.0763037[/C][C]0.961848[/C][/ROW]
[ROW][C]163[/C][C]0.0318461[/C][C]0.0636922[/C][C]0.968154[/C][/ROW]
[ROW][C]164[/C][C]0.0314071[/C][C]0.0628141[/C][C]0.968593[/C][/ROW]
[ROW][C]165[/C][C]0.0294719[/C][C]0.0589438[/C][C]0.970528[/C][/ROW]
[ROW][C]166[/C][C]0.025599[/C][C]0.0511979[/C][C]0.974401[/C][/ROW]
[ROW][C]167[/C][C]0.0203661[/C][C]0.0407321[/C][C]0.979634[/C][/ROW]
[ROW][C]168[/C][C]0.0281348[/C][C]0.0562696[/C][C]0.971865[/C][/ROW]
[ROW][C]169[/C][C]0.0306516[/C][C]0.0613033[/C][C]0.969348[/C][/ROW]
[ROW][C]170[/C][C]0.0296873[/C][C]0.0593746[/C][C]0.970313[/C][/ROW]
[ROW][C]171[/C][C]0.0255643[/C][C]0.0511285[/C][C]0.974436[/C][/ROW]
[ROW][C]172[/C][C]0.0205848[/C][C]0.0411696[/C][C]0.979415[/C][/ROW]
[ROW][C]173[/C][C]0.0197232[/C][C]0.0394464[/C][C]0.980277[/C][/ROW]
[ROW][C]174[/C][C]0.024383[/C][C]0.0487661[/C][C]0.975617[/C][/ROW]
[ROW][C]175[/C][C]0.0327127[/C][C]0.0654255[/C][C]0.967287[/C][/ROW]
[ROW][C]176[/C][C]0.0299067[/C][C]0.0598134[/C][C]0.970093[/C][/ROW]
[ROW][C]177[/C][C]0.0251535[/C][C]0.0503069[/C][C]0.974847[/C][/ROW]
[ROW][C]178[/C][C]0.0198021[/C][C]0.0396042[/C][C]0.980198[/C][/ROW]
[ROW][C]179[/C][C]0.0161963[/C][C]0.0323927[/C][C]0.983804[/C][/ROW]
[ROW][C]180[/C][C]0.0134302[/C][C]0.0268604[/C][C]0.98657[/C][/ROW]
[ROW][C]181[/C][C]0.0107912[/C][C]0.0215824[/C][C]0.989209[/C][/ROW]
[ROW][C]182[/C][C]0.00840112[/C][C]0.0168022[/C][C]0.991599[/C][/ROW]
[ROW][C]183[/C][C]0.00799633[/C][C]0.0159927[/C][C]0.992004[/C][/ROW]
[ROW][C]184[/C][C]0.00622983[/C][C]0.0124597[/C][C]0.99377[/C][/ROW]
[ROW][C]185[/C][C]0.176901[/C][C]0.353801[/C][C]0.823099[/C][/ROW]
[ROW][C]186[/C][C]0.163038[/C][C]0.326075[/C][C]0.836962[/C][/ROW]
[ROW][C]187[/C][C]0.184777[/C][C]0.369554[/C][C]0.815223[/C][/ROW]
[ROW][C]188[/C][C]0.208691[/C][C]0.417382[/C][C]0.791309[/C][/ROW]
[ROW][C]189[/C][C]0.179536[/C][C]0.359071[/C][C]0.820464[/C][/ROW]
[ROW][C]190[/C][C]0.178798[/C][C]0.357596[/C][C]0.821202[/C][/ROW]
[ROW][C]191[/C][C]0.179789[/C][C]0.359577[/C][C]0.820211[/C][/ROW]
[ROW][C]192[/C][C]0.168504[/C][C]0.337008[/C][C]0.831496[/C][/ROW]
[ROW][C]193[/C][C]0.176376[/C][C]0.352751[/C][C]0.823624[/C][/ROW]
[ROW][C]194[/C][C]0.172624[/C][C]0.345248[/C][C]0.827376[/C][/ROW]
[ROW][C]195[/C][C]0.174224[/C][C]0.348447[/C][C]0.825776[/C][/ROW]
[ROW][C]196[/C][C]0.149251[/C][C]0.298502[/C][C]0.850749[/C][/ROW]
[ROW][C]197[/C][C]0.172403[/C][C]0.344807[/C][C]0.827597[/C][/ROW]
[ROW][C]198[/C][C]0.149328[/C][C]0.298655[/C][C]0.850672[/C][/ROW]
[ROW][C]199[/C][C]0.145986[/C][C]0.291972[/C][C]0.854014[/C][/ROW]
[ROW][C]200[/C][C]0.13308[/C][C]0.266161[/C][C]0.86692[/C][/ROW]
[ROW][C]201[/C][C]0.150573[/C][C]0.301145[/C][C]0.849427[/C][/ROW]
[ROW][C]202[/C][C]0.126989[/C][C]0.253978[/C][C]0.873011[/C][/ROW]
[ROW][C]203[/C][C]0.161645[/C][C]0.323291[/C][C]0.838355[/C][/ROW]
[ROW][C]204[/C][C]0.165998[/C][C]0.331997[/C][C]0.834002[/C][/ROW]
[ROW][C]205[/C][C]0.161402[/C][C]0.322805[/C][C]0.838598[/C][/ROW]
[ROW][C]206[/C][C]0.134037[/C][C]0.268074[/C][C]0.865963[/C][/ROW]
[ROW][C]207[/C][C]0.114251[/C][C]0.228503[/C][C]0.885749[/C][/ROW]
[ROW][C]208[/C][C]0.0931786[/C][C]0.186357[/C][C]0.906821[/C][/ROW]
[ROW][C]209[/C][C]0.134156[/C][C]0.268313[/C][C]0.865844[/C][/ROW]
[ROW][C]210[/C][C]0.111104[/C][C]0.222207[/C][C]0.888896[/C][/ROW]
[ROW][C]211[/C][C]0.115699[/C][C]0.231399[/C][C]0.884301[/C][/ROW]
[ROW][C]212[/C][C]0.117125[/C][C]0.23425[/C][C]0.882875[/C][/ROW]
[ROW][C]213[/C][C]0.158669[/C][C]0.317339[/C][C]0.841331[/C][/ROW]
[ROW][C]214[/C][C]0.545095[/C][C]0.90981[/C][C]0.454905[/C][/ROW]
[ROW][C]215[/C][C]0.528509[/C][C]0.942982[/C][C]0.471491[/C][/ROW]
[ROW][C]216[/C][C]0.481091[/C][C]0.962182[/C][C]0.518909[/C][/ROW]
[ROW][C]217[/C][C]0.494762[/C][C]0.989524[/C][C]0.505238[/C][/ROW]
[ROW][C]218[/C][C]0.451969[/C][C]0.903938[/C][C]0.548031[/C][/ROW]
[ROW][C]219[/C][C]0.423207[/C][C]0.846414[/C][C]0.576793[/C][/ROW]
[ROW][C]220[/C][C]0.393362[/C][C]0.786724[/C][C]0.606638[/C][/ROW]
[ROW][C]221[/C][C]0.608552[/C][C]0.782895[/C][C]0.391448[/C][/ROW]
[ROW][C]222[/C][C]0.702704[/C][C]0.594591[/C][C]0.297296[/C][/ROW]
[ROW][C]223[/C][C]0.661006[/C][C]0.677989[/C][C]0.338994[/C][/ROW]
[ROW][C]224[/C][C]0.62161[/C][C]0.75678[/C][C]0.37839[/C][/ROW]
[ROW][C]225[/C][C]0.592072[/C][C]0.815856[/C][C]0.407928[/C][/ROW]
[ROW][C]226[/C][C]0.569067[/C][C]0.861866[/C][C]0.430933[/C][/ROW]
[ROW][C]227[/C][C]0.665026[/C][C]0.669947[/C][C]0.334974[/C][/ROW]
[ROW][C]228[/C][C]0.604363[/C][C]0.791274[/C][C]0.395637[/C][/ROW]
[ROW][C]229[/C][C]0.533897[/C][C]0.932206[/C][C]0.466103[/C][/ROW]
[ROW][C]230[/C][C]0.483195[/C][C]0.966391[/C][C]0.516805[/C][/ROW]
[ROW][C]231[/C][C]0.431867[/C][C]0.863734[/C][C]0.568133[/C][/ROW]
[ROW][C]232[/C][C]0.464927[/C][C]0.929854[/C][C]0.535073[/C][/ROW]
[ROW][C]233[/C][C]0.411467[/C][C]0.822934[/C][C]0.588533[/C][/ROW]
[ROW][C]234[/C][C]0.379647[/C][C]0.759295[/C][C]0.620353[/C][/ROW]
[ROW][C]235[/C][C]0.346156[/C][C]0.692312[/C][C]0.653844[/C][/ROW]
[ROW][C]236[/C][C]0.308591[/C][C]0.617182[/C][C]0.691409[/C][/ROW]
[ROW][C]237[/C][C]0.433883[/C][C]0.867767[/C][C]0.566117[/C][/ROW]
[ROW][C]238[/C][C]0.333025[/C][C]0.666051[/C][C]0.666975[/C][/ROW]
[ROW][C]239[/C][C]0.2666[/C][C]0.533199[/C][C]0.7334[/C][/ROW]
[ROW][C]240[/C][C]0.191604[/C][C]0.383208[/C][C]0.808396[/C][/ROW]
[ROW][C]241[/C][C]0.10641[/C][C]0.212819[/C][C]0.89359[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221816&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221816&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
230.4018630.8037260.598137
240.781490.437020.21851
250.8592350.281530.140765
260.829170.341660.17083
270.7993570.4012860.200643
280.7511740.4976520.248826
290.7003830.5992350.299617
300.724740.5505190.27526
310.769170.4616590.23083
320.7068410.5863180.293159
330.6424440.7151120.357556
340.5693070.8613850.430693
350.5143060.9713890.485694
360.598570.8028590.40143
370.5435940.9128130.456406
380.5037930.9924150.496207
390.4428260.8856520.557174
400.3799070.7598130.620093
410.3236650.6473310.676335
420.2732530.5465070.726747
430.2417640.4835280.758236
440.1985060.3970120.801494
450.1644180.3288370.835582
460.3067620.6135250.693238
470.5477980.9044030.452202
480.515410.969180.48459
490.5509120.8981770.449088
500.5253510.9492980.474649
510.5068380.9863240.493162
520.4561140.9122290.543886
530.4642010.9284030.535799
540.421740.843480.57826
550.5030670.9938670.496933
560.4579520.9159040.542048
570.4073960.8147920.592604
580.410250.82050.58975
590.3678550.7357110.632145
600.3821120.7642250.617888
610.3583340.7166670.641666
620.3276710.6553410.672329
630.3000520.6001030.699948
640.265490.5309810.73451
650.2325030.4650050.767497
660.1988930.3977850.801107
670.1785930.3571860.821407
680.2217060.4434120.778294
690.3644260.7288520.635574
700.3230880.6461760.676912
710.4831250.966250.516875
720.4422390.8844780.557761
730.4373350.874670.562665
740.418940.8378810.58106
750.3935620.7871240.606438
760.3986930.7973850.601307
770.3630.7260.637
780.3345480.6690960.665452
790.3653960.7307920.634604
800.3575290.7150590.642471
810.3527120.7054240.647288
820.3154680.6309350.684532
830.2794940.5589890.720506
840.2450240.4900470.754976
850.2336210.4672430.766379
860.2033420.4066830.796658
870.1753540.3507080.824646
880.1538510.3077030.846149
890.133270.266540.86673
900.13170.26340.8683
910.1148850.229770.885115
920.09688570.1937710.903114
930.08103010.162060.91897
940.07729130.1545830.922709
950.07202910.1440580.927971
960.06055470.1211090.939445
970.05943370.1188670.940566
980.04839180.09678370.951608
990.04187920.08375830.958121
1000.04676290.09352580.953237
1010.04079790.08159580.959202
1020.04514780.09029550.954852
1030.03814420.07628840.961856
1040.03288970.06577940.96711
1050.03330320.06660630.966697
1060.02900740.05801480.970993
1070.0235480.04709590.976452
1080.02260660.04521310.977393
1090.01885640.03771280.981144
1100.01557320.03114630.984427
1110.01229910.02459820.987701
1120.01075710.02151410.989243
1130.01039690.02079390.989603
1140.01747520.03495050.982525
1150.01541410.03082820.984586
1160.01477040.02954070.98523
1170.0134780.0269560.986522
1180.01240810.02481620.987592
1190.01017260.02034510.989827
1200.008934080.01786820.991066
1210.006981370.01396270.993019
1220.01244080.02488170.987559
1230.01208550.0241710.987915
1240.01279420.02558830.987206
1250.01052820.02105640.989472
1260.008475240.01695050.991525
1270.006900250.01380050.9931
1280.005953540.01190710.994046
1290.007696840.01539370.992303
1300.008961820.01792360.991038
1310.01324850.02649690.986752
1320.01417380.02834770.985826
1330.0165170.0330340.983483
1340.01703810.03407620.982962
1350.01459330.02918660.985407
1360.01151870.02303730.988481
1370.009012630.01802530.990987
1380.01084550.02169110.989154
1390.01033240.02066470.989668
1400.01240050.02480110.987599
1410.02416840.04833690.975832
1420.02231330.04462660.977687
1430.01858270.03716530.981417
1440.01794230.03588450.982058
1450.0419650.08392990.958035
1460.04310470.08620950.956895
1470.057380.114760.94262
1480.04793750.0958750.952063
1490.03929050.07858090.96071
1500.06282790.1256560.937172
1510.06217350.1243470.937826
1520.0617640.1235280.938236
1530.1150330.2300660.884967
1540.109260.2185210.89074
1550.1119770.2239550.888023
1560.0961130.1922260.903887
1570.08507770.1701550.914922
1580.07264940.1452990.927351
1590.06231280.1246260.937687
1600.05601860.1120370.943981
1610.04589580.09179170.954104
1620.03815180.07630370.961848
1630.03184610.06369220.968154
1640.03140710.06281410.968593
1650.02947190.05894380.970528
1660.0255990.05119790.974401
1670.02036610.04073210.979634
1680.02813480.05626960.971865
1690.03065160.06130330.969348
1700.02968730.05937460.970313
1710.02556430.05112850.974436
1720.02058480.04116960.979415
1730.01972320.03944640.980277
1740.0243830.04876610.975617
1750.03271270.06542550.967287
1760.02990670.05981340.970093
1770.02515350.05030690.974847
1780.01980210.03960420.980198
1790.01619630.03239270.983804
1800.01343020.02686040.98657
1810.01079120.02158240.989209
1820.008401120.01680220.991599
1830.007996330.01599270.992004
1840.006229830.01245970.99377
1850.1769010.3538010.823099
1860.1630380.3260750.836962
1870.1847770.3695540.815223
1880.2086910.4173820.791309
1890.1795360.3590710.820464
1900.1787980.3575960.821202
1910.1797890.3595770.820211
1920.1685040.3370080.831496
1930.1763760.3527510.823624
1940.1726240.3452480.827376
1950.1742240.3484470.825776
1960.1492510.2985020.850749
1970.1724030.3448070.827597
1980.1493280.2986550.850672
1990.1459860.2919720.854014
2000.133080.2661610.86692
2010.1505730.3011450.849427
2020.1269890.2539780.873011
2030.1616450.3232910.838355
2040.1659980.3319970.834002
2050.1614020.3228050.838598
2060.1340370.2680740.865963
2070.1142510.2285030.885749
2080.09317860.1863570.906821
2090.1341560.2683130.865844
2100.1111040.2222070.888896
2110.1156990.2313990.884301
2120.1171250.234250.882875
2130.1586690.3173390.841331
2140.5450950.909810.454905
2150.5285090.9429820.471491
2160.4810910.9621820.518909
2170.4947620.9895240.505238
2180.4519690.9039380.548031
2190.4232070.8464140.576793
2200.3933620.7867240.606638
2210.6085520.7828950.391448
2220.7027040.5945910.297296
2230.6610060.6779890.338994
2240.621610.756780.37839
2250.5920720.8158560.407928
2260.5690670.8618660.430933
2270.6650260.6699470.334974
2280.6043630.7912740.395637
2290.5338970.9322060.466103
2300.4831950.9663910.516805
2310.4318670.8637340.568133
2320.4649270.9298540.535073
2330.4114670.8229340.588533
2340.3796470.7592950.620353
2350.3461560.6923120.653844
2360.3085910.6171820.691409
2370.4338830.8677670.566117
2380.3330250.6660510.666975
2390.26660.5331990.7334
2400.1916040.3832080.808396
2410.106410.2128190.89359






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level490.223744NOK
10% type I error level750.342466NOK

\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 & 49 & 0.223744 & NOK \tabularnewline
10% type I error level & 75 & 0.342466 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221816&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]49[/C][C]0.223744[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]75[/C][C]0.342466[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221816&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221816&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 level490.223744NOK
10% type I error level750.342466NOK


Figures (Output of Computation)

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

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