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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 04 Nov 2013 02:18:26 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/04/t1383549546qors6rmrq59npkg.htm/, Retrieved Sat, 27 Apr 2024 22:47:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=222037, Retrieved Sat, 27 Apr 2024 22:47:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact642

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-11-04 07:18:26] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
- R  D    [Multiple Regression] [Workshop 7] [2013-11-20 22:08:24] [f12bfb29749f0c3f544bf278d0782c85]
-   PD    [Multiple Regression] [Workshop 7] [2013-11-20 22:28:31] [f12bfb29749f0c3f544bf278d0782c85]
- RM      [Multiple Regression] [Workshop 7] [2013-11-20 22:55:14] [f12bfb29749f0c3f544bf278d0782c85]
-  MPD    [Multiple Regression] [] [2014-11-04 18:35:38] [272d52cebbec48285fb11674f7e19cee]
-  MPD    [Multiple Regression] [] [2014-11-09 14:03:23] [1cdaa45029ce10ae2dbbd5f1b3428ba0]
-  MPD    [Multiple Regression] [] [2014-11-09 14:23:04] [1cdaa45029ce10ae2dbbd5f1b3428ba0]
- RMPD    [Multiple Regression] [WS7 (depression)] [2014-11-10 13:12:39] [7c87d1c7801dd67c2a0c90c2b6a05b3c]
- RMPD    [Multiple Regression] [WS7 (connected)] [2014-11-10 14:07:06] [7c87d1c7801dd67c2a0c90c2b6a05b3c]
- RMPD    [Multiple Regression] [WS7 (learning)] [2014-11-10 14:32:18] [7c87d1c7801dd67c2a0c90c2b6a05b3c]
- RM D    [Multiple Regression] [WS7] [2014-11-11 10:39:43] [02abc6ae7a9692fad1b511df4cb1357e]
- RMPD    [Central Tendency] [WS7] [2014-11-11 11:05:23] [02abc6ae7a9692fad1b511df4cb1357e]
- RMPD    [Bootstrap Plot - Central Tendency] [WS7] [2014-11-11 11:08:52] [02abc6ae7a9692fad1b511df4cb1357e]
-  MPD    [Multiple Regression] [WS7] [2014-11-11 12:50:58] [02abc6ae7a9692fad1b511df4cb1357e]
-  MPD    [Multiple Regression] [WS7] [2014-11-11 12:56:58] [02abc6ae7a9692fad1b511df4cb1357e]
-  MPD    [Multiple Regression] [WS7] [2014-11-11 13:01:44] [02abc6ae7a9692fad1b511df4cb1357e]
-  MPD    [Multiple Regression] [WS7] [2014-11-11 13:04:36] [02abc6ae7a9692fad1b511df4cb1357e]
-  M D    [Multiple Regression] [] [2014-11-11 16:34:00] [3f7e537763d373cc2ab5235e2041342a]
-  MPD    [Multiple Regression] [] [2014-11-11 17:00:38] [67894a4ff6098ffac356bc81e6028257]
- RMPD    [Multiple Regression] [] [2014-11-11 18:57:37] [67894a4ff6098ffac356bc81e6028257]
- RM      [Multiple Regression] [WS 7 - 1] [2014-11-11 18:56:49] [cd1b7e95165bf631f3d18465885d954c]
- RM      [Multiple Regression] [WS 7 - 2] [2014-11-11 19:28:03] [cd1b7e95165bf631f3d18465885d954c]
- RMPD    [Multiple Regression] [] [2014-11-11 20:27:31] [67894a4ff6098ffac356bc81e6028257]
- RMPD    [Skewness and Kurtosis Test] [ws7 II] [2014-11-11 23:18:26] [f176b1b29c5f5a4f79e289091c8f32ca]
- RMPD    [Box-Cox Normality Plot] [WS7 III] [2014-11-11 23:22:48] [f176b1b29c5f5a4f79e289091c8f32ca]
- RM D    [Multiple Regression] [WS7 task1] [2014-11-12 07:37:18] [46c7ebd23dbdec306a09830d8b7528e7]
- RM      [Multiple Regression] [ws7 v1] [2014-11-12 10:07:03] [e3727f74ca0896859afbe865e40a3465]
- RM D    [Multiple Regression] [] [2014-11-12 12:01:57] [394a9522c47495260fca596e959e6202]
- RM D    [Multiple Regression] [ws7 1] [2014-11-12 12:13:01] [15866c21ed6246d5efde5ff3ba421193]
- RM      [Multiple Regression] [] [2014-11-12 12:15:00] [6adb05d815951664662021960079d6d2]
- RM D    [Multiple Regression] [] [2014-11-12 12:15:08] [394a9522c47495260fca596e959e6202]
- RM      [Multiple Regression] [] [2014-11-12 12:23:38] [6795cd14e59cd8fafcdf800c40b889d9]
- RMPD    [Multiple Regression] [Multiple linear r...] [2014-11-12 12:23:57] [81f624c2f0b20a2549c93e7c3dccf981]
- RM      [Multiple Regression] [ws7 2] [2014-11-12 12:25:30] [15866c21ed6246d5efde5ff3ba421193]
- RM D    [Multiple Regression] [MLR] [2014-11-12 12:32:08] [861cf3a5e9222e55170c5866e1781f14]
- RM      [Multiple Regression] [] [2014-11-12 12:35:44] [6adb05d815951664662021960079d6d2]
- RM D    [Multiple Regression] [workshop 7 bereke...] [2014-11-12 12:38:47] [b007041690f75f30ec26eb43925b7b35]
- RMPD      [Testing Mean with unknown Variance - Critical Value] [1] [2015-01-15 12:46:36] [b007041690f75f30ec26eb43925b7b35]
- RMPD      [Skewness and Kurtosis Test] [2] [2015-01-15 12:47:11] [b007041690f75f30ec26eb43925b7b35]
- RMPD      [Central Tendency] [3] [2015-01-15 12:48:10] [b007041690f75f30ec26eb43925b7b35]
- RMPD      [Two-Way ANOVA] [4] [2015-01-15 12:52:30] [b007041690f75f30ec26eb43925b7b35]
- RMPD      [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [5] [2015-01-15 12:56:34] [b007041690f75f30ec26eb43925b7b35]
- RM D    [Multiple Regression] [] [2014-11-12 12:40:13] [394a9522c47495260fca596e959e6202]
- RM      [Multiple Regression] [ws7 3] [2014-11-12 12:40:23] [15866c21ed6246d5efde5ff3ba421193]
- RM      [Multiple Regression] [WS 7 T1] [2014-11-12 12:38:58] [fa1b8827d7de91b8b87087311d3d9fa1]
- RMPD      [Survey Scores] [Survey score I2] [2014-12-09 12:30:49] [fa1b8827d7de91b8b87087311d3d9fa1]
- RMPD      [Survey Scores] [Surve score I3] [2014-12-09 13:07:59] [fa1b8827d7de91b8b87087311d3d9fa1]
- RMPD      [Survey Scores] [Survey scale E3] [2014-12-09 13:17:49] [fa1b8827d7de91b8b87087311d3d9fa1]
- RMPD      [Survey Scores] [Survey score E3] [2014-12-09 13:30:27] [fa1b8827d7de91b8b87087311d3d9fa1]

[Truncated]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time18 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 18 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222037&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]18 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222037&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222037&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 time18 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 14.6535 + 0.0142012Connected[t] + 0.0102798Separate[t] + 0.11286Learning[t] -0.00764117Software[t] -0.376277Depression[t] + 0.0230057Sport1[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  14.6535 +  0.0142012Connected[t] +  0.0102798Separate[t] +  0.11286Learning[t] -0.00764117Software[t] -0.376277Depression[t] +  0.0230057Sport1[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222037&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  14.6535 +  0.0142012Connected[t] +  0.0102798Separate[t] +  0.11286Learning[t] -0.00764117Software[t] -0.376277Depression[t] +  0.0230057Sport1[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222037&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222037&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
Happiness[t] = + 14.6535 + 0.0142012Connected[t] + 0.0102798Separate[t] + 0.11286Learning[t] -0.00764117Software[t] -0.376277Depression[t] + 0.0230057Sport1[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)14.65351.831857.9994.29315e-142.14657e-14
Connected0.01420120.03721840.38160.70310.35155
Separate0.01027980.03825840.26870.7883810.394191
Learning0.112860.06652071.6970.09097960.0454898
Software-0.007641170.0687789-0.11110.9116260.455813
Depression-0.3762770.0388242-9.6923.92391e-191.96196e-19
Sport10.02300570.01275031.8040.07235030.0361751

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 14.6535 & 1.83185 & 7.999 & 4.29315e-14 & 2.14657e-14 \tabularnewline
Connected & 0.0142012 & 0.0372184 & 0.3816 & 0.7031 & 0.35155 \tabularnewline
Separate & 0.0102798 & 0.0382584 & 0.2687 & 0.788381 & 0.394191 \tabularnewline
Learning & 0.11286 & 0.0665207 & 1.697 & 0.0909796 & 0.0454898 \tabularnewline
Software & -0.00764117 & 0.0687789 & -0.1111 & 0.911626 & 0.455813 \tabularnewline
Depression & -0.376277 & 0.0388242 & -9.692 & 3.92391e-19 & 1.96196e-19 \tabularnewline
Sport1 & 0.0230057 & 0.0127503 & 1.804 & 0.0723503 & 0.0361751 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222037&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]14.6535[/C][C]1.83185[/C][C]7.999[/C][C]4.29315e-14[/C][C]2.14657e-14[/C][/ROW]
[ROW][C]Connected[/C][C]0.0142012[/C][C]0.0372184[/C][C]0.3816[/C][C]0.7031[/C][C]0.35155[/C][/ROW]
[ROW][C]Separate[/C][C]0.0102798[/C][C]0.0382584[/C][C]0.2687[/C][C]0.788381[/C][C]0.394191[/C][/ROW]
[ROW][C]Learning[/C][C]0.11286[/C][C]0.0665207[/C][C]1.697[/C][C]0.0909796[/C][C]0.0454898[/C][/ROW]
[ROW][C]Software[/C][C]-0.00764117[/C][C]0.0687789[/C][C]-0.1111[/C][C]0.911626[/C][C]0.455813[/C][/ROW]
[ROW][C]Depression[/C][C]-0.376277[/C][C]0.0388242[/C][C]-9.692[/C][C]3.92391e-19[/C][C]1.96196e-19[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0230057[/C][C]0.0127503[/C][C]1.804[/C][C]0.0723503[/C][C]0.0361751[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222037&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222037&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)14.65351.831857.9994.29315e-142.14657e-14
Connected0.01420120.03721840.38160.70310.35155
Separate0.01027980.03825840.26870.7883810.394191
Learning0.112860.06652071.6970.09097960.0454898
Software-0.007641170.0687789-0.11110.9116260.455813
Depression-0.3762770.0388242-9.6923.92391e-191.96196e-19
Sport10.02300570.01275031.8040.07235030.0361751






Multiple Linear Regression - Regression Statistics
Multiple R0.6025
R-squared0.363006
Adjusted R-squared0.348135
F-TEST (value)24.4096
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01736
Sum Squared Residuals1045.92

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.6025 \tabularnewline
R-squared & 0.363006 \tabularnewline
Adjusted R-squared & 0.348135 \tabularnewline
F-TEST (value) & 24.4096 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 257 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.01736 \tabularnewline
Sum Squared Residuals & 1045.92 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222037&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.6025[/C][/ROW]
[ROW][C]R-squared[/C][C]0.363006[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.348135[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]24.4096[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]257[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.01736[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1045.92[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222037&T=3

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

Multiple Linear Regression - Regression Statistics
Multiple R0.6025
R-squared0.363006
Adjusted R-squared0.348135
F-TEST (value)24.4096
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01736
Sum Squared Residuals1045.92






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.70580.294153
21815.02842.97156
31113.7196-2.71955
41214.1061-2.10608
51610.8445.15598
61814.11853.88145
71410.51993.48012
81414.7937-0.793748
91514.95250.0474647
101514.05050.949459
111715.29581.70415
121915.46043.53959
131013.1642-3.16424
141613.29412.70588
151815.54522.45478
161413.11480.885167
171413.56770.432262
181715.63471.36526
191415.255-1.255
201613.57072.42932
211815.11262.88737
221113.423-2.42299
231414.37-0.36997
241213.322-1.32201
251715.20271.79733
26915.838-6.83795
271614.86331.13673
281413.03170.968342
291513.7021.29799
301113.629-2.62899
311615.46760.532419
321312.25720.742768
331714.87192.12812
341515.0242-0.0241935
351413.74390.256096
361615.14550.854528
37910.3677-1.36766
381514.11040.889595
391715.0991.90098
401315.0437-2.04375
411515.5532-0.553176
421613.42152.57853
431615.89680.103225
441212.9218-0.921825
451514.4330.567044
461113.3613-2.36129
471515.1836-0.183641
481514.66690.333117
491713.33543.66465
501314.5968-1.59683
511615.0910.909003
521413.19350.806532
531111.3862-0.386175
541213.3919-1.39188
551213.7247-1.72474
561513.36541.63465
571614.08171.91825
581515.2838-0.283804
591215.0745-3.07451
601213.1957-1.19565
61810.362-2.36197
621314.5128-1.51284
631114.5201-3.52005
641412.87791.12206
651513.51981.48021
661015.0516-5.05159
671112.5707-1.57071
681214.4686-2.46861
691513.43891.56108
701513.56451.43552
711413.28050.719528
721612.57853.42149
731514.43360.566379
741515.3637-0.363746
751314.9214-1.9214
761212.0568-0.056789
771713.98453.01548
781312.36740.632589
791513.62511.37487
801315.0264-2.02638
811514.88470.115316
821515.4919-0.491874
831614.28351.71652
841514.20740.792612
851414.05-0.0500028
861513.93921.06084
871414.2578-0.257791
881312.70650.293489
89710.3949-3.39489
901713.53723.46282
911312.89590.104144
921514.16590.834079
931413.23930.760705
941313.8862-0.886211
951615.00820.991821
961212.8121-0.812128
971414.8616-0.861605
981714.96692.03306
991514.96730.0326958
1001715.24771.75233
1011212.9194-0.919433
1021615.12780.872158
1031114.384-3.38395
1041513.04181.95822
105911.3411-2.34112
1061614.98931.01075
1071512.96372.0363
1081012.8444-2.8444
109109.024360.975645
1101513.83071.16927
1111113.19-2.19003
1121315.2494-2.24943
1131412.06041.93964
1141814.03953.96052
1151615.65580.344235
1161412.98851.01153
1171413.71620.283773
1181415.066-1.06596
1191413.70360.296354
1201212.4838-0.483775
1211413.55830.441724
1221514.8780.121994
1231516.0066-1.00658
1241514.61740.382647
1251314.8025-1.80252
1261716.21310.786913
1271715.45351.54651
1281914.84084.15924
1291513.52491.47515
1301314.6709-1.67088
131910.4175-1.41748
1321515.3552-0.355202
1331512.46682.53319
1341514.2450.754977
1351613.69492.30513
136119.263641.73636
1371413.28650.713535
1381111.8263-0.826256
1391514.12660.873435
1401313.6983-0.698291
1411514.68160.318378
1421613.74862.25138
1431414.7065-0.706501
1441514.3080.692002
1451614.51621.48385
1461614.55081.44925
1471113.399-2.39905
1481214.7271-2.72706
149911.4081-2.40806
1501614.10931.89067
1511312.64460.355387
1521615.51090.489124
1531214.4525-2.45246
154911.4997-2.4997
1551311.52971.47025
1561312.89590.104144
1571413.22910.770858
1581914.84084.15924
1591315.733-2.73299
1601211.95130.0487413
1611312.47940.520571
162109.182710.817289
1631413.24980.750211
1641611.7054.29504
1651012.0372-2.03717
166118.958142.04186
1671414.1939-0.19388
1681212.864-0.864039
169912.7685-3.7685
170912.0378-3.03779
1711110.55350.446489
1721614.40031.59975
173914.1526-5.15257
1741311.24521.75479
1751613.482.51998
1761315.4845-2.48453
177912.3553-3.35533
1781211.48790.512109
1791614.69471.30535
1801113.2936-2.29359
1811414.3521-0.352145
1821314.8094-1.80944
1831514.96490.0351127
1841415.201-1.20099
1851613.97342.02659
1861311.79131.20875
1871413.78340.216629
1881514.3130.686974
1891312.50140.498628
1901110.18280.817199
1911112.949-1.94897
1921415.2811-1.28106
1931512.72182.27819
1941112.6585-1.65853
1951513.21621.7838
1961214.2659-2.26586
1971411.86022.1398
1981413.57390.426097
199811.2497-3.24974
2001313.9456-0.945592
201912.2927-3.29269
2021513.87841.12158
2031714.21412.78591
2041312.70240.297647
2051514.62080.379211
2061513.92611.07392
2071414.6928-0.692765
2081612.78683.21317
2091313.0115-0.0115483
2101614.50921.49078
211911.8139-2.81386
2121614.74411.25588
2131112.3462-1.34621
2141013.9661-3.96611
2151112.3691-1.36908
2161513.41551.58447
2171715.13291.86706
2181414.4546-0.45464
219810.0558-2.05585
2201513.78551.21455
2211114.0984-3.09837
2221613.88592.11414
2231012.312-2.31201
2241514.97820.0218416
22599.87723-0.877228
2261614.36671.63328
2271914.02964.97042
2281213.917-1.91696
22989.51227-1.51227
2301113.5005-2.50048
2311413.98420.0158494
232912.0859-3.08591
2331515.1652-0.165203
2341312.75920.240808
2351615.1260.874019
2361112.991-1.99099
2371211.24470.755342
2381313.0765-0.0764699
2391014.6154-4.61544
2401113.7035-2.70354
2411214.9208-2.92081
242810.8506-2.85065
2431211.75850.241454
2441212.4091-0.409056
2451513.73271.2673
2461110.78020.219823
2471312.89920.100763
248148.911415.08859
2491010.1952-0.195174
2501211.64170.358255
2511512.97372.02625
2521311.92391.07606
2531314.3171-1.31709
2541313.9529-0.952895
2551211.96380.0362316
2561212.8688-0.868792
257911.0686-2.06858
258911.595-2.59497
2591512.80882.19119
2601014.7867-4.78671
2611413.91120.0887831
2621513.72581.2742
26379.92786-2.92786
2641414.0466-0.0466467

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 13.7058 & 0.294153 \tabularnewline
2 & 18 & 15.0284 & 2.97156 \tabularnewline
3 & 11 & 13.7196 & -2.71955 \tabularnewline
4 & 12 & 14.1061 & -2.10608 \tabularnewline
5 & 16 & 10.844 & 5.15598 \tabularnewline
6 & 18 & 14.1185 & 3.88145 \tabularnewline
7 & 14 & 10.5199 & 3.48012 \tabularnewline
8 & 14 & 14.7937 & -0.793748 \tabularnewline
9 & 15 & 14.9525 & 0.0474647 \tabularnewline
10 & 15 & 14.0505 & 0.949459 \tabularnewline
11 & 17 & 15.2958 & 1.70415 \tabularnewline
12 & 19 & 15.4604 & 3.53959 \tabularnewline
13 & 10 & 13.1642 & -3.16424 \tabularnewline
14 & 16 & 13.2941 & 2.70588 \tabularnewline
15 & 18 & 15.5452 & 2.45478 \tabularnewline
16 & 14 & 13.1148 & 0.885167 \tabularnewline
17 & 14 & 13.5677 & 0.432262 \tabularnewline
18 & 17 & 15.6347 & 1.36526 \tabularnewline
19 & 14 & 15.255 & -1.255 \tabularnewline
20 & 16 & 13.5707 & 2.42932 \tabularnewline
21 & 18 & 15.1126 & 2.88737 \tabularnewline
22 & 11 & 13.423 & -2.42299 \tabularnewline
23 & 14 & 14.37 & -0.36997 \tabularnewline
24 & 12 & 13.322 & -1.32201 \tabularnewline
25 & 17 & 15.2027 & 1.79733 \tabularnewline
26 & 9 & 15.838 & -6.83795 \tabularnewline
27 & 16 & 14.8633 & 1.13673 \tabularnewline
28 & 14 & 13.0317 & 0.968342 \tabularnewline
29 & 15 & 13.702 & 1.29799 \tabularnewline
30 & 11 & 13.629 & -2.62899 \tabularnewline
31 & 16 & 15.4676 & 0.532419 \tabularnewline
32 & 13 & 12.2572 & 0.742768 \tabularnewline
33 & 17 & 14.8719 & 2.12812 \tabularnewline
34 & 15 & 15.0242 & -0.0241935 \tabularnewline
35 & 14 & 13.7439 & 0.256096 \tabularnewline
36 & 16 & 15.1455 & 0.854528 \tabularnewline
37 & 9 & 10.3677 & -1.36766 \tabularnewline
38 & 15 & 14.1104 & 0.889595 \tabularnewline
39 & 17 & 15.099 & 1.90098 \tabularnewline
40 & 13 & 15.0437 & -2.04375 \tabularnewline
41 & 15 & 15.5532 & -0.553176 \tabularnewline
42 & 16 & 13.4215 & 2.57853 \tabularnewline
43 & 16 & 15.8968 & 0.103225 \tabularnewline
44 & 12 & 12.9218 & -0.921825 \tabularnewline
45 & 15 & 14.433 & 0.567044 \tabularnewline
46 & 11 & 13.3613 & -2.36129 \tabularnewline
47 & 15 & 15.1836 & -0.183641 \tabularnewline
48 & 15 & 14.6669 & 0.333117 \tabularnewline
49 & 17 & 13.3354 & 3.66465 \tabularnewline
50 & 13 & 14.5968 & -1.59683 \tabularnewline
51 & 16 & 15.091 & 0.909003 \tabularnewline
52 & 14 & 13.1935 & 0.806532 \tabularnewline
53 & 11 & 11.3862 & -0.386175 \tabularnewline
54 & 12 & 13.3919 & -1.39188 \tabularnewline
55 & 12 & 13.7247 & -1.72474 \tabularnewline
56 & 15 & 13.3654 & 1.63465 \tabularnewline
57 & 16 & 14.0817 & 1.91825 \tabularnewline
58 & 15 & 15.2838 & -0.283804 \tabularnewline
59 & 12 & 15.0745 & -3.07451 \tabularnewline
60 & 12 & 13.1957 & -1.19565 \tabularnewline
61 & 8 & 10.362 & -2.36197 \tabularnewline
62 & 13 & 14.5128 & -1.51284 \tabularnewline
63 & 11 & 14.5201 & -3.52005 \tabularnewline
64 & 14 & 12.8779 & 1.12206 \tabularnewline
65 & 15 & 13.5198 & 1.48021 \tabularnewline
66 & 10 & 15.0516 & -5.05159 \tabularnewline
67 & 11 & 12.5707 & -1.57071 \tabularnewline
68 & 12 & 14.4686 & -2.46861 \tabularnewline
69 & 15 & 13.4389 & 1.56108 \tabularnewline
70 & 15 & 13.5645 & 1.43552 \tabularnewline
71 & 14 & 13.2805 & 0.719528 \tabularnewline
72 & 16 & 12.5785 & 3.42149 \tabularnewline
73 & 15 & 14.4336 & 0.566379 \tabularnewline
74 & 15 & 15.3637 & -0.363746 \tabularnewline
75 & 13 & 14.9214 & -1.9214 \tabularnewline
76 & 12 & 12.0568 & -0.056789 \tabularnewline
77 & 17 & 13.9845 & 3.01548 \tabularnewline
78 & 13 & 12.3674 & 0.632589 \tabularnewline
79 & 15 & 13.6251 & 1.37487 \tabularnewline
80 & 13 & 15.0264 & -2.02638 \tabularnewline
81 & 15 & 14.8847 & 0.115316 \tabularnewline
82 & 15 & 15.4919 & -0.491874 \tabularnewline
83 & 16 & 14.2835 & 1.71652 \tabularnewline
84 & 15 & 14.2074 & 0.792612 \tabularnewline
85 & 14 & 14.05 & -0.0500028 \tabularnewline
86 & 15 & 13.9392 & 1.06084 \tabularnewline
87 & 14 & 14.2578 & -0.257791 \tabularnewline
88 & 13 & 12.7065 & 0.293489 \tabularnewline
89 & 7 & 10.3949 & -3.39489 \tabularnewline
90 & 17 & 13.5372 & 3.46282 \tabularnewline
91 & 13 & 12.8959 & 0.104144 \tabularnewline
92 & 15 & 14.1659 & 0.834079 \tabularnewline
93 & 14 & 13.2393 & 0.760705 \tabularnewline
94 & 13 & 13.8862 & -0.886211 \tabularnewline
95 & 16 & 15.0082 & 0.991821 \tabularnewline
96 & 12 & 12.8121 & -0.812128 \tabularnewline
97 & 14 & 14.8616 & -0.861605 \tabularnewline
98 & 17 & 14.9669 & 2.03306 \tabularnewline
99 & 15 & 14.9673 & 0.0326958 \tabularnewline
100 & 17 & 15.2477 & 1.75233 \tabularnewline
101 & 12 & 12.9194 & -0.919433 \tabularnewline
102 & 16 & 15.1278 & 0.872158 \tabularnewline
103 & 11 & 14.384 & -3.38395 \tabularnewline
104 & 15 & 13.0418 & 1.95822 \tabularnewline
105 & 9 & 11.3411 & -2.34112 \tabularnewline
106 & 16 & 14.9893 & 1.01075 \tabularnewline
107 & 15 & 12.9637 & 2.0363 \tabularnewline
108 & 10 & 12.8444 & -2.8444 \tabularnewline
109 & 10 & 9.02436 & 0.975645 \tabularnewline
110 & 15 & 13.8307 & 1.16927 \tabularnewline
111 & 11 & 13.19 & -2.19003 \tabularnewline
112 & 13 & 15.2494 & -2.24943 \tabularnewline
113 & 14 & 12.0604 & 1.93964 \tabularnewline
114 & 18 & 14.0395 & 3.96052 \tabularnewline
115 & 16 & 15.6558 & 0.344235 \tabularnewline
116 & 14 & 12.9885 & 1.01153 \tabularnewline
117 & 14 & 13.7162 & 0.283773 \tabularnewline
118 & 14 & 15.066 & -1.06596 \tabularnewline
119 & 14 & 13.7036 & 0.296354 \tabularnewline
120 & 12 & 12.4838 & -0.483775 \tabularnewline
121 & 14 & 13.5583 & 0.441724 \tabularnewline
122 & 15 & 14.878 & 0.121994 \tabularnewline
123 & 15 & 16.0066 & -1.00658 \tabularnewline
124 & 15 & 14.6174 & 0.382647 \tabularnewline
125 & 13 & 14.8025 & -1.80252 \tabularnewline
126 & 17 & 16.2131 & 0.786913 \tabularnewline
127 & 17 & 15.4535 & 1.54651 \tabularnewline
128 & 19 & 14.8408 & 4.15924 \tabularnewline
129 & 15 & 13.5249 & 1.47515 \tabularnewline
130 & 13 & 14.6709 & -1.67088 \tabularnewline
131 & 9 & 10.4175 & -1.41748 \tabularnewline
132 & 15 & 15.3552 & -0.355202 \tabularnewline
133 & 15 & 12.4668 & 2.53319 \tabularnewline
134 & 15 & 14.245 & 0.754977 \tabularnewline
135 & 16 & 13.6949 & 2.30513 \tabularnewline
136 & 11 & 9.26364 & 1.73636 \tabularnewline
137 & 14 & 13.2865 & 0.713535 \tabularnewline
138 & 11 & 11.8263 & -0.826256 \tabularnewline
139 & 15 & 14.1266 & 0.873435 \tabularnewline
140 & 13 & 13.6983 & -0.698291 \tabularnewline
141 & 15 & 14.6816 & 0.318378 \tabularnewline
142 & 16 & 13.7486 & 2.25138 \tabularnewline
143 & 14 & 14.7065 & -0.706501 \tabularnewline
144 & 15 & 14.308 & 0.692002 \tabularnewline
145 & 16 & 14.5162 & 1.48385 \tabularnewline
146 & 16 & 14.5508 & 1.44925 \tabularnewline
147 & 11 & 13.399 & -2.39905 \tabularnewline
148 & 12 & 14.7271 & -2.72706 \tabularnewline
149 & 9 & 11.4081 & -2.40806 \tabularnewline
150 & 16 & 14.1093 & 1.89067 \tabularnewline
151 & 13 & 12.6446 & 0.355387 \tabularnewline
152 & 16 & 15.5109 & 0.489124 \tabularnewline
153 & 12 & 14.4525 & -2.45246 \tabularnewline
154 & 9 & 11.4997 & -2.4997 \tabularnewline
155 & 13 & 11.5297 & 1.47025 \tabularnewline
156 & 13 & 12.8959 & 0.104144 \tabularnewline
157 & 14 & 13.2291 & 0.770858 \tabularnewline
158 & 19 & 14.8408 & 4.15924 \tabularnewline
159 & 13 & 15.733 & -2.73299 \tabularnewline
160 & 12 & 11.9513 & 0.0487413 \tabularnewline
161 & 13 & 12.4794 & 0.520571 \tabularnewline
162 & 10 & 9.18271 & 0.817289 \tabularnewline
163 & 14 & 13.2498 & 0.750211 \tabularnewline
164 & 16 & 11.705 & 4.29504 \tabularnewline
165 & 10 & 12.0372 & -2.03717 \tabularnewline
166 & 11 & 8.95814 & 2.04186 \tabularnewline
167 & 14 & 14.1939 & -0.19388 \tabularnewline
168 & 12 & 12.864 & -0.864039 \tabularnewline
169 & 9 & 12.7685 & -3.7685 \tabularnewline
170 & 9 & 12.0378 & -3.03779 \tabularnewline
171 & 11 & 10.5535 & 0.446489 \tabularnewline
172 & 16 & 14.4003 & 1.59975 \tabularnewline
173 & 9 & 14.1526 & -5.15257 \tabularnewline
174 & 13 & 11.2452 & 1.75479 \tabularnewline
175 & 16 & 13.48 & 2.51998 \tabularnewline
176 & 13 & 15.4845 & -2.48453 \tabularnewline
177 & 9 & 12.3553 & -3.35533 \tabularnewline
178 & 12 & 11.4879 & 0.512109 \tabularnewline
179 & 16 & 14.6947 & 1.30535 \tabularnewline
180 & 11 & 13.2936 & -2.29359 \tabularnewline
181 & 14 & 14.3521 & -0.352145 \tabularnewline
182 & 13 & 14.8094 & -1.80944 \tabularnewline
183 & 15 & 14.9649 & 0.0351127 \tabularnewline
184 & 14 & 15.201 & -1.20099 \tabularnewline
185 & 16 & 13.9734 & 2.02659 \tabularnewline
186 & 13 & 11.7913 & 1.20875 \tabularnewline
187 & 14 & 13.7834 & 0.216629 \tabularnewline
188 & 15 & 14.313 & 0.686974 \tabularnewline
189 & 13 & 12.5014 & 0.498628 \tabularnewline
190 & 11 & 10.1828 & 0.817199 \tabularnewline
191 & 11 & 12.949 & -1.94897 \tabularnewline
192 & 14 & 15.2811 & -1.28106 \tabularnewline
193 & 15 & 12.7218 & 2.27819 \tabularnewline
194 & 11 & 12.6585 & -1.65853 \tabularnewline
195 & 15 & 13.2162 & 1.7838 \tabularnewline
196 & 12 & 14.2659 & -2.26586 \tabularnewline
197 & 14 & 11.8602 & 2.1398 \tabularnewline
198 & 14 & 13.5739 & 0.426097 \tabularnewline
199 & 8 & 11.2497 & -3.24974 \tabularnewline
200 & 13 & 13.9456 & -0.945592 \tabularnewline
201 & 9 & 12.2927 & -3.29269 \tabularnewline
202 & 15 & 13.8784 & 1.12158 \tabularnewline
203 & 17 & 14.2141 & 2.78591 \tabularnewline
204 & 13 & 12.7024 & 0.297647 \tabularnewline
205 & 15 & 14.6208 & 0.379211 \tabularnewline
206 & 15 & 13.9261 & 1.07392 \tabularnewline
207 & 14 & 14.6928 & -0.692765 \tabularnewline
208 & 16 & 12.7868 & 3.21317 \tabularnewline
209 & 13 & 13.0115 & -0.0115483 \tabularnewline
210 & 16 & 14.5092 & 1.49078 \tabularnewline
211 & 9 & 11.8139 & -2.81386 \tabularnewline
212 & 16 & 14.7441 & 1.25588 \tabularnewline
213 & 11 & 12.3462 & -1.34621 \tabularnewline
214 & 10 & 13.9661 & -3.96611 \tabularnewline
215 & 11 & 12.3691 & -1.36908 \tabularnewline
216 & 15 & 13.4155 & 1.58447 \tabularnewline
217 & 17 & 15.1329 & 1.86706 \tabularnewline
218 & 14 & 14.4546 & -0.45464 \tabularnewline
219 & 8 & 10.0558 & -2.05585 \tabularnewline
220 & 15 & 13.7855 & 1.21455 \tabularnewline
221 & 11 & 14.0984 & -3.09837 \tabularnewline
222 & 16 & 13.8859 & 2.11414 \tabularnewline
223 & 10 & 12.312 & -2.31201 \tabularnewline
224 & 15 & 14.9782 & 0.0218416 \tabularnewline
225 & 9 & 9.87723 & -0.877228 \tabularnewline
226 & 16 & 14.3667 & 1.63328 \tabularnewline
227 & 19 & 14.0296 & 4.97042 \tabularnewline
228 & 12 & 13.917 & -1.91696 \tabularnewline
229 & 8 & 9.51227 & -1.51227 \tabularnewline
230 & 11 & 13.5005 & -2.50048 \tabularnewline
231 & 14 & 13.9842 & 0.0158494 \tabularnewline
232 & 9 & 12.0859 & -3.08591 \tabularnewline
233 & 15 & 15.1652 & -0.165203 \tabularnewline
234 & 13 & 12.7592 & 0.240808 \tabularnewline
235 & 16 & 15.126 & 0.874019 \tabularnewline
236 & 11 & 12.991 & -1.99099 \tabularnewline
237 & 12 & 11.2447 & 0.755342 \tabularnewline
238 & 13 & 13.0765 & -0.0764699 \tabularnewline
239 & 10 & 14.6154 & -4.61544 \tabularnewline
240 & 11 & 13.7035 & -2.70354 \tabularnewline
241 & 12 & 14.9208 & -2.92081 \tabularnewline
242 & 8 & 10.8506 & -2.85065 \tabularnewline
243 & 12 & 11.7585 & 0.241454 \tabularnewline
244 & 12 & 12.4091 & -0.409056 \tabularnewline
245 & 15 & 13.7327 & 1.2673 \tabularnewline
246 & 11 & 10.7802 & 0.219823 \tabularnewline
247 & 13 & 12.8992 & 0.100763 \tabularnewline
248 & 14 & 8.91141 & 5.08859 \tabularnewline
249 & 10 & 10.1952 & -0.195174 \tabularnewline
250 & 12 & 11.6417 & 0.358255 \tabularnewline
251 & 15 & 12.9737 & 2.02625 \tabularnewline
252 & 13 & 11.9239 & 1.07606 \tabularnewline
253 & 13 & 14.3171 & -1.31709 \tabularnewline
254 & 13 & 13.9529 & -0.952895 \tabularnewline
255 & 12 & 11.9638 & 0.0362316 \tabularnewline
256 & 12 & 12.8688 & -0.868792 \tabularnewline
257 & 9 & 11.0686 & -2.06858 \tabularnewline
258 & 9 & 11.595 & -2.59497 \tabularnewline
259 & 15 & 12.8088 & 2.19119 \tabularnewline
260 & 10 & 14.7867 & -4.78671 \tabularnewline
261 & 14 & 13.9112 & 0.0887831 \tabularnewline
262 & 15 & 13.7258 & 1.2742 \tabularnewline
263 & 7 & 9.92786 & -2.92786 \tabularnewline
264 & 14 & 14.0466 & -0.0466467 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222037&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]14[/C][C]13.7058[/C][C]0.294153[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.0284[/C][C]2.97156[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.7196[/C][C]-2.71955[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.1061[/C][C]-2.10608[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]10.844[/C][C]5.15598[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.1185[/C][C]3.88145[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.5199[/C][C]3.48012[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.7937[/C][C]-0.793748[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]14.9525[/C][C]0.0474647[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.0505[/C][C]0.949459[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.2958[/C][C]1.70415[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.4604[/C][C]3.53959[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.1642[/C][C]-3.16424[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.2941[/C][C]2.70588[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.5452[/C][C]2.45478[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.1148[/C][C]0.885167[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.5677[/C][C]0.432262[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.6347[/C][C]1.36526[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.255[/C][C]-1.255[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.5707[/C][C]2.42932[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.1126[/C][C]2.88737[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.423[/C][C]-2.42299[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.37[/C][C]-0.36997[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.322[/C][C]-1.32201[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.2027[/C][C]1.79733[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.838[/C][C]-6.83795[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.8633[/C][C]1.13673[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.0317[/C][C]0.968342[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.702[/C][C]1.29799[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.629[/C][C]-2.62899[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.4676[/C][C]0.532419[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.2572[/C][C]0.742768[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]14.8719[/C][C]2.12812[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.0242[/C][C]-0.0241935[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.7439[/C][C]0.256096[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.1455[/C][C]0.854528[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.3677[/C][C]-1.36766[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.1104[/C][C]0.889595[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.099[/C][C]1.90098[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.0437[/C][C]-2.04375[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.5532[/C][C]-0.553176[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.4215[/C][C]2.57853[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.8968[/C][C]0.103225[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]12.9218[/C][C]-0.921825[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.433[/C][C]0.567044[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.3613[/C][C]-2.36129[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.1836[/C][C]-0.183641[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.6669[/C][C]0.333117[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.3354[/C][C]3.66465[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.5968[/C][C]-1.59683[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.091[/C][C]0.909003[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.1935[/C][C]0.806532[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.3862[/C][C]-0.386175[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.3919[/C][C]-1.39188[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]13.7247[/C][C]-1.72474[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.3654[/C][C]1.63465[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.0817[/C][C]1.91825[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.2838[/C][C]-0.283804[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.0745[/C][C]-3.07451[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.1957[/C][C]-1.19565[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.362[/C][C]-2.36197[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.5128[/C][C]-1.51284[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.5201[/C][C]-3.52005[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]12.8779[/C][C]1.12206[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.5198[/C][C]1.48021[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.0516[/C][C]-5.05159[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.5707[/C][C]-1.57071[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.4686[/C][C]-2.46861[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.4389[/C][C]1.56108[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.5645[/C][C]1.43552[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.2805[/C][C]0.719528[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.5785[/C][C]3.42149[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.4336[/C][C]0.566379[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.3637[/C][C]-0.363746[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.9214[/C][C]-1.9214[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.0568[/C][C]-0.056789[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.9845[/C][C]3.01548[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.3674[/C][C]0.632589[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.6251[/C][C]1.37487[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]15.0264[/C][C]-2.02638[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.8847[/C][C]0.115316[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.4919[/C][C]-0.491874[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.2835[/C][C]1.71652[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2074[/C][C]0.792612[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.05[/C][C]-0.0500028[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.9392[/C][C]1.06084[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.2578[/C][C]-0.257791[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.7065[/C][C]0.293489[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.3949[/C][C]-3.39489[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.5372[/C][C]3.46282[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.8959[/C][C]0.104144[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.1659[/C][C]0.834079[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.2393[/C][C]0.760705[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.8862[/C][C]-0.886211[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]15.0082[/C][C]0.991821[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.8121[/C][C]-0.812128[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.8616[/C][C]-0.861605[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.9669[/C][C]2.03306[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]14.9673[/C][C]0.0326958[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.2477[/C][C]1.75233[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.9194[/C][C]-0.919433[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.1278[/C][C]0.872158[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.384[/C][C]-3.38395[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.0418[/C][C]1.95822[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.3411[/C][C]-2.34112[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.9893[/C][C]1.01075[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9637[/C][C]2.0363[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.8444[/C][C]-2.8444[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.02436[/C][C]0.975645[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.8307[/C][C]1.16927[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.19[/C][C]-2.19003[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.2494[/C][C]-2.24943[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]12.0604[/C][C]1.93964[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.0395[/C][C]3.96052[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.6558[/C][C]0.344235[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]12.9885[/C][C]1.01153[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.7162[/C][C]0.283773[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.066[/C][C]-1.06596[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.7036[/C][C]0.296354[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.4838[/C][C]-0.483775[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.5583[/C][C]0.441724[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.878[/C][C]0.121994[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]16.0066[/C][C]-1.00658[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.6174[/C][C]0.382647[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.8025[/C][C]-1.80252[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.2131[/C][C]0.786913[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.4535[/C][C]1.54651[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.8408[/C][C]4.15924[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5249[/C][C]1.47515[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.6709[/C][C]-1.67088[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.4175[/C][C]-1.41748[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.3552[/C][C]-0.355202[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.4668[/C][C]2.53319[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.245[/C][C]0.754977[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.6949[/C][C]2.30513[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.26364[/C][C]1.73636[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.2865[/C][C]0.713535[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]11.8263[/C][C]-0.826256[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.1266[/C][C]0.873435[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.6983[/C][C]-0.698291[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.6816[/C][C]0.318378[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.7486[/C][C]2.25138[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.7065[/C][C]-0.706501[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.308[/C][C]0.692002[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.5162[/C][C]1.48385[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.5508[/C][C]1.44925[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.399[/C][C]-2.39905[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.7271[/C][C]-2.72706[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.4081[/C][C]-2.40806[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.1093[/C][C]1.89067[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.6446[/C][C]0.355387[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.5109[/C][C]0.489124[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.4525[/C][C]-2.45246[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.4997[/C][C]-2.4997[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.5297[/C][C]1.47025[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.8959[/C][C]0.104144[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.2291[/C][C]0.770858[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.8408[/C][C]4.15924[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.733[/C][C]-2.73299[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.9513[/C][C]0.0487413[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.4794[/C][C]0.520571[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.18271[/C][C]0.817289[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.2498[/C][C]0.750211[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.705[/C][C]4.29504[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]12.0372[/C][C]-2.03717[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]8.95814[/C][C]2.04186[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.1939[/C][C]-0.19388[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.864[/C][C]-0.864039[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.7685[/C][C]-3.7685[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]12.0378[/C][C]-3.03779[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.5535[/C][C]0.446489[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.4003[/C][C]1.59975[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]14.1526[/C][C]-5.15257[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.2452[/C][C]1.75479[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.48[/C][C]2.51998[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.4845[/C][C]-2.48453[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.3553[/C][C]-3.35533[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.4879[/C][C]0.512109[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.6947[/C][C]1.30535[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.2936[/C][C]-2.29359[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]14.3521[/C][C]-0.352145[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.8094[/C][C]-1.80944[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.9649[/C][C]0.0351127[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]15.201[/C][C]-1.20099[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]13.9734[/C][C]2.02659[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.7913[/C][C]1.20875[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.7834[/C][C]0.216629[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.313[/C][C]0.686974[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.5014[/C][C]0.498628[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.1828[/C][C]0.817199[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.949[/C][C]-1.94897[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]15.2811[/C][C]-1.28106[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.7218[/C][C]2.27819[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.6585[/C][C]-1.65853[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.2162[/C][C]1.7838[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.2659[/C][C]-2.26586[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.8602[/C][C]2.1398[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.5739[/C][C]0.426097[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.2497[/C][C]-3.24974[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.9456[/C][C]-0.945592[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.2927[/C][C]-3.29269[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.8784[/C][C]1.12158[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.2141[/C][C]2.78591[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.7024[/C][C]0.297647[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.6208[/C][C]0.379211[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.9261[/C][C]1.07392[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.6928[/C][C]-0.692765[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.7868[/C][C]3.21317[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]13.0115[/C][C]-0.0115483[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.5092[/C][C]1.49078[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.8139[/C][C]-2.81386[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.7441[/C][C]1.25588[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.3462[/C][C]-1.34621[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.9661[/C][C]-3.96611[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.3691[/C][C]-1.36908[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.4155[/C][C]1.58447[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]15.1329[/C][C]1.86706[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.4546[/C][C]-0.45464[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]10.0558[/C][C]-2.05585[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.7855[/C][C]1.21455[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]14.0984[/C][C]-3.09837[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.8859[/C][C]2.11414[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.312[/C][C]-2.31201[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.9782[/C][C]0.0218416[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.87723[/C][C]-0.877228[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.3667[/C][C]1.63328[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]14.0296[/C][C]4.97042[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.917[/C][C]-1.91696[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.51227[/C][C]-1.51227[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.5005[/C][C]-2.50048[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.9842[/C][C]0.0158494[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]12.0859[/C][C]-3.08591[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]15.1652[/C][C]-0.165203[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.7592[/C][C]0.240808[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]15.126[/C][C]0.874019[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.991[/C][C]-1.99099[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.2447[/C][C]0.755342[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.0765[/C][C]-0.0764699[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.6154[/C][C]-4.61544[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.7035[/C][C]-2.70354[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.9208[/C][C]-2.92081[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.8506[/C][C]-2.85065[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.7585[/C][C]0.241454[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.4091[/C][C]-0.409056[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.7327[/C][C]1.2673[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.7802[/C][C]0.219823[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.8992[/C][C]0.100763[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.91141[/C][C]5.08859[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.1952[/C][C]-0.195174[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.6417[/C][C]0.358255[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.9737[/C][C]2.02625[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.9239[/C][C]1.07606[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.3171[/C][C]-1.31709[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.9529[/C][C]-0.952895[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.9638[/C][C]0.0362316[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.8688[/C][C]-0.868792[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]11.0686[/C][C]-2.06858[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.595[/C][C]-2.59497[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.8088[/C][C]2.19119[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.7867[/C][C]-4.78671[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.9112[/C][C]0.0887831[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.7258[/C][C]1.2742[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.92786[/C][C]-2.92786[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]14.0466[/C][C]-0.0466467[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222037&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222037&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
11413.70580.294153
21815.02842.97156
31113.7196-2.71955
41214.1061-2.10608
51610.8445.15598
61814.11853.88145
71410.51993.48012
81414.7937-0.793748
91514.95250.0474647
101514.05050.949459
111715.29581.70415
121915.46043.53959
131013.1642-3.16424
141613.29412.70588
151815.54522.45478
161413.11480.885167
171413.56770.432262
181715.63471.36526
191415.255-1.255
201613.57072.42932
211815.11262.88737
221113.423-2.42299
231414.37-0.36997
241213.322-1.32201
251715.20271.79733
26915.838-6.83795
271614.86331.13673
281413.03170.968342
291513.7021.29799
301113.629-2.62899
311615.46760.532419
321312.25720.742768
331714.87192.12812
341515.0242-0.0241935
351413.74390.256096
361615.14550.854528
37910.3677-1.36766
381514.11040.889595
391715.0991.90098
401315.0437-2.04375
411515.5532-0.553176
421613.42152.57853
431615.89680.103225
441212.9218-0.921825
451514.4330.567044
461113.3613-2.36129
471515.1836-0.183641
481514.66690.333117
491713.33543.66465
501314.5968-1.59683
511615.0910.909003
521413.19350.806532
531111.3862-0.386175
541213.3919-1.39188
551213.7247-1.72474
561513.36541.63465
571614.08171.91825
581515.2838-0.283804
591215.0745-3.07451
601213.1957-1.19565
61810.362-2.36197
621314.5128-1.51284
631114.5201-3.52005
641412.87791.12206
651513.51981.48021
661015.0516-5.05159
671112.5707-1.57071
681214.4686-2.46861
691513.43891.56108
701513.56451.43552
711413.28050.719528
721612.57853.42149
731514.43360.566379
741515.3637-0.363746
751314.9214-1.9214
761212.0568-0.056789
771713.98453.01548
781312.36740.632589
791513.62511.37487
801315.0264-2.02638
811514.88470.115316
821515.4919-0.491874
831614.28351.71652
841514.20740.792612
851414.05-0.0500028
861513.93921.06084
871414.2578-0.257791
881312.70650.293489
89710.3949-3.39489
901713.53723.46282
911312.89590.104144
921514.16590.834079
931413.23930.760705
941313.8862-0.886211
951615.00820.991821
961212.8121-0.812128
971414.8616-0.861605
981714.96692.03306
991514.96730.0326958
1001715.24771.75233
1011212.9194-0.919433
1021615.12780.872158
1031114.384-3.38395
1041513.04181.95822
105911.3411-2.34112
1061614.98931.01075
1071512.96372.0363
1081012.8444-2.8444
109109.024360.975645
1101513.83071.16927
1111113.19-2.19003
1121315.2494-2.24943
1131412.06041.93964
1141814.03953.96052
1151615.65580.344235
1161412.98851.01153
1171413.71620.283773
1181415.066-1.06596
1191413.70360.296354
1201212.4838-0.483775
1211413.55830.441724
1221514.8780.121994
1231516.0066-1.00658
1241514.61740.382647
1251314.8025-1.80252
1261716.21310.786913
1271715.45351.54651
1281914.84084.15924
1291513.52491.47515
1301314.6709-1.67088
131910.4175-1.41748
1321515.3552-0.355202
1331512.46682.53319
1341514.2450.754977
1351613.69492.30513
136119.263641.73636
1371413.28650.713535
1381111.8263-0.826256
1391514.12660.873435
1401313.6983-0.698291
1411514.68160.318378
1421613.74862.25138
1431414.7065-0.706501
1441514.3080.692002
1451614.51621.48385
1461614.55081.44925
1471113.399-2.39905
1481214.7271-2.72706
149911.4081-2.40806
1501614.10931.89067
1511312.64460.355387
1521615.51090.489124
1531214.4525-2.45246
154911.4997-2.4997
1551311.52971.47025
1561312.89590.104144
1571413.22910.770858
1581914.84084.15924
1591315.733-2.73299
1601211.95130.0487413
1611312.47940.520571
162109.182710.817289
1631413.24980.750211
1641611.7054.29504
1651012.0372-2.03717
166118.958142.04186
1671414.1939-0.19388
1681212.864-0.864039
169912.7685-3.7685
170912.0378-3.03779
1711110.55350.446489
1721614.40031.59975
173914.1526-5.15257
1741311.24521.75479
1751613.482.51998
1761315.4845-2.48453
177912.3553-3.35533
1781211.48790.512109
1791614.69471.30535
1801113.2936-2.29359
1811414.3521-0.352145
1821314.8094-1.80944
1831514.96490.0351127
1841415.201-1.20099
1851613.97342.02659
1861311.79131.20875
1871413.78340.216629
1881514.3130.686974
1891312.50140.498628
1901110.18280.817199
1911112.949-1.94897
1921415.2811-1.28106
1931512.72182.27819
1941112.6585-1.65853
1951513.21621.7838
1961214.2659-2.26586
1971411.86022.1398
1981413.57390.426097
199811.2497-3.24974
2001313.9456-0.945592
201912.2927-3.29269
2021513.87841.12158
2031714.21412.78591
2041312.70240.297647
2051514.62080.379211
2061513.92611.07392
2071414.6928-0.692765
2081612.78683.21317
2091313.0115-0.0115483
2101614.50921.49078
211911.8139-2.81386
2121614.74411.25588
2131112.3462-1.34621
2141013.9661-3.96611
2151112.3691-1.36908
2161513.41551.58447
2171715.13291.86706
2181414.4546-0.45464
219810.0558-2.05585
2201513.78551.21455
2211114.0984-3.09837
2221613.88592.11414
2231012.312-2.31201
2241514.97820.0218416
22599.87723-0.877228
2261614.36671.63328
2271914.02964.97042
2281213.917-1.91696
22989.51227-1.51227
2301113.5005-2.50048
2311413.98420.0158494
232912.0859-3.08591
2331515.1652-0.165203
2341312.75920.240808
2351615.1260.874019
2361112.991-1.99099
2371211.24470.755342
2381313.0765-0.0764699
2391014.6154-4.61544
2401113.7035-2.70354
2411214.9208-2.92081
242810.8506-2.85065
2431211.75850.241454
2441212.4091-0.409056
2451513.73271.2673
2461110.78020.219823
2471312.89920.100763
248148.911415.08859
2491010.1952-0.195174
2501211.64170.358255
2511512.97372.02625
2521311.92391.07606
2531314.3171-1.31709
2541313.9529-0.952895
2551211.96380.0362316
2561212.8688-0.868792
257911.0686-2.06858
258911.595-2.59497
2591512.80882.19119
2601014.7867-4.78671
2611413.91120.0887831
2621513.72581.2742
26379.92786-2.92786
2641414.0466-0.0466467






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.05059810.1011960.949402
110.01419620.02839230.985804
120.8276930.3446140.172307
130.9657070.06858590.034293
140.9675350.06493030.0324651
150.9763450.04730950.0236547
160.9608990.07820230.0391011
170.948070.103860.0519299
180.9292720.1414560.0707278
190.9067710.1864580.093229
200.9011170.1977670.0988835
210.9171090.1657810.0828905
220.9508630.09827380.0491369
230.9317690.1364610.0682307
240.915210.1695810.0847905
250.8908920.2182150.109108
260.9983260.003348230.00167411
270.9974490.005102640.00255132
280.9960890.007822310.00391115
290.9941840.01163250.00581624
300.996820.00635920.0031796
310.995220.009560190.00478009
320.9930620.0138760.006938
330.99170.01659970.00829987
340.9881910.02361760.0118088
350.9843110.03137890.0156895
360.9784570.04308590.0215429
370.9842040.03159160.0157958
380.9786160.04276760.0213838
390.9760240.04795150.0239757
400.9763240.04735120.0236756
410.9693980.06120330.0306016
420.9671690.06566130.0328306
430.9575390.08492120.0424606
440.9497440.1005130.0502564
450.9362860.1274280.063714
460.9467670.1064670.0532335
470.9326970.1346060.0673031
480.9161080.1677850.0838925
490.933560.132880.0664399
500.9294720.1410560.0705278
510.9149920.1700150.0850075
520.8967610.2064770.103239
530.8806630.2386730.119337
540.8725760.2548490.127424
550.8629550.2740890.137045
560.8435480.3129050.156452
570.8303590.3392820.169641
580.80140.3971990.1986
590.8380250.323950.161975
600.8330540.3338920.166946
610.851620.296760.14838
620.8477590.3044830.152241
630.9005270.1989460.0994729
640.8881390.2237210.111861
650.8781210.2437580.121879
660.9547840.0904320.045216
670.9532440.09351130.0467556
680.9580640.0838710.0419355
690.9527450.0945110.0472555
700.9460840.1078330.0539164
710.9348040.1303920.065196
720.9502330.09953350.0497667
730.9395980.1208030.0604016
740.9274350.1451310.0725654
750.9225980.1548040.077402
760.9082770.1834460.0917232
770.9213530.1572950.0786473
780.9068340.1863320.0931658
790.8974590.2050820.102541
800.8901260.2197480.109874
810.8708640.2582730.129136
820.8506050.298790.149395
830.8430490.3139010.156951
840.8218430.3563150.178157
850.7957280.4085430.204272
860.7714770.4570470.228523
870.7421440.5157120.257856
880.7110030.5779940.288997
890.786690.426620.21331
900.8213560.3572880.178644
910.7963220.4073560.203678
920.772150.4556990.22785
930.7480740.5038530.251926
940.7228520.5542970.277148
950.6958940.6082110.304106
960.6700450.6599090.329955
970.6420750.7158510.357925
980.640670.718660.35933
990.6065040.7869920.393496
1000.5970130.8059730.402987
1010.5727270.8545450.427273
1020.5431320.9137370.456868
1030.5933360.8133270.406664
1040.5820620.8358760.417938
1050.5982030.8035940.401797
1060.5705540.8588930.429446
1070.5632030.8735940.436797
1080.6003430.7993140.399657
1090.5740360.8519280.425964
1100.5479910.9040190.452009
1110.5526030.8947930.447397
1120.583670.8326610.41633
1130.5834660.8330670.416534
1140.6687680.6624640.331232
1150.637140.7257210.36286
1160.6140230.7719530.385977
1170.5840450.8319090.415955
1180.5604280.8791430.439572
1190.5260520.9478960.473948
1200.4949540.9899090.505046
1210.4638810.9277620.536119
1220.4328830.8657650.567117
1230.4067240.8134490.593276
1240.3740660.7481310.625934
1250.3632430.7264870.636757
1260.3337550.667510.666245
1270.3207170.6414350.679283
1280.4243680.8487360.575632
1290.4071940.8143880.592806
1300.3955040.7910070.604496
1310.3809440.7618890.619056
1320.3529080.7058170.647092
1330.3735630.7471250.626437
1340.3475970.6951930.652403
1350.3581120.7162240.641888
1360.347250.69450.65275
1370.3199970.6399940.680003
1380.2961110.5922220.703889
1390.2716530.5433060.728347
1400.2485070.4970140.751493
1410.2223430.4446860.777657
1420.2282790.4565570.771721
1430.2040190.4080380.795981
1440.1834590.3669180.816541
1450.1707110.3414210.829289
1460.1630030.3260060.836997
1470.1701340.3402670.829866
1480.1859720.3719440.814028
1490.2028060.4056130.797194
1500.2041020.4082030.795898
1510.182650.36530.81735
1520.1635170.3270340.836483
1530.1756910.3513820.824309
1540.1909310.3818630.809069
1550.1783490.3566980.821651
1560.1560850.312170.843915
1570.139910.279820.86009
1580.2271140.4542280.772886
1590.2458410.4916820.754159
1600.22460.44920.7754
1610.2030120.4060240.796988
1620.1798890.3597780.820111
1630.1587180.3174360.841282
1640.2615190.5230370.738481
1650.258370.5167410.74163
1660.2559320.5118640.744068
1670.2278240.4556480.772176
1680.2065850.4131710.793415
1690.2645960.5291930.735404
1700.2933920.5867830.706608
1710.2657850.531570.734215
1720.2614230.5228470.738577
1730.4317490.8634980.568251
1740.4173640.8347280.582636
1750.4394960.8789930.560504
1760.4527430.9054860.547257
1770.5096070.9807860.490393
1780.4757230.9514470.524277
1790.4537290.9074570.546271
1800.4568720.9137450.543128
1810.4193680.8387360.580632
1820.4121620.8243240.587838
1830.3748940.7497890.625106
1840.3482520.6965040.651748
1850.3648140.7296280.635186
1860.3555330.7110670.644467
1870.3204580.6409160.679542
1880.2913350.582670.708665
1890.2594130.5188250.740587
1900.2378770.4757540.762123
1910.2468830.4937670.753117
1920.2280660.4561310.771934
1930.2456130.4912260.754387
1940.2343570.4687140.765643
1950.234320.4686410.76568
1960.246560.493120.75344
1970.2959960.5919920.704004
1980.2770860.5541730.722914
1990.3135850.6271710.686415
2000.2803550.5607090.719645
2010.3175330.6350660.682467
2020.2945050.589010.705495
2030.3422230.6844460.657777
2040.3046220.6092430.695378
2050.2700560.5401120.729944
2060.2483620.4967230.751638
2070.2163340.4326670.783666
2080.239910.479820.76009
2090.2074730.4149460.792527
2100.2157050.431410.784295
2110.2417660.4835320.758234
2120.2306140.4612280.769386
2130.203560.407120.79644
2140.2509490.5018970.749051
2150.2249620.4499250.775038
2160.2133080.4266170.786692
2170.2449360.4898720.755064
2180.2134740.4269480.786526
2190.2023260.4046510.797674
2200.2168580.4337160.783142
2210.2301220.4602440.769878
2220.2219220.4438430.778078
2230.2080470.4160940.791953
2240.1753410.3506820.824659
2250.1732770.3465550.826723
2260.2063160.4126310.793684
2270.41310.82620.5869
2280.3844240.7688480.615576
2290.3580250.716050.641975
2300.3421260.6842530.657874
2310.2992360.5984730.700764
2320.3425710.6851430.657429
2330.2968610.5937220.703139
2340.252610.5052210.74739
2350.2521810.5043610.747819
2360.2279620.4559240.772038
2370.1947140.3894280.805286
2380.1551010.3102010.844899
2390.2880950.576190.711905
2400.2775020.5550040.722498
2410.2458630.4917250.754137
2420.4721510.9443030.527849
2430.4292480.8584950.570752
2440.3659460.7318920.634054
2450.4928580.9857150.507142
2460.4075710.8151420.592429
2470.3240820.6481640.675918
2480.490860.9817210.50914
2490.3906160.7812310.609384
2500.2941830.5883670.705817
2510.4441990.8883990.555801
2520.9216020.1567960.078398
2530.8405630.3188740.159437
2540.7905890.4188230.209411

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.0505981 & 0.101196 & 0.949402 \tabularnewline
11 & 0.0141962 & 0.0283923 & 0.985804 \tabularnewline
12 & 0.827693 & 0.344614 & 0.172307 \tabularnewline
13 & 0.965707 & 0.0685859 & 0.034293 \tabularnewline
14 & 0.967535 & 0.0649303 & 0.0324651 \tabularnewline
15 & 0.976345 & 0.0473095 & 0.0236547 \tabularnewline
16 & 0.960899 & 0.0782023 & 0.0391011 \tabularnewline
17 & 0.94807 & 0.10386 & 0.0519299 \tabularnewline
18 & 0.929272 & 0.141456 & 0.0707278 \tabularnewline
19 & 0.906771 & 0.186458 & 0.093229 \tabularnewline
20 & 0.901117 & 0.197767 & 0.0988835 \tabularnewline
21 & 0.917109 & 0.165781 & 0.0828905 \tabularnewline
22 & 0.950863 & 0.0982738 & 0.0491369 \tabularnewline
23 & 0.931769 & 0.136461 & 0.0682307 \tabularnewline
24 & 0.91521 & 0.169581 & 0.0847905 \tabularnewline
25 & 0.890892 & 0.218215 & 0.109108 \tabularnewline
26 & 0.998326 & 0.00334823 & 0.00167411 \tabularnewline
27 & 0.997449 & 0.00510264 & 0.00255132 \tabularnewline
28 & 0.996089 & 0.00782231 & 0.00391115 \tabularnewline
29 & 0.994184 & 0.0116325 & 0.00581624 \tabularnewline
30 & 0.99682 & 0.0063592 & 0.0031796 \tabularnewline
31 & 0.99522 & 0.00956019 & 0.00478009 \tabularnewline
32 & 0.993062 & 0.013876 & 0.006938 \tabularnewline
33 & 0.9917 & 0.0165997 & 0.00829987 \tabularnewline
34 & 0.988191 & 0.0236176 & 0.0118088 \tabularnewline
35 & 0.984311 & 0.0313789 & 0.0156895 \tabularnewline
36 & 0.978457 & 0.0430859 & 0.0215429 \tabularnewline
37 & 0.984204 & 0.0315916 & 0.0157958 \tabularnewline
38 & 0.978616 & 0.0427676 & 0.0213838 \tabularnewline
39 & 0.976024 & 0.0479515 & 0.0239757 \tabularnewline
40 & 0.976324 & 0.0473512 & 0.0236756 \tabularnewline
41 & 0.969398 & 0.0612033 & 0.0306016 \tabularnewline
42 & 0.967169 & 0.0656613 & 0.0328306 \tabularnewline
43 & 0.957539 & 0.0849212 & 0.0424606 \tabularnewline
44 & 0.949744 & 0.100513 & 0.0502564 \tabularnewline
45 & 0.936286 & 0.127428 & 0.063714 \tabularnewline
46 & 0.946767 & 0.106467 & 0.0532335 \tabularnewline
47 & 0.932697 & 0.134606 & 0.0673031 \tabularnewline
48 & 0.916108 & 0.167785 & 0.0838925 \tabularnewline
49 & 0.93356 & 0.13288 & 0.0664399 \tabularnewline
50 & 0.929472 & 0.141056 & 0.0705278 \tabularnewline
51 & 0.914992 & 0.170015 & 0.0850075 \tabularnewline
52 & 0.896761 & 0.206477 & 0.103239 \tabularnewline
53 & 0.880663 & 0.238673 & 0.119337 \tabularnewline
54 & 0.872576 & 0.254849 & 0.127424 \tabularnewline
55 & 0.862955 & 0.274089 & 0.137045 \tabularnewline
56 & 0.843548 & 0.312905 & 0.156452 \tabularnewline
57 & 0.830359 & 0.339282 & 0.169641 \tabularnewline
58 & 0.8014 & 0.397199 & 0.1986 \tabularnewline
59 & 0.838025 & 0.32395 & 0.161975 \tabularnewline
60 & 0.833054 & 0.333892 & 0.166946 \tabularnewline
61 & 0.85162 & 0.29676 & 0.14838 \tabularnewline
62 & 0.847759 & 0.304483 & 0.152241 \tabularnewline
63 & 0.900527 & 0.198946 & 0.0994729 \tabularnewline
64 & 0.888139 & 0.223721 & 0.111861 \tabularnewline
65 & 0.878121 & 0.243758 & 0.121879 \tabularnewline
66 & 0.954784 & 0.090432 & 0.045216 \tabularnewline
67 & 0.953244 & 0.0935113 & 0.0467556 \tabularnewline
68 & 0.958064 & 0.083871 & 0.0419355 \tabularnewline
69 & 0.952745 & 0.094511 & 0.0472555 \tabularnewline
70 & 0.946084 & 0.107833 & 0.0539164 \tabularnewline
71 & 0.934804 & 0.130392 & 0.065196 \tabularnewline
72 & 0.950233 & 0.0995335 & 0.0497667 \tabularnewline
73 & 0.939598 & 0.120803 & 0.0604016 \tabularnewline
74 & 0.927435 & 0.145131 & 0.0725654 \tabularnewline
75 & 0.922598 & 0.154804 & 0.077402 \tabularnewline
76 & 0.908277 & 0.183446 & 0.0917232 \tabularnewline
77 & 0.921353 & 0.157295 & 0.0786473 \tabularnewline
78 & 0.906834 & 0.186332 & 0.0931658 \tabularnewline
79 & 0.897459 & 0.205082 & 0.102541 \tabularnewline
80 & 0.890126 & 0.219748 & 0.109874 \tabularnewline
81 & 0.870864 & 0.258273 & 0.129136 \tabularnewline
82 & 0.850605 & 0.29879 & 0.149395 \tabularnewline
83 & 0.843049 & 0.313901 & 0.156951 \tabularnewline
84 & 0.821843 & 0.356315 & 0.178157 \tabularnewline
85 & 0.795728 & 0.408543 & 0.204272 \tabularnewline
86 & 0.771477 & 0.457047 & 0.228523 \tabularnewline
87 & 0.742144 & 0.515712 & 0.257856 \tabularnewline
88 & 0.711003 & 0.577994 & 0.288997 \tabularnewline
89 & 0.78669 & 0.42662 & 0.21331 \tabularnewline
90 & 0.821356 & 0.357288 & 0.178644 \tabularnewline
91 & 0.796322 & 0.407356 & 0.203678 \tabularnewline
92 & 0.77215 & 0.455699 & 0.22785 \tabularnewline
93 & 0.748074 & 0.503853 & 0.251926 \tabularnewline
94 & 0.722852 & 0.554297 & 0.277148 \tabularnewline
95 & 0.695894 & 0.608211 & 0.304106 \tabularnewline
96 & 0.670045 & 0.659909 & 0.329955 \tabularnewline
97 & 0.642075 & 0.715851 & 0.357925 \tabularnewline
98 & 0.64067 & 0.71866 & 0.35933 \tabularnewline
99 & 0.606504 & 0.786992 & 0.393496 \tabularnewline
100 & 0.597013 & 0.805973 & 0.402987 \tabularnewline
101 & 0.572727 & 0.854545 & 0.427273 \tabularnewline
102 & 0.543132 & 0.913737 & 0.456868 \tabularnewline
103 & 0.593336 & 0.813327 & 0.406664 \tabularnewline
104 & 0.582062 & 0.835876 & 0.417938 \tabularnewline
105 & 0.598203 & 0.803594 & 0.401797 \tabularnewline
106 & 0.570554 & 0.858893 & 0.429446 \tabularnewline
107 & 0.563203 & 0.873594 & 0.436797 \tabularnewline
108 & 0.600343 & 0.799314 & 0.399657 \tabularnewline
109 & 0.574036 & 0.851928 & 0.425964 \tabularnewline
110 & 0.547991 & 0.904019 & 0.452009 \tabularnewline
111 & 0.552603 & 0.894793 & 0.447397 \tabularnewline
112 & 0.58367 & 0.832661 & 0.41633 \tabularnewline
113 & 0.583466 & 0.833067 & 0.416534 \tabularnewline
114 & 0.668768 & 0.662464 & 0.331232 \tabularnewline
115 & 0.63714 & 0.725721 & 0.36286 \tabularnewline
116 & 0.614023 & 0.771953 & 0.385977 \tabularnewline
117 & 0.584045 & 0.831909 & 0.415955 \tabularnewline
118 & 0.560428 & 0.879143 & 0.439572 \tabularnewline
119 & 0.526052 & 0.947896 & 0.473948 \tabularnewline
120 & 0.494954 & 0.989909 & 0.505046 \tabularnewline
121 & 0.463881 & 0.927762 & 0.536119 \tabularnewline
122 & 0.432883 & 0.865765 & 0.567117 \tabularnewline
123 & 0.406724 & 0.813449 & 0.593276 \tabularnewline
124 & 0.374066 & 0.748131 & 0.625934 \tabularnewline
125 & 0.363243 & 0.726487 & 0.636757 \tabularnewline
126 & 0.333755 & 0.66751 & 0.666245 \tabularnewline
127 & 0.320717 & 0.641435 & 0.679283 \tabularnewline
128 & 0.424368 & 0.848736 & 0.575632 \tabularnewline
129 & 0.407194 & 0.814388 & 0.592806 \tabularnewline
130 & 0.395504 & 0.791007 & 0.604496 \tabularnewline
131 & 0.380944 & 0.761889 & 0.619056 \tabularnewline
132 & 0.352908 & 0.705817 & 0.647092 \tabularnewline
133 & 0.373563 & 0.747125 & 0.626437 \tabularnewline
134 & 0.347597 & 0.695193 & 0.652403 \tabularnewline
135 & 0.358112 & 0.716224 & 0.641888 \tabularnewline
136 & 0.34725 & 0.6945 & 0.65275 \tabularnewline
137 & 0.319997 & 0.639994 & 0.680003 \tabularnewline
138 & 0.296111 & 0.592222 & 0.703889 \tabularnewline
139 & 0.271653 & 0.543306 & 0.728347 \tabularnewline
140 & 0.248507 & 0.497014 & 0.751493 \tabularnewline
141 & 0.222343 & 0.444686 & 0.777657 \tabularnewline
142 & 0.228279 & 0.456557 & 0.771721 \tabularnewline
143 & 0.204019 & 0.408038 & 0.795981 \tabularnewline
144 & 0.183459 & 0.366918 & 0.816541 \tabularnewline
145 & 0.170711 & 0.341421 & 0.829289 \tabularnewline
146 & 0.163003 & 0.326006 & 0.836997 \tabularnewline
147 & 0.170134 & 0.340267 & 0.829866 \tabularnewline
148 & 0.185972 & 0.371944 & 0.814028 \tabularnewline
149 & 0.202806 & 0.405613 & 0.797194 \tabularnewline
150 & 0.204102 & 0.408203 & 0.795898 \tabularnewline
151 & 0.18265 & 0.3653 & 0.81735 \tabularnewline
152 & 0.163517 & 0.327034 & 0.836483 \tabularnewline
153 & 0.175691 & 0.351382 & 0.824309 \tabularnewline
154 & 0.190931 & 0.381863 & 0.809069 \tabularnewline
155 & 0.178349 & 0.356698 & 0.821651 \tabularnewline
156 & 0.156085 & 0.31217 & 0.843915 \tabularnewline
157 & 0.13991 & 0.27982 & 0.86009 \tabularnewline
158 & 0.227114 & 0.454228 & 0.772886 \tabularnewline
159 & 0.245841 & 0.491682 & 0.754159 \tabularnewline
160 & 0.2246 & 0.4492 & 0.7754 \tabularnewline
161 & 0.203012 & 0.406024 & 0.796988 \tabularnewline
162 & 0.179889 & 0.359778 & 0.820111 \tabularnewline
163 & 0.158718 & 0.317436 & 0.841282 \tabularnewline
164 & 0.261519 & 0.523037 & 0.738481 \tabularnewline
165 & 0.25837 & 0.516741 & 0.74163 \tabularnewline
166 & 0.255932 & 0.511864 & 0.744068 \tabularnewline
167 & 0.227824 & 0.455648 & 0.772176 \tabularnewline
168 & 0.206585 & 0.413171 & 0.793415 \tabularnewline
169 & 0.264596 & 0.529193 & 0.735404 \tabularnewline
170 & 0.293392 & 0.586783 & 0.706608 \tabularnewline
171 & 0.265785 & 0.53157 & 0.734215 \tabularnewline
172 & 0.261423 & 0.522847 & 0.738577 \tabularnewline
173 & 0.431749 & 0.863498 & 0.568251 \tabularnewline
174 & 0.417364 & 0.834728 & 0.582636 \tabularnewline
175 & 0.439496 & 0.878993 & 0.560504 \tabularnewline
176 & 0.452743 & 0.905486 & 0.547257 \tabularnewline
177 & 0.509607 & 0.980786 & 0.490393 \tabularnewline
178 & 0.475723 & 0.951447 & 0.524277 \tabularnewline
179 & 0.453729 & 0.907457 & 0.546271 \tabularnewline
180 & 0.456872 & 0.913745 & 0.543128 \tabularnewline
181 & 0.419368 & 0.838736 & 0.580632 \tabularnewline
182 & 0.412162 & 0.824324 & 0.587838 \tabularnewline
183 & 0.374894 & 0.749789 & 0.625106 \tabularnewline
184 & 0.348252 & 0.696504 & 0.651748 \tabularnewline
185 & 0.364814 & 0.729628 & 0.635186 \tabularnewline
186 & 0.355533 & 0.711067 & 0.644467 \tabularnewline
187 & 0.320458 & 0.640916 & 0.679542 \tabularnewline
188 & 0.291335 & 0.58267 & 0.708665 \tabularnewline
189 & 0.259413 & 0.518825 & 0.740587 \tabularnewline
190 & 0.237877 & 0.475754 & 0.762123 \tabularnewline
191 & 0.246883 & 0.493767 & 0.753117 \tabularnewline
192 & 0.228066 & 0.456131 & 0.771934 \tabularnewline
193 & 0.245613 & 0.491226 & 0.754387 \tabularnewline
194 & 0.234357 & 0.468714 & 0.765643 \tabularnewline
195 & 0.23432 & 0.468641 & 0.76568 \tabularnewline
196 & 0.24656 & 0.49312 & 0.75344 \tabularnewline
197 & 0.295996 & 0.591992 & 0.704004 \tabularnewline
198 & 0.277086 & 0.554173 & 0.722914 \tabularnewline
199 & 0.313585 & 0.627171 & 0.686415 \tabularnewline
200 & 0.280355 & 0.560709 & 0.719645 \tabularnewline
201 & 0.317533 & 0.635066 & 0.682467 \tabularnewline
202 & 0.294505 & 0.58901 & 0.705495 \tabularnewline
203 & 0.342223 & 0.684446 & 0.657777 \tabularnewline
204 & 0.304622 & 0.609243 & 0.695378 \tabularnewline
205 & 0.270056 & 0.540112 & 0.729944 \tabularnewline
206 & 0.248362 & 0.496723 & 0.751638 \tabularnewline
207 & 0.216334 & 0.432667 & 0.783666 \tabularnewline
208 & 0.23991 & 0.47982 & 0.76009 \tabularnewline
209 & 0.207473 & 0.414946 & 0.792527 \tabularnewline
210 & 0.215705 & 0.43141 & 0.784295 \tabularnewline
211 & 0.241766 & 0.483532 & 0.758234 \tabularnewline
212 & 0.230614 & 0.461228 & 0.769386 \tabularnewline
213 & 0.20356 & 0.40712 & 0.79644 \tabularnewline
214 & 0.250949 & 0.501897 & 0.749051 \tabularnewline
215 & 0.224962 & 0.449925 & 0.775038 \tabularnewline
216 & 0.213308 & 0.426617 & 0.786692 \tabularnewline
217 & 0.244936 & 0.489872 & 0.755064 \tabularnewline
218 & 0.213474 & 0.426948 & 0.786526 \tabularnewline
219 & 0.202326 & 0.404651 & 0.797674 \tabularnewline
220 & 0.216858 & 0.433716 & 0.783142 \tabularnewline
221 & 0.230122 & 0.460244 & 0.769878 \tabularnewline
222 & 0.221922 & 0.443843 & 0.778078 \tabularnewline
223 & 0.208047 & 0.416094 & 0.791953 \tabularnewline
224 & 0.175341 & 0.350682 & 0.824659 \tabularnewline
225 & 0.173277 & 0.346555 & 0.826723 \tabularnewline
226 & 0.206316 & 0.412631 & 0.793684 \tabularnewline
227 & 0.4131 & 0.8262 & 0.5869 \tabularnewline
228 & 0.384424 & 0.768848 & 0.615576 \tabularnewline
229 & 0.358025 & 0.71605 & 0.641975 \tabularnewline
230 & 0.342126 & 0.684253 & 0.657874 \tabularnewline
231 & 0.299236 & 0.598473 & 0.700764 \tabularnewline
232 & 0.342571 & 0.685143 & 0.657429 \tabularnewline
233 & 0.296861 & 0.593722 & 0.703139 \tabularnewline
234 & 0.25261 & 0.505221 & 0.74739 \tabularnewline
235 & 0.252181 & 0.504361 & 0.747819 \tabularnewline
236 & 0.227962 & 0.455924 & 0.772038 \tabularnewline
237 & 0.194714 & 0.389428 & 0.805286 \tabularnewline
238 & 0.155101 & 0.310201 & 0.844899 \tabularnewline
239 & 0.288095 & 0.57619 & 0.711905 \tabularnewline
240 & 0.277502 & 0.555004 & 0.722498 \tabularnewline
241 & 0.245863 & 0.491725 & 0.754137 \tabularnewline
242 & 0.472151 & 0.944303 & 0.527849 \tabularnewline
243 & 0.429248 & 0.858495 & 0.570752 \tabularnewline
244 & 0.365946 & 0.731892 & 0.634054 \tabularnewline
245 & 0.492858 & 0.985715 & 0.507142 \tabularnewline
246 & 0.407571 & 0.815142 & 0.592429 \tabularnewline
247 & 0.324082 & 0.648164 & 0.675918 \tabularnewline
248 & 0.49086 & 0.981721 & 0.50914 \tabularnewline
249 & 0.390616 & 0.781231 & 0.609384 \tabularnewline
250 & 0.294183 & 0.588367 & 0.705817 \tabularnewline
251 & 0.444199 & 0.888399 & 0.555801 \tabularnewline
252 & 0.921602 & 0.156796 & 0.078398 \tabularnewline
253 & 0.840563 & 0.318874 & 0.159437 \tabularnewline
254 & 0.790589 & 0.418823 & 0.209411 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222037&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]10[/C][C]0.0505981[/C][C]0.101196[/C][C]0.949402[/C][/ROW]
[ROW][C]11[/C][C]0.0141962[/C][C]0.0283923[/C][C]0.985804[/C][/ROW]
[ROW][C]12[/C][C]0.827693[/C][C]0.344614[/C][C]0.172307[/C][/ROW]
[ROW][C]13[/C][C]0.965707[/C][C]0.0685859[/C][C]0.034293[/C][/ROW]
[ROW][C]14[/C][C]0.967535[/C][C]0.0649303[/C][C]0.0324651[/C][/ROW]
[ROW][C]15[/C][C]0.976345[/C][C]0.0473095[/C][C]0.0236547[/C][/ROW]
[ROW][C]16[/C][C]0.960899[/C][C]0.0782023[/C][C]0.0391011[/C][/ROW]
[ROW][C]17[/C][C]0.94807[/C][C]0.10386[/C][C]0.0519299[/C][/ROW]
[ROW][C]18[/C][C]0.929272[/C][C]0.141456[/C][C]0.0707278[/C][/ROW]
[ROW][C]19[/C][C]0.906771[/C][C]0.186458[/C][C]0.093229[/C][/ROW]
[ROW][C]20[/C][C]0.901117[/C][C]0.197767[/C][C]0.0988835[/C][/ROW]
[ROW][C]21[/C][C]0.917109[/C][C]0.165781[/C][C]0.0828905[/C][/ROW]
[ROW][C]22[/C][C]0.950863[/C][C]0.0982738[/C][C]0.0491369[/C][/ROW]
[ROW][C]23[/C][C]0.931769[/C][C]0.136461[/C][C]0.0682307[/C][/ROW]
[ROW][C]24[/C][C]0.91521[/C][C]0.169581[/C][C]0.0847905[/C][/ROW]
[ROW][C]25[/C][C]0.890892[/C][C]0.218215[/C][C]0.109108[/C][/ROW]
[ROW][C]26[/C][C]0.998326[/C][C]0.00334823[/C][C]0.00167411[/C][/ROW]
[ROW][C]27[/C][C]0.997449[/C][C]0.00510264[/C][C]0.00255132[/C][/ROW]
[ROW][C]28[/C][C]0.996089[/C][C]0.00782231[/C][C]0.00391115[/C][/ROW]
[ROW][C]29[/C][C]0.994184[/C][C]0.0116325[/C][C]0.00581624[/C][/ROW]
[ROW][C]30[/C][C]0.99682[/C][C]0.0063592[/C][C]0.0031796[/C][/ROW]
[ROW][C]31[/C][C]0.99522[/C][C]0.00956019[/C][C]0.00478009[/C][/ROW]
[ROW][C]32[/C][C]0.993062[/C][C]0.013876[/C][C]0.006938[/C][/ROW]
[ROW][C]33[/C][C]0.9917[/C][C]0.0165997[/C][C]0.00829987[/C][/ROW]
[ROW][C]34[/C][C]0.988191[/C][C]0.0236176[/C][C]0.0118088[/C][/ROW]
[ROW][C]35[/C][C]0.984311[/C][C]0.0313789[/C][C]0.0156895[/C][/ROW]
[ROW][C]36[/C][C]0.978457[/C][C]0.0430859[/C][C]0.0215429[/C][/ROW]
[ROW][C]37[/C][C]0.984204[/C][C]0.0315916[/C][C]0.0157958[/C][/ROW]
[ROW][C]38[/C][C]0.978616[/C][C]0.0427676[/C][C]0.0213838[/C][/ROW]
[ROW][C]39[/C][C]0.976024[/C][C]0.0479515[/C][C]0.0239757[/C][/ROW]
[ROW][C]40[/C][C]0.976324[/C][C]0.0473512[/C][C]0.0236756[/C][/ROW]
[ROW][C]41[/C][C]0.969398[/C][C]0.0612033[/C][C]0.0306016[/C][/ROW]
[ROW][C]42[/C][C]0.967169[/C][C]0.0656613[/C][C]0.0328306[/C][/ROW]
[ROW][C]43[/C][C]0.957539[/C][C]0.0849212[/C][C]0.0424606[/C][/ROW]
[ROW][C]44[/C][C]0.949744[/C][C]0.100513[/C][C]0.0502564[/C][/ROW]
[ROW][C]45[/C][C]0.936286[/C][C]0.127428[/C][C]0.063714[/C][/ROW]
[ROW][C]46[/C][C]0.946767[/C][C]0.106467[/C][C]0.0532335[/C][/ROW]
[ROW][C]47[/C][C]0.932697[/C][C]0.134606[/C][C]0.0673031[/C][/ROW]
[ROW][C]48[/C][C]0.916108[/C][C]0.167785[/C][C]0.0838925[/C][/ROW]
[ROW][C]49[/C][C]0.93356[/C][C]0.13288[/C][C]0.0664399[/C][/ROW]
[ROW][C]50[/C][C]0.929472[/C][C]0.141056[/C][C]0.0705278[/C][/ROW]
[ROW][C]51[/C][C]0.914992[/C][C]0.170015[/C][C]0.0850075[/C][/ROW]
[ROW][C]52[/C][C]0.896761[/C][C]0.206477[/C][C]0.103239[/C][/ROW]
[ROW][C]53[/C][C]0.880663[/C][C]0.238673[/C][C]0.119337[/C][/ROW]
[ROW][C]54[/C][C]0.872576[/C][C]0.254849[/C][C]0.127424[/C][/ROW]
[ROW][C]55[/C][C]0.862955[/C][C]0.274089[/C][C]0.137045[/C][/ROW]
[ROW][C]56[/C][C]0.843548[/C][C]0.312905[/C][C]0.156452[/C][/ROW]
[ROW][C]57[/C][C]0.830359[/C][C]0.339282[/C][C]0.169641[/C][/ROW]
[ROW][C]58[/C][C]0.8014[/C][C]0.397199[/C][C]0.1986[/C][/ROW]
[ROW][C]59[/C][C]0.838025[/C][C]0.32395[/C][C]0.161975[/C][/ROW]
[ROW][C]60[/C][C]0.833054[/C][C]0.333892[/C][C]0.166946[/C][/ROW]
[ROW][C]61[/C][C]0.85162[/C][C]0.29676[/C][C]0.14838[/C][/ROW]
[ROW][C]62[/C][C]0.847759[/C][C]0.304483[/C][C]0.152241[/C][/ROW]
[ROW][C]63[/C][C]0.900527[/C][C]0.198946[/C][C]0.0994729[/C][/ROW]
[ROW][C]64[/C][C]0.888139[/C][C]0.223721[/C][C]0.111861[/C][/ROW]
[ROW][C]65[/C][C]0.878121[/C][C]0.243758[/C][C]0.121879[/C][/ROW]
[ROW][C]66[/C][C]0.954784[/C][C]0.090432[/C][C]0.045216[/C][/ROW]
[ROW][C]67[/C][C]0.953244[/C][C]0.0935113[/C][C]0.0467556[/C][/ROW]
[ROW][C]68[/C][C]0.958064[/C][C]0.083871[/C][C]0.0419355[/C][/ROW]
[ROW][C]69[/C][C]0.952745[/C][C]0.094511[/C][C]0.0472555[/C][/ROW]
[ROW][C]70[/C][C]0.946084[/C][C]0.107833[/C][C]0.0539164[/C][/ROW]
[ROW][C]71[/C][C]0.934804[/C][C]0.130392[/C][C]0.065196[/C][/ROW]
[ROW][C]72[/C][C]0.950233[/C][C]0.0995335[/C][C]0.0497667[/C][/ROW]
[ROW][C]73[/C][C]0.939598[/C][C]0.120803[/C][C]0.0604016[/C][/ROW]
[ROW][C]74[/C][C]0.927435[/C][C]0.145131[/C][C]0.0725654[/C][/ROW]
[ROW][C]75[/C][C]0.922598[/C][C]0.154804[/C][C]0.077402[/C][/ROW]
[ROW][C]76[/C][C]0.908277[/C][C]0.183446[/C][C]0.0917232[/C][/ROW]
[ROW][C]77[/C][C]0.921353[/C][C]0.157295[/C][C]0.0786473[/C][/ROW]
[ROW][C]78[/C][C]0.906834[/C][C]0.186332[/C][C]0.0931658[/C][/ROW]
[ROW][C]79[/C][C]0.897459[/C][C]0.205082[/C][C]0.102541[/C][/ROW]
[ROW][C]80[/C][C]0.890126[/C][C]0.219748[/C][C]0.109874[/C][/ROW]
[ROW][C]81[/C][C]0.870864[/C][C]0.258273[/C][C]0.129136[/C][/ROW]
[ROW][C]82[/C][C]0.850605[/C][C]0.29879[/C][C]0.149395[/C][/ROW]
[ROW][C]83[/C][C]0.843049[/C][C]0.313901[/C][C]0.156951[/C][/ROW]
[ROW][C]84[/C][C]0.821843[/C][C]0.356315[/C][C]0.178157[/C][/ROW]
[ROW][C]85[/C][C]0.795728[/C][C]0.408543[/C][C]0.204272[/C][/ROW]
[ROW][C]86[/C][C]0.771477[/C][C]0.457047[/C][C]0.228523[/C][/ROW]
[ROW][C]87[/C][C]0.742144[/C][C]0.515712[/C][C]0.257856[/C][/ROW]
[ROW][C]88[/C][C]0.711003[/C][C]0.577994[/C][C]0.288997[/C][/ROW]
[ROW][C]89[/C][C]0.78669[/C][C]0.42662[/C][C]0.21331[/C][/ROW]
[ROW][C]90[/C][C]0.821356[/C][C]0.357288[/C][C]0.178644[/C][/ROW]
[ROW][C]91[/C][C]0.796322[/C][C]0.407356[/C][C]0.203678[/C][/ROW]
[ROW][C]92[/C][C]0.77215[/C][C]0.455699[/C][C]0.22785[/C][/ROW]
[ROW][C]93[/C][C]0.748074[/C][C]0.503853[/C][C]0.251926[/C][/ROW]
[ROW][C]94[/C][C]0.722852[/C][C]0.554297[/C][C]0.277148[/C][/ROW]
[ROW][C]95[/C][C]0.695894[/C][C]0.608211[/C][C]0.304106[/C][/ROW]
[ROW][C]96[/C][C]0.670045[/C][C]0.659909[/C][C]0.329955[/C][/ROW]
[ROW][C]97[/C][C]0.642075[/C][C]0.715851[/C][C]0.357925[/C][/ROW]
[ROW][C]98[/C][C]0.64067[/C][C]0.71866[/C][C]0.35933[/C][/ROW]
[ROW][C]99[/C][C]0.606504[/C][C]0.786992[/C][C]0.393496[/C][/ROW]
[ROW][C]100[/C][C]0.597013[/C][C]0.805973[/C][C]0.402987[/C][/ROW]
[ROW][C]101[/C][C]0.572727[/C][C]0.854545[/C][C]0.427273[/C][/ROW]
[ROW][C]102[/C][C]0.543132[/C][C]0.913737[/C][C]0.456868[/C][/ROW]
[ROW][C]103[/C][C]0.593336[/C][C]0.813327[/C][C]0.406664[/C][/ROW]
[ROW][C]104[/C][C]0.582062[/C][C]0.835876[/C][C]0.417938[/C][/ROW]
[ROW][C]105[/C][C]0.598203[/C][C]0.803594[/C][C]0.401797[/C][/ROW]
[ROW][C]106[/C][C]0.570554[/C][C]0.858893[/C][C]0.429446[/C][/ROW]
[ROW][C]107[/C][C]0.563203[/C][C]0.873594[/C][C]0.436797[/C][/ROW]
[ROW][C]108[/C][C]0.600343[/C][C]0.799314[/C][C]0.399657[/C][/ROW]
[ROW][C]109[/C][C]0.574036[/C][C]0.851928[/C][C]0.425964[/C][/ROW]
[ROW][C]110[/C][C]0.547991[/C][C]0.904019[/C][C]0.452009[/C][/ROW]
[ROW][C]111[/C][C]0.552603[/C][C]0.894793[/C][C]0.447397[/C][/ROW]
[ROW][C]112[/C][C]0.58367[/C][C]0.832661[/C][C]0.41633[/C][/ROW]
[ROW][C]113[/C][C]0.583466[/C][C]0.833067[/C][C]0.416534[/C][/ROW]
[ROW][C]114[/C][C]0.668768[/C][C]0.662464[/C][C]0.331232[/C][/ROW]
[ROW][C]115[/C][C]0.63714[/C][C]0.725721[/C][C]0.36286[/C][/ROW]
[ROW][C]116[/C][C]0.614023[/C][C]0.771953[/C][C]0.385977[/C][/ROW]
[ROW][C]117[/C][C]0.584045[/C][C]0.831909[/C][C]0.415955[/C][/ROW]
[ROW][C]118[/C][C]0.560428[/C][C]0.879143[/C][C]0.439572[/C][/ROW]
[ROW][C]119[/C][C]0.526052[/C][C]0.947896[/C][C]0.473948[/C][/ROW]
[ROW][C]120[/C][C]0.494954[/C][C]0.989909[/C][C]0.505046[/C][/ROW]
[ROW][C]121[/C][C]0.463881[/C][C]0.927762[/C][C]0.536119[/C][/ROW]
[ROW][C]122[/C][C]0.432883[/C][C]0.865765[/C][C]0.567117[/C][/ROW]
[ROW][C]123[/C][C]0.406724[/C][C]0.813449[/C][C]0.593276[/C][/ROW]
[ROW][C]124[/C][C]0.374066[/C][C]0.748131[/C][C]0.625934[/C][/ROW]
[ROW][C]125[/C][C]0.363243[/C][C]0.726487[/C][C]0.636757[/C][/ROW]
[ROW][C]126[/C][C]0.333755[/C][C]0.66751[/C][C]0.666245[/C][/ROW]
[ROW][C]127[/C][C]0.320717[/C][C]0.641435[/C][C]0.679283[/C][/ROW]
[ROW][C]128[/C][C]0.424368[/C][C]0.848736[/C][C]0.575632[/C][/ROW]
[ROW][C]129[/C][C]0.407194[/C][C]0.814388[/C][C]0.592806[/C][/ROW]
[ROW][C]130[/C][C]0.395504[/C][C]0.791007[/C][C]0.604496[/C][/ROW]
[ROW][C]131[/C][C]0.380944[/C][C]0.761889[/C][C]0.619056[/C][/ROW]
[ROW][C]132[/C][C]0.352908[/C][C]0.705817[/C][C]0.647092[/C][/ROW]
[ROW][C]133[/C][C]0.373563[/C][C]0.747125[/C][C]0.626437[/C][/ROW]
[ROW][C]134[/C][C]0.347597[/C][C]0.695193[/C][C]0.652403[/C][/ROW]
[ROW][C]135[/C][C]0.358112[/C][C]0.716224[/C][C]0.641888[/C][/ROW]
[ROW][C]136[/C][C]0.34725[/C][C]0.6945[/C][C]0.65275[/C][/ROW]
[ROW][C]137[/C][C]0.319997[/C][C]0.639994[/C][C]0.680003[/C][/ROW]
[ROW][C]138[/C][C]0.296111[/C][C]0.592222[/C][C]0.703889[/C][/ROW]
[ROW][C]139[/C][C]0.271653[/C][C]0.543306[/C][C]0.728347[/C][/ROW]
[ROW][C]140[/C][C]0.248507[/C][C]0.497014[/C][C]0.751493[/C][/ROW]
[ROW][C]141[/C][C]0.222343[/C][C]0.444686[/C][C]0.777657[/C][/ROW]
[ROW][C]142[/C][C]0.228279[/C][C]0.456557[/C][C]0.771721[/C][/ROW]
[ROW][C]143[/C][C]0.204019[/C][C]0.408038[/C][C]0.795981[/C][/ROW]
[ROW][C]144[/C][C]0.183459[/C][C]0.366918[/C][C]0.816541[/C][/ROW]
[ROW][C]145[/C][C]0.170711[/C][C]0.341421[/C][C]0.829289[/C][/ROW]
[ROW][C]146[/C][C]0.163003[/C][C]0.326006[/C][C]0.836997[/C][/ROW]
[ROW][C]147[/C][C]0.170134[/C][C]0.340267[/C][C]0.829866[/C][/ROW]
[ROW][C]148[/C][C]0.185972[/C][C]0.371944[/C][C]0.814028[/C][/ROW]
[ROW][C]149[/C][C]0.202806[/C][C]0.405613[/C][C]0.797194[/C][/ROW]
[ROW][C]150[/C][C]0.204102[/C][C]0.408203[/C][C]0.795898[/C][/ROW]
[ROW][C]151[/C][C]0.18265[/C][C]0.3653[/C][C]0.81735[/C][/ROW]
[ROW][C]152[/C][C]0.163517[/C][C]0.327034[/C][C]0.836483[/C][/ROW]
[ROW][C]153[/C][C]0.175691[/C][C]0.351382[/C][C]0.824309[/C][/ROW]
[ROW][C]154[/C][C]0.190931[/C][C]0.381863[/C][C]0.809069[/C][/ROW]
[ROW][C]155[/C][C]0.178349[/C][C]0.356698[/C][C]0.821651[/C][/ROW]
[ROW][C]156[/C][C]0.156085[/C][C]0.31217[/C][C]0.843915[/C][/ROW]
[ROW][C]157[/C][C]0.13991[/C][C]0.27982[/C][C]0.86009[/C][/ROW]
[ROW][C]158[/C][C]0.227114[/C][C]0.454228[/C][C]0.772886[/C][/ROW]
[ROW][C]159[/C][C]0.245841[/C][C]0.491682[/C][C]0.754159[/C][/ROW]
[ROW][C]160[/C][C]0.2246[/C][C]0.4492[/C][C]0.7754[/C][/ROW]
[ROW][C]161[/C][C]0.203012[/C][C]0.406024[/C][C]0.796988[/C][/ROW]
[ROW][C]162[/C][C]0.179889[/C][C]0.359778[/C][C]0.820111[/C][/ROW]
[ROW][C]163[/C][C]0.158718[/C][C]0.317436[/C][C]0.841282[/C][/ROW]
[ROW][C]164[/C][C]0.261519[/C][C]0.523037[/C][C]0.738481[/C][/ROW]
[ROW][C]165[/C][C]0.25837[/C][C]0.516741[/C][C]0.74163[/C][/ROW]
[ROW][C]166[/C][C]0.255932[/C][C]0.511864[/C][C]0.744068[/C][/ROW]
[ROW][C]167[/C][C]0.227824[/C][C]0.455648[/C][C]0.772176[/C][/ROW]
[ROW][C]168[/C][C]0.206585[/C][C]0.413171[/C][C]0.793415[/C][/ROW]
[ROW][C]169[/C][C]0.264596[/C][C]0.529193[/C][C]0.735404[/C][/ROW]
[ROW][C]170[/C][C]0.293392[/C][C]0.586783[/C][C]0.706608[/C][/ROW]
[ROW][C]171[/C][C]0.265785[/C][C]0.53157[/C][C]0.734215[/C][/ROW]
[ROW][C]172[/C][C]0.261423[/C][C]0.522847[/C][C]0.738577[/C][/ROW]
[ROW][C]173[/C][C]0.431749[/C][C]0.863498[/C][C]0.568251[/C][/ROW]
[ROW][C]174[/C][C]0.417364[/C][C]0.834728[/C][C]0.582636[/C][/ROW]
[ROW][C]175[/C][C]0.439496[/C][C]0.878993[/C][C]0.560504[/C][/ROW]
[ROW][C]176[/C][C]0.452743[/C][C]0.905486[/C][C]0.547257[/C][/ROW]
[ROW][C]177[/C][C]0.509607[/C][C]0.980786[/C][C]0.490393[/C][/ROW]
[ROW][C]178[/C][C]0.475723[/C][C]0.951447[/C][C]0.524277[/C][/ROW]
[ROW][C]179[/C][C]0.453729[/C][C]0.907457[/C][C]0.546271[/C][/ROW]
[ROW][C]180[/C][C]0.456872[/C][C]0.913745[/C][C]0.543128[/C][/ROW]
[ROW][C]181[/C][C]0.419368[/C][C]0.838736[/C][C]0.580632[/C][/ROW]
[ROW][C]182[/C][C]0.412162[/C][C]0.824324[/C][C]0.587838[/C][/ROW]
[ROW][C]183[/C][C]0.374894[/C][C]0.749789[/C][C]0.625106[/C][/ROW]
[ROW][C]184[/C][C]0.348252[/C][C]0.696504[/C][C]0.651748[/C][/ROW]
[ROW][C]185[/C][C]0.364814[/C][C]0.729628[/C][C]0.635186[/C][/ROW]
[ROW][C]186[/C][C]0.355533[/C][C]0.711067[/C][C]0.644467[/C][/ROW]
[ROW][C]187[/C][C]0.320458[/C][C]0.640916[/C][C]0.679542[/C][/ROW]
[ROW][C]188[/C][C]0.291335[/C][C]0.58267[/C][C]0.708665[/C][/ROW]
[ROW][C]189[/C][C]0.259413[/C][C]0.518825[/C][C]0.740587[/C][/ROW]
[ROW][C]190[/C][C]0.237877[/C][C]0.475754[/C][C]0.762123[/C][/ROW]
[ROW][C]191[/C][C]0.246883[/C][C]0.493767[/C][C]0.753117[/C][/ROW]
[ROW][C]192[/C][C]0.228066[/C][C]0.456131[/C][C]0.771934[/C][/ROW]
[ROW][C]193[/C][C]0.245613[/C][C]0.491226[/C][C]0.754387[/C][/ROW]
[ROW][C]194[/C][C]0.234357[/C][C]0.468714[/C][C]0.765643[/C][/ROW]
[ROW][C]195[/C][C]0.23432[/C][C]0.468641[/C][C]0.76568[/C][/ROW]
[ROW][C]196[/C][C]0.24656[/C][C]0.49312[/C][C]0.75344[/C][/ROW]
[ROW][C]197[/C][C]0.295996[/C][C]0.591992[/C][C]0.704004[/C][/ROW]
[ROW][C]198[/C][C]0.277086[/C][C]0.554173[/C][C]0.722914[/C][/ROW]
[ROW][C]199[/C][C]0.313585[/C][C]0.627171[/C][C]0.686415[/C][/ROW]
[ROW][C]200[/C][C]0.280355[/C][C]0.560709[/C][C]0.719645[/C][/ROW]
[ROW][C]201[/C][C]0.317533[/C][C]0.635066[/C][C]0.682467[/C][/ROW]
[ROW][C]202[/C][C]0.294505[/C][C]0.58901[/C][C]0.705495[/C][/ROW]
[ROW][C]203[/C][C]0.342223[/C][C]0.684446[/C][C]0.657777[/C][/ROW]
[ROW][C]204[/C][C]0.304622[/C][C]0.609243[/C][C]0.695378[/C][/ROW]
[ROW][C]205[/C][C]0.270056[/C][C]0.540112[/C][C]0.729944[/C][/ROW]
[ROW][C]206[/C][C]0.248362[/C][C]0.496723[/C][C]0.751638[/C][/ROW]
[ROW][C]207[/C][C]0.216334[/C][C]0.432667[/C][C]0.783666[/C][/ROW]
[ROW][C]208[/C][C]0.23991[/C][C]0.47982[/C][C]0.76009[/C][/ROW]
[ROW][C]209[/C][C]0.207473[/C][C]0.414946[/C][C]0.792527[/C][/ROW]
[ROW][C]210[/C][C]0.215705[/C][C]0.43141[/C][C]0.784295[/C][/ROW]
[ROW][C]211[/C][C]0.241766[/C][C]0.483532[/C][C]0.758234[/C][/ROW]
[ROW][C]212[/C][C]0.230614[/C][C]0.461228[/C][C]0.769386[/C][/ROW]
[ROW][C]213[/C][C]0.20356[/C][C]0.40712[/C][C]0.79644[/C][/ROW]
[ROW][C]214[/C][C]0.250949[/C][C]0.501897[/C][C]0.749051[/C][/ROW]
[ROW][C]215[/C][C]0.224962[/C][C]0.449925[/C][C]0.775038[/C][/ROW]
[ROW][C]216[/C][C]0.213308[/C][C]0.426617[/C][C]0.786692[/C][/ROW]
[ROW][C]217[/C][C]0.244936[/C][C]0.489872[/C][C]0.755064[/C][/ROW]
[ROW][C]218[/C][C]0.213474[/C][C]0.426948[/C][C]0.786526[/C][/ROW]
[ROW][C]219[/C][C]0.202326[/C][C]0.404651[/C][C]0.797674[/C][/ROW]
[ROW][C]220[/C][C]0.216858[/C][C]0.433716[/C][C]0.783142[/C][/ROW]
[ROW][C]221[/C][C]0.230122[/C][C]0.460244[/C][C]0.769878[/C][/ROW]
[ROW][C]222[/C][C]0.221922[/C][C]0.443843[/C][C]0.778078[/C][/ROW]
[ROW][C]223[/C][C]0.208047[/C][C]0.416094[/C][C]0.791953[/C][/ROW]
[ROW][C]224[/C][C]0.175341[/C][C]0.350682[/C][C]0.824659[/C][/ROW]
[ROW][C]225[/C][C]0.173277[/C][C]0.346555[/C][C]0.826723[/C][/ROW]
[ROW][C]226[/C][C]0.206316[/C][C]0.412631[/C][C]0.793684[/C][/ROW]
[ROW][C]227[/C][C]0.4131[/C][C]0.8262[/C][C]0.5869[/C][/ROW]
[ROW][C]228[/C][C]0.384424[/C][C]0.768848[/C][C]0.615576[/C][/ROW]
[ROW][C]229[/C][C]0.358025[/C][C]0.71605[/C][C]0.641975[/C][/ROW]
[ROW][C]230[/C][C]0.342126[/C][C]0.684253[/C][C]0.657874[/C][/ROW]
[ROW][C]231[/C][C]0.299236[/C][C]0.598473[/C][C]0.700764[/C][/ROW]
[ROW][C]232[/C][C]0.342571[/C][C]0.685143[/C][C]0.657429[/C][/ROW]
[ROW][C]233[/C][C]0.296861[/C][C]0.593722[/C][C]0.703139[/C][/ROW]
[ROW][C]234[/C][C]0.25261[/C][C]0.505221[/C][C]0.74739[/C][/ROW]
[ROW][C]235[/C][C]0.252181[/C][C]0.504361[/C][C]0.747819[/C][/ROW]
[ROW][C]236[/C][C]0.227962[/C][C]0.455924[/C][C]0.772038[/C][/ROW]
[ROW][C]237[/C][C]0.194714[/C][C]0.389428[/C][C]0.805286[/C][/ROW]
[ROW][C]238[/C][C]0.155101[/C][C]0.310201[/C][C]0.844899[/C][/ROW]
[ROW][C]239[/C][C]0.288095[/C][C]0.57619[/C][C]0.711905[/C][/ROW]
[ROW][C]240[/C][C]0.277502[/C][C]0.555004[/C][C]0.722498[/C][/ROW]
[ROW][C]241[/C][C]0.245863[/C][C]0.491725[/C][C]0.754137[/C][/ROW]
[ROW][C]242[/C][C]0.472151[/C][C]0.944303[/C][C]0.527849[/C][/ROW]
[ROW][C]243[/C][C]0.429248[/C][C]0.858495[/C][C]0.570752[/C][/ROW]
[ROW][C]244[/C][C]0.365946[/C][C]0.731892[/C][C]0.634054[/C][/ROW]
[ROW][C]245[/C][C]0.492858[/C][C]0.985715[/C][C]0.507142[/C][/ROW]
[ROW][C]246[/C][C]0.407571[/C][C]0.815142[/C][C]0.592429[/C][/ROW]
[ROW][C]247[/C][C]0.324082[/C][C]0.648164[/C][C]0.675918[/C][/ROW]
[ROW][C]248[/C][C]0.49086[/C][C]0.981721[/C][C]0.50914[/C][/ROW]
[ROW][C]249[/C][C]0.390616[/C][C]0.781231[/C][C]0.609384[/C][/ROW]
[ROW][C]250[/C][C]0.294183[/C][C]0.588367[/C][C]0.705817[/C][/ROW]
[ROW][C]251[/C][C]0.444199[/C][C]0.888399[/C][C]0.555801[/C][/ROW]
[ROW][C]252[/C][C]0.921602[/C][C]0.156796[/C][C]0.078398[/C][/ROW]
[ROW][C]253[/C][C]0.840563[/C][C]0.318874[/C][C]0.159437[/C][/ROW]
[ROW][C]254[/C][C]0.790589[/C][C]0.418823[/C][C]0.209411[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222037&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222037&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
100.05059810.1011960.949402
110.01419620.02839230.985804
120.8276930.3446140.172307
130.9657070.06858590.034293
140.9675350.06493030.0324651
150.9763450.04730950.0236547
160.9608990.07820230.0391011
170.948070.103860.0519299
180.9292720.1414560.0707278
190.9067710.1864580.093229
200.9011170.1977670.0988835
210.9171090.1657810.0828905
220.9508630.09827380.0491369
230.9317690.1364610.0682307
240.915210.1695810.0847905
250.8908920.2182150.109108
260.9983260.003348230.00167411
270.9974490.005102640.00255132
280.9960890.007822310.00391115
290.9941840.01163250.00581624
300.996820.00635920.0031796
310.995220.009560190.00478009
320.9930620.0138760.006938
330.99170.01659970.00829987
340.9881910.02361760.0118088
350.9843110.03137890.0156895
360.9784570.04308590.0215429
370.9842040.03159160.0157958
380.9786160.04276760.0213838
390.9760240.04795150.0239757
400.9763240.04735120.0236756
410.9693980.06120330.0306016
420.9671690.06566130.0328306
430.9575390.08492120.0424606
440.9497440.1005130.0502564
450.9362860.1274280.063714
460.9467670.1064670.0532335
470.9326970.1346060.0673031
480.9161080.1677850.0838925
490.933560.132880.0664399
500.9294720.1410560.0705278
510.9149920.1700150.0850075
520.8967610.2064770.103239
530.8806630.2386730.119337
540.8725760.2548490.127424
550.8629550.2740890.137045
560.8435480.3129050.156452
570.8303590.3392820.169641
580.80140.3971990.1986
590.8380250.323950.161975
600.8330540.3338920.166946
610.851620.296760.14838
620.8477590.3044830.152241
630.9005270.1989460.0994729
640.8881390.2237210.111861
650.8781210.2437580.121879
660.9547840.0904320.045216
670.9532440.09351130.0467556
680.9580640.0838710.0419355
690.9527450.0945110.0472555
700.9460840.1078330.0539164
710.9348040.1303920.065196
720.9502330.09953350.0497667
730.9395980.1208030.0604016
740.9274350.1451310.0725654
750.9225980.1548040.077402
760.9082770.1834460.0917232
770.9213530.1572950.0786473
780.9068340.1863320.0931658
790.8974590.2050820.102541
800.8901260.2197480.109874
810.8708640.2582730.129136
820.8506050.298790.149395
830.8430490.3139010.156951
840.8218430.3563150.178157
850.7957280.4085430.204272
860.7714770.4570470.228523
870.7421440.5157120.257856
880.7110030.5779940.288997
890.786690.426620.21331
900.8213560.3572880.178644
910.7963220.4073560.203678
920.772150.4556990.22785
930.7480740.5038530.251926
940.7228520.5542970.277148
950.6958940.6082110.304106
960.6700450.6599090.329955
970.6420750.7158510.357925
980.640670.718660.35933
990.6065040.7869920.393496
1000.5970130.8059730.402987
1010.5727270.8545450.427273
1020.5431320.9137370.456868
1030.5933360.8133270.406664
1040.5820620.8358760.417938
1050.5982030.8035940.401797
1060.5705540.8588930.429446
1070.5632030.8735940.436797
1080.6003430.7993140.399657
1090.5740360.8519280.425964
1100.5479910.9040190.452009
1110.5526030.8947930.447397
1120.583670.8326610.41633
1130.5834660.8330670.416534
1140.6687680.6624640.331232
1150.637140.7257210.36286
1160.6140230.7719530.385977
1170.5840450.8319090.415955
1180.5604280.8791430.439572
1190.5260520.9478960.473948
1200.4949540.9899090.505046
1210.4638810.9277620.536119
1220.4328830.8657650.567117
1230.4067240.8134490.593276
1240.3740660.7481310.625934
1250.3632430.7264870.636757
1260.3337550.667510.666245
1270.3207170.6414350.679283
1280.4243680.8487360.575632
1290.4071940.8143880.592806
1300.3955040.7910070.604496
1310.3809440.7618890.619056
1320.3529080.7058170.647092
1330.3735630.7471250.626437
1340.3475970.6951930.652403
1350.3581120.7162240.641888
1360.347250.69450.65275
1370.3199970.6399940.680003
1380.2961110.5922220.703889
1390.2716530.5433060.728347
1400.2485070.4970140.751493
1410.2223430.4446860.777657
1420.2282790.4565570.771721
1430.2040190.4080380.795981
1440.1834590.3669180.816541
1450.1707110.3414210.829289
1460.1630030.3260060.836997
1470.1701340.3402670.829866
1480.1859720.3719440.814028
1490.2028060.4056130.797194
1500.2041020.4082030.795898
1510.182650.36530.81735
1520.1635170.3270340.836483
1530.1756910.3513820.824309
1540.1909310.3818630.809069
1550.1783490.3566980.821651
1560.1560850.312170.843915
1570.139910.279820.86009
1580.2271140.4542280.772886
1590.2458410.4916820.754159
1600.22460.44920.7754
1610.2030120.4060240.796988
1620.1798890.3597780.820111
1630.1587180.3174360.841282
1640.2615190.5230370.738481
1650.258370.5167410.74163
1660.2559320.5118640.744068
1670.2278240.4556480.772176
1680.2065850.4131710.793415
1690.2645960.5291930.735404
1700.2933920.5867830.706608
1710.2657850.531570.734215
1720.2614230.5228470.738577
1730.4317490.8634980.568251
1740.4173640.8347280.582636
1750.4394960.8789930.560504
1760.4527430.9054860.547257
1770.5096070.9807860.490393
1780.4757230.9514470.524277
1790.4537290.9074570.546271
1800.4568720.9137450.543128
1810.4193680.8387360.580632
1820.4121620.8243240.587838
1830.3748940.7497890.625106
1840.3482520.6965040.651748
1850.3648140.7296280.635186
1860.3555330.7110670.644467
1870.3204580.6409160.679542
1880.2913350.582670.708665
1890.2594130.5188250.740587
1900.2378770.4757540.762123
1910.2468830.4937670.753117
1920.2280660.4561310.771934
1930.2456130.4912260.754387
1940.2343570.4687140.765643
1950.234320.4686410.76568
1960.246560.493120.75344
1970.2959960.5919920.704004
1980.2770860.5541730.722914
1990.3135850.6271710.686415
2000.2803550.5607090.719645
2010.3175330.6350660.682467
2020.2945050.589010.705495
2030.3422230.6844460.657777
2040.3046220.6092430.695378
2050.2700560.5401120.729944
2060.2483620.4967230.751638
2070.2163340.4326670.783666
2080.239910.479820.76009
2090.2074730.4149460.792527
2100.2157050.431410.784295
2110.2417660.4835320.758234
2120.2306140.4612280.769386
2130.203560.407120.79644
2140.2509490.5018970.749051
2150.2249620.4499250.775038
2160.2133080.4266170.786692
2170.2449360.4898720.755064
2180.2134740.4269480.786526
2190.2023260.4046510.797674
2200.2168580.4337160.783142
2210.2301220.4602440.769878
2220.2219220.4438430.778078
2230.2080470.4160940.791953
2240.1753410.3506820.824659
2250.1732770.3465550.826723
2260.2063160.4126310.793684
2270.41310.82620.5869
2280.3844240.7688480.615576
2290.3580250.716050.641975
2300.3421260.6842530.657874
2310.2992360.5984730.700764
2320.3425710.6851430.657429
2330.2968610.5937220.703139
2340.252610.5052210.74739
2350.2521810.5043610.747819
2360.2279620.4559240.772038
2370.1947140.3894280.805286
2380.1551010.3102010.844899
2390.2880950.576190.711905
2400.2775020.5550040.722498
2410.2458630.4917250.754137
2420.4721510.9443030.527849
2430.4292480.8584950.570752
2440.3659460.7318920.634054
2450.4928580.9857150.507142
2460.4075710.8151420.592429
2470.3240820.6481640.675918
2480.490860.9817210.50914
2490.3906160.7812310.609384
2500.2941830.5883670.705817
2510.4441990.8883990.555801
2520.9216020.1567960.078398
2530.8405630.3188740.159437
2540.7905890.4188230.209411






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.0204082NOK
5% type I error level170.0693878NOK
10% type I error level290.118367NOK

\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 & 5 & 0.0204082 & NOK \tabularnewline
5% type I error level & 17 & 0.0693878 & NOK \tabularnewline
10% type I error level & 29 & 0.118367 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222037&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]5[/C][C]0.0204082[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]17[/C][C]0.0693878[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]29[/C][C]0.118367[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222037&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222037&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 level50.0204082NOK
5% type I error level170.0693878NOK
10% type I error level290.118367NOK


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