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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 computationSun, 03 Nov 2013 06:36:38 -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/03/t13834786200fjj50g4ipsvqz1.htm/, Retrieved Mon, 29 Apr 2024 14:17:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221870, Retrieved Mon, 29 Apr 2024 14:17:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [WS7] [2013-11-03 11:36:38] [7363efa32e0ba5074b153190cd9b70c3] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time23 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 & 23 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221870&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]23 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=221870&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221870&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 time23 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 22.7566 + 0.428907Separate[t] + 0.110822Learning[t] -0.0623794Software[t] + 0.00934045Happiness[t] -0.0422823Depression[t] -0.0543569Sport1[t] + 0.121613Sport2[t] -0.480224Month[t] -0.00121396t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  22.7566 +  0.428907Separate[t] +  0.110822Learning[t] -0.0623794Software[t] +  0.00934045Happiness[t] -0.0422823Depression[t] -0.0543569Sport1[t] +  0.121613Sport2[t] -0.480224Month[t] -0.00121396t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221870&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  22.7566 +  0.428907Separate[t] +  0.110822Learning[t] -0.0623794Software[t] +  0.00934045Happiness[t] -0.0422823Depression[t] -0.0543569Sport1[t] +  0.121613Sport2[t] -0.480224Month[t] -0.00121396t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221870&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221870&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
Connected[t] = + 22.7566 + 0.428907Separate[t] + 0.110822Learning[t] -0.0623794Software[t] + 0.00934045Happiness[t] -0.0422823Depression[t] -0.0543569Sport1[t] + 0.121613Sport2[t] -0.480224Month[t] -0.00121396t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)22.75666.901133.2980.001114830.000557417
Separate0.4289070.05779397.4211.74467e-128.72334e-13
Learning0.1108220.1131140.97970.3281470.164074
Software-0.06237940.116927-0.53350.5941610.29708
Happiness0.009340450.1052340.088760.9293430.464672
Depression-0.04228230.0767155-0.55120.5820110.291005
Sport1-0.05435690.0685519-0.79290.4285580.214279
Sport20.1216130.1016451.1960.2326380.116319
Month-0.4802240.737854-0.65080.5157390.25787
t-0.001213960.00785934-0.15450.8773690.438685

\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) & 22.7566 & 6.90113 & 3.298 & 0.00111483 & 0.000557417 \tabularnewline
Separate & 0.428907 & 0.0577939 & 7.421 & 1.74467e-12 & 8.72334e-13 \tabularnewline
Learning & 0.110822 & 0.113114 & 0.9797 & 0.328147 & 0.164074 \tabularnewline
Software & -0.0623794 & 0.116927 & -0.5335 & 0.594161 & 0.29708 \tabularnewline
Happiness & 0.00934045 & 0.105234 & 0.08876 & 0.929343 & 0.464672 \tabularnewline
Depression & -0.0422823 & 0.0767155 & -0.5512 & 0.582011 & 0.291005 \tabularnewline
Sport1 & -0.0543569 & 0.0685519 & -0.7929 & 0.428558 & 0.214279 \tabularnewline
Sport2 & 0.121613 & 0.101645 & 1.196 & 0.232638 & 0.116319 \tabularnewline
Month & -0.480224 & 0.737854 & -0.6508 & 0.515739 & 0.25787 \tabularnewline
t & -0.00121396 & 0.00785934 & -0.1545 & 0.877369 & 0.438685 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221870&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]22.7566[/C][C]6.90113[/C][C]3.298[/C][C]0.00111483[/C][C]0.000557417[/C][/ROW]
[ROW][C]Separate[/C][C]0.428907[/C][C]0.0577939[/C][C]7.421[/C][C]1.74467e-12[/C][C]8.72334e-13[/C][/ROW]
[ROW][C]Learning[/C][C]0.110822[/C][C]0.113114[/C][C]0.9797[/C][C]0.328147[/C][C]0.164074[/C][/ROW]
[ROW][C]Software[/C][C]-0.0623794[/C][C]0.116927[/C][C]-0.5335[/C][C]0.594161[/C][C]0.29708[/C][/ROW]
[ROW][C]Happiness[/C][C]0.00934045[/C][C]0.105234[/C][C]0.08876[/C][C]0.929343[/C][C]0.464672[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0422823[/C][C]0.0767155[/C][C]-0.5512[/C][C]0.582011[/C][C]0.291005[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.0543569[/C][C]0.0685519[/C][C]-0.7929[/C][C]0.428558[/C][C]0.214279[/C][/ROW]
[ROW][C]Sport2[/C][C]0.121613[/C][C]0.101645[/C][C]1.196[/C][C]0.232638[/C][C]0.116319[/C][/ROW]
[ROW][C]Month[/C][C]-0.480224[/C][C]0.737854[/C][C]-0.6508[/C][C]0.515739[/C][C]0.25787[/C][/ROW]
[ROW][C]t[/C][C]-0.00121396[/C][C]0.00785934[/C][C]-0.1545[/C][C]0.877369[/C][C]0.438685[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221870&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221870&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)22.75666.901133.2980.001114830.000557417
Separate0.4289070.05779397.4211.74467e-128.72334e-13
Learning0.1108220.1131140.97970.3281470.164074
Software-0.06237940.116927-0.53350.5941610.29708
Happiness0.009340450.1052340.088760.9293430.464672
Depression-0.04228230.0767155-0.55120.5820110.291005
Sport1-0.05435690.0685519-0.79290.4285580.214279
Sport20.1216130.1016451.1960.2326380.116319
Month-0.4802240.737854-0.65080.5157390.25787
t-0.001213960.00785934-0.15450.8773690.438685






Multiple Linear Regression - Regression Statistics
Multiple R0.493598
R-squared0.243639
Adjusted R-squared0.216839
F-TEST (value)9.09094
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value6.51679e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.35975
Sum Squared Residuals2867.13

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.493598 \tabularnewline
R-squared & 0.243639 \tabularnewline
Adjusted R-squared & 0.216839 \tabularnewline
F-TEST (value) & 9.09094 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 254 \tabularnewline
p-value & 6.51679e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.35975 \tabularnewline
Sum Squared Residuals & 2867.13 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221870&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.493598[/C][/ROW]
[ROW][C]R-squared[/C][C]0.243639[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.216839[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]9.09094[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]254[/C][/ROW]
[ROW][C]p-value[/C][C]6.51679e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.35975[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2867.13[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221870&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221870&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.493598
R-squared0.243639
Adjusted R-squared0.216839
F-TEST (value)9.09094
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value6.51679e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.35975
Sum Squared Residuals2867.13






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14136.0584.94195
23934.63784.36218
33035.6436-5.6436
43134.8206-3.82063
53435.7632-1.76324
63532.81922.18079
73933.89865.10141
83435.9307-1.93069
93635.40580.594182
103736.9970.00304733
113834.26753.73249
123634.94461.05538
133835.38022.61985
143936.43852.56151
153336.696-3.69597
163234.247-2.24705
173634.11211.88786
183837.65650.34353
193937.23381.76615
203234.0394-2.03943
213234.815-2.81502
223133.8941-2.89409
233936.70122.29885
243737.1956-0.195631
253934.60754.39245
264134.27196.72813
273635.34550.654512
283336.1561-3.15605
293334.3588-1.35881
303434.7419-0.741945
313133.9862-2.98624
322733.5167-6.51673
333733.72433.27566
343436.9636-2.9636
353432.72871.27131
363234.5192-2.5192
372932.5462-3.5462
383634.34811.65192
392934.0318-5.03175
403534.7450.254962
413734.46892.53107
423434.1722-0.172184
433834.27733.7227
443533.92641.07361
453832.34925.65082
463734.58232.4177
473837.30120.698794
483335.1277-2.12774
493636.3704-0.370436
503833.9544.046
513236.7349-4.73488
523232.9278-0.927802
533233.5223-1.52234
543437.3739-3.37392
553233.3789-1.3789
563735.66731.33272
573935.02283.97722
582935.197-6.19701
593735.73031.26966
603534.99620.00382939
613031.5029-1.50291
623834.86793.1321
633435.3539-1.35392
643134.7162-3.71623
653433.34480.655216
663536.0556-1.05563
673634.91041.08961
683031.3837-1.3837
693936.39542.60456
703535.6688-0.668818
713835.20822.79184
723135.6239-4.62393
733436.7396-2.73956
743837.40240.597619
753431.63942.36061
763932.97116.02892
773735.72621.27384
783433.24570.75426
792832.9675-4.96747
803731.28125.71883
813335.2963-2.29629
823536.1218-1.12179
833733.82473.17532
843234.4814-2.48138
853333.4081-0.408076
863836.55371.44632
873334.4367-1.43668
882933.1623-4.1623
893333.4736-0.473575
903135.2895-4.28947
913633.08232.91766
923537.4516-2.45162
933231.64130.358675
942932.3597-3.35975
953935.48063.51935
963734.72612.27391
973533.36451.63552
983734.5712.42897
993235.3829-3.3829
1003835.25092.74912
1013734.87062.12942
1023636.3264-0.32645
1033231.97270.0272964
1043336.5277-3.52767
1054032.81467.18539
1063835.24192.75812
1074136.41014.58995
1083634.45911.5409
1094336.95596.04406
1103034.68-4.67996
1113133.6705-2.67046
1123238.163-6.16302
1133231.49430.505669
1143734.35032.6497
1153734.22112.77893
1163336.3272-3.32717
1173437.3112-3.31124
1183334.6847-1.68472
1193835.56832.43172
1203334.9886-1.98856
1213131.3521-0.352067
1223836.63011.36989
1233736.38990.610112
1243633.13092.86912
1253133.8719-2.87195
1263934.18214.81791
1274436.78997.21011
1283336.0955-3.09549
1293533.62311.37691
1303234.0046-2.00456
1312832.4578-4.45778
1324036.06383.9362
1332732.141-5.141
1343736.09760.90238
1353232.5252-0.525205
1362828.3127-0.312689
1373434.998-0.998026
1383034.1412-4.14124
1393534.260.740034
1403134.3033-3.30332
1413234.4354-2.43539
1423035.9462-5.94623
1433035.135-5.13497
1443129.77281.22718
1454033.21896.78107
1463231.76820.231779
1473634.82161.17835
1483233.2598-1.25982
1493533.28461.71538
1503836.63841.36158
1514235.31636.68375
1523436.1757-2.17574
1533536.9368-1.93685
1543834.64243.35762
1553332.99430.0057328
1563633.00342.99656
1573235.7173-3.71729
1583336.0591-3.05907
1593433.95050.049486
1603235.7551-3.7551
1613435.4297-1.4297
1622729.9664-2.96638
1633130.11040.889615
1643833.36684.63317
1653435.6877-1.68773
1662430.9572-6.95722
1673033.5116-3.51164
1682629.312-3.31205
1693435.2905-1.29051
1702734.503-7.50299
1713731.98295.01706
1723635.23880.761169
1734134.03466.96541
1742928.99830.00165742
1753630.88955.11055
1763234.1004-2.1004
1773733.18473.81534
1783031.4802-1.48022
1793132.5515-1.55151
1803834.48983.51024
1813634.46331.53672
1823532.05032.94973
1833135.0836-4.08356
1843833.08644.91361
1852230.9323-8.93226
1863234.2515-2.2515
1873633.77352.22647
1883932.66286.33722
1892830.2791-2.27907
1903234.2332-2.23323
1913232.3111-0.311127
1923836.40411.59591
1933233.3995-1.39949
1943535.2374-0.237402
1953232.7648-0.76476
1963735.59911.40087
1973432.61351.38653
1983335.3409-2.34091
1993332.77750.222505
2002632.7182-6.71822
2013032.0876-2.08755
2022431.7705-7.77045
2033431.90612.09389
2043432.38351.61652
2053333.9621-0.962072
2063434.6815-0.681483
2073535.8711-0.871147
2083534.14550.854459
2093633.04512.95494
2103433.56840.431596
2113432.70421.29582
2124138.23392.76615
2133236.0988-4.09881
2143033.3112-3.31125
2153533.8561.14397
2162829.9057-1.90568
2173334.8175-1.81748
2183934.15574.84432
2193633.36852.63152
2203636.263-0.262986
2213533.11031.88965
2223833.83244.16764
2233332.65410.345894
2243132.8925-1.89252
2253431.98922.01077
2263234.2337-2.23372
2273132.6416-1.64162
2283333.0853-0.0853386
2293432.63011.36988
2303433.95260.0474285
2313432.12071.87927
2323335.092-2.092
2333234.1579-2.15793
2344133.54867.45138
2353432.9371.06305
2363632.01423.98583
2373731.46555.53454
2383630.3255.67503
2392932.4487-3.44868
2403731.75425.24581
2412733.0888-6.08877
2423533.36111.63892
2432830.6489-2.64894
2443533.11081.8892
2453733.04773.95225
2462933.6323-4.6323
2473234.1964-2.19641
2483631.73824.26175
2491927.5916-8.59157
2502126.7203-5.72027
2513133.3856-2.38557
2523332.44340.556595
2533633.85342.14662
2543333.2332-0.233197
2553733.07263.92743
2563433.24790.752074
2573534.4050.594963
2583132.7558-1.75581
2593733.34723.65284
2603531.84933.15074
2612731.7665-4.76649
2623434.8476-0.847618
2634033.88596.11415
2642932.8078-3.80781

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 36.058 & 4.94195 \tabularnewline
2 & 39 & 34.6378 & 4.36218 \tabularnewline
3 & 30 & 35.6436 & -5.6436 \tabularnewline
4 & 31 & 34.8206 & -3.82063 \tabularnewline
5 & 34 & 35.7632 & -1.76324 \tabularnewline
6 & 35 & 32.8192 & 2.18079 \tabularnewline
7 & 39 & 33.8986 & 5.10141 \tabularnewline
8 & 34 & 35.9307 & -1.93069 \tabularnewline
9 & 36 & 35.4058 & 0.594182 \tabularnewline
10 & 37 & 36.997 & 0.00304733 \tabularnewline
11 & 38 & 34.2675 & 3.73249 \tabularnewline
12 & 36 & 34.9446 & 1.05538 \tabularnewline
13 & 38 & 35.3802 & 2.61985 \tabularnewline
14 & 39 & 36.4385 & 2.56151 \tabularnewline
15 & 33 & 36.696 & -3.69597 \tabularnewline
16 & 32 & 34.247 & -2.24705 \tabularnewline
17 & 36 & 34.1121 & 1.88786 \tabularnewline
18 & 38 & 37.6565 & 0.34353 \tabularnewline
19 & 39 & 37.2338 & 1.76615 \tabularnewline
20 & 32 & 34.0394 & -2.03943 \tabularnewline
21 & 32 & 34.815 & -2.81502 \tabularnewline
22 & 31 & 33.8941 & -2.89409 \tabularnewline
23 & 39 & 36.7012 & 2.29885 \tabularnewline
24 & 37 & 37.1956 & -0.195631 \tabularnewline
25 & 39 & 34.6075 & 4.39245 \tabularnewline
26 & 41 & 34.2719 & 6.72813 \tabularnewline
27 & 36 & 35.3455 & 0.654512 \tabularnewline
28 & 33 & 36.1561 & -3.15605 \tabularnewline
29 & 33 & 34.3588 & -1.35881 \tabularnewline
30 & 34 & 34.7419 & -0.741945 \tabularnewline
31 & 31 & 33.9862 & -2.98624 \tabularnewline
32 & 27 & 33.5167 & -6.51673 \tabularnewline
33 & 37 & 33.7243 & 3.27566 \tabularnewline
34 & 34 & 36.9636 & -2.9636 \tabularnewline
35 & 34 & 32.7287 & 1.27131 \tabularnewline
36 & 32 & 34.5192 & -2.5192 \tabularnewline
37 & 29 & 32.5462 & -3.5462 \tabularnewline
38 & 36 & 34.3481 & 1.65192 \tabularnewline
39 & 29 & 34.0318 & -5.03175 \tabularnewline
40 & 35 & 34.745 & 0.254962 \tabularnewline
41 & 37 & 34.4689 & 2.53107 \tabularnewline
42 & 34 & 34.1722 & -0.172184 \tabularnewline
43 & 38 & 34.2773 & 3.7227 \tabularnewline
44 & 35 & 33.9264 & 1.07361 \tabularnewline
45 & 38 & 32.3492 & 5.65082 \tabularnewline
46 & 37 & 34.5823 & 2.4177 \tabularnewline
47 & 38 & 37.3012 & 0.698794 \tabularnewline
48 & 33 & 35.1277 & -2.12774 \tabularnewline
49 & 36 & 36.3704 & -0.370436 \tabularnewline
50 & 38 & 33.954 & 4.046 \tabularnewline
51 & 32 & 36.7349 & -4.73488 \tabularnewline
52 & 32 & 32.9278 & -0.927802 \tabularnewline
53 & 32 & 33.5223 & -1.52234 \tabularnewline
54 & 34 & 37.3739 & -3.37392 \tabularnewline
55 & 32 & 33.3789 & -1.3789 \tabularnewline
56 & 37 & 35.6673 & 1.33272 \tabularnewline
57 & 39 & 35.0228 & 3.97722 \tabularnewline
58 & 29 & 35.197 & -6.19701 \tabularnewline
59 & 37 & 35.7303 & 1.26966 \tabularnewline
60 & 35 & 34.9962 & 0.00382939 \tabularnewline
61 & 30 & 31.5029 & -1.50291 \tabularnewline
62 & 38 & 34.8679 & 3.1321 \tabularnewline
63 & 34 & 35.3539 & -1.35392 \tabularnewline
64 & 31 & 34.7162 & -3.71623 \tabularnewline
65 & 34 & 33.3448 & 0.655216 \tabularnewline
66 & 35 & 36.0556 & -1.05563 \tabularnewline
67 & 36 & 34.9104 & 1.08961 \tabularnewline
68 & 30 & 31.3837 & -1.3837 \tabularnewline
69 & 39 & 36.3954 & 2.60456 \tabularnewline
70 & 35 & 35.6688 & -0.668818 \tabularnewline
71 & 38 & 35.2082 & 2.79184 \tabularnewline
72 & 31 & 35.6239 & -4.62393 \tabularnewline
73 & 34 & 36.7396 & -2.73956 \tabularnewline
74 & 38 & 37.4024 & 0.597619 \tabularnewline
75 & 34 & 31.6394 & 2.36061 \tabularnewline
76 & 39 & 32.9711 & 6.02892 \tabularnewline
77 & 37 & 35.7262 & 1.27384 \tabularnewline
78 & 34 & 33.2457 & 0.75426 \tabularnewline
79 & 28 & 32.9675 & -4.96747 \tabularnewline
80 & 37 & 31.2812 & 5.71883 \tabularnewline
81 & 33 & 35.2963 & -2.29629 \tabularnewline
82 & 35 & 36.1218 & -1.12179 \tabularnewline
83 & 37 & 33.8247 & 3.17532 \tabularnewline
84 & 32 & 34.4814 & -2.48138 \tabularnewline
85 & 33 & 33.4081 & -0.408076 \tabularnewline
86 & 38 & 36.5537 & 1.44632 \tabularnewline
87 & 33 & 34.4367 & -1.43668 \tabularnewline
88 & 29 & 33.1623 & -4.1623 \tabularnewline
89 & 33 & 33.4736 & -0.473575 \tabularnewline
90 & 31 & 35.2895 & -4.28947 \tabularnewline
91 & 36 & 33.0823 & 2.91766 \tabularnewline
92 & 35 & 37.4516 & -2.45162 \tabularnewline
93 & 32 & 31.6413 & 0.358675 \tabularnewline
94 & 29 & 32.3597 & -3.35975 \tabularnewline
95 & 39 & 35.4806 & 3.51935 \tabularnewline
96 & 37 & 34.7261 & 2.27391 \tabularnewline
97 & 35 & 33.3645 & 1.63552 \tabularnewline
98 & 37 & 34.571 & 2.42897 \tabularnewline
99 & 32 & 35.3829 & -3.3829 \tabularnewline
100 & 38 & 35.2509 & 2.74912 \tabularnewline
101 & 37 & 34.8706 & 2.12942 \tabularnewline
102 & 36 & 36.3264 & -0.32645 \tabularnewline
103 & 32 & 31.9727 & 0.0272964 \tabularnewline
104 & 33 & 36.5277 & -3.52767 \tabularnewline
105 & 40 & 32.8146 & 7.18539 \tabularnewline
106 & 38 & 35.2419 & 2.75812 \tabularnewline
107 & 41 & 36.4101 & 4.58995 \tabularnewline
108 & 36 & 34.4591 & 1.5409 \tabularnewline
109 & 43 & 36.9559 & 6.04406 \tabularnewline
110 & 30 & 34.68 & -4.67996 \tabularnewline
111 & 31 & 33.6705 & -2.67046 \tabularnewline
112 & 32 & 38.163 & -6.16302 \tabularnewline
113 & 32 & 31.4943 & 0.505669 \tabularnewline
114 & 37 & 34.3503 & 2.6497 \tabularnewline
115 & 37 & 34.2211 & 2.77893 \tabularnewline
116 & 33 & 36.3272 & -3.32717 \tabularnewline
117 & 34 & 37.3112 & -3.31124 \tabularnewline
118 & 33 & 34.6847 & -1.68472 \tabularnewline
119 & 38 & 35.5683 & 2.43172 \tabularnewline
120 & 33 & 34.9886 & -1.98856 \tabularnewline
121 & 31 & 31.3521 & -0.352067 \tabularnewline
122 & 38 & 36.6301 & 1.36989 \tabularnewline
123 & 37 & 36.3899 & 0.610112 \tabularnewline
124 & 36 & 33.1309 & 2.86912 \tabularnewline
125 & 31 & 33.8719 & -2.87195 \tabularnewline
126 & 39 & 34.1821 & 4.81791 \tabularnewline
127 & 44 & 36.7899 & 7.21011 \tabularnewline
128 & 33 & 36.0955 & -3.09549 \tabularnewline
129 & 35 & 33.6231 & 1.37691 \tabularnewline
130 & 32 & 34.0046 & -2.00456 \tabularnewline
131 & 28 & 32.4578 & -4.45778 \tabularnewline
132 & 40 & 36.0638 & 3.9362 \tabularnewline
133 & 27 & 32.141 & -5.141 \tabularnewline
134 & 37 & 36.0976 & 0.90238 \tabularnewline
135 & 32 & 32.5252 & -0.525205 \tabularnewline
136 & 28 & 28.3127 & -0.312689 \tabularnewline
137 & 34 & 34.998 & -0.998026 \tabularnewline
138 & 30 & 34.1412 & -4.14124 \tabularnewline
139 & 35 & 34.26 & 0.740034 \tabularnewline
140 & 31 & 34.3033 & -3.30332 \tabularnewline
141 & 32 & 34.4354 & -2.43539 \tabularnewline
142 & 30 & 35.9462 & -5.94623 \tabularnewline
143 & 30 & 35.135 & -5.13497 \tabularnewline
144 & 31 & 29.7728 & 1.22718 \tabularnewline
145 & 40 & 33.2189 & 6.78107 \tabularnewline
146 & 32 & 31.7682 & 0.231779 \tabularnewline
147 & 36 & 34.8216 & 1.17835 \tabularnewline
148 & 32 & 33.2598 & -1.25982 \tabularnewline
149 & 35 & 33.2846 & 1.71538 \tabularnewline
150 & 38 & 36.6384 & 1.36158 \tabularnewline
151 & 42 & 35.3163 & 6.68375 \tabularnewline
152 & 34 & 36.1757 & -2.17574 \tabularnewline
153 & 35 & 36.9368 & -1.93685 \tabularnewline
154 & 38 & 34.6424 & 3.35762 \tabularnewline
155 & 33 & 32.9943 & 0.0057328 \tabularnewline
156 & 36 & 33.0034 & 2.99656 \tabularnewline
157 & 32 & 35.7173 & -3.71729 \tabularnewline
158 & 33 & 36.0591 & -3.05907 \tabularnewline
159 & 34 & 33.9505 & 0.049486 \tabularnewline
160 & 32 & 35.7551 & -3.7551 \tabularnewline
161 & 34 & 35.4297 & -1.4297 \tabularnewline
162 & 27 & 29.9664 & -2.96638 \tabularnewline
163 & 31 & 30.1104 & 0.889615 \tabularnewline
164 & 38 & 33.3668 & 4.63317 \tabularnewline
165 & 34 & 35.6877 & -1.68773 \tabularnewline
166 & 24 & 30.9572 & -6.95722 \tabularnewline
167 & 30 & 33.5116 & -3.51164 \tabularnewline
168 & 26 & 29.312 & -3.31205 \tabularnewline
169 & 34 & 35.2905 & -1.29051 \tabularnewline
170 & 27 & 34.503 & -7.50299 \tabularnewline
171 & 37 & 31.9829 & 5.01706 \tabularnewline
172 & 36 & 35.2388 & 0.761169 \tabularnewline
173 & 41 & 34.0346 & 6.96541 \tabularnewline
174 & 29 & 28.9983 & 0.00165742 \tabularnewline
175 & 36 & 30.8895 & 5.11055 \tabularnewline
176 & 32 & 34.1004 & -2.1004 \tabularnewline
177 & 37 & 33.1847 & 3.81534 \tabularnewline
178 & 30 & 31.4802 & -1.48022 \tabularnewline
179 & 31 & 32.5515 & -1.55151 \tabularnewline
180 & 38 & 34.4898 & 3.51024 \tabularnewline
181 & 36 & 34.4633 & 1.53672 \tabularnewline
182 & 35 & 32.0503 & 2.94973 \tabularnewline
183 & 31 & 35.0836 & -4.08356 \tabularnewline
184 & 38 & 33.0864 & 4.91361 \tabularnewline
185 & 22 & 30.9323 & -8.93226 \tabularnewline
186 & 32 & 34.2515 & -2.2515 \tabularnewline
187 & 36 & 33.7735 & 2.22647 \tabularnewline
188 & 39 & 32.6628 & 6.33722 \tabularnewline
189 & 28 & 30.2791 & -2.27907 \tabularnewline
190 & 32 & 34.2332 & -2.23323 \tabularnewline
191 & 32 & 32.3111 & -0.311127 \tabularnewline
192 & 38 & 36.4041 & 1.59591 \tabularnewline
193 & 32 & 33.3995 & -1.39949 \tabularnewline
194 & 35 & 35.2374 & -0.237402 \tabularnewline
195 & 32 & 32.7648 & -0.76476 \tabularnewline
196 & 37 & 35.5991 & 1.40087 \tabularnewline
197 & 34 & 32.6135 & 1.38653 \tabularnewline
198 & 33 & 35.3409 & -2.34091 \tabularnewline
199 & 33 & 32.7775 & 0.222505 \tabularnewline
200 & 26 & 32.7182 & -6.71822 \tabularnewline
201 & 30 & 32.0876 & -2.08755 \tabularnewline
202 & 24 & 31.7705 & -7.77045 \tabularnewline
203 & 34 & 31.9061 & 2.09389 \tabularnewline
204 & 34 & 32.3835 & 1.61652 \tabularnewline
205 & 33 & 33.9621 & -0.962072 \tabularnewline
206 & 34 & 34.6815 & -0.681483 \tabularnewline
207 & 35 & 35.8711 & -0.871147 \tabularnewline
208 & 35 & 34.1455 & 0.854459 \tabularnewline
209 & 36 & 33.0451 & 2.95494 \tabularnewline
210 & 34 & 33.5684 & 0.431596 \tabularnewline
211 & 34 & 32.7042 & 1.29582 \tabularnewline
212 & 41 & 38.2339 & 2.76615 \tabularnewline
213 & 32 & 36.0988 & -4.09881 \tabularnewline
214 & 30 & 33.3112 & -3.31125 \tabularnewline
215 & 35 & 33.856 & 1.14397 \tabularnewline
216 & 28 & 29.9057 & -1.90568 \tabularnewline
217 & 33 & 34.8175 & -1.81748 \tabularnewline
218 & 39 & 34.1557 & 4.84432 \tabularnewline
219 & 36 & 33.3685 & 2.63152 \tabularnewline
220 & 36 & 36.263 & -0.262986 \tabularnewline
221 & 35 & 33.1103 & 1.88965 \tabularnewline
222 & 38 & 33.8324 & 4.16764 \tabularnewline
223 & 33 & 32.6541 & 0.345894 \tabularnewline
224 & 31 & 32.8925 & -1.89252 \tabularnewline
225 & 34 & 31.9892 & 2.01077 \tabularnewline
226 & 32 & 34.2337 & -2.23372 \tabularnewline
227 & 31 & 32.6416 & -1.64162 \tabularnewline
228 & 33 & 33.0853 & -0.0853386 \tabularnewline
229 & 34 & 32.6301 & 1.36988 \tabularnewline
230 & 34 & 33.9526 & 0.0474285 \tabularnewline
231 & 34 & 32.1207 & 1.87927 \tabularnewline
232 & 33 & 35.092 & -2.092 \tabularnewline
233 & 32 & 34.1579 & -2.15793 \tabularnewline
234 & 41 & 33.5486 & 7.45138 \tabularnewline
235 & 34 & 32.937 & 1.06305 \tabularnewline
236 & 36 & 32.0142 & 3.98583 \tabularnewline
237 & 37 & 31.4655 & 5.53454 \tabularnewline
238 & 36 & 30.325 & 5.67503 \tabularnewline
239 & 29 & 32.4487 & -3.44868 \tabularnewline
240 & 37 & 31.7542 & 5.24581 \tabularnewline
241 & 27 & 33.0888 & -6.08877 \tabularnewline
242 & 35 & 33.3611 & 1.63892 \tabularnewline
243 & 28 & 30.6489 & -2.64894 \tabularnewline
244 & 35 & 33.1108 & 1.8892 \tabularnewline
245 & 37 & 33.0477 & 3.95225 \tabularnewline
246 & 29 & 33.6323 & -4.6323 \tabularnewline
247 & 32 & 34.1964 & -2.19641 \tabularnewline
248 & 36 & 31.7382 & 4.26175 \tabularnewline
249 & 19 & 27.5916 & -8.59157 \tabularnewline
250 & 21 & 26.7203 & -5.72027 \tabularnewline
251 & 31 & 33.3856 & -2.38557 \tabularnewline
252 & 33 & 32.4434 & 0.556595 \tabularnewline
253 & 36 & 33.8534 & 2.14662 \tabularnewline
254 & 33 & 33.2332 & -0.233197 \tabularnewline
255 & 37 & 33.0726 & 3.92743 \tabularnewline
256 & 34 & 33.2479 & 0.752074 \tabularnewline
257 & 35 & 34.405 & 0.594963 \tabularnewline
258 & 31 & 32.7558 & -1.75581 \tabularnewline
259 & 37 & 33.3472 & 3.65284 \tabularnewline
260 & 35 & 31.8493 & 3.15074 \tabularnewline
261 & 27 & 31.7665 & -4.76649 \tabularnewline
262 & 34 & 34.8476 & -0.847618 \tabularnewline
263 & 40 & 33.8859 & 6.11415 \tabularnewline
264 & 29 & 32.8078 & -3.80781 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221870&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]41[/C][C]36.058[/C][C]4.94195[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]34.6378[/C][C]4.36218[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]35.6436[/C][C]-5.6436[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]34.8206[/C][C]-3.82063[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]35.7632[/C][C]-1.76324[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]32.8192[/C][C]2.18079[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]33.8986[/C][C]5.10141[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]35.9307[/C][C]-1.93069[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]35.4058[/C][C]0.594182[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]36.997[/C][C]0.00304733[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]34.2675[/C][C]3.73249[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]34.9446[/C][C]1.05538[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]35.3802[/C][C]2.61985[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]36.4385[/C][C]2.56151[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]36.696[/C][C]-3.69597[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]34.247[/C][C]-2.24705[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]34.1121[/C][C]1.88786[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]37.6565[/C][C]0.34353[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]37.2338[/C][C]1.76615[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]34.0394[/C][C]-2.03943[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.815[/C][C]-2.81502[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]33.8941[/C][C]-2.89409[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]36.7012[/C][C]2.29885[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]37.1956[/C][C]-0.195631[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]34.6075[/C][C]4.39245[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]34.2719[/C][C]6.72813[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]35.3455[/C][C]0.654512[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]36.1561[/C][C]-3.15605[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]34.3588[/C][C]-1.35881[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]34.7419[/C][C]-0.741945[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]33.9862[/C][C]-2.98624[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]33.5167[/C][C]-6.51673[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]33.7243[/C][C]3.27566[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]36.9636[/C][C]-2.9636[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]32.7287[/C][C]1.27131[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]34.5192[/C][C]-2.5192[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]32.5462[/C][C]-3.5462[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]34.3481[/C][C]1.65192[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]34.0318[/C][C]-5.03175[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]34.745[/C][C]0.254962[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]34.4689[/C][C]2.53107[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]34.1722[/C][C]-0.172184[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]34.2773[/C][C]3.7227[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]33.9264[/C][C]1.07361[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]32.3492[/C][C]5.65082[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]34.5823[/C][C]2.4177[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]37.3012[/C][C]0.698794[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]35.1277[/C][C]-2.12774[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]36.3704[/C][C]-0.370436[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]33.954[/C][C]4.046[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]36.7349[/C][C]-4.73488[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.9278[/C][C]-0.927802[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]33.5223[/C][C]-1.52234[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]37.3739[/C][C]-3.37392[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]33.3789[/C][C]-1.3789[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]35.6673[/C][C]1.33272[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]35.0228[/C][C]3.97722[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]35.197[/C][C]-6.19701[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]35.7303[/C][C]1.26966[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]34.9962[/C][C]0.00382939[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]31.5029[/C][C]-1.50291[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]34.8679[/C][C]3.1321[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]35.3539[/C][C]-1.35392[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]34.7162[/C][C]-3.71623[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]33.3448[/C][C]0.655216[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]36.0556[/C][C]-1.05563[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]34.9104[/C][C]1.08961[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]31.3837[/C][C]-1.3837[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]36.3954[/C][C]2.60456[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]35.6688[/C][C]-0.668818[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]35.2082[/C][C]2.79184[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]35.6239[/C][C]-4.62393[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]36.7396[/C][C]-2.73956[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]37.4024[/C][C]0.597619[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]31.6394[/C][C]2.36061[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.9711[/C][C]6.02892[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.7262[/C][C]1.27384[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]33.2457[/C][C]0.75426[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]32.9675[/C][C]-4.96747[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]31.2812[/C][C]5.71883[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]35.2963[/C][C]-2.29629[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]36.1218[/C][C]-1.12179[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]33.8247[/C][C]3.17532[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.4814[/C][C]-2.48138[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]33.4081[/C][C]-0.408076[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]36.5537[/C][C]1.44632[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]34.4367[/C][C]-1.43668[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]33.1623[/C][C]-4.1623[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.4736[/C][C]-0.473575[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]35.2895[/C][C]-4.28947[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]33.0823[/C][C]2.91766[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]37.4516[/C][C]-2.45162[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.6413[/C][C]0.358675[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]32.3597[/C][C]-3.35975[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]35.4806[/C][C]3.51935[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.7261[/C][C]2.27391[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]33.3645[/C][C]1.63552[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]34.571[/C][C]2.42897[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]35.3829[/C][C]-3.3829[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]35.2509[/C][C]2.74912[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]34.8706[/C][C]2.12942[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]36.3264[/C][C]-0.32645[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]31.9727[/C][C]0.0272964[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]36.5277[/C][C]-3.52767[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]32.8146[/C][C]7.18539[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]35.2419[/C][C]2.75812[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]36.4101[/C][C]4.58995[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]34.4591[/C][C]1.5409[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]36.9559[/C][C]6.04406[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]34.68[/C][C]-4.67996[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]33.6705[/C][C]-2.67046[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]38.163[/C][C]-6.16302[/C][/ROW]
[ROW][C]113[/C][C]32[/C][C]31.4943[/C][C]0.505669[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.3503[/C][C]2.6497[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]34.2211[/C][C]2.77893[/C][/ROW]
[ROW][C]116[/C][C]33[/C][C]36.3272[/C][C]-3.32717[/C][/ROW]
[ROW][C]117[/C][C]34[/C][C]37.3112[/C][C]-3.31124[/C][/ROW]
[ROW][C]118[/C][C]33[/C][C]34.6847[/C][C]-1.68472[/C][/ROW]
[ROW][C]119[/C][C]38[/C][C]35.5683[/C][C]2.43172[/C][/ROW]
[ROW][C]120[/C][C]33[/C][C]34.9886[/C][C]-1.98856[/C][/ROW]
[ROW][C]121[/C][C]31[/C][C]31.3521[/C][C]-0.352067[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]36.6301[/C][C]1.36989[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]36.3899[/C][C]0.610112[/C][/ROW]
[ROW][C]124[/C][C]36[/C][C]33.1309[/C][C]2.86912[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]33.8719[/C][C]-2.87195[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]34.1821[/C][C]4.81791[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]36.7899[/C][C]7.21011[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]36.0955[/C][C]-3.09549[/C][/ROW]
[ROW][C]129[/C][C]35[/C][C]33.6231[/C][C]1.37691[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]34.0046[/C][C]-2.00456[/C][/ROW]
[ROW][C]131[/C][C]28[/C][C]32.4578[/C][C]-4.45778[/C][/ROW]
[ROW][C]132[/C][C]40[/C][C]36.0638[/C][C]3.9362[/C][/ROW]
[ROW][C]133[/C][C]27[/C][C]32.141[/C][C]-5.141[/C][/ROW]
[ROW][C]134[/C][C]37[/C][C]36.0976[/C][C]0.90238[/C][/ROW]
[ROW][C]135[/C][C]32[/C][C]32.5252[/C][C]-0.525205[/C][/ROW]
[ROW][C]136[/C][C]28[/C][C]28.3127[/C][C]-0.312689[/C][/ROW]
[ROW][C]137[/C][C]34[/C][C]34.998[/C][C]-0.998026[/C][/ROW]
[ROW][C]138[/C][C]30[/C][C]34.1412[/C][C]-4.14124[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]34.26[/C][C]0.740034[/C][/ROW]
[ROW][C]140[/C][C]31[/C][C]34.3033[/C][C]-3.30332[/C][/ROW]
[ROW][C]141[/C][C]32[/C][C]34.4354[/C][C]-2.43539[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]35.9462[/C][C]-5.94623[/C][/ROW]
[ROW][C]143[/C][C]30[/C][C]35.135[/C][C]-5.13497[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]29.7728[/C][C]1.22718[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]33.2189[/C][C]6.78107[/C][/ROW]
[ROW][C]146[/C][C]32[/C][C]31.7682[/C][C]0.231779[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.8216[/C][C]1.17835[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]33.2598[/C][C]-1.25982[/C][/ROW]
[ROW][C]149[/C][C]35[/C][C]33.2846[/C][C]1.71538[/C][/ROW]
[ROW][C]150[/C][C]38[/C][C]36.6384[/C][C]1.36158[/C][/ROW]
[ROW][C]151[/C][C]42[/C][C]35.3163[/C][C]6.68375[/C][/ROW]
[ROW][C]152[/C][C]34[/C][C]36.1757[/C][C]-2.17574[/C][/ROW]
[ROW][C]153[/C][C]35[/C][C]36.9368[/C][C]-1.93685[/C][/ROW]
[ROW][C]154[/C][C]38[/C][C]34.6424[/C][C]3.35762[/C][/ROW]
[ROW][C]155[/C][C]33[/C][C]32.9943[/C][C]0.0057328[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]33.0034[/C][C]2.99656[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]35.7173[/C][C]-3.71729[/C][/ROW]
[ROW][C]158[/C][C]33[/C][C]36.0591[/C][C]-3.05907[/C][/ROW]
[ROW][C]159[/C][C]34[/C][C]33.9505[/C][C]0.049486[/C][/ROW]
[ROW][C]160[/C][C]32[/C][C]35.7551[/C][C]-3.7551[/C][/ROW]
[ROW][C]161[/C][C]34[/C][C]35.4297[/C][C]-1.4297[/C][/ROW]
[ROW][C]162[/C][C]27[/C][C]29.9664[/C][C]-2.96638[/C][/ROW]
[ROW][C]163[/C][C]31[/C][C]30.1104[/C][C]0.889615[/C][/ROW]
[ROW][C]164[/C][C]38[/C][C]33.3668[/C][C]4.63317[/C][/ROW]
[ROW][C]165[/C][C]34[/C][C]35.6877[/C][C]-1.68773[/C][/ROW]
[ROW][C]166[/C][C]24[/C][C]30.9572[/C][C]-6.95722[/C][/ROW]
[ROW][C]167[/C][C]30[/C][C]33.5116[/C][C]-3.51164[/C][/ROW]
[ROW][C]168[/C][C]26[/C][C]29.312[/C][C]-3.31205[/C][/ROW]
[ROW][C]169[/C][C]34[/C][C]35.2905[/C][C]-1.29051[/C][/ROW]
[ROW][C]170[/C][C]27[/C][C]34.503[/C][C]-7.50299[/C][/ROW]
[ROW][C]171[/C][C]37[/C][C]31.9829[/C][C]5.01706[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]35.2388[/C][C]0.761169[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]34.0346[/C][C]6.96541[/C][/ROW]
[ROW][C]174[/C][C]29[/C][C]28.9983[/C][C]0.00165742[/C][/ROW]
[ROW][C]175[/C][C]36[/C][C]30.8895[/C][C]5.11055[/C][/ROW]
[ROW][C]176[/C][C]32[/C][C]34.1004[/C][C]-2.1004[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]33.1847[/C][C]3.81534[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.4802[/C][C]-1.48022[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]32.5515[/C][C]-1.55151[/C][/ROW]
[ROW][C]180[/C][C]38[/C][C]34.4898[/C][C]3.51024[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.4633[/C][C]1.53672[/C][/ROW]
[ROW][C]182[/C][C]35[/C][C]32.0503[/C][C]2.94973[/C][/ROW]
[ROW][C]183[/C][C]31[/C][C]35.0836[/C][C]-4.08356[/C][/ROW]
[ROW][C]184[/C][C]38[/C][C]33.0864[/C][C]4.91361[/C][/ROW]
[ROW][C]185[/C][C]22[/C][C]30.9323[/C][C]-8.93226[/C][/ROW]
[ROW][C]186[/C][C]32[/C][C]34.2515[/C][C]-2.2515[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]33.7735[/C][C]2.22647[/C][/ROW]
[ROW][C]188[/C][C]39[/C][C]32.6628[/C][C]6.33722[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.2791[/C][C]-2.27907[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]34.2332[/C][C]-2.23323[/C][/ROW]
[ROW][C]191[/C][C]32[/C][C]32.3111[/C][C]-0.311127[/C][/ROW]
[ROW][C]192[/C][C]38[/C][C]36.4041[/C][C]1.59591[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]33.3995[/C][C]-1.39949[/C][/ROW]
[ROW][C]194[/C][C]35[/C][C]35.2374[/C][C]-0.237402[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]32.7648[/C][C]-0.76476[/C][/ROW]
[ROW][C]196[/C][C]37[/C][C]35.5991[/C][C]1.40087[/C][/ROW]
[ROW][C]197[/C][C]34[/C][C]32.6135[/C][C]1.38653[/C][/ROW]
[ROW][C]198[/C][C]33[/C][C]35.3409[/C][C]-2.34091[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]32.7775[/C][C]0.222505[/C][/ROW]
[ROW][C]200[/C][C]26[/C][C]32.7182[/C][C]-6.71822[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]32.0876[/C][C]-2.08755[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]31.7705[/C][C]-7.77045[/C][/ROW]
[ROW][C]203[/C][C]34[/C][C]31.9061[/C][C]2.09389[/C][/ROW]
[ROW][C]204[/C][C]34[/C][C]32.3835[/C][C]1.61652[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]33.9621[/C][C]-0.962072[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]34.6815[/C][C]-0.681483[/C][/ROW]
[ROW][C]207[/C][C]35[/C][C]35.8711[/C][C]-0.871147[/C][/ROW]
[ROW][C]208[/C][C]35[/C][C]34.1455[/C][C]0.854459[/C][/ROW]
[ROW][C]209[/C][C]36[/C][C]33.0451[/C][C]2.95494[/C][/ROW]
[ROW][C]210[/C][C]34[/C][C]33.5684[/C][C]0.431596[/C][/ROW]
[ROW][C]211[/C][C]34[/C][C]32.7042[/C][C]1.29582[/C][/ROW]
[ROW][C]212[/C][C]41[/C][C]38.2339[/C][C]2.76615[/C][/ROW]
[ROW][C]213[/C][C]32[/C][C]36.0988[/C][C]-4.09881[/C][/ROW]
[ROW][C]214[/C][C]30[/C][C]33.3112[/C][C]-3.31125[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]33.856[/C][C]1.14397[/C][/ROW]
[ROW][C]216[/C][C]28[/C][C]29.9057[/C][C]-1.90568[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]34.8175[/C][C]-1.81748[/C][/ROW]
[ROW][C]218[/C][C]39[/C][C]34.1557[/C][C]4.84432[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]33.3685[/C][C]2.63152[/C][/ROW]
[ROW][C]220[/C][C]36[/C][C]36.263[/C][C]-0.262986[/C][/ROW]
[ROW][C]221[/C][C]35[/C][C]33.1103[/C][C]1.88965[/C][/ROW]
[ROW][C]222[/C][C]38[/C][C]33.8324[/C][C]4.16764[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]32.6541[/C][C]0.345894[/C][/ROW]
[ROW][C]224[/C][C]31[/C][C]32.8925[/C][C]-1.89252[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]31.9892[/C][C]2.01077[/C][/ROW]
[ROW][C]226[/C][C]32[/C][C]34.2337[/C][C]-2.23372[/C][/ROW]
[ROW][C]227[/C][C]31[/C][C]32.6416[/C][C]-1.64162[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]33.0853[/C][C]-0.0853386[/C][/ROW]
[ROW][C]229[/C][C]34[/C][C]32.6301[/C][C]1.36988[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]33.9526[/C][C]0.0474285[/C][/ROW]
[ROW][C]231[/C][C]34[/C][C]32.1207[/C][C]1.87927[/C][/ROW]
[ROW][C]232[/C][C]33[/C][C]35.092[/C][C]-2.092[/C][/ROW]
[ROW][C]233[/C][C]32[/C][C]34.1579[/C][C]-2.15793[/C][/ROW]
[ROW][C]234[/C][C]41[/C][C]33.5486[/C][C]7.45138[/C][/ROW]
[ROW][C]235[/C][C]34[/C][C]32.937[/C][C]1.06305[/C][/ROW]
[ROW][C]236[/C][C]36[/C][C]32.0142[/C][C]3.98583[/C][/ROW]
[ROW][C]237[/C][C]37[/C][C]31.4655[/C][C]5.53454[/C][/ROW]
[ROW][C]238[/C][C]36[/C][C]30.325[/C][C]5.67503[/C][/ROW]
[ROW][C]239[/C][C]29[/C][C]32.4487[/C][C]-3.44868[/C][/ROW]
[ROW][C]240[/C][C]37[/C][C]31.7542[/C][C]5.24581[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]33.0888[/C][C]-6.08877[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.3611[/C][C]1.63892[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]30.6489[/C][C]-2.64894[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]33.1108[/C][C]1.8892[/C][/ROW]
[ROW][C]245[/C][C]37[/C][C]33.0477[/C][C]3.95225[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]33.6323[/C][C]-4.6323[/C][/ROW]
[ROW][C]247[/C][C]32[/C][C]34.1964[/C][C]-2.19641[/C][/ROW]
[ROW][C]248[/C][C]36[/C][C]31.7382[/C][C]4.26175[/C][/ROW]
[ROW][C]249[/C][C]19[/C][C]27.5916[/C][C]-8.59157[/C][/ROW]
[ROW][C]250[/C][C]21[/C][C]26.7203[/C][C]-5.72027[/C][/ROW]
[ROW][C]251[/C][C]31[/C][C]33.3856[/C][C]-2.38557[/C][/ROW]
[ROW][C]252[/C][C]33[/C][C]32.4434[/C][C]0.556595[/C][/ROW]
[ROW][C]253[/C][C]36[/C][C]33.8534[/C][C]2.14662[/C][/ROW]
[ROW][C]254[/C][C]33[/C][C]33.2332[/C][C]-0.233197[/C][/ROW]
[ROW][C]255[/C][C]37[/C][C]33.0726[/C][C]3.92743[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]33.2479[/C][C]0.752074[/C][/ROW]
[ROW][C]257[/C][C]35[/C][C]34.405[/C][C]0.594963[/C][/ROW]
[ROW][C]258[/C][C]31[/C][C]32.7558[/C][C]-1.75581[/C][/ROW]
[ROW][C]259[/C][C]37[/C][C]33.3472[/C][C]3.65284[/C][/ROW]
[ROW][C]260[/C][C]35[/C][C]31.8493[/C][C]3.15074[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]31.7665[/C][C]-4.76649[/C][/ROW]
[ROW][C]262[/C][C]34[/C][C]34.8476[/C][C]-0.847618[/C][/ROW]
[ROW][C]263[/C][C]40[/C][C]33.8859[/C][C]6.11415[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]32.8078[/C][C]-3.80781[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221870&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221870&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
14136.0584.94195
23934.63784.36218
33035.6436-5.6436
43134.8206-3.82063
53435.7632-1.76324
63532.81922.18079
73933.89865.10141
83435.9307-1.93069
93635.40580.594182
103736.9970.00304733
113834.26753.73249
123634.94461.05538
133835.38022.61985
143936.43852.56151
153336.696-3.69597
163234.247-2.24705
173634.11211.88786
183837.65650.34353
193937.23381.76615
203234.0394-2.03943
213234.815-2.81502
223133.8941-2.89409
233936.70122.29885
243737.1956-0.195631
253934.60754.39245
264134.27196.72813
273635.34550.654512
283336.1561-3.15605
293334.3588-1.35881
303434.7419-0.741945
313133.9862-2.98624
322733.5167-6.51673
333733.72433.27566
343436.9636-2.9636
353432.72871.27131
363234.5192-2.5192
372932.5462-3.5462
383634.34811.65192
392934.0318-5.03175
403534.7450.254962
413734.46892.53107
423434.1722-0.172184
433834.27733.7227
443533.92641.07361
453832.34925.65082
463734.58232.4177
473837.30120.698794
483335.1277-2.12774
493636.3704-0.370436
503833.9544.046
513236.7349-4.73488
523232.9278-0.927802
533233.5223-1.52234
543437.3739-3.37392
553233.3789-1.3789
563735.66731.33272
573935.02283.97722
582935.197-6.19701
593735.73031.26966
603534.99620.00382939
613031.5029-1.50291
623834.86793.1321
633435.3539-1.35392
643134.7162-3.71623
653433.34480.655216
663536.0556-1.05563
673634.91041.08961
683031.3837-1.3837
693936.39542.60456
703535.6688-0.668818
713835.20822.79184
723135.6239-4.62393
733436.7396-2.73956
743837.40240.597619
753431.63942.36061
763932.97116.02892
773735.72621.27384
783433.24570.75426
792832.9675-4.96747
803731.28125.71883
813335.2963-2.29629
823536.1218-1.12179
833733.82473.17532
843234.4814-2.48138
853333.4081-0.408076
863836.55371.44632
873334.4367-1.43668
882933.1623-4.1623
893333.4736-0.473575
903135.2895-4.28947
913633.08232.91766
923537.4516-2.45162
933231.64130.358675
942932.3597-3.35975
953935.48063.51935
963734.72612.27391
973533.36451.63552
983734.5712.42897
993235.3829-3.3829
1003835.25092.74912
1013734.87062.12942
1023636.3264-0.32645
1033231.97270.0272964
1043336.5277-3.52767
1054032.81467.18539
1063835.24192.75812
1074136.41014.58995
1083634.45911.5409
1094336.95596.04406
1103034.68-4.67996
1113133.6705-2.67046
1123238.163-6.16302
1133231.49430.505669
1143734.35032.6497
1153734.22112.77893
1163336.3272-3.32717
1173437.3112-3.31124
1183334.6847-1.68472
1193835.56832.43172
1203334.9886-1.98856
1213131.3521-0.352067
1223836.63011.36989
1233736.38990.610112
1243633.13092.86912
1253133.8719-2.87195
1263934.18214.81791
1274436.78997.21011
1283336.0955-3.09549
1293533.62311.37691
1303234.0046-2.00456
1312832.4578-4.45778
1324036.06383.9362
1332732.141-5.141
1343736.09760.90238
1353232.5252-0.525205
1362828.3127-0.312689
1373434.998-0.998026
1383034.1412-4.14124
1393534.260.740034
1403134.3033-3.30332
1413234.4354-2.43539
1423035.9462-5.94623
1433035.135-5.13497
1443129.77281.22718
1454033.21896.78107
1463231.76820.231779
1473634.82161.17835
1483233.2598-1.25982
1493533.28461.71538
1503836.63841.36158
1514235.31636.68375
1523436.1757-2.17574
1533536.9368-1.93685
1543834.64243.35762
1553332.99430.0057328
1563633.00342.99656
1573235.7173-3.71729
1583336.0591-3.05907
1593433.95050.049486
1603235.7551-3.7551
1613435.4297-1.4297
1622729.9664-2.96638
1633130.11040.889615
1643833.36684.63317
1653435.6877-1.68773
1662430.9572-6.95722
1673033.5116-3.51164
1682629.312-3.31205
1693435.2905-1.29051
1702734.503-7.50299
1713731.98295.01706
1723635.23880.761169
1734134.03466.96541
1742928.99830.00165742
1753630.88955.11055
1763234.1004-2.1004
1773733.18473.81534
1783031.4802-1.48022
1793132.5515-1.55151
1803834.48983.51024
1813634.46331.53672
1823532.05032.94973
1833135.0836-4.08356
1843833.08644.91361
1852230.9323-8.93226
1863234.2515-2.2515
1873633.77352.22647
1883932.66286.33722
1892830.2791-2.27907
1903234.2332-2.23323
1913232.3111-0.311127
1923836.40411.59591
1933233.3995-1.39949
1943535.2374-0.237402
1953232.7648-0.76476
1963735.59911.40087
1973432.61351.38653
1983335.3409-2.34091
1993332.77750.222505
2002632.7182-6.71822
2013032.0876-2.08755
2022431.7705-7.77045
2033431.90612.09389
2043432.38351.61652
2053333.9621-0.962072
2063434.6815-0.681483
2073535.8711-0.871147
2083534.14550.854459
2093633.04512.95494
2103433.56840.431596
2113432.70421.29582
2124138.23392.76615
2133236.0988-4.09881
2143033.3112-3.31125
2153533.8561.14397
2162829.9057-1.90568
2173334.8175-1.81748
2183934.15574.84432
2193633.36852.63152
2203636.263-0.262986
2213533.11031.88965
2223833.83244.16764
2233332.65410.345894
2243132.8925-1.89252
2253431.98922.01077
2263234.2337-2.23372
2273132.6416-1.64162
2283333.0853-0.0853386
2293432.63011.36988
2303433.95260.0474285
2313432.12071.87927
2323335.092-2.092
2333234.1579-2.15793
2344133.54867.45138
2353432.9371.06305
2363632.01423.98583
2373731.46555.53454
2383630.3255.67503
2392932.4487-3.44868
2403731.75425.24581
2412733.0888-6.08877
2423533.36111.63892
2432830.6489-2.64894
2443533.11081.8892
2453733.04773.95225
2462933.6323-4.6323
2473234.1964-2.19641
2483631.73824.26175
2491927.5916-8.59157
2502126.7203-5.72027
2513133.3856-2.38557
2523332.44340.556595
2533633.85342.14662
2543333.2332-0.233197
2553733.07263.92743
2563433.24790.752074
2573534.4050.594963
2583132.7558-1.75581
2593733.34723.65284
2603531.84933.15074
2612731.7665-4.76649
2623434.8476-0.847618
2634033.88596.11415
2642932.8078-3.80781






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.8140060.3719880.185994
140.7717080.4565840.228292
150.6808030.6383940.319197
160.6932840.6134330.306716
170.7421310.5157390.257869
180.7290740.5418530.270926
190.6422170.7155670.357783
200.6694890.6610230.330511
210.6943470.6113070.305653
220.6307880.7384240.369212
230.6394880.7210250.360512
240.5627660.8744690.437234
250.6471870.7056270.352813
260.7909170.4181650.209083
270.7667350.4665290.233265
280.7228440.5543120.277156
290.7025330.5949350.297467
300.6437080.7125850.356292
310.6159690.7680620.384031
320.6951980.6096040.304802
330.715830.5683410.28417
340.6666590.6666820.333341
350.6165990.7668010.383401
360.5626550.874690.437345
370.5143130.9713740.485687
380.4997260.9994520.500274
390.5644430.8711150.435557
400.5125270.9749460.487473
410.4966240.9932490.503376
420.4474010.8948020.552599
430.413530.8270590.58647
440.3737290.7474590.626271
450.4642830.9285660.535717
460.4847590.9695180.515241
470.4633750.9267510.536625
480.4262050.852410.573795
490.3774570.7549140.622543
500.3936250.7872510.606375
510.4258050.851610.574195
520.382870.765740.61713
530.3396830.6793670.660317
540.3050010.6100020.694999
550.2657260.5314520.734274
560.2630670.5261350.736933
570.2843510.5687030.715649
580.3866650.773330.613335
590.3509320.7018640.649068
600.3097760.6195520.690224
610.2764570.5529150.723543
620.2644540.5289080.735546
630.2343330.4686650.765667
640.2322270.4644540.767773
650.2002690.4005390.799731
660.1713010.3426020.828699
670.1506450.301290.849355
680.1528950.305790.847105
690.1693440.3386880.830656
700.1441980.2883960.855802
710.1541840.3083690.845816
720.177250.35450.82275
730.1665940.3331890.833406
740.1425820.2851650.857418
750.1259840.2519680.874016
760.1726520.3453030.827348
770.1508890.3017780.849111
780.128570.2571410.87143
790.1604920.3209840.839508
800.1862760.3725520.813724
810.1752910.3505820.824709
820.1521430.3042860.847857
830.146970.2939390.85303
840.1375760.2751530.862424
850.1186480.2372970.881352
860.1076210.2152420.892379
870.09396770.1879350.906032
880.1062130.2124260.893787
890.08937320.1787460.910627
900.0901750.180350.909825
910.0863640.1727280.913636
920.07583140.1516630.924169
930.06317640.1263530.936824
940.06240730.1248150.937593
950.0657410.1314820.934259
960.06287940.1257590.937121
970.05392540.1078510.946075
980.04957430.09914850.950426
990.04746710.09493420.952533
1000.04573380.09146770.954266
1010.04200890.08401780.957991
1020.03439830.06879660.965602
1030.02792640.05585270.972074
1040.0268510.0537020.973149
1050.06560450.1312090.934395
1060.06322350.1264470.936776
1070.07962470.1592490.920375
1080.06951650.1390330.930484
1090.1129560.2259110.887044
1100.1284240.2568490.871576
1110.1218040.2436080.878196
1120.1540540.3081090.845946
1130.1420280.2840560.857972
1140.1409380.2818760.859062
1150.136370.272740.86363
1160.1316430.2632860.868357
1170.1256980.2513960.874302
1180.1100520.2201040.889948
1190.1055060.2110120.894494
1200.09379320.1875860.906207
1210.08104770.1620950.918952
1220.0750290.1500580.924971
1230.06465360.1293070.935346
1240.06252820.1250560.937472
1250.05840020.11680.9416
1260.0732870.1465740.926713
1270.1322220.2644450.867778
1280.128740.2574810.87126
1290.1149360.2298730.885064
1300.1055680.2111360.894432
1310.1131910.2263810.886809
1320.1222790.2445570.877721
1330.1447860.2895710.855214
1340.1284220.2568430.871578
1350.1108130.2216260.889187
1360.09617160.1923430.903828
1370.08226290.1645260.917737
1380.08899220.1779840.911008
1390.07632150.1526430.923678
1400.07526850.1505370.924731
1410.07132450.1426490.928675
1420.09790170.1958030.902098
1430.1170050.234010.882995
1440.1058090.2116180.894191
1450.1821270.3642550.817873
1460.1629650.3259310.837035
1470.1487750.297550.851225
1480.1299490.2598970.870051
1490.1188990.2377990.881101
1500.1064420.2128850.893558
1510.1743730.3487460.825627
1520.1598650.319730.840135
1530.1441860.2883710.855814
1540.1612190.3224390.838781
1550.1415320.2830640.858468
1560.1558940.3117890.844106
1570.1492270.2984550.850773
1580.1365270.2730540.863473
1590.1314060.2628110.868594
1600.1211020.2422040.878898
1610.1035210.2070420.896479
1620.09667420.1933480.903326
1630.08824210.1764840.911758
1640.1165870.2331740.883413
1650.1042680.2085370.895732
1660.1776860.3553720.822314
1670.1755430.3510860.824457
1680.1633220.3266430.836678
1690.1488040.2976070.851196
1700.2518990.5037980.748101
1710.2819830.5639660.718017
1720.2523140.5046280.747686
1730.3541220.7082430.645878
1740.319130.6382610.68087
1750.385660.7713210.61434
1760.3584690.7169380.641531
1770.3630480.7260970.636952
1780.3305860.6611710.669414
1790.3005730.6011470.699427
1800.2992530.5985060.700747
1810.2697840.5395680.730216
1820.2692570.5385130.730743
1830.2803530.5607070.719647
1840.3557510.7115010.644249
1850.5819690.8360620.418031
1860.5613260.8773480.438674
1870.5575940.8848130.442406
1880.7179290.5641420.282071
1890.6912120.6175770.308788
1900.6898230.6203530.310177
1910.6529850.694030.347015
1920.6237840.7524330.376216
1930.5877730.8244530.412227
1940.5522860.8954270.447714
1950.5117430.9765150.488257
1960.4735960.9471920.526404
1970.468110.936220.53189
1980.4377250.875450.562275
1990.3971690.7943380.602831
2000.4638060.9276110.536194
2010.4287770.8575530.571223
2020.5827220.8345550.417278
2030.5591330.8817350.440867
2040.5248590.9502810.475141
2050.4808260.9616520.519174
2060.44080.88160.5592
2070.4027420.8054830.597258
2080.3632920.7265840.636708
2090.3356640.6713280.664336
2100.3016140.6032280.698386
2110.2682270.5364550.731773
2120.2454450.490890.754555
2130.3043050.608610.695695
2140.2919090.5838180.708091
2150.2534040.5068080.746596
2160.2215250.443050.778475
2170.1982970.3965930.801703
2180.2117160.4234330.788284
2190.1838390.3676790.816161
2200.1741220.3482440.825878
2210.1459480.2918970.854052
2220.1519160.3038310.848084
2230.1236990.2473980.876301
2240.1072070.2144140.892793
2250.1517540.3035080.848246
2260.1441240.2882490.855876
2270.1313010.2626030.868699
2280.1246280.2492560.875372
2290.1008090.2016190.899191
2300.07917340.1583470.920827
2310.07311760.1462350.926882
2320.219270.438540.78073
2330.1880720.3761430.811928
2340.2625820.5251640.737418
2350.2131330.4262670.786867
2360.2038240.4076490.796176
2370.1724970.3449950.827503
2380.2388910.4777820.761109
2390.1925370.3850740.807463
2400.4025920.8051840.597408
2410.4044220.8088440.595578
2420.3384750.6769490.661525
2430.2673270.5346530.732673
2440.296050.59210.70395
2450.3370180.6740360.662982
2460.4513580.9027170.548642
2470.4293310.8586610.570669
2480.3526590.7053170.647341
2490.550010.899980.44999
2500.4728790.9457590.527121
2510.3987240.7974470.601276

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.814006 & 0.371988 & 0.185994 \tabularnewline
14 & 0.771708 & 0.456584 & 0.228292 \tabularnewline
15 & 0.680803 & 0.638394 & 0.319197 \tabularnewline
16 & 0.693284 & 0.613433 & 0.306716 \tabularnewline
17 & 0.742131 & 0.515739 & 0.257869 \tabularnewline
18 & 0.729074 & 0.541853 & 0.270926 \tabularnewline
19 & 0.642217 & 0.715567 & 0.357783 \tabularnewline
20 & 0.669489 & 0.661023 & 0.330511 \tabularnewline
21 & 0.694347 & 0.611307 & 0.305653 \tabularnewline
22 & 0.630788 & 0.738424 & 0.369212 \tabularnewline
23 & 0.639488 & 0.721025 & 0.360512 \tabularnewline
24 & 0.562766 & 0.874469 & 0.437234 \tabularnewline
25 & 0.647187 & 0.705627 & 0.352813 \tabularnewline
26 & 0.790917 & 0.418165 & 0.209083 \tabularnewline
27 & 0.766735 & 0.466529 & 0.233265 \tabularnewline
28 & 0.722844 & 0.554312 & 0.277156 \tabularnewline
29 & 0.702533 & 0.594935 & 0.297467 \tabularnewline
30 & 0.643708 & 0.712585 & 0.356292 \tabularnewline
31 & 0.615969 & 0.768062 & 0.384031 \tabularnewline
32 & 0.695198 & 0.609604 & 0.304802 \tabularnewline
33 & 0.71583 & 0.568341 & 0.28417 \tabularnewline
34 & 0.666659 & 0.666682 & 0.333341 \tabularnewline
35 & 0.616599 & 0.766801 & 0.383401 \tabularnewline
36 & 0.562655 & 0.87469 & 0.437345 \tabularnewline
37 & 0.514313 & 0.971374 & 0.485687 \tabularnewline
38 & 0.499726 & 0.999452 & 0.500274 \tabularnewline
39 & 0.564443 & 0.871115 & 0.435557 \tabularnewline
40 & 0.512527 & 0.974946 & 0.487473 \tabularnewline
41 & 0.496624 & 0.993249 & 0.503376 \tabularnewline
42 & 0.447401 & 0.894802 & 0.552599 \tabularnewline
43 & 0.41353 & 0.827059 & 0.58647 \tabularnewline
44 & 0.373729 & 0.747459 & 0.626271 \tabularnewline
45 & 0.464283 & 0.928566 & 0.535717 \tabularnewline
46 & 0.484759 & 0.969518 & 0.515241 \tabularnewline
47 & 0.463375 & 0.926751 & 0.536625 \tabularnewline
48 & 0.426205 & 0.85241 & 0.573795 \tabularnewline
49 & 0.377457 & 0.754914 & 0.622543 \tabularnewline
50 & 0.393625 & 0.787251 & 0.606375 \tabularnewline
51 & 0.425805 & 0.85161 & 0.574195 \tabularnewline
52 & 0.38287 & 0.76574 & 0.61713 \tabularnewline
53 & 0.339683 & 0.679367 & 0.660317 \tabularnewline
54 & 0.305001 & 0.610002 & 0.694999 \tabularnewline
55 & 0.265726 & 0.531452 & 0.734274 \tabularnewline
56 & 0.263067 & 0.526135 & 0.736933 \tabularnewline
57 & 0.284351 & 0.568703 & 0.715649 \tabularnewline
58 & 0.386665 & 0.77333 & 0.613335 \tabularnewline
59 & 0.350932 & 0.701864 & 0.649068 \tabularnewline
60 & 0.309776 & 0.619552 & 0.690224 \tabularnewline
61 & 0.276457 & 0.552915 & 0.723543 \tabularnewline
62 & 0.264454 & 0.528908 & 0.735546 \tabularnewline
63 & 0.234333 & 0.468665 & 0.765667 \tabularnewline
64 & 0.232227 & 0.464454 & 0.767773 \tabularnewline
65 & 0.200269 & 0.400539 & 0.799731 \tabularnewline
66 & 0.171301 & 0.342602 & 0.828699 \tabularnewline
67 & 0.150645 & 0.30129 & 0.849355 \tabularnewline
68 & 0.152895 & 0.30579 & 0.847105 \tabularnewline
69 & 0.169344 & 0.338688 & 0.830656 \tabularnewline
70 & 0.144198 & 0.288396 & 0.855802 \tabularnewline
71 & 0.154184 & 0.308369 & 0.845816 \tabularnewline
72 & 0.17725 & 0.3545 & 0.82275 \tabularnewline
73 & 0.166594 & 0.333189 & 0.833406 \tabularnewline
74 & 0.142582 & 0.285165 & 0.857418 \tabularnewline
75 & 0.125984 & 0.251968 & 0.874016 \tabularnewline
76 & 0.172652 & 0.345303 & 0.827348 \tabularnewline
77 & 0.150889 & 0.301778 & 0.849111 \tabularnewline
78 & 0.12857 & 0.257141 & 0.87143 \tabularnewline
79 & 0.160492 & 0.320984 & 0.839508 \tabularnewline
80 & 0.186276 & 0.372552 & 0.813724 \tabularnewline
81 & 0.175291 & 0.350582 & 0.824709 \tabularnewline
82 & 0.152143 & 0.304286 & 0.847857 \tabularnewline
83 & 0.14697 & 0.293939 & 0.85303 \tabularnewline
84 & 0.137576 & 0.275153 & 0.862424 \tabularnewline
85 & 0.118648 & 0.237297 & 0.881352 \tabularnewline
86 & 0.107621 & 0.215242 & 0.892379 \tabularnewline
87 & 0.0939677 & 0.187935 & 0.906032 \tabularnewline
88 & 0.106213 & 0.212426 & 0.893787 \tabularnewline
89 & 0.0893732 & 0.178746 & 0.910627 \tabularnewline
90 & 0.090175 & 0.18035 & 0.909825 \tabularnewline
91 & 0.086364 & 0.172728 & 0.913636 \tabularnewline
92 & 0.0758314 & 0.151663 & 0.924169 \tabularnewline
93 & 0.0631764 & 0.126353 & 0.936824 \tabularnewline
94 & 0.0624073 & 0.124815 & 0.937593 \tabularnewline
95 & 0.065741 & 0.131482 & 0.934259 \tabularnewline
96 & 0.0628794 & 0.125759 & 0.937121 \tabularnewline
97 & 0.0539254 & 0.107851 & 0.946075 \tabularnewline
98 & 0.0495743 & 0.0991485 & 0.950426 \tabularnewline
99 & 0.0474671 & 0.0949342 & 0.952533 \tabularnewline
100 & 0.0457338 & 0.0914677 & 0.954266 \tabularnewline
101 & 0.0420089 & 0.0840178 & 0.957991 \tabularnewline
102 & 0.0343983 & 0.0687966 & 0.965602 \tabularnewline
103 & 0.0279264 & 0.0558527 & 0.972074 \tabularnewline
104 & 0.026851 & 0.053702 & 0.973149 \tabularnewline
105 & 0.0656045 & 0.131209 & 0.934395 \tabularnewline
106 & 0.0632235 & 0.126447 & 0.936776 \tabularnewline
107 & 0.0796247 & 0.159249 & 0.920375 \tabularnewline
108 & 0.0695165 & 0.139033 & 0.930484 \tabularnewline
109 & 0.112956 & 0.225911 & 0.887044 \tabularnewline
110 & 0.128424 & 0.256849 & 0.871576 \tabularnewline
111 & 0.121804 & 0.243608 & 0.878196 \tabularnewline
112 & 0.154054 & 0.308109 & 0.845946 \tabularnewline
113 & 0.142028 & 0.284056 & 0.857972 \tabularnewline
114 & 0.140938 & 0.281876 & 0.859062 \tabularnewline
115 & 0.13637 & 0.27274 & 0.86363 \tabularnewline
116 & 0.131643 & 0.263286 & 0.868357 \tabularnewline
117 & 0.125698 & 0.251396 & 0.874302 \tabularnewline
118 & 0.110052 & 0.220104 & 0.889948 \tabularnewline
119 & 0.105506 & 0.211012 & 0.894494 \tabularnewline
120 & 0.0937932 & 0.187586 & 0.906207 \tabularnewline
121 & 0.0810477 & 0.162095 & 0.918952 \tabularnewline
122 & 0.075029 & 0.150058 & 0.924971 \tabularnewline
123 & 0.0646536 & 0.129307 & 0.935346 \tabularnewline
124 & 0.0625282 & 0.125056 & 0.937472 \tabularnewline
125 & 0.0584002 & 0.1168 & 0.9416 \tabularnewline
126 & 0.073287 & 0.146574 & 0.926713 \tabularnewline
127 & 0.132222 & 0.264445 & 0.867778 \tabularnewline
128 & 0.12874 & 0.257481 & 0.87126 \tabularnewline
129 & 0.114936 & 0.229873 & 0.885064 \tabularnewline
130 & 0.105568 & 0.211136 & 0.894432 \tabularnewline
131 & 0.113191 & 0.226381 & 0.886809 \tabularnewline
132 & 0.122279 & 0.244557 & 0.877721 \tabularnewline
133 & 0.144786 & 0.289571 & 0.855214 \tabularnewline
134 & 0.128422 & 0.256843 & 0.871578 \tabularnewline
135 & 0.110813 & 0.221626 & 0.889187 \tabularnewline
136 & 0.0961716 & 0.192343 & 0.903828 \tabularnewline
137 & 0.0822629 & 0.164526 & 0.917737 \tabularnewline
138 & 0.0889922 & 0.177984 & 0.911008 \tabularnewline
139 & 0.0763215 & 0.152643 & 0.923678 \tabularnewline
140 & 0.0752685 & 0.150537 & 0.924731 \tabularnewline
141 & 0.0713245 & 0.142649 & 0.928675 \tabularnewline
142 & 0.0979017 & 0.195803 & 0.902098 \tabularnewline
143 & 0.117005 & 0.23401 & 0.882995 \tabularnewline
144 & 0.105809 & 0.211618 & 0.894191 \tabularnewline
145 & 0.182127 & 0.364255 & 0.817873 \tabularnewline
146 & 0.162965 & 0.325931 & 0.837035 \tabularnewline
147 & 0.148775 & 0.29755 & 0.851225 \tabularnewline
148 & 0.129949 & 0.259897 & 0.870051 \tabularnewline
149 & 0.118899 & 0.237799 & 0.881101 \tabularnewline
150 & 0.106442 & 0.212885 & 0.893558 \tabularnewline
151 & 0.174373 & 0.348746 & 0.825627 \tabularnewline
152 & 0.159865 & 0.31973 & 0.840135 \tabularnewline
153 & 0.144186 & 0.288371 & 0.855814 \tabularnewline
154 & 0.161219 & 0.322439 & 0.838781 \tabularnewline
155 & 0.141532 & 0.283064 & 0.858468 \tabularnewline
156 & 0.155894 & 0.311789 & 0.844106 \tabularnewline
157 & 0.149227 & 0.298455 & 0.850773 \tabularnewline
158 & 0.136527 & 0.273054 & 0.863473 \tabularnewline
159 & 0.131406 & 0.262811 & 0.868594 \tabularnewline
160 & 0.121102 & 0.242204 & 0.878898 \tabularnewline
161 & 0.103521 & 0.207042 & 0.896479 \tabularnewline
162 & 0.0966742 & 0.193348 & 0.903326 \tabularnewline
163 & 0.0882421 & 0.176484 & 0.911758 \tabularnewline
164 & 0.116587 & 0.233174 & 0.883413 \tabularnewline
165 & 0.104268 & 0.208537 & 0.895732 \tabularnewline
166 & 0.177686 & 0.355372 & 0.822314 \tabularnewline
167 & 0.175543 & 0.351086 & 0.824457 \tabularnewline
168 & 0.163322 & 0.326643 & 0.836678 \tabularnewline
169 & 0.148804 & 0.297607 & 0.851196 \tabularnewline
170 & 0.251899 & 0.503798 & 0.748101 \tabularnewline
171 & 0.281983 & 0.563966 & 0.718017 \tabularnewline
172 & 0.252314 & 0.504628 & 0.747686 \tabularnewline
173 & 0.354122 & 0.708243 & 0.645878 \tabularnewline
174 & 0.31913 & 0.638261 & 0.68087 \tabularnewline
175 & 0.38566 & 0.771321 & 0.61434 \tabularnewline
176 & 0.358469 & 0.716938 & 0.641531 \tabularnewline
177 & 0.363048 & 0.726097 & 0.636952 \tabularnewline
178 & 0.330586 & 0.661171 & 0.669414 \tabularnewline
179 & 0.300573 & 0.601147 & 0.699427 \tabularnewline
180 & 0.299253 & 0.598506 & 0.700747 \tabularnewline
181 & 0.269784 & 0.539568 & 0.730216 \tabularnewline
182 & 0.269257 & 0.538513 & 0.730743 \tabularnewline
183 & 0.280353 & 0.560707 & 0.719647 \tabularnewline
184 & 0.355751 & 0.711501 & 0.644249 \tabularnewline
185 & 0.581969 & 0.836062 & 0.418031 \tabularnewline
186 & 0.561326 & 0.877348 & 0.438674 \tabularnewline
187 & 0.557594 & 0.884813 & 0.442406 \tabularnewline
188 & 0.717929 & 0.564142 & 0.282071 \tabularnewline
189 & 0.691212 & 0.617577 & 0.308788 \tabularnewline
190 & 0.689823 & 0.620353 & 0.310177 \tabularnewline
191 & 0.652985 & 0.69403 & 0.347015 \tabularnewline
192 & 0.623784 & 0.752433 & 0.376216 \tabularnewline
193 & 0.587773 & 0.824453 & 0.412227 \tabularnewline
194 & 0.552286 & 0.895427 & 0.447714 \tabularnewline
195 & 0.511743 & 0.976515 & 0.488257 \tabularnewline
196 & 0.473596 & 0.947192 & 0.526404 \tabularnewline
197 & 0.46811 & 0.93622 & 0.53189 \tabularnewline
198 & 0.437725 & 0.87545 & 0.562275 \tabularnewline
199 & 0.397169 & 0.794338 & 0.602831 \tabularnewline
200 & 0.463806 & 0.927611 & 0.536194 \tabularnewline
201 & 0.428777 & 0.857553 & 0.571223 \tabularnewline
202 & 0.582722 & 0.834555 & 0.417278 \tabularnewline
203 & 0.559133 & 0.881735 & 0.440867 \tabularnewline
204 & 0.524859 & 0.950281 & 0.475141 \tabularnewline
205 & 0.480826 & 0.961652 & 0.519174 \tabularnewline
206 & 0.4408 & 0.8816 & 0.5592 \tabularnewline
207 & 0.402742 & 0.805483 & 0.597258 \tabularnewline
208 & 0.363292 & 0.726584 & 0.636708 \tabularnewline
209 & 0.335664 & 0.671328 & 0.664336 \tabularnewline
210 & 0.301614 & 0.603228 & 0.698386 \tabularnewline
211 & 0.268227 & 0.536455 & 0.731773 \tabularnewline
212 & 0.245445 & 0.49089 & 0.754555 \tabularnewline
213 & 0.304305 & 0.60861 & 0.695695 \tabularnewline
214 & 0.291909 & 0.583818 & 0.708091 \tabularnewline
215 & 0.253404 & 0.506808 & 0.746596 \tabularnewline
216 & 0.221525 & 0.44305 & 0.778475 \tabularnewline
217 & 0.198297 & 0.396593 & 0.801703 \tabularnewline
218 & 0.211716 & 0.423433 & 0.788284 \tabularnewline
219 & 0.183839 & 0.367679 & 0.816161 \tabularnewline
220 & 0.174122 & 0.348244 & 0.825878 \tabularnewline
221 & 0.145948 & 0.291897 & 0.854052 \tabularnewline
222 & 0.151916 & 0.303831 & 0.848084 \tabularnewline
223 & 0.123699 & 0.247398 & 0.876301 \tabularnewline
224 & 0.107207 & 0.214414 & 0.892793 \tabularnewline
225 & 0.151754 & 0.303508 & 0.848246 \tabularnewline
226 & 0.144124 & 0.288249 & 0.855876 \tabularnewline
227 & 0.131301 & 0.262603 & 0.868699 \tabularnewline
228 & 0.124628 & 0.249256 & 0.875372 \tabularnewline
229 & 0.100809 & 0.201619 & 0.899191 \tabularnewline
230 & 0.0791734 & 0.158347 & 0.920827 \tabularnewline
231 & 0.0731176 & 0.146235 & 0.926882 \tabularnewline
232 & 0.21927 & 0.43854 & 0.78073 \tabularnewline
233 & 0.188072 & 0.376143 & 0.811928 \tabularnewline
234 & 0.262582 & 0.525164 & 0.737418 \tabularnewline
235 & 0.213133 & 0.426267 & 0.786867 \tabularnewline
236 & 0.203824 & 0.407649 & 0.796176 \tabularnewline
237 & 0.172497 & 0.344995 & 0.827503 \tabularnewline
238 & 0.238891 & 0.477782 & 0.761109 \tabularnewline
239 & 0.192537 & 0.385074 & 0.807463 \tabularnewline
240 & 0.402592 & 0.805184 & 0.597408 \tabularnewline
241 & 0.404422 & 0.808844 & 0.595578 \tabularnewline
242 & 0.338475 & 0.676949 & 0.661525 \tabularnewline
243 & 0.267327 & 0.534653 & 0.732673 \tabularnewline
244 & 0.29605 & 0.5921 & 0.70395 \tabularnewline
245 & 0.337018 & 0.674036 & 0.662982 \tabularnewline
246 & 0.451358 & 0.902717 & 0.548642 \tabularnewline
247 & 0.429331 & 0.858661 & 0.570669 \tabularnewline
248 & 0.352659 & 0.705317 & 0.647341 \tabularnewline
249 & 0.55001 & 0.89998 & 0.44999 \tabularnewline
250 & 0.472879 & 0.945759 & 0.527121 \tabularnewline
251 & 0.398724 & 0.797447 & 0.601276 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221870&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]13[/C][C]0.814006[/C][C]0.371988[/C][C]0.185994[/C][/ROW]
[ROW][C]14[/C][C]0.771708[/C][C]0.456584[/C][C]0.228292[/C][/ROW]
[ROW][C]15[/C][C]0.680803[/C][C]0.638394[/C][C]0.319197[/C][/ROW]
[ROW][C]16[/C][C]0.693284[/C][C]0.613433[/C][C]0.306716[/C][/ROW]
[ROW][C]17[/C][C]0.742131[/C][C]0.515739[/C][C]0.257869[/C][/ROW]
[ROW][C]18[/C][C]0.729074[/C][C]0.541853[/C][C]0.270926[/C][/ROW]
[ROW][C]19[/C][C]0.642217[/C][C]0.715567[/C][C]0.357783[/C][/ROW]
[ROW][C]20[/C][C]0.669489[/C][C]0.661023[/C][C]0.330511[/C][/ROW]
[ROW][C]21[/C][C]0.694347[/C][C]0.611307[/C][C]0.305653[/C][/ROW]
[ROW][C]22[/C][C]0.630788[/C][C]0.738424[/C][C]0.369212[/C][/ROW]
[ROW][C]23[/C][C]0.639488[/C][C]0.721025[/C][C]0.360512[/C][/ROW]
[ROW][C]24[/C][C]0.562766[/C][C]0.874469[/C][C]0.437234[/C][/ROW]
[ROW][C]25[/C][C]0.647187[/C][C]0.705627[/C][C]0.352813[/C][/ROW]
[ROW][C]26[/C][C]0.790917[/C][C]0.418165[/C][C]0.209083[/C][/ROW]
[ROW][C]27[/C][C]0.766735[/C][C]0.466529[/C][C]0.233265[/C][/ROW]
[ROW][C]28[/C][C]0.722844[/C][C]0.554312[/C][C]0.277156[/C][/ROW]
[ROW][C]29[/C][C]0.702533[/C][C]0.594935[/C][C]0.297467[/C][/ROW]
[ROW][C]30[/C][C]0.643708[/C][C]0.712585[/C][C]0.356292[/C][/ROW]
[ROW][C]31[/C][C]0.615969[/C][C]0.768062[/C][C]0.384031[/C][/ROW]
[ROW][C]32[/C][C]0.695198[/C][C]0.609604[/C][C]0.304802[/C][/ROW]
[ROW][C]33[/C][C]0.71583[/C][C]0.568341[/C][C]0.28417[/C][/ROW]
[ROW][C]34[/C][C]0.666659[/C][C]0.666682[/C][C]0.333341[/C][/ROW]
[ROW][C]35[/C][C]0.616599[/C][C]0.766801[/C][C]0.383401[/C][/ROW]
[ROW][C]36[/C][C]0.562655[/C][C]0.87469[/C][C]0.437345[/C][/ROW]
[ROW][C]37[/C][C]0.514313[/C][C]0.971374[/C][C]0.485687[/C][/ROW]
[ROW][C]38[/C][C]0.499726[/C][C]0.999452[/C][C]0.500274[/C][/ROW]
[ROW][C]39[/C][C]0.564443[/C][C]0.871115[/C][C]0.435557[/C][/ROW]
[ROW][C]40[/C][C]0.512527[/C][C]0.974946[/C][C]0.487473[/C][/ROW]
[ROW][C]41[/C][C]0.496624[/C][C]0.993249[/C][C]0.503376[/C][/ROW]
[ROW][C]42[/C][C]0.447401[/C][C]0.894802[/C][C]0.552599[/C][/ROW]
[ROW][C]43[/C][C]0.41353[/C][C]0.827059[/C][C]0.58647[/C][/ROW]
[ROW][C]44[/C][C]0.373729[/C][C]0.747459[/C][C]0.626271[/C][/ROW]
[ROW][C]45[/C][C]0.464283[/C][C]0.928566[/C][C]0.535717[/C][/ROW]
[ROW][C]46[/C][C]0.484759[/C][C]0.969518[/C][C]0.515241[/C][/ROW]
[ROW][C]47[/C][C]0.463375[/C][C]0.926751[/C][C]0.536625[/C][/ROW]
[ROW][C]48[/C][C]0.426205[/C][C]0.85241[/C][C]0.573795[/C][/ROW]
[ROW][C]49[/C][C]0.377457[/C][C]0.754914[/C][C]0.622543[/C][/ROW]
[ROW][C]50[/C][C]0.393625[/C][C]0.787251[/C][C]0.606375[/C][/ROW]
[ROW][C]51[/C][C]0.425805[/C][C]0.85161[/C][C]0.574195[/C][/ROW]
[ROW][C]52[/C][C]0.38287[/C][C]0.76574[/C][C]0.61713[/C][/ROW]
[ROW][C]53[/C][C]0.339683[/C][C]0.679367[/C][C]0.660317[/C][/ROW]
[ROW][C]54[/C][C]0.305001[/C][C]0.610002[/C][C]0.694999[/C][/ROW]
[ROW][C]55[/C][C]0.265726[/C][C]0.531452[/C][C]0.734274[/C][/ROW]
[ROW][C]56[/C][C]0.263067[/C][C]0.526135[/C][C]0.736933[/C][/ROW]
[ROW][C]57[/C][C]0.284351[/C][C]0.568703[/C][C]0.715649[/C][/ROW]
[ROW][C]58[/C][C]0.386665[/C][C]0.77333[/C][C]0.613335[/C][/ROW]
[ROW][C]59[/C][C]0.350932[/C][C]0.701864[/C][C]0.649068[/C][/ROW]
[ROW][C]60[/C][C]0.309776[/C][C]0.619552[/C][C]0.690224[/C][/ROW]
[ROW][C]61[/C][C]0.276457[/C][C]0.552915[/C][C]0.723543[/C][/ROW]
[ROW][C]62[/C][C]0.264454[/C][C]0.528908[/C][C]0.735546[/C][/ROW]
[ROW][C]63[/C][C]0.234333[/C][C]0.468665[/C][C]0.765667[/C][/ROW]
[ROW][C]64[/C][C]0.232227[/C][C]0.464454[/C][C]0.767773[/C][/ROW]
[ROW][C]65[/C][C]0.200269[/C][C]0.400539[/C][C]0.799731[/C][/ROW]
[ROW][C]66[/C][C]0.171301[/C][C]0.342602[/C][C]0.828699[/C][/ROW]
[ROW][C]67[/C][C]0.150645[/C][C]0.30129[/C][C]0.849355[/C][/ROW]
[ROW][C]68[/C][C]0.152895[/C][C]0.30579[/C][C]0.847105[/C][/ROW]
[ROW][C]69[/C][C]0.169344[/C][C]0.338688[/C][C]0.830656[/C][/ROW]
[ROW][C]70[/C][C]0.144198[/C][C]0.288396[/C][C]0.855802[/C][/ROW]
[ROW][C]71[/C][C]0.154184[/C][C]0.308369[/C][C]0.845816[/C][/ROW]
[ROW][C]72[/C][C]0.17725[/C][C]0.3545[/C][C]0.82275[/C][/ROW]
[ROW][C]73[/C][C]0.166594[/C][C]0.333189[/C][C]0.833406[/C][/ROW]
[ROW][C]74[/C][C]0.142582[/C][C]0.285165[/C][C]0.857418[/C][/ROW]
[ROW][C]75[/C][C]0.125984[/C][C]0.251968[/C][C]0.874016[/C][/ROW]
[ROW][C]76[/C][C]0.172652[/C][C]0.345303[/C][C]0.827348[/C][/ROW]
[ROW][C]77[/C][C]0.150889[/C][C]0.301778[/C][C]0.849111[/C][/ROW]
[ROW][C]78[/C][C]0.12857[/C][C]0.257141[/C][C]0.87143[/C][/ROW]
[ROW][C]79[/C][C]0.160492[/C][C]0.320984[/C][C]0.839508[/C][/ROW]
[ROW][C]80[/C][C]0.186276[/C][C]0.372552[/C][C]0.813724[/C][/ROW]
[ROW][C]81[/C][C]0.175291[/C][C]0.350582[/C][C]0.824709[/C][/ROW]
[ROW][C]82[/C][C]0.152143[/C][C]0.304286[/C][C]0.847857[/C][/ROW]
[ROW][C]83[/C][C]0.14697[/C][C]0.293939[/C][C]0.85303[/C][/ROW]
[ROW][C]84[/C][C]0.137576[/C][C]0.275153[/C][C]0.862424[/C][/ROW]
[ROW][C]85[/C][C]0.118648[/C][C]0.237297[/C][C]0.881352[/C][/ROW]
[ROW][C]86[/C][C]0.107621[/C][C]0.215242[/C][C]0.892379[/C][/ROW]
[ROW][C]87[/C][C]0.0939677[/C][C]0.187935[/C][C]0.906032[/C][/ROW]
[ROW][C]88[/C][C]0.106213[/C][C]0.212426[/C][C]0.893787[/C][/ROW]
[ROW][C]89[/C][C]0.0893732[/C][C]0.178746[/C][C]0.910627[/C][/ROW]
[ROW][C]90[/C][C]0.090175[/C][C]0.18035[/C][C]0.909825[/C][/ROW]
[ROW][C]91[/C][C]0.086364[/C][C]0.172728[/C][C]0.913636[/C][/ROW]
[ROW][C]92[/C][C]0.0758314[/C][C]0.151663[/C][C]0.924169[/C][/ROW]
[ROW][C]93[/C][C]0.0631764[/C][C]0.126353[/C][C]0.936824[/C][/ROW]
[ROW][C]94[/C][C]0.0624073[/C][C]0.124815[/C][C]0.937593[/C][/ROW]
[ROW][C]95[/C][C]0.065741[/C][C]0.131482[/C][C]0.934259[/C][/ROW]
[ROW][C]96[/C][C]0.0628794[/C][C]0.125759[/C][C]0.937121[/C][/ROW]
[ROW][C]97[/C][C]0.0539254[/C][C]0.107851[/C][C]0.946075[/C][/ROW]
[ROW][C]98[/C][C]0.0495743[/C][C]0.0991485[/C][C]0.950426[/C][/ROW]
[ROW][C]99[/C][C]0.0474671[/C][C]0.0949342[/C][C]0.952533[/C][/ROW]
[ROW][C]100[/C][C]0.0457338[/C][C]0.0914677[/C][C]0.954266[/C][/ROW]
[ROW][C]101[/C][C]0.0420089[/C][C]0.0840178[/C][C]0.957991[/C][/ROW]
[ROW][C]102[/C][C]0.0343983[/C][C]0.0687966[/C][C]0.965602[/C][/ROW]
[ROW][C]103[/C][C]0.0279264[/C][C]0.0558527[/C][C]0.972074[/C][/ROW]
[ROW][C]104[/C][C]0.026851[/C][C]0.053702[/C][C]0.973149[/C][/ROW]
[ROW][C]105[/C][C]0.0656045[/C][C]0.131209[/C][C]0.934395[/C][/ROW]
[ROW][C]106[/C][C]0.0632235[/C][C]0.126447[/C][C]0.936776[/C][/ROW]
[ROW][C]107[/C][C]0.0796247[/C][C]0.159249[/C][C]0.920375[/C][/ROW]
[ROW][C]108[/C][C]0.0695165[/C][C]0.139033[/C][C]0.930484[/C][/ROW]
[ROW][C]109[/C][C]0.112956[/C][C]0.225911[/C][C]0.887044[/C][/ROW]
[ROW][C]110[/C][C]0.128424[/C][C]0.256849[/C][C]0.871576[/C][/ROW]
[ROW][C]111[/C][C]0.121804[/C][C]0.243608[/C][C]0.878196[/C][/ROW]
[ROW][C]112[/C][C]0.154054[/C][C]0.308109[/C][C]0.845946[/C][/ROW]
[ROW][C]113[/C][C]0.142028[/C][C]0.284056[/C][C]0.857972[/C][/ROW]
[ROW][C]114[/C][C]0.140938[/C][C]0.281876[/C][C]0.859062[/C][/ROW]
[ROW][C]115[/C][C]0.13637[/C][C]0.27274[/C][C]0.86363[/C][/ROW]
[ROW][C]116[/C][C]0.131643[/C][C]0.263286[/C][C]0.868357[/C][/ROW]
[ROW][C]117[/C][C]0.125698[/C][C]0.251396[/C][C]0.874302[/C][/ROW]
[ROW][C]118[/C][C]0.110052[/C][C]0.220104[/C][C]0.889948[/C][/ROW]
[ROW][C]119[/C][C]0.105506[/C][C]0.211012[/C][C]0.894494[/C][/ROW]
[ROW][C]120[/C][C]0.0937932[/C][C]0.187586[/C][C]0.906207[/C][/ROW]
[ROW][C]121[/C][C]0.0810477[/C][C]0.162095[/C][C]0.918952[/C][/ROW]
[ROW][C]122[/C][C]0.075029[/C][C]0.150058[/C][C]0.924971[/C][/ROW]
[ROW][C]123[/C][C]0.0646536[/C][C]0.129307[/C][C]0.935346[/C][/ROW]
[ROW][C]124[/C][C]0.0625282[/C][C]0.125056[/C][C]0.937472[/C][/ROW]
[ROW][C]125[/C][C]0.0584002[/C][C]0.1168[/C][C]0.9416[/C][/ROW]
[ROW][C]126[/C][C]0.073287[/C][C]0.146574[/C][C]0.926713[/C][/ROW]
[ROW][C]127[/C][C]0.132222[/C][C]0.264445[/C][C]0.867778[/C][/ROW]
[ROW][C]128[/C][C]0.12874[/C][C]0.257481[/C][C]0.87126[/C][/ROW]
[ROW][C]129[/C][C]0.114936[/C][C]0.229873[/C][C]0.885064[/C][/ROW]
[ROW][C]130[/C][C]0.105568[/C][C]0.211136[/C][C]0.894432[/C][/ROW]
[ROW][C]131[/C][C]0.113191[/C][C]0.226381[/C][C]0.886809[/C][/ROW]
[ROW][C]132[/C][C]0.122279[/C][C]0.244557[/C][C]0.877721[/C][/ROW]
[ROW][C]133[/C][C]0.144786[/C][C]0.289571[/C][C]0.855214[/C][/ROW]
[ROW][C]134[/C][C]0.128422[/C][C]0.256843[/C][C]0.871578[/C][/ROW]
[ROW][C]135[/C][C]0.110813[/C][C]0.221626[/C][C]0.889187[/C][/ROW]
[ROW][C]136[/C][C]0.0961716[/C][C]0.192343[/C][C]0.903828[/C][/ROW]
[ROW][C]137[/C][C]0.0822629[/C][C]0.164526[/C][C]0.917737[/C][/ROW]
[ROW][C]138[/C][C]0.0889922[/C][C]0.177984[/C][C]0.911008[/C][/ROW]
[ROW][C]139[/C][C]0.0763215[/C][C]0.152643[/C][C]0.923678[/C][/ROW]
[ROW][C]140[/C][C]0.0752685[/C][C]0.150537[/C][C]0.924731[/C][/ROW]
[ROW][C]141[/C][C]0.0713245[/C][C]0.142649[/C][C]0.928675[/C][/ROW]
[ROW][C]142[/C][C]0.0979017[/C][C]0.195803[/C][C]0.902098[/C][/ROW]
[ROW][C]143[/C][C]0.117005[/C][C]0.23401[/C][C]0.882995[/C][/ROW]
[ROW][C]144[/C][C]0.105809[/C][C]0.211618[/C][C]0.894191[/C][/ROW]
[ROW][C]145[/C][C]0.182127[/C][C]0.364255[/C][C]0.817873[/C][/ROW]
[ROW][C]146[/C][C]0.162965[/C][C]0.325931[/C][C]0.837035[/C][/ROW]
[ROW][C]147[/C][C]0.148775[/C][C]0.29755[/C][C]0.851225[/C][/ROW]
[ROW][C]148[/C][C]0.129949[/C][C]0.259897[/C][C]0.870051[/C][/ROW]
[ROW][C]149[/C][C]0.118899[/C][C]0.237799[/C][C]0.881101[/C][/ROW]
[ROW][C]150[/C][C]0.106442[/C][C]0.212885[/C][C]0.893558[/C][/ROW]
[ROW][C]151[/C][C]0.174373[/C][C]0.348746[/C][C]0.825627[/C][/ROW]
[ROW][C]152[/C][C]0.159865[/C][C]0.31973[/C][C]0.840135[/C][/ROW]
[ROW][C]153[/C][C]0.144186[/C][C]0.288371[/C][C]0.855814[/C][/ROW]
[ROW][C]154[/C][C]0.161219[/C][C]0.322439[/C][C]0.838781[/C][/ROW]
[ROW][C]155[/C][C]0.141532[/C][C]0.283064[/C][C]0.858468[/C][/ROW]
[ROW][C]156[/C][C]0.155894[/C][C]0.311789[/C][C]0.844106[/C][/ROW]
[ROW][C]157[/C][C]0.149227[/C][C]0.298455[/C][C]0.850773[/C][/ROW]
[ROW][C]158[/C][C]0.136527[/C][C]0.273054[/C][C]0.863473[/C][/ROW]
[ROW][C]159[/C][C]0.131406[/C][C]0.262811[/C][C]0.868594[/C][/ROW]
[ROW][C]160[/C][C]0.121102[/C][C]0.242204[/C][C]0.878898[/C][/ROW]
[ROW][C]161[/C][C]0.103521[/C][C]0.207042[/C][C]0.896479[/C][/ROW]
[ROW][C]162[/C][C]0.0966742[/C][C]0.193348[/C][C]0.903326[/C][/ROW]
[ROW][C]163[/C][C]0.0882421[/C][C]0.176484[/C][C]0.911758[/C][/ROW]
[ROW][C]164[/C][C]0.116587[/C][C]0.233174[/C][C]0.883413[/C][/ROW]
[ROW][C]165[/C][C]0.104268[/C][C]0.208537[/C][C]0.895732[/C][/ROW]
[ROW][C]166[/C][C]0.177686[/C][C]0.355372[/C][C]0.822314[/C][/ROW]
[ROW][C]167[/C][C]0.175543[/C][C]0.351086[/C][C]0.824457[/C][/ROW]
[ROW][C]168[/C][C]0.163322[/C][C]0.326643[/C][C]0.836678[/C][/ROW]
[ROW][C]169[/C][C]0.148804[/C][C]0.297607[/C][C]0.851196[/C][/ROW]
[ROW][C]170[/C][C]0.251899[/C][C]0.503798[/C][C]0.748101[/C][/ROW]
[ROW][C]171[/C][C]0.281983[/C][C]0.563966[/C][C]0.718017[/C][/ROW]
[ROW][C]172[/C][C]0.252314[/C][C]0.504628[/C][C]0.747686[/C][/ROW]
[ROW][C]173[/C][C]0.354122[/C][C]0.708243[/C][C]0.645878[/C][/ROW]
[ROW][C]174[/C][C]0.31913[/C][C]0.638261[/C][C]0.68087[/C][/ROW]
[ROW][C]175[/C][C]0.38566[/C][C]0.771321[/C][C]0.61434[/C][/ROW]
[ROW][C]176[/C][C]0.358469[/C][C]0.716938[/C][C]0.641531[/C][/ROW]
[ROW][C]177[/C][C]0.363048[/C][C]0.726097[/C][C]0.636952[/C][/ROW]
[ROW][C]178[/C][C]0.330586[/C][C]0.661171[/C][C]0.669414[/C][/ROW]
[ROW][C]179[/C][C]0.300573[/C][C]0.601147[/C][C]0.699427[/C][/ROW]
[ROW][C]180[/C][C]0.299253[/C][C]0.598506[/C][C]0.700747[/C][/ROW]
[ROW][C]181[/C][C]0.269784[/C][C]0.539568[/C][C]0.730216[/C][/ROW]
[ROW][C]182[/C][C]0.269257[/C][C]0.538513[/C][C]0.730743[/C][/ROW]
[ROW][C]183[/C][C]0.280353[/C][C]0.560707[/C][C]0.719647[/C][/ROW]
[ROW][C]184[/C][C]0.355751[/C][C]0.711501[/C][C]0.644249[/C][/ROW]
[ROW][C]185[/C][C]0.581969[/C][C]0.836062[/C][C]0.418031[/C][/ROW]
[ROW][C]186[/C][C]0.561326[/C][C]0.877348[/C][C]0.438674[/C][/ROW]
[ROW][C]187[/C][C]0.557594[/C][C]0.884813[/C][C]0.442406[/C][/ROW]
[ROW][C]188[/C][C]0.717929[/C][C]0.564142[/C][C]0.282071[/C][/ROW]
[ROW][C]189[/C][C]0.691212[/C][C]0.617577[/C][C]0.308788[/C][/ROW]
[ROW][C]190[/C][C]0.689823[/C][C]0.620353[/C][C]0.310177[/C][/ROW]
[ROW][C]191[/C][C]0.652985[/C][C]0.69403[/C][C]0.347015[/C][/ROW]
[ROW][C]192[/C][C]0.623784[/C][C]0.752433[/C][C]0.376216[/C][/ROW]
[ROW][C]193[/C][C]0.587773[/C][C]0.824453[/C][C]0.412227[/C][/ROW]
[ROW][C]194[/C][C]0.552286[/C][C]0.895427[/C][C]0.447714[/C][/ROW]
[ROW][C]195[/C][C]0.511743[/C][C]0.976515[/C][C]0.488257[/C][/ROW]
[ROW][C]196[/C][C]0.473596[/C][C]0.947192[/C][C]0.526404[/C][/ROW]
[ROW][C]197[/C][C]0.46811[/C][C]0.93622[/C][C]0.53189[/C][/ROW]
[ROW][C]198[/C][C]0.437725[/C][C]0.87545[/C][C]0.562275[/C][/ROW]
[ROW][C]199[/C][C]0.397169[/C][C]0.794338[/C][C]0.602831[/C][/ROW]
[ROW][C]200[/C][C]0.463806[/C][C]0.927611[/C][C]0.536194[/C][/ROW]
[ROW][C]201[/C][C]0.428777[/C][C]0.857553[/C][C]0.571223[/C][/ROW]
[ROW][C]202[/C][C]0.582722[/C][C]0.834555[/C][C]0.417278[/C][/ROW]
[ROW][C]203[/C][C]0.559133[/C][C]0.881735[/C][C]0.440867[/C][/ROW]
[ROW][C]204[/C][C]0.524859[/C][C]0.950281[/C][C]0.475141[/C][/ROW]
[ROW][C]205[/C][C]0.480826[/C][C]0.961652[/C][C]0.519174[/C][/ROW]
[ROW][C]206[/C][C]0.4408[/C][C]0.8816[/C][C]0.5592[/C][/ROW]
[ROW][C]207[/C][C]0.402742[/C][C]0.805483[/C][C]0.597258[/C][/ROW]
[ROW][C]208[/C][C]0.363292[/C][C]0.726584[/C][C]0.636708[/C][/ROW]
[ROW][C]209[/C][C]0.335664[/C][C]0.671328[/C][C]0.664336[/C][/ROW]
[ROW][C]210[/C][C]0.301614[/C][C]0.603228[/C][C]0.698386[/C][/ROW]
[ROW][C]211[/C][C]0.268227[/C][C]0.536455[/C][C]0.731773[/C][/ROW]
[ROW][C]212[/C][C]0.245445[/C][C]0.49089[/C][C]0.754555[/C][/ROW]
[ROW][C]213[/C][C]0.304305[/C][C]0.60861[/C][C]0.695695[/C][/ROW]
[ROW][C]214[/C][C]0.291909[/C][C]0.583818[/C][C]0.708091[/C][/ROW]
[ROW][C]215[/C][C]0.253404[/C][C]0.506808[/C][C]0.746596[/C][/ROW]
[ROW][C]216[/C][C]0.221525[/C][C]0.44305[/C][C]0.778475[/C][/ROW]
[ROW][C]217[/C][C]0.198297[/C][C]0.396593[/C][C]0.801703[/C][/ROW]
[ROW][C]218[/C][C]0.211716[/C][C]0.423433[/C][C]0.788284[/C][/ROW]
[ROW][C]219[/C][C]0.183839[/C][C]0.367679[/C][C]0.816161[/C][/ROW]
[ROW][C]220[/C][C]0.174122[/C][C]0.348244[/C][C]0.825878[/C][/ROW]
[ROW][C]221[/C][C]0.145948[/C][C]0.291897[/C][C]0.854052[/C][/ROW]
[ROW][C]222[/C][C]0.151916[/C][C]0.303831[/C][C]0.848084[/C][/ROW]
[ROW][C]223[/C][C]0.123699[/C][C]0.247398[/C][C]0.876301[/C][/ROW]
[ROW][C]224[/C][C]0.107207[/C][C]0.214414[/C][C]0.892793[/C][/ROW]
[ROW][C]225[/C][C]0.151754[/C][C]0.303508[/C][C]0.848246[/C][/ROW]
[ROW][C]226[/C][C]0.144124[/C][C]0.288249[/C][C]0.855876[/C][/ROW]
[ROW][C]227[/C][C]0.131301[/C][C]0.262603[/C][C]0.868699[/C][/ROW]
[ROW][C]228[/C][C]0.124628[/C][C]0.249256[/C][C]0.875372[/C][/ROW]
[ROW][C]229[/C][C]0.100809[/C][C]0.201619[/C][C]0.899191[/C][/ROW]
[ROW][C]230[/C][C]0.0791734[/C][C]0.158347[/C][C]0.920827[/C][/ROW]
[ROW][C]231[/C][C]0.0731176[/C][C]0.146235[/C][C]0.926882[/C][/ROW]
[ROW][C]232[/C][C]0.21927[/C][C]0.43854[/C][C]0.78073[/C][/ROW]
[ROW][C]233[/C][C]0.188072[/C][C]0.376143[/C][C]0.811928[/C][/ROW]
[ROW][C]234[/C][C]0.262582[/C][C]0.525164[/C][C]0.737418[/C][/ROW]
[ROW][C]235[/C][C]0.213133[/C][C]0.426267[/C][C]0.786867[/C][/ROW]
[ROW][C]236[/C][C]0.203824[/C][C]0.407649[/C][C]0.796176[/C][/ROW]
[ROW][C]237[/C][C]0.172497[/C][C]0.344995[/C][C]0.827503[/C][/ROW]
[ROW][C]238[/C][C]0.238891[/C][C]0.477782[/C][C]0.761109[/C][/ROW]
[ROW][C]239[/C][C]0.192537[/C][C]0.385074[/C][C]0.807463[/C][/ROW]
[ROW][C]240[/C][C]0.402592[/C][C]0.805184[/C][C]0.597408[/C][/ROW]
[ROW][C]241[/C][C]0.404422[/C][C]0.808844[/C][C]0.595578[/C][/ROW]
[ROW][C]242[/C][C]0.338475[/C][C]0.676949[/C][C]0.661525[/C][/ROW]
[ROW][C]243[/C][C]0.267327[/C][C]0.534653[/C][C]0.732673[/C][/ROW]
[ROW][C]244[/C][C]0.29605[/C][C]0.5921[/C][C]0.70395[/C][/ROW]
[ROW][C]245[/C][C]0.337018[/C][C]0.674036[/C][C]0.662982[/C][/ROW]
[ROW][C]246[/C][C]0.451358[/C][C]0.902717[/C][C]0.548642[/C][/ROW]
[ROW][C]247[/C][C]0.429331[/C][C]0.858661[/C][C]0.570669[/C][/ROW]
[ROW][C]248[/C][C]0.352659[/C][C]0.705317[/C][C]0.647341[/C][/ROW]
[ROW][C]249[/C][C]0.55001[/C][C]0.89998[/C][C]0.44999[/C][/ROW]
[ROW][C]250[/C][C]0.472879[/C][C]0.945759[/C][C]0.527121[/C][/ROW]
[ROW][C]251[/C][C]0.398724[/C][C]0.797447[/C][C]0.601276[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221870&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221870&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.8140060.3719880.185994
140.7717080.4565840.228292
150.6808030.6383940.319197
160.6932840.6134330.306716
170.7421310.5157390.257869
180.7290740.5418530.270926
190.6422170.7155670.357783
200.6694890.6610230.330511
210.6943470.6113070.305653
220.6307880.7384240.369212
230.6394880.7210250.360512
240.5627660.8744690.437234
250.6471870.7056270.352813
260.7909170.4181650.209083
270.7667350.4665290.233265
280.7228440.5543120.277156
290.7025330.5949350.297467
300.6437080.7125850.356292
310.6159690.7680620.384031
320.6951980.6096040.304802
330.715830.5683410.28417
340.6666590.6666820.333341
350.6165990.7668010.383401
360.5626550.874690.437345
370.5143130.9713740.485687
380.4997260.9994520.500274
390.5644430.8711150.435557
400.5125270.9749460.487473
410.4966240.9932490.503376
420.4474010.8948020.552599
430.413530.8270590.58647
440.3737290.7474590.626271
450.4642830.9285660.535717
460.4847590.9695180.515241
470.4633750.9267510.536625
480.4262050.852410.573795
490.3774570.7549140.622543
500.3936250.7872510.606375
510.4258050.851610.574195
520.382870.765740.61713
530.3396830.6793670.660317
540.3050010.6100020.694999
550.2657260.5314520.734274
560.2630670.5261350.736933
570.2843510.5687030.715649
580.3866650.773330.613335
590.3509320.7018640.649068
600.3097760.6195520.690224
610.2764570.5529150.723543
620.2644540.5289080.735546
630.2343330.4686650.765667
640.2322270.4644540.767773
650.2002690.4005390.799731
660.1713010.3426020.828699
670.1506450.301290.849355
680.1528950.305790.847105
690.1693440.3386880.830656
700.1441980.2883960.855802
710.1541840.3083690.845816
720.177250.35450.82275
730.1665940.3331890.833406
740.1425820.2851650.857418
750.1259840.2519680.874016
760.1726520.3453030.827348
770.1508890.3017780.849111
780.128570.2571410.87143
790.1604920.3209840.839508
800.1862760.3725520.813724
810.1752910.3505820.824709
820.1521430.3042860.847857
830.146970.2939390.85303
840.1375760.2751530.862424
850.1186480.2372970.881352
860.1076210.2152420.892379
870.09396770.1879350.906032
880.1062130.2124260.893787
890.08937320.1787460.910627
900.0901750.180350.909825
910.0863640.1727280.913636
920.07583140.1516630.924169
930.06317640.1263530.936824
940.06240730.1248150.937593
950.0657410.1314820.934259
960.06287940.1257590.937121
970.05392540.1078510.946075
980.04957430.09914850.950426
990.04746710.09493420.952533
1000.04573380.09146770.954266
1010.04200890.08401780.957991
1020.03439830.06879660.965602
1030.02792640.05585270.972074
1040.0268510.0537020.973149
1050.06560450.1312090.934395
1060.06322350.1264470.936776
1070.07962470.1592490.920375
1080.06951650.1390330.930484
1090.1129560.2259110.887044
1100.1284240.2568490.871576
1110.1218040.2436080.878196
1120.1540540.3081090.845946
1130.1420280.2840560.857972
1140.1409380.2818760.859062
1150.136370.272740.86363
1160.1316430.2632860.868357
1170.1256980.2513960.874302
1180.1100520.2201040.889948
1190.1055060.2110120.894494
1200.09379320.1875860.906207
1210.08104770.1620950.918952
1220.0750290.1500580.924971
1230.06465360.1293070.935346
1240.06252820.1250560.937472
1250.05840020.11680.9416
1260.0732870.1465740.926713
1270.1322220.2644450.867778
1280.128740.2574810.87126
1290.1149360.2298730.885064
1300.1055680.2111360.894432
1310.1131910.2263810.886809
1320.1222790.2445570.877721
1330.1447860.2895710.855214
1340.1284220.2568430.871578
1350.1108130.2216260.889187
1360.09617160.1923430.903828
1370.08226290.1645260.917737
1380.08899220.1779840.911008
1390.07632150.1526430.923678
1400.07526850.1505370.924731
1410.07132450.1426490.928675
1420.09790170.1958030.902098
1430.1170050.234010.882995
1440.1058090.2116180.894191
1450.1821270.3642550.817873
1460.1629650.3259310.837035
1470.1487750.297550.851225
1480.1299490.2598970.870051
1490.1188990.2377990.881101
1500.1064420.2128850.893558
1510.1743730.3487460.825627
1520.1598650.319730.840135
1530.1441860.2883710.855814
1540.1612190.3224390.838781
1550.1415320.2830640.858468
1560.1558940.3117890.844106
1570.1492270.2984550.850773
1580.1365270.2730540.863473
1590.1314060.2628110.868594
1600.1211020.2422040.878898
1610.1035210.2070420.896479
1620.09667420.1933480.903326
1630.08824210.1764840.911758
1640.1165870.2331740.883413
1650.1042680.2085370.895732
1660.1776860.3553720.822314
1670.1755430.3510860.824457
1680.1633220.3266430.836678
1690.1488040.2976070.851196
1700.2518990.5037980.748101
1710.2819830.5639660.718017
1720.2523140.5046280.747686
1730.3541220.7082430.645878
1740.319130.6382610.68087
1750.385660.7713210.61434
1760.3584690.7169380.641531
1770.3630480.7260970.636952
1780.3305860.6611710.669414
1790.3005730.6011470.699427
1800.2992530.5985060.700747
1810.2697840.5395680.730216
1820.2692570.5385130.730743
1830.2803530.5607070.719647
1840.3557510.7115010.644249
1850.5819690.8360620.418031
1860.5613260.8773480.438674
1870.5575940.8848130.442406
1880.7179290.5641420.282071
1890.6912120.6175770.308788
1900.6898230.6203530.310177
1910.6529850.694030.347015
1920.6237840.7524330.376216
1930.5877730.8244530.412227
1940.5522860.8954270.447714
1950.5117430.9765150.488257
1960.4735960.9471920.526404
1970.468110.936220.53189
1980.4377250.875450.562275
1990.3971690.7943380.602831
2000.4638060.9276110.536194
2010.4287770.8575530.571223
2020.5827220.8345550.417278
2030.5591330.8817350.440867
2040.5248590.9502810.475141
2050.4808260.9616520.519174
2060.44080.88160.5592
2070.4027420.8054830.597258
2080.3632920.7265840.636708
2090.3356640.6713280.664336
2100.3016140.6032280.698386
2110.2682270.5364550.731773
2120.2454450.490890.754555
2130.3043050.608610.695695
2140.2919090.5838180.708091
2150.2534040.5068080.746596
2160.2215250.443050.778475
2170.1982970.3965930.801703
2180.2117160.4234330.788284
2190.1838390.3676790.816161
2200.1741220.3482440.825878
2210.1459480.2918970.854052
2220.1519160.3038310.848084
2230.1236990.2473980.876301
2240.1072070.2144140.892793
2250.1517540.3035080.848246
2260.1441240.2882490.855876
2270.1313010.2626030.868699
2280.1246280.2492560.875372
2290.1008090.2016190.899191
2300.07917340.1583470.920827
2310.07311760.1462350.926882
2320.219270.438540.78073
2330.1880720.3761430.811928
2340.2625820.5251640.737418
2350.2131330.4262670.786867
2360.2038240.4076490.796176
2370.1724970.3449950.827503
2380.2388910.4777820.761109
2390.1925370.3850740.807463
2400.4025920.8051840.597408
2410.4044220.8088440.595578
2420.3384750.6769490.661525
2430.2673270.5346530.732673
2440.296050.59210.70395
2450.3370180.6740360.662982
2460.4513580.9027170.548642
2470.4293310.8586610.570669
2480.3526590.7053170.647341
2490.550010.899980.44999
2500.4728790.9457590.527121
2510.3987240.7974470.601276






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level70.0292887OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 7 & 0.0292887 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221870&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]7[/C][C]0.0292887[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221870&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221870&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level70.0292887OK


Figures (Output of Computation)

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

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