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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 20 Nov 2013 08:00:18 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/20/t1384952439tgjem5wan13bbe8.htm/, Retrieved Wed, 01 May 2024 22:59:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226596, Retrieved Wed, 01 May 2024 22:59:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [time effect in su...] [2010-11-17 08:55:33] [b98453cac15ba1066b407e146608df68]
- RMPD  [Multiple Regression] [WS 7] [2013-11-18 17:03:12] [d1af3aceda32c4de5f8ef20fdfdffdc9]
- R PD    [Multiple Regression] [regressie] [2013-11-20 12:55:33] [c6f8b1ebc3c8db7b9216fced5f615834]
- R P         [Multiple Regression] [multiple regres] [2013-11-20 13:00:18] [f8aff9f47a6e961fa8f039c54f435553] [Current]
- R P           [Multiple Regression] [multiple regression] [2013-11-20 13:07:29] [c6f8b1ebc3c8db7b9216fced5f615834]
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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 time25 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 25 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226596&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]25 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226596&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226596&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 time25 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 24.4755 -0.027795Connected[t] + 0.00335189Separate[t] -0.0567553Learning[t] -0.00534309Software[t] -0.679487Happiness[t] -0.158205Sport1[t] + 0.155997Sport2[t] + 0.440018Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Depression[t] =  +  24.4755 -0.027795Connected[t] +  0.00335189Separate[t] -0.0567553Learning[t] -0.00534309Software[t] -0.679487Happiness[t] -0.158205Sport1[t] +  0.155997Sport2[t] +  0.440018Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226596&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Depression[t] =  +  24.4755 -0.027795Connected[t] +  0.00335189Separate[t] -0.0567553Learning[t] -0.00534309Software[t] -0.679487Happiness[t] -0.158205Sport1[t] +  0.155997Sport2[t] +  0.440018Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226596&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226596&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 24.4755 -0.027795Connected[t] + 0.00335189Separate[t] -0.0567553Learning[t] -0.00534309Software[t] -0.679487Happiness[t] -0.158205Sport1[t] + 0.155997Sport2[t] + 0.440018Month[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)24.47553.624466.7539.74485e-114.87243e-11
Connected-0.0277950.0513215-0.54160.5885770.294288
Separate0.003351890.05217630.064240.9488280.474414
Learning-0.05675530.0922729-0.61510.539050.269525
Software-0.005343090.0942581-0.056690.954840.47742
Happiness-0.6794870.0742896-9.1461.93288e-179.66442e-18
Sport1-0.1582050.0548633-2.8840.0042670.0021335
Sport20.1559970.08219671.8980.0588450.0294225
Month0.4400180.2365681.860.06403640.0320182

\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) & 24.4755 & 3.62446 & 6.753 & 9.74485e-11 & 4.87243e-11 \tabularnewline
Connected & -0.027795 & 0.0513215 & -0.5416 & 0.588577 & 0.294288 \tabularnewline
Separate & 0.00335189 & 0.0521763 & 0.06424 & 0.948828 & 0.474414 \tabularnewline
Learning & -0.0567553 & 0.0922729 & -0.6151 & 0.53905 & 0.269525 \tabularnewline
Software & -0.00534309 & 0.0942581 & -0.05669 & 0.95484 & 0.47742 \tabularnewline
Happiness & -0.679487 & 0.0742896 & -9.146 & 1.93288e-17 & 9.66442e-18 \tabularnewline
Sport1 & -0.158205 & 0.0548633 & -2.884 & 0.004267 & 0.0021335 \tabularnewline
Sport2 & 0.155997 & 0.0821967 & 1.898 & 0.058845 & 0.0294225 \tabularnewline
Month & 0.440018 & 0.236568 & 1.86 & 0.0640364 & 0.0320182 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226596&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]24.4755[/C][C]3.62446[/C][C]6.753[/C][C]9.74485e-11[/C][C]4.87243e-11[/C][/ROW]
[ROW][C]Connected[/C][C]-0.027795[/C][C]0.0513215[/C][C]-0.5416[/C][C]0.588577[/C][C]0.294288[/C][/ROW]
[ROW][C]Separate[/C][C]0.00335189[/C][C]0.0521763[/C][C]0.06424[/C][C]0.948828[/C][C]0.474414[/C][/ROW]
[ROW][C]Learning[/C][C]-0.0567553[/C][C]0.0922729[/C][C]-0.6151[/C][C]0.53905[/C][C]0.269525[/C][/ROW]
[ROW][C]Software[/C][C]-0.00534309[/C][C]0.0942581[/C][C]-0.05669[/C][C]0.95484[/C][C]0.47742[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.679487[/C][C]0.0742896[/C][C]-9.146[/C][C]1.93288e-17[/C][C]9.66442e-18[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.158205[/C][C]0.0548633[/C][C]-2.884[/C][C]0.004267[/C][C]0.0021335[/C][/ROW]
[ROW][C]Sport2[/C][C]0.155997[/C][C]0.0821967[/C][C]1.898[/C][C]0.058845[/C][C]0.0294225[/C][/ROW]
[ROW][C]Month[/C][C]0.440018[/C][C]0.236568[/C][C]1.86[/C][C]0.0640364[/C][C]0.0320182[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226596&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226596&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)24.47553.624466.7539.74485e-114.87243e-11
Connected-0.0277950.0513215-0.54160.5885770.294288
Separate0.003351890.05217630.064240.9488280.474414
Learning-0.05675530.0922729-0.61510.539050.269525
Software-0.005343090.0942581-0.056690.954840.47742
Happiness-0.6794870.0742896-9.1461.93288e-179.66442e-18
Sport1-0.1582050.0548633-2.8840.0042670.0021335
Sport20.1559970.08219671.8980.0588450.0294225
Month0.4400180.2365681.860.06403640.0320182






Multiple Linear Regression - Regression Statistics
Multiple R0.625295
R-squared0.390994
Adjusted R-squared0.371887
F-TEST (value)20.4643
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.74975
Sum Squared Residuals1928.09

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.625295 \tabularnewline
R-squared & 0.390994 \tabularnewline
Adjusted R-squared & 0.371887 \tabularnewline
F-TEST (value) & 20.4643 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.74975 \tabularnewline
Sum Squared Residuals & 1928.09 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226596&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.625295[/C][/ROW]
[ROW][C]R-squared[/C][C]0.390994[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.371887[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]20.4643[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.74975[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1928.09[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226596&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226596&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 R0.625295
R-squared0.390994
Adjusted R-squared0.371887
F-TEST (value)20.4643
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.74975
Sum Squared Residuals1928.09






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.7158-1.71577
2119.086181.91382
31415.1967-1.19667
41214.4436-2.44359
52111.03129.96884
6129.529952.47005
72214.18747.81265
81112.1599-1.15986
91011.8141-1.81411
101311.75121.24877
111010.1163-0.116281
12810.2714-2.27143
131515.6819-0.68189
141412.24531.75474
15108.870761.12924
161413.66860.331378
171412.27931.72073
18119.258181.74182
191013.1567-3.15665
201312.40770.592255
219.510.4136-0.913608
221415.3373-1.33735
231213.4233-1.42328
241415.3297-1.32973
25119.384951.61505
26914.9292-5.92916
271110.40340.596603
281513.15131.84873
291411.14452.85554
301315.5431-2.54307
31910.8782-1.8782
321514.84020.159802
331010.5872-0.587241
341111.5848-0.584822
351312.06440.935561
36811.8115-3.81145
372016.80753.19248
381211.970.0299716
391010.3731-0.373058
401013.4144-3.41439
41911.6734-2.67344
421410.86933.13069
43812.0045-4.00455
441415.1809-1.1809
451112.0688-1.06878
461314.8438-1.84377
47912.8784-3.87843
481111.8405-0.840525
49159.889035.11097
501112.9492-1.94924
511011.2921-1.29208
521412.92621.07385
531815.24232.75768
541415.8538-1.85382
551114.6112-3.61115
5614.511.8142.68604
571310.93442.06562
58912.5313-3.53126
591013.6229-3.62293
601514.0950.904983
612018.14841.85161
621212.526-0.52602
631213.9822-1.98222
641413.93450.0655383
651313.0349-0.034913
661115.1852-4.18522
671715.5321.46798
681213.7451-1.74508
691312.94930.050713
701412.49821.50185
711314.0812-1.08121
721513.02111.97885
731311.4461.55402
741011.992-1.99198
751112.7263-1.72631
761913.7135.28703
771311.0761.92396
781714.18212.81785
791312.35720.642782
80914.7371-5.73711
811111.5923-0.59233
82912.6497-3.64973
831211.32960.670401
841212.471-0.470958
851312.73820.26185
861312.06980.930228
871213.2232-1.22317
881514.97620.0237681
892218.03083.96922
901311.48121.51878
911514.70890.291118
921311.86991.13009
931512.16692.83307
9412.513.2104-0.710431
951110.75460.245449
961614.6251.37503
971112.3737-1.3737
981110.11110.888944
991012.2189-2.21894
1001010.4023-0.402311
1011614.31481.68517
1021210.57651.42349
1031115.806-4.80603
1041611.76374.23627
1051916.59182.40819
1061111.3444-0.344372
1071612.17773.82233
1081516.8355-1.83553
1092417.71056.28953
1101411.65582.34423
1111514.82420.175844
1121112.9246-1.92458
1131513.49171.50834
1141210.30431.6957
1151010.6539-0.653948
1161414.3205-0.320547
1171313.9788-0.978775
118913.4021-4.40213
1191511.79663.20344
1201515.7369-0.736908
1211412.76651.23349
1221111.2996-0.299606
123812.1078-4.10778
1241112.3368-1.33683
1251113.1368-2.13681
12689.78434-1.78434
1271010.3653-0.365283
128119.722741.27726
1291312.55450.445513
1301113.6214-2.62138
1312017.26142.73863
1321011.7389-1.7389
1331513.25021.74976
1341212.3924-0.392388
1351411.11672.88332
1362316.51586.48422
1371414.2101-0.210055
1381616.9239-0.923924
1391113.2155-2.21552
1401214.1054-2.10541
1411013.5619-3.56195
1421411.06132.93867
1431212.2636-0.263612
1441211.92610.0739024
1451110.88530.114651
1461211.42220.577772
1471316.1551-3.15507
1481114.2746-3.27465
1491916.73582.26422
1501211.29390.706078
1511712.91194.08809
152911.3934-2.39343
1531214.4128-2.41275
1541916.33252.6675
1551814.23463.76536
1561514.70890.291118
1571413.61930.380656
158119.722741.27726
159912.9044-3.90441
1601813.74664.25335
1611614.69721.30281
1622417.33276.66734
1631412.82191.17811
1642011.28588.71424
1651816.11891.88107
1662317.26945.7306
1671213.3742-1.37422
1681414.9913-0.991309
1691616.4078-0.40782
1701816.44861.55136
1712016.81173.18827
1721212.0683-0.0682657
1731216.4355-4.43547
1741715.33781.66224
1751312.26510.73488
176913.3241-4.32407
1771617.5087-1.50869
1781815.17922.82081
1791012.6344-2.63436
1801415.0248-1.02476
1811114.5556-3.5556
182914.7499-5.74993
1831113.0135-2.01349
1841012.77-2.77
1851111.9078-0.907759
1861913.58175.41826
1871412.89341.10663
1881211.77290.227101
1891415.2731-1.27314
1902116.8554.14503
1911315.9181-2.9181
1921012.9071-2.90709
1931513.28331.71675
1941616.6129-0.612896
1951413.02310.976875
1961215.1349-3.13494
1971912.99536.0047
1981512.54152.45847
1991918.19370.806252
2001313.5769-0.576894
2011717.4426-0.442597
2021213.0327-1.03265
2031110.93750.0625455
2041415.8163-1.81629
2051112.7432-1.74321
2061312.70170.298323
2071213.1197-1.11969
2081513.22881.77116
2091414.7042-0.704192
2101211.21540.784584
2111717.7355-0.735529
2121111.6853-0.685292
2131814.83263.16742
2141316.0459-3.04588
2151715.65381.34617
2161313.6935-0.693528
2171110.60540.394637
2181212.9657-0.965721
2192218.18143.81863
2201412.47711.52286
2211215.3295-3.32953
2221212.3204-0.320424
2231716.26860.73143
224913.113-4.11302
2252117.29433.70573
2261012.025-2.02496
2271111.4079-0.407933
2281214.853-2.85296
2292318.48344.51661
2301315.9181-2.91805
2311213.6639-1.6639
2321618.0537-2.05365
233913.8478-4.84782
2341714.14212.85786
235912.288-3.28805
2361415.9005-1.90047
2371715.75121.24876
2381316.008-3.00801
2391116.1636-5.16365
2401215.7817-3.78169
2411014.1407-4.1407
2421919.2035-0.203537
2431616.1779-0.177919
2441615.32820.671834
2451412.58921.41079
2462016.06463.93542
2471514.81760.182435
2482315.85687.14318
2492018.09581.90423
2501616.2111-0.211138
2511413.19160.808421
2521714.05942.94064
2531114.514-3.51396
2541314.3454-1.34538
2551715.61551.38446
2561515.5823-0.582277
2572116.22194.77814
2581818.0398-0.0398334
2591513.20851.79146
260816.3864-8.3864
2611214.0457-2.04569
2621213.2553-1.2553
2632219.18172.81833
2641213.5786-1.57859

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 13.7158 & -1.71577 \tabularnewline
2 & 11 & 9.08618 & 1.91382 \tabularnewline
3 & 14 & 15.1967 & -1.19667 \tabularnewline
4 & 12 & 14.4436 & -2.44359 \tabularnewline
5 & 21 & 11.0312 & 9.96884 \tabularnewline
6 & 12 & 9.52995 & 2.47005 \tabularnewline
7 & 22 & 14.1874 & 7.81265 \tabularnewline
8 & 11 & 12.1599 & -1.15986 \tabularnewline
9 & 10 & 11.8141 & -1.81411 \tabularnewline
10 & 13 & 11.7512 & 1.24877 \tabularnewline
11 & 10 & 10.1163 & -0.116281 \tabularnewline
12 & 8 & 10.2714 & -2.27143 \tabularnewline
13 & 15 & 15.6819 & -0.68189 \tabularnewline
14 & 14 & 12.2453 & 1.75474 \tabularnewline
15 & 10 & 8.87076 & 1.12924 \tabularnewline
16 & 14 & 13.6686 & 0.331378 \tabularnewline
17 & 14 & 12.2793 & 1.72073 \tabularnewline
18 & 11 & 9.25818 & 1.74182 \tabularnewline
19 & 10 & 13.1567 & -3.15665 \tabularnewline
20 & 13 & 12.4077 & 0.592255 \tabularnewline
21 & 9.5 & 10.4136 & -0.913608 \tabularnewline
22 & 14 & 15.3373 & -1.33735 \tabularnewline
23 & 12 & 13.4233 & -1.42328 \tabularnewline
24 & 14 & 15.3297 & -1.32973 \tabularnewline
25 & 11 & 9.38495 & 1.61505 \tabularnewline
26 & 9 & 14.9292 & -5.92916 \tabularnewline
27 & 11 & 10.4034 & 0.596603 \tabularnewline
28 & 15 & 13.1513 & 1.84873 \tabularnewline
29 & 14 & 11.1445 & 2.85554 \tabularnewline
30 & 13 & 15.5431 & -2.54307 \tabularnewline
31 & 9 & 10.8782 & -1.8782 \tabularnewline
32 & 15 & 14.8402 & 0.159802 \tabularnewline
33 & 10 & 10.5872 & -0.587241 \tabularnewline
34 & 11 & 11.5848 & -0.584822 \tabularnewline
35 & 13 & 12.0644 & 0.935561 \tabularnewline
36 & 8 & 11.8115 & -3.81145 \tabularnewline
37 & 20 & 16.8075 & 3.19248 \tabularnewline
38 & 12 & 11.97 & 0.0299716 \tabularnewline
39 & 10 & 10.3731 & -0.373058 \tabularnewline
40 & 10 & 13.4144 & -3.41439 \tabularnewline
41 & 9 & 11.6734 & -2.67344 \tabularnewline
42 & 14 & 10.8693 & 3.13069 \tabularnewline
43 & 8 & 12.0045 & -4.00455 \tabularnewline
44 & 14 & 15.1809 & -1.1809 \tabularnewline
45 & 11 & 12.0688 & -1.06878 \tabularnewline
46 & 13 & 14.8438 & -1.84377 \tabularnewline
47 & 9 & 12.8784 & -3.87843 \tabularnewline
48 & 11 & 11.8405 & -0.840525 \tabularnewline
49 & 15 & 9.88903 & 5.11097 \tabularnewline
50 & 11 & 12.9492 & -1.94924 \tabularnewline
51 & 10 & 11.2921 & -1.29208 \tabularnewline
52 & 14 & 12.9262 & 1.07385 \tabularnewline
53 & 18 & 15.2423 & 2.75768 \tabularnewline
54 & 14 & 15.8538 & -1.85382 \tabularnewline
55 & 11 & 14.6112 & -3.61115 \tabularnewline
56 & 14.5 & 11.814 & 2.68604 \tabularnewline
57 & 13 & 10.9344 & 2.06562 \tabularnewline
58 & 9 & 12.5313 & -3.53126 \tabularnewline
59 & 10 & 13.6229 & -3.62293 \tabularnewline
60 & 15 & 14.095 & 0.904983 \tabularnewline
61 & 20 & 18.1484 & 1.85161 \tabularnewline
62 & 12 & 12.526 & -0.52602 \tabularnewline
63 & 12 & 13.9822 & -1.98222 \tabularnewline
64 & 14 & 13.9345 & 0.0655383 \tabularnewline
65 & 13 & 13.0349 & -0.034913 \tabularnewline
66 & 11 & 15.1852 & -4.18522 \tabularnewline
67 & 17 & 15.532 & 1.46798 \tabularnewline
68 & 12 & 13.7451 & -1.74508 \tabularnewline
69 & 13 & 12.9493 & 0.050713 \tabularnewline
70 & 14 & 12.4982 & 1.50185 \tabularnewline
71 & 13 & 14.0812 & -1.08121 \tabularnewline
72 & 15 & 13.0211 & 1.97885 \tabularnewline
73 & 13 & 11.446 & 1.55402 \tabularnewline
74 & 10 & 11.992 & -1.99198 \tabularnewline
75 & 11 & 12.7263 & -1.72631 \tabularnewline
76 & 19 & 13.713 & 5.28703 \tabularnewline
77 & 13 & 11.076 & 1.92396 \tabularnewline
78 & 17 & 14.1821 & 2.81785 \tabularnewline
79 & 13 & 12.3572 & 0.642782 \tabularnewline
80 & 9 & 14.7371 & -5.73711 \tabularnewline
81 & 11 & 11.5923 & -0.59233 \tabularnewline
82 & 9 & 12.6497 & -3.64973 \tabularnewline
83 & 12 & 11.3296 & 0.670401 \tabularnewline
84 & 12 & 12.471 & -0.470958 \tabularnewline
85 & 13 & 12.7382 & 0.26185 \tabularnewline
86 & 13 & 12.0698 & 0.930228 \tabularnewline
87 & 12 & 13.2232 & -1.22317 \tabularnewline
88 & 15 & 14.9762 & 0.0237681 \tabularnewline
89 & 22 & 18.0308 & 3.96922 \tabularnewline
90 & 13 & 11.4812 & 1.51878 \tabularnewline
91 & 15 & 14.7089 & 0.291118 \tabularnewline
92 & 13 & 11.8699 & 1.13009 \tabularnewline
93 & 15 & 12.1669 & 2.83307 \tabularnewline
94 & 12.5 & 13.2104 & -0.710431 \tabularnewline
95 & 11 & 10.7546 & 0.245449 \tabularnewline
96 & 16 & 14.625 & 1.37503 \tabularnewline
97 & 11 & 12.3737 & -1.3737 \tabularnewline
98 & 11 & 10.1111 & 0.888944 \tabularnewline
99 & 10 & 12.2189 & -2.21894 \tabularnewline
100 & 10 & 10.4023 & -0.402311 \tabularnewline
101 & 16 & 14.3148 & 1.68517 \tabularnewline
102 & 12 & 10.5765 & 1.42349 \tabularnewline
103 & 11 & 15.806 & -4.80603 \tabularnewline
104 & 16 & 11.7637 & 4.23627 \tabularnewline
105 & 19 & 16.5918 & 2.40819 \tabularnewline
106 & 11 & 11.3444 & -0.344372 \tabularnewline
107 & 16 & 12.1777 & 3.82233 \tabularnewline
108 & 15 & 16.8355 & -1.83553 \tabularnewline
109 & 24 & 17.7105 & 6.28953 \tabularnewline
110 & 14 & 11.6558 & 2.34423 \tabularnewline
111 & 15 & 14.8242 & 0.175844 \tabularnewline
112 & 11 & 12.9246 & -1.92458 \tabularnewline
113 & 15 & 13.4917 & 1.50834 \tabularnewline
114 & 12 & 10.3043 & 1.6957 \tabularnewline
115 & 10 & 10.6539 & -0.653948 \tabularnewline
116 & 14 & 14.3205 & -0.320547 \tabularnewline
117 & 13 & 13.9788 & -0.978775 \tabularnewline
118 & 9 & 13.4021 & -4.40213 \tabularnewline
119 & 15 & 11.7966 & 3.20344 \tabularnewline
120 & 15 & 15.7369 & -0.736908 \tabularnewline
121 & 14 & 12.7665 & 1.23349 \tabularnewline
122 & 11 & 11.2996 & -0.299606 \tabularnewline
123 & 8 & 12.1078 & -4.10778 \tabularnewline
124 & 11 & 12.3368 & -1.33683 \tabularnewline
125 & 11 & 13.1368 & -2.13681 \tabularnewline
126 & 8 & 9.78434 & -1.78434 \tabularnewline
127 & 10 & 10.3653 & -0.365283 \tabularnewline
128 & 11 & 9.72274 & 1.27726 \tabularnewline
129 & 13 & 12.5545 & 0.445513 \tabularnewline
130 & 11 & 13.6214 & -2.62138 \tabularnewline
131 & 20 & 17.2614 & 2.73863 \tabularnewline
132 & 10 & 11.7389 & -1.7389 \tabularnewline
133 & 15 & 13.2502 & 1.74976 \tabularnewline
134 & 12 & 12.3924 & -0.392388 \tabularnewline
135 & 14 & 11.1167 & 2.88332 \tabularnewline
136 & 23 & 16.5158 & 6.48422 \tabularnewline
137 & 14 & 14.2101 & -0.210055 \tabularnewline
138 & 16 & 16.9239 & -0.923924 \tabularnewline
139 & 11 & 13.2155 & -2.21552 \tabularnewline
140 & 12 & 14.1054 & -2.10541 \tabularnewline
141 & 10 & 13.5619 & -3.56195 \tabularnewline
142 & 14 & 11.0613 & 2.93867 \tabularnewline
143 & 12 & 12.2636 & -0.263612 \tabularnewline
144 & 12 & 11.9261 & 0.0739024 \tabularnewline
145 & 11 & 10.8853 & 0.114651 \tabularnewline
146 & 12 & 11.4222 & 0.577772 \tabularnewline
147 & 13 & 16.1551 & -3.15507 \tabularnewline
148 & 11 & 14.2746 & -3.27465 \tabularnewline
149 & 19 & 16.7358 & 2.26422 \tabularnewline
150 & 12 & 11.2939 & 0.706078 \tabularnewline
151 & 17 & 12.9119 & 4.08809 \tabularnewline
152 & 9 & 11.3934 & -2.39343 \tabularnewline
153 & 12 & 14.4128 & -2.41275 \tabularnewline
154 & 19 & 16.3325 & 2.6675 \tabularnewline
155 & 18 & 14.2346 & 3.76536 \tabularnewline
156 & 15 & 14.7089 & 0.291118 \tabularnewline
157 & 14 & 13.6193 & 0.380656 \tabularnewline
158 & 11 & 9.72274 & 1.27726 \tabularnewline
159 & 9 & 12.9044 & -3.90441 \tabularnewline
160 & 18 & 13.7466 & 4.25335 \tabularnewline
161 & 16 & 14.6972 & 1.30281 \tabularnewline
162 & 24 & 17.3327 & 6.66734 \tabularnewline
163 & 14 & 12.8219 & 1.17811 \tabularnewline
164 & 20 & 11.2858 & 8.71424 \tabularnewline
165 & 18 & 16.1189 & 1.88107 \tabularnewline
166 & 23 & 17.2694 & 5.7306 \tabularnewline
167 & 12 & 13.3742 & -1.37422 \tabularnewline
168 & 14 & 14.9913 & -0.991309 \tabularnewline
169 & 16 & 16.4078 & -0.40782 \tabularnewline
170 & 18 & 16.4486 & 1.55136 \tabularnewline
171 & 20 & 16.8117 & 3.18827 \tabularnewline
172 & 12 & 12.0683 & -0.0682657 \tabularnewline
173 & 12 & 16.4355 & -4.43547 \tabularnewline
174 & 17 & 15.3378 & 1.66224 \tabularnewline
175 & 13 & 12.2651 & 0.73488 \tabularnewline
176 & 9 & 13.3241 & -4.32407 \tabularnewline
177 & 16 & 17.5087 & -1.50869 \tabularnewline
178 & 18 & 15.1792 & 2.82081 \tabularnewline
179 & 10 & 12.6344 & -2.63436 \tabularnewline
180 & 14 & 15.0248 & -1.02476 \tabularnewline
181 & 11 & 14.5556 & -3.5556 \tabularnewline
182 & 9 & 14.7499 & -5.74993 \tabularnewline
183 & 11 & 13.0135 & -2.01349 \tabularnewline
184 & 10 & 12.77 & -2.77 \tabularnewline
185 & 11 & 11.9078 & -0.907759 \tabularnewline
186 & 19 & 13.5817 & 5.41826 \tabularnewline
187 & 14 & 12.8934 & 1.10663 \tabularnewline
188 & 12 & 11.7729 & 0.227101 \tabularnewline
189 & 14 & 15.2731 & -1.27314 \tabularnewline
190 & 21 & 16.855 & 4.14503 \tabularnewline
191 & 13 & 15.9181 & -2.9181 \tabularnewline
192 & 10 & 12.9071 & -2.90709 \tabularnewline
193 & 15 & 13.2833 & 1.71675 \tabularnewline
194 & 16 & 16.6129 & -0.612896 \tabularnewline
195 & 14 & 13.0231 & 0.976875 \tabularnewline
196 & 12 & 15.1349 & -3.13494 \tabularnewline
197 & 19 & 12.9953 & 6.0047 \tabularnewline
198 & 15 & 12.5415 & 2.45847 \tabularnewline
199 & 19 & 18.1937 & 0.806252 \tabularnewline
200 & 13 & 13.5769 & -0.576894 \tabularnewline
201 & 17 & 17.4426 & -0.442597 \tabularnewline
202 & 12 & 13.0327 & -1.03265 \tabularnewline
203 & 11 & 10.9375 & 0.0625455 \tabularnewline
204 & 14 & 15.8163 & -1.81629 \tabularnewline
205 & 11 & 12.7432 & -1.74321 \tabularnewline
206 & 13 & 12.7017 & 0.298323 \tabularnewline
207 & 12 & 13.1197 & -1.11969 \tabularnewline
208 & 15 & 13.2288 & 1.77116 \tabularnewline
209 & 14 & 14.7042 & -0.704192 \tabularnewline
210 & 12 & 11.2154 & 0.784584 \tabularnewline
211 & 17 & 17.7355 & -0.735529 \tabularnewline
212 & 11 & 11.6853 & -0.685292 \tabularnewline
213 & 18 & 14.8326 & 3.16742 \tabularnewline
214 & 13 & 16.0459 & -3.04588 \tabularnewline
215 & 17 & 15.6538 & 1.34617 \tabularnewline
216 & 13 & 13.6935 & -0.693528 \tabularnewline
217 & 11 & 10.6054 & 0.394637 \tabularnewline
218 & 12 & 12.9657 & -0.965721 \tabularnewline
219 & 22 & 18.1814 & 3.81863 \tabularnewline
220 & 14 & 12.4771 & 1.52286 \tabularnewline
221 & 12 & 15.3295 & -3.32953 \tabularnewline
222 & 12 & 12.3204 & -0.320424 \tabularnewline
223 & 17 & 16.2686 & 0.73143 \tabularnewline
224 & 9 & 13.113 & -4.11302 \tabularnewline
225 & 21 & 17.2943 & 3.70573 \tabularnewline
226 & 10 & 12.025 & -2.02496 \tabularnewline
227 & 11 & 11.4079 & -0.407933 \tabularnewline
228 & 12 & 14.853 & -2.85296 \tabularnewline
229 & 23 & 18.4834 & 4.51661 \tabularnewline
230 & 13 & 15.9181 & -2.91805 \tabularnewline
231 & 12 & 13.6639 & -1.6639 \tabularnewline
232 & 16 & 18.0537 & -2.05365 \tabularnewline
233 & 9 & 13.8478 & -4.84782 \tabularnewline
234 & 17 & 14.1421 & 2.85786 \tabularnewline
235 & 9 & 12.288 & -3.28805 \tabularnewline
236 & 14 & 15.9005 & -1.90047 \tabularnewline
237 & 17 & 15.7512 & 1.24876 \tabularnewline
238 & 13 & 16.008 & -3.00801 \tabularnewline
239 & 11 & 16.1636 & -5.16365 \tabularnewline
240 & 12 & 15.7817 & -3.78169 \tabularnewline
241 & 10 & 14.1407 & -4.1407 \tabularnewline
242 & 19 & 19.2035 & -0.203537 \tabularnewline
243 & 16 & 16.1779 & -0.177919 \tabularnewline
244 & 16 & 15.3282 & 0.671834 \tabularnewline
245 & 14 & 12.5892 & 1.41079 \tabularnewline
246 & 20 & 16.0646 & 3.93542 \tabularnewline
247 & 15 & 14.8176 & 0.182435 \tabularnewline
248 & 23 & 15.8568 & 7.14318 \tabularnewline
249 & 20 & 18.0958 & 1.90423 \tabularnewline
250 & 16 & 16.2111 & -0.211138 \tabularnewline
251 & 14 & 13.1916 & 0.808421 \tabularnewline
252 & 17 & 14.0594 & 2.94064 \tabularnewline
253 & 11 & 14.514 & -3.51396 \tabularnewline
254 & 13 & 14.3454 & -1.34538 \tabularnewline
255 & 17 & 15.6155 & 1.38446 \tabularnewline
256 & 15 & 15.5823 & -0.582277 \tabularnewline
257 & 21 & 16.2219 & 4.77814 \tabularnewline
258 & 18 & 18.0398 & -0.0398334 \tabularnewline
259 & 15 & 13.2085 & 1.79146 \tabularnewline
260 & 8 & 16.3864 & -8.3864 \tabularnewline
261 & 12 & 14.0457 & -2.04569 \tabularnewline
262 & 12 & 13.2553 & -1.2553 \tabularnewline
263 & 22 & 19.1817 & 2.81833 \tabularnewline
264 & 12 & 13.5786 & -1.57859 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226596&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]13.7158[/C][C]-1.71577[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]9.08618[/C][C]1.91382[/C][/ROW]
[ROW][C]3[/C][C]14[/C][C]15.1967[/C][C]-1.19667[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.4436[/C][C]-2.44359[/C][/ROW]
[ROW][C]5[/C][C]21[/C][C]11.0312[/C][C]9.96884[/C][/ROW]
[ROW][C]6[/C][C]12[/C][C]9.52995[/C][C]2.47005[/C][/ROW]
[ROW][C]7[/C][C]22[/C][C]14.1874[/C][C]7.81265[/C][/ROW]
[ROW][C]8[/C][C]11[/C][C]12.1599[/C][C]-1.15986[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]11.8141[/C][C]-1.81411[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]11.7512[/C][C]1.24877[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.1163[/C][C]-0.116281[/C][/ROW]
[ROW][C]12[/C][C]8[/C][C]10.2714[/C][C]-2.27143[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]15.6819[/C][C]-0.68189[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]12.2453[/C][C]1.75474[/C][/ROW]
[ROW][C]15[/C][C]10[/C][C]8.87076[/C][C]1.12924[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.6686[/C][C]0.331378[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]12.2793[/C][C]1.72073[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]9.25818[/C][C]1.74182[/C][/ROW]
[ROW][C]19[/C][C]10[/C][C]13.1567[/C][C]-3.15665[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]12.4077[/C][C]0.592255[/C][/ROW]
[ROW][C]21[/C][C]9.5[/C][C]10.4136[/C][C]-0.913608[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]15.3373[/C][C]-1.33735[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]13.4233[/C][C]-1.42328[/C][/ROW]
[ROW][C]24[/C][C]14[/C][C]15.3297[/C][C]-1.32973[/C][/ROW]
[ROW][C]25[/C][C]11[/C][C]9.38495[/C][C]1.61505[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]14.9292[/C][C]-5.92916[/C][/ROW]
[ROW][C]27[/C][C]11[/C][C]10.4034[/C][C]0.596603[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]13.1513[/C][C]1.84873[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]11.1445[/C][C]2.85554[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]15.5431[/C][C]-2.54307[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]10.8782[/C][C]-1.8782[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]14.8402[/C][C]0.159802[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.5872[/C][C]-0.587241[/C][/ROW]
[ROW][C]34[/C][C]11[/C][C]11.5848[/C][C]-0.584822[/C][/ROW]
[ROW][C]35[/C][C]13[/C][C]12.0644[/C][C]0.935561[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]11.8115[/C][C]-3.81145[/C][/ROW]
[ROW][C]37[/C][C]20[/C][C]16.8075[/C][C]3.19248[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]11.97[/C][C]0.0299716[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.3731[/C][C]-0.373058[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]13.4144[/C][C]-3.41439[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]11.6734[/C][C]-2.67344[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]10.8693[/C][C]3.13069[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]12.0045[/C][C]-4.00455[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]15.1809[/C][C]-1.1809[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]12.0688[/C][C]-1.06878[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]14.8438[/C][C]-1.84377[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]12.8784[/C][C]-3.87843[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.8405[/C][C]-0.840525[/C][/ROW]
[ROW][C]49[/C][C]15[/C][C]9.88903[/C][C]5.11097[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]12.9492[/C][C]-1.94924[/C][/ROW]
[ROW][C]51[/C][C]10[/C][C]11.2921[/C][C]-1.29208[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]12.9262[/C][C]1.07385[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]15.2423[/C][C]2.75768[/C][/ROW]
[ROW][C]54[/C][C]14[/C][C]15.8538[/C][C]-1.85382[/C][/ROW]
[ROW][C]55[/C][C]11[/C][C]14.6112[/C][C]-3.61115[/C][/ROW]
[ROW][C]56[/C][C]14.5[/C][C]11.814[/C][C]2.68604[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]10.9344[/C][C]2.06562[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]12.5313[/C][C]-3.53126[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]13.6229[/C][C]-3.62293[/C][/ROW]
[ROW][C]60[/C][C]15[/C][C]14.095[/C][C]0.904983[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]18.1484[/C][C]1.85161[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]12.526[/C][C]-0.52602[/C][/ROW]
[ROW][C]63[/C][C]12[/C][C]13.9822[/C][C]-1.98222[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.9345[/C][C]0.0655383[/C][/ROW]
[ROW][C]65[/C][C]13[/C][C]13.0349[/C][C]-0.034913[/C][/ROW]
[ROW][C]66[/C][C]11[/C][C]15.1852[/C][C]-4.18522[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]15.532[/C][C]1.46798[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]13.7451[/C][C]-1.74508[/C][/ROW]
[ROW][C]69[/C][C]13[/C][C]12.9493[/C][C]0.050713[/C][/ROW]
[ROW][C]70[/C][C]14[/C][C]12.4982[/C][C]1.50185[/C][/ROW]
[ROW][C]71[/C][C]13[/C][C]14.0812[/C][C]-1.08121[/C][/ROW]
[ROW][C]72[/C][C]15[/C][C]13.0211[/C][C]1.97885[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]11.446[/C][C]1.55402[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]11.992[/C][C]-1.99198[/C][/ROW]
[ROW][C]75[/C][C]11[/C][C]12.7263[/C][C]-1.72631[/C][/ROW]
[ROW][C]76[/C][C]19[/C][C]13.713[/C][C]5.28703[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.076[/C][C]1.92396[/C][/ROW]
[ROW][C]78[/C][C]17[/C][C]14.1821[/C][C]2.81785[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.3572[/C][C]0.642782[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]14.7371[/C][C]-5.73711[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]11.5923[/C][C]-0.59233[/C][/ROW]
[ROW][C]82[/C][C]9[/C][C]12.6497[/C][C]-3.64973[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.3296[/C][C]0.670401[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.471[/C][C]-0.470958[/C][/ROW]
[ROW][C]85[/C][C]13[/C][C]12.7382[/C][C]0.26185[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]12.0698[/C][C]0.930228[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]13.2232[/C][C]-1.22317[/C][/ROW]
[ROW][C]88[/C][C]15[/C][C]14.9762[/C][C]0.0237681[/C][/ROW]
[ROW][C]89[/C][C]22[/C][C]18.0308[/C][C]3.96922[/C][/ROW]
[ROW][C]90[/C][C]13[/C][C]11.4812[/C][C]1.51878[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]14.7089[/C][C]0.291118[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]11.8699[/C][C]1.13009[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]12.1669[/C][C]2.83307[/C][/ROW]
[ROW][C]94[/C][C]12.5[/C][C]13.2104[/C][C]-0.710431[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]10.7546[/C][C]0.245449[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.625[/C][C]1.37503[/C][/ROW]
[ROW][C]97[/C][C]11[/C][C]12.3737[/C][C]-1.3737[/C][/ROW]
[ROW][C]98[/C][C]11[/C][C]10.1111[/C][C]0.888944[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]12.2189[/C][C]-2.21894[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]10.4023[/C][C]-0.402311[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.3148[/C][C]1.68517[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]10.5765[/C][C]1.42349[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]15.806[/C][C]-4.80603[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]11.7637[/C][C]4.23627[/C][/ROW]
[ROW][C]105[/C][C]19[/C][C]16.5918[/C][C]2.40819[/C][/ROW]
[ROW][C]106[/C][C]11[/C][C]11.3444[/C][C]-0.344372[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]12.1777[/C][C]3.82233[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]16.8355[/C][C]-1.83553[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]17.7105[/C][C]6.28953[/C][/ROW]
[ROW][C]110[/C][C]14[/C][C]11.6558[/C][C]2.34423[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]14.8242[/C][C]0.175844[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.9246[/C][C]-1.92458[/C][/ROW]
[ROW][C]113[/C][C]15[/C][C]13.4917[/C][C]1.50834[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]10.3043[/C][C]1.6957[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]10.6539[/C][C]-0.653948[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.3205[/C][C]-0.320547[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]13.9788[/C][C]-0.978775[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]13.4021[/C][C]-4.40213[/C][/ROW]
[ROW][C]119[/C][C]15[/C][C]11.7966[/C][C]3.20344[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]15.7369[/C][C]-0.736908[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]12.7665[/C][C]1.23349[/C][/ROW]
[ROW][C]122[/C][C]11[/C][C]11.2996[/C][C]-0.299606[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]12.1078[/C][C]-4.10778[/C][/ROW]
[ROW][C]124[/C][C]11[/C][C]12.3368[/C][C]-1.33683[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]13.1368[/C][C]-2.13681[/C][/ROW]
[ROW][C]126[/C][C]8[/C][C]9.78434[/C][C]-1.78434[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.3653[/C][C]-0.365283[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.72274[/C][C]1.27726[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]12.5545[/C][C]0.445513[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]13.6214[/C][C]-2.62138[/C][/ROW]
[ROW][C]131[/C][C]20[/C][C]17.2614[/C][C]2.73863[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]11.7389[/C][C]-1.7389[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.2502[/C][C]1.74976[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]12.3924[/C][C]-0.392388[/C][/ROW]
[ROW][C]135[/C][C]14[/C][C]11.1167[/C][C]2.88332[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]16.5158[/C][C]6.48422[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]14.2101[/C][C]-0.210055[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]16.9239[/C][C]-0.923924[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]13.2155[/C][C]-2.21552[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]14.1054[/C][C]-2.10541[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.5619[/C][C]-3.56195[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]11.0613[/C][C]2.93867[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]12.2636[/C][C]-0.263612[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]11.9261[/C][C]0.0739024[/C][/ROW]
[ROW][C]145[/C][C]11[/C][C]10.8853[/C][C]0.114651[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.4222[/C][C]0.577772[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]16.1551[/C][C]-3.15507[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.2746[/C][C]-3.27465[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]16.7358[/C][C]2.26422[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]11.2939[/C][C]0.706078[/C][/ROW]
[ROW][C]151[/C][C]17[/C][C]12.9119[/C][C]4.08809[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.3934[/C][C]-2.39343[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.4128[/C][C]-2.41275[/C][/ROW]
[ROW][C]154[/C][C]19[/C][C]16.3325[/C][C]2.6675[/C][/ROW]
[ROW][C]155[/C][C]18[/C][C]14.2346[/C][C]3.76536[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]14.7089[/C][C]0.291118[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.6193[/C][C]0.380656[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]9.72274[/C][C]1.27726[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]12.9044[/C][C]-3.90441[/C][/ROW]
[ROW][C]160[/C][C]18[/C][C]13.7466[/C][C]4.25335[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]14.6972[/C][C]1.30281[/C][/ROW]
[ROW][C]162[/C][C]24[/C][C]17.3327[/C][C]6.66734[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]12.8219[/C][C]1.17811[/C][/ROW]
[ROW][C]164[/C][C]20[/C][C]11.2858[/C][C]8.71424[/C][/ROW]
[ROW][C]165[/C][C]18[/C][C]16.1189[/C][C]1.88107[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]17.2694[/C][C]5.7306[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]13.3742[/C][C]-1.37422[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]14.9913[/C][C]-0.991309[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]16.4078[/C][C]-0.40782[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]16.4486[/C][C]1.55136[/C][/ROW]
[ROW][C]171[/C][C]20[/C][C]16.8117[/C][C]3.18827[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]12.0683[/C][C]-0.0682657[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]16.4355[/C][C]-4.43547[/C][/ROW]
[ROW][C]174[/C][C]17[/C][C]15.3378[/C][C]1.66224[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]12.2651[/C][C]0.73488[/C][/ROW]
[ROW][C]176[/C][C]9[/C][C]13.3241[/C][C]-4.32407[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]17.5087[/C][C]-1.50869[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]15.1792[/C][C]2.82081[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]12.6344[/C][C]-2.63436[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]15.0248[/C][C]-1.02476[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]14.5556[/C][C]-3.5556[/C][/ROW]
[ROW][C]182[/C][C]9[/C][C]14.7499[/C][C]-5.74993[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]13.0135[/C][C]-2.01349[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]12.77[/C][C]-2.77[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]11.9078[/C][C]-0.907759[/C][/ROW]
[ROW][C]186[/C][C]19[/C][C]13.5817[/C][C]5.41826[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]12.8934[/C][C]1.10663[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]11.7729[/C][C]0.227101[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]15.2731[/C][C]-1.27314[/C][/ROW]
[ROW][C]190[/C][C]21[/C][C]16.855[/C][C]4.14503[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]15.9181[/C][C]-2.9181[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]12.9071[/C][C]-2.90709[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]13.2833[/C][C]1.71675[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]16.6129[/C][C]-0.612896[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]13.0231[/C][C]0.976875[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]15.1349[/C][C]-3.13494[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]12.9953[/C][C]6.0047[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]12.5415[/C][C]2.45847[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]18.1937[/C][C]0.806252[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.5769[/C][C]-0.576894[/C][/ROW]
[ROW][C]201[/C][C]17[/C][C]17.4426[/C][C]-0.442597[/C][/ROW]
[ROW][C]202[/C][C]12[/C][C]13.0327[/C][C]-1.03265[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]10.9375[/C][C]0.0625455[/C][/ROW]
[ROW][C]204[/C][C]14[/C][C]15.8163[/C][C]-1.81629[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]12.7432[/C][C]-1.74321[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]12.7017[/C][C]0.298323[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]13.1197[/C][C]-1.11969[/C][/ROW]
[ROW][C]208[/C][C]15[/C][C]13.2288[/C][C]1.77116[/C][/ROW]
[ROW][C]209[/C][C]14[/C][C]14.7042[/C][C]-0.704192[/C][/ROW]
[ROW][C]210[/C][C]12[/C][C]11.2154[/C][C]0.784584[/C][/ROW]
[ROW][C]211[/C][C]17[/C][C]17.7355[/C][C]-0.735529[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]11.6853[/C][C]-0.685292[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]14.8326[/C][C]3.16742[/C][/ROW]
[ROW][C]214[/C][C]13[/C][C]16.0459[/C][C]-3.04588[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.6538[/C][C]1.34617[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]13.6935[/C][C]-0.693528[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]10.6054[/C][C]0.394637[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]12.9657[/C][C]-0.965721[/C][/ROW]
[ROW][C]219[/C][C]22[/C][C]18.1814[/C][C]3.81863[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]12.4771[/C][C]1.52286[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]15.3295[/C][C]-3.32953[/C][/ROW]
[ROW][C]222[/C][C]12[/C][C]12.3204[/C][C]-0.320424[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]16.2686[/C][C]0.73143[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]13.113[/C][C]-4.11302[/C][/ROW]
[ROW][C]225[/C][C]21[/C][C]17.2943[/C][C]3.70573[/C][/ROW]
[ROW][C]226[/C][C]10[/C][C]12.025[/C][C]-2.02496[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]11.4079[/C][C]-0.407933[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]14.853[/C][C]-2.85296[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]18.4834[/C][C]4.51661[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]15.9181[/C][C]-2.91805[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]13.6639[/C][C]-1.6639[/C][/ROW]
[ROW][C]232[/C][C]16[/C][C]18.0537[/C][C]-2.05365[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]13.8478[/C][C]-4.84782[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]14.1421[/C][C]2.85786[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]12.288[/C][C]-3.28805[/C][/ROW]
[ROW][C]236[/C][C]14[/C][C]15.9005[/C][C]-1.90047[/C][/ROW]
[ROW][C]237[/C][C]17[/C][C]15.7512[/C][C]1.24876[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]16.008[/C][C]-3.00801[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]16.1636[/C][C]-5.16365[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]15.7817[/C][C]-3.78169[/C][/ROW]
[ROW][C]241[/C][C]10[/C][C]14.1407[/C][C]-4.1407[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]19.2035[/C][C]-0.203537[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]16.1779[/C][C]-0.177919[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]15.3282[/C][C]0.671834[/C][/ROW]
[ROW][C]245[/C][C]14[/C][C]12.5892[/C][C]1.41079[/C][/ROW]
[ROW][C]246[/C][C]20[/C][C]16.0646[/C][C]3.93542[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]14.8176[/C][C]0.182435[/C][/ROW]
[ROW][C]248[/C][C]23[/C][C]15.8568[/C][C]7.14318[/C][/ROW]
[ROW][C]249[/C][C]20[/C][C]18.0958[/C][C]1.90423[/C][/ROW]
[ROW][C]250[/C][C]16[/C][C]16.2111[/C][C]-0.211138[/C][/ROW]
[ROW][C]251[/C][C]14[/C][C]13.1916[/C][C]0.808421[/C][/ROW]
[ROW][C]252[/C][C]17[/C][C]14.0594[/C][C]2.94064[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]14.514[/C][C]-3.51396[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]14.3454[/C][C]-1.34538[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]15.6155[/C][C]1.38446[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]15.5823[/C][C]-0.582277[/C][/ROW]
[ROW][C]257[/C][C]21[/C][C]16.2219[/C][C]4.77814[/C][/ROW]
[ROW][C]258[/C][C]18[/C][C]18.0398[/C][C]-0.0398334[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]13.2085[/C][C]1.79146[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]16.3864[/C][C]-8.3864[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]14.0457[/C][C]-2.04569[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]13.2553[/C][C]-1.2553[/C][/ROW]
[ROW][C]263[/C][C]22[/C][C]19.1817[/C][C]2.81833[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]13.5786[/C][C]-1.57859[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226596&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226596&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.7158-1.71577
2119.086181.91382
31415.1967-1.19667
41214.4436-2.44359
52111.03129.96884
6129.529952.47005
72214.18747.81265
81112.1599-1.15986
91011.8141-1.81411
101311.75121.24877
111010.1163-0.116281
12810.2714-2.27143
131515.6819-0.68189
141412.24531.75474
15108.870761.12924
161413.66860.331378
171412.27931.72073
18119.258181.74182
191013.1567-3.15665
201312.40770.592255
219.510.4136-0.913608
221415.3373-1.33735
231213.4233-1.42328
241415.3297-1.32973
25119.384951.61505
26914.9292-5.92916
271110.40340.596603
281513.15131.84873
291411.14452.85554
301315.5431-2.54307
31910.8782-1.8782
321514.84020.159802
331010.5872-0.587241
341111.5848-0.584822
351312.06440.935561
36811.8115-3.81145
372016.80753.19248
381211.970.0299716
391010.3731-0.373058
401013.4144-3.41439
41911.6734-2.67344
421410.86933.13069
43812.0045-4.00455
441415.1809-1.1809
451112.0688-1.06878
461314.8438-1.84377
47912.8784-3.87843
481111.8405-0.840525
49159.889035.11097
501112.9492-1.94924
511011.2921-1.29208
521412.92621.07385
531815.24232.75768
541415.8538-1.85382
551114.6112-3.61115
5614.511.8142.68604
571310.93442.06562
58912.5313-3.53126
591013.6229-3.62293
601514.0950.904983
612018.14841.85161
621212.526-0.52602
631213.9822-1.98222
641413.93450.0655383
651313.0349-0.034913
661115.1852-4.18522
671715.5321.46798
681213.7451-1.74508
691312.94930.050713
701412.49821.50185
711314.0812-1.08121
721513.02111.97885
731311.4461.55402
741011.992-1.99198
751112.7263-1.72631
761913.7135.28703
771311.0761.92396
781714.18212.81785
791312.35720.642782
80914.7371-5.73711
811111.5923-0.59233
82912.6497-3.64973
831211.32960.670401
841212.471-0.470958
851312.73820.26185
861312.06980.930228
871213.2232-1.22317
881514.97620.0237681
892218.03083.96922
901311.48121.51878
911514.70890.291118
921311.86991.13009
931512.16692.83307
9412.513.2104-0.710431
951110.75460.245449
961614.6251.37503
971112.3737-1.3737
981110.11110.888944
991012.2189-2.21894
1001010.4023-0.402311
1011614.31481.68517
1021210.57651.42349
1031115.806-4.80603
1041611.76374.23627
1051916.59182.40819
1061111.3444-0.344372
1071612.17773.82233
1081516.8355-1.83553
1092417.71056.28953
1101411.65582.34423
1111514.82420.175844
1121112.9246-1.92458
1131513.49171.50834
1141210.30431.6957
1151010.6539-0.653948
1161414.3205-0.320547
1171313.9788-0.978775
118913.4021-4.40213
1191511.79663.20344
1201515.7369-0.736908
1211412.76651.23349
1221111.2996-0.299606
123812.1078-4.10778
1241112.3368-1.33683
1251113.1368-2.13681
12689.78434-1.78434
1271010.3653-0.365283
128119.722741.27726
1291312.55450.445513
1301113.6214-2.62138
1312017.26142.73863
1321011.7389-1.7389
1331513.25021.74976
1341212.3924-0.392388
1351411.11672.88332
1362316.51586.48422
1371414.2101-0.210055
1381616.9239-0.923924
1391113.2155-2.21552
1401214.1054-2.10541
1411013.5619-3.56195
1421411.06132.93867
1431212.2636-0.263612
1441211.92610.0739024
1451110.88530.114651
1461211.42220.577772
1471316.1551-3.15507
1481114.2746-3.27465
1491916.73582.26422
1501211.29390.706078
1511712.91194.08809
152911.3934-2.39343
1531214.4128-2.41275
1541916.33252.6675
1551814.23463.76536
1561514.70890.291118
1571413.61930.380656
158119.722741.27726
159912.9044-3.90441
1601813.74664.25335
1611614.69721.30281
1622417.33276.66734
1631412.82191.17811
1642011.28588.71424
1651816.11891.88107
1662317.26945.7306
1671213.3742-1.37422
1681414.9913-0.991309
1691616.4078-0.40782
1701816.44861.55136
1712016.81173.18827
1721212.0683-0.0682657
1731216.4355-4.43547
1741715.33781.66224
1751312.26510.73488
176913.3241-4.32407
1771617.5087-1.50869
1781815.17922.82081
1791012.6344-2.63436
1801415.0248-1.02476
1811114.5556-3.5556
182914.7499-5.74993
1831113.0135-2.01349
1841012.77-2.77
1851111.9078-0.907759
1861913.58175.41826
1871412.89341.10663
1881211.77290.227101
1891415.2731-1.27314
1902116.8554.14503
1911315.9181-2.9181
1921012.9071-2.90709
1931513.28331.71675
1941616.6129-0.612896
1951413.02310.976875
1961215.1349-3.13494
1971912.99536.0047
1981512.54152.45847
1991918.19370.806252
2001313.5769-0.576894
2011717.4426-0.442597
2021213.0327-1.03265
2031110.93750.0625455
2041415.8163-1.81629
2051112.7432-1.74321
2061312.70170.298323
2071213.1197-1.11969
2081513.22881.77116
2091414.7042-0.704192
2101211.21540.784584
2111717.7355-0.735529
2121111.6853-0.685292
2131814.83263.16742
2141316.0459-3.04588
2151715.65381.34617
2161313.6935-0.693528
2171110.60540.394637
2181212.9657-0.965721
2192218.18143.81863
2201412.47711.52286
2211215.3295-3.32953
2221212.3204-0.320424
2231716.26860.73143
224913.113-4.11302
2252117.29433.70573
2261012.025-2.02496
2271111.4079-0.407933
2281214.853-2.85296
2292318.48344.51661
2301315.9181-2.91805
2311213.6639-1.6639
2321618.0537-2.05365
233913.8478-4.84782
2341714.14212.85786
235912.288-3.28805
2361415.9005-1.90047
2371715.75121.24876
2381316.008-3.00801
2391116.1636-5.16365
2401215.7817-3.78169
2411014.1407-4.1407
2421919.2035-0.203537
2431616.1779-0.177919
2441615.32820.671834
2451412.58921.41079
2462016.06463.93542
2471514.81760.182435
2482315.85687.14318
2492018.09581.90423
2501616.2111-0.211138
2511413.19160.808421
2521714.05942.94064
2531114.514-3.51396
2541314.3454-1.34538
2551715.61551.38446
2561515.5823-0.582277
2572116.22194.77814
2581818.0398-0.0398334
2591513.20851.79146
260816.3864-8.3864
2611214.0457-2.04569
2621213.2553-1.2553
2632219.18172.81833
2641213.5786-1.57859






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.9788350.04232950.0211648
130.9732880.05342420.0267121
140.9796290.04074230.0203712
150.9645490.07090160.0354508
160.9407120.1185760.0592879
170.9715670.05686540.0284327
180.9594270.08114690.0405735
190.9747270.05054690.0252734
200.961430.07713950.0385698
210.9531360.09372850.0468642
220.9489050.102190.0510952
230.9280910.1438180.0719091
240.9122970.1754060.0877029
250.8819430.2361140.118057
260.8795610.2408780.120439
270.8879440.2241130.112056
280.8552890.2894220.144711
290.8817250.2365490.118275
300.8718180.2563640.128182
310.8751650.249670.124835
320.8482520.3034960.151748
330.8207340.3585310.179266
340.7982590.4034820.201741
350.7684480.4631030.231552
360.7950310.4099370.204969
370.8679230.2641540.132077
380.8373310.3253370.162669
390.8069240.3861520.193076
400.8033650.393270.196635
410.7903770.4192460.209623
420.7800560.4398880.219944
430.8253860.3492280.174614
440.7920110.4159790.207989
450.7571450.4857110.242855
460.7306360.5387280.269364
470.7797260.4405480.220274
480.746990.506020.25301
490.7992990.4014020.200701
500.7734350.453130.226565
510.7609380.4781240.239062
520.7287910.5424170.271209
530.7328850.534230.267115
540.699650.6006990.30035
550.7061920.5876170.293808
560.7224570.5550860.277543
570.7020180.5959630.297982
580.7336310.5327390.266369
590.7452420.5095150.254758
600.7226940.5546110.277306
610.7343330.5313330.265667
620.6983620.6032750.301638
630.6740120.6519770.325988
640.6344610.7310790.365539
650.5937830.8124330.406217
660.581250.83750.41875
670.6042190.7915620.395781
680.5756080.8487850.424392
690.5348280.9303440.465172
700.506410.987180.49359
710.4685990.9371980.531401
720.439240.878480.56076
730.4068150.8136310.593185
740.3913050.7826110.608695
750.3644560.7289110.635544
760.4976840.9953670.502316
770.4666610.9333210.533339
780.4585930.9171850.541407
790.4205490.8410990.579451
800.5542140.8915710.445786
810.5211140.9577720.478886
820.557780.8844410.44222
830.5195260.9609470.480474
840.4829730.9659450.517027
850.4440040.8880090.555996
860.4080290.8160580.591971
870.3781580.7563170.621842
880.3432020.6864030.656798
890.4201440.8402880.579856
900.3876340.7752680.612366
910.3548860.7097730.645114
920.3227920.6455840.677208
930.3146290.6292590.685371
940.2872440.5744890.712756
950.256190.5123810.74381
960.2353590.4707180.764641
970.2181250.4362510.781875
980.1923240.3846480.807676
990.1901410.3802820.809859
1000.167480.334960.83252
1010.1537290.3074580.846271
1020.1356920.2713840.864308
1030.1819090.3638180.818091
1040.2064830.4129660.793517
1050.2076530.4153060.792347
1060.1834950.3669890.816505
1070.199870.3997410.80013
1080.186490.3729790.81351
1090.2884920.5769850.711508
1100.2756540.5513070.724346
1110.2463040.4926090.753696
1120.2392210.4784430.760779
1130.217310.434620.78269
1140.1982970.3965940.801703
1150.1760890.3521780.823911
1160.1547470.3094940.845253
1170.1394430.2788860.860557
1180.1809490.3618980.819051
1190.1836220.3672440.816378
1200.1628140.3256270.837186
1210.1462520.2925040.853748
1220.1293240.2586480.870676
1230.1595530.3191060.840447
1240.1442210.2884420.855779
1250.136690.2733810.86331
1260.1298360.2596710.870164
1270.1145890.2291770.885411
1280.100420.200840.89958
1290.08548340.1709670.914517
1300.0867850.173570.913215
1310.08610560.1722110.913894
1320.08065250.1613050.919347
1330.07172350.1434470.928276
1340.06078620.1215720.939214
1350.06023620.1204720.939764
1360.1158020.2316050.884198
1370.09955180.1991040.900448
1380.0876190.1752380.912381
1390.08590660.1718130.914093
1400.08275190.1655040.917248
1410.09776270.1955250.902237
1420.09667310.1933460.903327
1430.0825230.1650460.917477
1440.06970750.1394150.930292
1450.05903940.1180790.940961
1460.04923970.09847940.95076
1470.05646010.112920.94354
1480.06558480.131170.934415
1490.05972920.1194580.940271
1500.04996090.09992180.950039
1510.05830860.1166170.941691
1520.05783010.115660.94217
1530.05915680.1183140.940843
1540.05492970.1098590.94507
1550.05845970.1169190.94154
1560.04935380.09870760.950646
1570.04092530.08185070.959075
1580.03410420.06820830.965896
1590.05008550.1001710.949915
1600.05358260.1071650.946417
1610.04490820.08981650.955092
1620.09088860.1817770.909111
1630.08214390.1642880.917856
1640.291860.583720.70814
1650.2683410.5366820.731659
1660.3429520.6859040.657048
1670.3245720.6491450.675428
1680.3052590.6105170.694741
1690.2761110.5522220.723889
1700.2527750.5055510.747225
1710.2491090.4982180.750891
1720.2217510.4435020.778249
1730.2768210.5536420.723179
1740.2644890.5289780.735511
1750.2460160.4920330.753984
1760.2924660.5849320.707534
1770.2744480.5488950.725552
1780.2803490.5606980.719651
1790.2780350.556070.721965
1800.2516130.5032260.748387
1810.2869610.5739230.713039
1820.4010330.8020670.598967
1830.3904210.7808430.609579
1840.3846870.7693740.615313
1850.3704220.7408450.629578
1860.4863510.9727030.513649
1870.4512650.902530.548735
1880.41920.83840.5808
1890.3863080.7726150.613692
1900.4179930.8359860.582007
1910.4497170.8994340.550283
1920.4711670.9423350.528833
1930.4601630.9203260.539837
1940.4298910.8597810.570109
1950.4012840.8025690.598716
1960.4405210.8810410.559479
1970.6414380.7171230.358562
1980.6467470.7065070.353253
1990.6062980.7874050.393702
2000.5654570.8690860.434543
2010.5242170.9515670.475783
2020.4844090.9688180.515591
2030.4599210.9198420.540079
2040.4583020.9166030.541698
2050.4239640.8479280.576036
2060.3816360.7632720.618364
2070.3436270.6872540.656373
2080.3075720.6151450.692428
2090.2701940.5403890.729806
2100.2626790.5253570.737321
2110.2395780.4791560.760422
2120.2089860.4179730.791014
2130.2313630.4627260.768637
2140.217390.4347810.78261
2150.1863910.3727820.813609
2160.158610.317220.84139
2170.1494950.2989910.850505
2180.1248360.2496720.875164
2190.1256460.2512930.874354
2200.1175230.2350460.882477
2210.1179790.2359590.882021
2220.09582720.1916540.904173
2230.0771180.1542360.922882
2240.07920930.1584190.920791
2250.07043450.1408690.929565
2260.0566410.1132820.943359
2270.04323480.08646950.956765
2280.04068840.08137670.959312
2290.05539360.1107870.944606
2300.05284090.1056820.947159
2310.04006530.08013060.959935
2320.04120580.08241170.958794
2330.09159080.1831820.908409
2340.0958320.1916640.904168
2350.09120930.1824190.908791
2360.06959990.13920.9304
2370.09167430.1833490.908326
2380.1280880.2561760.871912
2390.2152920.4305830.784708
2400.213020.426040.78698
2410.1722740.3445480.827726
2420.2114010.4228030.788599
2430.1589770.3179550.841023
2440.1143210.2286410.885679
2450.1734520.3469040.826548
2460.1879510.3759010.812049
2470.1313710.2627430.868629
2480.1613080.3226150.838692
2490.2442380.4884760.755762
2500.1607520.3215030.839248
2510.1756820.3513640.824318
2520.798820.4023590.20118

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.978835 & 0.0423295 & 0.0211648 \tabularnewline
13 & 0.973288 & 0.0534242 & 0.0267121 \tabularnewline
14 & 0.979629 & 0.0407423 & 0.0203712 \tabularnewline
15 & 0.964549 & 0.0709016 & 0.0354508 \tabularnewline
16 & 0.940712 & 0.118576 & 0.0592879 \tabularnewline
17 & 0.971567 & 0.0568654 & 0.0284327 \tabularnewline
18 & 0.959427 & 0.0811469 & 0.0405735 \tabularnewline
19 & 0.974727 & 0.0505469 & 0.0252734 \tabularnewline
20 & 0.96143 & 0.0771395 & 0.0385698 \tabularnewline
21 & 0.953136 & 0.0937285 & 0.0468642 \tabularnewline
22 & 0.948905 & 0.10219 & 0.0510952 \tabularnewline
23 & 0.928091 & 0.143818 & 0.0719091 \tabularnewline
24 & 0.912297 & 0.175406 & 0.0877029 \tabularnewline
25 & 0.881943 & 0.236114 & 0.118057 \tabularnewline
26 & 0.879561 & 0.240878 & 0.120439 \tabularnewline
27 & 0.887944 & 0.224113 & 0.112056 \tabularnewline
28 & 0.855289 & 0.289422 & 0.144711 \tabularnewline
29 & 0.881725 & 0.236549 & 0.118275 \tabularnewline
30 & 0.871818 & 0.256364 & 0.128182 \tabularnewline
31 & 0.875165 & 0.24967 & 0.124835 \tabularnewline
32 & 0.848252 & 0.303496 & 0.151748 \tabularnewline
33 & 0.820734 & 0.358531 & 0.179266 \tabularnewline
34 & 0.798259 & 0.403482 & 0.201741 \tabularnewline
35 & 0.768448 & 0.463103 & 0.231552 \tabularnewline
36 & 0.795031 & 0.409937 & 0.204969 \tabularnewline
37 & 0.867923 & 0.264154 & 0.132077 \tabularnewline
38 & 0.837331 & 0.325337 & 0.162669 \tabularnewline
39 & 0.806924 & 0.386152 & 0.193076 \tabularnewline
40 & 0.803365 & 0.39327 & 0.196635 \tabularnewline
41 & 0.790377 & 0.419246 & 0.209623 \tabularnewline
42 & 0.780056 & 0.439888 & 0.219944 \tabularnewline
43 & 0.825386 & 0.349228 & 0.174614 \tabularnewline
44 & 0.792011 & 0.415979 & 0.207989 \tabularnewline
45 & 0.757145 & 0.485711 & 0.242855 \tabularnewline
46 & 0.730636 & 0.538728 & 0.269364 \tabularnewline
47 & 0.779726 & 0.440548 & 0.220274 \tabularnewline
48 & 0.74699 & 0.50602 & 0.25301 \tabularnewline
49 & 0.799299 & 0.401402 & 0.200701 \tabularnewline
50 & 0.773435 & 0.45313 & 0.226565 \tabularnewline
51 & 0.760938 & 0.478124 & 0.239062 \tabularnewline
52 & 0.728791 & 0.542417 & 0.271209 \tabularnewline
53 & 0.732885 & 0.53423 & 0.267115 \tabularnewline
54 & 0.69965 & 0.600699 & 0.30035 \tabularnewline
55 & 0.706192 & 0.587617 & 0.293808 \tabularnewline
56 & 0.722457 & 0.555086 & 0.277543 \tabularnewline
57 & 0.702018 & 0.595963 & 0.297982 \tabularnewline
58 & 0.733631 & 0.532739 & 0.266369 \tabularnewline
59 & 0.745242 & 0.509515 & 0.254758 \tabularnewline
60 & 0.722694 & 0.554611 & 0.277306 \tabularnewline
61 & 0.734333 & 0.531333 & 0.265667 \tabularnewline
62 & 0.698362 & 0.603275 & 0.301638 \tabularnewline
63 & 0.674012 & 0.651977 & 0.325988 \tabularnewline
64 & 0.634461 & 0.731079 & 0.365539 \tabularnewline
65 & 0.593783 & 0.812433 & 0.406217 \tabularnewline
66 & 0.58125 & 0.8375 & 0.41875 \tabularnewline
67 & 0.604219 & 0.791562 & 0.395781 \tabularnewline
68 & 0.575608 & 0.848785 & 0.424392 \tabularnewline
69 & 0.534828 & 0.930344 & 0.465172 \tabularnewline
70 & 0.50641 & 0.98718 & 0.49359 \tabularnewline
71 & 0.468599 & 0.937198 & 0.531401 \tabularnewline
72 & 0.43924 & 0.87848 & 0.56076 \tabularnewline
73 & 0.406815 & 0.813631 & 0.593185 \tabularnewline
74 & 0.391305 & 0.782611 & 0.608695 \tabularnewline
75 & 0.364456 & 0.728911 & 0.635544 \tabularnewline
76 & 0.497684 & 0.995367 & 0.502316 \tabularnewline
77 & 0.466661 & 0.933321 & 0.533339 \tabularnewline
78 & 0.458593 & 0.917185 & 0.541407 \tabularnewline
79 & 0.420549 & 0.841099 & 0.579451 \tabularnewline
80 & 0.554214 & 0.891571 & 0.445786 \tabularnewline
81 & 0.521114 & 0.957772 & 0.478886 \tabularnewline
82 & 0.55778 & 0.884441 & 0.44222 \tabularnewline
83 & 0.519526 & 0.960947 & 0.480474 \tabularnewline
84 & 0.482973 & 0.965945 & 0.517027 \tabularnewline
85 & 0.444004 & 0.888009 & 0.555996 \tabularnewline
86 & 0.408029 & 0.816058 & 0.591971 \tabularnewline
87 & 0.378158 & 0.756317 & 0.621842 \tabularnewline
88 & 0.343202 & 0.686403 & 0.656798 \tabularnewline
89 & 0.420144 & 0.840288 & 0.579856 \tabularnewline
90 & 0.387634 & 0.775268 & 0.612366 \tabularnewline
91 & 0.354886 & 0.709773 & 0.645114 \tabularnewline
92 & 0.322792 & 0.645584 & 0.677208 \tabularnewline
93 & 0.314629 & 0.629259 & 0.685371 \tabularnewline
94 & 0.287244 & 0.574489 & 0.712756 \tabularnewline
95 & 0.25619 & 0.512381 & 0.74381 \tabularnewline
96 & 0.235359 & 0.470718 & 0.764641 \tabularnewline
97 & 0.218125 & 0.436251 & 0.781875 \tabularnewline
98 & 0.192324 & 0.384648 & 0.807676 \tabularnewline
99 & 0.190141 & 0.380282 & 0.809859 \tabularnewline
100 & 0.16748 & 0.33496 & 0.83252 \tabularnewline
101 & 0.153729 & 0.307458 & 0.846271 \tabularnewline
102 & 0.135692 & 0.271384 & 0.864308 \tabularnewline
103 & 0.181909 & 0.363818 & 0.818091 \tabularnewline
104 & 0.206483 & 0.412966 & 0.793517 \tabularnewline
105 & 0.207653 & 0.415306 & 0.792347 \tabularnewline
106 & 0.183495 & 0.366989 & 0.816505 \tabularnewline
107 & 0.19987 & 0.399741 & 0.80013 \tabularnewline
108 & 0.18649 & 0.372979 & 0.81351 \tabularnewline
109 & 0.288492 & 0.576985 & 0.711508 \tabularnewline
110 & 0.275654 & 0.551307 & 0.724346 \tabularnewline
111 & 0.246304 & 0.492609 & 0.753696 \tabularnewline
112 & 0.239221 & 0.478443 & 0.760779 \tabularnewline
113 & 0.21731 & 0.43462 & 0.78269 \tabularnewline
114 & 0.198297 & 0.396594 & 0.801703 \tabularnewline
115 & 0.176089 & 0.352178 & 0.823911 \tabularnewline
116 & 0.154747 & 0.309494 & 0.845253 \tabularnewline
117 & 0.139443 & 0.278886 & 0.860557 \tabularnewline
118 & 0.180949 & 0.361898 & 0.819051 \tabularnewline
119 & 0.183622 & 0.367244 & 0.816378 \tabularnewline
120 & 0.162814 & 0.325627 & 0.837186 \tabularnewline
121 & 0.146252 & 0.292504 & 0.853748 \tabularnewline
122 & 0.129324 & 0.258648 & 0.870676 \tabularnewline
123 & 0.159553 & 0.319106 & 0.840447 \tabularnewline
124 & 0.144221 & 0.288442 & 0.855779 \tabularnewline
125 & 0.13669 & 0.273381 & 0.86331 \tabularnewline
126 & 0.129836 & 0.259671 & 0.870164 \tabularnewline
127 & 0.114589 & 0.229177 & 0.885411 \tabularnewline
128 & 0.10042 & 0.20084 & 0.89958 \tabularnewline
129 & 0.0854834 & 0.170967 & 0.914517 \tabularnewline
130 & 0.086785 & 0.17357 & 0.913215 \tabularnewline
131 & 0.0861056 & 0.172211 & 0.913894 \tabularnewline
132 & 0.0806525 & 0.161305 & 0.919347 \tabularnewline
133 & 0.0717235 & 0.143447 & 0.928276 \tabularnewline
134 & 0.0607862 & 0.121572 & 0.939214 \tabularnewline
135 & 0.0602362 & 0.120472 & 0.939764 \tabularnewline
136 & 0.115802 & 0.231605 & 0.884198 \tabularnewline
137 & 0.0995518 & 0.199104 & 0.900448 \tabularnewline
138 & 0.087619 & 0.175238 & 0.912381 \tabularnewline
139 & 0.0859066 & 0.171813 & 0.914093 \tabularnewline
140 & 0.0827519 & 0.165504 & 0.917248 \tabularnewline
141 & 0.0977627 & 0.195525 & 0.902237 \tabularnewline
142 & 0.0966731 & 0.193346 & 0.903327 \tabularnewline
143 & 0.082523 & 0.165046 & 0.917477 \tabularnewline
144 & 0.0697075 & 0.139415 & 0.930292 \tabularnewline
145 & 0.0590394 & 0.118079 & 0.940961 \tabularnewline
146 & 0.0492397 & 0.0984794 & 0.95076 \tabularnewline
147 & 0.0564601 & 0.11292 & 0.94354 \tabularnewline
148 & 0.0655848 & 0.13117 & 0.934415 \tabularnewline
149 & 0.0597292 & 0.119458 & 0.940271 \tabularnewline
150 & 0.0499609 & 0.0999218 & 0.950039 \tabularnewline
151 & 0.0583086 & 0.116617 & 0.941691 \tabularnewline
152 & 0.0578301 & 0.11566 & 0.94217 \tabularnewline
153 & 0.0591568 & 0.118314 & 0.940843 \tabularnewline
154 & 0.0549297 & 0.109859 & 0.94507 \tabularnewline
155 & 0.0584597 & 0.116919 & 0.94154 \tabularnewline
156 & 0.0493538 & 0.0987076 & 0.950646 \tabularnewline
157 & 0.0409253 & 0.0818507 & 0.959075 \tabularnewline
158 & 0.0341042 & 0.0682083 & 0.965896 \tabularnewline
159 & 0.0500855 & 0.100171 & 0.949915 \tabularnewline
160 & 0.0535826 & 0.107165 & 0.946417 \tabularnewline
161 & 0.0449082 & 0.0898165 & 0.955092 \tabularnewline
162 & 0.0908886 & 0.181777 & 0.909111 \tabularnewline
163 & 0.0821439 & 0.164288 & 0.917856 \tabularnewline
164 & 0.29186 & 0.58372 & 0.70814 \tabularnewline
165 & 0.268341 & 0.536682 & 0.731659 \tabularnewline
166 & 0.342952 & 0.685904 & 0.657048 \tabularnewline
167 & 0.324572 & 0.649145 & 0.675428 \tabularnewline
168 & 0.305259 & 0.610517 & 0.694741 \tabularnewline
169 & 0.276111 & 0.552222 & 0.723889 \tabularnewline
170 & 0.252775 & 0.505551 & 0.747225 \tabularnewline
171 & 0.249109 & 0.498218 & 0.750891 \tabularnewline
172 & 0.221751 & 0.443502 & 0.778249 \tabularnewline
173 & 0.276821 & 0.553642 & 0.723179 \tabularnewline
174 & 0.264489 & 0.528978 & 0.735511 \tabularnewline
175 & 0.246016 & 0.492033 & 0.753984 \tabularnewline
176 & 0.292466 & 0.584932 & 0.707534 \tabularnewline
177 & 0.274448 & 0.548895 & 0.725552 \tabularnewline
178 & 0.280349 & 0.560698 & 0.719651 \tabularnewline
179 & 0.278035 & 0.55607 & 0.721965 \tabularnewline
180 & 0.251613 & 0.503226 & 0.748387 \tabularnewline
181 & 0.286961 & 0.573923 & 0.713039 \tabularnewline
182 & 0.401033 & 0.802067 & 0.598967 \tabularnewline
183 & 0.390421 & 0.780843 & 0.609579 \tabularnewline
184 & 0.384687 & 0.769374 & 0.615313 \tabularnewline
185 & 0.370422 & 0.740845 & 0.629578 \tabularnewline
186 & 0.486351 & 0.972703 & 0.513649 \tabularnewline
187 & 0.451265 & 0.90253 & 0.548735 \tabularnewline
188 & 0.4192 & 0.8384 & 0.5808 \tabularnewline
189 & 0.386308 & 0.772615 & 0.613692 \tabularnewline
190 & 0.417993 & 0.835986 & 0.582007 \tabularnewline
191 & 0.449717 & 0.899434 & 0.550283 \tabularnewline
192 & 0.471167 & 0.942335 & 0.528833 \tabularnewline
193 & 0.460163 & 0.920326 & 0.539837 \tabularnewline
194 & 0.429891 & 0.859781 & 0.570109 \tabularnewline
195 & 0.401284 & 0.802569 & 0.598716 \tabularnewline
196 & 0.440521 & 0.881041 & 0.559479 \tabularnewline
197 & 0.641438 & 0.717123 & 0.358562 \tabularnewline
198 & 0.646747 & 0.706507 & 0.353253 \tabularnewline
199 & 0.606298 & 0.787405 & 0.393702 \tabularnewline
200 & 0.565457 & 0.869086 & 0.434543 \tabularnewline
201 & 0.524217 & 0.951567 & 0.475783 \tabularnewline
202 & 0.484409 & 0.968818 & 0.515591 \tabularnewline
203 & 0.459921 & 0.919842 & 0.540079 \tabularnewline
204 & 0.458302 & 0.916603 & 0.541698 \tabularnewline
205 & 0.423964 & 0.847928 & 0.576036 \tabularnewline
206 & 0.381636 & 0.763272 & 0.618364 \tabularnewline
207 & 0.343627 & 0.687254 & 0.656373 \tabularnewline
208 & 0.307572 & 0.615145 & 0.692428 \tabularnewline
209 & 0.270194 & 0.540389 & 0.729806 \tabularnewline
210 & 0.262679 & 0.525357 & 0.737321 \tabularnewline
211 & 0.239578 & 0.479156 & 0.760422 \tabularnewline
212 & 0.208986 & 0.417973 & 0.791014 \tabularnewline
213 & 0.231363 & 0.462726 & 0.768637 \tabularnewline
214 & 0.21739 & 0.434781 & 0.78261 \tabularnewline
215 & 0.186391 & 0.372782 & 0.813609 \tabularnewline
216 & 0.15861 & 0.31722 & 0.84139 \tabularnewline
217 & 0.149495 & 0.298991 & 0.850505 \tabularnewline
218 & 0.124836 & 0.249672 & 0.875164 \tabularnewline
219 & 0.125646 & 0.251293 & 0.874354 \tabularnewline
220 & 0.117523 & 0.235046 & 0.882477 \tabularnewline
221 & 0.117979 & 0.235959 & 0.882021 \tabularnewline
222 & 0.0958272 & 0.191654 & 0.904173 \tabularnewline
223 & 0.077118 & 0.154236 & 0.922882 \tabularnewline
224 & 0.0792093 & 0.158419 & 0.920791 \tabularnewline
225 & 0.0704345 & 0.140869 & 0.929565 \tabularnewline
226 & 0.056641 & 0.113282 & 0.943359 \tabularnewline
227 & 0.0432348 & 0.0864695 & 0.956765 \tabularnewline
228 & 0.0406884 & 0.0813767 & 0.959312 \tabularnewline
229 & 0.0553936 & 0.110787 & 0.944606 \tabularnewline
230 & 0.0528409 & 0.105682 & 0.947159 \tabularnewline
231 & 0.0400653 & 0.0801306 & 0.959935 \tabularnewline
232 & 0.0412058 & 0.0824117 & 0.958794 \tabularnewline
233 & 0.0915908 & 0.183182 & 0.908409 \tabularnewline
234 & 0.095832 & 0.191664 & 0.904168 \tabularnewline
235 & 0.0912093 & 0.182419 & 0.908791 \tabularnewline
236 & 0.0695999 & 0.1392 & 0.9304 \tabularnewline
237 & 0.0916743 & 0.183349 & 0.908326 \tabularnewline
238 & 0.128088 & 0.256176 & 0.871912 \tabularnewline
239 & 0.215292 & 0.430583 & 0.784708 \tabularnewline
240 & 0.21302 & 0.42604 & 0.78698 \tabularnewline
241 & 0.172274 & 0.344548 & 0.827726 \tabularnewline
242 & 0.211401 & 0.422803 & 0.788599 \tabularnewline
243 & 0.158977 & 0.317955 & 0.841023 \tabularnewline
244 & 0.114321 & 0.228641 & 0.885679 \tabularnewline
245 & 0.173452 & 0.346904 & 0.826548 \tabularnewline
246 & 0.187951 & 0.375901 & 0.812049 \tabularnewline
247 & 0.131371 & 0.262743 & 0.868629 \tabularnewline
248 & 0.161308 & 0.322615 & 0.838692 \tabularnewline
249 & 0.244238 & 0.488476 & 0.755762 \tabularnewline
250 & 0.160752 & 0.321503 & 0.839248 \tabularnewline
251 & 0.175682 & 0.351364 & 0.824318 \tabularnewline
252 & 0.79882 & 0.402359 & 0.20118 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226596&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]12[/C][C]0.978835[/C][C]0.0423295[/C][C]0.0211648[/C][/ROW]
[ROW][C]13[/C][C]0.973288[/C][C]0.0534242[/C][C]0.0267121[/C][/ROW]
[ROW][C]14[/C][C]0.979629[/C][C]0.0407423[/C][C]0.0203712[/C][/ROW]
[ROW][C]15[/C][C]0.964549[/C][C]0.0709016[/C][C]0.0354508[/C][/ROW]
[ROW][C]16[/C][C]0.940712[/C][C]0.118576[/C][C]0.0592879[/C][/ROW]
[ROW][C]17[/C][C]0.971567[/C][C]0.0568654[/C][C]0.0284327[/C][/ROW]
[ROW][C]18[/C][C]0.959427[/C][C]0.0811469[/C][C]0.0405735[/C][/ROW]
[ROW][C]19[/C][C]0.974727[/C][C]0.0505469[/C][C]0.0252734[/C][/ROW]
[ROW][C]20[/C][C]0.96143[/C][C]0.0771395[/C][C]0.0385698[/C][/ROW]
[ROW][C]21[/C][C]0.953136[/C][C]0.0937285[/C][C]0.0468642[/C][/ROW]
[ROW][C]22[/C][C]0.948905[/C][C]0.10219[/C][C]0.0510952[/C][/ROW]
[ROW][C]23[/C][C]0.928091[/C][C]0.143818[/C][C]0.0719091[/C][/ROW]
[ROW][C]24[/C][C]0.912297[/C][C]0.175406[/C][C]0.0877029[/C][/ROW]
[ROW][C]25[/C][C]0.881943[/C][C]0.236114[/C][C]0.118057[/C][/ROW]
[ROW][C]26[/C][C]0.879561[/C][C]0.240878[/C][C]0.120439[/C][/ROW]
[ROW][C]27[/C][C]0.887944[/C][C]0.224113[/C][C]0.112056[/C][/ROW]
[ROW][C]28[/C][C]0.855289[/C][C]0.289422[/C][C]0.144711[/C][/ROW]
[ROW][C]29[/C][C]0.881725[/C][C]0.236549[/C][C]0.118275[/C][/ROW]
[ROW][C]30[/C][C]0.871818[/C][C]0.256364[/C][C]0.128182[/C][/ROW]
[ROW][C]31[/C][C]0.875165[/C][C]0.24967[/C][C]0.124835[/C][/ROW]
[ROW][C]32[/C][C]0.848252[/C][C]0.303496[/C][C]0.151748[/C][/ROW]
[ROW][C]33[/C][C]0.820734[/C][C]0.358531[/C][C]0.179266[/C][/ROW]
[ROW][C]34[/C][C]0.798259[/C][C]0.403482[/C][C]0.201741[/C][/ROW]
[ROW][C]35[/C][C]0.768448[/C][C]0.463103[/C][C]0.231552[/C][/ROW]
[ROW][C]36[/C][C]0.795031[/C][C]0.409937[/C][C]0.204969[/C][/ROW]
[ROW][C]37[/C][C]0.867923[/C][C]0.264154[/C][C]0.132077[/C][/ROW]
[ROW][C]38[/C][C]0.837331[/C][C]0.325337[/C][C]0.162669[/C][/ROW]
[ROW][C]39[/C][C]0.806924[/C][C]0.386152[/C][C]0.193076[/C][/ROW]
[ROW][C]40[/C][C]0.803365[/C][C]0.39327[/C][C]0.196635[/C][/ROW]
[ROW][C]41[/C][C]0.790377[/C][C]0.419246[/C][C]0.209623[/C][/ROW]
[ROW][C]42[/C][C]0.780056[/C][C]0.439888[/C][C]0.219944[/C][/ROW]
[ROW][C]43[/C][C]0.825386[/C][C]0.349228[/C][C]0.174614[/C][/ROW]
[ROW][C]44[/C][C]0.792011[/C][C]0.415979[/C][C]0.207989[/C][/ROW]
[ROW][C]45[/C][C]0.757145[/C][C]0.485711[/C][C]0.242855[/C][/ROW]
[ROW][C]46[/C][C]0.730636[/C][C]0.538728[/C][C]0.269364[/C][/ROW]
[ROW][C]47[/C][C]0.779726[/C][C]0.440548[/C][C]0.220274[/C][/ROW]
[ROW][C]48[/C][C]0.74699[/C][C]0.50602[/C][C]0.25301[/C][/ROW]
[ROW][C]49[/C][C]0.799299[/C][C]0.401402[/C][C]0.200701[/C][/ROW]
[ROW][C]50[/C][C]0.773435[/C][C]0.45313[/C][C]0.226565[/C][/ROW]
[ROW][C]51[/C][C]0.760938[/C][C]0.478124[/C][C]0.239062[/C][/ROW]
[ROW][C]52[/C][C]0.728791[/C][C]0.542417[/C][C]0.271209[/C][/ROW]
[ROW][C]53[/C][C]0.732885[/C][C]0.53423[/C][C]0.267115[/C][/ROW]
[ROW][C]54[/C][C]0.69965[/C][C]0.600699[/C][C]0.30035[/C][/ROW]
[ROW][C]55[/C][C]0.706192[/C][C]0.587617[/C][C]0.293808[/C][/ROW]
[ROW][C]56[/C][C]0.722457[/C][C]0.555086[/C][C]0.277543[/C][/ROW]
[ROW][C]57[/C][C]0.702018[/C][C]0.595963[/C][C]0.297982[/C][/ROW]
[ROW][C]58[/C][C]0.733631[/C][C]0.532739[/C][C]0.266369[/C][/ROW]
[ROW][C]59[/C][C]0.745242[/C][C]0.509515[/C][C]0.254758[/C][/ROW]
[ROW][C]60[/C][C]0.722694[/C][C]0.554611[/C][C]0.277306[/C][/ROW]
[ROW][C]61[/C][C]0.734333[/C][C]0.531333[/C][C]0.265667[/C][/ROW]
[ROW][C]62[/C][C]0.698362[/C][C]0.603275[/C][C]0.301638[/C][/ROW]
[ROW][C]63[/C][C]0.674012[/C][C]0.651977[/C][C]0.325988[/C][/ROW]
[ROW][C]64[/C][C]0.634461[/C][C]0.731079[/C][C]0.365539[/C][/ROW]
[ROW][C]65[/C][C]0.593783[/C][C]0.812433[/C][C]0.406217[/C][/ROW]
[ROW][C]66[/C][C]0.58125[/C][C]0.8375[/C][C]0.41875[/C][/ROW]
[ROW][C]67[/C][C]0.604219[/C][C]0.791562[/C][C]0.395781[/C][/ROW]
[ROW][C]68[/C][C]0.575608[/C][C]0.848785[/C][C]0.424392[/C][/ROW]
[ROW][C]69[/C][C]0.534828[/C][C]0.930344[/C][C]0.465172[/C][/ROW]
[ROW][C]70[/C][C]0.50641[/C][C]0.98718[/C][C]0.49359[/C][/ROW]
[ROW][C]71[/C][C]0.468599[/C][C]0.937198[/C][C]0.531401[/C][/ROW]
[ROW][C]72[/C][C]0.43924[/C][C]0.87848[/C][C]0.56076[/C][/ROW]
[ROW][C]73[/C][C]0.406815[/C][C]0.813631[/C][C]0.593185[/C][/ROW]
[ROW][C]74[/C][C]0.391305[/C][C]0.782611[/C][C]0.608695[/C][/ROW]
[ROW][C]75[/C][C]0.364456[/C][C]0.728911[/C][C]0.635544[/C][/ROW]
[ROW][C]76[/C][C]0.497684[/C][C]0.995367[/C][C]0.502316[/C][/ROW]
[ROW][C]77[/C][C]0.466661[/C][C]0.933321[/C][C]0.533339[/C][/ROW]
[ROW][C]78[/C][C]0.458593[/C][C]0.917185[/C][C]0.541407[/C][/ROW]
[ROW][C]79[/C][C]0.420549[/C][C]0.841099[/C][C]0.579451[/C][/ROW]
[ROW][C]80[/C][C]0.554214[/C][C]0.891571[/C][C]0.445786[/C][/ROW]
[ROW][C]81[/C][C]0.521114[/C][C]0.957772[/C][C]0.478886[/C][/ROW]
[ROW][C]82[/C][C]0.55778[/C][C]0.884441[/C][C]0.44222[/C][/ROW]
[ROW][C]83[/C][C]0.519526[/C][C]0.960947[/C][C]0.480474[/C][/ROW]
[ROW][C]84[/C][C]0.482973[/C][C]0.965945[/C][C]0.517027[/C][/ROW]
[ROW][C]85[/C][C]0.444004[/C][C]0.888009[/C][C]0.555996[/C][/ROW]
[ROW][C]86[/C][C]0.408029[/C][C]0.816058[/C][C]0.591971[/C][/ROW]
[ROW][C]87[/C][C]0.378158[/C][C]0.756317[/C][C]0.621842[/C][/ROW]
[ROW][C]88[/C][C]0.343202[/C][C]0.686403[/C][C]0.656798[/C][/ROW]
[ROW][C]89[/C][C]0.420144[/C][C]0.840288[/C][C]0.579856[/C][/ROW]
[ROW][C]90[/C][C]0.387634[/C][C]0.775268[/C][C]0.612366[/C][/ROW]
[ROW][C]91[/C][C]0.354886[/C][C]0.709773[/C][C]0.645114[/C][/ROW]
[ROW][C]92[/C][C]0.322792[/C][C]0.645584[/C][C]0.677208[/C][/ROW]
[ROW][C]93[/C][C]0.314629[/C][C]0.629259[/C][C]0.685371[/C][/ROW]
[ROW][C]94[/C][C]0.287244[/C][C]0.574489[/C][C]0.712756[/C][/ROW]
[ROW][C]95[/C][C]0.25619[/C][C]0.512381[/C][C]0.74381[/C][/ROW]
[ROW][C]96[/C][C]0.235359[/C][C]0.470718[/C][C]0.764641[/C][/ROW]
[ROW][C]97[/C][C]0.218125[/C][C]0.436251[/C][C]0.781875[/C][/ROW]
[ROW][C]98[/C][C]0.192324[/C][C]0.384648[/C][C]0.807676[/C][/ROW]
[ROW][C]99[/C][C]0.190141[/C][C]0.380282[/C][C]0.809859[/C][/ROW]
[ROW][C]100[/C][C]0.16748[/C][C]0.33496[/C][C]0.83252[/C][/ROW]
[ROW][C]101[/C][C]0.153729[/C][C]0.307458[/C][C]0.846271[/C][/ROW]
[ROW][C]102[/C][C]0.135692[/C][C]0.271384[/C][C]0.864308[/C][/ROW]
[ROW][C]103[/C][C]0.181909[/C][C]0.363818[/C][C]0.818091[/C][/ROW]
[ROW][C]104[/C][C]0.206483[/C][C]0.412966[/C][C]0.793517[/C][/ROW]
[ROW][C]105[/C][C]0.207653[/C][C]0.415306[/C][C]0.792347[/C][/ROW]
[ROW][C]106[/C][C]0.183495[/C][C]0.366989[/C][C]0.816505[/C][/ROW]
[ROW][C]107[/C][C]0.19987[/C][C]0.399741[/C][C]0.80013[/C][/ROW]
[ROW][C]108[/C][C]0.18649[/C][C]0.372979[/C][C]0.81351[/C][/ROW]
[ROW][C]109[/C][C]0.288492[/C][C]0.576985[/C][C]0.711508[/C][/ROW]
[ROW][C]110[/C][C]0.275654[/C][C]0.551307[/C][C]0.724346[/C][/ROW]
[ROW][C]111[/C][C]0.246304[/C][C]0.492609[/C][C]0.753696[/C][/ROW]
[ROW][C]112[/C][C]0.239221[/C][C]0.478443[/C][C]0.760779[/C][/ROW]
[ROW][C]113[/C][C]0.21731[/C][C]0.43462[/C][C]0.78269[/C][/ROW]
[ROW][C]114[/C][C]0.198297[/C][C]0.396594[/C][C]0.801703[/C][/ROW]
[ROW][C]115[/C][C]0.176089[/C][C]0.352178[/C][C]0.823911[/C][/ROW]
[ROW][C]116[/C][C]0.154747[/C][C]0.309494[/C][C]0.845253[/C][/ROW]
[ROW][C]117[/C][C]0.139443[/C][C]0.278886[/C][C]0.860557[/C][/ROW]
[ROW][C]118[/C][C]0.180949[/C][C]0.361898[/C][C]0.819051[/C][/ROW]
[ROW][C]119[/C][C]0.183622[/C][C]0.367244[/C][C]0.816378[/C][/ROW]
[ROW][C]120[/C][C]0.162814[/C][C]0.325627[/C][C]0.837186[/C][/ROW]
[ROW][C]121[/C][C]0.146252[/C][C]0.292504[/C][C]0.853748[/C][/ROW]
[ROW][C]122[/C][C]0.129324[/C][C]0.258648[/C][C]0.870676[/C][/ROW]
[ROW][C]123[/C][C]0.159553[/C][C]0.319106[/C][C]0.840447[/C][/ROW]
[ROW][C]124[/C][C]0.144221[/C][C]0.288442[/C][C]0.855779[/C][/ROW]
[ROW][C]125[/C][C]0.13669[/C][C]0.273381[/C][C]0.86331[/C][/ROW]
[ROW][C]126[/C][C]0.129836[/C][C]0.259671[/C][C]0.870164[/C][/ROW]
[ROW][C]127[/C][C]0.114589[/C][C]0.229177[/C][C]0.885411[/C][/ROW]
[ROW][C]128[/C][C]0.10042[/C][C]0.20084[/C][C]0.89958[/C][/ROW]
[ROW][C]129[/C][C]0.0854834[/C][C]0.170967[/C][C]0.914517[/C][/ROW]
[ROW][C]130[/C][C]0.086785[/C][C]0.17357[/C][C]0.913215[/C][/ROW]
[ROW][C]131[/C][C]0.0861056[/C][C]0.172211[/C][C]0.913894[/C][/ROW]
[ROW][C]132[/C][C]0.0806525[/C][C]0.161305[/C][C]0.919347[/C][/ROW]
[ROW][C]133[/C][C]0.0717235[/C][C]0.143447[/C][C]0.928276[/C][/ROW]
[ROW][C]134[/C][C]0.0607862[/C][C]0.121572[/C][C]0.939214[/C][/ROW]
[ROW][C]135[/C][C]0.0602362[/C][C]0.120472[/C][C]0.939764[/C][/ROW]
[ROW][C]136[/C][C]0.115802[/C][C]0.231605[/C][C]0.884198[/C][/ROW]
[ROW][C]137[/C][C]0.0995518[/C][C]0.199104[/C][C]0.900448[/C][/ROW]
[ROW][C]138[/C][C]0.087619[/C][C]0.175238[/C][C]0.912381[/C][/ROW]
[ROW][C]139[/C][C]0.0859066[/C][C]0.171813[/C][C]0.914093[/C][/ROW]
[ROW][C]140[/C][C]0.0827519[/C][C]0.165504[/C][C]0.917248[/C][/ROW]
[ROW][C]141[/C][C]0.0977627[/C][C]0.195525[/C][C]0.902237[/C][/ROW]
[ROW][C]142[/C][C]0.0966731[/C][C]0.193346[/C][C]0.903327[/C][/ROW]
[ROW][C]143[/C][C]0.082523[/C][C]0.165046[/C][C]0.917477[/C][/ROW]
[ROW][C]144[/C][C]0.0697075[/C][C]0.139415[/C][C]0.930292[/C][/ROW]
[ROW][C]145[/C][C]0.0590394[/C][C]0.118079[/C][C]0.940961[/C][/ROW]
[ROW][C]146[/C][C]0.0492397[/C][C]0.0984794[/C][C]0.95076[/C][/ROW]
[ROW][C]147[/C][C]0.0564601[/C][C]0.11292[/C][C]0.94354[/C][/ROW]
[ROW][C]148[/C][C]0.0655848[/C][C]0.13117[/C][C]0.934415[/C][/ROW]
[ROW][C]149[/C][C]0.0597292[/C][C]0.119458[/C][C]0.940271[/C][/ROW]
[ROW][C]150[/C][C]0.0499609[/C][C]0.0999218[/C][C]0.950039[/C][/ROW]
[ROW][C]151[/C][C]0.0583086[/C][C]0.116617[/C][C]0.941691[/C][/ROW]
[ROW][C]152[/C][C]0.0578301[/C][C]0.11566[/C][C]0.94217[/C][/ROW]
[ROW][C]153[/C][C]0.0591568[/C][C]0.118314[/C][C]0.940843[/C][/ROW]
[ROW][C]154[/C][C]0.0549297[/C][C]0.109859[/C][C]0.94507[/C][/ROW]
[ROW][C]155[/C][C]0.0584597[/C][C]0.116919[/C][C]0.94154[/C][/ROW]
[ROW][C]156[/C][C]0.0493538[/C][C]0.0987076[/C][C]0.950646[/C][/ROW]
[ROW][C]157[/C][C]0.0409253[/C][C]0.0818507[/C][C]0.959075[/C][/ROW]
[ROW][C]158[/C][C]0.0341042[/C][C]0.0682083[/C][C]0.965896[/C][/ROW]
[ROW][C]159[/C][C]0.0500855[/C][C]0.100171[/C][C]0.949915[/C][/ROW]
[ROW][C]160[/C][C]0.0535826[/C][C]0.107165[/C][C]0.946417[/C][/ROW]
[ROW][C]161[/C][C]0.0449082[/C][C]0.0898165[/C][C]0.955092[/C][/ROW]
[ROW][C]162[/C][C]0.0908886[/C][C]0.181777[/C][C]0.909111[/C][/ROW]
[ROW][C]163[/C][C]0.0821439[/C][C]0.164288[/C][C]0.917856[/C][/ROW]
[ROW][C]164[/C][C]0.29186[/C][C]0.58372[/C][C]0.70814[/C][/ROW]
[ROW][C]165[/C][C]0.268341[/C][C]0.536682[/C][C]0.731659[/C][/ROW]
[ROW][C]166[/C][C]0.342952[/C][C]0.685904[/C][C]0.657048[/C][/ROW]
[ROW][C]167[/C][C]0.324572[/C][C]0.649145[/C][C]0.675428[/C][/ROW]
[ROW][C]168[/C][C]0.305259[/C][C]0.610517[/C][C]0.694741[/C][/ROW]
[ROW][C]169[/C][C]0.276111[/C][C]0.552222[/C][C]0.723889[/C][/ROW]
[ROW][C]170[/C][C]0.252775[/C][C]0.505551[/C][C]0.747225[/C][/ROW]
[ROW][C]171[/C][C]0.249109[/C][C]0.498218[/C][C]0.750891[/C][/ROW]
[ROW][C]172[/C][C]0.221751[/C][C]0.443502[/C][C]0.778249[/C][/ROW]
[ROW][C]173[/C][C]0.276821[/C][C]0.553642[/C][C]0.723179[/C][/ROW]
[ROW][C]174[/C][C]0.264489[/C][C]0.528978[/C][C]0.735511[/C][/ROW]
[ROW][C]175[/C][C]0.246016[/C][C]0.492033[/C][C]0.753984[/C][/ROW]
[ROW][C]176[/C][C]0.292466[/C][C]0.584932[/C][C]0.707534[/C][/ROW]
[ROW][C]177[/C][C]0.274448[/C][C]0.548895[/C][C]0.725552[/C][/ROW]
[ROW][C]178[/C][C]0.280349[/C][C]0.560698[/C][C]0.719651[/C][/ROW]
[ROW][C]179[/C][C]0.278035[/C][C]0.55607[/C][C]0.721965[/C][/ROW]
[ROW][C]180[/C][C]0.251613[/C][C]0.503226[/C][C]0.748387[/C][/ROW]
[ROW][C]181[/C][C]0.286961[/C][C]0.573923[/C][C]0.713039[/C][/ROW]
[ROW][C]182[/C][C]0.401033[/C][C]0.802067[/C][C]0.598967[/C][/ROW]
[ROW][C]183[/C][C]0.390421[/C][C]0.780843[/C][C]0.609579[/C][/ROW]
[ROW][C]184[/C][C]0.384687[/C][C]0.769374[/C][C]0.615313[/C][/ROW]
[ROW][C]185[/C][C]0.370422[/C][C]0.740845[/C][C]0.629578[/C][/ROW]
[ROW][C]186[/C][C]0.486351[/C][C]0.972703[/C][C]0.513649[/C][/ROW]
[ROW][C]187[/C][C]0.451265[/C][C]0.90253[/C][C]0.548735[/C][/ROW]
[ROW][C]188[/C][C]0.4192[/C][C]0.8384[/C][C]0.5808[/C][/ROW]
[ROW][C]189[/C][C]0.386308[/C][C]0.772615[/C][C]0.613692[/C][/ROW]
[ROW][C]190[/C][C]0.417993[/C][C]0.835986[/C][C]0.582007[/C][/ROW]
[ROW][C]191[/C][C]0.449717[/C][C]0.899434[/C][C]0.550283[/C][/ROW]
[ROW][C]192[/C][C]0.471167[/C][C]0.942335[/C][C]0.528833[/C][/ROW]
[ROW][C]193[/C][C]0.460163[/C][C]0.920326[/C][C]0.539837[/C][/ROW]
[ROW][C]194[/C][C]0.429891[/C][C]0.859781[/C][C]0.570109[/C][/ROW]
[ROW][C]195[/C][C]0.401284[/C][C]0.802569[/C][C]0.598716[/C][/ROW]
[ROW][C]196[/C][C]0.440521[/C][C]0.881041[/C][C]0.559479[/C][/ROW]
[ROW][C]197[/C][C]0.641438[/C][C]0.717123[/C][C]0.358562[/C][/ROW]
[ROW][C]198[/C][C]0.646747[/C][C]0.706507[/C][C]0.353253[/C][/ROW]
[ROW][C]199[/C][C]0.606298[/C][C]0.787405[/C][C]0.393702[/C][/ROW]
[ROW][C]200[/C][C]0.565457[/C][C]0.869086[/C][C]0.434543[/C][/ROW]
[ROW][C]201[/C][C]0.524217[/C][C]0.951567[/C][C]0.475783[/C][/ROW]
[ROW][C]202[/C][C]0.484409[/C][C]0.968818[/C][C]0.515591[/C][/ROW]
[ROW][C]203[/C][C]0.459921[/C][C]0.919842[/C][C]0.540079[/C][/ROW]
[ROW][C]204[/C][C]0.458302[/C][C]0.916603[/C][C]0.541698[/C][/ROW]
[ROW][C]205[/C][C]0.423964[/C][C]0.847928[/C][C]0.576036[/C][/ROW]
[ROW][C]206[/C][C]0.381636[/C][C]0.763272[/C][C]0.618364[/C][/ROW]
[ROW][C]207[/C][C]0.343627[/C][C]0.687254[/C][C]0.656373[/C][/ROW]
[ROW][C]208[/C][C]0.307572[/C][C]0.615145[/C][C]0.692428[/C][/ROW]
[ROW][C]209[/C][C]0.270194[/C][C]0.540389[/C][C]0.729806[/C][/ROW]
[ROW][C]210[/C][C]0.262679[/C][C]0.525357[/C][C]0.737321[/C][/ROW]
[ROW][C]211[/C][C]0.239578[/C][C]0.479156[/C][C]0.760422[/C][/ROW]
[ROW][C]212[/C][C]0.208986[/C][C]0.417973[/C][C]0.791014[/C][/ROW]
[ROW][C]213[/C][C]0.231363[/C][C]0.462726[/C][C]0.768637[/C][/ROW]
[ROW][C]214[/C][C]0.21739[/C][C]0.434781[/C][C]0.78261[/C][/ROW]
[ROW][C]215[/C][C]0.186391[/C][C]0.372782[/C][C]0.813609[/C][/ROW]
[ROW][C]216[/C][C]0.15861[/C][C]0.31722[/C][C]0.84139[/C][/ROW]
[ROW][C]217[/C][C]0.149495[/C][C]0.298991[/C][C]0.850505[/C][/ROW]
[ROW][C]218[/C][C]0.124836[/C][C]0.249672[/C][C]0.875164[/C][/ROW]
[ROW][C]219[/C][C]0.125646[/C][C]0.251293[/C][C]0.874354[/C][/ROW]
[ROW][C]220[/C][C]0.117523[/C][C]0.235046[/C][C]0.882477[/C][/ROW]
[ROW][C]221[/C][C]0.117979[/C][C]0.235959[/C][C]0.882021[/C][/ROW]
[ROW][C]222[/C][C]0.0958272[/C][C]0.191654[/C][C]0.904173[/C][/ROW]
[ROW][C]223[/C][C]0.077118[/C][C]0.154236[/C][C]0.922882[/C][/ROW]
[ROW][C]224[/C][C]0.0792093[/C][C]0.158419[/C][C]0.920791[/C][/ROW]
[ROW][C]225[/C][C]0.0704345[/C][C]0.140869[/C][C]0.929565[/C][/ROW]
[ROW][C]226[/C][C]0.056641[/C][C]0.113282[/C][C]0.943359[/C][/ROW]
[ROW][C]227[/C][C]0.0432348[/C][C]0.0864695[/C][C]0.956765[/C][/ROW]
[ROW][C]228[/C][C]0.0406884[/C][C]0.0813767[/C][C]0.959312[/C][/ROW]
[ROW][C]229[/C][C]0.0553936[/C][C]0.110787[/C][C]0.944606[/C][/ROW]
[ROW][C]230[/C][C]0.0528409[/C][C]0.105682[/C][C]0.947159[/C][/ROW]
[ROW][C]231[/C][C]0.0400653[/C][C]0.0801306[/C][C]0.959935[/C][/ROW]
[ROW][C]232[/C][C]0.0412058[/C][C]0.0824117[/C][C]0.958794[/C][/ROW]
[ROW][C]233[/C][C]0.0915908[/C][C]0.183182[/C][C]0.908409[/C][/ROW]
[ROW][C]234[/C][C]0.095832[/C][C]0.191664[/C][C]0.904168[/C][/ROW]
[ROW][C]235[/C][C]0.0912093[/C][C]0.182419[/C][C]0.908791[/C][/ROW]
[ROW][C]236[/C][C]0.0695999[/C][C]0.1392[/C][C]0.9304[/C][/ROW]
[ROW][C]237[/C][C]0.0916743[/C][C]0.183349[/C][C]0.908326[/C][/ROW]
[ROW][C]238[/C][C]0.128088[/C][C]0.256176[/C][C]0.871912[/C][/ROW]
[ROW][C]239[/C][C]0.215292[/C][C]0.430583[/C][C]0.784708[/C][/ROW]
[ROW][C]240[/C][C]0.21302[/C][C]0.42604[/C][C]0.78698[/C][/ROW]
[ROW][C]241[/C][C]0.172274[/C][C]0.344548[/C][C]0.827726[/C][/ROW]
[ROW][C]242[/C][C]0.211401[/C][C]0.422803[/C][C]0.788599[/C][/ROW]
[ROW][C]243[/C][C]0.158977[/C][C]0.317955[/C][C]0.841023[/C][/ROW]
[ROW][C]244[/C][C]0.114321[/C][C]0.228641[/C][C]0.885679[/C][/ROW]
[ROW][C]245[/C][C]0.173452[/C][C]0.346904[/C][C]0.826548[/C][/ROW]
[ROW][C]246[/C][C]0.187951[/C][C]0.375901[/C][C]0.812049[/C][/ROW]
[ROW][C]247[/C][C]0.131371[/C][C]0.262743[/C][C]0.868629[/C][/ROW]
[ROW][C]248[/C][C]0.161308[/C][C]0.322615[/C][C]0.838692[/C][/ROW]
[ROW][C]249[/C][C]0.244238[/C][C]0.488476[/C][C]0.755762[/C][/ROW]
[ROW][C]250[/C][C]0.160752[/C][C]0.321503[/C][C]0.839248[/C][/ROW]
[ROW][C]251[/C][C]0.175682[/C][C]0.351364[/C][C]0.824318[/C][/ROW]
[ROW][C]252[/C][C]0.79882[/C][C]0.402359[/C][C]0.20118[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226596&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226596&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
120.9788350.04232950.0211648
130.9732880.05342420.0267121
140.9796290.04074230.0203712
150.9645490.07090160.0354508
160.9407120.1185760.0592879
170.9715670.05686540.0284327
180.9594270.08114690.0405735
190.9747270.05054690.0252734
200.961430.07713950.0385698
210.9531360.09372850.0468642
220.9489050.102190.0510952
230.9280910.1438180.0719091
240.9122970.1754060.0877029
250.8819430.2361140.118057
260.8795610.2408780.120439
270.8879440.2241130.112056
280.8552890.2894220.144711
290.8817250.2365490.118275
300.8718180.2563640.128182
310.8751650.249670.124835
320.8482520.3034960.151748
330.8207340.3585310.179266
340.7982590.4034820.201741
350.7684480.4631030.231552
360.7950310.4099370.204969
370.8679230.2641540.132077
380.8373310.3253370.162669
390.8069240.3861520.193076
400.8033650.393270.196635
410.7903770.4192460.209623
420.7800560.4398880.219944
430.8253860.3492280.174614
440.7920110.4159790.207989
450.7571450.4857110.242855
460.7306360.5387280.269364
470.7797260.4405480.220274
480.746990.506020.25301
490.7992990.4014020.200701
500.7734350.453130.226565
510.7609380.4781240.239062
520.7287910.5424170.271209
530.7328850.534230.267115
540.699650.6006990.30035
550.7061920.5876170.293808
560.7224570.5550860.277543
570.7020180.5959630.297982
580.7336310.5327390.266369
590.7452420.5095150.254758
600.7226940.5546110.277306
610.7343330.5313330.265667
620.6983620.6032750.301638
630.6740120.6519770.325988
640.6344610.7310790.365539
650.5937830.8124330.406217
660.581250.83750.41875
670.6042190.7915620.395781
680.5756080.8487850.424392
690.5348280.9303440.465172
700.506410.987180.49359
710.4685990.9371980.531401
720.439240.878480.56076
730.4068150.8136310.593185
740.3913050.7826110.608695
750.3644560.7289110.635544
760.4976840.9953670.502316
770.4666610.9333210.533339
780.4585930.9171850.541407
790.4205490.8410990.579451
800.5542140.8915710.445786
810.5211140.9577720.478886
820.557780.8844410.44222
830.5195260.9609470.480474
840.4829730.9659450.517027
850.4440040.8880090.555996
860.4080290.8160580.591971
870.3781580.7563170.621842
880.3432020.6864030.656798
890.4201440.8402880.579856
900.3876340.7752680.612366
910.3548860.7097730.645114
920.3227920.6455840.677208
930.3146290.6292590.685371
940.2872440.5744890.712756
950.256190.5123810.74381
960.2353590.4707180.764641
970.2181250.4362510.781875
980.1923240.3846480.807676
990.1901410.3802820.809859
1000.167480.334960.83252
1010.1537290.3074580.846271
1020.1356920.2713840.864308
1030.1819090.3638180.818091
1040.2064830.4129660.793517
1050.2076530.4153060.792347
1060.1834950.3669890.816505
1070.199870.3997410.80013
1080.186490.3729790.81351
1090.2884920.5769850.711508
1100.2756540.5513070.724346
1110.2463040.4926090.753696
1120.2392210.4784430.760779
1130.217310.434620.78269
1140.1982970.3965940.801703
1150.1760890.3521780.823911
1160.1547470.3094940.845253
1170.1394430.2788860.860557
1180.1809490.3618980.819051
1190.1836220.3672440.816378
1200.1628140.3256270.837186
1210.1462520.2925040.853748
1220.1293240.2586480.870676
1230.1595530.3191060.840447
1240.1442210.2884420.855779
1250.136690.2733810.86331
1260.1298360.2596710.870164
1270.1145890.2291770.885411
1280.100420.200840.89958
1290.08548340.1709670.914517
1300.0867850.173570.913215
1310.08610560.1722110.913894
1320.08065250.1613050.919347
1330.07172350.1434470.928276
1340.06078620.1215720.939214
1350.06023620.1204720.939764
1360.1158020.2316050.884198
1370.09955180.1991040.900448
1380.0876190.1752380.912381
1390.08590660.1718130.914093
1400.08275190.1655040.917248
1410.09776270.1955250.902237
1420.09667310.1933460.903327
1430.0825230.1650460.917477
1440.06970750.1394150.930292
1450.05903940.1180790.940961
1460.04923970.09847940.95076
1470.05646010.112920.94354
1480.06558480.131170.934415
1490.05972920.1194580.940271
1500.04996090.09992180.950039
1510.05830860.1166170.941691
1520.05783010.115660.94217
1530.05915680.1183140.940843
1540.05492970.1098590.94507
1550.05845970.1169190.94154
1560.04935380.09870760.950646
1570.04092530.08185070.959075
1580.03410420.06820830.965896
1590.05008550.1001710.949915
1600.05358260.1071650.946417
1610.04490820.08981650.955092
1620.09088860.1817770.909111
1630.08214390.1642880.917856
1640.291860.583720.70814
1650.2683410.5366820.731659
1660.3429520.6859040.657048
1670.3245720.6491450.675428
1680.3052590.6105170.694741
1690.2761110.5522220.723889
1700.2527750.5055510.747225
1710.2491090.4982180.750891
1720.2217510.4435020.778249
1730.2768210.5536420.723179
1740.2644890.5289780.735511
1750.2460160.4920330.753984
1760.2924660.5849320.707534
1770.2744480.5488950.725552
1780.2803490.5606980.719651
1790.2780350.556070.721965
1800.2516130.5032260.748387
1810.2869610.5739230.713039
1820.4010330.8020670.598967
1830.3904210.7808430.609579
1840.3846870.7693740.615313
1850.3704220.7408450.629578
1860.4863510.9727030.513649
1870.4512650.902530.548735
1880.41920.83840.5808
1890.3863080.7726150.613692
1900.4179930.8359860.582007
1910.4497170.8994340.550283
1920.4711670.9423350.528833
1930.4601630.9203260.539837
1940.4298910.8597810.570109
1950.4012840.8025690.598716
1960.4405210.8810410.559479
1970.6414380.7171230.358562
1980.6467470.7065070.353253
1990.6062980.7874050.393702
2000.5654570.8690860.434543
2010.5242170.9515670.475783
2020.4844090.9688180.515591
2030.4599210.9198420.540079
2040.4583020.9166030.541698
2050.4239640.8479280.576036
2060.3816360.7632720.618364
2070.3436270.6872540.656373
2080.3075720.6151450.692428
2090.2701940.5403890.729806
2100.2626790.5253570.737321
2110.2395780.4791560.760422
2120.2089860.4179730.791014
2130.2313630.4627260.768637
2140.217390.4347810.78261
2150.1863910.3727820.813609
2160.158610.317220.84139
2170.1494950.2989910.850505
2180.1248360.2496720.875164
2190.1256460.2512930.874354
2200.1175230.2350460.882477
2210.1179790.2359590.882021
2220.09582720.1916540.904173
2230.0771180.1542360.922882
2240.07920930.1584190.920791
2250.07043450.1408690.929565
2260.0566410.1132820.943359
2270.04323480.08646950.956765
2280.04068840.08137670.959312
2290.05539360.1107870.944606
2300.05284090.1056820.947159
2310.04006530.08013060.959935
2320.04120580.08241170.958794
2330.09159080.1831820.908409
2340.0958320.1916640.904168
2350.09120930.1824190.908791
2360.06959990.13920.9304
2370.09167430.1833490.908326
2380.1280880.2561760.871912
2390.2152920.4305830.784708
2400.213020.426040.78698
2410.1722740.3445480.827726
2420.2114010.4228030.788599
2430.1589770.3179550.841023
2440.1143210.2286410.885679
2450.1734520.3469040.826548
2460.1879510.3759010.812049
2470.1313710.2627430.868629
2480.1613080.3226150.838692
2490.2442380.4884760.755762
2500.1607520.3215030.839248
2510.1756820.3513640.824318
2520.798820.4023590.20118






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00829876OK
10% type I error level190.0788382OK

\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 & 2 & 0.00829876 & OK \tabularnewline
10% type I error level & 19 & 0.0788382 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226596&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]2[/C][C]0.00829876[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]19[/C][C]0.0788382[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226596&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226596&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 level20.00829876OK
10% type I error level190.0788382OK


Figures (Output of Computation)

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

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