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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 computationFri, 12 Dec 2014 11:57:16 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/12/t14183855110biukuf70jhp4yv.htm/, Retrieved Thu, 16 May 2024 23:22:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266569, Retrieved Thu, 16 May 2024 23:22:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Multiple Regressi...] [2014-12-12 11:57:16] [9636d26fd774798d33054b538c301d75] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 11 8 7 18 12 20 4
12.2 19 18 20 23 20 19 4
12.8 16 12 9 22 14 18 5
7.4 24 24 19 22 25 24 4
6.7 15 16 12 19 15 20 4
12.6 17 19 16 25 20 20 9
14.8 19 16 17 28 21 24 8
13.3 19 15 9 16 15 21 11
11.1 28 28 28 28 28 28 4
8.2 26 21 20 21 11 10 4
11.4 15 18 16 22 22 22 6
6.4 26 22 22 24 22 19 4
10.6 16 19 17 24 27 27 8
12.0 24 22 12 26 24 23 4
6.3 25 25 18 28 23 24 4
11.3 22 20 20 24 24 24 11
11.9 15 16 12 20 21 25 4
9.3 21 19 16 26 20 24 4
9.6 22 18 16 21 19 21 6
10.0 27 26 21 28 25 28 6
6.4 26 24 15 27 16 28 4
13.8 26 20 17 23 24 22 8
10.8 22 19 17 24 21 26 5
13.8 21 19 17 24 22 26 4
11.7 22 23 18 22 25 21 9
10.9 20 18 15 21 23 26 4
16.1 21 16 20 25 20 23 7
13.4 20 18 13 20 21 20 10
9.9 22 21 21 21 22 24 4
11.5 21 20 12 26 25 25 4
8.3 8 15 6 23 23 24 7
11.7 22 19 13 21 19 20 12
9.0 20 19 19 27 21 24 7
9.7 24 7 12 25 19 25 5
10.8 17 20 14 23 25 23 8
10.3 20 20 13 25 16 21 5
10.4 23 19 12 23 24 23 4
12.7 20 19 17 19 24 21 9
9.3 22 20 19 22 18 18 7
11.8 19 18 10 24 28 24 4
5.9 15 14 10 19 15 18 4
11.4 20 17 11 21 17 21 4
13.0 22 17 11 27 18 23 4
10.8 17 8 10 25 26 25 4
12.3 14 9 7 25 18 22 7
11.3 24 22 22 23 22 22 4
11.8 17 20 12 17 19 23 7
7.9 23 20 18 28 17 24 4
12.7 25 22 20 25 26 25 4
12.3 16 22 9 20 21 22 4
11.6 18 22 16 25 26 24 4
6.7 20 16 14 21 21 21 8
10.9 18 14 11 24 12 24 4
12.1 23 24 20 28 20 25 4
13.3 24 21 17 20 20 23 4
10.1 23 20 14 19 24 27 4
5.7 13 20 8 24 24 27 7
14.3 20 18 16 21 22 23 12
8.0 20 14 11 24 21 18 4
13.3 19 19 10 23 20 20 4
9.3 22 24 15 18 23 23 4
12.5 22 19 15 27 19 24 5
7.6 15 16 10 25 24 26 15
15.9 17 16 10 20 21 20 5
9.2 19 16 18 21 16 23 10
9.1 20 14 10 23 17 22 9
11.1 22 22 22 27 23 23 8
13.0 21 21 16 24 20 17 4
14.5 21 15 10 27 19 20 5
12.2 16 14 7 24 18 22 4
12.3 20 15 16 23 18 18 9
11.4 21 14 16 24 21 19 4
8.8 20 20 16 21 20 19 10
14.6 23 21 22 23 17 16 4
12.6 18 14 5 27 25 26 4
NA 22 19 18 24 15 14 6
13.0 16 16 10 25 17 25 7
12.6 17 13 8 19 17 23 5
13.2 24 26 16 24 24 18 4
9.9 13 13 8 25 21 22 4
7.7 19 18 16 23 22 26 4
10.5 20 15 14 23 18 25 4
13.4 22 18 15 25 22 26 4
10.9 19 21 9 26 20 26 4
4.3 21 17 21 26 21 24 6
10.3 15 18 7 16 21 22 10
11.8 21 20 17 23 20 21 7
11.2 24 18 18 26 18 22 4
11.4 22 25 16 25 25 28 4
8.6 20 20 16 23 23 22 7
13.2 21 19 14 26 21 26 4
12.6 19 18 15 22 20 20 8
5.6 14 12 8 20 21 24 11
9.9 25 22 22 27 20 21 6
8.8 11 16 5 20 22 23 14
7.7 17 18 13 22 15 23 5
9.0 22 23 22 24 24 23 4
7.3 20 20 18 21 22 22 8
11.4 22 20 15 24 21 23 9
13.6 15 16 11 26 17 21 4
7.9 23 22 19 24 23 27 4
10.7 20 19 19 24 22 23 5
10.3 22 23 21 27 23 26 4
8.3 16 6 4 25 16 27 5
9.6 25 19 17 27 18 27 4
14.2 18 24 10 19 25 23 4
8.5 19 19 13 22 18 23 7
13.5 25 15 15 22 14 23 10
4.9 21 18 11 25 20 28 4
6.4 22 18 20 23 19 24 5
9.6 21 22 13 24 18 20 4
11.6 22 23 18 24 22 23 4
11.1 23 18 20 23 21 22 4
4.35 20 17 15 22 14 15 6
12.7 6 6 4 24 5 27 4
18.1 15 22 9 19 25 23 8
17.85 18 20 18 25 21 23 5
16.6 24 16 12 26 11 20 4
12.6 22 16 17 18 20 18 17
17.1 21 17 12 24 9 22 4
19.1 23 20 16 28 15 20 4
16.1 20 23 17 23 23 21 8
13.35 20 18 14 19 21 25 4
18.4 18 13 13 19 9 19 7
14.7 25 22 20 27 24 25 4
10.6 16 20 16 24 16 24 4
12.6 20 20 15 26 20 22 5
16.2 14 13 10 21 15 28 7
13.6 22 16 16 25 18 22 4
18.9 26 25 21 28 22 21 4
14.1 20 16 15 19 21 23 7
14.5 17 15 16 20 21 19 11
16.15 22 19 19 26 21 21 7
14.75 22 19 9 27 20 25 4
14.8 20 24 19 23 24 23 4
12.45 17 9 7 18 15 28 4
12.65 22 22 23 23 24 14 4
17.35 17 15 14 21 18 23 4
8.6 22 22 10 23 24 24 4
18.4 21 22 16 22 24 25 6
16.1 25 24 12 21 15 15 8
11.6 11 12 10 14 19 23 23
17.75 19 21 7 24 20 26 4
15.25 24 25 20 26 26 21 8
17.65 17 26 9 24 26 26 6
16.35 22 21 12 22 23 23 4
17.65 17 14 10 20 13 15 7
13.6 26 28 19 20 16 16 4
14.35 20 21 11 18 22 20 4
14.75 19 16 15 18 21 20 4
18.25 21 16 14 25 11 21 10
9.9 24 25 11 28 23 28 6
16 21 21 14 23 18 19 5
18.25 19 22 15 20 19 21 5
16.85 13 9 7 22 15 22 4
14.6 24 20 22 27 8 27 4
13.85 28 19 19 24 15 20 5
18.95 27 24 22 23 21 17 5
15.6 22 22 11 20 25 26 5
14.85 23 22 19 22 14 21 5
11.75 19 12 9 21 21 24 4
18.45 18 17 11 24 18 21 6
15.9 23 18 17 26 18 25 4
17.1 21 10 12 24 12 22 4
16.1 22 22 17 18 24 17 4
19.9 17 24 10 17 17 14 9
10.95 15 18 17 23 20 23 18
18.45 21 18 13 21 24 28 6
15.1 20 23 11 21 22 24 5
15 26 21 19 24 15 22 4
11.35 19 21 21 22 22 24 11
15.95 28 28 24 24 26 25 4
18.1 21 17 13 24 17 21 10
14.6 19 21 16 24 23 22 6
15.4 22 21 13 23 19 16 8
15.4 21 20 15 21 21 18 8
17.6 20 18 15 24 23 27 6
13.35 19 17 11 19 19 17 8
19.1 11 7 7 19 18 25 4
15.35 17 17 13 23 16 24 4
7.6 19 14 13 25 23 21 9
13.4 20 18 12 24 13 21 9
13.9 17 14 8 21 18 19 5
19.1 21 23 7 18 23 27 4
15.25 21 20 17 23 21 28 4
12.9 12 14 9 20 23 19 15
16.1 23 17 18 23 16 23 10
17.35 22 21 17 23 17 25 9
13.15 22 23 17 23 20 26 7
12.15 21 24 18 23 18 25 9
12.6 20 21 12 27 20 25 6
10.35 18 14 14 19 19 24 4
15.4 21 24 22 25 26 24 7
9.6 24 16 19 25 9 24 4
18.2 22 21 21 21 23 22 7
13.6 20 8 10 25 9 21 4
14.85 17 17 16 17 13 17 15
14.75 19 18 11 22 27 23 4
14.1 16 17 15 23 22 17 9
14.9 19 16 12 27 12 25 4
16.25 23 22 21 27 18 19 4
19.25 8 17 22 5 6 8 28
13.6 22 21 20 19 17 14 4
13.6 23 20 15 24 22 22 4
15.65 15 20 9 23 22 25 4
12.75 17 19 15 28 23 28 5
14.6 21 8 14 25 19 25 4
9.85 25 19 11 27 20 24 4
12.65 18 11 9 16 17 15 12
19.2 20 13 12 25 24 24 4
16.6 21 18 11 26 20 28 6
11.2 21 19 14 24 18 24 6
15.25 24 23 10 23 23 25 5
11.9 22 20 18 24 27 23 4
13.2 22 22 11 27 25 26 4
16.35 23 19 14 25 24 26 4
12.4 17 16 16 19 12 22 10
15.85 15 11 11 19 16 25 7
18.15 22 21 16 24 24 22 4
11.15 19 14 13 20 23 26 7
15.65 18 21 12 21 24 20 4
17.75 21 20 17 28 24 26 4
7.65 20 21 23 26 26 26 12
12.35 19 20 14 19 19 21 5
15.6 19 19 10 23 28 21 8
19.3 16 19 16 23 23 24 6
15.2 18 18 11 21 21 21 17
17.1 23 20 16 26 19 18 4
15.6 22 21 19 25 23 23 5
18.4 23 22 17 25 23 26 4
19.05 20 19 12 24 20 23 5
18.55 24 23 17 23 18 25 5
19.1 25 16 11 22 20 20 6
13.1 25 23 19 27 28 25 4
12.85 20 18 12 26 21 26 4
9.5 23 23 8 23 25 19 4
4.5 21 20 17 22 18 21 6
11.85 23 20 13 26 24 23 8
13.6 23 23 17 22 28 24 10
11.7 11 13 7 17 9 6 4
12.4 21 21 23 25 22 22 5
13.35 27 26 18 22 26 21 4
11.4 19 18 13 28 28 28 4
14.9 21 19 17 22 18 24 4
19.9 16 18 13 21 23 14 16
11.2 21 18 8 24 15 20 7
14.6 22 19 16 26 24 28 4
17.6 16 13 14 26 12 19 4
14.05 18 10 13 24 12 24 14
16.1 23 21 19 27 20 21 5
13.35 24 24 15 22 25 21 5
11.85 20 21 15 23 24 26 5
11.95 20 23 8 22 23 24 5
14.75 18 18 14 23 18 26 7
15.15 4 11 7 15 20 25 19
13.2 14 16 11 20 22 23 16
16.85 22 20 17 22 20 24 4
7.85 17 20 19 25 25 24 4
7.7 23 26 17 27 28 26 7
12.6 20 21 12 24 25 23 9
7.85 18 12 12 21 14 20 5
10.95 19 15 18 17 16 16 14
12.35 20 18 16 26 24 24 4
9.95 15 14 15 20 13 20 16
14.9 24 18 20 22 19 23 10
16.65 21 16 16 24 18 23 5
13.4 19 19 12 23 16 18 6
13.95 19 7 10 22 8 21 4
15.7 27 21 28 28 27 25 4
16.85 23 24 19 21 23 23 4
10.95 23 21 18 24 20 26 5
15.35 20 20 19 28 20 26 4
12.2 17 22 8 25 26 24 4
15.1 21 17 17 24 23 23 5
17.75 23 19 16 24 24 21 4
15.2 22 20 18 21 21 23 4
14.6 16 16 12 20 15 20 5
16.65 20 20 17 26 22 23 8
8.1 16 16 13 16 25 24 15

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266569&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]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266569&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266569&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 time10 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 15.5971 + 0.0544527AMS.I1[t] + 0.0859278AMS.I2[t] -0.0609023AMS.I3[t] -0.0608701AMS.E1[t] -0.0684604AMS.E2[t] -0.0708473AMS.E3[t] -0.00882652AMS.A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  15.5971 +  0.0544527AMS.I1[t] +  0.0859278AMS.I2[t] -0.0609023AMS.I3[t] -0.0608701AMS.E1[t] -0.0684604AMS.E2[t] -0.0708473AMS.E3[t] -0.00882652AMS.A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266569&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  15.5971 +  0.0544527AMS.I1[t] +  0.0859278AMS.I2[t] -0.0609023AMS.I3[t] -0.0608701AMS.E1[t] -0.0684604AMS.E2[t] -0.0708473AMS.E3[t] -0.00882652AMS.A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266569&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266569&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
TOT[t] = + 15.5971 + 0.0544527AMS.I1[t] + 0.0859278AMS.I2[t] -0.0609023AMS.I3[t] -0.0608701AMS.E1[t] -0.0684604AMS.E2[t] -0.0708473AMS.E3[t] -0.00882652AMS.A[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.59712.346176.6481.64011e-108.20057e-11
AMS.I10.05445270.08431680.64580.518950.259475
AMS.I20.08592780.07210151.1920.2344010.117201
AMS.I3-0.06090230.0624562-0.97510.3303740.165187
AMS.E1-0.06087010.0863238-0.70510.4813330.240666
AMS.E2-0.06846040.0589105-1.1620.2462180.123109
AMS.E3-0.07084730.0713003-0.99360.3212850.160642
AMS.A-0.008826520.0710813-0.12420.9012690.450635

\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) & 15.5971 & 2.34617 & 6.648 & 1.64011e-10 & 8.20057e-11 \tabularnewline
AMS.I1 & 0.0544527 & 0.0843168 & 0.6458 & 0.51895 & 0.259475 \tabularnewline
AMS.I2 & 0.0859278 & 0.0721015 & 1.192 & 0.234401 & 0.117201 \tabularnewline
AMS.I3 & -0.0609023 & 0.0624562 & -0.9751 & 0.330374 & 0.165187 \tabularnewline
AMS.E1 & -0.0608701 & 0.0863238 & -0.7051 & 0.481333 & 0.240666 \tabularnewline
AMS.E2 & -0.0684604 & 0.0589105 & -1.162 & 0.246218 & 0.123109 \tabularnewline
AMS.E3 & -0.0708473 & 0.0713003 & -0.9936 & 0.321285 & 0.160642 \tabularnewline
AMS.A & -0.00882652 & 0.0710813 & -0.1242 & 0.901269 & 0.450635 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266569&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]15.5971[/C][C]2.34617[/C][C]6.648[/C][C]1.64011e-10[/C][C]8.20057e-11[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.0544527[/C][C]0.0843168[/C][C]0.6458[/C][C]0.51895[/C][C]0.259475[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.0859278[/C][C]0.0721015[/C][C]1.192[/C][C]0.234401[/C][C]0.117201[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0609023[/C][C]0.0624562[/C][C]-0.9751[/C][C]0.330374[/C][C]0.165187[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0608701[/C][C]0.0863238[/C][C]-0.7051[/C][C]0.481333[/C][C]0.240666[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0684604[/C][C]0.0589105[/C][C]-1.162[/C][C]0.246218[/C][C]0.123109[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0708473[/C][C]0.0713003[/C][C]-0.9936[/C][C]0.321285[/C][C]0.160642[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.00882652[/C][C]0.0710813[/C][C]-0.1242[/C][C]0.901269[/C][C]0.450635[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266569&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266569&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)15.59712.346176.6481.64011e-108.20057e-11
AMS.I10.05445270.08431680.64580.518950.259475
AMS.I20.08592780.07210151.1920.2344010.117201
AMS.I3-0.06090230.0624562-0.97510.3303740.165187
AMS.E1-0.06087010.0863238-0.70510.4813330.240666
AMS.E2-0.06846040.0589105-1.1620.2462180.123109
AMS.E3-0.07084730.0713003-0.99360.3212850.160642
AMS.A-0.008826520.0710813-0.12420.9012690.450635






Multiple Linear Regression - Regression Statistics
Multiple R0.158695
R-squared0.0251842
Adjusted R-squared-8.87951e-05
F-TEST (value)0.996487
F-TEST (DF numerator)7
F-TEST (DF denominator)270
p-value0.434075
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.39451
Sum Squared Residuals3111.13

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.158695 \tabularnewline
R-squared & 0.0251842 \tabularnewline
Adjusted R-squared & -8.87951e-05 \tabularnewline
F-TEST (value) & 0.996487 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 270 \tabularnewline
p-value & 0.434075 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.39451 \tabularnewline
Sum Squared Residuals & 3111.13 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266569&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.158695[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0251842[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]-8.87951e-05[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]0.996487[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]270[/C][/ROW]
[ROW][C]p-value[/C][C]0.434075[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.39451[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3111.13[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266569&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266569&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 R0.158695
R-squared0.0251842
Adjusted R-squared-8.87951e-05
F-TEST (value)0.996487
F-TEST (DF numerator)7
F-TEST (DF denominator)270
p-value0.434075
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.39451
Sum Squared Residuals3111.13






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.0877-0.187704
212.212.8097-0.609688
312.813.3343-0.534341
47.413.0228-5.62275
56.713.4222-6.72217
612.612.7936-0.193599
714.812.05822.74181
813.313.7867-0.486742
911.112.1822-1.08216
108.214.8241-6.62415
1111.412.5292-1.12924
126.413.215-6.81497
1310.611.7728-1.17279
141213.173-1.17304
156.312.9957-6.69573
1611.312.3942-1.09417
1711.912.5963-0.696305
189.312.7113-3.41128
199.613.2475-3.64751
201012.5699-2.5699
216.413.4037-7.00367
2213.813.02370.77627
2310.812.6076-1.80759
2413.812.49351.30649
2511.713.0572-1.35723
2610.912.5891-1.68908
2716.112.31513.78487
2813.413.28080.1192
299.912.8005-2.90051
3011.512.6277-1.12767
318.312.2195-3.91946
3211.713.534-1.83403
33912.3183-3.31831
349.712.1368-2.43677
3510.812.5771-1.77705
3610.313.4639-3.16389
3710.413.0434-2.64341
3812.712.9166-0.216587
399.313.448-4.14796
4011.812.4559-0.655921
415.913.5138-7.61382
4211.413.5118-2.11176
431313.0453-0.0452896
4410.811.4929-0.69294
4512.312.332-0.0319622
4611.312.9544-1.6544
4711.813.4837-1.68367
487.912.868-4.96795
4912.712.52250.177471
5012.313.5616-1.26157
5111.612.4558-0.855816
526.712.934-6.23398
5310.913.0922-2.19222
5412.112.8136-0.713631
5513.313.4217-0.121663
5610.112.9676-2.86763
575.712.4577-6.75768
5814.312.73861.56143
59813.0101-5.01007
6013.313.4338-0.133791
619.313.6087-4.3087
6212.512.8254-0.325402
637.612.0404-4.44044
6415.913.17242.72757
659.212.8189-3.61887
669.113.0782-3.97816
6711.112.4274-1.3274
681313.5008-0.50081
6914.513.01511.48486
7012.212.9579-0.757857
7112.313.0136-0.713601
7211.412.6892-1.28916
738.813.3484-4.54839
7414.613.58141.0186
7512.612.24330.356656
76NANA0.284426
771313.5586-0.558616
7812.613.1491-0.549119
7913.215.6814-2.48142
809.914.6204-4.72044
817.79.88361-2.18361
8210.59.622970.877035
8313.415.5589-2.15885
8410.918.7488-7.8488
854.37.47574-3.17574
8610.311.605-1.30498
8711.813.5455-1.74552
8811.212.5165-1.31648
8911.415.6352-4.2352
908.68.022930.577067
9113.213.6689-0.468916
9212.619.4508-6.85081
935.68.65548-3.05548
949.913.8898-3.98978
958.814.3381-5.53805
967.711.3628-3.66278
97914.5948-5.59477
987.38.89256-1.59256
9911.410.64920.750782
10013.618.2991-4.69908
1017.99.72096-1.82096
10210.712.797-2.09699
10310.314.1661-3.86613
1048.311.4317-3.1317
1059.68.897610.702386
10614.218.9099-4.70985
1078.58.318420.181584
10813.521.3073-7.80735
1094.911.1784-6.27844
1106.410.4938-4.09382
1119.611.0433-1.44331
11211.613.2465-1.6465
11311.120.5701-9.47009
1144.354.094360.255638
11512.77.7884.912
11618.112.81655.28352
11717.8515.012.84
11816.617.2444-0.64435
11912.69.299543.30046
12017.111.41015.68993
12119.116.09413.0059
12216.115.72950.37051
12313.358.671984.67802
12418.416.23772.16229
12514.717.0205-2.32053
12610.610.9365-0.336529
12712.68.916743.68326
12816.215.44740.752562
12913.67.848485.75152
13018.917.66191.23805
13114.112.3391.76103
13214.511.05063.44937
13316.1514.46031.68967
13414.7512.83341.91662
13514.815.0782-0.278188
13612.4513.0144-0.564445
13712.658.083684.56632
13817.3522.0477-4.6977
1398.63.050215.54979
14018.417.15131.24869
14116.117.1327-1.03272
14211.67.15244.4476
14317.7515.41312.33693
14415.2510.67294.57709
14517.6514.59013.05985
14616.3512.58483.76516
14717.6518.83-1.18003
14813.613.01660.583373
14914.3512.70741.64261
15014.759.91194.8381
15118.2521.4166-3.16656
1529.97.569882.33012
1531611.30854.69154
15418.2514.0924.15802
15516.8515.39331.45673
15614.614.39840.20165
15713.858.603485.24652
15818.9516.55042.39957
15915.614.50321.09678
16014.8515.7631-0.913089
16111.756.434135.31587
16218.4515.28943.16057
16315.911.79274.10734
16417.114.67172.42833
16516.110.90615.19392
16619.921.3176-1.41762
16710.955.037535.91247
16818.4516.81371.63634
16915.113.67841.42157
1701516.1645-1.1645
17111.358.418712.93129
17215.9511.05884.89116
17318.116.31461.78537
17414.613.10281.49716
17515.413.48381.91622
17615.410.1185.28203
17717.617.9402-0.34021
17813.356.425916.92409
17919.116.71082.38922
18015.3520.1293-4.77934
1817.67.78388-0.183884
18213.412.83770.562267
18313.98.472155.42785
18419.116.41712.68293
18515.2514.98490.26513
18612.99.800873.09913
18716.111.89974.2003
18817.3517.2630.0870189
18913.1514.2237-1.07367
19012.1512.4729-0.322925
19112.614.9846-2.38464
19210.357.349143.00086
19315.419.0481-3.64809
1949.64.247265.35274
19518.217.70350.496485
19613.612.49751.10249
19714.8512.75612.09393
19814.7513.47561.27445
19914.112.20421.89583
20014.911.85373.04625
20116.2511.62464.62543
20219.2519.6839-0.433928
20313.613.09350.506467
20413.610.82172.77835
20515.6514.8350.814963
20612.7510.09642.65364
20714.617.9227-3.32274
2089.8510.8679-1.01791
20912.655.62197.0281
21019.215.22883.97118
21116.618.4741-1.8741
21211.29.431321.76868
21315.2515.7932-0.543224
21411.911.48320.416836
21513.29.437333.76267
21616.3517.2482-0.898198
21712.49.154263.24574
21815.8510.62725.22282
21918.1519.3471-1.19711
22011.158.777292.37271
22115.6510.0995.55097
22217.7521.8793-4.1293
2237.658.80838-1.15838
22412.359.529952.82005
22515.68.69866.9014
22619.317.20022.0998
22715.211.49973.70034
22817.114.17242.92761
22915.69.930865.66914
23018.412.43425.9658
23119.0513.89735.15269
23218.5512.9355.61496
23319.118.41070.689302
23413.112.85440.245643
23512.8517.1957-4.34566
2369.518.3116-8.8116
2374.55.50052-1.00052
23811.8510.99580.854164
23913.616.6755-3.07546
24011.711.8136-0.11364
24112.412.6129-0.21295
24213.3513.6963-0.346344
24311.49.530781.86922
24414.98.237326.66268
24519.922.5335-2.63353
24611.28.80852.3915
24714.69.947184.65282
24817.616.08841.51156
24914.0510.90223.14782
25016.116.2201-0.120077
25113.3514.1478-0.797836
25211.8513.417-1.56703
25311.959.935162.01484
25414.7511.71263.03739
25515.1514.52010.629929
25613.29.384243.81576
25716.8521.1153-4.26526
2587.8512.7341-4.88405
2597.77.97845-0.278448
26012.617.9297-5.32972
2617.8510.337-2.48705
26210.9510.89710.0529391
26312.3515.4377-3.08774
2649.957.924932.02507
26514.911.02423.87582
26616.6516.9599-0.30987
26713.412.66420.735795
26813.9510.05723.89278
26915.712.08693.61306
27016.8518.7415-1.89146
27110.957.896623.05338
27215.3516.0386-0.688582
27312.29.55692.6431
27415.110.23064.86937
27517.7515.58662.1634
27615.214.00691.19307
27714.610.53054.06952
27816.6521.0833-4.43325
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.0877 & -0.187704 \tabularnewline
2 & 12.2 & 12.8097 & -0.609688 \tabularnewline
3 & 12.8 & 13.3343 & -0.534341 \tabularnewline
4 & 7.4 & 13.0228 & -5.62275 \tabularnewline
5 & 6.7 & 13.4222 & -6.72217 \tabularnewline
6 & 12.6 & 12.7936 & -0.193599 \tabularnewline
7 & 14.8 & 12.0582 & 2.74181 \tabularnewline
8 & 13.3 & 13.7867 & -0.486742 \tabularnewline
9 & 11.1 & 12.1822 & -1.08216 \tabularnewline
10 & 8.2 & 14.8241 & -6.62415 \tabularnewline
11 & 11.4 & 12.5292 & -1.12924 \tabularnewline
12 & 6.4 & 13.215 & -6.81497 \tabularnewline
13 & 10.6 & 11.7728 & -1.17279 \tabularnewline
14 & 12 & 13.173 & -1.17304 \tabularnewline
15 & 6.3 & 12.9957 & -6.69573 \tabularnewline
16 & 11.3 & 12.3942 & -1.09417 \tabularnewline
17 & 11.9 & 12.5963 & -0.696305 \tabularnewline
18 & 9.3 & 12.7113 & -3.41128 \tabularnewline
19 & 9.6 & 13.2475 & -3.64751 \tabularnewline
20 & 10 & 12.5699 & -2.5699 \tabularnewline
21 & 6.4 & 13.4037 & -7.00367 \tabularnewline
22 & 13.8 & 13.0237 & 0.77627 \tabularnewline
23 & 10.8 & 12.6076 & -1.80759 \tabularnewline
24 & 13.8 & 12.4935 & 1.30649 \tabularnewline
25 & 11.7 & 13.0572 & -1.35723 \tabularnewline
26 & 10.9 & 12.5891 & -1.68908 \tabularnewline
27 & 16.1 & 12.3151 & 3.78487 \tabularnewline
28 & 13.4 & 13.2808 & 0.1192 \tabularnewline
29 & 9.9 & 12.8005 & -2.90051 \tabularnewline
30 & 11.5 & 12.6277 & -1.12767 \tabularnewline
31 & 8.3 & 12.2195 & -3.91946 \tabularnewline
32 & 11.7 & 13.534 & -1.83403 \tabularnewline
33 & 9 & 12.3183 & -3.31831 \tabularnewline
34 & 9.7 & 12.1368 & -2.43677 \tabularnewline
35 & 10.8 & 12.5771 & -1.77705 \tabularnewline
36 & 10.3 & 13.4639 & -3.16389 \tabularnewline
37 & 10.4 & 13.0434 & -2.64341 \tabularnewline
38 & 12.7 & 12.9166 & -0.216587 \tabularnewline
39 & 9.3 & 13.448 & -4.14796 \tabularnewline
40 & 11.8 & 12.4559 & -0.655921 \tabularnewline
41 & 5.9 & 13.5138 & -7.61382 \tabularnewline
42 & 11.4 & 13.5118 & -2.11176 \tabularnewline
43 & 13 & 13.0453 & -0.0452896 \tabularnewline
44 & 10.8 & 11.4929 & -0.69294 \tabularnewline
45 & 12.3 & 12.332 & -0.0319622 \tabularnewline
46 & 11.3 & 12.9544 & -1.6544 \tabularnewline
47 & 11.8 & 13.4837 & -1.68367 \tabularnewline
48 & 7.9 & 12.868 & -4.96795 \tabularnewline
49 & 12.7 & 12.5225 & 0.177471 \tabularnewline
50 & 12.3 & 13.5616 & -1.26157 \tabularnewline
51 & 11.6 & 12.4558 & -0.855816 \tabularnewline
52 & 6.7 & 12.934 & -6.23398 \tabularnewline
53 & 10.9 & 13.0922 & -2.19222 \tabularnewline
54 & 12.1 & 12.8136 & -0.713631 \tabularnewline
55 & 13.3 & 13.4217 & -0.121663 \tabularnewline
56 & 10.1 & 12.9676 & -2.86763 \tabularnewline
57 & 5.7 & 12.4577 & -6.75768 \tabularnewline
58 & 14.3 & 12.7386 & 1.56143 \tabularnewline
59 & 8 & 13.0101 & -5.01007 \tabularnewline
60 & 13.3 & 13.4338 & -0.133791 \tabularnewline
61 & 9.3 & 13.6087 & -4.3087 \tabularnewline
62 & 12.5 & 12.8254 & -0.325402 \tabularnewline
63 & 7.6 & 12.0404 & -4.44044 \tabularnewline
64 & 15.9 & 13.1724 & 2.72757 \tabularnewline
65 & 9.2 & 12.8189 & -3.61887 \tabularnewline
66 & 9.1 & 13.0782 & -3.97816 \tabularnewline
67 & 11.1 & 12.4274 & -1.3274 \tabularnewline
68 & 13 & 13.5008 & -0.50081 \tabularnewline
69 & 14.5 & 13.0151 & 1.48486 \tabularnewline
70 & 12.2 & 12.9579 & -0.757857 \tabularnewline
71 & 12.3 & 13.0136 & -0.713601 \tabularnewline
72 & 11.4 & 12.6892 & -1.28916 \tabularnewline
73 & 8.8 & 13.3484 & -4.54839 \tabularnewline
74 & 14.6 & 13.5814 & 1.0186 \tabularnewline
75 & 12.6 & 12.2433 & 0.356656 \tabularnewline
76 & NA & NA & 0.284426 \tabularnewline
77 & 13 & 13.5586 & -0.558616 \tabularnewline
78 & 12.6 & 13.1491 & -0.549119 \tabularnewline
79 & 13.2 & 15.6814 & -2.48142 \tabularnewline
80 & 9.9 & 14.6204 & -4.72044 \tabularnewline
81 & 7.7 & 9.88361 & -2.18361 \tabularnewline
82 & 10.5 & 9.62297 & 0.877035 \tabularnewline
83 & 13.4 & 15.5589 & -2.15885 \tabularnewline
84 & 10.9 & 18.7488 & -7.8488 \tabularnewline
85 & 4.3 & 7.47574 & -3.17574 \tabularnewline
86 & 10.3 & 11.605 & -1.30498 \tabularnewline
87 & 11.8 & 13.5455 & -1.74552 \tabularnewline
88 & 11.2 & 12.5165 & -1.31648 \tabularnewline
89 & 11.4 & 15.6352 & -4.2352 \tabularnewline
90 & 8.6 & 8.02293 & 0.577067 \tabularnewline
91 & 13.2 & 13.6689 & -0.468916 \tabularnewline
92 & 12.6 & 19.4508 & -6.85081 \tabularnewline
93 & 5.6 & 8.65548 & -3.05548 \tabularnewline
94 & 9.9 & 13.8898 & -3.98978 \tabularnewline
95 & 8.8 & 14.3381 & -5.53805 \tabularnewline
96 & 7.7 & 11.3628 & -3.66278 \tabularnewline
97 & 9 & 14.5948 & -5.59477 \tabularnewline
98 & 7.3 & 8.89256 & -1.59256 \tabularnewline
99 & 11.4 & 10.6492 & 0.750782 \tabularnewline
100 & 13.6 & 18.2991 & -4.69908 \tabularnewline
101 & 7.9 & 9.72096 & -1.82096 \tabularnewline
102 & 10.7 & 12.797 & -2.09699 \tabularnewline
103 & 10.3 & 14.1661 & -3.86613 \tabularnewline
104 & 8.3 & 11.4317 & -3.1317 \tabularnewline
105 & 9.6 & 8.89761 & 0.702386 \tabularnewline
106 & 14.2 & 18.9099 & -4.70985 \tabularnewline
107 & 8.5 & 8.31842 & 0.181584 \tabularnewline
108 & 13.5 & 21.3073 & -7.80735 \tabularnewline
109 & 4.9 & 11.1784 & -6.27844 \tabularnewline
110 & 6.4 & 10.4938 & -4.09382 \tabularnewline
111 & 9.6 & 11.0433 & -1.44331 \tabularnewline
112 & 11.6 & 13.2465 & -1.6465 \tabularnewline
113 & 11.1 & 20.5701 & -9.47009 \tabularnewline
114 & 4.35 & 4.09436 & 0.255638 \tabularnewline
115 & 12.7 & 7.788 & 4.912 \tabularnewline
116 & 18.1 & 12.8165 & 5.28352 \tabularnewline
117 & 17.85 & 15.01 & 2.84 \tabularnewline
118 & 16.6 & 17.2444 & -0.64435 \tabularnewline
119 & 12.6 & 9.29954 & 3.30046 \tabularnewline
120 & 17.1 & 11.4101 & 5.68993 \tabularnewline
121 & 19.1 & 16.0941 & 3.0059 \tabularnewline
122 & 16.1 & 15.7295 & 0.37051 \tabularnewline
123 & 13.35 & 8.67198 & 4.67802 \tabularnewline
124 & 18.4 & 16.2377 & 2.16229 \tabularnewline
125 & 14.7 & 17.0205 & -2.32053 \tabularnewline
126 & 10.6 & 10.9365 & -0.336529 \tabularnewline
127 & 12.6 & 8.91674 & 3.68326 \tabularnewline
128 & 16.2 & 15.4474 & 0.752562 \tabularnewline
129 & 13.6 & 7.84848 & 5.75152 \tabularnewline
130 & 18.9 & 17.6619 & 1.23805 \tabularnewline
131 & 14.1 & 12.339 & 1.76103 \tabularnewline
132 & 14.5 & 11.0506 & 3.44937 \tabularnewline
133 & 16.15 & 14.4603 & 1.68967 \tabularnewline
134 & 14.75 & 12.8334 & 1.91662 \tabularnewline
135 & 14.8 & 15.0782 & -0.278188 \tabularnewline
136 & 12.45 & 13.0144 & -0.564445 \tabularnewline
137 & 12.65 & 8.08368 & 4.56632 \tabularnewline
138 & 17.35 & 22.0477 & -4.6977 \tabularnewline
139 & 8.6 & 3.05021 & 5.54979 \tabularnewline
140 & 18.4 & 17.1513 & 1.24869 \tabularnewline
141 & 16.1 & 17.1327 & -1.03272 \tabularnewline
142 & 11.6 & 7.1524 & 4.4476 \tabularnewline
143 & 17.75 & 15.4131 & 2.33693 \tabularnewline
144 & 15.25 & 10.6729 & 4.57709 \tabularnewline
145 & 17.65 & 14.5901 & 3.05985 \tabularnewline
146 & 16.35 & 12.5848 & 3.76516 \tabularnewline
147 & 17.65 & 18.83 & -1.18003 \tabularnewline
148 & 13.6 & 13.0166 & 0.583373 \tabularnewline
149 & 14.35 & 12.7074 & 1.64261 \tabularnewline
150 & 14.75 & 9.9119 & 4.8381 \tabularnewline
151 & 18.25 & 21.4166 & -3.16656 \tabularnewline
152 & 9.9 & 7.56988 & 2.33012 \tabularnewline
153 & 16 & 11.3085 & 4.69154 \tabularnewline
154 & 18.25 & 14.092 & 4.15802 \tabularnewline
155 & 16.85 & 15.3933 & 1.45673 \tabularnewline
156 & 14.6 & 14.3984 & 0.20165 \tabularnewline
157 & 13.85 & 8.60348 & 5.24652 \tabularnewline
158 & 18.95 & 16.5504 & 2.39957 \tabularnewline
159 & 15.6 & 14.5032 & 1.09678 \tabularnewline
160 & 14.85 & 15.7631 & -0.913089 \tabularnewline
161 & 11.75 & 6.43413 & 5.31587 \tabularnewline
162 & 18.45 & 15.2894 & 3.16057 \tabularnewline
163 & 15.9 & 11.7927 & 4.10734 \tabularnewline
164 & 17.1 & 14.6717 & 2.42833 \tabularnewline
165 & 16.1 & 10.9061 & 5.19392 \tabularnewline
166 & 19.9 & 21.3176 & -1.41762 \tabularnewline
167 & 10.95 & 5.03753 & 5.91247 \tabularnewline
168 & 18.45 & 16.8137 & 1.63634 \tabularnewline
169 & 15.1 & 13.6784 & 1.42157 \tabularnewline
170 & 15 & 16.1645 & -1.1645 \tabularnewline
171 & 11.35 & 8.41871 & 2.93129 \tabularnewline
172 & 15.95 & 11.0588 & 4.89116 \tabularnewline
173 & 18.1 & 16.3146 & 1.78537 \tabularnewline
174 & 14.6 & 13.1028 & 1.49716 \tabularnewline
175 & 15.4 & 13.4838 & 1.91622 \tabularnewline
176 & 15.4 & 10.118 & 5.28203 \tabularnewline
177 & 17.6 & 17.9402 & -0.34021 \tabularnewline
178 & 13.35 & 6.42591 & 6.92409 \tabularnewline
179 & 19.1 & 16.7108 & 2.38922 \tabularnewline
180 & 15.35 & 20.1293 & -4.77934 \tabularnewline
181 & 7.6 & 7.78388 & -0.183884 \tabularnewline
182 & 13.4 & 12.8377 & 0.562267 \tabularnewline
183 & 13.9 & 8.47215 & 5.42785 \tabularnewline
184 & 19.1 & 16.4171 & 2.68293 \tabularnewline
185 & 15.25 & 14.9849 & 0.26513 \tabularnewline
186 & 12.9 & 9.80087 & 3.09913 \tabularnewline
187 & 16.1 & 11.8997 & 4.2003 \tabularnewline
188 & 17.35 & 17.263 & 0.0870189 \tabularnewline
189 & 13.15 & 14.2237 & -1.07367 \tabularnewline
190 & 12.15 & 12.4729 & -0.322925 \tabularnewline
191 & 12.6 & 14.9846 & -2.38464 \tabularnewline
192 & 10.35 & 7.34914 & 3.00086 \tabularnewline
193 & 15.4 & 19.0481 & -3.64809 \tabularnewline
194 & 9.6 & 4.24726 & 5.35274 \tabularnewline
195 & 18.2 & 17.7035 & 0.496485 \tabularnewline
196 & 13.6 & 12.4975 & 1.10249 \tabularnewline
197 & 14.85 & 12.7561 & 2.09393 \tabularnewline
198 & 14.75 & 13.4756 & 1.27445 \tabularnewline
199 & 14.1 & 12.2042 & 1.89583 \tabularnewline
200 & 14.9 & 11.8537 & 3.04625 \tabularnewline
201 & 16.25 & 11.6246 & 4.62543 \tabularnewline
202 & 19.25 & 19.6839 & -0.433928 \tabularnewline
203 & 13.6 & 13.0935 & 0.506467 \tabularnewline
204 & 13.6 & 10.8217 & 2.77835 \tabularnewline
205 & 15.65 & 14.835 & 0.814963 \tabularnewline
206 & 12.75 & 10.0964 & 2.65364 \tabularnewline
207 & 14.6 & 17.9227 & -3.32274 \tabularnewline
208 & 9.85 & 10.8679 & -1.01791 \tabularnewline
209 & 12.65 & 5.6219 & 7.0281 \tabularnewline
210 & 19.2 & 15.2288 & 3.97118 \tabularnewline
211 & 16.6 & 18.4741 & -1.8741 \tabularnewline
212 & 11.2 & 9.43132 & 1.76868 \tabularnewline
213 & 15.25 & 15.7932 & -0.543224 \tabularnewline
214 & 11.9 & 11.4832 & 0.416836 \tabularnewline
215 & 13.2 & 9.43733 & 3.76267 \tabularnewline
216 & 16.35 & 17.2482 & -0.898198 \tabularnewline
217 & 12.4 & 9.15426 & 3.24574 \tabularnewline
218 & 15.85 & 10.6272 & 5.22282 \tabularnewline
219 & 18.15 & 19.3471 & -1.19711 \tabularnewline
220 & 11.15 & 8.77729 & 2.37271 \tabularnewline
221 & 15.65 & 10.099 & 5.55097 \tabularnewline
222 & 17.75 & 21.8793 & -4.1293 \tabularnewline
223 & 7.65 & 8.80838 & -1.15838 \tabularnewline
224 & 12.35 & 9.52995 & 2.82005 \tabularnewline
225 & 15.6 & 8.6986 & 6.9014 \tabularnewline
226 & 19.3 & 17.2002 & 2.0998 \tabularnewline
227 & 15.2 & 11.4997 & 3.70034 \tabularnewline
228 & 17.1 & 14.1724 & 2.92761 \tabularnewline
229 & 15.6 & 9.93086 & 5.66914 \tabularnewline
230 & 18.4 & 12.4342 & 5.9658 \tabularnewline
231 & 19.05 & 13.8973 & 5.15269 \tabularnewline
232 & 18.55 & 12.935 & 5.61496 \tabularnewline
233 & 19.1 & 18.4107 & 0.689302 \tabularnewline
234 & 13.1 & 12.8544 & 0.245643 \tabularnewline
235 & 12.85 & 17.1957 & -4.34566 \tabularnewline
236 & 9.5 & 18.3116 & -8.8116 \tabularnewline
237 & 4.5 & 5.50052 & -1.00052 \tabularnewline
238 & 11.85 & 10.9958 & 0.854164 \tabularnewline
239 & 13.6 & 16.6755 & -3.07546 \tabularnewline
240 & 11.7 & 11.8136 & -0.11364 \tabularnewline
241 & 12.4 & 12.6129 & -0.21295 \tabularnewline
242 & 13.35 & 13.6963 & -0.346344 \tabularnewline
243 & 11.4 & 9.53078 & 1.86922 \tabularnewline
244 & 14.9 & 8.23732 & 6.66268 \tabularnewline
245 & 19.9 & 22.5335 & -2.63353 \tabularnewline
246 & 11.2 & 8.8085 & 2.3915 \tabularnewline
247 & 14.6 & 9.94718 & 4.65282 \tabularnewline
248 & 17.6 & 16.0884 & 1.51156 \tabularnewline
249 & 14.05 & 10.9022 & 3.14782 \tabularnewline
250 & 16.1 & 16.2201 & -0.120077 \tabularnewline
251 & 13.35 & 14.1478 & -0.797836 \tabularnewline
252 & 11.85 & 13.417 & -1.56703 \tabularnewline
253 & 11.95 & 9.93516 & 2.01484 \tabularnewline
254 & 14.75 & 11.7126 & 3.03739 \tabularnewline
255 & 15.15 & 14.5201 & 0.629929 \tabularnewline
256 & 13.2 & 9.38424 & 3.81576 \tabularnewline
257 & 16.85 & 21.1153 & -4.26526 \tabularnewline
258 & 7.85 & 12.7341 & -4.88405 \tabularnewline
259 & 7.7 & 7.97845 & -0.278448 \tabularnewline
260 & 12.6 & 17.9297 & -5.32972 \tabularnewline
261 & 7.85 & 10.337 & -2.48705 \tabularnewline
262 & 10.95 & 10.8971 & 0.0529391 \tabularnewline
263 & 12.35 & 15.4377 & -3.08774 \tabularnewline
264 & 9.95 & 7.92493 & 2.02507 \tabularnewline
265 & 14.9 & 11.0242 & 3.87582 \tabularnewline
266 & 16.65 & 16.9599 & -0.30987 \tabularnewline
267 & 13.4 & 12.6642 & 0.735795 \tabularnewline
268 & 13.95 & 10.0572 & 3.89278 \tabularnewline
269 & 15.7 & 12.0869 & 3.61306 \tabularnewline
270 & 16.85 & 18.7415 & -1.89146 \tabularnewline
271 & 10.95 & 7.89662 & 3.05338 \tabularnewline
272 & 15.35 & 16.0386 & -0.688582 \tabularnewline
273 & 12.2 & 9.5569 & 2.6431 \tabularnewline
274 & 15.1 & 10.2306 & 4.86937 \tabularnewline
275 & 17.75 & 15.5866 & 2.1634 \tabularnewline
276 & 15.2 & 14.0069 & 1.19307 \tabularnewline
277 & 14.6 & 10.5305 & 4.06952 \tabularnewline
278 & 16.65 & 21.0833 & -4.43325 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266569&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]12.9[/C][C]13.0877[/C][C]-0.187704[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.8097[/C][C]-0.609688[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.3343[/C][C]-0.534341[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]13.0228[/C][C]-5.62275[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]13.4222[/C][C]-6.72217[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]12.7936[/C][C]-0.193599[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.0582[/C][C]2.74181[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.7867[/C][C]-0.486742[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.1822[/C][C]-1.08216[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.8241[/C][C]-6.62415[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.5292[/C][C]-1.12924[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]13.215[/C][C]-6.81497[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.7728[/C][C]-1.17279[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.173[/C][C]-1.17304[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]12.9957[/C][C]-6.69573[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.3942[/C][C]-1.09417[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.5963[/C][C]-0.696305[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.7113[/C][C]-3.41128[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]13.2475[/C][C]-3.64751[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.5699[/C][C]-2.5699[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]13.4037[/C][C]-7.00367[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]13.0237[/C][C]0.77627[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.6076[/C][C]-1.80759[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.4935[/C][C]1.30649[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]13.0572[/C][C]-1.35723[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.5891[/C][C]-1.68908[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.3151[/C][C]3.78487[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.2808[/C][C]0.1192[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]12.8005[/C][C]-2.90051[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.6277[/C][C]-1.12767[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.2195[/C][C]-3.91946[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.534[/C][C]-1.83403[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.3183[/C][C]-3.31831[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.1368[/C][C]-2.43677[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.5771[/C][C]-1.77705[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]13.4639[/C][C]-3.16389[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]13.0434[/C][C]-2.64341[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.9166[/C][C]-0.216587[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]13.448[/C][C]-4.14796[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.4559[/C][C]-0.655921[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.5138[/C][C]-7.61382[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.5118[/C][C]-2.11176[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]13.0453[/C][C]-0.0452896[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.4929[/C][C]-0.69294[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]12.332[/C][C]-0.0319622[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.9544[/C][C]-1.6544[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]13.4837[/C][C]-1.68367[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.868[/C][C]-4.96795[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]12.5225[/C][C]0.177471[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]13.5616[/C][C]-1.26157[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.4558[/C][C]-0.855816[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]12.934[/C][C]-6.23398[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.0922[/C][C]-2.19222[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.8136[/C][C]-0.713631[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.4217[/C][C]-0.121663[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]12.9676[/C][C]-2.86763[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.4577[/C][C]-6.75768[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.7386[/C][C]1.56143[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]13.0101[/C][C]-5.01007[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]13.4338[/C][C]-0.133791[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.6087[/C][C]-4.3087[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]12.8254[/C][C]-0.325402[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]12.0404[/C][C]-4.44044[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.1724[/C][C]2.72757[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]12.8189[/C][C]-3.61887[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]13.0782[/C][C]-3.97816[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.4274[/C][C]-1.3274[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.5008[/C][C]-0.50081[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]13.0151[/C][C]1.48486[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.9579[/C][C]-0.757857[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.0136[/C][C]-0.713601[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.6892[/C][C]-1.28916[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]13.3484[/C][C]-4.54839[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.5814[/C][C]1.0186[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.2433[/C][C]0.356656[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.284426[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]13.5586[/C][C]-0.558616[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]13.1491[/C][C]-0.549119[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]15.6814[/C][C]-2.48142[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]14.6204[/C][C]-4.72044[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]9.88361[/C][C]-2.18361[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]9.62297[/C][C]0.877035[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]15.5589[/C][C]-2.15885[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]18.7488[/C][C]-7.8488[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]7.47574[/C][C]-3.17574[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]11.605[/C][C]-1.30498[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]13.5455[/C][C]-1.74552[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]12.5165[/C][C]-1.31648[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]15.6352[/C][C]-4.2352[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]8.02293[/C][C]0.577067[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]13.6689[/C][C]-0.468916[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]19.4508[/C][C]-6.85081[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]8.65548[/C][C]-3.05548[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]13.8898[/C][C]-3.98978[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]14.3381[/C][C]-5.53805[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]11.3628[/C][C]-3.66278[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]14.5948[/C][C]-5.59477[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]8.89256[/C][C]-1.59256[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]10.6492[/C][C]0.750782[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]18.2991[/C][C]-4.69908[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]9.72096[/C][C]-1.82096[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]12.797[/C][C]-2.09699[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]14.1661[/C][C]-3.86613[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]11.4317[/C][C]-3.1317[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]8.89761[/C][C]0.702386[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]18.9099[/C][C]-4.70985[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]8.31842[/C][C]0.181584[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]21.3073[/C][C]-7.80735[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]11.1784[/C][C]-6.27844[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]10.4938[/C][C]-4.09382[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]11.0433[/C][C]-1.44331[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]13.2465[/C][C]-1.6465[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]20.5701[/C][C]-9.47009[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]4.09436[/C][C]0.255638[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]7.788[/C][C]4.912[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]12.8165[/C][C]5.28352[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]15.01[/C][C]2.84[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]17.2444[/C][C]-0.64435[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]9.29954[/C][C]3.30046[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]11.4101[/C][C]5.68993[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]16.0941[/C][C]3.0059[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]15.7295[/C][C]0.37051[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]8.67198[/C][C]4.67802[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]16.2377[/C][C]2.16229[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.0205[/C][C]-2.32053[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]10.9365[/C][C]-0.336529[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]8.91674[/C][C]3.68326[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]15.4474[/C][C]0.752562[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]7.84848[/C][C]5.75152[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]17.6619[/C][C]1.23805[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]12.339[/C][C]1.76103[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]11.0506[/C][C]3.44937[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.4603[/C][C]1.68967[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]12.8334[/C][C]1.91662[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]15.0782[/C][C]-0.278188[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]13.0144[/C][C]-0.564445[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]8.08368[/C][C]4.56632[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]22.0477[/C][C]-4.6977[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]3.05021[/C][C]5.54979[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]17.1513[/C][C]1.24869[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]17.1327[/C][C]-1.03272[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]7.1524[/C][C]4.4476[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]15.4131[/C][C]2.33693[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]10.6729[/C][C]4.57709[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]14.5901[/C][C]3.05985[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]12.5848[/C][C]3.76516[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]18.83[/C][C]-1.18003[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]13.0166[/C][C]0.583373[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]12.7074[/C][C]1.64261[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]9.9119[/C][C]4.8381[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]21.4166[/C][C]-3.16656[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]7.56988[/C][C]2.33012[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.3085[/C][C]4.69154[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]14.092[/C][C]4.15802[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]15.3933[/C][C]1.45673[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]14.3984[/C][C]0.20165[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]8.60348[/C][C]5.24652[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]16.5504[/C][C]2.39957[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]14.5032[/C][C]1.09678[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.7631[/C][C]-0.913089[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]6.43413[/C][C]5.31587[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.2894[/C][C]3.16057[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]11.7927[/C][C]4.10734[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]14.6717[/C][C]2.42833[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]10.9061[/C][C]5.19392[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]21.3176[/C][C]-1.41762[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]5.03753[/C][C]5.91247[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]16.8137[/C][C]1.63634[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]13.6784[/C][C]1.42157[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]16.1645[/C][C]-1.1645[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]8.41871[/C][C]2.93129[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]11.0588[/C][C]4.89116[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]16.3146[/C][C]1.78537[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]13.1028[/C][C]1.49716[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.4838[/C][C]1.91622[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]10.118[/C][C]5.28203[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]17.9402[/C][C]-0.34021[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]6.42591[/C][C]6.92409[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]16.7108[/C][C]2.38922[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]20.1293[/C][C]-4.77934[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]7.78388[/C][C]-0.183884[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]12.8377[/C][C]0.562267[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]8.47215[/C][C]5.42785[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]16.4171[/C][C]2.68293[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]14.9849[/C][C]0.26513[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]9.80087[/C][C]3.09913[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]11.8997[/C][C]4.2003[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]17.263[/C][C]0.0870189[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]14.2237[/C][C]-1.07367[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]12.4729[/C][C]-0.322925[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]14.9846[/C][C]-2.38464[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]7.34914[/C][C]3.00086[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]19.0481[/C][C]-3.64809[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]4.24726[/C][C]5.35274[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]17.7035[/C][C]0.496485[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.4975[/C][C]1.10249[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]12.7561[/C][C]2.09393[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]13.4756[/C][C]1.27445[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]12.2042[/C][C]1.89583[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.8537[/C][C]3.04625[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]11.6246[/C][C]4.62543[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]19.6839[/C][C]-0.433928[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.0935[/C][C]0.506467[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]10.8217[/C][C]2.77835[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]14.835[/C][C]0.814963[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]10.0964[/C][C]2.65364[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]17.9227[/C][C]-3.32274[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]10.8679[/C][C]-1.01791[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]5.6219[/C][C]7.0281[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]15.2288[/C][C]3.97118[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]18.4741[/C][C]-1.8741[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]9.43132[/C][C]1.76868[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]15.7932[/C][C]-0.543224[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]11.4832[/C][C]0.416836[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]9.43733[/C][C]3.76267[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]17.2482[/C][C]-0.898198[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.15426[/C][C]3.24574[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]10.6272[/C][C]5.22282[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]19.3471[/C][C]-1.19711[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]8.77729[/C][C]2.37271[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]10.099[/C][C]5.55097[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]21.8793[/C][C]-4.1293[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]8.80838[/C][C]-1.15838[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]9.52995[/C][C]2.82005[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]8.6986[/C][C]6.9014[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]17.2002[/C][C]2.0998[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]11.4997[/C][C]3.70034[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]14.1724[/C][C]2.92761[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]9.93086[/C][C]5.66914[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]12.4342[/C][C]5.9658[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]13.8973[/C][C]5.15269[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]12.935[/C][C]5.61496[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]18.4107[/C][C]0.689302[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]12.8544[/C][C]0.245643[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]17.1957[/C][C]-4.34566[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]18.3116[/C][C]-8.8116[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]5.50052[/C][C]-1.00052[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]10.9958[/C][C]0.854164[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]16.6755[/C][C]-3.07546[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]11.8136[/C][C]-0.11364[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]12.6129[/C][C]-0.21295[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]13.6963[/C][C]-0.346344[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]9.53078[/C][C]1.86922[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]8.23732[/C][C]6.66268[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]22.5335[/C][C]-2.63353[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]8.8085[/C][C]2.3915[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]9.94718[/C][C]4.65282[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]16.0884[/C][C]1.51156[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]10.9022[/C][C]3.14782[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]16.2201[/C][C]-0.120077[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]14.1478[/C][C]-0.797836[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]13.417[/C][C]-1.56703[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]9.93516[/C][C]2.01484[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]11.7126[/C][C]3.03739[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]14.5201[/C][C]0.629929[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]9.38424[/C][C]3.81576[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.1153[/C][C]-4.26526[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]12.7341[/C][C]-4.88405[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]7.97845[/C][C]-0.278448[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]17.9297[/C][C]-5.32972[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]10.337[/C][C]-2.48705[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]10.8971[/C][C]0.0529391[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]15.4377[/C][C]-3.08774[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]7.92493[/C][C]2.02507[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]11.0242[/C][C]3.87582[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.9599[/C][C]-0.30987[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]12.6642[/C][C]0.735795[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]10.0572[/C][C]3.89278[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]12.0869[/C][C]3.61306[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]18.7415[/C][C]-1.89146[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]7.89662[/C][C]3.05338[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]16.0386[/C][C]-0.688582[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]9.5569[/C][C]2.6431[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]10.2306[/C][C]4.86937[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.5866[/C][C]2.1634[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]14.0069[/C][C]1.19307[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]10.5305[/C][C]4.06952[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]21.0833[/C][C]-4.43325[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266569&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266569&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
112.913.0877-0.187704
212.212.8097-0.609688
312.813.3343-0.534341
47.413.0228-5.62275
56.713.4222-6.72217
612.612.7936-0.193599
714.812.05822.74181
813.313.7867-0.486742
911.112.1822-1.08216
108.214.8241-6.62415
1111.412.5292-1.12924
126.413.215-6.81497
1310.611.7728-1.17279
141213.173-1.17304
156.312.9957-6.69573
1611.312.3942-1.09417
1711.912.5963-0.696305
189.312.7113-3.41128
199.613.2475-3.64751
201012.5699-2.5699
216.413.4037-7.00367
2213.813.02370.77627
2310.812.6076-1.80759
2413.812.49351.30649
2511.713.0572-1.35723
2610.912.5891-1.68908
2716.112.31513.78487
2813.413.28080.1192
299.912.8005-2.90051
3011.512.6277-1.12767
318.312.2195-3.91946
3211.713.534-1.83403
33912.3183-3.31831
349.712.1368-2.43677
3510.812.5771-1.77705
3610.313.4639-3.16389
3710.413.0434-2.64341
3812.712.9166-0.216587
399.313.448-4.14796
4011.812.4559-0.655921
415.913.5138-7.61382
4211.413.5118-2.11176
431313.0453-0.0452896
4410.811.4929-0.69294
4512.312.332-0.0319622
4611.312.9544-1.6544
4711.813.4837-1.68367
487.912.868-4.96795
4912.712.52250.177471
5012.313.5616-1.26157
5111.612.4558-0.855816
526.712.934-6.23398
5310.913.0922-2.19222
5412.112.8136-0.713631
5513.313.4217-0.121663
5610.112.9676-2.86763
575.712.4577-6.75768
5814.312.73861.56143
59813.0101-5.01007
6013.313.4338-0.133791
619.313.6087-4.3087
6212.512.8254-0.325402
637.612.0404-4.44044
6415.913.17242.72757
659.212.8189-3.61887
669.113.0782-3.97816
6711.112.4274-1.3274
681313.5008-0.50081
6914.513.01511.48486
7012.212.9579-0.757857
7112.313.0136-0.713601
7211.412.6892-1.28916
738.813.3484-4.54839
7414.613.58141.0186
7512.612.24330.356656
76NANA0.284426
771313.5586-0.558616
7812.613.1491-0.549119
7913.215.6814-2.48142
809.914.6204-4.72044
817.79.88361-2.18361
8210.59.622970.877035
8313.415.5589-2.15885
8410.918.7488-7.8488
854.37.47574-3.17574
8610.311.605-1.30498
8711.813.5455-1.74552
8811.212.5165-1.31648
8911.415.6352-4.2352
908.68.022930.577067
9113.213.6689-0.468916
9212.619.4508-6.85081
935.68.65548-3.05548
949.913.8898-3.98978
958.814.3381-5.53805
967.711.3628-3.66278
97914.5948-5.59477
987.38.89256-1.59256
9911.410.64920.750782
10013.618.2991-4.69908
1017.99.72096-1.82096
10210.712.797-2.09699
10310.314.1661-3.86613
1048.311.4317-3.1317
1059.68.897610.702386
10614.218.9099-4.70985
1078.58.318420.181584
10813.521.3073-7.80735
1094.911.1784-6.27844
1106.410.4938-4.09382
1119.611.0433-1.44331
11211.613.2465-1.6465
11311.120.5701-9.47009
1144.354.094360.255638
11512.77.7884.912
11618.112.81655.28352
11717.8515.012.84
11816.617.2444-0.64435
11912.69.299543.30046
12017.111.41015.68993
12119.116.09413.0059
12216.115.72950.37051
12313.358.671984.67802
12418.416.23772.16229
12514.717.0205-2.32053
12610.610.9365-0.336529
12712.68.916743.68326
12816.215.44740.752562
12913.67.848485.75152
13018.917.66191.23805
13114.112.3391.76103
13214.511.05063.44937
13316.1514.46031.68967
13414.7512.83341.91662
13514.815.0782-0.278188
13612.4513.0144-0.564445
13712.658.083684.56632
13817.3522.0477-4.6977
1398.63.050215.54979
14018.417.15131.24869
14116.117.1327-1.03272
14211.67.15244.4476
14317.7515.41312.33693
14415.2510.67294.57709
14517.6514.59013.05985
14616.3512.58483.76516
14717.6518.83-1.18003
14813.613.01660.583373
14914.3512.70741.64261
15014.759.91194.8381
15118.2521.4166-3.16656
1529.97.569882.33012
1531611.30854.69154
15418.2514.0924.15802
15516.8515.39331.45673
15614.614.39840.20165
15713.858.603485.24652
15818.9516.55042.39957
15915.614.50321.09678
16014.8515.7631-0.913089
16111.756.434135.31587
16218.4515.28943.16057
16315.911.79274.10734
16417.114.67172.42833
16516.110.90615.19392
16619.921.3176-1.41762
16710.955.037535.91247
16818.4516.81371.63634
16915.113.67841.42157
1701516.1645-1.1645
17111.358.418712.93129
17215.9511.05884.89116
17318.116.31461.78537
17414.613.10281.49716
17515.413.48381.91622
17615.410.1185.28203
17717.617.9402-0.34021
17813.356.425916.92409
17919.116.71082.38922
18015.3520.1293-4.77934
1817.67.78388-0.183884
18213.412.83770.562267
18313.98.472155.42785
18419.116.41712.68293
18515.2514.98490.26513
18612.99.800873.09913
18716.111.89974.2003
18817.3517.2630.0870189
18913.1514.2237-1.07367
19012.1512.4729-0.322925
19112.614.9846-2.38464
19210.357.349143.00086
19315.419.0481-3.64809
1949.64.247265.35274
19518.217.70350.496485
19613.612.49751.10249
19714.8512.75612.09393
19814.7513.47561.27445
19914.112.20421.89583
20014.911.85373.04625
20116.2511.62464.62543
20219.2519.6839-0.433928
20313.613.09350.506467
20413.610.82172.77835
20515.6514.8350.814963
20612.7510.09642.65364
20714.617.9227-3.32274
2089.8510.8679-1.01791
20912.655.62197.0281
21019.215.22883.97118
21116.618.4741-1.8741
21211.29.431321.76868
21315.2515.7932-0.543224
21411.911.48320.416836
21513.29.437333.76267
21616.3517.2482-0.898198
21712.49.154263.24574
21815.8510.62725.22282
21918.1519.3471-1.19711
22011.158.777292.37271
22115.6510.0995.55097
22217.7521.8793-4.1293
2237.658.80838-1.15838
22412.359.529952.82005
22515.68.69866.9014
22619.317.20022.0998
22715.211.49973.70034
22817.114.17242.92761
22915.69.930865.66914
23018.412.43425.9658
23119.0513.89735.15269
23218.5512.9355.61496
23319.118.41070.689302
23413.112.85440.245643
23512.8517.1957-4.34566
2369.518.3116-8.8116
2374.55.50052-1.00052
23811.8510.99580.854164
23913.616.6755-3.07546
24011.711.8136-0.11364
24112.412.6129-0.21295
24213.3513.6963-0.346344
24311.49.530781.86922
24414.98.237326.66268
24519.922.5335-2.63353
24611.28.80852.3915
24714.69.947184.65282
24817.616.08841.51156
24914.0510.90223.14782
25016.116.2201-0.120077
25113.3514.1478-0.797836
25211.8513.417-1.56703
25311.959.935162.01484
25414.7511.71263.03739
25515.1514.52010.629929
25613.29.384243.81576
25716.8521.1153-4.26526
2587.8512.7341-4.88405
2597.77.97845-0.278448
26012.617.9297-5.32972
2617.8510.337-2.48705
26210.9510.89710.0529391
26312.3515.4377-3.08774
2649.957.924932.02507
26514.911.02423.87582
26616.6516.9599-0.30987
26713.412.66420.735795
26813.9510.05723.89278
26915.712.08693.61306
27016.8518.7415-1.89146
27110.957.896623.05338
27215.3516.0386-0.688582
27312.29.55692.6431
27415.110.23064.86937
27517.7515.58662.1634
27615.214.00691.19307
27714.610.53054.06952
27816.6521.0833-4.43325
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.0979610.1959220.902039
120.2238220.4476440.776178
130.1601350.3202690.839865
140.1504530.3009060.849547
150.181380.3627610.81862
160.1497890.2995780.850211
170.1068790.2137580.893121
180.07870250.1574050.921297
190.05291540.1058310.947085
200.03213010.06426020.96787
210.02234510.04469030.977655
220.01422870.02845740.985771
230.007881220.01576240.992119
240.00980070.01960140.990199
250.006455340.01291070.993545
260.003600140.007200270.9964
270.002953030.005906060.997047
280.001709480.003418950.998291
290.0009608220.001921640.999039
300.0005024270.001004850.999498
310.0005321070.001064210.999468
320.0002940920.0005881840.999706
330.0003896880.0007793770.99961
340.009768780.01953760.990231
350.0064920.0129840.993508
360.004655870.009311730.995344
370.003008510.006017020.996991
380.001858590.003717180.998141
390.001407470.002814940.998593
400.0008923440.001784690.999108
410.002010290.004020580.99799
420.00163860.003277210.998361
430.001666760.003333510.998333
440.001619170.003238330.998381
450.001028490.002056980.998972
460.0007541240.001508250.999246
470.0005477950.001095590.999452
480.000465530.0009310590.999534
490.0003990030.0007980060.999601
500.0004570090.0009140170.999543
510.0003186180.0006372360.999681
520.001199980.002399960.9988
530.0008487310.001697460.999151
540.0007658870.001531770.999234
550.000850610.001701220.999149
560.0006136050.001227210.999386
570.001852260.003704530.998148
580.001410840.002821690.998589
590.001472090.002944190.998528
600.001844530.003689050.998155
610.001507970.003015950.998492
620.001239260.002478510.998761
630.002710880.005421770.997289
640.004963740.009927490.995036
650.004642560.009285130.995357
660.004262950.00852590.995737
670.003118570.006237150.996881
680.002814280.005628560.997186
690.003088740.006177490.996911
700.002393010.004786010.997607
710.00172740.003454790.998273
720.001254560.002509110.998745
730.001274140.002548270.998726
740.001457260.002914530.998543
750.001090730.002181470.998909
760.0009840870.001968170.999016
770.0007573380.001514680.999243
780.0006566390.001313280.999343
790.0005323850.001064770.999468
800.0006326660.001265330.999367
810.0004689490.0009378970.999531
820.0004173190.0008346380.999583
830.0003149940.0006299880.999685
840.001703940.003407890.998296
850.001410160.002820310.99859
860.00107760.00215520.998922
870.0008143890.001628780.999186
880.0006354880.001270980.999365
890.0006845810.001369160.999315
900.0006104780.001220960.99939
910.0004718720.0009437440.999528
920.001448850.00289770.998551
930.001232660.002465330.998767
940.001188270.002376550.998812
950.001483530.002967060.998516
960.001447870.002895740.998552
970.002150110.004300220.99785
980.001689210.003378410.998311
990.001594070.003188130.998406
1000.001891790.003783580.998108
1010.001550340.003100670.99845
1020.001305530.002611060.998694
1030.001482120.002964230.998518
1040.001319650.00263930.99868
1050.001315820.002631650.998684
1060.001517210.003034420.998483
1070.001484330.002968660.998516
1080.005515420.01103080.994485
1090.01043920.02087830.989561
1100.01129370.02258740.988706
1110.01002580.02005160.989974
1120.008791460.01758290.991209
1130.05077920.1015580.949221
1140.05836390.1167280.941636
1150.1083820.2167630.891618
1160.1846140.3692280.815386
1170.2281790.4563570.771821
1180.2088830.4177660.791117
1190.2656960.5313910.734304
1200.3819940.7639890.618006
1210.4077160.8154310.592284
1220.3997510.7995030.600249
1230.4931370.9862750.506863
1240.4935770.9871530.506423
1250.4933590.9867180.506641
1260.4680170.9360330.531983
1270.5065670.9868650.493433
1280.4842760.9685510.515724
1290.5904960.8190070.409504
1300.5796610.8406780.420339
1310.567840.8643190.43216
1320.5825570.8348870.417443
1330.5652890.8694210.434711
1340.5585290.8829420.441471
1350.5416910.9166180.458309
1360.5178590.9642820.482141
1370.5641980.8716030.435802
1380.611760.7764790.38824
1390.696220.607560.30378
1400.6810360.6379270.318964
1410.6544670.6910660.345533
1420.6928960.6142090.307104
1430.683450.63310.31655
1440.7163290.5673410.283671
1450.7173040.5653930.282696
1460.7310080.5379840.268992
1470.7100590.5798820.289941
1480.6861070.6277860.313893
1490.6706370.6587270.329363
1500.7183550.563290.281645
1510.7198980.5602050.280102
1520.7049650.5900690.295035
1530.7337480.5325040.266252
1540.7455810.5088390.254419
1550.7251020.5497970.274898
1560.6988820.6022360.301118
1570.7429380.5141230.257062
1580.7312710.5374580.268729
1590.7054850.5890310.294515
1600.6888860.6222280.311114
1610.7322150.535570.267785
1620.7274660.5450670.272534
1630.7364220.5271560.263578
1640.7201390.5597220.279861
1650.7608970.4782070.239103
1660.7406410.5187180.259359
1670.7928490.4143020.207151
1680.7712010.4575980.228799
1690.7469730.5060540.253027
1700.7323890.5352220.267611
1710.7220550.555890.277945
1720.7559590.4880830.244041
1730.7337460.5325080.266254
1740.7099890.5800220.290011
1750.6867490.6265020.313251
1760.7215870.5568270.278413
1770.6913140.6173730.308686
1780.7656730.4686550.234327
1790.7466540.5066920.253346
1800.7949590.4100810.205041
1810.7678790.4642430.232121
1820.7388680.5222640.261132
1830.7927670.4144660.207233
1840.7786590.4426830.221341
1850.7530870.4938260.246913
1860.7425480.5149040.257452
1870.7571080.4857840.242892
1880.7266450.546710.273355
1890.6989620.6020760.301038
1900.6672410.6655180.332759
1910.6646240.6707520.335376
1920.6479570.7040870.352043
1930.6752990.6494010.324701
1940.7066060.5867890.293394
1950.6756530.6486940.324347
1960.6417430.7165140.358257
1970.6143330.7713340.385667
1980.5802530.8394940.419747
1990.5471050.9057910.452895
2000.525460.949080.47454
2010.6147650.770470.385235
2020.5762920.8474150.423708
2030.5388550.9222910.461145
2040.5190150.961970.480985
2050.4861080.9722160.513892
2060.4640360.9280730.535964
2070.5031570.9936870.496843
2080.4692890.9385790.530711
2090.5231440.9537110.476856
2100.5141350.9717290.485865
2110.497140.994280.50286
2120.4641640.9283280.535836
2130.4387420.8774840.561258
2140.4005590.8011190.599441
2150.384440.7688790.61556
2160.3462070.6924150.653793
2170.3305070.6610140.669493
2180.3571620.7143250.642838
2190.3328680.6657360.667132
2200.311480.622960.68852
2210.3312170.6624340.668783
2220.4103550.8207110.589645
2230.3691760.7383510.630824
2240.3478590.6957170.652141
2250.4585220.9170450.541478
2260.4255190.8510380.574481
2270.409450.81890.59055
2280.3795470.7590930.620453
2290.4299310.8598620.570069
2300.5219670.9560660.478033
2310.6118650.7762710.388135
2320.6845010.6309980.315499
2330.6398060.7203880.360194
2340.5908070.8183860.409193
2350.5824370.8351250.417563
2360.8498980.3002050.150102
2370.8252190.3495610.174781
2380.7883470.4233060.211653
2390.7907880.4184240.209212
2400.7765850.446830.223415
2410.7317120.5365760.268288
2420.6922870.6154260.307713
2430.6514710.6970580.348529
2440.7891390.4217220.210861
2450.7572060.4855890.242794
2460.711060.577880.28894
2470.7023330.5953350.297667
2480.6474590.7050820.352541
2490.6188010.7623970.381199
2500.5546560.8906880.445344
2510.5044410.9911180.495559
2520.4418020.8836040.558198
2530.3793650.758730.620635
2540.5642650.871470.435735
2550.6550.690.345
2560.6233490.7533020.376651
2570.7144720.5710560.285528
2580.8814810.2370380.118519
2590.8298910.3402180.170109
2600.9471910.1056180.0528088
2610.9418990.1162010.0581005
2620.9353680.1292650.0646323
2630.8961160.2077680.103884
2640.8514450.297110.148555
2650.8183760.3632480.181624
2660.9266590.1466820.0733411
2670.8493630.3012740.150637
2680.9897210.02055840.0102792

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.097961 & 0.195922 & 0.902039 \tabularnewline
12 & 0.223822 & 0.447644 & 0.776178 \tabularnewline
13 & 0.160135 & 0.320269 & 0.839865 \tabularnewline
14 & 0.150453 & 0.300906 & 0.849547 \tabularnewline
15 & 0.18138 & 0.362761 & 0.81862 \tabularnewline
16 & 0.149789 & 0.299578 & 0.850211 \tabularnewline
17 & 0.106879 & 0.213758 & 0.893121 \tabularnewline
18 & 0.0787025 & 0.157405 & 0.921297 \tabularnewline
19 & 0.0529154 & 0.105831 & 0.947085 \tabularnewline
20 & 0.0321301 & 0.0642602 & 0.96787 \tabularnewline
21 & 0.0223451 & 0.0446903 & 0.977655 \tabularnewline
22 & 0.0142287 & 0.0284574 & 0.985771 \tabularnewline
23 & 0.00788122 & 0.0157624 & 0.992119 \tabularnewline
24 & 0.0098007 & 0.0196014 & 0.990199 \tabularnewline
25 & 0.00645534 & 0.0129107 & 0.993545 \tabularnewline
26 & 0.00360014 & 0.00720027 & 0.9964 \tabularnewline
27 & 0.00295303 & 0.00590606 & 0.997047 \tabularnewline
28 & 0.00170948 & 0.00341895 & 0.998291 \tabularnewline
29 & 0.000960822 & 0.00192164 & 0.999039 \tabularnewline
30 & 0.000502427 & 0.00100485 & 0.999498 \tabularnewline
31 & 0.000532107 & 0.00106421 & 0.999468 \tabularnewline
32 & 0.000294092 & 0.000588184 & 0.999706 \tabularnewline
33 & 0.000389688 & 0.000779377 & 0.99961 \tabularnewline
34 & 0.00976878 & 0.0195376 & 0.990231 \tabularnewline
35 & 0.006492 & 0.012984 & 0.993508 \tabularnewline
36 & 0.00465587 & 0.00931173 & 0.995344 \tabularnewline
37 & 0.00300851 & 0.00601702 & 0.996991 \tabularnewline
38 & 0.00185859 & 0.00371718 & 0.998141 \tabularnewline
39 & 0.00140747 & 0.00281494 & 0.998593 \tabularnewline
40 & 0.000892344 & 0.00178469 & 0.999108 \tabularnewline
41 & 0.00201029 & 0.00402058 & 0.99799 \tabularnewline
42 & 0.0016386 & 0.00327721 & 0.998361 \tabularnewline
43 & 0.00166676 & 0.00333351 & 0.998333 \tabularnewline
44 & 0.00161917 & 0.00323833 & 0.998381 \tabularnewline
45 & 0.00102849 & 0.00205698 & 0.998972 \tabularnewline
46 & 0.000754124 & 0.00150825 & 0.999246 \tabularnewline
47 & 0.000547795 & 0.00109559 & 0.999452 \tabularnewline
48 & 0.00046553 & 0.000931059 & 0.999534 \tabularnewline
49 & 0.000399003 & 0.000798006 & 0.999601 \tabularnewline
50 & 0.000457009 & 0.000914017 & 0.999543 \tabularnewline
51 & 0.000318618 & 0.000637236 & 0.999681 \tabularnewline
52 & 0.00119998 & 0.00239996 & 0.9988 \tabularnewline
53 & 0.000848731 & 0.00169746 & 0.999151 \tabularnewline
54 & 0.000765887 & 0.00153177 & 0.999234 \tabularnewline
55 & 0.00085061 & 0.00170122 & 0.999149 \tabularnewline
56 & 0.000613605 & 0.00122721 & 0.999386 \tabularnewline
57 & 0.00185226 & 0.00370453 & 0.998148 \tabularnewline
58 & 0.00141084 & 0.00282169 & 0.998589 \tabularnewline
59 & 0.00147209 & 0.00294419 & 0.998528 \tabularnewline
60 & 0.00184453 & 0.00368905 & 0.998155 \tabularnewline
61 & 0.00150797 & 0.00301595 & 0.998492 \tabularnewline
62 & 0.00123926 & 0.00247851 & 0.998761 \tabularnewline
63 & 0.00271088 & 0.00542177 & 0.997289 \tabularnewline
64 & 0.00496374 & 0.00992749 & 0.995036 \tabularnewline
65 & 0.00464256 & 0.00928513 & 0.995357 \tabularnewline
66 & 0.00426295 & 0.0085259 & 0.995737 \tabularnewline
67 & 0.00311857 & 0.00623715 & 0.996881 \tabularnewline
68 & 0.00281428 & 0.00562856 & 0.997186 \tabularnewline
69 & 0.00308874 & 0.00617749 & 0.996911 \tabularnewline
70 & 0.00239301 & 0.00478601 & 0.997607 \tabularnewline
71 & 0.0017274 & 0.00345479 & 0.998273 \tabularnewline
72 & 0.00125456 & 0.00250911 & 0.998745 \tabularnewline
73 & 0.00127414 & 0.00254827 & 0.998726 \tabularnewline
74 & 0.00145726 & 0.00291453 & 0.998543 \tabularnewline
75 & 0.00109073 & 0.00218147 & 0.998909 \tabularnewline
76 & 0.000984087 & 0.00196817 & 0.999016 \tabularnewline
77 & 0.000757338 & 0.00151468 & 0.999243 \tabularnewline
78 & 0.000656639 & 0.00131328 & 0.999343 \tabularnewline
79 & 0.000532385 & 0.00106477 & 0.999468 \tabularnewline
80 & 0.000632666 & 0.00126533 & 0.999367 \tabularnewline
81 & 0.000468949 & 0.000937897 & 0.999531 \tabularnewline
82 & 0.000417319 & 0.000834638 & 0.999583 \tabularnewline
83 & 0.000314994 & 0.000629988 & 0.999685 \tabularnewline
84 & 0.00170394 & 0.00340789 & 0.998296 \tabularnewline
85 & 0.00141016 & 0.00282031 & 0.99859 \tabularnewline
86 & 0.0010776 & 0.0021552 & 0.998922 \tabularnewline
87 & 0.000814389 & 0.00162878 & 0.999186 \tabularnewline
88 & 0.000635488 & 0.00127098 & 0.999365 \tabularnewline
89 & 0.000684581 & 0.00136916 & 0.999315 \tabularnewline
90 & 0.000610478 & 0.00122096 & 0.99939 \tabularnewline
91 & 0.000471872 & 0.000943744 & 0.999528 \tabularnewline
92 & 0.00144885 & 0.0028977 & 0.998551 \tabularnewline
93 & 0.00123266 & 0.00246533 & 0.998767 \tabularnewline
94 & 0.00118827 & 0.00237655 & 0.998812 \tabularnewline
95 & 0.00148353 & 0.00296706 & 0.998516 \tabularnewline
96 & 0.00144787 & 0.00289574 & 0.998552 \tabularnewline
97 & 0.00215011 & 0.00430022 & 0.99785 \tabularnewline
98 & 0.00168921 & 0.00337841 & 0.998311 \tabularnewline
99 & 0.00159407 & 0.00318813 & 0.998406 \tabularnewline
100 & 0.00189179 & 0.00378358 & 0.998108 \tabularnewline
101 & 0.00155034 & 0.00310067 & 0.99845 \tabularnewline
102 & 0.00130553 & 0.00261106 & 0.998694 \tabularnewline
103 & 0.00148212 & 0.00296423 & 0.998518 \tabularnewline
104 & 0.00131965 & 0.0026393 & 0.99868 \tabularnewline
105 & 0.00131582 & 0.00263165 & 0.998684 \tabularnewline
106 & 0.00151721 & 0.00303442 & 0.998483 \tabularnewline
107 & 0.00148433 & 0.00296866 & 0.998516 \tabularnewline
108 & 0.00551542 & 0.0110308 & 0.994485 \tabularnewline
109 & 0.0104392 & 0.0208783 & 0.989561 \tabularnewline
110 & 0.0112937 & 0.0225874 & 0.988706 \tabularnewline
111 & 0.0100258 & 0.0200516 & 0.989974 \tabularnewline
112 & 0.00879146 & 0.0175829 & 0.991209 \tabularnewline
113 & 0.0507792 & 0.101558 & 0.949221 \tabularnewline
114 & 0.0583639 & 0.116728 & 0.941636 \tabularnewline
115 & 0.108382 & 0.216763 & 0.891618 \tabularnewline
116 & 0.184614 & 0.369228 & 0.815386 \tabularnewline
117 & 0.228179 & 0.456357 & 0.771821 \tabularnewline
118 & 0.208883 & 0.417766 & 0.791117 \tabularnewline
119 & 0.265696 & 0.531391 & 0.734304 \tabularnewline
120 & 0.381994 & 0.763989 & 0.618006 \tabularnewline
121 & 0.407716 & 0.815431 & 0.592284 \tabularnewline
122 & 0.399751 & 0.799503 & 0.600249 \tabularnewline
123 & 0.493137 & 0.986275 & 0.506863 \tabularnewline
124 & 0.493577 & 0.987153 & 0.506423 \tabularnewline
125 & 0.493359 & 0.986718 & 0.506641 \tabularnewline
126 & 0.468017 & 0.936033 & 0.531983 \tabularnewline
127 & 0.506567 & 0.986865 & 0.493433 \tabularnewline
128 & 0.484276 & 0.968551 & 0.515724 \tabularnewline
129 & 0.590496 & 0.819007 & 0.409504 \tabularnewline
130 & 0.579661 & 0.840678 & 0.420339 \tabularnewline
131 & 0.56784 & 0.864319 & 0.43216 \tabularnewline
132 & 0.582557 & 0.834887 & 0.417443 \tabularnewline
133 & 0.565289 & 0.869421 & 0.434711 \tabularnewline
134 & 0.558529 & 0.882942 & 0.441471 \tabularnewline
135 & 0.541691 & 0.916618 & 0.458309 \tabularnewline
136 & 0.517859 & 0.964282 & 0.482141 \tabularnewline
137 & 0.564198 & 0.871603 & 0.435802 \tabularnewline
138 & 0.61176 & 0.776479 & 0.38824 \tabularnewline
139 & 0.69622 & 0.60756 & 0.30378 \tabularnewline
140 & 0.681036 & 0.637927 & 0.318964 \tabularnewline
141 & 0.654467 & 0.691066 & 0.345533 \tabularnewline
142 & 0.692896 & 0.614209 & 0.307104 \tabularnewline
143 & 0.68345 & 0.6331 & 0.31655 \tabularnewline
144 & 0.716329 & 0.567341 & 0.283671 \tabularnewline
145 & 0.717304 & 0.565393 & 0.282696 \tabularnewline
146 & 0.731008 & 0.537984 & 0.268992 \tabularnewline
147 & 0.710059 & 0.579882 & 0.289941 \tabularnewline
148 & 0.686107 & 0.627786 & 0.313893 \tabularnewline
149 & 0.670637 & 0.658727 & 0.329363 \tabularnewline
150 & 0.718355 & 0.56329 & 0.281645 \tabularnewline
151 & 0.719898 & 0.560205 & 0.280102 \tabularnewline
152 & 0.704965 & 0.590069 & 0.295035 \tabularnewline
153 & 0.733748 & 0.532504 & 0.266252 \tabularnewline
154 & 0.745581 & 0.508839 & 0.254419 \tabularnewline
155 & 0.725102 & 0.549797 & 0.274898 \tabularnewline
156 & 0.698882 & 0.602236 & 0.301118 \tabularnewline
157 & 0.742938 & 0.514123 & 0.257062 \tabularnewline
158 & 0.731271 & 0.537458 & 0.268729 \tabularnewline
159 & 0.705485 & 0.589031 & 0.294515 \tabularnewline
160 & 0.688886 & 0.622228 & 0.311114 \tabularnewline
161 & 0.732215 & 0.53557 & 0.267785 \tabularnewline
162 & 0.727466 & 0.545067 & 0.272534 \tabularnewline
163 & 0.736422 & 0.527156 & 0.263578 \tabularnewline
164 & 0.720139 & 0.559722 & 0.279861 \tabularnewline
165 & 0.760897 & 0.478207 & 0.239103 \tabularnewline
166 & 0.740641 & 0.518718 & 0.259359 \tabularnewline
167 & 0.792849 & 0.414302 & 0.207151 \tabularnewline
168 & 0.771201 & 0.457598 & 0.228799 \tabularnewline
169 & 0.746973 & 0.506054 & 0.253027 \tabularnewline
170 & 0.732389 & 0.535222 & 0.267611 \tabularnewline
171 & 0.722055 & 0.55589 & 0.277945 \tabularnewline
172 & 0.755959 & 0.488083 & 0.244041 \tabularnewline
173 & 0.733746 & 0.532508 & 0.266254 \tabularnewline
174 & 0.709989 & 0.580022 & 0.290011 \tabularnewline
175 & 0.686749 & 0.626502 & 0.313251 \tabularnewline
176 & 0.721587 & 0.556827 & 0.278413 \tabularnewline
177 & 0.691314 & 0.617373 & 0.308686 \tabularnewline
178 & 0.765673 & 0.468655 & 0.234327 \tabularnewline
179 & 0.746654 & 0.506692 & 0.253346 \tabularnewline
180 & 0.794959 & 0.410081 & 0.205041 \tabularnewline
181 & 0.767879 & 0.464243 & 0.232121 \tabularnewline
182 & 0.738868 & 0.522264 & 0.261132 \tabularnewline
183 & 0.792767 & 0.414466 & 0.207233 \tabularnewline
184 & 0.778659 & 0.442683 & 0.221341 \tabularnewline
185 & 0.753087 & 0.493826 & 0.246913 \tabularnewline
186 & 0.742548 & 0.514904 & 0.257452 \tabularnewline
187 & 0.757108 & 0.485784 & 0.242892 \tabularnewline
188 & 0.726645 & 0.54671 & 0.273355 \tabularnewline
189 & 0.698962 & 0.602076 & 0.301038 \tabularnewline
190 & 0.667241 & 0.665518 & 0.332759 \tabularnewline
191 & 0.664624 & 0.670752 & 0.335376 \tabularnewline
192 & 0.647957 & 0.704087 & 0.352043 \tabularnewline
193 & 0.675299 & 0.649401 & 0.324701 \tabularnewline
194 & 0.706606 & 0.586789 & 0.293394 \tabularnewline
195 & 0.675653 & 0.648694 & 0.324347 \tabularnewline
196 & 0.641743 & 0.716514 & 0.358257 \tabularnewline
197 & 0.614333 & 0.771334 & 0.385667 \tabularnewline
198 & 0.580253 & 0.839494 & 0.419747 \tabularnewline
199 & 0.547105 & 0.905791 & 0.452895 \tabularnewline
200 & 0.52546 & 0.94908 & 0.47454 \tabularnewline
201 & 0.614765 & 0.77047 & 0.385235 \tabularnewline
202 & 0.576292 & 0.847415 & 0.423708 \tabularnewline
203 & 0.538855 & 0.922291 & 0.461145 \tabularnewline
204 & 0.519015 & 0.96197 & 0.480985 \tabularnewline
205 & 0.486108 & 0.972216 & 0.513892 \tabularnewline
206 & 0.464036 & 0.928073 & 0.535964 \tabularnewline
207 & 0.503157 & 0.993687 & 0.496843 \tabularnewline
208 & 0.469289 & 0.938579 & 0.530711 \tabularnewline
209 & 0.523144 & 0.953711 & 0.476856 \tabularnewline
210 & 0.514135 & 0.971729 & 0.485865 \tabularnewline
211 & 0.49714 & 0.99428 & 0.50286 \tabularnewline
212 & 0.464164 & 0.928328 & 0.535836 \tabularnewline
213 & 0.438742 & 0.877484 & 0.561258 \tabularnewline
214 & 0.400559 & 0.801119 & 0.599441 \tabularnewline
215 & 0.38444 & 0.768879 & 0.61556 \tabularnewline
216 & 0.346207 & 0.692415 & 0.653793 \tabularnewline
217 & 0.330507 & 0.661014 & 0.669493 \tabularnewline
218 & 0.357162 & 0.714325 & 0.642838 \tabularnewline
219 & 0.332868 & 0.665736 & 0.667132 \tabularnewline
220 & 0.31148 & 0.62296 & 0.68852 \tabularnewline
221 & 0.331217 & 0.662434 & 0.668783 \tabularnewline
222 & 0.410355 & 0.820711 & 0.589645 \tabularnewline
223 & 0.369176 & 0.738351 & 0.630824 \tabularnewline
224 & 0.347859 & 0.695717 & 0.652141 \tabularnewline
225 & 0.458522 & 0.917045 & 0.541478 \tabularnewline
226 & 0.425519 & 0.851038 & 0.574481 \tabularnewline
227 & 0.40945 & 0.8189 & 0.59055 \tabularnewline
228 & 0.379547 & 0.759093 & 0.620453 \tabularnewline
229 & 0.429931 & 0.859862 & 0.570069 \tabularnewline
230 & 0.521967 & 0.956066 & 0.478033 \tabularnewline
231 & 0.611865 & 0.776271 & 0.388135 \tabularnewline
232 & 0.684501 & 0.630998 & 0.315499 \tabularnewline
233 & 0.639806 & 0.720388 & 0.360194 \tabularnewline
234 & 0.590807 & 0.818386 & 0.409193 \tabularnewline
235 & 0.582437 & 0.835125 & 0.417563 \tabularnewline
236 & 0.849898 & 0.300205 & 0.150102 \tabularnewline
237 & 0.825219 & 0.349561 & 0.174781 \tabularnewline
238 & 0.788347 & 0.423306 & 0.211653 \tabularnewline
239 & 0.790788 & 0.418424 & 0.209212 \tabularnewline
240 & 0.776585 & 0.44683 & 0.223415 \tabularnewline
241 & 0.731712 & 0.536576 & 0.268288 \tabularnewline
242 & 0.692287 & 0.615426 & 0.307713 \tabularnewline
243 & 0.651471 & 0.697058 & 0.348529 \tabularnewline
244 & 0.789139 & 0.421722 & 0.210861 \tabularnewline
245 & 0.757206 & 0.485589 & 0.242794 \tabularnewline
246 & 0.71106 & 0.57788 & 0.28894 \tabularnewline
247 & 0.702333 & 0.595335 & 0.297667 \tabularnewline
248 & 0.647459 & 0.705082 & 0.352541 \tabularnewline
249 & 0.618801 & 0.762397 & 0.381199 \tabularnewline
250 & 0.554656 & 0.890688 & 0.445344 \tabularnewline
251 & 0.504441 & 0.991118 & 0.495559 \tabularnewline
252 & 0.441802 & 0.883604 & 0.558198 \tabularnewline
253 & 0.379365 & 0.75873 & 0.620635 \tabularnewline
254 & 0.564265 & 0.87147 & 0.435735 \tabularnewline
255 & 0.655 & 0.69 & 0.345 \tabularnewline
256 & 0.623349 & 0.753302 & 0.376651 \tabularnewline
257 & 0.714472 & 0.571056 & 0.285528 \tabularnewline
258 & 0.881481 & 0.237038 & 0.118519 \tabularnewline
259 & 0.829891 & 0.340218 & 0.170109 \tabularnewline
260 & 0.947191 & 0.105618 & 0.0528088 \tabularnewline
261 & 0.941899 & 0.116201 & 0.0581005 \tabularnewline
262 & 0.935368 & 0.129265 & 0.0646323 \tabularnewline
263 & 0.896116 & 0.207768 & 0.103884 \tabularnewline
264 & 0.851445 & 0.29711 & 0.148555 \tabularnewline
265 & 0.818376 & 0.363248 & 0.181624 \tabularnewline
266 & 0.926659 & 0.146682 & 0.0733411 \tabularnewline
267 & 0.849363 & 0.301274 & 0.150637 \tabularnewline
268 & 0.989721 & 0.0205584 & 0.0102792 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266569&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]11[/C][C]0.097961[/C][C]0.195922[/C][C]0.902039[/C][/ROW]
[ROW][C]12[/C][C]0.223822[/C][C]0.447644[/C][C]0.776178[/C][/ROW]
[ROW][C]13[/C][C]0.160135[/C][C]0.320269[/C][C]0.839865[/C][/ROW]
[ROW][C]14[/C][C]0.150453[/C][C]0.300906[/C][C]0.849547[/C][/ROW]
[ROW][C]15[/C][C]0.18138[/C][C]0.362761[/C][C]0.81862[/C][/ROW]
[ROW][C]16[/C][C]0.149789[/C][C]0.299578[/C][C]0.850211[/C][/ROW]
[ROW][C]17[/C][C]0.106879[/C][C]0.213758[/C][C]0.893121[/C][/ROW]
[ROW][C]18[/C][C]0.0787025[/C][C]0.157405[/C][C]0.921297[/C][/ROW]
[ROW][C]19[/C][C]0.0529154[/C][C]0.105831[/C][C]0.947085[/C][/ROW]
[ROW][C]20[/C][C]0.0321301[/C][C]0.0642602[/C][C]0.96787[/C][/ROW]
[ROW][C]21[/C][C]0.0223451[/C][C]0.0446903[/C][C]0.977655[/C][/ROW]
[ROW][C]22[/C][C]0.0142287[/C][C]0.0284574[/C][C]0.985771[/C][/ROW]
[ROW][C]23[/C][C]0.00788122[/C][C]0.0157624[/C][C]0.992119[/C][/ROW]
[ROW][C]24[/C][C]0.0098007[/C][C]0.0196014[/C][C]0.990199[/C][/ROW]
[ROW][C]25[/C][C]0.00645534[/C][C]0.0129107[/C][C]0.993545[/C][/ROW]
[ROW][C]26[/C][C]0.00360014[/C][C]0.00720027[/C][C]0.9964[/C][/ROW]
[ROW][C]27[/C][C]0.00295303[/C][C]0.00590606[/C][C]0.997047[/C][/ROW]
[ROW][C]28[/C][C]0.00170948[/C][C]0.00341895[/C][C]0.998291[/C][/ROW]
[ROW][C]29[/C][C]0.000960822[/C][C]0.00192164[/C][C]0.999039[/C][/ROW]
[ROW][C]30[/C][C]0.000502427[/C][C]0.00100485[/C][C]0.999498[/C][/ROW]
[ROW][C]31[/C][C]0.000532107[/C][C]0.00106421[/C][C]0.999468[/C][/ROW]
[ROW][C]32[/C][C]0.000294092[/C][C]0.000588184[/C][C]0.999706[/C][/ROW]
[ROW][C]33[/C][C]0.000389688[/C][C]0.000779377[/C][C]0.99961[/C][/ROW]
[ROW][C]34[/C][C]0.00976878[/C][C]0.0195376[/C][C]0.990231[/C][/ROW]
[ROW][C]35[/C][C]0.006492[/C][C]0.012984[/C][C]0.993508[/C][/ROW]
[ROW][C]36[/C][C]0.00465587[/C][C]0.00931173[/C][C]0.995344[/C][/ROW]
[ROW][C]37[/C][C]0.00300851[/C][C]0.00601702[/C][C]0.996991[/C][/ROW]
[ROW][C]38[/C][C]0.00185859[/C][C]0.00371718[/C][C]0.998141[/C][/ROW]
[ROW][C]39[/C][C]0.00140747[/C][C]0.00281494[/C][C]0.998593[/C][/ROW]
[ROW][C]40[/C][C]0.000892344[/C][C]0.00178469[/C][C]0.999108[/C][/ROW]
[ROW][C]41[/C][C]0.00201029[/C][C]0.00402058[/C][C]0.99799[/C][/ROW]
[ROW][C]42[/C][C]0.0016386[/C][C]0.00327721[/C][C]0.998361[/C][/ROW]
[ROW][C]43[/C][C]0.00166676[/C][C]0.00333351[/C][C]0.998333[/C][/ROW]
[ROW][C]44[/C][C]0.00161917[/C][C]0.00323833[/C][C]0.998381[/C][/ROW]
[ROW][C]45[/C][C]0.00102849[/C][C]0.00205698[/C][C]0.998972[/C][/ROW]
[ROW][C]46[/C][C]0.000754124[/C][C]0.00150825[/C][C]0.999246[/C][/ROW]
[ROW][C]47[/C][C]0.000547795[/C][C]0.00109559[/C][C]0.999452[/C][/ROW]
[ROW][C]48[/C][C]0.00046553[/C][C]0.000931059[/C][C]0.999534[/C][/ROW]
[ROW][C]49[/C][C]0.000399003[/C][C]0.000798006[/C][C]0.999601[/C][/ROW]
[ROW][C]50[/C][C]0.000457009[/C][C]0.000914017[/C][C]0.999543[/C][/ROW]
[ROW][C]51[/C][C]0.000318618[/C][C]0.000637236[/C][C]0.999681[/C][/ROW]
[ROW][C]52[/C][C]0.00119998[/C][C]0.00239996[/C][C]0.9988[/C][/ROW]
[ROW][C]53[/C][C]0.000848731[/C][C]0.00169746[/C][C]0.999151[/C][/ROW]
[ROW][C]54[/C][C]0.000765887[/C][C]0.00153177[/C][C]0.999234[/C][/ROW]
[ROW][C]55[/C][C]0.00085061[/C][C]0.00170122[/C][C]0.999149[/C][/ROW]
[ROW][C]56[/C][C]0.000613605[/C][C]0.00122721[/C][C]0.999386[/C][/ROW]
[ROW][C]57[/C][C]0.00185226[/C][C]0.00370453[/C][C]0.998148[/C][/ROW]
[ROW][C]58[/C][C]0.00141084[/C][C]0.00282169[/C][C]0.998589[/C][/ROW]
[ROW][C]59[/C][C]0.00147209[/C][C]0.00294419[/C][C]0.998528[/C][/ROW]
[ROW][C]60[/C][C]0.00184453[/C][C]0.00368905[/C][C]0.998155[/C][/ROW]
[ROW][C]61[/C][C]0.00150797[/C][C]0.00301595[/C][C]0.998492[/C][/ROW]
[ROW][C]62[/C][C]0.00123926[/C][C]0.00247851[/C][C]0.998761[/C][/ROW]
[ROW][C]63[/C][C]0.00271088[/C][C]0.00542177[/C][C]0.997289[/C][/ROW]
[ROW][C]64[/C][C]0.00496374[/C][C]0.00992749[/C][C]0.995036[/C][/ROW]
[ROW][C]65[/C][C]0.00464256[/C][C]0.00928513[/C][C]0.995357[/C][/ROW]
[ROW][C]66[/C][C]0.00426295[/C][C]0.0085259[/C][C]0.995737[/C][/ROW]
[ROW][C]67[/C][C]0.00311857[/C][C]0.00623715[/C][C]0.996881[/C][/ROW]
[ROW][C]68[/C][C]0.00281428[/C][C]0.00562856[/C][C]0.997186[/C][/ROW]
[ROW][C]69[/C][C]0.00308874[/C][C]0.00617749[/C][C]0.996911[/C][/ROW]
[ROW][C]70[/C][C]0.00239301[/C][C]0.00478601[/C][C]0.997607[/C][/ROW]
[ROW][C]71[/C][C]0.0017274[/C][C]0.00345479[/C][C]0.998273[/C][/ROW]
[ROW][C]72[/C][C]0.00125456[/C][C]0.00250911[/C][C]0.998745[/C][/ROW]
[ROW][C]73[/C][C]0.00127414[/C][C]0.00254827[/C][C]0.998726[/C][/ROW]
[ROW][C]74[/C][C]0.00145726[/C][C]0.00291453[/C][C]0.998543[/C][/ROW]
[ROW][C]75[/C][C]0.00109073[/C][C]0.00218147[/C][C]0.998909[/C][/ROW]
[ROW][C]76[/C][C]0.000984087[/C][C]0.00196817[/C][C]0.999016[/C][/ROW]
[ROW][C]77[/C][C]0.000757338[/C][C]0.00151468[/C][C]0.999243[/C][/ROW]
[ROW][C]78[/C][C]0.000656639[/C][C]0.00131328[/C][C]0.999343[/C][/ROW]
[ROW][C]79[/C][C]0.000532385[/C][C]0.00106477[/C][C]0.999468[/C][/ROW]
[ROW][C]80[/C][C]0.000632666[/C][C]0.00126533[/C][C]0.999367[/C][/ROW]
[ROW][C]81[/C][C]0.000468949[/C][C]0.000937897[/C][C]0.999531[/C][/ROW]
[ROW][C]82[/C][C]0.000417319[/C][C]0.000834638[/C][C]0.999583[/C][/ROW]
[ROW][C]83[/C][C]0.000314994[/C][C]0.000629988[/C][C]0.999685[/C][/ROW]
[ROW][C]84[/C][C]0.00170394[/C][C]0.00340789[/C][C]0.998296[/C][/ROW]
[ROW][C]85[/C][C]0.00141016[/C][C]0.00282031[/C][C]0.99859[/C][/ROW]
[ROW][C]86[/C][C]0.0010776[/C][C]0.0021552[/C][C]0.998922[/C][/ROW]
[ROW][C]87[/C][C]0.000814389[/C][C]0.00162878[/C][C]0.999186[/C][/ROW]
[ROW][C]88[/C][C]0.000635488[/C][C]0.00127098[/C][C]0.999365[/C][/ROW]
[ROW][C]89[/C][C]0.000684581[/C][C]0.00136916[/C][C]0.999315[/C][/ROW]
[ROW][C]90[/C][C]0.000610478[/C][C]0.00122096[/C][C]0.99939[/C][/ROW]
[ROW][C]91[/C][C]0.000471872[/C][C]0.000943744[/C][C]0.999528[/C][/ROW]
[ROW][C]92[/C][C]0.00144885[/C][C]0.0028977[/C][C]0.998551[/C][/ROW]
[ROW][C]93[/C][C]0.00123266[/C][C]0.00246533[/C][C]0.998767[/C][/ROW]
[ROW][C]94[/C][C]0.00118827[/C][C]0.00237655[/C][C]0.998812[/C][/ROW]
[ROW][C]95[/C][C]0.00148353[/C][C]0.00296706[/C][C]0.998516[/C][/ROW]
[ROW][C]96[/C][C]0.00144787[/C][C]0.00289574[/C][C]0.998552[/C][/ROW]
[ROW][C]97[/C][C]0.00215011[/C][C]0.00430022[/C][C]0.99785[/C][/ROW]
[ROW][C]98[/C][C]0.00168921[/C][C]0.00337841[/C][C]0.998311[/C][/ROW]
[ROW][C]99[/C][C]0.00159407[/C][C]0.00318813[/C][C]0.998406[/C][/ROW]
[ROW][C]100[/C][C]0.00189179[/C][C]0.00378358[/C][C]0.998108[/C][/ROW]
[ROW][C]101[/C][C]0.00155034[/C][C]0.00310067[/C][C]0.99845[/C][/ROW]
[ROW][C]102[/C][C]0.00130553[/C][C]0.00261106[/C][C]0.998694[/C][/ROW]
[ROW][C]103[/C][C]0.00148212[/C][C]0.00296423[/C][C]0.998518[/C][/ROW]
[ROW][C]104[/C][C]0.00131965[/C][C]0.0026393[/C][C]0.99868[/C][/ROW]
[ROW][C]105[/C][C]0.00131582[/C][C]0.00263165[/C][C]0.998684[/C][/ROW]
[ROW][C]106[/C][C]0.00151721[/C][C]0.00303442[/C][C]0.998483[/C][/ROW]
[ROW][C]107[/C][C]0.00148433[/C][C]0.00296866[/C][C]0.998516[/C][/ROW]
[ROW][C]108[/C][C]0.00551542[/C][C]0.0110308[/C][C]0.994485[/C][/ROW]
[ROW][C]109[/C][C]0.0104392[/C][C]0.0208783[/C][C]0.989561[/C][/ROW]
[ROW][C]110[/C][C]0.0112937[/C][C]0.0225874[/C][C]0.988706[/C][/ROW]
[ROW][C]111[/C][C]0.0100258[/C][C]0.0200516[/C][C]0.989974[/C][/ROW]
[ROW][C]112[/C][C]0.00879146[/C][C]0.0175829[/C][C]0.991209[/C][/ROW]
[ROW][C]113[/C][C]0.0507792[/C][C]0.101558[/C][C]0.949221[/C][/ROW]
[ROW][C]114[/C][C]0.0583639[/C][C]0.116728[/C][C]0.941636[/C][/ROW]
[ROW][C]115[/C][C]0.108382[/C][C]0.216763[/C][C]0.891618[/C][/ROW]
[ROW][C]116[/C][C]0.184614[/C][C]0.369228[/C][C]0.815386[/C][/ROW]
[ROW][C]117[/C][C]0.228179[/C][C]0.456357[/C][C]0.771821[/C][/ROW]
[ROW][C]118[/C][C]0.208883[/C][C]0.417766[/C][C]0.791117[/C][/ROW]
[ROW][C]119[/C][C]0.265696[/C][C]0.531391[/C][C]0.734304[/C][/ROW]
[ROW][C]120[/C][C]0.381994[/C][C]0.763989[/C][C]0.618006[/C][/ROW]
[ROW][C]121[/C][C]0.407716[/C][C]0.815431[/C][C]0.592284[/C][/ROW]
[ROW][C]122[/C][C]0.399751[/C][C]0.799503[/C][C]0.600249[/C][/ROW]
[ROW][C]123[/C][C]0.493137[/C][C]0.986275[/C][C]0.506863[/C][/ROW]
[ROW][C]124[/C][C]0.493577[/C][C]0.987153[/C][C]0.506423[/C][/ROW]
[ROW][C]125[/C][C]0.493359[/C][C]0.986718[/C][C]0.506641[/C][/ROW]
[ROW][C]126[/C][C]0.468017[/C][C]0.936033[/C][C]0.531983[/C][/ROW]
[ROW][C]127[/C][C]0.506567[/C][C]0.986865[/C][C]0.493433[/C][/ROW]
[ROW][C]128[/C][C]0.484276[/C][C]0.968551[/C][C]0.515724[/C][/ROW]
[ROW][C]129[/C][C]0.590496[/C][C]0.819007[/C][C]0.409504[/C][/ROW]
[ROW][C]130[/C][C]0.579661[/C][C]0.840678[/C][C]0.420339[/C][/ROW]
[ROW][C]131[/C][C]0.56784[/C][C]0.864319[/C][C]0.43216[/C][/ROW]
[ROW][C]132[/C][C]0.582557[/C][C]0.834887[/C][C]0.417443[/C][/ROW]
[ROW][C]133[/C][C]0.565289[/C][C]0.869421[/C][C]0.434711[/C][/ROW]
[ROW][C]134[/C][C]0.558529[/C][C]0.882942[/C][C]0.441471[/C][/ROW]
[ROW][C]135[/C][C]0.541691[/C][C]0.916618[/C][C]0.458309[/C][/ROW]
[ROW][C]136[/C][C]0.517859[/C][C]0.964282[/C][C]0.482141[/C][/ROW]
[ROW][C]137[/C][C]0.564198[/C][C]0.871603[/C][C]0.435802[/C][/ROW]
[ROW][C]138[/C][C]0.61176[/C][C]0.776479[/C][C]0.38824[/C][/ROW]
[ROW][C]139[/C][C]0.69622[/C][C]0.60756[/C][C]0.30378[/C][/ROW]
[ROW][C]140[/C][C]0.681036[/C][C]0.637927[/C][C]0.318964[/C][/ROW]
[ROW][C]141[/C][C]0.654467[/C][C]0.691066[/C][C]0.345533[/C][/ROW]
[ROW][C]142[/C][C]0.692896[/C][C]0.614209[/C][C]0.307104[/C][/ROW]
[ROW][C]143[/C][C]0.68345[/C][C]0.6331[/C][C]0.31655[/C][/ROW]
[ROW][C]144[/C][C]0.716329[/C][C]0.567341[/C][C]0.283671[/C][/ROW]
[ROW][C]145[/C][C]0.717304[/C][C]0.565393[/C][C]0.282696[/C][/ROW]
[ROW][C]146[/C][C]0.731008[/C][C]0.537984[/C][C]0.268992[/C][/ROW]
[ROW][C]147[/C][C]0.710059[/C][C]0.579882[/C][C]0.289941[/C][/ROW]
[ROW][C]148[/C][C]0.686107[/C][C]0.627786[/C][C]0.313893[/C][/ROW]
[ROW][C]149[/C][C]0.670637[/C][C]0.658727[/C][C]0.329363[/C][/ROW]
[ROW][C]150[/C][C]0.718355[/C][C]0.56329[/C][C]0.281645[/C][/ROW]
[ROW][C]151[/C][C]0.719898[/C][C]0.560205[/C][C]0.280102[/C][/ROW]
[ROW][C]152[/C][C]0.704965[/C][C]0.590069[/C][C]0.295035[/C][/ROW]
[ROW][C]153[/C][C]0.733748[/C][C]0.532504[/C][C]0.266252[/C][/ROW]
[ROW][C]154[/C][C]0.745581[/C][C]0.508839[/C][C]0.254419[/C][/ROW]
[ROW][C]155[/C][C]0.725102[/C][C]0.549797[/C][C]0.274898[/C][/ROW]
[ROW][C]156[/C][C]0.698882[/C][C]0.602236[/C][C]0.301118[/C][/ROW]
[ROW][C]157[/C][C]0.742938[/C][C]0.514123[/C][C]0.257062[/C][/ROW]
[ROW][C]158[/C][C]0.731271[/C][C]0.537458[/C][C]0.268729[/C][/ROW]
[ROW][C]159[/C][C]0.705485[/C][C]0.589031[/C][C]0.294515[/C][/ROW]
[ROW][C]160[/C][C]0.688886[/C][C]0.622228[/C][C]0.311114[/C][/ROW]
[ROW][C]161[/C][C]0.732215[/C][C]0.53557[/C][C]0.267785[/C][/ROW]
[ROW][C]162[/C][C]0.727466[/C][C]0.545067[/C][C]0.272534[/C][/ROW]
[ROW][C]163[/C][C]0.736422[/C][C]0.527156[/C][C]0.263578[/C][/ROW]
[ROW][C]164[/C][C]0.720139[/C][C]0.559722[/C][C]0.279861[/C][/ROW]
[ROW][C]165[/C][C]0.760897[/C][C]0.478207[/C][C]0.239103[/C][/ROW]
[ROW][C]166[/C][C]0.740641[/C][C]0.518718[/C][C]0.259359[/C][/ROW]
[ROW][C]167[/C][C]0.792849[/C][C]0.414302[/C][C]0.207151[/C][/ROW]
[ROW][C]168[/C][C]0.771201[/C][C]0.457598[/C][C]0.228799[/C][/ROW]
[ROW][C]169[/C][C]0.746973[/C][C]0.506054[/C][C]0.253027[/C][/ROW]
[ROW][C]170[/C][C]0.732389[/C][C]0.535222[/C][C]0.267611[/C][/ROW]
[ROW][C]171[/C][C]0.722055[/C][C]0.55589[/C][C]0.277945[/C][/ROW]
[ROW][C]172[/C][C]0.755959[/C][C]0.488083[/C][C]0.244041[/C][/ROW]
[ROW][C]173[/C][C]0.733746[/C][C]0.532508[/C][C]0.266254[/C][/ROW]
[ROW][C]174[/C][C]0.709989[/C][C]0.580022[/C][C]0.290011[/C][/ROW]
[ROW][C]175[/C][C]0.686749[/C][C]0.626502[/C][C]0.313251[/C][/ROW]
[ROW][C]176[/C][C]0.721587[/C][C]0.556827[/C][C]0.278413[/C][/ROW]
[ROW][C]177[/C][C]0.691314[/C][C]0.617373[/C][C]0.308686[/C][/ROW]
[ROW][C]178[/C][C]0.765673[/C][C]0.468655[/C][C]0.234327[/C][/ROW]
[ROW][C]179[/C][C]0.746654[/C][C]0.506692[/C][C]0.253346[/C][/ROW]
[ROW][C]180[/C][C]0.794959[/C][C]0.410081[/C][C]0.205041[/C][/ROW]
[ROW][C]181[/C][C]0.767879[/C][C]0.464243[/C][C]0.232121[/C][/ROW]
[ROW][C]182[/C][C]0.738868[/C][C]0.522264[/C][C]0.261132[/C][/ROW]
[ROW][C]183[/C][C]0.792767[/C][C]0.414466[/C][C]0.207233[/C][/ROW]
[ROW][C]184[/C][C]0.778659[/C][C]0.442683[/C][C]0.221341[/C][/ROW]
[ROW][C]185[/C][C]0.753087[/C][C]0.493826[/C][C]0.246913[/C][/ROW]
[ROW][C]186[/C][C]0.742548[/C][C]0.514904[/C][C]0.257452[/C][/ROW]
[ROW][C]187[/C][C]0.757108[/C][C]0.485784[/C][C]0.242892[/C][/ROW]
[ROW][C]188[/C][C]0.726645[/C][C]0.54671[/C][C]0.273355[/C][/ROW]
[ROW][C]189[/C][C]0.698962[/C][C]0.602076[/C][C]0.301038[/C][/ROW]
[ROW][C]190[/C][C]0.667241[/C][C]0.665518[/C][C]0.332759[/C][/ROW]
[ROW][C]191[/C][C]0.664624[/C][C]0.670752[/C][C]0.335376[/C][/ROW]
[ROW][C]192[/C][C]0.647957[/C][C]0.704087[/C][C]0.352043[/C][/ROW]
[ROW][C]193[/C][C]0.675299[/C][C]0.649401[/C][C]0.324701[/C][/ROW]
[ROW][C]194[/C][C]0.706606[/C][C]0.586789[/C][C]0.293394[/C][/ROW]
[ROW][C]195[/C][C]0.675653[/C][C]0.648694[/C][C]0.324347[/C][/ROW]
[ROW][C]196[/C][C]0.641743[/C][C]0.716514[/C][C]0.358257[/C][/ROW]
[ROW][C]197[/C][C]0.614333[/C][C]0.771334[/C][C]0.385667[/C][/ROW]
[ROW][C]198[/C][C]0.580253[/C][C]0.839494[/C][C]0.419747[/C][/ROW]
[ROW][C]199[/C][C]0.547105[/C][C]0.905791[/C][C]0.452895[/C][/ROW]
[ROW][C]200[/C][C]0.52546[/C][C]0.94908[/C][C]0.47454[/C][/ROW]
[ROW][C]201[/C][C]0.614765[/C][C]0.77047[/C][C]0.385235[/C][/ROW]
[ROW][C]202[/C][C]0.576292[/C][C]0.847415[/C][C]0.423708[/C][/ROW]
[ROW][C]203[/C][C]0.538855[/C][C]0.922291[/C][C]0.461145[/C][/ROW]
[ROW][C]204[/C][C]0.519015[/C][C]0.96197[/C][C]0.480985[/C][/ROW]
[ROW][C]205[/C][C]0.486108[/C][C]0.972216[/C][C]0.513892[/C][/ROW]
[ROW][C]206[/C][C]0.464036[/C][C]0.928073[/C][C]0.535964[/C][/ROW]
[ROW][C]207[/C][C]0.503157[/C][C]0.993687[/C][C]0.496843[/C][/ROW]
[ROW][C]208[/C][C]0.469289[/C][C]0.938579[/C][C]0.530711[/C][/ROW]
[ROW][C]209[/C][C]0.523144[/C][C]0.953711[/C][C]0.476856[/C][/ROW]
[ROW][C]210[/C][C]0.514135[/C][C]0.971729[/C][C]0.485865[/C][/ROW]
[ROW][C]211[/C][C]0.49714[/C][C]0.99428[/C][C]0.50286[/C][/ROW]
[ROW][C]212[/C][C]0.464164[/C][C]0.928328[/C][C]0.535836[/C][/ROW]
[ROW][C]213[/C][C]0.438742[/C][C]0.877484[/C][C]0.561258[/C][/ROW]
[ROW][C]214[/C][C]0.400559[/C][C]0.801119[/C][C]0.599441[/C][/ROW]
[ROW][C]215[/C][C]0.38444[/C][C]0.768879[/C][C]0.61556[/C][/ROW]
[ROW][C]216[/C][C]0.346207[/C][C]0.692415[/C][C]0.653793[/C][/ROW]
[ROW][C]217[/C][C]0.330507[/C][C]0.661014[/C][C]0.669493[/C][/ROW]
[ROW][C]218[/C][C]0.357162[/C][C]0.714325[/C][C]0.642838[/C][/ROW]
[ROW][C]219[/C][C]0.332868[/C][C]0.665736[/C][C]0.667132[/C][/ROW]
[ROW][C]220[/C][C]0.31148[/C][C]0.62296[/C][C]0.68852[/C][/ROW]
[ROW][C]221[/C][C]0.331217[/C][C]0.662434[/C][C]0.668783[/C][/ROW]
[ROW][C]222[/C][C]0.410355[/C][C]0.820711[/C][C]0.589645[/C][/ROW]
[ROW][C]223[/C][C]0.369176[/C][C]0.738351[/C][C]0.630824[/C][/ROW]
[ROW][C]224[/C][C]0.347859[/C][C]0.695717[/C][C]0.652141[/C][/ROW]
[ROW][C]225[/C][C]0.458522[/C][C]0.917045[/C][C]0.541478[/C][/ROW]
[ROW][C]226[/C][C]0.425519[/C][C]0.851038[/C][C]0.574481[/C][/ROW]
[ROW][C]227[/C][C]0.40945[/C][C]0.8189[/C][C]0.59055[/C][/ROW]
[ROW][C]228[/C][C]0.379547[/C][C]0.759093[/C][C]0.620453[/C][/ROW]
[ROW][C]229[/C][C]0.429931[/C][C]0.859862[/C][C]0.570069[/C][/ROW]
[ROW][C]230[/C][C]0.521967[/C][C]0.956066[/C][C]0.478033[/C][/ROW]
[ROW][C]231[/C][C]0.611865[/C][C]0.776271[/C][C]0.388135[/C][/ROW]
[ROW][C]232[/C][C]0.684501[/C][C]0.630998[/C][C]0.315499[/C][/ROW]
[ROW][C]233[/C][C]0.639806[/C][C]0.720388[/C][C]0.360194[/C][/ROW]
[ROW][C]234[/C][C]0.590807[/C][C]0.818386[/C][C]0.409193[/C][/ROW]
[ROW][C]235[/C][C]0.582437[/C][C]0.835125[/C][C]0.417563[/C][/ROW]
[ROW][C]236[/C][C]0.849898[/C][C]0.300205[/C][C]0.150102[/C][/ROW]
[ROW][C]237[/C][C]0.825219[/C][C]0.349561[/C][C]0.174781[/C][/ROW]
[ROW][C]238[/C][C]0.788347[/C][C]0.423306[/C][C]0.211653[/C][/ROW]
[ROW][C]239[/C][C]0.790788[/C][C]0.418424[/C][C]0.209212[/C][/ROW]
[ROW][C]240[/C][C]0.776585[/C][C]0.44683[/C][C]0.223415[/C][/ROW]
[ROW][C]241[/C][C]0.731712[/C][C]0.536576[/C][C]0.268288[/C][/ROW]
[ROW][C]242[/C][C]0.692287[/C][C]0.615426[/C][C]0.307713[/C][/ROW]
[ROW][C]243[/C][C]0.651471[/C][C]0.697058[/C][C]0.348529[/C][/ROW]
[ROW][C]244[/C][C]0.789139[/C][C]0.421722[/C][C]0.210861[/C][/ROW]
[ROW][C]245[/C][C]0.757206[/C][C]0.485589[/C][C]0.242794[/C][/ROW]
[ROW][C]246[/C][C]0.71106[/C][C]0.57788[/C][C]0.28894[/C][/ROW]
[ROW][C]247[/C][C]0.702333[/C][C]0.595335[/C][C]0.297667[/C][/ROW]
[ROW][C]248[/C][C]0.647459[/C][C]0.705082[/C][C]0.352541[/C][/ROW]
[ROW][C]249[/C][C]0.618801[/C][C]0.762397[/C][C]0.381199[/C][/ROW]
[ROW][C]250[/C][C]0.554656[/C][C]0.890688[/C][C]0.445344[/C][/ROW]
[ROW][C]251[/C][C]0.504441[/C][C]0.991118[/C][C]0.495559[/C][/ROW]
[ROW][C]252[/C][C]0.441802[/C][C]0.883604[/C][C]0.558198[/C][/ROW]
[ROW][C]253[/C][C]0.379365[/C][C]0.75873[/C][C]0.620635[/C][/ROW]
[ROW][C]254[/C][C]0.564265[/C][C]0.87147[/C][C]0.435735[/C][/ROW]
[ROW][C]255[/C][C]0.655[/C][C]0.69[/C][C]0.345[/C][/ROW]
[ROW][C]256[/C][C]0.623349[/C][C]0.753302[/C][C]0.376651[/C][/ROW]
[ROW][C]257[/C][C]0.714472[/C][C]0.571056[/C][C]0.285528[/C][/ROW]
[ROW][C]258[/C][C]0.881481[/C][C]0.237038[/C][C]0.118519[/C][/ROW]
[ROW][C]259[/C][C]0.829891[/C][C]0.340218[/C][C]0.170109[/C][/ROW]
[ROW][C]260[/C][C]0.947191[/C][C]0.105618[/C][C]0.0528088[/C][/ROW]
[ROW][C]261[/C][C]0.941899[/C][C]0.116201[/C][C]0.0581005[/C][/ROW]
[ROW][C]262[/C][C]0.935368[/C][C]0.129265[/C][C]0.0646323[/C][/ROW]
[ROW][C]263[/C][C]0.896116[/C][C]0.207768[/C][C]0.103884[/C][/ROW]
[ROW][C]264[/C][C]0.851445[/C][C]0.29711[/C][C]0.148555[/C][/ROW]
[ROW][C]265[/C][C]0.818376[/C][C]0.363248[/C][C]0.181624[/C][/ROW]
[ROW][C]266[/C][C]0.926659[/C][C]0.146682[/C][C]0.0733411[/C][/ROW]
[ROW][C]267[/C][C]0.849363[/C][C]0.301274[/C][C]0.150637[/C][/ROW]
[ROW][C]268[/C][C]0.989721[/C][C]0.0205584[/C][C]0.0102792[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266569&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266569&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
110.0979610.1959220.902039
120.2238220.4476440.776178
130.1601350.3202690.839865
140.1504530.3009060.849547
150.181380.3627610.81862
160.1497890.2995780.850211
170.1068790.2137580.893121
180.07870250.1574050.921297
190.05291540.1058310.947085
200.03213010.06426020.96787
210.02234510.04469030.977655
220.01422870.02845740.985771
230.007881220.01576240.992119
240.00980070.01960140.990199
250.006455340.01291070.993545
260.003600140.007200270.9964
270.002953030.005906060.997047
280.001709480.003418950.998291
290.0009608220.001921640.999039
300.0005024270.001004850.999498
310.0005321070.001064210.999468
320.0002940920.0005881840.999706
330.0003896880.0007793770.99961
340.009768780.01953760.990231
350.0064920.0129840.993508
360.004655870.009311730.995344
370.003008510.006017020.996991
380.001858590.003717180.998141
390.001407470.002814940.998593
400.0008923440.001784690.999108
410.002010290.004020580.99799
420.00163860.003277210.998361
430.001666760.003333510.998333
440.001619170.003238330.998381
450.001028490.002056980.998972
460.0007541240.001508250.999246
470.0005477950.001095590.999452
480.000465530.0009310590.999534
490.0003990030.0007980060.999601
500.0004570090.0009140170.999543
510.0003186180.0006372360.999681
520.001199980.002399960.9988
530.0008487310.001697460.999151
540.0007658870.001531770.999234
550.000850610.001701220.999149
560.0006136050.001227210.999386
570.001852260.003704530.998148
580.001410840.002821690.998589
590.001472090.002944190.998528
600.001844530.003689050.998155
610.001507970.003015950.998492
620.001239260.002478510.998761
630.002710880.005421770.997289
640.004963740.009927490.995036
650.004642560.009285130.995357
660.004262950.00852590.995737
670.003118570.006237150.996881
680.002814280.005628560.997186
690.003088740.006177490.996911
700.002393010.004786010.997607
710.00172740.003454790.998273
720.001254560.002509110.998745
730.001274140.002548270.998726
740.001457260.002914530.998543
750.001090730.002181470.998909
760.0009840870.001968170.999016
770.0007573380.001514680.999243
780.0006566390.001313280.999343
790.0005323850.001064770.999468
800.0006326660.001265330.999367
810.0004689490.0009378970.999531
820.0004173190.0008346380.999583
830.0003149940.0006299880.999685
840.001703940.003407890.998296
850.001410160.002820310.99859
860.00107760.00215520.998922
870.0008143890.001628780.999186
880.0006354880.001270980.999365
890.0006845810.001369160.999315
900.0006104780.001220960.99939
910.0004718720.0009437440.999528
920.001448850.00289770.998551
930.001232660.002465330.998767
940.001188270.002376550.998812
950.001483530.002967060.998516
960.001447870.002895740.998552
970.002150110.004300220.99785
980.001689210.003378410.998311
990.001594070.003188130.998406
1000.001891790.003783580.998108
1010.001550340.003100670.99845
1020.001305530.002611060.998694
1030.001482120.002964230.998518
1040.001319650.00263930.99868
1050.001315820.002631650.998684
1060.001517210.003034420.998483
1070.001484330.002968660.998516
1080.005515420.01103080.994485
1090.01043920.02087830.989561
1100.01129370.02258740.988706
1110.01002580.02005160.989974
1120.008791460.01758290.991209
1130.05077920.1015580.949221
1140.05836390.1167280.941636
1150.1083820.2167630.891618
1160.1846140.3692280.815386
1170.2281790.4563570.771821
1180.2088830.4177660.791117
1190.2656960.5313910.734304
1200.3819940.7639890.618006
1210.4077160.8154310.592284
1220.3997510.7995030.600249
1230.4931370.9862750.506863
1240.4935770.9871530.506423
1250.4933590.9867180.506641
1260.4680170.9360330.531983
1270.5065670.9868650.493433
1280.4842760.9685510.515724
1290.5904960.8190070.409504
1300.5796610.8406780.420339
1310.567840.8643190.43216
1320.5825570.8348870.417443
1330.5652890.8694210.434711
1340.5585290.8829420.441471
1350.5416910.9166180.458309
1360.5178590.9642820.482141
1370.5641980.8716030.435802
1380.611760.7764790.38824
1390.696220.607560.30378
1400.6810360.6379270.318964
1410.6544670.6910660.345533
1420.6928960.6142090.307104
1430.683450.63310.31655
1440.7163290.5673410.283671
1450.7173040.5653930.282696
1460.7310080.5379840.268992
1470.7100590.5798820.289941
1480.6861070.6277860.313893
1490.6706370.6587270.329363
1500.7183550.563290.281645
1510.7198980.5602050.280102
1520.7049650.5900690.295035
1530.7337480.5325040.266252
1540.7455810.5088390.254419
1550.7251020.5497970.274898
1560.6988820.6022360.301118
1570.7429380.5141230.257062
1580.7312710.5374580.268729
1590.7054850.5890310.294515
1600.6888860.6222280.311114
1610.7322150.535570.267785
1620.7274660.5450670.272534
1630.7364220.5271560.263578
1640.7201390.5597220.279861
1650.7608970.4782070.239103
1660.7406410.5187180.259359
1670.7928490.4143020.207151
1680.7712010.4575980.228799
1690.7469730.5060540.253027
1700.7323890.5352220.267611
1710.7220550.555890.277945
1720.7559590.4880830.244041
1730.7337460.5325080.266254
1740.7099890.5800220.290011
1750.6867490.6265020.313251
1760.7215870.5568270.278413
1770.6913140.6173730.308686
1780.7656730.4686550.234327
1790.7466540.5066920.253346
1800.7949590.4100810.205041
1810.7678790.4642430.232121
1820.7388680.5222640.261132
1830.7927670.4144660.207233
1840.7786590.4426830.221341
1850.7530870.4938260.246913
1860.7425480.5149040.257452
1870.7571080.4857840.242892
1880.7266450.546710.273355
1890.6989620.6020760.301038
1900.6672410.6655180.332759
1910.6646240.6707520.335376
1920.6479570.7040870.352043
1930.6752990.6494010.324701
1940.7066060.5867890.293394
1950.6756530.6486940.324347
1960.6417430.7165140.358257
1970.6143330.7713340.385667
1980.5802530.8394940.419747
1990.5471050.9057910.452895
2000.525460.949080.47454
2010.6147650.770470.385235
2020.5762920.8474150.423708
2030.5388550.9222910.461145
2040.5190150.961970.480985
2050.4861080.9722160.513892
2060.4640360.9280730.535964
2070.5031570.9936870.496843
2080.4692890.9385790.530711
2090.5231440.9537110.476856
2100.5141350.9717290.485865
2110.497140.994280.50286
2120.4641640.9283280.535836
2130.4387420.8774840.561258
2140.4005590.8011190.599441
2150.384440.7688790.61556
2160.3462070.6924150.653793
2170.3305070.6610140.669493
2180.3571620.7143250.642838
2190.3328680.6657360.667132
2200.311480.622960.68852
2210.3312170.6624340.668783
2220.4103550.8207110.589645
2230.3691760.7383510.630824
2240.3478590.6957170.652141
2250.4585220.9170450.541478
2260.4255190.8510380.574481
2270.409450.81890.59055
2280.3795470.7590930.620453
2290.4299310.8598620.570069
2300.5219670.9560660.478033
2310.6118650.7762710.388135
2320.6845010.6309980.315499
2330.6398060.7203880.360194
2340.5908070.8183860.409193
2350.5824370.8351250.417563
2360.8498980.3002050.150102
2370.8252190.3495610.174781
2380.7883470.4233060.211653
2390.7907880.4184240.209212
2400.7765850.446830.223415
2410.7317120.5365760.268288
2420.6922870.6154260.307713
2430.6514710.6970580.348529
2440.7891390.4217220.210861
2450.7572060.4855890.242794
2460.711060.577880.28894
2470.7023330.5953350.297667
2480.6474590.7050820.352541
2490.6188010.7623970.381199
2500.5546560.8906880.445344
2510.5044410.9911180.495559
2520.4418020.8836040.558198
2530.3793650.758730.620635
2540.5642650.871470.435735
2550.6550.690.345
2560.6233490.7533020.376651
2570.7144720.5710560.285528
2580.8814810.2370380.118519
2590.8298910.3402180.170109
2600.9471910.1056180.0528088
2610.9418990.1162010.0581005
2620.9353680.1292650.0646323
2630.8961160.2077680.103884
2640.8514450.297110.148555
2650.8183760.3632480.181624
2660.9266590.1466820.0733411
2670.8493630.3012740.150637
2680.9897210.02055840.0102792






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level800.310078NOK
5% type I error level930.360465NOK
10% type I error level940.364341NOK

\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 & 80 & 0.310078 & NOK \tabularnewline
5% type I error level & 93 & 0.360465 & NOK \tabularnewline
10% type I error level & 94 & 0.364341 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266569&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]80[/C][C]0.310078[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]93[/C][C]0.360465[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]94[/C][C]0.364341[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266569&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266569&T=6

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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 level800.310078NOK
5% type I error level930.360465NOK
10% type I error level940.364341NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 1 ; 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')
}