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R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Wed, 17 Dec 2014 19:55:46 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/17/t141884626990dibobh7m40zje.htm/, Retrieved Thu, 16 May 2024 18:38:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270632, Retrieved Thu, 16 May 2024 18:38:38 +0000

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Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Multiple Regression] [bin] [2014-12-17 19:55:46] [c74d77b31b20c44b46a6349cc3b2e683] [Current]

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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 24 22 12 26 24 23 4
6.3 25 25 18 28 23 24 4
11.3 0 0 0 0 0 0 0
11.9 15 16 12 20 21 25 4
9.3 21 19 16 26 20 24 4
9.6 0 0 0 0 0 0 0
10 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 0 0 0 0 0 0 0
13.4 0 0 0 0 0 0 0
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 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 0 0 0 0 0 0 0
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 22 17 11 27 18 23 4
10.8 17 8 10 25 26 25 4
12.3 0 0 0 0 0 0 0
11.3 24 22 22 23 22 22 4
11.8 17 20 12 17 19 23 7
7.9 0 0 0 0 0 0 0
12.7 25 22 20 25 26 25 4
12.3 0 0 0 0 0 0 0
11.6 0 0 0 0 0 0 0
6.7 0 0 0 0 0 0 0
10.9 18 14 11 24 12 24 4
12.1 0 0 0 0 0 0 0
13.3 24 21 17 20 20 23 4
10.1 23 20 14 19 24 27 4
5.7 0 0 0 0 0 0 0
14.3 20 18 16 21 22 23 12
8 0 0 0 0 0 0 0
13.3 0 0 0 0 0 0 0
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 0 0 0 0 0 0 0
11.1 22 22 22 27 23 23 8
13 21 21 16 24 20 17 4
14.5 21 15 10 27 19 20 5
12.2 0 0 0 0 0 0 0
12.3 20 15 16 23 18 18 9
11.4 21 14 16 24 21 19 4
8.8 0 0 0 0 0 0 0
14.6 0 0 0 0 0 0 0
12.6 18 14 5 27 25 26 4
13 16 16 10 25 17 25 7
12.6 0 0 0 0 0 0 0
13.2 24 26 16 24 24 18 4
9.9 0 0 0 0 0 0 0
7.7 19 18 16 23 22 26 4
10.5 0 0 0 0 0 0 0
13.4 0 0 0 0 0 0 0
10.9 0 0 0 0 0 0 0
4.3 0 0 0 0 0 0 0
10.3 0 0 0 0 0 0 0
11.8 0 0 0 0 0 0 0
11.2 0 0 0 0 0 0 0
11.4 0 0 0 0 0 0 0
8.6 0 0 0 0 0 0 0
13.2 0 0 0 0 0 0 0
12.6 0 0 0 0 0 0 0
5.6 0 0 0 0 0 0 0
9.9 0 0 0 0 0 0 0
8.8 0 0 0 0 0 0 0
7.7 0 0 0 0 0 0 0
9 0 0 0 0 0 0 0
7.3 0 0 0 0 0 0 0
11.4 0 0 0 0 0 0 0
13.6 0 0 0 0 0 0 0
7.9 0 0 0 0 0 0 0
10.7 0 0 0 0 0 0 0
10.3 0 0 0 0 0 0 0
8.3 0 0 0 0 0 0 0
9.6 0 0 0 0 0 0 0
14.2 0 0 0 0 0 0 0
8.5 0 0 0 0 0 0 0
13.5 0 0 0 0 0 0 0
4.9 0 0 0 0 0 0 0
6.4 0 0 0 0 0 0 0
9.6 0 0 0 0 0 0 0
11.6 0 0 0 0 0 0 0
11.1 0 0 0 0 0 0 0
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 0 0 0 0 0 0 0
12.6 0 0 0 0 0 0 0
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 0 0 0 0 0 0 0
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 0 0 0 0 0 0 0
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 0 0 0 0 0 0 0
13.85 0 0 0 0 0 0 0
18.95 27 24 22 23 21 17 5
15.6 22 22 11 20 25 26 5
14.85 0 0 0 0 0 0 0
11.75 0 0 0 0 0 0 0
18.45 0 0 0 0 0 0 0
15.9 0 0 0 0 0 0 0
17.1 21 10 12 24 12 22 4
16.1 22 22 17 18 24 17 4
19.9 0 0 0 0 0 0 0
10.95 0 0 0 0 0 0 0
18.45 0 0 0 0 0 0 0
15.1 0 0 0 0 0 0 0
15 0 0 0 0 0 0 0
11.35 0 0 0 0 0 0 0
15.95 0 0 0 0 0 0 0
18.1 0 0 0 0 0 0 0
14.6 0 0 0 0 0 0 0
15.4 22 21 13 23 19 16 8
15.4 21 20 15 21 21 18 8
17.6 0 0 0 0 0 0 0
13.35 19 17 11 19 19 17 8
19.1 11 7 7 19 18 25 4
15.35 0 0 0 0 0 0 0
7.6 19 14 13 25 23 21 9
13.4 0 0 0 0 0 0 0
13.9 0 0 0 0 0 0 0
19.1 21 23 7 18 23 27 4
15.25 0 0 0 0 0 0 0
12.9 0 0 0 0 0 0 0
16.1 0 0 0 0 0 0 0
17.35 0 0 0 0 0 0 0
13.15 0 0 0 0 0 0 0
12.15 0 0 0 0 0 0 0
12.6 0 0 0 0 0 0 0
10.35 0 0 0 0 0 0 0
15.4 0 0 0 0 0 0 0
9.6 0 0 0 0 0 0 0
18.2 0 0 0 0 0 0 0
13.6 0 0 0 0 0 0 0
14.85 0 0 0 0 0 0 0
14.75 19 18 11 22 27 23 4
14.1 0 0 0 0 0 0 0
14.9 0 0 0 0 0 0 0
16.25 0 0 0 0 0 0 0
19.25 8 17 22 5 6 8 28
13.6 0 0 0 0 0 0 0
13.6 23 20 15 24 22 22 4
15.65 0 0 0 0 0 0 0
12.75 17 19 15 28 23 28 5
14.6 0 0 0 0 0 0 0
9.85 25 19 11 27 20 24 4
12.65 0 0 0 0 0 0 0
19.2 0 0 0 0 0 0 0
16.6 0 0 0 0 0 0 0
11.2 0 0 0 0 0 0 0
15.25 24 23 10 23 23 25 5
11.9 22 20 18 24 27 23 4
13.2 0 0 0 0 0 0 0
16.35 23 19 14 25 24 26 4
12.4 17 16 16 19 12 22 10
15.85 0 0 0 0 0 0 0
18.15 22 21 16 24 24 22 4
11.15 0 0 0 0 0 0 0
15.65 0 0 0 0 0 0 0
17.75 21 20 17 28 24 26 4
7.65 0 0 0 0 0 0 0
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 0 0 0 0 0 0 0
17.1 23 20 16 26 19 18 4
15.6 0 0 0 0 0 0 0
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 0 0 0 0 0 0 0
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 0 0 0 0 0 0 0
13.6 23 23 17 22 28 24 10
11.7 11 13 7 17 9 6 4
12.4 0 0 0 0 0 0 0
13.35 27 26 18 22 26 21 4
11.4 0 0 0 0 0 0 0
14.9 0 0 0 0 0 0 0
19.9 0 0 0 0 0 0 0
11.2 0 0 0 0 0 0 0
14.6 0 0 0 0 0 0 0
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 0 0 0 0 0 0 0
15.15 0 0 0 0 0 0 0
13.2 14 16 11 20 22 23 16
16.85 0 0 0 0 0 0 0
7.85 0 0 0 0 0 0 0
7.7 23 26 17 27 28 26 7
12.6 0 0 0 0 0 0 0
7.85 0 0 0 0 0 0 0
10.95 0 0 0 0 0 0 0
12.35 0 0 0 0 0 0 0
9.95 0 0 0 0 0 0 0
14.9 0 0 0 0 0 0 0
16.65 0 0 0 0 0 0 0
13.4 0 0 0 0 0 0 0
13.95 0 0 0 0 0 0 0
15.7 0 0 0 0 0 0 0
16.85 0 0 0 0 0 0 0
10.95 0 0 0 0 0 0 0
15.35 0 0 0 0 0 0 0
12.2 0 0 0 0 0 0 0
15.1 0 0 0 0 0 0 0
17.75 0 0 0 0 0 0 0
15.2 0 0 0 0 0 0 0
14.6 16 16 12 20 15 20 5
16.65 0 0 0 0 0 0 0
8.1 0 0 0 0 0 0 0

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'Sir Maurice George Kendall' @ kendall.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 & 9 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270632&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270632&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270632&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 12.771 + 0.040977AMS.I1[t] + 0.0827119AMS.I2[t] -0.10568AMS.I3[t] -0.0201227AMS.E1[t] -0.0732797AMS.E2[t] + 0.0291382AMS.E3[t] + 0.141061AMS.A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  12.771 +  0.040977AMS.I1[t] +  0.0827119AMS.I2[t] -0.10568AMS.I3[t] -0.0201227AMS.E1[t] -0.0732797AMS.E2[t] +  0.0291382AMS.E3[t] +  0.141061AMS.A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270632&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  12.771 +  0.040977AMS.I1[t] +  0.0827119AMS.I2[t] -0.10568AMS.I3[t] -0.0201227AMS.E1[t] -0.0732797AMS.E2[t] +  0.0291382AMS.E3[t] +  0.141061AMS.A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270632&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270632&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 12.771 + 0.040977AMS.I1[t] + 0.0827119AMS.I2[t] -0.10568AMS.I3[t] -0.0201227AMS.E1[t] -0.0732797AMS.E2[t] + 0.0291382AMS.E3[t] + 0.141061AMS.A[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	12.771	0.290728	43.93	5.37766e-125	2.68883e-125
AMS.I1	0.040977	0.110888	0.3695	0.712019	0.35601
AMS.I2	0.0827119	0.102187	0.8094	0.418987	0.209494
AMS.I3	-0.10568	0.0879852	-1.201	0.230759	0.11538
AMS.E1	-0.0201227	0.0997994	-0.2016	0.840357	0.420178
AMS.E2	-0.0732797	0.0825508	-0.8877	0.375496	0.187748
AMS.E3	0.0291382	0.087809	0.3318	0.740271	0.370135
AMS.A	0.141061	0.0914368	1.543	0.124071	0.0620357

\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) & 12.771 & 0.290728 & 43.93 & 5.37766e-125 & 2.68883e-125 \tabularnewline
AMS.I1 & 0.040977 & 0.110888 & 0.3695 & 0.712019 & 0.35601 \tabularnewline
AMS.I2 & 0.0827119 & 0.102187 & 0.8094 & 0.418987 & 0.209494 \tabularnewline
AMS.I3 & -0.10568 & 0.0879852 & -1.201 & 0.230759 & 0.11538 \tabularnewline
AMS.E1 & -0.0201227 & 0.0997994 & -0.2016 & 0.840357 & 0.420178 \tabularnewline
AMS.E2 & -0.0732797 & 0.0825508 & -0.8877 & 0.375496 & 0.187748 \tabularnewline
AMS.E3 & 0.0291382 & 0.087809 & 0.3318 & 0.740271 & 0.370135 \tabularnewline
AMS.A & 0.141061 & 0.0914368 & 1.543 & 0.124071 & 0.0620357 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270632&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]12.771[/C][C]0.290728[/C][C]43.93[/C][C]5.37766e-125[/C][C]2.68883e-125[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.040977[/C][C]0.110888[/C][C]0.3695[/C][C]0.712019[/C][C]0.35601[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.0827119[/C][C]0.102187[/C][C]0.8094[/C][C]0.418987[/C][C]0.209494[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.10568[/C][C]0.0879852[/C][C]-1.201[/C][C]0.230759[/C][C]0.11538[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0201227[/C][C]0.0997994[/C][C]-0.2016[/C][C]0.840357[/C][C]0.420178[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0732797[/C][C]0.0825508[/C][C]-0.8877[/C][C]0.375496[/C][C]0.187748[/C][/ROW]
[ROW][C]AMS.E3[/C][C]0.0291382[/C][C]0.087809[/C][C]0.3318[/C][C]0.740271[/C][C]0.370135[/C][/ROW]
[ROW][C]AMS.A[/C][C]0.141061[/C][C]0.0914368[/C][C]1.543[/C][C]0.124071[/C][C]0.0620357[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270632&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270632&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	12.771	0.290728	43.93	5.37766e-125	2.68883e-125
AMS.I1	0.040977	0.110888	0.3695	0.712019	0.35601
AMS.I2	0.0827119	0.102187	0.8094	0.418987	0.209494
AMS.I3	-0.10568	0.0879852	-1.201	0.230759	0.11538
AMS.E1	-0.0201227	0.0997994	-0.2016	0.840357	0.420178
AMS.E2	-0.0732797	0.0825508	-0.8877	0.375496	0.187748
AMS.E3	0.0291382	0.087809	0.3318	0.740271	0.370135
AMS.A	0.141061	0.0914368	1.543	0.124071	0.0620357

Multiple Linear Regression - Regression Statistics
Multiple R	0.133632
R-squared	0.0178575
Adjusted R-squared	-0.00760542
F-TEST (value)	0.701314
F-TEST (DF numerator)	7
F-TEST (DF denominator)	270
p-value	0.670951
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.40724
Sum Squared Residuals	3134.51

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.133632 \tabularnewline
R-squared & 0.0178575 \tabularnewline
Adjusted R-squared & -0.00760542 \tabularnewline
F-TEST (value) & 0.701314 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 270 \tabularnewline
p-value & 0.670951 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.40724 \tabularnewline
Sum Squared Residuals & 3134.51 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270632&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.133632[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0178575[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]-0.00760542[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]0.701314[/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]0.670951[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.40724[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3134.51[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270632&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270632&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.133632
R-squared	0.0178575
Adjusted R-squared	-0.00760542
F-TEST (value)	0.701314
F-TEST (DF numerator)	7
F-TEST (DF denominator)	270
p-value	0.670951
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.40724
Sum Squared Residuals	3134.51

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	13.0491	-0.149128
2	12.2	12.1142	0.0857714
3	12.8	13.2292	-0.429234
4	7.4	12.7205	-5.32048
5	6.7	13.1064	-6.40637
6	12.6	13.2319	-0.631905
7	14.8	12.8019	1.99811
8	13.3	14.5815	-1.28154
9	11.1	12.0401	-0.94009
10	8.2	13.0867	-4.88672
11	11.4	12.6161	-1.21614
12	6.4	12.3539	-5.95387
13	10.6	12.6553	-2.05532
14	12	13.2585	-1.25847
15	6.3	12.9757	-6.67567
16	11.3	12.771	-1.47101
17	11.9	12.7923	-0.892257
18	9.3	12.7869	-3.48694
19	9.6	12.771	-3.17101
20	10	13.0754	-3.07541
21	6.4	13.9006	-7.50061
22	13.8	13.2421	0.557928
23	10.8	12.8885	-2.08854
24	13.8	12.6332	1.16678
25	11.7	13.2794	-1.57938
26	10.9	12.708	-1.80798
27	16.1	12.771	3.32899
28	13.4	12.771	0.628993
29	9.9	12.419	-2.51899
30	11.5	12.9551	-1.45511
31	8.3	13.2439	-4.94391
32	11.7	14.3308	-2.63078
33	9	12.7587	-3.7587
34	9.7	12.6037	-2.90365
35	10.8	13.1462	-2.34618
36	10.3	13.5126	-3.2126
37	10.4	13.0297	-2.62973
38	12.7	12.771	-0.0710068
39	9.3	13.069	-3.76899
40	11.8	12.7104	-0.910363
41	5.9	13.094	-7.19403
42	11.4	13.342	-1.94198
43	13	13.2882	-0.288193
44	10.8	11.9569	-1.15687
45	12.3	12.771	-0.471007
46	11.3	12.3795	-1.07946
47	11.8	13.7769	-1.97689
48	7.9	12.771	-4.87101
49	12.7	12.3858	0.314156
50	12.3	12.771	-0.471007
51	11.6	12.771	-1.17101
52	6.7	12.771	-6.07101
53	10.9	13.4053	-2.50533
54	12.1	12.771	-0.671007
55	13.3	13.0612	0.238789
56	10.1	13.0981	-2.99812
57	5.7	12.771	-7.07101
58	14.3	13.7167	0.583347
59	8	12.771	-4.77101
60	13.3	12.771	0.528993
61	9.3	13.2592	-3.95916
62	12.5	13.1278	-0.627814
63	7.6	14.264	-6.66397
64	15.9	13.0809	2.81906
65	9.2	13.4564	-4.25645
66	9.1	12.771	-3.67101
67	11.1	12.7371	-1.63711
68	13	12.7886	0.211359
69	14.5	13.1678	1.33216
70	12.2	12.771	-0.571007
71	12.3	13.1525	-0.852517
72	11.4	12.1947	-0.794654
73	8.8	12.771	-3.97101
74	14.6	12.771	1.82899
75	12.6	13.0847	-0.484688
76	13	13.6603	-0.660283
77	12.6	12.771	-0.171007
78	13.2	13.0612	0.13885
79	9.9	12.771	-2.87101
80	7.7	12.5944	-4.89436
81	10.5	12.771	-2.27101
82	13.4	12.771	0.628993
83	10.9	12.771	-1.87101
84	4.3	12.771	-8.47101
85	10.3	12.771	-2.47101
86	11.8	12.771	-0.971007
87	11.2	12.771	-1.57101
88	11.4	12.771	-1.37101
89	8.6	12.771	-4.17101
90	13.2	12.771	0.428993
91	12.6	12.771	-0.171007
92	5.6	12.771	-7.17101
93	9.9	12.771	-2.87101
94	8.8	12.771	-3.97101
95	7.7	12.771	-5.07101
96	9	12.771	-3.77101
97	7.3	12.771	-5.47101
98	11.4	12.771	-1.37101
99	13.6	12.771	0.828993
100	7.9	12.771	-4.87101
101	10.7	12.771	-2.07101
102	10.3	12.771	-2.47101
103	8.3	12.771	-4.47101
104	9.6	12.771	-3.17101
105	14.2	12.771	1.42899
106	8.5	12.771	-4.27101
107	13.5	12.771	0.728993
108	4.9	12.771	-7.87101
109	6.4	12.771	-6.37101
110	9.6	12.771	-3.17101
111	11.6	12.771	-1.17101
112	11.1	12.771	-1.67101
113	4.35	13.2263	-8.87627
114	12.7	13.592	-0.89205
115	18.1	13.8385	4.26146
116	17.85	12.5941	5.25588
117	16.6	12.771	3.82899
118	12.6	12.771	-0.171007
119	17.1	13.8323	3.26772
120	19.1	13.1612	5.93879
121	16.1	13.2885	2.81151
122	13.35	12.9713	0.378672
123	18.4	13.7092	4.69079
124	14.7	12.4922	2.20784
125	10.6	12.9981	-2.39813
126	12.6	13.0171	-0.417139
127	16.2	13.6447	2.55534
128	13.6	12.6882	0.911814
129	18.9	12.771	6.12899
130	14.1	13.0651	1.03487
131	14.5	13.1814	1.31863
132	16.15	12.7734	3.37664
133	14.75	13.5767	1.17331
134	14.8	12.5806	2.21941
135	12.45	13.391	-0.940968
136	12.65	11.8122	0.837844
137	17.35	12.7216	4.62842
138	8.6	13.4774	-4.87738
139	18.4	13.1337	5.26629
140	16.1	14.5561	1.54386
141	11.6	12.771	-1.17101
142	17.75	13.9201	3.82995
143	15.25	13.0206	2.22943
144	17.65	13.8827	3.76726
145	16.35	13.2476	3.10243
146	17.65	13.6382	4.01181
147	13.6	13.5999	6.0829e-05
148	14.35	13.3377	1.01234
149	14.75	12.5337	2.21632
150	18.25	14.1888	4.06125
151	9.9	14.0731	-4.17313
152	16	13.366	2.63398
153	18.25	13.3065	4.94354
154	16.85	12.9717	3.87826
155	14.6	12.771	1.82899
156	13.85	12.771	1.07899
157	18.95	12.7365	6.21354
158	15.6	13.5581	2.04187
159	14.85	12.771	2.07899
160	11.75	12.771	-1.02101
161	18.45	12.771	5.67899
162	15.9	12.771	3.12899
163	17.1	13.0335	4.06654
164	16.1	12.6343	3.46573
165	19.9	12.771	7.12899
166	10.95	12.771	-1.82101
167	18.45	12.771	5.67899
168	15.1	12.771	2.32899
169	15	12.771	2.22899
170	11.35	12.771	-1.42101
171	15.95	12.771	3.17899
172	18.1	12.771	5.32899
173	14.6	12.771	1.82899
174	15.4	13.7752	1.62483
175	15.4	13.3921	2.00792
176	17.6	12.771	4.82899
177	13.35	13.6424	-0.292378
178	19.1	12.6523	6.44769
179	15.35	12.771	2.57899
180	7.6	13.0266	-5.42664
181	13.4	12.771	0.628993
182	13.9	12.771	1.12899
183	19.1	14.0975	5.00253
184	15.25	12.771	2.47899
185	12.9	12.771	0.128993
186	16.1	12.771	3.32899
187	17.35	12.771	4.57899
188	13.15	12.771	0.378993
189	12.15	12.771	-0.621007
190	12.6	12.771	-0.171007
191	10.35	12.771	-2.42101
192	15.4	12.771	2.62899
193	9.6	12.771	-3.17101
194	18.2	12.771	5.42899
195	13.6	12.771	0.828993
196	14.85	12.771	2.07899
197	14.75	12.6891	2.06093
198	14.1	12.771	1.32899
199	14.9	12.771	2.12899
200	16.25	12.771	3.47899
201	19.25	15.8225	3.42753
202	13.6	12.771	0.828993
203	13.6	12.8927	0.707305
204	15.65	12.771	2.87899
205	12.75	12.7262	0.0237598
206	14.6	12.771	1.82899
207	9.85	13.4591	-3.60913
208	12.65	12.771	-0.121007
209	19.2	12.771	6.42899
210	16.6	12.771	3.82899
211	11.2	12.771	-1.57101
212	15.25	13.8855	1.36447
213	11.9	12.1974	-0.297416
214	13.2	12.771	0.428993
215	16.35	12.8655	3.48447
216	12.4	13.8901	-1.49008
217	15.85	12.771	3.07899
218	18.15	12.6822	5.46781
219	11.15	12.771	-1.62101
220	15.65	12.771	2.87899
221	17.75	12.4889	5.26112
222	7.65	12.771	-5.12101
223	12.35	13.2668	-0.916842
224	15.6	13.29	2.30997
225	19.3	12.7047	6.5953
226	15.2	12.771	2.42899
227	17.1	12.8501	4.24994
228	15.6	12.771	2.82899
229	18.4	12.8699	5.53009
230	19.05	13.3209	5.72915
231	18.55	13.5122	5.03784
232	19.1	13.4772	5.62283
233	13.1	12.771	0.328993
234	12.85	13.071	-0.220968
235	9.5	13.5935	-4.09346
236	4.5	13.1857	-8.68573
237	11.85	12.771	-0.921007
238	13.6	13.4347	0.165322
239	11.7	13.2947	-1.59471
240	12.4	12.771	-0.371007
241	13.35	12.9538	0.396179
242	11.4	12.771	-1.37101
243	14.9	12.771	2.12899
244	19.9	12.771	7.12899
245	11.2	12.771	-1.57101
246	14.6	12.771	1.82899
247	17.6	12.7377	4.86231
248	14.05	14.2737	-0.223734
249	16.1	12.7508	3.3492
250	13.35	13.1968	0.153152
251	11.85	12.9837	-1.13365
252	11.95	13.924	-1.97396
253	14.75	12.771	1.97899
254	15.15	12.771	2.37899
255	13.2	14.4181	-1.21814
256	16.85	12.771	4.07899
257	7.85	12.771	-4.92101
258	7.7	13.2173	-5.51729
259	12.6	12.771	-0.171007
260	7.85	12.771	-4.92101
261	10.95	12.771	-1.82101
262	12.35	12.771	-0.421007
263	9.95	12.771	-2.82101
264	14.9	12.771	2.12899
265	16.65	12.771	3.87899
266	13.4	12.771	0.628993
267	13.95	12.771	1.17899
268	15.7	12.771	2.92899
269	16.85	12.771	4.07899
270	10.95	12.771	-1.82101
271	15.35	12.771	2.57899
272	12.2	12.771	-0.571007
273	15.1	12.771	2.32899
274	17.75	12.771	4.97899
275	15.2	12.771	2.42899
276	14.6	13.2683	1.33172
277	16.65	12.771	3.87899
278	8.1	12.771	-4.67101

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.0491 & -0.149128 \tabularnewline
2 & 12.2 & 12.1142 & 0.0857714 \tabularnewline
3 & 12.8 & 13.2292 & -0.429234 \tabularnewline
4 & 7.4 & 12.7205 & -5.32048 \tabularnewline
5 & 6.7 & 13.1064 & -6.40637 \tabularnewline
6 & 12.6 & 13.2319 & -0.631905 \tabularnewline
7 & 14.8 & 12.8019 & 1.99811 \tabularnewline
8 & 13.3 & 14.5815 & -1.28154 \tabularnewline
9 & 11.1 & 12.0401 & -0.94009 \tabularnewline
10 & 8.2 & 13.0867 & -4.88672 \tabularnewline
11 & 11.4 & 12.6161 & -1.21614 \tabularnewline
12 & 6.4 & 12.3539 & -5.95387 \tabularnewline
13 & 10.6 & 12.6553 & -2.05532 \tabularnewline
14 & 12 & 13.2585 & -1.25847 \tabularnewline
15 & 6.3 & 12.9757 & -6.67567 \tabularnewline
16 & 11.3 & 12.771 & -1.47101 \tabularnewline
17 & 11.9 & 12.7923 & -0.892257 \tabularnewline
18 & 9.3 & 12.7869 & -3.48694 \tabularnewline
19 & 9.6 & 12.771 & -3.17101 \tabularnewline
20 & 10 & 13.0754 & -3.07541 \tabularnewline
21 & 6.4 & 13.9006 & -7.50061 \tabularnewline
22 & 13.8 & 13.2421 & 0.557928 \tabularnewline
23 & 10.8 & 12.8885 & -2.08854 \tabularnewline
24 & 13.8 & 12.6332 & 1.16678 \tabularnewline
25 & 11.7 & 13.2794 & -1.57938 \tabularnewline
26 & 10.9 & 12.708 & -1.80798 \tabularnewline
27 & 16.1 & 12.771 & 3.32899 \tabularnewline
28 & 13.4 & 12.771 & 0.628993 \tabularnewline
29 & 9.9 & 12.419 & -2.51899 \tabularnewline
30 & 11.5 & 12.9551 & -1.45511 \tabularnewline
31 & 8.3 & 13.2439 & -4.94391 \tabularnewline
32 & 11.7 & 14.3308 & -2.63078 \tabularnewline
33 & 9 & 12.7587 & -3.7587 \tabularnewline
34 & 9.7 & 12.6037 & -2.90365 \tabularnewline
35 & 10.8 & 13.1462 & -2.34618 \tabularnewline
36 & 10.3 & 13.5126 & -3.2126 \tabularnewline
37 & 10.4 & 13.0297 & -2.62973 \tabularnewline
38 & 12.7 & 12.771 & -0.0710068 \tabularnewline
39 & 9.3 & 13.069 & -3.76899 \tabularnewline
40 & 11.8 & 12.7104 & -0.910363 \tabularnewline
41 & 5.9 & 13.094 & -7.19403 \tabularnewline
42 & 11.4 & 13.342 & -1.94198 \tabularnewline
43 & 13 & 13.2882 & -0.288193 \tabularnewline
44 & 10.8 & 11.9569 & -1.15687 \tabularnewline
45 & 12.3 & 12.771 & -0.471007 \tabularnewline
46 & 11.3 & 12.3795 & -1.07946 \tabularnewline
47 & 11.8 & 13.7769 & -1.97689 \tabularnewline
48 & 7.9 & 12.771 & -4.87101 \tabularnewline
49 & 12.7 & 12.3858 & 0.314156 \tabularnewline
50 & 12.3 & 12.771 & -0.471007 \tabularnewline
51 & 11.6 & 12.771 & -1.17101 \tabularnewline
52 & 6.7 & 12.771 & -6.07101 \tabularnewline
53 & 10.9 & 13.4053 & -2.50533 \tabularnewline
54 & 12.1 & 12.771 & -0.671007 \tabularnewline
55 & 13.3 & 13.0612 & 0.238789 \tabularnewline
56 & 10.1 & 13.0981 & -2.99812 \tabularnewline
57 & 5.7 & 12.771 & -7.07101 \tabularnewline
58 & 14.3 & 13.7167 & 0.583347 \tabularnewline
59 & 8 & 12.771 & -4.77101 \tabularnewline
60 & 13.3 & 12.771 & 0.528993 \tabularnewline
61 & 9.3 & 13.2592 & -3.95916 \tabularnewline
62 & 12.5 & 13.1278 & -0.627814 \tabularnewline
63 & 7.6 & 14.264 & -6.66397 \tabularnewline
64 & 15.9 & 13.0809 & 2.81906 \tabularnewline
65 & 9.2 & 13.4564 & -4.25645 \tabularnewline
66 & 9.1 & 12.771 & -3.67101 \tabularnewline
67 & 11.1 & 12.7371 & -1.63711 \tabularnewline
68 & 13 & 12.7886 & 0.211359 \tabularnewline
69 & 14.5 & 13.1678 & 1.33216 \tabularnewline
70 & 12.2 & 12.771 & -0.571007 \tabularnewline
71 & 12.3 & 13.1525 & -0.852517 \tabularnewline
72 & 11.4 & 12.1947 & -0.794654 \tabularnewline
73 & 8.8 & 12.771 & -3.97101 \tabularnewline
74 & 14.6 & 12.771 & 1.82899 \tabularnewline
75 & 12.6 & 13.0847 & -0.484688 \tabularnewline
76 & 13 & 13.6603 & -0.660283 \tabularnewline
77 & 12.6 & 12.771 & -0.171007 \tabularnewline
78 & 13.2 & 13.0612 & 0.13885 \tabularnewline
79 & 9.9 & 12.771 & -2.87101 \tabularnewline
80 & 7.7 & 12.5944 & -4.89436 \tabularnewline
81 & 10.5 & 12.771 & -2.27101 \tabularnewline
82 & 13.4 & 12.771 & 0.628993 \tabularnewline
83 & 10.9 & 12.771 & -1.87101 \tabularnewline
84 & 4.3 & 12.771 & -8.47101 \tabularnewline
85 & 10.3 & 12.771 & -2.47101 \tabularnewline
86 & 11.8 & 12.771 & -0.971007 \tabularnewline
87 & 11.2 & 12.771 & -1.57101 \tabularnewline
88 & 11.4 & 12.771 & -1.37101 \tabularnewline
89 & 8.6 & 12.771 & -4.17101 \tabularnewline
90 & 13.2 & 12.771 & 0.428993 \tabularnewline
91 & 12.6 & 12.771 & -0.171007 \tabularnewline
92 & 5.6 & 12.771 & -7.17101 \tabularnewline
93 & 9.9 & 12.771 & -2.87101 \tabularnewline
94 & 8.8 & 12.771 & -3.97101 \tabularnewline
95 & 7.7 & 12.771 & -5.07101 \tabularnewline
96 & 9 & 12.771 & -3.77101 \tabularnewline
97 & 7.3 & 12.771 & -5.47101 \tabularnewline
98 & 11.4 & 12.771 & -1.37101 \tabularnewline
99 & 13.6 & 12.771 & 0.828993 \tabularnewline
100 & 7.9 & 12.771 & -4.87101 \tabularnewline
101 & 10.7 & 12.771 & -2.07101 \tabularnewline
102 & 10.3 & 12.771 & -2.47101 \tabularnewline
103 & 8.3 & 12.771 & -4.47101 \tabularnewline
104 & 9.6 & 12.771 & -3.17101 \tabularnewline
105 & 14.2 & 12.771 & 1.42899 \tabularnewline
106 & 8.5 & 12.771 & -4.27101 \tabularnewline
107 & 13.5 & 12.771 & 0.728993 \tabularnewline
108 & 4.9 & 12.771 & -7.87101 \tabularnewline
109 & 6.4 & 12.771 & -6.37101 \tabularnewline
110 & 9.6 & 12.771 & -3.17101 \tabularnewline
111 & 11.6 & 12.771 & -1.17101 \tabularnewline
112 & 11.1 & 12.771 & -1.67101 \tabularnewline
113 & 4.35 & 13.2263 & -8.87627 \tabularnewline
114 & 12.7 & 13.592 & -0.89205 \tabularnewline
115 & 18.1 & 13.8385 & 4.26146 \tabularnewline
116 & 17.85 & 12.5941 & 5.25588 \tabularnewline
117 & 16.6 & 12.771 & 3.82899 \tabularnewline
118 & 12.6 & 12.771 & -0.171007 \tabularnewline
119 & 17.1 & 13.8323 & 3.26772 \tabularnewline
120 & 19.1 & 13.1612 & 5.93879 \tabularnewline
121 & 16.1 & 13.2885 & 2.81151 \tabularnewline
122 & 13.35 & 12.9713 & 0.378672 \tabularnewline
123 & 18.4 & 13.7092 & 4.69079 \tabularnewline
124 & 14.7 & 12.4922 & 2.20784 \tabularnewline
125 & 10.6 & 12.9981 & -2.39813 \tabularnewline
126 & 12.6 & 13.0171 & -0.417139 \tabularnewline
127 & 16.2 & 13.6447 & 2.55534 \tabularnewline
128 & 13.6 & 12.6882 & 0.911814 \tabularnewline
129 & 18.9 & 12.771 & 6.12899 \tabularnewline
130 & 14.1 & 13.0651 & 1.03487 \tabularnewline
131 & 14.5 & 13.1814 & 1.31863 \tabularnewline
132 & 16.15 & 12.7734 & 3.37664 \tabularnewline
133 & 14.75 & 13.5767 & 1.17331 \tabularnewline
134 & 14.8 & 12.5806 & 2.21941 \tabularnewline
135 & 12.45 & 13.391 & -0.940968 \tabularnewline
136 & 12.65 & 11.8122 & 0.837844 \tabularnewline
137 & 17.35 & 12.7216 & 4.62842 \tabularnewline
138 & 8.6 & 13.4774 & -4.87738 \tabularnewline
139 & 18.4 & 13.1337 & 5.26629 \tabularnewline
140 & 16.1 & 14.5561 & 1.54386 \tabularnewline
141 & 11.6 & 12.771 & -1.17101 \tabularnewline
142 & 17.75 & 13.9201 & 3.82995 \tabularnewline
143 & 15.25 & 13.0206 & 2.22943 \tabularnewline
144 & 17.65 & 13.8827 & 3.76726 \tabularnewline
145 & 16.35 & 13.2476 & 3.10243 \tabularnewline
146 & 17.65 & 13.6382 & 4.01181 \tabularnewline
147 & 13.6 & 13.5999 & 6.0829e-05 \tabularnewline
148 & 14.35 & 13.3377 & 1.01234 \tabularnewline
149 & 14.75 & 12.5337 & 2.21632 \tabularnewline
150 & 18.25 & 14.1888 & 4.06125 \tabularnewline
151 & 9.9 & 14.0731 & -4.17313 \tabularnewline
152 & 16 & 13.366 & 2.63398 \tabularnewline
153 & 18.25 & 13.3065 & 4.94354 \tabularnewline
154 & 16.85 & 12.9717 & 3.87826 \tabularnewline
155 & 14.6 & 12.771 & 1.82899 \tabularnewline
156 & 13.85 & 12.771 & 1.07899 \tabularnewline
157 & 18.95 & 12.7365 & 6.21354 \tabularnewline
158 & 15.6 & 13.5581 & 2.04187 \tabularnewline
159 & 14.85 & 12.771 & 2.07899 \tabularnewline
160 & 11.75 & 12.771 & -1.02101 \tabularnewline
161 & 18.45 & 12.771 & 5.67899 \tabularnewline
162 & 15.9 & 12.771 & 3.12899 \tabularnewline
163 & 17.1 & 13.0335 & 4.06654 \tabularnewline
164 & 16.1 & 12.6343 & 3.46573 \tabularnewline
165 & 19.9 & 12.771 & 7.12899 \tabularnewline
166 & 10.95 & 12.771 & -1.82101 \tabularnewline
167 & 18.45 & 12.771 & 5.67899 \tabularnewline
168 & 15.1 & 12.771 & 2.32899 \tabularnewline
169 & 15 & 12.771 & 2.22899 \tabularnewline
170 & 11.35 & 12.771 & -1.42101 \tabularnewline
171 & 15.95 & 12.771 & 3.17899 \tabularnewline
172 & 18.1 & 12.771 & 5.32899 \tabularnewline
173 & 14.6 & 12.771 & 1.82899 \tabularnewline
174 & 15.4 & 13.7752 & 1.62483 \tabularnewline
175 & 15.4 & 13.3921 & 2.00792 \tabularnewline
176 & 17.6 & 12.771 & 4.82899 \tabularnewline
177 & 13.35 & 13.6424 & -0.292378 \tabularnewline
178 & 19.1 & 12.6523 & 6.44769 \tabularnewline
179 & 15.35 & 12.771 & 2.57899 \tabularnewline
180 & 7.6 & 13.0266 & -5.42664 \tabularnewline
181 & 13.4 & 12.771 & 0.628993 \tabularnewline
182 & 13.9 & 12.771 & 1.12899 \tabularnewline
183 & 19.1 & 14.0975 & 5.00253 \tabularnewline
184 & 15.25 & 12.771 & 2.47899 \tabularnewline
185 & 12.9 & 12.771 & 0.128993 \tabularnewline
186 & 16.1 & 12.771 & 3.32899 \tabularnewline
187 & 17.35 & 12.771 & 4.57899 \tabularnewline
188 & 13.15 & 12.771 & 0.378993 \tabularnewline
189 & 12.15 & 12.771 & -0.621007 \tabularnewline
190 & 12.6 & 12.771 & -0.171007 \tabularnewline
191 & 10.35 & 12.771 & -2.42101 \tabularnewline
192 & 15.4 & 12.771 & 2.62899 \tabularnewline
193 & 9.6 & 12.771 & -3.17101 \tabularnewline
194 & 18.2 & 12.771 & 5.42899 \tabularnewline
195 & 13.6 & 12.771 & 0.828993 \tabularnewline
196 & 14.85 & 12.771 & 2.07899 \tabularnewline
197 & 14.75 & 12.6891 & 2.06093 \tabularnewline
198 & 14.1 & 12.771 & 1.32899 \tabularnewline
199 & 14.9 & 12.771 & 2.12899 \tabularnewline
200 & 16.25 & 12.771 & 3.47899 \tabularnewline
201 & 19.25 & 15.8225 & 3.42753 \tabularnewline
202 & 13.6 & 12.771 & 0.828993 \tabularnewline
203 & 13.6 & 12.8927 & 0.707305 \tabularnewline
204 & 15.65 & 12.771 & 2.87899 \tabularnewline
205 & 12.75 & 12.7262 & 0.0237598 \tabularnewline
206 & 14.6 & 12.771 & 1.82899 \tabularnewline
207 & 9.85 & 13.4591 & -3.60913 \tabularnewline
208 & 12.65 & 12.771 & -0.121007 \tabularnewline
209 & 19.2 & 12.771 & 6.42899 \tabularnewline
210 & 16.6 & 12.771 & 3.82899 \tabularnewline
211 & 11.2 & 12.771 & -1.57101 \tabularnewline
212 & 15.25 & 13.8855 & 1.36447 \tabularnewline
213 & 11.9 & 12.1974 & -0.297416 \tabularnewline
214 & 13.2 & 12.771 & 0.428993 \tabularnewline
215 & 16.35 & 12.8655 & 3.48447 \tabularnewline
216 & 12.4 & 13.8901 & -1.49008 \tabularnewline
217 & 15.85 & 12.771 & 3.07899 \tabularnewline
218 & 18.15 & 12.6822 & 5.46781 \tabularnewline
219 & 11.15 & 12.771 & -1.62101 \tabularnewline
220 & 15.65 & 12.771 & 2.87899 \tabularnewline
221 & 17.75 & 12.4889 & 5.26112 \tabularnewline
222 & 7.65 & 12.771 & -5.12101 \tabularnewline
223 & 12.35 & 13.2668 & -0.916842 \tabularnewline
224 & 15.6 & 13.29 & 2.30997 \tabularnewline
225 & 19.3 & 12.7047 & 6.5953 \tabularnewline
226 & 15.2 & 12.771 & 2.42899 \tabularnewline
227 & 17.1 & 12.8501 & 4.24994 \tabularnewline
228 & 15.6 & 12.771 & 2.82899 \tabularnewline
229 & 18.4 & 12.8699 & 5.53009 \tabularnewline
230 & 19.05 & 13.3209 & 5.72915 \tabularnewline
231 & 18.55 & 13.5122 & 5.03784 \tabularnewline
232 & 19.1 & 13.4772 & 5.62283 \tabularnewline
233 & 13.1 & 12.771 & 0.328993 \tabularnewline
234 & 12.85 & 13.071 & -0.220968 \tabularnewline
235 & 9.5 & 13.5935 & -4.09346 \tabularnewline
236 & 4.5 & 13.1857 & -8.68573 \tabularnewline
237 & 11.85 & 12.771 & -0.921007 \tabularnewline
238 & 13.6 & 13.4347 & 0.165322 \tabularnewline
239 & 11.7 & 13.2947 & -1.59471 \tabularnewline
240 & 12.4 & 12.771 & -0.371007 \tabularnewline
241 & 13.35 & 12.9538 & 0.396179 \tabularnewline
242 & 11.4 & 12.771 & -1.37101 \tabularnewline
243 & 14.9 & 12.771 & 2.12899 \tabularnewline
244 & 19.9 & 12.771 & 7.12899 \tabularnewline
245 & 11.2 & 12.771 & -1.57101 \tabularnewline
246 & 14.6 & 12.771 & 1.82899 \tabularnewline
247 & 17.6 & 12.7377 & 4.86231 \tabularnewline
248 & 14.05 & 14.2737 & -0.223734 \tabularnewline
249 & 16.1 & 12.7508 & 3.3492 \tabularnewline
250 & 13.35 & 13.1968 & 0.153152 \tabularnewline
251 & 11.85 & 12.9837 & -1.13365 \tabularnewline
252 & 11.95 & 13.924 & -1.97396 \tabularnewline
253 & 14.75 & 12.771 & 1.97899 \tabularnewline
254 & 15.15 & 12.771 & 2.37899 \tabularnewline
255 & 13.2 & 14.4181 & -1.21814 \tabularnewline
256 & 16.85 & 12.771 & 4.07899 \tabularnewline
257 & 7.85 & 12.771 & -4.92101 \tabularnewline
258 & 7.7 & 13.2173 & -5.51729 \tabularnewline
259 & 12.6 & 12.771 & -0.171007 \tabularnewline
260 & 7.85 & 12.771 & -4.92101 \tabularnewline
261 & 10.95 & 12.771 & -1.82101 \tabularnewline
262 & 12.35 & 12.771 & -0.421007 \tabularnewline
263 & 9.95 & 12.771 & -2.82101 \tabularnewline
264 & 14.9 & 12.771 & 2.12899 \tabularnewline
265 & 16.65 & 12.771 & 3.87899 \tabularnewline
266 & 13.4 & 12.771 & 0.628993 \tabularnewline
267 & 13.95 & 12.771 & 1.17899 \tabularnewline
268 & 15.7 & 12.771 & 2.92899 \tabularnewline
269 & 16.85 & 12.771 & 4.07899 \tabularnewline
270 & 10.95 & 12.771 & -1.82101 \tabularnewline
271 & 15.35 & 12.771 & 2.57899 \tabularnewline
272 & 12.2 & 12.771 & -0.571007 \tabularnewline
273 & 15.1 & 12.771 & 2.32899 \tabularnewline
274 & 17.75 & 12.771 & 4.97899 \tabularnewline
275 & 15.2 & 12.771 & 2.42899 \tabularnewline
276 & 14.6 & 13.2683 & 1.33172 \tabularnewline
277 & 16.65 & 12.771 & 3.87899 \tabularnewline
278 & 8.1 & 12.771 & -4.67101 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270632&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]13.0491[/C][C]-0.149128[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.1142[/C][C]0.0857714[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.2292[/C][C]-0.429234[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.7205[/C][C]-5.32048[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]13.1064[/C][C]-6.40637[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.2319[/C][C]-0.631905[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.8019[/C][C]1.99811[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]14.5815[/C][C]-1.28154[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.0401[/C][C]-0.94009[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]13.0867[/C][C]-4.88672[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.6161[/C][C]-1.21614[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]12.3539[/C][C]-5.95387[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]12.6553[/C][C]-2.05532[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.2585[/C][C]-1.25847[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]12.9757[/C][C]-6.67567[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.771[/C][C]-1.47101[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.7923[/C][C]-0.892257[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.7869[/C][C]-3.48694[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.771[/C][C]-3.17101[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]13.0754[/C][C]-3.07541[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]13.9006[/C][C]-7.50061[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]13.2421[/C][C]0.557928[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.8885[/C][C]-2.08854[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.6332[/C][C]1.16678[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]13.2794[/C][C]-1.57938[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.708[/C][C]-1.80798[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.771[/C][C]3.32899[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]12.771[/C][C]0.628993[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]12.419[/C][C]-2.51899[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.9551[/C][C]-1.45511[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]13.2439[/C][C]-4.94391[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]14.3308[/C][C]-2.63078[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.7587[/C][C]-3.7587[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.6037[/C][C]-2.90365[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]13.1462[/C][C]-2.34618[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]13.5126[/C][C]-3.2126[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]13.0297[/C][C]-2.62973[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.771[/C][C]-0.0710068[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]13.069[/C][C]-3.76899[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.7104[/C][C]-0.910363[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.094[/C][C]-7.19403[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.342[/C][C]-1.94198[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]13.2882[/C][C]-0.288193[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.9569[/C][C]-1.15687[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]12.771[/C][C]-0.471007[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.3795[/C][C]-1.07946[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]13.7769[/C][C]-1.97689[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.771[/C][C]-4.87101[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]12.3858[/C][C]0.314156[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]12.771[/C][C]-0.471007[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.771[/C][C]-1.17101[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]12.771[/C][C]-6.07101[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.4053[/C][C]-2.50533[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.771[/C][C]-0.671007[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.0612[/C][C]0.238789[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.0981[/C][C]-2.99812[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.771[/C][C]-7.07101[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]13.7167[/C][C]0.583347[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]12.771[/C][C]-4.77101[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.771[/C][C]0.528993[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.2592[/C][C]-3.95916[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]13.1278[/C][C]-0.627814[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]14.264[/C][C]-6.66397[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.0809[/C][C]2.81906[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.4564[/C][C]-4.25645[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]12.771[/C][C]-3.67101[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.7371[/C][C]-1.63711[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]12.7886[/C][C]0.211359[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]13.1678[/C][C]1.33216[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.771[/C][C]-0.571007[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.1525[/C][C]-0.852517[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.1947[/C][C]-0.794654[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]12.771[/C][C]-3.97101[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]12.771[/C][C]1.82899[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]13.0847[/C][C]-0.484688[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]13.6603[/C][C]-0.660283[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]12.771[/C][C]-0.171007[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]13.0612[/C][C]0.13885[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]12.771[/C][C]-2.87101[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]12.5944[/C][C]-4.89436[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]12.771[/C][C]-2.27101[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]12.771[/C][C]0.628993[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]12.771[/C][C]-1.87101[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]12.771[/C][C]-8.47101[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]12.771[/C][C]-2.47101[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]12.771[/C][C]-0.971007[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]12.771[/C][C]-1.57101[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]12.771[/C][C]-1.37101[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]12.771[/C][C]-4.17101[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]12.771[/C][C]0.428993[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]12.771[/C][C]-0.171007[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]12.771[/C][C]-7.17101[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]12.771[/C][C]-2.87101[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]12.771[/C][C]-3.97101[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]12.771[/C][C]-5.07101[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]12.771[/C][C]-3.77101[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]12.771[/C][C]-5.47101[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]12.771[/C][C]-1.37101[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]12.771[/C][C]0.828993[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]12.771[/C][C]-4.87101[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]12.771[/C][C]-2.07101[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]12.771[/C][C]-2.47101[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]12.771[/C][C]-4.47101[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]12.771[/C][C]-3.17101[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]12.771[/C][C]1.42899[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]12.771[/C][C]-4.27101[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]12.771[/C][C]0.728993[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]12.771[/C][C]-7.87101[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]12.771[/C][C]-6.37101[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]12.771[/C][C]-3.17101[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]12.771[/C][C]-1.17101[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]12.771[/C][C]-1.67101[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]13.2263[/C][C]-8.87627[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]13.592[/C][C]-0.89205[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]13.8385[/C][C]4.26146[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]12.5941[/C][C]5.25588[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]12.771[/C][C]3.82899[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]12.771[/C][C]-0.171007[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]13.8323[/C][C]3.26772[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]13.1612[/C][C]5.93879[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]13.2885[/C][C]2.81151[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]12.9713[/C][C]0.378672[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]13.7092[/C][C]4.69079[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]12.4922[/C][C]2.20784[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]12.9981[/C][C]-2.39813[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]13.0171[/C][C]-0.417139[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]13.6447[/C][C]2.55534[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]12.6882[/C][C]0.911814[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]12.771[/C][C]6.12899[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]13.0651[/C][C]1.03487[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]13.1814[/C][C]1.31863[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]12.7734[/C][C]3.37664[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]13.5767[/C][C]1.17331[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]12.5806[/C][C]2.21941[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]13.391[/C][C]-0.940968[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]11.8122[/C][C]0.837844[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]12.7216[/C][C]4.62842[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]13.4774[/C][C]-4.87738[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]13.1337[/C][C]5.26629[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]14.5561[/C][C]1.54386[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]12.771[/C][C]-1.17101[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]13.9201[/C][C]3.82995[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]13.0206[/C][C]2.22943[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]13.8827[/C][C]3.76726[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]13.2476[/C][C]3.10243[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]13.6382[/C][C]4.01181[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]13.5999[/C][C]6.0829e-05[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]13.3377[/C][C]1.01234[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]12.5337[/C][C]2.21632[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]14.1888[/C][C]4.06125[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]14.0731[/C][C]-4.17313[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.366[/C][C]2.63398[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]13.3065[/C][C]4.94354[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]12.9717[/C][C]3.87826[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]12.771[/C][C]1.82899[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]12.771[/C][C]1.07899[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]12.7365[/C][C]6.21354[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]13.5581[/C][C]2.04187[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]12.771[/C][C]2.07899[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]12.771[/C][C]-1.02101[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]12.771[/C][C]5.67899[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]12.771[/C][C]3.12899[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]13.0335[/C][C]4.06654[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]12.6343[/C][C]3.46573[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]12.771[/C][C]7.12899[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]12.771[/C][C]-1.82101[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]12.771[/C][C]5.67899[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]12.771[/C][C]2.32899[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]12.771[/C][C]2.22899[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]12.771[/C][C]-1.42101[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]12.771[/C][C]3.17899[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]12.771[/C][C]5.32899[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]12.771[/C][C]1.82899[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]13.7752[/C][C]1.62483[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.3921[/C][C]2.00792[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]12.771[/C][C]4.82899[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]13.6424[/C][C]-0.292378[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]12.6523[/C][C]6.44769[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]12.771[/C][C]2.57899[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]13.0266[/C][C]-5.42664[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]12.771[/C][C]0.628993[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]12.771[/C][C]1.12899[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]14.0975[/C][C]5.00253[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]12.771[/C][C]2.47899[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]12.771[/C][C]0.128993[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]12.771[/C][C]3.32899[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]12.771[/C][C]4.57899[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]12.771[/C][C]0.378993[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]12.771[/C][C]-0.621007[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]12.771[/C][C]-0.171007[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]12.771[/C][C]-2.42101[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]12.771[/C][C]2.62899[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]12.771[/C][C]-3.17101[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]12.771[/C][C]5.42899[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]12.771[/C][C]0.828993[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]12.771[/C][C]2.07899[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]12.6891[/C][C]2.06093[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]12.771[/C][C]1.32899[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]12.771[/C][C]2.12899[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]12.771[/C][C]3.47899[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]15.8225[/C][C]3.42753[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]12.771[/C][C]0.828993[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]12.8927[/C][C]0.707305[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]12.771[/C][C]2.87899[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]12.7262[/C][C]0.0237598[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]12.771[/C][C]1.82899[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]13.4591[/C][C]-3.60913[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]12.771[/C][C]-0.121007[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]12.771[/C][C]6.42899[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]12.771[/C][C]3.82899[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]12.771[/C][C]-1.57101[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]13.8855[/C][C]1.36447[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]12.1974[/C][C]-0.297416[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]12.771[/C][C]0.428993[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]12.8655[/C][C]3.48447[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]13.8901[/C][C]-1.49008[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]12.771[/C][C]3.07899[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]12.6822[/C][C]5.46781[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]12.771[/C][C]-1.62101[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]12.771[/C][C]2.87899[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]12.4889[/C][C]5.26112[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]12.771[/C][C]-5.12101[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.2668[/C][C]-0.916842[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]13.29[/C][C]2.30997[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]12.7047[/C][C]6.5953[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]12.771[/C][C]2.42899[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]12.8501[/C][C]4.24994[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]12.771[/C][C]2.82899[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]12.8699[/C][C]5.53009[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]13.3209[/C][C]5.72915[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]13.5122[/C][C]5.03784[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]13.4772[/C][C]5.62283[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]12.771[/C][C]0.328993[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]13.071[/C][C]-0.220968[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]13.5935[/C][C]-4.09346[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]13.1857[/C][C]-8.68573[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]12.771[/C][C]-0.921007[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]13.4347[/C][C]0.165322[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]13.2947[/C][C]-1.59471[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.771[/C][C]-0.371007[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]12.9538[/C][C]0.396179[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]12.771[/C][C]-1.37101[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]12.771[/C][C]2.12899[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]12.771[/C][C]7.12899[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]12.771[/C][C]-1.57101[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]12.771[/C][C]1.82899[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]12.7377[/C][C]4.86231[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]14.2737[/C][C]-0.223734[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]12.7508[/C][C]3.3492[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]13.1968[/C][C]0.153152[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]12.9837[/C][C]-1.13365[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]13.924[/C][C]-1.97396[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]12.771[/C][C]1.97899[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]12.771[/C][C]2.37899[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]14.4181[/C][C]-1.21814[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]12.771[/C][C]4.07899[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]12.771[/C][C]-4.92101[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]13.2173[/C][C]-5.51729[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]12.771[/C][C]-0.171007[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]12.771[/C][C]-4.92101[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]12.771[/C][C]-1.82101[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]12.771[/C][C]-0.421007[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]12.771[/C][C]-2.82101[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]12.771[/C][C]2.12899[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]12.771[/C][C]3.87899[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]12.771[/C][C]0.628993[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]12.771[/C][C]1.17899[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]12.771[/C][C]2.92899[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]12.771[/C][C]4.07899[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]12.771[/C][C]-1.82101[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]12.771[/C][C]2.57899[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]12.771[/C][C]-0.571007[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]12.771[/C][C]2.32899[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]12.771[/C][C]4.97899[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]12.771[/C][C]2.42899[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]13.2683[/C][C]1.33172[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]12.771[/C][C]3.87899[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]12.771[/C][C]-4.67101[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270632&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270632&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	13.0491	-0.149128
2	12.2	12.1142	0.0857714
3	12.8	13.2292	-0.429234
4	7.4	12.7205	-5.32048
5	6.7	13.1064	-6.40637
6	12.6	13.2319	-0.631905
7	14.8	12.8019	1.99811
8	13.3	14.5815	-1.28154
9	11.1	12.0401	-0.94009
10	8.2	13.0867	-4.88672
11	11.4	12.6161	-1.21614
12	6.4	12.3539	-5.95387
13	10.6	12.6553	-2.05532
14	12	13.2585	-1.25847
15	6.3	12.9757	-6.67567
16	11.3	12.771	-1.47101
17	11.9	12.7923	-0.892257
18	9.3	12.7869	-3.48694
19	9.6	12.771	-3.17101
20	10	13.0754	-3.07541
21	6.4	13.9006	-7.50061
22	13.8	13.2421	0.557928
23	10.8	12.8885	-2.08854
24	13.8	12.6332	1.16678
25	11.7	13.2794	-1.57938
26	10.9	12.708	-1.80798
27	16.1	12.771	3.32899
28	13.4	12.771	0.628993
29	9.9	12.419	-2.51899
30	11.5	12.9551	-1.45511
31	8.3	13.2439	-4.94391
32	11.7	14.3308	-2.63078
33	9	12.7587	-3.7587
34	9.7	12.6037	-2.90365
35	10.8	13.1462	-2.34618
36	10.3	13.5126	-3.2126
37	10.4	13.0297	-2.62973
38	12.7	12.771	-0.0710068
39	9.3	13.069	-3.76899
40	11.8	12.7104	-0.910363
41	5.9	13.094	-7.19403
42	11.4	13.342	-1.94198
43	13	13.2882	-0.288193
44	10.8	11.9569	-1.15687
45	12.3	12.771	-0.471007
46	11.3	12.3795	-1.07946
47	11.8	13.7769	-1.97689
48	7.9	12.771	-4.87101
49	12.7	12.3858	0.314156
50	12.3	12.771	-0.471007
51	11.6	12.771	-1.17101
52	6.7	12.771	-6.07101
53	10.9	13.4053	-2.50533
54	12.1	12.771	-0.671007
55	13.3	13.0612	0.238789
56	10.1	13.0981	-2.99812
57	5.7	12.771	-7.07101
58	14.3	13.7167	0.583347
59	8	12.771	-4.77101
60	13.3	12.771	0.528993
61	9.3	13.2592	-3.95916
62	12.5	13.1278	-0.627814
63	7.6	14.264	-6.66397
64	15.9	13.0809	2.81906
65	9.2	13.4564	-4.25645
66	9.1	12.771	-3.67101
67	11.1	12.7371	-1.63711
68	13	12.7886	0.211359
69	14.5	13.1678	1.33216
70	12.2	12.771	-0.571007
71	12.3	13.1525	-0.852517
72	11.4	12.1947	-0.794654
73	8.8	12.771	-3.97101
74	14.6	12.771	1.82899
75	12.6	13.0847	-0.484688
76	13	13.6603	-0.660283
77	12.6	12.771	-0.171007
78	13.2	13.0612	0.13885
79	9.9	12.771	-2.87101
80	7.7	12.5944	-4.89436
81	10.5	12.771	-2.27101
82	13.4	12.771	0.628993
83	10.9	12.771	-1.87101
84	4.3	12.771	-8.47101
85	10.3	12.771	-2.47101
86	11.8	12.771	-0.971007
87	11.2	12.771	-1.57101
88	11.4	12.771	-1.37101
89	8.6	12.771	-4.17101
90	13.2	12.771	0.428993
91	12.6	12.771	-0.171007
92	5.6	12.771	-7.17101
93	9.9	12.771	-2.87101
94	8.8	12.771	-3.97101
95	7.7	12.771	-5.07101
96	9	12.771	-3.77101
97	7.3	12.771	-5.47101
98	11.4	12.771	-1.37101
99	13.6	12.771	0.828993
100	7.9	12.771	-4.87101
101	10.7	12.771	-2.07101
102	10.3	12.771	-2.47101
103	8.3	12.771	-4.47101
104	9.6	12.771	-3.17101
105	14.2	12.771	1.42899
106	8.5	12.771	-4.27101
107	13.5	12.771	0.728993
108	4.9	12.771	-7.87101
109	6.4	12.771	-6.37101
110	9.6	12.771	-3.17101
111	11.6	12.771	-1.17101
112	11.1	12.771	-1.67101
113	4.35	13.2263	-8.87627
114	12.7	13.592	-0.89205
115	18.1	13.8385	4.26146
116	17.85	12.5941	5.25588
117	16.6	12.771	3.82899
118	12.6	12.771	-0.171007
119	17.1	13.8323	3.26772
120	19.1	13.1612	5.93879
121	16.1	13.2885	2.81151
122	13.35	12.9713	0.378672
123	18.4	13.7092	4.69079
124	14.7	12.4922	2.20784
125	10.6	12.9981	-2.39813
126	12.6	13.0171	-0.417139
127	16.2	13.6447	2.55534
128	13.6	12.6882	0.911814
129	18.9	12.771	6.12899
130	14.1	13.0651	1.03487
131	14.5	13.1814	1.31863
132	16.15	12.7734	3.37664
133	14.75	13.5767	1.17331
134	14.8	12.5806	2.21941
135	12.45	13.391	-0.940968
136	12.65	11.8122	0.837844
137	17.35	12.7216	4.62842
138	8.6	13.4774	-4.87738
139	18.4	13.1337	5.26629
140	16.1	14.5561	1.54386
141	11.6	12.771	-1.17101
142	17.75	13.9201	3.82995
143	15.25	13.0206	2.22943
144	17.65	13.8827	3.76726
145	16.35	13.2476	3.10243
146	17.65	13.6382	4.01181
147	13.6	13.5999	6.0829e-05
148	14.35	13.3377	1.01234
149	14.75	12.5337	2.21632
150	18.25	14.1888	4.06125
151	9.9	14.0731	-4.17313
152	16	13.366	2.63398
153	18.25	13.3065	4.94354
154	16.85	12.9717	3.87826
155	14.6	12.771	1.82899
156	13.85	12.771	1.07899
157	18.95	12.7365	6.21354
158	15.6	13.5581	2.04187
159	14.85	12.771	2.07899
160	11.75	12.771	-1.02101
161	18.45	12.771	5.67899
162	15.9	12.771	3.12899
163	17.1	13.0335	4.06654
164	16.1	12.6343	3.46573
165	19.9	12.771	7.12899
166	10.95	12.771	-1.82101
167	18.45	12.771	5.67899
168	15.1	12.771	2.32899
169	15	12.771	2.22899
170	11.35	12.771	-1.42101
171	15.95	12.771	3.17899
172	18.1	12.771	5.32899
173	14.6	12.771	1.82899
174	15.4	13.7752	1.62483
175	15.4	13.3921	2.00792
176	17.6	12.771	4.82899
177	13.35	13.6424	-0.292378
178	19.1	12.6523	6.44769
179	15.35	12.771	2.57899
180	7.6	13.0266	-5.42664
181	13.4	12.771	0.628993
182	13.9	12.771	1.12899
183	19.1	14.0975	5.00253
184	15.25	12.771	2.47899
185	12.9	12.771	0.128993
186	16.1	12.771	3.32899
187	17.35	12.771	4.57899
188	13.15	12.771	0.378993
189	12.15	12.771	-0.621007
190	12.6	12.771	-0.171007
191	10.35	12.771	-2.42101
192	15.4	12.771	2.62899
193	9.6	12.771	-3.17101
194	18.2	12.771	5.42899
195	13.6	12.771	0.828993
196	14.85	12.771	2.07899
197	14.75	12.6891	2.06093
198	14.1	12.771	1.32899
199	14.9	12.771	2.12899
200	16.25	12.771	3.47899
201	19.25	15.8225	3.42753
202	13.6	12.771	0.828993
203	13.6	12.8927	0.707305
204	15.65	12.771	2.87899
205	12.75	12.7262	0.0237598
206	14.6	12.771	1.82899
207	9.85	13.4591	-3.60913
208	12.65	12.771	-0.121007
209	19.2	12.771	6.42899
210	16.6	12.771	3.82899
211	11.2	12.771	-1.57101
212	15.25	13.8855	1.36447
213	11.9	12.1974	-0.297416
214	13.2	12.771	0.428993
215	16.35	12.8655	3.48447
216	12.4	13.8901	-1.49008
217	15.85	12.771	3.07899
218	18.15	12.6822	5.46781
219	11.15	12.771	-1.62101
220	15.65	12.771	2.87899
221	17.75	12.4889	5.26112
222	7.65	12.771	-5.12101
223	12.35	13.2668	-0.916842
224	15.6	13.29	2.30997
225	19.3	12.7047	6.5953
226	15.2	12.771	2.42899
227	17.1	12.8501	4.24994
228	15.6	12.771	2.82899
229	18.4	12.8699	5.53009
230	19.05	13.3209	5.72915
231	18.55	13.5122	5.03784
232	19.1	13.4772	5.62283
233	13.1	12.771	0.328993
234	12.85	13.071	-0.220968
235	9.5	13.5935	-4.09346
236	4.5	13.1857	-8.68573
237	11.85	12.771	-0.921007
238	13.6	13.4347	0.165322
239	11.7	13.2947	-1.59471
240	12.4	12.771	-0.371007
241	13.35	12.9538	0.396179
242	11.4	12.771	-1.37101
243	14.9	12.771	2.12899
244	19.9	12.771	7.12899
245	11.2	12.771	-1.57101
246	14.6	12.771	1.82899
247	17.6	12.7377	4.86231
248	14.05	14.2737	-0.223734
249	16.1	12.7508	3.3492
250	13.35	13.1968	0.153152
251	11.85	12.9837	-1.13365
252	11.95	13.924	-1.97396
253	14.75	12.771	1.97899
254	15.15	12.771	2.37899
255	13.2	14.4181	-1.21814
256	16.85	12.771	4.07899
257	7.85	12.771	-4.92101
258	7.7	13.2173	-5.51729
259	12.6	12.771	-0.171007
260	7.85	12.771	-4.92101
261	10.95	12.771	-1.82101
262	12.35	12.771	-0.421007
263	9.95	12.771	-2.82101
264	14.9	12.771	2.12899
265	16.65	12.771	3.87899
266	13.4	12.771	0.628993
267	13.95	12.771	1.17899
268	15.7	12.771	2.92899
269	16.85	12.771	4.07899
270	10.95	12.771	-1.82101
271	15.35	12.771	2.57899
272	12.2	12.771	-0.571007
273	15.1	12.771	2.32899
274	17.75	12.771	4.97899
275	15.2	12.771	2.42899
276	14.6	13.2683	1.33172
277	16.65	12.771	3.87899
278	8.1	12.771	-4.67101

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
11	0.0955664	0.191133	0.904434
12	0.216851	0.433702	0.783149
13	0.154246	0.308492	0.845754
14	0.144187	0.288373	0.855813
15	0.174011	0.348022	0.825989
16	0.141373	0.282746	0.858627
17	0.0971456	0.194291	0.902854
18	0.0638594	0.127719	0.936141
19	0.0397219	0.0794439	0.960278
20	0.025261	0.0505221	0.974739
21	0.0157625	0.0315251	0.984237
22	0.00869881	0.0173976	0.991301
23	0.00465684	0.00931367	0.995343
24	0.00581831	0.0116366	0.994182
25	0.00332409	0.00664819	0.996676
26	0.00182588	0.00365176	0.998174
27	0.00982595	0.0196519	0.990174
28	0.0065973	0.0131946	0.993403
29	0.00398633	0.00797266	0.996014
30	0.00232051	0.00464101	0.997679
31	0.00267065	0.00534129	0.997329
32	0.00166337	0.00332673	0.998337
33	0.0016251	0.00325021	0.998375
34	0.0124949	0.0249898	0.987505
35	0.00859088	0.0171818	0.991409
36	0.00632146	0.0126429	0.993679
37	0.00413245	0.0082649	0.995868
38	0.00259119	0.00518238	0.997409
39	0.0019905	0.00398099	0.99801
40	0.00125068	0.00250137	0.998749
41	0.00379162	0.00758323	0.996208
42	0.00283658	0.00567317	0.997163
43	0.00321077	0.00642153	0.996789
44	0.00283535	0.0056707	0.997165
45	0.00182991	0.00365982	0.99817
46	0.00136829	0.00273658	0.998632
47	0.000934848	0.0018697	0.999065
48	0.00169031	0.00338061	0.99831
49	0.00151259	0.00302518	0.998487
50	0.000995219	0.00199044	0.999005
51	0.000639582	0.00127916	0.99936
52	0.0016777	0.00335539	0.998322
53	0.00124572	0.00249144	0.998754
54	0.000844056	0.00168811	0.999156
55	0.000864529	0.00172906	0.999135
56	0.000669951	0.0013399	0.99933
57	0.00235883	0.00471766	0.997641
58	0.00170554	0.00341109	0.998294
59	0.00185368	0.00370737	0.998146
60	0.00167701	0.00335402	0.998323
61	0.00141703	0.00283406	0.998583
62	0.00124964	0.00249928	0.99875
63	0.00354805	0.0070961	0.996452
64	0.00618985	0.0123797	0.99381
65	0.00636515	0.0127303	0.993635
66	0.00558716	0.0111743	0.994413
67	0.00439562	0.00879125	0.995604
68	0.00410101	0.00820202	0.995899
69	0.00402388	0.00804775	0.995976
70	0.00308789	0.00617578	0.996912
71	0.00227521	0.00455043	0.997725
72	0.00168539	0.00337078	0.998315
73	0.00156106	0.00312211	0.998439
74	0.00185128	0.00370256	0.998149
75	0.00132179	0.00264358	0.998678
76	0.00116956	0.00233911	0.99883
77	0.000899364	0.00179873	0.999101
78	0.000772171	0.00154434	0.999228
79	0.000606276	0.00121255	0.999394
80	0.00082658	0.00165316	0.999173
81	0.000612772	0.00122554	0.999387
82	0.000527144	0.00105429	0.999473
83	0.000379206	0.000758411	0.999621
84	0.00234483	0.00468966	0.997655
85	0.00182798	0.00365597	0.998172
86	0.00138323	0.00276645	0.998617
87	0.0010284	0.0020568	0.998972
88	0.000759862	0.00151972	0.99924
89	0.000768126	0.00153625	0.999232
90	0.000663043	0.00132609	0.999337
91	0.000521088	0.00104218	0.999479
92	0.00154748	0.00309496	0.998453
93	0.00127332	0.00254664	0.998727
94	0.00124501	0.00249002	0.998755
95	0.00158589	0.00317178	0.998414
96	0.0014977	0.0029954	0.998502
97	0.00213129	0.00426258	0.997869
98	0.00168448	0.00336895	0.998316
99	0.00164564	0.00329127	0.998354
100	0.00202036	0.00404073	0.99798
101	0.00162475	0.00324949	0.998375
102	0.0013386	0.00267721	0.998661
103	0.00152148	0.00304296	0.998479
104	0.00136632	0.00273264	0.998634
105	0.00152552	0.00305105	0.998474
106	0.00169475	0.0033895	0.998305
107	0.00163112	0.00326224	0.998369
108	0.00630308	0.0126062	0.993697
109	0.0122256	0.0244512	0.987774
110	0.0117792	0.0235584	0.988221
111	0.0102126	0.0204253	0.989787
112	0.00888943	0.0177789	0.991111
113	0.0438387	0.0876775	0.956161
114	0.0457582	0.0915165	0.954242
115	0.0799391	0.159878	0.920061
116	0.141307	0.282614	0.858693
117	0.19139	0.38278	0.80861
118	0.178596	0.357192	0.821404
119	0.242263	0.484526	0.757737
120	0.366346	0.732692	0.633654
121	0.384289	0.768579	0.615711
122	0.374074	0.748148	0.625926
123	0.458078	0.916157	0.541922
124	0.453241	0.906481	0.546759
125	0.466648	0.933295	0.533352
126	0.442257	0.884514	0.557743
127	0.442606	0.885213	0.557394
128	0.422871	0.845741	0.577129
129	0.573028	0.853945	0.426972
130	0.555274	0.889451	0.444726
131	0.533722	0.932557	0.466278
132	0.539613	0.920774	0.460387
133	0.516088	0.967825	0.483912
134	0.510593	0.978814	0.489407
135	0.507051	0.985898	0.492949
136	0.48266	0.965321	0.51734
137	0.514273	0.971454	0.485727
138	0.558805	0.882389	0.441195
139	0.621381	0.757239	0.378619
140	0.617057	0.765886	0.382943
141	0.597492	0.805016	0.402508
142	0.625724	0.748553	0.374276
143	0.609743	0.780513	0.390257
144	0.648966	0.702069	0.351034
145	0.647893	0.704213	0.352107
146	0.676355	0.647289	0.323645
147	0.652529	0.694942	0.347471
148	0.624712	0.750576	0.375288
149	0.613758	0.772483	0.386242
150	0.630049	0.739902	0.369951
151	0.649363	0.701275	0.350637
152	0.63752	0.724959	0.36248
153	0.671268	0.657465	0.328732
154	0.681862	0.636275	0.318138
155	0.670301	0.659399	0.329699
156	0.650636	0.698728	0.349364
157	0.706279	0.587441	0.293721
158	0.685023	0.629953	0.314977
159	0.674055	0.65189	0.325945
160	0.654273	0.691454	0.345727
161	0.72515	0.549701	0.27485
162	0.726869	0.546262	0.273131
163	0.725002	0.549997	0.274998
164	0.719022	0.561956	0.280978
165	0.819966	0.360068	0.180034
166	0.810744	0.378512	0.189256
167	0.85383	0.29234	0.14617
168	0.843604	0.312792	0.156396
169	0.831718	0.336564	0.168282
170	0.819012	0.361976	0.180988
171	0.815582	0.368836	0.184418
172	0.847422	0.305155	0.152578
173	0.831591	0.336818	0.168409
174	0.820726	0.358547	0.179274
175	0.804467	0.391065	0.195533
176	0.826298	0.347404	0.173702
177	0.801646	0.396707	0.198354
178	0.836186	0.327629	0.163814
179	0.824289	0.351423	0.175711
180	0.872146	0.255707	0.127854
181	0.853264	0.293472	0.146736
182	0.833286	0.333428	0.166714
183	0.880713	0.238573	0.119287
184	0.869553	0.260895	0.130447
185	0.850262	0.299477	0.149738
186	0.845489	0.309022	0.154511
187	0.858212	0.283575	0.141788
188	0.836913	0.326173	0.163087
189	0.816791	0.366419	0.183209
190	0.793072	0.413856	0.206928
191	0.790381	0.419239	0.209619
192	0.774076	0.451847	0.225924
193	0.785833	0.428334	0.214167
194	0.817264	0.365472	0.182736
195	0.791629	0.416742	0.208371
196	0.769346	0.461308	0.230654
197	0.743134	0.513732	0.256866
198	0.713139	0.573722	0.286861
199	0.68691	0.62618	0.31309
200	0.678659	0.642682	0.321341
201	0.737093	0.525815	0.262907
202	0.704489	0.591022	0.295511
203	0.675151	0.649698	0.324849
204	0.656204	0.687592	0.343796
205	0.64079	0.718421	0.35921
206	0.608157	0.783686	0.391843
207	0.687154	0.625693	0.312846
208	0.652526	0.694947	0.347474
209	0.731221	0.537559	0.268779
210	0.731762	0.536476	0.268238
211	0.711354	0.577291	0.288646
212	0.682021	0.635958	0.317979
213	0.720704	0.558592	0.279296
214	0.684038	0.631924	0.315962
215	0.662566	0.674868	0.337434
216	0.623279	0.753443	0.376721
217	0.605867	0.788266	0.394133
218	0.604084	0.791833	0.395916
219	0.580421	0.839158	0.419579
220	0.557663	0.884674	0.442337
221	0.536817	0.926367	0.463183
222	0.624283	0.751435	0.375717
223	0.581537	0.836926	0.418463
224	0.545858	0.908285	0.454142
225	0.637433	0.725133	0.362567
226	0.605167	0.789665	0.394833
227	0.590878	0.818243	0.409122
228	0.563757	0.872486	0.436243
229	0.590433	0.819134	0.409567
230	0.663776	0.672449	0.336224
231	0.788707	0.422586	0.211293
232	0.776269	0.447462	0.223731
233	0.73695	0.5261	0.26305
234	0.708625	0.58275	0.291375
235	0.806398	0.387204	0.193602
236	0.873882	0.252237	0.126118
237	0.852207	0.295586	0.147793
238	0.823044	0.353913	0.176956
239	0.806993	0.386014	0.193007
240	0.771896	0.456208	0.228104
241	0.72902	0.54196	0.27098
242	0.703019	0.593963	0.296981
243	0.658398	0.683204	0.341602
244	0.793341	0.413319	0.206659
245	0.770529	0.458942	0.229471
246	0.726479	0.547042	0.273521
247	0.712132	0.575736	0.287868
248	0.757091	0.485818	0.242909
249	0.706138	0.587724	0.293862
250	0.645394	0.709213	0.354606
251	0.580242	0.839516	0.419758
252	0.512848	0.974305	0.487152
253	0.452368	0.904736	0.547632
254	0.399613	0.799226	0.600387
255	0.330461	0.660922	0.669539
256	0.331136	0.662272	0.668864
257	0.436892	0.873784	0.563108
258	0.366689	0.733377	0.633311
259	0.294065	0.588131	0.705935
260	0.431492	0.862984	0.568508
261	0.404746	0.809493	0.595254
262	0.332454	0.664909	0.667546
263	0.376732	0.753464	0.623268
264	0.276523	0.553046	0.723477
265	0.217331	0.434661	0.782669
266	0.136485	0.272969	0.863515
267	0.0724104	0.144821	0.92759

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.0955664 & 0.191133 & 0.904434 \tabularnewline
12 & 0.216851 & 0.433702 & 0.783149 \tabularnewline
13 & 0.154246 & 0.308492 & 0.845754 \tabularnewline
14 & 0.144187 & 0.288373 & 0.855813 \tabularnewline
15 & 0.174011 & 0.348022 & 0.825989 \tabularnewline
16 & 0.141373 & 0.282746 & 0.858627 \tabularnewline
17 & 0.0971456 & 0.194291 & 0.902854 \tabularnewline
18 & 0.0638594 & 0.127719 & 0.936141 \tabularnewline
19 & 0.0397219 & 0.0794439 & 0.960278 \tabularnewline
20 & 0.025261 & 0.0505221 & 0.974739 \tabularnewline
21 & 0.0157625 & 0.0315251 & 0.984237 \tabularnewline
22 & 0.00869881 & 0.0173976 & 0.991301 \tabularnewline
23 & 0.00465684 & 0.00931367 & 0.995343 \tabularnewline
24 & 0.00581831 & 0.0116366 & 0.994182 \tabularnewline
25 & 0.00332409 & 0.00664819 & 0.996676 \tabularnewline
26 & 0.00182588 & 0.00365176 & 0.998174 \tabularnewline
27 & 0.00982595 & 0.0196519 & 0.990174 \tabularnewline
28 & 0.0065973 & 0.0131946 & 0.993403 \tabularnewline
29 & 0.00398633 & 0.00797266 & 0.996014 \tabularnewline
30 & 0.00232051 & 0.00464101 & 0.997679 \tabularnewline
31 & 0.00267065 & 0.00534129 & 0.997329 \tabularnewline
32 & 0.00166337 & 0.00332673 & 0.998337 \tabularnewline
33 & 0.0016251 & 0.00325021 & 0.998375 \tabularnewline
34 & 0.0124949 & 0.0249898 & 0.987505 \tabularnewline
35 & 0.00859088 & 0.0171818 & 0.991409 \tabularnewline
36 & 0.00632146 & 0.0126429 & 0.993679 \tabularnewline
37 & 0.00413245 & 0.0082649 & 0.995868 \tabularnewline
38 & 0.00259119 & 0.00518238 & 0.997409 \tabularnewline
39 & 0.0019905 & 0.00398099 & 0.99801 \tabularnewline
40 & 0.00125068 & 0.00250137 & 0.998749 \tabularnewline
41 & 0.00379162 & 0.00758323 & 0.996208 \tabularnewline
42 & 0.00283658 & 0.00567317 & 0.997163 \tabularnewline
43 & 0.00321077 & 0.00642153 & 0.996789 \tabularnewline
44 & 0.00283535 & 0.0056707 & 0.997165 \tabularnewline
45 & 0.00182991 & 0.00365982 & 0.99817 \tabularnewline
46 & 0.00136829 & 0.00273658 & 0.998632 \tabularnewline
47 & 0.000934848 & 0.0018697 & 0.999065 \tabularnewline
48 & 0.00169031 & 0.00338061 & 0.99831 \tabularnewline
49 & 0.00151259 & 0.00302518 & 0.998487 \tabularnewline
50 & 0.000995219 & 0.00199044 & 0.999005 \tabularnewline
51 & 0.000639582 & 0.00127916 & 0.99936 \tabularnewline
52 & 0.0016777 & 0.00335539 & 0.998322 \tabularnewline
53 & 0.00124572 & 0.00249144 & 0.998754 \tabularnewline
54 & 0.000844056 & 0.00168811 & 0.999156 \tabularnewline
55 & 0.000864529 & 0.00172906 & 0.999135 \tabularnewline
56 & 0.000669951 & 0.0013399 & 0.99933 \tabularnewline
57 & 0.00235883 & 0.00471766 & 0.997641 \tabularnewline
58 & 0.00170554 & 0.00341109 & 0.998294 \tabularnewline
59 & 0.00185368 & 0.00370737 & 0.998146 \tabularnewline
60 & 0.00167701 & 0.00335402 & 0.998323 \tabularnewline
61 & 0.00141703 & 0.00283406 & 0.998583 \tabularnewline
62 & 0.00124964 & 0.00249928 & 0.99875 \tabularnewline
63 & 0.00354805 & 0.0070961 & 0.996452 \tabularnewline
64 & 0.00618985 & 0.0123797 & 0.99381 \tabularnewline
65 & 0.00636515 & 0.0127303 & 0.993635 \tabularnewline
66 & 0.00558716 & 0.0111743 & 0.994413 \tabularnewline
67 & 0.00439562 & 0.00879125 & 0.995604 \tabularnewline
68 & 0.00410101 & 0.00820202 & 0.995899 \tabularnewline
69 & 0.00402388 & 0.00804775 & 0.995976 \tabularnewline
70 & 0.00308789 & 0.00617578 & 0.996912 \tabularnewline
71 & 0.00227521 & 0.00455043 & 0.997725 \tabularnewline
72 & 0.00168539 & 0.00337078 & 0.998315 \tabularnewline
73 & 0.00156106 & 0.00312211 & 0.998439 \tabularnewline
74 & 0.00185128 & 0.00370256 & 0.998149 \tabularnewline
75 & 0.00132179 & 0.00264358 & 0.998678 \tabularnewline
76 & 0.00116956 & 0.00233911 & 0.99883 \tabularnewline
77 & 0.000899364 & 0.00179873 & 0.999101 \tabularnewline
78 & 0.000772171 & 0.00154434 & 0.999228 \tabularnewline
79 & 0.000606276 & 0.00121255 & 0.999394 \tabularnewline
80 & 0.00082658 & 0.00165316 & 0.999173 \tabularnewline
81 & 0.000612772 & 0.00122554 & 0.999387 \tabularnewline
82 & 0.000527144 & 0.00105429 & 0.999473 \tabularnewline
83 & 0.000379206 & 0.000758411 & 0.999621 \tabularnewline
84 & 0.00234483 & 0.00468966 & 0.997655 \tabularnewline
85 & 0.00182798 & 0.00365597 & 0.998172 \tabularnewline
86 & 0.00138323 & 0.00276645 & 0.998617 \tabularnewline
87 & 0.0010284 & 0.0020568 & 0.998972 \tabularnewline
88 & 0.000759862 & 0.00151972 & 0.99924 \tabularnewline
89 & 0.000768126 & 0.00153625 & 0.999232 \tabularnewline
90 & 0.000663043 & 0.00132609 & 0.999337 \tabularnewline
91 & 0.000521088 & 0.00104218 & 0.999479 \tabularnewline
92 & 0.00154748 & 0.00309496 & 0.998453 \tabularnewline
93 & 0.00127332 & 0.00254664 & 0.998727 \tabularnewline
94 & 0.00124501 & 0.00249002 & 0.998755 \tabularnewline
95 & 0.00158589 & 0.00317178 & 0.998414 \tabularnewline
96 & 0.0014977 & 0.0029954 & 0.998502 \tabularnewline
97 & 0.00213129 & 0.00426258 & 0.997869 \tabularnewline
98 & 0.00168448 & 0.00336895 & 0.998316 \tabularnewline
99 & 0.00164564 & 0.00329127 & 0.998354 \tabularnewline
100 & 0.00202036 & 0.00404073 & 0.99798 \tabularnewline
101 & 0.00162475 & 0.00324949 & 0.998375 \tabularnewline
102 & 0.0013386 & 0.00267721 & 0.998661 \tabularnewline
103 & 0.00152148 & 0.00304296 & 0.998479 \tabularnewline
104 & 0.00136632 & 0.00273264 & 0.998634 \tabularnewline
105 & 0.00152552 & 0.00305105 & 0.998474 \tabularnewline
106 & 0.00169475 & 0.0033895 & 0.998305 \tabularnewline
107 & 0.00163112 & 0.00326224 & 0.998369 \tabularnewline
108 & 0.00630308 & 0.0126062 & 0.993697 \tabularnewline
109 & 0.0122256 & 0.0244512 & 0.987774 \tabularnewline
110 & 0.0117792 & 0.0235584 & 0.988221 \tabularnewline
111 & 0.0102126 & 0.0204253 & 0.989787 \tabularnewline
112 & 0.00888943 & 0.0177789 & 0.991111 \tabularnewline
113 & 0.0438387 & 0.0876775 & 0.956161 \tabularnewline
114 & 0.0457582 & 0.0915165 & 0.954242 \tabularnewline
115 & 0.0799391 & 0.159878 & 0.920061 \tabularnewline
116 & 0.141307 & 0.282614 & 0.858693 \tabularnewline
117 & 0.19139 & 0.38278 & 0.80861 \tabularnewline
118 & 0.178596 & 0.357192 & 0.821404 \tabularnewline
119 & 0.242263 & 0.484526 & 0.757737 \tabularnewline
120 & 0.366346 & 0.732692 & 0.633654 \tabularnewline
121 & 0.384289 & 0.768579 & 0.615711 \tabularnewline
122 & 0.374074 & 0.748148 & 0.625926 \tabularnewline
123 & 0.458078 & 0.916157 & 0.541922 \tabularnewline
124 & 0.453241 & 0.906481 & 0.546759 \tabularnewline
125 & 0.466648 & 0.933295 & 0.533352 \tabularnewline
126 & 0.442257 & 0.884514 & 0.557743 \tabularnewline
127 & 0.442606 & 0.885213 & 0.557394 \tabularnewline
128 & 0.422871 & 0.845741 & 0.577129 \tabularnewline
129 & 0.573028 & 0.853945 & 0.426972 \tabularnewline
130 & 0.555274 & 0.889451 & 0.444726 \tabularnewline
131 & 0.533722 & 0.932557 & 0.466278 \tabularnewline
132 & 0.539613 & 0.920774 & 0.460387 \tabularnewline
133 & 0.516088 & 0.967825 & 0.483912 \tabularnewline
134 & 0.510593 & 0.978814 & 0.489407 \tabularnewline
135 & 0.507051 & 0.985898 & 0.492949 \tabularnewline
136 & 0.48266 & 0.965321 & 0.51734 \tabularnewline
137 & 0.514273 & 0.971454 & 0.485727 \tabularnewline
138 & 0.558805 & 0.882389 & 0.441195 \tabularnewline
139 & 0.621381 & 0.757239 & 0.378619 \tabularnewline
140 & 0.617057 & 0.765886 & 0.382943 \tabularnewline
141 & 0.597492 & 0.805016 & 0.402508 \tabularnewline
142 & 0.625724 & 0.748553 & 0.374276 \tabularnewline
143 & 0.609743 & 0.780513 & 0.390257 \tabularnewline
144 & 0.648966 & 0.702069 & 0.351034 \tabularnewline
145 & 0.647893 & 0.704213 & 0.352107 \tabularnewline
146 & 0.676355 & 0.647289 & 0.323645 \tabularnewline
147 & 0.652529 & 0.694942 & 0.347471 \tabularnewline
148 & 0.624712 & 0.750576 & 0.375288 \tabularnewline
149 & 0.613758 & 0.772483 & 0.386242 \tabularnewline
150 & 0.630049 & 0.739902 & 0.369951 \tabularnewline
151 & 0.649363 & 0.701275 & 0.350637 \tabularnewline
152 & 0.63752 & 0.724959 & 0.36248 \tabularnewline
153 & 0.671268 & 0.657465 & 0.328732 \tabularnewline
154 & 0.681862 & 0.636275 & 0.318138 \tabularnewline
155 & 0.670301 & 0.659399 & 0.329699 \tabularnewline
156 & 0.650636 & 0.698728 & 0.349364 \tabularnewline
157 & 0.706279 & 0.587441 & 0.293721 \tabularnewline
158 & 0.685023 & 0.629953 & 0.314977 \tabularnewline
159 & 0.674055 & 0.65189 & 0.325945 \tabularnewline
160 & 0.654273 & 0.691454 & 0.345727 \tabularnewline
161 & 0.72515 & 0.549701 & 0.27485 \tabularnewline
162 & 0.726869 & 0.546262 & 0.273131 \tabularnewline
163 & 0.725002 & 0.549997 & 0.274998 \tabularnewline
164 & 0.719022 & 0.561956 & 0.280978 \tabularnewline
165 & 0.819966 & 0.360068 & 0.180034 \tabularnewline
166 & 0.810744 & 0.378512 & 0.189256 \tabularnewline
167 & 0.85383 & 0.29234 & 0.14617 \tabularnewline
168 & 0.843604 & 0.312792 & 0.156396 \tabularnewline
169 & 0.831718 & 0.336564 & 0.168282 \tabularnewline
170 & 0.819012 & 0.361976 & 0.180988 \tabularnewline
171 & 0.815582 & 0.368836 & 0.184418 \tabularnewline
172 & 0.847422 & 0.305155 & 0.152578 \tabularnewline
173 & 0.831591 & 0.336818 & 0.168409 \tabularnewline
174 & 0.820726 & 0.358547 & 0.179274 \tabularnewline
175 & 0.804467 & 0.391065 & 0.195533 \tabularnewline
176 & 0.826298 & 0.347404 & 0.173702 \tabularnewline
177 & 0.801646 & 0.396707 & 0.198354 \tabularnewline
178 & 0.836186 & 0.327629 & 0.163814 \tabularnewline
179 & 0.824289 & 0.351423 & 0.175711 \tabularnewline
180 & 0.872146 & 0.255707 & 0.127854 \tabularnewline
181 & 0.853264 & 0.293472 & 0.146736 \tabularnewline
182 & 0.833286 & 0.333428 & 0.166714 \tabularnewline
183 & 0.880713 & 0.238573 & 0.119287 \tabularnewline
184 & 0.869553 & 0.260895 & 0.130447 \tabularnewline
185 & 0.850262 & 0.299477 & 0.149738 \tabularnewline
186 & 0.845489 & 0.309022 & 0.154511 \tabularnewline
187 & 0.858212 & 0.283575 & 0.141788 \tabularnewline
188 & 0.836913 & 0.326173 & 0.163087 \tabularnewline
189 & 0.816791 & 0.366419 & 0.183209 \tabularnewline
190 & 0.793072 & 0.413856 & 0.206928 \tabularnewline
191 & 0.790381 & 0.419239 & 0.209619 \tabularnewline
192 & 0.774076 & 0.451847 & 0.225924 \tabularnewline
193 & 0.785833 & 0.428334 & 0.214167 \tabularnewline
194 & 0.817264 & 0.365472 & 0.182736 \tabularnewline
195 & 0.791629 & 0.416742 & 0.208371 \tabularnewline
196 & 0.769346 & 0.461308 & 0.230654 \tabularnewline
197 & 0.743134 & 0.513732 & 0.256866 \tabularnewline
198 & 0.713139 & 0.573722 & 0.286861 \tabularnewline
199 & 0.68691 & 0.62618 & 0.31309 \tabularnewline
200 & 0.678659 & 0.642682 & 0.321341 \tabularnewline
201 & 0.737093 & 0.525815 & 0.262907 \tabularnewline
202 & 0.704489 & 0.591022 & 0.295511 \tabularnewline
203 & 0.675151 & 0.649698 & 0.324849 \tabularnewline
204 & 0.656204 & 0.687592 & 0.343796 \tabularnewline
205 & 0.64079 & 0.718421 & 0.35921 \tabularnewline
206 & 0.608157 & 0.783686 & 0.391843 \tabularnewline
207 & 0.687154 & 0.625693 & 0.312846 \tabularnewline
208 & 0.652526 & 0.694947 & 0.347474 \tabularnewline
209 & 0.731221 & 0.537559 & 0.268779 \tabularnewline
210 & 0.731762 & 0.536476 & 0.268238 \tabularnewline
211 & 0.711354 & 0.577291 & 0.288646 \tabularnewline
212 & 0.682021 & 0.635958 & 0.317979 \tabularnewline
213 & 0.720704 & 0.558592 & 0.279296 \tabularnewline
214 & 0.684038 & 0.631924 & 0.315962 \tabularnewline
215 & 0.662566 & 0.674868 & 0.337434 \tabularnewline
216 & 0.623279 & 0.753443 & 0.376721 \tabularnewline
217 & 0.605867 & 0.788266 & 0.394133 \tabularnewline
218 & 0.604084 & 0.791833 & 0.395916 \tabularnewline
219 & 0.580421 & 0.839158 & 0.419579 \tabularnewline
220 & 0.557663 & 0.884674 & 0.442337 \tabularnewline
221 & 0.536817 & 0.926367 & 0.463183 \tabularnewline
222 & 0.624283 & 0.751435 & 0.375717 \tabularnewline
223 & 0.581537 & 0.836926 & 0.418463 \tabularnewline
224 & 0.545858 & 0.908285 & 0.454142 \tabularnewline
225 & 0.637433 & 0.725133 & 0.362567 \tabularnewline
226 & 0.605167 & 0.789665 & 0.394833 \tabularnewline
227 & 0.590878 & 0.818243 & 0.409122 \tabularnewline
228 & 0.563757 & 0.872486 & 0.436243 \tabularnewline
229 & 0.590433 & 0.819134 & 0.409567 \tabularnewline
230 & 0.663776 & 0.672449 & 0.336224 \tabularnewline
231 & 0.788707 & 0.422586 & 0.211293 \tabularnewline
232 & 0.776269 & 0.447462 & 0.223731 \tabularnewline
233 & 0.73695 & 0.5261 & 0.26305 \tabularnewline
234 & 0.708625 & 0.58275 & 0.291375 \tabularnewline
235 & 0.806398 & 0.387204 & 0.193602 \tabularnewline
236 & 0.873882 & 0.252237 & 0.126118 \tabularnewline
237 & 0.852207 & 0.295586 & 0.147793 \tabularnewline
238 & 0.823044 & 0.353913 & 0.176956 \tabularnewline
239 & 0.806993 & 0.386014 & 0.193007 \tabularnewline
240 & 0.771896 & 0.456208 & 0.228104 \tabularnewline
241 & 0.72902 & 0.54196 & 0.27098 \tabularnewline
242 & 0.703019 & 0.593963 & 0.296981 \tabularnewline
243 & 0.658398 & 0.683204 & 0.341602 \tabularnewline
244 & 0.793341 & 0.413319 & 0.206659 \tabularnewline
245 & 0.770529 & 0.458942 & 0.229471 \tabularnewline
246 & 0.726479 & 0.547042 & 0.273521 \tabularnewline
247 & 0.712132 & 0.575736 & 0.287868 \tabularnewline
248 & 0.757091 & 0.485818 & 0.242909 \tabularnewline
249 & 0.706138 & 0.587724 & 0.293862 \tabularnewline
250 & 0.645394 & 0.709213 & 0.354606 \tabularnewline
251 & 0.580242 & 0.839516 & 0.419758 \tabularnewline
252 & 0.512848 & 0.974305 & 0.487152 \tabularnewline
253 & 0.452368 & 0.904736 & 0.547632 \tabularnewline
254 & 0.399613 & 0.799226 & 0.600387 \tabularnewline
255 & 0.330461 & 0.660922 & 0.669539 \tabularnewline
256 & 0.331136 & 0.662272 & 0.668864 \tabularnewline
257 & 0.436892 & 0.873784 & 0.563108 \tabularnewline
258 & 0.366689 & 0.733377 & 0.633311 \tabularnewline
259 & 0.294065 & 0.588131 & 0.705935 \tabularnewline
260 & 0.431492 & 0.862984 & 0.568508 \tabularnewline
261 & 0.404746 & 0.809493 & 0.595254 \tabularnewline
262 & 0.332454 & 0.664909 & 0.667546 \tabularnewline
263 & 0.376732 & 0.753464 & 0.623268 \tabularnewline
264 & 0.276523 & 0.553046 & 0.723477 \tabularnewline
265 & 0.217331 & 0.434661 & 0.782669 \tabularnewline
266 & 0.136485 & 0.272969 & 0.863515 \tabularnewline
267 & 0.0724104 & 0.144821 & 0.92759 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270632&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]0.0955664[/C][C]0.191133[/C][C]0.904434[/C][/ROW]
[ROW][C]12[/C][C]0.216851[/C][C]0.433702[/C][C]0.783149[/C][/ROW]
[ROW][C]13[/C][C]0.154246[/C][C]0.308492[/C][C]0.845754[/C][/ROW]
[ROW][C]14[/C][C]0.144187[/C][C]0.288373[/C][C]0.855813[/C][/ROW]
[ROW][C]15[/C][C]0.174011[/C][C]0.348022[/C][C]0.825989[/C][/ROW]
[ROW][C]16[/C][C]0.141373[/C][C]0.282746[/C][C]0.858627[/C][/ROW]
[ROW][C]17[/C][C]0.0971456[/C][C]0.194291[/C][C]0.902854[/C][/ROW]
[ROW][C]18[/C][C]0.0638594[/C][C]0.127719[/C][C]0.936141[/C][/ROW]
[ROW][C]19[/C][C]0.0397219[/C][C]0.0794439[/C][C]0.960278[/C][/ROW]
[ROW][C]20[/C][C]0.025261[/C][C]0.0505221[/C][C]0.974739[/C][/ROW]
[ROW][C]21[/C][C]0.0157625[/C][C]0.0315251[/C][C]0.984237[/C][/ROW]
[ROW][C]22[/C][C]0.00869881[/C][C]0.0173976[/C][C]0.991301[/C][/ROW]
[ROW][C]23[/C][C]0.00465684[/C][C]0.00931367[/C][C]0.995343[/C][/ROW]
[ROW][C]24[/C][C]0.00581831[/C][C]0.0116366[/C][C]0.994182[/C][/ROW]
[ROW][C]25[/C][C]0.00332409[/C][C]0.00664819[/C][C]0.996676[/C][/ROW]
[ROW][C]26[/C][C]0.00182588[/C][C]0.00365176[/C][C]0.998174[/C][/ROW]
[ROW][C]27[/C][C]0.00982595[/C][C]0.0196519[/C][C]0.990174[/C][/ROW]
[ROW][C]28[/C][C]0.0065973[/C][C]0.0131946[/C][C]0.993403[/C][/ROW]
[ROW][C]29[/C][C]0.00398633[/C][C]0.00797266[/C][C]0.996014[/C][/ROW]
[ROW][C]30[/C][C]0.00232051[/C][C]0.00464101[/C][C]0.997679[/C][/ROW]
[ROW][C]31[/C][C]0.00267065[/C][C]0.00534129[/C][C]0.997329[/C][/ROW]
[ROW][C]32[/C][C]0.00166337[/C][C]0.00332673[/C][C]0.998337[/C][/ROW]
[ROW][C]33[/C][C]0.0016251[/C][C]0.00325021[/C][C]0.998375[/C][/ROW]
[ROW][C]34[/C][C]0.0124949[/C][C]0.0249898[/C][C]0.987505[/C][/ROW]
[ROW][C]35[/C][C]0.00859088[/C][C]0.0171818[/C][C]0.991409[/C][/ROW]
[ROW][C]36[/C][C]0.00632146[/C][C]0.0126429[/C][C]0.993679[/C][/ROW]
[ROW][C]37[/C][C]0.00413245[/C][C]0.0082649[/C][C]0.995868[/C][/ROW]
[ROW][C]38[/C][C]0.00259119[/C][C]0.00518238[/C][C]0.997409[/C][/ROW]
[ROW][C]39[/C][C]0.0019905[/C][C]0.00398099[/C][C]0.99801[/C][/ROW]
[ROW][C]40[/C][C]0.00125068[/C][C]0.00250137[/C][C]0.998749[/C][/ROW]
[ROW][C]41[/C][C]0.00379162[/C][C]0.00758323[/C][C]0.996208[/C][/ROW]
[ROW][C]42[/C][C]0.00283658[/C][C]0.00567317[/C][C]0.997163[/C][/ROW]
[ROW][C]43[/C][C]0.00321077[/C][C]0.00642153[/C][C]0.996789[/C][/ROW]
[ROW][C]44[/C][C]0.00283535[/C][C]0.0056707[/C][C]0.997165[/C][/ROW]
[ROW][C]45[/C][C]0.00182991[/C][C]0.00365982[/C][C]0.99817[/C][/ROW]
[ROW][C]46[/C][C]0.00136829[/C][C]0.00273658[/C][C]0.998632[/C][/ROW]
[ROW][C]47[/C][C]0.000934848[/C][C]0.0018697[/C][C]0.999065[/C][/ROW]
[ROW][C]48[/C][C]0.00169031[/C][C]0.00338061[/C][C]0.99831[/C][/ROW]
[ROW][C]49[/C][C]0.00151259[/C][C]0.00302518[/C][C]0.998487[/C][/ROW]
[ROW][C]50[/C][C]0.000995219[/C][C]0.00199044[/C][C]0.999005[/C][/ROW]
[ROW][C]51[/C][C]0.000639582[/C][C]0.00127916[/C][C]0.99936[/C][/ROW]
[ROW][C]52[/C][C]0.0016777[/C][C]0.00335539[/C][C]0.998322[/C][/ROW]
[ROW][C]53[/C][C]0.00124572[/C][C]0.00249144[/C][C]0.998754[/C][/ROW]
[ROW][C]54[/C][C]0.000844056[/C][C]0.00168811[/C][C]0.999156[/C][/ROW]
[ROW][C]55[/C][C]0.000864529[/C][C]0.00172906[/C][C]0.999135[/C][/ROW]
[ROW][C]56[/C][C]0.000669951[/C][C]0.0013399[/C][C]0.99933[/C][/ROW]
[ROW][C]57[/C][C]0.00235883[/C][C]0.00471766[/C][C]0.997641[/C][/ROW]
[ROW][C]58[/C][C]0.00170554[/C][C]0.00341109[/C][C]0.998294[/C][/ROW]
[ROW][C]59[/C][C]0.00185368[/C][C]0.00370737[/C][C]0.998146[/C][/ROW]
[ROW][C]60[/C][C]0.00167701[/C][C]0.00335402[/C][C]0.998323[/C][/ROW]
[ROW][C]61[/C][C]0.00141703[/C][C]0.00283406[/C][C]0.998583[/C][/ROW]
[ROW][C]62[/C][C]0.00124964[/C][C]0.00249928[/C][C]0.99875[/C][/ROW]
[ROW][C]63[/C][C]0.00354805[/C][C]0.0070961[/C][C]0.996452[/C][/ROW]
[ROW][C]64[/C][C]0.00618985[/C][C]0.0123797[/C][C]0.99381[/C][/ROW]
[ROW][C]65[/C][C]0.00636515[/C][C]0.0127303[/C][C]0.993635[/C][/ROW]
[ROW][C]66[/C][C]0.00558716[/C][C]0.0111743[/C][C]0.994413[/C][/ROW]
[ROW][C]67[/C][C]0.00439562[/C][C]0.00879125[/C][C]0.995604[/C][/ROW]
[ROW][C]68[/C][C]0.00410101[/C][C]0.00820202[/C][C]0.995899[/C][/ROW]
[ROW][C]69[/C][C]0.00402388[/C][C]0.00804775[/C][C]0.995976[/C][/ROW]
[ROW][C]70[/C][C]0.00308789[/C][C]0.00617578[/C][C]0.996912[/C][/ROW]
[ROW][C]71[/C][C]0.00227521[/C][C]0.00455043[/C][C]0.997725[/C][/ROW]
[ROW][C]72[/C][C]0.00168539[/C][C]0.00337078[/C][C]0.998315[/C][/ROW]
[ROW][C]73[/C][C]0.00156106[/C][C]0.00312211[/C][C]0.998439[/C][/ROW]
[ROW][C]74[/C][C]0.00185128[/C][C]0.00370256[/C][C]0.998149[/C][/ROW]
[ROW][C]75[/C][C]0.00132179[/C][C]0.00264358[/C][C]0.998678[/C][/ROW]
[ROW][C]76[/C][C]0.00116956[/C][C]0.00233911[/C][C]0.99883[/C][/ROW]
[ROW][C]77[/C][C]0.000899364[/C][C]0.00179873[/C][C]0.999101[/C][/ROW]
[ROW][C]78[/C][C]0.000772171[/C][C]0.00154434[/C][C]0.999228[/C][/ROW]
[ROW][C]79[/C][C]0.000606276[/C][C]0.00121255[/C][C]0.999394[/C][/ROW]
[ROW][C]80[/C][C]0.00082658[/C][C]0.00165316[/C][C]0.999173[/C][/ROW]
[ROW][C]81[/C][C]0.000612772[/C][C]0.00122554[/C][C]0.999387[/C][/ROW]
[ROW][C]82[/C][C]0.000527144[/C][C]0.00105429[/C][C]0.999473[/C][/ROW]
[ROW][C]83[/C][C]0.000379206[/C][C]0.000758411[/C][C]0.999621[/C][/ROW]
[ROW][C]84[/C][C]0.00234483[/C][C]0.00468966[/C][C]0.997655[/C][/ROW]
[ROW][C]85[/C][C]0.00182798[/C][C]0.00365597[/C][C]0.998172[/C][/ROW]
[ROW][C]86[/C][C]0.00138323[/C][C]0.00276645[/C][C]0.998617[/C][/ROW]
[ROW][C]87[/C][C]0.0010284[/C][C]0.0020568[/C][C]0.998972[/C][/ROW]
[ROW][C]88[/C][C]0.000759862[/C][C]0.00151972[/C][C]0.99924[/C][/ROW]
[ROW][C]89[/C][C]0.000768126[/C][C]0.00153625[/C][C]0.999232[/C][/ROW]
[ROW][C]90[/C][C]0.000663043[/C][C]0.00132609[/C][C]0.999337[/C][/ROW]
[ROW][C]91[/C][C]0.000521088[/C][C]0.00104218[/C][C]0.999479[/C][/ROW]
[ROW][C]92[/C][C]0.00154748[/C][C]0.00309496[/C][C]0.998453[/C][/ROW]
[ROW][C]93[/C][C]0.00127332[/C][C]0.00254664[/C][C]0.998727[/C][/ROW]
[ROW][C]94[/C][C]0.00124501[/C][C]0.00249002[/C][C]0.998755[/C][/ROW]
[ROW][C]95[/C][C]0.00158589[/C][C]0.00317178[/C][C]0.998414[/C][/ROW]
[ROW][C]96[/C][C]0.0014977[/C][C]0.0029954[/C][C]0.998502[/C][/ROW]
[ROW][C]97[/C][C]0.00213129[/C][C]0.00426258[/C][C]0.997869[/C][/ROW]
[ROW][C]98[/C][C]0.00168448[/C][C]0.00336895[/C][C]0.998316[/C][/ROW]
[ROW][C]99[/C][C]0.00164564[/C][C]0.00329127[/C][C]0.998354[/C][/ROW]
[ROW][C]100[/C][C]0.00202036[/C][C]0.00404073[/C][C]0.99798[/C][/ROW]
[ROW][C]101[/C][C]0.00162475[/C][C]0.00324949[/C][C]0.998375[/C][/ROW]
[ROW][C]102[/C][C]0.0013386[/C][C]0.00267721[/C][C]0.998661[/C][/ROW]
[ROW][C]103[/C][C]0.00152148[/C][C]0.00304296[/C][C]0.998479[/C][/ROW]
[ROW][C]104[/C][C]0.00136632[/C][C]0.00273264[/C][C]0.998634[/C][/ROW]
[ROW][C]105[/C][C]0.00152552[/C][C]0.00305105[/C][C]0.998474[/C][/ROW]
[ROW][C]106[/C][C]0.00169475[/C][C]0.0033895[/C][C]0.998305[/C][/ROW]
[ROW][C]107[/C][C]0.00163112[/C][C]0.00326224[/C][C]0.998369[/C][/ROW]
[ROW][C]108[/C][C]0.00630308[/C][C]0.0126062[/C][C]0.993697[/C][/ROW]
[ROW][C]109[/C][C]0.0122256[/C][C]0.0244512[/C][C]0.987774[/C][/ROW]
[ROW][C]110[/C][C]0.0117792[/C][C]0.0235584[/C][C]0.988221[/C][/ROW]
[ROW][C]111[/C][C]0.0102126[/C][C]0.0204253[/C][C]0.989787[/C][/ROW]
[ROW][C]112[/C][C]0.00888943[/C][C]0.0177789[/C][C]0.991111[/C][/ROW]
[ROW][C]113[/C][C]0.0438387[/C][C]0.0876775[/C][C]0.956161[/C][/ROW]
[ROW][C]114[/C][C]0.0457582[/C][C]0.0915165[/C][C]0.954242[/C][/ROW]
[ROW][C]115[/C][C]0.0799391[/C][C]0.159878[/C][C]0.920061[/C][/ROW]
[ROW][C]116[/C][C]0.141307[/C][C]0.282614[/C][C]0.858693[/C][/ROW]
[ROW][C]117[/C][C]0.19139[/C][C]0.38278[/C][C]0.80861[/C][/ROW]
[ROW][C]118[/C][C]0.178596[/C][C]0.357192[/C][C]0.821404[/C][/ROW]
[ROW][C]119[/C][C]0.242263[/C][C]0.484526[/C][C]0.757737[/C][/ROW]
[ROW][C]120[/C][C]0.366346[/C][C]0.732692[/C][C]0.633654[/C][/ROW]
[ROW][C]121[/C][C]0.384289[/C][C]0.768579[/C][C]0.615711[/C][/ROW]
[ROW][C]122[/C][C]0.374074[/C][C]0.748148[/C][C]0.625926[/C][/ROW]
[ROW][C]123[/C][C]0.458078[/C][C]0.916157[/C][C]0.541922[/C][/ROW]
[ROW][C]124[/C][C]0.453241[/C][C]0.906481[/C][C]0.546759[/C][/ROW]
[ROW][C]125[/C][C]0.466648[/C][C]0.933295[/C][C]0.533352[/C][/ROW]
[ROW][C]126[/C][C]0.442257[/C][C]0.884514[/C][C]0.557743[/C][/ROW]
[ROW][C]127[/C][C]0.442606[/C][C]0.885213[/C][C]0.557394[/C][/ROW]
[ROW][C]128[/C][C]0.422871[/C][C]0.845741[/C][C]0.577129[/C][/ROW]
[ROW][C]129[/C][C]0.573028[/C][C]0.853945[/C][C]0.426972[/C][/ROW]
[ROW][C]130[/C][C]0.555274[/C][C]0.889451[/C][C]0.444726[/C][/ROW]
[ROW][C]131[/C][C]0.533722[/C][C]0.932557[/C][C]0.466278[/C][/ROW]
[ROW][C]132[/C][C]0.539613[/C][C]0.920774[/C][C]0.460387[/C][/ROW]
[ROW][C]133[/C][C]0.516088[/C][C]0.967825[/C][C]0.483912[/C][/ROW]
[ROW][C]134[/C][C]0.510593[/C][C]0.978814[/C][C]0.489407[/C][/ROW]
[ROW][C]135[/C][C]0.507051[/C][C]0.985898[/C][C]0.492949[/C][/ROW]
[ROW][C]136[/C][C]0.48266[/C][C]0.965321[/C][C]0.51734[/C][/ROW]
[ROW][C]137[/C][C]0.514273[/C][C]0.971454[/C][C]0.485727[/C][/ROW]
[ROW][C]138[/C][C]0.558805[/C][C]0.882389[/C][C]0.441195[/C][/ROW]
[ROW][C]139[/C][C]0.621381[/C][C]0.757239[/C][C]0.378619[/C][/ROW]
[ROW][C]140[/C][C]0.617057[/C][C]0.765886[/C][C]0.382943[/C][/ROW]
[ROW][C]141[/C][C]0.597492[/C][C]0.805016[/C][C]0.402508[/C][/ROW]
[ROW][C]142[/C][C]0.625724[/C][C]0.748553[/C][C]0.374276[/C][/ROW]
[ROW][C]143[/C][C]0.609743[/C][C]0.780513[/C][C]0.390257[/C][/ROW]
[ROW][C]144[/C][C]0.648966[/C][C]0.702069[/C][C]0.351034[/C][/ROW]
[ROW][C]145[/C][C]0.647893[/C][C]0.704213[/C][C]0.352107[/C][/ROW]
[ROW][C]146[/C][C]0.676355[/C][C]0.647289[/C][C]0.323645[/C][/ROW]
[ROW][C]147[/C][C]0.652529[/C][C]0.694942[/C][C]0.347471[/C][/ROW]
[ROW][C]148[/C][C]0.624712[/C][C]0.750576[/C][C]0.375288[/C][/ROW]
[ROW][C]149[/C][C]0.613758[/C][C]0.772483[/C][C]0.386242[/C][/ROW]
[ROW][C]150[/C][C]0.630049[/C][C]0.739902[/C][C]0.369951[/C][/ROW]
[ROW][C]151[/C][C]0.649363[/C][C]0.701275[/C][C]0.350637[/C][/ROW]
[ROW][C]152[/C][C]0.63752[/C][C]0.724959[/C][C]0.36248[/C][/ROW]
[ROW][C]153[/C][C]0.671268[/C][C]0.657465[/C][C]0.328732[/C][/ROW]
[ROW][C]154[/C][C]0.681862[/C][C]0.636275[/C][C]0.318138[/C][/ROW]
[ROW][C]155[/C][C]0.670301[/C][C]0.659399[/C][C]0.329699[/C][/ROW]
[ROW][C]156[/C][C]0.650636[/C][C]0.698728[/C][C]0.349364[/C][/ROW]
[ROW][C]157[/C][C]0.706279[/C][C]0.587441[/C][C]0.293721[/C][/ROW]
[ROW][C]158[/C][C]0.685023[/C][C]0.629953[/C][C]0.314977[/C][/ROW]
[ROW][C]159[/C][C]0.674055[/C][C]0.65189[/C][C]0.325945[/C][/ROW]
[ROW][C]160[/C][C]0.654273[/C][C]0.691454[/C][C]0.345727[/C][/ROW]
[ROW][C]161[/C][C]0.72515[/C][C]0.549701[/C][C]0.27485[/C][/ROW]
[ROW][C]162[/C][C]0.726869[/C][C]0.546262[/C][C]0.273131[/C][/ROW]
[ROW][C]163[/C][C]0.725002[/C][C]0.549997[/C][C]0.274998[/C][/ROW]
[ROW][C]164[/C][C]0.719022[/C][C]0.561956[/C][C]0.280978[/C][/ROW]
[ROW][C]165[/C][C]0.819966[/C][C]0.360068[/C][C]0.180034[/C][/ROW]
[ROW][C]166[/C][C]0.810744[/C][C]0.378512[/C][C]0.189256[/C][/ROW]
[ROW][C]167[/C][C]0.85383[/C][C]0.29234[/C][C]0.14617[/C][/ROW]
[ROW][C]168[/C][C]0.843604[/C][C]0.312792[/C][C]0.156396[/C][/ROW]
[ROW][C]169[/C][C]0.831718[/C][C]0.336564[/C][C]0.168282[/C][/ROW]
[ROW][C]170[/C][C]0.819012[/C][C]0.361976[/C][C]0.180988[/C][/ROW]
[ROW][C]171[/C][C]0.815582[/C][C]0.368836[/C][C]0.184418[/C][/ROW]
[ROW][C]172[/C][C]0.847422[/C][C]0.305155[/C][C]0.152578[/C][/ROW]
[ROW][C]173[/C][C]0.831591[/C][C]0.336818[/C][C]0.168409[/C][/ROW]
[ROW][C]174[/C][C]0.820726[/C][C]0.358547[/C][C]0.179274[/C][/ROW]
[ROW][C]175[/C][C]0.804467[/C][C]0.391065[/C][C]0.195533[/C][/ROW]
[ROW][C]176[/C][C]0.826298[/C][C]0.347404[/C][C]0.173702[/C][/ROW]
[ROW][C]177[/C][C]0.801646[/C][C]0.396707[/C][C]0.198354[/C][/ROW]
[ROW][C]178[/C][C]0.836186[/C][C]0.327629[/C][C]0.163814[/C][/ROW]
[ROW][C]179[/C][C]0.824289[/C][C]0.351423[/C][C]0.175711[/C][/ROW]
[ROW][C]180[/C][C]0.872146[/C][C]0.255707[/C][C]0.127854[/C][/ROW]
[ROW][C]181[/C][C]0.853264[/C][C]0.293472[/C][C]0.146736[/C][/ROW]
[ROW][C]182[/C][C]0.833286[/C][C]0.333428[/C][C]0.166714[/C][/ROW]
[ROW][C]183[/C][C]0.880713[/C][C]0.238573[/C][C]0.119287[/C][/ROW]
[ROW][C]184[/C][C]0.869553[/C][C]0.260895[/C][C]0.130447[/C][/ROW]
[ROW][C]185[/C][C]0.850262[/C][C]0.299477[/C][C]0.149738[/C][/ROW]
[ROW][C]186[/C][C]0.845489[/C][C]0.309022[/C][C]0.154511[/C][/ROW]
[ROW][C]187[/C][C]0.858212[/C][C]0.283575[/C][C]0.141788[/C][/ROW]
[ROW][C]188[/C][C]0.836913[/C][C]0.326173[/C][C]0.163087[/C][/ROW]
[ROW][C]189[/C][C]0.816791[/C][C]0.366419[/C][C]0.183209[/C][/ROW]
[ROW][C]190[/C][C]0.793072[/C][C]0.413856[/C][C]0.206928[/C][/ROW]
[ROW][C]191[/C][C]0.790381[/C][C]0.419239[/C][C]0.209619[/C][/ROW]
[ROW][C]192[/C][C]0.774076[/C][C]0.451847[/C][C]0.225924[/C][/ROW]
[ROW][C]193[/C][C]0.785833[/C][C]0.428334[/C][C]0.214167[/C][/ROW]
[ROW][C]194[/C][C]0.817264[/C][C]0.365472[/C][C]0.182736[/C][/ROW]
[ROW][C]195[/C][C]0.791629[/C][C]0.416742[/C][C]0.208371[/C][/ROW]
[ROW][C]196[/C][C]0.769346[/C][C]0.461308[/C][C]0.230654[/C][/ROW]
[ROW][C]197[/C][C]0.743134[/C][C]0.513732[/C][C]0.256866[/C][/ROW]
[ROW][C]198[/C][C]0.713139[/C][C]0.573722[/C][C]0.286861[/C][/ROW]
[ROW][C]199[/C][C]0.68691[/C][C]0.62618[/C][C]0.31309[/C][/ROW]
[ROW][C]200[/C][C]0.678659[/C][C]0.642682[/C][C]0.321341[/C][/ROW]
[ROW][C]201[/C][C]0.737093[/C][C]0.525815[/C][C]0.262907[/C][/ROW]
[ROW][C]202[/C][C]0.704489[/C][C]0.591022[/C][C]0.295511[/C][/ROW]
[ROW][C]203[/C][C]0.675151[/C][C]0.649698[/C][C]0.324849[/C][/ROW]
[ROW][C]204[/C][C]0.656204[/C][C]0.687592[/C][C]0.343796[/C][/ROW]
[ROW][C]205[/C][C]0.64079[/C][C]0.718421[/C][C]0.35921[/C][/ROW]
[ROW][C]206[/C][C]0.608157[/C][C]0.783686[/C][C]0.391843[/C][/ROW]
[ROW][C]207[/C][C]0.687154[/C][C]0.625693[/C][C]0.312846[/C][/ROW]
[ROW][C]208[/C][C]0.652526[/C][C]0.694947[/C][C]0.347474[/C][/ROW]
[ROW][C]209[/C][C]0.731221[/C][C]0.537559[/C][C]0.268779[/C][/ROW]
[ROW][C]210[/C][C]0.731762[/C][C]0.536476[/C][C]0.268238[/C][/ROW]
[ROW][C]211[/C][C]0.711354[/C][C]0.577291[/C][C]0.288646[/C][/ROW]
[ROW][C]212[/C][C]0.682021[/C][C]0.635958[/C][C]0.317979[/C][/ROW]
[ROW][C]213[/C][C]0.720704[/C][C]0.558592[/C][C]0.279296[/C][/ROW]
[ROW][C]214[/C][C]0.684038[/C][C]0.631924[/C][C]0.315962[/C][/ROW]
[ROW][C]215[/C][C]0.662566[/C][C]0.674868[/C][C]0.337434[/C][/ROW]
[ROW][C]216[/C][C]0.623279[/C][C]0.753443[/C][C]0.376721[/C][/ROW]
[ROW][C]217[/C][C]0.605867[/C][C]0.788266[/C][C]0.394133[/C][/ROW]
[ROW][C]218[/C][C]0.604084[/C][C]0.791833[/C][C]0.395916[/C][/ROW]
[ROW][C]219[/C][C]0.580421[/C][C]0.839158[/C][C]0.419579[/C][/ROW]
[ROW][C]220[/C][C]0.557663[/C][C]0.884674[/C][C]0.442337[/C][/ROW]
[ROW][C]221[/C][C]0.536817[/C][C]0.926367[/C][C]0.463183[/C][/ROW]
[ROW][C]222[/C][C]0.624283[/C][C]0.751435[/C][C]0.375717[/C][/ROW]
[ROW][C]223[/C][C]0.581537[/C][C]0.836926[/C][C]0.418463[/C][/ROW]
[ROW][C]224[/C][C]0.545858[/C][C]0.908285[/C][C]0.454142[/C][/ROW]
[ROW][C]225[/C][C]0.637433[/C][C]0.725133[/C][C]0.362567[/C][/ROW]
[ROW][C]226[/C][C]0.605167[/C][C]0.789665[/C][C]0.394833[/C][/ROW]
[ROW][C]227[/C][C]0.590878[/C][C]0.818243[/C][C]0.409122[/C][/ROW]
[ROW][C]228[/C][C]0.563757[/C][C]0.872486[/C][C]0.436243[/C][/ROW]
[ROW][C]229[/C][C]0.590433[/C][C]0.819134[/C][C]0.409567[/C][/ROW]
[ROW][C]230[/C][C]0.663776[/C][C]0.672449[/C][C]0.336224[/C][/ROW]
[ROW][C]231[/C][C]0.788707[/C][C]0.422586[/C][C]0.211293[/C][/ROW]
[ROW][C]232[/C][C]0.776269[/C][C]0.447462[/C][C]0.223731[/C][/ROW]
[ROW][C]233[/C][C]0.73695[/C][C]0.5261[/C][C]0.26305[/C][/ROW]
[ROW][C]234[/C][C]0.708625[/C][C]0.58275[/C][C]0.291375[/C][/ROW]
[ROW][C]235[/C][C]0.806398[/C][C]0.387204[/C][C]0.193602[/C][/ROW]
[ROW][C]236[/C][C]0.873882[/C][C]0.252237[/C][C]0.126118[/C][/ROW]
[ROW][C]237[/C][C]0.852207[/C][C]0.295586[/C][C]0.147793[/C][/ROW]
[ROW][C]238[/C][C]0.823044[/C][C]0.353913[/C][C]0.176956[/C][/ROW]
[ROW][C]239[/C][C]0.806993[/C][C]0.386014[/C][C]0.193007[/C][/ROW]
[ROW][C]240[/C][C]0.771896[/C][C]0.456208[/C][C]0.228104[/C][/ROW]
[ROW][C]241[/C][C]0.72902[/C][C]0.54196[/C][C]0.27098[/C][/ROW]
[ROW][C]242[/C][C]0.703019[/C][C]0.593963[/C][C]0.296981[/C][/ROW]
[ROW][C]243[/C][C]0.658398[/C][C]0.683204[/C][C]0.341602[/C][/ROW]
[ROW][C]244[/C][C]0.793341[/C][C]0.413319[/C][C]0.206659[/C][/ROW]
[ROW][C]245[/C][C]0.770529[/C][C]0.458942[/C][C]0.229471[/C][/ROW]
[ROW][C]246[/C][C]0.726479[/C][C]0.547042[/C][C]0.273521[/C][/ROW]
[ROW][C]247[/C][C]0.712132[/C][C]0.575736[/C][C]0.287868[/C][/ROW]
[ROW][C]248[/C][C]0.757091[/C][C]0.485818[/C][C]0.242909[/C][/ROW]
[ROW][C]249[/C][C]0.706138[/C][C]0.587724[/C][C]0.293862[/C][/ROW]
[ROW][C]250[/C][C]0.645394[/C][C]0.709213[/C][C]0.354606[/C][/ROW]
[ROW][C]251[/C][C]0.580242[/C][C]0.839516[/C][C]0.419758[/C][/ROW]
[ROW][C]252[/C][C]0.512848[/C][C]0.974305[/C][C]0.487152[/C][/ROW]
[ROW][C]253[/C][C]0.452368[/C][C]0.904736[/C][C]0.547632[/C][/ROW]
[ROW][C]254[/C][C]0.399613[/C][C]0.799226[/C][C]0.600387[/C][/ROW]
[ROW][C]255[/C][C]0.330461[/C][C]0.660922[/C][C]0.669539[/C][/ROW]
[ROW][C]256[/C][C]0.331136[/C][C]0.662272[/C][C]0.668864[/C][/ROW]
[ROW][C]257[/C][C]0.436892[/C][C]0.873784[/C][C]0.563108[/C][/ROW]
[ROW][C]258[/C][C]0.366689[/C][C]0.733377[/C][C]0.633311[/C][/ROW]
[ROW][C]259[/C][C]0.294065[/C][C]0.588131[/C][C]0.705935[/C][/ROW]
[ROW][C]260[/C][C]0.431492[/C][C]0.862984[/C][C]0.568508[/C][/ROW]
[ROW][C]261[/C][C]0.404746[/C][C]0.809493[/C][C]0.595254[/C][/ROW]
[ROW][C]262[/C][C]0.332454[/C][C]0.664909[/C][C]0.667546[/C][/ROW]
[ROW][C]263[/C][C]0.376732[/C][C]0.753464[/C][C]0.623268[/C][/ROW]
[ROW][C]264[/C][C]0.276523[/C][C]0.553046[/C][C]0.723477[/C][/ROW]
[ROW][C]265[/C][C]0.217331[/C][C]0.434661[/C][C]0.782669[/C][/ROW]
[ROW][C]266[/C][C]0.136485[/C][C]0.272969[/C][C]0.863515[/C][/ROW]
[ROW][C]267[/C][C]0.0724104[/C][C]0.144821[/C][C]0.92759[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270632&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270632&T=5

As an alternative you can also use a QR Code:

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

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
11	0.0955664	0.191133	0.904434
12	0.216851	0.433702	0.783149
13	0.154246	0.308492	0.845754
14	0.144187	0.288373	0.855813
15	0.174011	0.348022	0.825989
16	0.141373	0.282746	0.858627
17	0.0971456	0.194291	0.902854
18	0.0638594	0.127719	0.936141
19	0.0397219	0.0794439	0.960278
20	0.025261	0.0505221	0.974739
21	0.0157625	0.0315251	0.984237
22	0.00869881	0.0173976	0.991301
23	0.00465684	0.00931367	0.995343
24	0.00581831	0.0116366	0.994182
25	0.00332409	0.00664819	0.996676
26	0.00182588	0.00365176	0.998174
27	0.00982595	0.0196519	0.990174
28	0.0065973	0.0131946	0.993403
29	0.00398633	0.00797266	0.996014
30	0.00232051	0.00464101	0.997679
31	0.00267065	0.00534129	0.997329
32	0.00166337	0.00332673	0.998337
33	0.0016251	0.00325021	0.998375
34	0.0124949	0.0249898	0.987505
35	0.00859088	0.0171818	0.991409
36	0.00632146	0.0126429	0.993679
37	0.00413245	0.0082649	0.995868
38	0.00259119	0.00518238	0.997409
39	0.0019905	0.00398099	0.99801
40	0.00125068	0.00250137	0.998749
41	0.00379162	0.00758323	0.996208
42	0.00283658	0.00567317	0.997163
43	0.00321077	0.00642153	0.996789
44	0.00283535	0.0056707	0.997165
45	0.00182991	0.00365982	0.99817
46	0.00136829	0.00273658	0.998632
47	0.000934848	0.0018697	0.999065
48	0.00169031	0.00338061	0.99831
49	0.00151259	0.00302518	0.998487
50	0.000995219	0.00199044	0.999005
51	0.000639582	0.00127916	0.99936
52	0.0016777	0.00335539	0.998322
53	0.00124572	0.00249144	0.998754
54	0.000844056	0.00168811	0.999156
55	0.000864529	0.00172906	0.999135
56	0.000669951	0.0013399	0.99933
57	0.00235883	0.00471766	0.997641
58	0.00170554	0.00341109	0.998294
59	0.00185368	0.00370737	0.998146
60	0.00167701	0.00335402	0.998323
61	0.00141703	0.00283406	0.998583
62	0.00124964	0.00249928	0.99875
63	0.00354805	0.0070961	0.996452
64	0.00618985	0.0123797	0.99381
65	0.00636515	0.0127303	0.993635
66	0.00558716	0.0111743	0.994413
67	0.00439562	0.00879125	0.995604
68	0.00410101	0.00820202	0.995899
69	0.00402388	0.00804775	0.995976
70	0.00308789	0.00617578	0.996912
71	0.00227521	0.00455043	0.997725
72	0.00168539	0.00337078	0.998315
73	0.00156106	0.00312211	0.998439
74	0.00185128	0.00370256	0.998149
75	0.00132179	0.00264358	0.998678
76	0.00116956	0.00233911	0.99883
77	0.000899364	0.00179873	0.999101
78	0.000772171	0.00154434	0.999228
79	0.000606276	0.00121255	0.999394
80	0.00082658	0.00165316	0.999173
81	0.000612772	0.00122554	0.999387
82	0.000527144	0.00105429	0.999473
83	0.000379206	0.000758411	0.999621
84	0.00234483	0.00468966	0.997655
85	0.00182798	0.00365597	0.998172
86	0.00138323	0.00276645	0.998617
87	0.0010284	0.0020568	0.998972
88	0.000759862	0.00151972	0.99924
89	0.000768126	0.00153625	0.999232
90	0.000663043	0.00132609	0.999337
91	0.000521088	0.00104218	0.999479
92	0.00154748	0.00309496	0.998453
93	0.00127332	0.00254664	0.998727
94	0.00124501	0.00249002	0.998755
95	0.00158589	0.00317178	0.998414
96	0.0014977	0.0029954	0.998502
97	0.00213129	0.00426258	0.997869
98	0.00168448	0.00336895	0.998316
99	0.00164564	0.00329127	0.998354
100	0.00202036	0.00404073	0.99798
101	0.00162475	0.00324949	0.998375
102	0.0013386	0.00267721	0.998661
103	0.00152148	0.00304296	0.998479
104	0.00136632	0.00273264	0.998634
105	0.00152552	0.00305105	0.998474
106	0.00169475	0.0033895	0.998305
107	0.00163112	0.00326224	0.998369
108	0.00630308	0.0126062	0.993697
109	0.0122256	0.0244512	0.987774
110	0.0117792	0.0235584	0.988221
111	0.0102126	0.0204253	0.989787
112	0.00888943	0.0177789	0.991111
113	0.0438387	0.0876775	0.956161
114	0.0457582	0.0915165	0.954242
115	0.0799391	0.159878	0.920061
116	0.141307	0.282614	0.858693
117	0.19139	0.38278	0.80861
118	0.178596	0.357192	0.821404
119	0.242263	0.484526	0.757737
120	0.366346	0.732692	0.633654
121	0.384289	0.768579	0.615711
122	0.374074	0.748148	0.625926
123	0.458078	0.916157	0.541922
124	0.453241	0.906481	0.546759
125	0.466648	0.933295	0.533352
126	0.442257	0.884514	0.557743
127	0.442606	0.885213	0.557394
128	0.422871	0.845741	0.577129
129	0.573028	0.853945	0.426972
130	0.555274	0.889451	0.444726
131	0.533722	0.932557	0.466278
132	0.539613	0.920774	0.460387
133	0.516088	0.967825	0.483912
134	0.510593	0.978814	0.489407
135	0.507051	0.985898	0.492949
136	0.48266	0.965321	0.51734
137	0.514273	0.971454	0.485727
138	0.558805	0.882389	0.441195
139	0.621381	0.757239	0.378619
140	0.617057	0.765886	0.382943
141	0.597492	0.805016	0.402508
142	0.625724	0.748553	0.374276
143	0.609743	0.780513	0.390257
144	0.648966	0.702069	0.351034
145	0.647893	0.704213	0.352107
146	0.676355	0.647289	0.323645
147	0.652529	0.694942	0.347471
148	0.624712	0.750576	0.375288
149	0.613758	0.772483	0.386242
150	0.630049	0.739902	0.369951
151	0.649363	0.701275	0.350637
152	0.63752	0.724959	0.36248
153	0.671268	0.657465	0.328732
154	0.681862	0.636275	0.318138
155	0.670301	0.659399	0.329699
156	0.650636	0.698728	0.349364
157	0.706279	0.587441	0.293721
158	0.685023	0.629953	0.314977
159	0.674055	0.65189	0.325945
160	0.654273	0.691454	0.345727
161	0.72515	0.549701	0.27485
162	0.726869	0.546262	0.273131
163	0.725002	0.549997	0.274998
164	0.719022	0.561956	0.280978
165	0.819966	0.360068	0.180034
166	0.810744	0.378512	0.189256
167	0.85383	0.29234	0.14617
168	0.843604	0.312792	0.156396
169	0.831718	0.336564	0.168282
170	0.819012	0.361976	0.180988
171	0.815582	0.368836	0.184418
172	0.847422	0.305155	0.152578
173	0.831591	0.336818	0.168409
174	0.820726	0.358547	0.179274
175	0.804467	0.391065	0.195533
176	0.826298	0.347404	0.173702
177	0.801646	0.396707	0.198354
178	0.836186	0.327629	0.163814
179	0.824289	0.351423	0.175711
180	0.872146	0.255707	0.127854
181	0.853264	0.293472	0.146736
182	0.833286	0.333428	0.166714
183	0.880713	0.238573	0.119287
184	0.869553	0.260895	0.130447
185	0.850262	0.299477	0.149738
186	0.845489	0.309022	0.154511
187	0.858212	0.283575	0.141788
188	0.836913	0.326173	0.163087
189	0.816791	0.366419	0.183209
190	0.793072	0.413856	0.206928
191	0.790381	0.419239	0.209619
192	0.774076	0.451847	0.225924
193	0.785833	0.428334	0.214167
194	0.817264	0.365472	0.182736
195	0.791629	0.416742	0.208371
196	0.769346	0.461308	0.230654
197	0.743134	0.513732	0.256866
198	0.713139	0.573722	0.286861
199	0.68691	0.62618	0.31309
200	0.678659	0.642682	0.321341
201	0.737093	0.525815	0.262907
202	0.704489	0.591022	0.295511
203	0.675151	0.649698	0.324849
204	0.656204	0.687592	0.343796
205	0.64079	0.718421	0.35921
206	0.608157	0.783686	0.391843
207	0.687154	0.625693	0.312846
208	0.652526	0.694947	0.347474
209	0.731221	0.537559	0.268779
210	0.731762	0.536476	0.268238
211	0.711354	0.577291	0.288646
212	0.682021	0.635958	0.317979
213	0.720704	0.558592	0.279296
214	0.684038	0.631924	0.315962
215	0.662566	0.674868	0.337434
216	0.623279	0.753443	0.376721
217	0.605867	0.788266	0.394133
218	0.604084	0.791833	0.395916
219	0.580421	0.839158	0.419579
220	0.557663	0.884674	0.442337
221	0.536817	0.926367	0.463183
222	0.624283	0.751435	0.375717
223	0.581537	0.836926	0.418463
224	0.545858	0.908285	0.454142
225	0.637433	0.725133	0.362567
226	0.605167	0.789665	0.394833
227	0.590878	0.818243	0.409122
228	0.563757	0.872486	0.436243
229	0.590433	0.819134	0.409567
230	0.663776	0.672449	0.336224
231	0.788707	0.422586	0.211293
232	0.776269	0.447462	0.223731
233	0.73695	0.5261	0.26305
234	0.708625	0.58275	0.291375
235	0.806398	0.387204	0.193602
236	0.873882	0.252237	0.126118
237	0.852207	0.295586	0.147793
238	0.823044	0.353913	0.176956
239	0.806993	0.386014	0.193007
240	0.771896	0.456208	0.228104
241	0.72902	0.54196	0.27098
242	0.703019	0.593963	0.296981
243	0.658398	0.683204	0.341602
244	0.793341	0.413319	0.206659
245	0.770529	0.458942	0.229471
246	0.726479	0.547042	0.273521
247	0.712132	0.575736	0.287868
248	0.757091	0.485818	0.242909
249	0.706138	0.587724	0.293862
250	0.645394	0.709213	0.354606
251	0.580242	0.839516	0.419758
252	0.512848	0.974305	0.487152
253	0.452368	0.904736	0.547632
254	0.399613	0.799226	0.600387
255	0.330461	0.660922	0.669539
256	0.331136	0.662272	0.668864
257	0.436892	0.873784	0.563108
258	0.366689	0.733377	0.633311
259	0.294065	0.588131	0.705935
260	0.431492	0.862984	0.568508
261	0.404746	0.809493	0.595254
262	0.332454	0.664909	0.667546
263	0.376732	0.753464	0.623268
264	0.276523	0.553046	0.723477
265	0.217331	0.434661	0.782669
266	0.136485	0.272969	0.863515
267	0.0724104	0.144821	0.92759

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	76	0.29572	NOK
5% type I error level	92	0.357977	NOK
10% type I error level	96	0.373541	NOK

\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 & 76 & 0.29572 & NOK \tabularnewline
5% type I error level & 92 & 0.357977 & NOK \tabularnewline
10% type I error level & 96 & 0.373541 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270632&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]76[/C][C]0.29572[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]92[/C][C]0.357977[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]96[/C][C]0.373541[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270632&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270632&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	76	0.29572	NOK
5% type I error level	92	0.357977	NOK
10% type I error level	96	0.373541	NOK

Figure 1

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code