FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 12 Dec 2014 10:39:39 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/12/t1418380793ic94b3iyu15e2ac.htm/, Retrieved Thu, 16 May 2024 16:18:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266484, Retrieved Thu, 16 May 2024 16:18:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-12 10:39:39] [a36dddfa959c0d492544a38e0b694048] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
11 8 7 18 12 20 12.9
15 18 18 23 20 25 7.4
19 18 20 23 20 19 12.2
16 12 9 22 14 18 12.8
24 24 19 22 25 24 7.4
15 16 12 19 15 20 6.7
17 19 16 25 20 20 12.6
19 16 17 28 21 24 14.8
19 15 9 16 15 21 13.3
28 28 28 28 28 28 11.1
26 21 20 21 11 10 8.2
15 18 16 22 22 22 11.4
26 22 22 24 22 19 6.4
16 19 17 24 27 27 10.6
24 22 12 26 24 23 12.0
25 25 18 28 23 24 6.3
22 20 20 24 24 24 11.3
15 16 12 20 21 25 11.9
21 19 16 26 20 24 9.3
22 18 16 21 19 21 9.6
27 26 21 28 25 28 10.0
26 24 15 27 16 28 6.4
26 20 17 23 24 22 13.8
22 19 17 24 21 26 10.8
21 19 17 24 22 26 13.8
22 23 18 22 25 21 11.7
20 18 15 21 23 26 10.9
21 16 20 25 20 23 16.1
20 18 13 20 21 20 13.4
22 21 21 21 22 24 9.9
21 20 12 26 25 25 11.5
8 15 6 23 23 24 8.3
22 19 13 21 19 20 11.7
18 27 6 27 27 23 6.1
20 19 19 27 21 24 9.0
24 7 12 25 19 25 9.7
17 20 14 23 25 23 10.8
20 20 13 25 16 21 10.3
23 19 12 23 24 23 10.4
20 19 17 19 24 21 12.7
22 20 19 22 18 18 9.3
19 18 10 24 28 24 11.8
15 14 10 19 15 18 5.9
20 17 11 21 17 21 11.4
22 17 11 27 18 23 13.0
17 8 10 25 26 25 10.8
14 9 7 25 18 22 12.3
24 22 22 23 22 22 11.3
17 20 12 17 19 23 11.8
23 20 18 28 17 24 7.9
25 22 20 25 26 25 12.7
16 22 9 20 21 22 12.3
18 22 16 25 26 24 11.6
20 16 14 21 21 21 6.7
18 14 11 24 12 24 10.9
23 24 20 28 20 25 12.1
24 21 17 20 20 23 13.3
23 20 14 19 24 27 10.1
13 20 8 24 24 27 5.7
20 18 16 21 22 23 14.3
20 14 11 24 21 18 8.0
19 19 10 23 20 20 13.3
22 24 15 18 23 23 9.3
22 19 15 27 19 24 12.5
15 16 10 25 24 26 7.6
17 16 10 20 21 20 15.9
19 16 18 21 16 23 9.2
20 14 10 23 17 22 9.1
22 22 22 27 23 23 11.1
21 21 16 24 20 17 13.0
21 15 10 27 19 20 14.5
16 14 7 24 18 22 12.2
20 15 16 23 18 18 12.3
21 14 16 24 21 19 11.4
20 20 16 21 20 19 8.8
23 21 22 23 17 16 14.6
15 17 13 22 20 24 7.3
18 14 5 27 25 26 12.6
22 19 18 24 15 14 NA
16 16 10 25 17 25 13.0
17 13 8 19 17 23 12.6
24 26 16 24 24 18 13.2
13 13 8 25 21 22 9.9
19 18 16 23 22 26 7.7
20 15 14 23 18 25 10.5
22 18 15 25 22 26 13.4
19 21 9 26 20 26 10.9
21 17 21 26 21 24 4.3
15 18 7 16 21 22 10.3
21 20 17 23 20 21 11.8
24 18 18 26 18 22 11.2
22 25 16 25 25 28 11.4
20 20 16 23 23 22 8.6
21 19 14 26 21 26 13.2
19 18 15 22 20 20 12.6
14 12 8 20 21 24 5.6
25 22 22 27 20 21 9.9
11 16 5 20 22 23 8.8
17 18 13 22 15 23 7.7
22 23 22 24 24 23 9.0
20 20 18 21 22 22 7.3
22 20 15 24 21 23 11.4
15 16 11 26 17 21 13.6
23 22 19 24 23 27 7.9
20 19 19 24 22 23 10.7
22 23 21 27 23 26 10.3
16 6 4 25 16 27 8.3
25 19 17 27 18 27 9.6
18 24 10 19 25 23 14.2
19 19 13 22 18 23 8.5
25 15 15 22 14 23 13.5
21 18 11 25 20 28 4.9
22 18 20 23 19 24 6.4
21 22 13 24 18 20 9.6
22 23 18 24 22 23 11.6
23 18 20 23 21 22 11.1
20 17 15 22 14 15 4.35
6 6 4 24 5 27 12.7
15 22 9 19 25 23 18.1
18 20 18 25 21 23 17.85
24 16 12 26 11 20 16.6
22 16 17 18 20 18 12.6
21 17 12 24 9 22 17.1
23 20 16 28 15 20 19.1
20 23 17 23 23 21 16.1
20 18 14 19 21 25 13.35
18 13 13 19 9 19 18.4
25 22 20 27 24 25 14.7
16 20 16 24 16 24 10.6
20 20 15 26 20 22 12.6
14 13 10 21 15 28 16.2
22 16 16 25 18 22 13.6
26 25 21 28 22 21 18.9
20 16 15 19 21 23 14.1
17 15 16 20 21 19 14.5
22 19 19 26 21 21 16.15
22 19 9 27 20 25 14.75
20 24 19 23 24 23 14.8
17 9 7 18 15 28 12.45
22 22 23 23 24 14 12.65
17 15 14 21 18 23 17.35
22 22 10 23 24 24 8.6
21 22 16 22 24 25 18.4
25 24 12 21 15 15 16.1
11 12 10 14 19 23 11.6
19 21 7 24 20 26 17.75
24 25 20 26 26 21 15.25
17 26 9 24 26 26 17.65
22 19 14 26 18 15 15.6
22 21 12 22 23 23 16.35
17 14 10 20 13 15 17.65
26 28 19 20 16 16 13.6
19 16 16 20 19 20 11.7
20 21 11 18 22 20 14.35
19 16 15 18 21 20 14.75
21 16 14 25 11 21 18.25
24 25 11 28 23 28 9.9
21 21 14 23 18 19 16
19 22 15 20 19 21 18.25
13 9 7 22 15 22 16.85
24 20 22 27 8 27 14.6
28 19 19 24 15 20 13.85
27 24 22 23 21 17 18.95
22 22 11 20 25 26 15.6
23 22 19 22 14 21 14.85
19 12 9 21 21 24 11.75
18 17 11 24 18 21 18.45
23 18 17 26 18 25 15.9
21 10 12 24 12 22 17.1
22 22 17 18 24 17 16.1
17 24 10 17 17 14 19.9
15 18 17 23 20 23 10.95
21 18 13 21 24 28 18.45
20 23 11 21 22 24 15.1
26 21 19 24 15 22 15
19 21 21 22 22 24 11.35
28 28 24 24 26 25 15.95
21 17 13 24 17 21 18.1
19 21 16 24 23 22 14.6
22 21 13 23 19 16 15.4
21 20 15 21 21 18 15.4
20 18 15 24 23 27 17.6
19 17 11 19 19 17 13.35
11 7 7 19 18 25 19.1
17 17 13 23 16 24 15.35
19 14 13 25 23 21 7.6
20 18 12 24 13 21 13.4
17 14 8 21 18 19 13.9
21 23 7 18 23 27 19.1
21 20 17 23 21 28 15.25
12 14 9 20 23 19 12.9
23 17 18 23 16 23 16.1
22 21 17 23 17 25 17.35
22 23 17 23 20 26 13.15
21 24 18 23 18 25 12.15
20 21 12 27 20 25 12.6
18 14 14 19 19 24 10.35
21 24 22 25 26 24 15.4
24 16 19 25 9 24 9.6
22 21 21 21 23 22 18.2
20 8 10 25 9 21 13.6
17 17 16 17 13 17 14.85
19 18 11 22 27 23 14.75
16 17 15 23 22 17 14.1
19 16 12 27 12 25 14.9
23 22 21 27 18 19 16.25
8 17 22 5 6 8 19.25
22 21 20 19 17 14 13.6
23 20 15 24 22 22 13.6
15 20 9 23 22 25 15.65
17 19 15 28 23 28 12.75
21 8 14 25 19 25 14.6
25 19 11 27 20 24 9.85
18 11 9 16 17 15 12.65
23 15 18 23 18 25 11.9
20 13 12 25 24 24 19.2
21 18 11 26 20 28 16.6
21 19 14 24 18 24 11.2
24 23 10 23 23 25 15.25
22 20 18 24 27 23 11.9
22 22 11 27 25 26 13.2
23 19 14 25 24 26 16.35
17 16 16 19 12 22 12.4
15 11 11 19 16 25 15.85
24 11 8 14 16 20 14.35
22 21 16 24 24 22 18.15
19 14 13 20 23 26 11.15
18 21 12 21 24 20 15.65
21 20 17 28 24 26 17.75
20 21 23 26 26 26 7.65
19 20 14 19 19 21 12.35
19 19 10 23 28 21 15.6
16 19 16 23 23 24 19.3
18 18 11 21 21 21 15.2
23 20 16 26 19 18 17.1
22 21 19 25 23 23 15.6
23 22 17 25 23 26 18.4
20 19 12 24 20 23 19.05
24 23 17 23 18 25 18.55
25 16 11 22 20 20 19.1
25 23 19 27 28 25 13.1
20 18 12 26 21 26 12.85
23 23 8 23 25 19 9.5
21 20 17 22 18 21 4.5
23 20 13 26 24 23 11.85
23 23 17 22 28 24 13.6
11 13 7 17 9 6 11.7
21 21 23 25 22 22 12.4
27 26 18 22 26 21 13.35
19 18 13 28 28 28 11.4
21 19 17 22 18 24 14.9
16 18 13 21 23 14 19.9
22 19 13 21 22 17 17.75
21 18 8 24 15 20 11.2
22 19 16 26 24 28 14.6
16 13 14 26 12 19 17.6
18 10 13 24 12 24 14.05
23 21 19 27 20 21 16.1
24 24 15 22 25 21 13.35
20 21 15 23 24 26 11.85
20 23 8 22 23 24 11.95
18 18 14 23 18 26 14.75
4 11 7 15 20 25 15.15
14 16 11 20 22 23 13.2
22 20 17 22 20 24 16.85
17 20 19 25 25 24 7.85
23 26 17 27 28 26 7.7
20 21 12 24 25 23 12.6
18 12 12 21 14 20 7.85
19 15 18 17 16 16 10.95
20 18 16 26 24 24 12.35
15 14 15 20 13 20 9.95
24 18 20 22 19 23 14.9
21 16 16 24 18 23 16.65
19 19 12 23 16 18 13.4
19 7 10 22 8 21 13.95
27 21 28 28 27 25 15.7
23 24 19 21 23 23 16.85
23 21 18 24 20 26 10.95
20 20 19 28 20 26 15.35
17 22 8 25 26 24 12.2
21 17 17 24 23 23 15.1
23 19 16 24 24 21 17.75
22 20 18 21 21 23 15.2
16 16 12 20 15 20 14.6
20 20 17 26 22 23 16.65
16 16 13 16 25 24 8.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266484&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266484&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266484&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 15.6527 + 0.100827AMS.I1[t] + 0.0555911AMS.I2[t] -0.0606925AMS.I3[t] -0.0742813AMS.E1[t] -0.0635414AMS.E2[t] -0.0849801AMS.E3[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  15.6527 +  0.100827AMS.I1[t] +  0.0555911AMS.I2[t] -0.0606925AMS.I3[t] -0.0742813AMS.E1[t] -0.0635414AMS.E2[t] -0.0849801AMS.E3[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266484&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  15.6527 +  0.100827AMS.I1[t] +  0.0555911AMS.I2[t] -0.0606925AMS.I3[t] -0.0742813AMS.E1[t] -0.0635414AMS.E2[t] -0.0849801AMS.E3[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266484&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266484&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 15.6527 + 0.100827AMS.I1[t] + 0.0555911AMS.I2[t] -0.0606925AMS.I3[t] -0.0742813AMS.E1[t] -0.0635414AMS.E2[t] -0.0849801AMS.E3[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.65271.826538.577.20032e-163.60016e-16
AMS.I10.1008270.07645771.3190.1883420.0941708
AMS.I20.05559110.06993990.79480.4273820.213691
AMS.I3-0.06069250.0585604-1.0360.300910.150455
AMS.E1-0.07428130.0789683-0.94060.3476990.17385
AMS.E2-0.06354140.0587161-1.0820.2801070.140053
AMS.E3-0.08498010.0694174-1.2240.2219130.110956

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 15.6527 & 1.82653 & 8.57 & 7.20032e-16 & 3.60016e-16 \tabularnewline
AMS.I1 & 0.100827 & 0.0764577 & 1.319 & 0.188342 & 0.0941708 \tabularnewline
AMS.I2 & 0.0555911 & 0.0699399 & 0.7948 & 0.427382 & 0.213691 \tabularnewline
AMS.I3 & -0.0606925 & 0.0585604 & -1.036 & 0.30091 & 0.150455 \tabularnewline
AMS.E1 & -0.0742813 & 0.0789683 & -0.9406 & 0.347699 & 0.17385 \tabularnewline
AMS.E2 & -0.0635414 & 0.0587161 & -1.082 & 0.280107 & 0.140053 \tabularnewline
AMS.E3 & -0.0849801 & 0.0694174 & -1.224 & 0.221913 & 0.110956 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266484&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]15.6527[/C][C]1.82653[/C][C]8.57[/C][C]7.20032e-16[/C][C]3.60016e-16[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.100827[/C][C]0.0764577[/C][C]1.319[/C][C]0.188342[/C][C]0.0941708[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.0555911[/C][C]0.0699399[/C][C]0.7948[/C][C]0.427382[/C][C]0.213691[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0606925[/C][C]0.0585604[/C][C]-1.036[/C][C]0.30091[/C][C]0.150455[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0742813[/C][C]0.0789683[/C][C]-0.9406[/C][C]0.347699[/C][C]0.17385[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0635414[/C][C]0.0587161[/C][C]-1.082[/C][C]0.280107[/C][C]0.140053[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0849801[/C][C]0.0694174[/C][C]-1.224[/C][C]0.221913[/C][C]0.110956[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266484&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266484&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.65271.826538.577.20032e-163.60016e-16
AMS.I10.1008270.07645771.3190.1883420.0941708
AMS.I20.05559110.06993990.79480.4273820.213691
AMS.I3-0.06069250.0585604-1.0360.300910.150455
AMS.E1-0.07428130.0789683-0.94060.3476990.17385
AMS.E2-0.06354140.0587161-1.0820.2801070.140053
AMS.E3-0.08498010.0694174-1.2240.2219130.110956






Multiple Linear Regression - Regression Statistics
Multiple R0.175824
R-squared0.0309141
Adjusted R-squared0.0100735
F-TEST (value)1.48336
F-TEST (DF numerator)6
F-TEST (DF denominator)279
p-value0.183741
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.40399
Sum Squared Residuals3232.81

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.175824 \tabularnewline
R-squared & 0.0309141 \tabularnewline
Adjusted R-squared & 0.0100735 \tabularnewline
F-TEST (value) & 1.48336 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 279 \tabularnewline
p-value & 0.183741 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.40399 \tabularnewline
Sum Squared Residuals & 3232.81 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266484&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.175824[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0309141[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0100735[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]1.48336[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]279[/C][/ROW]
[ROW][C]p-value[/C][C]0.183741[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.40399[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3232.81[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266484&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266484&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.175824
R-squared0.0309141
Adjusted R-squared0.0100735
F-TEST (value)1.48336
F-TEST (DF numerator)6
F-TEST (DF denominator)279
p-value0.183741
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.40399
Sum Squared Residuals3232.81






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.9825-0.082498
27.411.9695-4.56946
312.212.7613-0.561264
412.813.3334-0.533364
57.412.9913-5.59131
66.713.2622-6.56217
712.612.6244-0.0244287
814.811.97232.82769
913.313.9298-0.629824
1011.112.0945-0.994518
118.215.1191-6.91908
1211.412.293-0.892985
136.413.3667-6.96667
1410.611.4975-0.89754
151213.1564-1.15637
166.312.8898-6.58982
1711.312.4216-1.12158
1811.912.3817-0.481736
199.312.6135-3.31353
209.613.3487-3.74866
211012.498-2.49798
226.413.2963-6.89628
2313.813.25120.548794
2410.812.5687-1.76873
2513.812.40441.39564
2611.713.0497-1.3497
2710.912.5286-1.62863
2816.112.36333.73675
2913.413.36130.0387395
309.912.7664-2.8664
3111.512.5092-1.00921
328.311.7196-3.41957
3311.713.6713-1.97131
346.112.9286-6.82862
35912.1928-3.19281
369.712.5445-2.84453
3710.812.3773-1.57732
3810.313.3338-3.03376
3910.413.1116-2.71162
4012.712.9728-0.272759
419.313.522-4.22196
4211.812.3607-0.560676
435.913.4423-7.54233
4411.413.522-2.12196
451313.0444-0.044423
4610.811.5709-0.770933
4712.312.26940.0306078
4811.312.9844-1.68435
4911.813.3256-1.52564
507.912.7915-4.89146
5112.712.54890.151102
5212.313.2531-0.953127
5311.612.1709-0.57086
546.713.0301-6.33012
5510.912.9935-2.09345
5612.112.6168-0.516831
5713.313.4972-0.197172
5810.113.003-2.90303
595.711.9875-6.28751
6014.312.78641.51358
61813.1331-5.13312
6213.313.3388-0.0387997
639.313.5416-4.24162
6412.512.7643-0.264314
657.611.8561-4.25611
6615.913.12972.77032
679.212.8343-3.63427
689.113.1823-4.08234
6911.112.3371-1.23705
701313.4681-0.46814
7114.513.08451.41549
7212.212.8233-0.623282
7312.313.1502-0.85015
7411.412.8455-1.4455
758.813.3646-4.56461
7614.613.65550.944476
777.312.3766-5.07659
7812.612.13880.461233
79NANA0.513293
801313.5578-0.557793
8112.613.1094-0.50943
8213.215.4396-2.23961
839.914.4821-4.58209
847.79.87667-2.17667
8510.59.59670.903299
8613.415.2779-1.87795
8710.918.7353-7.83535
884.37.34845-3.04845
8910.311.5862-1.28622
9011.813.6361-1.83608
9111.212.2646-1.06456
9211.415.5705-4.17048
938.67.901420.698582
9413.213.654-0.454028
9512.619.3863-6.78629
965.68.70012-3.10012
979.913.6097-3.70969
988.814.1365-5.33653
997.711.2519-3.55195
100914.5612-5.5612
1017.38.90065-1.60065
10211.410.39081.00917
10313.618.2029-4.60288
1047.99.63709-1.73709
10510.712.5984-1.8984
10610.314.1885-3.88853
1078.311.454-3.15401
1089.68.640410.959594
10914.218.8031-4.60315
1108.58.61852-0.118523
11113.521.1958-7.69577
1124.911.2024-6.30239
1136.410.378-3.97795
1149.610.9218-1.3218
11511.613.3461-1.74609
11611.120.6554-9.55541
1174.353.60350.7465
11812.77.487445.21256
11918.112.5915.50902
12017.8515.15382.6962
12116.617.591-0.991026
12212.69.26263.3374
12317.111.37985.72016
12419.115.96153.13846
12516.115.69990.400051
12613.358.753414.59659
12718.416.22742.17258
12814.716.6677-1.96772
12910.610.799-0.198951
13012.68.687553.91245
13116.215.51890.681088
13213.67.827055.77295
13318.917.7481.15197
13414.112.39491.70509
13514.511.07373.42632
13616.1514.37991.77005
13714.7512.61222.13776
13814.815.1226-0.322585
13912.4513.0748-0.624767
14012.657.992724.65728
14117.3521.964-4.61397
1428.62.938295.66171
14318.417.29151.1085
14416.117.1202-1.02018
14511.66.89794.7021
14617.7515.38052.36952
14715.2510.22165.02843
14817.6515.77761.87235
14915.612.50983.09021
15016.3512.65173.69828
15117.6518.8656-1.2156
15213.614.9943-1.39426
15311.711.08440.61556
15414.3512.77641.57357
15514.759.969244.78076
15618.2521.2239-2.97392
1579.97.520932.37907
1581611.15354.84648
15918.2513.9824.26797
16016.8515.29071.55927
16114.614.6934-0.0934347
16213.858.786465.06354
16318.9516.49262.45738
16415.614.48321.1168
16514.8515.8555-1.00546
16611.756.333925.41608
16718.4515.2913.15899
16815.911.98283.91716
16917.114.75542.34461
17016.110.76135.33871
17119.921.1501-1.25011
17210.955.017345.93266
17318.4516.63291.81714
17415.113.7831.317
1751516.0396-1.03964
17611.358.416442.93356
17715.9511.12864.82144
17818.116.1511.94904
17914.613.17381.42615
18015.413.54761.85244
18115.410.02085.37919
18217.618.0325-0.432532
18313.356.296487.05352
18419.116.50812.59187
18515.3520.2046-4.8546
1867.67.74818-0.148179
18713.412.84120.558799
18813.98.330825.56918
18919.116.27782.82219
19015.2514.88290.367051
19112.99.944612.95539
19216.111.84334.25666
19317.3517.12890.221083
19413.1514.0351-0.885051
19512.1512.2574-0.107398
19612.614.988-2.38799
19710.357.170373.17963
19815.419.1404-3.7404
1999.64.272825.32718
20018.217.89350.306463
20113.612.55721.04277
20214.8512.69712.15293
20314.7513.39951.35047
20414.112.03692.06305
20514.911.80623.0938
20616.2511.63664.61338
20719.2519.7932-0.543168
20813.613.12290.477088
20913.610.44983.15021
21015.6514.49181.15819
21112.7510.32632.42374
21214.617.996-3.39602
2139.8511.1894-1.33943
21412.6513.4864-0.836385
21511.94.942056.95795
21619.215.12154.07851
21716.618.4106-1.81056
21811.29.399771.80023
21915.2515.7873-0.53732
22011.911.32260.577352
22113.29.436733.76327
22216.3517.1917-0.841714
22312.49.106463.29354
22415.8515.9423-0.0922871
22514.359.08995.2601
22618.1519.4011-1.25111
22711.158.622172.52783
22815.659.935745.71426
22917.7521.7478-3.99783
2307.658.72731-1.07731
23112.359.495492.85451
23215.68.441627.15838
23319.317.22172.07827
23415.211.54423.6558
23517.114.11212.9879
23615.69.834975.76503
23718.412.3396.06098
23819.0513.84265.20737
23918.5513.24065.30942
24019.118.38950.710464
24113.112.71640.383615
24212.8517.2031-4.35313
2439.518.2876-8.78758
2444.55.53367-1.03367
24511.8511.01570.834346
24613.616.6151-3.01508
24711.711.717-0.0170279
24812.412.7071-0.307065
24913.3513.4916-0.141553
25011.49.477051.92295
25114.98.266476.63353
25219.915.88564.01438
25317.7520.3997-2.64967
25411.28.720282.47972
25514.69.830474.76953
25617.616.19971.40029
25714.0510.8753.17505
25816.116.239-0.139021
25913.3513.9833-0.6333
26011.8513.2271-1.37711
26111.959.756812.19319
26214.7511.33313.4169
26315.1514.3980.75198
26413.29.356383.84362
26516.8520.8403-3.99031
2667.8512.5411-4.69106
2677.77.8825-0.182495
26812.618.0073-5.40726
2697.8510.5707-2.72067
27010.9510.8030.147049
27112.3515.4217-3.07171
2729.958.11331.8367
27314.911.05743.84261
27416.6516.8915-0.241541
27513.412.87350.526495
27613.9510.1733.77696
27715.712.02683.67317
27816.8518.6836-1.83359
27910.957.66773.2823
28015.3515.7056-0.355573
28112.29.584582.61542
28215.110.31454.78547
28317.7515.59142.15859
28415.213.88871.31129
28514.610.41554.1845
28616.6521.0998-4.44981
2878.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.9825 & -0.082498 \tabularnewline
2 & 7.4 & 11.9695 & -4.56946 \tabularnewline
3 & 12.2 & 12.7613 & -0.561264 \tabularnewline
4 & 12.8 & 13.3334 & -0.533364 \tabularnewline
5 & 7.4 & 12.9913 & -5.59131 \tabularnewline
6 & 6.7 & 13.2622 & -6.56217 \tabularnewline
7 & 12.6 & 12.6244 & -0.0244287 \tabularnewline
8 & 14.8 & 11.9723 & 2.82769 \tabularnewline
9 & 13.3 & 13.9298 & -0.629824 \tabularnewline
10 & 11.1 & 12.0945 & -0.994518 \tabularnewline
11 & 8.2 & 15.1191 & -6.91908 \tabularnewline
12 & 11.4 & 12.293 & -0.892985 \tabularnewline
13 & 6.4 & 13.3667 & -6.96667 \tabularnewline
14 & 10.6 & 11.4975 & -0.89754 \tabularnewline
15 & 12 & 13.1564 & -1.15637 \tabularnewline
16 & 6.3 & 12.8898 & -6.58982 \tabularnewline
17 & 11.3 & 12.4216 & -1.12158 \tabularnewline
18 & 11.9 & 12.3817 & -0.481736 \tabularnewline
19 & 9.3 & 12.6135 & -3.31353 \tabularnewline
20 & 9.6 & 13.3487 & -3.74866 \tabularnewline
21 & 10 & 12.498 & -2.49798 \tabularnewline
22 & 6.4 & 13.2963 & -6.89628 \tabularnewline
23 & 13.8 & 13.2512 & 0.548794 \tabularnewline
24 & 10.8 & 12.5687 & -1.76873 \tabularnewline
25 & 13.8 & 12.4044 & 1.39564 \tabularnewline
26 & 11.7 & 13.0497 & -1.3497 \tabularnewline
27 & 10.9 & 12.5286 & -1.62863 \tabularnewline
28 & 16.1 & 12.3633 & 3.73675 \tabularnewline
29 & 13.4 & 13.3613 & 0.0387395 \tabularnewline
30 & 9.9 & 12.7664 & -2.8664 \tabularnewline
31 & 11.5 & 12.5092 & -1.00921 \tabularnewline
32 & 8.3 & 11.7196 & -3.41957 \tabularnewline
33 & 11.7 & 13.6713 & -1.97131 \tabularnewline
34 & 6.1 & 12.9286 & -6.82862 \tabularnewline
35 & 9 & 12.1928 & -3.19281 \tabularnewline
36 & 9.7 & 12.5445 & -2.84453 \tabularnewline
37 & 10.8 & 12.3773 & -1.57732 \tabularnewline
38 & 10.3 & 13.3338 & -3.03376 \tabularnewline
39 & 10.4 & 13.1116 & -2.71162 \tabularnewline
40 & 12.7 & 12.9728 & -0.272759 \tabularnewline
41 & 9.3 & 13.522 & -4.22196 \tabularnewline
42 & 11.8 & 12.3607 & -0.560676 \tabularnewline
43 & 5.9 & 13.4423 & -7.54233 \tabularnewline
44 & 11.4 & 13.522 & -2.12196 \tabularnewline
45 & 13 & 13.0444 & -0.044423 \tabularnewline
46 & 10.8 & 11.5709 & -0.770933 \tabularnewline
47 & 12.3 & 12.2694 & 0.0306078 \tabularnewline
48 & 11.3 & 12.9844 & -1.68435 \tabularnewline
49 & 11.8 & 13.3256 & -1.52564 \tabularnewline
50 & 7.9 & 12.7915 & -4.89146 \tabularnewline
51 & 12.7 & 12.5489 & 0.151102 \tabularnewline
52 & 12.3 & 13.2531 & -0.953127 \tabularnewline
53 & 11.6 & 12.1709 & -0.57086 \tabularnewline
54 & 6.7 & 13.0301 & -6.33012 \tabularnewline
55 & 10.9 & 12.9935 & -2.09345 \tabularnewline
56 & 12.1 & 12.6168 & -0.516831 \tabularnewline
57 & 13.3 & 13.4972 & -0.197172 \tabularnewline
58 & 10.1 & 13.003 & -2.90303 \tabularnewline
59 & 5.7 & 11.9875 & -6.28751 \tabularnewline
60 & 14.3 & 12.7864 & 1.51358 \tabularnewline
61 & 8 & 13.1331 & -5.13312 \tabularnewline
62 & 13.3 & 13.3388 & -0.0387997 \tabularnewline
63 & 9.3 & 13.5416 & -4.24162 \tabularnewline
64 & 12.5 & 12.7643 & -0.264314 \tabularnewline
65 & 7.6 & 11.8561 & -4.25611 \tabularnewline
66 & 15.9 & 13.1297 & 2.77032 \tabularnewline
67 & 9.2 & 12.8343 & -3.63427 \tabularnewline
68 & 9.1 & 13.1823 & -4.08234 \tabularnewline
69 & 11.1 & 12.3371 & -1.23705 \tabularnewline
70 & 13 & 13.4681 & -0.46814 \tabularnewline
71 & 14.5 & 13.0845 & 1.41549 \tabularnewline
72 & 12.2 & 12.8233 & -0.623282 \tabularnewline
73 & 12.3 & 13.1502 & -0.85015 \tabularnewline
74 & 11.4 & 12.8455 & -1.4455 \tabularnewline
75 & 8.8 & 13.3646 & -4.56461 \tabularnewline
76 & 14.6 & 13.6555 & 0.944476 \tabularnewline
77 & 7.3 & 12.3766 & -5.07659 \tabularnewline
78 & 12.6 & 12.1388 & 0.461233 \tabularnewline
79 & NA & NA & 0.513293 \tabularnewline
80 & 13 & 13.5578 & -0.557793 \tabularnewline
81 & 12.6 & 13.1094 & -0.50943 \tabularnewline
82 & 13.2 & 15.4396 & -2.23961 \tabularnewline
83 & 9.9 & 14.4821 & -4.58209 \tabularnewline
84 & 7.7 & 9.87667 & -2.17667 \tabularnewline
85 & 10.5 & 9.5967 & 0.903299 \tabularnewline
86 & 13.4 & 15.2779 & -1.87795 \tabularnewline
87 & 10.9 & 18.7353 & -7.83535 \tabularnewline
88 & 4.3 & 7.34845 & -3.04845 \tabularnewline
89 & 10.3 & 11.5862 & -1.28622 \tabularnewline
90 & 11.8 & 13.6361 & -1.83608 \tabularnewline
91 & 11.2 & 12.2646 & -1.06456 \tabularnewline
92 & 11.4 & 15.5705 & -4.17048 \tabularnewline
93 & 8.6 & 7.90142 & 0.698582 \tabularnewline
94 & 13.2 & 13.654 & -0.454028 \tabularnewline
95 & 12.6 & 19.3863 & -6.78629 \tabularnewline
96 & 5.6 & 8.70012 & -3.10012 \tabularnewline
97 & 9.9 & 13.6097 & -3.70969 \tabularnewline
98 & 8.8 & 14.1365 & -5.33653 \tabularnewline
99 & 7.7 & 11.2519 & -3.55195 \tabularnewline
100 & 9 & 14.5612 & -5.5612 \tabularnewline
101 & 7.3 & 8.90065 & -1.60065 \tabularnewline
102 & 11.4 & 10.3908 & 1.00917 \tabularnewline
103 & 13.6 & 18.2029 & -4.60288 \tabularnewline
104 & 7.9 & 9.63709 & -1.73709 \tabularnewline
105 & 10.7 & 12.5984 & -1.8984 \tabularnewline
106 & 10.3 & 14.1885 & -3.88853 \tabularnewline
107 & 8.3 & 11.454 & -3.15401 \tabularnewline
108 & 9.6 & 8.64041 & 0.959594 \tabularnewline
109 & 14.2 & 18.8031 & -4.60315 \tabularnewline
110 & 8.5 & 8.61852 & -0.118523 \tabularnewline
111 & 13.5 & 21.1958 & -7.69577 \tabularnewline
112 & 4.9 & 11.2024 & -6.30239 \tabularnewline
113 & 6.4 & 10.378 & -3.97795 \tabularnewline
114 & 9.6 & 10.9218 & -1.3218 \tabularnewline
115 & 11.6 & 13.3461 & -1.74609 \tabularnewline
116 & 11.1 & 20.6554 & -9.55541 \tabularnewline
117 & 4.35 & 3.6035 & 0.7465 \tabularnewline
118 & 12.7 & 7.48744 & 5.21256 \tabularnewline
119 & 18.1 & 12.591 & 5.50902 \tabularnewline
120 & 17.85 & 15.1538 & 2.6962 \tabularnewline
121 & 16.6 & 17.591 & -0.991026 \tabularnewline
122 & 12.6 & 9.2626 & 3.3374 \tabularnewline
123 & 17.1 & 11.3798 & 5.72016 \tabularnewline
124 & 19.1 & 15.9615 & 3.13846 \tabularnewline
125 & 16.1 & 15.6999 & 0.400051 \tabularnewline
126 & 13.35 & 8.75341 & 4.59659 \tabularnewline
127 & 18.4 & 16.2274 & 2.17258 \tabularnewline
128 & 14.7 & 16.6677 & -1.96772 \tabularnewline
129 & 10.6 & 10.799 & -0.198951 \tabularnewline
130 & 12.6 & 8.68755 & 3.91245 \tabularnewline
131 & 16.2 & 15.5189 & 0.681088 \tabularnewline
132 & 13.6 & 7.82705 & 5.77295 \tabularnewline
133 & 18.9 & 17.748 & 1.15197 \tabularnewline
134 & 14.1 & 12.3949 & 1.70509 \tabularnewline
135 & 14.5 & 11.0737 & 3.42632 \tabularnewline
136 & 16.15 & 14.3799 & 1.77005 \tabularnewline
137 & 14.75 & 12.6122 & 2.13776 \tabularnewline
138 & 14.8 & 15.1226 & -0.322585 \tabularnewline
139 & 12.45 & 13.0748 & -0.624767 \tabularnewline
140 & 12.65 & 7.99272 & 4.65728 \tabularnewline
141 & 17.35 & 21.964 & -4.61397 \tabularnewline
142 & 8.6 & 2.93829 & 5.66171 \tabularnewline
143 & 18.4 & 17.2915 & 1.1085 \tabularnewline
144 & 16.1 & 17.1202 & -1.02018 \tabularnewline
145 & 11.6 & 6.8979 & 4.7021 \tabularnewline
146 & 17.75 & 15.3805 & 2.36952 \tabularnewline
147 & 15.25 & 10.2216 & 5.02843 \tabularnewline
148 & 17.65 & 15.7776 & 1.87235 \tabularnewline
149 & 15.6 & 12.5098 & 3.09021 \tabularnewline
150 & 16.35 & 12.6517 & 3.69828 \tabularnewline
151 & 17.65 & 18.8656 & -1.2156 \tabularnewline
152 & 13.6 & 14.9943 & -1.39426 \tabularnewline
153 & 11.7 & 11.0844 & 0.61556 \tabularnewline
154 & 14.35 & 12.7764 & 1.57357 \tabularnewline
155 & 14.75 & 9.96924 & 4.78076 \tabularnewline
156 & 18.25 & 21.2239 & -2.97392 \tabularnewline
157 & 9.9 & 7.52093 & 2.37907 \tabularnewline
158 & 16 & 11.1535 & 4.84648 \tabularnewline
159 & 18.25 & 13.982 & 4.26797 \tabularnewline
160 & 16.85 & 15.2907 & 1.55927 \tabularnewline
161 & 14.6 & 14.6934 & -0.0934347 \tabularnewline
162 & 13.85 & 8.78646 & 5.06354 \tabularnewline
163 & 18.95 & 16.4926 & 2.45738 \tabularnewline
164 & 15.6 & 14.4832 & 1.1168 \tabularnewline
165 & 14.85 & 15.8555 & -1.00546 \tabularnewline
166 & 11.75 & 6.33392 & 5.41608 \tabularnewline
167 & 18.45 & 15.291 & 3.15899 \tabularnewline
168 & 15.9 & 11.9828 & 3.91716 \tabularnewline
169 & 17.1 & 14.7554 & 2.34461 \tabularnewline
170 & 16.1 & 10.7613 & 5.33871 \tabularnewline
171 & 19.9 & 21.1501 & -1.25011 \tabularnewline
172 & 10.95 & 5.01734 & 5.93266 \tabularnewline
173 & 18.45 & 16.6329 & 1.81714 \tabularnewline
174 & 15.1 & 13.783 & 1.317 \tabularnewline
175 & 15 & 16.0396 & -1.03964 \tabularnewline
176 & 11.35 & 8.41644 & 2.93356 \tabularnewline
177 & 15.95 & 11.1286 & 4.82144 \tabularnewline
178 & 18.1 & 16.151 & 1.94904 \tabularnewline
179 & 14.6 & 13.1738 & 1.42615 \tabularnewline
180 & 15.4 & 13.5476 & 1.85244 \tabularnewline
181 & 15.4 & 10.0208 & 5.37919 \tabularnewline
182 & 17.6 & 18.0325 & -0.432532 \tabularnewline
183 & 13.35 & 6.29648 & 7.05352 \tabularnewline
184 & 19.1 & 16.5081 & 2.59187 \tabularnewline
185 & 15.35 & 20.2046 & -4.8546 \tabularnewline
186 & 7.6 & 7.74818 & -0.148179 \tabularnewline
187 & 13.4 & 12.8412 & 0.558799 \tabularnewline
188 & 13.9 & 8.33082 & 5.56918 \tabularnewline
189 & 19.1 & 16.2778 & 2.82219 \tabularnewline
190 & 15.25 & 14.8829 & 0.367051 \tabularnewline
191 & 12.9 & 9.94461 & 2.95539 \tabularnewline
192 & 16.1 & 11.8433 & 4.25666 \tabularnewline
193 & 17.35 & 17.1289 & 0.221083 \tabularnewline
194 & 13.15 & 14.0351 & -0.885051 \tabularnewline
195 & 12.15 & 12.2574 & -0.107398 \tabularnewline
196 & 12.6 & 14.988 & -2.38799 \tabularnewline
197 & 10.35 & 7.17037 & 3.17963 \tabularnewline
198 & 15.4 & 19.1404 & -3.7404 \tabularnewline
199 & 9.6 & 4.27282 & 5.32718 \tabularnewline
200 & 18.2 & 17.8935 & 0.306463 \tabularnewline
201 & 13.6 & 12.5572 & 1.04277 \tabularnewline
202 & 14.85 & 12.6971 & 2.15293 \tabularnewline
203 & 14.75 & 13.3995 & 1.35047 \tabularnewline
204 & 14.1 & 12.0369 & 2.06305 \tabularnewline
205 & 14.9 & 11.8062 & 3.0938 \tabularnewline
206 & 16.25 & 11.6366 & 4.61338 \tabularnewline
207 & 19.25 & 19.7932 & -0.543168 \tabularnewline
208 & 13.6 & 13.1229 & 0.477088 \tabularnewline
209 & 13.6 & 10.4498 & 3.15021 \tabularnewline
210 & 15.65 & 14.4918 & 1.15819 \tabularnewline
211 & 12.75 & 10.3263 & 2.42374 \tabularnewline
212 & 14.6 & 17.996 & -3.39602 \tabularnewline
213 & 9.85 & 11.1894 & -1.33943 \tabularnewline
214 & 12.65 & 13.4864 & -0.836385 \tabularnewline
215 & 11.9 & 4.94205 & 6.95795 \tabularnewline
216 & 19.2 & 15.1215 & 4.07851 \tabularnewline
217 & 16.6 & 18.4106 & -1.81056 \tabularnewline
218 & 11.2 & 9.39977 & 1.80023 \tabularnewline
219 & 15.25 & 15.7873 & -0.53732 \tabularnewline
220 & 11.9 & 11.3226 & 0.577352 \tabularnewline
221 & 13.2 & 9.43673 & 3.76327 \tabularnewline
222 & 16.35 & 17.1917 & -0.841714 \tabularnewline
223 & 12.4 & 9.10646 & 3.29354 \tabularnewline
224 & 15.85 & 15.9423 & -0.0922871 \tabularnewline
225 & 14.35 & 9.0899 & 5.2601 \tabularnewline
226 & 18.15 & 19.4011 & -1.25111 \tabularnewline
227 & 11.15 & 8.62217 & 2.52783 \tabularnewline
228 & 15.65 & 9.93574 & 5.71426 \tabularnewline
229 & 17.75 & 21.7478 & -3.99783 \tabularnewline
230 & 7.65 & 8.72731 & -1.07731 \tabularnewline
231 & 12.35 & 9.49549 & 2.85451 \tabularnewline
232 & 15.6 & 8.44162 & 7.15838 \tabularnewline
233 & 19.3 & 17.2217 & 2.07827 \tabularnewline
234 & 15.2 & 11.5442 & 3.6558 \tabularnewline
235 & 17.1 & 14.1121 & 2.9879 \tabularnewline
236 & 15.6 & 9.83497 & 5.76503 \tabularnewline
237 & 18.4 & 12.339 & 6.06098 \tabularnewline
238 & 19.05 & 13.8426 & 5.20737 \tabularnewline
239 & 18.55 & 13.2406 & 5.30942 \tabularnewline
240 & 19.1 & 18.3895 & 0.710464 \tabularnewline
241 & 13.1 & 12.7164 & 0.383615 \tabularnewline
242 & 12.85 & 17.2031 & -4.35313 \tabularnewline
243 & 9.5 & 18.2876 & -8.78758 \tabularnewline
244 & 4.5 & 5.53367 & -1.03367 \tabularnewline
245 & 11.85 & 11.0157 & 0.834346 \tabularnewline
246 & 13.6 & 16.6151 & -3.01508 \tabularnewline
247 & 11.7 & 11.717 & -0.0170279 \tabularnewline
248 & 12.4 & 12.7071 & -0.307065 \tabularnewline
249 & 13.35 & 13.4916 & -0.141553 \tabularnewline
250 & 11.4 & 9.47705 & 1.92295 \tabularnewline
251 & 14.9 & 8.26647 & 6.63353 \tabularnewline
252 & 19.9 & 15.8856 & 4.01438 \tabularnewline
253 & 17.75 & 20.3997 & -2.64967 \tabularnewline
254 & 11.2 & 8.72028 & 2.47972 \tabularnewline
255 & 14.6 & 9.83047 & 4.76953 \tabularnewline
256 & 17.6 & 16.1997 & 1.40029 \tabularnewline
257 & 14.05 & 10.875 & 3.17505 \tabularnewline
258 & 16.1 & 16.239 & -0.139021 \tabularnewline
259 & 13.35 & 13.9833 & -0.6333 \tabularnewline
260 & 11.85 & 13.2271 & -1.37711 \tabularnewline
261 & 11.95 & 9.75681 & 2.19319 \tabularnewline
262 & 14.75 & 11.3331 & 3.4169 \tabularnewline
263 & 15.15 & 14.398 & 0.75198 \tabularnewline
264 & 13.2 & 9.35638 & 3.84362 \tabularnewline
265 & 16.85 & 20.8403 & -3.99031 \tabularnewline
266 & 7.85 & 12.5411 & -4.69106 \tabularnewline
267 & 7.7 & 7.8825 & -0.182495 \tabularnewline
268 & 12.6 & 18.0073 & -5.40726 \tabularnewline
269 & 7.85 & 10.5707 & -2.72067 \tabularnewline
270 & 10.95 & 10.803 & 0.147049 \tabularnewline
271 & 12.35 & 15.4217 & -3.07171 \tabularnewline
272 & 9.95 & 8.1133 & 1.8367 \tabularnewline
273 & 14.9 & 11.0574 & 3.84261 \tabularnewline
274 & 16.65 & 16.8915 & -0.241541 \tabularnewline
275 & 13.4 & 12.8735 & 0.526495 \tabularnewline
276 & 13.95 & 10.173 & 3.77696 \tabularnewline
277 & 15.7 & 12.0268 & 3.67317 \tabularnewline
278 & 16.85 & 18.6836 & -1.83359 \tabularnewline
279 & 10.95 & 7.6677 & 3.2823 \tabularnewline
280 & 15.35 & 15.7056 & -0.355573 \tabularnewline
281 & 12.2 & 9.58458 & 2.61542 \tabularnewline
282 & 15.1 & 10.3145 & 4.78547 \tabularnewline
283 & 17.75 & 15.5914 & 2.15859 \tabularnewline
284 & 15.2 & 13.8887 & 1.31129 \tabularnewline
285 & 14.6 & 10.4155 & 4.1845 \tabularnewline
286 & 16.65 & 21.0998 & -4.44981 \tabularnewline
287 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266484&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]12.9825[/C][C]-0.082498[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]11.9695[/C][C]-4.56946[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]12.7613[/C][C]-0.561264[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]13.3334[/C][C]-0.533364[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]12.9913[/C][C]-5.59131[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]13.2622[/C][C]-6.56217[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]12.6244[/C][C]-0.0244287[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]11.9723[/C][C]2.82769[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]13.9298[/C][C]-0.629824[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]12.0945[/C][C]-0.994518[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]15.1191[/C][C]-6.91908[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]12.293[/C][C]-0.892985[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]13.3667[/C][C]-6.96667[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]11.4975[/C][C]-0.89754[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]13.1564[/C][C]-1.15637[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]12.8898[/C][C]-6.58982[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]12.4216[/C][C]-1.12158[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]12.3817[/C][C]-0.481736[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]12.6135[/C][C]-3.31353[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]13.3487[/C][C]-3.74866[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]12.498[/C][C]-2.49798[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]13.2963[/C][C]-6.89628[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]13.2512[/C][C]0.548794[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]12.5687[/C][C]-1.76873[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]12.4044[/C][C]1.39564[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]13.0497[/C][C]-1.3497[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]12.5286[/C][C]-1.62863[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]12.3633[/C][C]3.73675[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]13.3613[/C][C]0.0387395[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]12.7664[/C][C]-2.8664[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]12.5092[/C][C]-1.00921[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]11.7196[/C][C]-3.41957[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]13.6713[/C][C]-1.97131[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]12.9286[/C][C]-6.82862[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]12.1928[/C][C]-3.19281[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]12.5445[/C][C]-2.84453[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]12.3773[/C][C]-1.57732[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]13.3338[/C][C]-3.03376[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]13.1116[/C][C]-2.71162[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]12.9728[/C][C]-0.272759[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]13.522[/C][C]-4.22196[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]12.3607[/C][C]-0.560676[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]13.4423[/C][C]-7.54233[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]13.522[/C][C]-2.12196[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]13.0444[/C][C]-0.044423[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]11.5709[/C][C]-0.770933[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]12.2694[/C][C]0.0306078[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]12.9844[/C][C]-1.68435[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]13.3256[/C][C]-1.52564[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]12.7915[/C][C]-4.89146[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]12.5489[/C][C]0.151102[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]13.2531[/C][C]-0.953127[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]12.1709[/C][C]-0.57086[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]13.0301[/C][C]-6.33012[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]12.9935[/C][C]-2.09345[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]12.6168[/C][C]-0.516831[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]13.4972[/C][C]-0.197172[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]13.003[/C][C]-2.90303[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]11.9875[/C][C]-6.28751[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]12.7864[/C][C]1.51358[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]13.1331[/C][C]-5.13312[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]13.3388[/C][C]-0.0387997[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]13.5416[/C][C]-4.24162[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]12.7643[/C][C]-0.264314[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]11.8561[/C][C]-4.25611[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]13.1297[/C][C]2.77032[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]12.8343[/C][C]-3.63427[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]13.1823[/C][C]-4.08234[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]12.3371[/C][C]-1.23705[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]13.4681[/C][C]-0.46814[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]13.0845[/C][C]1.41549[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]12.8233[/C][C]-0.623282[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]13.1502[/C][C]-0.85015[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]12.8455[/C][C]-1.4455[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]13.3646[/C][C]-4.56461[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]13.6555[/C][C]0.944476[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]12.3766[/C][C]-5.07659[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]12.1388[/C][C]0.461233[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]0.513293[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]13.5578[/C][C]-0.557793[/C][/ROW]
[ROW][C]81[/C][C]12.6[/C][C]13.1094[/C][C]-0.50943[/C][/ROW]
[ROW][C]82[/C][C]13.2[/C][C]15.4396[/C][C]-2.23961[/C][/ROW]
[ROW][C]83[/C][C]9.9[/C][C]14.4821[/C][C]-4.58209[/C][/ROW]
[ROW][C]84[/C][C]7.7[/C][C]9.87667[/C][C]-2.17667[/C][/ROW]
[ROW][C]85[/C][C]10.5[/C][C]9.5967[/C][C]0.903299[/C][/ROW]
[ROW][C]86[/C][C]13.4[/C][C]15.2779[/C][C]-1.87795[/C][/ROW]
[ROW][C]87[/C][C]10.9[/C][C]18.7353[/C][C]-7.83535[/C][/ROW]
[ROW][C]88[/C][C]4.3[/C][C]7.34845[/C][C]-3.04845[/C][/ROW]
[ROW][C]89[/C][C]10.3[/C][C]11.5862[/C][C]-1.28622[/C][/ROW]
[ROW][C]90[/C][C]11.8[/C][C]13.6361[/C][C]-1.83608[/C][/ROW]
[ROW][C]91[/C][C]11.2[/C][C]12.2646[/C][C]-1.06456[/C][/ROW]
[ROW][C]92[/C][C]11.4[/C][C]15.5705[/C][C]-4.17048[/C][/ROW]
[ROW][C]93[/C][C]8.6[/C][C]7.90142[/C][C]0.698582[/C][/ROW]
[ROW][C]94[/C][C]13.2[/C][C]13.654[/C][C]-0.454028[/C][/ROW]
[ROW][C]95[/C][C]12.6[/C][C]19.3863[/C][C]-6.78629[/C][/ROW]
[ROW][C]96[/C][C]5.6[/C][C]8.70012[/C][C]-3.10012[/C][/ROW]
[ROW][C]97[/C][C]9.9[/C][C]13.6097[/C][C]-3.70969[/C][/ROW]
[ROW][C]98[/C][C]8.8[/C][C]14.1365[/C][C]-5.33653[/C][/ROW]
[ROW][C]99[/C][C]7.7[/C][C]11.2519[/C][C]-3.55195[/C][/ROW]
[ROW][C]100[/C][C]9[/C][C]14.5612[/C][C]-5.5612[/C][/ROW]
[ROW][C]101[/C][C]7.3[/C][C]8.90065[/C][C]-1.60065[/C][/ROW]
[ROW][C]102[/C][C]11.4[/C][C]10.3908[/C][C]1.00917[/C][/ROW]
[ROW][C]103[/C][C]13.6[/C][C]18.2029[/C][C]-4.60288[/C][/ROW]
[ROW][C]104[/C][C]7.9[/C][C]9.63709[/C][C]-1.73709[/C][/ROW]
[ROW][C]105[/C][C]10.7[/C][C]12.5984[/C][C]-1.8984[/C][/ROW]
[ROW][C]106[/C][C]10.3[/C][C]14.1885[/C][C]-3.88853[/C][/ROW]
[ROW][C]107[/C][C]8.3[/C][C]11.454[/C][C]-3.15401[/C][/ROW]
[ROW][C]108[/C][C]9.6[/C][C]8.64041[/C][C]0.959594[/C][/ROW]
[ROW][C]109[/C][C]14.2[/C][C]18.8031[/C][C]-4.60315[/C][/ROW]
[ROW][C]110[/C][C]8.5[/C][C]8.61852[/C][C]-0.118523[/C][/ROW]
[ROW][C]111[/C][C]13.5[/C][C]21.1958[/C][C]-7.69577[/C][/ROW]
[ROW][C]112[/C][C]4.9[/C][C]11.2024[/C][C]-6.30239[/C][/ROW]
[ROW][C]113[/C][C]6.4[/C][C]10.378[/C][C]-3.97795[/C][/ROW]
[ROW][C]114[/C][C]9.6[/C][C]10.9218[/C][C]-1.3218[/C][/ROW]
[ROW][C]115[/C][C]11.6[/C][C]13.3461[/C][C]-1.74609[/C][/ROW]
[ROW][C]116[/C][C]11.1[/C][C]20.6554[/C][C]-9.55541[/C][/ROW]
[ROW][C]117[/C][C]4.35[/C][C]3.6035[/C][C]0.7465[/C][/ROW]
[ROW][C]118[/C][C]12.7[/C][C]7.48744[/C][C]5.21256[/C][/ROW]
[ROW][C]119[/C][C]18.1[/C][C]12.591[/C][C]5.50902[/C][/ROW]
[ROW][C]120[/C][C]17.85[/C][C]15.1538[/C][C]2.6962[/C][/ROW]
[ROW][C]121[/C][C]16.6[/C][C]17.591[/C][C]-0.991026[/C][/ROW]
[ROW][C]122[/C][C]12.6[/C][C]9.2626[/C][C]3.3374[/C][/ROW]
[ROW][C]123[/C][C]17.1[/C][C]11.3798[/C][C]5.72016[/C][/ROW]
[ROW][C]124[/C][C]19.1[/C][C]15.9615[/C][C]3.13846[/C][/ROW]
[ROW][C]125[/C][C]16.1[/C][C]15.6999[/C][C]0.400051[/C][/ROW]
[ROW][C]126[/C][C]13.35[/C][C]8.75341[/C][C]4.59659[/C][/ROW]
[ROW][C]127[/C][C]18.4[/C][C]16.2274[/C][C]2.17258[/C][/ROW]
[ROW][C]128[/C][C]14.7[/C][C]16.6677[/C][C]-1.96772[/C][/ROW]
[ROW][C]129[/C][C]10.6[/C][C]10.799[/C][C]-0.198951[/C][/ROW]
[ROW][C]130[/C][C]12.6[/C][C]8.68755[/C][C]3.91245[/C][/ROW]
[ROW][C]131[/C][C]16.2[/C][C]15.5189[/C][C]0.681088[/C][/ROW]
[ROW][C]132[/C][C]13.6[/C][C]7.82705[/C][C]5.77295[/C][/ROW]
[ROW][C]133[/C][C]18.9[/C][C]17.748[/C][C]1.15197[/C][/ROW]
[ROW][C]134[/C][C]14.1[/C][C]12.3949[/C][C]1.70509[/C][/ROW]
[ROW][C]135[/C][C]14.5[/C][C]11.0737[/C][C]3.42632[/C][/ROW]
[ROW][C]136[/C][C]16.15[/C][C]14.3799[/C][C]1.77005[/C][/ROW]
[ROW][C]137[/C][C]14.75[/C][C]12.6122[/C][C]2.13776[/C][/ROW]
[ROW][C]138[/C][C]14.8[/C][C]15.1226[/C][C]-0.322585[/C][/ROW]
[ROW][C]139[/C][C]12.45[/C][C]13.0748[/C][C]-0.624767[/C][/ROW]
[ROW][C]140[/C][C]12.65[/C][C]7.99272[/C][C]4.65728[/C][/ROW]
[ROW][C]141[/C][C]17.35[/C][C]21.964[/C][C]-4.61397[/C][/ROW]
[ROW][C]142[/C][C]8.6[/C][C]2.93829[/C][C]5.66171[/C][/ROW]
[ROW][C]143[/C][C]18.4[/C][C]17.2915[/C][C]1.1085[/C][/ROW]
[ROW][C]144[/C][C]16.1[/C][C]17.1202[/C][C]-1.02018[/C][/ROW]
[ROW][C]145[/C][C]11.6[/C][C]6.8979[/C][C]4.7021[/C][/ROW]
[ROW][C]146[/C][C]17.75[/C][C]15.3805[/C][C]2.36952[/C][/ROW]
[ROW][C]147[/C][C]15.25[/C][C]10.2216[/C][C]5.02843[/C][/ROW]
[ROW][C]148[/C][C]17.65[/C][C]15.7776[/C][C]1.87235[/C][/ROW]
[ROW][C]149[/C][C]15.6[/C][C]12.5098[/C][C]3.09021[/C][/ROW]
[ROW][C]150[/C][C]16.35[/C][C]12.6517[/C][C]3.69828[/C][/ROW]
[ROW][C]151[/C][C]17.65[/C][C]18.8656[/C][C]-1.2156[/C][/ROW]
[ROW][C]152[/C][C]13.6[/C][C]14.9943[/C][C]-1.39426[/C][/ROW]
[ROW][C]153[/C][C]11.7[/C][C]11.0844[/C][C]0.61556[/C][/ROW]
[ROW][C]154[/C][C]14.35[/C][C]12.7764[/C][C]1.57357[/C][/ROW]
[ROW][C]155[/C][C]14.75[/C][C]9.96924[/C][C]4.78076[/C][/ROW]
[ROW][C]156[/C][C]18.25[/C][C]21.2239[/C][C]-2.97392[/C][/ROW]
[ROW][C]157[/C][C]9.9[/C][C]7.52093[/C][C]2.37907[/C][/ROW]
[ROW][C]158[/C][C]16[/C][C]11.1535[/C][C]4.84648[/C][/ROW]
[ROW][C]159[/C][C]18.25[/C][C]13.982[/C][C]4.26797[/C][/ROW]
[ROW][C]160[/C][C]16.85[/C][C]15.2907[/C][C]1.55927[/C][/ROW]
[ROW][C]161[/C][C]14.6[/C][C]14.6934[/C][C]-0.0934347[/C][/ROW]
[ROW][C]162[/C][C]13.85[/C][C]8.78646[/C][C]5.06354[/C][/ROW]
[ROW][C]163[/C][C]18.95[/C][C]16.4926[/C][C]2.45738[/C][/ROW]
[ROW][C]164[/C][C]15.6[/C][C]14.4832[/C][C]1.1168[/C][/ROW]
[ROW][C]165[/C][C]14.85[/C][C]15.8555[/C][C]-1.00546[/C][/ROW]
[ROW][C]166[/C][C]11.75[/C][C]6.33392[/C][C]5.41608[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]15.291[/C][C]3.15899[/C][/ROW]
[ROW][C]168[/C][C]15.9[/C][C]11.9828[/C][C]3.91716[/C][/ROW]
[ROW][C]169[/C][C]17.1[/C][C]14.7554[/C][C]2.34461[/C][/ROW]
[ROW][C]170[/C][C]16.1[/C][C]10.7613[/C][C]5.33871[/C][/ROW]
[ROW][C]171[/C][C]19.9[/C][C]21.1501[/C][C]-1.25011[/C][/ROW]
[ROW][C]172[/C][C]10.95[/C][C]5.01734[/C][C]5.93266[/C][/ROW]
[ROW][C]173[/C][C]18.45[/C][C]16.6329[/C][C]1.81714[/C][/ROW]
[ROW][C]174[/C][C]15.1[/C][C]13.783[/C][C]1.317[/C][/ROW]
[ROW][C]175[/C][C]15[/C][C]16.0396[/C][C]-1.03964[/C][/ROW]
[ROW][C]176[/C][C]11.35[/C][C]8.41644[/C][C]2.93356[/C][/ROW]
[ROW][C]177[/C][C]15.95[/C][C]11.1286[/C][C]4.82144[/C][/ROW]
[ROW][C]178[/C][C]18.1[/C][C]16.151[/C][C]1.94904[/C][/ROW]
[ROW][C]179[/C][C]14.6[/C][C]13.1738[/C][C]1.42615[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]13.5476[/C][C]1.85244[/C][/ROW]
[ROW][C]181[/C][C]15.4[/C][C]10.0208[/C][C]5.37919[/C][/ROW]
[ROW][C]182[/C][C]17.6[/C][C]18.0325[/C][C]-0.432532[/C][/ROW]
[ROW][C]183[/C][C]13.35[/C][C]6.29648[/C][C]7.05352[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]16.5081[/C][C]2.59187[/C][/ROW]
[ROW][C]185[/C][C]15.35[/C][C]20.2046[/C][C]-4.8546[/C][/ROW]
[ROW][C]186[/C][C]7.6[/C][C]7.74818[/C][C]-0.148179[/C][/ROW]
[ROW][C]187[/C][C]13.4[/C][C]12.8412[/C][C]0.558799[/C][/ROW]
[ROW][C]188[/C][C]13.9[/C][C]8.33082[/C][C]5.56918[/C][/ROW]
[ROW][C]189[/C][C]19.1[/C][C]16.2778[/C][C]2.82219[/C][/ROW]
[ROW][C]190[/C][C]15.25[/C][C]14.8829[/C][C]0.367051[/C][/ROW]
[ROW][C]191[/C][C]12.9[/C][C]9.94461[/C][C]2.95539[/C][/ROW]
[ROW][C]192[/C][C]16.1[/C][C]11.8433[/C][C]4.25666[/C][/ROW]
[ROW][C]193[/C][C]17.35[/C][C]17.1289[/C][C]0.221083[/C][/ROW]
[ROW][C]194[/C][C]13.15[/C][C]14.0351[/C][C]-0.885051[/C][/ROW]
[ROW][C]195[/C][C]12.15[/C][C]12.2574[/C][C]-0.107398[/C][/ROW]
[ROW][C]196[/C][C]12.6[/C][C]14.988[/C][C]-2.38799[/C][/ROW]
[ROW][C]197[/C][C]10.35[/C][C]7.17037[/C][C]3.17963[/C][/ROW]
[ROW][C]198[/C][C]15.4[/C][C]19.1404[/C][C]-3.7404[/C][/ROW]
[ROW][C]199[/C][C]9.6[/C][C]4.27282[/C][C]5.32718[/C][/ROW]
[ROW][C]200[/C][C]18.2[/C][C]17.8935[/C][C]0.306463[/C][/ROW]
[ROW][C]201[/C][C]13.6[/C][C]12.5572[/C][C]1.04277[/C][/ROW]
[ROW][C]202[/C][C]14.85[/C][C]12.6971[/C][C]2.15293[/C][/ROW]
[ROW][C]203[/C][C]14.75[/C][C]13.3995[/C][C]1.35047[/C][/ROW]
[ROW][C]204[/C][C]14.1[/C][C]12.0369[/C][C]2.06305[/C][/ROW]
[ROW][C]205[/C][C]14.9[/C][C]11.8062[/C][C]3.0938[/C][/ROW]
[ROW][C]206[/C][C]16.25[/C][C]11.6366[/C][C]4.61338[/C][/ROW]
[ROW][C]207[/C][C]19.25[/C][C]19.7932[/C][C]-0.543168[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]13.1229[/C][C]0.477088[/C][/ROW]
[ROW][C]209[/C][C]13.6[/C][C]10.4498[/C][C]3.15021[/C][/ROW]
[ROW][C]210[/C][C]15.65[/C][C]14.4918[/C][C]1.15819[/C][/ROW]
[ROW][C]211[/C][C]12.75[/C][C]10.3263[/C][C]2.42374[/C][/ROW]
[ROW][C]212[/C][C]14.6[/C][C]17.996[/C][C]-3.39602[/C][/ROW]
[ROW][C]213[/C][C]9.85[/C][C]11.1894[/C][C]-1.33943[/C][/ROW]
[ROW][C]214[/C][C]12.65[/C][C]13.4864[/C][C]-0.836385[/C][/ROW]
[ROW][C]215[/C][C]11.9[/C][C]4.94205[/C][C]6.95795[/C][/ROW]
[ROW][C]216[/C][C]19.2[/C][C]15.1215[/C][C]4.07851[/C][/ROW]
[ROW][C]217[/C][C]16.6[/C][C]18.4106[/C][C]-1.81056[/C][/ROW]
[ROW][C]218[/C][C]11.2[/C][C]9.39977[/C][C]1.80023[/C][/ROW]
[ROW][C]219[/C][C]15.25[/C][C]15.7873[/C][C]-0.53732[/C][/ROW]
[ROW][C]220[/C][C]11.9[/C][C]11.3226[/C][C]0.577352[/C][/ROW]
[ROW][C]221[/C][C]13.2[/C][C]9.43673[/C][C]3.76327[/C][/ROW]
[ROW][C]222[/C][C]16.35[/C][C]17.1917[/C][C]-0.841714[/C][/ROW]
[ROW][C]223[/C][C]12.4[/C][C]9.10646[/C][C]3.29354[/C][/ROW]
[ROW][C]224[/C][C]15.85[/C][C]15.9423[/C][C]-0.0922871[/C][/ROW]
[ROW][C]225[/C][C]14.35[/C][C]9.0899[/C][C]5.2601[/C][/ROW]
[ROW][C]226[/C][C]18.15[/C][C]19.4011[/C][C]-1.25111[/C][/ROW]
[ROW][C]227[/C][C]11.15[/C][C]8.62217[/C][C]2.52783[/C][/ROW]
[ROW][C]228[/C][C]15.65[/C][C]9.93574[/C][C]5.71426[/C][/ROW]
[ROW][C]229[/C][C]17.75[/C][C]21.7478[/C][C]-3.99783[/C][/ROW]
[ROW][C]230[/C][C]7.65[/C][C]8.72731[/C][C]-1.07731[/C][/ROW]
[ROW][C]231[/C][C]12.35[/C][C]9.49549[/C][C]2.85451[/C][/ROW]
[ROW][C]232[/C][C]15.6[/C][C]8.44162[/C][C]7.15838[/C][/ROW]
[ROW][C]233[/C][C]19.3[/C][C]17.2217[/C][C]2.07827[/C][/ROW]
[ROW][C]234[/C][C]15.2[/C][C]11.5442[/C][C]3.6558[/C][/ROW]
[ROW][C]235[/C][C]17.1[/C][C]14.1121[/C][C]2.9879[/C][/ROW]
[ROW][C]236[/C][C]15.6[/C][C]9.83497[/C][C]5.76503[/C][/ROW]
[ROW][C]237[/C][C]18.4[/C][C]12.339[/C][C]6.06098[/C][/ROW]
[ROW][C]238[/C][C]19.05[/C][C]13.8426[/C][C]5.20737[/C][/ROW]
[ROW][C]239[/C][C]18.55[/C][C]13.2406[/C][C]5.30942[/C][/ROW]
[ROW][C]240[/C][C]19.1[/C][C]18.3895[/C][C]0.710464[/C][/ROW]
[ROW][C]241[/C][C]13.1[/C][C]12.7164[/C][C]0.383615[/C][/ROW]
[ROW][C]242[/C][C]12.85[/C][C]17.2031[/C][C]-4.35313[/C][/ROW]
[ROW][C]243[/C][C]9.5[/C][C]18.2876[/C][C]-8.78758[/C][/ROW]
[ROW][C]244[/C][C]4.5[/C][C]5.53367[/C][C]-1.03367[/C][/ROW]
[ROW][C]245[/C][C]11.85[/C][C]11.0157[/C][C]0.834346[/C][/ROW]
[ROW][C]246[/C][C]13.6[/C][C]16.6151[/C][C]-3.01508[/C][/ROW]
[ROW][C]247[/C][C]11.7[/C][C]11.717[/C][C]-0.0170279[/C][/ROW]
[ROW][C]248[/C][C]12.4[/C][C]12.7071[/C][C]-0.307065[/C][/ROW]
[ROW][C]249[/C][C]13.35[/C][C]13.4916[/C][C]-0.141553[/C][/ROW]
[ROW][C]250[/C][C]11.4[/C][C]9.47705[/C][C]1.92295[/C][/ROW]
[ROW][C]251[/C][C]14.9[/C][C]8.26647[/C][C]6.63353[/C][/ROW]
[ROW][C]252[/C][C]19.9[/C][C]15.8856[/C][C]4.01438[/C][/ROW]
[ROW][C]253[/C][C]17.75[/C][C]20.3997[/C][C]-2.64967[/C][/ROW]
[ROW][C]254[/C][C]11.2[/C][C]8.72028[/C][C]2.47972[/C][/ROW]
[ROW][C]255[/C][C]14.6[/C][C]9.83047[/C][C]4.76953[/C][/ROW]
[ROW][C]256[/C][C]17.6[/C][C]16.1997[/C][C]1.40029[/C][/ROW]
[ROW][C]257[/C][C]14.05[/C][C]10.875[/C][C]3.17505[/C][/ROW]
[ROW][C]258[/C][C]16.1[/C][C]16.239[/C][C]-0.139021[/C][/ROW]
[ROW][C]259[/C][C]13.35[/C][C]13.9833[/C][C]-0.6333[/C][/ROW]
[ROW][C]260[/C][C]11.85[/C][C]13.2271[/C][C]-1.37711[/C][/ROW]
[ROW][C]261[/C][C]11.95[/C][C]9.75681[/C][C]2.19319[/C][/ROW]
[ROW][C]262[/C][C]14.75[/C][C]11.3331[/C][C]3.4169[/C][/ROW]
[ROW][C]263[/C][C]15.15[/C][C]14.398[/C][C]0.75198[/C][/ROW]
[ROW][C]264[/C][C]13.2[/C][C]9.35638[/C][C]3.84362[/C][/ROW]
[ROW][C]265[/C][C]16.85[/C][C]20.8403[/C][C]-3.99031[/C][/ROW]
[ROW][C]266[/C][C]7.85[/C][C]12.5411[/C][C]-4.69106[/C][/ROW]
[ROW][C]267[/C][C]7.7[/C][C]7.8825[/C][C]-0.182495[/C][/ROW]
[ROW][C]268[/C][C]12.6[/C][C]18.0073[/C][C]-5.40726[/C][/ROW]
[ROW][C]269[/C][C]7.85[/C][C]10.5707[/C][C]-2.72067[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]10.803[/C][C]0.147049[/C][/ROW]
[ROW][C]271[/C][C]12.35[/C][C]15.4217[/C][C]-3.07171[/C][/ROW]
[ROW][C]272[/C][C]9.95[/C][C]8.1133[/C][C]1.8367[/C][/ROW]
[ROW][C]273[/C][C]14.9[/C][C]11.0574[/C][C]3.84261[/C][/ROW]
[ROW][C]274[/C][C]16.65[/C][C]16.8915[/C][C]-0.241541[/C][/ROW]
[ROW][C]275[/C][C]13.4[/C][C]12.8735[/C][C]0.526495[/C][/ROW]
[ROW][C]276[/C][C]13.95[/C][C]10.173[/C][C]3.77696[/C][/ROW]
[ROW][C]277[/C][C]15.7[/C][C]12.0268[/C][C]3.67317[/C][/ROW]
[ROW][C]278[/C][C]16.85[/C][C]18.6836[/C][C]-1.83359[/C][/ROW]
[ROW][C]279[/C][C]10.95[/C][C]7.6677[/C][C]3.2823[/C][/ROW]
[ROW][C]280[/C][C]15.35[/C][C]15.7056[/C][C]-0.355573[/C][/ROW]
[ROW][C]281[/C][C]12.2[/C][C]9.58458[/C][C]2.61542[/C][/ROW]
[ROW][C]282[/C][C]15.1[/C][C]10.3145[/C][C]4.78547[/C][/ROW]
[ROW][C]283[/C][C]17.75[/C][C]15.5914[/C][C]2.15859[/C][/ROW]
[ROW][C]284[/C][C]15.2[/C][C]13.8887[/C][C]1.31129[/C][/ROW]
[ROW][C]285[/C][C]14.6[/C][C]10.4155[/C][C]4.1845[/C][/ROW]
[ROW][C]286[/C][C]16.65[/C][C]21.0998[/C][C]-4.44981[/C][/ROW]
[ROW][C]287[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266484&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266484&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.9825-0.082498
27.411.9695-4.56946
312.212.7613-0.561264
412.813.3334-0.533364
57.412.9913-5.59131
66.713.2622-6.56217
712.612.6244-0.0244287
814.811.97232.82769
913.313.9298-0.629824
1011.112.0945-0.994518
118.215.1191-6.91908
1211.412.293-0.892985
136.413.3667-6.96667
1410.611.4975-0.89754
151213.1564-1.15637
166.312.8898-6.58982
1711.312.4216-1.12158
1811.912.3817-0.481736
199.312.6135-3.31353
209.613.3487-3.74866
211012.498-2.49798
226.413.2963-6.89628
2313.813.25120.548794
2410.812.5687-1.76873
2513.812.40441.39564
2611.713.0497-1.3497
2710.912.5286-1.62863
2816.112.36333.73675
2913.413.36130.0387395
309.912.7664-2.8664
3111.512.5092-1.00921
328.311.7196-3.41957
3311.713.6713-1.97131
346.112.9286-6.82862
35912.1928-3.19281
369.712.5445-2.84453
3710.812.3773-1.57732
3810.313.3338-3.03376
3910.413.1116-2.71162
4012.712.9728-0.272759
419.313.522-4.22196
4211.812.3607-0.560676
435.913.4423-7.54233
4411.413.522-2.12196
451313.0444-0.044423
4610.811.5709-0.770933
4712.312.26940.0306078
4811.312.9844-1.68435
4911.813.3256-1.52564
507.912.7915-4.89146
5112.712.54890.151102
5212.313.2531-0.953127
5311.612.1709-0.57086
546.713.0301-6.33012
5510.912.9935-2.09345
5612.112.6168-0.516831
5713.313.4972-0.197172
5810.113.003-2.90303
595.711.9875-6.28751
6014.312.78641.51358
61813.1331-5.13312
6213.313.3388-0.0387997
639.313.5416-4.24162
6412.512.7643-0.264314
657.611.8561-4.25611
6615.913.12972.77032
679.212.8343-3.63427
689.113.1823-4.08234
6911.112.3371-1.23705
701313.4681-0.46814
7114.513.08451.41549
7212.212.8233-0.623282
7312.313.1502-0.85015
7411.412.8455-1.4455
758.813.3646-4.56461
7614.613.65550.944476
777.312.3766-5.07659
7812.612.13880.461233
79NANA0.513293
801313.5578-0.557793
8112.613.1094-0.50943
8213.215.4396-2.23961
839.914.4821-4.58209
847.79.87667-2.17667
8510.59.59670.903299
8613.415.2779-1.87795
8710.918.7353-7.83535
884.37.34845-3.04845
8910.311.5862-1.28622
9011.813.6361-1.83608
9111.212.2646-1.06456
9211.415.5705-4.17048
938.67.901420.698582
9413.213.654-0.454028
9512.619.3863-6.78629
965.68.70012-3.10012
979.913.6097-3.70969
988.814.1365-5.33653
997.711.2519-3.55195
100914.5612-5.5612
1017.38.90065-1.60065
10211.410.39081.00917
10313.618.2029-4.60288
1047.99.63709-1.73709
10510.712.5984-1.8984
10610.314.1885-3.88853
1078.311.454-3.15401
1089.68.640410.959594
10914.218.8031-4.60315
1108.58.61852-0.118523
11113.521.1958-7.69577
1124.911.2024-6.30239
1136.410.378-3.97795
1149.610.9218-1.3218
11511.613.3461-1.74609
11611.120.6554-9.55541
1174.353.60350.7465
11812.77.487445.21256
11918.112.5915.50902
12017.8515.15382.6962
12116.617.591-0.991026
12212.69.26263.3374
12317.111.37985.72016
12419.115.96153.13846
12516.115.69990.400051
12613.358.753414.59659
12718.416.22742.17258
12814.716.6677-1.96772
12910.610.799-0.198951
13012.68.687553.91245
13116.215.51890.681088
13213.67.827055.77295
13318.917.7481.15197
13414.112.39491.70509
13514.511.07373.42632
13616.1514.37991.77005
13714.7512.61222.13776
13814.815.1226-0.322585
13912.4513.0748-0.624767
14012.657.992724.65728
14117.3521.964-4.61397
1428.62.938295.66171
14318.417.29151.1085
14416.117.1202-1.02018
14511.66.89794.7021
14617.7515.38052.36952
14715.2510.22165.02843
14817.6515.77761.87235
14915.612.50983.09021
15016.3512.65173.69828
15117.6518.8656-1.2156
15213.614.9943-1.39426
15311.711.08440.61556
15414.3512.77641.57357
15514.759.969244.78076
15618.2521.2239-2.97392
1579.97.520932.37907
1581611.15354.84648
15918.2513.9824.26797
16016.8515.29071.55927
16114.614.6934-0.0934347
16213.858.786465.06354
16318.9516.49262.45738
16415.614.48321.1168
16514.8515.8555-1.00546
16611.756.333925.41608
16718.4515.2913.15899
16815.911.98283.91716
16917.114.75542.34461
17016.110.76135.33871
17119.921.1501-1.25011
17210.955.017345.93266
17318.4516.63291.81714
17415.113.7831.317
1751516.0396-1.03964
17611.358.416442.93356
17715.9511.12864.82144
17818.116.1511.94904
17914.613.17381.42615
18015.413.54761.85244
18115.410.02085.37919
18217.618.0325-0.432532
18313.356.296487.05352
18419.116.50812.59187
18515.3520.2046-4.8546
1867.67.74818-0.148179
18713.412.84120.558799
18813.98.330825.56918
18919.116.27782.82219
19015.2514.88290.367051
19112.99.944612.95539
19216.111.84334.25666
19317.3517.12890.221083
19413.1514.0351-0.885051
19512.1512.2574-0.107398
19612.614.988-2.38799
19710.357.170373.17963
19815.419.1404-3.7404
1999.64.272825.32718
20018.217.89350.306463
20113.612.55721.04277
20214.8512.69712.15293
20314.7513.39951.35047
20414.112.03692.06305
20514.911.80623.0938
20616.2511.63664.61338
20719.2519.7932-0.543168
20813.613.12290.477088
20913.610.44983.15021
21015.6514.49181.15819
21112.7510.32632.42374
21214.617.996-3.39602
2139.8511.1894-1.33943
21412.6513.4864-0.836385
21511.94.942056.95795
21619.215.12154.07851
21716.618.4106-1.81056
21811.29.399771.80023
21915.2515.7873-0.53732
22011.911.32260.577352
22113.29.436733.76327
22216.3517.1917-0.841714
22312.49.106463.29354
22415.8515.9423-0.0922871
22514.359.08995.2601
22618.1519.4011-1.25111
22711.158.622172.52783
22815.659.935745.71426
22917.7521.7478-3.99783
2307.658.72731-1.07731
23112.359.495492.85451
23215.68.441627.15838
23319.317.22172.07827
23415.211.54423.6558
23517.114.11212.9879
23615.69.834975.76503
23718.412.3396.06098
23819.0513.84265.20737
23918.5513.24065.30942
24019.118.38950.710464
24113.112.71640.383615
24212.8517.2031-4.35313
2439.518.2876-8.78758
2444.55.53367-1.03367
24511.8511.01570.834346
24613.616.6151-3.01508
24711.711.717-0.0170279
24812.412.7071-0.307065
24913.3513.4916-0.141553
25011.49.477051.92295
25114.98.266476.63353
25219.915.88564.01438
25317.7520.3997-2.64967
25411.28.720282.47972
25514.69.830474.76953
25617.616.19971.40029
25714.0510.8753.17505
25816.116.239-0.139021
25913.3513.9833-0.6333
26011.8513.2271-1.37711
26111.959.756812.19319
26214.7511.33313.4169
26315.1514.3980.75198
26413.29.356383.84362
26516.8520.8403-3.99031
2667.8512.5411-4.69106
2677.77.8825-0.182495
26812.618.0073-5.40726
2697.8510.5707-2.72067
27010.9510.8030.147049
27112.3515.4217-3.07171
2729.958.11331.8367
27314.911.05743.84261
27416.6516.8915-0.241541
27513.412.87350.526495
27613.9510.1733.77696
27715.712.02683.67317
27816.8518.6836-1.83359
27910.957.66773.2823
28015.3515.7056-0.355573
28112.29.584582.61542
28215.110.31454.78547
28317.7515.59142.15859
28415.213.88871.31129
28514.610.41554.1845
28616.6521.0998-4.44981
2878.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.3970440.7940890.602956
110.2919580.5839170.708042
120.1927330.3854650.807267
130.3973620.7947230.602638
140.2888670.5777340.711133
150.2032810.4065620.796719
160.220120.4402390.77988
170.151590.3031790.84841
180.103980.2079590.89602
190.07960810.1592160.920392
200.05771140.1154230.942289
210.04094560.08189110.959054
220.02776160.05552320.972238
230.01775870.03551740.982241
240.01061560.02123130.989384
250.009786740.01957350.990213
260.008146370.01629270.991854
270.005278540.01055710.994721
280.005110170.01022030.99489
290.003818480.007636950.996182
300.002273980.004547960.997726
310.001396920.002793840.998603
320.001140540.002281090.998859
330.0007112660.001422530.999289
340.0005318950.001063790.999468
350.0004502020.0009004040.99955
360.02024730.04049460.979753
370.01403430.02806860.985966
380.01117820.02235640.988822
390.007981020.0159620.992019
400.005452930.01090590.994547
410.004125740.008251470.995874
420.002687650.005375310.997312
430.006926650.01385330.993073
440.0052390.0104780.994761
450.005039820.01007960.99496
460.00655060.01310120.993449
470.004514210.009028410.995486
480.003167070.006334150.996833
490.002569290.005138580.997431
500.002205810.004411630.997794
510.001658560.003317130.998341
520.001671680.003343360.998328
530.001195990.002391980.998804
540.002945120.005890250.997055
550.002157370.004314730.997843
560.002064330.004128660.997936
570.001871950.003743910.998128
580.001469250.00293850.998531
590.002547110.005094230.997453
600.002557440.005114880.997443
610.003062590.006125190.996937
620.003419570.006839140.99658
630.002910880.005821750.997089
640.002519250.005038510.997481
650.002834430.005668860.997166
660.004889020.009778040.995111
670.004383770.008767550.995616
680.003976630.007953260.996023
690.002965920.005931850.997034
700.002722130.005444260.997278
710.003038680.006077350.996961
720.002394650.004789290.997605
730.001749830.003499670.99825
740.001300160.002600330.9987
750.001274130.002548260.998726
760.001415880.002831750.998584
770.001721640.003443280.998278
780.00133030.002660590.99867
790.00130680.002613590.998693
800.001009820.002019630.99899
810.0009297250.001859450.99907
820.0007358170.001471630.999264
830.0008503620.001700720.99915
840.0006378940.001275790.999362
850.0005634340.001126870.999437
860.0004501720.0009003430.99955
870.002348920.004697830.997651
880.00193390.003867790.998066
890.001516030.003032060.998484
900.001160870.002321730.998839
910.0009489660.001897930.999051
920.0009946290.001989260.999005
930.0009094770.001818950.999091
940.0007249920.001449980.999275
950.002077810.004155610.997922
960.001808070.003616130.998192
970.001749370.003498750.998251
980.002087790.004175580.997912
990.001983880.003967750.998016
1000.002911670.005823350.997088
1010.002349820.004699630.99765
1020.002385010.004770020.997615
1030.002753220.005506440.997247
1040.002262280.004524560.997738
1050.001918330.003836650.998082
1060.002252830.004505670.997747
1070.002046570.004093150.997953
1080.002297940.004595880.997702
1090.002628050.00525610.997372
1100.002343720.004687450.997656
1110.00783240.01566480.992168
1120.01443840.02887690.985562
1130.01527240.03054490.984728
1140.01366310.02732620.986337
1150.01183350.0236670.988167
1160.06097080.1219420.939029
1170.06943080.1388620.930569
1180.135210.270420.86479
1190.228780.457560.77122
1200.273050.54610.72695
1210.2527170.5054330.747283
1220.3133110.6266220.686689
1230.4381790.8763570.561821
1240.4709270.9418550.529073
1250.4581570.9163140.541843
1260.5441880.9116230.455812
1270.5451440.9097110.454856
1280.5371710.9256580.462829
1290.5135680.9728640.486432
1300.5534930.8930140.446507
1310.5300420.9399170.469958
1320.6357160.7285680.364284
1330.6226280.7547440.377372
1340.6108310.7783380.389169
1350.624520.7509610.37548
1360.6105480.7789030.389452
1370.6074230.7851540.392577
1380.5836620.8326750.416338
1390.5573050.8853910.442695
1400.6086690.7826630.391331
1410.6514660.6970680.348534
1420.7357610.5284770.264239
1430.7218210.5563570.278179
1440.7045840.5908330.295416
1450.7464620.5070750.253538
1460.7392230.5215530.260777
1470.7784240.4431530.221576
1480.7627940.4744130.237206
1490.7650350.469930.234965
1500.7766190.4467610.223381
1510.7566070.4867860.243393
1520.7416650.516670.258335
1530.7185940.5628120.281406
1540.7017830.5964340.298217
1550.7369190.5261610.263081
1560.7448920.5102170.255108
1570.7317720.5364560.268228
1580.7647930.4704140.235207
1590.7802330.4395330.219767
1600.7607880.4784230.239212
1610.7361510.5276980.263849
1620.7739330.4521340.226067
1630.7647020.4705960.235298
1640.740740.5185210.25926
1650.7222020.5555960.277798
1660.7638820.4722370.236118
1670.7594510.4810980.240549
1680.7669670.4660650.233033
1690.753670.4926590.24633
1700.7924850.415030.207515
1710.7803860.4392290.219614
1720.8286920.3426160.171308
1730.8109980.3780040.189002
1740.7892380.4215230.210762
1750.7772120.4455750.222788
1760.7686480.4627030.231352
1770.792730.4145390.20727
1780.7739760.4520480.226024
1790.7506330.4987350.249367
1800.7286990.5426020.271301
1810.7627130.4745740.237287
1820.7356020.5287960.264398
1830.8147480.3705030.185252
1840.8006790.3986420.199321
1850.8460280.3079440.153972
1860.8238930.3522140.176107
1870.7996670.4006670.200333
1880.8469290.3061420.153071
1890.8368580.3262830.163142
1900.8162450.367510.183755
1910.805940.388120.19406
1920.8186160.3627680.181384
1930.7932240.4135510.206776
1940.7692230.4615550.230777
1950.7418370.5163270.258163
1960.7374570.5250860.262543
1970.7245760.5508480.275424
1980.7464930.5070140.253507
1990.7745510.4508990.225449
2000.747290.505420.25271
2010.716930.566140.28307
2020.6930510.6138990.306949
2030.6629450.674110.337055
2040.6335860.7328280.366414
2050.613830.7723390.38617
2060.680650.63870.31935
2070.6453050.709390.354695
2080.6101630.7796740.389837
2090.5983150.8033690.401685
2100.5664960.8670070.433504
2110.5408170.9183650.459183
2120.5847010.8305980.415299
2130.5552960.8894090.444704
2140.5352220.9295550.464778
2150.5898180.8203650.410182
2160.5823070.8353870.417693
2170.566470.8670610.43353
2180.5338150.9323690.466185
2190.5079620.9840760.492038
2200.4704260.9408510.529574
2210.4548250.909650.545175
2220.4156930.8313850.584307
2230.403530.807060.59647
2240.3633270.7266530.636673
2250.3906370.7812740.609363
2260.3651550.7303090.634845
2270.3451790.6903580.654821
2280.3690650.7381310.630935
2290.4472840.8945690.552716
2300.4063540.8127090.593646
2310.3810810.7621610.618919
2320.493520.9870390.50648
2330.4635780.9271560.536422
2340.4452630.8905250.554737
2350.4152020.8304030.584798
2360.4679790.9359580.532021
2370.5580930.8838130.441907
2380.6532190.6935630.346781
2390.7013070.5973860.298693
2400.6596880.6806240.340312
2410.612770.7744590.38723
2420.6181130.7637740.381887
2430.8668140.2663720.133186
2440.8473730.3052540.152627
2450.8139440.3721130.186056
2460.826430.3471390.17357
2470.8108350.378330.189165
2480.7724750.4550490.227525
2490.7365660.5268680.263434
2500.7034490.5931010.296551
2510.7635860.4728290.236414
2520.8040890.3918220.195911
2530.7830280.4339440.216972
2540.7411450.5177090.258855
2550.7428480.5143030.257152
2560.6902370.6195260.309763
2570.6583280.6833440.341672
2580.5974630.8050730.402537
2590.5444790.9110410.455521
2600.4828010.9656010.517199
2610.4203550.840710.579645
2620.619020.7619590.38098
2630.6526040.6947910.347396
2640.6426610.7146770.357339
2650.6358970.7282060.364103
2660.8984170.2031650.101583
2670.8666760.2666490.133324
2680.9364360.1271280.0635639
2690.9326150.134770.0673849
2700.9107790.1784410.0892205
2710.907390.1852210.0926104
2720.8470940.3058130.152906
2730.8071240.3857510.192876
2740.9715120.05697690.0284885
2750.9386350.1227310.0613655
2760.9873670.0252660.012633
2770.9350220.1299560.064978

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.397044 & 0.794089 & 0.602956 \tabularnewline
11 & 0.291958 & 0.583917 & 0.708042 \tabularnewline
12 & 0.192733 & 0.385465 & 0.807267 \tabularnewline
13 & 0.397362 & 0.794723 & 0.602638 \tabularnewline
14 & 0.288867 & 0.577734 & 0.711133 \tabularnewline
15 & 0.203281 & 0.406562 & 0.796719 \tabularnewline
16 & 0.22012 & 0.440239 & 0.77988 \tabularnewline
17 & 0.15159 & 0.303179 & 0.84841 \tabularnewline
18 & 0.10398 & 0.207959 & 0.89602 \tabularnewline
19 & 0.0796081 & 0.159216 & 0.920392 \tabularnewline
20 & 0.0577114 & 0.115423 & 0.942289 \tabularnewline
21 & 0.0409456 & 0.0818911 & 0.959054 \tabularnewline
22 & 0.0277616 & 0.0555232 & 0.972238 \tabularnewline
23 & 0.0177587 & 0.0355174 & 0.982241 \tabularnewline
24 & 0.0106156 & 0.0212313 & 0.989384 \tabularnewline
25 & 0.00978674 & 0.0195735 & 0.990213 \tabularnewline
26 & 0.00814637 & 0.0162927 & 0.991854 \tabularnewline
27 & 0.00527854 & 0.0105571 & 0.994721 \tabularnewline
28 & 0.00511017 & 0.0102203 & 0.99489 \tabularnewline
29 & 0.00381848 & 0.00763695 & 0.996182 \tabularnewline
30 & 0.00227398 & 0.00454796 & 0.997726 \tabularnewline
31 & 0.00139692 & 0.00279384 & 0.998603 \tabularnewline
32 & 0.00114054 & 0.00228109 & 0.998859 \tabularnewline
33 & 0.000711266 & 0.00142253 & 0.999289 \tabularnewline
34 & 0.000531895 & 0.00106379 & 0.999468 \tabularnewline
35 & 0.000450202 & 0.000900404 & 0.99955 \tabularnewline
36 & 0.0202473 & 0.0404946 & 0.979753 \tabularnewline
37 & 0.0140343 & 0.0280686 & 0.985966 \tabularnewline
38 & 0.0111782 & 0.0223564 & 0.988822 \tabularnewline
39 & 0.00798102 & 0.015962 & 0.992019 \tabularnewline
40 & 0.00545293 & 0.0109059 & 0.994547 \tabularnewline
41 & 0.00412574 & 0.00825147 & 0.995874 \tabularnewline
42 & 0.00268765 & 0.00537531 & 0.997312 \tabularnewline
43 & 0.00692665 & 0.0138533 & 0.993073 \tabularnewline
44 & 0.005239 & 0.010478 & 0.994761 \tabularnewline
45 & 0.00503982 & 0.0100796 & 0.99496 \tabularnewline
46 & 0.0065506 & 0.0131012 & 0.993449 \tabularnewline
47 & 0.00451421 & 0.00902841 & 0.995486 \tabularnewline
48 & 0.00316707 & 0.00633415 & 0.996833 \tabularnewline
49 & 0.00256929 & 0.00513858 & 0.997431 \tabularnewline
50 & 0.00220581 & 0.00441163 & 0.997794 \tabularnewline
51 & 0.00165856 & 0.00331713 & 0.998341 \tabularnewline
52 & 0.00167168 & 0.00334336 & 0.998328 \tabularnewline
53 & 0.00119599 & 0.00239198 & 0.998804 \tabularnewline
54 & 0.00294512 & 0.00589025 & 0.997055 \tabularnewline
55 & 0.00215737 & 0.00431473 & 0.997843 \tabularnewline
56 & 0.00206433 & 0.00412866 & 0.997936 \tabularnewline
57 & 0.00187195 & 0.00374391 & 0.998128 \tabularnewline
58 & 0.00146925 & 0.0029385 & 0.998531 \tabularnewline
59 & 0.00254711 & 0.00509423 & 0.997453 \tabularnewline
60 & 0.00255744 & 0.00511488 & 0.997443 \tabularnewline
61 & 0.00306259 & 0.00612519 & 0.996937 \tabularnewline
62 & 0.00341957 & 0.00683914 & 0.99658 \tabularnewline
63 & 0.00291088 & 0.00582175 & 0.997089 \tabularnewline
64 & 0.00251925 & 0.00503851 & 0.997481 \tabularnewline
65 & 0.00283443 & 0.00566886 & 0.997166 \tabularnewline
66 & 0.00488902 & 0.00977804 & 0.995111 \tabularnewline
67 & 0.00438377 & 0.00876755 & 0.995616 \tabularnewline
68 & 0.00397663 & 0.00795326 & 0.996023 \tabularnewline
69 & 0.00296592 & 0.00593185 & 0.997034 \tabularnewline
70 & 0.00272213 & 0.00544426 & 0.997278 \tabularnewline
71 & 0.00303868 & 0.00607735 & 0.996961 \tabularnewline
72 & 0.00239465 & 0.00478929 & 0.997605 \tabularnewline
73 & 0.00174983 & 0.00349967 & 0.99825 \tabularnewline
74 & 0.00130016 & 0.00260033 & 0.9987 \tabularnewline
75 & 0.00127413 & 0.00254826 & 0.998726 \tabularnewline
76 & 0.00141588 & 0.00283175 & 0.998584 \tabularnewline
77 & 0.00172164 & 0.00344328 & 0.998278 \tabularnewline
78 & 0.0013303 & 0.00266059 & 0.99867 \tabularnewline
79 & 0.0013068 & 0.00261359 & 0.998693 \tabularnewline
80 & 0.00100982 & 0.00201963 & 0.99899 \tabularnewline
81 & 0.000929725 & 0.00185945 & 0.99907 \tabularnewline
82 & 0.000735817 & 0.00147163 & 0.999264 \tabularnewline
83 & 0.000850362 & 0.00170072 & 0.99915 \tabularnewline
84 & 0.000637894 & 0.00127579 & 0.999362 \tabularnewline
85 & 0.000563434 & 0.00112687 & 0.999437 \tabularnewline
86 & 0.000450172 & 0.000900343 & 0.99955 \tabularnewline
87 & 0.00234892 & 0.00469783 & 0.997651 \tabularnewline
88 & 0.0019339 & 0.00386779 & 0.998066 \tabularnewline
89 & 0.00151603 & 0.00303206 & 0.998484 \tabularnewline
90 & 0.00116087 & 0.00232173 & 0.998839 \tabularnewline
91 & 0.000948966 & 0.00189793 & 0.999051 \tabularnewline
92 & 0.000994629 & 0.00198926 & 0.999005 \tabularnewline
93 & 0.000909477 & 0.00181895 & 0.999091 \tabularnewline
94 & 0.000724992 & 0.00144998 & 0.999275 \tabularnewline
95 & 0.00207781 & 0.00415561 & 0.997922 \tabularnewline
96 & 0.00180807 & 0.00361613 & 0.998192 \tabularnewline
97 & 0.00174937 & 0.00349875 & 0.998251 \tabularnewline
98 & 0.00208779 & 0.00417558 & 0.997912 \tabularnewline
99 & 0.00198388 & 0.00396775 & 0.998016 \tabularnewline
100 & 0.00291167 & 0.00582335 & 0.997088 \tabularnewline
101 & 0.00234982 & 0.00469963 & 0.99765 \tabularnewline
102 & 0.00238501 & 0.00477002 & 0.997615 \tabularnewline
103 & 0.00275322 & 0.00550644 & 0.997247 \tabularnewline
104 & 0.00226228 & 0.00452456 & 0.997738 \tabularnewline
105 & 0.00191833 & 0.00383665 & 0.998082 \tabularnewline
106 & 0.00225283 & 0.00450567 & 0.997747 \tabularnewline
107 & 0.00204657 & 0.00409315 & 0.997953 \tabularnewline
108 & 0.00229794 & 0.00459588 & 0.997702 \tabularnewline
109 & 0.00262805 & 0.0052561 & 0.997372 \tabularnewline
110 & 0.00234372 & 0.00468745 & 0.997656 \tabularnewline
111 & 0.0078324 & 0.0156648 & 0.992168 \tabularnewline
112 & 0.0144384 & 0.0288769 & 0.985562 \tabularnewline
113 & 0.0152724 & 0.0305449 & 0.984728 \tabularnewline
114 & 0.0136631 & 0.0273262 & 0.986337 \tabularnewline
115 & 0.0118335 & 0.023667 & 0.988167 \tabularnewline
116 & 0.0609708 & 0.121942 & 0.939029 \tabularnewline
117 & 0.0694308 & 0.138862 & 0.930569 \tabularnewline
118 & 0.13521 & 0.27042 & 0.86479 \tabularnewline
119 & 0.22878 & 0.45756 & 0.77122 \tabularnewline
120 & 0.27305 & 0.5461 & 0.72695 \tabularnewline
121 & 0.252717 & 0.505433 & 0.747283 \tabularnewline
122 & 0.313311 & 0.626622 & 0.686689 \tabularnewline
123 & 0.438179 & 0.876357 & 0.561821 \tabularnewline
124 & 0.470927 & 0.941855 & 0.529073 \tabularnewline
125 & 0.458157 & 0.916314 & 0.541843 \tabularnewline
126 & 0.544188 & 0.911623 & 0.455812 \tabularnewline
127 & 0.545144 & 0.909711 & 0.454856 \tabularnewline
128 & 0.537171 & 0.925658 & 0.462829 \tabularnewline
129 & 0.513568 & 0.972864 & 0.486432 \tabularnewline
130 & 0.553493 & 0.893014 & 0.446507 \tabularnewline
131 & 0.530042 & 0.939917 & 0.469958 \tabularnewline
132 & 0.635716 & 0.728568 & 0.364284 \tabularnewline
133 & 0.622628 & 0.754744 & 0.377372 \tabularnewline
134 & 0.610831 & 0.778338 & 0.389169 \tabularnewline
135 & 0.62452 & 0.750961 & 0.37548 \tabularnewline
136 & 0.610548 & 0.778903 & 0.389452 \tabularnewline
137 & 0.607423 & 0.785154 & 0.392577 \tabularnewline
138 & 0.583662 & 0.832675 & 0.416338 \tabularnewline
139 & 0.557305 & 0.885391 & 0.442695 \tabularnewline
140 & 0.608669 & 0.782663 & 0.391331 \tabularnewline
141 & 0.651466 & 0.697068 & 0.348534 \tabularnewline
142 & 0.735761 & 0.528477 & 0.264239 \tabularnewline
143 & 0.721821 & 0.556357 & 0.278179 \tabularnewline
144 & 0.704584 & 0.590833 & 0.295416 \tabularnewline
145 & 0.746462 & 0.507075 & 0.253538 \tabularnewline
146 & 0.739223 & 0.521553 & 0.260777 \tabularnewline
147 & 0.778424 & 0.443153 & 0.221576 \tabularnewline
148 & 0.762794 & 0.474413 & 0.237206 \tabularnewline
149 & 0.765035 & 0.46993 & 0.234965 \tabularnewline
150 & 0.776619 & 0.446761 & 0.223381 \tabularnewline
151 & 0.756607 & 0.486786 & 0.243393 \tabularnewline
152 & 0.741665 & 0.51667 & 0.258335 \tabularnewline
153 & 0.718594 & 0.562812 & 0.281406 \tabularnewline
154 & 0.701783 & 0.596434 & 0.298217 \tabularnewline
155 & 0.736919 & 0.526161 & 0.263081 \tabularnewline
156 & 0.744892 & 0.510217 & 0.255108 \tabularnewline
157 & 0.731772 & 0.536456 & 0.268228 \tabularnewline
158 & 0.764793 & 0.470414 & 0.235207 \tabularnewline
159 & 0.780233 & 0.439533 & 0.219767 \tabularnewline
160 & 0.760788 & 0.478423 & 0.239212 \tabularnewline
161 & 0.736151 & 0.527698 & 0.263849 \tabularnewline
162 & 0.773933 & 0.452134 & 0.226067 \tabularnewline
163 & 0.764702 & 0.470596 & 0.235298 \tabularnewline
164 & 0.74074 & 0.518521 & 0.25926 \tabularnewline
165 & 0.722202 & 0.555596 & 0.277798 \tabularnewline
166 & 0.763882 & 0.472237 & 0.236118 \tabularnewline
167 & 0.759451 & 0.481098 & 0.240549 \tabularnewline
168 & 0.766967 & 0.466065 & 0.233033 \tabularnewline
169 & 0.75367 & 0.492659 & 0.24633 \tabularnewline
170 & 0.792485 & 0.41503 & 0.207515 \tabularnewline
171 & 0.780386 & 0.439229 & 0.219614 \tabularnewline
172 & 0.828692 & 0.342616 & 0.171308 \tabularnewline
173 & 0.810998 & 0.378004 & 0.189002 \tabularnewline
174 & 0.789238 & 0.421523 & 0.210762 \tabularnewline
175 & 0.777212 & 0.445575 & 0.222788 \tabularnewline
176 & 0.768648 & 0.462703 & 0.231352 \tabularnewline
177 & 0.79273 & 0.414539 & 0.20727 \tabularnewline
178 & 0.773976 & 0.452048 & 0.226024 \tabularnewline
179 & 0.750633 & 0.498735 & 0.249367 \tabularnewline
180 & 0.728699 & 0.542602 & 0.271301 \tabularnewline
181 & 0.762713 & 0.474574 & 0.237287 \tabularnewline
182 & 0.735602 & 0.528796 & 0.264398 \tabularnewline
183 & 0.814748 & 0.370503 & 0.185252 \tabularnewline
184 & 0.800679 & 0.398642 & 0.199321 \tabularnewline
185 & 0.846028 & 0.307944 & 0.153972 \tabularnewline
186 & 0.823893 & 0.352214 & 0.176107 \tabularnewline
187 & 0.799667 & 0.400667 & 0.200333 \tabularnewline
188 & 0.846929 & 0.306142 & 0.153071 \tabularnewline
189 & 0.836858 & 0.326283 & 0.163142 \tabularnewline
190 & 0.816245 & 0.36751 & 0.183755 \tabularnewline
191 & 0.80594 & 0.38812 & 0.19406 \tabularnewline
192 & 0.818616 & 0.362768 & 0.181384 \tabularnewline
193 & 0.793224 & 0.413551 & 0.206776 \tabularnewline
194 & 0.769223 & 0.461555 & 0.230777 \tabularnewline
195 & 0.741837 & 0.516327 & 0.258163 \tabularnewline
196 & 0.737457 & 0.525086 & 0.262543 \tabularnewline
197 & 0.724576 & 0.550848 & 0.275424 \tabularnewline
198 & 0.746493 & 0.507014 & 0.253507 \tabularnewline
199 & 0.774551 & 0.450899 & 0.225449 \tabularnewline
200 & 0.74729 & 0.50542 & 0.25271 \tabularnewline
201 & 0.71693 & 0.56614 & 0.28307 \tabularnewline
202 & 0.693051 & 0.613899 & 0.306949 \tabularnewline
203 & 0.662945 & 0.67411 & 0.337055 \tabularnewline
204 & 0.633586 & 0.732828 & 0.366414 \tabularnewline
205 & 0.61383 & 0.772339 & 0.38617 \tabularnewline
206 & 0.68065 & 0.6387 & 0.31935 \tabularnewline
207 & 0.645305 & 0.70939 & 0.354695 \tabularnewline
208 & 0.610163 & 0.779674 & 0.389837 \tabularnewline
209 & 0.598315 & 0.803369 & 0.401685 \tabularnewline
210 & 0.566496 & 0.867007 & 0.433504 \tabularnewline
211 & 0.540817 & 0.918365 & 0.459183 \tabularnewline
212 & 0.584701 & 0.830598 & 0.415299 \tabularnewline
213 & 0.555296 & 0.889409 & 0.444704 \tabularnewline
214 & 0.535222 & 0.929555 & 0.464778 \tabularnewline
215 & 0.589818 & 0.820365 & 0.410182 \tabularnewline
216 & 0.582307 & 0.835387 & 0.417693 \tabularnewline
217 & 0.56647 & 0.867061 & 0.43353 \tabularnewline
218 & 0.533815 & 0.932369 & 0.466185 \tabularnewline
219 & 0.507962 & 0.984076 & 0.492038 \tabularnewline
220 & 0.470426 & 0.940851 & 0.529574 \tabularnewline
221 & 0.454825 & 0.90965 & 0.545175 \tabularnewline
222 & 0.415693 & 0.831385 & 0.584307 \tabularnewline
223 & 0.40353 & 0.80706 & 0.59647 \tabularnewline
224 & 0.363327 & 0.726653 & 0.636673 \tabularnewline
225 & 0.390637 & 0.781274 & 0.609363 \tabularnewline
226 & 0.365155 & 0.730309 & 0.634845 \tabularnewline
227 & 0.345179 & 0.690358 & 0.654821 \tabularnewline
228 & 0.369065 & 0.738131 & 0.630935 \tabularnewline
229 & 0.447284 & 0.894569 & 0.552716 \tabularnewline
230 & 0.406354 & 0.812709 & 0.593646 \tabularnewline
231 & 0.381081 & 0.762161 & 0.618919 \tabularnewline
232 & 0.49352 & 0.987039 & 0.50648 \tabularnewline
233 & 0.463578 & 0.927156 & 0.536422 \tabularnewline
234 & 0.445263 & 0.890525 & 0.554737 \tabularnewline
235 & 0.415202 & 0.830403 & 0.584798 \tabularnewline
236 & 0.467979 & 0.935958 & 0.532021 \tabularnewline
237 & 0.558093 & 0.883813 & 0.441907 \tabularnewline
238 & 0.653219 & 0.693563 & 0.346781 \tabularnewline
239 & 0.701307 & 0.597386 & 0.298693 \tabularnewline
240 & 0.659688 & 0.680624 & 0.340312 \tabularnewline
241 & 0.61277 & 0.774459 & 0.38723 \tabularnewline
242 & 0.618113 & 0.763774 & 0.381887 \tabularnewline
243 & 0.866814 & 0.266372 & 0.133186 \tabularnewline
244 & 0.847373 & 0.305254 & 0.152627 \tabularnewline
245 & 0.813944 & 0.372113 & 0.186056 \tabularnewline
246 & 0.82643 & 0.347139 & 0.17357 \tabularnewline
247 & 0.810835 & 0.37833 & 0.189165 \tabularnewline
248 & 0.772475 & 0.455049 & 0.227525 \tabularnewline
249 & 0.736566 & 0.526868 & 0.263434 \tabularnewline
250 & 0.703449 & 0.593101 & 0.296551 \tabularnewline
251 & 0.763586 & 0.472829 & 0.236414 \tabularnewline
252 & 0.804089 & 0.391822 & 0.195911 \tabularnewline
253 & 0.783028 & 0.433944 & 0.216972 \tabularnewline
254 & 0.741145 & 0.517709 & 0.258855 \tabularnewline
255 & 0.742848 & 0.514303 & 0.257152 \tabularnewline
256 & 0.690237 & 0.619526 & 0.309763 \tabularnewline
257 & 0.658328 & 0.683344 & 0.341672 \tabularnewline
258 & 0.597463 & 0.805073 & 0.402537 \tabularnewline
259 & 0.544479 & 0.911041 & 0.455521 \tabularnewline
260 & 0.482801 & 0.965601 & 0.517199 \tabularnewline
261 & 0.420355 & 0.84071 & 0.579645 \tabularnewline
262 & 0.61902 & 0.761959 & 0.38098 \tabularnewline
263 & 0.652604 & 0.694791 & 0.347396 \tabularnewline
264 & 0.642661 & 0.714677 & 0.357339 \tabularnewline
265 & 0.635897 & 0.728206 & 0.364103 \tabularnewline
266 & 0.898417 & 0.203165 & 0.101583 \tabularnewline
267 & 0.866676 & 0.266649 & 0.133324 \tabularnewline
268 & 0.936436 & 0.127128 & 0.0635639 \tabularnewline
269 & 0.932615 & 0.13477 & 0.0673849 \tabularnewline
270 & 0.910779 & 0.178441 & 0.0892205 \tabularnewline
271 & 0.90739 & 0.185221 & 0.0926104 \tabularnewline
272 & 0.847094 & 0.305813 & 0.152906 \tabularnewline
273 & 0.807124 & 0.385751 & 0.192876 \tabularnewline
274 & 0.971512 & 0.0569769 & 0.0284885 \tabularnewline
275 & 0.938635 & 0.122731 & 0.0613655 \tabularnewline
276 & 0.987367 & 0.025266 & 0.012633 \tabularnewline
277 & 0.935022 & 0.129956 & 0.064978 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266484&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]10[/C][C]0.397044[/C][C]0.794089[/C][C]0.602956[/C][/ROW]
[ROW][C]11[/C][C]0.291958[/C][C]0.583917[/C][C]0.708042[/C][/ROW]
[ROW][C]12[/C][C]0.192733[/C][C]0.385465[/C][C]0.807267[/C][/ROW]
[ROW][C]13[/C][C]0.397362[/C][C]0.794723[/C][C]0.602638[/C][/ROW]
[ROW][C]14[/C][C]0.288867[/C][C]0.577734[/C][C]0.711133[/C][/ROW]
[ROW][C]15[/C][C]0.203281[/C][C]0.406562[/C][C]0.796719[/C][/ROW]
[ROW][C]16[/C][C]0.22012[/C][C]0.440239[/C][C]0.77988[/C][/ROW]
[ROW][C]17[/C][C]0.15159[/C][C]0.303179[/C][C]0.84841[/C][/ROW]
[ROW][C]18[/C][C]0.10398[/C][C]0.207959[/C][C]0.89602[/C][/ROW]
[ROW][C]19[/C][C]0.0796081[/C][C]0.159216[/C][C]0.920392[/C][/ROW]
[ROW][C]20[/C][C]0.0577114[/C][C]0.115423[/C][C]0.942289[/C][/ROW]
[ROW][C]21[/C][C]0.0409456[/C][C]0.0818911[/C][C]0.959054[/C][/ROW]
[ROW][C]22[/C][C]0.0277616[/C][C]0.0555232[/C][C]0.972238[/C][/ROW]
[ROW][C]23[/C][C]0.0177587[/C][C]0.0355174[/C][C]0.982241[/C][/ROW]
[ROW][C]24[/C][C]0.0106156[/C][C]0.0212313[/C][C]0.989384[/C][/ROW]
[ROW][C]25[/C][C]0.00978674[/C][C]0.0195735[/C][C]0.990213[/C][/ROW]
[ROW][C]26[/C][C]0.00814637[/C][C]0.0162927[/C][C]0.991854[/C][/ROW]
[ROW][C]27[/C][C]0.00527854[/C][C]0.0105571[/C][C]0.994721[/C][/ROW]
[ROW][C]28[/C][C]0.00511017[/C][C]0.0102203[/C][C]0.99489[/C][/ROW]
[ROW][C]29[/C][C]0.00381848[/C][C]0.00763695[/C][C]0.996182[/C][/ROW]
[ROW][C]30[/C][C]0.00227398[/C][C]0.00454796[/C][C]0.997726[/C][/ROW]
[ROW][C]31[/C][C]0.00139692[/C][C]0.00279384[/C][C]0.998603[/C][/ROW]
[ROW][C]32[/C][C]0.00114054[/C][C]0.00228109[/C][C]0.998859[/C][/ROW]
[ROW][C]33[/C][C]0.000711266[/C][C]0.00142253[/C][C]0.999289[/C][/ROW]
[ROW][C]34[/C][C]0.000531895[/C][C]0.00106379[/C][C]0.999468[/C][/ROW]
[ROW][C]35[/C][C]0.000450202[/C][C]0.000900404[/C][C]0.99955[/C][/ROW]
[ROW][C]36[/C][C]0.0202473[/C][C]0.0404946[/C][C]0.979753[/C][/ROW]
[ROW][C]37[/C][C]0.0140343[/C][C]0.0280686[/C][C]0.985966[/C][/ROW]
[ROW][C]38[/C][C]0.0111782[/C][C]0.0223564[/C][C]0.988822[/C][/ROW]
[ROW][C]39[/C][C]0.00798102[/C][C]0.015962[/C][C]0.992019[/C][/ROW]
[ROW][C]40[/C][C]0.00545293[/C][C]0.0109059[/C][C]0.994547[/C][/ROW]
[ROW][C]41[/C][C]0.00412574[/C][C]0.00825147[/C][C]0.995874[/C][/ROW]
[ROW][C]42[/C][C]0.00268765[/C][C]0.00537531[/C][C]0.997312[/C][/ROW]
[ROW][C]43[/C][C]0.00692665[/C][C]0.0138533[/C][C]0.993073[/C][/ROW]
[ROW][C]44[/C][C]0.005239[/C][C]0.010478[/C][C]0.994761[/C][/ROW]
[ROW][C]45[/C][C]0.00503982[/C][C]0.0100796[/C][C]0.99496[/C][/ROW]
[ROW][C]46[/C][C]0.0065506[/C][C]0.0131012[/C][C]0.993449[/C][/ROW]
[ROW][C]47[/C][C]0.00451421[/C][C]0.00902841[/C][C]0.995486[/C][/ROW]
[ROW][C]48[/C][C]0.00316707[/C][C]0.00633415[/C][C]0.996833[/C][/ROW]
[ROW][C]49[/C][C]0.00256929[/C][C]0.00513858[/C][C]0.997431[/C][/ROW]
[ROW][C]50[/C][C]0.00220581[/C][C]0.00441163[/C][C]0.997794[/C][/ROW]
[ROW][C]51[/C][C]0.00165856[/C][C]0.00331713[/C][C]0.998341[/C][/ROW]
[ROW][C]52[/C][C]0.00167168[/C][C]0.00334336[/C][C]0.998328[/C][/ROW]
[ROW][C]53[/C][C]0.00119599[/C][C]0.00239198[/C][C]0.998804[/C][/ROW]
[ROW][C]54[/C][C]0.00294512[/C][C]0.00589025[/C][C]0.997055[/C][/ROW]
[ROW][C]55[/C][C]0.00215737[/C][C]0.00431473[/C][C]0.997843[/C][/ROW]
[ROW][C]56[/C][C]0.00206433[/C][C]0.00412866[/C][C]0.997936[/C][/ROW]
[ROW][C]57[/C][C]0.00187195[/C][C]0.00374391[/C][C]0.998128[/C][/ROW]
[ROW][C]58[/C][C]0.00146925[/C][C]0.0029385[/C][C]0.998531[/C][/ROW]
[ROW][C]59[/C][C]0.00254711[/C][C]0.00509423[/C][C]0.997453[/C][/ROW]
[ROW][C]60[/C][C]0.00255744[/C][C]0.00511488[/C][C]0.997443[/C][/ROW]
[ROW][C]61[/C][C]0.00306259[/C][C]0.00612519[/C][C]0.996937[/C][/ROW]
[ROW][C]62[/C][C]0.00341957[/C][C]0.00683914[/C][C]0.99658[/C][/ROW]
[ROW][C]63[/C][C]0.00291088[/C][C]0.00582175[/C][C]0.997089[/C][/ROW]
[ROW][C]64[/C][C]0.00251925[/C][C]0.00503851[/C][C]0.997481[/C][/ROW]
[ROW][C]65[/C][C]0.00283443[/C][C]0.00566886[/C][C]0.997166[/C][/ROW]
[ROW][C]66[/C][C]0.00488902[/C][C]0.00977804[/C][C]0.995111[/C][/ROW]
[ROW][C]67[/C][C]0.00438377[/C][C]0.00876755[/C][C]0.995616[/C][/ROW]
[ROW][C]68[/C][C]0.00397663[/C][C]0.00795326[/C][C]0.996023[/C][/ROW]
[ROW][C]69[/C][C]0.00296592[/C][C]0.00593185[/C][C]0.997034[/C][/ROW]
[ROW][C]70[/C][C]0.00272213[/C][C]0.00544426[/C][C]0.997278[/C][/ROW]
[ROW][C]71[/C][C]0.00303868[/C][C]0.00607735[/C][C]0.996961[/C][/ROW]
[ROW][C]72[/C][C]0.00239465[/C][C]0.00478929[/C][C]0.997605[/C][/ROW]
[ROW][C]73[/C][C]0.00174983[/C][C]0.00349967[/C][C]0.99825[/C][/ROW]
[ROW][C]74[/C][C]0.00130016[/C][C]0.00260033[/C][C]0.9987[/C][/ROW]
[ROW][C]75[/C][C]0.00127413[/C][C]0.00254826[/C][C]0.998726[/C][/ROW]
[ROW][C]76[/C][C]0.00141588[/C][C]0.00283175[/C][C]0.998584[/C][/ROW]
[ROW][C]77[/C][C]0.00172164[/C][C]0.00344328[/C][C]0.998278[/C][/ROW]
[ROW][C]78[/C][C]0.0013303[/C][C]0.00266059[/C][C]0.99867[/C][/ROW]
[ROW][C]79[/C][C]0.0013068[/C][C]0.00261359[/C][C]0.998693[/C][/ROW]
[ROW][C]80[/C][C]0.00100982[/C][C]0.00201963[/C][C]0.99899[/C][/ROW]
[ROW][C]81[/C][C]0.000929725[/C][C]0.00185945[/C][C]0.99907[/C][/ROW]
[ROW][C]82[/C][C]0.000735817[/C][C]0.00147163[/C][C]0.999264[/C][/ROW]
[ROW][C]83[/C][C]0.000850362[/C][C]0.00170072[/C][C]0.99915[/C][/ROW]
[ROW][C]84[/C][C]0.000637894[/C][C]0.00127579[/C][C]0.999362[/C][/ROW]
[ROW][C]85[/C][C]0.000563434[/C][C]0.00112687[/C][C]0.999437[/C][/ROW]
[ROW][C]86[/C][C]0.000450172[/C][C]0.000900343[/C][C]0.99955[/C][/ROW]
[ROW][C]87[/C][C]0.00234892[/C][C]0.00469783[/C][C]0.997651[/C][/ROW]
[ROW][C]88[/C][C]0.0019339[/C][C]0.00386779[/C][C]0.998066[/C][/ROW]
[ROW][C]89[/C][C]0.00151603[/C][C]0.00303206[/C][C]0.998484[/C][/ROW]
[ROW][C]90[/C][C]0.00116087[/C][C]0.00232173[/C][C]0.998839[/C][/ROW]
[ROW][C]91[/C][C]0.000948966[/C][C]0.00189793[/C][C]0.999051[/C][/ROW]
[ROW][C]92[/C][C]0.000994629[/C][C]0.00198926[/C][C]0.999005[/C][/ROW]
[ROW][C]93[/C][C]0.000909477[/C][C]0.00181895[/C][C]0.999091[/C][/ROW]
[ROW][C]94[/C][C]0.000724992[/C][C]0.00144998[/C][C]0.999275[/C][/ROW]
[ROW][C]95[/C][C]0.00207781[/C][C]0.00415561[/C][C]0.997922[/C][/ROW]
[ROW][C]96[/C][C]0.00180807[/C][C]0.00361613[/C][C]0.998192[/C][/ROW]
[ROW][C]97[/C][C]0.00174937[/C][C]0.00349875[/C][C]0.998251[/C][/ROW]
[ROW][C]98[/C][C]0.00208779[/C][C]0.00417558[/C][C]0.997912[/C][/ROW]
[ROW][C]99[/C][C]0.00198388[/C][C]0.00396775[/C][C]0.998016[/C][/ROW]
[ROW][C]100[/C][C]0.00291167[/C][C]0.00582335[/C][C]0.997088[/C][/ROW]
[ROW][C]101[/C][C]0.00234982[/C][C]0.00469963[/C][C]0.99765[/C][/ROW]
[ROW][C]102[/C][C]0.00238501[/C][C]0.00477002[/C][C]0.997615[/C][/ROW]
[ROW][C]103[/C][C]0.00275322[/C][C]0.00550644[/C][C]0.997247[/C][/ROW]
[ROW][C]104[/C][C]0.00226228[/C][C]0.00452456[/C][C]0.997738[/C][/ROW]
[ROW][C]105[/C][C]0.00191833[/C][C]0.00383665[/C][C]0.998082[/C][/ROW]
[ROW][C]106[/C][C]0.00225283[/C][C]0.00450567[/C][C]0.997747[/C][/ROW]
[ROW][C]107[/C][C]0.00204657[/C][C]0.00409315[/C][C]0.997953[/C][/ROW]
[ROW][C]108[/C][C]0.00229794[/C][C]0.00459588[/C][C]0.997702[/C][/ROW]
[ROW][C]109[/C][C]0.00262805[/C][C]0.0052561[/C][C]0.997372[/C][/ROW]
[ROW][C]110[/C][C]0.00234372[/C][C]0.00468745[/C][C]0.997656[/C][/ROW]
[ROW][C]111[/C][C]0.0078324[/C][C]0.0156648[/C][C]0.992168[/C][/ROW]
[ROW][C]112[/C][C]0.0144384[/C][C]0.0288769[/C][C]0.985562[/C][/ROW]
[ROW][C]113[/C][C]0.0152724[/C][C]0.0305449[/C][C]0.984728[/C][/ROW]
[ROW][C]114[/C][C]0.0136631[/C][C]0.0273262[/C][C]0.986337[/C][/ROW]
[ROW][C]115[/C][C]0.0118335[/C][C]0.023667[/C][C]0.988167[/C][/ROW]
[ROW][C]116[/C][C]0.0609708[/C][C]0.121942[/C][C]0.939029[/C][/ROW]
[ROW][C]117[/C][C]0.0694308[/C][C]0.138862[/C][C]0.930569[/C][/ROW]
[ROW][C]118[/C][C]0.13521[/C][C]0.27042[/C][C]0.86479[/C][/ROW]
[ROW][C]119[/C][C]0.22878[/C][C]0.45756[/C][C]0.77122[/C][/ROW]
[ROW][C]120[/C][C]0.27305[/C][C]0.5461[/C][C]0.72695[/C][/ROW]
[ROW][C]121[/C][C]0.252717[/C][C]0.505433[/C][C]0.747283[/C][/ROW]
[ROW][C]122[/C][C]0.313311[/C][C]0.626622[/C][C]0.686689[/C][/ROW]
[ROW][C]123[/C][C]0.438179[/C][C]0.876357[/C][C]0.561821[/C][/ROW]
[ROW][C]124[/C][C]0.470927[/C][C]0.941855[/C][C]0.529073[/C][/ROW]
[ROW][C]125[/C][C]0.458157[/C][C]0.916314[/C][C]0.541843[/C][/ROW]
[ROW][C]126[/C][C]0.544188[/C][C]0.911623[/C][C]0.455812[/C][/ROW]
[ROW][C]127[/C][C]0.545144[/C][C]0.909711[/C][C]0.454856[/C][/ROW]
[ROW][C]128[/C][C]0.537171[/C][C]0.925658[/C][C]0.462829[/C][/ROW]
[ROW][C]129[/C][C]0.513568[/C][C]0.972864[/C][C]0.486432[/C][/ROW]
[ROW][C]130[/C][C]0.553493[/C][C]0.893014[/C][C]0.446507[/C][/ROW]
[ROW][C]131[/C][C]0.530042[/C][C]0.939917[/C][C]0.469958[/C][/ROW]
[ROW][C]132[/C][C]0.635716[/C][C]0.728568[/C][C]0.364284[/C][/ROW]
[ROW][C]133[/C][C]0.622628[/C][C]0.754744[/C][C]0.377372[/C][/ROW]
[ROW][C]134[/C][C]0.610831[/C][C]0.778338[/C][C]0.389169[/C][/ROW]
[ROW][C]135[/C][C]0.62452[/C][C]0.750961[/C][C]0.37548[/C][/ROW]
[ROW][C]136[/C][C]0.610548[/C][C]0.778903[/C][C]0.389452[/C][/ROW]
[ROW][C]137[/C][C]0.607423[/C][C]0.785154[/C][C]0.392577[/C][/ROW]
[ROW][C]138[/C][C]0.583662[/C][C]0.832675[/C][C]0.416338[/C][/ROW]
[ROW][C]139[/C][C]0.557305[/C][C]0.885391[/C][C]0.442695[/C][/ROW]
[ROW][C]140[/C][C]0.608669[/C][C]0.782663[/C][C]0.391331[/C][/ROW]
[ROW][C]141[/C][C]0.651466[/C][C]0.697068[/C][C]0.348534[/C][/ROW]
[ROW][C]142[/C][C]0.735761[/C][C]0.528477[/C][C]0.264239[/C][/ROW]
[ROW][C]143[/C][C]0.721821[/C][C]0.556357[/C][C]0.278179[/C][/ROW]
[ROW][C]144[/C][C]0.704584[/C][C]0.590833[/C][C]0.295416[/C][/ROW]
[ROW][C]145[/C][C]0.746462[/C][C]0.507075[/C][C]0.253538[/C][/ROW]
[ROW][C]146[/C][C]0.739223[/C][C]0.521553[/C][C]0.260777[/C][/ROW]
[ROW][C]147[/C][C]0.778424[/C][C]0.443153[/C][C]0.221576[/C][/ROW]
[ROW][C]148[/C][C]0.762794[/C][C]0.474413[/C][C]0.237206[/C][/ROW]
[ROW][C]149[/C][C]0.765035[/C][C]0.46993[/C][C]0.234965[/C][/ROW]
[ROW][C]150[/C][C]0.776619[/C][C]0.446761[/C][C]0.223381[/C][/ROW]
[ROW][C]151[/C][C]0.756607[/C][C]0.486786[/C][C]0.243393[/C][/ROW]
[ROW][C]152[/C][C]0.741665[/C][C]0.51667[/C][C]0.258335[/C][/ROW]
[ROW][C]153[/C][C]0.718594[/C][C]0.562812[/C][C]0.281406[/C][/ROW]
[ROW][C]154[/C][C]0.701783[/C][C]0.596434[/C][C]0.298217[/C][/ROW]
[ROW][C]155[/C][C]0.736919[/C][C]0.526161[/C][C]0.263081[/C][/ROW]
[ROW][C]156[/C][C]0.744892[/C][C]0.510217[/C][C]0.255108[/C][/ROW]
[ROW][C]157[/C][C]0.731772[/C][C]0.536456[/C][C]0.268228[/C][/ROW]
[ROW][C]158[/C][C]0.764793[/C][C]0.470414[/C][C]0.235207[/C][/ROW]
[ROW][C]159[/C][C]0.780233[/C][C]0.439533[/C][C]0.219767[/C][/ROW]
[ROW][C]160[/C][C]0.760788[/C][C]0.478423[/C][C]0.239212[/C][/ROW]
[ROW][C]161[/C][C]0.736151[/C][C]0.527698[/C][C]0.263849[/C][/ROW]
[ROW][C]162[/C][C]0.773933[/C][C]0.452134[/C][C]0.226067[/C][/ROW]
[ROW][C]163[/C][C]0.764702[/C][C]0.470596[/C][C]0.235298[/C][/ROW]
[ROW][C]164[/C][C]0.74074[/C][C]0.518521[/C][C]0.25926[/C][/ROW]
[ROW][C]165[/C][C]0.722202[/C][C]0.555596[/C][C]0.277798[/C][/ROW]
[ROW][C]166[/C][C]0.763882[/C][C]0.472237[/C][C]0.236118[/C][/ROW]
[ROW][C]167[/C][C]0.759451[/C][C]0.481098[/C][C]0.240549[/C][/ROW]
[ROW][C]168[/C][C]0.766967[/C][C]0.466065[/C][C]0.233033[/C][/ROW]
[ROW][C]169[/C][C]0.75367[/C][C]0.492659[/C][C]0.24633[/C][/ROW]
[ROW][C]170[/C][C]0.792485[/C][C]0.41503[/C][C]0.207515[/C][/ROW]
[ROW][C]171[/C][C]0.780386[/C][C]0.439229[/C][C]0.219614[/C][/ROW]
[ROW][C]172[/C][C]0.828692[/C][C]0.342616[/C][C]0.171308[/C][/ROW]
[ROW][C]173[/C][C]0.810998[/C][C]0.378004[/C][C]0.189002[/C][/ROW]
[ROW][C]174[/C][C]0.789238[/C][C]0.421523[/C][C]0.210762[/C][/ROW]
[ROW][C]175[/C][C]0.777212[/C][C]0.445575[/C][C]0.222788[/C][/ROW]
[ROW][C]176[/C][C]0.768648[/C][C]0.462703[/C][C]0.231352[/C][/ROW]
[ROW][C]177[/C][C]0.79273[/C][C]0.414539[/C][C]0.20727[/C][/ROW]
[ROW][C]178[/C][C]0.773976[/C][C]0.452048[/C][C]0.226024[/C][/ROW]
[ROW][C]179[/C][C]0.750633[/C][C]0.498735[/C][C]0.249367[/C][/ROW]
[ROW][C]180[/C][C]0.728699[/C][C]0.542602[/C][C]0.271301[/C][/ROW]
[ROW][C]181[/C][C]0.762713[/C][C]0.474574[/C][C]0.237287[/C][/ROW]
[ROW][C]182[/C][C]0.735602[/C][C]0.528796[/C][C]0.264398[/C][/ROW]
[ROW][C]183[/C][C]0.814748[/C][C]0.370503[/C][C]0.185252[/C][/ROW]
[ROW][C]184[/C][C]0.800679[/C][C]0.398642[/C][C]0.199321[/C][/ROW]
[ROW][C]185[/C][C]0.846028[/C][C]0.307944[/C][C]0.153972[/C][/ROW]
[ROW][C]186[/C][C]0.823893[/C][C]0.352214[/C][C]0.176107[/C][/ROW]
[ROW][C]187[/C][C]0.799667[/C][C]0.400667[/C][C]0.200333[/C][/ROW]
[ROW][C]188[/C][C]0.846929[/C][C]0.306142[/C][C]0.153071[/C][/ROW]
[ROW][C]189[/C][C]0.836858[/C][C]0.326283[/C][C]0.163142[/C][/ROW]
[ROW][C]190[/C][C]0.816245[/C][C]0.36751[/C][C]0.183755[/C][/ROW]
[ROW][C]191[/C][C]0.80594[/C][C]0.38812[/C][C]0.19406[/C][/ROW]
[ROW][C]192[/C][C]0.818616[/C][C]0.362768[/C][C]0.181384[/C][/ROW]
[ROW][C]193[/C][C]0.793224[/C][C]0.413551[/C][C]0.206776[/C][/ROW]
[ROW][C]194[/C][C]0.769223[/C][C]0.461555[/C][C]0.230777[/C][/ROW]
[ROW][C]195[/C][C]0.741837[/C][C]0.516327[/C][C]0.258163[/C][/ROW]
[ROW][C]196[/C][C]0.737457[/C][C]0.525086[/C][C]0.262543[/C][/ROW]
[ROW][C]197[/C][C]0.724576[/C][C]0.550848[/C][C]0.275424[/C][/ROW]
[ROW][C]198[/C][C]0.746493[/C][C]0.507014[/C][C]0.253507[/C][/ROW]
[ROW][C]199[/C][C]0.774551[/C][C]0.450899[/C][C]0.225449[/C][/ROW]
[ROW][C]200[/C][C]0.74729[/C][C]0.50542[/C][C]0.25271[/C][/ROW]
[ROW][C]201[/C][C]0.71693[/C][C]0.56614[/C][C]0.28307[/C][/ROW]
[ROW][C]202[/C][C]0.693051[/C][C]0.613899[/C][C]0.306949[/C][/ROW]
[ROW][C]203[/C][C]0.662945[/C][C]0.67411[/C][C]0.337055[/C][/ROW]
[ROW][C]204[/C][C]0.633586[/C][C]0.732828[/C][C]0.366414[/C][/ROW]
[ROW][C]205[/C][C]0.61383[/C][C]0.772339[/C][C]0.38617[/C][/ROW]
[ROW][C]206[/C][C]0.68065[/C][C]0.6387[/C][C]0.31935[/C][/ROW]
[ROW][C]207[/C][C]0.645305[/C][C]0.70939[/C][C]0.354695[/C][/ROW]
[ROW][C]208[/C][C]0.610163[/C][C]0.779674[/C][C]0.389837[/C][/ROW]
[ROW][C]209[/C][C]0.598315[/C][C]0.803369[/C][C]0.401685[/C][/ROW]
[ROW][C]210[/C][C]0.566496[/C][C]0.867007[/C][C]0.433504[/C][/ROW]
[ROW][C]211[/C][C]0.540817[/C][C]0.918365[/C][C]0.459183[/C][/ROW]
[ROW][C]212[/C][C]0.584701[/C][C]0.830598[/C][C]0.415299[/C][/ROW]
[ROW][C]213[/C][C]0.555296[/C][C]0.889409[/C][C]0.444704[/C][/ROW]
[ROW][C]214[/C][C]0.535222[/C][C]0.929555[/C][C]0.464778[/C][/ROW]
[ROW][C]215[/C][C]0.589818[/C][C]0.820365[/C][C]0.410182[/C][/ROW]
[ROW][C]216[/C][C]0.582307[/C][C]0.835387[/C][C]0.417693[/C][/ROW]
[ROW][C]217[/C][C]0.56647[/C][C]0.867061[/C][C]0.43353[/C][/ROW]
[ROW][C]218[/C][C]0.533815[/C][C]0.932369[/C][C]0.466185[/C][/ROW]
[ROW][C]219[/C][C]0.507962[/C][C]0.984076[/C][C]0.492038[/C][/ROW]
[ROW][C]220[/C][C]0.470426[/C][C]0.940851[/C][C]0.529574[/C][/ROW]
[ROW][C]221[/C][C]0.454825[/C][C]0.90965[/C][C]0.545175[/C][/ROW]
[ROW][C]222[/C][C]0.415693[/C][C]0.831385[/C][C]0.584307[/C][/ROW]
[ROW][C]223[/C][C]0.40353[/C][C]0.80706[/C][C]0.59647[/C][/ROW]
[ROW][C]224[/C][C]0.363327[/C][C]0.726653[/C][C]0.636673[/C][/ROW]
[ROW][C]225[/C][C]0.390637[/C][C]0.781274[/C][C]0.609363[/C][/ROW]
[ROW][C]226[/C][C]0.365155[/C][C]0.730309[/C][C]0.634845[/C][/ROW]
[ROW][C]227[/C][C]0.345179[/C][C]0.690358[/C][C]0.654821[/C][/ROW]
[ROW][C]228[/C][C]0.369065[/C][C]0.738131[/C][C]0.630935[/C][/ROW]
[ROW][C]229[/C][C]0.447284[/C][C]0.894569[/C][C]0.552716[/C][/ROW]
[ROW][C]230[/C][C]0.406354[/C][C]0.812709[/C][C]0.593646[/C][/ROW]
[ROW][C]231[/C][C]0.381081[/C][C]0.762161[/C][C]0.618919[/C][/ROW]
[ROW][C]232[/C][C]0.49352[/C][C]0.987039[/C][C]0.50648[/C][/ROW]
[ROW][C]233[/C][C]0.463578[/C][C]0.927156[/C][C]0.536422[/C][/ROW]
[ROW][C]234[/C][C]0.445263[/C][C]0.890525[/C][C]0.554737[/C][/ROW]
[ROW][C]235[/C][C]0.415202[/C][C]0.830403[/C][C]0.584798[/C][/ROW]
[ROW][C]236[/C][C]0.467979[/C][C]0.935958[/C][C]0.532021[/C][/ROW]
[ROW][C]237[/C][C]0.558093[/C][C]0.883813[/C][C]0.441907[/C][/ROW]
[ROW][C]238[/C][C]0.653219[/C][C]0.693563[/C][C]0.346781[/C][/ROW]
[ROW][C]239[/C][C]0.701307[/C][C]0.597386[/C][C]0.298693[/C][/ROW]
[ROW][C]240[/C][C]0.659688[/C][C]0.680624[/C][C]0.340312[/C][/ROW]
[ROW][C]241[/C][C]0.61277[/C][C]0.774459[/C][C]0.38723[/C][/ROW]
[ROW][C]242[/C][C]0.618113[/C][C]0.763774[/C][C]0.381887[/C][/ROW]
[ROW][C]243[/C][C]0.866814[/C][C]0.266372[/C][C]0.133186[/C][/ROW]
[ROW][C]244[/C][C]0.847373[/C][C]0.305254[/C][C]0.152627[/C][/ROW]
[ROW][C]245[/C][C]0.813944[/C][C]0.372113[/C][C]0.186056[/C][/ROW]
[ROW][C]246[/C][C]0.82643[/C][C]0.347139[/C][C]0.17357[/C][/ROW]
[ROW][C]247[/C][C]0.810835[/C][C]0.37833[/C][C]0.189165[/C][/ROW]
[ROW][C]248[/C][C]0.772475[/C][C]0.455049[/C][C]0.227525[/C][/ROW]
[ROW][C]249[/C][C]0.736566[/C][C]0.526868[/C][C]0.263434[/C][/ROW]
[ROW][C]250[/C][C]0.703449[/C][C]0.593101[/C][C]0.296551[/C][/ROW]
[ROW][C]251[/C][C]0.763586[/C][C]0.472829[/C][C]0.236414[/C][/ROW]
[ROW][C]252[/C][C]0.804089[/C][C]0.391822[/C][C]0.195911[/C][/ROW]
[ROW][C]253[/C][C]0.783028[/C][C]0.433944[/C][C]0.216972[/C][/ROW]
[ROW][C]254[/C][C]0.741145[/C][C]0.517709[/C][C]0.258855[/C][/ROW]
[ROW][C]255[/C][C]0.742848[/C][C]0.514303[/C][C]0.257152[/C][/ROW]
[ROW][C]256[/C][C]0.690237[/C][C]0.619526[/C][C]0.309763[/C][/ROW]
[ROW][C]257[/C][C]0.658328[/C][C]0.683344[/C][C]0.341672[/C][/ROW]
[ROW][C]258[/C][C]0.597463[/C][C]0.805073[/C][C]0.402537[/C][/ROW]
[ROW][C]259[/C][C]0.544479[/C][C]0.911041[/C][C]0.455521[/C][/ROW]
[ROW][C]260[/C][C]0.482801[/C][C]0.965601[/C][C]0.517199[/C][/ROW]
[ROW][C]261[/C][C]0.420355[/C][C]0.84071[/C][C]0.579645[/C][/ROW]
[ROW][C]262[/C][C]0.61902[/C][C]0.761959[/C][C]0.38098[/C][/ROW]
[ROW][C]263[/C][C]0.652604[/C][C]0.694791[/C][C]0.347396[/C][/ROW]
[ROW][C]264[/C][C]0.642661[/C][C]0.714677[/C][C]0.357339[/C][/ROW]
[ROW][C]265[/C][C]0.635897[/C][C]0.728206[/C][C]0.364103[/C][/ROW]
[ROW][C]266[/C][C]0.898417[/C][C]0.203165[/C][C]0.101583[/C][/ROW]
[ROW][C]267[/C][C]0.866676[/C][C]0.266649[/C][C]0.133324[/C][/ROW]
[ROW][C]268[/C][C]0.936436[/C][C]0.127128[/C][C]0.0635639[/C][/ROW]
[ROW][C]269[/C][C]0.932615[/C][C]0.13477[/C][C]0.0673849[/C][/ROW]
[ROW][C]270[/C][C]0.910779[/C][C]0.178441[/C][C]0.0892205[/C][/ROW]
[ROW][C]271[/C][C]0.90739[/C][C]0.185221[/C][C]0.0926104[/C][/ROW]
[ROW][C]272[/C][C]0.847094[/C][C]0.305813[/C][C]0.152906[/C][/ROW]
[ROW][C]273[/C][C]0.807124[/C][C]0.385751[/C][C]0.192876[/C][/ROW]
[ROW][C]274[/C][C]0.971512[/C][C]0.0569769[/C][C]0.0284885[/C][/ROW]
[ROW][C]275[/C][C]0.938635[/C][C]0.122731[/C][C]0.0613655[/C][/ROW]
[ROW][C]276[/C][C]0.987367[/C][C]0.025266[/C][C]0.012633[/C][/ROW]
[ROW][C]277[/C][C]0.935022[/C][C]0.129956[/C][C]0.064978[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266484&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266484&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.3970440.7940890.602956
110.2919580.5839170.708042
120.1927330.3854650.807267
130.3973620.7947230.602638
140.2888670.5777340.711133
150.2032810.4065620.796719
160.220120.4402390.77988
170.151590.3031790.84841
180.103980.2079590.89602
190.07960810.1592160.920392
200.05771140.1154230.942289
210.04094560.08189110.959054
220.02776160.05552320.972238
230.01775870.03551740.982241
240.01061560.02123130.989384
250.009786740.01957350.990213
260.008146370.01629270.991854
270.005278540.01055710.994721
280.005110170.01022030.99489
290.003818480.007636950.996182
300.002273980.004547960.997726
310.001396920.002793840.998603
320.001140540.002281090.998859
330.0007112660.001422530.999289
340.0005318950.001063790.999468
350.0004502020.0009004040.99955
360.02024730.04049460.979753
370.01403430.02806860.985966
380.01117820.02235640.988822
390.007981020.0159620.992019
400.005452930.01090590.994547
410.004125740.008251470.995874
420.002687650.005375310.997312
430.006926650.01385330.993073
440.0052390.0104780.994761
450.005039820.01007960.99496
460.00655060.01310120.993449
470.004514210.009028410.995486
480.003167070.006334150.996833
490.002569290.005138580.997431
500.002205810.004411630.997794
510.001658560.003317130.998341
520.001671680.003343360.998328
530.001195990.002391980.998804
540.002945120.005890250.997055
550.002157370.004314730.997843
560.002064330.004128660.997936
570.001871950.003743910.998128
580.001469250.00293850.998531
590.002547110.005094230.997453
600.002557440.005114880.997443
610.003062590.006125190.996937
620.003419570.006839140.99658
630.002910880.005821750.997089
640.002519250.005038510.997481
650.002834430.005668860.997166
660.004889020.009778040.995111
670.004383770.008767550.995616
680.003976630.007953260.996023
690.002965920.005931850.997034
700.002722130.005444260.997278
710.003038680.006077350.996961
720.002394650.004789290.997605
730.001749830.003499670.99825
740.001300160.002600330.9987
750.001274130.002548260.998726
760.001415880.002831750.998584
770.001721640.003443280.998278
780.00133030.002660590.99867
790.00130680.002613590.998693
800.001009820.002019630.99899
810.0009297250.001859450.99907
820.0007358170.001471630.999264
830.0008503620.001700720.99915
840.0006378940.001275790.999362
850.0005634340.001126870.999437
860.0004501720.0009003430.99955
870.002348920.004697830.997651
880.00193390.003867790.998066
890.001516030.003032060.998484
900.001160870.002321730.998839
910.0009489660.001897930.999051
920.0009946290.001989260.999005
930.0009094770.001818950.999091
940.0007249920.001449980.999275
950.002077810.004155610.997922
960.001808070.003616130.998192
970.001749370.003498750.998251
980.002087790.004175580.997912
990.001983880.003967750.998016
1000.002911670.005823350.997088
1010.002349820.004699630.99765
1020.002385010.004770020.997615
1030.002753220.005506440.997247
1040.002262280.004524560.997738
1050.001918330.003836650.998082
1060.002252830.004505670.997747
1070.002046570.004093150.997953
1080.002297940.004595880.997702
1090.002628050.00525610.997372
1100.002343720.004687450.997656
1110.00783240.01566480.992168
1120.01443840.02887690.985562
1130.01527240.03054490.984728
1140.01366310.02732620.986337
1150.01183350.0236670.988167
1160.06097080.1219420.939029
1170.06943080.1388620.930569
1180.135210.270420.86479
1190.228780.457560.77122
1200.273050.54610.72695
1210.2527170.5054330.747283
1220.3133110.6266220.686689
1230.4381790.8763570.561821
1240.4709270.9418550.529073
1250.4581570.9163140.541843
1260.5441880.9116230.455812
1270.5451440.9097110.454856
1280.5371710.9256580.462829
1290.5135680.9728640.486432
1300.5534930.8930140.446507
1310.5300420.9399170.469958
1320.6357160.7285680.364284
1330.6226280.7547440.377372
1340.6108310.7783380.389169
1350.624520.7509610.37548
1360.6105480.7789030.389452
1370.6074230.7851540.392577
1380.5836620.8326750.416338
1390.5573050.8853910.442695
1400.6086690.7826630.391331
1410.6514660.6970680.348534
1420.7357610.5284770.264239
1430.7218210.5563570.278179
1440.7045840.5908330.295416
1450.7464620.5070750.253538
1460.7392230.5215530.260777
1470.7784240.4431530.221576
1480.7627940.4744130.237206
1490.7650350.469930.234965
1500.7766190.4467610.223381
1510.7566070.4867860.243393
1520.7416650.516670.258335
1530.7185940.5628120.281406
1540.7017830.5964340.298217
1550.7369190.5261610.263081
1560.7448920.5102170.255108
1570.7317720.5364560.268228
1580.7647930.4704140.235207
1590.7802330.4395330.219767
1600.7607880.4784230.239212
1610.7361510.5276980.263849
1620.7739330.4521340.226067
1630.7647020.4705960.235298
1640.740740.5185210.25926
1650.7222020.5555960.277798
1660.7638820.4722370.236118
1670.7594510.4810980.240549
1680.7669670.4660650.233033
1690.753670.4926590.24633
1700.7924850.415030.207515
1710.7803860.4392290.219614
1720.8286920.3426160.171308
1730.8109980.3780040.189002
1740.7892380.4215230.210762
1750.7772120.4455750.222788
1760.7686480.4627030.231352
1770.792730.4145390.20727
1780.7739760.4520480.226024
1790.7506330.4987350.249367
1800.7286990.5426020.271301
1810.7627130.4745740.237287
1820.7356020.5287960.264398
1830.8147480.3705030.185252
1840.8006790.3986420.199321
1850.8460280.3079440.153972
1860.8238930.3522140.176107
1870.7996670.4006670.200333
1880.8469290.3061420.153071
1890.8368580.3262830.163142
1900.8162450.367510.183755
1910.805940.388120.19406
1920.8186160.3627680.181384
1930.7932240.4135510.206776
1940.7692230.4615550.230777
1950.7418370.5163270.258163
1960.7374570.5250860.262543
1970.7245760.5508480.275424
1980.7464930.5070140.253507
1990.7745510.4508990.225449
2000.747290.505420.25271
2010.716930.566140.28307
2020.6930510.6138990.306949
2030.6629450.674110.337055
2040.6335860.7328280.366414
2050.613830.7723390.38617
2060.680650.63870.31935
2070.6453050.709390.354695
2080.6101630.7796740.389837
2090.5983150.8033690.401685
2100.5664960.8670070.433504
2110.5408170.9183650.459183
2120.5847010.8305980.415299
2130.5552960.8894090.444704
2140.5352220.9295550.464778
2150.5898180.8203650.410182
2160.5823070.8353870.417693
2170.566470.8670610.43353
2180.5338150.9323690.466185
2190.5079620.9840760.492038
2200.4704260.9408510.529574
2210.4548250.909650.545175
2220.4156930.8313850.584307
2230.403530.807060.59647
2240.3633270.7266530.636673
2250.3906370.7812740.609363
2260.3651550.7303090.634845
2270.3451790.6903580.654821
2280.3690650.7381310.630935
2290.4472840.8945690.552716
2300.4063540.8127090.593646
2310.3810810.7621610.618919
2320.493520.9870390.50648
2330.4635780.9271560.536422
2340.4452630.8905250.554737
2350.4152020.8304030.584798
2360.4679790.9359580.532021
2370.5580930.8838130.441907
2380.6532190.6935630.346781
2390.7013070.5973860.298693
2400.6596880.6806240.340312
2410.612770.7744590.38723
2420.6181130.7637740.381887
2430.8668140.2663720.133186
2440.8473730.3052540.152627
2450.8139440.3721130.186056
2460.826430.3471390.17357
2470.8108350.378330.189165
2480.7724750.4550490.227525
2490.7365660.5268680.263434
2500.7034490.5931010.296551
2510.7635860.4728290.236414
2520.8040890.3918220.195911
2530.7830280.4339440.216972
2540.7411450.5177090.258855
2550.7428480.5143030.257152
2560.6902370.6195260.309763
2570.6583280.6833440.341672
2580.5974630.8050730.402537
2590.5444790.9110410.455521
2600.4828010.9656010.517199
2610.4203550.840710.579645
2620.619020.7619590.38098
2630.6526040.6947910.347396
2640.6426610.7146770.357339
2650.6358970.7282060.364103
2660.8984170.2031650.101583
2670.8666760.2666490.133324
2680.9364360.1271280.0635639
2690.9326150.134770.0673849
2700.9107790.1784410.0892205
2710.907390.1852210.0926104
2720.8470940.3058130.152906
2730.8071240.3857510.192876
2740.9715120.05697690.0284885
2750.9386350.1227310.0613655
2760.9873670.0252660.012633
2770.9350220.1299560.064978






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level730.272388NOK
5% type I error level940.350746NOK
10% type I error level970.36194NOK

\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 & 73 & 0.272388 & NOK \tabularnewline
5% type I error level & 94 & 0.350746 & NOK \tabularnewline
10% type I error level & 97 & 0.36194 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266484&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]73[/C][C]0.272388[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]94[/C][C]0.350746[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]97[/C][C]0.36194[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266484&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266484&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level730.272388NOK
5% type I error level940.350746NOK
10% type I error level970.36194NOK


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 5
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 6
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 7
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 8
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 9
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 10
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Input Parameters & R Code

Parameters (Session):
par1 = 7 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 7 ; 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')
}