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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 09 Dec 2014 10:48:28 +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/09/t1418123061jq00jmbxb8ngf4u.htm/, Retrieved Thu, 16 May 2024 16:40:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264451, Retrieved Thu, 16 May 2024 16:40:10 +0000
QR Codes:

Original text written by user:Motivaties en totaal
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact82

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Multiple Regression] [2014-12-09 10:48:28] [9636d26fd774798d33054b538c301d75] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264451&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264451&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264451&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 time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
AMS.I1[t] = + 7.75741 + 0.293172AMS.I2[t] + 0.315338AMS.I3[t] + 0.244157AMS.E1[t] -0.0479193AMS.E2[t] -0.0518305AMS.E3[t] -0.253685AMS.A[t] + 0.0283242TOT[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
AMS.I1[t] =  +  7.75741 +  0.293172AMS.I2[t] +  0.315338AMS.I3[t] +  0.244157AMS.E1[t] -0.0479193AMS.E2[t] -0.0518305AMS.E3[t] -0.253685AMS.A[t] +  0.0283242TOT[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264451&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]AMS.I1[t] =  +  7.75741 +  0.293172AMS.I2[t] +  0.315338AMS.I3[t] +  0.244157AMS.E1[t] -0.0479193AMS.E2[t] -0.0518305AMS.E3[t] -0.253685AMS.A[t] +  0.0283242TOT[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264451&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264451&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
AMS.I1[t] = + 7.75741 + 0.293172AMS.I2[t] + 0.315338AMS.I3[t] + 0.244157AMS.E1[t] -0.0479193AMS.E2[t] -0.0518305AMS.E3[t] -0.253685AMS.A[t] + 0.0283242TOT[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)7.757411.763244.41.56305e-057.81527e-06
AMS.I20.2931720.04898995.9846.88639e-093.44319e-09
AMS.I30.3153380.04083987.7212.25263e-131.12631e-13
AMS.E10.2441570.06051854.0347.13124e-053.56562e-05
AMS.E2-0.04791930.0424937-1.1280.2604560.130228
AMS.E3-0.05183050.0514206-1.0080.314370.157185
AMS.A-0.2536850.0488869-5.1894.15455e-072.07728e-07
TOT0.02832420.04385830.64580.518950.259475

\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) & 7.75741 & 1.76324 & 4.4 & 1.56305e-05 & 7.81527e-06 \tabularnewline
AMS.I2 & 0.293172 & 0.0489899 & 5.984 & 6.88639e-09 & 3.44319e-09 \tabularnewline
AMS.I3 & 0.315338 & 0.0408398 & 7.721 & 2.25263e-13 & 1.12631e-13 \tabularnewline
AMS.E1 & 0.244157 & 0.0605185 & 4.034 & 7.13124e-05 & 3.56562e-05 \tabularnewline
AMS.E2 & -0.0479193 & 0.0424937 & -1.128 & 0.260456 & 0.130228 \tabularnewline
AMS.E3 & -0.0518305 & 0.0514206 & -1.008 & 0.31437 & 0.157185 \tabularnewline
AMS.A & -0.253685 & 0.0488869 & -5.189 & 4.15455e-07 & 2.07728e-07 \tabularnewline
TOT & 0.0283242 & 0.0438583 & 0.6458 & 0.51895 & 0.259475 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264451&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]7.75741[/C][C]1.76324[/C][C]4.4[/C][C]1.56305e-05[/C][C]7.81527e-06[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.293172[/C][C]0.0489899[/C][C]5.984[/C][C]6.88639e-09[/C][C]3.44319e-09[/C][/ROW]
[ROW][C]AMS.I3[/C][C]0.315338[/C][C]0.0408398[/C][C]7.721[/C][C]2.25263e-13[/C][C]1.12631e-13[/C][/ROW]
[ROW][C]AMS.E1[/C][C]0.244157[/C][C]0.0605185[/C][C]4.034[/C][C]7.13124e-05[/C][C]3.56562e-05[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0479193[/C][C]0.0424937[/C][C]-1.128[/C][C]0.260456[/C][C]0.130228[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0518305[/C][C]0.0514206[/C][C]-1.008[/C][C]0.31437[/C][C]0.157185[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.253685[/C][C]0.0488869[/C][C]-5.189[/C][C]4.15455e-07[/C][C]2.07728e-07[/C][/ROW]
[ROW][C]TOT[/C][C]0.0283242[/C][C]0.0438583[/C][C]0.6458[/C][C]0.51895[/C][C]0.259475[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264451&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264451&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)7.757411.763244.41.56305e-057.81527e-06
AMS.I20.2931720.04898995.9846.88639e-093.44319e-09
AMS.I30.3153380.04083987.7212.25263e-131.12631e-13
AMS.E10.2441570.06051854.0347.13124e-053.56562e-05
AMS.E2-0.04791930.0424937-1.1280.2604560.130228
AMS.E3-0.05183050.0514206-1.0080.314370.157185
AMS.A-0.2536850.0488869-5.1894.15455e-072.07728e-07
TOT0.02832420.04385830.64580.518950.259475






Multiple Linear Regression - Regression Statistics
Multiple R0.759361
R-squared0.57663
Adjusted R-squared0.565654
F-TEST (value)52.5343
F-TEST (DF numerator)7
F-TEST (DF denominator)270
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.44819
Sum Squared Residuals1618.29

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.759361 \tabularnewline
R-squared & 0.57663 \tabularnewline
Adjusted R-squared & 0.565654 \tabularnewline
F-TEST (value) & 52.5343 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 270 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.44819 \tabularnewline
Sum Squared Residuals & 1618.29 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264451&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.759361[/C][/ROW]
[ROW][C]R-squared[/C][C]0.57663[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.565654[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]52.5343[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]270[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.44819[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1618.29[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264451&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264451&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 R0.759361
R-squared0.57663
Adjusted R-squared0.565654
F-TEST (value)52.5343
F-TEST (DF numerator)7
F-TEST (DF denominator)270
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.44819
Sum Squared Residuals1618.29






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11114.444-3.44397
21922.3445-3.3445
31616.9753-0.975261
42422.90931.09067
51518.2908-3.29082
61720.5557-3.55571
71920.7848-1.78476
81914.67854.32152
92828.1387-0.138717
102623.52022.47984
111520.0576-5.05764
122624.13191.8681
131620.1257-4.12568
142421.32232.6777
152524.41680.58321
162220.92291.07711
171518.1356-3.13559
182121.7675-0.767502
192219.95812.04192
202724.95022.04976
212623.06442.93561
222620.66825.33176
232221.23170.768253
242121.5225-0.522485
252221.30970.690316
262019.73610.263891
272121.3886-0.388561
282017.81682.1832
292222.6309-0.630905
302120.57020.42979
31815.7758-7.77583
322217.89444.10555
332022.1402-2.1402
342416.49777.50233
351719.5375-2.53751
362020.9923-0.992313
372319.6653.33501
382019.16540.834566
392221.67580.324174
401918.78140.218552
411517.1548-2.1548
422018.74241.25758
432220.10111.8989
441716.10960.890427
451415.277-1.27701
462423.8710.128958
471718.0114-1.01142
482323.2838-0.283767
492523.42121.57883
501619.1154-3.11543
511822.1805-4.18049
522018.05571.94428
531818.6653-0.665317
542325.0105-2.0105
552421.36942.63063
562319.39643.60361
571317.8395-4.83947
582018.32171.67832
592018.46291.53711
601919.4636-0.463626
612220.87281.12716
622221.58120.418807
631515.6178-0.617782
641717.6237-0.623679
651919.0164-0.0164442
662016.65053.34952
672223.7275-1.72751
682122.3331-1.33314
692119.09581.90421
701617.2569-1.25693
712019.08570.914285
722120.0840.915955
732019.56280.437229
742324.2219-1.22192
751816.82731.1727
761618.1875-2.18748
771715.8121.18795
782423.56120.43884
791317.3144-4.31435
801920.497-1.49704
812019.30970.690332
822220.83151.16853
831920.0881-1.08814
842122.0609-1.06094
851514.75670.243319
862121.1088-0.108788
872422.35831.64168
882222.8949-0.894937
892020.5072-0.507225
902121.0957-0.0957111
911919.4684-0.468418
921413.79910.200853
932524.44830.551685
941113.3593-2.35931
951719.5441-2.54411
962224.1956-2.19556
972020.407-0.406999
982220.0521.94801
991519.7323-4.73234
1002322.76580.234188
1012021.9672-1.96716
1022224.5419-2.54194
1031613.68222.31776
1042522.27582.72416
1051819.5833-1.58326
1061919.2088-0.208817
1072518.2396.76095
1082119.32151.67846
1092221.71530.284695
1102121.5243-0.524349
1112223.1037-1.10369
1122322.10990.890064
1132019.99560.00438933
114614.3435-8.34351
1151517.7773-2.7773
1161822.4396-4.43959
1172420.4723.528
1182216.35665.64338
1192120.28320.716802
1202323.2735-0.273483
1212021.7127-1.71265
1222019.14950.850479
1231817.63630.363677
1242524.0620.938034
1251621.8009-5.80086
1262021.6888-1.68878
1271416.3623-2.36232
1282220.96511.03488
1292625.92310.0769022
1302018.24241.75764
1311717.7126-0.712599
1322222.2541-0.254053
1332219.90682.09317
1342023.4628-3.46284
1351714.1662.83401
1362224.5434-2.54342
1371719.119-2.11904
1382219.8112.18898
1392121.1773-0.177262
1402520.63524.36484
1411110.23830.761724
1421919.1632-0.163172
1432423.80960.190354
1441720.462-3.46199
1452220.22361.77637
1461717.222-0.222041
1472624.61521.38477
1482019.07840.921576
1491918.93320.0668349
1502119.33131.66869
1512421.59672.4033
1522121.2818-0.281778
1531921.07-2.06997
1541315.5782-2.57823
1552424.7665-0.766514
1562822.54735.45269
1572724.72752.27255
1582219.18692.81311
1592322.96290.0370759
1601916.30862.69137
1611819.1193-1.11928
1622322.02060.979384
1632118.08722.91276
1642221.37280.627159
1651718.8378-1.8378
1661517.6042-2.60417
1672118.66032.33967
1682019.95750.0425266
1692623.31622.68375
1701921.1403-2.14034
1712826.28941.71056
1722118.77322.22677
1731921.4682-2.46818
1742220.2961.70404
1752119.94571.05435
1762020.0992-0.0991507
1771917.40611.59392
1781114.0239-3.02389
1791719.8657-2.86571
1801917.80661.19337
1812019.06330.936702
1821716.78980.210242
1832118.12722.87278
1842121.5568-0.556828
1851214.0562-2.05617
1862319.99343.00663
1872220.98821.01178
1882221.76740.232612
1892121.9879-0.987872
1902020.8709-0.870922
1911818.0395-0.0395315
1922124.0054-3.00543
1932422.12551.87455
1942222.1607-0.160682
1952017.21082.78917
1961717.0487-0.0486614
1971918.79180.208222
1981619.2679-3.26786
1991920.3609-1.36093
2002325.0197-2.01971
201813.6394-5.63944
2022222.69-0.689955
2032321.38661.61336
2041519.153-4.15303
2051721.4334-4.43343
2062117.8143.18601
2072520.45054.54945
2081813.44884.55116
2092018.59171.4083
2102119.38971.61028
2112120.29080.709202
2122420.03493.96505
2132221.99310.0069268
2142221.08170.918307
2152320.7972.20298
2161718.2316-1.2316
2171515.7007-0.70066
2182222.0282-0.0281844
2191916.93462.06538
2201820.0672-2.06721
2212122.8083-1.80833
2222022.0938-2.09382
2231919.757-0.757016
2241918.07880.921154
2251620.6671-4.66715
2261815.65362.34636
2272322.64050.359495
2282222.8885-0.888531
2292322.72850.271471
2302020.0921-0.0921449
2312422.57541.42462
2322518.31226.6878
2332523.80281.1972
2342020.162-0.161951
2352319.71023.28976
2362121.0074-0.00738835
2372320.03232.9677
2382320.49522.50477
2391116.5011-5.50106
2402124.159-3.15899
2412723.45643.54356
2421920.4854-1.48544
2432121.3607-0.360667
2441616.9381-0.938098
2452118.2032.797
2462221.51860.481379
2471620.2554-4.2554
2481815.67572.32432
2492323.6384-0.638426
2502421.71832.28168
2512020.8292-0.829241
2522019.11850.881523
2531819.4967-1.49667
254410.207-6.20696
2551414.8686-0.868596
2562221.61320.386768
2571722.4819-5.48186
2582323.0858-0.0858081
2592019.24150.75854
2601817.43330.56675
2611917.14431.85571
2622021.369-1.36904
2631516.0383-1.03831
2642420.49533.50469
2652120.50180.498159
2661919.8851-0.885102
2671916.2432.75698
2682726.42020.579782
2692323.0805-0.0805085
2702322.18560.814404
2712023.5627-3.5627
2721719.6748-2.67478
2732120.82690.173149
2742321.48231.51766
2752221.64160.358411
2761618.505-2.50505
2772021.5254-1.52545
2781614.43631.56371

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 11 & 14.444 & -3.44397 \tabularnewline
2 & 19 & 22.3445 & -3.3445 \tabularnewline
3 & 16 & 16.9753 & -0.975261 \tabularnewline
4 & 24 & 22.9093 & 1.09067 \tabularnewline
5 & 15 & 18.2908 & -3.29082 \tabularnewline
6 & 17 & 20.5557 & -3.55571 \tabularnewline
7 & 19 & 20.7848 & -1.78476 \tabularnewline
8 & 19 & 14.6785 & 4.32152 \tabularnewline
9 & 28 & 28.1387 & -0.138717 \tabularnewline
10 & 26 & 23.5202 & 2.47984 \tabularnewline
11 & 15 & 20.0576 & -5.05764 \tabularnewline
12 & 26 & 24.1319 & 1.8681 \tabularnewline
13 & 16 & 20.1257 & -4.12568 \tabularnewline
14 & 24 & 21.3223 & 2.6777 \tabularnewline
15 & 25 & 24.4168 & 0.58321 \tabularnewline
16 & 22 & 20.9229 & 1.07711 \tabularnewline
17 & 15 & 18.1356 & -3.13559 \tabularnewline
18 & 21 & 21.7675 & -0.767502 \tabularnewline
19 & 22 & 19.9581 & 2.04192 \tabularnewline
20 & 27 & 24.9502 & 2.04976 \tabularnewline
21 & 26 & 23.0644 & 2.93561 \tabularnewline
22 & 26 & 20.6682 & 5.33176 \tabularnewline
23 & 22 & 21.2317 & 0.768253 \tabularnewline
24 & 21 & 21.5225 & -0.522485 \tabularnewline
25 & 22 & 21.3097 & 0.690316 \tabularnewline
26 & 20 & 19.7361 & 0.263891 \tabularnewline
27 & 21 & 21.3886 & -0.388561 \tabularnewline
28 & 20 & 17.8168 & 2.1832 \tabularnewline
29 & 22 & 22.6309 & -0.630905 \tabularnewline
30 & 21 & 20.5702 & 0.42979 \tabularnewline
31 & 8 & 15.7758 & -7.77583 \tabularnewline
32 & 22 & 17.8944 & 4.10555 \tabularnewline
33 & 20 & 22.1402 & -2.1402 \tabularnewline
34 & 24 & 16.4977 & 7.50233 \tabularnewline
35 & 17 & 19.5375 & -2.53751 \tabularnewline
36 & 20 & 20.9923 & -0.992313 \tabularnewline
37 & 23 & 19.665 & 3.33501 \tabularnewline
38 & 20 & 19.1654 & 0.834566 \tabularnewline
39 & 22 & 21.6758 & 0.324174 \tabularnewline
40 & 19 & 18.7814 & 0.218552 \tabularnewline
41 & 15 & 17.1548 & -2.1548 \tabularnewline
42 & 20 & 18.7424 & 1.25758 \tabularnewline
43 & 22 & 20.1011 & 1.8989 \tabularnewline
44 & 17 & 16.1096 & 0.890427 \tabularnewline
45 & 14 & 15.277 & -1.27701 \tabularnewline
46 & 24 & 23.871 & 0.128958 \tabularnewline
47 & 17 & 18.0114 & -1.01142 \tabularnewline
48 & 23 & 23.2838 & -0.283767 \tabularnewline
49 & 25 & 23.4212 & 1.57883 \tabularnewline
50 & 16 & 19.1154 & -3.11543 \tabularnewline
51 & 18 & 22.1805 & -4.18049 \tabularnewline
52 & 20 & 18.0557 & 1.94428 \tabularnewline
53 & 18 & 18.6653 & -0.665317 \tabularnewline
54 & 23 & 25.0105 & -2.0105 \tabularnewline
55 & 24 & 21.3694 & 2.63063 \tabularnewline
56 & 23 & 19.3964 & 3.60361 \tabularnewline
57 & 13 & 17.8395 & -4.83947 \tabularnewline
58 & 20 & 18.3217 & 1.67832 \tabularnewline
59 & 20 & 18.4629 & 1.53711 \tabularnewline
60 & 19 & 19.4636 & -0.463626 \tabularnewline
61 & 22 & 20.8728 & 1.12716 \tabularnewline
62 & 22 & 21.5812 & 0.418807 \tabularnewline
63 & 15 & 15.6178 & -0.617782 \tabularnewline
64 & 17 & 17.6237 & -0.623679 \tabularnewline
65 & 19 & 19.0164 & -0.0164442 \tabularnewline
66 & 20 & 16.6505 & 3.34952 \tabularnewline
67 & 22 & 23.7275 & -1.72751 \tabularnewline
68 & 21 & 22.3331 & -1.33314 \tabularnewline
69 & 21 & 19.0958 & 1.90421 \tabularnewline
70 & 16 & 17.2569 & -1.25693 \tabularnewline
71 & 20 & 19.0857 & 0.914285 \tabularnewline
72 & 21 & 20.084 & 0.915955 \tabularnewline
73 & 20 & 19.5628 & 0.437229 \tabularnewline
74 & 23 & 24.2219 & -1.22192 \tabularnewline
75 & 18 & 16.8273 & 1.1727 \tabularnewline
76 & 16 & 18.1875 & -2.18748 \tabularnewline
77 & 17 & 15.812 & 1.18795 \tabularnewline
78 & 24 & 23.5612 & 0.43884 \tabularnewline
79 & 13 & 17.3144 & -4.31435 \tabularnewline
80 & 19 & 20.497 & -1.49704 \tabularnewline
81 & 20 & 19.3097 & 0.690332 \tabularnewline
82 & 22 & 20.8315 & 1.16853 \tabularnewline
83 & 19 & 20.0881 & -1.08814 \tabularnewline
84 & 21 & 22.0609 & -1.06094 \tabularnewline
85 & 15 & 14.7567 & 0.243319 \tabularnewline
86 & 21 & 21.1088 & -0.108788 \tabularnewline
87 & 24 & 22.3583 & 1.64168 \tabularnewline
88 & 22 & 22.8949 & -0.894937 \tabularnewline
89 & 20 & 20.5072 & -0.507225 \tabularnewline
90 & 21 & 21.0957 & -0.0957111 \tabularnewline
91 & 19 & 19.4684 & -0.468418 \tabularnewline
92 & 14 & 13.7991 & 0.200853 \tabularnewline
93 & 25 & 24.4483 & 0.551685 \tabularnewline
94 & 11 & 13.3593 & -2.35931 \tabularnewline
95 & 17 & 19.5441 & -2.54411 \tabularnewline
96 & 22 & 24.1956 & -2.19556 \tabularnewline
97 & 20 & 20.407 & -0.406999 \tabularnewline
98 & 22 & 20.052 & 1.94801 \tabularnewline
99 & 15 & 19.7323 & -4.73234 \tabularnewline
100 & 23 & 22.7658 & 0.234188 \tabularnewline
101 & 20 & 21.9672 & -1.96716 \tabularnewline
102 & 22 & 24.5419 & -2.54194 \tabularnewline
103 & 16 & 13.6822 & 2.31776 \tabularnewline
104 & 25 & 22.2758 & 2.72416 \tabularnewline
105 & 18 & 19.5833 & -1.58326 \tabularnewline
106 & 19 & 19.2088 & -0.208817 \tabularnewline
107 & 25 & 18.239 & 6.76095 \tabularnewline
108 & 21 & 19.3215 & 1.67846 \tabularnewline
109 & 22 & 21.7153 & 0.284695 \tabularnewline
110 & 21 & 21.5243 & -0.524349 \tabularnewline
111 & 22 & 23.1037 & -1.10369 \tabularnewline
112 & 23 & 22.1099 & 0.890064 \tabularnewline
113 & 20 & 19.9956 & 0.00438933 \tabularnewline
114 & 6 & 14.3435 & -8.34351 \tabularnewline
115 & 15 & 17.7773 & -2.7773 \tabularnewline
116 & 18 & 22.4396 & -4.43959 \tabularnewline
117 & 24 & 20.472 & 3.528 \tabularnewline
118 & 22 & 16.3566 & 5.64338 \tabularnewline
119 & 21 & 20.2832 & 0.716802 \tabularnewline
120 & 23 & 23.2735 & -0.273483 \tabularnewline
121 & 20 & 21.7127 & -1.71265 \tabularnewline
122 & 20 & 19.1495 & 0.850479 \tabularnewline
123 & 18 & 17.6363 & 0.363677 \tabularnewline
124 & 25 & 24.062 & 0.938034 \tabularnewline
125 & 16 & 21.8009 & -5.80086 \tabularnewline
126 & 20 & 21.6888 & -1.68878 \tabularnewline
127 & 14 & 16.3623 & -2.36232 \tabularnewline
128 & 22 & 20.9651 & 1.03488 \tabularnewline
129 & 26 & 25.9231 & 0.0769022 \tabularnewline
130 & 20 & 18.2424 & 1.75764 \tabularnewline
131 & 17 & 17.7126 & -0.712599 \tabularnewline
132 & 22 & 22.2541 & -0.254053 \tabularnewline
133 & 22 & 19.9068 & 2.09317 \tabularnewline
134 & 20 & 23.4628 & -3.46284 \tabularnewline
135 & 17 & 14.166 & 2.83401 \tabularnewline
136 & 22 & 24.5434 & -2.54342 \tabularnewline
137 & 17 & 19.119 & -2.11904 \tabularnewline
138 & 22 & 19.811 & 2.18898 \tabularnewline
139 & 21 & 21.1773 & -0.177262 \tabularnewline
140 & 25 & 20.6352 & 4.36484 \tabularnewline
141 & 11 & 10.2383 & 0.761724 \tabularnewline
142 & 19 & 19.1632 & -0.163172 \tabularnewline
143 & 24 & 23.8096 & 0.190354 \tabularnewline
144 & 17 & 20.462 & -3.46199 \tabularnewline
145 & 22 & 20.2236 & 1.77637 \tabularnewline
146 & 17 & 17.222 & -0.222041 \tabularnewline
147 & 26 & 24.6152 & 1.38477 \tabularnewline
148 & 20 & 19.0784 & 0.921576 \tabularnewline
149 & 19 & 18.9332 & 0.0668349 \tabularnewline
150 & 21 & 19.3313 & 1.66869 \tabularnewline
151 & 24 & 21.5967 & 2.4033 \tabularnewline
152 & 21 & 21.2818 & -0.281778 \tabularnewline
153 & 19 & 21.07 & -2.06997 \tabularnewline
154 & 13 & 15.5782 & -2.57823 \tabularnewline
155 & 24 & 24.7665 & -0.766514 \tabularnewline
156 & 28 & 22.5473 & 5.45269 \tabularnewline
157 & 27 & 24.7275 & 2.27255 \tabularnewline
158 & 22 & 19.1869 & 2.81311 \tabularnewline
159 & 23 & 22.9629 & 0.0370759 \tabularnewline
160 & 19 & 16.3086 & 2.69137 \tabularnewline
161 & 18 & 19.1193 & -1.11928 \tabularnewline
162 & 23 & 22.0206 & 0.979384 \tabularnewline
163 & 21 & 18.0872 & 2.91276 \tabularnewline
164 & 22 & 21.3728 & 0.627159 \tabularnewline
165 & 17 & 18.8378 & -1.8378 \tabularnewline
166 & 15 & 17.6042 & -2.60417 \tabularnewline
167 & 21 & 18.6603 & 2.33967 \tabularnewline
168 & 20 & 19.9575 & 0.0425266 \tabularnewline
169 & 26 & 23.3162 & 2.68375 \tabularnewline
170 & 19 & 21.1403 & -2.14034 \tabularnewline
171 & 28 & 26.2894 & 1.71056 \tabularnewline
172 & 21 & 18.7732 & 2.22677 \tabularnewline
173 & 19 & 21.4682 & -2.46818 \tabularnewline
174 & 22 & 20.296 & 1.70404 \tabularnewline
175 & 21 & 19.9457 & 1.05435 \tabularnewline
176 & 20 & 20.0992 & -0.0991507 \tabularnewline
177 & 19 & 17.4061 & 1.59392 \tabularnewline
178 & 11 & 14.0239 & -3.02389 \tabularnewline
179 & 17 & 19.8657 & -2.86571 \tabularnewline
180 & 19 & 17.8066 & 1.19337 \tabularnewline
181 & 20 & 19.0633 & 0.936702 \tabularnewline
182 & 17 & 16.7898 & 0.210242 \tabularnewline
183 & 21 & 18.1272 & 2.87278 \tabularnewline
184 & 21 & 21.5568 & -0.556828 \tabularnewline
185 & 12 & 14.0562 & -2.05617 \tabularnewline
186 & 23 & 19.9934 & 3.00663 \tabularnewline
187 & 22 & 20.9882 & 1.01178 \tabularnewline
188 & 22 & 21.7674 & 0.232612 \tabularnewline
189 & 21 & 21.9879 & -0.987872 \tabularnewline
190 & 20 & 20.8709 & -0.870922 \tabularnewline
191 & 18 & 18.0395 & -0.0395315 \tabularnewline
192 & 21 & 24.0054 & -3.00543 \tabularnewline
193 & 24 & 22.1255 & 1.87455 \tabularnewline
194 & 22 & 22.1607 & -0.160682 \tabularnewline
195 & 20 & 17.2108 & 2.78917 \tabularnewline
196 & 17 & 17.0487 & -0.0486614 \tabularnewline
197 & 19 & 18.7918 & 0.208222 \tabularnewline
198 & 16 & 19.2679 & -3.26786 \tabularnewline
199 & 19 & 20.3609 & -1.36093 \tabularnewline
200 & 23 & 25.0197 & -2.01971 \tabularnewline
201 & 8 & 13.6394 & -5.63944 \tabularnewline
202 & 22 & 22.69 & -0.689955 \tabularnewline
203 & 23 & 21.3866 & 1.61336 \tabularnewline
204 & 15 & 19.153 & -4.15303 \tabularnewline
205 & 17 & 21.4334 & -4.43343 \tabularnewline
206 & 21 & 17.814 & 3.18601 \tabularnewline
207 & 25 & 20.4505 & 4.54945 \tabularnewline
208 & 18 & 13.4488 & 4.55116 \tabularnewline
209 & 20 & 18.5917 & 1.4083 \tabularnewline
210 & 21 & 19.3897 & 1.61028 \tabularnewline
211 & 21 & 20.2908 & 0.709202 \tabularnewline
212 & 24 & 20.0349 & 3.96505 \tabularnewline
213 & 22 & 21.9931 & 0.0069268 \tabularnewline
214 & 22 & 21.0817 & 0.918307 \tabularnewline
215 & 23 & 20.797 & 2.20298 \tabularnewline
216 & 17 & 18.2316 & -1.2316 \tabularnewline
217 & 15 & 15.7007 & -0.70066 \tabularnewline
218 & 22 & 22.0282 & -0.0281844 \tabularnewline
219 & 19 & 16.9346 & 2.06538 \tabularnewline
220 & 18 & 20.0672 & -2.06721 \tabularnewline
221 & 21 & 22.8083 & -1.80833 \tabularnewline
222 & 20 & 22.0938 & -2.09382 \tabularnewline
223 & 19 & 19.757 & -0.757016 \tabularnewline
224 & 19 & 18.0788 & 0.921154 \tabularnewline
225 & 16 & 20.6671 & -4.66715 \tabularnewline
226 & 18 & 15.6536 & 2.34636 \tabularnewline
227 & 23 & 22.6405 & 0.359495 \tabularnewline
228 & 22 & 22.8885 & -0.888531 \tabularnewline
229 & 23 & 22.7285 & 0.271471 \tabularnewline
230 & 20 & 20.0921 & -0.0921449 \tabularnewline
231 & 24 & 22.5754 & 1.42462 \tabularnewline
232 & 25 & 18.3122 & 6.6878 \tabularnewline
233 & 25 & 23.8028 & 1.1972 \tabularnewline
234 & 20 & 20.162 & -0.161951 \tabularnewline
235 & 23 & 19.7102 & 3.28976 \tabularnewline
236 & 21 & 21.0074 & -0.00738835 \tabularnewline
237 & 23 & 20.0323 & 2.9677 \tabularnewline
238 & 23 & 20.4952 & 2.50477 \tabularnewline
239 & 11 & 16.5011 & -5.50106 \tabularnewline
240 & 21 & 24.159 & -3.15899 \tabularnewline
241 & 27 & 23.4564 & 3.54356 \tabularnewline
242 & 19 & 20.4854 & -1.48544 \tabularnewline
243 & 21 & 21.3607 & -0.360667 \tabularnewline
244 & 16 & 16.9381 & -0.938098 \tabularnewline
245 & 21 & 18.203 & 2.797 \tabularnewline
246 & 22 & 21.5186 & 0.481379 \tabularnewline
247 & 16 & 20.2554 & -4.2554 \tabularnewline
248 & 18 & 15.6757 & 2.32432 \tabularnewline
249 & 23 & 23.6384 & -0.638426 \tabularnewline
250 & 24 & 21.7183 & 2.28168 \tabularnewline
251 & 20 & 20.8292 & -0.829241 \tabularnewline
252 & 20 & 19.1185 & 0.881523 \tabularnewline
253 & 18 & 19.4967 & -1.49667 \tabularnewline
254 & 4 & 10.207 & -6.20696 \tabularnewline
255 & 14 & 14.8686 & -0.868596 \tabularnewline
256 & 22 & 21.6132 & 0.386768 \tabularnewline
257 & 17 & 22.4819 & -5.48186 \tabularnewline
258 & 23 & 23.0858 & -0.0858081 \tabularnewline
259 & 20 & 19.2415 & 0.75854 \tabularnewline
260 & 18 & 17.4333 & 0.56675 \tabularnewline
261 & 19 & 17.1443 & 1.85571 \tabularnewline
262 & 20 & 21.369 & -1.36904 \tabularnewline
263 & 15 & 16.0383 & -1.03831 \tabularnewline
264 & 24 & 20.4953 & 3.50469 \tabularnewline
265 & 21 & 20.5018 & 0.498159 \tabularnewline
266 & 19 & 19.8851 & -0.885102 \tabularnewline
267 & 19 & 16.243 & 2.75698 \tabularnewline
268 & 27 & 26.4202 & 0.579782 \tabularnewline
269 & 23 & 23.0805 & -0.0805085 \tabularnewline
270 & 23 & 22.1856 & 0.814404 \tabularnewline
271 & 20 & 23.5627 & -3.5627 \tabularnewline
272 & 17 & 19.6748 & -2.67478 \tabularnewline
273 & 21 & 20.8269 & 0.173149 \tabularnewline
274 & 23 & 21.4823 & 1.51766 \tabularnewline
275 & 22 & 21.6416 & 0.358411 \tabularnewline
276 & 16 & 18.505 & -2.50505 \tabularnewline
277 & 20 & 21.5254 & -1.52545 \tabularnewline
278 & 16 & 14.4363 & 1.56371 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264451&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]11[/C][C]14.444[/C][C]-3.44397[/C][/ROW]
[ROW][C]2[/C][C]19[/C][C]22.3445[/C][C]-3.3445[/C][/ROW]
[ROW][C]3[/C][C]16[/C][C]16.9753[/C][C]-0.975261[/C][/ROW]
[ROW][C]4[/C][C]24[/C][C]22.9093[/C][C]1.09067[/C][/ROW]
[ROW][C]5[/C][C]15[/C][C]18.2908[/C][C]-3.29082[/C][/ROW]
[ROW][C]6[/C][C]17[/C][C]20.5557[/C][C]-3.55571[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]20.7848[/C][C]-1.78476[/C][/ROW]
[ROW][C]8[/C][C]19[/C][C]14.6785[/C][C]4.32152[/C][/ROW]
[ROW][C]9[/C][C]28[/C][C]28.1387[/C][C]-0.138717[/C][/ROW]
[ROW][C]10[/C][C]26[/C][C]23.5202[/C][C]2.47984[/C][/ROW]
[ROW][C]11[/C][C]15[/C][C]20.0576[/C][C]-5.05764[/C][/ROW]
[ROW][C]12[/C][C]26[/C][C]24.1319[/C][C]1.8681[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]20.1257[/C][C]-4.12568[/C][/ROW]
[ROW][C]14[/C][C]24[/C][C]21.3223[/C][C]2.6777[/C][/ROW]
[ROW][C]15[/C][C]25[/C][C]24.4168[/C][C]0.58321[/C][/ROW]
[ROW][C]16[/C][C]22[/C][C]20.9229[/C][C]1.07711[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]18.1356[/C][C]-3.13559[/C][/ROW]
[ROW][C]18[/C][C]21[/C][C]21.7675[/C][C]-0.767502[/C][/ROW]
[ROW][C]19[/C][C]22[/C][C]19.9581[/C][C]2.04192[/C][/ROW]
[ROW][C]20[/C][C]27[/C][C]24.9502[/C][C]2.04976[/C][/ROW]
[ROW][C]21[/C][C]26[/C][C]23.0644[/C][C]2.93561[/C][/ROW]
[ROW][C]22[/C][C]26[/C][C]20.6682[/C][C]5.33176[/C][/ROW]
[ROW][C]23[/C][C]22[/C][C]21.2317[/C][C]0.768253[/C][/ROW]
[ROW][C]24[/C][C]21[/C][C]21.5225[/C][C]-0.522485[/C][/ROW]
[ROW][C]25[/C][C]22[/C][C]21.3097[/C][C]0.690316[/C][/ROW]
[ROW][C]26[/C][C]20[/C][C]19.7361[/C][C]0.263891[/C][/ROW]
[ROW][C]27[/C][C]21[/C][C]21.3886[/C][C]-0.388561[/C][/ROW]
[ROW][C]28[/C][C]20[/C][C]17.8168[/C][C]2.1832[/C][/ROW]
[ROW][C]29[/C][C]22[/C][C]22.6309[/C][C]-0.630905[/C][/ROW]
[ROW][C]30[/C][C]21[/C][C]20.5702[/C][C]0.42979[/C][/ROW]
[ROW][C]31[/C][C]8[/C][C]15.7758[/C][C]-7.77583[/C][/ROW]
[ROW][C]32[/C][C]22[/C][C]17.8944[/C][C]4.10555[/C][/ROW]
[ROW][C]33[/C][C]20[/C][C]22.1402[/C][C]-2.1402[/C][/ROW]
[ROW][C]34[/C][C]24[/C][C]16.4977[/C][C]7.50233[/C][/ROW]
[ROW][C]35[/C][C]17[/C][C]19.5375[/C][C]-2.53751[/C][/ROW]
[ROW][C]36[/C][C]20[/C][C]20.9923[/C][C]-0.992313[/C][/ROW]
[ROW][C]37[/C][C]23[/C][C]19.665[/C][C]3.33501[/C][/ROW]
[ROW][C]38[/C][C]20[/C][C]19.1654[/C][C]0.834566[/C][/ROW]
[ROW][C]39[/C][C]22[/C][C]21.6758[/C][C]0.324174[/C][/ROW]
[ROW][C]40[/C][C]19[/C][C]18.7814[/C][C]0.218552[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]17.1548[/C][C]-2.1548[/C][/ROW]
[ROW][C]42[/C][C]20[/C][C]18.7424[/C][C]1.25758[/C][/ROW]
[ROW][C]43[/C][C]22[/C][C]20.1011[/C][C]1.8989[/C][/ROW]
[ROW][C]44[/C][C]17[/C][C]16.1096[/C][C]0.890427[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]15.277[/C][C]-1.27701[/C][/ROW]
[ROW][C]46[/C][C]24[/C][C]23.871[/C][C]0.128958[/C][/ROW]
[ROW][C]47[/C][C]17[/C][C]18.0114[/C][C]-1.01142[/C][/ROW]
[ROW][C]48[/C][C]23[/C][C]23.2838[/C][C]-0.283767[/C][/ROW]
[ROW][C]49[/C][C]25[/C][C]23.4212[/C][C]1.57883[/C][/ROW]
[ROW][C]50[/C][C]16[/C][C]19.1154[/C][C]-3.11543[/C][/ROW]
[ROW][C]51[/C][C]18[/C][C]22.1805[/C][C]-4.18049[/C][/ROW]
[ROW][C]52[/C][C]20[/C][C]18.0557[/C][C]1.94428[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]18.6653[/C][C]-0.665317[/C][/ROW]
[ROW][C]54[/C][C]23[/C][C]25.0105[/C][C]-2.0105[/C][/ROW]
[ROW][C]55[/C][C]24[/C][C]21.3694[/C][C]2.63063[/C][/ROW]
[ROW][C]56[/C][C]23[/C][C]19.3964[/C][C]3.60361[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]17.8395[/C][C]-4.83947[/C][/ROW]
[ROW][C]58[/C][C]20[/C][C]18.3217[/C][C]1.67832[/C][/ROW]
[ROW][C]59[/C][C]20[/C][C]18.4629[/C][C]1.53711[/C][/ROW]
[ROW][C]60[/C][C]19[/C][C]19.4636[/C][C]-0.463626[/C][/ROW]
[ROW][C]61[/C][C]22[/C][C]20.8728[/C][C]1.12716[/C][/ROW]
[ROW][C]62[/C][C]22[/C][C]21.5812[/C][C]0.418807[/C][/ROW]
[ROW][C]63[/C][C]15[/C][C]15.6178[/C][C]-0.617782[/C][/ROW]
[ROW][C]64[/C][C]17[/C][C]17.6237[/C][C]-0.623679[/C][/ROW]
[ROW][C]65[/C][C]19[/C][C]19.0164[/C][C]-0.0164442[/C][/ROW]
[ROW][C]66[/C][C]20[/C][C]16.6505[/C][C]3.34952[/C][/ROW]
[ROW][C]67[/C][C]22[/C][C]23.7275[/C][C]-1.72751[/C][/ROW]
[ROW][C]68[/C][C]21[/C][C]22.3331[/C][C]-1.33314[/C][/ROW]
[ROW][C]69[/C][C]21[/C][C]19.0958[/C][C]1.90421[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]17.2569[/C][C]-1.25693[/C][/ROW]
[ROW][C]71[/C][C]20[/C][C]19.0857[/C][C]0.914285[/C][/ROW]
[ROW][C]72[/C][C]21[/C][C]20.084[/C][C]0.915955[/C][/ROW]
[ROW][C]73[/C][C]20[/C][C]19.5628[/C][C]0.437229[/C][/ROW]
[ROW][C]74[/C][C]23[/C][C]24.2219[/C][C]-1.22192[/C][/ROW]
[ROW][C]75[/C][C]18[/C][C]16.8273[/C][C]1.1727[/C][/ROW]
[ROW][C]76[/C][C]16[/C][C]18.1875[/C][C]-2.18748[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]15.812[/C][C]1.18795[/C][/ROW]
[ROW][C]78[/C][C]24[/C][C]23.5612[/C][C]0.43884[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]17.3144[/C][C]-4.31435[/C][/ROW]
[ROW][C]80[/C][C]19[/C][C]20.497[/C][C]-1.49704[/C][/ROW]
[ROW][C]81[/C][C]20[/C][C]19.3097[/C][C]0.690332[/C][/ROW]
[ROW][C]82[/C][C]22[/C][C]20.8315[/C][C]1.16853[/C][/ROW]
[ROW][C]83[/C][C]19[/C][C]20.0881[/C][C]-1.08814[/C][/ROW]
[ROW][C]84[/C][C]21[/C][C]22.0609[/C][C]-1.06094[/C][/ROW]
[ROW][C]85[/C][C]15[/C][C]14.7567[/C][C]0.243319[/C][/ROW]
[ROW][C]86[/C][C]21[/C][C]21.1088[/C][C]-0.108788[/C][/ROW]
[ROW][C]87[/C][C]24[/C][C]22.3583[/C][C]1.64168[/C][/ROW]
[ROW][C]88[/C][C]22[/C][C]22.8949[/C][C]-0.894937[/C][/ROW]
[ROW][C]89[/C][C]20[/C][C]20.5072[/C][C]-0.507225[/C][/ROW]
[ROW][C]90[/C][C]21[/C][C]21.0957[/C][C]-0.0957111[/C][/ROW]
[ROW][C]91[/C][C]19[/C][C]19.4684[/C][C]-0.468418[/C][/ROW]
[ROW][C]92[/C][C]14[/C][C]13.7991[/C][C]0.200853[/C][/ROW]
[ROW][C]93[/C][C]25[/C][C]24.4483[/C][C]0.551685[/C][/ROW]
[ROW][C]94[/C][C]11[/C][C]13.3593[/C][C]-2.35931[/C][/ROW]
[ROW][C]95[/C][C]17[/C][C]19.5441[/C][C]-2.54411[/C][/ROW]
[ROW][C]96[/C][C]22[/C][C]24.1956[/C][C]-2.19556[/C][/ROW]
[ROW][C]97[/C][C]20[/C][C]20.407[/C][C]-0.406999[/C][/ROW]
[ROW][C]98[/C][C]22[/C][C]20.052[/C][C]1.94801[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]19.7323[/C][C]-4.73234[/C][/ROW]
[ROW][C]100[/C][C]23[/C][C]22.7658[/C][C]0.234188[/C][/ROW]
[ROW][C]101[/C][C]20[/C][C]21.9672[/C][C]-1.96716[/C][/ROW]
[ROW][C]102[/C][C]22[/C][C]24.5419[/C][C]-2.54194[/C][/ROW]
[ROW][C]103[/C][C]16[/C][C]13.6822[/C][C]2.31776[/C][/ROW]
[ROW][C]104[/C][C]25[/C][C]22.2758[/C][C]2.72416[/C][/ROW]
[ROW][C]105[/C][C]18[/C][C]19.5833[/C][C]-1.58326[/C][/ROW]
[ROW][C]106[/C][C]19[/C][C]19.2088[/C][C]-0.208817[/C][/ROW]
[ROW][C]107[/C][C]25[/C][C]18.239[/C][C]6.76095[/C][/ROW]
[ROW][C]108[/C][C]21[/C][C]19.3215[/C][C]1.67846[/C][/ROW]
[ROW][C]109[/C][C]22[/C][C]21.7153[/C][C]0.284695[/C][/ROW]
[ROW][C]110[/C][C]21[/C][C]21.5243[/C][C]-0.524349[/C][/ROW]
[ROW][C]111[/C][C]22[/C][C]23.1037[/C][C]-1.10369[/C][/ROW]
[ROW][C]112[/C][C]23[/C][C]22.1099[/C][C]0.890064[/C][/ROW]
[ROW][C]113[/C][C]20[/C][C]19.9956[/C][C]0.00438933[/C][/ROW]
[ROW][C]114[/C][C]6[/C][C]14.3435[/C][C]-8.34351[/C][/ROW]
[ROW][C]115[/C][C]15[/C][C]17.7773[/C][C]-2.7773[/C][/ROW]
[ROW][C]116[/C][C]18[/C][C]22.4396[/C][C]-4.43959[/C][/ROW]
[ROW][C]117[/C][C]24[/C][C]20.472[/C][C]3.528[/C][/ROW]
[ROW][C]118[/C][C]22[/C][C]16.3566[/C][C]5.64338[/C][/ROW]
[ROW][C]119[/C][C]21[/C][C]20.2832[/C][C]0.716802[/C][/ROW]
[ROW][C]120[/C][C]23[/C][C]23.2735[/C][C]-0.273483[/C][/ROW]
[ROW][C]121[/C][C]20[/C][C]21.7127[/C][C]-1.71265[/C][/ROW]
[ROW][C]122[/C][C]20[/C][C]19.1495[/C][C]0.850479[/C][/ROW]
[ROW][C]123[/C][C]18[/C][C]17.6363[/C][C]0.363677[/C][/ROW]
[ROW][C]124[/C][C]25[/C][C]24.062[/C][C]0.938034[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]21.8009[/C][C]-5.80086[/C][/ROW]
[ROW][C]126[/C][C]20[/C][C]21.6888[/C][C]-1.68878[/C][/ROW]
[ROW][C]127[/C][C]14[/C][C]16.3623[/C][C]-2.36232[/C][/ROW]
[ROW][C]128[/C][C]22[/C][C]20.9651[/C][C]1.03488[/C][/ROW]
[ROW][C]129[/C][C]26[/C][C]25.9231[/C][C]0.0769022[/C][/ROW]
[ROW][C]130[/C][C]20[/C][C]18.2424[/C][C]1.75764[/C][/ROW]
[ROW][C]131[/C][C]17[/C][C]17.7126[/C][C]-0.712599[/C][/ROW]
[ROW][C]132[/C][C]22[/C][C]22.2541[/C][C]-0.254053[/C][/ROW]
[ROW][C]133[/C][C]22[/C][C]19.9068[/C][C]2.09317[/C][/ROW]
[ROW][C]134[/C][C]20[/C][C]23.4628[/C][C]-3.46284[/C][/ROW]
[ROW][C]135[/C][C]17[/C][C]14.166[/C][C]2.83401[/C][/ROW]
[ROW][C]136[/C][C]22[/C][C]24.5434[/C][C]-2.54342[/C][/ROW]
[ROW][C]137[/C][C]17[/C][C]19.119[/C][C]-2.11904[/C][/ROW]
[ROW][C]138[/C][C]22[/C][C]19.811[/C][C]2.18898[/C][/ROW]
[ROW][C]139[/C][C]21[/C][C]21.1773[/C][C]-0.177262[/C][/ROW]
[ROW][C]140[/C][C]25[/C][C]20.6352[/C][C]4.36484[/C][/ROW]
[ROW][C]141[/C][C]11[/C][C]10.2383[/C][C]0.761724[/C][/ROW]
[ROW][C]142[/C][C]19[/C][C]19.1632[/C][C]-0.163172[/C][/ROW]
[ROW][C]143[/C][C]24[/C][C]23.8096[/C][C]0.190354[/C][/ROW]
[ROW][C]144[/C][C]17[/C][C]20.462[/C][C]-3.46199[/C][/ROW]
[ROW][C]145[/C][C]22[/C][C]20.2236[/C][C]1.77637[/C][/ROW]
[ROW][C]146[/C][C]17[/C][C]17.222[/C][C]-0.222041[/C][/ROW]
[ROW][C]147[/C][C]26[/C][C]24.6152[/C][C]1.38477[/C][/ROW]
[ROW][C]148[/C][C]20[/C][C]19.0784[/C][C]0.921576[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]18.9332[/C][C]0.0668349[/C][/ROW]
[ROW][C]150[/C][C]21[/C][C]19.3313[/C][C]1.66869[/C][/ROW]
[ROW][C]151[/C][C]24[/C][C]21.5967[/C][C]2.4033[/C][/ROW]
[ROW][C]152[/C][C]21[/C][C]21.2818[/C][C]-0.281778[/C][/ROW]
[ROW][C]153[/C][C]19[/C][C]21.07[/C][C]-2.06997[/C][/ROW]
[ROW][C]154[/C][C]13[/C][C]15.5782[/C][C]-2.57823[/C][/ROW]
[ROW][C]155[/C][C]24[/C][C]24.7665[/C][C]-0.766514[/C][/ROW]
[ROW][C]156[/C][C]28[/C][C]22.5473[/C][C]5.45269[/C][/ROW]
[ROW][C]157[/C][C]27[/C][C]24.7275[/C][C]2.27255[/C][/ROW]
[ROW][C]158[/C][C]22[/C][C]19.1869[/C][C]2.81311[/C][/ROW]
[ROW][C]159[/C][C]23[/C][C]22.9629[/C][C]0.0370759[/C][/ROW]
[ROW][C]160[/C][C]19[/C][C]16.3086[/C][C]2.69137[/C][/ROW]
[ROW][C]161[/C][C]18[/C][C]19.1193[/C][C]-1.11928[/C][/ROW]
[ROW][C]162[/C][C]23[/C][C]22.0206[/C][C]0.979384[/C][/ROW]
[ROW][C]163[/C][C]21[/C][C]18.0872[/C][C]2.91276[/C][/ROW]
[ROW][C]164[/C][C]22[/C][C]21.3728[/C][C]0.627159[/C][/ROW]
[ROW][C]165[/C][C]17[/C][C]18.8378[/C][C]-1.8378[/C][/ROW]
[ROW][C]166[/C][C]15[/C][C]17.6042[/C][C]-2.60417[/C][/ROW]
[ROW][C]167[/C][C]21[/C][C]18.6603[/C][C]2.33967[/C][/ROW]
[ROW][C]168[/C][C]20[/C][C]19.9575[/C][C]0.0425266[/C][/ROW]
[ROW][C]169[/C][C]26[/C][C]23.3162[/C][C]2.68375[/C][/ROW]
[ROW][C]170[/C][C]19[/C][C]21.1403[/C][C]-2.14034[/C][/ROW]
[ROW][C]171[/C][C]28[/C][C]26.2894[/C][C]1.71056[/C][/ROW]
[ROW][C]172[/C][C]21[/C][C]18.7732[/C][C]2.22677[/C][/ROW]
[ROW][C]173[/C][C]19[/C][C]21.4682[/C][C]-2.46818[/C][/ROW]
[ROW][C]174[/C][C]22[/C][C]20.296[/C][C]1.70404[/C][/ROW]
[ROW][C]175[/C][C]21[/C][C]19.9457[/C][C]1.05435[/C][/ROW]
[ROW][C]176[/C][C]20[/C][C]20.0992[/C][C]-0.0991507[/C][/ROW]
[ROW][C]177[/C][C]19[/C][C]17.4061[/C][C]1.59392[/C][/ROW]
[ROW][C]178[/C][C]11[/C][C]14.0239[/C][C]-3.02389[/C][/ROW]
[ROW][C]179[/C][C]17[/C][C]19.8657[/C][C]-2.86571[/C][/ROW]
[ROW][C]180[/C][C]19[/C][C]17.8066[/C][C]1.19337[/C][/ROW]
[ROW][C]181[/C][C]20[/C][C]19.0633[/C][C]0.936702[/C][/ROW]
[ROW][C]182[/C][C]17[/C][C]16.7898[/C][C]0.210242[/C][/ROW]
[ROW][C]183[/C][C]21[/C][C]18.1272[/C][C]2.87278[/C][/ROW]
[ROW][C]184[/C][C]21[/C][C]21.5568[/C][C]-0.556828[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]14.0562[/C][C]-2.05617[/C][/ROW]
[ROW][C]186[/C][C]23[/C][C]19.9934[/C][C]3.00663[/C][/ROW]
[ROW][C]187[/C][C]22[/C][C]20.9882[/C][C]1.01178[/C][/ROW]
[ROW][C]188[/C][C]22[/C][C]21.7674[/C][C]0.232612[/C][/ROW]
[ROW][C]189[/C][C]21[/C][C]21.9879[/C][C]-0.987872[/C][/ROW]
[ROW][C]190[/C][C]20[/C][C]20.8709[/C][C]-0.870922[/C][/ROW]
[ROW][C]191[/C][C]18[/C][C]18.0395[/C][C]-0.0395315[/C][/ROW]
[ROW][C]192[/C][C]21[/C][C]24.0054[/C][C]-3.00543[/C][/ROW]
[ROW][C]193[/C][C]24[/C][C]22.1255[/C][C]1.87455[/C][/ROW]
[ROW][C]194[/C][C]22[/C][C]22.1607[/C][C]-0.160682[/C][/ROW]
[ROW][C]195[/C][C]20[/C][C]17.2108[/C][C]2.78917[/C][/ROW]
[ROW][C]196[/C][C]17[/C][C]17.0487[/C][C]-0.0486614[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]18.7918[/C][C]0.208222[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]19.2679[/C][C]-3.26786[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]20.3609[/C][C]-1.36093[/C][/ROW]
[ROW][C]200[/C][C]23[/C][C]25.0197[/C][C]-2.01971[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]13.6394[/C][C]-5.63944[/C][/ROW]
[ROW][C]202[/C][C]22[/C][C]22.69[/C][C]-0.689955[/C][/ROW]
[ROW][C]203[/C][C]23[/C][C]21.3866[/C][C]1.61336[/C][/ROW]
[ROW][C]204[/C][C]15[/C][C]19.153[/C][C]-4.15303[/C][/ROW]
[ROW][C]205[/C][C]17[/C][C]21.4334[/C][C]-4.43343[/C][/ROW]
[ROW][C]206[/C][C]21[/C][C]17.814[/C][C]3.18601[/C][/ROW]
[ROW][C]207[/C][C]25[/C][C]20.4505[/C][C]4.54945[/C][/ROW]
[ROW][C]208[/C][C]18[/C][C]13.4488[/C][C]4.55116[/C][/ROW]
[ROW][C]209[/C][C]20[/C][C]18.5917[/C][C]1.4083[/C][/ROW]
[ROW][C]210[/C][C]21[/C][C]19.3897[/C][C]1.61028[/C][/ROW]
[ROW][C]211[/C][C]21[/C][C]20.2908[/C][C]0.709202[/C][/ROW]
[ROW][C]212[/C][C]24[/C][C]20.0349[/C][C]3.96505[/C][/ROW]
[ROW][C]213[/C][C]22[/C][C]21.9931[/C][C]0.0069268[/C][/ROW]
[ROW][C]214[/C][C]22[/C][C]21.0817[/C][C]0.918307[/C][/ROW]
[ROW][C]215[/C][C]23[/C][C]20.797[/C][C]2.20298[/C][/ROW]
[ROW][C]216[/C][C]17[/C][C]18.2316[/C][C]-1.2316[/C][/ROW]
[ROW][C]217[/C][C]15[/C][C]15.7007[/C][C]-0.70066[/C][/ROW]
[ROW][C]218[/C][C]22[/C][C]22.0282[/C][C]-0.0281844[/C][/ROW]
[ROW][C]219[/C][C]19[/C][C]16.9346[/C][C]2.06538[/C][/ROW]
[ROW][C]220[/C][C]18[/C][C]20.0672[/C][C]-2.06721[/C][/ROW]
[ROW][C]221[/C][C]21[/C][C]22.8083[/C][C]-1.80833[/C][/ROW]
[ROW][C]222[/C][C]20[/C][C]22.0938[/C][C]-2.09382[/C][/ROW]
[ROW][C]223[/C][C]19[/C][C]19.757[/C][C]-0.757016[/C][/ROW]
[ROW][C]224[/C][C]19[/C][C]18.0788[/C][C]0.921154[/C][/ROW]
[ROW][C]225[/C][C]16[/C][C]20.6671[/C][C]-4.66715[/C][/ROW]
[ROW][C]226[/C][C]18[/C][C]15.6536[/C][C]2.34636[/C][/ROW]
[ROW][C]227[/C][C]23[/C][C]22.6405[/C][C]0.359495[/C][/ROW]
[ROW][C]228[/C][C]22[/C][C]22.8885[/C][C]-0.888531[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]22.7285[/C][C]0.271471[/C][/ROW]
[ROW][C]230[/C][C]20[/C][C]20.0921[/C][C]-0.0921449[/C][/ROW]
[ROW][C]231[/C][C]24[/C][C]22.5754[/C][C]1.42462[/C][/ROW]
[ROW][C]232[/C][C]25[/C][C]18.3122[/C][C]6.6878[/C][/ROW]
[ROW][C]233[/C][C]25[/C][C]23.8028[/C][C]1.1972[/C][/ROW]
[ROW][C]234[/C][C]20[/C][C]20.162[/C][C]-0.161951[/C][/ROW]
[ROW][C]235[/C][C]23[/C][C]19.7102[/C][C]3.28976[/C][/ROW]
[ROW][C]236[/C][C]21[/C][C]21.0074[/C][C]-0.00738835[/C][/ROW]
[ROW][C]237[/C][C]23[/C][C]20.0323[/C][C]2.9677[/C][/ROW]
[ROW][C]238[/C][C]23[/C][C]20.4952[/C][C]2.50477[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]16.5011[/C][C]-5.50106[/C][/ROW]
[ROW][C]240[/C][C]21[/C][C]24.159[/C][C]-3.15899[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]23.4564[/C][C]3.54356[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]20.4854[/C][C]-1.48544[/C][/ROW]
[ROW][C]243[/C][C]21[/C][C]21.3607[/C][C]-0.360667[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]16.9381[/C][C]-0.938098[/C][/ROW]
[ROW][C]245[/C][C]21[/C][C]18.203[/C][C]2.797[/C][/ROW]
[ROW][C]246[/C][C]22[/C][C]21.5186[/C][C]0.481379[/C][/ROW]
[ROW][C]247[/C][C]16[/C][C]20.2554[/C][C]-4.2554[/C][/ROW]
[ROW][C]248[/C][C]18[/C][C]15.6757[/C][C]2.32432[/C][/ROW]
[ROW][C]249[/C][C]23[/C][C]23.6384[/C][C]-0.638426[/C][/ROW]
[ROW][C]250[/C][C]24[/C][C]21.7183[/C][C]2.28168[/C][/ROW]
[ROW][C]251[/C][C]20[/C][C]20.8292[/C][C]-0.829241[/C][/ROW]
[ROW][C]252[/C][C]20[/C][C]19.1185[/C][C]0.881523[/C][/ROW]
[ROW][C]253[/C][C]18[/C][C]19.4967[/C][C]-1.49667[/C][/ROW]
[ROW][C]254[/C][C]4[/C][C]10.207[/C][C]-6.20696[/C][/ROW]
[ROW][C]255[/C][C]14[/C][C]14.8686[/C][C]-0.868596[/C][/ROW]
[ROW][C]256[/C][C]22[/C][C]21.6132[/C][C]0.386768[/C][/ROW]
[ROW][C]257[/C][C]17[/C][C]22.4819[/C][C]-5.48186[/C][/ROW]
[ROW][C]258[/C][C]23[/C][C]23.0858[/C][C]-0.0858081[/C][/ROW]
[ROW][C]259[/C][C]20[/C][C]19.2415[/C][C]0.75854[/C][/ROW]
[ROW][C]260[/C][C]18[/C][C]17.4333[/C][C]0.56675[/C][/ROW]
[ROW][C]261[/C][C]19[/C][C]17.1443[/C][C]1.85571[/C][/ROW]
[ROW][C]262[/C][C]20[/C][C]21.369[/C][C]-1.36904[/C][/ROW]
[ROW][C]263[/C][C]15[/C][C]16.0383[/C][C]-1.03831[/C][/ROW]
[ROW][C]264[/C][C]24[/C][C]20.4953[/C][C]3.50469[/C][/ROW]
[ROW][C]265[/C][C]21[/C][C]20.5018[/C][C]0.498159[/C][/ROW]
[ROW][C]266[/C][C]19[/C][C]19.8851[/C][C]-0.885102[/C][/ROW]
[ROW][C]267[/C][C]19[/C][C]16.243[/C][C]2.75698[/C][/ROW]
[ROW][C]268[/C][C]27[/C][C]26.4202[/C][C]0.579782[/C][/ROW]
[ROW][C]269[/C][C]23[/C][C]23.0805[/C][C]-0.0805085[/C][/ROW]
[ROW][C]270[/C][C]23[/C][C]22.1856[/C][C]0.814404[/C][/ROW]
[ROW][C]271[/C][C]20[/C][C]23.5627[/C][C]-3.5627[/C][/ROW]
[ROW][C]272[/C][C]17[/C][C]19.6748[/C][C]-2.67478[/C][/ROW]
[ROW][C]273[/C][C]21[/C][C]20.8269[/C][C]0.173149[/C][/ROW]
[ROW][C]274[/C][C]23[/C][C]21.4823[/C][C]1.51766[/C][/ROW]
[ROW][C]275[/C][C]22[/C][C]21.6416[/C][C]0.358411[/C][/ROW]
[ROW][C]276[/C][C]16[/C][C]18.505[/C][C]-2.50505[/C][/ROW]
[ROW][C]277[/C][C]20[/C][C]21.5254[/C][C]-1.52545[/C][/ROW]
[ROW][C]278[/C][C]16[/C][C]14.4363[/C][C]1.56371[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264451&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264451&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
11114.444-3.44397
21922.3445-3.3445
31616.9753-0.975261
42422.90931.09067
51518.2908-3.29082
61720.5557-3.55571
71920.7848-1.78476
81914.67854.32152
92828.1387-0.138717
102623.52022.47984
111520.0576-5.05764
122624.13191.8681
131620.1257-4.12568
142421.32232.6777
152524.41680.58321
162220.92291.07711
171518.1356-3.13559
182121.7675-0.767502
192219.95812.04192
202724.95022.04976
212623.06442.93561
222620.66825.33176
232221.23170.768253
242121.5225-0.522485
252221.30970.690316
262019.73610.263891
272121.3886-0.388561
282017.81682.1832
292222.6309-0.630905
302120.57020.42979
31815.7758-7.77583
322217.89444.10555
332022.1402-2.1402
342416.49777.50233
351719.5375-2.53751
362020.9923-0.992313
372319.6653.33501
382019.16540.834566
392221.67580.324174
401918.78140.218552
411517.1548-2.1548
422018.74241.25758
432220.10111.8989
441716.10960.890427
451415.277-1.27701
462423.8710.128958
471718.0114-1.01142
482323.2838-0.283767
492523.42121.57883
501619.1154-3.11543
511822.1805-4.18049
522018.05571.94428
531818.6653-0.665317
542325.0105-2.0105
552421.36942.63063
562319.39643.60361
571317.8395-4.83947
582018.32171.67832
592018.46291.53711
601919.4636-0.463626
612220.87281.12716
622221.58120.418807
631515.6178-0.617782
641717.6237-0.623679
651919.0164-0.0164442
662016.65053.34952
672223.7275-1.72751
682122.3331-1.33314
692119.09581.90421
701617.2569-1.25693
712019.08570.914285
722120.0840.915955
732019.56280.437229
742324.2219-1.22192
751816.82731.1727
761618.1875-2.18748
771715.8121.18795
782423.56120.43884
791317.3144-4.31435
801920.497-1.49704
812019.30970.690332
822220.83151.16853
831920.0881-1.08814
842122.0609-1.06094
851514.75670.243319
862121.1088-0.108788
872422.35831.64168
882222.8949-0.894937
892020.5072-0.507225
902121.0957-0.0957111
911919.4684-0.468418
921413.79910.200853
932524.44830.551685
941113.3593-2.35931
951719.5441-2.54411
962224.1956-2.19556
972020.407-0.406999
982220.0521.94801
991519.7323-4.73234
1002322.76580.234188
1012021.9672-1.96716
1022224.5419-2.54194
1031613.68222.31776
1042522.27582.72416
1051819.5833-1.58326
1061919.2088-0.208817
1072518.2396.76095
1082119.32151.67846
1092221.71530.284695
1102121.5243-0.524349
1112223.1037-1.10369
1122322.10990.890064
1132019.99560.00438933
114614.3435-8.34351
1151517.7773-2.7773
1161822.4396-4.43959
1172420.4723.528
1182216.35665.64338
1192120.28320.716802
1202323.2735-0.273483
1212021.7127-1.71265
1222019.14950.850479
1231817.63630.363677
1242524.0620.938034
1251621.8009-5.80086
1262021.6888-1.68878
1271416.3623-2.36232
1282220.96511.03488
1292625.92310.0769022
1302018.24241.75764
1311717.7126-0.712599
1322222.2541-0.254053
1332219.90682.09317
1342023.4628-3.46284
1351714.1662.83401
1362224.5434-2.54342
1371719.119-2.11904
1382219.8112.18898
1392121.1773-0.177262
1402520.63524.36484
1411110.23830.761724
1421919.1632-0.163172
1432423.80960.190354
1441720.462-3.46199
1452220.22361.77637
1461717.222-0.222041
1472624.61521.38477
1482019.07840.921576
1491918.93320.0668349
1502119.33131.66869
1512421.59672.4033
1522121.2818-0.281778
1531921.07-2.06997
1541315.5782-2.57823
1552424.7665-0.766514
1562822.54735.45269
1572724.72752.27255
1582219.18692.81311
1592322.96290.0370759
1601916.30862.69137
1611819.1193-1.11928
1622322.02060.979384
1632118.08722.91276
1642221.37280.627159
1651718.8378-1.8378
1661517.6042-2.60417
1672118.66032.33967
1682019.95750.0425266
1692623.31622.68375
1701921.1403-2.14034
1712826.28941.71056
1722118.77322.22677
1731921.4682-2.46818
1742220.2961.70404
1752119.94571.05435
1762020.0992-0.0991507
1771917.40611.59392
1781114.0239-3.02389
1791719.8657-2.86571
1801917.80661.19337
1812019.06330.936702
1821716.78980.210242
1832118.12722.87278
1842121.5568-0.556828
1851214.0562-2.05617
1862319.99343.00663
1872220.98821.01178
1882221.76740.232612
1892121.9879-0.987872
1902020.8709-0.870922
1911818.0395-0.0395315
1922124.0054-3.00543
1932422.12551.87455
1942222.1607-0.160682
1952017.21082.78917
1961717.0487-0.0486614
1971918.79180.208222
1981619.2679-3.26786
1991920.3609-1.36093
2002325.0197-2.01971
201813.6394-5.63944
2022222.69-0.689955
2032321.38661.61336
2041519.153-4.15303
2051721.4334-4.43343
2062117.8143.18601
2072520.45054.54945
2081813.44884.55116
2092018.59171.4083
2102119.38971.61028
2112120.29080.709202
2122420.03493.96505
2132221.99310.0069268
2142221.08170.918307
2152320.7972.20298
2161718.2316-1.2316
2171515.7007-0.70066
2182222.0282-0.0281844
2191916.93462.06538
2201820.0672-2.06721
2212122.8083-1.80833
2222022.0938-2.09382
2231919.757-0.757016
2241918.07880.921154
2251620.6671-4.66715
2261815.65362.34636
2272322.64050.359495
2282222.8885-0.888531
2292322.72850.271471
2302020.0921-0.0921449
2312422.57541.42462
2322518.31226.6878
2332523.80281.1972
2342020.162-0.161951
2352319.71023.28976
2362121.0074-0.00738835
2372320.03232.9677
2382320.49522.50477
2391116.5011-5.50106
2402124.159-3.15899
2412723.45643.54356
2421920.4854-1.48544
2432121.3607-0.360667
2441616.9381-0.938098
2452118.2032.797
2462221.51860.481379
2471620.2554-4.2554
2481815.67572.32432
2492323.6384-0.638426
2502421.71832.28168
2512020.8292-0.829241
2522019.11850.881523
2531819.4967-1.49667
254410.207-6.20696
2551414.8686-0.868596
2562221.61320.386768
2571722.4819-5.48186
2582323.0858-0.0858081
2592019.24150.75854
2601817.43330.56675
2611917.14431.85571
2622021.369-1.36904
2631516.0383-1.03831
2642420.49533.50469
2652120.50180.498159
2661919.8851-0.885102
2671916.2432.75698
2682726.42020.579782
2692323.0805-0.0805085
2702322.18560.814404
2712023.5627-3.5627
2721719.6748-2.67478
2732120.82690.173149
2742321.48231.51766
2752221.64160.358411
2761618.505-2.50505
2772021.5254-1.52545
2781614.43631.56371






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.7264090.5471830.273591
120.9170030.1659940.0829972
130.8696160.2607670.130384
140.8388830.3222340.161117
150.7671650.465670.232835
160.7560940.4878120.243906
170.6867360.6265280.313264
180.608210.7835810.39179
190.628020.7439610.37198
200.5466310.9067380.453369
210.480450.96090.51955
220.6904650.6190710.309535
230.6676040.6647910.332396
240.5984550.803090.401545
250.5779030.8441940.422097
260.5442860.9114280.455714
270.4933920.9867830.506608
280.4310770.8621540.568923
290.3692670.7385340.630733
300.3181380.6362750.681862
310.464410.9288190.53559
320.4380840.8761690.561916
330.3849410.7698820.615059
340.9982040.003591080.00179554
350.9978230.004353750.00217687
360.9971190.005762310.00288115
370.9985930.002813290.00140665
380.9979430.004114540.00205727
390.9969950.006009830.00300491
400.9962310.007538470.00376923
410.9952130.009574260.00478713
420.9937880.01242450.00621226
430.9924650.01507030.00753515
440.9921980.01560470.00780234
450.9897830.02043310.0102165
460.9861090.02778290.0138914
470.9822560.03548750.0177437
480.9769420.04611620.0230581
490.9721680.05566480.0278324
500.9731170.05376560.0268828
510.9803050.03938960.0196948
520.9775020.04499650.0224982
530.9713660.05726750.0286338
540.969050.06190060.0309503
550.970520.05896050.0294803
560.9773520.04529510.0226476
570.9853980.02920310.0146015
580.9817470.03650520.0182526
590.9804970.0390060.019503
600.9750410.04991770.0249588
610.9697770.06044670.0302234
620.9621920.07561650.0378083
630.9531280.09374310.0468716
640.9424490.1151030.0575514
650.9312610.1374790.0687393
660.9411350.1177290.0588647
670.9374760.1250490.0625245
680.9272040.1455930.0727964
690.9240650.1518690.0759346
700.9108050.178390.0891951
710.8943170.2113660.105683
720.8770470.2459060.122953
730.8557550.2884890.144245
740.8437150.312570.156285
750.8331860.3336280.166814
760.8262850.347430.173715
770.8061260.3877470.193874
780.7803190.4393630.219681
790.8203330.3593350.179667
800.802160.395680.19784
810.7763530.4472940.223647
820.7534170.4931660.246583
830.7254520.5490950.274548
840.6986370.6027250.301363
850.6645980.6708040.335402
860.6297720.7404550.370228
870.607960.784080.39204
880.5742320.8515350.425768
890.5381120.9237770.461888
900.500520.998960.49948
910.4661170.9322340.533883
920.4297850.8595690.570215
930.3942470.7884940.605753
940.3884680.7769370.611532
950.3890180.7780350.610982
960.383390.7667790.61661
970.3497380.6994760.650262
980.3346770.6693550.665323
990.4238370.8476750.576163
1000.388710.7774210.61129
1010.3791370.7582730.620863
1020.3808610.7617220.619139
1030.3855180.7710370.614482
1040.3923290.7846580.607671
1050.3675920.7351840.632408
1060.3345360.6690720.665464
1070.5106980.9786030.489302
1080.4984410.9968820.501559
1090.462780.9255610.53722
1100.4295590.8591180.570441
1110.400840.801680.59916
1120.3695460.7390930.630454
1130.3371540.6743090.662846
1140.7248610.5502780.275139
1150.7303150.539370.269685
1160.7867160.4265680.213284
1170.8203770.3592470.179623
1180.8838560.2322870.116144
1190.8677570.2644860.132243
1200.8481080.3037830.151892
1210.8380940.3238110.161906
1220.8188050.3623910.181195
1230.7954050.4091910.204595
1240.7747530.4504940.225247
1250.8801750.239650.119825
1260.871040.2579190.12896
1270.8722350.255530.127765
1280.8565240.2869530.143476
1290.8361690.3276610.163831
1300.823720.352560.17628
1310.8082210.3835590.191779
1320.7843810.4312370.215619
1330.7861740.4276510.213826
1340.8077620.3844770.192238
1350.8134830.3730340.186517
1360.8139430.3721150.186057
1370.8075220.3849560.192478
1380.8069460.3861070.193054
1390.7820860.4358290.217914
1400.83190.33620.1681
1410.8198740.3602520.180126
1420.7986970.4026060.201303
1430.7735690.4528610.226431
1440.8001770.3996450.199823
1450.7906160.4187680.209384
1460.7650050.4699890.234995
1470.7446470.5107060.255353
1480.7202380.5595230.279762
1490.6899390.6201220.310061
1500.6709480.6581040.329052
1510.6685350.6629310.331465
1520.6367120.7265770.363288
1530.6283330.7433330.371667
1540.6370520.7258960.362948
1550.6084890.7830220.391511
1560.7343980.5312050.265602
1570.7379730.5240550.262027
1580.7452480.5095030.254752
1590.716470.567060.28353
1600.7198340.5603320.280166
1610.6972410.6055170.302759
1620.6706430.6587140.329357
1630.6810380.6379240.318962
1640.6519530.6960940.348047
1650.6407890.7184210.359211
1660.6519690.6960620.348031
1670.6471460.7057070.352854
1680.6143750.7712510.385625
1690.622770.7544610.37723
1700.6145070.7709870.385493
1710.6031820.7936370.396818
1720.5963730.8072530.403627
1730.5959170.8081660.404083
1740.5780740.8438510.421926
1750.550750.89850.44925
1760.514510.970980.48549
1770.4927330.9854670.507267
1780.5276510.9446990.472349
1790.5484020.9031970.451598
1800.5193570.9612870.480643
1810.4872730.9745450.512727
1820.4513440.9026880.548656
1830.451490.902980.54851
1840.4177140.8354290.582286
1850.4118880.8237760.588112
1860.4386530.8773050.561347
1870.4135430.8270850.586457
1880.3786890.7573780.621311
1890.3477530.6955070.652247
1900.3192550.638510.680745
1910.2873640.5747280.712636
1920.2915410.5830810.708459
1930.2838550.5677110.716145
1940.2543080.5086160.745692
1950.2597050.5194110.740295
1960.236990.473980.76301
1970.2109820.4219640.789018
1980.2317530.4635060.768247
1990.2088140.4176280.791186
2000.1913420.3826830.808658
2010.2684460.5368910.731554
2020.2380860.4761730.761914
2030.2196460.4392910.780354
2040.2942390.5884790.705761
2050.3817350.7634690.618265
2060.4120680.8241360.587932
2070.4979580.9959160.502042
2080.6073470.7853050.392653
2090.5870550.8258890.412945
2100.5563960.8872070.443604
2110.5175320.9649350.482468
2120.5510230.8979540.448977
2130.5091770.9816450.490823
2140.4696310.9392610.530369
2150.460870.921740.53913
2160.4273270.8546550.572673
2170.386450.7728990.61355
2180.345460.690920.65454
2190.3485640.6971290.651436
2200.3382770.6765540.661723
2210.3165580.6331160.683442
2220.3026830.6053650.697317
2230.268420.536840.73158
2240.237680.475360.76232
2250.3369040.6738080.663096
2260.3197390.6394780.680261
2270.280140.560280.71986
2280.2481270.4962540.751873
2290.2132440.4264880.786756
2300.1814280.3628550.818572
2310.1537520.3075040.846248
2320.4269620.8539250.573038
2330.388070.7761410.61193
2340.3410760.6821530.658924
2350.3943310.7886630.605669
2360.3464820.6929650.653518
2370.3943880.7887750.605612
2380.3903190.7806370.609681
2390.5623420.8753170.437658
2400.627180.7456410.37282
2410.6483660.7032690.351634
2420.5986410.8027180.401359
2430.5453390.9093210.454661
2440.4882510.9765020.511749
2450.5308290.9383420.469171
2460.4981060.9962120.501894
2470.6200320.7599350.379968
2480.6990930.6018130.300907
2490.6468540.7062930.353146
2500.6167650.7664690.383235
2510.5508890.8982210.449111
2520.5521080.8957850.447892
2530.4827170.9654350.517283
2540.8174940.3650120.182506
2550.8073150.385370.192685
2560.7464920.5070170.253508
2570.9225850.1548310.0774155
2580.920020.1599610.0799805
2590.933280.1334390.0667196
2600.893550.2128990.10645
2610.8377470.3245060.162253
2620.7745520.4508970.225448
2630.7421690.5156620.257831
2640.8018070.3963850.198193
2650.7032720.5934560.296728
2660.5858810.8282370.414119
2670.6291890.7416220.370811

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.726409 & 0.547183 & 0.273591 \tabularnewline
12 & 0.917003 & 0.165994 & 0.0829972 \tabularnewline
13 & 0.869616 & 0.260767 & 0.130384 \tabularnewline
14 & 0.838883 & 0.322234 & 0.161117 \tabularnewline
15 & 0.767165 & 0.46567 & 0.232835 \tabularnewline
16 & 0.756094 & 0.487812 & 0.243906 \tabularnewline
17 & 0.686736 & 0.626528 & 0.313264 \tabularnewline
18 & 0.60821 & 0.783581 & 0.39179 \tabularnewline
19 & 0.62802 & 0.743961 & 0.37198 \tabularnewline
20 & 0.546631 & 0.906738 & 0.453369 \tabularnewline
21 & 0.48045 & 0.9609 & 0.51955 \tabularnewline
22 & 0.690465 & 0.619071 & 0.309535 \tabularnewline
23 & 0.667604 & 0.664791 & 0.332396 \tabularnewline
24 & 0.598455 & 0.80309 & 0.401545 \tabularnewline
25 & 0.577903 & 0.844194 & 0.422097 \tabularnewline
26 & 0.544286 & 0.911428 & 0.455714 \tabularnewline
27 & 0.493392 & 0.986783 & 0.506608 \tabularnewline
28 & 0.431077 & 0.862154 & 0.568923 \tabularnewline
29 & 0.369267 & 0.738534 & 0.630733 \tabularnewline
30 & 0.318138 & 0.636275 & 0.681862 \tabularnewline
31 & 0.46441 & 0.928819 & 0.53559 \tabularnewline
32 & 0.438084 & 0.876169 & 0.561916 \tabularnewline
33 & 0.384941 & 0.769882 & 0.615059 \tabularnewline
34 & 0.998204 & 0.00359108 & 0.00179554 \tabularnewline
35 & 0.997823 & 0.00435375 & 0.00217687 \tabularnewline
36 & 0.997119 & 0.00576231 & 0.00288115 \tabularnewline
37 & 0.998593 & 0.00281329 & 0.00140665 \tabularnewline
38 & 0.997943 & 0.00411454 & 0.00205727 \tabularnewline
39 & 0.996995 & 0.00600983 & 0.00300491 \tabularnewline
40 & 0.996231 & 0.00753847 & 0.00376923 \tabularnewline
41 & 0.995213 & 0.00957426 & 0.00478713 \tabularnewline
42 & 0.993788 & 0.0124245 & 0.00621226 \tabularnewline
43 & 0.992465 & 0.0150703 & 0.00753515 \tabularnewline
44 & 0.992198 & 0.0156047 & 0.00780234 \tabularnewline
45 & 0.989783 & 0.0204331 & 0.0102165 \tabularnewline
46 & 0.986109 & 0.0277829 & 0.0138914 \tabularnewline
47 & 0.982256 & 0.0354875 & 0.0177437 \tabularnewline
48 & 0.976942 & 0.0461162 & 0.0230581 \tabularnewline
49 & 0.972168 & 0.0556648 & 0.0278324 \tabularnewline
50 & 0.973117 & 0.0537656 & 0.0268828 \tabularnewline
51 & 0.980305 & 0.0393896 & 0.0196948 \tabularnewline
52 & 0.977502 & 0.0449965 & 0.0224982 \tabularnewline
53 & 0.971366 & 0.0572675 & 0.0286338 \tabularnewline
54 & 0.96905 & 0.0619006 & 0.0309503 \tabularnewline
55 & 0.97052 & 0.0589605 & 0.0294803 \tabularnewline
56 & 0.977352 & 0.0452951 & 0.0226476 \tabularnewline
57 & 0.985398 & 0.0292031 & 0.0146015 \tabularnewline
58 & 0.981747 & 0.0365052 & 0.0182526 \tabularnewline
59 & 0.980497 & 0.039006 & 0.019503 \tabularnewline
60 & 0.975041 & 0.0499177 & 0.0249588 \tabularnewline
61 & 0.969777 & 0.0604467 & 0.0302234 \tabularnewline
62 & 0.962192 & 0.0756165 & 0.0378083 \tabularnewline
63 & 0.953128 & 0.0937431 & 0.0468716 \tabularnewline
64 & 0.942449 & 0.115103 & 0.0575514 \tabularnewline
65 & 0.931261 & 0.137479 & 0.0687393 \tabularnewline
66 & 0.941135 & 0.117729 & 0.0588647 \tabularnewline
67 & 0.937476 & 0.125049 & 0.0625245 \tabularnewline
68 & 0.927204 & 0.145593 & 0.0727964 \tabularnewline
69 & 0.924065 & 0.151869 & 0.0759346 \tabularnewline
70 & 0.910805 & 0.17839 & 0.0891951 \tabularnewline
71 & 0.894317 & 0.211366 & 0.105683 \tabularnewline
72 & 0.877047 & 0.245906 & 0.122953 \tabularnewline
73 & 0.855755 & 0.288489 & 0.144245 \tabularnewline
74 & 0.843715 & 0.31257 & 0.156285 \tabularnewline
75 & 0.833186 & 0.333628 & 0.166814 \tabularnewline
76 & 0.826285 & 0.34743 & 0.173715 \tabularnewline
77 & 0.806126 & 0.387747 & 0.193874 \tabularnewline
78 & 0.780319 & 0.439363 & 0.219681 \tabularnewline
79 & 0.820333 & 0.359335 & 0.179667 \tabularnewline
80 & 0.80216 & 0.39568 & 0.19784 \tabularnewline
81 & 0.776353 & 0.447294 & 0.223647 \tabularnewline
82 & 0.753417 & 0.493166 & 0.246583 \tabularnewline
83 & 0.725452 & 0.549095 & 0.274548 \tabularnewline
84 & 0.698637 & 0.602725 & 0.301363 \tabularnewline
85 & 0.664598 & 0.670804 & 0.335402 \tabularnewline
86 & 0.629772 & 0.740455 & 0.370228 \tabularnewline
87 & 0.60796 & 0.78408 & 0.39204 \tabularnewline
88 & 0.574232 & 0.851535 & 0.425768 \tabularnewline
89 & 0.538112 & 0.923777 & 0.461888 \tabularnewline
90 & 0.50052 & 0.99896 & 0.49948 \tabularnewline
91 & 0.466117 & 0.932234 & 0.533883 \tabularnewline
92 & 0.429785 & 0.859569 & 0.570215 \tabularnewline
93 & 0.394247 & 0.788494 & 0.605753 \tabularnewline
94 & 0.388468 & 0.776937 & 0.611532 \tabularnewline
95 & 0.389018 & 0.778035 & 0.610982 \tabularnewline
96 & 0.38339 & 0.766779 & 0.61661 \tabularnewline
97 & 0.349738 & 0.699476 & 0.650262 \tabularnewline
98 & 0.334677 & 0.669355 & 0.665323 \tabularnewline
99 & 0.423837 & 0.847675 & 0.576163 \tabularnewline
100 & 0.38871 & 0.777421 & 0.61129 \tabularnewline
101 & 0.379137 & 0.758273 & 0.620863 \tabularnewline
102 & 0.380861 & 0.761722 & 0.619139 \tabularnewline
103 & 0.385518 & 0.771037 & 0.614482 \tabularnewline
104 & 0.392329 & 0.784658 & 0.607671 \tabularnewline
105 & 0.367592 & 0.735184 & 0.632408 \tabularnewline
106 & 0.334536 & 0.669072 & 0.665464 \tabularnewline
107 & 0.510698 & 0.978603 & 0.489302 \tabularnewline
108 & 0.498441 & 0.996882 & 0.501559 \tabularnewline
109 & 0.46278 & 0.925561 & 0.53722 \tabularnewline
110 & 0.429559 & 0.859118 & 0.570441 \tabularnewline
111 & 0.40084 & 0.80168 & 0.59916 \tabularnewline
112 & 0.369546 & 0.739093 & 0.630454 \tabularnewline
113 & 0.337154 & 0.674309 & 0.662846 \tabularnewline
114 & 0.724861 & 0.550278 & 0.275139 \tabularnewline
115 & 0.730315 & 0.53937 & 0.269685 \tabularnewline
116 & 0.786716 & 0.426568 & 0.213284 \tabularnewline
117 & 0.820377 & 0.359247 & 0.179623 \tabularnewline
118 & 0.883856 & 0.232287 & 0.116144 \tabularnewline
119 & 0.867757 & 0.264486 & 0.132243 \tabularnewline
120 & 0.848108 & 0.303783 & 0.151892 \tabularnewline
121 & 0.838094 & 0.323811 & 0.161906 \tabularnewline
122 & 0.818805 & 0.362391 & 0.181195 \tabularnewline
123 & 0.795405 & 0.409191 & 0.204595 \tabularnewline
124 & 0.774753 & 0.450494 & 0.225247 \tabularnewline
125 & 0.880175 & 0.23965 & 0.119825 \tabularnewline
126 & 0.87104 & 0.257919 & 0.12896 \tabularnewline
127 & 0.872235 & 0.25553 & 0.127765 \tabularnewline
128 & 0.856524 & 0.286953 & 0.143476 \tabularnewline
129 & 0.836169 & 0.327661 & 0.163831 \tabularnewline
130 & 0.82372 & 0.35256 & 0.17628 \tabularnewline
131 & 0.808221 & 0.383559 & 0.191779 \tabularnewline
132 & 0.784381 & 0.431237 & 0.215619 \tabularnewline
133 & 0.786174 & 0.427651 & 0.213826 \tabularnewline
134 & 0.807762 & 0.384477 & 0.192238 \tabularnewline
135 & 0.813483 & 0.373034 & 0.186517 \tabularnewline
136 & 0.813943 & 0.372115 & 0.186057 \tabularnewline
137 & 0.807522 & 0.384956 & 0.192478 \tabularnewline
138 & 0.806946 & 0.386107 & 0.193054 \tabularnewline
139 & 0.782086 & 0.435829 & 0.217914 \tabularnewline
140 & 0.8319 & 0.3362 & 0.1681 \tabularnewline
141 & 0.819874 & 0.360252 & 0.180126 \tabularnewline
142 & 0.798697 & 0.402606 & 0.201303 \tabularnewline
143 & 0.773569 & 0.452861 & 0.226431 \tabularnewline
144 & 0.800177 & 0.399645 & 0.199823 \tabularnewline
145 & 0.790616 & 0.418768 & 0.209384 \tabularnewline
146 & 0.765005 & 0.469989 & 0.234995 \tabularnewline
147 & 0.744647 & 0.510706 & 0.255353 \tabularnewline
148 & 0.720238 & 0.559523 & 0.279762 \tabularnewline
149 & 0.689939 & 0.620122 & 0.310061 \tabularnewline
150 & 0.670948 & 0.658104 & 0.329052 \tabularnewline
151 & 0.668535 & 0.662931 & 0.331465 \tabularnewline
152 & 0.636712 & 0.726577 & 0.363288 \tabularnewline
153 & 0.628333 & 0.743333 & 0.371667 \tabularnewline
154 & 0.637052 & 0.725896 & 0.362948 \tabularnewline
155 & 0.608489 & 0.783022 & 0.391511 \tabularnewline
156 & 0.734398 & 0.531205 & 0.265602 \tabularnewline
157 & 0.737973 & 0.524055 & 0.262027 \tabularnewline
158 & 0.745248 & 0.509503 & 0.254752 \tabularnewline
159 & 0.71647 & 0.56706 & 0.28353 \tabularnewline
160 & 0.719834 & 0.560332 & 0.280166 \tabularnewline
161 & 0.697241 & 0.605517 & 0.302759 \tabularnewline
162 & 0.670643 & 0.658714 & 0.329357 \tabularnewline
163 & 0.681038 & 0.637924 & 0.318962 \tabularnewline
164 & 0.651953 & 0.696094 & 0.348047 \tabularnewline
165 & 0.640789 & 0.718421 & 0.359211 \tabularnewline
166 & 0.651969 & 0.696062 & 0.348031 \tabularnewline
167 & 0.647146 & 0.705707 & 0.352854 \tabularnewline
168 & 0.614375 & 0.771251 & 0.385625 \tabularnewline
169 & 0.62277 & 0.754461 & 0.37723 \tabularnewline
170 & 0.614507 & 0.770987 & 0.385493 \tabularnewline
171 & 0.603182 & 0.793637 & 0.396818 \tabularnewline
172 & 0.596373 & 0.807253 & 0.403627 \tabularnewline
173 & 0.595917 & 0.808166 & 0.404083 \tabularnewline
174 & 0.578074 & 0.843851 & 0.421926 \tabularnewline
175 & 0.55075 & 0.8985 & 0.44925 \tabularnewline
176 & 0.51451 & 0.97098 & 0.48549 \tabularnewline
177 & 0.492733 & 0.985467 & 0.507267 \tabularnewline
178 & 0.527651 & 0.944699 & 0.472349 \tabularnewline
179 & 0.548402 & 0.903197 & 0.451598 \tabularnewline
180 & 0.519357 & 0.961287 & 0.480643 \tabularnewline
181 & 0.487273 & 0.974545 & 0.512727 \tabularnewline
182 & 0.451344 & 0.902688 & 0.548656 \tabularnewline
183 & 0.45149 & 0.90298 & 0.54851 \tabularnewline
184 & 0.417714 & 0.835429 & 0.582286 \tabularnewline
185 & 0.411888 & 0.823776 & 0.588112 \tabularnewline
186 & 0.438653 & 0.877305 & 0.561347 \tabularnewline
187 & 0.413543 & 0.827085 & 0.586457 \tabularnewline
188 & 0.378689 & 0.757378 & 0.621311 \tabularnewline
189 & 0.347753 & 0.695507 & 0.652247 \tabularnewline
190 & 0.319255 & 0.63851 & 0.680745 \tabularnewline
191 & 0.287364 & 0.574728 & 0.712636 \tabularnewline
192 & 0.291541 & 0.583081 & 0.708459 \tabularnewline
193 & 0.283855 & 0.567711 & 0.716145 \tabularnewline
194 & 0.254308 & 0.508616 & 0.745692 \tabularnewline
195 & 0.259705 & 0.519411 & 0.740295 \tabularnewline
196 & 0.23699 & 0.47398 & 0.76301 \tabularnewline
197 & 0.210982 & 0.421964 & 0.789018 \tabularnewline
198 & 0.231753 & 0.463506 & 0.768247 \tabularnewline
199 & 0.208814 & 0.417628 & 0.791186 \tabularnewline
200 & 0.191342 & 0.382683 & 0.808658 \tabularnewline
201 & 0.268446 & 0.536891 & 0.731554 \tabularnewline
202 & 0.238086 & 0.476173 & 0.761914 \tabularnewline
203 & 0.219646 & 0.439291 & 0.780354 \tabularnewline
204 & 0.294239 & 0.588479 & 0.705761 \tabularnewline
205 & 0.381735 & 0.763469 & 0.618265 \tabularnewline
206 & 0.412068 & 0.824136 & 0.587932 \tabularnewline
207 & 0.497958 & 0.995916 & 0.502042 \tabularnewline
208 & 0.607347 & 0.785305 & 0.392653 \tabularnewline
209 & 0.587055 & 0.825889 & 0.412945 \tabularnewline
210 & 0.556396 & 0.887207 & 0.443604 \tabularnewline
211 & 0.517532 & 0.964935 & 0.482468 \tabularnewline
212 & 0.551023 & 0.897954 & 0.448977 \tabularnewline
213 & 0.509177 & 0.981645 & 0.490823 \tabularnewline
214 & 0.469631 & 0.939261 & 0.530369 \tabularnewline
215 & 0.46087 & 0.92174 & 0.53913 \tabularnewline
216 & 0.427327 & 0.854655 & 0.572673 \tabularnewline
217 & 0.38645 & 0.772899 & 0.61355 \tabularnewline
218 & 0.34546 & 0.69092 & 0.65454 \tabularnewline
219 & 0.348564 & 0.697129 & 0.651436 \tabularnewline
220 & 0.338277 & 0.676554 & 0.661723 \tabularnewline
221 & 0.316558 & 0.633116 & 0.683442 \tabularnewline
222 & 0.302683 & 0.605365 & 0.697317 \tabularnewline
223 & 0.26842 & 0.53684 & 0.73158 \tabularnewline
224 & 0.23768 & 0.47536 & 0.76232 \tabularnewline
225 & 0.336904 & 0.673808 & 0.663096 \tabularnewline
226 & 0.319739 & 0.639478 & 0.680261 \tabularnewline
227 & 0.28014 & 0.56028 & 0.71986 \tabularnewline
228 & 0.248127 & 0.496254 & 0.751873 \tabularnewline
229 & 0.213244 & 0.426488 & 0.786756 \tabularnewline
230 & 0.181428 & 0.362855 & 0.818572 \tabularnewline
231 & 0.153752 & 0.307504 & 0.846248 \tabularnewline
232 & 0.426962 & 0.853925 & 0.573038 \tabularnewline
233 & 0.38807 & 0.776141 & 0.61193 \tabularnewline
234 & 0.341076 & 0.682153 & 0.658924 \tabularnewline
235 & 0.394331 & 0.788663 & 0.605669 \tabularnewline
236 & 0.346482 & 0.692965 & 0.653518 \tabularnewline
237 & 0.394388 & 0.788775 & 0.605612 \tabularnewline
238 & 0.390319 & 0.780637 & 0.609681 \tabularnewline
239 & 0.562342 & 0.875317 & 0.437658 \tabularnewline
240 & 0.62718 & 0.745641 & 0.37282 \tabularnewline
241 & 0.648366 & 0.703269 & 0.351634 \tabularnewline
242 & 0.598641 & 0.802718 & 0.401359 \tabularnewline
243 & 0.545339 & 0.909321 & 0.454661 \tabularnewline
244 & 0.488251 & 0.976502 & 0.511749 \tabularnewline
245 & 0.530829 & 0.938342 & 0.469171 \tabularnewline
246 & 0.498106 & 0.996212 & 0.501894 \tabularnewline
247 & 0.620032 & 0.759935 & 0.379968 \tabularnewline
248 & 0.699093 & 0.601813 & 0.300907 \tabularnewline
249 & 0.646854 & 0.706293 & 0.353146 \tabularnewline
250 & 0.616765 & 0.766469 & 0.383235 \tabularnewline
251 & 0.550889 & 0.898221 & 0.449111 \tabularnewline
252 & 0.552108 & 0.895785 & 0.447892 \tabularnewline
253 & 0.482717 & 0.965435 & 0.517283 \tabularnewline
254 & 0.817494 & 0.365012 & 0.182506 \tabularnewline
255 & 0.807315 & 0.38537 & 0.192685 \tabularnewline
256 & 0.746492 & 0.507017 & 0.253508 \tabularnewline
257 & 0.922585 & 0.154831 & 0.0774155 \tabularnewline
258 & 0.92002 & 0.159961 & 0.0799805 \tabularnewline
259 & 0.93328 & 0.133439 & 0.0667196 \tabularnewline
260 & 0.89355 & 0.212899 & 0.10645 \tabularnewline
261 & 0.837747 & 0.324506 & 0.162253 \tabularnewline
262 & 0.774552 & 0.450897 & 0.225448 \tabularnewline
263 & 0.742169 & 0.515662 & 0.257831 \tabularnewline
264 & 0.801807 & 0.396385 & 0.198193 \tabularnewline
265 & 0.703272 & 0.593456 & 0.296728 \tabularnewline
266 & 0.585881 & 0.828237 & 0.414119 \tabularnewline
267 & 0.629189 & 0.741622 & 0.370811 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264451&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.726409[/C][C]0.547183[/C][C]0.273591[/C][/ROW]
[ROW][C]12[/C][C]0.917003[/C][C]0.165994[/C][C]0.0829972[/C][/ROW]
[ROW][C]13[/C][C]0.869616[/C][C]0.260767[/C][C]0.130384[/C][/ROW]
[ROW][C]14[/C][C]0.838883[/C][C]0.322234[/C][C]0.161117[/C][/ROW]
[ROW][C]15[/C][C]0.767165[/C][C]0.46567[/C][C]0.232835[/C][/ROW]
[ROW][C]16[/C][C]0.756094[/C][C]0.487812[/C][C]0.243906[/C][/ROW]
[ROW][C]17[/C][C]0.686736[/C][C]0.626528[/C][C]0.313264[/C][/ROW]
[ROW][C]18[/C][C]0.60821[/C][C]0.783581[/C][C]0.39179[/C][/ROW]
[ROW][C]19[/C][C]0.62802[/C][C]0.743961[/C][C]0.37198[/C][/ROW]
[ROW][C]20[/C][C]0.546631[/C][C]0.906738[/C][C]0.453369[/C][/ROW]
[ROW][C]21[/C][C]0.48045[/C][C]0.9609[/C][C]0.51955[/C][/ROW]
[ROW][C]22[/C][C]0.690465[/C][C]0.619071[/C][C]0.309535[/C][/ROW]
[ROW][C]23[/C][C]0.667604[/C][C]0.664791[/C][C]0.332396[/C][/ROW]
[ROW][C]24[/C][C]0.598455[/C][C]0.80309[/C][C]0.401545[/C][/ROW]
[ROW][C]25[/C][C]0.577903[/C][C]0.844194[/C][C]0.422097[/C][/ROW]
[ROW][C]26[/C][C]0.544286[/C][C]0.911428[/C][C]0.455714[/C][/ROW]
[ROW][C]27[/C][C]0.493392[/C][C]0.986783[/C][C]0.506608[/C][/ROW]
[ROW][C]28[/C][C]0.431077[/C][C]0.862154[/C][C]0.568923[/C][/ROW]
[ROW][C]29[/C][C]0.369267[/C][C]0.738534[/C][C]0.630733[/C][/ROW]
[ROW][C]30[/C][C]0.318138[/C][C]0.636275[/C][C]0.681862[/C][/ROW]
[ROW][C]31[/C][C]0.46441[/C][C]0.928819[/C][C]0.53559[/C][/ROW]
[ROW][C]32[/C][C]0.438084[/C][C]0.876169[/C][C]0.561916[/C][/ROW]
[ROW][C]33[/C][C]0.384941[/C][C]0.769882[/C][C]0.615059[/C][/ROW]
[ROW][C]34[/C][C]0.998204[/C][C]0.00359108[/C][C]0.00179554[/C][/ROW]
[ROW][C]35[/C][C]0.997823[/C][C]0.00435375[/C][C]0.00217687[/C][/ROW]
[ROW][C]36[/C][C]0.997119[/C][C]0.00576231[/C][C]0.00288115[/C][/ROW]
[ROW][C]37[/C][C]0.998593[/C][C]0.00281329[/C][C]0.00140665[/C][/ROW]
[ROW][C]38[/C][C]0.997943[/C][C]0.00411454[/C][C]0.00205727[/C][/ROW]
[ROW][C]39[/C][C]0.996995[/C][C]0.00600983[/C][C]0.00300491[/C][/ROW]
[ROW][C]40[/C][C]0.996231[/C][C]0.00753847[/C][C]0.00376923[/C][/ROW]
[ROW][C]41[/C][C]0.995213[/C][C]0.00957426[/C][C]0.00478713[/C][/ROW]
[ROW][C]42[/C][C]0.993788[/C][C]0.0124245[/C][C]0.00621226[/C][/ROW]
[ROW][C]43[/C][C]0.992465[/C][C]0.0150703[/C][C]0.00753515[/C][/ROW]
[ROW][C]44[/C][C]0.992198[/C][C]0.0156047[/C][C]0.00780234[/C][/ROW]
[ROW][C]45[/C][C]0.989783[/C][C]0.0204331[/C][C]0.0102165[/C][/ROW]
[ROW][C]46[/C][C]0.986109[/C][C]0.0277829[/C][C]0.0138914[/C][/ROW]
[ROW][C]47[/C][C]0.982256[/C][C]0.0354875[/C][C]0.0177437[/C][/ROW]
[ROW][C]48[/C][C]0.976942[/C][C]0.0461162[/C][C]0.0230581[/C][/ROW]
[ROW][C]49[/C][C]0.972168[/C][C]0.0556648[/C][C]0.0278324[/C][/ROW]
[ROW][C]50[/C][C]0.973117[/C][C]0.0537656[/C][C]0.0268828[/C][/ROW]
[ROW][C]51[/C][C]0.980305[/C][C]0.0393896[/C][C]0.0196948[/C][/ROW]
[ROW][C]52[/C][C]0.977502[/C][C]0.0449965[/C][C]0.0224982[/C][/ROW]
[ROW][C]53[/C][C]0.971366[/C][C]0.0572675[/C][C]0.0286338[/C][/ROW]
[ROW][C]54[/C][C]0.96905[/C][C]0.0619006[/C][C]0.0309503[/C][/ROW]
[ROW][C]55[/C][C]0.97052[/C][C]0.0589605[/C][C]0.0294803[/C][/ROW]
[ROW][C]56[/C][C]0.977352[/C][C]0.0452951[/C][C]0.0226476[/C][/ROW]
[ROW][C]57[/C][C]0.985398[/C][C]0.0292031[/C][C]0.0146015[/C][/ROW]
[ROW][C]58[/C][C]0.981747[/C][C]0.0365052[/C][C]0.0182526[/C][/ROW]
[ROW][C]59[/C][C]0.980497[/C][C]0.039006[/C][C]0.019503[/C][/ROW]
[ROW][C]60[/C][C]0.975041[/C][C]0.0499177[/C][C]0.0249588[/C][/ROW]
[ROW][C]61[/C][C]0.969777[/C][C]0.0604467[/C][C]0.0302234[/C][/ROW]
[ROW][C]62[/C][C]0.962192[/C][C]0.0756165[/C][C]0.0378083[/C][/ROW]
[ROW][C]63[/C][C]0.953128[/C][C]0.0937431[/C][C]0.0468716[/C][/ROW]
[ROW][C]64[/C][C]0.942449[/C][C]0.115103[/C][C]0.0575514[/C][/ROW]
[ROW][C]65[/C][C]0.931261[/C][C]0.137479[/C][C]0.0687393[/C][/ROW]
[ROW][C]66[/C][C]0.941135[/C][C]0.117729[/C][C]0.0588647[/C][/ROW]
[ROW][C]67[/C][C]0.937476[/C][C]0.125049[/C][C]0.0625245[/C][/ROW]
[ROW][C]68[/C][C]0.927204[/C][C]0.145593[/C][C]0.0727964[/C][/ROW]
[ROW][C]69[/C][C]0.924065[/C][C]0.151869[/C][C]0.0759346[/C][/ROW]
[ROW][C]70[/C][C]0.910805[/C][C]0.17839[/C][C]0.0891951[/C][/ROW]
[ROW][C]71[/C][C]0.894317[/C][C]0.211366[/C][C]0.105683[/C][/ROW]
[ROW][C]72[/C][C]0.877047[/C][C]0.245906[/C][C]0.122953[/C][/ROW]
[ROW][C]73[/C][C]0.855755[/C][C]0.288489[/C][C]0.144245[/C][/ROW]
[ROW][C]74[/C][C]0.843715[/C][C]0.31257[/C][C]0.156285[/C][/ROW]
[ROW][C]75[/C][C]0.833186[/C][C]0.333628[/C][C]0.166814[/C][/ROW]
[ROW][C]76[/C][C]0.826285[/C][C]0.34743[/C][C]0.173715[/C][/ROW]
[ROW][C]77[/C][C]0.806126[/C][C]0.387747[/C][C]0.193874[/C][/ROW]
[ROW][C]78[/C][C]0.780319[/C][C]0.439363[/C][C]0.219681[/C][/ROW]
[ROW][C]79[/C][C]0.820333[/C][C]0.359335[/C][C]0.179667[/C][/ROW]
[ROW][C]80[/C][C]0.80216[/C][C]0.39568[/C][C]0.19784[/C][/ROW]
[ROW][C]81[/C][C]0.776353[/C][C]0.447294[/C][C]0.223647[/C][/ROW]
[ROW][C]82[/C][C]0.753417[/C][C]0.493166[/C][C]0.246583[/C][/ROW]
[ROW][C]83[/C][C]0.725452[/C][C]0.549095[/C][C]0.274548[/C][/ROW]
[ROW][C]84[/C][C]0.698637[/C][C]0.602725[/C][C]0.301363[/C][/ROW]
[ROW][C]85[/C][C]0.664598[/C][C]0.670804[/C][C]0.335402[/C][/ROW]
[ROW][C]86[/C][C]0.629772[/C][C]0.740455[/C][C]0.370228[/C][/ROW]
[ROW][C]87[/C][C]0.60796[/C][C]0.78408[/C][C]0.39204[/C][/ROW]
[ROW][C]88[/C][C]0.574232[/C][C]0.851535[/C][C]0.425768[/C][/ROW]
[ROW][C]89[/C][C]0.538112[/C][C]0.923777[/C][C]0.461888[/C][/ROW]
[ROW][C]90[/C][C]0.50052[/C][C]0.99896[/C][C]0.49948[/C][/ROW]
[ROW][C]91[/C][C]0.466117[/C][C]0.932234[/C][C]0.533883[/C][/ROW]
[ROW][C]92[/C][C]0.429785[/C][C]0.859569[/C][C]0.570215[/C][/ROW]
[ROW][C]93[/C][C]0.394247[/C][C]0.788494[/C][C]0.605753[/C][/ROW]
[ROW][C]94[/C][C]0.388468[/C][C]0.776937[/C][C]0.611532[/C][/ROW]
[ROW][C]95[/C][C]0.389018[/C][C]0.778035[/C][C]0.610982[/C][/ROW]
[ROW][C]96[/C][C]0.38339[/C][C]0.766779[/C][C]0.61661[/C][/ROW]
[ROW][C]97[/C][C]0.349738[/C][C]0.699476[/C][C]0.650262[/C][/ROW]
[ROW][C]98[/C][C]0.334677[/C][C]0.669355[/C][C]0.665323[/C][/ROW]
[ROW][C]99[/C][C]0.423837[/C][C]0.847675[/C][C]0.576163[/C][/ROW]
[ROW][C]100[/C][C]0.38871[/C][C]0.777421[/C][C]0.61129[/C][/ROW]
[ROW][C]101[/C][C]0.379137[/C][C]0.758273[/C][C]0.620863[/C][/ROW]
[ROW][C]102[/C][C]0.380861[/C][C]0.761722[/C][C]0.619139[/C][/ROW]
[ROW][C]103[/C][C]0.385518[/C][C]0.771037[/C][C]0.614482[/C][/ROW]
[ROW][C]104[/C][C]0.392329[/C][C]0.784658[/C][C]0.607671[/C][/ROW]
[ROW][C]105[/C][C]0.367592[/C][C]0.735184[/C][C]0.632408[/C][/ROW]
[ROW][C]106[/C][C]0.334536[/C][C]0.669072[/C][C]0.665464[/C][/ROW]
[ROW][C]107[/C][C]0.510698[/C][C]0.978603[/C][C]0.489302[/C][/ROW]
[ROW][C]108[/C][C]0.498441[/C][C]0.996882[/C][C]0.501559[/C][/ROW]
[ROW][C]109[/C][C]0.46278[/C][C]0.925561[/C][C]0.53722[/C][/ROW]
[ROW][C]110[/C][C]0.429559[/C][C]0.859118[/C][C]0.570441[/C][/ROW]
[ROW][C]111[/C][C]0.40084[/C][C]0.80168[/C][C]0.59916[/C][/ROW]
[ROW][C]112[/C][C]0.369546[/C][C]0.739093[/C][C]0.630454[/C][/ROW]
[ROW][C]113[/C][C]0.337154[/C][C]0.674309[/C][C]0.662846[/C][/ROW]
[ROW][C]114[/C][C]0.724861[/C][C]0.550278[/C][C]0.275139[/C][/ROW]
[ROW][C]115[/C][C]0.730315[/C][C]0.53937[/C][C]0.269685[/C][/ROW]
[ROW][C]116[/C][C]0.786716[/C][C]0.426568[/C][C]0.213284[/C][/ROW]
[ROW][C]117[/C][C]0.820377[/C][C]0.359247[/C][C]0.179623[/C][/ROW]
[ROW][C]118[/C][C]0.883856[/C][C]0.232287[/C][C]0.116144[/C][/ROW]
[ROW][C]119[/C][C]0.867757[/C][C]0.264486[/C][C]0.132243[/C][/ROW]
[ROW][C]120[/C][C]0.848108[/C][C]0.303783[/C][C]0.151892[/C][/ROW]
[ROW][C]121[/C][C]0.838094[/C][C]0.323811[/C][C]0.161906[/C][/ROW]
[ROW][C]122[/C][C]0.818805[/C][C]0.362391[/C][C]0.181195[/C][/ROW]
[ROW][C]123[/C][C]0.795405[/C][C]0.409191[/C][C]0.204595[/C][/ROW]
[ROW][C]124[/C][C]0.774753[/C][C]0.450494[/C][C]0.225247[/C][/ROW]
[ROW][C]125[/C][C]0.880175[/C][C]0.23965[/C][C]0.119825[/C][/ROW]
[ROW][C]126[/C][C]0.87104[/C][C]0.257919[/C][C]0.12896[/C][/ROW]
[ROW][C]127[/C][C]0.872235[/C][C]0.25553[/C][C]0.127765[/C][/ROW]
[ROW][C]128[/C][C]0.856524[/C][C]0.286953[/C][C]0.143476[/C][/ROW]
[ROW][C]129[/C][C]0.836169[/C][C]0.327661[/C][C]0.163831[/C][/ROW]
[ROW][C]130[/C][C]0.82372[/C][C]0.35256[/C][C]0.17628[/C][/ROW]
[ROW][C]131[/C][C]0.808221[/C][C]0.383559[/C][C]0.191779[/C][/ROW]
[ROW][C]132[/C][C]0.784381[/C][C]0.431237[/C][C]0.215619[/C][/ROW]
[ROW][C]133[/C][C]0.786174[/C][C]0.427651[/C][C]0.213826[/C][/ROW]
[ROW][C]134[/C][C]0.807762[/C][C]0.384477[/C][C]0.192238[/C][/ROW]
[ROW][C]135[/C][C]0.813483[/C][C]0.373034[/C][C]0.186517[/C][/ROW]
[ROW][C]136[/C][C]0.813943[/C][C]0.372115[/C][C]0.186057[/C][/ROW]
[ROW][C]137[/C][C]0.807522[/C][C]0.384956[/C][C]0.192478[/C][/ROW]
[ROW][C]138[/C][C]0.806946[/C][C]0.386107[/C][C]0.193054[/C][/ROW]
[ROW][C]139[/C][C]0.782086[/C][C]0.435829[/C][C]0.217914[/C][/ROW]
[ROW][C]140[/C][C]0.8319[/C][C]0.3362[/C][C]0.1681[/C][/ROW]
[ROW][C]141[/C][C]0.819874[/C][C]0.360252[/C][C]0.180126[/C][/ROW]
[ROW][C]142[/C][C]0.798697[/C][C]0.402606[/C][C]0.201303[/C][/ROW]
[ROW][C]143[/C][C]0.773569[/C][C]0.452861[/C][C]0.226431[/C][/ROW]
[ROW][C]144[/C][C]0.800177[/C][C]0.399645[/C][C]0.199823[/C][/ROW]
[ROW][C]145[/C][C]0.790616[/C][C]0.418768[/C][C]0.209384[/C][/ROW]
[ROW][C]146[/C][C]0.765005[/C][C]0.469989[/C][C]0.234995[/C][/ROW]
[ROW][C]147[/C][C]0.744647[/C][C]0.510706[/C][C]0.255353[/C][/ROW]
[ROW][C]148[/C][C]0.720238[/C][C]0.559523[/C][C]0.279762[/C][/ROW]
[ROW][C]149[/C][C]0.689939[/C][C]0.620122[/C][C]0.310061[/C][/ROW]
[ROW][C]150[/C][C]0.670948[/C][C]0.658104[/C][C]0.329052[/C][/ROW]
[ROW][C]151[/C][C]0.668535[/C][C]0.662931[/C][C]0.331465[/C][/ROW]
[ROW][C]152[/C][C]0.636712[/C][C]0.726577[/C][C]0.363288[/C][/ROW]
[ROW][C]153[/C][C]0.628333[/C][C]0.743333[/C][C]0.371667[/C][/ROW]
[ROW][C]154[/C][C]0.637052[/C][C]0.725896[/C][C]0.362948[/C][/ROW]
[ROW][C]155[/C][C]0.608489[/C][C]0.783022[/C][C]0.391511[/C][/ROW]
[ROW][C]156[/C][C]0.734398[/C][C]0.531205[/C][C]0.265602[/C][/ROW]
[ROW][C]157[/C][C]0.737973[/C][C]0.524055[/C][C]0.262027[/C][/ROW]
[ROW][C]158[/C][C]0.745248[/C][C]0.509503[/C][C]0.254752[/C][/ROW]
[ROW][C]159[/C][C]0.71647[/C][C]0.56706[/C][C]0.28353[/C][/ROW]
[ROW][C]160[/C][C]0.719834[/C][C]0.560332[/C][C]0.280166[/C][/ROW]
[ROW][C]161[/C][C]0.697241[/C][C]0.605517[/C][C]0.302759[/C][/ROW]
[ROW][C]162[/C][C]0.670643[/C][C]0.658714[/C][C]0.329357[/C][/ROW]
[ROW][C]163[/C][C]0.681038[/C][C]0.637924[/C][C]0.318962[/C][/ROW]
[ROW][C]164[/C][C]0.651953[/C][C]0.696094[/C][C]0.348047[/C][/ROW]
[ROW][C]165[/C][C]0.640789[/C][C]0.718421[/C][C]0.359211[/C][/ROW]
[ROW][C]166[/C][C]0.651969[/C][C]0.696062[/C][C]0.348031[/C][/ROW]
[ROW][C]167[/C][C]0.647146[/C][C]0.705707[/C][C]0.352854[/C][/ROW]
[ROW][C]168[/C][C]0.614375[/C][C]0.771251[/C][C]0.385625[/C][/ROW]
[ROW][C]169[/C][C]0.62277[/C][C]0.754461[/C][C]0.37723[/C][/ROW]
[ROW][C]170[/C][C]0.614507[/C][C]0.770987[/C][C]0.385493[/C][/ROW]
[ROW][C]171[/C][C]0.603182[/C][C]0.793637[/C][C]0.396818[/C][/ROW]
[ROW][C]172[/C][C]0.596373[/C][C]0.807253[/C][C]0.403627[/C][/ROW]
[ROW][C]173[/C][C]0.595917[/C][C]0.808166[/C][C]0.404083[/C][/ROW]
[ROW][C]174[/C][C]0.578074[/C][C]0.843851[/C][C]0.421926[/C][/ROW]
[ROW][C]175[/C][C]0.55075[/C][C]0.8985[/C][C]0.44925[/C][/ROW]
[ROW][C]176[/C][C]0.51451[/C][C]0.97098[/C][C]0.48549[/C][/ROW]
[ROW][C]177[/C][C]0.492733[/C][C]0.985467[/C][C]0.507267[/C][/ROW]
[ROW][C]178[/C][C]0.527651[/C][C]0.944699[/C][C]0.472349[/C][/ROW]
[ROW][C]179[/C][C]0.548402[/C][C]0.903197[/C][C]0.451598[/C][/ROW]
[ROW][C]180[/C][C]0.519357[/C][C]0.961287[/C][C]0.480643[/C][/ROW]
[ROW][C]181[/C][C]0.487273[/C][C]0.974545[/C][C]0.512727[/C][/ROW]
[ROW][C]182[/C][C]0.451344[/C][C]0.902688[/C][C]0.548656[/C][/ROW]
[ROW][C]183[/C][C]0.45149[/C][C]0.90298[/C][C]0.54851[/C][/ROW]
[ROW][C]184[/C][C]0.417714[/C][C]0.835429[/C][C]0.582286[/C][/ROW]
[ROW][C]185[/C][C]0.411888[/C][C]0.823776[/C][C]0.588112[/C][/ROW]
[ROW][C]186[/C][C]0.438653[/C][C]0.877305[/C][C]0.561347[/C][/ROW]
[ROW][C]187[/C][C]0.413543[/C][C]0.827085[/C][C]0.586457[/C][/ROW]
[ROW][C]188[/C][C]0.378689[/C][C]0.757378[/C][C]0.621311[/C][/ROW]
[ROW][C]189[/C][C]0.347753[/C][C]0.695507[/C][C]0.652247[/C][/ROW]
[ROW][C]190[/C][C]0.319255[/C][C]0.63851[/C][C]0.680745[/C][/ROW]
[ROW][C]191[/C][C]0.287364[/C][C]0.574728[/C][C]0.712636[/C][/ROW]
[ROW][C]192[/C][C]0.291541[/C][C]0.583081[/C][C]0.708459[/C][/ROW]
[ROW][C]193[/C][C]0.283855[/C][C]0.567711[/C][C]0.716145[/C][/ROW]
[ROW][C]194[/C][C]0.254308[/C][C]0.508616[/C][C]0.745692[/C][/ROW]
[ROW][C]195[/C][C]0.259705[/C][C]0.519411[/C][C]0.740295[/C][/ROW]
[ROW][C]196[/C][C]0.23699[/C][C]0.47398[/C][C]0.76301[/C][/ROW]
[ROW][C]197[/C][C]0.210982[/C][C]0.421964[/C][C]0.789018[/C][/ROW]
[ROW][C]198[/C][C]0.231753[/C][C]0.463506[/C][C]0.768247[/C][/ROW]
[ROW][C]199[/C][C]0.208814[/C][C]0.417628[/C][C]0.791186[/C][/ROW]
[ROW][C]200[/C][C]0.191342[/C][C]0.382683[/C][C]0.808658[/C][/ROW]
[ROW][C]201[/C][C]0.268446[/C][C]0.536891[/C][C]0.731554[/C][/ROW]
[ROW][C]202[/C][C]0.238086[/C][C]0.476173[/C][C]0.761914[/C][/ROW]
[ROW][C]203[/C][C]0.219646[/C][C]0.439291[/C][C]0.780354[/C][/ROW]
[ROW][C]204[/C][C]0.294239[/C][C]0.588479[/C][C]0.705761[/C][/ROW]
[ROW][C]205[/C][C]0.381735[/C][C]0.763469[/C][C]0.618265[/C][/ROW]
[ROW][C]206[/C][C]0.412068[/C][C]0.824136[/C][C]0.587932[/C][/ROW]
[ROW][C]207[/C][C]0.497958[/C][C]0.995916[/C][C]0.502042[/C][/ROW]
[ROW][C]208[/C][C]0.607347[/C][C]0.785305[/C][C]0.392653[/C][/ROW]
[ROW][C]209[/C][C]0.587055[/C][C]0.825889[/C][C]0.412945[/C][/ROW]
[ROW][C]210[/C][C]0.556396[/C][C]0.887207[/C][C]0.443604[/C][/ROW]
[ROW][C]211[/C][C]0.517532[/C][C]0.964935[/C][C]0.482468[/C][/ROW]
[ROW][C]212[/C][C]0.551023[/C][C]0.897954[/C][C]0.448977[/C][/ROW]
[ROW][C]213[/C][C]0.509177[/C][C]0.981645[/C][C]0.490823[/C][/ROW]
[ROW][C]214[/C][C]0.469631[/C][C]0.939261[/C][C]0.530369[/C][/ROW]
[ROW][C]215[/C][C]0.46087[/C][C]0.92174[/C][C]0.53913[/C][/ROW]
[ROW][C]216[/C][C]0.427327[/C][C]0.854655[/C][C]0.572673[/C][/ROW]
[ROW][C]217[/C][C]0.38645[/C][C]0.772899[/C][C]0.61355[/C][/ROW]
[ROW][C]218[/C][C]0.34546[/C][C]0.69092[/C][C]0.65454[/C][/ROW]
[ROW][C]219[/C][C]0.348564[/C][C]0.697129[/C][C]0.651436[/C][/ROW]
[ROW][C]220[/C][C]0.338277[/C][C]0.676554[/C][C]0.661723[/C][/ROW]
[ROW][C]221[/C][C]0.316558[/C][C]0.633116[/C][C]0.683442[/C][/ROW]
[ROW][C]222[/C][C]0.302683[/C][C]0.605365[/C][C]0.697317[/C][/ROW]
[ROW][C]223[/C][C]0.26842[/C][C]0.53684[/C][C]0.73158[/C][/ROW]
[ROW][C]224[/C][C]0.23768[/C][C]0.47536[/C][C]0.76232[/C][/ROW]
[ROW][C]225[/C][C]0.336904[/C][C]0.673808[/C][C]0.663096[/C][/ROW]
[ROW][C]226[/C][C]0.319739[/C][C]0.639478[/C][C]0.680261[/C][/ROW]
[ROW][C]227[/C][C]0.28014[/C][C]0.56028[/C][C]0.71986[/C][/ROW]
[ROW][C]228[/C][C]0.248127[/C][C]0.496254[/C][C]0.751873[/C][/ROW]
[ROW][C]229[/C][C]0.213244[/C][C]0.426488[/C][C]0.786756[/C][/ROW]
[ROW][C]230[/C][C]0.181428[/C][C]0.362855[/C][C]0.818572[/C][/ROW]
[ROW][C]231[/C][C]0.153752[/C][C]0.307504[/C][C]0.846248[/C][/ROW]
[ROW][C]232[/C][C]0.426962[/C][C]0.853925[/C][C]0.573038[/C][/ROW]
[ROW][C]233[/C][C]0.38807[/C][C]0.776141[/C][C]0.61193[/C][/ROW]
[ROW][C]234[/C][C]0.341076[/C][C]0.682153[/C][C]0.658924[/C][/ROW]
[ROW][C]235[/C][C]0.394331[/C][C]0.788663[/C][C]0.605669[/C][/ROW]
[ROW][C]236[/C][C]0.346482[/C][C]0.692965[/C][C]0.653518[/C][/ROW]
[ROW][C]237[/C][C]0.394388[/C][C]0.788775[/C][C]0.605612[/C][/ROW]
[ROW][C]238[/C][C]0.390319[/C][C]0.780637[/C][C]0.609681[/C][/ROW]
[ROW][C]239[/C][C]0.562342[/C][C]0.875317[/C][C]0.437658[/C][/ROW]
[ROW][C]240[/C][C]0.62718[/C][C]0.745641[/C][C]0.37282[/C][/ROW]
[ROW][C]241[/C][C]0.648366[/C][C]0.703269[/C][C]0.351634[/C][/ROW]
[ROW][C]242[/C][C]0.598641[/C][C]0.802718[/C][C]0.401359[/C][/ROW]
[ROW][C]243[/C][C]0.545339[/C][C]0.909321[/C][C]0.454661[/C][/ROW]
[ROW][C]244[/C][C]0.488251[/C][C]0.976502[/C][C]0.511749[/C][/ROW]
[ROW][C]245[/C][C]0.530829[/C][C]0.938342[/C][C]0.469171[/C][/ROW]
[ROW][C]246[/C][C]0.498106[/C][C]0.996212[/C][C]0.501894[/C][/ROW]
[ROW][C]247[/C][C]0.620032[/C][C]0.759935[/C][C]0.379968[/C][/ROW]
[ROW][C]248[/C][C]0.699093[/C][C]0.601813[/C][C]0.300907[/C][/ROW]
[ROW][C]249[/C][C]0.646854[/C][C]0.706293[/C][C]0.353146[/C][/ROW]
[ROW][C]250[/C][C]0.616765[/C][C]0.766469[/C][C]0.383235[/C][/ROW]
[ROW][C]251[/C][C]0.550889[/C][C]0.898221[/C][C]0.449111[/C][/ROW]
[ROW][C]252[/C][C]0.552108[/C][C]0.895785[/C][C]0.447892[/C][/ROW]
[ROW][C]253[/C][C]0.482717[/C][C]0.965435[/C][C]0.517283[/C][/ROW]
[ROW][C]254[/C][C]0.817494[/C][C]0.365012[/C][C]0.182506[/C][/ROW]
[ROW][C]255[/C][C]0.807315[/C][C]0.38537[/C][C]0.192685[/C][/ROW]
[ROW][C]256[/C][C]0.746492[/C][C]0.507017[/C][C]0.253508[/C][/ROW]
[ROW][C]257[/C][C]0.922585[/C][C]0.154831[/C][C]0.0774155[/C][/ROW]
[ROW][C]258[/C][C]0.92002[/C][C]0.159961[/C][C]0.0799805[/C][/ROW]
[ROW][C]259[/C][C]0.93328[/C][C]0.133439[/C][C]0.0667196[/C][/ROW]
[ROW][C]260[/C][C]0.89355[/C][C]0.212899[/C][C]0.10645[/C][/ROW]
[ROW][C]261[/C][C]0.837747[/C][C]0.324506[/C][C]0.162253[/C][/ROW]
[ROW][C]262[/C][C]0.774552[/C][C]0.450897[/C][C]0.225448[/C][/ROW]
[ROW][C]263[/C][C]0.742169[/C][C]0.515662[/C][C]0.257831[/C][/ROW]
[ROW][C]264[/C][C]0.801807[/C][C]0.396385[/C][C]0.198193[/C][/ROW]
[ROW][C]265[/C][C]0.703272[/C][C]0.593456[/C][C]0.296728[/C][/ROW]
[ROW][C]266[/C][C]0.585881[/C][C]0.828237[/C][C]0.414119[/C][/ROW]
[ROW][C]267[/C][C]0.629189[/C][C]0.741622[/C][C]0.370811[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264451&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264451&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.7264090.5471830.273591
120.9170030.1659940.0829972
130.8696160.2607670.130384
140.8388830.3222340.161117
150.7671650.465670.232835
160.7560940.4878120.243906
170.6867360.6265280.313264
180.608210.7835810.39179
190.628020.7439610.37198
200.5466310.9067380.453369
210.480450.96090.51955
220.6904650.6190710.309535
230.6676040.6647910.332396
240.5984550.803090.401545
250.5779030.8441940.422097
260.5442860.9114280.455714
270.4933920.9867830.506608
280.4310770.8621540.568923
290.3692670.7385340.630733
300.3181380.6362750.681862
310.464410.9288190.53559
320.4380840.8761690.561916
330.3849410.7698820.615059
340.9982040.003591080.00179554
350.9978230.004353750.00217687
360.9971190.005762310.00288115
370.9985930.002813290.00140665
380.9979430.004114540.00205727
390.9969950.006009830.00300491
400.9962310.007538470.00376923
410.9952130.009574260.00478713
420.9937880.01242450.00621226
430.9924650.01507030.00753515
440.9921980.01560470.00780234
450.9897830.02043310.0102165
460.9861090.02778290.0138914
470.9822560.03548750.0177437
480.9769420.04611620.0230581
490.9721680.05566480.0278324
500.9731170.05376560.0268828
510.9803050.03938960.0196948
520.9775020.04499650.0224982
530.9713660.05726750.0286338
540.969050.06190060.0309503
550.970520.05896050.0294803
560.9773520.04529510.0226476
570.9853980.02920310.0146015
580.9817470.03650520.0182526
590.9804970.0390060.019503
600.9750410.04991770.0249588
610.9697770.06044670.0302234
620.9621920.07561650.0378083
630.9531280.09374310.0468716
640.9424490.1151030.0575514
650.9312610.1374790.0687393
660.9411350.1177290.0588647
670.9374760.1250490.0625245
680.9272040.1455930.0727964
690.9240650.1518690.0759346
700.9108050.178390.0891951
710.8943170.2113660.105683
720.8770470.2459060.122953
730.8557550.2884890.144245
740.8437150.312570.156285
750.8331860.3336280.166814
760.8262850.347430.173715
770.8061260.3877470.193874
780.7803190.4393630.219681
790.8203330.3593350.179667
800.802160.395680.19784
810.7763530.4472940.223647
820.7534170.4931660.246583
830.7254520.5490950.274548
840.6986370.6027250.301363
850.6645980.6708040.335402
860.6297720.7404550.370228
870.607960.784080.39204
880.5742320.8515350.425768
890.5381120.9237770.461888
900.500520.998960.49948
910.4661170.9322340.533883
920.4297850.8595690.570215
930.3942470.7884940.605753
940.3884680.7769370.611532
950.3890180.7780350.610982
960.383390.7667790.61661
970.3497380.6994760.650262
980.3346770.6693550.665323
990.4238370.8476750.576163
1000.388710.7774210.61129
1010.3791370.7582730.620863
1020.3808610.7617220.619139
1030.3855180.7710370.614482
1040.3923290.7846580.607671
1050.3675920.7351840.632408
1060.3345360.6690720.665464
1070.5106980.9786030.489302
1080.4984410.9968820.501559
1090.462780.9255610.53722
1100.4295590.8591180.570441
1110.400840.801680.59916
1120.3695460.7390930.630454
1130.3371540.6743090.662846
1140.7248610.5502780.275139
1150.7303150.539370.269685
1160.7867160.4265680.213284
1170.8203770.3592470.179623
1180.8838560.2322870.116144
1190.8677570.2644860.132243
1200.8481080.3037830.151892
1210.8380940.3238110.161906
1220.8188050.3623910.181195
1230.7954050.4091910.204595
1240.7747530.4504940.225247
1250.8801750.239650.119825
1260.871040.2579190.12896
1270.8722350.255530.127765
1280.8565240.2869530.143476
1290.8361690.3276610.163831
1300.823720.352560.17628
1310.8082210.3835590.191779
1320.7843810.4312370.215619
1330.7861740.4276510.213826
1340.8077620.3844770.192238
1350.8134830.3730340.186517
1360.8139430.3721150.186057
1370.8075220.3849560.192478
1380.8069460.3861070.193054
1390.7820860.4358290.217914
1400.83190.33620.1681
1410.8198740.3602520.180126
1420.7986970.4026060.201303
1430.7735690.4528610.226431
1440.8001770.3996450.199823
1450.7906160.4187680.209384
1460.7650050.4699890.234995
1470.7446470.5107060.255353
1480.7202380.5595230.279762
1490.6899390.6201220.310061
1500.6709480.6581040.329052
1510.6685350.6629310.331465
1520.6367120.7265770.363288
1530.6283330.7433330.371667
1540.6370520.7258960.362948
1550.6084890.7830220.391511
1560.7343980.5312050.265602
1570.7379730.5240550.262027
1580.7452480.5095030.254752
1590.716470.567060.28353
1600.7198340.5603320.280166
1610.6972410.6055170.302759
1620.6706430.6587140.329357
1630.6810380.6379240.318962
1640.6519530.6960940.348047
1650.6407890.7184210.359211
1660.6519690.6960620.348031
1670.6471460.7057070.352854
1680.6143750.7712510.385625
1690.622770.7544610.37723
1700.6145070.7709870.385493
1710.6031820.7936370.396818
1720.5963730.8072530.403627
1730.5959170.8081660.404083
1740.5780740.8438510.421926
1750.550750.89850.44925
1760.514510.970980.48549
1770.4927330.9854670.507267
1780.5276510.9446990.472349
1790.5484020.9031970.451598
1800.5193570.9612870.480643
1810.4872730.9745450.512727
1820.4513440.9026880.548656
1830.451490.902980.54851
1840.4177140.8354290.582286
1850.4118880.8237760.588112
1860.4386530.8773050.561347
1870.4135430.8270850.586457
1880.3786890.7573780.621311
1890.3477530.6955070.652247
1900.3192550.638510.680745
1910.2873640.5747280.712636
1920.2915410.5830810.708459
1930.2838550.5677110.716145
1940.2543080.5086160.745692
1950.2597050.5194110.740295
1960.236990.473980.76301
1970.2109820.4219640.789018
1980.2317530.4635060.768247
1990.2088140.4176280.791186
2000.1913420.3826830.808658
2010.2684460.5368910.731554
2020.2380860.4761730.761914
2030.2196460.4392910.780354
2040.2942390.5884790.705761
2050.3817350.7634690.618265
2060.4120680.8241360.587932
2070.4979580.9959160.502042
2080.6073470.7853050.392653
2090.5870550.8258890.412945
2100.5563960.8872070.443604
2110.5175320.9649350.482468
2120.5510230.8979540.448977
2130.5091770.9816450.490823
2140.4696310.9392610.530369
2150.460870.921740.53913
2160.4273270.8546550.572673
2170.386450.7728990.61355
2180.345460.690920.65454
2190.3485640.6971290.651436
2200.3382770.6765540.661723
2210.3165580.6331160.683442
2220.3026830.6053650.697317
2230.268420.536840.73158
2240.237680.475360.76232
2250.3369040.6738080.663096
2260.3197390.6394780.680261
2270.280140.560280.71986
2280.2481270.4962540.751873
2290.2132440.4264880.786756
2300.1814280.3628550.818572
2310.1537520.3075040.846248
2320.4269620.8539250.573038
2330.388070.7761410.61193
2340.3410760.6821530.658924
2350.3943310.7886630.605669
2360.3464820.6929650.653518
2370.3943880.7887750.605612
2380.3903190.7806370.609681
2390.5623420.8753170.437658
2400.627180.7456410.37282
2410.6483660.7032690.351634
2420.5986410.8027180.401359
2430.5453390.9093210.454661
2440.4882510.9765020.511749
2450.5308290.9383420.469171
2460.4981060.9962120.501894
2470.6200320.7599350.379968
2480.6990930.6018130.300907
2490.6468540.7062930.353146
2500.6167650.7664690.383235
2510.5508890.8982210.449111
2520.5521080.8957850.447892
2530.4827170.9654350.517283
2540.8174940.3650120.182506
2550.8073150.385370.192685
2560.7464920.5070170.253508
2570.9225850.1548310.0774155
2580.920020.1599610.0799805
2590.933280.1334390.0667196
2600.893550.2128990.10645
2610.8377470.3245060.162253
2620.7745520.4508970.225448
2630.7421690.5156620.257831
2640.8018070.3963850.198193
2650.7032720.5934560.296728
2660.5858810.8282370.414119
2670.6291890.7416220.370811






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level80.0311284NOK
5% type I error level220.0856031NOK
10% type I error level300.116732NOK

\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 & 8 & 0.0311284 & NOK \tabularnewline
5% type I error level & 22 & 0.0856031 & NOK \tabularnewline
10% type I error level & 30 & 0.116732 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264451&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]8[/C][C]0.0311284[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]22[/C][C]0.0856031[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]30[/C][C]0.116732[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264451&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264451&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 level80.0311284NOK
5% type I error level220.0856031NOK
10% type I error level300.116732NOK


Figures (Output of Computation)

Figure 1
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Figure 10
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Input Parameters & R Code

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