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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 17 Dec 2014 15:05:06 +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/17/t1418828721tm9gc5tngqueofx.htm/, Retrieved Thu, 16 May 2024 17:32:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270376, Retrieved Thu, 16 May 2024 17:32:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact50

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-17 15:05:06] [ce2f801bda31f4b58163e4bbe4fada83] [Current]
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Dataset

Dataseries X:
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Histogram
Boxplots 
12,9	11	8	7	18	12	20	4
7,4	15	18	18	23	20	25	9
12,2	19	18	20	23	20	19	4
12,8	16	12	9	22	14	18	5
7,4	24	24	19	22	25	24	4
6,7	15	16	12	19	15	20	4
12,6	17	19	16	25	20	20	9
14,8	19	16	17	28	21	24	8
13,3	19	15	9	16	15	21	11
11,1	28	28	28	28	28	28	4
8,2	26	21	20	21	11	10	4
11,4	15	18	16	22	22	22	6
6,4	26	22	22	24	22	19	4
10,6	16	19	17	24	27	27	8
12,0	24	22	12	26	24	23	4
6,3	25	25	18	28	23	24	4
11,3	22	20	20	24	24	24	11
11,9	15	16	12	20	21	25	4
9,3	21	19	16	26	20	24	4
9,6	22	18	16	21	19	21	6
10,0	27	26	21	28	25	28	6
6,4	26	24	15	27	16	28	4
13,8	26	20	17	23	24	22	8
10,8	22	19	17	24	21	26	5
13,8	21	19	17	24	22	26	4
11,7	22	23	18	22	25	21	9
10,9	20	18	15	21	23	26	4
16,1	21	16	20	25	20	23	7
13,4	20	18	13	20	21	20	10
9,9	22	21	21	21	22	24	4
11,5	21	20	12	26	25	25	4
8,3	8	15	6	23	23	24	7
11,7	22	19	13	21	19	20	12
6,1	18	27	6	27	27	23	4
9,0	20	19	19	27	21	24	7
9,7	24	7	12	25	19	25	5
10,8	17	20	14	23	25	23	8
10,3	20	20	13	25	16	21	5
10,4	23	19	12	23	24	23	4
12,7	20	19	17	19	24	21	9
9,3	22	20	19	22	18	18	7
11,8	19	18	10	24	28	24	4
5,9	15	14	10	19	15	18	4
11,4	20	17	11	21	17	21	4
13,0	22	17	11	27	18	23	4
10,8	17	8	10	25	26	25	4
12,3	14	9	7	25	18	22	7
11,3	24	22	22	23	22	22	4
11,8	17	20	12	17	19	23	7
7,9	23	20	18	28	17	24	4
12,7	25	22	20	25	26	25	4
12,3	16	22	9	20	21	22	4
11,6	18	22	16	25	26	24	4
6,7	20	16	14	21	21	21	8
10,9	18	14	11	24	12	24	4
12,1	23	24	20	28	20	25	4
13,3	24	21	17	20	20	23	4
10,1	23	20	14	19	24	27	4
5,7	13	20	8	24	24	27	7
14,3	20	18	16	21	22	23	12
8,0	20	14	11	24	21	18	4
13,3	19	19	10	23	20	20	4
9,3	22	24	15	18	23	23	4
12,5	22	19	15	27	19	24	5
7,6	15	16	10	25	24	26	15
15,9	17	16	10	20	21	20	5
9,2	19	16	18	21	16	23	10
9,1	20	14	10	23	17	22	9
11,1	22	22	22	27	23	23	8
13,0	21	21	16	24	20	17	4
14,5	21	15	10	27	19	20	5
12,2	16	14	7	24	18	22	4
12,3	20	15	16	23	18	18	9
11,4	21	14	16	24	21	19	4
8,8	20	20	16	21	20	19	10
14,6	23	21	22	23	17	16	4
7,3	15	17	13	22	20	24	7
12,6	18	14	5	27	25	26	4
13,0	16	16	10	25	17	25	7
12,6	17	13	8	19	17	23	5
13,2	24	26	16	24	24	18	4
9,9	13	13	8	25	21	22	4
7,7	19	18	16	23	22	26	4
10,5	20	15	14	23	18	25	4
13,4	22	18	15	25	22	26	4
10,9	19	21	9	26	20	26	4
4,3	21	17	21	26	21	24	6
10,3	15	18	7	16	21	22	10
11,8	21	20	17	23	20	21	7
11,2	24	18	18	26	18	22	4
11,4	22	25	16	25	25	28	4
8,6	20	20	16	23	23	22	7
13,2	21	19	14	26	21	26	4
12,6	19	18	15	22	20	20	8
5,6	14	12	8	20	21	24	11
9,9	25	22	22	27	20	21	6
8,8	11	16	5	20	22	23	14
7,7	17	18	13	22	15	23	5
9,0	22	23	22	24	24	23	4
7,3	20	20	18	21	22	22	8
11,4	22	20	15	24	21	23	9
13,6	15	16	11	26	17	21	4
7,9	23	22	19	24	23	27	4
10,7	20	19	19	24	22	23	5
10,3	22	23	21	27	23	26	4
8,3	16	6	4	25	16	27	5
9,6	25	19	17	27	18	27	4
14,2	18	24	10	19	25	23	4
8,5	19	19	13	22	18	23	7
13,5	25	15	15	22	14	23	10
4,9	21	18	11	25	20	28	4
6,4	22	18	20	23	19	24	5
9,6	21	22	13	24	18	20	4
11,6	22	23	18	24	22	23	4
11,1	23	18	20	23	21	22	4
4,35	20	17	15	22	14	15	6
12,7	6	6	4	24	5	27	4
18,1	15	22	9	19	25	23	8
17,85	18	20	18	25	21	23	5
16,6	24	16	12	26	11	20	4
12,6	22	16	17	18	20	18	17
17,1	21	17	12	24	9	22	4
19,1	23	20	16	28	15	20	4
16,1	20	23	17	23	23	21	8
13,35	20	18	14	19	21	25	4
18,4	18	13	13	19	9	19	7
14,7	25	22	20	27	24	25	4
10,6	16	20	16	24	16	24	4
12,6	20	20	15	26	20	22	5
16,2	14	13	10	21	15	28	7
13,6	22	16	16	25	18	22	4
18,9	26	25	21	28	22	21	4
14,1	20	16	15	19	21	23	7
14,5	17	15	16	20	21	19	11
16,15	22	19	19	26	21	21	7
14,75	22	19	9	27	20	25	4
14,8	20	24	19	23	24	23	4
12,45	17	9	7	18	15	28	4
12,65	22	22	23	23	24	14	4
17,35	17	15	14	21	18	23	4
8,6	22	22	10	23	24	24	4
18,4	21	22	16	22	24	25	6
16,1	25	24	12	21	15	15	8
11,6	11	12	10	14	19	23	23
17,75	19	21	7	24	20	26	4
15,25	24	25	20	26	26	21	8
17,65	17	26	9	24	26	26	6
15,6	22	19	14	26	18	15	4
16,35	22	21	12	22	23	23	4
17,65	17	14	10	20	13	15	7
13,6	26	28	19	20	16	16	4
11,7	19	16	16	20	19	20	4
14,35	20	21	11	18	22	20	4
14,75	19	16	15	18	21	20	4
18,25	21	16	14	25	11	21	10
9,9	24	25	11	28	23	28	6
16	21	21	14	23	18	19	5
18,25	19	22	15	20	19	21	5
16,85	13	9	7	22	15	22	4
14,6	24	20	22	27	8	27	4
13,85	28	19	19	24	15	20	5
18,95	27	24	22	23	21	17	5
15,6	22	22	11	20	25	26	5
14,85	23	22	19	22	14	21	5
11,75	19	12	9	21	21	24	4
18,45	18	17	11	24	18	21	6
15,9	23	18	17	26	18	25	4
17,1	21	10	12	24	12	22	4
16,1	22	22	17	18	24	17	4
19,9	17	24	10	17	17	14	9
10,95	15	18	17	23	20	23	18
18,45	21	18	13	21	24	28	6
15,1	20	23	11	21	22	24	5
15	26	21	19	24	15	22	4
11,35	19	21	21	22	22	24	11
15,95	28	28	24	24	26	25	4
18,1	21	17	13	24	17	21	10
14,6	19	21	16	24	23	22	6
15,4	22	21	13	23	19	16	8
15,4	21	20	15	21	21	18	8
17,6	20	18	15	24	23	27	6
13,35	19	17	11	19	19	17	8
19,1	11	7	7	19	18	25	4
15,35	17	17	13	23	16	24	4
7,6	19	14	13	25	23	21	9
13,4	20	18	12	24	13	21	9
13,9	17	14	8	21	18	19	5
19,1	21	23	7	18	23	27	4
15,25	21	20	17	23	21	28	4
12,9	12	14	9	20	23	19	15
16,1	23	17	18	23	16	23	10
17,35	22	21	17	23	17	25	9
13,15	22	23	17	23	20	26	7
12,15	21	24	18	23	18	25	9
12,6	20	21	12	27	20	25	6
10,35	18	14	14	19	19	24	4
15,4	21	24	22	25	26	24	7
9,6	24	16	19	25	9	24	4
18,2	22	21	21	21	23	22	7
13,6	20	8	10	25	9	21	4
14,85	17	17	16	17	13	17	15
14,75	19	18	11	22	27	23	4
14,1	16	17	15	23	22	17	9
14,9	19	16	12	27	12	25	4
16,25	23	22	21	27	18	19	4
19,25	8	17	22	5	6	8	28
13,6	22	21	20	19	17	14	4
13,6	23	20	15	24	22	22	4
15,65	15	20	9	23	22	25	4
12,75	17	19	15	28	23	28	5
14,6	21	8	14	25	19	25	4
9,85	25	19	11	27	20	24	4
12,65	18	11	9	16	17	15	12
11,9	23	15	18	23	18	25	5
19,2	20	13	12	25	24	24	4
16,6	21	18	11	26	20	28	6
11,2	21	19	14	24	18	24	6
15,25	24	23	10	23	23	25	5
11,9	22	20	18	24	27	23	4
13,2	22	22	11	27	25	26	4
16,35	23	19	14	25	24	26	4
12,4	17	16	16	19	12	22	10
15,85	15	11	11	19	16	25	7
14,35	24	11	8	14	16	20	4
18,15	22	21	16	24	24	22	4
11,15	19	14	13	20	23	26	7
15,65	18	21	12	21	24	20	4
17,75	21	20	17	28	24	26	4
7,65	20	21	23	26	26	26	12
12,35	19	20	14	19	19	21	5
15,6	19	19	10	23	28	21	8
19,3	16	19	16	23	23	24	6
15,2	18	18	11	21	21	21	17
17,1	23	20	16	26	19	18	4
15,6	22	21	19	25	23	23	5
18,4	23	22	17	25	23	26	4
19,05	20	19	12	24	20	23	5
18,55	24	23	17	23	18	25	5
19,1	25	16	11	22	20	20	6
13,1	25	23	19	27	28	25	4
12,85	20	18	12	26	21	26	4
9,5	23	23	8	23	25	19	4
4,5	21	20	17	22	18	21	6
11,85	23	20	13	26	24	23	8
13,6	23	23	17	22	28	24	10
11,7	11	13	7	17	9	6	4
12,4	21	21	23	25	22	22	5
13,35	27	26	18	22	26	21	4
11,4	19	18	13	28	28	28	4
14,9	21	19	17	22	18	24	4
19,9	16	18	13	21	23	14	16
17,75	22	19	13	21	22	17	4
11,2	21	18	8	24	15	20	7
14,6	22	19	16	26	24	28	4
17,6	16	13	14	26	12	19	4
14,05	18	10	13	24	12	24	14
16,1	23	21	19	27	20	21	5
13,35	24	24	15	22	25	21	5
11,85	20	21	15	23	24	26	5
11,95	20	23	8	22	23	24	5
14,75	18	18	14	23	18	26	7
15,15	4	11	7	15	20	25	19
13,2	14	16	11	20	22	23	16
16,85	22	20	17	22	20	24	4
7,85	17	20	19	25	25	24	4
7,7	23	26	17	27	28	26	7
12,6	20	21	12	24	25	23	9
7,85	18	12	12	21	14	20	5
10,95	19	15	18	17	16	16	14
12,35	20	18	16	26	24	24	4
9,95	15	14	15	20	13	20	16
14,9	24	18	20	22	19	23	10
16,65	21	16	16	24	18	23	5
13,4	19	19	12	23	16	18	6
13,95	19	7	10	22	8	21	4
15,7	27	21	28	28	27	25	4
16,85	23	24	19	21	23	23	4
10,95	23	21	18	24	20	26	5
15,35	20	20	19	28	20	26	4
12,2	17	22	8	25	26	24	4
15,1	21	17	17	24	23	23	5
17,75	23	19	16	24	24	21	4
15,2	22	20	18	21	21	23	4
14,6	16	16	12	20	15	20	5
16,65	20	20	17	26	22	23	8
8,1	16	16	13	16	25	24	15

Tables (Output of Computation)





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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270376&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270376&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270376&T=0

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


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

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






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 15.8631 + 0.0968227AMS.I1[t] + 0.0552291AMS.I2[t] -0.0582817AMS.I3[t] -0.0780222AMS.E1[t] -0.0630236AMS.E2[t] -0.0857553AMS.E3[t] -0.0105356AMS.A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  15.8631 +  0.0968227AMS.I1[t] +  0.0552291AMS.I2[t] -0.0582817AMS.I3[t] -0.0780222AMS.E1[t] -0.0630236AMS.E2[t] -0.0857553AMS.E3[t] -0.0105356AMS.A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270376&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  15.8631 +  0.0968227AMS.I1[t] +  0.0552291AMS.I2[t] -0.0582817AMS.I3[t] -0.0780222AMS.E1[t] -0.0630236AMS.E2[t] -0.0857553AMS.E3[t] -0.0105356AMS.A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270376&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270376&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 15.8631 + 0.0968227AMS.I1[t] + 0.0552291AMS.I2[t] -0.0582817AMS.I3[t] -0.0780222AMS.E1[t] -0.0630236AMS.E2[t] -0.0857553AMS.E3[t] -0.0105356AMS.A[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.86312.313366.8574.54081e-112.27041e-11
AMS.I10.09682270.08118931.1930.2340610.11703
AMS.I20.05522910.07010510.78780.4314820.215741
AMS.I3-0.05828170.0608631-0.95760.3391030.169552
AMS.E1-0.07802220.0830126-0.93990.3480930.174046
AMS.E2-0.06302360.0589223-1.070.2857240.142862
AMS.E3-0.08575530.0697345-1.230.2198350.109917
AMS.A-0.01053560.0708657-0.14870.8819220.440961

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 15.8631 & 2.31336 & 6.857 & 4.54081e-11 & 2.27041e-11 \tabularnewline
AMS.I1 & 0.0968227 & 0.0811893 & 1.193 & 0.234061 & 0.11703 \tabularnewline
AMS.I2 & 0.0552291 & 0.0701051 & 0.7878 & 0.431482 & 0.215741 \tabularnewline
AMS.I3 & -0.0582817 & 0.0608631 & -0.9576 & 0.339103 & 0.169552 \tabularnewline
AMS.E1 & -0.0780222 & 0.0830126 & -0.9399 & 0.348093 & 0.174046 \tabularnewline
AMS.E2 & -0.0630236 & 0.0589223 & -1.07 & 0.285724 & 0.142862 \tabularnewline
AMS.E3 & -0.0857553 & 0.0697345 & -1.23 & 0.219835 & 0.109917 \tabularnewline
AMS.A & -0.0105356 & 0.0708657 & -0.1487 & 0.881922 & 0.440961 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270376&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]15.8631[/C][C]2.31336[/C][C]6.857[/C][C]4.54081e-11[/C][C]2.27041e-11[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.0968227[/C][C]0.0811893[/C][C]1.193[/C][C]0.234061[/C][C]0.11703[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.0552291[/C][C]0.0701051[/C][C]0.7878[/C][C]0.431482[/C][C]0.215741[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0582817[/C][C]0.0608631[/C][C]-0.9576[/C][C]0.339103[/C][C]0.169552[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0780222[/C][C]0.0830126[/C][C]-0.9399[/C][C]0.348093[/C][C]0.174046[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0630236[/C][C]0.0589223[/C][C]-1.07[/C][C]0.285724[/C][C]0.142862[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0857553[/C][C]0.0697345[/C][C]-1.23[/C][C]0.219835[/C][C]0.109917[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0105356[/C][C]0.0708657[/C][C]-0.1487[/C][C]0.881922[/C][C]0.440961[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270376&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270376&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.86312.313366.8574.54081e-112.27041e-11
AMS.I10.09682270.08118931.1930.2340610.11703
AMS.I20.05522910.07010510.78780.4314820.215741
AMS.I3-0.05828170.0608631-0.95760.3391030.169552
AMS.E1-0.07802220.0830126-0.93990.3480930.174046
AMS.E2-0.06302360.0589223-1.070.2857240.142862
AMS.E3-0.08575530.0697345-1.230.2198350.109917
AMS.A-0.01053560.0708657-0.14870.8819220.440961






Multiple Linear Regression - Regression Statistics
Multiple R0.176043
R-squared0.0309911
Adjusted R-squared0.00659164
F-TEST (value)1.27015
F-TEST (DF numerator)7
F-TEST (DF denominator)278
p-value0.265082
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.40997
Sum Squared Residuals3232.56

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.176043 \tabularnewline
R-squared & 0.0309911 \tabularnewline
Adjusted R-squared & 0.00659164 \tabularnewline
F-TEST (value) & 1.27015 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 278 \tabularnewline
p-value & 0.265082 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.40997 \tabularnewline
Sum Squared Residuals & 3232.56 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270376&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.176043[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0309911[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.00659164[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]1.27015[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]278[/C][/ROW]
[ROW][C]p-value[/C][C]0.265082[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.40997[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3232.56[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270376&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270376&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 R0.176043
R-squared0.0309911
Adjusted R-squared0.00659164
F-TEST (value)1.27015
F-TEST (DF numerator)7
F-TEST (DF denominator)278
p-value0.265082
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.40997
Sum Squared Residuals3232.56






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.0441-0.144106
27.411.9668-4.56683
312.212.8048-0.604772
412.813.3554-0.555412
57.413.0127-5.61267
66.713.3147-6.61473
712.612.605-0.00500442
814.811.94512.85489
913.313.8962-0.596197
1011.112.0961-0.996116
118.215.1433-6.94327
1211.412.3242-0.924246
136.413.3828-6.98281
1410.611.497-0.897006
151213.1469-1.14687
166.312.8809-6.58092
1711.312.3731-1.07306
1811.912.4298-0.529788
199.312.6239-3.32393
209.613.3549-3.75485
211012.4648-2.46481
226.413.2735-6.87352
2313.813.21630.583669
2410.812.5734-1.77345
2513.812.42411.37586
2611.713.0267-1.32666
2710.912.5597-1.65969
2816.112.35733.74271
2913.413.33160.0683593
309.912.8039-2.90387
3111.512.5114-1.01141
328.311.7405-3.44052
3311.713.6075-1.90747
346.112.9247-6.82468
35912.1796-3.17961
369.712.5295-2.82953
3710.812.371-1.57099
3810.313.334-3.03403
3910.413.1184-2.71843
4012.712.9675-0.267474
419.313.5222-4.2222
4211.812.3766-0.576601
435.913.4923-7.59234
4411.413.5445-2.14451
451313.0355-0.0354838
4610.811.5929-0.792935
4712.312.26240.0376111
4811.313.0099-1.70993
4911.813.3444-1.54437
507.912.7893-4.88927
5112.712.55790.142093
5212.313.2901-0.990096
5311.612.199-0.59903
546.713.0202-6.32019
5510.913.009-2.10896
5612.112.6188-0.518795
5713.313.5205-0.220464
5810.113.0262-2.92616
595.711.9859-6.28591
6014.312.73741.56259
61813.1499-5.14992
6213.313.3571-0.0570629
639.313.576-4.27604
6412.512.7535-0.2535
657.611.7655-4.16552
6615.913.15822.74176
679.212.8128-3.61278
689.113.1426-4.04262
6911.112.3133-1.21327
701313.4907-0.49072
7114.513.07021.42981
7212.212.8418-0.641809
7312.313.1282-0.828159
7411.412.8696-1.46958
758.813.338-4.53801
7614.613.68750.912477
777.312.3879-5.08786
7812.612.13380.466235
791312.47360.526449
8012.613.182-0.581965
8113.213.7195-0.519484
829.912.1707-2.27074
837.712.3116-4.61156
8410.512.6971-2.19711
8513.412.50430.89573
8610.912.7772-1.8772
874.312.138-7.83797
8810.313.3378-3.0378
8911.813.0806-1.2806
9011.213.0402-1.84016
9111.412.472-1.07201
928.612.7672-4.16724
9313.212.5060.69404
9412.613.0463-0.446305
955.612.3572-6.75718
969.912.9854-3.08539
978.812.4536-3.6536
987.713.0587-5.35868
99912.5817-3.58168
1007.312.8592-5.55921
10111.412.9604-1.56036
10213.612.61510.984948
1037.912.5181-4.61813
10410.712.4575-1.75748
10510.312.2117-1.91166
1068.312.1835-3.88353
1079.612.7437-3.1437
10814.213.27610.923909
1098.513.0974-4.59741
11013.513.5614-0.0613588
1114.912.5951-7.69511
1126.412.719-6.31895
1139.613.5896-3.98958
11411.612.9409-1.34086
11511.112.8718-1.77177
1164.3513.9159-9.56589
11712.711.99710.702875
11818.112.89135.2087
11917.8512.36235.48765
12016.613.89212.70793
12112.613.4985-0.89853
12217.113.76743.33259
12319.113.37495.7251
12416.112.94993.15014
12513.3512.98580.364181
12618.413.81354.58648
12714.712.52792.17209
12810.612.6032-2.00318
12912.612.8016-0.201593
13016.212.29513.90491
13113.612.93060.669354
13218.913.12325.77682
13314.112.9571.14302
13414.512.77591.72414
13516.1512.70853.44146
13614.7512.96491.78505
13714.812.69612.10386
13812.4512.8052-0.355159
13912.6513.318-0.667993
14017.3512.73424.6158
1418.613.2181-4.6181
14218.412.74285.65721
14316.114.95541.14462
14411.612.5037-0.903658
14517.7513.04984.70019
14615.2512.84962.40037
14717.6512.61655.03346
14815.613.73521.86484
14916.3513.27313.07689
15017.6513.95973.69033
15113.614.8365-1.23653
15211.713.1388-1.43878
15314.3513.77010.579874
15414.7513.22711.52295
15518.2513.41414.83591
1569.912.828-2.92797
1571613.62932.37069
15818.2513.43214.81786
15916.8512.62034.22969
16014.613.04091.55907
16113.8513.9305-0.0804922
16218.9513.89215.05788
16315.613.14882.45118
16414.8513.74541.10462
16511.7512.7787-1.02874
16618.4513.03275.4173
16715.912.74443.15564
16817.113.19173.90826
16916.113.80052.29947
17019.914.55865.34138
17110.9512.1018-1.15181
17218.4512.51755.93253
17315.113.2931.80704
1741513.68631.31367
17511.3512.3616-1.01163
17615.9513.02462.92536
17718.113.22754.87252
17814.612.65821.94184
17915.413.9471.45295
18015.413.53691.86308
18117.612.21885.3812
18213.3513.7786-0.428559
18319.112.10396.99606
18415.3512.78722.56281
1857.612.4225-4.82252
18613.413.5068-0.106803
18713.913.36110.538853
18819.113.54725.55278
18915.2512.44892.8011
19012.912.47630.423701
19116.113.09933.00074
19217.3513.05764.29237
19313.1512.91430.235663
19412.1513.0052-0.855193
19512.612.6858-0.0858439
19610.3512.7831-2.43306
19715.412.21873.18134
1989.613.3451-3.74515
19918.212.88075.31925
20013.613.29780.302174
20114.8513.75391.09606
20214.7512.62312.12686
20314.112.74331.35673
20414.912.83812.06186
20516.2513.16873.08134
20619.2514.54514.70489
20713.614.1909-0.590863
20813.613.13260.467406
20915.6512.52853.12154
21012.7511.59621.15375
21114.612.18832.41174
2129.8513.2246-3.37461
21312.6513.9564-1.30641
21411.912.7439-0.843919
21519.212.25486.94521
21616.612.4964.10398
21711.213.0015-1.80151
21815.2513.43371.81629
21911.912.4601-0.560053
22013.212.61320.586802
22116.3512.58863.76144
22212.413.2296-0.829593
22315.8512.57353.27654
22414.3514.4702-0.120202
22518.1512.90675.24333
22611.1512.4049-1.25493
22715.6513.15812.49192
22817.7512.04125.70877
2297.6511.5957-3.94566
23012.3513.458-1.10799
23115.612.7252.87502
23219.312.16377.13626
23315.213.0172.18297
23417.113.45043.64964
23515.612.62052.97946
23618.412.64245.75758
23719.0512.99156.0585
23818.5513.34095.20914
23919.113.7715.32902
24013.112.38930.710674
24112.8512.47050.379529
2429.513.8525-4.35247
2434.513.2952-8.79521
24411.8512.8392-0.989168
24513.612.72490.875104
24611.714.7879-3.08792
24712.412.4394-0.0393661
24813.3513.6661-0.31612
24911.411.5466-0.146646
25014.913.00381.89622
25119.913.19166.7084
25217.7513.75993.99005
25311.213.8175-2.61753
25414.612.12562.47436
25517.612.8584.74203
25614.0512.56611.48388
25716.112.92193.1781
25813.3513.4925-0.142527
25911.8512.4958-0.645773
26011.9513.3268-1.37676
26114.7512.55182.19821
26215.1511.67513.4749
26313.212.37330.826694
26416.8513.02983.82021
2657.8511.8799-4.02993
2667.712.3606-4.66057
26712.612.7447-0.144696
2687.8513.2807-5.43072
26910.9513.6278-2.67779
27012.3512.21980.130216
2719.9512.951-3.00102
27214.913.02371.8763
27316.6512.81563.83445
27413.413.643-0.243033
27513.9513.44290.507136
27615.711.9333.76702
27716.8513.20573.64433
27810.9512.7855-1.83547
27915.3512.07993.27006
28012.212.5685-0.368461
28115.112.49742.60262
28217.7512.97884.77121
28315.213.07232.12774
28414.613.3231.27701
28516.6512.44164.20838
2868.112.4982-4.39819

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.0441 & -0.144106 \tabularnewline
2 & 7.4 & 11.9668 & -4.56683 \tabularnewline
3 & 12.2 & 12.8048 & -0.604772 \tabularnewline
4 & 12.8 & 13.3554 & -0.555412 \tabularnewline
5 & 7.4 & 13.0127 & -5.61267 \tabularnewline
6 & 6.7 & 13.3147 & -6.61473 \tabularnewline
7 & 12.6 & 12.605 & -0.00500442 \tabularnewline
8 & 14.8 & 11.9451 & 2.85489 \tabularnewline
9 & 13.3 & 13.8962 & -0.596197 \tabularnewline
10 & 11.1 & 12.0961 & -0.996116 \tabularnewline
11 & 8.2 & 15.1433 & -6.94327 \tabularnewline
12 & 11.4 & 12.3242 & -0.924246 \tabularnewline
13 & 6.4 & 13.3828 & -6.98281 \tabularnewline
14 & 10.6 & 11.497 & -0.897006 \tabularnewline
15 & 12 & 13.1469 & -1.14687 \tabularnewline
16 & 6.3 & 12.8809 & -6.58092 \tabularnewline
17 & 11.3 & 12.3731 & -1.07306 \tabularnewline
18 & 11.9 & 12.4298 & -0.529788 \tabularnewline
19 & 9.3 & 12.6239 & -3.32393 \tabularnewline
20 & 9.6 & 13.3549 & -3.75485 \tabularnewline
21 & 10 & 12.4648 & -2.46481 \tabularnewline
22 & 6.4 & 13.2735 & -6.87352 \tabularnewline
23 & 13.8 & 13.2163 & 0.583669 \tabularnewline
24 & 10.8 & 12.5734 & -1.77345 \tabularnewline
25 & 13.8 & 12.4241 & 1.37586 \tabularnewline
26 & 11.7 & 13.0267 & -1.32666 \tabularnewline
27 & 10.9 & 12.5597 & -1.65969 \tabularnewline
28 & 16.1 & 12.3573 & 3.74271 \tabularnewline
29 & 13.4 & 13.3316 & 0.0683593 \tabularnewline
30 & 9.9 & 12.8039 & -2.90387 \tabularnewline
31 & 11.5 & 12.5114 & -1.01141 \tabularnewline
32 & 8.3 & 11.7405 & -3.44052 \tabularnewline
33 & 11.7 & 13.6075 & -1.90747 \tabularnewline
34 & 6.1 & 12.9247 & -6.82468 \tabularnewline
35 & 9 & 12.1796 & -3.17961 \tabularnewline
36 & 9.7 & 12.5295 & -2.82953 \tabularnewline
37 & 10.8 & 12.371 & -1.57099 \tabularnewline
38 & 10.3 & 13.334 & -3.03403 \tabularnewline
39 & 10.4 & 13.1184 & -2.71843 \tabularnewline
40 & 12.7 & 12.9675 & -0.267474 \tabularnewline
41 & 9.3 & 13.5222 & -4.2222 \tabularnewline
42 & 11.8 & 12.3766 & -0.576601 \tabularnewline
43 & 5.9 & 13.4923 & -7.59234 \tabularnewline
44 & 11.4 & 13.5445 & -2.14451 \tabularnewline
45 & 13 & 13.0355 & -0.0354838 \tabularnewline
46 & 10.8 & 11.5929 & -0.792935 \tabularnewline
47 & 12.3 & 12.2624 & 0.0376111 \tabularnewline
48 & 11.3 & 13.0099 & -1.70993 \tabularnewline
49 & 11.8 & 13.3444 & -1.54437 \tabularnewline
50 & 7.9 & 12.7893 & -4.88927 \tabularnewline
51 & 12.7 & 12.5579 & 0.142093 \tabularnewline
52 & 12.3 & 13.2901 & -0.990096 \tabularnewline
53 & 11.6 & 12.199 & -0.59903 \tabularnewline
54 & 6.7 & 13.0202 & -6.32019 \tabularnewline
55 & 10.9 & 13.009 & -2.10896 \tabularnewline
56 & 12.1 & 12.6188 & -0.518795 \tabularnewline
57 & 13.3 & 13.5205 & -0.220464 \tabularnewline
58 & 10.1 & 13.0262 & -2.92616 \tabularnewline
59 & 5.7 & 11.9859 & -6.28591 \tabularnewline
60 & 14.3 & 12.7374 & 1.56259 \tabularnewline
61 & 8 & 13.1499 & -5.14992 \tabularnewline
62 & 13.3 & 13.3571 & -0.0570629 \tabularnewline
63 & 9.3 & 13.576 & -4.27604 \tabularnewline
64 & 12.5 & 12.7535 & -0.2535 \tabularnewline
65 & 7.6 & 11.7655 & -4.16552 \tabularnewline
66 & 15.9 & 13.1582 & 2.74176 \tabularnewline
67 & 9.2 & 12.8128 & -3.61278 \tabularnewline
68 & 9.1 & 13.1426 & -4.04262 \tabularnewline
69 & 11.1 & 12.3133 & -1.21327 \tabularnewline
70 & 13 & 13.4907 & -0.49072 \tabularnewline
71 & 14.5 & 13.0702 & 1.42981 \tabularnewline
72 & 12.2 & 12.8418 & -0.641809 \tabularnewline
73 & 12.3 & 13.1282 & -0.828159 \tabularnewline
74 & 11.4 & 12.8696 & -1.46958 \tabularnewline
75 & 8.8 & 13.338 & -4.53801 \tabularnewline
76 & 14.6 & 13.6875 & 0.912477 \tabularnewline
77 & 7.3 & 12.3879 & -5.08786 \tabularnewline
78 & 12.6 & 12.1338 & 0.466235 \tabularnewline
79 & 13 & 12.4736 & 0.526449 \tabularnewline
80 & 12.6 & 13.182 & -0.581965 \tabularnewline
81 & 13.2 & 13.7195 & -0.519484 \tabularnewline
82 & 9.9 & 12.1707 & -2.27074 \tabularnewline
83 & 7.7 & 12.3116 & -4.61156 \tabularnewline
84 & 10.5 & 12.6971 & -2.19711 \tabularnewline
85 & 13.4 & 12.5043 & 0.89573 \tabularnewline
86 & 10.9 & 12.7772 & -1.8772 \tabularnewline
87 & 4.3 & 12.138 & -7.83797 \tabularnewline
88 & 10.3 & 13.3378 & -3.0378 \tabularnewline
89 & 11.8 & 13.0806 & -1.2806 \tabularnewline
90 & 11.2 & 13.0402 & -1.84016 \tabularnewline
91 & 11.4 & 12.472 & -1.07201 \tabularnewline
92 & 8.6 & 12.7672 & -4.16724 \tabularnewline
93 & 13.2 & 12.506 & 0.69404 \tabularnewline
94 & 12.6 & 13.0463 & -0.446305 \tabularnewline
95 & 5.6 & 12.3572 & -6.75718 \tabularnewline
96 & 9.9 & 12.9854 & -3.08539 \tabularnewline
97 & 8.8 & 12.4536 & -3.6536 \tabularnewline
98 & 7.7 & 13.0587 & -5.35868 \tabularnewline
99 & 9 & 12.5817 & -3.58168 \tabularnewline
100 & 7.3 & 12.8592 & -5.55921 \tabularnewline
101 & 11.4 & 12.9604 & -1.56036 \tabularnewline
102 & 13.6 & 12.6151 & 0.984948 \tabularnewline
103 & 7.9 & 12.5181 & -4.61813 \tabularnewline
104 & 10.7 & 12.4575 & -1.75748 \tabularnewline
105 & 10.3 & 12.2117 & -1.91166 \tabularnewline
106 & 8.3 & 12.1835 & -3.88353 \tabularnewline
107 & 9.6 & 12.7437 & -3.1437 \tabularnewline
108 & 14.2 & 13.2761 & 0.923909 \tabularnewline
109 & 8.5 & 13.0974 & -4.59741 \tabularnewline
110 & 13.5 & 13.5614 & -0.0613588 \tabularnewline
111 & 4.9 & 12.5951 & -7.69511 \tabularnewline
112 & 6.4 & 12.719 & -6.31895 \tabularnewline
113 & 9.6 & 13.5896 & -3.98958 \tabularnewline
114 & 11.6 & 12.9409 & -1.34086 \tabularnewline
115 & 11.1 & 12.8718 & -1.77177 \tabularnewline
116 & 4.35 & 13.9159 & -9.56589 \tabularnewline
117 & 12.7 & 11.9971 & 0.702875 \tabularnewline
118 & 18.1 & 12.8913 & 5.2087 \tabularnewline
119 & 17.85 & 12.3623 & 5.48765 \tabularnewline
120 & 16.6 & 13.8921 & 2.70793 \tabularnewline
121 & 12.6 & 13.4985 & -0.89853 \tabularnewline
122 & 17.1 & 13.7674 & 3.33259 \tabularnewline
123 & 19.1 & 13.3749 & 5.7251 \tabularnewline
124 & 16.1 & 12.9499 & 3.15014 \tabularnewline
125 & 13.35 & 12.9858 & 0.364181 \tabularnewline
126 & 18.4 & 13.8135 & 4.58648 \tabularnewline
127 & 14.7 & 12.5279 & 2.17209 \tabularnewline
128 & 10.6 & 12.6032 & -2.00318 \tabularnewline
129 & 12.6 & 12.8016 & -0.201593 \tabularnewline
130 & 16.2 & 12.2951 & 3.90491 \tabularnewline
131 & 13.6 & 12.9306 & 0.669354 \tabularnewline
132 & 18.9 & 13.1232 & 5.77682 \tabularnewline
133 & 14.1 & 12.957 & 1.14302 \tabularnewline
134 & 14.5 & 12.7759 & 1.72414 \tabularnewline
135 & 16.15 & 12.7085 & 3.44146 \tabularnewline
136 & 14.75 & 12.9649 & 1.78505 \tabularnewline
137 & 14.8 & 12.6961 & 2.10386 \tabularnewline
138 & 12.45 & 12.8052 & -0.355159 \tabularnewline
139 & 12.65 & 13.318 & -0.667993 \tabularnewline
140 & 17.35 & 12.7342 & 4.6158 \tabularnewline
141 & 8.6 & 13.2181 & -4.6181 \tabularnewline
142 & 18.4 & 12.7428 & 5.65721 \tabularnewline
143 & 16.1 & 14.9554 & 1.14462 \tabularnewline
144 & 11.6 & 12.5037 & -0.903658 \tabularnewline
145 & 17.75 & 13.0498 & 4.70019 \tabularnewline
146 & 15.25 & 12.8496 & 2.40037 \tabularnewline
147 & 17.65 & 12.6165 & 5.03346 \tabularnewline
148 & 15.6 & 13.7352 & 1.86484 \tabularnewline
149 & 16.35 & 13.2731 & 3.07689 \tabularnewline
150 & 17.65 & 13.9597 & 3.69033 \tabularnewline
151 & 13.6 & 14.8365 & -1.23653 \tabularnewline
152 & 11.7 & 13.1388 & -1.43878 \tabularnewline
153 & 14.35 & 13.7701 & 0.579874 \tabularnewline
154 & 14.75 & 13.2271 & 1.52295 \tabularnewline
155 & 18.25 & 13.4141 & 4.83591 \tabularnewline
156 & 9.9 & 12.828 & -2.92797 \tabularnewline
157 & 16 & 13.6293 & 2.37069 \tabularnewline
158 & 18.25 & 13.4321 & 4.81786 \tabularnewline
159 & 16.85 & 12.6203 & 4.22969 \tabularnewline
160 & 14.6 & 13.0409 & 1.55907 \tabularnewline
161 & 13.85 & 13.9305 & -0.0804922 \tabularnewline
162 & 18.95 & 13.8921 & 5.05788 \tabularnewline
163 & 15.6 & 13.1488 & 2.45118 \tabularnewline
164 & 14.85 & 13.7454 & 1.10462 \tabularnewline
165 & 11.75 & 12.7787 & -1.02874 \tabularnewline
166 & 18.45 & 13.0327 & 5.4173 \tabularnewline
167 & 15.9 & 12.7444 & 3.15564 \tabularnewline
168 & 17.1 & 13.1917 & 3.90826 \tabularnewline
169 & 16.1 & 13.8005 & 2.29947 \tabularnewline
170 & 19.9 & 14.5586 & 5.34138 \tabularnewline
171 & 10.95 & 12.1018 & -1.15181 \tabularnewline
172 & 18.45 & 12.5175 & 5.93253 \tabularnewline
173 & 15.1 & 13.293 & 1.80704 \tabularnewline
174 & 15 & 13.6863 & 1.31367 \tabularnewline
175 & 11.35 & 12.3616 & -1.01163 \tabularnewline
176 & 15.95 & 13.0246 & 2.92536 \tabularnewline
177 & 18.1 & 13.2275 & 4.87252 \tabularnewline
178 & 14.6 & 12.6582 & 1.94184 \tabularnewline
179 & 15.4 & 13.947 & 1.45295 \tabularnewline
180 & 15.4 & 13.5369 & 1.86308 \tabularnewline
181 & 17.6 & 12.2188 & 5.3812 \tabularnewline
182 & 13.35 & 13.7786 & -0.428559 \tabularnewline
183 & 19.1 & 12.1039 & 6.99606 \tabularnewline
184 & 15.35 & 12.7872 & 2.56281 \tabularnewline
185 & 7.6 & 12.4225 & -4.82252 \tabularnewline
186 & 13.4 & 13.5068 & -0.106803 \tabularnewline
187 & 13.9 & 13.3611 & 0.538853 \tabularnewline
188 & 19.1 & 13.5472 & 5.55278 \tabularnewline
189 & 15.25 & 12.4489 & 2.8011 \tabularnewline
190 & 12.9 & 12.4763 & 0.423701 \tabularnewline
191 & 16.1 & 13.0993 & 3.00074 \tabularnewline
192 & 17.35 & 13.0576 & 4.29237 \tabularnewline
193 & 13.15 & 12.9143 & 0.235663 \tabularnewline
194 & 12.15 & 13.0052 & -0.855193 \tabularnewline
195 & 12.6 & 12.6858 & -0.0858439 \tabularnewline
196 & 10.35 & 12.7831 & -2.43306 \tabularnewline
197 & 15.4 & 12.2187 & 3.18134 \tabularnewline
198 & 9.6 & 13.3451 & -3.74515 \tabularnewline
199 & 18.2 & 12.8807 & 5.31925 \tabularnewline
200 & 13.6 & 13.2978 & 0.302174 \tabularnewline
201 & 14.85 & 13.7539 & 1.09606 \tabularnewline
202 & 14.75 & 12.6231 & 2.12686 \tabularnewline
203 & 14.1 & 12.7433 & 1.35673 \tabularnewline
204 & 14.9 & 12.8381 & 2.06186 \tabularnewline
205 & 16.25 & 13.1687 & 3.08134 \tabularnewline
206 & 19.25 & 14.5451 & 4.70489 \tabularnewline
207 & 13.6 & 14.1909 & -0.590863 \tabularnewline
208 & 13.6 & 13.1326 & 0.467406 \tabularnewline
209 & 15.65 & 12.5285 & 3.12154 \tabularnewline
210 & 12.75 & 11.5962 & 1.15375 \tabularnewline
211 & 14.6 & 12.1883 & 2.41174 \tabularnewline
212 & 9.85 & 13.2246 & -3.37461 \tabularnewline
213 & 12.65 & 13.9564 & -1.30641 \tabularnewline
214 & 11.9 & 12.7439 & -0.843919 \tabularnewline
215 & 19.2 & 12.2548 & 6.94521 \tabularnewline
216 & 16.6 & 12.496 & 4.10398 \tabularnewline
217 & 11.2 & 13.0015 & -1.80151 \tabularnewline
218 & 15.25 & 13.4337 & 1.81629 \tabularnewline
219 & 11.9 & 12.4601 & -0.560053 \tabularnewline
220 & 13.2 & 12.6132 & 0.586802 \tabularnewline
221 & 16.35 & 12.5886 & 3.76144 \tabularnewline
222 & 12.4 & 13.2296 & -0.829593 \tabularnewline
223 & 15.85 & 12.5735 & 3.27654 \tabularnewline
224 & 14.35 & 14.4702 & -0.120202 \tabularnewline
225 & 18.15 & 12.9067 & 5.24333 \tabularnewline
226 & 11.15 & 12.4049 & -1.25493 \tabularnewline
227 & 15.65 & 13.1581 & 2.49192 \tabularnewline
228 & 17.75 & 12.0412 & 5.70877 \tabularnewline
229 & 7.65 & 11.5957 & -3.94566 \tabularnewline
230 & 12.35 & 13.458 & -1.10799 \tabularnewline
231 & 15.6 & 12.725 & 2.87502 \tabularnewline
232 & 19.3 & 12.1637 & 7.13626 \tabularnewline
233 & 15.2 & 13.017 & 2.18297 \tabularnewline
234 & 17.1 & 13.4504 & 3.64964 \tabularnewline
235 & 15.6 & 12.6205 & 2.97946 \tabularnewline
236 & 18.4 & 12.6424 & 5.75758 \tabularnewline
237 & 19.05 & 12.9915 & 6.0585 \tabularnewline
238 & 18.55 & 13.3409 & 5.20914 \tabularnewline
239 & 19.1 & 13.771 & 5.32902 \tabularnewline
240 & 13.1 & 12.3893 & 0.710674 \tabularnewline
241 & 12.85 & 12.4705 & 0.379529 \tabularnewline
242 & 9.5 & 13.8525 & -4.35247 \tabularnewline
243 & 4.5 & 13.2952 & -8.79521 \tabularnewline
244 & 11.85 & 12.8392 & -0.989168 \tabularnewline
245 & 13.6 & 12.7249 & 0.875104 \tabularnewline
246 & 11.7 & 14.7879 & -3.08792 \tabularnewline
247 & 12.4 & 12.4394 & -0.0393661 \tabularnewline
248 & 13.35 & 13.6661 & -0.31612 \tabularnewline
249 & 11.4 & 11.5466 & -0.146646 \tabularnewline
250 & 14.9 & 13.0038 & 1.89622 \tabularnewline
251 & 19.9 & 13.1916 & 6.7084 \tabularnewline
252 & 17.75 & 13.7599 & 3.99005 \tabularnewline
253 & 11.2 & 13.8175 & -2.61753 \tabularnewline
254 & 14.6 & 12.1256 & 2.47436 \tabularnewline
255 & 17.6 & 12.858 & 4.74203 \tabularnewline
256 & 14.05 & 12.5661 & 1.48388 \tabularnewline
257 & 16.1 & 12.9219 & 3.1781 \tabularnewline
258 & 13.35 & 13.4925 & -0.142527 \tabularnewline
259 & 11.85 & 12.4958 & -0.645773 \tabularnewline
260 & 11.95 & 13.3268 & -1.37676 \tabularnewline
261 & 14.75 & 12.5518 & 2.19821 \tabularnewline
262 & 15.15 & 11.6751 & 3.4749 \tabularnewline
263 & 13.2 & 12.3733 & 0.826694 \tabularnewline
264 & 16.85 & 13.0298 & 3.82021 \tabularnewline
265 & 7.85 & 11.8799 & -4.02993 \tabularnewline
266 & 7.7 & 12.3606 & -4.66057 \tabularnewline
267 & 12.6 & 12.7447 & -0.144696 \tabularnewline
268 & 7.85 & 13.2807 & -5.43072 \tabularnewline
269 & 10.95 & 13.6278 & -2.67779 \tabularnewline
270 & 12.35 & 12.2198 & 0.130216 \tabularnewline
271 & 9.95 & 12.951 & -3.00102 \tabularnewline
272 & 14.9 & 13.0237 & 1.8763 \tabularnewline
273 & 16.65 & 12.8156 & 3.83445 \tabularnewline
274 & 13.4 & 13.643 & -0.243033 \tabularnewline
275 & 13.95 & 13.4429 & 0.507136 \tabularnewline
276 & 15.7 & 11.933 & 3.76702 \tabularnewline
277 & 16.85 & 13.2057 & 3.64433 \tabularnewline
278 & 10.95 & 12.7855 & -1.83547 \tabularnewline
279 & 15.35 & 12.0799 & 3.27006 \tabularnewline
280 & 12.2 & 12.5685 & -0.368461 \tabularnewline
281 & 15.1 & 12.4974 & 2.60262 \tabularnewline
282 & 17.75 & 12.9788 & 4.77121 \tabularnewline
283 & 15.2 & 13.0723 & 2.12774 \tabularnewline
284 & 14.6 & 13.323 & 1.27701 \tabularnewline
285 & 16.65 & 12.4416 & 4.20838 \tabularnewline
286 & 8.1 & 12.4982 & -4.39819 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270376&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]13.0441[/C][C]-0.144106[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]11.9668[/C][C]-4.56683[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]12.8048[/C][C]-0.604772[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]13.3554[/C][C]-0.555412[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]13.0127[/C][C]-5.61267[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]13.3147[/C][C]-6.61473[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]12.605[/C][C]-0.00500442[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]11.9451[/C][C]2.85489[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]13.8962[/C][C]-0.596197[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]12.0961[/C][C]-0.996116[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]15.1433[/C][C]-6.94327[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]12.3242[/C][C]-0.924246[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]13.3828[/C][C]-6.98281[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]11.497[/C][C]-0.897006[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]13.1469[/C][C]-1.14687[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]12.8809[/C][C]-6.58092[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]12.3731[/C][C]-1.07306[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]12.4298[/C][C]-0.529788[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]12.6239[/C][C]-3.32393[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]13.3549[/C][C]-3.75485[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]12.4648[/C][C]-2.46481[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]13.2735[/C][C]-6.87352[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]13.2163[/C][C]0.583669[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]12.5734[/C][C]-1.77345[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]12.4241[/C][C]1.37586[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]13.0267[/C][C]-1.32666[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]12.5597[/C][C]-1.65969[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]12.3573[/C][C]3.74271[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]13.3316[/C][C]0.0683593[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]12.8039[/C][C]-2.90387[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]12.5114[/C][C]-1.01141[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]11.7405[/C][C]-3.44052[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]13.6075[/C][C]-1.90747[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]12.9247[/C][C]-6.82468[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]12.1796[/C][C]-3.17961[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]12.5295[/C][C]-2.82953[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]12.371[/C][C]-1.57099[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]13.334[/C][C]-3.03403[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]13.1184[/C][C]-2.71843[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]12.9675[/C][C]-0.267474[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]13.5222[/C][C]-4.2222[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]12.3766[/C][C]-0.576601[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]13.4923[/C][C]-7.59234[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]13.5445[/C][C]-2.14451[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]13.0355[/C][C]-0.0354838[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]11.5929[/C][C]-0.792935[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]12.2624[/C][C]0.0376111[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]13.0099[/C][C]-1.70993[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]13.3444[/C][C]-1.54437[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]12.7893[/C][C]-4.88927[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]12.5579[/C][C]0.142093[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]13.2901[/C][C]-0.990096[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]12.199[/C][C]-0.59903[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]13.0202[/C][C]-6.32019[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]13.009[/C][C]-2.10896[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]12.6188[/C][C]-0.518795[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]13.5205[/C][C]-0.220464[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]13.0262[/C][C]-2.92616[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]11.9859[/C][C]-6.28591[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]12.7374[/C][C]1.56259[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]13.1499[/C][C]-5.14992[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]13.3571[/C][C]-0.0570629[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]13.576[/C][C]-4.27604[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]12.7535[/C][C]-0.2535[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]11.7655[/C][C]-4.16552[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]13.1582[/C][C]2.74176[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]12.8128[/C][C]-3.61278[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]13.1426[/C][C]-4.04262[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]12.3133[/C][C]-1.21327[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]13.4907[/C][C]-0.49072[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]13.0702[/C][C]1.42981[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]12.8418[/C][C]-0.641809[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]13.1282[/C][C]-0.828159[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]12.8696[/C][C]-1.46958[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]13.338[/C][C]-4.53801[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]13.6875[/C][C]0.912477[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]12.3879[/C][C]-5.08786[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]12.1338[/C][C]0.466235[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.4736[/C][C]0.526449[/C][/ROW]
[ROW][C]80[/C][C]12.6[/C][C]13.182[/C][C]-0.581965[/C][/ROW]
[ROW][C]81[/C][C]13.2[/C][C]13.7195[/C][C]-0.519484[/C][/ROW]
[ROW][C]82[/C][C]9.9[/C][C]12.1707[/C][C]-2.27074[/C][/ROW]
[ROW][C]83[/C][C]7.7[/C][C]12.3116[/C][C]-4.61156[/C][/ROW]
[ROW][C]84[/C][C]10.5[/C][C]12.6971[/C][C]-2.19711[/C][/ROW]
[ROW][C]85[/C][C]13.4[/C][C]12.5043[/C][C]0.89573[/C][/ROW]
[ROW][C]86[/C][C]10.9[/C][C]12.7772[/C][C]-1.8772[/C][/ROW]
[ROW][C]87[/C][C]4.3[/C][C]12.138[/C][C]-7.83797[/C][/ROW]
[ROW][C]88[/C][C]10.3[/C][C]13.3378[/C][C]-3.0378[/C][/ROW]
[ROW][C]89[/C][C]11.8[/C][C]13.0806[/C][C]-1.2806[/C][/ROW]
[ROW][C]90[/C][C]11.2[/C][C]13.0402[/C][C]-1.84016[/C][/ROW]
[ROW][C]91[/C][C]11.4[/C][C]12.472[/C][C]-1.07201[/C][/ROW]
[ROW][C]92[/C][C]8.6[/C][C]12.7672[/C][C]-4.16724[/C][/ROW]
[ROW][C]93[/C][C]13.2[/C][C]12.506[/C][C]0.69404[/C][/ROW]
[ROW][C]94[/C][C]12.6[/C][C]13.0463[/C][C]-0.446305[/C][/ROW]
[ROW][C]95[/C][C]5.6[/C][C]12.3572[/C][C]-6.75718[/C][/ROW]
[ROW][C]96[/C][C]9.9[/C][C]12.9854[/C][C]-3.08539[/C][/ROW]
[ROW][C]97[/C][C]8.8[/C][C]12.4536[/C][C]-3.6536[/C][/ROW]
[ROW][C]98[/C][C]7.7[/C][C]13.0587[/C][C]-5.35868[/C][/ROW]
[ROW][C]99[/C][C]9[/C][C]12.5817[/C][C]-3.58168[/C][/ROW]
[ROW][C]100[/C][C]7.3[/C][C]12.8592[/C][C]-5.55921[/C][/ROW]
[ROW][C]101[/C][C]11.4[/C][C]12.9604[/C][C]-1.56036[/C][/ROW]
[ROW][C]102[/C][C]13.6[/C][C]12.6151[/C][C]0.984948[/C][/ROW]
[ROW][C]103[/C][C]7.9[/C][C]12.5181[/C][C]-4.61813[/C][/ROW]
[ROW][C]104[/C][C]10.7[/C][C]12.4575[/C][C]-1.75748[/C][/ROW]
[ROW][C]105[/C][C]10.3[/C][C]12.2117[/C][C]-1.91166[/C][/ROW]
[ROW][C]106[/C][C]8.3[/C][C]12.1835[/C][C]-3.88353[/C][/ROW]
[ROW][C]107[/C][C]9.6[/C][C]12.7437[/C][C]-3.1437[/C][/ROW]
[ROW][C]108[/C][C]14.2[/C][C]13.2761[/C][C]0.923909[/C][/ROW]
[ROW][C]109[/C][C]8.5[/C][C]13.0974[/C][C]-4.59741[/C][/ROW]
[ROW][C]110[/C][C]13.5[/C][C]13.5614[/C][C]-0.0613588[/C][/ROW]
[ROW][C]111[/C][C]4.9[/C][C]12.5951[/C][C]-7.69511[/C][/ROW]
[ROW][C]112[/C][C]6.4[/C][C]12.719[/C][C]-6.31895[/C][/ROW]
[ROW][C]113[/C][C]9.6[/C][C]13.5896[/C][C]-3.98958[/C][/ROW]
[ROW][C]114[/C][C]11.6[/C][C]12.9409[/C][C]-1.34086[/C][/ROW]
[ROW][C]115[/C][C]11.1[/C][C]12.8718[/C][C]-1.77177[/C][/ROW]
[ROW][C]116[/C][C]4.35[/C][C]13.9159[/C][C]-9.56589[/C][/ROW]
[ROW][C]117[/C][C]12.7[/C][C]11.9971[/C][C]0.702875[/C][/ROW]
[ROW][C]118[/C][C]18.1[/C][C]12.8913[/C][C]5.2087[/C][/ROW]
[ROW][C]119[/C][C]17.85[/C][C]12.3623[/C][C]5.48765[/C][/ROW]
[ROW][C]120[/C][C]16.6[/C][C]13.8921[/C][C]2.70793[/C][/ROW]
[ROW][C]121[/C][C]12.6[/C][C]13.4985[/C][C]-0.89853[/C][/ROW]
[ROW][C]122[/C][C]17.1[/C][C]13.7674[/C][C]3.33259[/C][/ROW]
[ROW][C]123[/C][C]19.1[/C][C]13.3749[/C][C]5.7251[/C][/ROW]
[ROW][C]124[/C][C]16.1[/C][C]12.9499[/C][C]3.15014[/C][/ROW]
[ROW][C]125[/C][C]13.35[/C][C]12.9858[/C][C]0.364181[/C][/ROW]
[ROW][C]126[/C][C]18.4[/C][C]13.8135[/C][C]4.58648[/C][/ROW]
[ROW][C]127[/C][C]14.7[/C][C]12.5279[/C][C]2.17209[/C][/ROW]
[ROW][C]128[/C][C]10.6[/C][C]12.6032[/C][C]-2.00318[/C][/ROW]
[ROW][C]129[/C][C]12.6[/C][C]12.8016[/C][C]-0.201593[/C][/ROW]
[ROW][C]130[/C][C]16.2[/C][C]12.2951[/C][C]3.90491[/C][/ROW]
[ROW][C]131[/C][C]13.6[/C][C]12.9306[/C][C]0.669354[/C][/ROW]
[ROW][C]132[/C][C]18.9[/C][C]13.1232[/C][C]5.77682[/C][/ROW]
[ROW][C]133[/C][C]14.1[/C][C]12.957[/C][C]1.14302[/C][/ROW]
[ROW][C]134[/C][C]14.5[/C][C]12.7759[/C][C]1.72414[/C][/ROW]
[ROW][C]135[/C][C]16.15[/C][C]12.7085[/C][C]3.44146[/C][/ROW]
[ROW][C]136[/C][C]14.75[/C][C]12.9649[/C][C]1.78505[/C][/ROW]
[ROW][C]137[/C][C]14.8[/C][C]12.6961[/C][C]2.10386[/C][/ROW]
[ROW][C]138[/C][C]12.45[/C][C]12.8052[/C][C]-0.355159[/C][/ROW]
[ROW][C]139[/C][C]12.65[/C][C]13.318[/C][C]-0.667993[/C][/ROW]
[ROW][C]140[/C][C]17.35[/C][C]12.7342[/C][C]4.6158[/C][/ROW]
[ROW][C]141[/C][C]8.6[/C][C]13.2181[/C][C]-4.6181[/C][/ROW]
[ROW][C]142[/C][C]18.4[/C][C]12.7428[/C][C]5.65721[/C][/ROW]
[ROW][C]143[/C][C]16.1[/C][C]14.9554[/C][C]1.14462[/C][/ROW]
[ROW][C]144[/C][C]11.6[/C][C]12.5037[/C][C]-0.903658[/C][/ROW]
[ROW][C]145[/C][C]17.75[/C][C]13.0498[/C][C]4.70019[/C][/ROW]
[ROW][C]146[/C][C]15.25[/C][C]12.8496[/C][C]2.40037[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]12.6165[/C][C]5.03346[/C][/ROW]
[ROW][C]148[/C][C]15.6[/C][C]13.7352[/C][C]1.86484[/C][/ROW]
[ROW][C]149[/C][C]16.35[/C][C]13.2731[/C][C]3.07689[/C][/ROW]
[ROW][C]150[/C][C]17.65[/C][C]13.9597[/C][C]3.69033[/C][/ROW]
[ROW][C]151[/C][C]13.6[/C][C]14.8365[/C][C]-1.23653[/C][/ROW]
[ROW][C]152[/C][C]11.7[/C][C]13.1388[/C][C]-1.43878[/C][/ROW]
[ROW][C]153[/C][C]14.35[/C][C]13.7701[/C][C]0.579874[/C][/ROW]
[ROW][C]154[/C][C]14.75[/C][C]13.2271[/C][C]1.52295[/C][/ROW]
[ROW][C]155[/C][C]18.25[/C][C]13.4141[/C][C]4.83591[/C][/ROW]
[ROW][C]156[/C][C]9.9[/C][C]12.828[/C][C]-2.92797[/C][/ROW]
[ROW][C]157[/C][C]16[/C][C]13.6293[/C][C]2.37069[/C][/ROW]
[ROW][C]158[/C][C]18.25[/C][C]13.4321[/C][C]4.81786[/C][/ROW]
[ROW][C]159[/C][C]16.85[/C][C]12.6203[/C][C]4.22969[/C][/ROW]
[ROW][C]160[/C][C]14.6[/C][C]13.0409[/C][C]1.55907[/C][/ROW]
[ROW][C]161[/C][C]13.85[/C][C]13.9305[/C][C]-0.0804922[/C][/ROW]
[ROW][C]162[/C][C]18.95[/C][C]13.8921[/C][C]5.05788[/C][/ROW]
[ROW][C]163[/C][C]15.6[/C][C]13.1488[/C][C]2.45118[/C][/ROW]
[ROW][C]164[/C][C]14.85[/C][C]13.7454[/C][C]1.10462[/C][/ROW]
[ROW][C]165[/C][C]11.75[/C][C]12.7787[/C][C]-1.02874[/C][/ROW]
[ROW][C]166[/C][C]18.45[/C][C]13.0327[/C][C]5.4173[/C][/ROW]
[ROW][C]167[/C][C]15.9[/C][C]12.7444[/C][C]3.15564[/C][/ROW]
[ROW][C]168[/C][C]17.1[/C][C]13.1917[/C][C]3.90826[/C][/ROW]
[ROW][C]169[/C][C]16.1[/C][C]13.8005[/C][C]2.29947[/C][/ROW]
[ROW][C]170[/C][C]19.9[/C][C]14.5586[/C][C]5.34138[/C][/ROW]
[ROW][C]171[/C][C]10.95[/C][C]12.1018[/C][C]-1.15181[/C][/ROW]
[ROW][C]172[/C][C]18.45[/C][C]12.5175[/C][C]5.93253[/C][/ROW]
[ROW][C]173[/C][C]15.1[/C][C]13.293[/C][C]1.80704[/C][/ROW]
[ROW][C]174[/C][C]15[/C][C]13.6863[/C][C]1.31367[/C][/ROW]
[ROW][C]175[/C][C]11.35[/C][C]12.3616[/C][C]-1.01163[/C][/ROW]
[ROW][C]176[/C][C]15.95[/C][C]13.0246[/C][C]2.92536[/C][/ROW]
[ROW][C]177[/C][C]18.1[/C][C]13.2275[/C][C]4.87252[/C][/ROW]
[ROW][C]178[/C][C]14.6[/C][C]12.6582[/C][C]1.94184[/C][/ROW]
[ROW][C]179[/C][C]15.4[/C][C]13.947[/C][C]1.45295[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]13.5369[/C][C]1.86308[/C][/ROW]
[ROW][C]181[/C][C]17.6[/C][C]12.2188[/C][C]5.3812[/C][/ROW]
[ROW][C]182[/C][C]13.35[/C][C]13.7786[/C][C]-0.428559[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]12.1039[/C][C]6.99606[/C][/ROW]
[ROW][C]184[/C][C]15.35[/C][C]12.7872[/C][C]2.56281[/C][/ROW]
[ROW][C]185[/C][C]7.6[/C][C]12.4225[/C][C]-4.82252[/C][/ROW]
[ROW][C]186[/C][C]13.4[/C][C]13.5068[/C][C]-0.106803[/C][/ROW]
[ROW][C]187[/C][C]13.9[/C][C]13.3611[/C][C]0.538853[/C][/ROW]
[ROW][C]188[/C][C]19.1[/C][C]13.5472[/C][C]5.55278[/C][/ROW]
[ROW][C]189[/C][C]15.25[/C][C]12.4489[/C][C]2.8011[/C][/ROW]
[ROW][C]190[/C][C]12.9[/C][C]12.4763[/C][C]0.423701[/C][/ROW]
[ROW][C]191[/C][C]16.1[/C][C]13.0993[/C][C]3.00074[/C][/ROW]
[ROW][C]192[/C][C]17.35[/C][C]13.0576[/C][C]4.29237[/C][/ROW]
[ROW][C]193[/C][C]13.15[/C][C]12.9143[/C][C]0.235663[/C][/ROW]
[ROW][C]194[/C][C]12.15[/C][C]13.0052[/C][C]-0.855193[/C][/ROW]
[ROW][C]195[/C][C]12.6[/C][C]12.6858[/C][C]-0.0858439[/C][/ROW]
[ROW][C]196[/C][C]10.35[/C][C]12.7831[/C][C]-2.43306[/C][/ROW]
[ROW][C]197[/C][C]15.4[/C][C]12.2187[/C][C]3.18134[/C][/ROW]
[ROW][C]198[/C][C]9.6[/C][C]13.3451[/C][C]-3.74515[/C][/ROW]
[ROW][C]199[/C][C]18.2[/C][C]12.8807[/C][C]5.31925[/C][/ROW]
[ROW][C]200[/C][C]13.6[/C][C]13.2978[/C][C]0.302174[/C][/ROW]
[ROW][C]201[/C][C]14.85[/C][C]13.7539[/C][C]1.09606[/C][/ROW]
[ROW][C]202[/C][C]14.75[/C][C]12.6231[/C][C]2.12686[/C][/ROW]
[ROW][C]203[/C][C]14.1[/C][C]12.7433[/C][C]1.35673[/C][/ROW]
[ROW][C]204[/C][C]14.9[/C][C]12.8381[/C][C]2.06186[/C][/ROW]
[ROW][C]205[/C][C]16.25[/C][C]13.1687[/C][C]3.08134[/C][/ROW]
[ROW][C]206[/C][C]19.25[/C][C]14.5451[/C][C]4.70489[/C][/ROW]
[ROW][C]207[/C][C]13.6[/C][C]14.1909[/C][C]-0.590863[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]13.1326[/C][C]0.467406[/C][/ROW]
[ROW][C]209[/C][C]15.65[/C][C]12.5285[/C][C]3.12154[/C][/ROW]
[ROW][C]210[/C][C]12.75[/C][C]11.5962[/C][C]1.15375[/C][/ROW]
[ROW][C]211[/C][C]14.6[/C][C]12.1883[/C][C]2.41174[/C][/ROW]
[ROW][C]212[/C][C]9.85[/C][C]13.2246[/C][C]-3.37461[/C][/ROW]
[ROW][C]213[/C][C]12.65[/C][C]13.9564[/C][C]-1.30641[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]12.7439[/C][C]-0.843919[/C][/ROW]
[ROW][C]215[/C][C]19.2[/C][C]12.2548[/C][C]6.94521[/C][/ROW]
[ROW][C]216[/C][C]16.6[/C][C]12.496[/C][C]4.10398[/C][/ROW]
[ROW][C]217[/C][C]11.2[/C][C]13.0015[/C][C]-1.80151[/C][/ROW]
[ROW][C]218[/C][C]15.25[/C][C]13.4337[/C][C]1.81629[/C][/ROW]
[ROW][C]219[/C][C]11.9[/C][C]12.4601[/C][C]-0.560053[/C][/ROW]
[ROW][C]220[/C][C]13.2[/C][C]12.6132[/C][C]0.586802[/C][/ROW]
[ROW][C]221[/C][C]16.35[/C][C]12.5886[/C][C]3.76144[/C][/ROW]
[ROW][C]222[/C][C]12.4[/C][C]13.2296[/C][C]-0.829593[/C][/ROW]
[ROW][C]223[/C][C]15.85[/C][C]12.5735[/C][C]3.27654[/C][/ROW]
[ROW][C]224[/C][C]14.35[/C][C]14.4702[/C][C]-0.120202[/C][/ROW]
[ROW][C]225[/C][C]18.15[/C][C]12.9067[/C][C]5.24333[/C][/ROW]
[ROW][C]226[/C][C]11.15[/C][C]12.4049[/C][C]-1.25493[/C][/ROW]
[ROW][C]227[/C][C]15.65[/C][C]13.1581[/C][C]2.49192[/C][/ROW]
[ROW][C]228[/C][C]17.75[/C][C]12.0412[/C][C]5.70877[/C][/ROW]
[ROW][C]229[/C][C]7.65[/C][C]11.5957[/C][C]-3.94566[/C][/ROW]
[ROW][C]230[/C][C]12.35[/C][C]13.458[/C][C]-1.10799[/C][/ROW]
[ROW][C]231[/C][C]15.6[/C][C]12.725[/C][C]2.87502[/C][/ROW]
[ROW][C]232[/C][C]19.3[/C][C]12.1637[/C][C]7.13626[/C][/ROW]
[ROW][C]233[/C][C]15.2[/C][C]13.017[/C][C]2.18297[/C][/ROW]
[ROW][C]234[/C][C]17.1[/C][C]13.4504[/C][C]3.64964[/C][/ROW]
[ROW][C]235[/C][C]15.6[/C][C]12.6205[/C][C]2.97946[/C][/ROW]
[ROW][C]236[/C][C]18.4[/C][C]12.6424[/C][C]5.75758[/C][/ROW]
[ROW][C]237[/C][C]19.05[/C][C]12.9915[/C][C]6.0585[/C][/ROW]
[ROW][C]238[/C][C]18.55[/C][C]13.3409[/C][C]5.20914[/C][/ROW]
[ROW][C]239[/C][C]19.1[/C][C]13.771[/C][C]5.32902[/C][/ROW]
[ROW][C]240[/C][C]13.1[/C][C]12.3893[/C][C]0.710674[/C][/ROW]
[ROW][C]241[/C][C]12.85[/C][C]12.4705[/C][C]0.379529[/C][/ROW]
[ROW][C]242[/C][C]9.5[/C][C]13.8525[/C][C]-4.35247[/C][/ROW]
[ROW][C]243[/C][C]4.5[/C][C]13.2952[/C][C]-8.79521[/C][/ROW]
[ROW][C]244[/C][C]11.85[/C][C]12.8392[/C][C]-0.989168[/C][/ROW]
[ROW][C]245[/C][C]13.6[/C][C]12.7249[/C][C]0.875104[/C][/ROW]
[ROW][C]246[/C][C]11.7[/C][C]14.7879[/C][C]-3.08792[/C][/ROW]
[ROW][C]247[/C][C]12.4[/C][C]12.4394[/C][C]-0.0393661[/C][/ROW]
[ROW][C]248[/C][C]13.35[/C][C]13.6661[/C][C]-0.31612[/C][/ROW]
[ROW][C]249[/C][C]11.4[/C][C]11.5466[/C][C]-0.146646[/C][/ROW]
[ROW][C]250[/C][C]14.9[/C][C]13.0038[/C][C]1.89622[/C][/ROW]
[ROW][C]251[/C][C]19.9[/C][C]13.1916[/C][C]6.7084[/C][/ROW]
[ROW][C]252[/C][C]17.75[/C][C]13.7599[/C][C]3.99005[/C][/ROW]
[ROW][C]253[/C][C]11.2[/C][C]13.8175[/C][C]-2.61753[/C][/ROW]
[ROW][C]254[/C][C]14.6[/C][C]12.1256[/C][C]2.47436[/C][/ROW]
[ROW][C]255[/C][C]17.6[/C][C]12.858[/C][C]4.74203[/C][/ROW]
[ROW][C]256[/C][C]14.05[/C][C]12.5661[/C][C]1.48388[/C][/ROW]
[ROW][C]257[/C][C]16.1[/C][C]12.9219[/C][C]3.1781[/C][/ROW]
[ROW][C]258[/C][C]13.35[/C][C]13.4925[/C][C]-0.142527[/C][/ROW]
[ROW][C]259[/C][C]11.85[/C][C]12.4958[/C][C]-0.645773[/C][/ROW]
[ROW][C]260[/C][C]11.95[/C][C]13.3268[/C][C]-1.37676[/C][/ROW]
[ROW][C]261[/C][C]14.75[/C][C]12.5518[/C][C]2.19821[/C][/ROW]
[ROW][C]262[/C][C]15.15[/C][C]11.6751[/C][C]3.4749[/C][/ROW]
[ROW][C]263[/C][C]13.2[/C][C]12.3733[/C][C]0.826694[/C][/ROW]
[ROW][C]264[/C][C]16.85[/C][C]13.0298[/C][C]3.82021[/C][/ROW]
[ROW][C]265[/C][C]7.85[/C][C]11.8799[/C][C]-4.02993[/C][/ROW]
[ROW][C]266[/C][C]7.7[/C][C]12.3606[/C][C]-4.66057[/C][/ROW]
[ROW][C]267[/C][C]12.6[/C][C]12.7447[/C][C]-0.144696[/C][/ROW]
[ROW][C]268[/C][C]7.85[/C][C]13.2807[/C][C]-5.43072[/C][/ROW]
[ROW][C]269[/C][C]10.95[/C][C]13.6278[/C][C]-2.67779[/C][/ROW]
[ROW][C]270[/C][C]12.35[/C][C]12.2198[/C][C]0.130216[/C][/ROW]
[ROW][C]271[/C][C]9.95[/C][C]12.951[/C][C]-3.00102[/C][/ROW]
[ROW][C]272[/C][C]14.9[/C][C]13.0237[/C][C]1.8763[/C][/ROW]
[ROW][C]273[/C][C]16.65[/C][C]12.8156[/C][C]3.83445[/C][/ROW]
[ROW][C]274[/C][C]13.4[/C][C]13.643[/C][C]-0.243033[/C][/ROW]
[ROW][C]275[/C][C]13.95[/C][C]13.4429[/C][C]0.507136[/C][/ROW]
[ROW][C]276[/C][C]15.7[/C][C]11.933[/C][C]3.76702[/C][/ROW]
[ROW][C]277[/C][C]16.85[/C][C]13.2057[/C][C]3.64433[/C][/ROW]
[ROW][C]278[/C][C]10.95[/C][C]12.7855[/C][C]-1.83547[/C][/ROW]
[ROW][C]279[/C][C]15.35[/C][C]12.0799[/C][C]3.27006[/C][/ROW]
[ROW][C]280[/C][C]12.2[/C][C]12.5685[/C][C]-0.368461[/C][/ROW]
[ROW][C]281[/C][C]15.1[/C][C]12.4974[/C][C]2.60262[/C][/ROW]
[ROW][C]282[/C][C]17.75[/C][C]12.9788[/C][C]4.77121[/C][/ROW]
[ROW][C]283[/C][C]15.2[/C][C]13.0723[/C][C]2.12774[/C][/ROW]
[ROW][C]284[/C][C]14.6[/C][C]13.323[/C][C]1.27701[/C][/ROW]
[ROW][C]285[/C][C]16.65[/C][C]12.4416[/C][C]4.20838[/C][/ROW]
[ROW][C]286[/C][C]8.1[/C][C]12.4982[/C][C]-4.39819[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270376&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270376&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.0441-0.144106
27.411.9668-4.56683
312.212.8048-0.604772
412.813.3554-0.555412
57.413.0127-5.61267
66.713.3147-6.61473
712.612.605-0.00500442
814.811.94512.85489
913.313.8962-0.596197
1011.112.0961-0.996116
118.215.1433-6.94327
1211.412.3242-0.924246
136.413.3828-6.98281
1410.611.497-0.897006
151213.1469-1.14687
166.312.8809-6.58092
1711.312.3731-1.07306
1811.912.4298-0.529788
199.312.6239-3.32393
209.613.3549-3.75485
211012.4648-2.46481
226.413.2735-6.87352
2313.813.21630.583669
2410.812.5734-1.77345
2513.812.42411.37586
2611.713.0267-1.32666
2710.912.5597-1.65969
2816.112.35733.74271
2913.413.33160.0683593
309.912.8039-2.90387
3111.512.5114-1.01141
328.311.7405-3.44052
3311.713.6075-1.90747
346.112.9247-6.82468
35912.1796-3.17961
369.712.5295-2.82953
3710.812.371-1.57099
3810.313.334-3.03403
3910.413.1184-2.71843
4012.712.9675-0.267474
419.313.5222-4.2222
4211.812.3766-0.576601
435.913.4923-7.59234
4411.413.5445-2.14451
451313.0355-0.0354838
4610.811.5929-0.792935
4712.312.26240.0376111
4811.313.0099-1.70993
4911.813.3444-1.54437
507.912.7893-4.88927
5112.712.55790.142093
5212.313.2901-0.990096
5311.612.199-0.59903
546.713.0202-6.32019
5510.913.009-2.10896
5612.112.6188-0.518795
5713.313.5205-0.220464
5810.113.0262-2.92616
595.711.9859-6.28591
6014.312.73741.56259
61813.1499-5.14992
6213.313.3571-0.0570629
639.313.576-4.27604
6412.512.7535-0.2535
657.611.7655-4.16552
6615.913.15822.74176
679.212.8128-3.61278
689.113.1426-4.04262
6911.112.3133-1.21327
701313.4907-0.49072
7114.513.07021.42981
7212.212.8418-0.641809
7312.313.1282-0.828159
7411.412.8696-1.46958
758.813.338-4.53801
7614.613.68750.912477
777.312.3879-5.08786
7812.612.13380.466235
791312.47360.526449
8012.613.182-0.581965
8113.213.7195-0.519484
829.912.1707-2.27074
837.712.3116-4.61156
8410.512.6971-2.19711
8513.412.50430.89573
8610.912.7772-1.8772
874.312.138-7.83797
8810.313.3378-3.0378
8911.813.0806-1.2806
9011.213.0402-1.84016
9111.412.472-1.07201
928.612.7672-4.16724
9313.212.5060.69404
9412.613.0463-0.446305
955.612.3572-6.75718
969.912.9854-3.08539
978.812.4536-3.6536
987.713.0587-5.35868
99912.5817-3.58168
1007.312.8592-5.55921
10111.412.9604-1.56036
10213.612.61510.984948
1037.912.5181-4.61813
10410.712.4575-1.75748
10510.312.2117-1.91166
1068.312.1835-3.88353
1079.612.7437-3.1437
10814.213.27610.923909
1098.513.0974-4.59741
11013.513.5614-0.0613588
1114.912.5951-7.69511
1126.412.719-6.31895
1139.613.5896-3.98958
11411.612.9409-1.34086
11511.112.8718-1.77177
1164.3513.9159-9.56589
11712.711.99710.702875
11818.112.89135.2087
11917.8512.36235.48765
12016.613.89212.70793
12112.613.4985-0.89853
12217.113.76743.33259
12319.113.37495.7251
12416.112.94993.15014
12513.3512.98580.364181
12618.413.81354.58648
12714.712.52792.17209
12810.612.6032-2.00318
12912.612.8016-0.201593
13016.212.29513.90491
13113.612.93060.669354
13218.913.12325.77682
13314.112.9571.14302
13414.512.77591.72414
13516.1512.70853.44146
13614.7512.96491.78505
13714.812.69612.10386
13812.4512.8052-0.355159
13912.6513.318-0.667993
14017.3512.73424.6158
1418.613.2181-4.6181
14218.412.74285.65721
14316.114.95541.14462
14411.612.5037-0.903658
14517.7513.04984.70019
14615.2512.84962.40037
14717.6512.61655.03346
14815.613.73521.86484
14916.3513.27313.07689
15017.6513.95973.69033
15113.614.8365-1.23653
15211.713.1388-1.43878
15314.3513.77010.579874
15414.7513.22711.52295
15518.2513.41414.83591
1569.912.828-2.92797
1571613.62932.37069
15818.2513.43214.81786
15916.8512.62034.22969
16014.613.04091.55907
16113.8513.9305-0.0804922
16218.9513.89215.05788
16315.613.14882.45118
16414.8513.74541.10462
16511.7512.7787-1.02874
16618.4513.03275.4173
16715.912.74443.15564
16817.113.19173.90826
16916.113.80052.29947
17019.914.55865.34138
17110.9512.1018-1.15181
17218.4512.51755.93253
17315.113.2931.80704
1741513.68631.31367
17511.3512.3616-1.01163
17615.9513.02462.92536
17718.113.22754.87252
17814.612.65821.94184
17915.413.9471.45295
18015.413.53691.86308
18117.612.21885.3812
18213.3513.7786-0.428559
18319.112.10396.99606
18415.3512.78722.56281
1857.612.4225-4.82252
18613.413.5068-0.106803
18713.913.36110.538853
18819.113.54725.55278
18915.2512.44892.8011
19012.912.47630.423701
19116.113.09933.00074
19217.3513.05764.29237
19313.1512.91430.235663
19412.1513.0052-0.855193
19512.612.6858-0.0858439
19610.3512.7831-2.43306
19715.412.21873.18134
1989.613.3451-3.74515
19918.212.88075.31925
20013.613.29780.302174
20114.8513.75391.09606
20214.7512.62312.12686
20314.112.74331.35673
20414.912.83812.06186
20516.2513.16873.08134
20619.2514.54514.70489
20713.614.1909-0.590863
20813.613.13260.467406
20915.6512.52853.12154
21012.7511.59621.15375
21114.612.18832.41174
2129.8513.2246-3.37461
21312.6513.9564-1.30641
21411.912.7439-0.843919
21519.212.25486.94521
21616.612.4964.10398
21711.213.0015-1.80151
21815.2513.43371.81629
21911.912.4601-0.560053
22013.212.61320.586802
22116.3512.58863.76144
22212.413.2296-0.829593
22315.8512.57353.27654
22414.3514.4702-0.120202
22518.1512.90675.24333
22611.1512.4049-1.25493
22715.6513.15812.49192
22817.7512.04125.70877
2297.6511.5957-3.94566
23012.3513.458-1.10799
23115.612.7252.87502
23219.312.16377.13626
23315.213.0172.18297
23417.113.45043.64964
23515.612.62052.97946
23618.412.64245.75758
23719.0512.99156.0585
23818.5513.34095.20914
23919.113.7715.32902
24013.112.38930.710674
24112.8512.47050.379529
2429.513.8525-4.35247
2434.513.2952-8.79521
24411.8512.8392-0.989168
24513.612.72490.875104
24611.714.7879-3.08792
24712.412.4394-0.0393661
24813.3513.6661-0.31612
24911.411.5466-0.146646
25014.913.00381.89622
25119.913.19166.7084
25217.7513.75993.99005
25311.213.8175-2.61753
25414.612.12562.47436
25517.612.8584.74203
25614.0512.56611.48388
25716.112.92193.1781
25813.3513.4925-0.142527
25911.8512.4958-0.645773
26011.9513.3268-1.37676
26114.7512.55182.19821
26215.1511.67513.4749
26313.212.37330.826694
26416.8513.02983.82021
2657.8511.8799-4.02993
2667.712.3606-4.66057
26712.612.7447-0.144696
2687.8513.2807-5.43072
26910.9513.6278-2.67779
27012.3512.21980.130216
2719.9512.951-3.00102
27214.913.02371.8763
27316.6512.81563.83445
27413.413.643-0.243033
27513.9513.44290.507136
27615.711.9333.76702
27716.8513.20573.64433
27810.9512.7855-1.83547
27915.3512.07993.27006
28012.212.5685-0.368461
28115.112.49742.60262
28217.7512.97884.77121
28315.213.07232.12774
28414.613.3231.27701
28516.6512.44164.20838
2868.112.4982-4.39819






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.296180.592360.70382
120.1767820.3535640.823218
130.4355740.8711480.564426
140.3228920.6457840.677108
150.219430.4388610.78057
160.2080470.4160940.791953
170.1613880.3227750.838612
180.1213880.2427760.878612
190.08632090.1726420.913679
200.06189750.1237950.938102
210.04224440.08448870.957756
220.02782310.05564620.972177
230.01673060.03346120.983269
240.009637390.01927480.990363
250.01135130.02270260.988649
260.007971190.01594240.992029
270.00466050.0093210.995339
280.004174620.008349250.995825
290.002515010.005030020.997485
300.001520110.003040220.99848
310.0008349050.001669810.999165
320.0006864660.001372930.999314
330.0003807420.0007614840.999619
340.0003064830.0006129660.999694
350.0003087510.0006175020.999691
360.01269830.02539670.987302
370.008552970.01710590.991447
380.006593780.01318760.993406
390.004396460.008792920.995604
400.002826430.005652860.997174
410.002144820.004289640.997855
420.001372580.002745150.998627
430.002792120.005584230.997208
440.002262410.004524830.997738
450.002264650.004529310.997735
460.002444960.004889910.997555
470.001589980.003179960.99841
480.001176350.002352690.998824
490.0009254880.001850980.999075
500.00076180.00152360.999238
510.0006375990.00127520.999362
520.0008366620.001673320.999163
530.000645380.001290760.999355
540.002143040.004286090.997857
550.001573410.003146810.998427
560.001561920.003123830.998438
570.00158080.00316160.998419
580.001187220.002374430.998813
590.002364710.004729410.997635
600.001885670.003771340.998114
610.002069460.004138910.997931
620.002582710.005165420.997417
630.002135010.004270010.997865
640.001809140.003618290.998191
650.003114680.006229360.996885
660.005621180.01124240.994379
670.005233980.0104680.994766
680.004843820.009687640.995156
690.003599970.007199940.9964
700.00335850.0067170.996641
710.003723790.007447580.996276
720.00297170.005943390.997028
730.002166770.004333540.997833
740.001609650.00321930.99839
750.001598450.003196890.998402
760.001789710.003579420.99821
770.002174320.004348640.997826
780.001688270.003376530.998312
790.001645750.00329150.998354
800.001282050.00256410.998718
810.00118340.00236680.998817
820.0009450040.001890010.999055
830.001089210.002178430.998911
840.0008246110.001649220.999175
850.0007343450.001468690.999266
860.0005887620.001177520.999411
870.002946580.005893150.997053
880.002437790.004875580.997562
890.001912180.003824360.998088
900.00147170.002943390.998528
910.001212660.002425310.998787
920.001270540.002541080.998729
930.001165610.002331220.998834
940.0009279220.001855840.999072
950.002548860.005097710.997451
960.002202460.004404910.997798
970.002052610.004105220.997947
980.00248660.004973190.997513
990.002413370.004826740.997587
1000.003497270.006994530.996503
1010.002806770.005613540.997193
1020.002820180.005640360.99718
1030.003298450.006596890.996702
1040.002741210.005482420.997259
1050.002343850.004687710.997656
1060.00273160.005463210.997268
1070.002463890.004927790.997536
1080.002707680.005415350.997292
1090.003065260.006130530.996935
1100.002796410.005592830.997204
1110.009146080.01829220.990854
1120.01699340.03398680.983007
1130.01814480.03628950.981855
1140.01641420.03282840.983586
1150.01445490.02890980.985545
1160.07271160.1454230.927288
1170.08307930.1661590.916921
1180.1565890.3131790.843411
1190.2543370.5086740.745663
1200.3016870.6033750.698313
1210.2774990.5549980.722501
1220.3398790.6797570.660121
1230.4676310.9352620.532369
1240.5004920.9990160.499508
1250.489090.9781790.51091
1260.5728840.8542320.427116
1270.5736310.8527390.426369
1280.5732690.8534620.426731
1290.5503970.8992070.449603
1300.5880120.8239760.411988
1310.5650210.8699580.434979
1320.6691350.661730.330865
1330.6563490.6873020.343651
1340.6448580.7102840.355142
1350.658820.6823610.34118
1360.6452710.7094590.354729
1370.6422350.715530.357765
1380.6218750.7562510.378125
1390.5998970.8002070.400103
1400.643130.7137410.35687
1410.6859180.6281650.314082
1420.7645680.4708650.235432
1430.7522910.4954180.247709
1440.7286790.5426420.271321
1450.7679330.4641340.232067
1460.7616340.4767320.238366
1470.797890.404220.20211
1480.7828720.4342550.217128
1490.7845060.4309890.215494
1500.7945070.4109860.205493
1510.7769260.4461480.223074
1520.7676470.4647060.232353
1530.7468960.5062090.253104
1540.7310020.5379970.268998
1550.7725710.4548590.227429
1560.7723780.4552450.227622
1570.7594180.4811640.240582
1580.7861220.4277560.213878
1590.796320.407360.20368
1600.777570.4448610.22243
1610.7530010.4939980.246999
1620.7890210.4219580.210979
1630.7796950.440610.220305
1640.7564710.4870580.243529
1650.740430.519140.25957
1660.7799990.4400030.220001
1670.7753530.4492950.224647
1680.7816690.4366630.218331
1690.7665410.4669190.233459
1700.8026760.3946480.197324
1710.7848650.4302710.215135
1720.8321070.3357870.167893
1730.8141590.3716820.185841
1740.7924360.4151280.207564
1750.7791970.4416050.220803
1760.770040.4599210.22996
1770.8002280.3995430.199772
1780.7815220.4369560.218478
1790.7596550.4806890.240345
1800.7382620.5234760.261738
1810.7713380.4573240.228662
1820.7446780.5106450.255322
1830.81170.37660.1883
1840.7959620.4080760.204038
1850.8386320.3227360.161368
1860.8154750.369050.184525
1870.7904120.4191760.209588
1880.8370380.3259240.162962
1890.825790.3484190.17421
1900.8046570.3906850.195343
1910.7951060.4097880.204894
1920.8095370.3809270.190463
1930.783290.433420.21671
1940.7581090.4837820.241891
1950.7296850.5406290.270315
1960.728380.543240.27162
1970.7150860.5698280.284914
1980.7368630.5262750.263137
1990.7641750.471650.235825
2000.7360230.5279540.263977
2010.7053980.5892040.294602
2020.6800260.6399480.319974
2030.6492760.7014480.350724
2040.6193820.7612350.380618
2050.5990790.8018420.400921
2060.683640.6327210.31636
2070.6485030.7029930.351497
2080.6135690.7728630.386431
2090.5964040.8071930.403596
2100.5651630.8696750.434837
2110.5403440.9193120.459656
2120.5777270.8445450.422273
2130.5460180.9079630.453982
2140.52660.94680.4734
2150.5764220.8471560.423578
2160.5703060.8593890.429694
2170.5528890.8942230.447111
2180.5207730.9584530.479227
2190.498050.99610.50195
2200.4599890.9199790.540011
2210.4433040.8866070.556696
2220.4035640.8071280.596436
2230.3873140.7746270.612686
2240.3471420.6942840.652858
2250.3710320.7420640.628968
2260.349250.69850.65075
2270.3257450.6514910.674255
2280.3477040.6954080.652296
2290.4186950.837390.581305
2300.3782320.7564650.621768
2310.3533340.7066680.646666
2320.4646340.9292670.535366
2330.4330320.8660650.566968
2340.4143760.8287510.585624
2350.3843090.7686170.615691
2360.4352840.8705680.564716
2370.5242510.9514980.475749
2380.6199820.7600350.380018
2390.6692880.6614240.330712
2400.6256080.7487830.374392
2410.5769220.8461570.423078
2420.5816420.8367170.418358
2430.8436210.3127580.156379
2440.8213610.3572780.178639
2450.7842180.4315640.215782
2460.8059660.3880690.194034
2470.791940.4161190.20806
2480.7507720.4984560.249228
2490.7140450.571910.285955
2500.6753550.6492910.324645
2510.7707560.4584890.229244
2520.7977170.4045660.202283
2530.766320.467360.23368
2540.7210970.5578050.278903
2550.7123430.5753140.287657
2560.6581260.6837470.341874
2570.6295930.7408140.370407
2580.5658620.8682760.434138
2590.5156360.9687290.484364
2600.4525390.9050790.547461
2610.3899630.7799270.610037
2620.5755130.8489740.424487
2630.665110.6697810.33489
2640.6333860.7332280.366614
2650.7222920.5554170.277708
2660.8851570.2296860.114843
2670.8345280.3309430.165472
2680.9489060.1021870.0510937
2690.9437080.1125840.056292
2700.9372240.1255530.0627763
2710.898610.2027810.10139
2720.8544070.2911870.145593
2730.8213770.3572470.178623
2740.9278520.1442960.0721481
2750.8511730.2976540.148827

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.29618 & 0.59236 & 0.70382 \tabularnewline
12 & 0.176782 & 0.353564 & 0.823218 \tabularnewline
13 & 0.435574 & 0.871148 & 0.564426 \tabularnewline
14 & 0.322892 & 0.645784 & 0.677108 \tabularnewline
15 & 0.21943 & 0.438861 & 0.78057 \tabularnewline
16 & 0.208047 & 0.416094 & 0.791953 \tabularnewline
17 & 0.161388 & 0.322775 & 0.838612 \tabularnewline
18 & 0.121388 & 0.242776 & 0.878612 \tabularnewline
19 & 0.0863209 & 0.172642 & 0.913679 \tabularnewline
20 & 0.0618975 & 0.123795 & 0.938102 \tabularnewline
21 & 0.0422444 & 0.0844887 & 0.957756 \tabularnewline
22 & 0.0278231 & 0.0556462 & 0.972177 \tabularnewline
23 & 0.0167306 & 0.0334612 & 0.983269 \tabularnewline
24 & 0.00963739 & 0.0192748 & 0.990363 \tabularnewline
25 & 0.0113513 & 0.0227026 & 0.988649 \tabularnewline
26 & 0.00797119 & 0.0159424 & 0.992029 \tabularnewline
27 & 0.0046605 & 0.009321 & 0.995339 \tabularnewline
28 & 0.00417462 & 0.00834925 & 0.995825 \tabularnewline
29 & 0.00251501 & 0.00503002 & 0.997485 \tabularnewline
30 & 0.00152011 & 0.00304022 & 0.99848 \tabularnewline
31 & 0.000834905 & 0.00166981 & 0.999165 \tabularnewline
32 & 0.000686466 & 0.00137293 & 0.999314 \tabularnewline
33 & 0.000380742 & 0.000761484 & 0.999619 \tabularnewline
34 & 0.000306483 & 0.000612966 & 0.999694 \tabularnewline
35 & 0.000308751 & 0.000617502 & 0.999691 \tabularnewline
36 & 0.0126983 & 0.0253967 & 0.987302 \tabularnewline
37 & 0.00855297 & 0.0171059 & 0.991447 \tabularnewline
38 & 0.00659378 & 0.0131876 & 0.993406 \tabularnewline
39 & 0.00439646 & 0.00879292 & 0.995604 \tabularnewline
40 & 0.00282643 & 0.00565286 & 0.997174 \tabularnewline
41 & 0.00214482 & 0.00428964 & 0.997855 \tabularnewline
42 & 0.00137258 & 0.00274515 & 0.998627 \tabularnewline
43 & 0.00279212 & 0.00558423 & 0.997208 \tabularnewline
44 & 0.00226241 & 0.00452483 & 0.997738 \tabularnewline
45 & 0.00226465 & 0.00452931 & 0.997735 \tabularnewline
46 & 0.00244496 & 0.00488991 & 0.997555 \tabularnewline
47 & 0.00158998 & 0.00317996 & 0.99841 \tabularnewline
48 & 0.00117635 & 0.00235269 & 0.998824 \tabularnewline
49 & 0.000925488 & 0.00185098 & 0.999075 \tabularnewline
50 & 0.0007618 & 0.0015236 & 0.999238 \tabularnewline
51 & 0.000637599 & 0.0012752 & 0.999362 \tabularnewline
52 & 0.000836662 & 0.00167332 & 0.999163 \tabularnewline
53 & 0.00064538 & 0.00129076 & 0.999355 \tabularnewline
54 & 0.00214304 & 0.00428609 & 0.997857 \tabularnewline
55 & 0.00157341 & 0.00314681 & 0.998427 \tabularnewline
56 & 0.00156192 & 0.00312383 & 0.998438 \tabularnewline
57 & 0.0015808 & 0.0031616 & 0.998419 \tabularnewline
58 & 0.00118722 & 0.00237443 & 0.998813 \tabularnewline
59 & 0.00236471 & 0.00472941 & 0.997635 \tabularnewline
60 & 0.00188567 & 0.00377134 & 0.998114 \tabularnewline
61 & 0.00206946 & 0.00413891 & 0.997931 \tabularnewline
62 & 0.00258271 & 0.00516542 & 0.997417 \tabularnewline
63 & 0.00213501 & 0.00427001 & 0.997865 \tabularnewline
64 & 0.00180914 & 0.00361829 & 0.998191 \tabularnewline
65 & 0.00311468 & 0.00622936 & 0.996885 \tabularnewline
66 & 0.00562118 & 0.0112424 & 0.994379 \tabularnewline
67 & 0.00523398 & 0.010468 & 0.994766 \tabularnewline
68 & 0.00484382 & 0.00968764 & 0.995156 \tabularnewline
69 & 0.00359997 & 0.00719994 & 0.9964 \tabularnewline
70 & 0.0033585 & 0.006717 & 0.996641 \tabularnewline
71 & 0.00372379 & 0.00744758 & 0.996276 \tabularnewline
72 & 0.0029717 & 0.00594339 & 0.997028 \tabularnewline
73 & 0.00216677 & 0.00433354 & 0.997833 \tabularnewline
74 & 0.00160965 & 0.0032193 & 0.99839 \tabularnewline
75 & 0.00159845 & 0.00319689 & 0.998402 \tabularnewline
76 & 0.00178971 & 0.00357942 & 0.99821 \tabularnewline
77 & 0.00217432 & 0.00434864 & 0.997826 \tabularnewline
78 & 0.00168827 & 0.00337653 & 0.998312 \tabularnewline
79 & 0.00164575 & 0.0032915 & 0.998354 \tabularnewline
80 & 0.00128205 & 0.0025641 & 0.998718 \tabularnewline
81 & 0.0011834 & 0.0023668 & 0.998817 \tabularnewline
82 & 0.000945004 & 0.00189001 & 0.999055 \tabularnewline
83 & 0.00108921 & 0.00217843 & 0.998911 \tabularnewline
84 & 0.000824611 & 0.00164922 & 0.999175 \tabularnewline
85 & 0.000734345 & 0.00146869 & 0.999266 \tabularnewline
86 & 0.000588762 & 0.00117752 & 0.999411 \tabularnewline
87 & 0.00294658 & 0.00589315 & 0.997053 \tabularnewline
88 & 0.00243779 & 0.00487558 & 0.997562 \tabularnewline
89 & 0.00191218 & 0.00382436 & 0.998088 \tabularnewline
90 & 0.0014717 & 0.00294339 & 0.998528 \tabularnewline
91 & 0.00121266 & 0.00242531 & 0.998787 \tabularnewline
92 & 0.00127054 & 0.00254108 & 0.998729 \tabularnewline
93 & 0.00116561 & 0.00233122 & 0.998834 \tabularnewline
94 & 0.000927922 & 0.00185584 & 0.999072 \tabularnewline
95 & 0.00254886 & 0.00509771 & 0.997451 \tabularnewline
96 & 0.00220246 & 0.00440491 & 0.997798 \tabularnewline
97 & 0.00205261 & 0.00410522 & 0.997947 \tabularnewline
98 & 0.0024866 & 0.00497319 & 0.997513 \tabularnewline
99 & 0.00241337 & 0.00482674 & 0.997587 \tabularnewline
100 & 0.00349727 & 0.00699453 & 0.996503 \tabularnewline
101 & 0.00280677 & 0.00561354 & 0.997193 \tabularnewline
102 & 0.00282018 & 0.00564036 & 0.99718 \tabularnewline
103 & 0.00329845 & 0.00659689 & 0.996702 \tabularnewline
104 & 0.00274121 & 0.00548242 & 0.997259 \tabularnewline
105 & 0.00234385 & 0.00468771 & 0.997656 \tabularnewline
106 & 0.0027316 & 0.00546321 & 0.997268 \tabularnewline
107 & 0.00246389 & 0.00492779 & 0.997536 \tabularnewline
108 & 0.00270768 & 0.00541535 & 0.997292 \tabularnewline
109 & 0.00306526 & 0.00613053 & 0.996935 \tabularnewline
110 & 0.00279641 & 0.00559283 & 0.997204 \tabularnewline
111 & 0.00914608 & 0.0182922 & 0.990854 \tabularnewline
112 & 0.0169934 & 0.0339868 & 0.983007 \tabularnewline
113 & 0.0181448 & 0.0362895 & 0.981855 \tabularnewline
114 & 0.0164142 & 0.0328284 & 0.983586 \tabularnewline
115 & 0.0144549 & 0.0289098 & 0.985545 \tabularnewline
116 & 0.0727116 & 0.145423 & 0.927288 \tabularnewline
117 & 0.0830793 & 0.166159 & 0.916921 \tabularnewline
118 & 0.156589 & 0.313179 & 0.843411 \tabularnewline
119 & 0.254337 & 0.508674 & 0.745663 \tabularnewline
120 & 0.301687 & 0.603375 & 0.698313 \tabularnewline
121 & 0.277499 & 0.554998 & 0.722501 \tabularnewline
122 & 0.339879 & 0.679757 & 0.660121 \tabularnewline
123 & 0.467631 & 0.935262 & 0.532369 \tabularnewline
124 & 0.500492 & 0.999016 & 0.499508 \tabularnewline
125 & 0.48909 & 0.978179 & 0.51091 \tabularnewline
126 & 0.572884 & 0.854232 & 0.427116 \tabularnewline
127 & 0.573631 & 0.852739 & 0.426369 \tabularnewline
128 & 0.573269 & 0.853462 & 0.426731 \tabularnewline
129 & 0.550397 & 0.899207 & 0.449603 \tabularnewline
130 & 0.588012 & 0.823976 & 0.411988 \tabularnewline
131 & 0.565021 & 0.869958 & 0.434979 \tabularnewline
132 & 0.669135 & 0.66173 & 0.330865 \tabularnewline
133 & 0.656349 & 0.687302 & 0.343651 \tabularnewline
134 & 0.644858 & 0.710284 & 0.355142 \tabularnewline
135 & 0.65882 & 0.682361 & 0.34118 \tabularnewline
136 & 0.645271 & 0.709459 & 0.354729 \tabularnewline
137 & 0.642235 & 0.71553 & 0.357765 \tabularnewline
138 & 0.621875 & 0.756251 & 0.378125 \tabularnewline
139 & 0.599897 & 0.800207 & 0.400103 \tabularnewline
140 & 0.64313 & 0.713741 & 0.35687 \tabularnewline
141 & 0.685918 & 0.628165 & 0.314082 \tabularnewline
142 & 0.764568 & 0.470865 & 0.235432 \tabularnewline
143 & 0.752291 & 0.495418 & 0.247709 \tabularnewline
144 & 0.728679 & 0.542642 & 0.271321 \tabularnewline
145 & 0.767933 & 0.464134 & 0.232067 \tabularnewline
146 & 0.761634 & 0.476732 & 0.238366 \tabularnewline
147 & 0.79789 & 0.40422 & 0.20211 \tabularnewline
148 & 0.782872 & 0.434255 & 0.217128 \tabularnewline
149 & 0.784506 & 0.430989 & 0.215494 \tabularnewline
150 & 0.794507 & 0.410986 & 0.205493 \tabularnewline
151 & 0.776926 & 0.446148 & 0.223074 \tabularnewline
152 & 0.767647 & 0.464706 & 0.232353 \tabularnewline
153 & 0.746896 & 0.506209 & 0.253104 \tabularnewline
154 & 0.731002 & 0.537997 & 0.268998 \tabularnewline
155 & 0.772571 & 0.454859 & 0.227429 \tabularnewline
156 & 0.772378 & 0.455245 & 0.227622 \tabularnewline
157 & 0.759418 & 0.481164 & 0.240582 \tabularnewline
158 & 0.786122 & 0.427756 & 0.213878 \tabularnewline
159 & 0.79632 & 0.40736 & 0.20368 \tabularnewline
160 & 0.77757 & 0.444861 & 0.22243 \tabularnewline
161 & 0.753001 & 0.493998 & 0.246999 \tabularnewline
162 & 0.789021 & 0.421958 & 0.210979 \tabularnewline
163 & 0.779695 & 0.44061 & 0.220305 \tabularnewline
164 & 0.756471 & 0.487058 & 0.243529 \tabularnewline
165 & 0.74043 & 0.51914 & 0.25957 \tabularnewline
166 & 0.779999 & 0.440003 & 0.220001 \tabularnewline
167 & 0.775353 & 0.449295 & 0.224647 \tabularnewline
168 & 0.781669 & 0.436663 & 0.218331 \tabularnewline
169 & 0.766541 & 0.466919 & 0.233459 \tabularnewline
170 & 0.802676 & 0.394648 & 0.197324 \tabularnewline
171 & 0.784865 & 0.430271 & 0.215135 \tabularnewline
172 & 0.832107 & 0.335787 & 0.167893 \tabularnewline
173 & 0.814159 & 0.371682 & 0.185841 \tabularnewline
174 & 0.792436 & 0.415128 & 0.207564 \tabularnewline
175 & 0.779197 & 0.441605 & 0.220803 \tabularnewline
176 & 0.77004 & 0.459921 & 0.22996 \tabularnewline
177 & 0.800228 & 0.399543 & 0.199772 \tabularnewline
178 & 0.781522 & 0.436956 & 0.218478 \tabularnewline
179 & 0.759655 & 0.480689 & 0.240345 \tabularnewline
180 & 0.738262 & 0.523476 & 0.261738 \tabularnewline
181 & 0.771338 & 0.457324 & 0.228662 \tabularnewline
182 & 0.744678 & 0.510645 & 0.255322 \tabularnewline
183 & 0.8117 & 0.3766 & 0.1883 \tabularnewline
184 & 0.795962 & 0.408076 & 0.204038 \tabularnewline
185 & 0.838632 & 0.322736 & 0.161368 \tabularnewline
186 & 0.815475 & 0.36905 & 0.184525 \tabularnewline
187 & 0.790412 & 0.419176 & 0.209588 \tabularnewline
188 & 0.837038 & 0.325924 & 0.162962 \tabularnewline
189 & 0.82579 & 0.348419 & 0.17421 \tabularnewline
190 & 0.804657 & 0.390685 & 0.195343 \tabularnewline
191 & 0.795106 & 0.409788 & 0.204894 \tabularnewline
192 & 0.809537 & 0.380927 & 0.190463 \tabularnewline
193 & 0.78329 & 0.43342 & 0.21671 \tabularnewline
194 & 0.758109 & 0.483782 & 0.241891 \tabularnewline
195 & 0.729685 & 0.540629 & 0.270315 \tabularnewline
196 & 0.72838 & 0.54324 & 0.27162 \tabularnewline
197 & 0.715086 & 0.569828 & 0.284914 \tabularnewline
198 & 0.736863 & 0.526275 & 0.263137 \tabularnewline
199 & 0.764175 & 0.47165 & 0.235825 \tabularnewline
200 & 0.736023 & 0.527954 & 0.263977 \tabularnewline
201 & 0.705398 & 0.589204 & 0.294602 \tabularnewline
202 & 0.680026 & 0.639948 & 0.319974 \tabularnewline
203 & 0.649276 & 0.701448 & 0.350724 \tabularnewline
204 & 0.619382 & 0.761235 & 0.380618 \tabularnewline
205 & 0.599079 & 0.801842 & 0.400921 \tabularnewline
206 & 0.68364 & 0.632721 & 0.31636 \tabularnewline
207 & 0.648503 & 0.702993 & 0.351497 \tabularnewline
208 & 0.613569 & 0.772863 & 0.386431 \tabularnewline
209 & 0.596404 & 0.807193 & 0.403596 \tabularnewline
210 & 0.565163 & 0.869675 & 0.434837 \tabularnewline
211 & 0.540344 & 0.919312 & 0.459656 \tabularnewline
212 & 0.577727 & 0.844545 & 0.422273 \tabularnewline
213 & 0.546018 & 0.907963 & 0.453982 \tabularnewline
214 & 0.5266 & 0.9468 & 0.4734 \tabularnewline
215 & 0.576422 & 0.847156 & 0.423578 \tabularnewline
216 & 0.570306 & 0.859389 & 0.429694 \tabularnewline
217 & 0.552889 & 0.894223 & 0.447111 \tabularnewline
218 & 0.520773 & 0.958453 & 0.479227 \tabularnewline
219 & 0.49805 & 0.9961 & 0.50195 \tabularnewline
220 & 0.459989 & 0.919979 & 0.540011 \tabularnewline
221 & 0.443304 & 0.886607 & 0.556696 \tabularnewline
222 & 0.403564 & 0.807128 & 0.596436 \tabularnewline
223 & 0.387314 & 0.774627 & 0.612686 \tabularnewline
224 & 0.347142 & 0.694284 & 0.652858 \tabularnewline
225 & 0.371032 & 0.742064 & 0.628968 \tabularnewline
226 & 0.34925 & 0.6985 & 0.65075 \tabularnewline
227 & 0.325745 & 0.651491 & 0.674255 \tabularnewline
228 & 0.347704 & 0.695408 & 0.652296 \tabularnewline
229 & 0.418695 & 0.83739 & 0.581305 \tabularnewline
230 & 0.378232 & 0.756465 & 0.621768 \tabularnewline
231 & 0.353334 & 0.706668 & 0.646666 \tabularnewline
232 & 0.464634 & 0.929267 & 0.535366 \tabularnewline
233 & 0.433032 & 0.866065 & 0.566968 \tabularnewline
234 & 0.414376 & 0.828751 & 0.585624 \tabularnewline
235 & 0.384309 & 0.768617 & 0.615691 \tabularnewline
236 & 0.435284 & 0.870568 & 0.564716 \tabularnewline
237 & 0.524251 & 0.951498 & 0.475749 \tabularnewline
238 & 0.619982 & 0.760035 & 0.380018 \tabularnewline
239 & 0.669288 & 0.661424 & 0.330712 \tabularnewline
240 & 0.625608 & 0.748783 & 0.374392 \tabularnewline
241 & 0.576922 & 0.846157 & 0.423078 \tabularnewline
242 & 0.581642 & 0.836717 & 0.418358 \tabularnewline
243 & 0.843621 & 0.312758 & 0.156379 \tabularnewline
244 & 0.821361 & 0.357278 & 0.178639 \tabularnewline
245 & 0.784218 & 0.431564 & 0.215782 \tabularnewline
246 & 0.805966 & 0.388069 & 0.194034 \tabularnewline
247 & 0.79194 & 0.416119 & 0.20806 \tabularnewline
248 & 0.750772 & 0.498456 & 0.249228 \tabularnewline
249 & 0.714045 & 0.57191 & 0.285955 \tabularnewline
250 & 0.675355 & 0.649291 & 0.324645 \tabularnewline
251 & 0.770756 & 0.458489 & 0.229244 \tabularnewline
252 & 0.797717 & 0.404566 & 0.202283 \tabularnewline
253 & 0.76632 & 0.46736 & 0.23368 \tabularnewline
254 & 0.721097 & 0.557805 & 0.278903 \tabularnewline
255 & 0.712343 & 0.575314 & 0.287657 \tabularnewline
256 & 0.658126 & 0.683747 & 0.341874 \tabularnewline
257 & 0.629593 & 0.740814 & 0.370407 \tabularnewline
258 & 0.565862 & 0.868276 & 0.434138 \tabularnewline
259 & 0.515636 & 0.968729 & 0.484364 \tabularnewline
260 & 0.452539 & 0.905079 & 0.547461 \tabularnewline
261 & 0.389963 & 0.779927 & 0.610037 \tabularnewline
262 & 0.575513 & 0.848974 & 0.424487 \tabularnewline
263 & 0.66511 & 0.669781 & 0.33489 \tabularnewline
264 & 0.633386 & 0.733228 & 0.366614 \tabularnewline
265 & 0.722292 & 0.555417 & 0.277708 \tabularnewline
266 & 0.885157 & 0.229686 & 0.114843 \tabularnewline
267 & 0.834528 & 0.330943 & 0.165472 \tabularnewline
268 & 0.948906 & 0.102187 & 0.0510937 \tabularnewline
269 & 0.943708 & 0.112584 & 0.056292 \tabularnewline
270 & 0.937224 & 0.125553 & 0.0627763 \tabularnewline
271 & 0.89861 & 0.202781 & 0.10139 \tabularnewline
272 & 0.854407 & 0.291187 & 0.145593 \tabularnewline
273 & 0.821377 & 0.357247 & 0.178623 \tabularnewline
274 & 0.927852 & 0.144296 & 0.0721481 \tabularnewline
275 & 0.851173 & 0.297654 & 0.148827 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270376&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]0.29618[/C][C]0.59236[/C][C]0.70382[/C][/ROW]
[ROW][C]12[/C][C]0.176782[/C][C]0.353564[/C][C]0.823218[/C][/ROW]
[ROW][C]13[/C][C]0.435574[/C][C]0.871148[/C][C]0.564426[/C][/ROW]
[ROW][C]14[/C][C]0.322892[/C][C]0.645784[/C][C]0.677108[/C][/ROW]
[ROW][C]15[/C][C]0.21943[/C][C]0.438861[/C][C]0.78057[/C][/ROW]
[ROW][C]16[/C][C]0.208047[/C][C]0.416094[/C][C]0.791953[/C][/ROW]
[ROW][C]17[/C][C]0.161388[/C][C]0.322775[/C][C]0.838612[/C][/ROW]
[ROW][C]18[/C][C]0.121388[/C][C]0.242776[/C][C]0.878612[/C][/ROW]
[ROW][C]19[/C][C]0.0863209[/C][C]0.172642[/C][C]0.913679[/C][/ROW]
[ROW][C]20[/C][C]0.0618975[/C][C]0.123795[/C][C]0.938102[/C][/ROW]
[ROW][C]21[/C][C]0.0422444[/C][C]0.0844887[/C][C]0.957756[/C][/ROW]
[ROW][C]22[/C][C]0.0278231[/C][C]0.0556462[/C][C]0.972177[/C][/ROW]
[ROW][C]23[/C][C]0.0167306[/C][C]0.0334612[/C][C]0.983269[/C][/ROW]
[ROW][C]24[/C][C]0.00963739[/C][C]0.0192748[/C][C]0.990363[/C][/ROW]
[ROW][C]25[/C][C]0.0113513[/C][C]0.0227026[/C][C]0.988649[/C][/ROW]
[ROW][C]26[/C][C]0.00797119[/C][C]0.0159424[/C][C]0.992029[/C][/ROW]
[ROW][C]27[/C][C]0.0046605[/C][C]0.009321[/C][C]0.995339[/C][/ROW]
[ROW][C]28[/C][C]0.00417462[/C][C]0.00834925[/C][C]0.995825[/C][/ROW]
[ROW][C]29[/C][C]0.00251501[/C][C]0.00503002[/C][C]0.997485[/C][/ROW]
[ROW][C]30[/C][C]0.00152011[/C][C]0.00304022[/C][C]0.99848[/C][/ROW]
[ROW][C]31[/C][C]0.000834905[/C][C]0.00166981[/C][C]0.999165[/C][/ROW]
[ROW][C]32[/C][C]0.000686466[/C][C]0.00137293[/C][C]0.999314[/C][/ROW]
[ROW][C]33[/C][C]0.000380742[/C][C]0.000761484[/C][C]0.999619[/C][/ROW]
[ROW][C]34[/C][C]0.000306483[/C][C]0.000612966[/C][C]0.999694[/C][/ROW]
[ROW][C]35[/C][C]0.000308751[/C][C]0.000617502[/C][C]0.999691[/C][/ROW]
[ROW][C]36[/C][C]0.0126983[/C][C]0.0253967[/C][C]0.987302[/C][/ROW]
[ROW][C]37[/C][C]0.00855297[/C][C]0.0171059[/C][C]0.991447[/C][/ROW]
[ROW][C]38[/C][C]0.00659378[/C][C]0.0131876[/C][C]0.993406[/C][/ROW]
[ROW][C]39[/C][C]0.00439646[/C][C]0.00879292[/C][C]0.995604[/C][/ROW]
[ROW][C]40[/C][C]0.00282643[/C][C]0.00565286[/C][C]0.997174[/C][/ROW]
[ROW][C]41[/C][C]0.00214482[/C][C]0.00428964[/C][C]0.997855[/C][/ROW]
[ROW][C]42[/C][C]0.00137258[/C][C]0.00274515[/C][C]0.998627[/C][/ROW]
[ROW][C]43[/C][C]0.00279212[/C][C]0.00558423[/C][C]0.997208[/C][/ROW]
[ROW][C]44[/C][C]0.00226241[/C][C]0.00452483[/C][C]0.997738[/C][/ROW]
[ROW][C]45[/C][C]0.00226465[/C][C]0.00452931[/C][C]0.997735[/C][/ROW]
[ROW][C]46[/C][C]0.00244496[/C][C]0.00488991[/C][C]0.997555[/C][/ROW]
[ROW][C]47[/C][C]0.00158998[/C][C]0.00317996[/C][C]0.99841[/C][/ROW]
[ROW][C]48[/C][C]0.00117635[/C][C]0.00235269[/C][C]0.998824[/C][/ROW]
[ROW][C]49[/C][C]0.000925488[/C][C]0.00185098[/C][C]0.999075[/C][/ROW]
[ROW][C]50[/C][C]0.0007618[/C][C]0.0015236[/C][C]0.999238[/C][/ROW]
[ROW][C]51[/C][C]0.000637599[/C][C]0.0012752[/C][C]0.999362[/C][/ROW]
[ROW][C]52[/C][C]0.000836662[/C][C]0.00167332[/C][C]0.999163[/C][/ROW]
[ROW][C]53[/C][C]0.00064538[/C][C]0.00129076[/C][C]0.999355[/C][/ROW]
[ROW][C]54[/C][C]0.00214304[/C][C]0.00428609[/C][C]0.997857[/C][/ROW]
[ROW][C]55[/C][C]0.00157341[/C][C]0.00314681[/C][C]0.998427[/C][/ROW]
[ROW][C]56[/C][C]0.00156192[/C][C]0.00312383[/C][C]0.998438[/C][/ROW]
[ROW][C]57[/C][C]0.0015808[/C][C]0.0031616[/C][C]0.998419[/C][/ROW]
[ROW][C]58[/C][C]0.00118722[/C][C]0.00237443[/C][C]0.998813[/C][/ROW]
[ROW][C]59[/C][C]0.00236471[/C][C]0.00472941[/C][C]0.997635[/C][/ROW]
[ROW][C]60[/C][C]0.00188567[/C][C]0.00377134[/C][C]0.998114[/C][/ROW]
[ROW][C]61[/C][C]0.00206946[/C][C]0.00413891[/C][C]0.997931[/C][/ROW]
[ROW][C]62[/C][C]0.00258271[/C][C]0.00516542[/C][C]0.997417[/C][/ROW]
[ROW][C]63[/C][C]0.00213501[/C][C]0.00427001[/C][C]0.997865[/C][/ROW]
[ROW][C]64[/C][C]0.00180914[/C][C]0.00361829[/C][C]0.998191[/C][/ROW]
[ROW][C]65[/C][C]0.00311468[/C][C]0.00622936[/C][C]0.996885[/C][/ROW]
[ROW][C]66[/C][C]0.00562118[/C][C]0.0112424[/C][C]0.994379[/C][/ROW]
[ROW][C]67[/C][C]0.00523398[/C][C]0.010468[/C][C]0.994766[/C][/ROW]
[ROW][C]68[/C][C]0.00484382[/C][C]0.00968764[/C][C]0.995156[/C][/ROW]
[ROW][C]69[/C][C]0.00359997[/C][C]0.00719994[/C][C]0.9964[/C][/ROW]
[ROW][C]70[/C][C]0.0033585[/C][C]0.006717[/C][C]0.996641[/C][/ROW]
[ROW][C]71[/C][C]0.00372379[/C][C]0.00744758[/C][C]0.996276[/C][/ROW]
[ROW][C]72[/C][C]0.0029717[/C][C]0.00594339[/C][C]0.997028[/C][/ROW]
[ROW][C]73[/C][C]0.00216677[/C][C]0.00433354[/C][C]0.997833[/C][/ROW]
[ROW][C]74[/C][C]0.00160965[/C][C]0.0032193[/C][C]0.99839[/C][/ROW]
[ROW][C]75[/C][C]0.00159845[/C][C]0.00319689[/C][C]0.998402[/C][/ROW]
[ROW][C]76[/C][C]0.00178971[/C][C]0.00357942[/C][C]0.99821[/C][/ROW]
[ROW][C]77[/C][C]0.00217432[/C][C]0.00434864[/C][C]0.997826[/C][/ROW]
[ROW][C]78[/C][C]0.00168827[/C][C]0.00337653[/C][C]0.998312[/C][/ROW]
[ROW][C]79[/C][C]0.00164575[/C][C]0.0032915[/C][C]0.998354[/C][/ROW]
[ROW][C]80[/C][C]0.00128205[/C][C]0.0025641[/C][C]0.998718[/C][/ROW]
[ROW][C]81[/C][C]0.0011834[/C][C]0.0023668[/C][C]0.998817[/C][/ROW]
[ROW][C]82[/C][C]0.000945004[/C][C]0.00189001[/C][C]0.999055[/C][/ROW]
[ROW][C]83[/C][C]0.00108921[/C][C]0.00217843[/C][C]0.998911[/C][/ROW]
[ROW][C]84[/C][C]0.000824611[/C][C]0.00164922[/C][C]0.999175[/C][/ROW]
[ROW][C]85[/C][C]0.000734345[/C][C]0.00146869[/C][C]0.999266[/C][/ROW]
[ROW][C]86[/C][C]0.000588762[/C][C]0.00117752[/C][C]0.999411[/C][/ROW]
[ROW][C]87[/C][C]0.00294658[/C][C]0.00589315[/C][C]0.997053[/C][/ROW]
[ROW][C]88[/C][C]0.00243779[/C][C]0.00487558[/C][C]0.997562[/C][/ROW]
[ROW][C]89[/C][C]0.00191218[/C][C]0.00382436[/C][C]0.998088[/C][/ROW]
[ROW][C]90[/C][C]0.0014717[/C][C]0.00294339[/C][C]0.998528[/C][/ROW]
[ROW][C]91[/C][C]0.00121266[/C][C]0.00242531[/C][C]0.998787[/C][/ROW]
[ROW][C]92[/C][C]0.00127054[/C][C]0.00254108[/C][C]0.998729[/C][/ROW]
[ROW][C]93[/C][C]0.00116561[/C][C]0.00233122[/C][C]0.998834[/C][/ROW]
[ROW][C]94[/C][C]0.000927922[/C][C]0.00185584[/C][C]0.999072[/C][/ROW]
[ROW][C]95[/C][C]0.00254886[/C][C]0.00509771[/C][C]0.997451[/C][/ROW]
[ROW][C]96[/C][C]0.00220246[/C][C]0.00440491[/C][C]0.997798[/C][/ROW]
[ROW][C]97[/C][C]0.00205261[/C][C]0.00410522[/C][C]0.997947[/C][/ROW]
[ROW][C]98[/C][C]0.0024866[/C][C]0.00497319[/C][C]0.997513[/C][/ROW]
[ROW][C]99[/C][C]0.00241337[/C][C]0.00482674[/C][C]0.997587[/C][/ROW]
[ROW][C]100[/C][C]0.00349727[/C][C]0.00699453[/C][C]0.996503[/C][/ROW]
[ROW][C]101[/C][C]0.00280677[/C][C]0.00561354[/C][C]0.997193[/C][/ROW]
[ROW][C]102[/C][C]0.00282018[/C][C]0.00564036[/C][C]0.99718[/C][/ROW]
[ROW][C]103[/C][C]0.00329845[/C][C]0.00659689[/C][C]0.996702[/C][/ROW]
[ROW][C]104[/C][C]0.00274121[/C][C]0.00548242[/C][C]0.997259[/C][/ROW]
[ROW][C]105[/C][C]0.00234385[/C][C]0.00468771[/C][C]0.997656[/C][/ROW]
[ROW][C]106[/C][C]0.0027316[/C][C]0.00546321[/C][C]0.997268[/C][/ROW]
[ROW][C]107[/C][C]0.00246389[/C][C]0.00492779[/C][C]0.997536[/C][/ROW]
[ROW][C]108[/C][C]0.00270768[/C][C]0.00541535[/C][C]0.997292[/C][/ROW]
[ROW][C]109[/C][C]0.00306526[/C][C]0.00613053[/C][C]0.996935[/C][/ROW]
[ROW][C]110[/C][C]0.00279641[/C][C]0.00559283[/C][C]0.997204[/C][/ROW]
[ROW][C]111[/C][C]0.00914608[/C][C]0.0182922[/C][C]0.990854[/C][/ROW]
[ROW][C]112[/C][C]0.0169934[/C][C]0.0339868[/C][C]0.983007[/C][/ROW]
[ROW][C]113[/C][C]0.0181448[/C][C]0.0362895[/C][C]0.981855[/C][/ROW]
[ROW][C]114[/C][C]0.0164142[/C][C]0.0328284[/C][C]0.983586[/C][/ROW]
[ROW][C]115[/C][C]0.0144549[/C][C]0.0289098[/C][C]0.985545[/C][/ROW]
[ROW][C]116[/C][C]0.0727116[/C][C]0.145423[/C][C]0.927288[/C][/ROW]
[ROW][C]117[/C][C]0.0830793[/C][C]0.166159[/C][C]0.916921[/C][/ROW]
[ROW][C]118[/C][C]0.156589[/C][C]0.313179[/C][C]0.843411[/C][/ROW]
[ROW][C]119[/C][C]0.254337[/C][C]0.508674[/C][C]0.745663[/C][/ROW]
[ROW][C]120[/C][C]0.301687[/C][C]0.603375[/C][C]0.698313[/C][/ROW]
[ROW][C]121[/C][C]0.277499[/C][C]0.554998[/C][C]0.722501[/C][/ROW]
[ROW][C]122[/C][C]0.339879[/C][C]0.679757[/C][C]0.660121[/C][/ROW]
[ROW][C]123[/C][C]0.467631[/C][C]0.935262[/C][C]0.532369[/C][/ROW]
[ROW][C]124[/C][C]0.500492[/C][C]0.999016[/C][C]0.499508[/C][/ROW]
[ROW][C]125[/C][C]0.48909[/C][C]0.978179[/C][C]0.51091[/C][/ROW]
[ROW][C]126[/C][C]0.572884[/C][C]0.854232[/C][C]0.427116[/C][/ROW]
[ROW][C]127[/C][C]0.573631[/C][C]0.852739[/C][C]0.426369[/C][/ROW]
[ROW][C]128[/C][C]0.573269[/C][C]0.853462[/C][C]0.426731[/C][/ROW]
[ROW][C]129[/C][C]0.550397[/C][C]0.899207[/C][C]0.449603[/C][/ROW]
[ROW][C]130[/C][C]0.588012[/C][C]0.823976[/C][C]0.411988[/C][/ROW]
[ROW][C]131[/C][C]0.565021[/C][C]0.869958[/C][C]0.434979[/C][/ROW]
[ROW][C]132[/C][C]0.669135[/C][C]0.66173[/C][C]0.330865[/C][/ROW]
[ROW][C]133[/C][C]0.656349[/C][C]0.687302[/C][C]0.343651[/C][/ROW]
[ROW][C]134[/C][C]0.644858[/C][C]0.710284[/C][C]0.355142[/C][/ROW]
[ROW][C]135[/C][C]0.65882[/C][C]0.682361[/C][C]0.34118[/C][/ROW]
[ROW][C]136[/C][C]0.645271[/C][C]0.709459[/C][C]0.354729[/C][/ROW]
[ROW][C]137[/C][C]0.642235[/C][C]0.71553[/C][C]0.357765[/C][/ROW]
[ROW][C]138[/C][C]0.621875[/C][C]0.756251[/C][C]0.378125[/C][/ROW]
[ROW][C]139[/C][C]0.599897[/C][C]0.800207[/C][C]0.400103[/C][/ROW]
[ROW][C]140[/C][C]0.64313[/C][C]0.713741[/C][C]0.35687[/C][/ROW]
[ROW][C]141[/C][C]0.685918[/C][C]0.628165[/C][C]0.314082[/C][/ROW]
[ROW][C]142[/C][C]0.764568[/C][C]0.470865[/C][C]0.235432[/C][/ROW]
[ROW][C]143[/C][C]0.752291[/C][C]0.495418[/C][C]0.247709[/C][/ROW]
[ROW][C]144[/C][C]0.728679[/C][C]0.542642[/C][C]0.271321[/C][/ROW]
[ROW][C]145[/C][C]0.767933[/C][C]0.464134[/C][C]0.232067[/C][/ROW]
[ROW][C]146[/C][C]0.761634[/C][C]0.476732[/C][C]0.238366[/C][/ROW]
[ROW][C]147[/C][C]0.79789[/C][C]0.40422[/C][C]0.20211[/C][/ROW]
[ROW][C]148[/C][C]0.782872[/C][C]0.434255[/C][C]0.217128[/C][/ROW]
[ROW][C]149[/C][C]0.784506[/C][C]0.430989[/C][C]0.215494[/C][/ROW]
[ROW][C]150[/C][C]0.794507[/C][C]0.410986[/C][C]0.205493[/C][/ROW]
[ROW][C]151[/C][C]0.776926[/C][C]0.446148[/C][C]0.223074[/C][/ROW]
[ROW][C]152[/C][C]0.767647[/C][C]0.464706[/C][C]0.232353[/C][/ROW]
[ROW][C]153[/C][C]0.746896[/C][C]0.506209[/C][C]0.253104[/C][/ROW]
[ROW][C]154[/C][C]0.731002[/C][C]0.537997[/C][C]0.268998[/C][/ROW]
[ROW][C]155[/C][C]0.772571[/C][C]0.454859[/C][C]0.227429[/C][/ROW]
[ROW][C]156[/C][C]0.772378[/C][C]0.455245[/C][C]0.227622[/C][/ROW]
[ROW][C]157[/C][C]0.759418[/C][C]0.481164[/C][C]0.240582[/C][/ROW]
[ROW][C]158[/C][C]0.786122[/C][C]0.427756[/C][C]0.213878[/C][/ROW]
[ROW][C]159[/C][C]0.79632[/C][C]0.40736[/C][C]0.20368[/C][/ROW]
[ROW][C]160[/C][C]0.77757[/C][C]0.444861[/C][C]0.22243[/C][/ROW]
[ROW][C]161[/C][C]0.753001[/C][C]0.493998[/C][C]0.246999[/C][/ROW]
[ROW][C]162[/C][C]0.789021[/C][C]0.421958[/C][C]0.210979[/C][/ROW]
[ROW][C]163[/C][C]0.779695[/C][C]0.44061[/C][C]0.220305[/C][/ROW]
[ROW][C]164[/C][C]0.756471[/C][C]0.487058[/C][C]0.243529[/C][/ROW]
[ROW][C]165[/C][C]0.74043[/C][C]0.51914[/C][C]0.25957[/C][/ROW]
[ROW][C]166[/C][C]0.779999[/C][C]0.440003[/C][C]0.220001[/C][/ROW]
[ROW][C]167[/C][C]0.775353[/C][C]0.449295[/C][C]0.224647[/C][/ROW]
[ROW][C]168[/C][C]0.781669[/C][C]0.436663[/C][C]0.218331[/C][/ROW]
[ROW][C]169[/C][C]0.766541[/C][C]0.466919[/C][C]0.233459[/C][/ROW]
[ROW][C]170[/C][C]0.802676[/C][C]0.394648[/C][C]0.197324[/C][/ROW]
[ROW][C]171[/C][C]0.784865[/C][C]0.430271[/C][C]0.215135[/C][/ROW]
[ROW][C]172[/C][C]0.832107[/C][C]0.335787[/C][C]0.167893[/C][/ROW]
[ROW][C]173[/C][C]0.814159[/C][C]0.371682[/C][C]0.185841[/C][/ROW]
[ROW][C]174[/C][C]0.792436[/C][C]0.415128[/C][C]0.207564[/C][/ROW]
[ROW][C]175[/C][C]0.779197[/C][C]0.441605[/C][C]0.220803[/C][/ROW]
[ROW][C]176[/C][C]0.77004[/C][C]0.459921[/C][C]0.22996[/C][/ROW]
[ROW][C]177[/C][C]0.800228[/C][C]0.399543[/C][C]0.199772[/C][/ROW]
[ROW][C]178[/C][C]0.781522[/C][C]0.436956[/C][C]0.218478[/C][/ROW]
[ROW][C]179[/C][C]0.759655[/C][C]0.480689[/C][C]0.240345[/C][/ROW]
[ROW][C]180[/C][C]0.738262[/C][C]0.523476[/C][C]0.261738[/C][/ROW]
[ROW][C]181[/C][C]0.771338[/C][C]0.457324[/C][C]0.228662[/C][/ROW]
[ROW][C]182[/C][C]0.744678[/C][C]0.510645[/C][C]0.255322[/C][/ROW]
[ROW][C]183[/C][C]0.8117[/C][C]0.3766[/C][C]0.1883[/C][/ROW]
[ROW][C]184[/C][C]0.795962[/C][C]0.408076[/C][C]0.204038[/C][/ROW]
[ROW][C]185[/C][C]0.838632[/C][C]0.322736[/C][C]0.161368[/C][/ROW]
[ROW][C]186[/C][C]0.815475[/C][C]0.36905[/C][C]0.184525[/C][/ROW]
[ROW][C]187[/C][C]0.790412[/C][C]0.419176[/C][C]0.209588[/C][/ROW]
[ROW][C]188[/C][C]0.837038[/C][C]0.325924[/C][C]0.162962[/C][/ROW]
[ROW][C]189[/C][C]0.82579[/C][C]0.348419[/C][C]0.17421[/C][/ROW]
[ROW][C]190[/C][C]0.804657[/C][C]0.390685[/C][C]0.195343[/C][/ROW]
[ROW][C]191[/C][C]0.795106[/C][C]0.409788[/C][C]0.204894[/C][/ROW]
[ROW][C]192[/C][C]0.809537[/C][C]0.380927[/C][C]0.190463[/C][/ROW]
[ROW][C]193[/C][C]0.78329[/C][C]0.43342[/C][C]0.21671[/C][/ROW]
[ROW][C]194[/C][C]0.758109[/C][C]0.483782[/C][C]0.241891[/C][/ROW]
[ROW][C]195[/C][C]0.729685[/C][C]0.540629[/C][C]0.270315[/C][/ROW]
[ROW][C]196[/C][C]0.72838[/C][C]0.54324[/C][C]0.27162[/C][/ROW]
[ROW][C]197[/C][C]0.715086[/C][C]0.569828[/C][C]0.284914[/C][/ROW]
[ROW][C]198[/C][C]0.736863[/C][C]0.526275[/C][C]0.263137[/C][/ROW]
[ROW][C]199[/C][C]0.764175[/C][C]0.47165[/C][C]0.235825[/C][/ROW]
[ROW][C]200[/C][C]0.736023[/C][C]0.527954[/C][C]0.263977[/C][/ROW]
[ROW][C]201[/C][C]0.705398[/C][C]0.589204[/C][C]0.294602[/C][/ROW]
[ROW][C]202[/C][C]0.680026[/C][C]0.639948[/C][C]0.319974[/C][/ROW]
[ROW][C]203[/C][C]0.649276[/C][C]0.701448[/C][C]0.350724[/C][/ROW]
[ROW][C]204[/C][C]0.619382[/C][C]0.761235[/C][C]0.380618[/C][/ROW]
[ROW][C]205[/C][C]0.599079[/C][C]0.801842[/C][C]0.400921[/C][/ROW]
[ROW][C]206[/C][C]0.68364[/C][C]0.632721[/C][C]0.31636[/C][/ROW]
[ROW][C]207[/C][C]0.648503[/C][C]0.702993[/C][C]0.351497[/C][/ROW]
[ROW][C]208[/C][C]0.613569[/C][C]0.772863[/C][C]0.386431[/C][/ROW]
[ROW][C]209[/C][C]0.596404[/C][C]0.807193[/C][C]0.403596[/C][/ROW]
[ROW][C]210[/C][C]0.565163[/C][C]0.869675[/C][C]0.434837[/C][/ROW]
[ROW][C]211[/C][C]0.540344[/C][C]0.919312[/C][C]0.459656[/C][/ROW]
[ROW][C]212[/C][C]0.577727[/C][C]0.844545[/C][C]0.422273[/C][/ROW]
[ROW][C]213[/C][C]0.546018[/C][C]0.907963[/C][C]0.453982[/C][/ROW]
[ROW][C]214[/C][C]0.5266[/C][C]0.9468[/C][C]0.4734[/C][/ROW]
[ROW][C]215[/C][C]0.576422[/C][C]0.847156[/C][C]0.423578[/C][/ROW]
[ROW][C]216[/C][C]0.570306[/C][C]0.859389[/C][C]0.429694[/C][/ROW]
[ROW][C]217[/C][C]0.552889[/C][C]0.894223[/C][C]0.447111[/C][/ROW]
[ROW][C]218[/C][C]0.520773[/C][C]0.958453[/C][C]0.479227[/C][/ROW]
[ROW][C]219[/C][C]0.49805[/C][C]0.9961[/C][C]0.50195[/C][/ROW]
[ROW][C]220[/C][C]0.459989[/C][C]0.919979[/C][C]0.540011[/C][/ROW]
[ROW][C]221[/C][C]0.443304[/C][C]0.886607[/C][C]0.556696[/C][/ROW]
[ROW][C]222[/C][C]0.403564[/C][C]0.807128[/C][C]0.596436[/C][/ROW]
[ROW][C]223[/C][C]0.387314[/C][C]0.774627[/C][C]0.612686[/C][/ROW]
[ROW][C]224[/C][C]0.347142[/C][C]0.694284[/C][C]0.652858[/C][/ROW]
[ROW][C]225[/C][C]0.371032[/C][C]0.742064[/C][C]0.628968[/C][/ROW]
[ROW][C]226[/C][C]0.34925[/C][C]0.6985[/C][C]0.65075[/C][/ROW]
[ROW][C]227[/C][C]0.325745[/C][C]0.651491[/C][C]0.674255[/C][/ROW]
[ROW][C]228[/C][C]0.347704[/C][C]0.695408[/C][C]0.652296[/C][/ROW]
[ROW][C]229[/C][C]0.418695[/C][C]0.83739[/C][C]0.581305[/C][/ROW]
[ROW][C]230[/C][C]0.378232[/C][C]0.756465[/C][C]0.621768[/C][/ROW]
[ROW][C]231[/C][C]0.353334[/C][C]0.706668[/C][C]0.646666[/C][/ROW]
[ROW][C]232[/C][C]0.464634[/C][C]0.929267[/C][C]0.535366[/C][/ROW]
[ROW][C]233[/C][C]0.433032[/C][C]0.866065[/C][C]0.566968[/C][/ROW]
[ROW][C]234[/C][C]0.414376[/C][C]0.828751[/C][C]0.585624[/C][/ROW]
[ROW][C]235[/C][C]0.384309[/C][C]0.768617[/C][C]0.615691[/C][/ROW]
[ROW][C]236[/C][C]0.435284[/C][C]0.870568[/C][C]0.564716[/C][/ROW]
[ROW][C]237[/C][C]0.524251[/C][C]0.951498[/C][C]0.475749[/C][/ROW]
[ROW][C]238[/C][C]0.619982[/C][C]0.760035[/C][C]0.380018[/C][/ROW]
[ROW][C]239[/C][C]0.669288[/C][C]0.661424[/C][C]0.330712[/C][/ROW]
[ROW][C]240[/C][C]0.625608[/C][C]0.748783[/C][C]0.374392[/C][/ROW]
[ROW][C]241[/C][C]0.576922[/C][C]0.846157[/C][C]0.423078[/C][/ROW]
[ROW][C]242[/C][C]0.581642[/C][C]0.836717[/C][C]0.418358[/C][/ROW]
[ROW][C]243[/C][C]0.843621[/C][C]0.312758[/C][C]0.156379[/C][/ROW]
[ROW][C]244[/C][C]0.821361[/C][C]0.357278[/C][C]0.178639[/C][/ROW]
[ROW][C]245[/C][C]0.784218[/C][C]0.431564[/C][C]0.215782[/C][/ROW]
[ROW][C]246[/C][C]0.805966[/C][C]0.388069[/C][C]0.194034[/C][/ROW]
[ROW][C]247[/C][C]0.79194[/C][C]0.416119[/C][C]0.20806[/C][/ROW]
[ROW][C]248[/C][C]0.750772[/C][C]0.498456[/C][C]0.249228[/C][/ROW]
[ROW][C]249[/C][C]0.714045[/C][C]0.57191[/C][C]0.285955[/C][/ROW]
[ROW][C]250[/C][C]0.675355[/C][C]0.649291[/C][C]0.324645[/C][/ROW]
[ROW][C]251[/C][C]0.770756[/C][C]0.458489[/C][C]0.229244[/C][/ROW]
[ROW][C]252[/C][C]0.797717[/C][C]0.404566[/C][C]0.202283[/C][/ROW]
[ROW][C]253[/C][C]0.76632[/C][C]0.46736[/C][C]0.23368[/C][/ROW]
[ROW][C]254[/C][C]0.721097[/C][C]0.557805[/C][C]0.278903[/C][/ROW]
[ROW][C]255[/C][C]0.712343[/C][C]0.575314[/C][C]0.287657[/C][/ROW]
[ROW][C]256[/C][C]0.658126[/C][C]0.683747[/C][C]0.341874[/C][/ROW]
[ROW][C]257[/C][C]0.629593[/C][C]0.740814[/C][C]0.370407[/C][/ROW]
[ROW][C]258[/C][C]0.565862[/C][C]0.868276[/C][C]0.434138[/C][/ROW]
[ROW][C]259[/C][C]0.515636[/C][C]0.968729[/C][C]0.484364[/C][/ROW]
[ROW][C]260[/C][C]0.452539[/C][C]0.905079[/C][C]0.547461[/C][/ROW]
[ROW][C]261[/C][C]0.389963[/C][C]0.779927[/C][C]0.610037[/C][/ROW]
[ROW][C]262[/C][C]0.575513[/C][C]0.848974[/C][C]0.424487[/C][/ROW]
[ROW][C]263[/C][C]0.66511[/C][C]0.669781[/C][C]0.33489[/C][/ROW]
[ROW][C]264[/C][C]0.633386[/C][C]0.733228[/C][C]0.366614[/C][/ROW]
[ROW][C]265[/C][C]0.722292[/C][C]0.555417[/C][C]0.277708[/C][/ROW]
[ROW][C]266[/C][C]0.885157[/C][C]0.229686[/C][C]0.114843[/C][/ROW]
[ROW][C]267[/C][C]0.834528[/C][C]0.330943[/C][C]0.165472[/C][/ROW]
[ROW][C]268[/C][C]0.948906[/C][C]0.102187[/C][C]0.0510937[/C][/ROW]
[ROW][C]269[/C][C]0.943708[/C][C]0.112584[/C][C]0.056292[/C][/ROW]
[ROW][C]270[/C][C]0.937224[/C][C]0.125553[/C][C]0.0627763[/C][/ROW]
[ROW][C]271[/C][C]0.89861[/C][C]0.202781[/C][C]0.10139[/C][/ROW]
[ROW][C]272[/C][C]0.854407[/C][C]0.291187[/C][C]0.145593[/C][/ROW]
[ROW][C]273[/C][C]0.821377[/C][C]0.357247[/C][C]0.178623[/C][/ROW]
[ROW][C]274[/C][C]0.927852[/C][C]0.144296[/C][C]0.0721481[/C][/ROW]
[ROW][C]275[/C][C]0.851173[/C][C]0.297654[/C][C]0.148827[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270376&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270376&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
110.296180.592360.70382
120.1767820.3535640.823218
130.4355740.8711480.564426
140.3228920.6457840.677108
150.219430.4388610.78057
160.2080470.4160940.791953
170.1613880.3227750.838612
180.1213880.2427760.878612
190.08632090.1726420.913679
200.06189750.1237950.938102
210.04224440.08448870.957756
220.02782310.05564620.972177
230.01673060.03346120.983269
240.009637390.01927480.990363
250.01135130.02270260.988649
260.007971190.01594240.992029
270.00466050.0093210.995339
280.004174620.008349250.995825
290.002515010.005030020.997485
300.001520110.003040220.99848
310.0008349050.001669810.999165
320.0006864660.001372930.999314
330.0003807420.0007614840.999619
340.0003064830.0006129660.999694
350.0003087510.0006175020.999691
360.01269830.02539670.987302
370.008552970.01710590.991447
380.006593780.01318760.993406
390.004396460.008792920.995604
400.002826430.005652860.997174
410.002144820.004289640.997855
420.001372580.002745150.998627
430.002792120.005584230.997208
440.002262410.004524830.997738
450.002264650.004529310.997735
460.002444960.004889910.997555
470.001589980.003179960.99841
480.001176350.002352690.998824
490.0009254880.001850980.999075
500.00076180.00152360.999238
510.0006375990.00127520.999362
520.0008366620.001673320.999163
530.000645380.001290760.999355
540.002143040.004286090.997857
550.001573410.003146810.998427
560.001561920.003123830.998438
570.00158080.00316160.998419
580.001187220.002374430.998813
590.002364710.004729410.997635
600.001885670.003771340.998114
610.002069460.004138910.997931
620.002582710.005165420.997417
630.002135010.004270010.997865
640.001809140.003618290.998191
650.003114680.006229360.996885
660.005621180.01124240.994379
670.005233980.0104680.994766
680.004843820.009687640.995156
690.003599970.007199940.9964
700.00335850.0067170.996641
710.003723790.007447580.996276
720.00297170.005943390.997028
730.002166770.004333540.997833
740.001609650.00321930.99839
750.001598450.003196890.998402
760.001789710.003579420.99821
770.002174320.004348640.997826
780.001688270.003376530.998312
790.001645750.00329150.998354
800.001282050.00256410.998718
810.00118340.00236680.998817
820.0009450040.001890010.999055
830.001089210.002178430.998911
840.0008246110.001649220.999175
850.0007343450.001468690.999266
860.0005887620.001177520.999411
870.002946580.005893150.997053
880.002437790.004875580.997562
890.001912180.003824360.998088
900.00147170.002943390.998528
910.001212660.002425310.998787
920.001270540.002541080.998729
930.001165610.002331220.998834
940.0009279220.001855840.999072
950.002548860.005097710.997451
960.002202460.004404910.997798
970.002052610.004105220.997947
980.00248660.004973190.997513
990.002413370.004826740.997587
1000.003497270.006994530.996503
1010.002806770.005613540.997193
1020.002820180.005640360.99718
1030.003298450.006596890.996702
1040.002741210.005482420.997259
1050.002343850.004687710.997656
1060.00273160.005463210.997268
1070.002463890.004927790.997536
1080.002707680.005415350.997292
1090.003065260.006130530.996935
1100.002796410.005592830.997204
1110.009146080.01829220.990854
1120.01699340.03398680.983007
1130.01814480.03628950.981855
1140.01641420.03282840.983586
1150.01445490.02890980.985545
1160.07271160.1454230.927288
1170.08307930.1661590.916921
1180.1565890.3131790.843411
1190.2543370.5086740.745663
1200.3016870.6033750.698313
1210.2774990.5549980.722501
1220.3398790.6797570.660121
1230.4676310.9352620.532369
1240.5004920.9990160.499508
1250.489090.9781790.51091
1260.5728840.8542320.427116
1270.5736310.8527390.426369
1280.5732690.8534620.426731
1290.5503970.8992070.449603
1300.5880120.8239760.411988
1310.5650210.8699580.434979
1320.6691350.661730.330865
1330.6563490.6873020.343651
1340.6448580.7102840.355142
1350.658820.6823610.34118
1360.6452710.7094590.354729
1370.6422350.715530.357765
1380.6218750.7562510.378125
1390.5998970.8002070.400103
1400.643130.7137410.35687
1410.6859180.6281650.314082
1420.7645680.4708650.235432
1430.7522910.4954180.247709
1440.7286790.5426420.271321
1450.7679330.4641340.232067
1460.7616340.4767320.238366
1470.797890.404220.20211
1480.7828720.4342550.217128
1490.7845060.4309890.215494
1500.7945070.4109860.205493
1510.7769260.4461480.223074
1520.7676470.4647060.232353
1530.7468960.5062090.253104
1540.7310020.5379970.268998
1550.7725710.4548590.227429
1560.7723780.4552450.227622
1570.7594180.4811640.240582
1580.7861220.4277560.213878
1590.796320.407360.20368
1600.777570.4448610.22243
1610.7530010.4939980.246999
1620.7890210.4219580.210979
1630.7796950.440610.220305
1640.7564710.4870580.243529
1650.740430.519140.25957
1660.7799990.4400030.220001
1670.7753530.4492950.224647
1680.7816690.4366630.218331
1690.7665410.4669190.233459
1700.8026760.3946480.197324
1710.7848650.4302710.215135
1720.8321070.3357870.167893
1730.8141590.3716820.185841
1740.7924360.4151280.207564
1750.7791970.4416050.220803
1760.770040.4599210.22996
1770.8002280.3995430.199772
1780.7815220.4369560.218478
1790.7596550.4806890.240345
1800.7382620.5234760.261738
1810.7713380.4573240.228662
1820.7446780.5106450.255322
1830.81170.37660.1883
1840.7959620.4080760.204038
1850.8386320.3227360.161368
1860.8154750.369050.184525
1870.7904120.4191760.209588
1880.8370380.3259240.162962
1890.825790.3484190.17421
1900.8046570.3906850.195343
1910.7951060.4097880.204894
1920.8095370.3809270.190463
1930.783290.433420.21671
1940.7581090.4837820.241891
1950.7296850.5406290.270315
1960.728380.543240.27162
1970.7150860.5698280.284914
1980.7368630.5262750.263137
1990.7641750.471650.235825
2000.7360230.5279540.263977
2010.7053980.5892040.294602
2020.6800260.6399480.319974
2030.6492760.7014480.350724
2040.6193820.7612350.380618
2050.5990790.8018420.400921
2060.683640.6327210.31636
2070.6485030.7029930.351497
2080.6135690.7728630.386431
2090.5964040.8071930.403596
2100.5651630.8696750.434837
2110.5403440.9193120.459656
2120.5777270.8445450.422273
2130.5460180.9079630.453982
2140.52660.94680.4734
2150.5764220.8471560.423578
2160.5703060.8593890.429694
2170.5528890.8942230.447111
2180.5207730.9584530.479227
2190.498050.99610.50195
2200.4599890.9199790.540011
2210.4433040.8866070.556696
2220.4035640.8071280.596436
2230.3873140.7746270.612686
2240.3471420.6942840.652858
2250.3710320.7420640.628968
2260.349250.69850.65075
2270.3257450.6514910.674255
2280.3477040.6954080.652296
2290.4186950.837390.581305
2300.3782320.7564650.621768
2310.3533340.7066680.646666
2320.4646340.9292670.535366
2330.4330320.8660650.566968
2340.4143760.8287510.585624
2350.3843090.7686170.615691
2360.4352840.8705680.564716
2370.5242510.9514980.475749
2380.6199820.7600350.380018
2390.6692880.6614240.330712
2400.6256080.7487830.374392
2410.5769220.8461570.423078
2420.5816420.8367170.418358
2430.8436210.3127580.156379
2440.8213610.3572780.178639
2450.7842180.4315640.215782
2460.8059660.3880690.194034
2470.791940.4161190.20806
2480.7507720.4984560.249228
2490.7140450.571910.285955
2500.6753550.6492910.324645
2510.7707560.4584890.229244
2520.7977170.4045660.202283
2530.766320.467360.23368
2540.7210970.5578050.278903
2550.7123430.5753140.287657
2560.6581260.6837470.341874
2570.6295930.7408140.370407
2580.5658620.8682760.434138
2590.5156360.9687290.484364
2600.4525390.9050790.547461
2610.3899630.7799270.610037
2620.5755130.8489740.424487
2630.665110.6697810.33489
2640.6333860.7332280.366614
2650.7222920.5554170.277708
2660.8851570.2296860.114843
2670.8345280.3309430.165472
2680.9489060.1021870.0510937
2690.9437080.1125840.056292
2700.9372240.1255530.0627763
2710.898610.2027810.10139
2720.8544070.2911870.145593
2730.8213770.3572470.178623
2740.9278520.1442960.0721481
2750.8511730.2976540.148827






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level790.298113NOK
5% type I error level930.350943NOK
10% type I error level950.358491NOK

\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 & 79 & 0.298113 & NOK \tabularnewline
5% type I error level & 93 & 0.350943 & NOK \tabularnewline
10% type I error level & 95 & 0.358491 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270376&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]79[/C][C]0.298113[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]93[/C][C]0.350943[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]95[/C][C]0.358491[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270376&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270376&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 level790.298113NOK
5% type I error level930.350943NOK
10% type I error level950.358491NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 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')
}