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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareMultiple Regression
Date of computationWed, 14 Dec 2011 03:38:45 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/14/t1323852063qfl61lzk9daphun.htm/, Retrieved Thu, 31 Oct 2024 23:00:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154801, Retrieved Thu, 31 Oct 2024 23:00:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
- RMP     [Multiple Regression] [] [2011-12-14 08:38:45] [3f0da162950979c43b1152c5680f6843] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	1	41	38	13	12	14
1	1	39	32	16	11	18
1	1	30	35	19	15	11
1	0	31	33	15	6	12
1	1	34	37	14	13	16
1	1	35	29	13	10	18
1	1	39	31	19	12	14
1	1	34	36	15	14	14
1	1	36	35	14	12	15
1	1	37	38	15	9	15
1	0	38	31	16	10	17
1	1	36	34	16	12	19
1	0	38	35	16	12	10
1	1	39	38	16	11	16
1	1	33	37	17	15	18
1	0	32	33	15	12	14
1	0	36	32	15	10	14
1	1	38	38	20	12	17
1	0	39	38	18	11	14
1	1	32	32	16	12	16
1	0	32	33	16	11	18
1	1	31	31	16	12	11
1	1	39	38	19	13	14
1	1	37	39	16	11	12
1	0	39	32	17	12	17
1	1	41	32	17	13	9
1	0	36	35	16	10	16
1	1	33	37	15	14	14
1	1	33	33	16	12	15
1	0	34	33	14	10	11
1	1	31	31	15	12	16
1	0	27	32	12	8	13
1	1	37	31	14	10	17
1	1	34	37	16	12	15
1	0	34	30	14	12	14
1	0	32	33	10	7	16
1	0	29	31	10	9	9
1	0	36	33	14	12	15
1	1	29	31	16	10	17
1	0	35	33	16	10	13
1	0	37	32	16	10	15
1	1	34	33	14	12	16
1	0	38	32	20	15	16
1	0	35	33	14	10	12
1	1	38	28	14	10	15
1	1	37	35	11	12	11
1	1	38	39	14	13	15
1	1	33	34	15	11	15
1	1	36	38	16	11	17
1	0	38	32	14	12	13
1	1	32	38	16	14	16
1	0	32	30	14	10	14
1	0	32	33	12	12	11
1	1	34	38	16	13	12
1	0	32	32	9	5	12
1	1	37	35	14	6	15
1	1	39	34	16	12	16
1	1	29	34	16	12	15
1	0	37	36	15	11	12
1	1	35	34	16	10	12
1	0	30	28	12	7	8
1	0	38	34	16	12	13
1	1	34	35	16	14	11
1	1	31	35	14	11	14
1	1	34	31	16	12	15
1	0	35	37	17	13	10
1	1	36	35	18	14	11
1	0	30	27	18	11	12
1	1	39	40	12	12	15
1	0	35	37	16	12	15
1	0	38	36	10	8	14
1	1	31	38	14	11	16
1	1	34	39	18	14	15
1	0	38	41	18	14	15
1	0	34	27	16	12	13
1	1	39	30	17	9	12
1	1	37	37	16	13	17
1	1	34	31	16	11	13
1	0	28	31	13	12	15
1	0	37	27	16	12	13
1	0	33	36	16	12	15
1	1	35	37	16	12	15
1	0	37	33	15	12	16
1	1	32	34	15	11	15
1	1	33	31	16	10	14
1	0	38	39	14	9	15
1	1	33	34	16	12	14
1	1	29	32	16	12	13
1	1	33	33	15	12	7
1	1	31	36	12	9	17
1	1	36	32	17	15	13
1	1	35	41	16	12	15
1	1	32	28	15	12	14
1	1	29	30	13	12	13
1	1	39	36	16	10	16
1	1	37	35	16	13	12
1	1	35	31	16	9	14
1	0	37	34	16	12	17
1	0	32	36	14	10	15
1	1	38	36	16	14	17
1	0	37	35	16	11	12
1	1	36	37	20	15	16
1	0	32	28	15	11	11
1	1	33	39	16	11	15
1	0	40	32	13	12	9
1	1	38	35	17	12	16
1	0	41	39	16	12	15
1	0	36	35	16	11	10
1	1	43	42	12	7	10
1	1	30	34	16	12	15
1	1	31	33	16	14	11
1	1	32	41	17	11	13
1	1	37	34	12	10	18
1	0	37	32	18	13	16
1	1	33	40	14	13	14
1	1	34	40	14	8	14
1	1	33	35	13	11	14
1	1	38	36	16	12	14
1	0	33	37	13	11	12
1	1	31	27	16	13	14
1	1	38	39	13	12	15
1	1	37	38	16	14	15
1	1	36	31	15	13	15
1	1	31	33	16	15	13
1	0	39	32	15	10	17
1	1	44	39	17	11	17
1	1	33	36	15	9	19
1	1	35	33	12	11	15
1	0	32	33	16	10	13
1	0	28	32	10	11	9
1	1	40	37	16	8	15
1	0	27	30	12	11	15
1	0	37	38	14	12	15
1	1	32	29	15	12	16
1	0	28	22	13	9	11
1	0	34	35	15	11	14
1	1	30	35	11	10	11
1	1	35	34	12	8	15
1	0	31	35	11	9	13
1	1	32	34	16	8	15
1	0	30	37	15	9	16
1	1	30	35	17	15	14
1	0	31	23	16	11	15
1	1	40	31	10	8	16
1	1	32	27	18	13	16
1	0	36	36	13	12	11
1	0	32	31	16	12	12
1	0	35	32	13	9	9
1	1	38	39	10	7	16
1	1	42	37	15	13	13
1	0	34	38	16	9	16
1	1	35	39	16	6	12
1	1	38	34	14	8	9
1	1	33	31	10	8	13
1	1	32	37	13	6	14
1	1	33	36	15	9	19
1	1	34	32	16	11	13
1	1	32	38	12	8	12
0	0	27	26	13	10	10
0	0	31	26	12	8	14
0	0	38	33	17	14	16
0	1	34	39	15	10	10
0	0	24	30	10	8	11
0	0	30	33	14	11	14
0	1	26	25	11	12	12
0	1	34	38	13	12	9
0	0	27	37	16	12	9
0	0	37	31	12	5	11
0	1	36	37	16	12	16
0	0	41	35	12	10	9
0	1	29	25	9	7	13
0	1	36	28	12	12	16
0	0	32	35	15	11	13
0	1	37	33	12	8	9
0	0	30	30	12	9	12
0	1	31	31	14	10	16
0	1	38	37	12	9	11
0	1	36	36	16	12	14
0	0	35	30	11	6	13
0	0	31	36	19	15	15
0	0	38	32	15	12	14
0	1	22	28	8	12	16
0	1	32	36	16	12	13
0	0	36	34	17	11	14
0	1	39	31	12	7	15
0	0	28	28	11	7	13
0	0	32	36	11	5	11
0	1	32	36	14	12	11
0	1	38	40	16	12	14
0	1	32	33	12	3	15
0	1	35	37	16	11	11
0	1	32	32	13	10	15
0	0	37	38	15	12	12
0	1	34	31	16	9	14
0	1	33	37	16	12	14
0	0	33	33	14	9	8
0	0	30	30	16	12	9
0	0	24	30	14	10	15
0	0	34	31	11	9	17
0	0	34	32	12	12	13
0	1	33	34	15	8	15
0	1	34	36	15	11	15
0	1	35	37	16	11	14
0	0	35	36	16	12	16
0	0	36	33	11	10	13
0	0	34	33	15	10	16
0	1	34	33	12	12	9
0	0	41	44	12	12	16
0	0	32	39	15	11	11
0	0	30	32	15	8	10
0	1	35	35	16	12	11
0	0	28	25	14	10	15
0	1	33	35	17	11	17
0	1	39	34	14	10	14
0	0	36	35	13	8	8
0	1	36	39	15	12	15
0	0	35	33	13	12	11
0	0	38	36	14	10	16
0	1	33	32	15	12	10
0	0	31	32	12	9	15
0	1	32	36	8	6	16
0	0	31	32	14	10	19
0	0	33	34	14	9	12
0	0	34	33	11	9	8
0	0	34	35	12	9	11
0	1	34	30	13	6	14
0	0	33	38	10	10	9
0	0	32	34	16	6	15
0	1	41	33	18	14	13
0	1	34	32	13	10	16
0	0	36	31	11	10	11
0	0	37	30	4	6	12
0	0	36	27	13	12	13
0	1	29	31	16	12	10
0	0	37	30	10	7	11
0	0	27	32	12	8	12
0	0	35	35	12	11	8
0	0	28	28	10	3	12
0	0	35	33	13	6	12
0	0	29	35	12	8	11
0	0	32	35	14	9	13
0	1	36	32	10	9	14
0	1	19	21	12	8	10
0	1	21	20	12	9	12
0	0	31	34	11	7	15
0	0	33	32	10	7	13
0	1	36	34	12	6	13
0	1	33	32	16	9	13
0	0	37	33	12	10	12
0	0	34	33	14	11	12
0	0	35	37	16	12	9
0	1	31	32	14	8	9
0	1	37	34	13	11	15
0	1	35	30	4	3	10
0	1	27	30	15	11	14
0	0	34	38	11	12	15
0	0	40	36	11	7	7
0	0	29	32	14	9	14
0	0	38	34	15	12	8
0	1	34	33	14	8	10
0	0	21	27	13	11	13
0	0	36	32	11	8	13
0	1	38	34	15	10	13
0	0	30	29	11	8	8
0	0	35	35	13	7	12
0	1	30	27	13	8	13
0	1	36	33	16	10	12
0	0	34	38	13	8	10
0	1	35	36	16	12	13
0	0	34	33	16	14	12
0	0	32	39	12	7	9
0	1	33	29	7	6	15
0	0	33	32	16	11	13
0	1	26	34	5	4	13
0	0	35	38	16	9	13
0	0	21	17	4	5	15
0	0	38	35	12	9	15
0	0	35	32	15	11	14
0	1	33	34	14	12	15
0	0	37	36	11	9	11
0	0	38	31	16	12	15
0	1	34	35	15	10	14
0	0	27	29	12	9	13
0	1	16	22	6	6	12
0	0	40	41	16	10	16
0	0	36	36	10	9	16
0	1	42	42	15	13	9
0	1	30	33	14	12	14

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 13 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154801&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154801&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154801&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 time13 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 1.94933228525292 + 0.653493146925309Pop[t] + 0.0305177066962302Gender[t] + 0.0700025359624757Connected[t] + 0.0563924721194769Separate[t] + 0.623309096789489Software[t] + 0.0764750221538193Happiness[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  1.94933228525292 +  0.653493146925309Pop[t] +  0.0305177066962302Gender[t] +  0.0700025359624757Connected[t] +  0.0563924721194769Separate[t] +  0.623309096789489Software[t] +  0.0764750221538193Happiness[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154801&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  1.94933228525292 +  0.653493146925309Pop[t] +  0.0305177066962302Gender[t] +  0.0700025359624757Connected[t] +  0.0563924721194769Separate[t] +  0.623309096789489Software[t] +  0.0764750221538193Happiness[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154801&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154801&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
Learning[t] = + 1.94933228525292 + 0.653493146925309Pop[t] + 0.0305177066962302Gender[t] + 0.0700025359624757Connected[t] + 0.0563924721194769Separate[t] + 0.623309096789489Software[t] + 0.0764750221538193Happiness[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.949332285252921.2462661.56410.1189110.059455
Pop0.6534931469253090.2484842.62990.0090110.004506
Gender0.03051770669623020.2345460.13010.8965690.448285
Connected0.07000253596247570.032882.12910.0341190.017059
Separate0.05639247211947690.0342851.64480.1011260.050563
Software0.6233090967894890.05167212.062700
Happiness0.07647502215381930.0476151.60610.1093730.054687

\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) & 1.94933228525292 & 1.246266 & 1.5641 & 0.118911 & 0.059455 \tabularnewline
Pop & 0.653493146925309 & 0.248484 & 2.6299 & 0.009011 & 0.004506 \tabularnewline
Gender & 0.0305177066962302 & 0.234546 & 0.1301 & 0.896569 & 0.448285 \tabularnewline
Connected & 0.0700025359624757 & 0.03288 & 2.1291 & 0.034119 & 0.017059 \tabularnewline
Separate & 0.0563924721194769 & 0.034285 & 1.6448 & 0.101126 & 0.050563 \tabularnewline
Software & 0.623309096789489 & 0.051672 & 12.0627 & 0 & 0 \tabularnewline
Happiness & 0.0764750221538193 & 0.047615 & 1.6061 & 0.109373 & 0.054687 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154801&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]1.94933228525292[/C][C]1.246266[/C][C]1.5641[/C][C]0.118911[/C][C]0.059455[/C][/ROW]
[ROW][C]Pop[/C][C]0.653493146925309[/C][C]0.248484[/C][C]2.6299[/C][C]0.009011[/C][C]0.004506[/C][/ROW]
[ROW][C]Gender[/C][C]0.0305177066962302[/C][C]0.234546[/C][C]0.1301[/C][C]0.896569[/C][C]0.448285[/C][/ROW]
[ROW][C]Connected[/C][C]0.0700025359624757[/C][C]0.03288[/C][C]2.1291[/C][C]0.034119[/C][C]0.017059[/C][/ROW]
[ROW][C]Separate[/C][C]0.0563924721194769[/C][C]0.034285[/C][C]1.6448[/C][C]0.101126[/C][C]0.050563[/C][/ROW]
[ROW][C]Software[/C][C]0.623309096789489[/C][C]0.051672[/C][C]12.0627[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0764750221538193[/C][C]0.047615[/C][C]1.6061[/C][C]0.109373[/C][C]0.054687[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154801&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154801&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)1.949332285252921.2462661.56410.1189110.059455
Pop0.6534931469253090.2484842.62990.0090110.004506
Gender0.03051770669623020.2345460.13010.8965690.448285
Connected0.07000253596247570.032882.12910.0341190.017059
Separate0.05639247211947690.0342851.64480.1011260.050563
Software0.6233090967894890.05167212.062700
Happiness0.07647502215381930.0476151.60610.1093730.054687






Multiple Linear Regression - Regression Statistics
Multiple R0.697110633887777
R-squared0.485963235879419
Adjusted R-squared0.474987361912431
F-TEST (value)44.2755845540015
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.89915449290687
Sum Squared Residuals1013.50736840787

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.697110633887777 \tabularnewline
R-squared & 0.485963235879419 \tabularnewline
Adjusted R-squared & 0.474987361912431 \tabularnewline
F-TEST (value) & 44.2755845540015 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.89915449290687 \tabularnewline
Sum Squared Residuals & 1013.50736840787 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154801&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.697110633887777[/C][/ROW]
[ROW][C]R-squared[/C][C]0.485963235879419[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.474987361912431[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]44.2755845540015[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]281[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.89915449290687[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1013.50736840787[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154801&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154801&T=3

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

Multiple Linear Regression - Regression Statistics
Multiple R0.697110633887777
R-squared0.485963235879419
Adjusted R-squared0.474987361912431
F-TEST (value)44.2755845540015
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.89915449290687
Sum Squared Residuals1013.50736840787






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.1967205255034-3.19672052550342
21615.40095161268740.599048387312611
31916.89801743746482.10198256253524
41511.29141047354053.70858952645953
51416.4265694427437-2.42656944274373
61314.3284549556896-1.32845495568956
71915.66196814874213.33803185125787
81516.8405360231061-1.84053602310611
91415.7540054514864-1.75400545148642
101514.12325811343890.876741886561136
111614.54425477896591.4557452210341
121616.0035130679822-0.00351306798222513
131615.4811177059460.518882294053951
141615.58635640109660.413643598903387
151717.7561351446679-0.756135144667875
161515.2542176345475-0.254217634547518
171514.2312171126990.768782887301033
182016.21613798407743.78386201592255
191815.40288865009272.59711134990726
201615.38129291343190.61870708656809
211614.93680862637331.06319137362669
221614.87252279458091.12747720541914
231916.6800245503682.31997544963205
241615.19684371267590.803156287324139
251715.91726798062681.08273201937317
261716.09929967880690.900700321193056
271614.5533445733651.44665542663496
281516.8269259592631-1.82692595926311
291615.431212899360.568787100639956
301413.9181794464320.0818205535679657
311515.25489790535-0.254897905349958
321212.2781010733039-0.278101073303888
331414.5047699496997-0.504769949699654
341615.72678532380040.273214676199573
351415.225045290114-1.22504529011404
361012.2906221949077-2.29062219490771
371012.6791226812836-2.67912268128358
381415.6107028005512-1.61070280055124
391613.94474966199982.05525033800015
401614.14113202670211.85886797329785
411614.37769467081531.62230532918474
421415.5776904574763-1.57769045747634
432017.6407177128792.359282287121
441414.0646570045483-0.0646570045483293
451414.2526450249961-0.25264502499606
461115.5181078988336-4.51810789883362
471416.7428895086788-2.74288950867877
481514.864296274690.135703725309968
491615.4528238153630.547176184636995
501415.5413653560491-1.54136535604908
511616.9662659397277-0.966265939727749
521413.83842202461010.16157797538989
531215.0247925680861-3.02479256808606
541616.1770618262479-0.177061826247934
55910.681711440594-1.68171144059398
561412.0841534067121.91584659328803
571615.98409560940820.0159043905918059
581615.20759522762960.792404772370382
591514.99714858962120.00285141037880004
601614.1515671833641.84843281663596
611211.25685458515480.743145414845178
621615.6541503002880.34584969971197
631616.5547184845252-0.554718484525173
641414.7042086527307-0.704208652730738
651615.38843049108360.611569508916434
661716.00720413908710.992795860912937
671816.69472355645011.30527644354988
681813.99959858880864.00040141119142
691216.2459754199712-4.24597541997123
701615.76627015306670.233729846933328
711013.3501738795228-3.35017387952285
721415.0263361133968-1.02633611339681
731817.08618846161840.913811538381643
741817.4484658430110.551534156989016
751614.97939285160181.02060714839821
761713.58269834194653.41730165805346
771616.713052072785-0.713052072784981
781614.61217134998641.38782865001356
791314.9378975686125-1.93789756861248
801615.18940045948920.810599540510784
811615.56987260902220.430127390977757
821615.79678785976290.203212140237098
831515.7571803586675-0.757180358667536
841514.79429373872760.205706261272444
851613.99533473938832.00466526061171
861414.2191354148246-0.219135414824587
871615.41113034932570.588869650674299
881614.9418602390831.05813976091697
891514.81941272212950.180587277870511
901213.7434079977327-1.74340799773269
911717.3018052811888-0.301805281188821
921616.0223577482408-0.0223577482408099
931515.0027729806464-0.00277298064636426
941314.8290752948441-1.82907529484407
951614.85026236006821.14973763993183
961616.2178920177769-0.217892017776931
971613.51203071452382.48796928547624
981615.89004785294080.109952147059168
991414.2532518794808-0.253251879480791
1001617.3499712334175-1.34997123341747
1011614.94075611750171.05924388249828
1022017.81319270824772.18680729175234
1031514.11952111069920.880478889300813
1041615.14625863528740.853741364712584
1051315.3754703393588-2.37547033935875
1061715.97048554556521.0295144544348
1071616.2990703130805-0.29907031308048
1081614.71780353723161.28219646276839
1091213.1398499133436-1.13984991334355
1101615.27759776359210.722402236407906
1111616.2319259323988-0.231925932398792
1121715.03609099925631.96390900074375
1131214.7504223882119-2.7504223882119
1141816.32409698333751.67590301666245
1151416.372794278832-2.37279427883205
1161413.32625133084710.673748669152917
1171314.8442137246557-1.84421372465569
1181615.8739279733770.126072026622967
1191314.7735309178908-1.77353091789077
1201615.49968706935390.5003129306461
1211316.1195804118893-3.11958041188928
1221617.2398035973863-1.23980359738631
1231516.151744659798-1.15174465979801
1241617.0081850734959-1.00818507349592
1251514.67064978704790.329350212952148
1261716.06923657518230.930763424817713
1271514.03636311396530.963636886034715
1281214.9479088744955-2.94790887449551
1291613.93112441881472.06887558118528
1301013.9121308110196-3.91213081101955
1311613.65356415241732.34643584758267
1321214.188193463741-2.18819346374104
1331415.9626676971111-1.9626676971111
1341515.2121154970735-0.21211549707348
1351312.25453794055340.745462059446554
1361514.88369855392190.116301446078065
1371113.7814719535173-2.78147195351732
1381213.1343740562465-1.13437405624652
1391113.3505977303017-2.35059773030171
1401612.92436644835913.07563355164091
1411513.62280520503961.37719479496035
1421717.1274425039262-0.127442503926216
1431614.07345630275461.92654369724539
1441013.3916843418543-3.39168434185428
1451815.7226396496242.27736035037599
1461315.4739801282944-2.47398012829439
1471614.98848264600091.01151735399907
1481313.1555303691779-0.155530369177906
1491013.0795099500957-3.07950995009566
1501516.7571646639821-1.75716466398208
1511613.9592078210092.04079217899097
1521611.94029315680354.05970684319653
1531412.8855315312111.11446846878897
1541012.6722415236555-2.6722415236555
1551311.77045064898471.22954935101528
1561514.03636311396530.963636886034715
1571614.66856382210591.33143617789409
1581212.9205112703755-0.920511270375539
1591312.30344622077920.696553779220762
1601211.64273825966540.357261740334559
1611716.42030794128370.57969205871632
1621513.5570838167661.442916183234
1631011.1488653299446-1.14886532994456
1641413.83741031890780.16258968109223
1651113.6071371572801-2.60713715728013
1661314.6708345160717-1.67083451607168
1671614.09390658551861.90609341448136
1681210.24536347920781.75463652079224
1691615.28977227095390.710227729046111
1701213.7145389511754-1.71453895117537
171910.7770743033739-1.77707430337394
1721214.7822400218786-2.7822400218786
1731514.01372531291790.986274687082145
1741212.1056433762038-0.105643376203766
1751212.2686646646627-0.268664664662723
1761413.35478656484570.645213435154328
1771213.1774749417413-1.17747494174128
1781615.08042975452680.919570245473226
1791110.82522507626050.174774923739546
1801916.64630168054052.35369831945955
1811514.96434723127760.0356527687224131
182813.8022045184039-5.80220451840394
1831614.72394458852311.27605541147695
1841714.31381800680212.6861819931979
1851211.96840454002320.0315954599768082
1861110.84573147707370.15426852292634
1871110.17731315999280.822686840007238
1881414.5709945442154-0.570994544215412
1891615.44600471492960.553995285070368
190129.097935345366862.90206465463314
1911614.21408552743281.78591447256717
1921313.4047065507738-0.404706550773805
1931515.0797494837243-0.0797494837243336
1941612.7885350316363.21146496836403
1951614.92681461875881.07318538124118
1961412.34194960029331.6580503997067
1971613.90916688856972.09083311143027
1981412.70138361213881.29861638786118
1991112.9874423914012-1.9874423914012
2001214.6078620652739-2.60786206527386
2011512.34087583739632.65912416260374
2021514.39359060796620.606409392033847
2031614.44351059389431.55648940610571
2041615.13285955617570.867140443824294
2051113.5576414157393-2.55764141573932
2061513.64706141027581.35293858972418
2071214.3888721554743-2.38887215547429
2081216.0040145489064-4.00401454890638
2091514.08634515708810.913654842911876
2101511.60519046780453.39480953219545
2111614.72460967998341.27539032001664
2121412.69943139539131.30056860460867
2131714.42014564419182.57985435580816
2141413.93103422459630.0689657754037305
2151312.04143305563020.958566944369805
2161515.326082193039-0.326082193039023
2171314.5813070290482-1.58130702904818
2181414.0962489704842-0.0962489704841559
2191514.33895216954620.661047830453838
2201212.6808772113256-0.68087721132561
221811.2135150742476-3.21351507424758
2221413.61008639673040.389913603269623
2231412.70424216102811.29575783897194
2241112.4119521362558-1.41195213625578
2251212.7541621469562-0.754162146956191
2261310.8622152691482.13778473085197
2271013.323696079834-3.323696079834
2281610.99373740115865.00626259884143
2291816.43140818940591.56859181059412
2301313.6211866448526-0.621186644852576
2311113.2919064271927-2.29190642719272
232410.8887551260316-6.88875512603158
2331314.4659047766014-1.46590477660143
2341614.00254955357681.99745044642322
2351011.4355892006673-1.43558920066726
2361211.54813290422480.451867095775239
2371213.8413578100362-1.84135781003619
238108.276020067761891.72397993223811
2391310.91792747046512.08207252953493
2401211.78084037035430.219159629645677
2411412.76710711933891.23289288066112
2421012.9849325756804-2.9849325756804
2431210.24536308559931.7546369144007
2441211.10523482650190.894765173498097
2451111.5470439619856-0.547043961985587
2461011.4213140453639-1.42131404536395
2471211.15131520739710.848684792602932
2481612.69844994563923.30155005436085
2491213.551168929548-1.55116892954797
2501413.964470418450.0355295815499662
2511614.65392687321841.34607312678155
2521411.62923568830942.37076431169056
2531314.4908132716146-1.49081327161463
25448.75639042612676-4.75639042612676
2551513.48874300135811.51125699864186
2561115.0991669422984-4.09916694229836
2571111.6780515526563-0.678051552656267
2581412.46439711724681.53560288275316
2591514.61828204259360.381717957406375
2601411.97211079047022.02788920952984
2611312.79255764037480.207442359625192
2621112.2546307500409-1.25463075004086
2631513.784556666481.21544333352003
2641111.2830630071385-0.28306300713848
2651311.65402151149351.34597848850649
2661311.58317088036491.41682911963515
2671613.51168410028172.48831589971827
2681312.22355544437130.776444555628687
2691614.93395219641051.06604780358952
2701615.83439770881850.165602291181501
2711211.44015872562250.55984127437747
272710.8122952832199-3.8122952832199
2731613.91455043252192.0854495674781
27459.20467165419333-4.20467165419333
2751613.14629214358472.85370785641527
27648.64172838275074-4.64172838275074
2771213.3400723794214-1.34007237942137
2781514.13103052660070.868969473399329
2791414.8341122245542-0.834112224554212
2801113.0205622269631-2.02056222696309
2811614.98442978131191.01557021868807
2821513.63741401690341.36258598309663
2831212.0787396068096-0.0787396068096383
28468.99807980056001-2.99807980056001
2851614.51821640300651.48178359699351
2861013.3329348017697-3.33293480176972
2871516.0797337890389-1.07973378903888
2881414.4912371223935-0.491237122393489

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.1967205255034 & -3.19672052550342 \tabularnewline
2 & 16 & 15.4009516126874 & 0.599048387312611 \tabularnewline
3 & 19 & 16.8980174374648 & 2.10198256253524 \tabularnewline
4 & 15 & 11.2914104735405 & 3.70858952645953 \tabularnewline
5 & 14 & 16.4265694427437 & -2.42656944274373 \tabularnewline
6 & 13 & 14.3284549556896 & -1.32845495568956 \tabularnewline
7 & 19 & 15.6619681487421 & 3.33803185125787 \tabularnewline
8 & 15 & 16.8405360231061 & -1.84053602310611 \tabularnewline
9 & 14 & 15.7540054514864 & -1.75400545148642 \tabularnewline
10 & 15 & 14.1232581134389 & 0.876741886561136 \tabularnewline
11 & 16 & 14.5442547789659 & 1.4557452210341 \tabularnewline
12 & 16 & 16.0035130679822 & -0.00351306798222513 \tabularnewline
13 & 16 & 15.481117705946 & 0.518882294053951 \tabularnewline
14 & 16 & 15.5863564010966 & 0.413643598903387 \tabularnewline
15 & 17 & 17.7561351446679 & -0.756135144667875 \tabularnewline
16 & 15 & 15.2542176345475 & -0.254217634547518 \tabularnewline
17 & 15 & 14.231217112699 & 0.768782887301033 \tabularnewline
18 & 20 & 16.2161379840774 & 3.78386201592255 \tabularnewline
19 & 18 & 15.4028886500927 & 2.59711134990726 \tabularnewline
20 & 16 & 15.3812929134319 & 0.61870708656809 \tabularnewline
21 & 16 & 14.9368086263733 & 1.06319137362669 \tabularnewline
22 & 16 & 14.8725227945809 & 1.12747720541914 \tabularnewline
23 & 19 & 16.680024550368 & 2.31997544963205 \tabularnewline
24 & 16 & 15.1968437126759 & 0.803156287324139 \tabularnewline
25 & 17 & 15.9172679806268 & 1.08273201937317 \tabularnewline
26 & 17 & 16.0992996788069 & 0.900700321193056 \tabularnewline
27 & 16 & 14.553344573365 & 1.44665542663496 \tabularnewline
28 & 15 & 16.8269259592631 & -1.82692595926311 \tabularnewline
29 & 16 & 15.43121289936 & 0.568787100639956 \tabularnewline
30 & 14 & 13.918179446432 & 0.0818205535679657 \tabularnewline
31 & 15 & 15.25489790535 & -0.254897905349958 \tabularnewline
32 & 12 & 12.2781010733039 & -0.278101073303888 \tabularnewline
33 & 14 & 14.5047699496997 & -0.504769949699654 \tabularnewline
34 & 16 & 15.7267853238004 & 0.273214676199573 \tabularnewline
35 & 14 & 15.225045290114 & -1.22504529011404 \tabularnewline
36 & 10 & 12.2906221949077 & -2.29062219490771 \tabularnewline
37 & 10 & 12.6791226812836 & -2.67912268128358 \tabularnewline
38 & 14 & 15.6107028005512 & -1.61070280055124 \tabularnewline
39 & 16 & 13.9447496619998 & 2.05525033800015 \tabularnewline
40 & 16 & 14.1411320267021 & 1.85886797329785 \tabularnewline
41 & 16 & 14.3776946708153 & 1.62230532918474 \tabularnewline
42 & 14 & 15.5776904574763 & -1.57769045747634 \tabularnewline
43 & 20 & 17.640717712879 & 2.359282287121 \tabularnewline
44 & 14 & 14.0646570045483 & -0.0646570045483293 \tabularnewline
45 & 14 & 14.2526450249961 & -0.25264502499606 \tabularnewline
46 & 11 & 15.5181078988336 & -4.51810789883362 \tabularnewline
47 & 14 & 16.7428895086788 & -2.74288950867877 \tabularnewline
48 & 15 & 14.86429627469 & 0.135703725309968 \tabularnewline
49 & 16 & 15.452823815363 & 0.547176184636995 \tabularnewline
50 & 14 & 15.5413653560491 & -1.54136535604908 \tabularnewline
51 & 16 & 16.9662659397277 & -0.966265939727749 \tabularnewline
52 & 14 & 13.8384220246101 & 0.16157797538989 \tabularnewline
53 & 12 & 15.0247925680861 & -3.02479256808606 \tabularnewline
54 & 16 & 16.1770618262479 & -0.177061826247934 \tabularnewline
55 & 9 & 10.681711440594 & -1.68171144059398 \tabularnewline
56 & 14 & 12.084153406712 & 1.91584659328803 \tabularnewline
57 & 16 & 15.9840956094082 & 0.0159043905918059 \tabularnewline
58 & 16 & 15.2075952276296 & 0.792404772370382 \tabularnewline
59 & 15 & 14.9971485896212 & 0.00285141037880004 \tabularnewline
60 & 16 & 14.151567183364 & 1.84843281663596 \tabularnewline
61 & 12 & 11.2568545851548 & 0.743145414845178 \tabularnewline
62 & 16 & 15.654150300288 & 0.34584969971197 \tabularnewline
63 & 16 & 16.5547184845252 & -0.554718484525173 \tabularnewline
64 & 14 & 14.7042086527307 & -0.704208652730738 \tabularnewline
65 & 16 & 15.3884304910836 & 0.611569508916434 \tabularnewline
66 & 17 & 16.0072041390871 & 0.992795860912937 \tabularnewline
67 & 18 & 16.6947235564501 & 1.30527644354988 \tabularnewline
68 & 18 & 13.9995985888086 & 4.00040141119142 \tabularnewline
69 & 12 & 16.2459754199712 & -4.24597541997123 \tabularnewline
70 & 16 & 15.7662701530667 & 0.233729846933328 \tabularnewline
71 & 10 & 13.3501738795228 & -3.35017387952285 \tabularnewline
72 & 14 & 15.0263361133968 & -1.02633611339681 \tabularnewline
73 & 18 & 17.0861884616184 & 0.913811538381643 \tabularnewline
74 & 18 & 17.448465843011 & 0.551534156989016 \tabularnewline
75 & 16 & 14.9793928516018 & 1.02060714839821 \tabularnewline
76 & 17 & 13.5826983419465 & 3.41730165805346 \tabularnewline
77 & 16 & 16.713052072785 & -0.713052072784981 \tabularnewline
78 & 16 & 14.6121713499864 & 1.38782865001356 \tabularnewline
79 & 13 & 14.9378975686125 & -1.93789756861248 \tabularnewline
80 & 16 & 15.1894004594892 & 0.810599540510784 \tabularnewline
81 & 16 & 15.5698726090222 & 0.430127390977757 \tabularnewline
82 & 16 & 15.7967878597629 & 0.203212140237098 \tabularnewline
83 & 15 & 15.7571803586675 & -0.757180358667536 \tabularnewline
84 & 15 & 14.7942937387276 & 0.205706261272444 \tabularnewline
85 & 16 & 13.9953347393883 & 2.00466526061171 \tabularnewline
86 & 14 & 14.2191354148246 & -0.219135414824587 \tabularnewline
87 & 16 & 15.4111303493257 & 0.588869650674299 \tabularnewline
88 & 16 & 14.941860239083 & 1.05813976091697 \tabularnewline
89 & 15 & 14.8194127221295 & 0.180587277870511 \tabularnewline
90 & 12 & 13.7434079977327 & -1.74340799773269 \tabularnewline
91 & 17 & 17.3018052811888 & -0.301805281188821 \tabularnewline
92 & 16 & 16.0223577482408 & -0.0223577482408099 \tabularnewline
93 & 15 & 15.0027729806464 & -0.00277298064636426 \tabularnewline
94 & 13 & 14.8290752948441 & -1.82907529484407 \tabularnewline
95 & 16 & 14.8502623600682 & 1.14973763993183 \tabularnewline
96 & 16 & 16.2178920177769 & -0.217892017776931 \tabularnewline
97 & 16 & 13.5120307145238 & 2.48796928547624 \tabularnewline
98 & 16 & 15.8900478529408 & 0.109952147059168 \tabularnewline
99 & 14 & 14.2532518794808 & -0.253251879480791 \tabularnewline
100 & 16 & 17.3499712334175 & -1.34997123341747 \tabularnewline
101 & 16 & 14.9407561175017 & 1.05924388249828 \tabularnewline
102 & 20 & 17.8131927082477 & 2.18680729175234 \tabularnewline
103 & 15 & 14.1195211106992 & 0.880478889300813 \tabularnewline
104 & 16 & 15.1462586352874 & 0.853741364712584 \tabularnewline
105 & 13 & 15.3754703393588 & -2.37547033935875 \tabularnewline
106 & 17 & 15.9704855455652 & 1.0295144544348 \tabularnewline
107 & 16 & 16.2990703130805 & -0.29907031308048 \tabularnewline
108 & 16 & 14.7178035372316 & 1.28219646276839 \tabularnewline
109 & 12 & 13.1398499133436 & -1.13984991334355 \tabularnewline
110 & 16 & 15.2775977635921 & 0.722402236407906 \tabularnewline
111 & 16 & 16.2319259323988 & -0.231925932398792 \tabularnewline
112 & 17 & 15.0360909992563 & 1.96390900074375 \tabularnewline
113 & 12 & 14.7504223882119 & -2.7504223882119 \tabularnewline
114 & 18 & 16.3240969833375 & 1.67590301666245 \tabularnewline
115 & 14 & 16.372794278832 & -2.37279427883205 \tabularnewline
116 & 14 & 13.3262513308471 & 0.673748669152917 \tabularnewline
117 & 13 & 14.8442137246557 & -1.84421372465569 \tabularnewline
118 & 16 & 15.873927973377 & 0.126072026622967 \tabularnewline
119 & 13 & 14.7735309178908 & -1.77353091789077 \tabularnewline
120 & 16 & 15.4996870693539 & 0.5003129306461 \tabularnewline
121 & 13 & 16.1195804118893 & -3.11958041188928 \tabularnewline
122 & 16 & 17.2398035973863 & -1.23980359738631 \tabularnewline
123 & 15 & 16.151744659798 & -1.15174465979801 \tabularnewline
124 & 16 & 17.0081850734959 & -1.00818507349592 \tabularnewline
125 & 15 & 14.6706497870479 & 0.329350212952148 \tabularnewline
126 & 17 & 16.0692365751823 & 0.930763424817713 \tabularnewline
127 & 15 & 14.0363631139653 & 0.963636886034715 \tabularnewline
128 & 12 & 14.9479088744955 & -2.94790887449551 \tabularnewline
129 & 16 & 13.9311244188147 & 2.06887558118528 \tabularnewline
130 & 10 & 13.9121308110196 & -3.91213081101955 \tabularnewline
131 & 16 & 13.6535641524173 & 2.34643584758267 \tabularnewline
132 & 12 & 14.188193463741 & -2.18819346374104 \tabularnewline
133 & 14 & 15.9626676971111 & -1.9626676971111 \tabularnewline
134 & 15 & 15.2121154970735 & -0.21211549707348 \tabularnewline
135 & 13 & 12.2545379405534 & 0.745462059446554 \tabularnewline
136 & 15 & 14.8836985539219 & 0.116301446078065 \tabularnewline
137 & 11 & 13.7814719535173 & -2.78147195351732 \tabularnewline
138 & 12 & 13.1343740562465 & -1.13437405624652 \tabularnewline
139 & 11 & 13.3505977303017 & -2.35059773030171 \tabularnewline
140 & 16 & 12.9243664483591 & 3.07563355164091 \tabularnewline
141 & 15 & 13.6228052050396 & 1.37719479496035 \tabularnewline
142 & 17 & 17.1274425039262 & -0.127442503926216 \tabularnewline
143 & 16 & 14.0734563027546 & 1.92654369724539 \tabularnewline
144 & 10 & 13.3916843418543 & -3.39168434185428 \tabularnewline
145 & 18 & 15.722639649624 & 2.27736035037599 \tabularnewline
146 & 13 & 15.4739801282944 & -2.47398012829439 \tabularnewline
147 & 16 & 14.9884826460009 & 1.01151735399907 \tabularnewline
148 & 13 & 13.1555303691779 & -0.155530369177906 \tabularnewline
149 & 10 & 13.0795099500957 & -3.07950995009566 \tabularnewline
150 & 15 & 16.7571646639821 & -1.75716466398208 \tabularnewline
151 & 16 & 13.959207821009 & 2.04079217899097 \tabularnewline
152 & 16 & 11.9402931568035 & 4.05970684319653 \tabularnewline
153 & 14 & 12.885531531211 & 1.11446846878897 \tabularnewline
154 & 10 & 12.6722415236555 & -2.6722415236555 \tabularnewline
155 & 13 & 11.7704506489847 & 1.22954935101528 \tabularnewline
156 & 15 & 14.0363631139653 & 0.963636886034715 \tabularnewline
157 & 16 & 14.6685638221059 & 1.33143617789409 \tabularnewline
158 & 12 & 12.9205112703755 & -0.920511270375539 \tabularnewline
159 & 13 & 12.3034462207792 & 0.696553779220762 \tabularnewline
160 & 12 & 11.6427382596654 & 0.357261740334559 \tabularnewline
161 & 17 & 16.4203079412837 & 0.57969205871632 \tabularnewline
162 & 15 & 13.557083816766 & 1.442916183234 \tabularnewline
163 & 10 & 11.1488653299446 & -1.14886532994456 \tabularnewline
164 & 14 & 13.8374103189078 & 0.16258968109223 \tabularnewline
165 & 11 & 13.6071371572801 & -2.60713715728013 \tabularnewline
166 & 13 & 14.6708345160717 & -1.67083451607168 \tabularnewline
167 & 16 & 14.0939065855186 & 1.90609341448136 \tabularnewline
168 & 12 & 10.2453634792078 & 1.75463652079224 \tabularnewline
169 & 16 & 15.2897722709539 & 0.710227729046111 \tabularnewline
170 & 12 & 13.7145389511754 & -1.71453895117537 \tabularnewline
171 & 9 & 10.7770743033739 & -1.77707430337394 \tabularnewline
172 & 12 & 14.7822400218786 & -2.7822400218786 \tabularnewline
173 & 15 & 14.0137253129179 & 0.986274687082145 \tabularnewline
174 & 12 & 12.1056433762038 & -0.105643376203766 \tabularnewline
175 & 12 & 12.2686646646627 & -0.268664664662723 \tabularnewline
176 & 14 & 13.3547865648457 & 0.645213435154328 \tabularnewline
177 & 12 & 13.1774749417413 & -1.17747494174128 \tabularnewline
178 & 16 & 15.0804297545268 & 0.919570245473226 \tabularnewline
179 & 11 & 10.8252250762605 & 0.174774923739546 \tabularnewline
180 & 19 & 16.6463016805405 & 2.35369831945955 \tabularnewline
181 & 15 & 14.9643472312776 & 0.0356527687224131 \tabularnewline
182 & 8 & 13.8022045184039 & -5.80220451840394 \tabularnewline
183 & 16 & 14.7239445885231 & 1.27605541147695 \tabularnewline
184 & 17 & 14.3138180068021 & 2.6861819931979 \tabularnewline
185 & 12 & 11.9684045400232 & 0.0315954599768082 \tabularnewline
186 & 11 & 10.8457314770737 & 0.15426852292634 \tabularnewline
187 & 11 & 10.1773131599928 & 0.822686840007238 \tabularnewline
188 & 14 & 14.5709945442154 & -0.570994544215412 \tabularnewline
189 & 16 & 15.4460047149296 & 0.553995285070368 \tabularnewline
190 & 12 & 9.09793534536686 & 2.90206465463314 \tabularnewline
191 & 16 & 14.2140855274328 & 1.78591447256717 \tabularnewline
192 & 13 & 13.4047065507738 & -0.404706550773805 \tabularnewline
193 & 15 & 15.0797494837243 & -0.0797494837243336 \tabularnewline
194 & 16 & 12.788535031636 & 3.21146496836403 \tabularnewline
195 & 16 & 14.9268146187588 & 1.07318538124118 \tabularnewline
196 & 14 & 12.3419496002933 & 1.6580503997067 \tabularnewline
197 & 16 & 13.9091668885697 & 2.09083311143027 \tabularnewline
198 & 14 & 12.7013836121388 & 1.29861638786118 \tabularnewline
199 & 11 & 12.9874423914012 & -1.9874423914012 \tabularnewline
200 & 12 & 14.6078620652739 & -2.60786206527386 \tabularnewline
201 & 15 & 12.3408758373963 & 2.65912416260374 \tabularnewline
202 & 15 & 14.3935906079662 & 0.606409392033847 \tabularnewline
203 & 16 & 14.4435105938943 & 1.55648940610571 \tabularnewline
204 & 16 & 15.1328595561757 & 0.867140443824294 \tabularnewline
205 & 11 & 13.5576414157393 & -2.55764141573932 \tabularnewline
206 & 15 & 13.6470614102758 & 1.35293858972418 \tabularnewline
207 & 12 & 14.3888721554743 & -2.38887215547429 \tabularnewline
208 & 12 & 16.0040145489064 & -4.00401454890638 \tabularnewline
209 & 15 & 14.0863451570881 & 0.913654842911876 \tabularnewline
210 & 15 & 11.6051904678045 & 3.39480953219545 \tabularnewline
211 & 16 & 14.7246096799834 & 1.27539032001664 \tabularnewline
212 & 14 & 12.6994313953913 & 1.30056860460867 \tabularnewline
213 & 17 & 14.4201456441918 & 2.57985435580816 \tabularnewline
214 & 14 & 13.9310342245963 & 0.0689657754037305 \tabularnewline
215 & 13 & 12.0414330556302 & 0.958566944369805 \tabularnewline
216 & 15 & 15.326082193039 & -0.326082193039023 \tabularnewline
217 & 13 & 14.5813070290482 & -1.58130702904818 \tabularnewline
218 & 14 & 14.0962489704842 & -0.0962489704841559 \tabularnewline
219 & 15 & 14.3389521695462 & 0.661047830453838 \tabularnewline
220 & 12 & 12.6808772113256 & -0.68087721132561 \tabularnewline
221 & 8 & 11.2135150742476 & -3.21351507424758 \tabularnewline
222 & 14 & 13.6100863967304 & 0.389913603269623 \tabularnewline
223 & 14 & 12.7042421610281 & 1.29575783897194 \tabularnewline
224 & 11 & 12.4119521362558 & -1.41195213625578 \tabularnewline
225 & 12 & 12.7541621469562 & -0.754162146956191 \tabularnewline
226 & 13 & 10.862215269148 & 2.13778473085197 \tabularnewline
227 & 10 & 13.323696079834 & -3.323696079834 \tabularnewline
228 & 16 & 10.9937374011586 & 5.00626259884143 \tabularnewline
229 & 18 & 16.4314081894059 & 1.56859181059412 \tabularnewline
230 & 13 & 13.6211866448526 & -0.621186644852576 \tabularnewline
231 & 11 & 13.2919064271927 & -2.29190642719272 \tabularnewline
232 & 4 & 10.8887551260316 & -6.88875512603158 \tabularnewline
233 & 13 & 14.4659047766014 & -1.46590477660143 \tabularnewline
234 & 16 & 14.0025495535768 & 1.99745044642322 \tabularnewline
235 & 10 & 11.4355892006673 & -1.43558920066726 \tabularnewline
236 & 12 & 11.5481329042248 & 0.451867095775239 \tabularnewline
237 & 12 & 13.8413578100362 & -1.84135781003619 \tabularnewline
238 & 10 & 8.27602006776189 & 1.72397993223811 \tabularnewline
239 & 13 & 10.9179274704651 & 2.08207252953493 \tabularnewline
240 & 12 & 11.7808403703543 & 0.219159629645677 \tabularnewline
241 & 14 & 12.7671071193389 & 1.23289288066112 \tabularnewline
242 & 10 & 12.9849325756804 & -2.9849325756804 \tabularnewline
243 & 12 & 10.2453630855993 & 1.7546369144007 \tabularnewline
244 & 12 & 11.1052348265019 & 0.894765173498097 \tabularnewline
245 & 11 & 11.5470439619856 & -0.547043961985587 \tabularnewline
246 & 10 & 11.4213140453639 & -1.42131404536395 \tabularnewline
247 & 12 & 11.1513152073971 & 0.848684792602932 \tabularnewline
248 & 16 & 12.6984499456392 & 3.30155005436085 \tabularnewline
249 & 12 & 13.551168929548 & -1.55116892954797 \tabularnewline
250 & 14 & 13.96447041845 & 0.0355295815499662 \tabularnewline
251 & 16 & 14.6539268732184 & 1.34607312678155 \tabularnewline
252 & 14 & 11.6292356883094 & 2.37076431169056 \tabularnewline
253 & 13 & 14.4908132716146 & -1.49081327161463 \tabularnewline
254 & 4 & 8.75639042612676 & -4.75639042612676 \tabularnewline
255 & 15 & 13.4887430013581 & 1.51125699864186 \tabularnewline
256 & 11 & 15.0991669422984 & -4.09916694229836 \tabularnewline
257 & 11 & 11.6780515526563 & -0.678051552656267 \tabularnewline
258 & 14 & 12.4643971172468 & 1.53560288275316 \tabularnewline
259 & 15 & 14.6182820425936 & 0.381717957406375 \tabularnewline
260 & 14 & 11.9721107904702 & 2.02788920952984 \tabularnewline
261 & 13 & 12.7925576403748 & 0.207442359625192 \tabularnewline
262 & 11 & 12.2546307500409 & -1.25463075004086 \tabularnewline
263 & 15 & 13.78455666648 & 1.21544333352003 \tabularnewline
264 & 11 & 11.2830630071385 & -0.28306300713848 \tabularnewline
265 & 13 & 11.6540215114935 & 1.34597848850649 \tabularnewline
266 & 13 & 11.5831708803649 & 1.41682911963515 \tabularnewline
267 & 16 & 13.5116841002817 & 2.48831589971827 \tabularnewline
268 & 13 & 12.2235554443713 & 0.776444555628687 \tabularnewline
269 & 16 & 14.9339521964105 & 1.06604780358952 \tabularnewline
270 & 16 & 15.8343977088185 & 0.165602291181501 \tabularnewline
271 & 12 & 11.4401587256225 & 0.55984127437747 \tabularnewline
272 & 7 & 10.8122952832199 & -3.8122952832199 \tabularnewline
273 & 16 & 13.9145504325219 & 2.0854495674781 \tabularnewline
274 & 5 & 9.20467165419333 & -4.20467165419333 \tabularnewline
275 & 16 & 13.1462921435847 & 2.85370785641527 \tabularnewline
276 & 4 & 8.64172838275074 & -4.64172838275074 \tabularnewline
277 & 12 & 13.3400723794214 & -1.34007237942137 \tabularnewline
278 & 15 & 14.1310305266007 & 0.868969473399329 \tabularnewline
279 & 14 & 14.8341122245542 & -0.834112224554212 \tabularnewline
280 & 11 & 13.0205622269631 & -2.02056222696309 \tabularnewline
281 & 16 & 14.9844297813119 & 1.01557021868807 \tabularnewline
282 & 15 & 13.6374140169034 & 1.36258598309663 \tabularnewline
283 & 12 & 12.0787396068096 & -0.0787396068096383 \tabularnewline
284 & 6 & 8.99807980056001 & -2.99807980056001 \tabularnewline
285 & 16 & 14.5182164030065 & 1.48178359699351 \tabularnewline
286 & 10 & 13.3329348017697 & -3.33293480176972 \tabularnewline
287 & 15 & 16.0797337890389 & -1.07973378903888 \tabularnewline
288 & 14 & 14.4912371223935 & -0.491237122393489 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154801&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]13[/C][C]16.1967205255034[/C][C]-3.19672052550342[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.4009516126874[/C][C]0.599048387312611[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.8980174374648[/C][C]2.10198256253524[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]11.2914104735405[/C][C]3.70858952645953[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.4265694427437[/C][C]-2.42656944274373[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.3284549556896[/C][C]-1.32845495568956[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.6619681487421[/C][C]3.33803185125787[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.8405360231061[/C][C]-1.84053602310611[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.7540054514864[/C][C]-1.75400545148642[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.1232581134389[/C][C]0.876741886561136[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.5442547789659[/C][C]1.4557452210341[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.0035130679822[/C][C]-0.00351306798222513[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.481117705946[/C][C]0.518882294053951[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.5863564010966[/C][C]0.413643598903387[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.7561351446679[/C][C]-0.756135144667875[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.2542176345475[/C][C]-0.254217634547518[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.231217112699[/C][C]0.768782887301033[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.2161379840774[/C][C]3.78386201592255[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.4028886500927[/C][C]2.59711134990726[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.3812929134319[/C][C]0.61870708656809[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]14.9368086263733[/C][C]1.06319137362669[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]14.8725227945809[/C][C]1.12747720541914[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.680024550368[/C][C]2.31997544963205[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.1968437126759[/C][C]0.803156287324139[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.9172679806268[/C][C]1.08273201937317[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.0992996788069[/C][C]0.900700321193056[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.553344573365[/C][C]1.44665542663496[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.8269259592631[/C][C]-1.82692595926311[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.43121289936[/C][C]0.568787100639956[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]13.918179446432[/C][C]0.0818205535679657[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.25489790535[/C][C]-0.254897905349958[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.2781010733039[/C][C]-0.278101073303888[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.5047699496997[/C][C]-0.504769949699654[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.7267853238004[/C][C]0.273214676199573[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.225045290114[/C][C]-1.22504529011404[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.2906221949077[/C][C]-2.29062219490771[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.6791226812836[/C][C]-2.67912268128358[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.6107028005512[/C][C]-1.61070280055124[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]13.9447496619998[/C][C]2.05525033800015[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.1411320267021[/C][C]1.85886797329785[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.3776946708153[/C][C]1.62230532918474[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.5776904574763[/C][C]-1.57769045747634[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.640717712879[/C][C]2.359282287121[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.0646570045483[/C][C]-0.0646570045483293[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.2526450249961[/C][C]-0.25264502499606[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.5181078988336[/C][C]-4.51810789883362[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.7428895086788[/C][C]-2.74288950867877[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.86429627469[/C][C]0.135703725309968[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.452823815363[/C][C]0.547176184636995[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.5413653560491[/C][C]-1.54136535604908[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.9662659397277[/C][C]-0.966265939727749[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.8384220246101[/C][C]0.16157797538989[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]15.0247925680861[/C][C]-3.02479256808606[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]16.1770618262479[/C][C]-0.177061826247934[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]10.681711440594[/C][C]-1.68171144059398[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.084153406712[/C][C]1.91584659328803[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.9840956094082[/C][C]0.0159043905918059[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.2075952276296[/C][C]0.792404772370382[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.9971485896212[/C][C]0.00285141037880004[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.151567183364[/C][C]1.84843281663596[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.2568545851548[/C][C]0.743145414845178[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.654150300288[/C][C]0.34584969971197[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.5547184845252[/C][C]-0.554718484525173[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.7042086527307[/C][C]-0.704208652730738[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.3884304910836[/C][C]0.611569508916434[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.0072041390871[/C][C]0.992795860912937[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.6947235564501[/C][C]1.30527644354988[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]13.9995985888086[/C][C]4.00040141119142[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]16.2459754199712[/C][C]-4.24597541997123[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.7662701530667[/C][C]0.233729846933328[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.3501738795228[/C][C]-3.35017387952285[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]15.0263361133968[/C][C]-1.02633611339681[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]17.0861884616184[/C][C]0.913811538381643[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.448465843011[/C][C]0.551534156989016[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]14.9793928516018[/C][C]1.02060714839821[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.5826983419465[/C][C]3.41730165805346[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.713052072785[/C][C]-0.713052072784981[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.6121713499864[/C][C]1.38782865001356[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]14.9378975686125[/C][C]-1.93789756861248[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.1894004594892[/C][C]0.810599540510784[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.5698726090222[/C][C]0.430127390977757[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.7967878597629[/C][C]0.203212140237098[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.7571803586675[/C][C]-0.757180358667536[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.7942937387276[/C][C]0.205706261272444[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]13.9953347393883[/C][C]2.00466526061171[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.2191354148246[/C][C]-0.219135414824587[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.4111303493257[/C][C]0.588869650674299[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.941860239083[/C][C]1.05813976091697[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.8194127221295[/C][C]0.180587277870511[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.7434079977327[/C][C]-1.74340799773269[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]17.3018052811888[/C][C]-0.301805281188821[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]16.0223577482408[/C][C]-0.0223577482408099[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.0027729806464[/C][C]-0.00277298064636426[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.8290752948441[/C][C]-1.82907529484407[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.8502623600682[/C][C]1.14973763993183[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]16.2178920177769[/C][C]-0.217892017776931[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.5120307145238[/C][C]2.48796928547624[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8900478529408[/C][C]0.109952147059168[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.2532518794808[/C][C]-0.253251879480791[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.3499712334175[/C][C]-1.34997123341747[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.9407561175017[/C][C]1.05924388249828[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.8131927082477[/C][C]2.18680729175234[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.1195211106992[/C][C]0.880478889300813[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]15.1462586352874[/C][C]0.853741364712584[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]15.3754703393588[/C][C]-2.37547033935875[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.9704855455652[/C][C]1.0295144544348[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]16.2990703130805[/C][C]-0.29907031308048[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.7178035372316[/C][C]1.28219646276839[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]13.1398499133436[/C][C]-1.13984991334355[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2775977635921[/C][C]0.722402236407906[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.2319259323988[/C][C]-0.231925932398792[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.0360909992563[/C][C]1.96390900074375[/C][/ROW]
[ROW][C]113[/C][C]12[/C][C]14.7504223882119[/C][C]-2.7504223882119[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]16.3240969833375[/C][C]1.67590301666245[/C][/ROW]
[ROW][C]115[/C][C]14[/C][C]16.372794278832[/C][C]-2.37279427883205[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.3262513308471[/C][C]0.673748669152917[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]14.8442137246557[/C][C]-1.84421372465569[/C][/ROW]
[ROW][C]118[/C][C]16[/C][C]15.873927973377[/C][C]0.126072026622967[/C][/ROW]
[ROW][C]119[/C][C]13[/C][C]14.7735309178908[/C][C]-1.77353091789077[/C][/ROW]
[ROW][C]120[/C][C]16[/C][C]15.4996870693539[/C][C]0.5003129306461[/C][/ROW]
[ROW][C]121[/C][C]13[/C][C]16.1195804118893[/C][C]-3.11958041188928[/C][/ROW]
[ROW][C]122[/C][C]16[/C][C]17.2398035973863[/C][C]-1.23980359738631[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]16.151744659798[/C][C]-1.15174465979801[/C][/ROW]
[ROW][C]124[/C][C]16[/C][C]17.0081850734959[/C][C]-1.00818507349592[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]14.6706497870479[/C][C]0.329350212952148[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.0692365751823[/C][C]0.930763424817713[/C][/ROW]
[ROW][C]127[/C][C]15[/C][C]14.0363631139653[/C][C]0.963636886034715[/C][/ROW]
[ROW][C]128[/C][C]12[/C][C]14.9479088744955[/C][C]-2.94790887449551[/C][/ROW]
[ROW][C]129[/C][C]16[/C][C]13.9311244188147[/C][C]2.06887558118528[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]13.9121308110196[/C][C]-3.91213081101955[/C][/ROW]
[ROW][C]131[/C][C]16[/C][C]13.6535641524173[/C][C]2.34643584758267[/C][/ROW]
[ROW][C]132[/C][C]12[/C][C]14.188193463741[/C][C]-2.18819346374104[/C][/ROW]
[ROW][C]133[/C][C]14[/C][C]15.9626676971111[/C][C]-1.9626676971111[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]15.2121154970735[/C][C]-0.21211549707348[/C][/ROW]
[ROW][C]135[/C][C]13[/C][C]12.2545379405534[/C][C]0.745462059446554[/C][/ROW]
[ROW][C]136[/C][C]15[/C][C]14.8836985539219[/C][C]0.116301446078065[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]13.7814719535173[/C][C]-2.78147195351732[/C][/ROW]
[ROW][C]138[/C][C]12[/C][C]13.1343740562465[/C][C]-1.13437405624652[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]13.3505977303017[/C][C]-2.35059773030171[/C][/ROW]
[ROW][C]140[/C][C]16[/C][C]12.9243664483591[/C][C]3.07563355164091[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]13.6228052050396[/C][C]1.37719479496035[/C][/ROW]
[ROW][C]142[/C][C]17[/C][C]17.1274425039262[/C][C]-0.127442503926216[/C][/ROW]
[ROW][C]143[/C][C]16[/C][C]14.0734563027546[/C][C]1.92654369724539[/C][/ROW]
[ROW][C]144[/C][C]10[/C][C]13.3916843418543[/C][C]-3.39168434185428[/C][/ROW]
[ROW][C]145[/C][C]18[/C][C]15.722639649624[/C][C]2.27736035037599[/C][/ROW]
[ROW][C]146[/C][C]13[/C][C]15.4739801282944[/C][C]-2.47398012829439[/C][/ROW]
[ROW][C]147[/C][C]16[/C][C]14.9884826460009[/C][C]1.01151735399907[/C][/ROW]
[ROW][C]148[/C][C]13[/C][C]13.1555303691779[/C][C]-0.155530369177906[/C][/ROW]
[ROW][C]149[/C][C]10[/C][C]13.0795099500957[/C][C]-3.07950995009566[/C][/ROW]
[ROW][C]150[/C][C]15[/C][C]16.7571646639821[/C][C]-1.75716466398208[/C][/ROW]
[ROW][C]151[/C][C]16[/C][C]13.959207821009[/C][C]2.04079217899097[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]11.9402931568035[/C][C]4.05970684319653[/C][/ROW]
[ROW][C]153[/C][C]14[/C][C]12.885531531211[/C][C]1.11446846878897[/C][/ROW]
[ROW][C]154[/C][C]10[/C][C]12.6722415236555[/C][C]-2.6722415236555[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.7704506489847[/C][C]1.22954935101528[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]14.0363631139653[/C][C]0.963636886034715[/C][/ROW]
[ROW][C]157[/C][C]16[/C][C]14.6685638221059[/C][C]1.33143617789409[/C][/ROW]
[ROW][C]158[/C][C]12[/C][C]12.9205112703755[/C][C]-0.920511270375539[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]12.3034462207792[/C][C]0.696553779220762[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.6427382596654[/C][C]0.357261740334559[/C][/ROW]
[ROW][C]161[/C][C]17[/C][C]16.4203079412837[/C][C]0.57969205871632[/C][/ROW]
[ROW][C]162[/C][C]15[/C][C]13.557083816766[/C][C]1.442916183234[/C][/ROW]
[ROW][C]163[/C][C]10[/C][C]11.1488653299446[/C][C]-1.14886532994456[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]13.8374103189078[/C][C]0.16258968109223[/C][/ROW]
[ROW][C]165[/C][C]11[/C][C]13.6071371572801[/C][C]-2.60713715728013[/C][/ROW]
[ROW][C]166[/C][C]13[/C][C]14.6708345160717[/C][C]-1.67083451607168[/C][/ROW]
[ROW][C]167[/C][C]16[/C][C]14.0939065855186[/C][C]1.90609341448136[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]10.2453634792078[/C][C]1.75463652079224[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]15.2897722709539[/C][C]0.710227729046111[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]13.7145389511754[/C][C]-1.71453895117537[/C][/ROW]
[ROW][C]171[/C][C]9[/C][C]10.7770743033739[/C][C]-1.77707430337394[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]14.7822400218786[/C][C]-2.7822400218786[/C][/ROW]
[ROW][C]173[/C][C]15[/C][C]14.0137253129179[/C][C]0.986274687082145[/C][/ROW]
[ROW][C]174[/C][C]12[/C][C]12.1056433762038[/C][C]-0.105643376203766[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]12.2686646646627[/C][C]-0.268664664662723[/C][/ROW]
[ROW][C]176[/C][C]14[/C][C]13.3547865648457[/C][C]0.645213435154328[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]13.1774749417413[/C][C]-1.17747494174128[/C][/ROW]
[ROW][C]178[/C][C]16[/C][C]15.0804297545268[/C][C]0.919570245473226[/C][/ROW]
[ROW][C]179[/C][C]11[/C][C]10.8252250762605[/C][C]0.174774923739546[/C][/ROW]
[ROW][C]180[/C][C]19[/C][C]16.6463016805405[/C][C]2.35369831945955[/C][/ROW]
[ROW][C]181[/C][C]15[/C][C]14.9643472312776[/C][C]0.0356527687224131[/C][/ROW]
[ROW][C]182[/C][C]8[/C][C]13.8022045184039[/C][C]-5.80220451840394[/C][/ROW]
[ROW][C]183[/C][C]16[/C][C]14.7239445885231[/C][C]1.27605541147695[/C][/ROW]
[ROW][C]184[/C][C]17[/C][C]14.3138180068021[/C][C]2.6861819931979[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]11.9684045400232[/C][C]0.0315954599768082[/C][/ROW]
[ROW][C]186[/C][C]11[/C][C]10.8457314770737[/C][C]0.15426852292634[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]10.1773131599928[/C][C]0.822686840007238[/C][/ROW]
[ROW][C]188[/C][C]14[/C][C]14.5709945442154[/C][C]-0.570994544215412[/C][/ROW]
[ROW][C]189[/C][C]16[/C][C]15.4460047149296[/C][C]0.553995285070368[/C][/ROW]
[ROW][C]190[/C][C]12[/C][C]9.09793534536686[/C][C]2.90206465463314[/C][/ROW]
[ROW][C]191[/C][C]16[/C][C]14.2140855274328[/C][C]1.78591447256717[/C][/ROW]
[ROW][C]192[/C][C]13[/C][C]13.4047065507738[/C][C]-0.404706550773805[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]15.0797494837243[/C][C]-0.0797494837243336[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]12.788535031636[/C][C]3.21146496836403[/C][/ROW]
[ROW][C]195[/C][C]16[/C][C]14.9268146187588[/C][C]1.07318538124118[/C][/ROW]
[ROW][C]196[/C][C]14[/C][C]12.3419496002933[/C][C]1.6580503997067[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]13.9091668885697[/C][C]2.09083311143027[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]12.7013836121388[/C][C]1.29861638786118[/C][/ROW]
[ROW][C]199[/C][C]11[/C][C]12.9874423914012[/C][C]-1.9874423914012[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]14.6078620652739[/C][C]-2.60786206527386[/C][/ROW]
[ROW][C]201[/C][C]15[/C][C]12.3408758373963[/C][C]2.65912416260374[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]14.3935906079662[/C][C]0.606409392033847[/C][/ROW]
[ROW][C]203[/C][C]16[/C][C]14.4435105938943[/C][C]1.55648940610571[/C][/ROW]
[ROW][C]204[/C][C]16[/C][C]15.1328595561757[/C][C]0.867140443824294[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]13.5576414157393[/C][C]-2.55764141573932[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.6470614102758[/C][C]1.35293858972418[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]14.3888721554743[/C][C]-2.38887215547429[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]16.0040145489064[/C][C]-4.00401454890638[/C][/ROW]
[ROW][C]209[/C][C]15[/C][C]14.0863451570881[/C][C]0.913654842911876[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]11.6051904678045[/C][C]3.39480953219545[/C][/ROW]
[ROW][C]211[/C][C]16[/C][C]14.7246096799834[/C][C]1.27539032001664[/C][/ROW]
[ROW][C]212[/C][C]14[/C][C]12.6994313953913[/C][C]1.30056860460867[/C][/ROW]
[ROW][C]213[/C][C]17[/C][C]14.4201456441918[/C][C]2.57985435580816[/C][/ROW]
[ROW][C]214[/C][C]14[/C][C]13.9310342245963[/C][C]0.0689657754037305[/C][/ROW]
[ROW][C]215[/C][C]13[/C][C]12.0414330556302[/C][C]0.958566944369805[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]15.326082193039[/C][C]-0.326082193039023[/C][/ROW]
[ROW][C]217[/C][C]13[/C][C]14.5813070290482[/C][C]-1.58130702904818[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.0962489704842[/C][C]-0.0962489704841559[/C][/ROW]
[ROW][C]219[/C][C]15[/C][C]14.3389521695462[/C][C]0.661047830453838[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]12.6808772113256[/C][C]-0.68087721132561[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]11.2135150742476[/C][C]-3.21351507424758[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]13.6100863967304[/C][C]0.389913603269623[/C][/ROW]
[ROW][C]223[/C][C]14[/C][C]12.7042421610281[/C][C]1.29575783897194[/C][/ROW]
[ROW][C]224[/C][C]11[/C][C]12.4119521362558[/C][C]-1.41195213625578[/C][/ROW]
[ROW][C]225[/C][C]12[/C][C]12.7541621469562[/C][C]-0.754162146956191[/C][/ROW]
[ROW][C]226[/C][C]13[/C][C]10.862215269148[/C][C]2.13778473085197[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]13.323696079834[/C][C]-3.323696079834[/C][/ROW]
[ROW][C]228[/C][C]16[/C][C]10.9937374011586[/C][C]5.00626259884143[/C][/ROW]
[ROW][C]229[/C][C]18[/C][C]16.4314081894059[/C][C]1.56859181059412[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]13.6211866448526[/C][C]-0.621186644852576[/C][/ROW]
[ROW][C]231[/C][C]11[/C][C]13.2919064271927[/C][C]-2.29190642719272[/C][/ROW]
[ROW][C]232[/C][C]4[/C][C]10.8887551260316[/C][C]-6.88875512603158[/C][/ROW]
[ROW][C]233[/C][C]13[/C][C]14.4659047766014[/C][C]-1.46590477660143[/C][/ROW]
[ROW][C]234[/C][C]16[/C][C]14.0025495535768[/C][C]1.99745044642322[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]11.4355892006673[/C][C]-1.43558920066726[/C][/ROW]
[ROW][C]236[/C][C]12[/C][C]11.5481329042248[/C][C]0.451867095775239[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]13.8413578100362[/C][C]-1.84135781003619[/C][/ROW]
[ROW][C]238[/C][C]10[/C][C]8.27602006776189[/C][C]1.72397993223811[/C][/ROW]
[ROW][C]239[/C][C]13[/C][C]10.9179274704651[/C][C]2.08207252953493[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]11.7808403703543[/C][C]0.219159629645677[/C][/ROW]
[ROW][C]241[/C][C]14[/C][C]12.7671071193389[/C][C]1.23289288066112[/C][/ROW]
[ROW][C]242[/C][C]10[/C][C]12.9849325756804[/C][C]-2.9849325756804[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]10.2453630855993[/C][C]1.7546369144007[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]11.1052348265019[/C][C]0.894765173498097[/C][/ROW]
[ROW][C]245[/C][C]11[/C][C]11.5470439619856[/C][C]-0.547043961985587[/C][/ROW]
[ROW][C]246[/C][C]10[/C][C]11.4213140453639[/C][C]-1.42131404536395[/C][/ROW]
[ROW][C]247[/C][C]12[/C][C]11.1513152073971[/C][C]0.848684792602932[/C][/ROW]
[ROW][C]248[/C][C]16[/C][C]12.6984499456392[/C][C]3.30155005436085[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]13.551168929548[/C][C]-1.55116892954797[/C][/ROW]
[ROW][C]250[/C][C]14[/C][C]13.96447041845[/C][C]0.0355295815499662[/C][/ROW]
[ROW][C]251[/C][C]16[/C][C]14.6539268732184[/C][C]1.34607312678155[/C][/ROW]
[ROW][C]252[/C][C]14[/C][C]11.6292356883094[/C][C]2.37076431169056[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.4908132716146[/C][C]-1.49081327161463[/C][/ROW]
[ROW][C]254[/C][C]4[/C][C]8.75639042612676[/C][C]-4.75639042612676[/C][/ROW]
[ROW][C]255[/C][C]15[/C][C]13.4887430013581[/C][C]1.51125699864186[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]15.0991669422984[/C][C]-4.09916694229836[/C][/ROW]
[ROW][C]257[/C][C]11[/C][C]11.6780515526563[/C][C]-0.678051552656267[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]12.4643971172468[/C][C]1.53560288275316[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]14.6182820425936[/C][C]0.381717957406375[/C][/ROW]
[ROW][C]260[/C][C]14[/C][C]11.9721107904702[/C][C]2.02788920952984[/C][/ROW]
[ROW][C]261[/C][C]13[/C][C]12.7925576403748[/C][C]0.207442359625192[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]12.2546307500409[/C][C]-1.25463075004086[/C][/ROW]
[ROW][C]263[/C][C]15[/C][C]13.78455666648[/C][C]1.21544333352003[/C][/ROW]
[ROW][C]264[/C][C]11[/C][C]11.2830630071385[/C][C]-0.28306300713848[/C][/ROW]
[ROW][C]265[/C][C]13[/C][C]11.6540215114935[/C][C]1.34597848850649[/C][/ROW]
[ROW][C]266[/C][C]13[/C][C]11.5831708803649[/C][C]1.41682911963515[/C][/ROW]
[ROW][C]267[/C][C]16[/C][C]13.5116841002817[/C][C]2.48831589971827[/C][/ROW]
[ROW][C]268[/C][C]13[/C][C]12.2235554443713[/C][C]0.776444555628687[/C][/ROW]
[ROW][C]269[/C][C]16[/C][C]14.9339521964105[/C][C]1.06604780358952[/C][/ROW]
[ROW][C]270[/C][C]16[/C][C]15.8343977088185[/C][C]0.165602291181501[/C][/ROW]
[ROW][C]271[/C][C]12[/C][C]11.4401587256225[/C][C]0.55984127437747[/C][/ROW]
[ROW][C]272[/C][C]7[/C][C]10.8122952832199[/C][C]-3.8122952832199[/C][/ROW]
[ROW][C]273[/C][C]16[/C][C]13.9145504325219[/C][C]2.0854495674781[/C][/ROW]
[ROW][C]274[/C][C]5[/C][C]9.20467165419333[/C][C]-4.20467165419333[/C][/ROW]
[ROW][C]275[/C][C]16[/C][C]13.1462921435847[/C][C]2.85370785641527[/C][/ROW]
[ROW][C]276[/C][C]4[/C][C]8.64172838275074[/C][C]-4.64172838275074[/C][/ROW]
[ROW][C]277[/C][C]12[/C][C]13.3400723794214[/C][C]-1.34007237942137[/C][/ROW]
[ROW][C]278[/C][C]15[/C][C]14.1310305266007[/C][C]0.868969473399329[/C][/ROW]
[ROW][C]279[/C][C]14[/C][C]14.8341122245542[/C][C]-0.834112224554212[/C][/ROW]
[ROW][C]280[/C][C]11[/C][C]13.0205622269631[/C][C]-2.02056222696309[/C][/ROW]
[ROW][C]281[/C][C]16[/C][C]14.9844297813119[/C][C]1.01557021868807[/C][/ROW]
[ROW][C]282[/C][C]15[/C][C]13.6374140169034[/C][C]1.36258598309663[/C][/ROW]
[ROW][C]283[/C][C]12[/C][C]12.0787396068096[/C][C]-0.0787396068096383[/C][/ROW]
[ROW][C]284[/C][C]6[/C][C]8.99807980056001[/C][C]-2.99807980056001[/C][/ROW]
[ROW][C]285[/C][C]16[/C][C]14.5182164030065[/C][C]1.48178359699351[/C][/ROW]
[ROW][C]286[/C][C]10[/C][C]13.3329348017697[/C][C]-3.33293480176972[/C][/ROW]
[ROW][C]287[/C][C]15[/C][C]16.0797337890389[/C][C]-1.07973378903888[/C][/ROW]
[ROW][C]288[/C][C]14[/C][C]14.4912371223935[/C][C]-0.491237122393489[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154801&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154801&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
11316.1967205255034-3.19672052550342
21615.40095161268740.599048387312611
31916.89801743746482.10198256253524
41511.29141047354053.70858952645953
51416.4265694427437-2.42656944274373
61314.3284549556896-1.32845495568956
71915.66196814874213.33803185125787
81516.8405360231061-1.84053602310611
91415.7540054514864-1.75400545148642
101514.12325811343890.876741886561136
111614.54425477896591.4557452210341
121616.0035130679822-0.00351306798222513
131615.4811177059460.518882294053951
141615.58635640109660.413643598903387
151717.7561351446679-0.756135144667875
161515.2542176345475-0.254217634547518
171514.2312171126990.768782887301033
182016.21613798407743.78386201592255
191815.40288865009272.59711134990726
201615.38129291343190.61870708656809
211614.93680862637331.06319137362669
221614.87252279458091.12747720541914
231916.6800245503682.31997544963205
241615.19684371267590.803156287324139
251715.91726798062681.08273201937317
261716.09929967880690.900700321193056
271614.5533445733651.44665542663496
281516.8269259592631-1.82692595926311
291615.431212899360.568787100639956
301413.9181794464320.0818205535679657
311515.25489790535-0.254897905349958
321212.2781010733039-0.278101073303888
331414.5047699496997-0.504769949699654
341615.72678532380040.273214676199573
351415.225045290114-1.22504529011404
361012.2906221949077-2.29062219490771
371012.6791226812836-2.67912268128358
381415.6107028005512-1.61070280055124
391613.94474966199982.05525033800015
401614.14113202670211.85886797329785
411614.37769467081531.62230532918474
421415.5776904574763-1.57769045747634
432017.6407177128792.359282287121
441414.0646570045483-0.0646570045483293
451414.2526450249961-0.25264502499606
461115.5181078988336-4.51810789883362
471416.7428895086788-2.74288950867877
481514.864296274690.135703725309968
491615.4528238153630.547176184636995
501415.5413653560491-1.54136535604908
511616.9662659397277-0.966265939727749
521413.83842202461010.16157797538989
531215.0247925680861-3.02479256808606
541616.1770618262479-0.177061826247934
55910.681711440594-1.68171144059398
561412.0841534067121.91584659328803
571615.98409560940820.0159043905918059
581615.20759522762960.792404772370382
591514.99714858962120.00285141037880004
601614.1515671833641.84843281663596
611211.25685458515480.743145414845178
621615.6541503002880.34584969971197
631616.5547184845252-0.554718484525173
641414.7042086527307-0.704208652730738
651615.38843049108360.611569508916434
661716.00720413908710.992795860912937
671816.69472355645011.30527644354988
681813.99959858880864.00040141119142
691216.2459754199712-4.24597541997123
701615.76627015306670.233729846933328
711013.3501738795228-3.35017387952285
721415.0263361133968-1.02633611339681
731817.08618846161840.913811538381643
741817.4484658430110.551534156989016
751614.97939285160181.02060714839821
761713.58269834194653.41730165805346
771616.713052072785-0.713052072784981
781614.61217134998641.38782865001356
791314.9378975686125-1.93789756861248
801615.18940045948920.810599540510784
811615.56987260902220.430127390977757
821615.79678785976290.203212140237098
831515.7571803586675-0.757180358667536
841514.79429373872760.205706261272444
851613.99533473938832.00466526061171
861414.2191354148246-0.219135414824587
871615.41113034932570.588869650674299
881614.9418602390831.05813976091697
891514.81941272212950.180587277870511
901213.7434079977327-1.74340799773269
911717.3018052811888-0.301805281188821
921616.0223577482408-0.0223577482408099
931515.0027729806464-0.00277298064636426
941314.8290752948441-1.82907529484407
951614.85026236006821.14973763993183
961616.2178920177769-0.217892017776931
971613.51203071452382.48796928547624
981615.89004785294080.109952147059168
991414.2532518794808-0.253251879480791
1001617.3499712334175-1.34997123341747
1011614.94075611750171.05924388249828
1022017.81319270824772.18680729175234
1031514.11952111069920.880478889300813
1041615.14625863528740.853741364712584
1051315.3754703393588-2.37547033935875
1061715.97048554556521.0295144544348
1071616.2990703130805-0.29907031308048
1081614.71780353723161.28219646276839
1091213.1398499133436-1.13984991334355
1101615.27759776359210.722402236407906
1111616.2319259323988-0.231925932398792
1121715.03609099925631.96390900074375
1131214.7504223882119-2.7504223882119
1141816.32409698333751.67590301666245
1151416.372794278832-2.37279427883205
1161413.32625133084710.673748669152917
1171314.8442137246557-1.84421372465569
1181615.8739279733770.126072026622967
1191314.7735309178908-1.77353091789077
1201615.49968706935390.5003129306461
1211316.1195804118893-3.11958041188928
1221617.2398035973863-1.23980359738631
1231516.151744659798-1.15174465979801
1241617.0081850734959-1.00818507349592
1251514.67064978704790.329350212952148
1261716.06923657518230.930763424817713
1271514.03636311396530.963636886034715
1281214.9479088744955-2.94790887449551
1291613.93112441881472.06887558118528
1301013.9121308110196-3.91213081101955
1311613.65356415241732.34643584758267
1321214.188193463741-2.18819346374104
1331415.9626676971111-1.9626676971111
1341515.2121154970735-0.21211549707348
1351312.25453794055340.745462059446554
1361514.88369855392190.116301446078065
1371113.7814719535173-2.78147195351732
1381213.1343740562465-1.13437405624652
1391113.3505977303017-2.35059773030171
1401612.92436644835913.07563355164091
1411513.62280520503961.37719479496035
1421717.1274425039262-0.127442503926216
1431614.07345630275461.92654369724539
1441013.3916843418543-3.39168434185428
1451815.7226396496242.27736035037599
1461315.4739801282944-2.47398012829439
1471614.98848264600091.01151735399907
1481313.1555303691779-0.155530369177906
1491013.0795099500957-3.07950995009566
1501516.7571646639821-1.75716466398208
1511613.9592078210092.04079217899097
1521611.94029315680354.05970684319653
1531412.8855315312111.11446846878897
1541012.6722415236555-2.6722415236555
1551311.77045064898471.22954935101528
1561514.03636311396530.963636886034715
1571614.66856382210591.33143617789409
1581212.9205112703755-0.920511270375539
1591312.30344622077920.696553779220762
1601211.64273825966540.357261740334559
1611716.42030794128370.57969205871632
1621513.5570838167661.442916183234
1631011.1488653299446-1.14886532994456
1641413.83741031890780.16258968109223
1651113.6071371572801-2.60713715728013
1661314.6708345160717-1.67083451607168
1671614.09390658551861.90609341448136
1681210.24536347920781.75463652079224
1691615.28977227095390.710227729046111
1701213.7145389511754-1.71453895117537
171910.7770743033739-1.77707430337394
1721214.7822400218786-2.7822400218786
1731514.01372531291790.986274687082145
1741212.1056433762038-0.105643376203766
1751212.2686646646627-0.268664664662723
1761413.35478656484570.645213435154328
1771213.1774749417413-1.17747494174128
1781615.08042975452680.919570245473226
1791110.82522507626050.174774923739546
1801916.64630168054052.35369831945955
1811514.96434723127760.0356527687224131
182813.8022045184039-5.80220451840394
1831614.72394458852311.27605541147695
1841714.31381800680212.6861819931979
1851211.96840454002320.0315954599768082
1861110.84573147707370.15426852292634
1871110.17731315999280.822686840007238
1881414.5709945442154-0.570994544215412
1891615.44600471492960.553995285070368
190129.097935345366862.90206465463314
1911614.21408552743281.78591447256717
1921313.4047065507738-0.404706550773805
1931515.0797494837243-0.0797494837243336
1941612.7885350316363.21146496836403
1951614.92681461875881.07318538124118
1961412.34194960029331.6580503997067
1971613.90916688856972.09083311143027
1981412.70138361213881.29861638786118
1991112.9874423914012-1.9874423914012
2001214.6078620652739-2.60786206527386
2011512.34087583739632.65912416260374
2021514.39359060796620.606409392033847
2031614.44351059389431.55648940610571
2041615.13285955617570.867140443824294
2051113.5576414157393-2.55764141573932
2061513.64706141027581.35293858972418
2071214.3888721554743-2.38887215547429
2081216.0040145489064-4.00401454890638
2091514.08634515708810.913654842911876
2101511.60519046780453.39480953219545
2111614.72460967998341.27539032001664
2121412.69943139539131.30056860460867
2131714.42014564419182.57985435580816
2141413.93103422459630.0689657754037305
2151312.04143305563020.958566944369805
2161515.326082193039-0.326082193039023
2171314.5813070290482-1.58130702904818
2181414.0962489704842-0.0962489704841559
2191514.33895216954620.661047830453838
2201212.6808772113256-0.68087721132561
221811.2135150742476-3.21351507424758
2221413.61008639673040.389913603269623
2231412.70424216102811.29575783897194
2241112.4119521362558-1.41195213625578
2251212.7541621469562-0.754162146956191
2261310.8622152691482.13778473085197
2271013.323696079834-3.323696079834
2281610.99373740115865.00626259884143
2291816.43140818940591.56859181059412
2301313.6211866448526-0.621186644852576
2311113.2919064271927-2.29190642719272
232410.8887551260316-6.88875512603158
2331314.4659047766014-1.46590477660143
2341614.00254955357681.99745044642322
2351011.4355892006673-1.43558920066726
2361211.54813290422480.451867095775239
2371213.8413578100362-1.84135781003619
238108.276020067761891.72397993223811
2391310.91792747046512.08207252953493
2401211.78084037035430.219159629645677
2411412.76710711933891.23289288066112
2421012.9849325756804-2.9849325756804
2431210.24536308559931.7546369144007
2441211.10523482650190.894765173498097
2451111.5470439619856-0.547043961985587
2461011.4213140453639-1.42131404536395
2471211.15131520739710.848684792602932
2481612.69844994563923.30155005436085
2491213.551168929548-1.55116892954797
2501413.964470418450.0355295815499662
2511614.65392687321841.34607312678155
2521411.62923568830942.37076431169056
2531314.4908132716146-1.49081327161463
25448.75639042612676-4.75639042612676
2551513.48874300135811.51125699864186
2561115.0991669422984-4.09916694229836
2571111.6780515526563-0.678051552656267
2581412.46439711724681.53560288275316
2591514.61828204259360.381717957406375
2601411.97211079047022.02788920952984
2611312.79255764037480.207442359625192
2621112.2546307500409-1.25463075004086
2631513.784556666481.21544333352003
2641111.2830630071385-0.28306300713848
2651311.65402151149351.34597848850649
2661311.58317088036491.41682911963515
2671613.51168410028172.48831589971827
2681312.22355544437130.776444555628687
2691614.93395219641051.06604780358952
2701615.83439770881850.165602291181501
2711211.44015872562250.55984127437747
272710.8122952832199-3.8122952832199
2731613.91455043252192.0854495674781
27459.20467165419333-4.20467165419333
2751613.14629214358472.85370785641527
27648.64172838275074-4.64172838275074
2771213.3400723794214-1.34007237942137
2781514.13103052660070.868969473399329
2791414.8341122245542-0.834112224554212
2801113.0205622269631-2.02056222696309
2811614.98442978131191.01557021868807
2821513.63741401690341.36258598309663
2831212.0787396068096-0.0787396068096383
28468.99807980056001-2.99807980056001
2851614.51821640300651.48178359699351
2861013.3329348017697-3.33293480176972
2871516.0797337890389-1.07973378903888
2881414.4912371223935-0.491237122393489






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.8140862613476920.3718274773046150.185913738652308
110.7612293255232210.4775413489535570.238770674476779
120.7841446657999930.4317106684000140.215855334200007
130.7191614508461330.5616770983077340.280838549153867
140.7124118792216670.5751762415566660.287588120778333
150.6690445118395930.6619109763208150.330955488160407
160.6126003870800610.7747992258398780.387399612919939
170.5248228024046360.9503543951907280.475177197595364
180.8557411548144980.2885176903710040.144258845185502
190.8499988195131080.3000023609737840.150001180486892
200.8020028104764740.3959943790470510.197997189523526
210.7458978699309550.508204260138090.254102130069045
220.6840991192378350.631801761524330.315900880762165
230.7037922041831720.5924155916336560.296207795816828
240.6406156376062710.7187687247874590.359384362393729
250.5774827891777590.8450344216444830.422517210822241
260.5108401999270480.9783196001459040.489159800072952
270.4471861019728040.8943722039456080.552813898027196
280.4304026560372970.8608053120745930.569597343962703
290.3698740709033980.7397481418067950.630125929096602
300.3562798871512190.7125597743024370.643720112848781
310.3008568742063120.6017137484126230.699143125793688
320.2852031921920630.5704063843841250.714796807807937
330.2518397659076080.5036795318152170.748160234092392
340.2070497439005980.4140994878011950.792950256099402
350.2059318389328850.411863677865770.794068161067115
360.2941915899265720.5883831798531450.705808410073428
370.3817228398264890.7634456796529780.618277160173511
380.3839898087595720.7679796175191430.616010191240428
390.4124447145954080.8248894291908150.587555285404592
400.3916937442342660.7833874884685330.608306255765734
410.3579916186913320.7159832373826640.642008381308668
420.3449277142197560.6898554284395130.655072285780244
430.3579077685250750.7158155370501490.642092231474925
440.3171954455687940.6343908911375890.682804554431206
450.2811120651802720.5622241303605440.718887934819728
460.5164212282543060.9671575434913880.483578771745694
470.5678737517681450.864252496463710.432126248231855
480.521401393801850.95719721239630.47859860619815
490.4771553371604970.9543106743209940.522844662839503
500.4806792223422820.9613584446845630.519320777657718
510.4385739707537030.8771479415074060.561426029246297
520.3933249243458170.7866498486916330.606675075654183
530.4469614550474480.8939229100948960.553038544952552
540.4044714514543890.8089429029087780.595528548545611
550.4064749814498850.812949962899770.593525018550115
560.3908125607846750.7816251215693490.609187439215325
570.349516667635940.699033335271880.65048333236406
580.3267119493300670.6534238986601340.673288050669933
590.2876534718023190.5753069436046380.712346528197681
600.2897043244540.5794086489079990.710295675546
610.2602931663714970.5205863327429930.739706833628503
620.226680753266020.453361506532040.77331924673398
630.1959689301742270.3919378603484550.804031069825773
640.1694479268146370.3388958536292740.830552073185363
650.146350810803730.292701621607460.85364918919627
660.1341386618317310.2682773236634620.865861338168269
670.1275037929362760.2550075858725530.872496207063724
680.2180354331711610.4360708663423230.781964566828839
690.342188534506530.684377069013060.65781146549347
700.306235927463670.6124718549273410.69376407253633
710.3901941962943040.7803883925886090.609805803705696
720.3563342382306560.7126684764613130.643665761769344
730.3388847802933720.6777695605867430.661115219706628
740.3113932376317010.6227864752634010.688606762368299
750.2807091037819710.5614182075639430.719290896218029
760.3356875115392270.6713750230784540.664312488460773
770.3035697589250740.6071395178501480.696430241074926
780.2815181555452730.5630363110905460.718481844454727
790.2851268266922550.5702536533845110.714873173307745
800.2575864015428530.5151728030857070.742413598457147
810.2311650440810890.4623300881621780.768834955918911
820.2038981452279640.4077962904559280.796101854772036
830.1840796810841610.3681593621683230.815920318915839
840.1598012191588830.3196024383177670.840198780841117
850.1567521448925120.3135042897850240.843247855107488
860.1348756955921810.2697513911843620.865124304407819
870.1169085959141210.2338171918282430.883091404085879
880.1039357236142440.2078714472284880.896064276385756
890.0879825793184290.1759651586368580.912017420681571
900.08352602653409890.1670520530681980.916473973465901
910.07159428467458920.1431885693491780.928405715325411
920.06096379234753460.1219275846950690.939036207652465
930.05170201875076780.1034040375015360.948297981249232
940.05324089096623810.1064817819324760.946759109033762
950.0467347530242470.09346950604849410.953265246975753
960.03851270702205370.07702541404410750.961487292977946
970.04173626823298220.08347253646596440.958263731767018
980.03417195519859030.06834391039718060.96582804480141
990.02775027892762710.05550055785525420.972249721072373
1000.02487829510464460.04975659020928920.975121704895355
1010.02149313980458090.04298627960916170.978506860195419
1020.02541587268610980.05083174537221960.97458412731389
1030.0213231475601710.04264629512034210.978676852439829
1040.01884408542353980.03768817084707950.98115591457646
1050.02390946662175340.04781893324350680.976090533378247
1060.02047789422199950.0409557884439990.979522105778
1070.01639389221686640.03278778443373270.983606107783134
1080.01492521248356980.02985042496713960.98507478751643
1090.01273970087880190.02547940175760380.987260299121198
1100.01050517190899170.02101034381798340.989494828091008
1110.008264613650698120.01652922730139620.991735386349302
1120.009715275811988610.01943055162397720.990284724188011
1130.01363487668293550.02726975336587090.986365123317064
1140.01317657175091870.02635314350183750.986823428249081
1150.01399432638675620.02798865277351240.986005673613244
1160.01173484127448180.02346968254896350.988265158725518
1170.01162594874193710.02325189748387430.988374051258063
1180.009221128411250790.01844225682250160.990778871588749
1190.008611333599435180.01722266719887040.991388666400565
1200.006928218441909860.01385643688381970.99307178155809
1210.00999639730020540.01999279460041080.990003602699795
1220.008508087144945460.01701617428989090.991491912855055
1230.007583086132328110.01516617226465620.992416913867672
1240.006323852762019190.01264770552403840.993676147237981
1250.005013055485901860.01002611097180370.994986944514098
1260.004200402659141930.008400805318283860.995799597340858
1270.003470472969516520.006940945939033030.996529527030483
1280.005358242649316180.01071648529863240.994641757350684
1290.005686989990036470.01137397998007290.994313010009964
1300.01242702636511830.02485405273023660.987572973634882
1310.01378151505749970.02756303011499940.9862184849425
1320.01481808699730920.02963617399461840.985181913002691
1330.01464176515981880.02928353031963770.985358234840181
1340.01187164020185530.02374328040371070.988128359798145
1350.009855847538316460.01971169507663290.990144152461684
1360.007829474633713190.01565894926742640.992170525366287
1370.01043672218303350.02087344436606710.989563277816966
1380.009335755459675630.01867151091935130.990664244540324
1390.01073087542126360.02146175084252720.989269124578736
1400.01479957758111680.02959915516223370.985200422418883
1410.01373722145651140.02747444291302290.986262778543489
1420.01136873195900690.02273746391801380.988631268040993
1430.01139006616548880.02278013233097750.988609933834511
1440.02143703321449250.04287406642898510.978562966785507
1450.02303778816797050.0460755763359410.976962211832029
1460.02610276356587020.05220552713174050.97389723643413
1470.02257786365748860.04515572731497710.977422136342511
1480.01837780091774150.0367556018354830.981622199082259
1490.02709098540291320.05418197080582630.972909014597087
1500.02738604207767880.05477208415535760.972613957922321
1510.02749566038506880.05499132077013750.972504339614931
1520.05087320033130.10174640066260.9491267996687
1530.04523353040822960.09046706081645910.95476646959177
1540.05664353360257410.1132870672051480.943356466397426
1550.04976128128593770.09952256257187530.950238718714062
1560.04276904270758760.08553808541517510.957230957292412
1570.04065705042095860.08131410084191720.959342949579041
1580.03418247708361460.06836495416722920.965817522916385
1590.02887217028877610.05774434057755230.971127829711224
1600.0246136352485870.04922727049717410.975386364751413
1610.0206410007401240.04128200148024810.979358999259876
1620.01812052324281720.03624104648563440.981879476757183
1630.01673820747661930.03347641495323860.983261792523381
1640.01347007455917910.02694014911835830.986529925440821
1650.01678351478001290.03356702956002580.983216485219987
1660.01663275318425060.03326550636850120.983367246815749
1670.01705087258657190.03410174517314370.982949127413428
1680.01712043348233310.03424086696466620.982879566517667
1690.01402725267470930.02805450534941860.985972747325291
1700.0133266804177280.0266533608354560.986673319582272
1710.01315856787937450.0263171357587490.986841432120625
1720.01581471300029530.03162942600059060.984185286999705
1730.01362034075457110.02724068150914210.986379659245429
1740.01088081640971120.02176163281942230.989119183590289
1750.008641516464229070.01728303292845810.991358483535771
1760.007006756854311790.01401351370862360.992993243145688
1770.006047189478334180.01209437895666840.993952810521666
1780.005039130401716680.01007826080343340.994960869598283
1790.004017473887700620.008034947775401230.995982526112299
1800.004510273025549640.009020546051099270.99548972697445
1810.003508499530577940.007016999061155880.996491500469422
1820.02756007798642260.05512015597284530.972439922013577
1830.02449280291011910.04898560582023830.975507197089881
1840.03084061564265060.06168123128530110.969159384357349
1850.0256600952988660.05132019059773190.974339904701134
1860.02098504312937280.04197008625874560.979014956870627
1870.0177004827624060.0354009655248120.982299517237594
1880.01554643384075210.03109286768150420.984453566159248
1890.01260412689452780.02520825378905570.987395873105472
1900.01784867667659460.03569735335318910.982151323323405
1910.01636104626076160.03272209252152330.983638953739238
1920.01332258138988130.02664516277976260.986677418610119
1930.01058179421409740.02116358842819490.989418205785903
1940.01601914381091560.03203828762183120.983980856189084
1950.01320841386013520.02641682772027040.986791586139865
1960.01225954580846580.02451909161693170.987740454191534
1970.0120194386826860.02403887736537190.987980561317314
1980.01004513669702220.02009027339404430.989954863302978
1990.009926721825565620.01985344365113120.990073278174434
2000.01226261352992980.02452522705985960.98773738647007
2010.01470893447035830.02941786894071650.985291065529642
2020.01169188168058370.02338376336116730.988308118319416
2030.0101582554304050.020316510860810.989841744569595
2040.008182880878085550.01636576175617110.991817119121914
2050.009555559632548860.01911111926509770.990444440367451
2060.008558420058212170.01711684011642430.991441579941788
2070.01122619008189460.02245238016378920.988773809918105
2080.02552479683615350.0510495936723070.974475203163847
2090.02084213620861310.04168427241722620.979157863791387
2100.03261697244305040.06523394488610080.96738302755695
2110.02745096233805890.05490192467611790.972549037661941
2120.02525404978544570.05050809957089150.974745950214554
2130.02708965548692540.05417931097385080.972910344513075
2140.02171575303529770.04343150607059550.978284246964702
2150.01858013983210270.03716027966420550.981419860167897
2160.01544263949156360.03088527898312730.984557360508436
2170.01454197982285460.02908395964570930.985458020177145
2180.01138227197938810.02276454395877610.988617728020612
2190.008832454616521670.01766490923304330.991167545383478
2200.006945924605108970.01389184921021790.993054075394891
2210.0110796042713710.0221592085427420.988920395728629
2220.008605177078161180.01721035415632240.991394822921839
2230.007446686336571880.01489337267314380.992553313663428
2240.006339804859731760.01267960971946350.993660195140268
2250.004940182187088070.009880364374176140.995059817812912
2260.006294580317984580.01258916063596920.993705419682015
2270.01425488199220590.02850976398441190.985745118007794
2280.07864574048134910.1572914809626980.921354259518651
2290.07104672914948750.1420934582989750.928953270850513
2300.05842344279041880.1168468855808380.941576557209581
2310.05909084471262150.1181816894252430.940909155287379
2320.2424185272717440.4848370545434870.757581472728256
2330.2231501293507640.4463002587015290.776849870649236
2340.2030243302324960.4060486604649910.796975669767504
2350.1801257682150020.3602515364300050.819874231784998
2360.153650275120110.3073005502402210.84634972487989
2370.1842165213620630.3684330427241260.815783478637937
2380.2364590019391090.4729180038782180.763540998060891
2390.2981290554912990.5962581109825980.701870944508701
2400.2589403529625240.5178807059250480.741059647037476
2410.2437323627548450.487464725509690.756267637245155
2420.2789335140642430.5578670281284860.721066485935757
2430.2672745110244040.5345490220488090.732725488975596
2440.2429772965926560.4859545931853130.757022703407344
2450.2140900768047560.4281801536095120.785909923195244
2460.1834888320704750.3669776641409510.816511167929525
2470.182159754920510.364319509841020.81784024507949
2480.2786693686087050.557338737217410.721330631391295
2490.2622324218221340.5244648436442690.737767578177866
2500.2226566328175240.4453132656350470.777343367182476
2510.1892864918028720.3785729836057430.810713508197128
2520.2123375524413410.4246751048826820.787662447558659
2530.194095847845210.388191695690420.80590415215479
2540.2589856068697410.5179712137394830.741014393130259
2550.2482788499968250.496557699993650.751721150003175
2560.5008675846472510.9982648307054990.499132415352749
2570.4531964180963760.9063928361927520.546803581903624
2580.4617611743972530.9235223487945060.538238825602747
2590.440693714007840.881387428015680.55930628599216
2600.4630870717865010.9261741435730020.536912928213499
2610.4035094630596150.8070189261192310.596490536940385
2620.3541890244965670.7083780489931340.645810975503433
2630.3166099071448780.6332198142897570.683390092855122
2640.2595669442197520.5191338884395050.740433055780248
2650.2570806740001040.5141613480002080.742919325999896
2660.3685860648588610.7371721297177210.631413935141139
2670.6137508847718530.7724982304562940.386249115228147
2680.5520437504713050.8959124990573910.447956249528695
2690.5030510903809940.9938978192380120.496948909619006
2700.5136613544517810.9726772910964380.486338645548219
2710.4419418194148280.8838836388296550.558058180585172
2720.4186395152439280.8372790304878560.581360484756072
2730.3648645309291520.7297290618583040.635135469070848
2740.2889469151035030.5778938302070060.711053084896497
2750.4255951014211270.8511902028422530.574404898578873
2760.3767772755928810.7535545511857630.623222724407119
2770.2666056130175070.5332112260350140.733394386982493
2780.171092306073470.342184612146940.82890769392653

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.814086261347692 & 0.371827477304615 & 0.185913738652308 \tabularnewline
11 & 0.761229325523221 & 0.477541348953557 & 0.238770674476779 \tabularnewline
12 & 0.784144665799993 & 0.431710668400014 & 0.215855334200007 \tabularnewline
13 & 0.719161450846133 & 0.561677098307734 & 0.280838549153867 \tabularnewline
14 & 0.712411879221667 & 0.575176241556666 & 0.287588120778333 \tabularnewline
15 & 0.669044511839593 & 0.661910976320815 & 0.330955488160407 \tabularnewline
16 & 0.612600387080061 & 0.774799225839878 & 0.387399612919939 \tabularnewline
17 & 0.524822802404636 & 0.950354395190728 & 0.475177197595364 \tabularnewline
18 & 0.855741154814498 & 0.288517690371004 & 0.144258845185502 \tabularnewline
19 & 0.849998819513108 & 0.300002360973784 & 0.150001180486892 \tabularnewline
20 & 0.802002810476474 & 0.395994379047051 & 0.197997189523526 \tabularnewline
21 & 0.745897869930955 & 0.50820426013809 & 0.254102130069045 \tabularnewline
22 & 0.684099119237835 & 0.63180176152433 & 0.315900880762165 \tabularnewline
23 & 0.703792204183172 & 0.592415591633656 & 0.296207795816828 \tabularnewline
24 & 0.640615637606271 & 0.718768724787459 & 0.359384362393729 \tabularnewline
25 & 0.577482789177759 & 0.845034421644483 & 0.422517210822241 \tabularnewline
26 & 0.510840199927048 & 0.978319600145904 & 0.489159800072952 \tabularnewline
27 & 0.447186101972804 & 0.894372203945608 & 0.552813898027196 \tabularnewline
28 & 0.430402656037297 & 0.860805312074593 & 0.569597343962703 \tabularnewline
29 & 0.369874070903398 & 0.739748141806795 & 0.630125929096602 \tabularnewline
30 & 0.356279887151219 & 0.712559774302437 & 0.643720112848781 \tabularnewline
31 & 0.300856874206312 & 0.601713748412623 & 0.699143125793688 \tabularnewline
32 & 0.285203192192063 & 0.570406384384125 & 0.714796807807937 \tabularnewline
33 & 0.251839765907608 & 0.503679531815217 & 0.748160234092392 \tabularnewline
34 & 0.207049743900598 & 0.414099487801195 & 0.792950256099402 \tabularnewline
35 & 0.205931838932885 & 0.41186367786577 & 0.794068161067115 \tabularnewline
36 & 0.294191589926572 & 0.588383179853145 & 0.705808410073428 \tabularnewline
37 & 0.381722839826489 & 0.763445679652978 & 0.618277160173511 \tabularnewline
38 & 0.383989808759572 & 0.767979617519143 & 0.616010191240428 \tabularnewline
39 & 0.412444714595408 & 0.824889429190815 & 0.587555285404592 \tabularnewline
40 & 0.391693744234266 & 0.783387488468533 & 0.608306255765734 \tabularnewline
41 & 0.357991618691332 & 0.715983237382664 & 0.642008381308668 \tabularnewline
42 & 0.344927714219756 & 0.689855428439513 & 0.655072285780244 \tabularnewline
43 & 0.357907768525075 & 0.715815537050149 & 0.642092231474925 \tabularnewline
44 & 0.317195445568794 & 0.634390891137589 & 0.682804554431206 \tabularnewline
45 & 0.281112065180272 & 0.562224130360544 & 0.718887934819728 \tabularnewline
46 & 0.516421228254306 & 0.967157543491388 & 0.483578771745694 \tabularnewline
47 & 0.567873751768145 & 0.86425249646371 & 0.432126248231855 \tabularnewline
48 & 0.52140139380185 & 0.9571972123963 & 0.47859860619815 \tabularnewline
49 & 0.477155337160497 & 0.954310674320994 & 0.522844662839503 \tabularnewline
50 & 0.480679222342282 & 0.961358444684563 & 0.519320777657718 \tabularnewline
51 & 0.438573970753703 & 0.877147941507406 & 0.561426029246297 \tabularnewline
52 & 0.393324924345817 & 0.786649848691633 & 0.606675075654183 \tabularnewline
53 & 0.446961455047448 & 0.893922910094896 & 0.553038544952552 \tabularnewline
54 & 0.404471451454389 & 0.808942902908778 & 0.595528548545611 \tabularnewline
55 & 0.406474981449885 & 0.81294996289977 & 0.593525018550115 \tabularnewline
56 & 0.390812560784675 & 0.781625121569349 & 0.609187439215325 \tabularnewline
57 & 0.34951666763594 & 0.69903333527188 & 0.65048333236406 \tabularnewline
58 & 0.326711949330067 & 0.653423898660134 & 0.673288050669933 \tabularnewline
59 & 0.287653471802319 & 0.575306943604638 & 0.712346528197681 \tabularnewline
60 & 0.289704324454 & 0.579408648907999 & 0.710295675546 \tabularnewline
61 & 0.260293166371497 & 0.520586332742993 & 0.739706833628503 \tabularnewline
62 & 0.22668075326602 & 0.45336150653204 & 0.77331924673398 \tabularnewline
63 & 0.195968930174227 & 0.391937860348455 & 0.804031069825773 \tabularnewline
64 & 0.169447926814637 & 0.338895853629274 & 0.830552073185363 \tabularnewline
65 & 0.14635081080373 & 0.29270162160746 & 0.85364918919627 \tabularnewline
66 & 0.134138661831731 & 0.268277323663462 & 0.865861338168269 \tabularnewline
67 & 0.127503792936276 & 0.255007585872553 & 0.872496207063724 \tabularnewline
68 & 0.218035433171161 & 0.436070866342323 & 0.781964566828839 \tabularnewline
69 & 0.34218853450653 & 0.68437706901306 & 0.65781146549347 \tabularnewline
70 & 0.30623592746367 & 0.612471854927341 & 0.69376407253633 \tabularnewline
71 & 0.390194196294304 & 0.780388392588609 & 0.609805803705696 \tabularnewline
72 & 0.356334238230656 & 0.712668476461313 & 0.643665761769344 \tabularnewline
73 & 0.338884780293372 & 0.677769560586743 & 0.661115219706628 \tabularnewline
74 & 0.311393237631701 & 0.622786475263401 & 0.688606762368299 \tabularnewline
75 & 0.280709103781971 & 0.561418207563943 & 0.719290896218029 \tabularnewline
76 & 0.335687511539227 & 0.671375023078454 & 0.664312488460773 \tabularnewline
77 & 0.303569758925074 & 0.607139517850148 & 0.696430241074926 \tabularnewline
78 & 0.281518155545273 & 0.563036311090546 & 0.718481844454727 \tabularnewline
79 & 0.285126826692255 & 0.570253653384511 & 0.714873173307745 \tabularnewline
80 & 0.257586401542853 & 0.515172803085707 & 0.742413598457147 \tabularnewline
81 & 0.231165044081089 & 0.462330088162178 & 0.768834955918911 \tabularnewline
82 & 0.203898145227964 & 0.407796290455928 & 0.796101854772036 \tabularnewline
83 & 0.184079681084161 & 0.368159362168323 & 0.815920318915839 \tabularnewline
84 & 0.159801219158883 & 0.319602438317767 & 0.840198780841117 \tabularnewline
85 & 0.156752144892512 & 0.313504289785024 & 0.843247855107488 \tabularnewline
86 & 0.134875695592181 & 0.269751391184362 & 0.865124304407819 \tabularnewline
87 & 0.116908595914121 & 0.233817191828243 & 0.883091404085879 \tabularnewline
88 & 0.103935723614244 & 0.207871447228488 & 0.896064276385756 \tabularnewline
89 & 0.087982579318429 & 0.175965158636858 & 0.912017420681571 \tabularnewline
90 & 0.0835260265340989 & 0.167052053068198 & 0.916473973465901 \tabularnewline
91 & 0.0715942846745892 & 0.143188569349178 & 0.928405715325411 \tabularnewline
92 & 0.0609637923475346 & 0.121927584695069 & 0.939036207652465 \tabularnewline
93 & 0.0517020187507678 & 0.103404037501536 & 0.948297981249232 \tabularnewline
94 & 0.0532408909662381 & 0.106481781932476 & 0.946759109033762 \tabularnewline
95 & 0.046734753024247 & 0.0934695060484941 & 0.953265246975753 \tabularnewline
96 & 0.0385127070220537 & 0.0770254140441075 & 0.961487292977946 \tabularnewline
97 & 0.0417362682329822 & 0.0834725364659644 & 0.958263731767018 \tabularnewline
98 & 0.0341719551985903 & 0.0683439103971806 & 0.96582804480141 \tabularnewline
99 & 0.0277502789276271 & 0.0555005578552542 & 0.972249721072373 \tabularnewline
100 & 0.0248782951046446 & 0.0497565902092892 & 0.975121704895355 \tabularnewline
101 & 0.0214931398045809 & 0.0429862796091617 & 0.978506860195419 \tabularnewline
102 & 0.0254158726861098 & 0.0508317453722196 & 0.97458412731389 \tabularnewline
103 & 0.021323147560171 & 0.0426462951203421 & 0.978676852439829 \tabularnewline
104 & 0.0188440854235398 & 0.0376881708470795 & 0.98115591457646 \tabularnewline
105 & 0.0239094666217534 & 0.0478189332435068 & 0.976090533378247 \tabularnewline
106 & 0.0204778942219995 & 0.040955788443999 & 0.979522105778 \tabularnewline
107 & 0.0163938922168664 & 0.0327877844337327 & 0.983606107783134 \tabularnewline
108 & 0.0149252124835698 & 0.0298504249671396 & 0.98507478751643 \tabularnewline
109 & 0.0127397008788019 & 0.0254794017576038 & 0.987260299121198 \tabularnewline
110 & 0.0105051719089917 & 0.0210103438179834 & 0.989494828091008 \tabularnewline
111 & 0.00826461365069812 & 0.0165292273013962 & 0.991735386349302 \tabularnewline
112 & 0.00971527581198861 & 0.0194305516239772 & 0.990284724188011 \tabularnewline
113 & 0.0136348766829355 & 0.0272697533658709 & 0.986365123317064 \tabularnewline
114 & 0.0131765717509187 & 0.0263531435018375 & 0.986823428249081 \tabularnewline
115 & 0.0139943263867562 & 0.0279886527735124 & 0.986005673613244 \tabularnewline
116 & 0.0117348412744818 & 0.0234696825489635 & 0.988265158725518 \tabularnewline
117 & 0.0116259487419371 & 0.0232518974838743 & 0.988374051258063 \tabularnewline
118 & 0.00922112841125079 & 0.0184422568225016 & 0.990778871588749 \tabularnewline
119 & 0.00861133359943518 & 0.0172226671988704 & 0.991388666400565 \tabularnewline
120 & 0.00692821844190986 & 0.0138564368838197 & 0.99307178155809 \tabularnewline
121 & 0.0099963973002054 & 0.0199927946004108 & 0.990003602699795 \tabularnewline
122 & 0.00850808714494546 & 0.0170161742898909 & 0.991491912855055 \tabularnewline
123 & 0.00758308613232811 & 0.0151661722646562 & 0.992416913867672 \tabularnewline
124 & 0.00632385276201919 & 0.0126477055240384 & 0.993676147237981 \tabularnewline
125 & 0.00501305548590186 & 0.0100261109718037 & 0.994986944514098 \tabularnewline
126 & 0.00420040265914193 & 0.00840080531828386 & 0.995799597340858 \tabularnewline
127 & 0.00347047296951652 & 0.00694094593903303 & 0.996529527030483 \tabularnewline
128 & 0.00535824264931618 & 0.0107164852986324 & 0.994641757350684 \tabularnewline
129 & 0.00568698999003647 & 0.0113739799800729 & 0.994313010009964 \tabularnewline
130 & 0.0124270263651183 & 0.0248540527302366 & 0.987572973634882 \tabularnewline
131 & 0.0137815150574997 & 0.0275630301149994 & 0.9862184849425 \tabularnewline
132 & 0.0148180869973092 & 0.0296361739946184 & 0.985181913002691 \tabularnewline
133 & 0.0146417651598188 & 0.0292835303196377 & 0.985358234840181 \tabularnewline
134 & 0.0118716402018553 & 0.0237432804037107 & 0.988128359798145 \tabularnewline
135 & 0.00985584753831646 & 0.0197116950766329 & 0.990144152461684 \tabularnewline
136 & 0.00782947463371319 & 0.0156589492674264 & 0.992170525366287 \tabularnewline
137 & 0.0104367221830335 & 0.0208734443660671 & 0.989563277816966 \tabularnewline
138 & 0.00933575545967563 & 0.0186715109193513 & 0.990664244540324 \tabularnewline
139 & 0.0107308754212636 & 0.0214617508425272 & 0.989269124578736 \tabularnewline
140 & 0.0147995775811168 & 0.0295991551622337 & 0.985200422418883 \tabularnewline
141 & 0.0137372214565114 & 0.0274744429130229 & 0.986262778543489 \tabularnewline
142 & 0.0113687319590069 & 0.0227374639180138 & 0.988631268040993 \tabularnewline
143 & 0.0113900661654888 & 0.0227801323309775 & 0.988609933834511 \tabularnewline
144 & 0.0214370332144925 & 0.0428740664289851 & 0.978562966785507 \tabularnewline
145 & 0.0230377881679705 & 0.046075576335941 & 0.976962211832029 \tabularnewline
146 & 0.0261027635658702 & 0.0522055271317405 & 0.97389723643413 \tabularnewline
147 & 0.0225778636574886 & 0.0451557273149771 & 0.977422136342511 \tabularnewline
148 & 0.0183778009177415 & 0.036755601835483 & 0.981622199082259 \tabularnewline
149 & 0.0270909854029132 & 0.0541819708058263 & 0.972909014597087 \tabularnewline
150 & 0.0273860420776788 & 0.0547720841553576 & 0.972613957922321 \tabularnewline
151 & 0.0274956603850688 & 0.0549913207701375 & 0.972504339614931 \tabularnewline
152 & 0.0508732003313 & 0.1017464006626 & 0.9491267996687 \tabularnewline
153 & 0.0452335304082296 & 0.0904670608164591 & 0.95476646959177 \tabularnewline
154 & 0.0566435336025741 & 0.113287067205148 & 0.943356466397426 \tabularnewline
155 & 0.0497612812859377 & 0.0995225625718753 & 0.950238718714062 \tabularnewline
156 & 0.0427690427075876 & 0.0855380854151751 & 0.957230957292412 \tabularnewline
157 & 0.0406570504209586 & 0.0813141008419172 & 0.959342949579041 \tabularnewline
158 & 0.0341824770836146 & 0.0683649541672292 & 0.965817522916385 \tabularnewline
159 & 0.0288721702887761 & 0.0577443405775523 & 0.971127829711224 \tabularnewline
160 & 0.024613635248587 & 0.0492272704971741 & 0.975386364751413 \tabularnewline
161 & 0.020641000740124 & 0.0412820014802481 & 0.979358999259876 \tabularnewline
162 & 0.0181205232428172 & 0.0362410464856344 & 0.981879476757183 \tabularnewline
163 & 0.0167382074766193 & 0.0334764149532386 & 0.983261792523381 \tabularnewline
164 & 0.0134700745591791 & 0.0269401491183583 & 0.986529925440821 \tabularnewline
165 & 0.0167835147800129 & 0.0335670295600258 & 0.983216485219987 \tabularnewline
166 & 0.0166327531842506 & 0.0332655063685012 & 0.983367246815749 \tabularnewline
167 & 0.0170508725865719 & 0.0341017451731437 & 0.982949127413428 \tabularnewline
168 & 0.0171204334823331 & 0.0342408669646662 & 0.982879566517667 \tabularnewline
169 & 0.0140272526747093 & 0.0280545053494186 & 0.985972747325291 \tabularnewline
170 & 0.013326680417728 & 0.026653360835456 & 0.986673319582272 \tabularnewline
171 & 0.0131585678793745 & 0.026317135758749 & 0.986841432120625 \tabularnewline
172 & 0.0158147130002953 & 0.0316294260005906 & 0.984185286999705 \tabularnewline
173 & 0.0136203407545711 & 0.0272406815091421 & 0.986379659245429 \tabularnewline
174 & 0.0108808164097112 & 0.0217616328194223 & 0.989119183590289 \tabularnewline
175 & 0.00864151646422907 & 0.0172830329284581 & 0.991358483535771 \tabularnewline
176 & 0.00700675685431179 & 0.0140135137086236 & 0.992993243145688 \tabularnewline
177 & 0.00604718947833418 & 0.0120943789566684 & 0.993952810521666 \tabularnewline
178 & 0.00503913040171668 & 0.0100782608034334 & 0.994960869598283 \tabularnewline
179 & 0.00401747388770062 & 0.00803494777540123 & 0.995982526112299 \tabularnewline
180 & 0.00451027302554964 & 0.00902054605109927 & 0.99548972697445 \tabularnewline
181 & 0.00350849953057794 & 0.00701699906115588 & 0.996491500469422 \tabularnewline
182 & 0.0275600779864226 & 0.0551201559728453 & 0.972439922013577 \tabularnewline
183 & 0.0244928029101191 & 0.0489856058202383 & 0.975507197089881 \tabularnewline
184 & 0.0308406156426506 & 0.0616812312853011 & 0.969159384357349 \tabularnewline
185 & 0.025660095298866 & 0.0513201905977319 & 0.974339904701134 \tabularnewline
186 & 0.0209850431293728 & 0.0419700862587456 & 0.979014956870627 \tabularnewline
187 & 0.017700482762406 & 0.035400965524812 & 0.982299517237594 \tabularnewline
188 & 0.0155464338407521 & 0.0310928676815042 & 0.984453566159248 \tabularnewline
189 & 0.0126041268945278 & 0.0252082537890557 & 0.987395873105472 \tabularnewline
190 & 0.0178486766765946 & 0.0356973533531891 & 0.982151323323405 \tabularnewline
191 & 0.0163610462607616 & 0.0327220925215233 & 0.983638953739238 \tabularnewline
192 & 0.0133225813898813 & 0.0266451627797626 & 0.986677418610119 \tabularnewline
193 & 0.0105817942140974 & 0.0211635884281949 & 0.989418205785903 \tabularnewline
194 & 0.0160191438109156 & 0.0320382876218312 & 0.983980856189084 \tabularnewline
195 & 0.0132084138601352 & 0.0264168277202704 & 0.986791586139865 \tabularnewline
196 & 0.0122595458084658 & 0.0245190916169317 & 0.987740454191534 \tabularnewline
197 & 0.012019438682686 & 0.0240388773653719 & 0.987980561317314 \tabularnewline
198 & 0.0100451366970222 & 0.0200902733940443 & 0.989954863302978 \tabularnewline
199 & 0.00992672182556562 & 0.0198534436511312 & 0.990073278174434 \tabularnewline
200 & 0.0122626135299298 & 0.0245252270598596 & 0.98773738647007 \tabularnewline
201 & 0.0147089344703583 & 0.0294178689407165 & 0.985291065529642 \tabularnewline
202 & 0.0116918816805837 & 0.0233837633611673 & 0.988308118319416 \tabularnewline
203 & 0.010158255430405 & 0.02031651086081 & 0.989841744569595 \tabularnewline
204 & 0.00818288087808555 & 0.0163657617561711 & 0.991817119121914 \tabularnewline
205 & 0.00955555963254886 & 0.0191111192650977 & 0.990444440367451 \tabularnewline
206 & 0.00855842005821217 & 0.0171168401164243 & 0.991441579941788 \tabularnewline
207 & 0.0112261900818946 & 0.0224523801637892 & 0.988773809918105 \tabularnewline
208 & 0.0255247968361535 & 0.051049593672307 & 0.974475203163847 \tabularnewline
209 & 0.0208421362086131 & 0.0416842724172262 & 0.979157863791387 \tabularnewline
210 & 0.0326169724430504 & 0.0652339448861008 & 0.96738302755695 \tabularnewline
211 & 0.0274509623380589 & 0.0549019246761179 & 0.972549037661941 \tabularnewline
212 & 0.0252540497854457 & 0.0505080995708915 & 0.974745950214554 \tabularnewline
213 & 0.0270896554869254 & 0.0541793109738508 & 0.972910344513075 \tabularnewline
214 & 0.0217157530352977 & 0.0434315060705955 & 0.978284246964702 \tabularnewline
215 & 0.0185801398321027 & 0.0371602796642055 & 0.981419860167897 \tabularnewline
216 & 0.0154426394915636 & 0.0308852789831273 & 0.984557360508436 \tabularnewline
217 & 0.0145419798228546 & 0.0290839596457093 & 0.985458020177145 \tabularnewline
218 & 0.0113822719793881 & 0.0227645439587761 & 0.988617728020612 \tabularnewline
219 & 0.00883245461652167 & 0.0176649092330433 & 0.991167545383478 \tabularnewline
220 & 0.00694592460510897 & 0.0138918492102179 & 0.993054075394891 \tabularnewline
221 & 0.011079604271371 & 0.022159208542742 & 0.988920395728629 \tabularnewline
222 & 0.00860517707816118 & 0.0172103541563224 & 0.991394822921839 \tabularnewline
223 & 0.00744668633657188 & 0.0148933726731438 & 0.992553313663428 \tabularnewline
224 & 0.00633980485973176 & 0.0126796097194635 & 0.993660195140268 \tabularnewline
225 & 0.00494018218708807 & 0.00988036437417614 & 0.995059817812912 \tabularnewline
226 & 0.00629458031798458 & 0.0125891606359692 & 0.993705419682015 \tabularnewline
227 & 0.0142548819922059 & 0.0285097639844119 & 0.985745118007794 \tabularnewline
228 & 0.0786457404813491 & 0.157291480962698 & 0.921354259518651 \tabularnewline
229 & 0.0710467291494875 & 0.142093458298975 & 0.928953270850513 \tabularnewline
230 & 0.0584234427904188 & 0.116846885580838 & 0.941576557209581 \tabularnewline
231 & 0.0590908447126215 & 0.118181689425243 & 0.940909155287379 \tabularnewline
232 & 0.242418527271744 & 0.484837054543487 & 0.757581472728256 \tabularnewline
233 & 0.223150129350764 & 0.446300258701529 & 0.776849870649236 \tabularnewline
234 & 0.203024330232496 & 0.406048660464991 & 0.796975669767504 \tabularnewline
235 & 0.180125768215002 & 0.360251536430005 & 0.819874231784998 \tabularnewline
236 & 0.15365027512011 & 0.307300550240221 & 0.84634972487989 \tabularnewline
237 & 0.184216521362063 & 0.368433042724126 & 0.815783478637937 \tabularnewline
238 & 0.236459001939109 & 0.472918003878218 & 0.763540998060891 \tabularnewline
239 & 0.298129055491299 & 0.596258110982598 & 0.701870944508701 \tabularnewline
240 & 0.258940352962524 & 0.517880705925048 & 0.741059647037476 \tabularnewline
241 & 0.243732362754845 & 0.48746472550969 & 0.756267637245155 \tabularnewline
242 & 0.278933514064243 & 0.557867028128486 & 0.721066485935757 \tabularnewline
243 & 0.267274511024404 & 0.534549022048809 & 0.732725488975596 \tabularnewline
244 & 0.242977296592656 & 0.485954593185313 & 0.757022703407344 \tabularnewline
245 & 0.214090076804756 & 0.428180153609512 & 0.785909923195244 \tabularnewline
246 & 0.183488832070475 & 0.366977664140951 & 0.816511167929525 \tabularnewline
247 & 0.18215975492051 & 0.36431950984102 & 0.81784024507949 \tabularnewline
248 & 0.278669368608705 & 0.55733873721741 & 0.721330631391295 \tabularnewline
249 & 0.262232421822134 & 0.524464843644269 & 0.737767578177866 \tabularnewline
250 & 0.222656632817524 & 0.445313265635047 & 0.777343367182476 \tabularnewline
251 & 0.189286491802872 & 0.378572983605743 & 0.810713508197128 \tabularnewline
252 & 0.212337552441341 & 0.424675104882682 & 0.787662447558659 \tabularnewline
253 & 0.19409584784521 & 0.38819169569042 & 0.80590415215479 \tabularnewline
254 & 0.258985606869741 & 0.517971213739483 & 0.741014393130259 \tabularnewline
255 & 0.248278849996825 & 0.49655769999365 & 0.751721150003175 \tabularnewline
256 & 0.500867584647251 & 0.998264830705499 & 0.499132415352749 \tabularnewline
257 & 0.453196418096376 & 0.906392836192752 & 0.546803581903624 \tabularnewline
258 & 0.461761174397253 & 0.923522348794506 & 0.538238825602747 \tabularnewline
259 & 0.44069371400784 & 0.88138742801568 & 0.55930628599216 \tabularnewline
260 & 0.463087071786501 & 0.926174143573002 & 0.536912928213499 \tabularnewline
261 & 0.403509463059615 & 0.807018926119231 & 0.596490536940385 \tabularnewline
262 & 0.354189024496567 & 0.708378048993134 & 0.645810975503433 \tabularnewline
263 & 0.316609907144878 & 0.633219814289757 & 0.683390092855122 \tabularnewline
264 & 0.259566944219752 & 0.519133888439505 & 0.740433055780248 \tabularnewline
265 & 0.257080674000104 & 0.514161348000208 & 0.742919325999896 \tabularnewline
266 & 0.368586064858861 & 0.737172129717721 & 0.631413935141139 \tabularnewline
267 & 0.613750884771853 & 0.772498230456294 & 0.386249115228147 \tabularnewline
268 & 0.552043750471305 & 0.895912499057391 & 0.447956249528695 \tabularnewline
269 & 0.503051090380994 & 0.993897819238012 & 0.496948909619006 \tabularnewline
270 & 0.513661354451781 & 0.972677291096438 & 0.486338645548219 \tabularnewline
271 & 0.441941819414828 & 0.883883638829655 & 0.558058180585172 \tabularnewline
272 & 0.418639515243928 & 0.837279030487856 & 0.581360484756072 \tabularnewline
273 & 0.364864530929152 & 0.729729061858304 & 0.635135469070848 \tabularnewline
274 & 0.288946915103503 & 0.577893830207006 & 0.711053084896497 \tabularnewline
275 & 0.425595101421127 & 0.851190202842253 & 0.574404898578873 \tabularnewline
276 & 0.376777275592881 & 0.753554551185763 & 0.623222724407119 \tabularnewline
277 & 0.266605613017507 & 0.533211226035014 & 0.733394386982493 \tabularnewline
278 & 0.17109230607347 & 0.34218461214694 & 0.82890769392653 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154801&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]10[/C][C]0.814086261347692[/C][C]0.371827477304615[/C][C]0.185913738652308[/C][/ROW]
[ROW][C]11[/C][C]0.761229325523221[/C][C]0.477541348953557[/C][C]0.238770674476779[/C][/ROW]
[ROW][C]12[/C][C]0.784144665799993[/C][C]0.431710668400014[/C][C]0.215855334200007[/C][/ROW]
[ROW][C]13[/C][C]0.719161450846133[/C][C]0.561677098307734[/C][C]0.280838549153867[/C][/ROW]
[ROW][C]14[/C][C]0.712411879221667[/C][C]0.575176241556666[/C][C]0.287588120778333[/C][/ROW]
[ROW][C]15[/C][C]0.669044511839593[/C][C]0.661910976320815[/C][C]0.330955488160407[/C][/ROW]
[ROW][C]16[/C][C]0.612600387080061[/C][C]0.774799225839878[/C][C]0.387399612919939[/C][/ROW]
[ROW][C]17[/C][C]0.524822802404636[/C][C]0.950354395190728[/C][C]0.475177197595364[/C][/ROW]
[ROW][C]18[/C][C]0.855741154814498[/C][C]0.288517690371004[/C][C]0.144258845185502[/C][/ROW]
[ROW][C]19[/C][C]0.849998819513108[/C][C]0.300002360973784[/C][C]0.150001180486892[/C][/ROW]
[ROW][C]20[/C][C]0.802002810476474[/C][C]0.395994379047051[/C][C]0.197997189523526[/C][/ROW]
[ROW][C]21[/C][C]0.745897869930955[/C][C]0.50820426013809[/C][C]0.254102130069045[/C][/ROW]
[ROW][C]22[/C][C]0.684099119237835[/C][C]0.63180176152433[/C][C]0.315900880762165[/C][/ROW]
[ROW][C]23[/C][C]0.703792204183172[/C][C]0.592415591633656[/C][C]0.296207795816828[/C][/ROW]
[ROW][C]24[/C][C]0.640615637606271[/C][C]0.718768724787459[/C][C]0.359384362393729[/C][/ROW]
[ROW][C]25[/C][C]0.577482789177759[/C][C]0.845034421644483[/C][C]0.422517210822241[/C][/ROW]
[ROW][C]26[/C][C]0.510840199927048[/C][C]0.978319600145904[/C][C]0.489159800072952[/C][/ROW]
[ROW][C]27[/C][C]0.447186101972804[/C][C]0.894372203945608[/C][C]0.552813898027196[/C][/ROW]
[ROW][C]28[/C][C]0.430402656037297[/C][C]0.860805312074593[/C][C]0.569597343962703[/C][/ROW]
[ROW][C]29[/C][C]0.369874070903398[/C][C]0.739748141806795[/C][C]0.630125929096602[/C][/ROW]
[ROW][C]30[/C][C]0.356279887151219[/C][C]0.712559774302437[/C][C]0.643720112848781[/C][/ROW]
[ROW][C]31[/C][C]0.300856874206312[/C][C]0.601713748412623[/C][C]0.699143125793688[/C][/ROW]
[ROW][C]32[/C][C]0.285203192192063[/C][C]0.570406384384125[/C][C]0.714796807807937[/C][/ROW]
[ROW][C]33[/C][C]0.251839765907608[/C][C]0.503679531815217[/C][C]0.748160234092392[/C][/ROW]
[ROW][C]34[/C][C]0.207049743900598[/C][C]0.414099487801195[/C][C]0.792950256099402[/C][/ROW]
[ROW][C]35[/C][C]0.205931838932885[/C][C]0.41186367786577[/C][C]0.794068161067115[/C][/ROW]
[ROW][C]36[/C][C]0.294191589926572[/C][C]0.588383179853145[/C][C]0.705808410073428[/C][/ROW]
[ROW][C]37[/C][C]0.381722839826489[/C][C]0.763445679652978[/C][C]0.618277160173511[/C][/ROW]
[ROW][C]38[/C][C]0.383989808759572[/C][C]0.767979617519143[/C][C]0.616010191240428[/C][/ROW]
[ROW][C]39[/C][C]0.412444714595408[/C][C]0.824889429190815[/C][C]0.587555285404592[/C][/ROW]
[ROW][C]40[/C][C]0.391693744234266[/C][C]0.783387488468533[/C][C]0.608306255765734[/C][/ROW]
[ROW][C]41[/C][C]0.357991618691332[/C][C]0.715983237382664[/C][C]0.642008381308668[/C][/ROW]
[ROW][C]42[/C][C]0.344927714219756[/C][C]0.689855428439513[/C][C]0.655072285780244[/C][/ROW]
[ROW][C]43[/C][C]0.357907768525075[/C][C]0.715815537050149[/C][C]0.642092231474925[/C][/ROW]
[ROW][C]44[/C][C]0.317195445568794[/C][C]0.634390891137589[/C][C]0.682804554431206[/C][/ROW]
[ROW][C]45[/C][C]0.281112065180272[/C][C]0.562224130360544[/C][C]0.718887934819728[/C][/ROW]
[ROW][C]46[/C][C]0.516421228254306[/C][C]0.967157543491388[/C][C]0.483578771745694[/C][/ROW]
[ROW][C]47[/C][C]0.567873751768145[/C][C]0.86425249646371[/C][C]0.432126248231855[/C][/ROW]
[ROW][C]48[/C][C]0.52140139380185[/C][C]0.9571972123963[/C][C]0.47859860619815[/C][/ROW]
[ROW][C]49[/C][C]0.477155337160497[/C][C]0.954310674320994[/C][C]0.522844662839503[/C][/ROW]
[ROW][C]50[/C][C]0.480679222342282[/C][C]0.961358444684563[/C][C]0.519320777657718[/C][/ROW]
[ROW][C]51[/C][C]0.438573970753703[/C][C]0.877147941507406[/C][C]0.561426029246297[/C][/ROW]
[ROW][C]52[/C][C]0.393324924345817[/C][C]0.786649848691633[/C][C]0.606675075654183[/C][/ROW]
[ROW][C]53[/C][C]0.446961455047448[/C][C]0.893922910094896[/C][C]0.553038544952552[/C][/ROW]
[ROW][C]54[/C][C]0.404471451454389[/C][C]0.808942902908778[/C][C]0.595528548545611[/C][/ROW]
[ROW][C]55[/C][C]0.406474981449885[/C][C]0.81294996289977[/C][C]0.593525018550115[/C][/ROW]
[ROW][C]56[/C][C]0.390812560784675[/C][C]0.781625121569349[/C][C]0.609187439215325[/C][/ROW]
[ROW][C]57[/C][C]0.34951666763594[/C][C]0.69903333527188[/C][C]0.65048333236406[/C][/ROW]
[ROW][C]58[/C][C]0.326711949330067[/C][C]0.653423898660134[/C][C]0.673288050669933[/C][/ROW]
[ROW][C]59[/C][C]0.287653471802319[/C][C]0.575306943604638[/C][C]0.712346528197681[/C][/ROW]
[ROW][C]60[/C][C]0.289704324454[/C][C]0.579408648907999[/C][C]0.710295675546[/C][/ROW]
[ROW][C]61[/C][C]0.260293166371497[/C][C]0.520586332742993[/C][C]0.739706833628503[/C][/ROW]
[ROW][C]62[/C][C]0.22668075326602[/C][C]0.45336150653204[/C][C]0.77331924673398[/C][/ROW]
[ROW][C]63[/C][C]0.195968930174227[/C][C]0.391937860348455[/C][C]0.804031069825773[/C][/ROW]
[ROW][C]64[/C][C]0.169447926814637[/C][C]0.338895853629274[/C][C]0.830552073185363[/C][/ROW]
[ROW][C]65[/C][C]0.14635081080373[/C][C]0.29270162160746[/C][C]0.85364918919627[/C][/ROW]
[ROW][C]66[/C][C]0.134138661831731[/C][C]0.268277323663462[/C][C]0.865861338168269[/C][/ROW]
[ROW][C]67[/C][C]0.127503792936276[/C][C]0.255007585872553[/C][C]0.872496207063724[/C][/ROW]
[ROW][C]68[/C][C]0.218035433171161[/C][C]0.436070866342323[/C][C]0.781964566828839[/C][/ROW]
[ROW][C]69[/C][C]0.34218853450653[/C][C]0.68437706901306[/C][C]0.65781146549347[/C][/ROW]
[ROW][C]70[/C][C]0.30623592746367[/C][C]0.612471854927341[/C][C]0.69376407253633[/C][/ROW]
[ROW][C]71[/C][C]0.390194196294304[/C][C]0.780388392588609[/C][C]0.609805803705696[/C][/ROW]
[ROW][C]72[/C][C]0.356334238230656[/C][C]0.712668476461313[/C][C]0.643665761769344[/C][/ROW]
[ROW][C]73[/C][C]0.338884780293372[/C][C]0.677769560586743[/C][C]0.661115219706628[/C][/ROW]
[ROW][C]74[/C][C]0.311393237631701[/C][C]0.622786475263401[/C][C]0.688606762368299[/C][/ROW]
[ROW][C]75[/C][C]0.280709103781971[/C][C]0.561418207563943[/C][C]0.719290896218029[/C][/ROW]
[ROW][C]76[/C][C]0.335687511539227[/C][C]0.671375023078454[/C][C]0.664312488460773[/C][/ROW]
[ROW][C]77[/C][C]0.303569758925074[/C][C]0.607139517850148[/C][C]0.696430241074926[/C][/ROW]
[ROW][C]78[/C][C]0.281518155545273[/C][C]0.563036311090546[/C][C]0.718481844454727[/C][/ROW]
[ROW][C]79[/C][C]0.285126826692255[/C][C]0.570253653384511[/C][C]0.714873173307745[/C][/ROW]
[ROW][C]80[/C][C]0.257586401542853[/C][C]0.515172803085707[/C][C]0.742413598457147[/C][/ROW]
[ROW][C]81[/C][C]0.231165044081089[/C][C]0.462330088162178[/C][C]0.768834955918911[/C][/ROW]
[ROW][C]82[/C][C]0.203898145227964[/C][C]0.407796290455928[/C][C]0.796101854772036[/C][/ROW]
[ROW][C]83[/C][C]0.184079681084161[/C][C]0.368159362168323[/C][C]0.815920318915839[/C][/ROW]
[ROW][C]84[/C][C]0.159801219158883[/C][C]0.319602438317767[/C][C]0.840198780841117[/C][/ROW]
[ROW][C]85[/C][C]0.156752144892512[/C][C]0.313504289785024[/C][C]0.843247855107488[/C][/ROW]
[ROW][C]86[/C][C]0.134875695592181[/C][C]0.269751391184362[/C][C]0.865124304407819[/C][/ROW]
[ROW][C]87[/C][C]0.116908595914121[/C][C]0.233817191828243[/C][C]0.883091404085879[/C][/ROW]
[ROW][C]88[/C][C]0.103935723614244[/C][C]0.207871447228488[/C][C]0.896064276385756[/C][/ROW]
[ROW][C]89[/C][C]0.087982579318429[/C][C]0.175965158636858[/C][C]0.912017420681571[/C][/ROW]
[ROW][C]90[/C][C]0.0835260265340989[/C][C]0.167052053068198[/C][C]0.916473973465901[/C][/ROW]
[ROW][C]91[/C][C]0.0715942846745892[/C][C]0.143188569349178[/C][C]0.928405715325411[/C][/ROW]
[ROW][C]92[/C][C]0.0609637923475346[/C][C]0.121927584695069[/C][C]0.939036207652465[/C][/ROW]
[ROW][C]93[/C][C]0.0517020187507678[/C][C]0.103404037501536[/C][C]0.948297981249232[/C][/ROW]
[ROW][C]94[/C][C]0.0532408909662381[/C][C]0.106481781932476[/C][C]0.946759109033762[/C][/ROW]
[ROW][C]95[/C][C]0.046734753024247[/C][C]0.0934695060484941[/C][C]0.953265246975753[/C][/ROW]
[ROW][C]96[/C][C]0.0385127070220537[/C][C]0.0770254140441075[/C][C]0.961487292977946[/C][/ROW]
[ROW][C]97[/C][C]0.0417362682329822[/C][C]0.0834725364659644[/C][C]0.958263731767018[/C][/ROW]
[ROW][C]98[/C][C]0.0341719551985903[/C][C]0.0683439103971806[/C][C]0.96582804480141[/C][/ROW]
[ROW][C]99[/C][C]0.0277502789276271[/C][C]0.0555005578552542[/C][C]0.972249721072373[/C][/ROW]
[ROW][C]100[/C][C]0.0248782951046446[/C][C]0.0497565902092892[/C][C]0.975121704895355[/C][/ROW]
[ROW][C]101[/C][C]0.0214931398045809[/C][C]0.0429862796091617[/C][C]0.978506860195419[/C][/ROW]
[ROW][C]102[/C][C]0.0254158726861098[/C][C]0.0508317453722196[/C][C]0.97458412731389[/C][/ROW]
[ROW][C]103[/C][C]0.021323147560171[/C][C]0.0426462951203421[/C][C]0.978676852439829[/C][/ROW]
[ROW][C]104[/C][C]0.0188440854235398[/C][C]0.0376881708470795[/C][C]0.98115591457646[/C][/ROW]
[ROW][C]105[/C][C]0.0239094666217534[/C][C]0.0478189332435068[/C][C]0.976090533378247[/C][/ROW]
[ROW][C]106[/C][C]0.0204778942219995[/C][C]0.040955788443999[/C][C]0.979522105778[/C][/ROW]
[ROW][C]107[/C][C]0.0163938922168664[/C][C]0.0327877844337327[/C][C]0.983606107783134[/C][/ROW]
[ROW][C]108[/C][C]0.0149252124835698[/C][C]0.0298504249671396[/C][C]0.98507478751643[/C][/ROW]
[ROW][C]109[/C][C]0.0127397008788019[/C][C]0.0254794017576038[/C][C]0.987260299121198[/C][/ROW]
[ROW][C]110[/C][C]0.0105051719089917[/C][C]0.0210103438179834[/C][C]0.989494828091008[/C][/ROW]
[ROW][C]111[/C][C]0.00826461365069812[/C][C]0.0165292273013962[/C][C]0.991735386349302[/C][/ROW]
[ROW][C]112[/C][C]0.00971527581198861[/C][C]0.0194305516239772[/C][C]0.990284724188011[/C][/ROW]
[ROW][C]113[/C][C]0.0136348766829355[/C][C]0.0272697533658709[/C][C]0.986365123317064[/C][/ROW]
[ROW][C]114[/C][C]0.0131765717509187[/C][C]0.0263531435018375[/C][C]0.986823428249081[/C][/ROW]
[ROW][C]115[/C][C]0.0139943263867562[/C][C]0.0279886527735124[/C][C]0.986005673613244[/C][/ROW]
[ROW][C]116[/C][C]0.0117348412744818[/C][C]0.0234696825489635[/C][C]0.988265158725518[/C][/ROW]
[ROW][C]117[/C][C]0.0116259487419371[/C][C]0.0232518974838743[/C][C]0.988374051258063[/C][/ROW]
[ROW][C]118[/C][C]0.00922112841125079[/C][C]0.0184422568225016[/C][C]0.990778871588749[/C][/ROW]
[ROW][C]119[/C][C]0.00861133359943518[/C][C]0.0172226671988704[/C][C]0.991388666400565[/C][/ROW]
[ROW][C]120[/C][C]0.00692821844190986[/C][C]0.0138564368838197[/C][C]0.99307178155809[/C][/ROW]
[ROW][C]121[/C][C]0.0099963973002054[/C][C]0.0199927946004108[/C][C]0.990003602699795[/C][/ROW]
[ROW][C]122[/C][C]0.00850808714494546[/C][C]0.0170161742898909[/C][C]0.991491912855055[/C][/ROW]
[ROW][C]123[/C][C]0.00758308613232811[/C][C]0.0151661722646562[/C][C]0.992416913867672[/C][/ROW]
[ROW][C]124[/C][C]0.00632385276201919[/C][C]0.0126477055240384[/C][C]0.993676147237981[/C][/ROW]
[ROW][C]125[/C][C]0.00501305548590186[/C][C]0.0100261109718037[/C][C]0.994986944514098[/C][/ROW]
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[ROW][C]271[/C][C]0.441941819414828[/C][C]0.883883638829655[/C][C]0.558058180585172[/C][/ROW]
[ROW][C]272[/C][C]0.418639515243928[/C][C]0.837279030487856[/C][C]0.581360484756072[/C][/ROW]
[ROW][C]273[/C][C]0.364864530929152[/C][C]0.729729061858304[/C][C]0.635135469070848[/C][/ROW]
[ROW][C]274[/C][C]0.288946915103503[/C][C]0.577893830207006[/C][C]0.711053084896497[/C][/ROW]
[ROW][C]275[/C][C]0.425595101421127[/C][C]0.851190202842253[/C][C]0.574404898578873[/C][/ROW]
[ROW][C]276[/C][C]0.376777275592881[/C][C]0.753554551185763[/C][C]0.623222724407119[/C][/ROW]
[ROW][C]277[/C][C]0.266605613017507[/C][C]0.533211226035014[/C][C]0.733394386982493[/C][/ROW]
[ROW][C]278[/C][C]0.17109230607347[/C][C]0.34218461214694[/C][C]0.82890769392653[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154801&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154801&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.8140862613476920.3718274773046150.185913738652308
110.7612293255232210.4775413489535570.238770674476779
120.7841446657999930.4317106684000140.215855334200007
130.7191614508461330.5616770983077340.280838549153867
140.7124118792216670.5751762415566660.287588120778333
150.6690445118395930.6619109763208150.330955488160407
160.6126003870800610.7747992258398780.387399612919939
170.5248228024046360.9503543951907280.475177197595364
180.8557411548144980.2885176903710040.144258845185502
190.8499988195131080.3000023609737840.150001180486892
200.8020028104764740.3959943790470510.197997189523526
210.7458978699309550.508204260138090.254102130069045
220.6840991192378350.631801761524330.315900880762165
230.7037922041831720.5924155916336560.296207795816828
240.6406156376062710.7187687247874590.359384362393729
250.5774827891777590.8450344216444830.422517210822241
260.5108401999270480.9783196001459040.489159800072952
270.4471861019728040.8943722039456080.552813898027196
280.4304026560372970.8608053120745930.569597343962703
290.3698740709033980.7397481418067950.630125929096602
300.3562798871512190.7125597743024370.643720112848781
310.3008568742063120.6017137484126230.699143125793688
320.2852031921920630.5704063843841250.714796807807937
330.2518397659076080.5036795318152170.748160234092392
340.2070497439005980.4140994878011950.792950256099402
350.2059318389328850.411863677865770.794068161067115
360.2941915899265720.5883831798531450.705808410073428
370.3817228398264890.7634456796529780.618277160173511
380.3839898087595720.7679796175191430.616010191240428
390.4124447145954080.8248894291908150.587555285404592
400.3916937442342660.7833874884685330.608306255765734
410.3579916186913320.7159832373826640.642008381308668
420.3449277142197560.6898554284395130.655072285780244
430.3579077685250750.7158155370501490.642092231474925
440.3171954455687940.6343908911375890.682804554431206
450.2811120651802720.5622241303605440.718887934819728
460.5164212282543060.9671575434913880.483578771745694
470.5678737517681450.864252496463710.432126248231855
480.521401393801850.95719721239630.47859860619815
490.4771553371604970.9543106743209940.522844662839503
500.4806792223422820.9613584446845630.519320777657718
510.4385739707537030.8771479415074060.561426029246297
520.3933249243458170.7866498486916330.606675075654183
530.4469614550474480.8939229100948960.553038544952552
540.4044714514543890.8089429029087780.595528548545611
550.4064749814498850.812949962899770.593525018550115
560.3908125607846750.7816251215693490.609187439215325
570.349516667635940.699033335271880.65048333236406
580.3267119493300670.6534238986601340.673288050669933
590.2876534718023190.5753069436046380.712346528197681
600.2897043244540.5794086489079990.710295675546
610.2602931663714970.5205863327429930.739706833628503
620.226680753266020.453361506532040.77331924673398
630.1959689301742270.3919378603484550.804031069825773
640.1694479268146370.3388958536292740.830552073185363
650.146350810803730.292701621607460.85364918919627
660.1341386618317310.2682773236634620.865861338168269
670.1275037929362760.2550075858725530.872496207063724
680.2180354331711610.4360708663423230.781964566828839
690.342188534506530.684377069013060.65781146549347
700.306235927463670.6124718549273410.69376407253633
710.3901941962943040.7803883925886090.609805803705696
720.3563342382306560.7126684764613130.643665761769344
730.3388847802933720.6777695605867430.661115219706628
740.3113932376317010.6227864752634010.688606762368299
750.2807091037819710.5614182075639430.719290896218029
760.3356875115392270.6713750230784540.664312488460773
770.3035697589250740.6071395178501480.696430241074926
780.2815181555452730.5630363110905460.718481844454727
790.2851268266922550.5702536533845110.714873173307745
800.2575864015428530.5151728030857070.742413598457147
810.2311650440810890.4623300881621780.768834955918911
820.2038981452279640.4077962904559280.796101854772036
830.1840796810841610.3681593621683230.815920318915839
840.1598012191588830.3196024383177670.840198780841117
850.1567521448925120.3135042897850240.843247855107488
860.1348756955921810.2697513911843620.865124304407819
870.1169085959141210.2338171918282430.883091404085879
880.1039357236142440.2078714472284880.896064276385756
890.0879825793184290.1759651586368580.912017420681571
900.08352602653409890.1670520530681980.916473973465901
910.07159428467458920.1431885693491780.928405715325411
920.06096379234753460.1219275846950690.939036207652465
930.05170201875076780.1034040375015360.948297981249232
940.05324089096623810.1064817819324760.946759109033762
950.0467347530242470.09346950604849410.953265246975753
960.03851270702205370.07702541404410750.961487292977946
970.04173626823298220.08347253646596440.958263731767018
980.03417195519859030.06834391039718060.96582804480141
990.02775027892762710.05550055785525420.972249721072373
1000.02487829510464460.04975659020928920.975121704895355
1010.02149313980458090.04298627960916170.978506860195419
1020.02541587268610980.05083174537221960.97458412731389
1030.0213231475601710.04264629512034210.978676852439829
1040.01884408542353980.03768817084707950.98115591457646
1050.02390946662175340.04781893324350680.976090533378247
1060.02047789422199950.0409557884439990.979522105778
1070.01639389221686640.03278778443373270.983606107783134
1080.01492521248356980.02985042496713960.98507478751643
1090.01273970087880190.02547940175760380.987260299121198
1100.01050517190899170.02101034381798340.989494828091008
1110.008264613650698120.01652922730139620.991735386349302
1120.009715275811988610.01943055162397720.990284724188011
1130.01363487668293550.02726975336587090.986365123317064
1140.01317657175091870.02635314350183750.986823428249081
1150.01399432638675620.02798865277351240.986005673613244
1160.01173484127448180.02346968254896350.988265158725518
1170.01162594874193710.02325189748387430.988374051258063
1180.009221128411250790.01844225682250160.990778871588749
1190.008611333599435180.01722266719887040.991388666400565
1200.006928218441909860.01385643688381970.99307178155809
1210.00999639730020540.01999279460041080.990003602699795
1220.008508087144945460.01701617428989090.991491912855055
1230.007583086132328110.01516617226465620.992416913867672
1240.006323852762019190.01264770552403840.993676147237981
1250.005013055485901860.01002611097180370.994986944514098
1260.004200402659141930.008400805318283860.995799597340858
1270.003470472969516520.006940945939033030.996529527030483
1280.005358242649316180.01071648529863240.994641757350684
1290.005686989990036470.01137397998007290.994313010009964
1300.01242702636511830.02485405273023660.987572973634882
1310.01378151505749970.02756303011499940.9862184849425
1320.01481808699730920.02963617399461840.985181913002691
1330.01464176515981880.02928353031963770.985358234840181
1340.01187164020185530.02374328040371070.988128359798145
1350.009855847538316460.01971169507663290.990144152461684
1360.007829474633713190.01565894926742640.992170525366287
1370.01043672218303350.02087344436606710.989563277816966
1380.009335755459675630.01867151091935130.990664244540324
1390.01073087542126360.02146175084252720.989269124578736
1400.01479957758111680.02959915516223370.985200422418883
1410.01373722145651140.02747444291302290.986262778543489
1420.01136873195900690.02273746391801380.988631268040993
1430.01139006616548880.02278013233097750.988609933834511
1440.02143703321449250.04287406642898510.978562966785507
1450.02303778816797050.0460755763359410.976962211832029
1460.02610276356587020.05220552713174050.97389723643413
1470.02257786365748860.04515572731497710.977422136342511
1480.01837780091774150.0367556018354830.981622199082259
1490.02709098540291320.05418197080582630.972909014597087
1500.02738604207767880.05477208415535760.972613957922321
1510.02749566038506880.05499132077013750.972504339614931
1520.05087320033130.10174640066260.9491267996687
1530.04523353040822960.09046706081645910.95476646959177
1540.05664353360257410.1132870672051480.943356466397426
1550.04976128128593770.09952256257187530.950238718714062
1560.04276904270758760.08553808541517510.957230957292412
1570.04065705042095860.08131410084191720.959342949579041
1580.03418247708361460.06836495416722920.965817522916385
1590.02887217028877610.05774434057755230.971127829711224
1600.0246136352485870.04922727049717410.975386364751413
1610.0206410007401240.04128200148024810.979358999259876
1620.01812052324281720.03624104648563440.981879476757183
1630.01673820747661930.03347641495323860.983261792523381
1640.01347007455917910.02694014911835830.986529925440821
1650.01678351478001290.03356702956002580.983216485219987
1660.01663275318425060.03326550636850120.983367246815749
1670.01705087258657190.03410174517314370.982949127413428
1680.01712043348233310.03424086696466620.982879566517667
1690.01402725267470930.02805450534941860.985972747325291
1700.0133266804177280.0266533608354560.986673319582272
1710.01315856787937450.0263171357587490.986841432120625
1720.01581471300029530.03162942600059060.984185286999705
1730.01362034075457110.02724068150914210.986379659245429
1740.01088081640971120.02176163281942230.989119183590289
1750.008641516464229070.01728303292845810.991358483535771
1760.007006756854311790.01401351370862360.992993243145688
1770.006047189478334180.01209437895666840.993952810521666
1780.005039130401716680.01007826080343340.994960869598283
1790.004017473887700620.008034947775401230.995982526112299
1800.004510273025549640.009020546051099270.99548972697445
1810.003508499530577940.007016999061155880.996491500469422
1820.02756007798642260.05512015597284530.972439922013577
1830.02449280291011910.04898560582023830.975507197089881
1840.03084061564265060.06168123128530110.969159384357349
1850.0256600952988660.05132019059773190.974339904701134
1860.02098504312937280.04197008625874560.979014956870627
1870.0177004827624060.0354009655248120.982299517237594
1880.01554643384075210.03109286768150420.984453566159248
1890.01260412689452780.02520825378905570.987395873105472
1900.01784867667659460.03569735335318910.982151323323405
1910.01636104626076160.03272209252152330.983638953739238
1920.01332258138988130.02664516277976260.986677418610119
1930.01058179421409740.02116358842819490.989418205785903
1940.01601914381091560.03203828762183120.983980856189084
1950.01320841386013520.02641682772027040.986791586139865
1960.01225954580846580.02451909161693170.987740454191534
1970.0120194386826860.02403887736537190.987980561317314
1980.01004513669702220.02009027339404430.989954863302978
1990.009926721825565620.01985344365113120.990073278174434
2000.01226261352992980.02452522705985960.98773738647007
2010.01470893447035830.02941786894071650.985291065529642
2020.01169188168058370.02338376336116730.988308118319416
2030.0101582554304050.020316510860810.989841744569595
2040.008182880878085550.01636576175617110.991817119121914
2050.009555559632548860.01911111926509770.990444440367451
2060.008558420058212170.01711684011642430.991441579941788
2070.01122619008189460.02245238016378920.988773809918105
2080.02552479683615350.0510495936723070.974475203163847
2090.02084213620861310.04168427241722620.979157863791387
2100.03261697244305040.06523394488610080.96738302755695
2110.02745096233805890.05490192467611790.972549037661941
2120.02525404978544570.05050809957089150.974745950214554
2130.02708965548692540.05417931097385080.972910344513075
2140.02171575303529770.04343150607059550.978284246964702
2150.01858013983210270.03716027966420550.981419860167897
2160.01544263949156360.03088527898312730.984557360508436
2170.01454197982285460.02908395964570930.985458020177145
2180.01138227197938810.02276454395877610.988617728020612
2190.008832454616521670.01766490923304330.991167545383478
2200.006945924605108970.01389184921021790.993054075394891
2210.0110796042713710.0221592085427420.988920395728629
2220.008605177078161180.01721035415632240.991394822921839
2230.007446686336571880.01489337267314380.992553313663428
2240.006339804859731760.01267960971946350.993660195140268
2250.004940182187088070.009880364374176140.995059817812912
2260.006294580317984580.01258916063596920.993705419682015
2270.01425488199220590.02850976398441190.985745118007794
2280.07864574048134910.1572914809626980.921354259518651
2290.07104672914948750.1420934582989750.928953270850513
2300.05842344279041880.1168468855808380.941576557209581
2310.05909084471262150.1181816894252430.940909155287379
2320.2424185272717440.4848370545434870.757581472728256
2330.2231501293507640.4463002587015290.776849870649236
2340.2030243302324960.4060486604649910.796975669767504
2350.1801257682150020.3602515364300050.819874231784998
2360.153650275120110.3073005502402210.84634972487989
2370.1842165213620630.3684330427241260.815783478637937
2380.2364590019391090.4729180038782180.763540998060891
2390.2981290554912990.5962581109825980.701870944508701
2400.2589403529625240.5178807059250480.741059647037476
2410.2437323627548450.487464725509690.756267637245155
2420.2789335140642430.5578670281284860.721066485935757
2430.2672745110244040.5345490220488090.732725488975596
2440.2429772965926560.4859545931853130.757022703407344
2450.2140900768047560.4281801536095120.785909923195244
2460.1834888320704750.3669776641409510.816511167929525
2470.182159754920510.364319509841020.81784024507949
2480.2786693686087050.557338737217410.721330631391295
2490.2622324218221340.5244648436442690.737767578177866
2500.2226566328175240.4453132656350470.777343367182476
2510.1892864918028720.3785729836057430.810713508197128
2520.2123375524413410.4246751048826820.787662447558659
2530.194095847845210.388191695690420.80590415215479
2540.2589856068697410.5179712137394830.741014393130259
2550.2482788499968250.496557699993650.751721150003175
2560.5008675846472510.9982648307054990.499132415352749
2570.4531964180963760.9063928361927520.546803581903624
2580.4617611743972530.9235223487945060.538238825602747
2590.440693714007840.881387428015680.55930628599216
2600.4630870717865010.9261741435730020.536912928213499
2610.4035094630596150.8070189261192310.596490536940385
2620.3541890244965670.7083780489931340.645810975503433
2630.3166099071448780.6332198142897570.683390092855122
2640.2595669442197520.5191338884395050.740433055780248
2650.2570806740001040.5141613480002080.742919325999896
2660.3685860648588610.7371721297177210.631413935141139
2670.6137508847718530.7724982304562940.386249115228147
2680.5520437504713050.8959124990573910.447956249528695
2690.5030510903809940.9938978192380120.496948909619006
2700.5136613544517810.9726772910964380.486338645548219
2710.4419418194148280.8838836388296550.558058180585172
2720.4186395152439280.8372790304878560.581360484756072
2730.3648645309291520.7297290618583040.635135469070848
2740.2889469151035030.5778938302070060.711053084896497
2750.4255951014211270.8511902028422530.574404898578873
2760.3767772755928810.7535545511857630.623222724407119
2770.2666056130175070.5332112260350140.733394386982493
2780.171092306073470.342184612146940.82890769392653






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level60.0223048327137546NOK
5% type I error level1070.397769516728625NOK
10% type I error level1310.486988847583643NOK

\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 & 6 & 0.0223048327137546 & NOK \tabularnewline
5% type I error level & 107 & 0.397769516728625 & NOK \tabularnewline
10% type I error level & 131 & 0.486988847583643 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154801&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]6[/C][C]0.0223048327137546[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]107[/C][C]0.397769516728625[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]131[/C][C]0.486988847583643[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154801&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154801&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level60.0223048327137546NOK
5% type I error level1070.397769516728625NOK
10% type I error level1310.486988847583643NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = no ;
Parameters (R input):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = no ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], 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,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
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, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
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,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
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,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
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,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
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,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
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')
}