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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 10 Dec 2012 08:16:58 -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/2012/Dec/10/t1355145465cjzsnfdoegblhzb.htm/, Retrieved Sat, 27 Apr 2024 02:42:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198137, Retrieved Sat, 27 Apr 2024 02:42:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100

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]
- R P     [Multiple Regression] [] [2012-12-10 13:16:58] [83e112fa93ceccb07add2c645a38d5d2] [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 time15 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 15 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198137&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]15 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198137&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198137&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 time15 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 13.6212781892182 + 0.629648559238144Pop[t] -0.386684460937783Gender[t] + 0.497661998445189Separate[t] + 0.226780695612353Learning[t] -0.0489027894673267Software[t] + 0.0568679220657549Happiness[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  13.6212781892182 +  0.629648559238144Pop[t] -0.386684460937783Gender[t] +  0.497661998445189Separate[t] +  0.226780695612353Learning[t] -0.0489027894673267Software[t] +  0.0568679220657549Happiness[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198137&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  13.6212781892182 +  0.629648559238144Pop[t] -0.386684460937783Gender[t] +  0.497661998445189Separate[t] +  0.226780695612353Learning[t] -0.0489027894673267Software[t] +  0.0568679220657549Happiness[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198137&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198137&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
Connected[t] = + 13.6212781892182 + 0.629648559238144Pop[t] -0.386684460937783Gender[t] + 0.497661998445189Separate[t] + 0.226780695612353Learning[t] -0.0489027894673267Software[t] + 0.0568679220657549Happiness[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)13.62127818921822.1012426.482500
Pop0.6296485592381440.4511551.39560.1639250.081963
Gender-0.3866844609377830.421539-0.91730.3597630.179882
Separate0.4976619984451890.0544369.142100
Learning0.2267806956123530.1065172.12910.0341190.017059
Software-0.04890278946732670.114544-0.42690.6697550.334878
Happiness0.05686792206575490.0860280.6610.5091270.254563

\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) & 13.6212781892182 & 2.101242 & 6.4825 & 0 & 0 \tabularnewline
Pop & 0.629648559238144 & 0.451155 & 1.3956 & 0.163925 & 0.081963 \tabularnewline
Gender & -0.386684460937783 & 0.421539 & -0.9173 & 0.359763 & 0.179882 \tabularnewline
Separate & 0.497661998445189 & 0.054436 & 9.1421 & 0 & 0 \tabularnewline
Learning & 0.226780695612353 & 0.106517 & 2.1291 & 0.034119 & 0.017059 \tabularnewline
Software & -0.0489027894673267 & 0.114544 & -0.4269 & 0.669755 & 0.334878 \tabularnewline
Happiness & 0.0568679220657549 & 0.086028 & 0.661 & 0.509127 & 0.254563 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198137&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]13.6212781892182[/C][C]2.101242[/C][C]6.4825[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Pop[/C][C]0.629648559238144[/C][C]0.451155[/C][C]1.3956[/C][C]0.163925[/C][C]0.081963[/C][/ROW]
[ROW][C]Gender[/C][C]-0.386684460937783[/C][C]0.421539[/C][C]-0.9173[/C][C]0.359763[/C][C]0.179882[/C][/ROW]
[ROW][C]Separate[/C][C]0.497661998445189[/C][C]0.054436[/C][C]9.1421[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Learning[/C][C]0.226780695612353[/C][C]0.106517[/C][C]2.1291[/C][C]0.034119[/C][C]0.017059[/C][/ROW]
[ROW][C]Software[/C][C]-0.0489027894673267[/C][C]0.114544[/C][C]-0.4269[/C][C]0.669755[/C][C]0.334878[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0568679220657549[/C][C]0.086028[/C][C]0.661[/C][C]0.509127[/C][C]0.254563[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198137&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198137&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)13.62127818921822.1012426.482500
Pop0.6296485592381440.4511551.39560.1639250.081963
Gender-0.3866844609377830.421539-0.91730.3597630.179882
Separate0.4976619984451890.0544369.142100
Learning0.2267806956123530.1065172.12910.0341190.017059
Software-0.04890278946732670.114544-0.42690.6697550.334878
Happiness0.05686792206575490.0860280.6610.5091270.254563






Multiple Linear Regression - Regression Statistics
Multiple R0.55273098024722
R-squared0.305511536525053
Adjusted R-squared0.290682601361887
F-TEST (value)20.6023920911003
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.41827068189702
Sum Squared Residuals3283.36542177541

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.55273098024722 \tabularnewline
R-squared & 0.305511536525053 \tabularnewline
Adjusted R-squared & 0.290682601361887 \tabularnewline
F-TEST (value) & 20.6023920911003 \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 & 3.41827068189702 \tabularnewline
Sum Squared Residuals & 3283.36542177541 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198137&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.55273098024722[/C][/ROW]
[ROW][C]R-squared[/C][C]0.305511536525053[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.290682601361887[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]20.6023920911003[/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]3.41827068189702[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3283.36542177541[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198137&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198137&T=3

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

Multiple Linear Regression - Regression Statistics
Multiple R0.55273098024722
R-squared0.305511536525053
Adjusted R-squared0.290682601361887
F-TEST (value)20.6023920911003
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.41827068189702
Sum Squared Residuals3283.36542177541






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14135.9328647067095.06713529329102
23933.90360928060525.09639071939478
33035.4832507504482-5.48325075044825
43134.464481459318-3.46448145931795
53435.7268164585403-1.72681645854029
63531.77918398789993.22081601210008
73933.80991489126675.19008510873326
83435.2932965221086-1.29329652210862
93634.72352732905151.27647267094851
103736.59000238840140.409997611598612
113833.78466661049944.21533338950061
123634.9068984100941.09310158990597
133835.27943357088522.7205664291148
143936.77584542714482.22415457285516
153336.4230888105742-3.42308881057421
163234.2848005666455-2.28480056664549
173633.8849441471352.11505585286504
183837.69093334219270.309066657807318
193937.50235543517581.49764456482418
203233.7409706470064-1.74097064700638
213234.7879557399882-2.78795573998819
223132.9589690382324-1.95896903823242
233937.24464609091571.75535390908426
243737.046035737327-0.0460357373270109
253934.41130372562234.58869627437772
264133.52077309869117.47922690130887
273635.71844668221440.281553317785613
283335.7909585205538-2.79095852055381
293334.1817647233858-1.18176472338582
303433.98522168377050.0147783162294705
313133.0165279529488-2.01652795294884
322733.2455397171668-6.2455397171668
333732.94442075833694.0555792416631
343436.1724127171666-2.17241271716657
353432.56503387569761.43496612430242
363233.5091468800519-1.50914688005187
372932.0179418497666-3.01794184976656
383634.11488779309891.8851122069011
392933.3979821495616-4.3979821495616
403534.55251891912670.447481080873255
413734.16859276481312.83140723518693
423433.78507125422690.214928745773132
433834.88806952199163.1119304780084
443534.04208960583630.957910394163715
453831.33769891886986.66230108113018
463733.81571355395143.18428644604859
473836.66527253336491.33472746663508
483334.501548815686-1.50154881568598
493636.8327133492106-0.832713349210597
503833.50348995052224.4965100494778
513236.6291370587429-4.62913705874286
523232.6628394546322-0.66283945463223
533233.4338547136112-1.43385471361117
543436.4505681599472-2.45056815994717
553232.655038076666-0.655038076665965
563735.01694406585541.98305593414455
573934.73629464389684.26370535610324
582934.679426721831-5.67942672183101
593735.71295350731691.28704649268312
603534.60662853456840.393371465431605
613031.0194549025246-1.0194549025246
623834.95237533863733.04762466136272
633434.8518114530785-0.851811453078522
643134.7155621964531-3.71556219645306
653433.18644072649540.813559273504559
663536.4526354739206-1.45263547392061
673635.30537284430320.694627155696772
683031.9143376081472-1.91433760814724
693936.75827593005272.24172406994727
703536.5590971781044-1.55909717810436
713834.83949424178863.1605057582114
723136.3222840359201-5.32228403592014
733437.523492526347-3.523492526347
743838.9055009841752-0.905500984175162
753431.4687413495212.53125865047904
763932.89166402586736.10833597413268
773736.23724577183080.762754228169245
783433.12160767183130.878392328168742
792832.8927831005962-4.89278310059617
803731.4687413495215.53125865047904
813336.0614351796592-3.06143517965917
823536.1724127171666-1.17241271716657
833734.3985364107772.601463589223
843234.501548815686-2.50154881568598
853333.2273783833643-0.227378383364339
863837.2475681521720.752431847827993
873334.6225587997653-1.62255879976525
882933.5703668808091-4.57036688080912
893333.5000406512474-0.500040651247426
903135.0280721488055-4.02807214880546
913633.65043920801952.34956079198051
923538.1630607109473-3.16306071094733
933231.40980611348180.590193886518231
942931.8947007970817-2.89470079708168
953935.82942421972183.17057578027821
963734.95758216461162.0424178353884
973533.27628117283171.72371882716833
983735.17984702690031.8201529730997
993235.7056793673691-3.70567936736911
1003835.69068098391822.30931901608176
1013735.4420722044841.55792779551596
1023636.9896950532798-0.989695053279759
1033231.67478959768960.325210402310386
1043337.2166395035243-4.21663950352428
1054033.04923756664686.95076243335318
1063835.46073733795432.5392626620457
1074137.55442117499473.44557882500527
1083635.32833636035250.671663639647469
1094337.7137742639515.28622573604904
1103034.679426721831-4.67942672183101
1113133.8564874561881-2.85648745618815
1123238.3250083518955-6.3250083518955
1133734.04071328451352.95928671548649
1143734.53231370970152.46768629029845
1153337.1060666097443-4.10606660974435
1163437.350580557081-3.35058055708098
1173334.4887815008407-1.48878150084071
1183835.61788279665562.38211720334437
1193335.7570541145374-2.75705411453736
1203131.0900220211816-0.0900220211816067
1213836.48739462721991.51260537278011
1223736.57226913667710.427730863322893
1233632.91075724141583.08924275858424
1243133.9213205108523-2.92132051085233
1253934.05554791333224.94445208666778
1264437.55715604326816.44284395673186
1273335.822150079774-2.82215007977403
1283533.32354473040371.67645526959627
1293234.5525189191267-2.55251891912675
1302832.4177982692771-4.41779826927709
1314036.36802387503593.63197612496412
1322732.217243196006-5.21724319600595
1333736.60319778532480.396802214675162
1343232.0212039560585-0.0212039560584669
1352828.3330617947284-0.33306179472843
1363435.3290273530032-1.3290273530032
1373033.9135191328861-3.91351913288606
1383533.96791509725091.0320849027491
1393134.4628422274227-3.46284222742269
1403234.8750378797003-2.87503787970031
1413036.5358927729597-6.53589277295974
1423035.2002931254208-5.20029312542081
1433129.6407319893391.35926801066096
1444032.07823563275647.92176436724362
1453231.65731925653780.342680743462178
1463635.15362140455910.846378595440911
1473233.402521421236-1.40252142123596
1483533.19594593504881.80405406495119
1493836.10843440978521.89156559021478
1504235.78299338795546.21700661204462
1513437.2603354670173-3.26033546701728
1523537.2905496846636-2.29054968466364
1533834.08026895608113.91973104391892
1543331.90763186655911.09236813344088
1553235.7286194450677-3.72861944506772
1563335.822150079774-2.82215007977403
1573433.61926967027640.380730329723553
1583235.7879593248344-3.78795932483439
1592729.588290517738-2.58829051773796
1603129.68678708932331.31321291067672
1613834.12464366382893.87535633617109
1623436.1247734278123-2.12477342781233
1632431.0532699256821-7.05326992568206
1643033.4772741012623-3.47727410126232
1652628.2663129323271-2.26631293232714
1663435.018876537142-1.01887653714203
1672735.5882410864717-8.58824108647168
1683732.15120168375394.84879831624606
1693635.59963207999420.400367920005818
1704133.78359988606657.21640011393345
1712928.11413341050480.885866589495181
1723630.21355131153815.78644868846193
1733234.6425108716993-2.6425108716993
1743732.4993970071734.50060299282696
1753031.5147964495052-1.51479644950519
1763132.257904277033-1.257904277033
1773834.5548780556183.44512194438202
1783634.98823423741751.01176576258252
1793531.49159204436063.50840795563942
1803135.9654203388561-4.9654203388561
1813833.15749000896224.84250999103784
1822229.3064285290887-7.30642852908866
1833234.9313663153517-2.93136631535173
1843634.65527818654461.34472181345543
1853931.89418333214457.10581666785548
1862830.4473652580029-2.44736525800287
1873234.4127309803675-2.41273098036752
1883234.3640690799955-2.36406907999551
1893836.97888223119821.02111776880176
1903233.0851184869042-1.0851184869042
1913535.3641952591327-0.364195259132734
1923232.4719176578001-0.47191765780008
1933736.02972615550180.970273844498219
1943432.64663261359351.35336738640648
1953335.4858962358627-2.48589623586267
1963333.2338721478024-0.233872147802447
1973032.1046070973554-2.10460709735536
1982432.0900588174598-8.09005881745984
1993432.07001736266681.92998263733319
2003432.42028000005931.57971999994065
2013334.0186086248498-1.01860862484982
2023434.8672242533382-0.867224253338212
2033535.53479902533-0.534799025329999
2043535.4886545424868-0.488654542486777
2053632.78896688182683.21103311817316
2063433.86669343047350.133306569526488
2073432.30378584930371.69621415069627
2084138.56282774759892.43717225240113
2093236.5194230213485-4.51942302134854
2103033.1256294785684-3.12562947856845
2113534.3199684727750.68003152722497
2122829.6017488252339-1.6017488252339
2133334.9368594902492-1.93685949024924
2143933.63715442823715.36284557176295
2153634.05131823854781.9486817614522
2163636.3113074592065-0.311307459206451
2173533.03098684998541.96901315001462
2183835.13289873019672.86710126980328
2193332.54333385976140.456666140238642
2203132.6807242125928-1.68072421259284
2213233.5811412534541-1.58114125345413
2223133.3128545026132-2.31285450261324
2233333.9590058345107-0.959005834510654
2243432.55353006096541.44646993903461
2253433.94623851966540.0537614803346173
2263431.61533689671332.38466310328675
2273334.8230244901774-1.82302449017741
2283234.7298793603346-2.72987936033461
2294133.79413613230627.20586386769378
2303432.52878557986581.47121442013416
2313631.67990704080494.32009295919505
2323729.84725925300847.15274074699165
2333630.15875070344585.84124929655424
2342932.2724525569285-3.27245255692852
2353731.10217271514945.89782728485061
2362732.5590232358629-5.5590232358629
2373533.67782917453351.32217082546654
2382830.3593277981941-2.35932779819407
2393533.38127150885511.61872849114491
2402933.9951413091327-4.99514130913271
2413234.5135357550216-2.5135357550216
2423631.78361043836464.21638956163541
2431926.5843209478965-7.58432094789653
2442126.1514920041155-5.15149200411553
2453133.5470730928055-2.54707309280551
2463332.21123255617130.788767443828725
2473633.32233627281592.6776637271841
2483333.087426689973-0.0874266899729551
2493732.95887965537344.04112034462657
2503433.36353825713080.636461742869187
2513535.5882410864717-0.588241086471681
2523132.4552963999526-1.45529639995256
2533733.41833886522313.58166113477687
2543529.4935473163415.50645268365896
2552731.8243843406013-4.82438434060133
2563435.2932071392496-1.29320713924963
2574034.08745371316995.91254628683015
2582933.0774176817518-4.07741768175179
2593833.8116064734584.18839352654199
2603433.00982632046350.9901736795365
2612130.2076534929131-9.20765349291308
2623632.38911046231633.6108895376837
2633833.80706720178374.19293279821635
2643030.611784856652-0.611784856651961
2653534.32769271627810.672307283721856
2663029.96767740037730.0323225996227195
2673633.47931797688512.52068202311494
2683435.6580400780149-1.65804007801487
2693534.93136631535170.0686336846482713
2703433.67039127995350.329608720046461
2713235.9209562482493-3.92095624824928
2723329.81385864665973.1861413533403
2733333.3763055719761-0.376305571976085
2742631.8326769824641-5.83267698246408
2753536.4600831415819-1.46008314158187
2762123.5971598288855-2.59715982888549
2773834.17371020792843.8262897920716
2783533.20639279842951.79360720157051
2793333.5962167713682-0.596216771368156
2803734.21711982249822.78288017750178
2813832.94347662819515.05652337180492
2823434.3615971222946-0.361597122294596
2832731.0740023731258-4.07400237312576
2841625.9328401957338-9.93284019573377
2854038.07477011364741.92522988635263
2863634.27467873721461.72532126278536
2874237.41418313268024.58581686731984
2883033.0416868508572-3.04168685085721

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 35.932864706709 & 5.06713529329102 \tabularnewline
2 & 39 & 33.9036092806052 & 5.09639071939478 \tabularnewline
3 & 30 & 35.4832507504482 & -5.48325075044825 \tabularnewline
4 & 31 & 34.464481459318 & -3.46448145931795 \tabularnewline
5 & 34 & 35.7268164585403 & -1.72681645854029 \tabularnewline
6 & 35 & 31.7791839878999 & 3.22081601210008 \tabularnewline
7 & 39 & 33.8099148912667 & 5.19008510873326 \tabularnewline
8 & 34 & 35.2932965221086 & -1.29329652210862 \tabularnewline
9 & 36 & 34.7235273290515 & 1.27647267094851 \tabularnewline
10 & 37 & 36.5900023884014 & 0.409997611598612 \tabularnewline
11 & 38 & 33.7846666104994 & 4.21533338950061 \tabularnewline
12 & 36 & 34.906898410094 & 1.09310158990597 \tabularnewline
13 & 38 & 35.2794335708852 & 2.7205664291148 \tabularnewline
14 & 39 & 36.7758454271448 & 2.22415457285516 \tabularnewline
15 & 33 & 36.4230888105742 & -3.42308881057421 \tabularnewline
16 & 32 & 34.2848005666455 & -2.28480056664549 \tabularnewline
17 & 36 & 33.884944147135 & 2.11505585286504 \tabularnewline
18 & 38 & 37.6909333421927 & 0.309066657807318 \tabularnewline
19 & 39 & 37.5023554351758 & 1.49764456482418 \tabularnewline
20 & 32 & 33.7409706470064 & -1.74097064700638 \tabularnewline
21 & 32 & 34.7879557399882 & -2.78795573998819 \tabularnewline
22 & 31 & 32.9589690382324 & -1.95896903823242 \tabularnewline
23 & 39 & 37.2446460909157 & 1.75535390908426 \tabularnewline
24 & 37 & 37.046035737327 & -0.0460357373270109 \tabularnewline
25 & 39 & 34.4113037256223 & 4.58869627437772 \tabularnewline
26 & 41 & 33.5207730986911 & 7.47922690130887 \tabularnewline
27 & 36 & 35.7184466822144 & 0.281553317785613 \tabularnewline
28 & 33 & 35.7909585205538 & -2.79095852055381 \tabularnewline
29 & 33 & 34.1817647233858 & -1.18176472338582 \tabularnewline
30 & 34 & 33.9852216837705 & 0.0147783162294705 \tabularnewline
31 & 31 & 33.0165279529488 & -2.01652795294884 \tabularnewline
32 & 27 & 33.2455397171668 & -6.2455397171668 \tabularnewline
33 & 37 & 32.9444207583369 & 4.0555792416631 \tabularnewline
34 & 34 & 36.1724127171666 & -2.17241271716657 \tabularnewline
35 & 34 & 32.5650338756976 & 1.43496612430242 \tabularnewline
36 & 32 & 33.5091468800519 & -1.50914688005187 \tabularnewline
37 & 29 & 32.0179418497666 & -3.01794184976656 \tabularnewline
38 & 36 & 34.1148877930989 & 1.8851122069011 \tabularnewline
39 & 29 & 33.3979821495616 & -4.3979821495616 \tabularnewline
40 & 35 & 34.5525189191267 & 0.447481080873255 \tabularnewline
41 & 37 & 34.1685927648131 & 2.83140723518693 \tabularnewline
42 & 34 & 33.7850712542269 & 0.214928745773132 \tabularnewline
43 & 38 & 34.8880695219916 & 3.1119304780084 \tabularnewline
44 & 35 & 34.0420896058363 & 0.957910394163715 \tabularnewline
45 & 38 & 31.3376989188698 & 6.66230108113018 \tabularnewline
46 & 37 & 33.8157135539514 & 3.18428644604859 \tabularnewline
47 & 38 & 36.6652725333649 & 1.33472746663508 \tabularnewline
48 & 33 & 34.501548815686 & -1.50154881568598 \tabularnewline
49 & 36 & 36.8327133492106 & -0.832713349210597 \tabularnewline
50 & 38 & 33.5034899505222 & 4.4965100494778 \tabularnewline
51 & 32 & 36.6291370587429 & -4.62913705874286 \tabularnewline
52 & 32 & 32.6628394546322 & -0.66283945463223 \tabularnewline
53 & 32 & 33.4338547136112 & -1.43385471361117 \tabularnewline
54 & 34 & 36.4505681599472 & -2.45056815994717 \tabularnewline
55 & 32 & 32.655038076666 & -0.655038076665965 \tabularnewline
56 & 37 & 35.0169440658554 & 1.98305593414455 \tabularnewline
57 & 39 & 34.7362946438968 & 4.26370535610324 \tabularnewline
58 & 29 & 34.679426721831 & -5.67942672183101 \tabularnewline
59 & 37 & 35.7129535073169 & 1.28704649268312 \tabularnewline
60 & 35 & 34.6066285345684 & 0.393371465431605 \tabularnewline
61 & 30 & 31.0194549025246 & -1.0194549025246 \tabularnewline
62 & 38 & 34.9523753386373 & 3.04762466136272 \tabularnewline
63 & 34 & 34.8518114530785 & -0.851811453078522 \tabularnewline
64 & 31 & 34.7155621964531 & -3.71556219645306 \tabularnewline
65 & 34 & 33.1864407264954 & 0.813559273504559 \tabularnewline
66 & 35 & 36.4526354739206 & -1.45263547392061 \tabularnewline
67 & 36 & 35.3053728443032 & 0.694627155696772 \tabularnewline
68 & 30 & 31.9143376081472 & -1.91433760814724 \tabularnewline
69 & 39 & 36.7582759300527 & 2.24172406994727 \tabularnewline
70 & 35 & 36.5590971781044 & -1.55909717810436 \tabularnewline
71 & 38 & 34.8394942417886 & 3.1605057582114 \tabularnewline
72 & 31 & 36.3222840359201 & -5.32228403592014 \tabularnewline
73 & 34 & 37.523492526347 & -3.523492526347 \tabularnewline
74 & 38 & 38.9055009841752 & -0.905500984175162 \tabularnewline
75 & 34 & 31.468741349521 & 2.53125865047904 \tabularnewline
76 & 39 & 32.8916640258673 & 6.10833597413268 \tabularnewline
77 & 37 & 36.2372457718308 & 0.762754228169245 \tabularnewline
78 & 34 & 33.1216076718313 & 0.878392328168742 \tabularnewline
79 & 28 & 32.8927831005962 & -4.89278310059617 \tabularnewline
80 & 37 & 31.468741349521 & 5.53125865047904 \tabularnewline
81 & 33 & 36.0614351796592 & -3.06143517965917 \tabularnewline
82 & 35 & 36.1724127171666 & -1.17241271716657 \tabularnewline
83 & 37 & 34.398536410777 & 2.601463589223 \tabularnewline
84 & 32 & 34.501548815686 & -2.50154881568598 \tabularnewline
85 & 33 & 33.2273783833643 & -0.227378383364339 \tabularnewline
86 & 38 & 37.247568152172 & 0.752431847827993 \tabularnewline
87 & 33 & 34.6225587997653 & -1.62255879976525 \tabularnewline
88 & 29 & 33.5703668808091 & -4.57036688080912 \tabularnewline
89 & 33 & 33.5000406512474 & -0.500040651247426 \tabularnewline
90 & 31 & 35.0280721488055 & -4.02807214880546 \tabularnewline
91 & 36 & 33.6504392080195 & 2.34956079198051 \tabularnewline
92 & 35 & 38.1630607109473 & -3.16306071094733 \tabularnewline
93 & 32 & 31.4098061134818 & 0.590193886518231 \tabularnewline
94 & 29 & 31.8947007970817 & -2.89470079708168 \tabularnewline
95 & 39 & 35.8294242197218 & 3.17057578027821 \tabularnewline
96 & 37 & 34.9575821646116 & 2.0424178353884 \tabularnewline
97 & 35 & 33.2762811728317 & 1.72371882716833 \tabularnewline
98 & 37 & 35.1798470269003 & 1.8201529730997 \tabularnewline
99 & 32 & 35.7056793673691 & -3.70567936736911 \tabularnewline
100 & 38 & 35.6906809839182 & 2.30931901608176 \tabularnewline
101 & 37 & 35.442072204484 & 1.55792779551596 \tabularnewline
102 & 36 & 36.9896950532798 & -0.989695053279759 \tabularnewline
103 & 32 & 31.6747895976896 & 0.325210402310386 \tabularnewline
104 & 33 & 37.2166395035243 & -4.21663950352428 \tabularnewline
105 & 40 & 33.0492375666468 & 6.95076243335318 \tabularnewline
106 & 38 & 35.4607373379543 & 2.5392626620457 \tabularnewline
107 & 41 & 37.5544211749947 & 3.44557882500527 \tabularnewline
108 & 36 & 35.3283363603525 & 0.671663639647469 \tabularnewline
109 & 43 & 37.713774263951 & 5.28622573604904 \tabularnewline
110 & 30 & 34.679426721831 & -4.67942672183101 \tabularnewline
111 & 31 & 33.8564874561881 & -2.85648745618815 \tabularnewline
112 & 32 & 38.3250083518955 & -6.3250083518955 \tabularnewline
113 & 37 & 34.0407132845135 & 2.95928671548649 \tabularnewline
114 & 37 & 34.5323137097015 & 2.46768629029845 \tabularnewline
115 & 33 & 37.1060666097443 & -4.10606660974435 \tabularnewline
116 & 34 & 37.350580557081 & -3.35058055708098 \tabularnewline
117 & 33 & 34.4887815008407 & -1.48878150084071 \tabularnewline
118 & 38 & 35.6178827966556 & 2.38211720334437 \tabularnewline
119 & 33 & 35.7570541145374 & -2.75705411453736 \tabularnewline
120 & 31 & 31.0900220211816 & -0.0900220211816067 \tabularnewline
121 & 38 & 36.4873946272199 & 1.51260537278011 \tabularnewline
122 & 37 & 36.5722691366771 & 0.427730863322893 \tabularnewline
123 & 36 & 32.9107572414158 & 3.08924275858424 \tabularnewline
124 & 31 & 33.9213205108523 & -2.92132051085233 \tabularnewline
125 & 39 & 34.0555479133322 & 4.94445208666778 \tabularnewline
126 & 44 & 37.5571560432681 & 6.44284395673186 \tabularnewline
127 & 33 & 35.822150079774 & -2.82215007977403 \tabularnewline
128 & 35 & 33.3235447304037 & 1.67645526959627 \tabularnewline
129 & 32 & 34.5525189191267 & -2.55251891912675 \tabularnewline
130 & 28 & 32.4177982692771 & -4.41779826927709 \tabularnewline
131 & 40 & 36.3680238750359 & 3.63197612496412 \tabularnewline
132 & 27 & 32.217243196006 & -5.21724319600595 \tabularnewline
133 & 37 & 36.6031977853248 & 0.396802214675162 \tabularnewline
134 & 32 & 32.0212039560585 & -0.0212039560584669 \tabularnewline
135 & 28 & 28.3330617947284 & -0.33306179472843 \tabularnewline
136 & 34 & 35.3290273530032 & -1.3290273530032 \tabularnewline
137 & 30 & 33.9135191328861 & -3.91351913288606 \tabularnewline
138 & 35 & 33.9679150972509 & 1.0320849027491 \tabularnewline
139 & 31 & 34.4628422274227 & -3.46284222742269 \tabularnewline
140 & 32 & 34.8750378797003 & -2.87503787970031 \tabularnewline
141 & 30 & 36.5358927729597 & -6.53589277295974 \tabularnewline
142 & 30 & 35.2002931254208 & -5.20029312542081 \tabularnewline
143 & 31 & 29.640731989339 & 1.35926801066096 \tabularnewline
144 & 40 & 32.0782356327564 & 7.92176436724362 \tabularnewline
145 & 32 & 31.6573192565378 & 0.342680743462178 \tabularnewline
146 & 36 & 35.1536214045591 & 0.846378595440911 \tabularnewline
147 & 32 & 33.402521421236 & -1.40252142123596 \tabularnewline
148 & 35 & 33.1959459350488 & 1.80405406495119 \tabularnewline
149 & 38 & 36.1084344097852 & 1.89156559021478 \tabularnewline
150 & 42 & 35.7829933879554 & 6.21700661204462 \tabularnewline
151 & 34 & 37.2603354670173 & -3.26033546701728 \tabularnewline
152 & 35 & 37.2905496846636 & -2.29054968466364 \tabularnewline
153 & 38 & 34.0802689560811 & 3.91973104391892 \tabularnewline
154 & 33 & 31.9076318665591 & 1.09236813344088 \tabularnewline
155 & 32 & 35.7286194450677 & -3.72861944506772 \tabularnewline
156 & 33 & 35.822150079774 & -2.82215007977403 \tabularnewline
157 & 34 & 33.6192696702764 & 0.380730329723553 \tabularnewline
158 & 32 & 35.7879593248344 & -3.78795932483439 \tabularnewline
159 & 27 & 29.588290517738 & -2.58829051773796 \tabularnewline
160 & 31 & 29.6867870893233 & 1.31321291067672 \tabularnewline
161 & 38 & 34.1246436638289 & 3.87535633617109 \tabularnewline
162 & 34 & 36.1247734278123 & -2.12477342781233 \tabularnewline
163 & 24 & 31.0532699256821 & -7.05326992568206 \tabularnewline
164 & 30 & 33.4772741012623 & -3.47727410126232 \tabularnewline
165 & 26 & 28.2663129323271 & -2.26631293232714 \tabularnewline
166 & 34 & 35.018876537142 & -1.01887653714203 \tabularnewline
167 & 27 & 35.5882410864717 & -8.58824108647168 \tabularnewline
168 & 37 & 32.1512016837539 & 4.84879831624606 \tabularnewline
169 & 36 & 35.5996320799942 & 0.400367920005818 \tabularnewline
170 & 41 & 33.7835998860665 & 7.21640011393345 \tabularnewline
171 & 29 & 28.1141334105048 & 0.885866589495181 \tabularnewline
172 & 36 & 30.2135513115381 & 5.78644868846193 \tabularnewline
173 & 32 & 34.6425108716993 & -2.6425108716993 \tabularnewline
174 & 37 & 32.499397007173 & 4.50060299282696 \tabularnewline
175 & 30 & 31.5147964495052 & -1.51479644950519 \tabularnewline
176 & 31 & 32.257904277033 & -1.257904277033 \tabularnewline
177 & 38 & 34.554878055618 & 3.44512194438202 \tabularnewline
178 & 36 & 34.9882342374175 & 1.01176576258252 \tabularnewline
179 & 35 & 31.4915920443606 & 3.50840795563942 \tabularnewline
180 & 31 & 35.9654203388561 & -4.9654203388561 \tabularnewline
181 & 38 & 33.1574900089622 & 4.84250999103784 \tabularnewline
182 & 22 & 29.3064285290887 & -7.30642852908866 \tabularnewline
183 & 32 & 34.9313663153517 & -2.93136631535173 \tabularnewline
184 & 36 & 34.6552781865446 & 1.34472181345543 \tabularnewline
185 & 39 & 31.8941833321445 & 7.10581666785548 \tabularnewline
186 & 28 & 30.4473652580029 & -2.44736525800287 \tabularnewline
187 & 32 & 34.4127309803675 & -2.41273098036752 \tabularnewline
188 & 32 & 34.3640690799955 & -2.36406907999551 \tabularnewline
189 & 38 & 36.9788822311982 & 1.02111776880176 \tabularnewline
190 & 32 & 33.0851184869042 & -1.0851184869042 \tabularnewline
191 & 35 & 35.3641952591327 & -0.364195259132734 \tabularnewline
192 & 32 & 32.4719176578001 & -0.47191765780008 \tabularnewline
193 & 37 & 36.0297261555018 & 0.970273844498219 \tabularnewline
194 & 34 & 32.6466326135935 & 1.35336738640648 \tabularnewline
195 & 33 & 35.4858962358627 & -2.48589623586267 \tabularnewline
196 & 33 & 33.2338721478024 & -0.233872147802447 \tabularnewline
197 & 30 & 32.1046070973554 & -2.10460709735536 \tabularnewline
198 & 24 & 32.0900588174598 & -8.09005881745984 \tabularnewline
199 & 34 & 32.0700173626668 & 1.92998263733319 \tabularnewline
200 & 34 & 32.4202800000593 & 1.57971999994065 \tabularnewline
201 & 33 & 34.0186086248498 & -1.01860862484982 \tabularnewline
202 & 34 & 34.8672242533382 & -0.867224253338212 \tabularnewline
203 & 35 & 35.53479902533 & -0.534799025329999 \tabularnewline
204 & 35 & 35.4886545424868 & -0.488654542486777 \tabularnewline
205 & 36 & 32.7889668818268 & 3.21103311817316 \tabularnewline
206 & 34 & 33.8666934304735 & 0.133306569526488 \tabularnewline
207 & 34 & 32.3037858493037 & 1.69621415069627 \tabularnewline
208 & 41 & 38.5628277475989 & 2.43717225240113 \tabularnewline
209 & 32 & 36.5194230213485 & -4.51942302134854 \tabularnewline
210 & 30 & 33.1256294785684 & -3.12562947856845 \tabularnewline
211 & 35 & 34.319968472775 & 0.68003152722497 \tabularnewline
212 & 28 & 29.6017488252339 & -1.6017488252339 \tabularnewline
213 & 33 & 34.9368594902492 & -1.93685949024924 \tabularnewline
214 & 39 & 33.6371544282371 & 5.36284557176295 \tabularnewline
215 & 36 & 34.0513182385478 & 1.9486817614522 \tabularnewline
216 & 36 & 36.3113074592065 & -0.311307459206451 \tabularnewline
217 & 35 & 33.0309868499854 & 1.96901315001462 \tabularnewline
218 & 38 & 35.1328987301967 & 2.86710126980328 \tabularnewline
219 & 33 & 32.5433338597614 & 0.456666140238642 \tabularnewline
220 & 31 & 32.6807242125928 & -1.68072421259284 \tabularnewline
221 & 32 & 33.5811412534541 & -1.58114125345413 \tabularnewline
222 & 31 & 33.3128545026132 & -2.31285450261324 \tabularnewline
223 & 33 & 33.9590058345107 & -0.959005834510654 \tabularnewline
224 & 34 & 32.5535300609654 & 1.44646993903461 \tabularnewline
225 & 34 & 33.9462385196654 & 0.0537614803346173 \tabularnewline
226 & 34 & 31.6153368967133 & 2.38466310328675 \tabularnewline
227 & 33 & 34.8230244901774 & -1.82302449017741 \tabularnewline
228 & 32 & 34.7298793603346 & -2.72987936033461 \tabularnewline
229 & 41 & 33.7941361323062 & 7.20586386769378 \tabularnewline
230 & 34 & 32.5287855798658 & 1.47121442013416 \tabularnewline
231 & 36 & 31.6799070408049 & 4.32009295919505 \tabularnewline
232 & 37 & 29.8472592530084 & 7.15274074699165 \tabularnewline
233 & 36 & 30.1587507034458 & 5.84124929655424 \tabularnewline
234 & 29 & 32.2724525569285 & -3.27245255692852 \tabularnewline
235 & 37 & 31.1021727151494 & 5.89782728485061 \tabularnewline
236 & 27 & 32.5590232358629 & -5.5590232358629 \tabularnewline
237 & 35 & 33.6778291745335 & 1.32217082546654 \tabularnewline
238 & 28 & 30.3593277981941 & -2.35932779819407 \tabularnewline
239 & 35 & 33.3812715088551 & 1.61872849114491 \tabularnewline
240 & 29 & 33.9951413091327 & -4.99514130913271 \tabularnewline
241 & 32 & 34.5135357550216 & -2.5135357550216 \tabularnewline
242 & 36 & 31.7836104383646 & 4.21638956163541 \tabularnewline
243 & 19 & 26.5843209478965 & -7.58432094789653 \tabularnewline
244 & 21 & 26.1514920041155 & -5.15149200411553 \tabularnewline
245 & 31 & 33.5470730928055 & -2.54707309280551 \tabularnewline
246 & 33 & 32.2112325561713 & 0.788767443828725 \tabularnewline
247 & 36 & 33.3223362728159 & 2.6776637271841 \tabularnewline
248 & 33 & 33.087426689973 & -0.0874266899729551 \tabularnewline
249 & 37 & 32.9588796553734 & 4.04112034462657 \tabularnewline
250 & 34 & 33.3635382571308 & 0.636461742869187 \tabularnewline
251 & 35 & 35.5882410864717 & -0.588241086471681 \tabularnewline
252 & 31 & 32.4552963999526 & -1.45529639995256 \tabularnewline
253 & 37 & 33.4183388652231 & 3.58166113477687 \tabularnewline
254 & 35 & 29.493547316341 & 5.50645268365896 \tabularnewline
255 & 27 & 31.8243843406013 & -4.82438434060133 \tabularnewline
256 & 34 & 35.2932071392496 & -1.29320713924963 \tabularnewline
257 & 40 & 34.0874537131699 & 5.91254628683015 \tabularnewline
258 & 29 & 33.0774176817518 & -4.07741768175179 \tabularnewline
259 & 38 & 33.811606473458 & 4.18839352654199 \tabularnewline
260 & 34 & 33.0098263204635 & 0.9901736795365 \tabularnewline
261 & 21 & 30.2076534929131 & -9.20765349291308 \tabularnewline
262 & 36 & 32.3891104623163 & 3.6108895376837 \tabularnewline
263 & 38 & 33.8070672017837 & 4.19293279821635 \tabularnewline
264 & 30 & 30.611784856652 & -0.611784856651961 \tabularnewline
265 & 35 & 34.3276927162781 & 0.672307283721856 \tabularnewline
266 & 30 & 29.9676774003773 & 0.0323225996227195 \tabularnewline
267 & 36 & 33.4793179768851 & 2.52068202311494 \tabularnewline
268 & 34 & 35.6580400780149 & -1.65804007801487 \tabularnewline
269 & 35 & 34.9313663153517 & 0.0686336846482713 \tabularnewline
270 & 34 & 33.6703912799535 & 0.329608720046461 \tabularnewline
271 & 32 & 35.9209562482493 & -3.92095624824928 \tabularnewline
272 & 33 & 29.8138586466597 & 3.1861413533403 \tabularnewline
273 & 33 & 33.3763055719761 & -0.376305571976085 \tabularnewline
274 & 26 & 31.8326769824641 & -5.83267698246408 \tabularnewline
275 & 35 & 36.4600831415819 & -1.46008314158187 \tabularnewline
276 & 21 & 23.5971598288855 & -2.59715982888549 \tabularnewline
277 & 38 & 34.1737102079284 & 3.8262897920716 \tabularnewline
278 & 35 & 33.2063927984295 & 1.79360720157051 \tabularnewline
279 & 33 & 33.5962167713682 & -0.596216771368156 \tabularnewline
280 & 37 & 34.2171198224982 & 2.78288017750178 \tabularnewline
281 & 38 & 32.9434766281951 & 5.05652337180492 \tabularnewline
282 & 34 & 34.3615971222946 & -0.361597122294596 \tabularnewline
283 & 27 & 31.0740023731258 & -4.07400237312576 \tabularnewline
284 & 16 & 25.9328401957338 & -9.93284019573377 \tabularnewline
285 & 40 & 38.0747701136474 & 1.92522988635263 \tabularnewline
286 & 36 & 34.2746787372146 & 1.72532126278536 \tabularnewline
287 & 42 & 37.4141831326802 & 4.58581686731984 \tabularnewline
288 & 30 & 33.0416868508572 & -3.04168685085721 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198137&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]41[/C][C]35.932864706709[/C][C]5.06713529329102[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]33.9036092806052[/C][C]5.09639071939478[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]35.4832507504482[/C][C]-5.48325075044825[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]34.464481459318[/C][C]-3.46448145931795[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]35.7268164585403[/C][C]-1.72681645854029[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]31.7791839878999[/C][C]3.22081601210008[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]33.8099148912667[/C][C]5.19008510873326[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]35.2932965221086[/C][C]-1.29329652210862[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]34.7235273290515[/C][C]1.27647267094851[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]36.5900023884014[/C][C]0.409997611598612[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]33.7846666104994[/C][C]4.21533338950061[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]34.906898410094[/C][C]1.09310158990597[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]35.2794335708852[/C][C]2.7205664291148[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]36.7758454271448[/C][C]2.22415457285516[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]36.4230888105742[/C][C]-3.42308881057421[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]34.2848005666455[/C][C]-2.28480056664549[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]33.884944147135[/C][C]2.11505585286504[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]37.6909333421927[/C][C]0.309066657807318[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]37.5023554351758[/C][C]1.49764456482418[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.7409706470064[/C][C]-1.74097064700638[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.7879557399882[/C][C]-2.78795573998819[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]32.9589690382324[/C][C]-1.95896903823242[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]37.2446460909157[/C][C]1.75535390908426[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]37.046035737327[/C][C]-0.0460357373270109[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]34.4113037256223[/C][C]4.58869627437772[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]33.5207730986911[/C][C]7.47922690130887[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]35.7184466822144[/C][C]0.281553317785613[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]35.7909585205538[/C][C]-2.79095852055381[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]34.1817647233858[/C][C]-1.18176472338582[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]33.9852216837705[/C][C]0.0147783162294705[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]33.0165279529488[/C][C]-2.01652795294884[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]33.2455397171668[/C][C]-6.2455397171668[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]32.9444207583369[/C][C]4.0555792416631[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]36.1724127171666[/C][C]-2.17241271716657[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]32.5650338756976[/C][C]1.43496612430242[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]33.5091468800519[/C][C]-1.50914688005187[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]32.0179418497666[/C][C]-3.01794184976656[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]34.1148877930989[/C][C]1.8851122069011[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]33.3979821495616[/C][C]-4.3979821495616[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]34.5525189191267[/C][C]0.447481080873255[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]34.1685927648131[/C][C]2.83140723518693[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]33.7850712542269[/C][C]0.214928745773132[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]34.8880695219916[/C][C]3.1119304780084[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]34.0420896058363[/C][C]0.957910394163715[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]31.3376989188698[/C][C]6.66230108113018[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]33.8157135539514[/C][C]3.18428644604859[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]36.6652725333649[/C][C]1.33472746663508[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]34.501548815686[/C][C]-1.50154881568598[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]36.8327133492106[/C][C]-0.832713349210597[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]33.5034899505222[/C][C]4.4965100494778[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]36.6291370587429[/C][C]-4.62913705874286[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.6628394546322[/C][C]-0.66283945463223[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]33.4338547136112[/C][C]-1.43385471361117[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]36.4505681599472[/C][C]-2.45056815994717[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]32.655038076666[/C][C]-0.655038076665965[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]35.0169440658554[/C][C]1.98305593414455[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]34.7362946438968[/C][C]4.26370535610324[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]34.679426721831[/C][C]-5.67942672183101[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]35.7129535073169[/C][C]1.28704649268312[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]34.6066285345684[/C][C]0.393371465431605[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]31.0194549025246[/C][C]-1.0194549025246[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]34.9523753386373[/C][C]3.04762466136272[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]34.8518114530785[/C][C]-0.851811453078522[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]34.7155621964531[/C][C]-3.71556219645306[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]33.1864407264954[/C][C]0.813559273504559[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]36.4526354739206[/C][C]-1.45263547392061[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]35.3053728443032[/C][C]0.694627155696772[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]31.9143376081472[/C][C]-1.91433760814724[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]36.7582759300527[/C][C]2.24172406994727[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]36.5590971781044[/C][C]-1.55909717810436[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]34.8394942417886[/C][C]3.1605057582114[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]36.3222840359201[/C][C]-5.32228403592014[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]37.523492526347[/C][C]-3.523492526347[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]38.9055009841752[/C][C]-0.905500984175162[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]31.468741349521[/C][C]2.53125865047904[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.8916640258673[/C][C]6.10833597413268[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]36.2372457718308[/C][C]0.762754228169245[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]33.1216076718313[/C][C]0.878392328168742[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]32.8927831005962[/C][C]-4.89278310059617[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]31.468741349521[/C][C]5.53125865047904[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]36.0614351796592[/C][C]-3.06143517965917[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]36.1724127171666[/C][C]-1.17241271716657[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]34.398536410777[/C][C]2.601463589223[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.501548815686[/C][C]-2.50154881568598[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]33.2273783833643[/C][C]-0.227378383364339[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]37.247568152172[/C][C]0.752431847827993[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]34.6225587997653[/C][C]-1.62255879976525[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]33.5703668808091[/C][C]-4.57036688080912[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.5000406512474[/C][C]-0.500040651247426[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]35.0280721488055[/C][C]-4.02807214880546[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]33.6504392080195[/C][C]2.34956079198051[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]38.1630607109473[/C][C]-3.16306071094733[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.4098061134818[/C][C]0.590193886518231[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]31.8947007970817[/C][C]-2.89470079708168[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]35.8294242197218[/C][C]3.17057578027821[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.9575821646116[/C][C]2.0424178353884[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]33.2762811728317[/C][C]1.72371882716833[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]35.1798470269003[/C][C]1.8201529730997[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]35.7056793673691[/C][C]-3.70567936736911[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]35.6906809839182[/C][C]2.30931901608176[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]35.442072204484[/C][C]1.55792779551596[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]36.9896950532798[/C][C]-0.989695053279759[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]31.6747895976896[/C][C]0.325210402310386[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]37.2166395035243[/C][C]-4.21663950352428[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]33.0492375666468[/C][C]6.95076243335318[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]35.4607373379543[/C][C]2.5392626620457[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]37.5544211749947[/C][C]3.44557882500527[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]35.3283363603525[/C][C]0.671663639647469[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]37.713774263951[/C][C]5.28622573604904[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]34.679426721831[/C][C]-4.67942672183101[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]33.8564874561881[/C][C]-2.85648745618815[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]38.3250083518955[/C][C]-6.3250083518955[/C][/ROW]
[ROW][C]113[/C][C]37[/C][C]34.0407132845135[/C][C]2.95928671548649[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.5323137097015[/C][C]2.46768629029845[/C][/ROW]
[ROW][C]115[/C][C]33[/C][C]37.1060666097443[/C][C]-4.10606660974435[/C][/ROW]
[ROW][C]116[/C][C]34[/C][C]37.350580557081[/C][C]-3.35058055708098[/C][/ROW]
[ROW][C]117[/C][C]33[/C][C]34.4887815008407[/C][C]-1.48878150084071[/C][/ROW]
[ROW][C]118[/C][C]38[/C][C]35.6178827966556[/C][C]2.38211720334437[/C][/ROW]
[ROW][C]119[/C][C]33[/C][C]35.7570541145374[/C][C]-2.75705411453736[/C][/ROW]
[ROW][C]120[/C][C]31[/C][C]31.0900220211816[/C][C]-0.0900220211816067[/C][/ROW]
[ROW][C]121[/C][C]38[/C][C]36.4873946272199[/C][C]1.51260537278011[/C][/ROW]
[ROW][C]122[/C][C]37[/C][C]36.5722691366771[/C][C]0.427730863322893[/C][/ROW]
[ROW][C]123[/C][C]36[/C][C]32.9107572414158[/C][C]3.08924275858424[/C][/ROW]
[ROW][C]124[/C][C]31[/C][C]33.9213205108523[/C][C]-2.92132051085233[/C][/ROW]
[ROW][C]125[/C][C]39[/C][C]34.0555479133322[/C][C]4.94445208666778[/C][/ROW]
[ROW][C]126[/C][C]44[/C][C]37.5571560432681[/C][C]6.44284395673186[/C][/ROW]
[ROW][C]127[/C][C]33[/C][C]35.822150079774[/C][C]-2.82215007977403[/C][/ROW]
[ROW][C]128[/C][C]35[/C][C]33.3235447304037[/C][C]1.67645526959627[/C][/ROW]
[ROW][C]129[/C][C]32[/C][C]34.5525189191267[/C][C]-2.55251891912675[/C][/ROW]
[ROW][C]130[/C][C]28[/C][C]32.4177982692771[/C][C]-4.41779826927709[/C][/ROW]
[ROW][C]131[/C][C]40[/C][C]36.3680238750359[/C][C]3.63197612496412[/C][/ROW]
[ROW][C]132[/C][C]27[/C][C]32.217243196006[/C][C]-5.21724319600595[/C][/ROW]
[ROW][C]133[/C][C]37[/C][C]36.6031977853248[/C][C]0.396802214675162[/C][/ROW]
[ROW][C]134[/C][C]32[/C][C]32.0212039560585[/C][C]-0.0212039560584669[/C][/ROW]
[ROW][C]135[/C][C]28[/C][C]28.3330617947284[/C][C]-0.33306179472843[/C][/ROW]
[ROW][C]136[/C][C]34[/C][C]35.3290273530032[/C][C]-1.3290273530032[/C][/ROW]
[ROW][C]137[/C][C]30[/C][C]33.9135191328861[/C][C]-3.91351913288606[/C][/ROW]
[ROW][C]138[/C][C]35[/C][C]33.9679150972509[/C][C]1.0320849027491[/C][/ROW]
[ROW][C]139[/C][C]31[/C][C]34.4628422274227[/C][C]-3.46284222742269[/C][/ROW]
[ROW][C]140[/C][C]32[/C][C]34.8750378797003[/C][C]-2.87503787970031[/C][/ROW]
[ROW][C]141[/C][C]30[/C][C]36.5358927729597[/C][C]-6.53589277295974[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]35.2002931254208[/C][C]-5.20029312542081[/C][/ROW]
[ROW][C]143[/C][C]31[/C][C]29.640731989339[/C][C]1.35926801066096[/C][/ROW]
[ROW][C]144[/C][C]40[/C][C]32.0782356327564[/C][C]7.92176436724362[/C][/ROW]
[ROW][C]145[/C][C]32[/C][C]31.6573192565378[/C][C]0.342680743462178[/C][/ROW]
[ROW][C]146[/C][C]36[/C][C]35.1536214045591[/C][C]0.846378595440911[/C][/ROW]
[ROW][C]147[/C][C]32[/C][C]33.402521421236[/C][C]-1.40252142123596[/C][/ROW]
[ROW][C]148[/C][C]35[/C][C]33.1959459350488[/C][C]1.80405406495119[/C][/ROW]
[ROW][C]149[/C][C]38[/C][C]36.1084344097852[/C][C]1.89156559021478[/C][/ROW]
[ROW][C]150[/C][C]42[/C][C]35.7829933879554[/C][C]6.21700661204462[/C][/ROW]
[ROW][C]151[/C][C]34[/C][C]37.2603354670173[/C][C]-3.26033546701728[/C][/ROW]
[ROW][C]152[/C][C]35[/C][C]37.2905496846636[/C][C]-2.29054968466364[/C][/ROW]
[ROW][C]153[/C][C]38[/C][C]34.0802689560811[/C][C]3.91973104391892[/C][/ROW]
[ROW][C]154[/C][C]33[/C][C]31.9076318665591[/C][C]1.09236813344088[/C][/ROW]
[ROW][C]155[/C][C]32[/C][C]35.7286194450677[/C][C]-3.72861944506772[/C][/ROW]
[ROW][C]156[/C][C]33[/C][C]35.822150079774[/C][C]-2.82215007977403[/C][/ROW]
[ROW][C]157[/C][C]34[/C][C]33.6192696702764[/C][C]0.380730329723553[/C][/ROW]
[ROW][C]158[/C][C]32[/C][C]35.7879593248344[/C][C]-3.78795932483439[/C][/ROW]
[ROW][C]159[/C][C]27[/C][C]29.588290517738[/C][C]-2.58829051773796[/C][/ROW]
[ROW][C]160[/C][C]31[/C][C]29.6867870893233[/C][C]1.31321291067672[/C][/ROW]
[ROW][C]161[/C][C]38[/C][C]34.1246436638289[/C][C]3.87535633617109[/C][/ROW]
[ROW][C]162[/C][C]34[/C][C]36.1247734278123[/C][C]-2.12477342781233[/C][/ROW]
[ROW][C]163[/C][C]24[/C][C]31.0532699256821[/C][C]-7.05326992568206[/C][/ROW]
[ROW][C]164[/C][C]30[/C][C]33.4772741012623[/C][C]-3.47727410126232[/C][/ROW]
[ROW][C]165[/C][C]26[/C][C]28.2663129323271[/C][C]-2.26631293232714[/C][/ROW]
[ROW][C]166[/C][C]34[/C][C]35.018876537142[/C][C]-1.01887653714203[/C][/ROW]
[ROW][C]167[/C][C]27[/C][C]35.5882410864717[/C][C]-8.58824108647168[/C][/ROW]
[ROW][C]168[/C][C]37[/C][C]32.1512016837539[/C][C]4.84879831624606[/C][/ROW]
[ROW][C]169[/C][C]36[/C][C]35.5996320799942[/C][C]0.400367920005818[/C][/ROW]
[ROW][C]170[/C][C]41[/C][C]33.7835998860665[/C][C]7.21640011393345[/C][/ROW]
[ROW][C]171[/C][C]29[/C][C]28.1141334105048[/C][C]0.885866589495181[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]30.2135513115381[/C][C]5.78644868846193[/C][/ROW]
[ROW][C]173[/C][C]32[/C][C]34.6425108716993[/C][C]-2.6425108716993[/C][/ROW]
[ROW][C]174[/C][C]37[/C][C]32.499397007173[/C][C]4.50060299282696[/C][/ROW]
[ROW][C]175[/C][C]30[/C][C]31.5147964495052[/C][C]-1.51479644950519[/C][/ROW]
[ROW][C]176[/C][C]31[/C][C]32.257904277033[/C][C]-1.257904277033[/C][/ROW]
[ROW][C]177[/C][C]38[/C][C]34.554878055618[/C][C]3.44512194438202[/C][/ROW]
[ROW][C]178[/C][C]36[/C][C]34.9882342374175[/C][C]1.01176576258252[/C][/ROW]
[ROW][C]179[/C][C]35[/C][C]31.4915920443606[/C][C]3.50840795563942[/C][/ROW]
[ROW][C]180[/C][C]31[/C][C]35.9654203388561[/C][C]-4.9654203388561[/C][/ROW]
[ROW][C]181[/C][C]38[/C][C]33.1574900089622[/C][C]4.84250999103784[/C][/ROW]
[ROW][C]182[/C][C]22[/C][C]29.3064285290887[/C][C]-7.30642852908866[/C][/ROW]
[ROW][C]183[/C][C]32[/C][C]34.9313663153517[/C][C]-2.93136631535173[/C][/ROW]
[ROW][C]184[/C][C]36[/C][C]34.6552781865446[/C][C]1.34472181345543[/C][/ROW]
[ROW][C]185[/C][C]39[/C][C]31.8941833321445[/C][C]7.10581666785548[/C][/ROW]
[ROW][C]186[/C][C]28[/C][C]30.4473652580029[/C][C]-2.44736525800287[/C][/ROW]
[ROW][C]187[/C][C]32[/C][C]34.4127309803675[/C][C]-2.41273098036752[/C][/ROW]
[ROW][C]188[/C][C]32[/C][C]34.3640690799955[/C][C]-2.36406907999551[/C][/ROW]
[ROW][C]189[/C][C]38[/C][C]36.9788822311982[/C][C]1.02111776880176[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]33.0851184869042[/C][C]-1.0851184869042[/C][/ROW]
[ROW][C]191[/C][C]35[/C][C]35.3641952591327[/C][C]-0.364195259132734[/C][/ROW]
[ROW][C]192[/C][C]32[/C][C]32.4719176578001[/C][C]-0.47191765780008[/C][/ROW]
[ROW][C]193[/C][C]37[/C][C]36.0297261555018[/C][C]0.970273844498219[/C][/ROW]
[ROW][C]194[/C][C]34[/C][C]32.6466326135935[/C][C]1.35336738640648[/C][/ROW]
[ROW][C]195[/C][C]33[/C][C]35.4858962358627[/C][C]-2.48589623586267[/C][/ROW]
[ROW][C]196[/C][C]33[/C][C]33.2338721478024[/C][C]-0.233872147802447[/C][/ROW]
[ROW][C]197[/C][C]30[/C][C]32.1046070973554[/C][C]-2.10460709735536[/C][/ROW]
[ROW][C]198[/C][C]24[/C][C]32.0900588174598[/C][C]-8.09005881745984[/C][/ROW]
[ROW][C]199[/C][C]34[/C][C]32.0700173626668[/C][C]1.92998263733319[/C][/ROW]
[ROW][C]200[/C][C]34[/C][C]32.4202800000593[/C][C]1.57971999994065[/C][/ROW]
[ROW][C]201[/C][C]33[/C][C]34.0186086248498[/C][C]-1.01860862484982[/C][/ROW]
[ROW][C]202[/C][C]34[/C][C]34.8672242533382[/C][C]-0.867224253338212[/C][/ROW]
[ROW][C]203[/C][C]35[/C][C]35.53479902533[/C][C]-0.534799025329999[/C][/ROW]
[ROW][C]204[/C][C]35[/C][C]35.4886545424868[/C][C]-0.488654542486777[/C][/ROW]
[ROW][C]205[/C][C]36[/C][C]32.7889668818268[/C][C]3.21103311817316[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]33.8666934304735[/C][C]0.133306569526488[/C][/ROW]
[ROW][C]207[/C][C]34[/C][C]32.3037858493037[/C][C]1.69621415069627[/C][/ROW]
[ROW][C]208[/C][C]41[/C][C]38.5628277475989[/C][C]2.43717225240113[/C][/ROW]
[ROW][C]209[/C][C]32[/C][C]36.5194230213485[/C][C]-4.51942302134854[/C][/ROW]
[ROW][C]210[/C][C]30[/C][C]33.1256294785684[/C][C]-3.12562947856845[/C][/ROW]
[ROW][C]211[/C][C]35[/C][C]34.319968472775[/C][C]0.68003152722497[/C][/ROW]
[ROW][C]212[/C][C]28[/C][C]29.6017488252339[/C][C]-1.6017488252339[/C][/ROW]
[ROW][C]213[/C][C]33[/C][C]34.9368594902492[/C][C]-1.93685949024924[/C][/ROW]
[ROW][C]214[/C][C]39[/C][C]33.6371544282371[/C][C]5.36284557176295[/C][/ROW]
[ROW][C]215[/C][C]36[/C][C]34.0513182385478[/C][C]1.9486817614522[/C][/ROW]
[ROW][C]216[/C][C]36[/C][C]36.3113074592065[/C][C]-0.311307459206451[/C][/ROW]
[ROW][C]217[/C][C]35[/C][C]33.0309868499854[/C][C]1.96901315001462[/C][/ROW]
[ROW][C]218[/C][C]38[/C][C]35.1328987301967[/C][C]2.86710126980328[/C][/ROW]
[ROW][C]219[/C][C]33[/C][C]32.5433338597614[/C][C]0.456666140238642[/C][/ROW]
[ROW][C]220[/C][C]31[/C][C]32.6807242125928[/C][C]-1.68072421259284[/C][/ROW]
[ROW][C]221[/C][C]32[/C][C]33.5811412534541[/C][C]-1.58114125345413[/C][/ROW]
[ROW][C]222[/C][C]31[/C][C]33.3128545026132[/C][C]-2.31285450261324[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]33.9590058345107[/C][C]-0.959005834510654[/C][/ROW]
[ROW][C]224[/C][C]34[/C][C]32.5535300609654[/C][C]1.44646993903461[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]33.9462385196654[/C][C]0.0537614803346173[/C][/ROW]
[ROW][C]226[/C][C]34[/C][C]31.6153368967133[/C][C]2.38466310328675[/C][/ROW]
[ROW][C]227[/C][C]33[/C][C]34.8230244901774[/C][C]-1.82302449017741[/C][/ROW]
[ROW][C]228[/C][C]32[/C][C]34.7298793603346[/C][C]-2.72987936033461[/C][/ROW]
[ROW][C]229[/C][C]41[/C][C]33.7941361323062[/C][C]7.20586386769378[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]32.5287855798658[/C][C]1.47121442013416[/C][/ROW]
[ROW][C]231[/C][C]36[/C][C]31.6799070408049[/C][C]4.32009295919505[/C][/ROW]
[ROW][C]232[/C][C]37[/C][C]29.8472592530084[/C][C]7.15274074699165[/C][/ROW]
[ROW][C]233[/C][C]36[/C][C]30.1587507034458[/C][C]5.84124929655424[/C][/ROW]
[ROW][C]234[/C][C]29[/C][C]32.2724525569285[/C][C]-3.27245255692852[/C][/ROW]
[ROW][C]235[/C][C]37[/C][C]31.1021727151494[/C][C]5.89782728485061[/C][/ROW]
[ROW][C]236[/C][C]27[/C][C]32.5590232358629[/C][C]-5.5590232358629[/C][/ROW]
[ROW][C]237[/C][C]35[/C][C]33.6778291745335[/C][C]1.32217082546654[/C][/ROW]
[ROW][C]238[/C][C]28[/C][C]30.3593277981941[/C][C]-2.35932779819407[/C][/ROW]
[ROW][C]239[/C][C]35[/C][C]33.3812715088551[/C][C]1.61872849114491[/C][/ROW]
[ROW][C]240[/C][C]29[/C][C]33.9951413091327[/C][C]-4.99514130913271[/C][/ROW]
[ROW][C]241[/C][C]32[/C][C]34.5135357550216[/C][C]-2.5135357550216[/C][/ROW]
[ROW][C]242[/C][C]36[/C][C]31.7836104383646[/C][C]4.21638956163541[/C][/ROW]
[ROW][C]243[/C][C]19[/C][C]26.5843209478965[/C][C]-7.58432094789653[/C][/ROW]
[ROW][C]244[/C][C]21[/C][C]26.1514920041155[/C][C]-5.15149200411553[/C][/ROW]
[ROW][C]245[/C][C]31[/C][C]33.5470730928055[/C][C]-2.54707309280551[/C][/ROW]
[ROW][C]246[/C][C]33[/C][C]32.2112325561713[/C][C]0.788767443828725[/C][/ROW]
[ROW][C]247[/C][C]36[/C][C]33.3223362728159[/C][C]2.6776637271841[/C][/ROW]
[ROW][C]248[/C][C]33[/C][C]33.087426689973[/C][C]-0.0874266899729551[/C][/ROW]
[ROW][C]249[/C][C]37[/C][C]32.9588796553734[/C][C]4.04112034462657[/C][/ROW]
[ROW][C]250[/C][C]34[/C][C]33.3635382571308[/C][C]0.636461742869187[/C][/ROW]
[ROW][C]251[/C][C]35[/C][C]35.5882410864717[/C][C]-0.588241086471681[/C][/ROW]
[ROW][C]252[/C][C]31[/C][C]32.4552963999526[/C][C]-1.45529639995256[/C][/ROW]
[ROW][C]253[/C][C]37[/C][C]33.4183388652231[/C][C]3.58166113477687[/C][/ROW]
[ROW][C]254[/C][C]35[/C][C]29.493547316341[/C][C]5.50645268365896[/C][/ROW]
[ROW][C]255[/C][C]27[/C][C]31.8243843406013[/C][C]-4.82438434060133[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]35.2932071392496[/C][C]-1.29320713924963[/C][/ROW]
[ROW][C]257[/C][C]40[/C][C]34.0874537131699[/C][C]5.91254628683015[/C][/ROW]
[ROW][C]258[/C][C]29[/C][C]33.0774176817518[/C][C]-4.07741768175179[/C][/ROW]
[ROW][C]259[/C][C]38[/C][C]33.811606473458[/C][C]4.18839352654199[/C][/ROW]
[ROW][C]260[/C][C]34[/C][C]33.0098263204635[/C][C]0.9901736795365[/C][/ROW]
[ROW][C]261[/C][C]21[/C][C]30.2076534929131[/C][C]-9.20765349291308[/C][/ROW]
[ROW][C]262[/C][C]36[/C][C]32.3891104623163[/C][C]3.6108895376837[/C][/ROW]
[ROW][C]263[/C][C]38[/C][C]33.8070672017837[/C][C]4.19293279821635[/C][/ROW]
[ROW][C]264[/C][C]30[/C][C]30.611784856652[/C][C]-0.611784856651961[/C][/ROW]
[ROW][C]265[/C][C]35[/C][C]34.3276927162781[/C][C]0.672307283721856[/C][/ROW]
[ROW][C]266[/C][C]30[/C][C]29.9676774003773[/C][C]0.0323225996227195[/C][/ROW]
[ROW][C]267[/C][C]36[/C][C]33.4793179768851[/C][C]2.52068202311494[/C][/ROW]
[ROW][C]268[/C][C]34[/C][C]35.6580400780149[/C][C]-1.65804007801487[/C][/ROW]
[ROW][C]269[/C][C]35[/C][C]34.9313663153517[/C][C]0.0686336846482713[/C][/ROW]
[ROW][C]270[/C][C]34[/C][C]33.6703912799535[/C][C]0.329608720046461[/C][/ROW]
[ROW][C]271[/C][C]32[/C][C]35.9209562482493[/C][C]-3.92095624824928[/C][/ROW]
[ROW][C]272[/C][C]33[/C][C]29.8138586466597[/C][C]3.1861413533403[/C][/ROW]
[ROW][C]273[/C][C]33[/C][C]33.3763055719761[/C][C]-0.376305571976085[/C][/ROW]
[ROW][C]274[/C][C]26[/C][C]31.8326769824641[/C][C]-5.83267698246408[/C][/ROW]
[ROW][C]275[/C][C]35[/C][C]36.4600831415819[/C][C]-1.46008314158187[/C][/ROW]
[ROW][C]276[/C][C]21[/C][C]23.5971598288855[/C][C]-2.59715982888549[/C][/ROW]
[ROW][C]277[/C][C]38[/C][C]34.1737102079284[/C][C]3.8262897920716[/C][/ROW]
[ROW][C]278[/C][C]35[/C][C]33.2063927984295[/C][C]1.79360720157051[/C][/ROW]
[ROW][C]279[/C][C]33[/C][C]33.5962167713682[/C][C]-0.596216771368156[/C][/ROW]
[ROW][C]280[/C][C]37[/C][C]34.2171198224982[/C][C]2.78288017750178[/C][/ROW]
[ROW][C]281[/C][C]38[/C][C]32.9434766281951[/C][C]5.05652337180492[/C][/ROW]
[ROW][C]282[/C][C]34[/C][C]34.3615971222946[/C][C]-0.361597122294596[/C][/ROW]
[ROW][C]283[/C][C]27[/C][C]31.0740023731258[/C][C]-4.07400237312576[/C][/ROW]
[ROW][C]284[/C][C]16[/C][C]25.9328401957338[/C][C]-9.93284019573377[/C][/ROW]
[ROW][C]285[/C][C]40[/C][C]38.0747701136474[/C][C]1.92522988635263[/C][/ROW]
[ROW][C]286[/C][C]36[/C][C]34.2746787372146[/C][C]1.72532126278536[/C][/ROW]
[ROW][C]287[/C][C]42[/C][C]37.4141831326802[/C][C]4.58581686731984[/C][/ROW]
[ROW][C]288[/C][C]30[/C][C]33.0416868508572[/C][C]-3.04168685085721[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198137&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198137&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
14135.9328647067095.06713529329102
23933.90360928060525.09639071939478
33035.4832507504482-5.48325075044825
43134.464481459318-3.46448145931795
53435.7268164585403-1.72681645854029
63531.77918398789993.22081601210008
73933.80991489126675.19008510873326
83435.2932965221086-1.29329652210862
93634.72352732905151.27647267094851
103736.59000238840140.409997611598612
113833.78466661049944.21533338950061
123634.9068984100941.09310158990597
133835.27943357088522.7205664291148
143936.77584542714482.22415457285516
153336.4230888105742-3.42308881057421
163234.2848005666455-2.28480056664549
173633.8849441471352.11505585286504
183837.69093334219270.309066657807318
193937.50235543517581.49764456482418
203233.7409706470064-1.74097064700638
213234.7879557399882-2.78795573998819
223132.9589690382324-1.95896903823242
233937.24464609091571.75535390908426
243737.046035737327-0.0460357373270109
253934.41130372562234.58869627437772
264133.52077309869117.47922690130887
273635.71844668221440.281553317785613
283335.7909585205538-2.79095852055381
293334.1817647233858-1.18176472338582
303433.98522168377050.0147783162294705
313133.0165279529488-2.01652795294884
322733.2455397171668-6.2455397171668
333732.94442075833694.0555792416631
343436.1724127171666-2.17241271716657
353432.56503387569761.43496612430242
363233.5091468800519-1.50914688005187
372932.0179418497666-3.01794184976656
383634.11488779309891.8851122069011
392933.3979821495616-4.3979821495616
403534.55251891912670.447481080873255
413734.16859276481312.83140723518693
423433.78507125422690.214928745773132
433834.88806952199163.1119304780084
443534.04208960583630.957910394163715
453831.33769891886986.66230108113018
463733.81571355395143.18428644604859
473836.66527253336491.33472746663508
483334.501548815686-1.50154881568598
493636.8327133492106-0.832713349210597
503833.50348995052224.4965100494778
513236.6291370587429-4.62913705874286
523232.6628394546322-0.66283945463223
533233.4338547136112-1.43385471361117
543436.4505681599472-2.45056815994717
553232.655038076666-0.655038076665965
563735.01694406585541.98305593414455
573934.73629464389684.26370535610324
582934.679426721831-5.67942672183101
593735.71295350731691.28704649268312
603534.60662853456840.393371465431605
613031.0194549025246-1.0194549025246
623834.95237533863733.04762466136272
633434.8518114530785-0.851811453078522
643134.7155621964531-3.71556219645306
653433.18644072649540.813559273504559
663536.4526354739206-1.45263547392061
673635.30537284430320.694627155696772
683031.9143376081472-1.91433760814724
693936.75827593005272.24172406994727
703536.5590971781044-1.55909717810436
713834.83949424178863.1605057582114
723136.3222840359201-5.32228403592014
733437.523492526347-3.523492526347
743838.9055009841752-0.905500984175162
753431.4687413495212.53125865047904
763932.89166402586736.10833597413268
773736.23724577183080.762754228169245
783433.12160767183130.878392328168742
792832.8927831005962-4.89278310059617
803731.4687413495215.53125865047904
813336.0614351796592-3.06143517965917
823536.1724127171666-1.17241271716657
833734.3985364107772.601463589223
843234.501548815686-2.50154881568598
853333.2273783833643-0.227378383364339
863837.2475681521720.752431847827993
873334.6225587997653-1.62255879976525
882933.5703668808091-4.57036688080912
893333.5000406512474-0.500040651247426
903135.0280721488055-4.02807214880546
913633.65043920801952.34956079198051
923538.1630607109473-3.16306071094733
933231.40980611348180.590193886518231
942931.8947007970817-2.89470079708168
953935.82942421972183.17057578027821
963734.95758216461162.0424178353884
973533.27628117283171.72371882716833
983735.17984702690031.8201529730997
993235.7056793673691-3.70567936736911
1003835.69068098391822.30931901608176
1013735.4420722044841.55792779551596
1023636.9896950532798-0.989695053279759
1033231.67478959768960.325210402310386
1043337.2166395035243-4.21663950352428
1054033.04923756664686.95076243335318
1063835.46073733795432.5392626620457
1074137.55442117499473.44557882500527
1083635.32833636035250.671663639647469
1094337.7137742639515.28622573604904
1103034.679426721831-4.67942672183101
1113133.8564874561881-2.85648745618815
1123238.3250083518955-6.3250083518955
1133734.04071328451352.95928671548649
1143734.53231370970152.46768629029845
1153337.1060666097443-4.10606660974435
1163437.350580557081-3.35058055708098
1173334.4887815008407-1.48878150084071
1183835.61788279665562.38211720334437
1193335.7570541145374-2.75705411453736
1203131.0900220211816-0.0900220211816067
1213836.48739462721991.51260537278011
1223736.57226913667710.427730863322893
1233632.91075724141583.08924275858424
1243133.9213205108523-2.92132051085233
1253934.05554791333224.94445208666778
1264437.55715604326816.44284395673186
1273335.822150079774-2.82215007977403
1283533.32354473040371.67645526959627
1293234.5525189191267-2.55251891912675
1302832.4177982692771-4.41779826927709
1314036.36802387503593.63197612496412
1322732.217243196006-5.21724319600595
1333736.60319778532480.396802214675162
1343232.0212039560585-0.0212039560584669
1352828.3330617947284-0.33306179472843
1363435.3290273530032-1.3290273530032
1373033.9135191328861-3.91351913288606
1383533.96791509725091.0320849027491
1393134.4628422274227-3.46284222742269
1403234.8750378797003-2.87503787970031
1413036.5358927729597-6.53589277295974
1423035.2002931254208-5.20029312542081
1433129.6407319893391.35926801066096
1444032.07823563275647.92176436724362
1453231.65731925653780.342680743462178
1463635.15362140455910.846378595440911
1473233.402521421236-1.40252142123596
1483533.19594593504881.80405406495119
1493836.10843440978521.89156559021478
1504235.78299338795546.21700661204462
1513437.2603354670173-3.26033546701728
1523537.2905496846636-2.29054968466364
1533834.08026895608113.91973104391892
1543331.90763186655911.09236813344088
1553235.7286194450677-3.72861944506772
1563335.822150079774-2.82215007977403
1573433.61926967027640.380730329723553
1583235.7879593248344-3.78795932483439
1592729.588290517738-2.58829051773796
1603129.68678708932331.31321291067672
1613834.12464366382893.87535633617109
1623436.1247734278123-2.12477342781233
1632431.0532699256821-7.05326992568206
1643033.4772741012623-3.47727410126232
1652628.2663129323271-2.26631293232714
1663435.018876537142-1.01887653714203
1672735.5882410864717-8.58824108647168
1683732.15120168375394.84879831624606
1693635.59963207999420.400367920005818
1704133.78359988606657.21640011393345
1712928.11413341050480.885866589495181
1723630.21355131153815.78644868846193
1733234.6425108716993-2.6425108716993
1743732.4993970071734.50060299282696
1753031.5147964495052-1.51479644950519
1763132.257904277033-1.257904277033
1773834.5548780556183.44512194438202
1783634.98823423741751.01176576258252
1793531.49159204436063.50840795563942
1803135.9654203388561-4.9654203388561
1813833.15749000896224.84250999103784
1822229.3064285290887-7.30642852908866
1833234.9313663153517-2.93136631535173
1843634.65527818654461.34472181345543
1853931.89418333214457.10581666785548
1862830.4473652580029-2.44736525800287
1873234.4127309803675-2.41273098036752
1883234.3640690799955-2.36406907999551
1893836.97888223119821.02111776880176
1903233.0851184869042-1.0851184869042
1913535.3641952591327-0.364195259132734
1923232.4719176578001-0.47191765780008
1933736.02972615550180.970273844498219
1943432.64663261359351.35336738640648
1953335.4858962358627-2.48589623586267
1963333.2338721478024-0.233872147802447
1973032.1046070973554-2.10460709735536
1982432.0900588174598-8.09005881745984
1993432.07001736266681.92998263733319
2003432.42028000005931.57971999994065
2013334.0186086248498-1.01860862484982
2023434.8672242533382-0.867224253338212
2033535.53479902533-0.534799025329999
2043535.4886545424868-0.488654542486777
2053632.78896688182683.21103311817316
2063433.86669343047350.133306569526488
2073432.30378584930371.69621415069627
2084138.56282774759892.43717225240113
2093236.5194230213485-4.51942302134854
2103033.1256294785684-3.12562947856845
2113534.3199684727750.68003152722497
2122829.6017488252339-1.6017488252339
2133334.9368594902492-1.93685949024924
2143933.63715442823715.36284557176295
2153634.05131823854781.9486817614522
2163636.3113074592065-0.311307459206451
2173533.03098684998541.96901315001462
2183835.13289873019672.86710126980328
2193332.54333385976140.456666140238642
2203132.6807242125928-1.68072421259284
2213233.5811412534541-1.58114125345413
2223133.3128545026132-2.31285450261324
2233333.9590058345107-0.959005834510654
2243432.55353006096541.44646993903461
2253433.94623851966540.0537614803346173
2263431.61533689671332.38466310328675
2273334.8230244901774-1.82302449017741
2283234.7298793603346-2.72987936033461
2294133.79413613230627.20586386769378
2303432.52878557986581.47121442013416
2313631.67990704080494.32009295919505
2323729.84725925300847.15274074699165
2333630.15875070344585.84124929655424
2342932.2724525569285-3.27245255692852
2353731.10217271514945.89782728485061
2362732.5590232358629-5.5590232358629
2373533.67782917453351.32217082546654
2382830.3593277981941-2.35932779819407
2393533.38127150885511.61872849114491
2402933.9951413091327-4.99514130913271
2413234.5135357550216-2.5135357550216
2423631.78361043836464.21638956163541
2431926.5843209478965-7.58432094789653
2442126.1514920041155-5.15149200411553
2453133.5470730928055-2.54707309280551
2463332.21123255617130.788767443828725
2473633.32233627281592.6776637271841
2483333.087426689973-0.0874266899729551
2493732.95887965537344.04112034462657
2503433.36353825713080.636461742869187
2513535.5882410864717-0.588241086471681
2523132.4552963999526-1.45529639995256
2533733.41833886522313.58166113477687
2543529.4935473163415.50645268365896
2552731.8243843406013-4.82438434060133
2563435.2932071392496-1.29320713924963
2574034.08745371316995.91254628683015
2582933.0774176817518-4.07741768175179
2593833.8116064734584.18839352654199
2603433.00982632046350.9901736795365
2612130.2076534929131-9.20765349291308
2623632.38911046231633.6108895376837
2633833.80706720178374.19293279821635
2643030.611784856652-0.611784856651961
2653534.32769271627810.672307283721856
2663029.96767740037730.0323225996227195
2673633.47931797688512.52068202311494
2683435.6580400780149-1.65804007801487
2693534.93136631535170.0686336846482713
2703433.67039127995350.329608720046461
2713235.9209562482493-3.92095624824928
2723329.81385864665973.1861413533403
2733333.3763055719761-0.376305571976085
2742631.8326769824641-5.83267698246408
2753536.4600831415819-1.46008314158187
2762123.5971598288855-2.59715982888549
2773834.17371020792843.8262897920716
2783533.20639279842951.79360720157051
2793333.5962167713682-0.596216771368156
2803734.21711982249822.78288017750178
2813832.94347662819515.05652337180492
2823434.3615971222946-0.361597122294596
2832731.0740023731258-4.07400237312576
2841625.9328401957338-9.93284019573377
2854038.07477011364741.92522988635263
2863634.27467873721461.72532126278536
2874237.41418313268024.58581686731984
2883033.0416868508572-3.04168685085721






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.8367679496485560.3264641007028870.163232050351444
110.8245786770122370.3508426459755270.175421322987763
120.8062578847888240.3874842304223520.193742115211176
130.8396963988813750.3206072022372510.160303601118625
140.7810495593721190.4379008812557620.218950440627881
150.7969387561078910.4061224877842170.203061243892109
160.7624183573749360.4751632852501290.237581642625064
170.6929754808624950.614049038275010.307024519137505
180.6157111091010480.7685777817979040.384288890898952
190.5743600276705050.8512799446589910.425639972329496
200.5613882919183830.8772234161632330.438611708081617
210.5738616564712560.8522766870574870.426138343528744
220.5333550186694950.933289962661010.466644981330505
230.4873757521082480.9747515042164970.512624247891752
240.4148990399010680.8297980798021370.585100960098932
250.4408979971635190.8817959943270370.559102002836481
260.6547221788450390.6905556423099230.345277821154961
270.5918300355850020.8163399288299970.408169964414998
280.5597157393846050.880568521230790.440284260615395
290.5274125435614780.9451749128770430.472587456438521
300.4666572733912070.9333145467824130.533342726608793
310.4617576957085160.9235153914170320.538242304291484
320.6061443732686880.7877112534626230.393855626731312
330.5891413133621310.8217173732757380.410858686637869
340.557300879002320.8853982419953610.44269912099768
350.5110789370717430.9778421258565140.488921062928257
360.4571283047761160.9142566095522330.542871695223883
370.4148665422430550.8297330844861090.585133457756945
380.3894947528966340.7789895057932680.610505247103366
390.4946154572970370.9892309145940750.505384542702963
400.4415865375155210.8831730750310410.558413462484479
410.4109372184108050.821874436821610.589062781589195
420.3608629437618640.7217258875237280.639137056238136
430.3219497303172190.6438994606344370.678050269682781
440.282267024485970.5645340489719410.71773297551403
450.3539669800898670.7079339601797340.646033019910133
460.3770697433292760.7541394866585510.622930256670724
470.3482020533745480.6964041067490970.651797946625452
480.3199908910017720.6399817820035450.680009108998228
490.2791295105126190.5582590210252390.720870489487381
500.2955883620852470.5911767241704940.704411637914753
510.3264784077406770.6529568154813550.673521592259323
520.295358539933030.590717079866060.70464146006697
530.2621947538481910.5243895076963820.737805246151809
540.2385740546810740.4771481093621480.761425945318926
550.2043557089389050.4087114178778110.795644291061095
560.1840727773069870.3681455546139740.815927222693013
570.1907620894684450.381524178936890.809237910531555
580.2769951208031460.5539902416062920.723004879196854
590.2502777657032980.5005555314065950.749722234296702
600.2166749677835140.4333499355670280.783325032216486
610.1950201162877240.3900402325754490.804979883712276
620.1864601313161790.3729202626323580.813539868683821
630.1606595319969980.3213190639939960.839340468003002
640.1637541905138880.3275083810277750.836245809486112
650.1394157621612350.278831524322470.860584237838765
660.1194447846833430.2388895693666860.880555215316657
670.09982804821710240.1996560964342050.900171951782898
680.1057364908369810.2114729816739610.894263509163019
690.1044283433559730.2088566867119460.895571656644027
700.08975488571693190.1795097714338640.910245114283068
710.09281098705709030.1856219741141810.90718901294291
720.1181320780176580.2362641560353160.881867921982342
730.1158848117211820.2317696234423650.884115188278818
740.09734650387646610.1946930077529320.902653496123534
750.08452647749174640.1690529549834930.915473522508254
760.1121189503387070.2242379006774150.887881049661293
770.09539796135829880.1907959227165980.904602038641701
780.0800677748350230.1601355496700460.919932225164977
790.1032694052696160.2065388105392320.896730594730384
800.1196824832108280.2393649664216570.880317516789171
810.1133882296633790.2267764593267580.886611770336621
820.09693276798768530.1938655359753710.903067232012315
830.09002272296103080.1800454459220620.909977277038969
840.08506304724829330.1701260944965870.914936952751707
850.07308238080886220.1461647616177240.926917619191138
860.06348615129396610.1269723025879320.936513848706034
870.05546883430767770.1109376686153550.944531165692322
880.07029126764574420.1405825352914880.929708732354256
890.05835278270655430.1167055654131090.941647217293446
900.0608555265054710.1217110530109420.939144473494529
910.05409682071542640.1081936414308530.945903179284574
920.04890102013845910.09780204027691810.951098979861541
930.04064081122575130.08128162245150260.959359188774249
940.03987780509281880.07975561018563760.960122194907181
950.03964825584124590.07929651168249190.960351744158754
960.03564693156115810.07129386312231630.964353068438842
970.02996932713945870.05993865427891730.970030672860541
980.02552401932330020.05104803864660030.9744759806767
990.02590307955317250.0518061591063450.974096920446827
1000.02366427669335430.04732855338670860.976335723306646
1010.02008296653012250.04016593306024490.979917033469878
1020.0164756623644280.0329513247288560.983524337635572
1030.01338689268701230.02677378537402470.986613107312988
1040.0141655660564490.02833113211289810.985834433943551
1050.03092658228251220.06185316456502440.969073417717488
1060.02852508211880760.05705016423761520.971474917881192
1070.03127284948268910.06254569896537820.968727150517311
1080.02583912276538750.0516782455307750.974160877234613
1090.04420224320872770.08840448641745550.955797756791272
1100.05268027895038040.1053605579007610.94731972104962
1110.04996761356976290.09993522713952590.950032386430237
1120.07174585978581710.1434917195716340.928254140214183
1130.07005097514524450.1401019502904890.929949024854756
1140.06438140097463120.1287628019492620.935618599025369
1150.06521471711571240.1304294342314250.934785282884288
1160.06222169027738010.124443380554760.93777830972262
1170.05351669121784070.1070333824356810.946483308782159
1180.04998663522225960.09997327044451930.95001336477774
1190.04567854951558090.09135709903116170.954321450484419
1200.0389662901811260.0779325803622520.961033709818874
1210.03540381919943350.0708076383988670.964596180800567
1220.02963499560104690.05926999120209380.970365004398953
1230.02838981911432620.05677963822865250.971610180885674
1240.02688076887997970.05376153775995930.97311923112002
1250.03307336833907010.06614673667814020.96692663166093
1260.05867791344866070.1173558268973210.941322086551339
1270.05585050500596440.1117010100119290.944149494994036
1280.04936720417366180.09873440834732360.950632795826338
1290.0465809218009320.0931618436018640.953419078199068
1300.05081795180510060.1016359036102010.949182048194899
1310.05317708707451440.1063541741490290.946822912925486
1320.06732596081976620.1346519216395320.932674039180234
1330.05754236721237610.1150847344247520.942457632787624
1340.04882549932614490.09765099865228970.951174500673855
1350.04308581548537050.08617163097074090.95691418451463
1360.03656883694141340.07313767388282690.963431163058587
1370.03740295338916720.07480590677833430.962597046610833
1380.03159400984505950.06318801969011890.968405990154941
1390.03082752753985780.06165505507971560.969172472460142
1400.03015593201007820.06031186402015630.969844067989922
1410.04999501667725560.09999003335451120.950004983322744
1420.06532473594865680.1306494718973140.934675264051343
1430.05836151501063120.1167230300212620.941638484989369
1440.1136494493665960.2272988987331920.886350550633404
1450.1016449290463470.2032898580926940.898355070953653
1460.08971637354735570.1794327470947110.910283626452644
1470.07849871487709540.1569974297541910.921501285122905
1480.0710355284379280.1420710568758560.928964471562072
1490.06379666214610910.1275933242922180.936203337853891
1500.1016599477594710.2033198955189430.898340052240529
1510.09575121930185280.1915024386037060.904248780698147
1520.08607172707952360.1721434541590470.913928272920476
1530.09785606753623670.1957121350724730.902143932463763
1540.09011808111535310.1802361622307060.909881918884647
1550.08691140003682180.1738228000736440.913088599963178
1560.07947386766444760.1589477353288950.920526132335552
1570.07577892897157940.1515578579431590.924221071028421
1580.06897720035654740.1379544007130950.931022799643453
1590.05896097221181510.117921944423630.941039027788185
1600.0548654780823120.1097309561646240.945134521917688
1610.06221751766008120.1244350353201620.937782482339919
1620.05711235036593270.1142247007318650.942887649634067
1630.08929343507178390.1785868701435680.910706564928216
1640.08371842414675120.1674368482935020.916281575853249
1650.07317034878292170.1463406975658430.926829651217078
1660.06737103199245210.1347420639849040.932628968007548
1670.1300434387546830.2600868775093660.869956561245317
1680.1728391986969560.3456783973939120.827160801303044
1690.1557641592574980.3115283185149960.844235840742502
1700.256307644737070.5126152894741390.74369235526293
1710.2329640300746120.4659280601492230.767035969925388
1720.2945386906317540.5890773812635080.705461309368246
1730.2800486805984570.5600973611969140.719951319401543
1740.3003537302345180.6007074604690350.699646269765482
1750.2748195375254010.5496390750508030.725180462474599
1760.2496462178984410.4992924357968820.750353782101559
1770.2469393618214540.4938787236429070.753060638178546
1780.2222409083069830.4444818166139650.777759091693017
1790.2275950984285570.4551901968571140.772404901571443
1800.2540851161499370.5081702322998730.745914883850063
1810.2899381367065030.5798762734130060.710061863293497
1820.4249112651877640.8498225303755290.575088734812236
1830.4213341238313980.8426682476627950.578665876168602
1840.3968233729456450.7936467458912910.603176627054355
1850.5283335787629970.9433328424740060.471666421237003
1860.5069858648063060.9860282703873870.493014135193693
1870.4883377997396880.9766755994793760.511662200260312
1880.4837562073272770.9675124146545540.516243792672723
1890.452820931263840.905641862527680.54717906873616
1900.4228598654754880.8457197309509770.577140134524512
1910.3902902487204230.7805804974408470.609709751279577
1920.356628980724640.7132579614492810.64337101927536
1930.3280621936700990.6561243873401990.671937806329901
1940.3107652689910460.6215305379820920.689234731008954
1950.3040522561595890.6081045123191780.695947743840411
1960.2726669476889490.5453338953778980.727333052311051
1970.250340624318010.5006812486360210.74965937568199
1980.3769737461809190.7539474923618380.623026253819081
1990.356201126213980.7124022524279610.64379887378602
2000.3284092501232220.6568185002464450.671590749876778
2010.2968521013100380.5937042026200750.703147898689962
2020.2700442855785740.5400885711571470.729955714421426
2030.2429545378511460.4859090757022920.757045462148854
2040.2163262412686130.4326524825372260.783673758731387
2050.2096742939347990.4193485878695980.790325706065201
2060.1841102922502120.3682205845004230.815889707749788
2070.1632199860281170.3264399720562340.836780013971883
2080.1535951170063530.3071902340127050.846404882993647
2090.1912418136129690.3824836272259380.808758186387031
2100.178973044473530.3579460889470590.82102695552647
2110.1558258179865350.311651635973070.844174182013465
2120.1369245874602890.2738491749205780.863075412539711
2130.1231448796364350.2462897592728690.876855120363565
2140.1474865583477280.2949731166954560.852513441652272
2150.1315114091664670.2630228183329330.868488590833533
2160.1184226966253760.2368453932507520.881577303374624
2170.1033080478668420.2066160957336830.896691952133158
2180.09520534075392390.1904106815078480.904794659246076
2190.07948167098593060.1589633419718610.920518329014069
2200.06827949922609510.136558998452190.931720500773905
2210.06285965409638610.1257193081927720.937140345903614
2220.05538460343433890.1107692068686780.944615396565661
2230.04557915949803180.09115831899606350.954420840501968
2240.03761745114091870.07523490228183740.962382548859081
2250.03028662532654450.06057325065308890.969713374673456
2260.03013626079100780.06027252158201550.969863739208992
2270.03381269535391130.06762539070782250.966187304646089
2280.02794687870438610.05589375740877230.972053121295614
2290.05608326141977170.1121665228395430.943916738580228
2300.04715614691905290.09431229383810580.952843853080947
2310.04915079113802140.09830158227604280.950849208861979
2320.0779752367376570.1559504734753140.922024763262343
2330.1397418833741960.2794837667483910.860258116625804
2340.1313237161260550.2626474322521110.868676283873945
2350.207665166787410.4153303335748190.79233483321259
2360.2476967542661860.4953935085323720.752303245733814
2370.2147565717754290.4295131435508580.785243428224571
2380.187748333498780.3754966669975590.81225166650122
2390.1695991498745530.3391982997491050.830400850125447
2400.2149296461554390.4298592923108780.785070353844561
2410.2038859140249310.4077718280498610.796114085975069
2420.2175716253361880.4351432506723750.782428374663812
2430.2584028801334090.5168057602668180.741597119866591
2440.2444181597292940.4888363194585880.755581840270706
2450.2295404771448520.4590809542897050.770459522855148
2460.1952854647819390.3905709295638780.804714535218061
2470.1759458870047750.351891774009550.824054112995225
2480.1451440301711810.2902880603423630.854855969828819
2490.1513365519221570.3026731038443140.848663448077843
2500.123751550984910.247503101969820.87624844901509
2510.1053271640065950.2106543280131890.894672835993405
2520.0874109042506170.1748218085012340.912589095749383
2530.08682336020703670.1736467204140730.913176639792963
2540.1522972120355480.3045944240710970.847702787964452
2550.165270166824670.3305403336493410.83472983317533
2560.1450471103021250.2900942206042510.854952889697875
2570.2154232989869190.4308465979738390.784576701013081
2580.232675963245210.4653519264904210.76732403675479
2590.2644255278947360.5288510557894720.735574472105264
2600.2312569621597110.4625139243194220.768743037840289
2610.5489477095408010.9021045809183980.451052290459199
2620.5776274863869060.8447450272261870.422372513613094
2630.6135088635223350.7729822729553290.386491136477665
2640.5853830308456540.8292339383086920.414616969154346
2650.5332314103277980.9335371793444040.466768589672202
2660.5216109167122890.9567781665754220.478389083287711
2670.644523282036980.710953435926040.35547671796302
2680.5662774179016320.8674451641967360.433722582098368
2690.4831121681007530.9662243362015050.516887831899247
2700.4497038743388630.8994077486777250.550296125661137
2710.3843697216765180.7687394433530360.615630278323482
2720.7960949264835540.4078101470328930.203905073516447
2730.7253264920089120.5493470159821750.274673507991088
2740.6422430722710480.7155138554579050.357756927728952
2750.5625824603608980.8748350792782030.437417539639102
2760.6514299144784990.6971401710430010.348570085521501
2770.6287900861257630.7424198277484740.371209913874237
2780.4592407463626150.9184814927252310.540759253637385

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.836767949648556 & 0.326464100702887 & 0.163232050351444 \tabularnewline
11 & 0.824578677012237 & 0.350842645975527 & 0.175421322987763 \tabularnewline
12 & 0.806257884788824 & 0.387484230422352 & 0.193742115211176 \tabularnewline
13 & 0.839696398881375 & 0.320607202237251 & 0.160303601118625 \tabularnewline
14 & 0.781049559372119 & 0.437900881255762 & 0.218950440627881 \tabularnewline
15 & 0.796938756107891 & 0.406122487784217 & 0.203061243892109 \tabularnewline
16 & 0.762418357374936 & 0.475163285250129 & 0.237581642625064 \tabularnewline
17 & 0.692975480862495 & 0.61404903827501 & 0.307024519137505 \tabularnewline
18 & 0.615711109101048 & 0.768577781797904 & 0.384288890898952 \tabularnewline
19 & 0.574360027670505 & 0.851279944658991 & 0.425639972329496 \tabularnewline
20 & 0.561388291918383 & 0.877223416163233 & 0.438611708081617 \tabularnewline
21 & 0.573861656471256 & 0.852276687057487 & 0.426138343528744 \tabularnewline
22 & 0.533355018669495 & 0.93328996266101 & 0.466644981330505 \tabularnewline
23 & 0.487375752108248 & 0.974751504216497 & 0.512624247891752 \tabularnewline
24 & 0.414899039901068 & 0.829798079802137 & 0.585100960098932 \tabularnewline
25 & 0.440897997163519 & 0.881795994327037 & 0.559102002836481 \tabularnewline
26 & 0.654722178845039 & 0.690555642309923 & 0.345277821154961 \tabularnewline
27 & 0.591830035585002 & 0.816339928829997 & 0.408169964414998 \tabularnewline
28 & 0.559715739384605 & 0.88056852123079 & 0.440284260615395 \tabularnewline
29 & 0.527412543561478 & 0.945174912877043 & 0.472587456438521 \tabularnewline
30 & 0.466657273391207 & 0.933314546782413 & 0.533342726608793 \tabularnewline
31 & 0.461757695708516 & 0.923515391417032 & 0.538242304291484 \tabularnewline
32 & 0.606144373268688 & 0.787711253462623 & 0.393855626731312 \tabularnewline
33 & 0.589141313362131 & 0.821717373275738 & 0.410858686637869 \tabularnewline
34 & 0.55730087900232 & 0.885398241995361 & 0.44269912099768 \tabularnewline
35 & 0.511078937071743 & 0.977842125856514 & 0.488921062928257 \tabularnewline
36 & 0.457128304776116 & 0.914256609552233 & 0.542871695223883 \tabularnewline
37 & 0.414866542243055 & 0.829733084486109 & 0.585133457756945 \tabularnewline
38 & 0.389494752896634 & 0.778989505793268 & 0.610505247103366 \tabularnewline
39 & 0.494615457297037 & 0.989230914594075 & 0.505384542702963 \tabularnewline
40 & 0.441586537515521 & 0.883173075031041 & 0.558413462484479 \tabularnewline
41 & 0.410937218410805 & 0.82187443682161 & 0.589062781589195 \tabularnewline
42 & 0.360862943761864 & 0.721725887523728 & 0.639137056238136 \tabularnewline
43 & 0.321949730317219 & 0.643899460634437 & 0.678050269682781 \tabularnewline
44 & 0.28226702448597 & 0.564534048971941 & 0.71773297551403 \tabularnewline
45 & 0.353966980089867 & 0.707933960179734 & 0.646033019910133 \tabularnewline
46 & 0.377069743329276 & 0.754139486658551 & 0.622930256670724 \tabularnewline
47 & 0.348202053374548 & 0.696404106749097 & 0.651797946625452 \tabularnewline
48 & 0.319990891001772 & 0.639981782003545 & 0.680009108998228 \tabularnewline
49 & 0.279129510512619 & 0.558259021025239 & 0.720870489487381 \tabularnewline
50 & 0.295588362085247 & 0.591176724170494 & 0.704411637914753 \tabularnewline
51 & 0.326478407740677 & 0.652956815481355 & 0.673521592259323 \tabularnewline
52 & 0.29535853993303 & 0.59071707986606 & 0.70464146006697 \tabularnewline
53 & 0.262194753848191 & 0.524389507696382 & 0.737805246151809 \tabularnewline
54 & 0.238574054681074 & 0.477148109362148 & 0.761425945318926 \tabularnewline
55 & 0.204355708938905 & 0.408711417877811 & 0.795644291061095 \tabularnewline
56 & 0.184072777306987 & 0.368145554613974 & 0.815927222693013 \tabularnewline
57 & 0.190762089468445 & 0.38152417893689 & 0.809237910531555 \tabularnewline
58 & 0.276995120803146 & 0.553990241606292 & 0.723004879196854 \tabularnewline
59 & 0.250277765703298 & 0.500555531406595 & 0.749722234296702 \tabularnewline
60 & 0.216674967783514 & 0.433349935567028 & 0.783325032216486 \tabularnewline
61 & 0.195020116287724 & 0.390040232575449 & 0.804979883712276 \tabularnewline
62 & 0.186460131316179 & 0.372920262632358 & 0.813539868683821 \tabularnewline
63 & 0.160659531996998 & 0.321319063993996 & 0.839340468003002 \tabularnewline
64 & 0.163754190513888 & 0.327508381027775 & 0.836245809486112 \tabularnewline
65 & 0.139415762161235 & 0.27883152432247 & 0.860584237838765 \tabularnewline
66 & 0.119444784683343 & 0.238889569366686 & 0.880555215316657 \tabularnewline
67 & 0.0998280482171024 & 0.199656096434205 & 0.900171951782898 \tabularnewline
68 & 0.105736490836981 & 0.211472981673961 & 0.894263509163019 \tabularnewline
69 & 0.104428343355973 & 0.208856686711946 & 0.895571656644027 \tabularnewline
70 & 0.0897548857169319 & 0.179509771433864 & 0.910245114283068 \tabularnewline
71 & 0.0928109870570903 & 0.185621974114181 & 0.90718901294291 \tabularnewline
72 & 0.118132078017658 & 0.236264156035316 & 0.881867921982342 \tabularnewline
73 & 0.115884811721182 & 0.231769623442365 & 0.884115188278818 \tabularnewline
74 & 0.0973465038764661 & 0.194693007752932 & 0.902653496123534 \tabularnewline
75 & 0.0845264774917464 & 0.169052954983493 & 0.915473522508254 \tabularnewline
76 & 0.112118950338707 & 0.224237900677415 & 0.887881049661293 \tabularnewline
77 & 0.0953979613582988 & 0.190795922716598 & 0.904602038641701 \tabularnewline
78 & 0.080067774835023 & 0.160135549670046 & 0.919932225164977 \tabularnewline
79 & 0.103269405269616 & 0.206538810539232 & 0.896730594730384 \tabularnewline
80 & 0.119682483210828 & 0.239364966421657 & 0.880317516789171 \tabularnewline
81 & 0.113388229663379 & 0.226776459326758 & 0.886611770336621 \tabularnewline
82 & 0.0969327679876853 & 0.193865535975371 & 0.903067232012315 \tabularnewline
83 & 0.0900227229610308 & 0.180045445922062 & 0.909977277038969 \tabularnewline
84 & 0.0850630472482933 & 0.170126094496587 & 0.914936952751707 \tabularnewline
85 & 0.0730823808088622 & 0.146164761617724 & 0.926917619191138 \tabularnewline
86 & 0.0634861512939661 & 0.126972302587932 & 0.936513848706034 \tabularnewline
87 & 0.0554688343076777 & 0.110937668615355 & 0.944531165692322 \tabularnewline
88 & 0.0702912676457442 & 0.140582535291488 & 0.929708732354256 \tabularnewline
89 & 0.0583527827065543 & 0.116705565413109 & 0.941647217293446 \tabularnewline
90 & 0.060855526505471 & 0.121711053010942 & 0.939144473494529 \tabularnewline
91 & 0.0540968207154264 & 0.108193641430853 & 0.945903179284574 \tabularnewline
92 & 0.0489010201384591 & 0.0978020402769181 & 0.951098979861541 \tabularnewline
93 & 0.0406408112257513 & 0.0812816224515026 & 0.959359188774249 \tabularnewline
94 & 0.0398778050928188 & 0.0797556101856376 & 0.960122194907181 \tabularnewline
95 & 0.0396482558412459 & 0.0792965116824919 & 0.960351744158754 \tabularnewline
96 & 0.0356469315611581 & 0.0712938631223163 & 0.964353068438842 \tabularnewline
97 & 0.0299693271394587 & 0.0599386542789173 & 0.970030672860541 \tabularnewline
98 & 0.0255240193233002 & 0.0510480386466003 & 0.9744759806767 \tabularnewline
99 & 0.0259030795531725 & 0.051806159106345 & 0.974096920446827 \tabularnewline
100 & 0.0236642766933543 & 0.0473285533867086 & 0.976335723306646 \tabularnewline
101 & 0.0200829665301225 & 0.0401659330602449 & 0.979917033469878 \tabularnewline
102 & 0.016475662364428 & 0.032951324728856 & 0.983524337635572 \tabularnewline
103 & 0.0133868926870123 & 0.0267737853740247 & 0.986613107312988 \tabularnewline
104 & 0.014165566056449 & 0.0283311321128981 & 0.985834433943551 \tabularnewline
105 & 0.0309265822825122 & 0.0618531645650244 & 0.969073417717488 \tabularnewline
106 & 0.0285250821188076 & 0.0570501642376152 & 0.971474917881192 \tabularnewline
107 & 0.0312728494826891 & 0.0625456989653782 & 0.968727150517311 \tabularnewline
108 & 0.0258391227653875 & 0.051678245530775 & 0.974160877234613 \tabularnewline
109 & 0.0442022432087277 & 0.0884044864174555 & 0.955797756791272 \tabularnewline
110 & 0.0526802789503804 & 0.105360557900761 & 0.94731972104962 \tabularnewline
111 & 0.0499676135697629 & 0.0999352271395259 & 0.950032386430237 \tabularnewline
112 & 0.0717458597858171 & 0.143491719571634 & 0.928254140214183 \tabularnewline
113 & 0.0700509751452445 & 0.140101950290489 & 0.929949024854756 \tabularnewline
114 & 0.0643814009746312 & 0.128762801949262 & 0.935618599025369 \tabularnewline
115 & 0.0652147171157124 & 0.130429434231425 & 0.934785282884288 \tabularnewline
116 & 0.0622216902773801 & 0.12444338055476 & 0.93777830972262 \tabularnewline
117 & 0.0535166912178407 & 0.107033382435681 & 0.946483308782159 \tabularnewline
118 & 0.0499866352222596 & 0.0999732704445193 & 0.95001336477774 \tabularnewline
119 & 0.0456785495155809 & 0.0913570990311617 & 0.954321450484419 \tabularnewline
120 & 0.038966290181126 & 0.077932580362252 & 0.961033709818874 \tabularnewline
121 & 0.0354038191994335 & 0.070807638398867 & 0.964596180800567 \tabularnewline
122 & 0.0296349956010469 & 0.0592699912020938 & 0.970365004398953 \tabularnewline
123 & 0.0283898191143262 & 0.0567796382286525 & 0.971610180885674 \tabularnewline
124 & 0.0268807688799797 & 0.0537615377599593 & 0.97311923112002 \tabularnewline
125 & 0.0330733683390701 & 0.0661467366781402 & 0.96692663166093 \tabularnewline
126 & 0.0586779134486607 & 0.117355826897321 & 0.941322086551339 \tabularnewline
127 & 0.0558505050059644 & 0.111701010011929 & 0.944149494994036 \tabularnewline
128 & 0.0493672041736618 & 0.0987344083473236 & 0.950632795826338 \tabularnewline
129 & 0.046580921800932 & 0.093161843601864 & 0.953419078199068 \tabularnewline
130 & 0.0508179518051006 & 0.101635903610201 & 0.949182048194899 \tabularnewline
131 & 0.0531770870745144 & 0.106354174149029 & 0.946822912925486 \tabularnewline
132 & 0.0673259608197662 & 0.134651921639532 & 0.932674039180234 \tabularnewline
133 & 0.0575423672123761 & 0.115084734424752 & 0.942457632787624 \tabularnewline
134 & 0.0488254993261449 & 0.0976509986522897 & 0.951174500673855 \tabularnewline
135 & 0.0430858154853705 & 0.0861716309707409 & 0.95691418451463 \tabularnewline
136 & 0.0365688369414134 & 0.0731376738828269 & 0.963431163058587 \tabularnewline
137 & 0.0374029533891672 & 0.0748059067783343 & 0.962597046610833 \tabularnewline
138 & 0.0315940098450595 & 0.0631880196901189 & 0.968405990154941 \tabularnewline
139 & 0.0308275275398578 & 0.0616550550797156 & 0.969172472460142 \tabularnewline
140 & 0.0301559320100782 & 0.0603118640201563 & 0.969844067989922 \tabularnewline
141 & 0.0499950166772556 & 0.0999900333545112 & 0.950004983322744 \tabularnewline
142 & 0.0653247359486568 & 0.130649471897314 & 0.934675264051343 \tabularnewline
143 & 0.0583615150106312 & 0.116723030021262 & 0.941638484989369 \tabularnewline
144 & 0.113649449366596 & 0.227298898733192 & 0.886350550633404 \tabularnewline
145 & 0.101644929046347 & 0.203289858092694 & 0.898355070953653 \tabularnewline
146 & 0.0897163735473557 & 0.179432747094711 & 0.910283626452644 \tabularnewline
147 & 0.0784987148770954 & 0.156997429754191 & 0.921501285122905 \tabularnewline
148 & 0.071035528437928 & 0.142071056875856 & 0.928964471562072 \tabularnewline
149 & 0.0637966621461091 & 0.127593324292218 & 0.936203337853891 \tabularnewline
150 & 0.101659947759471 & 0.203319895518943 & 0.898340052240529 \tabularnewline
151 & 0.0957512193018528 & 0.191502438603706 & 0.904248780698147 \tabularnewline
152 & 0.0860717270795236 & 0.172143454159047 & 0.913928272920476 \tabularnewline
153 & 0.0978560675362367 & 0.195712135072473 & 0.902143932463763 \tabularnewline
154 & 0.0901180811153531 & 0.180236162230706 & 0.909881918884647 \tabularnewline
155 & 0.0869114000368218 & 0.173822800073644 & 0.913088599963178 \tabularnewline
156 & 0.0794738676644476 & 0.158947735328895 & 0.920526132335552 \tabularnewline
157 & 0.0757789289715794 & 0.151557857943159 & 0.924221071028421 \tabularnewline
158 & 0.0689772003565474 & 0.137954400713095 & 0.931022799643453 \tabularnewline
159 & 0.0589609722118151 & 0.11792194442363 & 0.941039027788185 \tabularnewline
160 & 0.054865478082312 & 0.109730956164624 & 0.945134521917688 \tabularnewline
161 & 0.0622175176600812 & 0.124435035320162 & 0.937782482339919 \tabularnewline
162 & 0.0571123503659327 & 0.114224700731865 & 0.942887649634067 \tabularnewline
163 & 0.0892934350717839 & 0.178586870143568 & 0.910706564928216 \tabularnewline
164 & 0.0837184241467512 & 0.167436848293502 & 0.916281575853249 \tabularnewline
165 & 0.0731703487829217 & 0.146340697565843 & 0.926829651217078 \tabularnewline
166 & 0.0673710319924521 & 0.134742063984904 & 0.932628968007548 \tabularnewline
167 & 0.130043438754683 & 0.260086877509366 & 0.869956561245317 \tabularnewline
168 & 0.172839198696956 & 0.345678397393912 & 0.827160801303044 \tabularnewline
169 & 0.155764159257498 & 0.311528318514996 & 0.844235840742502 \tabularnewline
170 & 0.25630764473707 & 0.512615289474139 & 0.74369235526293 \tabularnewline
171 & 0.232964030074612 & 0.465928060149223 & 0.767035969925388 \tabularnewline
172 & 0.294538690631754 & 0.589077381263508 & 0.705461309368246 \tabularnewline
173 & 0.280048680598457 & 0.560097361196914 & 0.719951319401543 \tabularnewline
174 & 0.300353730234518 & 0.600707460469035 & 0.699646269765482 \tabularnewline
175 & 0.274819537525401 & 0.549639075050803 & 0.725180462474599 \tabularnewline
176 & 0.249646217898441 & 0.499292435796882 & 0.750353782101559 \tabularnewline
177 & 0.246939361821454 & 0.493878723642907 & 0.753060638178546 \tabularnewline
178 & 0.222240908306983 & 0.444481816613965 & 0.777759091693017 \tabularnewline
179 & 0.227595098428557 & 0.455190196857114 & 0.772404901571443 \tabularnewline
180 & 0.254085116149937 & 0.508170232299873 & 0.745914883850063 \tabularnewline
181 & 0.289938136706503 & 0.579876273413006 & 0.710061863293497 \tabularnewline
182 & 0.424911265187764 & 0.849822530375529 & 0.575088734812236 \tabularnewline
183 & 0.421334123831398 & 0.842668247662795 & 0.578665876168602 \tabularnewline
184 & 0.396823372945645 & 0.793646745891291 & 0.603176627054355 \tabularnewline
185 & 0.528333578762997 & 0.943332842474006 & 0.471666421237003 \tabularnewline
186 & 0.506985864806306 & 0.986028270387387 & 0.493014135193693 \tabularnewline
187 & 0.488337799739688 & 0.976675599479376 & 0.511662200260312 \tabularnewline
188 & 0.483756207327277 & 0.967512414654554 & 0.516243792672723 \tabularnewline
189 & 0.45282093126384 & 0.90564186252768 & 0.54717906873616 \tabularnewline
190 & 0.422859865475488 & 0.845719730950977 & 0.577140134524512 \tabularnewline
191 & 0.390290248720423 & 0.780580497440847 & 0.609709751279577 \tabularnewline
192 & 0.35662898072464 & 0.713257961449281 & 0.64337101927536 \tabularnewline
193 & 0.328062193670099 & 0.656124387340199 & 0.671937806329901 \tabularnewline
194 & 0.310765268991046 & 0.621530537982092 & 0.689234731008954 \tabularnewline
195 & 0.304052256159589 & 0.608104512319178 & 0.695947743840411 \tabularnewline
196 & 0.272666947688949 & 0.545333895377898 & 0.727333052311051 \tabularnewline
197 & 0.25034062431801 & 0.500681248636021 & 0.74965937568199 \tabularnewline
198 & 0.376973746180919 & 0.753947492361838 & 0.623026253819081 \tabularnewline
199 & 0.35620112621398 & 0.712402252427961 & 0.64379887378602 \tabularnewline
200 & 0.328409250123222 & 0.656818500246445 & 0.671590749876778 \tabularnewline
201 & 0.296852101310038 & 0.593704202620075 & 0.703147898689962 \tabularnewline
202 & 0.270044285578574 & 0.540088571157147 & 0.729955714421426 \tabularnewline
203 & 0.242954537851146 & 0.485909075702292 & 0.757045462148854 \tabularnewline
204 & 0.216326241268613 & 0.432652482537226 & 0.783673758731387 \tabularnewline
205 & 0.209674293934799 & 0.419348587869598 & 0.790325706065201 \tabularnewline
206 & 0.184110292250212 & 0.368220584500423 & 0.815889707749788 \tabularnewline
207 & 0.163219986028117 & 0.326439972056234 & 0.836780013971883 \tabularnewline
208 & 0.153595117006353 & 0.307190234012705 & 0.846404882993647 \tabularnewline
209 & 0.191241813612969 & 0.382483627225938 & 0.808758186387031 \tabularnewline
210 & 0.17897304447353 & 0.357946088947059 & 0.82102695552647 \tabularnewline
211 & 0.155825817986535 & 0.31165163597307 & 0.844174182013465 \tabularnewline
212 & 0.136924587460289 & 0.273849174920578 & 0.863075412539711 \tabularnewline
213 & 0.123144879636435 & 0.246289759272869 & 0.876855120363565 \tabularnewline
214 & 0.147486558347728 & 0.294973116695456 & 0.852513441652272 \tabularnewline
215 & 0.131511409166467 & 0.263022818332933 & 0.868488590833533 \tabularnewline
216 & 0.118422696625376 & 0.236845393250752 & 0.881577303374624 \tabularnewline
217 & 0.103308047866842 & 0.206616095733683 & 0.896691952133158 \tabularnewline
218 & 0.0952053407539239 & 0.190410681507848 & 0.904794659246076 \tabularnewline
219 & 0.0794816709859306 & 0.158963341971861 & 0.920518329014069 \tabularnewline
220 & 0.0682794992260951 & 0.13655899845219 & 0.931720500773905 \tabularnewline
221 & 0.0628596540963861 & 0.125719308192772 & 0.937140345903614 \tabularnewline
222 & 0.0553846034343389 & 0.110769206868678 & 0.944615396565661 \tabularnewline
223 & 0.0455791594980318 & 0.0911583189960635 & 0.954420840501968 \tabularnewline
224 & 0.0376174511409187 & 0.0752349022818374 & 0.962382548859081 \tabularnewline
225 & 0.0302866253265445 & 0.0605732506530889 & 0.969713374673456 \tabularnewline
226 & 0.0301362607910078 & 0.0602725215820155 & 0.969863739208992 \tabularnewline
227 & 0.0338126953539113 & 0.0676253907078225 & 0.966187304646089 \tabularnewline
228 & 0.0279468787043861 & 0.0558937574087723 & 0.972053121295614 \tabularnewline
229 & 0.0560832614197717 & 0.112166522839543 & 0.943916738580228 \tabularnewline
230 & 0.0471561469190529 & 0.0943122938381058 & 0.952843853080947 \tabularnewline
231 & 0.0491507911380214 & 0.0983015822760428 & 0.950849208861979 \tabularnewline
232 & 0.077975236737657 & 0.155950473475314 & 0.922024763262343 \tabularnewline
233 & 0.139741883374196 & 0.279483766748391 & 0.860258116625804 \tabularnewline
234 & 0.131323716126055 & 0.262647432252111 & 0.868676283873945 \tabularnewline
235 & 0.20766516678741 & 0.415330333574819 & 0.79233483321259 \tabularnewline
236 & 0.247696754266186 & 0.495393508532372 & 0.752303245733814 \tabularnewline
237 & 0.214756571775429 & 0.429513143550858 & 0.785243428224571 \tabularnewline
238 & 0.18774833349878 & 0.375496666997559 & 0.81225166650122 \tabularnewline
239 & 0.169599149874553 & 0.339198299749105 & 0.830400850125447 \tabularnewline
240 & 0.214929646155439 & 0.429859292310878 & 0.785070353844561 \tabularnewline
241 & 0.203885914024931 & 0.407771828049861 & 0.796114085975069 \tabularnewline
242 & 0.217571625336188 & 0.435143250672375 & 0.782428374663812 \tabularnewline
243 & 0.258402880133409 & 0.516805760266818 & 0.741597119866591 \tabularnewline
244 & 0.244418159729294 & 0.488836319458588 & 0.755581840270706 \tabularnewline
245 & 0.229540477144852 & 0.459080954289705 & 0.770459522855148 \tabularnewline
246 & 0.195285464781939 & 0.390570929563878 & 0.804714535218061 \tabularnewline
247 & 0.175945887004775 & 0.35189177400955 & 0.824054112995225 \tabularnewline
248 & 0.145144030171181 & 0.290288060342363 & 0.854855969828819 \tabularnewline
249 & 0.151336551922157 & 0.302673103844314 & 0.848663448077843 \tabularnewline
250 & 0.12375155098491 & 0.24750310196982 & 0.87624844901509 \tabularnewline
251 & 0.105327164006595 & 0.210654328013189 & 0.894672835993405 \tabularnewline
252 & 0.087410904250617 & 0.174821808501234 & 0.912589095749383 \tabularnewline
253 & 0.0868233602070367 & 0.173646720414073 & 0.913176639792963 \tabularnewline
254 & 0.152297212035548 & 0.304594424071097 & 0.847702787964452 \tabularnewline
255 & 0.16527016682467 & 0.330540333649341 & 0.83472983317533 \tabularnewline
256 & 0.145047110302125 & 0.290094220604251 & 0.854952889697875 \tabularnewline
257 & 0.215423298986919 & 0.430846597973839 & 0.784576701013081 \tabularnewline
258 & 0.23267596324521 & 0.465351926490421 & 0.76732403675479 \tabularnewline
259 & 0.264425527894736 & 0.528851055789472 & 0.735574472105264 \tabularnewline
260 & 0.231256962159711 & 0.462513924319422 & 0.768743037840289 \tabularnewline
261 & 0.548947709540801 & 0.902104580918398 & 0.451052290459199 \tabularnewline
262 & 0.577627486386906 & 0.844745027226187 & 0.422372513613094 \tabularnewline
263 & 0.613508863522335 & 0.772982272955329 & 0.386491136477665 \tabularnewline
264 & 0.585383030845654 & 0.829233938308692 & 0.414616969154346 \tabularnewline
265 & 0.533231410327798 & 0.933537179344404 & 0.466768589672202 \tabularnewline
266 & 0.521610916712289 & 0.956778166575422 & 0.478389083287711 \tabularnewline
267 & 0.64452328203698 & 0.71095343592604 & 0.35547671796302 \tabularnewline
268 & 0.566277417901632 & 0.867445164196736 & 0.433722582098368 \tabularnewline
269 & 0.483112168100753 & 0.966224336201505 & 0.516887831899247 \tabularnewline
270 & 0.449703874338863 & 0.899407748677725 & 0.550296125661137 \tabularnewline
271 & 0.384369721676518 & 0.768739443353036 & 0.615630278323482 \tabularnewline
272 & 0.796094926483554 & 0.407810147032893 & 0.203905073516447 \tabularnewline
273 & 0.725326492008912 & 0.549347015982175 & 0.274673507991088 \tabularnewline
274 & 0.642243072271048 & 0.715513855457905 & 0.357756927728952 \tabularnewline
275 & 0.562582460360898 & 0.874835079278203 & 0.437417539639102 \tabularnewline
276 & 0.651429914478499 & 0.697140171043001 & 0.348570085521501 \tabularnewline
277 & 0.628790086125763 & 0.742419827748474 & 0.371209913874237 \tabularnewline
278 & 0.459240746362615 & 0.918481492725231 & 0.540759253637385 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198137&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]0.836767949648556[/C][C]0.326464100702887[/C][C]0.163232050351444[/C][/ROW]
[ROW][C]11[/C][C]0.824578677012237[/C][C]0.350842645975527[/C][C]0.175421322987763[/C][/ROW]
[ROW][C]12[/C][C]0.806257884788824[/C][C]0.387484230422352[/C][C]0.193742115211176[/C][/ROW]
[ROW][C]13[/C][C]0.839696398881375[/C][C]0.320607202237251[/C][C]0.160303601118625[/C][/ROW]
[ROW][C]14[/C][C]0.781049559372119[/C][C]0.437900881255762[/C][C]0.218950440627881[/C][/ROW]
[ROW][C]15[/C][C]0.796938756107891[/C][C]0.406122487784217[/C][C]0.203061243892109[/C][/ROW]
[ROW][C]16[/C][C]0.762418357374936[/C][C]0.475163285250129[/C][C]0.237581642625064[/C][/ROW]
[ROW][C]17[/C][C]0.692975480862495[/C][C]0.61404903827501[/C][C]0.307024519137505[/C][/ROW]
[ROW][C]18[/C][C]0.615711109101048[/C][C]0.768577781797904[/C][C]0.384288890898952[/C][/ROW]
[ROW][C]19[/C][C]0.574360027670505[/C][C]0.851279944658991[/C][C]0.425639972329496[/C][/ROW]
[ROW][C]20[/C][C]0.561388291918383[/C][C]0.877223416163233[/C][C]0.438611708081617[/C][/ROW]
[ROW][C]21[/C][C]0.573861656471256[/C][C]0.852276687057487[/C][C]0.426138343528744[/C][/ROW]
[ROW][C]22[/C][C]0.533355018669495[/C][C]0.93328996266101[/C][C]0.466644981330505[/C][/ROW]
[ROW][C]23[/C][C]0.487375752108248[/C][C]0.974751504216497[/C][C]0.512624247891752[/C][/ROW]
[ROW][C]24[/C][C]0.414899039901068[/C][C]0.829798079802137[/C][C]0.585100960098932[/C][/ROW]
[ROW][C]25[/C][C]0.440897997163519[/C][C]0.881795994327037[/C][C]0.559102002836481[/C][/ROW]
[ROW][C]26[/C][C]0.654722178845039[/C][C]0.690555642309923[/C][C]0.345277821154961[/C][/ROW]
[ROW][C]27[/C][C]0.591830035585002[/C][C]0.816339928829997[/C][C]0.408169964414998[/C][/ROW]
[ROW][C]28[/C][C]0.559715739384605[/C][C]0.88056852123079[/C][C]0.440284260615395[/C][/ROW]
[ROW][C]29[/C][C]0.527412543561478[/C][C]0.945174912877043[/C][C]0.472587456438521[/C][/ROW]
[ROW][C]30[/C][C]0.466657273391207[/C][C]0.933314546782413[/C][C]0.533342726608793[/C][/ROW]
[ROW][C]31[/C][C]0.461757695708516[/C][C]0.923515391417032[/C][C]0.538242304291484[/C][/ROW]
[ROW][C]32[/C][C]0.606144373268688[/C][C]0.787711253462623[/C][C]0.393855626731312[/C][/ROW]
[ROW][C]33[/C][C]0.589141313362131[/C][C]0.821717373275738[/C][C]0.410858686637869[/C][/ROW]
[ROW][C]34[/C][C]0.55730087900232[/C][C]0.885398241995361[/C][C]0.44269912099768[/C][/ROW]
[ROW][C]35[/C][C]0.511078937071743[/C][C]0.977842125856514[/C][C]0.488921062928257[/C][/ROW]
[ROW][C]36[/C][C]0.457128304776116[/C][C]0.914256609552233[/C][C]0.542871695223883[/C][/ROW]
[ROW][C]37[/C][C]0.414866542243055[/C][C]0.829733084486109[/C][C]0.585133457756945[/C][/ROW]
[ROW][C]38[/C][C]0.389494752896634[/C][C]0.778989505793268[/C][C]0.610505247103366[/C][/ROW]
[ROW][C]39[/C][C]0.494615457297037[/C][C]0.989230914594075[/C][C]0.505384542702963[/C][/ROW]
[ROW][C]40[/C][C]0.441586537515521[/C][C]0.883173075031041[/C][C]0.558413462484479[/C][/ROW]
[ROW][C]41[/C][C]0.410937218410805[/C][C]0.82187443682161[/C][C]0.589062781589195[/C][/ROW]
[ROW][C]42[/C][C]0.360862943761864[/C][C]0.721725887523728[/C][C]0.639137056238136[/C][/ROW]
[ROW][C]43[/C][C]0.321949730317219[/C][C]0.643899460634437[/C][C]0.678050269682781[/C][/ROW]
[ROW][C]44[/C][C]0.28226702448597[/C][C]0.564534048971941[/C][C]0.71773297551403[/C][/ROW]
[ROW][C]45[/C][C]0.353966980089867[/C][C]0.707933960179734[/C][C]0.646033019910133[/C][/ROW]
[ROW][C]46[/C][C]0.377069743329276[/C][C]0.754139486658551[/C][C]0.622930256670724[/C][/ROW]
[ROW][C]47[/C][C]0.348202053374548[/C][C]0.696404106749097[/C][C]0.651797946625452[/C][/ROW]
[ROW][C]48[/C][C]0.319990891001772[/C][C]0.639981782003545[/C][C]0.680009108998228[/C][/ROW]
[ROW][C]49[/C][C]0.279129510512619[/C][C]0.558259021025239[/C][C]0.720870489487381[/C][/ROW]
[ROW][C]50[/C][C]0.295588362085247[/C][C]0.591176724170494[/C][C]0.704411637914753[/C][/ROW]
[ROW][C]51[/C][C]0.326478407740677[/C][C]0.652956815481355[/C][C]0.673521592259323[/C][/ROW]
[ROW][C]52[/C][C]0.29535853993303[/C][C]0.59071707986606[/C][C]0.70464146006697[/C][/ROW]
[ROW][C]53[/C][C]0.262194753848191[/C][C]0.524389507696382[/C][C]0.737805246151809[/C][/ROW]
[ROW][C]54[/C][C]0.238574054681074[/C][C]0.477148109362148[/C][C]0.761425945318926[/C][/ROW]
[ROW][C]55[/C][C]0.204355708938905[/C][C]0.408711417877811[/C][C]0.795644291061095[/C][/ROW]
[ROW][C]56[/C][C]0.184072777306987[/C][C]0.368145554613974[/C][C]0.815927222693013[/C][/ROW]
[ROW][C]57[/C][C]0.190762089468445[/C][C]0.38152417893689[/C][C]0.809237910531555[/C][/ROW]
[ROW][C]58[/C][C]0.276995120803146[/C][C]0.553990241606292[/C][C]0.723004879196854[/C][/ROW]
[ROW][C]59[/C][C]0.250277765703298[/C][C]0.500555531406595[/C][C]0.749722234296702[/C][/ROW]
[ROW][C]60[/C][C]0.216674967783514[/C][C]0.433349935567028[/C][C]0.783325032216486[/C][/ROW]
[ROW][C]61[/C][C]0.195020116287724[/C][C]0.390040232575449[/C][C]0.804979883712276[/C][/ROW]
[ROW][C]62[/C][C]0.186460131316179[/C][C]0.372920262632358[/C][C]0.813539868683821[/C][/ROW]
[ROW][C]63[/C][C]0.160659531996998[/C][C]0.321319063993996[/C][C]0.839340468003002[/C][/ROW]
[ROW][C]64[/C][C]0.163754190513888[/C][C]0.327508381027775[/C][C]0.836245809486112[/C][/ROW]
[ROW][C]65[/C][C]0.139415762161235[/C][C]0.27883152432247[/C][C]0.860584237838765[/C][/ROW]
[ROW][C]66[/C][C]0.119444784683343[/C][C]0.238889569366686[/C][C]0.880555215316657[/C][/ROW]
[ROW][C]67[/C][C]0.0998280482171024[/C][C]0.199656096434205[/C][C]0.900171951782898[/C][/ROW]
[ROW][C]68[/C][C]0.105736490836981[/C][C]0.211472981673961[/C][C]0.894263509163019[/C][/ROW]
[ROW][C]69[/C][C]0.104428343355973[/C][C]0.208856686711946[/C][C]0.895571656644027[/C][/ROW]
[ROW][C]70[/C][C]0.0897548857169319[/C][C]0.179509771433864[/C][C]0.910245114283068[/C][/ROW]
[ROW][C]71[/C][C]0.0928109870570903[/C][C]0.185621974114181[/C][C]0.90718901294291[/C][/ROW]
[ROW][C]72[/C][C]0.118132078017658[/C][C]0.236264156035316[/C][C]0.881867921982342[/C][/ROW]
[ROW][C]73[/C][C]0.115884811721182[/C][C]0.231769623442365[/C][C]0.884115188278818[/C][/ROW]
[ROW][C]74[/C][C]0.0973465038764661[/C][C]0.194693007752932[/C][C]0.902653496123534[/C][/ROW]
[ROW][C]75[/C][C]0.0845264774917464[/C][C]0.169052954983493[/C][C]0.915473522508254[/C][/ROW]
[ROW][C]76[/C][C]0.112118950338707[/C][C]0.224237900677415[/C][C]0.887881049661293[/C][/ROW]
[ROW][C]77[/C][C]0.0953979613582988[/C][C]0.190795922716598[/C][C]0.904602038641701[/C][/ROW]
[ROW][C]78[/C][C]0.080067774835023[/C][C]0.160135549670046[/C][C]0.919932225164977[/C][/ROW]
[ROW][C]79[/C][C]0.103269405269616[/C][C]0.206538810539232[/C][C]0.896730594730384[/C][/ROW]
[ROW][C]80[/C][C]0.119682483210828[/C][C]0.239364966421657[/C][C]0.880317516789171[/C][/ROW]
[ROW][C]81[/C][C]0.113388229663379[/C][C]0.226776459326758[/C][C]0.886611770336621[/C][/ROW]
[ROW][C]82[/C][C]0.0969327679876853[/C][C]0.193865535975371[/C][C]0.903067232012315[/C][/ROW]
[ROW][C]83[/C][C]0.0900227229610308[/C][C]0.180045445922062[/C][C]0.909977277038969[/C][/ROW]
[ROW][C]84[/C][C]0.0850630472482933[/C][C]0.170126094496587[/C][C]0.914936952751707[/C][/ROW]
[ROW][C]85[/C][C]0.0730823808088622[/C][C]0.146164761617724[/C][C]0.926917619191138[/C][/ROW]
[ROW][C]86[/C][C]0.0634861512939661[/C][C]0.126972302587932[/C][C]0.936513848706034[/C][/ROW]
[ROW][C]87[/C][C]0.0554688343076777[/C][C]0.110937668615355[/C][C]0.944531165692322[/C][/ROW]
[ROW][C]88[/C][C]0.0702912676457442[/C][C]0.140582535291488[/C][C]0.929708732354256[/C][/ROW]
[ROW][C]89[/C][C]0.0583527827065543[/C][C]0.116705565413109[/C][C]0.941647217293446[/C][/ROW]
[ROW][C]90[/C][C]0.060855526505471[/C][C]0.121711053010942[/C][C]0.939144473494529[/C][/ROW]
[ROW][C]91[/C][C]0.0540968207154264[/C][C]0.108193641430853[/C][C]0.945903179284574[/C][/ROW]
[ROW][C]92[/C][C]0.0489010201384591[/C][C]0.0978020402769181[/C][C]0.951098979861541[/C][/ROW]
[ROW][C]93[/C][C]0.0406408112257513[/C][C]0.0812816224515026[/C][C]0.959359188774249[/C][/ROW]
[ROW][C]94[/C][C]0.0398778050928188[/C][C]0.0797556101856376[/C][C]0.960122194907181[/C][/ROW]
[ROW][C]95[/C][C]0.0396482558412459[/C][C]0.0792965116824919[/C][C]0.960351744158754[/C][/ROW]
[ROW][C]96[/C][C]0.0356469315611581[/C][C]0.0712938631223163[/C][C]0.964353068438842[/C][/ROW]
[ROW][C]97[/C][C]0.0299693271394587[/C][C]0.0599386542789173[/C][C]0.970030672860541[/C][/ROW]
[ROW][C]98[/C][C]0.0255240193233002[/C][C]0.0510480386466003[/C][C]0.9744759806767[/C][/ROW]
[ROW][C]99[/C][C]0.0259030795531725[/C][C]0.051806159106345[/C][C]0.974096920446827[/C][/ROW]
[ROW][C]100[/C][C]0.0236642766933543[/C][C]0.0473285533867086[/C][C]0.976335723306646[/C][/ROW]
[ROW][C]101[/C][C]0.0200829665301225[/C][C]0.0401659330602449[/C][C]0.979917033469878[/C][/ROW]
[ROW][C]102[/C][C]0.016475662364428[/C][C]0.032951324728856[/C][C]0.983524337635572[/C][/ROW]
[ROW][C]103[/C][C]0.0133868926870123[/C][C]0.0267737853740247[/C][C]0.986613107312988[/C][/ROW]
[ROW][C]104[/C][C]0.014165566056449[/C][C]0.0283311321128981[/C][C]0.985834433943551[/C][/ROW]
[ROW][C]105[/C][C]0.0309265822825122[/C][C]0.0618531645650244[/C][C]0.969073417717488[/C][/ROW]
[ROW][C]106[/C][C]0.0285250821188076[/C][C]0.0570501642376152[/C][C]0.971474917881192[/C][/ROW]
[ROW][C]107[/C][C]0.0312728494826891[/C][C]0.0625456989653782[/C][C]0.968727150517311[/C][/ROW]
[ROW][C]108[/C][C]0.0258391227653875[/C][C]0.051678245530775[/C][C]0.974160877234613[/C][/ROW]
[ROW][C]109[/C][C]0.0442022432087277[/C][C]0.0884044864174555[/C][C]0.955797756791272[/C][/ROW]
[ROW][C]110[/C][C]0.0526802789503804[/C][C]0.105360557900761[/C][C]0.94731972104962[/C][/ROW]
[ROW][C]111[/C][C]0.0499676135697629[/C][C]0.0999352271395259[/C][C]0.950032386430237[/C][/ROW]
[ROW][C]112[/C][C]0.0717458597858171[/C][C]0.143491719571634[/C][C]0.928254140214183[/C][/ROW]
[ROW][C]113[/C][C]0.0700509751452445[/C][C]0.140101950290489[/C][C]0.929949024854756[/C][/ROW]
[ROW][C]114[/C][C]0.0643814009746312[/C][C]0.128762801949262[/C][C]0.935618599025369[/C][/ROW]
[ROW][C]115[/C][C]0.0652147171157124[/C][C]0.130429434231425[/C][C]0.934785282884288[/C][/ROW]
[ROW][C]116[/C][C]0.0622216902773801[/C][C]0.12444338055476[/C][C]0.93777830972262[/C][/ROW]
[ROW][C]117[/C][C]0.0535166912178407[/C][C]0.107033382435681[/C][C]0.946483308782159[/C][/ROW]
[ROW][C]118[/C][C]0.0499866352222596[/C][C]0.0999732704445193[/C][C]0.95001336477774[/C][/ROW]
[ROW][C]119[/C][C]0.0456785495155809[/C][C]0.0913570990311617[/C][C]0.954321450484419[/C][/ROW]
[ROW][C]120[/C][C]0.038966290181126[/C][C]0.077932580362252[/C][C]0.961033709818874[/C][/ROW]
[ROW][C]121[/C][C]0.0354038191994335[/C][C]0.070807638398867[/C][C]0.964596180800567[/C][/ROW]
[ROW][C]122[/C][C]0.0296349956010469[/C][C]0.0592699912020938[/C][C]0.970365004398953[/C][/ROW]
[ROW][C]123[/C][C]0.0283898191143262[/C][C]0.0567796382286525[/C][C]0.971610180885674[/C][/ROW]
[ROW][C]124[/C][C]0.0268807688799797[/C][C]0.0537615377599593[/C][C]0.97311923112002[/C][/ROW]
[ROW][C]125[/C][C]0.0330733683390701[/C][C]0.0661467366781402[/C][C]0.96692663166093[/C][/ROW]
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[ROW][C]271[/C][C]0.384369721676518[/C][C]0.768739443353036[/C][C]0.615630278323482[/C][/ROW]
[ROW][C]272[/C][C]0.796094926483554[/C][C]0.407810147032893[/C][C]0.203905073516447[/C][/ROW]
[ROW][C]273[/C][C]0.725326492008912[/C][C]0.549347015982175[/C][C]0.274673507991088[/C][/ROW]
[ROW][C]274[/C][C]0.642243072271048[/C][C]0.715513855457905[/C][C]0.357756927728952[/C][/ROW]
[ROW][C]275[/C][C]0.562582460360898[/C][C]0.874835079278203[/C][C]0.437417539639102[/C][/ROW]
[ROW][C]276[/C][C]0.651429914478499[/C][C]0.697140171043001[/C][C]0.348570085521501[/C][/ROW]
[ROW][C]277[/C][C]0.628790086125763[/C][C]0.742419827748474[/C][C]0.371209913874237[/C][/ROW]
[ROW][C]278[/C][C]0.459240746362615[/C][C]0.918481492725231[/C][C]0.540759253637385[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198137&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198137&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
100.8367679496485560.3264641007028870.163232050351444
110.8245786770122370.3508426459755270.175421322987763
120.8062578847888240.3874842304223520.193742115211176
130.8396963988813750.3206072022372510.160303601118625
140.7810495593721190.4379008812557620.218950440627881
150.7969387561078910.4061224877842170.203061243892109
160.7624183573749360.4751632852501290.237581642625064
170.6929754808624950.614049038275010.307024519137505
180.6157111091010480.7685777817979040.384288890898952
190.5743600276705050.8512799446589910.425639972329496
200.5613882919183830.8772234161632330.438611708081617
210.5738616564712560.8522766870574870.426138343528744
220.5333550186694950.933289962661010.466644981330505
230.4873757521082480.9747515042164970.512624247891752
240.4148990399010680.8297980798021370.585100960098932
250.4408979971635190.8817959943270370.559102002836481
260.6547221788450390.6905556423099230.345277821154961
270.5918300355850020.8163399288299970.408169964414998
280.5597157393846050.880568521230790.440284260615395
290.5274125435614780.9451749128770430.472587456438521
300.4666572733912070.9333145467824130.533342726608793
310.4617576957085160.9235153914170320.538242304291484
320.6061443732686880.7877112534626230.393855626731312
330.5891413133621310.8217173732757380.410858686637869
340.557300879002320.8853982419953610.44269912099768
350.5110789370717430.9778421258565140.488921062928257
360.4571283047761160.9142566095522330.542871695223883
370.4148665422430550.8297330844861090.585133457756945
380.3894947528966340.7789895057932680.610505247103366
390.4946154572970370.9892309145940750.505384542702963
400.4415865375155210.8831730750310410.558413462484479
410.4109372184108050.821874436821610.589062781589195
420.3608629437618640.7217258875237280.639137056238136
430.3219497303172190.6438994606344370.678050269682781
440.282267024485970.5645340489719410.71773297551403
450.3539669800898670.7079339601797340.646033019910133
460.3770697433292760.7541394866585510.622930256670724
470.3482020533745480.6964041067490970.651797946625452
480.3199908910017720.6399817820035450.680009108998228
490.2791295105126190.5582590210252390.720870489487381
500.2955883620852470.5911767241704940.704411637914753
510.3264784077406770.6529568154813550.673521592259323
520.295358539933030.590717079866060.70464146006697
530.2621947538481910.5243895076963820.737805246151809
540.2385740546810740.4771481093621480.761425945318926
550.2043557089389050.4087114178778110.795644291061095
560.1840727773069870.3681455546139740.815927222693013
570.1907620894684450.381524178936890.809237910531555
580.2769951208031460.5539902416062920.723004879196854
590.2502777657032980.5005555314065950.749722234296702
600.2166749677835140.4333499355670280.783325032216486
610.1950201162877240.3900402325754490.804979883712276
620.1864601313161790.3729202626323580.813539868683821
630.1606595319969980.3213190639939960.839340468003002
640.1637541905138880.3275083810277750.836245809486112
650.1394157621612350.278831524322470.860584237838765
660.1194447846833430.2388895693666860.880555215316657
670.09982804821710240.1996560964342050.900171951782898
680.1057364908369810.2114729816739610.894263509163019
690.1044283433559730.2088566867119460.895571656644027
700.08975488571693190.1795097714338640.910245114283068
710.09281098705709030.1856219741141810.90718901294291
720.1181320780176580.2362641560353160.881867921982342
730.1158848117211820.2317696234423650.884115188278818
740.09734650387646610.1946930077529320.902653496123534
750.08452647749174640.1690529549834930.915473522508254
760.1121189503387070.2242379006774150.887881049661293
770.09539796135829880.1907959227165980.904602038641701
780.0800677748350230.1601355496700460.919932225164977
790.1032694052696160.2065388105392320.896730594730384
800.1196824832108280.2393649664216570.880317516789171
810.1133882296633790.2267764593267580.886611770336621
820.09693276798768530.1938655359753710.903067232012315
830.09002272296103080.1800454459220620.909977277038969
840.08506304724829330.1701260944965870.914936952751707
850.07308238080886220.1461647616177240.926917619191138
860.06348615129396610.1269723025879320.936513848706034
870.05546883430767770.1109376686153550.944531165692322
880.07029126764574420.1405825352914880.929708732354256
890.05835278270655430.1167055654131090.941647217293446
900.0608555265054710.1217110530109420.939144473494529
910.05409682071542640.1081936414308530.945903179284574
920.04890102013845910.09780204027691810.951098979861541
930.04064081122575130.08128162245150260.959359188774249
940.03987780509281880.07975561018563760.960122194907181
950.03964825584124590.07929651168249190.960351744158754
960.03564693156115810.07129386312231630.964353068438842
970.02996932713945870.05993865427891730.970030672860541
980.02552401932330020.05104803864660030.9744759806767
990.02590307955317250.0518061591063450.974096920446827
1000.02366427669335430.04732855338670860.976335723306646
1010.02008296653012250.04016593306024490.979917033469878
1020.0164756623644280.0329513247288560.983524337635572
1030.01338689268701230.02677378537402470.986613107312988
1040.0141655660564490.02833113211289810.985834433943551
1050.03092658228251220.06185316456502440.969073417717488
1060.02852508211880760.05705016423761520.971474917881192
1070.03127284948268910.06254569896537820.968727150517311
1080.02583912276538750.0516782455307750.974160877234613
1090.04420224320872770.08840448641745550.955797756791272
1100.05268027895038040.1053605579007610.94731972104962
1110.04996761356976290.09993522713952590.950032386430237
1120.07174585978581710.1434917195716340.928254140214183
1130.07005097514524450.1401019502904890.929949024854756
1140.06438140097463120.1287628019492620.935618599025369
1150.06521471711571240.1304294342314250.934785282884288
1160.06222169027738010.124443380554760.93777830972262
1170.05351669121784070.1070333824356810.946483308782159
1180.04998663522225960.09997327044451930.95001336477774
1190.04567854951558090.09135709903116170.954321450484419
1200.0389662901811260.0779325803622520.961033709818874
1210.03540381919943350.0708076383988670.964596180800567
1220.02963499560104690.05926999120209380.970365004398953
1230.02838981911432620.05677963822865250.971610180885674
1240.02688076887997970.05376153775995930.97311923112002
1250.03307336833907010.06614673667814020.96692663166093
1260.05867791344866070.1173558268973210.941322086551339
1270.05585050500596440.1117010100119290.944149494994036
1280.04936720417366180.09873440834732360.950632795826338
1290.0465809218009320.0931618436018640.953419078199068
1300.05081795180510060.1016359036102010.949182048194899
1310.05317708707451440.1063541741490290.946822912925486
1320.06732596081976620.1346519216395320.932674039180234
1330.05754236721237610.1150847344247520.942457632787624
1340.04882549932614490.09765099865228970.951174500673855
1350.04308581548537050.08617163097074090.95691418451463
1360.03656883694141340.07313767388282690.963431163058587
1370.03740295338916720.07480590677833430.962597046610833
1380.03159400984505950.06318801969011890.968405990154941
1390.03082752753985780.06165505507971560.969172472460142
1400.03015593201007820.06031186402015630.969844067989922
1410.04999501667725560.09999003335451120.950004983322744
1420.06532473594865680.1306494718973140.934675264051343
1430.05836151501063120.1167230300212620.941638484989369
1440.1136494493665960.2272988987331920.886350550633404
1450.1016449290463470.2032898580926940.898355070953653
1460.08971637354735570.1794327470947110.910283626452644
1470.07849871487709540.1569974297541910.921501285122905
1480.0710355284379280.1420710568758560.928964471562072
1490.06379666214610910.1275933242922180.936203337853891
1500.1016599477594710.2033198955189430.898340052240529
1510.09575121930185280.1915024386037060.904248780698147
1520.08607172707952360.1721434541590470.913928272920476
1530.09785606753623670.1957121350724730.902143932463763
1540.09011808111535310.1802361622307060.909881918884647
1550.08691140003682180.1738228000736440.913088599963178
1560.07947386766444760.1589477353288950.920526132335552
1570.07577892897157940.1515578579431590.924221071028421
1580.06897720035654740.1379544007130950.931022799643453
1590.05896097221181510.117921944423630.941039027788185
1600.0548654780823120.1097309561646240.945134521917688
1610.06221751766008120.1244350353201620.937782482339919
1620.05711235036593270.1142247007318650.942887649634067
1630.08929343507178390.1785868701435680.910706564928216
1640.08371842414675120.1674368482935020.916281575853249
1650.07317034878292170.1463406975658430.926829651217078
1660.06737103199245210.1347420639849040.932628968007548
1670.1300434387546830.2600868775093660.869956561245317
1680.1728391986969560.3456783973939120.827160801303044
1690.1557641592574980.3115283185149960.844235840742502
1700.256307644737070.5126152894741390.74369235526293
1710.2329640300746120.4659280601492230.767035969925388
1720.2945386906317540.5890773812635080.705461309368246
1730.2800486805984570.5600973611969140.719951319401543
1740.3003537302345180.6007074604690350.699646269765482
1750.2748195375254010.5496390750508030.725180462474599
1760.2496462178984410.4992924357968820.750353782101559
1770.2469393618214540.4938787236429070.753060638178546
1780.2222409083069830.4444818166139650.777759091693017
1790.2275950984285570.4551901968571140.772404901571443
1800.2540851161499370.5081702322998730.745914883850063
1810.2899381367065030.5798762734130060.710061863293497
1820.4249112651877640.8498225303755290.575088734812236
1830.4213341238313980.8426682476627950.578665876168602
1840.3968233729456450.7936467458912910.603176627054355
1850.5283335787629970.9433328424740060.471666421237003
1860.5069858648063060.9860282703873870.493014135193693
1870.4883377997396880.9766755994793760.511662200260312
1880.4837562073272770.9675124146545540.516243792672723
1890.452820931263840.905641862527680.54717906873616
1900.4228598654754880.8457197309509770.577140134524512
1910.3902902487204230.7805804974408470.609709751279577
1920.356628980724640.7132579614492810.64337101927536
1930.3280621936700990.6561243873401990.671937806329901
1940.3107652689910460.6215305379820920.689234731008954
1950.3040522561595890.6081045123191780.695947743840411
1960.2726669476889490.5453338953778980.727333052311051
1970.250340624318010.5006812486360210.74965937568199
1980.3769737461809190.7539474923618380.623026253819081
1990.356201126213980.7124022524279610.64379887378602
2000.3284092501232220.6568185002464450.671590749876778
2010.2968521013100380.5937042026200750.703147898689962
2020.2700442855785740.5400885711571470.729955714421426
2030.2429545378511460.4859090757022920.757045462148854
2040.2163262412686130.4326524825372260.783673758731387
2050.2096742939347990.4193485878695980.790325706065201
2060.1841102922502120.3682205845004230.815889707749788
2070.1632199860281170.3264399720562340.836780013971883
2080.1535951170063530.3071902340127050.846404882993647
2090.1912418136129690.3824836272259380.808758186387031
2100.178973044473530.3579460889470590.82102695552647
2110.1558258179865350.311651635973070.844174182013465
2120.1369245874602890.2738491749205780.863075412539711
2130.1231448796364350.2462897592728690.876855120363565
2140.1474865583477280.2949731166954560.852513441652272
2150.1315114091664670.2630228183329330.868488590833533
2160.1184226966253760.2368453932507520.881577303374624
2170.1033080478668420.2066160957336830.896691952133158
2180.09520534075392390.1904106815078480.904794659246076
2190.07948167098593060.1589633419718610.920518329014069
2200.06827949922609510.136558998452190.931720500773905
2210.06285965409638610.1257193081927720.937140345903614
2220.05538460343433890.1107692068686780.944615396565661
2230.04557915949803180.09115831899606350.954420840501968
2240.03761745114091870.07523490228183740.962382548859081
2250.03028662532654450.06057325065308890.969713374673456
2260.03013626079100780.06027252158201550.969863739208992
2270.03381269535391130.06762539070782250.966187304646089
2280.02794687870438610.05589375740877230.972053121295614
2290.05608326141977170.1121665228395430.943916738580228
2300.04715614691905290.09431229383810580.952843853080947
2310.04915079113802140.09830158227604280.950849208861979
2320.0779752367376570.1559504734753140.922024763262343
2330.1397418833741960.2794837667483910.860258116625804
2340.1313237161260550.2626474322521110.868676283873945
2350.207665166787410.4153303335748190.79233483321259
2360.2476967542661860.4953935085323720.752303245733814
2370.2147565717754290.4295131435508580.785243428224571
2380.187748333498780.3754966669975590.81225166650122
2390.1695991498745530.3391982997491050.830400850125447
2400.2149296461554390.4298592923108780.785070353844561
2410.2038859140249310.4077718280498610.796114085975069
2420.2175716253361880.4351432506723750.782428374663812
2430.2584028801334090.5168057602668180.741597119866591
2440.2444181597292940.4888363194585880.755581840270706
2450.2295404771448520.4590809542897050.770459522855148
2460.1952854647819390.3905709295638780.804714535218061
2470.1759458870047750.351891774009550.824054112995225
2480.1451440301711810.2902880603423630.854855969828819
2490.1513365519221570.3026731038443140.848663448077843
2500.123751550984910.247503101969820.87624844901509
2510.1053271640065950.2106543280131890.894672835993405
2520.0874109042506170.1748218085012340.912589095749383
2530.08682336020703670.1736467204140730.913176639792963
2540.1522972120355480.3045944240710970.847702787964452
2550.165270166824670.3305403336493410.83472983317533
2560.1450471103021250.2900942206042510.854952889697875
2570.2154232989869190.4308465979738390.784576701013081
2580.232675963245210.4653519264904210.76732403675479
2590.2644255278947360.5288510557894720.735574472105264
2600.2312569621597110.4625139243194220.768743037840289
2610.5489477095408010.9021045809183980.451052290459199
2620.5776274863869060.8447450272261870.422372513613094
2630.6135088635223350.7729822729553290.386491136477665
2640.5853830308456540.8292339383086920.414616969154346
2650.5332314103277980.9335371793444040.466768589672202
2660.5216109167122890.9567781665754220.478389083287711
2670.644523282036980.710953435926040.35547671796302
2680.5662774179016320.8674451641967360.433722582098368
2690.4831121681007530.9662243362015050.516887831899247
2700.4497038743388630.8994077486777250.550296125661137
2710.3843697216765180.7687394433530360.615630278323482
2720.7960949264835540.4078101470328930.203905073516447
2730.7253264920089120.5493470159821750.274673507991088
2740.6422430722710480.7155138554579050.357756927728952
2750.5625824603608980.8748350792782030.437417539639102
2760.6514299144784990.6971401710430010.348570085521501
2770.6287900861257630.7424198277484740.371209913874237
2780.4592407463626150.9184814927252310.540759253637385






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level50.0185873605947955OK
10% type I error level450.16728624535316NOK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 5 & 0.0185873605947955 & OK \tabularnewline
10% type I error level & 45 & 0.16728624535316 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198137&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]5[/C][C]0.0185873605947955[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]45[/C][C]0.16728624535316[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198137&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198137&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 level00OK
5% type I error level50.0185873605947955OK
10% type I error level450.16728624535316NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 3 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 3 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$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')
}