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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 computationFri, 01 Nov 2013 13:40:53 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/01/t1383327825j6whr72ia4eljgo.htm/, Retrieved Mon, 29 Apr 2024 10:29:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221697, Retrieved Mon, 29 Apr 2024 10:29:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact54

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [ws 7software] [2013-11-01 17:40:53] [0147fd68123b42babc023061627c5370] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 12 14 12
39 32 16 11 18 11
30 35 19 15 11 14
31 33 15 6 12 12
34 37 14 13 16 21
35 29 13 10 18 12
39 31 19 12 14 22
34 36 15 14 14 11
36 35 14 12 15 10
37 38 15 9 15 13
38 31 16 10 17 10
36 34 16 12 19 8
38 35 16 12 10 15
39 38 16 11 16 14
33 37 17 15 18 10
32 33 15 12 14 14
36 32 15 10 14 14
38 38 20 12 17 11
39 38 18 11 14 10
32 32 16 12 16 13
32 33 16 11 18 9.5
31 31 16 12 11 14
39 38 19 13 14 12
37 39 16 11 12 14
39 32 17 12 17 11
41 32 17 13 9 9
36 35 16 10 16 11
33 37 15 14 14 15
33 33 16 12 15 14
34 33 14 10 11 13
31 31 15 12 16 9
27 32 12 8 13 15
37 31 14 10 17 10
34 37 16 12 15 11
34 30 14 12 14 13
32 33 10 7 16 8
29 31 10 9 9 20
36 33 14 12 15 12
29 31 16 10 17 10
35 33 16 10 13 10
37 32 16 10 15 9
34 33 14 12 16 14
38 32 20 15 16 8
35 33 14 10 12 14
38 28 14 10 15 11
37 35 11 12 11 13
38 39 14 13 15 9
33 34 15 11 15 11
36 38 16 11 17 15
38 32 14 12 13 11
32 38 16 14 16 10
32 30 14 10 14 14
32 33 12 12 11 18
34 38 16 13 12 14
32 32 9 5 12 11
37 35 14 6 15 14.5
39 34 16 12 16 13
29 34 16 12 15 9
37 36 15 11 12 10
35 34 16 10 12 15
30 28 12 7 8 20
38 34 16 12 13 12
34 35 16 14 11 12
31 35 14 11 14 14
34 31 16 12 15 13
35 37 17 13 10 11
36 35 18 14 11 17
30 27 18 11 12 12
39 40 12 12 15 13
35 37 16 12 15 14
38 36 10 8 14 13
31 38 14 11 16 15
34 39 18 14 15 13
38 41 18 14 15 10
34 27 16 12 13 11
39 30 17 9 12 19
37 37 16 13 17 13
34 31 16 11 13 17
28 31 13 12 15 13
37 27 16 12 13 9
33 36 16 12 15 11
35 37 16 12 15 9
37 33 15 12 16 12
32 34 15 11 15 12
33 31 16 10 14 13
38 39 14 9 15 13
33 34 16 12 14 12
29 32 16 12 13 15
33 33 15 12 7 22
31 36 12 9 17 13
36 32 17 15 13 15
35 41 16 12 15 13
32 28 15 12 14 15
29 30 13 12 13 12.5
39 36 16 10 16 11
37 35 16 13 12 16
35 31 16 9 14 11
37 34 16 12 17 11
32 36 14 10 15 10
38 36 16 14 17 10
37 35 16 11 12 16
36 37 20 15 16 12
32 28 15 11 11 11
33 39 16 11 15 16
40 32 13 12 9 19
38 35 17 12 16 11
41 39 16 12 15 16
36 35 16 11 10 15
43 42 12 7 10 24
30 34 16 12 15 14
31 33 16 14 11 15
32 41 17 11 13 11
32 33 13 11 14 15
37 34 12 10 18 12
37 32 18 13 16 10
33 40 14 13 14 14
34 40 14 8 14 13
33 35 13 11 14 9
38 36 16 12 14 15
33 37 13 11 12 15
31 27 16 13 14 14
38 39 13 12 15 11
37 38 16 14 15 8
36 31 15 13 15 11
31 33 16 15 13 11
39 32 15 10 17 8
44 39 17 11 17 10
33 36 15 9 19 11
35 33 12 11 15 13
32 33 16 10 13 11
28 32 10 11 9 20
40 37 16 8 15 10
27 30 12 11 15 15
37 38 14 12 15 12
32 29 15 12 16 14
28 22 13 9 11 23
34 35 15 11 14 14
30 35 11 10 11 16
35 34 12 8 15 11
31 35 11 9 13 12
32 34 16 8 15 10
30 37 15 9 16 14
30 35 17 15 14 12
31 23 16 11 15 12
40 31 10 8 16 11
32 27 18 13 16 12
36 36 13 12 11 13
32 31 16 12 12 11
35 32 13 9 9 19
38 39 10 7 16 12
42 37 15 13 13 17
34 38 16 9 16 9
35 39 16 6 12 12
38 34 14 8 9 19
33 31 10 8 13 18
36 32 17 15 13 15
32 37 13 6 14 14
33 36 15 9 19 11
34 32 16 11 13 9
32 38 12 8 12 18
34 36 13 8 13 16
27 26 13 10 10 24
31 26 12 8 14 14
38 33 17 14 16 20
34 39 15 10 10 18
24 30 10 8 11 23
30 33 14 11 14 12
26 25 11 12 12 14
34 38 13 12 9 16
27 37 16 12 9 18
37 31 12 5 11 20
36 37 16 12 16 12
41 35 12 10 9 12
29 25 9 7 13 17
36 28 12 12 16 13
32 35 15 11 13 9
37 33 12 8 9 16
30 30 12 9 12 18
31 31 14 10 16 10
38 37 12 9 11 14
36 36 16 12 14 11
35 30 11 6 13 9
31 36 19 15 15 11
38 32 15 12 14 10
22 28 8 12 16 11
32 36 16 12 13 19
36 34 17 11 14 14
39 31 12 7 15 12
28 28 11 7 13 14
32 36 11 5 11 21
32 36 14 12 11 13
38 40 16 12 14 10
32 33 12 3 15 15
35 37 16 11 11 16
32 32 13 10 15 14
37 38 15 12 12 12
34 31 16 9 14 19
33 37 16 12 14 15
33 33 14 9 8 19
26 32 16 12 13 13
30 30 16 12 9 17
24 30 14 10 15 12
34 31 11 9 17 11
34 32 12 12 13 14
33 34 15 8 15 11
34 36 15 11 15 13
35 37 16 11 14 12
35 36 16 12 16 15
36 33 11 10 13 14
34 33 15 10 16 12
34 33 12 12 9 17
41 44 12 12 16 11
32 39 15 11 11 18
30 32 15 8 10 13
35 35 16 12 11 17
28 25 14 10 15 13
33 35 17 11 17 11
39 34 14 10 14 12
36 35 13 8 8 22
36 39 15 12 15 14
35 33 13 12 11 12
38 36 14 10 16 12
33 32 15 12 10 17
31 32 12 9 15 9
34 36 13 9 9 21
32 36 8 6 16 10
31 32 14 10 19 11
33 34 14 9 12 12
34 33 11 9 8 23
34 35 12 9 11 13
34 30 13 6 14 12
33 38 10 10 9 16
32 34 16 6 15 9
41 33 18 14 13 17
34 32 13 10 16 9
36 31 11 10 11 14
37 30 4 6 12 17
36 27 13 12 13 13
29 31 16 12 10 11
37 30 10 7 11 12
27 32 12 8 12 10
35 35 12 11 8 19
28 28 10 3 12 16
35 33 13 6 12 16
37 31 15 10 15 14
29 35 12 8 11 20
32 35 14 9 13 15
36 32 10 9 14 23
19 21 12 8 10 20
21 20 12 9 12 16
31 34 11 7 15 14
33 32 10 7 13 17
36 34 12 6 13 11
33 32 16 9 13 13
37 33 12 10 12 17
34 33 14 11 12 15
35 37 16 12 9 21
31 32 14 8 9 18
37 34 13 11 15 15
35 30 4 3 10 8
27 30 15 11 14 12
34 38 11 12 15 12
40 36 11 7 7 22
29 32 14 9 14 12

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time18 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 18 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221697&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]18 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221697&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221697&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 time18 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 1.66484 -0.0107895Connected[t] + 0.0377922Separate[t] + 0.575835Learning[t] -0.00393975Happiness[t] -0.0145268Depression[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Software[t] =  +  1.66484 -0.0107895Connected[t] +  0.0377922Separate[t] +  0.575835Learning[t] -0.00393975Happiness[t] -0.0145268Depression[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221697&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Software[t] =  +  1.66484 -0.0107895Connected[t] +  0.0377922Separate[t] +  0.575835Learning[t] -0.00393975Happiness[t] -0.0145268Depression[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221697&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221697&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
Software[t] = + 1.66484 -0.0107895Connected[t] + 0.0377922Separate[t] + 0.575835Learning[t] -0.00393975Happiness[t] -0.0145268Depression[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.664841.703420.97730.3293120.164656
Connected-0.01078950.0336567-0.32060.7487910.374395
Separate0.03779220.03455231.0940.2750760.137538
Learning0.5758350.048801311.85.53114e-262.76557e-26
Happiness-0.003939750.0561224-0.07020.9440890.472045
Depression-0.01452680.0402547-0.36090.7184910.359245

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 1.66484 & 1.70342 & 0.9773 & 0.329312 & 0.164656 \tabularnewline
Connected & -0.0107895 & 0.0336567 & -0.3206 & 0.748791 & 0.374395 \tabularnewline
Separate & 0.0377922 & 0.0345523 & 1.094 & 0.275076 & 0.137538 \tabularnewline
Learning & 0.575835 & 0.0488013 & 11.8 & 5.53114e-26 & 2.76557e-26 \tabularnewline
Happiness & -0.00393975 & 0.0561224 & -0.0702 & 0.944089 & 0.472045 \tabularnewline
Depression & -0.0145268 & 0.0402547 & -0.3609 & 0.718491 & 0.359245 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221697&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]1.66484[/C][C]1.70342[/C][C]0.9773[/C][C]0.329312[/C][C]0.164656[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0107895[/C][C]0.0336567[/C][C]-0.3206[/C][C]0.748791[/C][C]0.374395[/C][/ROW]
[ROW][C]Separate[/C][C]0.0377922[/C][C]0.0345523[/C][C]1.094[/C][C]0.275076[/C][C]0.137538[/C][/ROW]
[ROW][C]Learning[/C][C]0.575835[/C][C]0.0488013[/C][C]11.8[/C][C]5.53114e-26[/C][C]2.76557e-26[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.00393975[/C][C]0.0561224[/C][C]-0.0702[/C][C]0.944089[/C][C]0.472045[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0145268[/C][C]0.0402547[/C][C]-0.3609[/C][C]0.718491[/C][C]0.359245[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221697&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221697&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.664841.703420.97730.3293120.164656
Connected-0.01078950.0336567-0.32060.7487910.374395
Separate0.03779220.03455231.0940.2750760.137538
Learning0.5758350.048801311.85.53114e-262.76557e-26
Happiness-0.003939750.0561224-0.07020.9440890.472045
Depression-0.01452680.0402547-0.36090.7184910.359245






Multiple Linear Regression - Regression Statistics
Multiple R0.626081
R-squared0.391977
Adjusted R-squared0.380194
F-TEST (value)33.2652
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.82652
Sum Squared Residuals860.73

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.626081 \tabularnewline
R-squared & 0.391977 \tabularnewline
Adjusted R-squared & 0.380194 \tabularnewline
F-TEST (value) & 33.2652 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 258 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.82652 \tabularnewline
Sum Squared Residuals & 860.73 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221697&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.626081[/C][/ROW]
[ROW][C]R-squared[/C][C]0.391977[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.380194[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]33.2652[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]258[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.82652[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]860.73[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221697&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221697&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.626081
R-squared0.391977
Adjusted R-squared0.380194
F-TEST (value)33.2652
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.82652
Sum Squared Residuals860.73






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1129.914952.08505
21111.436-0.436049
31513.3581.64196
4610.9934-4.99343
51310.38992.6101
6109.62380.376202
71212.9817-0.981727
81411.08112.91891
91210.45651.54353
10911.0913-2.09131
111011.4275-1.42751
121211.58360.416357
131211.53360.466374
141111.6271-0.627102
151512.28012.71989
161210.94571.05429
171010.8648-0.864761
181213.9809-1.98087
191112.8448-1.84476
201211.49040.509598
211111.5712-0.571158
221211.46860.531429
231313.3915-0.391541
241111.7022-0.702232
251212.0158-0.0158242
261312.05480.945183
271011.5897-1.58967
281411.07162.92844
291211.50680.493182
301010.3746-0.374643
311210.94571.05433
3289.22377-1.22377
331010.2866-0.286632
341211.69080.309223
351210.24941.75055
3678.14582-1.14582
3797.955861.04414
381210.35181.64817
391011.5246-1.52462
401011.5512-1.55123
411011.4985-1.4985
421210.34041.65958
431513.80161.19836
441010.3454-0.345387
451010.1558-0.155819
46128.690353.30965
471310.60062.39941
481111.0124-0.012355
491111.641-0.641004
501210.31491.68513
511411.76072.23926
521010.2565-0.2565
53129.171922.82808
541311.69681.30319
5557.50437-2.50437
56610.3803-4.38031
571211.49050.50954
581211.66040.339598
591111.0711-0.0711273
601011.5203-1.52032
6178.9873-1.9873
621211.52760.472405
631411.61642.38357
641110.45630.54375
651211.4350.56503
661312.27550.724478
671412.67391.32612
681112.505-1.50498
69129.417812.58219
701211.63640.363593
7188.1297-0.129702
721110.54720.452779
731412.8891.11102
741412.9651.03501
751211.32070.679265
76911.8437-2.84372
771311.62151.37852
781111.3847-0.384743
79129.77222.2278
801211.31740.68258
811211.66380.336225
821211.7090.290959
831210.91291.08706
841111.0086-0.00861774
851011.4497-1.4497
86910.5425-1.54248
871211.57760.422397
881211.50550.494464
891210.84631.15371
9099.34508-0.34508
911512.00582.99416
921211.80210.197897
931210.74221.25778
94129.738762.26124
951011.5951-1.5951
961311.5221.47799
97911.4572-2.45717
981211.53720.462847
991010.5374-0.537421
1001411.61652.38353
1011111.522-0.52201
1021513.95411.04593
1031110.81220.18785
1041111.7045-0.704517
105129.6172.383
1061212.1439-0.14393
1071211.61820.381799
1081111.5552-0.555205
10979.31014-2.31014
1101211.5770.423022
1111411.52962.47037
1121112.4472-1.44724
113119.779511.22049
114109.215350.784655
1151312.63170.368295
1161310.62362.37637
117810.6274-2.62737
118119.931471.06853
1191211.55570.44434
120119.927771.07223
1211311.30561.69442
122129.99572.0043
1231411.73982.26022
1241310.86662.13339
1251511.57993.42014
1261010.9077-0.907734
1271112.2409-1.24095
128911.0722-2.07218
129119.196421.80358
1301011.5691-1.56907
131118.004442.99556
132811.6406-3.64057
133119.140311.85969
1341210.531.47
1351210.78671.21334
13699.30256-0.302563
1371110.99970.000282898
138108.72231.2777
13989.26327-1.26327
14098.761740.238262
141811.6135-3.61351
142911.1106-2.11058
1431512.22362.7764
1441111.1795-0.179528
14587.940340.0596642
1461312.46760.532362
147129.890612.10939
1481211.49740.502578
14999.67095-0.670945
15078.24973-1.24973
1511310.94932.05066
152911.7537-2.75368
153611.7529-5.75286
154810.29-2.29
15587.925990.0740057
1561512.00582.99416
15769.94521-3.94521
158911.0722-2.07218
1591111.5387-0.538749
16089.35694-1.35694
16189.86073-1.86073
162109.453930.546065
16388.96445-0.96445
1641411.93762.0624
1651011.1085-1.10854
16687.920550.0794465
1671110.42050.579491
168128.412653.58735
169129.952072.04793
1701211.68830.311745
17159.01333-4.01333
1721211.65070.349268
173109.245440.754563
17477.18109-0.181091
175128.992733.00727
1761111.0979-0.0978698
17789.1549-1.1549
17899.07618-0.0761809
1791010.3553-0.355309
18099.31646-0.316457
1811211.63530.364654
18268.5732-2.5732
1831513.41291.58714
1841210.90131.09871
185126.86955.1305
1861211.56620.433771
1871112.092-1.09202
18879.09221-2.09221
18978.50051-1.50051
19058.66588-3.66588
1911210.50961.4904
1921211.77950.220538
19339.19974-6.19974
1941111.6231-0.623113
195109.752310.247691
1961211.11770.882342
197911.3517-2.35175
1981211.64740.3526
199910.3101-1.31009
2001211.5670.433042
2011211.40590.594132
2021010.3679-0.36793
20398.576970.423032
204129.162772.83723
205811.0124-3.01235
2061111.0481-0.0480964
2071111.6694-0.669401
2081211.58010.419851
209108.603151.39685
2101010.9453-0.945307
211129.172752.82725
212129.572522.42748
2131111.1262-0.126177
214810.9598-2.95978
2151211.5330.466998
2161010.1213-0.121284
2171112.1939-1.19394
2181010.3612-0.361196
21989.73389-1.73389
2201211.12540.874633
221129.802552.19745
2221010.4397-0.43969
2231210.86931.13069
22499.2599-0.259898
22599.80385-0.80385
22667.07847-1.07847
2271010.3668-0.366755
228910.4338-1.43381
22998.513690.486311
23099.29856-0.298558
23169.68814-3.68814
232108.235351.76465
233611.628-5.62803
2341412.53651.46353
235109.799420.200576
236108.535451.46455
23764.40851.5915
238129.54262.4574
2391211.53770.46233
24077.94008-0.940084
24189.30035-1.30035
242119.212431.78757
24337.89956-4.89956
24469.7405-3.7405
2451010.8122-0.81224
24689.25082-1.25082
247910.4349-1.43487
24897.854841.14516
24988.83356-0.833562
25098.824420.175582
25178.68701-1.68701
25277.97831-0.978313
25369.26036-3.26036
254911.4914-2.49143
255109.128560.871442
2561110.34170.65835
2571211.55840.441641
258810.3045-2.30447
259119.759421.24058
26034.5687-1.5687
2611110.91530.0846638
262128.834873.16513
26378.5808-1.5808
264910.3935-1.39351

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 9.91495 & 2.08505 \tabularnewline
2 & 11 & 11.436 & -0.436049 \tabularnewline
3 & 15 & 13.358 & 1.64196 \tabularnewline
4 & 6 & 10.9934 & -4.99343 \tabularnewline
5 & 13 & 10.3899 & 2.6101 \tabularnewline
6 & 10 & 9.6238 & 0.376202 \tabularnewline
7 & 12 & 12.9817 & -0.981727 \tabularnewline
8 & 14 & 11.0811 & 2.91891 \tabularnewline
9 & 12 & 10.4565 & 1.54353 \tabularnewline
10 & 9 & 11.0913 & -2.09131 \tabularnewline
11 & 10 & 11.4275 & -1.42751 \tabularnewline
12 & 12 & 11.5836 & 0.416357 \tabularnewline
13 & 12 & 11.5336 & 0.466374 \tabularnewline
14 & 11 & 11.6271 & -0.627102 \tabularnewline
15 & 15 & 12.2801 & 2.71989 \tabularnewline
16 & 12 & 10.9457 & 1.05429 \tabularnewline
17 & 10 & 10.8648 & -0.864761 \tabularnewline
18 & 12 & 13.9809 & -1.98087 \tabularnewline
19 & 11 & 12.8448 & -1.84476 \tabularnewline
20 & 12 & 11.4904 & 0.509598 \tabularnewline
21 & 11 & 11.5712 & -0.571158 \tabularnewline
22 & 12 & 11.4686 & 0.531429 \tabularnewline
23 & 13 & 13.3915 & -0.391541 \tabularnewline
24 & 11 & 11.7022 & -0.702232 \tabularnewline
25 & 12 & 12.0158 & -0.0158242 \tabularnewline
26 & 13 & 12.0548 & 0.945183 \tabularnewline
27 & 10 & 11.5897 & -1.58967 \tabularnewline
28 & 14 & 11.0716 & 2.92844 \tabularnewline
29 & 12 & 11.5068 & 0.493182 \tabularnewline
30 & 10 & 10.3746 & -0.374643 \tabularnewline
31 & 12 & 10.9457 & 1.05433 \tabularnewline
32 & 8 & 9.22377 & -1.22377 \tabularnewline
33 & 10 & 10.2866 & -0.286632 \tabularnewline
34 & 12 & 11.6908 & 0.309223 \tabularnewline
35 & 12 & 10.2494 & 1.75055 \tabularnewline
36 & 7 & 8.14582 & -1.14582 \tabularnewline
37 & 9 & 7.95586 & 1.04414 \tabularnewline
38 & 12 & 10.3518 & 1.64817 \tabularnewline
39 & 10 & 11.5246 & -1.52462 \tabularnewline
40 & 10 & 11.5512 & -1.55123 \tabularnewline
41 & 10 & 11.4985 & -1.4985 \tabularnewline
42 & 12 & 10.3404 & 1.65958 \tabularnewline
43 & 15 & 13.8016 & 1.19836 \tabularnewline
44 & 10 & 10.3454 & -0.345387 \tabularnewline
45 & 10 & 10.1558 & -0.155819 \tabularnewline
46 & 12 & 8.69035 & 3.30965 \tabularnewline
47 & 13 & 10.6006 & 2.39941 \tabularnewline
48 & 11 & 11.0124 & -0.012355 \tabularnewline
49 & 11 & 11.641 & -0.641004 \tabularnewline
50 & 12 & 10.3149 & 1.68513 \tabularnewline
51 & 14 & 11.7607 & 2.23926 \tabularnewline
52 & 10 & 10.2565 & -0.2565 \tabularnewline
53 & 12 & 9.17192 & 2.82808 \tabularnewline
54 & 13 & 11.6968 & 1.30319 \tabularnewline
55 & 5 & 7.50437 & -2.50437 \tabularnewline
56 & 6 & 10.3803 & -4.38031 \tabularnewline
57 & 12 & 11.4905 & 0.50954 \tabularnewline
58 & 12 & 11.6604 & 0.339598 \tabularnewline
59 & 11 & 11.0711 & -0.0711273 \tabularnewline
60 & 10 & 11.5203 & -1.52032 \tabularnewline
61 & 7 & 8.9873 & -1.9873 \tabularnewline
62 & 12 & 11.5276 & 0.472405 \tabularnewline
63 & 14 & 11.6164 & 2.38357 \tabularnewline
64 & 11 & 10.4563 & 0.54375 \tabularnewline
65 & 12 & 11.435 & 0.56503 \tabularnewline
66 & 13 & 12.2755 & 0.724478 \tabularnewline
67 & 14 & 12.6739 & 1.32612 \tabularnewline
68 & 11 & 12.505 & -1.50498 \tabularnewline
69 & 12 & 9.41781 & 2.58219 \tabularnewline
70 & 12 & 11.6364 & 0.363593 \tabularnewline
71 & 8 & 8.1297 & -0.129702 \tabularnewline
72 & 11 & 10.5472 & 0.452779 \tabularnewline
73 & 14 & 12.889 & 1.11102 \tabularnewline
74 & 14 & 12.965 & 1.03501 \tabularnewline
75 & 12 & 11.3207 & 0.679265 \tabularnewline
76 & 9 & 11.8437 & -2.84372 \tabularnewline
77 & 13 & 11.6215 & 1.37852 \tabularnewline
78 & 11 & 11.3847 & -0.384743 \tabularnewline
79 & 12 & 9.7722 & 2.2278 \tabularnewline
80 & 12 & 11.3174 & 0.68258 \tabularnewline
81 & 12 & 11.6638 & 0.336225 \tabularnewline
82 & 12 & 11.709 & 0.290959 \tabularnewline
83 & 12 & 10.9129 & 1.08706 \tabularnewline
84 & 11 & 11.0086 & -0.00861774 \tabularnewline
85 & 10 & 11.4497 & -1.4497 \tabularnewline
86 & 9 & 10.5425 & -1.54248 \tabularnewline
87 & 12 & 11.5776 & 0.422397 \tabularnewline
88 & 12 & 11.5055 & 0.494464 \tabularnewline
89 & 12 & 10.8463 & 1.15371 \tabularnewline
90 & 9 & 9.34508 & -0.34508 \tabularnewline
91 & 15 & 12.0058 & 2.99416 \tabularnewline
92 & 12 & 11.8021 & 0.197897 \tabularnewline
93 & 12 & 10.7422 & 1.25778 \tabularnewline
94 & 12 & 9.73876 & 2.26124 \tabularnewline
95 & 10 & 11.5951 & -1.5951 \tabularnewline
96 & 13 & 11.522 & 1.47799 \tabularnewline
97 & 9 & 11.4572 & -2.45717 \tabularnewline
98 & 12 & 11.5372 & 0.462847 \tabularnewline
99 & 10 & 10.5374 & -0.537421 \tabularnewline
100 & 14 & 11.6165 & 2.38353 \tabularnewline
101 & 11 & 11.522 & -0.52201 \tabularnewline
102 & 15 & 13.9541 & 1.04593 \tabularnewline
103 & 11 & 10.8122 & 0.18785 \tabularnewline
104 & 11 & 11.7045 & -0.704517 \tabularnewline
105 & 12 & 9.617 & 2.383 \tabularnewline
106 & 12 & 12.1439 & -0.14393 \tabularnewline
107 & 12 & 11.6182 & 0.381799 \tabularnewline
108 & 11 & 11.5552 & -0.555205 \tabularnewline
109 & 7 & 9.31014 & -2.31014 \tabularnewline
110 & 12 & 11.577 & 0.423022 \tabularnewline
111 & 14 & 11.5296 & 2.47037 \tabularnewline
112 & 11 & 12.4472 & -1.44724 \tabularnewline
113 & 11 & 9.77951 & 1.22049 \tabularnewline
114 & 10 & 9.21535 & 0.784655 \tabularnewline
115 & 13 & 12.6317 & 0.368295 \tabularnewline
116 & 13 & 10.6236 & 2.37637 \tabularnewline
117 & 8 & 10.6274 & -2.62737 \tabularnewline
118 & 11 & 9.93147 & 1.06853 \tabularnewline
119 & 12 & 11.5557 & 0.44434 \tabularnewline
120 & 11 & 9.92777 & 1.07223 \tabularnewline
121 & 13 & 11.3056 & 1.69442 \tabularnewline
122 & 12 & 9.9957 & 2.0043 \tabularnewline
123 & 14 & 11.7398 & 2.26022 \tabularnewline
124 & 13 & 10.8666 & 2.13339 \tabularnewline
125 & 15 & 11.5799 & 3.42014 \tabularnewline
126 & 10 & 10.9077 & -0.907734 \tabularnewline
127 & 11 & 12.2409 & -1.24095 \tabularnewline
128 & 9 & 11.0722 & -2.07218 \tabularnewline
129 & 11 & 9.19642 & 1.80358 \tabularnewline
130 & 10 & 11.5691 & -1.56907 \tabularnewline
131 & 11 & 8.00444 & 2.99556 \tabularnewline
132 & 8 & 11.6406 & -3.64057 \tabularnewline
133 & 11 & 9.14031 & 1.85969 \tabularnewline
134 & 12 & 10.53 & 1.47 \tabularnewline
135 & 12 & 10.7867 & 1.21334 \tabularnewline
136 & 9 & 9.30256 & -0.302563 \tabularnewline
137 & 11 & 10.9997 & 0.000282898 \tabularnewline
138 & 10 & 8.7223 & 1.2777 \tabularnewline
139 & 8 & 9.26327 & -1.26327 \tabularnewline
140 & 9 & 8.76174 & 0.238262 \tabularnewline
141 & 8 & 11.6135 & -3.61351 \tabularnewline
142 & 9 & 11.1106 & -2.11058 \tabularnewline
143 & 15 & 12.2236 & 2.7764 \tabularnewline
144 & 11 & 11.1795 & -0.179528 \tabularnewline
145 & 8 & 7.94034 & 0.0596642 \tabularnewline
146 & 13 & 12.4676 & 0.532362 \tabularnewline
147 & 12 & 9.89061 & 2.10939 \tabularnewline
148 & 12 & 11.4974 & 0.502578 \tabularnewline
149 & 9 & 9.67095 & -0.670945 \tabularnewline
150 & 7 & 8.24973 & -1.24973 \tabularnewline
151 & 13 & 10.9493 & 2.05066 \tabularnewline
152 & 9 & 11.7537 & -2.75368 \tabularnewline
153 & 6 & 11.7529 & -5.75286 \tabularnewline
154 & 8 & 10.29 & -2.29 \tabularnewline
155 & 8 & 7.92599 & 0.0740057 \tabularnewline
156 & 15 & 12.0058 & 2.99416 \tabularnewline
157 & 6 & 9.94521 & -3.94521 \tabularnewline
158 & 9 & 11.0722 & -2.07218 \tabularnewline
159 & 11 & 11.5387 & -0.538749 \tabularnewline
160 & 8 & 9.35694 & -1.35694 \tabularnewline
161 & 8 & 9.86073 & -1.86073 \tabularnewline
162 & 10 & 9.45393 & 0.546065 \tabularnewline
163 & 8 & 8.96445 & -0.96445 \tabularnewline
164 & 14 & 11.9376 & 2.0624 \tabularnewline
165 & 10 & 11.1085 & -1.10854 \tabularnewline
166 & 8 & 7.92055 & 0.0794465 \tabularnewline
167 & 11 & 10.4205 & 0.579491 \tabularnewline
168 & 12 & 8.41265 & 3.58735 \tabularnewline
169 & 12 & 9.95207 & 2.04793 \tabularnewline
170 & 12 & 11.6883 & 0.311745 \tabularnewline
171 & 5 & 9.01333 & -4.01333 \tabularnewline
172 & 12 & 11.6507 & 0.349268 \tabularnewline
173 & 10 & 9.24544 & 0.754563 \tabularnewline
174 & 7 & 7.18109 & -0.181091 \tabularnewline
175 & 12 & 8.99273 & 3.00727 \tabularnewline
176 & 11 & 11.0979 & -0.0978698 \tabularnewline
177 & 8 & 9.1549 & -1.1549 \tabularnewline
178 & 9 & 9.07618 & -0.0761809 \tabularnewline
179 & 10 & 10.3553 & -0.355309 \tabularnewline
180 & 9 & 9.31646 & -0.316457 \tabularnewline
181 & 12 & 11.6353 & 0.364654 \tabularnewline
182 & 6 & 8.5732 & -2.5732 \tabularnewline
183 & 15 & 13.4129 & 1.58714 \tabularnewline
184 & 12 & 10.9013 & 1.09871 \tabularnewline
185 & 12 & 6.8695 & 5.1305 \tabularnewline
186 & 12 & 11.5662 & 0.433771 \tabularnewline
187 & 11 & 12.092 & -1.09202 \tabularnewline
188 & 7 & 9.09221 & -2.09221 \tabularnewline
189 & 7 & 8.50051 & -1.50051 \tabularnewline
190 & 5 & 8.66588 & -3.66588 \tabularnewline
191 & 12 & 10.5096 & 1.4904 \tabularnewline
192 & 12 & 11.7795 & 0.220538 \tabularnewline
193 & 3 & 9.19974 & -6.19974 \tabularnewline
194 & 11 & 11.6231 & -0.623113 \tabularnewline
195 & 10 & 9.75231 & 0.247691 \tabularnewline
196 & 12 & 11.1177 & 0.882342 \tabularnewline
197 & 9 & 11.3517 & -2.35175 \tabularnewline
198 & 12 & 11.6474 & 0.3526 \tabularnewline
199 & 9 & 10.3101 & -1.31009 \tabularnewline
200 & 12 & 11.567 & 0.433042 \tabularnewline
201 & 12 & 11.4059 & 0.594132 \tabularnewline
202 & 10 & 10.3679 & -0.36793 \tabularnewline
203 & 9 & 8.57697 & 0.423032 \tabularnewline
204 & 12 & 9.16277 & 2.83723 \tabularnewline
205 & 8 & 11.0124 & -3.01235 \tabularnewline
206 & 11 & 11.0481 & -0.0480964 \tabularnewline
207 & 11 & 11.6694 & -0.669401 \tabularnewline
208 & 12 & 11.5801 & 0.419851 \tabularnewline
209 & 10 & 8.60315 & 1.39685 \tabularnewline
210 & 10 & 10.9453 & -0.945307 \tabularnewline
211 & 12 & 9.17275 & 2.82725 \tabularnewline
212 & 12 & 9.57252 & 2.42748 \tabularnewline
213 & 11 & 11.1262 & -0.126177 \tabularnewline
214 & 8 & 10.9598 & -2.95978 \tabularnewline
215 & 12 & 11.533 & 0.466998 \tabularnewline
216 & 10 & 10.1213 & -0.121284 \tabularnewline
217 & 11 & 12.1939 & -1.19394 \tabularnewline
218 & 10 & 10.3612 & -0.361196 \tabularnewline
219 & 8 & 9.73389 & -1.73389 \tabularnewline
220 & 12 & 11.1254 & 0.874633 \tabularnewline
221 & 12 & 9.80255 & 2.19745 \tabularnewline
222 & 10 & 10.4397 & -0.43969 \tabularnewline
223 & 12 & 10.8693 & 1.13069 \tabularnewline
224 & 9 & 9.2599 & -0.259898 \tabularnewline
225 & 9 & 9.80385 & -0.80385 \tabularnewline
226 & 6 & 7.07847 & -1.07847 \tabularnewline
227 & 10 & 10.3668 & -0.366755 \tabularnewline
228 & 9 & 10.4338 & -1.43381 \tabularnewline
229 & 9 & 8.51369 & 0.486311 \tabularnewline
230 & 9 & 9.29856 & -0.298558 \tabularnewline
231 & 6 & 9.68814 & -3.68814 \tabularnewline
232 & 10 & 8.23535 & 1.76465 \tabularnewline
233 & 6 & 11.628 & -5.62803 \tabularnewline
234 & 14 & 12.5365 & 1.46353 \tabularnewline
235 & 10 & 9.79942 & 0.200576 \tabularnewline
236 & 10 & 8.53545 & 1.46455 \tabularnewline
237 & 6 & 4.4085 & 1.5915 \tabularnewline
238 & 12 & 9.5426 & 2.4574 \tabularnewline
239 & 12 & 11.5377 & 0.46233 \tabularnewline
240 & 7 & 7.94008 & -0.940084 \tabularnewline
241 & 8 & 9.30035 & -1.30035 \tabularnewline
242 & 11 & 9.21243 & 1.78757 \tabularnewline
243 & 3 & 7.89956 & -4.89956 \tabularnewline
244 & 6 & 9.7405 & -3.7405 \tabularnewline
245 & 10 & 10.8122 & -0.81224 \tabularnewline
246 & 8 & 9.25082 & -1.25082 \tabularnewline
247 & 9 & 10.4349 & -1.43487 \tabularnewline
248 & 9 & 7.85484 & 1.14516 \tabularnewline
249 & 8 & 8.83356 & -0.833562 \tabularnewline
250 & 9 & 8.82442 & 0.175582 \tabularnewline
251 & 7 & 8.68701 & -1.68701 \tabularnewline
252 & 7 & 7.97831 & -0.978313 \tabularnewline
253 & 6 & 9.26036 & -3.26036 \tabularnewline
254 & 9 & 11.4914 & -2.49143 \tabularnewline
255 & 10 & 9.12856 & 0.871442 \tabularnewline
256 & 11 & 10.3417 & 0.65835 \tabularnewline
257 & 12 & 11.5584 & 0.441641 \tabularnewline
258 & 8 & 10.3045 & -2.30447 \tabularnewline
259 & 11 & 9.75942 & 1.24058 \tabularnewline
260 & 3 & 4.5687 & -1.5687 \tabularnewline
261 & 11 & 10.9153 & 0.0846638 \tabularnewline
262 & 12 & 8.83487 & 3.16513 \tabularnewline
263 & 7 & 8.5808 & -1.5808 \tabularnewline
264 & 9 & 10.3935 & -1.39351 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221697&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]9.91495[/C][C]2.08505[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]11.436[/C][C]-0.436049[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]13.358[/C][C]1.64196[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]10.9934[/C][C]-4.99343[/C][/ROW]
[ROW][C]5[/C][C]13[/C][C]10.3899[/C][C]2.6101[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]9.6238[/C][C]0.376202[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]12.9817[/C][C]-0.981727[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.0811[/C][C]2.91891[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]10.4565[/C][C]1.54353[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]11.0913[/C][C]-2.09131[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]11.4275[/C][C]-1.42751[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]11.5836[/C][C]0.416357[/C][/ROW]
[ROW][C]13[/C][C]12[/C][C]11.5336[/C][C]0.466374[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.6271[/C][C]-0.627102[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]12.2801[/C][C]2.71989[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]10.9457[/C][C]1.05429[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]10.8648[/C][C]-0.864761[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]13.9809[/C][C]-1.98087[/C][/ROW]
[ROW][C]19[/C][C]11[/C][C]12.8448[/C][C]-1.84476[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.4904[/C][C]0.509598[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]11.5712[/C][C]-0.571158[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]11.4686[/C][C]0.531429[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]13.3915[/C][C]-0.391541[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]11.7022[/C][C]-0.702232[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]12.0158[/C][C]-0.0158242[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]12.0548[/C][C]0.945183[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]11.5897[/C][C]-1.58967[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]11.0716[/C][C]2.92844[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.5068[/C][C]0.493182[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.3746[/C][C]-0.374643[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]10.9457[/C][C]1.05433[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.22377[/C][C]-1.22377[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.2866[/C][C]-0.286632[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.6908[/C][C]0.309223[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.2494[/C][C]1.75055[/C][/ROW]
[ROW][C]36[/C][C]7[/C][C]8.14582[/C][C]-1.14582[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]7.95586[/C][C]1.04414[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]10.3518[/C][C]1.64817[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]11.5246[/C][C]-1.52462[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]11.5512[/C][C]-1.55123[/C][/ROW]
[ROW][C]41[/C][C]10[/C][C]11.4985[/C][C]-1.4985[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.3404[/C][C]1.65958[/C][/ROW]
[ROW][C]43[/C][C]15[/C][C]13.8016[/C][C]1.19836[/C][/ROW]
[ROW][C]44[/C][C]10[/C][C]10.3454[/C][C]-0.345387[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.1558[/C][C]-0.155819[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]8.69035[/C][C]3.30965[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]10.6006[/C][C]2.39941[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.0124[/C][C]-0.012355[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]11.641[/C][C]-0.641004[/C][/ROW]
[ROW][C]50[/C][C]12[/C][C]10.3149[/C][C]1.68513[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]11.7607[/C][C]2.23926[/C][/ROW]
[ROW][C]52[/C][C]10[/C][C]10.2565[/C][C]-0.2565[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]9.17192[/C][C]2.82808[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.6968[/C][C]1.30319[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]7.50437[/C][C]-2.50437[/C][/ROW]
[ROW][C]56[/C][C]6[/C][C]10.3803[/C][C]-4.38031[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.4905[/C][C]0.50954[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]11.6604[/C][C]0.339598[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.0711[/C][C]-0.0711273[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]11.5203[/C][C]-1.52032[/C][/ROW]
[ROW][C]61[/C][C]7[/C][C]8.9873[/C][C]-1.9873[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]11.5276[/C][C]0.472405[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]11.6164[/C][C]2.38357[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.4563[/C][C]0.54375[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]11.435[/C][C]0.56503[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]12.2755[/C][C]0.724478[/C][/ROW]
[ROW][C]67[/C][C]14[/C][C]12.6739[/C][C]1.32612[/C][/ROW]
[ROW][C]68[/C][C]11[/C][C]12.505[/C][C]-1.50498[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]9.41781[/C][C]2.58219[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]11.6364[/C][C]0.363593[/C][/ROW]
[ROW][C]71[/C][C]8[/C][C]8.1297[/C][C]-0.129702[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]10.5472[/C][C]0.452779[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]12.889[/C][C]1.11102[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]12.965[/C][C]1.03501[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]11.3207[/C][C]0.679265[/C][/ROW]
[ROW][C]76[/C][C]9[/C][C]11.8437[/C][C]-2.84372[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.6215[/C][C]1.37852[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]11.3847[/C][C]-0.384743[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]9.7722[/C][C]2.2278[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.3174[/C][C]0.68258[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.6638[/C][C]0.336225[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]11.709[/C][C]0.290959[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]10.9129[/C][C]1.08706[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]11.0086[/C][C]-0.00861774[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]11.4497[/C][C]-1.4497[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]10.5425[/C][C]-1.54248[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]11.5776[/C][C]0.422397[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.5055[/C][C]0.494464[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]10.8463[/C][C]1.15371[/C][/ROW]
[ROW][C]90[/C][C]9[/C][C]9.34508[/C][C]-0.34508[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]12.0058[/C][C]2.99416[/C][/ROW]
[ROW][C]92[/C][C]12[/C][C]11.8021[/C][C]0.197897[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]10.7422[/C][C]1.25778[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]9.73876[/C][C]2.26124[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]11.5951[/C][C]-1.5951[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]11.522[/C][C]1.47799[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]11.4572[/C][C]-2.45717[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]11.5372[/C][C]0.462847[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]10.5374[/C][C]-0.537421[/C][/ROW]
[ROW][C]100[/C][C]14[/C][C]11.6165[/C][C]2.38353[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]11.522[/C][C]-0.52201[/C][/ROW]
[ROW][C]102[/C][C]15[/C][C]13.9541[/C][C]1.04593[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]10.8122[/C][C]0.18785[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]11.7045[/C][C]-0.704517[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]9.617[/C][C]2.383[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]12.1439[/C][C]-0.14393[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.6182[/C][C]0.381799[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]11.5552[/C][C]-0.555205[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]9.31014[/C][C]-2.31014[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]11.577[/C][C]0.423022[/C][/ROW]
[ROW][C]111[/C][C]14[/C][C]11.5296[/C][C]2.47037[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.4472[/C][C]-1.44724[/C][/ROW]
[ROW][C]113[/C][C]11[/C][C]9.77951[/C][C]1.22049[/C][/ROW]
[ROW][C]114[/C][C]10[/C][C]9.21535[/C][C]0.784655[/C][/ROW]
[ROW][C]115[/C][C]13[/C][C]12.6317[/C][C]0.368295[/C][/ROW]
[ROW][C]116[/C][C]13[/C][C]10.6236[/C][C]2.37637[/C][/ROW]
[ROW][C]117[/C][C]8[/C][C]10.6274[/C][C]-2.62737[/C][/ROW]
[ROW][C]118[/C][C]11[/C][C]9.93147[/C][C]1.06853[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]11.5557[/C][C]0.44434[/C][/ROW]
[ROW][C]120[/C][C]11[/C][C]9.92777[/C][C]1.07223[/C][/ROW]
[ROW][C]121[/C][C]13[/C][C]11.3056[/C][C]1.69442[/C][/ROW]
[ROW][C]122[/C][C]12[/C][C]9.9957[/C][C]2.0043[/C][/ROW]
[ROW][C]123[/C][C]14[/C][C]11.7398[/C][C]2.26022[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]10.8666[/C][C]2.13339[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]11.5799[/C][C]3.42014[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]10.9077[/C][C]-0.907734[/C][/ROW]
[ROW][C]127[/C][C]11[/C][C]12.2409[/C][C]-1.24095[/C][/ROW]
[ROW][C]128[/C][C]9[/C][C]11.0722[/C][C]-2.07218[/C][/ROW]
[ROW][C]129[/C][C]11[/C][C]9.19642[/C][C]1.80358[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]11.5691[/C][C]-1.56907[/C][/ROW]
[ROW][C]131[/C][C]11[/C][C]8.00444[/C][C]2.99556[/C][/ROW]
[ROW][C]132[/C][C]8[/C][C]11.6406[/C][C]-3.64057[/C][/ROW]
[ROW][C]133[/C][C]11[/C][C]9.14031[/C][C]1.85969[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]10.53[/C][C]1.47[/C][/ROW]
[ROW][C]135[/C][C]12[/C][C]10.7867[/C][C]1.21334[/C][/ROW]
[ROW][C]136[/C][C]9[/C][C]9.30256[/C][C]-0.302563[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]10.9997[/C][C]0.000282898[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]8.7223[/C][C]1.2777[/C][/ROW]
[ROW][C]139[/C][C]8[/C][C]9.26327[/C][C]-1.26327[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]8.76174[/C][C]0.238262[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]11.6135[/C][C]-3.61351[/C][/ROW]
[ROW][C]142[/C][C]9[/C][C]11.1106[/C][C]-2.11058[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]12.2236[/C][C]2.7764[/C][/ROW]
[ROW][C]144[/C][C]11[/C][C]11.1795[/C][C]-0.179528[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]7.94034[/C][C]0.0596642[/C][/ROW]
[ROW][C]146[/C][C]13[/C][C]12.4676[/C][C]0.532362[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]9.89061[/C][C]2.10939[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]11.4974[/C][C]0.502578[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]9.67095[/C][C]-0.670945[/C][/ROW]
[ROW][C]150[/C][C]7[/C][C]8.24973[/C][C]-1.24973[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]10.9493[/C][C]2.05066[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.7537[/C][C]-2.75368[/C][/ROW]
[ROW][C]153[/C][C]6[/C][C]11.7529[/C][C]-5.75286[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]10.29[/C][C]-2.29[/C][/ROW]
[ROW][C]155[/C][C]8[/C][C]7.92599[/C][C]0.0740057[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]12.0058[/C][C]2.99416[/C][/ROW]
[ROW][C]157[/C][C]6[/C][C]9.94521[/C][C]-3.94521[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]11.0722[/C][C]-2.07218[/C][/ROW]
[ROW][C]159[/C][C]11[/C][C]11.5387[/C][C]-0.538749[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]9.35694[/C][C]-1.35694[/C][/ROW]
[ROW][C]161[/C][C]8[/C][C]9.86073[/C][C]-1.86073[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.45393[/C][C]0.546065[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]8.96445[/C][C]-0.96445[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]11.9376[/C][C]2.0624[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.1085[/C][C]-1.10854[/C][/ROW]
[ROW][C]166[/C][C]8[/C][C]7.92055[/C][C]0.0794465[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.4205[/C][C]0.579491[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]8.41265[/C][C]3.58735[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]9.95207[/C][C]2.04793[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]11.6883[/C][C]0.311745[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]9.01333[/C][C]-4.01333[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.6507[/C][C]0.349268[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]9.24544[/C][C]0.754563[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]7.18109[/C][C]-0.181091[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]8.99273[/C][C]3.00727[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]11.0979[/C][C]-0.0978698[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]9.1549[/C][C]-1.1549[/C][/ROW]
[ROW][C]178[/C][C]9[/C][C]9.07618[/C][C]-0.0761809[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]10.3553[/C][C]-0.355309[/C][/ROW]
[ROW][C]180[/C][C]9[/C][C]9.31646[/C][C]-0.316457[/C][/ROW]
[ROW][C]181[/C][C]12[/C][C]11.6353[/C][C]0.364654[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]8.5732[/C][C]-2.5732[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]13.4129[/C][C]1.58714[/C][/ROW]
[ROW][C]184[/C][C]12[/C][C]10.9013[/C][C]1.09871[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]6.8695[/C][C]5.1305[/C][/ROW]
[ROW][C]186[/C][C]12[/C][C]11.5662[/C][C]0.433771[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]12.092[/C][C]-1.09202[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]9.09221[/C][C]-2.09221[/C][/ROW]
[ROW][C]189[/C][C]7[/C][C]8.50051[/C][C]-1.50051[/C][/ROW]
[ROW][C]190[/C][C]5[/C][C]8.66588[/C][C]-3.66588[/C][/ROW]
[ROW][C]191[/C][C]12[/C][C]10.5096[/C][C]1.4904[/C][/ROW]
[ROW][C]192[/C][C]12[/C][C]11.7795[/C][C]0.220538[/C][/ROW]
[ROW][C]193[/C][C]3[/C][C]9.19974[/C][C]-6.19974[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]11.6231[/C][C]-0.623113[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]9.75231[/C][C]0.247691[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]11.1177[/C][C]0.882342[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]11.3517[/C][C]-2.35175[/C][/ROW]
[ROW][C]198[/C][C]12[/C][C]11.6474[/C][C]0.3526[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]10.3101[/C][C]-1.31009[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]11.567[/C][C]0.433042[/C][/ROW]
[ROW][C]201[/C][C]12[/C][C]11.4059[/C][C]0.594132[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]10.3679[/C][C]-0.36793[/C][/ROW]
[ROW][C]203[/C][C]9[/C][C]8.57697[/C][C]0.423032[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]9.16277[/C][C]2.83723[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]11.0124[/C][C]-3.01235[/C][/ROW]
[ROW][C]206[/C][C]11[/C][C]11.0481[/C][C]-0.0480964[/C][/ROW]
[ROW][C]207[/C][C]11[/C][C]11.6694[/C][C]-0.669401[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]11.5801[/C][C]0.419851[/C][/ROW]
[ROW][C]209[/C][C]10[/C][C]8.60315[/C][C]1.39685[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]10.9453[/C][C]-0.945307[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]9.17275[/C][C]2.82725[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]9.57252[/C][C]2.42748[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.1262[/C][C]-0.126177[/C][/ROW]
[ROW][C]214[/C][C]8[/C][C]10.9598[/C][C]-2.95978[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]11.533[/C][C]0.466998[/C][/ROW]
[ROW][C]216[/C][C]10[/C][C]10.1213[/C][C]-0.121284[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]12.1939[/C][C]-1.19394[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]10.3612[/C][C]-0.361196[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.73389[/C][C]-1.73389[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]11.1254[/C][C]0.874633[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]9.80255[/C][C]2.19745[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]10.4397[/C][C]-0.43969[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]10.8693[/C][C]1.13069[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]9.2599[/C][C]-0.259898[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.80385[/C][C]-0.80385[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]7.07847[/C][C]-1.07847[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]10.3668[/C][C]-0.366755[/C][/ROW]
[ROW][C]228[/C][C]9[/C][C]10.4338[/C][C]-1.43381[/C][/ROW]
[ROW][C]229[/C][C]9[/C][C]8.51369[/C][C]0.486311[/C][/ROW]
[ROW][C]230[/C][C]9[/C][C]9.29856[/C][C]-0.298558[/C][/ROW]
[ROW][C]231[/C][C]6[/C][C]9.68814[/C][C]-3.68814[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.23535[/C][C]1.76465[/C][/ROW]
[ROW][C]233[/C][C]6[/C][C]11.628[/C][C]-5.62803[/C][/ROW]
[ROW][C]234[/C][C]14[/C][C]12.5365[/C][C]1.46353[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]9.79942[/C][C]0.200576[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]8.53545[/C][C]1.46455[/C][/ROW]
[ROW][C]237[/C][C]6[/C][C]4.4085[/C][C]1.5915[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]9.5426[/C][C]2.4574[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]11.5377[/C][C]0.46233[/C][/ROW]
[ROW][C]240[/C][C]7[/C][C]7.94008[/C][C]-0.940084[/C][/ROW]
[ROW][C]241[/C][C]8[/C][C]9.30035[/C][C]-1.30035[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]9.21243[/C][C]1.78757[/C][/ROW]
[ROW][C]243[/C][C]3[/C][C]7.89956[/C][C]-4.89956[/C][/ROW]
[ROW][C]244[/C][C]6[/C][C]9.7405[/C][C]-3.7405[/C][/ROW]
[ROW][C]245[/C][C]10[/C][C]10.8122[/C][C]-0.81224[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]9.25082[/C][C]-1.25082[/C][/ROW]
[ROW][C]247[/C][C]9[/C][C]10.4349[/C][C]-1.43487[/C][/ROW]
[ROW][C]248[/C][C]9[/C][C]7.85484[/C][C]1.14516[/C][/ROW]
[ROW][C]249[/C][C]8[/C][C]8.83356[/C][C]-0.833562[/C][/ROW]
[ROW][C]250[/C][C]9[/C][C]8.82442[/C][C]0.175582[/C][/ROW]
[ROW][C]251[/C][C]7[/C][C]8.68701[/C][C]-1.68701[/C][/ROW]
[ROW][C]252[/C][C]7[/C][C]7.97831[/C][C]-0.978313[/C][/ROW]
[ROW][C]253[/C][C]6[/C][C]9.26036[/C][C]-3.26036[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]11.4914[/C][C]-2.49143[/C][/ROW]
[ROW][C]255[/C][C]10[/C][C]9.12856[/C][C]0.871442[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]10.3417[/C][C]0.65835[/C][/ROW]
[ROW][C]257[/C][C]12[/C][C]11.5584[/C][C]0.441641[/C][/ROW]
[ROW][C]258[/C][C]8[/C][C]10.3045[/C][C]-2.30447[/C][/ROW]
[ROW][C]259[/C][C]11[/C][C]9.75942[/C][C]1.24058[/C][/ROW]
[ROW][C]260[/C][C]3[/C][C]4.5687[/C][C]-1.5687[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.9153[/C][C]0.0846638[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]8.83487[/C][C]3.16513[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]8.5808[/C][C]-1.5808[/C][/ROW]
[ROW][C]264[/C][C]9[/C][C]10.3935[/C][C]-1.39351[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221697&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221697&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
1129.914952.08505
21111.436-0.436049
31513.3581.64196
4610.9934-4.99343
51310.38992.6101
6109.62380.376202
71212.9817-0.981727
81411.08112.91891
91210.45651.54353
10911.0913-2.09131
111011.4275-1.42751
121211.58360.416357
131211.53360.466374
141111.6271-0.627102
151512.28012.71989
161210.94571.05429
171010.8648-0.864761
181213.9809-1.98087
191112.8448-1.84476
201211.49040.509598
211111.5712-0.571158
221211.46860.531429
231313.3915-0.391541
241111.7022-0.702232
251212.0158-0.0158242
261312.05480.945183
271011.5897-1.58967
281411.07162.92844
291211.50680.493182
301010.3746-0.374643
311210.94571.05433
3289.22377-1.22377
331010.2866-0.286632
341211.69080.309223
351210.24941.75055
3678.14582-1.14582
3797.955861.04414
381210.35181.64817
391011.5246-1.52462
401011.5512-1.55123
411011.4985-1.4985
421210.34041.65958
431513.80161.19836
441010.3454-0.345387
451010.1558-0.155819
46128.690353.30965
471310.60062.39941
481111.0124-0.012355
491111.641-0.641004
501210.31491.68513
511411.76072.23926
521010.2565-0.2565
53129.171922.82808
541311.69681.30319
5557.50437-2.50437
56610.3803-4.38031
571211.49050.50954
581211.66040.339598
591111.0711-0.0711273
601011.5203-1.52032
6178.9873-1.9873
621211.52760.472405
631411.61642.38357
641110.45630.54375
651211.4350.56503
661312.27550.724478
671412.67391.32612
681112.505-1.50498
69129.417812.58219
701211.63640.363593
7188.1297-0.129702
721110.54720.452779
731412.8891.11102
741412.9651.03501
751211.32070.679265
76911.8437-2.84372
771311.62151.37852
781111.3847-0.384743
79129.77222.2278
801211.31740.68258
811211.66380.336225
821211.7090.290959
831210.91291.08706
841111.0086-0.00861774
851011.4497-1.4497
86910.5425-1.54248
871211.57760.422397
881211.50550.494464
891210.84631.15371
9099.34508-0.34508
911512.00582.99416
921211.80210.197897
931210.74221.25778
94129.738762.26124
951011.5951-1.5951
961311.5221.47799
97911.4572-2.45717
981211.53720.462847
991010.5374-0.537421
1001411.61652.38353
1011111.522-0.52201
1021513.95411.04593
1031110.81220.18785
1041111.7045-0.704517
105129.6172.383
1061212.1439-0.14393
1071211.61820.381799
1081111.5552-0.555205
10979.31014-2.31014
1101211.5770.423022
1111411.52962.47037
1121112.4472-1.44724
113119.779511.22049
114109.215350.784655
1151312.63170.368295
1161310.62362.37637
117810.6274-2.62737
118119.931471.06853
1191211.55570.44434
120119.927771.07223
1211311.30561.69442
122129.99572.0043
1231411.73982.26022
1241310.86662.13339
1251511.57993.42014
1261010.9077-0.907734
1271112.2409-1.24095
128911.0722-2.07218
129119.196421.80358
1301011.5691-1.56907
131118.004442.99556
132811.6406-3.64057
133119.140311.85969
1341210.531.47
1351210.78671.21334
13699.30256-0.302563
1371110.99970.000282898
138108.72231.2777
13989.26327-1.26327
14098.761740.238262
141811.6135-3.61351
142911.1106-2.11058
1431512.22362.7764
1441111.1795-0.179528
14587.940340.0596642
1461312.46760.532362
147129.890612.10939
1481211.49740.502578
14999.67095-0.670945
15078.24973-1.24973
1511310.94932.05066
152911.7537-2.75368
153611.7529-5.75286
154810.29-2.29
15587.925990.0740057
1561512.00582.99416
15769.94521-3.94521
158911.0722-2.07218
1591111.5387-0.538749
16089.35694-1.35694
16189.86073-1.86073
162109.453930.546065
16388.96445-0.96445
1641411.93762.0624
1651011.1085-1.10854
16687.920550.0794465
1671110.42050.579491
168128.412653.58735
169129.952072.04793
1701211.68830.311745
17159.01333-4.01333
1721211.65070.349268
173109.245440.754563
17477.18109-0.181091
175128.992733.00727
1761111.0979-0.0978698
17789.1549-1.1549
17899.07618-0.0761809
1791010.3553-0.355309
18099.31646-0.316457
1811211.63530.364654
18268.5732-2.5732
1831513.41291.58714
1841210.90131.09871
185126.86955.1305
1861211.56620.433771
1871112.092-1.09202
18879.09221-2.09221
18978.50051-1.50051
19058.66588-3.66588
1911210.50961.4904
1921211.77950.220538
19339.19974-6.19974
1941111.6231-0.623113
195109.752310.247691
1961211.11770.882342
197911.3517-2.35175
1981211.64740.3526
199910.3101-1.31009
2001211.5670.433042
2011211.40590.594132
2021010.3679-0.36793
20398.576970.423032
204129.162772.83723
205811.0124-3.01235
2061111.0481-0.0480964
2071111.6694-0.669401
2081211.58010.419851
209108.603151.39685
2101010.9453-0.945307
211129.172752.82725
212129.572522.42748
2131111.1262-0.126177
214810.9598-2.95978
2151211.5330.466998
2161010.1213-0.121284
2171112.1939-1.19394
2181010.3612-0.361196
21989.73389-1.73389
2201211.12540.874633
221129.802552.19745
2221010.4397-0.43969
2231210.86931.13069
22499.2599-0.259898
22599.80385-0.80385
22667.07847-1.07847
2271010.3668-0.366755
228910.4338-1.43381
22998.513690.486311
23099.29856-0.298558
23169.68814-3.68814
232108.235351.76465
233611.628-5.62803
2341412.53651.46353
235109.799420.200576
236108.535451.46455
23764.40851.5915
238129.54262.4574
2391211.53770.46233
24077.94008-0.940084
24189.30035-1.30035
242119.212431.78757
24337.89956-4.89956
24469.7405-3.7405
2451010.8122-0.81224
24689.25082-1.25082
247910.4349-1.43487
24897.854841.14516
24988.83356-0.833562
25098.824420.175582
25178.68701-1.68701
25277.97831-0.978313
25369.26036-3.26036
254911.4914-2.49143
255109.128560.871442
2561110.34170.65835
2571211.55840.441641
258810.3045-2.30447
259119.759421.24058
26034.5687-1.5687
2611110.91530.0846638
262128.834873.16513
26378.5808-1.5808
264910.3935-1.39351






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9068470.1863060.0931528
100.9887610.02247830.0112392
110.9790040.04199260.0209963
120.9626180.07476460.0373823
130.9441730.1116540.055827
140.9380850.1238290.0619147
150.9238980.1522040.0761021
160.8959910.2080170.104009
170.853490.293020.14651
180.8631590.2736820.136841
190.832470.3350590.16753
200.7805180.4389640.219482
210.7346570.5306860.265343
220.6879760.6240480.312024
230.6264280.7471450.373572
240.5808320.8383360.419168
250.5325020.9349950.467498
260.585130.829740.41487
270.5684970.8630050.431503
280.5888160.8223670.411184
290.5279780.9440430.472022
300.480710.961420.51929
310.4342530.8685060.565747
320.4772030.9544070.522797
330.4195350.839070.580465
340.3636140.7272270.636386
350.3577490.7154990.642251
360.3564790.7129580.643521
370.3077020.6154040.692298
380.2941890.5883790.705811
390.2746380.5492750.725362
400.252990.505980.74701
410.2260710.4521420.773929
420.2083020.4166040.791698
430.225010.4500190.77499
440.1911320.3822650.808868
450.1583440.3166890.841656
460.2022770.4045540.797723
470.2031220.4062430.796878
480.1701140.3402270.829886
490.1543770.3087550.845623
500.1447550.2895110.855245
510.1523790.3047580.847621
520.126650.2532990.87335
530.1342440.2684890.865756
540.1146810.2293620.885319
550.1849110.3698210.815089
560.425360.8507190.57464
570.3847410.7694830.615259
580.3439740.6879470.656026
590.3053870.6107730.694613
600.3009590.6019190.699041
610.3085920.6171830.691408
620.2737750.5475510.726225
630.2930250.586050.706975
640.257960.515920.74204
650.2305860.4611720.769414
660.2012580.4025170.798742
670.1843990.3687970.815601
680.1647090.3294170.835291
690.1630870.3261730.836913
700.1392890.2785790.860711
710.1231220.2462430.876878
720.1047680.2095360.895232
730.08983350.1796670.910167
740.07606070.1521210.923939
750.0700970.1401940.929903
760.08534310.1706860.914657
770.07598170.1519630.924018
780.06271860.1254370.937281
790.06894260.1378850.931057
800.0635770.1271540.936423
810.05237120.1047420.947629
820.04298090.08596170.957019
830.03754050.07508110.962459
840.0303360.0606720.969664
850.02756280.05512550.972437
860.03102490.06204980.968975
870.02493950.0498790.97506
880.02005970.04011940.97994
890.01713210.03426430.982868
900.01435480.02870950.985645
910.02363780.04727550.976362
920.01944640.03889280.980554
930.01802110.03604220.981979
940.02008540.04017080.979915
950.01967440.03934870.980326
960.01774360.03548730.982256
970.02163560.04327130.978364
980.01750410.03500820.982496
990.01476420.02952840.985236
1000.01765430.03530850.982346
1010.01452730.02905460.985473
1020.01237050.02474090.98763
1030.009723830.01944770.990276
1040.008506740.01701350.991493
1050.0097250.019450.990275
1060.007576290.01515260.992424
1070.005926370.01185270.994074
1080.004843160.009686320.995157
1090.007217530.01443510.992782
1100.005637030.01127410.994363
1110.006746920.01349380.993253
1120.007015950.01403190.992984
1130.005949150.01189830.994051
1140.004773240.009546480.995227
1150.003719160.007438330.996281
1160.004219620.008439230.99578
1170.006630860.01326170.993369
1180.005500780.01100160.994499
1190.00430510.008610190.995695
1200.003533240.007066470.996467
1210.003422710.006845420.996577
1220.00357350.007147010.996426
1230.004209790.008419580.99579
1240.004747810.009495630.995252
1250.009052660.01810530.990947
1260.007509760.01501950.99249
1270.006374980.012750.993625
1280.007058550.01411710.992941
1290.006908240.01381650.993092
1300.00678250.0135650.993218
1310.008726830.01745370.991273
1320.01715920.03431830.982841
1330.01654040.03308080.98346
1340.01543010.03086010.98457
1350.01357820.02715640.986422
1360.01115580.02231170.988844
1370.008891470.01778290.991109
1380.007722440.01544490.992278
1390.007094980.014190.992905
1400.005730060.01146010.99427
1410.01216940.02433890.987831
1420.01357470.02714940.986425
1430.01895810.03791620.981042
1440.01522830.03045660.984772
1450.01211050.02422090.98789
1460.009851350.01970270.990149
1470.01054350.0210870.989456
1480.008551090.01710220.991449
1490.007168670.01433730.992831
1500.006413650.01282730.993586
1510.007028680.01405740.992971
1520.009196680.01839340.990803
1530.05757870.1151570.942421
1540.06508390.1301680.934916
1550.05493410.1098680.945066
1560.07585790.1517160.924142
1570.1350560.2701110.864944
1580.1380180.2760360.861982
1590.1202870.2405740.879713
1600.1139580.2279150.886042
1610.1149740.2299490.885026
1620.1011970.2023940.898803
1630.09029280.1805860.909707
1640.09850880.1970180.901491
1650.08882040.1776410.91118
1660.07583460.1516690.924165
1670.0650610.1301220.934939
1680.1083880.2167760.891612
1690.111420.222840.88858
1700.0967640.1935280.903236
1710.1669640.3339280.833036
1720.1460040.2920080.853996
1730.1291240.2582490.870876
1740.1116570.2233150.888343
1750.150280.3005590.84972
1760.1299680.2599360.870032
1770.1175120.2350240.882488
1780.1008910.2017810.899109
1790.08597320.1719460.914027
1800.07243330.1448670.927567
1810.06127290.1225460.938727
1820.0703410.1406820.929659
1830.07214590.1442920.927854
1840.0665970.1331940.933403
1850.2375450.475090.762455
1860.2143620.4287230.785638
1870.1932010.3864020.806799
1880.2019960.4039930.798004
1890.1878620.3757230.812138
1900.2683690.5367380.731631
1910.2666050.5332090.733395
1920.2357590.4715170.764241
1930.6103210.7793570.389679
1940.5730690.8538610.426931
1950.53620.92760.4638
1960.5090970.9818070.490903
1970.535390.929220.46461
1980.4985890.9971780.501411
1990.4740160.9480320.525984
2000.4624080.9248160.537592
2010.4419720.8839440.558028
2020.4176170.8352340.582383
2030.380230.760460.61977
2040.4555850.911170.544415
2050.4943210.9886430.505679
2060.4519140.9038270.548086
2070.4101640.8203280.589836
2080.3715110.7430230.628489
2090.3542950.708590.645705
2100.3177030.6354050.682297
2110.3928440.7856880.607156
2120.4198990.8397970.580101
2130.3786650.757330.621335
2140.396830.7936590.60317
2150.3598480.7196960.640152
2160.3236410.6472830.676359
2170.2862740.5725480.713726
2180.2474760.4949520.752524
2190.2498280.4996560.750172
2200.2289980.4579950.771002
2210.2734740.5469480.726526
2220.2337480.4674960.766252
2230.2239520.4479040.776048
2240.1971450.394290.802855
2250.1686690.3373380.831331
2260.1407360.2814730.859264
2270.1169270.2338540.883073
2280.09620190.1924040.903798
2290.07549670.1509930.924503
2300.05911180.1182240.940888
2310.08942330.1788470.910577
2320.1110220.2220450.888978
2330.3192990.6385970.680701
2340.2773910.5547810.722609
2350.2312250.462450.768775
2360.2262020.4524030.773798
2370.2260450.452090.773955
2380.3089430.6178860.691057
2390.3162530.6325060.683747
2400.2682870.5365740.731713
2410.218450.4368990.78155
2420.3048950.609790.695105
2430.6009870.7980260.399013
2440.7369610.5260790.263039
2450.676240.647520.32376
2460.630650.7386990.36935
2470.5840120.8319750.415988
2480.501040.9979190.49896
2490.4090640.8181290.590936
2500.4259580.8519150.574042
2510.5702460.8595080.429754
2520.7396160.5207690.260384
2530.7975920.4048150.202408
2540.8424750.3150510.157525
2550.7980540.4038920.201946

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.906847 & 0.186306 & 0.0931528 \tabularnewline
10 & 0.988761 & 0.0224783 & 0.0112392 \tabularnewline
11 & 0.979004 & 0.0419926 & 0.0209963 \tabularnewline
12 & 0.962618 & 0.0747646 & 0.0373823 \tabularnewline
13 & 0.944173 & 0.111654 & 0.055827 \tabularnewline
14 & 0.938085 & 0.123829 & 0.0619147 \tabularnewline
15 & 0.923898 & 0.152204 & 0.0761021 \tabularnewline
16 & 0.895991 & 0.208017 & 0.104009 \tabularnewline
17 & 0.85349 & 0.29302 & 0.14651 \tabularnewline
18 & 0.863159 & 0.273682 & 0.136841 \tabularnewline
19 & 0.83247 & 0.335059 & 0.16753 \tabularnewline
20 & 0.780518 & 0.438964 & 0.219482 \tabularnewline
21 & 0.734657 & 0.530686 & 0.265343 \tabularnewline
22 & 0.687976 & 0.624048 & 0.312024 \tabularnewline
23 & 0.626428 & 0.747145 & 0.373572 \tabularnewline
24 & 0.580832 & 0.838336 & 0.419168 \tabularnewline
25 & 0.532502 & 0.934995 & 0.467498 \tabularnewline
26 & 0.58513 & 0.82974 & 0.41487 \tabularnewline
27 & 0.568497 & 0.863005 & 0.431503 \tabularnewline
28 & 0.588816 & 0.822367 & 0.411184 \tabularnewline
29 & 0.527978 & 0.944043 & 0.472022 \tabularnewline
30 & 0.48071 & 0.96142 & 0.51929 \tabularnewline
31 & 0.434253 & 0.868506 & 0.565747 \tabularnewline
32 & 0.477203 & 0.954407 & 0.522797 \tabularnewline
33 & 0.419535 & 0.83907 & 0.580465 \tabularnewline
34 & 0.363614 & 0.727227 & 0.636386 \tabularnewline
35 & 0.357749 & 0.715499 & 0.642251 \tabularnewline
36 & 0.356479 & 0.712958 & 0.643521 \tabularnewline
37 & 0.307702 & 0.615404 & 0.692298 \tabularnewline
38 & 0.294189 & 0.588379 & 0.705811 \tabularnewline
39 & 0.274638 & 0.549275 & 0.725362 \tabularnewline
40 & 0.25299 & 0.50598 & 0.74701 \tabularnewline
41 & 0.226071 & 0.452142 & 0.773929 \tabularnewline
42 & 0.208302 & 0.416604 & 0.791698 \tabularnewline
43 & 0.22501 & 0.450019 & 0.77499 \tabularnewline
44 & 0.191132 & 0.382265 & 0.808868 \tabularnewline
45 & 0.158344 & 0.316689 & 0.841656 \tabularnewline
46 & 0.202277 & 0.404554 & 0.797723 \tabularnewline
47 & 0.203122 & 0.406243 & 0.796878 \tabularnewline
48 & 0.170114 & 0.340227 & 0.829886 \tabularnewline
49 & 0.154377 & 0.308755 & 0.845623 \tabularnewline
50 & 0.144755 & 0.289511 & 0.855245 \tabularnewline
51 & 0.152379 & 0.304758 & 0.847621 \tabularnewline
52 & 0.12665 & 0.253299 & 0.87335 \tabularnewline
53 & 0.134244 & 0.268489 & 0.865756 \tabularnewline
54 & 0.114681 & 0.229362 & 0.885319 \tabularnewline
55 & 0.184911 & 0.369821 & 0.815089 \tabularnewline
56 & 0.42536 & 0.850719 & 0.57464 \tabularnewline
57 & 0.384741 & 0.769483 & 0.615259 \tabularnewline
58 & 0.343974 & 0.687947 & 0.656026 \tabularnewline
59 & 0.305387 & 0.610773 & 0.694613 \tabularnewline
60 & 0.300959 & 0.601919 & 0.699041 \tabularnewline
61 & 0.308592 & 0.617183 & 0.691408 \tabularnewline
62 & 0.273775 & 0.547551 & 0.726225 \tabularnewline
63 & 0.293025 & 0.58605 & 0.706975 \tabularnewline
64 & 0.25796 & 0.51592 & 0.74204 \tabularnewline
65 & 0.230586 & 0.461172 & 0.769414 \tabularnewline
66 & 0.201258 & 0.402517 & 0.798742 \tabularnewline
67 & 0.184399 & 0.368797 & 0.815601 \tabularnewline
68 & 0.164709 & 0.329417 & 0.835291 \tabularnewline
69 & 0.163087 & 0.326173 & 0.836913 \tabularnewline
70 & 0.139289 & 0.278579 & 0.860711 \tabularnewline
71 & 0.123122 & 0.246243 & 0.876878 \tabularnewline
72 & 0.104768 & 0.209536 & 0.895232 \tabularnewline
73 & 0.0898335 & 0.179667 & 0.910167 \tabularnewline
74 & 0.0760607 & 0.152121 & 0.923939 \tabularnewline
75 & 0.070097 & 0.140194 & 0.929903 \tabularnewline
76 & 0.0853431 & 0.170686 & 0.914657 \tabularnewline
77 & 0.0759817 & 0.151963 & 0.924018 \tabularnewline
78 & 0.0627186 & 0.125437 & 0.937281 \tabularnewline
79 & 0.0689426 & 0.137885 & 0.931057 \tabularnewline
80 & 0.063577 & 0.127154 & 0.936423 \tabularnewline
81 & 0.0523712 & 0.104742 & 0.947629 \tabularnewline
82 & 0.0429809 & 0.0859617 & 0.957019 \tabularnewline
83 & 0.0375405 & 0.0750811 & 0.962459 \tabularnewline
84 & 0.030336 & 0.060672 & 0.969664 \tabularnewline
85 & 0.0275628 & 0.0551255 & 0.972437 \tabularnewline
86 & 0.0310249 & 0.0620498 & 0.968975 \tabularnewline
87 & 0.0249395 & 0.049879 & 0.97506 \tabularnewline
88 & 0.0200597 & 0.0401194 & 0.97994 \tabularnewline
89 & 0.0171321 & 0.0342643 & 0.982868 \tabularnewline
90 & 0.0143548 & 0.0287095 & 0.985645 \tabularnewline
91 & 0.0236378 & 0.0472755 & 0.976362 \tabularnewline
92 & 0.0194464 & 0.0388928 & 0.980554 \tabularnewline
93 & 0.0180211 & 0.0360422 & 0.981979 \tabularnewline
94 & 0.0200854 & 0.0401708 & 0.979915 \tabularnewline
95 & 0.0196744 & 0.0393487 & 0.980326 \tabularnewline
96 & 0.0177436 & 0.0354873 & 0.982256 \tabularnewline
97 & 0.0216356 & 0.0432713 & 0.978364 \tabularnewline
98 & 0.0175041 & 0.0350082 & 0.982496 \tabularnewline
99 & 0.0147642 & 0.0295284 & 0.985236 \tabularnewline
100 & 0.0176543 & 0.0353085 & 0.982346 \tabularnewline
101 & 0.0145273 & 0.0290546 & 0.985473 \tabularnewline
102 & 0.0123705 & 0.0247409 & 0.98763 \tabularnewline
103 & 0.00972383 & 0.0194477 & 0.990276 \tabularnewline
104 & 0.00850674 & 0.0170135 & 0.991493 \tabularnewline
105 & 0.009725 & 0.01945 & 0.990275 \tabularnewline
106 & 0.00757629 & 0.0151526 & 0.992424 \tabularnewline
107 & 0.00592637 & 0.0118527 & 0.994074 \tabularnewline
108 & 0.00484316 & 0.00968632 & 0.995157 \tabularnewline
109 & 0.00721753 & 0.0144351 & 0.992782 \tabularnewline
110 & 0.00563703 & 0.0112741 & 0.994363 \tabularnewline
111 & 0.00674692 & 0.0134938 & 0.993253 \tabularnewline
112 & 0.00701595 & 0.0140319 & 0.992984 \tabularnewline
113 & 0.00594915 & 0.0118983 & 0.994051 \tabularnewline
114 & 0.00477324 & 0.00954648 & 0.995227 \tabularnewline
115 & 0.00371916 & 0.00743833 & 0.996281 \tabularnewline
116 & 0.00421962 & 0.00843923 & 0.99578 \tabularnewline
117 & 0.00663086 & 0.0132617 & 0.993369 \tabularnewline
118 & 0.00550078 & 0.0110016 & 0.994499 \tabularnewline
119 & 0.0043051 & 0.00861019 & 0.995695 \tabularnewline
120 & 0.00353324 & 0.00706647 & 0.996467 \tabularnewline
121 & 0.00342271 & 0.00684542 & 0.996577 \tabularnewline
122 & 0.0035735 & 0.00714701 & 0.996426 \tabularnewline
123 & 0.00420979 & 0.00841958 & 0.99579 \tabularnewline
124 & 0.00474781 & 0.00949563 & 0.995252 \tabularnewline
125 & 0.00905266 & 0.0181053 & 0.990947 \tabularnewline
126 & 0.00750976 & 0.0150195 & 0.99249 \tabularnewline
127 & 0.00637498 & 0.01275 & 0.993625 \tabularnewline
128 & 0.00705855 & 0.0141171 & 0.992941 \tabularnewline
129 & 0.00690824 & 0.0138165 & 0.993092 \tabularnewline
130 & 0.0067825 & 0.013565 & 0.993218 \tabularnewline
131 & 0.00872683 & 0.0174537 & 0.991273 \tabularnewline
132 & 0.0171592 & 0.0343183 & 0.982841 \tabularnewline
133 & 0.0165404 & 0.0330808 & 0.98346 \tabularnewline
134 & 0.0154301 & 0.0308601 & 0.98457 \tabularnewline
135 & 0.0135782 & 0.0271564 & 0.986422 \tabularnewline
136 & 0.0111558 & 0.0223117 & 0.988844 \tabularnewline
137 & 0.00889147 & 0.0177829 & 0.991109 \tabularnewline
138 & 0.00772244 & 0.0154449 & 0.992278 \tabularnewline
139 & 0.00709498 & 0.01419 & 0.992905 \tabularnewline
140 & 0.00573006 & 0.0114601 & 0.99427 \tabularnewline
141 & 0.0121694 & 0.0243389 & 0.987831 \tabularnewline
142 & 0.0135747 & 0.0271494 & 0.986425 \tabularnewline
143 & 0.0189581 & 0.0379162 & 0.981042 \tabularnewline
144 & 0.0152283 & 0.0304566 & 0.984772 \tabularnewline
145 & 0.0121105 & 0.0242209 & 0.98789 \tabularnewline
146 & 0.00985135 & 0.0197027 & 0.990149 \tabularnewline
147 & 0.0105435 & 0.021087 & 0.989456 \tabularnewline
148 & 0.00855109 & 0.0171022 & 0.991449 \tabularnewline
149 & 0.00716867 & 0.0143373 & 0.992831 \tabularnewline
150 & 0.00641365 & 0.0128273 & 0.993586 \tabularnewline
151 & 0.00702868 & 0.0140574 & 0.992971 \tabularnewline
152 & 0.00919668 & 0.0183934 & 0.990803 \tabularnewline
153 & 0.0575787 & 0.115157 & 0.942421 \tabularnewline
154 & 0.0650839 & 0.130168 & 0.934916 \tabularnewline
155 & 0.0549341 & 0.109868 & 0.945066 \tabularnewline
156 & 0.0758579 & 0.151716 & 0.924142 \tabularnewline
157 & 0.135056 & 0.270111 & 0.864944 \tabularnewline
158 & 0.138018 & 0.276036 & 0.861982 \tabularnewline
159 & 0.120287 & 0.240574 & 0.879713 \tabularnewline
160 & 0.113958 & 0.227915 & 0.886042 \tabularnewline
161 & 0.114974 & 0.229949 & 0.885026 \tabularnewline
162 & 0.101197 & 0.202394 & 0.898803 \tabularnewline
163 & 0.0902928 & 0.180586 & 0.909707 \tabularnewline
164 & 0.0985088 & 0.197018 & 0.901491 \tabularnewline
165 & 0.0888204 & 0.177641 & 0.91118 \tabularnewline
166 & 0.0758346 & 0.151669 & 0.924165 \tabularnewline
167 & 0.065061 & 0.130122 & 0.934939 \tabularnewline
168 & 0.108388 & 0.216776 & 0.891612 \tabularnewline
169 & 0.11142 & 0.22284 & 0.88858 \tabularnewline
170 & 0.096764 & 0.193528 & 0.903236 \tabularnewline
171 & 0.166964 & 0.333928 & 0.833036 \tabularnewline
172 & 0.146004 & 0.292008 & 0.853996 \tabularnewline
173 & 0.129124 & 0.258249 & 0.870876 \tabularnewline
174 & 0.111657 & 0.223315 & 0.888343 \tabularnewline
175 & 0.15028 & 0.300559 & 0.84972 \tabularnewline
176 & 0.129968 & 0.259936 & 0.870032 \tabularnewline
177 & 0.117512 & 0.235024 & 0.882488 \tabularnewline
178 & 0.100891 & 0.201781 & 0.899109 \tabularnewline
179 & 0.0859732 & 0.171946 & 0.914027 \tabularnewline
180 & 0.0724333 & 0.144867 & 0.927567 \tabularnewline
181 & 0.0612729 & 0.122546 & 0.938727 \tabularnewline
182 & 0.070341 & 0.140682 & 0.929659 \tabularnewline
183 & 0.0721459 & 0.144292 & 0.927854 \tabularnewline
184 & 0.066597 & 0.133194 & 0.933403 \tabularnewline
185 & 0.237545 & 0.47509 & 0.762455 \tabularnewline
186 & 0.214362 & 0.428723 & 0.785638 \tabularnewline
187 & 0.193201 & 0.386402 & 0.806799 \tabularnewline
188 & 0.201996 & 0.403993 & 0.798004 \tabularnewline
189 & 0.187862 & 0.375723 & 0.812138 \tabularnewline
190 & 0.268369 & 0.536738 & 0.731631 \tabularnewline
191 & 0.266605 & 0.533209 & 0.733395 \tabularnewline
192 & 0.235759 & 0.471517 & 0.764241 \tabularnewline
193 & 0.610321 & 0.779357 & 0.389679 \tabularnewline
194 & 0.573069 & 0.853861 & 0.426931 \tabularnewline
195 & 0.5362 & 0.9276 & 0.4638 \tabularnewline
196 & 0.509097 & 0.981807 & 0.490903 \tabularnewline
197 & 0.53539 & 0.92922 & 0.46461 \tabularnewline
198 & 0.498589 & 0.997178 & 0.501411 \tabularnewline
199 & 0.474016 & 0.948032 & 0.525984 \tabularnewline
200 & 0.462408 & 0.924816 & 0.537592 \tabularnewline
201 & 0.441972 & 0.883944 & 0.558028 \tabularnewline
202 & 0.417617 & 0.835234 & 0.582383 \tabularnewline
203 & 0.38023 & 0.76046 & 0.61977 \tabularnewline
204 & 0.455585 & 0.91117 & 0.544415 \tabularnewline
205 & 0.494321 & 0.988643 & 0.505679 \tabularnewline
206 & 0.451914 & 0.903827 & 0.548086 \tabularnewline
207 & 0.410164 & 0.820328 & 0.589836 \tabularnewline
208 & 0.371511 & 0.743023 & 0.628489 \tabularnewline
209 & 0.354295 & 0.70859 & 0.645705 \tabularnewline
210 & 0.317703 & 0.635405 & 0.682297 \tabularnewline
211 & 0.392844 & 0.785688 & 0.607156 \tabularnewline
212 & 0.419899 & 0.839797 & 0.580101 \tabularnewline
213 & 0.378665 & 0.75733 & 0.621335 \tabularnewline
214 & 0.39683 & 0.793659 & 0.60317 \tabularnewline
215 & 0.359848 & 0.719696 & 0.640152 \tabularnewline
216 & 0.323641 & 0.647283 & 0.676359 \tabularnewline
217 & 0.286274 & 0.572548 & 0.713726 \tabularnewline
218 & 0.247476 & 0.494952 & 0.752524 \tabularnewline
219 & 0.249828 & 0.499656 & 0.750172 \tabularnewline
220 & 0.228998 & 0.457995 & 0.771002 \tabularnewline
221 & 0.273474 & 0.546948 & 0.726526 \tabularnewline
222 & 0.233748 & 0.467496 & 0.766252 \tabularnewline
223 & 0.223952 & 0.447904 & 0.776048 \tabularnewline
224 & 0.197145 & 0.39429 & 0.802855 \tabularnewline
225 & 0.168669 & 0.337338 & 0.831331 \tabularnewline
226 & 0.140736 & 0.281473 & 0.859264 \tabularnewline
227 & 0.116927 & 0.233854 & 0.883073 \tabularnewline
228 & 0.0962019 & 0.192404 & 0.903798 \tabularnewline
229 & 0.0754967 & 0.150993 & 0.924503 \tabularnewline
230 & 0.0591118 & 0.118224 & 0.940888 \tabularnewline
231 & 0.0894233 & 0.178847 & 0.910577 \tabularnewline
232 & 0.111022 & 0.222045 & 0.888978 \tabularnewline
233 & 0.319299 & 0.638597 & 0.680701 \tabularnewline
234 & 0.277391 & 0.554781 & 0.722609 \tabularnewline
235 & 0.231225 & 0.46245 & 0.768775 \tabularnewline
236 & 0.226202 & 0.452403 & 0.773798 \tabularnewline
237 & 0.226045 & 0.45209 & 0.773955 \tabularnewline
238 & 0.308943 & 0.617886 & 0.691057 \tabularnewline
239 & 0.316253 & 0.632506 & 0.683747 \tabularnewline
240 & 0.268287 & 0.536574 & 0.731713 \tabularnewline
241 & 0.21845 & 0.436899 & 0.78155 \tabularnewline
242 & 0.304895 & 0.60979 & 0.695105 \tabularnewline
243 & 0.600987 & 0.798026 & 0.399013 \tabularnewline
244 & 0.736961 & 0.526079 & 0.263039 \tabularnewline
245 & 0.67624 & 0.64752 & 0.32376 \tabularnewline
246 & 0.63065 & 0.738699 & 0.36935 \tabularnewline
247 & 0.584012 & 0.831975 & 0.415988 \tabularnewline
248 & 0.50104 & 0.997919 & 0.49896 \tabularnewline
249 & 0.409064 & 0.818129 & 0.590936 \tabularnewline
250 & 0.425958 & 0.851915 & 0.574042 \tabularnewline
251 & 0.570246 & 0.859508 & 0.429754 \tabularnewline
252 & 0.739616 & 0.520769 & 0.260384 \tabularnewline
253 & 0.797592 & 0.404815 & 0.202408 \tabularnewline
254 & 0.842475 & 0.315051 & 0.157525 \tabularnewline
255 & 0.798054 & 0.403892 & 0.201946 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221697&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]9[/C][C]0.906847[/C][C]0.186306[/C][C]0.0931528[/C][/ROW]
[ROW][C]10[/C][C]0.988761[/C][C]0.0224783[/C][C]0.0112392[/C][/ROW]
[ROW][C]11[/C][C]0.979004[/C][C]0.0419926[/C][C]0.0209963[/C][/ROW]
[ROW][C]12[/C][C]0.962618[/C][C]0.0747646[/C][C]0.0373823[/C][/ROW]
[ROW][C]13[/C][C]0.944173[/C][C]0.111654[/C][C]0.055827[/C][/ROW]
[ROW][C]14[/C][C]0.938085[/C][C]0.123829[/C][C]0.0619147[/C][/ROW]
[ROW][C]15[/C][C]0.923898[/C][C]0.152204[/C][C]0.0761021[/C][/ROW]
[ROW][C]16[/C][C]0.895991[/C][C]0.208017[/C][C]0.104009[/C][/ROW]
[ROW][C]17[/C][C]0.85349[/C][C]0.29302[/C][C]0.14651[/C][/ROW]
[ROW][C]18[/C][C]0.863159[/C][C]0.273682[/C][C]0.136841[/C][/ROW]
[ROW][C]19[/C][C]0.83247[/C][C]0.335059[/C][C]0.16753[/C][/ROW]
[ROW][C]20[/C][C]0.780518[/C][C]0.438964[/C][C]0.219482[/C][/ROW]
[ROW][C]21[/C][C]0.734657[/C][C]0.530686[/C][C]0.265343[/C][/ROW]
[ROW][C]22[/C][C]0.687976[/C][C]0.624048[/C][C]0.312024[/C][/ROW]
[ROW][C]23[/C][C]0.626428[/C][C]0.747145[/C][C]0.373572[/C][/ROW]
[ROW][C]24[/C][C]0.580832[/C][C]0.838336[/C][C]0.419168[/C][/ROW]
[ROW][C]25[/C][C]0.532502[/C][C]0.934995[/C][C]0.467498[/C][/ROW]
[ROW][C]26[/C][C]0.58513[/C][C]0.82974[/C][C]0.41487[/C][/ROW]
[ROW][C]27[/C][C]0.568497[/C][C]0.863005[/C][C]0.431503[/C][/ROW]
[ROW][C]28[/C][C]0.588816[/C][C]0.822367[/C][C]0.411184[/C][/ROW]
[ROW][C]29[/C][C]0.527978[/C][C]0.944043[/C][C]0.472022[/C][/ROW]
[ROW][C]30[/C][C]0.48071[/C][C]0.96142[/C][C]0.51929[/C][/ROW]
[ROW][C]31[/C][C]0.434253[/C][C]0.868506[/C][C]0.565747[/C][/ROW]
[ROW][C]32[/C][C]0.477203[/C][C]0.954407[/C][C]0.522797[/C][/ROW]
[ROW][C]33[/C][C]0.419535[/C][C]0.83907[/C][C]0.580465[/C][/ROW]
[ROW][C]34[/C][C]0.363614[/C][C]0.727227[/C][C]0.636386[/C][/ROW]
[ROW][C]35[/C][C]0.357749[/C][C]0.715499[/C][C]0.642251[/C][/ROW]
[ROW][C]36[/C][C]0.356479[/C][C]0.712958[/C][C]0.643521[/C][/ROW]
[ROW][C]37[/C][C]0.307702[/C][C]0.615404[/C][C]0.692298[/C][/ROW]
[ROW][C]38[/C][C]0.294189[/C][C]0.588379[/C][C]0.705811[/C][/ROW]
[ROW][C]39[/C][C]0.274638[/C][C]0.549275[/C][C]0.725362[/C][/ROW]
[ROW][C]40[/C][C]0.25299[/C][C]0.50598[/C][C]0.74701[/C][/ROW]
[ROW][C]41[/C][C]0.226071[/C][C]0.452142[/C][C]0.773929[/C][/ROW]
[ROW][C]42[/C][C]0.208302[/C][C]0.416604[/C][C]0.791698[/C][/ROW]
[ROW][C]43[/C][C]0.22501[/C][C]0.450019[/C][C]0.77499[/C][/ROW]
[ROW][C]44[/C][C]0.191132[/C][C]0.382265[/C][C]0.808868[/C][/ROW]
[ROW][C]45[/C][C]0.158344[/C][C]0.316689[/C][C]0.841656[/C][/ROW]
[ROW][C]46[/C][C]0.202277[/C][C]0.404554[/C][C]0.797723[/C][/ROW]
[ROW][C]47[/C][C]0.203122[/C][C]0.406243[/C][C]0.796878[/C][/ROW]
[ROW][C]48[/C][C]0.170114[/C][C]0.340227[/C][C]0.829886[/C][/ROW]
[ROW][C]49[/C][C]0.154377[/C][C]0.308755[/C][C]0.845623[/C][/ROW]
[ROW][C]50[/C][C]0.144755[/C][C]0.289511[/C][C]0.855245[/C][/ROW]
[ROW][C]51[/C][C]0.152379[/C][C]0.304758[/C][C]0.847621[/C][/ROW]
[ROW][C]52[/C][C]0.12665[/C][C]0.253299[/C][C]0.87335[/C][/ROW]
[ROW][C]53[/C][C]0.134244[/C][C]0.268489[/C][C]0.865756[/C][/ROW]
[ROW][C]54[/C][C]0.114681[/C][C]0.229362[/C][C]0.885319[/C][/ROW]
[ROW][C]55[/C][C]0.184911[/C][C]0.369821[/C][C]0.815089[/C][/ROW]
[ROW][C]56[/C][C]0.42536[/C][C]0.850719[/C][C]0.57464[/C][/ROW]
[ROW][C]57[/C][C]0.384741[/C][C]0.769483[/C][C]0.615259[/C][/ROW]
[ROW][C]58[/C][C]0.343974[/C][C]0.687947[/C][C]0.656026[/C][/ROW]
[ROW][C]59[/C][C]0.305387[/C][C]0.610773[/C][C]0.694613[/C][/ROW]
[ROW][C]60[/C][C]0.300959[/C][C]0.601919[/C][C]0.699041[/C][/ROW]
[ROW][C]61[/C][C]0.308592[/C][C]0.617183[/C][C]0.691408[/C][/ROW]
[ROW][C]62[/C][C]0.273775[/C][C]0.547551[/C][C]0.726225[/C][/ROW]
[ROW][C]63[/C][C]0.293025[/C][C]0.58605[/C][C]0.706975[/C][/ROW]
[ROW][C]64[/C][C]0.25796[/C][C]0.51592[/C][C]0.74204[/C][/ROW]
[ROW][C]65[/C][C]0.230586[/C][C]0.461172[/C][C]0.769414[/C][/ROW]
[ROW][C]66[/C][C]0.201258[/C][C]0.402517[/C][C]0.798742[/C][/ROW]
[ROW][C]67[/C][C]0.184399[/C][C]0.368797[/C][C]0.815601[/C][/ROW]
[ROW][C]68[/C][C]0.164709[/C][C]0.329417[/C][C]0.835291[/C][/ROW]
[ROW][C]69[/C][C]0.163087[/C][C]0.326173[/C][C]0.836913[/C][/ROW]
[ROW][C]70[/C][C]0.139289[/C][C]0.278579[/C][C]0.860711[/C][/ROW]
[ROW][C]71[/C][C]0.123122[/C][C]0.246243[/C][C]0.876878[/C][/ROW]
[ROW][C]72[/C][C]0.104768[/C][C]0.209536[/C][C]0.895232[/C][/ROW]
[ROW][C]73[/C][C]0.0898335[/C][C]0.179667[/C][C]0.910167[/C][/ROW]
[ROW][C]74[/C][C]0.0760607[/C][C]0.152121[/C][C]0.923939[/C][/ROW]
[ROW][C]75[/C][C]0.070097[/C][C]0.140194[/C][C]0.929903[/C][/ROW]
[ROW][C]76[/C][C]0.0853431[/C][C]0.170686[/C][C]0.914657[/C][/ROW]
[ROW][C]77[/C][C]0.0759817[/C][C]0.151963[/C][C]0.924018[/C][/ROW]
[ROW][C]78[/C][C]0.0627186[/C][C]0.125437[/C][C]0.937281[/C][/ROW]
[ROW][C]79[/C][C]0.0689426[/C][C]0.137885[/C][C]0.931057[/C][/ROW]
[ROW][C]80[/C][C]0.063577[/C][C]0.127154[/C][C]0.936423[/C][/ROW]
[ROW][C]81[/C][C]0.0523712[/C][C]0.104742[/C][C]0.947629[/C][/ROW]
[ROW][C]82[/C][C]0.0429809[/C][C]0.0859617[/C][C]0.957019[/C][/ROW]
[ROW][C]83[/C][C]0.0375405[/C][C]0.0750811[/C][C]0.962459[/C][/ROW]
[ROW][C]84[/C][C]0.030336[/C][C]0.060672[/C][C]0.969664[/C][/ROW]
[ROW][C]85[/C][C]0.0275628[/C][C]0.0551255[/C][C]0.972437[/C][/ROW]
[ROW][C]86[/C][C]0.0310249[/C][C]0.0620498[/C][C]0.968975[/C][/ROW]
[ROW][C]87[/C][C]0.0249395[/C][C]0.049879[/C][C]0.97506[/C][/ROW]
[ROW][C]88[/C][C]0.0200597[/C][C]0.0401194[/C][C]0.97994[/C][/ROW]
[ROW][C]89[/C][C]0.0171321[/C][C]0.0342643[/C][C]0.982868[/C][/ROW]
[ROW][C]90[/C][C]0.0143548[/C][C]0.0287095[/C][C]0.985645[/C][/ROW]
[ROW][C]91[/C][C]0.0236378[/C][C]0.0472755[/C][C]0.976362[/C][/ROW]
[ROW][C]92[/C][C]0.0194464[/C][C]0.0388928[/C][C]0.980554[/C][/ROW]
[ROW][C]93[/C][C]0.0180211[/C][C]0.0360422[/C][C]0.981979[/C][/ROW]
[ROW][C]94[/C][C]0.0200854[/C][C]0.0401708[/C][C]0.979915[/C][/ROW]
[ROW][C]95[/C][C]0.0196744[/C][C]0.0393487[/C][C]0.980326[/C][/ROW]
[ROW][C]96[/C][C]0.0177436[/C][C]0.0354873[/C][C]0.982256[/C][/ROW]
[ROW][C]97[/C][C]0.0216356[/C][C]0.0432713[/C][C]0.978364[/C][/ROW]
[ROW][C]98[/C][C]0.0175041[/C][C]0.0350082[/C][C]0.982496[/C][/ROW]
[ROW][C]99[/C][C]0.0147642[/C][C]0.0295284[/C][C]0.985236[/C][/ROW]
[ROW][C]100[/C][C]0.0176543[/C][C]0.0353085[/C][C]0.982346[/C][/ROW]
[ROW][C]101[/C][C]0.0145273[/C][C]0.0290546[/C][C]0.985473[/C][/ROW]
[ROW][C]102[/C][C]0.0123705[/C][C]0.0247409[/C][C]0.98763[/C][/ROW]
[ROW][C]103[/C][C]0.00972383[/C][C]0.0194477[/C][C]0.990276[/C][/ROW]
[ROW][C]104[/C][C]0.00850674[/C][C]0.0170135[/C][C]0.991493[/C][/ROW]
[ROW][C]105[/C][C]0.009725[/C][C]0.01945[/C][C]0.990275[/C][/ROW]
[ROW][C]106[/C][C]0.00757629[/C][C]0.0151526[/C][C]0.992424[/C][/ROW]
[ROW][C]107[/C][C]0.00592637[/C][C]0.0118527[/C][C]0.994074[/C][/ROW]
[ROW][C]108[/C][C]0.00484316[/C][C]0.00968632[/C][C]0.995157[/C][/ROW]
[ROW][C]109[/C][C]0.00721753[/C][C]0.0144351[/C][C]0.992782[/C][/ROW]
[ROW][C]110[/C][C]0.00563703[/C][C]0.0112741[/C][C]0.994363[/C][/ROW]
[ROW][C]111[/C][C]0.00674692[/C][C]0.0134938[/C][C]0.993253[/C][/ROW]
[ROW][C]112[/C][C]0.00701595[/C][C]0.0140319[/C][C]0.992984[/C][/ROW]
[ROW][C]113[/C][C]0.00594915[/C][C]0.0118983[/C][C]0.994051[/C][/ROW]
[ROW][C]114[/C][C]0.00477324[/C][C]0.00954648[/C][C]0.995227[/C][/ROW]
[ROW][C]115[/C][C]0.00371916[/C][C]0.00743833[/C][C]0.996281[/C][/ROW]
[ROW][C]116[/C][C]0.00421962[/C][C]0.00843923[/C][C]0.99578[/C][/ROW]
[ROW][C]117[/C][C]0.00663086[/C][C]0.0132617[/C][C]0.993369[/C][/ROW]
[ROW][C]118[/C][C]0.00550078[/C][C]0.0110016[/C][C]0.994499[/C][/ROW]
[ROW][C]119[/C][C]0.0043051[/C][C]0.00861019[/C][C]0.995695[/C][/ROW]
[ROW][C]120[/C][C]0.00353324[/C][C]0.00706647[/C][C]0.996467[/C][/ROW]
[ROW][C]121[/C][C]0.00342271[/C][C]0.00684542[/C][C]0.996577[/C][/ROW]
[ROW][C]122[/C][C]0.0035735[/C][C]0.00714701[/C][C]0.996426[/C][/ROW]
[ROW][C]123[/C][C]0.00420979[/C][C]0.00841958[/C][C]0.99579[/C][/ROW]
[ROW][C]124[/C][C]0.00474781[/C][C]0.00949563[/C][C]0.995252[/C][/ROW]
[ROW][C]125[/C][C]0.00905266[/C][C]0.0181053[/C][C]0.990947[/C][/ROW]
[ROW][C]126[/C][C]0.00750976[/C][C]0.0150195[/C][C]0.99249[/C][/ROW]
[ROW][C]127[/C][C]0.00637498[/C][C]0.01275[/C][C]0.993625[/C][/ROW]
[ROW][C]128[/C][C]0.00705855[/C][C]0.0141171[/C][C]0.992941[/C][/ROW]
[ROW][C]129[/C][C]0.00690824[/C][C]0.0138165[/C][C]0.993092[/C][/ROW]
[ROW][C]130[/C][C]0.0067825[/C][C]0.013565[/C][C]0.993218[/C][/ROW]
[ROW][C]131[/C][C]0.00872683[/C][C]0.0174537[/C][C]0.991273[/C][/ROW]
[ROW][C]132[/C][C]0.0171592[/C][C]0.0343183[/C][C]0.982841[/C][/ROW]
[ROW][C]133[/C][C]0.0165404[/C][C]0.0330808[/C][C]0.98346[/C][/ROW]
[ROW][C]134[/C][C]0.0154301[/C][C]0.0308601[/C][C]0.98457[/C][/ROW]
[ROW][C]135[/C][C]0.0135782[/C][C]0.0271564[/C][C]0.986422[/C][/ROW]
[ROW][C]136[/C][C]0.0111558[/C][C]0.0223117[/C][C]0.988844[/C][/ROW]
[ROW][C]137[/C][C]0.00889147[/C][C]0.0177829[/C][C]0.991109[/C][/ROW]
[ROW][C]138[/C][C]0.00772244[/C][C]0.0154449[/C][C]0.992278[/C][/ROW]
[ROW][C]139[/C][C]0.00709498[/C][C]0.01419[/C][C]0.992905[/C][/ROW]
[ROW][C]140[/C][C]0.00573006[/C][C]0.0114601[/C][C]0.99427[/C][/ROW]
[ROW][C]141[/C][C]0.0121694[/C][C]0.0243389[/C][C]0.987831[/C][/ROW]
[ROW][C]142[/C][C]0.0135747[/C][C]0.0271494[/C][C]0.986425[/C][/ROW]
[ROW][C]143[/C][C]0.0189581[/C][C]0.0379162[/C][C]0.981042[/C][/ROW]
[ROW][C]144[/C][C]0.0152283[/C][C]0.0304566[/C][C]0.984772[/C][/ROW]
[ROW][C]145[/C][C]0.0121105[/C][C]0.0242209[/C][C]0.98789[/C][/ROW]
[ROW][C]146[/C][C]0.00985135[/C][C]0.0197027[/C][C]0.990149[/C][/ROW]
[ROW][C]147[/C][C]0.0105435[/C][C]0.021087[/C][C]0.989456[/C][/ROW]
[ROW][C]148[/C][C]0.00855109[/C][C]0.0171022[/C][C]0.991449[/C][/ROW]
[ROW][C]149[/C][C]0.00716867[/C][C]0.0143373[/C][C]0.992831[/C][/ROW]
[ROW][C]150[/C][C]0.00641365[/C][C]0.0128273[/C][C]0.993586[/C][/ROW]
[ROW][C]151[/C][C]0.00702868[/C][C]0.0140574[/C][C]0.992971[/C][/ROW]
[ROW][C]152[/C][C]0.00919668[/C][C]0.0183934[/C][C]0.990803[/C][/ROW]
[ROW][C]153[/C][C]0.0575787[/C][C]0.115157[/C][C]0.942421[/C][/ROW]
[ROW][C]154[/C][C]0.0650839[/C][C]0.130168[/C][C]0.934916[/C][/ROW]
[ROW][C]155[/C][C]0.0549341[/C][C]0.109868[/C][C]0.945066[/C][/ROW]
[ROW][C]156[/C][C]0.0758579[/C][C]0.151716[/C][C]0.924142[/C][/ROW]
[ROW][C]157[/C][C]0.135056[/C][C]0.270111[/C][C]0.864944[/C][/ROW]
[ROW][C]158[/C][C]0.138018[/C][C]0.276036[/C][C]0.861982[/C][/ROW]
[ROW][C]159[/C][C]0.120287[/C][C]0.240574[/C][C]0.879713[/C][/ROW]
[ROW][C]160[/C][C]0.113958[/C][C]0.227915[/C][C]0.886042[/C][/ROW]
[ROW][C]161[/C][C]0.114974[/C][C]0.229949[/C][C]0.885026[/C][/ROW]
[ROW][C]162[/C][C]0.101197[/C][C]0.202394[/C][C]0.898803[/C][/ROW]
[ROW][C]163[/C][C]0.0902928[/C][C]0.180586[/C][C]0.909707[/C][/ROW]
[ROW][C]164[/C][C]0.0985088[/C][C]0.197018[/C][C]0.901491[/C][/ROW]
[ROW][C]165[/C][C]0.0888204[/C][C]0.177641[/C][C]0.91118[/C][/ROW]
[ROW][C]166[/C][C]0.0758346[/C][C]0.151669[/C][C]0.924165[/C][/ROW]
[ROW][C]167[/C][C]0.065061[/C][C]0.130122[/C][C]0.934939[/C][/ROW]
[ROW][C]168[/C][C]0.108388[/C][C]0.216776[/C][C]0.891612[/C][/ROW]
[ROW][C]169[/C][C]0.11142[/C][C]0.22284[/C][C]0.88858[/C][/ROW]
[ROW][C]170[/C][C]0.096764[/C][C]0.193528[/C][C]0.903236[/C][/ROW]
[ROW][C]171[/C][C]0.166964[/C][C]0.333928[/C][C]0.833036[/C][/ROW]
[ROW][C]172[/C][C]0.146004[/C][C]0.292008[/C][C]0.853996[/C][/ROW]
[ROW][C]173[/C][C]0.129124[/C][C]0.258249[/C][C]0.870876[/C][/ROW]
[ROW][C]174[/C][C]0.111657[/C][C]0.223315[/C][C]0.888343[/C][/ROW]
[ROW][C]175[/C][C]0.15028[/C][C]0.300559[/C][C]0.84972[/C][/ROW]
[ROW][C]176[/C][C]0.129968[/C][C]0.259936[/C][C]0.870032[/C][/ROW]
[ROW][C]177[/C][C]0.117512[/C][C]0.235024[/C][C]0.882488[/C][/ROW]
[ROW][C]178[/C][C]0.100891[/C][C]0.201781[/C][C]0.899109[/C][/ROW]
[ROW][C]179[/C][C]0.0859732[/C][C]0.171946[/C][C]0.914027[/C][/ROW]
[ROW][C]180[/C][C]0.0724333[/C][C]0.144867[/C][C]0.927567[/C][/ROW]
[ROW][C]181[/C][C]0.0612729[/C][C]0.122546[/C][C]0.938727[/C][/ROW]
[ROW][C]182[/C][C]0.070341[/C][C]0.140682[/C][C]0.929659[/C][/ROW]
[ROW][C]183[/C][C]0.0721459[/C][C]0.144292[/C][C]0.927854[/C][/ROW]
[ROW][C]184[/C][C]0.066597[/C][C]0.133194[/C][C]0.933403[/C][/ROW]
[ROW][C]185[/C][C]0.237545[/C][C]0.47509[/C][C]0.762455[/C][/ROW]
[ROW][C]186[/C][C]0.214362[/C][C]0.428723[/C][C]0.785638[/C][/ROW]
[ROW][C]187[/C][C]0.193201[/C][C]0.386402[/C][C]0.806799[/C][/ROW]
[ROW][C]188[/C][C]0.201996[/C][C]0.403993[/C][C]0.798004[/C][/ROW]
[ROW][C]189[/C][C]0.187862[/C][C]0.375723[/C][C]0.812138[/C][/ROW]
[ROW][C]190[/C][C]0.268369[/C][C]0.536738[/C][C]0.731631[/C][/ROW]
[ROW][C]191[/C][C]0.266605[/C][C]0.533209[/C][C]0.733395[/C][/ROW]
[ROW][C]192[/C][C]0.235759[/C][C]0.471517[/C][C]0.764241[/C][/ROW]
[ROW][C]193[/C][C]0.610321[/C][C]0.779357[/C][C]0.389679[/C][/ROW]
[ROW][C]194[/C][C]0.573069[/C][C]0.853861[/C][C]0.426931[/C][/ROW]
[ROW][C]195[/C][C]0.5362[/C][C]0.9276[/C][C]0.4638[/C][/ROW]
[ROW][C]196[/C][C]0.509097[/C][C]0.981807[/C][C]0.490903[/C][/ROW]
[ROW][C]197[/C][C]0.53539[/C][C]0.92922[/C][C]0.46461[/C][/ROW]
[ROW][C]198[/C][C]0.498589[/C][C]0.997178[/C][C]0.501411[/C][/ROW]
[ROW][C]199[/C][C]0.474016[/C][C]0.948032[/C][C]0.525984[/C][/ROW]
[ROW][C]200[/C][C]0.462408[/C][C]0.924816[/C][C]0.537592[/C][/ROW]
[ROW][C]201[/C][C]0.441972[/C][C]0.883944[/C][C]0.558028[/C][/ROW]
[ROW][C]202[/C][C]0.417617[/C][C]0.835234[/C][C]0.582383[/C][/ROW]
[ROW][C]203[/C][C]0.38023[/C][C]0.76046[/C][C]0.61977[/C][/ROW]
[ROW][C]204[/C][C]0.455585[/C][C]0.91117[/C][C]0.544415[/C][/ROW]
[ROW][C]205[/C][C]0.494321[/C][C]0.988643[/C][C]0.505679[/C][/ROW]
[ROW][C]206[/C][C]0.451914[/C][C]0.903827[/C][C]0.548086[/C][/ROW]
[ROW][C]207[/C][C]0.410164[/C][C]0.820328[/C][C]0.589836[/C][/ROW]
[ROW][C]208[/C][C]0.371511[/C][C]0.743023[/C][C]0.628489[/C][/ROW]
[ROW][C]209[/C][C]0.354295[/C][C]0.70859[/C][C]0.645705[/C][/ROW]
[ROW][C]210[/C][C]0.317703[/C][C]0.635405[/C][C]0.682297[/C][/ROW]
[ROW][C]211[/C][C]0.392844[/C][C]0.785688[/C][C]0.607156[/C][/ROW]
[ROW][C]212[/C][C]0.419899[/C][C]0.839797[/C][C]0.580101[/C][/ROW]
[ROW][C]213[/C][C]0.378665[/C][C]0.75733[/C][C]0.621335[/C][/ROW]
[ROW][C]214[/C][C]0.39683[/C][C]0.793659[/C][C]0.60317[/C][/ROW]
[ROW][C]215[/C][C]0.359848[/C][C]0.719696[/C][C]0.640152[/C][/ROW]
[ROW][C]216[/C][C]0.323641[/C][C]0.647283[/C][C]0.676359[/C][/ROW]
[ROW][C]217[/C][C]0.286274[/C][C]0.572548[/C][C]0.713726[/C][/ROW]
[ROW][C]218[/C][C]0.247476[/C][C]0.494952[/C][C]0.752524[/C][/ROW]
[ROW][C]219[/C][C]0.249828[/C][C]0.499656[/C][C]0.750172[/C][/ROW]
[ROW][C]220[/C][C]0.228998[/C][C]0.457995[/C][C]0.771002[/C][/ROW]
[ROW][C]221[/C][C]0.273474[/C][C]0.546948[/C][C]0.726526[/C][/ROW]
[ROW][C]222[/C][C]0.233748[/C][C]0.467496[/C][C]0.766252[/C][/ROW]
[ROW][C]223[/C][C]0.223952[/C][C]0.447904[/C][C]0.776048[/C][/ROW]
[ROW][C]224[/C][C]0.197145[/C][C]0.39429[/C][C]0.802855[/C][/ROW]
[ROW][C]225[/C][C]0.168669[/C][C]0.337338[/C][C]0.831331[/C][/ROW]
[ROW][C]226[/C][C]0.140736[/C][C]0.281473[/C][C]0.859264[/C][/ROW]
[ROW][C]227[/C][C]0.116927[/C][C]0.233854[/C][C]0.883073[/C][/ROW]
[ROW][C]228[/C][C]0.0962019[/C][C]0.192404[/C][C]0.903798[/C][/ROW]
[ROW][C]229[/C][C]0.0754967[/C][C]0.150993[/C][C]0.924503[/C][/ROW]
[ROW][C]230[/C][C]0.0591118[/C][C]0.118224[/C][C]0.940888[/C][/ROW]
[ROW][C]231[/C][C]0.0894233[/C][C]0.178847[/C][C]0.910577[/C][/ROW]
[ROW][C]232[/C][C]0.111022[/C][C]0.222045[/C][C]0.888978[/C][/ROW]
[ROW][C]233[/C][C]0.319299[/C][C]0.638597[/C][C]0.680701[/C][/ROW]
[ROW][C]234[/C][C]0.277391[/C][C]0.554781[/C][C]0.722609[/C][/ROW]
[ROW][C]235[/C][C]0.231225[/C][C]0.46245[/C][C]0.768775[/C][/ROW]
[ROW][C]236[/C][C]0.226202[/C][C]0.452403[/C][C]0.773798[/C][/ROW]
[ROW][C]237[/C][C]0.226045[/C][C]0.45209[/C][C]0.773955[/C][/ROW]
[ROW][C]238[/C][C]0.308943[/C][C]0.617886[/C][C]0.691057[/C][/ROW]
[ROW][C]239[/C][C]0.316253[/C][C]0.632506[/C][C]0.683747[/C][/ROW]
[ROW][C]240[/C][C]0.268287[/C][C]0.536574[/C][C]0.731713[/C][/ROW]
[ROW][C]241[/C][C]0.21845[/C][C]0.436899[/C][C]0.78155[/C][/ROW]
[ROW][C]242[/C][C]0.304895[/C][C]0.60979[/C][C]0.695105[/C][/ROW]
[ROW][C]243[/C][C]0.600987[/C][C]0.798026[/C][C]0.399013[/C][/ROW]
[ROW][C]244[/C][C]0.736961[/C][C]0.526079[/C][C]0.263039[/C][/ROW]
[ROW][C]245[/C][C]0.67624[/C][C]0.64752[/C][C]0.32376[/C][/ROW]
[ROW][C]246[/C][C]0.63065[/C][C]0.738699[/C][C]0.36935[/C][/ROW]
[ROW][C]247[/C][C]0.584012[/C][C]0.831975[/C][C]0.415988[/C][/ROW]
[ROW][C]248[/C][C]0.50104[/C][C]0.997919[/C][C]0.49896[/C][/ROW]
[ROW][C]249[/C][C]0.409064[/C][C]0.818129[/C][C]0.590936[/C][/ROW]
[ROW][C]250[/C][C]0.425958[/C][C]0.851915[/C][C]0.574042[/C][/ROW]
[ROW][C]251[/C][C]0.570246[/C][C]0.859508[/C][C]0.429754[/C][/ROW]
[ROW][C]252[/C][C]0.739616[/C][C]0.520769[/C][C]0.260384[/C][/ROW]
[ROW][C]253[/C][C]0.797592[/C][C]0.404815[/C][C]0.202408[/C][/ROW]
[ROW][C]254[/C][C]0.842475[/C][C]0.315051[/C][C]0.157525[/C][/ROW]
[ROW][C]255[/C][C]0.798054[/C][C]0.403892[/C][C]0.201946[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221697&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221697&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
90.9068470.1863060.0931528
100.9887610.02247830.0112392
110.9790040.04199260.0209963
120.9626180.07476460.0373823
130.9441730.1116540.055827
140.9380850.1238290.0619147
150.9238980.1522040.0761021
160.8959910.2080170.104009
170.853490.293020.14651
180.8631590.2736820.136841
190.832470.3350590.16753
200.7805180.4389640.219482
210.7346570.5306860.265343
220.6879760.6240480.312024
230.6264280.7471450.373572
240.5808320.8383360.419168
250.5325020.9349950.467498
260.585130.829740.41487
270.5684970.8630050.431503
280.5888160.8223670.411184
290.5279780.9440430.472022
300.480710.961420.51929
310.4342530.8685060.565747
320.4772030.9544070.522797
330.4195350.839070.580465
340.3636140.7272270.636386
350.3577490.7154990.642251
360.3564790.7129580.643521
370.3077020.6154040.692298
380.2941890.5883790.705811
390.2746380.5492750.725362
400.252990.505980.74701
410.2260710.4521420.773929
420.2083020.4166040.791698
430.225010.4500190.77499
440.1911320.3822650.808868
450.1583440.3166890.841656
460.2022770.4045540.797723
470.2031220.4062430.796878
480.1701140.3402270.829886
490.1543770.3087550.845623
500.1447550.2895110.855245
510.1523790.3047580.847621
520.126650.2532990.87335
530.1342440.2684890.865756
540.1146810.2293620.885319
550.1849110.3698210.815089
560.425360.8507190.57464
570.3847410.7694830.615259
580.3439740.6879470.656026
590.3053870.6107730.694613
600.3009590.6019190.699041
610.3085920.6171830.691408
620.2737750.5475510.726225
630.2930250.586050.706975
640.257960.515920.74204
650.2305860.4611720.769414
660.2012580.4025170.798742
670.1843990.3687970.815601
680.1647090.3294170.835291
690.1630870.3261730.836913
700.1392890.2785790.860711
710.1231220.2462430.876878
720.1047680.2095360.895232
730.08983350.1796670.910167
740.07606070.1521210.923939
750.0700970.1401940.929903
760.08534310.1706860.914657
770.07598170.1519630.924018
780.06271860.1254370.937281
790.06894260.1378850.931057
800.0635770.1271540.936423
810.05237120.1047420.947629
820.04298090.08596170.957019
830.03754050.07508110.962459
840.0303360.0606720.969664
850.02756280.05512550.972437
860.03102490.06204980.968975
870.02493950.0498790.97506
880.02005970.04011940.97994
890.01713210.03426430.982868
900.01435480.02870950.985645
910.02363780.04727550.976362
920.01944640.03889280.980554
930.01802110.03604220.981979
940.02008540.04017080.979915
950.01967440.03934870.980326
960.01774360.03548730.982256
970.02163560.04327130.978364
980.01750410.03500820.982496
990.01476420.02952840.985236
1000.01765430.03530850.982346
1010.01452730.02905460.985473
1020.01237050.02474090.98763
1030.009723830.01944770.990276
1040.008506740.01701350.991493
1050.0097250.019450.990275
1060.007576290.01515260.992424
1070.005926370.01185270.994074
1080.004843160.009686320.995157
1090.007217530.01443510.992782
1100.005637030.01127410.994363
1110.006746920.01349380.993253
1120.007015950.01403190.992984
1130.005949150.01189830.994051
1140.004773240.009546480.995227
1150.003719160.007438330.996281
1160.004219620.008439230.99578
1170.006630860.01326170.993369
1180.005500780.01100160.994499
1190.00430510.008610190.995695
1200.003533240.007066470.996467
1210.003422710.006845420.996577
1220.00357350.007147010.996426
1230.004209790.008419580.99579
1240.004747810.009495630.995252
1250.009052660.01810530.990947
1260.007509760.01501950.99249
1270.006374980.012750.993625
1280.007058550.01411710.992941
1290.006908240.01381650.993092
1300.00678250.0135650.993218
1310.008726830.01745370.991273
1320.01715920.03431830.982841
1330.01654040.03308080.98346
1340.01543010.03086010.98457
1350.01357820.02715640.986422
1360.01115580.02231170.988844
1370.008891470.01778290.991109
1380.007722440.01544490.992278
1390.007094980.014190.992905
1400.005730060.01146010.99427
1410.01216940.02433890.987831
1420.01357470.02714940.986425
1430.01895810.03791620.981042
1440.01522830.03045660.984772
1450.01211050.02422090.98789
1460.009851350.01970270.990149
1470.01054350.0210870.989456
1480.008551090.01710220.991449
1490.007168670.01433730.992831
1500.006413650.01282730.993586
1510.007028680.01405740.992971
1520.009196680.01839340.990803
1530.05757870.1151570.942421
1540.06508390.1301680.934916
1550.05493410.1098680.945066
1560.07585790.1517160.924142
1570.1350560.2701110.864944
1580.1380180.2760360.861982
1590.1202870.2405740.879713
1600.1139580.2279150.886042
1610.1149740.2299490.885026
1620.1011970.2023940.898803
1630.09029280.1805860.909707
1640.09850880.1970180.901491
1650.08882040.1776410.91118
1660.07583460.1516690.924165
1670.0650610.1301220.934939
1680.1083880.2167760.891612
1690.111420.222840.88858
1700.0967640.1935280.903236
1710.1669640.3339280.833036
1720.1460040.2920080.853996
1730.1291240.2582490.870876
1740.1116570.2233150.888343
1750.150280.3005590.84972
1760.1299680.2599360.870032
1770.1175120.2350240.882488
1780.1008910.2017810.899109
1790.08597320.1719460.914027
1800.07243330.1448670.927567
1810.06127290.1225460.938727
1820.0703410.1406820.929659
1830.07214590.1442920.927854
1840.0665970.1331940.933403
1850.2375450.475090.762455
1860.2143620.4287230.785638
1870.1932010.3864020.806799
1880.2019960.4039930.798004
1890.1878620.3757230.812138
1900.2683690.5367380.731631
1910.2666050.5332090.733395
1920.2357590.4715170.764241
1930.6103210.7793570.389679
1940.5730690.8538610.426931
1950.53620.92760.4638
1960.5090970.9818070.490903
1970.535390.929220.46461
1980.4985890.9971780.501411
1990.4740160.9480320.525984
2000.4624080.9248160.537592
2010.4419720.8839440.558028
2020.4176170.8352340.582383
2030.380230.760460.61977
2040.4555850.911170.544415
2050.4943210.9886430.505679
2060.4519140.9038270.548086
2070.4101640.8203280.589836
2080.3715110.7430230.628489
2090.3542950.708590.645705
2100.3177030.6354050.682297
2110.3928440.7856880.607156
2120.4198990.8397970.580101
2130.3786650.757330.621335
2140.396830.7936590.60317
2150.3598480.7196960.640152
2160.3236410.6472830.676359
2170.2862740.5725480.713726
2180.2474760.4949520.752524
2190.2498280.4996560.750172
2200.2289980.4579950.771002
2210.2734740.5469480.726526
2220.2337480.4674960.766252
2230.2239520.4479040.776048
2240.1971450.394290.802855
2250.1686690.3373380.831331
2260.1407360.2814730.859264
2270.1169270.2338540.883073
2280.09620190.1924040.903798
2290.07549670.1509930.924503
2300.05911180.1182240.940888
2310.08942330.1788470.910577
2320.1110220.2220450.888978
2330.3192990.6385970.680701
2340.2773910.5547810.722609
2350.2312250.462450.768775
2360.2262020.4524030.773798
2370.2260450.452090.773955
2380.3089430.6178860.691057
2390.3162530.6325060.683747
2400.2682870.5365740.731713
2410.218450.4368990.78155
2420.3048950.609790.695105
2430.6009870.7980260.399013
2440.7369610.5260790.263039
2450.676240.647520.32376
2460.630650.7386990.36935
2470.5840120.8319750.415988
2480.501040.9979190.49896
2490.4090640.8181290.590936
2500.4259580.8519150.574042
2510.5702460.8595080.429754
2520.7396160.5207690.260384
2530.7975920.4048150.202408
2540.8424750.3150510.157525
2550.7980540.4038920.201946






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0404858NOK
5% type I error level680.275304NOK
10% type I error level740.299595NOK

\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 & 10 & 0.0404858 & NOK \tabularnewline
5% type I error level & 68 & 0.275304 & NOK \tabularnewline
10% type I error level & 74 & 0.299595 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221697&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]10[/C][C]0.0404858[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]68[/C][C]0.275304[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]74[/C][C]0.299595[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221697&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221697&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0404858NOK
5% type I error level680.275304NOK
10% type I error level740.299595NOK


Figures (Output of Computation)

Figure 1
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

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