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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 19 Nov 2013 16:05:31 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/19/t13848952156hota5xkx1yrczc.htm/, Retrieved Fri, 03 May 2024 18:23:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226562, Retrieved Fri, 03 May 2024 18:23:44 +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] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- R  D    [Multiple Regression] [workshop 7 A] [2013-11-19 21:05:31] [0292d86b083cfbb80712452cc5129066] [Current]
-   P       [Multiple Regression] [Workshop 7 AA] [2013-11-19 21:23:28] [f661ab64c60045a179a329b9ddab9bfe]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41	38	12	12	53
39	32	11	11	83
30	35	15	14	66
31	33	6	12	67
34	37	13	21	76
35	29	10	12	78
39	31	12	22	53
34	36	14	11	80
36	35	12	10	74
37	38	9	13	76
38	31	10	10	79
36	34	12	8	54
38	35	12	15	67
39	38	11	14	54
33	37	15	10	87
32	33	12	14	58
36	32	10	14	75
38	38	12	11	88
39	38	11	10	64
32	32	12	13	57
32	33	11	9.5	66
31	31	12	14	68
39	38	13	12	54
37	39	11	14	56
39	32	12	11	86
41	32	13	9	80
36	35	10	11	76
33	37	14	15	69
33	33	12	14	78
34	33	10	13	67
31	31	12	9	80
27	32	8	15	54
37	31	10	10	71
34	37	12	11	84
34	30	12	13	74
32	33	7	8	71
29	31	9	20	63
36	33	12	12	71
29	31	10	10	76
35	33	10	10	69
37	32	10	9	74
34	33	12	14	75
38	32	15	8	54
35	33	10	14	52
38	28	10	11	69
37	35	12	13	68
38	39	13	9	65
33	34	11	11	75
36	38	11	15	74
38	32	12	11	75
32	38	14	10	72
32	30	10	14	67
32	33	12	18	63
34	38	13	14	62
32	32	5	11	63
37	35	6	14.5	76
39	34	12	13	74
29	34	12	9	67
37	36	11	10	73
35	34	10	15	70
30	28	7	20	53
38	34	12	12	77
34	35	14	12	80
31	35	11	14	52
34	31	12	13	54
35	37	13	11	80
36	35	14	17	66
30	27	11	12	73
39	40	12	13	63
35	37	12	14	69
38	36	8	13	67
31	38	11	15	54
34	39	14	13	81
38	41	14	10	69
34	27	12	11	84
39	30	9	19	80
37	37	13	13	70
34	31	11	17	69
28	31	12	13	77
37	27	12	9	54
33	36	12	11	79
35	37	12	9	71
37	33	12	12	73
32	34	11	12	72
33	31	10	13	77
38	39	9	13	75
33	34	12	12	69
29	32	12	15	54
33	33	12	22	70
31	36	9	13	73
36	32	15	15	54
35	41	12	13	77
32	28	12	15	82
29	30	12	12.5	80
39	36	10	11	80
37	35	13	16	69
35	31	9	11	78
37	34	12	11	81
32	36	10	10	76
38	36	14	10	76
37	35	11	16	73
36	37	15	12	85
32	28	11	11	66
33	39	11	16	79
40	32	12	19	68
38	35	12	11	76
41	39	12	16	71
36	35	11	15	54
43	42	7	24	46
30	34	12	14	85
31	33	14	15	74
32	41	11	11	88
32	33	11	15	38
37	34	10	12	76
37	32	13	10	86
33	40	13	14	54
34	40	8	13	67
33	35	11	9	69
38	36	12	15	90
33	37	11	15	54
31	27	13	14	76
38	39	12	11	89
37	38	14	8	76
36	31	13	11	73
31	33	15	11	79
39	32	10	8	90
44	39	11	10	74
33	36	9	11	81
35	33	11	13	72
32	33	10	11	71
28	32	11	20	66
40	37	8	10	77
27	30	11	15	65
37	38	12	12	74
32	29	12	14	85
28	22	9	23	54
34	35	11	14	63
30	35	10	16	54
35	34	8	11	64
31	35	9	12	69
32	34	8	10	54
30	37	9	14	84
30	35	15	12	86
31	23	11	12	77
40	31	8	11	89
32	27	13	12	76
36	36	12	13	60
32	31	12	11	75
35	32	9	19	73
38	39	7	12	85
42	37	13	17	79
34	38	9	9	71
35	39	6	12	72
38	34	8	19	69
33	31	8	18	78
36	32	15	15	54
32	37	6	14	69
33	36	9	11	81
34	32	11	9	84
32	38	8	18	84
34	36	8	16	69
27	26	10	24	66
31	26	8	14	81
38	33	14	20	82
34	39	10	18	72
24	30	8	23	54
30	33	11	12	78
26	25	12	14	74
34	38	12	16	82
27	37	12	18	73
37	31	5	20	55
36	37	12	12	72
41	35	10	12	78
29	25	7	17	59
36	28	12	13	72
32	35	11	9	78
37	33	8	16	68
30	30	9	18	69
31	31	10	10	67
38	37	9	14	74
36	36	12	11	54
35	30	6	9	67
31	36	15	11	70
38	32	12	10	80
22	28	12	11	89
32	36	12	19	76
36	34	11	14	74
39	31	7	12	87
28	28	7	14	54
32	36	5	21	61
32	36	12	13	38
38	40	12	10	75
32	33	3	15	69
35	37	11	16	62
32	32	10	14	72
37	38	12	12	70
34	31	9	19	79
33	37	12	15	87
33	33	9	19	62
26	32	12	13	77
30	30	12	17	69
24	30	10	12	69
34	31	9	11	75
34	32	12	14	54
33	34	8	11	72
34	36	11	13	74
35	37	11	12	85
35	36	12	15	52
36	33	10	14	70
34	33	10	12	84
34	33	12	17	64
41	44	12	11	84
32	39	11	18	87
30	32	8	13	79
35	35	12	17	67
28	25	10	13	65
33	35	11	11	85
39	34	10	12	83
36	35	8	22	61
36	39	12	14	82
35	33	12	12	76
38	36	10	12	58
33	32	12	17	72
31	32	9	9	72
34	36	9	21	38
32	36	6	10	78
31	32	10	11	54
33	34	9	12	63
34	33	9	23	66
34	35	9	13	70
34	30	6	12	71
33	38	10	16	67
32	34	6	9	58
41	33	14	17	72
34	32	10	9	72
36	31	10	14	70
37	30	6	17	76
36	27	12	13	50
29	31	12	11	72
37	30	7	12	72
27	32	8	10	88
35	35	11	19	53
28	28	3	16	58
35	33	6	16	66
37	31	10	14	82
29	35	8	20	69
32	35	9	15	68
36	32	9	23	44
19	21	8	20	56
21	20	9	16	53
31	34	7	14	70
33	32	7	17	78
36	34	6	11	71
33	32	9	13	72
37	33	10	17	68
34	33	11	15	67
35	37	12	21	75
31	32	8	18	62
37	34	11	15	67
35	30	3	8	83
27	30	11	12	64
34	38	12	12	68
40	36	7	22	62
29	32	9	12	72

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 15 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226562&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]15 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226562&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226562&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






Multiple Linear Regression - Estimated Regression Equation
Computer[t] = + 6.78260592802572 + 0.0246701702784855Connected[t] + 0.0962434746430366Separate[t] -0.0840353158110196Depression[t] + 0.0116307072093154`Sport\r\r`[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Computer[t] =  +  6.78260592802572 +  0.0246701702784855Connected[t] +  0.0962434746430366Separate[t] -0.0840353158110196Depression[t] +  0.0116307072093154`Sport\r\r`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226562&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Computer[t] =  +  6.78260592802572 +  0.0246701702784855Connected[t] +  0.0962434746430366Separate[t] -0.0840353158110196Depression[t] +  0.0116307072093154`Sport\r\r`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226562&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226562&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
Computer[t] = + 6.78260592802572 + 0.0246701702784855Connected[t] + 0.0962434746430366Separate[t] -0.0840353158110196Depression[t] + 0.0116307072093154`Sport\r\r`[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)6.782605928025721.9730243.43770.0006830.000342
Connected0.02467017027848550.0416130.59280.5538020.276901
Separate0.09624347464303660.042422.26880.0241040.012052
Depression-0.08403531581101960.042882-1.95970.0511050.025552
`Sport\r\r`0.01163070720931540.0142930.81370.4165460.208273

\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) & 6.78260592802572 & 1.973024 & 3.4377 & 0.000683 & 0.000342 \tabularnewline
Connected & 0.0246701702784855 & 0.041613 & 0.5928 & 0.553802 & 0.276901 \tabularnewline
Separate & 0.0962434746430366 & 0.04242 & 2.2688 & 0.024104 & 0.012052 \tabularnewline
Depression & -0.0840353158110196 & 0.042882 & -1.9597 & 0.051105 & 0.025552 \tabularnewline
`Sport\r\r` & 0.0116307072093154 & 0.014293 & 0.8137 & 0.416546 & 0.208273 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226562&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]6.78260592802572[/C][C]1.973024[/C][C]3.4377[/C][C]0.000683[/C][C]0.000342[/C][/ROW]
[ROW][C]Connected[/C][C]0.0246701702784855[/C][C]0.041613[/C][C]0.5928[/C][C]0.553802[/C][C]0.276901[/C][/ROW]
[ROW][C]Separate[/C][C]0.0962434746430366[/C][C]0.04242[/C][C]2.2688[/C][C]0.024104[/C][C]0.012052[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0840353158110196[/C][C]0.042882[/C][C]-1.9597[/C][C]0.051105[/C][C]0.025552[/C][/ROW]
[ROW][C]`Sport\r\r`[/C][C]0.0116307072093154[/C][C]0.014293[/C][C]0.8137[/C][C]0.416546[/C][C]0.208273[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226562&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226562&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)6.782605928025721.9730243.43770.0006830.000342
Connected0.02467017027848550.0416130.59280.5538020.276901
Separate0.09624347464303660.042422.26880.0241040.012052
Depression-0.08403531581101960.042882-1.95970.0511050.025552
`Sport\r\r`0.01163070720931540.0142930.81370.4165460.208273






Multiple Linear Regression - Regression Statistics
Multiple R0.24709091695121
R-squared0.0610539212397896
Adjusted R-squared0.0465528234983192
F-TEST (value)4.21029651191074
F-TEST (DF numerator)4
F-TEST (DF denominator)259
p-value0.00255076672020027
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.26539519520704
Sum Squared Residuals1329.19198613099

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.24709091695121 \tabularnewline
R-squared & 0.0610539212397896 \tabularnewline
Adjusted R-squared & 0.0465528234983192 \tabularnewline
F-TEST (value) & 4.21029651191074 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 259 \tabularnewline
p-value & 0.00255076672020027 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.26539519520704 \tabularnewline
Sum Squared Residuals & 1329.19198613099 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226562&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.24709091695121[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0610539212397896[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0465528234983192[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]4.21029651191074[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]259[/C][/ROW]
[ROW][C]p-value[/C][C]0.00255076672020027[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.26539519520704[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1329.19198613099[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226562&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226562&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 R0.24709091695121
R-squared0.0610539212397896
Adjusted R-squared0.0465528234983192
F-TEST (value)4.21029651191074
F-TEST (DF numerator)4
F-TEST (DF denominator)259
p-value0.00255076672020027
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.26539519520704
Sum Squared Residuals1329.19198613099






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11211.05933863824050.940661361759493
21110.86549398191580.13450601808421
31510.48236490334714.51763509665289
4610.4942494631709-4.49424946317088
51310.30159239516312.69840760483686
61010.3358940250151-0.335894025015141
7129.495940817072072.50405918292793
81411.09222490746762.90777509253244
91211.05957284593660.940427154063376
10911.1441289071298-2.14412890712979
111010.782092823968-0.782092823968026
121210.89878585872931.10121414127068
131210.60732165697331.39267834302671
141110.85355837327080.146441626729197
151511.32924847810833.67075152189166
161210.24617263694351.75382736305652
171010.4463318659728-0.446331865972751
181211.47643819554210.523561804457898
191111.306006708608-0.306006708608036
201210.22233377090221.77766622909785
211110.71737721576760.282622784232405
221210.14532258947211.85467741052792
231311.02162900489281.97837099510716
241110.92372292177550.0762770782245005
251210.90038610354371.09961389645626
261311.04801283246691.95198716753315
271010.9987989445442-0.998798944544235
281410.69971916928563.30028083071443
291210.50345695140831.49654304859172
301010.4842246581953-0.484224658195313
311210.7050676550391.29493234496104
3289.89602016625974-1.89602016625974
331010.664376996015-0.664376996015017
341211.23499121094790.765008789052139
351210.27690918473141.72309081526859
36710.9015837255307-3.9015837255307
3799.53361681800241-0.533616818002413
381210.66412314340061.33587685659943
391010.5251691698337-0.52516916983371
401010.7842621903255-0.784262190325488
411010.879547908097-0.879547908097019
421210.49323500005881.50676499994118
431510.75563925000024.24436074999979
441010.250398904523-0.250398904523047
451010.2930200121347-0.293020012134742
461210.76235282552621.23764717447384
471311.47324603599291.52675396400708
481110.81691425185640.183085748143573
491110.92812669081060.0718733091893641
501210.74777815396281.25222184603722
511411.22636117433322.77363882566684
521010.0621185778982-0.0621185778982125
53129.968184909745982.03181509025402
541310.82325317955292.1767468204471
55510.4601886457801-5.46018864578008
56610.7293455094842-4.72934550948415
571210.7852339346961.21476606530401
581210.793258544691.20674145531
591111.1688557836488-0.168855783648831
601010.4719597931227-0.471959793122742
6179.15324949225863-2.15324949225863
621210.87949120185651.12050879814353
631410.91194611701353.08805388298649
641110.34420517269520.655794827304822
651210.14053851518811.85946148481186
661311.21313855238911.78686144761091
671410.3782799775853.62172002241504
68119.961902688290061.03809731170994
691211.23475700325170.765242996748265
701210.83309482565361.16690517434644
71810.8716357632384-2.87163576323836
721110.57216169523190.427838304768101
731411.22451540698392.77548459301605
741411.62822049830522.37177950169476
751210.27255646451751.7274435354825
7699.96583238451361-0.965832384513614
771310.97810118923092.02189881076914
78119.978857860083791.02114213991621
791210.26002375933151.73997624066852
801210.16571639069551.83428360930447
811211.05592402997980.944075970020238
821211.27653281912730.723467180872715
831210.71205472809771.28794527190232
841110.6733166441390.326683355861025
851010.3833746107239-0.383374610723909
86911.253411844842-2.253411844842
871210.66309469278951.33690530721049
88129.945360506816712.05463949318329
89129.73812876724562.2618712327544
90910.7687288145449-1.76872881454486
911510.11805169876614.88194830123389
921211.39514969771120.604850302288754
93129.960056920940852.03994307905915
941210.26536023450041.73463976549961
951011.21557575886-1.21557575885999
961310.52187758530242.47812241469758
97910.6124162901122-1.61241629011223
981210.98537917622631.01462082377374
991011.0803970538843-1.08039705388435
1001411.22841807555532.77158192444474
1011110.56840041413970.431599585860323
1021511.21192694290313.78807305709687
1031110.11010686883590.889893131164117
1041110.92447787485380.0755221251462264
1051210.04342101756641.95657898243361
1061211.04813928510120.951860714898794
1071211.02879357940710.971206420592866
1081110.40678212269520.593217877304783
109710.4038141371722-3.40381413717217
1101210.60710486568111.39289513431893
1111410.3235584662033.67644153379697
1121111.6171475978003-0.617147597800298
113119.929523176946161.07047682305385
1141010.8431903243687-0.843190324368665
1151310.93508107879782.06491892120221
1161310.8980243008862.10197569911404
117811.1579289806966-3.15792898069657
1181111.0114441148656-0.0114441148656098
1191210.97107139743061.02892860256942
1201110.52525856114580.474741438854166
121139.853394348574463.14660565142554
1221211.58431237739450.415687622605546
1231411.56430548618492.43569451381511
1241310.57893292434412.42106707565586
1251510.71785326549374.28214673450632
1261011.1990148798141-1.19901487981406
1271111.6419081067367-0.641908106736654
128911.0791854443984-2.07918544439839
1291110.56704836452040.432951635479625
1301010.6494777780976-0.649477778097643
131119.640082243994911.35991775600509
132811.3856325979646-3.38563259796459
133119.831470996276131.16852900372387
1341211.20490280852220.79509719147782
1351210.17522783302291.82477216697715
13698.28597306361970.714026936380299
1371110.54615346283310.453846537166895
1381010.1747257852133-0.174725785213285
139810.7383168131109-2.73831681311093
140910.7099978268756-1.70999782687558
141810.6320345459933-2.63203454599334
142910.8842045824009-1.88420458240086
1431510.88304967915554.11695032084454
144119.648121788833661.35187821116633
145810.8637049208071-2.86370492080713
1461310.0461351504752.95386484952502
1471210.74088047221621.25911952778381
1481210.50351365764881.49648634235117
14999.97822370222054-0.978223702220537
150711.4537542327462-4.45375423274617
1511310.86998714226312.13001285773695
152911.3481061234918-2.34810612349184
153611.2285445281896-5.22854452818962
154810.1981983335048-2.1981983335048
15589.97482873887813-1.97482873887813
1561510.11805169876614.88194830123389
157610.7590843148181-4.7590843148181
158911.0791854443984-2.07918544439839
1591110.92184446935470.078155530645283
160810.6936471343568-2.69364713435679
161810.54411054911-2.54411054911
162108.701809962614131.29819003738587
16389.815304409978-1.815304409978
1641410.16911873677183.83088126322815
1651010.699662463045-0.699662463045012
16688.95724017965005-0.957240179650051
1671110.59751707219490.40248292780514
168129.514295133477332.48570486652268
1691210.88779669211721.11220330788283
1701210.34611502901891.65388497098114
17159.63793252255577-4.63793252255577
1721211.0607277491820.939272250817973
1731011.0613758945443-1.06137589454427
17479.16173908873999-2.16173908873999
1751210.11050116158371.88949883841632
1761111.091450309471-0.0914503094709631
177810.317759928807-2.31775992880703
17899.69989838851579-0.699898388515794
1791010.4698331455068-0.469833145506842
180910.9652588725356-1.96525887253559
1811210.83916686058231.16083313941767
182610.5563056677888-4.55630566778877
1831510.90190732453894.09809267546105
1841210.88996700582041.11003299417962
1851210.13091143186531.86908856813472
1861210.32407921158521.67592078841483
1871110.62718810804950.372811891950491
188710.731738020299-3.731738020299
18979.6197517537771-2.6197517537771
19059.9815479718234-4.9815479718234
1911210.38632423249731.6136757675027
1921211.60176126691810.398238733081907
193310.2900751004349-7.29007510043493
1941110.58360924356630.416390756433691
1951010.3127590632309-0.312759063230863
1961211.15837997968490.841620020315082
19799.92709430055491-0.927094300554908
1981210.90907189905321.09092810094676
19999.89718905700413-0.897189057004133
2001210.30692689341751.69307310658245
201129.783933704326812.21606629567319
2021010.056089261711-0.0560892617109985
203910.5528539982058-1.5528539982058
2041210.15274667402021.84725332597984
205810.7820221302285-2.78202213022848
2061110.85437003258960.145629967410369
2071111.1872567726246-0.187256772624642
2081210.45509401264111.54490598735886
2091010.4844218045692-0.484421804569211
2101010.7659819965647-0.765981996564695
2111210.11319127332331.88680872667671
2121212.0813867253985-0.0813867253985158
2131110.82478273062780.175217269372227
214810.4288689889501-2.42886898895012
2151210.36524051451581.63475948548421
216109.542994424961480.457005575038524
2171111.0294647985926-0.0294647985926177
2181010.9739456153908-0.973945615390844
21989.89994986248329-1.89994986248329
2201211.20145113893920.798548861060784
2211210.69760650916871.30239349083134
2221010.8509947141655-0.850994714165545
2231210.08532328607631.91467671392371
224910.7082654720075-1.70826547200748
22599.76338204656612-0.763382046566119
226611.103658468303-5.10365846830298
2271010.3308421106178-0.330842110617758
228910.5933104495336-1.59331044953362
22999.6322407928758-0.632240792875802
230910.7116037291093-1.71160372910933
231610.3260523789145-4.32605237891448
2321010.688665913699-0.688665913698952
233610.7625926906416-4.76259269064162
2341410.37892812294723.62107187705279
2351010.7822759828429-0.782275982842932
2361010.2919348552831-0.291934855283137
237610.0380398467414-4.03803984674142
238129.75838212833572.2416178716643
2391210.39461102518541.60538897481457
240710.4116935969593-3.41169359695926
241810.7116407904316-2.71164079043156
2421110.03433998196330.965660018036662
24339.49820395099232-6.49820395099232
244610.2451581738314-4.24515817383142
2451010.4561735120734-0.456173512073408
24689.98837495983045-1.98837495983045
247910.4709313425117-1.47093134251169
24899.3294621001848-0.329462100184796
24988.24306541832198-0.243065418321984
25098.497411425852050.50258857414795
251710.4573144278198-3.45731442781982
252710.1551075293322-3.15510752933218
253610.8444019338546-4.84440193385462
254910.4214645493204-1.42146454932037
2551010.233724612996-0.233724612996006
2561110.31615402657330.683845973426726
2571210.31463185823231.68536814176769
25889.83564055761514-1.83564055761514
2591110.48640801205180.513591987948233
260310.8264322989488-7.82643229894883
2611110.07194623649990.928053763500122
2621211.06110805443080.938891945569169
263710.1065047254496-3.10650472544958
264910.4068191840174-1.40681918401745

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 11.0593386382405 & 0.940661361759493 \tabularnewline
2 & 11 & 10.8654939819158 & 0.13450601808421 \tabularnewline
3 & 15 & 10.4823649033471 & 4.51763509665289 \tabularnewline
4 & 6 & 10.4942494631709 & -4.49424946317088 \tabularnewline
5 & 13 & 10.3015923951631 & 2.69840760483686 \tabularnewline
6 & 10 & 10.3358940250151 & -0.335894025015141 \tabularnewline
7 & 12 & 9.49594081707207 & 2.50405918292793 \tabularnewline
8 & 14 & 11.0922249074676 & 2.90777509253244 \tabularnewline
9 & 12 & 11.0595728459366 & 0.940427154063376 \tabularnewline
10 & 9 & 11.1441289071298 & -2.14412890712979 \tabularnewline
11 & 10 & 10.782092823968 & -0.782092823968026 \tabularnewline
12 & 12 & 10.8987858587293 & 1.10121414127068 \tabularnewline
13 & 12 & 10.6073216569733 & 1.39267834302671 \tabularnewline
14 & 11 & 10.8535583732708 & 0.146441626729197 \tabularnewline
15 & 15 & 11.3292484781083 & 3.67075152189166 \tabularnewline
16 & 12 & 10.2461726369435 & 1.75382736305652 \tabularnewline
17 & 10 & 10.4463318659728 & -0.446331865972751 \tabularnewline
18 & 12 & 11.4764381955421 & 0.523561804457898 \tabularnewline
19 & 11 & 11.306006708608 & -0.306006708608036 \tabularnewline
20 & 12 & 10.2223337709022 & 1.77766622909785 \tabularnewline
21 & 11 & 10.7173772157676 & 0.282622784232405 \tabularnewline
22 & 12 & 10.1453225894721 & 1.85467741052792 \tabularnewline
23 & 13 & 11.0216290048928 & 1.97837099510716 \tabularnewline
24 & 11 & 10.9237229217755 & 0.0762770782245005 \tabularnewline
25 & 12 & 10.9003861035437 & 1.09961389645626 \tabularnewline
26 & 13 & 11.0480128324669 & 1.95198716753315 \tabularnewline
27 & 10 & 10.9987989445442 & -0.998798944544235 \tabularnewline
28 & 14 & 10.6997191692856 & 3.30028083071443 \tabularnewline
29 & 12 & 10.5034569514083 & 1.49654304859172 \tabularnewline
30 & 10 & 10.4842246581953 & -0.484224658195313 \tabularnewline
31 & 12 & 10.705067655039 & 1.29493234496104 \tabularnewline
32 & 8 & 9.89602016625974 & -1.89602016625974 \tabularnewline
33 & 10 & 10.664376996015 & -0.664376996015017 \tabularnewline
34 & 12 & 11.2349912109479 & 0.765008789052139 \tabularnewline
35 & 12 & 10.2769091847314 & 1.72309081526859 \tabularnewline
36 & 7 & 10.9015837255307 & -3.9015837255307 \tabularnewline
37 & 9 & 9.53361681800241 & -0.533616818002413 \tabularnewline
38 & 12 & 10.6641231434006 & 1.33587685659943 \tabularnewline
39 & 10 & 10.5251691698337 & -0.52516916983371 \tabularnewline
40 & 10 & 10.7842621903255 & -0.784262190325488 \tabularnewline
41 & 10 & 10.879547908097 & -0.879547908097019 \tabularnewline
42 & 12 & 10.4932350000588 & 1.50676499994118 \tabularnewline
43 & 15 & 10.7556392500002 & 4.24436074999979 \tabularnewline
44 & 10 & 10.250398904523 & -0.250398904523047 \tabularnewline
45 & 10 & 10.2930200121347 & -0.293020012134742 \tabularnewline
46 & 12 & 10.7623528255262 & 1.23764717447384 \tabularnewline
47 & 13 & 11.4732460359929 & 1.52675396400708 \tabularnewline
48 & 11 & 10.8169142518564 & 0.183085748143573 \tabularnewline
49 & 11 & 10.9281266908106 & 0.0718733091893641 \tabularnewline
50 & 12 & 10.7477781539628 & 1.25222184603722 \tabularnewline
51 & 14 & 11.2263611743332 & 2.77363882566684 \tabularnewline
52 & 10 & 10.0621185778982 & -0.0621185778982125 \tabularnewline
53 & 12 & 9.96818490974598 & 2.03181509025402 \tabularnewline
54 & 13 & 10.8232531795529 & 2.1767468204471 \tabularnewline
55 & 5 & 10.4601886457801 & -5.46018864578008 \tabularnewline
56 & 6 & 10.7293455094842 & -4.72934550948415 \tabularnewline
57 & 12 & 10.785233934696 & 1.21476606530401 \tabularnewline
58 & 12 & 10.79325854469 & 1.20674145531 \tabularnewline
59 & 11 & 11.1688557836488 & -0.168855783648831 \tabularnewline
60 & 10 & 10.4719597931227 & -0.471959793122742 \tabularnewline
61 & 7 & 9.15324949225863 & -2.15324949225863 \tabularnewline
62 & 12 & 10.8794912018565 & 1.12050879814353 \tabularnewline
63 & 14 & 10.9119461170135 & 3.08805388298649 \tabularnewline
64 & 11 & 10.3442051726952 & 0.655794827304822 \tabularnewline
65 & 12 & 10.1405385151881 & 1.85946148481186 \tabularnewline
66 & 13 & 11.2131385523891 & 1.78686144761091 \tabularnewline
67 & 14 & 10.378279977585 & 3.62172002241504 \tabularnewline
68 & 11 & 9.96190268829006 & 1.03809731170994 \tabularnewline
69 & 12 & 11.2347570032517 & 0.765242996748265 \tabularnewline
70 & 12 & 10.8330948256536 & 1.16690517434644 \tabularnewline
71 & 8 & 10.8716357632384 & -2.87163576323836 \tabularnewline
72 & 11 & 10.5721616952319 & 0.427838304768101 \tabularnewline
73 & 14 & 11.2245154069839 & 2.77548459301605 \tabularnewline
74 & 14 & 11.6282204983052 & 2.37177950169476 \tabularnewline
75 & 12 & 10.2725564645175 & 1.7274435354825 \tabularnewline
76 & 9 & 9.96583238451361 & -0.965832384513614 \tabularnewline
77 & 13 & 10.9781011892309 & 2.02189881076914 \tabularnewline
78 & 11 & 9.97885786008379 & 1.02114213991621 \tabularnewline
79 & 12 & 10.2600237593315 & 1.73997624066852 \tabularnewline
80 & 12 & 10.1657163906955 & 1.83428360930447 \tabularnewline
81 & 12 & 11.0559240299798 & 0.944075970020238 \tabularnewline
82 & 12 & 11.2765328191273 & 0.723467180872715 \tabularnewline
83 & 12 & 10.7120547280977 & 1.28794527190232 \tabularnewline
84 & 11 & 10.673316644139 & 0.326683355861025 \tabularnewline
85 & 10 & 10.3833746107239 & -0.383374610723909 \tabularnewline
86 & 9 & 11.253411844842 & -2.253411844842 \tabularnewline
87 & 12 & 10.6630946927895 & 1.33690530721049 \tabularnewline
88 & 12 & 9.94536050681671 & 2.05463949318329 \tabularnewline
89 & 12 & 9.7381287672456 & 2.2618712327544 \tabularnewline
90 & 9 & 10.7687288145449 & -1.76872881454486 \tabularnewline
91 & 15 & 10.1180516987661 & 4.88194830123389 \tabularnewline
92 & 12 & 11.3951496977112 & 0.604850302288754 \tabularnewline
93 & 12 & 9.96005692094085 & 2.03994307905915 \tabularnewline
94 & 12 & 10.2653602345004 & 1.73463976549961 \tabularnewline
95 & 10 & 11.21557575886 & -1.21557575885999 \tabularnewline
96 & 13 & 10.5218775853024 & 2.47812241469758 \tabularnewline
97 & 9 & 10.6124162901122 & -1.61241629011223 \tabularnewline
98 & 12 & 10.9853791762263 & 1.01462082377374 \tabularnewline
99 & 10 & 11.0803970538843 & -1.08039705388435 \tabularnewline
100 & 14 & 11.2284180755553 & 2.77158192444474 \tabularnewline
101 & 11 & 10.5684004141397 & 0.431599585860323 \tabularnewline
102 & 15 & 11.2119269429031 & 3.78807305709687 \tabularnewline
103 & 11 & 10.1101068688359 & 0.889893131164117 \tabularnewline
104 & 11 & 10.9244778748538 & 0.0755221251462264 \tabularnewline
105 & 12 & 10.0434210175664 & 1.95657898243361 \tabularnewline
106 & 12 & 11.0481392851012 & 0.951860714898794 \tabularnewline
107 & 12 & 11.0287935794071 & 0.971206420592866 \tabularnewline
108 & 11 & 10.4067821226952 & 0.593217877304783 \tabularnewline
109 & 7 & 10.4038141371722 & -3.40381413717217 \tabularnewline
110 & 12 & 10.6071048656811 & 1.39289513431893 \tabularnewline
111 & 14 & 10.323558466203 & 3.67644153379697 \tabularnewline
112 & 11 & 11.6171475978003 & -0.617147597800298 \tabularnewline
113 & 11 & 9.92952317694616 & 1.07047682305385 \tabularnewline
114 & 10 & 10.8431903243687 & -0.843190324368665 \tabularnewline
115 & 13 & 10.9350810787978 & 2.06491892120221 \tabularnewline
116 & 13 & 10.898024300886 & 2.10197569911404 \tabularnewline
117 & 8 & 11.1579289806966 & -3.15792898069657 \tabularnewline
118 & 11 & 11.0114441148656 & -0.0114441148656098 \tabularnewline
119 & 12 & 10.9710713974306 & 1.02892860256942 \tabularnewline
120 & 11 & 10.5252585611458 & 0.474741438854166 \tabularnewline
121 & 13 & 9.85339434857446 & 3.14660565142554 \tabularnewline
122 & 12 & 11.5843123773945 & 0.415687622605546 \tabularnewline
123 & 14 & 11.5643054861849 & 2.43569451381511 \tabularnewline
124 & 13 & 10.5789329243441 & 2.42106707565586 \tabularnewline
125 & 15 & 10.7178532654937 & 4.28214673450632 \tabularnewline
126 & 10 & 11.1990148798141 & -1.19901487981406 \tabularnewline
127 & 11 & 11.6419081067367 & -0.641908106736654 \tabularnewline
128 & 9 & 11.0791854443984 & -2.07918544439839 \tabularnewline
129 & 11 & 10.5670483645204 & 0.432951635479625 \tabularnewline
130 & 10 & 10.6494777780976 & -0.649477778097643 \tabularnewline
131 & 11 & 9.64008224399491 & 1.35991775600509 \tabularnewline
132 & 8 & 11.3856325979646 & -3.38563259796459 \tabularnewline
133 & 11 & 9.83147099627613 & 1.16852900372387 \tabularnewline
134 & 12 & 11.2049028085222 & 0.79509719147782 \tabularnewline
135 & 12 & 10.1752278330229 & 1.82477216697715 \tabularnewline
136 & 9 & 8.2859730636197 & 0.714026936380299 \tabularnewline
137 & 11 & 10.5461534628331 & 0.453846537166895 \tabularnewline
138 & 10 & 10.1747257852133 & -0.174725785213285 \tabularnewline
139 & 8 & 10.7383168131109 & -2.73831681311093 \tabularnewline
140 & 9 & 10.7099978268756 & -1.70999782687558 \tabularnewline
141 & 8 & 10.6320345459933 & -2.63203454599334 \tabularnewline
142 & 9 & 10.8842045824009 & -1.88420458240086 \tabularnewline
143 & 15 & 10.8830496791555 & 4.11695032084454 \tabularnewline
144 & 11 & 9.64812178883366 & 1.35187821116633 \tabularnewline
145 & 8 & 10.8637049208071 & -2.86370492080713 \tabularnewline
146 & 13 & 10.046135150475 & 2.95386484952502 \tabularnewline
147 & 12 & 10.7408804722162 & 1.25911952778381 \tabularnewline
148 & 12 & 10.5035136576488 & 1.49648634235117 \tabularnewline
149 & 9 & 9.97822370222054 & -0.978223702220537 \tabularnewline
150 & 7 & 11.4537542327462 & -4.45375423274617 \tabularnewline
151 & 13 & 10.8699871422631 & 2.13001285773695 \tabularnewline
152 & 9 & 11.3481061234918 & -2.34810612349184 \tabularnewline
153 & 6 & 11.2285445281896 & -5.22854452818962 \tabularnewline
154 & 8 & 10.1981983335048 & -2.1981983335048 \tabularnewline
155 & 8 & 9.97482873887813 & -1.97482873887813 \tabularnewline
156 & 15 & 10.1180516987661 & 4.88194830123389 \tabularnewline
157 & 6 & 10.7590843148181 & -4.7590843148181 \tabularnewline
158 & 9 & 11.0791854443984 & -2.07918544439839 \tabularnewline
159 & 11 & 10.9218444693547 & 0.078155530645283 \tabularnewline
160 & 8 & 10.6936471343568 & -2.69364713435679 \tabularnewline
161 & 8 & 10.54411054911 & -2.54411054911 \tabularnewline
162 & 10 & 8.70180996261413 & 1.29819003738587 \tabularnewline
163 & 8 & 9.815304409978 & -1.815304409978 \tabularnewline
164 & 14 & 10.1691187367718 & 3.83088126322815 \tabularnewline
165 & 10 & 10.699662463045 & -0.699662463045012 \tabularnewline
166 & 8 & 8.95724017965005 & -0.957240179650051 \tabularnewline
167 & 11 & 10.5975170721949 & 0.40248292780514 \tabularnewline
168 & 12 & 9.51429513347733 & 2.48570486652268 \tabularnewline
169 & 12 & 10.8877966921172 & 1.11220330788283 \tabularnewline
170 & 12 & 10.3461150290189 & 1.65388497098114 \tabularnewline
171 & 5 & 9.63793252255577 & -4.63793252255577 \tabularnewline
172 & 12 & 11.060727749182 & 0.939272250817973 \tabularnewline
173 & 10 & 11.0613758945443 & -1.06137589454427 \tabularnewline
174 & 7 & 9.16173908873999 & -2.16173908873999 \tabularnewline
175 & 12 & 10.1105011615837 & 1.88949883841632 \tabularnewline
176 & 11 & 11.091450309471 & -0.0914503094709631 \tabularnewline
177 & 8 & 10.317759928807 & -2.31775992880703 \tabularnewline
178 & 9 & 9.69989838851579 & -0.699898388515794 \tabularnewline
179 & 10 & 10.4698331455068 & -0.469833145506842 \tabularnewline
180 & 9 & 10.9652588725356 & -1.96525887253559 \tabularnewline
181 & 12 & 10.8391668605823 & 1.16083313941767 \tabularnewline
182 & 6 & 10.5563056677888 & -4.55630566778877 \tabularnewline
183 & 15 & 10.9019073245389 & 4.09809267546105 \tabularnewline
184 & 12 & 10.8899670058204 & 1.11003299417962 \tabularnewline
185 & 12 & 10.1309114318653 & 1.86908856813472 \tabularnewline
186 & 12 & 10.3240792115852 & 1.67592078841483 \tabularnewline
187 & 11 & 10.6271881080495 & 0.372811891950491 \tabularnewline
188 & 7 & 10.731738020299 & -3.731738020299 \tabularnewline
189 & 7 & 9.6197517537771 & -2.6197517537771 \tabularnewline
190 & 5 & 9.9815479718234 & -4.9815479718234 \tabularnewline
191 & 12 & 10.3863242324973 & 1.6136757675027 \tabularnewline
192 & 12 & 11.6017612669181 & 0.398238733081907 \tabularnewline
193 & 3 & 10.2900751004349 & -7.29007510043493 \tabularnewline
194 & 11 & 10.5836092435663 & 0.416390756433691 \tabularnewline
195 & 10 & 10.3127590632309 & -0.312759063230863 \tabularnewline
196 & 12 & 11.1583799796849 & 0.841620020315082 \tabularnewline
197 & 9 & 9.92709430055491 & -0.927094300554908 \tabularnewline
198 & 12 & 10.9090718990532 & 1.09092810094676 \tabularnewline
199 & 9 & 9.89718905700413 & -0.897189057004133 \tabularnewline
200 & 12 & 10.3069268934175 & 1.69307310658245 \tabularnewline
201 & 12 & 9.78393370432681 & 2.21606629567319 \tabularnewline
202 & 10 & 10.056089261711 & -0.0560892617109985 \tabularnewline
203 & 9 & 10.5528539982058 & -1.5528539982058 \tabularnewline
204 & 12 & 10.1527466740202 & 1.84725332597984 \tabularnewline
205 & 8 & 10.7820221302285 & -2.78202213022848 \tabularnewline
206 & 11 & 10.8543700325896 & 0.145629967410369 \tabularnewline
207 & 11 & 11.1872567726246 & -0.187256772624642 \tabularnewline
208 & 12 & 10.4550940126411 & 1.54490598735886 \tabularnewline
209 & 10 & 10.4844218045692 & -0.484421804569211 \tabularnewline
210 & 10 & 10.7659819965647 & -0.765981996564695 \tabularnewline
211 & 12 & 10.1131912733233 & 1.88680872667671 \tabularnewline
212 & 12 & 12.0813867253985 & -0.0813867253985158 \tabularnewline
213 & 11 & 10.8247827306278 & 0.175217269372227 \tabularnewline
214 & 8 & 10.4288689889501 & -2.42886898895012 \tabularnewline
215 & 12 & 10.3652405145158 & 1.63475948548421 \tabularnewline
216 & 10 & 9.54299442496148 & 0.457005575038524 \tabularnewline
217 & 11 & 11.0294647985926 & -0.0294647985926177 \tabularnewline
218 & 10 & 10.9739456153908 & -0.973945615390844 \tabularnewline
219 & 8 & 9.89994986248329 & -1.89994986248329 \tabularnewline
220 & 12 & 11.2014511389392 & 0.798548861060784 \tabularnewline
221 & 12 & 10.6976065091687 & 1.30239349083134 \tabularnewline
222 & 10 & 10.8509947141655 & -0.850994714165545 \tabularnewline
223 & 12 & 10.0853232860763 & 1.91467671392371 \tabularnewline
224 & 9 & 10.7082654720075 & -1.70826547200748 \tabularnewline
225 & 9 & 9.76338204656612 & -0.763382046566119 \tabularnewline
226 & 6 & 11.103658468303 & -5.10365846830298 \tabularnewline
227 & 10 & 10.3308421106178 & -0.330842110617758 \tabularnewline
228 & 9 & 10.5933104495336 & -1.59331044953362 \tabularnewline
229 & 9 & 9.6322407928758 & -0.632240792875802 \tabularnewline
230 & 9 & 10.7116037291093 & -1.71160372910933 \tabularnewline
231 & 6 & 10.3260523789145 & -4.32605237891448 \tabularnewline
232 & 10 & 10.688665913699 & -0.688665913698952 \tabularnewline
233 & 6 & 10.7625926906416 & -4.76259269064162 \tabularnewline
234 & 14 & 10.3789281229472 & 3.62107187705279 \tabularnewline
235 & 10 & 10.7822759828429 & -0.782275982842932 \tabularnewline
236 & 10 & 10.2919348552831 & -0.291934855283137 \tabularnewline
237 & 6 & 10.0380398467414 & -4.03803984674142 \tabularnewline
238 & 12 & 9.7583821283357 & 2.2416178716643 \tabularnewline
239 & 12 & 10.3946110251854 & 1.60538897481457 \tabularnewline
240 & 7 & 10.4116935969593 & -3.41169359695926 \tabularnewline
241 & 8 & 10.7116407904316 & -2.71164079043156 \tabularnewline
242 & 11 & 10.0343399819633 & 0.965660018036662 \tabularnewline
243 & 3 & 9.49820395099232 & -6.49820395099232 \tabularnewline
244 & 6 & 10.2451581738314 & -4.24515817383142 \tabularnewline
245 & 10 & 10.4561735120734 & -0.456173512073408 \tabularnewline
246 & 8 & 9.98837495983045 & -1.98837495983045 \tabularnewline
247 & 9 & 10.4709313425117 & -1.47093134251169 \tabularnewline
248 & 9 & 9.3294621001848 & -0.329462100184796 \tabularnewline
249 & 8 & 8.24306541832198 & -0.243065418321984 \tabularnewline
250 & 9 & 8.49741142585205 & 0.50258857414795 \tabularnewline
251 & 7 & 10.4573144278198 & -3.45731442781982 \tabularnewline
252 & 7 & 10.1551075293322 & -3.15510752933218 \tabularnewline
253 & 6 & 10.8444019338546 & -4.84440193385462 \tabularnewline
254 & 9 & 10.4214645493204 & -1.42146454932037 \tabularnewline
255 & 10 & 10.233724612996 & -0.233724612996006 \tabularnewline
256 & 11 & 10.3161540265733 & 0.683845973426726 \tabularnewline
257 & 12 & 10.3146318582323 & 1.68536814176769 \tabularnewline
258 & 8 & 9.83564055761514 & -1.83564055761514 \tabularnewline
259 & 11 & 10.4864080120518 & 0.513591987948233 \tabularnewline
260 & 3 & 10.8264322989488 & -7.82643229894883 \tabularnewline
261 & 11 & 10.0719462364999 & 0.928053763500122 \tabularnewline
262 & 12 & 11.0611080544308 & 0.938891945569169 \tabularnewline
263 & 7 & 10.1065047254496 & -3.10650472544958 \tabularnewline
264 & 9 & 10.4068191840174 & -1.40681918401745 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226562&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]11.0593386382405[/C][C]0.940661361759493[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]10.8654939819158[/C][C]0.13450601808421[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]10.4823649033471[/C][C]4.51763509665289[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]10.4942494631709[/C][C]-4.49424946317088[/C][/ROW]
[ROW][C]5[/C][C]13[/C][C]10.3015923951631[/C][C]2.69840760483686[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]10.3358940250151[/C][C]-0.335894025015141[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]9.49594081707207[/C][C]2.50405918292793[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.0922249074676[/C][C]2.90777509253244[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]11.0595728459366[/C][C]0.940427154063376[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]11.1441289071298[/C][C]-2.14412890712979[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.782092823968[/C][C]-0.782092823968026[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]10.8987858587293[/C][C]1.10121414127068[/C][/ROW]
[ROW][C]13[/C][C]12[/C][C]10.6073216569733[/C][C]1.39267834302671[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]10.8535583732708[/C][C]0.146441626729197[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]11.3292484781083[/C][C]3.67075152189166[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]10.2461726369435[/C][C]1.75382736305652[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]10.4463318659728[/C][C]-0.446331865972751[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]11.4764381955421[/C][C]0.523561804457898[/C][/ROW]
[ROW][C]19[/C][C]11[/C][C]11.306006708608[/C][C]-0.306006708608036[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]10.2223337709022[/C][C]1.77766622909785[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]10.7173772157676[/C][C]0.282622784232405[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]10.1453225894721[/C][C]1.85467741052792[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]11.0216290048928[/C][C]1.97837099510716[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]10.9237229217755[/C][C]0.0762770782245005[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]10.9003861035437[/C][C]1.09961389645626[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]11.0480128324669[/C][C]1.95198716753315[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]10.9987989445442[/C][C]-0.998798944544235[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]10.6997191692856[/C][C]3.30028083071443[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]10.5034569514083[/C][C]1.49654304859172[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.4842246581953[/C][C]-0.484224658195313[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]10.705067655039[/C][C]1.29493234496104[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.89602016625974[/C][C]-1.89602016625974[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.664376996015[/C][C]-0.664376996015017[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.2349912109479[/C][C]0.765008789052139[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.2769091847314[/C][C]1.72309081526859[/C][/ROW]
[ROW][C]36[/C][C]7[/C][C]10.9015837255307[/C][C]-3.9015837255307[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]9.53361681800241[/C][C]-0.533616818002413[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]10.6641231434006[/C][C]1.33587685659943[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.5251691698337[/C][C]-0.52516916983371[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]10.7842621903255[/C][C]-0.784262190325488[/C][/ROW]
[ROW][C]41[/C][C]10[/C][C]10.879547908097[/C][C]-0.879547908097019[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.4932350000588[/C][C]1.50676499994118[/C][/ROW]
[ROW][C]43[/C][C]15[/C][C]10.7556392500002[/C][C]4.24436074999979[/C][/ROW]
[ROW][C]44[/C][C]10[/C][C]10.250398904523[/C][C]-0.250398904523047[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.2930200121347[/C][C]-0.293020012134742[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]10.7623528255262[/C][C]1.23764717447384[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]11.4732460359929[/C][C]1.52675396400708[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]10.8169142518564[/C][C]0.183085748143573[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]10.9281266908106[/C][C]0.0718733091893641[/C][/ROW]
[ROW][C]50[/C][C]12[/C][C]10.7477781539628[/C][C]1.25222184603722[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]11.2263611743332[/C][C]2.77363882566684[/C][/ROW]
[ROW][C]52[/C][C]10[/C][C]10.0621185778982[/C][C]-0.0621185778982125[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]9.96818490974598[/C][C]2.03181509025402[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]10.8232531795529[/C][C]2.1767468204471[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]10.4601886457801[/C][C]-5.46018864578008[/C][/ROW]
[ROW][C]56[/C][C]6[/C][C]10.7293455094842[/C][C]-4.72934550948415[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]10.785233934696[/C][C]1.21476606530401[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]10.79325854469[/C][C]1.20674145531[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.1688557836488[/C][C]-0.168855783648831[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]10.4719597931227[/C][C]-0.471959793122742[/C][/ROW]
[ROW][C]61[/C][C]7[/C][C]9.15324949225863[/C][C]-2.15324949225863[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]10.8794912018565[/C][C]1.12050879814353[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]10.9119461170135[/C][C]3.08805388298649[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.3442051726952[/C][C]0.655794827304822[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]10.1405385151881[/C][C]1.85946148481186[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]11.2131385523891[/C][C]1.78686144761091[/C][/ROW]
[ROW][C]67[/C][C]14[/C][C]10.378279977585[/C][C]3.62172002241504[/C][/ROW]
[ROW][C]68[/C][C]11[/C][C]9.96190268829006[/C][C]1.03809731170994[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]11.2347570032517[/C][C]0.765242996748265[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]10.8330948256536[/C][C]1.16690517434644[/C][/ROW]
[ROW][C]71[/C][C]8[/C][C]10.8716357632384[/C][C]-2.87163576323836[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]10.5721616952319[/C][C]0.427838304768101[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]11.2245154069839[/C][C]2.77548459301605[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]11.6282204983052[/C][C]2.37177950169476[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]10.2725564645175[/C][C]1.7274435354825[/C][/ROW]
[ROW][C]76[/C][C]9[/C][C]9.96583238451361[/C][C]-0.965832384513614[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.9781011892309[/C][C]2.02189881076914[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]9.97885786008379[/C][C]1.02114213991621[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]10.2600237593315[/C][C]1.73997624066852[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]10.1657163906955[/C][C]1.83428360930447[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.0559240299798[/C][C]0.944075970020238[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]11.2765328191273[/C][C]0.723467180872715[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]10.7120547280977[/C][C]1.28794527190232[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]10.673316644139[/C][C]0.326683355861025[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]10.3833746107239[/C][C]-0.383374610723909[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]11.253411844842[/C][C]-2.253411844842[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]10.6630946927895[/C][C]1.33690530721049[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]9.94536050681671[/C][C]2.05463949318329[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]9.7381287672456[/C][C]2.2618712327544[/C][/ROW]
[ROW][C]90[/C][C]9[/C][C]10.7687288145449[/C][C]-1.76872881454486[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]10.1180516987661[/C][C]4.88194830123389[/C][/ROW]
[ROW][C]92[/C][C]12[/C][C]11.3951496977112[/C][C]0.604850302288754[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]9.96005692094085[/C][C]2.03994307905915[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]10.2653602345004[/C][C]1.73463976549961[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]11.21557575886[/C][C]-1.21557575885999[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]10.5218775853024[/C][C]2.47812241469758[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]10.6124162901122[/C][C]-1.61241629011223[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]10.9853791762263[/C][C]1.01462082377374[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]11.0803970538843[/C][C]-1.08039705388435[/C][/ROW]
[ROW][C]100[/C][C]14[/C][C]11.2284180755553[/C][C]2.77158192444474[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]10.5684004141397[/C][C]0.431599585860323[/C][/ROW]
[ROW][C]102[/C][C]15[/C][C]11.2119269429031[/C][C]3.78807305709687[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]10.1101068688359[/C][C]0.889893131164117[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]10.9244778748538[/C][C]0.0755221251462264[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]10.0434210175664[/C][C]1.95657898243361[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]11.0481392851012[/C][C]0.951860714898794[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.0287935794071[/C][C]0.971206420592866[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]10.4067821226952[/C][C]0.593217877304783[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]10.4038141371722[/C][C]-3.40381413717217[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]10.6071048656811[/C][C]1.39289513431893[/C][/ROW]
[ROW][C]111[/C][C]14[/C][C]10.323558466203[/C][C]3.67644153379697[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]11.6171475978003[/C][C]-0.617147597800298[/C][/ROW]
[ROW][C]113[/C][C]11[/C][C]9.92952317694616[/C][C]1.07047682305385[/C][/ROW]
[ROW][C]114[/C][C]10[/C][C]10.8431903243687[/C][C]-0.843190324368665[/C][/ROW]
[ROW][C]115[/C][C]13[/C][C]10.9350810787978[/C][C]2.06491892120221[/C][/ROW]
[ROW][C]116[/C][C]13[/C][C]10.898024300886[/C][C]2.10197569911404[/C][/ROW]
[ROW][C]117[/C][C]8[/C][C]11.1579289806966[/C][C]-3.15792898069657[/C][/ROW]
[ROW][C]118[/C][C]11[/C][C]11.0114441148656[/C][C]-0.0114441148656098[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]10.9710713974306[/C][C]1.02892860256942[/C][/ROW]
[ROW][C]120[/C][C]11[/C][C]10.5252585611458[/C][C]0.474741438854166[/C][/ROW]
[ROW][C]121[/C][C]13[/C][C]9.85339434857446[/C][C]3.14660565142554[/C][/ROW]
[ROW][C]122[/C][C]12[/C][C]11.5843123773945[/C][C]0.415687622605546[/C][/ROW]
[ROW][C]123[/C][C]14[/C][C]11.5643054861849[/C][C]2.43569451381511[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]10.5789329243441[/C][C]2.42106707565586[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]10.7178532654937[/C][C]4.28214673450632[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]11.1990148798141[/C][C]-1.19901487981406[/C][/ROW]
[ROW][C]127[/C][C]11[/C][C]11.6419081067367[/C][C]-0.641908106736654[/C][/ROW]
[ROW][C]128[/C][C]9[/C][C]11.0791854443984[/C][C]-2.07918544439839[/C][/ROW]
[ROW][C]129[/C][C]11[/C][C]10.5670483645204[/C][C]0.432951635479625[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]10.6494777780976[/C][C]-0.649477778097643[/C][/ROW]
[ROW][C]131[/C][C]11[/C][C]9.64008224399491[/C][C]1.35991775600509[/C][/ROW]
[ROW][C]132[/C][C]8[/C][C]11.3856325979646[/C][C]-3.38563259796459[/C][/ROW]
[ROW][C]133[/C][C]11[/C][C]9.83147099627613[/C][C]1.16852900372387[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]11.2049028085222[/C][C]0.79509719147782[/C][/ROW]
[ROW][C]135[/C][C]12[/C][C]10.1752278330229[/C][C]1.82477216697715[/C][/ROW]
[ROW][C]136[/C][C]9[/C][C]8.2859730636197[/C][C]0.714026936380299[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]10.5461534628331[/C][C]0.453846537166895[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]10.1747257852133[/C][C]-0.174725785213285[/C][/ROW]
[ROW][C]139[/C][C]8[/C][C]10.7383168131109[/C][C]-2.73831681311093[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]10.7099978268756[/C][C]-1.70999782687558[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]10.6320345459933[/C][C]-2.63203454599334[/C][/ROW]
[ROW][C]142[/C][C]9[/C][C]10.8842045824009[/C][C]-1.88420458240086[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]10.8830496791555[/C][C]4.11695032084454[/C][/ROW]
[ROW][C]144[/C][C]11[/C][C]9.64812178883366[/C][C]1.35187821116633[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]10.8637049208071[/C][C]-2.86370492080713[/C][/ROW]
[ROW][C]146[/C][C]13[/C][C]10.046135150475[/C][C]2.95386484952502[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]10.7408804722162[/C][C]1.25911952778381[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]10.5035136576488[/C][C]1.49648634235117[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]9.97822370222054[/C][C]-0.978223702220537[/C][/ROW]
[ROW][C]150[/C][C]7[/C][C]11.4537542327462[/C][C]-4.45375423274617[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]10.8699871422631[/C][C]2.13001285773695[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.3481061234918[/C][C]-2.34810612349184[/C][/ROW]
[ROW][C]153[/C][C]6[/C][C]11.2285445281896[/C][C]-5.22854452818962[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]10.1981983335048[/C][C]-2.1981983335048[/C][/ROW]
[ROW][C]155[/C][C]8[/C][C]9.97482873887813[/C][C]-1.97482873887813[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]10.1180516987661[/C][C]4.88194830123389[/C][/ROW]
[ROW][C]157[/C][C]6[/C][C]10.7590843148181[/C][C]-4.7590843148181[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]11.0791854443984[/C][C]-2.07918544439839[/C][/ROW]
[ROW][C]159[/C][C]11[/C][C]10.9218444693547[/C][C]0.078155530645283[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]10.6936471343568[/C][C]-2.69364713435679[/C][/ROW]
[ROW][C]161[/C][C]8[/C][C]10.54411054911[/C][C]-2.54411054911[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]8.70180996261413[/C][C]1.29819003738587[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]9.815304409978[/C][C]-1.815304409978[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]10.1691187367718[/C][C]3.83088126322815[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]10.699662463045[/C][C]-0.699662463045012[/C][/ROW]
[ROW][C]166[/C][C]8[/C][C]8.95724017965005[/C][C]-0.957240179650051[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.5975170721949[/C][C]0.40248292780514[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]9.51429513347733[/C][C]2.48570486652268[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]10.8877966921172[/C][C]1.11220330788283[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]10.3461150290189[/C][C]1.65388497098114[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]9.63793252255577[/C][C]-4.63793252255577[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.060727749182[/C][C]0.939272250817973[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]11.0613758945443[/C][C]-1.06137589454427[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]9.16173908873999[/C][C]-2.16173908873999[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]10.1105011615837[/C][C]1.88949883841632[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]11.091450309471[/C][C]-0.0914503094709631[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]10.317759928807[/C][C]-2.31775992880703[/C][/ROW]
[ROW][C]178[/C][C]9[/C][C]9.69989838851579[/C][C]-0.699898388515794[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]10.4698331455068[/C][C]-0.469833145506842[/C][/ROW]
[ROW][C]180[/C][C]9[/C][C]10.9652588725356[/C][C]-1.96525887253559[/C][/ROW]
[ROW][C]181[/C][C]12[/C][C]10.8391668605823[/C][C]1.16083313941767[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]10.5563056677888[/C][C]-4.55630566778877[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]10.9019073245389[/C][C]4.09809267546105[/C][/ROW]
[ROW][C]184[/C][C]12[/C][C]10.8899670058204[/C][C]1.11003299417962[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]10.1309114318653[/C][C]1.86908856813472[/C][/ROW]
[ROW][C]186[/C][C]12[/C][C]10.3240792115852[/C][C]1.67592078841483[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]10.6271881080495[/C][C]0.372811891950491[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]10.731738020299[/C][C]-3.731738020299[/C][/ROW]
[ROW][C]189[/C][C]7[/C][C]9.6197517537771[/C][C]-2.6197517537771[/C][/ROW]
[ROW][C]190[/C][C]5[/C][C]9.9815479718234[/C][C]-4.9815479718234[/C][/ROW]
[ROW][C]191[/C][C]12[/C][C]10.3863242324973[/C][C]1.6136757675027[/C][/ROW]
[ROW][C]192[/C][C]12[/C][C]11.6017612669181[/C][C]0.398238733081907[/C][/ROW]
[ROW][C]193[/C][C]3[/C][C]10.2900751004349[/C][C]-7.29007510043493[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]10.5836092435663[/C][C]0.416390756433691[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]10.3127590632309[/C][C]-0.312759063230863[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]11.1583799796849[/C][C]0.841620020315082[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]9.92709430055491[/C][C]-0.927094300554908[/C][/ROW]
[ROW][C]198[/C][C]12[/C][C]10.9090718990532[/C][C]1.09092810094676[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]9.89718905700413[/C][C]-0.897189057004133[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]10.3069268934175[/C][C]1.69307310658245[/C][/ROW]
[ROW][C]201[/C][C]12[/C][C]9.78393370432681[/C][C]2.21606629567319[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]10.056089261711[/C][C]-0.0560892617109985[/C][/ROW]
[ROW][C]203[/C][C]9[/C][C]10.5528539982058[/C][C]-1.5528539982058[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]10.1527466740202[/C][C]1.84725332597984[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]10.7820221302285[/C][C]-2.78202213022848[/C][/ROW]
[ROW][C]206[/C][C]11[/C][C]10.8543700325896[/C][C]0.145629967410369[/C][/ROW]
[ROW][C]207[/C][C]11[/C][C]11.1872567726246[/C][C]-0.187256772624642[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]10.4550940126411[/C][C]1.54490598735886[/C][/ROW]
[ROW][C]209[/C][C]10[/C][C]10.4844218045692[/C][C]-0.484421804569211[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]10.7659819965647[/C][C]-0.765981996564695[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]10.1131912733233[/C][C]1.88680872667671[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]12.0813867253985[/C][C]-0.0813867253985158[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]10.8247827306278[/C][C]0.175217269372227[/C][/ROW]
[ROW][C]214[/C][C]8[/C][C]10.4288689889501[/C][C]-2.42886898895012[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]10.3652405145158[/C][C]1.63475948548421[/C][/ROW]
[ROW][C]216[/C][C]10[/C][C]9.54299442496148[/C][C]0.457005575038524[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]11.0294647985926[/C][C]-0.0294647985926177[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]10.9739456153908[/C][C]-0.973945615390844[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.89994986248329[/C][C]-1.89994986248329[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]11.2014511389392[/C][C]0.798548861060784[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]10.6976065091687[/C][C]1.30239349083134[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]10.8509947141655[/C][C]-0.850994714165545[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]10.0853232860763[/C][C]1.91467671392371[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]10.7082654720075[/C][C]-1.70826547200748[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.76338204656612[/C][C]-0.763382046566119[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]11.103658468303[/C][C]-5.10365846830298[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]10.3308421106178[/C][C]-0.330842110617758[/C][/ROW]
[ROW][C]228[/C][C]9[/C][C]10.5933104495336[/C][C]-1.59331044953362[/C][/ROW]
[ROW][C]229[/C][C]9[/C][C]9.6322407928758[/C][C]-0.632240792875802[/C][/ROW]
[ROW][C]230[/C][C]9[/C][C]10.7116037291093[/C][C]-1.71160372910933[/C][/ROW]
[ROW][C]231[/C][C]6[/C][C]10.3260523789145[/C][C]-4.32605237891448[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]10.688665913699[/C][C]-0.688665913698952[/C][/ROW]
[ROW][C]233[/C][C]6[/C][C]10.7625926906416[/C][C]-4.76259269064162[/C][/ROW]
[ROW][C]234[/C][C]14[/C][C]10.3789281229472[/C][C]3.62107187705279[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]10.7822759828429[/C][C]-0.782275982842932[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]10.2919348552831[/C][C]-0.291934855283137[/C][/ROW]
[ROW][C]237[/C][C]6[/C][C]10.0380398467414[/C][C]-4.03803984674142[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]9.7583821283357[/C][C]2.2416178716643[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]10.3946110251854[/C][C]1.60538897481457[/C][/ROW]
[ROW][C]240[/C][C]7[/C][C]10.4116935969593[/C][C]-3.41169359695926[/C][/ROW]
[ROW][C]241[/C][C]8[/C][C]10.7116407904316[/C][C]-2.71164079043156[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]10.0343399819633[/C][C]0.965660018036662[/C][/ROW]
[ROW][C]243[/C][C]3[/C][C]9.49820395099232[/C][C]-6.49820395099232[/C][/ROW]
[ROW][C]244[/C][C]6[/C][C]10.2451581738314[/C][C]-4.24515817383142[/C][/ROW]
[ROW][C]245[/C][C]10[/C][C]10.4561735120734[/C][C]-0.456173512073408[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]9.98837495983045[/C][C]-1.98837495983045[/C][/ROW]
[ROW][C]247[/C][C]9[/C][C]10.4709313425117[/C][C]-1.47093134251169[/C][/ROW]
[ROW][C]248[/C][C]9[/C][C]9.3294621001848[/C][C]-0.329462100184796[/C][/ROW]
[ROW][C]249[/C][C]8[/C][C]8.24306541832198[/C][C]-0.243065418321984[/C][/ROW]
[ROW][C]250[/C][C]9[/C][C]8.49741142585205[/C][C]0.50258857414795[/C][/ROW]
[ROW][C]251[/C][C]7[/C][C]10.4573144278198[/C][C]-3.45731442781982[/C][/ROW]
[ROW][C]252[/C][C]7[/C][C]10.1551075293322[/C][C]-3.15510752933218[/C][/ROW]
[ROW][C]253[/C][C]6[/C][C]10.8444019338546[/C][C]-4.84440193385462[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]10.4214645493204[/C][C]-1.42146454932037[/C][/ROW]
[ROW][C]255[/C][C]10[/C][C]10.233724612996[/C][C]-0.233724612996006[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]10.3161540265733[/C][C]0.683845973426726[/C][/ROW]
[ROW][C]257[/C][C]12[/C][C]10.3146318582323[/C][C]1.68536814176769[/C][/ROW]
[ROW][C]258[/C][C]8[/C][C]9.83564055761514[/C][C]-1.83564055761514[/C][/ROW]
[ROW][C]259[/C][C]11[/C][C]10.4864080120518[/C][C]0.513591987948233[/C][/ROW]
[ROW][C]260[/C][C]3[/C][C]10.8264322989488[/C][C]-7.82643229894883[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.0719462364999[/C][C]0.928053763500122[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]11.0611080544308[/C][C]0.938891945569169[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]10.1065047254496[/C][C]-3.10650472544958[/C][/ROW]
[ROW][C]264[/C][C]9[/C][C]10.4068191840174[/C][C]-1.40681918401745[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226562&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226562&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
11211.05933863824050.940661361759493
21110.86549398191580.13450601808421
31510.48236490334714.51763509665289
4610.4942494631709-4.49424946317088
51310.30159239516312.69840760483686
61010.3358940250151-0.335894025015141
7129.495940817072072.50405918292793
81411.09222490746762.90777509253244
91211.05957284593660.940427154063376
10911.1441289071298-2.14412890712979
111010.782092823968-0.782092823968026
121210.89878585872931.10121414127068
131210.60732165697331.39267834302671
141110.85355837327080.146441626729197
151511.32924847810833.67075152189166
161210.24617263694351.75382736305652
171010.4463318659728-0.446331865972751
181211.47643819554210.523561804457898
191111.306006708608-0.306006708608036
201210.22233377090221.77766622909785
211110.71737721576760.282622784232405
221210.14532258947211.85467741052792
231311.02162900489281.97837099510716
241110.92372292177550.0762770782245005
251210.90038610354371.09961389645626
261311.04801283246691.95198716753315
271010.9987989445442-0.998798944544235
281410.69971916928563.30028083071443
291210.50345695140831.49654304859172
301010.4842246581953-0.484224658195313
311210.7050676550391.29493234496104
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331010.664376996015-0.664376996015017
341211.23499121094790.765008789052139
351210.27690918473141.72309081526859
36710.9015837255307-3.9015837255307
3799.53361681800241-0.533616818002413
381210.66412314340061.33587685659943
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411010.879547908097-0.879547908097019
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471311.47324603599291.52675396400708
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1021511.21192694290313.78807305709687
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1191210.97107139743061.02892860256942
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121139.853394348574463.14660565142554
1221211.58431237739450.415687622605546
1231411.56430548618492.43569451381511
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1291110.56704836452040.432951635479625
1301010.6494777780976-0.649477778097643
131119.640082243994911.35991775600509
132811.3856325979646-3.38563259796459
133119.831470996276131.16852900372387
1341211.20490280852220.79509719147782
1351210.17522783302291.82477216697715
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1381010.1747257852133-0.174725785213285
139810.7383168131109-2.73831681311093
140910.7099978268756-1.70999782687558
141810.6320345459933-2.63203454599334
142910.8842045824009-1.88420458240086
1431510.88304967915554.11695032084454
144119.648121788833661.35187821116633
145810.8637049208071-2.86370492080713
1461310.0461351504752.95386484952502
1471210.74088047221621.25911952778381
1481210.50351365764881.49648634235117
14999.97822370222054-0.978223702220537
150711.4537542327462-4.45375423274617
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152911.3481061234918-2.34810612349184
153611.2285445281896-5.22854452818962
154810.1981983335048-2.1981983335048
15589.97482873887813-1.97482873887813
1561510.11805169876614.88194830123389
157610.7590843148181-4.7590843148181
158911.0791854443984-2.07918544439839
1591110.92184446935470.078155530645283
160810.6936471343568-2.69364713435679
161810.54411054911-2.54411054911
162108.701809962614131.29819003738587
16389.815304409978-1.815304409978
1641410.16911873677183.83088126322815
1651010.699662463045-0.699662463045012
16688.95724017965005-0.957240179650051
1671110.59751707219490.40248292780514
168129.514295133477332.48570486652268
1691210.88779669211721.11220330788283
1701210.34611502901891.65388497098114
17159.63793252255577-4.63793252255577
1721211.0607277491820.939272250817973
1731011.0613758945443-1.06137589454427
17479.16173908873999-2.16173908873999
1751210.11050116158371.88949883841632
1761111.091450309471-0.0914503094709631
177810.317759928807-2.31775992880703
17899.69989838851579-0.699898388515794
1791010.4698331455068-0.469833145506842
180910.9652588725356-1.96525887253559
1811210.83916686058231.16083313941767
182610.5563056677888-4.55630566778877
1831510.90190732453894.09809267546105
1841210.88996700582041.11003299417962
1851210.13091143186531.86908856813472
1861210.32407921158521.67592078841483
1871110.62718810804950.372811891950491
188710.731738020299-3.731738020299
18979.6197517537771-2.6197517537771
19059.9815479718234-4.9815479718234
1911210.38632423249731.6136757675027
1921211.60176126691810.398238733081907
193310.2900751004349-7.29007510043493
1941110.58360924356630.416390756433691
1951010.3127590632309-0.312759063230863
1961211.15837997968490.841620020315082
19799.92709430055491-0.927094300554908
1981210.90907189905321.09092810094676
19999.89718905700413-0.897189057004133
2001210.30692689341751.69307310658245
201129.783933704326812.21606629567319
2021010.056089261711-0.0560892617109985
203910.5528539982058-1.5528539982058
2041210.15274667402021.84725332597984
205810.7820221302285-2.78202213022848
2061110.85437003258960.145629967410369
2071111.1872567726246-0.187256772624642
2081210.45509401264111.54490598735886
2091010.4844218045692-0.484421804569211
2101010.7659819965647-0.765981996564695
2111210.11319127332331.88680872667671
2121212.0813867253985-0.0813867253985158
2131110.82478273062780.175217269372227
214810.4288689889501-2.42886898895012
2151210.36524051451581.63475948548421
216109.542994424961480.457005575038524
2171111.0294647985926-0.0294647985926177
2181010.9739456153908-0.973945615390844
21989.89994986248329-1.89994986248329
2201211.20145113893920.798548861060784
2211210.69760650916871.30239349083134
2221010.8509947141655-0.850994714165545
2231210.08532328607631.91467671392371
224910.7082654720075-1.70826547200748
22599.76338204656612-0.763382046566119
226611.103658468303-5.10365846830298
2271010.3308421106178-0.330842110617758
228910.5933104495336-1.59331044953362
22999.6322407928758-0.632240792875802
230910.7116037291093-1.71160372910933
231610.3260523789145-4.32605237891448
2321010.688665913699-0.688665913698952
233610.7625926906416-4.76259269064162
2341410.37892812294723.62107187705279
2351010.7822759828429-0.782275982842932
2361010.2919348552831-0.291934855283137
237610.0380398467414-4.03803984674142
238129.75838212833572.2416178716643
2391210.39461102518541.60538897481457
240710.4116935969593-3.41169359695926
241810.7116407904316-2.71164079043156
2421110.03433998196330.965660018036662
24339.49820395099232-6.49820395099232
244610.2451581738314-4.24515817383142
2451010.4561735120734-0.456173512073408
24689.98837495983045-1.98837495983045
247910.4709313425117-1.47093134251169
24899.3294621001848-0.329462100184796
24988.24306541832198-0.243065418321984
25098.497411425852050.50258857414795
251710.4573144278198-3.45731442781982
252710.1551075293322-3.15510752933218
253610.8444019338546-4.84440193385462
254910.4214645493204-1.42146454932037
2551010.233724612996-0.233724612996006
2561110.31615402657330.683845973426726
2571210.31463185823231.68536814176769
25889.83564055761514-1.83564055761514
2591110.48640801205180.513591987948233
260310.8264322989488-7.82643229894883
2611110.07194623649990.928053763500122
2621211.06110805443080.938891945569169
263710.1065047254496-3.10650472544958
264910.4068191840174-1.40681918401745






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.9378156031123090.1243687937753820.0621843968876909
90.881275278587190.237449442825620.11872472141281
100.9320265262807790.1359469474384430.0679734737192214
110.8856738728567980.2286522542864050.114326127143202
120.8442686419233510.3114627161532990.155731358076649
130.7768524441188870.4462951117622260.223147555881113
140.7173613824310910.5652772351378190.282638617568909
150.7457030504749610.5085938990500780.254296949525039
160.6770851934304610.6458296131390770.322914806569539
170.6124662734383010.7750674531233990.387533726561699
180.5333190025599670.9333619948800660.466680997440033
190.4606760457178370.9213520914356740.539323954282163
200.3942083329316150.7884166658632310.605791667068385
210.3237569355449390.6475138710898770.676243064455061
220.2654785872028620.5309571744057240.734521412797138
230.2271539115521990.4543078231043980.772846088447801
240.1994141338097030.3988282676194050.800585866190297
250.1688054444446860.3376108888893720.831194555555314
260.1740699157698310.3481398315396620.825930084230169
270.1597389236078930.3194778472157870.840261076392107
280.1490675143270210.2981350286540420.850932485672979
290.1156501766737230.2313003533474460.884349823326277
300.09983866880476590.1996773376095320.900161331195234
310.07787648654517020.155752973090340.92212351345483
320.1072318893760030.2144637787520060.892768110623997
330.08444760824575590.1688952164915120.915552391754244
340.06473684731674590.1294736946334920.935263152683254
350.05334758755806930.1066951751161390.946652412441931
360.1014289937985740.2028579875971480.898571006201426
370.09748854251004850.1949770850200970.902511457489952
380.07920540891978560.1584108178395710.920794591080214
390.06119545685439640.1223909137087930.938804543145604
400.0483264826925740.0966529653851480.951673517307426
410.03773418354165620.07546836708331240.962265816458344
420.02909270062696110.05818540125392220.970907299373039
430.08378926194175620.1675785238835120.916210738058244
440.06842849731401490.136856994628030.931571502685985
450.05362466175586090.1072493235117220.946375338244139
460.0418296313403280.0836592626806560.958170368659672
470.03330322323226920.06660644646453840.966696776767731
480.02507279271334740.05014558542669480.974927207286653
490.02080108048053470.04160216096106940.979198919519465
500.0160790566917290.03215811338345810.983920943308271
510.01704579836843040.03409159673686090.98295420163157
520.01260482815910230.02520965631820450.987395171840898
530.01028488525849520.02056977051699030.989715114741505
540.008346938162000930.01669387632400190.991653061837999
550.04702633389841410.09405266779682810.952973666101586
560.1637865579829480.3275731159658960.836213442017052
570.1398343967016260.2796687934032520.860165603298374
580.1234867695949650.2469735391899310.876513230405035
590.1044920790261960.2089841580523910.895507920973804
600.09054620324987830.1810924064997570.909453796750122
610.0902896165087890.1805792330175780.909710383491211
620.07526332315515460.1505266463103090.924736676844845
630.08172041750931740.1634408350186350.918279582490683
640.06696353630529350.1339270726105870.933036463694706
650.06423187629985810.1284637525997160.935768123700142
660.05496266136556930.1099253227311390.945037338634431
670.06468842760065120.1293768552013020.935311572399349
680.05805533181627240.1161106636325450.941944668183728
690.04848800397912870.09697600795825740.951511996020871
700.03960280664035340.07920561328070690.960397193359647
710.05864594855200190.1172918971040040.941354051447998
720.04823050602169960.09646101204339930.9517694939783
730.04583837645667660.09167675291335330.954161623543323
740.04179971960614180.08359943921228360.958200280393858
750.03947271567023910.07894543134047820.960527284329761
760.0354745849687190.07094916993743810.964525415031281
770.03133179382572240.06266358765144490.968668206174278
780.02552341246428540.05104682492857070.974476587535715
790.02242630400455280.04485260800910550.977573695995447
800.02354879580872330.04709759161744650.976451204191277
810.01889229180403060.03778458360806120.981107708195969
820.01507023127324910.03014046254649810.984929768726751
830.01235849651408890.02471699302817780.987641503485911
840.009622407655506770.01924481531101350.990377592344493
850.007598144554117180.01519628910823440.992401855445883
860.01055787510587850.02111575021175710.989442124894121
870.008649348733021130.01729869746604230.991350651266979
880.008014193970943190.01602838794188640.991985806029057
890.007156955314528840.01431391062905770.992843044685471
900.007766487010862690.01553297402172540.992233512989137
910.01918488331016880.03836976662033760.980815116689831
920.01553268706211110.03106537412422220.984467312937889
930.01437923065550730.02875846131101450.985620769344493
940.01265609845074390.02531219690148780.987343901549256
950.01155751879561730.02311503759123460.988442481204383
960.01124558060032180.02249116120064360.988754419399678
970.01061301636397080.02122603272794160.989386983636029
980.008581514036054410.01716302807210880.991418485963946
990.007474238576601950.01494847715320390.992525761423398
1000.008416523472204630.01683304694440930.991583476527795
1010.00666210210455850.0133242042091170.993337897895441
1020.009951717191055910.01990343438211180.990048282808944
1030.008093152883720240.01618630576744050.99190684711628
1040.006592752569976150.01318550513995230.993407247430024
1050.005807624742799010.0116152494855980.994192375257201
1060.004682661246552090.009365322493104190.995317338753448
1070.003805076963779910.007610153927559820.99619492303622
1080.002998794558430490.005997589116860970.99700120544157
1090.006573553079295690.01314710615859140.993426446920704
1100.005369136643626840.01073827328725370.994630863356373
1110.007639772115354470.01527954423070890.992360227884646
1120.006567361128971030.01313472225794210.993432638871029
1130.005409907356142950.01081981471228590.994590092643857
1140.004569433193788030.009138866387576070.995430566806212
1150.004364745926054940.008729491852109880.995635254073945
1160.004237967393136920.008475934786273850.995762032606863
1170.006570377533556730.01314075506711350.993429622466443
1180.005216233814732150.01043246762946430.994783766185268
1190.004217111681764430.008434223363528860.995782888318236
1200.003315608738161830.006631217476323670.996684391261838
1210.003991208875778360.007982417751556710.996008791124222
1220.003156724672334650.00631344934466930.996843275327665
1230.003591506529422790.007183013058845570.996408493470577
1240.003867890870407850.007735781740815690.996132109129592
1250.007760071824122170.01552014364824430.992239928175878
1260.006972025395269320.01394405079053860.993027974604731
1270.00570152917765230.01140305835530460.994298470822348
1280.006120940021153240.01224188004230650.993879059978847
1290.004924683155276470.009849366310552940.995075316844724
1300.004079971421613180.008159942843226370.995920028578387
1310.003284649700693070.006569299401386140.996715350299307
1320.004749504201608780.009499008403217560.995250495798391
1330.003874250086967410.007748500173934810.996125749913033
1340.00319706559638120.006394131192762410.996802934403619
1350.002865111998404830.005730223996809670.997134888001595
1360.002248617634009080.004497235268018150.997751382365991
1370.001765557232510940.003531114465021890.998234442767489
1380.001379235837673080.002758471675346160.998620764162327
1390.00168692110744210.00337384221488420.998313078892558
1400.001608050209950730.003216100419901450.998391949790049
1410.001810802427426620.003621604854853230.998189197572573
1420.0018617299525920.003723459905183990.998138270047408
1430.00370855768241610.007417115364832190.996291442317584
1440.003225244364699320.006450488729398640.996774755635301
1450.004004372289023590.008008744578047190.995995627710976
1460.005158501024749880.01031700204949980.99484149897525
1470.004530314244715820.009060628489431630.995469685755284
1480.00417792744977350.0083558548995470.995822072550226
1490.003614009530213530.007228019060427050.996385990469786
1500.007692469858551460.01538493971710290.992307530141449
1510.008071643641624340.01614328728324870.991928356358376
1520.008041244998955320.01608248999791060.991958755001045
1530.02205361557560840.04410723115121680.977946384424392
1540.02256442774046270.04512885548092530.977435572259537
1550.02273985618472970.04547971236945930.97726014381527
1560.05436535164554750.1087307032910950.945634648354452
1570.1012021396327150.2024042792654290.898797860367285
1580.09772241333781940.1954448266756390.902277586662181
1590.08561273408243180.1712254681648640.914387265917568
1600.09532685056778050.1906537011355610.90467314943222
1610.09986875292496140.1997375058499230.900131247075039
1620.08991493990825520.179829879816510.910085060091745
1630.08642219049792530.1728443809958510.913577809502075
1640.1298163714691940.2596327429383880.870183628530806
1650.1135780822568610.2271561645137230.886421917743139
1660.1034092704026350.2068185408052690.896590729597365
1670.08947014021924270.1789402804384850.910529859780757
1680.102949009148110.205898018296220.89705099085189
1690.09191911217993840.1838382243598770.908080887820062
1700.08313190142325820.1662638028465160.916868098576742
1710.1339899906926760.2679799813853530.866010009307324
1720.1213197096685220.2426394193370440.878680290331478
1730.1062591932358630.2125183864717260.893740806764137
1740.1045877330505040.2091754661010070.895412266949496
1750.1180083681004460.2360167362008920.881991631899554
1760.1020564972604140.2041129945208270.897943502739586
1770.0983451638012790.1966903276025580.901654836198721
1780.08496290098499250.1699258019699850.915037099015008
1790.0730503925986750.146100785197350.926949607401325
1800.06705265435030010.13410530870060.9329473456497
1810.06066993206023230.1213398641204650.939330067939768
1820.08731273273335910.1746254654667180.912687267266641
1830.1382868282982490.2765736565964990.861713171701751
1840.1392682197448220.2785364394896440.860731780255178
1850.1527843088024780.3055686176049550.847215691197522
1860.1470819950386770.2941639900773540.852918004961323
1870.1318472372849230.2636944745698460.868152762715077
1880.1449164816551260.2898329633102530.855083518344874
1890.1464125088672950.2928250177345890.853587491132705
1900.2618318189538090.5236636379076180.738168181046191
1910.2453318779775990.4906637559551970.754668122022401
1920.2231674983848020.4463349967696030.776832501615198
1930.5377387981068870.9245224037862260.462261201893113
1940.5001774334243160.9996451331513680.499822566575684
1950.463236739281020.926473478562040.53676326071898
1960.4421724851100280.8843449702200560.557827514889972
1970.4051462061194610.8102924122389220.594853793880539
1980.3887097341848740.7774194683697480.611290265815126
1990.3541960808617890.7083921617235770.645803919138211
2000.3664048205017530.7328096410035060.633595179498247
2010.3910195693232050.7820391386464110.608980430676795
2020.3656261299480840.7312522598961680.634373870051916
2030.3338647705185450.667729541037090.666135229481455
2040.341406310043150.6828126200862990.65859368995685
2050.3313496393664460.6626992787328930.668650360633554
2060.3022367847529120.6044735695058250.697763215247088
2070.2742233070993660.5484466141987320.725776692900634
2080.2661643509027330.5323287018054670.733835649097267
2090.2343253398476390.4686506796952780.765674660152361
2100.2071303658510970.4142607317021940.792869634148903
2110.2137089516054970.4274179032109930.786291048394503
2120.1907942351132070.3815884702264150.809205764886793
2130.1682625473306450.3365250946612890.831737452669355
2140.1522823314761560.3045646629523130.847717668523844
2150.1542899576234340.3085799152468680.845710042376566
2160.1441630398108580.2883260796217170.855836960189142
2170.1348043714588470.2696087429176940.865195628541153
2180.115102141678640.2302042833572790.88489785832136
2190.106401332676020.212802665352040.89359866732398
2200.1072837029882380.2145674059764760.892716297011762
2210.1257151638147180.2514303276294360.874284836185282
2220.103940397646610.2078807952932190.89605960235339
2230.123724589636610.2474491792732210.87627541036339
2240.1058466493270060.2116932986540120.894153350672994
2250.09381045449371270.1876209089874250.906189545506287
2260.1154414264650830.2308828529301650.884558573534917
2270.09485847223356430.1897169444671290.905141527766436
2280.07664213771234060.1532842754246810.923357862287659
2290.05992457163733220.1198491432746640.940075428362668
2300.04707095687465270.09414191374930530.952929043125347
2310.05286246106041190.1057249221208240.947137538939588
2320.04024495699296490.08048991398592980.959755043007035
2330.0653337830164060.1306675660328120.934666216983594
2340.1829301807060270.3658603614120530.817069819293973
2350.1536465782505530.3072931565011070.846353421749447
2360.1403100172611150.280620034522230.859689982738885
2370.1248930294781220.2497860589562430.875106970521878
2380.1805141927808710.3610283855617410.819485807219129
2390.2377795438646780.4755590877293560.762220456135322
2400.20103374041510.4020674808301990.7989662595849
2410.1636372263506960.3272744527013920.836362773649304
2420.1376056469947680.2752112939895360.862394353005232
2430.388115482167960.7762309643359210.61188451783204
2440.427907848609470.855815697218940.57209215139053
2450.547185560686530.9056288786269390.45281443931347
2460.594370082256760.811259835486480.40562991774324
2470.5435700945436750.912859810912650.456429905456325
2480.5015417470017890.9969165059964220.498458252998211
2490.4397844138939760.8795688277879520.560215586106024
2500.3557269728379540.7114539456759080.644273027162046
2510.4662023028694420.9324046057388840.533797697130558
2520.380236105846090.7604722116921790.61976389415391
2530.3951069960886350.7902139921772710.604893003911365
2540.2904099995691240.5808199991382480.709590000430876
2550.2816618953257040.5633237906514080.718338104674296
2560.2623240486022560.5246480972045130.737675951397744

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.937815603112309 & 0.124368793775382 & 0.0621843968876909 \tabularnewline
9 & 0.88127527858719 & 0.23744944282562 & 0.11872472141281 \tabularnewline
10 & 0.932026526280779 & 0.135946947438443 & 0.0679734737192214 \tabularnewline
11 & 0.885673872856798 & 0.228652254286405 & 0.114326127143202 \tabularnewline
12 & 0.844268641923351 & 0.311462716153299 & 0.155731358076649 \tabularnewline
13 & 0.776852444118887 & 0.446295111762226 & 0.223147555881113 \tabularnewline
14 & 0.717361382431091 & 0.565277235137819 & 0.282638617568909 \tabularnewline
15 & 0.745703050474961 & 0.508593899050078 & 0.254296949525039 \tabularnewline
16 & 0.677085193430461 & 0.645829613139077 & 0.322914806569539 \tabularnewline
17 & 0.612466273438301 & 0.775067453123399 & 0.387533726561699 \tabularnewline
18 & 0.533319002559967 & 0.933361994880066 & 0.466680997440033 \tabularnewline
19 & 0.460676045717837 & 0.921352091435674 & 0.539323954282163 \tabularnewline
20 & 0.394208332931615 & 0.788416665863231 & 0.605791667068385 \tabularnewline
21 & 0.323756935544939 & 0.647513871089877 & 0.676243064455061 \tabularnewline
22 & 0.265478587202862 & 0.530957174405724 & 0.734521412797138 \tabularnewline
23 & 0.227153911552199 & 0.454307823104398 & 0.772846088447801 \tabularnewline
24 & 0.199414133809703 & 0.398828267619405 & 0.800585866190297 \tabularnewline
25 & 0.168805444444686 & 0.337610888889372 & 0.831194555555314 \tabularnewline
26 & 0.174069915769831 & 0.348139831539662 & 0.825930084230169 \tabularnewline
27 & 0.159738923607893 & 0.319477847215787 & 0.840261076392107 \tabularnewline
28 & 0.149067514327021 & 0.298135028654042 & 0.850932485672979 \tabularnewline
29 & 0.115650176673723 & 0.231300353347446 & 0.884349823326277 \tabularnewline
30 & 0.0998386688047659 & 0.199677337609532 & 0.900161331195234 \tabularnewline
31 & 0.0778764865451702 & 0.15575297309034 & 0.92212351345483 \tabularnewline
32 & 0.107231889376003 & 0.214463778752006 & 0.892768110623997 \tabularnewline
33 & 0.0844476082457559 & 0.168895216491512 & 0.915552391754244 \tabularnewline
34 & 0.0647368473167459 & 0.129473694633492 & 0.935263152683254 \tabularnewline
35 & 0.0533475875580693 & 0.106695175116139 & 0.946652412441931 \tabularnewline
36 & 0.101428993798574 & 0.202857987597148 & 0.898571006201426 \tabularnewline
37 & 0.0974885425100485 & 0.194977085020097 & 0.902511457489952 \tabularnewline
38 & 0.0792054089197856 & 0.158410817839571 & 0.920794591080214 \tabularnewline
39 & 0.0611954568543964 & 0.122390913708793 & 0.938804543145604 \tabularnewline
40 & 0.048326482692574 & 0.096652965385148 & 0.951673517307426 \tabularnewline
41 & 0.0377341835416562 & 0.0754683670833124 & 0.962265816458344 \tabularnewline
42 & 0.0290927006269611 & 0.0581854012539222 & 0.970907299373039 \tabularnewline
43 & 0.0837892619417562 & 0.167578523883512 & 0.916210738058244 \tabularnewline
44 & 0.0684284973140149 & 0.13685699462803 & 0.931571502685985 \tabularnewline
45 & 0.0536246617558609 & 0.107249323511722 & 0.946375338244139 \tabularnewline
46 & 0.041829631340328 & 0.083659262680656 & 0.958170368659672 \tabularnewline
47 & 0.0333032232322692 & 0.0666064464645384 & 0.966696776767731 \tabularnewline
48 & 0.0250727927133474 & 0.0501455854266948 & 0.974927207286653 \tabularnewline
49 & 0.0208010804805347 & 0.0416021609610694 & 0.979198919519465 \tabularnewline
50 & 0.016079056691729 & 0.0321581133834581 & 0.983920943308271 \tabularnewline
51 & 0.0170457983684304 & 0.0340915967368609 & 0.98295420163157 \tabularnewline
52 & 0.0126048281591023 & 0.0252096563182045 & 0.987395171840898 \tabularnewline
53 & 0.0102848852584952 & 0.0205697705169903 & 0.989715114741505 \tabularnewline
54 & 0.00834693816200093 & 0.0166938763240019 & 0.991653061837999 \tabularnewline
55 & 0.0470263338984141 & 0.0940526677968281 & 0.952973666101586 \tabularnewline
56 & 0.163786557982948 & 0.327573115965896 & 0.836213442017052 \tabularnewline
57 & 0.139834396701626 & 0.279668793403252 & 0.860165603298374 \tabularnewline
58 & 0.123486769594965 & 0.246973539189931 & 0.876513230405035 \tabularnewline
59 & 0.104492079026196 & 0.208984158052391 & 0.895507920973804 \tabularnewline
60 & 0.0905462032498783 & 0.181092406499757 & 0.909453796750122 \tabularnewline
61 & 0.090289616508789 & 0.180579233017578 & 0.909710383491211 \tabularnewline
62 & 0.0752633231551546 & 0.150526646310309 & 0.924736676844845 \tabularnewline
63 & 0.0817204175093174 & 0.163440835018635 & 0.918279582490683 \tabularnewline
64 & 0.0669635363052935 & 0.133927072610587 & 0.933036463694706 \tabularnewline
65 & 0.0642318762998581 & 0.128463752599716 & 0.935768123700142 \tabularnewline
66 & 0.0549626613655693 & 0.109925322731139 & 0.945037338634431 \tabularnewline
67 & 0.0646884276006512 & 0.129376855201302 & 0.935311572399349 \tabularnewline
68 & 0.0580553318162724 & 0.116110663632545 & 0.941944668183728 \tabularnewline
69 & 0.0484880039791287 & 0.0969760079582574 & 0.951511996020871 \tabularnewline
70 & 0.0396028066403534 & 0.0792056132807069 & 0.960397193359647 \tabularnewline
71 & 0.0586459485520019 & 0.117291897104004 & 0.941354051447998 \tabularnewline
72 & 0.0482305060216996 & 0.0964610120433993 & 0.9517694939783 \tabularnewline
73 & 0.0458383764566766 & 0.0916767529133533 & 0.954161623543323 \tabularnewline
74 & 0.0417997196061418 & 0.0835994392122836 & 0.958200280393858 \tabularnewline
75 & 0.0394727156702391 & 0.0789454313404782 & 0.960527284329761 \tabularnewline
76 & 0.035474584968719 & 0.0709491699374381 & 0.964525415031281 \tabularnewline
77 & 0.0313317938257224 & 0.0626635876514449 & 0.968668206174278 \tabularnewline
78 & 0.0255234124642854 & 0.0510468249285707 & 0.974476587535715 \tabularnewline
79 & 0.0224263040045528 & 0.0448526080091055 & 0.977573695995447 \tabularnewline
80 & 0.0235487958087233 & 0.0470975916174465 & 0.976451204191277 \tabularnewline
81 & 0.0188922918040306 & 0.0377845836080612 & 0.981107708195969 \tabularnewline
82 & 0.0150702312732491 & 0.0301404625464981 & 0.984929768726751 \tabularnewline
83 & 0.0123584965140889 & 0.0247169930281778 & 0.987641503485911 \tabularnewline
84 & 0.00962240765550677 & 0.0192448153110135 & 0.990377592344493 \tabularnewline
85 & 0.00759814455411718 & 0.0151962891082344 & 0.992401855445883 \tabularnewline
86 & 0.0105578751058785 & 0.0211157502117571 & 0.989442124894121 \tabularnewline
87 & 0.00864934873302113 & 0.0172986974660423 & 0.991350651266979 \tabularnewline
88 & 0.00801419397094319 & 0.0160283879418864 & 0.991985806029057 \tabularnewline
89 & 0.00715695531452884 & 0.0143139106290577 & 0.992843044685471 \tabularnewline
90 & 0.00776648701086269 & 0.0155329740217254 & 0.992233512989137 \tabularnewline
91 & 0.0191848833101688 & 0.0383697666203376 & 0.980815116689831 \tabularnewline
92 & 0.0155326870621111 & 0.0310653741242222 & 0.984467312937889 \tabularnewline
93 & 0.0143792306555073 & 0.0287584613110145 & 0.985620769344493 \tabularnewline
94 & 0.0126560984507439 & 0.0253121969014878 & 0.987343901549256 \tabularnewline
95 & 0.0115575187956173 & 0.0231150375912346 & 0.988442481204383 \tabularnewline
96 & 0.0112455806003218 & 0.0224911612006436 & 0.988754419399678 \tabularnewline
97 & 0.0106130163639708 & 0.0212260327279416 & 0.989386983636029 \tabularnewline
98 & 0.00858151403605441 & 0.0171630280721088 & 0.991418485963946 \tabularnewline
99 & 0.00747423857660195 & 0.0149484771532039 & 0.992525761423398 \tabularnewline
100 & 0.00841652347220463 & 0.0168330469444093 & 0.991583476527795 \tabularnewline
101 & 0.0066621021045585 & 0.013324204209117 & 0.993337897895441 \tabularnewline
102 & 0.00995171719105591 & 0.0199034343821118 & 0.990048282808944 \tabularnewline
103 & 0.00809315288372024 & 0.0161863057674405 & 0.99190684711628 \tabularnewline
104 & 0.00659275256997615 & 0.0131855051399523 & 0.993407247430024 \tabularnewline
105 & 0.00580762474279901 & 0.011615249485598 & 0.994192375257201 \tabularnewline
106 & 0.00468266124655209 & 0.00936532249310419 & 0.995317338753448 \tabularnewline
107 & 0.00380507696377991 & 0.00761015392755982 & 0.99619492303622 \tabularnewline
108 & 0.00299879455843049 & 0.00599758911686097 & 0.99700120544157 \tabularnewline
109 & 0.00657355307929569 & 0.0131471061585914 & 0.993426446920704 \tabularnewline
110 & 0.00536913664362684 & 0.0107382732872537 & 0.994630863356373 \tabularnewline
111 & 0.00763977211535447 & 0.0152795442307089 & 0.992360227884646 \tabularnewline
112 & 0.00656736112897103 & 0.0131347222579421 & 0.993432638871029 \tabularnewline
113 & 0.00540990735614295 & 0.0108198147122859 & 0.994590092643857 \tabularnewline
114 & 0.00456943319378803 & 0.00913886638757607 & 0.995430566806212 \tabularnewline
115 & 0.00436474592605494 & 0.00872949185210988 & 0.995635254073945 \tabularnewline
116 & 0.00423796739313692 & 0.00847593478627385 & 0.995762032606863 \tabularnewline
117 & 0.00657037753355673 & 0.0131407550671135 & 0.993429622466443 \tabularnewline
118 & 0.00521623381473215 & 0.0104324676294643 & 0.994783766185268 \tabularnewline
119 & 0.00421711168176443 & 0.00843422336352886 & 0.995782888318236 \tabularnewline
120 & 0.00331560873816183 & 0.00663121747632367 & 0.996684391261838 \tabularnewline
121 & 0.00399120887577836 & 0.00798241775155671 & 0.996008791124222 \tabularnewline
122 & 0.00315672467233465 & 0.0063134493446693 & 0.996843275327665 \tabularnewline
123 & 0.00359150652942279 & 0.00718301305884557 & 0.996408493470577 \tabularnewline
124 & 0.00386789087040785 & 0.00773578174081569 & 0.996132109129592 \tabularnewline
125 & 0.00776007182412217 & 0.0155201436482443 & 0.992239928175878 \tabularnewline
126 & 0.00697202539526932 & 0.0139440507905386 & 0.993027974604731 \tabularnewline
127 & 0.0057015291776523 & 0.0114030583553046 & 0.994298470822348 \tabularnewline
128 & 0.00612094002115324 & 0.0122418800423065 & 0.993879059978847 \tabularnewline
129 & 0.00492468315527647 & 0.00984936631055294 & 0.995075316844724 \tabularnewline
130 & 0.00407997142161318 & 0.00815994284322637 & 0.995920028578387 \tabularnewline
131 & 0.00328464970069307 & 0.00656929940138614 & 0.996715350299307 \tabularnewline
132 & 0.00474950420160878 & 0.00949900840321756 & 0.995250495798391 \tabularnewline
133 & 0.00387425008696741 & 0.00774850017393481 & 0.996125749913033 \tabularnewline
134 & 0.0031970655963812 & 0.00639413119276241 & 0.996802934403619 \tabularnewline
135 & 0.00286511199840483 & 0.00573022399680967 & 0.997134888001595 \tabularnewline
136 & 0.00224861763400908 & 0.00449723526801815 & 0.997751382365991 \tabularnewline
137 & 0.00176555723251094 & 0.00353111446502189 & 0.998234442767489 \tabularnewline
138 & 0.00137923583767308 & 0.00275847167534616 & 0.998620764162327 \tabularnewline
139 & 0.0016869211074421 & 0.0033738422148842 & 0.998313078892558 \tabularnewline
140 & 0.00160805020995073 & 0.00321610041990145 & 0.998391949790049 \tabularnewline
141 & 0.00181080242742662 & 0.00362160485485323 & 0.998189197572573 \tabularnewline
142 & 0.001861729952592 & 0.00372345990518399 & 0.998138270047408 \tabularnewline
143 & 0.0037085576824161 & 0.00741711536483219 & 0.996291442317584 \tabularnewline
144 & 0.00322524436469932 & 0.00645048872939864 & 0.996774755635301 \tabularnewline
145 & 0.00400437228902359 & 0.00800874457804719 & 0.995995627710976 \tabularnewline
146 & 0.00515850102474988 & 0.0103170020494998 & 0.99484149897525 \tabularnewline
147 & 0.00453031424471582 & 0.00906062848943163 & 0.995469685755284 \tabularnewline
148 & 0.0041779274497735 & 0.008355854899547 & 0.995822072550226 \tabularnewline
149 & 0.00361400953021353 & 0.00722801906042705 & 0.996385990469786 \tabularnewline
150 & 0.00769246985855146 & 0.0153849397171029 & 0.992307530141449 \tabularnewline
151 & 0.00807164364162434 & 0.0161432872832487 & 0.991928356358376 \tabularnewline
152 & 0.00804124499895532 & 0.0160824899979106 & 0.991958755001045 \tabularnewline
153 & 0.0220536155756084 & 0.0441072311512168 & 0.977946384424392 \tabularnewline
154 & 0.0225644277404627 & 0.0451288554809253 & 0.977435572259537 \tabularnewline
155 & 0.0227398561847297 & 0.0454797123694593 & 0.97726014381527 \tabularnewline
156 & 0.0543653516455475 & 0.108730703291095 & 0.945634648354452 \tabularnewline
157 & 0.101202139632715 & 0.202404279265429 & 0.898797860367285 \tabularnewline
158 & 0.0977224133378194 & 0.195444826675639 & 0.902277586662181 \tabularnewline
159 & 0.0856127340824318 & 0.171225468164864 & 0.914387265917568 \tabularnewline
160 & 0.0953268505677805 & 0.190653701135561 & 0.90467314943222 \tabularnewline
161 & 0.0998687529249614 & 0.199737505849923 & 0.900131247075039 \tabularnewline
162 & 0.0899149399082552 & 0.17982987981651 & 0.910085060091745 \tabularnewline
163 & 0.0864221904979253 & 0.172844380995851 & 0.913577809502075 \tabularnewline
164 & 0.129816371469194 & 0.259632742938388 & 0.870183628530806 \tabularnewline
165 & 0.113578082256861 & 0.227156164513723 & 0.886421917743139 \tabularnewline
166 & 0.103409270402635 & 0.206818540805269 & 0.896590729597365 \tabularnewline
167 & 0.0894701402192427 & 0.178940280438485 & 0.910529859780757 \tabularnewline
168 & 0.10294900914811 & 0.20589801829622 & 0.89705099085189 \tabularnewline
169 & 0.0919191121799384 & 0.183838224359877 & 0.908080887820062 \tabularnewline
170 & 0.0831319014232582 & 0.166263802846516 & 0.916868098576742 \tabularnewline
171 & 0.133989990692676 & 0.267979981385353 & 0.866010009307324 \tabularnewline
172 & 0.121319709668522 & 0.242639419337044 & 0.878680290331478 \tabularnewline
173 & 0.106259193235863 & 0.212518386471726 & 0.893740806764137 \tabularnewline
174 & 0.104587733050504 & 0.209175466101007 & 0.895412266949496 \tabularnewline
175 & 0.118008368100446 & 0.236016736200892 & 0.881991631899554 \tabularnewline
176 & 0.102056497260414 & 0.204112994520827 & 0.897943502739586 \tabularnewline
177 & 0.098345163801279 & 0.196690327602558 & 0.901654836198721 \tabularnewline
178 & 0.0849629009849925 & 0.169925801969985 & 0.915037099015008 \tabularnewline
179 & 0.073050392598675 & 0.14610078519735 & 0.926949607401325 \tabularnewline
180 & 0.0670526543503001 & 0.1341053087006 & 0.9329473456497 \tabularnewline
181 & 0.0606699320602323 & 0.121339864120465 & 0.939330067939768 \tabularnewline
182 & 0.0873127327333591 & 0.174625465466718 & 0.912687267266641 \tabularnewline
183 & 0.138286828298249 & 0.276573656596499 & 0.861713171701751 \tabularnewline
184 & 0.139268219744822 & 0.278536439489644 & 0.860731780255178 \tabularnewline
185 & 0.152784308802478 & 0.305568617604955 & 0.847215691197522 \tabularnewline
186 & 0.147081995038677 & 0.294163990077354 & 0.852918004961323 \tabularnewline
187 & 0.131847237284923 & 0.263694474569846 & 0.868152762715077 \tabularnewline
188 & 0.144916481655126 & 0.289832963310253 & 0.855083518344874 \tabularnewline
189 & 0.146412508867295 & 0.292825017734589 & 0.853587491132705 \tabularnewline
190 & 0.261831818953809 & 0.523663637907618 & 0.738168181046191 \tabularnewline
191 & 0.245331877977599 & 0.490663755955197 & 0.754668122022401 \tabularnewline
192 & 0.223167498384802 & 0.446334996769603 & 0.776832501615198 \tabularnewline
193 & 0.537738798106887 & 0.924522403786226 & 0.462261201893113 \tabularnewline
194 & 0.500177433424316 & 0.999645133151368 & 0.499822566575684 \tabularnewline
195 & 0.46323673928102 & 0.92647347856204 & 0.53676326071898 \tabularnewline
196 & 0.442172485110028 & 0.884344970220056 & 0.557827514889972 \tabularnewline
197 & 0.405146206119461 & 0.810292412238922 & 0.594853793880539 \tabularnewline
198 & 0.388709734184874 & 0.777419468369748 & 0.611290265815126 \tabularnewline
199 & 0.354196080861789 & 0.708392161723577 & 0.645803919138211 \tabularnewline
200 & 0.366404820501753 & 0.732809641003506 & 0.633595179498247 \tabularnewline
201 & 0.391019569323205 & 0.782039138646411 & 0.608980430676795 \tabularnewline
202 & 0.365626129948084 & 0.731252259896168 & 0.634373870051916 \tabularnewline
203 & 0.333864770518545 & 0.66772954103709 & 0.666135229481455 \tabularnewline
204 & 0.34140631004315 & 0.682812620086299 & 0.65859368995685 \tabularnewline
205 & 0.331349639366446 & 0.662699278732893 & 0.668650360633554 \tabularnewline
206 & 0.302236784752912 & 0.604473569505825 & 0.697763215247088 \tabularnewline
207 & 0.274223307099366 & 0.548446614198732 & 0.725776692900634 \tabularnewline
208 & 0.266164350902733 & 0.532328701805467 & 0.733835649097267 \tabularnewline
209 & 0.234325339847639 & 0.468650679695278 & 0.765674660152361 \tabularnewline
210 & 0.207130365851097 & 0.414260731702194 & 0.792869634148903 \tabularnewline
211 & 0.213708951605497 & 0.427417903210993 & 0.786291048394503 \tabularnewline
212 & 0.190794235113207 & 0.381588470226415 & 0.809205764886793 \tabularnewline
213 & 0.168262547330645 & 0.336525094661289 & 0.831737452669355 \tabularnewline
214 & 0.152282331476156 & 0.304564662952313 & 0.847717668523844 \tabularnewline
215 & 0.154289957623434 & 0.308579915246868 & 0.845710042376566 \tabularnewline
216 & 0.144163039810858 & 0.288326079621717 & 0.855836960189142 \tabularnewline
217 & 0.134804371458847 & 0.269608742917694 & 0.865195628541153 \tabularnewline
218 & 0.11510214167864 & 0.230204283357279 & 0.88489785832136 \tabularnewline
219 & 0.10640133267602 & 0.21280266535204 & 0.89359866732398 \tabularnewline
220 & 0.107283702988238 & 0.214567405976476 & 0.892716297011762 \tabularnewline
221 & 0.125715163814718 & 0.251430327629436 & 0.874284836185282 \tabularnewline
222 & 0.10394039764661 & 0.207880795293219 & 0.89605960235339 \tabularnewline
223 & 0.12372458963661 & 0.247449179273221 & 0.87627541036339 \tabularnewline
224 & 0.105846649327006 & 0.211693298654012 & 0.894153350672994 \tabularnewline
225 & 0.0938104544937127 & 0.187620908987425 & 0.906189545506287 \tabularnewline
226 & 0.115441426465083 & 0.230882852930165 & 0.884558573534917 \tabularnewline
227 & 0.0948584722335643 & 0.189716944467129 & 0.905141527766436 \tabularnewline
228 & 0.0766421377123406 & 0.153284275424681 & 0.923357862287659 \tabularnewline
229 & 0.0599245716373322 & 0.119849143274664 & 0.940075428362668 \tabularnewline
230 & 0.0470709568746527 & 0.0941419137493053 & 0.952929043125347 \tabularnewline
231 & 0.0528624610604119 & 0.105724922120824 & 0.947137538939588 \tabularnewline
232 & 0.0402449569929649 & 0.0804899139859298 & 0.959755043007035 \tabularnewline
233 & 0.065333783016406 & 0.130667566032812 & 0.934666216983594 \tabularnewline
234 & 0.182930180706027 & 0.365860361412053 & 0.817069819293973 \tabularnewline
235 & 0.153646578250553 & 0.307293156501107 & 0.846353421749447 \tabularnewline
236 & 0.140310017261115 & 0.28062003452223 & 0.859689982738885 \tabularnewline
237 & 0.124893029478122 & 0.249786058956243 & 0.875106970521878 \tabularnewline
238 & 0.180514192780871 & 0.361028385561741 & 0.819485807219129 \tabularnewline
239 & 0.237779543864678 & 0.475559087729356 & 0.762220456135322 \tabularnewline
240 & 0.2010337404151 & 0.402067480830199 & 0.7989662595849 \tabularnewline
241 & 0.163637226350696 & 0.327274452701392 & 0.836362773649304 \tabularnewline
242 & 0.137605646994768 & 0.275211293989536 & 0.862394353005232 \tabularnewline
243 & 0.38811548216796 & 0.776230964335921 & 0.61188451783204 \tabularnewline
244 & 0.42790784860947 & 0.85581569721894 & 0.57209215139053 \tabularnewline
245 & 0.54718556068653 & 0.905628878626939 & 0.45281443931347 \tabularnewline
246 & 0.59437008225676 & 0.81125983548648 & 0.40562991774324 \tabularnewline
247 & 0.543570094543675 & 0.91285981091265 & 0.456429905456325 \tabularnewline
248 & 0.501541747001789 & 0.996916505996422 & 0.498458252998211 \tabularnewline
249 & 0.439784413893976 & 0.879568827787952 & 0.560215586106024 \tabularnewline
250 & 0.355726972837954 & 0.711453945675908 & 0.644273027162046 \tabularnewline
251 & 0.466202302869442 & 0.932404605738884 & 0.533797697130558 \tabularnewline
252 & 0.38023610584609 & 0.760472211692179 & 0.61976389415391 \tabularnewline
253 & 0.395106996088635 & 0.790213992177271 & 0.604893003911365 \tabularnewline
254 & 0.290409999569124 & 0.580819999138248 & 0.709590000430876 \tabularnewline
255 & 0.281661895325704 & 0.563323790651408 & 0.718338104674296 \tabularnewline
256 & 0.262324048602256 & 0.524648097204513 & 0.737675951397744 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226562&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]8[/C][C]0.937815603112309[/C][C]0.124368793775382[/C][C]0.0621843968876909[/C][/ROW]
[ROW][C]9[/C][C]0.88127527858719[/C][C]0.23744944282562[/C][C]0.11872472141281[/C][/ROW]
[ROW][C]10[/C][C]0.932026526280779[/C][C]0.135946947438443[/C][C]0.0679734737192214[/C][/ROW]
[ROW][C]11[/C][C]0.885673872856798[/C][C]0.228652254286405[/C][C]0.114326127143202[/C][/ROW]
[ROW][C]12[/C][C]0.844268641923351[/C][C]0.311462716153299[/C][C]0.155731358076649[/C][/ROW]
[ROW][C]13[/C][C]0.776852444118887[/C][C]0.446295111762226[/C][C]0.223147555881113[/C][/ROW]
[ROW][C]14[/C][C]0.717361382431091[/C][C]0.565277235137819[/C][C]0.282638617568909[/C][/ROW]
[ROW][C]15[/C][C]0.745703050474961[/C][C]0.508593899050078[/C][C]0.254296949525039[/C][/ROW]
[ROW][C]16[/C][C]0.677085193430461[/C][C]0.645829613139077[/C][C]0.322914806569539[/C][/ROW]
[ROW][C]17[/C][C]0.612466273438301[/C][C]0.775067453123399[/C][C]0.387533726561699[/C][/ROW]
[ROW][C]18[/C][C]0.533319002559967[/C][C]0.933361994880066[/C][C]0.466680997440033[/C][/ROW]
[ROW][C]19[/C][C]0.460676045717837[/C][C]0.921352091435674[/C][C]0.539323954282163[/C][/ROW]
[ROW][C]20[/C][C]0.394208332931615[/C][C]0.788416665863231[/C][C]0.605791667068385[/C][/ROW]
[ROW][C]21[/C][C]0.323756935544939[/C][C]0.647513871089877[/C][C]0.676243064455061[/C][/ROW]
[ROW][C]22[/C][C]0.265478587202862[/C][C]0.530957174405724[/C][C]0.734521412797138[/C][/ROW]
[ROW][C]23[/C][C]0.227153911552199[/C][C]0.454307823104398[/C][C]0.772846088447801[/C][/ROW]
[ROW][C]24[/C][C]0.199414133809703[/C][C]0.398828267619405[/C][C]0.800585866190297[/C][/ROW]
[ROW][C]25[/C][C]0.168805444444686[/C][C]0.337610888889372[/C][C]0.831194555555314[/C][/ROW]
[ROW][C]26[/C][C]0.174069915769831[/C][C]0.348139831539662[/C][C]0.825930084230169[/C][/ROW]
[ROW][C]27[/C][C]0.159738923607893[/C][C]0.319477847215787[/C][C]0.840261076392107[/C][/ROW]
[ROW][C]28[/C][C]0.149067514327021[/C][C]0.298135028654042[/C][C]0.850932485672979[/C][/ROW]
[ROW][C]29[/C][C]0.115650176673723[/C][C]0.231300353347446[/C][C]0.884349823326277[/C][/ROW]
[ROW][C]30[/C][C]0.0998386688047659[/C][C]0.199677337609532[/C][C]0.900161331195234[/C][/ROW]
[ROW][C]31[/C][C]0.0778764865451702[/C][C]0.15575297309034[/C][C]0.92212351345483[/C][/ROW]
[ROW][C]32[/C][C]0.107231889376003[/C][C]0.214463778752006[/C][C]0.892768110623997[/C][/ROW]
[ROW][C]33[/C][C]0.0844476082457559[/C][C]0.168895216491512[/C][C]0.915552391754244[/C][/ROW]
[ROW][C]34[/C][C]0.0647368473167459[/C][C]0.129473694633492[/C][C]0.935263152683254[/C][/ROW]
[ROW][C]35[/C][C]0.0533475875580693[/C][C]0.106695175116139[/C][C]0.946652412441931[/C][/ROW]
[ROW][C]36[/C][C]0.101428993798574[/C][C]0.202857987597148[/C][C]0.898571006201426[/C][/ROW]
[ROW][C]37[/C][C]0.0974885425100485[/C][C]0.194977085020097[/C][C]0.902511457489952[/C][/ROW]
[ROW][C]38[/C][C]0.0792054089197856[/C][C]0.158410817839571[/C][C]0.920794591080214[/C][/ROW]
[ROW][C]39[/C][C]0.0611954568543964[/C][C]0.122390913708793[/C][C]0.938804543145604[/C][/ROW]
[ROW][C]40[/C][C]0.048326482692574[/C][C]0.096652965385148[/C][C]0.951673517307426[/C][/ROW]
[ROW][C]41[/C][C]0.0377341835416562[/C][C]0.0754683670833124[/C][C]0.962265816458344[/C][/ROW]
[ROW][C]42[/C][C]0.0290927006269611[/C][C]0.0581854012539222[/C][C]0.970907299373039[/C][/ROW]
[ROW][C]43[/C][C]0.0837892619417562[/C][C]0.167578523883512[/C][C]0.916210738058244[/C][/ROW]
[ROW][C]44[/C][C]0.0684284973140149[/C][C]0.13685699462803[/C][C]0.931571502685985[/C][/ROW]
[ROW][C]45[/C][C]0.0536246617558609[/C][C]0.107249323511722[/C][C]0.946375338244139[/C][/ROW]
[ROW][C]46[/C][C]0.041829631340328[/C][C]0.083659262680656[/C][C]0.958170368659672[/C][/ROW]
[ROW][C]47[/C][C]0.0333032232322692[/C][C]0.0666064464645384[/C][C]0.966696776767731[/C][/ROW]
[ROW][C]48[/C][C]0.0250727927133474[/C][C]0.0501455854266948[/C][C]0.974927207286653[/C][/ROW]
[ROW][C]49[/C][C]0.0208010804805347[/C][C]0.0416021609610694[/C][C]0.979198919519465[/C][/ROW]
[ROW][C]50[/C][C]0.016079056691729[/C][C]0.0321581133834581[/C][C]0.983920943308271[/C][/ROW]
[ROW][C]51[/C][C]0.0170457983684304[/C][C]0.0340915967368609[/C][C]0.98295420163157[/C][/ROW]
[ROW][C]52[/C][C]0.0126048281591023[/C][C]0.0252096563182045[/C][C]0.987395171840898[/C][/ROW]
[ROW][C]53[/C][C]0.0102848852584952[/C][C]0.0205697705169903[/C][C]0.989715114741505[/C][/ROW]
[ROW][C]54[/C][C]0.00834693816200093[/C][C]0.0166938763240019[/C][C]0.991653061837999[/C][/ROW]
[ROW][C]55[/C][C]0.0470263338984141[/C][C]0.0940526677968281[/C][C]0.952973666101586[/C][/ROW]
[ROW][C]56[/C][C]0.163786557982948[/C][C]0.327573115965896[/C][C]0.836213442017052[/C][/ROW]
[ROW][C]57[/C][C]0.139834396701626[/C][C]0.279668793403252[/C][C]0.860165603298374[/C][/ROW]
[ROW][C]58[/C][C]0.123486769594965[/C][C]0.246973539189931[/C][C]0.876513230405035[/C][/ROW]
[ROW][C]59[/C][C]0.104492079026196[/C][C]0.208984158052391[/C][C]0.895507920973804[/C][/ROW]
[ROW][C]60[/C][C]0.0905462032498783[/C][C]0.181092406499757[/C][C]0.909453796750122[/C][/ROW]
[ROW][C]61[/C][C]0.090289616508789[/C][C]0.180579233017578[/C][C]0.909710383491211[/C][/ROW]
[ROW][C]62[/C][C]0.0752633231551546[/C][C]0.150526646310309[/C][C]0.924736676844845[/C][/ROW]
[ROW][C]63[/C][C]0.0817204175093174[/C][C]0.163440835018635[/C][C]0.918279582490683[/C][/ROW]
[ROW][C]64[/C][C]0.0669635363052935[/C][C]0.133927072610587[/C][C]0.933036463694706[/C][/ROW]
[ROW][C]65[/C][C]0.0642318762998581[/C][C]0.128463752599716[/C][C]0.935768123700142[/C][/ROW]
[ROW][C]66[/C][C]0.0549626613655693[/C][C]0.109925322731139[/C][C]0.945037338634431[/C][/ROW]
[ROW][C]67[/C][C]0.0646884276006512[/C][C]0.129376855201302[/C][C]0.935311572399349[/C][/ROW]
[ROW][C]68[/C][C]0.0580553318162724[/C][C]0.116110663632545[/C][C]0.941944668183728[/C][/ROW]
[ROW][C]69[/C][C]0.0484880039791287[/C][C]0.0969760079582574[/C][C]0.951511996020871[/C][/ROW]
[ROW][C]70[/C][C]0.0396028066403534[/C][C]0.0792056132807069[/C][C]0.960397193359647[/C][/ROW]
[ROW][C]71[/C][C]0.0586459485520019[/C][C]0.117291897104004[/C][C]0.941354051447998[/C][/ROW]
[ROW][C]72[/C][C]0.0482305060216996[/C][C]0.0964610120433993[/C][C]0.9517694939783[/C][/ROW]
[ROW][C]73[/C][C]0.0458383764566766[/C][C]0.0916767529133533[/C][C]0.954161623543323[/C][/ROW]
[ROW][C]74[/C][C]0.0417997196061418[/C][C]0.0835994392122836[/C][C]0.958200280393858[/C][/ROW]
[ROW][C]75[/C][C]0.0394727156702391[/C][C]0.0789454313404782[/C][C]0.960527284329761[/C][/ROW]
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[ROW][C]220[/C][C]0.107283702988238[/C][C]0.214567405976476[/C][C]0.892716297011762[/C][/ROW]
[ROW][C]221[/C][C]0.125715163814718[/C][C]0.251430327629436[/C][C]0.874284836185282[/C][/ROW]
[ROW][C]222[/C][C]0.10394039764661[/C][C]0.207880795293219[/C][C]0.89605960235339[/C][/ROW]
[ROW][C]223[/C][C]0.12372458963661[/C][C]0.247449179273221[/C][C]0.87627541036339[/C][/ROW]
[ROW][C]224[/C][C]0.105846649327006[/C][C]0.211693298654012[/C][C]0.894153350672994[/C][/ROW]
[ROW][C]225[/C][C]0.0938104544937127[/C][C]0.187620908987425[/C][C]0.906189545506287[/C][/ROW]
[ROW][C]226[/C][C]0.115441426465083[/C][C]0.230882852930165[/C][C]0.884558573534917[/C][/ROW]
[ROW][C]227[/C][C]0.0948584722335643[/C][C]0.189716944467129[/C][C]0.905141527766436[/C][/ROW]
[ROW][C]228[/C][C]0.0766421377123406[/C][C]0.153284275424681[/C][C]0.923357862287659[/C][/ROW]
[ROW][C]229[/C][C]0.0599245716373322[/C][C]0.119849143274664[/C][C]0.940075428362668[/C][/ROW]
[ROW][C]230[/C][C]0.0470709568746527[/C][C]0.0941419137493053[/C][C]0.952929043125347[/C][/ROW]
[ROW][C]231[/C][C]0.0528624610604119[/C][C]0.105724922120824[/C][C]0.947137538939588[/C][/ROW]
[ROW][C]232[/C][C]0.0402449569929649[/C][C]0.0804899139859298[/C][C]0.959755043007035[/C][/ROW]
[ROW][C]233[/C][C]0.065333783016406[/C][C]0.130667566032812[/C][C]0.934666216983594[/C][/ROW]
[ROW][C]234[/C][C]0.182930180706027[/C][C]0.365860361412053[/C][C]0.817069819293973[/C][/ROW]
[ROW][C]235[/C][C]0.153646578250553[/C][C]0.307293156501107[/C][C]0.846353421749447[/C][/ROW]
[ROW][C]236[/C][C]0.140310017261115[/C][C]0.28062003452223[/C][C]0.859689982738885[/C][/ROW]
[ROW][C]237[/C][C]0.124893029478122[/C][C]0.249786058956243[/C][C]0.875106970521878[/C][/ROW]
[ROW][C]238[/C][C]0.180514192780871[/C][C]0.361028385561741[/C][C]0.819485807219129[/C][/ROW]
[ROW][C]239[/C][C]0.237779543864678[/C][C]0.475559087729356[/C][C]0.762220456135322[/C][/ROW]
[ROW][C]240[/C][C]0.2010337404151[/C][C]0.402067480830199[/C][C]0.7989662595849[/C][/ROW]
[ROW][C]241[/C][C]0.163637226350696[/C][C]0.327274452701392[/C][C]0.836362773649304[/C][/ROW]
[ROW][C]242[/C][C]0.137605646994768[/C][C]0.275211293989536[/C][C]0.862394353005232[/C][/ROW]
[ROW][C]243[/C][C]0.38811548216796[/C][C]0.776230964335921[/C][C]0.61188451783204[/C][/ROW]
[ROW][C]244[/C][C]0.42790784860947[/C][C]0.85581569721894[/C][C]0.57209215139053[/C][/ROW]
[ROW][C]245[/C][C]0.54718556068653[/C][C]0.905628878626939[/C][C]0.45281443931347[/C][/ROW]
[ROW][C]246[/C][C]0.59437008225676[/C][C]0.81125983548648[/C][C]0.40562991774324[/C][/ROW]
[ROW][C]247[/C][C]0.543570094543675[/C][C]0.91285981091265[/C][C]0.456429905456325[/C][/ROW]
[ROW][C]248[/C][C]0.501541747001789[/C][C]0.996916505996422[/C][C]0.498458252998211[/C][/ROW]
[ROW][C]249[/C][C]0.439784413893976[/C][C]0.879568827787952[/C][C]0.560215586106024[/C][/ROW]
[ROW][C]250[/C][C]0.355726972837954[/C][C]0.711453945675908[/C][C]0.644273027162046[/C][/ROW]
[ROW][C]251[/C][C]0.466202302869442[/C][C]0.932404605738884[/C][C]0.533797697130558[/C][/ROW]
[ROW][C]252[/C][C]0.38023610584609[/C][C]0.760472211692179[/C][C]0.61976389415391[/C][/ROW]
[ROW][C]253[/C][C]0.395106996088635[/C][C]0.790213992177271[/C][C]0.604893003911365[/C][/ROW]
[ROW][C]254[/C][C]0.290409999569124[/C][C]0.580819999138248[/C][C]0.709590000430876[/C][/ROW]
[ROW][C]255[/C][C]0.281661895325704[/C][C]0.563323790651408[/C][C]0.718338104674296[/C][/ROW]
[ROW][C]256[/C][C]0.262324048602256[/C][C]0.524648097204513[/C][C]0.737675951397744[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226562&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226562&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
80.9378156031123090.1243687937753820.0621843968876909
90.881275278587190.237449442825620.11872472141281
100.9320265262807790.1359469474384430.0679734737192214
110.8856738728567980.2286522542864050.114326127143202
120.8442686419233510.3114627161532990.155731358076649
130.7768524441188870.4462951117622260.223147555881113
140.7173613824310910.5652772351378190.282638617568909
150.7457030504749610.5085938990500780.254296949525039
160.6770851934304610.6458296131390770.322914806569539
170.6124662734383010.7750674531233990.387533726561699
180.5333190025599670.9333619948800660.466680997440033
190.4606760457178370.9213520914356740.539323954282163
200.3942083329316150.7884166658632310.605791667068385
210.3237569355449390.6475138710898770.676243064455061
220.2654785872028620.5309571744057240.734521412797138
230.2271539115521990.4543078231043980.772846088447801
240.1994141338097030.3988282676194050.800585866190297
250.1688054444446860.3376108888893720.831194555555314
260.1740699157698310.3481398315396620.825930084230169
270.1597389236078930.3194778472157870.840261076392107
280.1490675143270210.2981350286540420.850932485672979
290.1156501766737230.2313003533474460.884349823326277
300.09983866880476590.1996773376095320.900161331195234
310.07787648654517020.155752973090340.92212351345483
320.1072318893760030.2144637787520060.892768110623997
330.08444760824575590.1688952164915120.915552391754244
340.06473684731674590.1294736946334920.935263152683254
350.05334758755806930.1066951751161390.946652412441931
360.1014289937985740.2028579875971480.898571006201426
370.09748854251004850.1949770850200970.902511457489952
380.07920540891978560.1584108178395710.920794591080214
390.06119545685439640.1223909137087930.938804543145604
400.0483264826925740.0966529653851480.951673517307426
410.03773418354165620.07546836708331240.962265816458344
420.02909270062696110.05818540125392220.970907299373039
430.08378926194175620.1675785238835120.916210738058244
440.06842849731401490.136856994628030.931571502685985
450.05362466175586090.1072493235117220.946375338244139
460.0418296313403280.0836592626806560.958170368659672
470.03330322323226920.06660644646453840.966696776767731
480.02507279271334740.05014558542669480.974927207286653
490.02080108048053470.04160216096106940.979198919519465
500.0160790566917290.03215811338345810.983920943308271
510.01704579836843040.03409159673686090.98295420163157
520.01260482815910230.02520965631820450.987395171840898
530.01028488525849520.02056977051699030.989715114741505
540.008346938162000930.01669387632400190.991653061837999
550.04702633389841410.09405266779682810.952973666101586
560.1637865579829480.3275731159658960.836213442017052
570.1398343967016260.2796687934032520.860165603298374
580.1234867695949650.2469735391899310.876513230405035
590.1044920790261960.2089841580523910.895507920973804
600.09054620324987830.1810924064997570.909453796750122
610.0902896165087890.1805792330175780.909710383491211
620.07526332315515460.1505266463103090.924736676844845
630.08172041750931740.1634408350186350.918279582490683
640.06696353630529350.1339270726105870.933036463694706
650.06423187629985810.1284637525997160.935768123700142
660.05496266136556930.1099253227311390.945037338634431
670.06468842760065120.1293768552013020.935311572399349
680.05805533181627240.1161106636325450.941944668183728
690.04848800397912870.09697600795825740.951511996020871
700.03960280664035340.07920561328070690.960397193359647
710.05864594855200190.1172918971040040.941354051447998
720.04823050602169960.09646101204339930.9517694939783
730.04583837645667660.09167675291335330.954161623543323
740.04179971960614180.08359943921228360.958200280393858
750.03947271567023910.07894543134047820.960527284329761
760.0354745849687190.07094916993743810.964525415031281
770.03133179382572240.06266358765144490.968668206174278
780.02552341246428540.05104682492857070.974476587535715
790.02242630400455280.04485260800910550.977573695995447
800.02354879580872330.04709759161744650.976451204191277
810.01889229180403060.03778458360806120.981107708195969
820.01507023127324910.03014046254649810.984929768726751
830.01235849651408890.02471699302817780.987641503485911
840.009622407655506770.01924481531101350.990377592344493
850.007598144554117180.01519628910823440.992401855445883
860.01055787510587850.02111575021175710.989442124894121
870.008649348733021130.01729869746604230.991350651266979
880.008014193970943190.01602838794188640.991985806029057
890.007156955314528840.01431391062905770.992843044685471
900.007766487010862690.01553297402172540.992233512989137
910.01918488331016880.03836976662033760.980815116689831
920.01553268706211110.03106537412422220.984467312937889
930.01437923065550730.02875846131101450.985620769344493
940.01265609845074390.02531219690148780.987343901549256
950.01155751879561730.02311503759123460.988442481204383
960.01124558060032180.02249116120064360.988754419399678
970.01061301636397080.02122603272794160.989386983636029
980.008581514036054410.01716302807210880.991418485963946
990.007474238576601950.01494847715320390.992525761423398
1000.008416523472204630.01683304694440930.991583476527795
1010.00666210210455850.0133242042091170.993337897895441
1020.009951717191055910.01990343438211180.990048282808944
1030.008093152883720240.01618630576744050.99190684711628
1040.006592752569976150.01318550513995230.993407247430024
1050.005807624742799010.0116152494855980.994192375257201
1060.004682661246552090.009365322493104190.995317338753448
1070.003805076963779910.007610153927559820.99619492303622
1080.002998794558430490.005997589116860970.99700120544157
1090.006573553079295690.01314710615859140.993426446920704
1100.005369136643626840.01073827328725370.994630863356373
1110.007639772115354470.01527954423070890.992360227884646
1120.006567361128971030.01313472225794210.993432638871029
1130.005409907356142950.01081981471228590.994590092643857
1140.004569433193788030.009138866387576070.995430566806212
1150.004364745926054940.008729491852109880.995635254073945
1160.004237967393136920.008475934786273850.995762032606863
1170.006570377533556730.01314075506711350.993429622466443
1180.005216233814732150.01043246762946430.994783766185268
1190.004217111681764430.008434223363528860.995782888318236
1200.003315608738161830.006631217476323670.996684391261838
1210.003991208875778360.007982417751556710.996008791124222
1220.003156724672334650.00631344934466930.996843275327665
1230.003591506529422790.007183013058845570.996408493470577
1240.003867890870407850.007735781740815690.996132109129592
1250.007760071824122170.01552014364824430.992239928175878
1260.006972025395269320.01394405079053860.993027974604731
1270.00570152917765230.01140305835530460.994298470822348
1280.006120940021153240.01224188004230650.993879059978847
1290.004924683155276470.009849366310552940.995075316844724
1300.004079971421613180.008159942843226370.995920028578387
1310.003284649700693070.006569299401386140.996715350299307
1320.004749504201608780.009499008403217560.995250495798391
1330.003874250086967410.007748500173934810.996125749913033
1340.00319706559638120.006394131192762410.996802934403619
1350.002865111998404830.005730223996809670.997134888001595
1360.002248617634009080.004497235268018150.997751382365991
1370.001765557232510940.003531114465021890.998234442767489
1380.001379235837673080.002758471675346160.998620764162327
1390.00168692110744210.00337384221488420.998313078892558
1400.001608050209950730.003216100419901450.998391949790049
1410.001810802427426620.003621604854853230.998189197572573
1420.0018617299525920.003723459905183990.998138270047408
1430.00370855768241610.007417115364832190.996291442317584
1440.003225244364699320.006450488729398640.996774755635301
1450.004004372289023590.008008744578047190.995995627710976
1460.005158501024749880.01031700204949980.99484149897525
1470.004530314244715820.009060628489431630.995469685755284
1480.00417792744977350.0083558548995470.995822072550226
1490.003614009530213530.007228019060427050.996385990469786
1500.007692469858551460.01538493971710290.992307530141449
1510.008071643641624340.01614328728324870.991928356358376
1520.008041244998955320.01608248999791060.991958755001045
1530.02205361557560840.04410723115121680.977946384424392
1540.02256442774046270.04512885548092530.977435572259537
1550.02273985618472970.04547971236945930.97726014381527
1560.05436535164554750.1087307032910950.945634648354452
1570.1012021396327150.2024042792654290.898797860367285
1580.09772241333781940.1954448266756390.902277586662181
1590.08561273408243180.1712254681648640.914387265917568
1600.09532685056778050.1906537011355610.90467314943222
1610.09986875292496140.1997375058499230.900131247075039
1620.08991493990825520.179829879816510.910085060091745
1630.08642219049792530.1728443809958510.913577809502075
1640.1298163714691940.2596327429383880.870183628530806
1650.1135780822568610.2271561645137230.886421917743139
1660.1034092704026350.2068185408052690.896590729597365
1670.08947014021924270.1789402804384850.910529859780757
1680.102949009148110.205898018296220.89705099085189
1690.09191911217993840.1838382243598770.908080887820062
1700.08313190142325820.1662638028465160.916868098576742
1710.1339899906926760.2679799813853530.866010009307324
1720.1213197096685220.2426394193370440.878680290331478
1730.1062591932358630.2125183864717260.893740806764137
1740.1045877330505040.2091754661010070.895412266949496
1750.1180083681004460.2360167362008920.881991631899554
1760.1020564972604140.2041129945208270.897943502739586
1770.0983451638012790.1966903276025580.901654836198721
1780.08496290098499250.1699258019699850.915037099015008
1790.0730503925986750.146100785197350.926949607401325
1800.06705265435030010.13410530870060.9329473456497
1810.06066993206023230.1213398641204650.939330067939768
1820.08731273273335910.1746254654667180.912687267266641
1830.1382868282982490.2765736565964990.861713171701751
1840.1392682197448220.2785364394896440.860731780255178
1850.1527843088024780.3055686176049550.847215691197522
1860.1470819950386770.2941639900773540.852918004961323
1870.1318472372849230.2636944745698460.868152762715077
1880.1449164816551260.2898329633102530.855083518344874
1890.1464125088672950.2928250177345890.853587491132705
1900.2618318189538090.5236636379076180.738168181046191
1910.2453318779775990.4906637559551970.754668122022401
1920.2231674983848020.4463349967696030.776832501615198
1930.5377387981068870.9245224037862260.462261201893113
1940.5001774334243160.9996451331513680.499822566575684
1950.463236739281020.926473478562040.53676326071898
1960.4421724851100280.8843449702200560.557827514889972
1970.4051462061194610.8102924122389220.594853793880539
1980.3887097341848740.7774194683697480.611290265815126
1990.3541960808617890.7083921617235770.645803919138211
2000.3664048205017530.7328096410035060.633595179498247
2010.3910195693232050.7820391386464110.608980430676795
2020.3656261299480840.7312522598961680.634373870051916
2030.3338647705185450.667729541037090.666135229481455
2040.341406310043150.6828126200862990.65859368995685
2050.3313496393664460.6626992787328930.668650360633554
2060.3022367847529120.6044735695058250.697763215247088
2070.2742233070993660.5484466141987320.725776692900634
2080.2661643509027330.5323287018054670.733835649097267
2090.2343253398476390.4686506796952780.765674660152361
2100.2071303658510970.4142607317021940.792869634148903
2110.2137089516054970.4274179032109930.786291048394503
2120.1907942351132070.3815884702264150.809205764886793
2130.1682625473306450.3365250946612890.831737452669355
2140.1522823314761560.3045646629523130.847717668523844
2150.1542899576234340.3085799152468680.845710042376566
2160.1441630398108580.2883260796217170.855836960189142
2170.1348043714588470.2696087429176940.865195628541153
2180.115102141678640.2302042833572790.88489785832136
2190.106401332676020.212802665352040.89359866732398
2200.1072837029882380.2145674059764760.892716297011762
2210.1257151638147180.2514303276294360.874284836185282
2220.103940397646610.2078807952932190.89605960235339
2230.123724589636610.2474491792732210.87627541036339
2240.1058466493270060.2116932986540120.894153350672994
2250.09381045449371270.1876209089874250.906189545506287
2260.1154414264650830.2308828529301650.884558573534917
2270.09485847223356430.1897169444671290.905141527766436
2280.07664213771234060.1532842754246810.923357862287659
2290.05992457163733220.1198491432746640.940075428362668
2300.04707095687465270.09414191374930530.952929043125347
2310.05286246106041190.1057249221208240.947137538939588
2320.04024495699296490.08048991398592980.959755043007035
2330.0653337830164060.1306675660328120.934666216983594
2340.1829301807060270.3658603614120530.817069819293973
2350.1536465782505530.3072931565011070.846353421749447
2360.1403100172611150.280620034522230.859689982738885
2370.1248930294781220.2497860589562430.875106970521878
2380.1805141927808710.3610283855617410.819485807219129
2390.2377795438646780.4755590877293560.762220456135322
2400.20103374041510.4020674808301990.7989662595849
2410.1636372263506960.3272744527013920.836362773649304
2420.1376056469947680.2752112939895360.862394353005232
2430.388115482167960.7762309643359210.61188451783204
2440.427907848609470.855815697218940.57209215139053
2450.547185560686530.9056288786269390.45281443931347
2460.594370082256760.811259835486480.40562991774324
2470.5435700945436750.912859810912650.456429905456325
2480.5015417470017890.9969165059964220.498458252998211
2490.4397844138939760.8795688277879520.560215586106024
2500.3557269728379540.7114539456759080.644273027162046
2510.4662023028694420.9324046057388840.533797697130558
2520.380236105846090.7604722116921790.61976389415391
2530.3951069960886350.7902139921772710.604893003911365
2540.2904099995691240.5808199991382480.709590000430876
2550.2816618953257040.5633237906514080.718338104674296
2560.2623240486022560.5246480972045130.737675951397744






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level320.1285140562249NOK
5% type I error level830.333333333333333NOK
10% type I error level1010.405622489959839NOK

\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 & 32 & 0.1285140562249 & NOK \tabularnewline
5% type I error level & 83 & 0.333333333333333 & NOK \tabularnewline
10% type I error level & 101 & 0.405622489959839 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226562&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]32[/C][C]0.1285140562249[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]83[/C][C]0.333333333333333[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]101[/C][C]0.405622489959839[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226562&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226562&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level320.1285140562249NOK
5% type I error level830.333333333333333NOK
10% type I error level1010.405622489959839NOK


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

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