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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 12 Dec 2014 12:19:01 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/12/t1418386773uo53hd4gog0rjko.htm/, Retrieved Thu, 16 May 2024 20:29:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266592, Retrieved Thu, 16 May 2024 20:29:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [] [2014-12-12 11:22:29] [bb1b6762b7e5624d262776d3f7139d34]
- RMPD    [Multiple Regression] [] [2014-12-12 12:19:01] [c4557137b9b718365486b3b7af9cd43b] [Current]
- RM        [Multiple Regression] [] [2014-12-12 12:22:10] [fa1b8827d7de91b8b87087311d3d9fa1]
- RMPD        [Central Tendency] [] [2014-12-12 12:29:56] [fa1b8827d7de91b8b87087311d3d9fa1]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26	50	4	12.9
57	62	4	12.2
37	54	5	12.8
67	71	4	7.4
43	54	4	6.7
52	65	9	12.6
52	73	8	14.8
43	52	11	13.3
84	84	4	11.1
67	42	4	8.2
49	66	6	11.4
70	65	4	6.4
52	78	8	10.6
58	73	4	12.0
68	75	4	6.3
62	72	11	11.3
43	66	4	11.9
56	70	4	9.3
56	61	6	9.6
74	81	6	10.0
65	71	4	6.4
63	69	8	13.8
58	71	5	10.8
57	72	4	13.8
63	68	9	11.7
53	70	4	10.9
57	68	7	16.1
51	61	10	13.4
64	67	4	9.9
53	76	4	11.5
29	70	7	8.3
54	60	12	11.7
58	72	7	9.0
43	69	5	9.7
51	71	8	10.8
53	62	5	10.3
54	70	4	10.4
56	64	9	12.7
61	58	7	9.3
47	76	4	11.8
39	52	4	5.9
48	59	4	11.4
50	68	4	13.0
35	76	4	10.8
30	65	7	12.3
68	67	4	11.3
49	59	7	11.8
61	69	4	7.9
67	76	4	12.7
47	63	4	12.3
56	75	4	11.6
50	63	8	6.7
43	60	4	10.9
67	73	4	12.1
62	63	4	13.3
57	70	4	10.1
41	75	7	5.7
54	66	12	14.3
45	63	4	8.0
48	63	4	13.3
61	64	4	9.3
56	70	5	12.5
41	75	15	7.6
43	61	5	15.9
53	60	10	9.2
44	62	9	9.1
66	73	8	11.1
58	61	4	13.0
46	66	5	14.5
37	64	4	12.2
51	59	9	12.3
51	64	4	11.4
56	60	10	8.8
66	56	4	14.6
37	78	4	12.6
42	67	7	13.0
38	59	5	12.6
66	66	4	13.2
34	68	4	9.9
53	71	4	7.7
49	66	4	10.5
55	73	4	13.4
49	72	4	10.9
59	71	6	4.3
40	59	10	10.3
58	64	7	11.8
60	66	4	11.2
63	78	4	11.4
56	68	7	8.6
54	73	4	13.2
52	62	8	12.6
34	65	11	5.6
69	68	6	9.9
32	65	14	8.8
48	60	5	7.7
67	71	4	9.0
58	65	8	7.3
57	68	9	11.4
42	64	4	13.6
64	74	4	7.9
58	69	5	10.7
66	76	4	10.3
26	68	5	8.3
61	72	4	9.6
52	67	4	14.2
51	63	7	8.5
55	59	10	13.5
50	73	4	4.9
60	66	5	6.4
56	62	4	9.6
63	69	4	11.6
61	66	4	11.1
52	51	6	4.35
16	56	4	12.7
46	67	8	18.1
56	69	5	17.85
52	57	4	16.6
55	56	17	12.6
50	55	4	17.1
59	63	4	19.1
60	67	8	16.1
52	65	4	13.35
44	47	7	18.4
67	76	4	14.7
52	64	4	10.6
55	68	5	12.6
37	64	7	16.2
54	65	4	13.6
72	71	4	18.9
51	63	7	14.1
48	60	11	14.5
60	68	7	16.15
50	72	4	14.75
63	70	4	14.8
33	61	4	12.45
67	61	4	12.65
46	62	4	17.35
54	71	4	8.6
59	71	6	18.4
61	51	8	16.1
33	56	23	11.6
47	70	4	17.75
69	73	8	15.25
52	76	6	17.65
55	68	4	16.35
41	48	7	17.65
73	52	4	13.6
52	60	4	14.35
50	59	4	14.75
51	57	10	18.25
60	79	6	9.9
56	60	5	16
56	60	5	18.25
29	59	4	16.85
66	62	4	14.6
66	59	5	13.85
73	61	5	18.95
55	71	5	15.6
64	57	5	14.85
40	66	4	11.75
46	63	6	18.45
58	69	4	15.9
43	58	4	17.1
61	59	4	16.1
51	48	9	19.9
50	66	18	10.95
52	73	6	18.45
54	67	5	15.1
66	61	4	15
61	68	11	11.35
80	75	4	15.95
51	62	10	18.1
56	69	6	14.6
56	58	8	15.4
56	60	8	15.4
53	74	6	17.6
47	55	8	13.35
25	62	4	19.1
47	63	4	15.35
46	69	9	7.6
50	58	9	13.4
39	58	5	13.9
51	68	4	19.1
58	72	4	15.25
35	62	15	12.9
58	62	10	16.1
60	65	9	17.35
62	69	7	13.15
63	66	9	12.15
53	72	6	12.6
46	62	4	10.35
67	75	7	15.4
59	58	4	9.6
64	66	7	18.2
38	55	4	13.6
50	47	15	14.85
48	72	4	14.75
48	62	9	14.1
47	64	4	14.9
66	64	4	16.25
47	19	28	19.25
63	50	4	13.6
58	68	4	13.6
44	70	4	15.65
51	79	5	12.75
43	69	4	14.6
55	71	4	9.85
38	48	12	12.65
45	73	4	19.2
50	74	6	16.6
54	66	6	11.2
57	71	5	15.25
60	74	4	11.9
55	78	4	13.2
56	75	4	16.35
49	53	10	12.4
37	60	7	15.85
59	70	4	18.15
46	69	7	11.15
51	65	4	15.65
58	78	4	17.75
64	78	12	7.65
53	59	5	12.35
48	72	8	15.6
51	70	6	19.3
47	63	17	15.2
59	63	4	17.1
62	71	5	15.6
62	74	4	18.4
51	67	5	19.05
64	66	5	18.55
52	62	6	19.1
67	80	4	13.1
50	73	4	12.85
54	67	4	9.5
58	61	6	4.5
56	73	8	11.85
63	74	10	13.6
31	32	4	11.7
65	69	5	12.4
71	69	4	13.35
50	84	4	11.4
57	64	4	14.9
47	58	16	19.9
47	59	7	11.2
57	78	4	14.6
43	57	4	17.6
41	60	14	14.05
63	68	5	16.1
63	68	5	13.35
56	73	5	11.85
51	69	5	11.95
50	67	7	14.75
22	60	19	15.15
41	65	16	13.2
59	66	4	16.85
56	74	4	7.85
66	81	7	7.7
53	72	9	12.6
42	55	5	7.85
52	49	14	10.95
54	74	4	12.35
44	53	16	9.95
62	64	10	14.9
53	65	5	16.65
50	57	6	13.4
36	51	4	13.95
76	80	4	15.7
66	67	4	16.85
62	70	5	10.95
59	74	4	15.35
47	75	4	12.2
55	70	5	15.1
58	69	4	17.75
60	65	4	15.2
44	55	5	14.6
57	71	8	16.65
45	65	15	8.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266592&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266592&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266592&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 time9 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Tot_Sc[t] = + 14.186 + 0.0161818IM_tot[t] -0.0606305EM_tot[t] -0.0764781AM_tot[t] + 0.0170787t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Tot_Sc[t] =  +  14.186 +  0.0161818IM_tot[t] -0.0606305EM_tot[t] -0.0764781AM_tot[t] +  0.0170787t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266592&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Tot_Sc[t] =  +  14.186 +  0.0161818IM_tot[t] -0.0606305EM_tot[t] -0.0764781AM_tot[t] +  0.0170787t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266592&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266592&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Tot_Sc[t] = + 14.186 + 0.0161818IM_tot[t] -0.0606305EM_tot[t] -0.0764781AM_tot[t] + 0.0170787t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)14.1861.859237.633.93246e-131.96623e-13
IM_tot0.01618180.01945280.83180.4062220.203111
EM_tot-0.06063050.0253522-2.3920.01745540.00872771
AM_tot-0.07647810.0576665-1.3260.1858770.0929385
t0.01707870.002331277.3262.68201e-121.341e-12

\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) & 14.186 & 1.85923 & 7.63 & 3.93246e-13 & 1.96623e-13 \tabularnewline
IM_tot & 0.0161818 & 0.0194528 & 0.8318 & 0.406222 & 0.203111 \tabularnewline
EM_tot & -0.0606305 & 0.0253522 & -2.392 & 0.0174554 & 0.00872771 \tabularnewline
AM_tot & -0.0764781 & 0.0576665 & -1.326 & 0.185877 & 0.0929385 \tabularnewline
t & 0.0170787 & 0.00233127 & 7.326 & 2.68201e-12 & 1.341e-12 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266592&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]14.186[/C][C]1.85923[/C][C]7.63[/C][C]3.93246e-13[/C][C]1.96623e-13[/C][/ROW]
[ROW][C]IM_tot[/C][C]0.0161818[/C][C]0.0194528[/C][C]0.8318[/C][C]0.406222[/C][C]0.203111[/C][/ROW]
[ROW][C]EM_tot[/C][C]-0.0606305[/C][C]0.0253522[/C][C]-2.392[/C][C]0.0174554[/C][C]0.00872771[/C][/ROW]
[ROW][C]AM_tot[/C][C]-0.0764781[/C][C]0.0576665[/C][C]-1.326[/C][C]0.185877[/C][C]0.0929385[/C][/ROW]
[ROW][C]t[/C][C]0.0170787[/C][C]0.00233127[/C][C]7.326[/C][C]2.68201e-12[/C][C]1.341e-12[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266592&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266592&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)14.1861.859237.633.93246e-131.96623e-13
IM_tot0.01618180.01945280.83180.4062220.203111
EM_tot-0.06063050.0253522-2.3920.01745540.00872771
AM_tot-0.07647810.0576665-1.3260.1858770.0929385
t0.01707870.002331277.3262.68201e-121.341e-12






Multiple Linear Regression - Regression Statistics
Multiple R0.42279
R-squared0.178751
Adjusted R-squared0.166718
F-TEST (value)14.8551
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value5.37828e-11
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.09852
Sum Squared Residuals2621.02

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.42279 \tabularnewline
R-squared & 0.178751 \tabularnewline
Adjusted R-squared & 0.166718 \tabularnewline
F-TEST (value) & 14.8551 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 273 \tabularnewline
p-value & 5.37828e-11 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.09852 \tabularnewline
Sum Squared Residuals & 2621.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266592&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.42279[/C][/ROW]
[ROW][C]R-squared[/C][C]0.178751[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.166718[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]14.8551[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]273[/C][/ROW]
[ROW][C]p-value[/C][C]5.37828e-11[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.09852[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2621.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266592&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266592&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 R0.42279
R-squared0.178751
Adjusted R-squared0.166718
F-TEST (value)14.8551
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value5.37828e-11
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.09852
Sum Squared Residuals2621.02






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.28631.61366
212.211.07751.12252
312.811.17951.62051
47.410.7278-3.32778
56.711.3872-4.68722
612.610.50062.09939
714.810.10914.69088
813.311.02442.27563
911.110.30010.79993
108.212.5885-4.38854
1111.410.70630.693741
126.411.2767-4.87674
1310.69.908440.691561
141210.63171.36833
156.310.6893-4.38931
1611.310.25581.04416
1711.910.86461.0354
189.310.8495-1.54952
199.611.2593-1.65931
201010.3551-0.355053
216.410.9858-4.58576
2213.810.78583.01418
2310.810.8302-0.0301645
2413.810.84692.95309
2511.710.82120.87879
2610.910.9376-0.0376003
2716.110.91125.18877
2813.411.02622.3738
299.911.3487-1.44873
3011.510.64210.857868
318.310.4052-2.1052
3211.711.05070.649265
33910.7874-1.78736
349.710.8966-1.19656
3510.810.69240.107598
3610.311.517-1.21695
3710.411.1416-0.741647
3812.711.17251.52752
399.311.7872-2.48721
4011.810.71581.08417
415.912.0586-6.15859
4211.411.7969-0.396886
431311.30071.69935
4410.810.590.210039
4512.310.96361.33637
4611.311.7038-0.403792
4711.811.6690.130973
487.911.5034-3.60342
4912.711.19321.50683
5012.311.67480.625188
5111.611.110.49004
526.711.4516-4.7516
5310.911.8432-0.943212
5412.111.46050.639544
5513.312.00291.29707
5610.111.5147-1.41469
575.710.7403-5.04027
5814.311.1313.169
59811.7962-3.79616
6013.311.86181.43822
619.312.0286-2.72859
6212.511.52450.9755
637.610.2309-2.63092
6415.911.8944.00603
659.211.7511-2.55111
669.111.5778-2.47776
6711.111.3604-0.260385
681312.28150.718512
6914.511.72482.77525
7012.211.79390.406063
7112.311.95830.341678
7211.412.0546-0.654639
738.811.9363-3.13628
7414.612.81661.78343
7512.611.03051.5695
761311.5661.43401
7712.612.15630.443656
7813.212.27860.921424
799.911.6566-1.75658
807.711.7992-4.09922
8110.512.0547-1.55472
8213.411.74451.65552
8310.911.7251-0.825096
844.311.8117-7.51167
8510.311.9429-1.64295
8611.812.1776-0.377578
8711.212.3352-1.13519
8811.411.6733-0.273251
898.611.9539-3.35393
9013.211.86491.33507
9112.612.21070.389336
925.611.5251-5.92514
939.912.3091-2.40908
948.811.2975-2.4975
957.712.5649-4.86495
96912.299-3.29902
977.312.2283-4.92833
9811.411.9709-0.570862
9913.612.37011.22987
1007.912.1369-4.2369
10110.712.2836-1.58356
10210.312.0822-1.78216
1038.311.8605-3.56053
1049.612.2779-2.67793
10514.212.45251.74748
1068.512.4665-3.96651
10713.512.56140.938597
1084.912.1076-7.20761
1096.412.6344-6.23445
1109.612.9058-3.3058
11111.612.6117-1.01174
11211.112.7783-1.67834
1134.3513.4063-9.05629
11412.712.69060.00937485
11518.112.22035.87969
11617.8512.50745.34262
11716.613.26383.33623
11812.612.39580.204186
11917.113.38683.71317
12019.113.06456.0355
12116.112.54933.55067
12213.3512.86410.485877
12318.413.61374.78634
12414.712.47412.22593
12510.612.976-2.37599
12612.612.7226-0.122614
12716.212.5383.66201
12813.612.9990.601041
12918.912.94355.95647
13014.112.87641.2236
13114.512.72091.77909
13216.1512.7533.39696
13314.7512.59522.15479
13414.812.94391.85609
13512.4513.0212-0.571215
13612.6513.5885-0.938473
13717.3513.20514.1449
1388.612.806-4.20596
13918.412.7515.64901
14016.113.86012.23991
14111.611.9738-0.373755
14217.7512.82164.92836
14315.2512.70692.54309
14417.6512.425.23004
14516.3513.12363.22641
14617.6513.89733.7527
14713.614.4191-0.819104
14814.3513.61130.738679
14914.7513.65671.09333
15018.2513.35234.89768
1519.912.4871-2.58707
1521613.66792.33211
15318.2513.6854.56504
15416.8513.40223.44776
15514.613.83620.763844
15613.8513.9586-0.108648
15718.9513.96774.98226
15815.613.08722.51276
15914.8514.09880.751218
16011.7513.2583-1.5083
16118.4513.40145.04859
16215.913.40182.49816
16317.113.84313.25687
16416.114.09082.00915
16519.914.23075.66935
16610.9512.4519-1.5019
16718.4512.99475.45534
16815.113.48441.61563
1691514.13590.864112
17011.3513.1123-1.7623
17115.9513.54782.40224
17218.113.42494.6751
17314.613.40441.19562
17415.413.93541.46456
17515.413.83131.56874
17617.613.10394.49608
17713.3514.0229-0.672934
17819.113.56555.53449
17915.3513.8781.47204
1807.613.1327-5.53268
18113.413.8814-0.481424
18213.914.0264-0.126416
18319.113.70785.39215
18415.2513.59571.65432
18512.913.0056-0.105622
18616.113.77732.32273
18717.3513.72133.6287
18813.1513.6812-0.531177
18912.1513.7434-1.59337
19012.613.4643-0.864284
19110.3514.1274-3.77735
19215.413.46661.93338
1939.614.6144-5.01439
19418.213.99794.2021
19513.614.4906-0.890627
19614.8514.34570.504328
19714.7513.65591.09412
19814.113.89690.203124
19914.914.15890.741098
20016.2514.48341.76657
20119.2515.0864.16404
20213.615.3179-1.71787
20313.614.1627-0.562694
20415.6513.8321.81803
20512.7513.3402-0.590165
20614.613.91060.689427
2079.8514.0006-4.15057
20812.6514.5252-1.87524
20919.213.75175.44835
21016.613.63612.96395
21111.214.2029-3.0029
21215.2514.04191.20815
21311.914.0021-2.10206
21413.213.6957-0.495709
21516.3513.91092.43914
21612.414.6897-2.28967
21715.8514.31761.53241
21818.1514.31383.8362
21911.1513.9517-2.80171
22015.6514.52171.12835
22117.7513.86383.8862
2227.6513.3661-5.71615
22312.3514.8926-2.54256
22415.613.81111.78891
22519.314.15095.14906
22615.213.68641.51356
22717.114.89192.20808
22815.614.3961.20398
22918.414.30774.09232
23019.0514.49474.5553
23118.5514.78283.76723
23219.114.77174.32829
23313.114.0931-0.993124
23412.8514.2595-1.40953
2359.514.7051-5.20512
2364.514.9977-10.4977
23711.8514.1019-2.25194
23813.614.0187-0.418705
23911.716.5233-4.82332
24012.414.7708-2.37077
24113.3514.9614-1.61142
24211.413.7292-2.32922
24314.915.0722-0.172181
24419.914.37355.52651
24511.215.0182-3.81824
24614.614.27460.32541
24717.615.33842.26163
24814.0514.3764-0.326408
24916.114.95271.14726
25013.3514.9698-1.61982
25111.8514.5705-2.72048
25211.9514.7492-2.79917
25314.7514.71840.0316302
25415.1513.7891.36096
25513.214.0398-0.839849
25616.8515.20531.64469
2577.8514.6888-6.8388
2587.714.2138-6.51384
25912.614.4133-1.81328
2607.8515.589-7.73899
26110.9515.4434-4.49337
26212.3514.7418-2.39183
2639.9514.9526-5.00259
26414.915.0529-0.152874
26516.6515.24611.40392
26613.415.6232-2.22318
26713.9515.9304-1.98045
26815.714.83650.863487
26916.8515.481.37003
27010.9515.174-4.22395
27115.3514.97640.373558
27212.214.7387-2.53871
27315.115.1119-0.0119165
27417.7515.31462.43535
27515.215.6066-0.406614
27614.615.8946-1.29461
27716.6514.92251.72747
2788.114.5739-6.47386

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 11.2863 & 1.61366 \tabularnewline
2 & 12.2 & 11.0775 & 1.12252 \tabularnewline
3 & 12.8 & 11.1795 & 1.62051 \tabularnewline
4 & 7.4 & 10.7278 & -3.32778 \tabularnewline
5 & 6.7 & 11.3872 & -4.68722 \tabularnewline
6 & 12.6 & 10.5006 & 2.09939 \tabularnewline
7 & 14.8 & 10.1091 & 4.69088 \tabularnewline
8 & 13.3 & 11.0244 & 2.27563 \tabularnewline
9 & 11.1 & 10.3001 & 0.79993 \tabularnewline
10 & 8.2 & 12.5885 & -4.38854 \tabularnewline
11 & 11.4 & 10.7063 & 0.693741 \tabularnewline
12 & 6.4 & 11.2767 & -4.87674 \tabularnewline
13 & 10.6 & 9.90844 & 0.691561 \tabularnewline
14 & 12 & 10.6317 & 1.36833 \tabularnewline
15 & 6.3 & 10.6893 & -4.38931 \tabularnewline
16 & 11.3 & 10.2558 & 1.04416 \tabularnewline
17 & 11.9 & 10.8646 & 1.0354 \tabularnewline
18 & 9.3 & 10.8495 & -1.54952 \tabularnewline
19 & 9.6 & 11.2593 & -1.65931 \tabularnewline
20 & 10 & 10.3551 & -0.355053 \tabularnewline
21 & 6.4 & 10.9858 & -4.58576 \tabularnewline
22 & 13.8 & 10.7858 & 3.01418 \tabularnewline
23 & 10.8 & 10.8302 & -0.0301645 \tabularnewline
24 & 13.8 & 10.8469 & 2.95309 \tabularnewline
25 & 11.7 & 10.8212 & 0.87879 \tabularnewline
26 & 10.9 & 10.9376 & -0.0376003 \tabularnewline
27 & 16.1 & 10.9112 & 5.18877 \tabularnewline
28 & 13.4 & 11.0262 & 2.3738 \tabularnewline
29 & 9.9 & 11.3487 & -1.44873 \tabularnewline
30 & 11.5 & 10.6421 & 0.857868 \tabularnewline
31 & 8.3 & 10.4052 & -2.1052 \tabularnewline
32 & 11.7 & 11.0507 & 0.649265 \tabularnewline
33 & 9 & 10.7874 & -1.78736 \tabularnewline
34 & 9.7 & 10.8966 & -1.19656 \tabularnewline
35 & 10.8 & 10.6924 & 0.107598 \tabularnewline
36 & 10.3 & 11.517 & -1.21695 \tabularnewline
37 & 10.4 & 11.1416 & -0.741647 \tabularnewline
38 & 12.7 & 11.1725 & 1.52752 \tabularnewline
39 & 9.3 & 11.7872 & -2.48721 \tabularnewline
40 & 11.8 & 10.7158 & 1.08417 \tabularnewline
41 & 5.9 & 12.0586 & -6.15859 \tabularnewline
42 & 11.4 & 11.7969 & -0.396886 \tabularnewline
43 & 13 & 11.3007 & 1.69935 \tabularnewline
44 & 10.8 & 10.59 & 0.210039 \tabularnewline
45 & 12.3 & 10.9636 & 1.33637 \tabularnewline
46 & 11.3 & 11.7038 & -0.403792 \tabularnewline
47 & 11.8 & 11.669 & 0.130973 \tabularnewline
48 & 7.9 & 11.5034 & -3.60342 \tabularnewline
49 & 12.7 & 11.1932 & 1.50683 \tabularnewline
50 & 12.3 & 11.6748 & 0.625188 \tabularnewline
51 & 11.6 & 11.11 & 0.49004 \tabularnewline
52 & 6.7 & 11.4516 & -4.7516 \tabularnewline
53 & 10.9 & 11.8432 & -0.943212 \tabularnewline
54 & 12.1 & 11.4605 & 0.639544 \tabularnewline
55 & 13.3 & 12.0029 & 1.29707 \tabularnewline
56 & 10.1 & 11.5147 & -1.41469 \tabularnewline
57 & 5.7 & 10.7403 & -5.04027 \tabularnewline
58 & 14.3 & 11.131 & 3.169 \tabularnewline
59 & 8 & 11.7962 & -3.79616 \tabularnewline
60 & 13.3 & 11.8618 & 1.43822 \tabularnewline
61 & 9.3 & 12.0286 & -2.72859 \tabularnewline
62 & 12.5 & 11.5245 & 0.9755 \tabularnewline
63 & 7.6 & 10.2309 & -2.63092 \tabularnewline
64 & 15.9 & 11.894 & 4.00603 \tabularnewline
65 & 9.2 & 11.7511 & -2.55111 \tabularnewline
66 & 9.1 & 11.5778 & -2.47776 \tabularnewline
67 & 11.1 & 11.3604 & -0.260385 \tabularnewline
68 & 13 & 12.2815 & 0.718512 \tabularnewline
69 & 14.5 & 11.7248 & 2.77525 \tabularnewline
70 & 12.2 & 11.7939 & 0.406063 \tabularnewline
71 & 12.3 & 11.9583 & 0.341678 \tabularnewline
72 & 11.4 & 12.0546 & -0.654639 \tabularnewline
73 & 8.8 & 11.9363 & -3.13628 \tabularnewline
74 & 14.6 & 12.8166 & 1.78343 \tabularnewline
75 & 12.6 & 11.0305 & 1.5695 \tabularnewline
76 & 13 & 11.566 & 1.43401 \tabularnewline
77 & 12.6 & 12.1563 & 0.443656 \tabularnewline
78 & 13.2 & 12.2786 & 0.921424 \tabularnewline
79 & 9.9 & 11.6566 & -1.75658 \tabularnewline
80 & 7.7 & 11.7992 & -4.09922 \tabularnewline
81 & 10.5 & 12.0547 & -1.55472 \tabularnewline
82 & 13.4 & 11.7445 & 1.65552 \tabularnewline
83 & 10.9 & 11.7251 & -0.825096 \tabularnewline
84 & 4.3 & 11.8117 & -7.51167 \tabularnewline
85 & 10.3 & 11.9429 & -1.64295 \tabularnewline
86 & 11.8 & 12.1776 & -0.377578 \tabularnewline
87 & 11.2 & 12.3352 & -1.13519 \tabularnewline
88 & 11.4 & 11.6733 & -0.273251 \tabularnewline
89 & 8.6 & 11.9539 & -3.35393 \tabularnewline
90 & 13.2 & 11.8649 & 1.33507 \tabularnewline
91 & 12.6 & 12.2107 & 0.389336 \tabularnewline
92 & 5.6 & 11.5251 & -5.92514 \tabularnewline
93 & 9.9 & 12.3091 & -2.40908 \tabularnewline
94 & 8.8 & 11.2975 & -2.4975 \tabularnewline
95 & 7.7 & 12.5649 & -4.86495 \tabularnewline
96 & 9 & 12.299 & -3.29902 \tabularnewline
97 & 7.3 & 12.2283 & -4.92833 \tabularnewline
98 & 11.4 & 11.9709 & -0.570862 \tabularnewline
99 & 13.6 & 12.3701 & 1.22987 \tabularnewline
100 & 7.9 & 12.1369 & -4.2369 \tabularnewline
101 & 10.7 & 12.2836 & -1.58356 \tabularnewline
102 & 10.3 & 12.0822 & -1.78216 \tabularnewline
103 & 8.3 & 11.8605 & -3.56053 \tabularnewline
104 & 9.6 & 12.2779 & -2.67793 \tabularnewline
105 & 14.2 & 12.4525 & 1.74748 \tabularnewline
106 & 8.5 & 12.4665 & -3.96651 \tabularnewline
107 & 13.5 & 12.5614 & 0.938597 \tabularnewline
108 & 4.9 & 12.1076 & -7.20761 \tabularnewline
109 & 6.4 & 12.6344 & -6.23445 \tabularnewline
110 & 9.6 & 12.9058 & -3.3058 \tabularnewline
111 & 11.6 & 12.6117 & -1.01174 \tabularnewline
112 & 11.1 & 12.7783 & -1.67834 \tabularnewline
113 & 4.35 & 13.4063 & -9.05629 \tabularnewline
114 & 12.7 & 12.6906 & 0.00937485 \tabularnewline
115 & 18.1 & 12.2203 & 5.87969 \tabularnewline
116 & 17.85 & 12.5074 & 5.34262 \tabularnewline
117 & 16.6 & 13.2638 & 3.33623 \tabularnewline
118 & 12.6 & 12.3958 & 0.204186 \tabularnewline
119 & 17.1 & 13.3868 & 3.71317 \tabularnewline
120 & 19.1 & 13.0645 & 6.0355 \tabularnewline
121 & 16.1 & 12.5493 & 3.55067 \tabularnewline
122 & 13.35 & 12.8641 & 0.485877 \tabularnewline
123 & 18.4 & 13.6137 & 4.78634 \tabularnewline
124 & 14.7 & 12.4741 & 2.22593 \tabularnewline
125 & 10.6 & 12.976 & -2.37599 \tabularnewline
126 & 12.6 & 12.7226 & -0.122614 \tabularnewline
127 & 16.2 & 12.538 & 3.66201 \tabularnewline
128 & 13.6 & 12.999 & 0.601041 \tabularnewline
129 & 18.9 & 12.9435 & 5.95647 \tabularnewline
130 & 14.1 & 12.8764 & 1.2236 \tabularnewline
131 & 14.5 & 12.7209 & 1.77909 \tabularnewline
132 & 16.15 & 12.753 & 3.39696 \tabularnewline
133 & 14.75 & 12.5952 & 2.15479 \tabularnewline
134 & 14.8 & 12.9439 & 1.85609 \tabularnewline
135 & 12.45 & 13.0212 & -0.571215 \tabularnewline
136 & 12.65 & 13.5885 & -0.938473 \tabularnewline
137 & 17.35 & 13.2051 & 4.1449 \tabularnewline
138 & 8.6 & 12.806 & -4.20596 \tabularnewline
139 & 18.4 & 12.751 & 5.64901 \tabularnewline
140 & 16.1 & 13.8601 & 2.23991 \tabularnewline
141 & 11.6 & 11.9738 & -0.373755 \tabularnewline
142 & 17.75 & 12.8216 & 4.92836 \tabularnewline
143 & 15.25 & 12.7069 & 2.54309 \tabularnewline
144 & 17.65 & 12.42 & 5.23004 \tabularnewline
145 & 16.35 & 13.1236 & 3.22641 \tabularnewline
146 & 17.65 & 13.8973 & 3.7527 \tabularnewline
147 & 13.6 & 14.4191 & -0.819104 \tabularnewline
148 & 14.35 & 13.6113 & 0.738679 \tabularnewline
149 & 14.75 & 13.6567 & 1.09333 \tabularnewline
150 & 18.25 & 13.3523 & 4.89768 \tabularnewline
151 & 9.9 & 12.4871 & -2.58707 \tabularnewline
152 & 16 & 13.6679 & 2.33211 \tabularnewline
153 & 18.25 & 13.685 & 4.56504 \tabularnewline
154 & 16.85 & 13.4022 & 3.44776 \tabularnewline
155 & 14.6 & 13.8362 & 0.763844 \tabularnewline
156 & 13.85 & 13.9586 & -0.108648 \tabularnewline
157 & 18.95 & 13.9677 & 4.98226 \tabularnewline
158 & 15.6 & 13.0872 & 2.51276 \tabularnewline
159 & 14.85 & 14.0988 & 0.751218 \tabularnewline
160 & 11.75 & 13.2583 & -1.5083 \tabularnewline
161 & 18.45 & 13.4014 & 5.04859 \tabularnewline
162 & 15.9 & 13.4018 & 2.49816 \tabularnewline
163 & 17.1 & 13.8431 & 3.25687 \tabularnewline
164 & 16.1 & 14.0908 & 2.00915 \tabularnewline
165 & 19.9 & 14.2307 & 5.66935 \tabularnewline
166 & 10.95 & 12.4519 & -1.5019 \tabularnewline
167 & 18.45 & 12.9947 & 5.45534 \tabularnewline
168 & 15.1 & 13.4844 & 1.61563 \tabularnewline
169 & 15 & 14.1359 & 0.864112 \tabularnewline
170 & 11.35 & 13.1123 & -1.7623 \tabularnewline
171 & 15.95 & 13.5478 & 2.40224 \tabularnewline
172 & 18.1 & 13.4249 & 4.6751 \tabularnewline
173 & 14.6 & 13.4044 & 1.19562 \tabularnewline
174 & 15.4 & 13.9354 & 1.46456 \tabularnewline
175 & 15.4 & 13.8313 & 1.56874 \tabularnewline
176 & 17.6 & 13.1039 & 4.49608 \tabularnewline
177 & 13.35 & 14.0229 & -0.672934 \tabularnewline
178 & 19.1 & 13.5655 & 5.53449 \tabularnewline
179 & 15.35 & 13.878 & 1.47204 \tabularnewline
180 & 7.6 & 13.1327 & -5.53268 \tabularnewline
181 & 13.4 & 13.8814 & -0.481424 \tabularnewline
182 & 13.9 & 14.0264 & -0.126416 \tabularnewline
183 & 19.1 & 13.7078 & 5.39215 \tabularnewline
184 & 15.25 & 13.5957 & 1.65432 \tabularnewline
185 & 12.9 & 13.0056 & -0.105622 \tabularnewline
186 & 16.1 & 13.7773 & 2.32273 \tabularnewline
187 & 17.35 & 13.7213 & 3.6287 \tabularnewline
188 & 13.15 & 13.6812 & -0.531177 \tabularnewline
189 & 12.15 & 13.7434 & -1.59337 \tabularnewline
190 & 12.6 & 13.4643 & -0.864284 \tabularnewline
191 & 10.35 & 14.1274 & -3.77735 \tabularnewline
192 & 15.4 & 13.4666 & 1.93338 \tabularnewline
193 & 9.6 & 14.6144 & -5.01439 \tabularnewline
194 & 18.2 & 13.9979 & 4.2021 \tabularnewline
195 & 13.6 & 14.4906 & -0.890627 \tabularnewline
196 & 14.85 & 14.3457 & 0.504328 \tabularnewline
197 & 14.75 & 13.6559 & 1.09412 \tabularnewline
198 & 14.1 & 13.8969 & 0.203124 \tabularnewline
199 & 14.9 & 14.1589 & 0.741098 \tabularnewline
200 & 16.25 & 14.4834 & 1.76657 \tabularnewline
201 & 19.25 & 15.086 & 4.16404 \tabularnewline
202 & 13.6 & 15.3179 & -1.71787 \tabularnewline
203 & 13.6 & 14.1627 & -0.562694 \tabularnewline
204 & 15.65 & 13.832 & 1.81803 \tabularnewline
205 & 12.75 & 13.3402 & -0.590165 \tabularnewline
206 & 14.6 & 13.9106 & 0.689427 \tabularnewline
207 & 9.85 & 14.0006 & -4.15057 \tabularnewline
208 & 12.65 & 14.5252 & -1.87524 \tabularnewline
209 & 19.2 & 13.7517 & 5.44835 \tabularnewline
210 & 16.6 & 13.6361 & 2.96395 \tabularnewline
211 & 11.2 & 14.2029 & -3.0029 \tabularnewline
212 & 15.25 & 14.0419 & 1.20815 \tabularnewline
213 & 11.9 & 14.0021 & -2.10206 \tabularnewline
214 & 13.2 & 13.6957 & -0.495709 \tabularnewline
215 & 16.35 & 13.9109 & 2.43914 \tabularnewline
216 & 12.4 & 14.6897 & -2.28967 \tabularnewline
217 & 15.85 & 14.3176 & 1.53241 \tabularnewline
218 & 18.15 & 14.3138 & 3.8362 \tabularnewline
219 & 11.15 & 13.9517 & -2.80171 \tabularnewline
220 & 15.65 & 14.5217 & 1.12835 \tabularnewline
221 & 17.75 & 13.8638 & 3.8862 \tabularnewline
222 & 7.65 & 13.3661 & -5.71615 \tabularnewline
223 & 12.35 & 14.8926 & -2.54256 \tabularnewline
224 & 15.6 & 13.8111 & 1.78891 \tabularnewline
225 & 19.3 & 14.1509 & 5.14906 \tabularnewline
226 & 15.2 & 13.6864 & 1.51356 \tabularnewline
227 & 17.1 & 14.8919 & 2.20808 \tabularnewline
228 & 15.6 & 14.396 & 1.20398 \tabularnewline
229 & 18.4 & 14.3077 & 4.09232 \tabularnewline
230 & 19.05 & 14.4947 & 4.5553 \tabularnewline
231 & 18.55 & 14.7828 & 3.76723 \tabularnewline
232 & 19.1 & 14.7717 & 4.32829 \tabularnewline
233 & 13.1 & 14.0931 & -0.993124 \tabularnewline
234 & 12.85 & 14.2595 & -1.40953 \tabularnewline
235 & 9.5 & 14.7051 & -5.20512 \tabularnewline
236 & 4.5 & 14.9977 & -10.4977 \tabularnewline
237 & 11.85 & 14.1019 & -2.25194 \tabularnewline
238 & 13.6 & 14.0187 & -0.418705 \tabularnewline
239 & 11.7 & 16.5233 & -4.82332 \tabularnewline
240 & 12.4 & 14.7708 & -2.37077 \tabularnewline
241 & 13.35 & 14.9614 & -1.61142 \tabularnewline
242 & 11.4 & 13.7292 & -2.32922 \tabularnewline
243 & 14.9 & 15.0722 & -0.172181 \tabularnewline
244 & 19.9 & 14.3735 & 5.52651 \tabularnewline
245 & 11.2 & 15.0182 & -3.81824 \tabularnewline
246 & 14.6 & 14.2746 & 0.32541 \tabularnewline
247 & 17.6 & 15.3384 & 2.26163 \tabularnewline
248 & 14.05 & 14.3764 & -0.326408 \tabularnewline
249 & 16.1 & 14.9527 & 1.14726 \tabularnewline
250 & 13.35 & 14.9698 & -1.61982 \tabularnewline
251 & 11.85 & 14.5705 & -2.72048 \tabularnewline
252 & 11.95 & 14.7492 & -2.79917 \tabularnewline
253 & 14.75 & 14.7184 & 0.0316302 \tabularnewline
254 & 15.15 & 13.789 & 1.36096 \tabularnewline
255 & 13.2 & 14.0398 & -0.839849 \tabularnewline
256 & 16.85 & 15.2053 & 1.64469 \tabularnewline
257 & 7.85 & 14.6888 & -6.8388 \tabularnewline
258 & 7.7 & 14.2138 & -6.51384 \tabularnewline
259 & 12.6 & 14.4133 & -1.81328 \tabularnewline
260 & 7.85 & 15.589 & -7.73899 \tabularnewline
261 & 10.95 & 15.4434 & -4.49337 \tabularnewline
262 & 12.35 & 14.7418 & -2.39183 \tabularnewline
263 & 9.95 & 14.9526 & -5.00259 \tabularnewline
264 & 14.9 & 15.0529 & -0.152874 \tabularnewline
265 & 16.65 & 15.2461 & 1.40392 \tabularnewline
266 & 13.4 & 15.6232 & -2.22318 \tabularnewline
267 & 13.95 & 15.9304 & -1.98045 \tabularnewline
268 & 15.7 & 14.8365 & 0.863487 \tabularnewline
269 & 16.85 & 15.48 & 1.37003 \tabularnewline
270 & 10.95 & 15.174 & -4.22395 \tabularnewline
271 & 15.35 & 14.9764 & 0.373558 \tabularnewline
272 & 12.2 & 14.7387 & -2.53871 \tabularnewline
273 & 15.1 & 15.1119 & -0.0119165 \tabularnewline
274 & 17.75 & 15.3146 & 2.43535 \tabularnewline
275 & 15.2 & 15.6066 & -0.406614 \tabularnewline
276 & 14.6 & 15.8946 & -1.29461 \tabularnewline
277 & 16.65 & 14.9225 & 1.72747 \tabularnewline
278 & 8.1 & 14.5739 & -6.47386 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266592&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]11.2863[/C][C]1.61366[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]11.0775[/C][C]1.12252[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.1795[/C][C]1.62051[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]10.7278[/C][C]-3.32778[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]11.3872[/C][C]-4.68722[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]10.5006[/C][C]2.09939[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]10.1091[/C][C]4.69088[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]11.0244[/C][C]2.27563[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]10.3001[/C][C]0.79993[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]12.5885[/C][C]-4.38854[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]10.7063[/C][C]0.693741[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.2767[/C][C]-4.87674[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.90844[/C][C]0.691561[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]10.6317[/C][C]1.36833[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]10.6893[/C][C]-4.38931[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]10.2558[/C][C]1.04416[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]10.8646[/C][C]1.0354[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.8495[/C][C]-1.54952[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.2593[/C][C]-1.65931[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]10.3551[/C][C]-0.355053[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]10.9858[/C][C]-4.58576[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]10.7858[/C][C]3.01418[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]10.8302[/C][C]-0.0301645[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]10.8469[/C][C]2.95309[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]10.8212[/C][C]0.87879[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]10.9376[/C][C]-0.0376003[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]10.9112[/C][C]5.18877[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]11.0262[/C][C]2.3738[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.3487[/C][C]-1.44873[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]10.6421[/C][C]0.857868[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]10.4052[/C][C]-2.1052[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.0507[/C][C]0.649265[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]10.7874[/C][C]-1.78736[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]10.8966[/C][C]-1.19656[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]10.6924[/C][C]0.107598[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]11.517[/C][C]-1.21695[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.1416[/C][C]-0.741647[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]11.1725[/C][C]1.52752[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]11.7872[/C][C]-2.48721[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]10.7158[/C][C]1.08417[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]12.0586[/C][C]-6.15859[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]11.7969[/C][C]-0.396886[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.3007[/C][C]1.69935[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]10.59[/C][C]0.210039[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]10.9636[/C][C]1.33637[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]11.7038[/C][C]-0.403792[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]11.669[/C][C]0.130973[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]11.5034[/C][C]-3.60342[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]11.1932[/C][C]1.50683[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]11.6748[/C][C]0.625188[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]11.11[/C][C]0.49004[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]11.4516[/C][C]-4.7516[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]11.8432[/C][C]-0.943212[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]11.4605[/C][C]0.639544[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]12.0029[/C][C]1.29707[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]11.5147[/C][C]-1.41469[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]10.7403[/C][C]-5.04027[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]11.131[/C][C]3.169[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]11.7962[/C][C]-3.79616[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]11.8618[/C][C]1.43822[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.0286[/C][C]-2.72859[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.5245[/C][C]0.9755[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]10.2309[/C][C]-2.63092[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]11.894[/C][C]4.00603[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.7511[/C][C]-2.55111[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]11.5778[/C][C]-2.47776[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]11.3604[/C][C]-0.260385[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]12.2815[/C][C]0.718512[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.7248[/C][C]2.77525[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.7939[/C][C]0.406063[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]11.9583[/C][C]0.341678[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.0546[/C][C]-0.654639[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.9363[/C][C]-3.13628[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]12.8166[/C][C]1.78343[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.0305[/C][C]1.5695[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]11.566[/C][C]1.43401[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]12.1563[/C][C]0.443656[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]12.2786[/C][C]0.921424[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]11.6566[/C][C]-1.75658[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]11.7992[/C][C]-4.09922[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]12.0547[/C][C]-1.55472[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]11.7445[/C][C]1.65552[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]11.7251[/C][C]-0.825096[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]11.8117[/C][C]-7.51167[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]11.9429[/C][C]-1.64295[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]12.1776[/C][C]-0.377578[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]12.3352[/C][C]-1.13519[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]11.6733[/C][C]-0.273251[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]11.9539[/C][C]-3.35393[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]11.8649[/C][C]1.33507[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]12.2107[/C][C]0.389336[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]11.5251[/C][C]-5.92514[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]12.3091[/C][C]-2.40908[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]11.2975[/C][C]-2.4975[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]12.5649[/C][C]-4.86495[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]12.299[/C][C]-3.29902[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]12.2283[/C][C]-4.92833[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]11.9709[/C][C]-0.570862[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]12.3701[/C][C]1.22987[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]12.1369[/C][C]-4.2369[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]12.2836[/C][C]-1.58356[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]12.0822[/C][C]-1.78216[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]11.8605[/C][C]-3.56053[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]12.2779[/C][C]-2.67793[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]12.4525[/C][C]1.74748[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]12.4665[/C][C]-3.96651[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]12.5614[/C][C]0.938597[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]12.1076[/C][C]-7.20761[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]12.6344[/C][C]-6.23445[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]12.9058[/C][C]-3.3058[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]12.6117[/C][C]-1.01174[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]12.7783[/C][C]-1.67834[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]13.4063[/C][C]-9.05629[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.6906[/C][C]0.00937485[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]12.2203[/C][C]5.87969[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]12.5074[/C][C]5.34262[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]13.2638[/C][C]3.33623[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]12.3958[/C][C]0.204186[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]13.3868[/C][C]3.71317[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]13.0645[/C][C]6.0355[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]12.5493[/C][C]3.55067[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]12.8641[/C][C]0.485877[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]13.6137[/C][C]4.78634[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]12.4741[/C][C]2.22593[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]12.976[/C][C]-2.37599[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]12.7226[/C][C]-0.122614[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]12.538[/C][C]3.66201[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]12.999[/C][C]0.601041[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]12.9435[/C][C]5.95647[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]12.8764[/C][C]1.2236[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]12.7209[/C][C]1.77909[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]12.753[/C][C]3.39696[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]12.5952[/C][C]2.15479[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]12.9439[/C][C]1.85609[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]13.0212[/C][C]-0.571215[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]13.5885[/C][C]-0.938473[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]13.2051[/C][C]4.1449[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]12.806[/C][C]-4.20596[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]12.751[/C][C]5.64901[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]13.8601[/C][C]2.23991[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]11.9738[/C][C]-0.373755[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]12.8216[/C][C]4.92836[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]12.7069[/C][C]2.54309[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]12.42[/C][C]5.23004[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]13.1236[/C][C]3.22641[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]13.8973[/C][C]3.7527[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]14.4191[/C][C]-0.819104[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]13.6113[/C][C]0.738679[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]13.6567[/C][C]1.09333[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]13.3523[/C][C]4.89768[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]12.4871[/C][C]-2.58707[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.6679[/C][C]2.33211[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]13.685[/C][C]4.56504[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]13.4022[/C][C]3.44776[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]13.8362[/C][C]0.763844[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]13.9586[/C][C]-0.108648[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]13.9677[/C][C]4.98226[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]13.0872[/C][C]2.51276[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]14.0988[/C][C]0.751218[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]13.2583[/C][C]-1.5083[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]13.4014[/C][C]5.04859[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]13.4018[/C][C]2.49816[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]13.8431[/C][C]3.25687[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]14.0908[/C][C]2.00915[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]14.2307[/C][C]5.66935[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]12.4519[/C][C]-1.5019[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]12.9947[/C][C]5.45534[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]13.4844[/C][C]1.61563[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]14.1359[/C][C]0.864112[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]13.1123[/C][C]-1.7623[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]13.5478[/C][C]2.40224[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]13.4249[/C][C]4.6751[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]13.4044[/C][C]1.19562[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]13.9354[/C][C]1.46456[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.8313[/C][C]1.56874[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]13.1039[/C][C]4.49608[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]14.0229[/C][C]-0.672934[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]13.5655[/C][C]5.53449[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]13.878[/C][C]1.47204[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]13.1327[/C][C]-5.53268[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]13.8814[/C][C]-0.481424[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]14.0264[/C][C]-0.126416[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]13.7078[/C][C]5.39215[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]13.5957[/C][C]1.65432[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]13.0056[/C][C]-0.105622[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]13.7773[/C][C]2.32273[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]13.7213[/C][C]3.6287[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]13.6812[/C][C]-0.531177[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]13.7434[/C][C]-1.59337[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]13.4643[/C][C]-0.864284[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]14.1274[/C][C]-3.77735[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]13.4666[/C][C]1.93338[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]14.6144[/C][C]-5.01439[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]13.9979[/C][C]4.2021[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]14.4906[/C][C]-0.890627[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]14.3457[/C][C]0.504328[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]13.6559[/C][C]1.09412[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]13.8969[/C][C]0.203124[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]14.1589[/C][C]0.741098[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]14.4834[/C][C]1.76657[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]15.086[/C][C]4.16404[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]15.3179[/C][C]-1.71787[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]14.1627[/C][C]-0.562694[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]13.832[/C][C]1.81803[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]13.3402[/C][C]-0.590165[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]13.9106[/C][C]0.689427[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]14.0006[/C][C]-4.15057[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]14.5252[/C][C]-1.87524[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]13.7517[/C][C]5.44835[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]13.6361[/C][C]2.96395[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]14.2029[/C][C]-3.0029[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]14.0419[/C][C]1.20815[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]14.0021[/C][C]-2.10206[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]13.6957[/C][C]-0.495709[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]13.9109[/C][C]2.43914[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]14.6897[/C][C]-2.28967[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]14.3176[/C][C]1.53241[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]14.3138[/C][C]3.8362[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]13.9517[/C][C]-2.80171[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]14.5217[/C][C]1.12835[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]13.8638[/C][C]3.8862[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]13.3661[/C][C]-5.71615[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]14.8926[/C][C]-2.54256[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]13.8111[/C][C]1.78891[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]14.1509[/C][C]5.14906[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]13.6864[/C][C]1.51356[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]14.8919[/C][C]2.20808[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]14.396[/C][C]1.20398[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]14.3077[/C][C]4.09232[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]14.4947[/C][C]4.5553[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]14.7828[/C][C]3.76723[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]14.7717[/C][C]4.32829[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]14.0931[/C][C]-0.993124[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]14.2595[/C][C]-1.40953[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]14.7051[/C][C]-5.20512[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]14.9977[/C][C]-10.4977[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]14.1019[/C][C]-2.25194[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]14.0187[/C][C]-0.418705[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]16.5233[/C][C]-4.82332[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]14.7708[/C][C]-2.37077[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]14.9614[/C][C]-1.61142[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]13.7292[/C][C]-2.32922[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]15.0722[/C][C]-0.172181[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]14.3735[/C][C]5.52651[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]15.0182[/C][C]-3.81824[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]14.2746[/C][C]0.32541[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]15.3384[/C][C]2.26163[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]14.3764[/C][C]-0.326408[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]14.9527[/C][C]1.14726[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]14.9698[/C][C]-1.61982[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]14.5705[/C][C]-2.72048[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]14.7492[/C][C]-2.79917[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]14.7184[/C][C]0.0316302[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]13.789[/C][C]1.36096[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]14.0398[/C][C]-0.839849[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]15.2053[/C][C]1.64469[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]14.6888[/C][C]-6.8388[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]14.2138[/C][C]-6.51384[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]14.4133[/C][C]-1.81328[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]15.589[/C][C]-7.73899[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]15.4434[/C][C]-4.49337[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]14.7418[/C][C]-2.39183[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]14.9526[/C][C]-5.00259[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]15.0529[/C][C]-0.152874[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]15.2461[/C][C]1.40392[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]15.6232[/C][C]-2.22318[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]15.9304[/C][C]-1.98045[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]14.8365[/C][C]0.863487[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]15.48[/C][C]1.37003[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]15.174[/C][C]-4.22395[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]14.9764[/C][C]0.373558[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]14.7387[/C][C]-2.53871[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]15.1119[/C][C]-0.0119165[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]15.3146[/C][C]2.43535[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]15.6066[/C][C]-0.406614[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]15.8946[/C][C]-1.29461[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]14.9225[/C][C]1.72747[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]14.5739[/C][C]-6.47386[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266592&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266592&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.28631.61366
212.211.07751.12252
312.811.17951.62051
47.410.7278-3.32778
56.711.3872-4.68722
612.610.50062.09939
714.810.10914.69088
813.311.02442.27563
911.110.30010.79993
108.212.5885-4.38854
1111.410.70630.693741
126.411.2767-4.87674
1310.69.908440.691561
141210.63171.36833
156.310.6893-4.38931
1611.310.25581.04416
1711.910.86461.0354
189.310.8495-1.54952
199.611.2593-1.65931
201010.3551-0.355053
216.410.9858-4.58576
2213.810.78583.01418
2310.810.8302-0.0301645
2413.810.84692.95309
2511.710.82120.87879
2610.910.9376-0.0376003
2716.110.91125.18877
2813.411.02622.3738
299.911.3487-1.44873
3011.510.64210.857868
318.310.4052-2.1052
3211.711.05070.649265
33910.7874-1.78736
349.710.8966-1.19656
3510.810.69240.107598
3610.311.517-1.21695
3710.411.1416-0.741647
3812.711.17251.52752
399.311.7872-2.48721
4011.810.71581.08417
415.912.0586-6.15859
4211.411.7969-0.396886
431311.30071.69935
4410.810.590.210039
4512.310.96361.33637
4611.311.7038-0.403792
4711.811.6690.130973
487.911.5034-3.60342
4912.711.19321.50683
5012.311.67480.625188
5111.611.110.49004
526.711.4516-4.7516
5310.911.8432-0.943212
5412.111.46050.639544
5513.312.00291.29707
5610.111.5147-1.41469
575.710.7403-5.04027
5814.311.1313.169
59811.7962-3.79616
6013.311.86181.43822
619.312.0286-2.72859
6212.511.52450.9755
637.610.2309-2.63092
6415.911.8944.00603
659.211.7511-2.55111
669.111.5778-2.47776
6711.111.3604-0.260385
681312.28150.718512
6914.511.72482.77525
7012.211.79390.406063
7112.311.95830.341678
7211.412.0546-0.654639
738.811.9363-3.13628
7414.612.81661.78343
7512.611.03051.5695
761311.5661.43401
7712.612.15630.443656
7813.212.27860.921424
799.911.6566-1.75658
807.711.7992-4.09922
8110.512.0547-1.55472
8213.411.74451.65552
8310.911.7251-0.825096
844.311.8117-7.51167
8510.311.9429-1.64295
8611.812.1776-0.377578
8711.212.3352-1.13519
8811.411.6733-0.273251
898.611.9539-3.35393
9013.211.86491.33507
9112.612.21070.389336
925.611.5251-5.92514
939.912.3091-2.40908
948.811.2975-2.4975
957.712.5649-4.86495
96912.299-3.29902
977.312.2283-4.92833
9811.411.9709-0.570862
9913.612.37011.22987
1007.912.1369-4.2369
10110.712.2836-1.58356
10210.312.0822-1.78216
1038.311.8605-3.56053
1049.612.2779-2.67793
10514.212.45251.74748
1068.512.4665-3.96651
10713.512.56140.938597
1084.912.1076-7.20761
1096.412.6344-6.23445
1109.612.9058-3.3058
11111.612.6117-1.01174
11211.112.7783-1.67834
1134.3513.4063-9.05629
11412.712.69060.00937485
11518.112.22035.87969
11617.8512.50745.34262
11716.613.26383.33623
11812.612.39580.204186
11917.113.38683.71317
12019.113.06456.0355
12116.112.54933.55067
12213.3512.86410.485877
12318.413.61374.78634
12414.712.47412.22593
12510.612.976-2.37599
12612.612.7226-0.122614
12716.212.5383.66201
12813.612.9990.601041
12918.912.94355.95647
13014.112.87641.2236
13114.512.72091.77909
13216.1512.7533.39696
13314.7512.59522.15479
13414.812.94391.85609
13512.4513.0212-0.571215
13612.6513.5885-0.938473
13717.3513.20514.1449
1388.612.806-4.20596
13918.412.7515.64901
14016.113.86012.23991
14111.611.9738-0.373755
14217.7512.82164.92836
14315.2512.70692.54309
14417.6512.425.23004
14516.3513.12363.22641
14617.6513.89733.7527
14713.614.4191-0.819104
14814.3513.61130.738679
14914.7513.65671.09333
15018.2513.35234.89768
1519.912.4871-2.58707
1521613.66792.33211
15318.2513.6854.56504
15416.8513.40223.44776
15514.613.83620.763844
15613.8513.9586-0.108648
15718.9513.96774.98226
15815.613.08722.51276
15914.8514.09880.751218
16011.7513.2583-1.5083
16118.4513.40145.04859
16215.913.40182.49816
16317.113.84313.25687
16416.114.09082.00915
16519.914.23075.66935
16610.9512.4519-1.5019
16718.4512.99475.45534
16815.113.48441.61563
1691514.13590.864112
17011.3513.1123-1.7623
17115.9513.54782.40224
17218.113.42494.6751
17314.613.40441.19562
17415.413.93541.46456
17515.413.83131.56874
17617.613.10394.49608
17713.3514.0229-0.672934
17819.113.56555.53449
17915.3513.8781.47204
1807.613.1327-5.53268
18113.413.8814-0.481424
18213.914.0264-0.126416
18319.113.70785.39215
18415.2513.59571.65432
18512.913.0056-0.105622
18616.113.77732.32273
18717.3513.72133.6287
18813.1513.6812-0.531177
18912.1513.7434-1.59337
19012.613.4643-0.864284
19110.3514.1274-3.77735
19215.413.46661.93338
1939.614.6144-5.01439
19418.213.99794.2021
19513.614.4906-0.890627
19614.8514.34570.504328
19714.7513.65591.09412
19814.113.89690.203124
19914.914.15890.741098
20016.2514.48341.76657
20119.2515.0864.16404
20213.615.3179-1.71787
20313.614.1627-0.562694
20415.6513.8321.81803
20512.7513.3402-0.590165
20614.613.91060.689427
2079.8514.0006-4.15057
20812.6514.5252-1.87524
20919.213.75175.44835
21016.613.63612.96395
21111.214.2029-3.0029
21215.2514.04191.20815
21311.914.0021-2.10206
21413.213.6957-0.495709
21516.3513.91092.43914
21612.414.6897-2.28967
21715.8514.31761.53241
21818.1514.31383.8362
21911.1513.9517-2.80171
22015.6514.52171.12835
22117.7513.86383.8862
2227.6513.3661-5.71615
22312.3514.8926-2.54256
22415.613.81111.78891
22519.314.15095.14906
22615.213.68641.51356
22717.114.89192.20808
22815.614.3961.20398
22918.414.30774.09232
23019.0514.49474.5553
23118.5514.78283.76723
23219.114.77174.32829
23313.114.0931-0.993124
23412.8514.2595-1.40953
2359.514.7051-5.20512
2364.514.9977-10.4977
23711.8514.1019-2.25194
23813.614.0187-0.418705
23911.716.5233-4.82332
24012.414.7708-2.37077
24113.3514.9614-1.61142
24211.413.7292-2.32922
24314.915.0722-0.172181
24419.914.37355.52651
24511.215.0182-3.81824
24614.614.27460.32541
24717.615.33842.26163
24814.0514.3764-0.326408
24916.114.95271.14726
25013.3514.9698-1.61982
25111.8514.5705-2.72048
25211.9514.7492-2.79917
25314.7514.71840.0316302
25415.1513.7891.36096
25513.214.0398-0.839849
25616.8515.20531.64469
2577.8514.6888-6.8388
2587.714.2138-6.51384
25912.614.4133-1.81328
2607.8515.589-7.73899
26110.9515.4434-4.49337
26212.3514.7418-2.39183
2639.9514.9526-5.00259
26414.915.0529-0.152874
26516.6515.24611.40392
26613.415.6232-2.22318
26713.9515.9304-1.98045
26815.714.83650.863487
26916.8515.481.37003
27010.9515.174-4.22395
27115.3514.97640.373558
27212.214.7387-2.53871
27315.115.1119-0.0119165
27417.7515.31462.43535
27515.215.6066-0.406614
27614.615.8946-1.29461
27716.6514.92251.72747
2788.114.5739-6.47386






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.2205670.4411350.779433
90.3902680.7805360.609732
100.3809680.7619370.619032
110.2593150.518630.740685
120.2124210.4248420.787579
130.1512010.3024010.848799
140.1697540.3395070.830246
150.1535080.3070150.846492
160.1034680.2069350.896532
170.09383350.1876670.906166
180.06091370.1218270.939086
190.03884020.07768040.96116
200.02516430.05032860.974836
210.02014350.04028710.979856
220.03557530.07115060.964425
230.02498480.04996960.975015
240.04359580.08719150.956404
250.02914210.05828420.970858
260.01904710.03809410.980953
270.04040390.08080790.959596
280.02807110.05614220.971929
290.01890730.03781450.981093
300.01250540.02501090.987495
310.04776170.09552340.952238
320.03766390.07532770.962336
330.03256720.06513430.967433
340.02424430.04848860.975756
350.01723760.03447510.982762
360.01205770.02411540.987942
370.008381920.01676380.991618
380.006144530.01228910.993855
390.004327670.008655340.995672
400.003165780.006331570.996834
410.005011940.01002390.994988
420.004472210.008944420.995528
430.005114110.01022820.994886
440.003483850.006967710.996516
450.002339340.004678690.997661
460.00203680.00407360.997963
470.001390140.002780270.99861
480.001167310.002334630.998833
490.001249530.002499070.99875
500.001032570.002065150.998967
510.0007091960.001418390.999291
520.001862510.003725010.998137
530.001295810.002591620.998704
540.001104710.002209410.998895
550.001347390.002694790.998653
560.0009267440.001853490.999073
570.004049850.008099710.99595
580.003508320.007016630.996492
590.003337940.006675880.996662
600.003499060.006998110.996501
610.002693190.005386380.997307
620.002182320.004364640.997818
630.004990810.009981620.995009
640.009718370.01943670.990282
650.008718330.01743670.991282
660.007712910.01542580.992287
670.00572350.0114470.994277
680.00520310.01040620.994797
690.0059660.0119320.994034
700.004547360.009094730.995453
710.003410520.006821040.996589
720.002498510.004997020.997501
730.002444750.004889510.997555
740.002840910.005681810.997159
750.002197020.004394030.997803
760.001710250.003420510.99829
770.001260590.002521180.998739
780.001016110.002032220.998984
790.0008290140.001658030.999171
800.001099860.002199710.9989
810.0008253580.001650720.999175
820.0006972580.001394520.999303
830.000499710.0009994210.9995
840.002873320.005746650.997127
850.002288370.004576740.997712
860.001718780.003437560.998281
870.001290830.002581670.998709
880.0009484380.001896880.999052
890.0009606170.001921230.999039
900.0008134750.001626950.999187
910.0006187440.001237490.999381
920.001778970.003557940.998221
930.001485560.002971130.998514
940.00134840.002696810.998652
950.001843730.003687450.998156
960.00177340.003546790.998227
970.002490210.004980420.99751
980.001992710.003985420.998007
990.001849230.003698460.998151
1000.002276290.004552580.997724
1010.001879120.003758250.998121
1020.001587330.003174670.998413
1030.001837230.003674460.998163
1040.00172750.0034550.998272
1050.001870150.003740290.99813
1060.002222070.004444150.997778
1070.002179780.004359560.99782
1080.008537020.0170740.991463
1090.01830060.03660130.981699
1100.01995210.03990420.980048
1110.01907050.03814090.98093
1120.01867620.03735230.981324
1130.08882810.1776560.911172
1140.08657950.1731590.91342
1150.1701710.3403420.829829
1160.2648080.5296160.735192
1170.3137680.6275370.686232
1180.2996660.5993320.700334
1190.3507850.7015690.649215
1200.4805750.9611510.519425
1210.5005130.9989750.499487
1220.4815180.9630360.518482
1230.5394220.9211560.460578
1240.5290370.9419270.470963
1250.5447240.9105530.455276
1260.5273220.9453550.472678
1270.5331580.9336830.466842
1280.5116450.9767110.488355
1290.5928240.8143530.407176
1300.5680660.8638680.431934
1310.5429570.9140870.457043
1320.536960.926080.46304
1330.5142570.9714850.485743
1340.4895150.9790310.510485
1350.475470.950940.52453
1360.4637540.9275080.536246
1370.4715530.9431060.528447
1380.5688590.8622820.431141
1390.6107360.7785290.389264
1400.5873470.8253060.412653
1410.5729910.8540170.427009
1420.5896670.8206670.410333
1430.5637390.8725210.436261
1440.5804130.8391730.419587
1450.5612080.8775840.438792
1460.555120.8897590.44488
1470.5386080.9227840.461392
1480.5091160.9817680.490884
1490.4781890.9563780.521811
1500.4905570.9811130.509443
1510.5336770.9326460.466323
1520.5043160.9913670.495684
1530.5081430.9837140.491857
1540.4887390.9774790.511261
1550.4578090.9156170.542191
1560.4349260.8698520.565074
1570.4477910.8955820.552209
1580.417060.834120.58294
1590.3857560.7715130.614244
1600.3906530.7813060.609347
1610.4014720.8029430.598528
1620.3712530.7425050.628747
1630.3500180.7000360.649982
1640.3193010.6386030.680699
1650.3550550.710110.644945
1660.361970.723940.63803
1670.3811580.7623150.618842
1680.3479580.6959150.652042
1690.3165360.6330710.683464
1700.3256190.6512380.674381
1710.2964870.5929740.703513
1720.3002290.6004590.699771
1730.2702870.5405740.729713
1740.2418580.4837160.758142
1750.2151960.4303910.784804
1760.2139550.427910.786045
1770.1981920.3963840.801808
1780.2297310.4594610.770269
1790.2048330.4096660.795167
1800.3294570.6589140.670543
1810.3071820.6143640.692818
1820.281080.5621610.71892
1830.3110290.6220590.688971
1840.2804280.5608570.719572
1850.2567420.5134840.743258
1860.2321320.4642650.767868
1870.2230310.4460630.776969
1880.205030.4100610.79497
1890.2013830.4027660.798617
1900.1883430.3766860.811657
1910.2257620.4515230.774238
1920.1993530.3987060.800647
1930.2821160.5642320.717884
1940.2797750.5595490.720225
1950.2589160.5178320.741084
1960.2299350.459870.770065
1970.2023250.4046490.797675
1980.178690.3573790.82131
1990.1552570.3105140.844743
2000.1352170.2704350.864783
2010.1657180.3314370.834282
2020.1512710.3025410.848729
2030.1340810.2681610.865919
2040.1152810.2305610.884719
2050.1042340.2084680.895766
2060.08791770.1758350.912082
2070.1200830.2401670.879917
2080.1107660.2215320.889234
2090.1272070.2544140.872793
2100.1153340.2306690.884666
2110.1239630.2479260.876037
2120.104830.209660.89517
2130.1046240.2092470.895376
2140.09232150.1846430.907678
2150.07923210.1584640.920768
2160.07500940.1500190.924991
2170.06291520.125830.937085
2180.0626550.125310.937345
2190.06561220.1312240.934388
2200.05370490.107410.946295
2210.05315490.106310.946845
2220.1077920.2155850.892208
2230.1051470.2102940.894853
2240.08843660.1768730.911563
2250.1119960.2239920.888004
2260.09498710.1899740.905013
2270.08611770.1722350.913882
2280.0719130.1438260.928087
2290.08393810.1678760.916062
2300.1233710.2467410.876629
2310.1588770.3177540.841123
2320.2583040.5166070.741696
2330.2272260.4544520.772774
2340.2004270.4008540.799573
2350.215540.431080.78446
2360.5869850.8260290.413015
2370.5525260.8949480.447474
2380.5027080.9945850.497292
2390.5112490.9775020.488751
2400.4818070.9636140.518193
2410.4440850.8881710.555915
2420.4057560.8115110.594244
2430.3549420.7098850.645058
2440.5642090.8715830.435791
2450.5539460.8921080.446054
2460.5048220.9903560.495178
2470.5324060.9351870.467594
2480.5054890.9890230.494511
2490.5031640.9936720.496836
2500.4478840.8957680.552116
2510.3951140.7902280.604886
2520.3437740.6875480.656226
2530.3188930.6377850.681107
2540.5508020.8983970.449198
2550.7863440.4273110.213656
2560.8513130.2973750.148687
2570.8692620.2614760.130738
2580.9271890.1456210.0728106
2590.9157830.1684340.084217
2600.9702750.05945080.0297254
2610.9556330.08873420.0443671
2620.9345990.1308020.0654011
2630.8992050.2015890.100795
2640.8740320.2519360.125968
2650.9065350.1869310.0934654
2660.8523450.2953110.147655
2670.8768780.2462440.123122
2680.7898220.4203560.210178
2690.8678610.2642790.132139
2700.7922460.4155090.207754

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.220567 & 0.441135 & 0.779433 \tabularnewline
9 & 0.390268 & 0.780536 & 0.609732 \tabularnewline
10 & 0.380968 & 0.761937 & 0.619032 \tabularnewline
11 & 0.259315 & 0.51863 & 0.740685 \tabularnewline
12 & 0.212421 & 0.424842 & 0.787579 \tabularnewline
13 & 0.151201 & 0.302401 & 0.848799 \tabularnewline
14 & 0.169754 & 0.339507 & 0.830246 \tabularnewline
15 & 0.153508 & 0.307015 & 0.846492 \tabularnewline
16 & 0.103468 & 0.206935 & 0.896532 \tabularnewline
17 & 0.0938335 & 0.187667 & 0.906166 \tabularnewline
18 & 0.0609137 & 0.121827 & 0.939086 \tabularnewline
19 & 0.0388402 & 0.0776804 & 0.96116 \tabularnewline
20 & 0.0251643 & 0.0503286 & 0.974836 \tabularnewline
21 & 0.0201435 & 0.0402871 & 0.979856 \tabularnewline
22 & 0.0355753 & 0.0711506 & 0.964425 \tabularnewline
23 & 0.0249848 & 0.0499696 & 0.975015 \tabularnewline
24 & 0.0435958 & 0.0871915 & 0.956404 \tabularnewline
25 & 0.0291421 & 0.0582842 & 0.970858 \tabularnewline
26 & 0.0190471 & 0.0380941 & 0.980953 \tabularnewline
27 & 0.0404039 & 0.0808079 & 0.959596 \tabularnewline
28 & 0.0280711 & 0.0561422 & 0.971929 \tabularnewline
29 & 0.0189073 & 0.0378145 & 0.981093 \tabularnewline
30 & 0.0125054 & 0.0250109 & 0.987495 \tabularnewline
31 & 0.0477617 & 0.0955234 & 0.952238 \tabularnewline
32 & 0.0376639 & 0.0753277 & 0.962336 \tabularnewline
33 & 0.0325672 & 0.0651343 & 0.967433 \tabularnewline
34 & 0.0242443 & 0.0484886 & 0.975756 \tabularnewline
35 & 0.0172376 & 0.0344751 & 0.982762 \tabularnewline
36 & 0.0120577 & 0.0241154 & 0.987942 \tabularnewline
37 & 0.00838192 & 0.0167638 & 0.991618 \tabularnewline
38 & 0.00614453 & 0.0122891 & 0.993855 \tabularnewline
39 & 0.00432767 & 0.00865534 & 0.995672 \tabularnewline
40 & 0.00316578 & 0.00633157 & 0.996834 \tabularnewline
41 & 0.00501194 & 0.0100239 & 0.994988 \tabularnewline
42 & 0.00447221 & 0.00894442 & 0.995528 \tabularnewline
43 & 0.00511411 & 0.0102282 & 0.994886 \tabularnewline
44 & 0.00348385 & 0.00696771 & 0.996516 \tabularnewline
45 & 0.00233934 & 0.00467869 & 0.997661 \tabularnewline
46 & 0.0020368 & 0.0040736 & 0.997963 \tabularnewline
47 & 0.00139014 & 0.00278027 & 0.99861 \tabularnewline
48 & 0.00116731 & 0.00233463 & 0.998833 \tabularnewline
49 & 0.00124953 & 0.00249907 & 0.99875 \tabularnewline
50 & 0.00103257 & 0.00206515 & 0.998967 \tabularnewline
51 & 0.000709196 & 0.00141839 & 0.999291 \tabularnewline
52 & 0.00186251 & 0.00372501 & 0.998137 \tabularnewline
53 & 0.00129581 & 0.00259162 & 0.998704 \tabularnewline
54 & 0.00110471 & 0.00220941 & 0.998895 \tabularnewline
55 & 0.00134739 & 0.00269479 & 0.998653 \tabularnewline
56 & 0.000926744 & 0.00185349 & 0.999073 \tabularnewline
57 & 0.00404985 & 0.00809971 & 0.99595 \tabularnewline
58 & 0.00350832 & 0.00701663 & 0.996492 \tabularnewline
59 & 0.00333794 & 0.00667588 & 0.996662 \tabularnewline
60 & 0.00349906 & 0.00699811 & 0.996501 \tabularnewline
61 & 0.00269319 & 0.00538638 & 0.997307 \tabularnewline
62 & 0.00218232 & 0.00436464 & 0.997818 \tabularnewline
63 & 0.00499081 & 0.00998162 & 0.995009 \tabularnewline
64 & 0.00971837 & 0.0194367 & 0.990282 \tabularnewline
65 & 0.00871833 & 0.0174367 & 0.991282 \tabularnewline
66 & 0.00771291 & 0.0154258 & 0.992287 \tabularnewline
67 & 0.0057235 & 0.011447 & 0.994277 \tabularnewline
68 & 0.0052031 & 0.0104062 & 0.994797 \tabularnewline
69 & 0.005966 & 0.011932 & 0.994034 \tabularnewline
70 & 0.00454736 & 0.00909473 & 0.995453 \tabularnewline
71 & 0.00341052 & 0.00682104 & 0.996589 \tabularnewline
72 & 0.00249851 & 0.00499702 & 0.997501 \tabularnewline
73 & 0.00244475 & 0.00488951 & 0.997555 \tabularnewline
74 & 0.00284091 & 0.00568181 & 0.997159 \tabularnewline
75 & 0.00219702 & 0.00439403 & 0.997803 \tabularnewline
76 & 0.00171025 & 0.00342051 & 0.99829 \tabularnewline
77 & 0.00126059 & 0.00252118 & 0.998739 \tabularnewline
78 & 0.00101611 & 0.00203222 & 0.998984 \tabularnewline
79 & 0.000829014 & 0.00165803 & 0.999171 \tabularnewline
80 & 0.00109986 & 0.00219971 & 0.9989 \tabularnewline
81 & 0.000825358 & 0.00165072 & 0.999175 \tabularnewline
82 & 0.000697258 & 0.00139452 & 0.999303 \tabularnewline
83 & 0.00049971 & 0.000999421 & 0.9995 \tabularnewline
84 & 0.00287332 & 0.00574665 & 0.997127 \tabularnewline
85 & 0.00228837 & 0.00457674 & 0.997712 \tabularnewline
86 & 0.00171878 & 0.00343756 & 0.998281 \tabularnewline
87 & 0.00129083 & 0.00258167 & 0.998709 \tabularnewline
88 & 0.000948438 & 0.00189688 & 0.999052 \tabularnewline
89 & 0.000960617 & 0.00192123 & 0.999039 \tabularnewline
90 & 0.000813475 & 0.00162695 & 0.999187 \tabularnewline
91 & 0.000618744 & 0.00123749 & 0.999381 \tabularnewline
92 & 0.00177897 & 0.00355794 & 0.998221 \tabularnewline
93 & 0.00148556 & 0.00297113 & 0.998514 \tabularnewline
94 & 0.0013484 & 0.00269681 & 0.998652 \tabularnewline
95 & 0.00184373 & 0.00368745 & 0.998156 \tabularnewline
96 & 0.0017734 & 0.00354679 & 0.998227 \tabularnewline
97 & 0.00249021 & 0.00498042 & 0.99751 \tabularnewline
98 & 0.00199271 & 0.00398542 & 0.998007 \tabularnewline
99 & 0.00184923 & 0.00369846 & 0.998151 \tabularnewline
100 & 0.00227629 & 0.00455258 & 0.997724 \tabularnewline
101 & 0.00187912 & 0.00375825 & 0.998121 \tabularnewline
102 & 0.00158733 & 0.00317467 & 0.998413 \tabularnewline
103 & 0.00183723 & 0.00367446 & 0.998163 \tabularnewline
104 & 0.0017275 & 0.003455 & 0.998272 \tabularnewline
105 & 0.00187015 & 0.00374029 & 0.99813 \tabularnewline
106 & 0.00222207 & 0.00444415 & 0.997778 \tabularnewline
107 & 0.00217978 & 0.00435956 & 0.99782 \tabularnewline
108 & 0.00853702 & 0.017074 & 0.991463 \tabularnewline
109 & 0.0183006 & 0.0366013 & 0.981699 \tabularnewline
110 & 0.0199521 & 0.0399042 & 0.980048 \tabularnewline
111 & 0.0190705 & 0.0381409 & 0.98093 \tabularnewline
112 & 0.0186762 & 0.0373523 & 0.981324 \tabularnewline
113 & 0.0888281 & 0.177656 & 0.911172 \tabularnewline
114 & 0.0865795 & 0.173159 & 0.91342 \tabularnewline
115 & 0.170171 & 0.340342 & 0.829829 \tabularnewline
116 & 0.264808 & 0.529616 & 0.735192 \tabularnewline
117 & 0.313768 & 0.627537 & 0.686232 \tabularnewline
118 & 0.299666 & 0.599332 & 0.700334 \tabularnewline
119 & 0.350785 & 0.701569 & 0.649215 \tabularnewline
120 & 0.480575 & 0.961151 & 0.519425 \tabularnewline
121 & 0.500513 & 0.998975 & 0.499487 \tabularnewline
122 & 0.481518 & 0.963036 & 0.518482 \tabularnewline
123 & 0.539422 & 0.921156 & 0.460578 \tabularnewline
124 & 0.529037 & 0.941927 & 0.470963 \tabularnewline
125 & 0.544724 & 0.910553 & 0.455276 \tabularnewline
126 & 0.527322 & 0.945355 & 0.472678 \tabularnewline
127 & 0.533158 & 0.933683 & 0.466842 \tabularnewline
128 & 0.511645 & 0.976711 & 0.488355 \tabularnewline
129 & 0.592824 & 0.814353 & 0.407176 \tabularnewline
130 & 0.568066 & 0.863868 & 0.431934 \tabularnewline
131 & 0.542957 & 0.914087 & 0.457043 \tabularnewline
132 & 0.53696 & 0.92608 & 0.46304 \tabularnewline
133 & 0.514257 & 0.971485 & 0.485743 \tabularnewline
134 & 0.489515 & 0.979031 & 0.510485 \tabularnewline
135 & 0.47547 & 0.95094 & 0.52453 \tabularnewline
136 & 0.463754 & 0.927508 & 0.536246 \tabularnewline
137 & 0.471553 & 0.943106 & 0.528447 \tabularnewline
138 & 0.568859 & 0.862282 & 0.431141 \tabularnewline
139 & 0.610736 & 0.778529 & 0.389264 \tabularnewline
140 & 0.587347 & 0.825306 & 0.412653 \tabularnewline
141 & 0.572991 & 0.854017 & 0.427009 \tabularnewline
142 & 0.589667 & 0.820667 & 0.410333 \tabularnewline
143 & 0.563739 & 0.872521 & 0.436261 \tabularnewline
144 & 0.580413 & 0.839173 & 0.419587 \tabularnewline
145 & 0.561208 & 0.877584 & 0.438792 \tabularnewline
146 & 0.55512 & 0.889759 & 0.44488 \tabularnewline
147 & 0.538608 & 0.922784 & 0.461392 \tabularnewline
148 & 0.509116 & 0.981768 & 0.490884 \tabularnewline
149 & 0.478189 & 0.956378 & 0.521811 \tabularnewline
150 & 0.490557 & 0.981113 & 0.509443 \tabularnewline
151 & 0.533677 & 0.932646 & 0.466323 \tabularnewline
152 & 0.504316 & 0.991367 & 0.495684 \tabularnewline
153 & 0.508143 & 0.983714 & 0.491857 \tabularnewline
154 & 0.488739 & 0.977479 & 0.511261 \tabularnewline
155 & 0.457809 & 0.915617 & 0.542191 \tabularnewline
156 & 0.434926 & 0.869852 & 0.565074 \tabularnewline
157 & 0.447791 & 0.895582 & 0.552209 \tabularnewline
158 & 0.41706 & 0.83412 & 0.58294 \tabularnewline
159 & 0.385756 & 0.771513 & 0.614244 \tabularnewline
160 & 0.390653 & 0.781306 & 0.609347 \tabularnewline
161 & 0.401472 & 0.802943 & 0.598528 \tabularnewline
162 & 0.371253 & 0.742505 & 0.628747 \tabularnewline
163 & 0.350018 & 0.700036 & 0.649982 \tabularnewline
164 & 0.319301 & 0.638603 & 0.680699 \tabularnewline
165 & 0.355055 & 0.71011 & 0.644945 \tabularnewline
166 & 0.36197 & 0.72394 & 0.63803 \tabularnewline
167 & 0.381158 & 0.762315 & 0.618842 \tabularnewline
168 & 0.347958 & 0.695915 & 0.652042 \tabularnewline
169 & 0.316536 & 0.633071 & 0.683464 \tabularnewline
170 & 0.325619 & 0.651238 & 0.674381 \tabularnewline
171 & 0.296487 & 0.592974 & 0.703513 \tabularnewline
172 & 0.300229 & 0.600459 & 0.699771 \tabularnewline
173 & 0.270287 & 0.540574 & 0.729713 \tabularnewline
174 & 0.241858 & 0.483716 & 0.758142 \tabularnewline
175 & 0.215196 & 0.430391 & 0.784804 \tabularnewline
176 & 0.213955 & 0.42791 & 0.786045 \tabularnewline
177 & 0.198192 & 0.396384 & 0.801808 \tabularnewline
178 & 0.229731 & 0.459461 & 0.770269 \tabularnewline
179 & 0.204833 & 0.409666 & 0.795167 \tabularnewline
180 & 0.329457 & 0.658914 & 0.670543 \tabularnewline
181 & 0.307182 & 0.614364 & 0.692818 \tabularnewline
182 & 0.28108 & 0.562161 & 0.71892 \tabularnewline
183 & 0.311029 & 0.622059 & 0.688971 \tabularnewline
184 & 0.280428 & 0.560857 & 0.719572 \tabularnewline
185 & 0.256742 & 0.513484 & 0.743258 \tabularnewline
186 & 0.232132 & 0.464265 & 0.767868 \tabularnewline
187 & 0.223031 & 0.446063 & 0.776969 \tabularnewline
188 & 0.20503 & 0.410061 & 0.79497 \tabularnewline
189 & 0.201383 & 0.402766 & 0.798617 \tabularnewline
190 & 0.188343 & 0.376686 & 0.811657 \tabularnewline
191 & 0.225762 & 0.451523 & 0.774238 \tabularnewline
192 & 0.199353 & 0.398706 & 0.800647 \tabularnewline
193 & 0.282116 & 0.564232 & 0.717884 \tabularnewline
194 & 0.279775 & 0.559549 & 0.720225 \tabularnewline
195 & 0.258916 & 0.517832 & 0.741084 \tabularnewline
196 & 0.229935 & 0.45987 & 0.770065 \tabularnewline
197 & 0.202325 & 0.404649 & 0.797675 \tabularnewline
198 & 0.17869 & 0.357379 & 0.82131 \tabularnewline
199 & 0.155257 & 0.310514 & 0.844743 \tabularnewline
200 & 0.135217 & 0.270435 & 0.864783 \tabularnewline
201 & 0.165718 & 0.331437 & 0.834282 \tabularnewline
202 & 0.151271 & 0.302541 & 0.848729 \tabularnewline
203 & 0.134081 & 0.268161 & 0.865919 \tabularnewline
204 & 0.115281 & 0.230561 & 0.884719 \tabularnewline
205 & 0.104234 & 0.208468 & 0.895766 \tabularnewline
206 & 0.0879177 & 0.175835 & 0.912082 \tabularnewline
207 & 0.120083 & 0.240167 & 0.879917 \tabularnewline
208 & 0.110766 & 0.221532 & 0.889234 \tabularnewline
209 & 0.127207 & 0.254414 & 0.872793 \tabularnewline
210 & 0.115334 & 0.230669 & 0.884666 \tabularnewline
211 & 0.123963 & 0.247926 & 0.876037 \tabularnewline
212 & 0.10483 & 0.20966 & 0.89517 \tabularnewline
213 & 0.104624 & 0.209247 & 0.895376 \tabularnewline
214 & 0.0923215 & 0.184643 & 0.907678 \tabularnewline
215 & 0.0792321 & 0.158464 & 0.920768 \tabularnewline
216 & 0.0750094 & 0.150019 & 0.924991 \tabularnewline
217 & 0.0629152 & 0.12583 & 0.937085 \tabularnewline
218 & 0.062655 & 0.12531 & 0.937345 \tabularnewline
219 & 0.0656122 & 0.131224 & 0.934388 \tabularnewline
220 & 0.0537049 & 0.10741 & 0.946295 \tabularnewline
221 & 0.0531549 & 0.10631 & 0.946845 \tabularnewline
222 & 0.107792 & 0.215585 & 0.892208 \tabularnewline
223 & 0.105147 & 0.210294 & 0.894853 \tabularnewline
224 & 0.0884366 & 0.176873 & 0.911563 \tabularnewline
225 & 0.111996 & 0.223992 & 0.888004 \tabularnewline
226 & 0.0949871 & 0.189974 & 0.905013 \tabularnewline
227 & 0.0861177 & 0.172235 & 0.913882 \tabularnewline
228 & 0.071913 & 0.143826 & 0.928087 \tabularnewline
229 & 0.0839381 & 0.167876 & 0.916062 \tabularnewline
230 & 0.123371 & 0.246741 & 0.876629 \tabularnewline
231 & 0.158877 & 0.317754 & 0.841123 \tabularnewline
232 & 0.258304 & 0.516607 & 0.741696 \tabularnewline
233 & 0.227226 & 0.454452 & 0.772774 \tabularnewline
234 & 0.200427 & 0.400854 & 0.799573 \tabularnewline
235 & 0.21554 & 0.43108 & 0.78446 \tabularnewline
236 & 0.586985 & 0.826029 & 0.413015 \tabularnewline
237 & 0.552526 & 0.894948 & 0.447474 \tabularnewline
238 & 0.502708 & 0.994585 & 0.497292 \tabularnewline
239 & 0.511249 & 0.977502 & 0.488751 \tabularnewline
240 & 0.481807 & 0.963614 & 0.518193 \tabularnewline
241 & 0.444085 & 0.888171 & 0.555915 \tabularnewline
242 & 0.405756 & 0.811511 & 0.594244 \tabularnewline
243 & 0.354942 & 0.709885 & 0.645058 \tabularnewline
244 & 0.564209 & 0.871583 & 0.435791 \tabularnewline
245 & 0.553946 & 0.892108 & 0.446054 \tabularnewline
246 & 0.504822 & 0.990356 & 0.495178 \tabularnewline
247 & 0.532406 & 0.935187 & 0.467594 \tabularnewline
248 & 0.505489 & 0.989023 & 0.494511 \tabularnewline
249 & 0.503164 & 0.993672 & 0.496836 \tabularnewline
250 & 0.447884 & 0.895768 & 0.552116 \tabularnewline
251 & 0.395114 & 0.790228 & 0.604886 \tabularnewline
252 & 0.343774 & 0.687548 & 0.656226 \tabularnewline
253 & 0.318893 & 0.637785 & 0.681107 \tabularnewline
254 & 0.550802 & 0.898397 & 0.449198 \tabularnewline
255 & 0.786344 & 0.427311 & 0.213656 \tabularnewline
256 & 0.851313 & 0.297375 & 0.148687 \tabularnewline
257 & 0.869262 & 0.261476 & 0.130738 \tabularnewline
258 & 0.927189 & 0.145621 & 0.0728106 \tabularnewline
259 & 0.915783 & 0.168434 & 0.084217 \tabularnewline
260 & 0.970275 & 0.0594508 & 0.0297254 \tabularnewline
261 & 0.955633 & 0.0887342 & 0.0443671 \tabularnewline
262 & 0.934599 & 0.130802 & 0.0654011 \tabularnewline
263 & 0.899205 & 0.201589 & 0.100795 \tabularnewline
264 & 0.874032 & 0.251936 & 0.125968 \tabularnewline
265 & 0.906535 & 0.186931 & 0.0934654 \tabularnewline
266 & 0.852345 & 0.295311 & 0.147655 \tabularnewline
267 & 0.876878 & 0.246244 & 0.123122 \tabularnewline
268 & 0.789822 & 0.420356 & 0.210178 \tabularnewline
269 & 0.867861 & 0.264279 & 0.132139 \tabularnewline
270 & 0.792246 & 0.415509 & 0.207754 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266592&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]0.220567[/C][C]0.441135[/C][C]0.779433[/C][/ROW]
[ROW][C]9[/C][C]0.390268[/C][C]0.780536[/C][C]0.609732[/C][/ROW]
[ROW][C]10[/C][C]0.380968[/C][C]0.761937[/C][C]0.619032[/C][/ROW]
[ROW][C]11[/C][C]0.259315[/C][C]0.51863[/C][C]0.740685[/C][/ROW]
[ROW][C]12[/C][C]0.212421[/C][C]0.424842[/C][C]0.787579[/C][/ROW]
[ROW][C]13[/C][C]0.151201[/C][C]0.302401[/C][C]0.848799[/C][/ROW]
[ROW][C]14[/C][C]0.169754[/C][C]0.339507[/C][C]0.830246[/C][/ROW]
[ROW][C]15[/C][C]0.153508[/C][C]0.307015[/C][C]0.846492[/C][/ROW]
[ROW][C]16[/C][C]0.103468[/C][C]0.206935[/C][C]0.896532[/C][/ROW]
[ROW][C]17[/C][C]0.0938335[/C][C]0.187667[/C][C]0.906166[/C][/ROW]
[ROW][C]18[/C][C]0.0609137[/C][C]0.121827[/C][C]0.939086[/C][/ROW]
[ROW][C]19[/C][C]0.0388402[/C][C]0.0776804[/C][C]0.96116[/C][/ROW]
[ROW][C]20[/C][C]0.0251643[/C][C]0.0503286[/C][C]0.974836[/C][/ROW]
[ROW][C]21[/C][C]0.0201435[/C][C]0.0402871[/C][C]0.979856[/C][/ROW]
[ROW][C]22[/C][C]0.0355753[/C][C]0.0711506[/C][C]0.964425[/C][/ROW]
[ROW][C]23[/C][C]0.0249848[/C][C]0.0499696[/C][C]0.975015[/C][/ROW]
[ROW][C]24[/C][C]0.0435958[/C][C]0.0871915[/C][C]0.956404[/C][/ROW]
[ROW][C]25[/C][C]0.0291421[/C][C]0.0582842[/C][C]0.970858[/C][/ROW]
[ROW][C]26[/C][C]0.0190471[/C][C]0.0380941[/C][C]0.980953[/C][/ROW]
[ROW][C]27[/C][C]0.0404039[/C][C]0.0808079[/C][C]0.959596[/C][/ROW]
[ROW][C]28[/C][C]0.0280711[/C][C]0.0561422[/C][C]0.971929[/C][/ROW]
[ROW][C]29[/C][C]0.0189073[/C][C]0.0378145[/C][C]0.981093[/C][/ROW]
[ROW][C]30[/C][C]0.0125054[/C][C]0.0250109[/C][C]0.987495[/C][/ROW]
[ROW][C]31[/C][C]0.0477617[/C][C]0.0955234[/C][C]0.952238[/C][/ROW]
[ROW][C]32[/C][C]0.0376639[/C][C]0.0753277[/C][C]0.962336[/C][/ROW]
[ROW][C]33[/C][C]0.0325672[/C][C]0.0651343[/C][C]0.967433[/C][/ROW]
[ROW][C]34[/C][C]0.0242443[/C][C]0.0484886[/C][C]0.975756[/C][/ROW]
[ROW][C]35[/C][C]0.0172376[/C][C]0.0344751[/C][C]0.982762[/C][/ROW]
[ROW][C]36[/C][C]0.0120577[/C][C]0.0241154[/C][C]0.987942[/C][/ROW]
[ROW][C]37[/C][C]0.00838192[/C][C]0.0167638[/C][C]0.991618[/C][/ROW]
[ROW][C]38[/C][C]0.00614453[/C][C]0.0122891[/C][C]0.993855[/C][/ROW]
[ROW][C]39[/C][C]0.00432767[/C][C]0.00865534[/C][C]0.995672[/C][/ROW]
[ROW][C]40[/C][C]0.00316578[/C][C]0.00633157[/C][C]0.996834[/C][/ROW]
[ROW][C]41[/C][C]0.00501194[/C][C]0.0100239[/C][C]0.994988[/C][/ROW]
[ROW][C]42[/C][C]0.00447221[/C][C]0.00894442[/C][C]0.995528[/C][/ROW]
[ROW][C]43[/C][C]0.00511411[/C][C]0.0102282[/C][C]0.994886[/C][/ROW]
[ROW][C]44[/C][C]0.00348385[/C][C]0.00696771[/C][C]0.996516[/C][/ROW]
[ROW][C]45[/C][C]0.00233934[/C][C]0.00467869[/C][C]0.997661[/C][/ROW]
[ROW][C]46[/C][C]0.0020368[/C][C]0.0040736[/C][C]0.997963[/C][/ROW]
[ROW][C]47[/C][C]0.00139014[/C][C]0.00278027[/C][C]0.99861[/C][/ROW]
[ROW][C]48[/C][C]0.00116731[/C][C]0.00233463[/C][C]0.998833[/C][/ROW]
[ROW][C]49[/C][C]0.00124953[/C][C]0.00249907[/C][C]0.99875[/C][/ROW]
[ROW][C]50[/C][C]0.00103257[/C][C]0.00206515[/C][C]0.998967[/C][/ROW]
[ROW][C]51[/C][C]0.000709196[/C][C]0.00141839[/C][C]0.999291[/C][/ROW]
[ROW][C]52[/C][C]0.00186251[/C][C]0.00372501[/C][C]0.998137[/C][/ROW]
[ROW][C]53[/C][C]0.00129581[/C][C]0.00259162[/C][C]0.998704[/C][/ROW]
[ROW][C]54[/C][C]0.00110471[/C][C]0.00220941[/C][C]0.998895[/C][/ROW]
[ROW][C]55[/C][C]0.00134739[/C][C]0.00269479[/C][C]0.998653[/C][/ROW]
[ROW][C]56[/C][C]0.000926744[/C][C]0.00185349[/C][C]0.999073[/C][/ROW]
[ROW][C]57[/C][C]0.00404985[/C][C]0.00809971[/C][C]0.99595[/C][/ROW]
[ROW][C]58[/C][C]0.00350832[/C][C]0.00701663[/C][C]0.996492[/C][/ROW]
[ROW][C]59[/C][C]0.00333794[/C][C]0.00667588[/C][C]0.996662[/C][/ROW]
[ROW][C]60[/C][C]0.00349906[/C][C]0.00699811[/C][C]0.996501[/C][/ROW]
[ROW][C]61[/C][C]0.00269319[/C][C]0.00538638[/C][C]0.997307[/C][/ROW]
[ROW][C]62[/C][C]0.00218232[/C][C]0.00436464[/C][C]0.997818[/C][/ROW]
[ROW][C]63[/C][C]0.00499081[/C][C]0.00998162[/C][C]0.995009[/C][/ROW]
[ROW][C]64[/C][C]0.00971837[/C][C]0.0194367[/C][C]0.990282[/C][/ROW]
[ROW][C]65[/C][C]0.00871833[/C][C]0.0174367[/C][C]0.991282[/C][/ROW]
[ROW][C]66[/C][C]0.00771291[/C][C]0.0154258[/C][C]0.992287[/C][/ROW]
[ROW][C]67[/C][C]0.0057235[/C][C]0.011447[/C][C]0.994277[/C][/ROW]
[ROW][C]68[/C][C]0.0052031[/C][C]0.0104062[/C][C]0.994797[/C][/ROW]
[ROW][C]69[/C][C]0.005966[/C][C]0.011932[/C][C]0.994034[/C][/ROW]
[ROW][C]70[/C][C]0.00454736[/C][C]0.00909473[/C][C]0.995453[/C][/ROW]
[ROW][C]71[/C][C]0.00341052[/C][C]0.00682104[/C][C]0.996589[/C][/ROW]
[ROW][C]72[/C][C]0.00249851[/C][C]0.00499702[/C][C]0.997501[/C][/ROW]
[ROW][C]73[/C][C]0.00244475[/C][C]0.00488951[/C][C]0.997555[/C][/ROW]
[ROW][C]74[/C][C]0.00284091[/C][C]0.00568181[/C][C]0.997159[/C][/ROW]
[ROW][C]75[/C][C]0.00219702[/C][C]0.00439403[/C][C]0.997803[/C][/ROW]
[ROW][C]76[/C][C]0.00171025[/C][C]0.00342051[/C][C]0.99829[/C][/ROW]
[ROW][C]77[/C][C]0.00126059[/C][C]0.00252118[/C][C]0.998739[/C][/ROW]
[ROW][C]78[/C][C]0.00101611[/C][C]0.00203222[/C][C]0.998984[/C][/ROW]
[ROW][C]79[/C][C]0.000829014[/C][C]0.00165803[/C][C]0.999171[/C][/ROW]
[ROW][C]80[/C][C]0.00109986[/C][C]0.00219971[/C][C]0.9989[/C][/ROW]
[ROW][C]81[/C][C]0.000825358[/C][C]0.00165072[/C][C]0.999175[/C][/ROW]
[ROW][C]82[/C][C]0.000697258[/C][C]0.00139452[/C][C]0.999303[/C][/ROW]
[ROW][C]83[/C][C]0.00049971[/C][C]0.000999421[/C][C]0.9995[/C][/ROW]
[ROW][C]84[/C][C]0.00287332[/C][C]0.00574665[/C][C]0.997127[/C][/ROW]
[ROW][C]85[/C][C]0.00228837[/C][C]0.00457674[/C][C]0.997712[/C][/ROW]
[ROW][C]86[/C][C]0.00171878[/C][C]0.00343756[/C][C]0.998281[/C][/ROW]
[ROW][C]87[/C][C]0.00129083[/C][C]0.00258167[/C][C]0.998709[/C][/ROW]
[ROW][C]88[/C][C]0.000948438[/C][C]0.00189688[/C][C]0.999052[/C][/ROW]
[ROW][C]89[/C][C]0.000960617[/C][C]0.00192123[/C][C]0.999039[/C][/ROW]
[ROW][C]90[/C][C]0.000813475[/C][C]0.00162695[/C][C]0.999187[/C][/ROW]
[ROW][C]91[/C][C]0.000618744[/C][C]0.00123749[/C][C]0.999381[/C][/ROW]
[ROW][C]92[/C][C]0.00177897[/C][C]0.00355794[/C][C]0.998221[/C][/ROW]
[ROW][C]93[/C][C]0.00148556[/C][C]0.00297113[/C][C]0.998514[/C][/ROW]
[ROW][C]94[/C][C]0.0013484[/C][C]0.00269681[/C][C]0.998652[/C][/ROW]
[ROW][C]95[/C][C]0.00184373[/C][C]0.00368745[/C][C]0.998156[/C][/ROW]
[ROW][C]96[/C][C]0.0017734[/C][C]0.00354679[/C][C]0.998227[/C][/ROW]
[ROW][C]97[/C][C]0.00249021[/C][C]0.00498042[/C][C]0.99751[/C][/ROW]
[ROW][C]98[/C][C]0.00199271[/C][C]0.00398542[/C][C]0.998007[/C][/ROW]
[ROW][C]99[/C][C]0.00184923[/C][C]0.00369846[/C][C]0.998151[/C][/ROW]
[ROW][C]100[/C][C]0.00227629[/C][C]0.00455258[/C][C]0.997724[/C][/ROW]
[ROW][C]101[/C][C]0.00187912[/C][C]0.00375825[/C][C]0.998121[/C][/ROW]
[ROW][C]102[/C][C]0.00158733[/C][C]0.00317467[/C][C]0.998413[/C][/ROW]
[ROW][C]103[/C][C]0.00183723[/C][C]0.00367446[/C][C]0.998163[/C][/ROW]
[ROW][C]104[/C][C]0.0017275[/C][C]0.003455[/C][C]0.998272[/C][/ROW]
[ROW][C]105[/C][C]0.00187015[/C][C]0.00374029[/C][C]0.99813[/C][/ROW]
[ROW][C]106[/C][C]0.00222207[/C][C]0.00444415[/C][C]0.997778[/C][/ROW]
[ROW][C]107[/C][C]0.00217978[/C][C]0.00435956[/C][C]0.99782[/C][/ROW]
[ROW][C]108[/C][C]0.00853702[/C][C]0.017074[/C][C]0.991463[/C][/ROW]
[ROW][C]109[/C][C]0.0183006[/C][C]0.0366013[/C][C]0.981699[/C][/ROW]
[ROW][C]110[/C][C]0.0199521[/C][C]0.0399042[/C][C]0.980048[/C][/ROW]
[ROW][C]111[/C][C]0.0190705[/C][C]0.0381409[/C][C]0.98093[/C][/ROW]
[ROW][C]112[/C][C]0.0186762[/C][C]0.0373523[/C][C]0.981324[/C][/ROW]
[ROW][C]113[/C][C]0.0888281[/C][C]0.177656[/C][C]0.911172[/C][/ROW]
[ROW][C]114[/C][C]0.0865795[/C][C]0.173159[/C][C]0.91342[/C][/ROW]
[ROW][C]115[/C][C]0.170171[/C][C]0.340342[/C][C]0.829829[/C][/ROW]
[ROW][C]116[/C][C]0.264808[/C][C]0.529616[/C][C]0.735192[/C][/ROW]
[ROW][C]117[/C][C]0.313768[/C][C]0.627537[/C][C]0.686232[/C][/ROW]
[ROW][C]118[/C][C]0.299666[/C][C]0.599332[/C][C]0.700334[/C][/ROW]
[ROW][C]119[/C][C]0.350785[/C][C]0.701569[/C][C]0.649215[/C][/ROW]
[ROW][C]120[/C][C]0.480575[/C][C]0.961151[/C][C]0.519425[/C][/ROW]
[ROW][C]121[/C][C]0.500513[/C][C]0.998975[/C][C]0.499487[/C][/ROW]
[ROW][C]122[/C][C]0.481518[/C][C]0.963036[/C][C]0.518482[/C][/ROW]
[ROW][C]123[/C][C]0.539422[/C][C]0.921156[/C][C]0.460578[/C][/ROW]
[ROW][C]124[/C][C]0.529037[/C][C]0.941927[/C][C]0.470963[/C][/ROW]
[ROW][C]125[/C][C]0.544724[/C][C]0.910553[/C][C]0.455276[/C][/ROW]
[ROW][C]126[/C][C]0.527322[/C][C]0.945355[/C][C]0.472678[/C][/ROW]
[ROW][C]127[/C][C]0.533158[/C][C]0.933683[/C][C]0.466842[/C][/ROW]
[ROW][C]128[/C][C]0.511645[/C][C]0.976711[/C][C]0.488355[/C][/ROW]
[ROW][C]129[/C][C]0.592824[/C][C]0.814353[/C][C]0.407176[/C][/ROW]
[ROW][C]130[/C][C]0.568066[/C][C]0.863868[/C][C]0.431934[/C][/ROW]
[ROW][C]131[/C][C]0.542957[/C][C]0.914087[/C][C]0.457043[/C][/ROW]
[ROW][C]132[/C][C]0.53696[/C][C]0.92608[/C][C]0.46304[/C][/ROW]
[ROW][C]133[/C][C]0.514257[/C][C]0.971485[/C][C]0.485743[/C][/ROW]
[ROW][C]134[/C][C]0.489515[/C][C]0.979031[/C][C]0.510485[/C][/ROW]
[ROW][C]135[/C][C]0.47547[/C][C]0.95094[/C][C]0.52453[/C][/ROW]
[ROW][C]136[/C][C]0.463754[/C][C]0.927508[/C][C]0.536246[/C][/ROW]
[ROW][C]137[/C][C]0.471553[/C][C]0.943106[/C][C]0.528447[/C][/ROW]
[ROW][C]138[/C][C]0.568859[/C][C]0.862282[/C][C]0.431141[/C][/ROW]
[ROW][C]139[/C][C]0.610736[/C][C]0.778529[/C][C]0.389264[/C][/ROW]
[ROW][C]140[/C][C]0.587347[/C][C]0.825306[/C][C]0.412653[/C][/ROW]
[ROW][C]141[/C][C]0.572991[/C][C]0.854017[/C][C]0.427009[/C][/ROW]
[ROW][C]142[/C][C]0.589667[/C][C]0.820667[/C][C]0.410333[/C][/ROW]
[ROW][C]143[/C][C]0.563739[/C][C]0.872521[/C][C]0.436261[/C][/ROW]
[ROW][C]144[/C][C]0.580413[/C][C]0.839173[/C][C]0.419587[/C][/ROW]
[ROW][C]145[/C][C]0.561208[/C][C]0.877584[/C][C]0.438792[/C][/ROW]
[ROW][C]146[/C][C]0.55512[/C][C]0.889759[/C][C]0.44488[/C][/ROW]
[ROW][C]147[/C][C]0.538608[/C][C]0.922784[/C][C]0.461392[/C][/ROW]
[ROW][C]148[/C][C]0.509116[/C][C]0.981768[/C][C]0.490884[/C][/ROW]
[ROW][C]149[/C][C]0.478189[/C][C]0.956378[/C][C]0.521811[/C][/ROW]
[ROW][C]150[/C][C]0.490557[/C][C]0.981113[/C][C]0.509443[/C][/ROW]
[ROW][C]151[/C][C]0.533677[/C][C]0.932646[/C][C]0.466323[/C][/ROW]
[ROW][C]152[/C][C]0.504316[/C][C]0.991367[/C][C]0.495684[/C][/ROW]
[ROW][C]153[/C][C]0.508143[/C][C]0.983714[/C][C]0.491857[/C][/ROW]
[ROW][C]154[/C][C]0.488739[/C][C]0.977479[/C][C]0.511261[/C][/ROW]
[ROW][C]155[/C][C]0.457809[/C][C]0.915617[/C][C]0.542191[/C][/ROW]
[ROW][C]156[/C][C]0.434926[/C][C]0.869852[/C][C]0.565074[/C][/ROW]
[ROW][C]157[/C][C]0.447791[/C][C]0.895582[/C][C]0.552209[/C][/ROW]
[ROW][C]158[/C][C]0.41706[/C][C]0.83412[/C][C]0.58294[/C][/ROW]
[ROW][C]159[/C][C]0.385756[/C][C]0.771513[/C][C]0.614244[/C][/ROW]
[ROW][C]160[/C][C]0.390653[/C][C]0.781306[/C][C]0.609347[/C][/ROW]
[ROW][C]161[/C][C]0.401472[/C][C]0.802943[/C][C]0.598528[/C][/ROW]
[ROW][C]162[/C][C]0.371253[/C][C]0.742505[/C][C]0.628747[/C][/ROW]
[ROW][C]163[/C][C]0.350018[/C][C]0.700036[/C][C]0.649982[/C][/ROW]
[ROW][C]164[/C][C]0.319301[/C][C]0.638603[/C][C]0.680699[/C][/ROW]
[ROW][C]165[/C][C]0.355055[/C][C]0.71011[/C][C]0.644945[/C][/ROW]
[ROW][C]166[/C][C]0.36197[/C][C]0.72394[/C][C]0.63803[/C][/ROW]
[ROW][C]167[/C][C]0.381158[/C][C]0.762315[/C][C]0.618842[/C][/ROW]
[ROW][C]168[/C][C]0.347958[/C][C]0.695915[/C][C]0.652042[/C][/ROW]
[ROW][C]169[/C][C]0.316536[/C][C]0.633071[/C][C]0.683464[/C][/ROW]
[ROW][C]170[/C][C]0.325619[/C][C]0.651238[/C][C]0.674381[/C][/ROW]
[ROW][C]171[/C][C]0.296487[/C][C]0.592974[/C][C]0.703513[/C][/ROW]
[ROW][C]172[/C][C]0.300229[/C][C]0.600459[/C][C]0.699771[/C][/ROW]
[ROW][C]173[/C][C]0.270287[/C][C]0.540574[/C][C]0.729713[/C][/ROW]
[ROW][C]174[/C][C]0.241858[/C][C]0.483716[/C][C]0.758142[/C][/ROW]
[ROW][C]175[/C][C]0.215196[/C][C]0.430391[/C][C]0.784804[/C][/ROW]
[ROW][C]176[/C][C]0.213955[/C][C]0.42791[/C][C]0.786045[/C][/ROW]
[ROW][C]177[/C][C]0.198192[/C][C]0.396384[/C][C]0.801808[/C][/ROW]
[ROW][C]178[/C][C]0.229731[/C][C]0.459461[/C][C]0.770269[/C][/ROW]
[ROW][C]179[/C][C]0.204833[/C][C]0.409666[/C][C]0.795167[/C][/ROW]
[ROW][C]180[/C][C]0.329457[/C][C]0.658914[/C][C]0.670543[/C][/ROW]
[ROW][C]181[/C][C]0.307182[/C][C]0.614364[/C][C]0.692818[/C][/ROW]
[ROW][C]182[/C][C]0.28108[/C][C]0.562161[/C][C]0.71892[/C][/ROW]
[ROW][C]183[/C][C]0.311029[/C][C]0.622059[/C][C]0.688971[/C][/ROW]
[ROW][C]184[/C][C]0.280428[/C][C]0.560857[/C][C]0.719572[/C][/ROW]
[ROW][C]185[/C][C]0.256742[/C][C]0.513484[/C][C]0.743258[/C][/ROW]
[ROW][C]186[/C][C]0.232132[/C][C]0.464265[/C][C]0.767868[/C][/ROW]
[ROW][C]187[/C][C]0.223031[/C][C]0.446063[/C][C]0.776969[/C][/ROW]
[ROW][C]188[/C][C]0.20503[/C][C]0.410061[/C][C]0.79497[/C][/ROW]
[ROW][C]189[/C][C]0.201383[/C][C]0.402766[/C][C]0.798617[/C][/ROW]
[ROW][C]190[/C][C]0.188343[/C][C]0.376686[/C][C]0.811657[/C][/ROW]
[ROW][C]191[/C][C]0.225762[/C][C]0.451523[/C][C]0.774238[/C][/ROW]
[ROW][C]192[/C][C]0.199353[/C][C]0.398706[/C][C]0.800647[/C][/ROW]
[ROW][C]193[/C][C]0.282116[/C][C]0.564232[/C][C]0.717884[/C][/ROW]
[ROW][C]194[/C][C]0.279775[/C][C]0.559549[/C][C]0.720225[/C][/ROW]
[ROW][C]195[/C][C]0.258916[/C][C]0.517832[/C][C]0.741084[/C][/ROW]
[ROW][C]196[/C][C]0.229935[/C][C]0.45987[/C][C]0.770065[/C][/ROW]
[ROW][C]197[/C][C]0.202325[/C][C]0.404649[/C][C]0.797675[/C][/ROW]
[ROW][C]198[/C][C]0.17869[/C][C]0.357379[/C][C]0.82131[/C][/ROW]
[ROW][C]199[/C][C]0.155257[/C][C]0.310514[/C][C]0.844743[/C][/ROW]
[ROW][C]200[/C][C]0.135217[/C][C]0.270435[/C][C]0.864783[/C][/ROW]
[ROW][C]201[/C][C]0.165718[/C][C]0.331437[/C][C]0.834282[/C][/ROW]
[ROW][C]202[/C][C]0.151271[/C][C]0.302541[/C][C]0.848729[/C][/ROW]
[ROW][C]203[/C][C]0.134081[/C][C]0.268161[/C][C]0.865919[/C][/ROW]
[ROW][C]204[/C][C]0.115281[/C][C]0.230561[/C][C]0.884719[/C][/ROW]
[ROW][C]205[/C][C]0.104234[/C][C]0.208468[/C][C]0.895766[/C][/ROW]
[ROW][C]206[/C][C]0.0879177[/C][C]0.175835[/C][C]0.912082[/C][/ROW]
[ROW][C]207[/C][C]0.120083[/C][C]0.240167[/C][C]0.879917[/C][/ROW]
[ROW][C]208[/C][C]0.110766[/C][C]0.221532[/C][C]0.889234[/C][/ROW]
[ROW][C]209[/C][C]0.127207[/C][C]0.254414[/C][C]0.872793[/C][/ROW]
[ROW][C]210[/C][C]0.115334[/C][C]0.230669[/C][C]0.884666[/C][/ROW]
[ROW][C]211[/C][C]0.123963[/C][C]0.247926[/C][C]0.876037[/C][/ROW]
[ROW][C]212[/C][C]0.10483[/C][C]0.20966[/C][C]0.89517[/C][/ROW]
[ROW][C]213[/C][C]0.104624[/C][C]0.209247[/C][C]0.895376[/C][/ROW]
[ROW][C]214[/C][C]0.0923215[/C][C]0.184643[/C][C]0.907678[/C][/ROW]
[ROW][C]215[/C][C]0.0792321[/C][C]0.158464[/C][C]0.920768[/C][/ROW]
[ROW][C]216[/C][C]0.0750094[/C][C]0.150019[/C][C]0.924991[/C][/ROW]
[ROW][C]217[/C][C]0.0629152[/C][C]0.12583[/C][C]0.937085[/C][/ROW]
[ROW][C]218[/C][C]0.062655[/C][C]0.12531[/C][C]0.937345[/C][/ROW]
[ROW][C]219[/C][C]0.0656122[/C][C]0.131224[/C][C]0.934388[/C][/ROW]
[ROW][C]220[/C][C]0.0537049[/C][C]0.10741[/C][C]0.946295[/C][/ROW]
[ROW][C]221[/C][C]0.0531549[/C][C]0.10631[/C][C]0.946845[/C][/ROW]
[ROW][C]222[/C][C]0.107792[/C][C]0.215585[/C][C]0.892208[/C][/ROW]
[ROW][C]223[/C][C]0.105147[/C][C]0.210294[/C][C]0.894853[/C][/ROW]
[ROW][C]224[/C][C]0.0884366[/C][C]0.176873[/C][C]0.911563[/C][/ROW]
[ROW][C]225[/C][C]0.111996[/C][C]0.223992[/C][C]0.888004[/C][/ROW]
[ROW][C]226[/C][C]0.0949871[/C][C]0.189974[/C][C]0.905013[/C][/ROW]
[ROW][C]227[/C][C]0.0861177[/C][C]0.172235[/C][C]0.913882[/C][/ROW]
[ROW][C]228[/C][C]0.071913[/C][C]0.143826[/C][C]0.928087[/C][/ROW]
[ROW][C]229[/C][C]0.0839381[/C][C]0.167876[/C][C]0.916062[/C][/ROW]
[ROW][C]230[/C][C]0.123371[/C][C]0.246741[/C][C]0.876629[/C][/ROW]
[ROW][C]231[/C][C]0.158877[/C][C]0.317754[/C][C]0.841123[/C][/ROW]
[ROW][C]232[/C][C]0.258304[/C][C]0.516607[/C][C]0.741696[/C][/ROW]
[ROW][C]233[/C][C]0.227226[/C][C]0.454452[/C][C]0.772774[/C][/ROW]
[ROW][C]234[/C][C]0.200427[/C][C]0.400854[/C][C]0.799573[/C][/ROW]
[ROW][C]235[/C][C]0.21554[/C][C]0.43108[/C][C]0.78446[/C][/ROW]
[ROW][C]236[/C][C]0.586985[/C][C]0.826029[/C][C]0.413015[/C][/ROW]
[ROW][C]237[/C][C]0.552526[/C][C]0.894948[/C][C]0.447474[/C][/ROW]
[ROW][C]238[/C][C]0.502708[/C][C]0.994585[/C][C]0.497292[/C][/ROW]
[ROW][C]239[/C][C]0.511249[/C][C]0.977502[/C][C]0.488751[/C][/ROW]
[ROW][C]240[/C][C]0.481807[/C][C]0.963614[/C][C]0.518193[/C][/ROW]
[ROW][C]241[/C][C]0.444085[/C][C]0.888171[/C][C]0.555915[/C][/ROW]
[ROW][C]242[/C][C]0.405756[/C][C]0.811511[/C][C]0.594244[/C][/ROW]
[ROW][C]243[/C][C]0.354942[/C][C]0.709885[/C][C]0.645058[/C][/ROW]
[ROW][C]244[/C][C]0.564209[/C][C]0.871583[/C][C]0.435791[/C][/ROW]
[ROW][C]245[/C][C]0.553946[/C][C]0.892108[/C][C]0.446054[/C][/ROW]
[ROW][C]246[/C][C]0.504822[/C][C]0.990356[/C][C]0.495178[/C][/ROW]
[ROW][C]247[/C][C]0.532406[/C][C]0.935187[/C][C]0.467594[/C][/ROW]
[ROW][C]248[/C][C]0.505489[/C][C]0.989023[/C][C]0.494511[/C][/ROW]
[ROW][C]249[/C][C]0.503164[/C][C]0.993672[/C][C]0.496836[/C][/ROW]
[ROW][C]250[/C][C]0.447884[/C][C]0.895768[/C][C]0.552116[/C][/ROW]
[ROW][C]251[/C][C]0.395114[/C][C]0.790228[/C][C]0.604886[/C][/ROW]
[ROW][C]252[/C][C]0.343774[/C][C]0.687548[/C][C]0.656226[/C][/ROW]
[ROW][C]253[/C][C]0.318893[/C][C]0.637785[/C][C]0.681107[/C][/ROW]
[ROW][C]254[/C][C]0.550802[/C][C]0.898397[/C][C]0.449198[/C][/ROW]
[ROW][C]255[/C][C]0.786344[/C][C]0.427311[/C][C]0.213656[/C][/ROW]
[ROW][C]256[/C][C]0.851313[/C][C]0.297375[/C][C]0.148687[/C][/ROW]
[ROW][C]257[/C][C]0.869262[/C][C]0.261476[/C][C]0.130738[/C][/ROW]
[ROW][C]258[/C][C]0.927189[/C][C]0.145621[/C][C]0.0728106[/C][/ROW]
[ROW][C]259[/C][C]0.915783[/C][C]0.168434[/C][C]0.084217[/C][/ROW]
[ROW][C]260[/C][C]0.970275[/C][C]0.0594508[/C][C]0.0297254[/C][/ROW]
[ROW][C]261[/C][C]0.955633[/C][C]0.0887342[/C][C]0.0443671[/C][/ROW]
[ROW][C]262[/C][C]0.934599[/C][C]0.130802[/C][C]0.0654011[/C][/ROW]
[ROW][C]263[/C][C]0.899205[/C][C]0.201589[/C][C]0.100795[/C][/ROW]
[ROW][C]264[/C][C]0.874032[/C][C]0.251936[/C][C]0.125968[/C][/ROW]
[ROW][C]265[/C][C]0.906535[/C][C]0.186931[/C][C]0.0934654[/C][/ROW]
[ROW][C]266[/C][C]0.852345[/C][C]0.295311[/C][C]0.147655[/C][/ROW]
[ROW][C]267[/C][C]0.876878[/C][C]0.246244[/C][C]0.123122[/C][/ROW]
[ROW][C]268[/C][C]0.789822[/C][C]0.420356[/C][C]0.210178[/C][/ROW]
[ROW][C]269[/C][C]0.867861[/C][C]0.264279[/C][C]0.132139[/C][/ROW]
[ROW][C]270[/C][C]0.792246[/C][C]0.415509[/C][C]0.207754[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266592&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266592&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
80.2205670.4411350.779433
90.3902680.7805360.609732
100.3809680.7619370.619032
110.2593150.518630.740685
120.2124210.4248420.787579
130.1512010.3024010.848799
140.1697540.3395070.830246
150.1535080.3070150.846492
160.1034680.2069350.896532
170.09383350.1876670.906166
180.06091370.1218270.939086
190.03884020.07768040.96116
200.02516430.05032860.974836
210.02014350.04028710.979856
220.03557530.07115060.964425
230.02498480.04996960.975015
240.04359580.08719150.956404
250.02914210.05828420.970858
260.01904710.03809410.980953
270.04040390.08080790.959596
280.02807110.05614220.971929
290.01890730.03781450.981093
300.01250540.02501090.987495
310.04776170.09552340.952238
320.03766390.07532770.962336
330.03256720.06513430.967433
340.02424430.04848860.975756
350.01723760.03447510.982762
360.01205770.02411540.987942
370.008381920.01676380.991618
380.006144530.01228910.993855
390.004327670.008655340.995672
400.003165780.006331570.996834
410.005011940.01002390.994988
420.004472210.008944420.995528
430.005114110.01022820.994886
440.003483850.006967710.996516
450.002339340.004678690.997661
460.00203680.00407360.997963
470.001390140.002780270.99861
480.001167310.002334630.998833
490.001249530.002499070.99875
500.001032570.002065150.998967
510.0007091960.001418390.999291
520.001862510.003725010.998137
530.001295810.002591620.998704
540.001104710.002209410.998895
550.001347390.002694790.998653
560.0009267440.001853490.999073
570.004049850.008099710.99595
580.003508320.007016630.996492
590.003337940.006675880.996662
600.003499060.006998110.996501
610.002693190.005386380.997307
620.002182320.004364640.997818
630.004990810.009981620.995009
640.009718370.01943670.990282
650.008718330.01743670.991282
660.007712910.01542580.992287
670.00572350.0114470.994277
680.00520310.01040620.994797
690.0059660.0119320.994034
700.004547360.009094730.995453
710.003410520.006821040.996589
720.002498510.004997020.997501
730.002444750.004889510.997555
740.002840910.005681810.997159
750.002197020.004394030.997803
760.001710250.003420510.99829
770.001260590.002521180.998739
780.001016110.002032220.998984
790.0008290140.001658030.999171
800.001099860.002199710.9989
810.0008253580.001650720.999175
820.0006972580.001394520.999303
830.000499710.0009994210.9995
840.002873320.005746650.997127
850.002288370.004576740.997712
860.001718780.003437560.998281
870.001290830.002581670.998709
880.0009484380.001896880.999052
890.0009606170.001921230.999039
900.0008134750.001626950.999187
910.0006187440.001237490.999381
920.001778970.003557940.998221
930.001485560.002971130.998514
940.00134840.002696810.998652
950.001843730.003687450.998156
960.00177340.003546790.998227
970.002490210.004980420.99751
980.001992710.003985420.998007
990.001849230.003698460.998151
1000.002276290.004552580.997724
1010.001879120.003758250.998121
1020.001587330.003174670.998413
1030.001837230.003674460.998163
1040.00172750.0034550.998272
1050.001870150.003740290.99813
1060.002222070.004444150.997778
1070.002179780.004359560.99782
1080.008537020.0170740.991463
1090.01830060.03660130.981699
1100.01995210.03990420.980048
1110.01907050.03814090.98093
1120.01867620.03735230.981324
1130.08882810.1776560.911172
1140.08657950.1731590.91342
1150.1701710.3403420.829829
1160.2648080.5296160.735192
1170.3137680.6275370.686232
1180.2996660.5993320.700334
1190.3507850.7015690.649215
1200.4805750.9611510.519425
1210.5005130.9989750.499487
1220.4815180.9630360.518482
1230.5394220.9211560.460578
1240.5290370.9419270.470963
1250.5447240.9105530.455276
1260.5273220.9453550.472678
1270.5331580.9336830.466842
1280.5116450.9767110.488355
1290.5928240.8143530.407176
1300.5680660.8638680.431934
1310.5429570.9140870.457043
1320.536960.926080.46304
1330.5142570.9714850.485743
1340.4895150.9790310.510485
1350.475470.950940.52453
1360.4637540.9275080.536246
1370.4715530.9431060.528447
1380.5688590.8622820.431141
1390.6107360.7785290.389264
1400.5873470.8253060.412653
1410.5729910.8540170.427009
1420.5896670.8206670.410333
1430.5637390.8725210.436261
1440.5804130.8391730.419587
1450.5612080.8775840.438792
1460.555120.8897590.44488
1470.5386080.9227840.461392
1480.5091160.9817680.490884
1490.4781890.9563780.521811
1500.4905570.9811130.509443
1510.5336770.9326460.466323
1520.5043160.9913670.495684
1530.5081430.9837140.491857
1540.4887390.9774790.511261
1550.4578090.9156170.542191
1560.4349260.8698520.565074
1570.4477910.8955820.552209
1580.417060.834120.58294
1590.3857560.7715130.614244
1600.3906530.7813060.609347
1610.4014720.8029430.598528
1620.3712530.7425050.628747
1630.3500180.7000360.649982
1640.3193010.6386030.680699
1650.3550550.710110.644945
1660.361970.723940.63803
1670.3811580.7623150.618842
1680.3479580.6959150.652042
1690.3165360.6330710.683464
1700.3256190.6512380.674381
1710.2964870.5929740.703513
1720.3002290.6004590.699771
1730.2702870.5405740.729713
1740.2418580.4837160.758142
1750.2151960.4303910.784804
1760.2139550.427910.786045
1770.1981920.3963840.801808
1780.2297310.4594610.770269
1790.2048330.4096660.795167
1800.3294570.6589140.670543
1810.3071820.6143640.692818
1820.281080.5621610.71892
1830.3110290.6220590.688971
1840.2804280.5608570.719572
1850.2567420.5134840.743258
1860.2321320.4642650.767868
1870.2230310.4460630.776969
1880.205030.4100610.79497
1890.2013830.4027660.798617
1900.1883430.3766860.811657
1910.2257620.4515230.774238
1920.1993530.3987060.800647
1930.2821160.5642320.717884
1940.2797750.5595490.720225
1950.2589160.5178320.741084
1960.2299350.459870.770065
1970.2023250.4046490.797675
1980.178690.3573790.82131
1990.1552570.3105140.844743
2000.1352170.2704350.864783
2010.1657180.3314370.834282
2020.1512710.3025410.848729
2030.1340810.2681610.865919
2040.1152810.2305610.884719
2050.1042340.2084680.895766
2060.08791770.1758350.912082
2070.1200830.2401670.879917
2080.1107660.2215320.889234
2090.1272070.2544140.872793
2100.1153340.2306690.884666
2110.1239630.2479260.876037
2120.104830.209660.89517
2130.1046240.2092470.895376
2140.09232150.1846430.907678
2150.07923210.1584640.920768
2160.07500940.1500190.924991
2170.06291520.125830.937085
2180.0626550.125310.937345
2190.06561220.1312240.934388
2200.05370490.107410.946295
2210.05315490.106310.946845
2220.1077920.2155850.892208
2230.1051470.2102940.894853
2240.08843660.1768730.911563
2250.1119960.2239920.888004
2260.09498710.1899740.905013
2270.08611770.1722350.913882
2280.0719130.1438260.928087
2290.08393810.1678760.916062
2300.1233710.2467410.876629
2310.1588770.3177540.841123
2320.2583040.5166070.741696
2330.2272260.4544520.772774
2340.2004270.4008540.799573
2350.215540.431080.78446
2360.5869850.8260290.413015
2370.5525260.8949480.447474
2380.5027080.9945850.497292
2390.5112490.9775020.488751
2400.4818070.9636140.518193
2410.4440850.8881710.555915
2420.4057560.8115110.594244
2430.3549420.7098850.645058
2440.5642090.8715830.435791
2450.5539460.8921080.446054
2460.5048220.9903560.495178
2470.5324060.9351870.467594
2480.5054890.9890230.494511
2490.5031640.9936720.496836
2500.4478840.8957680.552116
2510.3951140.7902280.604886
2520.3437740.6875480.656226
2530.3188930.6377850.681107
2540.5508020.8983970.449198
2550.7863440.4273110.213656
2560.8513130.2973750.148687
2570.8692620.2614760.130738
2580.9271890.1456210.0728106
2590.9157830.1684340.084217
2600.9702750.05945080.0297254
2610.9556330.08873420.0443671
2620.9345990.1308020.0654011
2630.8992050.2015890.100795
2640.8740320.2519360.125968
2650.9065350.1869310.0934654
2660.8523450.2953110.147655
2670.8768780.2462440.123122
2680.7898220.4203560.210178
2690.8678610.2642790.132139
2700.7922460.4155090.207754






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level610.231939NOK
5% type I error level840.319392NOK
10% type I error level960.365019NOK

\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 & 61 & 0.231939 & NOK \tabularnewline
5% type I error level & 84 & 0.319392 & NOK \tabularnewline
10% type I error level & 96 & 0.365019 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266592&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]61[/C][C]0.231939[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]84[/C][C]0.319392[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]96[/C][C]0.365019[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266592&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266592&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 level610.231939NOK
5% type I error level840.319392NOK
10% type I error level960.365019NOK


Figures (Output of Computation)

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Input Parameters & R Code

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