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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 16 Dec 2014 16:28:02 +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/16/t1418747392zcxlwcz6aq47b9w.htm/, Retrieved Thu, 16 May 2024 21:13:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269817, Retrieved Thu, 16 May 2024 21:13:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Percentiles] [Intrinsic Motivat...] [2010-10-12 12:10:58] [b98453cac15ba1066b407e146608df68]
- R  D  [Percentiles] [] [2011-10-18 22:34:54] [b98453cac15ba1066b407e146608df68]
- RMPD    [Percentiles] [] [2014-12-14 10:18:21] [2fea329c6e322b1612c5dc504f90c0ef]
-    D      [Percentiles] [] [2014-12-14 10:24:25] [2fea329c6e322b1612c5dc504f90c0ef]
-    D        [Percentiles] [] [2014-12-14 10:27:52] [2fea329c6e322b1612c5dc504f90c0ef]
-   PD          [Percentiles] [] [2014-12-16 14:14:51] [2fea329c6e322b1612c5dc504f90c0ef]
-    D            [Percentiles] [] [2014-12-16 14:30:23] [2fea329c6e322b1612c5dc504f90c0ef]
- RM D                [Multiple Regression] [] [2014-12-16 16:28:02] [4bf1efda48b6e8e35beb7b429a900cbb] [Current]
- R  D                  [Multiple Regression] [] [2014-12-16 16:45:36] [2fea329c6e322b1612c5dc504f90c0ef]
- R  D                  [Multiple Regression] [] [2014-12-16 16:47:32] [2fea329c6e322b1612c5dc504f90c0ef]
- R PD                    [Multiple Regression] [] [2014-12-17 15:01:44] [95c11abf048d3a1e472aeccb09199113]
-    D                      [Multiple Regression] [] [2014-12-17 15:21:27] [95c11abf048d3a1e472aeccb09199113]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9	26	50	21
7.4	51	68	26
12.2	57	62	22
12.8	37	54	22
7.4	67	71	18
6.7	43	54	23
12.6	52	65	12
14.8	52	73	20
13.3	43	52	22
11.1	84	84	21
8.2	67	42	19
11.4	49	66	22
6.4	70	65	15
10.6	52	78	20
12.0	58	73	19
6.3	68	75	18
11.3	62	72	15
11.9	43	66	20
9.3	56	70	21
9.6	56	61	21
10.0	74	81	15
6.4	65	71	16
13.8	63	69	23
10.8	58	71	21
13.8	57	72	18
11.7	63	68	25
10.9	53	70	9
16.1	57	68	30
13.4	51	61	20
9.9	64	67	23
11.5	53	76	16
8.3	29	70	16
11.7	54	60	19
6.1	51	77	25
9.0	58	72	25
9.7	43	69	18
10.8	51	71	23
10.3	53	62	21
10.4	54	70	10
12.7	56	64	14
9.3	61	58	22
11.8	47	76	26
5.9	39	52	23
11.4	48	59	23
13.0	50	68	24
10.8	35	76	24
12.3	30	65	18
11.3	68	67	23
11.8	49	59	15
7.9	61	69	19
12.7	67	76	16
12.3	47	63	25
11.6	56	75	23
6.7	50	63	17
10.9	43	60	19
12.1	67	73	21
13.3	62	63	18
10.1	57	70	27
5.7	41	75	21
14.3	54	66	13
8.0	45	63	8
13.3	48	63	29
9.3	61	64	28
12.5	56	70	23
7.6	41	75	21
15.9	43	61	19
9.2	53	60	19
9.1	44	62	20
11.1	66	73	18
13.0	58	61	19
14.5	46	66	17
12.2	37	64	19
12.3	51	59	25
11.4	51	64	19
8.8	56	60	22
14.6	66	56	23
7.3	45	66	26
12.6	37	78	14
NA	59	53	28
13.0	42	67	16
12.6	38	59	24
13.2	66	66	20
9.9	34	68	12
7.7	53	71	24
10.5	49	66	22
13.4	55	73	12
10.9	49	72	22
4.3	59	71	20
10.3	40	59	10
11.8	58	64	23
11.2	60	66	17
11.4	63	78	22
8.6	56	68	24
13.2	54	73	18
12.6	52	62	21
5.6	34	65	20
9.9	69	68	20
8.8	32	65	22
7.7	48	60	19
9.0	67	71	20
7.3	58	65	26
11.4	57	68	23
13.6	42	64	24
7.9	64	74	21
10.7	58	69	21
10.3	66	76	19
8.3	26	68	8
9.6	61	72	17
14.2	52	67	20
8.5	51	63	11
13.5	55	59	8
4.9	50	73	15
6.4	60	66	18
9.6	56	62	18
11.6	63	69	19
11.1	61	66	19
4.35	52	51	23
12.7	16	56	22
18.1	46	67	21
17.85	56	69	25
16.6	52	57	30
12.6	55	56	17
17.1	50	55	27
19.1	59	63	23
16.1	60	67	23
13.35	52	65	18
18.4	44	47	18
14.7	67	76	23
10.6	52	64	19
12.6	55	68	15
16.2	37	64	20
13.6	54	65	16
18.9	72	71	24
14.1	51	63	25
14.5	48	60	25
16.15	60	68	19
14.75	50	72	19
14.8	63	70	16
12.45	33	61	19
12.65	67	61	19
17.35	46	62	23
8.6	54	71	21
18.4	59	71	22
16.1	61	51	19
11.6	33	56	20
17.75	47	70	20
15.25	69	73	3
17.65	52	76	23
15.6	55	59	14
16.35	55	68	23
17.65	41	48	20
13.6	73	52	15
11.7	51	59	13
14.35	52	60	16
14.75	50	59	7
18.25	51	57	24
9.9	60	79	17
16	56	60	24
18.25	56	60	24
16.85	29	59	19
14.6	66	62	25
13.85	66	59	20
18.95	73	61	28
15.6	55	71	23
14.85	64	57	27
11.75	40	66	18
18.45	46	63	28
15.9	58	69	21
17.1	43	58	19
16.1	61	59	23
19.9	51	48	27
10.95	50	66	22
18.45	52	73	28
15.1	54	67	25
15	66	61	21
11.35	61	68	22
15.95	80	75	28
18.1	51	62	20
14.6	56	69	29
15.4	56	58	25
15.4	56	60	25
17.6	53	74	20
13.35	47	55	20
19.1	25	62	16
15.35	47	63	20
7.6	46	69	20
13.4	50	58	23
13.9	39	58	18
19.1	51	68	25
15.25	58	72	18
12.9	35	62	19
16.1	58	62	25
17.35	60	65	25
13.15	62	69	25
12.15	63	66	24
12.6	53	72	19
10.35	46	62	26
15.4	67	75	10
9.6	59	58	17
18.2	64	66	13
13.6	38	55	17
14.85	50	47	30
14.75	48	72	25
14.1	48	62	4
14.9	47	64	16
16.25	66	64	21
19.25	47	19	23
13.6	63	50	22
13.6	58	68	17
15.65	44	70	20
12.75	51	79	20
14.6	43	69	22
9.85	55	71	16
12.65	38	48	23
11.9	56	66	16
19.2	45	73	0
16.6	50	74	18
11.2	54	66	25
15.25	57	71	23
11.9	60	74	12
13.2	55	78	18
16.35	56	75	24
12.4	49	53	11
15.85	37	60	18
14.35	43	50	14
18.15	59	70	23
11.15	46	69	24
15.65	51	65	29
17.75	58	78	18
7.65	64	78	15
12.35	53	59	29
15.6	48	72	16
19.3	51	70	19
15.2	47	63	22
17.1	59	63	16
15.6	62	71	23
18.4	62	74	23
19.05	51	67	19
18.55	64	66	4
19.1	52	62	20
13.1	67	80	24
12.85	50	73	20
9.5	54	67	4
4.5	58	61	24
11.85	56	73	22
13.6	63	74	16
11.7	31	32	3
12.4	65	69	15
13.35	71	69	24
11.4	50	84	17
14.9	57	64	20
19.9	47	58	27
17.75	54	60	23
11.2	47	59	26
14.6	57	78	23
17.6	43	57	17
14.05	41	60	20
16.1	63	68	22
13.35	63	68	19
11.85	56	73	24
11.95	51	69	19
14.75	50	67	23
15.15	22	60	15
13.2	41	65	27
16.85	59	66	26
7.85	56	74	22
7.7	66	81	22
12.6	53	72	18
7.85	42	55	15
10.95	52	49	22
12.35	54	74	27
9.95	44	53	10
14.9	62	64	20
16.65	53	65	17
13.4	50	57	23
13.95	36	51	19
15.7	76	80	13
16.85	66	67	27
10.95	62	70	23
15.35	59	74	16
12.2	47	75	25
15.1	55	70	2
17.75	58	69	26
15.2	60	65	20
14.6	44	55	23
16.65	57	71	22
8.1	45	65	24

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269817&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269817&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269817&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 time8 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT.SCORE[t] = + 14.6611 + 0.02305AMS.I[t] -0.0630863AMS.E[t] + 0.0590883NUMERACY[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT.SCORE[t] =  +  14.6611 +  0.02305AMS.I[t] -0.0630863AMS.E[t] +  0.0590883NUMERACY[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269817&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT.SCORE[t] =  +  14.6611 +  0.02305AMS.I[t] -0.0630863AMS.E[t] +  0.0590883NUMERACY[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269817&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269817&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.SCORE[t] = + 14.6611 + 0.02305AMS.I[t] -0.0630863AMS.E[t] + 0.0590883NUMERACY[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)14.66111.874787.821.05947e-135.29735e-14
AMS.I0.023050.02111461.0920.2759150.137957
AMS.E-0.06308630.0263483-2.3940.01730440.00865218
NUMERACY0.05908830.03933111.5020.1341310.0670654

\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) & 14.6611 & 1.87478 & 7.82 & 1.05947e-13 & 5.29735e-14 \tabularnewline
AMS.I & 0.02305 & 0.0211146 & 1.092 & 0.275915 & 0.137957 \tabularnewline
AMS.E & -0.0630863 & 0.0263483 & -2.394 & 0.0173044 & 0.00865218 \tabularnewline
NUMERACY & 0.0590883 & 0.0393311 & 1.502 & 0.134131 & 0.0670654 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269817&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]14.6611[/C][C]1.87478[/C][C]7.82[/C][C]1.05947e-13[/C][C]5.29735e-14[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.02305[/C][C]0.0211146[/C][C]1.092[/C][C]0.275915[/C][C]0.137957[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0630863[/C][C]0.0263483[/C][C]-2.394[/C][C]0.0173044[/C][C]0.00865218[/C][/ROW]
[ROW][C]NUMERACY[/C][C]0.0590883[/C][C]0.0393311[/C][C]1.502[/C][C]0.134131[/C][C]0.0670654[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269817&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269817&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)14.66111.874787.821.05947e-135.29735e-14
AMS.I0.023050.02111461.0920.2759150.137957
AMS.E-0.06308630.0263483-2.3940.01730440.00865218
NUMERACY0.05908830.03933111.5020.1341310.0670654






Multiple Linear Regression - Regression Statistics
Multiple R0.172152
R-squared0.0296363
Adjusted R-squared0.0193133
F-TEST (value)2.87089
F-TEST (DF numerator)3
F-TEST (DF denominator)282
p-value0.0367538
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.38807
Sum Squared Residuals3237.08

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.172152 \tabularnewline
R-squared & 0.0296363 \tabularnewline
Adjusted R-squared & 0.0193133 \tabularnewline
F-TEST (value) & 2.87089 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 282 \tabularnewline
p-value & 0.0367538 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.38807 \tabularnewline
Sum Squared Residuals & 3237.08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269817&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.172152[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0296363[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0193133[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]2.87089[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]282[/C][/ROW]
[ROW][C]p-value[/C][C]0.0367538[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.38807[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3237.08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269817&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269817&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 R0.172152
R-squared0.0296363
Adjusted R-squared0.0193133
F-TEST (value)2.87089
F-TEST (DF numerator)3
F-TEST (DF denominator)282
p-value0.0367538
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.38807
Sum Squared Residuals3237.08






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.347-0.446978
27.413.0831-5.68312
312.213.3636-1.16358
412.813.4073-0.607271
57.412.79-5.38995
66.713.6047-6.90466
712.612.46820.131811
814.812.43622.3638
913.313.6717-0.371744
1011.112.5389-1.43894
118.214.6785-6.47854
1211.412.9268-1.52684
136.413.0604-6.66035
1410.612.1208-1.52077
151212.5154-0.515416
166.312.5607-6.26066
1711.312.4343-1.13435
1811.912.6704-0.770359
199.312.7768-3.47675
209.613.3445-3.74453
211012.1432-2.14317
226.412.6257-6.22567
2313.813.11940.680636
2410.812.7598-1.95977
2513.812.49641.30364
2611.713.3006-1.60063
2710.911.9985-1.09854
2816.113.45782.64223
2913.413.17020.22981
309.913.2686-3.36859
3111.512.0336-0.533643
328.311.859-3.55896
3311.713.2433-1.54334
346.112.4563-6.35625
35912.933-3.93303
369.712.3629-2.66292
3710.812.7166-1.91659
3810.313.2123-2.91229
3910.412.0807-1.68068
4012.712.7417-0.0416517
419.313.7081-4.40813
4211.812.4862-0.686225
435.913.6386-7.73863
4411.413.4045-2.00448
451312.94190.0581107
4610.812.0914-1.29145
4712.312.3156-0.0156191
4811.313.3608-2.06079
4911.812.9548-1.15482
507.912.8369-4.93691
5112.712.35630.343658
5212.313.2473-0.947259
5311.612.5795-0.979497
546.712.8437-6.1437
5510.912.9898-2.08979
5612.112.841-0.741043
5713.313.17940.120609
5810.113.1543-3.05433
595.712.1156-6.41557
6014.312.51031.78971
61812.1967-4.19666
6213.313.5067-0.206662
639.313.6841-4.38414
6412.512.8949-0.394928
657.612.1156-4.51557
6615.912.92672.9733
679.213.2203-4.02029
689.112.9458-3.84575
6911.112.6407-1.54073
701313.2725-0.272452
7114.512.56221.93776
7212.212.5991-0.399143
7312.313.5918-1.2918
7411.412.9218-1.52184
758.813.4667-4.6667
7614.614.00860.591364
777.313.071-5.77099
7812.611.42051.17951
79NANA0.65213
801313.6331-0.633066
8112.612.6005-0.000508443
8213.215.164-1.96403
839.915.0218-5.12178
847.710.1268-2.42684
8510.59.132651.36735
8613.415.0483-1.64832
8710.919.3237-8.42373
884.36.45193-2.15193
8910.311.8195-1.51955
9011.813.4849-1.68494
9111.212.2925-1.0925
9211.415.8802-4.48019
938.67.764130.835872
9413.213.7892-0.589242
9512.619.526-6.926
965.68.84349-3.24349
979.913.6981-3.79807
988.814.205-5.40504
997.711.6081-3.90813
100915.1337-6.13372
1017.38.94415-1.64415
10211.410.80980.590165
10313.618.4088-4.80881
1047.910.0859-2.18594
10510.712.9106-2.21056
10610.313.4433-3.14328
1078.311.2295-2.92948
1089.68.214721.38528
10914.218.2122-4.01222
1108.57.67950.820496
11113.520.6947-7.19466
1124.911.444-6.54403
1136.49.90418-3.50418
1149.610.883-1.28301
11511.613.5262-1.92617
11611.120.7514-9.65137
1174.354.44705-0.0970491
11812.77.335515.36449
11918.113.32624.77381
12017.8515.28652.56353
12116.617.4006-0.800557
12212.69.439283.16072
12317.111.40575.69432
12419.116.17642.92361
12516.115.57270.527281
12613.358.723874.62613
12718.416.471.93004
12814.717.0449-2.34489
12910.610.52530.0746552
13012.69.058233.54177
13116.215.35060.849358
13213.67.959735.64027
13318.918.13950.760541
13414.113.05961.04043
13514.511.22693.27305
13616.1513.79412.3559
13714.7512.59272.15734
13814.815.0462-0.246202
13912.4513.2799-0.829902
14012.658.469124.18088
14117.3521.4176-4.06757
1428.63.04195.5581
14318.416.27252.12754
14416.117.5707-1.47072
14511.66.360215.23979
14617.7514.32363.42645
14715.2510.02425.22579
14817.6515.0842.56597
14915.612.24813.35195
15016.3512.45983.89019
15117.6517.9996-0.349625
15213.614.7827-1.18275
15311.710.371.33003
15414.3512.10522.24483
15514.7510.15894.59111
15618.2520.4148-2.16482
1579.97.484882.41512
1581611.33494.66512
15918.2514.13024.11982
16016.8515.99830.851705
16114.614.39210.207887
16213.859.054.8
16318.9516.15882.79121
16415.614.88580.714197
16514.8515.583-0.733033
16611.756.701475.04853
16718.4515.43593.01406
16815.911.9163.98404
16917.114.70412.39587
17016.110.60395.49607
17119.921.8999-1.99989
17210.955.408915.54109
17318.4516.50631.94374
17415.113.6751.42497
1751516.7273-1.72726
17611.358.828142.52186
17715.9510.95714.9929
17818.116.81251.28746
17914.612.97011.62986
18015.413.6441.75603
18115.410.19625.20383
18217.617.7065-0.106508
18313.356.521456.82855
18419.116.70182.39818
18515.3520.3003-4.95025
1867.67.71366-0.113664
18713.412.46470.935327
18813.97.824036.07597
18919.116.36942.73059
19015.2515.02920.220784
19112.910.36392.5361
19216.112.17073.92926
19317.3517.4145-0.0644909
19413.1514.3677-1.21771
19512.1512.01330.136747
19612.615.5964-2.99638
19710.357.01493.3351
19815.419.1666-3.76658
1999.64.140795.45921
20018.217.67180.528206
20113.613.37120.228769
20214.8512.80252.04747
20314.7512.74252.00746
20414.111.85242.24762
20514.912.03582.86423
20616.2512.90493.34512
20719.2519.9089-0.658916
20813.612.71270.887329
20913.610.39113.20894
21015.6514.93460.715363
21112.7510.74932.00072
21214.617.1452-2.54517
2139.8511.0679-1.21793
21412.6513.4837-0.833656
21511.93.793098.10691
21619.214.80884.39116
21716.618.6194-2.01935
21811.28.804892.39511
21915.2515.4348-0.184812
22011.910.77171.12825
22113.29.488593.71141
22216.3517.047-0.696986
22312.49.34243.0576
22415.8514.82521.02479
22514.359.164085.18592
22618.1519.7866-1.6366
22711.158.949642.20036
22815.6510.04095.6091
22917.7522.2019-4.45193
2307.659.17426-1.52426
23112.358.920743.42926
23215.68.843336.75667
23319.317.172.13001
23415.211.09214.10794
23517.114.47012.62986
23615.69.980885.61912
23718.412.08266.31742
23819.0512.7096.341
23918.5512.58025.96985
24019.118.57670.523297
24113.112.64010.459895
24212.8515.2654-2.41541
2439.518.5679-9.06789
2444.55.29658-0.796581
24511.8510.64031.20968
24613.615.4342-1.83419
24711.711.9928-0.292758
24812.412.4129-0.0128525
24913.3513.4689-0.118891
25011.49.619231.78077
25114.98.680876.21913
25219.915.62974.27031
25317.7520.1087-2.35869
25411.29.013292.18671
25514.610.06094.53913
25617.616.55281.04722
25714.0511.07342.97664
25816.115.69610.403902
25913.3514.2648-0.914758
26011.8512.5064-0.656412
26111.9510.14591.80411
26214.7511.86942.88061
26315.1515.0510.0990368
26413.29.743693.45631
26516.8521.5835-4.73349
2667.8512.5224-4.67239
2677.77.504160.195836
26812.617.7958-5.19582
2697.8510.9685-3.11845
27010.9511.4328-0.482836
27112.3515.3226-2.97265
2729.958.284481.66552
27314.911.03673.86332
27416.6516.8268-0.17675
27513.412.84620.553785
27613.9510.38423.56582
27715.712.4013.29896
27816.8518.9332-2.08323
27910.957.898123.05188
28015.3515.6402-0.290224
28112.28.731023.46898
28215.110.53144.56862
28317.7515.67532.07471
28415.214.16461.03538
28514.610.74583.8542
28616.6521.5659-4.9159
2878.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.347 & -0.446978 \tabularnewline
2 & 7.4 & 13.0831 & -5.68312 \tabularnewline
3 & 12.2 & 13.3636 & -1.16358 \tabularnewline
4 & 12.8 & 13.4073 & -0.607271 \tabularnewline
5 & 7.4 & 12.79 & -5.38995 \tabularnewline
6 & 6.7 & 13.6047 & -6.90466 \tabularnewline
7 & 12.6 & 12.4682 & 0.131811 \tabularnewline
8 & 14.8 & 12.4362 & 2.3638 \tabularnewline
9 & 13.3 & 13.6717 & -0.371744 \tabularnewline
10 & 11.1 & 12.5389 & -1.43894 \tabularnewline
11 & 8.2 & 14.6785 & -6.47854 \tabularnewline
12 & 11.4 & 12.9268 & -1.52684 \tabularnewline
13 & 6.4 & 13.0604 & -6.66035 \tabularnewline
14 & 10.6 & 12.1208 & -1.52077 \tabularnewline
15 & 12 & 12.5154 & -0.515416 \tabularnewline
16 & 6.3 & 12.5607 & -6.26066 \tabularnewline
17 & 11.3 & 12.4343 & -1.13435 \tabularnewline
18 & 11.9 & 12.6704 & -0.770359 \tabularnewline
19 & 9.3 & 12.7768 & -3.47675 \tabularnewline
20 & 9.6 & 13.3445 & -3.74453 \tabularnewline
21 & 10 & 12.1432 & -2.14317 \tabularnewline
22 & 6.4 & 12.6257 & -6.22567 \tabularnewline
23 & 13.8 & 13.1194 & 0.680636 \tabularnewline
24 & 10.8 & 12.7598 & -1.95977 \tabularnewline
25 & 13.8 & 12.4964 & 1.30364 \tabularnewline
26 & 11.7 & 13.3006 & -1.60063 \tabularnewline
27 & 10.9 & 11.9985 & -1.09854 \tabularnewline
28 & 16.1 & 13.4578 & 2.64223 \tabularnewline
29 & 13.4 & 13.1702 & 0.22981 \tabularnewline
30 & 9.9 & 13.2686 & -3.36859 \tabularnewline
31 & 11.5 & 12.0336 & -0.533643 \tabularnewline
32 & 8.3 & 11.859 & -3.55896 \tabularnewline
33 & 11.7 & 13.2433 & -1.54334 \tabularnewline
34 & 6.1 & 12.4563 & -6.35625 \tabularnewline
35 & 9 & 12.933 & -3.93303 \tabularnewline
36 & 9.7 & 12.3629 & -2.66292 \tabularnewline
37 & 10.8 & 12.7166 & -1.91659 \tabularnewline
38 & 10.3 & 13.2123 & -2.91229 \tabularnewline
39 & 10.4 & 12.0807 & -1.68068 \tabularnewline
40 & 12.7 & 12.7417 & -0.0416517 \tabularnewline
41 & 9.3 & 13.7081 & -4.40813 \tabularnewline
42 & 11.8 & 12.4862 & -0.686225 \tabularnewline
43 & 5.9 & 13.6386 & -7.73863 \tabularnewline
44 & 11.4 & 13.4045 & -2.00448 \tabularnewline
45 & 13 & 12.9419 & 0.0581107 \tabularnewline
46 & 10.8 & 12.0914 & -1.29145 \tabularnewline
47 & 12.3 & 12.3156 & -0.0156191 \tabularnewline
48 & 11.3 & 13.3608 & -2.06079 \tabularnewline
49 & 11.8 & 12.9548 & -1.15482 \tabularnewline
50 & 7.9 & 12.8369 & -4.93691 \tabularnewline
51 & 12.7 & 12.3563 & 0.343658 \tabularnewline
52 & 12.3 & 13.2473 & -0.947259 \tabularnewline
53 & 11.6 & 12.5795 & -0.979497 \tabularnewline
54 & 6.7 & 12.8437 & -6.1437 \tabularnewline
55 & 10.9 & 12.9898 & -2.08979 \tabularnewline
56 & 12.1 & 12.841 & -0.741043 \tabularnewline
57 & 13.3 & 13.1794 & 0.120609 \tabularnewline
58 & 10.1 & 13.1543 & -3.05433 \tabularnewline
59 & 5.7 & 12.1156 & -6.41557 \tabularnewline
60 & 14.3 & 12.5103 & 1.78971 \tabularnewline
61 & 8 & 12.1967 & -4.19666 \tabularnewline
62 & 13.3 & 13.5067 & -0.206662 \tabularnewline
63 & 9.3 & 13.6841 & -4.38414 \tabularnewline
64 & 12.5 & 12.8949 & -0.394928 \tabularnewline
65 & 7.6 & 12.1156 & -4.51557 \tabularnewline
66 & 15.9 & 12.9267 & 2.9733 \tabularnewline
67 & 9.2 & 13.2203 & -4.02029 \tabularnewline
68 & 9.1 & 12.9458 & -3.84575 \tabularnewline
69 & 11.1 & 12.6407 & -1.54073 \tabularnewline
70 & 13 & 13.2725 & -0.272452 \tabularnewline
71 & 14.5 & 12.5622 & 1.93776 \tabularnewline
72 & 12.2 & 12.5991 & -0.399143 \tabularnewline
73 & 12.3 & 13.5918 & -1.2918 \tabularnewline
74 & 11.4 & 12.9218 & -1.52184 \tabularnewline
75 & 8.8 & 13.4667 & -4.6667 \tabularnewline
76 & 14.6 & 14.0086 & 0.591364 \tabularnewline
77 & 7.3 & 13.071 & -5.77099 \tabularnewline
78 & 12.6 & 11.4205 & 1.17951 \tabularnewline
79 & NA & NA & 0.65213 \tabularnewline
80 & 13 & 13.6331 & -0.633066 \tabularnewline
81 & 12.6 & 12.6005 & -0.000508443 \tabularnewline
82 & 13.2 & 15.164 & -1.96403 \tabularnewline
83 & 9.9 & 15.0218 & -5.12178 \tabularnewline
84 & 7.7 & 10.1268 & -2.42684 \tabularnewline
85 & 10.5 & 9.13265 & 1.36735 \tabularnewline
86 & 13.4 & 15.0483 & -1.64832 \tabularnewline
87 & 10.9 & 19.3237 & -8.42373 \tabularnewline
88 & 4.3 & 6.45193 & -2.15193 \tabularnewline
89 & 10.3 & 11.8195 & -1.51955 \tabularnewline
90 & 11.8 & 13.4849 & -1.68494 \tabularnewline
91 & 11.2 & 12.2925 & -1.0925 \tabularnewline
92 & 11.4 & 15.8802 & -4.48019 \tabularnewline
93 & 8.6 & 7.76413 & 0.835872 \tabularnewline
94 & 13.2 & 13.7892 & -0.589242 \tabularnewline
95 & 12.6 & 19.526 & -6.926 \tabularnewline
96 & 5.6 & 8.84349 & -3.24349 \tabularnewline
97 & 9.9 & 13.6981 & -3.79807 \tabularnewline
98 & 8.8 & 14.205 & -5.40504 \tabularnewline
99 & 7.7 & 11.6081 & -3.90813 \tabularnewline
100 & 9 & 15.1337 & -6.13372 \tabularnewline
101 & 7.3 & 8.94415 & -1.64415 \tabularnewline
102 & 11.4 & 10.8098 & 0.590165 \tabularnewline
103 & 13.6 & 18.4088 & -4.80881 \tabularnewline
104 & 7.9 & 10.0859 & -2.18594 \tabularnewline
105 & 10.7 & 12.9106 & -2.21056 \tabularnewline
106 & 10.3 & 13.4433 & -3.14328 \tabularnewline
107 & 8.3 & 11.2295 & -2.92948 \tabularnewline
108 & 9.6 & 8.21472 & 1.38528 \tabularnewline
109 & 14.2 & 18.2122 & -4.01222 \tabularnewline
110 & 8.5 & 7.6795 & 0.820496 \tabularnewline
111 & 13.5 & 20.6947 & -7.19466 \tabularnewline
112 & 4.9 & 11.444 & -6.54403 \tabularnewline
113 & 6.4 & 9.90418 & -3.50418 \tabularnewline
114 & 9.6 & 10.883 & -1.28301 \tabularnewline
115 & 11.6 & 13.5262 & -1.92617 \tabularnewline
116 & 11.1 & 20.7514 & -9.65137 \tabularnewline
117 & 4.35 & 4.44705 & -0.0970491 \tabularnewline
118 & 12.7 & 7.33551 & 5.36449 \tabularnewline
119 & 18.1 & 13.3262 & 4.77381 \tabularnewline
120 & 17.85 & 15.2865 & 2.56353 \tabularnewline
121 & 16.6 & 17.4006 & -0.800557 \tabularnewline
122 & 12.6 & 9.43928 & 3.16072 \tabularnewline
123 & 17.1 & 11.4057 & 5.69432 \tabularnewline
124 & 19.1 & 16.1764 & 2.92361 \tabularnewline
125 & 16.1 & 15.5727 & 0.527281 \tabularnewline
126 & 13.35 & 8.72387 & 4.62613 \tabularnewline
127 & 18.4 & 16.47 & 1.93004 \tabularnewline
128 & 14.7 & 17.0449 & -2.34489 \tabularnewline
129 & 10.6 & 10.5253 & 0.0746552 \tabularnewline
130 & 12.6 & 9.05823 & 3.54177 \tabularnewline
131 & 16.2 & 15.3506 & 0.849358 \tabularnewline
132 & 13.6 & 7.95973 & 5.64027 \tabularnewline
133 & 18.9 & 18.1395 & 0.760541 \tabularnewline
134 & 14.1 & 13.0596 & 1.04043 \tabularnewline
135 & 14.5 & 11.2269 & 3.27305 \tabularnewline
136 & 16.15 & 13.7941 & 2.3559 \tabularnewline
137 & 14.75 & 12.5927 & 2.15734 \tabularnewline
138 & 14.8 & 15.0462 & -0.246202 \tabularnewline
139 & 12.45 & 13.2799 & -0.829902 \tabularnewline
140 & 12.65 & 8.46912 & 4.18088 \tabularnewline
141 & 17.35 & 21.4176 & -4.06757 \tabularnewline
142 & 8.6 & 3.0419 & 5.5581 \tabularnewline
143 & 18.4 & 16.2725 & 2.12754 \tabularnewline
144 & 16.1 & 17.5707 & -1.47072 \tabularnewline
145 & 11.6 & 6.36021 & 5.23979 \tabularnewline
146 & 17.75 & 14.3236 & 3.42645 \tabularnewline
147 & 15.25 & 10.0242 & 5.22579 \tabularnewline
148 & 17.65 & 15.084 & 2.56597 \tabularnewline
149 & 15.6 & 12.2481 & 3.35195 \tabularnewline
150 & 16.35 & 12.4598 & 3.89019 \tabularnewline
151 & 17.65 & 17.9996 & -0.349625 \tabularnewline
152 & 13.6 & 14.7827 & -1.18275 \tabularnewline
153 & 11.7 & 10.37 & 1.33003 \tabularnewline
154 & 14.35 & 12.1052 & 2.24483 \tabularnewline
155 & 14.75 & 10.1589 & 4.59111 \tabularnewline
156 & 18.25 & 20.4148 & -2.16482 \tabularnewline
157 & 9.9 & 7.48488 & 2.41512 \tabularnewline
158 & 16 & 11.3349 & 4.66512 \tabularnewline
159 & 18.25 & 14.1302 & 4.11982 \tabularnewline
160 & 16.85 & 15.9983 & 0.851705 \tabularnewline
161 & 14.6 & 14.3921 & 0.207887 \tabularnewline
162 & 13.85 & 9.05 & 4.8 \tabularnewline
163 & 18.95 & 16.1588 & 2.79121 \tabularnewline
164 & 15.6 & 14.8858 & 0.714197 \tabularnewline
165 & 14.85 & 15.583 & -0.733033 \tabularnewline
166 & 11.75 & 6.70147 & 5.04853 \tabularnewline
167 & 18.45 & 15.4359 & 3.01406 \tabularnewline
168 & 15.9 & 11.916 & 3.98404 \tabularnewline
169 & 17.1 & 14.7041 & 2.39587 \tabularnewline
170 & 16.1 & 10.6039 & 5.49607 \tabularnewline
171 & 19.9 & 21.8999 & -1.99989 \tabularnewline
172 & 10.95 & 5.40891 & 5.54109 \tabularnewline
173 & 18.45 & 16.5063 & 1.94374 \tabularnewline
174 & 15.1 & 13.675 & 1.42497 \tabularnewline
175 & 15 & 16.7273 & -1.72726 \tabularnewline
176 & 11.35 & 8.82814 & 2.52186 \tabularnewline
177 & 15.95 & 10.9571 & 4.9929 \tabularnewline
178 & 18.1 & 16.8125 & 1.28746 \tabularnewline
179 & 14.6 & 12.9701 & 1.62986 \tabularnewline
180 & 15.4 & 13.644 & 1.75603 \tabularnewline
181 & 15.4 & 10.1962 & 5.20383 \tabularnewline
182 & 17.6 & 17.7065 & -0.106508 \tabularnewline
183 & 13.35 & 6.52145 & 6.82855 \tabularnewline
184 & 19.1 & 16.7018 & 2.39818 \tabularnewline
185 & 15.35 & 20.3003 & -4.95025 \tabularnewline
186 & 7.6 & 7.71366 & -0.113664 \tabularnewline
187 & 13.4 & 12.4647 & 0.935327 \tabularnewline
188 & 13.9 & 7.82403 & 6.07597 \tabularnewline
189 & 19.1 & 16.3694 & 2.73059 \tabularnewline
190 & 15.25 & 15.0292 & 0.220784 \tabularnewline
191 & 12.9 & 10.3639 & 2.5361 \tabularnewline
192 & 16.1 & 12.1707 & 3.92926 \tabularnewline
193 & 17.35 & 17.4145 & -0.0644909 \tabularnewline
194 & 13.15 & 14.3677 & -1.21771 \tabularnewline
195 & 12.15 & 12.0133 & 0.136747 \tabularnewline
196 & 12.6 & 15.5964 & -2.99638 \tabularnewline
197 & 10.35 & 7.0149 & 3.3351 \tabularnewline
198 & 15.4 & 19.1666 & -3.76658 \tabularnewline
199 & 9.6 & 4.14079 & 5.45921 \tabularnewline
200 & 18.2 & 17.6718 & 0.528206 \tabularnewline
201 & 13.6 & 13.3712 & 0.228769 \tabularnewline
202 & 14.85 & 12.8025 & 2.04747 \tabularnewline
203 & 14.75 & 12.7425 & 2.00746 \tabularnewline
204 & 14.1 & 11.8524 & 2.24762 \tabularnewline
205 & 14.9 & 12.0358 & 2.86423 \tabularnewline
206 & 16.25 & 12.9049 & 3.34512 \tabularnewline
207 & 19.25 & 19.9089 & -0.658916 \tabularnewline
208 & 13.6 & 12.7127 & 0.887329 \tabularnewline
209 & 13.6 & 10.3911 & 3.20894 \tabularnewline
210 & 15.65 & 14.9346 & 0.715363 \tabularnewline
211 & 12.75 & 10.7493 & 2.00072 \tabularnewline
212 & 14.6 & 17.1452 & -2.54517 \tabularnewline
213 & 9.85 & 11.0679 & -1.21793 \tabularnewline
214 & 12.65 & 13.4837 & -0.833656 \tabularnewline
215 & 11.9 & 3.79309 & 8.10691 \tabularnewline
216 & 19.2 & 14.8088 & 4.39116 \tabularnewline
217 & 16.6 & 18.6194 & -2.01935 \tabularnewline
218 & 11.2 & 8.80489 & 2.39511 \tabularnewline
219 & 15.25 & 15.4348 & -0.184812 \tabularnewline
220 & 11.9 & 10.7717 & 1.12825 \tabularnewline
221 & 13.2 & 9.48859 & 3.71141 \tabularnewline
222 & 16.35 & 17.047 & -0.696986 \tabularnewline
223 & 12.4 & 9.3424 & 3.0576 \tabularnewline
224 & 15.85 & 14.8252 & 1.02479 \tabularnewline
225 & 14.35 & 9.16408 & 5.18592 \tabularnewline
226 & 18.15 & 19.7866 & -1.6366 \tabularnewline
227 & 11.15 & 8.94964 & 2.20036 \tabularnewline
228 & 15.65 & 10.0409 & 5.6091 \tabularnewline
229 & 17.75 & 22.2019 & -4.45193 \tabularnewline
230 & 7.65 & 9.17426 & -1.52426 \tabularnewline
231 & 12.35 & 8.92074 & 3.42926 \tabularnewline
232 & 15.6 & 8.84333 & 6.75667 \tabularnewline
233 & 19.3 & 17.17 & 2.13001 \tabularnewline
234 & 15.2 & 11.0921 & 4.10794 \tabularnewline
235 & 17.1 & 14.4701 & 2.62986 \tabularnewline
236 & 15.6 & 9.98088 & 5.61912 \tabularnewline
237 & 18.4 & 12.0826 & 6.31742 \tabularnewline
238 & 19.05 & 12.709 & 6.341 \tabularnewline
239 & 18.55 & 12.5802 & 5.96985 \tabularnewline
240 & 19.1 & 18.5767 & 0.523297 \tabularnewline
241 & 13.1 & 12.6401 & 0.459895 \tabularnewline
242 & 12.85 & 15.2654 & -2.41541 \tabularnewline
243 & 9.5 & 18.5679 & -9.06789 \tabularnewline
244 & 4.5 & 5.29658 & -0.796581 \tabularnewline
245 & 11.85 & 10.6403 & 1.20968 \tabularnewline
246 & 13.6 & 15.4342 & -1.83419 \tabularnewline
247 & 11.7 & 11.9928 & -0.292758 \tabularnewline
248 & 12.4 & 12.4129 & -0.0128525 \tabularnewline
249 & 13.35 & 13.4689 & -0.118891 \tabularnewline
250 & 11.4 & 9.61923 & 1.78077 \tabularnewline
251 & 14.9 & 8.68087 & 6.21913 \tabularnewline
252 & 19.9 & 15.6297 & 4.27031 \tabularnewline
253 & 17.75 & 20.1087 & -2.35869 \tabularnewline
254 & 11.2 & 9.01329 & 2.18671 \tabularnewline
255 & 14.6 & 10.0609 & 4.53913 \tabularnewline
256 & 17.6 & 16.5528 & 1.04722 \tabularnewline
257 & 14.05 & 11.0734 & 2.97664 \tabularnewline
258 & 16.1 & 15.6961 & 0.403902 \tabularnewline
259 & 13.35 & 14.2648 & -0.914758 \tabularnewline
260 & 11.85 & 12.5064 & -0.656412 \tabularnewline
261 & 11.95 & 10.1459 & 1.80411 \tabularnewline
262 & 14.75 & 11.8694 & 2.88061 \tabularnewline
263 & 15.15 & 15.051 & 0.0990368 \tabularnewline
264 & 13.2 & 9.74369 & 3.45631 \tabularnewline
265 & 16.85 & 21.5835 & -4.73349 \tabularnewline
266 & 7.85 & 12.5224 & -4.67239 \tabularnewline
267 & 7.7 & 7.50416 & 0.195836 \tabularnewline
268 & 12.6 & 17.7958 & -5.19582 \tabularnewline
269 & 7.85 & 10.9685 & -3.11845 \tabularnewline
270 & 10.95 & 11.4328 & -0.482836 \tabularnewline
271 & 12.35 & 15.3226 & -2.97265 \tabularnewline
272 & 9.95 & 8.28448 & 1.66552 \tabularnewline
273 & 14.9 & 11.0367 & 3.86332 \tabularnewline
274 & 16.65 & 16.8268 & -0.17675 \tabularnewline
275 & 13.4 & 12.8462 & 0.553785 \tabularnewline
276 & 13.95 & 10.3842 & 3.56582 \tabularnewline
277 & 15.7 & 12.401 & 3.29896 \tabularnewline
278 & 16.85 & 18.9332 & -2.08323 \tabularnewline
279 & 10.95 & 7.89812 & 3.05188 \tabularnewline
280 & 15.35 & 15.6402 & -0.290224 \tabularnewline
281 & 12.2 & 8.73102 & 3.46898 \tabularnewline
282 & 15.1 & 10.5314 & 4.56862 \tabularnewline
283 & 17.75 & 15.6753 & 2.07471 \tabularnewline
284 & 15.2 & 14.1646 & 1.03538 \tabularnewline
285 & 14.6 & 10.7458 & 3.8542 \tabularnewline
286 & 16.65 & 21.5659 & -4.9159 \tabularnewline
287 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269817&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]13.347[/C][C]-0.446978[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]13.0831[/C][C]-5.68312[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]13.3636[/C][C]-1.16358[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]13.4073[/C][C]-0.607271[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]12.79[/C][C]-5.38995[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]13.6047[/C][C]-6.90466[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]12.4682[/C][C]0.131811[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]12.4362[/C][C]2.3638[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]13.6717[/C][C]-0.371744[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]12.5389[/C][C]-1.43894[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]14.6785[/C][C]-6.47854[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]12.9268[/C][C]-1.52684[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]13.0604[/C][C]-6.66035[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]12.1208[/C][C]-1.52077[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]12.5154[/C][C]-0.515416[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]12.5607[/C][C]-6.26066[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]12.4343[/C][C]-1.13435[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]12.6704[/C][C]-0.770359[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]12.7768[/C][C]-3.47675[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]13.3445[/C][C]-3.74453[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]12.1432[/C][C]-2.14317[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]12.6257[/C][C]-6.22567[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]13.1194[/C][C]0.680636[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]12.7598[/C][C]-1.95977[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]12.4964[/C][C]1.30364[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]13.3006[/C][C]-1.60063[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]11.9985[/C][C]-1.09854[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]13.4578[/C][C]2.64223[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]13.1702[/C][C]0.22981[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]13.2686[/C][C]-3.36859[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]12.0336[/C][C]-0.533643[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]11.859[/C][C]-3.55896[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]13.2433[/C][C]-1.54334[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]12.4563[/C][C]-6.35625[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]12.933[/C][C]-3.93303[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]12.3629[/C][C]-2.66292[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]12.7166[/C][C]-1.91659[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]13.2123[/C][C]-2.91229[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]12.0807[/C][C]-1.68068[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]12.7417[/C][C]-0.0416517[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]13.7081[/C][C]-4.40813[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]12.4862[/C][C]-0.686225[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]13.6386[/C][C]-7.73863[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]13.4045[/C][C]-2.00448[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]12.9419[/C][C]0.0581107[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]12.0914[/C][C]-1.29145[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]12.3156[/C][C]-0.0156191[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]13.3608[/C][C]-2.06079[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]12.9548[/C][C]-1.15482[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]12.8369[/C][C]-4.93691[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]12.3563[/C][C]0.343658[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]13.2473[/C][C]-0.947259[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]12.5795[/C][C]-0.979497[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]12.8437[/C][C]-6.1437[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]12.9898[/C][C]-2.08979[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]12.841[/C][C]-0.741043[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]13.1794[/C][C]0.120609[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]13.1543[/C][C]-3.05433[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]12.1156[/C][C]-6.41557[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]12.5103[/C][C]1.78971[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]12.1967[/C][C]-4.19666[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]13.5067[/C][C]-0.206662[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]13.6841[/C][C]-4.38414[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]12.8949[/C][C]-0.394928[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]12.1156[/C][C]-4.51557[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]12.9267[/C][C]2.9733[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]13.2203[/C][C]-4.02029[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]12.9458[/C][C]-3.84575[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]12.6407[/C][C]-1.54073[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]13.2725[/C][C]-0.272452[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]12.5622[/C][C]1.93776[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]12.5991[/C][C]-0.399143[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]13.5918[/C][C]-1.2918[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]12.9218[/C][C]-1.52184[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]13.4667[/C][C]-4.6667[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]14.0086[/C][C]0.591364[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]13.071[/C][C]-5.77099[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]11.4205[/C][C]1.17951[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]0.65213[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]13.6331[/C][C]-0.633066[/C][/ROW]
[ROW][C]81[/C][C]12.6[/C][C]12.6005[/C][C]-0.000508443[/C][/ROW]
[ROW][C]82[/C][C]13.2[/C][C]15.164[/C][C]-1.96403[/C][/ROW]
[ROW][C]83[/C][C]9.9[/C][C]15.0218[/C][C]-5.12178[/C][/ROW]
[ROW][C]84[/C][C]7.7[/C][C]10.1268[/C][C]-2.42684[/C][/ROW]
[ROW][C]85[/C][C]10.5[/C][C]9.13265[/C][C]1.36735[/C][/ROW]
[ROW][C]86[/C][C]13.4[/C][C]15.0483[/C][C]-1.64832[/C][/ROW]
[ROW][C]87[/C][C]10.9[/C][C]19.3237[/C][C]-8.42373[/C][/ROW]
[ROW][C]88[/C][C]4.3[/C][C]6.45193[/C][C]-2.15193[/C][/ROW]
[ROW][C]89[/C][C]10.3[/C][C]11.8195[/C][C]-1.51955[/C][/ROW]
[ROW][C]90[/C][C]11.8[/C][C]13.4849[/C][C]-1.68494[/C][/ROW]
[ROW][C]91[/C][C]11.2[/C][C]12.2925[/C][C]-1.0925[/C][/ROW]
[ROW][C]92[/C][C]11.4[/C][C]15.8802[/C][C]-4.48019[/C][/ROW]
[ROW][C]93[/C][C]8.6[/C][C]7.76413[/C][C]0.835872[/C][/ROW]
[ROW][C]94[/C][C]13.2[/C][C]13.7892[/C][C]-0.589242[/C][/ROW]
[ROW][C]95[/C][C]12.6[/C][C]19.526[/C][C]-6.926[/C][/ROW]
[ROW][C]96[/C][C]5.6[/C][C]8.84349[/C][C]-3.24349[/C][/ROW]
[ROW][C]97[/C][C]9.9[/C][C]13.6981[/C][C]-3.79807[/C][/ROW]
[ROW][C]98[/C][C]8.8[/C][C]14.205[/C][C]-5.40504[/C][/ROW]
[ROW][C]99[/C][C]7.7[/C][C]11.6081[/C][C]-3.90813[/C][/ROW]
[ROW][C]100[/C][C]9[/C][C]15.1337[/C][C]-6.13372[/C][/ROW]
[ROW][C]101[/C][C]7.3[/C][C]8.94415[/C][C]-1.64415[/C][/ROW]
[ROW][C]102[/C][C]11.4[/C][C]10.8098[/C][C]0.590165[/C][/ROW]
[ROW][C]103[/C][C]13.6[/C][C]18.4088[/C][C]-4.80881[/C][/ROW]
[ROW][C]104[/C][C]7.9[/C][C]10.0859[/C][C]-2.18594[/C][/ROW]
[ROW][C]105[/C][C]10.7[/C][C]12.9106[/C][C]-2.21056[/C][/ROW]
[ROW][C]106[/C][C]10.3[/C][C]13.4433[/C][C]-3.14328[/C][/ROW]
[ROW][C]107[/C][C]8.3[/C][C]11.2295[/C][C]-2.92948[/C][/ROW]
[ROW][C]108[/C][C]9.6[/C][C]8.21472[/C][C]1.38528[/C][/ROW]
[ROW][C]109[/C][C]14.2[/C][C]18.2122[/C][C]-4.01222[/C][/ROW]
[ROW][C]110[/C][C]8.5[/C][C]7.6795[/C][C]0.820496[/C][/ROW]
[ROW][C]111[/C][C]13.5[/C][C]20.6947[/C][C]-7.19466[/C][/ROW]
[ROW][C]112[/C][C]4.9[/C][C]11.444[/C][C]-6.54403[/C][/ROW]
[ROW][C]113[/C][C]6.4[/C][C]9.90418[/C][C]-3.50418[/C][/ROW]
[ROW][C]114[/C][C]9.6[/C][C]10.883[/C][C]-1.28301[/C][/ROW]
[ROW][C]115[/C][C]11.6[/C][C]13.5262[/C][C]-1.92617[/C][/ROW]
[ROW][C]116[/C][C]11.1[/C][C]20.7514[/C][C]-9.65137[/C][/ROW]
[ROW][C]117[/C][C]4.35[/C][C]4.44705[/C][C]-0.0970491[/C][/ROW]
[ROW][C]118[/C][C]12.7[/C][C]7.33551[/C][C]5.36449[/C][/ROW]
[ROW][C]119[/C][C]18.1[/C][C]13.3262[/C][C]4.77381[/C][/ROW]
[ROW][C]120[/C][C]17.85[/C][C]15.2865[/C][C]2.56353[/C][/ROW]
[ROW][C]121[/C][C]16.6[/C][C]17.4006[/C][C]-0.800557[/C][/ROW]
[ROW][C]122[/C][C]12.6[/C][C]9.43928[/C][C]3.16072[/C][/ROW]
[ROW][C]123[/C][C]17.1[/C][C]11.4057[/C][C]5.69432[/C][/ROW]
[ROW][C]124[/C][C]19.1[/C][C]16.1764[/C][C]2.92361[/C][/ROW]
[ROW][C]125[/C][C]16.1[/C][C]15.5727[/C][C]0.527281[/C][/ROW]
[ROW][C]126[/C][C]13.35[/C][C]8.72387[/C][C]4.62613[/C][/ROW]
[ROW][C]127[/C][C]18.4[/C][C]16.47[/C][C]1.93004[/C][/ROW]
[ROW][C]128[/C][C]14.7[/C][C]17.0449[/C][C]-2.34489[/C][/ROW]
[ROW][C]129[/C][C]10.6[/C][C]10.5253[/C][C]0.0746552[/C][/ROW]
[ROW][C]130[/C][C]12.6[/C][C]9.05823[/C][C]3.54177[/C][/ROW]
[ROW][C]131[/C][C]16.2[/C][C]15.3506[/C][C]0.849358[/C][/ROW]
[ROW][C]132[/C][C]13.6[/C][C]7.95973[/C][C]5.64027[/C][/ROW]
[ROW][C]133[/C][C]18.9[/C][C]18.1395[/C][C]0.760541[/C][/ROW]
[ROW][C]134[/C][C]14.1[/C][C]13.0596[/C][C]1.04043[/C][/ROW]
[ROW][C]135[/C][C]14.5[/C][C]11.2269[/C][C]3.27305[/C][/ROW]
[ROW][C]136[/C][C]16.15[/C][C]13.7941[/C][C]2.3559[/C][/ROW]
[ROW][C]137[/C][C]14.75[/C][C]12.5927[/C][C]2.15734[/C][/ROW]
[ROW][C]138[/C][C]14.8[/C][C]15.0462[/C][C]-0.246202[/C][/ROW]
[ROW][C]139[/C][C]12.45[/C][C]13.2799[/C][C]-0.829902[/C][/ROW]
[ROW][C]140[/C][C]12.65[/C][C]8.46912[/C][C]4.18088[/C][/ROW]
[ROW][C]141[/C][C]17.35[/C][C]21.4176[/C][C]-4.06757[/C][/ROW]
[ROW][C]142[/C][C]8.6[/C][C]3.0419[/C][C]5.5581[/C][/ROW]
[ROW][C]143[/C][C]18.4[/C][C]16.2725[/C][C]2.12754[/C][/ROW]
[ROW][C]144[/C][C]16.1[/C][C]17.5707[/C][C]-1.47072[/C][/ROW]
[ROW][C]145[/C][C]11.6[/C][C]6.36021[/C][C]5.23979[/C][/ROW]
[ROW][C]146[/C][C]17.75[/C][C]14.3236[/C][C]3.42645[/C][/ROW]
[ROW][C]147[/C][C]15.25[/C][C]10.0242[/C][C]5.22579[/C][/ROW]
[ROW][C]148[/C][C]17.65[/C][C]15.084[/C][C]2.56597[/C][/ROW]
[ROW][C]149[/C][C]15.6[/C][C]12.2481[/C][C]3.35195[/C][/ROW]
[ROW][C]150[/C][C]16.35[/C][C]12.4598[/C][C]3.89019[/C][/ROW]
[ROW][C]151[/C][C]17.65[/C][C]17.9996[/C][C]-0.349625[/C][/ROW]
[ROW][C]152[/C][C]13.6[/C][C]14.7827[/C][C]-1.18275[/C][/ROW]
[ROW][C]153[/C][C]11.7[/C][C]10.37[/C][C]1.33003[/C][/ROW]
[ROW][C]154[/C][C]14.35[/C][C]12.1052[/C][C]2.24483[/C][/ROW]
[ROW][C]155[/C][C]14.75[/C][C]10.1589[/C][C]4.59111[/C][/ROW]
[ROW][C]156[/C][C]18.25[/C][C]20.4148[/C][C]-2.16482[/C][/ROW]
[ROW][C]157[/C][C]9.9[/C][C]7.48488[/C][C]2.41512[/C][/ROW]
[ROW][C]158[/C][C]16[/C][C]11.3349[/C][C]4.66512[/C][/ROW]
[ROW][C]159[/C][C]18.25[/C][C]14.1302[/C][C]4.11982[/C][/ROW]
[ROW][C]160[/C][C]16.85[/C][C]15.9983[/C][C]0.851705[/C][/ROW]
[ROW][C]161[/C][C]14.6[/C][C]14.3921[/C][C]0.207887[/C][/ROW]
[ROW][C]162[/C][C]13.85[/C][C]9.05[/C][C]4.8[/C][/ROW]
[ROW][C]163[/C][C]18.95[/C][C]16.1588[/C][C]2.79121[/C][/ROW]
[ROW][C]164[/C][C]15.6[/C][C]14.8858[/C][C]0.714197[/C][/ROW]
[ROW][C]165[/C][C]14.85[/C][C]15.583[/C][C]-0.733033[/C][/ROW]
[ROW][C]166[/C][C]11.75[/C][C]6.70147[/C][C]5.04853[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]15.4359[/C][C]3.01406[/C][/ROW]
[ROW][C]168[/C][C]15.9[/C][C]11.916[/C][C]3.98404[/C][/ROW]
[ROW][C]169[/C][C]17.1[/C][C]14.7041[/C][C]2.39587[/C][/ROW]
[ROW][C]170[/C][C]16.1[/C][C]10.6039[/C][C]5.49607[/C][/ROW]
[ROW][C]171[/C][C]19.9[/C][C]21.8999[/C][C]-1.99989[/C][/ROW]
[ROW][C]172[/C][C]10.95[/C][C]5.40891[/C][C]5.54109[/C][/ROW]
[ROW][C]173[/C][C]18.45[/C][C]16.5063[/C][C]1.94374[/C][/ROW]
[ROW][C]174[/C][C]15.1[/C][C]13.675[/C][C]1.42497[/C][/ROW]
[ROW][C]175[/C][C]15[/C][C]16.7273[/C][C]-1.72726[/C][/ROW]
[ROW][C]176[/C][C]11.35[/C][C]8.82814[/C][C]2.52186[/C][/ROW]
[ROW][C]177[/C][C]15.95[/C][C]10.9571[/C][C]4.9929[/C][/ROW]
[ROW][C]178[/C][C]18.1[/C][C]16.8125[/C][C]1.28746[/C][/ROW]
[ROW][C]179[/C][C]14.6[/C][C]12.9701[/C][C]1.62986[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]13.644[/C][C]1.75603[/C][/ROW]
[ROW][C]181[/C][C]15.4[/C][C]10.1962[/C][C]5.20383[/C][/ROW]
[ROW][C]182[/C][C]17.6[/C][C]17.7065[/C][C]-0.106508[/C][/ROW]
[ROW][C]183[/C][C]13.35[/C][C]6.52145[/C][C]6.82855[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]16.7018[/C][C]2.39818[/C][/ROW]
[ROW][C]185[/C][C]15.35[/C][C]20.3003[/C][C]-4.95025[/C][/ROW]
[ROW][C]186[/C][C]7.6[/C][C]7.71366[/C][C]-0.113664[/C][/ROW]
[ROW][C]187[/C][C]13.4[/C][C]12.4647[/C][C]0.935327[/C][/ROW]
[ROW][C]188[/C][C]13.9[/C][C]7.82403[/C][C]6.07597[/C][/ROW]
[ROW][C]189[/C][C]19.1[/C][C]16.3694[/C][C]2.73059[/C][/ROW]
[ROW][C]190[/C][C]15.25[/C][C]15.0292[/C][C]0.220784[/C][/ROW]
[ROW][C]191[/C][C]12.9[/C][C]10.3639[/C][C]2.5361[/C][/ROW]
[ROW][C]192[/C][C]16.1[/C][C]12.1707[/C][C]3.92926[/C][/ROW]
[ROW][C]193[/C][C]17.35[/C][C]17.4145[/C][C]-0.0644909[/C][/ROW]
[ROW][C]194[/C][C]13.15[/C][C]14.3677[/C][C]-1.21771[/C][/ROW]
[ROW][C]195[/C][C]12.15[/C][C]12.0133[/C][C]0.136747[/C][/ROW]
[ROW][C]196[/C][C]12.6[/C][C]15.5964[/C][C]-2.99638[/C][/ROW]
[ROW][C]197[/C][C]10.35[/C][C]7.0149[/C][C]3.3351[/C][/ROW]
[ROW][C]198[/C][C]15.4[/C][C]19.1666[/C][C]-3.76658[/C][/ROW]
[ROW][C]199[/C][C]9.6[/C][C]4.14079[/C][C]5.45921[/C][/ROW]
[ROW][C]200[/C][C]18.2[/C][C]17.6718[/C][C]0.528206[/C][/ROW]
[ROW][C]201[/C][C]13.6[/C][C]13.3712[/C][C]0.228769[/C][/ROW]
[ROW][C]202[/C][C]14.85[/C][C]12.8025[/C][C]2.04747[/C][/ROW]
[ROW][C]203[/C][C]14.75[/C][C]12.7425[/C][C]2.00746[/C][/ROW]
[ROW][C]204[/C][C]14.1[/C][C]11.8524[/C][C]2.24762[/C][/ROW]
[ROW][C]205[/C][C]14.9[/C][C]12.0358[/C][C]2.86423[/C][/ROW]
[ROW][C]206[/C][C]16.25[/C][C]12.9049[/C][C]3.34512[/C][/ROW]
[ROW][C]207[/C][C]19.25[/C][C]19.9089[/C][C]-0.658916[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]12.7127[/C][C]0.887329[/C][/ROW]
[ROW][C]209[/C][C]13.6[/C][C]10.3911[/C][C]3.20894[/C][/ROW]
[ROW][C]210[/C][C]15.65[/C][C]14.9346[/C][C]0.715363[/C][/ROW]
[ROW][C]211[/C][C]12.75[/C][C]10.7493[/C][C]2.00072[/C][/ROW]
[ROW][C]212[/C][C]14.6[/C][C]17.1452[/C][C]-2.54517[/C][/ROW]
[ROW][C]213[/C][C]9.85[/C][C]11.0679[/C][C]-1.21793[/C][/ROW]
[ROW][C]214[/C][C]12.65[/C][C]13.4837[/C][C]-0.833656[/C][/ROW]
[ROW][C]215[/C][C]11.9[/C][C]3.79309[/C][C]8.10691[/C][/ROW]
[ROW][C]216[/C][C]19.2[/C][C]14.8088[/C][C]4.39116[/C][/ROW]
[ROW][C]217[/C][C]16.6[/C][C]18.6194[/C][C]-2.01935[/C][/ROW]
[ROW][C]218[/C][C]11.2[/C][C]8.80489[/C][C]2.39511[/C][/ROW]
[ROW][C]219[/C][C]15.25[/C][C]15.4348[/C][C]-0.184812[/C][/ROW]
[ROW][C]220[/C][C]11.9[/C][C]10.7717[/C][C]1.12825[/C][/ROW]
[ROW][C]221[/C][C]13.2[/C][C]9.48859[/C][C]3.71141[/C][/ROW]
[ROW][C]222[/C][C]16.35[/C][C]17.047[/C][C]-0.696986[/C][/ROW]
[ROW][C]223[/C][C]12.4[/C][C]9.3424[/C][C]3.0576[/C][/ROW]
[ROW][C]224[/C][C]15.85[/C][C]14.8252[/C][C]1.02479[/C][/ROW]
[ROW][C]225[/C][C]14.35[/C][C]9.16408[/C][C]5.18592[/C][/ROW]
[ROW][C]226[/C][C]18.15[/C][C]19.7866[/C][C]-1.6366[/C][/ROW]
[ROW][C]227[/C][C]11.15[/C][C]8.94964[/C][C]2.20036[/C][/ROW]
[ROW][C]228[/C][C]15.65[/C][C]10.0409[/C][C]5.6091[/C][/ROW]
[ROW][C]229[/C][C]17.75[/C][C]22.2019[/C][C]-4.45193[/C][/ROW]
[ROW][C]230[/C][C]7.65[/C][C]9.17426[/C][C]-1.52426[/C][/ROW]
[ROW][C]231[/C][C]12.35[/C][C]8.92074[/C][C]3.42926[/C][/ROW]
[ROW][C]232[/C][C]15.6[/C][C]8.84333[/C][C]6.75667[/C][/ROW]
[ROW][C]233[/C][C]19.3[/C][C]17.17[/C][C]2.13001[/C][/ROW]
[ROW][C]234[/C][C]15.2[/C][C]11.0921[/C][C]4.10794[/C][/ROW]
[ROW][C]235[/C][C]17.1[/C][C]14.4701[/C][C]2.62986[/C][/ROW]
[ROW][C]236[/C][C]15.6[/C][C]9.98088[/C][C]5.61912[/C][/ROW]
[ROW][C]237[/C][C]18.4[/C][C]12.0826[/C][C]6.31742[/C][/ROW]
[ROW][C]238[/C][C]19.05[/C][C]12.709[/C][C]6.341[/C][/ROW]
[ROW][C]239[/C][C]18.55[/C][C]12.5802[/C][C]5.96985[/C][/ROW]
[ROW][C]240[/C][C]19.1[/C][C]18.5767[/C][C]0.523297[/C][/ROW]
[ROW][C]241[/C][C]13.1[/C][C]12.6401[/C][C]0.459895[/C][/ROW]
[ROW][C]242[/C][C]12.85[/C][C]15.2654[/C][C]-2.41541[/C][/ROW]
[ROW][C]243[/C][C]9.5[/C][C]18.5679[/C][C]-9.06789[/C][/ROW]
[ROW][C]244[/C][C]4.5[/C][C]5.29658[/C][C]-0.796581[/C][/ROW]
[ROW][C]245[/C][C]11.85[/C][C]10.6403[/C][C]1.20968[/C][/ROW]
[ROW][C]246[/C][C]13.6[/C][C]15.4342[/C][C]-1.83419[/C][/ROW]
[ROW][C]247[/C][C]11.7[/C][C]11.9928[/C][C]-0.292758[/C][/ROW]
[ROW][C]248[/C][C]12.4[/C][C]12.4129[/C][C]-0.0128525[/C][/ROW]
[ROW][C]249[/C][C]13.35[/C][C]13.4689[/C][C]-0.118891[/C][/ROW]
[ROW][C]250[/C][C]11.4[/C][C]9.61923[/C][C]1.78077[/C][/ROW]
[ROW][C]251[/C][C]14.9[/C][C]8.68087[/C][C]6.21913[/C][/ROW]
[ROW][C]252[/C][C]19.9[/C][C]15.6297[/C][C]4.27031[/C][/ROW]
[ROW][C]253[/C][C]17.75[/C][C]20.1087[/C][C]-2.35869[/C][/ROW]
[ROW][C]254[/C][C]11.2[/C][C]9.01329[/C][C]2.18671[/C][/ROW]
[ROW][C]255[/C][C]14.6[/C][C]10.0609[/C][C]4.53913[/C][/ROW]
[ROW][C]256[/C][C]17.6[/C][C]16.5528[/C][C]1.04722[/C][/ROW]
[ROW][C]257[/C][C]14.05[/C][C]11.0734[/C][C]2.97664[/C][/ROW]
[ROW][C]258[/C][C]16.1[/C][C]15.6961[/C][C]0.403902[/C][/ROW]
[ROW][C]259[/C][C]13.35[/C][C]14.2648[/C][C]-0.914758[/C][/ROW]
[ROW][C]260[/C][C]11.85[/C][C]12.5064[/C][C]-0.656412[/C][/ROW]
[ROW][C]261[/C][C]11.95[/C][C]10.1459[/C][C]1.80411[/C][/ROW]
[ROW][C]262[/C][C]14.75[/C][C]11.8694[/C][C]2.88061[/C][/ROW]
[ROW][C]263[/C][C]15.15[/C][C]15.051[/C][C]0.0990368[/C][/ROW]
[ROW][C]264[/C][C]13.2[/C][C]9.74369[/C][C]3.45631[/C][/ROW]
[ROW][C]265[/C][C]16.85[/C][C]21.5835[/C][C]-4.73349[/C][/ROW]
[ROW][C]266[/C][C]7.85[/C][C]12.5224[/C][C]-4.67239[/C][/ROW]
[ROW][C]267[/C][C]7.7[/C][C]7.50416[/C][C]0.195836[/C][/ROW]
[ROW][C]268[/C][C]12.6[/C][C]17.7958[/C][C]-5.19582[/C][/ROW]
[ROW][C]269[/C][C]7.85[/C][C]10.9685[/C][C]-3.11845[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]11.4328[/C][C]-0.482836[/C][/ROW]
[ROW][C]271[/C][C]12.35[/C][C]15.3226[/C][C]-2.97265[/C][/ROW]
[ROW][C]272[/C][C]9.95[/C][C]8.28448[/C][C]1.66552[/C][/ROW]
[ROW][C]273[/C][C]14.9[/C][C]11.0367[/C][C]3.86332[/C][/ROW]
[ROW][C]274[/C][C]16.65[/C][C]16.8268[/C][C]-0.17675[/C][/ROW]
[ROW][C]275[/C][C]13.4[/C][C]12.8462[/C][C]0.553785[/C][/ROW]
[ROW][C]276[/C][C]13.95[/C][C]10.3842[/C][C]3.56582[/C][/ROW]
[ROW][C]277[/C][C]15.7[/C][C]12.401[/C][C]3.29896[/C][/ROW]
[ROW][C]278[/C][C]16.85[/C][C]18.9332[/C][C]-2.08323[/C][/ROW]
[ROW][C]279[/C][C]10.95[/C][C]7.89812[/C][C]3.05188[/C][/ROW]
[ROW][C]280[/C][C]15.35[/C][C]15.6402[/C][C]-0.290224[/C][/ROW]
[ROW][C]281[/C][C]12.2[/C][C]8.73102[/C][C]3.46898[/C][/ROW]
[ROW][C]282[/C][C]15.1[/C][C]10.5314[/C][C]4.56862[/C][/ROW]
[ROW][C]283[/C][C]17.75[/C][C]15.6753[/C][C]2.07471[/C][/ROW]
[ROW][C]284[/C][C]15.2[/C][C]14.1646[/C][C]1.03538[/C][/ROW]
[ROW][C]285[/C][C]14.6[/C][C]10.7458[/C][C]3.8542[/C][/ROW]
[ROW][C]286[/C][C]16.65[/C][C]21.5659[/C][C]-4.9159[/C][/ROW]
[ROW][C]287[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269817&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269817&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
112.913.347-0.446978
27.413.0831-5.68312
312.213.3636-1.16358
412.813.4073-0.607271
57.412.79-5.38995
66.713.6047-6.90466
712.612.46820.131811
814.812.43622.3638
913.313.6717-0.371744
1011.112.5389-1.43894
118.214.6785-6.47854
1211.412.9268-1.52684
136.413.0604-6.66035
1410.612.1208-1.52077
151212.5154-0.515416
166.312.5607-6.26066
1711.312.4343-1.13435
1811.912.6704-0.770359
199.312.7768-3.47675
209.613.3445-3.74453
211012.1432-2.14317
226.412.6257-6.22567
2313.813.11940.680636
2410.812.7598-1.95977
2513.812.49641.30364
2611.713.3006-1.60063
2710.911.9985-1.09854
2816.113.45782.64223
2913.413.17020.22981
309.913.2686-3.36859
3111.512.0336-0.533643
328.311.859-3.55896
3311.713.2433-1.54334
346.112.4563-6.35625
35912.933-3.93303
369.712.3629-2.66292
3710.812.7166-1.91659
3810.313.2123-2.91229
3910.412.0807-1.68068
4012.712.7417-0.0416517
419.313.7081-4.40813
4211.812.4862-0.686225
435.913.6386-7.73863
4411.413.4045-2.00448
451312.94190.0581107
4610.812.0914-1.29145
4712.312.3156-0.0156191
4811.313.3608-2.06079
4911.812.9548-1.15482
507.912.8369-4.93691
5112.712.35630.343658
5212.313.2473-0.947259
5311.612.5795-0.979497
546.712.8437-6.1437
5510.912.9898-2.08979
5612.112.841-0.741043
5713.313.17940.120609
5810.113.1543-3.05433
595.712.1156-6.41557
6014.312.51031.78971
61812.1967-4.19666
6213.313.5067-0.206662
639.313.6841-4.38414
6412.512.8949-0.394928
657.612.1156-4.51557
6615.912.92672.9733
679.213.2203-4.02029
689.112.9458-3.84575
6911.112.6407-1.54073
701313.2725-0.272452
7114.512.56221.93776
7212.212.5991-0.399143
7312.313.5918-1.2918
7411.412.9218-1.52184
758.813.4667-4.6667
7614.614.00860.591364
777.313.071-5.77099
7812.611.42051.17951
79NANA0.65213
801313.6331-0.633066
8112.612.6005-0.000508443
8213.215.164-1.96403
839.915.0218-5.12178
847.710.1268-2.42684
8510.59.132651.36735
8613.415.0483-1.64832
8710.919.3237-8.42373
884.36.45193-2.15193
8910.311.8195-1.51955
9011.813.4849-1.68494
9111.212.2925-1.0925
9211.415.8802-4.48019
938.67.764130.835872
9413.213.7892-0.589242
9512.619.526-6.926
965.68.84349-3.24349
979.913.6981-3.79807
988.814.205-5.40504
997.711.6081-3.90813
100915.1337-6.13372
1017.38.94415-1.64415
10211.410.80980.590165
10313.618.4088-4.80881
1047.910.0859-2.18594
10510.712.9106-2.21056
10610.313.4433-3.14328
1078.311.2295-2.92948
1089.68.214721.38528
10914.218.2122-4.01222
1108.57.67950.820496
11113.520.6947-7.19466
1124.911.444-6.54403
1136.49.90418-3.50418
1149.610.883-1.28301
11511.613.5262-1.92617
11611.120.7514-9.65137
1174.354.44705-0.0970491
11812.77.335515.36449
11918.113.32624.77381
12017.8515.28652.56353
12116.617.4006-0.800557
12212.69.439283.16072
12317.111.40575.69432
12419.116.17642.92361
12516.115.57270.527281
12613.358.723874.62613
12718.416.471.93004
12814.717.0449-2.34489
12910.610.52530.0746552
13012.69.058233.54177
13116.215.35060.849358
13213.67.959735.64027
13318.918.13950.760541
13414.113.05961.04043
13514.511.22693.27305
13616.1513.79412.3559
13714.7512.59272.15734
13814.815.0462-0.246202
13912.4513.2799-0.829902
14012.658.469124.18088
14117.3521.4176-4.06757
1428.63.04195.5581
14318.416.27252.12754
14416.117.5707-1.47072
14511.66.360215.23979
14617.7514.32363.42645
14715.2510.02425.22579
14817.6515.0842.56597
14915.612.24813.35195
15016.3512.45983.89019
15117.6517.9996-0.349625
15213.614.7827-1.18275
15311.710.371.33003
15414.3512.10522.24483
15514.7510.15894.59111
15618.2520.4148-2.16482
1579.97.484882.41512
1581611.33494.66512
15918.2514.13024.11982
16016.8515.99830.851705
16114.614.39210.207887
16213.859.054.8
16318.9516.15882.79121
16415.614.88580.714197
16514.8515.583-0.733033
16611.756.701475.04853
16718.4515.43593.01406
16815.911.9163.98404
16917.114.70412.39587
17016.110.60395.49607
17119.921.8999-1.99989
17210.955.408915.54109
17318.4516.50631.94374
17415.113.6751.42497
1751516.7273-1.72726
17611.358.828142.52186
17715.9510.95714.9929
17818.116.81251.28746
17914.612.97011.62986
18015.413.6441.75603
18115.410.19625.20383
18217.617.7065-0.106508
18313.356.521456.82855
18419.116.70182.39818
18515.3520.3003-4.95025
1867.67.71366-0.113664
18713.412.46470.935327
18813.97.824036.07597
18919.116.36942.73059
19015.2515.02920.220784
19112.910.36392.5361
19216.112.17073.92926
19317.3517.4145-0.0644909
19413.1514.3677-1.21771
19512.1512.01330.136747
19612.615.5964-2.99638
19710.357.01493.3351
19815.419.1666-3.76658
1999.64.140795.45921
20018.217.67180.528206
20113.613.37120.228769
20214.8512.80252.04747
20314.7512.74252.00746
20414.111.85242.24762
20514.912.03582.86423
20616.2512.90493.34512
20719.2519.9089-0.658916
20813.612.71270.887329
20913.610.39113.20894
21015.6514.93460.715363
21112.7510.74932.00072
21214.617.1452-2.54517
2139.8511.0679-1.21793
21412.6513.4837-0.833656
21511.93.793098.10691
21619.214.80884.39116
21716.618.6194-2.01935
21811.28.804892.39511
21915.2515.4348-0.184812
22011.910.77171.12825
22113.29.488593.71141
22216.3517.047-0.696986
22312.49.34243.0576
22415.8514.82521.02479
22514.359.164085.18592
22618.1519.7866-1.6366
22711.158.949642.20036
22815.6510.04095.6091
22917.7522.2019-4.45193
2307.659.17426-1.52426
23112.358.920743.42926
23215.68.843336.75667
23319.317.172.13001
23415.211.09214.10794
23517.114.47012.62986
23615.69.980885.61912
23718.412.08266.31742
23819.0512.7096.341
23918.5512.58025.96985
24019.118.57670.523297
24113.112.64010.459895
24212.8515.2654-2.41541
2439.518.5679-9.06789
2444.55.29658-0.796581
24511.8510.64031.20968
24613.615.4342-1.83419
24711.711.9928-0.292758
24812.412.4129-0.0128525
24913.3513.4689-0.118891
25011.49.619231.78077
25114.98.680876.21913
25219.915.62974.27031
25317.7520.1087-2.35869
25411.29.013292.18671
25514.610.06094.53913
25617.616.55281.04722
25714.0511.07342.97664
25816.115.69610.403902
25913.3514.2648-0.914758
26011.8512.5064-0.656412
26111.9510.14591.80411
26214.7511.86942.88061
26315.1515.0510.0990368
26413.29.743693.45631
26516.8521.5835-4.73349
2667.8512.5224-4.67239
2677.77.504160.195836
26812.617.7958-5.19582
2697.8510.9685-3.11845
27010.9511.4328-0.482836
27112.3515.3226-2.97265
2729.958.284481.66552
27314.911.03673.86332
27416.6516.8268-0.17675
27513.412.84620.553785
27613.9510.38423.56582
27715.712.4013.29896
27816.8518.9332-2.08323
27910.957.898123.05188
28015.3515.6402-0.290224
28112.28.731023.46898
28215.110.53144.56862
28317.7515.67532.07471
28415.214.16461.03538
28514.610.74583.8542
28616.6521.5659-4.9159
2878.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.526710.9465790.47329
80.5224650.955070.477535
90.5216480.9567040.478352
100.4706940.9413870.529306
110.3658080.7316170.634192
120.2647720.5295440.735228
130.3100490.6200970.689951
140.2468180.4936370.753182
150.1826280.3652560.817372
160.2169620.4339240.783038
170.160150.32030.83985
180.1130450.2260890.886955
190.08401360.1680270.915986
200.0580040.1160080.941996
210.03858310.07716610.961417
220.05100770.1020150.948992
230.0778640.1557280.922136
240.05520140.1104030.944799
250.05576880.1115380.944231
260.04451080.08902160.955489
270.03070340.06140680.969297
280.0488270.0976540.951173
290.04371830.08743660.956282
300.03226540.06453090.967735
310.02239020.04478030.97761
320.03581470.07162930.964185
330.02727240.05454470.972728
340.07041240.1408250.929588
350.06233920.1246780.937661
360.05013120.1002620.949869
370.03763030.07526060.96237
380.02848380.05696750.971516
390.0210350.04207010.978965
400.01892470.03784930.981075
410.01532520.03065030.984675
420.01093680.02187360.989063
430.02588370.05176740.974116
440.01964390.03928780.980356
450.01647290.03294570.983527
460.01234390.02468790.987656
470.009108030.01821610.990892
480.006917270.01383450.993083
490.005266780.01053360.994733
500.005314290.01062860.994686
510.004786550.009573110.995213
520.003591540.007183090.996408
530.002553280.005106550.997447
540.003956760.007913530.996043
550.00284760.00569520.997152
560.002234120.004468250.997766
570.002277530.004555060.997722
580.001743630.003487260.998256
590.004640530.009281070.995359
600.005647520.0112950.994352
610.005522660.01104530.994477
620.00467030.00934060.99533
630.004238760.008477530.995761
640.003393890.006787770.996606
650.003993120.007986240.996007
660.006996220.01399240.993004
670.006205860.01241170.993794
680.005562850.01112570.994437
690.004273740.008547480.995726
700.003739860.007479710.99626
710.004362010.008724010.995638
720.003369170.006738350.996631
730.002631030.005262060.997369
740.001979440.003958880.998021
750.001981230.003962470.998019
760.002218240.004436470.997782
770.003278520.006557050.996721
780.002751210.005502430.997249
790.002317390.004634780.997683
800.001816990.003633980.998183
810.001603850.003207710.998396
820.001246720.002493440.998753
830.001583420.003166840.998417
840.001243680.002487350.998756
850.001143980.002287960.998856
860.0008640110.001728020.999136
870.004027350.008054690.995973
880.003240740.006481490.996759
890.00259290.00518580.997407
900.002029540.004059090.99797
910.001591250.00318250.998409
920.001704360.003408720.998296
930.001516390.003032790.998484
940.001232670.002465340.998767
950.003318010.006636020.996682
960.002934940.005869890.997065
970.002982380.005964770.997018
980.004081370.008162730.995919
990.004088030.008176070.995912
1000.006482990.0129660.993517
1010.005447860.01089570.994552
1020.005183130.01036630.994817
1030.006475760.01295150.993524
1040.00556190.01112380.994438
1050.004814780.009629560.995185
1060.004984740.009969480.995015
1070.004623760.009247520.995376
1080.004837380.009674770.995163
1090.005296760.01059350.994703
1100.004880480.009760960.99512
1110.01487640.02975270.985124
1120.02854680.05709360.971453
1130.02888420.05776840.971116
1140.02575910.05151820.974241
1150.02327610.04655220.976724
1160.09732350.1946470.902676
1170.08889210.1777840.911108
1180.164330.3286610.83567
1190.249030.498060.75097
1200.2837470.5674930.716253
1210.2688120.5376250.731188
1220.3122540.6245090.687746
1230.4532760.9065520.546724
1240.4799230.9598460.520077
1250.4621410.9242820.537859
1260.5482750.903450.451725
1270.5484020.9031970.451598
1280.5404450.9191110.459555
1290.5195270.9609460.480473
1300.5471520.9056960.452848
1310.5296950.9406090.470305
1320.6407620.7184770.359238
1330.619890.760220.38011
1340.6001580.7996840.399842
1350.6203910.7592190.379609
1360.616830.766340.38317
1370.6128890.7742220.387111
1380.58820.8235990.4118
1390.5649930.8700130.435007
1400.6028530.7942950.397147
1410.6393410.7213170.360659
1420.7151490.5697030.284851
1430.7097090.5805810.290291
1440.6943370.6113260.305663
1450.7490590.5018830.250941
1460.7611880.4776240.238812
1470.8039610.3920770.196039
1480.8003270.3993460.199673
1490.8052260.3895480.194774
1500.8206320.3587360.179368
1510.8013410.3973180.198659
1520.7865720.4268560.213428
1530.7685190.4629620.231481
1540.7553940.4892120.244606
1550.7843140.4313720.215686
1560.7828350.4343290.217165
1570.7732660.4534680.226734
1580.8005980.3988030.199402
1590.8123640.3752710.187636
1600.7922890.4154220.207711
1610.7700260.4599470.229974
1620.7988040.4023930.201196
1630.7918830.4162340.208117
1640.7680270.4639470.231973
1650.7495970.5008060.250403
1660.7824460.4351080.217554
1670.7766780.4466430.223322
1680.7847410.4305180.215259
1690.7705610.4588770.229439
1700.8131880.3736240.186812
1710.8060610.3878790.193939
1720.842210.3155810.15779
1730.8264070.3471850.173593
1740.8066090.3867820.193391
1750.7961030.4077940.203897
1760.7825510.4348980.217449
1770.8085430.3829140.191457
1780.7859490.4281030.214051
1790.7638910.4722170.236109
1800.7414730.5170530.258527
1810.7730740.4538520.226926
1820.7468430.5063140.253157
1830.8219350.356130.178065
1840.807540.384920.19246
1850.8531380.2937240.146862
1860.832360.3352790.16764
1870.8100770.3798450.189923
1880.8557220.2885550.144278
1890.845230.309540.15477
1900.8235360.3529290.176464
1910.8098490.3803030.190151
1920.8141730.3716530.185827
1930.7900280.4199450.209972
1940.7712430.4575140.228757
1950.746330.507340.25367
1960.7496280.5007440.250372
1970.7424730.5150540.257527
1980.7689690.4620630.231031
1990.7988490.4023020.201151
2000.7723820.4552360.227618
2010.7431240.5137530.256876
2020.7187430.5625140.281257
2030.6946360.6107280.305364
2040.6696020.6607960.330398
2050.6520610.6958790.347939
2060.6765610.6468780.323439
2070.6420350.715930.357965
2080.6079060.7841870.392094
2090.5911040.8177920.408896
2100.5594870.8810260.440513
2110.5274340.9451320.472566
2120.5385180.9229640.461482
2130.5040650.9918710.495935
2140.4775320.9550630.522468
2150.5918830.8162350.408117
2160.5960990.8078010.403901
2170.5831490.8337010.416851
2180.5537290.8925410.446271
2190.5231190.9537620.476881
2200.4858130.9716250.514187
2210.4747510.9495010.525249
2220.4408460.8816920.559154
2230.4238320.8476640.576168
2240.3850260.7700530.614974
2250.4135110.8270220.586489
2260.3915110.7830230.608489
2270.3625350.725070.637465
2280.3957990.7915990.604201
2290.4802890.9605790.519711
2300.4485790.8971580.551421
2310.4297320.8594640.570268
2320.5239590.9520820.476041
2330.4912260.9824520.508774
2340.4876630.9753260.512337
2350.4560230.9120450.543977
2360.5022470.9955070.497753
2370.59160.81680.4084
2380.6651340.6697320.334866
2390.7439630.5120750.256037
2400.7044430.5911150.295557
2410.6613440.6773120.338656
2420.6513130.6973730.348687
2430.9089520.1820960.0910482
2440.8915550.2168890.108445
2450.8659830.2680340.134017
2460.8485340.3029320.151466
2470.8232670.3534660.176733
2480.7940850.4118310.205915
2490.7542790.4914420.245721
2500.7128720.5742560.287128
2510.815940.368120.18406
2520.83390.33220.1661
2530.8135540.3728920.186446
2540.7821240.4357510.217876
2550.8168240.3663520.183176
2560.781210.4375790.21879
2570.7575240.4849530.242476
2580.7074510.5850980.292549
2590.6605770.6788460.339423
2600.6071090.7857830.392891
2610.559390.8812190.44061
2620.6319640.7360710.368036
2630.5901530.8196940.409847
2640.5757440.8485130.424256
2650.6600270.6799460.339973
2660.8831550.233690.116845
2670.8430930.3138140.156907
2680.8822750.2354490.117725
2690.8865820.2268350.113418
2700.8466420.3067170.153358
2710.881850.2362990.11815
2720.8330570.3338850.166943
2730.8030970.3938060.196903
2740.7336880.5326250.266312
2750.640180.7196390.35982
2760.5580080.8839840.441992
2770.4323640.8647270.567636
2780.6717610.6564770.328239
2790.5087790.9824410.491221
2800.3486590.6973190.651341

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.52671 & 0.946579 & 0.47329 \tabularnewline
8 & 0.522465 & 0.95507 & 0.477535 \tabularnewline
9 & 0.521648 & 0.956704 & 0.478352 \tabularnewline
10 & 0.470694 & 0.941387 & 0.529306 \tabularnewline
11 & 0.365808 & 0.731617 & 0.634192 \tabularnewline
12 & 0.264772 & 0.529544 & 0.735228 \tabularnewline
13 & 0.310049 & 0.620097 & 0.689951 \tabularnewline
14 & 0.246818 & 0.493637 & 0.753182 \tabularnewline
15 & 0.182628 & 0.365256 & 0.817372 \tabularnewline
16 & 0.216962 & 0.433924 & 0.783038 \tabularnewline
17 & 0.16015 & 0.3203 & 0.83985 \tabularnewline
18 & 0.113045 & 0.226089 & 0.886955 \tabularnewline
19 & 0.0840136 & 0.168027 & 0.915986 \tabularnewline
20 & 0.058004 & 0.116008 & 0.941996 \tabularnewline
21 & 0.0385831 & 0.0771661 & 0.961417 \tabularnewline
22 & 0.0510077 & 0.102015 & 0.948992 \tabularnewline
23 & 0.077864 & 0.155728 & 0.922136 \tabularnewline
24 & 0.0552014 & 0.110403 & 0.944799 \tabularnewline
25 & 0.0557688 & 0.111538 & 0.944231 \tabularnewline
26 & 0.0445108 & 0.0890216 & 0.955489 \tabularnewline
27 & 0.0307034 & 0.0614068 & 0.969297 \tabularnewline
28 & 0.048827 & 0.097654 & 0.951173 \tabularnewline
29 & 0.0437183 & 0.0874366 & 0.956282 \tabularnewline
30 & 0.0322654 & 0.0645309 & 0.967735 \tabularnewline
31 & 0.0223902 & 0.0447803 & 0.97761 \tabularnewline
32 & 0.0358147 & 0.0716293 & 0.964185 \tabularnewline
33 & 0.0272724 & 0.0545447 & 0.972728 \tabularnewline
34 & 0.0704124 & 0.140825 & 0.929588 \tabularnewline
35 & 0.0623392 & 0.124678 & 0.937661 \tabularnewline
36 & 0.0501312 & 0.100262 & 0.949869 \tabularnewline
37 & 0.0376303 & 0.0752606 & 0.96237 \tabularnewline
38 & 0.0284838 & 0.0569675 & 0.971516 \tabularnewline
39 & 0.021035 & 0.0420701 & 0.978965 \tabularnewline
40 & 0.0189247 & 0.0378493 & 0.981075 \tabularnewline
41 & 0.0153252 & 0.0306503 & 0.984675 \tabularnewline
42 & 0.0109368 & 0.0218736 & 0.989063 \tabularnewline
43 & 0.0258837 & 0.0517674 & 0.974116 \tabularnewline
44 & 0.0196439 & 0.0392878 & 0.980356 \tabularnewline
45 & 0.0164729 & 0.0329457 & 0.983527 \tabularnewline
46 & 0.0123439 & 0.0246879 & 0.987656 \tabularnewline
47 & 0.00910803 & 0.0182161 & 0.990892 \tabularnewline
48 & 0.00691727 & 0.0138345 & 0.993083 \tabularnewline
49 & 0.00526678 & 0.0105336 & 0.994733 \tabularnewline
50 & 0.00531429 & 0.0106286 & 0.994686 \tabularnewline
51 & 0.00478655 & 0.00957311 & 0.995213 \tabularnewline
52 & 0.00359154 & 0.00718309 & 0.996408 \tabularnewline
53 & 0.00255328 & 0.00510655 & 0.997447 \tabularnewline
54 & 0.00395676 & 0.00791353 & 0.996043 \tabularnewline
55 & 0.0028476 & 0.0056952 & 0.997152 \tabularnewline
56 & 0.00223412 & 0.00446825 & 0.997766 \tabularnewline
57 & 0.00227753 & 0.00455506 & 0.997722 \tabularnewline
58 & 0.00174363 & 0.00348726 & 0.998256 \tabularnewline
59 & 0.00464053 & 0.00928107 & 0.995359 \tabularnewline
60 & 0.00564752 & 0.011295 & 0.994352 \tabularnewline
61 & 0.00552266 & 0.0110453 & 0.994477 \tabularnewline
62 & 0.0046703 & 0.0093406 & 0.99533 \tabularnewline
63 & 0.00423876 & 0.00847753 & 0.995761 \tabularnewline
64 & 0.00339389 & 0.00678777 & 0.996606 \tabularnewline
65 & 0.00399312 & 0.00798624 & 0.996007 \tabularnewline
66 & 0.00699622 & 0.0139924 & 0.993004 \tabularnewline
67 & 0.00620586 & 0.0124117 & 0.993794 \tabularnewline
68 & 0.00556285 & 0.0111257 & 0.994437 \tabularnewline
69 & 0.00427374 & 0.00854748 & 0.995726 \tabularnewline
70 & 0.00373986 & 0.00747971 & 0.99626 \tabularnewline
71 & 0.00436201 & 0.00872401 & 0.995638 \tabularnewline
72 & 0.00336917 & 0.00673835 & 0.996631 \tabularnewline
73 & 0.00263103 & 0.00526206 & 0.997369 \tabularnewline
74 & 0.00197944 & 0.00395888 & 0.998021 \tabularnewline
75 & 0.00198123 & 0.00396247 & 0.998019 \tabularnewline
76 & 0.00221824 & 0.00443647 & 0.997782 \tabularnewline
77 & 0.00327852 & 0.00655705 & 0.996721 \tabularnewline
78 & 0.00275121 & 0.00550243 & 0.997249 \tabularnewline
79 & 0.00231739 & 0.00463478 & 0.997683 \tabularnewline
80 & 0.00181699 & 0.00363398 & 0.998183 \tabularnewline
81 & 0.00160385 & 0.00320771 & 0.998396 \tabularnewline
82 & 0.00124672 & 0.00249344 & 0.998753 \tabularnewline
83 & 0.00158342 & 0.00316684 & 0.998417 \tabularnewline
84 & 0.00124368 & 0.00248735 & 0.998756 \tabularnewline
85 & 0.00114398 & 0.00228796 & 0.998856 \tabularnewline
86 & 0.000864011 & 0.00172802 & 0.999136 \tabularnewline
87 & 0.00402735 & 0.00805469 & 0.995973 \tabularnewline
88 & 0.00324074 & 0.00648149 & 0.996759 \tabularnewline
89 & 0.0025929 & 0.0051858 & 0.997407 \tabularnewline
90 & 0.00202954 & 0.00405909 & 0.99797 \tabularnewline
91 & 0.00159125 & 0.0031825 & 0.998409 \tabularnewline
92 & 0.00170436 & 0.00340872 & 0.998296 \tabularnewline
93 & 0.00151639 & 0.00303279 & 0.998484 \tabularnewline
94 & 0.00123267 & 0.00246534 & 0.998767 \tabularnewline
95 & 0.00331801 & 0.00663602 & 0.996682 \tabularnewline
96 & 0.00293494 & 0.00586989 & 0.997065 \tabularnewline
97 & 0.00298238 & 0.00596477 & 0.997018 \tabularnewline
98 & 0.00408137 & 0.00816273 & 0.995919 \tabularnewline
99 & 0.00408803 & 0.00817607 & 0.995912 \tabularnewline
100 & 0.00648299 & 0.012966 & 0.993517 \tabularnewline
101 & 0.00544786 & 0.0108957 & 0.994552 \tabularnewline
102 & 0.00518313 & 0.0103663 & 0.994817 \tabularnewline
103 & 0.00647576 & 0.0129515 & 0.993524 \tabularnewline
104 & 0.0055619 & 0.0111238 & 0.994438 \tabularnewline
105 & 0.00481478 & 0.00962956 & 0.995185 \tabularnewline
106 & 0.00498474 & 0.00996948 & 0.995015 \tabularnewline
107 & 0.00462376 & 0.00924752 & 0.995376 \tabularnewline
108 & 0.00483738 & 0.00967477 & 0.995163 \tabularnewline
109 & 0.00529676 & 0.0105935 & 0.994703 \tabularnewline
110 & 0.00488048 & 0.00976096 & 0.99512 \tabularnewline
111 & 0.0148764 & 0.0297527 & 0.985124 \tabularnewline
112 & 0.0285468 & 0.0570936 & 0.971453 \tabularnewline
113 & 0.0288842 & 0.0577684 & 0.971116 \tabularnewline
114 & 0.0257591 & 0.0515182 & 0.974241 \tabularnewline
115 & 0.0232761 & 0.0465522 & 0.976724 \tabularnewline
116 & 0.0973235 & 0.194647 & 0.902676 \tabularnewline
117 & 0.0888921 & 0.177784 & 0.911108 \tabularnewline
118 & 0.16433 & 0.328661 & 0.83567 \tabularnewline
119 & 0.24903 & 0.49806 & 0.75097 \tabularnewline
120 & 0.283747 & 0.567493 & 0.716253 \tabularnewline
121 & 0.268812 & 0.537625 & 0.731188 \tabularnewline
122 & 0.312254 & 0.624509 & 0.687746 \tabularnewline
123 & 0.453276 & 0.906552 & 0.546724 \tabularnewline
124 & 0.479923 & 0.959846 & 0.520077 \tabularnewline
125 & 0.462141 & 0.924282 & 0.537859 \tabularnewline
126 & 0.548275 & 0.90345 & 0.451725 \tabularnewline
127 & 0.548402 & 0.903197 & 0.451598 \tabularnewline
128 & 0.540445 & 0.919111 & 0.459555 \tabularnewline
129 & 0.519527 & 0.960946 & 0.480473 \tabularnewline
130 & 0.547152 & 0.905696 & 0.452848 \tabularnewline
131 & 0.529695 & 0.940609 & 0.470305 \tabularnewline
132 & 0.640762 & 0.718477 & 0.359238 \tabularnewline
133 & 0.61989 & 0.76022 & 0.38011 \tabularnewline
134 & 0.600158 & 0.799684 & 0.399842 \tabularnewline
135 & 0.620391 & 0.759219 & 0.379609 \tabularnewline
136 & 0.61683 & 0.76634 & 0.38317 \tabularnewline
137 & 0.612889 & 0.774222 & 0.387111 \tabularnewline
138 & 0.5882 & 0.823599 & 0.4118 \tabularnewline
139 & 0.564993 & 0.870013 & 0.435007 \tabularnewline
140 & 0.602853 & 0.794295 & 0.397147 \tabularnewline
141 & 0.639341 & 0.721317 & 0.360659 \tabularnewline
142 & 0.715149 & 0.569703 & 0.284851 \tabularnewline
143 & 0.709709 & 0.580581 & 0.290291 \tabularnewline
144 & 0.694337 & 0.611326 & 0.305663 \tabularnewline
145 & 0.749059 & 0.501883 & 0.250941 \tabularnewline
146 & 0.761188 & 0.477624 & 0.238812 \tabularnewline
147 & 0.803961 & 0.392077 & 0.196039 \tabularnewline
148 & 0.800327 & 0.399346 & 0.199673 \tabularnewline
149 & 0.805226 & 0.389548 & 0.194774 \tabularnewline
150 & 0.820632 & 0.358736 & 0.179368 \tabularnewline
151 & 0.801341 & 0.397318 & 0.198659 \tabularnewline
152 & 0.786572 & 0.426856 & 0.213428 \tabularnewline
153 & 0.768519 & 0.462962 & 0.231481 \tabularnewline
154 & 0.755394 & 0.489212 & 0.244606 \tabularnewline
155 & 0.784314 & 0.431372 & 0.215686 \tabularnewline
156 & 0.782835 & 0.434329 & 0.217165 \tabularnewline
157 & 0.773266 & 0.453468 & 0.226734 \tabularnewline
158 & 0.800598 & 0.398803 & 0.199402 \tabularnewline
159 & 0.812364 & 0.375271 & 0.187636 \tabularnewline
160 & 0.792289 & 0.415422 & 0.207711 \tabularnewline
161 & 0.770026 & 0.459947 & 0.229974 \tabularnewline
162 & 0.798804 & 0.402393 & 0.201196 \tabularnewline
163 & 0.791883 & 0.416234 & 0.208117 \tabularnewline
164 & 0.768027 & 0.463947 & 0.231973 \tabularnewline
165 & 0.749597 & 0.500806 & 0.250403 \tabularnewline
166 & 0.782446 & 0.435108 & 0.217554 \tabularnewline
167 & 0.776678 & 0.446643 & 0.223322 \tabularnewline
168 & 0.784741 & 0.430518 & 0.215259 \tabularnewline
169 & 0.770561 & 0.458877 & 0.229439 \tabularnewline
170 & 0.813188 & 0.373624 & 0.186812 \tabularnewline
171 & 0.806061 & 0.387879 & 0.193939 \tabularnewline
172 & 0.84221 & 0.315581 & 0.15779 \tabularnewline
173 & 0.826407 & 0.347185 & 0.173593 \tabularnewline
174 & 0.806609 & 0.386782 & 0.193391 \tabularnewline
175 & 0.796103 & 0.407794 & 0.203897 \tabularnewline
176 & 0.782551 & 0.434898 & 0.217449 \tabularnewline
177 & 0.808543 & 0.382914 & 0.191457 \tabularnewline
178 & 0.785949 & 0.428103 & 0.214051 \tabularnewline
179 & 0.763891 & 0.472217 & 0.236109 \tabularnewline
180 & 0.741473 & 0.517053 & 0.258527 \tabularnewline
181 & 0.773074 & 0.453852 & 0.226926 \tabularnewline
182 & 0.746843 & 0.506314 & 0.253157 \tabularnewline
183 & 0.821935 & 0.35613 & 0.178065 \tabularnewline
184 & 0.80754 & 0.38492 & 0.19246 \tabularnewline
185 & 0.853138 & 0.293724 & 0.146862 \tabularnewline
186 & 0.83236 & 0.335279 & 0.16764 \tabularnewline
187 & 0.810077 & 0.379845 & 0.189923 \tabularnewline
188 & 0.855722 & 0.288555 & 0.144278 \tabularnewline
189 & 0.84523 & 0.30954 & 0.15477 \tabularnewline
190 & 0.823536 & 0.352929 & 0.176464 \tabularnewline
191 & 0.809849 & 0.380303 & 0.190151 \tabularnewline
192 & 0.814173 & 0.371653 & 0.185827 \tabularnewline
193 & 0.790028 & 0.419945 & 0.209972 \tabularnewline
194 & 0.771243 & 0.457514 & 0.228757 \tabularnewline
195 & 0.74633 & 0.50734 & 0.25367 \tabularnewline
196 & 0.749628 & 0.500744 & 0.250372 \tabularnewline
197 & 0.742473 & 0.515054 & 0.257527 \tabularnewline
198 & 0.768969 & 0.462063 & 0.231031 \tabularnewline
199 & 0.798849 & 0.402302 & 0.201151 \tabularnewline
200 & 0.772382 & 0.455236 & 0.227618 \tabularnewline
201 & 0.743124 & 0.513753 & 0.256876 \tabularnewline
202 & 0.718743 & 0.562514 & 0.281257 \tabularnewline
203 & 0.694636 & 0.610728 & 0.305364 \tabularnewline
204 & 0.669602 & 0.660796 & 0.330398 \tabularnewline
205 & 0.652061 & 0.695879 & 0.347939 \tabularnewline
206 & 0.676561 & 0.646878 & 0.323439 \tabularnewline
207 & 0.642035 & 0.71593 & 0.357965 \tabularnewline
208 & 0.607906 & 0.784187 & 0.392094 \tabularnewline
209 & 0.591104 & 0.817792 & 0.408896 \tabularnewline
210 & 0.559487 & 0.881026 & 0.440513 \tabularnewline
211 & 0.527434 & 0.945132 & 0.472566 \tabularnewline
212 & 0.538518 & 0.922964 & 0.461482 \tabularnewline
213 & 0.504065 & 0.991871 & 0.495935 \tabularnewline
214 & 0.477532 & 0.955063 & 0.522468 \tabularnewline
215 & 0.591883 & 0.816235 & 0.408117 \tabularnewline
216 & 0.596099 & 0.807801 & 0.403901 \tabularnewline
217 & 0.583149 & 0.833701 & 0.416851 \tabularnewline
218 & 0.553729 & 0.892541 & 0.446271 \tabularnewline
219 & 0.523119 & 0.953762 & 0.476881 \tabularnewline
220 & 0.485813 & 0.971625 & 0.514187 \tabularnewline
221 & 0.474751 & 0.949501 & 0.525249 \tabularnewline
222 & 0.440846 & 0.881692 & 0.559154 \tabularnewline
223 & 0.423832 & 0.847664 & 0.576168 \tabularnewline
224 & 0.385026 & 0.770053 & 0.614974 \tabularnewline
225 & 0.413511 & 0.827022 & 0.586489 \tabularnewline
226 & 0.391511 & 0.783023 & 0.608489 \tabularnewline
227 & 0.362535 & 0.72507 & 0.637465 \tabularnewline
228 & 0.395799 & 0.791599 & 0.604201 \tabularnewline
229 & 0.480289 & 0.960579 & 0.519711 \tabularnewline
230 & 0.448579 & 0.897158 & 0.551421 \tabularnewline
231 & 0.429732 & 0.859464 & 0.570268 \tabularnewline
232 & 0.523959 & 0.952082 & 0.476041 \tabularnewline
233 & 0.491226 & 0.982452 & 0.508774 \tabularnewline
234 & 0.487663 & 0.975326 & 0.512337 \tabularnewline
235 & 0.456023 & 0.912045 & 0.543977 \tabularnewline
236 & 0.502247 & 0.995507 & 0.497753 \tabularnewline
237 & 0.5916 & 0.8168 & 0.4084 \tabularnewline
238 & 0.665134 & 0.669732 & 0.334866 \tabularnewline
239 & 0.743963 & 0.512075 & 0.256037 \tabularnewline
240 & 0.704443 & 0.591115 & 0.295557 \tabularnewline
241 & 0.661344 & 0.677312 & 0.338656 \tabularnewline
242 & 0.651313 & 0.697373 & 0.348687 \tabularnewline
243 & 0.908952 & 0.182096 & 0.0910482 \tabularnewline
244 & 0.891555 & 0.216889 & 0.108445 \tabularnewline
245 & 0.865983 & 0.268034 & 0.134017 \tabularnewline
246 & 0.848534 & 0.302932 & 0.151466 \tabularnewline
247 & 0.823267 & 0.353466 & 0.176733 \tabularnewline
248 & 0.794085 & 0.411831 & 0.205915 \tabularnewline
249 & 0.754279 & 0.491442 & 0.245721 \tabularnewline
250 & 0.712872 & 0.574256 & 0.287128 \tabularnewline
251 & 0.81594 & 0.36812 & 0.18406 \tabularnewline
252 & 0.8339 & 0.3322 & 0.1661 \tabularnewline
253 & 0.813554 & 0.372892 & 0.186446 \tabularnewline
254 & 0.782124 & 0.435751 & 0.217876 \tabularnewline
255 & 0.816824 & 0.366352 & 0.183176 \tabularnewline
256 & 0.78121 & 0.437579 & 0.21879 \tabularnewline
257 & 0.757524 & 0.484953 & 0.242476 \tabularnewline
258 & 0.707451 & 0.585098 & 0.292549 \tabularnewline
259 & 0.660577 & 0.678846 & 0.339423 \tabularnewline
260 & 0.607109 & 0.785783 & 0.392891 \tabularnewline
261 & 0.55939 & 0.881219 & 0.44061 \tabularnewline
262 & 0.631964 & 0.736071 & 0.368036 \tabularnewline
263 & 0.590153 & 0.819694 & 0.409847 \tabularnewline
264 & 0.575744 & 0.848513 & 0.424256 \tabularnewline
265 & 0.660027 & 0.679946 & 0.339973 \tabularnewline
266 & 0.883155 & 0.23369 & 0.116845 \tabularnewline
267 & 0.843093 & 0.313814 & 0.156907 \tabularnewline
268 & 0.882275 & 0.235449 & 0.117725 \tabularnewline
269 & 0.886582 & 0.226835 & 0.113418 \tabularnewline
270 & 0.846642 & 0.306717 & 0.153358 \tabularnewline
271 & 0.88185 & 0.236299 & 0.11815 \tabularnewline
272 & 0.833057 & 0.333885 & 0.166943 \tabularnewline
273 & 0.803097 & 0.393806 & 0.196903 \tabularnewline
274 & 0.733688 & 0.532625 & 0.266312 \tabularnewline
275 & 0.64018 & 0.719639 & 0.35982 \tabularnewline
276 & 0.558008 & 0.883984 & 0.441992 \tabularnewline
277 & 0.432364 & 0.864727 & 0.567636 \tabularnewline
278 & 0.671761 & 0.656477 & 0.328239 \tabularnewline
279 & 0.508779 & 0.982441 & 0.491221 \tabularnewline
280 & 0.348659 & 0.697319 & 0.651341 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269817&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]7[/C][C]0.52671[/C][C]0.946579[/C][C]0.47329[/C][/ROW]
[ROW][C]8[/C][C]0.522465[/C][C]0.95507[/C][C]0.477535[/C][/ROW]
[ROW][C]9[/C][C]0.521648[/C][C]0.956704[/C][C]0.478352[/C][/ROW]
[ROW][C]10[/C][C]0.470694[/C][C]0.941387[/C][C]0.529306[/C][/ROW]
[ROW][C]11[/C][C]0.365808[/C][C]0.731617[/C][C]0.634192[/C][/ROW]
[ROW][C]12[/C][C]0.264772[/C][C]0.529544[/C][C]0.735228[/C][/ROW]
[ROW][C]13[/C][C]0.310049[/C][C]0.620097[/C][C]0.689951[/C][/ROW]
[ROW][C]14[/C][C]0.246818[/C][C]0.493637[/C][C]0.753182[/C][/ROW]
[ROW][C]15[/C][C]0.182628[/C][C]0.365256[/C][C]0.817372[/C][/ROW]
[ROW][C]16[/C][C]0.216962[/C][C]0.433924[/C][C]0.783038[/C][/ROW]
[ROW][C]17[/C][C]0.16015[/C][C]0.3203[/C][C]0.83985[/C][/ROW]
[ROW][C]18[/C][C]0.113045[/C][C]0.226089[/C][C]0.886955[/C][/ROW]
[ROW][C]19[/C][C]0.0840136[/C][C]0.168027[/C][C]0.915986[/C][/ROW]
[ROW][C]20[/C][C]0.058004[/C][C]0.116008[/C][C]0.941996[/C][/ROW]
[ROW][C]21[/C][C]0.0385831[/C][C]0.0771661[/C][C]0.961417[/C][/ROW]
[ROW][C]22[/C][C]0.0510077[/C][C]0.102015[/C][C]0.948992[/C][/ROW]
[ROW][C]23[/C][C]0.077864[/C][C]0.155728[/C][C]0.922136[/C][/ROW]
[ROW][C]24[/C][C]0.0552014[/C][C]0.110403[/C][C]0.944799[/C][/ROW]
[ROW][C]25[/C][C]0.0557688[/C][C]0.111538[/C][C]0.944231[/C][/ROW]
[ROW][C]26[/C][C]0.0445108[/C][C]0.0890216[/C][C]0.955489[/C][/ROW]
[ROW][C]27[/C][C]0.0307034[/C][C]0.0614068[/C][C]0.969297[/C][/ROW]
[ROW][C]28[/C][C]0.048827[/C][C]0.097654[/C][C]0.951173[/C][/ROW]
[ROW][C]29[/C][C]0.0437183[/C][C]0.0874366[/C][C]0.956282[/C][/ROW]
[ROW][C]30[/C][C]0.0322654[/C][C]0.0645309[/C][C]0.967735[/C][/ROW]
[ROW][C]31[/C][C]0.0223902[/C][C]0.0447803[/C][C]0.97761[/C][/ROW]
[ROW][C]32[/C][C]0.0358147[/C][C]0.0716293[/C][C]0.964185[/C][/ROW]
[ROW][C]33[/C][C]0.0272724[/C][C]0.0545447[/C][C]0.972728[/C][/ROW]
[ROW][C]34[/C][C]0.0704124[/C][C]0.140825[/C][C]0.929588[/C][/ROW]
[ROW][C]35[/C][C]0.0623392[/C][C]0.124678[/C][C]0.937661[/C][/ROW]
[ROW][C]36[/C][C]0.0501312[/C][C]0.100262[/C][C]0.949869[/C][/ROW]
[ROW][C]37[/C][C]0.0376303[/C][C]0.0752606[/C][C]0.96237[/C][/ROW]
[ROW][C]38[/C][C]0.0284838[/C][C]0.0569675[/C][C]0.971516[/C][/ROW]
[ROW][C]39[/C][C]0.021035[/C][C]0.0420701[/C][C]0.978965[/C][/ROW]
[ROW][C]40[/C][C]0.0189247[/C][C]0.0378493[/C][C]0.981075[/C][/ROW]
[ROW][C]41[/C][C]0.0153252[/C][C]0.0306503[/C][C]0.984675[/C][/ROW]
[ROW][C]42[/C][C]0.0109368[/C][C]0.0218736[/C][C]0.989063[/C][/ROW]
[ROW][C]43[/C][C]0.0258837[/C][C]0.0517674[/C][C]0.974116[/C][/ROW]
[ROW][C]44[/C][C]0.0196439[/C][C]0.0392878[/C][C]0.980356[/C][/ROW]
[ROW][C]45[/C][C]0.0164729[/C][C]0.0329457[/C][C]0.983527[/C][/ROW]
[ROW][C]46[/C][C]0.0123439[/C][C]0.0246879[/C][C]0.987656[/C][/ROW]
[ROW][C]47[/C][C]0.00910803[/C][C]0.0182161[/C][C]0.990892[/C][/ROW]
[ROW][C]48[/C][C]0.00691727[/C][C]0.0138345[/C][C]0.993083[/C][/ROW]
[ROW][C]49[/C][C]0.00526678[/C][C]0.0105336[/C][C]0.994733[/C][/ROW]
[ROW][C]50[/C][C]0.00531429[/C][C]0.0106286[/C][C]0.994686[/C][/ROW]
[ROW][C]51[/C][C]0.00478655[/C][C]0.00957311[/C][C]0.995213[/C][/ROW]
[ROW][C]52[/C][C]0.00359154[/C][C]0.00718309[/C][C]0.996408[/C][/ROW]
[ROW][C]53[/C][C]0.00255328[/C][C]0.00510655[/C][C]0.997447[/C][/ROW]
[ROW][C]54[/C][C]0.00395676[/C][C]0.00791353[/C][C]0.996043[/C][/ROW]
[ROW][C]55[/C][C]0.0028476[/C][C]0.0056952[/C][C]0.997152[/C][/ROW]
[ROW][C]56[/C][C]0.00223412[/C][C]0.00446825[/C][C]0.997766[/C][/ROW]
[ROW][C]57[/C][C]0.00227753[/C][C]0.00455506[/C][C]0.997722[/C][/ROW]
[ROW][C]58[/C][C]0.00174363[/C][C]0.00348726[/C][C]0.998256[/C][/ROW]
[ROW][C]59[/C][C]0.00464053[/C][C]0.00928107[/C][C]0.995359[/C][/ROW]
[ROW][C]60[/C][C]0.00564752[/C][C]0.011295[/C][C]0.994352[/C][/ROW]
[ROW][C]61[/C][C]0.00552266[/C][C]0.0110453[/C][C]0.994477[/C][/ROW]
[ROW][C]62[/C][C]0.0046703[/C][C]0.0093406[/C][C]0.99533[/C][/ROW]
[ROW][C]63[/C][C]0.00423876[/C][C]0.00847753[/C][C]0.995761[/C][/ROW]
[ROW][C]64[/C][C]0.00339389[/C][C]0.00678777[/C][C]0.996606[/C][/ROW]
[ROW][C]65[/C][C]0.00399312[/C][C]0.00798624[/C][C]0.996007[/C][/ROW]
[ROW][C]66[/C][C]0.00699622[/C][C]0.0139924[/C][C]0.993004[/C][/ROW]
[ROW][C]67[/C][C]0.00620586[/C][C]0.0124117[/C][C]0.993794[/C][/ROW]
[ROW][C]68[/C][C]0.00556285[/C][C]0.0111257[/C][C]0.994437[/C][/ROW]
[ROW][C]69[/C][C]0.00427374[/C][C]0.00854748[/C][C]0.995726[/C][/ROW]
[ROW][C]70[/C][C]0.00373986[/C][C]0.00747971[/C][C]0.99626[/C][/ROW]
[ROW][C]71[/C][C]0.00436201[/C][C]0.00872401[/C][C]0.995638[/C][/ROW]
[ROW][C]72[/C][C]0.00336917[/C][C]0.00673835[/C][C]0.996631[/C][/ROW]
[ROW][C]73[/C][C]0.00263103[/C][C]0.00526206[/C][C]0.997369[/C][/ROW]
[ROW][C]74[/C][C]0.00197944[/C][C]0.00395888[/C][C]0.998021[/C][/ROW]
[ROW][C]75[/C][C]0.00198123[/C][C]0.00396247[/C][C]0.998019[/C][/ROW]
[ROW][C]76[/C][C]0.00221824[/C][C]0.00443647[/C][C]0.997782[/C][/ROW]
[ROW][C]77[/C][C]0.00327852[/C][C]0.00655705[/C][C]0.996721[/C][/ROW]
[ROW][C]78[/C][C]0.00275121[/C][C]0.00550243[/C][C]0.997249[/C][/ROW]
[ROW][C]79[/C][C]0.00231739[/C][C]0.00463478[/C][C]0.997683[/C][/ROW]
[ROW][C]80[/C][C]0.00181699[/C][C]0.00363398[/C][C]0.998183[/C][/ROW]
[ROW][C]81[/C][C]0.00160385[/C][C]0.00320771[/C][C]0.998396[/C][/ROW]
[ROW][C]82[/C][C]0.00124672[/C][C]0.00249344[/C][C]0.998753[/C][/ROW]
[ROW][C]83[/C][C]0.00158342[/C][C]0.00316684[/C][C]0.998417[/C][/ROW]
[ROW][C]84[/C][C]0.00124368[/C][C]0.00248735[/C][C]0.998756[/C][/ROW]
[ROW][C]85[/C][C]0.00114398[/C][C]0.00228796[/C][C]0.998856[/C][/ROW]
[ROW][C]86[/C][C]0.000864011[/C][C]0.00172802[/C][C]0.999136[/C][/ROW]
[ROW][C]87[/C][C]0.00402735[/C][C]0.00805469[/C][C]0.995973[/C][/ROW]
[ROW][C]88[/C][C]0.00324074[/C][C]0.00648149[/C][C]0.996759[/C][/ROW]
[ROW][C]89[/C][C]0.0025929[/C][C]0.0051858[/C][C]0.997407[/C][/ROW]
[ROW][C]90[/C][C]0.00202954[/C][C]0.00405909[/C][C]0.99797[/C][/ROW]
[ROW][C]91[/C][C]0.00159125[/C][C]0.0031825[/C][C]0.998409[/C][/ROW]
[ROW][C]92[/C][C]0.00170436[/C][C]0.00340872[/C][C]0.998296[/C][/ROW]
[ROW][C]93[/C][C]0.00151639[/C][C]0.00303279[/C][C]0.998484[/C][/ROW]
[ROW][C]94[/C][C]0.00123267[/C][C]0.00246534[/C][C]0.998767[/C][/ROW]
[ROW][C]95[/C][C]0.00331801[/C][C]0.00663602[/C][C]0.996682[/C][/ROW]
[ROW][C]96[/C][C]0.00293494[/C][C]0.00586989[/C][C]0.997065[/C][/ROW]
[ROW][C]97[/C][C]0.00298238[/C][C]0.00596477[/C][C]0.997018[/C][/ROW]
[ROW][C]98[/C][C]0.00408137[/C][C]0.00816273[/C][C]0.995919[/C][/ROW]
[ROW][C]99[/C][C]0.00408803[/C][C]0.00817607[/C][C]0.995912[/C][/ROW]
[ROW][C]100[/C][C]0.00648299[/C][C]0.012966[/C][C]0.993517[/C][/ROW]
[ROW][C]101[/C][C]0.00544786[/C][C]0.0108957[/C][C]0.994552[/C][/ROW]
[ROW][C]102[/C][C]0.00518313[/C][C]0.0103663[/C][C]0.994817[/C][/ROW]
[ROW][C]103[/C][C]0.00647576[/C][C]0.0129515[/C][C]0.993524[/C][/ROW]
[ROW][C]104[/C][C]0.0055619[/C][C]0.0111238[/C][C]0.994438[/C][/ROW]
[ROW][C]105[/C][C]0.00481478[/C][C]0.00962956[/C][C]0.995185[/C][/ROW]
[ROW][C]106[/C][C]0.00498474[/C][C]0.00996948[/C][C]0.995015[/C][/ROW]
[ROW][C]107[/C][C]0.00462376[/C][C]0.00924752[/C][C]0.995376[/C][/ROW]
[ROW][C]108[/C][C]0.00483738[/C][C]0.00967477[/C][C]0.995163[/C][/ROW]
[ROW][C]109[/C][C]0.00529676[/C][C]0.0105935[/C][C]0.994703[/C][/ROW]
[ROW][C]110[/C][C]0.00488048[/C][C]0.00976096[/C][C]0.99512[/C][/ROW]
[ROW][C]111[/C][C]0.0148764[/C][C]0.0297527[/C][C]0.985124[/C][/ROW]
[ROW][C]112[/C][C]0.0285468[/C][C]0.0570936[/C][C]0.971453[/C][/ROW]
[ROW][C]113[/C][C]0.0288842[/C][C]0.0577684[/C][C]0.971116[/C][/ROW]
[ROW][C]114[/C][C]0.0257591[/C][C]0.0515182[/C][C]0.974241[/C][/ROW]
[ROW][C]115[/C][C]0.0232761[/C][C]0.0465522[/C][C]0.976724[/C][/ROW]
[ROW][C]116[/C][C]0.0973235[/C][C]0.194647[/C][C]0.902676[/C][/ROW]
[ROW][C]117[/C][C]0.0888921[/C][C]0.177784[/C][C]0.911108[/C][/ROW]
[ROW][C]118[/C][C]0.16433[/C][C]0.328661[/C][C]0.83567[/C][/ROW]
[ROW][C]119[/C][C]0.24903[/C][C]0.49806[/C][C]0.75097[/C][/ROW]
[ROW][C]120[/C][C]0.283747[/C][C]0.567493[/C][C]0.716253[/C][/ROW]
[ROW][C]121[/C][C]0.268812[/C][C]0.537625[/C][C]0.731188[/C][/ROW]
[ROW][C]122[/C][C]0.312254[/C][C]0.624509[/C][C]0.687746[/C][/ROW]
[ROW][C]123[/C][C]0.453276[/C][C]0.906552[/C][C]0.546724[/C][/ROW]
[ROW][C]124[/C][C]0.479923[/C][C]0.959846[/C][C]0.520077[/C][/ROW]
[ROW][C]125[/C][C]0.462141[/C][C]0.924282[/C][C]0.537859[/C][/ROW]
[ROW][C]126[/C][C]0.548275[/C][C]0.90345[/C][C]0.451725[/C][/ROW]
[ROW][C]127[/C][C]0.548402[/C][C]0.903197[/C][C]0.451598[/C][/ROW]
[ROW][C]128[/C][C]0.540445[/C][C]0.919111[/C][C]0.459555[/C][/ROW]
[ROW][C]129[/C][C]0.519527[/C][C]0.960946[/C][C]0.480473[/C][/ROW]
[ROW][C]130[/C][C]0.547152[/C][C]0.905696[/C][C]0.452848[/C][/ROW]
[ROW][C]131[/C][C]0.529695[/C][C]0.940609[/C][C]0.470305[/C][/ROW]
[ROW][C]132[/C][C]0.640762[/C][C]0.718477[/C][C]0.359238[/C][/ROW]
[ROW][C]133[/C][C]0.61989[/C][C]0.76022[/C][C]0.38011[/C][/ROW]
[ROW][C]134[/C][C]0.600158[/C][C]0.799684[/C][C]0.399842[/C][/ROW]
[ROW][C]135[/C][C]0.620391[/C][C]0.759219[/C][C]0.379609[/C][/ROW]
[ROW][C]136[/C][C]0.61683[/C][C]0.76634[/C][C]0.38317[/C][/ROW]
[ROW][C]137[/C][C]0.612889[/C][C]0.774222[/C][C]0.387111[/C][/ROW]
[ROW][C]138[/C][C]0.5882[/C][C]0.823599[/C][C]0.4118[/C][/ROW]
[ROW][C]139[/C][C]0.564993[/C][C]0.870013[/C][C]0.435007[/C][/ROW]
[ROW][C]140[/C][C]0.602853[/C][C]0.794295[/C][C]0.397147[/C][/ROW]
[ROW][C]141[/C][C]0.639341[/C][C]0.721317[/C][C]0.360659[/C][/ROW]
[ROW][C]142[/C][C]0.715149[/C][C]0.569703[/C][C]0.284851[/C][/ROW]
[ROW][C]143[/C][C]0.709709[/C][C]0.580581[/C][C]0.290291[/C][/ROW]
[ROW][C]144[/C][C]0.694337[/C][C]0.611326[/C][C]0.305663[/C][/ROW]
[ROW][C]145[/C][C]0.749059[/C][C]0.501883[/C][C]0.250941[/C][/ROW]
[ROW][C]146[/C][C]0.761188[/C][C]0.477624[/C][C]0.238812[/C][/ROW]
[ROW][C]147[/C][C]0.803961[/C][C]0.392077[/C][C]0.196039[/C][/ROW]
[ROW][C]148[/C][C]0.800327[/C][C]0.399346[/C][C]0.199673[/C][/ROW]
[ROW][C]149[/C][C]0.805226[/C][C]0.389548[/C][C]0.194774[/C][/ROW]
[ROW][C]150[/C][C]0.820632[/C][C]0.358736[/C][C]0.179368[/C][/ROW]
[ROW][C]151[/C][C]0.801341[/C][C]0.397318[/C][C]0.198659[/C][/ROW]
[ROW][C]152[/C][C]0.786572[/C][C]0.426856[/C][C]0.213428[/C][/ROW]
[ROW][C]153[/C][C]0.768519[/C][C]0.462962[/C][C]0.231481[/C][/ROW]
[ROW][C]154[/C][C]0.755394[/C][C]0.489212[/C][C]0.244606[/C][/ROW]
[ROW][C]155[/C][C]0.784314[/C][C]0.431372[/C][C]0.215686[/C][/ROW]
[ROW][C]156[/C][C]0.782835[/C][C]0.434329[/C][C]0.217165[/C][/ROW]
[ROW][C]157[/C][C]0.773266[/C][C]0.453468[/C][C]0.226734[/C][/ROW]
[ROW][C]158[/C][C]0.800598[/C][C]0.398803[/C][C]0.199402[/C][/ROW]
[ROW][C]159[/C][C]0.812364[/C][C]0.375271[/C][C]0.187636[/C][/ROW]
[ROW][C]160[/C][C]0.792289[/C][C]0.415422[/C][C]0.207711[/C][/ROW]
[ROW][C]161[/C][C]0.770026[/C][C]0.459947[/C][C]0.229974[/C][/ROW]
[ROW][C]162[/C][C]0.798804[/C][C]0.402393[/C][C]0.201196[/C][/ROW]
[ROW][C]163[/C][C]0.791883[/C][C]0.416234[/C][C]0.208117[/C][/ROW]
[ROW][C]164[/C][C]0.768027[/C][C]0.463947[/C][C]0.231973[/C][/ROW]
[ROW][C]165[/C][C]0.749597[/C][C]0.500806[/C][C]0.250403[/C][/ROW]
[ROW][C]166[/C][C]0.782446[/C][C]0.435108[/C][C]0.217554[/C][/ROW]
[ROW][C]167[/C][C]0.776678[/C][C]0.446643[/C][C]0.223322[/C][/ROW]
[ROW][C]168[/C][C]0.784741[/C][C]0.430518[/C][C]0.215259[/C][/ROW]
[ROW][C]169[/C][C]0.770561[/C][C]0.458877[/C][C]0.229439[/C][/ROW]
[ROW][C]170[/C][C]0.813188[/C][C]0.373624[/C][C]0.186812[/C][/ROW]
[ROW][C]171[/C][C]0.806061[/C][C]0.387879[/C][C]0.193939[/C][/ROW]
[ROW][C]172[/C][C]0.84221[/C][C]0.315581[/C][C]0.15779[/C][/ROW]
[ROW][C]173[/C][C]0.826407[/C][C]0.347185[/C][C]0.173593[/C][/ROW]
[ROW][C]174[/C][C]0.806609[/C][C]0.386782[/C][C]0.193391[/C][/ROW]
[ROW][C]175[/C][C]0.796103[/C][C]0.407794[/C][C]0.203897[/C][/ROW]
[ROW][C]176[/C][C]0.782551[/C][C]0.434898[/C][C]0.217449[/C][/ROW]
[ROW][C]177[/C][C]0.808543[/C][C]0.382914[/C][C]0.191457[/C][/ROW]
[ROW][C]178[/C][C]0.785949[/C][C]0.428103[/C][C]0.214051[/C][/ROW]
[ROW][C]179[/C][C]0.763891[/C][C]0.472217[/C][C]0.236109[/C][/ROW]
[ROW][C]180[/C][C]0.741473[/C][C]0.517053[/C][C]0.258527[/C][/ROW]
[ROW][C]181[/C][C]0.773074[/C][C]0.453852[/C][C]0.226926[/C][/ROW]
[ROW][C]182[/C][C]0.746843[/C][C]0.506314[/C][C]0.253157[/C][/ROW]
[ROW][C]183[/C][C]0.821935[/C][C]0.35613[/C][C]0.178065[/C][/ROW]
[ROW][C]184[/C][C]0.80754[/C][C]0.38492[/C][C]0.19246[/C][/ROW]
[ROW][C]185[/C][C]0.853138[/C][C]0.293724[/C][C]0.146862[/C][/ROW]
[ROW][C]186[/C][C]0.83236[/C][C]0.335279[/C][C]0.16764[/C][/ROW]
[ROW][C]187[/C][C]0.810077[/C][C]0.379845[/C][C]0.189923[/C][/ROW]
[ROW][C]188[/C][C]0.855722[/C][C]0.288555[/C][C]0.144278[/C][/ROW]
[ROW][C]189[/C][C]0.84523[/C][C]0.30954[/C][C]0.15477[/C][/ROW]
[ROW][C]190[/C][C]0.823536[/C][C]0.352929[/C][C]0.176464[/C][/ROW]
[ROW][C]191[/C][C]0.809849[/C][C]0.380303[/C][C]0.190151[/C][/ROW]
[ROW][C]192[/C][C]0.814173[/C][C]0.371653[/C][C]0.185827[/C][/ROW]
[ROW][C]193[/C][C]0.790028[/C][C]0.419945[/C][C]0.209972[/C][/ROW]
[ROW][C]194[/C][C]0.771243[/C][C]0.457514[/C][C]0.228757[/C][/ROW]
[ROW][C]195[/C][C]0.74633[/C][C]0.50734[/C][C]0.25367[/C][/ROW]
[ROW][C]196[/C][C]0.749628[/C][C]0.500744[/C][C]0.250372[/C][/ROW]
[ROW][C]197[/C][C]0.742473[/C][C]0.515054[/C][C]0.257527[/C][/ROW]
[ROW][C]198[/C][C]0.768969[/C][C]0.462063[/C][C]0.231031[/C][/ROW]
[ROW][C]199[/C][C]0.798849[/C][C]0.402302[/C][C]0.201151[/C][/ROW]
[ROW][C]200[/C][C]0.772382[/C][C]0.455236[/C][C]0.227618[/C][/ROW]
[ROW][C]201[/C][C]0.743124[/C][C]0.513753[/C][C]0.256876[/C][/ROW]
[ROW][C]202[/C][C]0.718743[/C][C]0.562514[/C][C]0.281257[/C][/ROW]
[ROW][C]203[/C][C]0.694636[/C][C]0.610728[/C][C]0.305364[/C][/ROW]
[ROW][C]204[/C][C]0.669602[/C][C]0.660796[/C][C]0.330398[/C][/ROW]
[ROW][C]205[/C][C]0.652061[/C][C]0.695879[/C][C]0.347939[/C][/ROW]
[ROW][C]206[/C][C]0.676561[/C][C]0.646878[/C][C]0.323439[/C][/ROW]
[ROW][C]207[/C][C]0.642035[/C][C]0.71593[/C][C]0.357965[/C][/ROW]
[ROW][C]208[/C][C]0.607906[/C][C]0.784187[/C][C]0.392094[/C][/ROW]
[ROW][C]209[/C][C]0.591104[/C][C]0.817792[/C][C]0.408896[/C][/ROW]
[ROW][C]210[/C][C]0.559487[/C][C]0.881026[/C][C]0.440513[/C][/ROW]
[ROW][C]211[/C][C]0.527434[/C][C]0.945132[/C][C]0.472566[/C][/ROW]
[ROW][C]212[/C][C]0.538518[/C][C]0.922964[/C][C]0.461482[/C][/ROW]
[ROW][C]213[/C][C]0.504065[/C][C]0.991871[/C][C]0.495935[/C][/ROW]
[ROW][C]214[/C][C]0.477532[/C][C]0.955063[/C][C]0.522468[/C][/ROW]
[ROW][C]215[/C][C]0.591883[/C][C]0.816235[/C][C]0.408117[/C][/ROW]
[ROW][C]216[/C][C]0.596099[/C][C]0.807801[/C][C]0.403901[/C][/ROW]
[ROW][C]217[/C][C]0.583149[/C][C]0.833701[/C][C]0.416851[/C][/ROW]
[ROW][C]218[/C][C]0.553729[/C][C]0.892541[/C][C]0.446271[/C][/ROW]
[ROW][C]219[/C][C]0.523119[/C][C]0.953762[/C][C]0.476881[/C][/ROW]
[ROW][C]220[/C][C]0.485813[/C][C]0.971625[/C][C]0.514187[/C][/ROW]
[ROW][C]221[/C][C]0.474751[/C][C]0.949501[/C][C]0.525249[/C][/ROW]
[ROW][C]222[/C][C]0.440846[/C][C]0.881692[/C][C]0.559154[/C][/ROW]
[ROW][C]223[/C][C]0.423832[/C][C]0.847664[/C][C]0.576168[/C][/ROW]
[ROW][C]224[/C][C]0.385026[/C][C]0.770053[/C][C]0.614974[/C][/ROW]
[ROW][C]225[/C][C]0.413511[/C][C]0.827022[/C][C]0.586489[/C][/ROW]
[ROW][C]226[/C][C]0.391511[/C][C]0.783023[/C][C]0.608489[/C][/ROW]
[ROW][C]227[/C][C]0.362535[/C][C]0.72507[/C][C]0.637465[/C][/ROW]
[ROW][C]228[/C][C]0.395799[/C][C]0.791599[/C][C]0.604201[/C][/ROW]
[ROW][C]229[/C][C]0.480289[/C][C]0.960579[/C][C]0.519711[/C][/ROW]
[ROW][C]230[/C][C]0.448579[/C][C]0.897158[/C][C]0.551421[/C][/ROW]
[ROW][C]231[/C][C]0.429732[/C][C]0.859464[/C][C]0.570268[/C][/ROW]
[ROW][C]232[/C][C]0.523959[/C][C]0.952082[/C][C]0.476041[/C][/ROW]
[ROW][C]233[/C][C]0.491226[/C][C]0.982452[/C][C]0.508774[/C][/ROW]
[ROW][C]234[/C][C]0.487663[/C][C]0.975326[/C][C]0.512337[/C][/ROW]
[ROW][C]235[/C][C]0.456023[/C][C]0.912045[/C][C]0.543977[/C][/ROW]
[ROW][C]236[/C][C]0.502247[/C][C]0.995507[/C][C]0.497753[/C][/ROW]
[ROW][C]237[/C][C]0.5916[/C][C]0.8168[/C][C]0.4084[/C][/ROW]
[ROW][C]238[/C][C]0.665134[/C][C]0.669732[/C][C]0.334866[/C][/ROW]
[ROW][C]239[/C][C]0.743963[/C][C]0.512075[/C][C]0.256037[/C][/ROW]
[ROW][C]240[/C][C]0.704443[/C][C]0.591115[/C][C]0.295557[/C][/ROW]
[ROW][C]241[/C][C]0.661344[/C][C]0.677312[/C][C]0.338656[/C][/ROW]
[ROW][C]242[/C][C]0.651313[/C][C]0.697373[/C][C]0.348687[/C][/ROW]
[ROW][C]243[/C][C]0.908952[/C][C]0.182096[/C][C]0.0910482[/C][/ROW]
[ROW][C]244[/C][C]0.891555[/C][C]0.216889[/C][C]0.108445[/C][/ROW]
[ROW][C]245[/C][C]0.865983[/C][C]0.268034[/C][C]0.134017[/C][/ROW]
[ROW][C]246[/C][C]0.848534[/C][C]0.302932[/C][C]0.151466[/C][/ROW]
[ROW][C]247[/C][C]0.823267[/C][C]0.353466[/C][C]0.176733[/C][/ROW]
[ROW][C]248[/C][C]0.794085[/C][C]0.411831[/C][C]0.205915[/C][/ROW]
[ROW][C]249[/C][C]0.754279[/C][C]0.491442[/C][C]0.245721[/C][/ROW]
[ROW][C]250[/C][C]0.712872[/C][C]0.574256[/C][C]0.287128[/C][/ROW]
[ROW][C]251[/C][C]0.81594[/C][C]0.36812[/C][C]0.18406[/C][/ROW]
[ROW][C]252[/C][C]0.8339[/C][C]0.3322[/C][C]0.1661[/C][/ROW]
[ROW][C]253[/C][C]0.813554[/C][C]0.372892[/C][C]0.186446[/C][/ROW]
[ROW][C]254[/C][C]0.782124[/C][C]0.435751[/C][C]0.217876[/C][/ROW]
[ROW][C]255[/C][C]0.816824[/C][C]0.366352[/C][C]0.183176[/C][/ROW]
[ROW][C]256[/C][C]0.78121[/C][C]0.437579[/C][C]0.21879[/C][/ROW]
[ROW][C]257[/C][C]0.757524[/C][C]0.484953[/C][C]0.242476[/C][/ROW]
[ROW][C]258[/C][C]0.707451[/C][C]0.585098[/C][C]0.292549[/C][/ROW]
[ROW][C]259[/C][C]0.660577[/C][C]0.678846[/C][C]0.339423[/C][/ROW]
[ROW][C]260[/C][C]0.607109[/C][C]0.785783[/C][C]0.392891[/C][/ROW]
[ROW][C]261[/C][C]0.55939[/C][C]0.881219[/C][C]0.44061[/C][/ROW]
[ROW][C]262[/C][C]0.631964[/C][C]0.736071[/C][C]0.368036[/C][/ROW]
[ROW][C]263[/C][C]0.590153[/C][C]0.819694[/C][C]0.409847[/C][/ROW]
[ROW][C]264[/C][C]0.575744[/C][C]0.848513[/C][C]0.424256[/C][/ROW]
[ROW][C]265[/C][C]0.660027[/C][C]0.679946[/C][C]0.339973[/C][/ROW]
[ROW][C]266[/C][C]0.883155[/C][C]0.23369[/C][C]0.116845[/C][/ROW]
[ROW][C]267[/C][C]0.843093[/C][C]0.313814[/C][C]0.156907[/C][/ROW]
[ROW][C]268[/C][C]0.882275[/C][C]0.235449[/C][C]0.117725[/C][/ROW]
[ROW][C]269[/C][C]0.886582[/C][C]0.226835[/C][C]0.113418[/C][/ROW]
[ROW][C]270[/C][C]0.846642[/C][C]0.306717[/C][C]0.153358[/C][/ROW]
[ROW][C]271[/C][C]0.88185[/C][C]0.236299[/C][C]0.11815[/C][/ROW]
[ROW][C]272[/C][C]0.833057[/C][C]0.333885[/C][C]0.166943[/C][/ROW]
[ROW][C]273[/C][C]0.803097[/C][C]0.393806[/C][C]0.196903[/C][/ROW]
[ROW][C]274[/C][C]0.733688[/C][C]0.532625[/C][C]0.266312[/C][/ROW]
[ROW][C]275[/C][C]0.64018[/C][C]0.719639[/C][C]0.35982[/C][/ROW]
[ROW][C]276[/C][C]0.558008[/C][C]0.883984[/C][C]0.441992[/C][/ROW]
[ROW][C]277[/C][C]0.432364[/C][C]0.864727[/C][C]0.567636[/C][/ROW]
[ROW][C]278[/C][C]0.671761[/C][C]0.656477[/C][C]0.328239[/C][/ROW]
[ROW][C]279[/C][C]0.508779[/C][C]0.982441[/C][C]0.491221[/C][/ROW]
[ROW][C]280[/C][C]0.348659[/C][C]0.697319[/C][C]0.651341[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269817&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269817&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
70.526710.9465790.47329
80.5224650.955070.477535
90.5216480.9567040.478352
100.4706940.9413870.529306
110.3658080.7316170.634192
120.2647720.5295440.735228
130.3100490.6200970.689951
140.2468180.4936370.753182
150.1826280.3652560.817372
160.2169620.4339240.783038
170.160150.32030.83985
180.1130450.2260890.886955
190.08401360.1680270.915986
200.0580040.1160080.941996
210.03858310.07716610.961417
220.05100770.1020150.948992
230.0778640.1557280.922136
240.05520140.1104030.944799
250.05576880.1115380.944231
260.04451080.08902160.955489
270.03070340.06140680.969297
280.0488270.0976540.951173
290.04371830.08743660.956282
300.03226540.06453090.967735
310.02239020.04478030.97761
320.03581470.07162930.964185
330.02727240.05454470.972728
340.07041240.1408250.929588
350.06233920.1246780.937661
360.05013120.1002620.949869
370.03763030.07526060.96237
380.02848380.05696750.971516
390.0210350.04207010.978965
400.01892470.03784930.981075
410.01532520.03065030.984675
420.01093680.02187360.989063
430.02588370.05176740.974116
440.01964390.03928780.980356
450.01647290.03294570.983527
460.01234390.02468790.987656
470.009108030.01821610.990892
480.006917270.01383450.993083
490.005266780.01053360.994733
500.005314290.01062860.994686
510.004786550.009573110.995213
520.003591540.007183090.996408
530.002553280.005106550.997447
540.003956760.007913530.996043
550.00284760.00569520.997152
560.002234120.004468250.997766
570.002277530.004555060.997722
580.001743630.003487260.998256
590.004640530.009281070.995359
600.005647520.0112950.994352
610.005522660.01104530.994477
620.00467030.00934060.99533
630.004238760.008477530.995761
640.003393890.006787770.996606
650.003993120.007986240.996007
660.006996220.01399240.993004
670.006205860.01241170.993794
680.005562850.01112570.994437
690.004273740.008547480.995726
700.003739860.007479710.99626
710.004362010.008724010.995638
720.003369170.006738350.996631
730.002631030.005262060.997369
740.001979440.003958880.998021
750.001981230.003962470.998019
760.002218240.004436470.997782
770.003278520.006557050.996721
780.002751210.005502430.997249
790.002317390.004634780.997683
800.001816990.003633980.998183
810.001603850.003207710.998396
820.001246720.002493440.998753
830.001583420.003166840.998417
840.001243680.002487350.998756
850.001143980.002287960.998856
860.0008640110.001728020.999136
870.004027350.008054690.995973
880.003240740.006481490.996759
890.00259290.00518580.997407
900.002029540.004059090.99797
910.001591250.00318250.998409
920.001704360.003408720.998296
930.001516390.003032790.998484
940.001232670.002465340.998767
950.003318010.006636020.996682
960.002934940.005869890.997065
970.002982380.005964770.997018
980.004081370.008162730.995919
990.004088030.008176070.995912
1000.006482990.0129660.993517
1010.005447860.01089570.994552
1020.005183130.01036630.994817
1030.006475760.01295150.993524
1040.00556190.01112380.994438
1050.004814780.009629560.995185
1060.004984740.009969480.995015
1070.004623760.009247520.995376
1080.004837380.009674770.995163
1090.005296760.01059350.994703
1100.004880480.009760960.99512
1110.01487640.02975270.985124
1120.02854680.05709360.971453
1130.02888420.05776840.971116
1140.02575910.05151820.974241
1150.02327610.04655220.976724
1160.09732350.1946470.902676
1170.08889210.1777840.911108
1180.164330.3286610.83567
1190.249030.498060.75097
1200.2837470.5674930.716253
1210.2688120.5376250.731188
1220.3122540.6245090.687746
1230.4532760.9065520.546724
1240.4799230.9598460.520077
1250.4621410.9242820.537859
1260.5482750.903450.451725
1270.5484020.9031970.451598
1280.5404450.9191110.459555
1290.5195270.9609460.480473
1300.5471520.9056960.452848
1310.5296950.9406090.470305
1320.6407620.7184770.359238
1330.619890.760220.38011
1340.6001580.7996840.399842
1350.6203910.7592190.379609
1360.616830.766340.38317
1370.6128890.7742220.387111
1380.58820.8235990.4118
1390.5649930.8700130.435007
1400.6028530.7942950.397147
1410.6393410.7213170.360659
1420.7151490.5697030.284851
1430.7097090.5805810.290291
1440.6943370.6113260.305663
1450.7490590.5018830.250941
1460.7611880.4776240.238812
1470.8039610.3920770.196039
1480.8003270.3993460.199673
1490.8052260.3895480.194774
1500.8206320.3587360.179368
1510.8013410.3973180.198659
1520.7865720.4268560.213428
1530.7685190.4629620.231481
1540.7553940.4892120.244606
1550.7843140.4313720.215686
1560.7828350.4343290.217165
1570.7732660.4534680.226734
1580.8005980.3988030.199402
1590.8123640.3752710.187636
1600.7922890.4154220.207711
1610.7700260.4599470.229974
1620.7988040.4023930.201196
1630.7918830.4162340.208117
1640.7680270.4639470.231973
1650.7495970.5008060.250403
1660.7824460.4351080.217554
1670.7766780.4466430.223322
1680.7847410.4305180.215259
1690.7705610.4588770.229439
1700.8131880.3736240.186812
1710.8060610.3878790.193939
1720.842210.3155810.15779
1730.8264070.3471850.173593
1740.8066090.3867820.193391
1750.7961030.4077940.203897
1760.7825510.4348980.217449
1770.8085430.3829140.191457
1780.7859490.4281030.214051
1790.7638910.4722170.236109
1800.7414730.5170530.258527
1810.7730740.4538520.226926
1820.7468430.5063140.253157
1830.8219350.356130.178065
1840.807540.384920.19246
1850.8531380.2937240.146862
1860.832360.3352790.16764
1870.8100770.3798450.189923
1880.8557220.2885550.144278
1890.845230.309540.15477
1900.8235360.3529290.176464
1910.8098490.3803030.190151
1920.8141730.3716530.185827
1930.7900280.4199450.209972
1940.7712430.4575140.228757
1950.746330.507340.25367
1960.7496280.5007440.250372
1970.7424730.5150540.257527
1980.7689690.4620630.231031
1990.7988490.4023020.201151
2000.7723820.4552360.227618
2010.7431240.5137530.256876
2020.7187430.5625140.281257
2030.6946360.6107280.305364
2040.6696020.6607960.330398
2050.6520610.6958790.347939
2060.6765610.6468780.323439
2070.6420350.715930.357965
2080.6079060.7841870.392094
2090.5911040.8177920.408896
2100.5594870.8810260.440513
2110.5274340.9451320.472566
2120.5385180.9229640.461482
2130.5040650.9918710.495935
2140.4775320.9550630.522468
2150.5918830.8162350.408117
2160.5960990.8078010.403901
2170.5831490.8337010.416851
2180.5537290.8925410.446271
2190.5231190.9537620.476881
2200.4858130.9716250.514187
2210.4747510.9495010.525249
2220.4408460.8816920.559154
2230.4238320.8476640.576168
2240.3850260.7700530.614974
2250.4135110.8270220.586489
2260.3915110.7830230.608489
2270.3625350.725070.637465
2280.3957990.7915990.604201
2290.4802890.9605790.519711
2300.4485790.8971580.551421
2310.4297320.8594640.570268
2320.5239590.9520820.476041
2330.4912260.9824520.508774
2340.4876630.9753260.512337
2350.4560230.9120450.543977
2360.5022470.9955070.497753
2370.59160.81680.4084
2380.6651340.6697320.334866
2390.7439630.5120750.256037
2400.7044430.5911150.295557
2410.6613440.6773120.338656
2420.6513130.6973730.348687
2430.9089520.1820960.0910482
2440.8915550.2168890.108445
2450.8659830.2680340.134017
2460.8485340.3029320.151466
2470.8232670.3534660.176733
2480.7940850.4118310.205915
2490.7542790.4914420.245721
2500.7128720.5742560.287128
2510.815940.368120.18406
2520.83390.33220.1661
2530.8135540.3728920.186446
2540.7821240.4357510.217876
2550.8168240.3663520.183176
2560.781210.4375790.21879
2570.7575240.4849530.242476
2580.7074510.5850980.292549
2590.6605770.6788460.339423
2600.6071090.7857830.392891
2610.559390.8812190.44061
2620.6319640.7360710.368036
2630.5901530.8196940.409847
2640.5757440.8485130.424256
2650.6600270.6799460.339973
2660.8831550.233690.116845
2670.8430930.3138140.156907
2680.8822750.2354490.117725
2690.8865820.2268350.113418
2700.8466420.3067170.153358
2710.881850.2362990.11815
2720.8330570.3338850.166943
2730.8030970.3938060.196903
2740.7336880.5326250.266312
2750.640180.7196390.35982
2760.5580080.8839840.441992
2770.4323640.8647270.567636
2780.6717610.6564770.328239
2790.5087790.9824410.491221
2800.3486590.6973190.651341






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level490.178832NOK
5% type I error level740.270073NOK
10% type I error level880.321168NOK

\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 & 49 & 0.178832 & NOK \tabularnewline
5% type I error level & 74 & 0.270073 & NOK \tabularnewline
10% type I error level & 88 & 0.321168 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269817&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]49[/C][C]0.178832[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]74[/C][C]0.270073[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]88[/C][C]0.321168[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269817&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269817&T=6

As an alternative you can also use a QR Code:  
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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 level490.178832NOK
5% type I error level740.270073NOK
10% type I error level880.321168NOK


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Include Monthly Dummies'
par1 <- '1'
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')
}