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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 computationWed, 17 Dec 2014 11:25:55 +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/17/t14188156861520dfvqbenlkv3.htm/, Retrieved Thu, 16 May 2024 11:59:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270049, Retrieved Thu, 16 May 2024 11:59:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-17 11:25:55] [b22ed12f8980e34362f6926e9ebd1315] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12,9	1	26	50	4
12,2	0	57	62	4
12,8	1	37	54	5
7,4	0	67	71	4
6,7	0	43	54	4
12,6	0	52	65	9
14,8	1	52	73	8
13,3	0	43	52	11
11,1	0	84	84	4
8,2	0	67	42	4
11,4	0	49	66	6
6,4	0	70	65	4
10,6	0	52	78	8
12,0	1	58	73	4
6,3	1	68	75	4
11,3	1	62	72	11
11,9	0	43	66	4
9,3	1	56	70	4
9,6	0	56	61	6
10,0	1	74	81	6
6,4	0	65	71	4
13,8	0	63	69	8
10,8	1	58	71	5
13,8	0	57	72	4
11,7	0	63	68	9
10,9	0	53	70	4
16,1	0	57	68	7
13,4	1	51	61	10
9,9	0	64	67	4
11,5	1	53	76	4
8,3	1	29	70	7
11,7	1	54	60	12
9,0	0	58	72	7
9,7	0	43	69	5
10,8	0	51	71	8
10,3	0	53	62	5
10,4	1	54	70	4
12,7	0	56	64	9
9,3	0	61	58	7
11,8	1	47	76	4
5,9	0	39	52	4
11,4	0	48	59	4
13,0	0	50	68	4
10,8	0	35	76	4
12,3	0	30	65	7
11,3	1	68	67	4
11,8	0	49	59	7
7,9	0	61	69	4
12,7	1	67	76	4
12,3	0	47	63	4
11,6	0	56	75	4
6,7	0	50	63	8
10,9	0	43	60	4
12,1	0	67	73	4
13,3	0	62	63	4
10,1	0	57	70	4
5,7	1	41	75	7
14,3	0	54	66	12
8,0	1	45	63	4
13,3	0	48	63	4
9,3	0	61	64	4
12,5	1	56	70	5
7,6	1	41	75	15
15,9	0	43	61	5
9,2	1	53	60	10
9,1	0	44	62	9
11,1	1	66	73	8
13,0	0	58	61	4
14,5	0	46	66	5
12,2	1	37	64	4
12,3	1	51	59	9
11,4	1	51	64	4
8,8	1	56	60	10
14,6	0	66	56	4
12,6	1	37	78	4
13,0	1	42	67	7
12,6	0	38	59	5
13,2	1	66	66	4
9,9	1	34	68	4
7,7	0	53	71	4
10,5	1	49	66	4
13,4	1	55	73	4
10,9	1	49	72	4
4,3	0	59	71	6
10,3	1	40	59	10
11,8	0	58	64	7
11,2	0	60	66	4
11,4	1	63	78	4
8,6	1	56	68	7
13,2	1	54	73	4
12,6	0	52	62	8
5,6	0	34	65	11
9,9	0	69	68	6
8,8	1	32	65	14
7,7	0	48	60	5
9,0	1	67	71	4
7,3	0	58	65	8
11,4	0	57	68	9
13,6	0	42	64	4
7,9	0	64	74	4
10,7	0	58	69	5
10,3	1	66	76	4
8,3	0	26	68	5
9,6	0	61	72	4
14,2	0	52	67	4
8,5	1	51	63	7
13,5	1	55	59	10
4,9	1	50	73	4
6,4	1	60	66	5
9,6	1	56	62	4
11,6	1	63	69	4
11,1	0	61	66	4
4,35	0	52	51	6
12,7	0	16	56	4
18,1	0	46	67	8
17,85	0	56	69	5
16,6	1	52	57	4
12,6	0	55	56	17
17,1	0	50	55	4
19,1	1	59	63	4
16,1	0	60	67	8
13,35	1	52	65	4
18,4	1	44	47	7
14,7	0	67	76	4
10,6	0	52	64	4
12,6	0	55	68	5
16,2	0	37	64	7
13,6	0	54	65	4
18,9	0	72	71	4
14,1	0	51	63	7
14,5	0	48	60	11
16,15	1	60	68	7
14,75	0	50	72	4
14,8	0	63	70	4
12,45	0	33	61	4
12,65	0	67	61	4
17,35	0	46	62	4
8,6	0	54	71	4
18,4	1	59	71	6
16,1	0	61	51	8
11,6	0	33	56	23
17,75	0	47	70	4
15,25	0	69	73	8
17,65	0	52	76	6
16,35	1	55	68	4
17,65	1	41	48	7
13,6	0	73	52	4
14,35	1	52	60	4
14,75	1	50	59	4
18,25	0	51	57	10
9,9	1	60	79	6
16	0	56	60	5
18,25	0	56	60	5
16,85	1	29	59	4
14,6	0	66	62	4
13,85	0	66	59	5
18,95	0	73	61	5
15,6	1	55	71	5
14,85	1	64	57	5
11,75	1	40	66	4
18,45	1	46	63	6
15,9	0	58	69	4
17,1	1	43	58	4
16,1	0	61	59	4
19,9	1	51	48	9
10,95	0	50	66	18
18,45	1	52	73	6
15,1	0	54	67	5
15	1	66	61	4
11,35	1	61	68	11
15,95	0	80	75	4
18,1	1	51	62	10
14,6	0	56	69	6
15,4	0	56	58	8
15,4	0	56	60	8
17,6	0	53	74	6
13,35	0	47	55	8
19,1	1	25	62	4
15,35	0	47	63	4
7,6	1	46	69	9
13,4	1	50	58	9
13,9	1	39	58	5
19,1	0	51	68	4
15,25	1	58	72	4
12,9	0	35	62	15
16,1	1	58	62	10
17,35	1	60	65	9
13,15	1	62	69	7
12,15	1	63	66	9
12,6	0	53	72	6
10,35	0	46	62	4
15,4	0	67	75	7
9,6	0	59	58	4
18,2	1	64	66	7
13,6	1	38	55	4
14,85	0	50	47	15
14,75	1	48	72	4
14,1	1	48	62	9
14,9	1	47	64	4
16,25	1	66	64	4
19,25	0	47	19	28
13,6	0	63	50	4
13,6	1	58	68	4
15,65	1	44	70	4
12,75	0	51	79	5
14,6	1	43	69	4
9,85	0	55	71	4
12,65	0	38	48	12
19,2	1	45	73	4
16,6	0	50	74	6
11,2	0	54	66	6
15,25	0	57	71	5
11,9	1	60	74	4
13,2	1	55	78	4
16,35	1	56	75	4
12,4	0	49	53	10
15,85	0	37	60	7
18,15	0	59	70	4
11,15	0	46	69	7
15,65	1	51	65	4
17,75	1	58	78	4
7,65	1	64	78	12
12,35	0	53	59	5
15,6	0	48	72	8
19,3	1	51	70	6
15,2	1	47	63	17
17,1	1	59	63	4
15,6	0	62	71	5
18,4	0	62	74	4
19,05	1	51	67	5
18,55	1	64	66	5
19,1	1	52	62	6
13,1	0	67	80	4
12,85	0	50	73	4
9,5	0	54	67	4
4,5	0	58	61	6
11,85	1	56	73	8
13,6	0	63	74	10
11,7	0	31	32	4
12,4	0	65	69	5
13,35	1	71	69	4
11,4	1	50	84	4
14,9	0	57	64	4
19,9	1	47	58	16
11,2	0	47	59	7
14,6	0	57	78	4
17,6	1	43	57	4
14,05	0	41	60	14
16,1	1	63	68	5
13,35	0	63	68	5
11,85	0	56	73	5
11,95	1	51	69	5
14,75	0	50	67	7
15,15	1	22	60	19
13,2	0	41	65	16
16,85	1	59	66	4
7,85	0	56	74	4
7,7	1	66	81	7
12,6	1	53	72	9
7,85	0	42	55	5
10,95	0	52	49	14
12,35	1	54	74	4
9,95	0	44	53	16
14,9	0	62	64	10
16,65	1	53	65	5
13,4	0	50	57	6
13,95	1	36	51	4
15,7	1	76	80	4
16,85	0	66	67	4
10,95	0	62	70	5
15,35	1	59	74	4
12,2	0	47	75	4
15,1	1	55	70	5
17,75	1	58	69	4
15,2	0	60	65	4
14,6	1	44	55	5
16,65	1	57	71	8
8,1	0	45	65	15

Tables (Output of Computation)





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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270049&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270049&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270049&T=0

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


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

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






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 16.0154 + 1.09324gender_N[t] + 0.0264813AMS.I[t] -0.0724143AMS.E[t] -0.0275476AMS.A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  16.0154 +  1.09324gender_N[t] +  0.0264813AMS.I[t] -0.0724143AMS.E[t] -0.0275476AMS.A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270049&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  16.0154 +  1.09324gender_N[t] +  0.0264813AMS.I[t] -0.0724143AMS.E[t] -0.0275476AMS.A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270049&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270049&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[t] = + 16.0154 + 1.09324gender_N[t] + 0.0264813AMS.I[t] -0.0724143AMS.E[t] -0.0275476AMS.A[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)16.01541.989558.052.57044e-141.28522e-14
gender_N1.093240.4122782.6520.008476860.00423843
AMS.I0.02648130.02113951.2530.2113880.105694
AMS.E-0.07241430.0277697-2.6080.009617620.00480881
AMS.A-0.02754760.0618973-0.44510.6566340.328317

\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) & 16.0154 & 1.98955 & 8.05 & 2.57044e-14 & 1.28522e-14 \tabularnewline
gender_N & 1.09324 & 0.412278 & 2.652 & 0.00847686 & 0.00423843 \tabularnewline
AMS.I & 0.0264813 & 0.0211395 & 1.253 & 0.211388 & 0.105694 \tabularnewline
AMS.E & -0.0724143 & 0.0277697 & -2.608 & 0.00961762 & 0.00480881 \tabularnewline
AMS.A & -0.0275476 & 0.0618973 & -0.4451 & 0.656634 & 0.328317 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270049&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]16.0154[/C][C]1.98955[/C][C]8.05[/C][C]2.57044e-14[/C][C]1.28522e-14[/C][/ROW]
[ROW][C]gender_N[/C][C]1.09324[/C][C]0.412278[/C][C]2.652[/C][C]0.00847686[/C][C]0.00423843[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.0264813[/C][C]0.0211395[/C][C]1.253[/C][C]0.211388[/C][C]0.105694[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0724143[/C][C]0.0277697[/C][C]-2.608[/C][C]0.00961762[/C][C]0.00480881[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0275476[/C][C]0.0618973[/C][C]-0.4451[/C][C]0.656634[/C][C]0.328317[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270049&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270049&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)16.01541.989558.052.57044e-141.28522e-14
gender_N1.093240.4122782.6520.008476860.00423843
AMS.I0.02648130.02113951.2530.2113880.105694
AMS.E-0.07241430.0277697-2.6080.009617620.00480881
AMS.A-0.02754760.0618973-0.44510.6566340.328317






Multiple Linear Regression - Regression Statistics
Multiple R0.204885
R-squared0.0419778
Adjusted R-squared0.0279408
F-TEST (value)2.99052
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value0.0193098
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.3466
Sum Squared Residuals3057.53

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.204885 \tabularnewline
R-squared & 0.0419778 \tabularnewline
Adjusted R-squared & 0.0279408 \tabularnewline
F-TEST (value) & 2.99052 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 273 \tabularnewline
p-value & 0.0193098 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.3466 \tabularnewline
Sum Squared Residuals & 3057.53 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270049&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.204885[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0419778[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0279408[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]2.99052[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]273[/C][/ROW]
[ROW][C]p-value[/C][C]0.0193098[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.3466[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3057.53[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270049&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270049&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 R0.204885
R-squared0.0419778
Adjusted R-squared0.0279408
F-TEST (value)2.99052
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value0.0193098
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.3466
Sum Squared Residuals3057.53






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.0663-1.16626
212.212.925-0.724964
312.814.0403-1.24035
47.412.538-5.13805
56.713.1335-6.43354
612.612.43760.162423
714.812.97911.82095
813.313.08550.214465
911.112.0468-0.946846
108.214.6381-6.43806
1111.412.3684-0.968361
126.413.052-6.65198
1310.611.5237-0.923739
141213.2481-1.24813
156.313.3681-7.06812
1611.313.2336-1.93364
1711.912.2646-0.364569
189.313.4124-4.11241
199.612.9158-3.3158
201013.0374-3.03742
216.412.4851-6.08509
2213.812.46681.33324
2310.813.3654-2.56541
2413.812.20081.59918
2511.712.5116-0.811629
2610.912.2397-1.33972
2716.112.40783.69216
2813.413.7664-0.366447
299.912.7483-2.84826
3011.512.8985-1.39848
318.312.6148-4.31477
3211.713.8632-2.16321
33912.1447-3.14466
349.712.0198-2.31978
3510.812.0042-1.20416
3610.312.7915-2.49149
3710.413.3594-2.95945
3812.712.61590.0840836
399.313.2379-3.9379
4011.812.7396-0.939593
415.913.1724-7.27244
4211.412.9039-1.50388
431312.30510.694891
4410.811.3286-0.528575
4512.311.91010.389917
4611.313.9474-2.64743
4711.812.8477-1.04771
487.912.524-4.62399
4912.713.2692-0.56922
5012.312.5877-0.287737
5111.611.9571-0.357097
526.712.557-5.85699
5310.912.6991-1.79905
5412.112.3932-0.293221
5513.312.9850.315043
5610.112.3457-2.24565
575.712.5705-6.87048
5814.312.33551.96452
59813.628-5.62802
6013.312.61420.685782
619.312.8861-3.58606
6212.513.3849-0.884863
637.612.3501-4.7501
6415.912.59913.30091
659.213.8918-4.69182
669.112.443-3.34297
6711.113.3498-2.24979
681313.0239-0.0238599
6914.512.31652.18354
7012.213.3438-1.14375
7112.313.9388-1.63882
7211.413.7145-2.31449
738.813.9713-5.17127
7414.613.59781.00222
7512.612.330.270049
761313.1763-0.176272
7712.612.6115-0.0115142
7813.213.9669-0.766881
799.912.9747-3.07465
807.712.1673-4.46731
8110.513.5167-3.0167
8213.413.16870.231313
8310.913.0822-2.18221
844.312.2711-7.9711
8510.313.62-3.31998
8611.812.724-0.923974
8711.212.7148-1.51475
8811.413.0185-1.61847
898.613.4746-4.8746
9013.213.14220.0577947
9112.612.6824-0.0823672
925.611.9058-6.30582
939.912.7532-2.85316
948.812.8635-4.06345
957.712.8039-5.10391
96913.6313-4.63129
977.312.624-5.32401
9811.412.3527-0.952741
9913.612.38291.21708
1007.912.2414-4.34136
10110.712.417-1.717
10210.313.2427-2.94274
1038.311.642-3.34201
1049.612.3067-2.70675
10514.212.43051.76951
1068.513.7043-5.20426
10713.514.0172-0.517201
1084.913.0363-8.13628
1096.413.7804-7.38045
1109.613.9917-4.39173
11111.613.6702-2.07019
11211.112.7412-1.64123
1134.3513.534-9.18402
11412.712.27370.426285
11518.112.16145.93859
11617.8512.3645.48596
11716.614.24792.35213
11812.612.9484-0.348368
11917.113.24653.85351
12019.113.99885.10125
12116.112.53213.56785
12213.3513.6686-0.318557
12318.414.67753.72248
12414.712.1762.52402
12510.612.6477-2.04773
12612.612.410.190032
12716.212.16794.03213
12813.612.62830.971723
12918.912.67056.22954
13014.112.6111.48898
13114.512.63861.86137
13216.1513.58052.56948
13314.7512.01552.73455
13414.812.50452.29546
13512.4512.36180.0881734
13612.6513.2622-0.612192
13717.3512.63374.71633
1388.612.1938-3.59379
13918.413.36435.03565
14016.113.71732.38274
14111.612.2005-0.600493
14217.7512.08085.66916
14315.2512.3362.91401
14417.6511.72375.92634
14516.3513.53082.81924
14617.6514.52573.12434
14713.614.0728-0.472808
14814.3514.03060.319372
14914.7514.05010.69992
15018.2512.96295.28714
1519.912.8115-2.91151
1521613.01582.98424
15318.2513.01585.23424
15416.8513.4943.35603
15514.613.16331.4367
15613.8513.3530.497008
15718.9513.39355.55647
15815.613.2862.31403
15914.8514.53810.311901
16011.7513.2784-1.52837
16118.4513.59944.8506
16215.912.44453.45545
16317.113.93713.16288
16416.113.24812.85187
16519.914.73545.16462
16610.9512.0643-1.11427
16718.4513.03415.41585
16815.112.45592.6441
1691514.3290.671047
17011.3513.4968-2.14681
17115.9512.59263.35735
17218.113.6944.40597
17314.612.33652.26351
17415.413.07792.32205
17515.412.93312.46688
17617.611.8955.70503
17713.3513.05690.293139
17819.113.17085.9292
17915.3512.58772.76226
1807.613.0823-5.48227
18113.413.9848-0.584756
18213.913.80370.0963481
18319.112.33166.76841
18415.2513.32051.92946
18512.912.03940.860649
18616.113.87942.2206
18717.3513.74273.60733
18813.1513.5611-0.41107
18912.1513.7497-1.5997
19012.612.03980.560199
19110.3512.6337-2.28367
19215.412.16573.23425
1939.613.2676-3.66758
19418.213.83134.36872
19513.614.022-0.421961
19614.8513.52281.32721
19714.7513.05571.69427
19814.113.64210.457864
19914.913.60861.29144
20016.2514.11172.13829
20119.2515.11284.13718
20213.613.9528-0.352824
20313.613.6102-0.010202
20415.6513.09462.55537
20512.7511.50751.24251
20614.613.14061.45943
2079.8512.2203-2.37027
20812.6513.2152-0.565238
20919.212.90396.29613
21016.611.81554.78447
21111.212.5008-1.30077
21215.2512.24573.00431
21311.913.2287-1.32868
21413.212.80660.393385
21516.3513.05033.29966
21612.413.1996-0.799557
21715.8512.45753.39248
21818.1512.39865.75139
21911.1512.0441-0.894127
22015.6513.64212.00792
22117.7512.88614.86394
2227.6512.8246-5.17457
22312.3513.0087-0.658734
22415.611.85233.7477
22519.313.22496.07509
22615.213.32291.87714
22717.113.99883.10125
22815.612.37813.22191
22918.412.18846.2116
23019.0513.46975.5803
23118.5513.88644.66363
23219.113.83075.2693
23313.111.88631.21368
23412.8511.9430.906962
2359.512.4834-2.98345
2364.512.9688-8.46876
23711.8513.085-1.23498
23813.612.04961.5504
23911.714.4089-2.70888
24012.412.6024-0.202367
24113.3513.882-0.532045
24211.412.2397-0.839723
24314.912.78012.11986
24419.913.71256.18752
24511.212.7948-1.59475
24614.611.76632.83366
24717.614.00953.59046
24814.0512.37061.67938
24916.113.71512.38494
25013.3512.62180.728181
25111.8512.0744-0.224378
25211.9513.3249-1.37487
25314.7512.29492.45512
25415.1512.8232.32703
25513.211.95341.24655
25616.8513.78153.06849
2577.8512.0295-4.17951
2587.712.798-5.09802
25912.613.0504-0.4504
2607.8513.0071-5.1571
26110.9513.4585-2.50847
26212.3513.0698-0.719791
2639.9512.9019-2.95186
26414.912.74732.15274
26516.6513.66752.98251
26613.413.04660.353429
26713.9514.2587-0.308655
26815.713.21792.48211
26916.8512.80124.04878
27010.9512.4505-1.50051
27115.3513.20222.1478
27212.211.71880.481235
27315.113.35841.74162
27417.7513.53784.21221
27515.212.78722.41283
27614.614.15330.446699
27716.6513.25633.39371
2788.112.0869-3.98692

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 14.0663 & -1.16626 \tabularnewline
2 & 12.2 & 12.925 & -0.724964 \tabularnewline
3 & 12.8 & 14.0403 & -1.24035 \tabularnewline
4 & 7.4 & 12.538 & -5.13805 \tabularnewline
5 & 6.7 & 13.1335 & -6.43354 \tabularnewline
6 & 12.6 & 12.4376 & 0.162423 \tabularnewline
7 & 14.8 & 12.9791 & 1.82095 \tabularnewline
8 & 13.3 & 13.0855 & 0.214465 \tabularnewline
9 & 11.1 & 12.0468 & -0.946846 \tabularnewline
10 & 8.2 & 14.6381 & -6.43806 \tabularnewline
11 & 11.4 & 12.3684 & -0.968361 \tabularnewline
12 & 6.4 & 13.052 & -6.65198 \tabularnewline
13 & 10.6 & 11.5237 & -0.923739 \tabularnewline
14 & 12 & 13.2481 & -1.24813 \tabularnewline
15 & 6.3 & 13.3681 & -7.06812 \tabularnewline
16 & 11.3 & 13.2336 & -1.93364 \tabularnewline
17 & 11.9 & 12.2646 & -0.364569 \tabularnewline
18 & 9.3 & 13.4124 & -4.11241 \tabularnewline
19 & 9.6 & 12.9158 & -3.3158 \tabularnewline
20 & 10 & 13.0374 & -3.03742 \tabularnewline
21 & 6.4 & 12.4851 & -6.08509 \tabularnewline
22 & 13.8 & 12.4668 & 1.33324 \tabularnewline
23 & 10.8 & 13.3654 & -2.56541 \tabularnewline
24 & 13.8 & 12.2008 & 1.59918 \tabularnewline
25 & 11.7 & 12.5116 & -0.811629 \tabularnewline
26 & 10.9 & 12.2397 & -1.33972 \tabularnewline
27 & 16.1 & 12.4078 & 3.69216 \tabularnewline
28 & 13.4 & 13.7664 & -0.366447 \tabularnewline
29 & 9.9 & 12.7483 & -2.84826 \tabularnewline
30 & 11.5 & 12.8985 & -1.39848 \tabularnewline
31 & 8.3 & 12.6148 & -4.31477 \tabularnewline
32 & 11.7 & 13.8632 & -2.16321 \tabularnewline
33 & 9 & 12.1447 & -3.14466 \tabularnewline
34 & 9.7 & 12.0198 & -2.31978 \tabularnewline
35 & 10.8 & 12.0042 & -1.20416 \tabularnewline
36 & 10.3 & 12.7915 & -2.49149 \tabularnewline
37 & 10.4 & 13.3594 & -2.95945 \tabularnewline
38 & 12.7 & 12.6159 & 0.0840836 \tabularnewline
39 & 9.3 & 13.2379 & -3.9379 \tabularnewline
40 & 11.8 & 12.7396 & -0.939593 \tabularnewline
41 & 5.9 & 13.1724 & -7.27244 \tabularnewline
42 & 11.4 & 12.9039 & -1.50388 \tabularnewline
43 & 13 & 12.3051 & 0.694891 \tabularnewline
44 & 10.8 & 11.3286 & -0.528575 \tabularnewline
45 & 12.3 & 11.9101 & 0.389917 \tabularnewline
46 & 11.3 & 13.9474 & -2.64743 \tabularnewline
47 & 11.8 & 12.8477 & -1.04771 \tabularnewline
48 & 7.9 & 12.524 & -4.62399 \tabularnewline
49 & 12.7 & 13.2692 & -0.56922 \tabularnewline
50 & 12.3 & 12.5877 & -0.287737 \tabularnewline
51 & 11.6 & 11.9571 & -0.357097 \tabularnewline
52 & 6.7 & 12.557 & -5.85699 \tabularnewline
53 & 10.9 & 12.6991 & -1.79905 \tabularnewline
54 & 12.1 & 12.3932 & -0.293221 \tabularnewline
55 & 13.3 & 12.985 & 0.315043 \tabularnewline
56 & 10.1 & 12.3457 & -2.24565 \tabularnewline
57 & 5.7 & 12.5705 & -6.87048 \tabularnewline
58 & 14.3 & 12.3355 & 1.96452 \tabularnewline
59 & 8 & 13.628 & -5.62802 \tabularnewline
60 & 13.3 & 12.6142 & 0.685782 \tabularnewline
61 & 9.3 & 12.8861 & -3.58606 \tabularnewline
62 & 12.5 & 13.3849 & -0.884863 \tabularnewline
63 & 7.6 & 12.3501 & -4.7501 \tabularnewline
64 & 15.9 & 12.5991 & 3.30091 \tabularnewline
65 & 9.2 & 13.8918 & -4.69182 \tabularnewline
66 & 9.1 & 12.443 & -3.34297 \tabularnewline
67 & 11.1 & 13.3498 & -2.24979 \tabularnewline
68 & 13 & 13.0239 & -0.0238599 \tabularnewline
69 & 14.5 & 12.3165 & 2.18354 \tabularnewline
70 & 12.2 & 13.3438 & -1.14375 \tabularnewline
71 & 12.3 & 13.9388 & -1.63882 \tabularnewline
72 & 11.4 & 13.7145 & -2.31449 \tabularnewline
73 & 8.8 & 13.9713 & -5.17127 \tabularnewline
74 & 14.6 & 13.5978 & 1.00222 \tabularnewline
75 & 12.6 & 12.33 & 0.270049 \tabularnewline
76 & 13 & 13.1763 & -0.176272 \tabularnewline
77 & 12.6 & 12.6115 & -0.0115142 \tabularnewline
78 & 13.2 & 13.9669 & -0.766881 \tabularnewline
79 & 9.9 & 12.9747 & -3.07465 \tabularnewline
80 & 7.7 & 12.1673 & -4.46731 \tabularnewline
81 & 10.5 & 13.5167 & -3.0167 \tabularnewline
82 & 13.4 & 13.1687 & 0.231313 \tabularnewline
83 & 10.9 & 13.0822 & -2.18221 \tabularnewline
84 & 4.3 & 12.2711 & -7.9711 \tabularnewline
85 & 10.3 & 13.62 & -3.31998 \tabularnewline
86 & 11.8 & 12.724 & -0.923974 \tabularnewline
87 & 11.2 & 12.7148 & -1.51475 \tabularnewline
88 & 11.4 & 13.0185 & -1.61847 \tabularnewline
89 & 8.6 & 13.4746 & -4.8746 \tabularnewline
90 & 13.2 & 13.1422 & 0.0577947 \tabularnewline
91 & 12.6 & 12.6824 & -0.0823672 \tabularnewline
92 & 5.6 & 11.9058 & -6.30582 \tabularnewline
93 & 9.9 & 12.7532 & -2.85316 \tabularnewline
94 & 8.8 & 12.8635 & -4.06345 \tabularnewline
95 & 7.7 & 12.8039 & -5.10391 \tabularnewline
96 & 9 & 13.6313 & -4.63129 \tabularnewline
97 & 7.3 & 12.624 & -5.32401 \tabularnewline
98 & 11.4 & 12.3527 & -0.952741 \tabularnewline
99 & 13.6 & 12.3829 & 1.21708 \tabularnewline
100 & 7.9 & 12.2414 & -4.34136 \tabularnewline
101 & 10.7 & 12.417 & -1.717 \tabularnewline
102 & 10.3 & 13.2427 & -2.94274 \tabularnewline
103 & 8.3 & 11.642 & -3.34201 \tabularnewline
104 & 9.6 & 12.3067 & -2.70675 \tabularnewline
105 & 14.2 & 12.4305 & 1.76951 \tabularnewline
106 & 8.5 & 13.7043 & -5.20426 \tabularnewline
107 & 13.5 & 14.0172 & -0.517201 \tabularnewline
108 & 4.9 & 13.0363 & -8.13628 \tabularnewline
109 & 6.4 & 13.7804 & -7.38045 \tabularnewline
110 & 9.6 & 13.9917 & -4.39173 \tabularnewline
111 & 11.6 & 13.6702 & -2.07019 \tabularnewline
112 & 11.1 & 12.7412 & -1.64123 \tabularnewline
113 & 4.35 & 13.534 & -9.18402 \tabularnewline
114 & 12.7 & 12.2737 & 0.426285 \tabularnewline
115 & 18.1 & 12.1614 & 5.93859 \tabularnewline
116 & 17.85 & 12.364 & 5.48596 \tabularnewline
117 & 16.6 & 14.2479 & 2.35213 \tabularnewline
118 & 12.6 & 12.9484 & -0.348368 \tabularnewline
119 & 17.1 & 13.2465 & 3.85351 \tabularnewline
120 & 19.1 & 13.9988 & 5.10125 \tabularnewline
121 & 16.1 & 12.5321 & 3.56785 \tabularnewline
122 & 13.35 & 13.6686 & -0.318557 \tabularnewline
123 & 18.4 & 14.6775 & 3.72248 \tabularnewline
124 & 14.7 & 12.176 & 2.52402 \tabularnewline
125 & 10.6 & 12.6477 & -2.04773 \tabularnewline
126 & 12.6 & 12.41 & 0.190032 \tabularnewline
127 & 16.2 & 12.1679 & 4.03213 \tabularnewline
128 & 13.6 & 12.6283 & 0.971723 \tabularnewline
129 & 18.9 & 12.6705 & 6.22954 \tabularnewline
130 & 14.1 & 12.611 & 1.48898 \tabularnewline
131 & 14.5 & 12.6386 & 1.86137 \tabularnewline
132 & 16.15 & 13.5805 & 2.56948 \tabularnewline
133 & 14.75 & 12.0155 & 2.73455 \tabularnewline
134 & 14.8 & 12.5045 & 2.29546 \tabularnewline
135 & 12.45 & 12.3618 & 0.0881734 \tabularnewline
136 & 12.65 & 13.2622 & -0.612192 \tabularnewline
137 & 17.35 & 12.6337 & 4.71633 \tabularnewline
138 & 8.6 & 12.1938 & -3.59379 \tabularnewline
139 & 18.4 & 13.3643 & 5.03565 \tabularnewline
140 & 16.1 & 13.7173 & 2.38274 \tabularnewline
141 & 11.6 & 12.2005 & -0.600493 \tabularnewline
142 & 17.75 & 12.0808 & 5.66916 \tabularnewline
143 & 15.25 & 12.336 & 2.91401 \tabularnewline
144 & 17.65 & 11.7237 & 5.92634 \tabularnewline
145 & 16.35 & 13.5308 & 2.81924 \tabularnewline
146 & 17.65 & 14.5257 & 3.12434 \tabularnewline
147 & 13.6 & 14.0728 & -0.472808 \tabularnewline
148 & 14.35 & 14.0306 & 0.319372 \tabularnewline
149 & 14.75 & 14.0501 & 0.69992 \tabularnewline
150 & 18.25 & 12.9629 & 5.28714 \tabularnewline
151 & 9.9 & 12.8115 & -2.91151 \tabularnewline
152 & 16 & 13.0158 & 2.98424 \tabularnewline
153 & 18.25 & 13.0158 & 5.23424 \tabularnewline
154 & 16.85 & 13.494 & 3.35603 \tabularnewline
155 & 14.6 & 13.1633 & 1.4367 \tabularnewline
156 & 13.85 & 13.353 & 0.497008 \tabularnewline
157 & 18.95 & 13.3935 & 5.55647 \tabularnewline
158 & 15.6 & 13.286 & 2.31403 \tabularnewline
159 & 14.85 & 14.5381 & 0.311901 \tabularnewline
160 & 11.75 & 13.2784 & -1.52837 \tabularnewline
161 & 18.45 & 13.5994 & 4.8506 \tabularnewline
162 & 15.9 & 12.4445 & 3.45545 \tabularnewline
163 & 17.1 & 13.9371 & 3.16288 \tabularnewline
164 & 16.1 & 13.2481 & 2.85187 \tabularnewline
165 & 19.9 & 14.7354 & 5.16462 \tabularnewline
166 & 10.95 & 12.0643 & -1.11427 \tabularnewline
167 & 18.45 & 13.0341 & 5.41585 \tabularnewline
168 & 15.1 & 12.4559 & 2.6441 \tabularnewline
169 & 15 & 14.329 & 0.671047 \tabularnewline
170 & 11.35 & 13.4968 & -2.14681 \tabularnewline
171 & 15.95 & 12.5926 & 3.35735 \tabularnewline
172 & 18.1 & 13.694 & 4.40597 \tabularnewline
173 & 14.6 & 12.3365 & 2.26351 \tabularnewline
174 & 15.4 & 13.0779 & 2.32205 \tabularnewline
175 & 15.4 & 12.9331 & 2.46688 \tabularnewline
176 & 17.6 & 11.895 & 5.70503 \tabularnewline
177 & 13.35 & 13.0569 & 0.293139 \tabularnewline
178 & 19.1 & 13.1708 & 5.9292 \tabularnewline
179 & 15.35 & 12.5877 & 2.76226 \tabularnewline
180 & 7.6 & 13.0823 & -5.48227 \tabularnewline
181 & 13.4 & 13.9848 & -0.584756 \tabularnewline
182 & 13.9 & 13.8037 & 0.0963481 \tabularnewline
183 & 19.1 & 12.3316 & 6.76841 \tabularnewline
184 & 15.25 & 13.3205 & 1.92946 \tabularnewline
185 & 12.9 & 12.0394 & 0.860649 \tabularnewline
186 & 16.1 & 13.8794 & 2.2206 \tabularnewline
187 & 17.35 & 13.7427 & 3.60733 \tabularnewline
188 & 13.15 & 13.5611 & -0.41107 \tabularnewline
189 & 12.15 & 13.7497 & -1.5997 \tabularnewline
190 & 12.6 & 12.0398 & 0.560199 \tabularnewline
191 & 10.35 & 12.6337 & -2.28367 \tabularnewline
192 & 15.4 & 12.1657 & 3.23425 \tabularnewline
193 & 9.6 & 13.2676 & -3.66758 \tabularnewline
194 & 18.2 & 13.8313 & 4.36872 \tabularnewline
195 & 13.6 & 14.022 & -0.421961 \tabularnewline
196 & 14.85 & 13.5228 & 1.32721 \tabularnewline
197 & 14.75 & 13.0557 & 1.69427 \tabularnewline
198 & 14.1 & 13.6421 & 0.457864 \tabularnewline
199 & 14.9 & 13.6086 & 1.29144 \tabularnewline
200 & 16.25 & 14.1117 & 2.13829 \tabularnewline
201 & 19.25 & 15.1128 & 4.13718 \tabularnewline
202 & 13.6 & 13.9528 & -0.352824 \tabularnewline
203 & 13.6 & 13.6102 & -0.010202 \tabularnewline
204 & 15.65 & 13.0946 & 2.55537 \tabularnewline
205 & 12.75 & 11.5075 & 1.24251 \tabularnewline
206 & 14.6 & 13.1406 & 1.45943 \tabularnewline
207 & 9.85 & 12.2203 & -2.37027 \tabularnewline
208 & 12.65 & 13.2152 & -0.565238 \tabularnewline
209 & 19.2 & 12.9039 & 6.29613 \tabularnewline
210 & 16.6 & 11.8155 & 4.78447 \tabularnewline
211 & 11.2 & 12.5008 & -1.30077 \tabularnewline
212 & 15.25 & 12.2457 & 3.00431 \tabularnewline
213 & 11.9 & 13.2287 & -1.32868 \tabularnewline
214 & 13.2 & 12.8066 & 0.393385 \tabularnewline
215 & 16.35 & 13.0503 & 3.29966 \tabularnewline
216 & 12.4 & 13.1996 & -0.799557 \tabularnewline
217 & 15.85 & 12.4575 & 3.39248 \tabularnewline
218 & 18.15 & 12.3986 & 5.75139 \tabularnewline
219 & 11.15 & 12.0441 & -0.894127 \tabularnewline
220 & 15.65 & 13.6421 & 2.00792 \tabularnewline
221 & 17.75 & 12.8861 & 4.86394 \tabularnewline
222 & 7.65 & 12.8246 & -5.17457 \tabularnewline
223 & 12.35 & 13.0087 & -0.658734 \tabularnewline
224 & 15.6 & 11.8523 & 3.7477 \tabularnewline
225 & 19.3 & 13.2249 & 6.07509 \tabularnewline
226 & 15.2 & 13.3229 & 1.87714 \tabularnewline
227 & 17.1 & 13.9988 & 3.10125 \tabularnewline
228 & 15.6 & 12.3781 & 3.22191 \tabularnewline
229 & 18.4 & 12.1884 & 6.2116 \tabularnewline
230 & 19.05 & 13.4697 & 5.5803 \tabularnewline
231 & 18.55 & 13.8864 & 4.66363 \tabularnewline
232 & 19.1 & 13.8307 & 5.2693 \tabularnewline
233 & 13.1 & 11.8863 & 1.21368 \tabularnewline
234 & 12.85 & 11.943 & 0.906962 \tabularnewline
235 & 9.5 & 12.4834 & -2.98345 \tabularnewline
236 & 4.5 & 12.9688 & -8.46876 \tabularnewline
237 & 11.85 & 13.085 & -1.23498 \tabularnewline
238 & 13.6 & 12.0496 & 1.5504 \tabularnewline
239 & 11.7 & 14.4089 & -2.70888 \tabularnewline
240 & 12.4 & 12.6024 & -0.202367 \tabularnewline
241 & 13.35 & 13.882 & -0.532045 \tabularnewline
242 & 11.4 & 12.2397 & -0.839723 \tabularnewline
243 & 14.9 & 12.7801 & 2.11986 \tabularnewline
244 & 19.9 & 13.7125 & 6.18752 \tabularnewline
245 & 11.2 & 12.7948 & -1.59475 \tabularnewline
246 & 14.6 & 11.7663 & 2.83366 \tabularnewline
247 & 17.6 & 14.0095 & 3.59046 \tabularnewline
248 & 14.05 & 12.3706 & 1.67938 \tabularnewline
249 & 16.1 & 13.7151 & 2.38494 \tabularnewline
250 & 13.35 & 12.6218 & 0.728181 \tabularnewline
251 & 11.85 & 12.0744 & -0.224378 \tabularnewline
252 & 11.95 & 13.3249 & -1.37487 \tabularnewline
253 & 14.75 & 12.2949 & 2.45512 \tabularnewline
254 & 15.15 & 12.823 & 2.32703 \tabularnewline
255 & 13.2 & 11.9534 & 1.24655 \tabularnewline
256 & 16.85 & 13.7815 & 3.06849 \tabularnewline
257 & 7.85 & 12.0295 & -4.17951 \tabularnewline
258 & 7.7 & 12.798 & -5.09802 \tabularnewline
259 & 12.6 & 13.0504 & -0.4504 \tabularnewline
260 & 7.85 & 13.0071 & -5.1571 \tabularnewline
261 & 10.95 & 13.4585 & -2.50847 \tabularnewline
262 & 12.35 & 13.0698 & -0.719791 \tabularnewline
263 & 9.95 & 12.9019 & -2.95186 \tabularnewline
264 & 14.9 & 12.7473 & 2.15274 \tabularnewline
265 & 16.65 & 13.6675 & 2.98251 \tabularnewline
266 & 13.4 & 13.0466 & 0.353429 \tabularnewline
267 & 13.95 & 14.2587 & -0.308655 \tabularnewline
268 & 15.7 & 13.2179 & 2.48211 \tabularnewline
269 & 16.85 & 12.8012 & 4.04878 \tabularnewline
270 & 10.95 & 12.4505 & -1.50051 \tabularnewline
271 & 15.35 & 13.2022 & 2.1478 \tabularnewline
272 & 12.2 & 11.7188 & 0.481235 \tabularnewline
273 & 15.1 & 13.3584 & 1.74162 \tabularnewline
274 & 17.75 & 13.5378 & 4.21221 \tabularnewline
275 & 15.2 & 12.7872 & 2.41283 \tabularnewline
276 & 14.6 & 14.1533 & 0.446699 \tabularnewline
277 & 16.65 & 13.2563 & 3.39371 \tabularnewline
278 & 8.1 & 12.0869 & -3.98692 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270049&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]14.0663[/C][C]-1.16626[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.925[/C][C]-0.724964[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]14.0403[/C][C]-1.24035[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.538[/C][C]-5.13805[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]13.1335[/C][C]-6.43354[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]12.4376[/C][C]0.162423[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.9791[/C][C]1.82095[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.0855[/C][C]0.214465[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.0468[/C][C]-0.946846[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.6381[/C][C]-6.43806[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.3684[/C][C]-0.968361[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]13.052[/C][C]-6.65198[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.5237[/C][C]-0.923739[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.2481[/C][C]-1.24813[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]13.3681[/C][C]-7.06812[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]13.2336[/C][C]-1.93364[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.2646[/C][C]-0.364569[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]13.4124[/C][C]-4.11241[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.9158[/C][C]-3.3158[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]13.0374[/C][C]-3.03742[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]12.4851[/C][C]-6.08509[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.4668[/C][C]1.33324[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]13.3654[/C][C]-2.56541[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.2008[/C][C]1.59918[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]12.5116[/C][C]-0.811629[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.2397[/C][C]-1.33972[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.4078[/C][C]3.69216[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.7664[/C][C]-0.366447[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]12.7483[/C][C]-2.84826[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.8985[/C][C]-1.39848[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.6148[/C][C]-4.31477[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.8632[/C][C]-2.16321[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.1447[/C][C]-3.14466[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.0198[/C][C]-2.31978[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.0042[/C][C]-1.20416[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.7915[/C][C]-2.49149[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]13.3594[/C][C]-2.95945[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.6159[/C][C]0.0840836[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]13.2379[/C][C]-3.9379[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.7396[/C][C]-0.939593[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.1724[/C][C]-7.27244[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]12.9039[/C][C]-1.50388[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]12.3051[/C][C]0.694891[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.3286[/C][C]-0.528575[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]11.9101[/C][C]0.389917[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.9474[/C][C]-2.64743[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.8477[/C][C]-1.04771[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.524[/C][C]-4.62399[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]13.2692[/C][C]-0.56922[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]12.5877[/C][C]-0.287737[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]11.9571[/C][C]-0.357097[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]12.557[/C][C]-5.85699[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]12.6991[/C][C]-1.79905[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.3932[/C][C]-0.293221[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]12.985[/C][C]0.315043[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]12.3457[/C][C]-2.24565[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.5705[/C][C]-6.87048[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.3355[/C][C]1.96452[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]13.628[/C][C]-5.62802[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.6142[/C][C]0.685782[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.8861[/C][C]-3.58606[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]13.3849[/C][C]-0.884863[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]12.3501[/C][C]-4.7501[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]12.5991[/C][C]3.30091[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.8918[/C][C]-4.69182[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]12.443[/C][C]-3.34297[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]13.3498[/C][C]-2.24979[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.0239[/C][C]-0.0238599[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.3165[/C][C]2.18354[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]13.3438[/C][C]-1.14375[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.9388[/C][C]-1.63882[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]13.7145[/C][C]-2.31449[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]13.9713[/C][C]-5.17127[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.5978[/C][C]1.00222[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.33[/C][C]0.270049[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]13.1763[/C][C]-0.176272[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]12.6115[/C][C]-0.0115142[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]13.9669[/C][C]-0.766881[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]12.9747[/C][C]-3.07465[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]12.1673[/C][C]-4.46731[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]13.5167[/C][C]-3.0167[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]13.1687[/C][C]0.231313[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]13.0822[/C][C]-2.18221[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]12.2711[/C][C]-7.9711[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]13.62[/C][C]-3.31998[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]12.724[/C][C]-0.923974[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]12.7148[/C][C]-1.51475[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]13.0185[/C][C]-1.61847[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]13.4746[/C][C]-4.8746[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]13.1422[/C][C]0.0577947[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]12.6824[/C][C]-0.0823672[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]11.9058[/C][C]-6.30582[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]12.7532[/C][C]-2.85316[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]12.8635[/C][C]-4.06345[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]12.8039[/C][C]-5.10391[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]13.6313[/C][C]-4.63129[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]12.624[/C][C]-5.32401[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]12.3527[/C][C]-0.952741[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]12.3829[/C][C]1.21708[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]12.2414[/C][C]-4.34136[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]12.417[/C][C]-1.717[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]13.2427[/C][C]-2.94274[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]11.642[/C][C]-3.34201[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]12.3067[/C][C]-2.70675[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]12.4305[/C][C]1.76951[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]13.7043[/C][C]-5.20426[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]14.0172[/C][C]-0.517201[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]13.0363[/C][C]-8.13628[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]13.7804[/C][C]-7.38045[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]13.9917[/C][C]-4.39173[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]13.6702[/C][C]-2.07019[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]12.7412[/C][C]-1.64123[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]13.534[/C][C]-9.18402[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.2737[/C][C]0.426285[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]12.1614[/C][C]5.93859[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]12.364[/C][C]5.48596[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]14.2479[/C][C]2.35213[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]12.9484[/C][C]-0.348368[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]13.2465[/C][C]3.85351[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]13.9988[/C][C]5.10125[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]12.5321[/C][C]3.56785[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]13.6686[/C][C]-0.318557[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]14.6775[/C][C]3.72248[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]12.176[/C][C]2.52402[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]12.6477[/C][C]-2.04773[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]12.41[/C][C]0.190032[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]12.1679[/C][C]4.03213[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]12.6283[/C][C]0.971723[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]12.6705[/C][C]6.22954[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]12.611[/C][C]1.48898[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]12.6386[/C][C]1.86137[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]13.5805[/C][C]2.56948[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]12.0155[/C][C]2.73455[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]12.5045[/C][C]2.29546[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]12.3618[/C][C]0.0881734[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]13.2622[/C][C]-0.612192[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]12.6337[/C][C]4.71633[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]12.1938[/C][C]-3.59379[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]13.3643[/C][C]5.03565[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]13.7173[/C][C]2.38274[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]12.2005[/C][C]-0.600493[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]12.0808[/C][C]5.66916[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]12.336[/C][C]2.91401[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]11.7237[/C][C]5.92634[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]13.5308[/C][C]2.81924[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]14.5257[/C][C]3.12434[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]14.0728[/C][C]-0.472808[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]14.0306[/C][C]0.319372[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]14.0501[/C][C]0.69992[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]12.9629[/C][C]5.28714[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]12.8115[/C][C]-2.91151[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.0158[/C][C]2.98424[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]13.0158[/C][C]5.23424[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]13.494[/C][C]3.35603[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]13.1633[/C][C]1.4367[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]13.353[/C][C]0.497008[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]13.3935[/C][C]5.55647[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]13.286[/C][C]2.31403[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]14.5381[/C][C]0.311901[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]13.2784[/C][C]-1.52837[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]13.5994[/C][C]4.8506[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]12.4445[/C][C]3.45545[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]13.9371[/C][C]3.16288[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]13.2481[/C][C]2.85187[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]14.7354[/C][C]5.16462[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]12.0643[/C][C]-1.11427[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]13.0341[/C][C]5.41585[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]12.4559[/C][C]2.6441[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]14.329[/C][C]0.671047[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]13.4968[/C][C]-2.14681[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]12.5926[/C][C]3.35735[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]13.694[/C][C]4.40597[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]12.3365[/C][C]2.26351[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]13.0779[/C][C]2.32205[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]12.9331[/C][C]2.46688[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]11.895[/C][C]5.70503[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]13.0569[/C][C]0.293139[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]13.1708[/C][C]5.9292[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]12.5877[/C][C]2.76226[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]13.0823[/C][C]-5.48227[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]13.9848[/C][C]-0.584756[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]13.8037[/C][C]0.0963481[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]12.3316[/C][C]6.76841[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]13.3205[/C][C]1.92946[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]12.0394[/C][C]0.860649[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]13.8794[/C][C]2.2206[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]13.7427[/C][C]3.60733[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]13.5611[/C][C]-0.41107[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]13.7497[/C][C]-1.5997[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]12.0398[/C][C]0.560199[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]12.6337[/C][C]-2.28367[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]12.1657[/C][C]3.23425[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]13.2676[/C][C]-3.66758[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]13.8313[/C][C]4.36872[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]14.022[/C][C]-0.421961[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]13.5228[/C][C]1.32721[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]13.0557[/C][C]1.69427[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]13.6421[/C][C]0.457864[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]13.6086[/C][C]1.29144[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]14.1117[/C][C]2.13829[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]15.1128[/C][C]4.13718[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]13.9528[/C][C]-0.352824[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.6102[/C][C]-0.010202[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]13.0946[/C][C]2.55537[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]11.5075[/C][C]1.24251[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]13.1406[/C][C]1.45943[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]12.2203[/C][C]-2.37027[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]13.2152[/C][C]-0.565238[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]12.9039[/C][C]6.29613[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]11.8155[/C][C]4.78447[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]12.5008[/C][C]-1.30077[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]12.2457[/C][C]3.00431[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]13.2287[/C][C]-1.32868[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]12.8066[/C][C]0.393385[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]13.0503[/C][C]3.29966[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]13.1996[/C][C]-0.799557[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]12.4575[/C][C]3.39248[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]12.3986[/C][C]5.75139[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]12.0441[/C][C]-0.894127[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]13.6421[/C][C]2.00792[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]12.8861[/C][C]4.86394[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]12.8246[/C][C]-5.17457[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.0087[/C][C]-0.658734[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]11.8523[/C][C]3.7477[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]13.2249[/C][C]6.07509[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]13.3229[/C][C]1.87714[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]13.9988[/C][C]3.10125[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]12.3781[/C][C]3.22191[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]12.1884[/C][C]6.2116[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]13.4697[/C][C]5.5803[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]13.8864[/C][C]4.66363[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]13.8307[/C][C]5.2693[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]11.8863[/C][C]1.21368[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]11.943[/C][C]0.906962[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]12.4834[/C][C]-2.98345[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]12.9688[/C][C]-8.46876[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]13.085[/C][C]-1.23498[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]12.0496[/C][C]1.5504[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]14.4089[/C][C]-2.70888[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.6024[/C][C]-0.202367[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]13.882[/C][C]-0.532045[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]12.2397[/C][C]-0.839723[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]12.7801[/C][C]2.11986[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]13.7125[/C][C]6.18752[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]12.7948[/C][C]-1.59475[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]11.7663[/C][C]2.83366[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]14.0095[/C][C]3.59046[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]12.3706[/C][C]1.67938[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]13.7151[/C][C]2.38494[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]12.6218[/C][C]0.728181[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]12.0744[/C][C]-0.224378[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]13.3249[/C][C]-1.37487[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]12.2949[/C][C]2.45512[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]12.823[/C][C]2.32703[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]11.9534[/C][C]1.24655[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]13.7815[/C][C]3.06849[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]12.0295[/C][C]-4.17951[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]12.798[/C][C]-5.09802[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]13.0504[/C][C]-0.4504[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]13.0071[/C][C]-5.1571[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]13.4585[/C][C]-2.50847[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]13.0698[/C][C]-0.719791[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]12.9019[/C][C]-2.95186[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]12.7473[/C][C]2.15274[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]13.6675[/C][C]2.98251[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]13.0466[/C][C]0.353429[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]14.2587[/C][C]-0.308655[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]13.2179[/C][C]2.48211[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]12.8012[/C][C]4.04878[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]12.4505[/C][C]-1.50051[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]13.2022[/C][C]2.1478[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]11.7188[/C][C]0.481235[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]13.3584[/C][C]1.74162[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]13.5378[/C][C]4.21221[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]12.7872[/C][C]2.41283[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]14.1533[/C][C]0.446699[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]13.2563[/C][C]3.39371[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]12.0869[/C][C]-3.98692[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270049&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270049&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
112.914.0663-1.16626
212.212.925-0.724964
312.814.0403-1.24035
47.412.538-5.13805
56.713.1335-6.43354
612.612.43760.162423
714.812.97911.82095
813.313.08550.214465
911.112.0468-0.946846
108.214.6381-6.43806
1111.412.3684-0.968361
126.413.052-6.65198
1310.611.5237-0.923739
141213.2481-1.24813
156.313.3681-7.06812
1611.313.2336-1.93364
1711.912.2646-0.364569
189.313.4124-4.11241
199.612.9158-3.3158
201013.0374-3.03742
216.412.4851-6.08509
2213.812.46681.33324
2310.813.3654-2.56541
2413.812.20081.59918
2511.712.5116-0.811629
2610.912.2397-1.33972
2716.112.40783.69216
2813.413.7664-0.366447
299.912.7483-2.84826
3011.512.8985-1.39848
318.312.6148-4.31477
3211.713.8632-2.16321
33912.1447-3.14466
349.712.0198-2.31978
3510.812.0042-1.20416
3610.312.7915-2.49149
3710.413.3594-2.95945
3812.712.61590.0840836
399.313.2379-3.9379
4011.812.7396-0.939593
415.913.1724-7.27244
4211.412.9039-1.50388
431312.30510.694891
4410.811.3286-0.528575
4512.311.91010.389917
4611.313.9474-2.64743
4711.812.8477-1.04771
487.912.524-4.62399
4912.713.2692-0.56922
5012.312.5877-0.287737
5111.611.9571-0.357097
526.712.557-5.85699
5310.912.6991-1.79905
5412.112.3932-0.293221
5513.312.9850.315043
5610.112.3457-2.24565
575.712.5705-6.87048
5814.312.33551.96452
59813.628-5.62802
6013.312.61420.685782
619.312.8861-3.58606
6212.513.3849-0.884863
637.612.3501-4.7501
6415.912.59913.30091
659.213.8918-4.69182
669.112.443-3.34297
6711.113.3498-2.24979
681313.0239-0.0238599
6914.512.31652.18354
7012.213.3438-1.14375
7112.313.9388-1.63882
7211.413.7145-2.31449
738.813.9713-5.17127
7414.613.59781.00222
7512.612.330.270049
761313.1763-0.176272
7712.612.6115-0.0115142
7813.213.9669-0.766881
799.912.9747-3.07465
807.712.1673-4.46731
8110.513.5167-3.0167
8213.413.16870.231313
8310.913.0822-2.18221
844.312.2711-7.9711
8510.313.62-3.31998
8611.812.724-0.923974
8711.212.7148-1.51475
8811.413.0185-1.61847
898.613.4746-4.8746
9013.213.14220.0577947
9112.612.6824-0.0823672
925.611.9058-6.30582
939.912.7532-2.85316
948.812.8635-4.06345
957.712.8039-5.10391
96913.6313-4.63129
977.312.624-5.32401
9811.412.3527-0.952741
9913.612.38291.21708
1007.912.2414-4.34136
10110.712.417-1.717
10210.313.2427-2.94274
1038.311.642-3.34201
1049.612.3067-2.70675
10514.212.43051.76951
1068.513.7043-5.20426
10713.514.0172-0.517201
1084.913.0363-8.13628
1096.413.7804-7.38045
1109.613.9917-4.39173
11111.613.6702-2.07019
11211.112.7412-1.64123
1134.3513.534-9.18402
11412.712.27370.426285
11518.112.16145.93859
11617.8512.3645.48596
11716.614.24792.35213
11812.612.9484-0.348368
11917.113.24653.85351
12019.113.99885.10125
12116.112.53213.56785
12213.3513.6686-0.318557
12318.414.67753.72248
12414.712.1762.52402
12510.612.6477-2.04773
12612.612.410.190032
12716.212.16794.03213
12813.612.62830.971723
12918.912.67056.22954
13014.112.6111.48898
13114.512.63861.86137
13216.1513.58052.56948
13314.7512.01552.73455
13414.812.50452.29546
13512.4512.36180.0881734
13612.6513.2622-0.612192
13717.3512.63374.71633
1388.612.1938-3.59379
13918.413.36435.03565
14016.113.71732.38274
14111.612.2005-0.600493
14217.7512.08085.66916
14315.2512.3362.91401
14417.6511.72375.92634
14516.3513.53082.81924
14617.6514.52573.12434
14713.614.0728-0.472808
14814.3514.03060.319372
14914.7514.05010.69992
15018.2512.96295.28714
1519.912.8115-2.91151
1521613.01582.98424
15318.2513.01585.23424
15416.8513.4943.35603
15514.613.16331.4367
15613.8513.3530.497008
15718.9513.39355.55647
15815.613.2862.31403
15914.8514.53810.311901
16011.7513.2784-1.52837
16118.4513.59944.8506
16215.912.44453.45545
16317.113.93713.16288
16416.113.24812.85187
16519.914.73545.16462
16610.9512.0643-1.11427
16718.4513.03415.41585
16815.112.45592.6441
1691514.3290.671047
17011.3513.4968-2.14681
17115.9512.59263.35735
17218.113.6944.40597
17314.612.33652.26351
17415.413.07792.32205
17515.412.93312.46688
17617.611.8955.70503
17713.3513.05690.293139
17819.113.17085.9292
17915.3512.58772.76226
1807.613.0823-5.48227
18113.413.9848-0.584756
18213.913.80370.0963481
18319.112.33166.76841
18415.2513.32051.92946
18512.912.03940.860649
18616.113.87942.2206
18717.3513.74273.60733
18813.1513.5611-0.41107
18912.1513.7497-1.5997
19012.612.03980.560199
19110.3512.6337-2.28367
19215.412.16573.23425
1939.613.2676-3.66758
19418.213.83134.36872
19513.614.022-0.421961
19614.8513.52281.32721
19714.7513.05571.69427
19814.113.64210.457864
19914.913.60861.29144
20016.2514.11172.13829
20119.2515.11284.13718
20213.613.9528-0.352824
20313.613.6102-0.010202
20415.6513.09462.55537
20512.7511.50751.24251
20614.613.14061.45943
2079.8512.2203-2.37027
20812.6513.2152-0.565238
20919.212.90396.29613
21016.611.81554.78447
21111.212.5008-1.30077
21215.2512.24573.00431
21311.913.2287-1.32868
21413.212.80660.393385
21516.3513.05033.29966
21612.413.1996-0.799557
21715.8512.45753.39248
21818.1512.39865.75139
21911.1512.0441-0.894127
22015.6513.64212.00792
22117.7512.88614.86394
2227.6512.8246-5.17457
22312.3513.0087-0.658734
22415.611.85233.7477
22519.313.22496.07509
22615.213.32291.87714
22717.113.99883.10125
22815.612.37813.22191
22918.412.18846.2116
23019.0513.46975.5803
23118.5513.88644.66363
23219.113.83075.2693
23313.111.88631.21368
23412.8511.9430.906962
2359.512.4834-2.98345
2364.512.9688-8.46876
23711.8513.085-1.23498
23813.612.04961.5504
23911.714.4089-2.70888
24012.412.6024-0.202367
24113.3513.882-0.532045
24211.412.2397-0.839723
24314.912.78012.11986
24419.913.71256.18752
24511.212.7948-1.59475
24614.611.76632.83366
24717.614.00953.59046
24814.0512.37061.67938
24916.113.71512.38494
25013.3512.62180.728181
25111.8512.0744-0.224378
25211.9513.3249-1.37487
25314.7512.29492.45512
25415.1512.8232.32703
25513.211.95341.24655
25616.8513.78153.06849
2577.8512.0295-4.17951
2587.712.798-5.09802
25912.613.0504-0.4504
2607.8513.0071-5.1571
26110.9513.4585-2.50847
26212.3513.0698-0.719791
2639.9512.9019-2.95186
26414.912.74732.15274
26516.6513.66752.98251
26613.413.04660.353429
26713.9514.2587-0.308655
26815.713.21792.48211
26916.8512.80124.04878
27010.9512.4505-1.50051
27115.3513.20222.1478
27212.211.71880.481235
27315.113.35841.74162
27417.7513.53784.21221
27515.212.78722.41283
27614.614.15330.446699
27716.6513.25633.39371
2788.112.0869-3.98692






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.3405650.681130.659435
90.2101180.4202350.789882
100.1306950.2613890.869305
110.07163790.1432760.928362
120.08013280.1602660.919867
130.05426760.1085350.945732
140.02978810.05957610.970212
150.1205470.2410950.879453
160.1062250.2124510.893775
170.07229510.144590.927705
180.05094980.10190.94905
190.03271680.06543360.967283
200.01991090.03982190.980089
210.02047040.04094080.97953
220.0235890.04717810.976411
230.014730.02945990.98527
240.02323740.04647480.976763
250.01473520.02947030.985265
260.009189660.01837930.99081
270.02202960.04405920.97797
280.01449750.02899510.985502
290.009684020.0193680.990316
300.00615470.01230940.993845
310.02219070.04438130.977809
320.01673620.03347240.983264
330.01560150.03120290.984399
340.01208260.02416520.987917
350.008643370.01728670.991357
360.005831130.01166230.994169
370.003925950.007851910.996074
380.002615110.005230220.997385
390.001975170.003950330.998025
400.001316740.002633490.998683
410.002947120.005894240.997053
420.00225140.004502790.997749
430.002199870.004399740.9978
440.001464950.002929890.998535
450.0009340890.001868180.999066
460.0007432270.001486450.999257
470.0004868340.0009736690.999513
480.0004362240.0008724490.999564
490.0004053840.0008107690.999595
500.0003344430.0006688860.999666
510.0002271950.000454390.999773
520.0006615960.001323190.999338
530.0004502140.0009004280.99955
540.0003780370.0007560730.999622
550.0004820280.0009640560.999518
560.0003273260.0006546520.999673
570.001859050.003718090.998141
580.001493880.002987760.998506
590.001573060.003146130.998427
600.001580670.003161350.998419
610.001251550.002503090.998748
620.001021370.002042750.998979
630.002665340.005330680.997335
640.00492840.00985680.995072
650.004634120.009268230.995366
660.004361160.008722320.995639
670.00331860.00663720.996681
680.002935430.005870870.997065
690.003256230.006512460.996744
700.002576250.005152510.997424
710.002033370.004066750.997967
720.001575890.003151780.998424
730.001641180.003282360.998359
740.00203550.004071010.997964
750.001611550.00322310.998388
760.001316780.002633560.998683
770.0009886390.001977280.999011
780.0009238590.001847720.999076
790.0007612830.001522570.999239
800.0009593660.001918730.999041
810.0007648360.001529670.999235
820.0006940410.001388080.999306
830.000525890.001051780.999474
840.002798670.005597330.997201
850.002406180.004812360.997594
860.001846970.003693950.998153
870.0014160.0028320.998584
880.001104040.002208070.998896
890.001255230.002510460.998745
900.001099110.002198210.998901
910.0008639460.001727890.999136
920.002358280.004716550.997642
930.001999160.003998330.998001
940.002038520.004077040.997961
950.002779150.00555830.997221
960.003077030.006154060.996923
970.004376870.008753740.995623
980.003499280.006998560.996501
990.003199130.006398270.996801
1000.003890340.007780670.99611
1010.003179520.006359030.99682
1020.002875850.005751710.997124
1030.003161160.006322320.996839
1040.002877310.005754610.997123
1050.002991370.005982740.997009
1060.003919360.007838720.996081
1070.003681170.007362340.996319
1080.01542210.03084410.984578
1090.035460.070920.96454
1100.04032880.08065750.959671
1110.03844980.07689970.96155
1120.03429590.06859170.965704
1130.1291520.2583040.870848
1140.1166210.2332420.883379
1150.2162070.4324140.783793
1160.3264430.6528860.673557
1170.3811450.7622890.618855
1180.3574870.7149750.642513
1190.4225250.8450510.577475
1200.5675890.8648230.432411
1210.6054540.7890910.394546
1220.59140.81720.4086
1230.6554690.6890630.344531
1240.6598250.6803510.340175
1250.6492040.7015920.350796
1260.6245110.7509770.375489
1270.6568030.6863940.343197
1280.6357080.7285850.364292
1290.7533730.4932540.246627
1300.7375820.5248360.262418
1310.7255460.5489070.274454
1320.7381320.5237360.261868
1330.733810.5323810.26619
1340.7253670.5492650.274633
1350.6998030.6003940.300197
1360.6768770.6462460.323123
1370.7187810.5624390.281219
1380.7424880.5150240.257512
1390.8041280.3917430.195872
1400.8000160.3999680.199984
1410.7762350.4475310.223765
1420.8274350.345130.172565
1430.8254580.3490840.174542
1440.8723320.2553360.127668
1450.8755540.2488910.124446
1460.8840160.2319680.115984
1470.8705890.2588230.129411
1480.8586490.2827020.141351
1490.8461160.3077690.153884
1500.8804460.2391080.119554
1510.887020.2259590.11298
1520.8838710.2322580.116129
1530.9086130.1827730.0913866
1540.9104580.1790830.0895416
1550.8985680.2028630.101432
1560.8835380.2329230.116462
1570.9126020.1747950.0873977
1580.907840.184320.0921598
1590.8964910.2070180.103509
1600.8921310.2157380.107869
1610.9100080.1799840.089992
1620.90990.1801990.0900995
1630.9075480.1849050.0924523
1640.902030.195940.0979699
1650.9213090.1573810.0786906
1660.9103470.1793060.0896531
1670.9310560.1378890.0689443
1680.925380.1492390.0746197
1690.9137960.1724080.0862038
1700.9130610.1738780.086939
1710.9120530.1758940.0879468
1720.9204040.1591920.0795958
1730.9118670.1762660.088133
1740.9031670.1936660.096833
1750.8948870.2102260.105113
1760.9226040.1547910.0773957
1770.9085040.1829910.0914957
1780.9331120.1337770.0668885
1790.9286250.142750.071375
1800.9600160.07996730.0399836
1810.9542290.0915420.045771
1820.9459210.1081570.0540787
1830.9727110.05457890.0272894
1840.9680690.06386140.0319307
1850.9611420.07771560.0388578
1860.9553990.08920150.0446007
1870.9539170.09216640.0460832
1880.947950.10410.0520502
1890.9475510.1048990.0524493
1900.9367630.1264750.0632374
1910.931310.1373810.0686904
1920.9292480.1415030.0707515
1930.935990.128020.0640098
1940.9379210.1241580.0620788
1950.9289360.1421280.0710638
1960.9163890.1672210.0836105
1970.9031470.1937060.0968532
1980.8881840.2236320.111816
1990.8706030.2587940.129397
2000.8531050.293790.146895
2010.8855190.2289620.114481
2020.8653040.2693920.134696
2030.8490320.3019370.150968
2040.8310550.337890.168945
2050.806410.387180.19359
2060.7824750.435050.217525
2070.778150.44370.22185
2080.7472610.5054770.252739
2090.7851120.4297760.214888
2100.808210.383580.19179
2110.7858290.4283420.214171
2120.7757230.4485540.224277
2130.7719780.4560450.228022
2140.749360.501280.25064
2150.7285080.5429830.271492
2160.6931790.6136410.306821
2170.6950660.6098670.304934
2180.7617140.4765720.238286
2190.7294280.5411450.270572
2200.6960720.6078560.303928
2210.7002780.5994440.299722
2220.8236960.3526080.176304
2230.7935670.4128660.206433
2240.8075960.3848070.192404
2250.8432250.3135510.156775
2260.8160720.3678560.183928
2270.79330.4134010.2067
2280.7905940.4188130.209406
2290.8768020.2463960.123198
2300.8986490.2027020.101351
2310.899220.201560.10078
2320.9164960.1670080.0835042
2330.8993760.2012490.100624
2340.8824170.2351660.117583
2350.8704850.2590290.129515
2360.9745470.05090640.0254532
2370.9723040.05539180.0276959
2380.9641230.07175450.0358772
2390.9590790.08184180.0409209
2400.9455290.1089430.0544714
2410.9425360.1149270.0574635
2420.9277470.1445060.0722532
2430.916480.1670390.0835196
2440.9478260.1043480.0521741
2450.9339690.1320630.0660314
2460.9341090.1317810.0658906
2470.9278240.1443510.0721757
2480.9220890.1558220.0779108
2490.8984050.2031890.101595
2500.8679270.2641470.132073
2510.8294990.3410020.170501
2520.8107110.3785780.189289
2530.8150180.3699630.184982
2540.8511130.2977740.148887
2550.9278020.1443960.0721982
2560.9003970.1992060.0996028
2570.9149010.1701970.0850985
2580.993070.01385980.00692988
2590.9882440.02351260.0117563
2600.9964960.007007540.00350377
2610.9948510.01029730.00514867
2620.9948540.01029210.00514603
2630.9891860.02162730.0108136
2640.9849010.03019810.015099
2650.9731410.05371840.0268592
2660.9463820.1072360.0536179
2670.9124050.175190.0875951
2680.8933250.2133490.106675
2690.8664280.2671450.133572
2700.9200550.159890.0799449

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.340565 & 0.68113 & 0.659435 \tabularnewline
9 & 0.210118 & 0.420235 & 0.789882 \tabularnewline
10 & 0.130695 & 0.261389 & 0.869305 \tabularnewline
11 & 0.0716379 & 0.143276 & 0.928362 \tabularnewline
12 & 0.0801328 & 0.160266 & 0.919867 \tabularnewline
13 & 0.0542676 & 0.108535 & 0.945732 \tabularnewline
14 & 0.0297881 & 0.0595761 & 0.970212 \tabularnewline
15 & 0.120547 & 0.241095 & 0.879453 \tabularnewline
16 & 0.106225 & 0.212451 & 0.893775 \tabularnewline
17 & 0.0722951 & 0.14459 & 0.927705 \tabularnewline
18 & 0.0509498 & 0.1019 & 0.94905 \tabularnewline
19 & 0.0327168 & 0.0654336 & 0.967283 \tabularnewline
20 & 0.0199109 & 0.0398219 & 0.980089 \tabularnewline
21 & 0.0204704 & 0.0409408 & 0.97953 \tabularnewline
22 & 0.023589 & 0.0471781 & 0.976411 \tabularnewline
23 & 0.01473 & 0.0294599 & 0.98527 \tabularnewline
24 & 0.0232374 & 0.0464748 & 0.976763 \tabularnewline
25 & 0.0147352 & 0.0294703 & 0.985265 \tabularnewline
26 & 0.00918966 & 0.0183793 & 0.99081 \tabularnewline
27 & 0.0220296 & 0.0440592 & 0.97797 \tabularnewline
28 & 0.0144975 & 0.0289951 & 0.985502 \tabularnewline
29 & 0.00968402 & 0.019368 & 0.990316 \tabularnewline
30 & 0.0061547 & 0.0123094 & 0.993845 \tabularnewline
31 & 0.0221907 & 0.0443813 & 0.977809 \tabularnewline
32 & 0.0167362 & 0.0334724 & 0.983264 \tabularnewline
33 & 0.0156015 & 0.0312029 & 0.984399 \tabularnewline
34 & 0.0120826 & 0.0241652 & 0.987917 \tabularnewline
35 & 0.00864337 & 0.0172867 & 0.991357 \tabularnewline
36 & 0.00583113 & 0.0116623 & 0.994169 \tabularnewline
37 & 0.00392595 & 0.00785191 & 0.996074 \tabularnewline
38 & 0.00261511 & 0.00523022 & 0.997385 \tabularnewline
39 & 0.00197517 & 0.00395033 & 0.998025 \tabularnewline
40 & 0.00131674 & 0.00263349 & 0.998683 \tabularnewline
41 & 0.00294712 & 0.00589424 & 0.997053 \tabularnewline
42 & 0.0022514 & 0.00450279 & 0.997749 \tabularnewline
43 & 0.00219987 & 0.00439974 & 0.9978 \tabularnewline
44 & 0.00146495 & 0.00292989 & 0.998535 \tabularnewline
45 & 0.000934089 & 0.00186818 & 0.999066 \tabularnewline
46 & 0.000743227 & 0.00148645 & 0.999257 \tabularnewline
47 & 0.000486834 & 0.000973669 & 0.999513 \tabularnewline
48 & 0.000436224 & 0.000872449 & 0.999564 \tabularnewline
49 & 0.000405384 & 0.000810769 & 0.999595 \tabularnewline
50 & 0.000334443 & 0.000668886 & 0.999666 \tabularnewline
51 & 0.000227195 & 0.00045439 & 0.999773 \tabularnewline
52 & 0.000661596 & 0.00132319 & 0.999338 \tabularnewline
53 & 0.000450214 & 0.000900428 & 0.99955 \tabularnewline
54 & 0.000378037 & 0.000756073 & 0.999622 \tabularnewline
55 & 0.000482028 & 0.000964056 & 0.999518 \tabularnewline
56 & 0.000327326 & 0.000654652 & 0.999673 \tabularnewline
57 & 0.00185905 & 0.00371809 & 0.998141 \tabularnewline
58 & 0.00149388 & 0.00298776 & 0.998506 \tabularnewline
59 & 0.00157306 & 0.00314613 & 0.998427 \tabularnewline
60 & 0.00158067 & 0.00316135 & 0.998419 \tabularnewline
61 & 0.00125155 & 0.00250309 & 0.998748 \tabularnewline
62 & 0.00102137 & 0.00204275 & 0.998979 \tabularnewline
63 & 0.00266534 & 0.00533068 & 0.997335 \tabularnewline
64 & 0.0049284 & 0.0098568 & 0.995072 \tabularnewline
65 & 0.00463412 & 0.00926823 & 0.995366 \tabularnewline
66 & 0.00436116 & 0.00872232 & 0.995639 \tabularnewline
67 & 0.0033186 & 0.0066372 & 0.996681 \tabularnewline
68 & 0.00293543 & 0.00587087 & 0.997065 \tabularnewline
69 & 0.00325623 & 0.00651246 & 0.996744 \tabularnewline
70 & 0.00257625 & 0.00515251 & 0.997424 \tabularnewline
71 & 0.00203337 & 0.00406675 & 0.997967 \tabularnewline
72 & 0.00157589 & 0.00315178 & 0.998424 \tabularnewline
73 & 0.00164118 & 0.00328236 & 0.998359 \tabularnewline
74 & 0.0020355 & 0.00407101 & 0.997964 \tabularnewline
75 & 0.00161155 & 0.0032231 & 0.998388 \tabularnewline
76 & 0.00131678 & 0.00263356 & 0.998683 \tabularnewline
77 & 0.000988639 & 0.00197728 & 0.999011 \tabularnewline
78 & 0.000923859 & 0.00184772 & 0.999076 \tabularnewline
79 & 0.000761283 & 0.00152257 & 0.999239 \tabularnewline
80 & 0.000959366 & 0.00191873 & 0.999041 \tabularnewline
81 & 0.000764836 & 0.00152967 & 0.999235 \tabularnewline
82 & 0.000694041 & 0.00138808 & 0.999306 \tabularnewline
83 & 0.00052589 & 0.00105178 & 0.999474 \tabularnewline
84 & 0.00279867 & 0.00559733 & 0.997201 \tabularnewline
85 & 0.00240618 & 0.00481236 & 0.997594 \tabularnewline
86 & 0.00184697 & 0.00369395 & 0.998153 \tabularnewline
87 & 0.001416 & 0.002832 & 0.998584 \tabularnewline
88 & 0.00110404 & 0.00220807 & 0.998896 \tabularnewline
89 & 0.00125523 & 0.00251046 & 0.998745 \tabularnewline
90 & 0.00109911 & 0.00219821 & 0.998901 \tabularnewline
91 & 0.000863946 & 0.00172789 & 0.999136 \tabularnewline
92 & 0.00235828 & 0.00471655 & 0.997642 \tabularnewline
93 & 0.00199916 & 0.00399833 & 0.998001 \tabularnewline
94 & 0.00203852 & 0.00407704 & 0.997961 \tabularnewline
95 & 0.00277915 & 0.0055583 & 0.997221 \tabularnewline
96 & 0.00307703 & 0.00615406 & 0.996923 \tabularnewline
97 & 0.00437687 & 0.00875374 & 0.995623 \tabularnewline
98 & 0.00349928 & 0.00699856 & 0.996501 \tabularnewline
99 & 0.00319913 & 0.00639827 & 0.996801 \tabularnewline
100 & 0.00389034 & 0.00778067 & 0.99611 \tabularnewline
101 & 0.00317952 & 0.00635903 & 0.99682 \tabularnewline
102 & 0.00287585 & 0.00575171 & 0.997124 \tabularnewline
103 & 0.00316116 & 0.00632232 & 0.996839 \tabularnewline
104 & 0.00287731 & 0.00575461 & 0.997123 \tabularnewline
105 & 0.00299137 & 0.00598274 & 0.997009 \tabularnewline
106 & 0.00391936 & 0.00783872 & 0.996081 \tabularnewline
107 & 0.00368117 & 0.00736234 & 0.996319 \tabularnewline
108 & 0.0154221 & 0.0308441 & 0.984578 \tabularnewline
109 & 0.03546 & 0.07092 & 0.96454 \tabularnewline
110 & 0.0403288 & 0.0806575 & 0.959671 \tabularnewline
111 & 0.0384498 & 0.0768997 & 0.96155 \tabularnewline
112 & 0.0342959 & 0.0685917 & 0.965704 \tabularnewline
113 & 0.129152 & 0.258304 & 0.870848 \tabularnewline
114 & 0.116621 & 0.233242 & 0.883379 \tabularnewline
115 & 0.216207 & 0.432414 & 0.783793 \tabularnewline
116 & 0.326443 & 0.652886 & 0.673557 \tabularnewline
117 & 0.381145 & 0.762289 & 0.618855 \tabularnewline
118 & 0.357487 & 0.714975 & 0.642513 \tabularnewline
119 & 0.422525 & 0.845051 & 0.577475 \tabularnewline
120 & 0.567589 & 0.864823 & 0.432411 \tabularnewline
121 & 0.605454 & 0.789091 & 0.394546 \tabularnewline
122 & 0.5914 & 0.8172 & 0.4086 \tabularnewline
123 & 0.655469 & 0.689063 & 0.344531 \tabularnewline
124 & 0.659825 & 0.680351 & 0.340175 \tabularnewline
125 & 0.649204 & 0.701592 & 0.350796 \tabularnewline
126 & 0.624511 & 0.750977 & 0.375489 \tabularnewline
127 & 0.656803 & 0.686394 & 0.343197 \tabularnewline
128 & 0.635708 & 0.728585 & 0.364292 \tabularnewline
129 & 0.753373 & 0.493254 & 0.246627 \tabularnewline
130 & 0.737582 & 0.524836 & 0.262418 \tabularnewline
131 & 0.725546 & 0.548907 & 0.274454 \tabularnewline
132 & 0.738132 & 0.523736 & 0.261868 \tabularnewline
133 & 0.73381 & 0.532381 & 0.26619 \tabularnewline
134 & 0.725367 & 0.549265 & 0.274633 \tabularnewline
135 & 0.699803 & 0.600394 & 0.300197 \tabularnewline
136 & 0.676877 & 0.646246 & 0.323123 \tabularnewline
137 & 0.718781 & 0.562439 & 0.281219 \tabularnewline
138 & 0.742488 & 0.515024 & 0.257512 \tabularnewline
139 & 0.804128 & 0.391743 & 0.195872 \tabularnewline
140 & 0.800016 & 0.399968 & 0.199984 \tabularnewline
141 & 0.776235 & 0.447531 & 0.223765 \tabularnewline
142 & 0.827435 & 0.34513 & 0.172565 \tabularnewline
143 & 0.825458 & 0.349084 & 0.174542 \tabularnewline
144 & 0.872332 & 0.255336 & 0.127668 \tabularnewline
145 & 0.875554 & 0.248891 & 0.124446 \tabularnewline
146 & 0.884016 & 0.231968 & 0.115984 \tabularnewline
147 & 0.870589 & 0.258823 & 0.129411 \tabularnewline
148 & 0.858649 & 0.282702 & 0.141351 \tabularnewline
149 & 0.846116 & 0.307769 & 0.153884 \tabularnewline
150 & 0.880446 & 0.239108 & 0.119554 \tabularnewline
151 & 0.88702 & 0.225959 & 0.11298 \tabularnewline
152 & 0.883871 & 0.232258 & 0.116129 \tabularnewline
153 & 0.908613 & 0.182773 & 0.0913866 \tabularnewline
154 & 0.910458 & 0.179083 & 0.0895416 \tabularnewline
155 & 0.898568 & 0.202863 & 0.101432 \tabularnewline
156 & 0.883538 & 0.232923 & 0.116462 \tabularnewline
157 & 0.912602 & 0.174795 & 0.0873977 \tabularnewline
158 & 0.90784 & 0.18432 & 0.0921598 \tabularnewline
159 & 0.896491 & 0.207018 & 0.103509 \tabularnewline
160 & 0.892131 & 0.215738 & 0.107869 \tabularnewline
161 & 0.910008 & 0.179984 & 0.089992 \tabularnewline
162 & 0.9099 & 0.180199 & 0.0900995 \tabularnewline
163 & 0.907548 & 0.184905 & 0.0924523 \tabularnewline
164 & 0.90203 & 0.19594 & 0.0979699 \tabularnewline
165 & 0.921309 & 0.157381 & 0.0786906 \tabularnewline
166 & 0.910347 & 0.179306 & 0.0896531 \tabularnewline
167 & 0.931056 & 0.137889 & 0.0689443 \tabularnewline
168 & 0.92538 & 0.149239 & 0.0746197 \tabularnewline
169 & 0.913796 & 0.172408 & 0.0862038 \tabularnewline
170 & 0.913061 & 0.173878 & 0.086939 \tabularnewline
171 & 0.912053 & 0.175894 & 0.0879468 \tabularnewline
172 & 0.920404 & 0.159192 & 0.0795958 \tabularnewline
173 & 0.911867 & 0.176266 & 0.088133 \tabularnewline
174 & 0.903167 & 0.193666 & 0.096833 \tabularnewline
175 & 0.894887 & 0.210226 & 0.105113 \tabularnewline
176 & 0.922604 & 0.154791 & 0.0773957 \tabularnewline
177 & 0.908504 & 0.182991 & 0.0914957 \tabularnewline
178 & 0.933112 & 0.133777 & 0.0668885 \tabularnewline
179 & 0.928625 & 0.14275 & 0.071375 \tabularnewline
180 & 0.960016 & 0.0799673 & 0.0399836 \tabularnewline
181 & 0.954229 & 0.091542 & 0.045771 \tabularnewline
182 & 0.945921 & 0.108157 & 0.0540787 \tabularnewline
183 & 0.972711 & 0.0545789 & 0.0272894 \tabularnewline
184 & 0.968069 & 0.0638614 & 0.0319307 \tabularnewline
185 & 0.961142 & 0.0777156 & 0.0388578 \tabularnewline
186 & 0.955399 & 0.0892015 & 0.0446007 \tabularnewline
187 & 0.953917 & 0.0921664 & 0.0460832 \tabularnewline
188 & 0.94795 & 0.1041 & 0.0520502 \tabularnewline
189 & 0.947551 & 0.104899 & 0.0524493 \tabularnewline
190 & 0.936763 & 0.126475 & 0.0632374 \tabularnewline
191 & 0.93131 & 0.137381 & 0.0686904 \tabularnewline
192 & 0.929248 & 0.141503 & 0.0707515 \tabularnewline
193 & 0.93599 & 0.12802 & 0.0640098 \tabularnewline
194 & 0.937921 & 0.124158 & 0.0620788 \tabularnewline
195 & 0.928936 & 0.142128 & 0.0710638 \tabularnewline
196 & 0.916389 & 0.167221 & 0.0836105 \tabularnewline
197 & 0.903147 & 0.193706 & 0.0968532 \tabularnewline
198 & 0.888184 & 0.223632 & 0.111816 \tabularnewline
199 & 0.870603 & 0.258794 & 0.129397 \tabularnewline
200 & 0.853105 & 0.29379 & 0.146895 \tabularnewline
201 & 0.885519 & 0.228962 & 0.114481 \tabularnewline
202 & 0.865304 & 0.269392 & 0.134696 \tabularnewline
203 & 0.849032 & 0.301937 & 0.150968 \tabularnewline
204 & 0.831055 & 0.33789 & 0.168945 \tabularnewline
205 & 0.80641 & 0.38718 & 0.19359 \tabularnewline
206 & 0.782475 & 0.43505 & 0.217525 \tabularnewline
207 & 0.77815 & 0.4437 & 0.22185 \tabularnewline
208 & 0.747261 & 0.505477 & 0.252739 \tabularnewline
209 & 0.785112 & 0.429776 & 0.214888 \tabularnewline
210 & 0.80821 & 0.38358 & 0.19179 \tabularnewline
211 & 0.785829 & 0.428342 & 0.214171 \tabularnewline
212 & 0.775723 & 0.448554 & 0.224277 \tabularnewline
213 & 0.771978 & 0.456045 & 0.228022 \tabularnewline
214 & 0.74936 & 0.50128 & 0.25064 \tabularnewline
215 & 0.728508 & 0.542983 & 0.271492 \tabularnewline
216 & 0.693179 & 0.613641 & 0.306821 \tabularnewline
217 & 0.695066 & 0.609867 & 0.304934 \tabularnewline
218 & 0.761714 & 0.476572 & 0.238286 \tabularnewline
219 & 0.729428 & 0.541145 & 0.270572 \tabularnewline
220 & 0.696072 & 0.607856 & 0.303928 \tabularnewline
221 & 0.700278 & 0.599444 & 0.299722 \tabularnewline
222 & 0.823696 & 0.352608 & 0.176304 \tabularnewline
223 & 0.793567 & 0.412866 & 0.206433 \tabularnewline
224 & 0.807596 & 0.384807 & 0.192404 \tabularnewline
225 & 0.843225 & 0.313551 & 0.156775 \tabularnewline
226 & 0.816072 & 0.367856 & 0.183928 \tabularnewline
227 & 0.7933 & 0.413401 & 0.2067 \tabularnewline
228 & 0.790594 & 0.418813 & 0.209406 \tabularnewline
229 & 0.876802 & 0.246396 & 0.123198 \tabularnewline
230 & 0.898649 & 0.202702 & 0.101351 \tabularnewline
231 & 0.89922 & 0.20156 & 0.10078 \tabularnewline
232 & 0.916496 & 0.167008 & 0.0835042 \tabularnewline
233 & 0.899376 & 0.201249 & 0.100624 \tabularnewline
234 & 0.882417 & 0.235166 & 0.117583 \tabularnewline
235 & 0.870485 & 0.259029 & 0.129515 \tabularnewline
236 & 0.974547 & 0.0509064 & 0.0254532 \tabularnewline
237 & 0.972304 & 0.0553918 & 0.0276959 \tabularnewline
238 & 0.964123 & 0.0717545 & 0.0358772 \tabularnewline
239 & 0.959079 & 0.0818418 & 0.0409209 \tabularnewline
240 & 0.945529 & 0.108943 & 0.0544714 \tabularnewline
241 & 0.942536 & 0.114927 & 0.0574635 \tabularnewline
242 & 0.927747 & 0.144506 & 0.0722532 \tabularnewline
243 & 0.91648 & 0.167039 & 0.0835196 \tabularnewline
244 & 0.947826 & 0.104348 & 0.0521741 \tabularnewline
245 & 0.933969 & 0.132063 & 0.0660314 \tabularnewline
246 & 0.934109 & 0.131781 & 0.0658906 \tabularnewline
247 & 0.927824 & 0.144351 & 0.0721757 \tabularnewline
248 & 0.922089 & 0.155822 & 0.0779108 \tabularnewline
249 & 0.898405 & 0.203189 & 0.101595 \tabularnewline
250 & 0.867927 & 0.264147 & 0.132073 \tabularnewline
251 & 0.829499 & 0.341002 & 0.170501 \tabularnewline
252 & 0.810711 & 0.378578 & 0.189289 \tabularnewline
253 & 0.815018 & 0.369963 & 0.184982 \tabularnewline
254 & 0.851113 & 0.297774 & 0.148887 \tabularnewline
255 & 0.927802 & 0.144396 & 0.0721982 \tabularnewline
256 & 0.900397 & 0.199206 & 0.0996028 \tabularnewline
257 & 0.914901 & 0.170197 & 0.0850985 \tabularnewline
258 & 0.99307 & 0.0138598 & 0.00692988 \tabularnewline
259 & 0.988244 & 0.0235126 & 0.0117563 \tabularnewline
260 & 0.996496 & 0.00700754 & 0.00350377 \tabularnewline
261 & 0.994851 & 0.0102973 & 0.00514867 \tabularnewline
262 & 0.994854 & 0.0102921 & 0.00514603 \tabularnewline
263 & 0.989186 & 0.0216273 & 0.0108136 \tabularnewline
264 & 0.984901 & 0.0301981 & 0.015099 \tabularnewline
265 & 0.973141 & 0.0537184 & 0.0268592 \tabularnewline
266 & 0.946382 & 0.107236 & 0.0536179 \tabularnewline
267 & 0.912405 & 0.17519 & 0.0875951 \tabularnewline
268 & 0.893325 & 0.213349 & 0.106675 \tabularnewline
269 & 0.866428 & 0.267145 & 0.133572 \tabularnewline
270 & 0.920055 & 0.15989 & 0.0799449 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270049&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]8[/C][C]0.340565[/C][C]0.68113[/C][C]0.659435[/C][/ROW]
[ROW][C]9[/C][C]0.210118[/C][C]0.420235[/C][C]0.789882[/C][/ROW]
[ROW][C]10[/C][C]0.130695[/C][C]0.261389[/C][C]0.869305[/C][/ROW]
[ROW][C]11[/C][C]0.0716379[/C][C]0.143276[/C][C]0.928362[/C][/ROW]
[ROW][C]12[/C][C]0.0801328[/C][C]0.160266[/C][C]0.919867[/C][/ROW]
[ROW][C]13[/C][C]0.0542676[/C][C]0.108535[/C][C]0.945732[/C][/ROW]
[ROW][C]14[/C][C]0.0297881[/C][C]0.0595761[/C][C]0.970212[/C][/ROW]
[ROW][C]15[/C][C]0.120547[/C][C]0.241095[/C][C]0.879453[/C][/ROW]
[ROW][C]16[/C][C]0.106225[/C][C]0.212451[/C][C]0.893775[/C][/ROW]
[ROW][C]17[/C][C]0.0722951[/C][C]0.14459[/C][C]0.927705[/C][/ROW]
[ROW][C]18[/C][C]0.0509498[/C][C]0.1019[/C][C]0.94905[/C][/ROW]
[ROW][C]19[/C][C]0.0327168[/C][C]0.0654336[/C][C]0.967283[/C][/ROW]
[ROW][C]20[/C][C]0.0199109[/C][C]0.0398219[/C][C]0.980089[/C][/ROW]
[ROW][C]21[/C][C]0.0204704[/C][C]0.0409408[/C][C]0.97953[/C][/ROW]
[ROW][C]22[/C][C]0.023589[/C][C]0.0471781[/C][C]0.976411[/C][/ROW]
[ROW][C]23[/C][C]0.01473[/C][C]0.0294599[/C][C]0.98527[/C][/ROW]
[ROW][C]24[/C][C]0.0232374[/C][C]0.0464748[/C][C]0.976763[/C][/ROW]
[ROW][C]25[/C][C]0.0147352[/C][C]0.0294703[/C][C]0.985265[/C][/ROW]
[ROW][C]26[/C][C]0.00918966[/C][C]0.0183793[/C][C]0.99081[/C][/ROW]
[ROW][C]27[/C][C]0.0220296[/C][C]0.0440592[/C][C]0.97797[/C][/ROW]
[ROW][C]28[/C][C]0.0144975[/C][C]0.0289951[/C][C]0.985502[/C][/ROW]
[ROW][C]29[/C][C]0.00968402[/C][C]0.019368[/C][C]0.990316[/C][/ROW]
[ROW][C]30[/C][C]0.0061547[/C][C]0.0123094[/C][C]0.993845[/C][/ROW]
[ROW][C]31[/C][C]0.0221907[/C][C]0.0443813[/C][C]0.977809[/C][/ROW]
[ROW][C]32[/C][C]0.0167362[/C][C]0.0334724[/C][C]0.983264[/C][/ROW]
[ROW][C]33[/C][C]0.0156015[/C][C]0.0312029[/C][C]0.984399[/C][/ROW]
[ROW][C]34[/C][C]0.0120826[/C][C]0.0241652[/C][C]0.987917[/C][/ROW]
[ROW][C]35[/C][C]0.00864337[/C][C]0.0172867[/C][C]0.991357[/C][/ROW]
[ROW][C]36[/C][C]0.00583113[/C][C]0.0116623[/C][C]0.994169[/C][/ROW]
[ROW][C]37[/C][C]0.00392595[/C][C]0.00785191[/C][C]0.996074[/C][/ROW]
[ROW][C]38[/C][C]0.00261511[/C][C]0.00523022[/C][C]0.997385[/C][/ROW]
[ROW][C]39[/C][C]0.00197517[/C][C]0.00395033[/C][C]0.998025[/C][/ROW]
[ROW][C]40[/C][C]0.00131674[/C][C]0.00263349[/C][C]0.998683[/C][/ROW]
[ROW][C]41[/C][C]0.00294712[/C][C]0.00589424[/C][C]0.997053[/C][/ROW]
[ROW][C]42[/C][C]0.0022514[/C][C]0.00450279[/C][C]0.997749[/C][/ROW]
[ROW][C]43[/C][C]0.00219987[/C][C]0.00439974[/C][C]0.9978[/C][/ROW]
[ROW][C]44[/C][C]0.00146495[/C][C]0.00292989[/C][C]0.998535[/C][/ROW]
[ROW][C]45[/C][C]0.000934089[/C][C]0.00186818[/C][C]0.999066[/C][/ROW]
[ROW][C]46[/C][C]0.000743227[/C][C]0.00148645[/C][C]0.999257[/C][/ROW]
[ROW][C]47[/C][C]0.000486834[/C][C]0.000973669[/C][C]0.999513[/C][/ROW]
[ROW][C]48[/C][C]0.000436224[/C][C]0.000872449[/C][C]0.999564[/C][/ROW]
[ROW][C]49[/C][C]0.000405384[/C][C]0.000810769[/C][C]0.999595[/C][/ROW]
[ROW][C]50[/C][C]0.000334443[/C][C]0.000668886[/C][C]0.999666[/C][/ROW]
[ROW][C]51[/C][C]0.000227195[/C][C]0.00045439[/C][C]0.999773[/C][/ROW]
[ROW][C]52[/C][C]0.000661596[/C][C]0.00132319[/C][C]0.999338[/C][/ROW]
[ROW][C]53[/C][C]0.000450214[/C][C]0.000900428[/C][C]0.99955[/C][/ROW]
[ROW][C]54[/C][C]0.000378037[/C][C]0.000756073[/C][C]0.999622[/C][/ROW]
[ROW][C]55[/C][C]0.000482028[/C][C]0.000964056[/C][C]0.999518[/C][/ROW]
[ROW][C]56[/C][C]0.000327326[/C][C]0.000654652[/C][C]0.999673[/C][/ROW]
[ROW][C]57[/C][C]0.00185905[/C][C]0.00371809[/C][C]0.998141[/C][/ROW]
[ROW][C]58[/C][C]0.00149388[/C][C]0.00298776[/C][C]0.998506[/C][/ROW]
[ROW][C]59[/C][C]0.00157306[/C][C]0.00314613[/C][C]0.998427[/C][/ROW]
[ROW][C]60[/C][C]0.00158067[/C][C]0.00316135[/C][C]0.998419[/C][/ROW]
[ROW][C]61[/C][C]0.00125155[/C][C]0.00250309[/C][C]0.998748[/C][/ROW]
[ROW][C]62[/C][C]0.00102137[/C][C]0.00204275[/C][C]0.998979[/C][/ROW]
[ROW][C]63[/C][C]0.00266534[/C][C]0.00533068[/C][C]0.997335[/C][/ROW]
[ROW][C]64[/C][C]0.0049284[/C][C]0.0098568[/C][C]0.995072[/C][/ROW]
[ROW][C]65[/C][C]0.00463412[/C][C]0.00926823[/C][C]0.995366[/C][/ROW]
[ROW][C]66[/C][C]0.00436116[/C][C]0.00872232[/C][C]0.995639[/C][/ROW]
[ROW][C]67[/C][C]0.0033186[/C][C]0.0066372[/C][C]0.996681[/C][/ROW]
[ROW][C]68[/C][C]0.00293543[/C][C]0.00587087[/C][C]0.997065[/C][/ROW]
[ROW][C]69[/C][C]0.00325623[/C][C]0.00651246[/C][C]0.996744[/C][/ROW]
[ROW][C]70[/C][C]0.00257625[/C][C]0.00515251[/C][C]0.997424[/C][/ROW]
[ROW][C]71[/C][C]0.00203337[/C][C]0.00406675[/C][C]0.997967[/C][/ROW]
[ROW][C]72[/C][C]0.00157589[/C][C]0.00315178[/C][C]0.998424[/C][/ROW]
[ROW][C]73[/C][C]0.00164118[/C][C]0.00328236[/C][C]0.998359[/C][/ROW]
[ROW][C]74[/C][C]0.0020355[/C][C]0.00407101[/C][C]0.997964[/C][/ROW]
[ROW][C]75[/C][C]0.00161155[/C][C]0.0032231[/C][C]0.998388[/C][/ROW]
[ROW][C]76[/C][C]0.00131678[/C][C]0.00263356[/C][C]0.998683[/C][/ROW]
[ROW][C]77[/C][C]0.000988639[/C][C]0.00197728[/C][C]0.999011[/C][/ROW]
[ROW][C]78[/C][C]0.000923859[/C][C]0.00184772[/C][C]0.999076[/C][/ROW]
[ROW][C]79[/C][C]0.000761283[/C][C]0.00152257[/C][C]0.999239[/C][/ROW]
[ROW][C]80[/C][C]0.000959366[/C][C]0.00191873[/C][C]0.999041[/C][/ROW]
[ROW][C]81[/C][C]0.000764836[/C][C]0.00152967[/C][C]0.999235[/C][/ROW]
[ROW][C]82[/C][C]0.000694041[/C][C]0.00138808[/C][C]0.999306[/C][/ROW]
[ROW][C]83[/C][C]0.00052589[/C][C]0.00105178[/C][C]0.999474[/C][/ROW]
[ROW][C]84[/C][C]0.00279867[/C][C]0.00559733[/C][C]0.997201[/C][/ROW]
[ROW][C]85[/C][C]0.00240618[/C][C]0.00481236[/C][C]0.997594[/C][/ROW]
[ROW][C]86[/C][C]0.00184697[/C][C]0.00369395[/C][C]0.998153[/C][/ROW]
[ROW][C]87[/C][C]0.001416[/C][C]0.002832[/C][C]0.998584[/C][/ROW]
[ROW][C]88[/C][C]0.00110404[/C][C]0.00220807[/C][C]0.998896[/C][/ROW]
[ROW][C]89[/C][C]0.00125523[/C][C]0.00251046[/C][C]0.998745[/C][/ROW]
[ROW][C]90[/C][C]0.00109911[/C][C]0.00219821[/C][C]0.998901[/C][/ROW]
[ROW][C]91[/C][C]0.000863946[/C][C]0.00172789[/C][C]0.999136[/C][/ROW]
[ROW][C]92[/C][C]0.00235828[/C][C]0.00471655[/C][C]0.997642[/C][/ROW]
[ROW][C]93[/C][C]0.00199916[/C][C]0.00399833[/C][C]0.998001[/C][/ROW]
[ROW][C]94[/C][C]0.00203852[/C][C]0.00407704[/C][C]0.997961[/C][/ROW]
[ROW][C]95[/C][C]0.00277915[/C][C]0.0055583[/C][C]0.997221[/C][/ROW]
[ROW][C]96[/C][C]0.00307703[/C][C]0.00615406[/C][C]0.996923[/C][/ROW]
[ROW][C]97[/C][C]0.00437687[/C][C]0.00875374[/C][C]0.995623[/C][/ROW]
[ROW][C]98[/C][C]0.00349928[/C][C]0.00699856[/C][C]0.996501[/C][/ROW]
[ROW][C]99[/C][C]0.00319913[/C][C]0.00639827[/C][C]0.996801[/C][/ROW]
[ROW][C]100[/C][C]0.00389034[/C][C]0.00778067[/C][C]0.99611[/C][/ROW]
[ROW][C]101[/C][C]0.00317952[/C][C]0.00635903[/C][C]0.99682[/C][/ROW]
[ROW][C]102[/C][C]0.00287585[/C][C]0.00575171[/C][C]0.997124[/C][/ROW]
[ROW][C]103[/C][C]0.00316116[/C][C]0.00632232[/C][C]0.996839[/C][/ROW]
[ROW][C]104[/C][C]0.00287731[/C][C]0.00575461[/C][C]0.997123[/C][/ROW]
[ROW][C]105[/C][C]0.00299137[/C][C]0.00598274[/C][C]0.997009[/C][/ROW]
[ROW][C]106[/C][C]0.00391936[/C][C]0.00783872[/C][C]0.996081[/C][/ROW]
[ROW][C]107[/C][C]0.00368117[/C][C]0.00736234[/C][C]0.996319[/C][/ROW]
[ROW][C]108[/C][C]0.0154221[/C][C]0.0308441[/C][C]0.984578[/C][/ROW]
[ROW][C]109[/C][C]0.03546[/C][C]0.07092[/C][C]0.96454[/C][/ROW]
[ROW][C]110[/C][C]0.0403288[/C][C]0.0806575[/C][C]0.959671[/C][/ROW]
[ROW][C]111[/C][C]0.0384498[/C][C]0.0768997[/C][C]0.96155[/C][/ROW]
[ROW][C]112[/C][C]0.0342959[/C][C]0.0685917[/C][C]0.965704[/C][/ROW]
[ROW][C]113[/C][C]0.129152[/C][C]0.258304[/C][C]0.870848[/C][/ROW]
[ROW][C]114[/C][C]0.116621[/C][C]0.233242[/C][C]0.883379[/C][/ROW]
[ROW][C]115[/C][C]0.216207[/C][C]0.432414[/C][C]0.783793[/C][/ROW]
[ROW][C]116[/C][C]0.326443[/C][C]0.652886[/C][C]0.673557[/C][/ROW]
[ROW][C]117[/C][C]0.381145[/C][C]0.762289[/C][C]0.618855[/C][/ROW]
[ROW][C]118[/C][C]0.357487[/C][C]0.714975[/C][C]0.642513[/C][/ROW]
[ROW][C]119[/C][C]0.422525[/C][C]0.845051[/C][C]0.577475[/C][/ROW]
[ROW][C]120[/C][C]0.567589[/C][C]0.864823[/C][C]0.432411[/C][/ROW]
[ROW][C]121[/C][C]0.605454[/C][C]0.789091[/C][C]0.394546[/C][/ROW]
[ROW][C]122[/C][C]0.5914[/C][C]0.8172[/C][C]0.4086[/C][/ROW]
[ROW][C]123[/C][C]0.655469[/C][C]0.689063[/C][C]0.344531[/C][/ROW]
[ROW][C]124[/C][C]0.659825[/C][C]0.680351[/C][C]0.340175[/C][/ROW]
[ROW][C]125[/C][C]0.649204[/C][C]0.701592[/C][C]0.350796[/C][/ROW]
[ROW][C]126[/C][C]0.624511[/C][C]0.750977[/C][C]0.375489[/C][/ROW]
[ROW][C]127[/C][C]0.656803[/C][C]0.686394[/C][C]0.343197[/C][/ROW]
[ROW][C]128[/C][C]0.635708[/C][C]0.728585[/C][C]0.364292[/C][/ROW]
[ROW][C]129[/C][C]0.753373[/C][C]0.493254[/C][C]0.246627[/C][/ROW]
[ROW][C]130[/C][C]0.737582[/C][C]0.524836[/C][C]0.262418[/C][/ROW]
[ROW][C]131[/C][C]0.725546[/C][C]0.548907[/C][C]0.274454[/C][/ROW]
[ROW][C]132[/C][C]0.738132[/C][C]0.523736[/C][C]0.261868[/C][/ROW]
[ROW][C]133[/C][C]0.73381[/C][C]0.532381[/C][C]0.26619[/C][/ROW]
[ROW][C]134[/C][C]0.725367[/C][C]0.549265[/C][C]0.274633[/C][/ROW]
[ROW][C]135[/C][C]0.699803[/C][C]0.600394[/C][C]0.300197[/C][/ROW]
[ROW][C]136[/C][C]0.676877[/C][C]0.646246[/C][C]0.323123[/C][/ROW]
[ROW][C]137[/C][C]0.718781[/C][C]0.562439[/C][C]0.281219[/C][/ROW]
[ROW][C]138[/C][C]0.742488[/C][C]0.515024[/C][C]0.257512[/C][/ROW]
[ROW][C]139[/C][C]0.804128[/C][C]0.391743[/C][C]0.195872[/C][/ROW]
[ROW][C]140[/C][C]0.800016[/C][C]0.399968[/C][C]0.199984[/C][/ROW]
[ROW][C]141[/C][C]0.776235[/C][C]0.447531[/C][C]0.223765[/C][/ROW]
[ROW][C]142[/C][C]0.827435[/C][C]0.34513[/C][C]0.172565[/C][/ROW]
[ROW][C]143[/C][C]0.825458[/C][C]0.349084[/C][C]0.174542[/C][/ROW]
[ROW][C]144[/C][C]0.872332[/C][C]0.255336[/C][C]0.127668[/C][/ROW]
[ROW][C]145[/C][C]0.875554[/C][C]0.248891[/C][C]0.124446[/C][/ROW]
[ROW][C]146[/C][C]0.884016[/C][C]0.231968[/C][C]0.115984[/C][/ROW]
[ROW][C]147[/C][C]0.870589[/C][C]0.258823[/C][C]0.129411[/C][/ROW]
[ROW][C]148[/C][C]0.858649[/C][C]0.282702[/C][C]0.141351[/C][/ROW]
[ROW][C]149[/C][C]0.846116[/C][C]0.307769[/C][C]0.153884[/C][/ROW]
[ROW][C]150[/C][C]0.880446[/C][C]0.239108[/C][C]0.119554[/C][/ROW]
[ROW][C]151[/C][C]0.88702[/C][C]0.225959[/C][C]0.11298[/C][/ROW]
[ROW][C]152[/C][C]0.883871[/C][C]0.232258[/C][C]0.116129[/C][/ROW]
[ROW][C]153[/C][C]0.908613[/C][C]0.182773[/C][C]0.0913866[/C][/ROW]
[ROW][C]154[/C][C]0.910458[/C][C]0.179083[/C][C]0.0895416[/C][/ROW]
[ROW][C]155[/C][C]0.898568[/C][C]0.202863[/C][C]0.101432[/C][/ROW]
[ROW][C]156[/C][C]0.883538[/C][C]0.232923[/C][C]0.116462[/C][/ROW]
[ROW][C]157[/C][C]0.912602[/C][C]0.174795[/C][C]0.0873977[/C][/ROW]
[ROW][C]158[/C][C]0.90784[/C][C]0.18432[/C][C]0.0921598[/C][/ROW]
[ROW][C]159[/C][C]0.896491[/C][C]0.207018[/C][C]0.103509[/C][/ROW]
[ROW][C]160[/C][C]0.892131[/C][C]0.215738[/C][C]0.107869[/C][/ROW]
[ROW][C]161[/C][C]0.910008[/C][C]0.179984[/C][C]0.089992[/C][/ROW]
[ROW][C]162[/C][C]0.9099[/C][C]0.180199[/C][C]0.0900995[/C][/ROW]
[ROW][C]163[/C][C]0.907548[/C][C]0.184905[/C][C]0.0924523[/C][/ROW]
[ROW][C]164[/C][C]0.90203[/C][C]0.19594[/C][C]0.0979699[/C][/ROW]
[ROW][C]165[/C][C]0.921309[/C][C]0.157381[/C][C]0.0786906[/C][/ROW]
[ROW][C]166[/C][C]0.910347[/C][C]0.179306[/C][C]0.0896531[/C][/ROW]
[ROW][C]167[/C][C]0.931056[/C][C]0.137889[/C][C]0.0689443[/C][/ROW]
[ROW][C]168[/C][C]0.92538[/C][C]0.149239[/C][C]0.0746197[/C][/ROW]
[ROW][C]169[/C][C]0.913796[/C][C]0.172408[/C][C]0.0862038[/C][/ROW]
[ROW][C]170[/C][C]0.913061[/C][C]0.173878[/C][C]0.086939[/C][/ROW]
[ROW][C]171[/C][C]0.912053[/C][C]0.175894[/C][C]0.0879468[/C][/ROW]
[ROW][C]172[/C][C]0.920404[/C][C]0.159192[/C][C]0.0795958[/C][/ROW]
[ROW][C]173[/C][C]0.911867[/C][C]0.176266[/C][C]0.088133[/C][/ROW]
[ROW][C]174[/C][C]0.903167[/C][C]0.193666[/C][C]0.096833[/C][/ROW]
[ROW][C]175[/C][C]0.894887[/C][C]0.210226[/C][C]0.105113[/C][/ROW]
[ROW][C]176[/C][C]0.922604[/C][C]0.154791[/C][C]0.0773957[/C][/ROW]
[ROW][C]177[/C][C]0.908504[/C][C]0.182991[/C][C]0.0914957[/C][/ROW]
[ROW][C]178[/C][C]0.933112[/C][C]0.133777[/C][C]0.0668885[/C][/ROW]
[ROW][C]179[/C][C]0.928625[/C][C]0.14275[/C][C]0.071375[/C][/ROW]
[ROW][C]180[/C][C]0.960016[/C][C]0.0799673[/C][C]0.0399836[/C][/ROW]
[ROW][C]181[/C][C]0.954229[/C][C]0.091542[/C][C]0.045771[/C][/ROW]
[ROW][C]182[/C][C]0.945921[/C][C]0.108157[/C][C]0.0540787[/C][/ROW]
[ROW][C]183[/C][C]0.972711[/C][C]0.0545789[/C][C]0.0272894[/C][/ROW]
[ROW][C]184[/C][C]0.968069[/C][C]0.0638614[/C][C]0.0319307[/C][/ROW]
[ROW][C]185[/C][C]0.961142[/C][C]0.0777156[/C][C]0.0388578[/C][/ROW]
[ROW][C]186[/C][C]0.955399[/C][C]0.0892015[/C][C]0.0446007[/C][/ROW]
[ROW][C]187[/C][C]0.953917[/C][C]0.0921664[/C][C]0.0460832[/C][/ROW]
[ROW][C]188[/C][C]0.94795[/C][C]0.1041[/C][C]0.0520502[/C][/ROW]
[ROW][C]189[/C][C]0.947551[/C][C]0.104899[/C][C]0.0524493[/C][/ROW]
[ROW][C]190[/C][C]0.936763[/C][C]0.126475[/C][C]0.0632374[/C][/ROW]
[ROW][C]191[/C][C]0.93131[/C][C]0.137381[/C][C]0.0686904[/C][/ROW]
[ROW][C]192[/C][C]0.929248[/C][C]0.141503[/C][C]0.0707515[/C][/ROW]
[ROW][C]193[/C][C]0.93599[/C][C]0.12802[/C][C]0.0640098[/C][/ROW]
[ROW][C]194[/C][C]0.937921[/C][C]0.124158[/C][C]0.0620788[/C][/ROW]
[ROW][C]195[/C][C]0.928936[/C][C]0.142128[/C][C]0.0710638[/C][/ROW]
[ROW][C]196[/C][C]0.916389[/C][C]0.167221[/C][C]0.0836105[/C][/ROW]
[ROW][C]197[/C][C]0.903147[/C][C]0.193706[/C][C]0.0968532[/C][/ROW]
[ROW][C]198[/C][C]0.888184[/C][C]0.223632[/C][C]0.111816[/C][/ROW]
[ROW][C]199[/C][C]0.870603[/C][C]0.258794[/C][C]0.129397[/C][/ROW]
[ROW][C]200[/C][C]0.853105[/C][C]0.29379[/C][C]0.146895[/C][/ROW]
[ROW][C]201[/C][C]0.885519[/C][C]0.228962[/C][C]0.114481[/C][/ROW]
[ROW][C]202[/C][C]0.865304[/C][C]0.269392[/C][C]0.134696[/C][/ROW]
[ROW][C]203[/C][C]0.849032[/C][C]0.301937[/C][C]0.150968[/C][/ROW]
[ROW][C]204[/C][C]0.831055[/C][C]0.33789[/C][C]0.168945[/C][/ROW]
[ROW][C]205[/C][C]0.80641[/C][C]0.38718[/C][C]0.19359[/C][/ROW]
[ROW][C]206[/C][C]0.782475[/C][C]0.43505[/C][C]0.217525[/C][/ROW]
[ROW][C]207[/C][C]0.77815[/C][C]0.4437[/C][C]0.22185[/C][/ROW]
[ROW][C]208[/C][C]0.747261[/C][C]0.505477[/C][C]0.252739[/C][/ROW]
[ROW][C]209[/C][C]0.785112[/C][C]0.429776[/C][C]0.214888[/C][/ROW]
[ROW][C]210[/C][C]0.80821[/C][C]0.38358[/C][C]0.19179[/C][/ROW]
[ROW][C]211[/C][C]0.785829[/C][C]0.428342[/C][C]0.214171[/C][/ROW]
[ROW][C]212[/C][C]0.775723[/C][C]0.448554[/C][C]0.224277[/C][/ROW]
[ROW][C]213[/C][C]0.771978[/C][C]0.456045[/C][C]0.228022[/C][/ROW]
[ROW][C]214[/C][C]0.74936[/C][C]0.50128[/C][C]0.25064[/C][/ROW]
[ROW][C]215[/C][C]0.728508[/C][C]0.542983[/C][C]0.271492[/C][/ROW]
[ROW][C]216[/C][C]0.693179[/C][C]0.613641[/C][C]0.306821[/C][/ROW]
[ROW][C]217[/C][C]0.695066[/C][C]0.609867[/C][C]0.304934[/C][/ROW]
[ROW][C]218[/C][C]0.761714[/C][C]0.476572[/C][C]0.238286[/C][/ROW]
[ROW][C]219[/C][C]0.729428[/C][C]0.541145[/C][C]0.270572[/C][/ROW]
[ROW][C]220[/C][C]0.696072[/C][C]0.607856[/C][C]0.303928[/C][/ROW]
[ROW][C]221[/C][C]0.700278[/C][C]0.599444[/C][C]0.299722[/C][/ROW]
[ROW][C]222[/C][C]0.823696[/C][C]0.352608[/C][C]0.176304[/C][/ROW]
[ROW][C]223[/C][C]0.793567[/C][C]0.412866[/C][C]0.206433[/C][/ROW]
[ROW][C]224[/C][C]0.807596[/C][C]0.384807[/C][C]0.192404[/C][/ROW]
[ROW][C]225[/C][C]0.843225[/C][C]0.313551[/C][C]0.156775[/C][/ROW]
[ROW][C]226[/C][C]0.816072[/C][C]0.367856[/C][C]0.183928[/C][/ROW]
[ROW][C]227[/C][C]0.7933[/C][C]0.413401[/C][C]0.2067[/C][/ROW]
[ROW][C]228[/C][C]0.790594[/C][C]0.418813[/C][C]0.209406[/C][/ROW]
[ROW][C]229[/C][C]0.876802[/C][C]0.246396[/C][C]0.123198[/C][/ROW]
[ROW][C]230[/C][C]0.898649[/C][C]0.202702[/C][C]0.101351[/C][/ROW]
[ROW][C]231[/C][C]0.89922[/C][C]0.20156[/C][C]0.10078[/C][/ROW]
[ROW][C]232[/C][C]0.916496[/C][C]0.167008[/C][C]0.0835042[/C][/ROW]
[ROW][C]233[/C][C]0.899376[/C][C]0.201249[/C][C]0.100624[/C][/ROW]
[ROW][C]234[/C][C]0.882417[/C][C]0.235166[/C][C]0.117583[/C][/ROW]
[ROW][C]235[/C][C]0.870485[/C][C]0.259029[/C][C]0.129515[/C][/ROW]
[ROW][C]236[/C][C]0.974547[/C][C]0.0509064[/C][C]0.0254532[/C][/ROW]
[ROW][C]237[/C][C]0.972304[/C][C]0.0553918[/C][C]0.0276959[/C][/ROW]
[ROW][C]238[/C][C]0.964123[/C][C]0.0717545[/C][C]0.0358772[/C][/ROW]
[ROW][C]239[/C][C]0.959079[/C][C]0.0818418[/C][C]0.0409209[/C][/ROW]
[ROW][C]240[/C][C]0.945529[/C][C]0.108943[/C][C]0.0544714[/C][/ROW]
[ROW][C]241[/C][C]0.942536[/C][C]0.114927[/C][C]0.0574635[/C][/ROW]
[ROW][C]242[/C][C]0.927747[/C][C]0.144506[/C][C]0.0722532[/C][/ROW]
[ROW][C]243[/C][C]0.91648[/C][C]0.167039[/C][C]0.0835196[/C][/ROW]
[ROW][C]244[/C][C]0.947826[/C][C]0.104348[/C][C]0.0521741[/C][/ROW]
[ROW][C]245[/C][C]0.933969[/C][C]0.132063[/C][C]0.0660314[/C][/ROW]
[ROW][C]246[/C][C]0.934109[/C][C]0.131781[/C][C]0.0658906[/C][/ROW]
[ROW][C]247[/C][C]0.927824[/C][C]0.144351[/C][C]0.0721757[/C][/ROW]
[ROW][C]248[/C][C]0.922089[/C][C]0.155822[/C][C]0.0779108[/C][/ROW]
[ROW][C]249[/C][C]0.898405[/C][C]0.203189[/C][C]0.101595[/C][/ROW]
[ROW][C]250[/C][C]0.867927[/C][C]0.264147[/C][C]0.132073[/C][/ROW]
[ROW][C]251[/C][C]0.829499[/C][C]0.341002[/C][C]0.170501[/C][/ROW]
[ROW][C]252[/C][C]0.810711[/C][C]0.378578[/C][C]0.189289[/C][/ROW]
[ROW][C]253[/C][C]0.815018[/C][C]0.369963[/C][C]0.184982[/C][/ROW]
[ROW][C]254[/C][C]0.851113[/C][C]0.297774[/C][C]0.148887[/C][/ROW]
[ROW][C]255[/C][C]0.927802[/C][C]0.144396[/C][C]0.0721982[/C][/ROW]
[ROW][C]256[/C][C]0.900397[/C][C]0.199206[/C][C]0.0996028[/C][/ROW]
[ROW][C]257[/C][C]0.914901[/C][C]0.170197[/C][C]0.0850985[/C][/ROW]
[ROW][C]258[/C][C]0.99307[/C][C]0.0138598[/C][C]0.00692988[/C][/ROW]
[ROW][C]259[/C][C]0.988244[/C][C]0.0235126[/C][C]0.0117563[/C][/ROW]
[ROW][C]260[/C][C]0.996496[/C][C]0.00700754[/C][C]0.00350377[/C][/ROW]
[ROW][C]261[/C][C]0.994851[/C][C]0.0102973[/C][C]0.00514867[/C][/ROW]
[ROW][C]262[/C][C]0.994854[/C][C]0.0102921[/C][C]0.00514603[/C][/ROW]
[ROW][C]263[/C][C]0.989186[/C][C]0.0216273[/C][C]0.0108136[/C][/ROW]
[ROW][C]264[/C][C]0.984901[/C][C]0.0301981[/C][C]0.015099[/C][/ROW]
[ROW][C]265[/C][C]0.973141[/C][C]0.0537184[/C][C]0.0268592[/C][/ROW]
[ROW][C]266[/C][C]0.946382[/C][C]0.107236[/C][C]0.0536179[/C][/ROW]
[ROW][C]267[/C][C]0.912405[/C][C]0.17519[/C][C]0.0875951[/C][/ROW]
[ROW][C]268[/C][C]0.893325[/C][C]0.213349[/C][C]0.106675[/C][/ROW]
[ROW][C]269[/C][C]0.866428[/C][C]0.267145[/C][C]0.133572[/C][/ROW]
[ROW][C]270[/C][C]0.920055[/C][C]0.15989[/C][C]0.0799449[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270049&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270049&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.3405650.681130.659435
90.2101180.4202350.789882
100.1306950.2613890.869305
110.07163790.1432760.928362
120.08013280.1602660.919867
130.05426760.1085350.945732
140.02978810.05957610.970212
150.1205470.2410950.879453
160.1062250.2124510.893775
170.07229510.144590.927705
180.05094980.10190.94905
190.03271680.06543360.967283
200.01991090.03982190.980089
210.02047040.04094080.97953
220.0235890.04717810.976411
230.014730.02945990.98527
240.02323740.04647480.976763
250.01473520.02947030.985265
260.009189660.01837930.99081
270.02202960.04405920.97797
280.01449750.02899510.985502
290.009684020.0193680.990316
300.00615470.01230940.993845
310.02219070.04438130.977809
320.01673620.03347240.983264
330.01560150.03120290.984399
340.01208260.02416520.987917
350.008643370.01728670.991357
360.005831130.01166230.994169
370.003925950.007851910.996074
380.002615110.005230220.997385
390.001975170.003950330.998025
400.001316740.002633490.998683
410.002947120.005894240.997053
420.00225140.004502790.997749
430.002199870.004399740.9978
440.001464950.002929890.998535
450.0009340890.001868180.999066
460.0007432270.001486450.999257
470.0004868340.0009736690.999513
480.0004362240.0008724490.999564
490.0004053840.0008107690.999595
500.0003344430.0006688860.999666
510.0002271950.000454390.999773
520.0006615960.001323190.999338
530.0004502140.0009004280.99955
540.0003780370.0007560730.999622
550.0004820280.0009640560.999518
560.0003273260.0006546520.999673
570.001859050.003718090.998141
580.001493880.002987760.998506
590.001573060.003146130.998427
600.001580670.003161350.998419
610.001251550.002503090.998748
620.001021370.002042750.998979
630.002665340.005330680.997335
640.00492840.00985680.995072
650.004634120.009268230.995366
660.004361160.008722320.995639
670.00331860.00663720.996681
680.002935430.005870870.997065
690.003256230.006512460.996744
700.002576250.005152510.997424
710.002033370.004066750.997967
720.001575890.003151780.998424
730.001641180.003282360.998359
740.00203550.004071010.997964
750.001611550.00322310.998388
760.001316780.002633560.998683
770.0009886390.001977280.999011
780.0009238590.001847720.999076
790.0007612830.001522570.999239
800.0009593660.001918730.999041
810.0007648360.001529670.999235
820.0006940410.001388080.999306
830.000525890.001051780.999474
840.002798670.005597330.997201
850.002406180.004812360.997594
860.001846970.003693950.998153
870.0014160.0028320.998584
880.001104040.002208070.998896
890.001255230.002510460.998745
900.001099110.002198210.998901
910.0008639460.001727890.999136
920.002358280.004716550.997642
930.001999160.003998330.998001
940.002038520.004077040.997961
950.002779150.00555830.997221
960.003077030.006154060.996923
970.004376870.008753740.995623
980.003499280.006998560.996501
990.003199130.006398270.996801
1000.003890340.007780670.99611
1010.003179520.006359030.99682
1020.002875850.005751710.997124
1030.003161160.006322320.996839
1040.002877310.005754610.997123
1050.002991370.005982740.997009
1060.003919360.007838720.996081
1070.003681170.007362340.996319
1080.01542210.03084410.984578
1090.035460.070920.96454
1100.04032880.08065750.959671
1110.03844980.07689970.96155
1120.03429590.06859170.965704
1130.1291520.2583040.870848
1140.1166210.2332420.883379
1150.2162070.4324140.783793
1160.3264430.6528860.673557
1170.3811450.7622890.618855
1180.3574870.7149750.642513
1190.4225250.8450510.577475
1200.5675890.8648230.432411
1210.6054540.7890910.394546
1220.59140.81720.4086
1230.6554690.6890630.344531
1240.6598250.6803510.340175
1250.6492040.7015920.350796
1260.6245110.7509770.375489
1270.6568030.6863940.343197
1280.6357080.7285850.364292
1290.7533730.4932540.246627
1300.7375820.5248360.262418
1310.7255460.5489070.274454
1320.7381320.5237360.261868
1330.733810.5323810.26619
1340.7253670.5492650.274633
1350.6998030.6003940.300197
1360.6768770.6462460.323123
1370.7187810.5624390.281219
1380.7424880.5150240.257512
1390.8041280.3917430.195872
1400.8000160.3999680.199984
1410.7762350.4475310.223765
1420.8274350.345130.172565
1430.8254580.3490840.174542
1440.8723320.2553360.127668
1450.8755540.2488910.124446
1460.8840160.2319680.115984
1470.8705890.2588230.129411
1480.8586490.2827020.141351
1490.8461160.3077690.153884
1500.8804460.2391080.119554
1510.887020.2259590.11298
1520.8838710.2322580.116129
1530.9086130.1827730.0913866
1540.9104580.1790830.0895416
1550.8985680.2028630.101432
1560.8835380.2329230.116462
1570.9126020.1747950.0873977
1580.907840.184320.0921598
1590.8964910.2070180.103509
1600.8921310.2157380.107869
1610.9100080.1799840.089992
1620.90990.1801990.0900995
1630.9075480.1849050.0924523
1640.902030.195940.0979699
1650.9213090.1573810.0786906
1660.9103470.1793060.0896531
1670.9310560.1378890.0689443
1680.925380.1492390.0746197
1690.9137960.1724080.0862038
1700.9130610.1738780.086939
1710.9120530.1758940.0879468
1720.9204040.1591920.0795958
1730.9118670.1762660.088133
1740.9031670.1936660.096833
1750.8948870.2102260.105113
1760.9226040.1547910.0773957
1770.9085040.1829910.0914957
1780.9331120.1337770.0668885
1790.9286250.142750.071375
1800.9600160.07996730.0399836
1810.9542290.0915420.045771
1820.9459210.1081570.0540787
1830.9727110.05457890.0272894
1840.9680690.06386140.0319307
1850.9611420.07771560.0388578
1860.9553990.08920150.0446007
1870.9539170.09216640.0460832
1880.947950.10410.0520502
1890.9475510.1048990.0524493
1900.9367630.1264750.0632374
1910.931310.1373810.0686904
1920.9292480.1415030.0707515
1930.935990.128020.0640098
1940.9379210.1241580.0620788
1950.9289360.1421280.0710638
1960.9163890.1672210.0836105
1970.9031470.1937060.0968532
1980.8881840.2236320.111816
1990.8706030.2587940.129397
2000.8531050.293790.146895
2010.8855190.2289620.114481
2020.8653040.2693920.134696
2030.8490320.3019370.150968
2040.8310550.337890.168945
2050.806410.387180.19359
2060.7824750.435050.217525
2070.778150.44370.22185
2080.7472610.5054770.252739
2090.7851120.4297760.214888
2100.808210.383580.19179
2110.7858290.4283420.214171
2120.7757230.4485540.224277
2130.7719780.4560450.228022
2140.749360.501280.25064
2150.7285080.5429830.271492
2160.6931790.6136410.306821
2170.6950660.6098670.304934
2180.7617140.4765720.238286
2190.7294280.5411450.270572
2200.6960720.6078560.303928
2210.7002780.5994440.299722
2220.8236960.3526080.176304
2230.7935670.4128660.206433
2240.8075960.3848070.192404
2250.8432250.3135510.156775
2260.8160720.3678560.183928
2270.79330.4134010.2067
2280.7905940.4188130.209406
2290.8768020.2463960.123198
2300.8986490.2027020.101351
2310.899220.201560.10078
2320.9164960.1670080.0835042
2330.8993760.2012490.100624
2340.8824170.2351660.117583
2350.8704850.2590290.129515
2360.9745470.05090640.0254532
2370.9723040.05539180.0276959
2380.9641230.07175450.0358772
2390.9590790.08184180.0409209
2400.9455290.1089430.0544714
2410.9425360.1149270.0574635
2420.9277470.1445060.0722532
2430.916480.1670390.0835196
2440.9478260.1043480.0521741
2450.9339690.1320630.0660314
2460.9341090.1317810.0658906
2470.9278240.1443510.0721757
2480.9220890.1558220.0779108
2490.8984050.2031890.101595
2500.8679270.2641470.132073
2510.8294990.3410020.170501
2520.8107110.3785780.189289
2530.8150180.3699630.184982
2540.8511130.2977740.148887
2550.9278020.1443960.0721982
2560.9003970.1992060.0996028
2570.9149010.1701970.0850985
2580.993070.01385980.00692988
2590.9882440.02351260.0117563
2600.9964960.007007540.00350377
2610.9948510.01029730.00514867
2620.9948540.01029210.00514603
2630.9891860.02162730.0108136
2640.9849010.03019810.015099
2650.9731410.05371840.0268592
2660.9463820.1072360.0536179
2670.9124050.175190.0875951
2680.8933250.2133490.106675
2690.8664280.2671450.133572
2700.9200550.159890.0799449






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level720.273764NOK
5% type I error level960.365019NOK
10% type I error level1140.43346NOK

\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 & 72 & 0.273764 & NOK \tabularnewline
5% type I error level & 96 & 0.365019 & NOK \tabularnewline
10% type I error level & 114 & 0.43346 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270049&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]72[/C][C]0.273764[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]96[/C][C]0.365019[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]114[/C][C]0.43346[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270049&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270049&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level720.273764NOK
5% type I error level960.365019NOK
10% type I error level1140.43346NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
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 <- 'Do not include Seasonal 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')
}