FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationThu, 18 Dec 2014 14:22:30 +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/18/t1418913195a9pn1ouvrikfpaj.htm/, Retrieved Sun, 19 May 2024 17:01:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270999, Retrieved Sun, 19 May 2024 17:01:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact72

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-18 14:22:30] [6341ece6c012999a305a5ce37b6a24ca] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	149	86	12,9
1	139	70	12,2
1	148	71	12,8
1	158	108	7,4
1	128	64	6,7
1	224	119	12,6
1	159	97	14,8
1	105	129	13,3
1	159	153	11,1
1	167	78	8,2
1	165	80	11,4
1	159	99	6,4
1	119	68	10,6
1	176	147	12
1	54	40	6,3
0	91	57	11,3
1	163	120	11,9
1	124	71	9,3
0	137	84	9,6
1	121	68	10
1	153	55	6,4
1	148	137	13,8
1	221	79	10,8
1	188	116	13,8
1	149	101	11,7
1	244	111	10,9
0	148	189	16,1
0	92	66	13,4
1	150	81	9,9
1	153	63	11,5
1	94	69	8,3
1	156	71	11,7
1	132	64	9
1	161	143	9,7
1	105	85	10,8
1	97	86	10,3
1	151	55	10,4
0	131	69	12,7
1	166	120	9,3
1	157	96	11,8
1	111	60	5,9
1	145	95	11,4
1	162	100	13
1	163	68	10,8
0	59	57	12,3
1	187	105	11,3
1	109	85	11,8
0	90	103	7,9
1	105	57	12,7
0	83	51	12,3
0	116	69	11,6
0	42	41	6,7
1	148	49	10,9
0	155	50	12,1
1	125	93	13,3
1	116	58	10,1
0	128	54	5,7
1	138	74	14,3
0	49	15	8
0	96	69	13,3
1	164	107	9,3
1	162	65	12,5
1	99	58	7,6
1	202	107	15,9
1	186	70	9,2
0	66	53	9,1
1	183	136	11,1
1	214	126	13
1	188	95	14,5
0	104	69	12,2
1	177	136	12,3
1	126	58	11,4
0	76	59	8,8
0	99	118	14,6
1	139	82	12,6
1	162	102	13
0	108	65	12,6
1	159	90	13,2
0	74	64	9,9
1	110	83	7,7
0	96	70	10,5
0	116	50	13,4
0	87	77	10,9
0	97	37	4,3
0	127	81	10,3
0	106	101	11,8
0	80	79	11,2
0	74	71	11,4
0	91	60	8,6
0	133	55	13,2
0	74	44	12,6
0	114	40	5,6
0	140	56	9,9
0	95	43	8,8
0	98	45	7,7
0	121	32	9
0	126	56	7,3
0	98	40	11,4
0	95	34	13,6
0	110	89	7,9
0	70	50	10,7
0	102	56	10,3
0	86	46	8,3
0	130	76	9,6
0	96	64	14,2
0	102	74	8,5
0	100	57	13,5
0	94	45	4,9
0	52	30	6,4
0	98	62	9,6
0	118	51	11,6
0	99	36	11,1
1	48	34	4,35
1	50	61	12,7
1	150	70	18,1
1	154	69	17,85
0	109	145	16,6
0	68	23	12,6
1	194	120	17,1
1	158	147	19,1
1	159	215	16,1
1	67	24	13,35
1	147	84	18,4
1	39	30	14,7
1	100	77	10,6
1	111	46	12,6
1	138	61	16,2
1	101	178	13,6
0	131	160	18,9
1	101	57	14,1
1	114	42	14,5
1	165	163	16,15
1	114	75	14,75
1	111	94	14,8
1	75	45	12,45
1	82	78	12,65
1	121	47	17,35
1	32	29	8,6
1	150	97	18,4
1	117	116	16,1
0	71	32	11,6
1	165	50	17,75
1	154	118	15,25
1	126	66	17,65
1	149	86	16,35
1	145	89	17,65
1	120	76	13,6
1	109	75	14,35
1	132	57	14,75
1	172	72	18,25
1	169	60	9,9
1	114	109	16
1	156	76	18,25
1	172	65	16,85
0	68	40	14,6
0	89	58	13,85
1	167	123	18,95
1	113	71	15,6
0	115	102	14,85
0	78	80	11,75
0	118	97	18,45
0	87	46	15,9
1	173	93	17,1
1	2	19	16,1
0	162	140	19,9
0	49	78	10,95
0	122	98	18,45
0	96	40	15,1
0	100	80	15
0	82	76	11,35
0	100	79	15,95
0	115	87	18,1
0	141	95	14,6
1	165	49	15,4
1	165	49	15,4
0	110	80	17,6
1	118	86	13,35
1	158	69	19,1
0	146	79	15,35
1	49	52	7,6
0	90	120	13,4
0	121	69	13,9
1	155	94	19,1
0	104	72	15,25
0	147	43	12,9
0	110	87	16,1
0	108	52	17,35
0	113	71	13,15
0	115	61	12,15
0	61	51	12,6
0	60	50	10,35
0	109	67	15,4
0	68	30	9,6
0	111	70	18,2
0	77	52	13,6
0	73	75	14,85
1	151	87	14,75
0	89	69	14,1
0	78	72	14,9
0	110	79	16,25
1	220	121	19,25
0	65	43	13,6
1	141	58	13,6
0	117	57	15,65
1	122	50	12,75
0	63	69	14,6
1	44	64	9,85
0	52	38	12,65
0	131	90	19,2
0	101	96	16,6
0	42	49	11,2
1	152	56	15,25
1	107	102	11,9
0	77	40	13,2
1	154	100	16,35
1	103	67	12,4
0	96	78	15,85
1	175	55	18,15
0	57	59	11,15
0	112	96	15,65
1	143	86	17,75
0	49	38	7,65
1	110	43	12,35
1	131	23	15,6
1	167	77	19,3
0	56	48	15,2
1	137	26	17,1
0	86	91	15,6
1	121	94	18,4
1	149	62	19,05
1	168	74	18,55
1	140	114	19,1
0	88	52	13,1
1	168	64	12,85
1	94	31	9,5
1	51	38	4,5
0	48	27	11,85
1	145	105	13,6
1	66	64	11,7
0	85	62	12,4
1	109	65	13,35
0	63	58	11,4
0	102	76	14,9
0	162	140	19,9
0	86	68	11,2
0	114	80	14,6
1	164	71	17,6
1	119	76	14,05
1	126	63	16,1
1	132	46	13,35
1	142	53	11,85
1	83	74	11,95
0	94	70	14,75
0	81	78	15,15
1	166	56	13,2
0	110	100	16,85
0	64	51	7,85
1	93	52	7,7
0	104	102	12,6
0	105	78	7,85
0	49	78	10,95
0	88	55	12,35
0	95	98	9,95
0	102	76	14,9
0	99	73	16,65
0	63	47	13,4
0	76	45	13,95
0	109	83	15,7
0	117	60	16,85
0	57	48	10,95
0	120	50	15,35
0	73	56	12,2
0	91	77	15,1
0	108	91	17,75
0	105	76	15,2
1	117	68	14,6
0	119	74	16,65
0	31	29	8,1

Tables (Output of Computation)





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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270999&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=270999&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270999&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] = + 9.13494 -0.701374Studierichting[t] + 0.0211242LFM[t] + 0.0235065H[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  9.13494 -0.701374Studierichting[t] +  0.0211242LFM[t] +  0.0235065H[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270999&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  9.13494 -0.701374Studierichting[t] +  0.0211242LFM[t] +  0.0235065H[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270999&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270999&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] = + 9.13494 -0.701374Studierichting[t] + 0.0211242LFM[t] + 0.0235065H[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.134940.63204614.451.4042e-357.02099e-36
Studierichting-0.7013740.445798-1.5730.1168040.0584018
LFM0.02112420.006387373.3070.001068280.000534142
H0.02350650.007364313.1920.001577780.000788889

\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) & 9.13494 & 0.632046 & 14.45 & 1.4042e-35 & 7.02099e-36 \tabularnewline
Studierichting & -0.701374 & 0.445798 & -1.573 & 0.116804 & 0.0584018 \tabularnewline
LFM & 0.0211242 & 0.00638737 & 3.307 & 0.00106828 & 0.000534142 \tabularnewline
H & 0.0235065 & 0.00736431 & 3.192 & 0.00157778 & 0.000788889 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270999&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]9.13494[/C][C]0.632046[/C][C]14.45[/C][C]1.4042e-35[/C][C]7.02099e-36[/C][/ROW]
[ROW][C]Studierichting[/C][C]-0.701374[/C][C]0.445798[/C][C]-1.573[/C][C]0.116804[/C][C]0.0584018[/C][/ROW]
[ROW][C]LFM[/C][C]0.0211242[/C][C]0.00638737[/C][C]3.307[/C][C]0.00106828[/C][C]0.000534142[/C][/ROW]
[ROW][C]H[/C][C]0.0235065[/C][C]0.00736431[/C][C]3.192[/C][C]0.00157778[/C][C]0.000788889[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270999&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270999&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)9.134940.63204614.451.4042e-357.02099e-36
Studierichting-0.7013740.445798-1.5730.1168040.0584018
LFM0.02112420.006387373.3070.001068280.000534142
H0.02350650.007364313.1920.001577780.000788889






Multiple Linear Regression - Regression Statistics
Multiple R0.366158
R-squared0.134072
Adjusted R-squared0.124591
F-TEST (value)14.1412
F-TEST (DF numerator)3
F-TEST (DF denominator)274
p-value1.35055e-08
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.17587
Sum Squared Residuals2763.61

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.366158 \tabularnewline
R-squared & 0.134072 \tabularnewline
Adjusted R-squared & 0.124591 \tabularnewline
F-TEST (value) & 14.1412 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 274 \tabularnewline
p-value & 1.35055e-08 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.17587 \tabularnewline
Sum Squared Residuals & 2763.61 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270999&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.366158[/C][/ROW]
[ROW][C]R-squared[/C][C]0.134072[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.124591[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]14.1412[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]274[/C][/ROW]
[ROW][C]p-value[/C][C]1.35055e-08[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.17587[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2763.61[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270999&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270999&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 R0.366158
R-squared0.134072
Adjusted R-squared0.124591
F-TEST (value)14.1412
F-TEST (DF numerator)3
F-TEST (DF denominator)274
p-value1.35055e-08
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.17587
Sum Squared Residuals2763.61






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.6026-0.702632
212.213.0153-0.815287
312.813.2289-0.428911
47.414.3099-6.90989
56.712.6419-5.94188
612.615.9627-3.36266
714.814.07240.727554
813.313.6839-0.383947
911.115.3888-4.28881
108.213.7948-5.59482
1111.413.7996-2.39958
126.414.1195-7.71946
1310.612.5458-1.94579
141215.6069-3.60688
156.310.5145-4.21454
1611.312.3971-1.09711
1711.914.6976-2.79759
189.312.7219-3.42193
199.614.0035-4.4035
201012.588-2.58804
216.412.9584-6.55843
2213.814.7803-0.980339
2310.814.959-4.15903
2413.815.1317-1.33167
2511.713.9552-2.25523
2610.916.1971-5.29709
2716.116.7041-0.60405
2813.412.62980.770203
299.913.5062-3.60622
3011.513.1465-1.64648
318.312.0412-3.74119
3211.713.3979-1.6979
33912.7264-3.72638
349.715.196-5.49599
3510.812.6497-1.84966
3610.312.5042-2.20417
3710.412.9162-2.51618
3812.713.5242-0.82416
399.314.761-5.46096
4011.814.0067-2.20669
415.912.1887-6.28874
4211.413.7297-2.32969
431314.2063-1.20634
4410.813.4753-2.67525
4512.311.72110.57886
4611.314.852-3.55197
4711.812.7342-0.934158
487.913.4573-5.55729
4912.711.99150.70852
5012.312.08710.212918
5111.613.2073-1.6073
526.710.9859-4.28593
5310.912.7118-1.81177
5412.113.5845-1.48452
5513.313.26020.0398029
5610.112.2474-2.14735
575.713.1082-7.40819
5814.313.08821.21181
59810.5226-2.52263
6013.312.78480.515187
619.314.4131-5.11313
6212.513.3836-0.883611
637.611.8882-4.28824
6415.915.21590.684149
659.214.0081-4.80812
669.111.775-2.67498
6711.115.4962-4.39618
681315.916-2.91596
6914.514.638-0.138034
7012.212.9538-0.753807
7112.315.3694-3.06943
7211.412.4586-1.05859
738.812.1273-3.32726
7414.6140.599996
7512.613.2974-0.697364
761314.2534-1.25335
7712.612.9443-0.344278
7813.213.9079-0.7079
799.912.2025-2.30255
807.712.7083-5.00827
8110.512.8083-2.30832
8213.412.76070.639326
8310.912.7827-1.88275
844.312.0537-7.75373
8510.313.7217-3.42174
8611.813.7483-1.94826
8711.212.6819-1.48189
8811.412.3671-0.967094
898.612.4676-3.86763
9013.213.2373-0.0373177
9112.611.73240.867581
925.612.4834-6.88336
939.913.4087-3.50869
948.812.1525-3.35252
957.712.2629-4.56291
96912.4432-3.44318
977.313.113-5.81295
9811.412.1454-0.745374
9913.611.9411.65904
1007.913.5507-5.65068
10110.711.789-1.08896
10210.312.606-2.30597
1038.312.0329-3.73292
1049.613.6676-4.06758
10514.212.66731.53272
1068.513.0291-4.52909
10713.512.58720.912768
1084.912.1784-7.27841
1096.410.9386-4.5386
1109.612.6625-3.06252
11111.612.8264-1.22643
11211.112.0725-0.972472
1134.3510.2468-5.89675
11412.710.92371.77633
11518.113.24774.85235
11617.8513.30864.54136
11716.614.84591.75408
11812.611.1121.48796
11917.115.35241.74756
12019.115.22663.87335
12116.116.8462-0.746211
12213.3510.4132.93695
12318.413.51344.88663
12414.79.962614.73739
12510.612.356-1.75599
12612.611.85970.740347
12716.212.78263.4174
12813.614.7513-1.15127
12918.915.66333.23675
13014.111.9072.19302
13114.511.8292.671
13216.1515.75060.399381
13314.7512.60472.14529
13414.812.9881.81204
13512.4511.07571.37432
13612.6511.99930.650741
13717.3512.09445.2556
1388.69.79123-1.19123
13918.413.88234.51767
14016.113.63192.46815
14111.611.3870.213032
14217.7513.09444.65561
14315.2514.46050.789539
14417.6512.64665.00335
14516.3513.60262.74737
14617.6513.58874.06134
14713.612.7550.845034
14814.3512.49911.85091
14914.7512.56182.18817
15018.2513.75944.4906
1519.913.4139-3.51395
1521613.40392.59607
15318.2513.51544.73456
15416.8513.59493.25515
15514.611.51163.08835
15613.8512.37841.47163
15718.9514.85264.09739
15815.612.48963.11044
15914.8513.96190.888113
16011.7512.6631-0.913149
16118.4513.90774.54227
16215.912.0543.84595
16317.114.27422.82584
16416.18.922447.17756
16519.915.8484.05203
16610.9512.0035-1.05353
16718.4514.01574.43427
16815.112.10312.99687
1691513.12791.87212
17011.3512.6536-1.30362
17115.9513.10442.84562
17218.113.60934.49071
17314.614.34660.253429
17415.413.07092.32912
17515.413.07092.32912
17617.613.33914.26088
17713.3512.94780.402218
17819.113.39315.70686
17915.3514.07611.27391
1807.610.691-3.09099
18113.413.8569-0.456899
18213.913.31290.587082
18319.113.91745.18257
18415.2513.02432.22567
18512.913.251-0.350979
18616.113.50372.59633
18717.3512.63874.71131
18813.1513.1909-0.0409376
18912.1512.9981-0.848121
19012.611.62230.97765
19110.3511.5777-1.22772
19215.413.01242.38759
1939.611.2766-1.67658
19418.213.12525.07482
19513.611.98381.61616
19614.8512.442.41
19714.7513.66841.08161
19814.112.63691.46306
19914.912.47512.4249
20016.2513.31562.93438
20119.2515.92523.32482
20213.611.51882.08121
20313.612.77550.824543
20415.6512.94632.70366
20512.7512.1860.563955
20614.612.08772.51229
2079.8510.8674-1.01745
20812.6511.12661.52335
20919.214.01785.1822
21016.613.52513.07489
21111.211.1740.0260229
21215.2512.96082.28919
21311.913.0915-1.19152
21413.211.70181.49823
21516.3514.03732.31266
21612.412.18430.215704
21715.8512.99642.85363
21818.1513.42324.72684
21911.1511.7259-0.575905
22015.6513.75751.89252
22117.7513.47594.27411
2227.6511.0633-3.41328
22312.3511.7680.58199
22415.611.74153.85851
22519.313.77135.52869
22615.211.44623.75379
22717.111.93885.16125
22815.613.09072.50929
22918.413.19925.20079
23019.0513.03856.01152
23118.5513.72194.82809
23219.114.07075.0293
23313.112.21620.883791
23412.8513.4868-0.636849
2359.511.1479-1.64794
2364.510.4041-5.90415
23711.8510.78361.06642
23813.613.9648-0.364759
23911.711.33220.367819
24012.412.38790.0120982
24113.3512.2641.08597
24211.411.8291-0.429144
24314.913.07611.8239
24419.915.8484.05203
24511.212.5501-1.35006
24614.613.42361.17638
24717.613.56694.0331
24814.0512.73381.31616
24916.112.57613.52387
25013.3512.30331.04674
25111.8512.679-0.829049
25211.9511.92640.0236424
25314.7512.76611.98393
25415.1512.67952.47049
25513.213.2565-0.056549
25616.8513.80933.04075
2577.8511.6857-3.83572
2587.711.6205-3.92046
25912.613.7295-1.12952
2607.8513.1865-5.33649
26110.9512.0035-1.05353
26212.3512.28670.063271
2639.9513.4454-3.49538
26414.913.07611.8239
26516.6512.94223.70779
26613.411.57061.82943
26713.9511.79822.15183
26815.713.38852.31148
26916.8513.01693.83314
27010.9511.4673-0.517334
27115.3512.84522.50483
27212.211.99340.206627
27315.112.86722.23276
27417.7513.55544.19455
27515.213.13952.06052
27614.612.50352.09646
27716.6513.38823.2618
2788.110.4715-2.37148

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.6026 & -0.702632 \tabularnewline
2 & 12.2 & 13.0153 & -0.815287 \tabularnewline
3 & 12.8 & 13.2289 & -0.428911 \tabularnewline
4 & 7.4 & 14.3099 & -6.90989 \tabularnewline
5 & 6.7 & 12.6419 & -5.94188 \tabularnewline
6 & 12.6 & 15.9627 & -3.36266 \tabularnewline
7 & 14.8 & 14.0724 & 0.727554 \tabularnewline
8 & 13.3 & 13.6839 & -0.383947 \tabularnewline
9 & 11.1 & 15.3888 & -4.28881 \tabularnewline
10 & 8.2 & 13.7948 & -5.59482 \tabularnewline
11 & 11.4 & 13.7996 & -2.39958 \tabularnewline
12 & 6.4 & 14.1195 & -7.71946 \tabularnewline
13 & 10.6 & 12.5458 & -1.94579 \tabularnewline
14 & 12 & 15.6069 & -3.60688 \tabularnewline
15 & 6.3 & 10.5145 & -4.21454 \tabularnewline
16 & 11.3 & 12.3971 & -1.09711 \tabularnewline
17 & 11.9 & 14.6976 & -2.79759 \tabularnewline
18 & 9.3 & 12.7219 & -3.42193 \tabularnewline
19 & 9.6 & 14.0035 & -4.4035 \tabularnewline
20 & 10 & 12.588 & -2.58804 \tabularnewline
21 & 6.4 & 12.9584 & -6.55843 \tabularnewline
22 & 13.8 & 14.7803 & -0.980339 \tabularnewline
23 & 10.8 & 14.959 & -4.15903 \tabularnewline
24 & 13.8 & 15.1317 & -1.33167 \tabularnewline
25 & 11.7 & 13.9552 & -2.25523 \tabularnewline
26 & 10.9 & 16.1971 & -5.29709 \tabularnewline
27 & 16.1 & 16.7041 & -0.60405 \tabularnewline
28 & 13.4 & 12.6298 & 0.770203 \tabularnewline
29 & 9.9 & 13.5062 & -3.60622 \tabularnewline
30 & 11.5 & 13.1465 & -1.64648 \tabularnewline
31 & 8.3 & 12.0412 & -3.74119 \tabularnewline
32 & 11.7 & 13.3979 & -1.6979 \tabularnewline
33 & 9 & 12.7264 & -3.72638 \tabularnewline
34 & 9.7 & 15.196 & -5.49599 \tabularnewline
35 & 10.8 & 12.6497 & -1.84966 \tabularnewline
36 & 10.3 & 12.5042 & -2.20417 \tabularnewline
37 & 10.4 & 12.9162 & -2.51618 \tabularnewline
38 & 12.7 & 13.5242 & -0.82416 \tabularnewline
39 & 9.3 & 14.761 & -5.46096 \tabularnewline
40 & 11.8 & 14.0067 & -2.20669 \tabularnewline
41 & 5.9 & 12.1887 & -6.28874 \tabularnewline
42 & 11.4 & 13.7297 & -2.32969 \tabularnewline
43 & 13 & 14.2063 & -1.20634 \tabularnewline
44 & 10.8 & 13.4753 & -2.67525 \tabularnewline
45 & 12.3 & 11.7211 & 0.57886 \tabularnewline
46 & 11.3 & 14.852 & -3.55197 \tabularnewline
47 & 11.8 & 12.7342 & -0.934158 \tabularnewline
48 & 7.9 & 13.4573 & -5.55729 \tabularnewline
49 & 12.7 & 11.9915 & 0.70852 \tabularnewline
50 & 12.3 & 12.0871 & 0.212918 \tabularnewline
51 & 11.6 & 13.2073 & -1.6073 \tabularnewline
52 & 6.7 & 10.9859 & -4.28593 \tabularnewline
53 & 10.9 & 12.7118 & -1.81177 \tabularnewline
54 & 12.1 & 13.5845 & -1.48452 \tabularnewline
55 & 13.3 & 13.2602 & 0.0398029 \tabularnewline
56 & 10.1 & 12.2474 & -2.14735 \tabularnewline
57 & 5.7 & 13.1082 & -7.40819 \tabularnewline
58 & 14.3 & 13.0882 & 1.21181 \tabularnewline
59 & 8 & 10.5226 & -2.52263 \tabularnewline
60 & 13.3 & 12.7848 & 0.515187 \tabularnewline
61 & 9.3 & 14.4131 & -5.11313 \tabularnewline
62 & 12.5 & 13.3836 & -0.883611 \tabularnewline
63 & 7.6 & 11.8882 & -4.28824 \tabularnewline
64 & 15.9 & 15.2159 & 0.684149 \tabularnewline
65 & 9.2 & 14.0081 & -4.80812 \tabularnewline
66 & 9.1 & 11.775 & -2.67498 \tabularnewline
67 & 11.1 & 15.4962 & -4.39618 \tabularnewline
68 & 13 & 15.916 & -2.91596 \tabularnewline
69 & 14.5 & 14.638 & -0.138034 \tabularnewline
70 & 12.2 & 12.9538 & -0.753807 \tabularnewline
71 & 12.3 & 15.3694 & -3.06943 \tabularnewline
72 & 11.4 & 12.4586 & -1.05859 \tabularnewline
73 & 8.8 & 12.1273 & -3.32726 \tabularnewline
74 & 14.6 & 14 & 0.599996 \tabularnewline
75 & 12.6 & 13.2974 & -0.697364 \tabularnewline
76 & 13 & 14.2534 & -1.25335 \tabularnewline
77 & 12.6 & 12.9443 & -0.344278 \tabularnewline
78 & 13.2 & 13.9079 & -0.7079 \tabularnewline
79 & 9.9 & 12.2025 & -2.30255 \tabularnewline
80 & 7.7 & 12.7083 & -5.00827 \tabularnewline
81 & 10.5 & 12.8083 & -2.30832 \tabularnewline
82 & 13.4 & 12.7607 & 0.639326 \tabularnewline
83 & 10.9 & 12.7827 & -1.88275 \tabularnewline
84 & 4.3 & 12.0537 & -7.75373 \tabularnewline
85 & 10.3 & 13.7217 & -3.42174 \tabularnewline
86 & 11.8 & 13.7483 & -1.94826 \tabularnewline
87 & 11.2 & 12.6819 & -1.48189 \tabularnewline
88 & 11.4 & 12.3671 & -0.967094 \tabularnewline
89 & 8.6 & 12.4676 & -3.86763 \tabularnewline
90 & 13.2 & 13.2373 & -0.0373177 \tabularnewline
91 & 12.6 & 11.7324 & 0.867581 \tabularnewline
92 & 5.6 & 12.4834 & -6.88336 \tabularnewline
93 & 9.9 & 13.4087 & -3.50869 \tabularnewline
94 & 8.8 & 12.1525 & -3.35252 \tabularnewline
95 & 7.7 & 12.2629 & -4.56291 \tabularnewline
96 & 9 & 12.4432 & -3.44318 \tabularnewline
97 & 7.3 & 13.113 & -5.81295 \tabularnewline
98 & 11.4 & 12.1454 & -0.745374 \tabularnewline
99 & 13.6 & 11.941 & 1.65904 \tabularnewline
100 & 7.9 & 13.5507 & -5.65068 \tabularnewline
101 & 10.7 & 11.789 & -1.08896 \tabularnewline
102 & 10.3 & 12.606 & -2.30597 \tabularnewline
103 & 8.3 & 12.0329 & -3.73292 \tabularnewline
104 & 9.6 & 13.6676 & -4.06758 \tabularnewline
105 & 14.2 & 12.6673 & 1.53272 \tabularnewline
106 & 8.5 & 13.0291 & -4.52909 \tabularnewline
107 & 13.5 & 12.5872 & 0.912768 \tabularnewline
108 & 4.9 & 12.1784 & -7.27841 \tabularnewline
109 & 6.4 & 10.9386 & -4.5386 \tabularnewline
110 & 9.6 & 12.6625 & -3.06252 \tabularnewline
111 & 11.6 & 12.8264 & -1.22643 \tabularnewline
112 & 11.1 & 12.0725 & -0.972472 \tabularnewline
113 & 4.35 & 10.2468 & -5.89675 \tabularnewline
114 & 12.7 & 10.9237 & 1.77633 \tabularnewline
115 & 18.1 & 13.2477 & 4.85235 \tabularnewline
116 & 17.85 & 13.3086 & 4.54136 \tabularnewline
117 & 16.6 & 14.8459 & 1.75408 \tabularnewline
118 & 12.6 & 11.112 & 1.48796 \tabularnewline
119 & 17.1 & 15.3524 & 1.74756 \tabularnewline
120 & 19.1 & 15.2266 & 3.87335 \tabularnewline
121 & 16.1 & 16.8462 & -0.746211 \tabularnewline
122 & 13.35 & 10.413 & 2.93695 \tabularnewline
123 & 18.4 & 13.5134 & 4.88663 \tabularnewline
124 & 14.7 & 9.96261 & 4.73739 \tabularnewline
125 & 10.6 & 12.356 & -1.75599 \tabularnewline
126 & 12.6 & 11.8597 & 0.740347 \tabularnewline
127 & 16.2 & 12.7826 & 3.4174 \tabularnewline
128 & 13.6 & 14.7513 & -1.15127 \tabularnewline
129 & 18.9 & 15.6633 & 3.23675 \tabularnewline
130 & 14.1 & 11.907 & 2.19302 \tabularnewline
131 & 14.5 & 11.829 & 2.671 \tabularnewline
132 & 16.15 & 15.7506 & 0.399381 \tabularnewline
133 & 14.75 & 12.6047 & 2.14529 \tabularnewline
134 & 14.8 & 12.988 & 1.81204 \tabularnewline
135 & 12.45 & 11.0757 & 1.37432 \tabularnewline
136 & 12.65 & 11.9993 & 0.650741 \tabularnewline
137 & 17.35 & 12.0944 & 5.2556 \tabularnewline
138 & 8.6 & 9.79123 & -1.19123 \tabularnewline
139 & 18.4 & 13.8823 & 4.51767 \tabularnewline
140 & 16.1 & 13.6319 & 2.46815 \tabularnewline
141 & 11.6 & 11.387 & 0.213032 \tabularnewline
142 & 17.75 & 13.0944 & 4.65561 \tabularnewline
143 & 15.25 & 14.4605 & 0.789539 \tabularnewline
144 & 17.65 & 12.6466 & 5.00335 \tabularnewline
145 & 16.35 & 13.6026 & 2.74737 \tabularnewline
146 & 17.65 & 13.5887 & 4.06134 \tabularnewline
147 & 13.6 & 12.755 & 0.845034 \tabularnewline
148 & 14.35 & 12.4991 & 1.85091 \tabularnewline
149 & 14.75 & 12.5618 & 2.18817 \tabularnewline
150 & 18.25 & 13.7594 & 4.4906 \tabularnewline
151 & 9.9 & 13.4139 & -3.51395 \tabularnewline
152 & 16 & 13.4039 & 2.59607 \tabularnewline
153 & 18.25 & 13.5154 & 4.73456 \tabularnewline
154 & 16.85 & 13.5949 & 3.25515 \tabularnewline
155 & 14.6 & 11.5116 & 3.08835 \tabularnewline
156 & 13.85 & 12.3784 & 1.47163 \tabularnewline
157 & 18.95 & 14.8526 & 4.09739 \tabularnewline
158 & 15.6 & 12.4896 & 3.11044 \tabularnewline
159 & 14.85 & 13.9619 & 0.888113 \tabularnewline
160 & 11.75 & 12.6631 & -0.913149 \tabularnewline
161 & 18.45 & 13.9077 & 4.54227 \tabularnewline
162 & 15.9 & 12.054 & 3.84595 \tabularnewline
163 & 17.1 & 14.2742 & 2.82584 \tabularnewline
164 & 16.1 & 8.92244 & 7.17756 \tabularnewline
165 & 19.9 & 15.848 & 4.05203 \tabularnewline
166 & 10.95 & 12.0035 & -1.05353 \tabularnewline
167 & 18.45 & 14.0157 & 4.43427 \tabularnewline
168 & 15.1 & 12.1031 & 2.99687 \tabularnewline
169 & 15 & 13.1279 & 1.87212 \tabularnewline
170 & 11.35 & 12.6536 & -1.30362 \tabularnewline
171 & 15.95 & 13.1044 & 2.84562 \tabularnewline
172 & 18.1 & 13.6093 & 4.49071 \tabularnewline
173 & 14.6 & 14.3466 & 0.253429 \tabularnewline
174 & 15.4 & 13.0709 & 2.32912 \tabularnewline
175 & 15.4 & 13.0709 & 2.32912 \tabularnewline
176 & 17.6 & 13.3391 & 4.26088 \tabularnewline
177 & 13.35 & 12.9478 & 0.402218 \tabularnewline
178 & 19.1 & 13.3931 & 5.70686 \tabularnewline
179 & 15.35 & 14.0761 & 1.27391 \tabularnewline
180 & 7.6 & 10.691 & -3.09099 \tabularnewline
181 & 13.4 & 13.8569 & -0.456899 \tabularnewline
182 & 13.9 & 13.3129 & 0.587082 \tabularnewline
183 & 19.1 & 13.9174 & 5.18257 \tabularnewline
184 & 15.25 & 13.0243 & 2.22567 \tabularnewline
185 & 12.9 & 13.251 & -0.350979 \tabularnewline
186 & 16.1 & 13.5037 & 2.59633 \tabularnewline
187 & 17.35 & 12.6387 & 4.71131 \tabularnewline
188 & 13.15 & 13.1909 & -0.0409376 \tabularnewline
189 & 12.15 & 12.9981 & -0.848121 \tabularnewline
190 & 12.6 & 11.6223 & 0.97765 \tabularnewline
191 & 10.35 & 11.5777 & -1.22772 \tabularnewline
192 & 15.4 & 13.0124 & 2.38759 \tabularnewline
193 & 9.6 & 11.2766 & -1.67658 \tabularnewline
194 & 18.2 & 13.1252 & 5.07482 \tabularnewline
195 & 13.6 & 11.9838 & 1.61616 \tabularnewline
196 & 14.85 & 12.44 & 2.41 \tabularnewline
197 & 14.75 & 13.6684 & 1.08161 \tabularnewline
198 & 14.1 & 12.6369 & 1.46306 \tabularnewline
199 & 14.9 & 12.4751 & 2.4249 \tabularnewline
200 & 16.25 & 13.3156 & 2.93438 \tabularnewline
201 & 19.25 & 15.9252 & 3.32482 \tabularnewline
202 & 13.6 & 11.5188 & 2.08121 \tabularnewline
203 & 13.6 & 12.7755 & 0.824543 \tabularnewline
204 & 15.65 & 12.9463 & 2.70366 \tabularnewline
205 & 12.75 & 12.186 & 0.563955 \tabularnewline
206 & 14.6 & 12.0877 & 2.51229 \tabularnewline
207 & 9.85 & 10.8674 & -1.01745 \tabularnewline
208 & 12.65 & 11.1266 & 1.52335 \tabularnewline
209 & 19.2 & 14.0178 & 5.1822 \tabularnewline
210 & 16.6 & 13.5251 & 3.07489 \tabularnewline
211 & 11.2 & 11.174 & 0.0260229 \tabularnewline
212 & 15.25 & 12.9608 & 2.28919 \tabularnewline
213 & 11.9 & 13.0915 & -1.19152 \tabularnewline
214 & 13.2 & 11.7018 & 1.49823 \tabularnewline
215 & 16.35 & 14.0373 & 2.31266 \tabularnewline
216 & 12.4 & 12.1843 & 0.215704 \tabularnewline
217 & 15.85 & 12.9964 & 2.85363 \tabularnewline
218 & 18.15 & 13.4232 & 4.72684 \tabularnewline
219 & 11.15 & 11.7259 & -0.575905 \tabularnewline
220 & 15.65 & 13.7575 & 1.89252 \tabularnewline
221 & 17.75 & 13.4759 & 4.27411 \tabularnewline
222 & 7.65 & 11.0633 & -3.41328 \tabularnewline
223 & 12.35 & 11.768 & 0.58199 \tabularnewline
224 & 15.6 & 11.7415 & 3.85851 \tabularnewline
225 & 19.3 & 13.7713 & 5.52869 \tabularnewline
226 & 15.2 & 11.4462 & 3.75379 \tabularnewline
227 & 17.1 & 11.9388 & 5.16125 \tabularnewline
228 & 15.6 & 13.0907 & 2.50929 \tabularnewline
229 & 18.4 & 13.1992 & 5.20079 \tabularnewline
230 & 19.05 & 13.0385 & 6.01152 \tabularnewline
231 & 18.55 & 13.7219 & 4.82809 \tabularnewline
232 & 19.1 & 14.0707 & 5.0293 \tabularnewline
233 & 13.1 & 12.2162 & 0.883791 \tabularnewline
234 & 12.85 & 13.4868 & -0.636849 \tabularnewline
235 & 9.5 & 11.1479 & -1.64794 \tabularnewline
236 & 4.5 & 10.4041 & -5.90415 \tabularnewline
237 & 11.85 & 10.7836 & 1.06642 \tabularnewline
238 & 13.6 & 13.9648 & -0.364759 \tabularnewline
239 & 11.7 & 11.3322 & 0.367819 \tabularnewline
240 & 12.4 & 12.3879 & 0.0120982 \tabularnewline
241 & 13.35 & 12.264 & 1.08597 \tabularnewline
242 & 11.4 & 11.8291 & -0.429144 \tabularnewline
243 & 14.9 & 13.0761 & 1.8239 \tabularnewline
244 & 19.9 & 15.848 & 4.05203 \tabularnewline
245 & 11.2 & 12.5501 & -1.35006 \tabularnewline
246 & 14.6 & 13.4236 & 1.17638 \tabularnewline
247 & 17.6 & 13.5669 & 4.0331 \tabularnewline
248 & 14.05 & 12.7338 & 1.31616 \tabularnewline
249 & 16.1 & 12.5761 & 3.52387 \tabularnewline
250 & 13.35 & 12.3033 & 1.04674 \tabularnewline
251 & 11.85 & 12.679 & -0.829049 \tabularnewline
252 & 11.95 & 11.9264 & 0.0236424 \tabularnewline
253 & 14.75 & 12.7661 & 1.98393 \tabularnewline
254 & 15.15 & 12.6795 & 2.47049 \tabularnewline
255 & 13.2 & 13.2565 & -0.056549 \tabularnewline
256 & 16.85 & 13.8093 & 3.04075 \tabularnewline
257 & 7.85 & 11.6857 & -3.83572 \tabularnewline
258 & 7.7 & 11.6205 & -3.92046 \tabularnewline
259 & 12.6 & 13.7295 & -1.12952 \tabularnewline
260 & 7.85 & 13.1865 & -5.33649 \tabularnewline
261 & 10.95 & 12.0035 & -1.05353 \tabularnewline
262 & 12.35 & 12.2867 & 0.063271 \tabularnewline
263 & 9.95 & 13.4454 & -3.49538 \tabularnewline
264 & 14.9 & 13.0761 & 1.8239 \tabularnewline
265 & 16.65 & 12.9422 & 3.70779 \tabularnewline
266 & 13.4 & 11.5706 & 1.82943 \tabularnewline
267 & 13.95 & 11.7982 & 2.15183 \tabularnewline
268 & 15.7 & 13.3885 & 2.31148 \tabularnewline
269 & 16.85 & 13.0169 & 3.83314 \tabularnewline
270 & 10.95 & 11.4673 & -0.517334 \tabularnewline
271 & 15.35 & 12.8452 & 2.50483 \tabularnewline
272 & 12.2 & 11.9934 & 0.206627 \tabularnewline
273 & 15.1 & 12.8672 & 2.23276 \tabularnewline
274 & 17.75 & 13.5554 & 4.19455 \tabularnewline
275 & 15.2 & 13.1395 & 2.06052 \tabularnewline
276 & 14.6 & 12.5035 & 2.09646 \tabularnewline
277 & 16.65 & 13.3882 & 3.2618 \tabularnewline
278 & 8.1 & 10.4715 & -2.37148 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270999&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]13.6026[/C][C]-0.702632[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]13.0153[/C][C]-0.815287[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.2289[/C][C]-0.428911[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]14.3099[/C][C]-6.90989[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]12.6419[/C][C]-5.94188[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]15.9627[/C][C]-3.36266[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]14.0724[/C][C]0.727554[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.6839[/C][C]-0.383947[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]15.3888[/C][C]-4.28881[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]13.7948[/C][C]-5.59482[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]13.7996[/C][C]-2.39958[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.1195[/C][C]-7.71946[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]12.5458[/C][C]-1.94579[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]15.6069[/C][C]-3.60688[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]10.5145[/C][C]-4.21454[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.3971[/C][C]-1.09711[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]14.6976[/C][C]-2.79759[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.7219[/C][C]-3.42193[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]14.0035[/C][C]-4.4035[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.588[/C][C]-2.58804[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]12.9584[/C][C]-6.55843[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]14.7803[/C][C]-0.980339[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]14.959[/C][C]-4.15903[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]15.1317[/C][C]-1.33167[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]13.9552[/C][C]-2.25523[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]16.1971[/C][C]-5.29709[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]16.7041[/C][C]-0.60405[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]12.6298[/C][C]0.770203[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]13.5062[/C][C]-3.60622[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]13.1465[/C][C]-1.64648[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.0412[/C][C]-3.74119[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.3979[/C][C]-1.6979[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.7264[/C][C]-3.72638[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]15.196[/C][C]-5.49599[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.6497[/C][C]-1.84966[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.5042[/C][C]-2.20417[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]12.9162[/C][C]-2.51618[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]13.5242[/C][C]-0.82416[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]14.761[/C][C]-5.46096[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.0067[/C][C]-2.20669[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]12.1887[/C][C]-6.28874[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.7297[/C][C]-2.32969[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]14.2063[/C][C]-1.20634[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]13.4753[/C][C]-2.67525[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]11.7211[/C][C]0.57886[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]14.852[/C][C]-3.55197[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.7342[/C][C]-0.934158[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]13.4573[/C][C]-5.55729[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]11.9915[/C][C]0.70852[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]12.0871[/C][C]0.212918[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]13.2073[/C][C]-1.6073[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.9859[/C][C]-4.28593[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]12.7118[/C][C]-1.81177[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]13.5845[/C][C]-1.48452[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.2602[/C][C]0.0398029[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]12.2474[/C][C]-2.14735[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]13.1082[/C][C]-7.40819[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]13.0882[/C][C]1.21181[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]10.5226[/C][C]-2.52263[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.7848[/C][C]0.515187[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]14.4131[/C][C]-5.11313[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]13.3836[/C][C]-0.883611[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]11.8882[/C][C]-4.28824[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]15.2159[/C][C]0.684149[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]14.0081[/C][C]-4.80812[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]11.775[/C][C]-2.67498[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]15.4962[/C][C]-4.39618[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]15.916[/C][C]-2.91596[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]14.638[/C][C]-0.138034[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.9538[/C][C]-0.753807[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]15.3694[/C][C]-3.06943[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.4586[/C][C]-1.05859[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]12.1273[/C][C]-3.32726[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]14[/C][C]0.599996[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]13.2974[/C][C]-0.697364[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]14.2534[/C][C]-1.25335[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]12.9443[/C][C]-0.344278[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]13.9079[/C][C]-0.7079[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]12.2025[/C][C]-2.30255[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]12.7083[/C][C]-5.00827[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]12.8083[/C][C]-2.30832[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]12.7607[/C][C]0.639326[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]12.7827[/C][C]-1.88275[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]12.0537[/C][C]-7.75373[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]13.7217[/C][C]-3.42174[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]13.7483[/C][C]-1.94826[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]12.6819[/C][C]-1.48189[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]12.3671[/C][C]-0.967094[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]12.4676[/C][C]-3.86763[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]13.2373[/C][C]-0.0373177[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]11.7324[/C][C]0.867581[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]12.4834[/C][C]-6.88336[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]13.4087[/C][C]-3.50869[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]12.1525[/C][C]-3.35252[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]12.2629[/C][C]-4.56291[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]12.4432[/C][C]-3.44318[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]13.113[/C][C]-5.81295[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]12.1454[/C][C]-0.745374[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]11.941[/C][C]1.65904[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]13.5507[/C][C]-5.65068[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]11.789[/C][C]-1.08896[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]12.606[/C][C]-2.30597[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]12.0329[/C][C]-3.73292[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]13.6676[/C][C]-4.06758[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]12.6673[/C][C]1.53272[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]13.0291[/C][C]-4.52909[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]12.5872[/C][C]0.912768[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]12.1784[/C][C]-7.27841[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]10.9386[/C][C]-4.5386[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]12.6625[/C][C]-3.06252[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]12.8264[/C][C]-1.22643[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]12.0725[/C][C]-0.972472[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]10.2468[/C][C]-5.89675[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]10.9237[/C][C]1.77633[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]13.2477[/C][C]4.85235[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]13.3086[/C][C]4.54136[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]14.8459[/C][C]1.75408[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]11.112[/C][C]1.48796[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]15.3524[/C][C]1.74756[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]15.2266[/C][C]3.87335[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]16.8462[/C][C]-0.746211[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]10.413[/C][C]2.93695[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]13.5134[/C][C]4.88663[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]9.96261[/C][C]4.73739[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]12.356[/C][C]-1.75599[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]11.8597[/C][C]0.740347[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]12.7826[/C][C]3.4174[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]14.7513[/C][C]-1.15127[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]15.6633[/C][C]3.23675[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]11.907[/C][C]2.19302[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]11.829[/C][C]2.671[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]15.7506[/C][C]0.399381[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]12.6047[/C][C]2.14529[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]12.988[/C][C]1.81204[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]11.0757[/C][C]1.37432[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]11.9993[/C][C]0.650741[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]12.0944[/C][C]5.2556[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]9.79123[/C][C]-1.19123[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]13.8823[/C][C]4.51767[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]13.6319[/C][C]2.46815[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]11.387[/C][C]0.213032[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]13.0944[/C][C]4.65561[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]14.4605[/C][C]0.789539[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]12.6466[/C][C]5.00335[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]13.6026[/C][C]2.74737[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]13.5887[/C][C]4.06134[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]12.755[/C][C]0.845034[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]12.4991[/C][C]1.85091[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]12.5618[/C][C]2.18817[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]13.7594[/C][C]4.4906[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]13.4139[/C][C]-3.51395[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.4039[/C][C]2.59607[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]13.5154[/C][C]4.73456[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]13.5949[/C][C]3.25515[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]11.5116[/C][C]3.08835[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]12.3784[/C][C]1.47163[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]14.8526[/C][C]4.09739[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]12.4896[/C][C]3.11044[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]13.9619[/C][C]0.888113[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]12.6631[/C][C]-0.913149[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]13.9077[/C][C]4.54227[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]12.054[/C][C]3.84595[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]14.2742[/C][C]2.82584[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]8.92244[/C][C]7.17756[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]15.848[/C][C]4.05203[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]12.0035[/C][C]-1.05353[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]14.0157[/C][C]4.43427[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]12.1031[/C][C]2.99687[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]13.1279[/C][C]1.87212[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]12.6536[/C][C]-1.30362[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]13.1044[/C][C]2.84562[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]13.6093[/C][C]4.49071[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]14.3466[/C][C]0.253429[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]13.0709[/C][C]2.32912[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.0709[/C][C]2.32912[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]13.3391[/C][C]4.26088[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]12.9478[/C][C]0.402218[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]13.3931[/C][C]5.70686[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]14.0761[/C][C]1.27391[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]10.691[/C][C]-3.09099[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]13.8569[/C][C]-0.456899[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]13.3129[/C][C]0.587082[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]13.9174[/C][C]5.18257[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]13.0243[/C][C]2.22567[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]13.251[/C][C]-0.350979[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]13.5037[/C][C]2.59633[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]12.6387[/C][C]4.71131[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]13.1909[/C][C]-0.0409376[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]12.9981[/C][C]-0.848121[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]11.6223[/C][C]0.97765[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]11.5777[/C][C]-1.22772[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]13.0124[/C][C]2.38759[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]11.2766[/C][C]-1.67658[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]13.1252[/C][C]5.07482[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]11.9838[/C][C]1.61616[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]12.44[/C][C]2.41[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]13.6684[/C][C]1.08161[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]12.6369[/C][C]1.46306[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]12.4751[/C][C]2.4249[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]13.3156[/C][C]2.93438[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]15.9252[/C][C]3.32482[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]11.5188[/C][C]2.08121[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]12.7755[/C][C]0.824543[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]12.9463[/C][C]2.70366[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]12.186[/C][C]0.563955[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]12.0877[/C][C]2.51229[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]10.8674[/C][C]-1.01745[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]11.1266[/C][C]1.52335[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]14.0178[/C][C]5.1822[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]13.5251[/C][C]3.07489[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]11.174[/C][C]0.0260229[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]12.9608[/C][C]2.28919[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]13.0915[/C][C]-1.19152[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]11.7018[/C][C]1.49823[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]14.0373[/C][C]2.31266[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]12.1843[/C][C]0.215704[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]12.9964[/C][C]2.85363[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]13.4232[/C][C]4.72684[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]11.7259[/C][C]-0.575905[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]13.7575[/C][C]1.89252[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]13.4759[/C][C]4.27411[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]11.0633[/C][C]-3.41328[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]11.768[/C][C]0.58199[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]11.7415[/C][C]3.85851[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]13.7713[/C][C]5.52869[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]11.4462[/C][C]3.75379[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]11.9388[/C][C]5.16125[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]13.0907[/C][C]2.50929[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]13.1992[/C][C]5.20079[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]13.0385[/C][C]6.01152[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]13.7219[/C][C]4.82809[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]14.0707[/C][C]5.0293[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]12.2162[/C][C]0.883791[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]13.4868[/C][C]-0.636849[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]11.1479[/C][C]-1.64794[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]10.4041[/C][C]-5.90415[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]10.7836[/C][C]1.06642[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]13.9648[/C][C]-0.364759[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]11.3322[/C][C]0.367819[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.3879[/C][C]0.0120982[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]12.264[/C][C]1.08597[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]11.8291[/C][C]-0.429144[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]13.0761[/C][C]1.8239[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]15.848[/C][C]4.05203[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]12.5501[/C][C]-1.35006[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]13.4236[/C][C]1.17638[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]13.5669[/C][C]4.0331[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]12.7338[/C][C]1.31616[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]12.5761[/C][C]3.52387[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]12.3033[/C][C]1.04674[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]12.679[/C][C]-0.829049[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]11.9264[/C][C]0.0236424[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]12.7661[/C][C]1.98393[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]12.6795[/C][C]2.47049[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]13.2565[/C][C]-0.056549[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]13.8093[/C][C]3.04075[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]11.6857[/C][C]-3.83572[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]11.6205[/C][C]-3.92046[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]13.7295[/C][C]-1.12952[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]13.1865[/C][C]-5.33649[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]12.0035[/C][C]-1.05353[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]12.2867[/C][C]0.063271[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]13.4454[/C][C]-3.49538[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]13.0761[/C][C]1.8239[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]12.9422[/C][C]3.70779[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]11.5706[/C][C]1.82943[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]11.7982[/C][C]2.15183[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]13.3885[/C][C]2.31148[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]13.0169[/C][C]3.83314[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]11.4673[/C][C]-0.517334[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]12.8452[/C][C]2.50483[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]11.9934[/C][C]0.206627[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]12.8672[/C][C]2.23276[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]13.5554[/C][C]4.19455[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]13.1395[/C][C]2.06052[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]12.5035[/C][C]2.09646[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]13.3882[/C][C]3.2618[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]10.4715[/C][C]-2.37148[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270999&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270999&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.6026-0.702632
212.213.0153-0.815287
312.813.2289-0.428911
47.414.3099-6.90989
56.712.6419-5.94188
612.615.9627-3.36266
714.814.07240.727554
813.313.6839-0.383947
911.115.3888-4.28881
108.213.7948-5.59482
1111.413.7996-2.39958
126.414.1195-7.71946
1310.612.5458-1.94579
141215.6069-3.60688
156.310.5145-4.21454
1611.312.3971-1.09711
1711.914.6976-2.79759
189.312.7219-3.42193
199.614.0035-4.4035
201012.588-2.58804
216.412.9584-6.55843
2213.814.7803-0.980339
2310.814.959-4.15903
2413.815.1317-1.33167
2511.713.9552-2.25523
2610.916.1971-5.29709
2716.116.7041-0.60405
2813.412.62980.770203
299.913.5062-3.60622
3011.513.1465-1.64648
318.312.0412-3.74119
3211.713.3979-1.6979
33912.7264-3.72638
349.715.196-5.49599
3510.812.6497-1.84966
3610.312.5042-2.20417
3710.412.9162-2.51618
3812.713.5242-0.82416
399.314.761-5.46096
4011.814.0067-2.20669
415.912.1887-6.28874
4211.413.7297-2.32969
431314.2063-1.20634
4410.813.4753-2.67525
4512.311.72110.57886
4611.314.852-3.55197
4711.812.7342-0.934158
487.913.4573-5.55729
4912.711.99150.70852
5012.312.08710.212918
5111.613.2073-1.6073
526.710.9859-4.28593
5310.912.7118-1.81177
5412.113.5845-1.48452
5513.313.26020.0398029
5610.112.2474-2.14735
575.713.1082-7.40819
5814.313.08821.21181
59810.5226-2.52263
6013.312.78480.515187
619.314.4131-5.11313
6212.513.3836-0.883611
637.611.8882-4.28824
6415.915.21590.684149
659.214.0081-4.80812
669.111.775-2.67498
6711.115.4962-4.39618
681315.916-2.91596
6914.514.638-0.138034
7012.212.9538-0.753807
7112.315.3694-3.06943
7211.412.4586-1.05859
738.812.1273-3.32726
7414.6140.599996
7512.613.2974-0.697364
761314.2534-1.25335
7712.612.9443-0.344278
7813.213.9079-0.7079
799.912.2025-2.30255
807.712.7083-5.00827
8110.512.8083-2.30832
8213.412.76070.639326
8310.912.7827-1.88275
844.312.0537-7.75373
8510.313.7217-3.42174
8611.813.7483-1.94826
8711.212.6819-1.48189
8811.412.3671-0.967094
898.612.4676-3.86763
9013.213.2373-0.0373177
9112.611.73240.867581
925.612.4834-6.88336
939.913.4087-3.50869
948.812.1525-3.35252
957.712.2629-4.56291
96912.4432-3.44318
977.313.113-5.81295
9811.412.1454-0.745374
9913.611.9411.65904
1007.913.5507-5.65068
10110.711.789-1.08896
10210.312.606-2.30597
1038.312.0329-3.73292
1049.613.6676-4.06758
10514.212.66731.53272
1068.513.0291-4.52909
10713.512.58720.912768
1084.912.1784-7.27841
1096.410.9386-4.5386
1109.612.6625-3.06252
11111.612.8264-1.22643
11211.112.0725-0.972472
1134.3510.2468-5.89675
11412.710.92371.77633
11518.113.24774.85235
11617.8513.30864.54136
11716.614.84591.75408
11812.611.1121.48796
11917.115.35241.74756
12019.115.22663.87335
12116.116.8462-0.746211
12213.3510.4132.93695
12318.413.51344.88663
12414.79.962614.73739
12510.612.356-1.75599
12612.611.85970.740347
12716.212.78263.4174
12813.614.7513-1.15127
12918.915.66333.23675
13014.111.9072.19302
13114.511.8292.671
13216.1515.75060.399381
13314.7512.60472.14529
13414.812.9881.81204
13512.4511.07571.37432
13612.6511.99930.650741
13717.3512.09445.2556
1388.69.79123-1.19123
13918.413.88234.51767
14016.113.63192.46815
14111.611.3870.213032
14217.7513.09444.65561
14315.2514.46050.789539
14417.6512.64665.00335
14516.3513.60262.74737
14617.6513.58874.06134
14713.612.7550.845034
14814.3512.49911.85091
14914.7512.56182.18817
15018.2513.75944.4906
1519.913.4139-3.51395
1521613.40392.59607
15318.2513.51544.73456
15416.8513.59493.25515
15514.611.51163.08835
15613.8512.37841.47163
15718.9514.85264.09739
15815.612.48963.11044
15914.8513.96190.888113
16011.7512.6631-0.913149
16118.4513.90774.54227
16215.912.0543.84595
16317.114.27422.82584
16416.18.922447.17756
16519.915.8484.05203
16610.9512.0035-1.05353
16718.4514.01574.43427
16815.112.10312.99687
1691513.12791.87212
17011.3512.6536-1.30362
17115.9513.10442.84562
17218.113.60934.49071
17314.614.34660.253429
17415.413.07092.32912
17515.413.07092.32912
17617.613.33914.26088
17713.3512.94780.402218
17819.113.39315.70686
17915.3514.07611.27391
1807.610.691-3.09099
18113.413.8569-0.456899
18213.913.31290.587082
18319.113.91745.18257
18415.2513.02432.22567
18512.913.251-0.350979
18616.113.50372.59633
18717.3512.63874.71131
18813.1513.1909-0.0409376
18912.1512.9981-0.848121
19012.611.62230.97765
19110.3511.5777-1.22772
19215.413.01242.38759
1939.611.2766-1.67658
19418.213.12525.07482
19513.611.98381.61616
19614.8512.442.41
19714.7513.66841.08161
19814.112.63691.46306
19914.912.47512.4249
20016.2513.31562.93438
20119.2515.92523.32482
20213.611.51882.08121
20313.612.77550.824543
20415.6512.94632.70366
20512.7512.1860.563955
20614.612.08772.51229
2079.8510.8674-1.01745
20812.6511.12661.52335
20919.214.01785.1822
21016.613.52513.07489
21111.211.1740.0260229
21215.2512.96082.28919
21311.913.0915-1.19152
21413.211.70181.49823
21516.3514.03732.31266
21612.412.18430.215704
21715.8512.99642.85363
21818.1513.42324.72684
21911.1511.7259-0.575905
22015.6513.75751.89252
22117.7513.47594.27411
2227.6511.0633-3.41328
22312.3511.7680.58199
22415.611.74153.85851
22519.313.77135.52869
22615.211.44623.75379
22717.111.93885.16125
22815.613.09072.50929
22918.413.19925.20079
23019.0513.03856.01152
23118.5513.72194.82809
23219.114.07075.0293
23313.112.21620.883791
23412.8513.4868-0.636849
2359.511.1479-1.64794
2364.510.4041-5.90415
23711.8510.78361.06642
23813.613.9648-0.364759
23911.711.33220.367819
24012.412.38790.0120982
24113.3512.2641.08597
24211.411.8291-0.429144
24314.913.07611.8239
24419.915.8484.05203
24511.212.5501-1.35006
24614.613.42361.17638
24717.613.56694.0331
24814.0512.73381.31616
24916.112.57613.52387
25013.3512.30331.04674
25111.8512.679-0.829049
25211.9511.92640.0236424
25314.7512.76611.98393
25415.1512.67952.47049
25513.213.2565-0.056549
25616.8513.80933.04075
2577.8511.6857-3.83572
2587.711.6205-3.92046
25912.613.7295-1.12952
2607.8513.1865-5.33649
26110.9512.0035-1.05353
26212.3512.28670.063271
2639.9513.4454-3.49538
26414.913.07611.8239
26516.6512.94223.70779
26613.411.57061.82943
26713.9511.79822.15183
26815.713.38852.31148
26916.8513.01693.83314
27010.9511.4673-0.517334
27115.3512.84522.50483
27212.211.99340.206627
27315.112.86722.23276
27417.7513.55544.19455
27515.213.13952.06052
27614.612.50352.09646
27716.6513.38823.2618
2788.110.4715-2.37148






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.8089170.3821660.191083
80.7554690.4890630.244531
90.6673530.6652950.332647
100.6427750.714450.357225
110.5342960.9314090.465704
120.659810.680380.34019
130.5657020.8685960.434298
140.4756110.9512220.524389
150.4463240.8926490.553676
160.3602170.7204340.639783
170.2877220.5754450.712278
180.2253560.4507120.774644
190.2020350.404070.797965
200.1531310.3062610.846869
210.1716930.3433860.828307
220.143450.2868990.85655
230.1120130.2240250.887987
240.09839410.1967880.901606
250.0741780.1483560.925822
260.06117880.1223580.938821
270.04383180.08766360.956168
280.04253440.08506880.957466
290.0313780.0627560.968622
300.02698730.05397460.973013
310.02115150.0423030.978848
320.01753870.03507750.982461
330.01291570.02583150.987084
340.01556320.03112630.984437
350.01121480.02242960.988785
360.007806910.01561380.992193
370.005753340.01150670.994247
380.003965430.007930860.996035
390.004427290.008854590.995573
400.003312670.006625350.996687
410.005677090.01135420.994323
420.00424910.008498210.995751
430.00386420.00772840.996136
440.002926270.005852540.997074
450.002144050.004288090.997856
460.001660890.003321770.998339
470.00136340.00272680.998637
480.004056830.008113660.995943
490.005216360.01043270.994784
500.004065530.008131050.995934
510.002861680.005723370.997138
520.003973890.007947780.996026
530.003187210.006374420.996813
540.002319590.004639180.99768
550.002472330.004944670.997528
560.001846360.003692730.998154
570.007320290.01464060.99268
580.01068360.02136720.989316
590.008325860.01665170.991674
600.007967850.01593570.992032
610.009588880.01917780.990411
620.009095270.01819050.990905
630.00944990.01889980.99055
640.01335680.02671360.986643
650.01538490.03076970.984615
660.01256440.02512870.987436
670.01425440.02850870.985746
680.01427740.02855480.985723
690.01611710.03223410.983883
700.01321240.02642490.986788
710.01326430.02652850.986736
720.01180820.02361630.988192
730.01059990.02119980.9894
740.01007890.02015790.989921
750.009479430.01895890.990521
760.008943560.01788710.991056
770.007512530.01502510.992487
780.007354220.01470840.992646
790.005880280.01176060.99412
800.008585520.0171710.991414
810.007028880.01405780.992971
820.006854890.01370980.993145
830.005426250.01085250.994574
840.02364860.04729720.976351
850.0236070.0472140.976393
860.02012140.04024290.979879
870.01641040.03282070.98359
880.01333140.02666290.986669
890.0139090.02781790.986091
900.01309240.02618490.986908
910.01317470.02634930.986825
920.03485070.06970150.965149
930.03696530.07393060.963035
940.03608070.07216150.963919
950.04393510.08787030.956065
960.04577330.09154670.954227
970.08114920.1622980.918851
980.07537550.1507510.924624
990.091170.182340.90883
1000.1479240.2958470.852076
1010.1322810.2645620.867719
1020.1268620.2537250.873138
1030.1369950.2739910.863005
1040.1707650.341530.829235
1050.188620.377240.81138
1060.2372940.4745870.762706
1070.2444720.4889440.755528
1080.4743380.9486750.525662
1090.525010.9499790.47499
1100.548470.903060.45153
1110.5549980.8900040.445002
1120.5523470.8953060.447653
1130.6648810.6702380.335119
1140.697280.605440.30272
1150.8439690.3120630.156031
1160.9184290.1631410.0815706
1170.9223970.1552070.0776033
1180.9259240.1481520.0740759
1190.9378080.1243840.0621918
1200.9578050.08438920.0421946
1210.954690.09062080.0453104
1220.9667770.06644550.0332227
1230.9840880.03182330.0159117
1240.9938680.01226470.00613236
1250.9935210.01295870.00647933
1260.9927980.01440440.0072022
1270.9947530.01049450.00524724
1280.9939420.01211530.00605764
1290.9951960.009608840.00480442
1300.9952280.009544660.00477233
1310.9957160.008568110.00428406
1320.9956420.008715270.00435763
1330.9954680.009063940.00453197
1340.9949290.01014190.00507097
1350.9940990.01180150.00590077
1360.9926480.01470380.00735192
1370.9966460.006707930.00335396
1380.9957890.008422940.00421147
1390.9972470.005505340.00275267
1400.9969970.006005840.00300292
1410.9963630.007274970.00363748
1420.997830.004339890.00216994
1430.9976120.004776470.00238823
1440.9986620.002675890.00133795
1450.998630.002739610.00136981
1460.9988960.002207810.00110391
1470.9986120.002775640.00138782
1480.9983260.003348380.00167419
1490.9981020.003795550.00189777
1500.9985950.002810040.00140502
1510.9995150.0009707440.000485372
1520.9994450.00110940.000554702
1530.9996080.0007838320.000391916
1540.9996110.0007780620.000389031
1550.999680.0006399660.000319983
1560.9996210.0007578210.000378911
1570.9996570.0006858290.000342914
1580.999640.0007204640.000360232
1590.9995770.0008465710.000423285
1600.9994840.001032060.000516031
1610.9996610.0006770320.000338516
1620.999750.0005007530.000250377
1630.9997190.0005611290.000280564
1640.9999967.37627e-063.68814e-06
1650.9999975.98512e-062.99256e-06
1660.9999968.9476e-064.4738e-06
1670.9999976.61373e-063.30686e-06
1680.9999976.62542e-063.31271e-06
1690.9999968.81918e-064.40959e-06
1700.9999951.04648e-055.23238e-06
1710.9999941.18368e-055.91841e-06
1720.9999968.76671e-064.38336e-06
1730.9999967.92764e-063.96382e-06
1740.9999959.97874e-064.98937e-06
1750.9999941.26545e-056.32723e-06
1760.9999951.02862e-055.14311e-06
1770.9999921.51929e-057.59647e-06
1780.9999968.65825e-064.32913e-06
1790.9999959.32028e-064.66014e-06
1800.9999941.10882e-055.54411e-06
1810.9999931.40806e-057.0403e-06
1820.9999911.7234e-058.617e-06
1830.9999941.29539e-056.47695e-06
1840.9999911.76497e-058.82484e-06
1850.9999941.1433e-055.71648e-06
1860.9999921.53027e-057.65135e-06
1870.9999941.13916e-055.69581e-06
1880.9999931.30021e-056.50105e-06
1890.9999951.08492e-055.42458e-06
1900.9999921.60283e-058.01413e-06
1910.9999892.25413e-051.12707e-05
1920.9999843.12652e-051.56326e-05
1930.9999823.61933e-051.80966e-05
1940.9999872.61303e-051.30651e-05
1950.9999813.77459e-051.8873e-05
1960.9999774.53225e-052.26612e-05
1970.9999696.12807e-053.06403e-05
1980.9999559.05395e-054.52697e-05
1990.9999440.0001117455.58726e-05
2000.9999270.0001468937.34466e-05
2010.9999290.0001420077.10034e-05
2020.9999150.0001692998.46496e-05
2030.9998870.0002262080.000113104
2040.9998460.000308710.000154355
2050.9997790.0004416920.000220846
2060.9997760.0004489420.000224471
2070.9997070.0005862860.000293143
2080.9996630.0006742720.000337136
2090.9996790.0006418270.000320913
2100.9996080.0007840280.000392014
2110.999470.001060810.000530407
2120.9992830.001434350.000717175
2130.9990870.001826290.000913143
2140.9987690.002461120.00123056
2150.9983540.003291760.00164588
2160.9976610.004677150.00233858
2170.9971730.005654420.00282721
2180.9966890.006621970.00331099
2190.9953650.009269510.00463475
2200.9937380.01252420.00626212
2210.9931480.01370380.00685189
2220.992870.01425930.00712965
2230.9902520.01949510.00974756
2240.9894520.02109570.0105479
2250.9896970.02060550.0103028
2260.9935810.01283830.00641913
2270.9955290.008942140.00447107
2280.9944240.01115260.0055763
2290.9966620.006675490.00333775
2300.9982380.00352450.00176225
2310.9982580.003483970.00174198
2320.9989440.002112180.00105609
2330.9983790.003242640.00162132
2340.9984640.003072680.00153634
2350.9977940.00441180.0022059
2360.9986150.002770710.00138536
2370.9981880.003624110.00181205
2380.9978060.004387980.00219399
2390.9972910.005417880.00270894
2400.9959010.008198310.00409916
2410.9941660.01166850.00583423
2420.9912460.01750850.00875427
2430.9873890.0252220.012611
2440.9827010.03459750.0172987
2450.9791840.04163210.0208161
2460.9711020.05779610.028898
2470.9652370.06952650.0347632
2480.9542150.09157080.0457854
2490.9610210.07795820.0389791
2500.9468790.1062420.0531208
2510.9323170.1353650.0676827
2520.9281550.143690.0718452
2530.9050590.1898810.0949406
2540.8958110.2083780.104189
2550.8900730.2198550.109927
2560.875020.2499590.12498
2570.8961540.2076920.103846
2580.9210430.1579140.0789572
2590.8938950.212210.106105
2600.9966930.006614990.00330749
2610.994070.01185930.00592963
2620.9918890.01622240.0081112
2630.9999320.0001368776.84387e-05
2640.9998460.0003079910.000153996
2650.9997260.0005474210.00027371
2660.9997910.000418220.00020911
2670.9999040.0001926219.63106e-05
2680.9998150.0003702550.000185128
2690.9998190.0003628320.000181416
2700.9986790.002642660.00132133
2710.9946060.01078820.00539412

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.808917 & 0.382166 & 0.191083 \tabularnewline
8 & 0.755469 & 0.489063 & 0.244531 \tabularnewline
9 & 0.667353 & 0.665295 & 0.332647 \tabularnewline
10 & 0.642775 & 0.71445 & 0.357225 \tabularnewline
11 & 0.534296 & 0.931409 & 0.465704 \tabularnewline
12 & 0.65981 & 0.68038 & 0.34019 \tabularnewline
13 & 0.565702 & 0.868596 & 0.434298 \tabularnewline
14 & 0.475611 & 0.951222 & 0.524389 \tabularnewline
15 & 0.446324 & 0.892649 & 0.553676 \tabularnewline
16 & 0.360217 & 0.720434 & 0.639783 \tabularnewline
17 & 0.287722 & 0.575445 & 0.712278 \tabularnewline
18 & 0.225356 & 0.450712 & 0.774644 \tabularnewline
19 & 0.202035 & 0.40407 & 0.797965 \tabularnewline
20 & 0.153131 & 0.306261 & 0.846869 \tabularnewline
21 & 0.171693 & 0.343386 & 0.828307 \tabularnewline
22 & 0.14345 & 0.286899 & 0.85655 \tabularnewline
23 & 0.112013 & 0.224025 & 0.887987 \tabularnewline
24 & 0.0983941 & 0.196788 & 0.901606 \tabularnewline
25 & 0.074178 & 0.148356 & 0.925822 \tabularnewline
26 & 0.0611788 & 0.122358 & 0.938821 \tabularnewline
27 & 0.0438318 & 0.0876636 & 0.956168 \tabularnewline
28 & 0.0425344 & 0.0850688 & 0.957466 \tabularnewline
29 & 0.031378 & 0.062756 & 0.968622 \tabularnewline
30 & 0.0269873 & 0.0539746 & 0.973013 \tabularnewline
31 & 0.0211515 & 0.042303 & 0.978848 \tabularnewline
32 & 0.0175387 & 0.0350775 & 0.982461 \tabularnewline
33 & 0.0129157 & 0.0258315 & 0.987084 \tabularnewline
34 & 0.0155632 & 0.0311263 & 0.984437 \tabularnewline
35 & 0.0112148 & 0.0224296 & 0.988785 \tabularnewline
36 & 0.00780691 & 0.0156138 & 0.992193 \tabularnewline
37 & 0.00575334 & 0.0115067 & 0.994247 \tabularnewline
38 & 0.00396543 & 0.00793086 & 0.996035 \tabularnewline
39 & 0.00442729 & 0.00885459 & 0.995573 \tabularnewline
40 & 0.00331267 & 0.00662535 & 0.996687 \tabularnewline
41 & 0.00567709 & 0.0113542 & 0.994323 \tabularnewline
42 & 0.0042491 & 0.00849821 & 0.995751 \tabularnewline
43 & 0.0038642 & 0.0077284 & 0.996136 \tabularnewline
44 & 0.00292627 & 0.00585254 & 0.997074 \tabularnewline
45 & 0.00214405 & 0.00428809 & 0.997856 \tabularnewline
46 & 0.00166089 & 0.00332177 & 0.998339 \tabularnewline
47 & 0.0013634 & 0.0027268 & 0.998637 \tabularnewline
48 & 0.00405683 & 0.00811366 & 0.995943 \tabularnewline
49 & 0.00521636 & 0.0104327 & 0.994784 \tabularnewline
50 & 0.00406553 & 0.00813105 & 0.995934 \tabularnewline
51 & 0.00286168 & 0.00572337 & 0.997138 \tabularnewline
52 & 0.00397389 & 0.00794778 & 0.996026 \tabularnewline
53 & 0.00318721 & 0.00637442 & 0.996813 \tabularnewline
54 & 0.00231959 & 0.00463918 & 0.99768 \tabularnewline
55 & 0.00247233 & 0.00494467 & 0.997528 \tabularnewline
56 & 0.00184636 & 0.00369273 & 0.998154 \tabularnewline
57 & 0.00732029 & 0.0146406 & 0.99268 \tabularnewline
58 & 0.0106836 & 0.0213672 & 0.989316 \tabularnewline
59 & 0.00832586 & 0.0166517 & 0.991674 \tabularnewline
60 & 0.00796785 & 0.0159357 & 0.992032 \tabularnewline
61 & 0.00958888 & 0.0191778 & 0.990411 \tabularnewline
62 & 0.00909527 & 0.0181905 & 0.990905 \tabularnewline
63 & 0.0094499 & 0.0188998 & 0.99055 \tabularnewline
64 & 0.0133568 & 0.0267136 & 0.986643 \tabularnewline
65 & 0.0153849 & 0.0307697 & 0.984615 \tabularnewline
66 & 0.0125644 & 0.0251287 & 0.987436 \tabularnewline
67 & 0.0142544 & 0.0285087 & 0.985746 \tabularnewline
68 & 0.0142774 & 0.0285548 & 0.985723 \tabularnewline
69 & 0.0161171 & 0.0322341 & 0.983883 \tabularnewline
70 & 0.0132124 & 0.0264249 & 0.986788 \tabularnewline
71 & 0.0132643 & 0.0265285 & 0.986736 \tabularnewline
72 & 0.0118082 & 0.0236163 & 0.988192 \tabularnewline
73 & 0.0105999 & 0.0211998 & 0.9894 \tabularnewline
74 & 0.0100789 & 0.0201579 & 0.989921 \tabularnewline
75 & 0.00947943 & 0.0189589 & 0.990521 \tabularnewline
76 & 0.00894356 & 0.0178871 & 0.991056 \tabularnewline
77 & 0.00751253 & 0.0150251 & 0.992487 \tabularnewline
78 & 0.00735422 & 0.0147084 & 0.992646 \tabularnewline
79 & 0.00588028 & 0.0117606 & 0.99412 \tabularnewline
80 & 0.00858552 & 0.017171 & 0.991414 \tabularnewline
81 & 0.00702888 & 0.0140578 & 0.992971 \tabularnewline
82 & 0.00685489 & 0.0137098 & 0.993145 \tabularnewline
83 & 0.00542625 & 0.0108525 & 0.994574 \tabularnewline
84 & 0.0236486 & 0.0472972 & 0.976351 \tabularnewline
85 & 0.023607 & 0.047214 & 0.976393 \tabularnewline
86 & 0.0201214 & 0.0402429 & 0.979879 \tabularnewline
87 & 0.0164104 & 0.0328207 & 0.98359 \tabularnewline
88 & 0.0133314 & 0.0266629 & 0.986669 \tabularnewline
89 & 0.013909 & 0.0278179 & 0.986091 \tabularnewline
90 & 0.0130924 & 0.0261849 & 0.986908 \tabularnewline
91 & 0.0131747 & 0.0263493 & 0.986825 \tabularnewline
92 & 0.0348507 & 0.0697015 & 0.965149 \tabularnewline
93 & 0.0369653 & 0.0739306 & 0.963035 \tabularnewline
94 & 0.0360807 & 0.0721615 & 0.963919 \tabularnewline
95 & 0.0439351 & 0.0878703 & 0.956065 \tabularnewline
96 & 0.0457733 & 0.0915467 & 0.954227 \tabularnewline
97 & 0.0811492 & 0.162298 & 0.918851 \tabularnewline
98 & 0.0753755 & 0.150751 & 0.924624 \tabularnewline
99 & 0.09117 & 0.18234 & 0.90883 \tabularnewline
100 & 0.147924 & 0.295847 & 0.852076 \tabularnewline
101 & 0.132281 & 0.264562 & 0.867719 \tabularnewline
102 & 0.126862 & 0.253725 & 0.873138 \tabularnewline
103 & 0.136995 & 0.273991 & 0.863005 \tabularnewline
104 & 0.170765 & 0.34153 & 0.829235 \tabularnewline
105 & 0.18862 & 0.37724 & 0.81138 \tabularnewline
106 & 0.237294 & 0.474587 & 0.762706 \tabularnewline
107 & 0.244472 & 0.488944 & 0.755528 \tabularnewline
108 & 0.474338 & 0.948675 & 0.525662 \tabularnewline
109 & 0.52501 & 0.949979 & 0.47499 \tabularnewline
110 & 0.54847 & 0.90306 & 0.45153 \tabularnewline
111 & 0.554998 & 0.890004 & 0.445002 \tabularnewline
112 & 0.552347 & 0.895306 & 0.447653 \tabularnewline
113 & 0.664881 & 0.670238 & 0.335119 \tabularnewline
114 & 0.69728 & 0.60544 & 0.30272 \tabularnewline
115 & 0.843969 & 0.312063 & 0.156031 \tabularnewline
116 & 0.918429 & 0.163141 & 0.0815706 \tabularnewline
117 & 0.922397 & 0.155207 & 0.0776033 \tabularnewline
118 & 0.925924 & 0.148152 & 0.0740759 \tabularnewline
119 & 0.937808 & 0.124384 & 0.0621918 \tabularnewline
120 & 0.957805 & 0.0843892 & 0.0421946 \tabularnewline
121 & 0.95469 & 0.0906208 & 0.0453104 \tabularnewline
122 & 0.966777 & 0.0664455 & 0.0332227 \tabularnewline
123 & 0.984088 & 0.0318233 & 0.0159117 \tabularnewline
124 & 0.993868 & 0.0122647 & 0.00613236 \tabularnewline
125 & 0.993521 & 0.0129587 & 0.00647933 \tabularnewline
126 & 0.992798 & 0.0144044 & 0.0072022 \tabularnewline
127 & 0.994753 & 0.0104945 & 0.00524724 \tabularnewline
128 & 0.993942 & 0.0121153 & 0.00605764 \tabularnewline
129 & 0.995196 & 0.00960884 & 0.00480442 \tabularnewline
130 & 0.995228 & 0.00954466 & 0.00477233 \tabularnewline
131 & 0.995716 & 0.00856811 & 0.00428406 \tabularnewline
132 & 0.995642 & 0.00871527 & 0.00435763 \tabularnewline
133 & 0.995468 & 0.00906394 & 0.00453197 \tabularnewline
134 & 0.994929 & 0.0101419 & 0.00507097 \tabularnewline
135 & 0.994099 & 0.0118015 & 0.00590077 \tabularnewline
136 & 0.992648 & 0.0147038 & 0.00735192 \tabularnewline
137 & 0.996646 & 0.00670793 & 0.00335396 \tabularnewline
138 & 0.995789 & 0.00842294 & 0.00421147 \tabularnewline
139 & 0.997247 & 0.00550534 & 0.00275267 \tabularnewline
140 & 0.996997 & 0.00600584 & 0.00300292 \tabularnewline
141 & 0.996363 & 0.00727497 & 0.00363748 \tabularnewline
142 & 0.99783 & 0.00433989 & 0.00216994 \tabularnewline
143 & 0.997612 & 0.00477647 & 0.00238823 \tabularnewline
144 & 0.998662 & 0.00267589 & 0.00133795 \tabularnewline
145 & 0.99863 & 0.00273961 & 0.00136981 \tabularnewline
146 & 0.998896 & 0.00220781 & 0.00110391 \tabularnewline
147 & 0.998612 & 0.00277564 & 0.00138782 \tabularnewline
148 & 0.998326 & 0.00334838 & 0.00167419 \tabularnewline
149 & 0.998102 & 0.00379555 & 0.00189777 \tabularnewline
150 & 0.998595 & 0.00281004 & 0.00140502 \tabularnewline
151 & 0.999515 & 0.000970744 & 0.000485372 \tabularnewline
152 & 0.999445 & 0.0011094 & 0.000554702 \tabularnewline
153 & 0.999608 & 0.000783832 & 0.000391916 \tabularnewline
154 & 0.999611 & 0.000778062 & 0.000389031 \tabularnewline
155 & 0.99968 & 0.000639966 & 0.000319983 \tabularnewline
156 & 0.999621 & 0.000757821 & 0.000378911 \tabularnewline
157 & 0.999657 & 0.000685829 & 0.000342914 \tabularnewline
158 & 0.99964 & 0.000720464 & 0.000360232 \tabularnewline
159 & 0.999577 & 0.000846571 & 0.000423285 \tabularnewline
160 & 0.999484 & 0.00103206 & 0.000516031 \tabularnewline
161 & 0.999661 & 0.000677032 & 0.000338516 \tabularnewline
162 & 0.99975 & 0.000500753 & 0.000250377 \tabularnewline
163 & 0.999719 & 0.000561129 & 0.000280564 \tabularnewline
164 & 0.999996 & 7.37627e-06 & 3.68814e-06 \tabularnewline
165 & 0.999997 & 5.98512e-06 & 2.99256e-06 \tabularnewline
166 & 0.999996 & 8.9476e-06 & 4.4738e-06 \tabularnewline
167 & 0.999997 & 6.61373e-06 & 3.30686e-06 \tabularnewline
168 & 0.999997 & 6.62542e-06 & 3.31271e-06 \tabularnewline
169 & 0.999996 & 8.81918e-06 & 4.40959e-06 \tabularnewline
170 & 0.999995 & 1.04648e-05 & 5.23238e-06 \tabularnewline
171 & 0.999994 & 1.18368e-05 & 5.91841e-06 \tabularnewline
172 & 0.999996 & 8.76671e-06 & 4.38336e-06 \tabularnewline
173 & 0.999996 & 7.92764e-06 & 3.96382e-06 \tabularnewline
174 & 0.999995 & 9.97874e-06 & 4.98937e-06 \tabularnewline
175 & 0.999994 & 1.26545e-05 & 6.32723e-06 \tabularnewline
176 & 0.999995 & 1.02862e-05 & 5.14311e-06 \tabularnewline
177 & 0.999992 & 1.51929e-05 & 7.59647e-06 \tabularnewline
178 & 0.999996 & 8.65825e-06 & 4.32913e-06 \tabularnewline
179 & 0.999995 & 9.32028e-06 & 4.66014e-06 \tabularnewline
180 & 0.999994 & 1.10882e-05 & 5.54411e-06 \tabularnewline
181 & 0.999993 & 1.40806e-05 & 7.0403e-06 \tabularnewline
182 & 0.999991 & 1.7234e-05 & 8.617e-06 \tabularnewline
183 & 0.999994 & 1.29539e-05 & 6.47695e-06 \tabularnewline
184 & 0.999991 & 1.76497e-05 & 8.82484e-06 \tabularnewline
185 & 0.999994 & 1.1433e-05 & 5.71648e-06 \tabularnewline
186 & 0.999992 & 1.53027e-05 & 7.65135e-06 \tabularnewline
187 & 0.999994 & 1.13916e-05 & 5.69581e-06 \tabularnewline
188 & 0.999993 & 1.30021e-05 & 6.50105e-06 \tabularnewline
189 & 0.999995 & 1.08492e-05 & 5.42458e-06 \tabularnewline
190 & 0.999992 & 1.60283e-05 & 8.01413e-06 \tabularnewline
191 & 0.999989 & 2.25413e-05 & 1.12707e-05 \tabularnewline
192 & 0.999984 & 3.12652e-05 & 1.56326e-05 \tabularnewline
193 & 0.999982 & 3.61933e-05 & 1.80966e-05 \tabularnewline
194 & 0.999987 & 2.61303e-05 & 1.30651e-05 \tabularnewline
195 & 0.999981 & 3.77459e-05 & 1.8873e-05 \tabularnewline
196 & 0.999977 & 4.53225e-05 & 2.26612e-05 \tabularnewline
197 & 0.999969 & 6.12807e-05 & 3.06403e-05 \tabularnewline
198 & 0.999955 & 9.05395e-05 & 4.52697e-05 \tabularnewline
199 & 0.999944 & 0.000111745 & 5.58726e-05 \tabularnewline
200 & 0.999927 & 0.000146893 & 7.34466e-05 \tabularnewline
201 & 0.999929 & 0.000142007 & 7.10034e-05 \tabularnewline
202 & 0.999915 & 0.000169299 & 8.46496e-05 \tabularnewline
203 & 0.999887 & 0.000226208 & 0.000113104 \tabularnewline
204 & 0.999846 & 0.00030871 & 0.000154355 \tabularnewline
205 & 0.999779 & 0.000441692 & 0.000220846 \tabularnewline
206 & 0.999776 & 0.000448942 & 0.000224471 \tabularnewline
207 & 0.999707 & 0.000586286 & 0.000293143 \tabularnewline
208 & 0.999663 & 0.000674272 & 0.000337136 \tabularnewline
209 & 0.999679 & 0.000641827 & 0.000320913 \tabularnewline
210 & 0.999608 & 0.000784028 & 0.000392014 \tabularnewline
211 & 0.99947 & 0.00106081 & 0.000530407 \tabularnewline
212 & 0.999283 & 0.00143435 & 0.000717175 \tabularnewline
213 & 0.999087 & 0.00182629 & 0.000913143 \tabularnewline
214 & 0.998769 & 0.00246112 & 0.00123056 \tabularnewline
215 & 0.998354 & 0.00329176 & 0.00164588 \tabularnewline
216 & 0.997661 & 0.00467715 & 0.00233858 \tabularnewline
217 & 0.997173 & 0.00565442 & 0.00282721 \tabularnewline
218 & 0.996689 & 0.00662197 & 0.00331099 \tabularnewline
219 & 0.995365 & 0.00926951 & 0.00463475 \tabularnewline
220 & 0.993738 & 0.0125242 & 0.00626212 \tabularnewline
221 & 0.993148 & 0.0137038 & 0.00685189 \tabularnewline
222 & 0.99287 & 0.0142593 & 0.00712965 \tabularnewline
223 & 0.990252 & 0.0194951 & 0.00974756 \tabularnewline
224 & 0.989452 & 0.0210957 & 0.0105479 \tabularnewline
225 & 0.989697 & 0.0206055 & 0.0103028 \tabularnewline
226 & 0.993581 & 0.0128383 & 0.00641913 \tabularnewline
227 & 0.995529 & 0.00894214 & 0.00447107 \tabularnewline
228 & 0.994424 & 0.0111526 & 0.0055763 \tabularnewline
229 & 0.996662 & 0.00667549 & 0.00333775 \tabularnewline
230 & 0.998238 & 0.0035245 & 0.00176225 \tabularnewline
231 & 0.998258 & 0.00348397 & 0.00174198 \tabularnewline
232 & 0.998944 & 0.00211218 & 0.00105609 \tabularnewline
233 & 0.998379 & 0.00324264 & 0.00162132 \tabularnewline
234 & 0.998464 & 0.00307268 & 0.00153634 \tabularnewline
235 & 0.997794 & 0.0044118 & 0.0022059 \tabularnewline
236 & 0.998615 & 0.00277071 & 0.00138536 \tabularnewline
237 & 0.998188 & 0.00362411 & 0.00181205 \tabularnewline
238 & 0.997806 & 0.00438798 & 0.00219399 \tabularnewline
239 & 0.997291 & 0.00541788 & 0.00270894 \tabularnewline
240 & 0.995901 & 0.00819831 & 0.00409916 \tabularnewline
241 & 0.994166 & 0.0116685 & 0.00583423 \tabularnewline
242 & 0.991246 & 0.0175085 & 0.00875427 \tabularnewline
243 & 0.987389 & 0.025222 & 0.012611 \tabularnewline
244 & 0.982701 & 0.0345975 & 0.0172987 \tabularnewline
245 & 0.979184 & 0.0416321 & 0.0208161 \tabularnewline
246 & 0.971102 & 0.0577961 & 0.028898 \tabularnewline
247 & 0.965237 & 0.0695265 & 0.0347632 \tabularnewline
248 & 0.954215 & 0.0915708 & 0.0457854 \tabularnewline
249 & 0.961021 & 0.0779582 & 0.0389791 \tabularnewline
250 & 0.946879 & 0.106242 & 0.0531208 \tabularnewline
251 & 0.932317 & 0.135365 & 0.0676827 \tabularnewline
252 & 0.928155 & 0.14369 & 0.0718452 \tabularnewline
253 & 0.905059 & 0.189881 & 0.0949406 \tabularnewline
254 & 0.895811 & 0.208378 & 0.104189 \tabularnewline
255 & 0.890073 & 0.219855 & 0.109927 \tabularnewline
256 & 0.87502 & 0.249959 & 0.12498 \tabularnewline
257 & 0.896154 & 0.207692 & 0.103846 \tabularnewline
258 & 0.921043 & 0.157914 & 0.0789572 \tabularnewline
259 & 0.893895 & 0.21221 & 0.106105 \tabularnewline
260 & 0.996693 & 0.00661499 & 0.00330749 \tabularnewline
261 & 0.99407 & 0.0118593 & 0.00592963 \tabularnewline
262 & 0.991889 & 0.0162224 & 0.0081112 \tabularnewline
263 & 0.999932 & 0.000136877 & 6.84387e-05 \tabularnewline
264 & 0.999846 & 0.000307991 & 0.000153996 \tabularnewline
265 & 0.999726 & 0.000547421 & 0.00027371 \tabularnewline
266 & 0.999791 & 0.00041822 & 0.00020911 \tabularnewline
267 & 0.999904 & 0.000192621 & 9.63106e-05 \tabularnewline
268 & 0.999815 & 0.000370255 & 0.000185128 \tabularnewline
269 & 0.999819 & 0.000362832 & 0.000181416 \tabularnewline
270 & 0.998679 & 0.00264266 & 0.00132133 \tabularnewline
271 & 0.994606 & 0.0107882 & 0.00539412 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270999&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]7[/C][C]0.808917[/C][C]0.382166[/C][C]0.191083[/C][/ROW]
[ROW][C]8[/C][C]0.755469[/C][C]0.489063[/C][C]0.244531[/C][/ROW]
[ROW][C]9[/C][C]0.667353[/C][C]0.665295[/C][C]0.332647[/C][/ROW]
[ROW][C]10[/C][C]0.642775[/C][C]0.71445[/C][C]0.357225[/C][/ROW]
[ROW][C]11[/C][C]0.534296[/C][C]0.931409[/C][C]0.465704[/C][/ROW]
[ROW][C]12[/C][C]0.65981[/C][C]0.68038[/C][C]0.34019[/C][/ROW]
[ROW][C]13[/C][C]0.565702[/C][C]0.868596[/C][C]0.434298[/C][/ROW]
[ROW][C]14[/C][C]0.475611[/C][C]0.951222[/C][C]0.524389[/C][/ROW]
[ROW][C]15[/C][C]0.446324[/C][C]0.892649[/C][C]0.553676[/C][/ROW]
[ROW][C]16[/C][C]0.360217[/C][C]0.720434[/C][C]0.639783[/C][/ROW]
[ROW][C]17[/C][C]0.287722[/C][C]0.575445[/C][C]0.712278[/C][/ROW]
[ROW][C]18[/C][C]0.225356[/C][C]0.450712[/C][C]0.774644[/C][/ROW]
[ROW][C]19[/C][C]0.202035[/C][C]0.40407[/C][C]0.797965[/C][/ROW]
[ROW][C]20[/C][C]0.153131[/C][C]0.306261[/C][C]0.846869[/C][/ROW]
[ROW][C]21[/C][C]0.171693[/C][C]0.343386[/C][C]0.828307[/C][/ROW]
[ROW][C]22[/C][C]0.14345[/C][C]0.286899[/C][C]0.85655[/C][/ROW]
[ROW][C]23[/C][C]0.112013[/C][C]0.224025[/C][C]0.887987[/C][/ROW]
[ROW][C]24[/C][C]0.0983941[/C][C]0.196788[/C][C]0.901606[/C][/ROW]
[ROW][C]25[/C][C]0.074178[/C][C]0.148356[/C][C]0.925822[/C][/ROW]
[ROW][C]26[/C][C]0.0611788[/C][C]0.122358[/C][C]0.938821[/C][/ROW]
[ROW][C]27[/C][C]0.0438318[/C][C]0.0876636[/C][C]0.956168[/C][/ROW]
[ROW][C]28[/C][C]0.0425344[/C][C]0.0850688[/C][C]0.957466[/C][/ROW]
[ROW][C]29[/C][C]0.031378[/C][C]0.062756[/C][C]0.968622[/C][/ROW]
[ROW][C]30[/C][C]0.0269873[/C][C]0.0539746[/C][C]0.973013[/C][/ROW]
[ROW][C]31[/C][C]0.0211515[/C][C]0.042303[/C][C]0.978848[/C][/ROW]
[ROW][C]32[/C][C]0.0175387[/C][C]0.0350775[/C][C]0.982461[/C][/ROW]
[ROW][C]33[/C][C]0.0129157[/C][C]0.0258315[/C][C]0.987084[/C][/ROW]
[ROW][C]34[/C][C]0.0155632[/C][C]0.0311263[/C][C]0.984437[/C][/ROW]
[ROW][C]35[/C][C]0.0112148[/C][C]0.0224296[/C][C]0.988785[/C][/ROW]
[ROW][C]36[/C][C]0.00780691[/C][C]0.0156138[/C][C]0.992193[/C][/ROW]
[ROW][C]37[/C][C]0.00575334[/C][C]0.0115067[/C][C]0.994247[/C][/ROW]
[ROW][C]38[/C][C]0.00396543[/C][C]0.00793086[/C][C]0.996035[/C][/ROW]
[ROW][C]39[/C][C]0.00442729[/C][C]0.00885459[/C][C]0.995573[/C][/ROW]
[ROW][C]40[/C][C]0.00331267[/C][C]0.00662535[/C][C]0.996687[/C][/ROW]
[ROW][C]41[/C][C]0.00567709[/C][C]0.0113542[/C][C]0.994323[/C][/ROW]
[ROW][C]42[/C][C]0.0042491[/C][C]0.00849821[/C][C]0.995751[/C][/ROW]
[ROW][C]43[/C][C]0.0038642[/C][C]0.0077284[/C][C]0.996136[/C][/ROW]
[ROW][C]44[/C][C]0.00292627[/C][C]0.00585254[/C][C]0.997074[/C][/ROW]
[ROW][C]45[/C][C]0.00214405[/C][C]0.00428809[/C][C]0.997856[/C][/ROW]
[ROW][C]46[/C][C]0.00166089[/C][C]0.00332177[/C][C]0.998339[/C][/ROW]
[ROW][C]47[/C][C]0.0013634[/C][C]0.0027268[/C][C]0.998637[/C][/ROW]
[ROW][C]48[/C][C]0.00405683[/C][C]0.00811366[/C][C]0.995943[/C][/ROW]
[ROW][C]49[/C][C]0.00521636[/C][C]0.0104327[/C][C]0.994784[/C][/ROW]
[ROW][C]50[/C][C]0.00406553[/C][C]0.00813105[/C][C]0.995934[/C][/ROW]
[ROW][C]51[/C][C]0.00286168[/C][C]0.00572337[/C][C]0.997138[/C][/ROW]
[ROW][C]52[/C][C]0.00397389[/C][C]0.00794778[/C][C]0.996026[/C][/ROW]
[ROW][C]53[/C][C]0.00318721[/C][C]0.00637442[/C][C]0.996813[/C][/ROW]
[ROW][C]54[/C][C]0.00231959[/C][C]0.00463918[/C][C]0.99768[/C][/ROW]
[ROW][C]55[/C][C]0.00247233[/C][C]0.00494467[/C][C]0.997528[/C][/ROW]
[ROW][C]56[/C][C]0.00184636[/C][C]0.00369273[/C][C]0.998154[/C][/ROW]
[ROW][C]57[/C][C]0.00732029[/C][C]0.0146406[/C][C]0.99268[/C][/ROW]
[ROW][C]58[/C][C]0.0106836[/C][C]0.0213672[/C][C]0.989316[/C][/ROW]
[ROW][C]59[/C][C]0.00832586[/C][C]0.0166517[/C][C]0.991674[/C][/ROW]
[ROW][C]60[/C][C]0.00796785[/C][C]0.0159357[/C][C]0.992032[/C][/ROW]
[ROW][C]61[/C][C]0.00958888[/C][C]0.0191778[/C][C]0.990411[/C][/ROW]
[ROW][C]62[/C][C]0.00909527[/C][C]0.0181905[/C][C]0.990905[/C][/ROW]
[ROW][C]63[/C][C]0.0094499[/C][C]0.0188998[/C][C]0.99055[/C][/ROW]
[ROW][C]64[/C][C]0.0133568[/C][C]0.0267136[/C][C]0.986643[/C][/ROW]
[ROW][C]65[/C][C]0.0153849[/C][C]0.0307697[/C][C]0.984615[/C][/ROW]
[ROW][C]66[/C][C]0.0125644[/C][C]0.0251287[/C][C]0.987436[/C][/ROW]
[ROW][C]67[/C][C]0.0142544[/C][C]0.0285087[/C][C]0.985746[/C][/ROW]
[ROW][C]68[/C][C]0.0142774[/C][C]0.0285548[/C][C]0.985723[/C][/ROW]
[ROW][C]69[/C][C]0.0161171[/C][C]0.0322341[/C][C]0.983883[/C][/ROW]
[ROW][C]70[/C][C]0.0132124[/C][C]0.0264249[/C][C]0.986788[/C][/ROW]
[ROW][C]71[/C][C]0.0132643[/C][C]0.0265285[/C][C]0.986736[/C][/ROW]
[ROW][C]72[/C][C]0.0118082[/C][C]0.0236163[/C][C]0.988192[/C][/ROW]
[ROW][C]73[/C][C]0.0105999[/C][C]0.0211998[/C][C]0.9894[/C][/ROW]
[ROW][C]74[/C][C]0.0100789[/C][C]0.0201579[/C][C]0.989921[/C][/ROW]
[ROW][C]75[/C][C]0.00947943[/C][C]0.0189589[/C][C]0.990521[/C][/ROW]
[ROW][C]76[/C][C]0.00894356[/C][C]0.0178871[/C][C]0.991056[/C][/ROW]
[ROW][C]77[/C][C]0.00751253[/C][C]0.0150251[/C][C]0.992487[/C][/ROW]
[ROW][C]78[/C][C]0.00735422[/C][C]0.0147084[/C][C]0.992646[/C][/ROW]
[ROW][C]79[/C][C]0.00588028[/C][C]0.0117606[/C][C]0.99412[/C][/ROW]
[ROW][C]80[/C][C]0.00858552[/C][C]0.017171[/C][C]0.991414[/C][/ROW]
[ROW][C]81[/C][C]0.00702888[/C][C]0.0140578[/C][C]0.992971[/C][/ROW]
[ROW][C]82[/C][C]0.00685489[/C][C]0.0137098[/C][C]0.993145[/C][/ROW]
[ROW][C]83[/C][C]0.00542625[/C][C]0.0108525[/C][C]0.994574[/C][/ROW]
[ROW][C]84[/C][C]0.0236486[/C][C]0.0472972[/C][C]0.976351[/C][/ROW]
[ROW][C]85[/C][C]0.023607[/C][C]0.047214[/C][C]0.976393[/C][/ROW]
[ROW][C]86[/C][C]0.0201214[/C][C]0.0402429[/C][C]0.979879[/C][/ROW]
[ROW][C]87[/C][C]0.0164104[/C][C]0.0328207[/C][C]0.98359[/C][/ROW]
[ROW][C]88[/C][C]0.0133314[/C][C]0.0266629[/C][C]0.986669[/C][/ROW]
[ROW][C]89[/C][C]0.013909[/C][C]0.0278179[/C][C]0.986091[/C][/ROW]
[ROW][C]90[/C][C]0.0130924[/C][C]0.0261849[/C][C]0.986908[/C][/ROW]
[ROW][C]91[/C][C]0.0131747[/C][C]0.0263493[/C][C]0.986825[/C][/ROW]
[ROW][C]92[/C][C]0.0348507[/C][C]0.0697015[/C][C]0.965149[/C][/ROW]
[ROW][C]93[/C][C]0.0369653[/C][C]0.0739306[/C][C]0.963035[/C][/ROW]
[ROW][C]94[/C][C]0.0360807[/C][C]0.0721615[/C][C]0.963919[/C][/ROW]
[ROW][C]95[/C][C]0.0439351[/C][C]0.0878703[/C][C]0.956065[/C][/ROW]
[ROW][C]96[/C][C]0.0457733[/C][C]0.0915467[/C][C]0.954227[/C][/ROW]
[ROW][C]97[/C][C]0.0811492[/C][C]0.162298[/C][C]0.918851[/C][/ROW]
[ROW][C]98[/C][C]0.0753755[/C][C]0.150751[/C][C]0.924624[/C][/ROW]
[ROW][C]99[/C][C]0.09117[/C][C]0.18234[/C][C]0.90883[/C][/ROW]
[ROW][C]100[/C][C]0.147924[/C][C]0.295847[/C][C]0.852076[/C][/ROW]
[ROW][C]101[/C][C]0.132281[/C][C]0.264562[/C][C]0.867719[/C][/ROW]
[ROW][C]102[/C][C]0.126862[/C][C]0.253725[/C][C]0.873138[/C][/ROW]
[ROW][C]103[/C][C]0.136995[/C][C]0.273991[/C][C]0.863005[/C][/ROW]
[ROW][C]104[/C][C]0.170765[/C][C]0.34153[/C][C]0.829235[/C][/ROW]
[ROW][C]105[/C][C]0.18862[/C][C]0.37724[/C][C]0.81138[/C][/ROW]
[ROW][C]106[/C][C]0.237294[/C][C]0.474587[/C][C]0.762706[/C][/ROW]
[ROW][C]107[/C][C]0.244472[/C][C]0.488944[/C][C]0.755528[/C][/ROW]
[ROW][C]108[/C][C]0.474338[/C][C]0.948675[/C][C]0.525662[/C][/ROW]
[ROW][C]109[/C][C]0.52501[/C][C]0.949979[/C][C]0.47499[/C][/ROW]
[ROW][C]110[/C][C]0.54847[/C][C]0.90306[/C][C]0.45153[/C][/ROW]
[ROW][C]111[/C][C]0.554998[/C][C]0.890004[/C][C]0.445002[/C][/ROW]
[ROW][C]112[/C][C]0.552347[/C][C]0.895306[/C][C]0.447653[/C][/ROW]
[ROW][C]113[/C][C]0.664881[/C][C]0.670238[/C][C]0.335119[/C][/ROW]
[ROW][C]114[/C][C]0.69728[/C][C]0.60544[/C][C]0.30272[/C][/ROW]
[ROW][C]115[/C][C]0.843969[/C][C]0.312063[/C][C]0.156031[/C][/ROW]
[ROW][C]116[/C][C]0.918429[/C][C]0.163141[/C][C]0.0815706[/C][/ROW]
[ROW][C]117[/C][C]0.922397[/C][C]0.155207[/C][C]0.0776033[/C][/ROW]
[ROW][C]118[/C][C]0.925924[/C][C]0.148152[/C][C]0.0740759[/C][/ROW]
[ROW][C]119[/C][C]0.937808[/C][C]0.124384[/C][C]0.0621918[/C][/ROW]
[ROW][C]120[/C][C]0.957805[/C][C]0.0843892[/C][C]0.0421946[/C][/ROW]
[ROW][C]121[/C][C]0.95469[/C][C]0.0906208[/C][C]0.0453104[/C][/ROW]
[ROW][C]122[/C][C]0.966777[/C][C]0.0664455[/C][C]0.0332227[/C][/ROW]
[ROW][C]123[/C][C]0.984088[/C][C]0.0318233[/C][C]0.0159117[/C][/ROW]
[ROW][C]124[/C][C]0.993868[/C][C]0.0122647[/C][C]0.00613236[/C][/ROW]
[ROW][C]125[/C][C]0.993521[/C][C]0.0129587[/C][C]0.00647933[/C][/ROW]
[ROW][C]126[/C][C]0.992798[/C][C]0.0144044[/C][C]0.0072022[/C][/ROW]
[ROW][C]127[/C][C]0.994753[/C][C]0.0104945[/C][C]0.00524724[/C][/ROW]
[ROW][C]128[/C][C]0.993942[/C][C]0.0121153[/C][C]0.00605764[/C][/ROW]
[ROW][C]129[/C][C]0.995196[/C][C]0.00960884[/C][C]0.00480442[/C][/ROW]
[ROW][C]130[/C][C]0.995228[/C][C]0.00954466[/C][C]0.00477233[/C][/ROW]
[ROW][C]131[/C][C]0.995716[/C][C]0.00856811[/C][C]0.00428406[/C][/ROW]
[ROW][C]132[/C][C]0.995642[/C][C]0.00871527[/C][C]0.00435763[/C][/ROW]
[ROW][C]133[/C][C]0.995468[/C][C]0.00906394[/C][C]0.00453197[/C][/ROW]
[ROW][C]134[/C][C]0.994929[/C][C]0.0101419[/C][C]0.00507097[/C][/ROW]
[ROW][C]135[/C][C]0.994099[/C][C]0.0118015[/C][C]0.00590077[/C][/ROW]
[ROW][C]136[/C][C]0.992648[/C][C]0.0147038[/C][C]0.00735192[/C][/ROW]
[ROW][C]137[/C][C]0.996646[/C][C]0.00670793[/C][C]0.00335396[/C][/ROW]
[ROW][C]138[/C][C]0.995789[/C][C]0.00842294[/C][C]0.00421147[/C][/ROW]
[ROW][C]139[/C][C]0.997247[/C][C]0.00550534[/C][C]0.00275267[/C][/ROW]
[ROW][C]140[/C][C]0.996997[/C][C]0.00600584[/C][C]0.00300292[/C][/ROW]
[ROW][C]141[/C][C]0.996363[/C][C]0.00727497[/C][C]0.00363748[/C][/ROW]
[ROW][C]142[/C][C]0.99783[/C][C]0.00433989[/C][C]0.00216994[/C][/ROW]
[ROW][C]143[/C][C]0.997612[/C][C]0.00477647[/C][C]0.00238823[/C][/ROW]
[ROW][C]144[/C][C]0.998662[/C][C]0.00267589[/C][C]0.00133795[/C][/ROW]
[ROW][C]145[/C][C]0.99863[/C][C]0.00273961[/C][C]0.00136981[/C][/ROW]
[ROW][C]146[/C][C]0.998896[/C][C]0.00220781[/C][C]0.00110391[/C][/ROW]
[ROW][C]147[/C][C]0.998612[/C][C]0.00277564[/C][C]0.00138782[/C][/ROW]
[ROW][C]148[/C][C]0.998326[/C][C]0.00334838[/C][C]0.00167419[/C][/ROW]
[ROW][C]149[/C][C]0.998102[/C][C]0.00379555[/C][C]0.00189777[/C][/ROW]
[ROW][C]150[/C][C]0.998595[/C][C]0.00281004[/C][C]0.00140502[/C][/ROW]
[ROW][C]151[/C][C]0.999515[/C][C]0.000970744[/C][C]0.000485372[/C][/ROW]
[ROW][C]152[/C][C]0.999445[/C][C]0.0011094[/C][C]0.000554702[/C][/ROW]
[ROW][C]153[/C][C]0.999608[/C][C]0.000783832[/C][C]0.000391916[/C][/ROW]
[ROW][C]154[/C][C]0.999611[/C][C]0.000778062[/C][C]0.000389031[/C][/ROW]
[ROW][C]155[/C][C]0.99968[/C][C]0.000639966[/C][C]0.000319983[/C][/ROW]
[ROW][C]156[/C][C]0.999621[/C][C]0.000757821[/C][C]0.000378911[/C][/ROW]
[ROW][C]157[/C][C]0.999657[/C][C]0.000685829[/C][C]0.000342914[/C][/ROW]
[ROW][C]158[/C][C]0.99964[/C][C]0.000720464[/C][C]0.000360232[/C][/ROW]
[ROW][C]159[/C][C]0.999577[/C][C]0.000846571[/C][C]0.000423285[/C][/ROW]
[ROW][C]160[/C][C]0.999484[/C][C]0.00103206[/C][C]0.000516031[/C][/ROW]
[ROW][C]161[/C][C]0.999661[/C][C]0.000677032[/C][C]0.000338516[/C][/ROW]
[ROW][C]162[/C][C]0.99975[/C][C]0.000500753[/C][C]0.000250377[/C][/ROW]
[ROW][C]163[/C][C]0.999719[/C][C]0.000561129[/C][C]0.000280564[/C][/ROW]
[ROW][C]164[/C][C]0.999996[/C][C]7.37627e-06[/C][C]3.68814e-06[/C][/ROW]
[ROW][C]165[/C][C]0.999997[/C][C]5.98512e-06[/C][C]2.99256e-06[/C][/ROW]
[ROW][C]166[/C][C]0.999996[/C][C]8.9476e-06[/C][C]4.4738e-06[/C][/ROW]
[ROW][C]167[/C][C]0.999997[/C][C]6.61373e-06[/C][C]3.30686e-06[/C][/ROW]
[ROW][C]168[/C][C]0.999997[/C][C]6.62542e-06[/C][C]3.31271e-06[/C][/ROW]
[ROW][C]169[/C][C]0.999996[/C][C]8.81918e-06[/C][C]4.40959e-06[/C][/ROW]
[ROW][C]170[/C][C]0.999995[/C][C]1.04648e-05[/C][C]5.23238e-06[/C][/ROW]
[ROW][C]171[/C][C]0.999994[/C][C]1.18368e-05[/C][C]5.91841e-06[/C][/ROW]
[ROW][C]172[/C][C]0.999996[/C][C]8.76671e-06[/C][C]4.38336e-06[/C][/ROW]
[ROW][C]173[/C][C]0.999996[/C][C]7.92764e-06[/C][C]3.96382e-06[/C][/ROW]
[ROW][C]174[/C][C]0.999995[/C][C]9.97874e-06[/C][C]4.98937e-06[/C][/ROW]
[ROW][C]175[/C][C]0.999994[/C][C]1.26545e-05[/C][C]6.32723e-06[/C][/ROW]
[ROW][C]176[/C][C]0.999995[/C][C]1.02862e-05[/C][C]5.14311e-06[/C][/ROW]
[ROW][C]177[/C][C]0.999992[/C][C]1.51929e-05[/C][C]7.59647e-06[/C][/ROW]
[ROW][C]178[/C][C]0.999996[/C][C]8.65825e-06[/C][C]4.32913e-06[/C][/ROW]
[ROW][C]179[/C][C]0.999995[/C][C]9.32028e-06[/C][C]4.66014e-06[/C][/ROW]
[ROW][C]180[/C][C]0.999994[/C][C]1.10882e-05[/C][C]5.54411e-06[/C][/ROW]
[ROW][C]181[/C][C]0.999993[/C][C]1.40806e-05[/C][C]7.0403e-06[/C][/ROW]
[ROW][C]182[/C][C]0.999991[/C][C]1.7234e-05[/C][C]8.617e-06[/C][/ROW]
[ROW][C]183[/C][C]0.999994[/C][C]1.29539e-05[/C][C]6.47695e-06[/C][/ROW]
[ROW][C]184[/C][C]0.999991[/C][C]1.76497e-05[/C][C]8.82484e-06[/C][/ROW]
[ROW][C]185[/C][C]0.999994[/C][C]1.1433e-05[/C][C]5.71648e-06[/C][/ROW]
[ROW][C]186[/C][C]0.999992[/C][C]1.53027e-05[/C][C]7.65135e-06[/C][/ROW]
[ROW][C]187[/C][C]0.999994[/C][C]1.13916e-05[/C][C]5.69581e-06[/C][/ROW]
[ROW][C]188[/C][C]0.999993[/C][C]1.30021e-05[/C][C]6.50105e-06[/C][/ROW]
[ROW][C]189[/C][C]0.999995[/C][C]1.08492e-05[/C][C]5.42458e-06[/C][/ROW]
[ROW][C]190[/C][C]0.999992[/C][C]1.60283e-05[/C][C]8.01413e-06[/C][/ROW]
[ROW][C]191[/C][C]0.999989[/C][C]2.25413e-05[/C][C]1.12707e-05[/C][/ROW]
[ROW][C]192[/C][C]0.999984[/C][C]3.12652e-05[/C][C]1.56326e-05[/C][/ROW]
[ROW][C]193[/C][C]0.999982[/C][C]3.61933e-05[/C][C]1.80966e-05[/C][/ROW]
[ROW][C]194[/C][C]0.999987[/C][C]2.61303e-05[/C][C]1.30651e-05[/C][/ROW]
[ROW][C]195[/C][C]0.999981[/C][C]3.77459e-05[/C][C]1.8873e-05[/C][/ROW]
[ROW][C]196[/C][C]0.999977[/C][C]4.53225e-05[/C][C]2.26612e-05[/C][/ROW]
[ROW][C]197[/C][C]0.999969[/C][C]6.12807e-05[/C][C]3.06403e-05[/C][/ROW]
[ROW][C]198[/C][C]0.999955[/C][C]9.05395e-05[/C][C]4.52697e-05[/C][/ROW]
[ROW][C]199[/C][C]0.999944[/C][C]0.000111745[/C][C]5.58726e-05[/C][/ROW]
[ROW][C]200[/C][C]0.999927[/C][C]0.000146893[/C][C]7.34466e-05[/C][/ROW]
[ROW][C]201[/C][C]0.999929[/C][C]0.000142007[/C][C]7.10034e-05[/C][/ROW]
[ROW][C]202[/C][C]0.999915[/C][C]0.000169299[/C][C]8.46496e-05[/C][/ROW]
[ROW][C]203[/C][C]0.999887[/C][C]0.000226208[/C][C]0.000113104[/C][/ROW]
[ROW][C]204[/C][C]0.999846[/C][C]0.00030871[/C][C]0.000154355[/C][/ROW]
[ROW][C]205[/C][C]0.999779[/C][C]0.000441692[/C][C]0.000220846[/C][/ROW]
[ROW][C]206[/C][C]0.999776[/C][C]0.000448942[/C][C]0.000224471[/C][/ROW]
[ROW][C]207[/C][C]0.999707[/C][C]0.000586286[/C][C]0.000293143[/C][/ROW]
[ROW][C]208[/C][C]0.999663[/C][C]0.000674272[/C][C]0.000337136[/C][/ROW]
[ROW][C]209[/C][C]0.999679[/C][C]0.000641827[/C][C]0.000320913[/C][/ROW]
[ROW][C]210[/C][C]0.999608[/C][C]0.000784028[/C][C]0.000392014[/C][/ROW]
[ROW][C]211[/C][C]0.99947[/C][C]0.00106081[/C][C]0.000530407[/C][/ROW]
[ROW][C]212[/C][C]0.999283[/C][C]0.00143435[/C][C]0.000717175[/C][/ROW]
[ROW][C]213[/C][C]0.999087[/C][C]0.00182629[/C][C]0.000913143[/C][/ROW]
[ROW][C]214[/C][C]0.998769[/C][C]0.00246112[/C][C]0.00123056[/C][/ROW]
[ROW][C]215[/C][C]0.998354[/C][C]0.00329176[/C][C]0.00164588[/C][/ROW]
[ROW][C]216[/C][C]0.997661[/C][C]0.00467715[/C][C]0.00233858[/C][/ROW]
[ROW][C]217[/C][C]0.997173[/C][C]0.00565442[/C][C]0.00282721[/C][/ROW]
[ROW][C]218[/C][C]0.996689[/C][C]0.00662197[/C][C]0.00331099[/C][/ROW]
[ROW][C]219[/C][C]0.995365[/C][C]0.00926951[/C][C]0.00463475[/C][/ROW]
[ROW][C]220[/C][C]0.993738[/C][C]0.0125242[/C][C]0.00626212[/C][/ROW]
[ROW][C]221[/C][C]0.993148[/C][C]0.0137038[/C][C]0.00685189[/C][/ROW]
[ROW][C]222[/C][C]0.99287[/C][C]0.0142593[/C][C]0.00712965[/C][/ROW]
[ROW][C]223[/C][C]0.990252[/C][C]0.0194951[/C][C]0.00974756[/C][/ROW]
[ROW][C]224[/C][C]0.989452[/C][C]0.0210957[/C][C]0.0105479[/C][/ROW]
[ROW][C]225[/C][C]0.989697[/C][C]0.0206055[/C][C]0.0103028[/C][/ROW]
[ROW][C]226[/C][C]0.993581[/C][C]0.0128383[/C][C]0.00641913[/C][/ROW]
[ROW][C]227[/C][C]0.995529[/C][C]0.00894214[/C][C]0.00447107[/C][/ROW]
[ROW][C]228[/C][C]0.994424[/C][C]0.0111526[/C][C]0.0055763[/C][/ROW]
[ROW][C]229[/C][C]0.996662[/C][C]0.00667549[/C][C]0.00333775[/C][/ROW]
[ROW][C]230[/C][C]0.998238[/C][C]0.0035245[/C][C]0.00176225[/C][/ROW]
[ROW][C]231[/C][C]0.998258[/C][C]0.00348397[/C][C]0.00174198[/C][/ROW]
[ROW][C]232[/C][C]0.998944[/C][C]0.00211218[/C][C]0.00105609[/C][/ROW]
[ROW][C]233[/C][C]0.998379[/C][C]0.00324264[/C][C]0.00162132[/C][/ROW]
[ROW][C]234[/C][C]0.998464[/C][C]0.00307268[/C][C]0.00153634[/C][/ROW]
[ROW][C]235[/C][C]0.997794[/C][C]0.0044118[/C][C]0.0022059[/C][/ROW]
[ROW][C]236[/C][C]0.998615[/C][C]0.00277071[/C][C]0.00138536[/C][/ROW]
[ROW][C]237[/C][C]0.998188[/C][C]0.00362411[/C][C]0.00181205[/C][/ROW]
[ROW][C]238[/C][C]0.997806[/C][C]0.00438798[/C][C]0.00219399[/C][/ROW]
[ROW][C]239[/C][C]0.997291[/C][C]0.00541788[/C][C]0.00270894[/C][/ROW]
[ROW][C]240[/C][C]0.995901[/C][C]0.00819831[/C][C]0.00409916[/C][/ROW]
[ROW][C]241[/C][C]0.994166[/C][C]0.0116685[/C][C]0.00583423[/C][/ROW]
[ROW][C]242[/C][C]0.991246[/C][C]0.0175085[/C][C]0.00875427[/C][/ROW]
[ROW][C]243[/C][C]0.987389[/C][C]0.025222[/C][C]0.012611[/C][/ROW]
[ROW][C]244[/C][C]0.982701[/C][C]0.0345975[/C][C]0.0172987[/C][/ROW]
[ROW][C]245[/C][C]0.979184[/C][C]0.0416321[/C][C]0.0208161[/C][/ROW]
[ROW][C]246[/C][C]0.971102[/C][C]0.0577961[/C][C]0.028898[/C][/ROW]
[ROW][C]247[/C][C]0.965237[/C][C]0.0695265[/C][C]0.0347632[/C][/ROW]
[ROW][C]248[/C][C]0.954215[/C][C]0.0915708[/C][C]0.0457854[/C][/ROW]
[ROW][C]249[/C][C]0.961021[/C][C]0.0779582[/C][C]0.0389791[/C][/ROW]
[ROW][C]250[/C][C]0.946879[/C][C]0.106242[/C][C]0.0531208[/C][/ROW]
[ROW][C]251[/C][C]0.932317[/C][C]0.135365[/C][C]0.0676827[/C][/ROW]
[ROW][C]252[/C][C]0.928155[/C][C]0.14369[/C][C]0.0718452[/C][/ROW]
[ROW][C]253[/C][C]0.905059[/C][C]0.189881[/C][C]0.0949406[/C][/ROW]
[ROW][C]254[/C][C]0.895811[/C][C]0.208378[/C][C]0.104189[/C][/ROW]
[ROW][C]255[/C][C]0.890073[/C][C]0.219855[/C][C]0.109927[/C][/ROW]
[ROW][C]256[/C][C]0.87502[/C][C]0.249959[/C][C]0.12498[/C][/ROW]
[ROW][C]257[/C][C]0.896154[/C][C]0.207692[/C][C]0.103846[/C][/ROW]
[ROW][C]258[/C][C]0.921043[/C][C]0.157914[/C][C]0.0789572[/C][/ROW]
[ROW][C]259[/C][C]0.893895[/C][C]0.21221[/C][C]0.106105[/C][/ROW]
[ROW][C]260[/C][C]0.996693[/C][C]0.00661499[/C][C]0.00330749[/C][/ROW]
[ROW][C]261[/C][C]0.99407[/C][C]0.0118593[/C][C]0.00592963[/C][/ROW]
[ROW][C]262[/C][C]0.991889[/C][C]0.0162224[/C][C]0.0081112[/C][/ROW]
[ROW][C]263[/C][C]0.999932[/C][C]0.000136877[/C][C]6.84387e-05[/C][/ROW]
[ROW][C]264[/C][C]0.999846[/C][C]0.000307991[/C][C]0.000153996[/C][/ROW]
[ROW][C]265[/C][C]0.999726[/C][C]0.000547421[/C][C]0.00027371[/C][/ROW]
[ROW][C]266[/C][C]0.999791[/C][C]0.00041822[/C][C]0.00020911[/C][/ROW]
[ROW][C]267[/C][C]0.999904[/C][C]0.000192621[/C][C]9.63106e-05[/C][/ROW]
[ROW][C]268[/C][C]0.999815[/C][C]0.000370255[/C][C]0.000185128[/C][/ROW]
[ROW][C]269[/C][C]0.999819[/C][C]0.000362832[/C][C]0.000181416[/C][/ROW]
[ROW][C]270[/C][C]0.998679[/C][C]0.00264266[/C][C]0.00132133[/C][/ROW]
[ROW][C]271[/C][C]0.994606[/C][C]0.0107882[/C][C]0.00539412[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270999&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270999&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.8089170.3821660.191083
80.7554690.4890630.244531
90.6673530.6652950.332647
100.6427750.714450.357225
110.5342960.9314090.465704
120.659810.680380.34019
130.5657020.8685960.434298
140.4756110.9512220.524389
150.4463240.8926490.553676
160.3602170.7204340.639783
170.2877220.5754450.712278
180.2253560.4507120.774644
190.2020350.404070.797965
200.1531310.3062610.846869
210.1716930.3433860.828307
220.143450.2868990.85655
230.1120130.2240250.887987
240.09839410.1967880.901606
250.0741780.1483560.925822
260.06117880.1223580.938821
270.04383180.08766360.956168
280.04253440.08506880.957466
290.0313780.0627560.968622
300.02698730.05397460.973013
310.02115150.0423030.978848
320.01753870.03507750.982461
330.01291570.02583150.987084
340.01556320.03112630.984437
350.01121480.02242960.988785
360.007806910.01561380.992193
370.005753340.01150670.994247
380.003965430.007930860.996035
390.004427290.008854590.995573
400.003312670.006625350.996687
410.005677090.01135420.994323
420.00424910.008498210.995751
430.00386420.00772840.996136
440.002926270.005852540.997074
450.002144050.004288090.997856
460.001660890.003321770.998339
470.00136340.00272680.998637
480.004056830.008113660.995943
490.005216360.01043270.994784
500.004065530.008131050.995934
510.002861680.005723370.997138
520.003973890.007947780.996026
530.003187210.006374420.996813
540.002319590.004639180.99768
550.002472330.004944670.997528
560.001846360.003692730.998154
570.007320290.01464060.99268
580.01068360.02136720.989316
590.008325860.01665170.991674
600.007967850.01593570.992032
610.009588880.01917780.990411
620.009095270.01819050.990905
630.00944990.01889980.99055
640.01335680.02671360.986643
650.01538490.03076970.984615
660.01256440.02512870.987436
670.01425440.02850870.985746
680.01427740.02855480.985723
690.01611710.03223410.983883
700.01321240.02642490.986788
710.01326430.02652850.986736
720.01180820.02361630.988192
730.01059990.02119980.9894
740.01007890.02015790.989921
750.009479430.01895890.990521
760.008943560.01788710.991056
770.007512530.01502510.992487
780.007354220.01470840.992646
790.005880280.01176060.99412
800.008585520.0171710.991414
810.007028880.01405780.992971
820.006854890.01370980.993145
830.005426250.01085250.994574
840.02364860.04729720.976351
850.0236070.0472140.976393
860.02012140.04024290.979879
870.01641040.03282070.98359
880.01333140.02666290.986669
890.0139090.02781790.986091
900.01309240.02618490.986908
910.01317470.02634930.986825
920.03485070.06970150.965149
930.03696530.07393060.963035
940.03608070.07216150.963919
950.04393510.08787030.956065
960.04577330.09154670.954227
970.08114920.1622980.918851
980.07537550.1507510.924624
990.091170.182340.90883
1000.1479240.2958470.852076
1010.1322810.2645620.867719
1020.1268620.2537250.873138
1030.1369950.2739910.863005
1040.1707650.341530.829235
1050.188620.377240.81138
1060.2372940.4745870.762706
1070.2444720.4889440.755528
1080.4743380.9486750.525662
1090.525010.9499790.47499
1100.548470.903060.45153
1110.5549980.8900040.445002
1120.5523470.8953060.447653
1130.6648810.6702380.335119
1140.697280.605440.30272
1150.8439690.3120630.156031
1160.9184290.1631410.0815706
1170.9223970.1552070.0776033
1180.9259240.1481520.0740759
1190.9378080.1243840.0621918
1200.9578050.08438920.0421946
1210.954690.09062080.0453104
1220.9667770.06644550.0332227
1230.9840880.03182330.0159117
1240.9938680.01226470.00613236
1250.9935210.01295870.00647933
1260.9927980.01440440.0072022
1270.9947530.01049450.00524724
1280.9939420.01211530.00605764
1290.9951960.009608840.00480442
1300.9952280.009544660.00477233
1310.9957160.008568110.00428406
1320.9956420.008715270.00435763
1330.9954680.009063940.00453197
1340.9949290.01014190.00507097
1350.9940990.01180150.00590077
1360.9926480.01470380.00735192
1370.9966460.006707930.00335396
1380.9957890.008422940.00421147
1390.9972470.005505340.00275267
1400.9969970.006005840.00300292
1410.9963630.007274970.00363748
1420.997830.004339890.00216994
1430.9976120.004776470.00238823
1440.9986620.002675890.00133795
1450.998630.002739610.00136981
1460.9988960.002207810.00110391
1470.9986120.002775640.00138782
1480.9983260.003348380.00167419
1490.9981020.003795550.00189777
1500.9985950.002810040.00140502
1510.9995150.0009707440.000485372
1520.9994450.00110940.000554702
1530.9996080.0007838320.000391916
1540.9996110.0007780620.000389031
1550.999680.0006399660.000319983
1560.9996210.0007578210.000378911
1570.9996570.0006858290.000342914
1580.999640.0007204640.000360232
1590.9995770.0008465710.000423285
1600.9994840.001032060.000516031
1610.9996610.0006770320.000338516
1620.999750.0005007530.000250377
1630.9997190.0005611290.000280564
1640.9999967.37627e-063.68814e-06
1650.9999975.98512e-062.99256e-06
1660.9999968.9476e-064.4738e-06
1670.9999976.61373e-063.30686e-06
1680.9999976.62542e-063.31271e-06
1690.9999968.81918e-064.40959e-06
1700.9999951.04648e-055.23238e-06
1710.9999941.18368e-055.91841e-06
1720.9999968.76671e-064.38336e-06
1730.9999967.92764e-063.96382e-06
1740.9999959.97874e-064.98937e-06
1750.9999941.26545e-056.32723e-06
1760.9999951.02862e-055.14311e-06
1770.9999921.51929e-057.59647e-06
1780.9999968.65825e-064.32913e-06
1790.9999959.32028e-064.66014e-06
1800.9999941.10882e-055.54411e-06
1810.9999931.40806e-057.0403e-06
1820.9999911.7234e-058.617e-06
1830.9999941.29539e-056.47695e-06
1840.9999911.76497e-058.82484e-06
1850.9999941.1433e-055.71648e-06
1860.9999921.53027e-057.65135e-06
1870.9999941.13916e-055.69581e-06
1880.9999931.30021e-056.50105e-06
1890.9999951.08492e-055.42458e-06
1900.9999921.60283e-058.01413e-06
1910.9999892.25413e-051.12707e-05
1920.9999843.12652e-051.56326e-05
1930.9999823.61933e-051.80966e-05
1940.9999872.61303e-051.30651e-05
1950.9999813.77459e-051.8873e-05
1960.9999774.53225e-052.26612e-05
1970.9999696.12807e-053.06403e-05
1980.9999559.05395e-054.52697e-05
1990.9999440.0001117455.58726e-05
2000.9999270.0001468937.34466e-05
2010.9999290.0001420077.10034e-05
2020.9999150.0001692998.46496e-05
2030.9998870.0002262080.000113104
2040.9998460.000308710.000154355
2050.9997790.0004416920.000220846
2060.9997760.0004489420.000224471
2070.9997070.0005862860.000293143
2080.9996630.0006742720.000337136
2090.9996790.0006418270.000320913
2100.9996080.0007840280.000392014
2110.999470.001060810.000530407
2120.9992830.001434350.000717175
2130.9990870.001826290.000913143
2140.9987690.002461120.00123056
2150.9983540.003291760.00164588
2160.9976610.004677150.00233858
2170.9971730.005654420.00282721
2180.9966890.006621970.00331099
2190.9953650.009269510.00463475
2200.9937380.01252420.00626212
2210.9931480.01370380.00685189
2220.992870.01425930.00712965
2230.9902520.01949510.00974756
2240.9894520.02109570.0105479
2250.9896970.02060550.0103028
2260.9935810.01283830.00641913
2270.9955290.008942140.00447107
2280.9944240.01115260.0055763
2290.9966620.006675490.00333775
2300.9982380.00352450.00176225
2310.9982580.003483970.00174198
2320.9989440.002112180.00105609
2330.9983790.003242640.00162132
2340.9984640.003072680.00153634
2350.9977940.00441180.0022059
2360.9986150.002770710.00138536
2370.9981880.003624110.00181205
2380.9978060.004387980.00219399
2390.9972910.005417880.00270894
2400.9959010.008198310.00409916
2410.9941660.01166850.00583423
2420.9912460.01750850.00875427
2430.9873890.0252220.012611
2440.9827010.03459750.0172987
2450.9791840.04163210.0208161
2460.9711020.05779610.028898
2470.9652370.06952650.0347632
2480.9542150.09157080.0457854
2490.9610210.07795820.0389791
2500.9468790.1062420.0531208
2510.9323170.1353650.0676827
2520.9281550.143690.0718452
2530.9050590.1898810.0949406
2540.8958110.2083780.104189
2550.8900730.2198550.109927
2560.875020.2499590.12498
2570.8961540.2076920.103846
2580.9210430.1579140.0789572
2590.8938950.212210.106105
2600.9966930.006614990.00330749
2610.994070.01185930.00592963
2620.9918890.01622240.0081112
2630.9999320.0001368776.84387e-05
2640.9998460.0003079910.000153996
2650.9997260.0005474210.00027371
2660.9997910.000418220.00020911
2670.9999040.0001926219.63106e-05
2680.9998150.0003702550.000185128
2690.9998190.0003628320.000181416
2700.9986790.002642660.00132133
2710.9946060.01078820.00539412






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1270.479245NOK
5% type I error level1960.739623NOK
10% type I error level2120.8NOK

\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 & 127 & 0.479245 & NOK \tabularnewline
5% type I error level & 196 & 0.739623 & NOK \tabularnewline
10% type I error level & 212 & 0.8 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270999&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]127[/C][C]0.479245[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]196[/C][C]0.739623[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]212[/C][C]0.8[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270999&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270999&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1270.479245NOK
5% type I error level1960.739623NOK
10% type I error level2120.8NOK


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 5
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 6
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 7
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 8
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 9
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 10
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Input Parameters & R Code

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