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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 27 Nov 2014 13:34:44 +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/Nov/27/t1417095546bxr48hryqktoo2f.htm/, Retrieved Sun, 19 May 2024 19:42:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=260190, Retrieved Sun, 19 May 2024 19:42:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact82

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [paper] [2014-11-27 13:34:44] [627bde65e5570be47fd7fc8a9f75ea40] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12,9	86	149	21	26	50
7,4	62	152	26	51	68
12,2	70	139	22	57	62
12,8	71	148	22	37	54
7,4	108	158	18	67	71
6,7	64	128	23	43	54
12,6	119	224	12	52	65
14,8	97	159	20	52	73
13,3	129	105	22	43	52
11,1	153	159	21	84	84
8,2	78	167	19	67	42
11,4	80	165	22	49	66
6,4	99	159	15	70	65
10,6	68	119	20	52	78
12,0	147	176	19	58	73
6,3	40	54	18	68	75
11,3	57	91	15	62	72
11,9	120	163	20	43	66
9,3	71	124	21	56	70
9,6	84	137	21	56	61
10,0	68	121	15	74	81
6,4	55	153	16	65	71
13,8	137	148	23	63	69
10,8	79	221	21	58	71
13,8	116	188	18	57	72
11,7	101	149	25	63	68
10,9	111	244	9	53	70
16,1	189	148	30	57	68
13,4	66	92	20	51	61
9,9	81	150	23	64	67
11,5	63	153	16	53	76
8,3	69	94	16	29	70
11,7	71	156	19	54	60
6,1	70	146	25	51	77
9,0	64	132	25	58	72
9,7	143	161	18	43	69
10,8	85	105	23	51	71
10,3	86	97	21	53	62
10,4	55	151	10	54	70
12,7	69	131	14	56	64
9,3	120	166	22	61	58
11,8	96	157	26	47	76
5,9	60	111	23	39	52
11,4	95	145	23	48	59
13,0	100	162	24	50	68
10,8	68	163	24	35	76
12,3	57	59	18	30	65
11,3	105	187	23	68	67
11,8	85	109	15	49	59
7,9	103	90	19	61	69
12,7	57	105	16	67	76
12,3	51	83	25	47	63
11,6	69	116	23	56	75
6,7	41	42	17	50	63
10,9	49	148	19	43	60
12,1	50	155	21	67	73
13,3	93	125	18	62	63
10,1	58	116	27	57	70
5,7	54	128	21	41	75
14,3	74	138	13	54	66
8,0	15	49	8	45	63
13,3	69	96	29	48	63
9,3	107	164	28	61	64
12,5	65	162	23	56	70
7,6	58	99	21	41	75
15,9	107	202	19	43	61
9,2	70	186	19	53	60
9,1	53	66	20	44	62
11,1	136	183	18	66	73
13,0	126	214	19	58	61
14,5	95	188	17	46	66
12,2	69	104	19	37	64
12,3	136	177	25	51	59
11,4	58	126	19	51	64
8,8	59	76	22	56	60
14,6	118	99	23	66	56
7,3	110	157	26	45	66
12,6	82	139	14	37	78
NA	50	78	28	59	53
13,0	102	162	16	42	67
12,6	65	108	24	38	59
13,2	90	159	20	66	66
9,9	64	74	12	34	68
7,7	83	110	24	53	71
10,5	70	96	22	49	66
13,4	50	116	12	55	73
10,9	77	87	22	49	72
4,3	37	97	20	59	71
10,3	81	127	10	40	59
11,8	101	106	23	58	64
11,2	79	80	17	60	66
11,4	71	74	22	63	78
8,6	60	91	24	56	68
13,2	55	133	18	54	73
12,6	44	74	21	52	62
5,6	40	114	20	34	65
9,9	56	140	20	69	68
8,8	43	95	22	32	65
7,7	45	98	19	48	60
9,0	32	121	20	67	71
7,3	56	126	26	58	65
11,4	40	98	23	57	68
13,6	34	95	24	42	64
7,9	89	110	21	64	74
10,7	50	70	21	58	69
10,3	56	102	19	66	76
8,3	46	86	8	26	68
9,6	76	130	17	61	72
14,2	64	96	20	52	67
8,5	74	102	11	51	63
13,5	57	100	8	55	59
4,9	45	94	15	50	73
6,4	30	52	18	60	66
9,6	62	98	18	56	62
11,6	51	118	19	63	69
11,1	36	99	19	61	66
4,4	34	48	23	52	51
12,7	61	50	22	16	56
18,1	70	150	21	46	67
17,9	69	154	25	56	69
16,6	145	109	30	52	57
12,6	23	68	17	55	56
17,1	120	194	27	50	55
19,1	147	158	23	59	63
16,1	215	159	23	60	67
13,4	24	67	18	52	65
18,4	84	147	18	44	47
14,7	30	39	23	67	76
10,6	77	100	19	52	64
12,6	46	111	15	55	68
16,2	61	138	20	37	64
13,6	178	101	16	54	65
18,9	160	131	24	72	71
14,1	57	101	25	51	63
14,5	42	114	25	48	60
16,2	163	165	19	60	68
14,8	75	114	19	50	72
14,8	94	111	16	63	70
12,5	45	75	19	33	61
12,7	78	82	19	67	61
17,4	47	121	23	46	62
8,6	29	32	21	54	71
18,4	97	150	22	59	71
16,1	116	117	19	61	51
11,6	32	71	20	33	56
17,8	50	165	20	47	70
15,3	118	154	3	69	73
17,7	66	126	23	52	76
15,6	48	138	14	55	59
16,4	86	149	23	55	68
17,7	89	145	20	41	48
13,6	76	120	15	73	52
11,7	39	138	13	51	59
14,4	75	109	16	52	60
14,8	57	132	7	50	59
18,3	72	172	24	51	57
9,9	60	169	17	60	79
16,0	109	114	24	56	60
18,3	76	156	24	56	60
16,9	65	172	19	29	59
14,6	40	68	25	66	62
13,9	58	89	20	66	59
19,0	123	167	28	73	61
15,6	71	113	23	55	71
14,9	102	115	27	64	57
11,8	80	78	18	40	66
18,5	97	118	28	46	63
15,9	46	87	21	58	69
17,1	93	173	19	43	58
16,1	19	2	23	61	59
19,9	140	162	27	51	48
11,0	78	49	22	50	66
18,5	98	122	28	52	73
15,1	40	96	25	54	67
15,0	80	100	21	66	61
11,4	76	82	22	61	68
16,0	79	100	28	80	75
18,1	87	115	20	51	62
14,6	95	141	29	56	69
15,4	49	165	25	56	58
15,4	49	165	25	56	60
17,6	80	110	20	53	74
13,4	86	118	20	47	55
19,1	69	158	16	25	62
15,4	79	146	20	47	63
7,6	52	49	20	46	69
13,4	120	90	23	50	58
13,9	69	121	18	39	58
19,1	94	155	25	51	68
15,3	72	104	18	58	72
12,9	43	147	19	35	62
16,1	87	110	25	58	62
17,4	52	108	25	60	65
13,2	71	113	25	62	69
12,2	61	115	24	63	66
12,6	51	61	19	53	72
10,4	50	60	26	46	62
15,4	67	109	10	67	75
9,6	30	68	17	59	58
18,2	70	111	13	64	66
13,6	52	77	17	38	55
14,9	75	73	30	50	47
14,8	87	151	25	48	72
14,1	69	89	4	48	62
14,9	72	78	16	47	64
16,3	79	110	21	66	64
19,3	121	220	23	47	19
13,6	43	65	22	63	50
13,6	58	141	17	58	68
15,7	57	117	20	44	70
12,8	50	122	20	51	79
14,6	69	63	22	43	69
9,9	64	44	16	55	71
12,7	38	52	23	38	48
11,9	53	62	16	56	66
19,2	90	131	0	45	73
16,6	96	101	18	50	74
11,2	49	42	25	54	66
15,3	56	152	23	57	71
11,9	102	107	12	60	74
13,2	40	77	18	55	78
16,4	100	154	24	56	75
12,4	67	103	11	49	53
15,9	78	96	18	37	60
14,4	62	154	14	43	50
18,2	55	175	23	59	70
11,2	59	57	24	46	69
15,7	96	112	29	51	65
17,8	86	143	18	58	78
7,7	38	49	15	64	78
12,4	43	110	29	53	59
15,6	23	131	16	48	72
19,3	77	167	19	51	70
15,2	48	56	22	47	63
17,1	26	137	16	59	63
15,6	91	86	23	62	71
18,4	94	121	23	62	74
19,1	62	149	19	51	67
18,6	74	168	4	64	66
19,1	114	140	20	52	62
13,1	52	88	24	67	80
12,9	64	168	20	50	73
9,5	31	94	4	54	67
4,5	38	51	24	58	61
11,9	27	48	22	56	73
13,6	105	145	16	63	74
11,7	64	66	3	31	32
12,4	62	85	15	65	69
13,4	65	109	24	71	69
11,4	58	63	17	50	84
14,9	76	102	20	57	64
19,9	140	162	27	47	58
17,8	48	128	23	54	60
11,2	68	86	26	47	59
14,6	80	114	23	57	78
17,6	71	164	17	43	57
14,1	76	119	20	41	60
16,1	63	126	22	63	68
13,4	46	132	19	63	68
11,9	53	142	24	56	73
12,0	74	83	19	51	69
14,8	70	94	23	50	67
15,2	78	81	15	22	60
13,2	56	166	27	41	65
16,9	100	110	26	59	66
7,9	51	64	22	56	74
7,7	52	93	22	66	81
12,6	102	104	18	53	72
7,9	78	105	15	42	55
11,0	78	49	22	52	49
12,4	55	88	27	54	74
10,0	98	95	10	44	53
14,9	76	102	20	62	64
16,7	73	99	17	53	65
13,4	47	63	23	50	57
14,0	45	76	19	36	51
15,7	83	109	13	76	80
16,9	60	117	27	66	67
11,0	48	57	23	62	70
15,4	50	120	16	59	74
12,2	56	73	25	47	75
15,1	77	91	2	55	70
17,8	91	108	26	58	69
15,2	76	105	20	60	65
14,6	68	117	23	44	55
16,7	74	119	22	57	71
8,1	29	31	24	45	65

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
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260190&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]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260190&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260190&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
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






Multiple Linear Regression - Estimated Regression Equation
score[t] = + 11.6837 + 0.0211983RFC[t] + 0.015831LFM[t] + 0.0456032NUMERACY[t] + 0.00689869`I,MOT`[t] -0.0523091`E,MOT\r`[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
score[t] =  +  11.6837 +  0.0211983RFC[t] +  0.015831LFM[t] +  0.0456032NUMERACY[t] +  0.00689869`I,MOT`[t] -0.0523091`E,MOT\r`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260190&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]score[t] =  +  11.6837 +  0.0211983RFC[t] +  0.015831LFM[t] +  0.0456032NUMERACY[t] +  0.00689869`I,MOT`[t] -0.0523091`E,MOT\r`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260190&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260190&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
score[t] = + 11.6837 + 0.0211983RFC[t] + 0.015831LFM[t] + 0.0456032NUMERACY[t] + 0.00689869`I,MOT`[t] -0.0523091`E,MOT\r`[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)11.68371.866816.2591.45215e-097.26075e-10
RFC0.02119830.007497922.8270.005033920.00251696
LFM0.0158310.005589412.8320.004956550.00247828
NUMERACY0.04560320.03770521.2090.2275040.113752
`I,MOT`0.006898690.02038120.33850.7352530.367627
`E,MOT\r`-0.05230910.0252135-2.0750.03893250.0194662

\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) & 11.6837 & 1.86681 & 6.259 & 1.45215e-09 & 7.26075e-10 \tabularnewline
RFC & 0.0211983 & 0.00749792 & 2.827 & 0.00503392 & 0.00251696 \tabularnewline
LFM & 0.015831 & 0.00558941 & 2.832 & 0.00495655 & 0.00247828 \tabularnewline
NUMERACY & 0.0456032 & 0.0377052 & 1.209 & 0.227504 & 0.113752 \tabularnewline
`I,MOT` & 0.00689869 & 0.0203812 & 0.3385 & 0.735253 & 0.367627 \tabularnewline
`E,MOT\r` & -0.0523091 & 0.0252135 & -2.075 & 0.0389325 & 0.0194662 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260190&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]11.6837[/C][C]1.86681[/C][C]6.259[/C][C]1.45215e-09[/C][C]7.26075e-10[/C][/ROW]
[ROW][C]RFC[/C][C]0.0211983[/C][C]0.00749792[/C][C]2.827[/C][C]0.00503392[/C][C]0.00251696[/C][/ROW]
[ROW][C]LFM[/C][C]0.015831[/C][C]0.00558941[/C][C]2.832[/C][C]0.00495655[/C][C]0.00247828[/C][/ROW]
[ROW][C]NUMERACY[/C][C]0.0456032[/C][C]0.0377052[/C][C]1.209[/C][C]0.227504[/C][C]0.113752[/C][/ROW]
[ROW][C]`I,MOT`[/C][C]0.00689869[/C][C]0.0203812[/C][C]0.3385[/C][C]0.735253[/C][C]0.367627[/C][/ROW]
[ROW][C]`E,MOT\r`[/C][C]-0.0523091[/C][C]0.0252135[/C][C]-2.075[/C][C]0.0389325[/C][C]0.0194662[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260190&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260190&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)11.68371.866816.2591.45215e-097.26075e-10
RFC0.02119830.007497922.8270.005033920.00251696
LFM0.0158310.005589412.8320.004956550.00247828
NUMERACY0.04560320.03770521.2090.2275040.113752
`I,MOT`0.006898690.02038120.33850.7352530.367627
`E,MOT\r`-0.05230910.0252135-2.0750.03893250.0194662






Multiple Linear Regression - Regression Statistics
Multiple R0.360481
R-squared0.129946
Adjusted R-squared0.11441
F-TEST (value)8.36384
F-TEST (DF numerator)5
F-TEST (DF denominator)280
p-value2.18269e-07
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.22549
Sum Squared Residuals2913.06

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.360481 \tabularnewline
R-squared & 0.129946 \tabularnewline
Adjusted R-squared & 0.11441 \tabularnewline
F-TEST (value) & 8.36384 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 280 \tabularnewline
p-value & 2.18269e-07 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.22549 \tabularnewline
Sum Squared Residuals & 2913.06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260190&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.360481[/C][/ROW]
[ROW][C]R-squared[/C][C]0.129946[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.11441[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]8.36384[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]280[/C][/ROW]
[ROW][C]p-value[/C][C]2.18269e-07[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.22549[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2913.06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260190&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260190&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 R0.360481
R-squared0.129946
Adjusted R-squared0.11441
F-TEST (value)8.36384
F-TEST (DF numerator)5
F-TEST (DF denominator)280
p-value2.18269e-07
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.22549
Sum Squared Residuals2913.06






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.3872-1.48717
27.413.3848-5.98482
312.213.5214-1.32144
412.813.9656-1.16562
57.414.0436-6.64356
66.713.5876-6.8876
712.615.2583-2.65834
814.813.70931.09069
913.314.6604-1.3604
1011.114.5874-3.48738
118.215.1127-6.91265
1211.413.8806-2.4806
136.414.0663-7.66635
1410.612.1998-1.59978
151215.0341-3.03415
166.310.7533-4.45331
1711.311.6782-0.378153
1811.914.5643-2.66428
199.312.8342-3.5342
209.613.7864-4.18636
211011.9983-1.99827
226.412.7359-6.33589
2313.814.805-1.00504
2410.814.5009-3.70088
2513.814.5668-0.766779
2611.714.2012-2.50124
2710.915.0139-4.11392
2816.116.2375-0.137491
2913.412.61230.787701
309.913.7611-3.86111
3111.512.5611-1.06114
328.311.9026-3.60259
3311.713.7589-2.05888
346.112.943-6.84304
35912.904-3.90405
369.714.772-5.07204
3710.812.8346-2.03459
3810.313.1225-2.82251
3910.412.407-2.00703
4012.712.8973-0.197251
419.315.2456-5.94562
4211.813.7387-1.93865
435.913.3107-7.41071
4411.414.2868-2.88683
451314.2506-1.25056
4610.813.0661-2.26609
4712.311.45380.846225
4811.314.8832-3.58321
4911.813.147-1.347
507.912.9699-5.06989
5112.711.77060.929353
5212.312.24760.0523525
5311.612.4948-0.894814
546.711.0425-4.34246
5510.913.09-2.18998
5612.112.7988-0.698753
5713.313.5871-0.287139
5810.112.7125-2.61249
595.712.1721-6.47212
6014.312.951.34996
61810.1572-2.1572
6213.313.02430.275668
639.314.8981-5.59815
6412.513.3998-0.899793
657.611.7978-4.19782
6615.915.1220.77795
679.214.2057-5.00571
689.111.8245-2.72451
6911.114.9214-3.82137
701315.8183-2.81827
7114.514.3140.18602
7212.212.5668-0.366754
7312.315.7745-3.47445
7411.412.7784-1.37844
758.812.3886-3.58862
7614.614.32730.272735
777.314.5447-7.24472
7812.612.43610.163925
79NANA-0.925255
801313.4417-0.441745
8112.613.4237-0.823672
8213.214.7367-1.53668
839.915.1307-5.23075
847.79.77628-2.07628
8510.58.788131.71187
8613.414.7683-1.36833
8710.918.2088-7.3088
884.37.05706-2.75706
8910.312.104-1.80405
9011.812.9616-1.16164
9111.211.5181-0.318068
9211.415.12-3.72002
938.67.729970.87003
9413.212.46120.73883
9512.619.0829-6.48291
965.68.61822-3.01822
979.913.0231-3.12313
988.813.3481-4.54813
997.710.6379-2.93794
100914.7512-5.75124
1017.37.86817-0.568166
10211.49.744841.65516
10313.618.5401-4.94009
1047.98.80026-0.900264
10510.712.2319-1.53187
10610.313.0075-2.70748
1078.311.4826-3.18264
1089.67.726271.87373
10914.218.1251-3.92515
1108.57.133141.36686
11113.519.9362-6.43617
1124.99.42525-4.52525
1136.49.31347-2.91347
1149.610.3246-0.724639
11511.612.349-0.749004
11611.118.6042-7.50419
1174.43.65270.747298
11812.77.912554.78745
11918.113.70154.39855
12017.916.52831.37174
12116.615.47321.12684
12212.611.4981.10205
12317.113.46163.63841
12419.119.7166-0.616571
12516.113.73262.36735
12613.49.457413.94259
12718.414.17274.22733
12814.716.8765-2.1765
12910.69.922540.677463
13012.69.381033.21897
13116.217.358-1.15804
13213.69.726553.87345
13318.917.48741.41261
13414.112.31151.78855
13514.513.77450.725477
13616.213.92352.27654
13714.812.93621.86377
13814.814.02820.771773
13912.512.5731-0.0731446
14012.78.018644.68136
14117.419.2213-1.82131
1428.64.010954.58905
14318.416.91451.48553
14416.116.1965-0.0964733
14511.66.730414.86959
14617.815.91731.88265
14715.310.10965.19037
14817.714.91752.78245
14915.612.93692.66313
15016.413.24993.15006
15117.717.7621-0.0620881
15213.614.4536-0.853567
15311.710.2491.45099
15414.412.15962.24037
15514.810.89763.90238
15618.321.0878-2.78781
1579.98.041321.85868
1581611.80674.19332
15918.315.16483.13517
16016.914.26042.63962
16114.613.30331.29668
16213.910.42453.47547
1631916.09212.90794
16415.615.05770.542306
16514.915.3588-0.458804
16611.87.206774.59323
16718.514.38464.1154
16815.913.32312.5769
16917.111.50165.5984
17016.112.48843.61161
17119.920.9087-1.00871
172116.009594.99041
17318.515.45933.04068
17415.113.28481.81519
1751516.06-1.06
17611.48.247093.15291
1771611.26934.73073
17818.117.52920.570781
17914.613.0271.57297
18015.413.72241.67759
18115.410.32785.07219
18217.617.9341-0.334132
18313.47.606655.79335
18419.117.31051.78946
18515.418.9818-3.58182
1867.68.21218-0.612185
18713.412.61790.78207
18813.98.865065.03494
18919.116.11112.98885
19015.315.18720.112848
19112.910.36642.53358
19216.111.34974.75031
19317.417.13620.263829
19413.213.8741-0.674072
19512.210.79641.40364
19612.614.1533-1.55335
19710.46.824643.57536
19815.417.3445-1.94452
1999.63.90685.6932
20018.216.76541.43458
20113.612.38381.21625
20214.913.72341.17659
20314.812.52572.27425
20414.111.35092.74908
20514.911.7653.13501
20616.315.11081.18923
20719.318.14671.15331
20813.612.76370.83625
20913.610.19823.40178
21015.714.70650.993508
21112.810.03432.76566
21214.615.8321-1.2321
2139.99.312650.58735
21412.712.25230.447675
21511.94.85737.0427
21619.215.21263.9874
21716.616.8475-0.247543
21811.28.905292.29471
21915.316.0301-0.730149
22011.99.570812.32919
22113.210.59912.60086
22216.416.8019-0.401885
22312.49.294523.10548
22415.915.25560.64438
22514.49.614314.78569
22618.218.6393-0.439271
22711.29.266061.93394
22815.710.81154.88852
22917.820.4104-2.61042
2307.78.23854-0.53854
23112.48.339674.06033
23215.69.816425.78358
23319.315.71983.58019
23415.210.34494.85508
23517.114.23692.86312
23615.610.39765.20237
23718.412.37046.02958
23819.113.58355.51647
23918.613.84434.7557
24019.117.55111.54888
24113.113.3385-0.238452
24212.914.2792-1.37921
2439.516.6004-7.10038
2444.53.186991.31301
24511.911.79840.101569
24613.614.662-1.06203
24711.711.16680.533218
24812.411.76210.637858
24913.412.63680.763205
25011.49.367062.03294
25114.910.73774.1623
25219.915.11054.78954
25317.819.5104-1.71035
25411.29.14632.0537
25514.610.87543.72464
25617.616.7350.864958
25714.110.89483.20521
25816.115.19260.907409
25913.414.2175-0.817468
26011.912.0753-0.17533
261129.744812.25519
26214.811.91682.88323
26315.215.6128-0.41281
26413.29.985263.21474
26516.920.2967-3.39674
2667.911.6799-3.77986
2677.78.0126-0.312602
26812.617.7962-5.19623
2697.99.81176-1.91176
2701110.57570.424307
27112.415.6523-3.25229
272108.001551.99845
27314.910.73934.16074
27416.715.38961.31042
27513.411.68781.71215
2761410.40123.59883
27715.711.78973.91027
27816.917.3186-0.418556
279117.509153.49085
28015.414.76760.63238
28112.28.665613.53439
28215.110.5994.50101
28317.815.48292.31706
28415.214.05281.14716
28514.610.71883.88117
28616.719.3941-2.69405
2878.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 14.3872 & -1.48717 \tabularnewline
2 & 7.4 & 13.3848 & -5.98482 \tabularnewline
3 & 12.2 & 13.5214 & -1.32144 \tabularnewline
4 & 12.8 & 13.9656 & -1.16562 \tabularnewline
5 & 7.4 & 14.0436 & -6.64356 \tabularnewline
6 & 6.7 & 13.5876 & -6.8876 \tabularnewline
7 & 12.6 & 15.2583 & -2.65834 \tabularnewline
8 & 14.8 & 13.7093 & 1.09069 \tabularnewline
9 & 13.3 & 14.6604 & -1.3604 \tabularnewline
10 & 11.1 & 14.5874 & -3.48738 \tabularnewline
11 & 8.2 & 15.1127 & -6.91265 \tabularnewline
12 & 11.4 & 13.8806 & -2.4806 \tabularnewline
13 & 6.4 & 14.0663 & -7.66635 \tabularnewline
14 & 10.6 & 12.1998 & -1.59978 \tabularnewline
15 & 12 & 15.0341 & -3.03415 \tabularnewline
16 & 6.3 & 10.7533 & -4.45331 \tabularnewline
17 & 11.3 & 11.6782 & -0.378153 \tabularnewline
18 & 11.9 & 14.5643 & -2.66428 \tabularnewline
19 & 9.3 & 12.8342 & -3.5342 \tabularnewline
20 & 9.6 & 13.7864 & -4.18636 \tabularnewline
21 & 10 & 11.9983 & -1.99827 \tabularnewline
22 & 6.4 & 12.7359 & -6.33589 \tabularnewline
23 & 13.8 & 14.805 & -1.00504 \tabularnewline
24 & 10.8 & 14.5009 & -3.70088 \tabularnewline
25 & 13.8 & 14.5668 & -0.766779 \tabularnewline
26 & 11.7 & 14.2012 & -2.50124 \tabularnewline
27 & 10.9 & 15.0139 & -4.11392 \tabularnewline
28 & 16.1 & 16.2375 & -0.137491 \tabularnewline
29 & 13.4 & 12.6123 & 0.787701 \tabularnewline
30 & 9.9 & 13.7611 & -3.86111 \tabularnewline
31 & 11.5 & 12.5611 & -1.06114 \tabularnewline
32 & 8.3 & 11.9026 & -3.60259 \tabularnewline
33 & 11.7 & 13.7589 & -2.05888 \tabularnewline
34 & 6.1 & 12.943 & -6.84304 \tabularnewline
35 & 9 & 12.904 & -3.90405 \tabularnewline
36 & 9.7 & 14.772 & -5.07204 \tabularnewline
37 & 10.8 & 12.8346 & -2.03459 \tabularnewline
38 & 10.3 & 13.1225 & -2.82251 \tabularnewline
39 & 10.4 & 12.407 & -2.00703 \tabularnewline
40 & 12.7 & 12.8973 & -0.197251 \tabularnewline
41 & 9.3 & 15.2456 & -5.94562 \tabularnewline
42 & 11.8 & 13.7387 & -1.93865 \tabularnewline
43 & 5.9 & 13.3107 & -7.41071 \tabularnewline
44 & 11.4 & 14.2868 & -2.88683 \tabularnewline
45 & 13 & 14.2506 & -1.25056 \tabularnewline
46 & 10.8 & 13.0661 & -2.26609 \tabularnewline
47 & 12.3 & 11.4538 & 0.846225 \tabularnewline
48 & 11.3 & 14.8832 & -3.58321 \tabularnewline
49 & 11.8 & 13.147 & -1.347 \tabularnewline
50 & 7.9 & 12.9699 & -5.06989 \tabularnewline
51 & 12.7 & 11.7706 & 0.929353 \tabularnewline
52 & 12.3 & 12.2476 & 0.0523525 \tabularnewline
53 & 11.6 & 12.4948 & -0.894814 \tabularnewline
54 & 6.7 & 11.0425 & -4.34246 \tabularnewline
55 & 10.9 & 13.09 & -2.18998 \tabularnewline
56 & 12.1 & 12.7988 & -0.698753 \tabularnewline
57 & 13.3 & 13.5871 & -0.287139 \tabularnewline
58 & 10.1 & 12.7125 & -2.61249 \tabularnewline
59 & 5.7 & 12.1721 & -6.47212 \tabularnewline
60 & 14.3 & 12.95 & 1.34996 \tabularnewline
61 & 8 & 10.1572 & -2.1572 \tabularnewline
62 & 13.3 & 13.0243 & 0.275668 \tabularnewline
63 & 9.3 & 14.8981 & -5.59815 \tabularnewline
64 & 12.5 & 13.3998 & -0.899793 \tabularnewline
65 & 7.6 & 11.7978 & -4.19782 \tabularnewline
66 & 15.9 & 15.122 & 0.77795 \tabularnewline
67 & 9.2 & 14.2057 & -5.00571 \tabularnewline
68 & 9.1 & 11.8245 & -2.72451 \tabularnewline
69 & 11.1 & 14.9214 & -3.82137 \tabularnewline
70 & 13 & 15.8183 & -2.81827 \tabularnewline
71 & 14.5 & 14.314 & 0.18602 \tabularnewline
72 & 12.2 & 12.5668 & -0.366754 \tabularnewline
73 & 12.3 & 15.7745 & -3.47445 \tabularnewline
74 & 11.4 & 12.7784 & -1.37844 \tabularnewline
75 & 8.8 & 12.3886 & -3.58862 \tabularnewline
76 & 14.6 & 14.3273 & 0.272735 \tabularnewline
77 & 7.3 & 14.5447 & -7.24472 \tabularnewline
78 & 12.6 & 12.4361 & 0.163925 \tabularnewline
79 & NA & NA & -0.925255 \tabularnewline
80 & 13 & 13.4417 & -0.441745 \tabularnewline
81 & 12.6 & 13.4237 & -0.823672 \tabularnewline
82 & 13.2 & 14.7367 & -1.53668 \tabularnewline
83 & 9.9 & 15.1307 & -5.23075 \tabularnewline
84 & 7.7 & 9.77628 & -2.07628 \tabularnewline
85 & 10.5 & 8.78813 & 1.71187 \tabularnewline
86 & 13.4 & 14.7683 & -1.36833 \tabularnewline
87 & 10.9 & 18.2088 & -7.3088 \tabularnewline
88 & 4.3 & 7.05706 & -2.75706 \tabularnewline
89 & 10.3 & 12.104 & -1.80405 \tabularnewline
90 & 11.8 & 12.9616 & -1.16164 \tabularnewline
91 & 11.2 & 11.5181 & -0.318068 \tabularnewline
92 & 11.4 & 15.12 & -3.72002 \tabularnewline
93 & 8.6 & 7.72997 & 0.87003 \tabularnewline
94 & 13.2 & 12.4612 & 0.73883 \tabularnewline
95 & 12.6 & 19.0829 & -6.48291 \tabularnewline
96 & 5.6 & 8.61822 & -3.01822 \tabularnewline
97 & 9.9 & 13.0231 & -3.12313 \tabularnewline
98 & 8.8 & 13.3481 & -4.54813 \tabularnewline
99 & 7.7 & 10.6379 & -2.93794 \tabularnewline
100 & 9 & 14.7512 & -5.75124 \tabularnewline
101 & 7.3 & 7.86817 & -0.568166 \tabularnewline
102 & 11.4 & 9.74484 & 1.65516 \tabularnewline
103 & 13.6 & 18.5401 & -4.94009 \tabularnewline
104 & 7.9 & 8.80026 & -0.900264 \tabularnewline
105 & 10.7 & 12.2319 & -1.53187 \tabularnewline
106 & 10.3 & 13.0075 & -2.70748 \tabularnewline
107 & 8.3 & 11.4826 & -3.18264 \tabularnewline
108 & 9.6 & 7.72627 & 1.87373 \tabularnewline
109 & 14.2 & 18.1251 & -3.92515 \tabularnewline
110 & 8.5 & 7.13314 & 1.36686 \tabularnewline
111 & 13.5 & 19.9362 & -6.43617 \tabularnewline
112 & 4.9 & 9.42525 & -4.52525 \tabularnewline
113 & 6.4 & 9.31347 & -2.91347 \tabularnewline
114 & 9.6 & 10.3246 & -0.724639 \tabularnewline
115 & 11.6 & 12.349 & -0.749004 \tabularnewline
116 & 11.1 & 18.6042 & -7.50419 \tabularnewline
117 & 4.4 & 3.6527 & 0.747298 \tabularnewline
118 & 12.7 & 7.91255 & 4.78745 \tabularnewline
119 & 18.1 & 13.7015 & 4.39855 \tabularnewline
120 & 17.9 & 16.5283 & 1.37174 \tabularnewline
121 & 16.6 & 15.4732 & 1.12684 \tabularnewline
122 & 12.6 & 11.498 & 1.10205 \tabularnewline
123 & 17.1 & 13.4616 & 3.63841 \tabularnewline
124 & 19.1 & 19.7166 & -0.616571 \tabularnewline
125 & 16.1 & 13.7326 & 2.36735 \tabularnewline
126 & 13.4 & 9.45741 & 3.94259 \tabularnewline
127 & 18.4 & 14.1727 & 4.22733 \tabularnewline
128 & 14.7 & 16.8765 & -2.1765 \tabularnewline
129 & 10.6 & 9.92254 & 0.677463 \tabularnewline
130 & 12.6 & 9.38103 & 3.21897 \tabularnewline
131 & 16.2 & 17.358 & -1.15804 \tabularnewline
132 & 13.6 & 9.72655 & 3.87345 \tabularnewline
133 & 18.9 & 17.4874 & 1.41261 \tabularnewline
134 & 14.1 & 12.3115 & 1.78855 \tabularnewline
135 & 14.5 & 13.7745 & 0.725477 \tabularnewline
136 & 16.2 & 13.9235 & 2.27654 \tabularnewline
137 & 14.8 & 12.9362 & 1.86377 \tabularnewline
138 & 14.8 & 14.0282 & 0.771773 \tabularnewline
139 & 12.5 & 12.5731 & -0.0731446 \tabularnewline
140 & 12.7 & 8.01864 & 4.68136 \tabularnewline
141 & 17.4 & 19.2213 & -1.82131 \tabularnewline
142 & 8.6 & 4.01095 & 4.58905 \tabularnewline
143 & 18.4 & 16.9145 & 1.48553 \tabularnewline
144 & 16.1 & 16.1965 & -0.0964733 \tabularnewline
145 & 11.6 & 6.73041 & 4.86959 \tabularnewline
146 & 17.8 & 15.9173 & 1.88265 \tabularnewline
147 & 15.3 & 10.1096 & 5.19037 \tabularnewline
148 & 17.7 & 14.9175 & 2.78245 \tabularnewline
149 & 15.6 & 12.9369 & 2.66313 \tabularnewline
150 & 16.4 & 13.2499 & 3.15006 \tabularnewline
151 & 17.7 & 17.7621 & -0.0620881 \tabularnewline
152 & 13.6 & 14.4536 & -0.853567 \tabularnewline
153 & 11.7 & 10.249 & 1.45099 \tabularnewline
154 & 14.4 & 12.1596 & 2.24037 \tabularnewline
155 & 14.8 & 10.8976 & 3.90238 \tabularnewline
156 & 18.3 & 21.0878 & -2.78781 \tabularnewline
157 & 9.9 & 8.04132 & 1.85868 \tabularnewline
158 & 16 & 11.8067 & 4.19332 \tabularnewline
159 & 18.3 & 15.1648 & 3.13517 \tabularnewline
160 & 16.9 & 14.2604 & 2.63962 \tabularnewline
161 & 14.6 & 13.3033 & 1.29668 \tabularnewline
162 & 13.9 & 10.4245 & 3.47547 \tabularnewline
163 & 19 & 16.0921 & 2.90794 \tabularnewline
164 & 15.6 & 15.0577 & 0.542306 \tabularnewline
165 & 14.9 & 15.3588 & -0.458804 \tabularnewline
166 & 11.8 & 7.20677 & 4.59323 \tabularnewline
167 & 18.5 & 14.3846 & 4.1154 \tabularnewline
168 & 15.9 & 13.3231 & 2.5769 \tabularnewline
169 & 17.1 & 11.5016 & 5.5984 \tabularnewline
170 & 16.1 & 12.4884 & 3.61161 \tabularnewline
171 & 19.9 & 20.9087 & -1.00871 \tabularnewline
172 & 11 & 6.00959 & 4.99041 \tabularnewline
173 & 18.5 & 15.4593 & 3.04068 \tabularnewline
174 & 15.1 & 13.2848 & 1.81519 \tabularnewline
175 & 15 & 16.06 & -1.06 \tabularnewline
176 & 11.4 & 8.24709 & 3.15291 \tabularnewline
177 & 16 & 11.2693 & 4.73073 \tabularnewline
178 & 18.1 & 17.5292 & 0.570781 \tabularnewline
179 & 14.6 & 13.027 & 1.57297 \tabularnewline
180 & 15.4 & 13.7224 & 1.67759 \tabularnewline
181 & 15.4 & 10.3278 & 5.07219 \tabularnewline
182 & 17.6 & 17.9341 & -0.334132 \tabularnewline
183 & 13.4 & 7.60665 & 5.79335 \tabularnewline
184 & 19.1 & 17.3105 & 1.78946 \tabularnewline
185 & 15.4 & 18.9818 & -3.58182 \tabularnewline
186 & 7.6 & 8.21218 & -0.612185 \tabularnewline
187 & 13.4 & 12.6179 & 0.78207 \tabularnewline
188 & 13.9 & 8.86506 & 5.03494 \tabularnewline
189 & 19.1 & 16.1111 & 2.98885 \tabularnewline
190 & 15.3 & 15.1872 & 0.112848 \tabularnewline
191 & 12.9 & 10.3664 & 2.53358 \tabularnewline
192 & 16.1 & 11.3497 & 4.75031 \tabularnewline
193 & 17.4 & 17.1362 & 0.263829 \tabularnewline
194 & 13.2 & 13.8741 & -0.674072 \tabularnewline
195 & 12.2 & 10.7964 & 1.40364 \tabularnewline
196 & 12.6 & 14.1533 & -1.55335 \tabularnewline
197 & 10.4 & 6.82464 & 3.57536 \tabularnewline
198 & 15.4 & 17.3445 & -1.94452 \tabularnewline
199 & 9.6 & 3.9068 & 5.6932 \tabularnewline
200 & 18.2 & 16.7654 & 1.43458 \tabularnewline
201 & 13.6 & 12.3838 & 1.21625 \tabularnewline
202 & 14.9 & 13.7234 & 1.17659 \tabularnewline
203 & 14.8 & 12.5257 & 2.27425 \tabularnewline
204 & 14.1 & 11.3509 & 2.74908 \tabularnewline
205 & 14.9 & 11.765 & 3.13501 \tabularnewline
206 & 16.3 & 15.1108 & 1.18923 \tabularnewline
207 & 19.3 & 18.1467 & 1.15331 \tabularnewline
208 & 13.6 & 12.7637 & 0.83625 \tabularnewline
209 & 13.6 & 10.1982 & 3.40178 \tabularnewline
210 & 15.7 & 14.7065 & 0.993508 \tabularnewline
211 & 12.8 & 10.0343 & 2.76566 \tabularnewline
212 & 14.6 & 15.8321 & -1.2321 \tabularnewline
213 & 9.9 & 9.31265 & 0.58735 \tabularnewline
214 & 12.7 & 12.2523 & 0.447675 \tabularnewline
215 & 11.9 & 4.8573 & 7.0427 \tabularnewline
216 & 19.2 & 15.2126 & 3.9874 \tabularnewline
217 & 16.6 & 16.8475 & -0.247543 \tabularnewline
218 & 11.2 & 8.90529 & 2.29471 \tabularnewline
219 & 15.3 & 16.0301 & -0.730149 \tabularnewline
220 & 11.9 & 9.57081 & 2.32919 \tabularnewline
221 & 13.2 & 10.5991 & 2.60086 \tabularnewline
222 & 16.4 & 16.8019 & -0.401885 \tabularnewline
223 & 12.4 & 9.29452 & 3.10548 \tabularnewline
224 & 15.9 & 15.2556 & 0.64438 \tabularnewline
225 & 14.4 & 9.61431 & 4.78569 \tabularnewline
226 & 18.2 & 18.6393 & -0.439271 \tabularnewline
227 & 11.2 & 9.26606 & 1.93394 \tabularnewline
228 & 15.7 & 10.8115 & 4.88852 \tabularnewline
229 & 17.8 & 20.4104 & -2.61042 \tabularnewline
230 & 7.7 & 8.23854 & -0.53854 \tabularnewline
231 & 12.4 & 8.33967 & 4.06033 \tabularnewline
232 & 15.6 & 9.81642 & 5.78358 \tabularnewline
233 & 19.3 & 15.7198 & 3.58019 \tabularnewline
234 & 15.2 & 10.3449 & 4.85508 \tabularnewline
235 & 17.1 & 14.2369 & 2.86312 \tabularnewline
236 & 15.6 & 10.3976 & 5.20237 \tabularnewline
237 & 18.4 & 12.3704 & 6.02958 \tabularnewline
238 & 19.1 & 13.5835 & 5.51647 \tabularnewline
239 & 18.6 & 13.8443 & 4.7557 \tabularnewline
240 & 19.1 & 17.5511 & 1.54888 \tabularnewline
241 & 13.1 & 13.3385 & -0.238452 \tabularnewline
242 & 12.9 & 14.2792 & -1.37921 \tabularnewline
243 & 9.5 & 16.6004 & -7.10038 \tabularnewline
244 & 4.5 & 3.18699 & 1.31301 \tabularnewline
245 & 11.9 & 11.7984 & 0.101569 \tabularnewline
246 & 13.6 & 14.662 & -1.06203 \tabularnewline
247 & 11.7 & 11.1668 & 0.533218 \tabularnewline
248 & 12.4 & 11.7621 & 0.637858 \tabularnewline
249 & 13.4 & 12.6368 & 0.763205 \tabularnewline
250 & 11.4 & 9.36706 & 2.03294 \tabularnewline
251 & 14.9 & 10.7377 & 4.1623 \tabularnewline
252 & 19.9 & 15.1105 & 4.78954 \tabularnewline
253 & 17.8 & 19.5104 & -1.71035 \tabularnewline
254 & 11.2 & 9.1463 & 2.0537 \tabularnewline
255 & 14.6 & 10.8754 & 3.72464 \tabularnewline
256 & 17.6 & 16.735 & 0.864958 \tabularnewline
257 & 14.1 & 10.8948 & 3.20521 \tabularnewline
258 & 16.1 & 15.1926 & 0.907409 \tabularnewline
259 & 13.4 & 14.2175 & -0.817468 \tabularnewline
260 & 11.9 & 12.0753 & -0.17533 \tabularnewline
261 & 12 & 9.74481 & 2.25519 \tabularnewline
262 & 14.8 & 11.9168 & 2.88323 \tabularnewline
263 & 15.2 & 15.6128 & -0.41281 \tabularnewline
264 & 13.2 & 9.98526 & 3.21474 \tabularnewline
265 & 16.9 & 20.2967 & -3.39674 \tabularnewline
266 & 7.9 & 11.6799 & -3.77986 \tabularnewline
267 & 7.7 & 8.0126 & -0.312602 \tabularnewline
268 & 12.6 & 17.7962 & -5.19623 \tabularnewline
269 & 7.9 & 9.81176 & -1.91176 \tabularnewline
270 & 11 & 10.5757 & 0.424307 \tabularnewline
271 & 12.4 & 15.6523 & -3.25229 \tabularnewline
272 & 10 & 8.00155 & 1.99845 \tabularnewline
273 & 14.9 & 10.7393 & 4.16074 \tabularnewline
274 & 16.7 & 15.3896 & 1.31042 \tabularnewline
275 & 13.4 & 11.6878 & 1.71215 \tabularnewline
276 & 14 & 10.4012 & 3.59883 \tabularnewline
277 & 15.7 & 11.7897 & 3.91027 \tabularnewline
278 & 16.9 & 17.3186 & -0.418556 \tabularnewline
279 & 11 & 7.50915 & 3.49085 \tabularnewline
280 & 15.4 & 14.7676 & 0.63238 \tabularnewline
281 & 12.2 & 8.66561 & 3.53439 \tabularnewline
282 & 15.1 & 10.599 & 4.50101 \tabularnewline
283 & 17.8 & 15.4829 & 2.31706 \tabularnewline
284 & 15.2 & 14.0528 & 1.14716 \tabularnewline
285 & 14.6 & 10.7188 & 3.88117 \tabularnewline
286 & 16.7 & 19.3941 & -2.69405 \tabularnewline
287 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260190&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]14.3872[/C][C]-1.48717[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]13.3848[/C][C]-5.98482[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]13.5214[/C][C]-1.32144[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]13.9656[/C][C]-1.16562[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]14.0436[/C][C]-6.64356[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]13.5876[/C][C]-6.8876[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]15.2583[/C][C]-2.65834[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]13.7093[/C][C]1.09069[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]14.6604[/C][C]-1.3604[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]14.5874[/C][C]-3.48738[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]15.1127[/C][C]-6.91265[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]13.8806[/C][C]-2.4806[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]14.0663[/C][C]-7.66635[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]12.1998[/C][C]-1.59978[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]15.0341[/C][C]-3.03415[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]10.7533[/C][C]-4.45331[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]11.6782[/C][C]-0.378153[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]14.5643[/C][C]-2.66428[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]12.8342[/C][C]-3.5342[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]13.7864[/C][C]-4.18636[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]11.9983[/C][C]-1.99827[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]12.7359[/C][C]-6.33589[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]14.805[/C][C]-1.00504[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]14.5009[/C][C]-3.70088[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]14.5668[/C][C]-0.766779[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]14.2012[/C][C]-2.50124[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]15.0139[/C][C]-4.11392[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]16.2375[/C][C]-0.137491[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]12.6123[/C][C]0.787701[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]13.7611[/C][C]-3.86111[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]12.5611[/C][C]-1.06114[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]11.9026[/C][C]-3.60259[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]13.7589[/C][C]-2.05888[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]12.943[/C][C]-6.84304[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]12.904[/C][C]-3.90405[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]14.772[/C][C]-5.07204[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]12.8346[/C][C]-2.03459[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]13.1225[/C][C]-2.82251[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]12.407[/C][C]-2.00703[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]12.8973[/C][C]-0.197251[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]15.2456[/C][C]-5.94562[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]13.7387[/C][C]-1.93865[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]13.3107[/C][C]-7.41071[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]14.2868[/C][C]-2.88683[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]14.2506[/C][C]-1.25056[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]13.0661[/C][C]-2.26609[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]11.4538[/C][C]0.846225[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]14.8832[/C][C]-3.58321[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]13.147[/C][C]-1.347[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]12.9699[/C][C]-5.06989[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]11.7706[/C][C]0.929353[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]12.2476[/C][C]0.0523525[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]12.4948[/C][C]-0.894814[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]11.0425[/C][C]-4.34246[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]13.09[/C][C]-2.18998[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]12.7988[/C][C]-0.698753[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]13.5871[/C][C]-0.287139[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]12.7125[/C][C]-2.61249[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]12.1721[/C][C]-6.47212[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]12.95[/C][C]1.34996[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.1572[/C][C]-2.1572[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]13.0243[/C][C]0.275668[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]14.8981[/C][C]-5.59815[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]13.3998[/C][C]-0.899793[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]11.7978[/C][C]-4.19782[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]15.122[/C][C]0.77795[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]14.2057[/C][C]-5.00571[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]11.8245[/C][C]-2.72451[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]14.9214[/C][C]-3.82137[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]15.8183[/C][C]-2.81827[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]14.314[/C][C]0.18602[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]12.5668[/C][C]-0.366754[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]15.7745[/C][C]-3.47445[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]12.7784[/C][C]-1.37844[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]12.3886[/C][C]-3.58862[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]14.3273[/C][C]0.272735[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]14.5447[/C][C]-7.24472[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]12.4361[/C][C]0.163925[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]-0.925255[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]13.4417[/C][C]-0.441745[/C][/ROW]
[ROW][C]81[/C][C]12.6[/C][C]13.4237[/C][C]-0.823672[/C][/ROW]
[ROW][C]82[/C][C]13.2[/C][C]14.7367[/C][C]-1.53668[/C][/ROW]
[ROW][C]83[/C][C]9.9[/C][C]15.1307[/C][C]-5.23075[/C][/ROW]
[ROW][C]84[/C][C]7.7[/C][C]9.77628[/C][C]-2.07628[/C][/ROW]
[ROW][C]85[/C][C]10.5[/C][C]8.78813[/C][C]1.71187[/C][/ROW]
[ROW][C]86[/C][C]13.4[/C][C]14.7683[/C][C]-1.36833[/C][/ROW]
[ROW][C]87[/C][C]10.9[/C][C]18.2088[/C][C]-7.3088[/C][/ROW]
[ROW][C]88[/C][C]4.3[/C][C]7.05706[/C][C]-2.75706[/C][/ROW]
[ROW][C]89[/C][C]10.3[/C][C]12.104[/C][C]-1.80405[/C][/ROW]
[ROW][C]90[/C][C]11.8[/C][C]12.9616[/C][C]-1.16164[/C][/ROW]
[ROW][C]91[/C][C]11.2[/C][C]11.5181[/C][C]-0.318068[/C][/ROW]
[ROW][C]92[/C][C]11.4[/C][C]15.12[/C][C]-3.72002[/C][/ROW]
[ROW][C]93[/C][C]8.6[/C][C]7.72997[/C][C]0.87003[/C][/ROW]
[ROW][C]94[/C][C]13.2[/C][C]12.4612[/C][C]0.73883[/C][/ROW]
[ROW][C]95[/C][C]12.6[/C][C]19.0829[/C][C]-6.48291[/C][/ROW]
[ROW][C]96[/C][C]5.6[/C][C]8.61822[/C][C]-3.01822[/C][/ROW]
[ROW][C]97[/C][C]9.9[/C][C]13.0231[/C][C]-3.12313[/C][/ROW]
[ROW][C]98[/C][C]8.8[/C][C]13.3481[/C][C]-4.54813[/C][/ROW]
[ROW][C]99[/C][C]7.7[/C][C]10.6379[/C][C]-2.93794[/C][/ROW]
[ROW][C]100[/C][C]9[/C][C]14.7512[/C][C]-5.75124[/C][/ROW]
[ROW][C]101[/C][C]7.3[/C][C]7.86817[/C][C]-0.568166[/C][/ROW]
[ROW][C]102[/C][C]11.4[/C][C]9.74484[/C][C]1.65516[/C][/ROW]
[ROW][C]103[/C][C]13.6[/C][C]18.5401[/C][C]-4.94009[/C][/ROW]
[ROW][C]104[/C][C]7.9[/C][C]8.80026[/C][C]-0.900264[/C][/ROW]
[ROW][C]105[/C][C]10.7[/C][C]12.2319[/C][C]-1.53187[/C][/ROW]
[ROW][C]106[/C][C]10.3[/C][C]13.0075[/C][C]-2.70748[/C][/ROW]
[ROW][C]107[/C][C]8.3[/C][C]11.4826[/C][C]-3.18264[/C][/ROW]
[ROW][C]108[/C][C]9.6[/C][C]7.72627[/C][C]1.87373[/C][/ROW]
[ROW][C]109[/C][C]14.2[/C][C]18.1251[/C][C]-3.92515[/C][/ROW]
[ROW][C]110[/C][C]8.5[/C][C]7.13314[/C][C]1.36686[/C][/ROW]
[ROW][C]111[/C][C]13.5[/C][C]19.9362[/C][C]-6.43617[/C][/ROW]
[ROW][C]112[/C][C]4.9[/C][C]9.42525[/C][C]-4.52525[/C][/ROW]
[ROW][C]113[/C][C]6.4[/C][C]9.31347[/C][C]-2.91347[/C][/ROW]
[ROW][C]114[/C][C]9.6[/C][C]10.3246[/C][C]-0.724639[/C][/ROW]
[ROW][C]115[/C][C]11.6[/C][C]12.349[/C][C]-0.749004[/C][/ROW]
[ROW][C]116[/C][C]11.1[/C][C]18.6042[/C][C]-7.50419[/C][/ROW]
[ROW][C]117[/C][C]4.4[/C][C]3.6527[/C][C]0.747298[/C][/ROW]
[ROW][C]118[/C][C]12.7[/C][C]7.91255[/C][C]4.78745[/C][/ROW]
[ROW][C]119[/C][C]18.1[/C][C]13.7015[/C][C]4.39855[/C][/ROW]
[ROW][C]120[/C][C]17.9[/C][C]16.5283[/C][C]1.37174[/C][/ROW]
[ROW][C]121[/C][C]16.6[/C][C]15.4732[/C][C]1.12684[/C][/ROW]
[ROW][C]122[/C][C]12.6[/C][C]11.498[/C][C]1.10205[/C][/ROW]
[ROW][C]123[/C][C]17.1[/C][C]13.4616[/C][C]3.63841[/C][/ROW]
[ROW][C]124[/C][C]19.1[/C][C]19.7166[/C][C]-0.616571[/C][/ROW]
[ROW][C]125[/C][C]16.1[/C][C]13.7326[/C][C]2.36735[/C][/ROW]
[ROW][C]126[/C][C]13.4[/C][C]9.45741[/C][C]3.94259[/C][/ROW]
[ROW][C]127[/C][C]18.4[/C][C]14.1727[/C][C]4.22733[/C][/ROW]
[ROW][C]128[/C][C]14.7[/C][C]16.8765[/C][C]-2.1765[/C][/ROW]
[ROW][C]129[/C][C]10.6[/C][C]9.92254[/C][C]0.677463[/C][/ROW]
[ROW][C]130[/C][C]12.6[/C][C]9.38103[/C][C]3.21897[/C][/ROW]
[ROW][C]131[/C][C]16.2[/C][C]17.358[/C][C]-1.15804[/C][/ROW]
[ROW][C]132[/C][C]13.6[/C][C]9.72655[/C][C]3.87345[/C][/ROW]
[ROW][C]133[/C][C]18.9[/C][C]17.4874[/C][C]1.41261[/C][/ROW]
[ROW][C]134[/C][C]14.1[/C][C]12.3115[/C][C]1.78855[/C][/ROW]
[ROW][C]135[/C][C]14.5[/C][C]13.7745[/C][C]0.725477[/C][/ROW]
[ROW][C]136[/C][C]16.2[/C][C]13.9235[/C][C]2.27654[/C][/ROW]
[ROW][C]137[/C][C]14.8[/C][C]12.9362[/C][C]1.86377[/C][/ROW]
[ROW][C]138[/C][C]14.8[/C][C]14.0282[/C][C]0.771773[/C][/ROW]
[ROW][C]139[/C][C]12.5[/C][C]12.5731[/C][C]-0.0731446[/C][/ROW]
[ROW][C]140[/C][C]12.7[/C][C]8.01864[/C][C]4.68136[/C][/ROW]
[ROW][C]141[/C][C]17.4[/C][C]19.2213[/C][C]-1.82131[/C][/ROW]
[ROW][C]142[/C][C]8.6[/C][C]4.01095[/C][C]4.58905[/C][/ROW]
[ROW][C]143[/C][C]18.4[/C][C]16.9145[/C][C]1.48553[/C][/ROW]
[ROW][C]144[/C][C]16.1[/C][C]16.1965[/C][C]-0.0964733[/C][/ROW]
[ROW][C]145[/C][C]11.6[/C][C]6.73041[/C][C]4.86959[/C][/ROW]
[ROW][C]146[/C][C]17.8[/C][C]15.9173[/C][C]1.88265[/C][/ROW]
[ROW][C]147[/C][C]15.3[/C][C]10.1096[/C][C]5.19037[/C][/ROW]
[ROW][C]148[/C][C]17.7[/C][C]14.9175[/C][C]2.78245[/C][/ROW]
[ROW][C]149[/C][C]15.6[/C][C]12.9369[/C][C]2.66313[/C][/ROW]
[ROW][C]150[/C][C]16.4[/C][C]13.2499[/C][C]3.15006[/C][/ROW]
[ROW][C]151[/C][C]17.7[/C][C]17.7621[/C][C]-0.0620881[/C][/ROW]
[ROW][C]152[/C][C]13.6[/C][C]14.4536[/C][C]-0.853567[/C][/ROW]
[ROW][C]153[/C][C]11.7[/C][C]10.249[/C][C]1.45099[/C][/ROW]
[ROW][C]154[/C][C]14.4[/C][C]12.1596[/C][C]2.24037[/C][/ROW]
[ROW][C]155[/C][C]14.8[/C][C]10.8976[/C][C]3.90238[/C][/ROW]
[ROW][C]156[/C][C]18.3[/C][C]21.0878[/C][C]-2.78781[/C][/ROW]
[ROW][C]157[/C][C]9.9[/C][C]8.04132[/C][C]1.85868[/C][/ROW]
[ROW][C]158[/C][C]16[/C][C]11.8067[/C][C]4.19332[/C][/ROW]
[ROW][C]159[/C][C]18.3[/C][C]15.1648[/C][C]3.13517[/C][/ROW]
[ROW][C]160[/C][C]16.9[/C][C]14.2604[/C][C]2.63962[/C][/ROW]
[ROW][C]161[/C][C]14.6[/C][C]13.3033[/C][C]1.29668[/C][/ROW]
[ROW][C]162[/C][C]13.9[/C][C]10.4245[/C][C]3.47547[/C][/ROW]
[ROW][C]163[/C][C]19[/C][C]16.0921[/C][C]2.90794[/C][/ROW]
[ROW][C]164[/C][C]15.6[/C][C]15.0577[/C][C]0.542306[/C][/ROW]
[ROW][C]165[/C][C]14.9[/C][C]15.3588[/C][C]-0.458804[/C][/ROW]
[ROW][C]166[/C][C]11.8[/C][C]7.20677[/C][C]4.59323[/C][/ROW]
[ROW][C]167[/C][C]18.5[/C][C]14.3846[/C][C]4.1154[/C][/ROW]
[ROW][C]168[/C][C]15.9[/C][C]13.3231[/C][C]2.5769[/C][/ROW]
[ROW][C]169[/C][C]17.1[/C][C]11.5016[/C][C]5.5984[/C][/ROW]
[ROW][C]170[/C][C]16.1[/C][C]12.4884[/C][C]3.61161[/C][/ROW]
[ROW][C]171[/C][C]19.9[/C][C]20.9087[/C][C]-1.00871[/C][/ROW]
[ROW][C]172[/C][C]11[/C][C]6.00959[/C][C]4.99041[/C][/ROW]
[ROW][C]173[/C][C]18.5[/C][C]15.4593[/C][C]3.04068[/C][/ROW]
[ROW][C]174[/C][C]15.1[/C][C]13.2848[/C][C]1.81519[/C][/ROW]
[ROW][C]175[/C][C]15[/C][C]16.06[/C][C]-1.06[/C][/ROW]
[ROW][C]176[/C][C]11.4[/C][C]8.24709[/C][C]3.15291[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]11.2693[/C][C]4.73073[/C][/ROW]
[ROW][C]178[/C][C]18.1[/C][C]17.5292[/C][C]0.570781[/C][/ROW]
[ROW][C]179[/C][C]14.6[/C][C]13.027[/C][C]1.57297[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]13.7224[/C][C]1.67759[/C][/ROW]
[ROW][C]181[/C][C]15.4[/C][C]10.3278[/C][C]5.07219[/C][/ROW]
[ROW][C]182[/C][C]17.6[/C][C]17.9341[/C][C]-0.334132[/C][/ROW]
[ROW][C]183[/C][C]13.4[/C][C]7.60665[/C][C]5.79335[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]17.3105[/C][C]1.78946[/C][/ROW]
[ROW][C]185[/C][C]15.4[/C][C]18.9818[/C][C]-3.58182[/C][/ROW]
[ROW][C]186[/C][C]7.6[/C][C]8.21218[/C][C]-0.612185[/C][/ROW]
[ROW][C]187[/C][C]13.4[/C][C]12.6179[/C][C]0.78207[/C][/ROW]
[ROW][C]188[/C][C]13.9[/C][C]8.86506[/C][C]5.03494[/C][/ROW]
[ROW][C]189[/C][C]19.1[/C][C]16.1111[/C][C]2.98885[/C][/ROW]
[ROW][C]190[/C][C]15.3[/C][C]15.1872[/C][C]0.112848[/C][/ROW]
[ROW][C]191[/C][C]12.9[/C][C]10.3664[/C][C]2.53358[/C][/ROW]
[ROW][C]192[/C][C]16.1[/C][C]11.3497[/C][C]4.75031[/C][/ROW]
[ROW][C]193[/C][C]17.4[/C][C]17.1362[/C][C]0.263829[/C][/ROW]
[ROW][C]194[/C][C]13.2[/C][C]13.8741[/C][C]-0.674072[/C][/ROW]
[ROW][C]195[/C][C]12.2[/C][C]10.7964[/C][C]1.40364[/C][/ROW]
[ROW][C]196[/C][C]12.6[/C][C]14.1533[/C][C]-1.55335[/C][/ROW]
[ROW][C]197[/C][C]10.4[/C][C]6.82464[/C][C]3.57536[/C][/ROW]
[ROW][C]198[/C][C]15.4[/C][C]17.3445[/C][C]-1.94452[/C][/ROW]
[ROW][C]199[/C][C]9.6[/C][C]3.9068[/C][C]5.6932[/C][/ROW]
[ROW][C]200[/C][C]18.2[/C][C]16.7654[/C][C]1.43458[/C][/ROW]
[ROW][C]201[/C][C]13.6[/C][C]12.3838[/C][C]1.21625[/C][/ROW]
[ROW][C]202[/C][C]14.9[/C][C]13.7234[/C][C]1.17659[/C][/ROW]
[ROW][C]203[/C][C]14.8[/C][C]12.5257[/C][C]2.27425[/C][/ROW]
[ROW][C]204[/C][C]14.1[/C][C]11.3509[/C][C]2.74908[/C][/ROW]
[ROW][C]205[/C][C]14.9[/C][C]11.765[/C][C]3.13501[/C][/ROW]
[ROW][C]206[/C][C]16.3[/C][C]15.1108[/C][C]1.18923[/C][/ROW]
[ROW][C]207[/C][C]19.3[/C][C]18.1467[/C][C]1.15331[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]12.7637[/C][C]0.83625[/C][/ROW]
[ROW][C]209[/C][C]13.6[/C][C]10.1982[/C][C]3.40178[/C][/ROW]
[ROW][C]210[/C][C]15.7[/C][C]14.7065[/C][C]0.993508[/C][/ROW]
[ROW][C]211[/C][C]12.8[/C][C]10.0343[/C][C]2.76566[/C][/ROW]
[ROW][C]212[/C][C]14.6[/C][C]15.8321[/C][C]-1.2321[/C][/ROW]
[ROW][C]213[/C][C]9.9[/C][C]9.31265[/C][C]0.58735[/C][/ROW]
[ROW][C]214[/C][C]12.7[/C][C]12.2523[/C][C]0.447675[/C][/ROW]
[ROW][C]215[/C][C]11.9[/C][C]4.8573[/C][C]7.0427[/C][/ROW]
[ROW][C]216[/C][C]19.2[/C][C]15.2126[/C][C]3.9874[/C][/ROW]
[ROW][C]217[/C][C]16.6[/C][C]16.8475[/C][C]-0.247543[/C][/ROW]
[ROW][C]218[/C][C]11.2[/C][C]8.90529[/C][C]2.29471[/C][/ROW]
[ROW][C]219[/C][C]15.3[/C][C]16.0301[/C][C]-0.730149[/C][/ROW]
[ROW][C]220[/C][C]11.9[/C][C]9.57081[/C][C]2.32919[/C][/ROW]
[ROW][C]221[/C][C]13.2[/C][C]10.5991[/C][C]2.60086[/C][/ROW]
[ROW][C]222[/C][C]16.4[/C][C]16.8019[/C][C]-0.401885[/C][/ROW]
[ROW][C]223[/C][C]12.4[/C][C]9.29452[/C][C]3.10548[/C][/ROW]
[ROW][C]224[/C][C]15.9[/C][C]15.2556[/C][C]0.64438[/C][/ROW]
[ROW][C]225[/C][C]14.4[/C][C]9.61431[/C][C]4.78569[/C][/ROW]
[ROW][C]226[/C][C]18.2[/C][C]18.6393[/C][C]-0.439271[/C][/ROW]
[ROW][C]227[/C][C]11.2[/C][C]9.26606[/C][C]1.93394[/C][/ROW]
[ROW][C]228[/C][C]15.7[/C][C]10.8115[/C][C]4.88852[/C][/ROW]
[ROW][C]229[/C][C]17.8[/C][C]20.4104[/C][C]-2.61042[/C][/ROW]
[ROW][C]230[/C][C]7.7[/C][C]8.23854[/C][C]-0.53854[/C][/ROW]
[ROW][C]231[/C][C]12.4[/C][C]8.33967[/C][C]4.06033[/C][/ROW]
[ROW][C]232[/C][C]15.6[/C][C]9.81642[/C][C]5.78358[/C][/ROW]
[ROW][C]233[/C][C]19.3[/C][C]15.7198[/C][C]3.58019[/C][/ROW]
[ROW][C]234[/C][C]15.2[/C][C]10.3449[/C][C]4.85508[/C][/ROW]
[ROW][C]235[/C][C]17.1[/C][C]14.2369[/C][C]2.86312[/C][/ROW]
[ROW][C]236[/C][C]15.6[/C][C]10.3976[/C][C]5.20237[/C][/ROW]
[ROW][C]237[/C][C]18.4[/C][C]12.3704[/C][C]6.02958[/C][/ROW]
[ROW][C]238[/C][C]19.1[/C][C]13.5835[/C][C]5.51647[/C][/ROW]
[ROW][C]239[/C][C]18.6[/C][C]13.8443[/C][C]4.7557[/C][/ROW]
[ROW][C]240[/C][C]19.1[/C][C]17.5511[/C][C]1.54888[/C][/ROW]
[ROW][C]241[/C][C]13.1[/C][C]13.3385[/C][C]-0.238452[/C][/ROW]
[ROW][C]242[/C][C]12.9[/C][C]14.2792[/C][C]-1.37921[/C][/ROW]
[ROW][C]243[/C][C]9.5[/C][C]16.6004[/C][C]-7.10038[/C][/ROW]
[ROW][C]244[/C][C]4.5[/C][C]3.18699[/C][C]1.31301[/C][/ROW]
[ROW][C]245[/C][C]11.9[/C][C]11.7984[/C][C]0.101569[/C][/ROW]
[ROW][C]246[/C][C]13.6[/C][C]14.662[/C][C]-1.06203[/C][/ROW]
[ROW][C]247[/C][C]11.7[/C][C]11.1668[/C][C]0.533218[/C][/ROW]
[ROW][C]248[/C][C]12.4[/C][C]11.7621[/C][C]0.637858[/C][/ROW]
[ROW][C]249[/C][C]13.4[/C][C]12.6368[/C][C]0.763205[/C][/ROW]
[ROW][C]250[/C][C]11.4[/C][C]9.36706[/C][C]2.03294[/C][/ROW]
[ROW][C]251[/C][C]14.9[/C][C]10.7377[/C][C]4.1623[/C][/ROW]
[ROW][C]252[/C][C]19.9[/C][C]15.1105[/C][C]4.78954[/C][/ROW]
[ROW][C]253[/C][C]17.8[/C][C]19.5104[/C][C]-1.71035[/C][/ROW]
[ROW][C]254[/C][C]11.2[/C][C]9.1463[/C][C]2.0537[/C][/ROW]
[ROW][C]255[/C][C]14.6[/C][C]10.8754[/C][C]3.72464[/C][/ROW]
[ROW][C]256[/C][C]17.6[/C][C]16.735[/C][C]0.864958[/C][/ROW]
[ROW][C]257[/C][C]14.1[/C][C]10.8948[/C][C]3.20521[/C][/ROW]
[ROW][C]258[/C][C]16.1[/C][C]15.1926[/C][C]0.907409[/C][/ROW]
[ROW][C]259[/C][C]13.4[/C][C]14.2175[/C][C]-0.817468[/C][/ROW]
[ROW][C]260[/C][C]11.9[/C][C]12.0753[/C][C]-0.17533[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]9.74481[/C][C]2.25519[/C][/ROW]
[ROW][C]262[/C][C]14.8[/C][C]11.9168[/C][C]2.88323[/C][/ROW]
[ROW][C]263[/C][C]15.2[/C][C]15.6128[/C][C]-0.41281[/C][/ROW]
[ROW][C]264[/C][C]13.2[/C][C]9.98526[/C][C]3.21474[/C][/ROW]
[ROW][C]265[/C][C]16.9[/C][C]20.2967[/C][C]-3.39674[/C][/ROW]
[ROW][C]266[/C][C]7.9[/C][C]11.6799[/C][C]-3.77986[/C][/ROW]
[ROW][C]267[/C][C]7.7[/C][C]8.0126[/C][C]-0.312602[/C][/ROW]
[ROW][C]268[/C][C]12.6[/C][C]17.7962[/C][C]-5.19623[/C][/ROW]
[ROW][C]269[/C][C]7.9[/C][C]9.81176[/C][C]-1.91176[/C][/ROW]
[ROW][C]270[/C][C]11[/C][C]10.5757[/C][C]0.424307[/C][/ROW]
[ROW][C]271[/C][C]12.4[/C][C]15.6523[/C][C]-3.25229[/C][/ROW]
[ROW][C]272[/C][C]10[/C][C]8.00155[/C][C]1.99845[/C][/ROW]
[ROW][C]273[/C][C]14.9[/C][C]10.7393[/C][C]4.16074[/C][/ROW]
[ROW][C]274[/C][C]16.7[/C][C]15.3896[/C][C]1.31042[/C][/ROW]
[ROW][C]275[/C][C]13.4[/C][C]11.6878[/C][C]1.71215[/C][/ROW]
[ROW][C]276[/C][C]14[/C][C]10.4012[/C][C]3.59883[/C][/ROW]
[ROW][C]277[/C][C]15.7[/C][C]11.7897[/C][C]3.91027[/C][/ROW]
[ROW][C]278[/C][C]16.9[/C][C]17.3186[/C][C]-0.418556[/C][/ROW]
[ROW][C]279[/C][C]11[/C][C]7.50915[/C][C]3.49085[/C][/ROW]
[ROW][C]280[/C][C]15.4[/C][C]14.7676[/C][C]0.63238[/C][/ROW]
[ROW][C]281[/C][C]12.2[/C][C]8.66561[/C][C]3.53439[/C][/ROW]
[ROW][C]282[/C][C]15.1[/C][C]10.599[/C][C]4.50101[/C][/ROW]
[ROW][C]283[/C][C]17.8[/C][C]15.4829[/C][C]2.31706[/C][/ROW]
[ROW][C]284[/C][C]15.2[/C][C]14.0528[/C][C]1.14716[/C][/ROW]
[ROW][C]285[/C][C]14.6[/C][C]10.7188[/C][C]3.88117[/C][/ROW]
[ROW][C]286[/C][C]16.7[/C][C]19.3941[/C][C]-2.69405[/C][/ROW]
[ROW][C]287[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260190&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260190&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.3872-1.48717
27.413.3848-5.98482
312.213.5214-1.32144
412.813.9656-1.16562
57.414.0436-6.64356
66.713.5876-6.8876
712.615.2583-2.65834
814.813.70931.09069
913.314.6604-1.3604
1011.114.5874-3.48738
118.215.1127-6.91265
1211.413.8806-2.4806
136.414.0663-7.66635
1410.612.1998-1.59978
151215.0341-3.03415
166.310.7533-4.45331
1711.311.6782-0.378153
1811.914.5643-2.66428
199.312.8342-3.5342
209.613.7864-4.18636
211011.9983-1.99827
226.412.7359-6.33589
2313.814.805-1.00504
2410.814.5009-3.70088
2513.814.5668-0.766779
2611.714.2012-2.50124
2710.915.0139-4.11392
2816.116.2375-0.137491
2913.412.61230.787701
309.913.7611-3.86111
3111.512.5611-1.06114
328.311.9026-3.60259
3311.713.7589-2.05888
346.112.943-6.84304
35912.904-3.90405
369.714.772-5.07204
3710.812.8346-2.03459
3810.313.1225-2.82251
3910.412.407-2.00703
4012.712.8973-0.197251
419.315.2456-5.94562
4211.813.7387-1.93865
435.913.3107-7.41071
4411.414.2868-2.88683
451314.2506-1.25056
4610.813.0661-2.26609
4712.311.45380.846225
4811.314.8832-3.58321
4911.813.147-1.347
507.912.9699-5.06989
5112.711.77060.929353
5212.312.24760.0523525
5311.612.4948-0.894814
546.711.0425-4.34246
5510.913.09-2.18998
5612.112.7988-0.698753
5713.313.5871-0.287139
5810.112.7125-2.61249
595.712.1721-6.47212
6014.312.951.34996
61810.1572-2.1572
6213.313.02430.275668
639.314.8981-5.59815
6412.513.3998-0.899793
657.611.7978-4.19782
6615.915.1220.77795
679.214.2057-5.00571
689.111.8245-2.72451
6911.114.9214-3.82137
701315.8183-2.81827
7114.514.3140.18602
7212.212.5668-0.366754
7312.315.7745-3.47445
7411.412.7784-1.37844
758.812.3886-3.58862
7614.614.32730.272735
777.314.5447-7.24472
7812.612.43610.163925
79NANA-0.925255
801313.4417-0.441745
8112.613.4237-0.823672
8213.214.7367-1.53668
839.915.1307-5.23075
847.79.77628-2.07628
8510.58.788131.71187
8613.414.7683-1.36833
8710.918.2088-7.3088
884.37.05706-2.75706
8910.312.104-1.80405
9011.812.9616-1.16164
9111.211.5181-0.318068
9211.415.12-3.72002
938.67.729970.87003
9413.212.46120.73883
9512.619.0829-6.48291
965.68.61822-3.01822
979.913.0231-3.12313
988.813.3481-4.54813
997.710.6379-2.93794
100914.7512-5.75124
1017.37.86817-0.568166
10211.49.744841.65516
10313.618.5401-4.94009
1047.98.80026-0.900264
10510.712.2319-1.53187
10610.313.0075-2.70748
1078.311.4826-3.18264
1089.67.726271.87373
10914.218.1251-3.92515
1108.57.133141.36686
11113.519.9362-6.43617
1124.99.42525-4.52525
1136.49.31347-2.91347
1149.610.3246-0.724639
11511.612.349-0.749004
11611.118.6042-7.50419
1174.43.65270.747298
11812.77.912554.78745
11918.113.70154.39855
12017.916.52831.37174
12116.615.47321.12684
12212.611.4981.10205
12317.113.46163.63841
12419.119.7166-0.616571
12516.113.73262.36735
12613.49.457413.94259
12718.414.17274.22733
12814.716.8765-2.1765
12910.69.922540.677463
13012.69.381033.21897
13116.217.358-1.15804
13213.69.726553.87345
13318.917.48741.41261
13414.112.31151.78855
13514.513.77450.725477
13616.213.92352.27654
13714.812.93621.86377
13814.814.02820.771773
13912.512.5731-0.0731446
14012.78.018644.68136
14117.419.2213-1.82131
1428.64.010954.58905
14318.416.91451.48553
14416.116.1965-0.0964733
14511.66.730414.86959
14617.815.91731.88265
14715.310.10965.19037
14817.714.91752.78245
14915.612.93692.66313
15016.413.24993.15006
15117.717.7621-0.0620881
15213.614.4536-0.853567
15311.710.2491.45099
15414.412.15962.24037
15514.810.89763.90238
15618.321.0878-2.78781
1579.98.041321.85868
1581611.80674.19332
15918.315.16483.13517
16016.914.26042.63962
16114.613.30331.29668
16213.910.42453.47547
1631916.09212.90794
16415.615.05770.542306
16514.915.3588-0.458804
16611.87.206774.59323
16718.514.38464.1154
16815.913.32312.5769
16917.111.50165.5984
17016.112.48843.61161
17119.920.9087-1.00871
172116.009594.99041
17318.515.45933.04068
17415.113.28481.81519
1751516.06-1.06
17611.48.247093.15291
1771611.26934.73073
17818.117.52920.570781
17914.613.0271.57297
18015.413.72241.67759
18115.410.32785.07219
18217.617.9341-0.334132
18313.47.606655.79335
18419.117.31051.78946
18515.418.9818-3.58182
1867.68.21218-0.612185
18713.412.61790.78207
18813.98.865065.03494
18919.116.11112.98885
19015.315.18720.112848
19112.910.36642.53358
19216.111.34974.75031
19317.417.13620.263829
19413.213.8741-0.674072
19512.210.79641.40364
19612.614.1533-1.55335
19710.46.824643.57536
19815.417.3445-1.94452
1999.63.90685.6932
20018.216.76541.43458
20113.612.38381.21625
20214.913.72341.17659
20314.812.52572.27425
20414.111.35092.74908
20514.911.7653.13501
20616.315.11081.18923
20719.318.14671.15331
20813.612.76370.83625
20913.610.19823.40178
21015.714.70650.993508
21112.810.03432.76566
21214.615.8321-1.2321
2139.99.312650.58735
21412.712.25230.447675
21511.94.85737.0427
21619.215.21263.9874
21716.616.8475-0.247543
21811.28.905292.29471
21915.316.0301-0.730149
22011.99.570812.32919
22113.210.59912.60086
22216.416.8019-0.401885
22312.49.294523.10548
22415.915.25560.64438
22514.49.614314.78569
22618.218.6393-0.439271
22711.29.266061.93394
22815.710.81154.88852
22917.820.4104-2.61042
2307.78.23854-0.53854
23112.48.339674.06033
23215.69.816425.78358
23319.315.71983.58019
23415.210.34494.85508
23517.114.23692.86312
23615.610.39765.20237
23718.412.37046.02958
23819.113.58355.51647
23918.613.84434.7557
24019.117.55111.54888
24113.113.3385-0.238452
24212.914.2792-1.37921
2439.516.6004-7.10038
2444.53.186991.31301
24511.911.79840.101569
24613.614.662-1.06203
24711.711.16680.533218
24812.411.76210.637858
24913.412.63680.763205
25011.49.367062.03294
25114.910.73774.1623
25219.915.11054.78954
25317.819.5104-1.71035
25411.29.14632.0537
25514.610.87543.72464
25617.616.7350.864958
25714.110.89483.20521
25816.115.19260.907409
25913.414.2175-0.817468
26011.912.0753-0.17533
261129.744812.25519
26214.811.91682.88323
26315.215.6128-0.41281
26413.29.985263.21474
26516.920.2967-3.39674
2667.911.6799-3.77986
2677.78.0126-0.312602
26812.617.7962-5.19623
2697.99.81176-1.91176
2701110.57570.424307
27112.415.6523-3.25229
272108.001551.99845
27314.910.73934.16074
27416.715.38961.31042
27513.411.68781.71215
2761410.40123.59883
27715.711.78973.91027
27816.917.3186-0.418556
279117.509153.49085
28015.414.76760.63238
28112.28.665613.53439
28215.110.5994.50101
28317.815.48292.31706
28415.214.05281.14716
28514.610.71883.88117
28616.719.3941-2.69405
2878.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.7248890.5502220.275111
100.6027240.7945530.397276
110.5433620.9132760.456638
120.4208520.8417040.579148
130.3762030.7524060.623797
140.2943640.5887280.705636
150.2315020.4630030.768498
160.1647920.3295840.835208
170.1657070.3314150.834293
180.1269730.2539460.873027
190.08789690.1757940.912103
200.05948520.118970.940515
210.04401910.08803810.955981
220.03991720.07983450.960083
230.03602070.07204130.963979
240.02672620.05345240.973274
250.02137320.04274630.978627
260.01614140.03228290.983859
270.01180770.02361550.988192
280.007362690.01472540.992637
290.01089110.02178230.989109
300.007427830.01485570.992572
310.005150510.0103010.994849
320.0120430.02408590.987957
330.01029990.02059980.9897
340.02469840.04939690.975302
350.01832870.03665740.981671
360.03109670.06219340.968903
370.02252610.04505230.977474
380.01635010.03270010.98365
390.0130890.0261780.986911
400.01417360.02834720.985826
410.01531120.03062230.984689
420.01130970.02261930.98869
430.02280610.04561210.977194
440.01770610.03541210.982294
450.01519640.03039270.984804
460.01141370.02282750.988586
470.009190790.01838160.990809
480.007858390.01571680.992142
490.005894340.01178870.994106
500.007497090.01499420.992503
510.01061620.02123230.989384
520.01075530.02151060.989245
530.008665330.01733070.991335
540.008902050.01780410.991098
550.00717040.01434080.99283
560.008107870.01621570.991892
570.00863030.01726060.99137
580.006700490.0134010.9933
590.01573610.03147210.984264
600.02082130.04164250.979179
610.01631010.03262020.98369
620.01715860.03431720.982841
630.02001240.04002470.979988
640.01950080.03900150.980499
650.02161310.04322610.978387
660.02706420.05412840.972936
670.0299360.0598720.970064
680.02460580.04921160.975394
690.02541830.05083660.974582
700.02526050.05052110.974739
710.02631430.05262860.973686
720.0220690.0441380.977931
730.02213910.04427830.977861
740.01928460.03856920.980715
750.01667510.03335010.983325
760.01881550.03763090.981185
770.05186440.1037290.948136
780.04493190.08986380.955068
790.04041910.08083820.959581
800.03692310.07384610.963077
810.03823320.07646640.961767
820.03201680.06403360.967983
830.04384870.08769740.956151
840.03793040.07586080.96207
850.04309550.08619090.956905
860.03655960.07311920.96344
870.07915310.1583060.920847
880.07806080.1561220.921939
890.07086540.1417310.929135
900.06120910.1224180.938791
910.05509830.1101970.944902
920.05470170.1094030.945298
930.05931340.1186270.940687
940.06261390.1252280.937386
950.1205810.2411620.879419
960.1233920.2467850.876608
970.1224980.2449950.877502
980.1385990.2771980.861401
990.1396790.2793570.860321
1000.1998880.3997760.800112
1010.1981740.3963470.801826
1020.2341520.4683050.765848
1030.303190.6063810.69681
1040.2822060.5644120.717794
1050.2717250.5434490.728275
1060.2804640.5609290.719536
1070.3081280.6162560.691872
1080.3384050.676810.661595
1090.3772450.7544890.622755
1100.3836380.7672750.616362
1110.582980.834040.41702
1120.6197410.7605190.380259
1130.6277540.7444920.372246
1140.6297510.7404980.370249
1150.6232360.7535280.376764
1160.7789760.4420490.221024
1170.7680260.4639480.231974
1180.8761850.2476310.123815
1190.9367670.1264670.0632333
1200.9405010.1189980.0594988
1210.9438010.1123970.0561987
1220.9522550.09549050.0477452
1230.9665060.06698890.0334945
1240.9666730.06665370.0333268
1250.9728730.05425320.0271266
1260.9831750.03365070.0168254
1270.9923570.0152850.00764252
1280.9926370.01472640.0073632
1290.9920940.01581140.00790572
1300.9937960.01240720.00620358
1310.9935780.01284310.00642153
1320.9952950.009410220.00470511
1330.9950780.009844340.00492217
1340.9951950.00960990.00480495
1350.9955040.008992820.00449641
1360.9955370.008925790.0044629
1370.9953050.009389350.00469468
1380.9943730.01125360.0056268
1390.9932360.01352780.00676388
1400.9965220.006955240.00347762
1410.995770.008460650.00423032
1420.9973110.005378860.00268943
1430.9969450.006110190.00305509
1440.9961250.007749470.00387474
1450.9978370.004326870.00216343
1460.9978330.004334020.00216701
1470.9988290.002341280.00117064
1480.9989120.002176950.00108847
1490.9989130.002173090.00108654
1500.9989710.002057520.00102876
1510.9987880.002424280.00121214
1520.9987030.00259330.00129665
1530.9984430.003113430.00155671
1540.9982310.003538810.00176941
1550.9985250.00294940.0014747
1560.999430.001139140.000569572
1570.9993230.001353580.00067679
1580.9994580.001084810.000542407
1590.999420.001159510.000579754
1600.9994720.001056250.000528126
1610.999340.001320330.000660166
1620.9993390.001321140.000660572
1630.999310.001379540.000689769
1640.9991240.001751360.00087568
1650.9989010.002198450.00109923
1660.9991720.001655340.000827669
1670.9993990.001201780.000600891
1680.9993090.001382830.000691413
1690.9999320.0001362736.81363e-05
1700.999920.0001608858.04427e-05
1710.9998890.0002213380.000110669
1720.9999210.0001587537.93766e-05
1730.9999240.0001519757.59877e-05
1740.99990.0001998019.99006e-05
1750.9998780.0002443420.000122171
1760.999870.0002609070.000130454
1770.9999040.0001912639.56316e-05
1780.9998870.0002267290.000113364
1790.9998510.0002976010.000148801
1800.9998070.0003857070.000192854
1810.9998690.0002626780.000131339
1820.9998380.000324670.000162335
1830.9998970.000206930.000103465
1840.9998660.000267990.000133995
1850.9998890.0002229160.000111458
1860.9998640.0002727410.00013637
1870.9998140.0003712660.000185633
1880.9998320.0003351970.000167599
1890.9998060.0003889260.000194463
1900.999770.0004594860.000229743
1910.9997080.0005834290.000291714
1920.9998120.0003769440.000188472
1930.999750.0005006920.000250346
1940.9997010.0005973910.000298695
1950.9996090.0007818720.000390936
1960.9994860.001027510.000513755
1970.999460.001079470.000539737
1980.9993240.001352530.000676265
1990.9996290.0007429650.000371483
2000.9995090.0009815970.000490799
2010.9993910.001217050.000608527
2020.9993070.001385770.000692886
2030.9991290.001742240.000871118
2040.9990170.001965920.00098296
2050.9988870.002226590.0011133
2060.9986980.002603720.00130186
2070.9985360.002928970.00146448
2080.9982320.00353510.00176755
2090.9979490.004102890.00205144
2100.9974920.005015460.00250773
2110.9973670.005265750.00263288
2120.9964820.007035160.00351758
2130.9959820.008035230.00401762
2140.9946520.01069640.00534821
2150.9968660.006268250.00313412
2160.9967270.006546210.00327311
2170.995630.008739520.00436976
2180.9945350.01092970.00546484
2190.9944920.01101690.00550845
2200.9936030.01279490.00639747
2210.9923940.01521270.00760636
2220.9902810.01943850.00971924
2230.9893830.02123420.0106171
2240.987610.02477930.0123896
2250.986060.02788010.0139401
2260.9815370.03692570.0184628
2270.9762130.04757450.0237872
2280.974210.05157960.0257898
2290.9707830.0584350.0292175
2300.9643960.07120780.0356039
2310.9626030.07479410.037397
2320.9630320.07393640.0369682
2330.9744840.0510310.0255155
2340.9777330.04453320.0222666
2350.9733090.0533820.026691
2360.9745220.05095630.0254782
2370.9808640.03827270.0191363
2380.980610.03878090.0193905
2390.9786150.04277050.0213853
2400.9720560.0558870.0279435
2410.9724260.05514870.0275744
2420.9664310.06713810.0335691
2430.9904920.01901520.00950759
2440.9885620.02287650.0114382
2450.9892880.02142450.0107123
2460.9847180.03056440.0152822
2470.9785770.04284610.021423
2480.9719710.05605870.0280294
2490.9630340.0739330.0369665
2500.9507220.09855670.0492783
2510.9370080.1259840.0629921
2520.9438570.1122860.056143
2530.9332680.1334640.0667318
2540.9117640.1764730.0882364
2550.8944190.2111630.105581
2560.8625340.2749320.137466
2570.8357550.3284890.164245
2580.7935060.4129880.206494
2590.7847630.4304750.215237
2600.7354880.5290240.264512
2610.6901230.6197540.309877
2620.775030.4499410.22497
2630.7806310.4387380.219369
2640.7388830.5222330.261117
2650.7384750.5230510.261525
2660.9408330.1183340.0591671
2670.9135160.1729680.086484
2680.9893750.02125010.0106251
2690.9799130.04017320.0200866
2700.9725840.05483110.0274155
2710.99860.002800680.00140034
2720.9973310.005337180.00266859
2730.9952260.009548140.00477407
2740.9913790.01724290.00862144
2750.9933330.01333310.00666653
2760.9948210.01035710.00517853
2770.9895110.02097860.0104893
2780.9510990.09780130.0489007

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.724889 & 0.550222 & 0.275111 \tabularnewline
10 & 0.602724 & 0.794553 & 0.397276 \tabularnewline
11 & 0.543362 & 0.913276 & 0.456638 \tabularnewline
12 & 0.420852 & 0.841704 & 0.579148 \tabularnewline
13 & 0.376203 & 0.752406 & 0.623797 \tabularnewline
14 & 0.294364 & 0.588728 & 0.705636 \tabularnewline
15 & 0.231502 & 0.463003 & 0.768498 \tabularnewline
16 & 0.164792 & 0.329584 & 0.835208 \tabularnewline
17 & 0.165707 & 0.331415 & 0.834293 \tabularnewline
18 & 0.126973 & 0.253946 & 0.873027 \tabularnewline
19 & 0.0878969 & 0.175794 & 0.912103 \tabularnewline
20 & 0.0594852 & 0.11897 & 0.940515 \tabularnewline
21 & 0.0440191 & 0.0880381 & 0.955981 \tabularnewline
22 & 0.0399172 & 0.0798345 & 0.960083 \tabularnewline
23 & 0.0360207 & 0.0720413 & 0.963979 \tabularnewline
24 & 0.0267262 & 0.0534524 & 0.973274 \tabularnewline
25 & 0.0213732 & 0.0427463 & 0.978627 \tabularnewline
26 & 0.0161414 & 0.0322829 & 0.983859 \tabularnewline
27 & 0.0118077 & 0.0236155 & 0.988192 \tabularnewline
28 & 0.00736269 & 0.0147254 & 0.992637 \tabularnewline
29 & 0.0108911 & 0.0217823 & 0.989109 \tabularnewline
30 & 0.00742783 & 0.0148557 & 0.992572 \tabularnewline
31 & 0.00515051 & 0.010301 & 0.994849 \tabularnewline
32 & 0.012043 & 0.0240859 & 0.987957 \tabularnewline
33 & 0.0102999 & 0.0205998 & 0.9897 \tabularnewline
34 & 0.0246984 & 0.0493969 & 0.975302 \tabularnewline
35 & 0.0183287 & 0.0366574 & 0.981671 \tabularnewline
36 & 0.0310967 & 0.0621934 & 0.968903 \tabularnewline
37 & 0.0225261 & 0.0450523 & 0.977474 \tabularnewline
38 & 0.0163501 & 0.0327001 & 0.98365 \tabularnewline
39 & 0.013089 & 0.026178 & 0.986911 \tabularnewline
40 & 0.0141736 & 0.0283472 & 0.985826 \tabularnewline
41 & 0.0153112 & 0.0306223 & 0.984689 \tabularnewline
42 & 0.0113097 & 0.0226193 & 0.98869 \tabularnewline
43 & 0.0228061 & 0.0456121 & 0.977194 \tabularnewline
44 & 0.0177061 & 0.0354121 & 0.982294 \tabularnewline
45 & 0.0151964 & 0.0303927 & 0.984804 \tabularnewline
46 & 0.0114137 & 0.0228275 & 0.988586 \tabularnewline
47 & 0.00919079 & 0.0183816 & 0.990809 \tabularnewline
48 & 0.00785839 & 0.0157168 & 0.992142 \tabularnewline
49 & 0.00589434 & 0.0117887 & 0.994106 \tabularnewline
50 & 0.00749709 & 0.0149942 & 0.992503 \tabularnewline
51 & 0.0106162 & 0.0212323 & 0.989384 \tabularnewline
52 & 0.0107553 & 0.0215106 & 0.989245 \tabularnewline
53 & 0.00866533 & 0.0173307 & 0.991335 \tabularnewline
54 & 0.00890205 & 0.0178041 & 0.991098 \tabularnewline
55 & 0.0071704 & 0.0143408 & 0.99283 \tabularnewline
56 & 0.00810787 & 0.0162157 & 0.991892 \tabularnewline
57 & 0.0086303 & 0.0172606 & 0.99137 \tabularnewline
58 & 0.00670049 & 0.013401 & 0.9933 \tabularnewline
59 & 0.0157361 & 0.0314721 & 0.984264 \tabularnewline
60 & 0.0208213 & 0.0416425 & 0.979179 \tabularnewline
61 & 0.0163101 & 0.0326202 & 0.98369 \tabularnewline
62 & 0.0171586 & 0.0343172 & 0.982841 \tabularnewline
63 & 0.0200124 & 0.0400247 & 0.979988 \tabularnewline
64 & 0.0195008 & 0.0390015 & 0.980499 \tabularnewline
65 & 0.0216131 & 0.0432261 & 0.978387 \tabularnewline
66 & 0.0270642 & 0.0541284 & 0.972936 \tabularnewline
67 & 0.029936 & 0.059872 & 0.970064 \tabularnewline
68 & 0.0246058 & 0.0492116 & 0.975394 \tabularnewline
69 & 0.0254183 & 0.0508366 & 0.974582 \tabularnewline
70 & 0.0252605 & 0.0505211 & 0.974739 \tabularnewline
71 & 0.0263143 & 0.0526286 & 0.973686 \tabularnewline
72 & 0.022069 & 0.044138 & 0.977931 \tabularnewline
73 & 0.0221391 & 0.0442783 & 0.977861 \tabularnewline
74 & 0.0192846 & 0.0385692 & 0.980715 \tabularnewline
75 & 0.0166751 & 0.0333501 & 0.983325 \tabularnewline
76 & 0.0188155 & 0.0376309 & 0.981185 \tabularnewline
77 & 0.0518644 & 0.103729 & 0.948136 \tabularnewline
78 & 0.0449319 & 0.0898638 & 0.955068 \tabularnewline
79 & 0.0404191 & 0.0808382 & 0.959581 \tabularnewline
80 & 0.0369231 & 0.0738461 & 0.963077 \tabularnewline
81 & 0.0382332 & 0.0764664 & 0.961767 \tabularnewline
82 & 0.0320168 & 0.0640336 & 0.967983 \tabularnewline
83 & 0.0438487 & 0.0876974 & 0.956151 \tabularnewline
84 & 0.0379304 & 0.0758608 & 0.96207 \tabularnewline
85 & 0.0430955 & 0.0861909 & 0.956905 \tabularnewline
86 & 0.0365596 & 0.0731192 & 0.96344 \tabularnewline
87 & 0.0791531 & 0.158306 & 0.920847 \tabularnewline
88 & 0.0780608 & 0.156122 & 0.921939 \tabularnewline
89 & 0.0708654 & 0.141731 & 0.929135 \tabularnewline
90 & 0.0612091 & 0.122418 & 0.938791 \tabularnewline
91 & 0.0550983 & 0.110197 & 0.944902 \tabularnewline
92 & 0.0547017 & 0.109403 & 0.945298 \tabularnewline
93 & 0.0593134 & 0.118627 & 0.940687 \tabularnewline
94 & 0.0626139 & 0.125228 & 0.937386 \tabularnewline
95 & 0.120581 & 0.241162 & 0.879419 \tabularnewline
96 & 0.123392 & 0.246785 & 0.876608 \tabularnewline
97 & 0.122498 & 0.244995 & 0.877502 \tabularnewline
98 & 0.138599 & 0.277198 & 0.861401 \tabularnewline
99 & 0.139679 & 0.279357 & 0.860321 \tabularnewline
100 & 0.199888 & 0.399776 & 0.800112 \tabularnewline
101 & 0.198174 & 0.396347 & 0.801826 \tabularnewline
102 & 0.234152 & 0.468305 & 0.765848 \tabularnewline
103 & 0.30319 & 0.606381 & 0.69681 \tabularnewline
104 & 0.282206 & 0.564412 & 0.717794 \tabularnewline
105 & 0.271725 & 0.543449 & 0.728275 \tabularnewline
106 & 0.280464 & 0.560929 & 0.719536 \tabularnewline
107 & 0.308128 & 0.616256 & 0.691872 \tabularnewline
108 & 0.338405 & 0.67681 & 0.661595 \tabularnewline
109 & 0.377245 & 0.754489 & 0.622755 \tabularnewline
110 & 0.383638 & 0.767275 & 0.616362 \tabularnewline
111 & 0.58298 & 0.83404 & 0.41702 \tabularnewline
112 & 0.619741 & 0.760519 & 0.380259 \tabularnewline
113 & 0.627754 & 0.744492 & 0.372246 \tabularnewline
114 & 0.629751 & 0.740498 & 0.370249 \tabularnewline
115 & 0.623236 & 0.753528 & 0.376764 \tabularnewline
116 & 0.778976 & 0.442049 & 0.221024 \tabularnewline
117 & 0.768026 & 0.463948 & 0.231974 \tabularnewline
118 & 0.876185 & 0.247631 & 0.123815 \tabularnewline
119 & 0.936767 & 0.126467 & 0.0632333 \tabularnewline
120 & 0.940501 & 0.118998 & 0.0594988 \tabularnewline
121 & 0.943801 & 0.112397 & 0.0561987 \tabularnewline
122 & 0.952255 & 0.0954905 & 0.0477452 \tabularnewline
123 & 0.966506 & 0.0669889 & 0.0334945 \tabularnewline
124 & 0.966673 & 0.0666537 & 0.0333268 \tabularnewline
125 & 0.972873 & 0.0542532 & 0.0271266 \tabularnewline
126 & 0.983175 & 0.0336507 & 0.0168254 \tabularnewline
127 & 0.992357 & 0.015285 & 0.00764252 \tabularnewline
128 & 0.992637 & 0.0147264 & 0.0073632 \tabularnewline
129 & 0.992094 & 0.0158114 & 0.00790572 \tabularnewline
130 & 0.993796 & 0.0124072 & 0.00620358 \tabularnewline
131 & 0.993578 & 0.0128431 & 0.00642153 \tabularnewline
132 & 0.995295 & 0.00941022 & 0.00470511 \tabularnewline
133 & 0.995078 & 0.00984434 & 0.00492217 \tabularnewline
134 & 0.995195 & 0.0096099 & 0.00480495 \tabularnewline
135 & 0.995504 & 0.00899282 & 0.00449641 \tabularnewline
136 & 0.995537 & 0.00892579 & 0.0044629 \tabularnewline
137 & 0.995305 & 0.00938935 & 0.00469468 \tabularnewline
138 & 0.994373 & 0.0112536 & 0.0056268 \tabularnewline
139 & 0.993236 & 0.0135278 & 0.00676388 \tabularnewline
140 & 0.996522 & 0.00695524 & 0.00347762 \tabularnewline
141 & 0.99577 & 0.00846065 & 0.00423032 \tabularnewline
142 & 0.997311 & 0.00537886 & 0.00268943 \tabularnewline
143 & 0.996945 & 0.00611019 & 0.00305509 \tabularnewline
144 & 0.996125 & 0.00774947 & 0.00387474 \tabularnewline
145 & 0.997837 & 0.00432687 & 0.00216343 \tabularnewline
146 & 0.997833 & 0.00433402 & 0.00216701 \tabularnewline
147 & 0.998829 & 0.00234128 & 0.00117064 \tabularnewline
148 & 0.998912 & 0.00217695 & 0.00108847 \tabularnewline
149 & 0.998913 & 0.00217309 & 0.00108654 \tabularnewline
150 & 0.998971 & 0.00205752 & 0.00102876 \tabularnewline
151 & 0.998788 & 0.00242428 & 0.00121214 \tabularnewline
152 & 0.998703 & 0.0025933 & 0.00129665 \tabularnewline
153 & 0.998443 & 0.00311343 & 0.00155671 \tabularnewline
154 & 0.998231 & 0.00353881 & 0.00176941 \tabularnewline
155 & 0.998525 & 0.0029494 & 0.0014747 \tabularnewline
156 & 0.99943 & 0.00113914 & 0.000569572 \tabularnewline
157 & 0.999323 & 0.00135358 & 0.00067679 \tabularnewline
158 & 0.999458 & 0.00108481 & 0.000542407 \tabularnewline
159 & 0.99942 & 0.00115951 & 0.000579754 \tabularnewline
160 & 0.999472 & 0.00105625 & 0.000528126 \tabularnewline
161 & 0.99934 & 0.00132033 & 0.000660166 \tabularnewline
162 & 0.999339 & 0.00132114 & 0.000660572 \tabularnewline
163 & 0.99931 & 0.00137954 & 0.000689769 \tabularnewline
164 & 0.999124 & 0.00175136 & 0.00087568 \tabularnewline
165 & 0.998901 & 0.00219845 & 0.00109923 \tabularnewline
166 & 0.999172 & 0.00165534 & 0.000827669 \tabularnewline
167 & 0.999399 & 0.00120178 & 0.000600891 \tabularnewline
168 & 0.999309 & 0.00138283 & 0.000691413 \tabularnewline
169 & 0.999932 & 0.000136273 & 6.81363e-05 \tabularnewline
170 & 0.99992 & 0.000160885 & 8.04427e-05 \tabularnewline
171 & 0.999889 & 0.000221338 & 0.000110669 \tabularnewline
172 & 0.999921 & 0.000158753 & 7.93766e-05 \tabularnewline
173 & 0.999924 & 0.000151975 & 7.59877e-05 \tabularnewline
174 & 0.9999 & 0.000199801 & 9.99006e-05 \tabularnewline
175 & 0.999878 & 0.000244342 & 0.000122171 \tabularnewline
176 & 0.99987 & 0.000260907 & 0.000130454 \tabularnewline
177 & 0.999904 & 0.000191263 & 9.56316e-05 \tabularnewline
178 & 0.999887 & 0.000226729 & 0.000113364 \tabularnewline
179 & 0.999851 & 0.000297601 & 0.000148801 \tabularnewline
180 & 0.999807 & 0.000385707 & 0.000192854 \tabularnewline
181 & 0.999869 & 0.000262678 & 0.000131339 \tabularnewline
182 & 0.999838 & 0.00032467 & 0.000162335 \tabularnewline
183 & 0.999897 & 0.00020693 & 0.000103465 \tabularnewline
184 & 0.999866 & 0.00026799 & 0.000133995 \tabularnewline
185 & 0.999889 & 0.000222916 & 0.000111458 \tabularnewline
186 & 0.999864 & 0.000272741 & 0.00013637 \tabularnewline
187 & 0.999814 & 0.000371266 & 0.000185633 \tabularnewline
188 & 0.999832 & 0.000335197 & 0.000167599 \tabularnewline
189 & 0.999806 & 0.000388926 & 0.000194463 \tabularnewline
190 & 0.99977 & 0.000459486 & 0.000229743 \tabularnewline
191 & 0.999708 & 0.000583429 & 0.000291714 \tabularnewline
192 & 0.999812 & 0.000376944 & 0.000188472 \tabularnewline
193 & 0.99975 & 0.000500692 & 0.000250346 \tabularnewline
194 & 0.999701 & 0.000597391 & 0.000298695 \tabularnewline
195 & 0.999609 & 0.000781872 & 0.000390936 \tabularnewline
196 & 0.999486 & 0.00102751 & 0.000513755 \tabularnewline
197 & 0.99946 & 0.00107947 & 0.000539737 \tabularnewline
198 & 0.999324 & 0.00135253 & 0.000676265 \tabularnewline
199 & 0.999629 & 0.000742965 & 0.000371483 \tabularnewline
200 & 0.999509 & 0.000981597 & 0.000490799 \tabularnewline
201 & 0.999391 & 0.00121705 & 0.000608527 \tabularnewline
202 & 0.999307 & 0.00138577 & 0.000692886 \tabularnewline
203 & 0.999129 & 0.00174224 & 0.000871118 \tabularnewline
204 & 0.999017 & 0.00196592 & 0.00098296 \tabularnewline
205 & 0.998887 & 0.00222659 & 0.0011133 \tabularnewline
206 & 0.998698 & 0.00260372 & 0.00130186 \tabularnewline
207 & 0.998536 & 0.00292897 & 0.00146448 \tabularnewline
208 & 0.998232 & 0.0035351 & 0.00176755 \tabularnewline
209 & 0.997949 & 0.00410289 & 0.00205144 \tabularnewline
210 & 0.997492 & 0.00501546 & 0.00250773 \tabularnewline
211 & 0.997367 & 0.00526575 & 0.00263288 \tabularnewline
212 & 0.996482 & 0.00703516 & 0.00351758 \tabularnewline
213 & 0.995982 & 0.00803523 & 0.00401762 \tabularnewline
214 & 0.994652 & 0.0106964 & 0.00534821 \tabularnewline
215 & 0.996866 & 0.00626825 & 0.00313412 \tabularnewline
216 & 0.996727 & 0.00654621 & 0.00327311 \tabularnewline
217 & 0.99563 & 0.00873952 & 0.00436976 \tabularnewline
218 & 0.994535 & 0.0109297 & 0.00546484 \tabularnewline
219 & 0.994492 & 0.0110169 & 0.00550845 \tabularnewline
220 & 0.993603 & 0.0127949 & 0.00639747 \tabularnewline
221 & 0.992394 & 0.0152127 & 0.00760636 \tabularnewline
222 & 0.990281 & 0.0194385 & 0.00971924 \tabularnewline
223 & 0.989383 & 0.0212342 & 0.0106171 \tabularnewline
224 & 0.98761 & 0.0247793 & 0.0123896 \tabularnewline
225 & 0.98606 & 0.0278801 & 0.0139401 \tabularnewline
226 & 0.981537 & 0.0369257 & 0.0184628 \tabularnewline
227 & 0.976213 & 0.0475745 & 0.0237872 \tabularnewline
228 & 0.97421 & 0.0515796 & 0.0257898 \tabularnewline
229 & 0.970783 & 0.058435 & 0.0292175 \tabularnewline
230 & 0.964396 & 0.0712078 & 0.0356039 \tabularnewline
231 & 0.962603 & 0.0747941 & 0.037397 \tabularnewline
232 & 0.963032 & 0.0739364 & 0.0369682 \tabularnewline
233 & 0.974484 & 0.051031 & 0.0255155 \tabularnewline
234 & 0.977733 & 0.0445332 & 0.0222666 \tabularnewline
235 & 0.973309 & 0.053382 & 0.026691 \tabularnewline
236 & 0.974522 & 0.0509563 & 0.0254782 \tabularnewline
237 & 0.980864 & 0.0382727 & 0.0191363 \tabularnewline
238 & 0.98061 & 0.0387809 & 0.0193905 \tabularnewline
239 & 0.978615 & 0.0427705 & 0.0213853 \tabularnewline
240 & 0.972056 & 0.055887 & 0.0279435 \tabularnewline
241 & 0.972426 & 0.0551487 & 0.0275744 \tabularnewline
242 & 0.966431 & 0.0671381 & 0.0335691 \tabularnewline
243 & 0.990492 & 0.0190152 & 0.00950759 \tabularnewline
244 & 0.988562 & 0.0228765 & 0.0114382 \tabularnewline
245 & 0.989288 & 0.0214245 & 0.0107123 \tabularnewline
246 & 0.984718 & 0.0305644 & 0.0152822 \tabularnewline
247 & 0.978577 & 0.0428461 & 0.021423 \tabularnewline
248 & 0.971971 & 0.0560587 & 0.0280294 \tabularnewline
249 & 0.963034 & 0.073933 & 0.0369665 \tabularnewline
250 & 0.950722 & 0.0985567 & 0.0492783 \tabularnewline
251 & 0.937008 & 0.125984 & 0.0629921 \tabularnewline
252 & 0.943857 & 0.112286 & 0.056143 \tabularnewline
253 & 0.933268 & 0.133464 & 0.0667318 \tabularnewline
254 & 0.911764 & 0.176473 & 0.0882364 \tabularnewline
255 & 0.894419 & 0.211163 & 0.105581 \tabularnewline
256 & 0.862534 & 0.274932 & 0.137466 \tabularnewline
257 & 0.835755 & 0.328489 & 0.164245 \tabularnewline
258 & 0.793506 & 0.412988 & 0.206494 \tabularnewline
259 & 0.784763 & 0.430475 & 0.215237 \tabularnewline
260 & 0.735488 & 0.529024 & 0.264512 \tabularnewline
261 & 0.690123 & 0.619754 & 0.309877 \tabularnewline
262 & 0.77503 & 0.449941 & 0.22497 \tabularnewline
263 & 0.780631 & 0.438738 & 0.219369 \tabularnewline
264 & 0.738883 & 0.522233 & 0.261117 \tabularnewline
265 & 0.738475 & 0.523051 & 0.261525 \tabularnewline
266 & 0.940833 & 0.118334 & 0.0591671 \tabularnewline
267 & 0.913516 & 0.172968 & 0.086484 \tabularnewline
268 & 0.989375 & 0.0212501 & 0.0106251 \tabularnewline
269 & 0.979913 & 0.0401732 & 0.0200866 \tabularnewline
270 & 0.972584 & 0.0548311 & 0.0274155 \tabularnewline
271 & 0.9986 & 0.00280068 & 0.00140034 \tabularnewline
272 & 0.997331 & 0.00533718 & 0.00266859 \tabularnewline
273 & 0.995226 & 0.00954814 & 0.00477407 \tabularnewline
274 & 0.991379 & 0.0172429 & 0.00862144 \tabularnewline
275 & 0.993333 & 0.0133331 & 0.00666653 \tabularnewline
276 & 0.994821 & 0.0103571 & 0.00517853 \tabularnewline
277 & 0.989511 & 0.0209786 & 0.0104893 \tabularnewline
278 & 0.951099 & 0.0978013 & 0.0489007 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260190&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]9[/C][C]0.724889[/C][C]0.550222[/C][C]0.275111[/C][/ROW]
[ROW][C]10[/C][C]0.602724[/C][C]0.794553[/C][C]0.397276[/C][/ROW]
[ROW][C]11[/C][C]0.543362[/C][C]0.913276[/C][C]0.456638[/C][/ROW]
[ROW][C]12[/C][C]0.420852[/C][C]0.841704[/C][C]0.579148[/C][/ROW]
[ROW][C]13[/C][C]0.376203[/C][C]0.752406[/C][C]0.623797[/C][/ROW]
[ROW][C]14[/C][C]0.294364[/C][C]0.588728[/C][C]0.705636[/C][/ROW]
[ROW][C]15[/C][C]0.231502[/C][C]0.463003[/C][C]0.768498[/C][/ROW]
[ROW][C]16[/C][C]0.164792[/C][C]0.329584[/C][C]0.835208[/C][/ROW]
[ROW][C]17[/C][C]0.165707[/C][C]0.331415[/C][C]0.834293[/C][/ROW]
[ROW][C]18[/C][C]0.126973[/C][C]0.253946[/C][C]0.873027[/C][/ROW]
[ROW][C]19[/C][C]0.0878969[/C][C]0.175794[/C][C]0.912103[/C][/ROW]
[ROW][C]20[/C][C]0.0594852[/C][C]0.11897[/C][C]0.940515[/C][/ROW]
[ROW][C]21[/C][C]0.0440191[/C][C]0.0880381[/C][C]0.955981[/C][/ROW]
[ROW][C]22[/C][C]0.0399172[/C][C]0.0798345[/C][C]0.960083[/C][/ROW]
[ROW][C]23[/C][C]0.0360207[/C][C]0.0720413[/C][C]0.963979[/C][/ROW]
[ROW][C]24[/C][C]0.0267262[/C][C]0.0534524[/C][C]0.973274[/C][/ROW]
[ROW][C]25[/C][C]0.0213732[/C][C]0.0427463[/C][C]0.978627[/C][/ROW]
[ROW][C]26[/C][C]0.0161414[/C][C]0.0322829[/C][C]0.983859[/C][/ROW]
[ROW][C]27[/C][C]0.0118077[/C][C]0.0236155[/C][C]0.988192[/C][/ROW]
[ROW][C]28[/C][C]0.00736269[/C][C]0.0147254[/C][C]0.992637[/C][/ROW]
[ROW][C]29[/C][C]0.0108911[/C][C]0.0217823[/C][C]0.989109[/C][/ROW]
[ROW][C]30[/C][C]0.00742783[/C][C]0.0148557[/C][C]0.992572[/C][/ROW]
[ROW][C]31[/C][C]0.00515051[/C][C]0.010301[/C][C]0.994849[/C][/ROW]
[ROW][C]32[/C][C]0.012043[/C][C]0.0240859[/C][C]0.987957[/C][/ROW]
[ROW][C]33[/C][C]0.0102999[/C][C]0.0205998[/C][C]0.9897[/C][/ROW]
[ROW][C]34[/C][C]0.0246984[/C][C]0.0493969[/C][C]0.975302[/C][/ROW]
[ROW][C]35[/C][C]0.0183287[/C][C]0.0366574[/C][C]0.981671[/C][/ROW]
[ROW][C]36[/C][C]0.0310967[/C][C]0.0621934[/C][C]0.968903[/C][/ROW]
[ROW][C]37[/C][C]0.0225261[/C][C]0.0450523[/C][C]0.977474[/C][/ROW]
[ROW][C]38[/C][C]0.0163501[/C][C]0.0327001[/C][C]0.98365[/C][/ROW]
[ROW][C]39[/C][C]0.013089[/C][C]0.026178[/C][C]0.986911[/C][/ROW]
[ROW][C]40[/C][C]0.0141736[/C][C]0.0283472[/C][C]0.985826[/C][/ROW]
[ROW][C]41[/C][C]0.0153112[/C][C]0.0306223[/C][C]0.984689[/C][/ROW]
[ROW][C]42[/C][C]0.0113097[/C][C]0.0226193[/C][C]0.98869[/C][/ROW]
[ROW][C]43[/C][C]0.0228061[/C][C]0.0456121[/C][C]0.977194[/C][/ROW]
[ROW][C]44[/C][C]0.0177061[/C][C]0.0354121[/C][C]0.982294[/C][/ROW]
[ROW][C]45[/C][C]0.0151964[/C][C]0.0303927[/C][C]0.984804[/C][/ROW]
[ROW][C]46[/C][C]0.0114137[/C][C]0.0228275[/C][C]0.988586[/C][/ROW]
[ROW][C]47[/C][C]0.00919079[/C][C]0.0183816[/C][C]0.990809[/C][/ROW]
[ROW][C]48[/C][C]0.00785839[/C][C]0.0157168[/C][C]0.992142[/C][/ROW]
[ROW][C]49[/C][C]0.00589434[/C][C]0.0117887[/C][C]0.994106[/C][/ROW]
[ROW][C]50[/C][C]0.00749709[/C][C]0.0149942[/C][C]0.992503[/C][/ROW]
[ROW][C]51[/C][C]0.0106162[/C][C]0.0212323[/C][C]0.989384[/C][/ROW]
[ROW][C]52[/C][C]0.0107553[/C][C]0.0215106[/C][C]0.989245[/C][/ROW]
[ROW][C]53[/C][C]0.00866533[/C][C]0.0173307[/C][C]0.991335[/C][/ROW]
[ROW][C]54[/C][C]0.00890205[/C][C]0.0178041[/C][C]0.991098[/C][/ROW]
[ROW][C]55[/C][C]0.0071704[/C][C]0.0143408[/C][C]0.99283[/C][/ROW]
[ROW][C]56[/C][C]0.00810787[/C][C]0.0162157[/C][C]0.991892[/C][/ROW]
[ROW][C]57[/C][C]0.0086303[/C][C]0.0172606[/C][C]0.99137[/C][/ROW]
[ROW][C]58[/C][C]0.00670049[/C][C]0.013401[/C][C]0.9933[/C][/ROW]
[ROW][C]59[/C][C]0.0157361[/C][C]0.0314721[/C][C]0.984264[/C][/ROW]
[ROW][C]60[/C][C]0.0208213[/C][C]0.0416425[/C][C]0.979179[/C][/ROW]
[ROW][C]61[/C][C]0.0163101[/C][C]0.0326202[/C][C]0.98369[/C][/ROW]
[ROW][C]62[/C][C]0.0171586[/C][C]0.0343172[/C][C]0.982841[/C][/ROW]
[ROW][C]63[/C][C]0.0200124[/C][C]0.0400247[/C][C]0.979988[/C][/ROW]
[ROW][C]64[/C][C]0.0195008[/C][C]0.0390015[/C][C]0.980499[/C][/ROW]
[ROW][C]65[/C][C]0.0216131[/C][C]0.0432261[/C][C]0.978387[/C][/ROW]
[ROW][C]66[/C][C]0.0270642[/C][C]0.0541284[/C][C]0.972936[/C][/ROW]
[ROW][C]67[/C][C]0.029936[/C][C]0.059872[/C][C]0.970064[/C][/ROW]
[ROW][C]68[/C][C]0.0246058[/C][C]0.0492116[/C][C]0.975394[/C][/ROW]
[ROW][C]69[/C][C]0.0254183[/C][C]0.0508366[/C][C]0.974582[/C][/ROW]
[ROW][C]70[/C][C]0.0252605[/C][C]0.0505211[/C][C]0.974739[/C][/ROW]
[ROW][C]71[/C][C]0.0263143[/C][C]0.0526286[/C][C]0.973686[/C][/ROW]
[ROW][C]72[/C][C]0.022069[/C][C]0.044138[/C][C]0.977931[/C][/ROW]
[ROW][C]73[/C][C]0.0221391[/C][C]0.0442783[/C][C]0.977861[/C][/ROW]
[ROW][C]74[/C][C]0.0192846[/C][C]0.0385692[/C][C]0.980715[/C][/ROW]
[ROW][C]75[/C][C]0.0166751[/C][C]0.0333501[/C][C]0.983325[/C][/ROW]
[ROW][C]76[/C][C]0.0188155[/C][C]0.0376309[/C][C]0.981185[/C][/ROW]
[ROW][C]77[/C][C]0.0518644[/C][C]0.103729[/C][C]0.948136[/C][/ROW]
[ROW][C]78[/C][C]0.0449319[/C][C]0.0898638[/C][C]0.955068[/C][/ROW]
[ROW][C]79[/C][C]0.0404191[/C][C]0.0808382[/C][C]0.959581[/C][/ROW]
[ROW][C]80[/C][C]0.0369231[/C][C]0.0738461[/C][C]0.963077[/C][/ROW]
[ROW][C]81[/C][C]0.0382332[/C][C]0.0764664[/C][C]0.961767[/C][/ROW]
[ROW][C]82[/C][C]0.0320168[/C][C]0.0640336[/C][C]0.967983[/C][/ROW]
[ROW][C]83[/C][C]0.0438487[/C][C]0.0876974[/C][C]0.956151[/C][/ROW]
[ROW][C]84[/C][C]0.0379304[/C][C]0.0758608[/C][C]0.96207[/C][/ROW]
[ROW][C]85[/C][C]0.0430955[/C][C]0.0861909[/C][C]0.956905[/C][/ROW]
[ROW][C]86[/C][C]0.0365596[/C][C]0.0731192[/C][C]0.96344[/C][/ROW]
[ROW][C]87[/C][C]0.0791531[/C][C]0.158306[/C][C]0.920847[/C][/ROW]
[ROW][C]88[/C][C]0.0780608[/C][C]0.156122[/C][C]0.921939[/C][/ROW]
[ROW][C]89[/C][C]0.0708654[/C][C]0.141731[/C][C]0.929135[/C][/ROW]
[ROW][C]90[/C][C]0.0612091[/C][C]0.122418[/C][C]0.938791[/C][/ROW]
[ROW][C]91[/C][C]0.0550983[/C][C]0.110197[/C][C]0.944902[/C][/ROW]
[ROW][C]92[/C][C]0.0547017[/C][C]0.109403[/C][C]0.945298[/C][/ROW]
[ROW][C]93[/C][C]0.0593134[/C][C]0.118627[/C][C]0.940687[/C][/ROW]
[ROW][C]94[/C][C]0.0626139[/C][C]0.125228[/C][C]0.937386[/C][/ROW]
[ROW][C]95[/C][C]0.120581[/C][C]0.241162[/C][C]0.879419[/C][/ROW]
[ROW][C]96[/C][C]0.123392[/C][C]0.246785[/C][C]0.876608[/C][/ROW]
[ROW][C]97[/C][C]0.122498[/C][C]0.244995[/C][C]0.877502[/C][/ROW]
[ROW][C]98[/C][C]0.138599[/C][C]0.277198[/C][C]0.861401[/C][/ROW]
[ROW][C]99[/C][C]0.139679[/C][C]0.279357[/C][C]0.860321[/C][/ROW]
[ROW][C]100[/C][C]0.199888[/C][C]0.399776[/C][C]0.800112[/C][/ROW]
[ROW][C]101[/C][C]0.198174[/C][C]0.396347[/C][C]0.801826[/C][/ROW]
[ROW][C]102[/C][C]0.234152[/C][C]0.468305[/C][C]0.765848[/C][/ROW]
[ROW][C]103[/C][C]0.30319[/C][C]0.606381[/C][C]0.69681[/C][/ROW]
[ROW][C]104[/C][C]0.282206[/C][C]0.564412[/C][C]0.717794[/C][/ROW]
[ROW][C]105[/C][C]0.271725[/C][C]0.543449[/C][C]0.728275[/C][/ROW]
[ROW][C]106[/C][C]0.280464[/C][C]0.560929[/C][C]0.719536[/C][/ROW]
[ROW][C]107[/C][C]0.308128[/C][C]0.616256[/C][C]0.691872[/C][/ROW]
[ROW][C]108[/C][C]0.338405[/C][C]0.67681[/C][C]0.661595[/C][/ROW]
[ROW][C]109[/C][C]0.377245[/C][C]0.754489[/C][C]0.622755[/C][/ROW]
[ROW][C]110[/C][C]0.383638[/C][C]0.767275[/C][C]0.616362[/C][/ROW]
[ROW][C]111[/C][C]0.58298[/C][C]0.83404[/C][C]0.41702[/C][/ROW]
[ROW][C]112[/C][C]0.619741[/C][C]0.760519[/C][C]0.380259[/C][/ROW]
[ROW][C]113[/C][C]0.627754[/C][C]0.744492[/C][C]0.372246[/C][/ROW]
[ROW][C]114[/C][C]0.629751[/C][C]0.740498[/C][C]0.370249[/C][/ROW]
[ROW][C]115[/C][C]0.623236[/C][C]0.753528[/C][C]0.376764[/C][/ROW]
[ROW][C]116[/C][C]0.778976[/C][C]0.442049[/C][C]0.221024[/C][/ROW]
[ROW][C]117[/C][C]0.768026[/C][C]0.463948[/C][C]0.231974[/C][/ROW]
[ROW][C]118[/C][C]0.876185[/C][C]0.247631[/C][C]0.123815[/C][/ROW]
[ROW][C]119[/C][C]0.936767[/C][C]0.126467[/C][C]0.0632333[/C][/ROW]
[ROW][C]120[/C][C]0.940501[/C][C]0.118998[/C][C]0.0594988[/C][/ROW]
[ROW][C]121[/C][C]0.943801[/C][C]0.112397[/C][C]0.0561987[/C][/ROW]
[ROW][C]122[/C][C]0.952255[/C][C]0.0954905[/C][C]0.0477452[/C][/ROW]
[ROW][C]123[/C][C]0.966506[/C][C]0.0669889[/C][C]0.0334945[/C][/ROW]
[ROW][C]124[/C][C]0.966673[/C][C]0.0666537[/C][C]0.0333268[/C][/ROW]
[ROW][C]125[/C][C]0.972873[/C][C]0.0542532[/C][C]0.0271266[/C][/ROW]
[ROW][C]126[/C][C]0.983175[/C][C]0.0336507[/C][C]0.0168254[/C][/ROW]
[ROW][C]127[/C][C]0.992357[/C][C]0.015285[/C][C]0.00764252[/C][/ROW]
[ROW][C]128[/C][C]0.992637[/C][C]0.0147264[/C][C]0.0073632[/C][/ROW]
[ROW][C]129[/C][C]0.992094[/C][C]0.0158114[/C][C]0.00790572[/C][/ROW]
[ROW][C]130[/C][C]0.993796[/C][C]0.0124072[/C][C]0.00620358[/C][/ROW]
[ROW][C]131[/C][C]0.993578[/C][C]0.0128431[/C][C]0.00642153[/C][/ROW]
[ROW][C]132[/C][C]0.995295[/C][C]0.00941022[/C][C]0.00470511[/C][/ROW]
[ROW][C]133[/C][C]0.995078[/C][C]0.00984434[/C][C]0.00492217[/C][/ROW]
[ROW][C]134[/C][C]0.995195[/C][C]0.0096099[/C][C]0.00480495[/C][/ROW]
[ROW][C]135[/C][C]0.995504[/C][C]0.00899282[/C][C]0.00449641[/C][/ROW]
[ROW][C]136[/C][C]0.995537[/C][C]0.00892579[/C][C]0.0044629[/C][/ROW]
[ROW][C]137[/C][C]0.995305[/C][C]0.00938935[/C][C]0.00469468[/C][/ROW]
[ROW][C]138[/C][C]0.994373[/C][C]0.0112536[/C][C]0.0056268[/C][/ROW]
[ROW][C]139[/C][C]0.993236[/C][C]0.0135278[/C][C]0.00676388[/C][/ROW]
[ROW][C]140[/C][C]0.996522[/C][C]0.00695524[/C][C]0.00347762[/C][/ROW]
[ROW][C]141[/C][C]0.99577[/C][C]0.00846065[/C][C]0.00423032[/C][/ROW]
[ROW][C]142[/C][C]0.997311[/C][C]0.00537886[/C][C]0.00268943[/C][/ROW]
[ROW][C]143[/C][C]0.996945[/C][C]0.00611019[/C][C]0.00305509[/C][/ROW]
[ROW][C]144[/C][C]0.996125[/C][C]0.00774947[/C][C]0.00387474[/C][/ROW]
[ROW][C]145[/C][C]0.997837[/C][C]0.00432687[/C][C]0.00216343[/C][/ROW]
[ROW][C]146[/C][C]0.997833[/C][C]0.00433402[/C][C]0.00216701[/C][/ROW]
[ROW][C]147[/C][C]0.998829[/C][C]0.00234128[/C][C]0.00117064[/C][/ROW]
[ROW][C]148[/C][C]0.998912[/C][C]0.00217695[/C][C]0.00108847[/C][/ROW]
[ROW][C]149[/C][C]0.998913[/C][C]0.00217309[/C][C]0.00108654[/C][/ROW]
[ROW][C]150[/C][C]0.998971[/C][C]0.00205752[/C][C]0.00102876[/C][/ROW]
[ROW][C]151[/C][C]0.998788[/C][C]0.00242428[/C][C]0.00121214[/C][/ROW]
[ROW][C]152[/C][C]0.998703[/C][C]0.0025933[/C][C]0.00129665[/C][/ROW]
[ROW][C]153[/C][C]0.998443[/C][C]0.00311343[/C][C]0.00155671[/C][/ROW]
[ROW][C]154[/C][C]0.998231[/C][C]0.00353881[/C][C]0.00176941[/C][/ROW]
[ROW][C]155[/C][C]0.998525[/C][C]0.0029494[/C][C]0.0014747[/C][/ROW]
[ROW][C]156[/C][C]0.99943[/C][C]0.00113914[/C][C]0.000569572[/C][/ROW]
[ROW][C]157[/C][C]0.999323[/C][C]0.00135358[/C][C]0.00067679[/C][/ROW]
[ROW][C]158[/C][C]0.999458[/C][C]0.00108481[/C][C]0.000542407[/C][/ROW]
[ROW][C]159[/C][C]0.99942[/C][C]0.00115951[/C][C]0.000579754[/C][/ROW]
[ROW][C]160[/C][C]0.999472[/C][C]0.00105625[/C][C]0.000528126[/C][/ROW]
[ROW][C]161[/C][C]0.99934[/C][C]0.00132033[/C][C]0.000660166[/C][/ROW]
[ROW][C]162[/C][C]0.999339[/C][C]0.00132114[/C][C]0.000660572[/C][/ROW]
[ROW][C]163[/C][C]0.99931[/C][C]0.00137954[/C][C]0.000689769[/C][/ROW]
[ROW][C]164[/C][C]0.999124[/C][C]0.00175136[/C][C]0.00087568[/C][/ROW]
[ROW][C]165[/C][C]0.998901[/C][C]0.00219845[/C][C]0.00109923[/C][/ROW]
[ROW][C]166[/C][C]0.999172[/C][C]0.00165534[/C][C]0.000827669[/C][/ROW]
[ROW][C]167[/C][C]0.999399[/C][C]0.00120178[/C][C]0.000600891[/C][/ROW]
[ROW][C]168[/C][C]0.999309[/C][C]0.00138283[/C][C]0.000691413[/C][/ROW]
[ROW][C]169[/C][C]0.999932[/C][C]0.000136273[/C][C]6.81363e-05[/C][/ROW]
[ROW][C]170[/C][C]0.99992[/C][C]0.000160885[/C][C]8.04427e-05[/C][/ROW]
[ROW][C]171[/C][C]0.999889[/C][C]0.000221338[/C][C]0.000110669[/C][/ROW]
[ROW][C]172[/C][C]0.999921[/C][C]0.000158753[/C][C]7.93766e-05[/C][/ROW]
[ROW][C]173[/C][C]0.999924[/C][C]0.000151975[/C][C]7.59877e-05[/C][/ROW]
[ROW][C]174[/C][C]0.9999[/C][C]0.000199801[/C][C]9.99006e-05[/C][/ROW]
[ROW][C]175[/C][C]0.999878[/C][C]0.000244342[/C][C]0.000122171[/C][/ROW]
[ROW][C]176[/C][C]0.99987[/C][C]0.000260907[/C][C]0.000130454[/C][/ROW]
[ROW][C]177[/C][C]0.999904[/C][C]0.000191263[/C][C]9.56316e-05[/C][/ROW]
[ROW][C]178[/C][C]0.999887[/C][C]0.000226729[/C][C]0.000113364[/C][/ROW]
[ROW][C]179[/C][C]0.999851[/C][C]0.000297601[/C][C]0.000148801[/C][/ROW]
[ROW][C]180[/C][C]0.999807[/C][C]0.000385707[/C][C]0.000192854[/C][/ROW]
[ROW][C]181[/C][C]0.999869[/C][C]0.000262678[/C][C]0.000131339[/C][/ROW]
[ROW][C]182[/C][C]0.999838[/C][C]0.00032467[/C][C]0.000162335[/C][/ROW]
[ROW][C]183[/C][C]0.999897[/C][C]0.00020693[/C][C]0.000103465[/C][/ROW]
[ROW][C]184[/C][C]0.999866[/C][C]0.00026799[/C][C]0.000133995[/C][/ROW]
[ROW][C]185[/C][C]0.999889[/C][C]0.000222916[/C][C]0.000111458[/C][/ROW]
[ROW][C]186[/C][C]0.999864[/C][C]0.000272741[/C][C]0.00013637[/C][/ROW]
[ROW][C]187[/C][C]0.999814[/C][C]0.000371266[/C][C]0.000185633[/C][/ROW]
[ROW][C]188[/C][C]0.999832[/C][C]0.000335197[/C][C]0.000167599[/C][/ROW]
[ROW][C]189[/C][C]0.999806[/C][C]0.000388926[/C][C]0.000194463[/C][/ROW]
[ROW][C]190[/C][C]0.99977[/C][C]0.000459486[/C][C]0.000229743[/C][/ROW]
[ROW][C]191[/C][C]0.999708[/C][C]0.000583429[/C][C]0.000291714[/C][/ROW]
[ROW][C]192[/C][C]0.999812[/C][C]0.000376944[/C][C]0.000188472[/C][/ROW]
[ROW][C]193[/C][C]0.99975[/C][C]0.000500692[/C][C]0.000250346[/C][/ROW]
[ROW][C]194[/C][C]0.999701[/C][C]0.000597391[/C][C]0.000298695[/C][/ROW]
[ROW][C]195[/C][C]0.999609[/C][C]0.000781872[/C][C]0.000390936[/C][/ROW]
[ROW][C]196[/C][C]0.999486[/C][C]0.00102751[/C][C]0.000513755[/C][/ROW]
[ROW][C]197[/C][C]0.99946[/C][C]0.00107947[/C][C]0.000539737[/C][/ROW]
[ROW][C]198[/C][C]0.999324[/C][C]0.00135253[/C][C]0.000676265[/C][/ROW]
[ROW][C]199[/C][C]0.999629[/C][C]0.000742965[/C][C]0.000371483[/C][/ROW]
[ROW][C]200[/C][C]0.999509[/C][C]0.000981597[/C][C]0.000490799[/C][/ROW]
[ROW][C]201[/C][C]0.999391[/C][C]0.00121705[/C][C]0.000608527[/C][/ROW]
[ROW][C]202[/C][C]0.999307[/C][C]0.00138577[/C][C]0.000692886[/C][/ROW]
[ROW][C]203[/C][C]0.999129[/C][C]0.00174224[/C][C]0.000871118[/C][/ROW]
[ROW][C]204[/C][C]0.999017[/C][C]0.00196592[/C][C]0.00098296[/C][/ROW]
[ROW][C]205[/C][C]0.998887[/C][C]0.00222659[/C][C]0.0011133[/C][/ROW]
[ROW][C]206[/C][C]0.998698[/C][C]0.00260372[/C][C]0.00130186[/C][/ROW]
[ROW][C]207[/C][C]0.998536[/C][C]0.00292897[/C][C]0.00146448[/C][/ROW]
[ROW][C]208[/C][C]0.998232[/C][C]0.0035351[/C][C]0.00176755[/C][/ROW]
[ROW][C]209[/C][C]0.997949[/C][C]0.00410289[/C][C]0.00205144[/C][/ROW]
[ROW][C]210[/C][C]0.997492[/C][C]0.00501546[/C][C]0.00250773[/C][/ROW]
[ROW][C]211[/C][C]0.997367[/C][C]0.00526575[/C][C]0.00263288[/C][/ROW]
[ROW][C]212[/C][C]0.996482[/C][C]0.00703516[/C][C]0.00351758[/C][/ROW]
[ROW][C]213[/C][C]0.995982[/C][C]0.00803523[/C][C]0.00401762[/C][/ROW]
[ROW][C]214[/C][C]0.994652[/C][C]0.0106964[/C][C]0.00534821[/C][/ROW]
[ROW][C]215[/C][C]0.996866[/C][C]0.00626825[/C][C]0.00313412[/C][/ROW]
[ROW][C]216[/C][C]0.996727[/C][C]0.00654621[/C][C]0.00327311[/C][/ROW]
[ROW][C]217[/C][C]0.99563[/C][C]0.00873952[/C][C]0.00436976[/C][/ROW]
[ROW][C]218[/C][C]0.994535[/C][C]0.0109297[/C][C]0.00546484[/C][/ROW]
[ROW][C]219[/C][C]0.994492[/C][C]0.0110169[/C][C]0.00550845[/C][/ROW]
[ROW][C]220[/C][C]0.993603[/C][C]0.0127949[/C][C]0.00639747[/C][/ROW]
[ROW][C]221[/C][C]0.992394[/C][C]0.0152127[/C][C]0.00760636[/C][/ROW]
[ROW][C]222[/C][C]0.990281[/C][C]0.0194385[/C][C]0.00971924[/C][/ROW]
[ROW][C]223[/C][C]0.989383[/C][C]0.0212342[/C][C]0.0106171[/C][/ROW]
[ROW][C]224[/C][C]0.98761[/C][C]0.0247793[/C][C]0.0123896[/C][/ROW]
[ROW][C]225[/C][C]0.98606[/C][C]0.0278801[/C][C]0.0139401[/C][/ROW]
[ROW][C]226[/C][C]0.981537[/C][C]0.0369257[/C][C]0.0184628[/C][/ROW]
[ROW][C]227[/C][C]0.976213[/C][C]0.0475745[/C][C]0.0237872[/C][/ROW]
[ROW][C]228[/C][C]0.97421[/C][C]0.0515796[/C][C]0.0257898[/C][/ROW]
[ROW][C]229[/C][C]0.970783[/C][C]0.058435[/C][C]0.0292175[/C][/ROW]
[ROW][C]230[/C][C]0.964396[/C][C]0.0712078[/C][C]0.0356039[/C][/ROW]
[ROW][C]231[/C][C]0.962603[/C][C]0.0747941[/C][C]0.037397[/C][/ROW]
[ROW][C]232[/C][C]0.963032[/C][C]0.0739364[/C][C]0.0369682[/C][/ROW]
[ROW][C]233[/C][C]0.974484[/C][C]0.051031[/C][C]0.0255155[/C][/ROW]
[ROW][C]234[/C][C]0.977733[/C][C]0.0445332[/C][C]0.0222666[/C][/ROW]
[ROW][C]235[/C][C]0.973309[/C][C]0.053382[/C][C]0.026691[/C][/ROW]
[ROW][C]236[/C][C]0.974522[/C][C]0.0509563[/C][C]0.0254782[/C][/ROW]
[ROW][C]237[/C][C]0.980864[/C][C]0.0382727[/C][C]0.0191363[/C][/ROW]
[ROW][C]238[/C][C]0.98061[/C][C]0.0387809[/C][C]0.0193905[/C][/ROW]
[ROW][C]239[/C][C]0.978615[/C][C]0.0427705[/C][C]0.0213853[/C][/ROW]
[ROW][C]240[/C][C]0.972056[/C][C]0.055887[/C][C]0.0279435[/C][/ROW]
[ROW][C]241[/C][C]0.972426[/C][C]0.0551487[/C][C]0.0275744[/C][/ROW]
[ROW][C]242[/C][C]0.966431[/C][C]0.0671381[/C][C]0.0335691[/C][/ROW]
[ROW][C]243[/C][C]0.990492[/C][C]0.0190152[/C][C]0.00950759[/C][/ROW]
[ROW][C]244[/C][C]0.988562[/C][C]0.0228765[/C][C]0.0114382[/C][/ROW]
[ROW][C]245[/C][C]0.989288[/C][C]0.0214245[/C][C]0.0107123[/C][/ROW]
[ROW][C]246[/C][C]0.984718[/C][C]0.0305644[/C][C]0.0152822[/C][/ROW]
[ROW][C]247[/C][C]0.978577[/C][C]0.0428461[/C][C]0.021423[/C][/ROW]
[ROW][C]248[/C][C]0.971971[/C][C]0.0560587[/C][C]0.0280294[/C][/ROW]
[ROW][C]249[/C][C]0.963034[/C][C]0.073933[/C][C]0.0369665[/C][/ROW]
[ROW][C]250[/C][C]0.950722[/C][C]0.0985567[/C][C]0.0492783[/C][/ROW]
[ROW][C]251[/C][C]0.937008[/C][C]0.125984[/C][C]0.0629921[/C][/ROW]
[ROW][C]252[/C][C]0.943857[/C][C]0.112286[/C][C]0.056143[/C][/ROW]
[ROW][C]253[/C][C]0.933268[/C][C]0.133464[/C][C]0.0667318[/C][/ROW]
[ROW][C]254[/C][C]0.911764[/C][C]0.176473[/C][C]0.0882364[/C][/ROW]
[ROW][C]255[/C][C]0.894419[/C][C]0.211163[/C][C]0.105581[/C][/ROW]
[ROW][C]256[/C][C]0.862534[/C][C]0.274932[/C][C]0.137466[/C][/ROW]
[ROW][C]257[/C][C]0.835755[/C][C]0.328489[/C][C]0.164245[/C][/ROW]
[ROW][C]258[/C][C]0.793506[/C][C]0.412988[/C][C]0.206494[/C][/ROW]
[ROW][C]259[/C][C]0.784763[/C][C]0.430475[/C][C]0.215237[/C][/ROW]
[ROW][C]260[/C][C]0.735488[/C][C]0.529024[/C][C]0.264512[/C][/ROW]
[ROW][C]261[/C][C]0.690123[/C][C]0.619754[/C][C]0.309877[/C][/ROW]
[ROW][C]262[/C][C]0.77503[/C][C]0.449941[/C][C]0.22497[/C][/ROW]
[ROW][C]263[/C][C]0.780631[/C][C]0.438738[/C][C]0.219369[/C][/ROW]
[ROW][C]264[/C][C]0.738883[/C][C]0.522233[/C][C]0.261117[/C][/ROW]
[ROW][C]265[/C][C]0.738475[/C][C]0.523051[/C][C]0.261525[/C][/ROW]
[ROW][C]266[/C][C]0.940833[/C][C]0.118334[/C][C]0.0591671[/C][/ROW]
[ROW][C]267[/C][C]0.913516[/C][C]0.172968[/C][C]0.086484[/C][/ROW]
[ROW][C]268[/C][C]0.989375[/C][C]0.0212501[/C][C]0.0106251[/C][/ROW]
[ROW][C]269[/C][C]0.979913[/C][C]0.0401732[/C][C]0.0200866[/C][/ROW]
[ROW][C]270[/C][C]0.972584[/C][C]0.0548311[/C][C]0.0274155[/C][/ROW]
[ROW][C]271[/C][C]0.9986[/C][C]0.00280068[/C][C]0.00140034[/C][/ROW]
[ROW][C]272[/C][C]0.997331[/C][C]0.00533718[/C][C]0.00266859[/C][/ROW]
[ROW][C]273[/C][C]0.995226[/C][C]0.00954814[/C][C]0.00477407[/C][/ROW]
[ROW][C]274[/C][C]0.991379[/C][C]0.0172429[/C][C]0.00862144[/C][/ROW]
[ROW][C]275[/C][C]0.993333[/C][C]0.0133331[/C][C]0.00666653[/C][/ROW]
[ROW][C]276[/C][C]0.994821[/C][C]0.0103571[/C][C]0.00517853[/C][/ROW]
[ROW][C]277[/C][C]0.989511[/C][C]0.0209786[/C][C]0.0104893[/C][/ROW]
[ROW][C]278[/C][C]0.951099[/C][C]0.0978013[/C][C]0.0489007[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260190&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260190&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
90.7248890.5502220.275111
100.6027240.7945530.397276
110.5433620.9132760.456638
120.4208520.8417040.579148
130.3762030.7524060.623797
140.2943640.5887280.705636
150.2315020.4630030.768498
160.1647920.3295840.835208
170.1657070.3314150.834293
180.1269730.2539460.873027
190.08789690.1757940.912103
200.05948520.118970.940515
210.04401910.08803810.955981
220.03991720.07983450.960083
230.03602070.07204130.963979
240.02672620.05345240.973274
250.02137320.04274630.978627
260.01614140.03228290.983859
270.01180770.02361550.988192
280.007362690.01472540.992637
290.01089110.02178230.989109
300.007427830.01485570.992572
310.005150510.0103010.994849
320.0120430.02408590.987957
330.01029990.02059980.9897
340.02469840.04939690.975302
350.01832870.03665740.981671
360.03109670.06219340.968903
370.02252610.04505230.977474
380.01635010.03270010.98365
390.0130890.0261780.986911
400.01417360.02834720.985826
410.01531120.03062230.984689
420.01130970.02261930.98869
430.02280610.04561210.977194
440.01770610.03541210.982294
450.01519640.03039270.984804
460.01141370.02282750.988586
470.009190790.01838160.990809
480.007858390.01571680.992142
490.005894340.01178870.994106
500.007497090.01499420.992503
510.01061620.02123230.989384
520.01075530.02151060.989245
530.008665330.01733070.991335
540.008902050.01780410.991098
550.00717040.01434080.99283
560.008107870.01621570.991892
570.00863030.01726060.99137
580.006700490.0134010.9933
590.01573610.03147210.984264
600.02082130.04164250.979179
610.01631010.03262020.98369
620.01715860.03431720.982841
630.02001240.04002470.979988
640.01950080.03900150.980499
650.02161310.04322610.978387
660.02706420.05412840.972936
670.0299360.0598720.970064
680.02460580.04921160.975394
690.02541830.05083660.974582
700.02526050.05052110.974739
710.02631430.05262860.973686
720.0220690.0441380.977931
730.02213910.04427830.977861
740.01928460.03856920.980715
750.01667510.03335010.983325
760.01881550.03763090.981185
770.05186440.1037290.948136
780.04493190.08986380.955068
790.04041910.08083820.959581
800.03692310.07384610.963077
810.03823320.07646640.961767
820.03201680.06403360.967983
830.04384870.08769740.956151
840.03793040.07586080.96207
850.04309550.08619090.956905
860.03655960.07311920.96344
870.07915310.1583060.920847
880.07806080.1561220.921939
890.07086540.1417310.929135
900.06120910.1224180.938791
910.05509830.1101970.944902
920.05470170.1094030.945298
930.05931340.1186270.940687
940.06261390.1252280.937386
950.1205810.2411620.879419
960.1233920.2467850.876608
970.1224980.2449950.877502
980.1385990.2771980.861401
990.1396790.2793570.860321
1000.1998880.3997760.800112
1010.1981740.3963470.801826
1020.2341520.4683050.765848
1030.303190.6063810.69681
1040.2822060.5644120.717794
1050.2717250.5434490.728275
1060.2804640.5609290.719536
1070.3081280.6162560.691872
1080.3384050.676810.661595
1090.3772450.7544890.622755
1100.3836380.7672750.616362
1110.582980.834040.41702
1120.6197410.7605190.380259
1130.6277540.7444920.372246
1140.6297510.7404980.370249
1150.6232360.7535280.376764
1160.7789760.4420490.221024
1170.7680260.4639480.231974
1180.8761850.2476310.123815
1190.9367670.1264670.0632333
1200.9405010.1189980.0594988
1210.9438010.1123970.0561987
1220.9522550.09549050.0477452
1230.9665060.06698890.0334945
1240.9666730.06665370.0333268
1250.9728730.05425320.0271266
1260.9831750.03365070.0168254
1270.9923570.0152850.00764252
1280.9926370.01472640.0073632
1290.9920940.01581140.00790572
1300.9937960.01240720.00620358
1310.9935780.01284310.00642153
1320.9952950.009410220.00470511
1330.9950780.009844340.00492217
1340.9951950.00960990.00480495
1350.9955040.008992820.00449641
1360.9955370.008925790.0044629
1370.9953050.009389350.00469468
1380.9943730.01125360.0056268
1390.9932360.01352780.00676388
1400.9965220.006955240.00347762
1410.995770.008460650.00423032
1420.9973110.005378860.00268943
1430.9969450.006110190.00305509
1440.9961250.007749470.00387474
1450.9978370.004326870.00216343
1460.9978330.004334020.00216701
1470.9988290.002341280.00117064
1480.9989120.002176950.00108847
1490.9989130.002173090.00108654
1500.9989710.002057520.00102876
1510.9987880.002424280.00121214
1520.9987030.00259330.00129665
1530.9984430.003113430.00155671
1540.9982310.003538810.00176941
1550.9985250.00294940.0014747
1560.999430.001139140.000569572
1570.9993230.001353580.00067679
1580.9994580.001084810.000542407
1590.999420.001159510.000579754
1600.9994720.001056250.000528126
1610.999340.001320330.000660166
1620.9993390.001321140.000660572
1630.999310.001379540.000689769
1640.9991240.001751360.00087568
1650.9989010.002198450.00109923
1660.9991720.001655340.000827669
1670.9993990.001201780.000600891
1680.9993090.001382830.000691413
1690.9999320.0001362736.81363e-05
1700.999920.0001608858.04427e-05
1710.9998890.0002213380.000110669
1720.9999210.0001587537.93766e-05
1730.9999240.0001519757.59877e-05
1740.99990.0001998019.99006e-05
1750.9998780.0002443420.000122171
1760.999870.0002609070.000130454
1770.9999040.0001912639.56316e-05
1780.9998870.0002267290.000113364
1790.9998510.0002976010.000148801
1800.9998070.0003857070.000192854
1810.9998690.0002626780.000131339
1820.9998380.000324670.000162335
1830.9998970.000206930.000103465
1840.9998660.000267990.000133995
1850.9998890.0002229160.000111458
1860.9998640.0002727410.00013637
1870.9998140.0003712660.000185633
1880.9998320.0003351970.000167599
1890.9998060.0003889260.000194463
1900.999770.0004594860.000229743
1910.9997080.0005834290.000291714
1920.9998120.0003769440.000188472
1930.999750.0005006920.000250346
1940.9997010.0005973910.000298695
1950.9996090.0007818720.000390936
1960.9994860.001027510.000513755
1970.999460.001079470.000539737
1980.9993240.001352530.000676265
1990.9996290.0007429650.000371483
2000.9995090.0009815970.000490799
2010.9993910.001217050.000608527
2020.9993070.001385770.000692886
2030.9991290.001742240.000871118
2040.9990170.001965920.00098296
2050.9988870.002226590.0011133
2060.9986980.002603720.00130186
2070.9985360.002928970.00146448
2080.9982320.00353510.00176755
2090.9979490.004102890.00205144
2100.9974920.005015460.00250773
2110.9973670.005265750.00263288
2120.9964820.007035160.00351758
2130.9959820.008035230.00401762
2140.9946520.01069640.00534821
2150.9968660.006268250.00313412
2160.9967270.006546210.00327311
2170.995630.008739520.00436976
2180.9945350.01092970.00546484
2190.9944920.01101690.00550845
2200.9936030.01279490.00639747
2210.9923940.01521270.00760636
2220.9902810.01943850.00971924
2230.9893830.02123420.0106171
2240.987610.02477930.0123896
2250.986060.02788010.0139401
2260.9815370.03692570.0184628
2270.9762130.04757450.0237872
2280.974210.05157960.0257898
2290.9707830.0584350.0292175
2300.9643960.07120780.0356039
2310.9626030.07479410.037397
2320.9630320.07393640.0369682
2330.9744840.0510310.0255155
2340.9777330.04453320.0222666
2350.9733090.0533820.026691
2360.9745220.05095630.0254782
2370.9808640.03827270.0191363
2380.980610.03878090.0193905
2390.9786150.04277050.0213853
2400.9720560.0558870.0279435
2410.9724260.05514870.0275744
2420.9664310.06713810.0335691
2430.9904920.01901520.00950759
2440.9885620.02287650.0114382
2450.9892880.02142450.0107123
2460.9847180.03056440.0152822
2470.9785770.04284610.021423
2480.9719710.05605870.0280294
2490.9630340.0739330.0369665
2500.9507220.09855670.0492783
2510.9370080.1259840.0629921
2520.9438570.1122860.056143
2530.9332680.1334640.0667318
2540.9117640.1764730.0882364
2550.8944190.2111630.105581
2560.8625340.2749320.137466
2570.8357550.3284890.164245
2580.7935060.4129880.206494
2590.7847630.4304750.215237
2600.7354880.5290240.264512
2610.6901230.6197540.309877
2620.775030.4499410.22497
2630.7806310.4387380.219369
2640.7388830.5222330.261117
2650.7384750.5230510.261525
2660.9408330.1183340.0591671
2670.9135160.1729680.086484
2680.9893750.02125010.0106251
2690.9799130.04017320.0200866
2700.9725840.05483110.0274155
2710.99860.002800680.00140034
2720.9973310.005337180.00266859
2730.9952260.009548140.00477407
2740.9913790.01724290.00862144
2750.9933330.01333310.00666653
2760.9948210.01035710.00517853
2770.9895110.02097860.0104893
2780.9510990.09780130.0489007






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level860.318519NOK
5% type I error level1660.614815NOK
10% type I error level2050.759259NOK

\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 & 86 & 0.318519 & NOK \tabularnewline
5% type I error level & 166 & 0.614815 & NOK \tabularnewline
10% type I error level & 205 & 0.759259 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260190&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]86[/C][C]0.318519[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]166[/C][C]0.614815[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]205[/C][C]0.759259[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260190&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260190&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 level860.318519NOK
5% type I error level1660.614815NOK
10% type I error level2050.759259NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

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