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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 17 Dec 2014 15:01:44 +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/Dec/17/t1418828565dkpse7lhv25r5fs.htm/, Retrieved Thu, 16 May 2024 13:51:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270372, Retrieved Thu, 16 May 2024 13:51:29 +0000
QR Codes:

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

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Percentiles] [Intrinsic Motivat...] [2010-10-12 12:10:58] [b98453cac15ba1066b407e146608df68]
- R  D  [Percentiles] [] [2011-10-18 22:34:54] [b98453cac15ba1066b407e146608df68]
- RMPD    [Percentiles] [] [2014-12-14 10:18:21] [2fea329c6e322b1612c5dc504f90c0ef]
-    D      [Percentiles] [] [2014-12-14 10:24:25] [2fea329c6e322b1612c5dc504f90c0ef]
-    D        [Percentiles] [] [2014-12-14 10:27:52] [2fea329c6e322b1612c5dc504f90c0ef]
-   PD          [Percentiles] [] [2014-12-16 14:14:51] [2fea329c6e322b1612c5dc504f90c0ef]
-    D            [Percentiles] [] [2014-12-16 14:30:23] [2fea329c6e322b1612c5dc504f90c0ef]
- RM D              [Multiple Regression] [] [2014-12-16 16:28:02] [2fea329c6e322b1612c5dc504f90c0ef]
- R  D                [Multiple Regression] [] [2014-12-16 16:47:32] [2fea329c6e322b1612c5dc504f90c0ef]
- R PD                    [Multiple Regression] [] [2014-12-17 15:01:44] [d100ddac424efc880e37824ffef4fe9f] [Current]
-    D                      [Multiple Regression] [] [2014-12-17 15:21:27] [95c11abf048d3a1e472aeccb09199113]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21	12.9	149	96	86	13	12
22	12.2	139	70	70	8	8
22	12.8	148	88	71	14	11
18	7.4	158	114	108	16	13
23	6.7	128	69	64	14	11
12	12.6	224	176	119	13	10
20	14.8	159	114	97	15	7
22	13.3	105	121	129	13	10
21	11.1	159	110	153	20	15
19	8.2	167	158	78	17	12
22	11.4	165	116	80	15	12
15	6.4	159	181	99	16	10
20	10.6	119	77	68	12	10
19	12.0	176	141	147	17	14
18	6.3	54	35	40	11	6
15	11.3	91	80	57	16	12
20	11.9	163	152	120	16	14
21	9.3	124	97	71	15	11
21	9.6	137	99	84	13	8
15	10.0	121	84	68	14	12
16	6.4	153	68	55	19	15
23	13.8	148	101	137	16	13
21	10.8	221	107	79	17	11
18	13.8	188	88	116	10	12
25	11.7	149	112	101	15	7
9	10.9	244	171	111	14	11
30	16.1	148	137	189	14	7
20	13.4	92	77	66	16	12
23	9.9	150	66	81	15	12
16	11.5	153	93	63	17	13
16	8.3	94	105	69	14	9
19	11.7	156	131	71	16	11
25	9.0	132	102	64	15	12
18	9.7	161	161	143	16	15
23	10.8	105	120	85	16	12
21	10.3	97	127	86	10	6
10	10.4	151	77	55	8	5
14	12.7	131	108	69	17	13
22	9.3	166	85	120	14	11
26	11.8	157	168	96	10	6
23	5.9	111	48	60	14	12
23	11.4	145	152	95	12	10
24	13.0	162	75	100	16	6
24	10.8	163	107	68	16	12
18	12.3	59	62	57	16	11
23	11.3	187	121	105	8	6
15	11.8	109	124	85	16	12
19	7.9	90	72	103	15	12
16	12.7	105	40	57	8	8
25	12.3	83	58	51	13	10
23	11.6	116	97	69	14	11
17	6.7	42	88	41	13	7
19	10.9	148	126	49	16	12
21	12.1	155	104	50	19	13
18	13.3	125	148	93	19	14
27	10.1	116	146	58	14	12
21	5.7	128	80	54	15	6
13	14.3	138	97	74	13	14
8	8.0	49	25	15	10	10
29	13.3	96	99	69	16	12
28	9.3	164	118	107	15	11
23	12.5	162	58	65	11	10
21	7.6	99	63	58	9	7
19	15.9	202	139	107	16	12
19	9.2	186	50	70	12	7
20	9.1	66	60	53	12	12
18	11.1	183	152	136	14	12
19	13.0	214	142	126	14	10
17	14.5	188	94	95	13	10
19	12.2	104	66	69	15	12
25	12.3	177	127	136	17	12
19	11.4	126	67	58	14	12
22	8.8	76	90	59	11	8
23	14.6	99	75	118	9	10
14	12.6	139	128	82	7	5
16	13.0	162	146	102	15	10
24	12.6	108	69	65	12	12
20	13.2	159	186	90	15	11
12	9.9	74	81	64	14	9
24	7.7	110	85	83	16	12
22	10.5	96	54	70	14	11
12	13.4	116	46	50	13	10
22	10.9	87	106	77	16	12
20	4.3	97	34	37	13	10
10	10.3	127	60	81	16	9
23	11.8	106	95	101	16	11
17	11.2	80	57	79	16	12
22	11.4	74	62	71	10	7
24	8.6	91	36	60	12	11
18	13.2	133	56	55	12	12
21	12.6	74	54	44	12	6
20	5.6	114	64	40	12	9
20	9.9	140	76	56	19	15
22	8.8	95	98	43	14	10
19	7.7	98	88	45	13	11
20	9.0	121	35	32	16	12
26	7.3	126	102	56	15	12
23	11.4	98	61	40	12	12
24	13.6	95	80	34	8	11
21	7.9	110	49	89	10	9
21	10.7	70	78	50	16	11
19	10.3	102	90	56	16	12
8	8.3	86	45	46	10	12
17	9.6	130	55	76	18	14
20	14.2	96	96	64	12	8
11	8.5	102	43	74	16	10
8	13.5	100	52	57	10	9
15	4.9	94	60	45	14	10
18	6.4	52	54	30	12	9
18	9.6	98	51	62	11	10
19	11.6	118	51	51	15	12
19	11.1	99	38	36	7	11
23	4.4	48	41	34	16	9
22	12.7	50	146	61	16	11
21	18.1	150	182	70	16	12
25	17.9	154	192	69	16	12
30	16.6	109	263	145	12	7
17	12.6	68	35	23	15	12
27	17.1	194	439	120	14	12
23	19.1	158	214	147	15	12
23	16.1	159	341	215	16	10
18	13.4	67	58	24	13	15
18	18.4	147	292	84	10	10
23	14.7	39	85	30	17	15
19	10.6	100	200	77	15	10
15	12.6	111	158	46	18	15
20	16.2	138	199	61	16	9
16	13.6	101	297	178	20	15
24	18.9	131	227	160	16	12
25	14.1	101	108	57	17	13
25	14.5	114	86	42	16	12
19	16.2	165	302	163	15	12
19	14.8	114	148	75	13	8
16	14.8	111	178	94	16	9
19	12.5	75	120	45	16	15
19	12.7	82	207	78	16	12
23	17.4	121	157	47	17	12
21	8.6	32	128	29	20	15
22	18.4	150	296	97	14	11
19	16.1	117	323	116	17	12
20	11.6	71	79	32	6	6
20	17.8	165	70	50	16	14
3	15.3	154	146	118	15	12
23	17.7	126	246	66	16	12
23	16.4	149	196	86	16	12
20	17.7	145	199	89	14	11
15	13.6	120	127	76	16	12
16	14.4	109	153	75	16	12
7	14.8	132	299	57	16	12
24	18.3	172	228	72	14	12
17	9.9	169	190	60	14	8
24	16.0	114	180	109	16	8
24	18.3	156	212	76	16	12
19	16.9	172	269	65	15	12
25	14.6	68	130	40	16	11
20	13.9	89	179	58	16	10
28	19.0	167	243	123	18	11
23	15.6	113	190	71	15	12
27	14.9	115	299	102	16	13
18	11.8	78	121	80	16	12
28	18.5	118	137	97	16	12
21	15.9	87	305	46	17	10
19	17.1	173	157	93	14	10
23	16.1	2	96	19	18	11
27	19.9	162	183	140	9	8
22	11.0	49	52	78	15	12
28	18.5	122	238	98	14	9
25	15.1	96	40	40	15	12
21	15.0	100	226	80	13	9
22	11.4	82	190	76	16	11
28	16.0	100	214	79	20	15
20	18.1	115	145	87	14	8
29	14.6	141	119	95	12	8
25	15.4	165	222	49	15	11
25	15.4	165	222	49	15	11
20	17.6	110	159	80	15	11
20	13.4	118	165	86	16	13
16	19.1	158	249	69	11	7
20	15.4	146	125	79	16	12
20	7.6	49	122	52	7	8
23	13.4	90	186	120	11	8
18	13.9	121	148	69	9	4
25	19.1	155	274	94	15	11
18	15.3	104	172	72	16	10
19	12.9	147	84	43	14	7
25	16.1	110	168	87	15	12
25	17.4	108	102	52	13	11
25	13.2	113	106	71	13	9
24	12.2	115	2	61	12	10
19	12.6	61	139	51	16	8
26	10.4	60	95	50	14	8
10	15.4	109	130	67	16	11
17	9.6	68	72	30	14	12
13	18.2	111	141	70	15	10
17	13.6	77	113	52	10	10
30	14.9	73	206	75	16	12
25	14.8	151	268	87	14	8
4	14.1	89	175	69	16	11
16	14.9	78	77	72	12	8
21	16.3	110	125	79	16	10
23	19.3	220	255	121	16	14
22	13.6	65	111	43	15	9
17	13.6	141	132	58	14	9
20	15.7	117	211	57	16	10
20	12.8	122	92	50	11	13
22	14.6	63	76	69	15	12
16	9.9	44	171	64	18	13
23	12.7	52	83	38	13	8
0	19.2	131	266	90	7	3
18	16.6	101	186	96	7	8
25	11.2	42	50	49	17	12
23	15.3	152	117	56	18	11
12	11.9	107	219	102	15	9
18	13.2	77	246	40	8	12
24	16.4	154	279	100	13	12
11	12.4	103	148	67	13	12
18	15.9	96	137	78	15	10
23	18.2	175	181	55	18	13
24	11.2	57	98	59	16	9
29	15.7	112	226	96	14	12
18	17.8	143	234	86	15	11
15	7.7	49	138	38	19	14
29	12.4	110	85	43	16	11
16	15.6	131	66	23	12	9
19	19.3	167	236	77	16	12
22	15.2	56	106	48	11	8
16	17.1	137	135	26	16	15
23	15.6	86	122	91	15	12
23	18.4	121	218	94	19	14
19	19.1	149	199	62	15	12
4	18.6	168	112	74	14	9
20	19.1	140	278	114	14	9
24	13.1	88	94	52	17	13
20	12.9	168	113	64	16	13
4	9.5	94	84	31	20	15
24	4.5	51	86	38	16	11
22	11.9	48	62	27	9	7
16	13.6	145	222	105	13	10
3	11.7	66	167	64	15	11
15	12.4	85	82	62	19	14
24	13.4	109	207	65	16	14
17	11.4	63	184	58	17	13
20	14.9	102	83	76	16	12
27	19.9	162	183	140	9	8
26	11.2	86	89	68	11	13
23	14.6	114	225	80	14	9
17	17.6	164	237	71	19	12
20	14.1	119	102	76	13	13
22	16.1	126	221	63	14	11
19	13.4	132	128	46	15	11
24	11.9	142	91	53	15	13
19	12.0	83	198	74	14	12
23	14.8	94	204	70	16	12
15	15.2	81	158	78	17	10
27	13.2	166	138	56	12	9
26	16.9	110	226	100	15	10
22	7.9	64	44	51	17	13
22	7.7	93	196	52	15	13
18	12.6	104	83	102	10	9
15	7.9	105	79	78	16	11
22	11.0	49	52	78	15	12
27	12.4	88	105	55	11	8
10	10.0	95	116	98	16	12
20	14.9	102	83	76	16	12
17	16.7	99	196	73	16	12
23	13.4	63	153	47	14	9
19	14.0	76	157	45	14	12
13	15.7	109	75	83	16	12
27	16.9	117	106	60	16	11
23	11.0	57	58	48	18	12
16	15.4	120	75	50	14	6
25	12.2	73	74	56	20	7
2	15.1	91	185	77	15	10
26	17.8	108	265	91	16	12
20	15.2	105	131	76	16	10
23	14.6	117	139	68	16	12
22	16.7	119	196	74	12	9
24	8.1	31	78	29	8	3

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'Sir Maurice George Kendall' @ kendall.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270372&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270372&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270372&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'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Examen[t] = + 7.85287 + 0.0509677Numeracy[t] + 0.010792LFM[t] + 0.027112B[t] -0.00212458H[t] -0.0454249Confstat[t] + 0.0054228Confsoft[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Examen[t] =  +  7.85287 +  0.0509677Numeracy[t] +  0.010792LFM[t] +  0.027112B[t] -0.00212458H[t] -0.0454249Confstat[t] +  0.0054228Confsoft[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270372&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Examen[t] =  +  7.85287 +  0.0509677Numeracy[t] +  0.010792LFM[t] +  0.027112B[t] -0.00212458H[t] -0.0454249Confstat[t] +  0.0054228Confsoft[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270372&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270372&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
Examen[t] = + 7.85287 + 0.0509677Numeracy[t] + 0.010792LFM[t] + 0.027112B[t] -0.00212458H[t] -0.0454249Confstat[t] + 0.0054228Confsoft[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)7.852871.188856.6052.08826e-101.04413e-10
Numeracy0.05096770.0322061.5830.1146890.0573447
LFM0.0107920.004843932.2280.02670520.0133526
B0.0271120.0026715610.151.01371e-205.06857e-21
H-0.002124580.00680376-0.31230.7550790.377539
Confstat-0.04542490.0777245-0.58440.5594140.279707
Confsoft0.00542280.09206490.05890.9530740.476537

\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) & 7.85287 & 1.18885 & 6.605 & 2.08826e-10 & 1.04413e-10 \tabularnewline
Numeracy & 0.0509677 & 0.032206 & 1.583 & 0.114689 & 0.0573447 \tabularnewline
LFM & 0.010792 & 0.00484393 & 2.228 & 0.0267052 & 0.0133526 \tabularnewline
B & 0.027112 & 0.00267156 & 10.15 & 1.01371e-20 & 5.06857e-21 \tabularnewline
H & -0.00212458 & 0.00680376 & -0.3123 & 0.755079 & 0.377539 \tabularnewline
Confstat & -0.0454249 & 0.0777245 & -0.5844 & 0.559414 & 0.279707 \tabularnewline
Confsoft & 0.0054228 & 0.0920649 & 0.0589 & 0.953074 & 0.476537 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270372&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]7.85287[/C][C]1.18885[/C][C]6.605[/C][C]2.08826e-10[/C][C]1.04413e-10[/C][/ROW]
[ROW][C]Numeracy[/C][C]0.0509677[/C][C]0.032206[/C][C]1.583[/C][C]0.114689[/C][C]0.0573447[/C][/ROW]
[ROW][C]LFM[/C][C]0.010792[/C][C]0.00484393[/C][C]2.228[/C][C]0.0267052[/C][C]0.0133526[/C][/ROW]
[ROW][C]B[/C][C]0.027112[/C][C]0.00267156[/C][C]10.15[/C][C]1.01371e-20[/C][C]5.06857e-21[/C][/ROW]
[ROW][C]H[/C][C]-0.00212458[/C][C]0.00680376[/C][C]-0.3123[/C][C]0.755079[/C][C]0.377539[/C][/ROW]
[ROW][C]Confstat[/C][C]-0.0454249[/C][C]0.0777245[/C][C]-0.5844[/C][C]0.559414[/C][C]0.279707[/C][/ROW]
[ROW][C]Confsoft[/C][C]0.0054228[/C][C]0.0920649[/C][C]0.0589[/C][C]0.953074[/C][C]0.476537[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270372&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270372&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)7.852871.188856.6052.08826e-101.04413e-10
Numeracy0.05096770.0322061.5830.1146890.0573447
LFM0.0107920.004843932.2280.02670520.0133526
B0.0271120.0026715610.151.01371e-205.06857e-21
H-0.002124580.00680376-0.31230.7550790.377539
Confstat-0.04542490.0777245-0.58440.5594140.279707
Confsoft0.00542280.09206490.05890.9530740.476537






Multiple Linear Regression - Regression Statistics
Multiple R0.612031
R-squared0.374582
Adjusted R-squared0.360735
F-TEST (value)27.0517
F-TEST (DF numerator)6
F-TEST (DF denominator)271
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.71871
Sum Squared Residuals2003.07

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.612031 \tabularnewline
R-squared & 0.374582 \tabularnewline
Adjusted R-squared & 0.360735 \tabularnewline
F-TEST (value) & 27.0517 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 271 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.71871 \tabularnewline
Sum Squared Residuals & 2003.07 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270372&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.612031[/C][/ROW]
[ROW][C]R-squared[/C][C]0.374582[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.360735[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]27.0517[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]271[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.71871[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2003.07[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270372&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270372&T=3

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.612031
R-squared0.374582
Adjusted R-squared0.360735
F-TEST (value)27.0517
F-TEST (DF numerator)6
F-TEST (DF denominator)271
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.71871
Sum Squared Residuals2003.07






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.42580.47421
212.211.90340.296647
312.812.23010.569909
47.412.6804-5.28044
56.711.565-4.86496
612.614.8645-2.26448
714.812.82941.97058
813.312.57750.722494
911.112.4692-1.36922
108.214.0344-5.83435
1111.413.1136-1.71357
126.414.3577-7.95768
1310.611.6088-1.00876
141213.5348-1.53482
156.39.74986-3.44986
1611.310.98560.314407
1711.913.8465-1.94652
189.312.1187-2.8187
199.612.3602-2.76018
201011.4853-1.48528
216.411.2646-4.86456
2213.812.41331.38671
2310.813.3288-2.5288
2413.812.54941.25058
2511.712.9136-1.21362
2610.914.7689-3.86885
2716.113.69392.40607
2813.411.15082.24923
299.911.6449-1.74493
3011.512.0054-0.505372
318.311.7958-3.49582
3211.713.2385-1.53849
33912.5648-3.56476
349.713.9236-4.22356
3510.812.5694-1.76941
3610.312.8088-2.50881
3710.411.6266-1.22663
3812.712.05990.640056
399.312.2389-2.93891
4011.814.8015-3.00152
415.910.8261-4.92607
4211.414.0183-2.61829
431311.95111.04892
4410.812.93-2.12998
4512.310.29972.00029
4611.313.7698-2.46984
4711.812.3133-0.513288
487.910.9095-3.00947
4912.710.44492.25512
5012.310.95061.34935
5111.612.184-0.583971
526.710.9188-4.21877
5310.913.0688-2.16876
5412.112.5168-0.416796
5513.313.14710.152875
5610.113.7451-3.64512
575.711.71-6.00997
5814.311.96282.33721
5989.03533-1.03533
6013.312.24271.05727
619.313.4-4.10002
6212.511.76240.737613
637.611.2056-3.60557
6415.913.88082.01924
659.211.5283-2.32831
669.110.6186-1.51859
6711.114.0064-2.90643
681314.1312-1.13123
6914.512.55861.94138
7012.210.97011.22988
7112.313.4844-1.18438
7211.411.30350.0965459
738.811.6528-2.85279
7414.611.52163.07836
7512.613.0718-0.471767
761313.5312-0.531158
7712.611.49421.10576
7813.214.818-1.61805
799.910.736-0.836047
807.711.7297-4.02967
8110.510.7492-0.249223
8213.410.3213.07902
8310.911.9616-1.06162
844.310.226-5.92595
8510.310.5098-0.209769
8611.811.863-0.0629904
8711.210.29850.9015
8811.410.88660.513421
898.610.4213-1.82128
9013.211.1272.07298
9112.610.57982.02019
925.611.2564-5.65641
939.911.5429-1.64291
948.811.9833-3.1833
957.711.6383-3.93825
96910.3973-1.39727
977.312.568-5.26797
9811.411.17160.228431
9913.611.89431.70569
1007.910.8443-2.94427
10110.711.02-0.319992
10210.311.5814-1.28142
1038.39.92186-1.62186
1049.610.7102-1.11025
10514.211.87332.32668
1068.59.85033-1.35033
10713.510.22313.27691
1084.910.5812-5.68123
1096.410.2355-3.83549
1109.610.6334-1.03345
11111.610.75280.847226
11211.110.58510.514885
1134.49.90451-5.50451
11412.712.67540.0246362
11518.114.66593.43407
11617.915.18622.71379
11716.616.8735-0.273479
11812.69.736932.86307
11917.122.399-5.29898
12019.115.60363.49638
12116.118.8569-2.75689
12213.410.50572.89432
12318.417.69490.705072
12414.710.99593.70408
12510.614.5321-3.93212
12612.613.265-0.664956
12716.214.94921.25079
12813.616.6053-3.00527
12918.915.64263.25739
13014.112.32231.77768
13114.511.9382.56197
13216.217.8272-1.62715
13314.813.35761.44236
13414.813.81450.985503
13512.512.1430.356966
13612.714.4909-1.79094
13717.413.78053.61946
1388.611.8501-3.2501
13918.417.83570.564273
14016.117.8875-1.78749
14111.611.47230.127694
14217.811.79366.00636
14315.312.75912.54091
14417.716.25251.44748
14516.415.10261.29735
14617.715.0672.63303
14713.612.53251.06754
14814.413.17171.22825
14914.816.9578-2.15785
15018.316.391.90999
1519.914.9744-5.07441
1521614.27151.72845
15318.315.68422.6158
15416.917.2162-0.316209
15514.612.63331.96665
15613.913.890.010037
1571916.65112.34888
15815.614.62880.971243
15914.917.7036-2.80355
16011.812.0609-0.260926
16118.513.45.10004
16215.917.3155-1.41553
16317.114.16562.93445
16416.110.85115.2489
16519.915.27594.62408
1661110.13080.869224
16718.516.25392.24611
16815.110.54634.55371
1691515.418-0.418017
17011.414.1818-2.78177
1711615.16610.833866
17218.113.26714.83286
17314.613.37541.22462
17415.416.2008-0.800779
17515.416.2008-0.800779
17617.613.57854.02154
17713.413.7801-0.380144
17819.116.51612.58393
17915.413.00732.39271
1807.612.3236-4.72363
18113.414.328-0.927997
18213.913.5550.345032
18319.117.40711.69292
18415.313.73041.56962
18512.911.99570.904255
18616.114.06792.03214
18717.412.41674.98333
18813.212.52790.672132
18912.29.750932.44907
19012.612.45640.143634
19110.411.7024-1.3024
19215.412.25393.14606
1939.610.7706-1.17063
19418.212.76035.43971
19513.612.10351.49654
19614.914.9337-0.033719
19714.817.2453-2.44526
19814.112.94811.15192
19914.910.94313.95693
20016.312.65893.6411
20119.317.4051.89503
20213.611.96111.63885
20313.613.10940.490591
20415.715.06180.638153
20512.812.14770.652253
20614.610.95173.64833
2079.912.8962-2.99623
20812.711.20871.49127
20919.215.98553.21451
21016.614.42462.17544
21111.210.12471.07533
21215.312.96062.33936
21311.914.7075-2.80748
21413.215.8875-2.68751
21516.417.5644-1.1644
21612.412.8699-0.46987
21715.912.72783.1722
21818.214.9573.243
21911.211.5449-0.344872
22015.715.8921-0.192113
22117.815.85331.94669
2227.712.0198-4.31976
22312.412.06410.335929
22415.611.32634.27366
22519.316.19663.10337
22615.211.89413.30589
22717.113.10633.99372
22815.612.45133.14873
22918.415.25453.14549
23019.115.07654.02347
23118.612.1626.43802
23219.117.09092.00911
23313.111.76211.33789
23412.912.9567-0.0566627
2359.510.4556-0.95558
2364.511.2102-6.71024
23711.910.74491.15511
23813.615.4927-1.89268
23911.712.4881-0.788052
24012.410.8391.56099
24113.415.0756-1.67563
24211.413.5629-2.16287
24314.911.40013.49989
24419.915.27594.62408
24511.211.9455-0.745463
24614.615.5985-0.998504
24717.615.96591.63409
24814.112.24041.8596
24916.115.61560.484444
25013.412.99670.403316
25111.912.3523-0.452273
2521214.3571-2.35707
25314.814.760.0400237
25415.212.89152.30848
25513.214.1467-0.946657
25616.915.65291.24714
2577.910.0477-2.1477
2587.714.5704-6.87041
25912.611.52081.0792
2607.911.0595-3.15953
2611110.13080.869224
26212.412.4523-0.0523117
2631011.6628-1.66285
26414.911.40013.49989
26516.714.28492.41514
26613.413.16620.23384
2671413.23160.768449
26815.710.88714.81288
26916.912.57094.32909
2701110.35820.641786
27115.411.28724.11285
27212.210.93171.26835
27315.113.16191.93814
27417.816.67321.12682
27515.212.7232.47698
27614.613.25021.34984
27716.714.91881.78115
2788.111.1166-3.01664

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.4258 & 0.47421 \tabularnewline
2 & 12.2 & 11.9034 & 0.296647 \tabularnewline
3 & 12.8 & 12.2301 & 0.569909 \tabularnewline
4 & 7.4 & 12.6804 & -5.28044 \tabularnewline
5 & 6.7 & 11.565 & -4.86496 \tabularnewline
6 & 12.6 & 14.8645 & -2.26448 \tabularnewline
7 & 14.8 & 12.8294 & 1.97058 \tabularnewline
8 & 13.3 & 12.5775 & 0.722494 \tabularnewline
9 & 11.1 & 12.4692 & -1.36922 \tabularnewline
10 & 8.2 & 14.0344 & -5.83435 \tabularnewline
11 & 11.4 & 13.1136 & -1.71357 \tabularnewline
12 & 6.4 & 14.3577 & -7.95768 \tabularnewline
13 & 10.6 & 11.6088 & -1.00876 \tabularnewline
14 & 12 & 13.5348 & -1.53482 \tabularnewline
15 & 6.3 & 9.74986 & -3.44986 \tabularnewline
16 & 11.3 & 10.9856 & 0.314407 \tabularnewline
17 & 11.9 & 13.8465 & -1.94652 \tabularnewline
18 & 9.3 & 12.1187 & -2.8187 \tabularnewline
19 & 9.6 & 12.3602 & -2.76018 \tabularnewline
20 & 10 & 11.4853 & -1.48528 \tabularnewline
21 & 6.4 & 11.2646 & -4.86456 \tabularnewline
22 & 13.8 & 12.4133 & 1.38671 \tabularnewline
23 & 10.8 & 13.3288 & -2.5288 \tabularnewline
24 & 13.8 & 12.5494 & 1.25058 \tabularnewline
25 & 11.7 & 12.9136 & -1.21362 \tabularnewline
26 & 10.9 & 14.7689 & -3.86885 \tabularnewline
27 & 16.1 & 13.6939 & 2.40607 \tabularnewline
28 & 13.4 & 11.1508 & 2.24923 \tabularnewline
29 & 9.9 & 11.6449 & -1.74493 \tabularnewline
30 & 11.5 & 12.0054 & -0.505372 \tabularnewline
31 & 8.3 & 11.7958 & -3.49582 \tabularnewline
32 & 11.7 & 13.2385 & -1.53849 \tabularnewline
33 & 9 & 12.5648 & -3.56476 \tabularnewline
34 & 9.7 & 13.9236 & -4.22356 \tabularnewline
35 & 10.8 & 12.5694 & -1.76941 \tabularnewline
36 & 10.3 & 12.8088 & -2.50881 \tabularnewline
37 & 10.4 & 11.6266 & -1.22663 \tabularnewline
38 & 12.7 & 12.0599 & 0.640056 \tabularnewline
39 & 9.3 & 12.2389 & -2.93891 \tabularnewline
40 & 11.8 & 14.8015 & -3.00152 \tabularnewline
41 & 5.9 & 10.8261 & -4.92607 \tabularnewline
42 & 11.4 & 14.0183 & -2.61829 \tabularnewline
43 & 13 & 11.9511 & 1.04892 \tabularnewline
44 & 10.8 & 12.93 & -2.12998 \tabularnewline
45 & 12.3 & 10.2997 & 2.00029 \tabularnewline
46 & 11.3 & 13.7698 & -2.46984 \tabularnewline
47 & 11.8 & 12.3133 & -0.513288 \tabularnewline
48 & 7.9 & 10.9095 & -3.00947 \tabularnewline
49 & 12.7 & 10.4449 & 2.25512 \tabularnewline
50 & 12.3 & 10.9506 & 1.34935 \tabularnewline
51 & 11.6 & 12.184 & -0.583971 \tabularnewline
52 & 6.7 & 10.9188 & -4.21877 \tabularnewline
53 & 10.9 & 13.0688 & -2.16876 \tabularnewline
54 & 12.1 & 12.5168 & -0.416796 \tabularnewline
55 & 13.3 & 13.1471 & 0.152875 \tabularnewline
56 & 10.1 & 13.7451 & -3.64512 \tabularnewline
57 & 5.7 & 11.71 & -6.00997 \tabularnewline
58 & 14.3 & 11.9628 & 2.33721 \tabularnewline
59 & 8 & 9.03533 & -1.03533 \tabularnewline
60 & 13.3 & 12.2427 & 1.05727 \tabularnewline
61 & 9.3 & 13.4 & -4.10002 \tabularnewline
62 & 12.5 & 11.7624 & 0.737613 \tabularnewline
63 & 7.6 & 11.2056 & -3.60557 \tabularnewline
64 & 15.9 & 13.8808 & 2.01924 \tabularnewline
65 & 9.2 & 11.5283 & -2.32831 \tabularnewline
66 & 9.1 & 10.6186 & -1.51859 \tabularnewline
67 & 11.1 & 14.0064 & -2.90643 \tabularnewline
68 & 13 & 14.1312 & -1.13123 \tabularnewline
69 & 14.5 & 12.5586 & 1.94138 \tabularnewline
70 & 12.2 & 10.9701 & 1.22988 \tabularnewline
71 & 12.3 & 13.4844 & -1.18438 \tabularnewline
72 & 11.4 & 11.3035 & 0.0965459 \tabularnewline
73 & 8.8 & 11.6528 & -2.85279 \tabularnewline
74 & 14.6 & 11.5216 & 3.07836 \tabularnewline
75 & 12.6 & 13.0718 & -0.471767 \tabularnewline
76 & 13 & 13.5312 & -0.531158 \tabularnewline
77 & 12.6 & 11.4942 & 1.10576 \tabularnewline
78 & 13.2 & 14.818 & -1.61805 \tabularnewline
79 & 9.9 & 10.736 & -0.836047 \tabularnewline
80 & 7.7 & 11.7297 & -4.02967 \tabularnewline
81 & 10.5 & 10.7492 & -0.249223 \tabularnewline
82 & 13.4 & 10.321 & 3.07902 \tabularnewline
83 & 10.9 & 11.9616 & -1.06162 \tabularnewline
84 & 4.3 & 10.226 & -5.92595 \tabularnewline
85 & 10.3 & 10.5098 & -0.209769 \tabularnewline
86 & 11.8 & 11.863 & -0.0629904 \tabularnewline
87 & 11.2 & 10.2985 & 0.9015 \tabularnewline
88 & 11.4 & 10.8866 & 0.513421 \tabularnewline
89 & 8.6 & 10.4213 & -1.82128 \tabularnewline
90 & 13.2 & 11.127 & 2.07298 \tabularnewline
91 & 12.6 & 10.5798 & 2.02019 \tabularnewline
92 & 5.6 & 11.2564 & -5.65641 \tabularnewline
93 & 9.9 & 11.5429 & -1.64291 \tabularnewline
94 & 8.8 & 11.9833 & -3.1833 \tabularnewline
95 & 7.7 & 11.6383 & -3.93825 \tabularnewline
96 & 9 & 10.3973 & -1.39727 \tabularnewline
97 & 7.3 & 12.568 & -5.26797 \tabularnewline
98 & 11.4 & 11.1716 & 0.228431 \tabularnewline
99 & 13.6 & 11.8943 & 1.70569 \tabularnewline
100 & 7.9 & 10.8443 & -2.94427 \tabularnewline
101 & 10.7 & 11.02 & -0.319992 \tabularnewline
102 & 10.3 & 11.5814 & -1.28142 \tabularnewline
103 & 8.3 & 9.92186 & -1.62186 \tabularnewline
104 & 9.6 & 10.7102 & -1.11025 \tabularnewline
105 & 14.2 & 11.8733 & 2.32668 \tabularnewline
106 & 8.5 & 9.85033 & -1.35033 \tabularnewline
107 & 13.5 & 10.2231 & 3.27691 \tabularnewline
108 & 4.9 & 10.5812 & -5.68123 \tabularnewline
109 & 6.4 & 10.2355 & -3.83549 \tabularnewline
110 & 9.6 & 10.6334 & -1.03345 \tabularnewline
111 & 11.6 & 10.7528 & 0.847226 \tabularnewline
112 & 11.1 & 10.5851 & 0.514885 \tabularnewline
113 & 4.4 & 9.90451 & -5.50451 \tabularnewline
114 & 12.7 & 12.6754 & 0.0246362 \tabularnewline
115 & 18.1 & 14.6659 & 3.43407 \tabularnewline
116 & 17.9 & 15.1862 & 2.71379 \tabularnewline
117 & 16.6 & 16.8735 & -0.273479 \tabularnewline
118 & 12.6 & 9.73693 & 2.86307 \tabularnewline
119 & 17.1 & 22.399 & -5.29898 \tabularnewline
120 & 19.1 & 15.6036 & 3.49638 \tabularnewline
121 & 16.1 & 18.8569 & -2.75689 \tabularnewline
122 & 13.4 & 10.5057 & 2.89432 \tabularnewline
123 & 18.4 & 17.6949 & 0.705072 \tabularnewline
124 & 14.7 & 10.9959 & 3.70408 \tabularnewline
125 & 10.6 & 14.5321 & -3.93212 \tabularnewline
126 & 12.6 & 13.265 & -0.664956 \tabularnewline
127 & 16.2 & 14.9492 & 1.25079 \tabularnewline
128 & 13.6 & 16.6053 & -3.00527 \tabularnewline
129 & 18.9 & 15.6426 & 3.25739 \tabularnewline
130 & 14.1 & 12.3223 & 1.77768 \tabularnewline
131 & 14.5 & 11.938 & 2.56197 \tabularnewline
132 & 16.2 & 17.8272 & -1.62715 \tabularnewline
133 & 14.8 & 13.3576 & 1.44236 \tabularnewline
134 & 14.8 & 13.8145 & 0.985503 \tabularnewline
135 & 12.5 & 12.143 & 0.356966 \tabularnewline
136 & 12.7 & 14.4909 & -1.79094 \tabularnewline
137 & 17.4 & 13.7805 & 3.61946 \tabularnewline
138 & 8.6 & 11.8501 & -3.2501 \tabularnewline
139 & 18.4 & 17.8357 & 0.564273 \tabularnewline
140 & 16.1 & 17.8875 & -1.78749 \tabularnewline
141 & 11.6 & 11.4723 & 0.127694 \tabularnewline
142 & 17.8 & 11.7936 & 6.00636 \tabularnewline
143 & 15.3 & 12.7591 & 2.54091 \tabularnewline
144 & 17.7 & 16.2525 & 1.44748 \tabularnewline
145 & 16.4 & 15.1026 & 1.29735 \tabularnewline
146 & 17.7 & 15.067 & 2.63303 \tabularnewline
147 & 13.6 & 12.5325 & 1.06754 \tabularnewline
148 & 14.4 & 13.1717 & 1.22825 \tabularnewline
149 & 14.8 & 16.9578 & -2.15785 \tabularnewline
150 & 18.3 & 16.39 & 1.90999 \tabularnewline
151 & 9.9 & 14.9744 & -5.07441 \tabularnewline
152 & 16 & 14.2715 & 1.72845 \tabularnewline
153 & 18.3 & 15.6842 & 2.6158 \tabularnewline
154 & 16.9 & 17.2162 & -0.316209 \tabularnewline
155 & 14.6 & 12.6333 & 1.96665 \tabularnewline
156 & 13.9 & 13.89 & 0.010037 \tabularnewline
157 & 19 & 16.6511 & 2.34888 \tabularnewline
158 & 15.6 & 14.6288 & 0.971243 \tabularnewline
159 & 14.9 & 17.7036 & -2.80355 \tabularnewline
160 & 11.8 & 12.0609 & -0.260926 \tabularnewline
161 & 18.5 & 13.4 & 5.10004 \tabularnewline
162 & 15.9 & 17.3155 & -1.41553 \tabularnewline
163 & 17.1 & 14.1656 & 2.93445 \tabularnewline
164 & 16.1 & 10.8511 & 5.2489 \tabularnewline
165 & 19.9 & 15.2759 & 4.62408 \tabularnewline
166 & 11 & 10.1308 & 0.869224 \tabularnewline
167 & 18.5 & 16.2539 & 2.24611 \tabularnewline
168 & 15.1 & 10.5463 & 4.55371 \tabularnewline
169 & 15 & 15.418 & -0.418017 \tabularnewline
170 & 11.4 & 14.1818 & -2.78177 \tabularnewline
171 & 16 & 15.1661 & 0.833866 \tabularnewline
172 & 18.1 & 13.2671 & 4.83286 \tabularnewline
173 & 14.6 & 13.3754 & 1.22462 \tabularnewline
174 & 15.4 & 16.2008 & -0.800779 \tabularnewline
175 & 15.4 & 16.2008 & -0.800779 \tabularnewline
176 & 17.6 & 13.5785 & 4.02154 \tabularnewline
177 & 13.4 & 13.7801 & -0.380144 \tabularnewline
178 & 19.1 & 16.5161 & 2.58393 \tabularnewline
179 & 15.4 & 13.0073 & 2.39271 \tabularnewline
180 & 7.6 & 12.3236 & -4.72363 \tabularnewline
181 & 13.4 & 14.328 & -0.927997 \tabularnewline
182 & 13.9 & 13.555 & 0.345032 \tabularnewline
183 & 19.1 & 17.4071 & 1.69292 \tabularnewline
184 & 15.3 & 13.7304 & 1.56962 \tabularnewline
185 & 12.9 & 11.9957 & 0.904255 \tabularnewline
186 & 16.1 & 14.0679 & 2.03214 \tabularnewline
187 & 17.4 & 12.4167 & 4.98333 \tabularnewline
188 & 13.2 & 12.5279 & 0.672132 \tabularnewline
189 & 12.2 & 9.75093 & 2.44907 \tabularnewline
190 & 12.6 & 12.4564 & 0.143634 \tabularnewline
191 & 10.4 & 11.7024 & -1.3024 \tabularnewline
192 & 15.4 & 12.2539 & 3.14606 \tabularnewline
193 & 9.6 & 10.7706 & -1.17063 \tabularnewline
194 & 18.2 & 12.7603 & 5.43971 \tabularnewline
195 & 13.6 & 12.1035 & 1.49654 \tabularnewline
196 & 14.9 & 14.9337 & -0.033719 \tabularnewline
197 & 14.8 & 17.2453 & -2.44526 \tabularnewline
198 & 14.1 & 12.9481 & 1.15192 \tabularnewline
199 & 14.9 & 10.9431 & 3.95693 \tabularnewline
200 & 16.3 & 12.6589 & 3.6411 \tabularnewline
201 & 19.3 & 17.405 & 1.89503 \tabularnewline
202 & 13.6 & 11.9611 & 1.63885 \tabularnewline
203 & 13.6 & 13.1094 & 0.490591 \tabularnewline
204 & 15.7 & 15.0618 & 0.638153 \tabularnewline
205 & 12.8 & 12.1477 & 0.652253 \tabularnewline
206 & 14.6 & 10.9517 & 3.64833 \tabularnewline
207 & 9.9 & 12.8962 & -2.99623 \tabularnewline
208 & 12.7 & 11.2087 & 1.49127 \tabularnewline
209 & 19.2 & 15.9855 & 3.21451 \tabularnewline
210 & 16.6 & 14.4246 & 2.17544 \tabularnewline
211 & 11.2 & 10.1247 & 1.07533 \tabularnewline
212 & 15.3 & 12.9606 & 2.33936 \tabularnewline
213 & 11.9 & 14.7075 & -2.80748 \tabularnewline
214 & 13.2 & 15.8875 & -2.68751 \tabularnewline
215 & 16.4 & 17.5644 & -1.1644 \tabularnewline
216 & 12.4 & 12.8699 & -0.46987 \tabularnewline
217 & 15.9 & 12.7278 & 3.1722 \tabularnewline
218 & 18.2 & 14.957 & 3.243 \tabularnewline
219 & 11.2 & 11.5449 & -0.344872 \tabularnewline
220 & 15.7 & 15.8921 & -0.192113 \tabularnewline
221 & 17.8 & 15.8533 & 1.94669 \tabularnewline
222 & 7.7 & 12.0198 & -4.31976 \tabularnewline
223 & 12.4 & 12.0641 & 0.335929 \tabularnewline
224 & 15.6 & 11.3263 & 4.27366 \tabularnewline
225 & 19.3 & 16.1966 & 3.10337 \tabularnewline
226 & 15.2 & 11.8941 & 3.30589 \tabularnewline
227 & 17.1 & 13.1063 & 3.99372 \tabularnewline
228 & 15.6 & 12.4513 & 3.14873 \tabularnewline
229 & 18.4 & 15.2545 & 3.14549 \tabularnewline
230 & 19.1 & 15.0765 & 4.02347 \tabularnewline
231 & 18.6 & 12.162 & 6.43802 \tabularnewline
232 & 19.1 & 17.0909 & 2.00911 \tabularnewline
233 & 13.1 & 11.7621 & 1.33789 \tabularnewline
234 & 12.9 & 12.9567 & -0.0566627 \tabularnewline
235 & 9.5 & 10.4556 & -0.95558 \tabularnewline
236 & 4.5 & 11.2102 & -6.71024 \tabularnewline
237 & 11.9 & 10.7449 & 1.15511 \tabularnewline
238 & 13.6 & 15.4927 & -1.89268 \tabularnewline
239 & 11.7 & 12.4881 & -0.788052 \tabularnewline
240 & 12.4 & 10.839 & 1.56099 \tabularnewline
241 & 13.4 & 15.0756 & -1.67563 \tabularnewline
242 & 11.4 & 13.5629 & -2.16287 \tabularnewline
243 & 14.9 & 11.4001 & 3.49989 \tabularnewline
244 & 19.9 & 15.2759 & 4.62408 \tabularnewline
245 & 11.2 & 11.9455 & -0.745463 \tabularnewline
246 & 14.6 & 15.5985 & -0.998504 \tabularnewline
247 & 17.6 & 15.9659 & 1.63409 \tabularnewline
248 & 14.1 & 12.2404 & 1.8596 \tabularnewline
249 & 16.1 & 15.6156 & 0.484444 \tabularnewline
250 & 13.4 & 12.9967 & 0.403316 \tabularnewline
251 & 11.9 & 12.3523 & -0.452273 \tabularnewline
252 & 12 & 14.3571 & -2.35707 \tabularnewline
253 & 14.8 & 14.76 & 0.0400237 \tabularnewline
254 & 15.2 & 12.8915 & 2.30848 \tabularnewline
255 & 13.2 & 14.1467 & -0.946657 \tabularnewline
256 & 16.9 & 15.6529 & 1.24714 \tabularnewline
257 & 7.9 & 10.0477 & -2.1477 \tabularnewline
258 & 7.7 & 14.5704 & -6.87041 \tabularnewline
259 & 12.6 & 11.5208 & 1.0792 \tabularnewline
260 & 7.9 & 11.0595 & -3.15953 \tabularnewline
261 & 11 & 10.1308 & 0.869224 \tabularnewline
262 & 12.4 & 12.4523 & -0.0523117 \tabularnewline
263 & 10 & 11.6628 & -1.66285 \tabularnewline
264 & 14.9 & 11.4001 & 3.49989 \tabularnewline
265 & 16.7 & 14.2849 & 2.41514 \tabularnewline
266 & 13.4 & 13.1662 & 0.23384 \tabularnewline
267 & 14 & 13.2316 & 0.768449 \tabularnewline
268 & 15.7 & 10.8871 & 4.81288 \tabularnewline
269 & 16.9 & 12.5709 & 4.32909 \tabularnewline
270 & 11 & 10.3582 & 0.641786 \tabularnewline
271 & 15.4 & 11.2872 & 4.11285 \tabularnewline
272 & 12.2 & 10.9317 & 1.26835 \tabularnewline
273 & 15.1 & 13.1619 & 1.93814 \tabularnewline
274 & 17.8 & 16.6732 & 1.12682 \tabularnewline
275 & 15.2 & 12.723 & 2.47698 \tabularnewline
276 & 14.6 & 13.2502 & 1.34984 \tabularnewline
277 & 16.7 & 14.9188 & 1.78115 \tabularnewline
278 & 8.1 & 11.1166 & -3.01664 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270372&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]12.4258[/C][C]0.47421[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]11.9034[/C][C]0.296647[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]12.2301[/C][C]0.569909[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.6804[/C][C]-5.28044[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]11.565[/C][C]-4.86496[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]14.8645[/C][C]-2.26448[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.8294[/C][C]1.97058[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]12.5775[/C][C]0.722494[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.4692[/C][C]-1.36922[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.0344[/C][C]-5.83435[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]13.1136[/C][C]-1.71357[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.3577[/C][C]-7.95768[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.6088[/C][C]-1.00876[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.5348[/C][C]-1.53482[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]9.74986[/C][C]-3.44986[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]10.9856[/C][C]0.314407[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]13.8465[/C][C]-1.94652[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.1187[/C][C]-2.8187[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.3602[/C][C]-2.76018[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]11.4853[/C][C]-1.48528[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]11.2646[/C][C]-4.86456[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.4133[/C][C]1.38671[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]13.3288[/C][C]-2.5288[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.5494[/C][C]1.25058[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]12.9136[/C][C]-1.21362[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]14.7689[/C][C]-3.86885[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.6939[/C][C]2.40607[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]11.1508[/C][C]2.24923[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.6449[/C][C]-1.74493[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.0054[/C][C]-0.505372[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.7958[/C][C]-3.49582[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.2385[/C][C]-1.53849[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.5648[/C][C]-3.56476[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]13.9236[/C][C]-4.22356[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.5694[/C][C]-1.76941[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.8088[/C][C]-2.50881[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.6266[/C][C]-1.22663[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.0599[/C][C]0.640056[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]12.2389[/C][C]-2.93891[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.8015[/C][C]-3.00152[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.8261[/C][C]-4.92607[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]14.0183[/C][C]-2.61829[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.9511[/C][C]1.04892[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.93[/C][C]-2.12998[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]10.2997[/C][C]2.00029[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.7698[/C][C]-2.46984[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.3133[/C][C]-0.513288[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]10.9095[/C][C]-3.00947[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.4449[/C][C]2.25512[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]10.9506[/C][C]1.34935[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.184[/C][C]-0.583971[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.9188[/C][C]-4.21877[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.0688[/C][C]-2.16876[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.5168[/C][C]-0.416796[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.1471[/C][C]0.152875[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.7451[/C][C]-3.64512[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.71[/C][C]-6.00997[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]11.9628[/C][C]2.33721[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]9.03533[/C][C]-1.03533[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.2427[/C][C]1.05727[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.4[/C][C]-4.10002[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.7624[/C][C]0.737613[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]11.2056[/C][C]-3.60557[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.8808[/C][C]2.01924[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.5283[/C][C]-2.32831[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]10.6186[/C][C]-1.51859[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]14.0064[/C][C]-2.90643[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]14.1312[/C][C]-1.13123[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.5586[/C][C]1.94138[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.9701[/C][C]1.22988[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.4844[/C][C]-1.18438[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]11.3035[/C][C]0.0965459[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.6528[/C][C]-2.85279[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.5216[/C][C]3.07836[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]13.0718[/C][C]-0.471767[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]13.5312[/C][C]-0.531158[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]11.4942[/C][C]1.10576[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]14.818[/C][C]-1.61805[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]10.736[/C][C]-0.836047[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]11.7297[/C][C]-4.02967[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]10.7492[/C][C]-0.249223[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]10.321[/C][C]3.07902[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]11.9616[/C][C]-1.06162[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]10.226[/C][C]-5.92595[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]10.5098[/C][C]-0.209769[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]11.863[/C][C]-0.0629904[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]10.2985[/C][C]0.9015[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]10.8866[/C][C]0.513421[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.4213[/C][C]-1.82128[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]11.127[/C][C]2.07298[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]10.5798[/C][C]2.02019[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]11.2564[/C][C]-5.65641[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]11.5429[/C][C]-1.64291[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]11.9833[/C][C]-3.1833[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]11.6383[/C][C]-3.93825[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]10.3973[/C][C]-1.39727[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]12.568[/C][C]-5.26797[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]11.1716[/C][C]0.228431[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]11.8943[/C][C]1.70569[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]10.8443[/C][C]-2.94427[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]11.02[/C][C]-0.319992[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]11.5814[/C][C]-1.28142[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]9.92186[/C][C]-1.62186[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]10.7102[/C][C]-1.11025[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]11.8733[/C][C]2.32668[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]9.85033[/C][C]-1.35033[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]10.2231[/C][C]3.27691[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]10.5812[/C][C]-5.68123[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]10.2355[/C][C]-3.83549[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]10.6334[/C][C]-1.03345[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]10.7528[/C][C]0.847226[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]10.5851[/C][C]0.514885[/C][/ROW]
[ROW][C]113[/C][C]4.4[/C][C]9.90451[/C][C]-5.50451[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.6754[/C][C]0.0246362[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]14.6659[/C][C]3.43407[/C][/ROW]
[ROW][C]116[/C][C]17.9[/C][C]15.1862[/C][C]2.71379[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]16.8735[/C][C]-0.273479[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]9.73693[/C][C]2.86307[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]22.399[/C][C]-5.29898[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]15.6036[/C][C]3.49638[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]18.8569[/C][C]-2.75689[/C][/ROW]
[ROW][C]122[/C][C]13.4[/C][C]10.5057[/C][C]2.89432[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]17.6949[/C][C]0.705072[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]10.9959[/C][C]3.70408[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]14.5321[/C][C]-3.93212[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]13.265[/C][C]-0.664956[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]14.9492[/C][C]1.25079[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]16.6053[/C][C]-3.00527[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]15.6426[/C][C]3.25739[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]12.3223[/C][C]1.77768[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]11.938[/C][C]2.56197[/C][/ROW]
[ROW][C]132[/C][C]16.2[/C][C]17.8272[/C][C]-1.62715[/C][/ROW]
[ROW][C]133[/C][C]14.8[/C][C]13.3576[/C][C]1.44236[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]13.8145[/C][C]0.985503[/C][/ROW]
[ROW][C]135[/C][C]12.5[/C][C]12.143[/C][C]0.356966[/C][/ROW]
[ROW][C]136[/C][C]12.7[/C][C]14.4909[/C][C]-1.79094[/C][/ROW]
[ROW][C]137[/C][C]17.4[/C][C]13.7805[/C][C]3.61946[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]11.8501[/C][C]-3.2501[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]17.8357[/C][C]0.564273[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]17.8875[/C][C]-1.78749[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]11.4723[/C][C]0.127694[/C][/ROW]
[ROW][C]142[/C][C]17.8[/C][C]11.7936[/C][C]6.00636[/C][/ROW]
[ROW][C]143[/C][C]15.3[/C][C]12.7591[/C][C]2.54091[/C][/ROW]
[ROW][C]144[/C][C]17.7[/C][C]16.2525[/C][C]1.44748[/C][/ROW]
[ROW][C]145[/C][C]16.4[/C][C]15.1026[/C][C]1.29735[/C][/ROW]
[ROW][C]146[/C][C]17.7[/C][C]15.067[/C][C]2.63303[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]12.5325[/C][C]1.06754[/C][/ROW]
[ROW][C]148[/C][C]14.4[/C][C]13.1717[/C][C]1.22825[/C][/ROW]
[ROW][C]149[/C][C]14.8[/C][C]16.9578[/C][C]-2.15785[/C][/ROW]
[ROW][C]150[/C][C]18.3[/C][C]16.39[/C][C]1.90999[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]14.9744[/C][C]-5.07441[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.2715[/C][C]1.72845[/C][/ROW]
[ROW][C]153[/C][C]18.3[/C][C]15.6842[/C][C]2.6158[/C][/ROW]
[ROW][C]154[/C][C]16.9[/C][C]17.2162[/C][C]-0.316209[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]12.6333[/C][C]1.96665[/C][/ROW]
[ROW][C]156[/C][C]13.9[/C][C]13.89[/C][C]0.010037[/C][/ROW]
[ROW][C]157[/C][C]19[/C][C]16.6511[/C][C]2.34888[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]14.6288[/C][C]0.971243[/C][/ROW]
[ROW][C]159[/C][C]14.9[/C][C]17.7036[/C][C]-2.80355[/C][/ROW]
[ROW][C]160[/C][C]11.8[/C][C]12.0609[/C][C]-0.260926[/C][/ROW]
[ROW][C]161[/C][C]18.5[/C][C]13.4[/C][C]5.10004[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]17.3155[/C][C]-1.41553[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]14.1656[/C][C]2.93445[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]10.8511[/C][C]5.2489[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]15.2759[/C][C]4.62408[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]10.1308[/C][C]0.869224[/C][/ROW]
[ROW][C]167[/C][C]18.5[/C][C]16.2539[/C][C]2.24611[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]10.5463[/C][C]4.55371[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]15.418[/C][C]-0.418017[/C][/ROW]
[ROW][C]170[/C][C]11.4[/C][C]14.1818[/C][C]-2.78177[/C][/ROW]
[ROW][C]171[/C][C]16[/C][C]15.1661[/C][C]0.833866[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]13.2671[/C][C]4.83286[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]13.3754[/C][C]1.22462[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]16.2008[/C][C]-0.800779[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.2008[/C][C]-0.800779[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]13.5785[/C][C]4.02154[/C][/ROW]
[ROW][C]177[/C][C]13.4[/C][C]13.7801[/C][C]-0.380144[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]16.5161[/C][C]2.58393[/C][/ROW]
[ROW][C]179[/C][C]15.4[/C][C]13.0073[/C][C]2.39271[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]12.3236[/C][C]-4.72363[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]14.328[/C][C]-0.927997[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]13.555[/C][C]0.345032[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]17.4071[/C][C]1.69292[/C][/ROW]
[ROW][C]184[/C][C]15.3[/C][C]13.7304[/C][C]1.56962[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]11.9957[/C][C]0.904255[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]14.0679[/C][C]2.03214[/C][/ROW]
[ROW][C]187[/C][C]17.4[/C][C]12.4167[/C][C]4.98333[/C][/ROW]
[ROW][C]188[/C][C]13.2[/C][C]12.5279[/C][C]0.672132[/C][/ROW]
[ROW][C]189[/C][C]12.2[/C][C]9.75093[/C][C]2.44907[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]12.4564[/C][C]0.143634[/C][/ROW]
[ROW][C]191[/C][C]10.4[/C][C]11.7024[/C][C]-1.3024[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]12.2539[/C][C]3.14606[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]10.7706[/C][C]-1.17063[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]12.7603[/C][C]5.43971[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]12.1035[/C][C]1.49654[/C][/ROW]
[ROW][C]196[/C][C]14.9[/C][C]14.9337[/C][C]-0.033719[/C][/ROW]
[ROW][C]197[/C][C]14.8[/C][C]17.2453[/C][C]-2.44526[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]12.9481[/C][C]1.15192[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]10.9431[/C][C]3.95693[/C][/ROW]
[ROW][C]200[/C][C]16.3[/C][C]12.6589[/C][C]3.6411[/C][/ROW]
[ROW][C]201[/C][C]19.3[/C][C]17.405[/C][C]1.89503[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]11.9611[/C][C]1.63885[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.1094[/C][C]0.490591[/C][/ROW]
[ROW][C]204[/C][C]15.7[/C][C]15.0618[/C][C]0.638153[/C][/ROW]
[ROW][C]205[/C][C]12.8[/C][C]12.1477[/C][C]0.652253[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]10.9517[/C][C]3.64833[/C][/ROW]
[ROW][C]207[/C][C]9.9[/C][C]12.8962[/C][C]-2.99623[/C][/ROW]
[ROW][C]208[/C][C]12.7[/C][C]11.2087[/C][C]1.49127[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]15.9855[/C][C]3.21451[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]14.4246[/C][C]2.17544[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]10.1247[/C][C]1.07533[/C][/ROW]
[ROW][C]212[/C][C]15.3[/C][C]12.9606[/C][C]2.33936[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]14.7075[/C][C]-2.80748[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]15.8875[/C][C]-2.68751[/C][/ROW]
[ROW][C]215[/C][C]16.4[/C][C]17.5644[/C][C]-1.1644[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]12.8699[/C][C]-0.46987[/C][/ROW]
[ROW][C]217[/C][C]15.9[/C][C]12.7278[/C][C]3.1722[/C][/ROW]
[ROW][C]218[/C][C]18.2[/C][C]14.957[/C][C]3.243[/C][/ROW]
[ROW][C]219[/C][C]11.2[/C][C]11.5449[/C][C]-0.344872[/C][/ROW]
[ROW][C]220[/C][C]15.7[/C][C]15.8921[/C][C]-0.192113[/C][/ROW]
[ROW][C]221[/C][C]17.8[/C][C]15.8533[/C][C]1.94669[/C][/ROW]
[ROW][C]222[/C][C]7.7[/C][C]12.0198[/C][C]-4.31976[/C][/ROW]
[ROW][C]223[/C][C]12.4[/C][C]12.0641[/C][C]0.335929[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]11.3263[/C][C]4.27366[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]16.1966[/C][C]3.10337[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]11.8941[/C][C]3.30589[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]13.1063[/C][C]3.99372[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]12.4513[/C][C]3.14873[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]15.2545[/C][C]3.14549[/C][/ROW]
[ROW][C]230[/C][C]19.1[/C][C]15.0765[/C][C]4.02347[/C][/ROW]
[ROW][C]231[/C][C]18.6[/C][C]12.162[/C][C]6.43802[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]17.0909[/C][C]2.00911[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]11.7621[/C][C]1.33789[/C][/ROW]
[ROW][C]234[/C][C]12.9[/C][C]12.9567[/C][C]-0.0566627[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]10.4556[/C][C]-0.95558[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]11.2102[/C][C]-6.71024[/C][/ROW]
[ROW][C]237[/C][C]11.9[/C][C]10.7449[/C][C]1.15511[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]15.4927[/C][C]-1.89268[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]12.4881[/C][C]-0.788052[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]10.839[/C][C]1.56099[/C][/ROW]
[ROW][C]241[/C][C]13.4[/C][C]15.0756[/C][C]-1.67563[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]13.5629[/C][C]-2.16287[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]11.4001[/C][C]3.49989[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]15.2759[/C][C]4.62408[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]11.9455[/C][C]-0.745463[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]15.5985[/C][C]-0.998504[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]15.9659[/C][C]1.63409[/C][/ROW]
[ROW][C]248[/C][C]14.1[/C][C]12.2404[/C][C]1.8596[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]15.6156[/C][C]0.484444[/C][/ROW]
[ROW][C]250[/C][C]13.4[/C][C]12.9967[/C][C]0.403316[/C][/ROW]
[ROW][C]251[/C][C]11.9[/C][C]12.3523[/C][C]-0.452273[/C][/ROW]
[ROW][C]252[/C][C]12[/C][C]14.3571[/C][C]-2.35707[/C][/ROW]
[ROW][C]253[/C][C]14.8[/C][C]14.76[/C][C]0.0400237[/C][/ROW]
[ROW][C]254[/C][C]15.2[/C][C]12.8915[/C][C]2.30848[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]14.1467[/C][C]-0.946657[/C][/ROW]
[ROW][C]256[/C][C]16.9[/C][C]15.6529[/C][C]1.24714[/C][/ROW]
[ROW][C]257[/C][C]7.9[/C][C]10.0477[/C][C]-2.1477[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]14.5704[/C][C]-6.87041[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]11.5208[/C][C]1.0792[/C][/ROW]
[ROW][C]260[/C][C]7.9[/C][C]11.0595[/C][C]-3.15953[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.1308[/C][C]0.869224[/C][/ROW]
[ROW][C]262[/C][C]12.4[/C][C]12.4523[/C][C]-0.0523117[/C][/ROW]
[ROW][C]263[/C][C]10[/C][C]11.6628[/C][C]-1.66285[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]11.4001[/C][C]3.49989[/C][/ROW]
[ROW][C]265[/C][C]16.7[/C][C]14.2849[/C][C]2.41514[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]13.1662[/C][C]0.23384[/C][/ROW]
[ROW][C]267[/C][C]14[/C][C]13.2316[/C][C]0.768449[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]10.8871[/C][C]4.81288[/C][/ROW]
[ROW][C]269[/C][C]16.9[/C][C]12.5709[/C][C]4.32909[/C][/ROW]
[ROW][C]270[/C][C]11[/C][C]10.3582[/C][C]0.641786[/C][/ROW]
[ROW][C]271[/C][C]15.4[/C][C]11.2872[/C][C]4.11285[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]10.9317[/C][C]1.26835[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]13.1619[/C][C]1.93814[/C][/ROW]
[ROW][C]274[/C][C]17.8[/C][C]16.6732[/C][C]1.12682[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]12.723[/C][C]2.47698[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]13.2502[/C][C]1.34984[/C][/ROW]
[ROW][C]277[/C][C]16.7[/C][C]14.9188[/C][C]1.78115[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]11.1166[/C][C]-3.01664[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270372&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270372&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
112.912.42580.47421
212.211.90340.296647
312.812.23010.569909
47.412.6804-5.28044
56.711.565-4.86496
612.614.8645-2.26448
714.812.82941.97058
813.312.57750.722494
911.112.4692-1.36922
108.214.0344-5.83435
1111.413.1136-1.71357
126.414.3577-7.95768
1310.611.6088-1.00876
141213.5348-1.53482
156.39.74986-3.44986
1611.310.98560.314407
1711.913.8465-1.94652
189.312.1187-2.8187
199.612.3602-2.76018
201011.4853-1.48528
216.411.2646-4.86456
2213.812.41331.38671
2310.813.3288-2.5288
2413.812.54941.25058
2511.712.9136-1.21362
2610.914.7689-3.86885
2716.113.69392.40607
2813.411.15082.24923
299.911.6449-1.74493
3011.512.0054-0.505372
318.311.7958-3.49582
3211.713.2385-1.53849
33912.5648-3.56476
349.713.9236-4.22356
3510.812.5694-1.76941
3610.312.8088-2.50881
3710.411.6266-1.22663
3812.712.05990.640056
399.312.2389-2.93891
4011.814.8015-3.00152
415.910.8261-4.92607
4211.414.0183-2.61829
431311.95111.04892
4410.812.93-2.12998
4512.310.29972.00029
4611.313.7698-2.46984
4711.812.3133-0.513288
487.910.9095-3.00947
4912.710.44492.25512
5012.310.95061.34935
5111.612.184-0.583971
526.710.9188-4.21877
5310.913.0688-2.16876
5412.112.5168-0.416796
5513.313.14710.152875
5610.113.7451-3.64512
575.711.71-6.00997
5814.311.96282.33721
5989.03533-1.03533
6013.312.24271.05727
619.313.4-4.10002
6212.511.76240.737613
637.611.2056-3.60557
6415.913.88082.01924
659.211.5283-2.32831
669.110.6186-1.51859
6711.114.0064-2.90643
681314.1312-1.13123
6914.512.55861.94138
7012.210.97011.22988
7112.313.4844-1.18438
7211.411.30350.0965459
738.811.6528-2.85279
7414.611.52163.07836
7512.613.0718-0.471767
761313.5312-0.531158
7712.611.49421.10576
7813.214.818-1.61805
799.910.736-0.836047
807.711.7297-4.02967
8110.510.7492-0.249223
8213.410.3213.07902
8310.911.9616-1.06162
844.310.226-5.92595
8510.310.5098-0.209769
8611.811.863-0.0629904
8711.210.29850.9015
8811.410.88660.513421
898.610.4213-1.82128
9013.211.1272.07298
9112.610.57982.02019
925.611.2564-5.65641
939.911.5429-1.64291
948.811.9833-3.1833
957.711.6383-3.93825
96910.3973-1.39727
977.312.568-5.26797
9811.411.17160.228431
9913.611.89431.70569
1007.910.8443-2.94427
10110.711.02-0.319992
10210.311.5814-1.28142
1038.39.92186-1.62186
1049.610.7102-1.11025
10514.211.87332.32668
1068.59.85033-1.35033
10713.510.22313.27691
1084.910.5812-5.68123
1096.410.2355-3.83549
1109.610.6334-1.03345
11111.610.75280.847226
11211.110.58510.514885
1134.49.90451-5.50451
11412.712.67540.0246362
11518.114.66593.43407
11617.915.18622.71379
11716.616.8735-0.273479
11812.69.736932.86307
11917.122.399-5.29898
12019.115.60363.49638
12116.118.8569-2.75689
12213.410.50572.89432
12318.417.69490.705072
12414.710.99593.70408
12510.614.5321-3.93212
12612.613.265-0.664956
12716.214.94921.25079
12813.616.6053-3.00527
12918.915.64263.25739
13014.112.32231.77768
13114.511.9382.56197
13216.217.8272-1.62715
13314.813.35761.44236
13414.813.81450.985503
13512.512.1430.356966
13612.714.4909-1.79094
13717.413.78053.61946
1388.611.8501-3.2501
13918.417.83570.564273
14016.117.8875-1.78749
14111.611.47230.127694
14217.811.79366.00636
14315.312.75912.54091
14417.716.25251.44748
14516.415.10261.29735
14617.715.0672.63303
14713.612.53251.06754
14814.413.17171.22825
14914.816.9578-2.15785
15018.316.391.90999
1519.914.9744-5.07441
1521614.27151.72845
15318.315.68422.6158
15416.917.2162-0.316209
15514.612.63331.96665
15613.913.890.010037
1571916.65112.34888
15815.614.62880.971243
15914.917.7036-2.80355
16011.812.0609-0.260926
16118.513.45.10004
16215.917.3155-1.41553
16317.114.16562.93445
16416.110.85115.2489
16519.915.27594.62408
1661110.13080.869224
16718.516.25392.24611
16815.110.54634.55371
1691515.418-0.418017
17011.414.1818-2.78177
1711615.16610.833866
17218.113.26714.83286
17314.613.37541.22462
17415.416.2008-0.800779
17515.416.2008-0.800779
17617.613.57854.02154
17713.413.7801-0.380144
17819.116.51612.58393
17915.413.00732.39271
1807.612.3236-4.72363
18113.414.328-0.927997
18213.913.5550.345032
18319.117.40711.69292
18415.313.73041.56962
18512.911.99570.904255
18616.114.06792.03214
18717.412.41674.98333
18813.212.52790.672132
18912.29.750932.44907
19012.612.45640.143634
19110.411.7024-1.3024
19215.412.25393.14606
1939.610.7706-1.17063
19418.212.76035.43971
19513.612.10351.49654
19614.914.9337-0.033719
19714.817.2453-2.44526
19814.112.94811.15192
19914.910.94313.95693
20016.312.65893.6411
20119.317.4051.89503
20213.611.96111.63885
20313.613.10940.490591
20415.715.06180.638153
20512.812.14770.652253
20614.610.95173.64833
2079.912.8962-2.99623
20812.711.20871.49127
20919.215.98553.21451
21016.614.42462.17544
21111.210.12471.07533
21215.312.96062.33936
21311.914.7075-2.80748
21413.215.8875-2.68751
21516.417.5644-1.1644
21612.412.8699-0.46987
21715.912.72783.1722
21818.214.9573.243
21911.211.5449-0.344872
22015.715.8921-0.192113
22117.815.85331.94669
2227.712.0198-4.31976
22312.412.06410.335929
22415.611.32634.27366
22519.316.19663.10337
22615.211.89413.30589
22717.113.10633.99372
22815.612.45133.14873
22918.415.25453.14549
23019.115.07654.02347
23118.612.1626.43802
23219.117.09092.00911
23313.111.76211.33789
23412.912.9567-0.0566627
2359.510.4556-0.95558
2364.511.2102-6.71024
23711.910.74491.15511
23813.615.4927-1.89268
23911.712.4881-0.788052
24012.410.8391.56099
24113.415.0756-1.67563
24211.413.5629-2.16287
24314.911.40013.49989
24419.915.27594.62408
24511.211.9455-0.745463
24614.615.5985-0.998504
24717.615.96591.63409
24814.112.24041.8596
24916.115.61560.484444
25013.412.99670.403316
25111.912.3523-0.452273
2521214.3571-2.35707
25314.814.760.0400237
25415.212.89152.30848
25513.214.1467-0.946657
25616.915.65291.24714
2577.910.0477-2.1477
2587.714.5704-6.87041
25912.611.52081.0792
2607.911.0595-3.15953
2611110.13080.869224
26212.412.4523-0.0523117
2631011.6628-1.66285
26414.911.40013.49989
26516.714.28492.41514
26613.413.16620.23384
2671413.23160.768449
26815.710.88714.81288
26916.912.57094.32909
2701110.35820.641786
27115.411.28724.11285
27212.210.93171.26835
27315.113.16191.93814
27417.816.67321.12682
27515.212.7232.47698
27614.613.25021.34984
27716.714.91881.78115
2788.111.1166-3.01664






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.5474980.9050050.452502
110.4153580.8307160.584642
120.3005090.6010180.699491
130.3864610.7729220.613539
140.2769740.5539490.723026
150.2057590.4115180.794241
160.7036530.5926940.296347
170.6357530.7284950.364247
180.5527810.8944380.447219
190.4980450.9960890.501955
200.4226480.8452960.577352
210.3808460.7616930.619154
220.3182880.6365750.681712
230.2571980.5143950.742802
240.2018490.4036980.798151
250.15430.3085990.8457
260.122910.245820.87709
270.09235220.1847040.907648
280.1875330.3750660.812467
290.1567240.3134480.843276
300.1658180.3316370.834182
310.1374170.2748330.862583
320.1314960.2629910.868504
330.1134030.2268070.886597
340.1130880.2261760.886912
350.09160960.1832190.90839
360.07272030.1454410.92728
370.05514380.1102880.944856
380.08473590.1694720.915264
390.1074610.2149220.892539
400.0875530.1751060.912447
410.141490.282980.85851
420.1180730.2361470.881927
430.09719850.1943970.902802
440.08137040.1627410.91863
450.09630560.1926110.903694
460.08446540.1689310.915535
470.07437160.1487430.925628
480.08846890.1769380.911531
490.08687080.1737420.913129
500.08430930.1686190.915691
510.07140720.1428140.928593
520.07732930.1546590.922671
530.07061080.1412220.929389
540.0712280.1424560.928772
550.07901570.1580310.920984
560.06871650.1374330.931284
570.1287110.2574220.871289
580.1560490.3120990.843951
590.1323310.2646620.867669
600.1313710.2627420.868629
610.1526060.3052110.847394
620.1351660.2703310.864834
630.150930.301860.84907
640.1917270.3834540.808273
650.189690.379380.81031
660.1670250.334050.832975
670.1672140.3344270.832786
680.156440.312880.84356
690.1653670.3307340.834633
700.1533170.3066350.846683
710.1410990.2821990.858901
720.1234680.2469350.876532
730.1133750.2267510.886625
740.1113420.2226830.888658
750.1025230.2050460.897477
760.09712670.1942530.902873
770.08637460.1727490.913625
780.08432890.1686580.915671
790.0712530.1425060.928747
800.09192840.1838570.908072
810.07773550.1554710.922264
820.09106310.1821260.908937
830.0781460.1562920.921854
840.168790.337580.83121
850.1525970.3051940.847403
860.1353120.2706240.864688
870.1180010.2360030.881999
880.1023050.204610.897695
890.09887050.1977410.901129
900.09733930.1946790.902661
910.1064180.2128360.893582
920.1837990.3675970.816201
930.1767310.3534620.823269
940.1737110.3474210.826289
950.1926160.3852310.807384
960.185590.3711810.81441
970.2592910.5185820.740709
980.2420930.4841860.757907
990.2533240.5066480.746676
1000.3232940.6465880.676706
1010.3015130.6030260.698487
1020.2852620.5705230.714738
1030.2831050.566210.716895
1040.2874220.5748440.712578
1050.3177160.6354330.682284
1060.3254010.6508030.674599
1070.3381580.6763160.661842
1080.5252820.9494360.474718
1090.5683050.863390.431695
1100.5640710.8718580.435929
1110.5558430.8883140.444157
1120.5279850.9440290.472015
1130.6705350.658930.329465
1140.6708150.658370.329185
1150.79060.4187990.2094
1160.8454440.3091120.154556
1170.8261390.3477210.173861
1180.845710.3085790.15429
1190.8537930.2924140.146207
1200.8760020.2479970.123998
1210.8827690.2344620.117231
1220.8922150.2155690.107785
1230.889290.221420.11071
1240.9265180.1469640.0734822
1250.9372830.1254340.0627169
1260.9276450.1447090.0723545
1270.9345870.1308260.0654128
1280.9385890.1228210.0614107
1290.9448860.1102280.055114
1300.9430250.1139510.0569755
1310.9467080.1065840.0532919
1320.9471550.1056910.0528453
1330.9453010.1093990.0546994
1340.942130.1157410.0578704
1350.9323710.1352580.067629
1360.9229140.1541730.0770865
1370.9455670.1088670.0544333
1380.9434170.1131660.056583
1390.9368230.1263540.0631769
1400.9274130.1451730.0725867
1410.9148960.1702080.085104
1420.9538480.0923040.046152
1430.9530370.09392570.0469628
1440.9522220.09555590.047778
1450.947150.10570.0528498
1460.9476350.104730.0523649
1470.9410120.1179760.058988
1480.9332810.1334390.0667194
1490.9237620.1524760.0762378
1500.9190730.1618540.0809272
1510.9683550.063290.031645
1520.967310.06538040.0326902
1530.9677710.06445760.0322288
1540.9616240.07675220.0383761
1550.962260.07547960.0377398
1560.9551240.08975120.0448756
1570.9534080.0931840.046592
1580.9458230.1083540.054177
1590.9443380.1113250.0556624
1600.9356530.1286940.0643469
1610.9550830.08983450.0449173
1620.9462930.1074140.0537068
1630.9459060.1081870.0540937
1640.9877920.02441680.0122084
1650.9890150.02196970.0109848
1660.986190.02761990.0138099
1670.9853270.02934620.0146731
1680.9897070.0205860.010293
1690.9869590.02608170.0130408
1700.9871350.02572910.0128645
1710.9848650.03026960.0151348
1720.9896520.02069670.0103483
1730.9881190.02376280.0118814
1740.9859270.02814690.0140734
1750.98360.03280060.0164003
1760.9870940.02581250.0129062
1770.9846890.03062160.0153108
1780.9840930.03181380.0159069
1790.9818560.03628870.0181444
1800.9883080.02338420.0116921
1810.9871640.02567110.0128356
1820.9860310.02793740.0139687
1830.9833860.03322780.0166139
1840.9803840.03923130.0196156
1850.9802740.03945140.0197257
1860.9773220.04535670.0226783
1870.9862720.02745650.0137282
1880.9834390.03312150.0165607
1890.9805910.03881750.0194087
1900.9757090.04858110.0242906
1910.9720630.05587440.0279372
1920.9716090.05678270.0283913
1930.9660120.06797660.0339883
1940.9796970.04060680.0203034
1950.9760660.04786760.0239338
1960.9718610.05627870.0281394
1970.977540.0449210.0224605
1980.9728340.05433110.0271655
1990.9744320.05113620.0255681
2000.9742220.05155630.0257782
2010.9707620.05847570.0292378
2020.9673320.06533540.0326677
2030.9644120.07117570.0355879
2040.9559440.08811140.0440557
2050.9457710.1084590.0542294
2060.9572160.08556780.0427839
2070.9513680.09726320.0486316
2080.9460340.1079320.0539658
2090.9411050.117790.058895
2100.9336680.1326650.0663323
2110.9262990.1474010.0737007
2120.9154520.1690960.0845478
2130.9386250.122750.0613752
2140.929630.140740.0703702
2150.9243740.1512520.0756259
2160.9098580.1802850.0901423
2170.9064870.1870250.0935126
2180.8956870.2086260.104313
2190.8740080.2519840.125992
2200.8492030.3015940.150797
2210.8249670.3500660.175033
2220.8305050.338990.169495
2230.8011870.3976260.198813
2240.8101570.3796850.189843
2250.7915490.4169030.208451
2260.8422560.3154870.157744
2270.8938460.2123080.106154
2280.8925360.2149290.107464
2290.8901990.2196020.109801
2300.9121230.1757540.0878771
2310.9309910.1380180.0690088
2320.9138390.1723210.0861605
2330.9013470.1973060.0986531
2340.8877790.2244420.112221
2350.8618630.2762730.138137
2360.9540370.09192690.0459635
2370.9571510.08569860.0428493
2380.9716640.05667120.0283356
2390.9611290.07774240.0388712
2400.9494360.1011280.0505642
2410.9348450.1303110.0651555
2420.9172780.1654450.0827223
2430.9119430.1761150.0880574
2440.895290.209420.10471
2450.8668910.2662190.133109
2460.8508160.2983680.149184
2470.8176160.3647670.182384
2480.796350.40730.20365
2490.7486820.5026360.251318
2500.6930790.6138430.306921
2510.6380850.723830.361915
2520.5971720.8056560.402828
2530.5282020.9435950.471798
2540.4666830.9333660.533317
2550.503290.9934210.49671
2560.4309630.8619270.569037
2570.3876560.7753110.612344
2580.878290.2434210.12171
2590.8401110.3197780.159889
2600.9890080.02198460.0109923
2610.9908360.01832860.0091643
2620.9817720.03645560.0182278
2630.9989320.0021350.0010675
2640.9967650.006469110.00323456
2650.9916430.01671420.00835711
2660.9833350.03332930.0166647
2670.9612530.07749440.0387472
2680.9019760.1960490.0980244

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.547498 & 0.905005 & 0.452502 \tabularnewline
11 & 0.415358 & 0.830716 & 0.584642 \tabularnewline
12 & 0.300509 & 0.601018 & 0.699491 \tabularnewline
13 & 0.386461 & 0.772922 & 0.613539 \tabularnewline
14 & 0.276974 & 0.553949 & 0.723026 \tabularnewline
15 & 0.205759 & 0.411518 & 0.794241 \tabularnewline
16 & 0.703653 & 0.592694 & 0.296347 \tabularnewline
17 & 0.635753 & 0.728495 & 0.364247 \tabularnewline
18 & 0.552781 & 0.894438 & 0.447219 \tabularnewline
19 & 0.498045 & 0.996089 & 0.501955 \tabularnewline
20 & 0.422648 & 0.845296 & 0.577352 \tabularnewline
21 & 0.380846 & 0.761693 & 0.619154 \tabularnewline
22 & 0.318288 & 0.636575 & 0.681712 \tabularnewline
23 & 0.257198 & 0.514395 & 0.742802 \tabularnewline
24 & 0.201849 & 0.403698 & 0.798151 \tabularnewline
25 & 0.1543 & 0.308599 & 0.8457 \tabularnewline
26 & 0.12291 & 0.24582 & 0.87709 \tabularnewline
27 & 0.0923522 & 0.184704 & 0.907648 \tabularnewline
28 & 0.187533 & 0.375066 & 0.812467 \tabularnewline
29 & 0.156724 & 0.313448 & 0.843276 \tabularnewline
30 & 0.165818 & 0.331637 & 0.834182 \tabularnewline
31 & 0.137417 & 0.274833 & 0.862583 \tabularnewline
32 & 0.131496 & 0.262991 & 0.868504 \tabularnewline
33 & 0.113403 & 0.226807 & 0.886597 \tabularnewline
34 & 0.113088 & 0.226176 & 0.886912 \tabularnewline
35 & 0.0916096 & 0.183219 & 0.90839 \tabularnewline
36 & 0.0727203 & 0.145441 & 0.92728 \tabularnewline
37 & 0.0551438 & 0.110288 & 0.944856 \tabularnewline
38 & 0.0847359 & 0.169472 & 0.915264 \tabularnewline
39 & 0.107461 & 0.214922 & 0.892539 \tabularnewline
40 & 0.087553 & 0.175106 & 0.912447 \tabularnewline
41 & 0.14149 & 0.28298 & 0.85851 \tabularnewline
42 & 0.118073 & 0.236147 & 0.881927 \tabularnewline
43 & 0.0971985 & 0.194397 & 0.902802 \tabularnewline
44 & 0.0813704 & 0.162741 & 0.91863 \tabularnewline
45 & 0.0963056 & 0.192611 & 0.903694 \tabularnewline
46 & 0.0844654 & 0.168931 & 0.915535 \tabularnewline
47 & 0.0743716 & 0.148743 & 0.925628 \tabularnewline
48 & 0.0884689 & 0.176938 & 0.911531 \tabularnewline
49 & 0.0868708 & 0.173742 & 0.913129 \tabularnewline
50 & 0.0843093 & 0.168619 & 0.915691 \tabularnewline
51 & 0.0714072 & 0.142814 & 0.928593 \tabularnewline
52 & 0.0773293 & 0.154659 & 0.922671 \tabularnewline
53 & 0.0706108 & 0.141222 & 0.929389 \tabularnewline
54 & 0.071228 & 0.142456 & 0.928772 \tabularnewline
55 & 0.0790157 & 0.158031 & 0.920984 \tabularnewline
56 & 0.0687165 & 0.137433 & 0.931284 \tabularnewline
57 & 0.128711 & 0.257422 & 0.871289 \tabularnewline
58 & 0.156049 & 0.312099 & 0.843951 \tabularnewline
59 & 0.132331 & 0.264662 & 0.867669 \tabularnewline
60 & 0.131371 & 0.262742 & 0.868629 \tabularnewline
61 & 0.152606 & 0.305211 & 0.847394 \tabularnewline
62 & 0.135166 & 0.270331 & 0.864834 \tabularnewline
63 & 0.15093 & 0.30186 & 0.84907 \tabularnewline
64 & 0.191727 & 0.383454 & 0.808273 \tabularnewline
65 & 0.18969 & 0.37938 & 0.81031 \tabularnewline
66 & 0.167025 & 0.33405 & 0.832975 \tabularnewline
67 & 0.167214 & 0.334427 & 0.832786 \tabularnewline
68 & 0.15644 & 0.31288 & 0.84356 \tabularnewline
69 & 0.165367 & 0.330734 & 0.834633 \tabularnewline
70 & 0.153317 & 0.306635 & 0.846683 \tabularnewline
71 & 0.141099 & 0.282199 & 0.858901 \tabularnewline
72 & 0.123468 & 0.246935 & 0.876532 \tabularnewline
73 & 0.113375 & 0.226751 & 0.886625 \tabularnewline
74 & 0.111342 & 0.222683 & 0.888658 \tabularnewline
75 & 0.102523 & 0.205046 & 0.897477 \tabularnewline
76 & 0.0971267 & 0.194253 & 0.902873 \tabularnewline
77 & 0.0863746 & 0.172749 & 0.913625 \tabularnewline
78 & 0.0843289 & 0.168658 & 0.915671 \tabularnewline
79 & 0.071253 & 0.142506 & 0.928747 \tabularnewline
80 & 0.0919284 & 0.183857 & 0.908072 \tabularnewline
81 & 0.0777355 & 0.155471 & 0.922264 \tabularnewline
82 & 0.0910631 & 0.182126 & 0.908937 \tabularnewline
83 & 0.078146 & 0.156292 & 0.921854 \tabularnewline
84 & 0.16879 & 0.33758 & 0.83121 \tabularnewline
85 & 0.152597 & 0.305194 & 0.847403 \tabularnewline
86 & 0.135312 & 0.270624 & 0.864688 \tabularnewline
87 & 0.118001 & 0.236003 & 0.881999 \tabularnewline
88 & 0.102305 & 0.20461 & 0.897695 \tabularnewline
89 & 0.0988705 & 0.197741 & 0.901129 \tabularnewline
90 & 0.0973393 & 0.194679 & 0.902661 \tabularnewline
91 & 0.106418 & 0.212836 & 0.893582 \tabularnewline
92 & 0.183799 & 0.367597 & 0.816201 \tabularnewline
93 & 0.176731 & 0.353462 & 0.823269 \tabularnewline
94 & 0.173711 & 0.347421 & 0.826289 \tabularnewline
95 & 0.192616 & 0.385231 & 0.807384 \tabularnewline
96 & 0.18559 & 0.371181 & 0.81441 \tabularnewline
97 & 0.259291 & 0.518582 & 0.740709 \tabularnewline
98 & 0.242093 & 0.484186 & 0.757907 \tabularnewline
99 & 0.253324 & 0.506648 & 0.746676 \tabularnewline
100 & 0.323294 & 0.646588 & 0.676706 \tabularnewline
101 & 0.301513 & 0.603026 & 0.698487 \tabularnewline
102 & 0.285262 & 0.570523 & 0.714738 \tabularnewline
103 & 0.283105 & 0.56621 & 0.716895 \tabularnewline
104 & 0.287422 & 0.574844 & 0.712578 \tabularnewline
105 & 0.317716 & 0.635433 & 0.682284 \tabularnewline
106 & 0.325401 & 0.650803 & 0.674599 \tabularnewline
107 & 0.338158 & 0.676316 & 0.661842 \tabularnewline
108 & 0.525282 & 0.949436 & 0.474718 \tabularnewline
109 & 0.568305 & 0.86339 & 0.431695 \tabularnewline
110 & 0.564071 & 0.871858 & 0.435929 \tabularnewline
111 & 0.555843 & 0.888314 & 0.444157 \tabularnewline
112 & 0.527985 & 0.944029 & 0.472015 \tabularnewline
113 & 0.670535 & 0.65893 & 0.329465 \tabularnewline
114 & 0.670815 & 0.65837 & 0.329185 \tabularnewline
115 & 0.7906 & 0.418799 & 0.2094 \tabularnewline
116 & 0.845444 & 0.309112 & 0.154556 \tabularnewline
117 & 0.826139 & 0.347721 & 0.173861 \tabularnewline
118 & 0.84571 & 0.308579 & 0.15429 \tabularnewline
119 & 0.853793 & 0.292414 & 0.146207 \tabularnewline
120 & 0.876002 & 0.247997 & 0.123998 \tabularnewline
121 & 0.882769 & 0.234462 & 0.117231 \tabularnewline
122 & 0.892215 & 0.215569 & 0.107785 \tabularnewline
123 & 0.88929 & 0.22142 & 0.11071 \tabularnewline
124 & 0.926518 & 0.146964 & 0.0734822 \tabularnewline
125 & 0.937283 & 0.125434 & 0.0627169 \tabularnewline
126 & 0.927645 & 0.144709 & 0.0723545 \tabularnewline
127 & 0.934587 & 0.130826 & 0.0654128 \tabularnewline
128 & 0.938589 & 0.122821 & 0.0614107 \tabularnewline
129 & 0.944886 & 0.110228 & 0.055114 \tabularnewline
130 & 0.943025 & 0.113951 & 0.0569755 \tabularnewline
131 & 0.946708 & 0.106584 & 0.0532919 \tabularnewline
132 & 0.947155 & 0.105691 & 0.0528453 \tabularnewline
133 & 0.945301 & 0.109399 & 0.0546994 \tabularnewline
134 & 0.94213 & 0.115741 & 0.0578704 \tabularnewline
135 & 0.932371 & 0.135258 & 0.067629 \tabularnewline
136 & 0.922914 & 0.154173 & 0.0770865 \tabularnewline
137 & 0.945567 & 0.108867 & 0.0544333 \tabularnewline
138 & 0.943417 & 0.113166 & 0.056583 \tabularnewline
139 & 0.936823 & 0.126354 & 0.0631769 \tabularnewline
140 & 0.927413 & 0.145173 & 0.0725867 \tabularnewline
141 & 0.914896 & 0.170208 & 0.085104 \tabularnewline
142 & 0.953848 & 0.092304 & 0.046152 \tabularnewline
143 & 0.953037 & 0.0939257 & 0.0469628 \tabularnewline
144 & 0.952222 & 0.0955559 & 0.047778 \tabularnewline
145 & 0.94715 & 0.1057 & 0.0528498 \tabularnewline
146 & 0.947635 & 0.10473 & 0.0523649 \tabularnewline
147 & 0.941012 & 0.117976 & 0.058988 \tabularnewline
148 & 0.933281 & 0.133439 & 0.0667194 \tabularnewline
149 & 0.923762 & 0.152476 & 0.0762378 \tabularnewline
150 & 0.919073 & 0.161854 & 0.0809272 \tabularnewline
151 & 0.968355 & 0.06329 & 0.031645 \tabularnewline
152 & 0.96731 & 0.0653804 & 0.0326902 \tabularnewline
153 & 0.967771 & 0.0644576 & 0.0322288 \tabularnewline
154 & 0.961624 & 0.0767522 & 0.0383761 \tabularnewline
155 & 0.96226 & 0.0754796 & 0.0377398 \tabularnewline
156 & 0.955124 & 0.0897512 & 0.0448756 \tabularnewline
157 & 0.953408 & 0.093184 & 0.046592 \tabularnewline
158 & 0.945823 & 0.108354 & 0.054177 \tabularnewline
159 & 0.944338 & 0.111325 & 0.0556624 \tabularnewline
160 & 0.935653 & 0.128694 & 0.0643469 \tabularnewline
161 & 0.955083 & 0.0898345 & 0.0449173 \tabularnewline
162 & 0.946293 & 0.107414 & 0.0537068 \tabularnewline
163 & 0.945906 & 0.108187 & 0.0540937 \tabularnewline
164 & 0.987792 & 0.0244168 & 0.0122084 \tabularnewline
165 & 0.989015 & 0.0219697 & 0.0109848 \tabularnewline
166 & 0.98619 & 0.0276199 & 0.0138099 \tabularnewline
167 & 0.985327 & 0.0293462 & 0.0146731 \tabularnewline
168 & 0.989707 & 0.020586 & 0.010293 \tabularnewline
169 & 0.986959 & 0.0260817 & 0.0130408 \tabularnewline
170 & 0.987135 & 0.0257291 & 0.0128645 \tabularnewline
171 & 0.984865 & 0.0302696 & 0.0151348 \tabularnewline
172 & 0.989652 & 0.0206967 & 0.0103483 \tabularnewline
173 & 0.988119 & 0.0237628 & 0.0118814 \tabularnewline
174 & 0.985927 & 0.0281469 & 0.0140734 \tabularnewline
175 & 0.9836 & 0.0328006 & 0.0164003 \tabularnewline
176 & 0.987094 & 0.0258125 & 0.0129062 \tabularnewline
177 & 0.984689 & 0.0306216 & 0.0153108 \tabularnewline
178 & 0.984093 & 0.0318138 & 0.0159069 \tabularnewline
179 & 0.981856 & 0.0362887 & 0.0181444 \tabularnewline
180 & 0.988308 & 0.0233842 & 0.0116921 \tabularnewline
181 & 0.987164 & 0.0256711 & 0.0128356 \tabularnewline
182 & 0.986031 & 0.0279374 & 0.0139687 \tabularnewline
183 & 0.983386 & 0.0332278 & 0.0166139 \tabularnewline
184 & 0.980384 & 0.0392313 & 0.0196156 \tabularnewline
185 & 0.980274 & 0.0394514 & 0.0197257 \tabularnewline
186 & 0.977322 & 0.0453567 & 0.0226783 \tabularnewline
187 & 0.986272 & 0.0274565 & 0.0137282 \tabularnewline
188 & 0.983439 & 0.0331215 & 0.0165607 \tabularnewline
189 & 0.980591 & 0.0388175 & 0.0194087 \tabularnewline
190 & 0.975709 & 0.0485811 & 0.0242906 \tabularnewline
191 & 0.972063 & 0.0558744 & 0.0279372 \tabularnewline
192 & 0.971609 & 0.0567827 & 0.0283913 \tabularnewline
193 & 0.966012 & 0.0679766 & 0.0339883 \tabularnewline
194 & 0.979697 & 0.0406068 & 0.0203034 \tabularnewline
195 & 0.976066 & 0.0478676 & 0.0239338 \tabularnewline
196 & 0.971861 & 0.0562787 & 0.0281394 \tabularnewline
197 & 0.97754 & 0.044921 & 0.0224605 \tabularnewline
198 & 0.972834 & 0.0543311 & 0.0271655 \tabularnewline
199 & 0.974432 & 0.0511362 & 0.0255681 \tabularnewline
200 & 0.974222 & 0.0515563 & 0.0257782 \tabularnewline
201 & 0.970762 & 0.0584757 & 0.0292378 \tabularnewline
202 & 0.967332 & 0.0653354 & 0.0326677 \tabularnewline
203 & 0.964412 & 0.0711757 & 0.0355879 \tabularnewline
204 & 0.955944 & 0.0881114 & 0.0440557 \tabularnewline
205 & 0.945771 & 0.108459 & 0.0542294 \tabularnewline
206 & 0.957216 & 0.0855678 & 0.0427839 \tabularnewline
207 & 0.951368 & 0.0972632 & 0.0486316 \tabularnewline
208 & 0.946034 & 0.107932 & 0.0539658 \tabularnewline
209 & 0.941105 & 0.11779 & 0.058895 \tabularnewline
210 & 0.933668 & 0.132665 & 0.0663323 \tabularnewline
211 & 0.926299 & 0.147401 & 0.0737007 \tabularnewline
212 & 0.915452 & 0.169096 & 0.0845478 \tabularnewline
213 & 0.938625 & 0.12275 & 0.0613752 \tabularnewline
214 & 0.92963 & 0.14074 & 0.0703702 \tabularnewline
215 & 0.924374 & 0.151252 & 0.0756259 \tabularnewline
216 & 0.909858 & 0.180285 & 0.0901423 \tabularnewline
217 & 0.906487 & 0.187025 & 0.0935126 \tabularnewline
218 & 0.895687 & 0.208626 & 0.104313 \tabularnewline
219 & 0.874008 & 0.251984 & 0.125992 \tabularnewline
220 & 0.849203 & 0.301594 & 0.150797 \tabularnewline
221 & 0.824967 & 0.350066 & 0.175033 \tabularnewline
222 & 0.830505 & 0.33899 & 0.169495 \tabularnewline
223 & 0.801187 & 0.397626 & 0.198813 \tabularnewline
224 & 0.810157 & 0.379685 & 0.189843 \tabularnewline
225 & 0.791549 & 0.416903 & 0.208451 \tabularnewline
226 & 0.842256 & 0.315487 & 0.157744 \tabularnewline
227 & 0.893846 & 0.212308 & 0.106154 \tabularnewline
228 & 0.892536 & 0.214929 & 0.107464 \tabularnewline
229 & 0.890199 & 0.219602 & 0.109801 \tabularnewline
230 & 0.912123 & 0.175754 & 0.0878771 \tabularnewline
231 & 0.930991 & 0.138018 & 0.0690088 \tabularnewline
232 & 0.913839 & 0.172321 & 0.0861605 \tabularnewline
233 & 0.901347 & 0.197306 & 0.0986531 \tabularnewline
234 & 0.887779 & 0.224442 & 0.112221 \tabularnewline
235 & 0.861863 & 0.276273 & 0.138137 \tabularnewline
236 & 0.954037 & 0.0919269 & 0.0459635 \tabularnewline
237 & 0.957151 & 0.0856986 & 0.0428493 \tabularnewline
238 & 0.971664 & 0.0566712 & 0.0283356 \tabularnewline
239 & 0.961129 & 0.0777424 & 0.0388712 \tabularnewline
240 & 0.949436 & 0.101128 & 0.0505642 \tabularnewline
241 & 0.934845 & 0.130311 & 0.0651555 \tabularnewline
242 & 0.917278 & 0.165445 & 0.0827223 \tabularnewline
243 & 0.911943 & 0.176115 & 0.0880574 \tabularnewline
244 & 0.89529 & 0.20942 & 0.10471 \tabularnewline
245 & 0.866891 & 0.266219 & 0.133109 \tabularnewline
246 & 0.850816 & 0.298368 & 0.149184 \tabularnewline
247 & 0.817616 & 0.364767 & 0.182384 \tabularnewline
248 & 0.79635 & 0.4073 & 0.20365 \tabularnewline
249 & 0.748682 & 0.502636 & 0.251318 \tabularnewline
250 & 0.693079 & 0.613843 & 0.306921 \tabularnewline
251 & 0.638085 & 0.72383 & 0.361915 \tabularnewline
252 & 0.597172 & 0.805656 & 0.402828 \tabularnewline
253 & 0.528202 & 0.943595 & 0.471798 \tabularnewline
254 & 0.466683 & 0.933366 & 0.533317 \tabularnewline
255 & 0.50329 & 0.993421 & 0.49671 \tabularnewline
256 & 0.430963 & 0.861927 & 0.569037 \tabularnewline
257 & 0.387656 & 0.775311 & 0.612344 \tabularnewline
258 & 0.87829 & 0.243421 & 0.12171 \tabularnewline
259 & 0.840111 & 0.319778 & 0.159889 \tabularnewline
260 & 0.989008 & 0.0219846 & 0.0109923 \tabularnewline
261 & 0.990836 & 0.0183286 & 0.0091643 \tabularnewline
262 & 0.981772 & 0.0364556 & 0.0182278 \tabularnewline
263 & 0.998932 & 0.002135 & 0.0010675 \tabularnewline
264 & 0.996765 & 0.00646911 & 0.00323456 \tabularnewline
265 & 0.991643 & 0.0167142 & 0.00835711 \tabularnewline
266 & 0.983335 & 0.0333293 & 0.0166647 \tabularnewline
267 & 0.961253 & 0.0774944 & 0.0387472 \tabularnewline
268 & 0.901976 & 0.196049 & 0.0980244 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270372&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]10[/C][C]0.547498[/C][C]0.905005[/C][C]0.452502[/C][/ROW]
[ROW][C]11[/C][C]0.415358[/C][C]0.830716[/C][C]0.584642[/C][/ROW]
[ROW][C]12[/C][C]0.300509[/C][C]0.601018[/C][C]0.699491[/C][/ROW]
[ROW][C]13[/C][C]0.386461[/C][C]0.772922[/C][C]0.613539[/C][/ROW]
[ROW][C]14[/C][C]0.276974[/C][C]0.553949[/C][C]0.723026[/C][/ROW]
[ROW][C]15[/C][C]0.205759[/C][C]0.411518[/C][C]0.794241[/C][/ROW]
[ROW][C]16[/C][C]0.703653[/C][C]0.592694[/C][C]0.296347[/C][/ROW]
[ROW][C]17[/C][C]0.635753[/C][C]0.728495[/C][C]0.364247[/C][/ROW]
[ROW][C]18[/C][C]0.552781[/C][C]0.894438[/C][C]0.447219[/C][/ROW]
[ROW][C]19[/C][C]0.498045[/C][C]0.996089[/C][C]0.501955[/C][/ROW]
[ROW][C]20[/C][C]0.422648[/C][C]0.845296[/C][C]0.577352[/C][/ROW]
[ROW][C]21[/C][C]0.380846[/C][C]0.761693[/C][C]0.619154[/C][/ROW]
[ROW][C]22[/C][C]0.318288[/C][C]0.636575[/C][C]0.681712[/C][/ROW]
[ROW][C]23[/C][C]0.257198[/C][C]0.514395[/C][C]0.742802[/C][/ROW]
[ROW][C]24[/C][C]0.201849[/C][C]0.403698[/C][C]0.798151[/C][/ROW]
[ROW][C]25[/C][C]0.1543[/C][C]0.308599[/C][C]0.8457[/C][/ROW]
[ROW][C]26[/C][C]0.12291[/C][C]0.24582[/C][C]0.87709[/C][/ROW]
[ROW][C]27[/C][C]0.0923522[/C][C]0.184704[/C][C]0.907648[/C][/ROW]
[ROW][C]28[/C][C]0.187533[/C][C]0.375066[/C][C]0.812467[/C][/ROW]
[ROW][C]29[/C][C]0.156724[/C][C]0.313448[/C][C]0.843276[/C][/ROW]
[ROW][C]30[/C][C]0.165818[/C][C]0.331637[/C][C]0.834182[/C][/ROW]
[ROW][C]31[/C][C]0.137417[/C][C]0.274833[/C][C]0.862583[/C][/ROW]
[ROW][C]32[/C][C]0.131496[/C][C]0.262991[/C][C]0.868504[/C][/ROW]
[ROW][C]33[/C][C]0.113403[/C][C]0.226807[/C][C]0.886597[/C][/ROW]
[ROW][C]34[/C][C]0.113088[/C][C]0.226176[/C][C]0.886912[/C][/ROW]
[ROW][C]35[/C][C]0.0916096[/C][C]0.183219[/C][C]0.90839[/C][/ROW]
[ROW][C]36[/C][C]0.0727203[/C][C]0.145441[/C][C]0.92728[/C][/ROW]
[ROW][C]37[/C][C]0.0551438[/C][C]0.110288[/C][C]0.944856[/C][/ROW]
[ROW][C]38[/C][C]0.0847359[/C][C]0.169472[/C][C]0.915264[/C][/ROW]
[ROW][C]39[/C][C]0.107461[/C][C]0.214922[/C][C]0.892539[/C][/ROW]
[ROW][C]40[/C][C]0.087553[/C][C]0.175106[/C][C]0.912447[/C][/ROW]
[ROW][C]41[/C][C]0.14149[/C][C]0.28298[/C][C]0.85851[/C][/ROW]
[ROW][C]42[/C][C]0.118073[/C][C]0.236147[/C][C]0.881927[/C][/ROW]
[ROW][C]43[/C][C]0.0971985[/C][C]0.194397[/C][C]0.902802[/C][/ROW]
[ROW][C]44[/C][C]0.0813704[/C][C]0.162741[/C][C]0.91863[/C][/ROW]
[ROW][C]45[/C][C]0.0963056[/C][C]0.192611[/C][C]0.903694[/C][/ROW]
[ROW][C]46[/C][C]0.0844654[/C][C]0.168931[/C][C]0.915535[/C][/ROW]
[ROW][C]47[/C][C]0.0743716[/C][C]0.148743[/C][C]0.925628[/C][/ROW]
[ROW][C]48[/C][C]0.0884689[/C][C]0.176938[/C][C]0.911531[/C][/ROW]
[ROW][C]49[/C][C]0.0868708[/C][C]0.173742[/C][C]0.913129[/C][/ROW]
[ROW][C]50[/C][C]0.0843093[/C][C]0.168619[/C][C]0.915691[/C][/ROW]
[ROW][C]51[/C][C]0.0714072[/C][C]0.142814[/C][C]0.928593[/C][/ROW]
[ROW][C]52[/C][C]0.0773293[/C][C]0.154659[/C][C]0.922671[/C][/ROW]
[ROW][C]53[/C][C]0.0706108[/C][C]0.141222[/C][C]0.929389[/C][/ROW]
[ROW][C]54[/C][C]0.071228[/C][C]0.142456[/C][C]0.928772[/C][/ROW]
[ROW][C]55[/C][C]0.0790157[/C][C]0.158031[/C][C]0.920984[/C][/ROW]
[ROW][C]56[/C][C]0.0687165[/C][C]0.137433[/C][C]0.931284[/C][/ROW]
[ROW][C]57[/C][C]0.128711[/C][C]0.257422[/C][C]0.871289[/C][/ROW]
[ROW][C]58[/C][C]0.156049[/C][C]0.312099[/C][C]0.843951[/C][/ROW]
[ROW][C]59[/C][C]0.132331[/C][C]0.264662[/C][C]0.867669[/C][/ROW]
[ROW][C]60[/C][C]0.131371[/C][C]0.262742[/C][C]0.868629[/C][/ROW]
[ROW][C]61[/C][C]0.152606[/C][C]0.305211[/C][C]0.847394[/C][/ROW]
[ROW][C]62[/C][C]0.135166[/C][C]0.270331[/C][C]0.864834[/C][/ROW]
[ROW][C]63[/C][C]0.15093[/C][C]0.30186[/C][C]0.84907[/C][/ROW]
[ROW][C]64[/C][C]0.191727[/C][C]0.383454[/C][C]0.808273[/C][/ROW]
[ROW][C]65[/C][C]0.18969[/C][C]0.37938[/C][C]0.81031[/C][/ROW]
[ROW][C]66[/C][C]0.167025[/C][C]0.33405[/C][C]0.832975[/C][/ROW]
[ROW][C]67[/C][C]0.167214[/C][C]0.334427[/C][C]0.832786[/C][/ROW]
[ROW][C]68[/C][C]0.15644[/C][C]0.31288[/C][C]0.84356[/C][/ROW]
[ROW][C]69[/C][C]0.165367[/C][C]0.330734[/C][C]0.834633[/C][/ROW]
[ROW][C]70[/C][C]0.153317[/C][C]0.306635[/C][C]0.846683[/C][/ROW]
[ROW][C]71[/C][C]0.141099[/C][C]0.282199[/C][C]0.858901[/C][/ROW]
[ROW][C]72[/C][C]0.123468[/C][C]0.246935[/C][C]0.876532[/C][/ROW]
[ROW][C]73[/C][C]0.113375[/C][C]0.226751[/C][C]0.886625[/C][/ROW]
[ROW][C]74[/C][C]0.111342[/C][C]0.222683[/C][C]0.888658[/C][/ROW]
[ROW][C]75[/C][C]0.102523[/C][C]0.205046[/C][C]0.897477[/C][/ROW]
[ROW][C]76[/C][C]0.0971267[/C][C]0.194253[/C][C]0.902873[/C][/ROW]
[ROW][C]77[/C][C]0.0863746[/C][C]0.172749[/C][C]0.913625[/C][/ROW]
[ROW][C]78[/C][C]0.0843289[/C][C]0.168658[/C][C]0.915671[/C][/ROW]
[ROW][C]79[/C][C]0.071253[/C][C]0.142506[/C][C]0.928747[/C][/ROW]
[ROW][C]80[/C][C]0.0919284[/C][C]0.183857[/C][C]0.908072[/C][/ROW]
[ROW][C]81[/C][C]0.0777355[/C][C]0.155471[/C][C]0.922264[/C][/ROW]
[ROW][C]82[/C][C]0.0910631[/C][C]0.182126[/C][C]0.908937[/C][/ROW]
[ROW][C]83[/C][C]0.078146[/C][C]0.156292[/C][C]0.921854[/C][/ROW]
[ROW][C]84[/C][C]0.16879[/C][C]0.33758[/C][C]0.83121[/C][/ROW]
[ROW][C]85[/C][C]0.152597[/C][C]0.305194[/C][C]0.847403[/C][/ROW]
[ROW][C]86[/C][C]0.135312[/C][C]0.270624[/C][C]0.864688[/C][/ROW]
[ROW][C]87[/C][C]0.118001[/C][C]0.236003[/C][C]0.881999[/C][/ROW]
[ROW][C]88[/C][C]0.102305[/C][C]0.20461[/C][C]0.897695[/C][/ROW]
[ROW][C]89[/C][C]0.0988705[/C][C]0.197741[/C][C]0.901129[/C][/ROW]
[ROW][C]90[/C][C]0.0973393[/C][C]0.194679[/C][C]0.902661[/C][/ROW]
[ROW][C]91[/C][C]0.106418[/C][C]0.212836[/C][C]0.893582[/C][/ROW]
[ROW][C]92[/C][C]0.183799[/C][C]0.367597[/C][C]0.816201[/C][/ROW]
[ROW][C]93[/C][C]0.176731[/C][C]0.353462[/C][C]0.823269[/C][/ROW]
[ROW][C]94[/C][C]0.173711[/C][C]0.347421[/C][C]0.826289[/C][/ROW]
[ROW][C]95[/C][C]0.192616[/C][C]0.385231[/C][C]0.807384[/C][/ROW]
[ROW][C]96[/C][C]0.18559[/C][C]0.371181[/C][C]0.81441[/C][/ROW]
[ROW][C]97[/C][C]0.259291[/C][C]0.518582[/C][C]0.740709[/C][/ROW]
[ROW][C]98[/C][C]0.242093[/C][C]0.484186[/C][C]0.757907[/C][/ROW]
[ROW][C]99[/C][C]0.253324[/C][C]0.506648[/C][C]0.746676[/C][/ROW]
[ROW][C]100[/C][C]0.323294[/C][C]0.646588[/C][C]0.676706[/C][/ROW]
[ROW][C]101[/C][C]0.301513[/C][C]0.603026[/C][C]0.698487[/C][/ROW]
[ROW][C]102[/C][C]0.285262[/C][C]0.570523[/C][C]0.714738[/C][/ROW]
[ROW][C]103[/C][C]0.283105[/C][C]0.56621[/C][C]0.716895[/C][/ROW]
[ROW][C]104[/C][C]0.287422[/C][C]0.574844[/C][C]0.712578[/C][/ROW]
[ROW][C]105[/C][C]0.317716[/C][C]0.635433[/C][C]0.682284[/C][/ROW]
[ROW][C]106[/C][C]0.325401[/C][C]0.650803[/C][C]0.674599[/C][/ROW]
[ROW][C]107[/C][C]0.338158[/C][C]0.676316[/C][C]0.661842[/C][/ROW]
[ROW][C]108[/C][C]0.525282[/C][C]0.949436[/C][C]0.474718[/C][/ROW]
[ROW][C]109[/C][C]0.568305[/C][C]0.86339[/C][C]0.431695[/C][/ROW]
[ROW][C]110[/C][C]0.564071[/C][C]0.871858[/C][C]0.435929[/C][/ROW]
[ROW][C]111[/C][C]0.555843[/C][C]0.888314[/C][C]0.444157[/C][/ROW]
[ROW][C]112[/C][C]0.527985[/C][C]0.944029[/C][C]0.472015[/C][/ROW]
[ROW][C]113[/C][C]0.670535[/C][C]0.65893[/C][C]0.329465[/C][/ROW]
[ROW][C]114[/C][C]0.670815[/C][C]0.65837[/C][C]0.329185[/C][/ROW]
[ROW][C]115[/C][C]0.7906[/C][C]0.418799[/C][C]0.2094[/C][/ROW]
[ROW][C]116[/C][C]0.845444[/C][C]0.309112[/C][C]0.154556[/C][/ROW]
[ROW][C]117[/C][C]0.826139[/C][C]0.347721[/C][C]0.173861[/C][/ROW]
[ROW][C]118[/C][C]0.84571[/C][C]0.308579[/C][C]0.15429[/C][/ROW]
[ROW][C]119[/C][C]0.853793[/C][C]0.292414[/C][C]0.146207[/C][/ROW]
[ROW][C]120[/C][C]0.876002[/C][C]0.247997[/C][C]0.123998[/C][/ROW]
[ROW][C]121[/C][C]0.882769[/C][C]0.234462[/C][C]0.117231[/C][/ROW]
[ROW][C]122[/C][C]0.892215[/C][C]0.215569[/C][C]0.107785[/C][/ROW]
[ROW][C]123[/C][C]0.88929[/C][C]0.22142[/C][C]0.11071[/C][/ROW]
[ROW][C]124[/C][C]0.926518[/C][C]0.146964[/C][C]0.0734822[/C][/ROW]
[ROW][C]125[/C][C]0.937283[/C][C]0.125434[/C][C]0.0627169[/C][/ROW]
[ROW][C]126[/C][C]0.927645[/C][C]0.144709[/C][C]0.0723545[/C][/ROW]
[ROW][C]127[/C][C]0.934587[/C][C]0.130826[/C][C]0.0654128[/C][/ROW]
[ROW][C]128[/C][C]0.938589[/C][C]0.122821[/C][C]0.0614107[/C][/ROW]
[ROW][C]129[/C][C]0.944886[/C][C]0.110228[/C][C]0.055114[/C][/ROW]
[ROW][C]130[/C][C]0.943025[/C][C]0.113951[/C][C]0.0569755[/C][/ROW]
[ROW][C]131[/C][C]0.946708[/C][C]0.106584[/C][C]0.0532919[/C][/ROW]
[ROW][C]132[/C][C]0.947155[/C][C]0.105691[/C][C]0.0528453[/C][/ROW]
[ROW][C]133[/C][C]0.945301[/C][C]0.109399[/C][C]0.0546994[/C][/ROW]
[ROW][C]134[/C][C]0.94213[/C][C]0.115741[/C][C]0.0578704[/C][/ROW]
[ROW][C]135[/C][C]0.932371[/C][C]0.135258[/C][C]0.067629[/C][/ROW]
[ROW][C]136[/C][C]0.922914[/C][C]0.154173[/C][C]0.0770865[/C][/ROW]
[ROW][C]137[/C][C]0.945567[/C][C]0.108867[/C][C]0.0544333[/C][/ROW]
[ROW][C]138[/C][C]0.943417[/C][C]0.113166[/C][C]0.056583[/C][/ROW]
[ROW][C]139[/C][C]0.936823[/C][C]0.126354[/C][C]0.0631769[/C][/ROW]
[ROW][C]140[/C][C]0.927413[/C][C]0.145173[/C][C]0.0725867[/C][/ROW]
[ROW][C]141[/C][C]0.914896[/C][C]0.170208[/C][C]0.085104[/C][/ROW]
[ROW][C]142[/C][C]0.953848[/C][C]0.092304[/C][C]0.046152[/C][/ROW]
[ROW][C]143[/C][C]0.953037[/C][C]0.0939257[/C][C]0.0469628[/C][/ROW]
[ROW][C]144[/C][C]0.952222[/C][C]0.0955559[/C][C]0.047778[/C][/ROW]
[ROW][C]145[/C][C]0.94715[/C][C]0.1057[/C][C]0.0528498[/C][/ROW]
[ROW][C]146[/C][C]0.947635[/C][C]0.10473[/C][C]0.0523649[/C][/ROW]
[ROW][C]147[/C][C]0.941012[/C][C]0.117976[/C][C]0.058988[/C][/ROW]
[ROW][C]148[/C][C]0.933281[/C][C]0.133439[/C][C]0.0667194[/C][/ROW]
[ROW][C]149[/C][C]0.923762[/C][C]0.152476[/C][C]0.0762378[/C][/ROW]
[ROW][C]150[/C][C]0.919073[/C][C]0.161854[/C][C]0.0809272[/C][/ROW]
[ROW][C]151[/C][C]0.968355[/C][C]0.06329[/C][C]0.031645[/C][/ROW]
[ROW][C]152[/C][C]0.96731[/C][C]0.0653804[/C][C]0.0326902[/C][/ROW]
[ROW][C]153[/C][C]0.967771[/C][C]0.0644576[/C][C]0.0322288[/C][/ROW]
[ROW][C]154[/C][C]0.961624[/C][C]0.0767522[/C][C]0.0383761[/C][/ROW]
[ROW][C]155[/C][C]0.96226[/C][C]0.0754796[/C][C]0.0377398[/C][/ROW]
[ROW][C]156[/C][C]0.955124[/C][C]0.0897512[/C][C]0.0448756[/C][/ROW]
[ROW][C]157[/C][C]0.953408[/C][C]0.093184[/C][C]0.046592[/C][/ROW]
[ROW][C]158[/C][C]0.945823[/C][C]0.108354[/C][C]0.054177[/C][/ROW]
[ROW][C]159[/C][C]0.944338[/C][C]0.111325[/C][C]0.0556624[/C][/ROW]
[ROW][C]160[/C][C]0.935653[/C][C]0.128694[/C][C]0.0643469[/C][/ROW]
[ROW][C]161[/C][C]0.955083[/C][C]0.0898345[/C][C]0.0449173[/C][/ROW]
[ROW][C]162[/C][C]0.946293[/C][C]0.107414[/C][C]0.0537068[/C][/ROW]
[ROW][C]163[/C][C]0.945906[/C][C]0.108187[/C][C]0.0540937[/C][/ROW]
[ROW][C]164[/C][C]0.987792[/C][C]0.0244168[/C][C]0.0122084[/C][/ROW]
[ROW][C]165[/C][C]0.989015[/C][C]0.0219697[/C][C]0.0109848[/C][/ROW]
[ROW][C]166[/C][C]0.98619[/C][C]0.0276199[/C][C]0.0138099[/C][/ROW]
[ROW][C]167[/C][C]0.985327[/C][C]0.0293462[/C][C]0.0146731[/C][/ROW]
[ROW][C]168[/C][C]0.989707[/C][C]0.020586[/C][C]0.010293[/C][/ROW]
[ROW][C]169[/C][C]0.986959[/C][C]0.0260817[/C][C]0.0130408[/C][/ROW]
[ROW][C]170[/C][C]0.987135[/C][C]0.0257291[/C][C]0.0128645[/C][/ROW]
[ROW][C]171[/C][C]0.984865[/C][C]0.0302696[/C][C]0.0151348[/C][/ROW]
[ROW][C]172[/C][C]0.989652[/C][C]0.0206967[/C][C]0.0103483[/C][/ROW]
[ROW][C]173[/C][C]0.988119[/C][C]0.0237628[/C][C]0.0118814[/C][/ROW]
[ROW][C]174[/C][C]0.985927[/C][C]0.0281469[/C][C]0.0140734[/C][/ROW]
[ROW][C]175[/C][C]0.9836[/C][C]0.0328006[/C][C]0.0164003[/C][/ROW]
[ROW][C]176[/C][C]0.987094[/C][C]0.0258125[/C][C]0.0129062[/C][/ROW]
[ROW][C]177[/C][C]0.984689[/C][C]0.0306216[/C][C]0.0153108[/C][/ROW]
[ROW][C]178[/C][C]0.984093[/C][C]0.0318138[/C][C]0.0159069[/C][/ROW]
[ROW][C]179[/C][C]0.981856[/C][C]0.0362887[/C][C]0.0181444[/C][/ROW]
[ROW][C]180[/C][C]0.988308[/C][C]0.0233842[/C][C]0.0116921[/C][/ROW]
[ROW][C]181[/C][C]0.987164[/C][C]0.0256711[/C][C]0.0128356[/C][/ROW]
[ROW][C]182[/C][C]0.986031[/C][C]0.0279374[/C][C]0.0139687[/C][/ROW]
[ROW][C]183[/C][C]0.983386[/C][C]0.0332278[/C][C]0.0166139[/C][/ROW]
[ROW][C]184[/C][C]0.980384[/C][C]0.0392313[/C][C]0.0196156[/C][/ROW]
[ROW][C]185[/C][C]0.980274[/C][C]0.0394514[/C][C]0.0197257[/C][/ROW]
[ROW][C]186[/C][C]0.977322[/C][C]0.0453567[/C][C]0.0226783[/C][/ROW]
[ROW][C]187[/C][C]0.986272[/C][C]0.0274565[/C][C]0.0137282[/C][/ROW]
[ROW][C]188[/C][C]0.983439[/C][C]0.0331215[/C][C]0.0165607[/C][/ROW]
[ROW][C]189[/C][C]0.980591[/C][C]0.0388175[/C][C]0.0194087[/C][/ROW]
[ROW][C]190[/C][C]0.975709[/C][C]0.0485811[/C][C]0.0242906[/C][/ROW]
[ROW][C]191[/C][C]0.972063[/C][C]0.0558744[/C][C]0.0279372[/C][/ROW]
[ROW][C]192[/C][C]0.971609[/C][C]0.0567827[/C][C]0.0283913[/C][/ROW]
[ROW][C]193[/C][C]0.966012[/C][C]0.0679766[/C][C]0.0339883[/C][/ROW]
[ROW][C]194[/C][C]0.979697[/C][C]0.0406068[/C][C]0.0203034[/C][/ROW]
[ROW][C]195[/C][C]0.976066[/C][C]0.0478676[/C][C]0.0239338[/C][/ROW]
[ROW][C]196[/C][C]0.971861[/C][C]0.0562787[/C][C]0.0281394[/C][/ROW]
[ROW][C]197[/C][C]0.97754[/C][C]0.044921[/C][C]0.0224605[/C][/ROW]
[ROW][C]198[/C][C]0.972834[/C][C]0.0543311[/C][C]0.0271655[/C][/ROW]
[ROW][C]199[/C][C]0.974432[/C][C]0.0511362[/C][C]0.0255681[/C][/ROW]
[ROW][C]200[/C][C]0.974222[/C][C]0.0515563[/C][C]0.0257782[/C][/ROW]
[ROW][C]201[/C][C]0.970762[/C][C]0.0584757[/C][C]0.0292378[/C][/ROW]
[ROW][C]202[/C][C]0.967332[/C][C]0.0653354[/C][C]0.0326677[/C][/ROW]
[ROW][C]203[/C][C]0.964412[/C][C]0.0711757[/C][C]0.0355879[/C][/ROW]
[ROW][C]204[/C][C]0.955944[/C][C]0.0881114[/C][C]0.0440557[/C][/ROW]
[ROW][C]205[/C][C]0.945771[/C][C]0.108459[/C][C]0.0542294[/C][/ROW]
[ROW][C]206[/C][C]0.957216[/C][C]0.0855678[/C][C]0.0427839[/C][/ROW]
[ROW][C]207[/C][C]0.951368[/C][C]0.0972632[/C][C]0.0486316[/C][/ROW]
[ROW][C]208[/C][C]0.946034[/C][C]0.107932[/C][C]0.0539658[/C][/ROW]
[ROW][C]209[/C][C]0.941105[/C][C]0.11779[/C][C]0.058895[/C][/ROW]
[ROW][C]210[/C][C]0.933668[/C][C]0.132665[/C][C]0.0663323[/C][/ROW]
[ROW][C]211[/C][C]0.926299[/C][C]0.147401[/C][C]0.0737007[/C][/ROW]
[ROW][C]212[/C][C]0.915452[/C][C]0.169096[/C][C]0.0845478[/C][/ROW]
[ROW][C]213[/C][C]0.938625[/C][C]0.12275[/C][C]0.0613752[/C][/ROW]
[ROW][C]214[/C][C]0.92963[/C][C]0.14074[/C][C]0.0703702[/C][/ROW]
[ROW][C]215[/C][C]0.924374[/C][C]0.151252[/C][C]0.0756259[/C][/ROW]
[ROW][C]216[/C][C]0.909858[/C][C]0.180285[/C][C]0.0901423[/C][/ROW]
[ROW][C]217[/C][C]0.906487[/C][C]0.187025[/C][C]0.0935126[/C][/ROW]
[ROW][C]218[/C][C]0.895687[/C][C]0.208626[/C][C]0.104313[/C][/ROW]
[ROW][C]219[/C][C]0.874008[/C][C]0.251984[/C][C]0.125992[/C][/ROW]
[ROW][C]220[/C][C]0.849203[/C][C]0.301594[/C][C]0.150797[/C][/ROW]
[ROW][C]221[/C][C]0.824967[/C][C]0.350066[/C][C]0.175033[/C][/ROW]
[ROW][C]222[/C][C]0.830505[/C][C]0.33899[/C][C]0.169495[/C][/ROW]
[ROW][C]223[/C][C]0.801187[/C][C]0.397626[/C][C]0.198813[/C][/ROW]
[ROW][C]224[/C][C]0.810157[/C][C]0.379685[/C][C]0.189843[/C][/ROW]
[ROW][C]225[/C][C]0.791549[/C][C]0.416903[/C][C]0.208451[/C][/ROW]
[ROW][C]226[/C][C]0.842256[/C][C]0.315487[/C][C]0.157744[/C][/ROW]
[ROW][C]227[/C][C]0.893846[/C][C]0.212308[/C][C]0.106154[/C][/ROW]
[ROW][C]228[/C][C]0.892536[/C][C]0.214929[/C][C]0.107464[/C][/ROW]
[ROW][C]229[/C][C]0.890199[/C][C]0.219602[/C][C]0.109801[/C][/ROW]
[ROW][C]230[/C][C]0.912123[/C][C]0.175754[/C][C]0.0878771[/C][/ROW]
[ROW][C]231[/C][C]0.930991[/C][C]0.138018[/C][C]0.0690088[/C][/ROW]
[ROW][C]232[/C][C]0.913839[/C][C]0.172321[/C][C]0.0861605[/C][/ROW]
[ROW][C]233[/C][C]0.901347[/C][C]0.197306[/C][C]0.0986531[/C][/ROW]
[ROW][C]234[/C][C]0.887779[/C][C]0.224442[/C][C]0.112221[/C][/ROW]
[ROW][C]235[/C][C]0.861863[/C][C]0.276273[/C][C]0.138137[/C][/ROW]
[ROW][C]236[/C][C]0.954037[/C][C]0.0919269[/C][C]0.0459635[/C][/ROW]
[ROW][C]237[/C][C]0.957151[/C][C]0.0856986[/C][C]0.0428493[/C][/ROW]
[ROW][C]238[/C][C]0.971664[/C][C]0.0566712[/C][C]0.0283356[/C][/ROW]
[ROW][C]239[/C][C]0.961129[/C][C]0.0777424[/C][C]0.0388712[/C][/ROW]
[ROW][C]240[/C][C]0.949436[/C][C]0.101128[/C][C]0.0505642[/C][/ROW]
[ROW][C]241[/C][C]0.934845[/C][C]0.130311[/C][C]0.0651555[/C][/ROW]
[ROW][C]242[/C][C]0.917278[/C][C]0.165445[/C][C]0.0827223[/C][/ROW]
[ROW][C]243[/C][C]0.911943[/C][C]0.176115[/C][C]0.0880574[/C][/ROW]
[ROW][C]244[/C][C]0.89529[/C][C]0.20942[/C][C]0.10471[/C][/ROW]
[ROW][C]245[/C][C]0.866891[/C][C]0.266219[/C][C]0.133109[/C][/ROW]
[ROW][C]246[/C][C]0.850816[/C][C]0.298368[/C][C]0.149184[/C][/ROW]
[ROW][C]247[/C][C]0.817616[/C][C]0.364767[/C][C]0.182384[/C][/ROW]
[ROW][C]248[/C][C]0.79635[/C][C]0.4073[/C][C]0.20365[/C][/ROW]
[ROW][C]249[/C][C]0.748682[/C][C]0.502636[/C][C]0.251318[/C][/ROW]
[ROW][C]250[/C][C]0.693079[/C][C]0.613843[/C][C]0.306921[/C][/ROW]
[ROW][C]251[/C][C]0.638085[/C][C]0.72383[/C][C]0.361915[/C][/ROW]
[ROW][C]252[/C][C]0.597172[/C][C]0.805656[/C][C]0.402828[/C][/ROW]
[ROW][C]253[/C][C]0.528202[/C][C]0.943595[/C][C]0.471798[/C][/ROW]
[ROW][C]254[/C][C]0.466683[/C][C]0.933366[/C][C]0.533317[/C][/ROW]
[ROW][C]255[/C][C]0.50329[/C][C]0.993421[/C][C]0.49671[/C][/ROW]
[ROW][C]256[/C][C]0.430963[/C][C]0.861927[/C][C]0.569037[/C][/ROW]
[ROW][C]257[/C][C]0.387656[/C][C]0.775311[/C][C]0.612344[/C][/ROW]
[ROW][C]258[/C][C]0.87829[/C][C]0.243421[/C][C]0.12171[/C][/ROW]
[ROW][C]259[/C][C]0.840111[/C][C]0.319778[/C][C]0.159889[/C][/ROW]
[ROW][C]260[/C][C]0.989008[/C][C]0.0219846[/C][C]0.0109923[/C][/ROW]
[ROW][C]261[/C][C]0.990836[/C][C]0.0183286[/C][C]0.0091643[/C][/ROW]
[ROW][C]262[/C][C]0.981772[/C][C]0.0364556[/C][C]0.0182278[/C][/ROW]
[ROW][C]263[/C][C]0.998932[/C][C]0.002135[/C][C]0.0010675[/C][/ROW]
[ROW][C]264[/C][C]0.996765[/C][C]0.00646911[/C][C]0.00323456[/C][/ROW]
[ROW][C]265[/C][C]0.991643[/C][C]0.0167142[/C][C]0.00835711[/C][/ROW]
[ROW][C]266[/C][C]0.983335[/C][C]0.0333293[/C][C]0.0166647[/C][/ROW]
[ROW][C]267[/C][C]0.961253[/C][C]0.0774944[/C][C]0.0387472[/C][/ROW]
[ROW][C]268[/C][C]0.901976[/C][C]0.196049[/C][C]0.0980244[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270372&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270372&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
100.5474980.9050050.452502
110.4153580.8307160.584642
120.3005090.6010180.699491
130.3864610.7729220.613539
140.2769740.5539490.723026
150.2057590.4115180.794241
160.7036530.5926940.296347
170.6357530.7284950.364247
180.5527810.8944380.447219
190.4980450.9960890.501955
200.4226480.8452960.577352
210.3808460.7616930.619154
220.3182880.6365750.681712
230.2571980.5143950.742802
240.2018490.4036980.798151
250.15430.3085990.8457
260.122910.245820.87709
270.09235220.1847040.907648
280.1875330.3750660.812467
290.1567240.3134480.843276
300.1658180.3316370.834182
310.1374170.2748330.862583
320.1314960.2629910.868504
330.1134030.2268070.886597
340.1130880.2261760.886912
350.09160960.1832190.90839
360.07272030.1454410.92728
370.05514380.1102880.944856
380.08473590.1694720.915264
390.1074610.2149220.892539
400.0875530.1751060.912447
410.141490.282980.85851
420.1180730.2361470.881927
430.09719850.1943970.902802
440.08137040.1627410.91863
450.09630560.1926110.903694
460.08446540.1689310.915535
470.07437160.1487430.925628
480.08846890.1769380.911531
490.08687080.1737420.913129
500.08430930.1686190.915691
510.07140720.1428140.928593
520.07732930.1546590.922671
530.07061080.1412220.929389
540.0712280.1424560.928772
550.07901570.1580310.920984
560.06871650.1374330.931284
570.1287110.2574220.871289
580.1560490.3120990.843951
590.1323310.2646620.867669
600.1313710.2627420.868629
610.1526060.3052110.847394
620.1351660.2703310.864834
630.150930.301860.84907
640.1917270.3834540.808273
650.189690.379380.81031
660.1670250.334050.832975
670.1672140.3344270.832786
680.156440.312880.84356
690.1653670.3307340.834633
700.1533170.3066350.846683
710.1410990.2821990.858901
720.1234680.2469350.876532
730.1133750.2267510.886625
740.1113420.2226830.888658
750.1025230.2050460.897477
760.09712670.1942530.902873
770.08637460.1727490.913625
780.08432890.1686580.915671
790.0712530.1425060.928747
800.09192840.1838570.908072
810.07773550.1554710.922264
820.09106310.1821260.908937
830.0781460.1562920.921854
840.168790.337580.83121
850.1525970.3051940.847403
860.1353120.2706240.864688
870.1180010.2360030.881999
880.1023050.204610.897695
890.09887050.1977410.901129
900.09733930.1946790.902661
910.1064180.2128360.893582
920.1837990.3675970.816201
930.1767310.3534620.823269
940.1737110.3474210.826289
950.1926160.3852310.807384
960.185590.3711810.81441
970.2592910.5185820.740709
980.2420930.4841860.757907
990.2533240.5066480.746676
1000.3232940.6465880.676706
1010.3015130.6030260.698487
1020.2852620.5705230.714738
1030.2831050.566210.716895
1040.2874220.5748440.712578
1050.3177160.6354330.682284
1060.3254010.6508030.674599
1070.3381580.6763160.661842
1080.5252820.9494360.474718
1090.5683050.863390.431695
1100.5640710.8718580.435929
1110.5558430.8883140.444157
1120.5279850.9440290.472015
1130.6705350.658930.329465
1140.6708150.658370.329185
1150.79060.4187990.2094
1160.8454440.3091120.154556
1170.8261390.3477210.173861
1180.845710.3085790.15429
1190.8537930.2924140.146207
1200.8760020.2479970.123998
1210.8827690.2344620.117231
1220.8922150.2155690.107785
1230.889290.221420.11071
1240.9265180.1469640.0734822
1250.9372830.1254340.0627169
1260.9276450.1447090.0723545
1270.9345870.1308260.0654128
1280.9385890.1228210.0614107
1290.9448860.1102280.055114
1300.9430250.1139510.0569755
1310.9467080.1065840.0532919
1320.9471550.1056910.0528453
1330.9453010.1093990.0546994
1340.942130.1157410.0578704
1350.9323710.1352580.067629
1360.9229140.1541730.0770865
1370.9455670.1088670.0544333
1380.9434170.1131660.056583
1390.9368230.1263540.0631769
1400.9274130.1451730.0725867
1410.9148960.1702080.085104
1420.9538480.0923040.046152
1430.9530370.09392570.0469628
1440.9522220.09555590.047778
1450.947150.10570.0528498
1460.9476350.104730.0523649
1470.9410120.1179760.058988
1480.9332810.1334390.0667194
1490.9237620.1524760.0762378
1500.9190730.1618540.0809272
1510.9683550.063290.031645
1520.967310.06538040.0326902
1530.9677710.06445760.0322288
1540.9616240.07675220.0383761
1550.962260.07547960.0377398
1560.9551240.08975120.0448756
1570.9534080.0931840.046592
1580.9458230.1083540.054177
1590.9443380.1113250.0556624
1600.9356530.1286940.0643469
1610.9550830.08983450.0449173
1620.9462930.1074140.0537068
1630.9459060.1081870.0540937
1640.9877920.02441680.0122084
1650.9890150.02196970.0109848
1660.986190.02761990.0138099
1670.9853270.02934620.0146731
1680.9897070.0205860.010293
1690.9869590.02608170.0130408
1700.9871350.02572910.0128645
1710.9848650.03026960.0151348
1720.9896520.02069670.0103483
1730.9881190.02376280.0118814
1740.9859270.02814690.0140734
1750.98360.03280060.0164003
1760.9870940.02581250.0129062
1770.9846890.03062160.0153108
1780.9840930.03181380.0159069
1790.9818560.03628870.0181444
1800.9883080.02338420.0116921
1810.9871640.02567110.0128356
1820.9860310.02793740.0139687
1830.9833860.03322780.0166139
1840.9803840.03923130.0196156
1850.9802740.03945140.0197257
1860.9773220.04535670.0226783
1870.9862720.02745650.0137282
1880.9834390.03312150.0165607
1890.9805910.03881750.0194087
1900.9757090.04858110.0242906
1910.9720630.05587440.0279372
1920.9716090.05678270.0283913
1930.9660120.06797660.0339883
1940.9796970.04060680.0203034
1950.9760660.04786760.0239338
1960.9718610.05627870.0281394
1970.977540.0449210.0224605
1980.9728340.05433110.0271655
1990.9744320.05113620.0255681
2000.9742220.05155630.0257782
2010.9707620.05847570.0292378
2020.9673320.06533540.0326677
2030.9644120.07117570.0355879
2040.9559440.08811140.0440557
2050.9457710.1084590.0542294
2060.9572160.08556780.0427839
2070.9513680.09726320.0486316
2080.9460340.1079320.0539658
2090.9411050.117790.058895
2100.9336680.1326650.0663323
2110.9262990.1474010.0737007
2120.9154520.1690960.0845478
2130.9386250.122750.0613752
2140.929630.140740.0703702
2150.9243740.1512520.0756259
2160.9098580.1802850.0901423
2170.9064870.1870250.0935126
2180.8956870.2086260.104313
2190.8740080.2519840.125992
2200.8492030.3015940.150797
2210.8249670.3500660.175033
2220.8305050.338990.169495
2230.8011870.3976260.198813
2240.8101570.3796850.189843
2250.7915490.4169030.208451
2260.8422560.3154870.157744
2270.8938460.2123080.106154
2280.8925360.2149290.107464
2290.8901990.2196020.109801
2300.9121230.1757540.0878771
2310.9309910.1380180.0690088
2320.9138390.1723210.0861605
2330.9013470.1973060.0986531
2340.8877790.2244420.112221
2350.8618630.2762730.138137
2360.9540370.09192690.0459635
2370.9571510.08569860.0428493
2380.9716640.05667120.0283356
2390.9611290.07774240.0388712
2400.9494360.1011280.0505642
2410.9348450.1303110.0651555
2420.9172780.1654450.0827223
2430.9119430.1761150.0880574
2440.895290.209420.10471
2450.8668910.2662190.133109
2460.8508160.2983680.149184
2470.8176160.3647670.182384
2480.796350.40730.20365
2490.7486820.5026360.251318
2500.6930790.6138430.306921
2510.6380850.723830.361915
2520.5971720.8056560.402828
2530.5282020.9435950.471798
2540.4666830.9333660.533317
2550.503290.9934210.49671
2560.4309630.8619270.569037
2570.3876560.7753110.612344
2580.878290.2434210.12171
2590.8401110.3197780.159889
2600.9890080.02198460.0109923
2610.9908360.01832860.0091643
2620.9817720.03645560.0182278
2630.9989320.0021350.0010675
2640.9967650.006469110.00323456
2650.9916430.01671420.00835711
2660.9833350.03332930.0166647
2670.9612530.07749440.0387472
2680.9019760.1960490.0980244






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level20.00772201OK
5% type I error level370.142857NOK
10% type I error level660.254826NOK

\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 & 2 & 0.00772201 & OK \tabularnewline
5% type I error level & 37 & 0.142857 & NOK \tabularnewline
10% type I error level & 66 & 0.254826 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270372&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]2[/C][C]0.00772201[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]37[/C][C]0.142857[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]66[/C][C]0.254826[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270372&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270372&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level20.00772201OK
5% type I error level370.142857NOK
10% type I error level660.254826NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 2 3 4 5 6 7 ;
Parameters (R input):
par1 = 2 ; 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')
}