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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 16 Dec 2014 16:45:36 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/16/t1418748377l8naor89oo2280p.htm/, Retrieved Thu, 31 Oct 2024 23:11:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269831, Retrieved Thu, 31 Oct 2024 23:11:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140
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 16:45:36] [4bf1efda48b6e8e35beb7b429a900cbb] [Current]
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Dataseries X:
12,9	76	21	0	86	149	96	18	68
7,4	119	26	0	62	152	75	7	55
12,2	119	22	0	70	139	70	31	39
12,8	91	22	0	71	148	88	39	32
7,4	138	18	0	108	158	114	46	62
6,7	97	23	0	64	128	69	31	33
12,6	117	12	0	119	224	176	67	52
14,8	125	20	0	97	159	114	35	62
13,3	95	22	0	129	105	121	52	77
11,1	168	21	0	153	159	110	77	76
8,2	109	19	0	78	167	158	37	41
11,4	115	22	0	80	165	116	32	48
6,4	135	15	0	99	159	181	36	63
10,6	130	20	0	68	119	77	38	30
12,0	131	19	0	147	176	141	69	78
6,3	143	18	0	40	54	35	21	19
11,3	134	15	1	57	91	80	26	31
11,9	109	20	0	120	163	152	54	66
9,3	126	21	0	71	124	97	36	35
9,6	117	21	1	84	137	99	42	42
10,0	155	15	0	68	121	84	23	45
6,4	136	16	0	55	153	68	34	21
13,8	132	23	0	137	148	101	112	25
10,8	129	21	0	79	221	107	35	44
13,8	129	18	0	116	188	88	47	69
11,7	131	25	0	101	149	112	47	54
10,9	123	9	0	111	244	171	37	74
16,1	125	30	1	189	148	137	109	80
13,4	112	20	1	66	92	77	24	42
9,9	131	23	0	81	150	66	20	61
11,5	129	16	0	63	153	93	22	41
8,3	99	16	0	69	94	105	23	46
11,7	114	19	0	71	156	131	32	39
6,1	128	25	0	70	146	89	7	63
9,0	130	25	0	64	132	102	30	34
9,7	112	18	0	143	161	161	92	51
10,8	122	23	0	85	105	120	43	42
10,3	115	21	0	86	97	127	55	31
10,4	124	10	0	55	151	77	16	39
12,7	120	14	1	69	131	108	49	20
9,3	119	22	0	120	166	85	71	49
11,8	123	26	0	96	157	168	43	53
5,9	91	23	0	60	111	48	29	31
11,4	107	23	0	95	145	152	56	39
13,0	118	24	0	100	162	75	46	54
10,8	111	24	0	68	163	107	19	49
12,3	95	18	1	57	59	62	23	34
11,3	135	23	0	105	187	121	59	46
11,8	108	15	0	85	109	124	30	55
7,9	130	19	1	103	90	72	61	42
12,7	143	16	0	57	105	40	7	50
12,3	110	25	1	51	83	58	38	13
11,6	131	23	1	69	116	97	32	37
6,7	113	17	1	41	42	88	16	25
10,9	103	19	0	49	148	126	19	30
12,1	140	21	1	50	155	104	22	28
13,3	125	18	0	93	125	148	48	45
10,1	127	27	0	58	116	146	23	35
5,7	116	21	1	54	128	80	26	28
14,3	120	13	0	74	138	97	33	41
8,0	108	8	1	15	49	25	9	6
13,3	111	29	1	69	96	99	24	45
9,3	125	28	0	107	164	118	34	73
12,5	126	23	0	65	162	58	48	17
7,6	116	21	0	58	99	63	18	40
15,9	104	19	0	107	202	139	43	64
9,2	113	19	0	70	186	50	33	37
9,1	106	20	1	53	66	60	28	25
11,1	139	18	0	136	183	152	71	65
13,0	119	19	0	126	214	142	26	100
14,5	112	17	0	95	188	94	67	28
12,2	101	19	1	69	104	66	34	35
12,3	110	25	0	136	177	127	80	56
11,4	115	19	0	58	126	67	29	29
8,8	116	22	1	59	76	90	16	43
14,6	122	23	1	118	99	75	59	59
7,3	111	26	0	110	157	96	58	52
12,6	115	14	0	82	139	128	32	50
NA	112	28	0	50	78	41	47	3
13,0	109	16	0	102	162	146	43	59
12,6	97	24	1	65	108	69	38	27
13,2	132	20	0	90	159	186	29	61
9,9	102	12	1	64	74	81	36	28
7,7	124	24	0	83	110	85	32	51
10,5	115	22	1	70	96	54	35	35
13,4	128	12	1	50	116	46	21	29
10,9	121	22	1	77	87	106	29	48
4,3	130	20	1	37	97	34	12	25
10,3	99	10	1	81	127	60	37	44
11,8	122	23	1	101	106	95	37	64
11,2	126	17	1	79	80	57	47	32
11,4	141	22	1	71	74	62	51	20
8,6	124	24	1	60	91	36	32	28
13,2	127	18	1	55	133	56	21	34
12,6	114	21	1	44	74	54	13	31
5,6	99	20	1	40	114	64	14	26
9,9	137	20	1	56	140	76	-2	58
8,8	97	22	1	43	95	98	20	23
7,7	108	19	1	45	98	88	24	21
9,0	138	20	1	32	121	35	11	21
7,3	123	26	1	56	126	102	23	33
11,4	125	23	1	40	98	61	24	16
13,6	106	24	1	34	95	80	14	20
7,9	138	21	1	89	110	49	52	37
10,7	127	21	1	50	70	78	15	35
10,3	142	19	1	56	102	90	23	33
8,3	94	8	1	46	86	45	19	27
9,6	133	17	1	76	130	55	35	41
14,2	119	20	1	64	96	96	24	40
8,5	114	11	1	74	102	43	39	35
13,5	114	8	1	57	100	52	29	28
4,9	123	15	1	45	94	60	13	32
6,4	126	18	1	30	52	54	8	22
9,6	118	18	1	62	98	51	18	44
11,6	132	19	1	51	118	51	24	27
11,1	127	19	1	36	99	38	19	17
4,35	103	23	0	34	48	41	23	12
12,7	72	22	0	61	50	146	16	45
18,1	113	21	0	70	150	182	33	37
17,85	125	25	0	69	154	192	32	37
16,6	109	30	1	145	109	263	37	108
12,6	111	17	1	23	68	35	14	10
17,1	105	27	0	120	194	439	52	68
19,1	122	23	0	147	158	214	75	72
16,1	127	23	0	215	159	341	72	143
13,35	117	18	0	24	67	58	15	9
18,4	91	18	0	84	147	292	29	55
14,7	143	23	0	30	39	85	13	17
10,6	116	19	0	77	100	200	40	37
12,6	123	15	0	46	111	158	19	27
16,2	101	20	0	61	138	199	24	37
13,6	119	16	0	178	101	297	121	58
18,9	143	24	1	160	131	227	93	66
14,1	114	25	0	57	101	108	36	21
14,5	108	25	0	42	114	86	23	19
16,15	128	19	0	163	165	302	85	78
14,75	122	19	0	75	114	148	41	35
14,8	133	16	0	94	111	178	46	48
12,45	94	19	0	45	75	120	18	27
12,65	128	19	0	78	82	207	35	43
17,35	108	23	0	47	121	157	17	30
8,6	125	21	0	29	32	128	4	25
18,4	130	22	0	97	150	296	28	69
16,1	112	19	0	116	117	323	44	72
11,6	89	20	1	32	71	79	10	23
17,75	117	20	0	50	165	70	38	13
15,25	142	3	0	118	154	146	57	61
17,65	128	23	0	66	126	246	23	43
15,6	114	14	0	48	138	145	26	22
16,35	123	23	0	86	149	196	36	51
17,65	89	20	0	89	145	199	22	67
13,6	125	15	0	76	120	127	40	36
11,7	110	13	0	39	138	91	18	21
14,35	112	16	0	75	109	153	31	44
14,75	109	7	0	57	132	299	11	45
18,25	108	24	0	72	172	228	38	34
9,9	139	17	0	60	169	190	24	36
16	116	24	0	109	114	180	37	72
18,25	116	24	0	76	156	212	37	39
16,85	88	19	0	65	172	269	22	43
14,6	128	25	1	40	68	130	15	25
13,85	125	20	1	58	89	179	2	56
18,95	134	28	0	123	167	243	43	80
15,6	126	23	0	71	113	190	31	40
14,85	121	27	1	102	115	299	29	73
11,75	106	18	1	80	78	121	45	34
18,45	109	28	1	97	118	137	25	72
15,9	127	21	1	46	87	305	4	42
17,1	101	19	0	93	173	157	31	61
16,1	120	23	0	19	2	96	-4	23
19,9	99	27	1	140	162	183	66	74
10,95	116	22	1	78	49	52	61	16
18,45	125	28	1	98	122	238	32	66
15,1	121	25	1	40	96	40	31	9
15	127	21	1	80	100	226	39	41
11,35	129	22	1	76	82	190	19	57
15,95	155	28	1	79	100	214	31	48
18,1	113	20	1	87	115	145	36	51
14,6	125	29	1	95	141	119	42	53
15,4	114	25	0	49	165	222	21	29
15,4	116	25	0	49	165	222	21	29
17,6	127	20	1	80	110	159	25	55
13,35	102	20	0	86	118	165	32	54
19,1	87	16	0	69	158	249	26	43
15,35	110	20	1	79	146	125	28	51
7,6	115	20	0	52	49	122	32	20
13,4	108	23	1	120	90	186	41	79
13,9	97	18	1	69	121	148	29	39
19,1	119	25	0	94	155	274	33	61
15,25	130	18	1	72	104	172	17	55
12,9	97	19	1	43	147	84	13	30
16,1	120	25	1	87	110	168	32	55
17,35	125	25	1	52	108	102	30	22
13,15	131	25	1	71	113	106	34	37
12,15	129	24	1	61	115	2	59	2
12,6	125	19	1	51	61	139	13	38
10,35	108	26	1	50	60	95	23	27
15,4	142	10	1	67	109	130	10	56
9,6	117	17	1	30	68	72	5	25
18,2	130	13	1	70	111	141	31	39
13,6	93	17	1	52	77	113	19	33
14,85	97	30	1	75	73	206	32	43
14,75	120	25	0	87	151	268	30	57
14,1	110	4	1	69	89	175	25	43
14,9	111	16	1	72	78	77	48	23
16,25	130	21	1	79	110	125	35	44
19,25	66	23	0	121	220	255	67	54
13,6	113	22	1	43	65	111	15	28
13,6	126	17	0	58	141	132	22	36
15,65	114	20	1	57	117	211	18	39
12,75	130	20	0	50	122	92	33	16
14,6	112	22	1	69	63	76	46	23
9,85	126	16	0	64	44	171	24	40
12,65	86	23	1	38	52	83	14	24
11,9	122	16	1	53	62	119	23	29
19,2	118	0	1	90	131	266	12	78
16,6	124	18	1	96	101	186	38	57
11,2	120	25	1	49	42	50	12	37
15,25	128	23	0	56	152	117	28	27
11,9	134	12	0	102	107	219	41	61
13,2	133	18	1	40	77	246	12	27
16,35	131	24	0	100	154	279	31	69
12,4	102	11	0	67	103	148	33	34
15,85	97	18	1	78	96	137	34	44
14,35	93	14	0	62	154	130	41	21
18,15	129	23	0	55	175	181	21	34
11,15	115	24	1	59	57	98	20	39
15,65	116	29	1	96	112	226	44	51
17,75	136	18	0	86	143	234	52	34
7,65	142	15	1	38	49	138	7	31
12,35	112	29	0	43	110	85	29	13
15,6	120	16	0	23	131	66	11	12
19,3	121	19	0	77	167	236	26	51
15,2	110	22	1	48	56	106	24	24
17,1	122	16	0	26	137	135	7	19
15,6	133	23	1	91	86	122	60	30
18,4	136	23	0	94	121	218	13	81
19,05	118	19	0	62	149	199	20	42
18,55	130	4	0	74	168	112	52	22
19,1	114	20	0	114	140	278	28	85
13,1	147	24	1	52	88	94	25	27
12,85	123	20	0	64	168	113	39	25
9,5	121	4	0	31	94	84	9	22
4,5	119	24	0	38	51	86	19	19
11,85	129	22	1	27	48	62	13	14
13,6	137	16	0	105	145	222	60	45
11,7	63	3	0	64	66	167	19	45
12,4	134	15	1	62	85	82	34	28
13,35	140	24	0	65	109	207	14	51
11,4	134	17	1	58	63	184	17	41
14,9	121	20	1	76	102	83	45	31
19,9	105	27	1	140	162	183	66	74
17,75	114	23	0	48	128	85	24	24
11,2	106	26	1	68	86	89	48	19
14,6	135	23	1	80	114	225	29	51
17,6	100	17	0	71	164	237	-2	73
14,05	101	20	0	76	119	102	51	24
16,1	131	22	0	63	126	221	2	61
13,35	131	19	0	46	132	128	24	23
11,85	129	24	0	53	142	91	40	14
11,95	120	19	0	74	83	198	20	54
14,75	117	23	1	70	94	204	19	51
15,15	82	15	1	78	81	158	16	62
13,2	106	27	0	56	166	138	20	36
16,85	125	26	1	100	110	226	40	59
7,85	130	22	1	51	64	44	27	24
7,7	147	22	0	52	93	196	25	26
12,6	125	18	1	102	104	83	49	54
7,85	97	15	1	78	105	79	39	39
10,95	101	22	1	78	49	52	61	16
12,35	128	27	1	55	88	105	19	36
9,95	97	10	1	98	95	116	67	31
14,9	126	20	1	76	102	83	45	31
16,65	118	17	1	73	99	196	30	42
13,4	107	23	1	47	63	153	8	39
13,95	87	19	1	45	76	157	19	25
15,7	156	13	1	83	109	75	52	31
16,85	133	27	1	60	117	106	22	38
10,95	132	23	1	48	57	58	17	31
15,35	133	16	1	50	120	75	33	17
12,2	122	25	1	56	73	74	34	22
15,1	125	2	1	77	91	185	22	55
17,75	127	26	1	91	108	265	30	62
15,2	125	20	1	76	105	131	25	51
14,6	99	23	0	68	117	139	38	30
16,65	128	22	1	74	119	196	26	49
8,1	110	24	1	29	31	78	13	16




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 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 & 10 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269831&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]10 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=269831&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269831&T=0

As an alternative you can also use a 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 time10 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Multiple Linear Regression - Estimated Regression Equation
TOT.SCORE[t] = + 7.08954 -0.0114471TOT.AMS[t] + 0.0326666NUMERACY[t] + 1.51503BA_of_SCH[t] + 0.183531H[t] + 0.0210737zinvolle_teksten[t] + 0.0310855B[t] -0.179839PRH[t] -0.20493CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT.SCORE[t] =  +  7.08954 -0.0114471TOT.AMS[t] +  0.0326666NUMERACY[t] +  1.51503BA_of_SCH[t] +  0.183531H[t] +  0.0210737zinvolle_teksten[t] +  0.0310855B[t] -0.179839PRH[t] -0.20493CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269831&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT.SCORE[t] =  +  7.08954 -0.0114471TOT.AMS[t] +  0.0326666NUMERACY[t] +  1.51503BA_of_SCH[t] +  0.183531H[t] +  0.0210737zinvolle_teksten[t] +  0.0310855B[t] -0.179839PRH[t] -0.20493CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269831&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269831&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
TOT.SCORE[t] = + 7.08954 -0.0114471TOT.AMS[t] + 0.0326666NUMERACY[t] + 1.51503BA_of_SCH[t] + 0.183531H[t] + 0.0210737zinvolle_teksten[t] + 0.0310855B[t] -0.179839PRH[t] -0.20493CH[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)7.089541.503314.7163.818e-061.909e-06
TOT.AMS-0.01144710.010595-1.080.2808930.140447
NUMERACY0.03266660.03141631.040.299340.14967
BA_of_SCH1.515030.3845043.940.0001031185.15591e-05
H0.1835310.439930.41720.6768680.338434
zinvolle_teksten0.02107370.005386353.9120.0001150335.75165e-05
B0.03108550.0029072810.691.44821e-227.24107e-23
PRH-0.1798390.440728-0.40810.6835520.341776
CH-0.204930.439965-0.46580.6417340.320867

\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) & 7.08954 & 1.50331 & 4.716 & 3.818e-06 & 1.909e-06 \tabularnewline
TOT.AMS & -0.0114471 & 0.010595 & -1.08 & 0.280893 & 0.140447 \tabularnewline
NUMERACY & 0.0326666 & 0.0314163 & 1.04 & 0.29934 & 0.14967 \tabularnewline
BA_of_SCH & 1.51503 & 0.384504 & 3.94 & 0.000103118 & 5.15591e-05 \tabularnewline
H & 0.183531 & 0.43993 & 0.4172 & 0.676868 & 0.338434 \tabularnewline
zinvolle_teksten & 0.0210737 & 0.00538635 & 3.912 & 0.000115033 & 5.75165e-05 \tabularnewline
B & 0.0310855 & 0.00290728 & 10.69 & 1.44821e-22 & 7.24107e-23 \tabularnewline
PRH & -0.179839 & 0.440728 & -0.4081 & 0.683552 & 0.341776 \tabularnewline
CH & -0.20493 & 0.439965 & -0.4658 & 0.641734 & 0.320867 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269831&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]7.08954[/C][C]1.50331[/C][C]4.716[/C][C]3.818e-06[/C][C]1.909e-06[/C][/ROW]
[ROW][C]TOT.AMS[/C][C]-0.0114471[/C][C]0.010595[/C][C]-1.08[/C][C]0.280893[/C][C]0.140447[/C][/ROW]
[ROW][C]NUMERACY[/C][C]0.0326666[/C][C]0.0314163[/C][C]1.04[/C][C]0.29934[/C][C]0.14967[/C][/ROW]
[ROW][C]BA_of_SCH[/C][C]1.51503[/C][C]0.384504[/C][C]3.94[/C][C]0.000103118[/C][C]5.15591e-05[/C][/ROW]
[ROW][C]H[/C][C]0.183531[/C][C]0.43993[/C][C]0.4172[/C][C]0.676868[/C][C]0.338434[/C][/ROW]
[ROW][C]zinvolle_teksten[/C][C]0.0210737[/C][C]0.00538635[/C][C]3.912[/C][C]0.000115033[/C][C]5.75165e-05[/C][/ROW]
[ROW][C]B[/C][C]0.0310855[/C][C]0.00290728[/C][C]10.69[/C][C]1.44821e-22[/C][C]7.24107e-23[/C][/ROW]
[ROW][C]PRH[/C][C]-0.179839[/C][C]0.440728[/C][C]-0.4081[/C][C]0.683552[/C][C]0.341776[/C][/ROW]
[ROW][C]CH[/C][C]-0.20493[/C][C]0.439965[/C][C]-0.4658[/C][C]0.641734[/C][C]0.320867[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269831&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269831&T=2

As an alternative you can also use a 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)7.089541.503314.7163.818e-061.909e-06
TOT.AMS-0.01144710.010595-1.080.2808930.140447
NUMERACY0.03266660.03141631.040.299340.14967
BA_of_SCH1.515030.3845043.940.0001031185.15591e-05
H0.1835310.439930.41720.6768680.338434
zinvolle_teksten0.02107370.005386353.9120.0001150335.75165e-05
B0.03108550.0029072810.691.44821e-227.24107e-23
PRH-0.1798390.440728-0.40810.6835520.341776
CH-0.204930.439965-0.46580.6417340.320867







Multiple Linear Regression - Regression Statistics
Multiple R0.634612
R-squared0.402732
Adjusted R-squared0.385482
F-TEST (value)23.3473
F-TEST (DF numerator)8
F-TEST (DF denominator)277
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.68197
Sum Squared Residuals1992.45

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.634612 \tabularnewline
R-squared & 0.402732 \tabularnewline
Adjusted R-squared & 0.385482 \tabularnewline
F-TEST (value) & 23.3473 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 277 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.68197 \tabularnewline
Sum Squared Residuals & 1992.45 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269831&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.634612[/C][/ROW]
[ROW][C]R-squared[/C][C]0.402732[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.385482[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]23.3473[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]277[/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]2.68197[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1992.45[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269831&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269831&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.634612
R-squared0.402732
Adjusted R-squared0.385482
F-TEST (value)23.3473
F-TEST (DF numerator)8
F-TEST (DF denominator)277
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.68197
Sum Squared Residuals1992.45







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.64111.25893
27.410.9602-3.56018
312.210.83111.36888
412.812.08020.719832
57.411.8143-4.41432
66.710.9811-4.28112
712.615.4684-2.8684
814.812.00892.79107
913.311.23912.06093
1011.111.2805-0.180501
118.214.1525-5.95253
1211.412.6659-1.26586
136.413.7961-7.39614
1410.610.6544-0.0544257
151212.8883-0.88828
166.37.93752-1.63752
1711.311.3978-0.0978253
1811.913.4422-1.54217
199.311.3456-2.04558
209.613.1721-3.57212
211010.0883-0.0882972
226.411.0696-4.66964
2313.812.46691.33308
2410.813.47-2.66996
2513.811.59522.20477
2611.712.0462-0.346165
2710.914.9862-4.08623
2816.114.22181.8782
2913.411.4981.90196
309.910.3225-0.4225
3111.511.45460.0453786
328.310.8244-2.52441
3311.713.0485-1.34851
346.110.9621-4.86205
35911.7537-2.75372
369.714.0414-4.3414
3710.811.6473-0.847316
3810.311.9908-1.69081
3910.410.797-0.396989
4012.713.5591-0.859064
419.311.8001-2.50008
4211.814.0864-2.28642
435.910.0742-4.17417
4411.413.7689-2.3689
451311.28241.71759
4610.812.3857-1.58567
4712.310.63311.66691
4811.313.2311-1.93111
4911.811.42870.371302
507.911.1983-3.29835
5112.78.387324.31268
5212.311.57620.723764
5311.612.6426-1.04255
546.711.0111-4.31109
5510.912.995-2.09501
5612.113.6693-1.56934
5713.312.69580.604227
5810.112.8367-2.73674
595.712.6438-6.9438
6014.311.30852.99151
6189.3442-1.3442
6213.312.50750.792537
639.312.2609-2.96089
6412.511.42891.07113
657.69.70285-2.10285
6615.913.88672.0133
679.211.2207-2.02074
689.110.8689-1.7689
6911.113.5391-2.43906
701313.228-0.228003
7114.512.89491.60512
7212.211.68890.511053
7312.313.4219-1.12194
7411.410.61830.781701
758.811.5336-2.73358
7614.611.33233.26766
777.312.0624-4.7624
7812.612.18680.413165
79NANA-0.213104
801312.66160.338421
8112.613.5662-0.966201
8213.214.7401-1.54008
839.912.6413-2.74126
847.78.28876-0.588763
8510.57.962782.53722
8613.414.6465-1.24652
8710.916.9802-6.08016
884.35.53451-1.23451
8910.310.4134-0.113354
9011.811.26410.535911
9111.210.75630.443744
9211.413.3249-1.92488
938.67.032341.56766
9413.211.20831.9917
9512.619.0118-6.41183
965.67.45394-1.85394
979.913.9429-4.04291
988.813.5289-4.72892
997.79.60735-1.90735
100914.9507-5.95066
1017.37.53268-0.232676
10211.410.08771.31228
10313.616.6524-3.05238
1047.98.24303-0.343028
10510.712.3257-1.62571
10610.312.4934-2.19344
1078.310.0386-1.73858
1089.67.535632.06437
10914.216.2401-2.04015
1108.55.792642.70736
11113.519.4959-5.99586
1124.98.58344-3.68344
1136.47.41729-1.01729
1149.69.297110.30289
11511.611.24540.354636
11611.115.3425-4.24246
1174.353.322291.02771
11812.79.23073.4693
11918.115.26552.83454
12017.8517.8849-0.0348562
12116.614.06442.53555
12212.618.7413-6.14127
12317.113.16243.93757
12419.120.5437-1.44372
12516.112.16593.93409
12613.3512.69080.659231
12718.413.05235.34771
12814.718.1627-3.46272
12910.610.9146-0.314608
13012.611.37771.22226
13116.219.2329-3.03288
13213.611.38322.21676
13318.916.57042.32956
13414.111.0243.07599
13514.516.1046-1.60464
13616.1513.93562.21441
13714.7513.05481.69519
13814.813.78361.01635
13912.4513.4168-0.966774
14012.658.755723.89428
14117.3519.2277-1.87774
1428.67.509281.09072
14318.419.8561-1.45608
14416.116.05230.0476915
14511.65.585286.01472
14617.7514.7512.99902
14715.2513.44271.80728
14817.6515.33272.31732
14915.613.77361.82636
15016.3513.31333.03673
15117.6516.05271.59733
15213.613.50910.0909472
15311.79.906141.79386
15414.3517.0079-2.65795
15514.7513.26211.48785
15618.2523.1897-4.93967
1579.97.039342.86066
1581613.47532.52466
15918.2519.2506-1.0006
16016.8515.20051.64946
16114.614.8259-0.225916
16213.8510.89022.95979
16318.9517.29461.6554
16415.619.1144-3.51444
16514.8516.1064-1.25637
16611.756.868484.88152
16718.4520.8173-2.36728
16815.912.87293.02714
16917.19.986637.11337
17016.112.3163.78397
17119.919.66080.239219
17210.959.263491.68651
17318.4514.57453.87551
17415.116.3361-1.2361
1751517.9812-2.98125
17611.3510.99190.358105
17715.9511.78684.16319
17818.117.31250.787507
17914.615.4528-0.852804
18015.416.2299-0.82991
18115.411.78023.61983
18217.617.40370.196335
18313.3511.11212.23793
18419.117.72321.37681
18515.3518.6917-3.34166
1867.68.45899-0.858994
18713.414.1888-0.788807
18813.911.94431.95566
18919.117.97861.12137
19015.2515.5799-0.32991
19112.911.32921.57075
19216.111.8274.27299
19317.3517.13180.218182
19413.1511.57261.57743
19512.1512.1856-0.0355589
19612.614.1923-1.5923
19710.357.6162.734
19815.416.7752-1.37524
1999.64.943244.65676
20018.217.19461.00536
20113.614.3642-0.764173
20214.8517.0366-2.18661
20314.7514.7972-0.047247
20414.110.96253.1375
20514.911.84393.0561
20616.2515.74020.50981
20719.2517.95621.2938
20813.612.58811.01193
20913.614.1595-0.559488
21015.6514.54861.10141
21112.759.558953.19105
21214.616.3954-1.79538
2139.858.785491.06451
21412.6513.1343-0.484306
21511.99.358392.54161
21619.217.38761.81245
21716.615.13951.46051
21811.28.874982.32502
21915.2517.2063-1.95626
22011.915.2899-3.38987
22113.213.7801-0.580087
22216.3516.3968-0.0467789
22312.410.0982.30204
22415.8514.97070.879253
22514.3511.22853.12147
22618.1518.559-0.409007
22711.1512.3642-1.21424
22815.6513.77271.87731
22917.7522.254-4.50396
2307.657.027580.62242
23112.357.584684.76532
23215.612.48523.11477
23319.316.21433.08573
23415.211.01864.18144
23517.114.70132.39872
23615.611.12534.47471
23718.414.21054.18948
23819.0512.97526.07476
23918.5515.9482.60203
24019.117.99691.10311
24113.113.2469-0.146933
24212.8513.3397-0.489667
2439.514.923-5.42301
2444.53.183811.31619
24511.8513.5092-1.65918
24613.614.0557-0.455703
24711.710.72730.972714
24812.413.013-0.613011
24913.3515.8088-2.45877
25011.48.605182.79482
25114.911.04733.85265
25219.913.60066.29937
25317.7519.3236-1.57362
25411.212.8229-1.6229
25514.612.7541.846
25617.615.67341.92655
25714.0512.48591.56414
25816.115.13420.965794
25913.3513.3827-0.0326691
26011.8513.0589-1.20889
26111.9512.5178-0.567755
26214.7513.10671.64328
26315.1515.7997-0.649654
26413.212.78510.414893
26516.8519.1377-2.2877
2667.8514.0475-6.19755
2677.76.475271.22473
26812.616.7121-4.11212
2697.857.782490.0675121
27010.9511.0396-0.0895841
27112.3515.4128-3.06277
2729.957.097952.85205
27314.913.63371.26627
27416.6516.6598-0.00975863
27513.413.8801-0.480063
27613.959.650544.29946
27715.711.84293.85715
27816.8516.14840.701562
27910.957.823083.12692
28015.3514.66810.681857
28112.210.91181.28819
28215.114.46420.635779
28317.7515.66292.0871
28415.213.59241.60756
28514.613.27241.32756
28616.6519.463-2.81295
2878.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 11.6411 & 1.25893 \tabularnewline
2 & 7.4 & 10.9602 & -3.56018 \tabularnewline
3 & 12.2 & 10.8311 & 1.36888 \tabularnewline
4 & 12.8 & 12.0802 & 0.719832 \tabularnewline
5 & 7.4 & 11.8143 & -4.41432 \tabularnewline
6 & 6.7 & 10.9811 & -4.28112 \tabularnewline
7 & 12.6 & 15.4684 & -2.8684 \tabularnewline
8 & 14.8 & 12.0089 & 2.79107 \tabularnewline
9 & 13.3 & 11.2391 & 2.06093 \tabularnewline
10 & 11.1 & 11.2805 & -0.180501 \tabularnewline
11 & 8.2 & 14.1525 & -5.95253 \tabularnewline
12 & 11.4 & 12.6659 & -1.26586 \tabularnewline
13 & 6.4 & 13.7961 & -7.39614 \tabularnewline
14 & 10.6 & 10.6544 & -0.0544257 \tabularnewline
15 & 12 & 12.8883 & -0.88828 \tabularnewline
16 & 6.3 & 7.93752 & -1.63752 \tabularnewline
17 & 11.3 & 11.3978 & -0.0978253 \tabularnewline
18 & 11.9 & 13.4422 & -1.54217 \tabularnewline
19 & 9.3 & 11.3456 & -2.04558 \tabularnewline
20 & 9.6 & 13.1721 & -3.57212 \tabularnewline
21 & 10 & 10.0883 & -0.0882972 \tabularnewline
22 & 6.4 & 11.0696 & -4.66964 \tabularnewline
23 & 13.8 & 12.4669 & 1.33308 \tabularnewline
24 & 10.8 & 13.47 & -2.66996 \tabularnewline
25 & 13.8 & 11.5952 & 2.20477 \tabularnewline
26 & 11.7 & 12.0462 & -0.346165 \tabularnewline
27 & 10.9 & 14.9862 & -4.08623 \tabularnewline
28 & 16.1 & 14.2218 & 1.8782 \tabularnewline
29 & 13.4 & 11.498 & 1.90196 \tabularnewline
30 & 9.9 & 10.3225 & -0.4225 \tabularnewline
31 & 11.5 & 11.4546 & 0.0453786 \tabularnewline
32 & 8.3 & 10.8244 & -2.52441 \tabularnewline
33 & 11.7 & 13.0485 & -1.34851 \tabularnewline
34 & 6.1 & 10.9621 & -4.86205 \tabularnewline
35 & 9 & 11.7537 & -2.75372 \tabularnewline
36 & 9.7 & 14.0414 & -4.3414 \tabularnewline
37 & 10.8 & 11.6473 & -0.847316 \tabularnewline
38 & 10.3 & 11.9908 & -1.69081 \tabularnewline
39 & 10.4 & 10.797 & -0.396989 \tabularnewline
40 & 12.7 & 13.5591 & -0.859064 \tabularnewline
41 & 9.3 & 11.8001 & -2.50008 \tabularnewline
42 & 11.8 & 14.0864 & -2.28642 \tabularnewline
43 & 5.9 & 10.0742 & -4.17417 \tabularnewline
44 & 11.4 & 13.7689 & -2.3689 \tabularnewline
45 & 13 & 11.2824 & 1.71759 \tabularnewline
46 & 10.8 & 12.3857 & -1.58567 \tabularnewline
47 & 12.3 & 10.6331 & 1.66691 \tabularnewline
48 & 11.3 & 13.2311 & -1.93111 \tabularnewline
49 & 11.8 & 11.4287 & 0.371302 \tabularnewline
50 & 7.9 & 11.1983 & -3.29835 \tabularnewline
51 & 12.7 & 8.38732 & 4.31268 \tabularnewline
52 & 12.3 & 11.5762 & 0.723764 \tabularnewline
53 & 11.6 & 12.6426 & -1.04255 \tabularnewline
54 & 6.7 & 11.0111 & -4.31109 \tabularnewline
55 & 10.9 & 12.995 & -2.09501 \tabularnewline
56 & 12.1 & 13.6693 & -1.56934 \tabularnewline
57 & 13.3 & 12.6958 & 0.604227 \tabularnewline
58 & 10.1 & 12.8367 & -2.73674 \tabularnewline
59 & 5.7 & 12.6438 & -6.9438 \tabularnewline
60 & 14.3 & 11.3085 & 2.99151 \tabularnewline
61 & 8 & 9.3442 & -1.3442 \tabularnewline
62 & 13.3 & 12.5075 & 0.792537 \tabularnewline
63 & 9.3 & 12.2609 & -2.96089 \tabularnewline
64 & 12.5 & 11.4289 & 1.07113 \tabularnewline
65 & 7.6 & 9.70285 & -2.10285 \tabularnewline
66 & 15.9 & 13.8867 & 2.0133 \tabularnewline
67 & 9.2 & 11.2207 & -2.02074 \tabularnewline
68 & 9.1 & 10.8689 & -1.7689 \tabularnewline
69 & 11.1 & 13.5391 & -2.43906 \tabularnewline
70 & 13 & 13.228 & -0.228003 \tabularnewline
71 & 14.5 & 12.8949 & 1.60512 \tabularnewline
72 & 12.2 & 11.6889 & 0.511053 \tabularnewline
73 & 12.3 & 13.4219 & -1.12194 \tabularnewline
74 & 11.4 & 10.6183 & 0.781701 \tabularnewline
75 & 8.8 & 11.5336 & -2.73358 \tabularnewline
76 & 14.6 & 11.3323 & 3.26766 \tabularnewline
77 & 7.3 & 12.0624 & -4.7624 \tabularnewline
78 & 12.6 & 12.1868 & 0.413165 \tabularnewline
79 & NA & NA & -0.213104 \tabularnewline
80 & 13 & 12.6616 & 0.338421 \tabularnewline
81 & 12.6 & 13.5662 & -0.966201 \tabularnewline
82 & 13.2 & 14.7401 & -1.54008 \tabularnewline
83 & 9.9 & 12.6413 & -2.74126 \tabularnewline
84 & 7.7 & 8.28876 & -0.588763 \tabularnewline
85 & 10.5 & 7.96278 & 2.53722 \tabularnewline
86 & 13.4 & 14.6465 & -1.24652 \tabularnewline
87 & 10.9 & 16.9802 & -6.08016 \tabularnewline
88 & 4.3 & 5.53451 & -1.23451 \tabularnewline
89 & 10.3 & 10.4134 & -0.113354 \tabularnewline
90 & 11.8 & 11.2641 & 0.535911 \tabularnewline
91 & 11.2 & 10.7563 & 0.443744 \tabularnewline
92 & 11.4 & 13.3249 & -1.92488 \tabularnewline
93 & 8.6 & 7.03234 & 1.56766 \tabularnewline
94 & 13.2 & 11.2083 & 1.9917 \tabularnewline
95 & 12.6 & 19.0118 & -6.41183 \tabularnewline
96 & 5.6 & 7.45394 & -1.85394 \tabularnewline
97 & 9.9 & 13.9429 & -4.04291 \tabularnewline
98 & 8.8 & 13.5289 & -4.72892 \tabularnewline
99 & 7.7 & 9.60735 & -1.90735 \tabularnewline
100 & 9 & 14.9507 & -5.95066 \tabularnewline
101 & 7.3 & 7.53268 & -0.232676 \tabularnewline
102 & 11.4 & 10.0877 & 1.31228 \tabularnewline
103 & 13.6 & 16.6524 & -3.05238 \tabularnewline
104 & 7.9 & 8.24303 & -0.343028 \tabularnewline
105 & 10.7 & 12.3257 & -1.62571 \tabularnewline
106 & 10.3 & 12.4934 & -2.19344 \tabularnewline
107 & 8.3 & 10.0386 & -1.73858 \tabularnewline
108 & 9.6 & 7.53563 & 2.06437 \tabularnewline
109 & 14.2 & 16.2401 & -2.04015 \tabularnewline
110 & 8.5 & 5.79264 & 2.70736 \tabularnewline
111 & 13.5 & 19.4959 & -5.99586 \tabularnewline
112 & 4.9 & 8.58344 & -3.68344 \tabularnewline
113 & 6.4 & 7.41729 & -1.01729 \tabularnewline
114 & 9.6 & 9.29711 & 0.30289 \tabularnewline
115 & 11.6 & 11.2454 & 0.354636 \tabularnewline
116 & 11.1 & 15.3425 & -4.24246 \tabularnewline
117 & 4.35 & 3.32229 & 1.02771 \tabularnewline
118 & 12.7 & 9.2307 & 3.4693 \tabularnewline
119 & 18.1 & 15.2655 & 2.83454 \tabularnewline
120 & 17.85 & 17.8849 & -0.0348562 \tabularnewline
121 & 16.6 & 14.0644 & 2.53555 \tabularnewline
122 & 12.6 & 18.7413 & -6.14127 \tabularnewline
123 & 17.1 & 13.1624 & 3.93757 \tabularnewline
124 & 19.1 & 20.5437 & -1.44372 \tabularnewline
125 & 16.1 & 12.1659 & 3.93409 \tabularnewline
126 & 13.35 & 12.6908 & 0.659231 \tabularnewline
127 & 18.4 & 13.0523 & 5.34771 \tabularnewline
128 & 14.7 & 18.1627 & -3.46272 \tabularnewline
129 & 10.6 & 10.9146 & -0.314608 \tabularnewline
130 & 12.6 & 11.3777 & 1.22226 \tabularnewline
131 & 16.2 & 19.2329 & -3.03288 \tabularnewline
132 & 13.6 & 11.3832 & 2.21676 \tabularnewline
133 & 18.9 & 16.5704 & 2.32956 \tabularnewline
134 & 14.1 & 11.024 & 3.07599 \tabularnewline
135 & 14.5 & 16.1046 & -1.60464 \tabularnewline
136 & 16.15 & 13.9356 & 2.21441 \tabularnewline
137 & 14.75 & 13.0548 & 1.69519 \tabularnewline
138 & 14.8 & 13.7836 & 1.01635 \tabularnewline
139 & 12.45 & 13.4168 & -0.966774 \tabularnewline
140 & 12.65 & 8.75572 & 3.89428 \tabularnewline
141 & 17.35 & 19.2277 & -1.87774 \tabularnewline
142 & 8.6 & 7.50928 & 1.09072 \tabularnewline
143 & 18.4 & 19.8561 & -1.45608 \tabularnewline
144 & 16.1 & 16.0523 & 0.0476915 \tabularnewline
145 & 11.6 & 5.58528 & 6.01472 \tabularnewline
146 & 17.75 & 14.751 & 2.99902 \tabularnewline
147 & 15.25 & 13.4427 & 1.80728 \tabularnewline
148 & 17.65 & 15.3327 & 2.31732 \tabularnewline
149 & 15.6 & 13.7736 & 1.82636 \tabularnewline
150 & 16.35 & 13.3133 & 3.03673 \tabularnewline
151 & 17.65 & 16.0527 & 1.59733 \tabularnewline
152 & 13.6 & 13.5091 & 0.0909472 \tabularnewline
153 & 11.7 & 9.90614 & 1.79386 \tabularnewline
154 & 14.35 & 17.0079 & -2.65795 \tabularnewline
155 & 14.75 & 13.2621 & 1.48785 \tabularnewline
156 & 18.25 & 23.1897 & -4.93967 \tabularnewline
157 & 9.9 & 7.03934 & 2.86066 \tabularnewline
158 & 16 & 13.4753 & 2.52466 \tabularnewline
159 & 18.25 & 19.2506 & -1.0006 \tabularnewline
160 & 16.85 & 15.2005 & 1.64946 \tabularnewline
161 & 14.6 & 14.8259 & -0.225916 \tabularnewline
162 & 13.85 & 10.8902 & 2.95979 \tabularnewline
163 & 18.95 & 17.2946 & 1.6554 \tabularnewline
164 & 15.6 & 19.1144 & -3.51444 \tabularnewline
165 & 14.85 & 16.1064 & -1.25637 \tabularnewline
166 & 11.75 & 6.86848 & 4.88152 \tabularnewline
167 & 18.45 & 20.8173 & -2.36728 \tabularnewline
168 & 15.9 & 12.8729 & 3.02714 \tabularnewline
169 & 17.1 & 9.98663 & 7.11337 \tabularnewline
170 & 16.1 & 12.316 & 3.78397 \tabularnewline
171 & 19.9 & 19.6608 & 0.239219 \tabularnewline
172 & 10.95 & 9.26349 & 1.68651 \tabularnewline
173 & 18.45 & 14.5745 & 3.87551 \tabularnewline
174 & 15.1 & 16.3361 & -1.2361 \tabularnewline
175 & 15 & 17.9812 & -2.98125 \tabularnewline
176 & 11.35 & 10.9919 & 0.358105 \tabularnewline
177 & 15.95 & 11.7868 & 4.16319 \tabularnewline
178 & 18.1 & 17.3125 & 0.787507 \tabularnewline
179 & 14.6 & 15.4528 & -0.852804 \tabularnewline
180 & 15.4 & 16.2299 & -0.82991 \tabularnewline
181 & 15.4 & 11.7802 & 3.61983 \tabularnewline
182 & 17.6 & 17.4037 & 0.196335 \tabularnewline
183 & 13.35 & 11.1121 & 2.23793 \tabularnewline
184 & 19.1 & 17.7232 & 1.37681 \tabularnewline
185 & 15.35 & 18.6917 & -3.34166 \tabularnewline
186 & 7.6 & 8.45899 & -0.858994 \tabularnewline
187 & 13.4 & 14.1888 & -0.788807 \tabularnewline
188 & 13.9 & 11.9443 & 1.95566 \tabularnewline
189 & 19.1 & 17.9786 & 1.12137 \tabularnewline
190 & 15.25 & 15.5799 & -0.32991 \tabularnewline
191 & 12.9 & 11.3292 & 1.57075 \tabularnewline
192 & 16.1 & 11.827 & 4.27299 \tabularnewline
193 & 17.35 & 17.1318 & 0.218182 \tabularnewline
194 & 13.15 & 11.5726 & 1.57743 \tabularnewline
195 & 12.15 & 12.1856 & -0.0355589 \tabularnewline
196 & 12.6 & 14.1923 & -1.5923 \tabularnewline
197 & 10.35 & 7.616 & 2.734 \tabularnewline
198 & 15.4 & 16.7752 & -1.37524 \tabularnewline
199 & 9.6 & 4.94324 & 4.65676 \tabularnewline
200 & 18.2 & 17.1946 & 1.00536 \tabularnewline
201 & 13.6 & 14.3642 & -0.764173 \tabularnewline
202 & 14.85 & 17.0366 & -2.18661 \tabularnewline
203 & 14.75 & 14.7972 & -0.047247 \tabularnewline
204 & 14.1 & 10.9625 & 3.1375 \tabularnewline
205 & 14.9 & 11.8439 & 3.0561 \tabularnewline
206 & 16.25 & 15.7402 & 0.50981 \tabularnewline
207 & 19.25 & 17.9562 & 1.2938 \tabularnewline
208 & 13.6 & 12.5881 & 1.01193 \tabularnewline
209 & 13.6 & 14.1595 & -0.559488 \tabularnewline
210 & 15.65 & 14.5486 & 1.10141 \tabularnewline
211 & 12.75 & 9.55895 & 3.19105 \tabularnewline
212 & 14.6 & 16.3954 & -1.79538 \tabularnewline
213 & 9.85 & 8.78549 & 1.06451 \tabularnewline
214 & 12.65 & 13.1343 & -0.484306 \tabularnewline
215 & 11.9 & 9.35839 & 2.54161 \tabularnewline
216 & 19.2 & 17.3876 & 1.81245 \tabularnewline
217 & 16.6 & 15.1395 & 1.46051 \tabularnewline
218 & 11.2 & 8.87498 & 2.32502 \tabularnewline
219 & 15.25 & 17.2063 & -1.95626 \tabularnewline
220 & 11.9 & 15.2899 & -3.38987 \tabularnewline
221 & 13.2 & 13.7801 & -0.580087 \tabularnewline
222 & 16.35 & 16.3968 & -0.0467789 \tabularnewline
223 & 12.4 & 10.098 & 2.30204 \tabularnewline
224 & 15.85 & 14.9707 & 0.879253 \tabularnewline
225 & 14.35 & 11.2285 & 3.12147 \tabularnewline
226 & 18.15 & 18.559 & -0.409007 \tabularnewline
227 & 11.15 & 12.3642 & -1.21424 \tabularnewline
228 & 15.65 & 13.7727 & 1.87731 \tabularnewline
229 & 17.75 & 22.254 & -4.50396 \tabularnewline
230 & 7.65 & 7.02758 & 0.62242 \tabularnewline
231 & 12.35 & 7.58468 & 4.76532 \tabularnewline
232 & 15.6 & 12.4852 & 3.11477 \tabularnewline
233 & 19.3 & 16.2143 & 3.08573 \tabularnewline
234 & 15.2 & 11.0186 & 4.18144 \tabularnewline
235 & 17.1 & 14.7013 & 2.39872 \tabularnewline
236 & 15.6 & 11.1253 & 4.47471 \tabularnewline
237 & 18.4 & 14.2105 & 4.18948 \tabularnewline
238 & 19.05 & 12.9752 & 6.07476 \tabularnewline
239 & 18.55 & 15.948 & 2.60203 \tabularnewline
240 & 19.1 & 17.9969 & 1.10311 \tabularnewline
241 & 13.1 & 13.2469 & -0.146933 \tabularnewline
242 & 12.85 & 13.3397 & -0.489667 \tabularnewline
243 & 9.5 & 14.923 & -5.42301 \tabularnewline
244 & 4.5 & 3.18381 & 1.31619 \tabularnewline
245 & 11.85 & 13.5092 & -1.65918 \tabularnewline
246 & 13.6 & 14.0557 & -0.455703 \tabularnewline
247 & 11.7 & 10.7273 & 0.972714 \tabularnewline
248 & 12.4 & 13.013 & -0.613011 \tabularnewline
249 & 13.35 & 15.8088 & -2.45877 \tabularnewline
250 & 11.4 & 8.60518 & 2.79482 \tabularnewline
251 & 14.9 & 11.0473 & 3.85265 \tabularnewline
252 & 19.9 & 13.6006 & 6.29937 \tabularnewline
253 & 17.75 & 19.3236 & -1.57362 \tabularnewline
254 & 11.2 & 12.8229 & -1.6229 \tabularnewline
255 & 14.6 & 12.754 & 1.846 \tabularnewline
256 & 17.6 & 15.6734 & 1.92655 \tabularnewline
257 & 14.05 & 12.4859 & 1.56414 \tabularnewline
258 & 16.1 & 15.1342 & 0.965794 \tabularnewline
259 & 13.35 & 13.3827 & -0.0326691 \tabularnewline
260 & 11.85 & 13.0589 & -1.20889 \tabularnewline
261 & 11.95 & 12.5178 & -0.567755 \tabularnewline
262 & 14.75 & 13.1067 & 1.64328 \tabularnewline
263 & 15.15 & 15.7997 & -0.649654 \tabularnewline
264 & 13.2 & 12.7851 & 0.414893 \tabularnewline
265 & 16.85 & 19.1377 & -2.2877 \tabularnewline
266 & 7.85 & 14.0475 & -6.19755 \tabularnewline
267 & 7.7 & 6.47527 & 1.22473 \tabularnewline
268 & 12.6 & 16.7121 & -4.11212 \tabularnewline
269 & 7.85 & 7.78249 & 0.0675121 \tabularnewline
270 & 10.95 & 11.0396 & -0.0895841 \tabularnewline
271 & 12.35 & 15.4128 & -3.06277 \tabularnewline
272 & 9.95 & 7.09795 & 2.85205 \tabularnewline
273 & 14.9 & 13.6337 & 1.26627 \tabularnewline
274 & 16.65 & 16.6598 & -0.00975863 \tabularnewline
275 & 13.4 & 13.8801 & -0.480063 \tabularnewline
276 & 13.95 & 9.65054 & 4.29946 \tabularnewline
277 & 15.7 & 11.8429 & 3.85715 \tabularnewline
278 & 16.85 & 16.1484 & 0.701562 \tabularnewline
279 & 10.95 & 7.82308 & 3.12692 \tabularnewline
280 & 15.35 & 14.6681 & 0.681857 \tabularnewline
281 & 12.2 & 10.9118 & 1.28819 \tabularnewline
282 & 15.1 & 14.4642 & 0.635779 \tabularnewline
283 & 17.75 & 15.6629 & 2.0871 \tabularnewline
284 & 15.2 & 13.5924 & 1.60756 \tabularnewline
285 & 14.6 & 13.2724 & 1.32756 \tabularnewline
286 & 16.65 & 19.463 & -2.81295 \tabularnewline
287 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269831&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]11.6411[/C][C]1.25893[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]10.9602[/C][C]-3.56018[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]10.8311[/C][C]1.36888[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]12.0802[/C][C]0.719832[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]11.8143[/C][C]-4.41432[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]10.9811[/C][C]-4.28112[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]15.4684[/C][C]-2.8684[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]12.0089[/C][C]2.79107[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]11.2391[/C][C]2.06093[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]11.2805[/C][C]-0.180501[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]14.1525[/C][C]-5.95253[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]12.6659[/C][C]-1.26586[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]13.7961[/C][C]-7.39614[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]10.6544[/C][C]-0.0544257[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]12.8883[/C][C]-0.88828[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]7.93752[/C][C]-1.63752[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]11.3978[/C][C]-0.0978253[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]13.4422[/C][C]-1.54217[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]11.3456[/C][C]-2.04558[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]13.1721[/C][C]-3.57212[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]10.0883[/C][C]-0.0882972[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]11.0696[/C][C]-4.66964[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]12.4669[/C][C]1.33308[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]13.47[/C][C]-2.66996[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]11.5952[/C][C]2.20477[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]12.0462[/C][C]-0.346165[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]14.9862[/C][C]-4.08623[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]14.2218[/C][C]1.8782[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]11.498[/C][C]1.90196[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]10.3225[/C][C]-0.4225[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]11.4546[/C][C]0.0453786[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]10.8244[/C][C]-2.52441[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]13.0485[/C][C]-1.34851[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]10.9621[/C][C]-4.86205[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]11.7537[/C][C]-2.75372[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]14.0414[/C][C]-4.3414[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]11.6473[/C][C]-0.847316[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]11.9908[/C][C]-1.69081[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]10.797[/C][C]-0.396989[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]13.5591[/C][C]-0.859064[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]11.8001[/C][C]-2.50008[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]14.0864[/C][C]-2.28642[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]10.0742[/C][C]-4.17417[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]13.7689[/C][C]-2.3689[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]11.2824[/C][C]1.71759[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]12.3857[/C][C]-1.58567[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]10.6331[/C][C]1.66691[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]13.2311[/C][C]-1.93111[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]11.4287[/C][C]0.371302[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]11.1983[/C][C]-3.29835[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]8.38732[/C][C]4.31268[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]11.5762[/C][C]0.723764[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]12.6426[/C][C]-1.04255[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]11.0111[/C][C]-4.31109[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]12.995[/C][C]-2.09501[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]13.6693[/C][C]-1.56934[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]12.6958[/C][C]0.604227[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]12.8367[/C][C]-2.73674[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]12.6438[/C][C]-6.9438[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]11.3085[/C][C]2.99151[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]9.3442[/C][C]-1.3442[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]12.5075[/C][C]0.792537[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]12.2609[/C][C]-2.96089[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]11.4289[/C][C]1.07113[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]9.70285[/C][C]-2.10285[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]13.8867[/C][C]2.0133[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]11.2207[/C][C]-2.02074[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]10.8689[/C][C]-1.7689[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]13.5391[/C][C]-2.43906[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]13.228[/C][C]-0.228003[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]12.8949[/C][C]1.60512[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]11.6889[/C][C]0.511053[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]13.4219[/C][C]-1.12194[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]10.6183[/C][C]0.781701[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]11.5336[/C][C]-2.73358[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]11.3323[/C][C]3.26766[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]12.0624[/C][C]-4.7624[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]12.1868[/C][C]0.413165[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]-0.213104[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]12.6616[/C][C]0.338421[/C][/ROW]
[ROW][C]81[/C][C]12.6[/C][C]13.5662[/C][C]-0.966201[/C][/ROW]
[ROW][C]82[/C][C]13.2[/C][C]14.7401[/C][C]-1.54008[/C][/ROW]
[ROW][C]83[/C][C]9.9[/C][C]12.6413[/C][C]-2.74126[/C][/ROW]
[ROW][C]84[/C][C]7.7[/C][C]8.28876[/C][C]-0.588763[/C][/ROW]
[ROW][C]85[/C][C]10.5[/C][C]7.96278[/C][C]2.53722[/C][/ROW]
[ROW][C]86[/C][C]13.4[/C][C]14.6465[/C][C]-1.24652[/C][/ROW]
[ROW][C]87[/C][C]10.9[/C][C]16.9802[/C][C]-6.08016[/C][/ROW]
[ROW][C]88[/C][C]4.3[/C][C]5.53451[/C][C]-1.23451[/C][/ROW]
[ROW][C]89[/C][C]10.3[/C][C]10.4134[/C][C]-0.113354[/C][/ROW]
[ROW][C]90[/C][C]11.8[/C][C]11.2641[/C][C]0.535911[/C][/ROW]
[ROW][C]91[/C][C]11.2[/C][C]10.7563[/C][C]0.443744[/C][/ROW]
[ROW][C]92[/C][C]11.4[/C][C]13.3249[/C][C]-1.92488[/C][/ROW]
[ROW][C]93[/C][C]8.6[/C][C]7.03234[/C][C]1.56766[/C][/ROW]
[ROW][C]94[/C][C]13.2[/C][C]11.2083[/C][C]1.9917[/C][/ROW]
[ROW][C]95[/C][C]12.6[/C][C]19.0118[/C][C]-6.41183[/C][/ROW]
[ROW][C]96[/C][C]5.6[/C][C]7.45394[/C][C]-1.85394[/C][/ROW]
[ROW][C]97[/C][C]9.9[/C][C]13.9429[/C][C]-4.04291[/C][/ROW]
[ROW][C]98[/C][C]8.8[/C][C]13.5289[/C][C]-4.72892[/C][/ROW]
[ROW][C]99[/C][C]7.7[/C][C]9.60735[/C][C]-1.90735[/C][/ROW]
[ROW][C]100[/C][C]9[/C][C]14.9507[/C][C]-5.95066[/C][/ROW]
[ROW][C]101[/C][C]7.3[/C][C]7.53268[/C][C]-0.232676[/C][/ROW]
[ROW][C]102[/C][C]11.4[/C][C]10.0877[/C][C]1.31228[/C][/ROW]
[ROW][C]103[/C][C]13.6[/C][C]16.6524[/C][C]-3.05238[/C][/ROW]
[ROW][C]104[/C][C]7.9[/C][C]8.24303[/C][C]-0.343028[/C][/ROW]
[ROW][C]105[/C][C]10.7[/C][C]12.3257[/C][C]-1.62571[/C][/ROW]
[ROW][C]106[/C][C]10.3[/C][C]12.4934[/C][C]-2.19344[/C][/ROW]
[ROW][C]107[/C][C]8.3[/C][C]10.0386[/C][C]-1.73858[/C][/ROW]
[ROW][C]108[/C][C]9.6[/C][C]7.53563[/C][C]2.06437[/C][/ROW]
[ROW][C]109[/C][C]14.2[/C][C]16.2401[/C][C]-2.04015[/C][/ROW]
[ROW][C]110[/C][C]8.5[/C][C]5.79264[/C][C]2.70736[/C][/ROW]
[ROW][C]111[/C][C]13.5[/C][C]19.4959[/C][C]-5.99586[/C][/ROW]
[ROW][C]112[/C][C]4.9[/C][C]8.58344[/C][C]-3.68344[/C][/ROW]
[ROW][C]113[/C][C]6.4[/C][C]7.41729[/C][C]-1.01729[/C][/ROW]
[ROW][C]114[/C][C]9.6[/C][C]9.29711[/C][C]0.30289[/C][/ROW]
[ROW][C]115[/C][C]11.6[/C][C]11.2454[/C][C]0.354636[/C][/ROW]
[ROW][C]116[/C][C]11.1[/C][C]15.3425[/C][C]-4.24246[/C][/ROW]
[ROW][C]117[/C][C]4.35[/C][C]3.32229[/C][C]1.02771[/C][/ROW]
[ROW][C]118[/C][C]12.7[/C][C]9.2307[/C][C]3.4693[/C][/ROW]
[ROW][C]119[/C][C]18.1[/C][C]15.2655[/C][C]2.83454[/C][/ROW]
[ROW][C]120[/C][C]17.85[/C][C]17.8849[/C][C]-0.0348562[/C][/ROW]
[ROW][C]121[/C][C]16.6[/C][C]14.0644[/C][C]2.53555[/C][/ROW]
[ROW][C]122[/C][C]12.6[/C][C]18.7413[/C][C]-6.14127[/C][/ROW]
[ROW][C]123[/C][C]17.1[/C][C]13.1624[/C][C]3.93757[/C][/ROW]
[ROW][C]124[/C][C]19.1[/C][C]20.5437[/C][C]-1.44372[/C][/ROW]
[ROW][C]125[/C][C]16.1[/C][C]12.1659[/C][C]3.93409[/C][/ROW]
[ROW][C]126[/C][C]13.35[/C][C]12.6908[/C][C]0.659231[/C][/ROW]
[ROW][C]127[/C][C]18.4[/C][C]13.0523[/C][C]5.34771[/C][/ROW]
[ROW][C]128[/C][C]14.7[/C][C]18.1627[/C][C]-3.46272[/C][/ROW]
[ROW][C]129[/C][C]10.6[/C][C]10.9146[/C][C]-0.314608[/C][/ROW]
[ROW][C]130[/C][C]12.6[/C][C]11.3777[/C][C]1.22226[/C][/ROW]
[ROW][C]131[/C][C]16.2[/C][C]19.2329[/C][C]-3.03288[/C][/ROW]
[ROW][C]132[/C][C]13.6[/C][C]11.3832[/C][C]2.21676[/C][/ROW]
[ROW][C]133[/C][C]18.9[/C][C]16.5704[/C][C]2.32956[/C][/ROW]
[ROW][C]134[/C][C]14.1[/C][C]11.024[/C][C]3.07599[/C][/ROW]
[ROW][C]135[/C][C]14.5[/C][C]16.1046[/C][C]-1.60464[/C][/ROW]
[ROW][C]136[/C][C]16.15[/C][C]13.9356[/C][C]2.21441[/C][/ROW]
[ROW][C]137[/C][C]14.75[/C][C]13.0548[/C][C]1.69519[/C][/ROW]
[ROW][C]138[/C][C]14.8[/C][C]13.7836[/C][C]1.01635[/C][/ROW]
[ROW][C]139[/C][C]12.45[/C][C]13.4168[/C][C]-0.966774[/C][/ROW]
[ROW][C]140[/C][C]12.65[/C][C]8.75572[/C][C]3.89428[/C][/ROW]
[ROW][C]141[/C][C]17.35[/C][C]19.2277[/C][C]-1.87774[/C][/ROW]
[ROW][C]142[/C][C]8.6[/C][C]7.50928[/C][C]1.09072[/C][/ROW]
[ROW][C]143[/C][C]18.4[/C][C]19.8561[/C][C]-1.45608[/C][/ROW]
[ROW][C]144[/C][C]16.1[/C][C]16.0523[/C][C]0.0476915[/C][/ROW]
[ROW][C]145[/C][C]11.6[/C][C]5.58528[/C][C]6.01472[/C][/ROW]
[ROW][C]146[/C][C]17.75[/C][C]14.751[/C][C]2.99902[/C][/ROW]
[ROW][C]147[/C][C]15.25[/C][C]13.4427[/C][C]1.80728[/C][/ROW]
[ROW][C]148[/C][C]17.65[/C][C]15.3327[/C][C]2.31732[/C][/ROW]
[ROW][C]149[/C][C]15.6[/C][C]13.7736[/C][C]1.82636[/C][/ROW]
[ROW][C]150[/C][C]16.35[/C][C]13.3133[/C][C]3.03673[/C][/ROW]
[ROW][C]151[/C][C]17.65[/C][C]16.0527[/C][C]1.59733[/C][/ROW]
[ROW][C]152[/C][C]13.6[/C][C]13.5091[/C][C]0.0909472[/C][/ROW]
[ROW][C]153[/C][C]11.7[/C][C]9.90614[/C][C]1.79386[/C][/ROW]
[ROW][C]154[/C][C]14.35[/C][C]17.0079[/C][C]-2.65795[/C][/ROW]
[ROW][C]155[/C][C]14.75[/C][C]13.2621[/C][C]1.48785[/C][/ROW]
[ROW][C]156[/C][C]18.25[/C][C]23.1897[/C][C]-4.93967[/C][/ROW]
[ROW][C]157[/C][C]9.9[/C][C]7.03934[/C][C]2.86066[/C][/ROW]
[ROW][C]158[/C][C]16[/C][C]13.4753[/C][C]2.52466[/C][/ROW]
[ROW][C]159[/C][C]18.25[/C][C]19.2506[/C][C]-1.0006[/C][/ROW]
[ROW][C]160[/C][C]16.85[/C][C]15.2005[/C][C]1.64946[/C][/ROW]
[ROW][C]161[/C][C]14.6[/C][C]14.8259[/C][C]-0.225916[/C][/ROW]
[ROW][C]162[/C][C]13.85[/C][C]10.8902[/C][C]2.95979[/C][/ROW]
[ROW][C]163[/C][C]18.95[/C][C]17.2946[/C][C]1.6554[/C][/ROW]
[ROW][C]164[/C][C]15.6[/C][C]19.1144[/C][C]-3.51444[/C][/ROW]
[ROW][C]165[/C][C]14.85[/C][C]16.1064[/C][C]-1.25637[/C][/ROW]
[ROW][C]166[/C][C]11.75[/C][C]6.86848[/C][C]4.88152[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]20.8173[/C][C]-2.36728[/C][/ROW]
[ROW][C]168[/C][C]15.9[/C][C]12.8729[/C][C]3.02714[/C][/ROW]
[ROW][C]169[/C][C]17.1[/C][C]9.98663[/C][C]7.11337[/C][/ROW]
[ROW][C]170[/C][C]16.1[/C][C]12.316[/C][C]3.78397[/C][/ROW]
[ROW][C]171[/C][C]19.9[/C][C]19.6608[/C][C]0.239219[/C][/ROW]
[ROW][C]172[/C][C]10.95[/C][C]9.26349[/C][C]1.68651[/C][/ROW]
[ROW][C]173[/C][C]18.45[/C][C]14.5745[/C][C]3.87551[/C][/ROW]
[ROW][C]174[/C][C]15.1[/C][C]16.3361[/C][C]-1.2361[/C][/ROW]
[ROW][C]175[/C][C]15[/C][C]17.9812[/C][C]-2.98125[/C][/ROW]
[ROW][C]176[/C][C]11.35[/C][C]10.9919[/C][C]0.358105[/C][/ROW]
[ROW][C]177[/C][C]15.95[/C][C]11.7868[/C][C]4.16319[/C][/ROW]
[ROW][C]178[/C][C]18.1[/C][C]17.3125[/C][C]0.787507[/C][/ROW]
[ROW][C]179[/C][C]14.6[/C][C]15.4528[/C][C]-0.852804[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]16.2299[/C][C]-0.82991[/C][/ROW]
[ROW][C]181[/C][C]15.4[/C][C]11.7802[/C][C]3.61983[/C][/ROW]
[ROW][C]182[/C][C]17.6[/C][C]17.4037[/C][C]0.196335[/C][/ROW]
[ROW][C]183[/C][C]13.35[/C][C]11.1121[/C][C]2.23793[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]17.7232[/C][C]1.37681[/C][/ROW]
[ROW][C]185[/C][C]15.35[/C][C]18.6917[/C][C]-3.34166[/C][/ROW]
[ROW][C]186[/C][C]7.6[/C][C]8.45899[/C][C]-0.858994[/C][/ROW]
[ROW][C]187[/C][C]13.4[/C][C]14.1888[/C][C]-0.788807[/C][/ROW]
[ROW][C]188[/C][C]13.9[/C][C]11.9443[/C][C]1.95566[/C][/ROW]
[ROW][C]189[/C][C]19.1[/C][C]17.9786[/C][C]1.12137[/C][/ROW]
[ROW][C]190[/C][C]15.25[/C][C]15.5799[/C][C]-0.32991[/C][/ROW]
[ROW][C]191[/C][C]12.9[/C][C]11.3292[/C][C]1.57075[/C][/ROW]
[ROW][C]192[/C][C]16.1[/C][C]11.827[/C][C]4.27299[/C][/ROW]
[ROW][C]193[/C][C]17.35[/C][C]17.1318[/C][C]0.218182[/C][/ROW]
[ROW][C]194[/C][C]13.15[/C][C]11.5726[/C][C]1.57743[/C][/ROW]
[ROW][C]195[/C][C]12.15[/C][C]12.1856[/C][C]-0.0355589[/C][/ROW]
[ROW][C]196[/C][C]12.6[/C][C]14.1923[/C][C]-1.5923[/C][/ROW]
[ROW][C]197[/C][C]10.35[/C][C]7.616[/C][C]2.734[/C][/ROW]
[ROW][C]198[/C][C]15.4[/C][C]16.7752[/C][C]-1.37524[/C][/ROW]
[ROW][C]199[/C][C]9.6[/C][C]4.94324[/C][C]4.65676[/C][/ROW]
[ROW][C]200[/C][C]18.2[/C][C]17.1946[/C][C]1.00536[/C][/ROW]
[ROW][C]201[/C][C]13.6[/C][C]14.3642[/C][C]-0.764173[/C][/ROW]
[ROW][C]202[/C][C]14.85[/C][C]17.0366[/C][C]-2.18661[/C][/ROW]
[ROW][C]203[/C][C]14.75[/C][C]14.7972[/C][C]-0.047247[/C][/ROW]
[ROW][C]204[/C][C]14.1[/C][C]10.9625[/C][C]3.1375[/C][/ROW]
[ROW][C]205[/C][C]14.9[/C][C]11.8439[/C][C]3.0561[/C][/ROW]
[ROW][C]206[/C][C]16.25[/C][C]15.7402[/C][C]0.50981[/C][/ROW]
[ROW][C]207[/C][C]19.25[/C][C]17.9562[/C][C]1.2938[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]12.5881[/C][C]1.01193[/C][/ROW]
[ROW][C]209[/C][C]13.6[/C][C]14.1595[/C][C]-0.559488[/C][/ROW]
[ROW][C]210[/C][C]15.65[/C][C]14.5486[/C][C]1.10141[/C][/ROW]
[ROW][C]211[/C][C]12.75[/C][C]9.55895[/C][C]3.19105[/C][/ROW]
[ROW][C]212[/C][C]14.6[/C][C]16.3954[/C][C]-1.79538[/C][/ROW]
[ROW][C]213[/C][C]9.85[/C][C]8.78549[/C][C]1.06451[/C][/ROW]
[ROW][C]214[/C][C]12.65[/C][C]13.1343[/C][C]-0.484306[/C][/ROW]
[ROW][C]215[/C][C]11.9[/C][C]9.35839[/C][C]2.54161[/C][/ROW]
[ROW][C]216[/C][C]19.2[/C][C]17.3876[/C][C]1.81245[/C][/ROW]
[ROW][C]217[/C][C]16.6[/C][C]15.1395[/C][C]1.46051[/C][/ROW]
[ROW][C]218[/C][C]11.2[/C][C]8.87498[/C][C]2.32502[/C][/ROW]
[ROW][C]219[/C][C]15.25[/C][C]17.2063[/C][C]-1.95626[/C][/ROW]
[ROW][C]220[/C][C]11.9[/C][C]15.2899[/C][C]-3.38987[/C][/ROW]
[ROW][C]221[/C][C]13.2[/C][C]13.7801[/C][C]-0.580087[/C][/ROW]
[ROW][C]222[/C][C]16.35[/C][C]16.3968[/C][C]-0.0467789[/C][/ROW]
[ROW][C]223[/C][C]12.4[/C][C]10.098[/C][C]2.30204[/C][/ROW]
[ROW][C]224[/C][C]15.85[/C][C]14.9707[/C][C]0.879253[/C][/ROW]
[ROW][C]225[/C][C]14.35[/C][C]11.2285[/C][C]3.12147[/C][/ROW]
[ROW][C]226[/C][C]18.15[/C][C]18.559[/C][C]-0.409007[/C][/ROW]
[ROW][C]227[/C][C]11.15[/C][C]12.3642[/C][C]-1.21424[/C][/ROW]
[ROW][C]228[/C][C]15.65[/C][C]13.7727[/C][C]1.87731[/C][/ROW]
[ROW][C]229[/C][C]17.75[/C][C]22.254[/C][C]-4.50396[/C][/ROW]
[ROW][C]230[/C][C]7.65[/C][C]7.02758[/C][C]0.62242[/C][/ROW]
[ROW][C]231[/C][C]12.35[/C][C]7.58468[/C][C]4.76532[/C][/ROW]
[ROW][C]232[/C][C]15.6[/C][C]12.4852[/C][C]3.11477[/C][/ROW]
[ROW][C]233[/C][C]19.3[/C][C]16.2143[/C][C]3.08573[/C][/ROW]
[ROW][C]234[/C][C]15.2[/C][C]11.0186[/C][C]4.18144[/C][/ROW]
[ROW][C]235[/C][C]17.1[/C][C]14.7013[/C][C]2.39872[/C][/ROW]
[ROW][C]236[/C][C]15.6[/C][C]11.1253[/C][C]4.47471[/C][/ROW]
[ROW][C]237[/C][C]18.4[/C][C]14.2105[/C][C]4.18948[/C][/ROW]
[ROW][C]238[/C][C]19.05[/C][C]12.9752[/C][C]6.07476[/C][/ROW]
[ROW][C]239[/C][C]18.55[/C][C]15.948[/C][C]2.60203[/C][/ROW]
[ROW][C]240[/C][C]19.1[/C][C]17.9969[/C][C]1.10311[/C][/ROW]
[ROW][C]241[/C][C]13.1[/C][C]13.2469[/C][C]-0.146933[/C][/ROW]
[ROW][C]242[/C][C]12.85[/C][C]13.3397[/C][C]-0.489667[/C][/ROW]
[ROW][C]243[/C][C]9.5[/C][C]14.923[/C][C]-5.42301[/C][/ROW]
[ROW][C]244[/C][C]4.5[/C][C]3.18381[/C][C]1.31619[/C][/ROW]
[ROW][C]245[/C][C]11.85[/C][C]13.5092[/C][C]-1.65918[/C][/ROW]
[ROW][C]246[/C][C]13.6[/C][C]14.0557[/C][C]-0.455703[/C][/ROW]
[ROW][C]247[/C][C]11.7[/C][C]10.7273[/C][C]0.972714[/C][/ROW]
[ROW][C]248[/C][C]12.4[/C][C]13.013[/C][C]-0.613011[/C][/ROW]
[ROW][C]249[/C][C]13.35[/C][C]15.8088[/C][C]-2.45877[/C][/ROW]
[ROW][C]250[/C][C]11.4[/C][C]8.60518[/C][C]2.79482[/C][/ROW]
[ROW][C]251[/C][C]14.9[/C][C]11.0473[/C][C]3.85265[/C][/ROW]
[ROW][C]252[/C][C]19.9[/C][C]13.6006[/C][C]6.29937[/C][/ROW]
[ROW][C]253[/C][C]17.75[/C][C]19.3236[/C][C]-1.57362[/C][/ROW]
[ROW][C]254[/C][C]11.2[/C][C]12.8229[/C][C]-1.6229[/C][/ROW]
[ROW][C]255[/C][C]14.6[/C][C]12.754[/C][C]1.846[/C][/ROW]
[ROW][C]256[/C][C]17.6[/C][C]15.6734[/C][C]1.92655[/C][/ROW]
[ROW][C]257[/C][C]14.05[/C][C]12.4859[/C][C]1.56414[/C][/ROW]
[ROW][C]258[/C][C]16.1[/C][C]15.1342[/C][C]0.965794[/C][/ROW]
[ROW][C]259[/C][C]13.35[/C][C]13.3827[/C][C]-0.0326691[/C][/ROW]
[ROW][C]260[/C][C]11.85[/C][C]13.0589[/C][C]-1.20889[/C][/ROW]
[ROW][C]261[/C][C]11.95[/C][C]12.5178[/C][C]-0.567755[/C][/ROW]
[ROW][C]262[/C][C]14.75[/C][C]13.1067[/C][C]1.64328[/C][/ROW]
[ROW][C]263[/C][C]15.15[/C][C]15.7997[/C][C]-0.649654[/C][/ROW]
[ROW][C]264[/C][C]13.2[/C][C]12.7851[/C][C]0.414893[/C][/ROW]
[ROW][C]265[/C][C]16.85[/C][C]19.1377[/C][C]-2.2877[/C][/ROW]
[ROW][C]266[/C][C]7.85[/C][C]14.0475[/C][C]-6.19755[/C][/ROW]
[ROW][C]267[/C][C]7.7[/C][C]6.47527[/C][C]1.22473[/C][/ROW]
[ROW][C]268[/C][C]12.6[/C][C]16.7121[/C][C]-4.11212[/C][/ROW]
[ROW][C]269[/C][C]7.85[/C][C]7.78249[/C][C]0.0675121[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]11.0396[/C][C]-0.0895841[/C][/ROW]
[ROW][C]271[/C][C]12.35[/C][C]15.4128[/C][C]-3.06277[/C][/ROW]
[ROW][C]272[/C][C]9.95[/C][C]7.09795[/C][C]2.85205[/C][/ROW]
[ROW][C]273[/C][C]14.9[/C][C]13.6337[/C][C]1.26627[/C][/ROW]
[ROW][C]274[/C][C]16.65[/C][C]16.6598[/C][C]-0.00975863[/C][/ROW]
[ROW][C]275[/C][C]13.4[/C][C]13.8801[/C][C]-0.480063[/C][/ROW]
[ROW][C]276[/C][C]13.95[/C][C]9.65054[/C][C]4.29946[/C][/ROW]
[ROW][C]277[/C][C]15.7[/C][C]11.8429[/C][C]3.85715[/C][/ROW]
[ROW][C]278[/C][C]16.85[/C][C]16.1484[/C][C]0.701562[/C][/ROW]
[ROW][C]279[/C][C]10.95[/C][C]7.82308[/C][C]3.12692[/C][/ROW]
[ROW][C]280[/C][C]15.35[/C][C]14.6681[/C][C]0.681857[/C][/ROW]
[ROW][C]281[/C][C]12.2[/C][C]10.9118[/C][C]1.28819[/C][/ROW]
[ROW][C]282[/C][C]15.1[/C][C]14.4642[/C][C]0.635779[/C][/ROW]
[ROW][C]283[/C][C]17.75[/C][C]15.6629[/C][C]2.0871[/C][/ROW]
[ROW][C]284[/C][C]15.2[/C][C]13.5924[/C][C]1.60756[/C][/ROW]
[ROW][C]285[/C][C]14.6[/C][C]13.2724[/C][C]1.32756[/C][/ROW]
[ROW][C]286[/C][C]16.65[/C][C]19.463[/C][C]-2.81295[/C][/ROW]
[ROW][C]287[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269831&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269831&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.64111.25893
27.410.9602-3.56018
312.210.83111.36888
412.812.08020.719832
57.411.8143-4.41432
66.710.9811-4.28112
712.615.4684-2.8684
814.812.00892.79107
913.311.23912.06093
1011.111.2805-0.180501
118.214.1525-5.95253
1211.412.6659-1.26586
136.413.7961-7.39614
1410.610.6544-0.0544257
151212.8883-0.88828
166.37.93752-1.63752
1711.311.3978-0.0978253
1811.913.4422-1.54217
199.311.3456-2.04558
209.613.1721-3.57212
211010.0883-0.0882972
226.411.0696-4.66964
2313.812.46691.33308
2410.813.47-2.66996
2513.811.59522.20477
2611.712.0462-0.346165
2710.914.9862-4.08623
2816.114.22181.8782
2913.411.4981.90196
309.910.3225-0.4225
3111.511.45460.0453786
328.310.8244-2.52441
3311.713.0485-1.34851
346.110.9621-4.86205
35911.7537-2.75372
369.714.0414-4.3414
3710.811.6473-0.847316
3810.311.9908-1.69081
3910.410.797-0.396989
4012.713.5591-0.859064
419.311.8001-2.50008
4211.814.0864-2.28642
435.910.0742-4.17417
4411.413.7689-2.3689
451311.28241.71759
4610.812.3857-1.58567
4712.310.63311.66691
4811.313.2311-1.93111
4911.811.42870.371302
507.911.1983-3.29835
5112.78.387324.31268
5212.311.57620.723764
5311.612.6426-1.04255
546.711.0111-4.31109
5510.912.995-2.09501
5612.113.6693-1.56934
5713.312.69580.604227
5810.112.8367-2.73674
595.712.6438-6.9438
6014.311.30852.99151
6189.3442-1.3442
6213.312.50750.792537
639.312.2609-2.96089
6412.511.42891.07113
657.69.70285-2.10285
6615.913.88672.0133
679.211.2207-2.02074
689.110.8689-1.7689
6911.113.5391-2.43906
701313.228-0.228003
7114.512.89491.60512
7212.211.68890.511053
7312.313.4219-1.12194
7411.410.61830.781701
758.811.5336-2.73358
7614.611.33233.26766
777.312.0624-4.7624
7812.612.18680.413165
79NANA-0.213104
801312.66160.338421
8112.613.5662-0.966201
8213.214.7401-1.54008
839.912.6413-2.74126
847.78.28876-0.588763
8510.57.962782.53722
8613.414.6465-1.24652
8710.916.9802-6.08016
884.35.53451-1.23451
8910.310.4134-0.113354
9011.811.26410.535911
9111.210.75630.443744
9211.413.3249-1.92488
938.67.032341.56766
9413.211.20831.9917
9512.619.0118-6.41183
965.67.45394-1.85394
979.913.9429-4.04291
988.813.5289-4.72892
997.79.60735-1.90735
100914.9507-5.95066
1017.37.53268-0.232676
10211.410.08771.31228
10313.616.6524-3.05238
1047.98.24303-0.343028
10510.712.3257-1.62571
10610.312.4934-2.19344
1078.310.0386-1.73858
1089.67.535632.06437
10914.216.2401-2.04015
1108.55.792642.70736
11113.519.4959-5.99586
1124.98.58344-3.68344
1136.47.41729-1.01729
1149.69.297110.30289
11511.611.24540.354636
11611.115.3425-4.24246
1174.353.322291.02771
11812.79.23073.4693
11918.115.26552.83454
12017.8517.8849-0.0348562
12116.614.06442.53555
12212.618.7413-6.14127
12317.113.16243.93757
12419.120.5437-1.44372
12516.112.16593.93409
12613.3512.69080.659231
12718.413.05235.34771
12814.718.1627-3.46272
12910.610.9146-0.314608
13012.611.37771.22226
13116.219.2329-3.03288
13213.611.38322.21676
13318.916.57042.32956
13414.111.0243.07599
13514.516.1046-1.60464
13616.1513.93562.21441
13714.7513.05481.69519
13814.813.78361.01635
13912.4513.4168-0.966774
14012.658.755723.89428
14117.3519.2277-1.87774
1428.67.509281.09072
14318.419.8561-1.45608
14416.116.05230.0476915
14511.65.585286.01472
14617.7514.7512.99902
14715.2513.44271.80728
14817.6515.33272.31732
14915.613.77361.82636
15016.3513.31333.03673
15117.6516.05271.59733
15213.613.50910.0909472
15311.79.906141.79386
15414.3517.0079-2.65795
15514.7513.26211.48785
15618.2523.1897-4.93967
1579.97.039342.86066
1581613.47532.52466
15918.2519.2506-1.0006
16016.8515.20051.64946
16114.614.8259-0.225916
16213.8510.89022.95979
16318.9517.29461.6554
16415.619.1144-3.51444
16514.8516.1064-1.25637
16611.756.868484.88152
16718.4520.8173-2.36728
16815.912.87293.02714
16917.19.986637.11337
17016.112.3163.78397
17119.919.66080.239219
17210.959.263491.68651
17318.4514.57453.87551
17415.116.3361-1.2361
1751517.9812-2.98125
17611.3510.99190.358105
17715.9511.78684.16319
17818.117.31250.787507
17914.615.4528-0.852804
18015.416.2299-0.82991
18115.411.78023.61983
18217.617.40370.196335
18313.3511.11212.23793
18419.117.72321.37681
18515.3518.6917-3.34166
1867.68.45899-0.858994
18713.414.1888-0.788807
18813.911.94431.95566
18919.117.97861.12137
19015.2515.5799-0.32991
19112.911.32921.57075
19216.111.8274.27299
19317.3517.13180.218182
19413.1511.57261.57743
19512.1512.1856-0.0355589
19612.614.1923-1.5923
19710.357.6162.734
19815.416.7752-1.37524
1999.64.943244.65676
20018.217.19461.00536
20113.614.3642-0.764173
20214.8517.0366-2.18661
20314.7514.7972-0.047247
20414.110.96253.1375
20514.911.84393.0561
20616.2515.74020.50981
20719.2517.95621.2938
20813.612.58811.01193
20913.614.1595-0.559488
21015.6514.54861.10141
21112.759.558953.19105
21214.616.3954-1.79538
2139.858.785491.06451
21412.6513.1343-0.484306
21511.99.358392.54161
21619.217.38761.81245
21716.615.13951.46051
21811.28.874982.32502
21915.2517.2063-1.95626
22011.915.2899-3.38987
22113.213.7801-0.580087
22216.3516.3968-0.0467789
22312.410.0982.30204
22415.8514.97070.879253
22514.3511.22853.12147
22618.1518.559-0.409007
22711.1512.3642-1.21424
22815.6513.77271.87731
22917.7522.254-4.50396
2307.657.027580.62242
23112.357.584684.76532
23215.612.48523.11477
23319.316.21433.08573
23415.211.01864.18144
23517.114.70132.39872
23615.611.12534.47471
23718.414.21054.18948
23819.0512.97526.07476
23918.5515.9482.60203
24019.117.99691.10311
24113.113.2469-0.146933
24212.8513.3397-0.489667
2439.514.923-5.42301
2444.53.183811.31619
24511.8513.5092-1.65918
24613.614.0557-0.455703
24711.710.72730.972714
24812.413.013-0.613011
24913.3515.8088-2.45877
25011.48.605182.79482
25114.911.04733.85265
25219.913.60066.29937
25317.7519.3236-1.57362
25411.212.8229-1.6229
25514.612.7541.846
25617.615.67341.92655
25714.0512.48591.56414
25816.115.13420.965794
25913.3513.3827-0.0326691
26011.8513.0589-1.20889
26111.9512.5178-0.567755
26214.7513.10671.64328
26315.1515.7997-0.649654
26413.212.78510.414893
26516.8519.1377-2.2877
2667.8514.0475-6.19755
2677.76.475271.22473
26812.616.7121-4.11212
2697.857.782490.0675121
27010.9511.0396-0.0895841
27112.3515.4128-3.06277
2729.957.097952.85205
27314.913.63371.26627
27416.6516.6598-0.00975863
27513.413.8801-0.480063
27613.959.650544.29946
27715.711.84293.85715
27816.8516.14840.701562
27910.957.823083.12692
28015.3514.66810.681857
28112.210.91181.28819
28215.114.46420.635779
28317.7515.66292.0871
28415.213.59241.60756
28514.613.27241.32756
28616.6519.463-2.81295
2878.1NANA







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.9503430.09931410.049657
130.9126940.1746130.0873063
140.8915260.2169480.108474
150.8317290.3365410.168271
160.7548520.4902960.245148
170.6651220.6697550.334878
180.5722830.8554350.427717
190.4849030.9698060.515097
200.4983880.9967770.501612
210.4361160.8722320.563884
220.4830550.966110.516945
230.422810.845620.57719
240.3642070.7284130.635793
250.2993280.5986560.700672
260.2689050.537810.731095
270.2267230.4534460.773277
280.1779520.3559030.822048
290.1704930.3409870.829507
300.1319280.2638570.868072
310.128110.256220.87189
320.1117460.2234930.888254
330.1153540.2307090.884646
340.1301360.2602720.869864
350.1082670.2165340.891733
360.1370160.2740310.862984
370.1241620.2483240.875838
380.1003340.2006680.899666
390.07876520.157530.921235
400.06177130.1235430.938229
410.08354150.1670830.916459
420.08386330.1677270.916137
430.1455450.2910890.854455
440.1235070.2470130.876493
450.1122790.2245580.887721
460.09453170.1890630.905468
470.07697840.1539570.923022
480.06328620.1265720.936714
490.05546260.1109250.944537
500.0970760.1941520.902924
510.1359780.2719570.864022
520.1200730.2401460.879927
530.09882270.1976450.901177
540.1150260.2300530.884974
550.1044510.2089020.895549
560.09245810.1849160.907542
570.1048320.2096640.895168
580.09272290.1854460.907277
590.2023250.404650.797675
600.2523350.5046710.747665
610.2247210.4494420.775279
620.2165320.4330640.783468
630.2205350.4410690.779465
640.2144030.4288060.785597
650.205780.411560.79422
660.234090.468180.76591
670.2296310.4592620.770369
680.2069230.4138460.793077
690.198320.3966390.80168
700.1789980.3579960.821002
710.1789660.3579330.821034
720.1551070.3102130.844893
730.1402760.2805520.859724
740.1263310.2526630.873669
750.116370.2327410.88363
760.1147580.2295160.885242
770.1973940.3947880.802606
780.1856160.3712320.814384
790.1702370.3404740.829763
800.1505120.3010250.849488
810.1547060.3094120.845294
820.1381930.2763860.861807
830.1508160.3016320.849184
840.1312820.2625630.868718
850.1329560.2659130.867044
860.115490.230980.88451
870.2299850.459970.770015
880.2247420.4494840.775258
890.2008330.4016650.799167
900.1759170.3518340.824083
910.1579640.3159280.842036
920.151430.302860.84857
930.1489120.2978250.851088
940.1511950.3023890.848805
950.2770090.5540190.722991
960.2800950.5601910.719905
970.2879270.5758540.712073
980.3276770.6553550.672323
990.3243840.6487680.675616
1000.4406520.8813050.559348
1010.4282410.8564810.571759
1020.4656740.9313470.534326
1030.5320740.9358510.467926
1040.5056440.9887130.494356
1050.4918420.9836850.508158
1060.5035730.9928540.496427
1070.5287090.9425820.471291
1080.5503060.8993880.449694
1090.5819750.8360490.418025
1100.5860890.8278220.413911
1110.78950.4209990.2105
1120.8221670.3556670.177833
1130.832060.335880.16794
1140.832240.3355210.16776
1150.8273650.3452710.172635
1160.8582120.2835760.141788
1170.8547060.2905870.145294
1180.9226870.1546270.0773134
1190.9510690.0978630.0489315
1200.9433680.1132640.0566322
1210.9587090.08258110.0412905
1220.9611030.07779430.0388972
1230.9716780.0566430.0283215
1240.9738470.05230570.0261528
1250.9830790.03384160.0169208
1260.9834030.03319410.0165971
1270.9942280.01154470.00577235
1280.99470.01059930.00529967
1290.9934490.01310110.00655056
1300.9932210.01355860.00677932
1310.9922060.01558830.00779413
1320.9914630.01707340.00853668
1330.9913840.01723190.00861597
1340.9922080.01558380.00779188
1350.9910910.01781720.00890861
1360.9923610.01527840.00763918
1370.9912110.0175780.008789
1380.9893610.02127790.010639
1390.9867920.02641530.0132076
1400.9915570.01688690.00844343
1410.9904540.01909270.00954634
1420.9895530.02089460.0104473
1430.986980.02604090.0130205
1440.984850.03030020.0151501
1450.9936910.01261880.00630938
1460.9933150.01337060.00668531
1470.9936280.01274380.00637188
1480.9934160.01316790.00658393
1490.9923040.0153920.00769598
1500.9925550.01488990.00744496
1510.9909910.01801760.00900882
1520.9897680.02046320.0102316
1530.9879890.02402270.0120113
1540.9857810.02843730.0142187
1550.984640.03071970.0153598
1560.9951990.009602750.00480138
1570.9948260.01034710.00517355
1580.9950430.009913650.00495682
1590.9937870.0124260.00621298
1600.9935870.01282640.0064132
1610.9921780.01564340.00782169
1620.9918880.01622430.00811215
1630.9908630.01827450.00913724
1640.9912430.0175140.00875698
1650.9895260.02094880.0104744
1660.9925910.01481780.00740891
1670.9906970.01860580.0093029
1680.990650.01870060.0093503
1690.9997160.0005682980.000284149
1700.9997460.0005083710.000254186
1710.9996520.0006953240.000347662
1720.9995910.0008178560.000408928
1730.9996950.0006108120.000305406
1740.9995760.0008474250.000423712
1750.9996450.0007101050.000355053
1760.9995220.0009564750.000478237
1770.9996550.0006908850.000345442
1780.9996340.0007325110.000366256
1790.9995170.0009658490.000482925
1800.9993780.001243430.000621714
1810.9994490.001101550.000550774
1820.9992490.00150130.000750652
1830.9992290.001541330.000770667
1840.9991940.001612430.000806214
1850.9991310.001737340.000868671
1860.9989940.002011430.00100572
1870.998940.002120480.00106024
1880.9987910.002418150.00120908
1890.9984220.003155310.00157766
1900.9991090.001782120.000891058
1910.9988250.002350210.00117511
1920.9991970.001606220.000803108
1930.9990680.001863930.000931964
1940.9988370.002326350.00116317
1950.9984060.003188760.00159438
1960.9980370.003926480.00196324
1970.9978080.004383650.00219183
1980.9978570.004285730.00214287
1990.9985380.002924590.0014623
2000.9980280.003943610.0019718
2010.9975630.004874360.00243718
2020.9973820.005235710.00261785
2030.9965570.006885310.00344265
2040.9967250.006549920.00327496
2050.9962170.007566130.00378306
2060.9958930.008213650.00410682
2070.9950810.009838160.00491908
2080.9940490.01190250.00595123
2090.9923640.01527130.00763565
2100.9900110.01997870.00998937
2110.9933230.01335480.00667739
2120.9923740.01525150.00762576
2130.9911210.0177570.00887851
2140.9882570.02348540.0117427
2150.985810.02837930.0141897
2160.9822050.03558990.0177949
2170.9785890.04282150.0214107
2180.9741590.0516820.025841
2190.9700350.05993050.0299652
2200.9660970.06780520.0339026
2210.9608370.07832590.039163
2220.9504480.09910370.0495518
2230.9439750.112050.056025
2240.9338190.1323620.0661808
2250.9240340.1519310.0759656
2260.9065530.1868940.0934469
2270.8923190.2153610.107681
2280.8897380.2205240.110262
2290.912220.175560.08778
2300.8919580.2160840.108042
2310.8965980.2068050.103402
2320.8841580.2316840.115842
2330.9272030.1455940.0727971
2340.9354990.1290010.0645005
2350.9373480.1253040.0626521
2360.9438160.1123670.0561835
2370.9533780.09324460.0466223
2380.9721750.055650.027825
2390.967590.064820.03241
2400.9572530.08549490.0427474
2410.9553140.08937130.0446857
2420.9435710.1128570.0564287
2430.9584890.08302120.0415106
2440.9531860.09362780.0468139
2450.9426460.1147080.0573542
2460.9322260.1355470.0677736
2470.9115620.1768750.0884375
2480.8863670.2272650.113633
2490.8620020.2759960.137998
2500.8424060.3151870.157594
2510.8138380.3723240.186162
2520.9277440.1445120.0722561
2530.9100110.1799780.0899892
2540.9076980.1846030.0923016
2550.8780690.2438620.121931
2560.8895750.220850.110425
2570.8647360.2705280.135264
2580.8354130.3291740.164587
2590.7880260.4239480.211974
2600.7577140.4845710.242286
2610.7047360.5905280.295264
2620.6920190.6159620.307981
2630.6394350.7211310.360565
2640.5702860.8594280.429714
2650.5624720.8750560.437528
2660.9914910.01701740.00850871
2670.9915650.01687060.00843532
2680.9960360.007927320.00396366
2690.9961840.007631920.00381596
2700.9987720.002456770.00122839
2710.9995330.0009337820.000466891
2720.9980920.003815210.00190761
2730.9971060.005787860.00289393
2740.9974140.005172610.00258631
2750.9773050.04538950.0226947

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.950343 & 0.0993141 & 0.049657 \tabularnewline
13 & 0.912694 & 0.174613 & 0.0873063 \tabularnewline
14 & 0.891526 & 0.216948 & 0.108474 \tabularnewline
15 & 0.831729 & 0.336541 & 0.168271 \tabularnewline
16 & 0.754852 & 0.490296 & 0.245148 \tabularnewline
17 & 0.665122 & 0.669755 & 0.334878 \tabularnewline
18 & 0.572283 & 0.855435 & 0.427717 \tabularnewline
19 & 0.484903 & 0.969806 & 0.515097 \tabularnewline
20 & 0.498388 & 0.996777 & 0.501612 \tabularnewline
21 & 0.436116 & 0.872232 & 0.563884 \tabularnewline
22 & 0.483055 & 0.96611 & 0.516945 \tabularnewline
23 & 0.42281 & 0.84562 & 0.57719 \tabularnewline
24 & 0.364207 & 0.728413 & 0.635793 \tabularnewline
25 & 0.299328 & 0.598656 & 0.700672 \tabularnewline
26 & 0.268905 & 0.53781 & 0.731095 \tabularnewline
27 & 0.226723 & 0.453446 & 0.773277 \tabularnewline
28 & 0.177952 & 0.355903 & 0.822048 \tabularnewline
29 & 0.170493 & 0.340987 & 0.829507 \tabularnewline
30 & 0.131928 & 0.263857 & 0.868072 \tabularnewline
31 & 0.12811 & 0.25622 & 0.87189 \tabularnewline
32 & 0.111746 & 0.223493 & 0.888254 \tabularnewline
33 & 0.115354 & 0.230709 & 0.884646 \tabularnewline
34 & 0.130136 & 0.260272 & 0.869864 \tabularnewline
35 & 0.108267 & 0.216534 & 0.891733 \tabularnewline
36 & 0.137016 & 0.274031 & 0.862984 \tabularnewline
37 & 0.124162 & 0.248324 & 0.875838 \tabularnewline
38 & 0.100334 & 0.200668 & 0.899666 \tabularnewline
39 & 0.0787652 & 0.15753 & 0.921235 \tabularnewline
40 & 0.0617713 & 0.123543 & 0.938229 \tabularnewline
41 & 0.0835415 & 0.167083 & 0.916459 \tabularnewline
42 & 0.0838633 & 0.167727 & 0.916137 \tabularnewline
43 & 0.145545 & 0.291089 & 0.854455 \tabularnewline
44 & 0.123507 & 0.247013 & 0.876493 \tabularnewline
45 & 0.112279 & 0.224558 & 0.887721 \tabularnewline
46 & 0.0945317 & 0.189063 & 0.905468 \tabularnewline
47 & 0.0769784 & 0.153957 & 0.923022 \tabularnewline
48 & 0.0632862 & 0.126572 & 0.936714 \tabularnewline
49 & 0.0554626 & 0.110925 & 0.944537 \tabularnewline
50 & 0.097076 & 0.194152 & 0.902924 \tabularnewline
51 & 0.135978 & 0.271957 & 0.864022 \tabularnewline
52 & 0.120073 & 0.240146 & 0.879927 \tabularnewline
53 & 0.0988227 & 0.197645 & 0.901177 \tabularnewline
54 & 0.115026 & 0.230053 & 0.884974 \tabularnewline
55 & 0.104451 & 0.208902 & 0.895549 \tabularnewline
56 & 0.0924581 & 0.184916 & 0.907542 \tabularnewline
57 & 0.104832 & 0.209664 & 0.895168 \tabularnewline
58 & 0.0927229 & 0.185446 & 0.907277 \tabularnewline
59 & 0.202325 & 0.40465 & 0.797675 \tabularnewline
60 & 0.252335 & 0.504671 & 0.747665 \tabularnewline
61 & 0.224721 & 0.449442 & 0.775279 \tabularnewline
62 & 0.216532 & 0.433064 & 0.783468 \tabularnewline
63 & 0.220535 & 0.441069 & 0.779465 \tabularnewline
64 & 0.214403 & 0.428806 & 0.785597 \tabularnewline
65 & 0.20578 & 0.41156 & 0.79422 \tabularnewline
66 & 0.23409 & 0.46818 & 0.76591 \tabularnewline
67 & 0.229631 & 0.459262 & 0.770369 \tabularnewline
68 & 0.206923 & 0.413846 & 0.793077 \tabularnewline
69 & 0.19832 & 0.396639 & 0.80168 \tabularnewline
70 & 0.178998 & 0.357996 & 0.821002 \tabularnewline
71 & 0.178966 & 0.357933 & 0.821034 \tabularnewline
72 & 0.155107 & 0.310213 & 0.844893 \tabularnewline
73 & 0.140276 & 0.280552 & 0.859724 \tabularnewline
74 & 0.126331 & 0.252663 & 0.873669 \tabularnewline
75 & 0.11637 & 0.232741 & 0.88363 \tabularnewline
76 & 0.114758 & 0.229516 & 0.885242 \tabularnewline
77 & 0.197394 & 0.394788 & 0.802606 \tabularnewline
78 & 0.185616 & 0.371232 & 0.814384 \tabularnewline
79 & 0.170237 & 0.340474 & 0.829763 \tabularnewline
80 & 0.150512 & 0.301025 & 0.849488 \tabularnewline
81 & 0.154706 & 0.309412 & 0.845294 \tabularnewline
82 & 0.138193 & 0.276386 & 0.861807 \tabularnewline
83 & 0.150816 & 0.301632 & 0.849184 \tabularnewline
84 & 0.131282 & 0.262563 & 0.868718 \tabularnewline
85 & 0.132956 & 0.265913 & 0.867044 \tabularnewline
86 & 0.11549 & 0.23098 & 0.88451 \tabularnewline
87 & 0.229985 & 0.45997 & 0.770015 \tabularnewline
88 & 0.224742 & 0.449484 & 0.775258 \tabularnewline
89 & 0.200833 & 0.401665 & 0.799167 \tabularnewline
90 & 0.175917 & 0.351834 & 0.824083 \tabularnewline
91 & 0.157964 & 0.315928 & 0.842036 \tabularnewline
92 & 0.15143 & 0.30286 & 0.84857 \tabularnewline
93 & 0.148912 & 0.297825 & 0.851088 \tabularnewline
94 & 0.151195 & 0.302389 & 0.848805 \tabularnewline
95 & 0.277009 & 0.554019 & 0.722991 \tabularnewline
96 & 0.280095 & 0.560191 & 0.719905 \tabularnewline
97 & 0.287927 & 0.575854 & 0.712073 \tabularnewline
98 & 0.327677 & 0.655355 & 0.672323 \tabularnewline
99 & 0.324384 & 0.648768 & 0.675616 \tabularnewline
100 & 0.440652 & 0.881305 & 0.559348 \tabularnewline
101 & 0.428241 & 0.856481 & 0.571759 \tabularnewline
102 & 0.465674 & 0.931347 & 0.534326 \tabularnewline
103 & 0.532074 & 0.935851 & 0.467926 \tabularnewline
104 & 0.505644 & 0.988713 & 0.494356 \tabularnewline
105 & 0.491842 & 0.983685 & 0.508158 \tabularnewline
106 & 0.503573 & 0.992854 & 0.496427 \tabularnewline
107 & 0.528709 & 0.942582 & 0.471291 \tabularnewline
108 & 0.550306 & 0.899388 & 0.449694 \tabularnewline
109 & 0.581975 & 0.836049 & 0.418025 \tabularnewline
110 & 0.586089 & 0.827822 & 0.413911 \tabularnewline
111 & 0.7895 & 0.420999 & 0.2105 \tabularnewline
112 & 0.822167 & 0.355667 & 0.177833 \tabularnewline
113 & 0.83206 & 0.33588 & 0.16794 \tabularnewline
114 & 0.83224 & 0.335521 & 0.16776 \tabularnewline
115 & 0.827365 & 0.345271 & 0.172635 \tabularnewline
116 & 0.858212 & 0.283576 & 0.141788 \tabularnewline
117 & 0.854706 & 0.290587 & 0.145294 \tabularnewline
118 & 0.922687 & 0.154627 & 0.0773134 \tabularnewline
119 & 0.951069 & 0.097863 & 0.0489315 \tabularnewline
120 & 0.943368 & 0.113264 & 0.0566322 \tabularnewline
121 & 0.958709 & 0.0825811 & 0.0412905 \tabularnewline
122 & 0.961103 & 0.0777943 & 0.0388972 \tabularnewline
123 & 0.971678 & 0.056643 & 0.0283215 \tabularnewline
124 & 0.973847 & 0.0523057 & 0.0261528 \tabularnewline
125 & 0.983079 & 0.0338416 & 0.0169208 \tabularnewline
126 & 0.983403 & 0.0331941 & 0.0165971 \tabularnewline
127 & 0.994228 & 0.0115447 & 0.00577235 \tabularnewline
128 & 0.9947 & 0.0105993 & 0.00529967 \tabularnewline
129 & 0.993449 & 0.0131011 & 0.00655056 \tabularnewline
130 & 0.993221 & 0.0135586 & 0.00677932 \tabularnewline
131 & 0.992206 & 0.0155883 & 0.00779413 \tabularnewline
132 & 0.991463 & 0.0170734 & 0.00853668 \tabularnewline
133 & 0.991384 & 0.0172319 & 0.00861597 \tabularnewline
134 & 0.992208 & 0.0155838 & 0.00779188 \tabularnewline
135 & 0.991091 & 0.0178172 & 0.00890861 \tabularnewline
136 & 0.992361 & 0.0152784 & 0.00763918 \tabularnewline
137 & 0.991211 & 0.017578 & 0.008789 \tabularnewline
138 & 0.989361 & 0.0212779 & 0.010639 \tabularnewline
139 & 0.986792 & 0.0264153 & 0.0132076 \tabularnewline
140 & 0.991557 & 0.0168869 & 0.00844343 \tabularnewline
141 & 0.990454 & 0.0190927 & 0.00954634 \tabularnewline
142 & 0.989553 & 0.0208946 & 0.0104473 \tabularnewline
143 & 0.98698 & 0.0260409 & 0.0130205 \tabularnewline
144 & 0.98485 & 0.0303002 & 0.0151501 \tabularnewline
145 & 0.993691 & 0.0126188 & 0.00630938 \tabularnewline
146 & 0.993315 & 0.0133706 & 0.00668531 \tabularnewline
147 & 0.993628 & 0.0127438 & 0.00637188 \tabularnewline
148 & 0.993416 & 0.0131679 & 0.00658393 \tabularnewline
149 & 0.992304 & 0.015392 & 0.00769598 \tabularnewline
150 & 0.992555 & 0.0148899 & 0.00744496 \tabularnewline
151 & 0.990991 & 0.0180176 & 0.00900882 \tabularnewline
152 & 0.989768 & 0.0204632 & 0.0102316 \tabularnewline
153 & 0.987989 & 0.0240227 & 0.0120113 \tabularnewline
154 & 0.985781 & 0.0284373 & 0.0142187 \tabularnewline
155 & 0.98464 & 0.0307197 & 0.0153598 \tabularnewline
156 & 0.995199 & 0.00960275 & 0.00480138 \tabularnewline
157 & 0.994826 & 0.0103471 & 0.00517355 \tabularnewline
158 & 0.995043 & 0.00991365 & 0.00495682 \tabularnewline
159 & 0.993787 & 0.012426 & 0.00621298 \tabularnewline
160 & 0.993587 & 0.0128264 & 0.0064132 \tabularnewline
161 & 0.992178 & 0.0156434 & 0.00782169 \tabularnewline
162 & 0.991888 & 0.0162243 & 0.00811215 \tabularnewline
163 & 0.990863 & 0.0182745 & 0.00913724 \tabularnewline
164 & 0.991243 & 0.017514 & 0.00875698 \tabularnewline
165 & 0.989526 & 0.0209488 & 0.0104744 \tabularnewline
166 & 0.992591 & 0.0148178 & 0.00740891 \tabularnewline
167 & 0.990697 & 0.0186058 & 0.0093029 \tabularnewline
168 & 0.99065 & 0.0187006 & 0.0093503 \tabularnewline
169 & 0.999716 & 0.000568298 & 0.000284149 \tabularnewline
170 & 0.999746 & 0.000508371 & 0.000254186 \tabularnewline
171 & 0.999652 & 0.000695324 & 0.000347662 \tabularnewline
172 & 0.999591 & 0.000817856 & 0.000408928 \tabularnewline
173 & 0.999695 & 0.000610812 & 0.000305406 \tabularnewline
174 & 0.999576 & 0.000847425 & 0.000423712 \tabularnewline
175 & 0.999645 & 0.000710105 & 0.000355053 \tabularnewline
176 & 0.999522 & 0.000956475 & 0.000478237 \tabularnewline
177 & 0.999655 & 0.000690885 & 0.000345442 \tabularnewline
178 & 0.999634 & 0.000732511 & 0.000366256 \tabularnewline
179 & 0.999517 & 0.000965849 & 0.000482925 \tabularnewline
180 & 0.999378 & 0.00124343 & 0.000621714 \tabularnewline
181 & 0.999449 & 0.00110155 & 0.000550774 \tabularnewline
182 & 0.999249 & 0.0015013 & 0.000750652 \tabularnewline
183 & 0.999229 & 0.00154133 & 0.000770667 \tabularnewline
184 & 0.999194 & 0.00161243 & 0.000806214 \tabularnewline
185 & 0.999131 & 0.00173734 & 0.000868671 \tabularnewline
186 & 0.998994 & 0.00201143 & 0.00100572 \tabularnewline
187 & 0.99894 & 0.00212048 & 0.00106024 \tabularnewline
188 & 0.998791 & 0.00241815 & 0.00120908 \tabularnewline
189 & 0.998422 & 0.00315531 & 0.00157766 \tabularnewline
190 & 0.999109 & 0.00178212 & 0.000891058 \tabularnewline
191 & 0.998825 & 0.00235021 & 0.00117511 \tabularnewline
192 & 0.999197 & 0.00160622 & 0.000803108 \tabularnewline
193 & 0.999068 & 0.00186393 & 0.000931964 \tabularnewline
194 & 0.998837 & 0.00232635 & 0.00116317 \tabularnewline
195 & 0.998406 & 0.00318876 & 0.00159438 \tabularnewline
196 & 0.998037 & 0.00392648 & 0.00196324 \tabularnewline
197 & 0.997808 & 0.00438365 & 0.00219183 \tabularnewline
198 & 0.997857 & 0.00428573 & 0.00214287 \tabularnewline
199 & 0.998538 & 0.00292459 & 0.0014623 \tabularnewline
200 & 0.998028 & 0.00394361 & 0.0019718 \tabularnewline
201 & 0.997563 & 0.00487436 & 0.00243718 \tabularnewline
202 & 0.997382 & 0.00523571 & 0.00261785 \tabularnewline
203 & 0.996557 & 0.00688531 & 0.00344265 \tabularnewline
204 & 0.996725 & 0.00654992 & 0.00327496 \tabularnewline
205 & 0.996217 & 0.00756613 & 0.00378306 \tabularnewline
206 & 0.995893 & 0.00821365 & 0.00410682 \tabularnewline
207 & 0.995081 & 0.00983816 & 0.00491908 \tabularnewline
208 & 0.994049 & 0.0119025 & 0.00595123 \tabularnewline
209 & 0.992364 & 0.0152713 & 0.00763565 \tabularnewline
210 & 0.990011 & 0.0199787 & 0.00998937 \tabularnewline
211 & 0.993323 & 0.0133548 & 0.00667739 \tabularnewline
212 & 0.992374 & 0.0152515 & 0.00762576 \tabularnewline
213 & 0.991121 & 0.017757 & 0.00887851 \tabularnewline
214 & 0.988257 & 0.0234854 & 0.0117427 \tabularnewline
215 & 0.98581 & 0.0283793 & 0.0141897 \tabularnewline
216 & 0.982205 & 0.0355899 & 0.0177949 \tabularnewline
217 & 0.978589 & 0.0428215 & 0.0214107 \tabularnewline
218 & 0.974159 & 0.051682 & 0.025841 \tabularnewline
219 & 0.970035 & 0.0599305 & 0.0299652 \tabularnewline
220 & 0.966097 & 0.0678052 & 0.0339026 \tabularnewline
221 & 0.960837 & 0.0783259 & 0.039163 \tabularnewline
222 & 0.950448 & 0.0991037 & 0.0495518 \tabularnewline
223 & 0.943975 & 0.11205 & 0.056025 \tabularnewline
224 & 0.933819 & 0.132362 & 0.0661808 \tabularnewline
225 & 0.924034 & 0.151931 & 0.0759656 \tabularnewline
226 & 0.906553 & 0.186894 & 0.0934469 \tabularnewline
227 & 0.892319 & 0.215361 & 0.107681 \tabularnewline
228 & 0.889738 & 0.220524 & 0.110262 \tabularnewline
229 & 0.91222 & 0.17556 & 0.08778 \tabularnewline
230 & 0.891958 & 0.216084 & 0.108042 \tabularnewline
231 & 0.896598 & 0.206805 & 0.103402 \tabularnewline
232 & 0.884158 & 0.231684 & 0.115842 \tabularnewline
233 & 0.927203 & 0.145594 & 0.0727971 \tabularnewline
234 & 0.935499 & 0.129001 & 0.0645005 \tabularnewline
235 & 0.937348 & 0.125304 & 0.0626521 \tabularnewline
236 & 0.943816 & 0.112367 & 0.0561835 \tabularnewline
237 & 0.953378 & 0.0932446 & 0.0466223 \tabularnewline
238 & 0.972175 & 0.05565 & 0.027825 \tabularnewline
239 & 0.96759 & 0.06482 & 0.03241 \tabularnewline
240 & 0.957253 & 0.0854949 & 0.0427474 \tabularnewline
241 & 0.955314 & 0.0893713 & 0.0446857 \tabularnewline
242 & 0.943571 & 0.112857 & 0.0564287 \tabularnewline
243 & 0.958489 & 0.0830212 & 0.0415106 \tabularnewline
244 & 0.953186 & 0.0936278 & 0.0468139 \tabularnewline
245 & 0.942646 & 0.114708 & 0.0573542 \tabularnewline
246 & 0.932226 & 0.135547 & 0.0677736 \tabularnewline
247 & 0.911562 & 0.176875 & 0.0884375 \tabularnewline
248 & 0.886367 & 0.227265 & 0.113633 \tabularnewline
249 & 0.862002 & 0.275996 & 0.137998 \tabularnewline
250 & 0.842406 & 0.315187 & 0.157594 \tabularnewline
251 & 0.813838 & 0.372324 & 0.186162 \tabularnewline
252 & 0.927744 & 0.144512 & 0.0722561 \tabularnewline
253 & 0.910011 & 0.179978 & 0.0899892 \tabularnewline
254 & 0.907698 & 0.184603 & 0.0923016 \tabularnewline
255 & 0.878069 & 0.243862 & 0.121931 \tabularnewline
256 & 0.889575 & 0.22085 & 0.110425 \tabularnewline
257 & 0.864736 & 0.270528 & 0.135264 \tabularnewline
258 & 0.835413 & 0.329174 & 0.164587 \tabularnewline
259 & 0.788026 & 0.423948 & 0.211974 \tabularnewline
260 & 0.757714 & 0.484571 & 0.242286 \tabularnewline
261 & 0.704736 & 0.590528 & 0.295264 \tabularnewline
262 & 0.692019 & 0.615962 & 0.307981 \tabularnewline
263 & 0.639435 & 0.721131 & 0.360565 \tabularnewline
264 & 0.570286 & 0.859428 & 0.429714 \tabularnewline
265 & 0.562472 & 0.875056 & 0.437528 \tabularnewline
266 & 0.991491 & 0.0170174 & 0.00850871 \tabularnewline
267 & 0.991565 & 0.0168706 & 0.00843532 \tabularnewline
268 & 0.996036 & 0.00792732 & 0.00396366 \tabularnewline
269 & 0.996184 & 0.00763192 & 0.00381596 \tabularnewline
270 & 0.998772 & 0.00245677 & 0.00122839 \tabularnewline
271 & 0.999533 & 0.000933782 & 0.000466891 \tabularnewline
272 & 0.998092 & 0.00381521 & 0.00190761 \tabularnewline
273 & 0.997106 & 0.00578786 & 0.00289393 \tabularnewline
274 & 0.997414 & 0.00517261 & 0.00258631 \tabularnewline
275 & 0.977305 & 0.0453895 & 0.0226947 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269831&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]12[/C][C]0.950343[/C][C]0.0993141[/C][C]0.049657[/C][/ROW]
[ROW][C]13[/C][C]0.912694[/C][C]0.174613[/C][C]0.0873063[/C][/ROW]
[ROW][C]14[/C][C]0.891526[/C][C]0.216948[/C][C]0.108474[/C][/ROW]
[ROW][C]15[/C][C]0.831729[/C][C]0.336541[/C][C]0.168271[/C][/ROW]
[ROW][C]16[/C][C]0.754852[/C][C]0.490296[/C][C]0.245148[/C][/ROW]
[ROW][C]17[/C][C]0.665122[/C][C]0.669755[/C][C]0.334878[/C][/ROW]
[ROW][C]18[/C][C]0.572283[/C][C]0.855435[/C][C]0.427717[/C][/ROW]
[ROW][C]19[/C][C]0.484903[/C][C]0.969806[/C][C]0.515097[/C][/ROW]
[ROW][C]20[/C][C]0.498388[/C][C]0.996777[/C][C]0.501612[/C][/ROW]
[ROW][C]21[/C][C]0.436116[/C][C]0.872232[/C][C]0.563884[/C][/ROW]
[ROW][C]22[/C][C]0.483055[/C][C]0.96611[/C][C]0.516945[/C][/ROW]
[ROW][C]23[/C][C]0.42281[/C][C]0.84562[/C][C]0.57719[/C][/ROW]
[ROW][C]24[/C][C]0.364207[/C][C]0.728413[/C][C]0.635793[/C][/ROW]
[ROW][C]25[/C][C]0.299328[/C][C]0.598656[/C][C]0.700672[/C][/ROW]
[ROW][C]26[/C][C]0.268905[/C][C]0.53781[/C][C]0.731095[/C][/ROW]
[ROW][C]27[/C][C]0.226723[/C][C]0.453446[/C][C]0.773277[/C][/ROW]
[ROW][C]28[/C][C]0.177952[/C][C]0.355903[/C][C]0.822048[/C][/ROW]
[ROW][C]29[/C][C]0.170493[/C][C]0.340987[/C][C]0.829507[/C][/ROW]
[ROW][C]30[/C][C]0.131928[/C][C]0.263857[/C][C]0.868072[/C][/ROW]
[ROW][C]31[/C][C]0.12811[/C][C]0.25622[/C][C]0.87189[/C][/ROW]
[ROW][C]32[/C][C]0.111746[/C][C]0.223493[/C][C]0.888254[/C][/ROW]
[ROW][C]33[/C][C]0.115354[/C][C]0.230709[/C][C]0.884646[/C][/ROW]
[ROW][C]34[/C][C]0.130136[/C][C]0.260272[/C][C]0.869864[/C][/ROW]
[ROW][C]35[/C][C]0.108267[/C][C]0.216534[/C][C]0.891733[/C][/ROW]
[ROW][C]36[/C][C]0.137016[/C][C]0.274031[/C][C]0.862984[/C][/ROW]
[ROW][C]37[/C][C]0.124162[/C][C]0.248324[/C][C]0.875838[/C][/ROW]
[ROW][C]38[/C][C]0.100334[/C][C]0.200668[/C][C]0.899666[/C][/ROW]
[ROW][C]39[/C][C]0.0787652[/C][C]0.15753[/C][C]0.921235[/C][/ROW]
[ROW][C]40[/C][C]0.0617713[/C][C]0.123543[/C][C]0.938229[/C][/ROW]
[ROW][C]41[/C][C]0.0835415[/C][C]0.167083[/C][C]0.916459[/C][/ROW]
[ROW][C]42[/C][C]0.0838633[/C][C]0.167727[/C][C]0.916137[/C][/ROW]
[ROW][C]43[/C][C]0.145545[/C][C]0.291089[/C][C]0.854455[/C][/ROW]
[ROW][C]44[/C][C]0.123507[/C][C]0.247013[/C][C]0.876493[/C][/ROW]
[ROW][C]45[/C][C]0.112279[/C][C]0.224558[/C][C]0.887721[/C][/ROW]
[ROW][C]46[/C][C]0.0945317[/C][C]0.189063[/C][C]0.905468[/C][/ROW]
[ROW][C]47[/C][C]0.0769784[/C][C]0.153957[/C][C]0.923022[/C][/ROW]
[ROW][C]48[/C][C]0.0632862[/C][C]0.126572[/C][C]0.936714[/C][/ROW]
[ROW][C]49[/C][C]0.0554626[/C][C]0.110925[/C][C]0.944537[/C][/ROW]
[ROW][C]50[/C][C]0.097076[/C][C]0.194152[/C][C]0.902924[/C][/ROW]
[ROW][C]51[/C][C]0.135978[/C][C]0.271957[/C][C]0.864022[/C][/ROW]
[ROW][C]52[/C][C]0.120073[/C][C]0.240146[/C][C]0.879927[/C][/ROW]
[ROW][C]53[/C][C]0.0988227[/C][C]0.197645[/C][C]0.901177[/C][/ROW]
[ROW][C]54[/C][C]0.115026[/C][C]0.230053[/C][C]0.884974[/C][/ROW]
[ROW][C]55[/C][C]0.104451[/C][C]0.208902[/C][C]0.895549[/C][/ROW]
[ROW][C]56[/C][C]0.0924581[/C][C]0.184916[/C][C]0.907542[/C][/ROW]
[ROW][C]57[/C][C]0.104832[/C][C]0.209664[/C][C]0.895168[/C][/ROW]
[ROW][C]58[/C][C]0.0927229[/C][C]0.185446[/C][C]0.907277[/C][/ROW]
[ROW][C]59[/C][C]0.202325[/C][C]0.40465[/C][C]0.797675[/C][/ROW]
[ROW][C]60[/C][C]0.252335[/C][C]0.504671[/C][C]0.747665[/C][/ROW]
[ROW][C]61[/C][C]0.224721[/C][C]0.449442[/C][C]0.775279[/C][/ROW]
[ROW][C]62[/C][C]0.216532[/C][C]0.433064[/C][C]0.783468[/C][/ROW]
[ROW][C]63[/C][C]0.220535[/C][C]0.441069[/C][C]0.779465[/C][/ROW]
[ROW][C]64[/C][C]0.214403[/C][C]0.428806[/C][C]0.785597[/C][/ROW]
[ROW][C]65[/C][C]0.20578[/C][C]0.41156[/C][C]0.79422[/C][/ROW]
[ROW][C]66[/C][C]0.23409[/C][C]0.46818[/C][C]0.76591[/C][/ROW]
[ROW][C]67[/C][C]0.229631[/C][C]0.459262[/C][C]0.770369[/C][/ROW]
[ROW][C]68[/C][C]0.206923[/C][C]0.413846[/C][C]0.793077[/C][/ROW]
[ROW][C]69[/C][C]0.19832[/C][C]0.396639[/C][C]0.80168[/C][/ROW]
[ROW][C]70[/C][C]0.178998[/C][C]0.357996[/C][C]0.821002[/C][/ROW]
[ROW][C]71[/C][C]0.178966[/C][C]0.357933[/C][C]0.821034[/C][/ROW]
[ROW][C]72[/C][C]0.155107[/C][C]0.310213[/C][C]0.844893[/C][/ROW]
[ROW][C]73[/C][C]0.140276[/C][C]0.280552[/C][C]0.859724[/C][/ROW]
[ROW][C]74[/C][C]0.126331[/C][C]0.252663[/C][C]0.873669[/C][/ROW]
[ROW][C]75[/C][C]0.11637[/C][C]0.232741[/C][C]0.88363[/C][/ROW]
[ROW][C]76[/C][C]0.114758[/C][C]0.229516[/C][C]0.885242[/C][/ROW]
[ROW][C]77[/C][C]0.197394[/C][C]0.394788[/C][C]0.802606[/C][/ROW]
[ROW][C]78[/C][C]0.185616[/C][C]0.371232[/C][C]0.814384[/C][/ROW]
[ROW][C]79[/C][C]0.170237[/C][C]0.340474[/C][C]0.829763[/C][/ROW]
[ROW][C]80[/C][C]0.150512[/C][C]0.301025[/C][C]0.849488[/C][/ROW]
[ROW][C]81[/C][C]0.154706[/C][C]0.309412[/C][C]0.845294[/C][/ROW]
[ROW][C]82[/C][C]0.138193[/C][C]0.276386[/C][C]0.861807[/C][/ROW]
[ROW][C]83[/C][C]0.150816[/C][C]0.301632[/C][C]0.849184[/C][/ROW]
[ROW][C]84[/C][C]0.131282[/C][C]0.262563[/C][C]0.868718[/C][/ROW]
[ROW][C]85[/C][C]0.132956[/C][C]0.265913[/C][C]0.867044[/C][/ROW]
[ROW][C]86[/C][C]0.11549[/C][C]0.23098[/C][C]0.88451[/C][/ROW]
[ROW][C]87[/C][C]0.229985[/C][C]0.45997[/C][C]0.770015[/C][/ROW]
[ROW][C]88[/C][C]0.224742[/C][C]0.449484[/C][C]0.775258[/C][/ROW]
[ROW][C]89[/C][C]0.200833[/C][C]0.401665[/C][C]0.799167[/C][/ROW]
[ROW][C]90[/C][C]0.175917[/C][C]0.351834[/C][C]0.824083[/C][/ROW]
[ROW][C]91[/C][C]0.157964[/C][C]0.315928[/C][C]0.842036[/C][/ROW]
[ROW][C]92[/C][C]0.15143[/C][C]0.30286[/C][C]0.84857[/C][/ROW]
[ROW][C]93[/C][C]0.148912[/C][C]0.297825[/C][C]0.851088[/C][/ROW]
[ROW][C]94[/C][C]0.151195[/C][C]0.302389[/C][C]0.848805[/C][/ROW]
[ROW][C]95[/C][C]0.277009[/C][C]0.554019[/C][C]0.722991[/C][/ROW]
[ROW][C]96[/C][C]0.280095[/C][C]0.560191[/C][C]0.719905[/C][/ROW]
[ROW][C]97[/C][C]0.287927[/C][C]0.575854[/C][C]0.712073[/C][/ROW]
[ROW][C]98[/C][C]0.327677[/C][C]0.655355[/C][C]0.672323[/C][/ROW]
[ROW][C]99[/C][C]0.324384[/C][C]0.648768[/C][C]0.675616[/C][/ROW]
[ROW][C]100[/C][C]0.440652[/C][C]0.881305[/C][C]0.559348[/C][/ROW]
[ROW][C]101[/C][C]0.428241[/C][C]0.856481[/C][C]0.571759[/C][/ROW]
[ROW][C]102[/C][C]0.465674[/C][C]0.931347[/C][C]0.534326[/C][/ROW]
[ROW][C]103[/C][C]0.532074[/C][C]0.935851[/C][C]0.467926[/C][/ROW]
[ROW][C]104[/C][C]0.505644[/C][C]0.988713[/C][C]0.494356[/C][/ROW]
[ROW][C]105[/C][C]0.491842[/C][C]0.983685[/C][C]0.508158[/C][/ROW]
[ROW][C]106[/C][C]0.503573[/C][C]0.992854[/C][C]0.496427[/C][/ROW]
[ROW][C]107[/C][C]0.528709[/C][C]0.942582[/C][C]0.471291[/C][/ROW]
[ROW][C]108[/C][C]0.550306[/C][C]0.899388[/C][C]0.449694[/C][/ROW]
[ROW][C]109[/C][C]0.581975[/C][C]0.836049[/C][C]0.418025[/C][/ROW]
[ROW][C]110[/C][C]0.586089[/C][C]0.827822[/C][C]0.413911[/C][/ROW]
[ROW][C]111[/C][C]0.7895[/C][C]0.420999[/C][C]0.2105[/C][/ROW]
[ROW][C]112[/C][C]0.822167[/C][C]0.355667[/C][C]0.177833[/C][/ROW]
[ROW][C]113[/C][C]0.83206[/C][C]0.33588[/C][C]0.16794[/C][/ROW]
[ROW][C]114[/C][C]0.83224[/C][C]0.335521[/C][C]0.16776[/C][/ROW]
[ROW][C]115[/C][C]0.827365[/C][C]0.345271[/C][C]0.172635[/C][/ROW]
[ROW][C]116[/C][C]0.858212[/C][C]0.283576[/C][C]0.141788[/C][/ROW]
[ROW][C]117[/C][C]0.854706[/C][C]0.290587[/C][C]0.145294[/C][/ROW]
[ROW][C]118[/C][C]0.922687[/C][C]0.154627[/C][C]0.0773134[/C][/ROW]
[ROW][C]119[/C][C]0.951069[/C][C]0.097863[/C][C]0.0489315[/C][/ROW]
[ROW][C]120[/C][C]0.943368[/C][C]0.113264[/C][C]0.0566322[/C][/ROW]
[ROW][C]121[/C][C]0.958709[/C][C]0.0825811[/C][C]0.0412905[/C][/ROW]
[ROW][C]122[/C][C]0.961103[/C][C]0.0777943[/C][C]0.0388972[/C][/ROW]
[ROW][C]123[/C][C]0.971678[/C][C]0.056643[/C][C]0.0283215[/C][/ROW]
[ROW][C]124[/C][C]0.973847[/C][C]0.0523057[/C][C]0.0261528[/C][/ROW]
[ROW][C]125[/C][C]0.983079[/C][C]0.0338416[/C][C]0.0169208[/C][/ROW]
[ROW][C]126[/C][C]0.983403[/C][C]0.0331941[/C][C]0.0165971[/C][/ROW]
[ROW][C]127[/C][C]0.994228[/C][C]0.0115447[/C][C]0.00577235[/C][/ROW]
[ROW][C]128[/C][C]0.9947[/C][C]0.0105993[/C][C]0.00529967[/C][/ROW]
[ROW][C]129[/C][C]0.993449[/C][C]0.0131011[/C][C]0.00655056[/C][/ROW]
[ROW][C]130[/C][C]0.993221[/C][C]0.0135586[/C][C]0.00677932[/C][/ROW]
[ROW][C]131[/C][C]0.992206[/C][C]0.0155883[/C][C]0.00779413[/C][/ROW]
[ROW][C]132[/C][C]0.991463[/C][C]0.0170734[/C][C]0.00853668[/C][/ROW]
[ROW][C]133[/C][C]0.991384[/C][C]0.0172319[/C][C]0.00861597[/C][/ROW]
[ROW][C]134[/C][C]0.992208[/C][C]0.0155838[/C][C]0.00779188[/C][/ROW]
[ROW][C]135[/C][C]0.991091[/C][C]0.0178172[/C][C]0.00890861[/C][/ROW]
[ROW][C]136[/C][C]0.992361[/C][C]0.0152784[/C][C]0.00763918[/C][/ROW]
[ROW][C]137[/C][C]0.991211[/C][C]0.017578[/C][C]0.008789[/C][/ROW]
[ROW][C]138[/C][C]0.989361[/C][C]0.0212779[/C][C]0.010639[/C][/ROW]
[ROW][C]139[/C][C]0.986792[/C][C]0.0264153[/C][C]0.0132076[/C][/ROW]
[ROW][C]140[/C][C]0.991557[/C][C]0.0168869[/C][C]0.00844343[/C][/ROW]
[ROW][C]141[/C][C]0.990454[/C][C]0.0190927[/C][C]0.00954634[/C][/ROW]
[ROW][C]142[/C][C]0.989553[/C][C]0.0208946[/C][C]0.0104473[/C][/ROW]
[ROW][C]143[/C][C]0.98698[/C][C]0.0260409[/C][C]0.0130205[/C][/ROW]
[ROW][C]144[/C][C]0.98485[/C][C]0.0303002[/C][C]0.0151501[/C][/ROW]
[ROW][C]145[/C][C]0.993691[/C][C]0.0126188[/C][C]0.00630938[/C][/ROW]
[ROW][C]146[/C][C]0.993315[/C][C]0.0133706[/C][C]0.00668531[/C][/ROW]
[ROW][C]147[/C][C]0.993628[/C][C]0.0127438[/C][C]0.00637188[/C][/ROW]
[ROW][C]148[/C][C]0.993416[/C][C]0.0131679[/C][C]0.00658393[/C][/ROW]
[ROW][C]149[/C][C]0.992304[/C][C]0.015392[/C][C]0.00769598[/C][/ROW]
[ROW][C]150[/C][C]0.992555[/C][C]0.0148899[/C][C]0.00744496[/C][/ROW]
[ROW][C]151[/C][C]0.990991[/C][C]0.0180176[/C][C]0.00900882[/C][/ROW]
[ROW][C]152[/C][C]0.989768[/C][C]0.0204632[/C][C]0.0102316[/C][/ROW]
[ROW][C]153[/C][C]0.987989[/C][C]0.0240227[/C][C]0.0120113[/C][/ROW]
[ROW][C]154[/C][C]0.985781[/C][C]0.0284373[/C][C]0.0142187[/C][/ROW]
[ROW][C]155[/C][C]0.98464[/C][C]0.0307197[/C][C]0.0153598[/C][/ROW]
[ROW][C]156[/C][C]0.995199[/C][C]0.00960275[/C][C]0.00480138[/C][/ROW]
[ROW][C]157[/C][C]0.994826[/C][C]0.0103471[/C][C]0.00517355[/C][/ROW]
[ROW][C]158[/C][C]0.995043[/C][C]0.00991365[/C][C]0.00495682[/C][/ROW]
[ROW][C]159[/C][C]0.993787[/C][C]0.012426[/C][C]0.00621298[/C][/ROW]
[ROW][C]160[/C][C]0.993587[/C][C]0.0128264[/C][C]0.0064132[/C][/ROW]
[ROW][C]161[/C][C]0.992178[/C][C]0.0156434[/C][C]0.00782169[/C][/ROW]
[ROW][C]162[/C][C]0.991888[/C][C]0.0162243[/C][C]0.00811215[/C][/ROW]
[ROW][C]163[/C][C]0.990863[/C][C]0.0182745[/C][C]0.00913724[/C][/ROW]
[ROW][C]164[/C][C]0.991243[/C][C]0.017514[/C][C]0.00875698[/C][/ROW]
[ROW][C]165[/C][C]0.989526[/C][C]0.0209488[/C][C]0.0104744[/C][/ROW]
[ROW][C]166[/C][C]0.992591[/C][C]0.0148178[/C][C]0.00740891[/C][/ROW]
[ROW][C]167[/C][C]0.990697[/C][C]0.0186058[/C][C]0.0093029[/C][/ROW]
[ROW][C]168[/C][C]0.99065[/C][C]0.0187006[/C][C]0.0093503[/C][/ROW]
[ROW][C]169[/C][C]0.999716[/C][C]0.000568298[/C][C]0.000284149[/C][/ROW]
[ROW][C]170[/C][C]0.999746[/C][C]0.000508371[/C][C]0.000254186[/C][/ROW]
[ROW][C]171[/C][C]0.999652[/C][C]0.000695324[/C][C]0.000347662[/C][/ROW]
[ROW][C]172[/C][C]0.999591[/C][C]0.000817856[/C][C]0.000408928[/C][/ROW]
[ROW][C]173[/C][C]0.999695[/C][C]0.000610812[/C][C]0.000305406[/C][/ROW]
[ROW][C]174[/C][C]0.999576[/C][C]0.000847425[/C][C]0.000423712[/C][/ROW]
[ROW][C]175[/C][C]0.999645[/C][C]0.000710105[/C][C]0.000355053[/C][/ROW]
[ROW][C]176[/C][C]0.999522[/C][C]0.000956475[/C][C]0.000478237[/C][/ROW]
[ROW][C]177[/C][C]0.999655[/C][C]0.000690885[/C][C]0.000345442[/C][/ROW]
[ROW][C]178[/C][C]0.999634[/C][C]0.000732511[/C][C]0.000366256[/C][/ROW]
[ROW][C]179[/C][C]0.999517[/C][C]0.000965849[/C][C]0.000482925[/C][/ROW]
[ROW][C]180[/C][C]0.999378[/C][C]0.00124343[/C][C]0.000621714[/C][/ROW]
[ROW][C]181[/C][C]0.999449[/C][C]0.00110155[/C][C]0.000550774[/C][/ROW]
[ROW][C]182[/C][C]0.999249[/C][C]0.0015013[/C][C]0.000750652[/C][/ROW]
[ROW][C]183[/C][C]0.999229[/C][C]0.00154133[/C][C]0.000770667[/C][/ROW]
[ROW][C]184[/C][C]0.999194[/C][C]0.00161243[/C][C]0.000806214[/C][/ROW]
[ROW][C]185[/C][C]0.999131[/C][C]0.00173734[/C][C]0.000868671[/C][/ROW]
[ROW][C]186[/C][C]0.998994[/C][C]0.00201143[/C][C]0.00100572[/C][/ROW]
[ROW][C]187[/C][C]0.99894[/C][C]0.00212048[/C][C]0.00106024[/C][/ROW]
[ROW][C]188[/C][C]0.998791[/C][C]0.00241815[/C][C]0.00120908[/C][/ROW]
[ROW][C]189[/C][C]0.998422[/C][C]0.00315531[/C][C]0.00157766[/C][/ROW]
[ROW][C]190[/C][C]0.999109[/C][C]0.00178212[/C][C]0.000891058[/C][/ROW]
[ROW][C]191[/C][C]0.998825[/C][C]0.00235021[/C][C]0.00117511[/C][/ROW]
[ROW][C]192[/C][C]0.999197[/C][C]0.00160622[/C][C]0.000803108[/C][/ROW]
[ROW][C]193[/C][C]0.999068[/C][C]0.00186393[/C][C]0.000931964[/C][/ROW]
[ROW][C]194[/C][C]0.998837[/C][C]0.00232635[/C][C]0.00116317[/C][/ROW]
[ROW][C]195[/C][C]0.998406[/C][C]0.00318876[/C][C]0.00159438[/C][/ROW]
[ROW][C]196[/C][C]0.998037[/C][C]0.00392648[/C][C]0.00196324[/C][/ROW]
[ROW][C]197[/C][C]0.997808[/C][C]0.00438365[/C][C]0.00219183[/C][/ROW]
[ROW][C]198[/C][C]0.997857[/C][C]0.00428573[/C][C]0.00214287[/C][/ROW]
[ROW][C]199[/C][C]0.998538[/C][C]0.00292459[/C][C]0.0014623[/C][/ROW]
[ROW][C]200[/C][C]0.998028[/C][C]0.00394361[/C][C]0.0019718[/C][/ROW]
[ROW][C]201[/C][C]0.997563[/C][C]0.00487436[/C][C]0.00243718[/C][/ROW]
[ROW][C]202[/C][C]0.997382[/C][C]0.00523571[/C][C]0.00261785[/C][/ROW]
[ROW][C]203[/C][C]0.996557[/C][C]0.00688531[/C][C]0.00344265[/C][/ROW]
[ROW][C]204[/C][C]0.996725[/C][C]0.00654992[/C][C]0.00327496[/C][/ROW]
[ROW][C]205[/C][C]0.996217[/C][C]0.00756613[/C][C]0.00378306[/C][/ROW]
[ROW][C]206[/C][C]0.995893[/C][C]0.00821365[/C][C]0.00410682[/C][/ROW]
[ROW][C]207[/C][C]0.995081[/C][C]0.00983816[/C][C]0.00491908[/C][/ROW]
[ROW][C]208[/C][C]0.994049[/C][C]0.0119025[/C][C]0.00595123[/C][/ROW]
[ROW][C]209[/C][C]0.992364[/C][C]0.0152713[/C][C]0.00763565[/C][/ROW]
[ROW][C]210[/C][C]0.990011[/C][C]0.0199787[/C][C]0.00998937[/C][/ROW]
[ROW][C]211[/C][C]0.993323[/C][C]0.0133548[/C][C]0.00667739[/C][/ROW]
[ROW][C]212[/C][C]0.992374[/C][C]0.0152515[/C][C]0.00762576[/C][/ROW]
[ROW][C]213[/C][C]0.991121[/C][C]0.017757[/C][C]0.00887851[/C][/ROW]
[ROW][C]214[/C][C]0.988257[/C][C]0.0234854[/C][C]0.0117427[/C][/ROW]
[ROW][C]215[/C][C]0.98581[/C][C]0.0283793[/C][C]0.0141897[/C][/ROW]
[ROW][C]216[/C][C]0.982205[/C][C]0.0355899[/C][C]0.0177949[/C][/ROW]
[ROW][C]217[/C][C]0.978589[/C][C]0.0428215[/C][C]0.0214107[/C][/ROW]
[ROW][C]218[/C][C]0.974159[/C][C]0.051682[/C][C]0.025841[/C][/ROW]
[ROW][C]219[/C][C]0.970035[/C][C]0.0599305[/C][C]0.0299652[/C][/ROW]
[ROW][C]220[/C][C]0.966097[/C][C]0.0678052[/C][C]0.0339026[/C][/ROW]
[ROW][C]221[/C][C]0.960837[/C][C]0.0783259[/C][C]0.039163[/C][/ROW]
[ROW][C]222[/C][C]0.950448[/C][C]0.0991037[/C][C]0.0495518[/C][/ROW]
[ROW][C]223[/C][C]0.943975[/C][C]0.11205[/C][C]0.056025[/C][/ROW]
[ROW][C]224[/C][C]0.933819[/C][C]0.132362[/C][C]0.0661808[/C][/ROW]
[ROW][C]225[/C][C]0.924034[/C][C]0.151931[/C][C]0.0759656[/C][/ROW]
[ROW][C]226[/C][C]0.906553[/C][C]0.186894[/C][C]0.0934469[/C][/ROW]
[ROW][C]227[/C][C]0.892319[/C][C]0.215361[/C][C]0.107681[/C][/ROW]
[ROW][C]228[/C][C]0.889738[/C][C]0.220524[/C][C]0.110262[/C][/ROW]
[ROW][C]229[/C][C]0.91222[/C][C]0.17556[/C][C]0.08778[/C][/ROW]
[ROW][C]230[/C][C]0.891958[/C][C]0.216084[/C][C]0.108042[/C][/ROW]
[ROW][C]231[/C][C]0.896598[/C][C]0.206805[/C][C]0.103402[/C][/ROW]
[ROW][C]232[/C][C]0.884158[/C][C]0.231684[/C][C]0.115842[/C][/ROW]
[ROW][C]233[/C][C]0.927203[/C][C]0.145594[/C][C]0.0727971[/C][/ROW]
[ROW][C]234[/C][C]0.935499[/C][C]0.129001[/C][C]0.0645005[/C][/ROW]
[ROW][C]235[/C][C]0.937348[/C][C]0.125304[/C][C]0.0626521[/C][/ROW]
[ROW][C]236[/C][C]0.943816[/C][C]0.112367[/C][C]0.0561835[/C][/ROW]
[ROW][C]237[/C][C]0.953378[/C][C]0.0932446[/C][C]0.0466223[/C][/ROW]
[ROW][C]238[/C][C]0.972175[/C][C]0.05565[/C][C]0.027825[/C][/ROW]
[ROW][C]239[/C][C]0.96759[/C][C]0.06482[/C][C]0.03241[/C][/ROW]
[ROW][C]240[/C][C]0.957253[/C][C]0.0854949[/C][C]0.0427474[/C][/ROW]
[ROW][C]241[/C][C]0.955314[/C][C]0.0893713[/C][C]0.0446857[/C][/ROW]
[ROW][C]242[/C][C]0.943571[/C][C]0.112857[/C][C]0.0564287[/C][/ROW]
[ROW][C]243[/C][C]0.958489[/C][C]0.0830212[/C][C]0.0415106[/C][/ROW]
[ROW][C]244[/C][C]0.953186[/C][C]0.0936278[/C][C]0.0468139[/C][/ROW]
[ROW][C]245[/C][C]0.942646[/C][C]0.114708[/C][C]0.0573542[/C][/ROW]
[ROW][C]246[/C][C]0.932226[/C][C]0.135547[/C][C]0.0677736[/C][/ROW]
[ROW][C]247[/C][C]0.911562[/C][C]0.176875[/C][C]0.0884375[/C][/ROW]
[ROW][C]248[/C][C]0.886367[/C][C]0.227265[/C][C]0.113633[/C][/ROW]
[ROW][C]249[/C][C]0.862002[/C][C]0.275996[/C][C]0.137998[/C][/ROW]
[ROW][C]250[/C][C]0.842406[/C][C]0.315187[/C][C]0.157594[/C][/ROW]
[ROW][C]251[/C][C]0.813838[/C][C]0.372324[/C][C]0.186162[/C][/ROW]
[ROW][C]252[/C][C]0.927744[/C][C]0.144512[/C][C]0.0722561[/C][/ROW]
[ROW][C]253[/C][C]0.910011[/C][C]0.179978[/C][C]0.0899892[/C][/ROW]
[ROW][C]254[/C][C]0.907698[/C][C]0.184603[/C][C]0.0923016[/C][/ROW]
[ROW][C]255[/C][C]0.878069[/C][C]0.243862[/C][C]0.121931[/C][/ROW]
[ROW][C]256[/C][C]0.889575[/C][C]0.22085[/C][C]0.110425[/C][/ROW]
[ROW][C]257[/C][C]0.864736[/C][C]0.270528[/C][C]0.135264[/C][/ROW]
[ROW][C]258[/C][C]0.835413[/C][C]0.329174[/C][C]0.164587[/C][/ROW]
[ROW][C]259[/C][C]0.788026[/C][C]0.423948[/C][C]0.211974[/C][/ROW]
[ROW][C]260[/C][C]0.757714[/C][C]0.484571[/C][C]0.242286[/C][/ROW]
[ROW][C]261[/C][C]0.704736[/C][C]0.590528[/C][C]0.295264[/C][/ROW]
[ROW][C]262[/C][C]0.692019[/C][C]0.615962[/C][C]0.307981[/C][/ROW]
[ROW][C]263[/C][C]0.639435[/C][C]0.721131[/C][C]0.360565[/C][/ROW]
[ROW][C]264[/C][C]0.570286[/C][C]0.859428[/C][C]0.429714[/C][/ROW]
[ROW][C]265[/C][C]0.562472[/C][C]0.875056[/C][C]0.437528[/C][/ROW]
[ROW][C]266[/C][C]0.991491[/C][C]0.0170174[/C][C]0.00850871[/C][/ROW]
[ROW][C]267[/C][C]0.991565[/C][C]0.0168706[/C][C]0.00843532[/C][/ROW]
[ROW][C]268[/C][C]0.996036[/C][C]0.00792732[/C][C]0.00396366[/C][/ROW]
[ROW][C]269[/C][C]0.996184[/C][C]0.00763192[/C][C]0.00381596[/C][/ROW]
[ROW][C]270[/C][C]0.998772[/C][C]0.00245677[/C][C]0.00122839[/C][/ROW]
[ROW][C]271[/C][C]0.999533[/C][C]0.000933782[/C][C]0.000466891[/C][/ROW]
[ROW][C]272[/C][C]0.998092[/C][C]0.00381521[/C][C]0.00190761[/C][/ROW]
[ROW][C]273[/C][C]0.997106[/C][C]0.00578786[/C][C]0.00289393[/C][/ROW]
[ROW][C]274[/C][C]0.997414[/C][C]0.00517261[/C][C]0.00258631[/C][/ROW]
[ROW][C]275[/C][C]0.977305[/C][C]0.0453895[/C][C]0.0226947[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269831&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269831&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.9503430.09931410.049657
130.9126940.1746130.0873063
140.8915260.2169480.108474
150.8317290.3365410.168271
160.7548520.4902960.245148
170.6651220.6697550.334878
180.5722830.8554350.427717
190.4849030.9698060.515097
200.4983880.9967770.501612
210.4361160.8722320.563884
220.4830550.966110.516945
230.422810.845620.57719
240.3642070.7284130.635793
250.2993280.5986560.700672
260.2689050.537810.731095
270.2267230.4534460.773277
280.1779520.3559030.822048
290.1704930.3409870.829507
300.1319280.2638570.868072
310.128110.256220.87189
320.1117460.2234930.888254
330.1153540.2307090.884646
340.1301360.2602720.869864
350.1082670.2165340.891733
360.1370160.2740310.862984
370.1241620.2483240.875838
380.1003340.2006680.899666
390.07876520.157530.921235
400.06177130.1235430.938229
410.08354150.1670830.916459
420.08386330.1677270.916137
430.1455450.2910890.854455
440.1235070.2470130.876493
450.1122790.2245580.887721
460.09453170.1890630.905468
470.07697840.1539570.923022
480.06328620.1265720.936714
490.05546260.1109250.944537
500.0970760.1941520.902924
510.1359780.2719570.864022
520.1200730.2401460.879927
530.09882270.1976450.901177
540.1150260.2300530.884974
550.1044510.2089020.895549
560.09245810.1849160.907542
570.1048320.2096640.895168
580.09272290.1854460.907277
590.2023250.404650.797675
600.2523350.5046710.747665
610.2247210.4494420.775279
620.2165320.4330640.783468
630.2205350.4410690.779465
640.2144030.4288060.785597
650.205780.411560.79422
660.234090.468180.76591
670.2296310.4592620.770369
680.2069230.4138460.793077
690.198320.3966390.80168
700.1789980.3579960.821002
710.1789660.3579330.821034
720.1551070.3102130.844893
730.1402760.2805520.859724
740.1263310.2526630.873669
750.116370.2327410.88363
760.1147580.2295160.885242
770.1973940.3947880.802606
780.1856160.3712320.814384
790.1702370.3404740.829763
800.1505120.3010250.849488
810.1547060.3094120.845294
820.1381930.2763860.861807
830.1508160.3016320.849184
840.1312820.2625630.868718
850.1329560.2659130.867044
860.115490.230980.88451
870.2299850.459970.770015
880.2247420.4494840.775258
890.2008330.4016650.799167
900.1759170.3518340.824083
910.1579640.3159280.842036
920.151430.302860.84857
930.1489120.2978250.851088
940.1511950.3023890.848805
950.2770090.5540190.722991
960.2800950.5601910.719905
970.2879270.5758540.712073
980.3276770.6553550.672323
990.3243840.6487680.675616
1000.4406520.8813050.559348
1010.4282410.8564810.571759
1020.4656740.9313470.534326
1030.5320740.9358510.467926
1040.5056440.9887130.494356
1050.4918420.9836850.508158
1060.5035730.9928540.496427
1070.5287090.9425820.471291
1080.5503060.8993880.449694
1090.5819750.8360490.418025
1100.5860890.8278220.413911
1110.78950.4209990.2105
1120.8221670.3556670.177833
1130.832060.335880.16794
1140.832240.3355210.16776
1150.8273650.3452710.172635
1160.8582120.2835760.141788
1170.8547060.2905870.145294
1180.9226870.1546270.0773134
1190.9510690.0978630.0489315
1200.9433680.1132640.0566322
1210.9587090.08258110.0412905
1220.9611030.07779430.0388972
1230.9716780.0566430.0283215
1240.9738470.05230570.0261528
1250.9830790.03384160.0169208
1260.9834030.03319410.0165971
1270.9942280.01154470.00577235
1280.99470.01059930.00529967
1290.9934490.01310110.00655056
1300.9932210.01355860.00677932
1310.9922060.01558830.00779413
1320.9914630.01707340.00853668
1330.9913840.01723190.00861597
1340.9922080.01558380.00779188
1350.9910910.01781720.00890861
1360.9923610.01527840.00763918
1370.9912110.0175780.008789
1380.9893610.02127790.010639
1390.9867920.02641530.0132076
1400.9915570.01688690.00844343
1410.9904540.01909270.00954634
1420.9895530.02089460.0104473
1430.986980.02604090.0130205
1440.984850.03030020.0151501
1450.9936910.01261880.00630938
1460.9933150.01337060.00668531
1470.9936280.01274380.00637188
1480.9934160.01316790.00658393
1490.9923040.0153920.00769598
1500.9925550.01488990.00744496
1510.9909910.01801760.00900882
1520.9897680.02046320.0102316
1530.9879890.02402270.0120113
1540.9857810.02843730.0142187
1550.984640.03071970.0153598
1560.9951990.009602750.00480138
1570.9948260.01034710.00517355
1580.9950430.009913650.00495682
1590.9937870.0124260.00621298
1600.9935870.01282640.0064132
1610.9921780.01564340.00782169
1620.9918880.01622430.00811215
1630.9908630.01827450.00913724
1640.9912430.0175140.00875698
1650.9895260.02094880.0104744
1660.9925910.01481780.00740891
1670.9906970.01860580.0093029
1680.990650.01870060.0093503
1690.9997160.0005682980.000284149
1700.9997460.0005083710.000254186
1710.9996520.0006953240.000347662
1720.9995910.0008178560.000408928
1730.9996950.0006108120.000305406
1740.9995760.0008474250.000423712
1750.9996450.0007101050.000355053
1760.9995220.0009564750.000478237
1770.9996550.0006908850.000345442
1780.9996340.0007325110.000366256
1790.9995170.0009658490.000482925
1800.9993780.001243430.000621714
1810.9994490.001101550.000550774
1820.9992490.00150130.000750652
1830.9992290.001541330.000770667
1840.9991940.001612430.000806214
1850.9991310.001737340.000868671
1860.9989940.002011430.00100572
1870.998940.002120480.00106024
1880.9987910.002418150.00120908
1890.9984220.003155310.00157766
1900.9991090.001782120.000891058
1910.9988250.002350210.00117511
1920.9991970.001606220.000803108
1930.9990680.001863930.000931964
1940.9988370.002326350.00116317
1950.9984060.003188760.00159438
1960.9980370.003926480.00196324
1970.9978080.004383650.00219183
1980.9978570.004285730.00214287
1990.9985380.002924590.0014623
2000.9980280.003943610.0019718
2010.9975630.004874360.00243718
2020.9973820.005235710.00261785
2030.9965570.006885310.00344265
2040.9967250.006549920.00327496
2050.9962170.007566130.00378306
2060.9958930.008213650.00410682
2070.9950810.009838160.00491908
2080.9940490.01190250.00595123
2090.9923640.01527130.00763565
2100.9900110.01997870.00998937
2110.9933230.01335480.00667739
2120.9923740.01525150.00762576
2130.9911210.0177570.00887851
2140.9882570.02348540.0117427
2150.985810.02837930.0141897
2160.9822050.03558990.0177949
2170.9785890.04282150.0214107
2180.9741590.0516820.025841
2190.9700350.05993050.0299652
2200.9660970.06780520.0339026
2210.9608370.07832590.039163
2220.9504480.09910370.0495518
2230.9439750.112050.056025
2240.9338190.1323620.0661808
2250.9240340.1519310.0759656
2260.9065530.1868940.0934469
2270.8923190.2153610.107681
2280.8897380.2205240.110262
2290.912220.175560.08778
2300.8919580.2160840.108042
2310.8965980.2068050.103402
2320.8841580.2316840.115842
2330.9272030.1455940.0727971
2340.9354990.1290010.0645005
2350.9373480.1253040.0626521
2360.9438160.1123670.0561835
2370.9533780.09324460.0466223
2380.9721750.055650.027825
2390.967590.064820.03241
2400.9572530.08549490.0427474
2410.9553140.08937130.0446857
2420.9435710.1128570.0564287
2430.9584890.08302120.0415106
2440.9531860.09362780.0468139
2450.9426460.1147080.0573542
2460.9322260.1355470.0677736
2470.9115620.1768750.0884375
2480.8863670.2272650.113633
2490.8620020.2759960.137998
2500.8424060.3151870.157594
2510.8138380.3723240.186162
2520.9277440.1445120.0722561
2530.9100110.1799780.0899892
2540.9076980.1846030.0923016
2550.8780690.2438620.121931
2560.8895750.220850.110425
2570.8647360.2705280.135264
2580.8354130.3291740.164587
2590.7880260.4239480.211974
2600.7577140.4845710.242286
2610.7047360.5905280.295264
2620.6920190.6159620.307981
2630.6394350.7211310.360565
2640.5702860.8594280.429714
2650.5624720.8750560.437528
2660.9914910.01701740.00850871
2670.9915650.01687060.00843532
2680.9960360.007927320.00396366
2690.9961840.007631920.00381596
2700.9987720.002456770.00122839
2710.9995330.0009337820.000466891
2720.9980920.003815210.00190761
2730.9971060.005787860.00289393
2740.9974140.005172610.00258631
2750.9773050.04538950.0226947







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level480.181818NOK
5% type I error level1030.390152NOK
10% type I error level1210.458333NOK

\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 & 48 & 0.181818 & NOK \tabularnewline
5% type I error level & 103 & 0.390152 & NOK \tabularnewline
10% type I error level & 121 & 0.458333 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269831&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]48[/C][C]0.181818[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]103[/C][C]0.390152[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]121[/C][C]0.458333[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269831&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269831&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level480.181818NOK
5% type I error level1030.390152NOK
10% type I error level1210.458333NOK



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