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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 15 Dec 2014 12:34:11 +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/15/t1418646887ubyrax6rausrfha.htm/, Retrieved Thu, 16 May 2024 23:34:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268251, Retrieved Thu, 16 May 2024 23:34:12 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-15 12:34:11] [4bf1efda48b6e8e35beb7b429a900cbb] [Current]
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Dataset

Dataseries X:
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12,9	0	26	50	21	86	96	149	2,1	7,5
7,4	0	51	68	26	62	75	152	1,5	2,5
12,2	1	57	62	22	70	70	139	2,0	6,0
12,8	0	37	54	22	71	88	148	2,0	6,5
7,4	1	67	71	18	108	114	158	2,1	1,0
6,7	1	43	54	23	64	69	128	2,0	1,0
12,6	1	52	65	12	119	176	224	2,3	5,5
14,8	0	52	73	20	97	114	159	2,1	8,5
13,3	1	43	52	22	129	121	105	2,1	6,5
11,1	1	84	84	21	153	110	159	2,2	4,5
8,2	1	67	42	19	78	158	167	2,1	2,0
11,4	1	49	66	22	80	116	165	2,1	5,0
6,4	1	70	65	15	99	181	159	2,1	0,5
10,6	1	52	78	20	68	77	119	2,0	5,0
12,0	0	58	73	19	147	141	176	2,3	5,0
6,3	0	68	75	18	40	35	54	1,8	2,5
11,3	0	62	72	15	57	80	91	2,0	5,0
11,9	1	43	66	20	120	152	163	2,2	5,5
9,3	0	56	70	21	71	97	124	2,0	3,5
9,6	1	56	61	21	84	99	137	2,1	3,0
10,0	0	74	81	15	68	84	121	2,0	4,0
6,4	1	65	71	16	55	68	153	1,8	0,5
13,8	1	63	69	23	137	101	148	2,2	6,5
10,8	0	58	71	21	79	107	221	2,2	4,5
13,8	1	57	72	18	116	88	188	1,7	7,5
11,7	1	63	68	25	101	112	149	2,1	5,5
10,9	1	53	70	9	111	171	244	2,3	4,0
16,1	1	57	68	30	189	137	148	2,7	7,5
13,4	0	51	61	20	66	77	92	1,9	7,0
9,9	1	64	67	23	81	66	150	2,0	4,0
11,5	0	53	76	16	63	93	153	2,0	5,5
8,3	0	29	70	16	69	105	94	1,9	2,5
11,7	0	54	60	19	71	131	156	2,0	5,5
6,1	1	51	77	25	70	89	146	2,0	0,5
9,0	1	58	72	25	64	102	132	2,0	3,5
9,7	1	43	69	18	143	161	161	2,1	2,5
10,8	1	51	71	23	85	120	105	2,0	4,5
10,3	1	53	62	21	86	127	97	1,8	4,5
10,4	0	54	70	10	55	77	151	2,0	4,5
12,7	1	56	64	14	69	108	131	2,2	6,0
9,3	1	61	58	22	120	85	166	2,2	2,5
11,8	0	47	76	26	96	168	157	2,1	5,0
5,9	1	39	52	23	60	48	111	1,8	0,0
11,4	1	48	59	23	95	152	145	1,9	5,0
13,0	1	50	68	24	100	75	162	2,1	6,5
10,8	1	35	76	24	68	107	163	2,0	5,0
12,3	1	30	65	18	57	62	59	1,9	6,0
11,3	0	68	67	23	105	121	187	2,2	4,5
11,8	1	49	59	15	85	124	109	2,0	5,5
7,9	1	61	69	19	103	72	90	2,0	1,0
12,7	0	67	76	16	57	40	105	1,7	7,5
12,3	1	47	63	25	51	58	83	2,0	6,0
11,6	1	56	75	23	69	97	116	2,2	5,0
6,7	1	50	63	17	41	88	42	1,7	1,0
10,9	1	43	60	19	49	126	148	2,0	5,0
12,1	1	67	73	21	50	104	155	2,2	6,5
13,3	1	62	63	18	93	148	125	2,0	7,0
10,1	1	57	70	27	58	146	116	1,9	4,5
5,7	0	41	75	21	54	80	128	2,0	0,0
14,3	1	54	66	13	74	97	138	2,0	8,5
8,0	0	45	63	8	15	25	49	1,6	3,5
13,3	1	48	63	29	69	99	96	2,1	7,5
9,3	1	61	64	28	107	118	164	2,1	3,5
12,5	0	56	70	23	65	58	162	2,0	6,0
7,6	0	41	75	21	58	63	99	1,9	1,5
15,9	1	43	61	19	107	139	202	2,2	9,0
9,2	0	53	60	19	70	50	186	2,1	3,5
9,1	1	44	62	20	53	60	66	1,8	3,5
11,1	0	66	73	18	136	152	183	2,3	4,0
13,0	1	58	61	19	126	142	214	2,3	6,5
14,5	1	46	66	17	95	94	188	2,2	7,5
12,2	0	37	64	19	69	66	104	2,1	6,0
12,3	0	51	59	25	136	127	177	2,2	5,0
11,4	0	51	64	19	58	67	126	1,9	5,5
8,8	0	56	60	22	59	90	76	1,8	3,5
14,6	1	66	56	23	118	75	99	2,1	7,5
7,3	1	45	66	26	110	96	157	1,8	1,0
12,6	0	37	78	14	82	128	139	2,0	6,5
13,0	0	42	67	16	102	146	162	2,1	6,5
12,6	1	38	59	24	65	69	108	2,1	6,5
13,2	0	66	66	20	90	186	159	2,1	7,0
9,9	0	34	68	12	64	81	74	1,8	3,5
7,7	1	53	71	24	83	85	110	2,0	1,5
10,5	0	49	66	22	70	54	96	2,1	4,0
13,4	0	55	73	12	50	46	116	1,9	7,5
10,9	0	49	72	22	77	106	87	2,1	4,5
4,3	1	59	71	20	37	34	97	1,0	0,0
10,3	0	40	59	10	81	60	127	2,2	3,5
11,8	1	58	64	23	101	95	106	2,1	5,5
11,2	1	60	66	17	79	57	80	1,9	5,0
11,4	0	63	78	22	71	62	74	2,0	4,5
8,6	0	56	68	24	60	36	91	1,9	2,5
13,2	0	54	73	18	55	56	133	2,0	7,5
12,6	1	52	62	21	44	54	74	1,8	7,0
5,6	1	34	65	20	40	64	114	2,0	0,0
9,9	1	69	68	20	56	76	140	2,0	4,5
8,8	0	32	65	22	43	98	95	2,0	3,0
7,7	1	48	60	19	45	88	98	1,8	1,5
9,0	0	67	71	20	32	35	121	2,0	3,5
7,3	1	58	65	26	56	102	126	1,1	2,5
11,4	1	57	68	23	40	61	98	1,8	5,5
13,6	1	42	64	24	34	80	95	1,8	8,0
7,9	1	64	74	21	89	49	110	2,0	1,0
10,7	1	58	69	21	50	78	70	1,9	5,0
10,3	0	66	76	19	56	90	102	2,1	4,5
8,3	1	26	68	8	46	45	86	1,6	3,0
9,6	1	61	72	17	76	55	130	2,2	3,0
14,2	1	52	67	20	64	96	96	1,9	8,0
8,5	0	51	63	11	74	43	102	2,0	2,5
13,5	0	55	59	8	57	52	100	2,1	7,0
4,9	0	50	73	15	45	60	94	1,3	0,0
6,4	0	60	66	18	30	54	52	1,8	1,0
9,6	0	56	62	18	62	51	98	1,9	3,5
11,6	0	63	69	19	51	51	118	2,1	5,5
11,1	1	61	66	19	36	38	99	1,8	5,5
4,35	1	52	51	23	34	41	48	0,75	0,5
12,7	1	16	56	22	61	146	50	1,5	7,5
18,1	1	46	67	21	70	182	150	3	9
17,85	1	56	69	25	69	192	154	2,25	9,5
16,6	0	52	57	30	145	263	109	3	8,5
12,6	1	55	56	17	23	35	68	1,5	7
17,1	1	50	55	27	120	439	194	3	8
19,1	0	59	63	23	147	214	158	3	10
16,1	1	60	67	23	215	341	159	3	7
13,35	0	52	65	18	24	58	67	0,75	8,5
18,4	0	44	47	18	84	292	147	3	9
14,7	1	67	76	23	30	85	39	2,25	9,5
10,6	1	52	64	19	77	200	100	1,5	4
12,6	1	55	68	15	46	158	111	1,5	6
16,2	1	37	64	20	61	199	138	2,25	8
13,6	1	54	65	16	178	297	101	3	5,5
18,9	1	72	71	24	160	227	131	3	9,5
14,1	1	51	63	25	57	108	101	1,5	7,5
14,5	1	48	60	25	42	86	114	2,25	7
16,15	0	60	68	19	163	302	165	2,25	7,5
14,75	1	50	72	19	75	148	114	1,5	8
14,8	1	63	70	16	94	178	111	2,25	7
12,45	1	33	61	19	45	120	75	1,5	7
12,65	1	67	61	19	78	207	82	2,25	6
17,35	1	46	62	23	47	157	121	2,25	10
8,6	1	54	71	21	29	128	32	3	2,5
18,4	0	59	71	22	97	296	150	3	9
16,1	1	61	51	19	116	323	117	3	8
11,6	1	33	56	20	32	79	71	1,5	6
17,75	1	47	70	20	50	70	165	3	8,5
15,25	1	69	73	3	118	146	154	3	6
17,65	1	52	76	23	66	246	126	2,25	9
15,6	0	55	59	14	48	145	138	1,5	8
16,35	0	55	68	23	86	196	149	2,25	8
17,65	0	41	48	20	89	199	145	2,25	9
13,6	1	73	52	15	76	127	120	3	5,5
11,7	0	51	59	13	39	91	138	0,75	5
14,35	0	52	60	16	75	153	109	2,25	7
14,75	0	50	59	7	57	299	132	3	5,5
18,25	1	51	57	24	72	228	172	3	9
9,9	0	60	79	17	60	190	169	1,5	2
16	1	56	60	24	109	180	114	2,25	8,5
18,25	1	56	60	24	76	212	156	3	9
16,85	0	29	59	19	65	269	172	2,25	8,5
14,6	1	66	62	25	40	130	68	1,5	9
13,85	1	66	59	20	58	179	89	2,25	7,5
18,95	1	73	61	28	123	243	167	2,25	10
15,6	0	55	71	23	71	190	113	1,5	9
14,85	0	64	57	27	102	299	115	2,25	7,5
11,75	0	40	66	18	80	121	78	1,5	6
18,45	0	46	63	28	97	137	118	2,25	10,5
15,9	1	58	69	21	46	305	87	3	8,5
17,1	0	43	58	19	93	157	173	3	8
16,1	1	61	59	23	19	96	2	3	10
19,9	0	51	48	27	140	183	162	3	10,5
10,95	1	50	66	22	78	52	49	1,5	6,5
18,45	0	52	73	28	98	238	122	2,25	9,5
15,1	1	54	67	25	40	40	96	1,5	8,5
15	0	66	61	21	80	226	100	2,25	7,5
11,35	0	61	68	22	76	190	82	2,25	5
15,95	1	80	75	28	79	214	100	2,25	8
18,1	0	51	62	20	87	145	115	3	10
14,6	1	56	69	29	95	119	141	1,5	7
15,4	1	56	58	25	49	222	165	2,25	7,5
15,4	1	56	60	25	49	222	165	2,25	7,5
17,6	1	53	74	20	80	159	110	3	9,5
13,35	1	47	55	20	86	165	118	2,25	6
19,1	0	25	62	16	69	249	158	3	10
15,35	1	47	63	20	79	125	146	2,25	7
7,6	0	46	69	20	52	122	49	1,5	3
13,4	0	50	58	23	120	186	90	3	6
13,9	0	39	58	18	69	148	121	1,5	7
19,1	1	51	68	25	94	274	155	3	10
15,25	0	58	72	18	72	172	104	3	7
12,9	1	35	62	19	43	84	147	3	3,5
16,1	0	58	62	25	87	168	110	3	8
17,35	0	60	65	25	52	102	108	2,25	10
13,15	0	62	69	25	71	106	113	2,25	5,5
12,15	0	63	66	24	61	2	115	0,75	6
12,6	1	53	72	19	51	139	61	3	6,5
10,35	1	46	62	26	50	95	60	0,75	6,5
15,4	1	67	75	10	67	130	109	1,5	8,5
9,6	1	59	58	17	30	72	68	1,5	4
18,2	0	64	66	13	70	141	111	3	9,5
13,6	0	38	55	17	52	113	77	1,5	8
14,85	1	50	47	30	75	206	73	2,25	8,5
14,75	0	48	72	25	87	268	151	3	5,5
14,1	0	48	62	4	69	175	89	3	7
14,9	0	47	64	16	72	77	78	1,5	9
16,25	0	66	64	21	79	125	110	3	8
19,25	1	47	19	23	121	255	220	3	10
13,6	1	63	50	22	43	111	65	1,5	8
13,6	0	58	68	17	58	132	141	1,5	6
15,65	0	44	70	20	57	211	117	2,25	8
12,75	1	51	79	20	50	92	122	1,5	5
14,6	0	43	69	22	69	76	63	1,5	9
9,85	1	55	71	16	64	171	44	2,25	4,5
12,65	1	38	48	23	38	83	52	1,5	8,5
11,9	1	56	66	16	53	119	62	2,25	7
19,2	0	45	73	0	90	266	131	3	9,5
16,6	1	50	74	18	96	186	101	3	8,5
11,2	1	54	66	25	49	50	42	0,75	7,5
15,25	1	57	71	23	56	117	152	1,5	7,5
11,9	0	60	74	12	102	219	107	1,5	5
13,2	0	55	78	18	40	246	77	2,25	7
16,35	0	56	75	24	100	279	154	2,25	8
12,4	1	49	53	11	67	148	103	1,5	5,5
15,85	1	37	60	18	78	137	96	2,25	8,5
14,35	0	43	50	14	62	130	154	0,75	7,5
18,15	1	59	70	23	55	181	175	2,25	9,5
11,15	1	46	69	24	59	98	57	0,75	7
15,65	0	51	65	29	96	226	112	2,25	8
17,75	0	58	78	18	86	234	143	3	8,5
7,65	0	64	78	15	38	138	49	0,75	3,5
12,35	1	53	59	29	43	85	110	0,75	6,5
15,6	1	48	72	16	23	66	131	3	6,5
19,3	0	51	70	19	77	236	167	3	10,5
15,2	0	47	63	22	48	106	56	3	8,5
17,1	0	59	63	16	26	135	137	3	8
15,6	1	62	71	23	91	122	86	1,5	10
18,4	1	62	74	23	94	218	121	3	10
19,05	0	51	67	19	62	199	149	3	9,5
18,55	0	64	66	4	74	112	168	3	9
19,1	0	52	62	20	114	278	140	3	10
13,1	1	67	80	24	52	94	88	1,5	7,5
12,85	1	50	73	20	64	113	168	2,25	4,5
9,5	1	54	67	4	31	84	94	0,75	4,5
4,5	1	58	61	24	38	86	51	0,75	0,5
11,85	0	56	73	22	27	62	48	2,25	6,5
13,6	1	63	74	16	105	222	145	3	4,5
11,7	1	31	32	3	64	167	66	2,25	5,5
12,4	1	65	69	15	62	82	85	3	5
13,35	0	71	69	24	65	207	109	2,25	6
11,4	0	50	84	17	58	184	63	3	4
14,9	1	57	64	20	76	83	102	1,5	8
19,9	0	47	58	27	140	183	162	3	10,5
17,75	1	54	60	23	48	85	128	3	8,5
11,2	1	47	59	26	68	89	86	0,75	6,5
14,6	1	57	78	23	80	225	114	1,5	8
17,6	0	43	57	17	71	237	164	3	8,5
14,05	1	41	60	20	76	102	119	3	5,5
16,1	0	63	68	22	63	221	126	3	7
13,35	1	63	68	19	46	128	132	2,25	5
11,85	1	56	73	24	53	91	142	2,25	3,5
11,95	0	51	69	19	74	198	83	3	5
14,75	1	50	67	23	70	204	94	1,5	9
15,15	0	22	60	15	78	158	81	2,25	8,5
13,2	1	41	65	27	56	138	166	2,25	5
16,85	0	59	66	26	100	226	110	2,25	9,5
7,85	1	56	74	22	51	44	64	0,75	3
7,7	0	66	81	22	52	196	93	2,25	1,5
12,6	0	53	72	18	102	83	104	1,5	6
7,85	1	42	55	15	78	79	105	2,25	0,5
10,95	1	52	49	22	78	52	49	1,5	6,5
12,35	0	54	74	27	55	105	88	0,75	7,5
9,95	1	44	53	10	98	116	95	1,5	4,5
14,9	1	62	64	20	76	83	102	1,5	8
16,65	0	53	65	17	73	196	99	2,25	9
13,4	1	50	57	23	47	153	63	1,5	7,5
13,95	0	36	51	19	45	157	76	1,5	8,5
15,7	0	76	80	13	83	75	109	3	7
16,85	1	66	67	27	60	106	117	2,25	9,5
10,95	1	62	70	23	48	58	57	1,5	6,5
15,35	0	59	74	16	50	75	120	0,75	9,5
12,2	1	47	75	25	56	74	73	2,25	6
15,1	0	55	70	2	77	185	91	3	8
17,75	0	58	69	26	91	265	108	3	9,5
15,2	1	60	65	20	76	131	105	1,5	8
14,6	0	44	55	23	68	139	117	1,5	8
16,65	0	57	71	22	74	196	119	2,25	9
8,1	1	45	65	24	29	78	31	0,75	5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 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 & 11 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268251&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]11 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=268251&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268251&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 2.00305 -0.0155933geslacht[t] + 0.00152577IM[t] + 0.00233734EM[t] -0.00805721Numeracy_tot[t] -0.00111757uren_rfc[t] + 0.00417441blogs[t] + 0.0102954zinvolle_teksten[t] + 1.1329PE[t] + 1.10924ruwe_examenscore[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  2.00305 -0.0155933geslacht[t] +  0.00152577IM[t] +  0.00233734EM[t] -0.00805721Numeracy_tot[t] -0.00111757uren_rfc[t] +  0.00417441blogs[t] +  0.0102954zinvolle_teksten[t] +  1.1329PE[t] +  1.10924ruwe_examenscore[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268251&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  2.00305 -0.0155933geslacht[t] +  0.00152577IM[t] +  0.00233734EM[t] -0.00805721Numeracy_tot[t] -0.00111757uren_rfc[t] +  0.00417441blogs[t] +  0.0102954zinvolle_teksten[t] +  1.1329PE[t] +  1.10924ruwe_examenscore[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268251&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268251&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 2.00305 -0.0155933geslacht[t] + 0.00152577IM[t] + 0.00233734EM[t] -0.00805721Numeracy_tot[t] -0.00111757uren_rfc[t] + 0.00417441blogs[t] + 0.0102954zinvolle_teksten[t] + 1.1329PE[t] + 1.10924ruwe_examenscore[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.003050.4426474.5258.97729e-064.48865e-06
geslacht-0.01559330.0884214-0.17640.8601460.430073
IM0.001525770.00449330.33960.7344420.367221
EM0.002337340.005670230.41220.6805040.340252
Numeracy_tot-0.008057210.00855612-0.94170.3471750.173588
uren_rfc-0.001117570.001777-0.62890.5299280.264964
blogs0.004174410.0008040345.1924.04539e-072.0227e-07
zinvolle_teksten0.01029540.001247468.2536.41422e-153.20711e-15
PE1.13290.086098113.165.03933e-312.51966e-31
ruwe_examenscore1.109240.018865158.83.93835e-1581.96918e-158

\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) & 2.00305 & 0.442647 & 4.525 & 8.97729e-06 & 4.48865e-06 \tabularnewline
geslacht & -0.0155933 & 0.0884214 & -0.1764 & 0.860146 & 0.430073 \tabularnewline
IM & 0.00152577 & 0.0044933 & 0.3396 & 0.734442 & 0.367221 \tabularnewline
EM & 0.00233734 & 0.00567023 & 0.4122 & 0.680504 & 0.340252 \tabularnewline
Numeracy_tot & -0.00805721 & 0.00855612 & -0.9417 & 0.347175 & 0.173588 \tabularnewline
uren_rfc & -0.00111757 & 0.001777 & -0.6289 & 0.529928 & 0.264964 \tabularnewline
blogs & 0.00417441 & 0.000804034 & 5.192 & 4.04539e-07 & 2.0227e-07 \tabularnewline
zinvolle_teksten & 0.0102954 & 0.00124746 & 8.253 & 6.41422e-15 & 3.20711e-15 \tabularnewline
PE & 1.1329 & 0.0860981 & 13.16 & 5.03933e-31 & 2.51966e-31 \tabularnewline
ruwe_examenscore & 1.10924 & 0.0188651 & 58.8 & 3.93835e-158 & 1.96918e-158 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268251&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]2.00305[/C][C]0.442647[/C][C]4.525[/C][C]8.97729e-06[/C][C]4.48865e-06[/C][/ROW]
[ROW][C]geslacht[/C][C]-0.0155933[/C][C]0.0884214[/C][C]-0.1764[/C][C]0.860146[/C][C]0.430073[/C][/ROW]
[ROW][C]IM[/C][C]0.00152577[/C][C]0.0044933[/C][C]0.3396[/C][C]0.734442[/C][C]0.367221[/C][/ROW]
[ROW][C]EM[/C][C]0.00233734[/C][C]0.00567023[/C][C]0.4122[/C][C]0.680504[/C][C]0.340252[/C][/ROW]
[ROW][C]Numeracy_tot[/C][C]-0.00805721[/C][C]0.00855612[/C][C]-0.9417[/C][C]0.347175[/C][C]0.173588[/C][/ROW]
[ROW][C]uren_rfc[/C][C]-0.00111757[/C][C]0.001777[/C][C]-0.6289[/C][C]0.529928[/C][C]0.264964[/C][/ROW]
[ROW][C]blogs[/C][C]0.00417441[/C][C]0.000804034[/C][C]5.192[/C][C]4.04539e-07[/C][C]2.0227e-07[/C][/ROW]
[ROW][C]zinvolle_teksten[/C][C]0.0102954[/C][C]0.00124746[/C][C]8.253[/C][C]6.41422e-15[/C][C]3.20711e-15[/C][/ROW]
[ROW][C]PE[/C][C]1.1329[/C][C]0.0860981[/C][C]13.16[/C][C]5.03933e-31[/C][C]2.51966e-31[/C][/ROW]
[ROW][C]ruwe_examenscore[/C][C]1.10924[/C][C]0.0188651[/C][C]58.8[/C][C]3.93835e-158[/C][C]1.96918e-158[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268251&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268251&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.003050.4426474.5258.97729e-064.48865e-06
geslacht-0.01559330.0884214-0.17640.8601460.430073
IM0.001525770.00449330.33960.7344420.367221
EM0.002337340.005670230.41220.6805040.340252
Numeracy_tot-0.008057210.00855612-0.94170.3471750.173588
uren_rfc-0.001117570.001777-0.62890.5299280.264964
blogs0.004174410.0008040345.1924.04539e-072.0227e-07
zinvolle_teksten0.01029540.001247468.2536.41422e-153.20711e-15
PE1.13290.086098113.165.03933e-312.51966e-31
ruwe_examenscore1.109240.018865158.83.93835e-1581.96918e-158






Multiple Linear Regression - Regression Statistics
Multiple R0.979126
R-squared0.958688
Adjusted R-squared0.957341
F-TEST (value)711.649
F-TEST (DF numerator)9
F-TEST (DF denominator)276
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.706632
Sum Squared Residuals137.815

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.979126 \tabularnewline
R-squared & 0.958688 \tabularnewline
Adjusted R-squared & 0.957341 \tabularnewline
F-TEST (value) & 711.649 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 276 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.706632 \tabularnewline
Sum Squared Residuals & 137.815 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268251&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.979126[/C][/ROW]
[ROW][C]R-squared[/C][C]0.958688[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.957341[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]711.649[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]276[/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]0.706632[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]137.815[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268251&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268251&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.979126
R-squared0.958688
Adjusted R-squared0.957341
F-TEST (value)711.649
F-TEST (DF numerator)9
F-TEST (DF denominator)276
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.706632
Sum Squared Residuals137.815






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.5274-1.6274
27.48.31146-0.911458
312.212.6083-0.408348
412.813.296-0.496026
57.47.5808-0.1808
66.76.90333-0.203332
712.613.7364-1.13639
814.815.9039-1.10393
913.313.02840.271565
1011.111.5519-0.451875
118.28.92406-0.724056
1211.412.0581-0.658074
136.47.34095-0.940946
1410.611.3705-0.770542
151212.4972-0.497245
166.37.60674-1.30674
1711.311.16420.135801
1811.912.8179-0.917927
199.39.83324-0.533241
209.69.482950.117055
211010.4076-0.407576
226.46.51511-0.115105
2313.813.55420.245806
2410.812.2059-1.40591
2513.814.5161-0.716141
2611.712.4097-0.709662
2710.912.3039-1.4039
2816.115.25420.845846
2913.413.17430.225685
309.910.4884-0.588445
3111.512.3923-0.892257
328.38.33657-0.0365723
3311.712.5128-0.812787
346.16.66067-0.560665
3599.9042-0.904204
369.79.391330.30867
3710.810.79020.00976996
3810.310.5075-0.207519
3910.411.2404-0.840425
4012.712.9799-0.279917
419.39.234070.0659297
4211.812.1786-0.378585
435.95.298520.601477
4411.411.7332-0.333155
451313.4876-0.487626
4610.811.8859-1.08593
4712.311.65060.649399
4811.311.875-0.575042
4911.811.9907-0.190704
507.96.57581.3242
5112.713.5835-0.883499
5212.311.96590.334148
5311.611.6235-0.0235265
546.75.863130.836869
5510.911.8471-0.947143
5612.113.7676-1.66758
5713.313.9155-0.615543
5810.110.9035-0.803487
595.75.92893-0.228931
6014.315.5567-1.25667
6188.44155-0.441547
6213.313.9972-0.697169
639.310.3274-1.02739
6412.512.8253-0.325347
657.67.105490.494509
6615.917.0584-1.15841
679.210.3779-1.17793
689.18.830640.269356
6911.111.5386-0.438553
701314.5363-1.53633
7114.515.1084-0.608358
7212.212.3596-0.159642
7312.312.25640.0436442
7411.411.8428-0.442772
758.89.06524-0.265239
7614.613.93260.667446
777.37.043550.256452
7812.613.4786-0.878604
791313.8473-0.847281
8012.612.9064-0.306395
8113.214.5535-1.35345
829.99.067190.832806
837.77.365120.334876
8410.510.00640.493592
8513.413.9631-0.563107
8610.910.69160.208362
874.34.31442-0.0144232
8810.39.963590.336415
8911.811.8951-0.0951294
9011.210.76830.431722
9111.410.30291.09708
928.67.999770.600227
9313.214.2377-1.03771
9412.612.7845-0.184495
955.65.69206-0.09206
969.911.0439-1.14393
978.88.95916-0.159159
987.77.076940.623064
9999.6143-0.614305
1007.37.6981-0.398104
10111.411.407-0.00696069
10213.614.1949-0.594891
1037.96.701491.19851
10410.710.7571-0.0571274
10510.310.8622-0.562207
1068.38.283810.0161922
1079.69.4150.184998
10814.214.4062-0.206238
1098.58.325320.174684
11013.513.48710.012928
1114.94.769820.130176
1126.45.979540.420455
1139.69.275780.324222
11411.611.958-0.358017
11511.111.3594-0.259372
1164.354.032310.317686
11712.713.0402-0.340189
11818.117.65270.447297
11917.8517.42940.420609
12016.616.8591-0.259141
12112.612.34980.250212
12217.117.9431-0.843123
12319.118.90180.198204
12416.116.03380.0661804
12513.3513.27260.0774413
12618.418.05530.344677
12714.715.8916-1.1916
12810.69.977970.62203
12912.612.21520.384833
13016.215.63860.561419
13113.613.6731-0.0730772
13218.918.12380.776177
13314.113.45670.643309
13414.513.79890.701072
13516.1515.7460.403996
13614.7514.35990.390136
13714.814.21270.587251
13812.4512.7141-0.2641
13912.6512.9048-0.254779
14017.3517.5072-0.157237
1418.69.06976-0.469765
14218.418.13510.264868
14316.116.7425-0.642505
14411.611.38730.212684
14517.7516.82390.92607
14615.2514.35640.893599
14717.6516.84160.808355
14815.614.65770.942272
14916.3515.73960.610397
15017.6516.77290.877108
15113.613.27970.320305
15211.710.26691.43306
15314.3514.08450.265532
15414.7514.20380.546208
15518.2518.02910.220925
1569.98.526111.37389
1571615.80060.199437
15818.2517.80770.442272
15916.8516.83070.0192595
16014.614.9122-0.312181
16113.8514.5319-0.681912
16218.9518.25350.696536
16315.615.6273-0.0272557
16414.8515.2028-0.352816
16511.7511.64680.103173
16618.4517.86920.580753
16715.917.0127-1.11273
16817.116.65630.443708
16916.116.9243-0.824285
17019.919.29650.603483
17110.9511.5845-0.634514
17218.4517.25421.19578
17315.114.26350.836484
1741514.8290.171017
17511.3511.7254-0.375442
17615.9515.31670.633284
17718.118.2477-0.14774
17814.613.30681.29323
17915.415.446-0.046042
18015.415.4507-0.0507167
18117.617.7234-0.123416
18213.3513.03860.311447
18319.119.1373-0.0372577
18415.3514.29561.05439
1857.68.05607-0.45607
18613.413.6526-0.252634
18713.913.30350.596455
18819.119.1484-0.0483781
18915.2514.98640.263577
19012.911.12971.77025
19116.116.04420.0558037
19217.3517.16610.183932
19313.1512.23380.916153
19412.1510.68931.46069
19512.613.8435-1.24353
19610.3511.0112-0.661197
19715.414.90230.497729
1989.69.179490.420512
19918.217.73980.460174
20013.613.8322-0.232196
20114.8515.4371-0.587099
20214.7514.11880.631224
20314.114.922-0.822037
20414.914.82190.0780777
20516.2515.92270.327253
20619.2519.6036-0.353575
20713.613.6809-0.080938
20813.612.40611.19386
20915.6515.51720.132762
21012.7510.91851.83148
21114.614.6239-0.0239093
2129.8510.7443-0.894301
21312.6513.9395-1.28954
21411.913.4878-1.58777
21519.218.53730.6627
21616.616.6279-0.0278856
21711.211.778-0.577997
21815.2514.06441.18559
21911.911.31820.581778
22013.214.2129-1.01288
22116.3516.13170.218259
22212.411.5010.899014
22315.8515.48970.360256
22414.3513.30061.04945
22518.1517.63840.511648
22611.1511.5699-0.41987
22715.6515.41130.23873
22817.7517.3090.44101
2297.657.93223-0.282233
23012.3511.47150.878455
23115.614.30731.29268
23219.319.7555-0.455524
23315.215.8374-0.637358
23417.116.3290.771032
23515.616.1474-0.547391
23618.418.6115-0.211488
23719.0518.31630.733732
23818.5517.7190.830965
23919.119.03170.0683263
24013.113.3422-0.242201
24112.8511.74361.10636
2429.59.319240.180763
2434.54.271050.228951
24411.8512.5637-0.713745
24513.612.82010.779889
24611.712.0403-0.340309
24712.412.22010.179937
24813.3513.19740.152606
24911.411.32620.0737606
25014.913.94780.952212
25119.919.31380.586213
25217.7516.4711.27902
25311.211.2282-0.0282295
25414.614.6682-0.0681808
25517.617.49060.109432
25614.0513.09460.955373
25716.115.39360.706423
25813.3512.02661.32344
25911.8510.26411.5859
26011.9512.6323-0.682296
26114.7515.4586-0.70863
26215.1515.4399-0.289853
26313.212.30210.897866
26416.8517.0888-0.238778
2657.857.031570.818425
2667.78.04625-0.346248
26712.611.76520.834846
2687.856.486511.36349
26910.9511.5478-0.597831
27012.3512.4927-0.142652
2719.9510.1416-0.191589
27214.913.95540.944583
27316.6516.38690.263124
27413.413.26510.134947
27513.9514.5395-0.5895
27615.714.70710.992863
27716.8516.6940.156013
27810.9511.7451-0.795053
27915.3515.01720.332808
28012.212.2354-0.0353745
28115.116.1302-1.03016
28217.7518.0962-0.346211
28315.214.1861.01404
28414.614.29550.304522
28516.6516.57150.078492
2868.19.02288-0.92288

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 14.5274 & -1.6274 \tabularnewline
2 & 7.4 & 8.31146 & -0.911458 \tabularnewline
3 & 12.2 & 12.6083 & -0.408348 \tabularnewline
4 & 12.8 & 13.296 & -0.496026 \tabularnewline
5 & 7.4 & 7.5808 & -0.1808 \tabularnewline
6 & 6.7 & 6.90333 & -0.203332 \tabularnewline
7 & 12.6 & 13.7364 & -1.13639 \tabularnewline
8 & 14.8 & 15.9039 & -1.10393 \tabularnewline
9 & 13.3 & 13.0284 & 0.271565 \tabularnewline
10 & 11.1 & 11.5519 & -0.451875 \tabularnewline
11 & 8.2 & 8.92406 & -0.724056 \tabularnewline
12 & 11.4 & 12.0581 & -0.658074 \tabularnewline
13 & 6.4 & 7.34095 & -0.940946 \tabularnewline
14 & 10.6 & 11.3705 & -0.770542 \tabularnewline
15 & 12 & 12.4972 & -0.497245 \tabularnewline
16 & 6.3 & 7.60674 & -1.30674 \tabularnewline
17 & 11.3 & 11.1642 & 0.135801 \tabularnewline
18 & 11.9 & 12.8179 & -0.917927 \tabularnewline
19 & 9.3 & 9.83324 & -0.533241 \tabularnewline
20 & 9.6 & 9.48295 & 0.117055 \tabularnewline
21 & 10 & 10.4076 & -0.407576 \tabularnewline
22 & 6.4 & 6.51511 & -0.115105 \tabularnewline
23 & 13.8 & 13.5542 & 0.245806 \tabularnewline
24 & 10.8 & 12.2059 & -1.40591 \tabularnewline
25 & 13.8 & 14.5161 & -0.716141 \tabularnewline
26 & 11.7 & 12.4097 & -0.709662 \tabularnewline
27 & 10.9 & 12.3039 & -1.4039 \tabularnewline
28 & 16.1 & 15.2542 & 0.845846 \tabularnewline
29 & 13.4 & 13.1743 & 0.225685 \tabularnewline
30 & 9.9 & 10.4884 & -0.588445 \tabularnewline
31 & 11.5 & 12.3923 & -0.892257 \tabularnewline
32 & 8.3 & 8.33657 & -0.0365723 \tabularnewline
33 & 11.7 & 12.5128 & -0.812787 \tabularnewline
34 & 6.1 & 6.66067 & -0.560665 \tabularnewline
35 & 9 & 9.9042 & -0.904204 \tabularnewline
36 & 9.7 & 9.39133 & 0.30867 \tabularnewline
37 & 10.8 & 10.7902 & 0.00976996 \tabularnewline
38 & 10.3 & 10.5075 & -0.207519 \tabularnewline
39 & 10.4 & 11.2404 & -0.840425 \tabularnewline
40 & 12.7 & 12.9799 & -0.279917 \tabularnewline
41 & 9.3 & 9.23407 & 0.0659297 \tabularnewline
42 & 11.8 & 12.1786 & -0.378585 \tabularnewline
43 & 5.9 & 5.29852 & 0.601477 \tabularnewline
44 & 11.4 & 11.7332 & -0.333155 \tabularnewline
45 & 13 & 13.4876 & -0.487626 \tabularnewline
46 & 10.8 & 11.8859 & -1.08593 \tabularnewline
47 & 12.3 & 11.6506 & 0.649399 \tabularnewline
48 & 11.3 & 11.875 & -0.575042 \tabularnewline
49 & 11.8 & 11.9907 & -0.190704 \tabularnewline
50 & 7.9 & 6.5758 & 1.3242 \tabularnewline
51 & 12.7 & 13.5835 & -0.883499 \tabularnewline
52 & 12.3 & 11.9659 & 0.334148 \tabularnewline
53 & 11.6 & 11.6235 & -0.0235265 \tabularnewline
54 & 6.7 & 5.86313 & 0.836869 \tabularnewline
55 & 10.9 & 11.8471 & -0.947143 \tabularnewline
56 & 12.1 & 13.7676 & -1.66758 \tabularnewline
57 & 13.3 & 13.9155 & -0.615543 \tabularnewline
58 & 10.1 & 10.9035 & -0.803487 \tabularnewline
59 & 5.7 & 5.92893 & -0.228931 \tabularnewline
60 & 14.3 & 15.5567 & -1.25667 \tabularnewline
61 & 8 & 8.44155 & -0.441547 \tabularnewline
62 & 13.3 & 13.9972 & -0.697169 \tabularnewline
63 & 9.3 & 10.3274 & -1.02739 \tabularnewline
64 & 12.5 & 12.8253 & -0.325347 \tabularnewline
65 & 7.6 & 7.10549 & 0.494509 \tabularnewline
66 & 15.9 & 17.0584 & -1.15841 \tabularnewline
67 & 9.2 & 10.3779 & -1.17793 \tabularnewline
68 & 9.1 & 8.83064 & 0.269356 \tabularnewline
69 & 11.1 & 11.5386 & -0.438553 \tabularnewline
70 & 13 & 14.5363 & -1.53633 \tabularnewline
71 & 14.5 & 15.1084 & -0.608358 \tabularnewline
72 & 12.2 & 12.3596 & -0.159642 \tabularnewline
73 & 12.3 & 12.2564 & 0.0436442 \tabularnewline
74 & 11.4 & 11.8428 & -0.442772 \tabularnewline
75 & 8.8 & 9.06524 & -0.265239 \tabularnewline
76 & 14.6 & 13.9326 & 0.667446 \tabularnewline
77 & 7.3 & 7.04355 & 0.256452 \tabularnewline
78 & 12.6 & 13.4786 & -0.878604 \tabularnewline
79 & 13 & 13.8473 & -0.847281 \tabularnewline
80 & 12.6 & 12.9064 & -0.306395 \tabularnewline
81 & 13.2 & 14.5535 & -1.35345 \tabularnewline
82 & 9.9 & 9.06719 & 0.832806 \tabularnewline
83 & 7.7 & 7.36512 & 0.334876 \tabularnewline
84 & 10.5 & 10.0064 & 0.493592 \tabularnewline
85 & 13.4 & 13.9631 & -0.563107 \tabularnewline
86 & 10.9 & 10.6916 & 0.208362 \tabularnewline
87 & 4.3 & 4.31442 & -0.0144232 \tabularnewline
88 & 10.3 & 9.96359 & 0.336415 \tabularnewline
89 & 11.8 & 11.8951 & -0.0951294 \tabularnewline
90 & 11.2 & 10.7683 & 0.431722 \tabularnewline
91 & 11.4 & 10.3029 & 1.09708 \tabularnewline
92 & 8.6 & 7.99977 & 0.600227 \tabularnewline
93 & 13.2 & 14.2377 & -1.03771 \tabularnewline
94 & 12.6 & 12.7845 & -0.184495 \tabularnewline
95 & 5.6 & 5.69206 & -0.09206 \tabularnewline
96 & 9.9 & 11.0439 & -1.14393 \tabularnewline
97 & 8.8 & 8.95916 & -0.159159 \tabularnewline
98 & 7.7 & 7.07694 & 0.623064 \tabularnewline
99 & 9 & 9.6143 & -0.614305 \tabularnewline
100 & 7.3 & 7.6981 & -0.398104 \tabularnewline
101 & 11.4 & 11.407 & -0.00696069 \tabularnewline
102 & 13.6 & 14.1949 & -0.594891 \tabularnewline
103 & 7.9 & 6.70149 & 1.19851 \tabularnewline
104 & 10.7 & 10.7571 & -0.0571274 \tabularnewline
105 & 10.3 & 10.8622 & -0.562207 \tabularnewline
106 & 8.3 & 8.28381 & 0.0161922 \tabularnewline
107 & 9.6 & 9.415 & 0.184998 \tabularnewline
108 & 14.2 & 14.4062 & -0.206238 \tabularnewline
109 & 8.5 & 8.32532 & 0.174684 \tabularnewline
110 & 13.5 & 13.4871 & 0.012928 \tabularnewline
111 & 4.9 & 4.76982 & 0.130176 \tabularnewline
112 & 6.4 & 5.97954 & 0.420455 \tabularnewline
113 & 9.6 & 9.27578 & 0.324222 \tabularnewline
114 & 11.6 & 11.958 & -0.358017 \tabularnewline
115 & 11.1 & 11.3594 & -0.259372 \tabularnewline
116 & 4.35 & 4.03231 & 0.317686 \tabularnewline
117 & 12.7 & 13.0402 & -0.340189 \tabularnewline
118 & 18.1 & 17.6527 & 0.447297 \tabularnewline
119 & 17.85 & 17.4294 & 0.420609 \tabularnewline
120 & 16.6 & 16.8591 & -0.259141 \tabularnewline
121 & 12.6 & 12.3498 & 0.250212 \tabularnewline
122 & 17.1 & 17.9431 & -0.843123 \tabularnewline
123 & 19.1 & 18.9018 & 0.198204 \tabularnewline
124 & 16.1 & 16.0338 & 0.0661804 \tabularnewline
125 & 13.35 & 13.2726 & 0.0774413 \tabularnewline
126 & 18.4 & 18.0553 & 0.344677 \tabularnewline
127 & 14.7 & 15.8916 & -1.1916 \tabularnewline
128 & 10.6 & 9.97797 & 0.62203 \tabularnewline
129 & 12.6 & 12.2152 & 0.384833 \tabularnewline
130 & 16.2 & 15.6386 & 0.561419 \tabularnewline
131 & 13.6 & 13.6731 & -0.0730772 \tabularnewline
132 & 18.9 & 18.1238 & 0.776177 \tabularnewline
133 & 14.1 & 13.4567 & 0.643309 \tabularnewline
134 & 14.5 & 13.7989 & 0.701072 \tabularnewline
135 & 16.15 & 15.746 & 0.403996 \tabularnewline
136 & 14.75 & 14.3599 & 0.390136 \tabularnewline
137 & 14.8 & 14.2127 & 0.587251 \tabularnewline
138 & 12.45 & 12.7141 & -0.2641 \tabularnewline
139 & 12.65 & 12.9048 & -0.254779 \tabularnewline
140 & 17.35 & 17.5072 & -0.157237 \tabularnewline
141 & 8.6 & 9.06976 & -0.469765 \tabularnewline
142 & 18.4 & 18.1351 & 0.264868 \tabularnewline
143 & 16.1 & 16.7425 & -0.642505 \tabularnewline
144 & 11.6 & 11.3873 & 0.212684 \tabularnewline
145 & 17.75 & 16.8239 & 0.92607 \tabularnewline
146 & 15.25 & 14.3564 & 0.893599 \tabularnewline
147 & 17.65 & 16.8416 & 0.808355 \tabularnewline
148 & 15.6 & 14.6577 & 0.942272 \tabularnewline
149 & 16.35 & 15.7396 & 0.610397 \tabularnewline
150 & 17.65 & 16.7729 & 0.877108 \tabularnewline
151 & 13.6 & 13.2797 & 0.320305 \tabularnewline
152 & 11.7 & 10.2669 & 1.43306 \tabularnewline
153 & 14.35 & 14.0845 & 0.265532 \tabularnewline
154 & 14.75 & 14.2038 & 0.546208 \tabularnewline
155 & 18.25 & 18.0291 & 0.220925 \tabularnewline
156 & 9.9 & 8.52611 & 1.37389 \tabularnewline
157 & 16 & 15.8006 & 0.199437 \tabularnewline
158 & 18.25 & 17.8077 & 0.442272 \tabularnewline
159 & 16.85 & 16.8307 & 0.0192595 \tabularnewline
160 & 14.6 & 14.9122 & -0.312181 \tabularnewline
161 & 13.85 & 14.5319 & -0.681912 \tabularnewline
162 & 18.95 & 18.2535 & 0.696536 \tabularnewline
163 & 15.6 & 15.6273 & -0.0272557 \tabularnewline
164 & 14.85 & 15.2028 & -0.352816 \tabularnewline
165 & 11.75 & 11.6468 & 0.103173 \tabularnewline
166 & 18.45 & 17.8692 & 0.580753 \tabularnewline
167 & 15.9 & 17.0127 & -1.11273 \tabularnewline
168 & 17.1 & 16.6563 & 0.443708 \tabularnewline
169 & 16.1 & 16.9243 & -0.824285 \tabularnewline
170 & 19.9 & 19.2965 & 0.603483 \tabularnewline
171 & 10.95 & 11.5845 & -0.634514 \tabularnewline
172 & 18.45 & 17.2542 & 1.19578 \tabularnewline
173 & 15.1 & 14.2635 & 0.836484 \tabularnewline
174 & 15 & 14.829 & 0.171017 \tabularnewline
175 & 11.35 & 11.7254 & -0.375442 \tabularnewline
176 & 15.95 & 15.3167 & 0.633284 \tabularnewline
177 & 18.1 & 18.2477 & -0.14774 \tabularnewline
178 & 14.6 & 13.3068 & 1.29323 \tabularnewline
179 & 15.4 & 15.446 & -0.046042 \tabularnewline
180 & 15.4 & 15.4507 & -0.0507167 \tabularnewline
181 & 17.6 & 17.7234 & -0.123416 \tabularnewline
182 & 13.35 & 13.0386 & 0.311447 \tabularnewline
183 & 19.1 & 19.1373 & -0.0372577 \tabularnewline
184 & 15.35 & 14.2956 & 1.05439 \tabularnewline
185 & 7.6 & 8.05607 & -0.45607 \tabularnewline
186 & 13.4 & 13.6526 & -0.252634 \tabularnewline
187 & 13.9 & 13.3035 & 0.596455 \tabularnewline
188 & 19.1 & 19.1484 & -0.0483781 \tabularnewline
189 & 15.25 & 14.9864 & 0.263577 \tabularnewline
190 & 12.9 & 11.1297 & 1.77025 \tabularnewline
191 & 16.1 & 16.0442 & 0.0558037 \tabularnewline
192 & 17.35 & 17.1661 & 0.183932 \tabularnewline
193 & 13.15 & 12.2338 & 0.916153 \tabularnewline
194 & 12.15 & 10.6893 & 1.46069 \tabularnewline
195 & 12.6 & 13.8435 & -1.24353 \tabularnewline
196 & 10.35 & 11.0112 & -0.661197 \tabularnewline
197 & 15.4 & 14.9023 & 0.497729 \tabularnewline
198 & 9.6 & 9.17949 & 0.420512 \tabularnewline
199 & 18.2 & 17.7398 & 0.460174 \tabularnewline
200 & 13.6 & 13.8322 & -0.232196 \tabularnewline
201 & 14.85 & 15.4371 & -0.587099 \tabularnewline
202 & 14.75 & 14.1188 & 0.631224 \tabularnewline
203 & 14.1 & 14.922 & -0.822037 \tabularnewline
204 & 14.9 & 14.8219 & 0.0780777 \tabularnewline
205 & 16.25 & 15.9227 & 0.327253 \tabularnewline
206 & 19.25 & 19.6036 & -0.353575 \tabularnewline
207 & 13.6 & 13.6809 & -0.080938 \tabularnewline
208 & 13.6 & 12.4061 & 1.19386 \tabularnewline
209 & 15.65 & 15.5172 & 0.132762 \tabularnewline
210 & 12.75 & 10.9185 & 1.83148 \tabularnewline
211 & 14.6 & 14.6239 & -0.0239093 \tabularnewline
212 & 9.85 & 10.7443 & -0.894301 \tabularnewline
213 & 12.65 & 13.9395 & -1.28954 \tabularnewline
214 & 11.9 & 13.4878 & -1.58777 \tabularnewline
215 & 19.2 & 18.5373 & 0.6627 \tabularnewline
216 & 16.6 & 16.6279 & -0.0278856 \tabularnewline
217 & 11.2 & 11.778 & -0.577997 \tabularnewline
218 & 15.25 & 14.0644 & 1.18559 \tabularnewline
219 & 11.9 & 11.3182 & 0.581778 \tabularnewline
220 & 13.2 & 14.2129 & -1.01288 \tabularnewline
221 & 16.35 & 16.1317 & 0.218259 \tabularnewline
222 & 12.4 & 11.501 & 0.899014 \tabularnewline
223 & 15.85 & 15.4897 & 0.360256 \tabularnewline
224 & 14.35 & 13.3006 & 1.04945 \tabularnewline
225 & 18.15 & 17.6384 & 0.511648 \tabularnewline
226 & 11.15 & 11.5699 & -0.41987 \tabularnewline
227 & 15.65 & 15.4113 & 0.23873 \tabularnewline
228 & 17.75 & 17.309 & 0.44101 \tabularnewline
229 & 7.65 & 7.93223 & -0.282233 \tabularnewline
230 & 12.35 & 11.4715 & 0.878455 \tabularnewline
231 & 15.6 & 14.3073 & 1.29268 \tabularnewline
232 & 19.3 & 19.7555 & -0.455524 \tabularnewline
233 & 15.2 & 15.8374 & -0.637358 \tabularnewline
234 & 17.1 & 16.329 & 0.771032 \tabularnewline
235 & 15.6 & 16.1474 & -0.547391 \tabularnewline
236 & 18.4 & 18.6115 & -0.211488 \tabularnewline
237 & 19.05 & 18.3163 & 0.733732 \tabularnewline
238 & 18.55 & 17.719 & 0.830965 \tabularnewline
239 & 19.1 & 19.0317 & 0.0683263 \tabularnewline
240 & 13.1 & 13.3422 & -0.242201 \tabularnewline
241 & 12.85 & 11.7436 & 1.10636 \tabularnewline
242 & 9.5 & 9.31924 & 0.180763 \tabularnewline
243 & 4.5 & 4.27105 & 0.228951 \tabularnewline
244 & 11.85 & 12.5637 & -0.713745 \tabularnewline
245 & 13.6 & 12.8201 & 0.779889 \tabularnewline
246 & 11.7 & 12.0403 & -0.340309 \tabularnewline
247 & 12.4 & 12.2201 & 0.179937 \tabularnewline
248 & 13.35 & 13.1974 & 0.152606 \tabularnewline
249 & 11.4 & 11.3262 & 0.0737606 \tabularnewline
250 & 14.9 & 13.9478 & 0.952212 \tabularnewline
251 & 19.9 & 19.3138 & 0.586213 \tabularnewline
252 & 17.75 & 16.471 & 1.27902 \tabularnewline
253 & 11.2 & 11.2282 & -0.0282295 \tabularnewline
254 & 14.6 & 14.6682 & -0.0681808 \tabularnewline
255 & 17.6 & 17.4906 & 0.109432 \tabularnewline
256 & 14.05 & 13.0946 & 0.955373 \tabularnewline
257 & 16.1 & 15.3936 & 0.706423 \tabularnewline
258 & 13.35 & 12.0266 & 1.32344 \tabularnewline
259 & 11.85 & 10.2641 & 1.5859 \tabularnewline
260 & 11.95 & 12.6323 & -0.682296 \tabularnewline
261 & 14.75 & 15.4586 & -0.70863 \tabularnewline
262 & 15.15 & 15.4399 & -0.289853 \tabularnewline
263 & 13.2 & 12.3021 & 0.897866 \tabularnewline
264 & 16.85 & 17.0888 & -0.238778 \tabularnewline
265 & 7.85 & 7.03157 & 0.818425 \tabularnewline
266 & 7.7 & 8.04625 & -0.346248 \tabularnewline
267 & 12.6 & 11.7652 & 0.834846 \tabularnewline
268 & 7.85 & 6.48651 & 1.36349 \tabularnewline
269 & 10.95 & 11.5478 & -0.597831 \tabularnewline
270 & 12.35 & 12.4927 & -0.142652 \tabularnewline
271 & 9.95 & 10.1416 & -0.191589 \tabularnewline
272 & 14.9 & 13.9554 & 0.944583 \tabularnewline
273 & 16.65 & 16.3869 & 0.263124 \tabularnewline
274 & 13.4 & 13.2651 & 0.134947 \tabularnewline
275 & 13.95 & 14.5395 & -0.5895 \tabularnewline
276 & 15.7 & 14.7071 & 0.992863 \tabularnewline
277 & 16.85 & 16.694 & 0.156013 \tabularnewline
278 & 10.95 & 11.7451 & -0.795053 \tabularnewline
279 & 15.35 & 15.0172 & 0.332808 \tabularnewline
280 & 12.2 & 12.2354 & -0.0353745 \tabularnewline
281 & 15.1 & 16.1302 & -1.03016 \tabularnewline
282 & 17.75 & 18.0962 & -0.346211 \tabularnewline
283 & 15.2 & 14.186 & 1.01404 \tabularnewline
284 & 14.6 & 14.2955 & 0.304522 \tabularnewline
285 & 16.65 & 16.5715 & 0.078492 \tabularnewline
286 & 8.1 & 9.02288 & -0.92288 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268251&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]14.5274[/C][C]-1.6274[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]8.31146[/C][C]-0.911458[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]12.6083[/C][C]-0.408348[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]13.296[/C][C]-0.496026[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]7.5808[/C][C]-0.1808[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]6.90333[/C][C]-0.203332[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]13.7364[/C][C]-1.13639[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]15.9039[/C][C]-1.10393[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]13.0284[/C][C]0.271565[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]11.5519[/C][C]-0.451875[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]8.92406[/C][C]-0.724056[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]12.0581[/C][C]-0.658074[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]7.34095[/C][C]-0.940946[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]11.3705[/C][C]-0.770542[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]12.4972[/C][C]-0.497245[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]7.60674[/C][C]-1.30674[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]11.1642[/C][C]0.135801[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]12.8179[/C][C]-0.917927[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]9.83324[/C][C]-0.533241[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]9.48295[/C][C]0.117055[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]10.4076[/C][C]-0.407576[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]6.51511[/C][C]-0.115105[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]13.5542[/C][C]0.245806[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]12.2059[/C][C]-1.40591[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]14.5161[/C][C]-0.716141[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]12.4097[/C][C]-0.709662[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]12.3039[/C][C]-1.4039[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]15.2542[/C][C]0.845846[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]13.1743[/C][C]0.225685[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]10.4884[/C][C]-0.588445[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]12.3923[/C][C]-0.892257[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]8.33657[/C][C]-0.0365723[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]12.5128[/C][C]-0.812787[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]6.66067[/C][C]-0.560665[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]9.9042[/C][C]-0.904204[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]9.39133[/C][C]0.30867[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]10.7902[/C][C]0.00976996[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]10.5075[/C][C]-0.207519[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]11.2404[/C][C]-0.840425[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]12.9799[/C][C]-0.279917[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]9.23407[/C][C]0.0659297[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]12.1786[/C][C]-0.378585[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]5.29852[/C][C]0.601477[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]11.7332[/C][C]-0.333155[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]13.4876[/C][C]-0.487626[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]11.8859[/C][C]-1.08593[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]11.6506[/C][C]0.649399[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]11.875[/C][C]-0.575042[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]11.9907[/C][C]-0.190704[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]6.5758[/C][C]1.3242[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]13.5835[/C][C]-0.883499[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]11.9659[/C][C]0.334148[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]11.6235[/C][C]-0.0235265[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]5.86313[/C][C]0.836869[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]11.8471[/C][C]-0.947143[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]13.7676[/C][C]-1.66758[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]13.9155[/C][C]-0.615543[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]10.9035[/C][C]-0.803487[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]5.92893[/C][C]-0.228931[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]15.5567[/C][C]-1.25667[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]8.44155[/C][C]-0.441547[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]13.9972[/C][C]-0.697169[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]10.3274[/C][C]-1.02739[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]12.8253[/C][C]-0.325347[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]7.10549[/C][C]0.494509[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]17.0584[/C][C]-1.15841[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]10.3779[/C][C]-1.17793[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]8.83064[/C][C]0.269356[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]11.5386[/C][C]-0.438553[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]14.5363[/C][C]-1.53633[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]15.1084[/C][C]-0.608358[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]12.3596[/C][C]-0.159642[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]12.2564[/C][C]0.0436442[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]11.8428[/C][C]-0.442772[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]9.06524[/C][C]-0.265239[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]13.9326[/C][C]0.667446[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]7.04355[/C][C]0.256452[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]13.4786[/C][C]-0.878604[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]13.8473[/C][C]-0.847281[/C][/ROW]
[ROW][C]80[/C][C]12.6[/C][C]12.9064[/C][C]-0.306395[/C][/ROW]
[ROW][C]81[/C][C]13.2[/C][C]14.5535[/C][C]-1.35345[/C][/ROW]
[ROW][C]82[/C][C]9.9[/C][C]9.06719[/C][C]0.832806[/C][/ROW]
[ROW][C]83[/C][C]7.7[/C][C]7.36512[/C][C]0.334876[/C][/ROW]
[ROW][C]84[/C][C]10.5[/C][C]10.0064[/C][C]0.493592[/C][/ROW]
[ROW][C]85[/C][C]13.4[/C][C]13.9631[/C][C]-0.563107[/C][/ROW]
[ROW][C]86[/C][C]10.9[/C][C]10.6916[/C][C]0.208362[/C][/ROW]
[ROW][C]87[/C][C]4.3[/C][C]4.31442[/C][C]-0.0144232[/C][/ROW]
[ROW][C]88[/C][C]10.3[/C][C]9.96359[/C][C]0.336415[/C][/ROW]
[ROW][C]89[/C][C]11.8[/C][C]11.8951[/C][C]-0.0951294[/C][/ROW]
[ROW][C]90[/C][C]11.2[/C][C]10.7683[/C][C]0.431722[/C][/ROW]
[ROW][C]91[/C][C]11.4[/C][C]10.3029[/C][C]1.09708[/C][/ROW]
[ROW][C]92[/C][C]8.6[/C][C]7.99977[/C][C]0.600227[/C][/ROW]
[ROW][C]93[/C][C]13.2[/C][C]14.2377[/C][C]-1.03771[/C][/ROW]
[ROW][C]94[/C][C]12.6[/C][C]12.7845[/C][C]-0.184495[/C][/ROW]
[ROW][C]95[/C][C]5.6[/C][C]5.69206[/C][C]-0.09206[/C][/ROW]
[ROW][C]96[/C][C]9.9[/C][C]11.0439[/C][C]-1.14393[/C][/ROW]
[ROW][C]97[/C][C]8.8[/C][C]8.95916[/C][C]-0.159159[/C][/ROW]
[ROW][C]98[/C][C]7.7[/C][C]7.07694[/C][C]0.623064[/C][/ROW]
[ROW][C]99[/C][C]9[/C][C]9.6143[/C][C]-0.614305[/C][/ROW]
[ROW][C]100[/C][C]7.3[/C][C]7.6981[/C][C]-0.398104[/C][/ROW]
[ROW][C]101[/C][C]11.4[/C][C]11.407[/C][C]-0.00696069[/C][/ROW]
[ROW][C]102[/C][C]13.6[/C][C]14.1949[/C][C]-0.594891[/C][/ROW]
[ROW][C]103[/C][C]7.9[/C][C]6.70149[/C][C]1.19851[/C][/ROW]
[ROW][C]104[/C][C]10.7[/C][C]10.7571[/C][C]-0.0571274[/C][/ROW]
[ROW][C]105[/C][C]10.3[/C][C]10.8622[/C][C]-0.562207[/C][/ROW]
[ROW][C]106[/C][C]8.3[/C][C]8.28381[/C][C]0.0161922[/C][/ROW]
[ROW][C]107[/C][C]9.6[/C][C]9.415[/C][C]0.184998[/C][/ROW]
[ROW][C]108[/C][C]14.2[/C][C]14.4062[/C][C]-0.206238[/C][/ROW]
[ROW][C]109[/C][C]8.5[/C][C]8.32532[/C][C]0.174684[/C][/ROW]
[ROW][C]110[/C][C]13.5[/C][C]13.4871[/C][C]0.012928[/C][/ROW]
[ROW][C]111[/C][C]4.9[/C][C]4.76982[/C][C]0.130176[/C][/ROW]
[ROW][C]112[/C][C]6.4[/C][C]5.97954[/C][C]0.420455[/C][/ROW]
[ROW][C]113[/C][C]9.6[/C][C]9.27578[/C][C]0.324222[/C][/ROW]
[ROW][C]114[/C][C]11.6[/C][C]11.958[/C][C]-0.358017[/C][/ROW]
[ROW][C]115[/C][C]11.1[/C][C]11.3594[/C][C]-0.259372[/C][/ROW]
[ROW][C]116[/C][C]4.35[/C][C]4.03231[/C][C]0.317686[/C][/ROW]
[ROW][C]117[/C][C]12.7[/C][C]13.0402[/C][C]-0.340189[/C][/ROW]
[ROW][C]118[/C][C]18.1[/C][C]17.6527[/C][C]0.447297[/C][/ROW]
[ROW][C]119[/C][C]17.85[/C][C]17.4294[/C][C]0.420609[/C][/ROW]
[ROW][C]120[/C][C]16.6[/C][C]16.8591[/C][C]-0.259141[/C][/ROW]
[ROW][C]121[/C][C]12.6[/C][C]12.3498[/C][C]0.250212[/C][/ROW]
[ROW][C]122[/C][C]17.1[/C][C]17.9431[/C][C]-0.843123[/C][/ROW]
[ROW][C]123[/C][C]19.1[/C][C]18.9018[/C][C]0.198204[/C][/ROW]
[ROW][C]124[/C][C]16.1[/C][C]16.0338[/C][C]0.0661804[/C][/ROW]
[ROW][C]125[/C][C]13.35[/C][C]13.2726[/C][C]0.0774413[/C][/ROW]
[ROW][C]126[/C][C]18.4[/C][C]18.0553[/C][C]0.344677[/C][/ROW]
[ROW][C]127[/C][C]14.7[/C][C]15.8916[/C][C]-1.1916[/C][/ROW]
[ROW][C]128[/C][C]10.6[/C][C]9.97797[/C][C]0.62203[/C][/ROW]
[ROW][C]129[/C][C]12.6[/C][C]12.2152[/C][C]0.384833[/C][/ROW]
[ROW][C]130[/C][C]16.2[/C][C]15.6386[/C][C]0.561419[/C][/ROW]
[ROW][C]131[/C][C]13.6[/C][C]13.6731[/C][C]-0.0730772[/C][/ROW]
[ROW][C]132[/C][C]18.9[/C][C]18.1238[/C][C]0.776177[/C][/ROW]
[ROW][C]133[/C][C]14.1[/C][C]13.4567[/C][C]0.643309[/C][/ROW]
[ROW][C]134[/C][C]14.5[/C][C]13.7989[/C][C]0.701072[/C][/ROW]
[ROW][C]135[/C][C]16.15[/C][C]15.746[/C][C]0.403996[/C][/ROW]
[ROW][C]136[/C][C]14.75[/C][C]14.3599[/C][C]0.390136[/C][/ROW]
[ROW][C]137[/C][C]14.8[/C][C]14.2127[/C][C]0.587251[/C][/ROW]
[ROW][C]138[/C][C]12.45[/C][C]12.7141[/C][C]-0.2641[/C][/ROW]
[ROW][C]139[/C][C]12.65[/C][C]12.9048[/C][C]-0.254779[/C][/ROW]
[ROW][C]140[/C][C]17.35[/C][C]17.5072[/C][C]-0.157237[/C][/ROW]
[ROW][C]141[/C][C]8.6[/C][C]9.06976[/C][C]-0.469765[/C][/ROW]
[ROW][C]142[/C][C]18.4[/C][C]18.1351[/C][C]0.264868[/C][/ROW]
[ROW][C]143[/C][C]16.1[/C][C]16.7425[/C][C]-0.642505[/C][/ROW]
[ROW][C]144[/C][C]11.6[/C][C]11.3873[/C][C]0.212684[/C][/ROW]
[ROW][C]145[/C][C]17.75[/C][C]16.8239[/C][C]0.92607[/C][/ROW]
[ROW][C]146[/C][C]15.25[/C][C]14.3564[/C][C]0.893599[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]16.8416[/C][C]0.808355[/C][/ROW]
[ROW][C]148[/C][C]15.6[/C][C]14.6577[/C][C]0.942272[/C][/ROW]
[ROW][C]149[/C][C]16.35[/C][C]15.7396[/C][C]0.610397[/C][/ROW]
[ROW][C]150[/C][C]17.65[/C][C]16.7729[/C][C]0.877108[/C][/ROW]
[ROW][C]151[/C][C]13.6[/C][C]13.2797[/C][C]0.320305[/C][/ROW]
[ROW][C]152[/C][C]11.7[/C][C]10.2669[/C][C]1.43306[/C][/ROW]
[ROW][C]153[/C][C]14.35[/C][C]14.0845[/C][C]0.265532[/C][/ROW]
[ROW][C]154[/C][C]14.75[/C][C]14.2038[/C][C]0.546208[/C][/ROW]
[ROW][C]155[/C][C]18.25[/C][C]18.0291[/C][C]0.220925[/C][/ROW]
[ROW][C]156[/C][C]9.9[/C][C]8.52611[/C][C]1.37389[/C][/ROW]
[ROW][C]157[/C][C]16[/C][C]15.8006[/C][C]0.199437[/C][/ROW]
[ROW][C]158[/C][C]18.25[/C][C]17.8077[/C][C]0.442272[/C][/ROW]
[ROW][C]159[/C][C]16.85[/C][C]16.8307[/C][C]0.0192595[/C][/ROW]
[ROW][C]160[/C][C]14.6[/C][C]14.9122[/C][C]-0.312181[/C][/ROW]
[ROW][C]161[/C][C]13.85[/C][C]14.5319[/C][C]-0.681912[/C][/ROW]
[ROW][C]162[/C][C]18.95[/C][C]18.2535[/C][C]0.696536[/C][/ROW]
[ROW][C]163[/C][C]15.6[/C][C]15.6273[/C][C]-0.0272557[/C][/ROW]
[ROW][C]164[/C][C]14.85[/C][C]15.2028[/C][C]-0.352816[/C][/ROW]
[ROW][C]165[/C][C]11.75[/C][C]11.6468[/C][C]0.103173[/C][/ROW]
[ROW][C]166[/C][C]18.45[/C][C]17.8692[/C][C]0.580753[/C][/ROW]
[ROW][C]167[/C][C]15.9[/C][C]17.0127[/C][C]-1.11273[/C][/ROW]
[ROW][C]168[/C][C]17.1[/C][C]16.6563[/C][C]0.443708[/C][/ROW]
[ROW][C]169[/C][C]16.1[/C][C]16.9243[/C][C]-0.824285[/C][/ROW]
[ROW][C]170[/C][C]19.9[/C][C]19.2965[/C][C]0.603483[/C][/ROW]
[ROW][C]171[/C][C]10.95[/C][C]11.5845[/C][C]-0.634514[/C][/ROW]
[ROW][C]172[/C][C]18.45[/C][C]17.2542[/C][C]1.19578[/C][/ROW]
[ROW][C]173[/C][C]15.1[/C][C]14.2635[/C][C]0.836484[/C][/ROW]
[ROW][C]174[/C][C]15[/C][C]14.829[/C][C]0.171017[/C][/ROW]
[ROW][C]175[/C][C]11.35[/C][C]11.7254[/C][C]-0.375442[/C][/ROW]
[ROW][C]176[/C][C]15.95[/C][C]15.3167[/C][C]0.633284[/C][/ROW]
[ROW][C]177[/C][C]18.1[/C][C]18.2477[/C][C]-0.14774[/C][/ROW]
[ROW][C]178[/C][C]14.6[/C][C]13.3068[/C][C]1.29323[/C][/ROW]
[ROW][C]179[/C][C]15.4[/C][C]15.446[/C][C]-0.046042[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]15.4507[/C][C]-0.0507167[/C][/ROW]
[ROW][C]181[/C][C]17.6[/C][C]17.7234[/C][C]-0.123416[/C][/ROW]
[ROW][C]182[/C][C]13.35[/C][C]13.0386[/C][C]0.311447[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]19.1373[/C][C]-0.0372577[/C][/ROW]
[ROW][C]184[/C][C]15.35[/C][C]14.2956[/C][C]1.05439[/C][/ROW]
[ROW][C]185[/C][C]7.6[/C][C]8.05607[/C][C]-0.45607[/C][/ROW]
[ROW][C]186[/C][C]13.4[/C][C]13.6526[/C][C]-0.252634[/C][/ROW]
[ROW][C]187[/C][C]13.9[/C][C]13.3035[/C][C]0.596455[/C][/ROW]
[ROW][C]188[/C][C]19.1[/C][C]19.1484[/C][C]-0.0483781[/C][/ROW]
[ROW][C]189[/C][C]15.25[/C][C]14.9864[/C][C]0.263577[/C][/ROW]
[ROW][C]190[/C][C]12.9[/C][C]11.1297[/C][C]1.77025[/C][/ROW]
[ROW][C]191[/C][C]16.1[/C][C]16.0442[/C][C]0.0558037[/C][/ROW]
[ROW][C]192[/C][C]17.35[/C][C]17.1661[/C][C]0.183932[/C][/ROW]
[ROW][C]193[/C][C]13.15[/C][C]12.2338[/C][C]0.916153[/C][/ROW]
[ROW][C]194[/C][C]12.15[/C][C]10.6893[/C][C]1.46069[/C][/ROW]
[ROW][C]195[/C][C]12.6[/C][C]13.8435[/C][C]-1.24353[/C][/ROW]
[ROW][C]196[/C][C]10.35[/C][C]11.0112[/C][C]-0.661197[/C][/ROW]
[ROW][C]197[/C][C]15.4[/C][C]14.9023[/C][C]0.497729[/C][/ROW]
[ROW][C]198[/C][C]9.6[/C][C]9.17949[/C][C]0.420512[/C][/ROW]
[ROW][C]199[/C][C]18.2[/C][C]17.7398[/C][C]0.460174[/C][/ROW]
[ROW][C]200[/C][C]13.6[/C][C]13.8322[/C][C]-0.232196[/C][/ROW]
[ROW][C]201[/C][C]14.85[/C][C]15.4371[/C][C]-0.587099[/C][/ROW]
[ROW][C]202[/C][C]14.75[/C][C]14.1188[/C][C]0.631224[/C][/ROW]
[ROW][C]203[/C][C]14.1[/C][C]14.922[/C][C]-0.822037[/C][/ROW]
[ROW][C]204[/C][C]14.9[/C][C]14.8219[/C][C]0.0780777[/C][/ROW]
[ROW][C]205[/C][C]16.25[/C][C]15.9227[/C][C]0.327253[/C][/ROW]
[ROW][C]206[/C][C]19.25[/C][C]19.6036[/C][C]-0.353575[/C][/ROW]
[ROW][C]207[/C][C]13.6[/C][C]13.6809[/C][C]-0.080938[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]12.4061[/C][C]1.19386[/C][/ROW]
[ROW][C]209[/C][C]15.65[/C][C]15.5172[/C][C]0.132762[/C][/ROW]
[ROW][C]210[/C][C]12.75[/C][C]10.9185[/C][C]1.83148[/C][/ROW]
[ROW][C]211[/C][C]14.6[/C][C]14.6239[/C][C]-0.0239093[/C][/ROW]
[ROW][C]212[/C][C]9.85[/C][C]10.7443[/C][C]-0.894301[/C][/ROW]
[ROW][C]213[/C][C]12.65[/C][C]13.9395[/C][C]-1.28954[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]13.4878[/C][C]-1.58777[/C][/ROW]
[ROW][C]215[/C][C]19.2[/C][C]18.5373[/C][C]0.6627[/C][/ROW]
[ROW][C]216[/C][C]16.6[/C][C]16.6279[/C][C]-0.0278856[/C][/ROW]
[ROW][C]217[/C][C]11.2[/C][C]11.778[/C][C]-0.577997[/C][/ROW]
[ROW][C]218[/C][C]15.25[/C][C]14.0644[/C][C]1.18559[/C][/ROW]
[ROW][C]219[/C][C]11.9[/C][C]11.3182[/C][C]0.581778[/C][/ROW]
[ROW][C]220[/C][C]13.2[/C][C]14.2129[/C][C]-1.01288[/C][/ROW]
[ROW][C]221[/C][C]16.35[/C][C]16.1317[/C][C]0.218259[/C][/ROW]
[ROW][C]222[/C][C]12.4[/C][C]11.501[/C][C]0.899014[/C][/ROW]
[ROW][C]223[/C][C]15.85[/C][C]15.4897[/C][C]0.360256[/C][/ROW]
[ROW][C]224[/C][C]14.35[/C][C]13.3006[/C][C]1.04945[/C][/ROW]
[ROW][C]225[/C][C]18.15[/C][C]17.6384[/C][C]0.511648[/C][/ROW]
[ROW][C]226[/C][C]11.15[/C][C]11.5699[/C][C]-0.41987[/C][/ROW]
[ROW][C]227[/C][C]15.65[/C][C]15.4113[/C][C]0.23873[/C][/ROW]
[ROW][C]228[/C][C]17.75[/C][C]17.309[/C][C]0.44101[/C][/ROW]
[ROW][C]229[/C][C]7.65[/C][C]7.93223[/C][C]-0.282233[/C][/ROW]
[ROW][C]230[/C][C]12.35[/C][C]11.4715[/C][C]0.878455[/C][/ROW]
[ROW][C]231[/C][C]15.6[/C][C]14.3073[/C][C]1.29268[/C][/ROW]
[ROW][C]232[/C][C]19.3[/C][C]19.7555[/C][C]-0.455524[/C][/ROW]
[ROW][C]233[/C][C]15.2[/C][C]15.8374[/C][C]-0.637358[/C][/ROW]
[ROW][C]234[/C][C]17.1[/C][C]16.329[/C][C]0.771032[/C][/ROW]
[ROW][C]235[/C][C]15.6[/C][C]16.1474[/C][C]-0.547391[/C][/ROW]
[ROW][C]236[/C][C]18.4[/C][C]18.6115[/C][C]-0.211488[/C][/ROW]
[ROW][C]237[/C][C]19.05[/C][C]18.3163[/C][C]0.733732[/C][/ROW]
[ROW][C]238[/C][C]18.55[/C][C]17.719[/C][C]0.830965[/C][/ROW]
[ROW][C]239[/C][C]19.1[/C][C]19.0317[/C][C]0.0683263[/C][/ROW]
[ROW][C]240[/C][C]13.1[/C][C]13.3422[/C][C]-0.242201[/C][/ROW]
[ROW][C]241[/C][C]12.85[/C][C]11.7436[/C][C]1.10636[/C][/ROW]
[ROW][C]242[/C][C]9.5[/C][C]9.31924[/C][C]0.180763[/C][/ROW]
[ROW][C]243[/C][C]4.5[/C][C]4.27105[/C][C]0.228951[/C][/ROW]
[ROW][C]244[/C][C]11.85[/C][C]12.5637[/C][C]-0.713745[/C][/ROW]
[ROW][C]245[/C][C]13.6[/C][C]12.8201[/C][C]0.779889[/C][/ROW]
[ROW][C]246[/C][C]11.7[/C][C]12.0403[/C][C]-0.340309[/C][/ROW]
[ROW][C]247[/C][C]12.4[/C][C]12.2201[/C][C]0.179937[/C][/ROW]
[ROW][C]248[/C][C]13.35[/C][C]13.1974[/C][C]0.152606[/C][/ROW]
[ROW][C]249[/C][C]11.4[/C][C]11.3262[/C][C]0.0737606[/C][/ROW]
[ROW][C]250[/C][C]14.9[/C][C]13.9478[/C][C]0.952212[/C][/ROW]
[ROW][C]251[/C][C]19.9[/C][C]19.3138[/C][C]0.586213[/C][/ROW]
[ROW][C]252[/C][C]17.75[/C][C]16.471[/C][C]1.27902[/C][/ROW]
[ROW][C]253[/C][C]11.2[/C][C]11.2282[/C][C]-0.0282295[/C][/ROW]
[ROW][C]254[/C][C]14.6[/C][C]14.6682[/C][C]-0.0681808[/C][/ROW]
[ROW][C]255[/C][C]17.6[/C][C]17.4906[/C][C]0.109432[/C][/ROW]
[ROW][C]256[/C][C]14.05[/C][C]13.0946[/C][C]0.955373[/C][/ROW]
[ROW][C]257[/C][C]16.1[/C][C]15.3936[/C][C]0.706423[/C][/ROW]
[ROW][C]258[/C][C]13.35[/C][C]12.0266[/C][C]1.32344[/C][/ROW]
[ROW][C]259[/C][C]11.85[/C][C]10.2641[/C][C]1.5859[/C][/ROW]
[ROW][C]260[/C][C]11.95[/C][C]12.6323[/C][C]-0.682296[/C][/ROW]
[ROW][C]261[/C][C]14.75[/C][C]15.4586[/C][C]-0.70863[/C][/ROW]
[ROW][C]262[/C][C]15.15[/C][C]15.4399[/C][C]-0.289853[/C][/ROW]
[ROW][C]263[/C][C]13.2[/C][C]12.3021[/C][C]0.897866[/C][/ROW]
[ROW][C]264[/C][C]16.85[/C][C]17.0888[/C][C]-0.238778[/C][/ROW]
[ROW][C]265[/C][C]7.85[/C][C]7.03157[/C][C]0.818425[/C][/ROW]
[ROW][C]266[/C][C]7.7[/C][C]8.04625[/C][C]-0.346248[/C][/ROW]
[ROW][C]267[/C][C]12.6[/C][C]11.7652[/C][C]0.834846[/C][/ROW]
[ROW][C]268[/C][C]7.85[/C][C]6.48651[/C][C]1.36349[/C][/ROW]
[ROW][C]269[/C][C]10.95[/C][C]11.5478[/C][C]-0.597831[/C][/ROW]
[ROW][C]270[/C][C]12.35[/C][C]12.4927[/C][C]-0.142652[/C][/ROW]
[ROW][C]271[/C][C]9.95[/C][C]10.1416[/C][C]-0.191589[/C][/ROW]
[ROW][C]272[/C][C]14.9[/C][C]13.9554[/C][C]0.944583[/C][/ROW]
[ROW][C]273[/C][C]16.65[/C][C]16.3869[/C][C]0.263124[/C][/ROW]
[ROW][C]274[/C][C]13.4[/C][C]13.2651[/C][C]0.134947[/C][/ROW]
[ROW][C]275[/C][C]13.95[/C][C]14.5395[/C][C]-0.5895[/C][/ROW]
[ROW][C]276[/C][C]15.7[/C][C]14.7071[/C][C]0.992863[/C][/ROW]
[ROW][C]277[/C][C]16.85[/C][C]16.694[/C][C]0.156013[/C][/ROW]
[ROW][C]278[/C][C]10.95[/C][C]11.7451[/C][C]-0.795053[/C][/ROW]
[ROW][C]279[/C][C]15.35[/C][C]15.0172[/C][C]0.332808[/C][/ROW]
[ROW][C]280[/C][C]12.2[/C][C]12.2354[/C][C]-0.0353745[/C][/ROW]
[ROW][C]281[/C][C]15.1[/C][C]16.1302[/C][C]-1.03016[/C][/ROW]
[ROW][C]282[/C][C]17.75[/C][C]18.0962[/C][C]-0.346211[/C][/ROW]
[ROW][C]283[/C][C]15.2[/C][C]14.186[/C][C]1.01404[/C][/ROW]
[ROW][C]284[/C][C]14.6[/C][C]14.2955[/C][C]0.304522[/C][/ROW]
[ROW][C]285[/C][C]16.65[/C][C]16.5715[/C][C]0.078492[/C][/ROW]
[ROW][C]286[/C][C]8.1[/C][C]9.02288[/C][C]-0.92288[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268251&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268251&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.5274-1.6274
27.48.31146-0.911458
312.212.6083-0.408348
412.813.296-0.496026
57.47.5808-0.1808
66.76.90333-0.203332
712.613.7364-1.13639
814.815.9039-1.10393
913.313.02840.271565
1011.111.5519-0.451875
118.28.92406-0.724056
1211.412.0581-0.658074
136.47.34095-0.940946
1410.611.3705-0.770542
151212.4972-0.497245
166.37.60674-1.30674
1711.311.16420.135801
1811.912.8179-0.917927
199.39.83324-0.533241
209.69.482950.117055
211010.4076-0.407576
226.46.51511-0.115105
2313.813.55420.245806
2410.812.2059-1.40591
2513.814.5161-0.716141
2611.712.4097-0.709662
2710.912.3039-1.4039
2816.115.25420.845846
2913.413.17430.225685
309.910.4884-0.588445
3111.512.3923-0.892257
328.38.33657-0.0365723
3311.712.5128-0.812787
346.16.66067-0.560665
3599.9042-0.904204
369.79.391330.30867
3710.810.79020.00976996
3810.310.5075-0.207519
3910.411.2404-0.840425
4012.712.9799-0.279917
419.39.234070.0659297
4211.812.1786-0.378585
435.95.298520.601477
4411.411.7332-0.333155
451313.4876-0.487626
4610.811.8859-1.08593
4712.311.65060.649399
4811.311.875-0.575042
4911.811.9907-0.190704
507.96.57581.3242
5112.713.5835-0.883499
5212.311.96590.334148
5311.611.6235-0.0235265
546.75.863130.836869
5510.911.8471-0.947143
5612.113.7676-1.66758
5713.313.9155-0.615543
5810.110.9035-0.803487
595.75.92893-0.228931
6014.315.5567-1.25667
6188.44155-0.441547
6213.313.9972-0.697169
639.310.3274-1.02739
6412.512.8253-0.325347
657.67.105490.494509
6615.917.0584-1.15841
679.210.3779-1.17793
689.18.830640.269356
6911.111.5386-0.438553
701314.5363-1.53633
7114.515.1084-0.608358
7212.212.3596-0.159642
7312.312.25640.0436442
7411.411.8428-0.442772
758.89.06524-0.265239
7614.613.93260.667446
777.37.043550.256452
7812.613.4786-0.878604
791313.8473-0.847281
8012.612.9064-0.306395
8113.214.5535-1.35345
829.99.067190.832806
837.77.365120.334876
8410.510.00640.493592
8513.413.9631-0.563107
8610.910.69160.208362
874.34.31442-0.0144232
8810.39.963590.336415
8911.811.8951-0.0951294
9011.210.76830.431722
9111.410.30291.09708
928.67.999770.600227
9313.214.2377-1.03771
9412.612.7845-0.184495
955.65.69206-0.09206
969.911.0439-1.14393
978.88.95916-0.159159
987.77.076940.623064
9999.6143-0.614305
1007.37.6981-0.398104
10111.411.407-0.00696069
10213.614.1949-0.594891
1037.96.701491.19851
10410.710.7571-0.0571274
10510.310.8622-0.562207
1068.38.283810.0161922
1079.69.4150.184998
10814.214.4062-0.206238
1098.58.325320.174684
11013.513.48710.012928
1114.94.769820.130176
1126.45.979540.420455
1139.69.275780.324222
11411.611.958-0.358017
11511.111.3594-0.259372
1164.354.032310.317686
11712.713.0402-0.340189
11818.117.65270.447297
11917.8517.42940.420609
12016.616.8591-0.259141
12112.612.34980.250212
12217.117.9431-0.843123
12319.118.90180.198204
12416.116.03380.0661804
12513.3513.27260.0774413
12618.418.05530.344677
12714.715.8916-1.1916
12810.69.977970.62203
12912.612.21520.384833
13016.215.63860.561419
13113.613.6731-0.0730772
13218.918.12380.776177
13314.113.45670.643309
13414.513.79890.701072
13516.1515.7460.403996
13614.7514.35990.390136
13714.814.21270.587251
13812.4512.7141-0.2641
13912.6512.9048-0.254779
14017.3517.5072-0.157237
1418.69.06976-0.469765
14218.418.13510.264868
14316.116.7425-0.642505
14411.611.38730.212684
14517.7516.82390.92607
14615.2514.35640.893599
14717.6516.84160.808355
14815.614.65770.942272
14916.3515.73960.610397
15017.6516.77290.877108
15113.613.27970.320305
15211.710.26691.43306
15314.3514.08450.265532
15414.7514.20380.546208
15518.2518.02910.220925
1569.98.526111.37389
1571615.80060.199437
15818.2517.80770.442272
15916.8516.83070.0192595
16014.614.9122-0.312181
16113.8514.5319-0.681912
16218.9518.25350.696536
16315.615.6273-0.0272557
16414.8515.2028-0.352816
16511.7511.64680.103173
16618.4517.86920.580753
16715.917.0127-1.11273
16817.116.65630.443708
16916.116.9243-0.824285
17019.919.29650.603483
17110.9511.5845-0.634514
17218.4517.25421.19578
17315.114.26350.836484
1741514.8290.171017
17511.3511.7254-0.375442
17615.9515.31670.633284
17718.118.2477-0.14774
17814.613.30681.29323
17915.415.446-0.046042
18015.415.4507-0.0507167
18117.617.7234-0.123416
18213.3513.03860.311447
18319.119.1373-0.0372577
18415.3514.29561.05439
1857.68.05607-0.45607
18613.413.6526-0.252634
18713.913.30350.596455
18819.119.1484-0.0483781
18915.2514.98640.263577
19012.911.12971.77025
19116.116.04420.0558037
19217.3517.16610.183932
19313.1512.23380.916153
19412.1510.68931.46069
19512.613.8435-1.24353
19610.3511.0112-0.661197
19715.414.90230.497729
1989.69.179490.420512
19918.217.73980.460174
20013.613.8322-0.232196
20114.8515.4371-0.587099
20214.7514.11880.631224
20314.114.922-0.822037
20414.914.82190.0780777
20516.2515.92270.327253
20619.2519.6036-0.353575
20713.613.6809-0.080938
20813.612.40611.19386
20915.6515.51720.132762
21012.7510.91851.83148
21114.614.6239-0.0239093
2129.8510.7443-0.894301
21312.6513.9395-1.28954
21411.913.4878-1.58777
21519.218.53730.6627
21616.616.6279-0.0278856
21711.211.778-0.577997
21815.2514.06441.18559
21911.911.31820.581778
22013.214.2129-1.01288
22116.3516.13170.218259
22212.411.5010.899014
22315.8515.48970.360256
22414.3513.30061.04945
22518.1517.63840.511648
22611.1511.5699-0.41987
22715.6515.41130.23873
22817.7517.3090.44101
2297.657.93223-0.282233
23012.3511.47150.878455
23115.614.30731.29268
23219.319.7555-0.455524
23315.215.8374-0.637358
23417.116.3290.771032
23515.616.1474-0.547391
23618.418.6115-0.211488
23719.0518.31630.733732
23818.5517.7190.830965
23919.119.03170.0683263
24013.113.3422-0.242201
24112.8511.74361.10636
2429.59.319240.180763
2434.54.271050.228951
24411.8512.5637-0.713745
24513.612.82010.779889
24611.712.0403-0.340309
24712.412.22010.179937
24813.3513.19740.152606
24911.411.32620.0737606
25014.913.94780.952212
25119.919.31380.586213
25217.7516.4711.27902
25311.211.2282-0.0282295
25414.614.6682-0.0681808
25517.617.49060.109432
25614.0513.09460.955373
25716.115.39360.706423
25813.3512.02661.32344
25911.8510.26411.5859
26011.9512.6323-0.682296
26114.7515.4586-0.70863
26215.1515.4399-0.289853
26313.212.30210.897866
26416.8517.0888-0.238778
2657.857.031570.818425
2667.78.04625-0.346248
26712.611.76520.834846
2687.856.486511.36349
26910.9511.5478-0.597831
27012.3512.4927-0.142652
2719.9510.1416-0.191589
27214.913.95540.944583
27316.6516.38690.263124
27413.413.26510.134947
27513.9514.5395-0.5895
27615.714.70710.992863
27716.8516.6940.156013
27810.9511.7451-0.795053
27915.3515.01720.332808
28012.212.2354-0.0353745
28115.116.1302-1.03016
28217.7518.0962-0.346211
28315.214.1861.01404
28414.614.29550.304522
28516.6516.57150.078492
2868.19.02288-0.92288






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.3710020.7420030.628998
140.2588240.5176490.741176
150.1851520.3703050.814848
160.1129730.2259450.887027
170.4040270.8080540.595973
180.3225410.6450820.677459
190.2489070.4978130.751093
200.2156830.4313670.784317
210.173460.346920.82654
220.1405760.2811520.859424
230.1088780.2177560.891122
240.08462740.1692550.915373
250.05987630.1197530.940124
260.04261790.08523580.957382
270.03375480.06750960.966245
280.0294080.05881590.970592
290.03893950.0778790.96106
300.03021480.06042950.969785
310.02260180.04520350.977398
320.02142320.04284640.978577
330.01591410.03182810.984086
340.01071270.02142540.989287
350.007965270.01593050.992035
360.007014110.01402820.992986
370.005029880.01005980.99497
380.003153050.00630610.996847
390.002184620.004369240.997815
400.001488640.002977270.998511
410.0009071730.001814350.999093
420.000984650.00196930.999015
430.0009608370.001921670.999039
440.000623990.001247980.999376
450.0003962220.0007924440.999604
460.0003175590.0006351170.999682
470.0002784580.0005569160.999722
480.0002329370.0004658740.999767
490.0001388330.0002776650.999861
500.0002346130.0004692260.999765
510.0001717720.0003435440.999828
520.0001413480.0002826970.999859
539.84732e-050.0001969460.999902
548.48677e-050.0001697350.999915
556.25033e-050.0001250070.999937
560.0001087060.0002174130.999891
577.30117e-050.0001460230.999927
585.13477e-050.0001026950.999949
593.31121e-056.62242e-050.999967
604.26177e-058.52354e-050.999957
613.44952e-056.89904e-050.999966
623.13103e-056.26206e-050.999969
636.36024e-050.0001272050.999936
640.0001120280.0002240560.999888
659.72825e-050.0001945650.999903
660.0001151080.0002302160.999885
670.0002095740.0004191490.99979
680.0001369680.0002739360.999863
690.0001242650.0002485310.999876
700.0005684350.001136870.999432
710.0008312950.001662590.999169
720.0005880680.001176140.999412
730.000580220.001160440.99942
740.0005235820.001047160.999476
750.0003886010.0007772020.999611
760.0003379060.0006758110.999662
770.000280830.0005616610.999719
780.0003511770.0007023550.999649
790.0005291720.001058340.999471
800.0004245260.0008490520.999575
810.0009397270.001879450.99906
820.00122530.002450610.998775
830.0008996570.001799310.9991
840.0007458470.001491690.999254
850.0008296440.001659290.99917
860.000604340.001208680.999396
870.0005237850.001047570.999476
880.000405430.000810860.999595
890.0003377140.0006754270.999662
900.0002415420.0004830830.999758
910.0007737260.001547450.999226
920.0006470280.001294060.999353
930.001513180.003026350.998487
940.001112170.002224330.998888
950.001057310.002114610.998943
960.00420020.00840040.9958
970.003412970.006825940.996587
980.00494250.009885010.995057
990.008838660.01767730.991161
1000.0143390.02867810.985661
1010.01588090.03176190.984119
1020.01580790.03161590.984192
1030.01920830.03841670.980792
1040.01536250.0307250.984637
1050.0199550.03991010.980045
1060.01885420.03770840.981146
1070.02345340.04690680.976547
1080.02175720.04351450.978243
1090.02226250.04452490.977738
1100.02143410.04286830.978566
1110.023850.04770.97615
1120.01944630.03889260.980554
1130.01786410.03572810.982136
1140.03168510.06337010.968315
1150.03918070.07836130.960819
1160.03315360.06630730.966846
1170.03225420.06450840.967746
1180.1306260.2612530.869374
1190.4263230.8526460.573677
1200.4278380.8556760.572162
1210.432950.8658990.56705
1220.4929880.9859750.507012
1230.4973920.9947850.502608
1240.4837170.9674350.516283
1250.5553870.8892250.444613
1260.6478840.7042330.352116
1270.7643690.4712620.235631
1280.801830.396340.19817
1290.8461870.3076270.153813
1300.9006260.1987480.0993741
1310.9200630.1598730.0799366
1320.9314220.1371560.0685778
1330.9483050.1033910.0516953
1340.9603660.07926870.0396344
1350.9635230.07295440.0364772
1360.9654080.06918330.0345917
1370.9666930.06661360.0333068
1380.9611730.07765430.0388271
1390.9572250.08554910.0427746
1400.9524910.0950170.0475085
1410.9619340.07613220.0380661
1420.9654580.06908490.0345424
1430.965230.06953930.0347697
1440.9604660.07906760.0395338
1450.9848080.03038490.0151924
1460.9880320.0239360.011968
1470.9950290.009941080.00497054
1480.9981440.003711290.00185565
1490.9985110.002977060.00148853
1500.999150.001699930.000849967
1510.9989550.002089550.00104478
1520.9997230.0005544890.000277244
1530.9996270.0007468720.000373436
1540.9997250.0005504620.000275231
1550.9997120.0005755760.000287788
1560.9999030.0001946489.73239e-05
1570.9998640.0002714640.000135732
1580.9998530.0002938610.00014693
1590.9998150.0003699990.000184999
1600.9997620.00047550.00023775
1610.9997590.0004814770.000240739
1620.999770.0004602120.000230106
1630.9996810.0006376090.000318804
1640.9996070.0007854810.00039274
1650.9994640.001071090.000535545
1660.9994350.001129940.000564969
1670.9995170.0009653790.00048269
1680.9996090.000782230.000391115
1690.9998210.0003576240.000178812
1700.9997830.0004331340.000216567
1710.9998190.000362520.00018126
1720.9999676.53724e-053.26862e-05
1730.9999745.15309e-052.57654e-05
1740.9999715.70999e-052.855e-05
1750.9999647.17872e-053.58936e-05
1760.9999843.27708e-051.63854e-05
1770.9999774.59406e-052.29703e-05
1780.9999843.24242e-051.62121e-05
1790.9999833.40603e-051.70301e-05
1800.9999843.18715e-051.59357e-05
1810.9999764.75008e-052.37504e-05
1820.9999656.9595e-053.47975e-05
1830.9999529.6132e-054.8066e-05
1840.9999578.63419e-054.3171e-05
1850.9999519.70126e-054.85063e-05
1860.9999350.0001305196.52596e-05
1870.9999120.0001755178.77584e-05
1880.9998730.0002545090.000127255
1890.9998270.0003456460.000172823
1900.9999320.0001365816.82903e-05
1910.9998990.0002021620.000101081
1920.9998560.0002874970.000143748
1930.9998420.0003163980.000158199
1940.9998750.000249690.000124845
1950.999930.0001408747.04368e-05
1960.9999280.000144417.22049e-05
1970.9999060.0001880099.40044e-05
1980.9998790.0002427240.000121362
1990.9998620.0002764720.000138236
2000.9998050.0003907840.000195392
2010.9997980.0004044640.000202232
2020.9997370.0005259830.000262991
2030.9997710.0004572930.000228647
2040.9996660.0006673660.000333683
2050.9995340.0009324240.000466212
2060.9999290.0001427537.13763e-05
2070.9999140.0001720388.60189e-05
2080.9999120.0001765788.82888e-05
2090.999870.0002597920.000129896
2100.9999696.10116e-053.05058e-05
2110.9999617.74693e-053.87346e-05
2120.9999539.45867e-054.72933e-05
2130.9999715.77326e-052.88663e-05
2140.9999975.66953e-062.83476e-06
2150.9999992.17572e-061.08786e-06
2160.9999983.63861e-061.8193e-06
2170.9999975.46949e-062.73474e-06
2180.9999976.30736e-063.15368e-06
2190.9999976.41211e-063.20606e-06
2200.9999968.72648e-064.36324e-06
2210.9999921.50359e-057.51797e-06
2220.9999941.18704e-055.93522e-06
2230.9999931.35188e-056.75938e-06
2240.999991.94951e-059.74753e-06
2250.9999892.28435e-051.14217e-05
2260.9999813.71124e-051.85562e-05
2270.9999745.26395e-052.63198e-05
2280.9999627.626e-053.813e-05
2290.9999440.0001121335.60663e-05
2300.9999210.0001583857.91926e-05
2310.9999270.0001450527.25259e-05
2320.9999666.75476e-053.37738e-05
2330.9999450.0001102815.51405e-05
2340.9999170.0001660328.30158e-05
2350.9998930.0002130750.000106537
2360.9998390.000321880.00016094
2370.9997930.0004145250.000207262
2380.9997370.0005258190.000262909
2390.9995620.0008759690.000437984
2400.9994650.001070650.000535327
2410.9994610.001077160.000538579
2420.9991880.001624980.000812489
2430.9987090.002582610.00129131
2440.9983320.003335490.00166774
2450.997480.005040760.00252038
2460.9963440.007312580.00365629
2470.9952660.009467660.00473383
2480.9926250.01475080.00737538
2490.9938010.01239820.00619909
2500.9927370.01452510.00726257
2510.9903920.01921580.00960792
2520.9886060.02278770.0113938
2530.9841820.03163530.0158176
2540.9758590.04828250.0241412
2550.973370.05326040.0266302
2560.9629360.07412710.0370635
2570.9580330.08393440.0419672
2580.9540640.09187140.0459357
2590.9454850.1090310.0545153
2600.9255610.1488790.0744394
2610.909080.1818410.0909205
2620.8815330.2369330.118467
2630.8802320.2395370.119768
2640.8365870.3268270.163413
2650.8407490.3185030.159251
2660.8331430.3337150.166857
2670.8062810.3874380.193719
2680.7426690.5146620.257331
2690.6734530.6530940.326547
2700.5721250.8557490.427875
2710.6342780.7314440.365722
2720.4920830.9841660.507917
2730.4229860.8459710.577014

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.371002 & 0.742003 & 0.628998 \tabularnewline
14 & 0.258824 & 0.517649 & 0.741176 \tabularnewline
15 & 0.185152 & 0.370305 & 0.814848 \tabularnewline
16 & 0.112973 & 0.225945 & 0.887027 \tabularnewline
17 & 0.404027 & 0.808054 & 0.595973 \tabularnewline
18 & 0.322541 & 0.645082 & 0.677459 \tabularnewline
19 & 0.248907 & 0.497813 & 0.751093 \tabularnewline
20 & 0.215683 & 0.431367 & 0.784317 \tabularnewline
21 & 0.17346 & 0.34692 & 0.82654 \tabularnewline
22 & 0.140576 & 0.281152 & 0.859424 \tabularnewline
23 & 0.108878 & 0.217756 & 0.891122 \tabularnewline
24 & 0.0846274 & 0.169255 & 0.915373 \tabularnewline
25 & 0.0598763 & 0.119753 & 0.940124 \tabularnewline
26 & 0.0426179 & 0.0852358 & 0.957382 \tabularnewline
27 & 0.0337548 & 0.0675096 & 0.966245 \tabularnewline
28 & 0.029408 & 0.0588159 & 0.970592 \tabularnewline
29 & 0.0389395 & 0.077879 & 0.96106 \tabularnewline
30 & 0.0302148 & 0.0604295 & 0.969785 \tabularnewline
31 & 0.0226018 & 0.0452035 & 0.977398 \tabularnewline
32 & 0.0214232 & 0.0428464 & 0.978577 \tabularnewline
33 & 0.0159141 & 0.0318281 & 0.984086 \tabularnewline
34 & 0.0107127 & 0.0214254 & 0.989287 \tabularnewline
35 & 0.00796527 & 0.0159305 & 0.992035 \tabularnewline
36 & 0.00701411 & 0.0140282 & 0.992986 \tabularnewline
37 & 0.00502988 & 0.0100598 & 0.99497 \tabularnewline
38 & 0.00315305 & 0.0063061 & 0.996847 \tabularnewline
39 & 0.00218462 & 0.00436924 & 0.997815 \tabularnewline
40 & 0.00148864 & 0.00297727 & 0.998511 \tabularnewline
41 & 0.000907173 & 0.00181435 & 0.999093 \tabularnewline
42 & 0.00098465 & 0.0019693 & 0.999015 \tabularnewline
43 & 0.000960837 & 0.00192167 & 0.999039 \tabularnewline
44 & 0.00062399 & 0.00124798 & 0.999376 \tabularnewline
45 & 0.000396222 & 0.000792444 & 0.999604 \tabularnewline
46 & 0.000317559 & 0.000635117 & 0.999682 \tabularnewline
47 & 0.000278458 & 0.000556916 & 0.999722 \tabularnewline
48 & 0.000232937 & 0.000465874 & 0.999767 \tabularnewline
49 & 0.000138833 & 0.000277665 & 0.999861 \tabularnewline
50 & 0.000234613 & 0.000469226 & 0.999765 \tabularnewline
51 & 0.000171772 & 0.000343544 & 0.999828 \tabularnewline
52 & 0.000141348 & 0.000282697 & 0.999859 \tabularnewline
53 & 9.84732e-05 & 0.000196946 & 0.999902 \tabularnewline
54 & 8.48677e-05 & 0.000169735 & 0.999915 \tabularnewline
55 & 6.25033e-05 & 0.000125007 & 0.999937 \tabularnewline
56 & 0.000108706 & 0.000217413 & 0.999891 \tabularnewline
57 & 7.30117e-05 & 0.000146023 & 0.999927 \tabularnewline
58 & 5.13477e-05 & 0.000102695 & 0.999949 \tabularnewline
59 & 3.31121e-05 & 6.62242e-05 & 0.999967 \tabularnewline
60 & 4.26177e-05 & 8.52354e-05 & 0.999957 \tabularnewline
61 & 3.44952e-05 & 6.89904e-05 & 0.999966 \tabularnewline
62 & 3.13103e-05 & 6.26206e-05 & 0.999969 \tabularnewline
63 & 6.36024e-05 & 0.000127205 & 0.999936 \tabularnewline
64 & 0.000112028 & 0.000224056 & 0.999888 \tabularnewline
65 & 9.72825e-05 & 0.000194565 & 0.999903 \tabularnewline
66 & 0.000115108 & 0.000230216 & 0.999885 \tabularnewline
67 & 0.000209574 & 0.000419149 & 0.99979 \tabularnewline
68 & 0.000136968 & 0.000273936 & 0.999863 \tabularnewline
69 & 0.000124265 & 0.000248531 & 0.999876 \tabularnewline
70 & 0.000568435 & 0.00113687 & 0.999432 \tabularnewline
71 & 0.000831295 & 0.00166259 & 0.999169 \tabularnewline
72 & 0.000588068 & 0.00117614 & 0.999412 \tabularnewline
73 & 0.00058022 & 0.00116044 & 0.99942 \tabularnewline
74 & 0.000523582 & 0.00104716 & 0.999476 \tabularnewline
75 & 0.000388601 & 0.000777202 & 0.999611 \tabularnewline
76 & 0.000337906 & 0.000675811 & 0.999662 \tabularnewline
77 & 0.00028083 & 0.000561661 & 0.999719 \tabularnewline
78 & 0.000351177 & 0.000702355 & 0.999649 \tabularnewline
79 & 0.000529172 & 0.00105834 & 0.999471 \tabularnewline
80 & 0.000424526 & 0.000849052 & 0.999575 \tabularnewline
81 & 0.000939727 & 0.00187945 & 0.99906 \tabularnewline
82 & 0.0012253 & 0.00245061 & 0.998775 \tabularnewline
83 & 0.000899657 & 0.00179931 & 0.9991 \tabularnewline
84 & 0.000745847 & 0.00149169 & 0.999254 \tabularnewline
85 & 0.000829644 & 0.00165929 & 0.99917 \tabularnewline
86 & 0.00060434 & 0.00120868 & 0.999396 \tabularnewline
87 & 0.000523785 & 0.00104757 & 0.999476 \tabularnewline
88 & 0.00040543 & 0.00081086 & 0.999595 \tabularnewline
89 & 0.000337714 & 0.000675427 & 0.999662 \tabularnewline
90 & 0.000241542 & 0.000483083 & 0.999758 \tabularnewline
91 & 0.000773726 & 0.00154745 & 0.999226 \tabularnewline
92 & 0.000647028 & 0.00129406 & 0.999353 \tabularnewline
93 & 0.00151318 & 0.00302635 & 0.998487 \tabularnewline
94 & 0.00111217 & 0.00222433 & 0.998888 \tabularnewline
95 & 0.00105731 & 0.00211461 & 0.998943 \tabularnewline
96 & 0.0042002 & 0.0084004 & 0.9958 \tabularnewline
97 & 0.00341297 & 0.00682594 & 0.996587 \tabularnewline
98 & 0.0049425 & 0.00988501 & 0.995057 \tabularnewline
99 & 0.00883866 & 0.0176773 & 0.991161 \tabularnewline
100 & 0.014339 & 0.0286781 & 0.985661 \tabularnewline
101 & 0.0158809 & 0.0317619 & 0.984119 \tabularnewline
102 & 0.0158079 & 0.0316159 & 0.984192 \tabularnewline
103 & 0.0192083 & 0.0384167 & 0.980792 \tabularnewline
104 & 0.0153625 & 0.030725 & 0.984637 \tabularnewline
105 & 0.019955 & 0.0399101 & 0.980045 \tabularnewline
106 & 0.0188542 & 0.0377084 & 0.981146 \tabularnewline
107 & 0.0234534 & 0.0469068 & 0.976547 \tabularnewline
108 & 0.0217572 & 0.0435145 & 0.978243 \tabularnewline
109 & 0.0222625 & 0.0445249 & 0.977738 \tabularnewline
110 & 0.0214341 & 0.0428683 & 0.978566 \tabularnewline
111 & 0.02385 & 0.0477 & 0.97615 \tabularnewline
112 & 0.0194463 & 0.0388926 & 0.980554 \tabularnewline
113 & 0.0178641 & 0.0357281 & 0.982136 \tabularnewline
114 & 0.0316851 & 0.0633701 & 0.968315 \tabularnewline
115 & 0.0391807 & 0.0783613 & 0.960819 \tabularnewline
116 & 0.0331536 & 0.0663073 & 0.966846 \tabularnewline
117 & 0.0322542 & 0.0645084 & 0.967746 \tabularnewline
118 & 0.130626 & 0.261253 & 0.869374 \tabularnewline
119 & 0.426323 & 0.852646 & 0.573677 \tabularnewline
120 & 0.427838 & 0.855676 & 0.572162 \tabularnewline
121 & 0.43295 & 0.865899 & 0.56705 \tabularnewline
122 & 0.492988 & 0.985975 & 0.507012 \tabularnewline
123 & 0.497392 & 0.994785 & 0.502608 \tabularnewline
124 & 0.483717 & 0.967435 & 0.516283 \tabularnewline
125 & 0.555387 & 0.889225 & 0.444613 \tabularnewline
126 & 0.647884 & 0.704233 & 0.352116 \tabularnewline
127 & 0.764369 & 0.471262 & 0.235631 \tabularnewline
128 & 0.80183 & 0.39634 & 0.19817 \tabularnewline
129 & 0.846187 & 0.307627 & 0.153813 \tabularnewline
130 & 0.900626 & 0.198748 & 0.0993741 \tabularnewline
131 & 0.920063 & 0.159873 & 0.0799366 \tabularnewline
132 & 0.931422 & 0.137156 & 0.0685778 \tabularnewline
133 & 0.948305 & 0.103391 & 0.0516953 \tabularnewline
134 & 0.960366 & 0.0792687 & 0.0396344 \tabularnewline
135 & 0.963523 & 0.0729544 & 0.0364772 \tabularnewline
136 & 0.965408 & 0.0691833 & 0.0345917 \tabularnewline
137 & 0.966693 & 0.0666136 & 0.0333068 \tabularnewline
138 & 0.961173 & 0.0776543 & 0.0388271 \tabularnewline
139 & 0.957225 & 0.0855491 & 0.0427746 \tabularnewline
140 & 0.952491 & 0.095017 & 0.0475085 \tabularnewline
141 & 0.961934 & 0.0761322 & 0.0380661 \tabularnewline
142 & 0.965458 & 0.0690849 & 0.0345424 \tabularnewline
143 & 0.96523 & 0.0695393 & 0.0347697 \tabularnewline
144 & 0.960466 & 0.0790676 & 0.0395338 \tabularnewline
145 & 0.984808 & 0.0303849 & 0.0151924 \tabularnewline
146 & 0.988032 & 0.023936 & 0.011968 \tabularnewline
147 & 0.995029 & 0.00994108 & 0.00497054 \tabularnewline
148 & 0.998144 & 0.00371129 & 0.00185565 \tabularnewline
149 & 0.998511 & 0.00297706 & 0.00148853 \tabularnewline
150 & 0.99915 & 0.00169993 & 0.000849967 \tabularnewline
151 & 0.998955 & 0.00208955 & 0.00104478 \tabularnewline
152 & 0.999723 & 0.000554489 & 0.000277244 \tabularnewline
153 & 0.999627 & 0.000746872 & 0.000373436 \tabularnewline
154 & 0.999725 & 0.000550462 & 0.000275231 \tabularnewline
155 & 0.999712 & 0.000575576 & 0.000287788 \tabularnewline
156 & 0.999903 & 0.000194648 & 9.73239e-05 \tabularnewline
157 & 0.999864 & 0.000271464 & 0.000135732 \tabularnewline
158 & 0.999853 & 0.000293861 & 0.00014693 \tabularnewline
159 & 0.999815 & 0.000369999 & 0.000184999 \tabularnewline
160 & 0.999762 & 0.0004755 & 0.00023775 \tabularnewline
161 & 0.999759 & 0.000481477 & 0.000240739 \tabularnewline
162 & 0.99977 & 0.000460212 & 0.000230106 \tabularnewline
163 & 0.999681 & 0.000637609 & 0.000318804 \tabularnewline
164 & 0.999607 & 0.000785481 & 0.00039274 \tabularnewline
165 & 0.999464 & 0.00107109 & 0.000535545 \tabularnewline
166 & 0.999435 & 0.00112994 & 0.000564969 \tabularnewline
167 & 0.999517 & 0.000965379 & 0.00048269 \tabularnewline
168 & 0.999609 & 0.00078223 & 0.000391115 \tabularnewline
169 & 0.999821 & 0.000357624 & 0.000178812 \tabularnewline
170 & 0.999783 & 0.000433134 & 0.000216567 \tabularnewline
171 & 0.999819 & 0.00036252 & 0.00018126 \tabularnewline
172 & 0.999967 & 6.53724e-05 & 3.26862e-05 \tabularnewline
173 & 0.999974 & 5.15309e-05 & 2.57654e-05 \tabularnewline
174 & 0.999971 & 5.70999e-05 & 2.855e-05 \tabularnewline
175 & 0.999964 & 7.17872e-05 & 3.58936e-05 \tabularnewline
176 & 0.999984 & 3.27708e-05 & 1.63854e-05 \tabularnewline
177 & 0.999977 & 4.59406e-05 & 2.29703e-05 \tabularnewline
178 & 0.999984 & 3.24242e-05 & 1.62121e-05 \tabularnewline
179 & 0.999983 & 3.40603e-05 & 1.70301e-05 \tabularnewline
180 & 0.999984 & 3.18715e-05 & 1.59357e-05 \tabularnewline
181 & 0.999976 & 4.75008e-05 & 2.37504e-05 \tabularnewline
182 & 0.999965 & 6.9595e-05 & 3.47975e-05 \tabularnewline
183 & 0.999952 & 9.6132e-05 & 4.8066e-05 \tabularnewline
184 & 0.999957 & 8.63419e-05 & 4.3171e-05 \tabularnewline
185 & 0.999951 & 9.70126e-05 & 4.85063e-05 \tabularnewline
186 & 0.999935 & 0.000130519 & 6.52596e-05 \tabularnewline
187 & 0.999912 & 0.000175517 & 8.77584e-05 \tabularnewline
188 & 0.999873 & 0.000254509 & 0.000127255 \tabularnewline
189 & 0.999827 & 0.000345646 & 0.000172823 \tabularnewline
190 & 0.999932 & 0.000136581 & 6.82903e-05 \tabularnewline
191 & 0.999899 & 0.000202162 & 0.000101081 \tabularnewline
192 & 0.999856 & 0.000287497 & 0.000143748 \tabularnewline
193 & 0.999842 & 0.000316398 & 0.000158199 \tabularnewline
194 & 0.999875 & 0.00024969 & 0.000124845 \tabularnewline
195 & 0.99993 & 0.000140874 & 7.04368e-05 \tabularnewline
196 & 0.999928 & 0.00014441 & 7.22049e-05 \tabularnewline
197 & 0.999906 & 0.000188009 & 9.40044e-05 \tabularnewline
198 & 0.999879 & 0.000242724 & 0.000121362 \tabularnewline
199 & 0.999862 & 0.000276472 & 0.000138236 \tabularnewline
200 & 0.999805 & 0.000390784 & 0.000195392 \tabularnewline
201 & 0.999798 & 0.000404464 & 0.000202232 \tabularnewline
202 & 0.999737 & 0.000525983 & 0.000262991 \tabularnewline
203 & 0.999771 & 0.000457293 & 0.000228647 \tabularnewline
204 & 0.999666 & 0.000667366 & 0.000333683 \tabularnewline
205 & 0.999534 & 0.000932424 & 0.000466212 \tabularnewline
206 & 0.999929 & 0.000142753 & 7.13763e-05 \tabularnewline
207 & 0.999914 & 0.000172038 & 8.60189e-05 \tabularnewline
208 & 0.999912 & 0.000176578 & 8.82888e-05 \tabularnewline
209 & 0.99987 & 0.000259792 & 0.000129896 \tabularnewline
210 & 0.999969 & 6.10116e-05 & 3.05058e-05 \tabularnewline
211 & 0.999961 & 7.74693e-05 & 3.87346e-05 \tabularnewline
212 & 0.999953 & 9.45867e-05 & 4.72933e-05 \tabularnewline
213 & 0.999971 & 5.77326e-05 & 2.88663e-05 \tabularnewline
214 & 0.999997 & 5.66953e-06 & 2.83476e-06 \tabularnewline
215 & 0.999999 & 2.17572e-06 & 1.08786e-06 \tabularnewline
216 & 0.999998 & 3.63861e-06 & 1.8193e-06 \tabularnewline
217 & 0.999997 & 5.46949e-06 & 2.73474e-06 \tabularnewline
218 & 0.999997 & 6.30736e-06 & 3.15368e-06 \tabularnewline
219 & 0.999997 & 6.41211e-06 & 3.20606e-06 \tabularnewline
220 & 0.999996 & 8.72648e-06 & 4.36324e-06 \tabularnewline
221 & 0.999992 & 1.50359e-05 & 7.51797e-06 \tabularnewline
222 & 0.999994 & 1.18704e-05 & 5.93522e-06 \tabularnewline
223 & 0.999993 & 1.35188e-05 & 6.75938e-06 \tabularnewline
224 & 0.99999 & 1.94951e-05 & 9.74753e-06 \tabularnewline
225 & 0.999989 & 2.28435e-05 & 1.14217e-05 \tabularnewline
226 & 0.999981 & 3.71124e-05 & 1.85562e-05 \tabularnewline
227 & 0.999974 & 5.26395e-05 & 2.63198e-05 \tabularnewline
228 & 0.999962 & 7.626e-05 & 3.813e-05 \tabularnewline
229 & 0.999944 & 0.000112133 & 5.60663e-05 \tabularnewline
230 & 0.999921 & 0.000158385 & 7.91926e-05 \tabularnewline
231 & 0.999927 & 0.000145052 & 7.25259e-05 \tabularnewline
232 & 0.999966 & 6.75476e-05 & 3.37738e-05 \tabularnewline
233 & 0.999945 & 0.000110281 & 5.51405e-05 \tabularnewline
234 & 0.999917 & 0.000166032 & 8.30158e-05 \tabularnewline
235 & 0.999893 & 0.000213075 & 0.000106537 \tabularnewline
236 & 0.999839 & 0.00032188 & 0.00016094 \tabularnewline
237 & 0.999793 & 0.000414525 & 0.000207262 \tabularnewline
238 & 0.999737 & 0.000525819 & 0.000262909 \tabularnewline
239 & 0.999562 & 0.000875969 & 0.000437984 \tabularnewline
240 & 0.999465 & 0.00107065 & 0.000535327 \tabularnewline
241 & 0.999461 & 0.00107716 & 0.000538579 \tabularnewline
242 & 0.999188 & 0.00162498 & 0.000812489 \tabularnewline
243 & 0.998709 & 0.00258261 & 0.00129131 \tabularnewline
244 & 0.998332 & 0.00333549 & 0.00166774 \tabularnewline
245 & 0.99748 & 0.00504076 & 0.00252038 \tabularnewline
246 & 0.996344 & 0.00731258 & 0.00365629 \tabularnewline
247 & 0.995266 & 0.00946766 & 0.00473383 \tabularnewline
248 & 0.992625 & 0.0147508 & 0.00737538 \tabularnewline
249 & 0.993801 & 0.0123982 & 0.00619909 \tabularnewline
250 & 0.992737 & 0.0145251 & 0.00726257 \tabularnewline
251 & 0.990392 & 0.0192158 & 0.00960792 \tabularnewline
252 & 0.988606 & 0.0227877 & 0.0113938 \tabularnewline
253 & 0.984182 & 0.0316353 & 0.0158176 \tabularnewline
254 & 0.975859 & 0.0482825 & 0.0241412 \tabularnewline
255 & 0.97337 & 0.0532604 & 0.0266302 \tabularnewline
256 & 0.962936 & 0.0741271 & 0.0370635 \tabularnewline
257 & 0.958033 & 0.0839344 & 0.0419672 \tabularnewline
258 & 0.954064 & 0.0918714 & 0.0459357 \tabularnewline
259 & 0.945485 & 0.109031 & 0.0545153 \tabularnewline
260 & 0.925561 & 0.148879 & 0.0744394 \tabularnewline
261 & 0.90908 & 0.181841 & 0.0909205 \tabularnewline
262 & 0.881533 & 0.236933 & 0.118467 \tabularnewline
263 & 0.880232 & 0.239537 & 0.119768 \tabularnewline
264 & 0.836587 & 0.326827 & 0.163413 \tabularnewline
265 & 0.840749 & 0.318503 & 0.159251 \tabularnewline
266 & 0.833143 & 0.333715 & 0.166857 \tabularnewline
267 & 0.806281 & 0.387438 & 0.193719 \tabularnewline
268 & 0.742669 & 0.514662 & 0.257331 \tabularnewline
269 & 0.673453 & 0.653094 & 0.326547 \tabularnewline
270 & 0.572125 & 0.855749 & 0.427875 \tabularnewline
271 & 0.634278 & 0.731444 & 0.365722 \tabularnewline
272 & 0.492083 & 0.984166 & 0.507917 \tabularnewline
273 & 0.422986 & 0.845971 & 0.577014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268251&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]13[/C][C]0.371002[/C][C]0.742003[/C][C]0.628998[/C][/ROW]
[ROW][C]14[/C][C]0.258824[/C][C]0.517649[/C][C]0.741176[/C][/ROW]
[ROW][C]15[/C][C]0.185152[/C][C]0.370305[/C][C]0.814848[/C][/ROW]
[ROW][C]16[/C][C]0.112973[/C][C]0.225945[/C][C]0.887027[/C][/ROW]
[ROW][C]17[/C][C]0.404027[/C][C]0.808054[/C][C]0.595973[/C][/ROW]
[ROW][C]18[/C][C]0.322541[/C][C]0.645082[/C][C]0.677459[/C][/ROW]
[ROW][C]19[/C][C]0.248907[/C][C]0.497813[/C][C]0.751093[/C][/ROW]
[ROW][C]20[/C][C]0.215683[/C][C]0.431367[/C][C]0.784317[/C][/ROW]
[ROW][C]21[/C][C]0.17346[/C][C]0.34692[/C][C]0.82654[/C][/ROW]
[ROW][C]22[/C][C]0.140576[/C][C]0.281152[/C][C]0.859424[/C][/ROW]
[ROW][C]23[/C][C]0.108878[/C][C]0.217756[/C][C]0.891122[/C][/ROW]
[ROW][C]24[/C][C]0.0846274[/C][C]0.169255[/C][C]0.915373[/C][/ROW]
[ROW][C]25[/C][C]0.0598763[/C][C]0.119753[/C][C]0.940124[/C][/ROW]
[ROW][C]26[/C][C]0.0426179[/C][C]0.0852358[/C][C]0.957382[/C][/ROW]
[ROW][C]27[/C][C]0.0337548[/C][C]0.0675096[/C][C]0.966245[/C][/ROW]
[ROW][C]28[/C][C]0.029408[/C][C]0.0588159[/C][C]0.970592[/C][/ROW]
[ROW][C]29[/C][C]0.0389395[/C][C]0.077879[/C][C]0.96106[/C][/ROW]
[ROW][C]30[/C][C]0.0302148[/C][C]0.0604295[/C][C]0.969785[/C][/ROW]
[ROW][C]31[/C][C]0.0226018[/C][C]0.0452035[/C][C]0.977398[/C][/ROW]
[ROW][C]32[/C][C]0.0214232[/C][C]0.0428464[/C][C]0.978577[/C][/ROW]
[ROW][C]33[/C][C]0.0159141[/C][C]0.0318281[/C][C]0.984086[/C][/ROW]
[ROW][C]34[/C][C]0.0107127[/C][C]0.0214254[/C][C]0.989287[/C][/ROW]
[ROW][C]35[/C][C]0.00796527[/C][C]0.0159305[/C][C]0.992035[/C][/ROW]
[ROW][C]36[/C][C]0.00701411[/C][C]0.0140282[/C][C]0.992986[/C][/ROW]
[ROW][C]37[/C][C]0.00502988[/C][C]0.0100598[/C][C]0.99497[/C][/ROW]
[ROW][C]38[/C][C]0.00315305[/C][C]0.0063061[/C][C]0.996847[/C][/ROW]
[ROW][C]39[/C][C]0.00218462[/C][C]0.00436924[/C][C]0.997815[/C][/ROW]
[ROW][C]40[/C][C]0.00148864[/C][C]0.00297727[/C][C]0.998511[/C][/ROW]
[ROW][C]41[/C][C]0.000907173[/C][C]0.00181435[/C][C]0.999093[/C][/ROW]
[ROW][C]42[/C][C]0.00098465[/C][C]0.0019693[/C][C]0.999015[/C][/ROW]
[ROW][C]43[/C][C]0.000960837[/C][C]0.00192167[/C][C]0.999039[/C][/ROW]
[ROW][C]44[/C][C]0.00062399[/C][C]0.00124798[/C][C]0.999376[/C][/ROW]
[ROW][C]45[/C][C]0.000396222[/C][C]0.000792444[/C][C]0.999604[/C][/ROW]
[ROW][C]46[/C][C]0.000317559[/C][C]0.000635117[/C][C]0.999682[/C][/ROW]
[ROW][C]47[/C][C]0.000278458[/C][C]0.000556916[/C][C]0.999722[/C][/ROW]
[ROW][C]48[/C][C]0.000232937[/C][C]0.000465874[/C][C]0.999767[/C][/ROW]
[ROW][C]49[/C][C]0.000138833[/C][C]0.000277665[/C][C]0.999861[/C][/ROW]
[ROW][C]50[/C][C]0.000234613[/C][C]0.000469226[/C][C]0.999765[/C][/ROW]
[ROW][C]51[/C][C]0.000171772[/C][C]0.000343544[/C][C]0.999828[/C][/ROW]
[ROW][C]52[/C][C]0.000141348[/C][C]0.000282697[/C][C]0.999859[/C][/ROW]
[ROW][C]53[/C][C]9.84732e-05[/C][C]0.000196946[/C][C]0.999902[/C][/ROW]
[ROW][C]54[/C][C]8.48677e-05[/C][C]0.000169735[/C][C]0.999915[/C][/ROW]
[ROW][C]55[/C][C]6.25033e-05[/C][C]0.000125007[/C][C]0.999937[/C][/ROW]
[ROW][C]56[/C][C]0.000108706[/C][C]0.000217413[/C][C]0.999891[/C][/ROW]
[ROW][C]57[/C][C]7.30117e-05[/C][C]0.000146023[/C][C]0.999927[/C][/ROW]
[ROW][C]58[/C][C]5.13477e-05[/C][C]0.000102695[/C][C]0.999949[/C][/ROW]
[ROW][C]59[/C][C]3.31121e-05[/C][C]6.62242e-05[/C][C]0.999967[/C][/ROW]
[ROW][C]60[/C][C]4.26177e-05[/C][C]8.52354e-05[/C][C]0.999957[/C][/ROW]
[ROW][C]61[/C][C]3.44952e-05[/C][C]6.89904e-05[/C][C]0.999966[/C][/ROW]
[ROW][C]62[/C][C]3.13103e-05[/C][C]6.26206e-05[/C][C]0.999969[/C][/ROW]
[ROW][C]63[/C][C]6.36024e-05[/C][C]0.000127205[/C][C]0.999936[/C][/ROW]
[ROW][C]64[/C][C]0.000112028[/C][C]0.000224056[/C][C]0.999888[/C][/ROW]
[ROW][C]65[/C][C]9.72825e-05[/C][C]0.000194565[/C][C]0.999903[/C][/ROW]
[ROW][C]66[/C][C]0.000115108[/C][C]0.000230216[/C][C]0.999885[/C][/ROW]
[ROW][C]67[/C][C]0.000209574[/C][C]0.000419149[/C][C]0.99979[/C][/ROW]
[ROW][C]68[/C][C]0.000136968[/C][C]0.000273936[/C][C]0.999863[/C][/ROW]
[ROW][C]69[/C][C]0.000124265[/C][C]0.000248531[/C][C]0.999876[/C][/ROW]
[ROW][C]70[/C][C]0.000568435[/C][C]0.00113687[/C][C]0.999432[/C][/ROW]
[ROW][C]71[/C][C]0.000831295[/C][C]0.00166259[/C][C]0.999169[/C][/ROW]
[ROW][C]72[/C][C]0.000588068[/C][C]0.00117614[/C][C]0.999412[/C][/ROW]
[ROW][C]73[/C][C]0.00058022[/C][C]0.00116044[/C][C]0.99942[/C][/ROW]
[ROW][C]74[/C][C]0.000523582[/C][C]0.00104716[/C][C]0.999476[/C][/ROW]
[ROW][C]75[/C][C]0.000388601[/C][C]0.000777202[/C][C]0.999611[/C][/ROW]
[ROW][C]76[/C][C]0.000337906[/C][C]0.000675811[/C][C]0.999662[/C][/ROW]
[ROW][C]77[/C][C]0.00028083[/C][C]0.000561661[/C][C]0.999719[/C][/ROW]
[ROW][C]78[/C][C]0.000351177[/C][C]0.000702355[/C][C]0.999649[/C][/ROW]
[ROW][C]79[/C][C]0.000529172[/C][C]0.00105834[/C][C]0.999471[/C][/ROW]
[ROW][C]80[/C][C]0.000424526[/C][C]0.000849052[/C][C]0.999575[/C][/ROW]
[ROW][C]81[/C][C]0.000939727[/C][C]0.00187945[/C][C]0.99906[/C][/ROW]
[ROW][C]82[/C][C]0.0012253[/C][C]0.00245061[/C][C]0.998775[/C][/ROW]
[ROW][C]83[/C][C]0.000899657[/C][C]0.00179931[/C][C]0.9991[/C][/ROW]
[ROW][C]84[/C][C]0.000745847[/C][C]0.00149169[/C][C]0.999254[/C][/ROW]
[ROW][C]85[/C][C]0.000829644[/C][C]0.00165929[/C][C]0.99917[/C][/ROW]
[ROW][C]86[/C][C]0.00060434[/C][C]0.00120868[/C][C]0.999396[/C][/ROW]
[ROW][C]87[/C][C]0.000523785[/C][C]0.00104757[/C][C]0.999476[/C][/ROW]
[ROW][C]88[/C][C]0.00040543[/C][C]0.00081086[/C][C]0.999595[/C][/ROW]
[ROW][C]89[/C][C]0.000337714[/C][C]0.000675427[/C][C]0.999662[/C][/ROW]
[ROW][C]90[/C][C]0.000241542[/C][C]0.000483083[/C][C]0.999758[/C][/ROW]
[ROW][C]91[/C][C]0.000773726[/C][C]0.00154745[/C][C]0.999226[/C][/ROW]
[ROW][C]92[/C][C]0.000647028[/C][C]0.00129406[/C][C]0.999353[/C][/ROW]
[ROW][C]93[/C][C]0.00151318[/C][C]0.00302635[/C][C]0.998487[/C][/ROW]
[ROW][C]94[/C][C]0.00111217[/C][C]0.00222433[/C][C]0.998888[/C][/ROW]
[ROW][C]95[/C][C]0.00105731[/C][C]0.00211461[/C][C]0.998943[/C][/ROW]
[ROW][C]96[/C][C]0.0042002[/C][C]0.0084004[/C][C]0.9958[/C][/ROW]
[ROW][C]97[/C][C]0.00341297[/C][C]0.00682594[/C][C]0.996587[/C][/ROW]
[ROW][C]98[/C][C]0.0049425[/C][C]0.00988501[/C][C]0.995057[/C][/ROW]
[ROW][C]99[/C][C]0.00883866[/C][C]0.0176773[/C][C]0.991161[/C][/ROW]
[ROW][C]100[/C][C]0.014339[/C][C]0.0286781[/C][C]0.985661[/C][/ROW]
[ROW][C]101[/C][C]0.0158809[/C][C]0.0317619[/C][C]0.984119[/C][/ROW]
[ROW][C]102[/C][C]0.0158079[/C][C]0.0316159[/C][C]0.984192[/C][/ROW]
[ROW][C]103[/C][C]0.0192083[/C][C]0.0384167[/C][C]0.980792[/C][/ROW]
[ROW][C]104[/C][C]0.0153625[/C][C]0.030725[/C][C]0.984637[/C][/ROW]
[ROW][C]105[/C][C]0.019955[/C][C]0.0399101[/C][C]0.980045[/C][/ROW]
[ROW][C]106[/C][C]0.0188542[/C][C]0.0377084[/C][C]0.981146[/C][/ROW]
[ROW][C]107[/C][C]0.0234534[/C][C]0.0469068[/C][C]0.976547[/C][/ROW]
[ROW][C]108[/C][C]0.0217572[/C][C]0.0435145[/C][C]0.978243[/C][/ROW]
[ROW][C]109[/C][C]0.0222625[/C][C]0.0445249[/C][C]0.977738[/C][/ROW]
[ROW][C]110[/C][C]0.0214341[/C][C]0.0428683[/C][C]0.978566[/C][/ROW]
[ROW][C]111[/C][C]0.02385[/C][C]0.0477[/C][C]0.97615[/C][/ROW]
[ROW][C]112[/C][C]0.0194463[/C][C]0.0388926[/C][C]0.980554[/C][/ROW]
[ROW][C]113[/C][C]0.0178641[/C][C]0.0357281[/C][C]0.982136[/C][/ROW]
[ROW][C]114[/C][C]0.0316851[/C][C]0.0633701[/C][C]0.968315[/C][/ROW]
[ROW][C]115[/C][C]0.0391807[/C][C]0.0783613[/C][C]0.960819[/C][/ROW]
[ROW][C]116[/C][C]0.0331536[/C][C]0.0663073[/C][C]0.966846[/C][/ROW]
[ROW][C]117[/C][C]0.0322542[/C][C]0.0645084[/C][C]0.967746[/C][/ROW]
[ROW][C]118[/C][C]0.130626[/C][C]0.261253[/C][C]0.869374[/C][/ROW]
[ROW][C]119[/C][C]0.426323[/C][C]0.852646[/C][C]0.573677[/C][/ROW]
[ROW][C]120[/C][C]0.427838[/C][C]0.855676[/C][C]0.572162[/C][/ROW]
[ROW][C]121[/C][C]0.43295[/C][C]0.865899[/C][C]0.56705[/C][/ROW]
[ROW][C]122[/C][C]0.492988[/C][C]0.985975[/C][C]0.507012[/C][/ROW]
[ROW][C]123[/C][C]0.497392[/C][C]0.994785[/C][C]0.502608[/C][/ROW]
[ROW][C]124[/C][C]0.483717[/C][C]0.967435[/C][C]0.516283[/C][/ROW]
[ROW][C]125[/C][C]0.555387[/C][C]0.889225[/C][C]0.444613[/C][/ROW]
[ROW][C]126[/C][C]0.647884[/C][C]0.704233[/C][C]0.352116[/C][/ROW]
[ROW][C]127[/C][C]0.764369[/C][C]0.471262[/C][C]0.235631[/C][/ROW]
[ROW][C]128[/C][C]0.80183[/C][C]0.39634[/C][C]0.19817[/C][/ROW]
[ROW][C]129[/C][C]0.846187[/C][C]0.307627[/C][C]0.153813[/C][/ROW]
[ROW][C]130[/C][C]0.900626[/C][C]0.198748[/C][C]0.0993741[/C][/ROW]
[ROW][C]131[/C][C]0.920063[/C][C]0.159873[/C][C]0.0799366[/C][/ROW]
[ROW][C]132[/C][C]0.931422[/C][C]0.137156[/C][C]0.0685778[/C][/ROW]
[ROW][C]133[/C][C]0.948305[/C][C]0.103391[/C][C]0.0516953[/C][/ROW]
[ROW][C]134[/C][C]0.960366[/C][C]0.0792687[/C][C]0.0396344[/C][/ROW]
[ROW][C]135[/C][C]0.963523[/C][C]0.0729544[/C][C]0.0364772[/C][/ROW]
[ROW][C]136[/C][C]0.965408[/C][C]0.0691833[/C][C]0.0345917[/C][/ROW]
[ROW][C]137[/C][C]0.966693[/C][C]0.0666136[/C][C]0.0333068[/C][/ROW]
[ROW][C]138[/C][C]0.961173[/C][C]0.0776543[/C][C]0.0388271[/C][/ROW]
[ROW][C]139[/C][C]0.957225[/C][C]0.0855491[/C][C]0.0427746[/C][/ROW]
[ROW][C]140[/C][C]0.952491[/C][C]0.095017[/C][C]0.0475085[/C][/ROW]
[ROW][C]141[/C][C]0.961934[/C][C]0.0761322[/C][C]0.0380661[/C][/ROW]
[ROW][C]142[/C][C]0.965458[/C][C]0.0690849[/C][C]0.0345424[/C][/ROW]
[ROW][C]143[/C][C]0.96523[/C][C]0.0695393[/C][C]0.0347697[/C][/ROW]
[ROW][C]144[/C][C]0.960466[/C][C]0.0790676[/C][C]0.0395338[/C][/ROW]
[ROW][C]145[/C][C]0.984808[/C][C]0.0303849[/C][C]0.0151924[/C][/ROW]
[ROW][C]146[/C][C]0.988032[/C][C]0.023936[/C][C]0.011968[/C][/ROW]
[ROW][C]147[/C][C]0.995029[/C][C]0.00994108[/C][C]0.00497054[/C][/ROW]
[ROW][C]148[/C][C]0.998144[/C][C]0.00371129[/C][C]0.00185565[/C][/ROW]
[ROW][C]149[/C][C]0.998511[/C][C]0.00297706[/C][C]0.00148853[/C][/ROW]
[ROW][C]150[/C][C]0.99915[/C][C]0.00169993[/C][C]0.000849967[/C][/ROW]
[ROW][C]151[/C][C]0.998955[/C][C]0.00208955[/C][C]0.00104478[/C][/ROW]
[ROW][C]152[/C][C]0.999723[/C][C]0.000554489[/C][C]0.000277244[/C][/ROW]
[ROW][C]153[/C][C]0.999627[/C][C]0.000746872[/C][C]0.000373436[/C][/ROW]
[ROW][C]154[/C][C]0.999725[/C][C]0.000550462[/C][C]0.000275231[/C][/ROW]
[ROW][C]155[/C][C]0.999712[/C][C]0.000575576[/C][C]0.000287788[/C][/ROW]
[ROW][C]156[/C][C]0.999903[/C][C]0.000194648[/C][C]9.73239e-05[/C][/ROW]
[ROW][C]157[/C][C]0.999864[/C][C]0.000271464[/C][C]0.000135732[/C][/ROW]
[ROW][C]158[/C][C]0.999853[/C][C]0.000293861[/C][C]0.00014693[/C][/ROW]
[ROW][C]159[/C][C]0.999815[/C][C]0.000369999[/C][C]0.000184999[/C][/ROW]
[ROW][C]160[/C][C]0.999762[/C][C]0.0004755[/C][C]0.00023775[/C][/ROW]
[ROW][C]161[/C][C]0.999759[/C][C]0.000481477[/C][C]0.000240739[/C][/ROW]
[ROW][C]162[/C][C]0.99977[/C][C]0.000460212[/C][C]0.000230106[/C][/ROW]
[ROW][C]163[/C][C]0.999681[/C][C]0.000637609[/C][C]0.000318804[/C][/ROW]
[ROW][C]164[/C][C]0.999607[/C][C]0.000785481[/C][C]0.00039274[/C][/ROW]
[ROW][C]165[/C][C]0.999464[/C][C]0.00107109[/C][C]0.000535545[/C][/ROW]
[ROW][C]166[/C][C]0.999435[/C][C]0.00112994[/C][C]0.000564969[/C][/ROW]
[ROW][C]167[/C][C]0.999517[/C][C]0.000965379[/C][C]0.00048269[/C][/ROW]
[ROW][C]168[/C][C]0.999609[/C][C]0.00078223[/C][C]0.000391115[/C][/ROW]
[ROW][C]169[/C][C]0.999821[/C][C]0.000357624[/C][C]0.000178812[/C][/ROW]
[ROW][C]170[/C][C]0.999783[/C][C]0.000433134[/C][C]0.000216567[/C][/ROW]
[ROW][C]171[/C][C]0.999819[/C][C]0.00036252[/C][C]0.00018126[/C][/ROW]
[ROW][C]172[/C][C]0.999967[/C][C]6.53724e-05[/C][C]3.26862e-05[/C][/ROW]
[ROW][C]173[/C][C]0.999974[/C][C]5.15309e-05[/C][C]2.57654e-05[/C][/ROW]
[ROW][C]174[/C][C]0.999971[/C][C]5.70999e-05[/C][C]2.855e-05[/C][/ROW]
[ROW][C]175[/C][C]0.999964[/C][C]7.17872e-05[/C][C]3.58936e-05[/C][/ROW]
[ROW][C]176[/C][C]0.999984[/C][C]3.27708e-05[/C][C]1.63854e-05[/C][/ROW]
[ROW][C]177[/C][C]0.999977[/C][C]4.59406e-05[/C][C]2.29703e-05[/C][/ROW]
[ROW][C]178[/C][C]0.999984[/C][C]3.24242e-05[/C][C]1.62121e-05[/C][/ROW]
[ROW][C]179[/C][C]0.999983[/C][C]3.40603e-05[/C][C]1.70301e-05[/C][/ROW]
[ROW][C]180[/C][C]0.999984[/C][C]3.18715e-05[/C][C]1.59357e-05[/C][/ROW]
[ROW][C]181[/C][C]0.999976[/C][C]4.75008e-05[/C][C]2.37504e-05[/C][/ROW]
[ROW][C]182[/C][C]0.999965[/C][C]6.9595e-05[/C][C]3.47975e-05[/C][/ROW]
[ROW][C]183[/C][C]0.999952[/C][C]9.6132e-05[/C][C]4.8066e-05[/C][/ROW]
[ROW][C]184[/C][C]0.999957[/C][C]8.63419e-05[/C][C]4.3171e-05[/C][/ROW]
[ROW][C]185[/C][C]0.999951[/C][C]9.70126e-05[/C][C]4.85063e-05[/C][/ROW]
[ROW][C]186[/C][C]0.999935[/C][C]0.000130519[/C][C]6.52596e-05[/C][/ROW]
[ROW][C]187[/C][C]0.999912[/C][C]0.000175517[/C][C]8.77584e-05[/C][/ROW]
[ROW][C]188[/C][C]0.999873[/C][C]0.000254509[/C][C]0.000127255[/C][/ROW]
[ROW][C]189[/C][C]0.999827[/C][C]0.000345646[/C][C]0.000172823[/C][/ROW]
[ROW][C]190[/C][C]0.999932[/C][C]0.000136581[/C][C]6.82903e-05[/C][/ROW]
[ROW][C]191[/C][C]0.999899[/C][C]0.000202162[/C][C]0.000101081[/C][/ROW]
[ROW][C]192[/C][C]0.999856[/C][C]0.000287497[/C][C]0.000143748[/C][/ROW]
[ROW][C]193[/C][C]0.999842[/C][C]0.000316398[/C][C]0.000158199[/C][/ROW]
[ROW][C]194[/C][C]0.999875[/C][C]0.00024969[/C][C]0.000124845[/C][/ROW]
[ROW][C]195[/C][C]0.99993[/C][C]0.000140874[/C][C]7.04368e-05[/C][/ROW]
[ROW][C]196[/C][C]0.999928[/C][C]0.00014441[/C][C]7.22049e-05[/C][/ROW]
[ROW][C]197[/C][C]0.999906[/C][C]0.000188009[/C][C]9.40044e-05[/C][/ROW]
[ROW][C]198[/C][C]0.999879[/C][C]0.000242724[/C][C]0.000121362[/C][/ROW]
[ROW][C]199[/C][C]0.999862[/C][C]0.000276472[/C][C]0.000138236[/C][/ROW]
[ROW][C]200[/C][C]0.999805[/C][C]0.000390784[/C][C]0.000195392[/C][/ROW]
[ROW][C]201[/C][C]0.999798[/C][C]0.000404464[/C][C]0.000202232[/C][/ROW]
[ROW][C]202[/C][C]0.999737[/C][C]0.000525983[/C][C]0.000262991[/C][/ROW]
[ROW][C]203[/C][C]0.999771[/C][C]0.000457293[/C][C]0.000228647[/C][/ROW]
[ROW][C]204[/C][C]0.999666[/C][C]0.000667366[/C][C]0.000333683[/C][/ROW]
[ROW][C]205[/C][C]0.999534[/C][C]0.000932424[/C][C]0.000466212[/C][/ROW]
[ROW][C]206[/C][C]0.999929[/C][C]0.000142753[/C][C]7.13763e-05[/C][/ROW]
[ROW][C]207[/C][C]0.999914[/C][C]0.000172038[/C][C]8.60189e-05[/C][/ROW]
[ROW][C]208[/C][C]0.999912[/C][C]0.000176578[/C][C]8.82888e-05[/C][/ROW]
[ROW][C]209[/C][C]0.99987[/C][C]0.000259792[/C][C]0.000129896[/C][/ROW]
[ROW][C]210[/C][C]0.999969[/C][C]6.10116e-05[/C][C]3.05058e-05[/C][/ROW]
[ROW][C]211[/C][C]0.999961[/C][C]7.74693e-05[/C][C]3.87346e-05[/C][/ROW]
[ROW][C]212[/C][C]0.999953[/C][C]9.45867e-05[/C][C]4.72933e-05[/C][/ROW]
[ROW][C]213[/C][C]0.999971[/C][C]5.77326e-05[/C][C]2.88663e-05[/C][/ROW]
[ROW][C]214[/C][C]0.999997[/C][C]5.66953e-06[/C][C]2.83476e-06[/C][/ROW]
[ROW][C]215[/C][C]0.999999[/C][C]2.17572e-06[/C][C]1.08786e-06[/C][/ROW]
[ROW][C]216[/C][C]0.999998[/C][C]3.63861e-06[/C][C]1.8193e-06[/C][/ROW]
[ROW][C]217[/C][C]0.999997[/C][C]5.46949e-06[/C][C]2.73474e-06[/C][/ROW]
[ROW][C]218[/C][C]0.999997[/C][C]6.30736e-06[/C][C]3.15368e-06[/C][/ROW]
[ROW][C]219[/C][C]0.999997[/C][C]6.41211e-06[/C][C]3.20606e-06[/C][/ROW]
[ROW][C]220[/C][C]0.999996[/C][C]8.72648e-06[/C][C]4.36324e-06[/C][/ROW]
[ROW][C]221[/C][C]0.999992[/C][C]1.50359e-05[/C][C]7.51797e-06[/C][/ROW]
[ROW][C]222[/C][C]0.999994[/C][C]1.18704e-05[/C][C]5.93522e-06[/C][/ROW]
[ROW][C]223[/C][C]0.999993[/C][C]1.35188e-05[/C][C]6.75938e-06[/C][/ROW]
[ROW][C]224[/C][C]0.99999[/C][C]1.94951e-05[/C][C]9.74753e-06[/C][/ROW]
[ROW][C]225[/C][C]0.999989[/C][C]2.28435e-05[/C][C]1.14217e-05[/C][/ROW]
[ROW][C]226[/C][C]0.999981[/C][C]3.71124e-05[/C][C]1.85562e-05[/C][/ROW]
[ROW][C]227[/C][C]0.999974[/C][C]5.26395e-05[/C][C]2.63198e-05[/C][/ROW]
[ROW][C]228[/C][C]0.999962[/C][C]7.626e-05[/C][C]3.813e-05[/C][/ROW]
[ROW][C]229[/C][C]0.999944[/C][C]0.000112133[/C][C]5.60663e-05[/C][/ROW]
[ROW][C]230[/C][C]0.999921[/C][C]0.000158385[/C][C]7.91926e-05[/C][/ROW]
[ROW][C]231[/C][C]0.999927[/C][C]0.000145052[/C][C]7.25259e-05[/C][/ROW]
[ROW][C]232[/C][C]0.999966[/C][C]6.75476e-05[/C][C]3.37738e-05[/C][/ROW]
[ROW][C]233[/C][C]0.999945[/C][C]0.000110281[/C][C]5.51405e-05[/C][/ROW]
[ROW][C]234[/C][C]0.999917[/C][C]0.000166032[/C][C]8.30158e-05[/C][/ROW]
[ROW][C]235[/C][C]0.999893[/C][C]0.000213075[/C][C]0.000106537[/C][/ROW]
[ROW][C]236[/C][C]0.999839[/C][C]0.00032188[/C][C]0.00016094[/C][/ROW]
[ROW][C]237[/C][C]0.999793[/C][C]0.000414525[/C][C]0.000207262[/C][/ROW]
[ROW][C]238[/C][C]0.999737[/C][C]0.000525819[/C][C]0.000262909[/C][/ROW]
[ROW][C]239[/C][C]0.999562[/C][C]0.000875969[/C][C]0.000437984[/C][/ROW]
[ROW][C]240[/C][C]0.999465[/C][C]0.00107065[/C][C]0.000535327[/C][/ROW]
[ROW][C]241[/C][C]0.999461[/C][C]0.00107716[/C][C]0.000538579[/C][/ROW]
[ROW][C]242[/C][C]0.999188[/C][C]0.00162498[/C][C]0.000812489[/C][/ROW]
[ROW][C]243[/C][C]0.998709[/C][C]0.00258261[/C][C]0.00129131[/C][/ROW]
[ROW][C]244[/C][C]0.998332[/C][C]0.00333549[/C][C]0.00166774[/C][/ROW]
[ROW][C]245[/C][C]0.99748[/C][C]0.00504076[/C][C]0.00252038[/C][/ROW]
[ROW][C]246[/C][C]0.996344[/C][C]0.00731258[/C][C]0.00365629[/C][/ROW]
[ROW][C]247[/C][C]0.995266[/C][C]0.00946766[/C][C]0.00473383[/C][/ROW]
[ROW][C]248[/C][C]0.992625[/C][C]0.0147508[/C][C]0.00737538[/C][/ROW]
[ROW][C]249[/C][C]0.993801[/C][C]0.0123982[/C][C]0.00619909[/C][/ROW]
[ROW][C]250[/C][C]0.992737[/C][C]0.0145251[/C][C]0.00726257[/C][/ROW]
[ROW][C]251[/C][C]0.990392[/C][C]0.0192158[/C][C]0.00960792[/C][/ROW]
[ROW][C]252[/C][C]0.988606[/C][C]0.0227877[/C][C]0.0113938[/C][/ROW]
[ROW][C]253[/C][C]0.984182[/C][C]0.0316353[/C][C]0.0158176[/C][/ROW]
[ROW][C]254[/C][C]0.975859[/C][C]0.0482825[/C][C]0.0241412[/C][/ROW]
[ROW][C]255[/C][C]0.97337[/C][C]0.0532604[/C][C]0.0266302[/C][/ROW]
[ROW][C]256[/C][C]0.962936[/C][C]0.0741271[/C][C]0.0370635[/C][/ROW]
[ROW][C]257[/C][C]0.958033[/C][C]0.0839344[/C][C]0.0419672[/C][/ROW]
[ROW][C]258[/C][C]0.954064[/C][C]0.0918714[/C][C]0.0459357[/C][/ROW]
[ROW][C]259[/C][C]0.945485[/C][C]0.109031[/C][C]0.0545153[/C][/ROW]
[ROW][C]260[/C][C]0.925561[/C][C]0.148879[/C][C]0.0744394[/C][/ROW]
[ROW][C]261[/C][C]0.90908[/C][C]0.181841[/C][C]0.0909205[/C][/ROW]
[ROW][C]262[/C][C]0.881533[/C][C]0.236933[/C][C]0.118467[/C][/ROW]
[ROW][C]263[/C][C]0.880232[/C][C]0.239537[/C][C]0.119768[/C][/ROW]
[ROW][C]264[/C][C]0.836587[/C][C]0.326827[/C][C]0.163413[/C][/ROW]
[ROW][C]265[/C][C]0.840749[/C][C]0.318503[/C][C]0.159251[/C][/ROW]
[ROW][C]266[/C][C]0.833143[/C][C]0.333715[/C][C]0.166857[/C][/ROW]
[ROW][C]267[/C][C]0.806281[/C][C]0.387438[/C][C]0.193719[/C][/ROW]
[ROW][C]268[/C][C]0.742669[/C][C]0.514662[/C][C]0.257331[/C][/ROW]
[ROW][C]269[/C][C]0.673453[/C][C]0.653094[/C][C]0.326547[/C][/ROW]
[ROW][C]270[/C][C]0.572125[/C][C]0.855749[/C][C]0.427875[/C][/ROW]
[ROW][C]271[/C][C]0.634278[/C][C]0.731444[/C][C]0.365722[/C][/ROW]
[ROW][C]272[/C][C]0.492083[/C][C]0.984166[/C][C]0.507917[/C][/ROW]
[ROW][C]273[/C][C]0.422986[/C][C]0.845971[/C][C]0.577014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268251&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268251&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.3710020.7420030.628998
140.2588240.5176490.741176
150.1851520.3703050.814848
160.1129730.2259450.887027
170.4040270.8080540.595973
180.3225410.6450820.677459
190.2489070.4978130.751093
200.2156830.4313670.784317
210.173460.346920.82654
220.1405760.2811520.859424
230.1088780.2177560.891122
240.08462740.1692550.915373
250.05987630.1197530.940124
260.04261790.08523580.957382
270.03375480.06750960.966245
280.0294080.05881590.970592
290.03893950.0778790.96106
300.03021480.06042950.969785
310.02260180.04520350.977398
320.02142320.04284640.978577
330.01591410.03182810.984086
340.01071270.02142540.989287
350.007965270.01593050.992035
360.007014110.01402820.992986
370.005029880.01005980.99497
380.003153050.00630610.996847
390.002184620.004369240.997815
400.001488640.002977270.998511
410.0009071730.001814350.999093
420.000984650.00196930.999015
430.0009608370.001921670.999039
440.000623990.001247980.999376
450.0003962220.0007924440.999604
460.0003175590.0006351170.999682
470.0002784580.0005569160.999722
480.0002329370.0004658740.999767
490.0001388330.0002776650.999861
500.0002346130.0004692260.999765
510.0001717720.0003435440.999828
520.0001413480.0002826970.999859
539.84732e-050.0001969460.999902
548.48677e-050.0001697350.999915
556.25033e-050.0001250070.999937
560.0001087060.0002174130.999891
577.30117e-050.0001460230.999927
585.13477e-050.0001026950.999949
593.31121e-056.62242e-050.999967
604.26177e-058.52354e-050.999957
613.44952e-056.89904e-050.999966
623.13103e-056.26206e-050.999969
636.36024e-050.0001272050.999936
640.0001120280.0002240560.999888
659.72825e-050.0001945650.999903
660.0001151080.0002302160.999885
670.0002095740.0004191490.99979
680.0001369680.0002739360.999863
690.0001242650.0002485310.999876
700.0005684350.001136870.999432
710.0008312950.001662590.999169
720.0005880680.001176140.999412
730.000580220.001160440.99942
740.0005235820.001047160.999476
750.0003886010.0007772020.999611
760.0003379060.0006758110.999662
770.000280830.0005616610.999719
780.0003511770.0007023550.999649
790.0005291720.001058340.999471
800.0004245260.0008490520.999575
810.0009397270.001879450.99906
820.00122530.002450610.998775
830.0008996570.001799310.9991
840.0007458470.001491690.999254
850.0008296440.001659290.99917
860.000604340.001208680.999396
870.0005237850.001047570.999476
880.000405430.000810860.999595
890.0003377140.0006754270.999662
900.0002415420.0004830830.999758
910.0007737260.001547450.999226
920.0006470280.001294060.999353
930.001513180.003026350.998487
940.001112170.002224330.998888
950.001057310.002114610.998943
960.00420020.00840040.9958
970.003412970.006825940.996587
980.00494250.009885010.995057
990.008838660.01767730.991161
1000.0143390.02867810.985661
1010.01588090.03176190.984119
1020.01580790.03161590.984192
1030.01920830.03841670.980792
1040.01536250.0307250.984637
1050.0199550.03991010.980045
1060.01885420.03770840.981146
1070.02345340.04690680.976547
1080.02175720.04351450.978243
1090.02226250.04452490.977738
1100.02143410.04286830.978566
1110.023850.04770.97615
1120.01944630.03889260.980554
1130.01786410.03572810.982136
1140.03168510.06337010.968315
1150.03918070.07836130.960819
1160.03315360.06630730.966846
1170.03225420.06450840.967746
1180.1306260.2612530.869374
1190.4263230.8526460.573677
1200.4278380.8556760.572162
1210.432950.8658990.56705
1220.4929880.9859750.507012
1230.4973920.9947850.502608
1240.4837170.9674350.516283
1250.5553870.8892250.444613
1260.6478840.7042330.352116
1270.7643690.4712620.235631
1280.801830.396340.19817
1290.8461870.3076270.153813
1300.9006260.1987480.0993741
1310.9200630.1598730.0799366
1320.9314220.1371560.0685778
1330.9483050.1033910.0516953
1340.9603660.07926870.0396344
1350.9635230.07295440.0364772
1360.9654080.06918330.0345917
1370.9666930.06661360.0333068
1380.9611730.07765430.0388271
1390.9572250.08554910.0427746
1400.9524910.0950170.0475085
1410.9619340.07613220.0380661
1420.9654580.06908490.0345424
1430.965230.06953930.0347697
1440.9604660.07906760.0395338
1450.9848080.03038490.0151924
1460.9880320.0239360.011968
1470.9950290.009941080.00497054
1480.9981440.003711290.00185565
1490.9985110.002977060.00148853
1500.999150.001699930.000849967
1510.9989550.002089550.00104478
1520.9997230.0005544890.000277244
1530.9996270.0007468720.000373436
1540.9997250.0005504620.000275231
1550.9997120.0005755760.000287788
1560.9999030.0001946489.73239e-05
1570.9998640.0002714640.000135732
1580.9998530.0002938610.00014693
1590.9998150.0003699990.000184999
1600.9997620.00047550.00023775
1610.9997590.0004814770.000240739
1620.999770.0004602120.000230106
1630.9996810.0006376090.000318804
1640.9996070.0007854810.00039274
1650.9994640.001071090.000535545
1660.9994350.001129940.000564969
1670.9995170.0009653790.00048269
1680.9996090.000782230.000391115
1690.9998210.0003576240.000178812
1700.9997830.0004331340.000216567
1710.9998190.000362520.00018126
1720.9999676.53724e-053.26862e-05
1730.9999745.15309e-052.57654e-05
1740.9999715.70999e-052.855e-05
1750.9999647.17872e-053.58936e-05
1760.9999843.27708e-051.63854e-05
1770.9999774.59406e-052.29703e-05
1780.9999843.24242e-051.62121e-05
1790.9999833.40603e-051.70301e-05
1800.9999843.18715e-051.59357e-05
1810.9999764.75008e-052.37504e-05
1820.9999656.9595e-053.47975e-05
1830.9999529.6132e-054.8066e-05
1840.9999578.63419e-054.3171e-05
1850.9999519.70126e-054.85063e-05
1860.9999350.0001305196.52596e-05
1870.9999120.0001755178.77584e-05
1880.9998730.0002545090.000127255
1890.9998270.0003456460.000172823
1900.9999320.0001365816.82903e-05
1910.9998990.0002021620.000101081
1920.9998560.0002874970.000143748
1930.9998420.0003163980.000158199
1940.9998750.000249690.000124845
1950.999930.0001408747.04368e-05
1960.9999280.000144417.22049e-05
1970.9999060.0001880099.40044e-05
1980.9998790.0002427240.000121362
1990.9998620.0002764720.000138236
2000.9998050.0003907840.000195392
2010.9997980.0004044640.000202232
2020.9997370.0005259830.000262991
2030.9997710.0004572930.000228647
2040.9996660.0006673660.000333683
2050.9995340.0009324240.000466212
2060.9999290.0001427537.13763e-05
2070.9999140.0001720388.60189e-05
2080.9999120.0001765788.82888e-05
2090.999870.0002597920.000129896
2100.9999696.10116e-053.05058e-05
2110.9999617.74693e-053.87346e-05
2120.9999539.45867e-054.72933e-05
2130.9999715.77326e-052.88663e-05
2140.9999975.66953e-062.83476e-06
2150.9999992.17572e-061.08786e-06
2160.9999983.63861e-061.8193e-06
2170.9999975.46949e-062.73474e-06
2180.9999976.30736e-063.15368e-06
2190.9999976.41211e-063.20606e-06
2200.9999968.72648e-064.36324e-06
2210.9999921.50359e-057.51797e-06
2220.9999941.18704e-055.93522e-06
2230.9999931.35188e-056.75938e-06
2240.999991.94951e-059.74753e-06
2250.9999892.28435e-051.14217e-05
2260.9999813.71124e-051.85562e-05
2270.9999745.26395e-052.63198e-05
2280.9999627.626e-053.813e-05
2290.9999440.0001121335.60663e-05
2300.9999210.0001583857.91926e-05
2310.9999270.0001450527.25259e-05
2320.9999666.75476e-053.37738e-05
2330.9999450.0001102815.51405e-05
2340.9999170.0001660328.30158e-05
2350.9998930.0002130750.000106537
2360.9998390.000321880.00016094
2370.9997930.0004145250.000207262
2380.9997370.0005258190.000262909
2390.9995620.0008759690.000437984
2400.9994650.001070650.000535327
2410.9994610.001077160.000538579
2420.9991880.001624980.000812489
2430.9987090.002582610.00129131
2440.9983320.003335490.00166774
2450.997480.005040760.00252038
2460.9963440.007312580.00365629
2470.9952660.009467660.00473383
2480.9926250.01475080.00737538
2490.9938010.01239820.00619909
2500.9927370.01452510.00726257
2510.9903920.01921580.00960792
2520.9886060.02278770.0113938
2530.9841820.03163530.0158176
2540.9758590.04828250.0241412
2550.973370.05326040.0266302
2560.9629360.07412710.0370635
2570.9580330.08393440.0419672
2580.9540640.09187140.0459357
2590.9454850.1090310.0545153
2600.9255610.1488790.0744394
2610.909080.1818410.0909205
2620.8815330.2369330.118467
2630.8802320.2395370.119768
2640.8365870.3268270.163413
2650.8407490.3185030.159251
2660.8331430.3337150.166857
2670.8062810.3874380.193719
2680.7426690.5146620.257331
2690.6734530.6530940.326547
2700.5721250.8557490.427875
2710.6342780.7314440.365722
2720.4920830.9841660.507917
2730.4229860.8459710.577014






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1620.62069NOK
5% type I error level1930.739464NOK
10% type I error level2170.831418NOK

\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 & 162 & 0.62069 & NOK \tabularnewline
5% type I error level & 193 & 0.739464 & NOK \tabularnewline
10% type I error level & 217 & 0.831418 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268251&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]162[/C][C]0.62069[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]193[/C][C]0.739464[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]217[/C][C]0.831418[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268251&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268251&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1620.62069NOK
5% type I error level1930.739464NOK
10% type I error level2170.831418NOK


Figures (Output of Computation)

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Input Parameters & R Code

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