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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Sun, 18 Nov 2012 14:13:05 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/18/t135326601162ak0ee2h5lc4eb.htm/, Retrieved Mon, 29 Apr 2024 18:38:50 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=190339, Retrieved Mon, 29 Apr 2024 18:38:50 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

106

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Multiple Regression] [ws 7 berekening 5] [2012-11-18 19:13:05] [5948b95c00a54abd73f88aac58cf0e09] [Current]

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Boxplots

1	1	1	41	41	38	38	13	13	12	14	14	12	12	53	53
1	2	2	39	39	32	32	16	16	11	18	18	11	11	83	83
1	3	3	30	30	35	35	19	19	15	11	11	14	14	66	66
1	4	4	31	31	33	33	15	15	6	12	12	12	12	67	67
1	5	5	34	34	37	37	14	14	13	16	16	21	21	76	76
1	6	6	35	35	29	29	13	13	10	18	18	12	12	78	78
1	7	7	39	39	31	31	19	19	12	14	14	22	22	53	53
1	8	8	34	34	36	36	15	15	14	14	14	11	11	80	80
1	9	9	36	36	35	35	14	14	12	15	15	10	10	74	74
1	10	10	37	37	38	38	15	15	9	15	15	13	13	76	76
1	11	11	38	38	31	31	16	16	10	17	17	10	10	79	79
1	12	12	36	36	34	34	16	16	12	19	19	8	8	54	54
1	13	13	38	38	35	35	16	16	12	10	10	15	15	67	67
1	14	14	39	39	38	38	16	16	11	16	16	14	14	54	54
1	15	15	33	33	37	37	17	17	15	18	18	10	10	87	87
1	16	16	32	32	33	33	15	15	12	14	14	14	14	58	58
1	17	17	36	36	32	32	15	15	10	14	14	14	14	75	75
1	18	18	38	38	38	38	20	20	12	17	17	11	11	88	88
1	19	19	39	39	38	38	18	18	11	14	14	10	10	64	64
1	20	20	32	32	32	32	16	16	12	16	16	13	13	57	57
1	21	21	32	32	33	33	16	16	11	18	18	9.5	9.5	66	66
1	22	22	31	31	31	31	16	16	12	11	11	14	14	68	68
1	23	23	39	39	38	38	19	19	13	14	14	12	12	54	54
1	24	24	37	37	39	39	16	16	11	12	12	14	14	56	56
1	25	25	39	39	32	32	17	17	12	17	17	11	11	86	86
1	26	26	41	41	32	32	17	17	13	9	9	9	9	80	80
1	27	27	36	36	35	35	16	16	10	16	16	11	11	76	76
1	28	28	33	33	37	37	15	15	14	14	14	15	15	69	69
1	29	29	33	33	33	33	16	16	12	15	15	14	14	78	78
1	30	30	34	34	33	33	14	14	10	11	11	13	13	67	67
1	31	31	31	31	31	31	15	15	12	16	16	9	9	80	80
1	32	32	27	27	32	32	12	12	8	13	13	15	15	54	54
1	33	33	37	37	31	31	14	14	10	17	17	10	10	71	71
1	34	34	34	34	37	37	16	16	12	15	15	11	11	84	84
1	35	35	34	34	30	30	14	14	12	14	14	13	13	74	74
1	36	36	32	32	33	33	10	10	7	16	16	8	8	71	71
1	37	37	29	29	31	31	10	10	9	9	9	20	20	63	63
1	38	38	36	36	33	33	14	14	12	15	15	12	12	71	71
1	39	39	29	29	31	31	16	16	10	17	17	10	10	76	76
1	40	40	35	35	33	33	16	16	10	13	13	10	10	69	69
1	41	41	37	37	32	32	16	16	10	15	15	9	9	74	74
1	42	42	34	34	33	33	14	14	12	16	16	14	14	75	75
1	43	43	38	38	32	32	20	20	15	16	16	8	8	54	54
1	44	44	35	35	33	33	14	14	10	12	12	14	14	52	52
1	45	45	38	38	28	28	14	14	10	15	15	11	11	69	69
1	46	46	37	37	35	35	11	11	12	11	11	13	13	68	68
1	47	47	38	38	39	39	14	14	13	15	15	9	9	65	65
1	48	48	33	33	34	34	15	15	11	15	15	11	11	75	75
1	49	49	36	36	38	38	16	16	11	17	17	15	15	74	74
1	50	50	38	38	32	32	14	14	12	13	13	11	11	75	75
1	51	51	32	32	38	38	16	16	14	16	16	10	10	72	72
1	52	52	32	32	30	30	14	14	10	14	14	14	14	67	67
1	53	53	32	32	33	33	12	12	12	11	11	18	18	63	63
1	54	54	34	34	38	38	16	16	13	12	12	14	14	62	62
1	55	55	32	32	32	32	9	9	5	12	12	11	11	63	63
1	56	56	37	37	35	35	14	14	6	15	15	14.5	14.5	76	76
1	57	57	39	39	34	34	16	16	12	16	16	13	13	74	74
1	58	58	29	29	34	34	16	16	12	15	15	9	9	67	67
1	59	59	37	37	36	36	15	15	11	12	12	10	10	73	73
1	60	60	35	35	34	34	16	16	10	12	12	15	15	70	70
1	61	61	30	30	28	28	12	12	7	8	8	20	20	53	53
1	62	62	38	38	34	34	16	16	12	13	13	12	12	77	77
1	63	63	34	34	35	35	16	16	14	11	11	12	12	80	80
1	64	64	31	31	35	35	14	14	11	14	14	14	14	52	52
1	65	65	34	34	31	31	16	16	12	15	15	13	13	54	54
1	66	66	35	35	37	37	17	17	13	10	10	11	11	80	80
1	67	67	36	36	35	35	18	18	14	11	11	17	17	66	66
1	68	68	30	30	27	27	18	18	11	12	12	12	12	73	73
1	69	69	39	39	40	40	12	12	12	15	15	13	13	63	63
1	70	70	35	35	37	37	16	16	12	15	15	14	14	69	69
1	71	71	38	38	36	36	10	10	8	14	14	13	13	67	67
1	72	72	31	31	38	38	14	14	11	16	16	15	15	54	54
1	73	73	34	34	39	39	18	18	14	15	15	13	13	81	81
1	74	74	38	38	41	41	18	18	14	15	15	10	10	69	69
1	75	75	34	34	27	27	16	16	12	13	13	11	11	84	84
1	76	76	39	39	30	30	17	17	9	12	12	19	19	80	80
1	77	77	37	37	37	37	16	16	13	17	17	13	13	70	70
1	78	78	34	34	31	31	16	16	11	13	13	17	17	69	69
1	79	79	28	28	31	31	13	13	12	15	15	13	13	77	77
1	80	80	37	37	27	27	16	16	12	13	13	9	9	54	54
1	81	81	33	33	36	36	16	16	12	15	15	11	11	79	79
1	82	82	35	35	37	37	16	16	12	15	15	9	9	71	71
1	83	83	37	37	33	33	15	15	12	16	16	12	12	73	73
1	84	84	32	32	34	34	15	15	11	15	15	12	12	72	72
1	85	85	33	33	31	31	16	16	10	14	14	13	13	77	77
1	86	86	38	38	39	39	14	14	9	15	15	13	13	75	75
1	87	87	33	33	34	34	16	16	12	14	14	12	12	69	69
1	88	88	29	29	32	32	16	16	12	13	13	15	15	54	54
1	89	89	33	33	33	33	15	15	12	7	7	22	22	70	70
1	90	90	31	31	36	36	12	12	9	17	17	13	13	73	73
1	91	91	36	36	32	32	17	17	15	13	13	15	15	54	54
1	92	92	35	35	41	41	16	16	12	15	15	13	13	77	77
1	93	93	32	32	28	28	15	15	12	14	14	15	15	82	82
1	94	94	29	29	30	30	13	13	12	13	13	12.5	12.5	80	80
1	95	95	39	39	36	36	16	16	10	16	16	11	11	80	80
1	96	96	37	37	35	35	16	16	13	12	12	16	16	69	69
1	97	97	35	35	31	31	16	16	9	14	14	11	11	78	78
1	98	98	37	37	34	34	16	16	12	17	17	11	11	81	81
1	99	99	32	32	36	36	14	14	10	15	15	10	10	76	76
1	100	100	38	38	36	36	16	16	14	17	17	10	10	76	76
1	101	101	37	37	35	35	16	16	11	12	12	16	16	73	73
1	102	102	36	36	37	37	20	20	15	16	16	12	12	85	85
1	103	103	32	32	28	28	15	15	11	11	11	11	11	66	66
1	104	104	33	33	39	39	16	16	11	15	15	16	16	79	79
1	105	105	40	40	32	32	13	13	12	9	9	19	19	68	68
1	106	106	38	38	35	35	17	17	12	16	16	11	11	76	76
1	107	107	41	41	39	39	16	16	12	15	15	16	16	71	71
1	108	108	36	36	35	35	16	16	11	10	10	15	15	54	54
1	109	109	43	43	42	42	12	12	7	10	10	24	24	46	46
1	110	110	30	30	34	34	16	16	12	15	15	14	14	85	85
1	111	111	31	31	33	33	16	16	14	11	11	15	15	74	74
1	112	112	32	32	41	41	17	17	11	13	13	11	11	88	88
1	113	113	32	32	33	33	13	13	11	14	14	15	15	38	38
1	114	114	37	37	34	34	12	12	10	18	18	12	12	76	76
1	115	115	37	37	32	32	18	18	13	16	16	10	10	86	86
1	116	116	33	33	40	40	14	14	13	14	14	14	14	54	54
1	117	117	34	34	40	40	14	14	8	14	14	13	13	67	67
1	118	118	33	33	35	35	13	13	11	14	14	9	9	69	69
1	119	119	38	38	36	36	16	16	12	14	14	15	15	90	90
1	120	120	33	33	37	37	13	13	11	12	12	15	15	54	54
1	121	121	31	31	27	27	16	16	13	14	14	14	14	76	76
1	122	122	38	38	39	39	13	13	12	15	15	11	11	89	89
1	123	123	37	37	38	38	16	16	14	15	15	8	8	76	76
1	124	124	36	36	31	31	15	15	13	15	15	11	11	73	73
1	125	125	31	31	33	33	16	16	15	13	13	11	11	79	79
1	126	126	39	39	32	32	15	15	10	17	17	8	8	90	90
1	127	127	44	44	39	39	17	17	11	17	17	10	10	74	74
1	128	128	33	33	36	36	15	15	9	19	19	11	11	81	81
1	129	129	35	35	33	33	12	12	11	15	15	13	13	72	72
1	130	130	32	32	33	33	16	16	10	13	13	11	11	71	71
1	131	131	28	28	32	32	10	10	11	9	9	20	20	66	66
1	132	132	40	40	37	37	16	16	8	15	15	10	10	77	77
1	133	133	27	27	30	30	12	12	11	15	15	15	15	65	65
1	134	134	37	37	38	38	14	14	12	15	15	12	12	74	74
1	135	135	32	32	29	29	15	15	12	16	16	14	14	85	85
1	136	136	28	28	22	22	13	13	9	11	11	23	23	54	54
1	137	137	34	34	35	35	15	15	11	14	14	14	14	63	63
1	138	138	30	30	35	35	11	11	10	11	11	16	16	54	54
1	139	139	35	35	34	34	12	12	8	15	15	11	11	64	64
1	140	140	31	31	35	35	11	11	9	13	13	12	12	69	69
1	141	141	32	32	34	34	16	16	8	15	15	10	10	54	54
1	142	142	30	30	37	37	15	15	9	16	16	14	14	84	84
1	143	143	30	30	35	35	17	17	15	14	14	12	12	86	86
1	144	144	31	31	23	23	16	16	11	15	15	12	12	77	77
1	145	145	40	40	31	31	10	10	8	16	16	11	11	89	89
1	146	146	32	32	27	27	18	18	13	16	16	12	12	76	76
1	147	147	36	36	36	36	13	13	12	11	11	13	13	60	60
1	148	148	32	32	31	31	16	16	12	12	12	11	11	75	75
1	149	149	35	35	32	32	13	13	9	9	9	19	19	73	73
1	150	150	38	38	39	39	10	10	7	16	16	12	12	85	85
1	151	151	42	42	37	37	15	15	13	13	13	17	17	79	79
1	152	152	34	34	38	38	16	16	9	16	16	9	9	71	71
1	153	153	35	35	39	39	16	16	6	12	12	12	12	72	72
1	154	154	38	38	34	34	14	14	8	9	9	19	19	69	69
1	155	155	33	33	31	31	10	10	8	13	13	18	18	78	78
1	156	156	36	36	32	32	17	17	15	13	13	15	15	54	54
1	157	157	32	32	37	37	13	13	6	14	14	14	14	69	69
1	158	158	33	33	36	36	15	15	9	19	19	11	11	81	81
1	159	159	34	34	32	32	16	16	11	13	13	9	9	84	84
1	160	160	32	32	38	38	12	12	8	12	12	18	18	84	84
1	161	161	34	34	36	36	13	13	8	13	13	16	16	69	69
0	162	0	27	0	26	0	13	13	10	10	0	24	0	66	0
0	163	0	31	0	26	0	12	12	8	14	0	14	0	81	0
0	164	0	38	0	33	0	17	17	14	16	0	20	0	82	0
0	165	0	34	0	39	0	15	15	10	10	0	18	0	72	0
0	166	0	24	0	30	0	10	10	8	11	0	23	0	54	0
0	167	0	30	0	33	0	14	14	11	14	0	12	0	78	0
0	168	0	26	0	25	0	11	11	12	12	0	14	0	74	0
0	169	0	34	0	38	0	13	13	12	9	0	16	0	82	0
0	170	0	27	0	37	0	16	16	12	9	0	18	0	73	0
0	171	0	37	0	31	0	12	12	5	11	0	20	0	55	0
0	172	0	36	0	37	0	16	16	12	16	0	12	0	72	0
0	173	0	41	0	35	0	12	12	10	9	0	12	0	78	0
0	174	0	29	0	25	0	9	9	7	13	0	17	0	59	0
0	175	0	36	0	28	0	12	12	12	16	0	13	0	72	0
0	176	0	32	0	35	0	15	15	11	13	0	9	0	78	0
0	177	0	37	0	33	0	12	12	8	9	0	16	0	68	0
0	178	0	30	0	30	0	12	12	9	12	0	18	0	69	0
0	179	0	31	0	31	0	14	14	10	16	0	10	0	67	0
0	180	0	38	0	37	0	12	12	9	11	0	14	0	74	0
0	181	0	36	0	36	0	16	16	12	14	0	11	0	54	0
0	182	0	35	0	30	0	11	11	6	13	0	9	0	67	0
0	183	0	31	0	36	0	19	19	15	15	0	11	0	70	0
0	184	0	38	0	32	0	15	15	12	14	0	10	0	80	0
0	185	0	22	0	28	0	8	8	12	16	0	11	0	89	0
0	186	0	32	0	36	0	16	16	12	13	0	19	0	76	0
0	187	0	36	0	34	0	17	17	11	14	0	14	0	74	0
0	188	0	39	0	31	0	12	12	7	15	0	12	0	87	0
0	189	0	28	0	28	0	11	11	7	13	0	14	0	54	0
0	190	0	32	0	36	0	11	11	5	11	0	21	0	61	0
0	191	0	32	0	36	0	14	14	12	11	0	13	0	38	0
0	192	0	38	0	40	0	16	16	12	14	0	10	0	75	0
0	193	0	32	0	33	0	12	12	3	15	0	15	0	69	0
0	194	0	35	0	37	0	16	16	11	11	0	16	0	62	0
0	195	0	32	0	32	0	13	13	10	15	0	14	0	72	0
0	196	0	37	0	38	0	15	15	12	12	0	12	0	70	0
0	197	0	34	0	31	0	16	16	9	14	0	19	0	79	0
0	198	0	33	0	37	0	16	16	12	14	0	15	0	87	0
0	199	0	33	0	33	0	14	14	9	8	0	19	0	62	0
0	200	0	26	0	32	0	16	16	12	13	0	13	0	77	0
0	201	0	30	0	30	0	16	16	12	9	0	17	0	69	0
0	202	0	24	0	30	0	14	14	10	15	0	12	0	69	0
0	203	0	34	0	31	0	11	11	9	17	0	11	0	75	0
0	204	0	34	0	32	0	12	12	12	13	0	14	0	54	0
0	205	0	33	0	34	0	15	15	8	15	0	11	0	72	0
0	206	0	34	0	36	0	15	15	11	15	0	13	0	74	0
0	207	0	35	0	37	0	16	16	11	14	0	12	0	85	0
0	208	0	35	0	36	0	16	16	12	16	0	15	0	52	0
0	209	0	36	0	33	0	11	11	10	13	0	14	0	70	0
0	210	0	34	0	33	0	15	15	10	16	0	12	0	84	0
0	211	0	34	0	33	0	12	12	12	9	0	17	0	64	0
0	212	0	41	0	44	0	12	12	12	16	0	11	0	84	0
0	213	0	32	0	39	0	15	15	11	11	0	18	0	87	0
0	214	0	30	0	32	0	15	15	8	10	0	13	0	79	0
0	215	0	35	0	35	0	16	16	12	11	0	17	0	67	0
0	216	0	28	0	25	0	14	14	10	15	0	13	0	65	0
0	217	0	33	0	35	0	17	17	11	17	0	11	0	85	0
0	218	0	39	0	34	0	14	14	10	14	0	12	0	83	0
0	219	0	36	0	35	0	13	13	8	8	0	22	0	61	0
0	220	0	36	0	39	0	15	15	12	15	0	14	0	82	0
0	221	0	35	0	33	0	13	13	12	11	0	12	0	76	0
0	222	0	38	0	36	0	14	14	10	16	0	12	0	58	0
0	223	0	33	0	32	0	15	15	12	10	0	17	0	72	0
0	224	0	31	0	32	0	12	12	9	15	0	9	0	72	0
0	225	0	34	0	36	0	13	13	9	9	0	21	0	38	0
0	226	0	32	0	36	0	8	8	6	16	0	10	0	78	0
0	227	0	31	0	32	0	14	14	10	19	0	11	0	54	0
0	228	0	33	0	34	0	14	14	9	12	0	12	0	63	0
0	229	0	34	0	33	0	11	11	9	8	0	23	0	66	0
0	230	0	34	0	35	0	12	12	9	11	0	13	0	70	0
0	231	0	34	0	30	0	13	13	6	14	0	12	0	71	0
0	232	0	33	0	38	0	10	10	10	9	0	16	0	67	0
0	233	0	32	0	34	0	16	16	6	15	0	9	0	58	0
0	234	0	41	0	33	0	18	18	14	13	0	17	0	72	0
0	235	0	34	0	32	0	13	13	10	16	0	9	0	72	0
0	236	0	36	0	31	0	11	11	10	11	0	14	0	70	0
0	237	0	37	0	30	0	4	4	6	12	0	17	0	76	0
0	238	0	36	0	27	0	13	13	12	13	0	13	0	50	0
0	239	0	29	0	31	0	16	16	12	10	0	11	0	72	0
0	240	0	37	0	30	0	10	10	7	11	0	12	0	72	0
0	241	0	27	0	32	0	12	12	8	12	0	10	0	88	0
0	242	0	35	0	35	0	12	12	11	8	0	19	0	53	0
0	243	0	28	0	28	0	10	10	3	12	0	16	0	58	0
0	244	0	35	0	33	0	13	13	6	12	0	16	0	66	0
0	245	0	37	0	31	0	15	15	10	15	0	14	0	82	0
0	246	0	29	0	35	0	12	12	8	11	0	20	0	69	0
0	247	0	32	0	35	0	14	14	9	13	0	15	0	68	0
0	248	0	36	0	32	0	10	10	9	14	0	23	0	44	0
0	249	0	19	0	21	0	12	12	8	10	0	20	0	56	0
0	250	0	21	0	20	0	12	12	9	12	0	16	0	53	0
0	251	0	31	0	34	0	11	11	7	15	0	14	0	70	0
0	252	0	33	0	32	0	10	10	7	13	0	17	0	78	0
0	253	0	36	0	34	0	12	12	6	13	0	11	0	71	0
0	254	0	33	0	32	0	16	16	9	13	0	13	0	72	0
0	255	0	37	0	33	0	12	12	10	12	0	17	0	68	0
0	256	0	34	0	33	0	14	14	11	12	0	15	0	67	0
0	257	0	35	0	37	0	16	16	12	9	0	21	0	75	0
0	258	0	31	0	32	0	14	14	8	9	0	18	0	62	0
0	259	0	37	0	34	0	13	13	11	15	0	15	0	67	0
0	260	0	35	0	30	0	4	4	3	10	0	8	0	83	0
0	261	0	27	0	30	0	15	15	11	14	0	12	0	64	0
0	262	0	34	0	38	0	11	11	12	15	0	12	0	68	0
0	263	0	40	0	36	0	11	11	7	7	0	22	0	62	0
0	264	0	29	0	32	0	14	14	9	14	0	12	0	72	0

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	16 seconds
R Server	'Herman Ole Andreas Wold' @ wold.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 & 16 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190339&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]16 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190339&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190339&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	16 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Multiple Linear Regression - Estimated Regression Equation
Learning_p[t] = + 1.36685540574507e-16 -2.24130327401676e-16Pop[t] 0t 0Pop_t[t] 0Connected[t] 0Connected_p[t] 0Separate[t] 0Separate_p[t] + 1Learning[t] -1.92034237745733e-18Software[t] -8.89015228870144e-18Happiness[t] + 2.18919951146729e-18Happiness_p[t] -7.28235610420522e-18Depression[t] + 1.4446555024318e-17Depression_p[t] + 5.80567721635646e-19Belonging[t] -7.82099234232271e-19Belonging_p[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning_p[t] =  +  1.36685540574507e-16 -2.24130327401676e-16Pop[t] 0t 0Pop_t[t] 0Connected[t] 0Connected_p[t] 0Separate[t] 0Separate_p[t] +  1Learning[t] -1.92034237745733e-18Software[t] -8.89015228870144e-18Happiness[t] +  2.18919951146729e-18Happiness_p[t] -7.28235610420522e-18Depression[t] +  1.4446555024318e-17Depression_p[t] +  5.80567721635646e-19Belonging[t] -7.82099234232271e-19Belonging_p[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190339&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning_p[t] =  +  1.36685540574507e-16 -2.24130327401676e-16Pop[t] 0t 0Pop_t[t] 0Connected[t] 0Connected_p[t] 0Separate[t] 0Separate_p[t] +  1Learning[t] -1.92034237745733e-18Software[t] -8.89015228870144e-18Happiness[t] +  2.18919951146729e-18Happiness_p[t] -7.28235610420522e-18Depression[t] +  1.4446555024318e-17Depression_p[t] +  5.80567721635646e-19Belonging[t] -7.82099234232271e-19Belonging_p[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190339&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190339&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
Learning_p[t] = + 1.36685540574507e-16 -2.24130327401676e-16Pop[t] 0t 0Pop_t[t] 0Connected[t] 0Connected_p[t] 0Separate[t] 0Separate_p[t] + 1Learning[t] -1.92034237745733e-18Software[t] -8.89015228870144e-18Happiness[t] + 2.18919951146729e-18Happiness_p[t] -7.28235610420522e-18Depression[t] + 1.4446555024318e-17Depression_p[t] + 5.80567721635646e-19Belonging[t] -7.82099234232271e-19Belonging_p[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	1.36685540574507e-16	0	0.4571	0.648006	0.324003
Pop	-2.24130327401676e-16	0	-0.5995	0.549394	0.274697
t	0	0	0	1	0.5
Pop_t	0	0	0	1	0.5
Connected	0	0	0	1	0.5
Connected_p	0	0	0	1	0.5
Separate	0	0	0	1	0.5
Separate_p	0	0	0	1	0.5
Learning	1	0	174861327596863904	0	0
Software	-1.92034237745733e-18	0	-0.3326	0.739709	0.369855
Happiness	-8.89015228870144e-18	0	-1.1026	0.271275	0.135638
Happiness_p	2.18919951146729e-18	0	0.2061	0.836911	0.418456
Depression	-7.28235610420522e-18	0	-1.2993	0.195039	0.09752
Depression_p	1.4446555024318e-17	0	1.8968	0.059016	0.029508
Belonging	5.80567721635646e-19	0	0.3382	0.735488	0.367744
Belonging_p	-7.82099234232271e-19	0	-0.3524	0.724833	0.362416

\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) & 1.36685540574507e-16 & 0 & 0.4571 & 0.648006 & 0.324003 \tabularnewline
Pop & -2.24130327401676e-16 & 0 & -0.5995 & 0.549394 & 0.274697 \tabularnewline
t & 0 & 0 & 0 & 1 & 0.5 \tabularnewline
Pop_t & 0 & 0 & 0 & 1 & 0.5 \tabularnewline
Connected & 0 & 0 & 0 & 1 & 0.5 \tabularnewline
Connected_p & 0 & 0 & 0 & 1 & 0.5 \tabularnewline
Separate & 0 & 0 & 0 & 1 & 0.5 \tabularnewline
Separate_p & 0 & 0 & 0 & 1 & 0.5 \tabularnewline
Learning & 1 & 0 & 174861327596863904 & 0 & 0 \tabularnewline
Software & -1.92034237745733e-18 & 0 & -0.3326 & 0.739709 & 0.369855 \tabularnewline
Happiness & -8.89015228870144e-18 & 0 & -1.1026 & 0.271275 & 0.135638 \tabularnewline
Happiness_p & 2.18919951146729e-18 & 0 & 0.2061 & 0.836911 & 0.418456 \tabularnewline
Depression & -7.28235610420522e-18 & 0 & -1.2993 & 0.195039 & 0.09752 \tabularnewline
Depression_p & 1.4446555024318e-17 & 0 & 1.8968 & 0.059016 & 0.029508 \tabularnewline
Belonging & 5.80567721635646e-19 & 0 & 0.3382 & 0.735488 & 0.367744 \tabularnewline
Belonging_p & -7.82099234232271e-19 & 0 & -0.3524 & 0.724833 & 0.362416 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190339&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]1.36685540574507e-16[/C][C]0[/C][C]0.4571[/C][C]0.648006[/C][C]0.324003[/C][/ROW]
[ROW][C]Pop[/C][C]-2.24130327401676e-16[/C][C]0[/C][C]-0.5995[/C][C]0.549394[/C][C]0.274697[/C][/ROW]
[ROW][C]t[/C][C]0[/C][C]0[/C][C]0[/C][C]1[/C][C]0.5[/C][/ROW]
[ROW][C]Pop_t[/C][C]0[/C][C]0[/C][C]0[/C][C]1[/C][C]0.5[/C][/ROW]
[ROW][C]Connected[/C][C]0[/C][C]0[/C][C]0[/C][C]1[/C][C]0.5[/C][/ROW]
[ROW][C]Connected_p[/C][C]0[/C][C]0[/C][C]0[/C][C]1[/C][C]0.5[/C][/ROW]
[ROW][C]Separate[/C][C]0[/C][C]0[/C][C]0[/C][C]1[/C][C]0.5[/C][/ROW]
[ROW][C]Separate_p[/C][C]0[/C][C]0[/C][C]0[/C][C]1[/C][C]0.5[/C][/ROW]
[ROW][C]Learning[/C][C]1[/C][C]0[/C][C]174861327596863904[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Software[/C][C]-1.92034237745733e-18[/C][C]0[/C][C]-0.3326[/C][C]0.739709[/C][C]0.369855[/C][/ROW]
[ROW][C]Happiness[/C][C]-8.89015228870144e-18[/C][C]0[/C][C]-1.1026[/C][C]0.271275[/C][C]0.135638[/C][/ROW]
[ROW][C]Happiness_p[/C][C]2.18919951146729e-18[/C][C]0[/C][C]0.2061[/C][C]0.836911[/C][C]0.418456[/C][/ROW]
[ROW][C]Depression[/C][C]-7.28235610420522e-18[/C][C]0[/C][C]-1.2993[/C][C]0.195039[/C][C]0.09752[/C][/ROW]
[ROW][C]Depression_p[/C][C]1.4446555024318e-17[/C][C]0[/C][C]1.8968[/C][C]0.059016[/C][C]0.029508[/C][/ROW]
[ROW][C]Belonging[/C][C]5.80567721635646e-19[/C][C]0[/C][C]0.3382[/C][C]0.735488[/C][C]0.367744[/C][/ROW]
[ROW][C]Belonging_p[/C][C]-7.82099234232271e-19[/C][C]0[/C][C]-0.3524[/C][C]0.724833[/C][C]0.362416[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190339&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190339&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	1.36685540574507e-16	0	0.4571	0.648006	0.324003
Pop	-2.24130327401676e-16	0	-0.5995	0.549394	0.274697
t	0	0	0	1	0.5
Pop_t	0	0	0	1	0.5
Connected	0	0	0	1	0.5
Connected_p	0	0	0	1	0.5
Separate	0	0	0	1	0.5
Separate_p	0	0	0	1	0.5
Learning	1	0	174861327596863904	0	0
Software	-1.92034237745733e-18	0	-0.3326	0.739709	0.369855
Happiness	-8.89015228870144e-18	0	-1.1026	0.271275	0.135638
Happiness_p	2.18919951146729e-18	0	0.2061	0.836911	0.418456
Depression	-7.28235610420522e-18	0	-1.2993	0.195039	0.09752
Depression_p	1.4446555024318e-17	0	1.8968	0.059016	0.029508
Belonging	5.80567721635646e-19	0	0.3382	0.735488	0.367744
Belonging_p	-7.82099234232271e-19	0	-0.3524	0.724833	0.362416

Multiple Linear Regression - Regression Statistics
Multiple R	1
R-squared	1
Adjusted R-squared	1
F-TEST (value)	3.82527696498098e+33
F-TEST (DF numerator)	15
F-TEST (DF denominator)	248
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	1.66273983278766e-16
Sum Squared Residuals	6.85646530381604e-30

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 1 \tabularnewline
R-squared & 1 \tabularnewline
Adjusted R-squared & 1 \tabularnewline
F-TEST (value) & 3.82527696498098e+33 \tabularnewline
F-TEST (DF numerator) & 15 \tabularnewline
F-TEST (DF denominator) & 248 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.66273983278766e-16 \tabularnewline
Sum Squared Residuals & 6.85646530381604e-30 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190339&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]1[/C][/ROW]
[ROW][C]R-squared[/C][C]1[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]1[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]3.82527696498098e+33[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]15[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]248[/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]1.66273983278766e-16[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]6.85646530381604e-30[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190339&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190339&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	1
R-squared	1
Adjusted R-squared	1
F-TEST (value)	3.82527696498098e+33
F-TEST (DF numerator)	15
F-TEST (DF denominator)	248
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	1.66273983278766e-16
Sum Squared Residuals	6.85646530381604e-30

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	13	13	-1.45145152277389e-18
2	16	16	9.13382281187284e-17
3	19	19	2.20080812421479e-16
4	15	15	2.91131368272878e-16
5	14	14	-1.83785412959099e-17
6	13	13	1.47592556469601e-16
7	19	19	-2.14814933356497e-17
8	15	15	7.75199657230604e-17
9	14	14	-2.05182447936475e-15
10	15	15	9.62410813914866e-17
11	16	16	7.85385461039742e-17
12	16	16	1.07531583039445e-16
13	16	16	-1.29216766437425e-17
14	16	16	2.66834699914131e-17
15	17	17	-6.4936073361718e-18
16	15	15	1.325330699211e-17
17	15	15	4.24657846245047e-17
18	20	20	1.40677982937323e-16
19	18	18	8.79253859218245e-18
20	16	16	-2.8626478281246e-17
21	16	16	5.82748188361095e-17
22	16	16	3.77735641477304e-17
23	19	19	-1.52364038465625e-16
24	16	16	2.40251547160884e-18
25	17	17	3.74148914273145e-17
26	17	17	-1.75715879626839e-17
27	16	16	3.62099381836029e-17
28	15	15	9.0501729656722e-18
29	16	16	3.30078187093899e-17
30	14	14	1.07678824789097e-16
31	15	15	6.37198087735031e-17
32	12	12	1.39266515503507e-16
33	14	14	-3.95987452853688e-17
34	16	16	1.57782939346024e-17
35	14	14	3.49108358973607e-17
36	10	10	-2.28837617189125e-16
37	10	10	1.38298912807948e-16
38	14	14	-1.31415026081835e-18
39	16	16	-4.50670023380202e-17
40	16	16	-3.24048719677377e-17
41	16	16	3.15938321313444e-17
42	14	14	-1.58644527001878e-17
43	20	20	-1.13115475341791e-16
44	14	14	-8.4205038314338e-17
45	14	14	-3.76555848966257e-17
46	11	11	1.71658458255001e-16
47	14	14	7.78112582695865e-17
48	15	15	3.42530161207263e-17
49	16	16	-4.67461078036641e-17
50	14	14	1.61871146693924e-16
51	16	16	8.35525882758815e-17
52	14	14	-4.73561959356755e-18
53	12	12	2.04779445057439e-16
54	16	16	3.40527870555137e-17
55	9	9	-1.48036674294063e-16
56	14	14	6.11489634687792e-17
57	16	16	3.03583523892933e-17
58	16	16	4.97705904859719e-17
59	15	15	3.12105550153574e-17
60	16	16	1.01009962501312e-17
61	12	12	1.69064364291339e-16
62	16	16	5.88091682557375e-17
63	16	16	-2.0598932823686e-17
64	14	14	-6.08273341316093e-18
65	16	16	2.87364815093477e-17
66	17	17	2.86785999857939e-17
67	18	18	7.30435824472102e-17
68	18	18	-1.62372801622125e-16
69	12	12	2.33527753270681e-16
70	16	16	-1.33022756084014e-16
71	10	10	2.53162206071888e-16
72	14	14	8.52909694737138e-18
73	18	18	2.56535306277374e-17
74	18	18	1.3729797963058e-16
75	16	16	7.42932268971479e-19
76	17	17	-1.23894876598315e-16
77	16	16	8.4789353821386e-17
78	16	16	4.56905779004254e-17
79	13	13	1.05946251446967e-16
80	16	16	5.21599456906539e-17
81	16	16	1.61374974103592e-17
82	16	16	5.94642266030468e-17
83	15	15	2.19616392678152e-17
84	15	15	5.54820539816556e-17
85	16	16	8.92658485863697e-18
86	14	14	1.75630800855819e-17
87	16	16	5.13884139509994e-17
88	16	16	2.03781258908467e-17
89	15	15	-1.03663657305183e-16
90	12	12	-4.2170810208847e-17
91	17	17	7.27105744266447e-17
92	16	16	3.76135746323378e-17
93	15	15	-3.82614885196352e-17
94	13	13	-1.40279670152558e-17
95	16	16	-3.12035376786387e-17
96	16	16	-1.28081722090695e-16
97	16	16	5.90476242008081e-17
98	16	16	-1.01306612964251e-16
99	14	14	2.21439905096732e-17
100	16	16	-7.50898180015081e-17
101	16	16	5.36179649950678e-19
102	20	20	-2.37155954962517e-16
103	15	15	-3.8369631508224e-17
104	16	16	-2.67013326189195e-17
105	13	13	-3.67070062470712e-17
106	17	17	1.82034306386219e-16
107	16	16	-3.84916675760016e-17
108	16	16	-8.14526971637787e-17
109	12	12	-9.22592492559904e-17
110	16	16	7.88197935604034e-17
111	16	16	-6.86183445492531e-17
112	17	17	-1.30380223653069e-17
113	13	13	-5.86477358522615e-17
114	12	12	6.04288957434411e-17
115	18	18	-6.05106549949209e-17
116	14	14	-3.79376599438271e-17
117	14	14	-4.47525503114943e-17
118	13	13	1.11979000559608e-18
119	16	16	-1.83800595290055e-17
120	13	13	-2.73641060669539e-17
121	16	16	-6.00028728881568e-17
122	13	13	8.72923941850241e-17
123	16	16	-8.92486389404245e-17
124	15	15	2.10827288571686e-17
125	16	16	-6.39658135889376e-17
126	15	15	1.01163166115667e-17
127	17	17	9.82231628561124e-18
128	15	15	4.96981254429536e-17
129	12	12	-9.90415651722252e-17
130	16	16	-4.68132414647345e-17
131	10	10	-1.74068569794559e-17
132	16	16	-1.10885587182588e-16
133	12	12	9.15735735812237e-17
134	14	14	-9.25334759980161e-18
135	15	15	-5.15451391978378e-17
136	13	13	-1.1615213376683e-16
137	15	15	7.28997776456746e-17
138	11	11	-1.12448577436544e-16
139	12	12	6.25560341237487e-17
140	11	11	-1.02348110850709e-16
141	16	16	1.12330964930187e-16
142	15	15	-7.34012793830642e-17
143	17	17	-2.09703061002804e-16
144	16	16	-1.09115174332596e-16
145	10	10	5.18345097593176e-16
146	18	18	-1.24025104083988e-16
147	13	13	-3.38556418808434e-17
148	16	16	1.58635345205838e-16
149	13	13	-4.00635756829946e-17
150	10	10	4.35155502661914e-17
151	15	15	-3.43837688782738e-17
152	16	16	7.68108530534051e-17
153	16	16	1.34408472380051e-16
154	14	14	-1.16326902664211e-16
155	10	10	5.63298345187444e-17
156	17	17	3.017028556686e-17
157	13	13	-4.47710386545275e-17
158	15	15	-9.33430813097778e-17
159	16	16	1.84316922000909e-16
160	12	12	-1.06075721525982e-17
161	13	13	-9.17217266143978e-17
162	13	13	4.56152158099252e-17
163	12	12	-2.5874000376772e-17
164	17	17	-8.10074867061527e-17
165	15	15	-5.58380681886873e-17
166	10	10	1.5854474688277e-16
167	14	14	-3.74444173054824e-17
168	11	11	3.84621735512178e-17
169	13	13	7.62599845374198e-17
170	16	16	-1.17684548579949e-16
171	12	12	-4.350007754772e-17
172	16	16	-1.3640331422257e-17
173	12	12	1.29744768217893e-16
174	9	9	-9.12804241403528e-17
175	12	12	-4.66862750548388e-17
176	15	15	-9.59800703830095e-17
177	12	12	4.22139409726594e-17
178	12	12	-1.52358147313267e-18
179	14	14	-6.35805088406545e-17
180	12	12	1.5537334291736e-16
181	16	16	-8.77183982453098e-17
182	11	11	3.08450984587646e-17
183	19	19	4.14959840735588e-16
184	15	15	-2.62765880050525e-17
185	8	8	-1.48793006245311e-16
186	16	16	8.76784688049716e-18
187	17	17	-9.58114996116628e-17
188	12	12	9.93119219664588e-17
189	11	11	2.08866822805811e-17
190	11	11	-9.5186143950854e-17
191	14	14	-1.88166065478576e-17
192	16	16	-2.35361652590574e-17
193	12	12	-7.90565546845695e-18
194	16	16	-7.70005918191211e-17
195	13	13	1.98341791193701e-18
196	15	15	-5.14694064145262e-17
197	16	16	-2.35322351437047e-16
198	16	16	5.84401552501175e-17
199	14	14	-8.16779411742105e-17
200	16	16	6.99425349019296e-17
201	16	16	1.03477152566704e-16
202	14	14	8.63208681605092e-17
203	11	11	1.32879525263642e-16
204	12	12	4.30498560151617e-17
205	15	15	-1.55572316767153e-16
206	15	15	2.72760470188797e-17
207	16	16	4.04492631127119e-17
208	16	16	1.07987396690478e-17
209	11	11	1.18472859845156e-16
210	15	15	-1.26396416155576e-16
211	12	12	3.47324393686826e-17
212	12	12	1.47114331754982e-16
213	15	15	-6.35884841715272e-17
214	15	15	1.2340877414657e-16
215	16	16	-2.14273631647745e-16
216	14	14	1.95346419927467e-16
217	17	17	1.49632403006136e-16
218	14	14	-1.31030858249358e-17
219	13	13	-1.08420594899898e-17
220	15	15	4.10151998936579e-17
221	13	13	-2.65867152102666e-17
222	14	14	-1.36024061312366e-17
223	15	15	2.16863172817602e-17
224	12	12	1.39204405548261e-17
225	13	13	6.60683085541834e-17
226	8	8	-1.78018903032714e-16
227	14	14	3.81656199840313e-17
228	14	14	2.73411055272852e-18
229	11	11	-6.87003940841005e-17
230	12	12	-9.51662284624673e-17
231	13	13	-5.82078385392791e-17
232	10	10	-1.96810924806742e-16
233	16	16	-2.36104508990807e-16
234	18	18	9.73731736612677e-18
235	13	13	3.05577261129989e-17
236	11	11	3.84827184694763e-17
237	4	4	-2.18483378261541e-16
238	13	13	-8.32449428801257e-17
239	16	16	8.30388419490023e-17
240	10	10	1.08940410707996e-16
241	12	12	-3.5932874020546e-17
242	12	12	4.04195641875445e-17
243	10	10	2.22482403451848e-17
244	13	13	-1.21089488472482e-17
245	15	15	6.11484567379523e-17
246	12	12	5.6963162837555e-17
247	14	14	1.09173001732896e-16
248	10	10	1.02455589497642e-16
249	12	12	-7.64051349140271e-17
250	12	12	6.26015063115869e-17
251	11	11	-5.146819756764e-17
252	10	10	5.77712485380279e-17
253	12	12	9.78075005028212e-18
254	16	16	-7.57701718367407e-17
255	12	12	3.71942887391307e-17
256	14	14	-1.09480875236225e-17
257	16	16	2.18670411167949e-16
258	14	14	-1.18134024224867e-16
259	13	13	7.48003792223316e-18
260	4	4	-3.52537230481938e-17
261	15	15	1.09714250069526e-16
262	11	11	-4.23899059927633e-17
263	11	11	2.62897215568266e-17
264	14	14	-9.99001456225595e-17

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 13 & -1.45145152277389e-18 \tabularnewline
2 & 16 & 16 & 9.13382281187284e-17 \tabularnewline
3 & 19 & 19 & 2.20080812421479e-16 \tabularnewline
4 & 15 & 15 & 2.91131368272878e-16 \tabularnewline
5 & 14 & 14 & -1.83785412959099e-17 \tabularnewline
6 & 13 & 13 & 1.47592556469601e-16 \tabularnewline
7 & 19 & 19 & -2.14814933356497e-17 \tabularnewline
8 & 15 & 15 & 7.75199657230604e-17 \tabularnewline
9 & 14 & 14 & -2.05182447936475e-15 \tabularnewline
10 & 15 & 15 & 9.62410813914866e-17 \tabularnewline
11 & 16 & 16 & 7.85385461039742e-17 \tabularnewline
12 & 16 & 16 & 1.07531583039445e-16 \tabularnewline
13 & 16 & 16 & -1.29216766437425e-17 \tabularnewline
14 & 16 & 16 & 2.66834699914131e-17 \tabularnewline
15 & 17 & 17 & -6.4936073361718e-18 \tabularnewline
16 & 15 & 15 & 1.325330699211e-17 \tabularnewline
17 & 15 & 15 & 4.24657846245047e-17 \tabularnewline
18 & 20 & 20 & 1.40677982937323e-16 \tabularnewline
19 & 18 & 18 & 8.79253859218245e-18 \tabularnewline
20 & 16 & 16 & -2.8626478281246e-17 \tabularnewline
21 & 16 & 16 & 5.82748188361095e-17 \tabularnewline
22 & 16 & 16 & 3.77735641477304e-17 \tabularnewline
23 & 19 & 19 & -1.52364038465625e-16 \tabularnewline
24 & 16 & 16 & 2.40251547160884e-18 \tabularnewline
25 & 17 & 17 & 3.74148914273145e-17 \tabularnewline
26 & 17 & 17 & -1.75715879626839e-17 \tabularnewline
27 & 16 & 16 & 3.62099381836029e-17 \tabularnewline
28 & 15 & 15 & 9.0501729656722e-18 \tabularnewline
29 & 16 & 16 & 3.30078187093899e-17 \tabularnewline
30 & 14 & 14 & 1.07678824789097e-16 \tabularnewline
31 & 15 & 15 & 6.37198087735031e-17 \tabularnewline
32 & 12 & 12 & 1.39266515503507e-16 \tabularnewline
33 & 14 & 14 & -3.95987452853688e-17 \tabularnewline
34 & 16 & 16 & 1.57782939346024e-17 \tabularnewline
35 & 14 & 14 & 3.49108358973607e-17 \tabularnewline
36 & 10 & 10 & -2.28837617189125e-16 \tabularnewline
37 & 10 & 10 & 1.38298912807948e-16 \tabularnewline
38 & 14 & 14 & -1.31415026081835e-18 \tabularnewline
39 & 16 & 16 & -4.50670023380202e-17 \tabularnewline
40 & 16 & 16 & -3.24048719677377e-17 \tabularnewline
41 & 16 & 16 & 3.15938321313444e-17 \tabularnewline
42 & 14 & 14 & -1.58644527001878e-17 \tabularnewline
43 & 20 & 20 & -1.13115475341791e-16 \tabularnewline
44 & 14 & 14 & -8.4205038314338e-17 \tabularnewline
45 & 14 & 14 & -3.76555848966257e-17 \tabularnewline
46 & 11 & 11 & 1.71658458255001e-16 \tabularnewline
47 & 14 & 14 & 7.78112582695865e-17 \tabularnewline
48 & 15 & 15 & 3.42530161207263e-17 \tabularnewline
49 & 16 & 16 & -4.67461078036641e-17 \tabularnewline
50 & 14 & 14 & 1.61871146693924e-16 \tabularnewline
51 & 16 & 16 & 8.35525882758815e-17 \tabularnewline
52 & 14 & 14 & -4.73561959356755e-18 \tabularnewline
53 & 12 & 12 & 2.04779445057439e-16 \tabularnewline
54 & 16 & 16 & 3.40527870555137e-17 \tabularnewline
55 & 9 & 9 & -1.48036674294063e-16 \tabularnewline
56 & 14 & 14 & 6.11489634687792e-17 \tabularnewline
57 & 16 & 16 & 3.03583523892933e-17 \tabularnewline
58 & 16 & 16 & 4.97705904859719e-17 \tabularnewline
59 & 15 & 15 & 3.12105550153574e-17 \tabularnewline
60 & 16 & 16 & 1.01009962501312e-17 \tabularnewline
61 & 12 & 12 & 1.69064364291339e-16 \tabularnewline
62 & 16 & 16 & 5.88091682557375e-17 \tabularnewline
63 & 16 & 16 & -2.0598932823686e-17 \tabularnewline
64 & 14 & 14 & -6.08273341316093e-18 \tabularnewline
65 & 16 & 16 & 2.87364815093477e-17 \tabularnewline
66 & 17 & 17 & 2.86785999857939e-17 \tabularnewline
67 & 18 & 18 & 7.30435824472102e-17 \tabularnewline
68 & 18 & 18 & -1.62372801622125e-16 \tabularnewline
69 & 12 & 12 & 2.33527753270681e-16 \tabularnewline
70 & 16 & 16 & -1.33022756084014e-16 \tabularnewline
71 & 10 & 10 & 2.53162206071888e-16 \tabularnewline
72 & 14 & 14 & 8.52909694737138e-18 \tabularnewline
73 & 18 & 18 & 2.56535306277374e-17 \tabularnewline
74 & 18 & 18 & 1.3729797963058e-16 \tabularnewline
75 & 16 & 16 & 7.42932268971479e-19 \tabularnewline
76 & 17 & 17 & -1.23894876598315e-16 \tabularnewline
77 & 16 & 16 & 8.4789353821386e-17 \tabularnewline
78 & 16 & 16 & 4.56905779004254e-17 \tabularnewline
79 & 13 & 13 & 1.05946251446967e-16 \tabularnewline
80 & 16 & 16 & 5.21599456906539e-17 \tabularnewline
81 & 16 & 16 & 1.61374974103592e-17 \tabularnewline
82 & 16 & 16 & 5.94642266030468e-17 \tabularnewline
83 & 15 & 15 & 2.19616392678152e-17 \tabularnewline
84 & 15 & 15 & 5.54820539816556e-17 \tabularnewline
85 & 16 & 16 & 8.92658485863697e-18 \tabularnewline
86 & 14 & 14 & 1.75630800855819e-17 \tabularnewline
87 & 16 & 16 & 5.13884139509994e-17 \tabularnewline
88 & 16 & 16 & 2.03781258908467e-17 \tabularnewline
89 & 15 & 15 & -1.03663657305183e-16 \tabularnewline
90 & 12 & 12 & -4.2170810208847e-17 \tabularnewline
91 & 17 & 17 & 7.27105744266447e-17 \tabularnewline
92 & 16 & 16 & 3.76135746323378e-17 \tabularnewline
93 & 15 & 15 & -3.82614885196352e-17 \tabularnewline
94 & 13 & 13 & -1.40279670152558e-17 \tabularnewline
95 & 16 & 16 & -3.12035376786387e-17 \tabularnewline
96 & 16 & 16 & -1.28081722090695e-16 \tabularnewline
97 & 16 & 16 & 5.90476242008081e-17 \tabularnewline
98 & 16 & 16 & -1.01306612964251e-16 \tabularnewline
99 & 14 & 14 & 2.21439905096732e-17 \tabularnewline
100 & 16 & 16 & -7.50898180015081e-17 \tabularnewline
101 & 16 & 16 & 5.36179649950678e-19 \tabularnewline
102 & 20 & 20 & -2.37155954962517e-16 \tabularnewline
103 & 15 & 15 & -3.8369631508224e-17 \tabularnewline
104 & 16 & 16 & -2.67013326189195e-17 \tabularnewline
105 & 13 & 13 & -3.67070062470712e-17 \tabularnewline
106 & 17 & 17 & 1.82034306386219e-16 \tabularnewline
107 & 16 & 16 & -3.84916675760016e-17 \tabularnewline
108 & 16 & 16 & -8.14526971637787e-17 \tabularnewline
109 & 12 & 12 & -9.22592492559904e-17 \tabularnewline
110 & 16 & 16 & 7.88197935604034e-17 \tabularnewline
111 & 16 & 16 & -6.86183445492531e-17 \tabularnewline
112 & 17 & 17 & -1.30380223653069e-17 \tabularnewline
113 & 13 & 13 & -5.86477358522615e-17 \tabularnewline
114 & 12 & 12 & 6.04288957434411e-17 \tabularnewline
115 & 18 & 18 & -6.05106549949209e-17 \tabularnewline
116 & 14 & 14 & -3.79376599438271e-17 \tabularnewline
117 & 14 & 14 & -4.47525503114943e-17 \tabularnewline
118 & 13 & 13 & 1.11979000559608e-18 \tabularnewline
119 & 16 & 16 & -1.83800595290055e-17 \tabularnewline
120 & 13 & 13 & -2.73641060669539e-17 \tabularnewline
121 & 16 & 16 & -6.00028728881568e-17 \tabularnewline
122 & 13 & 13 & 8.72923941850241e-17 \tabularnewline
123 & 16 & 16 & -8.92486389404245e-17 \tabularnewline
124 & 15 & 15 & 2.10827288571686e-17 \tabularnewline
125 & 16 & 16 & -6.39658135889376e-17 \tabularnewline
126 & 15 & 15 & 1.01163166115667e-17 \tabularnewline
127 & 17 & 17 & 9.82231628561124e-18 \tabularnewline
128 & 15 & 15 & 4.96981254429536e-17 \tabularnewline
129 & 12 & 12 & -9.90415651722252e-17 \tabularnewline
130 & 16 & 16 & -4.68132414647345e-17 \tabularnewline
131 & 10 & 10 & -1.74068569794559e-17 \tabularnewline
132 & 16 & 16 & -1.10885587182588e-16 \tabularnewline
133 & 12 & 12 & 9.15735735812237e-17 \tabularnewline
134 & 14 & 14 & -9.25334759980161e-18 \tabularnewline
135 & 15 & 15 & -5.15451391978378e-17 \tabularnewline
136 & 13 & 13 & -1.1615213376683e-16 \tabularnewline
137 & 15 & 15 & 7.28997776456746e-17 \tabularnewline
138 & 11 & 11 & -1.12448577436544e-16 \tabularnewline
139 & 12 & 12 & 6.25560341237487e-17 \tabularnewline
140 & 11 & 11 & -1.02348110850709e-16 \tabularnewline
141 & 16 & 16 & 1.12330964930187e-16 \tabularnewline
142 & 15 & 15 & -7.34012793830642e-17 \tabularnewline
143 & 17 & 17 & -2.09703061002804e-16 \tabularnewline
144 & 16 & 16 & -1.09115174332596e-16 \tabularnewline
145 & 10 & 10 & 5.18345097593176e-16 \tabularnewline
146 & 18 & 18 & -1.24025104083988e-16 \tabularnewline
147 & 13 & 13 & -3.38556418808434e-17 \tabularnewline
148 & 16 & 16 & 1.58635345205838e-16 \tabularnewline
149 & 13 & 13 & -4.00635756829946e-17 \tabularnewline
150 & 10 & 10 & 4.35155502661914e-17 \tabularnewline
151 & 15 & 15 & -3.43837688782738e-17 \tabularnewline
152 & 16 & 16 & 7.68108530534051e-17 \tabularnewline
153 & 16 & 16 & 1.34408472380051e-16 \tabularnewline
154 & 14 & 14 & -1.16326902664211e-16 \tabularnewline
155 & 10 & 10 & 5.63298345187444e-17 \tabularnewline
156 & 17 & 17 & 3.017028556686e-17 \tabularnewline
157 & 13 & 13 & -4.47710386545275e-17 \tabularnewline
158 & 15 & 15 & -9.33430813097778e-17 \tabularnewline
159 & 16 & 16 & 1.84316922000909e-16 \tabularnewline
160 & 12 & 12 & -1.06075721525982e-17 \tabularnewline
161 & 13 & 13 & -9.17217266143978e-17 \tabularnewline
162 & 13 & 13 & 4.56152158099252e-17 \tabularnewline
163 & 12 & 12 & -2.5874000376772e-17 \tabularnewline
164 & 17 & 17 & -8.10074867061527e-17 \tabularnewline
165 & 15 & 15 & -5.58380681886873e-17 \tabularnewline
166 & 10 & 10 & 1.5854474688277e-16 \tabularnewline
167 & 14 & 14 & -3.74444173054824e-17 \tabularnewline
168 & 11 & 11 & 3.84621735512178e-17 \tabularnewline
169 & 13 & 13 & 7.62599845374198e-17 \tabularnewline
170 & 16 & 16 & -1.17684548579949e-16 \tabularnewline
171 & 12 & 12 & -4.350007754772e-17 \tabularnewline
172 & 16 & 16 & -1.3640331422257e-17 \tabularnewline
173 & 12 & 12 & 1.29744768217893e-16 \tabularnewline
174 & 9 & 9 & -9.12804241403528e-17 \tabularnewline
175 & 12 & 12 & -4.66862750548388e-17 \tabularnewline
176 & 15 & 15 & -9.59800703830095e-17 \tabularnewline
177 & 12 & 12 & 4.22139409726594e-17 \tabularnewline
178 & 12 & 12 & -1.52358147313267e-18 \tabularnewline
179 & 14 & 14 & -6.35805088406545e-17 \tabularnewline
180 & 12 & 12 & 1.5537334291736e-16 \tabularnewline
181 & 16 & 16 & -8.77183982453098e-17 \tabularnewline
182 & 11 & 11 & 3.08450984587646e-17 \tabularnewline
183 & 19 & 19 & 4.14959840735588e-16 \tabularnewline
184 & 15 & 15 & -2.62765880050525e-17 \tabularnewline
185 & 8 & 8 & -1.48793006245311e-16 \tabularnewline
186 & 16 & 16 & 8.76784688049716e-18 \tabularnewline
187 & 17 & 17 & -9.58114996116628e-17 \tabularnewline
188 & 12 & 12 & 9.93119219664588e-17 \tabularnewline
189 & 11 & 11 & 2.08866822805811e-17 \tabularnewline
190 & 11 & 11 & -9.5186143950854e-17 \tabularnewline
191 & 14 & 14 & -1.88166065478576e-17 \tabularnewline
192 & 16 & 16 & -2.35361652590574e-17 \tabularnewline
193 & 12 & 12 & -7.90565546845695e-18 \tabularnewline
194 & 16 & 16 & -7.70005918191211e-17 \tabularnewline
195 & 13 & 13 & 1.98341791193701e-18 \tabularnewline
196 & 15 & 15 & -5.14694064145262e-17 \tabularnewline
197 & 16 & 16 & -2.35322351437047e-16 \tabularnewline
198 & 16 & 16 & 5.84401552501175e-17 \tabularnewline
199 & 14 & 14 & -8.16779411742105e-17 \tabularnewline
200 & 16 & 16 & 6.99425349019296e-17 \tabularnewline
201 & 16 & 16 & 1.03477152566704e-16 \tabularnewline
202 & 14 & 14 & 8.63208681605092e-17 \tabularnewline
203 & 11 & 11 & 1.32879525263642e-16 \tabularnewline
204 & 12 & 12 & 4.30498560151617e-17 \tabularnewline
205 & 15 & 15 & -1.55572316767153e-16 \tabularnewline
206 & 15 & 15 & 2.72760470188797e-17 \tabularnewline
207 & 16 & 16 & 4.04492631127119e-17 \tabularnewline
208 & 16 & 16 & 1.07987396690478e-17 \tabularnewline
209 & 11 & 11 & 1.18472859845156e-16 \tabularnewline
210 & 15 & 15 & -1.26396416155576e-16 \tabularnewline
211 & 12 & 12 & 3.47324393686826e-17 \tabularnewline
212 & 12 & 12 & 1.47114331754982e-16 \tabularnewline
213 & 15 & 15 & -6.35884841715272e-17 \tabularnewline
214 & 15 & 15 & 1.2340877414657e-16 \tabularnewline
215 & 16 & 16 & -2.14273631647745e-16 \tabularnewline
216 & 14 & 14 & 1.95346419927467e-16 \tabularnewline
217 & 17 & 17 & 1.49632403006136e-16 \tabularnewline
218 & 14 & 14 & -1.31030858249358e-17 \tabularnewline
219 & 13 & 13 & -1.08420594899898e-17 \tabularnewline
220 & 15 & 15 & 4.10151998936579e-17 \tabularnewline
221 & 13 & 13 & -2.65867152102666e-17 \tabularnewline
222 & 14 & 14 & -1.36024061312366e-17 \tabularnewline
223 & 15 & 15 & 2.16863172817602e-17 \tabularnewline
224 & 12 & 12 & 1.39204405548261e-17 \tabularnewline
225 & 13 & 13 & 6.60683085541834e-17 \tabularnewline
226 & 8 & 8 & -1.78018903032714e-16 \tabularnewline
227 & 14 & 14 & 3.81656199840313e-17 \tabularnewline
228 & 14 & 14 & 2.73411055272852e-18 \tabularnewline
229 & 11 & 11 & -6.87003940841005e-17 \tabularnewline
230 & 12 & 12 & -9.51662284624673e-17 \tabularnewline
231 & 13 & 13 & -5.82078385392791e-17 \tabularnewline
232 & 10 & 10 & -1.96810924806742e-16 \tabularnewline
233 & 16 & 16 & -2.36104508990807e-16 \tabularnewline
234 & 18 & 18 & 9.73731736612677e-18 \tabularnewline
235 & 13 & 13 & 3.05577261129989e-17 \tabularnewline
236 & 11 & 11 & 3.84827184694763e-17 \tabularnewline
237 & 4 & 4 & -2.18483378261541e-16 \tabularnewline
238 & 13 & 13 & -8.32449428801257e-17 \tabularnewline
239 & 16 & 16 & 8.30388419490023e-17 \tabularnewline
240 & 10 & 10 & 1.08940410707996e-16 \tabularnewline
241 & 12 & 12 & -3.5932874020546e-17 \tabularnewline
242 & 12 & 12 & 4.04195641875445e-17 \tabularnewline
243 & 10 & 10 & 2.22482403451848e-17 \tabularnewline
244 & 13 & 13 & -1.21089488472482e-17 \tabularnewline
245 & 15 & 15 & 6.11484567379523e-17 \tabularnewline
246 & 12 & 12 & 5.6963162837555e-17 \tabularnewline
247 & 14 & 14 & 1.09173001732896e-16 \tabularnewline
248 & 10 & 10 & 1.02455589497642e-16 \tabularnewline
249 & 12 & 12 & -7.64051349140271e-17 \tabularnewline
250 & 12 & 12 & 6.26015063115869e-17 \tabularnewline
251 & 11 & 11 & -5.146819756764e-17 \tabularnewline
252 & 10 & 10 & 5.77712485380279e-17 \tabularnewline
253 & 12 & 12 & 9.78075005028212e-18 \tabularnewline
254 & 16 & 16 & -7.57701718367407e-17 \tabularnewline
255 & 12 & 12 & 3.71942887391307e-17 \tabularnewline
256 & 14 & 14 & -1.09480875236225e-17 \tabularnewline
257 & 16 & 16 & 2.18670411167949e-16 \tabularnewline
258 & 14 & 14 & -1.18134024224867e-16 \tabularnewline
259 & 13 & 13 & 7.48003792223316e-18 \tabularnewline
260 & 4 & 4 & -3.52537230481938e-17 \tabularnewline
261 & 15 & 15 & 1.09714250069526e-16 \tabularnewline
262 & 11 & 11 & -4.23899059927633e-17 \tabularnewline
263 & 11 & 11 & 2.62897215568266e-17 \tabularnewline
264 & 14 & 14 & -9.99001456225595e-17 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190339&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]13[/C][C]13[/C][C]-1.45145152277389e-18[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]16[/C][C]9.13382281187284e-17[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]19[/C][C]2.20080812421479e-16[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]15[/C][C]2.91131368272878e-16[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]14[/C][C]-1.83785412959099e-17[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]13[/C][C]1.47592556469601e-16[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]19[/C][C]-2.14814933356497e-17[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]15[/C][C]7.75199657230604e-17[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]14[/C][C]-2.05182447936475e-15[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]15[/C][C]9.62410813914866e-17[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]16[/C][C]7.85385461039742e-17[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16[/C][C]1.07531583039445e-16[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]16[/C][C]-1.29216766437425e-17[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]16[/C][C]2.66834699914131e-17[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17[/C][C]-6.4936073361718e-18[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15[/C][C]1.325330699211e-17[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]15[/C][C]4.24657846245047e-17[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]20[/C][C]1.40677982937323e-16[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]18[/C][C]8.79253859218245e-18[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]16[/C][C]-2.8626478281246e-17[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]16[/C][C]5.82748188361095e-17[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]16[/C][C]3.77735641477304e-17[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]19[/C][C]-1.52364038465625e-16[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]16[/C][C]2.40251547160884e-18[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]17[/C][C]3.74148914273145e-17[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]17[/C][C]-1.75715879626839e-17[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]16[/C][C]3.62099381836029e-17[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]15[/C][C]9.0501729656722e-18[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]16[/C][C]3.30078187093899e-17[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14[/C][C]1.07678824789097e-16[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15[/C][C]6.37198087735031e-17[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12[/C][C]1.39266515503507e-16[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14[/C][C]-3.95987452853688e-17[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]16[/C][C]1.57782939346024e-17[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14[/C][C]3.49108358973607e-17[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]10[/C][C]-2.28837617189125e-16[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]10[/C][C]1.38298912807948e-16[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]14[/C][C]-1.31415026081835e-18[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]16[/C][C]-4.50670023380202e-17[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]16[/C][C]-3.24048719677377e-17[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]16[/C][C]3.15938321313444e-17[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]14[/C][C]-1.58644527001878e-17[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]20[/C][C]-1.13115475341791e-16[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14[/C][C]-8.4205038314338e-17[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14[/C][C]-3.76555848966257e-17[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]11[/C][C]1.71658458255001e-16[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]14[/C][C]7.78112582695865e-17[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15[/C][C]3.42530161207263e-17[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]16[/C][C]-4.67461078036641e-17[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]14[/C][C]1.61871146693924e-16[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16[/C][C]8.35525882758815e-17[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14[/C][C]-4.73561959356755e-18[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]12[/C][C]2.04779445057439e-16[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]16[/C][C]3.40527870555137e-17[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]9[/C][C]-1.48036674294063e-16[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]14[/C][C]6.11489634687792e-17[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]16[/C][C]3.03583523892933e-17[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]16[/C][C]4.97705904859719e-17[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15[/C][C]3.12105550153574e-17[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]16[/C][C]1.01009962501312e-17[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]12[/C][C]1.69064364291339e-16[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]16[/C][C]5.88091682557375e-17[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16[/C][C]-2.0598932823686e-17[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14[/C][C]-6.08273341316093e-18[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]16[/C][C]2.87364815093477e-17[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]17[/C][C]2.86785999857939e-17[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]18[/C][C]7.30435824472102e-17[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]18[/C][C]-1.62372801622125e-16[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]12[/C][C]2.33527753270681e-16[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]16[/C][C]-1.33022756084014e-16[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]10[/C][C]2.53162206071888e-16[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14[/C][C]8.52909694737138e-18[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]18[/C][C]2.56535306277374e-17[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]18[/C][C]1.3729797963058e-16[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]16[/C][C]7.42932268971479e-19[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]17[/C][C]-1.23894876598315e-16[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16[/C][C]8.4789353821386e-17[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]16[/C][C]4.56905779004254e-17[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]13[/C][C]1.05946251446967e-16[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]16[/C][C]5.21599456906539e-17[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]16[/C][C]1.61374974103592e-17[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]16[/C][C]5.94642266030468e-17[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15[/C][C]2.19616392678152e-17[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]15[/C][C]5.54820539816556e-17[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]16[/C][C]8.92658485863697e-18[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14[/C][C]1.75630800855819e-17[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]16[/C][C]5.13884139509994e-17[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]16[/C][C]2.03781258908467e-17[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]15[/C][C]-1.03663657305183e-16[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]12[/C][C]-4.2170810208847e-17[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]17[/C][C]7.27105744266447e-17[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]16[/C][C]3.76135746323378e-17[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15[/C][C]-3.82614885196352e-17[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13[/C][C]-1.40279670152558e-17[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]16[/C][C]-3.12035376786387e-17[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]16[/C][C]-1.28081722090695e-16[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]16[/C][C]5.90476242008081e-17[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]16[/C][C]-1.01306612964251e-16[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14[/C][C]2.21439905096732e-17[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]16[/C][C]-7.50898180015081e-17[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]16[/C][C]5.36179649950678e-19[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]20[/C][C]-2.37155954962517e-16[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]15[/C][C]-3.8369631508224e-17[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]16[/C][C]-2.67013326189195e-17[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]13[/C][C]-3.67070062470712e-17[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]17[/C][C]1.82034306386219e-16[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]16[/C][C]-3.84916675760016e-17[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]16[/C][C]-8.14526971637787e-17[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12[/C][C]-9.22592492559904e-17[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]16[/C][C]7.88197935604034e-17[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16[/C][C]-6.86183445492531e-17[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]17[/C][C]-1.30380223653069e-17[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]13[/C][C]-5.86477358522615e-17[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]12[/C][C]6.04288957434411e-17[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]18[/C][C]-6.05106549949209e-17[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14[/C][C]-3.79376599438271e-17[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]14[/C][C]-4.47525503114943e-17[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]13[/C][C]1.11979000559608e-18[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]16[/C][C]-1.83800595290055e-17[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]13[/C][C]-2.73641060669539e-17[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]16[/C][C]-6.00028728881568e-17[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]13[/C][C]8.72923941850241e-17[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16[/C][C]-8.92486389404245e-17[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15[/C][C]2.10827288571686e-17[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16[/C][C]-6.39658135889376e-17[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]15[/C][C]1.01163166115667e-17[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]17[/C][C]9.82231628561124e-18[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]15[/C][C]4.96981254429536e-17[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]12[/C][C]-9.90415651722252e-17[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]16[/C][C]-4.68132414647345e-17[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]10[/C][C]-1.74068569794559e-17[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]16[/C][C]-1.10885587182588e-16[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]12[/C][C]9.15735735812237e-17[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]14[/C][C]-9.25334759980161e-18[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15[/C][C]-5.15451391978378e-17[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]13[/C][C]-1.1615213376683e-16[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]15[/C][C]7.28997776456746e-17[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]11[/C][C]-1.12448577436544e-16[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]12[/C][C]6.25560341237487e-17[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]11[/C][C]-1.02348110850709e-16[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]16[/C][C]1.12330964930187e-16[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]15[/C][C]-7.34012793830642e-17[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]17[/C][C]-2.09703061002804e-16[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]16[/C][C]-1.09115174332596e-16[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]10[/C][C]5.18345097593176e-16[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]18[/C][C]-1.24025104083988e-16[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]13[/C][C]-3.38556418808434e-17[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]16[/C][C]1.58635345205838e-16[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]13[/C][C]-4.00635756829946e-17[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]10[/C][C]4.35155502661914e-17[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15[/C][C]-3.43837688782738e-17[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]16[/C][C]7.68108530534051e-17[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]16[/C][C]1.34408472380051e-16[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]14[/C][C]-1.16326902664211e-16[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]10[/C][C]5.63298345187444e-17[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]17[/C][C]3.017028556686e-17[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]13[/C][C]-4.47710386545275e-17[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]15[/C][C]-9.33430813097778e-17[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]16[/C][C]1.84316922000909e-16[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12[/C][C]-1.06075721525982e-17[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]13[/C][C]-9.17217266143978e-17[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]13[/C][C]4.56152158099252e-17[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12[/C][C]-2.5874000376772e-17[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]17[/C][C]-8.10074867061527e-17[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]15[/C][C]-5.58380681886873e-17[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]10[/C][C]1.5854474688277e-16[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14[/C][C]-3.74444173054824e-17[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]11[/C][C]3.84621735512178e-17[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]13[/C][C]7.62599845374198e-17[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]16[/C][C]-1.17684548579949e-16[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]12[/C][C]-4.350007754772e-17[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]16[/C][C]-1.3640331422257e-17[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]12[/C][C]1.29744768217893e-16[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]9[/C][C]-9.12804241403528e-17[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]12[/C][C]-4.66862750548388e-17[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]15[/C][C]-9.59800703830095e-17[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12[/C][C]4.22139409726594e-17[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12[/C][C]-1.52358147313267e-18[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]14[/C][C]-6.35805088406545e-17[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]12[/C][C]1.5537334291736e-16[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]16[/C][C]-8.77183982453098e-17[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11[/C][C]3.08450984587646e-17[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]19[/C][C]4.14959840735588e-16[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15[/C][C]-2.62765880050525e-17[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]8[/C][C]-1.48793006245311e-16[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]16[/C][C]8.76784688049716e-18[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]17[/C][C]-9.58114996116628e-17[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12[/C][C]9.93119219664588e-17[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11[/C][C]2.08866822805811e-17[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]11[/C][C]-9.5186143950854e-17[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14[/C][C]-1.88166065478576e-17[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]16[/C][C]-2.35361652590574e-17[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]12[/C][C]-7.90565546845695e-18[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]16[/C][C]-7.70005918191211e-17[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13[/C][C]1.98341791193701e-18[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15[/C][C]-5.14694064145262e-17[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]16[/C][C]-2.35322351437047e-16[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]16[/C][C]5.84401552501175e-17[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]14[/C][C]-8.16779411742105e-17[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]16[/C][C]6.99425349019296e-17[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]16[/C][C]1.03477152566704e-16[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]14[/C][C]8.63208681605092e-17[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]11[/C][C]1.32879525263642e-16[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]12[/C][C]4.30498560151617e-17[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]15[/C][C]-1.55572316767153e-16[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]15[/C][C]2.72760470188797e-17[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]16[/C][C]4.04492631127119e-17[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]16[/C][C]1.07987396690478e-17[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]11[/C][C]1.18472859845156e-16[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]15[/C][C]-1.26396416155576e-16[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]12[/C][C]3.47324393686826e-17[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]12[/C][C]1.47114331754982e-16[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]15[/C][C]-6.35884841715272e-17[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]15[/C][C]1.2340877414657e-16[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]16[/C][C]-2.14273631647745e-16[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]14[/C][C]1.95346419927467e-16[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]17[/C][C]1.49632403006136e-16[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14[/C][C]-1.31030858249358e-17[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]13[/C][C]-1.08420594899898e-17[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15[/C][C]4.10151998936579e-17[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]13[/C][C]-2.65867152102666e-17[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14[/C][C]-1.36024061312366e-17[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]15[/C][C]2.16863172817602e-17[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]12[/C][C]1.39204405548261e-17[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]13[/C][C]6.60683085541834e-17[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]8[/C][C]-1.78018903032714e-16[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]14[/C][C]3.81656199840313e-17[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]14[/C][C]2.73411055272852e-18[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]11[/C][C]-6.87003940841005e-17[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12[/C][C]-9.51662284624673e-17[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]13[/C][C]-5.82078385392791e-17[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]10[/C][C]-1.96810924806742e-16[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]16[/C][C]-2.36104508990807e-16[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]18[/C][C]9.73731736612677e-18[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13[/C][C]3.05577261129989e-17[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]11[/C][C]3.84827184694763e-17[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]4[/C][C]-2.18483378261541e-16[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13[/C][C]-8.32449428801257e-17[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]16[/C][C]8.30388419490023e-17[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]10[/C][C]1.08940410707996e-16[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12[/C][C]-3.5932874020546e-17[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]12[/C][C]4.04195641875445e-17[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]10[/C][C]2.22482403451848e-17[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]13[/C][C]-1.21089488472482e-17[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]15[/C][C]6.11484567379523e-17[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]12[/C][C]5.6963162837555e-17[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]14[/C][C]1.09173001732896e-16[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]10[/C][C]1.02455589497642e-16[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]12[/C][C]-7.64051349140271e-17[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]12[/C][C]6.26015063115869e-17[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11[/C][C]-5.146819756764e-17[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]10[/C][C]5.77712485380279e-17[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]12[/C][C]9.78075005028212e-18[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]16[/C][C]-7.57701718367407e-17[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]12[/C][C]3.71942887391307e-17[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]14[/C][C]-1.09480875236225e-17[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]16[/C][C]2.18670411167949e-16[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]14[/C][C]-1.18134024224867e-16[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]13[/C][C]7.48003792223316e-18[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]4[/C][C]-3.52537230481938e-17[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]15[/C][C]1.09714250069526e-16[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]11[/C][C]-4.23899059927633e-17[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11[/C][C]2.62897215568266e-17[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]14[/C][C]-9.99001456225595e-17[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190339&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190339&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	13	13	-1.45145152277389e-18
2	16	16	9.13382281187284e-17
3	19	19	2.20080812421479e-16
4	15	15	2.91131368272878e-16
5	14	14	-1.83785412959099e-17
6	13	13	1.47592556469601e-16
7	19	19	-2.14814933356497e-17
8	15	15	7.75199657230604e-17
9	14	14	-2.05182447936475e-15
10	15	15	9.62410813914866e-17
11	16	16	7.85385461039742e-17
12	16	16	1.07531583039445e-16
13	16	16	-1.29216766437425e-17
14	16	16	2.66834699914131e-17
15	17	17	-6.4936073361718e-18
16	15	15	1.325330699211e-17
17	15	15	4.24657846245047e-17
18	20	20	1.40677982937323e-16
19	18	18	8.79253859218245e-18
20	16	16	-2.8626478281246e-17
21	16	16	5.82748188361095e-17
22	16	16	3.77735641477304e-17
23	19	19	-1.52364038465625e-16
24	16	16	2.40251547160884e-18
25	17	17	3.74148914273145e-17
26	17	17	-1.75715879626839e-17
27	16	16	3.62099381836029e-17
28	15	15	9.0501729656722e-18
29	16	16	3.30078187093899e-17
30	14	14	1.07678824789097e-16
31	15	15	6.37198087735031e-17
32	12	12	1.39266515503507e-16
33	14	14	-3.95987452853688e-17
34	16	16	1.57782939346024e-17
35	14	14	3.49108358973607e-17
36	10	10	-2.28837617189125e-16
37	10	10	1.38298912807948e-16
38	14	14	-1.31415026081835e-18
39	16	16	-4.50670023380202e-17
40	16	16	-3.24048719677377e-17
41	16	16	3.15938321313444e-17
42	14	14	-1.58644527001878e-17
43	20	20	-1.13115475341791e-16
44	14	14	-8.4205038314338e-17
45	14	14	-3.76555848966257e-17
46	11	11	1.71658458255001e-16
47	14	14	7.78112582695865e-17
48	15	15	3.42530161207263e-17
49	16	16	-4.67461078036641e-17
50	14	14	1.61871146693924e-16
51	16	16	8.35525882758815e-17
52	14	14	-4.73561959356755e-18
53	12	12	2.04779445057439e-16
54	16	16	3.40527870555137e-17
55	9	9	-1.48036674294063e-16
56	14	14	6.11489634687792e-17
57	16	16	3.03583523892933e-17
58	16	16	4.97705904859719e-17
59	15	15	3.12105550153574e-17
60	16	16	1.01009962501312e-17
61	12	12	1.69064364291339e-16
62	16	16	5.88091682557375e-17
63	16	16	-2.0598932823686e-17
64	14	14	-6.08273341316093e-18
65	16	16	2.87364815093477e-17
66	17	17	2.86785999857939e-17
67	18	18	7.30435824472102e-17
68	18	18	-1.62372801622125e-16
69	12	12	2.33527753270681e-16
70	16	16	-1.33022756084014e-16
71	10	10	2.53162206071888e-16
72	14	14	8.52909694737138e-18
73	18	18	2.56535306277374e-17
74	18	18	1.3729797963058e-16
75	16	16	7.42932268971479e-19
76	17	17	-1.23894876598315e-16
77	16	16	8.4789353821386e-17
78	16	16	4.56905779004254e-17
79	13	13	1.05946251446967e-16
80	16	16	5.21599456906539e-17
81	16	16	1.61374974103592e-17
82	16	16	5.94642266030468e-17
83	15	15	2.19616392678152e-17
84	15	15	5.54820539816556e-17
85	16	16	8.92658485863697e-18
86	14	14	1.75630800855819e-17
87	16	16	5.13884139509994e-17
88	16	16	2.03781258908467e-17
89	15	15	-1.03663657305183e-16
90	12	12	-4.2170810208847e-17
91	17	17	7.27105744266447e-17
92	16	16	3.76135746323378e-17
93	15	15	-3.82614885196352e-17
94	13	13	-1.40279670152558e-17
95	16	16	-3.12035376786387e-17
96	16	16	-1.28081722090695e-16
97	16	16	5.90476242008081e-17
98	16	16	-1.01306612964251e-16
99	14	14	2.21439905096732e-17
100	16	16	-7.50898180015081e-17
101	16	16	5.36179649950678e-19
102	20	20	-2.37155954962517e-16
103	15	15	-3.8369631508224e-17
104	16	16	-2.67013326189195e-17
105	13	13	-3.67070062470712e-17
106	17	17	1.82034306386219e-16
107	16	16	-3.84916675760016e-17
108	16	16	-8.14526971637787e-17
109	12	12	-9.22592492559904e-17
110	16	16	7.88197935604034e-17
111	16	16	-6.86183445492531e-17
112	17	17	-1.30380223653069e-17
113	13	13	-5.86477358522615e-17
114	12	12	6.04288957434411e-17
115	18	18	-6.05106549949209e-17
116	14	14	-3.79376599438271e-17
117	14	14	-4.47525503114943e-17
118	13	13	1.11979000559608e-18
119	16	16	-1.83800595290055e-17
120	13	13	-2.73641060669539e-17
121	16	16	-6.00028728881568e-17
122	13	13	8.72923941850241e-17
123	16	16	-8.92486389404245e-17
124	15	15	2.10827288571686e-17
125	16	16	-6.39658135889376e-17
126	15	15	1.01163166115667e-17
127	17	17	9.82231628561124e-18
128	15	15	4.96981254429536e-17
129	12	12	-9.90415651722252e-17
130	16	16	-4.68132414647345e-17
131	10	10	-1.74068569794559e-17
132	16	16	-1.10885587182588e-16
133	12	12	9.15735735812237e-17
134	14	14	-9.25334759980161e-18
135	15	15	-5.15451391978378e-17
136	13	13	-1.1615213376683e-16
137	15	15	7.28997776456746e-17
138	11	11	-1.12448577436544e-16
139	12	12	6.25560341237487e-17
140	11	11	-1.02348110850709e-16
141	16	16	1.12330964930187e-16
142	15	15	-7.34012793830642e-17
143	17	17	-2.09703061002804e-16
144	16	16	-1.09115174332596e-16
145	10	10	5.18345097593176e-16
146	18	18	-1.24025104083988e-16
147	13	13	-3.38556418808434e-17
148	16	16	1.58635345205838e-16
149	13	13	-4.00635756829946e-17
150	10	10	4.35155502661914e-17
151	15	15	-3.43837688782738e-17
152	16	16	7.68108530534051e-17
153	16	16	1.34408472380051e-16
154	14	14	-1.16326902664211e-16
155	10	10	5.63298345187444e-17
156	17	17	3.017028556686e-17
157	13	13	-4.47710386545275e-17
158	15	15	-9.33430813097778e-17
159	16	16	1.84316922000909e-16
160	12	12	-1.06075721525982e-17
161	13	13	-9.17217266143978e-17
162	13	13	4.56152158099252e-17
163	12	12	-2.5874000376772e-17
164	17	17	-8.10074867061527e-17
165	15	15	-5.58380681886873e-17
166	10	10	1.5854474688277e-16
167	14	14	-3.74444173054824e-17
168	11	11	3.84621735512178e-17
169	13	13	7.62599845374198e-17
170	16	16	-1.17684548579949e-16
171	12	12	-4.350007754772e-17
172	16	16	-1.3640331422257e-17
173	12	12	1.29744768217893e-16
174	9	9	-9.12804241403528e-17
175	12	12	-4.66862750548388e-17
176	15	15	-9.59800703830095e-17
177	12	12	4.22139409726594e-17
178	12	12	-1.52358147313267e-18
179	14	14	-6.35805088406545e-17
180	12	12	1.5537334291736e-16
181	16	16	-8.77183982453098e-17
182	11	11	3.08450984587646e-17
183	19	19	4.14959840735588e-16
184	15	15	-2.62765880050525e-17
185	8	8	-1.48793006245311e-16
186	16	16	8.76784688049716e-18
187	17	17	-9.58114996116628e-17
188	12	12	9.93119219664588e-17
189	11	11	2.08866822805811e-17
190	11	11	-9.5186143950854e-17
191	14	14	-1.88166065478576e-17
192	16	16	-2.35361652590574e-17
193	12	12	-7.90565546845695e-18
194	16	16	-7.70005918191211e-17
195	13	13	1.98341791193701e-18
196	15	15	-5.14694064145262e-17
197	16	16	-2.35322351437047e-16
198	16	16	5.84401552501175e-17
199	14	14	-8.16779411742105e-17
200	16	16	6.99425349019296e-17
201	16	16	1.03477152566704e-16
202	14	14	8.63208681605092e-17
203	11	11	1.32879525263642e-16
204	12	12	4.30498560151617e-17
205	15	15	-1.55572316767153e-16
206	15	15	2.72760470188797e-17
207	16	16	4.04492631127119e-17
208	16	16	1.07987396690478e-17
209	11	11	1.18472859845156e-16
210	15	15	-1.26396416155576e-16
211	12	12	3.47324393686826e-17
212	12	12	1.47114331754982e-16
213	15	15	-6.35884841715272e-17
214	15	15	1.2340877414657e-16
215	16	16	-2.14273631647745e-16
216	14	14	1.95346419927467e-16
217	17	17	1.49632403006136e-16
218	14	14	-1.31030858249358e-17
219	13	13	-1.08420594899898e-17
220	15	15	4.10151998936579e-17
221	13	13	-2.65867152102666e-17
222	14	14	-1.36024061312366e-17
223	15	15	2.16863172817602e-17
224	12	12	1.39204405548261e-17
225	13	13	6.60683085541834e-17
226	8	8	-1.78018903032714e-16
227	14	14	3.81656199840313e-17
228	14	14	2.73411055272852e-18
229	11	11	-6.87003940841005e-17
230	12	12	-9.51662284624673e-17
231	13	13	-5.82078385392791e-17
232	10	10	-1.96810924806742e-16
233	16	16	-2.36104508990807e-16
234	18	18	9.73731736612677e-18
235	13	13	3.05577261129989e-17
236	11	11	3.84827184694763e-17
237	4	4	-2.18483378261541e-16
238	13	13	-8.32449428801257e-17
239	16	16	8.30388419490023e-17
240	10	10	1.08940410707996e-16
241	12	12	-3.5932874020546e-17
242	12	12	4.04195641875445e-17
243	10	10	2.22482403451848e-17
244	13	13	-1.21089488472482e-17
245	15	15	6.11484567379523e-17
246	12	12	5.6963162837555e-17
247	14	14	1.09173001732896e-16
248	10	10	1.02455589497642e-16
249	12	12	-7.64051349140271e-17
250	12	12	6.26015063115869e-17
251	11	11	-5.146819756764e-17
252	10	10	5.77712485380279e-17
253	12	12	9.78075005028212e-18
254	16	16	-7.57701718367407e-17
255	12	12	3.71942887391307e-17
256	14	14	-1.09480875236225e-17
257	16	16	2.18670411167949e-16
258	14	14	-1.18134024224867e-16
259	13	13	7.48003792223316e-18
260	4	4	-3.52537230481938e-17
261	15	15	1.09714250069526e-16
262	11	11	-4.23899059927633e-17
263	11	11	2.62897215568266e-17
264	14	14	-9.99001456225595e-17

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
19	0.40228834589082	0.804576691781641	0.597711654109179
20	0.555319611918205	0.88936077616359	0.444680388081795
21	0.219406574488551	0.438813148977102	0.780593425511449
22	0.921069210027943	0.157861579944115	0.0789307899720573
23	0.984425201949361	0.0311495961012781	0.015574798050639
24	0.980335576578819	0.0393288468423628	0.0196644234211814
25	0.9149896124897	0.170020775020599	0.0850103875102996
26	0.000324993743970001	0.000649987487940002	0.99967500625603
27	0.0121619505025199	0.0243239010050397	0.98783804949748
28	1	3.71711121170752e-20	1.85855560585376e-20
29	0.929952407417836	0.140095185164328	0.0700475925821639
30	0.00818883043787245	0.0163776608757449	0.991811169562128
31	0.983695065517823	0.0326098689643546	0.0163049344821773
32	0.22777546228606	0.455550924572119	0.772224537713941
33	0.999999995836972	8.32605643792285e-09	4.16302821896143e-09
34	8.45639605661226e-09	1.69127921132245e-08	0.999999991543604
35	0.792927773596607	0.414144452806786	0.207072226403393
36	0.0750621955369129	0.150124391073826	0.924937804463087
37	9.97515352223561e-07	1.99503070444712e-06	0.999999002484648
38	0.300817059985505	0.601634119971011	0.699182940014495
39	0.952218781843188	0.0955624363136233	0.0477812181568116
40	3.34542976825003e-09	6.69085953650006e-09	0.99999999665457
41	5.1622663195582e-06	1.03245326391164e-05	0.99999483773368
42	0.999999999999997	6.21058167798393e-15	3.10529083899196e-15
43	0.999999999307931	1.384138672244e-09	6.92069336122e-10
44	0.559927873642394	0.880144252715212	0.440072126357606
45	0.998777052090295	0.00244589581940994	0.00122294790970497
46	0.999698331091523	0.00060333781695406	0.00030166890847703
47	0.06797925840233	0.13595851680466	0.93202074159767
48	0.999999998071932	3.85613524211471e-09	1.92806762105735e-09
49	1	6.66466807386733e-38	3.33233403693366e-38
50	0.974466940347459	0.0510661193050818	0.0255330596525409
51	9.39779328489027e-09	1.87955865697805e-08	0.999999990602207
52	0.954113144552137	0.0917737108957261	0.0458868554478631
53	1.32036612928931e-06	2.64073225857862e-06	0.999998679633871
54	0.224598151866797	0.449196303733594	0.775401848133203
55	0.999999999999972	5.58405117295423e-14	2.79202558647712e-14
56	0.00343596587561769	0.00687193175123537	0.996564034124382
57	0.999564044022912	0.000871911954175242	0.000435955977087621
58	0.605630399465222	0.788739201069556	0.394369600534778
59	0.995932713812751	0.00813457237449721	0.0040672861872486
60	4.90330117263184e-05	9.80660234526368e-05	0.999950966988274
61	1	2.83223115071108e-33	1.41611557535554e-33
62	0.999997960103697	4.07979260668682e-06	2.03989630334341e-06
63	1	3.5028916671508e-19	1.7514458335754e-19
64	7.06709236608769e-14	1.41341847321754e-13	0.999999999999929
65	1.54773334266328e-10	3.09546668532656e-10	0.999999999845227
66	2.47264810314444e-24	4.94529620628889e-24	1
67	0.698665804569396	0.602668390861207	0.301334195430604
68	1.15861258576554e-05	2.31722517153109e-05	0.999988413874142
69	8.37622982836868e-14	1.67524596567374e-13	0.999999999999916
70	3.74178160002837e-11	7.48356320005673e-11	0.999999999962582
71	1.70205694153655e-17	3.4041138830731e-17	1
72	0.999996087594178	7.82481164389571e-06	3.91240582194785e-06
73	0.00036411092597973	0.00072822185195946	0.99963588907402
74	0.999999997712796	4.57440743687688e-09	2.28720371843844e-09
75	0.466077475098999	0.932154950197998	0.533922524901001
76	0.999658352483215	0.000683295033569156	0.000341647516784578
77	0.999860655086887	0.000278689826225016	0.000139344913112508
78	2.6833313665706e-23	5.3666627331412e-23	1
79	0.0827527427151601	0.16550548543032	0.91724725728484
80	0.000129439722594522	0.000258879445189044	0.999870560277406
81	1.17551959287488e-13	2.35103918574977e-13	0.999999999999882
82	0.828171869818904	0.343656260362191	0.171828130181096
83	0.999999999475936	1.04812780928e-09	5.24063904640001e-10
84	0.00135018676139402	0.00270037352278805	0.998649813238606
85	0.823070357855832	0.353859284288336	0.176929642144168
86	5.27606702574724e-09	1.05521340514945e-08	0.999999994723933
87	6.63648623371417e-09	1.32729724674283e-08	0.999999993363514
88	0.999975817590579	4.83648188416528e-05	2.41824094208264e-05
89	1.97353094268119e-05	3.94706188536238e-05	0.999980264690573
90	0.4757727202199	0.9515454404398	0.5242272797801
91	3.24697087922979e-07	6.49394175845957e-07	0.999999675302912
92	1.30716268965404e-07	2.61432537930809e-07	0.999999869283731
93	0.99971827457237	0.000563450855260668	0.000281725427630334
94	2.24332243514111e-12	4.48664487028222e-12	0.999999999997757
95	0.298784475381549	0.597568950763098	0.701215524618451
96	0.10342468702221	0.20684937404442	0.89657531297779
97	0.0804586944895623	0.160917388979125	0.919541305510438
98	0.999999999898452	2.03096663603641e-10	1.0154833180182e-10
99	1.99563483359068e-08	3.99126966718135e-08	0.999999980043652
100	0.999478717036258	0.00104256592748431	0.000521282963742157
101	0.0194479799160829	0.0388959598321659	0.980552020083917
102	5.63957045055609e-32	1.12791409011122e-31	1
103	0.999999999626569	7.46860964247596e-10	3.73430482123798e-10
104	0.999999999897422	2.05156872163919e-10	1.0257843608196e-10
105	0.0454157991670118	0.0908315983340236	0.954584200832988
106	0.0513916661138937	0.102783332227787	0.948608333886106
107	0.99999990925488	1.81490239874159e-07	9.07451199370795e-08
108	2.46092768054643e-09	4.92185536109285e-09	0.999999997539072
109	0.955767519371303	0.0884649612573936	0.0442324806286968
110	8.85430035815885e-38	1.77086007163177e-37	1
111	0.910043343080715	0.179913313838571	0.0899566569192854
112	4.02264989991461e-09	8.04529979982922e-09	0.99999999597735
113	0.999950035773404	9.99284531911442e-05	4.99642265955721e-05
114	3.85943207318273e-08	7.71886414636545e-08	0.999999961405679
115	1.10343223125912e-07	2.20686446251824e-07	0.999999889656777
116	0.855071512643574	0.289856974712853	0.144928487356426
117	7.5214567813668e-21	1.50429135627336e-20	1
118	0.000881945515019417	0.00176389103003883	0.999118054484981
119	1	3.64858735516655e-20	1.82429367758327e-20
120	9.05887699030417e-09	1.81177539806083e-08	0.999999990941123
121	0.999999999970649	5.87009379933526e-11	2.93504689966763e-11
122	9.01155161647999e-15	1.802310323296e-14	0.999999999999991
123	0.999303765588447	0.00139246882310625	0.000696234411553123
124	4.88723627929409e-31	9.77447255858819e-31	1
125	1	2.2312844893789e-17	1.11564224468945e-17
126	1	1.97226843654285e-21	9.86134218271423e-22
127	0.00684739563639831	0.0136947912727966	0.993152604363602
128	0.670077666592013	0.659844666815975	0.329922333407987
129	1.63603678227241e-40	3.27207356454482e-40	1
130	3.99713952509614e-28	7.99427905019229e-28	1
131	2.0236859850622e-28	4.0473719701244e-28	1
132	3.02869668027751e-23	6.05739336055501e-23	1
133	6.12535841654327e-26	1.22507168330865e-25	1
134	2.54561479658834e-08	5.09122959317668e-08	0.999999974543852
135	0.00060293800412816	0.00120587600825632	0.999397061995872
136	0.00751114718628936	0.0150222943725787	0.992488852813711
137	0.99999999999961	7.79626476979923e-13	3.89813238489962e-13
138	0.999999999909938	1.80124089413312e-10	9.00620447066562e-11
139	9.2821992267036e-15	1.85643984534072e-14	0.999999999999991
140	1.0376847598637e-07	2.0753695197274e-07	0.999999896231524
141	0.937230617755944	0.125538764488112	0.0627693822440561
142	0.638784770665638	0.722430458668724	0.361215229334362
143	0.231569891661029	0.463139783322059	0.768430108338971
144	0.966021907251366	0.0679561854972681	0.0339780927486341
145	0.279954903653576	0.559909807307152	0.720045096346424
146	1.6576029868166e-42	3.31520597363319e-42	1
147	0.038796968257401	0.077593936514802	0.961203031742599
148	2.02515261138506e-21	4.05030522277012e-21	1
149	0.999999999999914	1.72058702809162e-13	8.60293514045811e-14
150	0.749370355927759	0.501259288144482	0.250629644072241
151	0.999999999999991	1.72811274358611e-14	8.64056371793056e-15
152	0.000205394445570046	0.000410788891140093	0.99979460555443
153	3.25535806263963e-48	6.51071612527927e-48	1
154	0.985855203841501	0.0282895923169979	0.0141447961584989
155	2.58142915431639e-11	5.16285830863278e-11	0.999999999974186
156	1	1.49023420917783e-26	7.45117104588917e-27
157	1	4.68225982959741e-17	2.3411299147987e-17
158	0.978526120807812	0.0429477583843767	0.0214738791921884
159	1	4.01763313027514e-31	2.00881656513757e-31
160	0.000213143399944063	0.000426286799888127	0.999786856600056
161	5.9550520689763e-16	1.19101041379526e-15	0.999999999999999
162	1.64688767434609e-13	3.29377534869217e-13	0.999999999999835
163	6.70017643553115e-17	1.34003528710623e-16	1
164	3.83843035710517e-13	7.67686071421033e-13	0.999999999999616
165	1.51994022412039e-17	3.03988044824078e-17	1
166	1.28016620446872e-25	2.56033240893743e-25	1
167	0.593088128741384	0.813823742517231	0.406911871258616
168	2.60321712083954e-13	5.20643424167908e-13	0.99999999999974
169	3.23001622025456e-42	6.46003244050912e-42	1
170	0.999999986847956	2.63040877600586e-08	1.31520438800293e-08
171	2.53986103914762e-29	5.07972207829524e-29	1
172	3.47918468813283e-35	6.95836937626566e-35	1
173	0.999999999999985	3.07955141578191e-14	1.53977570789096e-14
174	8.21141488423181e-90	1.64228297684636e-89	1
175	6.25132849804714e-28	1.25026569960943e-27	1
176	7.43628455566725e-16	1.48725691113345e-15	0.999999999999999
177	0.00326902110384998	0.00653804220769995	0.99673097889615
178	3.59699468959486e-10	7.19398937918973e-10	0.999999999640301
179	1	2.36600663296867e-23	1.18300331648434e-23
180	0.0191543965331648	0.0383087930663295	0.980845603466835
181	1	1.41303783616803e-20	7.06518918084016e-21
182	5.76088519119062e-24	1.15217703823812e-23	1
183	0.999999999989763	2.04733734391415e-11	1.02366867195708e-11
184	2.3562239951615e-32	4.712447990323e-32	1
185	8.91516987275113e-19	1.78303397455023e-18	1
186	0.142847818970043	0.285695637940087	0.857152181029957
187	0.00163802453345996	0.00327604906691993	0.99836197546654
188	5.57689119998738e-65	1.11537823999748e-64	1
189	0.162909792641298	0.325819585282597	0.837090207358702
190	1.21709975568818e-09	2.43419951137637e-09	0.9999999987829
191	3.45217498786514e-07	6.90434997573029e-07	0.999999654782501
192	1.46107455685421e-09	2.92214911370842e-09	0.999999998538925
193	1.25699173002184e-26	2.51398346004368e-26	1
194	0.0983068237218565	0.196613647443713	0.901693176278143
195	0.999996091190104	7.81761979149998e-06	3.90880989574999e-06
196	1	3.37701604961216e-20	1.68850802480608e-20
197	0.896838059550096	0.206323880899808	0.103161940449904
198	0.0165904094230384	0.0331808188460767	0.983409590576962
199	0.0319688337959431	0.0639376675918862	0.968031166204057
200	0.999953682205625	9.26355887509922e-05	4.63177943754961e-05
201	0.999999999999999	1.20903618697438e-15	6.04518093487192e-16
202	0.999744879825246	0.000510240349508426	0.000255120174754213
203	0.00121788534280533	0.00243577068561066	0.998782114657195
204	0.258325724972098	0.516651449944196	0.741674275027902
205	0.566751704037363	0.866496591925275	0.433248295962637
206	0.726452604769142	0.547094790461716	0.273547395230858
207	2.52712265688843e-14	5.05424531377686e-14	0.999999999999975
208	0.948906214257964	0.102187571484071	0.0510937857420357
209	1.87573600738136e-07	3.75147201476272e-07	0.999999812426399
210	6.02441862742376e-51	1.20488372548475e-50	1
211	0.999999864250961	2.71498078699179e-07	1.3574903934959e-07
212	1.11676956350019e-13	2.23353912700038e-13	0.999999999999888
213	0.031260673545819	0.0625213470916379	0.968739326454181
214	0.999969597357861	6.08052842772823e-05	3.04026421386412e-05
215	0.995193025153	0.00961394969399911	0.00480697484699956
216	2.09201122846258e-17	4.18402245692516e-17	1
217	0.102864133423368	0.205728266846736	0.897135866576632
218	1.68882768614764e-14	3.37765537229527e-14	0.999999999999983
219	0.998953967560097	0.00209206487980652	0.00104603243990326
220	0.987390062791942	0.0252198744161153	0.0126099372080577
221	0.00496542006744235	0.0099308401348847	0.995034579932558
222	8.64022300649583e-07	1.72804460129917e-06	0.999999135977699
223	0.232266847240211	0.464533694480422	0.767733152759789
224	4.59472394006803e-28	9.18944788013606e-28	1
225	1.73842839198542e-05	3.47685678397084e-05	0.99998261571608
226	0.999999603919366	7.92161267158628e-07	3.96080633579314e-07
227	2.02349653777178e-75	4.04699307554356e-75	1
228	0.0179935723953922	0.0359871447907844	0.982006427604608
229	0.959439433130366	0.0811211337392681	0.0405605668696341
230	0.0100670470672959	0.0201340941345918	0.989932952932704
231	0.724475547225072	0.551048905549855	0.275524452774928
232	0.999979285551499	4.14288970020791e-05	2.07144485010396e-05
233	3.20392018702718e-07	6.40784037405437e-07	0.999999679607981
234	0.0334871086078533	0.0669742172157066	0.966512891392147
235	9.32318339285568e-38	1.86463667857114e-37	1
236	1.76160151408192e-36	3.52320302816383e-36	1
237	0.0804861613185567	0.160972322637113	0.919513838681443
238	6.96810822832765e-21	1.39362164566553e-20	1
239	0.071969589390123	0.143939178780246	0.928030410609877
240	4.67178843092058e-06	9.34357686184117e-06	0.999995328211569
241	2.90490447052788e-08	5.80980894105576e-08	0.999999970950955
242	0.00173504047923199	0.00347008095846397	0.998264959520768
243	0.94090844523562	0.11818310952876	0.0590915547643798
244	5.0907906434921e-28	1.01815812869842e-27	1
245	0.00900792182580691	0.0180158436516138	0.990992078174193

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
19 & 0.40228834589082 & 0.804576691781641 & 0.597711654109179 \tabularnewline
20 & 0.555319611918205 & 0.88936077616359 & 0.444680388081795 \tabularnewline
21 & 0.219406574488551 & 0.438813148977102 & 0.780593425511449 \tabularnewline
22 & 0.921069210027943 & 0.157861579944115 & 0.0789307899720573 \tabularnewline
23 & 0.984425201949361 & 0.0311495961012781 & 0.015574798050639 \tabularnewline
24 & 0.980335576578819 & 0.0393288468423628 & 0.0196644234211814 \tabularnewline
25 & 0.9149896124897 & 0.170020775020599 & 0.0850103875102996 \tabularnewline
26 & 0.000324993743970001 & 0.000649987487940002 & 0.99967500625603 \tabularnewline
27 & 0.0121619505025199 & 0.0243239010050397 & 0.98783804949748 \tabularnewline
28 & 1 & 3.71711121170752e-20 & 1.85855560585376e-20 \tabularnewline
29 & 0.929952407417836 & 0.140095185164328 & 0.0700475925821639 \tabularnewline
30 & 0.00818883043787245 & 0.0163776608757449 & 0.991811169562128 \tabularnewline
31 & 0.983695065517823 & 0.0326098689643546 & 0.0163049344821773 \tabularnewline
32 & 0.22777546228606 & 0.455550924572119 & 0.772224537713941 \tabularnewline
33 & 0.999999995836972 & 8.32605643792285e-09 & 4.16302821896143e-09 \tabularnewline
34 & 8.45639605661226e-09 & 1.69127921132245e-08 & 0.999999991543604 \tabularnewline
35 & 0.792927773596607 & 0.414144452806786 & 0.207072226403393 \tabularnewline
36 & 0.0750621955369129 & 0.150124391073826 & 0.924937804463087 \tabularnewline
37 & 9.97515352223561e-07 & 1.99503070444712e-06 & 0.999999002484648 \tabularnewline
38 & 0.300817059985505 & 0.601634119971011 & 0.699182940014495 \tabularnewline
39 & 0.952218781843188 & 0.0955624363136233 & 0.0477812181568116 \tabularnewline
40 & 3.34542976825003e-09 & 6.69085953650006e-09 & 0.99999999665457 \tabularnewline
41 & 5.1622663195582e-06 & 1.03245326391164e-05 & 0.99999483773368 \tabularnewline
42 & 0.999999999999997 & 6.21058167798393e-15 & 3.10529083899196e-15 \tabularnewline
43 & 0.999999999307931 & 1.384138672244e-09 & 6.92069336122e-10 \tabularnewline
44 & 0.559927873642394 & 0.880144252715212 & 0.440072126357606 \tabularnewline
45 & 0.998777052090295 & 0.00244589581940994 & 0.00122294790970497 \tabularnewline
46 & 0.999698331091523 & 0.00060333781695406 & 0.00030166890847703 \tabularnewline
47 & 0.06797925840233 & 0.13595851680466 & 0.93202074159767 \tabularnewline
48 & 0.999999998071932 & 3.85613524211471e-09 & 1.92806762105735e-09 \tabularnewline
49 & 1 & 6.66466807386733e-38 & 3.33233403693366e-38 \tabularnewline
50 & 0.974466940347459 & 0.0510661193050818 & 0.0255330596525409 \tabularnewline
51 & 9.39779328489027e-09 & 1.87955865697805e-08 & 0.999999990602207 \tabularnewline
52 & 0.954113144552137 & 0.0917737108957261 & 0.0458868554478631 \tabularnewline
53 & 1.32036612928931e-06 & 2.64073225857862e-06 & 0.999998679633871 \tabularnewline
54 & 0.224598151866797 & 0.449196303733594 & 0.775401848133203 \tabularnewline
55 & 0.999999999999972 & 5.58405117295423e-14 & 2.79202558647712e-14 \tabularnewline
56 & 0.00343596587561769 & 0.00687193175123537 & 0.996564034124382 \tabularnewline
57 & 0.999564044022912 & 0.000871911954175242 & 0.000435955977087621 \tabularnewline
58 & 0.605630399465222 & 0.788739201069556 & 0.394369600534778 \tabularnewline
59 & 0.995932713812751 & 0.00813457237449721 & 0.0040672861872486 \tabularnewline
60 & 4.90330117263184e-05 & 9.80660234526368e-05 & 0.999950966988274 \tabularnewline
61 & 1 & 2.83223115071108e-33 & 1.41611557535554e-33 \tabularnewline
62 & 0.999997960103697 & 4.07979260668682e-06 & 2.03989630334341e-06 \tabularnewline
63 & 1 & 3.5028916671508e-19 & 1.7514458335754e-19 \tabularnewline
64 & 7.06709236608769e-14 & 1.41341847321754e-13 & 0.999999999999929 \tabularnewline
65 & 1.54773334266328e-10 & 3.09546668532656e-10 & 0.999999999845227 \tabularnewline
66 & 2.47264810314444e-24 & 4.94529620628889e-24 & 1 \tabularnewline
67 & 0.698665804569396 & 0.602668390861207 & 0.301334195430604 \tabularnewline
68 & 1.15861258576554e-05 & 2.31722517153109e-05 & 0.999988413874142 \tabularnewline
69 & 8.37622982836868e-14 & 1.67524596567374e-13 & 0.999999999999916 \tabularnewline
70 & 3.74178160002837e-11 & 7.48356320005673e-11 & 0.999999999962582 \tabularnewline
71 & 1.70205694153655e-17 & 3.4041138830731e-17 & 1 \tabularnewline
72 & 0.999996087594178 & 7.82481164389571e-06 & 3.91240582194785e-06 \tabularnewline
73 & 0.00036411092597973 & 0.00072822185195946 & 0.99963588907402 \tabularnewline
74 & 0.999999997712796 & 4.57440743687688e-09 & 2.28720371843844e-09 \tabularnewline
75 & 0.466077475098999 & 0.932154950197998 & 0.533922524901001 \tabularnewline
76 & 0.999658352483215 & 0.000683295033569156 & 0.000341647516784578 \tabularnewline
77 & 0.999860655086887 & 0.000278689826225016 & 0.000139344913112508 \tabularnewline
78 & 2.6833313665706e-23 & 5.3666627331412e-23 & 1 \tabularnewline
79 & 0.0827527427151601 & 0.16550548543032 & 0.91724725728484 \tabularnewline
80 & 0.000129439722594522 & 0.000258879445189044 & 0.999870560277406 \tabularnewline
81 & 1.17551959287488e-13 & 2.35103918574977e-13 & 0.999999999999882 \tabularnewline
82 & 0.828171869818904 & 0.343656260362191 & 0.171828130181096 \tabularnewline
83 & 0.999999999475936 & 1.04812780928e-09 & 5.24063904640001e-10 \tabularnewline
84 & 0.00135018676139402 & 0.00270037352278805 & 0.998649813238606 \tabularnewline
85 & 0.823070357855832 & 0.353859284288336 & 0.176929642144168 \tabularnewline
86 & 5.27606702574724e-09 & 1.05521340514945e-08 & 0.999999994723933 \tabularnewline
87 & 6.63648623371417e-09 & 1.32729724674283e-08 & 0.999999993363514 \tabularnewline
88 & 0.999975817590579 & 4.83648188416528e-05 & 2.41824094208264e-05 \tabularnewline
89 & 1.97353094268119e-05 & 3.94706188536238e-05 & 0.999980264690573 \tabularnewline
90 & 0.4757727202199 & 0.9515454404398 & 0.5242272797801 \tabularnewline
91 & 3.24697087922979e-07 & 6.49394175845957e-07 & 0.999999675302912 \tabularnewline
92 & 1.30716268965404e-07 & 2.61432537930809e-07 & 0.999999869283731 \tabularnewline
93 & 0.99971827457237 & 0.000563450855260668 & 0.000281725427630334 \tabularnewline
94 & 2.24332243514111e-12 & 4.48664487028222e-12 & 0.999999999997757 \tabularnewline
95 & 0.298784475381549 & 0.597568950763098 & 0.701215524618451 \tabularnewline
96 & 0.10342468702221 & 0.20684937404442 & 0.89657531297779 \tabularnewline
97 & 0.0804586944895623 & 0.160917388979125 & 0.919541305510438 \tabularnewline
98 & 0.999999999898452 & 2.03096663603641e-10 & 1.0154833180182e-10 \tabularnewline
99 & 1.99563483359068e-08 & 3.99126966718135e-08 & 0.999999980043652 \tabularnewline
100 & 0.999478717036258 & 0.00104256592748431 & 0.000521282963742157 \tabularnewline
101 & 0.0194479799160829 & 0.0388959598321659 & 0.980552020083917 \tabularnewline
102 & 5.63957045055609e-32 & 1.12791409011122e-31 & 1 \tabularnewline
103 & 0.999999999626569 & 7.46860964247596e-10 & 3.73430482123798e-10 \tabularnewline
104 & 0.999999999897422 & 2.05156872163919e-10 & 1.0257843608196e-10 \tabularnewline
105 & 0.0454157991670118 & 0.0908315983340236 & 0.954584200832988 \tabularnewline
106 & 0.0513916661138937 & 0.102783332227787 & 0.948608333886106 \tabularnewline
107 & 0.99999990925488 & 1.81490239874159e-07 & 9.07451199370795e-08 \tabularnewline
108 & 2.46092768054643e-09 & 4.92185536109285e-09 & 0.999999997539072 \tabularnewline
109 & 0.955767519371303 & 0.0884649612573936 & 0.0442324806286968 \tabularnewline
110 & 8.85430035815885e-38 & 1.77086007163177e-37 & 1 \tabularnewline
111 & 0.910043343080715 & 0.179913313838571 & 0.0899566569192854 \tabularnewline
112 & 4.02264989991461e-09 & 8.04529979982922e-09 & 0.99999999597735 \tabularnewline
113 & 0.999950035773404 & 9.99284531911442e-05 & 4.99642265955721e-05 \tabularnewline
114 & 3.85943207318273e-08 & 7.71886414636545e-08 & 0.999999961405679 \tabularnewline
115 & 1.10343223125912e-07 & 2.20686446251824e-07 & 0.999999889656777 \tabularnewline
116 & 0.855071512643574 & 0.289856974712853 & 0.144928487356426 \tabularnewline
117 & 7.5214567813668e-21 & 1.50429135627336e-20 & 1 \tabularnewline
118 & 0.000881945515019417 & 0.00176389103003883 & 0.999118054484981 \tabularnewline
119 & 1 & 3.64858735516655e-20 & 1.82429367758327e-20 \tabularnewline
120 & 9.05887699030417e-09 & 1.81177539806083e-08 & 0.999999990941123 \tabularnewline
121 & 0.999999999970649 & 5.87009379933526e-11 & 2.93504689966763e-11 \tabularnewline
122 & 9.01155161647999e-15 & 1.802310323296e-14 & 0.999999999999991 \tabularnewline
123 & 0.999303765588447 & 0.00139246882310625 & 0.000696234411553123 \tabularnewline
124 & 4.88723627929409e-31 & 9.77447255858819e-31 & 1 \tabularnewline
125 & 1 & 2.2312844893789e-17 & 1.11564224468945e-17 \tabularnewline
126 & 1 & 1.97226843654285e-21 & 9.86134218271423e-22 \tabularnewline
127 & 0.00684739563639831 & 0.0136947912727966 & 0.993152604363602 \tabularnewline
128 & 0.670077666592013 & 0.659844666815975 & 0.329922333407987 \tabularnewline
129 & 1.63603678227241e-40 & 3.27207356454482e-40 & 1 \tabularnewline
130 & 3.99713952509614e-28 & 7.99427905019229e-28 & 1 \tabularnewline
131 & 2.0236859850622e-28 & 4.0473719701244e-28 & 1 \tabularnewline
132 & 3.02869668027751e-23 & 6.05739336055501e-23 & 1 \tabularnewline
133 & 6.12535841654327e-26 & 1.22507168330865e-25 & 1 \tabularnewline
134 & 2.54561479658834e-08 & 5.09122959317668e-08 & 0.999999974543852 \tabularnewline
135 & 0.00060293800412816 & 0.00120587600825632 & 0.999397061995872 \tabularnewline
136 & 0.00751114718628936 & 0.0150222943725787 & 0.992488852813711 \tabularnewline
137 & 0.99999999999961 & 7.79626476979923e-13 & 3.89813238489962e-13 \tabularnewline
138 & 0.999999999909938 & 1.80124089413312e-10 & 9.00620447066562e-11 \tabularnewline
139 & 9.2821992267036e-15 & 1.85643984534072e-14 & 0.999999999999991 \tabularnewline
140 & 1.0376847598637e-07 & 2.0753695197274e-07 & 0.999999896231524 \tabularnewline
141 & 0.937230617755944 & 0.125538764488112 & 0.0627693822440561 \tabularnewline
142 & 0.638784770665638 & 0.722430458668724 & 0.361215229334362 \tabularnewline
143 & 0.231569891661029 & 0.463139783322059 & 0.768430108338971 \tabularnewline
144 & 0.966021907251366 & 0.0679561854972681 & 0.0339780927486341 \tabularnewline
145 & 0.279954903653576 & 0.559909807307152 & 0.720045096346424 \tabularnewline
146 & 1.6576029868166e-42 & 3.31520597363319e-42 & 1 \tabularnewline
147 & 0.038796968257401 & 0.077593936514802 & 0.961203031742599 \tabularnewline
148 & 2.02515261138506e-21 & 4.05030522277012e-21 & 1 \tabularnewline
149 & 0.999999999999914 & 1.72058702809162e-13 & 8.60293514045811e-14 \tabularnewline
150 & 0.749370355927759 & 0.501259288144482 & 0.250629644072241 \tabularnewline
151 & 0.999999999999991 & 1.72811274358611e-14 & 8.64056371793056e-15 \tabularnewline
152 & 0.000205394445570046 & 0.000410788891140093 & 0.99979460555443 \tabularnewline
153 & 3.25535806263963e-48 & 6.51071612527927e-48 & 1 \tabularnewline
154 & 0.985855203841501 & 0.0282895923169979 & 0.0141447961584989 \tabularnewline
155 & 2.58142915431639e-11 & 5.16285830863278e-11 & 0.999999999974186 \tabularnewline
156 & 1 & 1.49023420917783e-26 & 7.45117104588917e-27 \tabularnewline
157 & 1 & 4.68225982959741e-17 & 2.3411299147987e-17 \tabularnewline
158 & 0.978526120807812 & 0.0429477583843767 & 0.0214738791921884 \tabularnewline
159 & 1 & 4.01763313027514e-31 & 2.00881656513757e-31 \tabularnewline
160 & 0.000213143399944063 & 0.000426286799888127 & 0.999786856600056 \tabularnewline
161 & 5.9550520689763e-16 & 1.19101041379526e-15 & 0.999999999999999 \tabularnewline
162 & 1.64688767434609e-13 & 3.29377534869217e-13 & 0.999999999999835 \tabularnewline
163 & 6.70017643553115e-17 & 1.34003528710623e-16 & 1 \tabularnewline
164 & 3.83843035710517e-13 & 7.67686071421033e-13 & 0.999999999999616 \tabularnewline
165 & 1.51994022412039e-17 & 3.03988044824078e-17 & 1 \tabularnewline
166 & 1.28016620446872e-25 & 2.56033240893743e-25 & 1 \tabularnewline
167 & 0.593088128741384 & 0.813823742517231 & 0.406911871258616 \tabularnewline
168 & 2.60321712083954e-13 & 5.20643424167908e-13 & 0.99999999999974 \tabularnewline
169 & 3.23001622025456e-42 & 6.46003244050912e-42 & 1 \tabularnewline
170 & 0.999999986847956 & 2.63040877600586e-08 & 1.31520438800293e-08 \tabularnewline
171 & 2.53986103914762e-29 & 5.07972207829524e-29 & 1 \tabularnewline
172 & 3.47918468813283e-35 & 6.95836937626566e-35 & 1 \tabularnewline
173 & 0.999999999999985 & 3.07955141578191e-14 & 1.53977570789096e-14 \tabularnewline
174 & 8.21141488423181e-90 & 1.64228297684636e-89 & 1 \tabularnewline
175 & 6.25132849804714e-28 & 1.25026569960943e-27 & 1 \tabularnewline
176 & 7.43628455566725e-16 & 1.48725691113345e-15 & 0.999999999999999 \tabularnewline
177 & 0.00326902110384998 & 0.00653804220769995 & 0.99673097889615 \tabularnewline
178 & 3.59699468959486e-10 & 7.19398937918973e-10 & 0.999999999640301 \tabularnewline
179 & 1 & 2.36600663296867e-23 & 1.18300331648434e-23 \tabularnewline
180 & 0.0191543965331648 & 0.0383087930663295 & 0.980845603466835 \tabularnewline
181 & 1 & 1.41303783616803e-20 & 7.06518918084016e-21 \tabularnewline
182 & 5.76088519119062e-24 & 1.15217703823812e-23 & 1 \tabularnewline
183 & 0.999999999989763 & 2.04733734391415e-11 & 1.02366867195708e-11 \tabularnewline
184 & 2.3562239951615e-32 & 4.712447990323e-32 & 1 \tabularnewline
185 & 8.91516987275113e-19 & 1.78303397455023e-18 & 1 \tabularnewline
186 & 0.142847818970043 & 0.285695637940087 & 0.857152181029957 \tabularnewline
187 & 0.00163802453345996 & 0.00327604906691993 & 0.99836197546654 \tabularnewline
188 & 5.57689119998738e-65 & 1.11537823999748e-64 & 1 \tabularnewline
189 & 0.162909792641298 & 0.325819585282597 & 0.837090207358702 \tabularnewline
190 & 1.21709975568818e-09 & 2.43419951137637e-09 & 0.9999999987829 \tabularnewline
191 & 3.45217498786514e-07 & 6.90434997573029e-07 & 0.999999654782501 \tabularnewline
192 & 1.46107455685421e-09 & 2.92214911370842e-09 & 0.999999998538925 \tabularnewline
193 & 1.25699173002184e-26 & 2.51398346004368e-26 & 1 \tabularnewline
194 & 0.0983068237218565 & 0.196613647443713 & 0.901693176278143 \tabularnewline
195 & 0.999996091190104 & 7.81761979149998e-06 & 3.90880989574999e-06 \tabularnewline
196 & 1 & 3.37701604961216e-20 & 1.68850802480608e-20 \tabularnewline
197 & 0.896838059550096 & 0.206323880899808 & 0.103161940449904 \tabularnewline
198 & 0.0165904094230384 & 0.0331808188460767 & 0.983409590576962 \tabularnewline
199 & 0.0319688337959431 & 0.0639376675918862 & 0.968031166204057 \tabularnewline
200 & 0.999953682205625 & 9.26355887509922e-05 & 4.63177943754961e-05 \tabularnewline
201 & 0.999999999999999 & 1.20903618697438e-15 & 6.04518093487192e-16 \tabularnewline
202 & 0.999744879825246 & 0.000510240349508426 & 0.000255120174754213 \tabularnewline
203 & 0.00121788534280533 & 0.00243577068561066 & 0.998782114657195 \tabularnewline
204 & 0.258325724972098 & 0.516651449944196 & 0.741674275027902 \tabularnewline
205 & 0.566751704037363 & 0.866496591925275 & 0.433248295962637 \tabularnewline
206 & 0.726452604769142 & 0.547094790461716 & 0.273547395230858 \tabularnewline
207 & 2.52712265688843e-14 & 5.05424531377686e-14 & 0.999999999999975 \tabularnewline
208 & 0.948906214257964 & 0.102187571484071 & 0.0510937857420357 \tabularnewline
209 & 1.87573600738136e-07 & 3.75147201476272e-07 & 0.999999812426399 \tabularnewline
210 & 6.02441862742376e-51 & 1.20488372548475e-50 & 1 \tabularnewline
211 & 0.999999864250961 & 2.71498078699179e-07 & 1.3574903934959e-07 \tabularnewline
212 & 1.11676956350019e-13 & 2.23353912700038e-13 & 0.999999999999888 \tabularnewline
213 & 0.031260673545819 & 0.0625213470916379 & 0.968739326454181 \tabularnewline
214 & 0.999969597357861 & 6.08052842772823e-05 & 3.04026421386412e-05 \tabularnewline
215 & 0.995193025153 & 0.00961394969399911 & 0.00480697484699956 \tabularnewline
216 & 2.09201122846258e-17 & 4.18402245692516e-17 & 1 \tabularnewline
217 & 0.102864133423368 & 0.205728266846736 & 0.897135866576632 \tabularnewline
218 & 1.68882768614764e-14 & 3.37765537229527e-14 & 0.999999999999983 \tabularnewline
219 & 0.998953967560097 & 0.00209206487980652 & 0.00104603243990326 \tabularnewline
220 & 0.987390062791942 & 0.0252198744161153 & 0.0126099372080577 \tabularnewline
221 & 0.00496542006744235 & 0.0099308401348847 & 0.995034579932558 \tabularnewline
222 & 8.64022300649583e-07 & 1.72804460129917e-06 & 0.999999135977699 \tabularnewline
223 & 0.232266847240211 & 0.464533694480422 & 0.767733152759789 \tabularnewline
224 & 4.59472394006803e-28 & 9.18944788013606e-28 & 1 \tabularnewline
225 & 1.73842839198542e-05 & 3.47685678397084e-05 & 0.99998261571608 \tabularnewline
226 & 0.999999603919366 & 7.92161267158628e-07 & 3.96080633579314e-07 \tabularnewline
227 & 2.02349653777178e-75 & 4.04699307554356e-75 & 1 \tabularnewline
228 & 0.0179935723953922 & 0.0359871447907844 & 0.982006427604608 \tabularnewline
229 & 0.959439433130366 & 0.0811211337392681 & 0.0405605668696341 \tabularnewline
230 & 0.0100670470672959 & 0.0201340941345918 & 0.989932952932704 \tabularnewline
231 & 0.724475547225072 & 0.551048905549855 & 0.275524452774928 \tabularnewline
232 & 0.999979285551499 & 4.14288970020791e-05 & 2.07144485010396e-05 \tabularnewline
233 & 3.20392018702718e-07 & 6.40784037405437e-07 & 0.999999679607981 \tabularnewline
234 & 0.0334871086078533 & 0.0669742172157066 & 0.966512891392147 \tabularnewline
235 & 9.32318339285568e-38 & 1.86463667857114e-37 & 1 \tabularnewline
236 & 1.76160151408192e-36 & 3.52320302816383e-36 & 1 \tabularnewline
237 & 0.0804861613185567 & 0.160972322637113 & 0.919513838681443 \tabularnewline
238 & 6.96810822832765e-21 & 1.39362164566553e-20 & 1 \tabularnewline
239 & 0.071969589390123 & 0.143939178780246 & 0.928030410609877 \tabularnewline
240 & 4.67178843092058e-06 & 9.34357686184117e-06 & 0.999995328211569 \tabularnewline
241 & 2.90490447052788e-08 & 5.80980894105576e-08 & 0.999999970950955 \tabularnewline
242 & 0.00173504047923199 & 0.00347008095846397 & 0.998264959520768 \tabularnewline
243 & 0.94090844523562 & 0.11818310952876 & 0.0590915547643798 \tabularnewline
244 & 5.0907906434921e-28 & 1.01815812869842e-27 & 1 \tabularnewline
245 & 0.00900792182580691 & 0.0180158436516138 & 0.990992078174193 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190339&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]19[/C][C]0.40228834589082[/C][C]0.804576691781641[/C][C]0.597711654109179[/C][/ROW]
[ROW][C]20[/C][C]0.555319611918205[/C][C]0.88936077616359[/C][C]0.444680388081795[/C][/ROW]
[ROW][C]21[/C][C]0.219406574488551[/C][C]0.438813148977102[/C][C]0.780593425511449[/C][/ROW]
[ROW][C]22[/C][C]0.921069210027943[/C][C]0.157861579944115[/C][C]0.0789307899720573[/C][/ROW]
[ROW][C]23[/C][C]0.984425201949361[/C][C]0.0311495961012781[/C][C]0.015574798050639[/C][/ROW]
[ROW][C]24[/C][C]0.980335576578819[/C][C]0.0393288468423628[/C][C]0.0196644234211814[/C][/ROW]
[ROW][C]25[/C][C]0.9149896124897[/C][C]0.170020775020599[/C][C]0.0850103875102996[/C][/ROW]
[ROW][C]26[/C][C]0.000324993743970001[/C][C]0.000649987487940002[/C][C]0.99967500625603[/C][/ROW]
[ROW][C]27[/C][C]0.0121619505025199[/C][C]0.0243239010050397[/C][C]0.98783804949748[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]3.71711121170752e-20[/C][C]1.85855560585376e-20[/C][/ROW]
[ROW][C]29[/C][C]0.929952407417836[/C][C]0.140095185164328[/C][C]0.0700475925821639[/C][/ROW]
[ROW][C]30[/C][C]0.00818883043787245[/C][C]0.0163776608757449[/C][C]0.991811169562128[/C][/ROW]
[ROW][C]31[/C][C]0.983695065517823[/C][C]0.0326098689643546[/C][C]0.0163049344821773[/C][/ROW]
[ROW][C]32[/C][C]0.22777546228606[/C][C]0.455550924572119[/C][C]0.772224537713941[/C][/ROW]
[ROW][C]33[/C][C]0.999999995836972[/C][C]8.32605643792285e-09[/C][C]4.16302821896143e-09[/C][/ROW]
[ROW][C]34[/C][C]8.45639605661226e-09[/C][C]1.69127921132245e-08[/C][C]0.999999991543604[/C][/ROW]
[ROW][C]35[/C][C]0.792927773596607[/C][C]0.414144452806786[/C][C]0.207072226403393[/C][/ROW]
[ROW][C]36[/C][C]0.0750621955369129[/C][C]0.150124391073826[/C][C]0.924937804463087[/C][/ROW]
[ROW][C]37[/C][C]9.97515352223561e-07[/C][C]1.99503070444712e-06[/C][C]0.999999002484648[/C][/ROW]
[ROW][C]38[/C][C]0.300817059985505[/C][C]0.601634119971011[/C][C]0.699182940014495[/C][/ROW]
[ROW][C]39[/C][C]0.952218781843188[/C][C]0.0955624363136233[/C][C]0.0477812181568116[/C][/ROW]
[ROW][C]40[/C][C]3.34542976825003e-09[/C][C]6.69085953650006e-09[/C][C]0.99999999665457[/C][/ROW]
[ROW][C]41[/C][C]5.1622663195582e-06[/C][C]1.03245326391164e-05[/C][C]0.99999483773368[/C][/ROW]
[ROW][C]42[/C][C]0.999999999999997[/C][C]6.21058167798393e-15[/C][C]3.10529083899196e-15[/C][/ROW]
[ROW][C]43[/C][C]0.999999999307931[/C][C]1.384138672244e-09[/C][C]6.92069336122e-10[/C][/ROW]
[ROW][C]44[/C][C]0.559927873642394[/C][C]0.880144252715212[/C][C]0.440072126357606[/C][/ROW]
[ROW][C]45[/C][C]0.998777052090295[/C][C]0.00244589581940994[/C][C]0.00122294790970497[/C][/ROW]
[ROW][C]46[/C][C]0.999698331091523[/C][C]0.00060333781695406[/C][C]0.00030166890847703[/C][/ROW]
[ROW][C]47[/C][C]0.06797925840233[/C][C]0.13595851680466[/C][C]0.93202074159767[/C][/ROW]
[ROW][C]48[/C][C]0.999999998071932[/C][C]3.85613524211471e-09[/C][C]1.92806762105735e-09[/C][/ROW]
[ROW][C]49[/C][C]1[/C][C]6.66466807386733e-38[/C][C]3.33233403693366e-38[/C][/ROW]
[ROW][C]50[/C][C]0.974466940347459[/C][C]0.0510661193050818[/C][C]0.0255330596525409[/C][/ROW]
[ROW][C]51[/C][C]9.39779328489027e-09[/C][C]1.87955865697805e-08[/C][C]0.999999990602207[/C][/ROW]
[ROW][C]52[/C][C]0.954113144552137[/C][C]0.0917737108957261[/C][C]0.0458868554478631[/C][/ROW]
[ROW][C]53[/C][C]1.32036612928931e-06[/C][C]2.64073225857862e-06[/C][C]0.999998679633871[/C][/ROW]
[ROW][C]54[/C][C]0.224598151866797[/C][C]0.449196303733594[/C][C]0.775401848133203[/C][/ROW]
[ROW][C]55[/C][C]0.999999999999972[/C][C]5.58405117295423e-14[/C][C]2.79202558647712e-14[/C][/ROW]
[ROW][C]56[/C][C]0.00343596587561769[/C][C]0.00687193175123537[/C][C]0.996564034124382[/C][/ROW]
[ROW][C]57[/C][C]0.999564044022912[/C][C]0.000871911954175242[/C][C]0.000435955977087621[/C][/ROW]
[ROW][C]58[/C][C]0.605630399465222[/C][C]0.788739201069556[/C][C]0.394369600534778[/C][/ROW]
[ROW][C]59[/C][C]0.995932713812751[/C][C]0.00813457237449721[/C][C]0.0040672861872486[/C][/ROW]
[ROW][C]60[/C][C]4.90330117263184e-05[/C][C]9.80660234526368e-05[/C][C]0.999950966988274[/C][/ROW]
[ROW][C]61[/C][C]1[/C][C]2.83223115071108e-33[/C][C]1.41611557535554e-33[/C][/ROW]
[ROW][C]62[/C][C]0.999997960103697[/C][C]4.07979260668682e-06[/C][C]2.03989630334341e-06[/C][/ROW]
[ROW][C]63[/C][C]1[/C][C]3.5028916671508e-19[/C][C]1.7514458335754e-19[/C][/ROW]
[ROW][C]64[/C][C]7.06709236608769e-14[/C][C]1.41341847321754e-13[/C][C]0.999999999999929[/C][/ROW]
[ROW][C]65[/C][C]1.54773334266328e-10[/C][C]3.09546668532656e-10[/C][C]0.999999999845227[/C][/ROW]
[ROW][C]66[/C][C]2.47264810314444e-24[/C][C]4.94529620628889e-24[/C][C]1[/C][/ROW]
[ROW][C]67[/C][C]0.698665804569396[/C][C]0.602668390861207[/C][C]0.301334195430604[/C][/ROW]
[ROW][C]68[/C][C]1.15861258576554e-05[/C][C]2.31722517153109e-05[/C][C]0.999988413874142[/C][/ROW]
[ROW][C]69[/C][C]8.37622982836868e-14[/C][C]1.67524596567374e-13[/C][C]0.999999999999916[/C][/ROW]
[ROW][C]70[/C][C]3.74178160002837e-11[/C][C]7.48356320005673e-11[/C][C]0.999999999962582[/C][/ROW]
[ROW][C]71[/C][C]1.70205694153655e-17[/C][C]3.4041138830731e-17[/C][C]1[/C][/ROW]
[ROW][C]72[/C][C]0.999996087594178[/C][C]7.82481164389571e-06[/C][C]3.91240582194785e-06[/C][/ROW]
[ROW][C]73[/C][C]0.00036411092597973[/C][C]0.00072822185195946[/C][C]0.99963588907402[/C][/ROW]
[ROW][C]74[/C][C]0.999999997712796[/C][C]4.57440743687688e-09[/C][C]2.28720371843844e-09[/C][/ROW]
[ROW][C]75[/C][C]0.466077475098999[/C][C]0.932154950197998[/C][C]0.533922524901001[/C][/ROW]
[ROW][C]76[/C][C]0.999658352483215[/C][C]0.000683295033569156[/C][C]0.000341647516784578[/C][/ROW]
[ROW][C]77[/C][C]0.999860655086887[/C][C]0.000278689826225016[/C][C]0.000139344913112508[/C][/ROW]
[ROW][C]78[/C][C]2.6833313665706e-23[/C][C]5.3666627331412e-23[/C][C]1[/C][/ROW]
[ROW][C]79[/C][C]0.0827527427151601[/C][C]0.16550548543032[/C][C]0.91724725728484[/C][/ROW]
[ROW][C]80[/C][C]0.000129439722594522[/C][C]0.000258879445189044[/C][C]0.999870560277406[/C][/ROW]
[ROW][C]81[/C][C]1.17551959287488e-13[/C][C]2.35103918574977e-13[/C][C]0.999999999999882[/C][/ROW]
[ROW][C]82[/C][C]0.828171869818904[/C][C]0.343656260362191[/C][C]0.171828130181096[/C][/ROW]
[ROW][C]83[/C][C]0.999999999475936[/C][C]1.04812780928e-09[/C][C]5.24063904640001e-10[/C][/ROW]
[ROW][C]84[/C][C]0.00135018676139402[/C][C]0.00270037352278805[/C][C]0.998649813238606[/C][/ROW]
[ROW][C]85[/C][C]0.823070357855832[/C][C]0.353859284288336[/C][C]0.176929642144168[/C][/ROW]
[ROW][C]86[/C][C]5.27606702574724e-09[/C][C]1.05521340514945e-08[/C][C]0.999999994723933[/C][/ROW]
[ROW][C]87[/C][C]6.63648623371417e-09[/C][C]1.32729724674283e-08[/C][C]0.999999993363514[/C][/ROW]
[ROW][C]88[/C][C]0.999975817590579[/C][C]4.83648188416528e-05[/C][C]2.41824094208264e-05[/C][/ROW]
[ROW][C]89[/C][C]1.97353094268119e-05[/C][C]3.94706188536238e-05[/C][C]0.999980264690573[/C][/ROW]
[ROW][C]90[/C][C]0.4757727202199[/C][C]0.9515454404398[/C][C]0.5242272797801[/C][/ROW]
[ROW][C]91[/C][C]3.24697087922979e-07[/C][C]6.49394175845957e-07[/C][C]0.999999675302912[/C][/ROW]
[ROW][C]92[/C][C]1.30716268965404e-07[/C][C]2.61432537930809e-07[/C][C]0.999999869283731[/C][/ROW]
[ROW][C]93[/C][C]0.99971827457237[/C][C]0.000563450855260668[/C][C]0.000281725427630334[/C][/ROW]
[ROW][C]94[/C][C]2.24332243514111e-12[/C][C]4.48664487028222e-12[/C][C]0.999999999997757[/C][/ROW]
[ROW][C]95[/C][C]0.298784475381549[/C][C]0.597568950763098[/C][C]0.701215524618451[/C][/ROW]
[ROW][C]96[/C][C]0.10342468702221[/C][C]0.20684937404442[/C][C]0.89657531297779[/C][/ROW]
[ROW][C]97[/C][C]0.0804586944895623[/C][C]0.160917388979125[/C][C]0.919541305510438[/C][/ROW]
[ROW][C]98[/C][C]0.999999999898452[/C][C]2.03096663603641e-10[/C][C]1.0154833180182e-10[/C][/ROW]
[ROW][C]99[/C][C]1.99563483359068e-08[/C][C]3.99126966718135e-08[/C][C]0.999999980043652[/C][/ROW]
[ROW][C]100[/C][C]0.999478717036258[/C][C]0.00104256592748431[/C][C]0.000521282963742157[/C][/ROW]
[ROW][C]101[/C][C]0.0194479799160829[/C][C]0.0388959598321659[/C][C]0.980552020083917[/C][/ROW]
[ROW][C]102[/C][C]5.63957045055609e-32[/C][C]1.12791409011122e-31[/C][C]1[/C][/ROW]
[ROW][C]103[/C][C]0.999999999626569[/C][C]7.46860964247596e-10[/C][C]3.73430482123798e-10[/C][/ROW]
[ROW][C]104[/C][C]0.999999999897422[/C][C]2.05156872163919e-10[/C][C]1.0257843608196e-10[/C][/ROW]
[ROW][C]105[/C][C]0.0454157991670118[/C][C]0.0908315983340236[/C][C]0.954584200832988[/C][/ROW]
[ROW][C]106[/C][C]0.0513916661138937[/C][C]0.102783332227787[/C][C]0.948608333886106[/C][/ROW]
[ROW][C]107[/C][C]0.99999990925488[/C][C]1.81490239874159e-07[/C][C]9.07451199370795e-08[/C][/ROW]
[ROW][C]108[/C][C]2.46092768054643e-09[/C][C]4.92185536109285e-09[/C][C]0.999999997539072[/C][/ROW]
[ROW][C]109[/C][C]0.955767519371303[/C][C]0.0884649612573936[/C][C]0.0442324806286968[/C][/ROW]
[ROW][C]110[/C][C]8.85430035815885e-38[/C][C]1.77086007163177e-37[/C][C]1[/C][/ROW]
[ROW][C]111[/C][C]0.910043343080715[/C][C]0.179913313838571[/C][C]0.0899566569192854[/C][/ROW]
[ROW][C]112[/C][C]4.02264989991461e-09[/C][C]8.04529979982922e-09[/C][C]0.99999999597735[/C][/ROW]
[ROW][C]113[/C][C]0.999950035773404[/C][C]9.99284531911442e-05[/C][C]4.99642265955721e-05[/C][/ROW]
[ROW][C]114[/C][C]3.85943207318273e-08[/C][C]7.71886414636545e-08[/C][C]0.999999961405679[/C][/ROW]
[ROW][C]115[/C][C]1.10343223125912e-07[/C][C]2.20686446251824e-07[/C][C]0.999999889656777[/C][/ROW]
[ROW][C]116[/C][C]0.855071512643574[/C][C]0.289856974712853[/C][C]0.144928487356426[/C][/ROW]
[ROW][C]117[/C][C]7.5214567813668e-21[/C][C]1.50429135627336e-20[/C][C]1[/C][/ROW]
[ROW][C]118[/C][C]0.000881945515019417[/C][C]0.00176389103003883[/C][C]0.999118054484981[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]3.64858735516655e-20[/C][C]1.82429367758327e-20[/C][/ROW]
[ROW][C]120[/C][C]9.05887699030417e-09[/C][C]1.81177539806083e-08[/C][C]0.999999990941123[/C][/ROW]
[ROW][C]121[/C][C]0.999999999970649[/C][C]5.87009379933526e-11[/C][C]2.93504689966763e-11[/C][/ROW]
[ROW][C]122[/C][C]9.01155161647999e-15[/C][C]1.802310323296e-14[/C][C]0.999999999999991[/C][/ROW]
[ROW][C]123[/C][C]0.999303765588447[/C][C]0.00139246882310625[/C][C]0.000696234411553123[/C][/ROW]
[ROW][C]124[/C][C]4.88723627929409e-31[/C][C]9.77447255858819e-31[/C][C]1[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]2.2312844893789e-17[/C][C]1.11564224468945e-17[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]1.97226843654285e-21[/C][C]9.86134218271423e-22[/C][/ROW]
[ROW][C]127[/C][C]0.00684739563639831[/C][C]0.0136947912727966[/C][C]0.993152604363602[/C][/ROW]
[ROW][C]128[/C][C]0.670077666592013[/C][C]0.659844666815975[/C][C]0.329922333407987[/C][/ROW]
[ROW][C]129[/C][C]1.63603678227241e-40[/C][C]3.27207356454482e-40[/C][C]1[/C][/ROW]
[ROW][C]130[/C][C]3.99713952509614e-28[/C][C]7.99427905019229e-28[/C][C]1[/C][/ROW]
[ROW][C]131[/C][C]2.0236859850622e-28[/C][C]4.0473719701244e-28[/C][C]1[/C][/ROW]
[ROW][C]132[/C][C]3.02869668027751e-23[/C][C]6.05739336055501e-23[/C][C]1[/C][/ROW]
[ROW][C]133[/C][C]6.12535841654327e-26[/C][C]1.22507168330865e-25[/C][C]1[/C][/ROW]
[ROW][C]134[/C][C]2.54561479658834e-08[/C][C]5.09122959317668e-08[/C][C]0.999999974543852[/C][/ROW]
[ROW][C]135[/C][C]0.00060293800412816[/C][C]0.00120587600825632[/C][C]0.999397061995872[/C][/ROW]
[ROW][C]136[/C][C]0.00751114718628936[/C][C]0.0150222943725787[/C][C]0.992488852813711[/C][/ROW]
[ROW][C]137[/C][C]0.99999999999961[/C][C]7.79626476979923e-13[/C][C]3.89813238489962e-13[/C][/ROW]
[ROW][C]138[/C][C]0.999999999909938[/C][C]1.80124089413312e-10[/C][C]9.00620447066562e-11[/C][/ROW]
[ROW][C]139[/C][C]9.2821992267036e-15[/C][C]1.85643984534072e-14[/C][C]0.999999999999991[/C][/ROW]
[ROW][C]140[/C][C]1.0376847598637e-07[/C][C]2.0753695197274e-07[/C][C]0.999999896231524[/C][/ROW]
[ROW][C]141[/C][C]0.937230617755944[/C][C]0.125538764488112[/C][C]0.0627693822440561[/C][/ROW]
[ROW][C]142[/C][C]0.638784770665638[/C][C]0.722430458668724[/C][C]0.361215229334362[/C][/ROW]
[ROW][C]143[/C][C]0.231569891661029[/C][C]0.463139783322059[/C][C]0.768430108338971[/C][/ROW]
[ROW][C]144[/C][C]0.966021907251366[/C][C]0.0679561854972681[/C][C]0.0339780927486341[/C][/ROW]
[ROW][C]145[/C][C]0.279954903653576[/C][C]0.559909807307152[/C][C]0.720045096346424[/C][/ROW]
[ROW][C]146[/C][C]1.6576029868166e-42[/C][C]3.31520597363319e-42[/C][C]1[/C][/ROW]
[ROW][C]147[/C][C]0.038796968257401[/C][C]0.077593936514802[/C][C]0.961203031742599[/C][/ROW]
[ROW][C]148[/C][C]2.02515261138506e-21[/C][C]4.05030522277012e-21[/C][C]1[/C][/ROW]
[ROW][C]149[/C][C]0.999999999999914[/C][C]1.72058702809162e-13[/C][C]8.60293514045811e-14[/C][/ROW]
[ROW][C]150[/C][C]0.749370355927759[/C][C]0.501259288144482[/C][C]0.250629644072241[/C][/ROW]
[ROW][C]151[/C][C]0.999999999999991[/C][C]1.72811274358611e-14[/C][C]8.64056371793056e-15[/C][/ROW]
[ROW][C]152[/C][C]0.000205394445570046[/C][C]0.000410788891140093[/C][C]0.99979460555443[/C][/ROW]
[ROW][C]153[/C][C]3.25535806263963e-48[/C][C]6.51071612527927e-48[/C][C]1[/C][/ROW]
[ROW][C]154[/C][C]0.985855203841501[/C][C]0.0282895923169979[/C][C]0.0141447961584989[/C][/ROW]
[ROW][C]155[/C][C]2.58142915431639e-11[/C][C]5.16285830863278e-11[/C][C]0.999999999974186[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]1.49023420917783e-26[/C][C]7.45117104588917e-27[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]4.68225982959741e-17[/C][C]2.3411299147987e-17[/C][/ROW]
[ROW][C]158[/C][C]0.978526120807812[/C][C]0.0429477583843767[/C][C]0.0214738791921884[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]4.01763313027514e-31[/C][C]2.00881656513757e-31[/C][/ROW]
[ROW][C]160[/C][C]0.000213143399944063[/C][C]0.000426286799888127[/C][C]0.999786856600056[/C][/ROW]
[ROW][C]161[/C][C]5.9550520689763e-16[/C][C]1.19101041379526e-15[/C][C]0.999999999999999[/C][/ROW]
[ROW][C]162[/C][C]1.64688767434609e-13[/C][C]3.29377534869217e-13[/C][C]0.999999999999835[/C][/ROW]
[ROW][C]163[/C][C]6.70017643553115e-17[/C][C]1.34003528710623e-16[/C][C]1[/C][/ROW]
[ROW][C]164[/C][C]3.83843035710517e-13[/C][C]7.67686071421033e-13[/C][C]0.999999999999616[/C][/ROW]
[ROW][C]165[/C][C]1.51994022412039e-17[/C][C]3.03988044824078e-17[/C][C]1[/C][/ROW]
[ROW][C]166[/C][C]1.28016620446872e-25[/C][C]2.56033240893743e-25[/C][C]1[/C][/ROW]
[ROW][C]167[/C][C]0.593088128741384[/C][C]0.813823742517231[/C][C]0.406911871258616[/C][/ROW]
[ROW][C]168[/C][C]2.60321712083954e-13[/C][C]5.20643424167908e-13[/C][C]0.99999999999974[/C][/ROW]
[ROW][C]169[/C][C]3.23001622025456e-42[/C][C]6.46003244050912e-42[/C][C]1[/C][/ROW]
[ROW][C]170[/C][C]0.999999986847956[/C][C]2.63040877600586e-08[/C][C]1.31520438800293e-08[/C][/ROW]
[ROW][C]171[/C][C]2.53986103914762e-29[/C][C]5.07972207829524e-29[/C][C]1[/C][/ROW]
[ROW][C]172[/C][C]3.47918468813283e-35[/C][C]6.95836937626566e-35[/C][C]1[/C][/ROW]
[ROW][C]173[/C][C]0.999999999999985[/C][C]3.07955141578191e-14[/C][C]1.53977570789096e-14[/C][/ROW]
[ROW][C]174[/C][C]8.21141488423181e-90[/C][C]1.64228297684636e-89[/C][C]1[/C][/ROW]
[ROW][C]175[/C][C]6.25132849804714e-28[/C][C]1.25026569960943e-27[/C][C]1[/C][/ROW]
[ROW][C]176[/C][C]7.43628455566725e-16[/C][C]1.48725691113345e-15[/C][C]0.999999999999999[/C][/ROW]
[ROW][C]177[/C][C]0.00326902110384998[/C][C]0.00653804220769995[/C][C]0.99673097889615[/C][/ROW]
[ROW][C]178[/C][C]3.59699468959486e-10[/C][C]7.19398937918973e-10[/C][C]0.999999999640301[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]2.36600663296867e-23[/C][C]1.18300331648434e-23[/C][/ROW]
[ROW][C]180[/C][C]0.0191543965331648[/C][C]0.0383087930663295[/C][C]0.980845603466835[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]1.41303783616803e-20[/C][C]7.06518918084016e-21[/C][/ROW]
[ROW][C]182[/C][C]5.76088519119062e-24[/C][C]1.15217703823812e-23[/C][C]1[/C][/ROW]
[ROW][C]183[/C][C]0.999999999989763[/C][C]2.04733734391415e-11[/C][C]1.02366867195708e-11[/C][/ROW]
[ROW][C]184[/C][C]2.3562239951615e-32[/C][C]4.712447990323e-32[/C][C]1[/C][/ROW]
[ROW][C]185[/C][C]8.91516987275113e-19[/C][C]1.78303397455023e-18[/C][C]1[/C][/ROW]
[ROW][C]186[/C][C]0.142847818970043[/C][C]0.285695637940087[/C][C]0.857152181029957[/C][/ROW]
[ROW][C]187[/C][C]0.00163802453345996[/C][C]0.00327604906691993[/C][C]0.99836197546654[/C][/ROW]
[ROW][C]188[/C][C]5.57689119998738e-65[/C][C]1.11537823999748e-64[/C][C]1[/C][/ROW]
[ROW][C]189[/C][C]0.162909792641298[/C][C]0.325819585282597[/C][C]0.837090207358702[/C][/ROW]
[ROW][C]190[/C][C]1.21709975568818e-09[/C][C]2.43419951137637e-09[/C][C]0.9999999987829[/C][/ROW]
[ROW][C]191[/C][C]3.45217498786514e-07[/C][C]6.90434997573029e-07[/C][C]0.999999654782501[/C][/ROW]
[ROW][C]192[/C][C]1.46107455685421e-09[/C][C]2.92214911370842e-09[/C][C]0.999999998538925[/C][/ROW]
[ROW][C]193[/C][C]1.25699173002184e-26[/C][C]2.51398346004368e-26[/C][C]1[/C][/ROW]
[ROW][C]194[/C][C]0.0983068237218565[/C][C]0.196613647443713[/C][C]0.901693176278143[/C][/ROW]
[ROW][C]195[/C][C]0.999996091190104[/C][C]7.81761979149998e-06[/C][C]3.90880989574999e-06[/C][/ROW]
[ROW][C]196[/C][C]1[/C][C]3.37701604961216e-20[/C][C]1.68850802480608e-20[/C][/ROW]
[ROW][C]197[/C][C]0.896838059550096[/C][C]0.206323880899808[/C][C]0.103161940449904[/C][/ROW]
[ROW][C]198[/C][C]0.0165904094230384[/C][C]0.0331808188460767[/C][C]0.983409590576962[/C][/ROW]
[ROW][C]199[/C][C]0.0319688337959431[/C][C]0.0639376675918862[/C][C]0.968031166204057[/C][/ROW]
[ROW][C]200[/C][C]0.999953682205625[/C][C]9.26355887509922e-05[/C][C]4.63177943754961e-05[/C][/ROW]
[ROW][C]201[/C][C]0.999999999999999[/C][C]1.20903618697438e-15[/C][C]6.04518093487192e-16[/C][/ROW]
[ROW][C]202[/C][C]0.999744879825246[/C][C]0.000510240349508426[/C][C]0.000255120174754213[/C][/ROW]
[ROW][C]203[/C][C]0.00121788534280533[/C][C]0.00243577068561066[/C][C]0.998782114657195[/C][/ROW]
[ROW][C]204[/C][C]0.258325724972098[/C][C]0.516651449944196[/C][C]0.741674275027902[/C][/ROW]
[ROW][C]205[/C][C]0.566751704037363[/C][C]0.866496591925275[/C][C]0.433248295962637[/C][/ROW]
[ROW][C]206[/C][C]0.726452604769142[/C][C]0.547094790461716[/C][C]0.273547395230858[/C][/ROW]
[ROW][C]207[/C][C]2.52712265688843e-14[/C][C]5.05424531377686e-14[/C][C]0.999999999999975[/C][/ROW]
[ROW][C]208[/C][C]0.948906214257964[/C][C]0.102187571484071[/C][C]0.0510937857420357[/C][/ROW]
[ROW][C]209[/C][C]1.87573600738136e-07[/C][C]3.75147201476272e-07[/C][C]0.999999812426399[/C][/ROW]
[ROW][C]210[/C][C]6.02441862742376e-51[/C][C]1.20488372548475e-50[/C][C]1[/C][/ROW]
[ROW][C]211[/C][C]0.999999864250961[/C][C]2.71498078699179e-07[/C][C]1.3574903934959e-07[/C][/ROW]
[ROW][C]212[/C][C]1.11676956350019e-13[/C][C]2.23353912700038e-13[/C][C]0.999999999999888[/C][/ROW]
[ROW][C]213[/C][C]0.031260673545819[/C][C]0.0625213470916379[/C][C]0.968739326454181[/C][/ROW]
[ROW][C]214[/C][C]0.999969597357861[/C][C]6.08052842772823e-05[/C][C]3.04026421386412e-05[/C][/ROW]
[ROW][C]215[/C][C]0.995193025153[/C][C]0.00961394969399911[/C][C]0.00480697484699956[/C][/ROW]
[ROW][C]216[/C][C]2.09201122846258e-17[/C][C]4.18402245692516e-17[/C][C]1[/C][/ROW]
[ROW][C]217[/C][C]0.102864133423368[/C][C]0.205728266846736[/C][C]0.897135866576632[/C][/ROW]
[ROW][C]218[/C][C]1.68882768614764e-14[/C][C]3.37765537229527e-14[/C][C]0.999999999999983[/C][/ROW]
[ROW][C]219[/C][C]0.998953967560097[/C][C]0.00209206487980652[/C][C]0.00104603243990326[/C][/ROW]
[ROW][C]220[/C][C]0.987390062791942[/C][C]0.0252198744161153[/C][C]0.0126099372080577[/C][/ROW]
[ROW][C]221[/C][C]0.00496542006744235[/C][C]0.0099308401348847[/C][C]0.995034579932558[/C][/ROW]
[ROW][C]222[/C][C]8.64022300649583e-07[/C][C]1.72804460129917e-06[/C][C]0.999999135977699[/C][/ROW]
[ROW][C]223[/C][C]0.232266847240211[/C][C]0.464533694480422[/C][C]0.767733152759789[/C][/ROW]
[ROW][C]224[/C][C]4.59472394006803e-28[/C][C]9.18944788013606e-28[/C][C]1[/C][/ROW]
[ROW][C]225[/C][C]1.73842839198542e-05[/C][C]3.47685678397084e-05[/C][C]0.99998261571608[/C][/ROW]
[ROW][C]226[/C][C]0.999999603919366[/C][C]7.92161267158628e-07[/C][C]3.96080633579314e-07[/C][/ROW]
[ROW][C]227[/C][C]2.02349653777178e-75[/C][C]4.04699307554356e-75[/C][C]1[/C][/ROW]
[ROW][C]228[/C][C]0.0179935723953922[/C][C]0.0359871447907844[/C][C]0.982006427604608[/C][/ROW]
[ROW][C]229[/C][C]0.959439433130366[/C][C]0.0811211337392681[/C][C]0.0405605668696341[/C][/ROW]
[ROW][C]230[/C][C]0.0100670470672959[/C][C]0.0201340941345918[/C][C]0.989932952932704[/C][/ROW]
[ROW][C]231[/C][C]0.724475547225072[/C][C]0.551048905549855[/C][C]0.275524452774928[/C][/ROW]
[ROW][C]232[/C][C]0.999979285551499[/C][C]4.14288970020791e-05[/C][C]2.07144485010396e-05[/C][/ROW]
[ROW][C]233[/C][C]3.20392018702718e-07[/C][C]6.40784037405437e-07[/C][C]0.999999679607981[/C][/ROW]
[ROW][C]234[/C][C]0.0334871086078533[/C][C]0.0669742172157066[/C][C]0.966512891392147[/C][/ROW]
[ROW][C]235[/C][C]9.32318339285568e-38[/C][C]1.86463667857114e-37[/C][C]1[/C][/ROW]
[ROW][C]236[/C][C]1.76160151408192e-36[/C][C]3.52320302816383e-36[/C][C]1[/C][/ROW]
[ROW][C]237[/C][C]0.0804861613185567[/C][C]0.160972322637113[/C][C]0.919513838681443[/C][/ROW]
[ROW][C]238[/C][C]6.96810822832765e-21[/C][C]1.39362164566553e-20[/C][C]1[/C][/ROW]
[ROW][C]239[/C][C]0.071969589390123[/C][C]0.143939178780246[/C][C]0.928030410609877[/C][/ROW]
[ROW][C]240[/C][C]4.67178843092058e-06[/C][C]9.34357686184117e-06[/C][C]0.999995328211569[/C][/ROW]
[ROW][C]241[/C][C]2.90490447052788e-08[/C][C]5.80980894105576e-08[/C][C]0.999999970950955[/C][/ROW]
[ROW][C]242[/C][C]0.00173504047923199[/C][C]0.00347008095846397[/C][C]0.998264959520768[/C][/ROW]
[ROW][C]243[/C][C]0.94090844523562[/C][C]0.11818310952876[/C][C]0.0590915547643798[/C][/ROW]
[ROW][C]244[/C][C]5.0907906434921e-28[/C][C]1.01815812869842e-27[/C][C]1[/C][/ROW]
[ROW][C]245[/C][C]0.00900792182580691[/C][C]0.0180158436516138[/C][C]0.990992078174193[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190339&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190339&T=5

As an alternative you can also use a QR Code:

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

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
19	0.40228834589082	0.804576691781641	0.597711654109179
20	0.555319611918205	0.88936077616359	0.444680388081795
21	0.219406574488551	0.438813148977102	0.780593425511449
22	0.921069210027943	0.157861579944115	0.0789307899720573
23	0.984425201949361	0.0311495961012781	0.015574798050639
24	0.980335576578819	0.0393288468423628	0.0196644234211814
25	0.9149896124897	0.170020775020599	0.0850103875102996
26	0.000324993743970001	0.000649987487940002	0.99967500625603
27	0.0121619505025199	0.0243239010050397	0.98783804949748
28	1	3.71711121170752e-20	1.85855560585376e-20
29	0.929952407417836	0.140095185164328	0.0700475925821639
30	0.00818883043787245	0.0163776608757449	0.991811169562128
31	0.983695065517823	0.0326098689643546	0.0163049344821773
32	0.22777546228606	0.455550924572119	0.772224537713941
33	0.999999995836972	8.32605643792285e-09	4.16302821896143e-09
34	8.45639605661226e-09	1.69127921132245e-08	0.999999991543604
35	0.792927773596607	0.414144452806786	0.207072226403393
36	0.0750621955369129	0.150124391073826	0.924937804463087
37	9.97515352223561e-07	1.99503070444712e-06	0.999999002484648
38	0.300817059985505	0.601634119971011	0.699182940014495
39	0.952218781843188	0.0955624363136233	0.0477812181568116
40	3.34542976825003e-09	6.69085953650006e-09	0.99999999665457
41	5.1622663195582e-06	1.03245326391164e-05	0.99999483773368
42	0.999999999999997	6.21058167798393e-15	3.10529083899196e-15
43	0.999999999307931	1.384138672244e-09	6.92069336122e-10
44	0.559927873642394	0.880144252715212	0.440072126357606
45	0.998777052090295	0.00244589581940994	0.00122294790970497
46	0.999698331091523	0.00060333781695406	0.00030166890847703
47	0.06797925840233	0.13595851680466	0.93202074159767
48	0.999999998071932	3.85613524211471e-09	1.92806762105735e-09
49	1	6.66466807386733e-38	3.33233403693366e-38
50	0.974466940347459	0.0510661193050818	0.0255330596525409
51	9.39779328489027e-09	1.87955865697805e-08	0.999999990602207
52	0.954113144552137	0.0917737108957261	0.0458868554478631
53	1.32036612928931e-06	2.64073225857862e-06	0.999998679633871
54	0.224598151866797	0.449196303733594	0.775401848133203
55	0.999999999999972	5.58405117295423e-14	2.79202558647712e-14
56	0.00343596587561769	0.00687193175123537	0.996564034124382
57	0.999564044022912	0.000871911954175242	0.000435955977087621
58	0.605630399465222	0.788739201069556	0.394369600534778
59	0.995932713812751	0.00813457237449721	0.0040672861872486
60	4.90330117263184e-05	9.80660234526368e-05	0.999950966988274
61	1	2.83223115071108e-33	1.41611557535554e-33
62	0.999997960103697	4.07979260668682e-06	2.03989630334341e-06
63	1	3.5028916671508e-19	1.7514458335754e-19
64	7.06709236608769e-14	1.41341847321754e-13	0.999999999999929
65	1.54773334266328e-10	3.09546668532656e-10	0.999999999845227
66	2.47264810314444e-24	4.94529620628889e-24	1
67	0.698665804569396	0.602668390861207	0.301334195430604
68	1.15861258576554e-05	2.31722517153109e-05	0.999988413874142
69	8.37622982836868e-14	1.67524596567374e-13	0.999999999999916
70	3.74178160002837e-11	7.48356320005673e-11	0.999999999962582
71	1.70205694153655e-17	3.4041138830731e-17	1
72	0.999996087594178	7.82481164389571e-06	3.91240582194785e-06
73	0.00036411092597973	0.00072822185195946	0.99963588907402
74	0.999999997712796	4.57440743687688e-09	2.28720371843844e-09
75	0.466077475098999	0.932154950197998	0.533922524901001
76	0.999658352483215	0.000683295033569156	0.000341647516784578
77	0.999860655086887	0.000278689826225016	0.000139344913112508
78	2.6833313665706e-23	5.3666627331412e-23	1
79	0.0827527427151601	0.16550548543032	0.91724725728484
80	0.000129439722594522	0.000258879445189044	0.999870560277406
81	1.17551959287488e-13	2.35103918574977e-13	0.999999999999882
82	0.828171869818904	0.343656260362191	0.171828130181096
83	0.999999999475936	1.04812780928e-09	5.24063904640001e-10
84	0.00135018676139402	0.00270037352278805	0.998649813238606
85	0.823070357855832	0.353859284288336	0.176929642144168
86	5.27606702574724e-09	1.05521340514945e-08	0.999999994723933
87	6.63648623371417e-09	1.32729724674283e-08	0.999999993363514
88	0.999975817590579	4.83648188416528e-05	2.41824094208264e-05
89	1.97353094268119e-05	3.94706188536238e-05	0.999980264690573
90	0.4757727202199	0.9515454404398	0.5242272797801
91	3.24697087922979e-07	6.49394175845957e-07	0.999999675302912
92	1.30716268965404e-07	2.61432537930809e-07	0.999999869283731
93	0.99971827457237	0.000563450855260668	0.000281725427630334
94	2.24332243514111e-12	4.48664487028222e-12	0.999999999997757
95	0.298784475381549	0.597568950763098	0.701215524618451
96	0.10342468702221	0.20684937404442	0.89657531297779
97	0.0804586944895623	0.160917388979125	0.919541305510438
98	0.999999999898452	2.03096663603641e-10	1.0154833180182e-10
99	1.99563483359068e-08	3.99126966718135e-08	0.999999980043652
100	0.999478717036258	0.00104256592748431	0.000521282963742157
101	0.0194479799160829	0.0388959598321659	0.980552020083917
102	5.63957045055609e-32	1.12791409011122e-31	1
103	0.999999999626569	7.46860964247596e-10	3.73430482123798e-10
104	0.999999999897422	2.05156872163919e-10	1.0257843608196e-10
105	0.0454157991670118	0.0908315983340236	0.954584200832988
106	0.0513916661138937	0.102783332227787	0.948608333886106
107	0.99999990925488	1.81490239874159e-07	9.07451199370795e-08
108	2.46092768054643e-09	4.92185536109285e-09	0.999999997539072
109	0.955767519371303	0.0884649612573936	0.0442324806286968
110	8.85430035815885e-38	1.77086007163177e-37	1
111	0.910043343080715	0.179913313838571	0.0899566569192854
112	4.02264989991461e-09	8.04529979982922e-09	0.99999999597735
113	0.999950035773404	9.99284531911442e-05	4.99642265955721e-05
114	3.85943207318273e-08	7.71886414636545e-08	0.999999961405679
115	1.10343223125912e-07	2.20686446251824e-07	0.999999889656777
116	0.855071512643574	0.289856974712853	0.144928487356426
117	7.5214567813668e-21	1.50429135627336e-20	1
118	0.000881945515019417	0.00176389103003883	0.999118054484981
119	1	3.64858735516655e-20	1.82429367758327e-20
120	9.05887699030417e-09	1.81177539806083e-08	0.999999990941123
121	0.999999999970649	5.87009379933526e-11	2.93504689966763e-11
122	9.01155161647999e-15	1.802310323296e-14	0.999999999999991
123	0.999303765588447	0.00139246882310625	0.000696234411553123
124	4.88723627929409e-31	9.77447255858819e-31	1
125	1	2.2312844893789e-17	1.11564224468945e-17
126	1	1.97226843654285e-21	9.86134218271423e-22
127	0.00684739563639831	0.0136947912727966	0.993152604363602
128	0.670077666592013	0.659844666815975	0.329922333407987
129	1.63603678227241e-40	3.27207356454482e-40	1
130	3.99713952509614e-28	7.99427905019229e-28	1
131	2.0236859850622e-28	4.0473719701244e-28	1
132	3.02869668027751e-23	6.05739336055501e-23	1
133	6.12535841654327e-26	1.22507168330865e-25	1
134	2.54561479658834e-08	5.09122959317668e-08	0.999999974543852
135	0.00060293800412816	0.00120587600825632	0.999397061995872
136	0.00751114718628936	0.0150222943725787	0.992488852813711
137	0.99999999999961	7.79626476979923e-13	3.89813238489962e-13
138	0.999999999909938	1.80124089413312e-10	9.00620447066562e-11
139	9.2821992267036e-15	1.85643984534072e-14	0.999999999999991
140	1.0376847598637e-07	2.0753695197274e-07	0.999999896231524
141	0.937230617755944	0.125538764488112	0.0627693822440561
142	0.638784770665638	0.722430458668724	0.361215229334362
143	0.231569891661029	0.463139783322059	0.768430108338971
144	0.966021907251366	0.0679561854972681	0.0339780927486341
145	0.279954903653576	0.559909807307152	0.720045096346424
146	1.6576029868166e-42	3.31520597363319e-42	1
147	0.038796968257401	0.077593936514802	0.961203031742599
148	2.02515261138506e-21	4.05030522277012e-21	1
149	0.999999999999914	1.72058702809162e-13	8.60293514045811e-14
150	0.749370355927759	0.501259288144482	0.250629644072241
151	0.999999999999991	1.72811274358611e-14	8.64056371793056e-15
152	0.000205394445570046	0.000410788891140093	0.99979460555443
153	3.25535806263963e-48	6.51071612527927e-48	1
154	0.985855203841501	0.0282895923169979	0.0141447961584989
155	2.58142915431639e-11	5.16285830863278e-11	0.999999999974186
156	1	1.49023420917783e-26	7.45117104588917e-27
157	1	4.68225982959741e-17	2.3411299147987e-17
158	0.978526120807812	0.0429477583843767	0.0214738791921884
159	1	4.01763313027514e-31	2.00881656513757e-31
160	0.000213143399944063	0.000426286799888127	0.999786856600056
161	5.9550520689763e-16	1.19101041379526e-15	0.999999999999999
162	1.64688767434609e-13	3.29377534869217e-13	0.999999999999835
163	6.70017643553115e-17	1.34003528710623e-16	1
164	3.83843035710517e-13	7.67686071421033e-13	0.999999999999616
165	1.51994022412039e-17	3.03988044824078e-17	1
166	1.28016620446872e-25	2.56033240893743e-25	1
167	0.593088128741384	0.813823742517231	0.406911871258616
168	2.60321712083954e-13	5.20643424167908e-13	0.99999999999974
169	3.23001622025456e-42	6.46003244050912e-42	1
170	0.999999986847956	2.63040877600586e-08	1.31520438800293e-08
171	2.53986103914762e-29	5.07972207829524e-29	1
172	3.47918468813283e-35	6.95836937626566e-35	1
173	0.999999999999985	3.07955141578191e-14	1.53977570789096e-14
174	8.21141488423181e-90	1.64228297684636e-89	1
175	6.25132849804714e-28	1.25026569960943e-27	1
176	7.43628455566725e-16	1.48725691113345e-15	0.999999999999999
177	0.00326902110384998	0.00653804220769995	0.99673097889615
178	3.59699468959486e-10	7.19398937918973e-10	0.999999999640301
179	1	2.36600663296867e-23	1.18300331648434e-23
180	0.0191543965331648	0.0383087930663295	0.980845603466835
181	1	1.41303783616803e-20	7.06518918084016e-21
182	5.76088519119062e-24	1.15217703823812e-23	1
183	0.999999999989763	2.04733734391415e-11	1.02366867195708e-11
184	2.3562239951615e-32	4.712447990323e-32	1
185	8.91516987275113e-19	1.78303397455023e-18	1
186	0.142847818970043	0.285695637940087	0.857152181029957
187	0.00163802453345996	0.00327604906691993	0.99836197546654
188	5.57689119998738e-65	1.11537823999748e-64	1
189	0.162909792641298	0.325819585282597	0.837090207358702
190	1.21709975568818e-09	2.43419951137637e-09	0.9999999987829
191	3.45217498786514e-07	6.90434997573029e-07	0.999999654782501
192	1.46107455685421e-09	2.92214911370842e-09	0.999999998538925
193	1.25699173002184e-26	2.51398346004368e-26	1
194	0.0983068237218565	0.196613647443713	0.901693176278143
195	0.999996091190104	7.81761979149998e-06	3.90880989574999e-06
196	1	3.37701604961216e-20	1.68850802480608e-20
197	0.896838059550096	0.206323880899808	0.103161940449904
198	0.0165904094230384	0.0331808188460767	0.983409590576962
199	0.0319688337959431	0.0639376675918862	0.968031166204057
200	0.999953682205625	9.26355887509922e-05	4.63177943754961e-05
201	0.999999999999999	1.20903618697438e-15	6.04518093487192e-16
202	0.999744879825246	0.000510240349508426	0.000255120174754213
203	0.00121788534280533	0.00243577068561066	0.998782114657195
204	0.258325724972098	0.516651449944196	0.741674275027902
205	0.566751704037363	0.866496591925275	0.433248295962637
206	0.726452604769142	0.547094790461716	0.273547395230858
207	2.52712265688843e-14	5.05424531377686e-14	0.999999999999975
208	0.948906214257964	0.102187571484071	0.0510937857420357
209	1.87573600738136e-07	3.75147201476272e-07	0.999999812426399
210	6.02441862742376e-51	1.20488372548475e-50	1
211	0.999999864250961	2.71498078699179e-07	1.3574903934959e-07
212	1.11676956350019e-13	2.23353912700038e-13	0.999999999999888
213	0.031260673545819	0.0625213470916379	0.968739326454181
214	0.999969597357861	6.08052842772823e-05	3.04026421386412e-05
215	0.995193025153	0.00961394969399911	0.00480697484699956
216	2.09201122846258e-17	4.18402245692516e-17	1
217	0.102864133423368	0.205728266846736	0.897135866576632
218	1.68882768614764e-14	3.37765537229527e-14	0.999999999999983
219	0.998953967560097	0.00209206487980652	0.00104603243990326
220	0.987390062791942	0.0252198744161153	0.0126099372080577
221	0.00496542006744235	0.0099308401348847	0.995034579932558
222	8.64022300649583e-07	1.72804460129917e-06	0.999999135977699
223	0.232266847240211	0.464533694480422	0.767733152759789
224	4.59472394006803e-28	9.18944788013606e-28	1
225	1.73842839198542e-05	3.47685678397084e-05	0.99998261571608
226	0.999999603919366	7.92161267158628e-07	3.96080633579314e-07
227	2.02349653777178e-75	4.04699307554356e-75	1
228	0.0179935723953922	0.0359871447907844	0.982006427604608
229	0.959439433130366	0.0811211337392681	0.0405605668696341
230	0.0100670470672959	0.0201340941345918	0.989932952932704
231	0.724475547225072	0.551048905549855	0.275524452774928
232	0.999979285551499	4.14288970020791e-05	2.07144485010396e-05
233	3.20392018702718e-07	6.40784037405437e-07	0.999999679607981
234	0.0334871086078533	0.0669742172157066	0.966512891392147
235	9.32318339285568e-38	1.86463667857114e-37	1
236	1.76160151408192e-36	3.52320302816383e-36	1
237	0.0804861613185567	0.160972322637113	0.919513838681443
238	6.96810822832765e-21	1.39362164566553e-20	1
239	0.071969589390123	0.143939178780246	0.928030410609877
240	4.67178843092058e-06	9.34357686184117e-06	0.999995328211569
241	2.90490447052788e-08	5.80980894105576e-08	0.999999970950955
242	0.00173504047923199	0.00347008095846397	0.998264959520768
243	0.94090844523562	0.11818310952876	0.0590915547643798
244	5.0907906434921e-28	1.01815812869842e-27	1
245	0.00900792182580691	0.0180158436516138	0.990992078174193

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	153	0.674008810572687	NOK
5% type I error level	169	0.744493392070485	NOK
10% type I error level	180	0.79295154185022	NOK

\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 & 153 & 0.674008810572687 & NOK \tabularnewline
5% type I error level & 169 & 0.744493392070485 & NOK \tabularnewline
10% type I error level & 180 & 0.79295154185022 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190339&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]153[/C][C]0.674008810572687[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]169[/C][C]0.744493392070485[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]180[/C][C]0.79295154185022[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190339&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190339&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	153	0.674008810572687	NOK
5% type I error level	169	0.744493392070485	NOK
10% type I error level	180	0.79295154185022	NOK

Figure 1

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 9 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 9 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

R code (references can be found in the software module):

library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], 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,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
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, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
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,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
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,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
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,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
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,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code