Free Statistics

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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSat, 03 Nov 2012 09:59:57 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/03/t1351951415aeq5d0ox1iy2nmh.htm/, Retrieved Sun, 03 Jul 2022 13:59:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185728, Retrieved Sun, 03 Jul 2022 13:59:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-11-17 09:55:05] [b98453cac15ba1066b407e146608df68]
-   P     [Multiple Regression] [] [2012-11-03 13:59:57] [54fc54845b7758f1604e617c5518fca2] [Current]
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Dataseries X:
1	1	1	41	41	38	38	13	12	12	14	14	12	12	53	53
1	2	2	39	39	32	32	16	11	11	18	18	11	11	83	83
1	3	3	30	30	35	35	19	15	15	11	11	14	14	66	66
1	4	4	31	31	33	33	15	6	6	12	12	12	12	67	67
1	5	5	34	34	37	37	14	13	13	16	16	21	21	76	76
1	6	6	35	35	29	29	13	10	10	18	18	12	12	78	78
1	7	7	39	39	31	31	19	12	12	14	14	22	22	53	53
1	8	8	34	34	36	36	15	14	14	14	14	11	11	80	80
1	9	9	36	36	35	35	14	12	12	15	15	10	10	74	74
1	10	10	37	37	38	38	15	9	9	15	15	13	13	76	76
1	11	11	38	38	31	31	16	10	10	17	17	10	10	79	79
1	12	12	36	36	34	34	16	12	12	19	19	8	8	54	54
1	13	13	38	38	35	35	16	12	12	10	10	15	15	67	67
1	14	14	39	39	38	38	16	11	11	16	16	14	14	54	54
1	15	15	33	33	37	37	17	15	15	18	18	10	10	87	87
1	16	16	32	32	33	33	15	12	12	14	14	14	14	58	58
1	17	17	36	36	32	32	15	10	10	14	14	14	14	75	75
1	18	18	38	38	38	38	20	12	12	17	17	11	11	88	88
1	19	19	39	39	38	38	18	11	11	14	14	10	10	64	64
1	20	20	32	32	32	32	16	12	12	16	16	13	13	57	57
1	21	21	32	32	33	33	16	11	11	18	18	9.5	9.5	66	66
1	22	22	31	31	31	31	16	12	12	11	11	14	14	68	68
1	23	23	39	39	38	38	19	13	13	14	14	12	12	54	54
1	24	24	37	37	39	39	16	11	11	12	12	14	14	56	56
1	25	25	39	39	32	32	17	12	12	17	17	11	11	86	86
1	26	26	41	41	32	32	17	13	13	9	9	9	9	80	80
1	27	27	36	36	35	35	16	10	10	16	16	11	11	76	76
1	28	28	33	33	37	37	15	14	14	14	14	15	15	69	69
1	29	29	33	33	33	33	16	12	12	15	15	14	14	78	78
1	30	30	34	34	33	33	14	10	10	11	11	13	13	67	67
1	31	31	31	31	31	31	15	12	12	16	16	9	9	80	80
1	32	32	27	27	32	32	12	8	8	13	13	15	15	54	54
1	33	33	37	37	31	31	14	10	10	17	17	10	10	71	71
1	34	34	34	34	37	37	16	12	12	15	15	11	11	84	84
1	35	35	34	34	30	30	14	12	12	14	14	13	13	74	74
1	36	36	32	32	33	33	10	7	7	16	16	8	8	71	71
1	37	37	29	29	31	31	10	9	9	9	9	20	20	63	63
1	38	38	36	36	33	33	14	12	12	15	15	12	12	71	71
1	39	39	29	29	31	31	16	10	10	17	17	10	10	76	76
1	40	40	35	35	33	33	16	10	10	13	13	10	10	69	69
1	41	41	37	37	32	32	16	10	10	15	15	9	9	74	74
1	42	42	34	34	33	33	14	12	12	16	16	14	14	75	75
1	43	43	38	38	32	32	20	15	15	16	16	8	8	54	54
1	44	44	35	35	33	33	14	10	10	12	12	14	14	52	52
1	45	45	38	38	28	28	14	10	10	15	15	11	11	69	69
1	46	46	37	37	35	35	11	12	12	11	11	13	13	68	68
1	47	47	38	38	39	39	14	13	13	15	15	9	9	65	65
1	48	48	33	33	34	34	15	11	11	15	15	11	11	75	75
1	49	49	36	36	38	38	16	11	11	17	17	15	15	74	74
1	50	50	38	38	32	32	14	12	12	13	13	11	11	75	75
1	51	51	32	32	38	38	16	14	14	16	16	10	10	72	72
1	52	52	32	32	30	30	14	10	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	13	13	12	12	14	14	62	62
1	55	55	32	32	32	32	9	5	5	12	12	11	11	63	63
1	56	56	37	37	35	35	14	6	6	15	15	14.5	14.5	76	76
1	57	57	39	39	34	34	16	12	12	16	16	13	13	74	74
1	58	58	29	29	34	34	16	12	12	15	15	9	9	67	67
1	59	59	37	37	36	36	15	11	11	12	12	10	10	73	73
1	60	60	35	35	34	34	16	10	10	12	12	15	15	70	70
1	61	61	30	30	28	28	12	7	7	8	8	20	20	53	53
1	62	62	38	38	34	34	16	12	12	13	13	12	12	77	77
1	63	63	34	34	35	35	16	14	14	11	11	12	12	80	80
1	64	64	31	31	35	35	14	11	11	14	14	14	14	52	52
1	65	65	34	34	31	31	16	12	12	15	15	13	13	54	54
1	66	66	35	35	37	37	17	13	13	10	10	11	11	80	80
1	67	67	36	36	35	35	18	14	14	11	11	17	17	66	66
1	68	68	30	30	27	27	18	11	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	12	12	15	15	14	14	69	69
1	71	71	38	38	36	36	10	8	8	14	14	13	13	67	67
1	72	72	31	31	38	38	14	11	11	16	16	15	15	54	54
1	73	73	34	34	39	39	18	14	14	15	15	13	13	81	81
1	74	74	38	38	41	41	18	14	14	15	15	10	10	69	69
1	75	75	34	34	27	27	16	12	12	13	13	11	11	84	84
1	76	76	39	39	30	30	17	9	9	12	12	19	19	80	80
1	77	77	37	37	37	37	16	13	13	17	17	13	13	70	70
1	78	78	34	34	31	31	16	11	11	13	13	17	17	69	69
1	79	79	28	28	31	31	13	12	12	15	15	13	13	77	77
1	80	80	37	37	27	27	16	12	12	13	13	9	9	54	54
1	81	81	33	33	36	36	16	12	12	15	15	11	11	79	79
1	82	82	35	35	37	37	16	12	12	15	15	9	9	71	71
1	83	83	37	37	33	33	15	12	12	16	16	12	12	73	73
1	84	84	32	32	34	34	15	11	11	15	15	12	12	72	72
1	85	85	33	33	31	31	16	10	10	14	14	13	13	77	77
1	86	86	38	38	39	39	14	9	9	15	15	13	13	75	75
1	87	87	33	33	34	34	16	12	12	14	14	12	12	69	69
1	88	88	29	29	32	32	16	12	12	13	13	15	15	54	54
1	89	89	33	33	33	33	15	12	12	7	7	22	22	70	70
1	90	90	31	31	36	36	12	9	9	17	17	13	13	73	73
1	91	91	36	36	32	32	17	15	15	13	13	15	15	54	54
1	92	92	35	35	41	41	16	12	12	15	15	13	13	77	77
1	93	93	32	32	28	28	15	12	12	14	14	15	15	82	82
1	94	94	29	29	30	30	13	12	12	13	13	12.5	12.5	80	80
1	95	95	39	39	36	36	16	10	10	16	16	11	11	80	80
1	96	96	37	37	35	35	16	13	13	12	12	16	16	69	69
1	97	97	35	35	31	31	16	9	9	14	14	11	11	78	78
1	98	98	37	37	34	34	16	12	12	17	17	11	11	81	81
1	99	99	32	32	36	36	14	10	10	15	15	10	10	76	76
1	100	100	38	38	36	36	16	14	14	17	17	10	10	76	76
1	101	101	37	37	35	35	16	11	11	12	12	16	16	73	73
1	102	102	36	36	37	37	20	15	15	16	16	12	12	85	85
1	103	103	32	32	28	28	15	11	11	11	11	11	11	66	66
1	104	104	33	33	39	39	16	11	11	15	15	16	16	79	79
1	105	105	40	40	32	32	13	12	12	9	9	19	19	68	68
1	106	106	38	38	35	35	17	12	12	16	16	11	11	76	76
1	107	107	41	41	39	39	16	12	12	15	15	16	16	71	71
1	108	108	36	36	35	35	16	11	11	10	10	15	15	54	54
1	109	109	43	43	42	42	12	7	7	10	10	24	24	46	46
1	110	110	30	30	34	34	16	12	12	15	15	14	14	85	85
1	111	111	31	31	33	33	16	14	14	11	11	15	15	74	74
1	112	112	32	32	41	41	17	11	11	13	13	11	11	88	88
1	113	113	32	32	33	33	13	11	11	14	14	15	15	38	38
1	114	114	37	37	34	34	12	10	10	18	18	12	12	76	76
1	115	115	37	37	32	32	18	13	13	16	16	10	10	86	86
1	116	116	33	33	40	40	14	13	13	14	14	14	14	54	54
1	117	117	34	34	40	40	14	8	8	14	14	13	13	67	67
1	118	118	33	33	35	35	13	11	11	14	14	9	9	69	69
1	119	119	38	38	36	36	16	12	12	14	14	15	15	90	90
1	120	120	33	33	37	37	13	11	11	12	12	15	15	54	54
1	121	121	31	31	27	27	16	13	13	14	14	14	14	76	76
1	122	122	38	38	39	39	13	12	12	15	15	11	11	89	89
1	123	123	37	37	38	38	16	14	14	15	15	8	8	76	76
1	124	124	36	36	31	31	15	13	13	15	15	11	11	73	73
1	125	125	31	31	33	33	16	15	15	13	13	11	11	79	79
1	126	126	39	39	32	32	15	10	10	17	17	8	8	90	90
1	127	127	44	44	39	39	17	11	11	17	17	10	10	74	74
1	128	128	33	33	36	36	15	9	9	19	19	11	11	81	81
1	129	129	35	35	33	33	12	11	11	15	15	13	13	72	72
1	130	130	32	32	33	33	16	10	10	13	13	11	11	71	71
1	131	131	28	28	32	32	10	11	11	9	9	20	20	66	66
1	132	132	40	40	37	37	16	8	8	15	15	10	10	77	77
1	133	133	27	27	30	30	12	11	11	15	15	15	15	65	65
1	134	134	37	37	38	38	14	12	12	15	15	12	12	74	74
1	135	135	32	32	29	29	15	12	12	16	16	14	14	85	85
1	136	136	28	28	22	22	13	9	9	11	11	23	23	54	54
1	137	137	34	34	35	35	15	11	11	14	14	14	14	63	63
1	138	138	30	30	35	35	11	10	10	11	11	16	16	54	54
1	139	139	35	35	34	34	12	8	8	15	15	11	11	64	64
1	140	140	31	31	35	35	11	9	9	13	13	12	12	69	69
1	141	141	32	32	34	34	16	8	8	15	15	10	10	54	54
1	142	142	30	30	37	37	15	9	9	16	16	14	14	84	84
1	143	143	30	30	35	35	17	15	15	14	14	12	12	86	86
1	144	144	31	31	23	23	16	11	11	15	15	12	12	77	77
1	145	145	40	40	31	31	10	8	8	16	16	11	11	89	89
1	146	146	32	32	27	27	18	13	13	16	16	12	12	76	76
1	147	147	36	36	36	36	13	12	12	11	11	13	13	60	60
1	148	148	32	32	31	31	16	12	12	12	12	11	11	75	75
1	149	149	35	35	32	32	13	9	9	9	9	19	19	73	73
1	150	150	38	38	39	39	10	7	7	16	16	12	12	85	85
1	151	151	42	42	37	37	15	13	13	13	13	17	17	79	79
1	152	152	34	34	38	38	16	9	9	16	16	9	9	71	71
1	153	153	35	35	39	39	16	6	6	12	12	12	12	72	72
1	154	154	38	38	34	34	14	8	8	9	9	19	19	69	69
1	155	155	33	33	31	31	10	8	8	13	13	18	18	78	78
1	156	156	36	36	32	32	17	15	15	13	13	15	15	54	54
1	157	157	32	32	37	37	13	6	6	14	14	14	14	69	69
1	158	158	33	33	36	36	15	9	9	19	19	11	11	81	81
1	159	159	34	34	32	32	16	11	11	13	13	9	9	84	84
1	160	160	32	32	38	38	12	8	8	12	12	18	18	84	84
1	161	161	34	34	36	36	13	8	8	13	13	16	16	69	69
0	162	0	27	0	26	0	13	10	0	10	0	24	0	66	0
0	163	0	31	0	26	0	12	8	0	14	0	14	0	81	0
0	164	0	38	0	33	0	17	14	0	16	0	20	0	82	0
0	165	0	34	0	39	0	15	10	0	10	0	18	0	72	0
0	166	0	24	0	30	0	10	8	0	11	0	23	0	54	0
0	167	0	30	0	33	0	14	11	0	14	0	12	0	78	0
0	168	0	26	0	25	0	11	12	0	12	0	14	0	74	0
0	169	0	34	0	38	0	13	12	0	9	0	16	0	82	0
0	170	0	27	0	37	0	16	12	0	9	0	18	0	73	0
0	171	0	37	0	31	0	12	5	0	11	0	20	0	55	0
0	172	0	36	0	37	0	16	12	0	16	0	12	0	72	0
0	173	0	41	0	35	0	12	10	0	9	0	12	0	78	0
0	174	0	29	0	25	0	9	7	0	13	0	17	0	59	0
0	175	0	36	0	28	0	12	12	0	16	0	13	0	72	0
0	176	0	32	0	35	0	15	11	0	13	0	9	0	78	0
0	177	0	37	0	33	0	12	8	0	9	0	16	0	68	0
0	178	0	30	0	30	0	12	9	0	12	0	18	0	69	0
0	179	0	31	0	31	0	14	10	0	16	0	10	0	67	0
0	180	0	38	0	37	0	12	9	0	11	0	14	0	74	0
0	181	0	36	0	36	0	16	12	0	14	0	11	0	54	0
0	182	0	35	0	30	0	11	6	0	13	0	9	0	67	0
0	183	0	31	0	36	0	19	15	0	15	0	11	0	70	0
0	184	0	38	0	32	0	15	12	0	14	0	10	0	80	0
0	185	0	22	0	28	0	8	12	0	16	0	11	0	89	0
0	186	0	32	0	36	0	16	12	0	13	0	19	0	76	0
0	187	0	36	0	34	0	17	11	0	14	0	14	0	74	0
0	188	0	39	0	31	0	12	7	0	15	0	12	0	87	0
0	189	0	28	0	28	0	11	7	0	13	0	14	0	54	0
0	190	0	32	0	36	0	11	5	0	11	0	21	0	61	0
0	191	0	32	0	36	0	14	12	0	11	0	13	0	38	0
0	192	0	38	0	40	0	16	12	0	14	0	10	0	75	0
0	193	0	32	0	33	0	12	3	0	15	0	15	0	69	0
0	194	0	35	0	37	0	16	11	0	11	0	16	0	62	0
0	195	0	32	0	32	0	13	10	0	15	0	14	0	72	0
0	196	0	37	0	38	0	15	12	0	12	0	12	0	70	0
0	197	0	34	0	31	0	16	9	0	14	0	19	0	79	0
0	198	0	33	0	37	0	16	12	0	14	0	15	0	87	0
0	199	0	33	0	33	0	14	9	0	8	0	19	0	62	0
0	200	0	26	0	32	0	16	12	0	13	0	13	0	77	0
0	201	0	30	0	30	0	16	12	0	9	0	17	0	69	0
0	202	0	24	0	30	0	14	10	0	15	0	12	0	69	0
0	203	0	34	0	31	0	11	9	0	17	0	11	0	75	0
0	204	0	34	0	32	0	12	12	0	13	0	14	0	54	0
0	205	0	33	0	34	0	15	8	0	15	0	11	0	72	0
0	206	0	34	0	36	0	15	11	0	15	0	13	0	74	0
0	207	0	35	0	37	0	16	11	0	14	0	12	0	85	0
0	208	0	35	0	36	0	16	12	0	16	0	15	0	52	0
0	209	0	36	0	33	0	11	10	0	13	0	14	0	70	0
0	210	0	34	0	33	0	15	10	0	16	0	12	0	84	0
0	211	0	34	0	33	0	12	12	0	9	0	17	0	64	0
0	212	0	41	0	44	0	12	12	0	16	0	11	0	84	0
0	213	0	32	0	39	0	15	11	0	11	0	18	0	87	0
0	214	0	30	0	32	0	15	8	0	10	0	13	0	79	0
0	215	0	35	0	35	0	16	12	0	11	0	17	0	67	0
0	216	0	28	0	25	0	14	10	0	15	0	13	0	65	0
0	217	0	33	0	35	0	17	11	0	17	0	11	0	85	0
0	218	0	39	0	34	0	14	10	0	14	0	12	0	83	0
0	219	0	36	0	35	0	13	8	0	8	0	22	0	61	0
0	220	0	36	0	39	0	15	12	0	15	0	14	0	82	0
0	221	0	35	0	33	0	13	12	0	11	0	12	0	76	0
0	222	0	38	0	36	0	14	10	0	16	0	12	0	58	0
0	223	0	33	0	32	0	15	12	0	10	0	17	0	72	0
0	224	0	31	0	32	0	12	9	0	15	0	9	0	72	0
0	225	0	34	0	36	0	13	9	0	9	0	21	0	38	0
0	226	0	32	0	36	0	8	6	0	16	0	10	0	78	0
0	227	0	31	0	32	0	14	10	0	19	0	11	0	54	0
0	228	0	33	0	34	0	14	9	0	12	0	12	0	63	0
0	229	0	34	0	33	0	11	9	0	8	0	23	0	66	0
0	230	0	34	0	35	0	12	9	0	11	0	13	0	70	0
0	231	0	34	0	30	0	13	6	0	14	0	12	0	71	0
0	232	0	33	0	38	0	10	10	0	9	0	16	0	67	0
0	233	0	32	0	34	0	16	6	0	15	0	9	0	58	0
0	234	0	41	0	33	0	18	14	0	13	0	17	0	72	0
0	235	0	34	0	32	0	13	10	0	16	0	9	0	72	0
0	236	0	36	0	31	0	11	10	0	11	0	14	0	70	0
0	237	0	37	0	30	0	4	6	0	12	0	17	0	76	0
0	238	0	36	0	27	0	13	12	0	13	0	13	0	50	0
0	239	0	29	0	31	0	16	12	0	10	0	11	0	72	0
0	240	0	37	0	30	0	10	7	0	11	0	12	0	72	0
0	241	0	27	0	32	0	12	8	0	12	0	10	0	88	0
0	242	0	35	0	35	0	12	11	0	8	0	19	0	53	0
0	243	0	28	0	28	0	10	3	0	12	0	16	0	58	0
0	244	0	35	0	33	0	13	6	0	12	0	16	0	66	0
0	245	0	37	0	31	0	15	10	0	15	0	14	0	82	0
0	246	0	29	0	35	0	12	8	0	11	0	20	0	69	0
0	247	0	32	0	35	0	14	9	0	13	0	15	0	68	0
0	248	0	36	0	32	0	10	9	0	14	0	23	0	44	0
0	249	0	19	0	21	0	12	8	0	10	0	20	0	56	0
0	250	0	21	0	20	0	12	9	0	12	0	16	0	53	0
0	251	0	31	0	34	0	11	7	0	15	0	14	0	70	0
0	252	0	33	0	32	0	10	7	0	13	0	17	0	78	0
0	253	0	36	0	34	0	12	6	0	13	0	11	0	71	0
0	254	0	33	0	32	0	16	9	0	13	0	13	0	72	0
0	255	0	37	0	33	0	12	10	0	12	0	17	0	68	0
0	256	0	34	0	33	0	14	11	0	12	0	15	0	67	0
0	257	0	35	0	37	0	16	12	0	9	0	21	0	75	0
0	258	0	31	0	32	0	14	8	0	9	0	18	0	62	0
0	259	0	37	0	34	0	13	11	0	15	0	15	0	67	0
0	260	0	35	0	30	0	4	3	0	10	0	8	0	83	0
0	261	0	27	0	30	0	15	11	0	14	0	12	0	64	0
0	262	0	34	0	38	0	11	12	0	15	0	12	0	68	0
0	263	0	40	0	36	0	11	7	0	7	0	22	0	62	0
0	264	0	29	0	32	0	14	9	0	14	0	12	0	72	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time17 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 17 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185728&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]17 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185728&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185728&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time17 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 4.02213192467022 + 2.51220871915759Pop[t] -0.00416326360064588t + 0.000172174548079316Pop_t[t] -0.0555568413104843Connected[t] + 0.142876235895835Connected_p[t] + 0.157004790836635Separate[t] -0.171050529312447Separate_p[t] + 0.561688749040416Software[t] -0.0423405001257778Software_p[t] + 0.129559018015456Happiness[t] -0.0990921264717638Happiness_p[t] + 0.0223866216094669Depression[t] -0.105904658670812Depression_p[t] -0.00941064469108985Belonging[t] + 0.0247479684327579Belonging_p[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  4.02213192467022 +  2.51220871915759Pop[t] -0.00416326360064588t +  0.000172174548079316Pop_t[t] -0.0555568413104843Connected[t] +  0.142876235895835Connected_p[t] +  0.157004790836635Separate[t] -0.171050529312447Separate_p[t] +  0.561688749040416Software[t] -0.0423405001257778Software_p[t] +  0.129559018015456Happiness[t] -0.0990921264717638Happiness_p[t] +  0.0223866216094669Depression[t] -0.105904658670812Depression_p[t] -0.00941064469108985Belonging[t] +  0.0247479684327579Belonging_p[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185728&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  4.02213192467022 +  2.51220871915759Pop[t] -0.00416326360064588t +  0.000172174548079316Pop_t[t] -0.0555568413104843Connected[t] +  0.142876235895835Connected_p[t] +  0.157004790836635Separate[t] -0.171050529312447Separate_p[t] +  0.561688749040416Software[t] -0.0423405001257778Software_p[t] +  0.129559018015456Happiness[t] -0.0990921264717638Happiness_p[t] +  0.0223866216094669Depression[t] -0.105904658670812Depression_p[t] -0.00941064469108985Belonging[t] +  0.0247479684327579Belonging_p[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185728&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185728&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[t] = + 4.02213192467022 + 2.51220871915759Pop[t] -0.00416326360064588t + 0.000172174548079316Pop_t[t] -0.0555568413104843Connected[t] + 0.142876235895835Connected_p[t] + 0.157004790836635Separate[t] -0.171050529312447Separate_p[t] + 0.561688749040416Software[t] -0.0423405001257778Software_p[t] + 0.129559018015456Happiness[t] -0.0990921264717638Happiness_p[t] + 0.0223866216094669Depression[t] -0.105904658670812Depression_p[t] -0.00941064469108985Belonging[t] + 0.0247479684327579Belonging_p[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.022131924670223.3275781.20870.2279190.11396
Pop2.512208719157594.2401550.59250.5540690.277034
t-0.004163263600645880.006372-0.65340.5141130.257057
Pop_t0.0001721745480793160.0071810.0240.9808910.490446
Connected-0.05555684131048430.052264-1.0630.2888130.144406
Connected_p0.1428762358958350.070032.04020.0423880.021194
Separate0.1570047908366350.0597982.62560.0091870.004594
Separate_p-0.1710505293124470.074474-2.29680.0224650.011232
Software0.5616887490404160.0822326.830600
Software_p-0.04234050012577780.109405-0.3870.6990840.349542
Happiness0.1295590180154560.0893821.44950.1484620.074231
Happiness_p-0.09909212647176380.117868-0.84070.4013220.200661
Depression0.02238662160946690.0622070.35990.7192470.359624
Depression_p-0.1059046586708120.084312-1.25610.2102580.105129
Belonging-0.009410644691089850.019054-0.49390.6218160.310908
Belonging_p0.02474796843275790.0246211.00520.3158010.1579

\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) & 4.02213192467022 & 3.327578 & 1.2087 & 0.227919 & 0.11396 \tabularnewline
Pop & 2.51220871915759 & 4.240155 & 0.5925 & 0.554069 & 0.277034 \tabularnewline
t & -0.00416326360064588 & 0.006372 & -0.6534 & 0.514113 & 0.257057 \tabularnewline
Pop_t & 0.000172174548079316 & 0.007181 & 0.024 & 0.980891 & 0.490446 \tabularnewline
Connected & -0.0555568413104843 & 0.052264 & -1.063 & 0.288813 & 0.144406 \tabularnewline
Connected_p & 0.142876235895835 & 0.07003 & 2.0402 & 0.042388 & 0.021194 \tabularnewline
Separate & 0.157004790836635 & 0.059798 & 2.6256 & 0.009187 & 0.004594 \tabularnewline
Separate_p & -0.171050529312447 & 0.074474 & -2.2968 & 0.022465 & 0.011232 \tabularnewline
Software & 0.561688749040416 & 0.082232 & 6.8306 & 0 & 0 \tabularnewline
Software_p & -0.0423405001257778 & 0.109405 & -0.387 & 0.699084 & 0.349542 \tabularnewline
Happiness & 0.129559018015456 & 0.089382 & 1.4495 & 0.148462 & 0.074231 \tabularnewline
Happiness_p & -0.0990921264717638 & 0.117868 & -0.8407 & 0.401322 & 0.200661 \tabularnewline
Depression & 0.0223866216094669 & 0.062207 & 0.3599 & 0.719247 & 0.359624 \tabularnewline
Depression_p & -0.105904658670812 & 0.084312 & -1.2561 & 0.210258 & 0.105129 \tabularnewline
Belonging & -0.00941064469108985 & 0.019054 & -0.4939 & 0.621816 & 0.310908 \tabularnewline
Belonging_p & 0.0247479684327579 & 0.024621 & 1.0052 & 0.315801 & 0.1579 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185728&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]4.02213192467022[/C][C]3.327578[/C][C]1.2087[/C][C]0.227919[/C][C]0.11396[/C][/ROW]
[ROW][C]Pop[/C][C]2.51220871915759[/C][C]4.240155[/C][C]0.5925[/C][C]0.554069[/C][C]0.277034[/C][/ROW]
[ROW][C]t[/C][C]-0.00416326360064588[/C][C]0.006372[/C][C]-0.6534[/C][C]0.514113[/C][C]0.257057[/C][/ROW]
[ROW][C]Pop_t[/C][C]0.000172174548079316[/C][C]0.007181[/C][C]0.024[/C][C]0.980891[/C][C]0.490446[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0555568413104843[/C][C]0.052264[/C][C]-1.063[/C][C]0.288813[/C][C]0.144406[/C][/ROW]
[ROW][C]Connected_p[/C][C]0.142876235895835[/C][C]0.07003[/C][C]2.0402[/C][C]0.042388[/C][C]0.021194[/C][/ROW]
[ROW][C]Separate[/C][C]0.157004790836635[/C][C]0.059798[/C][C]2.6256[/C][C]0.009187[/C][C]0.004594[/C][/ROW]
[ROW][C]Separate_p[/C][C]-0.171050529312447[/C][C]0.074474[/C][C]-2.2968[/C][C]0.022465[/C][C]0.011232[/C][/ROW]
[ROW][C]Software[/C][C]0.561688749040416[/C][C]0.082232[/C][C]6.8306[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Software_p[/C][C]-0.0423405001257778[/C][C]0.109405[/C][C]-0.387[/C][C]0.699084[/C][C]0.349542[/C][/ROW]
[ROW][C]Happiness[/C][C]0.129559018015456[/C][C]0.089382[/C][C]1.4495[/C][C]0.148462[/C][C]0.074231[/C][/ROW]
[ROW][C]Happiness_p[/C][C]-0.0990921264717638[/C][C]0.117868[/C][C]-0.8407[/C][C]0.401322[/C][C]0.200661[/C][/ROW]
[ROW][C]Depression[/C][C]0.0223866216094669[/C][C]0.062207[/C][C]0.3599[/C][C]0.719247[/C][C]0.359624[/C][/ROW]
[ROW][C]Depression_p[/C][C]-0.105904658670812[/C][C]0.084312[/C][C]-1.2561[/C][C]0.210258[/C][C]0.105129[/C][/ROW]
[ROW][C]Belonging[/C][C]-0.00941064469108985[/C][C]0.019054[/C][C]-0.4939[/C][C]0.621816[/C][C]0.310908[/C][/ROW]
[ROW][C]Belonging_p[/C][C]0.0247479684327579[/C][C]0.024621[/C][C]1.0052[/C][C]0.315801[/C][C]0.1579[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185728&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185728&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.022131924670223.3275781.20870.2279190.11396
Pop2.512208719157594.2401550.59250.5540690.277034
t-0.004163263600645880.006372-0.65340.5141130.257057
Pop_t0.0001721745480793160.0071810.0240.9808910.490446
Connected-0.05555684131048430.052264-1.0630.2888130.144406
Connected_p0.1428762358958350.070032.04020.0423880.021194
Separate0.1570047908366350.0597982.62560.0091870.004594
Separate_p-0.1710505293124470.074474-2.29680.0224650.011232
Software0.5616887490404160.0822326.830600
Software_p-0.04234050012577780.109405-0.3870.6990840.349542
Happiness0.1295590180154560.0893821.44950.1484620.074231
Happiness_p-0.09909212647176380.117868-0.84070.4013220.200661
Depression0.02238662160946690.0622070.35990.7192470.359624
Depression_p-0.1059046586708120.084312-1.25610.2102580.105129
Belonging-0.009410644691089850.019054-0.49390.6218160.310908
Belonging_p0.02474796843275790.0246211.00520.3158010.1579







Multiple Linear Regression - Regression Statistics
Multiple R0.683693459674527
R-squared0.467436746801725
Adjusted R-squared0.435225259713119
F-TEST (value)14.5114922982577
F-TEST (DF numerator)15
F-TEST (DF denominator)248
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.8457000801965
Sum Squared Residuals844.838978937264

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.683693459674527 \tabularnewline
R-squared & 0.467436746801725 \tabularnewline
Adjusted R-squared & 0.435225259713119 \tabularnewline
F-TEST (value) & 14.5114922982577 \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 & 1.8457000801965 \tabularnewline
Sum Squared Residuals & 844.838978937264 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185728&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.683693459674527[/C][/ROW]
[ROW][C]R-squared[/C][C]0.467436746801725[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.435225259713119[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]14.5114922982577[/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]1.8457000801965[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]844.838978937264[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185728&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185728&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.683693459674527
R-squared0.467436746801725
Adjusted R-squared0.435225259713119
F-TEST (value)14.5114922982577
F-TEST (DF numerator)15
F-TEST (DF denominator)248
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.8457000801965
Sum Squared Residuals844.838978937264







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.0460838528533-3.04608385285332
21616.0978854720565-0.0978854720564726
31916.61871875636862.38128124363138
41512.26884458802932.73115541197066
51415.6143076175297-1.61430761752971
61315.0952278482479-2.09522784824791
71915.11063832808453.88936167191553
81516.9713242202552-1.9713242202552
91416.1392821471749-2.13928214717491
101514.40254902683560.597450973164367
111615.46104561611020.53895438388983
121616.1235117839571-0.123511783957114
131615.62067067091850.379329329081526
141615.2094476897910.790552310209006
151717.6741165821685-0.674116582168502
161515.1802222027614-0.180222202761399
171514.76159243630510.238407563694873
182016.42800219785453.57199780214554
191815.61600384710282.38399615289716
201615.3074180814340.692581918565993
211615.26131583146810.738684168531906
221615.15902031359790.840979686402121
231916.31832667718252.68167332281752
241614.88965935292741.11034064707262
251716.54098375244340.459016247556616
261717.0622567007993-0.0622567007993018
271615.00636954836510.993630451634888
281516.287354596739-1.28735459673898
291615.55287080604040.447129193959563
301414.3904425234722-0.390442523472173
311515.87707304005-0.877073040049984
321212.4410863242391-0.441086324239132
331415.163223672435-1.16322367243501
341615.90662985509370.0933701449062521
351415.6500827322888-1.65008273228881
361013.265086391234-3.26508639123402
371012.727741817731-2.72774181773097
381415.8385839962544-1.8385839962544
391614.51740860014511.48259139985485
401614.78001356928661.21998643071339
411615.18584544673760.814154553262369
421415.5727609632611-1.57276096326111
432017.66916236156272.33083763843728
441414.1387756696789-0.138775669678917
451415.0696607461849-1.06966074618494
461115.6144856270065-4.61448562700648
471416.5709069707458-2.57090697074579
481515.1481882666103-0.148188266610253
491615.06149671851080.938503281489179
501416.0633090042108-2.06330900421075
511616.6187303550879-0.6187303550879
521414.1780196281422-0.178019628142177
531214.6837657036483-2.68376570364832
541615.65273467634940.347265323650568
55911.6694846725896-2.66948467258964
561412.57777434350911.42222565649092
571616.0036265752432-0.00362657524322887
581615.32268553084720.677314469152829
591515.3869151033687-0.38691510336873
601614.25342629665071.74657370334928
611211.53887566369250.46112433630749
621615.93448106905030.0655189309496813
631616.5909413491474-0.590941349147434
641414.2618668653366-0.261866865336581
651615.24002473894630.759975261053671
661716.17189889622650.828101103773527
671816.11730306441781.88269693558221
681814.69913511195783.3008648880422
691215.6722816230555-3.67228162305551
701615.36965607647760.630343923522355
711013.5866524120327-3.5866524120327
721414.195891330998-0.195891330997985
731816.54853435757361.45146564242639
741816.93223559619481.06776440380516
751615.82251880560930.177481194390736
761713.8949822443113.10501775568903
771616.1954946350854-0.195494635085416
781614.50384625714061.49615374285942
791315.0129915707567-2.01299157075666
801615.77143790597510.228562094024869
811615.56908839480520.430911605194758
821615.77002784063690.229972159363091
831515.8074459225013-0.807445922501287
841514.78765965784620.212340342153843
851614.3564786199951.64352138000496
861414.1571625912084-0.157162591208444
871615.30587517141970.69412482858025
881614.46961712212471.53038287787534
891514.27882744411280.7211725558872
901213.6023588239322-1.60235882393221
911716.62692436380830.373075636191673
921615.43188579041260.568114209587381
931515.2277147708315-0.227714770831527
941315.0813275746976-2.08132757469762
951615.04423723303750.955762766962505
961615.72952952739410.270470472605888
971614.14624948948471.85375051051533
981615.97021736677540.0297826332246424
991414.4087389652808-0.408738965280757
1001617.0669910224862-1.06699102248623
1011614.73222687926871.26777312073132
1022017.33020551365792.66979448634215
1031514.66572992513880.334270074861162
1041614.49821769694741.50178230305259
1051315.1210647666331-2.12106476663309
1061715.90440880021231.09559119978767
1071615.58144924545380.418550754546195
1081614.34814496419761.65185503580237
1091211.90531554876780.0946844512321832
1101615.06094993674240.939050063257641
1111615.82292431418580.177075685814231
1121714.84557042888432.15442957111575
1131313.8834738038531-0.883473803853097
1141214.737925679879-2.73792567987902
1151816.5795463429741.42045365702602
1161415.2281114767074-1.22811147670737
1171412.997601783371.00239821663001
1181314.8993115345838-1.89931153458377
1191615.65819550510370.34180449489626
1201314.0711360179465-1.07113601794654
1211615.55353296477610.446467035223899
1221315.953286738566-2.95328673856601
1231616.9658873937755-0.96588739377553
1241516.1569827481446-1.15698274814463
1251616.7580898664056-0.758089866405581
1261515.4110906664556-0.411090666455593
1271715.85229137592431.14770862407565
1281513.97600467624881.0239953237512
1291214.8005465356512-2.80054653565118
1301614.10601398122161.89398601877844
1311013.3359227827828-3.33592278278283
1321613.93818327066542.06181672933456
1331213.8537668978712-1.85376689787118
1341415.5185421206393-1.5185421206393
1351515.2365070835217-0.236507083521652
1361312.04406001145220.95593998854782
1371514.40118610941360.598813890586378
1381113.1320965306762-2.13209653067624
1391213.2328826440951-1.23288264409513
1401113.3171512856996-2.3171512856996
1411612.89308708187863.10691291812139
1421513.34818269269091.6518173073091
1431716.62514951259640.374850487403569
1441614.69206466204911.30793533795091
1451014.1015702832193-4.10157028321932
1461815.76904499025742.23095500974264
1471314.9873219097027-1.98732190970275
1481615.13184475647920.868155243520752
1491313.0275017473578-0.0275017473578296
1501013.1303945600366-3.13039456003663
1511516.0188472173771-1.01884721737711
1521613.86170861869592.13829138130414
1531612.01586208539183.98413791460821
1541412.66071546501811.33928453498189
1551012.6056861353774-2.60568613537736
1561716.36750357539150.632496424608499
1571311.61391676011681.38608323988322
1581513.85627200467181.14372799532819
1591615.06472645802270.93527354197734
1601212.4616481771048-0.461648177104799
1611312.62783046371590.372169536284077
1621312.7584271073090.241572892690999
1631211.56186916598640.438130834013608
1641716.02200116430790.977998835692081
1651514.20731811040660.792681889593419
1661012.6331863748026-2.63318637480264
1671414.3683314267263-0.36833142672632
1681113.7153437366673-2.71534373666733
1691314.8885990551029-1.88859905510291
1701615.24579793527780.754202064722239
1711210.2854991539591.71450084604099
1721615.51946387742460.480536122575411
1731212.8367523332627-0.836752333262689
174911.0531284391401-2.05312843914013
1751214.1163175907024-2.11631759070241
1761514.3370390705290.662960929471049
1771211.78859249769670.211407502303293
1781212.6880411523742-0.688041152374177
1791413.70497897590840.295021024091634
1801213.0681347026367-1.06813470263668
1811615.21287666098140.78712333901862
1821110.65543835721040.344561642789644
1831917.14638929041181.85361070958822
1841514.19419064063410.805809359365868
185814.6477265300753-6.64772653007527
1861615.25678747987640.743212520123609
1871714.19114571967042.80885428032958
1881211.26498995727910.73501004272089
1891111.4971440575779-0.497144057577875
1901111.2351280597453-0.235128059745265
1911415.2001378944469-1.20013789444686
1921615.46397608197750.536023918022509
193129.936877583228892.06312241677111
1941614.45759801375191.54240198624807
1951313.6527489527911-0.652748952791145
1961515.0215787178556-0.0215787178555945
1971612.73111478028613.26888521971392
1981615.24477170617040.755228293829609
1991412.47498152772431.52501847227566
2001614.76009329963581.23990670036417
2011613.86628866102472.13371133897526
2021413.73750994725160.262490052748435
2031112.9533618586172-1.9533618586172
2041214.5378169642539-2.5378169642539
2051512.67903169423822.32096830576176
2061514.64433937195840.355660628041621
2071614.4861613266571.51383867334303
2081615.52351119692540.476488803074615
2091113.2889439413281-2.28894394132807
2101513.60804914550061.39195085449943
2111214.1204962557417-2.12049625574169
2121216.0388683048002-4.03886830480023
2131514.66868323688610.331316763113927
2141511.82532690439463.17467309560537
2151614.59318204365951.40681795634046
2161412.73200213779121.26799786220876
2171714.60792322403512.39207677596489
2181413.20425622963980.79574377036021
2191312.05393707393230.946062926067691
2201515.4547445845594-0.454744584559436
2211314.0575639701152-1.05756397011525
2221414.0515537515291-0.0515537515291178
2231514.02336300349450.976636996505471
2241212.9139492925951-0.913949292595147
2251313.1823819391275-0.182381939127509
226811.888500611787-3.88850061178705
2271414.195549170554-0.195549170554001
2281412.86337075024671.13662924975329
2291112.346430686068-1.34643068606798
2301212.7834452633279-0.783445263327946
2311310.66607158616872.33392841383131
2321013.6996524618582-3.69965246185822
2331611.58161543910614.41838456089387
2341815.20217171636742.79782828363262
2351313.3927306361125-0.392730636112462
2361112.6034082064064-1.60340820640645
237410.2801833291943-6.28018332919433
2381313.5153843221827-0.515384322182692
2391613.88765363063272.1123463693673
2401010.6255327401344-0.625532740134383
2411211.98685168009140.0131483199086499
2421213.7069303922495-1.7069303922495
243108.903144473420451.09685552657955
2441310.90488836442212.09511163557788
2451512.91569032845892.0843096715411
2461212.599045499187-0.599045499186976
2471413.146496033370.85350396663004
2481012.9835984954948-2.98359849549482
2491210.93683641274571.06316358725429
2501211.42404690839420.575953091605809
2511112.1229276563997-1.12292765639966
2521011.4263977997735-1.42639779977355
2531210.93943962805511.06056037194487
2541612.50836615236183.49163384763824
2551212.998299110583-0.998299110582997
2561413.68713252142640.312867478573624
2571614.48747784698391.51252215301608
2581411.72894151443612.27105848556386
2591314.053654051576-1.05365405157599
26048.08400355852546-4.08400355852546
2611513.80438982536241.19561017463759
2621115.320972187573-4.32097218757297
2631111.1048724893516-0.104872489351625
2641412.79613327800321.20386672199677

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.0460838528533 & -3.04608385285332 \tabularnewline
2 & 16 & 16.0978854720565 & -0.0978854720564726 \tabularnewline
3 & 19 & 16.6187187563686 & 2.38128124363138 \tabularnewline
4 & 15 & 12.2688445880293 & 2.73115541197066 \tabularnewline
5 & 14 & 15.6143076175297 & -1.61430761752971 \tabularnewline
6 & 13 & 15.0952278482479 & -2.09522784824791 \tabularnewline
7 & 19 & 15.1106383280845 & 3.88936167191553 \tabularnewline
8 & 15 & 16.9713242202552 & -1.9713242202552 \tabularnewline
9 & 14 & 16.1392821471749 & -2.13928214717491 \tabularnewline
10 & 15 & 14.4025490268356 & 0.597450973164367 \tabularnewline
11 & 16 & 15.4610456161102 & 0.53895438388983 \tabularnewline
12 & 16 & 16.1235117839571 & -0.123511783957114 \tabularnewline
13 & 16 & 15.6206706709185 & 0.379329329081526 \tabularnewline
14 & 16 & 15.209447689791 & 0.790552310209006 \tabularnewline
15 & 17 & 17.6741165821685 & -0.674116582168502 \tabularnewline
16 & 15 & 15.1802222027614 & -0.180222202761399 \tabularnewline
17 & 15 & 14.7615924363051 & 0.238407563694873 \tabularnewline
18 & 20 & 16.4280021978545 & 3.57199780214554 \tabularnewline
19 & 18 & 15.6160038471028 & 2.38399615289716 \tabularnewline
20 & 16 & 15.307418081434 & 0.692581918565993 \tabularnewline
21 & 16 & 15.2613158314681 & 0.738684168531906 \tabularnewline
22 & 16 & 15.1590203135979 & 0.840979686402121 \tabularnewline
23 & 19 & 16.3183266771825 & 2.68167332281752 \tabularnewline
24 & 16 & 14.8896593529274 & 1.11034064707262 \tabularnewline
25 & 17 & 16.5409837524434 & 0.459016247556616 \tabularnewline
26 & 17 & 17.0622567007993 & -0.0622567007993018 \tabularnewline
27 & 16 & 15.0063695483651 & 0.993630451634888 \tabularnewline
28 & 15 & 16.287354596739 & -1.28735459673898 \tabularnewline
29 & 16 & 15.5528708060404 & 0.447129193959563 \tabularnewline
30 & 14 & 14.3904425234722 & -0.390442523472173 \tabularnewline
31 & 15 & 15.87707304005 & -0.877073040049984 \tabularnewline
32 & 12 & 12.4410863242391 & -0.441086324239132 \tabularnewline
33 & 14 & 15.163223672435 & -1.16322367243501 \tabularnewline
34 & 16 & 15.9066298550937 & 0.0933701449062521 \tabularnewline
35 & 14 & 15.6500827322888 & -1.65008273228881 \tabularnewline
36 & 10 & 13.265086391234 & -3.26508639123402 \tabularnewline
37 & 10 & 12.727741817731 & -2.72774181773097 \tabularnewline
38 & 14 & 15.8385839962544 & -1.8385839962544 \tabularnewline
39 & 16 & 14.5174086001451 & 1.48259139985485 \tabularnewline
40 & 16 & 14.7800135692866 & 1.21998643071339 \tabularnewline
41 & 16 & 15.1858454467376 & 0.814154553262369 \tabularnewline
42 & 14 & 15.5727609632611 & -1.57276096326111 \tabularnewline
43 & 20 & 17.6691623615627 & 2.33083763843728 \tabularnewline
44 & 14 & 14.1387756696789 & -0.138775669678917 \tabularnewline
45 & 14 & 15.0696607461849 & -1.06966074618494 \tabularnewline
46 & 11 & 15.6144856270065 & -4.61448562700648 \tabularnewline
47 & 14 & 16.5709069707458 & -2.57090697074579 \tabularnewline
48 & 15 & 15.1481882666103 & -0.148188266610253 \tabularnewline
49 & 16 & 15.0614967185108 & 0.938503281489179 \tabularnewline
50 & 14 & 16.0633090042108 & -2.06330900421075 \tabularnewline
51 & 16 & 16.6187303550879 & -0.6187303550879 \tabularnewline
52 & 14 & 14.1780196281422 & -0.178019628142177 \tabularnewline
53 & 12 & 14.6837657036483 & -2.68376570364832 \tabularnewline
54 & 16 & 15.6527346763494 & 0.347265323650568 \tabularnewline
55 & 9 & 11.6694846725896 & -2.66948467258964 \tabularnewline
56 & 14 & 12.5777743435091 & 1.42222565649092 \tabularnewline
57 & 16 & 16.0036265752432 & -0.00362657524322887 \tabularnewline
58 & 16 & 15.3226855308472 & 0.677314469152829 \tabularnewline
59 & 15 & 15.3869151033687 & -0.38691510336873 \tabularnewline
60 & 16 & 14.2534262966507 & 1.74657370334928 \tabularnewline
61 & 12 & 11.5388756636925 & 0.46112433630749 \tabularnewline
62 & 16 & 15.9344810690503 & 0.0655189309496813 \tabularnewline
63 & 16 & 16.5909413491474 & -0.590941349147434 \tabularnewline
64 & 14 & 14.2618668653366 & -0.261866865336581 \tabularnewline
65 & 16 & 15.2400247389463 & 0.759975261053671 \tabularnewline
66 & 17 & 16.1718988962265 & 0.828101103773527 \tabularnewline
67 & 18 & 16.1173030644178 & 1.88269693558221 \tabularnewline
68 & 18 & 14.6991351119578 & 3.3008648880422 \tabularnewline
69 & 12 & 15.6722816230555 & -3.67228162305551 \tabularnewline
70 & 16 & 15.3696560764776 & 0.630343923522355 \tabularnewline
71 & 10 & 13.5866524120327 & -3.5866524120327 \tabularnewline
72 & 14 & 14.195891330998 & -0.195891330997985 \tabularnewline
73 & 18 & 16.5485343575736 & 1.45146564242639 \tabularnewline
74 & 18 & 16.9322355961948 & 1.06776440380516 \tabularnewline
75 & 16 & 15.8225188056093 & 0.177481194390736 \tabularnewline
76 & 17 & 13.894982244311 & 3.10501775568903 \tabularnewline
77 & 16 & 16.1954946350854 & -0.195494635085416 \tabularnewline
78 & 16 & 14.5038462571406 & 1.49615374285942 \tabularnewline
79 & 13 & 15.0129915707567 & -2.01299157075666 \tabularnewline
80 & 16 & 15.7714379059751 & 0.228562094024869 \tabularnewline
81 & 16 & 15.5690883948052 & 0.430911605194758 \tabularnewline
82 & 16 & 15.7700278406369 & 0.229972159363091 \tabularnewline
83 & 15 & 15.8074459225013 & -0.807445922501287 \tabularnewline
84 & 15 & 14.7876596578462 & 0.212340342153843 \tabularnewline
85 & 16 & 14.356478619995 & 1.64352138000496 \tabularnewline
86 & 14 & 14.1571625912084 & -0.157162591208444 \tabularnewline
87 & 16 & 15.3058751714197 & 0.69412482858025 \tabularnewline
88 & 16 & 14.4696171221247 & 1.53038287787534 \tabularnewline
89 & 15 & 14.2788274441128 & 0.7211725558872 \tabularnewline
90 & 12 & 13.6023588239322 & -1.60235882393221 \tabularnewline
91 & 17 & 16.6269243638083 & 0.373075636191673 \tabularnewline
92 & 16 & 15.4318857904126 & 0.568114209587381 \tabularnewline
93 & 15 & 15.2277147708315 & -0.227714770831527 \tabularnewline
94 & 13 & 15.0813275746976 & -2.08132757469762 \tabularnewline
95 & 16 & 15.0442372330375 & 0.955762766962505 \tabularnewline
96 & 16 & 15.7295295273941 & 0.270470472605888 \tabularnewline
97 & 16 & 14.1462494894847 & 1.85375051051533 \tabularnewline
98 & 16 & 15.9702173667754 & 0.0297826332246424 \tabularnewline
99 & 14 & 14.4087389652808 & -0.408738965280757 \tabularnewline
100 & 16 & 17.0669910224862 & -1.06699102248623 \tabularnewline
101 & 16 & 14.7322268792687 & 1.26777312073132 \tabularnewline
102 & 20 & 17.3302055136579 & 2.66979448634215 \tabularnewline
103 & 15 & 14.6657299251388 & 0.334270074861162 \tabularnewline
104 & 16 & 14.4982176969474 & 1.50178230305259 \tabularnewline
105 & 13 & 15.1210647666331 & -2.12106476663309 \tabularnewline
106 & 17 & 15.9044088002123 & 1.09559119978767 \tabularnewline
107 & 16 & 15.5814492454538 & 0.418550754546195 \tabularnewline
108 & 16 & 14.3481449641976 & 1.65185503580237 \tabularnewline
109 & 12 & 11.9053155487678 & 0.0946844512321832 \tabularnewline
110 & 16 & 15.0609499367424 & 0.939050063257641 \tabularnewline
111 & 16 & 15.8229243141858 & 0.177075685814231 \tabularnewline
112 & 17 & 14.8455704288843 & 2.15442957111575 \tabularnewline
113 & 13 & 13.8834738038531 & -0.883473803853097 \tabularnewline
114 & 12 & 14.737925679879 & -2.73792567987902 \tabularnewline
115 & 18 & 16.579546342974 & 1.42045365702602 \tabularnewline
116 & 14 & 15.2281114767074 & -1.22811147670737 \tabularnewline
117 & 14 & 12.99760178337 & 1.00239821663001 \tabularnewline
118 & 13 & 14.8993115345838 & -1.89931153458377 \tabularnewline
119 & 16 & 15.6581955051037 & 0.34180449489626 \tabularnewline
120 & 13 & 14.0711360179465 & -1.07113601794654 \tabularnewline
121 & 16 & 15.5535329647761 & 0.446467035223899 \tabularnewline
122 & 13 & 15.953286738566 & -2.95328673856601 \tabularnewline
123 & 16 & 16.9658873937755 & -0.96588739377553 \tabularnewline
124 & 15 & 16.1569827481446 & -1.15698274814463 \tabularnewline
125 & 16 & 16.7580898664056 & -0.758089866405581 \tabularnewline
126 & 15 & 15.4110906664556 & -0.411090666455593 \tabularnewline
127 & 17 & 15.8522913759243 & 1.14770862407565 \tabularnewline
128 & 15 & 13.9760046762488 & 1.0239953237512 \tabularnewline
129 & 12 & 14.8005465356512 & -2.80054653565118 \tabularnewline
130 & 16 & 14.1060139812216 & 1.89398601877844 \tabularnewline
131 & 10 & 13.3359227827828 & -3.33592278278283 \tabularnewline
132 & 16 & 13.9381832706654 & 2.06181672933456 \tabularnewline
133 & 12 & 13.8537668978712 & -1.85376689787118 \tabularnewline
134 & 14 & 15.5185421206393 & -1.5185421206393 \tabularnewline
135 & 15 & 15.2365070835217 & -0.236507083521652 \tabularnewline
136 & 13 & 12.0440600114522 & 0.95593998854782 \tabularnewline
137 & 15 & 14.4011861094136 & 0.598813890586378 \tabularnewline
138 & 11 & 13.1320965306762 & -2.13209653067624 \tabularnewline
139 & 12 & 13.2328826440951 & -1.23288264409513 \tabularnewline
140 & 11 & 13.3171512856996 & -2.3171512856996 \tabularnewline
141 & 16 & 12.8930870818786 & 3.10691291812139 \tabularnewline
142 & 15 & 13.3481826926909 & 1.6518173073091 \tabularnewline
143 & 17 & 16.6251495125964 & 0.374850487403569 \tabularnewline
144 & 16 & 14.6920646620491 & 1.30793533795091 \tabularnewline
145 & 10 & 14.1015702832193 & -4.10157028321932 \tabularnewline
146 & 18 & 15.7690449902574 & 2.23095500974264 \tabularnewline
147 & 13 & 14.9873219097027 & -1.98732190970275 \tabularnewline
148 & 16 & 15.1318447564792 & 0.868155243520752 \tabularnewline
149 & 13 & 13.0275017473578 & -0.0275017473578296 \tabularnewline
150 & 10 & 13.1303945600366 & -3.13039456003663 \tabularnewline
151 & 15 & 16.0188472173771 & -1.01884721737711 \tabularnewline
152 & 16 & 13.8617086186959 & 2.13829138130414 \tabularnewline
153 & 16 & 12.0158620853918 & 3.98413791460821 \tabularnewline
154 & 14 & 12.6607154650181 & 1.33928453498189 \tabularnewline
155 & 10 & 12.6056861353774 & -2.60568613537736 \tabularnewline
156 & 17 & 16.3675035753915 & 0.632496424608499 \tabularnewline
157 & 13 & 11.6139167601168 & 1.38608323988322 \tabularnewline
158 & 15 & 13.8562720046718 & 1.14372799532819 \tabularnewline
159 & 16 & 15.0647264580227 & 0.93527354197734 \tabularnewline
160 & 12 & 12.4616481771048 & -0.461648177104799 \tabularnewline
161 & 13 & 12.6278304637159 & 0.372169536284077 \tabularnewline
162 & 13 & 12.758427107309 & 0.241572892690999 \tabularnewline
163 & 12 & 11.5618691659864 & 0.438130834013608 \tabularnewline
164 & 17 & 16.0220011643079 & 0.977998835692081 \tabularnewline
165 & 15 & 14.2073181104066 & 0.792681889593419 \tabularnewline
166 & 10 & 12.6331863748026 & -2.63318637480264 \tabularnewline
167 & 14 & 14.3683314267263 & -0.36833142672632 \tabularnewline
168 & 11 & 13.7153437366673 & -2.71534373666733 \tabularnewline
169 & 13 & 14.8885990551029 & -1.88859905510291 \tabularnewline
170 & 16 & 15.2457979352778 & 0.754202064722239 \tabularnewline
171 & 12 & 10.285499153959 & 1.71450084604099 \tabularnewline
172 & 16 & 15.5194638774246 & 0.480536122575411 \tabularnewline
173 & 12 & 12.8367523332627 & -0.836752333262689 \tabularnewline
174 & 9 & 11.0531284391401 & -2.05312843914013 \tabularnewline
175 & 12 & 14.1163175907024 & -2.11631759070241 \tabularnewline
176 & 15 & 14.337039070529 & 0.662960929471049 \tabularnewline
177 & 12 & 11.7885924976967 & 0.211407502303293 \tabularnewline
178 & 12 & 12.6880411523742 & -0.688041152374177 \tabularnewline
179 & 14 & 13.7049789759084 & 0.295021024091634 \tabularnewline
180 & 12 & 13.0681347026367 & -1.06813470263668 \tabularnewline
181 & 16 & 15.2128766609814 & 0.78712333901862 \tabularnewline
182 & 11 & 10.6554383572104 & 0.344561642789644 \tabularnewline
183 & 19 & 17.1463892904118 & 1.85361070958822 \tabularnewline
184 & 15 & 14.1941906406341 & 0.805809359365868 \tabularnewline
185 & 8 & 14.6477265300753 & -6.64772653007527 \tabularnewline
186 & 16 & 15.2567874798764 & 0.743212520123609 \tabularnewline
187 & 17 & 14.1911457196704 & 2.80885428032958 \tabularnewline
188 & 12 & 11.2649899572791 & 0.73501004272089 \tabularnewline
189 & 11 & 11.4971440575779 & -0.497144057577875 \tabularnewline
190 & 11 & 11.2351280597453 & -0.235128059745265 \tabularnewline
191 & 14 & 15.2001378944469 & -1.20013789444686 \tabularnewline
192 & 16 & 15.4639760819775 & 0.536023918022509 \tabularnewline
193 & 12 & 9.93687758322889 & 2.06312241677111 \tabularnewline
194 & 16 & 14.4575980137519 & 1.54240198624807 \tabularnewline
195 & 13 & 13.6527489527911 & -0.652748952791145 \tabularnewline
196 & 15 & 15.0215787178556 & -0.0215787178555945 \tabularnewline
197 & 16 & 12.7311147802861 & 3.26888521971392 \tabularnewline
198 & 16 & 15.2447717061704 & 0.755228293829609 \tabularnewline
199 & 14 & 12.4749815277243 & 1.52501847227566 \tabularnewline
200 & 16 & 14.7600932996358 & 1.23990670036417 \tabularnewline
201 & 16 & 13.8662886610247 & 2.13371133897526 \tabularnewline
202 & 14 & 13.7375099472516 & 0.262490052748435 \tabularnewline
203 & 11 & 12.9533618586172 & -1.9533618586172 \tabularnewline
204 & 12 & 14.5378169642539 & -2.5378169642539 \tabularnewline
205 & 15 & 12.6790316942382 & 2.32096830576176 \tabularnewline
206 & 15 & 14.6443393719584 & 0.355660628041621 \tabularnewline
207 & 16 & 14.486161326657 & 1.51383867334303 \tabularnewline
208 & 16 & 15.5235111969254 & 0.476488803074615 \tabularnewline
209 & 11 & 13.2889439413281 & -2.28894394132807 \tabularnewline
210 & 15 & 13.6080491455006 & 1.39195085449943 \tabularnewline
211 & 12 & 14.1204962557417 & -2.12049625574169 \tabularnewline
212 & 12 & 16.0388683048002 & -4.03886830480023 \tabularnewline
213 & 15 & 14.6686832368861 & 0.331316763113927 \tabularnewline
214 & 15 & 11.8253269043946 & 3.17467309560537 \tabularnewline
215 & 16 & 14.5931820436595 & 1.40681795634046 \tabularnewline
216 & 14 & 12.7320021377912 & 1.26799786220876 \tabularnewline
217 & 17 & 14.6079232240351 & 2.39207677596489 \tabularnewline
218 & 14 & 13.2042562296398 & 0.79574377036021 \tabularnewline
219 & 13 & 12.0539370739323 & 0.946062926067691 \tabularnewline
220 & 15 & 15.4547445845594 & -0.454744584559436 \tabularnewline
221 & 13 & 14.0575639701152 & -1.05756397011525 \tabularnewline
222 & 14 & 14.0515537515291 & -0.0515537515291178 \tabularnewline
223 & 15 & 14.0233630034945 & 0.976636996505471 \tabularnewline
224 & 12 & 12.9139492925951 & -0.913949292595147 \tabularnewline
225 & 13 & 13.1823819391275 & -0.182381939127509 \tabularnewline
226 & 8 & 11.888500611787 & -3.88850061178705 \tabularnewline
227 & 14 & 14.195549170554 & -0.195549170554001 \tabularnewline
228 & 14 & 12.8633707502467 & 1.13662924975329 \tabularnewline
229 & 11 & 12.346430686068 & -1.34643068606798 \tabularnewline
230 & 12 & 12.7834452633279 & -0.783445263327946 \tabularnewline
231 & 13 & 10.6660715861687 & 2.33392841383131 \tabularnewline
232 & 10 & 13.6996524618582 & -3.69965246185822 \tabularnewline
233 & 16 & 11.5816154391061 & 4.41838456089387 \tabularnewline
234 & 18 & 15.2021717163674 & 2.79782828363262 \tabularnewline
235 & 13 & 13.3927306361125 & -0.392730636112462 \tabularnewline
236 & 11 & 12.6034082064064 & -1.60340820640645 \tabularnewline
237 & 4 & 10.2801833291943 & -6.28018332919433 \tabularnewline
238 & 13 & 13.5153843221827 & -0.515384322182692 \tabularnewline
239 & 16 & 13.8876536306327 & 2.1123463693673 \tabularnewline
240 & 10 & 10.6255327401344 & -0.625532740134383 \tabularnewline
241 & 12 & 11.9868516800914 & 0.0131483199086499 \tabularnewline
242 & 12 & 13.7069303922495 & -1.7069303922495 \tabularnewline
243 & 10 & 8.90314447342045 & 1.09685552657955 \tabularnewline
244 & 13 & 10.9048883644221 & 2.09511163557788 \tabularnewline
245 & 15 & 12.9156903284589 & 2.0843096715411 \tabularnewline
246 & 12 & 12.599045499187 & -0.599045499186976 \tabularnewline
247 & 14 & 13.14649603337 & 0.85350396663004 \tabularnewline
248 & 10 & 12.9835984954948 & -2.98359849549482 \tabularnewline
249 & 12 & 10.9368364127457 & 1.06316358725429 \tabularnewline
250 & 12 & 11.4240469083942 & 0.575953091605809 \tabularnewline
251 & 11 & 12.1229276563997 & -1.12292765639966 \tabularnewline
252 & 10 & 11.4263977997735 & -1.42639779977355 \tabularnewline
253 & 12 & 10.9394396280551 & 1.06056037194487 \tabularnewline
254 & 16 & 12.5083661523618 & 3.49163384763824 \tabularnewline
255 & 12 & 12.998299110583 & -0.998299110582997 \tabularnewline
256 & 14 & 13.6871325214264 & 0.312867478573624 \tabularnewline
257 & 16 & 14.4874778469839 & 1.51252215301608 \tabularnewline
258 & 14 & 11.7289415144361 & 2.27105848556386 \tabularnewline
259 & 13 & 14.053654051576 & -1.05365405157599 \tabularnewline
260 & 4 & 8.08400355852546 & -4.08400355852546 \tabularnewline
261 & 15 & 13.8043898253624 & 1.19561017463759 \tabularnewline
262 & 11 & 15.320972187573 & -4.32097218757297 \tabularnewline
263 & 11 & 11.1048724893516 & -0.104872489351625 \tabularnewline
264 & 14 & 12.7961332780032 & 1.20386672199677 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185728&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]16.0460838528533[/C][C]-3.04608385285332[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]16.0978854720565[/C][C]-0.0978854720564726[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.6187187563686[/C][C]2.38128124363138[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.2688445880293[/C][C]2.73115541197066[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]15.6143076175297[/C][C]-1.61430761752971[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]15.0952278482479[/C][C]-2.09522784824791[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.1106383280845[/C][C]3.88936167191553[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.9713242202552[/C][C]-1.9713242202552[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]16.1392821471749[/C][C]-2.13928214717491[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4025490268356[/C][C]0.597450973164367[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]15.4610456161102[/C][C]0.53895438388983[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1235117839571[/C][C]-0.123511783957114[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.6206706709185[/C][C]0.379329329081526[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.209447689791[/C][C]0.790552310209006[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.6741165821685[/C][C]-0.674116582168502[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.1802222027614[/C][C]-0.180222202761399[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.7615924363051[/C][C]0.238407563694873[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.4280021978545[/C][C]3.57199780214554[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.6160038471028[/C][C]2.38399615289716[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.307418081434[/C][C]0.692581918565993[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.2613158314681[/C][C]0.738684168531906[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.1590203135979[/C][C]0.840979686402121[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.3183266771825[/C][C]2.68167332281752[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.8896593529274[/C][C]1.11034064707262[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.5409837524434[/C][C]0.459016247556616[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]17.0622567007993[/C][C]-0.0622567007993018[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.0063695483651[/C][C]0.993630451634888[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.287354596739[/C][C]-1.28735459673898[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.5528708060404[/C][C]0.447129193959563[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.3904425234722[/C][C]-0.390442523472173[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.87707304005[/C][C]-0.877073040049984[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.4410863242391[/C][C]-0.441086324239132[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]15.163223672435[/C][C]-1.16322367243501[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.9066298550937[/C][C]0.0933701449062521[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.6500827322888[/C][C]-1.65008273228881[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]13.265086391234[/C][C]-3.26508639123402[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.727741817731[/C][C]-2.72774181773097[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.8385839962544[/C][C]-1.8385839962544[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.5174086001451[/C][C]1.48259139985485[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.7800135692866[/C][C]1.21998643071339[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]15.1858454467376[/C][C]0.814154553262369[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.5727609632611[/C][C]-1.57276096326111[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.6691623615627[/C][C]2.33083763843728[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.1387756696789[/C][C]-0.138775669678917[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]15.0696607461849[/C][C]-1.06966074618494[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.6144856270065[/C][C]-4.61448562700648[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.5709069707458[/C][C]-2.57090697074579[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.1481882666103[/C][C]-0.148188266610253[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.0614967185108[/C][C]0.938503281489179[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]16.0633090042108[/C][C]-2.06330900421075[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.6187303550879[/C][C]-0.6187303550879[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.1780196281422[/C][C]-0.178019628142177[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.6837657036483[/C][C]-2.68376570364832[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.6527346763494[/C][C]0.347265323650568[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.6694846725896[/C][C]-2.66948467258964[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.5777743435091[/C][C]1.42222565649092[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]16.0036265752432[/C][C]-0.00362657524322887[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.3226855308472[/C][C]0.677314469152829[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.3869151033687[/C][C]-0.38691510336873[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.2534262966507[/C][C]1.74657370334928[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.5388756636925[/C][C]0.46112433630749[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.9344810690503[/C][C]0.0655189309496813[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.5909413491474[/C][C]-0.590941349147434[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.2618668653366[/C][C]-0.261866865336581[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.2400247389463[/C][C]0.759975261053671[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.1718988962265[/C][C]0.828101103773527[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.1173030644178[/C][C]1.88269693558221[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.6991351119578[/C][C]3.3008648880422[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.6722816230555[/C][C]-3.67228162305551[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.3696560764776[/C][C]0.630343923522355[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.5866524120327[/C][C]-3.5866524120327[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.195891330998[/C][C]-0.195891330997985[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.5485343575736[/C][C]1.45146564242639[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]16.9322355961948[/C][C]1.06776440380516[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.8225188056093[/C][C]0.177481194390736[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.894982244311[/C][C]3.10501775568903[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.1954946350854[/C][C]-0.195494635085416[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.5038462571406[/C][C]1.49615374285942[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.0129915707567[/C][C]-2.01299157075666[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.7714379059751[/C][C]0.228562094024869[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.5690883948052[/C][C]0.430911605194758[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.7700278406369[/C][C]0.229972159363091[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.8074459225013[/C][C]-0.807445922501287[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.7876596578462[/C][C]0.212340342153843[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.356478619995[/C][C]1.64352138000496[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.1571625912084[/C][C]-0.157162591208444[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.3058751714197[/C][C]0.69412482858025[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.4696171221247[/C][C]1.53038287787534[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.2788274441128[/C][C]0.7211725558872[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.6023588239322[/C][C]-1.60235882393221[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.6269243638083[/C][C]0.373075636191673[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.4318857904126[/C][C]0.568114209587381[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.2277147708315[/C][C]-0.227714770831527[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]15.0813275746976[/C][C]-2.08132757469762[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]15.0442372330375[/C][C]0.955762766962505[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.7295295273941[/C][C]0.270470472605888[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]14.1462494894847[/C][C]1.85375051051533[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.9702173667754[/C][C]0.0297826332246424[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.4087389652808[/C][C]-0.408738965280757[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.0669910224862[/C][C]-1.06699102248623[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.7322268792687[/C][C]1.26777312073132[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.3302055136579[/C][C]2.66979448634215[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.6657299251388[/C][C]0.334270074861162[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.4982176969474[/C][C]1.50178230305259[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]15.1210647666331[/C][C]-2.12106476663309[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.9044088002123[/C][C]1.09559119978767[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.5814492454538[/C][C]0.418550754546195[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.3481449641976[/C][C]1.65185503580237[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]11.9053155487678[/C][C]0.0946844512321832[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.0609499367424[/C][C]0.939050063257641[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]15.8229243141858[/C][C]0.177075685814231[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]14.8455704288843[/C][C]2.15442957111575[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]13.8834738038531[/C][C]-0.883473803853097[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.737925679879[/C][C]-2.73792567987902[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.579546342974[/C][C]1.42045365702602[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.2281114767074[/C][C]-1.22811147670737[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]12.99760178337[/C][C]1.00239821663001[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.8993115345838[/C][C]-1.89931153458377[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.6581955051037[/C][C]0.34180449489626[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.0711360179465[/C][C]-1.07113601794654[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.5535329647761[/C][C]0.446467035223899[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.953286738566[/C][C]-2.95328673856601[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.9658873937755[/C][C]-0.96588739377553[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]16.1569827481446[/C][C]-1.15698274814463[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.7580898664056[/C][C]-0.758089866405581[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]15.4110906664556[/C][C]-0.411090666455593[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.8522913759243[/C][C]1.14770862407565[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.9760046762488[/C][C]1.0239953237512[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.8005465356512[/C][C]-2.80054653565118[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]14.1060139812216[/C][C]1.89398601877844[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.3359227827828[/C][C]-3.33592278278283[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.9381832706654[/C][C]2.06181672933456[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]13.8537668978712[/C][C]-1.85376689787118[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.5185421206393[/C][C]-1.5185421206393[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.2365070835217[/C][C]-0.236507083521652[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.0440600114522[/C][C]0.95593998854782[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.4011861094136[/C][C]0.598813890586378[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.1320965306762[/C][C]-2.13209653067624[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.2328826440951[/C][C]-1.23288264409513[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.3171512856996[/C][C]-2.3171512856996[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8930870818786[/C][C]3.10691291812139[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.3481826926909[/C][C]1.6518173073091[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.6251495125964[/C][C]0.374850487403569[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.6920646620491[/C][C]1.30793533795091[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]14.1015702832193[/C][C]-4.10157028321932[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.7690449902574[/C][C]2.23095500974264[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]14.9873219097027[/C][C]-1.98732190970275[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]15.1318447564792[/C][C]0.868155243520752[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]13.0275017473578[/C][C]-0.0275017473578296[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]13.1303945600366[/C][C]-3.13039456003663[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.0188472173771[/C][C]-1.01884721737711[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.8617086186959[/C][C]2.13829138130414[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]12.0158620853918[/C][C]3.98413791460821[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.6607154650181[/C][C]1.33928453498189[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.6056861353774[/C][C]-2.60568613537736[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.3675035753915[/C][C]0.632496424608499[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.6139167601168[/C][C]1.38608323988322[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.8562720046718[/C][C]1.14372799532819[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]15.0647264580227[/C][C]0.93527354197734[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.4616481771048[/C][C]-0.461648177104799[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6278304637159[/C][C]0.372169536284077[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.758427107309[/C][C]0.241572892690999[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]11.5618691659864[/C][C]0.438130834013608[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.0220011643079[/C][C]0.977998835692081[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]14.2073181104066[/C][C]0.792681889593419[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]12.6331863748026[/C][C]-2.63318637480264[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.3683314267263[/C][C]-0.36833142672632[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]13.7153437366673[/C][C]-2.71534373666733[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.8885990551029[/C][C]-1.88859905510291[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]15.2457979352778[/C][C]0.754202064722239[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.285499153959[/C][C]1.71450084604099[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.5194638774246[/C][C]0.480536122575411[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]12.8367523332627[/C][C]-0.836752333262689[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.0531284391401[/C][C]-2.05312843914013[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.1163175907024[/C][C]-2.11631759070241[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.337039070529[/C][C]0.662960929471049[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]11.7885924976967[/C][C]0.211407502303293[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6880411523742[/C][C]-0.688041152374177[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.7049789759084[/C][C]0.295021024091634[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.0681347026367[/C][C]-1.06813470263668[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.2128766609814[/C][C]0.78712333901862[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]10.6554383572104[/C][C]0.344561642789644[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]17.1463892904118[/C][C]1.85361070958822[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]14.1941906406341[/C][C]0.805809359365868[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.6477265300753[/C][C]-6.64772653007527[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]15.2567874798764[/C][C]0.743212520123609[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.1911457196704[/C][C]2.80885428032958[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]11.2649899572791[/C][C]0.73501004272089[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.4971440575779[/C][C]-0.497144057577875[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]11.2351280597453[/C][C]-0.235128059745265[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]15.2001378944469[/C][C]-1.20013789444686[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.4639760819775[/C][C]0.536023918022509[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.93687758322889[/C][C]2.06312241677111[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.4575980137519[/C][C]1.54240198624807[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.6527489527911[/C][C]-0.652748952791145[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.0215787178556[/C][C]-0.0215787178555945[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.7311147802861[/C][C]3.26888521971392[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.2447717061704[/C][C]0.755228293829609[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4749815277243[/C][C]1.52501847227566[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.7600932996358[/C][C]1.23990670036417[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]13.8662886610247[/C][C]2.13371133897526[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.7375099472516[/C][C]0.262490052748435[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]12.9533618586172[/C][C]-1.9533618586172[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.5378169642539[/C][C]-2.5378169642539[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.6790316942382[/C][C]2.32096830576176[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.6443393719584[/C][C]0.355660628041621[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.486161326657[/C][C]1.51383867334303[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]15.5235111969254[/C][C]0.476488803074615[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.2889439413281[/C][C]-2.28894394132807[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.6080491455006[/C][C]1.39195085449943[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.1204962557417[/C][C]-2.12049625574169[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]16.0388683048002[/C][C]-4.03886830480023[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.6686832368861[/C][C]0.331316763113927[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]11.8253269043946[/C][C]3.17467309560537[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.5931820436595[/C][C]1.40681795634046[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]12.7320021377912[/C][C]1.26799786220876[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.6079232240351[/C][C]2.39207677596489[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.2042562296398[/C][C]0.79574377036021[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]12.0539370739323[/C][C]0.946062926067691[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.4547445845594[/C][C]-0.454744584559436[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.0575639701152[/C][C]-1.05756397011525[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.0515537515291[/C][C]-0.0515537515291178[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.0233630034945[/C][C]0.976636996505471[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]12.9139492925951[/C][C]-0.913949292595147[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]13.1823819391275[/C][C]-0.182381939127509[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.888500611787[/C][C]-3.88850061178705[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]14.195549170554[/C][C]-0.195549170554001[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.8633707502467[/C][C]1.13662924975329[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.346430686068[/C][C]-1.34643068606798[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.7834452633279[/C][C]-0.783445263327946[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]10.6660715861687[/C][C]2.33392841383131[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.6996524618582[/C][C]-3.69965246185822[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.5816154391061[/C][C]4.41838456089387[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.2021717163674[/C][C]2.79782828363262[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.3927306361125[/C][C]-0.392730636112462[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.6034082064064[/C][C]-1.60340820640645[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.2801833291943[/C][C]-6.28018332919433[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.5153843221827[/C][C]-0.515384322182692[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]13.8876536306327[/C][C]2.1123463693673[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]10.6255327401344[/C][C]-0.625532740134383[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]11.9868516800914[/C][C]0.0131483199086499[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.7069303922495[/C][C]-1.7069303922495[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.90314447342045[/C][C]1.09685552657955[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]10.9048883644221[/C][C]2.09511163557788[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]12.9156903284589[/C][C]2.0843096715411[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]12.599045499187[/C][C]-0.599045499186976[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]13.14649603337[/C][C]0.85350396663004[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.9835984954948[/C][C]-2.98359849549482[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.9368364127457[/C][C]1.06316358725429[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.4240469083942[/C][C]0.575953091605809[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]12.1229276563997[/C][C]-1.12292765639966[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.4263977997735[/C][C]-1.42639779977355[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]10.9394396280551[/C][C]1.06056037194487[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.5083661523618[/C][C]3.49163384763824[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]12.998299110583[/C][C]-0.998299110582997[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.6871325214264[/C][C]0.312867478573624[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.4874778469839[/C][C]1.51252215301608[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.7289415144361[/C][C]2.27105848556386[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.053654051576[/C][C]-1.05365405157599[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]8.08400355852546[/C][C]-4.08400355852546[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.8043898253624[/C][C]1.19561017463759[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]15.320972187573[/C][C]-4.32097218757297[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.1048724893516[/C][C]-0.104872489351625[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.7961332780032[/C][C]1.20386672199677[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185728&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185728&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.0460838528533-3.04608385285332
21616.0978854720565-0.0978854720564726
31916.61871875636862.38128124363138
41512.26884458802932.73115541197066
51415.6143076175297-1.61430761752971
61315.0952278482479-2.09522784824791
71915.11063832808453.88936167191553
81516.9713242202552-1.9713242202552
91416.1392821471749-2.13928214717491
101514.40254902683560.597450973164367
111615.46104561611020.53895438388983
121616.1235117839571-0.123511783957114
131615.62067067091850.379329329081526
141615.2094476897910.790552310209006
151717.6741165821685-0.674116582168502
161515.1802222027614-0.180222202761399
171514.76159243630510.238407563694873
182016.42800219785453.57199780214554
191815.61600384710282.38399615289716
201615.3074180814340.692581918565993
211615.26131583146810.738684168531906
221615.15902031359790.840979686402121
231916.31832667718252.68167332281752
241614.88965935292741.11034064707262
251716.54098375244340.459016247556616
261717.0622567007993-0.0622567007993018
271615.00636954836510.993630451634888
281516.287354596739-1.28735459673898
291615.55287080604040.447129193959563
301414.3904425234722-0.390442523472173
311515.87707304005-0.877073040049984
321212.4410863242391-0.441086324239132
331415.163223672435-1.16322367243501
341615.90662985509370.0933701449062521
351415.6500827322888-1.65008273228881
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1521613.86170861869592.13829138130414
1531612.01586208539183.98413791460821
1541412.66071546501811.33928453498189
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1561716.36750357539150.632496424608499
1571311.61391676011681.38608323988322
1581513.85627200467181.14372799532819
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1601212.4616481771048-0.461648177104799
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1621312.7584271073090.241572892690999
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1651514.20731811040660.792681889593419
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1671414.3683314267263-0.36833142672632
1681113.7153437366673-2.71534373666733
1691314.8885990551029-1.88859905510291
1701615.24579793527780.754202064722239
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1751214.1163175907024-2.11631759070241
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1781212.6880411523742-0.688041152374177
1791413.70497897590840.295021024091634
1801213.0681347026367-1.06813470263668
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1841514.19419064063410.805809359365868
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1871714.19114571967042.80885428032958
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1911415.2001378944469-1.20013789444686
1921615.46397608197750.536023918022509
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1941614.45759801375191.54240198624807
1951313.6527489527911-0.652748952791145
1961515.0215787178556-0.0215787178555945
1971612.73111478028613.26888521971392
1981615.24477170617040.755228293829609
1991412.47498152772431.52501847227566
2001614.76009329963581.23990670036417
2011613.86628866102472.13371133897526
2021413.73750994725160.262490052748435
2031112.9533618586172-1.9533618586172
2041214.5378169642539-2.5378169642539
2051512.67903169423822.32096830576176
2061514.64433937195840.355660628041621
2071614.4861613266571.51383867334303
2081615.52351119692540.476488803074615
2091113.2889439413281-2.28894394132807
2101513.60804914550061.39195085449943
2111214.1204962557417-2.12049625574169
2121216.0388683048002-4.03886830480023
2131514.66868323688610.331316763113927
2141511.82532690439463.17467309560537
2151614.59318204365951.40681795634046
2161412.73200213779121.26799786220876
2171714.60792322403512.39207677596489
2181413.20425622963980.79574377036021
2191312.05393707393230.946062926067691
2201515.4547445845594-0.454744584559436
2211314.0575639701152-1.05756397011525
2221414.0515537515291-0.0515537515291178
2231514.02336300349450.976636996505471
2241212.9139492925951-0.913949292595147
2251313.1823819391275-0.182381939127509
226811.888500611787-3.88850061178705
2271414.195549170554-0.195549170554001
2281412.86337075024671.13662924975329
2291112.346430686068-1.34643068606798
2301212.7834452633279-0.783445263327946
2311310.66607158616872.33392841383131
2321013.6996524618582-3.69965246185822
2331611.58161543910614.41838456089387
2341815.20217171636742.79782828363262
2351313.3927306361125-0.392730636112462
2361112.6034082064064-1.60340820640645
237410.2801833291943-6.28018332919433
2381313.5153843221827-0.515384322182692
2391613.88765363063272.1123463693673
2401010.6255327401344-0.625532740134383
2411211.98685168009140.0131483199086499
2421213.7069303922495-1.7069303922495
243108.903144473420451.09685552657955
2441310.90488836442212.09511163557788
2451512.91569032845892.0843096715411
2461212.599045499187-0.599045499186976
2471413.146496033370.85350396663004
2481012.9835984954948-2.98359849549482
2491210.93683641274571.06316358725429
2501211.42404690839420.575953091605809
2511112.1229276563997-1.12292765639966
2521011.4263977997735-1.42639779977355
2531210.93943962805511.06056037194487
2541612.50836615236183.49163384763824
2551212.998299110583-0.998299110582997
2561413.68713252142640.312867478573624
2571614.48747784698391.51252215301608
2581411.72894151443612.27105848556386
2591314.053654051576-1.05365405157599
26048.08400355852546-4.08400355852546
2611513.80438982536241.19561017463759
2621115.320972187573-4.32097218757297
2631111.1048724893516-0.104872489351625
2641412.79613327800321.20386672199677







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
190.998342410934830.003315178130339930.00165758906516997
200.9959061174629930.008187765074013330.00409388253700666
210.9908262820651740.01834743586965290.00917371793482643
220.984925087703940.03014982459211960.0150749122960598
230.9773700103639870.04525997927202560.0226299896360128
240.9685847877411850.06283042451763050.0314152122588153
250.950494221430680.09901155713864070.0495057785693203
260.9300800538382360.1398398923235270.0699199461617637
270.9013016563254870.1973966873490270.0986983436745133
280.9129317320350440.1741365359299120.0870682679649558
290.8806837015055060.2386325969889890.119316298494494
300.8772128846867040.2455742306265930.122787115313296
310.8436563490209620.3126873019580760.156343650979038
320.8323304580631710.3353390838736570.167669541936829
330.8122311193400630.3755377613198750.187768880659937
340.7624885774420320.4750228451159360.237511422557968
350.74442019017710.5111596196457990.2555798098229
360.8132881432441340.3734237135117320.186711856755866
370.8531152440272320.2937695119455360.146884755972768
380.8343443045511990.3313113908976020.165655695448801
390.8560053337606740.2879893324786530.143994666239326
400.8394663186479120.3210673627041760.160533681352088
410.8111489051629190.3777021896741630.188851094837081
420.7849083372567060.4301833254865880.215091662743294
430.7912691506890620.4174616986218760.208730849310938
440.7511931188812630.4976137622374740.248806881118737
450.7146455311817030.5707089376365950.285354468818297
460.8660350194900060.2679299610199880.133964980509994
470.8718186551865950.256362689626810.128181344813405
480.8477741800091920.3044516399816170.152225819990808
490.8380645787075470.3238708425849070.161935421292453
500.8217974879327160.3564050241345680.178202512067284
510.787607199305180.424785601389640.21239280069482
520.7533089486620590.4933821026758820.246691051337941
530.7520812720111550.4958374559776910.247918727988845
540.7243456859672680.5513086280654640.275654314032732
550.7298814228999920.5402371542000170.270118577100008
560.7371446119665650.525710776066870.262855388033435
570.6992661310633940.6014677378732120.300733868936606
580.6824616281470750.6350767437058510.317538371852925
590.6434532977718570.7130934044562860.356546702228143
600.6640825568737780.6718348862524440.335917443126222
610.6349177269625160.7301645460749680.365082273037484
620.5956361920866310.8087276158267370.404363807913369
630.5557219934830980.8885560130338040.444278006516902
640.5103929173471230.9792141653057550.489607082652877
650.4758415615447290.9516831230894580.524158438455271
660.4576165856573740.9152331713147480.542383414342626
670.4603213562565580.9206427125131160.539678643743442
680.5827819183958670.8344361632082660.417218081604133
690.6845652871430850.6308694257138290.315434712856915
700.6531385039695680.6937229920608640.346861496030432
710.7264777219175960.5470445561648080.273522278082404
720.6903254549427630.6193490901144740.309674545057237
730.6843136355148980.6313727289702040.315686364485102
740.6632903926540840.6734192146918310.336709607345916
750.6246817291673630.7506365416652750.375318270832637
760.6814789954293050.6370420091413890.318521004570695
770.6433646840968250.7132706318063490.356635315903175
780.6218990989459260.7562018021081480.378100901054074
790.6264637932641940.7470724134716120.373536206735806
800.5865563254218760.8268873491562470.413443674578124
810.5507547618161870.8984904763676260.449245238183813
820.5131695982084660.9736608035830680.486830401791534
830.4808343215159820.9616686430319640.519165678484018
840.4420128444701680.8840256889403370.557987155529832
850.4304253977201460.8608507954402910.569574602279854
860.3914702775257380.7829405550514770.608529722474262
870.3576461169247760.7152922338495530.642353883075224
880.3398866492571350.6797732985142710.660113350742865
890.3073320461768060.6146640923536120.692667953823194
900.2945789090786410.5891578181572820.705421090921359
910.2632402627409770.5264805254819540.736759737259023
920.2359742939261260.4719485878522520.764025706073874
930.2087682755073930.4175365510147850.791231724492607
940.2181970581684120.4363941163368240.781802941831588
950.1976039189393570.3952078378787150.802396081060643
960.1719764842612250.343952968522450.828023515738775
970.1706978244635110.3413956489270220.829302175536489
980.1468973441803040.2937946883606070.853102655819696
990.1273083251028420.2546166502056830.872691674897158
1000.1149094355470720.2298188710941450.885090564452928
1010.1035147272791050.207029454558210.896485272720895
1020.1221563133918910.2443126267837810.877843686608109
1030.1037424436912590.2074848873825190.89625755630874
1040.09814798851360990.196295977027220.90185201148639
1050.1118713435241450.2237426870482910.888128656475855
1060.1002147637234450.2004295274468890.899785236276555
1070.08769065133532720.1753813026706540.912309348664673
1080.08438409511361960.1687681902272390.91561590488638
1090.07707971052293020.154159421045860.92292028947707
1100.0683190547364740.1366381094729480.931680945263526
1110.05817858099917110.1163571619983420.941821419000829
1120.0667847259085870.1335694518171740.933215274091413
1130.05740815675417820.1148163135083560.942591843245822
1140.06916809494023020.138336189880460.93083190505977
1150.06691465427446640.1338293085489330.933085345725534
1160.05911111910380870.1182222382076170.940888880896191
1170.0545895058597490.1091790117194980.945410494140251
1180.05340056121704560.1068011224340910.946599438782954
1190.05188455746379980.10376911492760.9481154425362
1200.04433770026974150.0886754005394830.955662299730259
1210.03846791820118190.07693583640236370.961532081798818
1220.04628135556232640.09256271112465280.953718644437674
1230.03892563936868640.07785127873737280.961074360631314
1240.03348914302010090.06697828604020180.966510856979899
1250.02774466140314850.0554893228062970.972255338596852
1260.02229561174337380.04459122348674770.977704388256626
1270.02168490289893810.04336980579787630.978315097101062
1280.02015086970433670.04030173940867340.979849130295663
1290.02342959807537940.04685919615075880.976570401924621
1300.0251054858535330.05021097170706610.974894514146467
1310.03414938710303830.06829877420607660.965850612896962
1320.0455277194627170.09105543892543390.954472280537283
1330.04554186665783740.09108373331567480.954458133342163
1340.04011021371484920.08022042742969850.959889786285151
1350.03338553934624060.06677107869248130.966614460653759
1360.02911143939182670.05822287878365340.970888560608173
1370.02559559566123820.05119119132247640.974404404338762
1380.02783573973645520.05567147947291040.972164260263545
1390.02392765787525580.04785531575051170.976072342124744
1400.03184330376932620.06368660753865230.968156696230674
1410.04065571822870720.08131143645741430.959344281771293
1420.03883549235950570.07767098471901130.961164507640494
1430.03195130063877040.06390260127754090.96804869936123
1440.0282667239515820.0565334479031640.971733276048418
1450.04557874729751250.09115749459502510.954421252702487
1460.05508200149677760.1101640029935550.944917998503222
1470.06836062609142330.1367212521828470.931639373908577
1480.05871908397584050.1174381679516810.94128091602416
1490.04932245087327810.09864490174655620.950677549126722
1500.06595038847376450.1319007769475290.934049611526236
1510.05928356021592870.1185671204318570.940716439784071
1520.06073440490579520.121468809811590.939265595094205
1530.07992990811021570.1598598162204310.920070091889784
1540.06972811169552540.1394562233910510.930271888304475
1550.06789970731612520.135799414632250.932100292683875
1560.05698171985566730.1139634397113350.943018280144333
1570.04965499969598290.09930999939196580.950345000304017
1580.04218398370976590.08436796741953170.957816016290234
1590.03516993602707010.07033987205414030.96483006397293
1600.0285842316182830.05716846323656590.971415768381717
1610.0230056238209910.0460112476419820.976994376179009
1620.01833275745816630.03666551491633260.981667242541834
1630.01457155848945670.02914311697891350.985428441510543
1640.01194192085099440.02388384170198880.988058079149006
1650.00953073827212750.0190614765442550.990469261727873
1660.009651050378038970.01930210075607790.990348949621961
1670.007481607138500120.01496321427700020.9925183928615
1680.008028104690218090.01605620938043620.991971895309782
1690.007340082027861290.01468016405572260.992659917972139
1700.005956848727888040.01191369745577610.994043151272112
1710.006979486973631360.01395897394726270.993020513026369
1720.005408012898740160.01081602579748030.99459198710126
1730.004288395692250530.008576791384501060.99571160430775
1740.004236450090441830.008472900180883650.995763549909558
1750.004231209160712920.008462418321425840.995768790839287
1760.00350217595153340.007004351903066790.996497824048467
1770.002619411663557470.005238823327114940.997380588336442
1780.002105808883725820.004211617767451640.997894191116274
1790.001616452890686890.003232905781373790.998383547109313
1800.001391319348260920.002782638696521840.998608680651739
1810.001094176173045270.002188352346090550.998905823826955
1820.0007935067346118760.001587013469223750.999206493265388
1830.0007847054731048530.001569410946209710.999215294526895
1840.0005798807103629910.001159761420725980.999420119289637
1850.01682086411471770.03364172822943530.983179135885282
1860.01437743826290880.02875487652581750.985622561737091
1870.01698938655710430.03397877311420870.983010613442896
1880.01337775973331760.02675551946663520.986622240266682
1890.01131635151616940.02263270303233880.988683648483831
1900.008964566761553440.01792913352310690.991035433238447
1910.00790479664502840.01580959329005680.992095203354972
1920.006102130213286970.01220426042657390.993897869786713
1930.005608552367255420.01121710473451080.994391447632745
1940.004873788056824570.009747576113649140.995126211943175
1950.003964896689821230.007929793379642460.996035103310179
1960.002897804204192820.005795608408385640.997102195795807
1970.003971742457702660.007943484915405310.996028257542297
1980.002898203853766010.005796407707532030.997101796146234
1990.002446588601850330.004893177203700670.99755341139815
2000.002053784380385110.004107568760770210.997946215619615
2010.00181149204614910.00362298409229820.998188507953851
2020.001389441103695510.002778882207391020.998610558896304
2030.001663395889689880.003326791779379760.99833660411031
2040.00264581159064530.005291623181290610.997354188409355
2050.002640136505073190.005280273010146390.997359863494927
2060.001880583872688320.003761167745376640.998119416127312
2070.001521576365375450.003043152730750890.998478423634625
2080.001078571817168880.002157143634337760.998921428182831
2090.001378861436947010.002757722873894030.998621138563053
2100.001036224283845430.002072448567690870.998963775716155
2110.001323842872877920.002647685745755850.998676157127122
2120.004032497523943890.008064995047887770.995967502476056
2130.002803906835009340.005607813670018680.997196093164991
2140.003704304240152790.007408608480305580.996295695759847
2150.002829670539017410.005659341078034820.997170329460983
2160.002030202005747620.004060404011495240.997969797994252
2170.002165603286302470.004331206572604940.997834396713698
2180.001679637059900320.003359274119800640.9983203629401
2190.001463459206152160.002926918412304310.998536540793848
2200.001007588085430270.002015176170860540.99899241191457
2210.0007379951617153930.001475990323430790.999262004838285
2220.0004748723775266510.0009497447550533020.999525127622473
2230.0003234869091067050.0006469738182134090.999676513090893
2240.0002187256122924760.0004374512245849530.999781274387707
2250.0001329043274539640.0002658086549079280.999867095672546
2260.000345001316703980.0006900026334079610.999654998683296
2270.0002401043357682360.0004802086715364720.999759895664232
2280.0001499246117902260.0002998492235804520.99985007538821
2299.76700348352576e-050.0001953400696705150.999902329965165
2305.8442096056655e-050.000116884192113310.999941557903943
2316.14139037689169e-050.0001228278075378340.999938586096231
2320.0002817367328122320.0005634734656244630.999718263267188
2330.00140086117832110.002801722356642190.998599138821679
2340.002289740949298370.004579481898596750.997710259050702
2350.001337847641138050.00267569528227610.998662152358862
2360.0008735973382415850.001747194676483170.999126402661758
2370.0191809140129550.03836182802590990.980819085987045
2380.01165371117857160.02330742235714330.988346288821428
2390.007944134142832880.01588826828566580.992055865857167
2400.004536144822264090.009072289644528170.995463855177736
2410.003125833397266380.006251666794532770.996874166602734
2420.005117902687495820.01023580537499160.994882097312504
2430.002930621448106940.005861242896213890.997069378551893
2440.002124768061856060.004249536123712120.997875231938144
2450.001113814824422490.002227629648844970.998886185175577

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
19 & 0.99834241093483 & 0.00331517813033993 & 0.00165758906516997 \tabularnewline
20 & 0.995906117462993 & 0.00818776507401333 & 0.00409388253700666 \tabularnewline
21 & 0.990826282065174 & 0.0183474358696529 & 0.00917371793482643 \tabularnewline
22 & 0.98492508770394 & 0.0301498245921196 & 0.0150749122960598 \tabularnewline
23 & 0.977370010363987 & 0.0452599792720256 & 0.0226299896360128 \tabularnewline
24 & 0.968584787741185 & 0.0628304245176305 & 0.0314152122588153 \tabularnewline
25 & 0.95049422143068 & 0.0990115571386407 & 0.0495057785693203 \tabularnewline
26 & 0.930080053838236 & 0.139839892323527 & 0.0699199461617637 \tabularnewline
27 & 0.901301656325487 & 0.197396687349027 & 0.0986983436745133 \tabularnewline
28 & 0.912931732035044 & 0.174136535929912 & 0.0870682679649558 \tabularnewline
29 & 0.880683701505506 & 0.238632596988989 & 0.119316298494494 \tabularnewline
30 & 0.877212884686704 & 0.245574230626593 & 0.122787115313296 \tabularnewline
31 & 0.843656349020962 & 0.312687301958076 & 0.156343650979038 \tabularnewline
32 & 0.832330458063171 & 0.335339083873657 & 0.167669541936829 \tabularnewline
33 & 0.812231119340063 & 0.375537761319875 & 0.187768880659937 \tabularnewline
34 & 0.762488577442032 & 0.475022845115936 & 0.237511422557968 \tabularnewline
35 & 0.7444201901771 & 0.511159619645799 & 0.2555798098229 \tabularnewline
36 & 0.813288143244134 & 0.373423713511732 & 0.186711856755866 \tabularnewline
37 & 0.853115244027232 & 0.293769511945536 & 0.146884755972768 \tabularnewline
38 & 0.834344304551199 & 0.331311390897602 & 0.165655695448801 \tabularnewline
39 & 0.856005333760674 & 0.287989332478653 & 0.143994666239326 \tabularnewline
40 & 0.839466318647912 & 0.321067362704176 & 0.160533681352088 \tabularnewline
41 & 0.811148905162919 & 0.377702189674163 & 0.188851094837081 \tabularnewline
42 & 0.784908337256706 & 0.430183325486588 & 0.215091662743294 \tabularnewline
43 & 0.791269150689062 & 0.417461698621876 & 0.208730849310938 \tabularnewline
44 & 0.751193118881263 & 0.497613762237474 & 0.248806881118737 \tabularnewline
45 & 0.714645531181703 & 0.570708937636595 & 0.285354468818297 \tabularnewline
46 & 0.866035019490006 & 0.267929961019988 & 0.133964980509994 \tabularnewline
47 & 0.871818655186595 & 0.25636268962681 & 0.128181344813405 \tabularnewline
48 & 0.847774180009192 & 0.304451639981617 & 0.152225819990808 \tabularnewline
49 & 0.838064578707547 & 0.323870842584907 & 0.161935421292453 \tabularnewline
50 & 0.821797487932716 & 0.356405024134568 & 0.178202512067284 \tabularnewline
51 & 0.78760719930518 & 0.42478560138964 & 0.21239280069482 \tabularnewline
52 & 0.753308948662059 & 0.493382102675882 & 0.246691051337941 \tabularnewline
53 & 0.752081272011155 & 0.495837455977691 & 0.247918727988845 \tabularnewline
54 & 0.724345685967268 & 0.551308628065464 & 0.275654314032732 \tabularnewline
55 & 0.729881422899992 & 0.540237154200017 & 0.270118577100008 \tabularnewline
56 & 0.737144611966565 & 0.52571077606687 & 0.262855388033435 \tabularnewline
57 & 0.699266131063394 & 0.601467737873212 & 0.300733868936606 \tabularnewline
58 & 0.682461628147075 & 0.635076743705851 & 0.317538371852925 \tabularnewline
59 & 0.643453297771857 & 0.713093404456286 & 0.356546702228143 \tabularnewline
60 & 0.664082556873778 & 0.671834886252444 & 0.335917443126222 \tabularnewline
61 & 0.634917726962516 & 0.730164546074968 & 0.365082273037484 \tabularnewline
62 & 0.595636192086631 & 0.808727615826737 & 0.404363807913369 \tabularnewline
63 & 0.555721993483098 & 0.888556013033804 & 0.444278006516902 \tabularnewline
64 & 0.510392917347123 & 0.979214165305755 & 0.489607082652877 \tabularnewline
65 & 0.475841561544729 & 0.951683123089458 & 0.524158438455271 \tabularnewline
66 & 0.457616585657374 & 0.915233171314748 & 0.542383414342626 \tabularnewline
67 & 0.460321356256558 & 0.920642712513116 & 0.539678643743442 \tabularnewline
68 & 0.582781918395867 & 0.834436163208266 & 0.417218081604133 \tabularnewline
69 & 0.684565287143085 & 0.630869425713829 & 0.315434712856915 \tabularnewline
70 & 0.653138503969568 & 0.693722992060864 & 0.346861496030432 \tabularnewline
71 & 0.726477721917596 & 0.547044556164808 & 0.273522278082404 \tabularnewline
72 & 0.690325454942763 & 0.619349090114474 & 0.309674545057237 \tabularnewline
73 & 0.684313635514898 & 0.631372728970204 & 0.315686364485102 \tabularnewline
74 & 0.663290392654084 & 0.673419214691831 & 0.336709607345916 \tabularnewline
75 & 0.624681729167363 & 0.750636541665275 & 0.375318270832637 \tabularnewline
76 & 0.681478995429305 & 0.637042009141389 & 0.318521004570695 \tabularnewline
77 & 0.643364684096825 & 0.713270631806349 & 0.356635315903175 \tabularnewline
78 & 0.621899098945926 & 0.756201802108148 & 0.378100901054074 \tabularnewline
79 & 0.626463793264194 & 0.747072413471612 & 0.373536206735806 \tabularnewline
80 & 0.586556325421876 & 0.826887349156247 & 0.413443674578124 \tabularnewline
81 & 0.550754761816187 & 0.898490476367626 & 0.449245238183813 \tabularnewline
82 & 0.513169598208466 & 0.973660803583068 & 0.486830401791534 \tabularnewline
83 & 0.480834321515982 & 0.961668643031964 & 0.519165678484018 \tabularnewline
84 & 0.442012844470168 & 0.884025688940337 & 0.557987155529832 \tabularnewline
85 & 0.430425397720146 & 0.860850795440291 & 0.569574602279854 \tabularnewline
86 & 0.391470277525738 & 0.782940555051477 & 0.608529722474262 \tabularnewline
87 & 0.357646116924776 & 0.715292233849553 & 0.642353883075224 \tabularnewline
88 & 0.339886649257135 & 0.679773298514271 & 0.660113350742865 \tabularnewline
89 & 0.307332046176806 & 0.614664092353612 & 0.692667953823194 \tabularnewline
90 & 0.294578909078641 & 0.589157818157282 & 0.705421090921359 \tabularnewline
91 & 0.263240262740977 & 0.526480525481954 & 0.736759737259023 \tabularnewline
92 & 0.235974293926126 & 0.471948587852252 & 0.764025706073874 \tabularnewline
93 & 0.208768275507393 & 0.417536551014785 & 0.791231724492607 \tabularnewline
94 & 0.218197058168412 & 0.436394116336824 & 0.781802941831588 \tabularnewline
95 & 0.197603918939357 & 0.395207837878715 & 0.802396081060643 \tabularnewline
96 & 0.171976484261225 & 0.34395296852245 & 0.828023515738775 \tabularnewline
97 & 0.170697824463511 & 0.341395648927022 & 0.829302175536489 \tabularnewline
98 & 0.146897344180304 & 0.293794688360607 & 0.853102655819696 \tabularnewline
99 & 0.127308325102842 & 0.254616650205683 & 0.872691674897158 \tabularnewline
100 & 0.114909435547072 & 0.229818871094145 & 0.885090564452928 \tabularnewline
101 & 0.103514727279105 & 0.20702945455821 & 0.896485272720895 \tabularnewline
102 & 0.122156313391891 & 0.244312626783781 & 0.877843686608109 \tabularnewline
103 & 0.103742443691259 & 0.207484887382519 & 0.89625755630874 \tabularnewline
104 & 0.0981479885136099 & 0.19629597702722 & 0.90185201148639 \tabularnewline
105 & 0.111871343524145 & 0.223742687048291 & 0.888128656475855 \tabularnewline
106 & 0.100214763723445 & 0.200429527446889 & 0.899785236276555 \tabularnewline
107 & 0.0876906513353272 & 0.175381302670654 & 0.912309348664673 \tabularnewline
108 & 0.0843840951136196 & 0.168768190227239 & 0.91561590488638 \tabularnewline
109 & 0.0770797105229302 & 0.15415942104586 & 0.92292028947707 \tabularnewline
110 & 0.068319054736474 & 0.136638109472948 & 0.931680945263526 \tabularnewline
111 & 0.0581785809991711 & 0.116357161998342 & 0.941821419000829 \tabularnewline
112 & 0.066784725908587 & 0.133569451817174 & 0.933215274091413 \tabularnewline
113 & 0.0574081567541782 & 0.114816313508356 & 0.942591843245822 \tabularnewline
114 & 0.0691680949402302 & 0.13833618988046 & 0.93083190505977 \tabularnewline
115 & 0.0669146542744664 & 0.133829308548933 & 0.933085345725534 \tabularnewline
116 & 0.0591111191038087 & 0.118222238207617 & 0.940888880896191 \tabularnewline
117 & 0.054589505859749 & 0.109179011719498 & 0.945410494140251 \tabularnewline
118 & 0.0534005612170456 & 0.106801122434091 & 0.946599438782954 \tabularnewline
119 & 0.0518845574637998 & 0.1037691149276 & 0.9481154425362 \tabularnewline
120 & 0.0443377002697415 & 0.088675400539483 & 0.955662299730259 \tabularnewline
121 & 0.0384679182011819 & 0.0769358364023637 & 0.961532081798818 \tabularnewline
122 & 0.0462813555623264 & 0.0925627111246528 & 0.953718644437674 \tabularnewline
123 & 0.0389256393686864 & 0.0778512787373728 & 0.961074360631314 \tabularnewline
124 & 0.0334891430201009 & 0.0669782860402018 & 0.966510856979899 \tabularnewline
125 & 0.0277446614031485 & 0.055489322806297 & 0.972255338596852 \tabularnewline
126 & 0.0222956117433738 & 0.0445912234867477 & 0.977704388256626 \tabularnewline
127 & 0.0216849028989381 & 0.0433698057978763 & 0.978315097101062 \tabularnewline
128 & 0.0201508697043367 & 0.0403017394086734 & 0.979849130295663 \tabularnewline
129 & 0.0234295980753794 & 0.0468591961507588 & 0.976570401924621 \tabularnewline
130 & 0.025105485853533 & 0.0502109717070661 & 0.974894514146467 \tabularnewline
131 & 0.0341493871030383 & 0.0682987742060766 & 0.965850612896962 \tabularnewline
132 & 0.045527719462717 & 0.0910554389254339 & 0.954472280537283 \tabularnewline
133 & 0.0455418666578374 & 0.0910837333156748 & 0.954458133342163 \tabularnewline
134 & 0.0401102137148492 & 0.0802204274296985 & 0.959889786285151 \tabularnewline
135 & 0.0333855393462406 & 0.0667710786924813 & 0.966614460653759 \tabularnewline
136 & 0.0291114393918267 & 0.0582228787836534 & 0.970888560608173 \tabularnewline
137 & 0.0255955956612382 & 0.0511911913224764 & 0.974404404338762 \tabularnewline
138 & 0.0278357397364552 & 0.0556714794729104 & 0.972164260263545 \tabularnewline
139 & 0.0239276578752558 & 0.0478553157505117 & 0.976072342124744 \tabularnewline
140 & 0.0318433037693262 & 0.0636866075386523 & 0.968156696230674 \tabularnewline
141 & 0.0406557182287072 & 0.0813114364574143 & 0.959344281771293 \tabularnewline
142 & 0.0388354923595057 & 0.0776709847190113 & 0.961164507640494 \tabularnewline
143 & 0.0319513006387704 & 0.0639026012775409 & 0.96804869936123 \tabularnewline
144 & 0.028266723951582 & 0.056533447903164 & 0.971733276048418 \tabularnewline
145 & 0.0455787472975125 & 0.0911574945950251 & 0.954421252702487 \tabularnewline
146 & 0.0550820014967776 & 0.110164002993555 & 0.944917998503222 \tabularnewline
147 & 0.0683606260914233 & 0.136721252182847 & 0.931639373908577 \tabularnewline
148 & 0.0587190839758405 & 0.117438167951681 & 0.94128091602416 \tabularnewline
149 & 0.0493224508732781 & 0.0986449017465562 & 0.950677549126722 \tabularnewline
150 & 0.0659503884737645 & 0.131900776947529 & 0.934049611526236 \tabularnewline
151 & 0.0592835602159287 & 0.118567120431857 & 0.940716439784071 \tabularnewline
152 & 0.0607344049057952 & 0.12146880981159 & 0.939265595094205 \tabularnewline
153 & 0.0799299081102157 & 0.159859816220431 & 0.920070091889784 \tabularnewline
154 & 0.0697281116955254 & 0.139456223391051 & 0.930271888304475 \tabularnewline
155 & 0.0678997073161252 & 0.13579941463225 & 0.932100292683875 \tabularnewline
156 & 0.0569817198556673 & 0.113963439711335 & 0.943018280144333 \tabularnewline
157 & 0.0496549996959829 & 0.0993099993919658 & 0.950345000304017 \tabularnewline
158 & 0.0421839837097659 & 0.0843679674195317 & 0.957816016290234 \tabularnewline
159 & 0.0351699360270701 & 0.0703398720541403 & 0.96483006397293 \tabularnewline
160 & 0.028584231618283 & 0.0571684632365659 & 0.971415768381717 \tabularnewline
161 & 0.023005623820991 & 0.046011247641982 & 0.976994376179009 \tabularnewline
162 & 0.0183327574581663 & 0.0366655149163326 & 0.981667242541834 \tabularnewline
163 & 0.0145715584894567 & 0.0291431169789135 & 0.985428441510543 \tabularnewline
164 & 0.0119419208509944 & 0.0238838417019888 & 0.988058079149006 \tabularnewline
165 & 0.0095307382721275 & 0.019061476544255 & 0.990469261727873 \tabularnewline
166 & 0.00965105037803897 & 0.0193021007560779 & 0.990348949621961 \tabularnewline
167 & 0.00748160713850012 & 0.0149632142770002 & 0.9925183928615 \tabularnewline
168 & 0.00802810469021809 & 0.0160562093804362 & 0.991971895309782 \tabularnewline
169 & 0.00734008202786129 & 0.0146801640557226 & 0.992659917972139 \tabularnewline
170 & 0.00595684872788804 & 0.0119136974557761 & 0.994043151272112 \tabularnewline
171 & 0.00697948697363136 & 0.0139589739472627 & 0.993020513026369 \tabularnewline
172 & 0.00540801289874016 & 0.0108160257974803 & 0.99459198710126 \tabularnewline
173 & 0.00428839569225053 & 0.00857679138450106 & 0.99571160430775 \tabularnewline
174 & 0.00423645009044183 & 0.00847290018088365 & 0.995763549909558 \tabularnewline
175 & 0.00423120916071292 & 0.00846241832142584 & 0.995768790839287 \tabularnewline
176 & 0.0035021759515334 & 0.00700435190306679 & 0.996497824048467 \tabularnewline
177 & 0.00261941166355747 & 0.00523882332711494 & 0.997380588336442 \tabularnewline
178 & 0.00210580888372582 & 0.00421161776745164 & 0.997894191116274 \tabularnewline
179 & 0.00161645289068689 & 0.00323290578137379 & 0.998383547109313 \tabularnewline
180 & 0.00139131934826092 & 0.00278263869652184 & 0.998608680651739 \tabularnewline
181 & 0.00109417617304527 & 0.00218835234609055 & 0.998905823826955 \tabularnewline
182 & 0.000793506734611876 & 0.00158701346922375 & 0.999206493265388 \tabularnewline
183 & 0.000784705473104853 & 0.00156941094620971 & 0.999215294526895 \tabularnewline
184 & 0.000579880710362991 & 0.00115976142072598 & 0.999420119289637 \tabularnewline
185 & 0.0168208641147177 & 0.0336417282294353 & 0.983179135885282 \tabularnewline
186 & 0.0143774382629088 & 0.0287548765258175 & 0.985622561737091 \tabularnewline
187 & 0.0169893865571043 & 0.0339787731142087 & 0.983010613442896 \tabularnewline
188 & 0.0133777597333176 & 0.0267555194666352 & 0.986622240266682 \tabularnewline
189 & 0.0113163515161694 & 0.0226327030323388 & 0.988683648483831 \tabularnewline
190 & 0.00896456676155344 & 0.0179291335231069 & 0.991035433238447 \tabularnewline
191 & 0.0079047966450284 & 0.0158095932900568 & 0.992095203354972 \tabularnewline
192 & 0.00610213021328697 & 0.0122042604265739 & 0.993897869786713 \tabularnewline
193 & 0.00560855236725542 & 0.0112171047345108 & 0.994391447632745 \tabularnewline
194 & 0.00487378805682457 & 0.00974757611364914 & 0.995126211943175 \tabularnewline
195 & 0.00396489668982123 & 0.00792979337964246 & 0.996035103310179 \tabularnewline
196 & 0.00289780420419282 & 0.00579560840838564 & 0.997102195795807 \tabularnewline
197 & 0.00397174245770266 & 0.00794348491540531 & 0.996028257542297 \tabularnewline
198 & 0.00289820385376601 & 0.00579640770753203 & 0.997101796146234 \tabularnewline
199 & 0.00244658860185033 & 0.00489317720370067 & 0.99755341139815 \tabularnewline
200 & 0.00205378438038511 & 0.00410756876077021 & 0.997946215619615 \tabularnewline
201 & 0.0018114920461491 & 0.0036229840922982 & 0.998188507953851 \tabularnewline
202 & 0.00138944110369551 & 0.00277888220739102 & 0.998610558896304 \tabularnewline
203 & 0.00166339588968988 & 0.00332679177937976 & 0.99833660411031 \tabularnewline
204 & 0.0026458115906453 & 0.00529162318129061 & 0.997354188409355 \tabularnewline
205 & 0.00264013650507319 & 0.00528027301014639 & 0.997359863494927 \tabularnewline
206 & 0.00188058387268832 & 0.00376116774537664 & 0.998119416127312 \tabularnewline
207 & 0.00152157636537545 & 0.00304315273075089 & 0.998478423634625 \tabularnewline
208 & 0.00107857181716888 & 0.00215714363433776 & 0.998921428182831 \tabularnewline
209 & 0.00137886143694701 & 0.00275772287389403 & 0.998621138563053 \tabularnewline
210 & 0.00103622428384543 & 0.00207244856769087 & 0.998963775716155 \tabularnewline
211 & 0.00132384287287792 & 0.00264768574575585 & 0.998676157127122 \tabularnewline
212 & 0.00403249752394389 & 0.00806499504788777 & 0.995967502476056 \tabularnewline
213 & 0.00280390683500934 & 0.00560781367001868 & 0.997196093164991 \tabularnewline
214 & 0.00370430424015279 & 0.00740860848030558 & 0.996295695759847 \tabularnewline
215 & 0.00282967053901741 & 0.00565934107803482 & 0.997170329460983 \tabularnewline
216 & 0.00203020200574762 & 0.00406040401149524 & 0.997969797994252 \tabularnewline
217 & 0.00216560328630247 & 0.00433120657260494 & 0.997834396713698 \tabularnewline
218 & 0.00167963705990032 & 0.00335927411980064 & 0.9983203629401 \tabularnewline
219 & 0.00146345920615216 & 0.00292691841230431 & 0.998536540793848 \tabularnewline
220 & 0.00100758808543027 & 0.00201517617086054 & 0.99899241191457 \tabularnewline
221 & 0.000737995161715393 & 0.00147599032343079 & 0.999262004838285 \tabularnewline
222 & 0.000474872377526651 & 0.000949744755053302 & 0.999525127622473 \tabularnewline
223 & 0.000323486909106705 & 0.000646973818213409 & 0.999676513090893 \tabularnewline
224 & 0.000218725612292476 & 0.000437451224584953 & 0.999781274387707 \tabularnewline
225 & 0.000132904327453964 & 0.000265808654907928 & 0.999867095672546 \tabularnewline
226 & 0.00034500131670398 & 0.000690002633407961 & 0.999654998683296 \tabularnewline
227 & 0.000240104335768236 & 0.000480208671536472 & 0.999759895664232 \tabularnewline
228 & 0.000149924611790226 & 0.000299849223580452 & 0.99985007538821 \tabularnewline
229 & 9.76700348352576e-05 & 0.000195340069670515 & 0.999902329965165 \tabularnewline
230 & 5.8442096056655e-05 & 0.00011688419211331 & 0.999941557903943 \tabularnewline
231 & 6.14139037689169e-05 & 0.000122827807537834 & 0.999938586096231 \tabularnewline
232 & 0.000281736732812232 & 0.000563473465624463 & 0.999718263267188 \tabularnewline
233 & 0.0014008611783211 & 0.00280172235664219 & 0.998599138821679 \tabularnewline
234 & 0.00228974094929837 & 0.00457948189859675 & 0.997710259050702 \tabularnewline
235 & 0.00133784764113805 & 0.0026756952822761 & 0.998662152358862 \tabularnewline
236 & 0.000873597338241585 & 0.00174719467648317 & 0.999126402661758 \tabularnewline
237 & 0.019180914012955 & 0.0383618280259099 & 0.980819085987045 \tabularnewline
238 & 0.0116537111785716 & 0.0233074223571433 & 0.988346288821428 \tabularnewline
239 & 0.00794413414283288 & 0.0158882682856658 & 0.992055865857167 \tabularnewline
240 & 0.00453614482226409 & 0.00907228964452817 & 0.995463855177736 \tabularnewline
241 & 0.00312583339726638 & 0.00625166679453277 & 0.996874166602734 \tabularnewline
242 & 0.00511790268749582 & 0.0102358053749916 & 0.994882097312504 \tabularnewline
243 & 0.00293062144810694 & 0.00586124289621389 & 0.997069378551893 \tabularnewline
244 & 0.00212476806185606 & 0.00424953612371212 & 0.997875231938144 \tabularnewline
245 & 0.00111381482442249 & 0.00222762964884497 & 0.998886185175577 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185728&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]0.99834241093483[/C][C]0.00331517813033993[/C][C]0.00165758906516997[/C][/ROW]
[ROW][C]20[/C][C]0.995906117462993[/C][C]0.00818776507401333[/C][C]0.00409388253700666[/C][/ROW]
[ROW][C]21[/C][C]0.990826282065174[/C][C]0.0183474358696529[/C][C]0.00917371793482643[/C][/ROW]
[ROW][C]22[/C][C]0.98492508770394[/C][C]0.0301498245921196[/C][C]0.0150749122960598[/C][/ROW]
[ROW][C]23[/C][C]0.977370010363987[/C][C]0.0452599792720256[/C][C]0.0226299896360128[/C][/ROW]
[ROW][C]24[/C][C]0.968584787741185[/C][C]0.0628304245176305[/C][C]0.0314152122588153[/C][/ROW]
[ROW][C]25[/C][C]0.95049422143068[/C][C]0.0990115571386407[/C][C]0.0495057785693203[/C][/ROW]
[ROW][C]26[/C][C]0.930080053838236[/C][C]0.139839892323527[/C][C]0.0699199461617637[/C][/ROW]
[ROW][C]27[/C][C]0.901301656325487[/C][C]0.197396687349027[/C][C]0.0986983436745133[/C][/ROW]
[ROW][C]28[/C][C]0.912931732035044[/C][C]0.174136535929912[/C][C]0.0870682679649558[/C][/ROW]
[ROW][C]29[/C][C]0.880683701505506[/C][C]0.238632596988989[/C][C]0.119316298494494[/C][/ROW]
[ROW][C]30[/C][C]0.877212884686704[/C][C]0.245574230626593[/C][C]0.122787115313296[/C][/ROW]
[ROW][C]31[/C][C]0.843656349020962[/C][C]0.312687301958076[/C][C]0.156343650979038[/C][/ROW]
[ROW][C]32[/C][C]0.832330458063171[/C][C]0.335339083873657[/C][C]0.167669541936829[/C][/ROW]
[ROW][C]33[/C][C]0.812231119340063[/C][C]0.375537761319875[/C][C]0.187768880659937[/C][/ROW]
[ROW][C]34[/C][C]0.762488577442032[/C][C]0.475022845115936[/C][C]0.237511422557968[/C][/ROW]
[ROW][C]35[/C][C]0.7444201901771[/C][C]0.511159619645799[/C][C]0.2555798098229[/C][/ROW]
[ROW][C]36[/C][C]0.813288143244134[/C][C]0.373423713511732[/C][C]0.186711856755866[/C][/ROW]
[ROW][C]37[/C][C]0.853115244027232[/C][C]0.293769511945536[/C][C]0.146884755972768[/C][/ROW]
[ROW][C]38[/C][C]0.834344304551199[/C][C]0.331311390897602[/C][C]0.165655695448801[/C][/ROW]
[ROW][C]39[/C][C]0.856005333760674[/C][C]0.287989332478653[/C][C]0.143994666239326[/C][/ROW]
[ROW][C]40[/C][C]0.839466318647912[/C][C]0.321067362704176[/C][C]0.160533681352088[/C][/ROW]
[ROW][C]41[/C][C]0.811148905162919[/C][C]0.377702189674163[/C][C]0.188851094837081[/C][/ROW]
[ROW][C]42[/C][C]0.784908337256706[/C][C]0.430183325486588[/C][C]0.215091662743294[/C][/ROW]
[ROW][C]43[/C][C]0.791269150689062[/C][C]0.417461698621876[/C][C]0.208730849310938[/C][/ROW]
[ROW][C]44[/C][C]0.751193118881263[/C][C]0.497613762237474[/C][C]0.248806881118737[/C][/ROW]
[ROW][C]45[/C][C]0.714645531181703[/C][C]0.570708937636595[/C][C]0.285354468818297[/C][/ROW]
[ROW][C]46[/C][C]0.866035019490006[/C][C]0.267929961019988[/C][C]0.133964980509994[/C][/ROW]
[ROW][C]47[/C][C]0.871818655186595[/C][C]0.25636268962681[/C][C]0.128181344813405[/C][/ROW]
[ROW][C]48[/C][C]0.847774180009192[/C][C]0.304451639981617[/C][C]0.152225819990808[/C][/ROW]
[ROW][C]49[/C][C]0.838064578707547[/C][C]0.323870842584907[/C][C]0.161935421292453[/C][/ROW]
[ROW][C]50[/C][C]0.821797487932716[/C][C]0.356405024134568[/C][C]0.178202512067284[/C][/ROW]
[ROW][C]51[/C][C]0.78760719930518[/C][C]0.42478560138964[/C][C]0.21239280069482[/C][/ROW]
[ROW][C]52[/C][C]0.753308948662059[/C][C]0.493382102675882[/C][C]0.246691051337941[/C][/ROW]
[ROW][C]53[/C][C]0.752081272011155[/C][C]0.495837455977691[/C][C]0.247918727988845[/C][/ROW]
[ROW][C]54[/C][C]0.724345685967268[/C][C]0.551308628065464[/C][C]0.275654314032732[/C][/ROW]
[ROW][C]55[/C][C]0.729881422899992[/C][C]0.540237154200017[/C][C]0.270118577100008[/C][/ROW]
[ROW][C]56[/C][C]0.737144611966565[/C][C]0.52571077606687[/C][C]0.262855388033435[/C][/ROW]
[ROW][C]57[/C][C]0.699266131063394[/C][C]0.601467737873212[/C][C]0.300733868936606[/C][/ROW]
[ROW][C]58[/C][C]0.682461628147075[/C][C]0.635076743705851[/C][C]0.317538371852925[/C][/ROW]
[ROW][C]59[/C][C]0.643453297771857[/C][C]0.713093404456286[/C][C]0.356546702228143[/C][/ROW]
[ROW][C]60[/C][C]0.664082556873778[/C][C]0.671834886252444[/C][C]0.335917443126222[/C][/ROW]
[ROW][C]61[/C][C]0.634917726962516[/C][C]0.730164546074968[/C][C]0.365082273037484[/C][/ROW]
[ROW][C]62[/C][C]0.595636192086631[/C][C]0.808727615826737[/C][C]0.404363807913369[/C][/ROW]
[ROW][C]63[/C][C]0.555721993483098[/C][C]0.888556013033804[/C][C]0.444278006516902[/C][/ROW]
[ROW][C]64[/C][C]0.510392917347123[/C][C]0.979214165305755[/C][C]0.489607082652877[/C][/ROW]
[ROW][C]65[/C][C]0.475841561544729[/C][C]0.951683123089458[/C][C]0.524158438455271[/C][/ROW]
[ROW][C]66[/C][C]0.457616585657374[/C][C]0.915233171314748[/C][C]0.542383414342626[/C][/ROW]
[ROW][C]67[/C][C]0.460321356256558[/C][C]0.920642712513116[/C][C]0.539678643743442[/C][/ROW]
[ROW][C]68[/C][C]0.582781918395867[/C][C]0.834436163208266[/C][C]0.417218081604133[/C][/ROW]
[ROW][C]69[/C][C]0.684565287143085[/C][C]0.630869425713829[/C][C]0.315434712856915[/C][/ROW]
[ROW][C]70[/C][C]0.653138503969568[/C][C]0.693722992060864[/C][C]0.346861496030432[/C][/ROW]
[ROW][C]71[/C][C]0.726477721917596[/C][C]0.547044556164808[/C][C]0.273522278082404[/C][/ROW]
[ROW][C]72[/C][C]0.690325454942763[/C][C]0.619349090114474[/C][C]0.309674545057237[/C][/ROW]
[ROW][C]73[/C][C]0.684313635514898[/C][C]0.631372728970204[/C][C]0.315686364485102[/C][/ROW]
[ROW][C]74[/C][C]0.663290392654084[/C][C]0.673419214691831[/C][C]0.336709607345916[/C][/ROW]
[ROW][C]75[/C][C]0.624681729167363[/C][C]0.750636541665275[/C][C]0.375318270832637[/C][/ROW]
[ROW][C]76[/C][C]0.681478995429305[/C][C]0.637042009141389[/C][C]0.318521004570695[/C][/ROW]
[ROW][C]77[/C][C]0.643364684096825[/C][C]0.713270631806349[/C][C]0.356635315903175[/C][/ROW]
[ROW][C]78[/C][C]0.621899098945926[/C][C]0.756201802108148[/C][C]0.378100901054074[/C][/ROW]
[ROW][C]79[/C][C]0.626463793264194[/C][C]0.747072413471612[/C][C]0.373536206735806[/C][/ROW]
[ROW][C]80[/C][C]0.586556325421876[/C][C]0.826887349156247[/C][C]0.413443674578124[/C][/ROW]
[ROW][C]81[/C][C]0.550754761816187[/C][C]0.898490476367626[/C][C]0.449245238183813[/C][/ROW]
[ROW][C]82[/C][C]0.513169598208466[/C][C]0.973660803583068[/C][C]0.486830401791534[/C][/ROW]
[ROW][C]83[/C][C]0.480834321515982[/C][C]0.961668643031964[/C][C]0.519165678484018[/C][/ROW]
[ROW][C]84[/C][C]0.442012844470168[/C][C]0.884025688940337[/C][C]0.557987155529832[/C][/ROW]
[ROW][C]85[/C][C]0.430425397720146[/C][C]0.860850795440291[/C][C]0.569574602279854[/C][/ROW]
[ROW][C]86[/C][C]0.391470277525738[/C][C]0.782940555051477[/C][C]0.608529722474262[/C][/ROW]
[ROW][C]87[/C][C]0.357646116924776[/C][C]0.715292233849553[/C][C]0.642353883075224[/C][/ROW]
[ROW][C]88[/C][C]0.339886649257135[/C][C]0.679773298514271[/C][C]0.660113350742865[/C][/ROW]
[ROW][C]89[/C][C]0.307332046176806[/C][C]0.614664092353612[/C][C]0.692667953823194[/C][/ROW]
[ROW][C]90[/C][C]0.294578909078641[/C][C]0.589157818157282[/C][C]0.705421090921359[/C][/ROW]
[ROW][C]91[/C][C]0.263240262740977[/C][C]0.526480525481954[/C][C]0.736759737259023[/C][/ROW]
[ROW][C]92[/C][C]0.235974293926126[/C][C]0.471948587852252[/C][C]0.764025706073874[/C][/ROW]
[ROW][C]93[/C][C]0.208768275507393[/C][C]0.417536551014785[/C][C]0.791231724492607[/C][/ROW]
[ROW][C]94[/C][C]0.218197058168412[/C][C]0.436394116336824[/C][C]0.781802941831588[/C][/ROW]
[ROW][C]95[/C][C]0.197603918939357[/C][C]0.395207837878715[/C][C]0.802396081060643[/C][/ROW]
[ROW][C]96[/C][C]0.171976484261225[/C][C]0.34395296852245[/C][C]0.828023515738775[/C][/ROW]
[ROW][C]97[/C][C]0.170697824463511[/C][C]0.341395648927022[/C][C]0.829302175536489[/C][/ROW]
[ROW][C]98[/C][C]0.146897344180304[/C][C]0.293794688360607[/C][C]0.853102655819696[/C][/ROW]
[ROW][C]99[/C][C]0.127308325102842[/C][C]0.254616650205683[/C][C]0.872691674897158[/C][/ROW]
[ROW][C]100[/C][C]0.114909435547072[/C][C]0.229818871094145[/C][C]0.885090564452928[/C][/ROW]
[ROW][C]101[/C][C]0.103514727279105[/C][C]0.20702945455821[/C][C]0.896485272720895[/C][/ROW]
[ROW][C]102[/C][C]0.122156313391891[/C][C]0.244312626783781[/C][C]0.877843686608109[/C][/ROW]
[ROW][C]103[/C][C]0.103742443691259[/C][C]0.207484887382519[/C][C]0.89625755630874[/C][/ROW]
[ROW][C]104[/C][C]0.0981479885136099[/C][C]0.19629597702722[/C][C]0.90185201148639[/C][/ROW]
[ROW][C]105[/C][C]0.111871343524145[/C][C]0.223742687048291[/C][C]0.888128656475855[/C][/ROW]
[ROW][C]106[/C][C]0.100214763723445[/C][C]0.200429527446889[/C][C]0.899785236276555[/C][/ROW]
[ROW][C]107[/C][C]0.0876906513353272[/C][C]0.175381302670654[/C][C]0.912309348664673[/C][/ROW]
[ROW][C]108[/C][C]0.0843840951136196[/C][C]0.168768190227239[/C][C]0.91561590488638[/C][/ROW]
[ROW][C]109[/C][C]0.0770797105229302[/C][C]0.15415942104586[/C][C]0.92292028947707[/C][/ROW]
[ROW][C]110[/C][C]0.068319054736474[/C][C]0.136638109472948[/C][C]0.931680945263526[/C][/ROW]
[ROW][C]111[/C][C]0.0581785809991711[/C][C]0.116357161998342[/C][C]0.941821419000829[/C][/ROW]
[ROW][C]112[/C][C]0.066784725908587[/C][C]0.133569451817174[/C][C]0.933215274091413[/C][/ROW]
[ROW][C]113[/C][C]0.0574081567541782[/C][C]0.114816313508356[/C][C]0.942591843245822[/C][/ROW]
[ROW][C]114[/C][C]0.0691680949402302[/C][C]0.13833618988046[/C][C]0.93083190505977[/C][/ROW]
[ROW][C]115[/C][C]0.0669146542744664[/C][C]0.133829308548933[/C][C]0.933085345725534[/C][/ROW]
[ROW][C]116[/C][C]0.0591111191038087[/C][C]0.118222238207617[/C][C]0.940888880896191[/C][/ROW]
[ROW][C]117[/C][C]0.054589505859749[/C][C]0.109179011719498[/C][C]0.945410494140251[/C][/ROW]
[ROW][C]118[/C][C]0.0534005612170456[/C][C]0.106801122434091[/C][C]0.946599438782954[/C][/ROW]
[ROW][C]119[/C][C]0.0518845574637998[/C][C]0.1037691149276[/C][C]0.9481154425362[/C][/ROW]
[ROW][C]120[/C][C]0.0443377002697415[/C][C]0.088675400539483[/C][C]0.955662299730259[/C][/ROW]
[ROW][C]121[/C][C]0.0384679182011819[/C][C]0.0769358364023637[/C][C]0.961532081798818[/C][/ROW]
[ROW][C]122[/C][C]0.0462813555623264[/C][C]0.0925627111246528[/C][C]0.953718644437674[/C][/ROW]
[ROW][C]123[/C][C]0.0389256393686864[/C][C]0.0778512787373728[/C][C]0.961074360631314[/C][/ROW]
[ROW][C]124[/C][C]0.0334891430201009[/C][C]0.0669782860402018[/C][C]0.966510856979899[/C][/ROW]
[ROW][C]125[/C][C]0.0277446614031485[/C][C]0.055489322806297[/C][C]0.972255338596852[/C][/ROW]
[ROW][C]126[/C][C]0.0222956117433738[/C][C]0.0445912234867477[/C][C]0.977704388256626[/C][/ROW]
[ROW][C]127[/C][C]0.0216849028989381[/C][C]0.0433698057978763[/C][C]0.978315097101062[/C][/ROW]
[ROW][C]128[/C][C]0.0201508697043367[/C][C]0.0403017394086734[/C][C]0.979849130295663[/C][/ROW]
[ROW][C]129[/C][C]0.0234295980753794[/C][C]0.0468591961507588[/C][C]0.976570401924621[/C][/ROW]
[ROW][C]130[/C][C]0.025105485853533[/C][C]0.0502109717070661[/C][C]0.974894514146467[/C][/ROW]
[ROW][C]131[/C][C]0.0341493871030383[/C][C]0.0682987742060766[/C][C]0.965850612896962[/C][/ROW]
[ROW][C]132[/C][C]0.045527719462717[/C][C]0.0910554389254339[/C][C]0.954472280537283[/C][/ROW]
[ROW][C]133[/C][C]0.0455418666578374[/C][C]0.0910837333156748[/C][C]0.954458133342163[/C][/ROW]
[ROW][C]134[/C][C]0.0401102137148492[/C][C]0.0802204274296985[/C][C]0.959889786285151[/C][/ROW]
[ROW][C]135[/C][C]0.0333855393462406[/C][C]0.0667710786924813[/C][C]0.966614460653759[/C][/ROW]
[ROW][C]136[/C][C]0.0291114393918267[/C][C]0.0582228787836534[/C][C]0.970888560608173[/C][/ROW]
[ROW][C]137[/C][C]0.0255955956612382[/C][C]0.0511911913224764[/C][C]0.974404404338762[/C][/ROW]
[ROW][C]138[/C][C]0.0278357397364552[/C][C]0.0556714794729104[/C][C]0.972164260263545[/C][/ROW]
[ROW][C]139[/C][C]0.0239276578752558[/C][C]0.0478553157505117[/C][C]0.976072342124744[/C][/ROW]
[ROW][C]140[/C][C]0.0318433037693262[/C][C]0.0636866075386523[/C][C]0.968156696230674[/C][/ROW]
[ROW][C]141[/C][C]0.0406557182287072[/C][C]0.0813114364574143[/C][C]0.959344281771293[/C][/ROW]
[ROW][C]142[/C][C]0.0388354923595057[/C][C]0.0776709847190113[/C][C]0.961164507640494[/C][/ROW]
[ROW][C]143[/C][C]0.0319513006387704[/C][C]0.0639026012775409[/C][C]0.96804869936123[/C][/ROW]
[ROW][C]144[/C][C]0.028266723951582[/C][C]0.056533447903164[/C][C]0.971733276048418[/C][/ROW]
[ROW][C]145[/C][C]0.0455787472975125[/C][C]0.0911574945950251[/C][C]0.954421252702487[/C][/ROW]
[ROW][C]146[/C][C]0.0550820014967776[/C][C]0.110164002993555[/C][C]0.944917998503222[/C][/ROW]
[ROW][C]147[/C][C]0.0683606260914233[/C][C]0.136721252182847[/C][C]0.931639373908577[/C][/ROW]
[ROW][C]148[/C][C]0.0587190839758405[/C][C]0.117438167951681[/C][C]0.94128091602416[/C][/ROW]
[ROW][C]149[/C][C]0.0493224508732781[/C][C]0.0986449017465562[/C][C]0.950677549126722[/C][/ROW]
[ROW][C]150[/C][C]0.0659503884737645[/C][C]0.131900776947529[/C][C]0.934049611526236[/C][/ROW]
[ROW][C]151[/C][C]0.0592835602159287[/C][C]0.118567120431857[/C][C]0.940716439784071[/C][/ROW]
[ROW][C]152[/C][C]0.0607344049057952[/C][C]0.12146880981159[/C][C]0.939265595094205[/C][/ROW]
[ROW][C]153[/C][C]0.0799299081102157[/C][C]0.159859816220431[/C][C]0.920070091889784[/C][/ROW]
[ROW][C]154[/C][C]0.0697281116955254[/C][C]0.139456223391051[/C][C]0.930271888304475[/C][/ROW]
[ROW][C]155[/C][C]0.0678997073161252[/C][C]0.13579941463225[/C][C]0.932100292683875[/C][/ROW]
[ROW][C]156[/C][C]0.0569817198556673[/C][C]0.113963439711335[/C][C]0.943018280144333[/C][/ROW]
[ROW][C]157[/C][C]0.0496549996959829[/C][C]0.0993099993919658[/C][C]0.950345000304017[/C][/ROW]
[ROW][C]158[/C][C]0.0421839837097659[/C][C]0.0843679674195317[/C][C]0.957816016290234[/C][/ROW]
[ROW][C]159[/C][C]0.0351699360270701[/C][C]0.0703398720541403[/C][C]0.96483006397293[/C][/ROW]
[ROW][C]160[/C][C]0.028584231618283[/C][C]0.0571684632365659[/C][C]0.971415768381717[/C][/ROW]
[ROW][C]161[/C][C]0.023005623820991[/C][C]0.046011247641982[/C][C]0.976994376179009[/C][/ROW]
[ROW][C]162[/C][C]0.0183327574581663[/C][C]0.0366655149163326[/C][C]0.981667242541834[/C][/ROW]
[ROW][C]163[/C][C]0.0145715584894567[/C][C]0.0291431169789135[/C][C]0.985428441510543[/C][/ROW]
[ROW][C]164[/C][C]0.0119419208509944[/C][C]0.0238838417019888[/C][C]0.988058079149006[/C][/ROW]
[ROW][C]165[/C][C]0.0095307382721275[/C][C]0.019061476544255[/C][C]0.990469261727873[/C][/ROW]
[ROW][C]166[/C][C]0.00965105037803897[/C][C]0.0193021007560779[/C][C]0.990348949621961[/C][/ROW]
[ROW][C]167[/C][C]0.00748160713850012[/C][C]0.0149632142770002[/C][C]0.9925183928615[/C][/ROW]
[ROW][C]168[/C][C]0.00802810469021809[/C][C]0.0160562093804362[/C][C]0.991971895309782[/C][/ROW]
[ROW][C]169[/C][C]0.00734008202786129[/C][C]0.0146801640557226[/C][C]0.992659917972139[/C][/ROW]
[ROW][C]170[/C][C]0.00595684872788804[/C][C]0.0119136974557761[/C][C]0.994043151272112[/C][/ROW]
[ROW][C]171[/C][C]0.00697948697363136[/C][C]0.0139589739472627[/C][C]0.993020513026369[/C][/ROW]
[ROW][C]172[/C][C]0.00540801289874016[/C][C]0.0108160257974803[/C][C]0.99459198710126[/C][/ROW]
[ROW][C]173[/C][C]0.00428839569225053[/C][C]0.00857679138450106[/C][C]0.99571160430775[/C][/ROW]
[ROW][C]174[/C][C]0.00423645009044183[/C][C]0.00847290018088365[/C][C]0.995763549909558[/C][/ROW]
[ROW][C]175[/C][C]0.00423120916071292[/C][C]0.00846241832142584[/C][C]0.995768790839287[/C][/ROW]
[ROW][C]176[/C][C]0.0035021759515334[/C][C]0.00700435190306679[/C][C]0.996497824048467[/C][/ROW]
[ROW][C]177[/C][C]0.00261941166355747[/C][C]0.00523882332711494[/C][C]0.997380588336442[/C][/ROW]
[ROW][C]178[/C][C]0.00210580888372582[/C][C]0.00421161776745164[/C][C]0.997894191116274[/C][/ROW]
[ROW][C]179[/C][C]0.00161645289068689[/C][C]0.00323290578137379[/C][C]0.998383547109313[/C][/ROW]
[ROW][C]180[/C][C]0.00139131934826092[/C][C]0.00278263869652184[/C][C]0.998608680651739[/C][/ROW]
[ROW][C]181[/C][C]0.00109417617304527[/C][C]0.00218835234609055[/C][C]0.998905823826955[/C][/ROW]
[ROW][C]182[/C][C]0.000793506734611876[/C][C]0.00158701346922375[/C][C]0.999206493265388[/C][/ROW]
[ROW][C]183[/C][C]0.000784705473104853[/C][C]0.00156941094620971[/C][C]0.999215294526895[/C][/ROW]
[ROW][C]184[/C][C]0.000579880710362991[/C][C]0.00115976142072598[/C][C]0.999420119289637[/C][/ROW]
[ROW][C]185[/C][C]0.0168208641147177[/C][C]0.0336417282294353[/C][C]0.983179135885282[/C][/ROW]
[ROW][C]186[/C][C]0.0143774382629088[/C][C]0.0287548765258175[/C][C]0.985622561737091[/C][/ROW]
[ROW][C]187[/C][C]0.0169893865571043[/C][C]0.0339787731142087[/C][C]0.983010613442896[/C][/ROW]
[ROW][C]188[/C][C]0.0133777597333176[/C][C]0.0267555194666352[/C][C]0.986622240266682[/C][/ROW]
[ROW][C]189[/C][C]0.0113163515161694[/C][C]0.0226327030323388[/C][C]0.988683648483831[/C][/ROW]
[ROW][C]190[/C][C]0.00896456676155344[/C][C]0.0179291335231069[/C][C]0.991035433238447[/C][/ROW]
[ROW][C]191[/C][C]0.0079047966450284[/C][C]0.0158095932900568[/C][C]0.992095203354972[/C][/ROW]
[ROW][C]192[/C][C]0.00610213021328697[/C][C]0.0122042604265739[/C][C]0.993897869786713[/C][/ROW]
[ROW][C]193[/C][C]0.00560855236725542[/C][C]0.0112171047345108[/C][C]0.994391447632745[/C][/ROW]
[ROW][C]194[/C][C]0.00487378805682457[/C][C]0.00974757611364914[/C][C]0.995126211943175[/C][/ROW]
[ROW][C]195[/C][C]0.00396489668982123[/C][C]0.00792979337964246[/C][C]0.996035103310179[/C][/ROW]
[ROW][C]196[/C][C]0.00289780420419282[/C][C]0.00579560840838564[/C][C]0.997102195795807[/C][/ROW]
[ROW][C]197[/C][C]0.00397174245770266[/C][C]0.00794348491540531[/C][C]0.996028257542297[/C][/ROW]
[ROW][C]198[/C][C]0.00289820385376601[/C][C]0.00579640770753203[/C][C]0.997101796146234[/C][/ROW]
[ROW][C]199[/C][C]0.00244658860185033[/C][C]0.00489317720370067[/C][C]0.99755341139815[/C][/ROW]
[ROW][C]200[/C][C]0.00205378438038511[/C][C]0.00410756876077021[/C][C]0.997946215619615[/C][/ROW]
[ROW][C]201[/C][C]0.0018114920461491[/C][C]0.0036229840922982[/C][C]0.998188507953851[/C][/ROW]
[ROW][C]202[/C][C]0.00138944110369551[/C][C]0.00277888220739102[/C][C]0.998610558896304[/C][/ROW]
[ROW][C]203[/C][C]0.00166339588968988[/C][C]0.00332679177937976[/C][C]0.99833660411031[/C][/ROW]
[ROW][C]204[/C][C]0.0026458115906453[/C][C]0.00529162318129061[/C][C]0.997354188409355[/C][/ROW]
[ROW][C]205[/C][C]0.00264013650507319[/C][C]0.00528027301014639[/C][C]0.997359863494927[/C][/ROW]
[ROW][C]206[/C][C]0.00188058387268832[/C][C]0.00376116774537664[/C][C]0.998119416127312[/C][/ROW]
[ROW][C]207[/C][C]0.00152157636537545[/C][C]0.00304315273075089[/C][C]0.998478423634625[/C][/ROW]
[ROW][C]208[/C][C]0.00107857181716888[/C][C]0.00215714363433776[/C][C]0.998921428182831[/C][/ROW]
[ROW][C]209[/C][C]0.00137886143694701[/C][C]0.00275772287389403[/C][C]0.998621138563053[/C][/ROW]
[ROW][C]210[/C][C]0.00103622428384543[/C][C]0.00207244856769087[/C][C]0.998963775716155[/C][/ROW]
[ROW][C]211[/C][C]0.00132384287287792[/C][C]0.00264768574575585[/C][C]0.998676157127122[/C][/ROW]
[ROW][C]212[/C][C]0.00403249752394389[/C][C]0.00806499504788777[/C][C]0.995967502476056[/C][/ROW]
[ROW][C]213[/C][C]0.00280390683500934[/C][C]0.00560781367001868[/C][C]0.997196093164991[/C][/ROW]
[ROW][C]214[/C][C]0.00370430424015279[/C][C]0.00740860848030558[/C][C]0.996295695759847[/C][/ROW]
[ROW][C]215[/C][C]0.00282967053901741[/C][C]0.00565934107803482[/C][C]0.997170329460983[/C][/ROW]
[ROW][C]216[/C][C]0.00203020200574762[/C][C]0.00406040401149524[/C][C]0.997969797994252[/C][/ROW]
[ROW][C]217[/C][C]0.00216560328630247[/C][C]0.00433120657260494[/C][C]0.997834396713698[/C][/ROW]
[ROW][C]218[/C][C]0.00167963705990032[/C][C]0.00335927411980064[/C][C]0.9983203629401[/C][/ROW]
[ROW][C]219[/C][C]0.00146345920615216[/C][C]0.00292691841230431[/C][C]0.998536540793848[/C][/ROW]
[ROW][C]220[/C][C]0.00100758808543027[/C][C]0.00201517617086054[/C][C]0.99899241191457[/C][/ROW]
[ROW][C]221[/C][C]0.000737995161715393[/C][C]0.00147599032343079[/C][C]0.999262004838285[/C][/ROW]
[ROW][C]222[/C][C]0.000474872377526651[/C][C]0.000949744755053302[/C][C]0.999525127622473[/C][/ROW]
[ROW][C]223[/C][C]0.000323486909106705[/C][C]0.000646973818213409[/C][C]0.999676513090893[/C][/ROW]
[ROW][C]224[/C][C]0.000218725612292476[/C][C]0.000437451224584953[/C][C]0.999781274387707[/C][/ROW]
[ROW][C]225[/C][C]0.000132904327453964[/C][C]0.000265808654907928[/C][C]0.999867095672546[/C][/ROW]
[ROW][C]226[/C][C]0.00034500131670398[/C][C]0.000690002633407961[/C][C]0.999654998683296[/C][/ROW]
[ROW][C]227[/C][C]0.000240104335768236[/C][C]0.000480208671536472[/C][C]0.999759895664232[/C][/ROW]
[ROW][C]228[/C][C]0.000149924611790226[/C][C]0.000299849223580452[/C][C]0.99985007538821[/C][/ROW]
[ROW][C]229[/C][C]9.76700348352576e-05[/C][C]0.000195340069670515[/C][C]0.999902329965165[/C][/ROW]
[ROW][C]230[/C][C]5.8442096056655e-05[/C][C]0.00011688419211331[/C][C]0.999941557903943[/C][/ROW]
[ROW][C]231[/C][C]6.14139037689169e-05[/C][C]0.000122827807537834[/C][C]0.999938586096231[/C][/ROW]
[ROW][C]232[/C][C]0.000281736732812232[/C][C]0.000563473465624463[/C][C]0.999718263267188[/C][/ROW]
[ROW][C]233[/C][C]0.0014008611783211[/C][C]0.00280172235664219[/C][C]0.998599138821679[/C][/ROW]
[ROW][C]234[/C][C]0.00228974094929837[/C][C]0.00457948189859675[/C][C]0.997710259050702[/C][/ROW]
[ROW][C]235[/C][C]0.00133784764113805[/C][C]0.0026756952822761[/C][C]0.998662152358862[/C][/ROW]
[ROW][C]236[/C][C]0.000873597338241585[/C][C]0.00174719467648317[/C][C]0.999126402661758[/C][/ROW]
[ROW][C]237[/C][C]0.019180914012955[/C][C]0.0383618280259099[/C][C]0.980819085987045[/C][/ROW]
[ROW][C]238[/C][C]0.0116537111785716[/C][C]0.0233074223571433[/C][C]0.988346288821428[/C][/ROW]
[ROW][C]239[/C][C]0.00794413414283288[/C][C]0.0158882682856658[/C][C]0.992055865857167[/C][/ROW]
[ROW][C]240[/C][C]0.00453614482226409[/C][C]0.00907228964452817[/C][C]0.995463855177736[/C][/ROW]
[ROW][C]241[/C][C]0.00312583339726638[/C][C]0.00625166679453277[/C][C]0.996874166602734[/C][/ROW]
[ROW][C]242[/C][C]0.00511790268749582[/C][C]0.0102358053749916[/C][C]0.994882097312504[/C][/ROW]
[ROW][C]243[/C][C]0.00293062144810694[/C][C]0.00586124289621389[/C][C]0.997069378551893[/C][/ROW]
[ROW][C]244[/C][C]0.00212476806185606[/C][C]0.00424953612371212[/C][C]0.997875231938144[/C][/ROW]
[ROW][C]245[/C][C]0.00111381482442249[/C][C]0.00222762964884497[/C][C]0.998886185175577[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185728&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185728&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
190.998342410934830.003315178130339930.00165758906516997
200.9959061174629930.008187765074013330.00409388253700666
210.9908262820651740.01834743586965290.00917371793482643
220.984925087703940.03014982459211960.0150749122960598
230.9773700103639870.04525997927202560.0226299896360128
240.9685847877411850.06283042451763050.0314152122588153
250.950494221430680.09901155713864070.0495057785693203
260.9300800538382360.1398398923235270.0699199461617637
270.9013016563254870.1973966873490270.0986983436745133
280.9129317320350440.1741365359299120.0870682679649558
290.8806837015055060.2386325969889890.119316298494494
300.8772128846867040.2455742306265930.122787115313296
310.8436563490209620.3126873019580760.156343650979038
320.8323304580631710.3353390838736570.167669541936829
330.8122311193400630.3755377613198750.187768880659937
340.7624885774420320.4750228451159360.237511422557968
350.74442019017710.5111596196457990.2555798098229
360.8132881432441340.3734237135117320.186711856755866
370.8531152440272320.2937695119455360.146884755972768
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1940.004873788056824570.009747576113649140.995126211943175
1950.003964896689821230.007929793379642460.996035103310179
1960.002897804204192820.005795608408385640.997102195795807
1970.003971742457702660.007943484915405310.996028257542297
1980.002898203853766010.005796407707532030.997101796146234
1990.002446588601850330.004893177203700670.99755341139815
2000.002053784380385110.004107568760770210.997946215619615
2010.00181149204614910.00362298409229820.998188507953851
2020.001389441103695510.002778882207391020.998610558896304
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2100.001036224283845430.002072448567690870.998963775716155
2110.001323842872877920.002647685745755850.998676157127122
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2450.001113814824422490.002227629648844970.998886185175577







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level620.273127753303965NOK
5% type I error level950.418502202643172NOK
10% type I error level1230.541850220264317NOK

\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 & 62 & 0.273127753303965 & NOK \tabularnewline
5% type I error level & 95 & 0.418502202643172 & NOK \tabularnewline
10% type I error level & 123 & 0.541850220264317 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185728&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]62[/C][C]0.273127753303965[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]95[/C][C]0.418502202643172[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]123[/C][C]0.541850220264317[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185728&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185728&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level620.273127753303965NOK
5% type I error level950.418502202643172NOK
10% type I error level1230.541850220264317NOK



Parameters (Session):
par1 = 3 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 8 ; 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')
}