Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareMultiple Regression
Date of computationThu, 20 Dec 2012 05:12:46 -0500
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/Dec/20/t135599837853zwfa6rt5d1viu.htm/, Retrieved Tue, 09 Aug 2022 20:05:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=202578, Retrieved Tue, 09 Aug 2022 20:05:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81
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]
- R  D  [Multiple Regression] [] [2012-11-03 10:00:51] [391561951b5d7f721cfaa4f5575ab127]
-  M        [Multiple Regression] [] [2012-12-20 10:12:46] [7338cd26db379c04f0557b08db763c32] [Current]
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Dataseries X:
1	1	1	41	41	38	38	13	12	12	14	14	53	53
1	2	2	39	39	32	32	16	11	11	18	18	83	83
1	3	3	30	30	35	35	19	15	15	11	11	66	66
1	4	4	31	31	33	33	15	6	6	12	12	67	67
1	5	5	34	34	37	37	14	13	13	16	16	76	76
1	6	6	35	35	29	29	13	10	10	18	18	78	78
1	7	7	39	39	31	31	19	12	12	14	14	53	53
1	8	8	34	34	36	36	15	14	14	14	14	80	80
1	9	9	36	36	35	35	14	12	12	15	15	74	74
1	10	10	37	37	38	38	15	9	9	15	15	76	76
1	11	11	38	38	31	31	16	10	10	17	17	79	79
1	12	12	36	36	34	34	16	12	12	19	19	54	54
1	13	13	38	38	35	35	16	12	12	10	10	67	67
1	14	14	39	39	38	38	16	11	11	16	16	54	54
1	15	15	33	33	37	37	17	15	15	18	18	87	87
1	16	16	32	32	33	33	15	12	12	14	14	58	58
1	17	17	36	36	32	32	15	10	10	14	14	75	75
1	18	18	38	38	38	38	20	12	12	17	17	88	88
1	19	19	39	39	38	38	18	11	11	14	14	64	64
1	20	20	32	32	32	32	16	12	12	16	16	57	57
1	21	21	32	32	33	33	16	11	11	18	18	66	66
1	22	22	31	31	31	31	16	12	12	11	11	68	68
1	23	23	39	39	38	38	19	13	13	14	14	54	54
1	24	24	37	37	39	39	16	11	11	12	12	56	56
1	25	25	39	39	32	32	17	12	12	17	17	86	86
1	26	26	41	41	32	32	17	13	13	9	9	80	80
1	27	27	36	36	35	35	16	10	10	16	16	76	76
1	28	28	33	33	37	37	15	14	14	14	14	69	69
1	29	29	33	33	33	33	16	12	12	15	15	78	78
1	30	30	34	34	33	33	14	10	10	11	11	67	67
1	31	31	31	31	31	31	15	12	12	16	16	80	80
1	32	32	27	27	32	32	12	8	8	13	13	54	54
1	33	33	37	37	31	31	14	10	10	17	17	71	71
1	34	34	34	34	37	37	16	12	12	15	15	84	84
1	35	35	34	34	30	30	14	12	12	14	14	74	74
1	36	36	32	32	33	33	10	7	7	16	16	71	71
1	37	37	29	29	31	31	10	9	9	9	9	63	63
1	38	38	36	36	33	33	14	12	12	15	15	71	71
1	39	39	29	29	31	31	16	10	10	17	17	76	76
1	40	40	35	35	33	33	16	10	10	13	13	69	69
1	41	41	37	37	32	32	16	10	10	15	15	74	74
1	42	42	34	34	33	33	14	12	12	16	16	75	75
1	43	43	38	38	32	32	20	15	15	16	16	54	54
1	44	44	35	35	33	33	14	10	10	12	12	52	52
1	45	45	38	38	28	28	14	10	10	15	15	69	69
1	46	46	37	37	35	35	11	12	12	11	11	68	68
1	47	47	38	38	39	39	14	13	13	15	15	65	65
1	48	48	33	33	34	34	15	11	11	15	15	75	75
1	49	49	36	36	38	38	16	11	11	17	17	74	74
1	50	50	38	38	32	32	14	12	12	13	13	75	75
1	51	51	32	32	38	38	16	14	14	16	16	72	72
1	52	52	32	32	30	30	14	10	10	14	14	67	67
1	53	53	32	32	33	33	12	12	12	11	11	63	63
1	54	54	34	34	38	38	16	13	13	12	12	62	62
1	55	55	32	32	32	32	9	5	5	12	12	63	63
1	56	56	37	37	35	35	14	6	6	15	15	76	76
1	57	57	39	39	34	34	16	12	12	16	16	74	74
1	58	58	29	29	34	34	16	12	12	15	15	67	67
1	59	59	37	37	36	36	15	11	11	12	12	73	73
1	60	60	35	35	34	34	16	10	10	12	12	70	70
1	61	61	30	30	28	28	12	7	7	8	8	53	53
1	62	62	38	38	34	34	16	12	12	13	13	77	77
1	63	63	34	34	35	35	16	14	14	11	11	80	80
1	64	64	31	31	35	35	14	11	11	14	14	52	52
1	65	65	34	34	31	31	16	12	12	15	15	54	54
1	66	66	35	35	37	37	17	13	13	10	10	80	80
1	67	67	36	36	35	35	18	14	14	11	11	66	66
1	68	68	30	30	27	27	18	11	11	12	12	73	73
1	69	69	39	39	40	40	12	12	12	15	15	63	63
1	70	70	35	35	37	37	16	12	12	15	15	69	69
1	71	71	38	38	36	36	10	8	8	14	14	67	67
1	72	72	31	31	38	38	14	11	11	16	16	54	54
1	73	73	34	34	39	39	18	14	14	15	15	81	81
1	74	74	38	38	41	41	18	14	14	15	15	69	69
1	75	75	34	34	27	27	16	12	12	13	13	84	84
1	76	76	39	39	30	30	17	9	9	12	12	80	80
1	77	77	37	37	37	37	16	13	13	17	17	70	70
1	78	78	34	34	31	31	16	11	11	13	13	69	69
1	79	79	28	28	31	31	13	12	12	15	15	77	77
1	80	80	37	37	27	27	16	12	12	13	13	54	54
1	81	81	33	33	36	36	16	12	12	15	15	79	79
1	82	82	35	35	37	37	16	12	12	15	15	71	71
1	83	83	37	37	33	33	15	12	12	16	16	73	73
1	84	84	32	32	34	34	15	11	11	15	15	72	72
1	85	85	33	33	31	31	16	10	10	14	14	77	77
1	86	86	38	38	39	39	14	9	9	15	15	75	75
1	87	87	33	33	34	34	16	12	12	14	14	69	69
1	88	88	29	29	32	32	16	12	12	13	13	54	54
1	89	89	33	33	33	33	15	12	12	7	7	70	70
1	90	90	31	31	36	36	12	9	9	17	17	73	73
1	91	91	36	36	32	32	17	15	15	13	13	54	54
1	92	92	35	35	41	41	16	12	12	15	15	77	77
1	93	93	32	32	28	28	15	12	12	14	14	82	82
1	94	94	29	29	30	30	13	12	12	13	13	80	80
1	95	95	39	39	36	36	16	10	10	16	16	80	80
1	96	96	37	37	35	35	16	13	13	12	12	69	69
1	97	97	35	35	31	31	16	9	9	14	14	78	78
1	98	98	37	37	34	34	16	12	12	17	17	81	81
1	99	99	32	32	36	36	14	10	10	15	15	76	76
1	100	100	38	38	36	36	16	14	14	17	17	76	76
1	101	101	37	37	35	35	16	11	11	12	12	73	73
1	102	102	36	36	37	37	20	15	15	16	16	85	85
1	103	103	32	32	28	28	15	11	11	11	11	66	66
1	104	104	33	33	39	39	16	11	11	15	15	79	79
1	105	105	40	40	32	32	13	12	12	9	9	68	68
1	106	106	38	38	35	35	17	12	12	16	16	76	76
1	107	107	41	41	39	39	16	12	12	15	15	71	71
1	108	108	36	36	35	35	16	11	11	10	10	54	54
1	109	109	43	43	42	42	12	7	7	10	10	46	46
1	110	110	30	30	34	34	16	12	12	15	15	85	85
1	111	111	31	31	33	33	16	14	14	11	11	74	74
1	112	112	32	32	41	41	17	11	11	13	13	88	88
1	113	113	32	32	33	33	13	11	11	14	14	38	38
1	114	114	37	37	34	34	12	10	10	18	18	76	76
1	115	115	37	37	32	32	18	13	13	16	16	86	86
1	116	116	33	33	40	40	14	13	13	14	14	54	54
1	117	117	34	34	40	40	14	8	8	14	14	67	67
1	118	118	33	33	35	35	13	11	11	14	14	69	69
1	119	119	38	38	36	36	16	12	12	14	14	90	90
1	120	120	33	33	37	37	13	11	11	12	12	54	54
1	121	121	31	31	27	27	16	13	13	14	14	76	76
1	122	122	38	38	39	39	13	12	12	15	15	89	89
1	123	123	37	37	38	38	16	14	14	15	15	76	76
1	124	124	36	36	31	31	15	13	13	15	15	73	73
1	125	125	31	31	33	33	16	15	15	13	13	79	79
1	126	126	39	39	32	32	15	10	10	17	17	90	90
1	127	127	44	44	39	39	17	11	11	17	17	74	74
1	128	128	33	33	36	36	15	9	9	19	19	81	81
1	129	129	35	35	33	33	12	11	11	15	15	72	72
1	130	130	32	32	33	33	16	10	10	13	13	71	71
1	131	131	28	28	32	32	10	11	11	9	9	66	66
1	132	132	40	40	37	37	16	8	8	15	15	77	77
1	133	133	27	27	30	30	12	11	11	15	15	65	65
1	134	134	37	37	38	38	14	12	12	15	15	74	74
1	135	135	32	32	29	29	15	12	12	16	16	85	85
1	136	136	28	28	22	22	13	9	9	11	11	54	54
1	137	137	34	34	35	35	15	11	11	14	14	63	63
1	138	138	30	30	35	35	11	10	10	11	11	54	54
1	139	139	35	35	34	34	12	8	8	15	15	64	64
1	140	140	31	31	35	35	11	9	9	13	13	69	69
1	141	141	32	32	34	34	16	8	8	15	15	54	54
1	142	142	30	30	37	37	15	9	9	16	16	84	84
1	143	143	30	30	35	35	17	15	15	14	14	86	86
1	144	144	31	31	23	23	16	11	11	15	15	77	77
1	145	145	40	40	31	31	10	8	8	16	16	89	89
1	146	146	32	32	27	27	18	13	13	16	16	76	76
1	147	147	36	36	36	36	13	12	12	11	11	60	60
1	148	148	32	32	31	31	16	12	12	12	12	75	75
1	149	149	35	35	32	32	13	9	9	9	9	73	73
1	150	150	38	38	39	39	10	7	7	16	16	85	85
1	151	151	42	42	37	37	15	13	13	13	13	79	79
1	152	152	34	34	38	38	16	9	9	16	16	71	71
1	153	153	35	35	39	39	16	6	6	12	12	72	72
1	154	154	38	38	34	34	14	8	8	9	9	69	69
1	155	155	33	33	31	31	10	8	8	13	13	78	78
1	156	156	36	36	32	32	17	15	15	13	13	54	54
1	157	157	32	32	37	37	13	6	6	14	14	69	69
1	158	158	33	33	36	36	15	9	9	19	19	81	81
1	159	159	34	34	32	32	16	11	11	13	13	84	84
1	160	160	32	32	38	38	12	8	8	12	12	84	84
1	161	161	34	34	36	36	13	8	8	13	13	69	69
0	162	0	27	0	26	0	13	10	0	10	0	66	0
0	163	0	31	0	26	0	12	8	0	14	0	81	0
0	164	0	38	0	33	0	17	14	0	16	0	82	0
0	165	0	34	0	39	0	15	10	0	10	0	72	0
0	166	0	24	0	30	0	10	8	0	11	0	54	0
0	167	0	30	0	33	0	14	11	0	14	0	78	0
0	168	0	26	0	25	0	11	12	0	12	0	74	0
0	169	0	34	0	38	0	13	12	0	9	0	82	0
0	170	0	27	0	37	0	16	12	0	9	0	73	0
0	171	0	37	0	31	0	12	5	0	11	0	55	0
0	172	0	36	0	37	0	16	12	0	16	0	72	0
0	173	0	41	0	35	0	12	10	0	9	0	78	0
0	174	0	29	0	25	0	9	7	0	13	0	59	0
0	175	0	36	0	28	0	12	12	0	16	0	72	0
0	176	0	32	0	35	0	15	11	0	13	0	78	0
0	177	0	37	0	33	0	12	8	0	9	0	68	0
0	178	0	30	0	30	0	12	9	0	12	0	69	0
0	179	0	31	0	31	0	14	10	0	16	0	67	0
0	180	0	38	0	37	0	12	9	0	11	0	74	0
0	181	0	36	0	36	0	16	12	0	14	0	54	0
0	182	0	35	0	30	0	11	6	0	13	0	67	0
0	183	0	31	0	36	0	19	15	0	15	0	70	0
0	184	0	38	0	32	0	15	12	0	14	0	80	0
0	185	0	22	0	28	0	8	12	0	16	0	89	0
0	186	0	32	0	36	0	16	12	0	13	0	76	0
0	187	0	36	0	34	0	17	11	0	14	0	74	0
0	188	0	39	0	31	0	12	7	0	15	0	87	0
0	189	0	28	0	28	0	11	7	0	13	0	54	0
0	190	0	32	0	36	0	11	5	0	11	0	61	0
0	191	0	32	0	36	0	14	12	0	11	0	38	0
0	192	0	38	0	40	0	16	12	0	14	0	75	0
0	193	0	32	0	33	0	12	3	0	15	0	69	0
0	194	0	35	0	37	0	16	11	0	11	0	62	0
0	195	0	32	0	32	0	13	10	0	15	0	72	0
0	196	0	37	0	38	0	15	12	0	12	0	70	0
0	197	0	34	0	31	0	16	9	0	14	0	79	0
0	198	0	33	0	37	0	16	12	0	14	0	87	0
0	199	0	33	0	33	0	14	9	0	8	0	62	0
0	200	0	26	0	32	0	16	12	0	13	0	77	0
0	201	0	30	0	30	0	16	12	0	9	0	69	0
0	202	0	24	0	30	0	14	10	0	15	0	69	0
0	203	0	34	0	31	0	11	9	0	17	0	75	0
0	204	0	34	0	32	0	12	12	0	13	0	54	0
0	205	0	33	0	34	0	15	8	0	15	0	72	0
0	206	0	34	0	36	0	15	11	0	15	0	74	0
0	207	0	35	0	37	0	16	11	0	14	0	85	0
0	208	0	35	0	36	0	16	12	0	16	0	52	0
0	209	0	36	0	33	0	11	10	0	13	0	70	0
0	210	0	34	0	33	0	15	10	0	16	0	84	0
0	211	0	34	0	33	0	12	12	0	9	0	64	0
0	212	0	41	0	44	0	12	12	0	16	0	84	0
0	213	0	32	0	39	0	15	11	0	11	0	87	0
0	214	0	30	0	32	0	15	8	0	10	0	79	0
0	215	0	35	0	35	0	16	12	0	11	0	67	0
0	216	0	28	0	25	0	14	10	0	15	0	65	0
0	217	0	33	0	35	0	17	11	0	17	0	85	0
0	218	0	39	0	34	0	14	10	0	14	0	83	0
0	219	0	36	0	35	0	13	8	0	8	0	61	0
0	220	0	36	0	39	0	15	12	0	15	0	82	0
0	221	0	35	0	33	0	13	12	0	11	0	76	0
0	222	0	38	0	36	0	14	10	0	16	0	58	0
0	223	0	33	0	32	0	15	12	0	10	0	72	0
0	224	0	31	0	32	0	12	9	0	15	0	72	0
0	225	0	34	0	36	0	13	9	0	9	0	38	0
0	226	0	32	0	36	0	8	6	0	16	0	78	0
0	227	0	31	0	32	0	14	10	0	19	0	54	0
0	228	0	33	0	34	0	14	9	0	12	0	63	0
0	229	0	34	0	33	0	11	9	0	8	0	66	0
0	230	0	34	0	35	0	12	9	0	11	0	70	0
0	231	0	34	0	30	0	13	6	0	14	0	71	0
0	232	0	33	0	38	0	10	10	0	9	0	67	0
0	233	0	32	0	34	0	16	6	0	15	0	58	0
0	234	0	41	0	33	0	18	14	0	13	0	72	0
0	235	0	34	0	32	0	13	10	0	16	0	72	0
0	236	0	36	0	31	0	11	10	0	11	0	70	0
0	237	0	37	0	30	0	4	6	0	12	0	76	0
0	238	0	36	0	27	0	13	12	0	13	0	50	0
0	239	0	29	0	31	0	16	12	0	10	0	72	0
0	240	0	37	0	30	0	10	7	0	11	0	72	0
0	241	0	27	0	32	0	12	8	0	12	0	88	0
0	242	0	35	0	35	0	12	11	0	8	0	53	0
0	243	0	28	0	28	0	10	3	0	12	0	58	0
0	244	0	35	0	33	0	13	6	0	12	0	66	0
0	245	0	37	0	31	0	15	10	0	15	0	82	0
0	246	0	29	0	35	0	12	8	0	11	0	69	0
0	247	0	32	0	35	0	14	9	0	13	0	68	0
0	248	0	36	0	32	0	10	9	0	14	0	44	0
0	249	0	19	0	21	0	12	8	0	10	0	56	0
0	250	0	21	0	20	0	12	9	0	12	0	53	0
0	251	0	31	0	34	0	11	7	0	15	0	70	0
0	252	0	33	0	32	0	10	7	0	13	0	78	0
0	253	0	36	0	34	0	12	6	0	13	0	71	0
0	254	0	33	0	32	0	16	9	0	13	0	72	0
0	255	0	37	0	33	0	12	10	0	12	0	68	0
0	256	0	34	0	33	0	14	11	0	12	0	67	0
0	257	0	35	0	37	0	16	12	0	9	0	75	0
0	258	0	31	0	32	0	14	8	0	9	0	62	0
0	259	0	37	0	34	0	13	11	0	15	0	67	0
0	260	0	35	0	30	0	4	3	0	10	0	83	0
0	261	0	27	0	30	0	15	11	0	14	0	64	0
0	262	0	34	0	38	0	11	12	0	15	0	68	0
0	263	0	40	0	36	0	11	7	0	7	0	62	0
0	264	0	29	0	32	0	14	9	0	14	0	72	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 16 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202578&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]16 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202578&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202578&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 time16 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 4.76348289506874 -0.485576603308534Pop[t] -0.00437931852270916t -5.10504111858711e-05Pop_t[t] -0.0558670662591829Connected[t] + 0.145224903907176Connected_p[t] + 0.156566737435064Separate[t] -0.170900646235258Separate_p[t] + 0.562361449228819Software[t] -0.0335162245982637Software_p[t] + 0.112073294456415Happiness[t] -0.0279623279275028Happiness_p[t] -0.011262554231335Belonging[t] + 0.0306569232903473Belonging_p[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  4.76348289506874 -0.485576603308534Pop[t] -0.00437931852270916t -5.10504111858711e-05Pop_t[t] -0.0558670662591829Connected[t] +  0.145224903907176Connected_p[t] +  0.156566737435064Separate[t] -0.170900646235258Separate_p[t] +  0.562361449228819Software[t] -0.0335162245982637Software_p[t] +  0.112073294456415Happiness[t] -0.0279623279275028Happiness_p[t] -0.011262554231335Belonging[t] +  0.0306569232903473Belonging_p[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202578&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  4.76348289506874 -0.485576603308534Pop[t] -0.00437931852270916t -5.10504111858711e-05Pop_t[t] -0.0558670662591829Connected[t] +  0.145224903907176Connected_p[t] +  0.156566737435064Separate[t] -0.170900646235258Separate_p[t] +  0.562361449228819Software[t] -0.0335162245982637Software_p[t] +  0.112073294456415Happiness[t] -0.0279623279275028Happiness_p[t] -0.011262554231335Belonging[t] +  0.0306569232903473Belonging_p[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202578&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202578&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] = + 4.76348289506874 -0.485576603308534Pop[t] -0.00437931852270916t -5.10504111858711e-05Pop_t[t] -0.0558670662591829Connected[t] + 0.145224903907176Connected_p[t] + 0.156566737435064Separate[t] -0.170900646235258Separate_p[t] + 0.562361449228819Software[t] -0.0335162245982637Software_p[t] + 0.112073294456415Happiness[t] -0.0279623279275028Happiness_p[t] -0.011262554231335Belonging[t] + 0.0306569232903473Belonging_p[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.763482895068742.614731.82180.0696820.034841
Pop-0.4855766033085343.374018-0.14390.8856820.442841
t-0.004379318522709160.006347-0.690.4908510.245425
Pop_t-5.10504111858711e-050.007154-0.00710.9943120.497156
Connected-0.05586706625918290.052286-1.06850.2863330.143167
Connected_p0.1452249039071760.070052.07310.0391830.019591
Separate0.1565667374350640.0598192.61730.0094020.004701
Separate_p-0.1709006462352580.074506-2.29380.0226320.011316
Software0.5623614492288190.0822576.836600
Software_p-0.03351622459826370.10926-0.30680.7592830.379642
Happiness0.1120732944564150.0750651.4930.1366910.068346
Happiness_p-0.02796232792750280.101031-0.27680.7821860.391093
Belonging-0.0112625542313350.018356-0.61360.5400670.270033
Belonging_p0.03065692329034730.0239321.2810.2013710.100685

\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) & 4.76348289506874 & 2.61473 & 1.8218 & 0.069682 & 0.034841 \tabularnewline
Pop & -0.485576603308534 & 3.374018 & -0.1439 & 0.885682 & 0.442841 \tabularnewline
t & -0.00437931852270916 & 0.006347 & -0.69 & 0.490851 & 0.245425 \tabularnewline
Pop_t & -5.10504111858711e-05 & 0.007154 & -0.0071 & 0.994312 & 0.497156 \tabularnewline
Connected & -0.0558670662591829 & 0.052286 & -1.0685 & 0.286333 & 0.143167 \tabularnewline
Connected_p & 0.145224903907176 & 0.07005 & 2.0731 & 0.039183 & 0.019591 \tabularnewline
Separate & 0.156566737435064 & 0.059819 & 2.6173 & 0.009402 & 0.004701 \tabularnewline
Separate_p & -0.170900646235258 & 0.074506 & -2.2938 & 0.022632 & 0.011316 \tabularnewline
Software & 0.562361449228819 & 0.082257 & 6.8366 & 0 & 0 \tabularnewline
Software_p & -0.0335162245982637 & 0.10926 & -0.3068 & 0.759283 & 0.379642 \tabularnewline
Happiness & 0.112073294456415 & 0.075065 & 1.493 & 0.136691 & 0.068346 \tabularnewline
Happiness_p & -0.0279623279275028 & 0.101031 & -0.2768 & 0.782186 & 0.391093 \tabularnewline
Belonging & -0.011262554231335 & 0.018356 & -0.6136 & 0.540067 & 0.270033 \tabularnewline
Belonging_p & 0.0306569232903473 & 0.023932 & 1.281 & 0.201371 & 0.100685 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202578&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]4.76348289506874[/C][C]2.61473[/C][C]1.8218[/C][C]0.069682[/C][C]0.034841[/C][/ROW]
[ROW][C]Pop[/C][C]-0.485576603308534[/C][C]3.374018[/C][C]-0.1439[/C][C]0.885682[/C][C]0.442841[/C][/ROW]
[ROW][C]t[/C][C]-0.00437931852270916[/C][C]0.006347[/C][C]-0.69[/C][C]0.490851[/C][C]0.245425[/C][/ROW]
[ROW][C]Pop_t[/C][C]-5.10504111858711e-05[/C][C]0.007154[/C][C]-0.0071[/C][C]0.994312[/C][C]0.497156[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0558670662591829[/C][C]0.052286[/C][C]-1.0685[/C][C]0.286333[/C][C]0.143167[/C][/ROW]
[ROW][C]Connected_p[/C][C]0.145224903907176[/C][C]0.07005[/C][C]2.0731[/C][C]0.039183[/C][C]0.019591[/C][/ROW]
[ROW][C]Separate[/C][C]0.156566737435064[/C][C]0.059819[/C][C]2.6173[/C][C]0.009402[/C][C]0.004701[/C][/ROW]
[ROW][C]Separate_p[/C][C]-0.170900646235258[/C][C]0.074506[/C][C]-2.2938[/C][C]0.022632[/C][C]0.011316[/C][/ROW]
[ROW][C]Software[/C][C]0.562361449228819[/C][C]0.082257[/C][C]6.8366[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Software_p[/C][C]-0.0335162245982637[/C][C]0.10926[/C][C]-0.3068[/C][C]0.759283[/C][C]0.379642[/C][/ROW]
[ROW][C]Happiness[/C][C]0.112073294456415[/C][C]0.075065[/C][C]1.493[/C][C]0.136691[/C][C]0.068346[/C][/ROW]
[ROW][C]Happiness_p[/C][C]-0.0279623279275028[/C][C]0.101031[/C][C]-0.2768[/C][C]0.782186[/C][C]0.391093[/C][/ROW]
[ROW][C]Belonging[/C][C]-0.011262554231335[/C][C]0.018356[/C][C]-0.6136[/C][C]0.540067[/C][C]0.270033[/C][/ROW]
[ROW][C]Belonging_p[/C][C]0.0306569232903473[/C][C]0.023932[/C][C]1.281[/C][C]0.201371[/C][C]0.100685[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202578&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202578&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)4.763482895068742.614731.82180.0696820.034841
Pop-0.4855766033085343.374018-0.14390.8856820.442841
t-0.004379318522709160.006347-0.690.4908510.245425
Pop_t-5.10504111858711e-050.007154-0.00710.9943120.497156
Connected-0.05586706625918290.052286-1.06850.2863330.143167
Connected_p0.1452249039071760.070052.07310.0391830.019591
Separate0.1565667374350640.0598192.61730.0094020.004701
Separate_p-0.1709006462352580.074506-2.29380.0226320.011316
Software0.5623614492288190.0822576.836600
Software_p-0.03351622459826370.10926-0.30680.7592830.379642
Happiness0.1120732944564150.0750651.4930.1366910.068346
Happiness_p-0.02796232792750280.101031-0.27680.7821860.391093
Belonging-0.0112625542313350.018356-0.61360.5400670.270033
Belonging_p0.03065692329034730.0239321.2810.2013710.100685







Multiple Linear Regression - Regression Statistics
Multiple R0.680098352063563
R-squared0.462533768479574
Adjusted R-squared0.434585524440512
F-TEST (value)16.5496539901795
F-TEST (DF numerator)13
F-TEST (DF denominator)250
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.84674512097084
Sum Squared Residuals852.616885457403

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.680098352063563 \tabularnewline
R-squared & 0.462533768479574 \tabularnewline
Adjusted R-squared & 0.434585524440512 \tabularnewline
F-TEST (value) & 16.5496539901795 \tabularnewline
F-TEST (DF numerator) & 13 \tabularnewline
F-TEST (DF denominator) & 250 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.84674512097084 \tabularnewline
Sum Squared Residuals & 852.616885457403 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202578&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.680098352063563[/C][/ROW]
[ROW][C]R-squared[/C][C]0.462533768479574[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.434585524440512[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]16.5496539901795[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]13[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]250[/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]1.84674512097084[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]852.616885457403[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202578&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202578&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 R0.680098352063563
R-squared0.462533768479574
Adjusted R-squared0.434585524440512
F-TEST (value)16.5496539901795
F-TEST (DF numerator)13
F-TEST (DF denominator)250
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.84674512097084
Sum Squared Residuals852.616885457403







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.9440565190857-2.94405651908571
21616.2363436409125-0.23634364091247
31916.58159086556272.41840913443732
41512.03908446579012.9609155342099
51416.45830173466-2.45830173466005
61315.2783754710599-2.27837547105988
71915.83909599178773.16090400821228
81516.8975453044673-1.89754530446734
91415.9962188225434-1.99621882254335
101514.49039762908320.509602370916777
111615.43091272426410.569087275735903
121615.94581810947730.0541818905227417
131615.60089760604610.399102393953892
141615.36651712513540.633482874864622
151717.7638906496412-0.763890649641175
161515.2420218355414-0.242021835541392
171514.88137055074180.118629449258239
182016.53180255091773.4681974490823
191815.37008703799822.6299129620018
201615.38746183260480.612538167395183
211615.18262358482910.817376415170891
221615.09636039289380.903639607106195
231916.21611232093362.78388767906639
241614.83150872370261.16849127629737
251716.63736252071160.362637479288438
261716.55123910511880.448760894881163
271614.98168143711911.01831856288093
281516.4919081196921-1.49190811969211
291615.74578322475790.254216775242091
301414.2232383184461-0.223238318446112
311515.7097743338415-0.709774333841459
321212.4616113118721-0.461611311872121
331415.0889318175983-1.08893181759831
341615.87201979688970.127980203110276
351415.6898721324382-1.68987213243815
361012.9295370645357-2.9295370645357
371012.9994597313448-2.99945973134484
381415.8382228338837-1.83822283388374
391614.44445874810611.55554125189393
401614.4753031379311.524696862069
411614.92911613144621.07088386855383
421415.8034741256171-1.80347412561714
432017.35006293972782.64993706027219
441414.0437664216633-0.0437664216633002
451414.9611162832643-0.9611162832643
461115.4688429291675-4.4688429291675
471416.30354074625-2.30354074624999
481515.0602439744061-0.0602439744061165
491615.41537904721420.584620952785766
501415.8874635339514-1.88746353395141
511616.5127229279992-0.512722927999202
521414.2423891525918-0.242389152591754
531214.9227371306956-2.9227371306956
541615.61891471515720.381085284842825
55911.310404695743-2.31040469574303
561412.7430667106331.25693328936703
571616.1500795019895-0.150079501989472
581615.03219920663370.967800793366348
591515.0491518114201-0.0491518114200926
601614.3076452529831.69235474701699
611211.68974533459980.310254665400209
621615.84442002726230.155579972737695
631616.4158760223166-0.415876022316569
641414.2661270324814-0.26612703248142
651615.23885074096980.761149259030229
661715.8503187444031.14968125559698
671816.30534905505081.6946509449492
681814.51277880668083.48722119331916
691215.7134625958035-3.71346259580352
701615.51096881703230.489031182967691
711013.5506652666734-3.55066526667343
721414.3946930257855-0.394693025785526
731816.67007493295151.3299250670485
741816.7616756683011.23832433169896
751615.66549182554410.334508174455855
761714.3166248017932.683375198207
771616.3751334365384-0.375133436538421
781614.77510432302591.22489567697406
791315.0867490383646-2.08674903836457
801615.32958242204830.670417577951724
811615.49179668285380.508203317146203
821615.49659312794360.503406872056406
831515.8511137741534-0.851113774153397
841514.75320974796090.246790252039134
851614.36515459721111.63484540278886
861414.209319149896-0.209319149895987
871615.21582762973180.784172370268221
881614.50760722539221.4923927746078
891514.65191840402080.348081595979188
901213.7385277319648-1.73852773196484
911716.70635665601810.293643343981867
921615.51132001775790.488679982242059
931515.4380178290487-0.438017829048742
941315.0139464249235-2.01394642492355
951615.0117334299940.988266570005964
961615.87967504269120.120324957308769
971613.98125498972882.01874501027116
981616.0095902503458-0.00959025034578832
991414.2068186479575-0.206818647957546
1001617.0221381364917-1.02213813649165
1011614.87741022499671.1225897750033
1022017.43951139416042.56048860583956
1031514.30222611054830.697773889451698
1041614.81805124634311.18194875365693
1051315.3503044683544-2.35030446835443
1061715.86808841589851.13191158410155
1071615.89331311288380.106686887116215
1081614.22032485963241.77967514036762
1091212.4705261416388-0.470526141638752
1101615.24027650278130.759723497218674
1111615.84744640379190.152553596208056
1121714.67091002809682.32908997190318
1131313.8955434431428-0.895543443142771
1141214.8681530193762-2.86815301937621
1151816.50464789946671.49535210053333
1161415.239273166593-1.23927316659303
1171412.93210130992151.06789869007849
1181314.5353070593503-1.53530705935028
1191615.8994589447260.100541055274027
1201314.0386410349391-1.0386410349391
1211615.65142258032840.348577419671636
1221315.9078827089936-2.9078827089936
1231616.6339920627059-0.633992062705861
1241516.0535128859177-1.05351288591774
1251616.5794602417009-0.579460241700854
1261515.2097822853631-0.209782285363102
1271715.77033906275421.22966093724583
1281514.07226627330270.927733726697263
1291214.8362505676798-2.83625056767976
1301613.84728515905452.1527148409455
1311013.5951868615487-3.59518686154867
1321613.72284918532072.27715081467934
1331214.0109075337477-2.01090753374774
1341415.4887788170539-1.48877881705388
1351515.4640134652598-0.464013465259818
1361312.59417315996970.405826840030297
1371514.42412167290020.575878327099804
1381113.1065325076259-2.10653250762593
1391213.0359223431769-1.03592234317685
1401113.1173218517186-2.11732185171859
1411612.5650444017753.43495559822504
1421513.53368389407431.46631610592566
1431716.60155949558440.398440504415638
1441614.65267461637641.34732538362363
1451014.0681012372182-4.06810123721825
1461815.79824312768682.2017568723132
1471314.7625289679238-1.76252896792382
1481614.8473632948131.15263670518698
1491313.2190152184265-0.219015218426485
1501013.1461397459846-3.14613974598463
1511516.3321807790856-1.33218077908561
1521613.580350848762.41964915124
1531611.74735923772564.2526407622744
1541412.8298463682341.17015363176601
1551012.9326217251075-2.93262172510748
1561716.4183826753150.581617324685043
1571311.60027089252721.39972910747278
1581513.93935520528591.06064479471411
1591614.69282606646541.30717393353456
1601212.7530299290138-0.753029929013813
1611312.749178483620.250821516379981
1621312.61737653628780.38262346371218
1631211.54416091862640.455839081373624
1641715.83173202838921.16826797161076
1651514.18096137817320.819038621826762
1661012.5162284574896-2.51622845748959
1671414.3993498832206-0.399349883220634
1681113.7491700074955-2.74917000749547
1691314.9069014283352-1.90690142833521
1701615.23838782427370.761612175726268
1711210.22627983902391.77372016097606
1721615.52260120632190.477398793678094
1731212.9489417965926-0.948941796592602
174911.024497259364-2.02449725936401
1751214.1003626138382-2.1003626138382
1761514.44926206441160.550737935588401
1771211.82966195652410.17033804347592
1781212.6339706678772-0.633970667877187
1791413.76347075604750.236529243952493
1801213.1058565971907-1.10585659719067
1811615.30519998943370.694800010566342
1821110.78463211772310.215367882276936
1831917.19473345812571.80526654187433
1841514.26123454159220.738765458407801
185814.647244934307-6.64724493430698
1861615.14692217431110.85307782568894
1871714.17817806957182.82182193042824
1881211.25271163250010.74728836749991
1891111.5406875312444-0.540687531244425
1901111.1376664801757-0.137666480175688
1911415.3288560535754-1.32885605357541
1921615.53504666404770.464953335952285
193129.888298157819712.11170184218029
1941614.47202088588391.52797911411606
1951313.625715265247-0.625715265246953
1961515.0924291635898-0.092429163589778
1971612.59538313494353.40461686505647
1981615.18325522112620.816744778873838
1991412.47464869422161.52535130577838
2001614.78328460857661.21671539142336
2011613.88411080617212.11588919382791
2021413.76265075348530.237349246514671
2031112.9503773241019-1.95037732410186
2041214.577869551733-2.57786955173304
2051512.71446559017322.28553440982683
2061514.63191191948520.368088080514808
2071614.49227088113731.50772911886274
2081615.48949715295520.510502847044806
2091113.2958817978772-2.2958817978772
2101513.58178073600341.41821926399659
2111214.1428623393701-2.14286233937013
2121216.0289096453871-4.02890964538706
2131514.58798465181680.412015348183227
2141511.89031509547483.10968490452521
2151614.57297040010911.42702959989093
2161412.74008855888071.25991144111931
2171714.58329823692772.41670176307235
2181413.21109355927940.788906440720609
2191311.98149570486251.01850429513746
2201515.4008285553322-0.40082855533223
2211314.1321980260207-1.13219802602067
2221414.0682872710141-0.068287271014069
2231514.01158370652750.988416293472523
2241212.9922206451188-0.992220645118751
2251313.1569941546857-0.15699415468565
226811.9112755129364-3.91127551293636
2271414.1924632927691-0.192463292769131
2281412.94124581809241.05875418190755
2291112.2423518553558-1.24235185535583
2301212.8422756781471-0.842275678147151
2311310.69293565390062.30706434609943
2321013.7310868426761-3.7310868426761
2331611.68066459857754.31933540142245
2341815.13398419196622.86601580803384
2351313.4508816862766-0.450881686276635
2361112.6403601339811-1.64036013398109
237410.2185991839173-6.21859918391726
2381313.5794551191926-0.579455119192583
2391614.00841613776581.9915838622342
2401010.7007996000469-0.700799600046881
2411212.06245829497-0.0624582949700043
2421213.7138232266365-1.71382322663655
243108.89763502272111.1023649772789
2441310.88200384139522.11799615860479
2451512.85822172806722.14177827193283
2461212.5004430180822-0.500443018082235
2471413.1262330931550.87376690684504
2481012.8110598932988-2.81105989329878
2491210.8883813115661.11161868843402
2501211.43599682392550.564003176074509
2511112.0849147298808-1.08491472988076
2521011.3414207812061-1.34142078120605
2531210.99905016916641.00094983083355
2541612.52496036800633.47503963199372
2551212.9490178935796-0.949017893579647
2561413.68586377729460.314136222705359
2571614.38792547426191.6120745257381
2581411.72114814169272.27885185830732
2591313.9979112437533-0.997911243753274
26048.23954017419469-4.23954017419469
2611513.8432706877971.15672931220298
2621115.3297403317004-4.32974033170044
2631111.0362068643451-0.0362068643450975
2641412.81670874227231.18329125772766

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.9440565190857 & -2.94405651908571 \tabularnewline
2 & 16 & 16.2363436409125 & -0.23634364091247 \tabularnewline
3 & 19 & 16.5815908655627 & 2.41840913443732 \tabularnewline
4 & 15 & 12.0390844657901 & 2.9609155342099 \tabularnewline
5 & 14 & 16.45830173466 & -2.45830173466005 \tabularnewline
6 & 13 & 15.2783754710599 & -2.27837547105988 \tabularnewline
7 & 19 & 15.8390959917877 & 3.16090400821228 \tabularnewline
8 & 15 & 16.8975453044673 & -1.89754530446734 \tabularnewline
9 & 14 & 15.9962188225434 & -1.99621882254335 \tabularnewline
10 & 15 & 14.4903976290832 & 0.509602370916777 \tabularnewline
11 & 16 & 15.4309127242641 & 0.569087275735903 \tabularnewline
12 & 16 & 15.9458181094773 & 0.0541818905227417 \tabularnewline
13 & 16 & 15.6008976060461 & 0.399102393953892 \tabularnewline
14 & 16 & 15.3665171251354 & 0.633482874864622 \tabularnewline
15 & 17 & 17.7638906496412 & -0.763890649641175 \tabularnewline
16 & 15 & 15.2420218355414 & -0.242021835541392 \tabularnewline
17 & 15 & 14.8813705507418 & 0.118629449258239 \tabularnewline
18 & 20 & 16.5318025509177 & 3.4681974490823 \tabularnewline
19 & 18 & 15.3700870379982 & 2.6299129620018 \tabularnewline
20 & 16 & 15.3874618326048 & 0.612538167395183 \tabularnewline
21 & 16 & 15.1826235848291 & 0.817376415170891 \tabularnewline
22 & 16 & 15.0963603928938 & 0.903639607106195 \tabularnewline
23 & 19 & 16.2161123209336 & 2.78388767906639 \tabularnewline
24 & 16 & 14.8315087237026 & 1.16849127629737 \tabularnewline
25 & 17 & 16.6373625207116 & 0.362637479288438 \tabularnewline
26 & 17 & 16.5512391051188 & 0.448760894881163 \tabularnewline
27 & 16 & 14.9816814371191 & 1.01831856288093 \tabularnewline
28 & 15 & 16.4919081196921 & -1.49190811969211 \tabularnewline
29 & 16 & 15.7457832247579 & 0.254216775242091 \tabularnewline
30 & 14 & 14.2232383184461 & -0.223238318446112 \tabularnewline
31 & 15 & 15.7097743338415 & -0.709774333841459 \tabularnewline
32 & 12 & 12.4616113118721 & -0.461611311872121 \tabularnewline
33 & 14 & 15.0889318175983 & -1.08893181759831 \tabularnewline
34 & 16 & 15.8720197968897 & 0.127980203110276 \tabularnewline
35 & 14 & 15.6898721324382 & -1.68987213243815 \tabularnewline
36 & 10 & 12.9295370645357 & -2.9295370645357 \tabularnewline
37 & 10 & 12.9994597313448 & -2.99945973134484 \tabularnewline
38 & 14 & 15.8382228338837 & -1.83822283388374 \tabularnewline
39 & 16 & 14.4444587481061 & 1.55554125189393 \tabularnewline
40 & 16 & 14.475303137931 & 1.524696862069 \tabularnewline
41 & 16 & 14.9291161314462 & 1.07088386855383 \tabularnewline
42 & 14 & 15.8034741256171 & -1.80347412561714 \tabularnewline
43 & 20 & 17.3500629397278 & 2.64993706027219 \tabularnewline
44 & 14 & 14.0437664216633 & -0.0437664216633002 \tabularnewline
45 & 14 & 14.9611162832643 & -0.9611162832643 \tabularnewline
46 & 11 & 15.4688429291675 & -4.4688429291675 \tabularnewline
47 & 14 & 16.30354074625 & -2.30354074624999 \tabularnewline
48 & 15 & 15.0602439744061 & -0.0602439744061165 \tabularnewline
49 & 16 & 15.4153790472142 & 0.584620952785766 \tabularnewline
50 & 14 & 15.8874635339514 & -1.88746353395141 \tabularnewline
51 & 16 & 16.5127229279992 & -0.512722927999202 \tabularnewline
52 & 14 & 14.2423891525918 & -0.242389152591754 \tabularnewline
53 & 12 & 14.9227371306956 & -2.9227371306956 \tabularnewline
54 & 16 & 15.6189147151572 & 0.381085284842825 \tabularnewline
55 & 9 & 11.310404695743 & -2.31040469574303 \tabularnewline
56 & 14 & 12.743066710633 & 1.25693328936703 \tabularnewline
57 & 16 & 16.1500795019895 & -0.150079501989472 \tabularnewline
58 & 16 & 15.0321992066337 & 0.967800793366348 \tabularnewline
59 & 15 & 15.0491518114201 & -0.0491518114200926 \tabularnewline
60 & 16 & 14.307645252983 & 1.69235474701699 \tabularnewline
61 & 12 & 11.6897453345998 & 0.310254665400209 \tabularnewline
62 & 16 & 15.8444200272623 & 0.155579972737695 \tabularnewline
63 & 16 & 16.4158760223166 & -0.415876022316569 \tabularnewline
64 & 14 & 14.2661270324814 & -0.26612703248142 \tabularnewline
65 & 16 & 15.2388507409698 & 0.761149259030229 \tabularnewline
66 & 17 & 15.850318744403 & 1.14968125559698 \tabularnewline
67 & 18 & 16.3053490550508 & 1.6946509449492 \tabularnewline
68 & 18 & 14.5127788066808 & 3.48722119331916 \tabularnewline
69 & 12 & 15.7134625958035 & -3.71346259580352 \tabularnewline
70 & 16 & 15.5109688170323 & 0.489031182967691 \tabularnewline
71 & 10 & 13.5506652666734 & -3.55066526667343 \tabularnewline
72 & 14 & 14.3946930257855 & -0.394693025785526 \tabularnewline
73 & 18 & 16.6700749329515 & 1.3299250670485 \tabularnewline
74 & 18 & 16.761675668301 & 1.23832433169896 \tabularnewline
75 & 16 & 15.6654918255441 & 0.334508174455855 \tabularnewline
76 & 17 & 14.316624801793 & 2.683375198207 \tabularnewline
77 & 16 & 16.3751334365384 & -0.375133436538421 \tabularnewline
78 & 16 & 14.7751043230259 & 1.22489567697406 \tabularnewline
79 & 13 & 15.0867490383646 & -2.08674903836457 \tabularnewline
80 & 16 & 15.3295824220483 & 0.670417577951724 \tabularnewline
81 & 16 & 15.4917966828538 & 0.508203317146203 \tabularnewline
82 & 16 & 15.4965931279436 & 0.503406872056406 \tabularnewline
83 & 15 & 15.8511137741534 & -0.851113774153397 \tabularnewline
84 & 15 & 14.7532097479609 & 0.246790252039134 \tabularnewline
85 & 16 & 14.3651545972111 & 1.63484540278886 \tabularnewline
86 & 14 & 14.209319149896 & -0.209319149895987 \tabularnewline
87 & 16 & 15.2158276297318 & 0.784172370268221 \tabularnewline
88 & 16 & 14.5076072253922 & 1.4923927746078 \tabularnewline
89 & 15 & 14.6519184040208 & 0.348081595979188 \tabularnewline
90 & 12 & 13.7385277319648 & -1.73852773196484 \tabularnewline
91 & 17 & 16.7063566560181 & 0.293643343981867 \tabularnewline
92 & 16 & 15.5113200177579 & 0.488679982242059 \tabularnewline
93 & 15 & 15.4380178290487 & -0.438017829048742 \tabularnewline
94 & 13 & 15.0139464249235 & -2.01394642492355 \tabularnewline
95 & 16 & 15.011733429994 & 0.988266570005964 \tabularnewline
96 & 16 & 15.8796750426912 & 0.120324957308769 \tabularnewline
97 & 16 & 13.9812549897288 & 2.01874501027116 \tabularnewline
98 & 16 & 16.0095902503458 & -0.00959025034578832 \tabularnewline
99 & 14 & 14.2068186479575 & -0.206818647957546 \tabularnewline
100 & 16 & 17.0221381364917 & -1.02213813649165 \tabularnewline
101 & 16 & 14.8774102249967 & 1.1225897750033 \tabularnewline
102 & 20 & 17.4395113941604 & 2.56048860583956 \tabularnewline
103 & 15 & 14.3022261105483 & 0.697773889451698 \tabularnewline
104 & 16 & 14.8180512463431 & 1.18194875365693 \tabularnewline
105 & 13 & 15.3503044683544 & -2.35030446835443 \tabularnewline
106 & 17 & 15.8680884158985 & 1.13191158410155 \tabularnewline
107 & 16 & 15.8933131128838 & 0.106686887116215 \tabularnewline
108 & 16 & 14.2203248596324 & 1.77967514036762 \tabularnewline
109 & 12 & 12.4705261416388 & -0.470526141638752 \tabularnewline
110 & 16 & 15.2402765027813 & 0.759723497218674 \tabularnewline
111 & 16 & 15.8474464037919 & 0.152553596208056 \tabularnewline
112 & 17 & 14.6709100280968 & 2.32908997190318 \tabularnewline
113 & 13 & 13.8955434431428 & -0.895543443142771 \tabularnewline
114 & 12 & 14.8681530193762 & -2.86815301937621 \tabularnewline
115 & 18 & 16.5046478994667 & 1.49535210053333 \tabularnewline
116 & 14 & 15.239273166593 & -1.23927316659303 \tabularnewline
117 & 14 & 12.9321013099215 & 1.06789869007849 \tabularnewline
118 & 13 & 14.5353070593503 & -1.53530705935028 \tabularnewline
119 & 16 & 15.899458944726 & 0.100541055274027 \tabularnewline
120 & 13 & 14.0386410349391 & -1.0386410349391 \tabularnewline
121 & 16 & 15.6514225803284 & 0.348577419671636 \tabularnewline
122 & 13 & 15.9078827089936 & -2.9078827089936 \tabularnewline
123 & 16 & 16.6339920627059 & -0.633992062705861 \tabularnewline
124 & 15 & 16.0535128859177 & -1.05351288591774 \tabularnewline
125 & 16 & 16.5794602417009 & -0.579460241700854 \tabularnewline
126 & 15 & 15.2097822853631 & -0.209782285363102 \tabularnewline
127 & 17 & 15.7703390627542 & 1.22966093724583 \tabularnewline
128 & 15 & 14.0722662733027 & 0.927733726697263 \tabularnewline
129 & 12 & 14.8362505676798 & -2.83625056767976 \tabularnewline
130 & 16 & 13.8472851590545 & 2.1527148409455 \tabularnewline
131 & 10 & 13.5951868615487 & -3.59518686154867 \tabularnewline
132 & 16 & 13.7228491853207 & 2.27715081467934 \tabularnewline
133 & 12 & 14.0109075337477 & -2.01090753374774 \tabularnewline
134 & 14 & 15.4887788170539 & -1.48877881705388 \tabularnewline
135 & 15 & 15.4640134652598 & -0.464013465259818 \tabularnewline
136 & 13 & 12.5941731599697 & 0.405826840030297 \tabularnewline
137 & 15 & 14.4241216729002 & 0.575878327099804 \tabularnewline
138 & 11 & 13.1065325076259 & -2.10653250762593 \tabularnewline
139 & 12 & 13.0359223431769 & -1.03592234317685 \tabularnewline
140 & 11 & 13.1173218517186 & -2.11732185171859 \tabularnewline
141 & 16 & 12.565044401775 & 3.43495559822504 \tabularnewline
142 & 15 & 13.5336838940743 & 1.46631610592566 \tabularnewline
143 & 17 & 16.6015594955844 & 0.398440504415638 \tabularnewline
144 & 16 & 14.6526746163764 & 1.34732538362363 \tabularnewline
145 & 10 & 14.0681012372182 & -4.06810123721825 \tabularnewline
146 & 18 & 15.7982431276868 & 2.2017568723132 \tabularnewline
147 & 13 & 14.7625289679238 & -1.76252896792382 \tabularnewline
148 & 16 & 14.847363294813 & 1.15263670518698 \tabularnewline
149 & 13 & 13.2190152184265 & -0.219015218426485 \tabularnewline
150 & 10 & 13.1461397459846 & -3.14613974598463 \tabularnewline
151 & 15 & 16.3321807790856 & -1.33218077908561 \tabularnewline
152 & 16 & 13.58035084876 & 2.41964915124 \tabularnewline
153 & 16 & 11.7473592377256 & 4.2526407622744 \tabularnewline
154 & 14 & 12.829846368234 & 1.17015363176601 \tabularnewline
155 & 10 & 12.9326217251075 & -2.93262172510748 \tabularnewline
156 & 17 & 16.418382675315 & 0.581617324685043 \tabularnewline
157 & 13 & 11.6002708925272 & 1.39972910747278 \tabularnewline
158 & 15 & 13.9393552052859 & 1.06064479471411 \tabularnewline
159 & 16 & 14.6928260664654 & 1.30717393353456 \tabularnewline
160 & 12 & 12.7530299290138 & -0.753029929013813 \tabularnewline
161 & 13 & 12.74917848362 & 0.250821516379981 \tabularnewline
162 & 13 & 12.6173765362878 & 0.38262346371218 \tabularnewline
163 & 12 & 11.5441609186264 & 0.455839081373624 \tabularnewline
164 & 17 & 15.8317320283892 & 1.16826797161076 \tabularnewline
165 & 15 & 14.1809613781732 & 0.819038621826762 \tabularnewline
166 & 10 & 12.5162284574896 & -2.51622845748959 \tabularnewline
167 & 14 & 14.3993498832206 & -0.399349883220634 \tabularnewline
168 & 11 & 13.7491700074955 & -2.74917000749547 \tabularnewline
169 & 13 & 14.9069014283352 & -1.90690142833521 \tabularnewline
170 & 16 & 15.2383878242737 & 0.761612175726268 \tabularnewline
171 & 12 & 10.2262798390239 & 1.77372016097606 \tabularnewline
172 & 16 & 15.5226012063219 & 0.477398793678094 \tabularnewline
173 & 12 & 12.9489417965926 & -0.948941796592602 \tabularnewline
174 & 9 & 11.024497259364 & -2.02449725936401 \tabularnewline
175 & 12 & 14.1003626138382 & -2.1003626138382 \tabularnewline
176 & 15 & 14.4492620644116 & 0.550737935588401 \tabularnewline
177 & 12 & 11.8296619565241 & 0.17033804347592 \tabularnewline
178 & 12 & 12.6339706678772 & -0.633970667877187 \tabularnewline
179 & 14 & 13.7634707560475 & 0.236529243952493 \tabularnewline
180 & 12 & 13.1058565971907 & -1.10585659719067 \tabularnewline
181 & 16 & 15.3051999894337 & 0.694800010566342 \tabularnewline
182 & 11 & 10.7846321177231 & 0.215367882276936 \tabularnewline
183 & 19 & 17.1947334581257 & 1.80526654187433 \tabularnewline
184 & 15 & 14.2612345415922 & 0.738765458407801 \tabularnewline
185 & 8 & 14.647244934307 & -6.64724493430698 \tabularnewline
186 & 16 & 15.1469221743111 & 0.85307782568894 \tabularnewline
187 & 17 & 14.1781780695718 & 2.82182193042824 \tabularnewline
188 & 12 & 11.2527116325001 & 0.74728836749991 \tabularnewline
189 & 11 & 11.5406875312444 & -0.540687531244425 \tabularnewline
190 & 11 & 11.1376664801757 & -0.137666480175688 \tabularnewline
191 & 14 & 15.3288560535754 & -1.32885605357541 \tabularnewline
192 & 16 & 15.5350466640477 & 0.464953335952285 \tabularnewline
193 & 12 & 9.88829815781971 & 2.11170184218029 \tabularnewline
194 & 16 & 14.4720208858839 & 1.52797911411606 \tabularnewline
195 & 13 & 13.625715265247 & -0.625715265246953 \tabularnewline
196 & 15 & 15.0924291635898 & -0.092429163589778 \tabularnewline
197 & 16 & 12.5953831349435 & 3.40461686505647 \tabularnewline
198 & 16 & 15.1832552211262 & 0.816744778873838 \tabularnewline
199 & 14 & 12.4746486942216 & 1.52535130577838 \tabularnewline
200 & 16 & 14.7832846085766 & 1.21671539142336 \tabularnewline
201 & 16 & 13.8841108061721 & 2.11588919382791 \tabularnewline
202 & 14 & 13.7626507534853 & 0.237349246514671 \tabularnewline
203 & 11 & 12.9503773241019 & -1.95037732410186 \tabularnewline
204 & 12 & 14.577869551733 & -2.57786955173304 \tabularnewline
205 & 15 & 12.7144655901732 & 2.28553440982683 \tabularnewline
206 & 15 & 14.6319119194852 & 0.368088080514808 \tabularnewline
207 & 16 & 14.4922708811373 & 1.50772911886274 \tabularnewline
208 & 16 & 15.4894971529552 & 0.510502847044806 \tabularnewline
209 & 11 & 13.2958817978772 & -2.2958817978772 \tabularnewline
210 & 15 & 13.5817807360034 & 1.41821926399659 \tabularnewline
211 & 12 & 14.1428623393701 & -2.14286233937013 \tabularnewline
212 & 12 & 16.0289096453871 & -4.02890964538706 \tabularnewline
213 & 15 & 14.5879846518168 & 0.412015348183227 \tabularnewline
214 & 15 & 11.8903150954748 & 3.10968490452521 \tabularnewline
215 & 16 & 14.5729704001091 & 1.42702959989093 \tabularnewline
216 & 14 & 12.7400885588807 & 1.25991144111931 \tabularnewline
217 & 17 & 14.5832982369277 & 2.41670176307235 \tabularnewline
218 & 14 & 13.2110935592794 & 0.788906440720609 \tabularnewline
219 & 13 & 11.9814957048625 & 1.01850429513746 \tabularnewline
220 & 15 & 15.4008285553322 & -0.40082855533223 \tabularnewline
221 & 13 & 14.1321980260207 & -1.13219802602067 \tabularnewline
222 & 14 & 14.0682872710141 & -0.068287271014069 \tabularnewline
223 & 15 & 14.0115837065275 & 0.988416293472523 \tabularnewline
224 & 12 & 12.9922206451188 & -0.992220645118751 \tabularnewline
225 & 13 & 13.1569941546857 & -0.15699415468565 \tabularnewline
226 & 8 & 11.9112755129364 & -3.91127551293636 \tabularnewline
227 & 14 & 14.1924632927691 & -0.192463292769131 \tabularnewline
228 & 14 & 12.9412458180924 & 1.05875418190755 \tabularnewline
229 & 11 & 12.2423518553558 & -1.24235185535583 \tabularnewline
230 & 12 & 12.8422756781471 & -0.842275678147151 \tabularnewline
231 & 13 & 10.6929356539006 & 2.30706434609943 \tabularnewline
232 & 10 & 13.7310868426761 & -3.7310868426761 \tabularnewline
233 & 16 & 11.6806645985775 & 4.31933540142245 \tabularnewline
234 & 18 & 15.1339841919662 & 2.86601580803384 \tabularnewline
235 & 13 & 13.4508816862766 & -0.450881686276635 \tabularnewline
236 & 11 & 12.6403601339811 & -1.64036013398109 \tabularnewline
237 & 4 & 10.2185991839173 & -6.21859918391726 \tabularnewline
238 & 13 & 13.5794551191926 & -0.579455119192583 \tabularnewline
239 & 16 & 14.0084161377658 & 1.9915838622342 \tabularnewline
240 & 10 & 10.7007996000469 & -0.700799600046881 \tabularnewline
241 & 12 & 12.06245829497 & -0.0624582949700043 \tabularnewline
242 & 12 & 13.7138232266365 & -1.71382322663655 \tabularnewline
243 & 10 & 8.8976350227211 & 1.1023649772789 \tabularnewline
244 & 13 & 10.8820038413952 & 2.11799615860479 \tabularnewline
245 & 15 & 12.8582217280672 & 2.14177827193283 \tabularnewline
246 & 12 & 12.5004430180822 & -0.500443018082235 \tabularnewline
247 & 14 & 13.126233093155 & 0.87376690684504 \tabularnewline
248 & 10 & 12.8110598932988 & -2.81105989329878 \tabularnewline
249 & 12 & 10.888381311566 & 1.11161868843402 \tabularnewline
250 & 12 & 11.4359968239255 & 0.564003176074509 \tabularnewline
251 & 11 & 12.0849147298808 & -1.08491472988076 \tabularnewline
252 & 10 & 11.3414207812061 & -1.34142078120605 \tabularnewline
253 & 12 & 10.9990501691664 & 1.00094983083355 \tabularnewline
254 & 16 & 12.5249603680063 & 3.47503963199372 \tabularnewline
255 & 12 & 12.9490178935796 & -0.949017893579647 \tabularnewline
256 & 14 & 13.6858637772946 & 0.314136222705359 \tabularnewline
257 & 16 & 14.3879254742619 & 1.6120745257381 \tabularnewline
258 & 14 & 11.7211481416927 & 2.27885185830732 \tabularnewline
259 & 13 & 13.9979112437533 & -0.997911243753274 \tabularnewline
260 & 4 & 8.23954017419469 & -4.23954017419469 \tabularnewline
261 & 15 & 13.843270687797 & 1.15672931220298 \tabularnewline
262 & 11 & 15.3297403317004 & -4.32974033170044 \tabularnewline
263 & 11 & 11.0362068643451 & -0.0362068643450975 \tabularnewline
264 & 14 & 12.8167087422723 & 1.18329125772766 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202578&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]15.9440565190857[/C][C]-2.94405651908571[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]16.2363436409125[/C][C]-0.23634364091247[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.5815908655627[/C][C]2.41840913443732[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.0390844657901[/C][C]2.9609155342099[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.45830173466[/C][C]-2.45830173466005[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]15.2783754710599[/C][C]-2.27837547105988[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.8390959917877[/C][C]3.16090400821228[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.8975453044673[/C][C]-1.89754530446734[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.9962188225434[/C][C]-1.99621882254335[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4903976290832[/C][C]0.509602370916777[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]15.4309127242641[/C][C]0.569087275735903[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]15.9458181094773[/C][C]0.0541818905227417[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.6008976060461[/C][C]0.399102393953892[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.3665171251354[/C][C]0.633482874864622[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.7638906496412[/C][C]-0.763890649641175[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.2420218355414[/C][C]-0.242021835541392[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.8813705507418[/C][C]0.118629449258239[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.5318025509177[/C][C]3.4681974490823[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.3700870379982[/C][C]2.6299129620018[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.3874618326048[/C][C]0.612538167395183[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.1826235848291[/C][C]0.817376415170891[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.0963603928938[/C][C]0.903639607106195[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.2161123209336[/C][C]2.78388767906639[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.8315087237026[/C][C]1.16849127629737[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.6373625207116[/C][C]0.362637479288438[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.5512391051188[/C][C]0.448760894881163[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.9816814371191[/C][C]1.01831856288093[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.4919081196921[/C][C]-1.49190811969211[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.7457832247579[/C][C]0.254216775242091[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.2232383184461[/C][C]-0.223238318446112[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.7097743338415[/C][C]-0.709774333841459[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.4616113118721[/C][C]-0.461611311872121[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]15.0889318175983[/C][C]-1.08893181759831[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.8720197968897[/C][C]0.127980203110276[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.6898721324382[/C][C]-1.68987213243815[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.9295370645357[/C][C]-2.9295370645357[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.9994597313448[/C][C]-2.99945973134484[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.8382228338837[/C][C]-1.83822283388374[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.4444587481061[/C][C]1.55554125189393[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.475303137931[/C][C]1.524696862069[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.9291161314462[/C][C]1.07088386855383[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.8034741256171[/C][C]-1.80347412561714[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.3500629397278[/C][C]2.64993706027219[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.0437664216633[/C][C]-0.0437664216633002[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.9611162832643[/C][C]-0.9611162832643[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.4688429291675[/C][C]-4.4688429291675[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.30354074625[/C][C]-2.30354074624999[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.0602439744061[/C][C]-0.0602439744061165[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.4153790472142[/C][C]0.584620952785766[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.8874635339514[/C][C]-1.88746353395141[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.5127229279992[/C][C]-0.512722927999202[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.2423891525918[/C][C]-0.242389152591754[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.9227371306956[/C][C]-2.9227371306956[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.6189147151572[/C][C]0.381085284842825[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.310404695743[/C][C]-2.31040469574303[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.743066710633[/C][C]1.25693328936703[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]16.1500795019895[/C][C]-0.150079501989472[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.0321992066337[/C][C]0.967800793366348[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.0491518114201[/C][C]-0.0491518114200926[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.307645252983[/C][C]1.69235474701699[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.6897453345998[/C][C]0.310254665400209[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.8444200272623[/C][C]0.155579972737695[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.4158760223166[/C][C]-0.415876022316569[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.2661270324814[/C][C]-0.26612703248142[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.2388507409698[/C][C]0.761149259030229[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]15.850318744403[/C][C]1.14968125559698[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.3053490550508[/C][C]1.6946509449492[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.5127788066808[/C][C]3.48722119331916[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.7134625958035[/C][C]-3.71346259580352[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.5109688170323[/C][C]0.489031182967691[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.5506652666734[/C][C]-3.55066526667343[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.3946930257855[/C][C]-0.394693025785526[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.6700749329515[/C][C]1.3299250670485[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]16.761675668301[/C][C]1.23832433169896[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.6654918255441[/C][C]0.334508174455855[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]14.316624801793[/C][C]2.683375198207[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.3751334365384[/C][C]-0.375133436538421[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.7751043230259[/C][C]1.22489567697406[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.0867490383646[/C][C]-2.08674903836457[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.3295824220483[/C][C]0.670417577951724[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.4917966828538[/C][C]0.508203317146203[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.4965931279436[/C][C]0.503406872056406[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.8511137741534[/C][C]-0.851113774153397[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.7532097479609[/C][C]0.246790252039134[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.3651545972111[/C][C]1.63484540278886[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.209319149896[/C][C]-0.209319149895987[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.2158276297318[/C][C]0.784172370268221[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.5076072253922[/C][C]1.4923927746078[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.6519184040208[/C][C]0.348081595979188[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.7385277319648[/C][C]-1.73852773196484[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.7063566560181[/C][C]0.293643343981867[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.5113200177579[/C][C]0.488679982242059[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.4380178290487[/C][C]-0.438017829048742[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]15.0139464249235[/C][C]-2.01394642492355[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]15.011733429994[/C][C]0.988266570005964[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.8796750426912[/C][C]0.120324957308769[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.9812549897288[/C][C]2.01874501027116[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]16.0095902503458[/C][C]-0.00959025034578832[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.2068186479575[/C][C]-0.206818647957546[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.0221381364917[/C][C]-1.02213813649165[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.8774102249967[/C][C]1.1225897750033[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4395113941604[/C][C]2.56048860583956[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.3022261105483[/C][C]0.697773889451698[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.8180512463431[/C][C]1.18194875365693[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]15.3503044683544[/C][C]-2.35030446835443[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.8680884158985[/C][C]1.13191158410155[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.8933131128838[/C][C]0.106686887116215[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.2203248596324[/C][C]1.77967514036762[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.4705261416388[/C][C]-0.470526141638752[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2402765027813[/C][C]0.759723497218674[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]15.8474464037919[/C][C]0.152553596208056[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]14.6709100280968[/C][C]2.32908997190318[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]13.8955434431428[/C][C]-0.895543443142771[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.8681530193762[/C][C]-2.86815301937621[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.5046478994667[/C][C]1.49535210053333[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.239273166593[/C][C]-1.23927316659303[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]12.9321013099215[/C][C]1.06789869007849[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.5353070593503[/C][C]-1.53530705935028[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.899458944726[/C][C]0.100541055274027[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.0386410349391[/C][C]-1.0386410349391[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.6514225803284[/C][C]0.348577419671636[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.9078827089936[/C][C]-2.9078827089936[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.6339920627059[/C][C]-0.633992062705861[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]16.0535128859177[/C][C]-1.05351288591774[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.5794602417009[/C][C]-0.579460241700854[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]15.2097822853631[/C][C]-0.209782285363102[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.7703390627542[/C][C]1.22966093724583[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.0722662733027[/C][C]0.927733726697263[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.8362505676798[/C][C]-2.83625056767976[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.8472851590545[/C][C]2.1527148409455[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.5951868615487[/C][C]-3.59518686154867[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.7228491853207[/C][C]2.27715081467934[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.0109075337477[/C][C]-2.01090753374774[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.4887788170539[/C][C]-1.48877881705388[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.4640134652598[/C][C]-0.464013465259818[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.5941731599697[/C][C]0.405826840030297[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.4241216729002[/C][C]0.575878327099804[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.1065325076259[/C][C]-2.10653250762593[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.0359223431769[/C][C]-1.03592234317685[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.1173218517186[/C][C]-2.11732185171859[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.565044401775[/C][C]3.43495559822504[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.5336838940743[/C][C]1.46631610592566[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.6015594955844[/C][C]0.398440504415638[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.6526746163764[/C][C]1.34732538362363[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]14.0681012372182[/C][C]-4.06810123721825[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.7982431276868[/C][C]2.2017568723132[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]14.7625289679238[/C][C]-1.76252896792382[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.847363294813[/C][C]1.15263670518698[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]13.2190152184265[/C][C]-0.219015218426485[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]13.1461397459846[/C][C]-3.14613974598463[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.3321807790856[/C][C]-1.33218077908561[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.58035084876[/C][C]2.41964915124[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.7473592377256[/C][C]4.2526407622744[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.829846368234[/C][C]1.17015363176601[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.9326217251075[/C][C]-2.93262172510748[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.418382675315[/C][C]0.581617324685043[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.6002708925272[/C][C]1.39972910747278[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.9393552052859[/C][C]1.06064479471411[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.6928260664654[/C][C]1.30717393353456[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.7530299290138[/C][C]-0.753029929013813[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.74917848362[/C][C]0.250821516379981[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.6173765362878[/C][C]0.38262346371218[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]11.5441609186264[/C][C]0.455839081373624[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]15.8317320283892[/C][C]1.16826797161076[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]14.1809613781732[/C][C]0.819038621826762[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]12.5162284574896[/C][C]-2.51622845748959[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.3993498832206[/C][C]-0.399349883220634[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]13.7491700074955[/C][C]-2.74917000749547[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.9069014283352[/C][C]-1.90690142833521[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]15.2383878242737[/C][C]0.761612175726268[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.2262798390239[/C][C]1.77372016097606[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.5226012063219[/C][C]0.477398793678094[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]12.9489417965926[/C][C]-0.948941796592602[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.024497259364[/C][C]-2.02449725936401[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.1003626138382[/C][C]-2.1003626138382[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.4492620644116[/C][C]0.550737935588401[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]11.8296619565241[/C][C]0.17033804347592[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6339706678772[/C][C]-0.633970667877187[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.7634707560475[/C][C]0.236529243952493[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.1058565971907[/C][C]-1.10585659719067[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.3051999894337[/C][C]0.694800010566342[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]10.7846321177231[/C][C]0.215367882276936[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]17.1947334581257[/C][C]1.80526654187433[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]14.2612345415922[/C][C]0.738765458407801[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.647244934307[/C][C]-6.64724493430698[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]15.1469221743111[/C][C]0.85307782568894[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.1781780695718[/C][C]2.82182193042824[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]11.2527116325001[/C][C]0.74728836749991[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.5406875312444[/C][C]-0.540687531244425[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]11.1376664801757[/C][C]-0.137666480175688[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]15.3288560535754[/C][C]-1.32885605357541[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.5350466640477[/C][C]0.464953335952285[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.88829815781971[/C][C]2.11170184218029[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.4720208858839[/C][C]1.52797911411606[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.625715265247[/C][C]-0.625715265246953[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.0924291635898[/C][C]-0.092429163589778[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.5953831349435[/C][C]3.40461686505647[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.1832552211262[/C][C]0.816744778873838[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4746486942216[/C][C]1.52535130577838[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.7832846085766[/C][C]1.21671539142336[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]13.8841108061721[/C][C]2.11588919382791[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.7626507534853[/C][C]0.237349246514671[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]12.9503773241019[/C][C]-1.95037732410186[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.577869551733[/C][C]-2.57786955173304[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.7144655901732[/C][C]2.28553440982683[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.6319119194852[/C][C]0.368088080514808[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.4922708811373[/C][C]1.50772911886274[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]15.4894971529552[/C][C]0.510502847044806[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.2958817978772[/C][C]-2.2958817978772[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.5817807360034[/C][C]1.41821926399659[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.1428623393701[/C][C]-2.14286233937013[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]16.0289096453871[/C][C]-4.02890964538706[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.5879846518168[/C][C]0.412015348183227[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]11.8903150954748[/C][C]3.10968490452521[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.5729704001091[/C][C]1.42702959989093[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]12.7400885588807[/C][C]1.25991144111931[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5832982369277[/C][C]2.41670176307235[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.2110935592794[/C][C]0.788906440720609[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.9814957048625[/C][C]1.01850429513746[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.4008285553322[/C][C]-0.40082855533223[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.1321980260207[/C][C]-1.13219802602067[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.0682872710141[/C][C]-0.068287271014069[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.0115837065275[/C][C]0.988416293472523[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]12.9922206451188[/C][C]-0.992220645118751[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]13.1569941546857[/C][C]-0.15699415468565[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.9112755129364[/C][C]-3.91127551293636[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]14.1924632927691[/C][C]-0.192463292769131[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.9412458180924[/C][C]1.05875418190755[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.2423518553558[/C][C]-1.24235185535583[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.8422756781471[/C][C]-0.842275678147151[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]10.6929356539006[/C][C]2.30706434609943[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.7310868426761[/C][C]-3.7310868426761[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.6806645985775[/C][C]4.31933540142245[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.1339841919662[/C][C]2.86601580803384[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.4508816862766[/C][C]-0.450881686276635[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.6403601339811[/C][C]-1.64036013398109[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.2185991839173[/C][C]-6.21859918391726[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.5794551191926[/C][C]-0.579455119192583[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.0084161377658[/C][C]1.9915838622342[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]10.7007996000469[/C][C]-0.700799600046881[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.06245829497[/C][C]-0.0624582949700043[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.7138232266365[/C][C]-1.71382322663655[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.8976350227211[/C][C]1.1023649772789[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]10.8820038413952[/C][C]2.11799615860479[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]12.8582217280672[/C][C]2.14177827193283[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]12.5004430180822[/C][C]-0.500443018082235[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]13.126233093155[/C][C]0.87376690684504[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.8110598932988[/C][C]-2.81105989329878[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.888381311566[/C][C]1.11161868843402[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.4359968239255[/C][C]0.564003176074509[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]12.0849147298808[/C][C]-1.08491472988076[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.3414207812061[/C][C]-1.34142078120605[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]10.9990501691664[/C][C]1.00094983083355[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.5249603680063[/C][C]3.47503963199372[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]12.9490178935796[/C][C]-0.949017893579647[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.6858637772946[/C][C]0.314136222705359[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.3879254742619[/C][C]1.6120745257381[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.7211481416927[/C][C]2.27885185830732[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]13.9979112437533[/C][C]-0.997911243753274[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]8.23954017419469[/C][C]-4.23954017419469[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.843270687797[/C][C]1.15672931220298[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]15.3297403317004[/C][C]-4.32974033170044[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.0362068643451[/C][C]-0.0362068643450975[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.8167087422723[/C][C]1.18329125772766[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202578&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202578&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
11315.9440565190857-2.94405651908571
21616.2363436409125-0.23634364091247
31916.58159086556272.41840913443732
41512.03908446579012.9609155342099
51416.45830173466-2.45830173466005
61315.2783754710599-2.27837547105988
71915.83909599178773.16090400821228
81516.8975453044673-1.89754530446734
91415.9962188225434-1.99621882254335
101514.49039762908320.509602370916777
111615.43091272426410.569087275735903
121615.94581810947730.0541818905227417
131615.60089760604610.399102393953892
141615.36651712513540.633482874864622
151717.7638906496412-0.763890649641175
161515.2420218355414-0.242021835541392
171514.88137055074180.118629449258239
182016.53180255091773.4681974490823
191815.37008703799822.6299129620018
201615.38746183260480.612538167395183
211615.18262358482910.817376415170891
221615.09636039289380.903639607106195
231916.21611232093362.78388767906639
241614.83150872370261.16849127629737
251716.63736252071160.362637479288438
261716.55123910511880.448760894881163
271614.98168143711911.01831856288093
281516.4919081196921-1.49190811969211
291615.74578322475790.254216775242091
301414.2232383184461-0.223238318446112
311515.7097743338415-0.709774333841459
321212.4616113118721-0.461611311872121
331415.0889318175983-1.08893181759831
341615.87201979688970.127980203110276
351415.6898721324382-1.68987213243815
361012.9295370645357-2.9295370645357
371012.9994597313448-2.99945973134484
381415.8382228338837-1.83822283388374
391614.44445874810611.55554125189393
401614.4753031379311.524696862069
411614.92911613144621.07088386855383
421415.8034741256171-1.80347412561714
432017.35006293972782.64993706027219
441414.0437664216633-0.0437664216633002
451414.9611162832643-0.9611162832643
461115.4688429291675-4.4688429291675
471416.30354074625-2.30354074624999
481515.0602439744061-0.0602439744061165
491615.41537904721420.584620952785766
501415.8874635339514-1.88746353395141
511616.5127229279992-0.512722927999202
521414.2423891525918-0.242389152591754
531214.9227371306956-2.9227371306956
541615.61891471515720.381085284842825
55911.310404695743-2.31040469574303
561412.7430667106331.25693328936703
571616.1500795019895-0.150079501989472
581615.03219920663370.967800793366348
591515.0491518114201-0.0491518114200926
601614.3076452529831.69235474701699
611211.68974533459980.310254665400209
621615.84442002726230.155579972737695
631616.4158760223166-0.415876022316569
641414.2661270324814-0.26612703248142
651615.23885074096980.761149259030229
661715.8503187444031.14968125559698
671816.30534905505081.6946509449492
681814.51277880668083.48722119331916
691215.7134625958035-3.71346259580352
701615.51096881703230.489031182967691
711013.5506652666734-3.55066526667343
721414.3946930257855-0.394693025785526
731816.67007493295151.3299250670485
741816.7616756683011.23832433169896
751615.66549182554410.334508174455855
761714.3166248017932.683375198207
771616.3751334365384-0.375133436538421
781614.77510432302591.22489567697406
791315.0867490383646-2.08674903836457
801615.32958242204830.670417577951724
811615.49179668285380.508203317146203
821615.49659312794360.503406872056406
831515.8511137741534-0.851113774153397
841514.75320974796090.246790252039134
851614.36515459721111.63484540278886
861414.209319149896-0.209319149895987
871615.21582762973180.784172370268221
881614.50760722539221.4923927746078
891514.65191840402080.348081595979188
901213.7385277319648-1.73852773196484
911716.70635665601810.293643343981867
921615.51132001775790.488679982242059
931515.4380178290487-0.438017829048742
941315.0139464249235-2.01394642492355
951615.0117334299940.988266570005964
961615.87967504269120.120324957308769
971613.98125498972882.01874501027116
981616.0095902503458-0.00959025034578832
991414.2068186479575-0.206818647957546
1001617.0221381364917-1.02213813649165
1011614.87741022499671.1225897750033
1022017.43951139416042.56048860583956
1031514.30222611054830.697773889451698
1041614.81805124634311.18194875365693
1051315.3503044683544-2.35030446835443
1061715.86808841589851.13191158410155
1071615.89331311288380.106686887116215
1081614.22032485963241.77967514036762
1091212.4705261416388-0.470526141638752
1101615.24027650278130.759723497218674
1111615.84744640379190.152553596208056
1121714.67091002809682.32908997190318
1131313.8955434431428-0.895543443142771
1141214.8681530193762-2.86815301937621
1151816.50464789946671.49535210053333
1161415.239273166593-1.23927316659303
1171412.93210130992151.06789869007849
1181314.5353070593503-1.53530705935028
1191615.8994589447260.100541055274027
1201314.0386410349391-1.0386410349391
1211615.65142258032840.348577419671636
1221315.9078827089936-2.9078827089936
1231616.6339920627059-0.633992062705861
1241516.0535128859177-1.05351288591774
1251616.5794602417009-0.579460241700854
1261515.2097822853631-0.209782285363102
1271715.77033906275421.22966093724583
1281514.07226627330270.927733726697263
1291214.8362505676798-2.83625056767976
1301613.84728515905452.1527148409455
1311013.5951868615487-3.59518686154867
1321613.72284918532072.27715081467934
1331214.0109075337477-2.01090753374774
1341415.4887788170539-1.48877881705388
1351515.4640134652598-0.464013465259818
1361312.59417315996970.405826840030297
1371514.42412167290020.575878327099804
1381113.1065325076259-2.10653250762593
1391213.0359223431769-1.03592234317685
1401113.1173218517186-2.11732185171859
1411612.5650444017753.43495559822504
1421513.53368389407431.46631610592566
1431716.60155949558440.398440504415638
1441614.65267461637641.34732538362363
1451014.0681012372182-4.06810123721825
1461815.79824312768682.2017568723132
1471314.7625289679238-1.76252896792382
1481614.8473632948131.15263670518698
1491313.2190152184265-0.219015218426485
1501013.1461397459846-3.14613974598463
1511516.3321807790856-1.33218077908561
1521613.580350848762.41964915124
1531611.74735923772564.2526407622744
1541412.8298463682341.17015363176601
1551012.9326217251075-2.93262172510748
1561716.4183826753150.581617324685043
1571311.60027089252721.39972910747278
1581513.93935520528591.06064479471411
1591614.69282606646541.30717393353456
1601212.7530299290138-0.753029929013813
1611312.749178483620.250821516379981
1621312.61737653628780.38262346371218
1631211.54416091862640.455839081373624
1641715.83173202838921.16826797161076
1651514.18096137817320.819038621826762
1661012.5162284574896-2.51622845748959
1671414.3993498832206-0.399349883220634
1681113.7491700074955-2.74917000749547
1691314.9069014283352-1.90690142833521
1701615.23838782427370.761612175726268
1711210.22627983902391.77372016097606
1721615.52260120632190.477398793678094
1731212.9489417965926-0.948941796592602
174911.024497259364-2.02449725936401
1751214.1003626138382-2.1003626138382
1761514.44926206441160.550737935588401
1771211.82966195652410.17033804347592
1781212.6339706678772-0.633970667877187
1791413.76347075604750.236529243952493
1801213.1058565971907-1.10585659719067
1811615.30519998943370.694800010566342
1821110.78463211772310.215367882276936
1831917.19473345812571.80526654187433
1841514.26123454159220.738765458407801
185814.647244934307-6.64724493430698
1861615.14692217431110.85307782568894
1871714.17817806957182.82182193042824
1881211.25271163250010.74728836749991
1891111.5406875312444-0.540687531244425
1901111.1376664801757-0.137666480175688
1911415.3288560535754-1.32885605357541
1921615.53504666404770.464953335952285
193129.888298157819712.11170184218029
1941614.47202088588391.52797911411606
1951313.625715265247-0.625715265246953
1961515.0924291635898-0.092429163589778
1971612.59538313494353.40461686505647
1981615.18325522112620.816744778873838
1991412.47464869422161.52535130577838
2001614.78328460857661.21671539142336
2011613.88411080617212.11588919382791
2021413.76265075348530.237349246514671
2031112.9503773241019-1.95037732410186
2041214.577869551733-2.57786955173304
2051512.71446559017322.28553440982683
2061514.63191191948520.368088080514808
2071614.49227088113731.50772911886274
2081615.48949715295520.510502847044806
2091113.2958817978772-2.2958817978772
2101513.58178073600341.41821926399659
2111214.1428623393701-2.14286233937013
2121216.0289096453871-4.02890964538706
2131514.58798465181680.412015348183227
2141511.89031509547483.10968490452521
2151614.57297040010911.42702959989093
2161412.74008855888071.25991144111931
2171714.58329823692772.41670176307235
2181413.21109355927940.788906440720609
2191311.98149570486251.01850429513746
2201515.4008285553322-0.40082855533223
2211314.1321980260207-1.13219802602067
2221414.0682872710141-0.068287271014069
2231514.01158370652750.988416293472523
2241212.9922206451188-0.992220645118751
2251313.1569941546857-0.15699415468565
226811.9112755129364-3.91127551293636
2271414.1924632927691-0.192463292769131
2281412.94124581809241.05875418190755
2291112.2423518553558-1.24235185535583
2301212.8422756781471-0.842275678147151
2311310.69293565390062.30706434609943
2321013.7310868426761-3.7310868426761
2331611.68066459857754.31933540142245
2341815.13398419196622.86601580803384
2351313.4508816862766-0.450881686276635
2361112.6403601339811-1.64036013398109
237410.2185991839173-6.21859918391726
2381313.5794551191926-0.579455119192583
2391614.00841613776581.9915838622342
2401010.7007996000469-0.700799600046881
2411212.06245829497-0.0624582949700043
2421213.7138232266365-1.71382322663655
243108.89763502272111.1023649772789
2441310.88200384139522.11799615860479
2451512.85822172806722.14177827193283
2461212.5004430180822-0.500443018082235
2471413.1262330931550.87376690684504
2481012.8110598932988-2.81105989329878
2491210.8883813115661.11161868843402
2501211.43599682392550.564003176074509
2511112.0849147298808-1.08491472988076
2521011.3414207812061-1.34142078120605
2531210.99905016916641.00094983083355
2541612.52496036800633.47503963199372
2551212.9490178935796-0.949017893579647
2561413.68586377729460.314136222705359
2571614.38792547426191.6120745257381
2581411.72114814169272.27885185830732
2591313.9979112437533-0.997911243753274
26048.23954017419469-4.23954017419469
2611513.8432706877971.15672931220298
2621115.3297403317004-4.32974033170044
2631111.0362068643451-0.0362068643450975
2641412.81670874227231.18329125772766







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
170.9779550875552120.04408982488957550.0220449124447877
180.9950186867951540.009962626409692230.00498131320484611
190.9910434663162510.0179130673674980.00895653368374899
200.9830046814190420.03399063716191580.0169953185809579
210.9692392514126340.06152149717473240.0307607485873662
220.9564157543079360.08716849138412860.0435842456920643
230.9414194235947140.1171611528105720.0585805764052862
240.9250375681141760.1499248637716490.0749624318858244
250.893277797090330.213444405819340.10672220290967
260.8662789262045390.2674421475909220.133721073795461
270.8239714167733330.3520571664533330.176028583226667
280.8405239322428840.3189521355142310.159476067757116
290.7947577695771710.4104844608456590.205242230422829
300.793390342552390.4132193148952190.20660965744761
310.7504450742193430.4991098515613130.249554925780656
320.7383233145921520.5233533708156960.261676685407848
330.7154342195052370.5691315609895260.284565780494763
340.6567400579175930.6865198841648130.343259942082407
350.6390602109418210.7218795781163580.360939789058179
360.7235918238734270.5528163522531470.276408176126573
370.7838673047604630.4322653904790750.216132695239537
380.7630969177182060.4738061645635890.236903082281794
390.794378314953960.411243370092080.20562168504604
400.7799661068543650.440067786291270.220033893145635
410.7498971712739240.5002056574521520.250102828726076
420.7296126912497470.5407746175005060.270387308750253
430.7554862618644940.4890274762710120.244513738135506
440.71504565885460.5699086822907990.2849543411454
450.679042281927180.641915436145640.32095771807282
460.8463515401532580.3072969196934840.153648459846742
470.8477800979009190.3044398041981630.152219902099081
480.8207314832903230.3585370334193550.179268516709677
490.7969672131486150.4060655737027710.203032786851385
500.777383743963250.44523251207350.22261625603675
510.73970579627690.52058840744620.2602942037231
520.7005411210383970.5989177579232050.299458878961603
530.7168838912464290.5662322175071410.283116108753571
540.6864670879923660.6270658240152680.313532912007634
550.6809407427339980.6381185145320050.319059257266002
560.6753136628641480.6493726742717040.324686337135852
570.6331751838406370.7336496323187260.366824816159363
580.6239232075620880.7521535848758240.376076792437912
590.5831467885220070.8337064229559850.416853211477993
600.597191195157750.8056176096844990.40280880484225
610.5625028809858130.8749942380283750.437497119014187
620.5218046151616520.9563907696766950.478195384838348
630.4800252619533680.9600505239067360.519974738046632
640.435406107910670.8708122158213390.56459389208933
650.4016044313180890.8032088626361790.598395568681911
660.388656308651110.7773126173022190.61134369134889
670.3842509067864860.7685018135729720.615749093213514
680.5177200560945230.9645598878109540.482279943905477
690.630617026494020.7387659470119590.36938297350598
700.5954160079073770.8091679841852460.404583992092623
710.6723711584608620.6552576830782750.327628841539137
720.6348543777328340.7302912445343320.365145622267166
730.6246708958679780.7506582082640450.375329104132022
740.6066483835577190.7867032328845620.393351616442281
750.5664999471467840.8670001057064320.433500052853216
760.6075920349676050.7848159300647890.392407965032395
770.5683178932687980.8633642134624050.431682106731202
780.5415581341885770.9168837316228460.458441865811423
790.5492965079020110.9014069841959790.450703492097989
800.5105676574295310.9788646851409380.489432342570469
810.4749516849870430.9499033699740860.525048315012957
820.4383894058297150.8767788116594310.561610594170285
830.4074304583241230.8148609166482460.592569541675877
840.3702547028324980.7405094056649960.629745297167502
850.3605181470943090.7210362941886180.639481852905691
860.3240333842846530.6480667685693060.675966615715347
870.2938873788514840.5877747577029680.706112621148516
880.2777302406271930.5554604812543860.722269759372807
890.2464300516126880.4928601032253760.753569948387312
900.2387403191129940.4774806382259870.761259680887006
910.2108160588742350.421632117748470.789183941125765
920.1867657320288050.3735314640576090.813234267971195
930.1640247807015460.3280495614030920.835975219298454
940.1703222636513120.3406445273026250.829677736348688
950.1533052193970030.3066104387940070.846694780602997
960.1315470358125150.263094071625030.868452964187485
970.1341529591981130.2683059183962270.865847040801887
980.1141902996061830.2283805992123650.885809700393817
990.09692825908044720.1938565181608940.903071740919553
1000.0866880830820240.1733761661640480.913311916917976
1010.07692686469778790.1538537293955760.923073135302212
1020.08925782461949090.1785156492389820.910742175380509
1030.07676477124007940.1535295424801590.923235228759921
1040.06931156604158130.1386231320831630.930688433958419
1050.08137706855224940.1627541371044990.918622931447751
1060.07273599574737620.1454719914947520.927264004252624
1070.06092819459853760.1218563891970750.939071805401462
1080.06154275615391670.1230855123078330.938457243846083
1090.05194774227158370.1038954845431670.948052257728416
1100.04413478284154250.08826956568308490.955865217158458
1110.03696479495482160.07392958990964320.963035205045178
1120.04545168057633380.09090336115266760.954548319423666
1130.03886715595143680.07773431190287370.961132844048563
1140.05095299485280770.1019059897056150.949047005147192
1150.04984357181055250.0996871436211050.950156428189448
1160.04427891095688970.08855782191377940.95572108904311
1170.04036899393477670.08073798786955350.959631006065223
1180.03695122869740330.07390245739480670.963048771302597
1190.03256742226337280.06513484452674570.967432577736627
1200.02754500052856950.05509000105713910.97245499947143
1210.02328702475222510.04657404950445030.976712975247775
1220.02888276090374820.05776552180749650.971117239096252
1230.02373924291598290.04747848583196590.976260757084017
1240.02005425156554160.04010850313108320.979945748434458
1250.01661382092386040.03322764184772070.98338617907614
1260.01332666533423540.02665333066847090.986673334665765
1270.01248359189361140.02496718378722280.987516408106389
1280.01079945287783880.02159890575567760.989200547122161
1290.01324600827588260.02649201655176520.986753991724117
1300.01667034516504480.03334069033008970.983329654834955
1310.02499479687049320.04998959374098640.975005203129507
1320.03752810325106340.07505620650212690.962471896748937
1330.03985263731822840.07970527463645680.960147362681772
1340.0349080697220820.06981613944416410.965091930277918
1350.02856609941917890.05713219883835770.971433900580821
1360.02374537464284180.04749074928568370.976254625357158
1370.02000386812088870.04000773624177740.979996131879111
1380.02413967294481510.04827934588963030.975860327055185
1390.02058014504569840.04116029009139680.979419854954302
1400.02651359628560590.05302719257121190.973486403714394
1410.03596954055510180.07193908111020360.964030459444898
1420.0322941684533620.06458833690672390.967705831546638
1430.02672852241373140.05345704482746280.973271477586269
1440.02347756688037320.04695513376074640.976522433119627
1450.03511284130417570.07022568260835130.964887158695824
1460.03814574654888720.07629149309777430.961854253451113
1470.04539737831891030.09079475663782060.95460262168109
1480.03934778932759860.07869557865519730.960652210672401
1490.03211262051082590.06422524102165180.967887379489174
1500.04268877707409690.08537755414819380.957311222925903
1510.05027607260586030.1005521452117210.94972392739414
1520.05186555067995630.1037311013599130.948134449320044
1530.07603465209323060.1520693041864610.923965347906769
1540.0804755300590510.1609510601181020.919524469940949
1550.08148259539578190.1629651907915640.918517404604218
1560.06890511576390460.1378102315278090.931094884236095
1570.0604351108358440.1208702216716880.939564889164156
1580.05150584558426630.1030116911685330.948494154415734
1590.04418640624898050.08837281249796110.955813593751019
1600.03663738579590310.07327477159180620.963362614204097
1610.02974948022484740.05949896044969480.970250519775153
1620.02404619813717260.04809239627434520.975953801862827
1630.01934760252277180.03869520504554360.980652397477228
1640.01618200824344360.03236401648688720.983817991756556
1650.01307079735971270.02614159471942530.986929202640287
1660.01305537019005960.02611074038011920.98694462980994
1670.0102469789445370.02049395788907390.989753021055463
1680.01101481111912360.02202962223824720.988985188880876
1690.01020063473567990.02040126947135990.98979936526432
1700.00848747534276590.01697495068553180.991512524657234
1710.01007545488037960.02015090976075920.98992454511962
1720.007861468588951230.01572293717790250.992138531411049
1730.006494486776939350.01298897355387870.993505513223061
1740.00624391504178240.01248783008356480.993756084958218
1750.006180905955750490.0123618119115010.99381909404425
1760.005235421400849430.01047084280169890.994764578599151
1770.00406258827243040.008125176544860810.99593741172757
1780.00331028131032040.006620562620640810.99668971868968
1790.00253941585122750.0050788317024550.997460584148772
1800.002141008960451010.004282017920902020.997858991039549
1810.001649175218778680.003298350437557360.998350824781221
1820.001216170421107310.002432340842214620.998783829578893
1830.001205689014739810.002411378029479630.99879431098526
1840.0009084383757359310.001816876751471860.999091561624264
1850.02235648217360940.04471296434721880.977643517826391
1860.01919159342655490.03838318685310990.980808406573445
1870.02347535473284290.04695070946568580.976524645267157
1880.01908765521684830.03817531043369650.980912344783152
1890.0164597524357790.03291950487155790.983540247564221
1900.01282077428276460.02564154856552920.987179225717235
1910.01211008146812190.02422016293624390.987889918531878
1920.009392308823360320.01878461764672060.99060769117664
1930.009012755531288280.01802551106257660.990987244468712
1940.008041758626017020.0160835172520340.991958241373983
1950.006542561835958250.01308512367191650.993457438164042
1960.004867918089105140.009735836178210290.995132081910895
1970.008273157192693270.01654631438538650.991726842807307
1980.006298744336119380.01259748867223880.993701255663881
1990.005531506791185120.01106301358237020.994468493208815
2000.004577844216077060.009155688432154120.995422155783923
2010.004131965889697060.008263931779394130.995868034110303
2020.00320494913838090.006409898276761810.996795050861619
2030.003738698191705140.007477396383410280.996261301808295
2040.005626306141211840.01125261228242370.994373693858788
2050.005556043483016570.01111208696603310.994443956516983
2060.00404293286866770.00808586573733540.995957067131332
2070.003341727450652120.006683454901304240.996658272549348
2080.002415683607813080.004831367215626150.997584316392187
2090.002985965927161990.005971931854323980.997014034072838
2100.002309858196491990.004619716392983980.997690141803508
2110.002863571442413230.005727142884826470.997136428557587
2120.007697196418164440.01539439283632890.992302803581836
2130.00551983437004560.01103966874009120.994480165629954
2140.006994681128725760.01398936225745150.993005318871274
2150.005516466018934750.01103293203786950.994483533981065
2160.004064985869492120.008129971738984240.995935014130508
2170.004284167379998780.008568334759997570.995715832620001
2180.003380626327490290.006761252654980580.99661937367251
2190.002861142789383170.005722285578766330.997138857210617
2200.001986036276292270.003972072552584540.998013963723708
2210.001487738294423310.002975476588846630.998512261705577
2220.0009940237907459940.001988047581491990.999005976209254
2230.000687627520339790.001375255040679580.99931237247966
2240.000481678381968720.0009633567639374390.999518321618031
2250.0003022356807954730.0006044713615909450.999697764319205
2260.0008276246188555640.001655249237711130.999172375381144
2270.000603937611804310.001207875223608620.999396062388196
2280.0003994449856239570.0007988899712479150.999600555014376
2290.000267407853993050.0005348157079861010.999732592146007
2300.0001681695905248750.0003363391810497510.999831830409475
2310.0001772597702539770.0003545195405079540.999822740229746
2320.000734775027998520.001469550055997040.999265224972001
2330.003580828309309280.007161656618618550.996419171690691
2340.005924061336728940.01184812267345790.994075938663271
2350.003744029407671640.007488058815343270.996255970592328
2360.002615348166964550.00523069633392910.997384651833035
2370.0378183870842050.075636774168410.962181612915795
2380.02590267360097340.05180534720194690.974097326399027
2390.01752929973707020.03505859947414040.98247070026293
2400.01193945928264010.02387891856528010.98806054071736
2410.009769453430093990.0195389068601880.990230546569906
2420.0140459992101740.02809199842034810.985954000789826
2430.009475560151936590.01895112030387320.990524439848063
2440.009194010494654850.01838802098930970.990805989505345
2450.00597192116816740.01194384233633480.994028078831833
2460.003827923506940760.007655847013881520.996172076493059
2470.001450931372056490.002901862744112980.998549068627943

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
17 & 0.977955087555212 & 0.0440898248895755 & 0.0220449124447877 \tabularnewline
18 & 0.995018686795154 & 0.00996262640969223 & 0.00498131320484611 \tabularnewline
19 & 0.991043466316251 & 0.017913067367498 & 0.00895653368374899 \tabularnewline
20 & 0.983004681419042 & 0.0339906371619158 & 0.0169953185809579 \tabularnewline
21 & 0.969239251412634 & 0.0615214971747324 & 0.0307607485873662 \tabularnewline
22 & 0.956415754307936 & 0.0871684913841286 & 0.0435842456920643 \tabularnewline
23 & 0.941419423594714 & 0.117161152810572 & 0.0585805764052862 \tabularnewline
24 & 0.925037568114176 & 0.149924863771649 & 0.0749624318858244 \tabularnewline
25 & 0.89327779709033 & 0.21344440581934 & 0.10672220290967 \tabularnewline
26 & 0.866278926204539 & 0.267442147590922 & 0.133721073795461 \tabularnewline
27 & 0.823971416773333 & 0.352057166453333 & 0.176028583226667 \tabularnewline
28 & 0.840523932242884 & 0.318952135514231 & 0.159476067757116 \tabularnewline
29 & 0.794757769577171 & 0.410484460845659 & 0.205242230422829 \tabularnewline
30 & 0.79339034255239 & 0.413219314895219 & 0.20660965744761 \tabularnewline
31 & 0.750445074219343 & 0.499109851561313 & 0.249554925780656 \tabularnewline
32 & 0.738323314592152 & 0.523353370815696 & 0.261676685407848 \tabularnewline
33 & 0.715434219505237 & 0.569131560989526 & 0.284565780494763 \tabularnewline
34 & 0.656740057917593 & 0.686519884164813 & 0.343259942082407 \tabularnewline
35 & 0.639060210941821 & 0.721879578116358 & 0.360939789058179 \tabularnewline
36 & 0.723591823873427 & 0.552816352253147 & 0.276408176126573 \tabularnewline
37 & 0.783867304760463 & 0.432265390479075 & 0.216132695239537 \tabularnewline
38 & 0.763096917718206 & 0.473806164563589 & 0.236903082281794 \tabularnewline
39 & 0.79437831495396 & 0.41124337009208 & 0.20562168504604 \tabularnewline
40 & 0.779966106854365 & 0.44006778629127 & 0.220033893145635 \tabularnewline
41 & 0.749897171273924 & 0.500205657452152 & 0.250102828726076 \tabularnewline
42 & 0.729612691249747 & 0.540774617500506 & 0.270387308750253 \tabularnewline
43 & 0.755486261864494 & 0.489027476271012 & 0.244513738135506 \tabularnewline
44 & 0.7150456588546 & 0.569908682290799 & 0.2849543411454 \tabularnewline
45 & 0.67904228192718 & 0.64191543614564 & 0.32095771807282 \tabularnewline
46 & 0.846351540153258 & 0.307296919693484 & 0.153648459846742 \tabularnewline
47 & 0.847780097900919 & 0.304439804198163 & 0.152219902099081 \tabularnewline
48 & 0.820731483290323 & 0.358537033419355 & 0.179268516709677 \tabularnewline
49 & 0.796967213148615 & 0.406065573702771 & 0.203032786851385 \tabularnewline
50 & 0.77738374396325 & 0.4452325120735 & 0.22261625603675 \tabularnewline
51 & 0.7397057962769 & 0.5205884074462 & 0.2602942037231 \tabularnewline
52 & 0.700541121038397 & 0.598917757923205 & 0.299458878961603 \tabularnewline
53 & 0.716883891246429 & 0.566232217507141 & 0.283116108753571 \tabularnewline
54 & 0.686467087992366 & 0.627065824015268 & 0.313532912007634 \tabularnewline
55 & 0.680940742733998 & 0.638118514532005 & 0.319059257266002 \tabularnewline
56 & 0.675313662864148 & 0.649372674271704 & 0.324686337135852 \tabularnewline
57 & 0.633175183840637 & 0.733649632318726 & 0.366824816159363 \tabularnewline
58 & 0.623923207562088 & 0.752153584875824 & 0.376076792437912 \tabularnewline
59 & 0.583146788522007 & 0.833706422955985 & 0.416853211477993 \tabularnewline
60 & 0.59719119515775 & 0.805617609684499 & 0.40280880484225 \tabularnewline
61 & 0.562502880985813 & 0.874994238028375 & 0.437497119014187 \tabularnewline
62 & 0.521804615161652 & 0.956390769676695 & 0.478195384838348 \tabularnewline
63 & 0.480025261953368 & 0.960050523906736 & 0.519974738046632 \tabularnewline
64 & 0.43540610791067 & 0.870812215821339 & 0.56459389208933 \tabularnewline
65 & 0.401604431318089 & 0.803208862636179 & 0.598395568681911 \tabularnewline
66 & 0.38865630865111 & 0.777312617302219 & 0.61134369134889 \tabularnewline
67 & 0.384250906786486 & 0.768501813572972 & 0.615749093213514 \tabularnewline
68 & 0.517720056094523 & 0.964559887810954 & 0.482279943905477 \tabularnewline
69 & 0.63061702649402 & 0.738765947011959 & 0.36938297350598 \tabularnewline
70 & 0.595416007907377 & 0.809167984185246 & 0.404583992092623 \tabularnewline
71 & 0.672371158460862 & 0.655257683078275 & 0.327628841539137 \tabularnewline
72 & 0.634854377732834 & 0.730291244534332 & 0.365145622267166 \tabularnewline
73 & 0.624670895867978 & 0.750658208264045 & 0.375329104132022 \tabularnewline
74 & 0.606648383557719 & 0.786703232884562 & 0.393351616442281 \tabularnewline
75 & 0.566499947146784 & 0.867000105706432 & 0.433500052853216 \tabularnewline
76 & 0.607592034967605 & 0.784815930064789 & 0.392407965032395 \tabularnewline
77 & 0.568317893268798 & 0.863364213462405 & 0.431682106731202 \tabularnewline
78 & 0.541558134188577 & 0.916883731622846 & 0.458441865811423 \tabularnewline
79 & 0.549296507902011 & 0.901406984195979 & 0.450703492097989 \tabularnewline
80 & 0.510567657429531 & 0.978864685140938 & 0.489432342570469 \tabularnewline
81 & 0.474951684987043 & 0.949903369974086 & 0.525048315012957 \tabularnewline
82 & 0.438389405829715 & 0.876778811659431 & 0.561610594170285 \tabularnewline
83 & 0.407430458324123 & 0.814860916648246 & 0.592569541675877 \tabularnewline
84 & 0.370254702832498 & 0.740509405664996 & 0.629745297167502 \tabularnewline
85 & 0.360518147094309 & 0.721036294188618 & 0.639481852905691 \tabularnewline
86 & 0.324033384284653 & 0.648066768569306 & 0.675966615715347 \tabularnewline
87 & 0.293887378851484 & 0.587774757702968 & 0.706112621148516 \tabularnewline
88 & 0.277730240627193 & 0.555460481254386 & 0.722269759372807 \tabularnewline
89 & 0.246430051612688 & 0.492860103225376 & 0.753569948387312 \tabularnewline
90 & 0.238740319112994 & 0.477480638225987 & 0.761259680887006 \tabularnewline
91 & 0.210816058874235 & 0.42163211774847 & 0.789183941125765 \tabularnewline
92 & 0.186765732028805 & 0.373531464057609 & 0.813234267971195 \tabularnewline
93 & 0.164024780701546 & 0.328049561403092 & 0.835975219298454 \tabularnewline
94 & 0.170322263651312 & 0.340644527302625 & 0.829677736348688 \tabularnewline
95 & 0.153305219397003 & 0.306610438794007 & 0.846694780602997 \tabularnewline
96 & 0.131547035812515 & 0.26309407162503 & 0.868452964187485 \tabularnewline
97 & 0.134152959198113 & 0.268305918396227 & 0.865847040801887 \tabularnewline
98 & 0.114190299606183 & 0.228380599212365 & 0.885809700393817 \tabularnewline
99 & 0.0969282590804472 & 0.193856518160894 & 0.903071740919553 \tabularnewline
100 & 0.086688083082024 & 0.173376166164048 & 0.913311916917976 \tabularnewline
101 & 0.0769268646977879 & 0.153853729395576 & 0.923073135302212 \tabularnewline
102 & 0.0892578246194909 & 0.178515649238982 & 0.910742175380509 \tabularnewline
103 & 0.0767647712400794 & 0.153529542480159 & 0.923235228759921 \tabularnewline
104 & 0.0693115660415813 & 0.138623132083163 & 0.930688433958419 \tabularnewline
105 & 0.0813770685522494 & 0.162754137104499 & 0.918622931447751 \tabularnewline
106 & 0.0727359957473762 & 0.145471991494752 & 0.927264004252624 \tabularnewline
107 & 0.0609281945985376 & 0.121856389197075 & 0.939071805401462 \tabularnewline
108 & 0.0615427561539167 & 0.123085512307833 & 0.938457243846083 \tabularnewline
109 & 0.0519477422715837 & 0.103895484543167 & 0.948052257728416 \tabularnewline
110 & 0.0441347828415425 & 0.0882695656830849 & 0.955865217158458 \tabularnewline
111 & 0.0369647949548216 & 0.0739295899096432 & 0.963035205045178 \tabularnewline
112 & 0.0454516805763338 & 0.0909033611526676 & 0.954548319423666 \tabularnewline
113 & 0.0388671559514368 & 0.0777343119028737 & 0.961132844048563 \tabularnewline
114 & 0.0509529948528077 & 0.101905989705615 & 0.949047005147192 \tabularnewline
115 & 0.0498435718105525 & 0.099687143621105 & 0.950156428189448 \tabularnewline
116 & 0.0442789109568897 & 0.0885578219137794 & 0.95572108904311 \tabularnewline
117 & 0.0403689939347767 & 0.0807379878695535 & 0.959631006065223 \tabularnewline
118 & 0.0369512286974033 & 0.0739024573948067 & 0.963048771302597 \tabularnewline
119 & 0.0325674222633728 & 0.0651348445267457 & 0.967432577736627 \tabularnewline
120 & 0.0275450005285695 & 0.0550900010571391 & 0.97245499947143 \tabularnewline
121 & 0.0232870247522251 & 0.0465740495044503 & 0.976712975247775 \tabularnewline
122 & 0.0288827609037482 & 0.0577655218074965 & 0.971117239096252 \tabularnewline
123 & 0.0237392429159829 & 0.0474784858319659 & 0.976260757084017 \tabularnewline
124 & 0.0200542515655416 & 0.0401085031310832 & 0.979945748434458 \tabularnewline
125 & 0.0166138209238604 & 0.0332276418477207 & 0.98338617907614 \tabularnewline
126 & 0.0133266653342354 & 0.0266533306684709 & 0.986673334665765 \tabularnewline
127 & 0.0124835918936114 & 0.0249671837872228 & 0.987516408106389 \tabularnewline
128 & 0.0107994528778388 & 0.0215989057556776 & 0.989200547122161 \tabularnewline
129 & 0.0132460082758826 & 0.0264920165517652 & 0.986753991724117 \tabularnewline
130 & 0.0166703451650448 & 0.0333406903300897 & 0.983329654834955 \tabularnewline
131 & 0.0249947968704932 & 0.0499895937409864 & 0.975005203129507 \tabularnewline
132 & 0.0375281032510634 & 0.0750562065021269 & 0.962471896748937 \tabularnewline
133 & 0.0398526373182284 & 0.0797052746364568 & 0.960147362681772 \tabularnewline
134 & 0.034908069722082 & 0.0698161394441641 & 0.965091930277918 \tabularnewline
135 & 0.0285660994191789 & 0.0571321988383577 & 0.971433900580821 \tabularnewline
136 & 0.0237453746428418 & 0.0474907492856837 & 0.976254625357158 \tabularnewline
137 & 0.0200038681208887 & 0.0400077362417774 & 0.979996131879111 \tabularnewline
138 & 0.0241396729448151 & 0.0482793458896303 & 0.975860327055185 \tabularnewline
139 & 0.0205801450456984 & 0.0411602900913968 & 0.979419854954302 \tabularnewline
140 & 0.0265135962856059 & 0.0530271925712119 & 0.973486403714394 \tabularnewline
141 & 0.0359695405551018 & 0.0719390811102036 & 0.964030459444898 \tabularnewline
142 & 0.032294168453362 & 0.0645883369067239 & 0.967705831546638 \tabularnewline
143 & 0.0267285224137314 & 0.0534570448274628 & 0.973271477586269 \tabularnewline
144 & 0.0234775668803732 & 0.0469551337607464 & 0.976522433119627 \tabularnewline
145 & 0.0351128413041757 & 0.0702256826083513 & 0.964887158695824 \tabularnewline
146 & 0.0381457465488872 & 0.0762914930977743 & 0.961854253451113 \tabularnewline
147 & 0.0453973783189103 & 0.0907947566378206 & 0.95460262168109 \tabularnewline
148 & 0.0393477893275986 & 0.0786955786551973 & 0.960652210672401 \tabularnewline
149 & 0.0321126205108259 & 0.0642252410216518 & 0.967887379489174 \tabularnewline
150 & 0.0426887770740969 & 0.0853775541481938 & 0.957311222925903 \tabularnewline
151 & 0.0502760726058603 & 0.100552145211721 & 0.94972392739414 \tabularnewline
152 & 0.0518655506799563 & 0.103731101359913 & 0.948134449320044 \tabularnewline
153 & 0.0760346520932306 & 0.152069304186461 & 0.923965347906769 \tabularnewline
154 & 0.080475530059051 & 0.160951060118102 & 0.919524469940949 \tabularnewline
155 & 0.0814825953957819 & 0.162965190791564 & 0.918517404604218 \tabularnewline
156 & 0.0689051157639046 & 0.137810231527809 & 0.931094884236095 \tabularnewline
157 & 0.060435110835844 & 0.120870221671688 & 0.939564889164156 \tabularnewline
158 & 0.0515058455842663 & 0.103011691168533 & 0.948494154415734 \tabularnewline
159 & 0.0441864062489805 & 0.0883728124979611 & 0.955813593751019 \tabularnewline
160 & 0.0366373857959031 & 0.0732747715918062 & 0.963362614204097 \tabularnewline
161 & 0.0297494802248474 & 0.0594989604496948 & 0.970250519775153 \tabularnewline
162 & 0.0240461981371726 & 0.0480923962743452 & 0.975953801862827 \tabularnewline
163 & 0.0193476025227718 & 0.0386952050455436 & 0.980652397477228 \tabularnewline
164 & 0.0161820082434436 & 0.0323640164868872 & 0.983817991756556 \tabularnewline
165 & 0.0130707973597127 & 0.0261415947194253 & 0.986929202640287 \tabularnewline
166 & 0.0130553701900596 & 0.0261107403801192 & 0.98694462980994 \tabularnewline
167 & 0.010246978944537 & 0.0204939578890739 & 0.989753021055463 \tabularnewline
168 & 0.0110148111191236 & 0.0220296222382472 & 0.988985188880876 \tabularnewline
169 & 0.0102006347356799 & 0.0204012694713599 & 0.98979936526432 \tabularnewline
170 & 0.0084874753427659 & 0.0169749506855318 & 0.991512524657234 \tabularnewline
171 & 0.0100754548803796 & 0.0201509097607592 & 0.98992454511962 \tabularnewline
172 & 0.00786146858895123 & 0.0157229371779025 & 0.992138531411049 \tabularnewline
173 & 0.00649448677693935 & 0.0129889735538787 & 0.993505513223061 \tabularnewline
174 & 0.0062439150417824 & 0.0124878300835648 & 0.993756084958218 \tabularnewline
175 & 0.00618090595575049 & 0.012361811911501 & 0.99381909404425 \tabularnewline
176 & 0.00523542140084943 & 0.0104708428016989 & 0.994764578599151 \tabularnewline
177 & 0.0040625882724304 & 0.00812517654486081 & 0.99593741172757 \tabularnewline
178 & 0.0033102813103204 & 0.00662056262064081 & 0.99668971868968 \tabularnewline
179 & 0.0025394158512275 & 0.005078831702455 & 0.997460584148772 \tabularnewline
180 & 0.00214100896045101 & 0.00428201792090202 & 0.997858991039549 \tabularnewline
181 & 0.00164917521877868 & 0.00329835043755736 & 0.998350824781221 \tabularnewline
182 & 0.00121617042110731 & 0.00243234084221462 & 0.998783829578893 \tabularnewline
183 & 0.00120568901473981 & 0.00241137802947963 & 0.99879431098526 \tabularnewline
184 & 0.000908438375735931 & 0.00181687675147186 & 0.999091561624264 \tabularnewline
185 & 0.0223564821736094 & 0.0447129643472188 & 0.977643517826391 \tabularnewline
186 & 0.0191915934265549 & 0.0383831868531099 & 0.980808406573445 \tabularnewline
187 & 0.0234753547328429 & 0.0469507094656858 & 0.976524645267157 \tabularnewline
188 & 0.0190876552168483 & 0.0381753104336965 & 0.980912344783152 \tabularnewline
189 & 0.016459752435779 & 0.0329195048715579 & 0.983540247564221 \tabularnewline
190 & 0.0128207742827646 & 0.0256415485655292 & 0.987179225717235 \tabularnewline
191 & 0.0121100814681219 & 0.0242201629362439 & 0.987889918531878 \tabularnewline
192 & 0.00939230882336032 & 0.0187846176467206 & 0.99060769117664 \tabularnewline
193 & 0.00901275553128828 & 0.0180255110625766 & 0.990987244468712 \tabularnewline
194 & 0.00804175862601702 & 0.016083517252034 & 0.991958241373983 \tabularnewline
195 & 0.00654256183595825 & 0.0130851236719165 & 0.993457438164042 \tabularnewline
196 & 0.00486791808910514 & 0.00973583617821029 & 0.995132081910895 \tabularnewline
197 & 0.00827315719269327 & 0.0165463143853865 & 0.991726842807307 \tabularnewline
198 & 0.00629874433611938 & 0.0125974886722388 & 0.993701255663881 \tabularnewline
199 & 0.00553150679118512 & 0.0110630135823702 & 0.994468493208815 \tabularnewline
200 & 0.00457784421607706 & 0.00915568843215412 & 0.995422155783923 \tabularnewline
201 & 0.00413196588969706 & 0.00826393177939413 & 0.995868034110303 \tabularnewline
202 & 0.0032049491383809 & 0.00640989827676181 & 0.996795050861619 \tabularnewline
203 & 0.00373869819170514 & 0.00747739638341028 & 0.996261301808295 \tabularnewline
204 & 0.00562630614121184 & 0.0112526122824237 & 0.994373693858788 \tabularnewline
205 & 0.00555604348301657 & 0.0111120869660331 & 0.994443956516983 \tabularnewline
206 & 0.0040429328686677 & 0.0080858657373354 & 0.995957067131332 \tabularnewline
207 & 0.00334172745065212 & 0.00668345490130424 & 0.996658272549348 \tabularnewline
208 & 0.00241568360781308 & 0.00483136721562615 & 0.997584316392187 \tabularnewline
209 & 0.00298596592716199 & 0.00597193185432398 & 0.997014034072838 \tabularnewline
210 & 0.00230985819649199 & 0.00461971639298398 & 0.997690141803508 \tabularnewline
211 & 0.00286357144241323 & 0.00572714288482647 & 0.997136428557587 \tabularnewline
212 & 0.00769719641816444 & 0.0153943928363289 & 0.992302803581836 \tabularnewline
213 & 0.0055198343700456 & 0.0110396687400912 & 0.994480165629954 \tabularnewline
214 & 0.00699468112872576 & 0.0139893622574515 & 0.993005318871274 \tabularnewline
215 & 0.00551646601893475 & 0.0110329320378695 & 0.994483533981065 \tabularnewline
216 & 0.00406498586949212 & 0.00812997173898424 & 0.995935014130508 \tabularnewline
217 & 0.00428416737999878 & 0.00856833475999757 & 0.995715832620001 \tabularnewline
218 & 0.00338062632749029 & 0.00676125265498058 & 0.99661937367251 \tabularnewline
219 & 0.00286114278938317 & 0.00572228557876633 & 0.997138857210617 \tabularnewline
220 & 0.00198603627629227 & 0.00397207255258454 & 0.998013963723708 \tabularnewline
221 & 0.00148773829442331 & 0.00297547658884663 & 0.998512261705577 \tabularnewline
222 & 0.000994023790745994 & 0.00198804758149199 & 0.999005976209254 \tabularnewline
223 & 0.00068762752033979 & 0.00137525504067958 & 0.99931237247966 \tabularnewline
224 & 0.00048167838196872 & 0.000963356763937439 & 0.999518321618031 \tabularnewline
225 & 0.000302235680795473 & 0.000604471361590945 & 0.999697764319205 \tabularnewline
226 & 0.000827624618855564 & 0.00165524923771113 & 0.999172375381144 \tabularnewline
227 & 0.00060393761180431 & 0.00120787522360862 & 0.999396062388196 \tabularnewline
228 & 0.000399444985623957 & 0.000798889971247915 & 0.999600555014376 \tabularnewline
229 & 0.00026740785399305 & 0.000534815707986101 & 0.999732592146007 \tabularnewline
230 & 0.000168169590524875 & 0.000336339181049751 & 0.999831830409475 \tabularnewline
231 & 0.000177259770253977 & 0.000354519540507954 & 0.999822740229746 \tabularnewline
232 & 0.00073477502799852 & 0.00146955005599704 & 0.999265224972001 \tabularnewline
233 & 0.00358082830930928 & 0.00716165661861855 & 0.996419171690691 \tabularnewline
234 & 0.00592406133672894 & 0.0118481226734579 & 0.994075938663271 \tabularnewline
235 & 0.00374402940767164 & 0.00748805881534327 & 0.996255970592328 \tabularnewline
236 & 0.00261534816696455 & 0.0052306963339291 & 0.997384651833035 \tabularnewline
237 & 0.037818387084205 & 0.07563677416841 & 0.962181612915795 \tabularnewline
238 & 0.0259026736009734 & 0.0518053472019469 & 0.974097326399027 \tabularnewline
239 & 0.0175292997370702 & 0.0350585994741404 & 0.98247070026293 \tabularnewline
240 & 0.0119394592826401 & 0.0238789185652801 & 0.98806054071736 \tabularnewline
241 & 0.00976945343009399 & 0.019538906860188 & 0.990230546569906 \tabularnewline
242 & 0.014045999210174 & 0.0280919984203481 & 0.985954000789826 \tabularnewline
243 & 0.00947556015193659 & 0.0189511203038732 & 0.990524439848063 \tabularnewline
244 & 0.00919401049465485 & 0.0183880209893097 & 0.990805989505345 \tabularnewline
245 & 0.0059719211681674 & 0.0119438423363348 & 0.994028078831833 \tabularnewline
246 & 0.00382792350694076 & 0.00765584701388152 & 0.996172076493059 \tabularnewline
247 & 0.00145093137205649 & 0.00290186274411298 & 0.998549068627943 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202578&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]17[/C][C]0.977955087555212[/C][C]0.0440898248895755[/C][C]0.0220449124447877[/C][/ROW]
[ROW][C]18[/C][C]0.995018686795154[/C][C]0.00996262640969223[/C][C]0.00498131320484611[/C][/ROW]
[ROW][C]19[/C][C]0.991043466316251[/C][C]0.017913067367498[/C][C]0.00895653368374899[/C][/ROW]
[ROW][C]20[/C][C]0.983004681419042[/C][C]0.0339906371619158[/C][C]0.0169953185809579[/C][/ROW]
[ROW][C]21[/C][C]0.969239251412634[/C][C]0.0615214971747324[/C][C]0.0307607485873662[/C][/ROW]
[ROW][C]22[/C][C]0.956415754307936[/C][C]0.0871684913841286[/C][C]0.0435842456920643[/C][/ROW]
[ROW][C]23[/C][C]0.941419423594714[/C][C]0.117161152810572[/C][C]0.0585805764052862[/C][/ROW]
[ROW][C]24[/C][C]0.925037568114176[/C][C]0.149924863771649[/C][C]0.0749624318858244[/C][/ROW]
[ROW][C]25[/C][C]0.89327779709033[/C][C]0.21344440581934[/C][C]0.10672220290967[/C][/ROW]
[ROW][C]26[/C][C]0.866278926204539[/C][C]0.267442147590922[/C][C]0.133721073795461[/C][/ROW]
[ROW][C]27[/C][C]0.823971416773333[/C][C]0.352057166453333[/C][C]0.176028583226667[/C][/ROW]
[ROW][C]28[/C][C]0.840523932242884[/C][C]0.318952135514231[/C][C]0.159476067757116[/C][/ROW]
[ROW][C]29[/C][C]0.794757769577171[/C][C]0.410484460845659[/C][C]0.205242230422829[/C][/ROW]
[ROW][C]30[/C][C]0.79339034255239[/C][C]0.413219314895219[/C][C]0.20660965744761[/C][/ROW]
[ROW][C]31[/C][C]0.750445074219343[/C][C]0.499109851561313[/C][C]0.249554925780656[/C][/ROW]
[ROW][C]32[/C][C]0.738323314592152[/C][C]0.523353370815696[/C][C]0.261676685407848[/C][/ROW]
[ROW][C]33[/C][C]0.715434219505237[/C][C]0.569131560989526[/C][C]0.284565780494763[/C][/ROW]
[ROW][C]34[/C][C]0.656740057917593[/C][C]0.686519884164813[/C][C]0.343259942082407[/C][/ROW]
[ROW][C]35[/C][C]0.639060210941821[/C][C]0.721879578116358[/C][C]0.360939789058179[/C][/ROW]
[ROW][C]36[/C][C]0.723591823873427[/C][C]0.552816352253147[/C][C]0.276408176126573[/C][/ROW]
[ROW][C]37[/C][C]0.783867304760463[/C][C]0.432265390479075[/C][C]0.216132695239537[/C][/ROW]
[ROW][C]38[/C][C]0.763096917718206[/C][C]0.473806164563589[/C][C]0.236903082281794[/C][/ROW]
[ROW][C]39[/C][C]0.79437831495396[/C][C]0.41124337009208[/C][C]0.20562168504604[/C][/ROW]
[ROW][C]40[/C][C]0.779966106854365[/C][C]0.44006778629127[/C][C]0.220033893145635[/C][/ROW]
[ROW][C]41[/C][C]0.749897171273924[/C][C]0.500205657452152[/C][C]0.250102828726076[/C][/ROW]
[ROW][C]42[/C][C]0.729612691249747[/C][C]0.540774617500506[/C][C]0.270387308750253[/C][/ROW]
[ROW][C]43[/C][C]0.755486261864494[/C][C]0.489027476271012[/C][C]0.244513738135506[/C][/ROW]
[ROW][C]44[/C][C]0.7150456588546[/C][C]0.569908682290799[/C][C]0.2849543411454[/C][/ROW]
[ROW][C]45[/C][C]0.67904228192718[/C][C]0.64191543614564[/C][C]0.32095771807282[/C][/ROW]
[ROW][C]46[/C][C]0.846351540153258[/C][C]0.307296919693484[/C][C]0.153648459846742[/C][/ROW]
[ROW][C]47[/C][C]0.847780097900919[/C][C]0.304439804198163[/C][C]0.152219902099081[/C][/ROW]
[ROW][C]48[/C][C]0.820731483290323[/C][C]0.358537033419355[/C][C]0.179268516709677[/C][/ROW]
[ROW][C]49[/C][C]0.796967213148615[/C][C]0.406065573702771[/C][C]0.203032786851385[/C][/ROW]
[ROW][C]50[/C][C]0.77738374396325[/C][C]0.4452325120735[/C][C]0.22261625603675[/C][/ROW]
[ROW][C]51[/C][C]0.7397057962769[/C][C]0.5205884074462[/C][C]0.2602942037231[/C][/ROW]
[ROW][C]52[/C][C]0.700541121038397[/C][C]0.598917757923205[/C][C]0.299458878961603[/C][/ROW]
[ROW][C]53[/C][C]0.716883891246429[/C][C]0.566232217507141[/C][C]0.283116108753571[/C][/ROW]
[ROW][C]54[/C][C]0.686467087992366[/C][C]0.627065824015268[/C][C]0.313532912007634[/C][/ROW]
[ROW][C]55[/C][C]0.680940742733998[/C][C]0.638118514532005[/C][C]0.319059257266002[/C][/ROW]
[ROW][C]56[/C][C]0.675313662864148[/C][C]0.649372674271704[/C][C]0.324686337135852[/C][/ROW]
[ROW][C]57[/C][C]0.633175183840637[/C][C]0.733649632318726[/C][C]0.366824816159363[/C][/ROW]
[ROW][C]58[/C][C]0.623923207562088[/C][C]0.752153584875824[/C][C]0.376076792437912[/C][/ROW]
[ROW][C]59[/C][C]0.583146788522007[/C][C]0.833706422955985[/C][C]0.416853211477993[/C][/ROW]
[ROW][C]60[/C][C]0.59719119515775[/C][C]0.805617609684499[/C][C]0.40280880484225[/C][/ROW]
[ROW][C]61[/C][C]0.562502880985813[/C][C]0.874994238028375[/C][C]0.437497119014187[/C][/ROW]
[ROW][C]62[/C][C]0.521804615161652[/C][C]0.956390769676695[/C][C]0.478195384838348[/C][/ROW]
[ROW][C]63[/C][C]0.480025261953368[/C][C]0.960050523906736[/C][C]0.519974738046632[/C][/ROW]
[ROW][C]64[/C][C]0.43540610791067[/C][C]0.870812215821339[/C][C]0.56459389208933[/C][/ROW]
[ROW][C]65[/C][C]0.401604431318089[/C][C]0.803208862636179[/C][C]0.598395568681911[/C][/ROW]
[ROW][C]66[/C][C]0.38865630865111[/C][C]0.777312617302219[/C][C]0.61134369134889[/C][/ROW]
[ROW][C]67[/C][C]0.384250906786486[/C][C]0.768501813572972[/C][C]0.615749093213514[/C][/ROW]
[ROW][C]68[/C][C]0.517720056094523[/C][C]0.964559887810954[/C][C]0.482279943905477[/C][/ROW]
[ROW][C]69[/C][C]0.63061702649402[/C][C]0.738765947011959[/C][C]0.36938297350598[/C][/ROW]
[ROW][C]70[/C][C]0.595416007907377[/C][C]0.809167984185246[/C][C]0.404583992092623[/C][/ROW]
[ROW][C]71[/C][C]0.672371158460862[/C][C]0.655257683078275[/C][C]0.327628841539137[/C][/ROW]
[ROW][C]72[/C][C]0.634854377732834[/C][C]0.730291244534332[/C][C]0.365145622267166[/C][/ROW]
[ROW][C]73[/C][C]0.624670895867978[/C][C]0.750658208264045[/C][C]0.375329104132022[/C][/ROW]
[ROW][C]74[/C][C]0.606648383557719[/C][C]0.786703232884562[/C][C]0.393351616442281[/C][/ROW]
[ROW][C]75[/C][C]0.566499947146784[/C][C]0.867000105706432[/C][C]0.433500052853216[/C][/ROW]
[ROW][C]76[/C][C]0.607592034967605[/C][C]0.784815930064789[/C][C]0.392407965032395[/C][/ROW]
[ROW][C]77[/C][C]0.568317893268798[/C][C]0.863364213462405[/C][C]0.431682106731202[/C][/ROW]
[ROW][C]78[/C][C]0.541558134188577[/C][C]0.916883731622846[/C][C]0.458441865811423[/C][/ROW]
[ROW][C]79[/C][C]0.549296507902011[/C][C]0.901406984195979[/C][C]0.450703492097989[/C][/ROW]
[ROW][C]80[/C][C]0.510567657429531[/C][C]0.978864685140938[/C][C]0.489432342570469[/C][/ROW]
[ROW][C]81[/C][C]0.474951684987043[/C][C]0.949903369974086[/C][C]0.525048315012957[/C][/ROW]
[ROW][C]82[/C][C]0.438389405829715[/C][C]0.876778811659431[/C][C]0.561610594170285[/C][/ROW]
[ROW][C]83[/C][C]0.407430458324123[/C][C]0.814860916648246[/C][C]0.592569541675877[/C][/ROW]
[ROW][C]84[/C][C]0.370254702832498[/C][C]0.740509405664996[/C][C]0.629745297167502[/C][/ROW]
[ROW][C]85[/C][C]0.360518147094309[/C][C]0.721036294188618[/C][C]0.639481852905691[/C][/ROW]
[ROW][C]86[/C][C]0.324033384284653[/C][C]0.648066768569306[/C][C]0.675966615715347[/C][/ROW]
[ROW][C]87[/C][C]0.293887378851484[/C][C]0.587774757702968[/C][C]0.706112621148516[/C][/ROW]
[ROW][C]88[/C][C]0.277730240627193[/C][C]0.555460481254386[/C][C]0.722269759372807[/C][/ROW]
[ROW][C]89[/C][C]0.246430051612688[/C][C]0.492860103225376[/C][C]0.753569948387312[/C][/ROW]
[ROW][C]90[/C][C]0.238740319112994[/C][C]0.477480638225987[/C][C]0.761259680887006[/C][/ROW]
[ROW][C]91[/C][C]0.210816058874235[/C][C]0.42163211774847[/C][C]0.789183941125765[/C][/ROW]
[ROW][C]92[/C][C]0.186765732028805[/C][C]0.373531464057609[/C][C]0.813234267971195[/C][/ROW]
[ROW][C]93[/C][C]0.164024780701546[/C][C]0.328049561403092[/C][C]0.835975219298454[/C][/ROW]
[ROW][C]94[/C][C]0.170322263651312[/C][C]0.340644527302625[/C][C]0.829677736348688[/C][/ROW]
[ROW][C]95[/C][C]0.153305219397003[/C][C]0.306610438794007[/C][C]0.846694780602997[/C][/ROW]
[ROW][C]96[/C][C]0.131547035812515[/C][C]0.26309407162503[/C][C]0.868452964187485[/C][/ROW]
[ROW][C]97[/C][C]0.134152959198113[/C][C]0.268305918396227[/C][C]0.865847040801887[/C][/ROW]
[ROW][C]98[/C][C]0.114190299606183[/C][C]0.228380599212365[/C][C]0.885809700393817[/C][/ROW]
[ROW][C]99[/C][C]0.0969282590804472[/C][C]0.193856518160894[/C][C]0.903071740919553[/C][/ROW]
[ROW][C]100[/C][C]0.086688083082024[/C][C]0.173376166164048[/C][C]0.913311916917976[/C][/ROW]
[ROW][C]101[/C][C]0.0769268646977879[/C][C]0.153853729395576[/C][C]0.923073135302212[/C][/ROW]
[ROW][C]102[/C][C]0.0892578246194909[/C][C]0.178515649238982[/C][C]0.910742175380509[/C][/ROW]
[ROW][C]103[/C][C]0.0767647712400794[/C][C]0.153529542480159[/C][C]0.923235228759921[/C][/ROW]
[ROW][C]104[/C][C]0.0693115660415813[/C][C]0.138623132083163[/C][C]0.930688433958419[/C][/ROW]
[ROW][C]105[/C][C]0.0813770685522494[/C][C]0.162754137104499[/C][C]0.918622931447751[/C][/ROW]
[ROW][C]106[/C][C]0.0727359957473762[/C][C]0.145471991494752[/C][C]0.927264004252624[/C][/ROW]
[ROW][C]107[/C][C]0.0609281945985376[/C][C]0.121856389197075[/C][C]0.939071805401462[/C][/ROW]
[ROW][C]108[/C][C]0.0615427561539167[/C][C]0.123085512307833[/C][C]0.938457243846083[/C][/ROW]
[ROW][C]109[/C][C]0.0519477422715837[/C][C]0.103895484543167[/C][C]0.948052257728416[/C][/ROW]
[ROW][C]110[/C][C]0.0441347828415425[/C][C]0.0882695656830849[/C][C]0.955865217158458[/C][/ROW]
[ROW][C]111[/C][C]0.0369647949548216[/C][C]0.0739295899096432[/C][C]0.963035205045178[/C][/ROW]
[ROW][C]112[/C][C]0.0454516805763338[/C][C]0.0909033611526676[/C][C]0.954548319423666[/C][/ROW]
[ROW][C]113[/C][C]0.0388671559514368[/C][C]0.0777343119028737[/C][C]0.961132844048563[/C][/ROW]
[ROW][C]114[/C][C]0.0509529948528077[/C][C]0.101905989705615[/C][C]0.949047005147192[/C][/ROW]
[ROW][C]115[/C][C]0.0498435718105525[/C][C]0.099687143621105[/C][C]0.950156428189448[/C][/ROW]
[ROW][C]116[/C][C]0.0442789109568897[/C][C]0.0885578219137794[/C][C]0.95572108904311[/C][/ROW]
[ROW][C]117[/C][C]0.0403689939347767[/C][C]0.0807379878695535[/C][C]0.959631006065223[/C][/ROW]
[ROW][C]118[/C][C]0.0369512286974033[/C][C]0.0739024573948067[/C][C]0.963048771302597[/C][/ROW]
[ROW][C]119[/C][C]0.0325674222633728[/C][C]0.0651348445267457[/C][C]0.967432577736627[/C][/ROW]
[ROW][C]120[/C][C]0.0275450005285695[/C][C]0.0550900010571391[/C][C]0.97245499947143[/C][/ROW]
[ROW][C]121[/C][C]0.0232870247522251[/C][C]0.0465740495044503[/C][C]0.976712975247775[/C][/ROW]
[ROW][C]122[/C][C]0.0288827609037482[/C][C]0.0577655218074965[/C][C]0.971117239096252[/C][/ROW]
[ROW][C]123[/C][C]0.0237392429159829[/C][C]0.0474784858319659[/C][C]0.976260757084017[/C][/ROW]
[ROW][C]124[/C][C]0.0200542515655416[/C][C]0.0401085031310832[/C][C]0.979945748434458[/C][/ROW]
[ROW][C]125[/C][C]0.0166138209238604[/C][C]0.0332276418477207[/C][C]0.98338617907614[/C][/ROW]
[ROW][C]126[/C][C]0.0133266653342354[/C][C]0.0266533306684709[/C][C]0.986673334665765[/C][/ROW]
[ROW][C]127[/C][C]0.0124835918936114[/C][C]0.0249671837872228[/C][C]0.987516408106389[/C][/ROW]
[ROW][C]128[/C][C]0.0107994528778388[/C][C]0.0215989057556776[/C][C]0.989200547122161[/C][/ROW]
[ROW][C]129[/C][C]0.0132460082758826[/C][C]0.0264920165517652[/C][C]0.986753991724117[/C][/ROW]
[ROW][C]130[/C][C]0.0166703451650448[/C][C]0.0333406903300897[/C][C]0.983329654834955[/C][/ROW]
[ROW][C]131[/C][C]0.0249947968704932[/C][C]0.0499895937409864[/C][C]0.975005203129507[/C][/ROW]
[ROW][C]132[/C][C]0.0375281032510634[/C][C]0.0750562065021269[/C][C]0.962471896748937[/C][/ROW]
[ROW][C]133[/C][C]0.0398526373182284[/C][C]0.0797052746364568[/C][C]0.960147362681772[/C][/ROW]
[ROW][C]134[/C][C]0.034908069722082[/C][C]0.0698161394441641[/C][C]0.965091930277918[/C][/ROW]
[ROW][C]135[/C][C]0.0285660994191789[/C][C]0.0571321988383577[/C][C]0.971433900580821[/C][/ROW]
[ROW][C]136[/C][C]0.0237453746428418[/C][C]0.0474907492856837[/C][C]0.976254625357158[/C][/ROW]
[ROW][C]137[/C][C]0.0200038681208887[/C][C]0.0400077362417774[/C][C]0.979996131879111[/C][/ROW]
[ROW][C]138[/C][C]0.0241396729448151[/C][C]0.0482793458896303[/C][C]0.975860327055185[/C][/ROW]
[ROW][C]139[/C][C]0.0205801450456984[/C][C]0.0411602900913968[/C][C]0.979419854954302[/C][/ROW]
[ROW][C]140[/C][C]0.0265135962856059[/C][C]0.0530271925712119[/C][C]0.973486403714394[/C][/ROW]
[ROW][C]141[/C][C]0.0359695405551018[/C][C]0.0719390811102036[/C][C]0.964030459444898[/C][/ROW]
[ROW][C]142[/C][C]0.032294168453362[/C][C]0.0645883369067239[/C][C]0.967705831546638[/C][/ROW]
[ROW][C]143[/C][C]0.0267285224137314[/C][C]0.0534570448274628[/C][C]0.973271477586269[/C][/ROW]
[ROW][C]144[/C][C]0.0234775668803732[/C][C]0.0469551337607464[/C][C]0.976522433119627[/C][/ROW]
[ROW][C]145[/C][C]0.0351128413041757[/C][C]0.0702256826083513[/C][C]0.964887158695824[/C][/ROW]
[ROW][C]146[/C][C]0.0381457465488872[/C][C]0.0762914930977743[/C][C]0.961854253451113[/C][/ROW]
[ROW][C]147[/C][C]0.0453973783189103[/C][C]0.0907947566378206[/C][C]0.95460262168109[/C][/ROW]
[ROW][C]148[/C][C]0.0393477893275986[/C][C]0.0786955786551973[/C][C]0.960652210672401[/C][/ROW]
[ROW][C]149[/C][C]0.0321126205108259[/C][C]0.0642252410216518[/C][C]0.967887379489174[/C][/ROW]
[ROW][C]150[/C][C]0.0426887770740969[/C][C]0.0853775541481938[/C][C]0.957311222925903[/C][/ROW]
[ROW][C]151[/C][C]0.0502760726058603[/C][C]0.100552145211721[/C][C]0.94972392739414[/C][/ROW]
[ROW][C]152[/C][C]0.0518655506799563[/C][C]0.103731101359913[/C][C]0.948134449320044[/C][/ROW]
[ROW][C]153[/C][C]0.0760346520932306[/C][C]0.152069304186461[/C][C]0.923965347906769[/C][/ROW]
[ROW][C]154[/C][C]0.080475530059051[/C][C]0.160951060118102[/C][C]0.919524469940949[/C][/ROW]
[ROW][C]155[/C][C]0.0814825953957819[/C][C]0.162965190791564[/C][C]0.918517404604218[/C][/ROW]
[ROW][C]156[/C][C]0.0689051157639046[/C][C]0.137810231527809[/C][C]0.931094884236095[/C][/ROW]
[ROW][C]157[/C][C]0.060435110835844[/C][C]0.120870221671688[/C][C]0.939564889164156[/C][/ROW]
[ROW][C]158[/C][C]0.0515058455842663[/C][C]0.103011691168533[/C][C]0.948494154415734[/C][/ROW]
[ROW][C]159[/C][C]0.0441864062489805[/C][C]0.0883728124979611[/C][C]0.955813593751019[/C][/ROW]
[ROW][C]160[/C][C]0.0366373857959031[/C][C]0.0732747715918062[/C][C]0.963362614204097[/C][/ROW]
[ROW][C]161[/C][C]0.0297494802248474[/C][C]0.0594989604496948[/C][C]0.970250519775153[/C][/ROW]
[ROW][C]162[/C][C]0.0240461981371726[/C][C]0.0480923962743452[/C][C]0.975953801862827[/C][/ROW]
[ROW][C]163[/C][C]0.0193476025227718[/C][C]0.0386952050455436[/C][C]0.980652397477228[/C][/ROW]
[ROW][C]164[/C][C]0.0161820082434436[/C][C]0.0323640164868872[/C][C]0.983817991756556[/C][/ROW]
[ROW][C]165[/C][C]0.0130707973597127[/C][C]0.0261415947194253[/C][C]0.986929202640287[/C][/ROW]
[ROW][C]166[/C][C]0.0130553701900596[/C][C]0.0261107403801192[/C][C]0.98694462980994[/C][/ROW]
[ROW][C]167[/C][C]0.010246978944537[/C][C]0.0204939578890739[/C][C]0.989753021055463[/C][/ROW]
[ROW][C]168[/C][C]0.0110148111191236[/C][C]0.0220296222382472[/C][C]0.988985188880876[/C][/ROW]
[ROW][C]169[/C][C]0.0102006347356799[/C][C]0.0204012694713599[/C][C]0.98979936526432[/C][/ROW]
[ROW][C]170[/C][C]0.0084874753427659[/C][C]0.0169749506855318[/C][C]0.991512524657234[/C][/ROW]
[ROW][C]171[/C][C]0.0100754548803796[/C][C]0.0201509097607592[/C][C]0.98992454511962[/C][/ROW]
[ROW][C]172[/C][C]0.00786146858895123[/C][C]0.0157229371779025[/C][C]0.992138531411049[/C][/ROW]
[ROW][C]173[/C][C]0.00649448677693935[/C][C]0.0129889735538787[/C][C]0.993505513223061[/C][/ROW]
[ROW][C]174[/C][C]0.0062439150417824[/C][C]0.0124878300835648[/C][C]0.993756084958218[/C][/ROW]
[ROW][C]175[/C][C]0.00618090595575049[/C][C]0.012361811911501[/C][C]0.99381909404425[/C][/ROW]
[ROW][C]176[/C][C]0.00523542140084943[/C][C]0.0104708428016989[/C][C]0.994764578599151[/C][/ROW]
[ROW][C]177[/C][C]0.0040625882724304[/C][C]0.00812517654486081[/C][C]0.99593741172757[/C][/ROW]
[ROW][C]178[/C][C]0.0033102813103204[/C][C]0.00662056262064081[/C][C]0.99668971868968[/C][/ROW]
[ROW][C]179[/C][C]0.0025394158512275[/C][C]0.005078831702455[/C][C]0.997460584148772[/C][/ROW]
[ROW][C]180[/C][C]0.00214100896045101[/C][C]0.00428201792090202[/C][C]0.997858991039549[/C][/ROW]
[ROW][C]181[/C][C]0.00164917521877868[/C][C]0.00329835043755736[/C][C]0.998350824781221[/C][/ROW]
[ROW][C]182[/C][C]0.00121617042110731[/C][C]0.00243234084221462[/C][C]0.998783829578893[/C][/ROW]
[ROW][C]183[/C][C]0.00120568901473981[/C][C]0.00241137802947963[/C][C]0.99879431098526[/C][/ROW]
[ROW][C]184[/C][C]0.000908438375735931[/C][C]0.00181687675147186[/C][C]0.999091561624264[/C][/ROW]
[ROW][C]185[/C][C]0.0223564821736094[/C][C]0.0447129643472188[/C][C]0.977643517826391[/C][/ROW]
[ROW][C]186[/C][C]0.0191915934265549[/C][C]0.0383831868531099[/C][C]0.980808406573445[/C][/ROW]
[ROW][C]187[/C][C]0.0234753547328429[/C][C]0.0469507094656858[/C][C]0.976524645267157[/C][/ROW]
[ROW][C]188[/C][C]0.0190876552168483[/C][C]0.0381753104336965[/C][C]0.980912344783152[/C][/ROW]
[ROW][C]189[/C][C]0.016459752435779[/C][C]0.0329195048715579[/C][C]0.983540247564221[/C][/ROW]
[ROW][C]190[/C][C]0.0128207742827646[/C][C]0.0256415485655292[/C][C]0.987179225717235[/C][/ROW]
[ROW][C]191[/C][C]0.0121100814681219[/C][C]0.0242201629362439[/C][C]0.987889918531878[/C][/ROW]
[ROW][C]192[/C][C]0.00939230882336032[/C][C]0.0187846176467206[/C][C]0.99060769117664[/C][/ROW]
[ROW][C]193[/C][C]0.00901275553128828[/C][C]0.0180255110625766[/C][C]0.990987244468712[/C][/ROW]
[ROW][C]194[/C][C]0.00804175862601702[/C][C]0.016083517252034[/C][C]0.991958241373983[/C][/ROW]
[ROW][C]195[/C][C]0.00654256183595825[/C][C]0.0130851236719165[/C][C]0.993457438164042[/C][/ROW]
[ROW][C]196[/C][C]0.00486791808910514[/C][C]0.00973583617821029[/C][C]0.995132081910895[/C][/ROW]
[ROW][C]197[/C][C]0.00827315719269327[/C][C]0.0165463143853865[/C][C]0.991726842807307[/C][/ROW]
[ROW][C]198[/C][C]0.00629874433611938[/C][C]0.0125974886722388[/C][C]0.993701255663881[/C][/ROW]
[ROW][C]199[/C][C]0.00553150679118512[/C][C]0.0110630135823702[/C][C]0.994468493208815[/C][/ROW]
[ROW][C]200[/C][C]0.00457784421607706[/C][C]0.00915568843215412[/C][C]0.995422155783923[/C][/ROW]
[ROW][C]201[/C][C]0.00413196588969706[/C][C]0.00826393177939413[/C][C]0.995868034110303[/C][/ROW]
[ROW][C]202[/C][C]0.0032049491383809[/C][C]0.00640989827676181[/C][C]0.996795050861619[/C][/ROW]
[ROW][C]203[/C][C]0.00373869819170514[/C][C]0.00747739638341028[/C][C]0.996261301808295[/C][/ROW]
[ROW][C]204[/C][C]0.00562630614121184[/C][C]0.0112526122824237[/C][C]0.994373693858788[/C][/ROW]
[ROW][C]205[/C][C]0.00555604348301657[/C][C]0.0111120869660331[/C][C]0.994443956516983[/C][/ROW]
[ROW][C]206[/C][C]0.0040429328686677[/C][C]0.0080858657373354[/C][C]0.995957067131332[/C][/ROW]
[ROW][C]207[/C][C]0.00334172745065212[/C][C]0.00668345490130424[/C][C]0.996658272549348[/C][/ROW]
[ROW][C]208[/C][C]0.00241568360781308[/C][C]0.00483136721562615[/C][C]0.997584316392187[/C][/ROW]
[ROW][C]209[/C][C]0.00298596592716199[/C][C]0.00597193185432398[/C][C]0.997014034072838[/C][/ROW]
[ROW][C]210[/C][C]0.00230985819649199[/C][C]0.00461971639298398[/C][C]0.997690141803508[/C][/ROW]
[ROW][C]211[/C][C]0.00286357144241323[/C][C]0.00572714288482647[/C][C]0.997136428557587[/C][/ROW]
[ROW][C]212[/C][C]0.00769719641816444[/C][C]0.0153943928363289[/C][C]0.992302803581836[/C][/ROW]
[ROW][C]213[/C][C]0.0055198343700456[/C][C]0.0110396687400912[/C][C]0.994480165629954[/C][/ROW]
[ROW][C]214[/C][C]0.00699468112872576[/C][C]0.0139893622574515[/C][C]0.993005318871274[/C][/ROW]
[ROW][C]215[/C][C]0.00551646601893475[/C][C]0.0110329320378695[/C][C]0.994483533981065[/C][/ROW]
[ROW][C]216[/C][C]0.00406498586949212[/C][C]0.00812997173898424[/C][C]0.995935014130508[/C][/ROW]
[ROW][C]217[/C][C]0.00428416737999878[/C][C]0.00856833475999757[/C][C]0.995715832620001[/C][/ROW]
[ROW][C]218[/C][C]0.00338062632749029[/C][C]0.00676125265498058[/C][C]0.99661937367251[/C][/ROW]
[ROW][C]219[/C][C]0.00286114278938317[/C][C]0.00572228557876633[/C][C]0.997138857210617[/C][/ROW]
[ROW][C]220[/C][C]0.00198603627629227[/C][C]0.00397207255258454[/C][C]0.998013963723708[/C][/ROW]
[ROW][C]221[/C][C]0.00148773829442331[/C][C]0.00297547658884663[/C][C]0.998512261705577[/C][/ROW]
[ROW][C]222[/C][C]0.000994023790745994[/C][C]0.00198804758149199[/C][C]0.999005976209254[/C][/ROW]
[ROW][C]223[/C][C]0.00068762752033979[/C][C]0.00137525504067958[/C][C]0.99931237247966[/C][/ROW]
[ROW][C]224[/C][C]0.00048167838196872[/C][C]0.000963356763937439[/C][C]0.999518321618031[/C][/ROW]
[ROW][C]225[/C][C]0.000302235680795473[/C][C]0.000604471361590945[/C][C]0.999697764319205[/C][/ROW]
[ROW][C]226[/C][C]0.000827624618855564[/C][C]0.00165524923771113[/C][C]0.999172375381144[/C][/ROW]
[ROW][C]227[/C][C]0.00060393761180431[/C][C]0.00120787522360862[/C][C]0.999396062388196[/C][/ROW]
[ROW][C]228[/C][C]0.000399444985623957[/C][C]0.000798889971247915[/C][C]0.999600555014376[/C][/ROW]
[ROW][C]229[/C][C]0.00026740785399305[/C][C]0.000534815707986101[/C][C]0.999732592146007[/C][/ROW]
[ROW][C]230[/C][C]0.000168169590524875[/C][C]0.000336339181049751[/C][C]0.999831830409475[/C][/ROW]
[ROW][C]231[/C][C]0.000177259770253977[/C][C]0.000354519540507954[/C][C]0.999822740229746[/C][/ROW]
[ROW][C]232[/C][C]0.00073477502799852[/C][C]0.00146955005599704[/C][C]0.999265224972001[/C][/ROW]
[ROW][C]233[/C][C]0.00358082830930928[/C][C]0.00716165661861855[/C][C]0.996419171690691[/C][/ROW]
[ROW][C]234[/C][C]0.00592406133672894[/C][C]0.0118481226734579[/C][C]0.994075938663271[/C][/ROW]
[ROW][C]235[/C][C]0.00374402940767164[/C][C]0.00748805881534327[/C][C]0.996255970592328[/C][/ROW]
[ROW][C]236[/C][C]0.00261534816696455[/C][C]0.0052306963339291[/C][C]0.997384651833035[/C][/ROW]
[ROW][C]237[/C][C]0.037818387084205[/C][C]0.07563677416841[/C][C]0.962181612915795[/C][/ROW]
[ROW][C]238[/C][C]0.0259026736009734[/C][C]0.0518053472019469[/C][C]0.974097326399027[/C][/ROW]
[ROW][C]239[/C][C]0.0175292997370702[/C][C]0.0350585994741404[/C][C]0.98247070026293[/C][/ROW]
[ROW][C]240[/C][C]0.0119394592826401[/C][C]0.0238789185652801[/C][C]0.98806054071736[/C][/ROW]
[ROW][C]241[/C][C]0.00976945343009399[/C][C]0.019538906860188[/C][C]0.990230546569906[/C][/ROW]
[ROW][C]242[/C][C]0.014045999210174[/C][C]0.0280919984203481[/C][C]0.985954000789826[/C][/ROW]
[ROW][C]243[/C][C]0.00947556015193659[/C][C]0.0189511203038732[/C][C]0.990524439848063[/C][/ROW]
[ROW][C]244[/C][C]0.00919401049465485[/C][C]0.0183880209893097[/C][C]0.990805989505345[/C][/ROW]
[ROW][C]245[/C][C]0.0059719211681674[/C][C]0.0119438423363348[/C][C]0.994028078831833[/C][/ROW]
[ROW][C]246[/C][C]0.00382792350694076[/C][C]0.00765584701388152[/C][C]0.996172076493059[/C][/ROW]
[ROW][C]247[/C][C]0.00145093137205649[/C][C]0.00290186274411298[/C][C]0.998549068627943[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202578&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202578&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
170.9779550875552120.04408982488957550.0220449124447877
180.9950186867951540.009962626409692230.00498131320484611
190.9910434663162510.0179130673674980.00895653368374899
200.9830046814190420.03399063716191580.0169953185809579
210.9692392514126340.06152149717473240.0307607485873662
220.9564157543079360.08716849138412860.0435842456920643
230.9414194235947140.1171611528105720.0585805764052862
240.9250375681141760.1499248637716490.0749624318858244
250.893277797090330.213444405819340.10672220290967
260.8662789262045390.2674421475909220.133721073795461
270.8239714167733330.3520571664533330.176028583226667
280.8405239322428840.3189521355142310.159476067757116
290.7947577695771710.4104844608456590.205242230422829
300.793390342552390.4132193148952190.20660965744761
310.7504450742193430.4991098515613130.249554925780656
320.7383233145921520.5233533708156960.261676685407848
330.7154342195052370.5691315609895260.284565780494763
340.6567400579175930.6865198841648130.343259942082407
350.6390602109418210.7218795781163580.360939789058179
360.7235918238734270.5528163522531470.276408176126573
370.7838673047604630.4322653904790750.216132695239537
380.7630969177182060.4738061645635890.236903082281794
390.794378314953960.411243370092080.20562168504604
400.7799661068543650.440067786291270.220033893145635
410.7498971712739240.5002056574521520.250102828726076
420.7296126912497470.5407746175005060.270387308750253
430.7554862618644940.4890274762710120.244513738135506
440.71504565885460.5699086822907990.2849543411454
450.679042281927180.641915436145640.32095771807282
460.8463515401532580.3072969196934840.153648459846742
470.8477800979009190.3044398041981630.152219902099081
480.8207314832903230.3585370334193550.179268516709677
490.7969672131486150.4060655737027710.203032786851385
500.777383743963250.44523251207350.22261625603675
510.73970579627690.52058840744620.2602942037231
520.7005411210383970.5989177579232050.299458878961603
530.7168838912464290.5662322175071410.283116108753571
540.6864670879923660.6270658240152680.313532912007634
550.6809407427339980.6381185145320050.319059257266002
560.6753136628641480.6493726742717040.324686337135852
570.6331751838406370.7336496323187260.366824816159363
580.6239232075620880.7521535848758240.376076792437912
590.5831467885220070.8337064229559850.416853211477993
600.597191195157750.8056176096844990.40280880484225
610.5625028809858130.8749942380283750.437497119014187
620.5218046151616520.9563907696766950.478195384838348
630.4800252619533680.9600505239067360.519974738046632
640.435406107910670.8708122158213390.56459389208933
650.4016044313180890.8032088626361790.598395568681911
660.388656308651110.7773126173022190.61134369134889
670.3842509067864860.7685018135729720.615749093213514
680.5177200560945230.9645598878109540.482279943905477
690.630617026494020.7387659470119590.36938297350598
700.5954160079073770.8091679841852460.404583992092623
710.6723711584608620.6552576830782750.327628841539137
720.6348543777328340.7302912445343320.365145622267166
730.6246708958679780.7506582082640450.375329104132022
740.6066483835577190.7867032328845620.393351616442281
750.5664999471467840.8670001057064320.433500052853216
760.6075920349676050.7848159300647890.392407965032395
770.5683178932687980.8633642134624050.431682106731202
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1900.01282077428276460.02564154856552920.987179225717235
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1920.009392308823360320.01878461764672060.99060769117664
1930.009012755531288280.01802551106257660.990987244468712
1940.008041758626017020.0160835172520340.991958241373983
1950.006542561835958250.01308512367191650.993457438164042
1960.004867918089105140.009735836178210290.995132081910895
1970.008273157192693270.01654631438538650.991726842807307
1980.006298744336119380.01259748867223880.993701255663881
1990.005531506791185120.01106301358237020.994468493208815
2000.004577844216077060.009155688432154120.995422155783923
2010.004131965889697060.008263931779394130.995868034110303
2020.00320494913838090.006409898276761810.996795050861619
2030.003738698191705140.007477396383410280.996261301808295
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2050.005556043483016570.01111208696603310.994443956516983
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2090.002985965927161990.005971931854323980.997014034072838
2100.002309858196491990.004619716392983980.997690141803508
2110.002863571442413230.005727142884826470.997136428557587
2120.007697196418164440.01539439283632890.992302803581836
2130.00551983437004560.01103966874009120.994480165629954
2140.006994681128725760.01398936225745150.993005318871274
2150.005516466018934750.01103293203786950.994483533981065
2160.004064985869492120.008129971738984240.995935014130508
2170.004284167379998780.008568334759997570.995715832620001
2180.003380626327490290.006761252654980580.99661937367251
2190.002861142789383170.005722285578766330.997138857210617
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2420.0140459992101740.02809199842034810.985954000789826
2430.009475560151936590.01895112030387320.990524439848063
2440.009194010494654850.01838802098930970.990805989505345
2450.00597192116816740.01194384233633480.994028078831833
2460.003827923506940760.007655847013881520.996172076493059
2470.001450931372056490.002901862744112980.998549068627943







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level420.181818181818182NOK
5% type I error level1030.445887445887446NOK
10% type I error level1350.584415584415584NOK

\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 & 42 & 0.181818181818182 & NOK \tabularnewline
5% type I error level & 103 & 0.445887445887446 & NOK \tabularnewline
10% type I error level & 135 & 0.584415584415584 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202578&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]42[/C][C]0.181818181818182[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]103[/C][C]0.445887445887446[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]135[/C][C]0.584415584415584[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202578&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202578&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 level420.181818181818182NOK
5% type I error level1030.445887445887446NOK
10% type I error level1350.584415584415584NOK



Parameters (Session):
par1 = 8 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 8 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')
}