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R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Thu, 06 Nov 2014 19:48:53 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/06/t1415303379vnpzn6ivglz33ra.htm/, Retrieved Mon, 20 May 2024 05:25:49 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=252898, Retrieved Mon, 20 May 2024 05:25:49 +0000

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Estimated Impact

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

-       [Multiple Regression] [] [2014-11-06 19:48:53] [63a9f0ea7bb98050796b649e85481845] [Current]

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1	0	149	96	18	68	86	7.5	1.8	2.1	1.5
1	0	152	75	7	55	62	2.5	1.6	1.5	1.8
1	1	139	70	31	39	70	6.0	2.1	2.0	2.1
1	0	148	88	39	32	71	6.5	2.2	2.0	2.1
1	1	158	114	46	62	108	1.0	2.3	2.1	1.9
1	1	128	69	31	33	64	1.0	2.1	2.0	1.6
1	1	224	176	67	52	119	5.5	2.7	2.3	2.1
1	0	159	114	35	62	97	8.5	2.1	2.1	2.1
1	1	105	121	52	77	129	6.5	2.4	2.1	2.2
1	1	159	110	77	76	153	4.5	2.9	2.2	1.5
1	1	167	158	37	41	78	2.0	2.2	2.1	1.9
1	1	165	116	32	48	80	5.0	2.1	2.1	2.2
1	1	159	181	36	63	99	0.5	2.2	2.1	1.6
1	1	119	77	38	30	68	5.0	2.2	2.0	1.5
1	0	176	141	69	78	147	5.0	2.7	2.3	1.9
1	0	54	35	21	19	40	2.5	1.9	1.8	0.1
0	0	91	80	26	31	57	5.0	2.0	2.0	2.2
1	1	163	152	54	66	120	5.5	2.5	2.2	1.8
1	0	124	97	36	35	71	3.5	2.2	2.0	1.6
0	1	137	99	42	42	84	3.0	2.3	2.1	2.2
1	0	121	84	23	45	68	4.0	1.9	2.0	2.1
1	1	153	68	34	21	55	0.5	2.1	1.8	1.9
1	1	148	101	112	25	137	6.5	3.5	2.2	1.6
1	0	221	107	35	44	79	4.5	2.1	2.2	1.9
1	1	188	88	47	69	116	7.5	2.3	1.7	2.2
1	1	149	112	47	54	101	5.5	2.3	2.1	1.8
1	1	244	171	37	74	111	4.0	2.2	2.3	2.4
0	1	148	137	109	80	189	7.5	3.5	2.7	2.4
0	0	92	77	24	42	66	7.0	1.9	1.9	2.5
1	1	150	66	20	61	81	4.0	1.9	2.0	1.9
1	0	153	93	22	41	63	5.5	1.9	2.0	2.1
1	0	94	105	23	46	69	2.5	1.9	1.9	1.9
1	0	156	131	32	39	71	5.5	2.1	2.0	2.1
1	1	146	89	7	63	70	0.5	1.6	2.0	1.9
1	1	132	102	30	34	64	3.5	2.0	2.0	1.5
1	1	161	161	92	51	143	2.5	3.2	2.1	1.9
1	1	105	120	43	42	85	4.5	2.3	2.0	2.1
1	1	97	127	55	31	86	4.5	2.5	1.8	1.5
1	0	151	77	16	39	55	4.5	1.8	2.0	2.1
0	1	131	108	49	20	69	6.0	2.4	2.2	2.1
1	1	166	85	71	49	120	2.5	2.8	2.2	1.8
1	0	157	168	43	53	96	5.0	2.3	2.1	2.4
1	1	111	48	29	31	60	0.0	2.0	1.8	2.1
1	1	145	152	56	39	95	5.0	2.5	1.9	1.9
1	1	162	75	46	54	100	6.5	2.3	2.1	2.1
1	1	163	107	19	49	68	5.0	1.8	2.0	1.9
0	1	59	62	23	34	57	6.0	1.9	1.9	2.4
1	0	187	121	59	46	105	4.5	2.6	2.2	2.1
1	1	109	124	30	55	85	5.5	2.0	2.0	2.2
0	1	90	72	61	42	103	1.0	2.6	2.0	2.2
1	0	105	40	7	50	57	7.5	1.6	1.7	1.8
0	1	83	58	38	13	51	6.0	2.2	2.0	2.1
0	1	116	97	32	37	69	5.0	2.1	2.2	2.4
0	1	42	88	16	25	41	1.0	1.8	1.7	2.2
1	1	148	126	19	30	49	5.0	1.8	2.0	2.1
0	1	155	104	22	28	50	6.5	1.9	2.2	1.5
1	1	125	148	48	45	93	7.0	2.4	2.0	1.9
1	1	116	146	23	35	58	4.5	1.9	1.9	1.8
0	0	128	80	26	28	54	0.0	2.0	2.0	1.8
1	1	138	97	33	41	74	8.5	2.1	2.0	1.6
0	0	49	25	9	6	15	3.5	1.7	1.6	1.2
0	1	96	99	24	45	69	7.5	1.9	2.1	1.8
1	1	164	118	34	73	107	3.5	2.1	2.1	1.5
1	0	162	58	48	17	65	6.0	2.4	2.0	2.1
1	0	99	63	18	40	58	1.5	1.8	1.9	2.4
1	1	202	139	43	64	107	9.0	2.3	2.2	2.4
1	0	186	50	33	37	70	3.5	2.1	2.1	1.5
0	1	66	60	28	25	53	3.5	2.0	1.8	1.8
1	0	183	152	71	65	136	4.0	2.8	2.3	2.1
1	1	214	142	26	100	126	6.5	2.0	2.3	2.2
1	1	188	94	67	28	95	7.5	2.7	2.2	2.1
0	0	104	66	34	35	69	6.0	2.1	2.1	1.9
1	0	177	127	80	56	136	5.0	2.9	2.2	2.1
1	0	126	67	29	29	58	5.5	2.0	1.9	1.9
0	0	76	90	16	43	59	3.5	1.8	1.8	1.6
0	1	99	75	59	59	118	7.5	2.6	2.1	2.4
1	1	157	96	58	52	110	1.0	2.5	1.8	1.9
1	0	139	128	32	50	82	6.5	2.1	2.0	1.9
1	1	78	41	47	3	50	NA	2.3	1.7	1.9
1	0	162	146	43	59	102	6.5	2.3	2.1	2.1
0	1	108	69	38	27	65	6.5	2.2	2.1	1.8
1	0	159	186	29	61	90	7.0	2.0	2.1	2.1
0	0	74	81	36	28	64	3.5	2.2	1.8	2.4
1	1	110	85	32	51	83	1.5	2.1	2.0	2.1
0	0	96	54	35	35	70	4.0	2.1	2.1	2.2
0	0	116	46	21	29	50	7.5	1.9	1.9	2.1
0	0	87	106	29	48	77	4.5	2.0	2.1	2.2
0	1	97	34	12	25	37	0.0	1.7	1.0	1.6
0	0	127	60	37	44	81	3.5	2.2	2.2	2.4
0	1	106	95	37	64	101	5.5	2.2	2.1	2.1
0	1	80	57	47	32	79	5.0	2.3	1.9	1.9
0	0	74	62	51	20	71	4.5	2.4	2.0	2.4
0	0	91	36	32	28	60	2.5	2.1	1.9	2.1
0	0	133	56	21	34	55	7.5	1.9	2.0	1.8
0	1	74	54	13	31	44	7.0	1.7	1.8	2.1
0	1	114	64	14	26	40	0.0	1.8	2.0	1.8
0	1	140	76	-2	58	56	4.5	1.5	2.0	1.9
0	0	95	98	20	23	43	3.0	1.9	2.0	1.9
0	1	98	88	24	21	45	1.5	1.9	1.8	2.4
0	0	121	35	11	21	32	3.5	1.7	2.0	1.8
0	1	126	102	23	33	56	2.5	1.9	1.1	1.8
0	1	98	61	24	16	40	5.5	1.9	1.8	2.1
0	1	95	80	14	20	34	8.0	1.8	1.8	2.1
0	1	110	49	52	37	89	1.0	2.4	2.0	2.4
0	1	70	78	15	35	50	5.0	1.8	1.9	1.9
0	0	102	90	23	33	56	4.5	1.9	2.1	1.8
0	1	86	45	19	27	46	3.0	1.8	1.6	1.8
0	1	130	55	35	41	76	3.0	2.1	2.2	2.2
0	1	96	96	24	40	64	8.0	1.9	1.9	2.4
0	0	102	43	39	35	74	2.5	2.2	2.0	1.8
0	0	100	52	29	28	57	7.0	2.0	2.1	2.4
0	0	94	60	13	32	45	0.0	1.7	1.3	1.8
0	0	52	54	8	22	30	1.0	1.7	1.8	1.9
0	0	98	51	18	44	62	3.5	1.8	1.9	2.4
0	0	118	51	24	27	51	5.5	1.9	2.1	2.1
0	1	99	38	19	17	36	5.5	1.8	1.8	1.9
1	1	48	41	23	12	34	0.5	1	0.75	2.1
1	1	50	146	16	45	61	7.5	1	1.5	2.7
1	1	150	182	33	37	70	9	4	3	2.1
1	1	154	192	32	37	69	9.5	4	2.25	2.1
0	0	109	263	37	108	145	8.5	3	3	2.1
0	1	68	35	14	10	23	7	2	1.5	2.1
1	1	194	439	52	68	120	8	4	3	2.1
1	0	158	214	75	72	147	10	4	3	2.1
1	1	159	341	72	143	215	7	4	3	2.1
1	0	67	58	15	9	24	8.5	2	0.75	2.1
1	0	147	292	29	55	84	9	4	3	2.4
1	1	39	85	13	17	30	9.5	1	2.25	1.95
1	1	100	200	40	37	77	4	3	1.5	2.1
1	1	111	158	19	27	46	6	3	1.5	2.1
1	1	138	199	24	37	61	8	4	2.25	1.95
1	1	101	297	121	58	178	5.5	3	3	2.1
0	1	131	227	93	66	160	9.5	4	3	2.4
1	1	101	108	36	21	57	7.5	3	1.5	2.1
1	1	114	86	23	19	42	7	3	2.25	2.25
1	0	165	302	85	78	163	7.5	4	2.25	2.4
1	1	114	148	41	35	75	8	3	1.5	2.25
1	1	111	178	46	48	94	7	3	2.25	2.55
1	1	75	120	18	27	45	7	2	1.5	1.95
1	1	82	207	35	43	78	6	2	2.25	2.4
1	1	121	157	17	30	47	10	3	2.25	2.1
1	1	32	128	4	25	29	2.5	1	3	2.1
1	0	150	296	28	69	97	9	4	3	2.4
1	1	117	323	44	72	116	8	3	3	2.1
0	1	71	79	10	23	32	6	2	1.5	2.1
1	1	165	70	38	13	50	8.5	4	3	2.25
1	1	154	146	57	61	118	6	4	3	2.25
1	1	126	246	23	43	66	9	4	2.25	2.4
1	0	138	145	26	22	48	8	4	1.5	2.1
1	0	149	196	36	51	86	8	4	2.25	2.1
1	0	145	199	22	67	89	9	4	2.25	2.4
1	1	120	127	40	36	76	5.5	3	3	2.1
1	0	138	91	18	21	39	5	4	0.75	1.95
1	0	109	153	31	44	75	7	3	2.25	2.1
1	0	132	299	11	45	57	5.5	4	3	2.25
1	1	172	228	38	34	72	9	4	3	2.25
1	0	169	190	24	36	60	2	4	1.5	2.4
1	1	114	180	37	72	109	8.5	3	2.25	2.25
1	1	156	212	37	39	76	9	4	3	2.25
1	0	172	269	22	43	65	8.5	4	2.25	2.1
0	1	68	130	15	25	40	9	2	1.5	2.1
0	1	89	179	2	56	58	7.5	2	2.25	2.1
1	1	167	243	43	80	123	10	4	2.25	2.7
1	0	113	190	31	40	71	9	3	1.5	2.1
0	0	115	299	29	73	102	7.5	3	2.25	2.1
0	0	78	121	45	34	80	6	2	1.5	2.25
0	0	118	137	25	72	97	10.5	3	2.25	2.7
0	1	87	305	4	42	46	8.5	2	3	2.4
1	0	173	157	31	61	93	8	4	3	2.1
1	1	2	96	-4	23	19	10	1	3	2.1
0	0	162	183	66	74	140	10.5	4	3	2.4
0	1	49	52	61	16	78	6.5	1	1.5	1.95
0	0	122	238	32	66	98	9.5	4	2.25	2.7
0	1	96	40	31	9	40	8.5	3	1.5	2.1
0	0	100	226	39	41	80	7.5	3	2.25	2.25
0	0	82	190	19	57	76	5	2	2.25	2.1
0	1	100	214	31	48	79	8	3	2.25	2.7
0	0	115	145	36	51	87	10	3	3	2.1
0	1	141	119	42	53	95	7	4	1.5	2.1
1	1	165	222	21	29	49	7.5	4	2.25	1.65
1	1	165	222	21	29	49	7.5	4	2.25	1.65
0	1	110	159	25	55	80	9.5	3	3	2.1
1	1	118	165	32	54	86	6	3	2.25	2.1
1	0	158	249	26	43	69	10	4	3	2.1
0	1	146	125	28	51	79	7	4	2.25	2.1
1	0	49	122	32	20	52	3	1	1.5	2.1
0	0	90	186	41	79	120	6	2	3	2.4
0	0	121	148	29	39	69	7	3	1.5	2.4
1	1	155	274	33	61	94	10	4	3	2.1
0	0	104	172	17	55	72	7	3	3	2.25
0	1	147	84	13	30	43	3.5	4	3	2.4
0	0	110	168	32	55	87	8	3	3	2.1
0	0	108	102	30	22	52	10	3	2.25	2.1
0	0	113	106	34	37	71	5.5	3	2.25	2.4
0	0	115	2	59	2	61	6	3	0.75	2.4
0	1	61	139	13	38	51	6.5	1	3	2.1
0	1	60	95	23	27	50	6.5	1	0.75	2.1
0	1	109	130	10	56	67	8.5	3	1.5	2.4
0	1	68	72	5	25	30	4	2	1.5	2.1
0	0	111	141	31	39	70	9.5	3	3	2.7
0	0	77	113	19	33	52	8	2	1.5	2.1
0	1	73	206	32	43	75	8.5	2	2.25	2.1
1	0	151	268	30	57	87	5.5	4	3	2.25
0	0	89	175	25	43	69	7	2	3	2.1
0	0	78	77	48	23	72	9	2	1.5	2.4
0	0	110	125	35	44	79	8	3	3	2.25
1	1	220	255	67	54	121	10	4	3	2.25
0	1	65	111	15	28	43	8	2	1.5	2.1
1	0	141	132	22	36	58	6	4	1.5	2.1
0	0	117	211	18	39	57	8	3	2.25	2.4
1	1	122	92	33	16	50	5	4	1.5	2.25
0	0	63	76	46	23	69	9	2	1.5	2.1
1	1	44	171	24	40	64	4.5	1	2.25	2.1
0	1	52	83	14	24	38	8.5	1	1.5	1.65
0	1	62	119	23	29	53	7	1	2.25	1.65
0	0	131	266	12	78	90	9.5	4	3	2.7
0	1	101	186	38	57	96	8.5	3	3	2.1
0	1	42	50	12	37	49	7.5	1	0.75	1.95
1	1	152	117	28	27	56	7.5	4	1.5	2.25
1	0	107	219	41	61	102	5	3	1.5	2.4
0	0	77	246	12	27	40	7	2	2.25	1.95
1	0	154	279	31	69	100	8	4	2.25	2.1
1	1	103	148	33	34	67	5.5	3	1.5	2.4
0	1	96	137	34	44	78	8.5	3	2.25	2.1
1	0	154	130	41	21	62	7.5	4	0.75	2.1
1	1	175	181	21	34	55	9.5	4	2.25	2.4
0	1	57	98	20	39	59	7	1	0.75	2.4
0	0	112	226	44	51	96	8	3	2.25	2.4
1	0	143	234	52	34	86	8.5	4	3	2.25
0	0	49	138	7	31	38	3.5	1	0.75	2.4
1	1	110	85	29	13	43	6.5	3	0.75	2.1
1	1	131	66	11	12	23	6.5	4	3	2.1
1	0	167	236	26	51	77	10.5	4	3	1.8
0	0	56	106	24	24	48	8.5	1	3	2.7
1	0	137	135	7	19	26	8	4	3	2.1
0	1	86	122	60	30	91	10	2	1.5	2.1
1	1	121	218	13	81	94	10	3	3	2.4
1	0	149	199	20	42	62	9.5	4	3	2.55
1	0	168	112	52	22	74	9	4	3	2.55
1	0	140	278	28	85	114	10	4	3	2.1
0	1	88	94	25	27	52	7.5	2	1.5	2.1
1	1	168	113	39	25	64	4.5	4	2.25	2.1
1	1	94	84	9	22	31	4.5	2	0.75	2.25
1	1	51	86	19	19	38	0.5	1	0.75	2.25
0	0	48	62	13	14	27	6.5	1	2.25	2.1
1	1	145	222	60	45	105	4.5	4	3	2.1
1	1	66	167	19	45	64	5.5	2	2.25	1.95
0	1	85	82	34	28	62	5	2	3	2.4
1	0	109	207	14	51	65	6	3	2.25	2.1
0	0	63	184	17	41	58	4	2	3	2.4
0	1	102	83	45	31	76	8	3	1.5	2.4
0	0	162	183	66	74	140	10.5	4	3	2.4
1	1	128	85	24	24	48	8.5	4	3	2.25
0	1	86	89	48	19	68	6.5	2	0.75	1.95
0	1	114	225	29	51	80	8	3	1.5	2.1
1	0	164	237	-2	73	71	8.5	4	3	2.1
1	1	119	102	51	24	76	5.5	3	3	2.55
1	0	126	221	2	61	63	7	4	3	2.1
1	1	132	128	24	23	46	5	4	2.25	2.1
1	1	142	91	40	14	53	3.5	4	2.25	2.1
1	0	83	198	20	54	74	5	2	3	1.95
0	1	94	204	19	51	70	9	2	1.5	2.25
0	0	81	158	16	62	78	8.5	2	2.25	2.4
1	1	166	138	20	36	56	5	4	2.25	1.95
0	0	110	226	40	59	100	9.5	3	2.25	2.1
0	1	64	44	27	24	51	3	2	0.75	2.1
1	0	93	196	25	26	52	1.5	2	2.25	1.95
0	0	104	83	49	54	102	6	3	1.5	2.1
0	1	105	79	39	39	78	0.5	3	2.25	2.1
0	1	49	52	61	16	78	6.5	1	1.5	1.95
0	0	88	105	19	36	55	7.5	2	0.75	2.1
0	1	95	116	67	31	98	4.5	2	1.5	1.95
0	1	102	83	45	31	76	8	3	1.5	2.4
0	0	99	196	30	42	73	9	3	2.25	2.4
0	1	63	153	8	39	47	7.5	2	1.5	2.4
0	0	76	157	19	25	45	8.5	2	1.5	1.95
0	0	109	75	52	31	83	7	3	3	2.7
0	1	117	106	22	38	60	9.5	3	2.25	2.1
0	1	57	58	17	31	48	6.5	1	1.5	1.95
0	0	120	75	33	17	50	9.5	3	0.75	2.1
0	1	73	74	34	22	56	6	2	2.25	1.95
0	0	91	185	22	55	77	8	2	3	2.1
0	0	108	265	30	62	91	9.5	3	3	2.25
0	1	105	131	25	51	76	8	3	1.5	2.7
1	0	117	139	38	30	68	8	3	1.5	2.1
0	0	119	196	26	49	74	9	3	2.25	2.4
0	1	31	78	13	16	29	5	1	0.75	1.35

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	11 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 11 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=252898&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=252898&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=252898&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	11 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Multiple Linear Regression - Estimated Regression Equation
Exam.10[t] = + 0.483843 -0.751349C[t] -0.0315109G[t] -0.00635228LFM[t] + 0.0103833B[t] -0.437834PRH[t] -0.430974CH[t] + 0.429438H[t] + 0.879207PR.4[t] + 0.265715PE.3[t] + 1.39704PA.3[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Exam.10[t] =  +  0.483843 -0.751349C[t] -0.0315109G[t] -0.00635228LFM[t] +  0.0103833B[t] -0.437834PRH[t] -0.430974CH[t] +  0.429438H[t] +  0.879207PR.4[t] +  0.265715PE.3[t] +  1.39704PA.3[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=252898&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Exam.10[t] =  +  0.483843 -0.751349C[t] -0.0315109G[t] -0.00635228LFM[t] +  0.0103833B[t] -0.437834PRH[t] -0.430974CH[t] +  0.429438H[t] +  0.879207PR.4[t] +  0.265715PE.3[t] +  1.39704PA.3[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=252898&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=252898&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
Exam.10[t] = + 0.483843 -0.751349C[t] -0.0315109G[t] -0.00635228LFM[t] + 0.0103833B[t] -0.437834PRH[t] -0.430974CH[t] + 0.429438H[t] + 0.879207PR.4[t] + 0.265715PE.3[t] + 1.39704PA.3[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	0.483843	1.07843	0.4487	0.654035	0.327017
C	-0.751349	0.316837	-2.371	0.0184095	0.00920477
G	-0.0315109	0.263247	-0.1197	0.904807	0.452404
LFM	-0.00635228	0.00504397	-1.259	0.20896	0.10448
B	0.0103833	0.00286764	3.621	0.000349517	0.000174758
PRH	-0.437834	0.352345	-1.243	0.215063	0.107531
CH	-0.430974	0.351391	-1.226	0.221067	0.110533
H	0.429438	0.351596	1.221	0.222983	0.111492
PR.4	0.879207	0.220198	3.993	8.3849e-05	4.19245e-05
PE.3	0.265715	0.260489	1.02	0.308595	0.154298
PA.3	1.39704	0.486983	2.869	0.00444012	0.00222006

\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) & 0.483843 & 1.07843 & 0.4487 & 0.654035 & 0.327017 \tabularnewline
C & -0.751349 & 0.316837 & -2.371 & 0.0184095 & 0.00920477 \tabularnewline
G & -0.0315109 & 0.263247 & -0.1197 & 0.904807 & 0.452404 \tabularnewline
LFM & -0.00635228 & 0.00504397 & -1.259 & 0.20896 & 0.10448 \tabularnewline
B & 0.0103833 & 0.00286764 & 3.621 & 0.000349517 & 0.000174758 \tabularnewline
PRH & -0.437834 & 0.352345 & -1.243 & 0.215063 & 0.107531 \tabularnewline
CH & -0.430974 & 0.351391 & -1.226 & 0.221067 & 0.110533 \tabularnewline
H & 0.429438 & 0.351596 & 1.221 & 0.222983 & 0.111492 \tabularnewline
PR.4 & 0.879207 & 0.220198 & 3.993 & 8.3849e-05 & 4.19245e-05 \tabularnewline
PE.3 & 0.265715 & 0.260489 & 1.02 & 0.308595 & 0.154298 \tabularnewline
PA.3 & 1.39704 & 0.486983 & 2.869 & 0.00444012 & 0.00222006 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=252898&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]0.483843[/C][C]1.07843[/C][C]0.4487[/C][C]0.654035[/C][C]0.327017[/C][/ROW]
[ROW][C]C[/C][C]-0.751349[/C][C]0.316837[/C][C]-2.371[/C][C]0.0184095[/C][C]0.00920477[/C][/ROW]
[ROW][C]G[/C][C]-0.0315109[/C][C]0.263247[/C][C]-0.1197[/C][C]0.904807[/C][C]0.452404[/C][/ROW]
[ROW][C]LFM[/C][C]-0.00635228[/C][C]0.00504397[/C][C]-1.259[/C][C]0.20896[/C][C]0.10448[/C][/ROW]
[ROW][C]B[/C][C]0.0103833[/C][C]0.00286764[/C][C]3.621[/C][C]0.000349517[/C][C]0.000174758[/C][/ROW]
[ROW][C]PRH[/C][C]-0.437834[/C][C]0.352345[/C][C]-1.243[/C][C]0.215063[/C][C]0.107531[/C][/ROW]
[ROW][C]CH[/C][C]-0.430974[/C][C]0.351391[/C][C]-1.226[/C][C]0.221067[/C][C]0.110533[/C][/ROW]
[ROW][C]H[/C][C]0.429438[/C][C]0.351596[/C][C]1.221[/C][C]0.222983[/C][C]0.111492[/C][/ROW]
[ROW][C]PR.4[/C][C]0.879207[/C][C]0.220198[/C][C]3.993[/C][C]8.3849e-05[/C][C]4.19245e-05[/C][/ROW]
[ROW][C]PE.3[/C][C]0.265715[/C][C]0.260489[/C][C]1.02[/C][C]0.308595[/C][C]0.154298[/C][/ROW]
[ROW][C]PA.3[/C][C]1.39704[/C][C]0.486983[/C][C]2.869[/C][C]0.00444012[/C][C]0.00222006[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=252898&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=252898&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	0.483843	1.07843	0.4487	0.654035	0.327017
C	-0.751349	0.316837	-2.371	0.0184095	0.00920477
G	-0.0315109	0.263247	-0.1197	0.904807	0.452404
LFM	-0.00635228	0.00504397	-1.259	0.20896	0.10448
B	0.0103833	0.00286764	3.621	0.000349517	0.000174758
PRH	-0.437834	0.352345	-1.243	0.215063	0.107531
CH	-0.430974	0.351391	-1.226	0.221067	0.110533
H	0.429438	0.351596	1.221	0.222983	0.111492
PR.4	0.879207	0.220198	3.993	8.3849e-05	4.19245e-05
PE.3	0.265715	0.260489	1.02	0.308595	0.154298
PA.3	1.39704	0.486983	2.869	0.00444012	0.00222006

Multiple Linear Regression - Regression Statistics
Multiple R	0.571243
R-squared	0.326319
Adjusted R-squared	0.301821
F-TEST (value)	13.3205
F-TEST (DF numerator)	10
F-TEST (DF denominator)	275
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.13634
Sum Squared Residuals	1255.09

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.571243 \tabularnewline
R-squared & 0.326319 \tabularnewline
Adjusted R-squared & 0.301821 \tabularnewline
F-TEST (value) & 13.3205 \tabularnewline
F-TEST (DF numerator) & 10 \tabularnewline
F-TEST (DF denominator) & 275 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.13634 \tabularnewline
Sum Squared Residuals & 1255.09 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=252898&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.571243[/C][/ROW]
[ROW][C]R-squared[/C][C]0.326319[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.301821[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]13.3205[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]10[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]275[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.13634[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1255.09[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=252898&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=252898&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.571243
R-squared	0.326319
Adjusted R-squared	0.301821
F-TEST (value)	13.3205
F-TEST (DF numerator)	10
F-TEST (DF denominator)	275
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.13634
Sum Squared Residuals	1255.09

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	3.76333	3.73667
2	2.5	3.7224	-1.2224
3	6	4.5362	1.4638
4	6.5	4.72894	1.77106
5	1	4.63409	-3.63409
6	1	3.90639	-2.90639
7	5.5	5.38188	0.118122
8	8.5	4.85517	3.64483
9	6.5	5.47705	1.02295
10	4.5	4.29969	0.200314
11	2	5.05369	-3.05369
12	5	4.99272	0.00728008
13	0.5	4.89881	-4.39881
14	5	3.94067	1.05933
15	5	5.01874	-0.0187353
16	2.5	1.83586	0.664144
17	5	5.83386	-0.833856
18	5.5	4.98628	0.513716
19	3.5	4.2969	-0.796903
20	3	5.84651	-2.84651
21	4	4.70953	-0.709525
22	0.5	4.09641	-3.59641
23	6.5	4.72783	1.77217
24	4.5	4.16347	0.336531
25	7.5	4.46723	3.03277
26	5.5	4.53468	0.965316
27	4	5.40051	-1.40051
28	7.5	7.04415	0.455846
29	7	6.10087	0.899133
30	4	4.0281	-0.0280962
31	5.5	4.61424	0.885756
32	2.5	4.79157	-2.29157
33	5.5	5.0847	0.415298
34	0.5	4.13464	-3.63464
35	3.5	4.00286	-0.502859
36	2.5	5.525	-3.025
37	4.5	5.34181	-0.841815
38	4.5	4.66593	-0.165933
39	4.5	4.42635	0.0736542
40	6	5.92789	0.0721069
41	2.5	4.41869	-1.91869
42	5	5.97019	-0.970188
43	0	4.37365	-4.37365
44	5	5.18531	-0.185307
45	6.5	4.49543	2.00457
46	5	4.31014	0.689857
47	6	6.00422	-0.00421588
48	4.5	5.03924	-0.53924
49	5.5	5.32306	0.176941
50	1	5.94238	-4.94238
51	7.5	3.71837	3.78163
52	6	5.58777	0.412231
53	5	6.18093	-1.18093
54	1	6.0343	-5.0343
55	5	4.91131	0.088689
56	6.5	4.67048	1.82952
57	7	5.26742	1.73258
58	4.5	4.92322	-0.423218
59	0	5.04461	-5.04461
60	8.5	4.10451	4.39549
61	3.5	3.94363	-0.443628
62	7.5	5.34298	2.15702
63	3.5	3.9867	-0.486704
64	6	4.45183	1.54817
65	1.5	4.98551	-3.48551
66	9	5.36138	3.63862
67	3.5	3.23611	0.26389
68	3.5	5.13395	-1.63395
69	4	5.459	-1.459
70	6.5	4.88713	1.61287
71	7.5	4.76944	2.73056
72	6	5.22797	0.772026
73	5	5.23714	-0.237138
74	5.5	4.25739	1.24261
75	3.5	5.03129	-1.53129
76	7.5	6.21302	1.28698
77	1	4.46428	-3.46428
78	6.5	4.86523	1.63477
79	NA	NA	1.21834
80	6.5	5.12913	1.37087
81	6.5	5.06676	1.43324
82	7	9.77498	-2.77498
83	3.5	6.84933	-3.34933
84	1.5	3.06491	-1.56491
85	4	1.61288	2.38712
86	7.5	9.10449	-1.60449
87	4.5	8.54566	-4.04566
88	0	2.29357	-2.29357
89	3.5	3.78246	-0.282457
90	5.5	5.77362	-0.273624
91	5	6.69303	-1.69303
92	4.5	7.25287	-2.75287
93	2.5	-0.291504	2.7915
94	7.5	5.79291	1.70709
95	7	11.8639	-4.86389
96	0	0.284446	-0.284446
97	4.5	7.05098	-2.55098
98	3	7.51145	-4.51145
99	1.5	2.49477	-0.99477
100	3.5	5.94468	-2.44468
101	2.5	2.31967	0.180332
102	5.5	3.0259	2.4741
103	8	12.7633	-4.76334
104	1	1.37966	-0.379664
105	5	5.76976	-0.769763
106	4.5	6.19467	-1.69467
107	3	5.34516	-2.34516
108	3	1.1046	1.8954
109	8	10.3815	-2.38153
110	2.5	1.27136	1.22864
111	7	11.7062	-4.70617
112	0	4.24057	-4.24057
113	1	3.11247	-2.11247
114	3.5	3.18311	0.316885
115	5.5	4.74762	0.752384
116	5.5	8.19308	-2.69308
117	0.5	-1.25435	1.75435
118	7.5	6.05174	1.44826
119	9	6.93927	2.06073
120	9.5	9.41421	0.0857932
121	8.5	6.41222	2.08778
122	7	8.73358	-1.73358
123	8	5.45827	2.54173
124	10	11.6552	-1.65519
125	7	3.16084	3.83916
126	8.5	8.66951	-0.169508
127	9	3.90185	5.09815
128	9.5	12.2197	-2.7197
129	4	4.40541	-0.405411
130	6	5.4712	0.528796
131	8	9.47729	-1.47729
132	5.5	5.19124	0.308756
133	9.5	7.81625	1.68375
134	7.5	6.52631	0.973692
135	7	7.95418	-0.954182
136	7.5	5.36563	2.13437
137	8	8.18207	-0.182067
138	7	5.15916	1.84084
139	7	7.67868	-0.678676
140	6	2.54297	3.45703
141	10	12.8649	-2.86492
142	2.5	2.67887	-0.17887
143	9	9.20006	-0.200062
144	8	7.36364	0.636359
145	6	3.56854	2.43146
146	8.5	9.6237	-1.1237
147	6	5.66329	0.336707
148	9	7.95854	1.04146
149	8	7.05954	0.940456
150	8	7.05762	0.942381
151	9	9.73478	-0.734781
152	5.5	6.55771	-1.05771
153	5	4.47012	0.529879
154	7	11.2239	-4.22385
155	5.5	4.5618	0.938198
156	9	14.6433	-5.64327
157	2	0.303356	1.69664
158	8.5	7.49802	1.00198
159	9	8.7307	0.269303
160	8.5	5.79663	2.70337
161	9	8.43282	0.567182
162	7.5	6.06604	1.43396
163	10	7.63575	2.36425
164	9	10.1716	-1.17155
165	7.5	8.04444	-0.544443
166	6	3.34375	2.65625
167	10.5	10.8769	-0.376932
168	8.5	8.08692	0.41308
169	8	3.29347	4.70653
170	10	7.85394	2.14606
171	10.5	8.5757	1.9243
172	6.5	6.69671	-0.196705
173	9.5	6.95372	2.54628
174	8.5	9.18362	-0.683615
175	7.5	9.47874	-1.97874
176	5	5.71259	-0.712591
177	8	5.24684	2.75316
178	10	10.2074	-0.207389
179	7	6.22744	0.772563
180	7.5	6.72744	0.772563
181	7.5	5.47867	2.02133
182	9.5	9.98228	-0.482278
183	6	4.27766	1.72234
184	10	10.5578	-0.557835
185	7	8.60015	-1.60015
186	3	4.28627	-1.28627
187	6	6.76707	-0.767066
188	7	5.43836	1.56164
189	10	10.96	-0.960004
190	7	11.4024	-4.40238
191	3.5	3.04486	0.455144
192	8	4.74047	3.25953
193	10	11.6127	-1.61273
194	5.5	4.96546	0.534542
195	6	5.45073	0.549273
196	6.5	4.83529	1.66471
197	6.5	5.75829	0.741706
198	8.5	10.2784	-1.77836
199	4	2.62936	1.37064
200	9.5	7.54858	1.95142
201	8	6.58289	1.41711
202	8.5	11.6739	-3.17387
203	5.5	5.87838	-0.378379
204	7	4.28885	2.71115
205	9	8.29964	0.700356
206	8	5.76302	2.23698
207	10	8.11379	1.88621
208	8	8.81658	-0.816579
209	6	6.30883	-0.30883
210	8	10.0678	-2.06779
211	5	1.54199	3.45801
212	9	9.84491	-0.844913
213	4.5	0.412306	4.08769
214	8.5	6.76806	1.73194
215	7	7.77904	-0.779041
216	9.5	9.1334	0.366598
217	8.5	5.34983	3.15017
218	7.5	7.16189	0.338112
219	7.5	9.77787	-2.27787
220	5	5.91671	-0.91671
221	7	7.33336	-0.333357
222	8	9.14321	-1.14321
223	5.5	4.08122	1.41878
224	8.5	7.37746	1.12254
225	7.5	5.70774	1.79226
226	9.5	7.81137	1.68863
227	7	7.68904	-0.689036
228	8	7.72228	0.277719
229	8.5	10.9305	-2.43047
230	3.5	2.82148	0.678517
231	6.5	6.6911	-0.191101
232	6.5	3.65411	2.84589
233	10.5	8.43873	2.06127
234	8.5	7.92377	0.576226
235	8	4.14314	3.85686
236	10	7.74998	2.25002
237	10	8.99626	1.00374
238	9.5	7.73427	1.76573
239	9	8.04124	0.958765
240	10	8.20875	1.79125
241	7.5	9.48972	-1.98972
242	4.5	4.96775	-0.467746
243	4.5	8.3031	-3.8031
244	0.5	-0.897106	1.39711
245	6.5	9.75984	-3.25984
246	4.5	4.86758	-0.367579
247	5.5	6.84379	-1.34379
248	5	6.1628	-1.1628
249	6	9.69691	-3.69691
250	4	2.62985	1.37015
251	8	5.85394	2.14606
252	10.5	8.98941	1.51059
253	8.5	7.50931	0.990692
254	6.5	6.21255	0.287455
255	8	7.80396	0.196045
256	8.5	9.96574	-1.46574
257	5.5	6.86406	-1.36406
258	7	8.57374	-1.57374
259	5	7.50552	-2.50552
260	3.5	4.79004	-1.29004
261	5	3.03585	1.96415
262	9	7.58945	1.41055
263	8.5	10.1951	-1.69508
264	5	3.80392	1.19608
265	9.5	11.6306	-2.13057
266	3	7.93695	-4.93695
267	1.5	1.23118	0.268819
268	6	11.8875	-5.88752
269	0.5	-1.4243	1.9243
270	6.5	4.69174	1.80826
271	7.5	8.32437	-0.824367
272	4.5	3.12985	1.37015
273	8	7.59149	0.408506
274	9	8.52358	0.476418
275	7.5	5.74396	1.75604
276	8.5	8.79274	-0.29274
277	7	4.23591	2.76409
278	9.5	7.50413	1.99587
279	6.5	2.96782	3.53218
280	9.5	9.01821	0.481788
281	6	5.04682	0.953179
282	8	6.85089	1.14911
283	9.5	9.1655	0.3345
284	8	6.03739	1.96261
285	8	6.6284	1.3716
286	9	7.89608	1.10392
287	5	NA	NA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 3.76333 & 3.73667 \tabularnewline
2 & 2.5 & 3.7224 & -1.2224 \tabularnewline
3 & 6 & 4.5362 & 1.4638 \tabularnewline
4 & 6.5 & 4.72894 & 1.77106 \tabularnewline
5 & 1 & 4.63409 & -3.63409 \tabularnewline
6 & 1 & 3.90639 & -2.90639 \tabularnewline
7 & 5.5 & 5.38188 & 0.118122 \tabularnewline
8 & 8.5 & 4.85517 & 3.64483 \tabularnewline
9 & 6.5 & 5.47705 & 1.02295 \tabularnewline
10 & 4.5 & 4.29969 & 0.200314 \tabularnewline
11 & 2 & 5.05369 & -3.05369 \tabularnewline
12 & 5 & 4.99272 & 0.00728008 \tabularnewline
13 & 0.5 & 4.89881 & -4.39881 \tabularnewline
14 & 5 & 3.94067 & 1.05933 \tabularnewline
15 & 5 & 5.01874 & -0.0187353 \tabularnewline
16 & 2.5 & 1.83586 & 0.664144 \tabularnewline
17 & 5 & 5.83386 & -0.833856 \tabularnewline
18 & 5.5 & 4.98628 & 0.513716 \tabularnewline
19 & 3.5 & 4.2969 & -0.796903 \tabularnewline
20 & 3 & 5.84651 & -2.84651 \tabularnewline
21 & 4 & 4.70953 & -0.709525 \tabularnewline
22 & 0.5 & 4.09641 & -3.59641 \tabularnewline
23 & 6.5 & 4.72783 & 1.77217 \tabularnewline
24 & 4.5 & 4.16347 & 0.336531 \tabularnewline
25 & 7.5 & 4.46723 & 3.03277 \tabularnewline
26 & 5.5 & 4.53468 & 0.965316 \tabularnewline
27 & 4 & 5.40051 & -1.40051 \tabularnewline
28 & 7.5 & 7.04415 & 0.455846 \tabularnewline
29 & 7 & 6.10087 & 0.899133 \tabularnewline
30 & 4 & 4.0281 & -0.0280962 \tabularnewline
31 & 5.5 & 4.61424 & 0.885756 \tabularnewline
32 & 2.5 & 4.79157 & -2.29157 \tabularnewline
33 & 5.5 & 5.0847 & 0.415298 \tabularnewline
34 & 0.5 & 4.13464 & -3.63464 \tabularnewline
35 & 3.5 & 4.00286 & -0.502859 \tabularnewline
36 & 2.5 & 5.525 & -3.025 \tabularnewline
37 & 4.5 & 5.34181 & -0.841815 \tabularnewline
38 & 4.5 & 4.66593 & -0.165933 \tabularnewline
39 & 4.5 & 4.42635 & 0.0736542 \tabularnewline
40 & 6 & 5.92789 & 0.0721069 \tabularnewline
41 & 2.5 & 4.41869 & -1.91869 \tabularnewline
42 & 5 & 5.97019 & -0.970188 \tabularnewline
43 & 0 & 4.37365 & -4.37365 \tabularnewline
44 & 5 & 5.18531 & -0.185307 \tabularnewline
45 & 6.5 & 4.49543 & 2.00457 \tabularnewline
46 & 5 & 4.31014 & 0.689857 \tabularnewline
47 & 6 & 6.00422 & -0.00421588 \tabularnewline
48 & 4.5 & 5.03924 & -0.53924 \tabularnewline
49 & 5.5 & 5.32306 & 0.176941 \tabularnewline
50 & 1 & 5.94238 & -4.94238 \tabularnewline
51 & 7.5 & 3.71837 & 3.78163 \tabularnewline
52 & 6 & 5.58777 & 0.412231 \tabularnewline
53 & 5 & 6.18093 & -1.18093 \tabularnewline
54 & 1 & 6.0343 & -5.0343 \tabularnewline
55 & 5 & 4.91131 & 0.088689 \tabularnewline
56 & 6.5 & 4.67048 & 1.82952 \tabularnewline
57 & 7 & 5.26742 & 1.73258 \tabularnewline
58 & 4.5 & 4.92322 & -0.423218 \tabularnewline
59 & 0 & 5.04461 & -5.04461 \tabularnewline
60 & 8.5 & 4.10451 & 4.39549 \tabularnewline
61 & 3.5 & 3.94363 & -0.443628 \tabularnewline
62 & 7.5 & 5.34298 & 2.15702 \tabularnewline
63 & 3.5 & 3.9867 & -0.486704 \tabularnewline
64 & 6 & 4.45183 & 1.54817 \tabularnewline
65 & 1.5 & 4.98551 & -3.48551 \tabularnewline
66 & 9 & 5.36138 & 3.63862 \tabularnewline
67 & 3.5 & 3.23611 & 0.26389 \tabularnewline
68 & 3.5 & 5.13395 & -1.63395 \tabularnewline
69 & 4 & 5.459 & -1.459 \tabularnewline
70 & 6.5 & 4.88713 & 1.61287 \tabularnewline
71 & 7.5 & 4.76944 & 2.73056 \tabularnewline
72 & 6 & 5.22797 & 0.772026 \tabularnewline
73 & 5 & 5.23714 & -0.237138 \tabularnewline
74 & 5.5 & 4.25739 & 1.24261 \tabularnewline
75 & 3.5 & 5.03129 & -1.53129 \tabularnewline
76 & 7.5 & 6.21302 & 1.28698 \tabularnewline
77 & 1 & 4.46428 & -3.46428 \tabularnewline
78 & 6.5 & 4.86523 & 1.63477 \tabularnewline
79 & NA & NA & 1.21834 \tabularnewline
80 & 6.5 & 5.12913 & 1.37087 \tabularnewline
81 & 6.5 & 5.06676 & 1.43324 \tabularnewline
82 & 7 & 9.77498 & -2.77498 \tabularnewline
83 & 3.5 & 6.84933 & -3.34933 \tabularnewline
84 & 1.5 & 3.06491 & -1.56491 \tabularnewline
85 & 4 & 1.61288 & 2.38712 \tabularnewline
86 & 7.5 & 9.10449 & -1.60449 \tabularnewline
87 & 4.5 & 8.54566 & -4.04566 \tabularnewline
88 & 0 & 2.29357 & -2.29357 \tabularnewline
89 & 3.5 & 3.78246 & -0.282457 \tabularnewline
90 & 5.5 & 5.77362 & -0.273624 \tabularnewline
91 & 5 & 6.69303 & -1.69303 \tabularnewline
92 & 4.5 & 7.25287 & -2.75287 \tabularnewline
93 & 2.5 & -0.291504 & 2.7915 \tabularnewline
94 & 7.5 & 5.79291 & 1.70709 \tabularnewline
95 & 7 & 11.8639 & -4.86389 \tabularnewline
96 & 0 & 0.284446 & -0.284446 \tabularnewline
97 & 4.5 & 7.05098 & -2.55098 \tabularnewline
98 & 3 & 7.51145 & -4.51145 \tabularnewline
99 & 1.5 & 2.49477 & -0.99477 \tabularnewline
100 & 3.5 & 5.94468 & -2.44468 \tabularnewline
101 & 2.5 & 2.31967 & 0.180332 \tabularnewline
102 & 5.5 & 3.0259 & 2.4741 \tabularnewline
103 & 8 & 12.7633 & -4.76334 \tabularnewline
104 & 1 & 1.37966 & -0.379664 \tabularnewline
105 & 5 & 5.76976 & -0.769763 \tabularnewline
106 & 4.5 & 6.19467 & -1.69467 \tabularnewline
107 & 3 & 5.34516 & -2.34516 \tabularnewline
108 & 3 & 1.1046 & 1.8954 \tabularnewline
109 & 8 & 10.3815 & -2.38153 \tabularnewline
110 & 2.5 & 1.27136 & 1.22864 \tabularnewline
111 & 7 & 11.7062 & -4.70617 \tabularnewline
112 & 0 & 4.24057 & -4.24057 \tabularnewline
113 & 1 & 3.11247 & -2.11247 \tabularnewline
114 & 3.5 & 3.18311 & 0.316885 \tabularnewline
115 & 5.5 & 4.74762 & 0.752384 \tabularnewline
116 & 5.5 & 8.19308 & -2.69308 \tabularnewline
117 & 0.5 & -1.25435 & 1.75435 \tabularnewline
118 & 7.5 & 6.05174 & 1.44826 \tabularnewline
119 & 9 & 6.93927 & 2.06073 \tabularnewline
120 & 9.5 & 9.41421 & 0.0857932 \tabularnewline
121 & 8.5 & 6.41222 & 2.08778 \tabularnewline
122 & 7 & 8.73358 & -1.73358 \tabularnewline
123 & 8 & 5.45827 & 2.54173 \tabularnewline
124 & 10 & 11.6552 & -1.65519 \tabularnewline
125 & 7 & 3.16084 & 3.83916 \tabularnewline
126 & 8.5 & 8.66951 & -0.169508 \tabularnewline
127 & 9 & 3.90185 & 5.09815 \tabularnewline
128 & 9.5 & 12.2197 & -2.7197 \tabularnewline
129 & 4 & 4.40541 & -0.405411 \tabularnewline
130 & 6 & 5.4712 & 0.528796 \tabularnewline
131 & 8 & 9.47729 & -1.47729 \tabularnewline
132 & 5.5 & 5.19124 & 0.308756 \tabularnewline
133 & 9.5 & 7.81625 & 1.68375 \tabularnewline
134 & 7.5 & 6.52631 & 0.973692 \tabularnewline
135 & 7 & 7.95418 & -0.954182 \tabularnewline
136 & 7.5 & 5.36563 & 2.13437 \tabularnewline
137 & 8 & 8.18207 & -0.182067 \tabularnewline
138 & 7 & 5.15916 & 1.84084 \tabularnewline
139 & 7 & 7.67868 & -0.678676 \tabularnewline
140 & 6 & 2.54297 & 3.45703 \tabularnewline
141 & 10 & 12.8649 & -2.86492 \tabularnewline
142 & 2.5 & 2.67887 & -0.17887 \tabularnewline
143 & 9 & 9.20006 & -0.200062 \tabularnewline
144 & 8 & 7.36364 & 0.636359 \tabularnewline
145 & 6 & 3.56854 & 2.43146 \tabularnewline
146 & 8.5 & 9.6237 & -1.1237 \tabularnewline
147 & 6 & 5.66329 & 0.336707 \tabularnewline
148 & 9 & 7.95854 & 1.04146 \tabularnewline
149 & 8 & 7.05954 & 0.940456 \tabularnewline
150 & 8 & 7.05762 & 0.942381 \tabularnewline
151 & 9 & 9.73478 & -0.734781 \tabularnewline
152 & 5.5 & 6.55771 & -1.05771 \tabularnewline
153 & 5 & 4.47012 & 0.529879 \tabularnewline
154 & 7 & 11.2239 & -4.22385 \tabularnewline
155 & 5.5 & 4.5618 & 0.938198 \tabularnewline
156 & 9 & 14.6433 & -5.64327 \tabularnewline
157 & 2 & 0.303356 & 1.69664 \tabularnewline
158 & 8.5 & 7.49802 & 1.00198 \tabularnewline
159 & 9 & 8.7307 & 0.269303 \tabularnewline
160 & 8.5 & 5.79663 & 2.70337 \tabularnewline
161 & 9 & 8.43282 & 0.567182 \tabularnewline
162 & 7.5 & 6.06604 & 1.43396 \tabularnewline
163 & 10 & 7.63575 & 2.36425 \tabularnewline
164 & 9 & 10.1716 & -1.17155 \tabularnewline
165 & 7.5 & 8.04444 & -0.544443 \tabularnewline
166 & 6 & 3.34375 & 2.65625 \tabularnewline
167 & 10.5 & 10.8769 & -0.376932 \tabularnewline
168 & 8.5 & 8.08692 & 0.41308 \tabularnewline
169 & 8 & 3.29347 & 4.70653 \tabularnewline
170 & 10 & 7.85394 & 2.14606 \tabularnewline
171 & 10.5 & 8.5757 & 1.9243 \tabularnewline
172 & 6.5 & 6.69671 & -0.196705 \tabularnewline
173 & 9.5 & 6.95372 & 2.54628 \tabularnewline
174 & 8.5 & 9.18362 & -0.683615 \tabularnewline
175 & 7.5 & 9.47874 & -1.97874 \tabularnewline
176 & 5 & 5.71259 & -0.712591 \tabularnewline
177 & 8 & 5.24684 & 2.75316 \tabularnewline
178 & 10 & 10.2074 & -0.207389 \tabularnewline
179 & 7 & 6.22744 & 0.772563 \tabularnewline
180 & 7.5 & 6.72744 & 0.772563 \tabularnewline
181 & 7.5 & 5.47867 & 2.02133 \tabularnewline
182 & 9.5 & 9.98228 & -0.482278 \tabularnewline
183 & 6 & 4.27766 & 1.72234 \tabularnewline
184 & 10 & 10.5578 & -0.557835 \tabularnewline
185 & 7 & 8.60015 & -1.60015 \tabularnewline
186 & 3 & 4.28627 & -1.28627 \tabularnewline
187 & 6 & 6.76707 & -0.767066 \tabularnewline
188 & 7 & 5.43836 & 1.56164 \tabularnewline
189 & 10 & 10.96 & -0.960004 \tabularnewline
190 & 7 & 11.4024 & -4.40238 \tabularnewline
191 & 3.5 & 3.04486 & 0.455144 \tabularnewline
192 & 8 & 4.74047 & 3.25953 \tabularnewline
193 & 10 & 11.6127 & -1.61273 \tabularnewline
194 & 5.5 & 4.96546 & 0.534542 \tabularnewline
195 & 6 & 5.45073 & 0.549273 \tabularnewline
196 & 6.5 & 4.83529 & 1.66471 \tabularnewline
197 & 6.5 & 5.75829 & 0.741706 \tabularnewline
198 & 8.5 & 10.2784 & -1.77836 \tabularnewline
199 & 4 & 2.62936 & 1.37064 \tabularnewline
200 & 9.5 & 7.54858 & 1.95142 \tabularnewline
201 & 8 & 6.58289 & 1.41711 \tabularnewline
202 & 8.5 & 11.6739 & -3.17387 \tabularnewline
203 & 5.5 & 5.87838 & -0.378379 \tabularnewline
204 & 7 & 4.28885 & 2.71115 \tabularnewline
205 & 9 & 8.29964 & 0.700356 \tabularnewline
206 & 8 & 5.76302 & 2.23698 \tabularnewline
207 & 10 & 8.11379 & 1.88621 \tabularnewline
208 & 8 & 8.81658 & -0.816579 \tabularnewline
209 & 6 & 6.30883 & -0.30883 \tabularnewline
210 & 8 & 10.0678 & -2.06779 \tabularnewline
211 & 5 & 1.54199 & 3.45801 \tabularnewline
212 & 9 & 9.84491 & -0.844913 \tabularnewline
213 & 4.5 & 0.412306 & 4.08769 \tabularnewline
214 & 8.5 & 6.76806 & 1.73194 \tabularnewline
215 & 7 & 7.77904 & -0.779041 \tabularnewline
216 & 9.5 & 9.1334 & 0.366598 \tabularnewline
217 & 8.5 & 5.34983 & 3.15017 \tabularnewline
218 & 7.5 & 7.16189 & 0.338112 \tabularnewline
219 & 7.5 & 9.77787 & -2.27787 \tabularnewline
220 & 5 & 5.91671 & -0.91671 \tabularnewline
221 & 7 & 7.33336 & -0.333357 \tabularnewline
222 & 8 & 9.14321 & -1.14321 \tabularnewline
223 & 5.5 & 4.08122 & 1.41878 \tabularnewline
224 & 8.5 & 7.37746 & 1.12254 \tabularnewline
225 & 7.5 & 5.70774 & 1.79226 \tabularnewline
226 & 9.5 & 7.81137 & 1.68863 \tabularnewline
227 & 7 & 7.68904 & -0.689036 \tabularnewline
228 & 8 & 7.72228 & 0.277719 \tabularnewline
229 & 8.5 & 10.9305 & -2.43047 \tabularnewline
230 & 3.5 & 2.82148 & 0.678517 \tabularnewline
231 & 6.5 & 6.6911 & -0.191101 \tabularnewline
232 & 6.5 & 3.65411 & 2.84589 \tabularnewline
233 & 10.5 & 8.43873 & 2.06127 \tabularnewline
234 & 8.5 & 7.92377 & 0.576226 \tabularnewline
235 & 8 & 4.14314 & 3.85686 \tabularnewline
236 & 10 & 7.74998 & 2.25002 \tabularnewline
237 & 10 & 8.99626 & 1.00374 \tabularnewline
238 & 9.5 & 7.73427 & 1.76573 \tabularnewline
239 & 9 & 8.04124 & 0.958765 \tabularnewline
240 & 10 & 8.20875 & 1.79125 \tabularnewline
241 & 7.5 & 9.48972 & -1.98972 \tabularnewline
242 & 4.5 & 4.96775 & -0.467746 \tabularnewline
243 & 4.5 & 8.3031 & -3.8031 \tabularnewline
244 & 0.5 & -0.897106 & 1.39711 \tabularnewline
245 & 6.5 & 9.75984 & -3.25984 \tabularnewline
246 & 4.5 & 4.86758 & -0.367579 \tabularnewline
247 & 5.5 & 6.84379 & -1.34379 \tabularnewline
248 & 5 & 6.1628 & -1.1628 \tabularnewline
249 & 6 & 9.69691 & -3.69691 \tabularnewline
250 & 4 & 2.62985 & 1.37015 \tabularnewline
251 & 8 & 5.85394 & 2.14606 \tabularnewline
252 & 10.5 & 8.98941 & 1.51059 \tabularnewline
253 & 8.5 & 7.50931 & 0.990692 \tabularnewline
254 & 6.5 & 6.21255 & 0.287455 \tabularnewline
255 & 8 & 7.80396 & 0.196045 \tabularnewline
256 & 8.5 & 9.96574 & -1.46574 \tabularnewline
257 & 5.5 & 6.86406 & -1.36406 \tabularnewline
258 & 7 & 8.57374 & -1.57374 \tabularnewline
259 & 5 & 7.50552 & -2.50552 \tabularnewline
260 & 3.5 & 4.79004 & -1.29004 \tabularnewline
261 & 5 & 3.03585 & 1.96415 \tabularnewline
262 & 9 & 7.58945 & 1.41055 \tabularnewline
263 & 8.5 & 10.1951 & -1.69508 \tabularnewline
264 & 5 & 3.80392 & 1.19608 \tabularnewline
265 & 9.5 & 11.6306 & -2.13057 \tabularnewline
266 & 3 & 7.93695 & -4.93695 \tabularnewline
267 & 1.5 & 1.23118 & 0.268819 \tabularnewline
268 & 6 & 11.8875 & -5.88752 \tabularnewline
269 & 0.5 & -1.4243 & 1.9243 \tabularnewline
270 & 6.5 & 4.69174 & 1.80826 \tabularnewline
271 & 7.5 & 8.32437 & -0.824367 \tabularnewline
272 & 4.5 & 3.12985 & 1.37015 \tabularnewline
273 & 8 & 7.59149 & 0.408506 \tabularnewline
274 & 9 & 8.52358 & 0.476418 \tabularnewline
275 & 7.5 & 5.74396 & 1.75604 \tabularnewline
276 & 8.5 & 8.79274 & -0.29274 \tabularnewline
277 & 7 & 4.23591 & 2.76409 \tabularnewline
278 & 9.5 & 7.50413 & 1.99587 \tabularnewline
279 & 6.5 & 2.96782 & 3.53218 \tabularnewline
280 & 9.5 & 9.01821 & 0.481788 \tabularnewline
281 & 6 & 5.04682 & 0.953179 \tabularnewline
282 & 8 & 6.85089 & 1.14911 \tabularnewline
283 & 9.5 & 9.1655 & 0.3345 \tabularnewline
284 & 8 & 6.03739 & 1.96261 \tabularnewline
285 & 8 & 6.6284 & 1.3716 \tabularnewline
286 & 9 & 7.89608 & 1.10392 \tabularnewline
287 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=252898&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]7.5[/C][C]3.76333[/C][C]3.73667[/C][/ROW]
[ROW][C]2[/C][C]2.5[/C][C]3.7224[/C][C]-1.2224[/C][/ROW]
[ROW][C]3[/C][C]6[/C][C]4.5362[/C][C]1.4638[/C][/ROW]
[ROW][C]4[/C][C]6.5[/C][C]4.72894[/C][C]1.77106[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]4.63409[/C][C]-3.63409[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]3.90639[/C][C]-2.90639[/C][/ROW]
[ROW][C]7[/C][C]5.5[/C][C]5.38188[/C][C]0.118122[/C][/ROW]
[ROW][C]8[/C][C]8.5[/C][C]4.85517[/C][C]3.64483[/C][/ROW]
[ROW][C]9[/C][C]6.5[/C][C]5.47705[/C][C]1.02295[/C][/ROW]
[ROW][C]10[/C][C]4.5[/C][C]4.29969[/C][C]0.200314[/C][/ROW]
[ROW][C]11[/C][C]2[/C][C]5.05369[/C][C]-3.05369[/C][/ROW]
[ROW][C]12[/C][C]5[/C][C]4.99272[/C][C]0.00728008[/C][/ROW]
[ROW][C]13[/C][C]0.5[/C][C]4.89881[/C][C]-4.39881[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]3.94067[/C][C]1.05933[/C][/ROW]
[ROW][C]15[/C][C]5[/C][C]5.01874[/C][C]-0.0187353[/C][/ROW]
[ROW][C]16[/C][C]2.5[/C][C]1.83586[/C][C]0.664144[/C][/ROW]
[ROW][C]17[/C][C]5[/C][C]5.83386[/C][C]-0.833856[/C][/ROW]
[ROW][C]18[/C][C]5.5[/C][C]4.98628[/C][C]0.513716[/C][/ROW]
[ROW][C]19[/C][C]3.5[/C][C]4.2969[/C][C]-0.796903[/C][/ROW]
[ROW][C]20[/C][C]3[/C][C]5.84651[/C][C]-2.84651[/C][/ROW]
[ROW][C]21[/C][C]4[/C][C]4.70953[/C][C]-0.709525[/C][/ROW]
[ROW][C]22[/C][C]0.5[/C][C]4.09641[/C][C]-3.59641[/C][/ROW]
[ROW][C]23[/C][C]6.5[/C][C]4.72783[/C][C]1.77217[/C][/ROW]
[ROW][C]24[/C][C]4.5[/C][C]4.16347[/C][C]0.336531[/C][/ROW]
[ROW][C]25[/C][C]7.5[/C][C]4.46723[/C][C]3.03277[/C][/ROW]
[ROW][C]26[/C][C]5.5[/C][C]4.53468[/C][C]0.965316[/C][/ROW]
[ROW][C]27[/C][C]4[/C][C]5.40051[/C][C]-1.40051[/C][/ROW]
[ROW][C]28[/C][C]7.5[/C][C]7.04415[/C][C]0.455846[/C][/ROW]
[ROW][C]29[/C][C]7[/C][C]6.10087[/C][C]0.899133[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]4.0281[/C][C]-0.0280962[/C][/ROW]
[ROW][C]31[/C][C]5.5[/C][C]4.61424[/C][C]0.885756[/C][/ROW]
[ROW][C]32[/C][C]2.5[/C][C]4.79157[/C][C]-2.29157[/C][/ROW]
[ROW][C]33[/C][C]5.5[/C][C]5.0847[/C][C]0.415298[/C][/ROW]
[ROW][C]34[/C][C]0.5[/C][C]4.13464[/C][C]-3.63464[/C][/ROW]
[ROW][C]35[/C][C]3.5[/C][C]4.00286[/C][C]-0.502859[/C][/ROW]
[ROW][C]36[/C][C]2.5[/C][C]5.525[/C][C]-3.025[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.34181[/C][C]-0.841815[/C][/ROW]
[ROW][C]38[/C][C]4.5[/C][C]4.66593[/C][C]-0.165933[/C][/ROW]
[ROW][C]39[/C][C]4.5[/C][C]4.42635[/C][C]0.0736542[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]5.92789[/C][C]0.0721069[/C][/ROW]
[ROW][C]41[/C][C]2.5[/C][C]4.41869[/C][C]-1.91869[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]5.97019[/C][C]-0.970188[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]4.37365[/C][C]-4.37365[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]5.18531[/C][C]-0.185307[/C][/ROW]
[ROW][C]45[/C][C]6.5[/C][C]4.49543[/C][C]2.00457[/C][/ROW]
[ROW][C]46[/C][C]5[/C][C]4.31014[/C][C]0.689857[/C][/ROW]
[ROW][C]47[/C][C]6[/C][C]6.00422[/C][C]-0.00421588[/C][/ROW]
[ROW][C]48[/C][C]4.5[/C][C]5.03924[/C][C]-0.53924[/C][/ROW]
[ROW][C]49[/C][C]5.5[/C][C]5.32306[/C][C]0.176941[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]5.94238[/C][C]-4.94238[/C][/ROW]
[ROW][C]51[/C][C]7.5[/C][C]3.71837[/C][C]3.78163[/C][/ROW]
[ROW][C]52[/C][C]6[/C][C]5.58777[/C][C]0.412231[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]6.18093[/C][C]-1.18093[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]6.0343[/C][C]-5.0343[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]4.91131[/C][C]0.088689[/C][/ROW]
[ROW][C]56[/C][C]6.5[/C][C]4.67048[/C][C]1.82952[/C][/ROW]
[ROW][C]57[/C][C]7[/C][C]5.26742[/C][C]1.73258[/C][/ROW]
[ROW][C]58[/C][C]4.5[/C][C]4.92322[/C][C]-0.423218[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]5.04461[/C][C]-5.04461[/C][/ROW]
[ROW][C]60[/C][C]8.5[/C][C]4.10451[/C][C]4.39549[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]3.94363[/C][C]-0.443628[/C][/ROW]
[ROW][C]62[/C][C]7.5[/C][C]5.34298[/C][C]2.15702[/C][/ROW]
[ROW][C]63[/C][C]3.5[/C][C]3.9867[/C][C]-0.486704[/C][/ROW]
[ROW][C]64[/C][C]6[/C][C]4.45183[/C][C]1.54817[/C][/ROW]
[ROW][C]65[/C][C]1.5[/C][C]4.98551[/C][C]-3.48551[/C][/ROW]
[ROW][C]66[/C][C]9[/C][C]5.36138[/C][C]3.63862[/C][/ROW]
[ROW][C]67[/C][C]3.5[/C][C]3.23611[/C][C]0.26389[/C][/ROW]
[ROW][C]68[/C][C]3.5[/C][C]5.13395[/C][C]-1.63395[/C][/ROW]
[ROW][C]69[/C][C]4[/C][C]5.459[/C][C]-1.459[/C][/ROW]
[ROW][C]70[/C][C]6.5[/C][C]4.88713[/C][C]1.61287[/C][/ROW]
[ROW][C]71[/C][C]7.5[/C][C]4.76944[/C][C]2.73056[/C][/ROW]
[ROW][C]72[/C][C]6[/C][C]5.22797[/C][C]0.772026[/C][/ROW]
[ROW][C]73[/C][C]5[/C][C]5.23714[/C][C]-0.237138[/C][/ROW]
[ROW][C]74[/C][C]5.5[/C][C]4.25739[/C][C]1.24261[/C][/ROW]
[ROW][C]75[/C][C]3.5[/C][C]5.03129[/C][C]-1.53129[/C][/ROW]
[ROW][C]76[/C][C]7.5[/C][C]6.21302[/C][C]1.28698[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]4.46428[/C][C]-3.46428[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]4.86523[/C][C]1.63477[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]1.21834[/C][/ROW]
[ROW][C]80[/C][C]6.5[/C][C]5.12913[/C][C]1.37087[/C][/ROW]
[ROW][C]81[/C][C]6.5[/C][C]5.06676[/C][C]1.43324[/C][/ROW]
[ROW][C]82[/C][C]7[/C][C]9.77498[/C][C]-2.77498[/C][/ROW]
[ROW][C]83[/C][C]3.5[/C][C]6.84933[/C][C]-3.34933[/C][/ROW]
[ROW][C]84[/C][C]1.5[/C][C]3.06491[/C][C]-1.56491[/C][/ROW]
[ROW][C]85[/C][C]4[/C][C]1.61288[/C][C]2.38712[/C][/ROW]
[ROW][C]86[/C][C]7.5[/C][C]9.10449[/C][C]-1.60449[/C][/ROW]
[ROW][C]87[/C][C]4.5[/C][C]8.54566[/C][C]-4.04566[/C][/ROW]
[ROW][C]88[/C][C]0[/C][C]2.29357[/C][C]-2.29357[/C][/ROW]
[ROW][C]89[/C][C]3.5[/C][C]3.78246[/C][C]-0.282457[/C][/ROW]
[ROW][C]90[/C][C]5.5[/C][C]5.77362[/C][C]-0.273624[/C][/ROW]
[ROW][C]91[/C][C]5[/C][C]6.69303[/C][C]-1.69303[/C][/ROW]
[ROW][C]92[/C][C]4.5[/C][C]7.25287[/C][C]-2.75287[/C][/ROW]
[ROW][C]93[/C][C]2.5[/C][C]-0.291504[/C][C]2.7915[/C][/ROW]
[ROW][C]94[/C][C]7.5[/C][C]5.79291[/C][C]1.70709[/C][/ROW]
[ROW][C]95[/C][C]7[/C][C]11.8639[/C][C]-4.86389[/C][/ROW]
[ROW][C]96[/C][C]0[/C][C]0.284446[/C][C]-0.284446[/C][/ROW]
[ROW][C]97[/C][C]4.5[/C][C]7.05098[/C][C]-2.55098[/C][/ROW]
[ROW][C]98[/C][C]3[/C][C]7.51145[/C][C]-4.51145[/C][/ROW]
[ROW][C]99[/C][C]1.5[/C][C]2.49477[/C][C]-0.99477[/C][/ROW]
[ROW][C]100[/C][C]3.5[/C][C]5.94468[/C][C]-2.44468[/C][/ROW]
[ROW][C]101[/C][C]2.5[/C][C]2.31967[/C][C]0.180332[/C][/ROW]
[ROW][C]102[/C][C]5.5[/C][C]3.0259[/C][C]2.4741[/C][/ROW]
[ROW][C]103[/C][C]8[/C][C]12.7633[/C][C]-4.76334[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]1.37966[/C][C]-0.379664[/C][/ROW]
[ROW][C]105[/C][C]5[/C][C]5.76976[/C][C]-0.769763[/C][/ROW]
[ROW][C]106[/C][C]4.5[/C][C]6.19467[/C][C]-1.69467[/C][/ROW]
[ROW][C]107[/C][C]3[/C][C]5.34516[/C][C]-2.34516[/C][/ROW]
[ROW][C]108[/C][C]3[/C][C]1.1046[/C][C]1.8954[/C][/ROW]
[ROW][C]109[/C][C]8[/C][C]10.3815[/C][C]-2.38153[/C][/ROW]
[ROW][C]110[/C][C]2.5[/C][C]1.27136[/C][C]1.22864[/C][/ROW]
[ROW][C]111[/C][C]7[/C][C]11.7062[/C][C]-4.70617[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]4.24057[/C][C]-4.24057[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]3.11247[/C][C]-2.11247[/C][/ROW]
[ROW][C]114[/C][C]3.5[/C][C]3.18311[/C][C]0.316885[/C][/ROW]
[ROW][C]115[/C][C]5.5[/C][C]4.74762[/C][C]0.752384[/C][/ROW]
[ROW][C]116[/C][C]5.5[/C][C]8.19308[/C][C]-2.69308[/C][/ROW]
[ROW][C]117[/C][C]0.5[/C][C]-1.25435[/C][C]1.75435[/C][/ROW]
[ROW][C]118[/C][C]7.5[/C][C]6.05174[/C][C]1.44826[/C][/ROW]
[ROW][C]119[/C][C]9[/C][C]6.93927[/C][C]2.06073[/C][/ROW]
[ROW][C]120[/C][C]9.5[/C][C]9.41421[/C][C]0.0857932[/C][/ROW]
[ROW][C]121[/C][C]8.5[/C][C]6.41222[/C][C]2.08778[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]8.73358[/C][C]-1.73358[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]5.45827[/C][C]2.54173[/C][/ROW]
[ROW][C]124[/C][C]10[/C][C]11.6552[/C][C]-1.65519[/C][/ROW]
[ROW][C]125[/C][C]7[/C][C]3.16084[/C][C]3.83916[/C][/ROW]
[ROW][C]126[/C][C]8.5[/C][C]8.66951[/C][C]-0.169508[/C][/ROW]
[ROW][C]127[/C][C]9[/C][C]3.90185[/C][C]5.09815[/C][/ROW]
[ROW][C]128[/C][C]9.5[/C][C]12.2197[/C][C]-2.7197[/C][/ROW]
[ROW][C]129[/C][C]4[/C][C]4.40541[/C][C]-0.405411[/C][/ROW]
[ROW][C]130[/C][C]6[/C][C]5.4712[/C][C]0.528796[/C][/ROW]
[ROW][C]131[/C][C]8[/C][C]9.47729[/C][C]-1.47729[/C][/ROW]
[ROW][C]132[/C][C]5.5[/C][C]5.19124[/C][C]0.308756[/C][/ROW]
[ROW][C]133[/C][C]9.5[/C][C]7.81625[/C][C]1.68375[/C][/ROW]
[ROW][C]134[/C][C]7.5[/C][C]6.52631[/C][C]0.973692[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]7.95418[/C][C]-0.954182[/C][/ROW]
[ROW][C]136[/C][C]7.5[/C][C]5.36563[/C][C]2.13437[/C][/ROW]
[ROW][C]137[/C][C]8[/C][C]8.18207[/C][C]-0.182067[/C][/ROW]
[ROW][C]138[/C][C]7[/C][C]5.15916[/C][C]1.84084[/C][/ROW]
[ROW][C]139[/C][C]7[/C][C]7.67868[/C][C]-0.678676[/C][/ROW]
[ROW][C]140[/C][C]6[/C][C]2.54297[/C][C]3.45703[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]12.8649[/C][C]-2.86492[/C][/ROW]
[ROW][C]142[/C][C]2.5[/C][C]2.67887[/C][C]-0.17887[/C][/ROW]
[ROW][C]143[/C][C]9[/C][C]9.20006[/C][C]-0.200062[/C][/ROW]
[ROW][C]144[/C][C]8[/C][C]7.36364[/C][C]0.636359[/C][/ROW]
[ROW][C]145[/C][C]6[/C][C]3.56854[/C][C]2.43146[/C][/ROW]
[ROW][C]146[/C][C]8.5[/C][C]9.6237[/C][C]-1.1237[/C][/ROW]
[ROW][C]147[/C][C]6[/C][C]5.66329[/C][C]0.336707[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]7.95854[/C][C]1.04146[/C][/ROW]
[ROW][C]149[/C][C]8[/C][C]7.05954[/C][C]0.940456[/C][/ROW]
[ROW][C]150[/C][C]8[/C][C]7.05762[/C][C]0.942381[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]9.73478[/C][C]-0.734781[/C][/ROW]
[ROW][C]152[/C][C]5.5[/C][C]6.55771[/C][C]-1.05771[/C][/ROW]
[ROW][C]153[/C][C]5[/C][C]4.47012[/C][C]0.529879[/C][/ROW]
[ROW][C]154[/C][C]7[/C][C]11.2239[/C][C]-4.22385[/C][/ROW]
[ROW][C]155[/C][C]5.5[/C][C]4.5618[/C][C]0.938198[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]14.6433[/C][C]-5.64327[/C][/ROW]
[ROW][C]157[/C][C]2[/C][C]0.303356[/C][C]1.69664[/C][/ROW]
[ROW][C]158[/C][C]8.5[/C][C]7.49802[/C][C]1.00198[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]8.7307[/C][C]0.269303[/C][/ROW]
[ROW][C]160[/C][C]8.5[/C][C]5.79663[/C][C]2.70337[/C][/ROW]
[ROW][C]161[/C][C]9[/C][C]8.43282[/C][C]0.567182[/C][/ROW]
[ROW][C]162[/C][C]7.5[/C][C]6.06604[/C][C]1.43396[/C][/ROW]
[ROW][C]163[/C][C]10[/C][C]7.63575[/C][C]2.36425[/C][/ROW]
[ROW][C]164[/C][C]9[/C][C]10.1716[/C][C]-1.17155[/C][/ROW]
[ROW][C]165[/C][C]7.5[/C][C]8.04444[/C][C]-0.544443[/C][/ROW]
[ROW][C]166[/C][C]6[/C][C]3.34375[/C][C]2.65625[/C][/ROW]
[ROW][C]167[/C][C]10.5[/C][C]10.8769[/C][C]-0.376932[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]8.08692[/C][C]0.41308[/C][/ROW]
[ROW][C]169[/C][C]8[/C][C]3.29347[/C][C]4.70653[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]7.85394[/C][C]2.14606[/C][/ROW]
[ROW][C]171[/C][C]10.5[/C][C]8.5757[/C][C]1.9243[/C][/ROW]
[ROW][C]172[/C][C]6.5[/C][C]6.69671[/C][C]-0.196705[/C][/ROW]
[ROW][C]173[/C][C]9.5[/C][C]6.95372[/C][C]2.54628[/C][/ROW]
[ROW][C]174[/C][C]8.5[/C][C]9.18362[/C][C]-0.683615[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]9.47874[/C][C]-1.97874[/C][/ROW]
[ROW][C]176[/C][C]5[/C][C]5.71259[/C][C]-0.712591[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]5.24684[/C][C]2.75316[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]10.2074[/C][C]-0.207389[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]6.22744[/C][C]0.772563[/C][/ROW]
[ROW][C]180[/C][C]7.5[/C][C]6.72744[/C][C]0.772563[/C][/ROW]
[ROW][C]181[/C][C]7.5[/C][C]5.47867[/C][C]2.02133[/C][/ROW]
[ROW][C]182[/C][C]9.5[/C][C]9.98228[/C][C]-0.482278[/C][/ROW]
[ROW][C]183[/C][C]6[/C][C]4.27766[/C][C]1.72234[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]10.5578[/C][C]-0.557835[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]8.60015[/C][C]-1.60015[/C][/ROW]
[ROW][C]186[/C][C]3[/C][C]4.28627[/C][C]-1.28627[/C][/ROW]
[ROW][C]187[/C][C]6[/C][C]6.76707[/C][C]-0.767066[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]5.43836[/C][C]1.56164[/C][/ROW]
[ROW][C]189[/C][C]10[/C][C]10.96[/C][C]-0.960004[/C][/ROW]
[ROW][C]190[/C][C]7[/C][C]11.4024[/C][C]-4.40238[/C][/ROW]
[ROW][C]191[/C][C]3.5[/C][C]3.04486[/C][C]0.455144[/C][/ROW]
[ROW][C]192[/C][C]8[/C][C]4.74047[/C][C]3.25953[/C][/ROW]
[ROW][C]193[/C][C]10[/C][C]11.6127[/C][C]-1.61273[/C][/ROW]
[ROW][C]194[/C][C]5.5[/C][C]4.96546[/C][C]0.534542[/C][/ROW]
[ROW][C]195[/C][C]6[/C][C]5.45073[/C][C]0.549273[/C][/ROW]
[ROW][C]196[/C][C]6.5[/C][C]4.83529[/C][C]1.66471[/C][/ROW]
[ROW][C]197[/C][C]6.5[/C][C]5.75829[/C][C]0.741706[/C][/ROW]
[ROW][C]198[/C][C]8.5[/C][C]10.2784[/C][C]-1.77836[/C][/ROW]
[ROW][C]199[/C][C]4[/C][C]2.62936[/C][C]1.37064[/C][/ROW]
[ROW][C]200[/C][C]9.5[/C][C]7.54858[/C][C]1.95142[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]6.58289[/C][C]1.41711[/C][/ROW]
[ROW][C]202[/C][C]8.5[/C][C]11.6739[/C][C]-3.17387[/C][/ROW]
[ROW][C]203[/C][C]5.5[/C][C]5.87838[/C][C]-0.378379[/C][/ROW]
[ROW][C]204[/C][C]7[/C][C]4.28885[/C][C]2.71115[/C][/ROW]
[ROW][C]205[/C][C]9[/C][C]8.29964[/C][C]0.700356[/C][/ROW]
[ROW][C]206[/C][C]8[/C][C]5.76302[/C][C]2.23698[/C][/ROW]
[ROW][C]207[/C][C]10[/C][C]8.11379[/C][C]1.88621[/C][/ROW]
[ROW][C]208[/C][C]8[/C][C]8.81658[/C][C]-0.816579[/C][/ROW]
[ROW][C]209[/C][C]6[/C][C]6.30883[/C][C]-0.30883[/C][/ROW]
[ROW][C]210[/C][C]8[/C][C]10.0678[/C][C]-2.06779[/C][/ROW]
[ROW][C]211[/C][C]5[/C][C]1.54199[/C][C]3.45801[/C][/ROW]
[ROW][C]212[/C][C]9[/C][C]9.84491[/C][C]-0.844913[/C][/ROW]
[ROW][C]213[/C][C]4.5[/C][C]0.412306[/C][C]4.08769[/C][/ROW]
[ROW][C]214[/C][C]8.5[/C][C]6.76806[/C][C]1.73194[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]7.77904[/C][C]-0.779041[/C][/ROW]
[ROW][C]216[/C][C]9.5[/C][C]9.1334[/C][C]0.366598[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]5.34983[/C][C]3.15017[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]7.16189[/C][C]0.338112[/C][/ROW]
[ROW][C]219[/C][C]7.5[/C][C]9.77787[/C][C]-2.27787[/C][/ROW]
[ROW][C]220[/C][C]5[/C][C]5.91671[/C][C]-0.91671[/C][/ROW]
[ROW][C]221[/C][C]7[/C][C]7.33336[/C][C]-0.333357[/C][/ROW]
[ROW][C]222[/C][C]8[/C][C]9.14321[/C][C]-1.14321[/C][/ROW]
[ROW][C]223[/C][C]5.5[/C][C]4.08122[/C][C]1.41878[/C][/ROW]
[ROW][C]224[/C][C]8.5[/C][C]7.37746[/C][C]1.12254[/C][/ROW]
[ROW][C]225[/C][C]7.5[/C][C]5.70774[/C][C]1.79226[/C][/ROW]
[ROW][C]226[/C][C]9.5[/C][C]7.81137[/C][C]1.68863[/C][/ROW]
[ROW][C]227[/C][C]7[/C][C]7.68904[/C][C]-0.689036[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]7.72228[/C][C]0.277719[/C][/ROW]
[ROW][C]229[/C][C]8.5[/C][C]10.9305[/C][C]-2.43047[/C][/ROW]
[ROW][C]230[/C][C]3.5[/C][C]2.82148[/C][C]0.678517[/C][/ROW]
[ROW][C]231[/C][C]6.5[/C][C]6.6911[/C][C]-0.191101[/C][/ROW]
[ROW][C]232[/C][C]6.5[/C][C]3.65411[/C][C]2.84589[/C][/ROW]
[ROW][C]233[/C][C]10.5[/C][C]8.43873[/C][C]2.06127[/C][/ROW]
[ROW][C]234[/C][C]8.5[/C][C]7.92377[/C][C]0.576226[/C][/ROW]
[ROW][C]235[/C][C]8[/C][C]4.14314[/C][C]3.85686[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]7.74998[/C][C]2.25002[/C][/ROW]
[ROW][C]237[/C][C]10[/C][C]8.99626[/C][C]1.00374[/C][/ROW]
[ROW][C]238[/C][C]9.5[/C][C]7.73427[/C][C]1.76573[/C][/ROW]
[ROW][C]239[/C][C]9[/C][C]8.04124[/C][C]0.958765[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]8.20875[/C][C]1.79125[/C][/ROW]
[ROW][C]241[/C][C]7.5[/C][C]9.48972[/C][C]-1.98972[/C][/ROW]
[ROW][C]242[/C][C]4.5[/C][C]4.96775[/C][C]-0.467746[/C][/ROW]
[ROW][C]243[/C][C]4.5[/C][C]8.3031[/C][C]-3.8031[/C][/ROW]
[ROW][C]244[/C][C]0.5[/C][C]-0.897106[/C][C]1.39711[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]9.75984[/C][C]-3.25984[/C][/ROW]
[ROW][C]246[/C][C]4.5[/C][C]4.86758[/C][C]-0.367579[/C][/ROW]
[ROW][C]247[/C][C]5.5[/C][C]6.84379[/C][C]-1.34379[/C][/ROW]
[ROW][C]248[/C][C]5[/C][C]6.1628[/C][C]-1.1628[/C][/ROW]
[ROW][C]249[/C][C]6[/C][C]9.69691[/C][C]-3.69691[/C][/ROW]
[ROW][C]250[/C][C]4[/C][C]2.62985[/C][C]1.37015[/C][/ROW]
[ROW][C]251[/C][C]8[/C][C]5.85394[/C][C]2.14606[/C][/ROW]
[ROW][C]252[/C][C]10.5[/C][C]8.98941[/C][C]1.51059[/C][/ROW]
[ROW][C]253[/C][C]8.5[/C][C]7.50931[/C][C]0.990692[/C][/ROW]
[ROW][C]254[/C][C]6.5[/C][C]6.21255[/C][C]0.287455[/C][/ROW]
[ROW][C]255[/C][C]8[/C][C]7.80396[/C][C]0.196045[/C][/ROW]
[ROW][C]256[/C][C]8.5[/C][C]9.96574[/C][C]-1.46574[/C][/ROW]
[ROW][C]257[/C][C]5.5[/C][C]6.86406[/C][C]-1.36406[/C][/ROW]
[ROW][C]258[/C][C]7[/C][C]8.57374[/C][C]-1.57374[/C][/ROW]
[ROW][C]259[/C][C]5[/C][C]7.50552[/C][C]-2.50552[/C][/ROW]
[ROW][C]260[/C][C]3.5[/C][C]4.79004[/C][C]-1.29004[/C][/ROW]
[ROW][C]261[/C][C]5[/C][C]3.03585[/C][C]1.96415[/C][/ROW]
[ROW][C]262[/C][C]9[/C][C]7.58945[/C][C]1.41055[/C][/ROW]
[ROW][C]263[/C][C]8.5[/C][C]10.1951[/C][C]-1.69508[/C][/ROW]
[ROW][C]264[/C][C]5[/C][C]3.80392[/C][C]1.19608[/C][/ROW]
[ROW][C]265[/C][C]9.5[/C][C]11.6306[/C][C]-2.13057[/C][/ROW]
[ROW][C]266[/C][C]3[/C][C]7.93695[/C][C]-4.93695[/C][/ROW]
[ROW][C]267[/C][C]1.5[/C][C]1.23118[/C][C]0.268819[/C][/ROW]
[ROW][C]268[/C][C]6[/C][C]11.8875[/C][C]-5.88752[/C][/ROW]
[ROW][C]269[/C][C]0.5[/C][C]-1.4243[/C][C]1.9243[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]4.69174[/C][C]1.80826[/C][/ROW]
[ROW][C]271[/C][C]7.5[/C][C]8.32437[/C][C]-0.824367[/C][/ROW]
[ROW][C]272[/C][C]4.5[/C][C]3.12985[/C][C]1.37015[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]7.59149[/C][C]0.408506[/C][/ROW]
[ROW][C]274[/C][C]9[/C][C]8.52358[/C][C]0.476418[/C][/ROW]
[ROW][C]275[/C][C]7.5[/C][C]5.74396[/C][C]1.75604[/C][/ROW]
[ROW][C]276[/C][C]8.5[/C][C]8.79274[/C][C]-0.29274[/C][/ROW]
[ROW][C]277[/C][C]7[/C][C]4.23591[/C][C]2.76409[/C][/ROW]
[ROW][C]278[/C][C]9.5[/C][C]7.50413[/C][C]1.99587[/C][/ROW]
[ROW][C]279[/C][C]6.5[/C][C]2.96782[/C][C]3.53218[/C][/ROW]
[ROW][C]280[/C][C]9.5[/C][C]9.01821[/C][C]0.481788[/C][/ROW]
[ROW][C]281[/C][C]6[/C][C]5.04682[/C][C]0.953179[/C][/ROW]
[ROW][C]282[/C][C]8[/C][C]6.85089[/C][C]1.14911[/C][/ROW]
[ROW][C]283[/C][C]9.5[/C][C]9.1655[/C][C]0.3345[/C][/ROW]
[ROW][C]284[/C][C]8[/C][C]6.03739[/C][C]1.96261[/C][/ROW]
[ROW][C]285[/C][C]8[/C][C]6.6284[/C][C]1.3716[/C][/ROW]
[ROW][C]286[/C][C]9[/C][C]7.89608[/C][C]1.10392[/C][/ROW]
[ROW][C]287[/C][C]5[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=252898&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=252898&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	3.76333	3.73667
2	2.5	3.7224	-1.2224
3	6	4.5362	1.4638
4	6.5	4.72894	1.77106
5	1	4.63409	-3.63409
6	1	3.90639	-2.90639
7	5.5	5.38188	0.118122
8	8.5	4.85517	3.64483
9	6.5	5.47705	1.02295
10	4.5	4.29969	0.200314
11	2	5.05369	-3.05369
12	5	4.99272	0.00728008
13	0.5	4.89881	-4.39881
14	5	3.94067	1.05933
15	5	5.01874	-0.0187353
16	2.5	1.83586	0.664144
17	5	5.83386	-0.833856
18	5.5	4.98628	0.513716
19	3.5	4.2969	-0.796903
20	3	5.84651	-2.84651
21	4	4.70953	-0.709525
22	0.5	4.09641	-3.59641
23	6.5	4.72783	1.77217
24	4.5	4.16347	0.336531
25	7.5	4.46723	3.03277
26	5.5	4.53468	0.965316
27	4	5.40051	-1.40051
28	7.5	7.04415	0.455846
29	7	6.10087	0.899133
30	4	4.0281	-0.0280962
31	5.5	4.61424	0.885756
32	2.5	4.79157	-2.29157
33	5.5	5.0847	0.415298
34	0.5	4.13464	-3.63464
35	3.5	4.00286	-0.502859
36	2.5	5.525	-3.025
37	4.5	5.34181	-0.841815
38	4.5	4.66593	-0.165933
39	4.5	4.42635	0.0736542
40	6	5.92789	0.0721069
41	2.5	4.41869	-1.91869
42	5	5.97019	-0.970188
43	0	4.37365	-4.37365
44	5	5.18531	-0.185307
45	6.5	4.49543	2.00457
46	5	4.31014	0.689857
47	6	6.00422	-0.00421588
48	4.5	5.03924	-0.53924
49	5.5	5.32306	0.176941
50	1	5.94238	-4.94238
51	7.5	3.71837	3.78163
52	6	5.58777	0.412231
53	5	6.18093	-1.18093
54	1	6.0343	-5.0343
55	5	4.91131	0.088689
56	6.5	4.67048	1.82952
57	7	5.26742	1.73258
58	4.5	4.92322	-0.423218
59	0	5.04461	-5.04461
60	8.5	4.10451	4.39549
61	3.5	3.94363	-0.443628
62	7.5	5.34298	2.15702
63	3.5	3.9867	-0.486704
64	6	4.45183	1.54817
65	1.5	4.98551	-3.48551
66	9	5.36138	3.63862
67	3.5	3.23611	0.26389
68	3.5	5.13395	-1.63395
69	4	5.459	-1.459
70	6.5	4.88713	1.61287
71	7.5	4.76944	2.73056
72	6	5.22797	0.772026
73	5	5.23714	-0.237138
74	5.5	4.25739	1.24261
75	3.5	5.03129	-1.53129
76	7.5	6.21302	1.28698
77	1	4.46428	-3.46428
78	6.5	4.86523	1.63477
79	NA	NA	1.21834
80	6.5	5.12913	1.37087
81	6.5	5.06676	1.43324
82	7	9.77498	-2.77498
83	3.5	6.84933	-3.34933
84	1.5	3.06491	-1.56491
85	4	1.61288	2.38712
86	7.5	9.10449	-1.60449
87	4.5	8.54566	-4.04566
88	0	2.29357	-2.29357
89	3.5	3.78246	-0.282457
90	5.5	5.77362	-0.273624
91	5	6.69303	-1.69303
92	4.5	7.25287	-2.75287
93	2.5	-0.291504	2.7915
94	7.5	5.79291	1.70709
95	7	11.8639	-4.86389
96	0	0.284446	-0.284446
97	4.5	7.05098	-2.55098
98	3	7.51145	-4.51145
99	1.5	2.49477	-0.99477
100	3.5	5.94468	-2.44468
101	2.5	2.31967	0.180332
102	5.5	3.0259	2.4741
103	8	12.7633	-4.76334
104	1	1.37966	-0.379664
105	5	5.76976	-0.769763
106	4.5	6.19467	-1.69467
107	3	5.34516	-2.34516
108	3	1.1046	1.8954
109	8	10.3815	-2.38153
110	2.5	1.27136	1.22864
111	7	11.7062	-4.70617
112	0	4.24057	-4.24057
113	1	3.11247	-2.11247
114	3.5	3.18311	0.316885
115	5.5	4.74762	0.752384
116	5.5	8.19308	-2.69308
117	0.5	-1.25435	1.75435
118	7.5	6.05174	1.44826
119	9	6.93927	2.06073
120	9.5	9.41421	0.0857932
121	8.5	6.41222	2.08778
122	7	8.73358	-1.73358
123	8	5.45827	2.54173
124	10	11.6552	-1.65519
125	7	3.16084	3.83916
126	8.5	8.66951	-0.169508
127	9	3.90185	5.09815
128	9.5	12.2197	-2.7197
129	4	4.40541	-0.405411
130	6	5.4712	0.528796
131	8	9.47729	-1.47729
132	5.5	5.19124	0.308756
133	9.5	7.81625	1.68375
134	7.5	6.52631	0.973692
135	7	7.95418	-0.954182
136	7.5	5.36563	2.13437
137	8	8.18207	-0.182067
138	7	5.15916	1.84084
139	7	7.67868	-0.678676
140	6	2.54297	3.45703
141	10	12.8649	-2.86492
142	2.5	2.67887	-0.17887
143	9	9.20006	-0.200062
144	8	7.36364	0.636359
145	6	3.56854	2.43146
146	8.5	9.6237	-1.1237
147	6	5.66329	0.336707
148	9	7.95854	1.04146
149	8	7.05954	0.940456
150	8	7.05762	0.942381
151	9	9.73478	-0.734781
152	5.5	6.55771	-1.05771
153	5	4.47012	0.529879
154	7	11.2239	-4.22385
155	5.5	4.5618	0.938198
156	9	14.6433	-5.64327
157	2	0.303356	1.69664
158	8.5	7.49802	1.00198
159	9	8.7307	0.269303
160	8.5	5.79663	2.70337
161	9	8.43282	0.567182
162	7.5	6.06604	1.43396
163	10	7.63575	2.36425
164	9	10.1716	-1.17155
165	7.5	8.04444	-0.544443
166	6	3.34375	2.65625
167	10.5	10.8769	-0.376932
168	8.5	8.08692	0.41308
169	8	3.29347	4.70653
170	10	7.85394	2.14606
171	10.5	8.5757	1.9243
172	6.5	6.69671	-0.196705
173	9.5	6.95372	2.54628
174	8.5	9.18362	-0.683615
175	7.5	9.47874	-1.97874
176	5	5.71259	-0.712591
177	8	5.24684	2.75316
178	10	10.2074	-0.207389
179	7	6.22744	0.772563
180	7.5	6.72744	0.772563
181	7.5	5.47867	2.02133
182	9.5	9.98228	-0.482278
183	6	4.27766	1.72234
184	10	10.5578	-0.557835
185	7	8.60015	-1.60015
186	3	4.28627	-1.28627
187	6	6.76707	-0.767066
188	7	5.43836	1.56164
189	10	10.96	-0.960004
190	7	11.4024	-4.40238
191	3.5	3.04486	0.455144
192	8	4.74047	3.25953
193	10	11.6127	-1.61273
194	5.5	4.96546	0.534542
195	6	5.45073	0.549273
196	6.5	4.83529	1.66471
197	6.5	5.75829	0.741706
198	8.5	10.2784	-1.77836
199	4	2.62936	1.37064
200	9.5	7.54858	1.95142
201	8	6.58289	1.41711
202	8.5	11.6739	-3.17387
203	5.5	5.87838	-0.378379
204	7	4.28885	2.71115
205	9	8.29964	0.700356
206	8	5.76302	2.23698
207	10	8.11379	1.88621
208	8	8.81658	-0.816579
209	6	6.30883	-0.30883
210	8	10.0678	-2.06779
211	5	1.54199	3.45801
212	9	9.84491	-0.844913
213	4.5	0.412306	4.08769
214	8.5	6.76806	1.73194
215	7	7.77904	-0.779041
216	9.5	9.1334	0.366598
217	8.5	5.34983	3.15017
218	7.5	7.16189	0.338112
219	7.5	9.77787	-2.27787
220	5	5.91671	-0.91671
221	7	7.33336	-0.333357
222	8	9.14321	-1.14321
223	5.5	4.08122	1.41878
224	8.5	7.37746	1.12254
225	7.5	5.70774	1.79226
226	9.5	7.81137	1.68863
227	7	7.68904	-0.689036
228	8	7.72228	0.277719
229	8.5	10.9305	-2.43047
230	3.5	2.82148	0.678517
231	6.5	6.6911	-0.191101
232	6.5	3.65411	2.84589
233	10.5	8.43873	2.06127
234	8.5	7.92377	0.576226
235	8	4.14314	3.85686
236	10	7.74998	2.25002
237	10	8.99626	1.00374
238	9.5	7.73427	1.76573
239	9	8.04124	0.958765
240	10	8.20875	1.79125
241	7.5	9.48972	-1.98972
242	4.5	4.96775	-0.467746
243	4.5	8.3031	-3.8031
244	0.5	-0.897106	1.39711
245	6.5	9.75984	-3.25984
246	4.5	4.86758	-0.367579
247	5.5	6.84379	-1.34379
248	5	6.1628	-1.1628
249	6	9.69691	-3.69691
250	4	2.62985	1.37015
251	8	5.85394	2.14606
252	10.5	8.98941	1.51059
253	8.5	7.50931	0.990692
254	6.5	6.21255	0.287455
255	8	7.80396	0.196045
256	8.5	9.96574	-1.46574
257	5.5	6.86406	-1.36406
258	7	8.57374	-1.57374
259	5	7.50552	-2.50552
260	3.5	4.79004	-1.29004
261	5	3.03585	1.96415
262	9	7.58945	1.41055
263	8.5	10.1951	-1.69508
264	5	3.80392	1.19608
265	9.5	11.6306	-2.13057
266	3	7.93695	-4.93695
267	1.5	1.23118	0.268819
268	6	11.8875	-5.88752
269	0.5	-1.4243	1.9243
270	6.5	4.69174	1.80826
271	7.5	8.32437	-0.824367
272	4.5	3.12985	1.37015
273	8	7.59149	0.408506
274	9	8.52358	0.476418
275	7.5	5.74396	1.75604
276	8.5	8.79274	-0.29274
277	7	4.23591	2.76409
278	9.5	7.50413	1.99587
279	6.5	2.96782	3.53218
280	9.5	9.01821	0.481788
281	6	5.04682	0.953179
282	8	6.85089	1.14911
283	9.5	9.1655	0.3345
284	8	6.03739	1.96261
285	8	6.6284	1.3716
286	9	7.89608	1.10392
287	5	NA	NA

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
14	0.873224	0.253553	0.126776
15	0.897393	0.205214	0.102607
16	0.835106	0.329789	0.164894
17	0.749565	0.500871	0.250435
18	0.726614	0.546772	0.273386
19	0.677854	0.644293	0.322146
20	0.589668	0.820664	0.410332
21	0.635572	0.728856	0.364428
22	0.609626	0.780748	0.390374
23	0.598329	0.803342	0.401671
24	0.541581	0.916839	0.458419
25	0.665491	0.669017	0.334509
26	0.609338	0.781324	0.390662
27	0.539073	0.921853	0.460927
28	0.471246	0.942493	0.528754
29	0.418016	0.836031	0.581984
30	0.350906	0.701812	0.649094
31	0.29064	0.58128	0.70936
32	0.304994	0.609989	0.695006
33	0.27092	0.54184	0.72908
34	0.326192	0.652384	0.673808
35	0.288057	0.576115	0.711943
36	0.285103	0.570206	0.714897
37	0.246059	0.492118	0.753941
38	0.244943	0.489885	0.755057
39	0.203125	0.406249	0.796875
40	0.194356	0.388712	0.805644
41	0.212349	0.424697	0.787651
42	0.175118	0.350237	0.824882
43	0.295354	0.590708	0.704646
44	0.267542	0.535084	0.732458
45	0.254404	0.508807	0.745596
46	0.22846	0.45692	0.77154
47	0.198916	0.397831	0.801084
48	0.169404	0.338808	0.830596
49	0.141388	0.282776	0.858612
50	0.266157	0.532314	0.733843
51	0.320567	0.641135	0.679433
52	0.31048	0.620959	0.68952
53	0.27228	0.544559	0.72772
54	0.306777	0.613553	0.693223
55	0.270841	0.541681	0.729159
56	0.286935	0.57387	0.713065
57	0.374201	0.748401	0.625799
58	0.337654	0.675308	0.662346
59	0.486351	0.972701	0.513649
60	0.658956	0.682088	0.341044
61	0.630769	0.738461	0.369231
62	0.631689	0.736622	0.368311
63	0.595962	0.808076	0.404038
64	0.576439	0.847123	0.423561
65	0.668347	0.663306	0.331653
66	0.766818	0.466363	0.233182
67	0.74106	0.517881	0.25894
68	0.712322	0.575355	0.287678
69	0.696671	0.606659	0.303329
70	0.680761	0.638477	0.319239
71	0.687099	0.625802	0.312901
72	0.652786	0.694429	0.347214
73	0.626022	0.747956	0.373978
74	0.596003	0.807994	0.403997
75	0.561552	0.876896	0.438448
76	0.567878	0.864244	0.432122
77	0.61728	0.76544	0.38272
78	0.616422	0.767157	0.383578
79	0.599572	0.800856	0.400428
80	0.584536	0.830929	0.415464
81	0.56994	0.860121	0.43006
82	0.553712	0.892576	0.446288
83	0.58326	0.833481	0.41674
84	0.578414	0.843173	0.421586
85	0.609451	0.781097	0.390549
86	0.591446	0.817108	0.408554
87	0.598555	0.802891	0.401445
88	0.602283	0.795434	0.397717
89	0.569997	0.860006	0.430003
90	0.535027	0.929946	0.464973
91	0.514097	0.971807	0.485903
92	0.519302	0.961396	0.480698
93	0.553059	0.893882	0.446941
94	0.560368	0.879265	0.439632
95	0.671018	0.657963	0.328982
96	0.637257	0.725487	0.362743
97	0.632186	0.735628	0.367814
98	0.701232	0.597536	0.298768
99	0.679594	0.640812	0.320406
100	0.677433	0.645134	0.322567
101	0.654292	0.691416	0.345708
102	0.736334	0.527333	0.263666
103	0.838049	0.323902	0.161951
104	0.821281	0.357439	0.178719
105	0.802814	0.394373	0.197186
106	0.793522	0.412956	0.206478
107	0.815556	0.368888	0.184444
108	0.827127	0.345745	0.172873
109	0.84144	0.317119	0.15856
110	0.826737	0.346525	0.173263
111	0.893598	0.212803	0.106402
112	0.93057	0.13886	0.0694298
113	0.936195	0.12761	0.0638048
114	0.927852	0.144296	0.072148
115	0.921023	0.157954	0.0789768
116	0.929177	0.141646	0.0708229
117	0.925989	0.148022	0.0740108
118	0.943921	0.112159	0.0560795
119	0.95145	0.0970991	0.0485496
120	0.942787	0.114426	0.057213
121	0.942264	0.115473	0.0577363
122	0.938061	0.123879	0.0619394
123	0.935723	0.128553	0.0642765
124	0.933602	0.132796	0.0663982
125	0.972525	0.0549502	0.0274751
126	0.968288	0.0634233	0.0317117
127	0.986251	0.0274974	0.0137487
128	0.985514	0.0289724	0.0144862
129	0.982352	0.0352964	0.0176482
130	0.978626	0.0427484	0.0213742
131	0.976713	0.046574	0.023287
132	0.973139	0.0537216	0.0268608
133	0.972751	0.0544972	0.0272486
134	0.967646	0.0647077	0.0323539
135	0.961971	0.076057	0.0380285
136	0.963414	0.0731728	0.0365864
137	0.956076	0.0878484	0.0439242
138	0.955848	0.0883045	0.0441523
139	0.94746	0.105081	0.0525403
140	0.958936	0.0821276	0.0410638
141	0.969825	0.0603503	0.0301751
142	0.964681	0.070639	0.0353195
143	0.957364	0.0852717	0.0426358
144	0.950254	0.0994921	0.049746
145	0.946845	0.10631	0.0531548
146	0.946922	0.106157	0.0530784
147	0.940635	0.118729	0.0593645
148	0.933984	0.132031	0.0660156
149	0.923503	0.152993	0.0764966
150	0.913864	0.172273	0.0861363
151	0.906323	0.187353	0.0936765
152	0.895802	0.208396	0.104198
153	0.879851	0.240298	0.120149
154	0.905159	0.189683	0.0948415
155	0.892759	0.214483	0.107241
156	0.961591	0.0768178	0.0384089
157	0.959109	0.0817812	0.0408906
158	0.953274	0.0934522	0.0467261
159	0.944483	0.111034	0.0555169
160	0.958434	0.0831316	0.0415658
161	0.95182	0.0963595	0.0481797
162	0.949214	0.101572	0.0507862
163	0.956608	0.0867839	0.0433919
164	0.951442	0.0971167	0.0485584
165	0.94777	0.104459	0.0522297
166	0.952587	0.0948262	0.0474131
167	0.943409	0.113182	0.0565909
168	0.932574	0.134852	0.0674259
169	0.983758	0.0324835	0.0162418
170	0.982054	0.035893	0.0179465
171	0.983654	0.0326911	0.0163456
172	0.979889	0.0402221	0.020111
173	0.98242	0.0351604	0.0175802
174	0.978539	0.0429217	0.0214609
175	0.98093	0.0381391	0.0190695
176	0.976247	0.047506	0.023753
177	0.976609	0.0467822	0.0233911
178	0.972936	0.0541289	0.0270645
179	0.966698	0.0666035	0.0333018
180	0.959308	0.0813845	0.0406922
181	0.956414	0.0871713	0.0435857
182	0.9477	0.104601	0.0523003
183	0.944835	0.110331	0.0551653
184	0.939286	0.121427	0.0607137
185	0.93088	0.138239	0.0691197
186	0.931963	0.136074	0.068037
187	0.928786	0.142427	0.0712137
188	0.92835	0.143301	0.0716504
189	0.920885	0.158229	0.0791145
190	0.975397	0.0492068	0.0246034
191	0.969961	0.0600772	0.0300386
192	0.974928	0.0501439	0.025072
193	0.978113	0.0437736	0.0218868
194	0.974893	0.0502146	0.0251073
195	0.968953	0.0620943	0.0310472
196	0.966339	0.0673225	0.0336613
197	0.960544	0.0789126	0.0394563
198	0.963585	0.0728294	0.0364147
199	0.957228	0.0855445	0.0427723
200	0.952879	0.0942428	0.0471214
201	0.951697	0.096605	0.0483025
202	0.959118	0.0817648	0.0408824
203	0.955689	0.0886219	0.0443109
204	0.957864	0.0842728	0.0421364
205	0.948622	0.102755	0.0513776
206	0.940635	0.11873	0.0593648
207	0.939341	0.121318	0.0606591
208	0.929636	0.140728	0.0703641
209	0.917315	0.16537	0.0826851
210	0.90743	0.18514	0.09257
211	0.935184	0.129632	0.0648161
212	0.926042	0.147917	0.0739585
213	0.948794	0.102412	0.0512059
214	0.939607	0.120786	0.0603929
215	0.932021	0.135958	0.0679789
216	0.917028	0.165944	0.0829718
217	0.927786	0.144428	0.072214
218	0.912153	0.175693	0.0878467
219	0.90257	0.194859	0.0974295
220	0.88913	0.221741	0.11087
221	0.868054	0.263892	0.131946
222	0.844634	0.310732	0.155366
223	0.829623	0.340754	0.170377
224	0.804471	0.391058	0.195529
225	0.782021	0.435958	0.217979
226	0.762691	0.474618	0.237309
227	0.751738	0.496524	0.248262
228	0.730005	0.539991	0.269995
229	0.775377	0.449246	0.224623
230	0.745659	0.508682	0.254341
231	0.715621	0.568758	0.284379
232	0.735693	0.528613	0.264307
233	0.723816	0.552368	0.276184
234	0.700801	0.598398	0.299199
235	0.77757	0.44486	0.22243
236	0.815178	0.369644	0.184822
237	0.798757	0.402486	0.201243
238	0.812443	0.375114	0.187557
239	0.795149	0.409702	0.204851
240	0.769463	0.461073	0.230537
241	0.749551	0.500899	0.250449
242	0.705107	0.589786	0.294893
243	0.74329	0.513419	0.25671
244	0.707552	0.584896	0.292448
245	0.684767	0.630465	0.315233
246	0.668594	0.662812	0.331406
247	0.627726	0.744547	0.372274
248	0.573777	0.852446	0.426223
249	0.677991	0.644018	0.322009
250	0.635778	0.728443	0.364222
251	0.619112	0.761775	0.380888
252	0.747463	0.505074	0.252537
253	0.695337	0.609327	0.304663
254	0.63895	0.7221	0.36105
255	0.58186	0.836279	0.41814
256	0.552694	0.894613	0.447306
257	0.504676	0.990649	0.495324
258	0.451553	0.903106	0.548447
259	0.38741	0.774819	0.61259
260	0.343897	0.687794	0.656103
261	0.28105	0.562099	0.71895
262	0.226455	0.45291	0.773545
263	0.174168	0.348335	0.825832
264	0.14758	0.295159	0.85242
265	0.1835	0.367001	0.8165
266	0.489934	0.979867	0.510066
267	0.577783	0.844434	0.422217
268	0.964605	0.0707899	0.0353949
269	0.996575	0.00685041	0.0034252
270	0.990407	0.0191867	0.00959334
271	0.990887	0.0182268	0.00911338
272	0.970029	0.0599423	0.0299711
273	0.884857	0.230285	0.115143

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
14 & 0.873224 & 0.253553 & 0.126776 \tabularnewline
15 & 0.897393 & 0.205214 & 0.102607 \tabularnewline
16 & 0.835106 & 0.329789 & 0.164894 \tabularnewline
17 & 0.749565 & 0.500871 & 0.250435 \tabularnewline
18 & 0.726614 & 0.546772 & 0.273386 \tabularnewline
19 & 0.677854 & 0.644293 & 0.322146 \tabularnewline
20 & 0.589668 & 0.820664 & 0.410332 \tabularnewline
21 & 0.635572 & 0.728856 & 0.364428 \tabularnewline
22 & 0.609626 & 0.780748 & 0.390374 \tabularnewline
23 & 0.598329 & 0.803342 & 0.401671 \tabularnewline
24 & 0.541581 & 0.916839 & 0.458419 \tabularnewline
25 & 0.665491 & 0.669017 & 0.334509 \tabularnewline
26 & 0.609338 & 0.781324 & 0.390662 \tabularnewline
27 & 0.539073 & 0.921853 & 0.460927 \tabularnewline
28 & 0.471246 & 0.942493 & 0.528754 \tabularnewline
29 & 0.418016 & 0.836031 & 0.581984 \tabularnewline
30 & 0.350906 & 0.701812 & 0.649094 \tabularnewline
31 & 0.29064 & 0.58128 & 0.70936 \tabularnewline
32 & 0.304994 & 0.609989 & 0.695006 \tabularnewline
33 & 0.27092 & 0.54184 & 0.72908 \tabularnewline
34 & 0.326192 & 0.652384 & 0.673808 \tabularnewline
35 & 0.288057 & 0.576115 & 0.711943 \tabularnewline
36 & 0.285103 & 0.570206 & 0.714897 \tabularnewline
37 & 0.246059 & 0.492118 & 0.753941 \tabularnewline
38 & 0.244943 & 0.489885 & 0.755057 \tabularnewline
39 & 0.203125 & 0.406249 & 0.796875 \tabularnewline
40 & 0.194356 & 0.388712 & 0.805644 \tabularnewline
41 & 0.212349 & 0.424697 & 0.787651 \tabularnewline
42 & 0.175118 & 0.350237 & 0.824882 \tabularnewline
43 & 0.295354 & 0.590708 & 0.704646 \tabularnewline
44 & 0.267542 & 0.535084 & 0.732458 \tabularnewline
45 & 0.254404 & 0.508807 & 0.745596 \tabularnewline
46 & 0.22846 & 0.45692 & 0.77154 \tabularnewline
47 & 0.198916 & 0.397831 & 0.801084 \tabularnewline
48 & 0.169404 & 0.338808 & 0.830596 \tabularnewline
49 & 0.141388 & 0.282776 & 0.858612 \tabularnewline
50 & 0.266157 & 0.532314 & 0.733843 \tabularnewline
51 & 0.320567 & 0.641135 & 0.679433 \tabularnewline
52 & 0.31048 & 0.620959 & 0.68952 \tabularnewline
53 & 0.27228 & 0.544559 & 0.72772 \tabularnewline
54 & 0.306777 & 0.613553 & 0.693223 \tabularnewline
55 & 0.270841 & 0.541681 & 0.729159 \tabularnewline
56 & 0.286935 & 0.57387 & 0.713065 \tabularnewline
57 & 0.374201 & 0.748401 & 0.625799 \tabularnewline
58 & 0.337654 & 0.675308 & 0.662346 \tabularnewline
59 & 0.486351 & 0.972701 & 0.513649 \tabularnewline
60 & 0.658956 & 0.682088 & 0.341044 \tabularnewline
61 & 0.630769 & 0.738461 & 0.369231 \tabularnewline
62 & 0.631689 & 0.736622 & 0.368311 \tabularnewline
63 & 0.595962 & 0.808076 & 0.404038 \tabularnewline
64 & 0.576439 & 0.847123 & 0.423561 \tabularnewline
65 & 0.668347 & 0.663306 & 0.331653 \tabularnewline
66 & 0.766818 & 0.466363 & 0.233182 \tabularnewline
67 & 0.74106 & 0.517881 & 0.25894 \tabularnewline
68 & 0.712322 & 0.575355 & 0.287678 \tabularnewline
69 & 0.696671 & 0.606659 & 0.303329 \tabularnewline
70 & 0.680761 & 0.638477 & 0.319239 \tabularnewline
71 & 0.687099 & 0.625802 & 0.312901 \tabularnewline
72 & 0.652786 & 0.694429 & 0.347214 \tabularnewline
73 & 0.626022 & 0.747956 & 0.373978 \tabularnewline
74 & 0.596003 & 0.807994 & 0.403997 \tabularnewline
75 & 0.561552 & 0.876896 & 0.438448 \tabularnewline
76 & 0.567878 & 0.864244 & 0.432122 \tabularnewline
77 & 0.61728 & 0.76544 & 0.38272 \tabularnewline
78 & 0.616422 & 0.767157 & 0.383578 \tabularnewline
79 & 0.599572 & 0.800856 & 0.400428 \tabularnewline
80 & 0.584536 & 0.830929 & 0.415464 \tabularnewline
81 & 0.56994 & 0.860121 & 0.43006 \tabularnewline
82 & 0.553712 & 0.892576 & 0.446288 \tabularnewline
83 & 0.58326 & 0.833481 & 0.41674 \tabularnewline
84 & 0.578414 & 0.843173 & 0.421586 \tabularnewline
85 & 0.609451 & 0.781097 & 0.390549 \tabularnewline
86 & 0.591446 & 0.817108 & 0.408554 \tabularnewline
87 & 0.598555 & 0.802891 & 0.401445 \tabularnewline
88 & 0.602283 & 0.795434 & 0.397717 \tabularnewline
89 & 0.569997 & 0.860006 & 0.430003 \tabularnewline
90 & 0.535027 & 0.929946 & 0.464973 \tabularnewline
91 & 0.514097 & 0.971807 & 0.485903 \tabularnewline
92 & 0.519302 & 0.961396 & 0.480698 \tabularnewline
93 & 0.553059 & 0.893882 & 0.446941 \tabularnewline
94 & 0.560368 & 0.879265 & 0.439632 \tabularnewline
95 & 0.671018 & 0.657963 & 0.328982 \tabularnewline
96 & 0.637257 & 0.725487 & 0.362743 \tabularnewline
97 & 0.632186 & 0.735628 & 0.367814 \tabularnewline
98 & 0.701232 & 0.597536 & 0.298768 \tabularnewline
99 & 0.679594 & 0.640812 & 0.320406 \tabularnewline
100 & 0.677433 & 0.645134 & 0.322567 \tabularnewline
101 & 0.654292 & 0.691416 & 0.345708 \tabularnewline
102 & 0.736334 & 0.527333 & 0.263666 \tabularnewline
103 & 0.838049 & 0.323902 & 0.161951 \tabularnewline
104 & 0.821281 & 0.357439 & 0.178719 \tabularnewline
105 & 0.802814 & 0.394373 & 0.197186 \tabularnewline
106 & 0.793522 & 0.412956 & 0.206478 \tabularnewline
107 & 0.815556 & 0.368888 & 0.184444 \tabularnewline
108 & 0.827127 & 0.345745 & 0.172873 \tabularnewline
109 & 0.84144 & 0.317119 & 0.15856 \tabularnewline
110 & 0.826737 & 0.346525 & 0.173263 \tabularnewline
111 & 0.893598 & 0.212803 & 0.106402 \tabularnewline
112 & 0.93057 & 0.13886 & 0.0694298 \tabularnewline
113 & 0.936195 & 0.12761 & 0.0638048 \tabularnewline
114 & 0.927852 & 0.144296 & 0.072148 \tabularnewline
115 & 0.921023 & 0.157954 & 0.0789768 \tabularnewline
116 & 0.929177 & 0.141646 & 0.0708229 \tabularnewline
117 & 0.925989 & 0.148022 & 0.0740108 \tabularnewline
118 & 0.943921 & 0.112159 & 0.0560795 \tabularnewline
119 & 0.95145 & 0.0970991 & 0.0485496 \tabularnewline
120 & 0.942787 & 0.114426 & 0.057213 \tabularnewline
121 & 0.942264 & 0.115473 & 0.0577363 \tabularnewline
122 & 0.938061 & 0.123879 & 0.0619394 \tabularnewline
123 & 0.935723 & 0.128553 & 0.0642765 \tabularnewline
124 & 0.933602 & 0.132796 & 0.0663982 \tabularnewline
125 & 0.972525 & 0.0549502 & 0.0274751 \tabularnewline
126 & 0.968288 & 0.0634233 & 0.0317117 \tabularnewline
127 & 0.986251 & 0.0274974 & 0.0137487 \tabularnewline
128 & 0.985514 & 0.0289724 & 0.0144862 \tabularnewline
129 & 0.982352 & 0.0352964 & 0.0176482 \tabularnewline
130 & 0.978626 & 0.0427484 & 0.0213742 \tabularnewline
131 & 0.976713 & 0.046574 & 0.023287 \tabularnewline
132 & 0.973139 & 0.0537216 & 0.0268608 \tabularnewline
133 & 0.972751 & 0.0544972 & 0.0272486 \tabularnewline
134 & 0.967646 & 0.0647077 & 0.0323539 \tabularnewline
135 & 0.961971 & 0.076057 & 0.0380285 \tabularnewline
136 & 0.963414 & 0.0731728 & 0.0365864 \tabularnewline
137 & 0.956076 & 0.0878484 & 0.0439242 \tabularnewline
138 & 0.955848 & 0.0883045 & 0.0441523 \tabularnewline
139 & 0.94746 & 0.105081 & 0.0525403 \tabularnewline
140 & 0.958936 & 0.0821276 & 0.0410638 \tabularnewline
141 & 0.969825 & 0.0603503 & 0.0301751 \tabularnewline
142 & 0.964681 & 0.070639 & 0.0353195 \tabularnewline
143 & 0.957364 & 0.0852717 & 0.0426358 \tabularnewline
144 & 0.950254 & 0.0994921 & 0.049746 \tabularnewline
145 & 0.946845 & 0.10631 & 0.0531548 \tabularnewline
146 & 0.946922 & 0.106157 & 0.0530784 \tabularnewline
147 & 0.940635 & 0.118729 & 0.0593645 \tabularnewline
148 & 0.933984 & 0.132031 & 0.0660156 \tabularnewline
149 & 0.923503 & 0.152993 & 0.0764966 \tabularnewline
150 & 0.913864 & 0.172273 & 0.0861363 \tabularnewline
151 & 0.906323 & 0.187353 & 0.0936765 \tabularnewline
152 & 0.895802 & 0.208396 & 0.104198 \tabularnewline
153 & 0.879851 & 0.240298 & 0.120149 \tabularnewline
154 & 0.905159 & 0.189683 & 0.0948415 \tabularnewline
155 & 0.892759 & 0.214483 & 0.107241 \tabularnewline
156 & 0.961591 & 0.0768178 & 0.0384089 \tabularnewline
157 & 0.959109 & 0.0817812 & 0.0408906 \tabularnewline
158 & 0.953274 & 0.0934522 & 0.0467261 \tabularnewline
159 & 0.944483 & 0.111034 & 0.0555169 \tabularnewline
160 & 0.958434 & 0.0831316 & 0.0415658 \tabularnewline
161 & 0.95182 & 0.0963595 & 0.0481797 \tabularnewline
162 & 0.949214 & 0.101572 & 0.0507862 \tabularnewline
163 & 0.956608 & 0.0867839 & 0.0433919 \tabularnewline
164 & 0.951442 & 0.0971167 & 0.0485584 \tabularnewline
165 & 0.94777 & 0.104459 & 0.0522297 \tabularnewline
166 & 0.952587 & 0.0948262 & 0.0474131 \tabularnewline
167 & 0.943409 & 0.113182 & 0.0565909 \tabularnewline
168 & 0.932574 & 0.134852 & 0.0674259 \tabularnewline
169 & 0.983758 & 0.0324835 & 0.0162418 \tabularnewline
170 & 0.982054 & 0.035893 & 0.0179465 \tabularnewline
171 & 0.983654 & 0.0326911 & 0.0163456 \tabularnewline
172 & 0.979889 & 0.0402221 & 0.020111 \tabularnewline
173 & 0.98242 & 0.0351604 & 0.0175802 \tabularnewline
174 & 0.978539 & 0.0429217 & 0.0214609 \tabularnewline
175 & 0.98093 & 0.0381391 & 0.0190695 \tabularnewline
176 & 0.976247 & 0.047506 & 0.023753 \tabularnewline
177 & 0.976609 & 0.0467822 & 0.0233911 \tabularnewline
178 & 0.972936 & 0.0541289 & 0.0270645 \tabularnewline
179 & 0.966698 & 0.0666035 & 0.0333018 \tabularnewline
180 & 0.959308 & 0.0813845 & 0.0406922 \tabularnewline
181 & 0.956414 & 0.0871713 & 0.0435857 \tabularnewline
182 & 0.9477 & 0.104601 & 0.0523003 \tabularnewline
183 & 0.944835 & 0.110331 & 0.0551653 \tabularnewline
184 & 0.939286 & 0.121427 & 0.0607137 \tabularnewline
185 & 0.93088 & 0.138239 & 0.0691197 \tabularnewline
186 & 0.931963 & 0.136074 & 0.068037 \tabularnewline
187 & 0.928786 & 0.142427 & 0.0712137 \tabularnewline
188 & 0.92835 & 0.143301 & 0.0716504 \tabularnewline
189 & 0.920885 & 0.158229 & 0.0791145 \tabularnewline
190 & 0.975397 & 0.0492068 & 0.0246034 \tabularnewline
191 & 0.969961 & 0.0600772 & 0.0300386 \tabularnewline
192 & 0.974928 & 0.0501439 & 0.025072 \tabularnewline
193 & 0.978113 & 0.0437736 & 0.0218868 \tabularnewline
194 & 0.974893 & 0.0502146 & 0.0251073 \tabularnewline
195 & 0.968953 & 0.0620943 & 0.0310472 \tabularnewline
196 & 0.966339 & 0.0673225 & 0.0336613 \tabularnewline
197 & 0.960544 & 0.0789126 & 0.0394563 \tabularnewline
198 & 0.963585 & 0.0728294 & 0.0364147 \tabularnewline
199 & 0.957228 & 0.0855445 & 0.0427723 \tabularnewline
200 & 0.952879 & 0.0942428 & 0.0471214 \tabularnewline
201 & 0.951697 & 0.096605 & 0.0483025 \tabularnewline
202 & 0.959118 & 0.0817648 & 0.0408824 \tabularnewline
203 & 0.955689 & 0.0886219 & 0.0443109 \tabularnewline
204 & 0.957864 & 0.0842728 & 0.0421364 \tabularnewline
205 & 0.948622 & 0.102755 & 0.0513776 \tabularnewline
206 & 0.940635 & 0.11873 & 0.0593648 \tabularnewline
207 & 0.939341 & 0.121318 & 0.0606591 \tabularnewline
208 & 0.929636 & 0.140728 & 0.0703641 \tabularnewline
209 & 0.917315 & 0.16537 & 0.0826851 \tabularnewline
210 & 0.90743 & 0.18514 & 0.09257 \tabularnewline
211 & 0.935184 & 0.129632 & 0.0648161 \tabularnewline
212 & 0.926042 & 0.147917 & 0.0739585 \tabularnewline
213 & 0.948794 & 0.102412 & 0.0512059 \tabularnewline
214 & 0.939607 & 0.120786 & 0.0603929 \tabularnewline
215 & 0.932021 & 0.135958 & 0.0679789 \tabularnewline
216 & 0.917028 & 0.165944 & 0.0829718 \tabularnewline
217 & 0.927786 & 0.144428 & 0.072214 \tabularnewline
218 & 0.912153 & 0.175693 & 0.0878467 \tabularnewline
219 & 0.90257 & 0.194859 & 0.0974295 \tabularnewline
220 & 0.88913 & 0.221741 & 0.11087 \tabularnewline
221 & 0.868054 & 0.263892 & 0.131946 \tabularnewline
222 & 0.844634 & 0.310732 & 0.155366 \tabularnewline
223 & 0.829623 & 0.340754 & 0.170377 \tabularnewline
224 & 0.804471 & 0.391058 & 0.195529 \tabularnewline
225 & 0.782021 & 0.435958 & 0.217979 \tabularnewline
226 & 0.762691 & 0.474618 & 0.237309 \tabularnewline
227 & 0.751738 & 0.496524 & 0.248262 \tabularnewline
228 & 0.730005 & 0.539991 & 0.269995 \tabularnewline
229 & 0.775377 & 0.449246 & 0.224623 \tabularnewline
230 & 0.745659 & 0.508682 & 0.254341 \tabularnewline
231 & 0.715621 & 0.568758 & 0.284379 \tabularnewline
232 & 0.735693 & 0.528613 & 0.264307 \tabularnewline
233 & 0.723816 & 0.552368 & 0.276184 \tabularnewline
234 & 0.700801 & 0.598398 & 0.299199 \tabularnewline
235 & 0.77757 & 0.44486 & 0.22243 \tabularnewline
236 & 0.815178 & 0.369644 & 0.184822 \tabularnewline
237 & 0.798757 & 0.402486 & 0.201243 \tabularnewline
238 & 0.812443 & 0.375114 & 0.187557 \tabularnewline
239 & 0.795149 & 0.409702 & 0.204851 \tabularnewline
240 & 0.769463 & 0.461073 & 0.230537 \tabularnewline
241 & 0.749551 & 0.500899 & 0.250449 \tabularnewline
242 & 0.705107 & 0.589786 & 0.294893 \tabularnewline
243 & 0.74329 & 0.513419 & 0.25671 \tabularnewline
244 & 0.707552 & 0.584896 & 0.292448 \tabularnewline
245 & 0.684767 & 0.630465 & 0.315233 \tabularnewline
246 & 0.668594 & 0.662812 & 0.331406 \tabularnewline
247 & 0.627726 & 0.744547 & 0.372274 \tabularnewline
248 & 0.573777 & 0.852446 & 0.426223 \tabularnewline
249 & 0.677991 & 0.644018 & 0.322009 \tabularnewline
250 & 0.635778 & 0.728443 & 0.364222 \tabularnewline
251 & 0.619112 & 0.761775 & 0.380888 \tabularnewline
252 & 0.747463 & 0.505074 & 0.252537 \tabularnewline
253 & 0.695337 & 0.609327 & 0.304663 \tabularnewline
254 & 0.63895 & 0.7221 & 0.36105 \tabularnewline
255 & 0.58186 & 0.836279 & 0.41814 \tabularnewline
256 & 0.552694 & 0.894613 & 0.447306 \tabularnewline
257 & 0.504676 & 0.990649 & 0.495324 \tabularnewline
258 & 0.451553 & 0.903106 & 0.548447 \tabularnewline
259 & 0.38741 & 0.774819 & 0.61259 \tabularnewline
260 & 0.343897 & 0.687794 & 0.656103 \tabularnewline
261 & 0.28105 & 0.562099 & 0.71895 \tabularnewline
262 & 0.226455 & 0.45291 & 0.773545 \tabularnewline
263 & 0.174168 & 0.348335 & 0.825832 \tabularnewline
264 & 0.14758 & 0.295159 & 0.85242 \tabularnewline
265 & 0.1835 & 0.367001 & 0.8165 \tabularnewline
266 & 0.489934 & 0.979867 & 0.510066 \tabularnewline
267 & 0.577783 & 0.844434 & 0.422217 \tabularnewline
268 & 0.964605 & 0.0707899 & 0.0353949 \tabularnewline
269 & 0.996575 & 0.00685041 & 0.0034252 \tabularnewline
270 & 0.990407 & 0.0191867 & 0.00959334 \tabularnewline
271 & 0.990887 & 0.0182268 & 0.00911338 \tabularnewline
272 & 0.970029 & 0.0599423 & 0.0299711 \tabularnewline
273 & 0.884857 & 0.230285 & 0.115143 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=252898&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]14[/C][C]0.873224[/C][C]0.253553[/C][C]0.126776[/C][/ROW]
[ROW][C]15[/C][C]0.897393[/C][C]0.205214[/C][C]0.102607[/C][/ROW]
[ROW][C]16[/C][C]0.835106[/C][C]0.329789[/C][C]0.164894[/C][/ROW]
[ROW][C]17[/C][C]0.749565[/C][C]0.500871[/C][C]0.250435[/C][/ROW]
[ROW][C]18[/C][C]0.726614[/C][C]0.546772[/C][C]0.273386[/C][/ROW]
[ROW][C]19[/C][C]0.677854[/C][C]0.644293[/C][C]0.322146[/C][/ROW]
[ROW][C]20[/C][C]0.589668[/C][C]0.820664[/C][C]0.410332[/C][/ROW]
[ROW][C]21[/C][C]0.635572[/C][C]0.728856[/C][C]0.364428[/C][/ROW]
[ROW][C]22[/C][C]0.609626[/C][C]0.780748[/C][C]0.390374[/C][/ROW]
[ROW][C]23[/C][C]0.598329[/C][C]0.803342[/C][C]0.401671[/C][/ROW]
[ROW][C]24[/C][C]0.541581[/C][C]0.916839[/C][C]0.458419[/C][/ROW]
[ROW][C]25[/C][C]0.665491[/C][C]0.669017[/C][C]0.334509[/C][/ROW]
[ROW][C]26[/C][C]0.609338[/C][C]0.781324[/C][C]0.390662[/C][/ROW]
[ROW][C]27[/C][C]0.539073[/C][C]0.921853[/C][C]0.460927[/C][/ROW]
[ROW][C]28[/C][C]0.471246[/C][C]0.942493[/C][C]0.528754[/C][/ROW]
[ROW][C]29[/C][C]0.418016[/C][C]0.836031[/C][C]0.581984[/C][/ROW]
[ROW][C]30[/C][C]0.350906[/C][C]0.701812[/C][C]0.649094[/C][/ROW]
[ROW][C]31[/C][C]0.29064[/C][C]0.58128[/C][C]0.70936[/C][/ROW]
[ROW][C]32[/C][C]0.304994[/C][C]0.609989[/C][C]0.695006[/C][/ROW]
[ROW][C]33[/C][C]0.27092[/C][C]0.54184[/C][C]0.72908[/C][/ROW]
[ROW][C]34[/C][C]0.326192[/C][C]0.652384[/C][C]0.673808[/C][/ROW]
[ROW][C]35[/C][C]0.288057[/C][C]0.576115[/C][C]0.711943[/C][/ROW]
[ROW][C]36[/C][C]0.285103[/C][C]0.570206[/C][C]0.714897[/C][/ROW]
[ROW][C]37[/C][C]0.246059[/C][C]0.492118[/C][C]0.753941[/C][/ROW]
[ROW][C]38[/C][C]0.244943[/C][C]0.489885[/C][C]0.755057[/C][/ROW]
[ROW][C]39[/C][C]0.203125[/C][C]0.406249[/C][C]0.796875[/C][/ROW]
[ROW][C]40[/C][C]0.194356[/C][C]0.388712[/C][C]0.805644[/C][/ROW]
[ROW][C]41[/C][C]0.212349[/C][C]0.424697[/C][C]0.787651[/C][/ROW]
[ROW][C]42[/C][C]0.175118[/C][C]0.350237[/C][C]0.824882[/C][/ROW]
[ROW][C]43[/C][C]0.295354[/C][C]0.590708[/C][C]0.704646[/C][/ROW]
[ROW][C]44[/C][C]0.267542[/C][C]0.535084[/C][C]0.732458[/C][/ROW]
[ROW][C]45[/C][C]0.254404[/C][C]0.508807[/C][C]0.745596[/C][/ROW]
[ROW][C]46[/C][C]0.22846[/C][C]0.45692[/C][C]0.77154[/C][/ROW]
[ROW][C]47[/C][C]0.198916[/C][C]0.397831[/C][C]0.801084[/C][/ROW]
[ROW][C]48[/C][C]0.169404[/C][C]0.338808[/C][C]0.830596[/C][/ROW]
[ROW][C]49[/C][C]0.141388[/C][C]0.282776[/C][C]0.858612[/C][/ROW]
[ROW][C]50[/C][C]0.266157[/C][C]0.532314[/C][C]0.733843[/C][/ROW]
[ROW][C]51[/C][C]0.320567[/C][C]0.641135[/C][C]0.679433[/C][/ROW]
[ROW][C]52[/C][C]0.31048[/C][C]0.620959[/C][C]0.68952[/C][/ROW]
[ROW][C]53[/C][C]0.27228[/C][C]0.544559[/C][C]0.72772[/C][/ROW]
[ROW][C]54[/C][C]0.306777[/C][C]0.613553[/C][C]0.693223[/C][/ROW]
[ROW][C]55[/C][C]0.270841[/C][C]0.541681[/C][C]0.729159[/C][/ROW]
[ROW][C]56[/C][C]0.286935[/C][C]0.57387[/C][C]0.713065[/C][/ROW]
[ROW][C]57[/C][C]0.374201[/C][C]0.748401[/C][C]0.625799[/C][/ROW]
[ROW][C]58[/C][C]0.337654[/C][C]0.675308[/C][C]0.662346[/C][/ROW]
[ROW][C]59[/C][C]0.486351[/C][C]0.972701[/C][C]0.513649[/C][/ROW]
[ROW][C]60[/C][C]0.658956[/C][C]0.682088[/C][C]0.341044[/C][/ROW]
[ROW][C]61[/C][C]0.630769[/C][C]0.738461[/C][C]0.369231[/C][/ROW]
[ROW][C]62[/C][C]0.631689[/C][C]0.736622[/C][C]0.368311[/C][/ROW]
[ROW][C]63[/C][C]0.595962[/C][C]0.808076[/C][C]0.404038[/C][/ROW]
[ROW][C]64[/C][C]0.576439[/C][C]0.847123[/C][C]0.423561[/C][/ROW]
[ROW][C]65[/C][C]0.668347[/C][C]0.663306[/C][C]0.331653[/C][/ROW]
[ROW][C]66[/C][C]0.766818[/C][C]0.466363[/C][C]0.233182[/C][/ROW]
[ROW][C]67[/C][C]0.74106[/C][C]0.517881[/C][C]0.25894[/C][/ROW]
[ROW][C]68[/C][C]0.712322[/C][C]0.575355[/C][C]0.287678[/C][/ROW]
[ROW][C]69[/C][C]0.696671[/C][C]0.606659[/C][C]0.303329[/C][/ROW]
[ROW][C]70[/C][C]0.680761[/C][C]0.638477[/C][C]0.319239[/C][/ROW]
[ROW][C]71[/C][C]0.687099[/C][C]0.625802[/C][C]0.312901[/C][/ROW]
[ROW][C]72[/C][C]0.652786[/C][C]0.694429[/C][C]0.347214[/C][/ROW]
[ROW][C]73[/C][C]0.626022[/C][C]0.747956[/C][C]0.373978[/C][/ROW]
[ROW][C]74[/C][C]0.596003[/C][C]0.807994[/C][C]0.403997[/C][/ROW]
[ROW][C]75[/C][C]0.561552[/C][C]0.876896[/C][C]0.438448[/C][/ROW]
[ROW][C]76[/C][C]0.567878[/C][C]0.864244[/C][C]0.432122[/C][/ROW]
[ROW][C]77[/C][C]0.61728[/C][C]0.76544[/C][C]0.38272[/C][/ROW]
[ROW][C]78[/C][C]0.616422[/C][C]0.767157[/C][C]0.383578[/C][/ROW]
[ROW][C]79[/C][C]0.599572[/C][C]0.800856[/C][C]0.400428[/C][/ROW]
[ROW][C]80[/C][C]0.584536[/C][C]0.830929[/C][C]0.415464[/C][/ROW]
[ROW][C]81[/C][C]0.56994[/C][C]0.860121[/C][C]0.43006[/C][/ROW]
[ROW][C]82[/C][C]0.553712[/C][C]0.892576[/C][C]0.446288[/C][/ROW]
[ROW][C]83[/C][C]0.58326[/C][C]0.833481[/C][C]0.41674[/C][/ROW]
[ROW][C]84[/C][C]0.578414[/C][C]0.843173[/C][C]0.421586[/C][/ROW]
[ROW][C]85[/C][C]0.609451[/C][C]0.781097[/C][C]0.390549[/C][/ROW]
[ROW][C]86[/C][C]0.591446[/C][C]0.817108[/C][C]0.408554[/C][/ROW]
[ROW][C]87[/C][C]0.598555[/C][C]0.802891[/C][C]0.401445[/C][/ROW]
[ROW][C]88[/C][C]0.602283[/C][C]0.795434[/C][C]0.397717[/C][/ROW]
[ROW][C]89[/C][C]0.569997[/C][C]0.860006[/C][C]0.430003[/C][/ROW]
[ROW][C]90[/C][C]0.535027[/C][C]0.929946[/C][C]0.464973[/C][/ROW]
[ROW][C]91[/C][C]0.514097[/C][C]0.971807[/C][C]0.485903[/C][/ROW]
[ROW][C]92[/C][C]0.519302[/C][C]0.961396[/C][C]0.480698[/C][/ROW]
[ROW][C]93[/C][C]0.553059[/C][C]0.893882[/C][C]0.446941[/C][/ROW]
[ROW][C]94[/C][C]0.560368[/C][C]0.879265[/C][C]0.439632[/C][/ROW]
[ROW][C]95[/C][C]0.671018[/C][C]0.657963[/C][C]0.328982[/C][/ROW]
[ROW][C]96[/C][C]0.637257[/C][C]0.725487[/C][C]0.362743[/C][/ROW]
[ROW][C]97[/C][C]0.632186[/C][C]0.735628[/C][C]0.367814[/C][/ROW]
[ROW][C]98[/C][C]0.701232[/C][C]0.597536[/C][C]0.298768[/C][/ROW]
[ROW][C]99[/C][C]0.679594[/C][C]0.640812[/C][C]0.320406[/C][/ROW]
[ROW][C]100[/C][C]0.677433[/C][C]0.645134[/C][C]0.322567[/C][/ROW]
[ROW][C]101[/C][C]0.654292[/C][C]0.691416[/C][C]0.345708[/C][/ROW]
[ROW][C]102[/C][C]0.736334[/C][C]0.527333[/C][C]0.263666[/C][/ROW]
[ROW][C]103[/C][C]0.838049[/C][C]0.323902[/C][C]0.161951[/C][/ROW]
[ROW][C]104[/C][C]0.821281[/C][C]0.357439[/C][C]0.178719[/C][/ROW]
[ROW][C]105[/C][C]0.802814[/C][C]0.394373[/C][C]0.197186[/C][/ROW]
[ROW][C]106[/C][C]0.793522[/C][C]0.412956[/C][C]0.206478[/C][/ROW]
[ROW][C]107[/C][C]0.815556[/C][C]0.368888[/C][C]0.184444[/C][/ROW]
[ROW][C]108[/C][C]0.827127[/C][C]0.345745[/C][C]0.172873[/C][/ROW]
[ROW][C]109[/C][C]0.84144[/C][C]0.317119[/C][C]0.15856[/C][/ROW]
[ROW][C]110[/C][C]0.826737[/C][C]0.346525[/C][C]0.173263[/C][/ROW]
[ROW][C]111[/C][C]0.893598[/C][C]0.212803[/C][C]0.106402[/C][/ROW]
[ROW][C]112[/C][C]0.93057[/C][C]0.13886[/C][C]0.0694298[/C][/ROW]
[ROW][C]113[/C][C]0.936195[/C][C]0.12761[/C][C]0.0638048[/C][/ROW]
[ROW][C]114[/C][C]0.927852[/C][C]0.144296[/C][C]0.072148[/C][/ROW]
[ROW][C]115[/C][C]0.921023[/C][C]0.157954[/C][C]0.0789768[/C][/ROW]
[ROW][C]116[/C][C]0.929177[/C][C]0.141646[/C][C]0.0708229[/C][/ROW]
[ROW][C]117[/C][C]0.925989[/C][C]0.148022[/C][C]0.0740108[/C][/ROW]
[ROW][C]118[/C][C]0.943921[/C][C]0.112159[/C][C]0.0560795[/C][/ROW]
[ROW][C]119[/C][C]0.95145[/C][C]0.0970991[/C][C]0.0485496[/C][/ROW]
[ROW][C]120[/C][C]0.942787[/C][C]0.114426[/C][C]0.057213[/C][/ROW]
[ROW][C]121[/C][C]0.942264[/C][C]0.115473[/C][C]0.0577363[/C][/ROW]
[ROW][C]122[/C][C]0.938061[/C][C]0.123879[/C][C]0.0619394[/C][/ROW]
[ROW][C]123[/C][C]0.935723[/C][C]0.128553[/C][C]0.0642765[/C][/ROW]
[ROW][C]124[/C][C]0.933602[/C][C]0.132796[/C][C]0.0663982[/C][/ROW]
[ROW][C]125[/C][C]0.972525[/C][C]0.0549502[/C][C]0.0274751[/C][/ROW]
[ROW][C]126[/C][C]0.968288[/C][C]0.0634233[/C][C]0.0317117[/C][/ROW]
[ROW][C]127[/C][C]0.986251[/C][C]0.0274974[/C][C]0.0137487[/C][/ROW]
[ROW][C]128[/C][C]0.985514[/C][C]0.0289724[/C][C]0.0144862[/C][/ROW]
[ROW][C]129[/C][C]0.982352[/C][C]0.0352964[/C][C]0.0176482[/C][/ROW]
[ROW][C]130[/C][C]0.978626[/C][C]0.0427484[/C][C]0.0213742[/C][/ROW]
[ROW][C]131[/C][C]0.976713[/C][C]0.046574[/C][C]0.023287[/C][/ROW]
[ROW][C]132[/C][C]0.973139[/C][C]0.0537216[/C][C]0.0268608[/C][/ROW]
[ROW][C]133[/C][C]0.972751[/C][C]0.0544972[/C][C]0.0272486[/C][/ROW]
[ROW][C]134[/C][C]0.967646[/C][C]0.0647077[/C][C]0.0323539[/C][/ROW]
[ROW][C]135[/C][C]0.961971[/C][C]0.076057[/C][C]0.0380285[/C][/ROW]
[ROW][C]136[/C][C]0.963414[/C][C]0.0731728[/C][C]0.0365864[/C][/ROW]
[ROW][C]137[/C][C]0.956076[/C][C]0.0878484[/C][C]0.0439242[/C][/ROW]
[ROW][C]138[/C][C]0.955848[/C][C]0.0883045[/C][C]0.0441523[/C][/ROW]
[ROW][C]139[/C][C]0.94746[/C][C]0.105081[/C][C]0.0525403[/C][/ROW]
[ROW][C]140[/C][C]0.958936[/C][C]0.0821276[/C][C]0.0410638[/C][/ROW]
[ROW][C]141[/C][C]0.969825[/C][C]0.0603503[/C][C]0.0301751[/C][/ROW]
[ROW][C]142[/C][C]0.964681[/C][C]0.070639[/C][C]0.0353195[/C][/ROW]
[ROW][C]143[/C][C]0.957364[/C][C]0.0852717[/C][C]0.0426358[/C][/ROW]
[ROW][C]144[/C][C]0.950254[/C][C]0.0994921[/C][C]0.049746[/C][/ROW]
[ROW][C]145[/C][C]0.946845[/C][C]0.10631[/C][C]0.0531548[/C][/ROW]
[ROW][C]146[/C][C]0.946922[/C][C]0.106157[/C][C]0.0530784[/C][/ROW]
[ROW][C]147[/C][C]0.940635[/C][C]0.118729[/C][C]0.0593645[/C][/ROW]
[ROW][C]148[/C][C]0.933984[/C][C]0.132031[/C][C]0.0660156[/C][/ROW]
[ROW][C]149[/C][C]0.923503[/C][C]0.152993[/C][C]0.0764966[/C][/ROW]
[ROW][C]150[/C][C]0.913864[/C][C]0.172273[/C][C]0.0861363[/C][/ROW]
[ROW][C]151[/C][C]0.906323[/C][C]0.187353[/C][C]0.0936765[/C][/ROW]
[ROW][C]152[/C][C]0.895802[/C][C]0.208396[/C][C]0.104198[/C][/ROW]
[ROW][C]153[/C][C]0.879851[/C][C]0.240298[/C][C]0.120149[/C][/ROW]
[ROW][C]154[/C][C]0.905159[/C][C]0.189683[/C][C]0.0948415[/C][/ROW]
[ROW][C]155[/C][C]0.892759[/C][C]0.214483[/C][C]0.107241[/C][/ROW]
[ROW][C]156[/C][C]0.961591[/C][C]0.0768178[/C][C]0.0384089[/C][/ROW]
[ROW][C]157[/C][C]0.959109[/C][C]0.0817812[/C][C]0.0408906[/C][/ROW]
[ROW][C]158[/C][C]0.953274[/C][C]0.0934522[/C][C]0.0467261[/C][/ROW]
[ROW][C]159[/C][C]0.944483[/C][C]0.111034[/C][C]0.0555169[/C][/ROW]
[ROW][C]160[/C][C]0.958434[/C][C]0.0831316[/C][C]0.0415658[/C][/ROW]
[ROW][C]161[/C][C]0.95182[/C][C]0.0963595[/C][C]0.0481797[/C][/ROW]
[ROW][C]162[/C][C]0.949214[/C][C]0.101572[/C][C]0.0507862[/C][/ROW]
[ROW][C]163[/C][C]0.956608[/C][C]0.0867839[/C][C]0.0433919[/C][/ROW]
[ROW][C]164[/C][C]0.951442[/C][C]0.0971167[/C][C]0.0485584[/C][/ROW]
[ROW][C]165[/C][C]0.94777[/C][C]0.104459[/C][C]0.0522297[/C][/ROW]
[ROW][C]166[/C][C]0.952587[/C][C]0.0948262[/C][C]0.0474131[/C][/ROW]
[ROW][C]167[/C][C]0.943409[/C][C]0.113182[/C][C]0.0565909[/C][/ROW]
[ROW][C]168[/C][C]0.932574[/C][C]0.134852[/C][C]0.0674259[/C][/ROW]
[ROW][C]169[/C][C]0.983758[/C][C]0.0324835[/C][C]0.0162418[/C][/ROW]
[ROW][C]170[/C][C]0.982054[/C][C]0.035893[/C][C]0.0179465[/C][/ROW]
[ROW][C]171[/C][C]0.983654[/C][C]0.0326911[/C][C]0.0163456[/C][/ROW]
[ROW][C]172[/C][C]0.979889[/C][C]0.0402221[/C][C]0.020111[/C][/ROW]
[ROW][C]173[/C][C]0.98242[/C][C]0.0351604[/C][C]0.0175802[/C][/ROW]
[ROW][C]174[/C][C]0.978539[/C][C]0.0429217[/C][C]0.0214609[/C][/ROW]
[ROW][C]175[/C][C]0.98093[/C][C]0.0381391[/C][C]0.0190695[/C][/ROW]
[ROW][C]176[/C][C]0.976247[/C][C]0.047506[/C][C]0.023753[/C][/ROW]
[ROW][C]177[/C][C]0.976609[/C][C]0.0467822[/C][C]0.0233911[/C][/ROW]
[ROW][C]178[/C][C]0.972936[/C][C]0.0541289[/C][C]0.0270645[/C][/ROW]
[ROW][C]179[/C][C]0.966698[/C][C]0.0666035[/C][C]0.0333018[/C][/ROW]
[ROW][C]180[/C][C]0.959308[/C][C]0.0813845[/C][C]0.0406922[/C][/ROW]
[ROW][C]181[/C][C]0.956414[/C][C]0.0871713[/C][C]0.0435857[/C][/ROW]
[ROW][C]182[/C][C]0.9477[/C][C]0.104601[/C][C]0.0523003[/C][/ROW]
[ROW][C]183[/C][C]0.944835[/C][C]0.110331[/C][C]0.0551653[/C][/ROW]
[ROW][C]184[/C][C]0.939286[/C][C]0.121427[/C][C]0.0607137[/C][/ROW]
[ROW][C]185[/C][C]0.93088[/C][C]0.138239[/C][C]0.0691197[/C][/ROW]
[ROW][C]186[/C][C]0.931963[/C][C]0.136074[/C][C]0.068037[/C][/ROW]
[ROW][C]187[/C][C]0.928786[/C][C]0.142427[/C][C]0.0712137[/C][/ROW]
[ROW][C]188[/C][C]0.92835[/C][C]0.143301[/C][C]0.0716504[/C][/ROW]
[ROW][C]189[/C][C]0.920885[/C][C]0.158229[/C][C]0.0791145[/C][/ROW]
[ROW][C]190[/C][C]0.975397[/C][C]0.0492068[/C][C]0.0246034[/C][/ROW]
[ROW][C]191[/C][C]0.969961[/C][C]0.0600772[/C][C]0.0300386[/C][/ROW]
[ROW][C]192[/C][C]0.974928[/C][C]0.0501439[/C][C]0.025072[/C][/ROW]
[ROW][C]193[/C][C]0.978113[/C][C]0.0437736[/C][C]0.0218868[/C][/ROW]
[ROW][C]194[/C][C]0.974893[/C][C]0.0502146[/C][C]0.0251073[/C][/ROW]
[ROW][C]195[/C][C]0.968953[/C][C]0.0620943[/C][C]0.0310472[/C][/ROW]
[ROW][C]196[/C][C]0.966339[/C][C]0.0673225[/C][C]0.0336613[/C][/ROW]
[ROW][C]197[/C][C]0.960544[/C][C]0.0789126[/C][C]0.0394563[/C][/ROW]
[ROW][C]198[/C][C]0.963585[/C][C]0.0728294[/C][C]0.0364147[/C][/ROW]
[ROW][C]199[/C][C]0.957228[/C][C]0.0855445[/C][C]0.0427723[/C][/ROW]
[ROW][C]200[/C][C]0.952879[/C][C]0.0942428[/C][C]0.0471214[/C][/ROW]
[ROW][C]201[/C][C]0.951697[/C][C]0.096605[/C][C]0.0483025[/C][/ROW]
[ROW][C]202[/C][C]0.959118[/C][C]0.0817648[/C][C]0.0408824[/C][/ROW]
[ROW][C]203[/C][C]0.955689[/C][C]0.0886219[/C][C]0.0443109[/C][/ROW]
[ROW][C]204[/C][C]0.957864[/C][C]0.0842728[/C][C]0.0421364[/C][/ROW]
[ROW][C]205[/C][C]0.948622[/C][C]0.102755[/C][C]0.0513776[/C][/ROW]
[ROW][C]206[/C][C]0.940635[/C][C]0.11873[/C][C]0.0593648[/C][/ROW]
[ROW][C]207[/C][C]0.939341[/C][C]0.121318[/C][C]0.0606591[/C][/ROW]
[ROW][C]208[/C][C]0.929636[/C][C]0.140728[/C][C]0.0703641[/C][/ROW]
[ROW][C]209[/C][C]0.917315[/C][C]0.16537[/C][C]0.0826851[/C][/ROW]
[ROW][C]210[/C][C]0.90743[/C][C]0.18514[/C][C]0.09257[/C][/ROW]
[ROW][C]211[/C][C]0.935184[/C][C]0.129632[/C][C]0.0648161[/C][/ROW]
[ROW][C]212[/C][C]0.926042[/C][C]0.147917[/C][C]0.0739585[/C][/ROW]
[ROW][C]213[/C][C]0.948794[/C][C]0.102412[/C][C]0.0512059[/C][/ROW]
[ROW][C]214[/C][C]0.939607[/C][C]0.120786[/C][C]0.0603929[/C][/ROW]
[ROW][C]215[/C][C]0.932021[/C][C]0.135958[/C][C]0.0679789[/C][/ROW]
[ROW][C]216[/C][C]0.917028[/C][C]0.165944[/C][C]0.0829718[/C][/ROW]
[ROW][C]217[/C][C]0.927786[/C][C]0.144428[/C][C]0.072214[/C][/ROW]
[ROW][C]218[/C][C]0.912153[/C][C]0.175693[/C][C]0.0878467[/C][/ROW]
[ROW][C]219[/C][C]0.90257[/C][C]0.194859[/C][C]0.0974295[/C][/ROW]
[ROW][C]220[/C][C]0.88913[/C][C]0.221741[/C][C]0.11087[/C][/ROW]
[ROW][C]221[/C][C]0.868054[/C][C]0.263892[/C][C]0.131946[/C][/ROW]
[ROW][C]222[/C][C]0.844634[/C][C]0.310732[/C][C]0.155366[/C][/ROW]
[ROW][C]223[/C][C]0.829623[/C][C]0.340754[/C][C]0.170377[/C][/ROW]
[ROW][C]224[/C][C]0.804471[/C][C]0.391058[/C][C]0.195529[/C][/ROW]
[ROW][C]225[/C][C]0.782021[/C][C]0.435958[/C][C]0.217979[/C][/ROW]
[ROW][C]226[/C][C]0.762691[/C][C]0.474618[/C][C]0.237309[/C][/ROW]
[ROW][C]227[/C][C]0.751738[/C][C]0.496524[/C][C]0.248262[/C][/ROW]
[ROW][C]228[/C][C]0.730005[/C][C]0.539991[/C][C]0.269995[/C][/ROW]
[ROW][C]229[/C][C]0.775377[/C][C]0.449246[/C][C]0.224623[/C][/ROW]
[ROW][C]230[/C][C]0.745659[/C][C]0.508682[/C][C]0.254341[/C][/ROW]
[ROW][C]231[/C][C]0.715621[/C][C]0.568758[/C][C]0.284379[/C][/ROW]
[ROW][C]232[/C][C]0.735693[/C][C]0.528613[/C][C]0.264307[/C][/ROW]
[ROW][C]233[/C][C]0.723816[/C][C]0.552368[/C][C]0.276184[/C][/ROW]
[ROW][C]234[/C][C]0.700801[/C][C]0.598398[/C][C]0.299199[/C][/ROW]
[ROW][C]235[/C][C]0.77757[/C][C]0.44486[/C][C]0.22243[/C][/ROW]
[ROW][C]236[/C][C]0.815178[/C][C]0.369644[/C][C]0.184822[/C][/ROW]
[ROW][C]237[/C][C]0.798757[/C][C]0.402486[/C][C]0.201243[/C][/ROW]
[ROW][C]238[/C][C]0.812443[/C][C]0.375114[/C][C]0.187557[/C][/ROW]
[ROW][C]239[/C][C]0.795149[/C][C]0.409702[/C][C]0.204851[/C][/ROW]
[ROW][C]240[/C][C]0.769463[/C][C]0.461073[/C][C]0.230537[/C][/ROW]
[ROW][C]241[/C][C]0.749551[/C][C]0.500899[/C][C]0.250449[/C][/ROW]
[ROW][C]242[/C][C]0.705107[/C][C]0.589786[/C][C]0.294893[/C][/ROW]
[ROW][C]243[/C][C]0.74329[/C][C]0.513419[/C][C]0.25671[/C][/ROW]
[ROW][C]244[/C][C]0.707552[/C][C]0.584896[/C][C]0.292448[/C][/ROW]
[ROW][C]245[/C][C]0.684767[/C][C]0.630465[/C][C]0.315233[/C][/ROW]
[ROW][C]246[/C][C]0.668594[/C][C]0.662812[/C][C]0.331406[/C][/ROW]
[ROW][C]247[/C][C]0.627726[/C][C]0.744547[/C][C]0.372274[/C][/ROW]
[ROW][C]248[/C][C]0.573777[/C][C]0.852446[/C][C]0.426223[/C][/ROW]
[ROW][C]249[/C][C]0.677991[/C][C]0.644018[/C][C]0.322009[/C][/ROW]
[ROW][C]250[/C][C]0.635778[/C][C]0.728443[/C][C]0.364222[/C][/ROW]
[ROW][C]251[/C][C]0.619112[/C][C]0.761775[/C][C]0.380888[/C][/ROW]
[ROW][C]252[/C][C]0.747463[/C][C]0.505074[/C][C]0.252537[/C][/ROW]
[ROW][C]253[/C][C]0.695337[/C][C]0.609327[/C][C]0.304663[/C][/ROW]
[ROW][C]254[/C][C]0.63895[/C][C]0.7221[/C][C]0.36105[/C][/ROW]
[ROW][C]255[/C][C]0.58186[/C][C]0.836279[/C][C]0.41814[/C][/ROW]
[ROW][C]256[/C][C]0.552694[/C][C]0.894613[/C][C]0.447306[/C][/ROW]
[ROW][C]257[/C][C]0.504676[/C][C]0.990649[/C][C]0.495324[/C][/ROW]
[ROW][C]258[/C][C]0.451553[/C][C]0.903106[/C][C]0.548447[/C][/ROW]
[ROW][C]259[/C][C]0.38741[/C][C]0.774819[/C][C]0.61259[/C][/ROW]
[ROW][C]260[/C][C]0.343897[/C][C]0.687794[/C][C]0.656103[/C][/ROW]
[ROW][C]261[/C][C]0.28105[/C][C]0.562099[/C][C]0.71895[/C][/ROW]
[ROW][C]262[/C][C]0.226455[/C][C]0.45291[/C][C]0.773545[/C][/ROW]
[ROW][C]263[/C][C]0.174168[/C][C]0.348335[/C][C]0.825832[/C][/ROW]
[ROW][C]264[/C][C]0.14758[/C][C]0.295159[/C][C]0.85242[/C][/ROW]
[ROW][C]265[/C][C]0.1835[/C][C]0.367001[/C][C]0.8165[/C][/ROW]
[ROW][C]266[/C][C]0.489934[/C][C]0.979867[/C][C]0.510066[/C][/ROW]
[ROW][C]267[/C][C]0.577783[/C][C]0.844434[/C][C]0.422217[/C][/ROW]
[ROW][C]268[/C][C]0.964605[/C][C]0.0707899[/C][C]0.0353949[/C][/ROW]
[ROW][C]269[/C][C]0.996575[/C][C]0.00685041[/C][C]0.0034252[/C][/ROW]
[ROW][C]270[/C][C]0.990407[/C][C]0.0191867[/C][C]0.00959334[/C][/ROW]
[ROW][C]271[/C][C]0.990887[/C][C]0.0182268[/C][C]0.00911338[/C][/ROW]
[ROW][C]272[/C][C]0.970029[/C][C]0.0599423[/C][C]0.0299711[/C][/ROW]
[ROW][C]273[/C][C]0.884857[/C][C]0.230285[/C][C]0.115143[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=252898&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=252898&T=5

As an alternative you can also use a QR Code:

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

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
14	0.873224	0.253553	0.126776
15	0.897393	0.205214	0.102607
16	0.835106	0.329789	0.164894
17	0.749565	0.500871	0.250435
18	0.726614	0.546772	0.273386
19	0.677854	0.644293	0.322146
20	0.589668	0.820664	0.410332
21	0.635572	0.728856	0.364428
22	0.609626	0.780748	0.390374
23	0.598329	0.803342	0.401671
24	0.541581	0.916839	0.458419
25	0.665491	0.669017	0.334509
26	0.609338	0.781324	0.390662
27	0.539073	0.921853	0.460927
28	0.471246	0.942493	0.528754
29	0.418016	0.836031	0.581984
30	0.350906	0.701812	0.649094
31	0.29064	0.58128	0.70936
32	0.304994	0.609989	0.695006
33	0.27092	0.54184	0.72908
34	0.326192	0.652384	0.673808
35	0.288057	0.576115	0.711943
36	0.285103	0.570206	0.714897
37	0.246059	0.492118	0.753941
38	0.244943	0.489885	0.755057
39	0.203125	0.406249	0.796875
40	0.194356	0.388712	0.805644
41	0.212349	0.424697	0.787651
42	0.175118	0.350237	0.824882
43	0.295354	0.590708	0.704646
44	0.267542	0.535084	0.732458
45	0.254404	0.508807	0.745596
46	0.22846	0.45692	0.77154
47	0.198916	0.397831	0.801084
48	0.169404	0.338808	0.830596
49	0.141388	0.282776	0.858612
50	0.266157	0.532314	0.733843
51	0.320567	0.641135	0.679433
52	0.31048	0.620959	0.68952
53	0.27228	0.544559	0.72772
54	0.306777	0.613553	0.693223
55	0.270841	0.541681	0.729159
56	0.286935	0.57387	0.713065
57	0.374201	0.748401	0.625799
58	0.337654	0.675308	0.662346
59	0.486351	0.972701	0.513649
60	0.658956	0.682088	0.341044
61	0.630769	0.738461	0.369231
62	0.631689	0.736622	0.368311
63	0.595962	0.808076	0.404038
64	0.576439	0.847123	0.423561
65	0.668347	0.663306	0.331653
66	0.766818	0.466363	0.233182
67	0.74106	0.517881	0.25894
68	0.712322	0.575355	0.287678
69	0.696671	0.606659	0.303329
70	0.680761	0.638477	0.319239
71	0.687099	0.625802	0.312901
72	0.652786	0.694429	0.347214
73	0.626022	0.747956	0.373978
74	0.596003	0.807994	0.403997
75	0.561552	0.876896	0.438448
76	0.567878	0.864244	0.432122
77	0.61728	0.76544	0.38272
78	0.616422	0.767157	0.383578
79	0.599572	0.800856	0.400428
80	0.584536	0.830929	0.415464
81	0.56994	0.860121	0.43006
82	0.553712	0.892576	0.446288
83	0.58326	0.833481	0.41674
84	0.578414	0.843173	0.421586
85	0.609451	0.781097	0.390549
86	0.591446	0.817108	0.408554
87	0.598555	0.802891	0.401445
88	0.602283	0.795434	0.397717
89	0.569997	0.860006	0.430003
90	0.535027	0.929946	0.464973
91	0.514097	0.971807	0.485903
92	0.519302	0.961396	0.480698
93	0.553059	0.893882	0.446941
94	0.560368	0.879265	0.439632
95	0.671018	0.657963	0.328982
96	0.637257	0.725487	0.362743
97	0.632186	0.735628	0.367814
98	0.701232	0.597536	0.298768
99	0.679594	0.640812	0.320406
100	0.677433	0.645134	0.322567
101	0.654292	0.691416	0.345708
102	0.736334	0.527333	0.263666
103	0.838049	0.323902	0.161951
104	0.821281	0.357439	0.178719
105	0.802814	0.394373	0.197186
106	0.793522	0.412956	0.206478
107	0.815556	0.368888	0.184444
108	0.827127	0.345745	0.172873
109	0.84144	0.317119	0.15856
110	0.826737	0.346525	0.173263
111	0.893598	0.212803	0.106402
112	0.93057	0.13886	0.0694298
113	0.936195	0.12761	0.0638048
114	0.927852	0.144296	0.072148
115	0.921023	0.157954	0.0789768
116	0.929177	0.141646	0.0708229
117	0.925989	0.148022	0.0740108
118	0.943921	0.112159	0.0560795
119	0.95145	0.0970991	0.0485496
120	0.942787	0.114426	0.057213
121	0.942264	0.115473	0.0577363
122	0.938061	0.123879	0.0619394
123	0.935723	0.128553	0.0642765
124	0.933602	0.132796	0.0663982
125	0.972525	0.0549502	0.0274751
126	0.968288	0.0634233	0.0317117
127	0.986251	0.0274974	0.0137487
128	0.985514	0.0289724	0.0144862
129	0.982352	0.0352964	0.0176482
130	0.978626	0.0427484	0.0213742
131	0.976713	0.046574	0.023287
132	0.973139	0.0537216	0.0268608
133	0.972751	0.0544972	0.0272486
134	0.967646	0.0647077	0.0323539
135	0.961971	0.076057	0.0380285
136	0.963414	0.0731728	0.0365864
137	0.956076	0.0878484	0.0439242
138	0.955848	0.0883045	0.0441523
139	0.94746	0.105081	0.0525403
140	0.958936	0.0821276	0.0410638
141	0.969825	0.0603503	0.0301751
142	0.964681	0.070639	0.0353195
143	0.957364	0.0852717	0.0426358
144	0.950254	0.0994921	0.049746
145	0.946845	0.10631	0.0531548
146	0.946922	0.106157	0.0530784
147	0.940635	0.118729	0.0593645
148	0.933984	0.132031	0.0660156
149	0.923503	0.152993	0.0764966
150	0.913864	0.172273	0.0861363
151	0.906323	0.187353	0.0936765
152	0.895802	0.208396	0.104198
153	0.879851	0.240298	0.120149
154	0.905159	0.189683	0.0948415
155	0.892759	0.214483	0.107241
156	0.961591	0.0768178	0.0384089
157	0.959109	0.0817812	0.0408906
158	0.953274	0.0934522	0.0467261
159	0.944483	0.111034	0.0555169
160	0.958434	0.0831316	0.0415658
161	0.95182	0.0963595	0.0481797
162	0.949214	0.101572	0.0507862
163	0.956608	0.0867839	0.0433919
164	0.951442	0.0971167	0.0485584
165	0.94777	0.104459	0.0522297
166	0.952587	0.0948262	0.0474131
167	0.943409	0.113182	0.0565909
168	0.932574	0.134852	0.0674259
169	0.983758	0.0324835	0.0162418
170	0.982054	0.035893	0.0179465
171	0.983654	0.0326911	0.0163456
172	0.979889	0.0402221	0.020111
173	0.98242	0.0351604	0.0175802
174	0.978539	0.0429217	0.0214609
175	0.98093	0.0381391	0.0190695
176	0.976247	0.047506	0.023753
177	0.976609	0.0467822	0.0233911
178	0.972936	0.0541289	0.0270645
179	0.966698	0.0666035	0.0333018
180	0.959308	0.0813845	0.0406922
181	0.956414	0.0871713	0.0435857
182	0.9477	0.104601	0.0523003
183	0.944835	0.110331	0.0551653
184	0.939286	0.121427	0.0607137
185	0.93088	0.138239	0.0691197
186	0.931963	0.136074	0.068037
187	0.928786	0.142427	0.0712137
188	0.92835	0.143301	0.0716504
189	0.920885	0.158229	0.0791145
190	0.975397	0.0492068	0.0246034
191	0.969961	0.0600772	0.0300386
192	0.974928	0.0501439	0.025072
193	0.978113	0.0437736	0.0218868
194	0.974893	0.0502146	0.0251073
195	0.968953	0.0620943	0.0310472
196	0.966339	0.0673225	0.0336613
197	0.960544	0.0789126	0.0394563
198	0.963585	0.0728294	0.0364147
199	0.957228	0.0855445	0.0427723
200	0.952879	0.0942428	0.0471214
201	0.951697	0.096605	0.0483025
202	0.959118	0.0817648	0.0408824
203	0.955689	0.0886219	0.0443109
204	0.957864	0.0842728	0.0421364
205	0.948622	0.102755	0.0513776
206	0.940635	0.11873	0.0593648
207	0.939341	0.121318	0.0606591
208	0.929636	0.140728	0.0703641
209	0.917315	0.16537	0.0826851
210	0.90743	0.18514	0.09257
211	0.935184	0.129632	0.0648161
212	0.926042	0.147917	0.0739585
213	0.948794	0.102412	0.0512059
214	0.939607	0.120786	0.0603929
215	0.932021	0.135958	0.0679789
216	0.917028	0.165944	0.0829718
217	0.927786	0.144428	0.072214
218	0.912153	0.175693	0.0878467
219	0.90257	0.194859	0.0974295
220	0.88913	0.221741	0.11087
221	0.868054	0.263892	0.131946
222	0.844634	0.310732	0.155366
223	0.829623	0.340754	0.170377
224	0.804471	0.391058	0.195529
225	0.782021	0.435958	0.217979
226	0.762691	0.474618	0.237309
227	0.751738	0.496524	0.248262
228	0.730005	0.539991	0.269995
229	0.775377	0.449246	0.224623
230	0.745659	0.508682	0.254341
231	0.715621	0.568758	0.284379
232	0.735693	0.528613	0.264307
233	0.723816	0.552368	0.276184
234	0.700801	0.598398	0.299199
235	0.77757	0.44486	0.22243
236	0.815178	0.369644	0.184822
237	0.798757	0.402486	0.201243
238	0.812443	0.375114	0.187557
239	0.795149	0.409702	0.204851
240	0.769463	0.461073	0.230537
241	0.749551	0.500899	0.250449
242	0.705107	0.589786	0.294893
243	0.74329	0.513419	0.25671
244	0.707552	0.584896	0.292448
245	0.684767	0.630465	0.315233
246	0.668594	0.662812	0.331406
247	0.627726	0.744547	0.372274
248	0.573777	0.852446	0.426223
249	0.677991	0.644018	0.322009
250	0.635778	0.728443	0.364222
251	0.619112	0.761775	0.380888
252	0.747463	0.505074	0.252537
253	0.695337	0.609327	0.304663
254	0.63895	0.7221	0.36105
255	0.58186	0.836279	0.41814
256	0.552694	0.894613	0.447306
257	0.504676	0.990649	0.495324
258	0.451553	0.903106	0.548447
259	0.38741	0.774819	0.61259
260	0.343897	0.687794	0.656103
261	0.28105	0.562099	0.71895
262	0.226455	0.45291	0.773545
263	0.174168	0.348335	0.825832
264	0.14758	0.295159	0.85242
265	0.1835	0.367001	0.8165
266	0.489934	0.979867	0.510066
267	0.577783	0.844434	0.422217
268	0.964605	0.0707899	0.0353949
269	0.996575	0.00685041	0.0034252
270	0.990407	0.0191867	0.00959334
271	0.990887	0.0182268	0.00911338
272	0.970029	0.0599423	0.0299711
273	0.884857	0.230285	0.115143

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	1	0.00384615	OK
5% type I error level	19	0.0730769	NOK
10% type I error level	61	0.234615	NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 1 & 0.00384615 & OK \tabularnewline
5% type I error level & 19 & 0.0730769 & NOK \tabularnewline
10% type I error level & 61 & 0.234615 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=252898&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]1[/C][C]0.00384615[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]19[/C][C]0.0730769[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]61[/C][C]0.234615[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=252898&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=252898&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	1	0.00384615	OK
5% type I error level	19	0.0730769	NOK
10% type I error level	61	0.234615	NOK

Figure 1

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 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 ;

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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code