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Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Tue, 13 Dec 2011 18:00:12 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/13/t1323817227gekw3s3lfmqtfmz.htm/, Retrieved Thu, 02 May 2024 17:17:49 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154771, Retrieved Thu, 02 May 2024 17:17:49 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

103

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

-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
- R PD  [Multiple Regression] [PLC] [2011-12-13 16:21:41] [7156a20ff7d97880b6dc50f7239ba03b]
-   P       [Multiple Regression] [PAG] [2011-12-13 23:00:12] [8aedcf735e397266388b06f47fe45218] [Current]
-   PD        [Multiple Regression] [idk] [2011-12-14 00:09:42] [7156a20ff7d97880b6dc50f7239ba03b] 

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Dataseries X:

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7	0.27	0.36	20.7	0.045	45	170	1.001	3	0.45	8.8	6
6.3	0.3	0.34	1.6	0.049	14	132	0.994	3.3	0.49	9.5	6
8.1	0.28	0.4	6.9	0.05	30	97	0.9951	3.26	0.44	10.1	6
7.2	0.23	0.32	8.5	0.058	47	186	0.9956	3.19	0.4	9.9	6
7.2	0.23	0.32	8.5	0.058	47	186	0.9956	3.19	0.4	9.9	6
8.1	0.28	0.4	6.9	0.05	30	97	0.9951	3.26	0.44	10.1	6
6.2	0.32	0.16	7	0.045	30	136	0.9949	3.18	0.47	9.6	6
7	0.27	0.36	20.7	0.045	45	170	1.001	3	0.45	8.8	6
6.3	0.3	0.34	1.6	0.049	14	132	0.994	3.3	0.49	9.5	6
8.1	0.22	0.43	1.5	0.044	28	129	0.9938	3.22	0.45	11	6
8.1	0.27	0.41	1.45	0.033	11	63	0.9908	2.99	0.56	12	5
8.6	0.23	0.4	4.2	0.035	17	109	0.9947	3.14	0.53	9.7	5
7.9	0.18	0.37	1.2	0.04	16	75	0.992	3.18	0.63	10.8	5
6.6	0.16	0.4	1.5	0.044	48	143	0.9912	3.54	0.52	12.4	7
8.3	0.42	0.62	19.25	0.04	41	172	1.0002	2.98	0.67	9.7	5
6.6	0.17	0.38	1.5	0.032	28	112	0.9914	3.25	0.55	11.4	7
6.3	0.48	0.04	1.1	0.046	30	99	0.9928	3.24	0.36	9.6	6
6.2	0.66	0.48	1.2	0.029	29	75	0.9892	3.33	0.39	12.8	8
7.4	0.34	0.42	1.1	0.033	17	171	0.9917	3.12	0.53	11.3	6
6.5	0.31	0.14	7.5	0.044	34	133	0.9955	3.22	0.5	9.5	5
6.2	0.66	0.48	1.2	0.029	29	75	0.9892	3.33	0.39	12.8	8
6.4	0.31	0.38	2.9	0.038	19	102	0.9912	3.17	0.35	11	7
6.8	0.26	0.42	1.7	0.049	41	122	0.993	3.47	0.48	10.5	8
7.6	0.67	0.14	1.5	0.074	25	168	0.9937	3.05	0.51	9.3	5
6.6	0.27	0.41	1.3	0.052	16	142	0.9951	3.42	0.47	10	6
7	0.25	0.32	9	0.046	56	245	0.9955	3.25	0.5	10.4	6
6.9	0.24	0.35	1	0.052	35	146	0.993	3.45	0.44	10	6
7	0.28	0.39	8.7	0.051	32	141	0.9961	3.38	0.53	10.5	6
7.4	0.27	0.48	1.1	0.047	17	132	0.9914	3.19	0.49	11.6	6
7.2	0.32	0.36	2	0.033	37	114	0.9906	3.1	0.71	12.3	7
8.5	0.24	0.39	10.4	0.044	20	142	0.9974	3.2	0.53	10	6
8.3	0.14	0.34	1.1	0.042	7	47	0.9934	3.47	0.4	10.2	6
7.4	0.25	0.36	2.05	0.05	31	100	0.992	3.19	0.44	10.8	6
6.2	0.12	0.34	1.5	0.045	43	117	0.9939	3.42	0.51	9	6
5.8	0.27	0.2	14.95	0.044	22	179	0.9962	3.37	0.37	10.2	5
7.3	0.28	0.43	1.7	0.08	21	123	0.9905	3.19	0.42	12.8	5
6.5	0.39	0.23	5.4	0.051	25	149	0.9934	3.24	0.35	10	5
7	0.33	0.32	1.2	0.053	38	138	0.9906	3.13	0.28	11.2	6
7.3	0.24	0.39	17.95	0.057	45	149	0.9999	3.21	0.36	8.6	5
7.3	0.24	0.39	17.95	0.057	45	149	0.9999	3.21	0.36	8.6	5
6.7	0.23	0.39	2.5	0.172	63	158	0.9937	3.11	0.36	9.4	6
6.7	0.24	0.39	2.9	0.173	63	157	0.9937	3.1	0.34	9.4	6
7	0.31	0.26	7.4	0.069	28	160	0.9954	3.13	0.46	9.8	6
6.6	0.24	0.27	1.4	0.057	33	152	0.9934	3.22	0.56	9.5	6
6.7	0.23	0.26	1.4	0.06	33	154	0.9934	3.24	0.56	9.5	6
7.4	0.18	0.31	1.4	0.058	38	167	0.9931	3.16	0.53	10	7
6.2	0.45	0.26	4.4	0.063	63	206	0.994	3.27	0.52	9.8	4
6.2	0.46	0.25	4.4	0.066	62	207	0.9939	3.25	0.52	9.8	5
7	0.31	0.26	7.4	0.069	28	160	0.9954	3.13	0.46	9.8	6
6.9	0.19	0.35	5	0.067	32	150	0.995	3.36	0.48	9.8	5
7.2	0.19	0.31	1.6	0.062	31	173	0.9917	3.35	0.44	11.7	6
6.6	0.25	0.29	1.1	0.068	39	124	0.9914	3.34	0.58	11	7
6.2	0.16	0.33	1.1	0.057	21	82	0.991	3.32	0.46	10.9	7
6.4	0.18	0.35	1	0.045	39	108	0.9911	3.31	0.35	10.9	6
6.8	0.2	0.59	0.9	0.147	38	132	0.993	3.05	0.38	9.1	6
6.9	0.25	0.35	1.3	0.039	29	191	0.9908	3.13	0.52	11	6
7.2	0.21	0.34	11.9	0.043	37	213	0.9962	3.09	0.5	9.6	6
6	0.19	0.26	12.4	0.048	50	147	0.9972	3.3	0.36	8.9	6
6.6	0.38	0.15	4.6	0.044	25	78	0.9931	3.11	0.38	10.2	6
7.4	0.2	0.36	1.2	0.038	44	111	0.9926	3.36	0.34	9.9	6
6.8	0.22	0.24	4.9	0.092	30	123	0.9951	3.03	0.46	8.6	6
6	0.19	0.26	12.4	0.048	50	147	0.9972	3.3	0.36	8.9	6
7	0.47	0.07	1.1	0.035	17	151	0.991	3.02	0.34	10.5	5
6.6	0.38	0.15	4.6	0.044	25	78	0.9931	3.11	0.38	10.2	6
7.2	0.24	0.27	1.4	0.038	31	122	0.9927	3.15	0.46	10.3	6
6.2	0.35	0.03	1.2	0.064	29	120	0.9934	3.22	0.54	9.1	5
6.4	0.26	0.24	6.4	0.04	27	124	0.9903	3.22	0.49	12.6	7
6.7	0.25	0.13	1.2	0.041	81	174	0.992	3.14	0.42	9.8	5
6.7	0.23	0.31	2.1	0.046	30	96	0.9926	3.33	0.64	10.7	8
7.4	0.24	0.29	10.1	0.05	21	105	0.9962	3.13	0.35	9.5	5
6.2	0.27	0.43	7.8	0.056	48	244	0.9956	3.1	0.51	9	6
6.8	0.3	0.23	4.6	0.061	50.5	238.5	0.9958	3.32	0.6	9.5	5
6	0.27	0.28	4.8	0.063	31	201	0.9964	3.69	0.71	10	5
8.6	0.23	0.46	1	0.054	9	72	0.9941	2.95	0.49	9.1	6
6.7	0.23	0.31	2.1	0.046	30	96	0.9926	3.33	0.64	10.7	8
7.4	0.24	0.29	10.1	0.05	21	105	0.9962	3.13	0.35	9.5	5
7.1	0.18	0.36	1.4	0.043	31	87	0.9898	3.26	0.37	12.7	7
7	0.32	0.34	1.3	0.042	20	69	0.9912	3.31	0.65	12	7
7.4	0.18	0.3	8.8	0.064	26	103	0.9961	2.94	0.56	9.3	5
6.7	0.54	0.28	5.4	0.06	21	105	0.9949	3.27	0.37	9	5
6.8	0.22	0.31	1.4	0.053	34	114	0.9929	3.39	0.77	10.6	6
7.1	0.2	0.34	16	0.05	51	166	0.9985	3.21	0.6	9.2	6
7.1	0.34	0.2	6.1	0.063	47	164	0.9946	3.17	0.42	10	5
7.3	0.22	0.3	8.2	0.047	42	207	0.9966	3.33	0.46	9.5	6
7.1	0.43	0.61	11.8	0.045	54	155	0.9974	3.11	0.45	8.7	5
7.1	0.44	0.62	11.8	0.044	52	152	0.9975	3.12	0.46	8.7	6
7.2	0.39	0.63	11	0.044	55	156	0.9974	3.09	0.44	8.7	6
6.8	0.25	0.31	13.3	0.05	69	202	0.9972	3.22	0.48	9.7	6
7.1	0.43	0.61	11.8	0.045	54	155	0.9974	3.11	0.45	8.7	5
7.1	0.44	0.62	11.8	0.044	52	152	0.9975	3.12	0.46	8.7	6
7.2	0.39	0.63	11	0.044	55	156	0.9974	3.09	0.44	8.7	6
6.1	0.27	0.43	7.5	0.049	65	243	0.9957	3.12	0.47	9	5
6.9	0.24	0.33	1.7	0.035	47	136	0.99	3.26	0.4	12.6	7
6.9	0.21	0.33	1.8	0.034	48	136	0.9899	3.25	0.41	12.6	7
7.5	0.17	0.32	1.7	0.04	51	148	0.9916	3.21	0.44	11.5	7
7.1	0.26	0.29	12.4	0.044	62	240	0.9969	3.04	0.42	9.2	6
6	0.34	0.66	15.9	0.046	26	164	0.9979	3.14	0.5	8.8	6
8.6	0.265	0.36	1.2	0.034	15	80	0.9913	2.95	0.36	11.4	7
9.8	0.36	0.46	10.5	0.038	4	83	0.9956	2.89	0.3	10.1	4
6	0.34	0.66	15.9	0.046	26	164	0.9979	3.14	0.5	8.8	6
7.4	0.25	0.37	13.5	0.06	52	192	0.9975	3	0.44	9.1	5
7.1	0.12	0.32	9.6	0.054	64	162	0.9962	3.4	0.41	9.4	5
6	0.21	0.24	12.1	0.05	55	164	0.997	3.34	0.39	9.4	5
7.5	0.305	0.4	18.9	0.059	44	170	1	2.99	0.46	9	5
7.4	0.25	0.37	13.5	0.06	52	192	0.9975	3	0.44	9.1	5
7.3	0.13	0.32	14.4	0.051	34	109	0.9974	3.2	0.35	9.2	6
7.1	0.12	0.32	9.6	0.054	64	162	0.9962	3.4	0.41	9.4	5
7.1	0.23	0.35	16.5	0.04	60	171	0.999	3.16	0.59	9.1	6
7.1	0.23	0.35	16.5	0.04	60	171	0.999	3.16	0.59	9.1	6
6.9	0.33	0.28	1.3	0.051	37	187	0.9927	3.27	0.6	10.3	5
6.5	0.17	0.54	8.5	0.082	64	163	0.9959	2.89	0.39	8.8	6
7.2	0.27	0.46	18.75	0.052	45	255	1	3.04	0.52	8.9	5
7.2	0.31	0.5	13.3	0.056	68	195	0.9982	3.01	0.47	9.2	5
6.7	0.41	0.34	9.2	0.049	29	150	0.9968	3.22	0.51	9.1	5
6.7	0.41	0.34	9.2	0.049	29	150	0.9968	3.22	0.51	9.1	5
5.5	0.485	0	1.5	0.065	8	103	0.994	3.63	0.4	9.7	4
6	0.31	0.24	3.3	0.041	25	143	0.9914	3.31	0.44	11.3	6
7	0.14	0.4	1.7	0.035	16	85	0.9911	3.19	0.42	11.8	6
7.2	0.31	0.5	13.3	0.056	68	195	0.9982	3.01	0.47	9.2	5
7.3	0.32	0.48	13.3	0.06	57	196	0.9982	3.04	0.5	9.2	5
5.9	0.36	0.04	5.7	0.046	21	87	0.9934	3.22	0.51	10.2	5
7.8	0.24	0.32	12.2	0.054	42	138	0.9984	3.01	0.54	8.8	5
7.4	0.16	0.31	6.85	0.059	31	131	0.9952	3.29	0.34	9.7	5
6.9	0.19	0.28	5	0.058	14	146	0.9952	3.29	0.36	9.1	6
6.4	0.13	0.47	1.6	0.092	40	158	0.9928	3.21	0.36	9.8	6
6.7	0.19	0.36	1.1	0.026	63	143	0.9912	3.27	0.48	11	6
7.4	0.39	0.23	7	0.033	29	126	0.994	3.14	0.42	10.5	5
6.5	0.24	0.32	7.6	0.038	48	203	0.9958	3.45	0.54	9.7	7
6.1	0.3	0.56	2.8	0.044	47	179	0.9924	3.3	0.57	10.9	7
6.1	0.3	0.56	2.7	0.046	46	184	0.9924	3.31	0.57	10.9	6
5.7	0.26	0.25	10.4	0.02	7	57	0.994	3.39	0.37	10.6	5
6.5	0.24	0.32	7.6	0.038	48	203	0.9958	3.45	0.54	9.7	7
6.5	0.425	0.4	13.1	0.038	59	241	0.9979	3.23	0.57	9	5
6.6	0.24	0.27	15.8	0.035	46	188	0.9982	3.24	0.51	9.2	5
6.8	0.27	0.22	8.1	0.034	55	203	0.9961	3.19	0.52	8.9	5
6.7	0.27	0.31	15.7	0.036	44	179	0.9979	3.26	0.56	9.6	5
8.2	0.23	0.4	1.2	0.027	36	121	0.992	3.12	0.38	10.7	6
7.1	0.37	0.67	10.5	0.045	49	155	0.9975	3.16	0.44	8.7	5
6.8	0.19	0.36	1.9	0.035	30	96	0.9917	3.15	0.54	10.8	7
8.1	0.28	0.39	1.9	0.029	18	79	0.9923	3.23	0.52	11.8	6
6.3	0.31	0.34	2.2	0.045	20	77	0.9927	3.3	0.43	10.2	5
7.1	0.37	0.67	10.5	0.045	49	155	0.9975	3.16	0.44	8.7	5
7.9	0.21	0.4	1.2	0.039	38	107	0.992	3.21	0.54	10.8	6
8.5	0.21	0.41	4.3	0.036	24	99	0.9947	3.18	0.53	9.7	6
8.1	0.2	0.4	2	0.037	19	87	0.9921	3.12	0.54	11.2	6
6.3	0.255	0.37	1.1	0.04	37	114	0.9905	3	0.39	10.9	6
5.6	0.16	0.27	1.4	0.044	53	168	0.9918	3.28	0.37	10.1	6
6.4	0.595	0.14	5.2	0.058	15	97	0.9951	3.38	0.36	9	4
6.3	0.34	0.33	4.6	0.034	19	80	0.9917	3.38	0.58	12	7
6.9	0.25	0.3	4.1	0.054	23	116	0.994	2.99	0.38	9.4	6
7.9	0.22	0.38	8	0.043	46	152	0.9934	3.12	0.32	11.5	7
7.6	0.18	0.46	10.2	0.055	58	135	0.9968	3.14	0.43	9.9	6
6.9	0.25	0.3	4.1	0.054	23	116	0.994	2.99	0.38	9.4	6
7.2	0.18	0.41	1.2	0.048	41	97	0.9919	3.14	0.45	10.4	5
8.2	0.23	0.4	7.5	0.049	12	76	0.9966	3.06	0.84	9.7	6
7.4	0.24	0.42	14	0.066	48	198	0.9979	2.89	0.42	8.9	6
7.4	0.24	0.42	14	0.066	48	198	0.9979	2.89	0.42	8.9	6
6.1	0.32	0.24	1.5	0.036	38	124	0.9898	3.29	0.42	12.4	7
5.2	0.44	0.04	1.4	0.036	43	119	0.9894	3.36	0.33	12.1	8
5.2	0.44	0.04	1.4	0.036	43	119	0.9894	3.36	0.33	12.1	8
6.1	0.32	0.24	1.5	0.036	38	124	0.9898	3.29	0.42	12.4	7
6.4	0.22	0.56	14.5	0.055	27	159	0.998	2.98	0.4	9.1	5
6.3	0.36	0.3	4.8	0.049	14	85	0.9932	3.28	0.39	10.6	5
7.4	0.24	0.42	14	0.066	48	198	0.9979	2.89	0.42	8.9	6
6.7	0.24	0.35	13.1	0.05	64	205	0.997	3.15	0.5	9.5	5
7	0.23	0.36	13	0.051	72	177	0.9972	3.16	0.49	9.8	5
8.4	0.27	0.46	8.7	0.048	39	197	0.9974	3.14	0.59	9.6	6
6.7	0.46	0.18	2.4	0.034	25	98	0.9896	3.08	0.44	12.6	7
7.5	0.29	0.31	8.95	0.055	20	151	0.9968	3.08	0.54	9.3	5
9.8	0.42	0.48	9.85	0.034	5	110	0.9958	2.87	0.29	10	5
7.1	0.3	0.46	1.5	0.066	29	133	0.9906	3.12	0.54	12.7	6
7.9	0.19	0.45	1.5	0.045	17	96	0.9917	3.13	0.39	11	6
7.6	0.48	0.37	0.8	0.037	4	100	0.9902	3.03	0.39	11.4	4
6.3	0.22	0.43	4.55	0.038	31	130	0.9918	3.35	0.33	11.5	7
7.5	0.27	0.31	17.7	0.051	33	173	0.999	3.09	0.64	10.2	5
6.9	0.23	0.4	7.5	0.04	50	151	0.9927	3.11	0.27	11.4	6
7.2	0.32	0.47	5.1	0.044	19	65	0.991	3.03	0.41	12.6	4
5.9	0.23	0.3	12.9	0.054	57	170	0.9972	3.28	0.39	9.4	5
6	0.67	0.07	1.2	0.06	9	108	0.9931	3.11	0.35	8.7	4
6.4	0.25	0.32	5.5	0.049	41	176	0.995	3.19	0.68	9.2	6
6.4	0.33	0.31	5.5	0.048	42	173	0.9951	3.19	0.66	9.3	6
7.1	0.34	0.15	1.2	0.053	61	183	0.9936	3.09	0.43	9.2	5
6.8	0.28	0.4	22	0.048	48	167	1.001	2.93	0.5	8.7	5
6.9	0.27	0.4	14	0.05	64	227	0.9979	3.18	0.58	9.6	6
6.8	0.26	0.56	11.9	0.043	64	226	0.997	3.02	0.63	9.3	5
6.8	0.29	0.56	11.9	0.043	66	230	0.9972	3.02	0.63	9.3	5
6.7	0.24	0.41	9.4	0.04	49	166	0.9954	3.12	0.61	9.9	6
5.9	0.3	0.23	4.2	0.038	42	119	0.9924	3.15	0.5	11	5
6.8	0.53	0.35	3.8	0.034	26	109	0.9906	3.26	0.57	12.7	8
6.5	0.28	0.28	8.5	0.047	54	210	0.9962	3.09	0.54	8.9	4
6.6	0.28	0.28	8.5	0.052	55	211	0.9962	3.09	0.55	8.9	6
6.8	0.28	0.4	22	0.048	48	167	1.001	2.93	0.5	8.7	5
6.8	0.28	0.36	8	0.045	28	123	0.9928	3.02	0.37	11.4	6
6.6	0.15	0.34	5.1	0.055	34	125	0.9942	3.36	0.42	9.6	5
6.4	0.29	0.44	3.6	0.2	75	181	0.9942	3.02	0.41	9.1	5
6.4	0.3	0.45	3.5	0.197	76	180	0.9942	3.02	0.39	9.1	6
6.4	0.29	0.44	3.6	0.197	75	183	0.9942	3.01	0.38	9.1	5
6.8	0.26	0.24	7.8	0.052	54	214	0.9961	3.13	0.47	8.9	5
7.1	0.32	0.24	13.1	0.05	52	204	0.998	3.1	0.49	8.8	5
6.8	0.26	0.24	7.8	0.052	54	214	0.9961	3.13	0.47	8.9	5
6.8	0.27	0.26	16.1	0.049	55	196	0.9984	3.15	0.5	9.3	5
7.1	0.32	0.24	13.1	0.05	52	204	0.998	3.1	0.49	8.8	5
6.9	0.54	0.32	13.2	0.05	53	236	0.9973	3.2	0.5	9.6	5
6.8	0.26	0.34	13.9	0.034	39	134	0.9949	3.33	0.53	12	6
5.8	0.28	0.35	2.3	0.053	36	114	0.9924	3.28	0.5	10.2	4
6.4	0.21	0.5	11.6	0.042	45	153	0.9972	3.15	0.43	8.8	5
7	0.16	0.32	8.3	0.045	38	126	0.9958	3.21	0.34	9.2	5
10.2	0.44	0.88	6.2	0.049	20	124	0.9968	2.99	0.51	9.9	4
6.8	0.57	0.29	2.2	0.04	15	77	0.9938	3.32	0.74	10.2	5
6.1	0.4	0.31	0.9	0.048	23	170	0.993	3.22	0.77	9.5	6
5.6	0.245	0.25	9.7	0.032	12	68	0.994	3.31	0.34	10.5	5
6.8	0.18	0.38	1.4	0.038	35	111	0.9918	3.32	0.59	11.2	7
7	0.16	0.32	8.3	0.045	38	126	0.9958	3.21	0.34	9.2	5
6.7	0.13	0.29	5.3	0.051	31	122	0.9944	3.44	0.37	9.7	6
6.2	0.25	0.25	1.4	0.03	35	105	0.9912	3.3	0.44	11.1	7
5.8	0.26	0.24	9.2	0.044	55	152	0.9961	3.31	0.38	9.4	5
7.5	0.27	0.36	7	0.036	45	164	0.9939	3.03	0.33	11	5
5.8	0.26	0.24	9.2	0.044	55	152	0.9961	3.31	0.38	9.4	5
5.7	0.28	0.24	17.5	0.044	60	167	0.9989	3.31	0.44	9.4	5
7.5	0.23	0.36	7	0.036	43	161	0.9938	3.04	0.32	11	5
7.5	0.27	0.36	7	0.036	45	164	0.9939	3.03	0.33	11	5
7.2	0.685	0.21	9.5	0.07	33	172	0.9971	3	0.55	9.1	6
6.2	0.25	0.25	1.4	0.03	35	105	0.9912	3.3	0.44	11.1	7
6.5	0.19	0.3	0.8	0.043	33	144	0.9936	3.42	0.39	9.1	6
6.3	0.495	0.22	1.8	0.046	31	140	0.9929	3.39	0.54	10.4	6
7.1	0.24	0.41	17.8	0.046	39	145	0.9998	3.32	0.39	8.7	5
6.4	0.17	0.32	2.4	0.048	41	200	0.9938	3.5	0.5	9.7	6
7.1	0.25	0.32	10.3	0.041	66	272	0.9969	3.17	0.52	9.1	6
6.4	0.17	0.32	2.4	0.048	41	200	0.9938	3.5	0.5	9.7	6
7.1	0.24	0.41	17.8	0.046	39	145	0.9998	3.32	0.39	8.7	5
6.8	0.64	0.08	9.7	0.062	26	142	0.9972	3.37	0.46	8.9	4
8.3	0.28	0.4	7.8	0.041	38	194	0.9976	3.34	0.51	9.6	6
8.2	0.27	0.39	7.8	0.039	49	208	0.9976	3.31	0.51	9.5	6
7.2	0.23	0.38	14.3	0.058	55	194	0.9979	3.09	0.44	9	6
7.2	0.23	0.38	14.3	0.058	55	194	0.9979	3.09	0.44	9	6
7.2	0.23	0.38	14.3	0.058	55	194	0.9979	3.09	0.44	9	6
7.2	0.23	0.38	14.3	0.058	55	194	0.9979	3.09	0.44	9	6
6.8	0.52	0.32	13.2	0.044	54	221	0.9972	3.27	0.5	9.6	6
7	0.26	0.59	1.4	0.037	40	120	0.9918	3.34	0.41	11.1	7
6.2	0.25	0.21	15.55	0.039	28	159	0.9982	3.48	0.64	9.6	6
7.3	0.32	0.23	13.7	0.05	49	197	0.9985	3.2	0.46	8.7	5
7.7	0.31	0.26	7.8	0.031	23	90	0.9944	3.13	0.5	10.4	5
7.1	0.21	0.37	2.4	0.026	23	100	0.9903	3.15	0.38	11.4	7
6.8	0.24	0.34	2.7	0.047	64.5	218.5	0.9934	3.3	0.58	9.7	6
6.9	0.4	0.56	11.2	0.043	40	142	0.9975	3.14	0.46	8.7	5
6.1	0.18	0.36	2	0.038	20	249.5	0.9923	3.37	0.79	11.3	6
6.8	0.21	0.27	2.1	0.03	26	139	0.99	3.16	0.61	12.6	7
5.8	0.2	0.27	1.4	0.031	12	77	0.9905	3.25	0.36	10.9	7
5.6	0.19	0.26	1.4	0.03	12	76	0.9905	3.25	0.37	10.9	7
6.1	0.41	0.14	10.4	0.037	18	119	0.996	3.38	0.45	10	5
5.9	0.21	0.28	4.6	0.053	40	199	0.9964	3.72	0.7	10	4
8.5	0.26	0.21	16.2	0.074	41	197	0.998	3.02	0.5	9.8	3
6.9	0.4	0.56	11.2	0.043	40	142	0.9975	3.14	0.46	8.7	5
5.8	0.24	0.44	3.5	0.029	5	109	0.9913	3.53	0.43	11.7	3
5.8	0.24	0.39	1.5	0.054	37	158	0.9932	3.21	0.52	9.3	6
6.7	0.26	0.39	1.1	0.04	45	147	0.9935	3.32	0.58	9.6	8
6.3	0.35	0.3	5.7	0.035	8	97	0.9927	3.27	0.41	11	7
6.3	0.35	0.3	5.7	0.035	8	97	0.9927	3.27	0.41	11	7
6.4	0.23	0.39	1.8	0.032	23	118	0.9912	3.32	0.5	11.8	6
5.8	0.36	0.38	0.9	0.037	3	75	0.9904	3.28	0.34	11.4	4
6.9	0.115	0.35	5.4	0.048	36	108	0.9939	3.32	0.42	10.2	6
6.9	0.29	0.4	19.45	0.043	36	156	0.9996	2.93	0.47	8.9	5
6.9	0.28	0.4	8.2	0.036	15	95	0.9944	3.17	0.33	10.2	5
7.2	0.29	0.4	13.6	0.045	66	231	0.9977	3.08	0.59	9.6	6
6.2	0.24	0.35	1.2	0.038	22	167	0.9912	3.1	0.48	10.6	6
6.9	0.29	0.4	19.45	0.043	36	156	0.9996	2.93	0.47	8.9	5
6.9	0.32	0.26	8.3	0.053	32	180	0.9965	3.25	0.51	9.2	6
5.3	0.58	0.07	6.9	0.043	34	149	0.9944	3.34	0.57	9.7	5
5.3	0.585	0.07	7.1	0.044	34	145	0.9945	3.34	0.57	9.7	6
5.4	0.59	0.07	7	0.045	36	147	0.9944	3.34	0.57	9.7	6
6.9	0.32	0.26	8.3	0.053	32	180	0.9965	3.25	0.51	9.2	6
5.2	0.6	0.07	7	0.044	33	147	0.9944	3.33	0.58	9.7	5
5.8	0.25	0.26	13.1	0.051	44	148	0.9972	3.29	0.38	9.3	5
6.6	0.58	0.3	5.1	0.057	30	123	0.9949	3.24	0.38	9	5
7	0.29	0.54	10.7	0.046	59	234	0.9966	3.05	0.61	9.5	5
6.6	0.19	0.41	8.9	0.046	51	169	0.9954	3.14	0.57	9.8	6
6.7	0.2	0.41	9.1	0.044	50	166	0.9954	3.14	0.58	9.8	6
7.7	0.26	0.4	1.1	0.042	9	60	0.9915	2.89	0.5	10.6	5
6.8	0.32	0.34	1.2	0.044	14	67	0.9919	3.05	0.47	10.6	4
7	0.3	0.49	4.7	0.036	17	105	0.9916	3.26	0.68	12.4	7
7	0.24	0.36	2.8	0.034	22	112	0.99	3.19	0.38	12.6	8
6.1	0.31	0.58	5	0.039	36	114	0.9909	3.3	0.6	12.3	8
6.8	0.44	0.37	5.1	0.047	46	201	0.9938	3.08	0.65	10.5	4
6.7	0.34	0.3	15.6	0.054	51	196	0.9982	3.19	0.49	9.3	5
7.1	0.35	0.24	15.4	0.055	46	198	0.9988	3.12	0.49	8.8	5
7.3	0.32	0.25	7.2	0.056	47	180	0.9961	3.08	0.47	8.8	5
6.5	0.28	0.33	15.7	0.053	51	190	0.9978	3.22	0.51	9.7	6
7.2	0.23	0.39	14.2	0.058	49	192	0.9979	2.98	0.48	9	7
7.2	0.23	0.39	14.2	0.058	49	192	0.9979	2.98	0.48	9	7
7.2	0.23	0.39	14.2	0.058	49	192	0.9979	2.98	0.48	9	7
7.2	0.23	0.39	14.2	0.058	49	192	0.9979	2.98	0.48	9	7
5.9	0.15	0.31	5.8	0.041	53	155	0.9945	3.52	0.46	10.5	6
7.4	0.28	0.42	19.8	0.066	53	195	1	2.96	0.44	9.1	5
6.2	0.28	0.22	7.3	0.041	26	157	0.9957	3.44	0.64	9.8	7
9.1	0.59	0.38	1.6	0.066	34	182	0.9968	3.23	0.38	8.5	3
6.3	0.33	0.27	1.2	0.046	34	175	0.9934	3.37	0.54	9.4	6
8.3	0.39	0.7	10.6	0.045	33	169	0.9976	3.09	0.57	9.4	5
7.2	0.19	0.46	3.8	0.041	82	187	0.9932	3.19	0.6	11.2	7

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	13 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 & 13 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154771&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]13 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=154771&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154771&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	13 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Multiple Linear Regression - Estimated Regression Equation
alcohol[t] = + 754.716059969812 + 0.471444132974329fixedAcidity[t] + 0.182545365196075volatileAcidity[t] + 0.372030078236447citricAcid[t] + 0.242856516388964residualSugar[t] + 1.55090379874483chlorides[t] -0.00171280477621307freeSulfurDioxide[t] + 0.00124058061391121totSulfurDioxide[t] -761.47834697612density[t] + 2.0765040080465pH[t] + 1.60415362635667sulphates[t] + 0.00363114910233295quality[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
alcohol[t] =  +  754.716059969812 +  0.471444132974329fixedAcidity[t] +  0.182545365196075volatileAcidity[t] +  0.372030078236447citricAcid[t] +  0.242856516388964residualSugar[t] +  1.55090379874483chlorides[t] -0.00171280477621307freeSulfurDioxide[t] +  0.00124058061391121totSulfurDioxide[t] -761.47834697612density[t] +  2.0765040080465pH[t] +  1.60415362635667sulphates[t] +  0.00363114910233295quality[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154771&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]alcohol[t] =  +  754.716059969812 +  0.471444132974329fixedAcidity[t] +  0.182545365196075volatileAcidity[t] +  0.372030078236447citricAcid[t] +  0.242856516388964residualSugar[t] +  1.55090379874483chlorides[t] -0.00171280477621307freeSulfurDioxide[t] +  0.00124058061391121totSulfurDioxide[t] -761.47834697612density[t] +  2.0765040080465pH[t] +  1.60415362635667sulphates[t] +  0.00363114910233295quality[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154771&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154771&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
alcohol[t] = + 754.716059969812 + 0.471444132974329fixedAcidity[t] + 0.182545365196075volatileAcidity[t] + 0.372030078236447citricAcid[t] + 0.242856516388964residualSugar[t] + 1.55090379874483chlorides[t] -0.00171280477621307freeSulfurDioxide[t] + 0.00124058061391121totSulfurDioxide[t] -761.47834697612density[t] + 2.0765040080465pH[t] + 1.60415362635667sulphates[t] + 0.00363114910233295quality[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)	754.716059969812	19.764355	38.1857	0	0
fixedAcidity	0.471444132974329	0.033386	14.1212	0	0
volatileAcidity	0.182545365196075	0.178686	1.0216	0.307836	0.153918
citricAcid	0.372030078236447	0.167355	2.223	0.026997	0.013499
residualSugar	0.242856516388964	0.009673	25.1079	0	0
chlorides	1.55090379874483	1.010435	1.5349	0.125917	0.062959
freeSulfurDioxide	-0.00171280477621307	0.001756	-0.9754	0.33021	0.165105
totSulfurDioxide	0.00124058061391121	0.000679	1.8263	0.068841	0.034421
density	-761.47834697612	20.213	-37.6727	0	0
pH	2.0765040080465	0.167193	12.4198	0	0
sulphates	1.60415362635667	0.209823	7.6453	0	0
quality	0.00363114910233295	0.023434	0.1549	0.876971	0.438485

\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) & 754.716059969812 & 19.764355 & 38.1857 & 0 & 0 \tabularnewline
fixedAcidity & 0.471444132974329 & 0.033386 & 14.1212 & 0 & 0 \tabularnewline
volatileAcidity & 0.182545365196075 & 0.178686 & 1.0216 & 0.307836 & 0.153918 \tabularnewline
citricAcid & 0.372030078236447 & 0.167355 & 2.223 & 0.026997 & 0.013499 \tabularnewline
residualSugar & 0.242856516388964 & 0.009673 & 25.1079 & 0 & 0 \tabularnewline
chlorides & 1.55090379874483 & 1.010435 & 1.5349 & 0.125917 & 0.062959 \tabularnewline
freeSulfurDioxide & -0.00171280477621307 & 0.001756 & -0.9754 & 0.33021 & 0.165105 \tabularnewline
totSulfurDioxide & 0.00124058061391121 & 0.000679 & 1.8263 & 0.068841 & 0.034421 \tabularnewline
density & -761.47834697612 & 20.213 & -37.6727 & 0 & 0 \tabularnewline
pH & 2.0765040080465 & 0.167193 & 12.4198 & 0 & 0 \tabularnewline
sulphates & 1.60415362635667 & 0.209823 & 7.6453 & 0 & 0 \tabularnewline
quality & 0.00363114910233295 & 0.023434 & 0.1549 & 0.876971 & 0.438485 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154771&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]754.716059969812[/C][C]19.764355[/C][C]38.1857[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]fixedAcidity[/C][C]0.471444132974329[/C][C]0.033386[/C][C]14.1212[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]volatileAcidity[/C][C]0.182545365196075[/C][C]0.178686[/C][C]1.0216[/C][C]0.307836[/C][C]0.153918[/C][/ROW]
[ROW][C]citricAcid[/C][C]0.372030078236447[/C][C]0.167355[/C][C]2.223[/C][C]0.026997[/C][C]0.013499[/C][/ROW]
[ROW][C]residualSugar[/C][C]0.242856516388964[/C][C]0.009673[/C][C]25.1079[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]chlorides[/C][C]1.55090379874483[/C][C]1.010435[/C][C]1.5349[/C][C]0.125917[/C][C]0.062959[/C][/ROW]
[ROW][C]freeSulfurDioxide[/C][C]-0.00171280477621307[/C][C]0.001756[/C][C]-0.9754[/C][C]0.33021[/C][C]0.165105[/C][/ROW]
[ROW][C]totSulfurDioxide[/C][C]0.00124058061391121[/C][C]0.000679[/C][C]1.8263[/C][C]0.068841[/C][C]0.034421[/C][/ROW]
[ROW][C]density[/C][C]-761.47834697612[/C][C]20.213[/C][C]-37.6727[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]pH[/C][C]2.0765040080465[/C][C]0.167193[/C][C]12.4198[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]sulphates[/C][C]1.60415362635667[/C][C]0.209823[/C][C]7.6453[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]quality[/C][C]0.00363114910233295[/C][C]0.023434[/C][C]0.1549[/C][C]0.876971[/C][C]0.438485[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154771&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154771&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)	754.716059969812	19.764355	38.1857	0	0
fixedAcidity	0.471444132974329	0.033386	14.1212	0	0
volatileAcidity	0.182545365196075	0.178686	1.0216	0.307836	0.153918
citricAcid	0.372030078236447	0.167355	2.223	0.026997	0.013499
residualSugar	0.242856516388964	0.009673	25.1079	0	0
chlorides	1.55090379874483	1.010435	1.5349	0.125917	0.062959
freeSulfurDioxide	-0.00171280477621307	0.001756	-0.9754	0.33021	0.165105
totSulfurDioxide	0.00124058061391121	0.000679	1.8263	0.068841	0.034421
density	-761.47834697612	20.213	-37.6727	0	0
pH	2.0765040080465	0.167193	12.4198	0	0
sulphates	1.60415362635667	0.209823	7.6453	0	0
quality	0.00363114910233295	0.023434	0.1549	0.876971	0.438485

Multiple Linear Regression - Regression Statistics
Multiple R	0.959830378064218
R-squared	0.9212743546549
Adjusted R-squared	0.91824644521855
F-TEST (value)	304.260868437813
F-TEST (DF numerator)	11
F-TEST (DF denominator)	286
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.312586283919976
Sum Squared Residuals	27.9451128799414

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.959830378064218 \tabularnewline
R-squared & 0.9212743546549 \tabularnewline
Adjusted R-squared & 0.91824644521855 \tabularnewline
F-TEST (value) & 304.260868437813 \tabularnewline
F-TEST (DF numerator) & 11 \tabularnewline
F-TEST (DF denominator) & 286 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.312586283919976 \tabularnewline
Sum Squared Residuals & 27.9451128799414 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154771&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.959830378064218[/C][/ROW]
[ROW][C]R-squared[/C][C]0.9212743546549[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.91824644521855[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]304.260868437813[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]11[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]286[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.312586283919976[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]27.9451128799414[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154771&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154771&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	0.959830378064218
R-squared	0.9212743546549
Adjusted R-squared	0.91824644521855
F-TEST (value)	304.260868437813
F-TEST (DF numerator)	11
F-TEST (DF denominator)	286
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.312586283919976
Sum Squared Residuals	27.9451128799414

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	8.8	8.16347275454783	0.636527245452176
2	9.5	9.22256243405778	0.277437565942221
3	10.1	10.3068039902424	-0.20680399024237
4	9.9	9.73562564699591	0.164374353004093
5	9.9	9.7356256469959	0.164374353004095
6	10.1	10.3068039902424	-0.20680399024237
7	9.6	9.42828846755214	0.171711532447862
8	8.8	8.16347275454793	0.636527245452074
9	9.5	9.22256243405778	0.277437565942221
10	11	9.95230897559305	1.04769102440695
11	12	11.8516971042345	0.148302895765465
12	9.7	10.0877296017907	-0.387729601790664
13	10.8	11.2756156316249	-0.475615631624878
14	12.4	11.9663880726033	0.433611927396679
15	9.7	9.46683091122643	0.23316908877357
16	11.4	11.2316029526606	0.168397047339363
17	9.6	9.53003037451511	0.0699696254848848
18	12.8	12.6328908353132	0.16710916468679
19	11.3	11.1170123334868	0.182987666513251
20	9.5	9.34042665750142	0.159573342498581
21	12.8	12.6328908353132	0.16710916468679
22	11	11.1805290832572	-0.1805290832572
23	10.5	10.5520839990232	-0.0520839990231735
24	9.3	9.60665199479784	-0.306651994797836
25	10	8.7048085983017	1.2951914016983
26	10.4	10.1667375913654	0.233262408634589
27	10	10.3312807894354	-0.331280789435379
28	10.5	9.90642367430835	0.593576325691651
29	11.6	11.409518611459	0.190481388541014
30	12.3	12.198827372486	0.101172627514031
31	10	9.66638947584319	0.333610524156808
32	10.2	10.5760180012219	-0.376018001221921
33	10.8	10.9958179607168	-0.195817960716757
34	9	9.40120192866265	-0.401201928662648
35	10.2	10.4822379540554	-0.282237954055368
36	12.8	12.0938840477947	0.706115952205271
37	10	10.3246467335986	-0.324646733598632
38	11.2	11.3251547010407	-0.125154701040685
39	8.6	8.76098081634356	-0.160980816343561
40	8.6	8.76098081634356	-0.160980816343561
41	9.4	9.39999088065615	9.11934384936096e-06
42	9.4	9.44642115144093	-0.0464211514409328
43	9.8	9.50777925996113	0.292220740038869
44	9.5	9.68616253659106	-0.186162536591058
45	9.5	9.77642514823915	-0.276425148239153
46	10	10.1382017172362	-0.138201717236216
47	9.8	9.861191040092	-0.0611910400919964
48	9.8	9.90515119338696	-0.105151193386958
49	9.8	9.50777925996113	0.292220740038869
50	9.8	9.67763682177239	0.122363178227608
51	11.7	11.432546851704	0.267453148296019
52	11	11.4024698893777	-0.402469889377747
53	10.9	11.2445733383179	-0.344573338317882
54	10.9	11.0314808637678	-0.131480863767785
55	9.1	9.53981462582532	-0.439814625825317
56	11	11.5910077757847	-0.591007775784732
57	9.6	10.0883656179811	-0.488365617981148
58	8.9	8.96426332645212	-0.0642633264521203
59	10.2	10.0572342646349	0.142765735365094
60	9.9	10.4887350431502	-0.588735043150182
61	8.6	8.78961625635363	-0.189616256353632
62	8.9	8.96426332645212	-0.0642633264521203
63	10.5	10.8172093496776	-0.317209349677577
64	10.2	10.0572342646349	0.142765735365094
65	10.3	10.1330342350189	0.166965764981104
66	9.1	9.32210109593979	-0.222101095939796
67	12.6	12.9997447746703	-0.399744774670274
68	9.8	10.226477281108	-0.426477281108007
69	10.7	10.8081609257808	-0.108160925780824
70	9.5	9.47547203609418	0.0245279639058235
71	9	9.19911767717135	-0.199117677171352
72	9.5	9.07784085314133	0.422159146858674
73	10	9.24023809439839	0.759761905601614
74	9.1	9.33199493241625	-0.231994932416246
75	10.7	10.8081609257808	-0.108160925780824
76	9.5	9.47547203609418	0.0245279639058235
77	12.7	12.3687139742039	0.331286025796081
78	12	11.7972776865352	0.202722313464836
79	9.3	9.18167794643633	0.118322053563668
80	9	9.3833033474705	-0.383303347470498
81	10.6	10.8072402921025	-0.207240292102464
82	9.2	9.62187288465302	-0.421872884653018
83	10	9.80992391087582	0.190076089124176
84	9.5	9.34368475687876	0.156315243121243
85	8.7	9.10349133867625	-0.403491338676248
86	8.7	9.0714799477712	-0.371479947771198
87	8.7	8.90052573053618	-0.200525730536185
88	9.7	9.65471228853888	0.0452877114611221
89	8.7	9.10349133867625	-0.403491338676248
90	8.7	9.0714799477712	-0.371479947771198
91	8.7	8.90052573053618	-0.200525730536185
92	9	8.93548667186321	0.0645133281367908
93	12.6	12.2638792047582	0.336120795241812
94	12.6	12.350849117747	0.24915088225305
95	11.5	11.2880130649426	0.211986935057384
96	9.2	9.38020935480103	-0.180209354801031
97	8.8	9.40885637087478	-0.608856370874783
98	11.4	11.2456126051405	0.154387394859508
99	10.1	10.6471323968508	-0.547132396850812
100	8.8	9.40885637087478	-0.608856370874783
101	9.1	9.28762110931969	-0.187621109319689
102	9.4	9.86203740109567	-0.462037401095671
103	9.4	9.18309362083297	0.216906379167027
104	9	8.75987253446172	0.240127465538276
105	9.1	9.28762110931969	-0.187621109319689
106	9.2	9.68315073290269	-0.483150732902694
107	9.4	9.86203740109567	-0.462037401095671
108	9.1	9.22717051652803	-0.127170516528027
109	9.1	9.22717051652803	-0.127170516528027
110	10.3	10.5481182273215	-0.248118227321526
111	8.8	8.5886430622981	0.211356937701901
112	8.9	8.89089817282215	0.00910182717784492
113	9.2	8.71004566774482	0.489954332255183
114	9.1	9.00376021263033	0.0962397873696651
115	9.1	9.00376021263033	0.0962397873696651
116	9.7	9.26112679171265	0.438873208287349
117	11.3	11.3614070825803	-0.0614070825803359
118	11.8	11.3541089849535	0.445891015046483
119	9.2	8.71004566774482	0.489954332255183
120	9.2	8.88827971050881	0.311720289491189
121	10.2	10.1757903350147	0.0242096649853132
122	8.8	8.57673949589614	0.223260504103863
123	9.7	9.78578796456735	-0.085787964567347
124	9.1	9.1769865096044	-0.0769865096043997
125	9.8	9.85979776478957	-0.059797764789574
126	11	11.2249233208218	-0.224923320821836
127	10.5	10.5219693827503	-0.0219693827502639
128	9.7	9.7930363619903	-0.0930363619903005
129	10.9	10.8459070509595	0.0540929490405465
130	10.9	10.8497728057419	0.0502271942580517
131	10.6	10.9007744305325	-0.300774430532542
132	9.7	9.7930363619903	-0.0930363619903005
133	9	9.20550861190603	-0.205508611906031
134	9.2	9.47416611328515	-0.27416611328515
135	8.9	9.19829804766415	-0.298298047664147
136	9.6	9.86137499242657	-0.26137499242657
137	10.7	10.9179884074864	-0.217988407486424
138	8.7	8.81934680347515	-0.119346803475153
139	10.8	10.9484870624104	-0.148487062410397
140	11.8	11.252631875406	0.547368124594005
141	10.2	10.1754309043109	0.0245690956890568
142	8.7	8.81934680347515	-0.119346803475153
143	10.8	11.2142713086692	-0.414271308669209
144	9.7	10.1287870072609	-0.428787007260905
145	11.2	11.2426165701738	-0.0426165701738322
146	10.9	10.9102050910513	-0.0102050910513273
147	10.1	10.2037126259524	-0.103712625952444
148	9	9.20495205070559	-0.204952050705595
149	12	11.9239012184277	0.0760987815722663
150	9.4	9.2408785782171	0.159121421782896
151	11.5	11.3061700816258	0.19382991837418
152	9.9	9.32377853751317	0.576221462486828
153	9.4	9.2408785782171	0.159121421782896
154	10.4	10.6617058477945	-0.261705847794529
155	9.7	9.57790556286348	0.122094437136524
156	8.9	8.88796684025449	0.0120331597455094
157	8.9	8.88796684025449	0.0120331597455094
158	12.4	12.0680265588568	0.331973441143199
159	12.1	11.8613776308506	0.238622369149387
160	12.1	11.8613776308506	0.238622369149387
161	12.4	12.0680265588568	0.331973441143199
162	9.1	8.63193388809268	0.468066111907317
163	10.6	10.3410736021129	0.258926397887073
164	8.9	8.88796684025449	0.0120331597455094
165	9.5	9.6197303994207	-0.1197303994207
166	9.8	9.54431287762572	0.255687122374277
167	9.6	9.25145868642761	0.348541313572388
168	12.6	12.3079209085889	0.292079091411105
169	9.3	9.07051033779842	0.229489662201578
170	10	10.3270121045615	-0.327012104561518
171	12.7	11.9174529113243	0.782547088675659
172	11	11.1554069360293	-0.15540693602931
173	11.4	11.809276259924	-0.409276259924046
174	11.5	11.4352535836562	0.0647464163437803
175	10.2	9.69660468448691	0.503395315513086
176	11.4	11.1382502069413	0.261749793058706
177	12.6	12.0376217050065	0.562378294993524
178	9.4	9.08954271209284	0.310457287907157
179	8.7	9.00588122739707	-0.305881227397075
180	9.2	9.52351461064851	-0.32351461064851
181	9.3	9.4191815814404	-0.119181581440402
182	9.2	9.19680776606393	0.00319223393607005
183	8.7	8.32861786291824	0.371382137081759
184	9.6	9.49288877631313	0.107111223686871
185	9.3	9.4110145334662	-0.111014533466195
186	9.3	9.26573193793009	0.0342680620699112
187	9.9	10.0414417661109	-0.14144176611093
188	11	10.4626425324884	0.537357467511574
189	12.7	12.6074848106726	0.092515189327444
190	8.9	8.9533669790534	-0.0533669790534021
191	8.9	9.03109752165049	-0.13109752165049
192	8.7	8.32861786291824	0.371382137081759
193	11.4	11.1148622510635	0.285137748936535
194	9.6	10.0093496076432	-0.409349607643152
195	9.1	9.11561103578885	-0.0156110357888537
196	9.1	9.06081311837312	0.0391868816268766
197	9.1	9.04454983674928	0.0554501632507235
198	8.9	8.96953377876625	-0.0695337787662456
199	8.8	8.91995636627874	-0.119956366278741
200	8.9	8.96953377876625	-0.0695337787662456
201	9.3	9.30406744369506	-0.00406744369506227
202	8.8	8.91995636627874	-0.119956366278741
203	9.6	9.7145881327453	-0.114588132745298
204	12	11.8156460753798	0.184353924620178
205	10.2	10.288715294649	-0.0887152946490209
206	8.8	8.85537998091907	-0.0553799809190726
207	9.2	9.29016004240908	-0.0901600424090756
208	9.9	9.63355080814836	0.266449191851642
209	10.2	10.1420142893824	0.057985710617622
210	9.5	10.0400646384194	-0.540064638419385
211	10.5	10.4903405543074	0.00965944569263113
212	11.2	11.2044368768407	-0.00443687684065584
213	9.2	9.29016004240908	-0.0901600424090756
214	9.7	10.0152740893276	-0.315274089327573
215	11.1	11.0408678324469	0.0591321675531039
216	9.4	8.97644963058407	0.423550369415932
217	11	10.3233207281407	0.676679271859254
218	9.4	8.97644963058407	0.423550369415932
219	9.4	8.9228197419948	0.477180258005196
220	11	10.3965941197581	0.603405880241902
221	11	10.3233207281407	0.676679271859254
222	9.1	8.74970874176077	0.350291258239234
223	11.1	11.0408678324469	0.0591321675531039
224	9.1	9.45399956518719	-0.353999565187193
225	10.4	10.3429599501956	0.0570400498043911
226	8.7	8.97864656264394	-0.278646562643939
227	9.7	10.0530214176837	-0.353021417683704
228	9.1	9.33810165190512	-0.238101651905123
229	9.7	10.0530214176837	-0.353021417683704
230	8.7	8.97864656264394	-0.278646562643939
231	8.9	9.0560114485733	-0.156011448573295
232	9.6	9.08705463578663	0.512945364213374
233	9.5	8.9674948162724	0.532505183727605
234	9	9.26785299965223	-0.267852999652233
235	9	9.26785299965223	-0.267852999652233
236	9	9.26785299965223	-0.267852999652233
237	9	9.26785299965223	-0.267852999652233
238	9.6	9.85930013972978	-0.259300139729784
239	11.1	11.145288374343	-0.0452883743429824
240	9.6	9.9159673257792	-0.315967325779199
241	8.7	8.93147977048173	-0.231479770481731
242	10.4	10.6197351390818	-0.219735139081779
243	11.4	12.0311186958335	-0.631118695833451
244	9.7	10.3334465555259	-0.633446555525917
245	8.7	8.84634947047622	-0.14634947047622
246	11.3	11.2504973817805	0.0495026182195186
247	12.6	12.447237216245	0.152762783754994
248	10.9	11.1576900213966	-0.257690021396588
249	10.9	11.0711054922183	-0.171105492218307
250	10	9.74486164607431	0.255138353925685
251	10	9.1427866485857	0.857213351414296
252	9.8	10.2007571258158	-0.400757125815754
253	8.7	8.84634947047622	-0.14634947047622
254	11.7	11.8568266413104	-0.156826641310438
255	9.3	9.44124052868172	-0.14124052868172
256	9.6	9.82647052354008	-0.226470523540082
257	11	10.9605896601922	0.0394103398078283
258	11	10.9605896601922	0.0394103398078283
259	11.8	11.4546637307794	0.345336269220582
260	11.4	11.224098269895	0.175901730104998
261	10.2	10.3346137017458	-0.134613701745796
262	8.9	8.77540144161934	0.124598558380663
263	10.2	10.2243441933693	-0.024344193369334
264	9.6	9.49529931571738	0.104700684282617
265	10.6	10.7844979682266	-0.184497968226646
266	8.9	8.77540144161934	0.124598558380663
267	9.2	9.16593907806879	0.0340609219312132
268	9.7	9.86962073373342	-0.169620733733425
269	9.7	9.84317665958494	-0.143176659584942
270	9.7	9.94370243824129	-0.243702438241289
271	9.2	9.16593907806879	0.0340609219312132
272	9.7	9.84647192290905	-0.146471922909047
273	9.3	9.07478378725305	0.225216212746947
274	9	9.23405330811937	-0.234053308119369
275	9.5	9.56985606647872	-0.0698560664787236
276	9.8	9.85070731654765	-0.050707316547651
277	9.8	9.95917927837539	-0.159179278375394
278	10.6	10.7493014565044	-0.149301456504377
279	10.6	10.3170336983017	0.282966301698252
280	12.4	12.355345409924	0.0446545900759643
281	12.6	12.4270147653152	0.172985234684768
282	12.3	12.5138793142294	-0.213879314229424
283	10.5	10.3175551329418	0.182444867058194
284	9.3	9.39707418244841	-0.0970741824484075
285	8.8	8.92693798147679	-0.126937981476792
286	8.8	8.94640326546733	-0.146403265467326
287	9.7	9.72088548110683	-0.0208854811068321
288	9	9.09446516949664	-0.0944651694966416
289	9	9.09446516949664	-0.0944651694966416
290	9	9.09446516949664	-0.0944651694966416
291	9	9.09446516949664	-0.0944651694966416
292	10.5	9.99273327952431	0.507266720475693
293	9.1	8.86625335953373	0.233746640466266
294	9.8	9.74991083945132	0.0500891605486793
295	8.5	8.19971866686954	0.30028133313046
296	9.4	9.80174021252601	-0.401740212526006
297	9.4	9.45598708551393	-0.0559870855139323
298	11.2	10.7059193722972	0.494080627702763

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 8.8 & 8.16347275454783 & 0.636527245452176 \tabularnewline
2 & 9.5 & 9.22256243405778 & 0.277437565942221 \tabularnewline
3 & 10.1 & 10.3068039902424 & -0.20680399024237 \tabularnewline
4 & 9.9 & 9.73562564699591 & 0.164374353004093 \tabularnewline
5 & 9.9 & 9.7356256469959 & 0.164374353004095 \tabularnewline
6 & 10.1 & 10.3068039902424 & -0.20680399024237 \tabularnewline
7 & 9.6 & 9.42828846755214 & 0.171711532447862 \tabularnewline
8 & 8.8 & 8.16347275454793 & 0.636527245452074 \tabularnewline
9 & 9.5 & 9.22256243405778 & 0.277437565942221 \tabularnewline
10 & 11 & 9.95230897559305 & 1.04769102440695 \tabularnewline
11 & 12 & 11.8516971042345 & 0.148302895765465 \tabularnewline
12 & 9.7 & 10.0877296017907 & -0.387729601790664 \tabularnewline
13 & 10.8 & 11.2756156316249 & -0.475615631624878 \tabularnewline
14 & 12.4 & 11.9663880726033 & 0.433611927396679 \tabularnewline
15 & 9.7 & 9.46683091122643 & 0.23316908877357 \tabularnewline
16 & 11.4 & 11.2316029526606 & 0.168397047339363 \tabularnewline
17 & 9.6 & 9.53003037451511 & 0.0699696254848848 \tabularnewline
18 & 12.8 & 12.6328908353132 & 0.16710916468679 \tabularnewline
19 & 11.3 & 11.1170123334868 & 0.182987666513251 \tabularnewline
20 & 9.5 & 9.34042665750142 & 0.159573342498581 \tabularnewline
21 & 12.8 & 12.6328908353132 & 0.16710916468679 \tabularnewline
22 & 11 & 11.1805290832572 & -0.1805290832572 \tabularnewline
23 & 10.5 & 10.5520839990232 & -0.0520839990231735 \tabularnewline
24 & 9.3 & 9.60665199479784 & -0.306651994797836 \tabularnewline
25 & 10 & 8.7048085983017 & 1.2951914016983 \tabularnewline
26 & 10.4 & 10.1667375913654 & 0.233262408634589 \tabularnewline
27 & 10 & 10.3312807894354 & -0.331280789435379 \tabularnewline
28 & 10.5 & 9.90642367430835 & 0.593576325691651 \tabularnewline
29 & 11.6 & 11.409518611459 & 0.190481388541014 \tabularnewline
30 & 12.3 & 12.198827372486 & 0.101172627514031 \tabularnewline
31 & 10 & 9.66638947584319 & 0.333610524156808 \tabularnewline
32 & 10.2 & 10.5760180012219 & -0.376018001221921 \tabularnewline
33 & 10.8 & 10.9958179607168 & -0.195817960716757 \tabularnewline
34 & 9 & 9.40120192866265 & -0.401201928662648 \tabularnewline
35 & 10.2 & 10.4822379540554 & -0.282237954055368 \tabularnewline
36 & 12.8 & 12.0938840477947 & 0.706115952205271 \tabularnewline
37 & 10 & 10.3246467335986 & -0.324646733598632 \tabularnewline
38 & 11.2 & 11.3251547010407 & -0.125154701040685 \tabularnewline
39 & 8.6 & 8.76098081634356 & -0.160980816343561 \tabularnewline
40 & 8.6 & 8.76098081634356 & -0.160980816343561 \tabularnewline
41 & 9.4 & 9.39999088065615 & 9.11934384936096e-06 \tabularnewline
42 & 9.4 & 9.44642115144093 & -0.0464211514409328 \tabularnewline
43 & 9.8 & 9.50777925996113 & 0.292220740038869 \tabularnewline
44 & 9.5 & 9.68616253659106 & -0.186162536591058 \tabularnewline
45 & 9.5 & 9.77642514823915 & -0.276425148239153 \tabularnewline
46 & 10 & 10.1382017172362 & -0.138201717236216 \tabularnewline
47 & 9.8 & 9.861191040092 & -0.0611910400919964 \tabularnewline
48 & 9.8 & 9.90515119338696 & -0.105151193386958 \tabularnewline
49 & 9.8 & 9.50777925996113 & 0.292220740038869 \tabularnewline
50 & 9.8 & 9.67763682177239 & 0.122363178227608 \tabularnewline
51 & 11.7 & 11.432546851704 & 0.267453148296019 \tabularnewline
52 & 11 & 11.4024698893777 & -0.402469889377747 \tabularnewline
53 & 10.9 & 11.2445733383179 & -0.344573338317882 \tabularnewline
54 & 10.9 & 11.0314808637678 & -0.131480863767785 \tabularnewline
55 & 9.1 & 9.53981462582532 & -0.439814625825317 \tabularnewline
56 & 11 & 11.5910077757847 & -0.591007775784732 \tabularnewline
57 & 9.6 & 10.0883656179811 & -0.488365617981148 \tabularnewline
58 & 8.9 & 8.96426332645212 & -0.0642633264521203 \tabularnewline
59 & 10.2 & 10.0572342646349 & 0.142765735365094 \tabularnewline
60 & 9.9 & 10.4887350431502 & -0.588735043150182 \tabularnewline
61 & 8.6 & 8.78961625635363 & -0.189616256353632 \tabularnewline
62 & 8.9 & 8.96426332645212 & -0.0642633264521203 \tabularnewline
63 & 10.5 & 10.8172093496776 & -0.317209349677577 \tabularnewline
64 & 10.2 & 10.0572342646349 & 0.142765735365094 \tabularnewline
65 & 10.3 & 10.1330342350189 & 0.166965764981104 \tabularnewline
66 & 9.1 & 9.32210109593979 & -0.222101095939796 \tabularnewline
67 & 12.6 & 12.9997447746703 & -0.399744774670274 \tabularnewline
68 & 9.8 & 10.226477281108 & -0.426477281108007 \tabularnewline
69 & 10.7 & 10.8081609257808 & -0.108160925780824 \tabularnewline
70 & 9.5 & 9.47547203609418 & 0.0245279639058235 \tabularnewline
71 & 9 & 9.19911767717135 & -0.199117677171352 \tabularnewline
72 & 9.5 & 9.07784085314133 & 0.422159146858674 \tabularnewline
73 & 10 & 9.24023809439839 & 0.759761905601614 \tabularnewline
74 & 9.1 & 9.33199493241625 & -0.231994932416246 \tabularnewline
75 & 10.7 & 10.8081609257808 & -0.108160925780824 \tabularnewline
76 & 9.5 & 9.47547203609418 & 0.0245279639058235 \tabularnewline
77 & 12.7 & 12.3687139742039 & 0.331286025796081 \tabularnewline
78 & 12 & 11.7972776865352 & 0.202722313464836 \tabularnewline
79 & 9.3 & 9.18167794643633 & 0.118322053563668 \tabularnewline
80 & 9 & 9.3833033474705 & -0.383303347470498 \tabularnewline
81 & 10.6 & 10.8072402921025 & -0.207240292102464 \tabularnewline
82 & 9.2 & 9.62187288465302 & -0.421872884653018 \tabularnewline
83 & 10 & 9.80992391087582 & 0.190076089124176 \tabularnewline
84 & 9.5 & 9.34368475687876 & 0.156315243121243 \tabularnewline
85 & 8.7 & 9.10349133867625 & -0.403491338676248 \tabularnewline
86 & 8.7 & 9.0714799477712 & -0.371479947771198 \tabularnewline
87 & 8.7 & 8.90052573053618 & -0.200525730536185 \tabularnewline
88 & 9.7 & 9.65471228853888 & 0.0452877114611221 \tabularnewline
89 & 8.7 & 9.10349133867625 & -0.403491338676248 \tabularnewline
90 & 8.7 & 9.0714799477712 & -0.371479947771198 \tabularnewline
91 & 8.7 & 8.90052573053618 & -0.200525730536185 \tabularnewline
92 & 9 & 8.93548667186321 & 0.0645133281367908 \tabularnewline
93 & 12.6 & 12.2638792047582 & 0.336120795241812 \tabularnewline
94 & 12.6 & 12.350849117747 & 0.24915088225305 \tabularnewline
95 & 11.5 & 11.2880130649426 & 0.211986935057384 \tabularnewline
96 & 9.2 & 9.38020935480103 & -0.180209354801031 \tabularnewline
97 & 8.8 & 9.40885637087478 & -0.608856370874783 \tabularnewline
98 & 11.4 & 11.2456126051405 & 0.154387394859508 \tabularnewline
99 & 10.1 & 10.6471323968508 & -0.547132396850812 \tabularnewline
100 & 8.8 & 9.40885637087478 & -0.608856370874783 \tabularnewline
101 & 9.1 & 9.28762110931969 & -0.187621109319689 \tabularnewline
102 & 9.4 & 9.86203740109567 & -0.462037401095671 \tabularnewline
103 & 9.4 & 9.18309362083297 & 0.216906379167027 \tabularnewline
104 & 9 & 8.75987253446172 & 0.240127465538276 \tabularnewline
105 & 9.1 & 9.28762110931969 & -0.187621109319689 \tabularnewline
106 & 9.2 & 9.68315073290269 & -0.483150732902694 \tabularnewline
107 & 9.4 & 9.86203740109567 & -0.462037401095671 \tabularnewline
108 & 9.1 & 9.22717051652803 & -0.127170516528027 \tabularnewline
109 & 9.1 & 9.22717051652803 & -0.127170516528027 \tabularnewline
110 & 10.3 & 10.5481182273215 & -0.248118227321526 \tabularnewline
111 & 8.8 & 8.5886430622981 & 0.211356937701901 \tabularnewline
112 & 8.9 & 8.89089817282215 & 0.00910182717784492 \tabularnewline
113 & 9.2 & 8.71004566774482 & 0.489954332255183 \tabularnewline
114 & 9.1 & 9.00376021263033 & 0.0962397873696651 \tabularnewline
115 & 9.1 & 9.00376021263033 & 0.0962397873696651 \tabularnewline
116 & 9.7 & 9.26112679171265 & 0.438873208287349 \tabularnewline
117 & 11.3 & 11.3614070825803 & -0.0614070825803359 \tabularnewline
118 & 11.8 & 11.3541089849535 & 0.445891015046483 \tabularnewline
119 & 9.2 & 8.71004566774482 & 0.489954332255183 \tabularnewline
120 & 9.2 & 8.88827971050881 & 0.311720289491189 \tabularnewline
121 & 10.2 & 10.1757903350147 & 0.0242096649853132 \tabularnewline
122 & 8.8 & 8.57673949589614 & 0.223260504103863 \tabularnewline
123 & 9.7 & 9.78578796456735 & -0.085787964567347 \tabularnewline
124 & 9.1 & 9.1769865096044 & -0.0769865096043997 \tabularnewline
125 & 9.8 & 9.85979776478957 & -0.059797764789574 \tabularnewline
126 & 11 & 11.2249233208218 & -0.224923320821836 \tabularnewline
127 & 10.5 & 10.5219693827503 & -0.0219693827502639 \tabularnewline
128 & 9.7 & 9.7930363619903 & -0.0930363619903005 \tabularnewline
129 & 10.9 & 10.8459070509595 & 0.0540929490405465 \tabularnewline
130 & 10.9 & 10.8497728057419 & 0.0502271942580517 \tabularnewline
131 & 10.6 & 10.9007744305325 & -0.300774430532542 \tabularnewline
132 & 9.7 & 9.7930363619903 & -0.0930363619903005 \tabularnewline
133 & 9 & 9.20550861190603 & -0.205508611906031 \tabularnewline
134 & 9.2 & 9.47416611328515 & -0.27416611328515 \tabularnewline
135 & 8.9 & 9.19829804766415 & -0.298298047664147 \tabularnewline
136 & 9.6 & 9.86137499242657 & -0.26137499242657 \tabularnewline
137 & 10.7 & 10.9179884074864 & -0.217988407486424 \tabularnewline
138 & 8.7 & 8.81934680347515 & -0.119346803475153 \tabularnewline
139 & 10.8 & 10.9484870624104 & -0.148487062410397 \tabularnewline
140 & 11.8 & 11.252631875406 & 0.547368124594005 \tabularnewline
141 & 10.2 & 10.1754309043109 & 0.0245690956890568 \tabularnewline
142 & 8.7 & 8.81934680347515 & -0.119346803475153 \tabularnewline
143 & 10.8 & 11.2142713086692 & -0.414271308669209 \tabularnewline
144 & 9.7 & 10.1287870072609 & -0.428787007260905 \tabularnewline
145 & 11.2 & 11.2426165701738 & -0.0426165701738322 \tabularnewline
146 & 10.9 & 10.9102050910513 & -0.0102050910513273 \tabularnewline
147 & 10.1 & 10.2037126259524 & -0.103712625952444 \tabularnewline
148 & 9 & 9.20495205070559 & -0.204952050705595 \tabularnewline
149 & 12 & 11.9239012184277 & 0.0760987815722663 \tabularnewline
150 & 9.4 & 9.2408785782171 & 0.159121421782896 \tabularnewline
151 & 11.5 & 11.3061700816258 & 0.19382991837418 \tabularnewline
152 & 9.9 & 9.32377853751317 & 0.576221462486828 \tabularnewline
153 & 9.4 & 9.2408785782171 & 0.159121421782896 \tabularnewline
154 & 10.4 & 10.6617058477945 & -0.261705847794529 \tabularnewline
155 & 9.7 & 9.57790556286348 & 0.122094437136524 \tabularnewline
156 & 8.9 & 8.88796684025449 & 0.0120331597455094 \tabularnewline
157 & 8.9 & 8.88796684025449 & 0.0120331597455094 \tabularnewline
158 & 12.4 & 12.0680265588568 & 0.331973441143199 \tabularnewline
159 & 12.1 & 11.8613776308506 & 0.238622369149387 \tabularnewline
160 & 12.1 & 11.8613776308506 & 0.238622369149387 \tabularnewline
161 & 12.4 & 12.0680265588568 & 0.331973441143199 \tabularnewline
162 & 9.1 & 8.63193388809268 & 0.468066111907317 \tabularnewline
163 & 10.6 & 10.3410736021129 & 0.258926397887073 \tabularnewline
164 & 8.9 & 8.88796684025449 & 0.0120331597455094 \tabularnewline
165 & 9.5 & 9.6197303994207 & -0.1197303994207 \tabularnewline
166 & 9.8 & 9.54431287762572 & 0.255687122374277 \tabularnewline
167 & 9.6 & 9.25145868642761 & 0.348541313572388 \tabularnewline
168 & 12.6 & 12.3079209085889 & 0.292079091411105 \tabularnewline
169 & 9.3 & 9.07051033779842 & 0.229489662201578 \tabularnewline
170 & 10 & 10.3270121045615 & -0.327012104561518 \tabularnewline
171 & 12.7 & 11.9174529113243 & 0.782547088675659 \tabularnewline
172 & 11 & 11.1554069360293 & -0.15540693602931 \tabularnewline
173 & 11.4 & 11.809276259924 & -0.409276259924046 \tabularnewline
174 & 11.5 & 11.4352535836562 & 0.0647464163437803 \tabularnewline
175 & 10.2 & 9.69660468448691 & 0.503395315513086 \tabularnewline
176 & 11.4 & 11.1382502069413 & 0.261749793058706 \tabularnewline
177 & 12.6 & 12.0376217050065 & 0.562378294993524 \tabularnewline
178 & 9.4 & 9.08954271209284 & 0.310457287907157 \tabularnewline
179 & 8.7 & 9.00588122739707 & -0.305881227397075 \tabularnewline
180 & 9.2 & 9.52351461064851 & -0.32351461064851 \tabularnewline
181 & 9.3 & 9.4191815814404 & -0.119181581440402 \tabularnewline
182 & 9.2 & 9.19680776606393 & 0.00319223393607005 \tabularnewline
183 & 8.7 & 8.32861786291824 & 0.371382137081759 \tabularnewline
184 & 9.6 & 9.49288877631313 & 0.107111223686871 \tabularnewline
185 & 9.3 & 9.4110145334662 & -0.111014533466195 \tabularnewline
186 & 9.3 & 9.26573193793009 & 0.0342680620699112 \tabularnewline
187 & 9.9 & 10.0414417661109 & -0.14144176611093 \tabularnewline
188 & 11 & 10.4626425324884 & 0.537357467511574 \tabularnewline
189 & 12.7 & 12.6074848106726 & 0.092515189327444 \tabularnewline
190 & 8.9 & 8.9533669790534 & -0.0533669790534021 \tabularnewline
191 & 8.9 & 9.03109752165049 & -0.13109752165049 \tabularnewline
192 & 8.7 & 8.32861786291824 & 0.371382137081759 \tabularnewline
193 & 11.4 & 11.1148622510635 & 0.285137748936535 \tabularnewline
194 & 9.6 & 10.0093496076432 & -0.409349607643152 \tabularnewline
195 & 9.1 & 9.11561103578885 & -0.0156110357888537 \tabularnewline
196 & 9.1 & 9.06081311837312 & 0.0391868816268766 \tabularnewline
197 & 9.1 & 9.04454983674928 & 0.0554501632507235 \tabularnewline
198 & 8.9 & 8.96953377876625 & -0.0695337787662456 \tabularnewline
199 & 8.8 & 8.91995636627874 & -0.119956366278741 \tabularnewline
200 & 8.9 & 8.96953377876625 & -0.0695337787662456 \tabularnewline
201 & 9.3 & 9.30406744369506 & -0.00406744369506227 \tabularnewline
202 & 8.8 & 8.91995636627874 & -0.119956366278741 \tabularnewline
203 & 9.6 & 9.7145881327453 & -0.114588132745298 \tabularnewline
204 & 12 & 11.8156460753798 & 0.184353924620178 \tabularnewline
205 & 10.2 & 10.288715294649 & -0.0887152946490209 \tabularnewline
206 & 8.8 & 8.85537998091907 & -0.0553799809190726 \tabularnewline
207 & 9.2 & 9.29016004240908 & -0.0901600424090756 \tabularnewline
208 & 9.9 & 9.63355080814836 & 0.266449191851642 \tabularnewline
209 & 10.2 & 10.1420142893824 & 0.057985710617622 \tabularnewline
210 & 9.5 & 10.0400646384194 & -0.540064638419385 \tabularnewline
211 & 10.5 & 10.4903405543074 & 0.00965944569263113 \tabularnewline
212 & 11.2 & 11.2044368768407 & -0.00443687684065584 \tabularnewline
213 & 9.2 & 9.29016004240908 & -0.0901600424090756 \tabularnewline
214 & 9.7 & 10.0152740893276 & -0.315274089327573 \tabularnewline
215 & 11.1 & 11.0408678324469 & 0.0591321675531039 \tabularnewline
216 & 9.4 & 8.97644963058407 & 0.423550369415932 \tabularnewline
217 & 11 & 10.3233207281407 & 0.676679271859254 \tabularnewline
218 & 9.4 & 8.97644963058407 & 0.423550369415932 \tabularnewline
219 & 9.4 & 8.9228197419948 & 0.477180258005196 \tabularnewline
220 & 11 & 10.3965941197581 & 0.603405880241902 \tabularnewline
221 & 11 & 10.3233207281407 & 0.676679271859254 \tabularnewline
222 & 9.1 & 8.74970874176077 & 0.350291258239234 \tabularnewline
223 & 11.1 & 11.0408678324469 & 0.0591321675531039 \tabularnewline
224 & 9.1 & 9.45399956518719 & -0.353999565187193 \tabularnewline
225 & 10.4 & 10.3429599501956 & 0.0570400498043911 \tabularnewline
226 & 8.7 & 8.97864656264394 & -0.278646562643939 \tabularnewline
227 & 9.7 & 10.0530214176837 & -0.353021417683704 \tabularnewline
228 & 9.1 & 9.33810165190512 & -0.238101651905123 \tabularnewline
229 & 9.7 & 10.0530214176837 & -0.353021417683704 \tabularnewline
230 & 8.7 & 8.97864656264394 & -0.278646562643939 \tabularnewline
231 & 8.9 & 9.0560114485733 & -0.156011448573295 \tabularnewline
232 & 9.6 & 9.08705463578663 & 0.512945364213374 \tabularnewline
233 & 9.5 & 8.9674948162724 & 0.532505183727605 \tabularnewline
234 & 9 & 9.26785299965223 & -0.267852999652233 \tabularnewline
235 & 9 & 9.26785299965223 & -0.267852999652233 \tabularnewline
236 & 9 & 9.26785299965223 & -0.267852999652233 \tabularnewline
237 & 9 & 9.26785299965223 & -0.267852999652233 \tabularnewline
238 & 9.6 & 9.85930013972978 & -0.259300139729784 \tabularnewline
239 & 11.1 & 11.145288374343 & -0.0452883743429824 \tabularnewline
240 & 9.6 & 9.9159673257792 & -0.315967325779199 \tabularnewline
241 & 8.7 & 8.93147977048173 & -0.231479770481731 \tabularnewline
242 & 10.4 & 10.6197351390818 & -0.219735139081779 \tabularnewline
243 & 11.4 & 12.0311186958335 & -0.631118695833451 \tabularnewline
244 & 9.7 & 10.3334465555259 & -0.633446555525917 \tabularnewline
245 & 8.7 & 8.84634947047622 & -0.14634947047622 \tabularnewline
246 & 11.3 & 11.2504973817805 & 0.0495026182195186 \tabularnewline
247 & 12.6 & 12.447237216245 & 0.152762783754994 \tabularnewline
248 & 10.9 & 11.1576900213966 & -0.257690021396588 \tabularnewline
249 & 10.9 & 11.0711054922183 & -0.171105492218307 \tabularnewline
250 & 10 & 9.74486164607431 & 0.255138353925685 \tabularnewline
251 & 10 & 9.1427866485857 & 0.857213351414296 \tabularnewline
252 & 9.8 & 10.2007571258158 & -0.400757125815754 \tabularnewline
253 & 8.7 & 8.84634947047622 & -0.14634947047622 \tabularnewline
254 & 11.7 & 11.8568266413104 & -0.156826641310438 \tabularnewline
255 & 9.3 & 9.44124052868172 & -0.14124052868172 \tabularnewline
256 & 9.6 & 9.82647052354008 & -0.226470523540082 \tabularnewline
257 & 11 & 10.9605896601922 & 0.0394103398078283 \tabularnewline
258 & 11 & 10.9605896601922 & 0.0394103398078283 \tabularnewline
259 & 11.8 & 11.4546637307794 & 0.345336269220582 \tabularnewline
260 & 11.4 & 11.224098269895 & 0.175901730104998 \tabularnewline
261 & 10.2 & 10.3346137017458 & -0.134613701745796 \tabularnewline
262 & 8.9 & 8.77540144161934 & 0.124598558380663 \tabularnewline
263 & 10.2 & 10.2243441933693 & -0.024344193369334 \tabularnewline
264 & 9.6 & 9.49529931571738 & 0.104700684282617 \tabularnewline
265 & 10.6 & 10.7844979682266 & -0.184497968226646 \tabularnewline
266 & 8.9 & 8.77540144161934 & 0.124598558380663 \tabularnewline
267 & 9.2 & 9.16593907806879 & 0.0340609219312132 \tabularnewline
268 & 9.7 & 9.86962073373342 & -0.169620733733425 \tabularnewline
269 & 9.7 & 9.84317665958494 & -0.143176659584942 \tabularnewline
270 & 9.7 & 9.94370243824129 & -0.243702438241289 \tabularnewline
271 & 9.2 & 9.16593907806879 & 0.0340609219312132 \tabularnewline
272 & 9.7 & 9.84647192290905 & -0.146471922909047 \tabularnewline
273 & 9.3 & 9.07478378725305 & 0.225216212746947 \tabularnewline
274 & 9 & 9.23405330811937 & -0.234053308119369 \tabularnewline
275 & 9.5 & 9.56985606647872 & -0.0698560664787236 \tabularnewline
276 & 9.8 & 9.85070731654765 & -0.050707316547651 \tabularnewline
277 & 9.8 & 9.95917927837539 & -0.159179278375394 \tabularnewline
278 & 10.6 & 10.7493014565044 & -0.149301456504377 \tabularnewline
279 & 10.6 & 10.3170336983017 & 0.282966301698252 \tabularnewline
280 & 12.4 & 12.355345409924 & 0.0446545900759643 \tabularnewline
281 & 12.6 & 12.4270147653152 & 0.172985234684768 \tabularnewline
282 & 12.3 & 12.5138793142294 & -0.213879314229424 \tabularnewline
283 & 10.5 & 10.3175551329418 & 0.182444867058194 \tabularnewline
284 & 9.3 & 9.39707418244841 & -0.0970741824484075 \tabularnewline
285 & 8.8 & 8.92693798147679 & -0.126937981476792 \tabularnewline
286 & 8.8 & 8.94640326546733 & -0.146403265467326 \tabularnewline
287 & 9.7 & 9.72088548110683 & -0.0208854811068321 \tabularnewline
288 & 9 & 9.09446516949664 & -0.0944651694966416 \tabularnewline
289 & 9 & 9.09446516949664 & -0.0944651694966416 \tabularnewline
290 & 9 & 9.09446516949664 & -0.0944651694966416 \tabularnewline
291 & 9 & 9.09446516949664 & -0.0944651694966416 \tabularnewline
292 & 10.5 & 9.99273327952431 & 0.507266720475693 \tabularnewline
293 & 9.1 & 8.86625335953373 & 0.233746640466266 \tabularnewline
294 & 9.8 & 9.74991083945132 & 0.0500891605486793 \tabularnewline
295 & 8.5 & 8.19971866686954 & 0.30028133313046 \tabularnewline
296 & 9.4 & 9.80174021252601 & -0.401740212526006 \tabularnewline
297 & 9.4 & 9.45598708551393 & -0.0559870855139323 \tabularnewline
298 & 11.2 & 10.7059193722972 & 0.494080627702763 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154771&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]8.8[/C][C]8.16347275454783[/C][C]0.636527245452176[/C][/ROW]
[ROW][C]2[/C][C]9.5[/C][C]9.22256243405778[/C][C]0.277437565942221[/C][/ROW]
[ROW][C]3[/C][C]10.1[/C][C]10.3068039902424[/C][C]-0.20680399024237[/C][/ROW]
[ROW][C]4[/C][C]9.9[/C][C]9.73562564699591[/C][C]0.164374353004093[/C][/ROW]
[ROW][C]5[/C][C]9.9[/C][C]9.7356256469959[/C][C]0.164374353004095[/C][/ROW]
[ROW][C]6[/C][C]10.1[/C][C]10.3068039902424[/C][C]-0.20680399024237[/C][/ROW]
[ROW][C]7[/C][C]9.6[/C][C]9.42828846755214[/C][C]0.171711532447862[/C][/ROW]
[ROW][C]8[/C][C]8.8[/C][C]8.16347275454793[/C][C]0.636527245452074[/C][/ROW]
[ROW][C]9[/C][C]9.5[/C][C]9.22256243405778[/C][C]0.277437565942221[/C][/ROW]
[ROW][C]10[/C][C]11[/C][C]9.95230897559305[/C][C]1.04769102440695[/C][/ROW]
[ROW][C]11[/C][C]12[/C][C]11.8516971042345[/C][C]0.148302895765465[/C][/ROW]
[ROW][C]12[/C][C]9.7[/C][C]10.0877296017907[/C][C]-0.387729601790664[/C][/ROW]
[ROW][C]13[/C][C]10.8[/C][C]11.2756156316249[/C][C]-0.475615631624878[/C][/ROW]
[ROW][C]14[/C][C]12.4[/C][C]11.9663880726033[/C][C]0.433611927396679[/C][/ROW]
[ROW][C]15[/C][C]9.7[/C][C]9.46683091122643[/C][C]0.23316908877357[/C][/ROW]
[ROW][C]16[/C][C]11.4[/C][C]11.2316029526606[/C][C]0.168397047339363[/C][/ROW]
[ROW][C]17[/C][C]9.6[/C][C]9.53003037451511[/C][C]0.0699696254848848[/C][/ROW]
[ROW][C]18[/C][C]12.8[/C][C]12.6328908353132[/C][C]0.16710916468679[/C][/ROW]
[ROW][C]19[/C][C]11.3[/C][C]11.1170123334868[/C][C]0.182987666513251[/C][/ROW]
[ROW][C]20[/C][C]9.5[/C][C]9.34042665750142[/C][C]0.159573342498581[/C][/ROW]
[ROW][C]21[/C][C]12.8[/C][C]12.6328908353132[/C][C]0.16710916468679[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]11.1805290832572[/C][C]-0.1805290832572[/C][/ROW]
[ROW][C]23[/C][C]10.5[/C][C]10.5520839990232[/C][C]-0.0520839990231735[/C][/ROW]
[ROW][C]24[/C][C]9.3[/C][C]9.60665199479784[/C][C]-0.306651994797836[/C][/ROW]
[ROW][C]25[/C][C]10[/C][C]8.7048085983017[/C][C]1.2951914016983[/C][/ROW]
[ROW][C]26[/C][C]10.4[/C][C]10.1667375913654[/C][C]0.233262408634589[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]10.3312807894354[/C][C]-0.331280789435379[/C][/ROW]
[ROW][C]28[/C][C]10.5[/C][C]9.90642367430835[/C][C]0.593576325691651[/C][/ROW]
[ROW][C]29[/C][C]11.6[/C][C]11.409518611459[/C][C]0.190481388541014[/C][/ROW]
[ROW][C]30[/C][C]12.3[/C][C]12.198827372486[/C][C]0.101172627514031[/C][/ROW]
[ROW][C]31[/C][C]10[/C][C]9.66638947584319[/C][C]0.333610524156808[/C][/ROW]
[ROW][C]32[/C][C]10.2[/C][C]10.5760180012219[/C][C]-0.376018001221921[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]10.9958179607168[/C][C]-0.195817960716757[/C][/ROW]
[ROW][C]34[/C][C]9[/C][C]9.40120192866265[/C][C]-0.401201928662648[/C][/ROW]
[ROW][C]35[/C][C]10.2[/C][C]10.4822379540554[/C][C]-0.282237954055368[/C][/ROW]
[ROW][C]36[/C][C]12.8[/C][C]12.0938840477947[/C][C]0.706115952205271[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]10.3246467335986[/C][C]-0.324646733598632[/C][/ROW]
[ROW][C]38[/C][C]11.2[/C][C]11.3251547010407[/C][C]-0.125154701040685[/C][/ROW]
[ROW][C]39[/C][C]8.6[/C][C]8.76098081634356[/C][C]-0.160980816343561[/C][/ROW]
[ROW][C]40[/C][C]8.6[/C][C]8.76098081634356[/C][C]-0.160980816343561[/C][/ROW]
[ROW][C]41[/C][C]9.4[/C][C]9.39999088065615[/C][C]9.11934384936096e-06[/C][/ROW]
[ROW][C]42[/C][C]9.4[/C][C]9.44642115144093[/C][C]-0.0464211514409328[/C][/ROW]
[ROW][C]43[/C][C]9.8[/C][C]9.50777925996113[/C][C]0.292220740038869[/C][/ROW]
[ROW][C]44[/C][C]9.5[/C][C]9.68616253659106[/C][C]-0.186162536591058[/C][/ROW]
[ROW][C]45[/C][C]9.5[/C][C]9.77642514823915[/C][C]-0.276425148239153[/C][/ROW]
[ROW][C]46[/C][C]10[/C][C]10.1382017172362[/C][C]-0.138201717236216[/C][/ROW]
[ROW][C]47[/C][C]9.8[/C][C]9.861191040092[/C][C]-0.0611910400919964[/C][/ROW]
[ROW][C]48[/C][C]9.8[/C][C]9.90515119338696[/C][C]-0.105151193386958[/C][/ROW]
[ROW][C]49[/C][C]9.8[/C][C]9.50777925996113[/C][C]0.292220740038869[/C][/ROW]
[ROW][C]50[/C][C]9.8[/C][C]9.67763682177239[/C][C]0.122363178227608[/C][/ROW]
[ROW][C]51[/C][C]11.7[/C][C]11.432546851704[/C][C]0.267453148296019[/C][/ROW]
[ROW][C]52[/C][C]11[/C][C]11.4024698893777[/C][C]-0.402469889377747[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]11.2445733383179[/C][C]-0.344573338317882[/C][/ROW]
[ROW][C]54[/C][C]10.9[/C][C]11.0314808637678[/C][C]-0.131480863767785[/C][/ROW]
[ROW][C]55[/C][C]9.1[/C][C]9.53981462582532[/C][C]-0.439814625825317[/C][/ROW]
[ROW][C]56[/C][C]11[/C][C]11.5910077757847[/C][C]-0.591007775784732[/C][/ROW]
[ROW][C]57[/C][C]9.6[/C][C]10.0883656179811[/C][C]-0.488365617981148[/C][/ROW]
[ROW][C]58[/C][C]8.9[/C][C]8.96426332645212[/C][C]-0.0642633264521203[/C][/ROW]
[ROW][C]59[/C][C]10.2[/C][C]10.0572342646349[/C][C]0.142765735365094[/C][/ROW]
[ROW][C]60[/C][C]9.9[/C][C]10.4887350431502[/C][C]-0.588735043150182[/C][/ROW]
[ROW][C]61[/C][C]8.6[/C][C]8.78961625635363[/C][C]-0.189616256353632[/C][/ROW]
[ROW][C]62[/C][C]8.9[/C][C]8.96426332645212[/C][C]-0.0642633264521203[/C][/ROW]
[ROW][C]63[/C][C]10.5[/C][C]10.8172093496776[/C][C]-0.317209349677577[/C][/ROW]
[ROW][C]64[/C][C]10.2[/C][C]10.0572342646349[/C][C]0.142765735365094[/C][/ROW]
[ROW][C]65[/C][C]10.3[/C][C]10.1330342350189[/C][C]0.166965764981104[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]9.32210109593979[/C][C]-0.222101095939796[/C][/ROW]
[ROW][C]67[/C][C]12.6[/C][C]12.9997447746703[/C][C]-0.399744774670274[/C][/ROW]
[ROW][C]68[/C][C]9.8[/C][C]10.226477281108[/C][C]-0.426477281108007[/C][/ROW]
[ROW][C]69[/C][C]10.7[/C][C]10.8081609257808[/C][C]-0.108160925780824[/C][/ROW]
[ROW][C]70[/C][C]9.5[/C][C]9.47547203609418[/C][C]0.0245279639058235[/C][/ROW]
[ROW][C]71[/C][C]9[/C][C]9.19911767717135[/C][C]-0.199117677171352[/C][/ROW]
[ROW][C]72[/C][C]9.5[/C][C]9.07784085314133[/C][C]0.422159146858674[/C][/ROW]
[ROW][C]73[/C][C]10[/C][C]9.24023809439839[/C][C]0.759761905601614[/C][/ROW]
[ROW][C]74[/C][C]9.1[/C][C]9.33199493241625[/C][C]-0.231994932416246[/C][/ROW]
[ROW][C]75[/C][C]10.7[/C][C]10.8081609257808[/C][C]-0.108160925780824[/C][/ROW]
[ROW][C]76[/C][C]9.5[/C][C]9.47547203609418[/C][C]0.0245279639058235[/C][/ROW]
[ROW][C]77[/C][C]12.7[/C][C]12.3687139742039[/C][C]0.331286025796081[/C][/ROW]
[ROW][C]78[/C][C]12[/C][C]11.7972776865352[/C][C]0.202722313464836[/C][/ROW]
[ROW][C]79[/C][C]9.3[/C][C]9.18167794643633[/C][C]0.118322053563668[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]9.3833033474705[/C][C]-0.383303347470498[/C][/ROW]
[ROW][C]81[/C][C]10.6[/C][C]10.8072402921025[/C][C]-0.207240292102464[/C][/ROW]
[ROW][C]82[/C][C]9.2[/C][C]9.62187288465302[/C][C]-0.421872884653018[/C][/ROW]
[ROW][C]83[/C][C]10[/C][C]9.80992391087582[/C][C]0.190076089124176[/C][/ROW]
[ROW][C]84[/C][C]9.5[/C][C]9.34368475687876[/C][C]0.156315243121243[/C][/ROW]
[ROW][C]85[/C][C]8.7[/C][C]9.10349133867625[/C][C]-0.403491338676248[/C][/ROW]
[ROW][C]86[/C][C]8.7[/C][C]9.0714799477712[/C][C]-0.371479947771198[/C][/ROW]
[ROW][C]87[/C][C]8.7[/C][C]8.90052573053618[/C][C]-0.200525730536185[/C][/ROW]
[ROW][C]88[/C][C]9.7[/C][C]9.65471228853888[/C][C]0.0452877114611221[/C][/ROW]
[ROW][C]89[/C][C]8.7[/C][C]9.10349133867625[/C][C]-0.403491338676248[/C][/ROW]
[ROW][C]90[/C][C]8.7[/C][C]9.0714799477712[/C][C]-0.371479947771198[/C][/ROW]
[ROW][C]91[/C][C]8.7[/C][C]8.90052573053618[/C][C]-0.200525730536185[/C][/ROW]
[ROW][C]92[/C][C]9[/C][C]8.93548667186321[/C][C]0.0645133281367908[/C][/ROW]
[ROW][C]93[/C][C]12.6[/C][C]12.2638792047582[/C][C]0.336120795241812[/C][/ROW]
[ROW][C]94[/C][C]12.6[/C][C]12.350849117747[/C][C]0.24915088225305[/C][/ROW]
[ROW][C]95[/C][C]11.5[/C][C]11.2880130649426[/C][C]0.211986935057384[/C][/ROW]
[ROW][C]96[/C][C]9.2[/C][C]9.38020935480103[/C][C]-0.180209354801031[/C][/ROW]
[ROW][C]97[/C][C]8.8[/C][C]9.40885637087478[/C][C]-0.608856370874783[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]11.2456126051405[/C][C]0.154387394859508[/C][/ROW]
[ROW][C]99[/C][C]10.1[/C][C]10.6471323968508[/C][C]-0.547132396850812[/C][/ROW]
[ROW][C]100[/C][C]8.8[/C][C]9.40885637087478[/C][C]-0.608856370874783[/C][/ROW]
[ROW][C]101[/C][C]9.1[/C][C]9.28762110931969[/C][C]-0.187621109319689[/C][/ROW]
[ROW][C]102[/C][C]9.4[/C][C]9.86203740109567[/C][C]-0.462037401095671[/C][/ROW]
[ROW][C]103[/C][C]9.4[/C][C]9.18309362083297[/C][C]0.216906379167027[/C][/ROW]
[ROW][C]104[/C][C]9[/C][C]8.75987253446172[/C][C]0.240127465538276[/C][/ROW]
[ROW][C]105[/C][C]9.1[/C][C]9.28762110931969[/C][C]-0.187621109319689[/C][/ROW]
[ROW][C]106[/C][C]9.2[/C][C]9.68315073290269[/C][C]-0.483150732902694[/C][/ROW]
[ROW][C]107[/C][C]9.4[/C][C]9.86203740109567[/C][C]-0.462037401095671[/C][/ROW]
[ROW][C]108[/C][C]9.1[/C][C]9.22717051652803[/C][C]-0.127170516528027[/C][/ROW]
[ROW][C]109[/C][C]9.1[/C][C]9.22717051652803[/C][C]-0.127170516528027[/C][/ROW]
[ROW][C]110[/C][C]10.3[/C][C]10.5481182273215[/C][C]-0.248118227321526[/C][/ROW]
[ROW][C]111[/C][C]8.8[/C][C]8.5886430622981[/C][C]0.211356937701901[/C][/ROW]
[ROW][C]112[/C][C]8.9[/C][C]8.89089817282215[/C][C]0.00910182717784492[/C][/ROW]
[ROW][C]113[/C][C]9.2[/C][C]8.71004566774482[/C][C]0.489954332255183[/C][/ROW]
[ROW][C]114[/C][C]9.1[/C][C]9.00376021263033[/C][C]0.0962397873696651[/C][/ROW]
[ROW][C]115[/C][C]9.1[/C][C]9.00376021263033[/C][C]0.0962397873696651[/C][/ROW]
[ROW][C]116[/C][C]9.7[/C][C]9.26112679171265[/C][C]0.438873208287349[/C][/ROW]
[ROW][C]117[/C][C]11.3[/C][C]11.3614070825803[/C][C]-0.0614070825803359[/C][/ROW]
[ROW][C]118[/C][C]11.8[/C][C]11.3541089849535[/C][C]0.445891015046483[/C][/ROW]
[ROW][C]119[/C][C]9.2[/C][C]8.71004566774482[/C][C]0.489954332255183[/C][/ROW]
[ROW][C]120[/C][C]9.2[/C][C]8.88827971050881[/C][C]0.311720289491189[/C][/ROW]
[ROW][C]121[/C][C]10.2[/C][C]10.1757903350147[/C][C]0.0242096649853132[/C][/ROW]
[ROW][C]122[/C][C]8.8[/C][C]8.57673949589614[/C][C]0.223260504103863[/C][/ROW]
[ROW][C]123[/C][C]9.7[/C][C]9.78578796456735[/C][C]-0.085787964567347[/C][/ROW]
[ROW][C]124[/C][C]9.1[/C][C]9.1769865096044[/C][C]-0.0769865096043997[/C][/ROW]
[ROW][C]125[/C][C]9.8[/C][C]9.85979776478957[/C][C]-0.059797764789574[/C][/ROW]
[ROW][C]126[/C][C]11[/C][C]11.2249233208218[/C][C]-0.224923320821836[/C][/ROW]
[ROW][C]127[/C][C]10.5[/C][C]10.5219693827503[/C][C]-0.0219693827502639[/C][/ROW]
[ROW][C]128[/C][C]9.7[/C][C]9.7930363619903[/C][C]-0.0930363619903005[/C][/ROW]
[ROW][C]129[/C][C]10.9[/C][C]10.8459070509595[/C][C]0.0540929490405465[/C][/ROW]
[ROW][C]130[/C][C]10.9[/C][C]10.8497728057419[/C][C]0.0502271942580517[/C][/ROW]
[ROW][C]131[/C][C]10.6[/C][C]10.9007744305325[/C][C]-0.300774430532542[/C][/ROW]
[ROW][C]132[/C][C]9.7[/C][C]9.7930363619903[/C][C]-0.0930363619903005[/C][/ROW]
[ROW][C]133[/C][C]9[/C][C]9.20550861190603[/C][C]-0.205508611906031[/C][/ROW]
[ROW][C]134[/C][C]9.2[/C][C]9.47416611328515[/C][C]-0.27416611328515[/C][/ROW]
[ROW][C]135[/C][C]8.9[/C][C]9.19829804766415[/C][C]-0.298298047664147[/C][/ROW]
[ROW][C]136[/C][C]9.6[/C][C]9.86137499242657[/C][C]-0.26137499242657[/C][/ROW]
[ROW][C]137[/C][C]10.7[/C][C]10.9179884074864[/C][C]-0.217988407486424[/C][/ROW]
[ROW][C]138[/C][C]8.7[/C][C]8.81934680347515[/C][C]-0.119346803475153[/C][/ROW]
[ROW][C]139[/C][C]10.8[/C][C]10.9484870624104[/C][C]-0.148487062410397[/C][/ROW]
[ROW][C]140[/C][C]11.8[/C][C]11.252631875406[/C][C]0.547368124594005[/C][/ROW]
[ROW][C]141[/C][C]10.2[/C][C]10.1754309043109[/C][C]0.0245690956890568[/C][/ROW]
[ROW][C]142[/C][C]8.7[/C][C]8.81934680347515[/C][C]-0.119346803475153[/C][/ROW]
[ROW][C]143[/C][C]10.8[/C][C]11.2142713086692[/C][C]-0.414271308669209[/C][/ROW]
[ROW][C]144[/C][C]9.7[/C][C]10.1287870072609[/C][C]-0.428787007260905[/C][/ROW]
[ROW][C]145[/C][C]11.2[/C][C]11.2426165701738[/C][C]-0.0426165701738322[/C][/ROW]
[ROW][C]146[/C][C]10.9[/C][C]10.9102050910513[/C][C]-0.0102050910513273[/C][/ROW]
[ROW][C]147[/C][C]10.1[/C][C]10.2037126259524[/C][C]-0.103712625952444[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]9.20495205070559[/C][C]-0.204952050705595[/C][/ROW]
[ROW][C]149[/C][C]12[/C][C]11.9239012184277[/C][C]0.0760987815722663[/C][/ROW]
[ROW][C]150[/C][C]9.4[/C][C]9.2408785782171[/C][C]0.159121421782896[/C][/ROW]
[ROW][C]151[/C][C]11.5[/C][C]11.3061700816258[/C][C]0.19382991837418[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]9.32377853751317[/C][C]0.576221462486828[/C][/ROW]
[ROW][C]153[/C][C]9.4[/C][C]9.2408785782171[/C][C]0.159121421782896[/C][/ROW]
[ROW][C]154[/C][C]10.4[/C][C]10.6617058477945[/C][C]-0.261705847794529[/C][/ROW]
[ROW][C]155[/C][C]9.7[/C][C]9.57790556286348[/C][C]0.122094437136524[/C][/ROW]
[ROW][C]156[/C][C]8.9[/C][C]8.88796684025449[/C][C]0.0120331597455094[/C][/ROW]
[ROW][C]157[/C][C]8.9[/C][C]8.88796684025449[/C][C]0.0120331597455094[/C][/ROW]
[ROW][C]158[/C][C]12.4[/C][C]12.0680265588568[/C][C]0.331973441143199[/C][/ROW]
[ROW][C]159[/C][C]12.1[/C][C]11.8613776308506[/C][C]0.238622369149387[/C][/ROW]
[ROW][C]160[/C][C]12.1[/C][C]11.8613776308506[/C][C]0.238622369149387[/C][/ROW]
[ROW][C]161[/C][C]12.4[/C][C]12.0680265588568[/C][C]0.331973441143199[/C][/ROW]
[ROW][C]162[/C][C]9.1[/C][C]8.63193388809268[/C][C]0.468066111907317[/C][/ROW]
[ROW][C]163[/C][C]10.6[/C][C]10.3410736021129[/C][C]0.258926397887073[/C][/ROW]
[ROW][C]164[/C][C]8.9[/C][C]8.88796684025449[/C][C]0.0120331597455094[/C][/ROW]
[ROW][C]165[/C][C]9.5[/C][C]9.6197303994207[/C][C]-0.1197303994207[/C][/ROW]
[ROW][C]166[/C][C]9.8[/C][C]9.54431287762572[/C][C]0.255687122374277[/C][/ROW]
[ROW][C]167[/C][C]9.6[/C][C]9.25145868642761[/C][C]0.348541313572388[/C][/ROW]
[ROW][C]168[/C][C]12.6[/C][C]12.3079209085889[/C][C]0.292079091411105[/C][/ROW]
[ROW][C]169[/C][C]9.3[/C][C]9.07051033779842[/C][C]0.229489662201578[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]10.3270121045615[/C][C]-0.327012104561518[/C][/ROW]
[ROW][C]171[/C][C]12.7[/C][C]11.9174529113243[/C][C]0.782547088675659[/C][/ROW]
[ROW][C]172[/C][C]11[/C][C]11.1554069360293[/C][C]-0.15540693602931[/C][/ROW]
[ROW][C]173[/C][C]11.4[/C][C]11.809276259924[/C][C]-0.409276259924046[/C][/ROW]
[ROW][C]174[/C][C]11.5[/C][C]11.4352535836562[/C][C]0.0647464163437803[/C][/ROW]
[ROW][C]175[/C][C]10.2[/C][C]9.69660468448691[/C][C]0.503395315513086[/C][/ROW]
[ROW][C]176[/C][C]11.4[/C][C]11.1382502069413[/C][C]0.261749793058706[/C][/ROW]
[ROW][C]177[/C][C]12.6[/C][C]12.0376217050065[/C][C]0.562378294993524[/C][/ROW]
[ROW][C]178[/C][C]9.4[/C][C]9.08954271209284[/C][C]0.310457287907157[/C][/ROW]
[ROW][C]179[/C][C]8.7[/C][C]9.00588122739707[/C][C]-0.305881227397075[/C][/ROW]
[ROW][C]180[/C][C]9.2[/C][C]9.52351461064851[/C][C]-0.32351461064851[/C][/ROW]
[ROW][C]181[/C][C]9.3[/C][C]9.4191815814404[/C][C]-0.119181581440402[/C][/ROW]
[ROW][C]182[/C][C]9.2[/C][C]9.19680776606393[/C][C]0.00319223393607005[/C][/ROW]
[ROW][C]183[/C][C]8.7[/C][C]8.32861786291824[/C][C]0.371382137081759[/C][/ROW]
[ROW][C]184[/C][C]9.6[/C][C]9.49288877631313[/C][C]0.107111223686871[/C][/ROW]
[ROW][C]185[/C][C]9.3[/C][C]9.4110145334662[/C][C]-0.111014533466195[/C][/ROW]
[ROW][C]186[/C][C]9.3[/C][C]9.26573193793009[/C][C]0.0342680620699112[/C][/ROW]
[ROW][C]187[/C][C]9.9[/C][C]10.0414417661109[/C][C]-0.14144176611093[/C][/ROW]
[ROW][C]188[/C][C]11[/C][C]10.4626425324884[/C][C]0.537357467511574[/C][/ROW]
[ROW][C]189[/C][C]12.7[/C][C]12.6074848106726[/C][C]0.092515189327444[/C][/ROW]
[ROW][C]190[/C][C]8.9[/C][C]8.9533669790534[/C][C]-0.0533669790534021[/C][/ROW]
[ROW][C]191[/C][C]8.9[/C][C]9.03109752165049[/C][C]-0.13109752165049[/C][/ROW]
[ROW][C]192[/C][C]8.7[/C][C]8.32861786291824[/C][C]0.371382137081759[/C][/ROW]
[ROW][C]193[/C][C]11.4[/C][C]11.1148622510635[/C][C]0.285137748936535[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]10.0093496076432[/C][C]-0.409349607643152[/C][/ROW]
[ROW][C]195[/C][C]9.1[/C][C]9.11561103578885[/C][C]-0.0156110357888537[/C][/ROW]
[ROW][C]196[/C][C]9.1[/C][C]9.06081311837312[/C][C]0.0391868816268766[/C][/ROW]
[ROW][C]197[/C][C]9.1[/C][C]9.04454983674928[/C][C]0.0554501632507235[/C][/ROW]
[ROW][C]198[/C][C]8.9[/C][C]8.96953377876625[/C][C]-0.0695337787662456[/C][/ROW]
[ROW][C]199[/C][C]8.8[/C][C]8.91995636627874[/C][C]-0.119956366278741[/C][/ROW]
[ROW][C]200[/C][C]8.9[/C][C]8.96953377876625[/C][C]-0.0695337787662456[/C][/ROW]
[ROW][C]201[/C][C]9.3[/C][C]9.30406744369506[/C][C]-0.00406744369506227[/C][/ROW]
[ROW][C]202[/C][C]8.8[/C][C]8.91995636627874[/C][C]-0.119956366278741[/C][/ROW]
[ROW][C]203[/C][C]9.6[/C][C]9.7145881327453[/C][C]-0.114588132745298[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]11.8156460753798[/C][C]0.184353924620178[/C][/ROW]
[ROW][C]205[/C][C]10.2[/C][C]10.288715294649[/C][C]-0.0887152946490209[/C][/ROW]
[ROW][C]206[/C][C]8.8[/C][C]8.85537998091907[/C][C]-0.0553799809190726[/C][/ROW]
[ROW][C]207[/C][C]9.2[/C][C]9.29016004240908[/C][C]-0.0901600424090756[/C][/ROW]
[ROW][C]208[/C][C]9.9[/C][C]9.63355080814836[/C][C]0.266449191851642[/C][/ROW]
[ROW][C]209[/C][C]10.2[/C][C]10.1420142893824[/C][C]0.057985710617622[/C][/ROW]
[ROW][C]210[/C][C]9.5[/C][C]10.0400646384194[/C][C]-0.540064638419385[/C][/ROW]
[ROW][C]211[/C][C]10.5[/C][C]10.4903405543074[/C][C]0.00965944569263113[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]11.2044368768407[/C][C]-0.00443687684065584[/C][/ROW]
[ROW][C]213[/C][C]9.2[/C][C]9.29016004240908[/C][C]-0.0901600424090756[/C][/ROW]
[ROW][C]214[/C][C]9.7[/C][C]10.0152740893276[/C][C]-0.315274089327573[/C][/ROW]
[ROW][C]215[/C][C]11.1[/C][C]11.0408678324469[/C][C]0.0591321675531039[/C][/ROW]
[ROW][C]216[/C][C]9.4[/C][C]8.97644963058407[/C][C]0.423550369415932[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]10.3233207281407[/C][C]0.676679271859254[/C][/ROW]
[ROW][C]218[/C][C]9.4[/C][C]8.97644963058407[/C][C]0.423550369415932[/C][/ROW]
[ROW][C]219[/C][C]9.4[/C][C]8.9228197419948[/C][C]0.477180258005196[/C][/ROW]
[ROW][C]220[/C][C]11[/C][C]10.3965941197581[/C][C]0.603405880241902[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]10.3233207281407[/C][C]0.676679271859254[/C][/ROW]
[ROW][C]222[/C][C]9.1[/C][C]8.74970874176077[/C][C]0.350291258239234[/C][/ROW]
[ROW][C]223[/C][C]11.1[/C][C]11.0408678324469[/C][C]0.0591321675531039[/C][/ROW]
[ROW][C]224[/C][C]9.1[/C][C]9.45399956518719[/C][C]-0.353999565187193[/C][/ROW]
[ROW][C]225[/C][C]10.4[/C][C]10.3429599501956[/C][C]0.0570400498043911[/C][/ROW]
[ROW][C]226[/C][C]8.7[/C][C]8.97864656264394[/C][C]-0.278646562643939[/C][/ROW]
[ROW][C]227[/C][C]9.7[/C][C]10.0530214176837[/C][C]-0.353021417683704[/C][/ROW]
[ROW][C]228[/C][C]9.1[/C][C]9.33810165190512[/C][C]-0.238101651905123[/C][/ROW]
[ROW][C]229[/C][C]9.7[/C][C]10.0530214176837[/C][C]-0.353021417683704[/C][/ROW]
[ROW][C]230[/C][C]8.7[/C][C]8.97864656264394[/C][C]-0.278646562643939[/C][/ROW]
[ROW][C]231[/C][C]8.9[/C][C]9.0560114485733[/C][C]-0.156011448573295[/C][/ROW]
[ROW][C]232[/C][C]9.6[/C][C]9.08705463578663[/C][C]0.512945364213374[/C][/ROW]
[ROW][C]233[/C][C]9.5[/C][C]8.9674948162724[/C][C]0.532505183727605[/C][/ROW]
[ROW][C]234[/C][C]9[/C][C]9.26785299965223[/C][C]-0.267852999652233[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]9.26785299965223[/C][C]-0.267852999652233[/C][/ROW]
[ROW][C]236[/C][C]9[/C][C]9.26785299965223[/C][C]-0.267852999652233[/C][/ROW]
[ROW][C]237[/C][C]9[/C][C]9.26785299965223[/C][C]-0.267852999652233[/C][/ROW]
[ROW][C]238[/C][C]9.6[/C][C]9.85930013972978[/C][C]-0.259300139729784[/C][/ROW]
[ROW][C]239[/C][C]11.1[/C][C]11.145288374343[/C][C]-0.0452883743429824[/C][/ROW]
[ROW][C]240[/C][C]9.6[/C][C]9.9159673257792[/C][C]-0.315967325779199[/C][/ROW]
[ROW][C]241[/C][C]8.7[/C][C]8.93147977048173[/C][C]-0.231479770481731[/C][/ROW]
[ROW][C]242[/C][C]10.4[/C][C]10.6197351390818[/C][C]-0.219735139081779[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]12.0311186958335[/C][C]-0.631118695833451[/C][/ROW]
[ROW][C]244[/C][C]9.7[/C][C]10.3334465555259[/C][C]-0.633446555525917[/C][/ROW]
[ROW][C]245[/C][C]8.7[/C][C]8.84634947047622[/C][C]-0.14634947047622[/C][/ROW]
[ROW][C]246[/C][C]11.3[/C][C]11.2504973817805[/C][C]0.0495026182195186[/C][/ROW]
[ROW][C]247[/C][C]12.6[/C][C]12.447237216245[/C][C]0.152762783754994[/C][/ROW]
[ROW][C]248[/C][C]10.9[/C][C]11.1576900213966[/C][C]-0.257690021396588[/C][/ROW]
[ROW][C]249[/C][C]10.9[/C][C]11.0711054922183[/C][C]-0.171105492218307[/C][/ROW]
[ROW][C]250[/C][C]10[/C][C]9.74486164607431[/C][C]0.255138353925685[/C][/ROW]
[ROW][C]251[/C][C]10[/C][C]9.1427866485857[/C][C]0.857213351414296[/C][/ROW]
[ROW][C]252[/C][C]9.8[/C][C]10.2007571258158[/C][C]-0.400757125815754[/C][/ROW]
[ROW][C]253[/C][C]8.7[/C][C]8.84634947047622[/C][C]-0.14634947047622[/C][/ROW]
[ROW][C]254[/C][C]11.7[/C][C]11.8568266413104[/C][C]-0.156826641310438[/C][/ROW]
[ROW][C]255[/C][C]9.3[/C][C]9.44124052868172[/C][C]-0.14124052868172[/C][/ROW]
[ROW][C]256[/C][C]9.6[/C][C]9.82647052354008[/C][C]-0.226470523540082[/C][/ROW]
[ROW][C]257[/C][C]11[/C][C]10.9605896601922[/C][C]0.0394103398078283[/C][/ROW]
[ROW][C]258[/C][C]11[/C][C]10.9605896601922[/C][C]0.0394103398078283[/C][/ROW]
[ROW][C]259[/C][C]11.8[/C][C]11.4546637307794[/C][C]0.345336269220582[/C][/ROW]
[ROW][C]260[/C][C]11.4[/C][C]11.224098269895[/C][C]0.175901730104998[/C][/ROW]
[ROW][C]261[/C][C]10.2[/C][C]10.3346137017458[/C][C]-0.134613701745796[/C][/ROW]
[ROW][C]262[/C][C]8.9[/C][C]8.77540144161934[/C][C]0.124598558380663[/C][/ROW]
[ROW][C]263[/C][C]10.2[/C][C]10.2243441933693[/C][C]-0.024344193369334[/C][/ROW]
[ROW][C]264[/C][C]9.6[/C][C]9.49529931571738[/C][C]0.104700684282617[/C][/ROW]
[ROW][C]265[/C][C]10.6[/C][C]10.7844979682266[/C][C]-0.184497968226646[/C][/ROW]
[ROW][C]266[/C][C]8.9[/C][C]8.77540144161934[/C][C]0.124598558380663[/C][/ROW]
[ROW][C]267[/C][C]9.2[/C][C]9.16593907806879[/C][C]0.0340609219312132[/C][/ROW]
[ROW][C]268[/C][C]9.7[/C][C]9.86962073373342[/C][C]-0.169620733733425[/C][/ROW]
[ROW][C]269[/C][C]9.7[/C][C]9.84317665958494[/C][C]-0.143176659584942[/C][/ROW]
[ROW][C]270[/C][C]9.7[/C][C]9.94370243824129[/C][C]-0.243702438241289[/C][/ROW]
[ROW][C]271[/C][C]9.2[/C][C]9.16593907806879[/C][C]0.0340609219312132[/C][/ROW]
[ROW][C]272[/C][C]9.7[/C][C]9.84647192290905[/C][C]-0.146471922909047[/C][/ROW]
[ROW][C]273[/C][C]9.3[/C][C]9.07478378725305[/C][C]0.225216212746947[/C][/ROW]
[ROW][C]274[/C][C]9[/C][C]9.23405330811937[/C][C]-0.234053308119369[/C][/ROW]
[ROW][C]275[/C][C]9.5[/C][C]9.56985606647872[/C][C]-0.0698560664787236[/C][/ROW]
[ROW][C]276[/C][C]9.8[/C][C]9.85070731654765[/C][C]-0.050707316547651[/C][/ROW]
[ROW][C]277[/C][C]9.8[/C][C]9.95917927837539[/C][C]-0.159179278375394[/C][/ROW]
[ROW][C]278[/C][C]10.6[/C][C]10.7493014565044[/C][C]-0.149301456504377[/C][/ROW]
[ROW][C]279[/C][C]10.6[/C][C]10.3170336983017[/C][C]0.282966301698252[/C][/ROW]
[ROW][C]280[/C][C]12.4[/C][C]12.355345409924[/C][C]0.0446545900759643[/C][/ROW]
[ROW][C]281[/C][C]12.6[/C][C]12.4270147653152[/C][C]0.172985234684768[/C][/ROW]
[ROW][C]282[/C][C]12.3[/C][C]12.5138793142294[/C][C]-0.213879314229424[/C][/ROW]
[ROW][C]283[/C][C]10.5[/C][C]10.3175551329418[/C][C]0.182444867058194[/C][/ROW]
[ROW][C]284[/C][C]9.3[/C][C]9.39707418244841[/C][C]-0.0970741824484075[/C][/ROW]
[ROW][C]285[/C][C]8.8[/C][C]8.92693798147679[/C][C]-0.126937981476792[/C][/ROW]
[ROW][C]286[/C][C]8.8[/C][C]8.94640326546733[/C][C]-0.146403265467326[/C][/ROW]
[ROW][C]287[/C][C]9.7[/C][C]9.72088548110683[/C][C]-0.0208854811068321[/C][/ROW]
[ROW][C]288[/C][C]9[/C][C]9.09446516949664[/C][C]-0.0944651694966416[/C][/ROW]
[ROW][C]289[/C][C]9[/C][C]9.09446516949664[/C][C]-0.0944651694966416[/C][/ROW]
[ROW][C]290[/C][C]9[/C][C]9.09446516949664[/C][C]-0.0944651694966416[/C][/ROW]
[ROW][C]291[/C][C]9[/C][C]9.09446516949664[/C][C]-0.0944651694966416[/C][/ROW]
[ROW][C]292[/C][C]10.5[/C][C]9.99273327952431[/C][C]0.507266720475693[/C][/ROW]
[ROW][C]293[/C][C]9.1[/C][C]8.86625335953373[/C][C]0.233746640466266[/C][/ROW]
[ROW][C]294[/C][C]9.8[/C][C]9.74991083945132[/C][C]0.0500891605486793[/C][/ROW]
[ROW][C]295[/C][C]8.5[/C][C]8.19971866686954[/C][C]0.30028133313046[/C][/ROW]
[ROW][C]296[/C][C]9.4[/C][C]9.80174021252601[/C][C]-0.401740212526006[/C][/ROW]
[ROW][C]297[/C][C]9.4[/C][C]9.45598708551393[/C][C]-0.0559870855139323[/C][/ROW]
[ROW][C]298[/C][C]11.2[/C][C]10.7059193722972[/C][C]0.494080627702763[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154771&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154771&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	8.8	8.16347275454783	0.636527245452176
2	9.5	9.22256243405778	0.277437565942221
3	10.1	10.3068039902424	-0.20680399024237
4	9.9	9.73562564699591	0.164374353004093
5	9.9	9.7356256469959	0.164374353004095
6	10.1	10.3068039902424	-0.20680399024237
7	9.6	9.42828846755214	0.171711532447862
8	8.8	8.16347275454793	0.636527245452074
9	9.5	9.22256243405778	0.277437565942221
10	11	9.95230897559305	1.04769102440695
11	12	11.8516971042345	0.148302895765465
12	9.7	10.0877296017907	-0.387729601790664
13	10.8	11.2756156316249	-0.475615631624878
14	12.4	11.9663880726033	0.433611927396679
15	9.7	9.46683091122643	0.23316908877357
16	11.4	11.2316029526606	0.168397047339363
17	9.6	9.53003037451511	0.0699696254848848
18	12.8	12.6328908353132	0.16710916468679
19	11.3	11.1170123334868	0.182987666513251
20	9.5	9.34042665750142	0.159573342498581
21	12.8	12.6328908353132	0.16710916468679
22	11	11.1805290832572	-0.1805290832572
23	10.5	10.5520839990232	-0.0520839990231735
24	9.3	9.60665199479784	-0.306651994797836
25	10	8.7048085983017	1.2951914016983
26	10.4	10.1667375913654	0.233262408634589
27	10	10.3312807894354	-0.331280789435379
28	10.5	9.90642367430835	0.593576325691651
29	11.6	11.409518611459	0.190481388541014
30	12.3	12.198827372486	0.101172627514031
31	10	9.66638947584319	0.333610524156808
32	10.2	10.5760180012219	-0.376018001221921
33	10.8	10.9958179607168	-0.195817960716757
34	9	9.40120192866265	-0.401201928662648
35	10.2	10.4822379540554	-0.282237954055368
36	12.8	12.0938840477947	0.706115952205271
37	10	10.3246467335986	-0.324646733598632
38	11.2	11.3251547010407	-0.125154701040685
39	8.6	8.76098081634356	-0.160980816343561
40	8.6	8.76098081634356	-0.160980816343561
41	9.4	9.39999088065615	9.11934384936096e-06
42	9.4	9.44642115144093	-0.0464211514409328
43	9.8	9.50777925996113	0.292220740038869
44	9.5	9.68616253659106	-0.186162536591058
45	9.5	9.77642514823915	-0.276425148239153
46	10	10.1382017172362	-0.138201717236216
47	9.8	9.861191040092	-0.0611910400919964
48	9.8	9.90515119338696	-0.105151193386958
49	9.8	9.50777925996113	0.292220740038869
50	9.8	9.67763682177239	0.122363178227608
51	11.7	11.432546851704	0.267453148296019
52	11	11.4024698893777	-0.402469889377747
53	10.9	11.2445733383179	-0.344573338317882
54	10.9	11.0314808637678	-0.131480863767785
55	9.1	9.53981462582532	-0.439814625825317
56	11	11.5910077757847	-0.591007775784732
57	9.6	10.0883656179811	-0.488365617981148
58	8.9	8.96426332645212	-0.0642633264521203
59	10.2	10.0572342646349	0.142765735365094
60	9.9	10.4887350431502	-0.588735043150182
61	8.6	8.78961625635363	-0.189616256353632
62	8.9	8.96426332645212	-0.0642633264521203
63	10.5	10.8172093496776	-0.317209349677577
64	10.2	10.0572342646349	0.142765735365094
65	10.3	10.1330342350189	0.166965764981104
66	9.1	9.32210109593979	-0.222101095939796
67	12.6	12.9997447746703	-0.399744774670274
68	9.8	10.226477281108	-0.426477281108007
69	10.7	10.8081609257808	-0.108160925780824
70	9.5	9.47547203609418	0.0245279639058235
71	9	9.19911767717135	-0.199117677171352
72	9.5	9.07784085314133	0.422159146858674
73	10	9.24023809439839	0.759761905601614
74	9.1	9.33199493241625	-0.231994932416246
75	10.7	10.8081609257808	-0.108160925780824
76	9.5	9.47547203609418	0.0245279639058235
77	12.7	12.3687139742039	0.331286025796081
78	12	11.7972776865352	0.202722313464836
79	9.3	9.18167794643633	0.118322053563668
80	9	9.3833033474705	-0.383303347470498
81	10.6	10.8072402921025	-0.207240292102464
82	9.2	9.62187288465302	-0.421872884653018
83	10	9.80992391087582	0.190076089124176
84	9.5	9.34368475687876	0.156315243121243
85	8.7	9.10349133867625	-0.403491338676248
86	8.7	9.0714799477712	-0.371479947771198
87	8.7	8.90052573053618	-0.200525730536185
88	9.7	9.65471228853888	0.0452877114611221
89	8.7	9.10349133867625	-0.403491338676248
90	8.7	9.0714799477712	-0.371479947771198
91	8.7	8.90052573053618	-0.200525730536185
92	9	8.93548667186321	0.0645133281367908
93	12.6	12.2638792047582	0.336120795241812
94	12.6	12.350849117747	0.24915088225305
95	11.5	11.2880130649426	0.211986935057384
96	9.2	9.38020935480103	-0.180209354801031
97	8.8	9.40885637087478	-0.608856370874783
98	11.4	11.2456126051405	0.154387394859508
99	10.1	10.6471323968508	-0.547132396850812
100	8.8	9.40885637087478	-0.608856370874783
101	9.1	9.28762110931969	-0.187621109319689
102	9.4	9.86203740109567	-0.462037401095671
103	9.4	9.18309362083297	0.216906379167027
104	9	8.75987253446172	0.240127465538276
105	9.1	9.28762110931969	-0.187621109319689
106	9.2	9.68315073290269	-0.483150732902694
107	9.4	9.86203740109567	-0.462037401095671
108	9.1	9.22717051652803	-0.127170516528027
109	9.1	9.22717051652803	-0.127170516528027
110	10.3	10.5481182273215	-0.248118227321526
111	8.8	8.5886430622981	0.211356937701901
112	8.9	8.89089817282215	0.00910182717784492
113	9.2	8.71004566774482	0.489954332255183
114	9.1	9.00376021263033	0.0962397873696651
115	9.1	9.00376021263033	0.0962397873696651
116	9.7	9.26112679171265	0.438873208287349
117	11.3	11.3614070825803	-0.0614070825803359
118	11.8	11.3541089849535	0.445891015046483
119	9.2	8.71004566774482	0.489954332255183
120	9.2	8.88827971050881	0.311720289491189
121	10.2	10.1757903350147	0.0242096649853132
122	8.8	8.57673949589614	0.223260504103863
123	9.7	9.78578796456735	-0.085787964567347
124	9.1	9.1769865096044	-0.0769865096043997
125	9.8	9.85979776478957	-0.059797764789574
126	11	11.2249233208218	-0.224923320821836
127	10.5	10.5219693827503	-0.0219693827502639
128	9.7	9.7930363619903	-0.0930363619903005
129	10.9	10.8459070509595	0.0540929490405465
130	10.9	10.8497728057419	0.0502271942580517
131	10.6	10.9007744305325	-0.300774430532542
132	9.7	9.7930363619903	-0.0930363619903005
133	9	9.20550861190603	-0.205508611906031
134	9.2	9.47416611328515	-0.27416611328515
135	8.9	9.19829804766415	-0.298298047664147
136	9.6	9.86137499242657	-0.26137499242657
137	10.7	10.9179884074864	-0.217988407486424
138	8.7	8.81934680347515	-0.119346803475153
139	10.8	10.9484870624104	-0.148487062410397
140	11.8	11.252631875406	0.547368124594005
141	10.2	10.1754309043109	0.0245690956890568
142	8.7	8.81934680347515	-0.119346803475153
143	10.8	11.2142713086692	-0.414271308669209
144	9.7	10.1287870072609	-0.428787007260905
145	11.2	11.2426165701738	-0.0426165701738322
146	10.9	10.9102050910513	-0.0102050910513273
147	10.1	10.2037126259524	-0.103712625952444
148	9	9.20495205070559	-0.204952050705595
149	12	11.9239012184277	0.0760987815722663
150	9.4	9.2408785782171	0.159121421782896
151	11.5	11.3061700816258	0.19382991837418
152	9.9	9.32377853751317	0.576221462486828
153	9.4	9.2408785782171	0.159121421782896
154	10.4	10.6617058477945	-0.261705847794529
155	9.7	9.57790556286348	0.122094437136524
156	8.9	8.88796684025449	0.0120331597455094
157	8.9	8.88796684025449	0.0120331597455094
158	12.4	12.0680265588568	0.331973441143199
159	12.1	11.8613776308506	0.238622369149387
160	12.1	11.8613776308506	0.238622369149387
161	12.4	12.0680265588568	0.331973441143199
162	9.1	8.63193388809268	0.468066111907317
163	10.6	10.3410736021129	0.258926397887073
164	8.9	8.88796684025449	0.0120331597455094
165	9.5	9.6197303994207	-0.1197303994207
166	9.8	9.54431287762572	0.255687122374277
167	9.6	9.25145868642761	0.348541313572388
168	12.6	12.3079209085889	0.292079091411105
169	9.3	9.07051033779842	0.229489662201578
170	10	10.3270121045615	-0.327012104561518
171	12.7	11.9174529113243	0.782547088675659
172	11	11.1554069360293	-0.15540693602931
173	11.4	11.809276259924	-0.409276259924046
174	11.5	11.4352535836562	0.0647464163437803
175	10.2	9.69660468448691	0.503395315513086
176	11.4	11.1382502069413	0.261749793058706
177	12.6	12.0376217050065	0.562378294993524
178	9.4	9.08954271209284	0.310457287907157
179	8.7	9.00588122739707	-0.305881227397075
180	9.2	9.52351461064851	-0.32351461064851
181	9.3	9.4191815814404	-0.119181581440402
182	9.2	9.19680776606393	0.00319223393607005
183	8.7	8.32861786291824	0.371382137081759
184	9.6	9.49288877631313	0.107111223686871
185	9.3	9.4110145334662	-0.111014533466195
186	9.3	9.26573193793009	0.0342680620699112
187	9.9	10.0414417661109	-0.14144176611093
188	11	10.4626425324884	0.537357467511574
189	12.7	12.6074848106726	0.092515189327444
190	8.9	8.9533669790534	-0.0533669790534021
191	8.9	9.03109752165049	-0.13109752165049
192	8.7	8.32861786291824	0.371382137081759
193	11.4	11.1148622510635	0.285137748936535
194	9.6	10.0093496076432	-0.409349607643152
195	9.1	9.11561103578885	-0.0156110357888537
196	9.1	9.06081311837312	0.0391868816268766
197	9.1	9.04454983674928	0.0554501632507235
198	8.9	8.96953377876625	-0.0695337787662456
199	8.8	8.91995636627874	-0.119956366278741
200	8.9	8.96953377876625	-0.0695337787662456
201	9.3	9.30406744369506	-0.00406744369506227
202	8.8	8.91995636627874	-0.119956366278741
203	9.6	9.7145881327453	-0.114588132745298
204	12	11.8156460753798	0.184353924620178
205	10.2	10.288715294649	-0.0887152946490209
206	8.8	8.85537998091907	-0.0553799809190726
207	9.2	9.29016004240908	-0.0901600424090756
208	9.9	9.63355080814836	0.266449191851642
209	10.2	10.1420142893824	0.057985710617622
210	9.5	10.0400646384194	-0.540064638419385
211	10.5	10.4903405543074	0.00965944569263113
212	11.2	11.2044368768407	-0.00443687684065584
213	9.2	9.29016004240908	-0.0901600424090756
214	9.7	10.0152740893276	-0.315274089327573
215	11.1	11.0408678324469	0.0591321675531039
216	9.4	8.97644963058407	0.423550369415932
217	11	10.3233207281407	0.676679271859254
218	9.4	8.97644963058407	0.423550369415932
219	9.4	8.9228197419948	0.477180258005196
220	11	10.3965941197581	0.603405880241902
221	11	10.3233207281407	0.676679271859254
222	9.1	8.74970874176077	0.350291258239234
223	11.1	11.0408678324469	0.0591321675531039
224	9.1	9.45399956518719	-0.353999565187193
225	10.4	10.3429599501956	0.0570400498043911
226	8.7	8.97864656264394	-0.278646562643939
227	9.7	10.0530214176837	-0.353021417683704
228	9.1	9.33810165190512	-0.238101651905123
229	9.7	10.0530214176837	-0.353021417683704
230	8.7	8.97864656264394	-0.278646562643939
231	8.9	9.0560114485733	-0.156011448573295
232	9.6	9.08705463578663	0.512945364213374
233	9.5	8.9674948162724	0.532505183727605
234	9	9.26785299965223	-0.267852999652233
235	9	9.26785299965223	-0.267852999652233
236	9	9.26785299965223	-0.267852999652233
237	9	9.26785299965223	-0.267852999652233
238	9.6	9.85930013972978	-0.259300139729784
239	11.1	11.145288374343	-0.0452883743429824
240	9.6	9.9159673257792	-0.315967325779199
241	8.7	8.93147977048173	-0.231479770481731
242	10.4	10.6197351390818	-0.219735139081779
243	11.4	12.0311186958335	-0.631118695833451
244	9.7	10.3334465555259	-0.633446555525917
245	8.7	8.84634947047622	-0.14634947047622
246	11.3	11.2504973817805	0.0495026182195186
247	12.6	12.447237216245	0.152762783754994
248	10.9	11.1576900213966	-0.257690021396588
249	10.9	11.0711054922183	-0.171105492218307
250	10	9.74486164607431	0.255138353925685
251	10	9.1427866485857	0.857213351414296
252	9.8	10.2007571258158	-0.400757125815754
253	8.7	8.84634947047622	-0.14634947047622
254	11.7	11.8568266413104	-0.156826641310438
255	9.3	9.44124052868172	-0.14124052868172
256	9.6	9.82647052354008	-0.226470523540082
257	11	10.9605896601922	0.0394103398078283
258	11	10.9605896601922	0.0394103398078283
259	11.8	11.4546637307794	0.345336269220582
260	11.4	11.224098269895	0.175901730104998
261	10.2	10.3346137017458	-0.134613701745796
262	8.9	8.77540144161934	0.124598558380663
263	10.2	10.2243441933693	-0.024344193369334
264	9.6	9.49529931571738	0.104700684282617
265	10.6	10.7844979682266	-0.184497968226646
266	8.9	8.77540144161934	0.124598558380663
267	9.2	9.16593907806879	0.0340609219312132
268	9.7	9.86962073373342	-0.169620733733425
269	9.7	9.84317665958494	-0.143176659584942
270	9.7	9.94370243824129	-0.243702438241289
271	9.2	9.16593907806879	0.0340609219312132
272	9.7	9.84647192290905	-0.146471922909047
273	9.3	9.07478378725305	0.225216212746947
274	9	9.23405330811937	-0.234053308119369
275	9.5	9.56985606647872	-0.0698560664787236
276	9.8	9.85070731654765	-0.050707316547651
277	9.8	9.95917927837539	-0.159179278375394
278	10.6	10.7493014565044	-0.149301456504377
279	10.6	10.3170336983017	0.282966301698252
280	12.4	12.355345409924	0.0446545900759643
281	12.6	12.4270147653152	0.172985234684768
282	12.3	12.5138793142294	-0.213879314229424
283	10.5	10.3175551329418	0.182444867058194
284	9.3	9.39707418244841	-0.0970741824484075
285	8.8	8.92693798147679	-0.126937981476792
286	8.8	8.94640326546733	-0.146403265467326
287	9.7	9.72088548110683	-0.0208854811068321
288	9	9.09446516949664	-0.0944651694966416
289	9	9.09446516949664	-0.0944651694966416
290	9	9.09446516949664	-0.0944651694966416
291	9	9.09446516949664	-0.0944651694966416
292	10.5	9.99273327952431	0.507266720475693
293	9.1	8.86625335953373	0.233746640466266
294	9.8	9.74991083945132	0.0500891605486793
295	8.5	8.19971866686954	0.30028133313046
296	9.4	9.80174021252601	-0.401740212526006
297	9.4	9.45598708551393	-0.0559870855139323
298	11.2	10.7059193722972	0.494080627702763

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
15	5.25595016926085e-40	1.05119003385217e-39	1
16	7.03172370631854e-55	1.40634474126371e-54	1
17	0.547557000086192	0.904885999827616	0.452442999913808
18	0.461663389715576	0.923326779431152	0.538336610284424
19	0.602898652720776	0.794202694558448	0.397101347279224
20	0.498878088536986	0.997756177073971	0.501121911463014
21	0.405727064076504	0.811454128153008	0.594272935923496
22	0.467187303288956	0.934374606577912	0.532812696711044
23	0.464745829704057	0.929491659408115	0.535254170295943
24	0.483195967417473	0.966391934834945	0.516804032582527
25	0.769025347086883	0.461949305826235	0.230974652913117
26	0.726805783329712	0.546388433340577	0.273194216670288
27	0.890371203031083	0.219257593937834	0.109628796968917
28	0.960258918309945	0.07948216338011	0.039741081690055
29	0.948218658166741	0.103562683666517	0.0517813418332585
30	0.93705210404215	0.1258957919157	0.0629478959578501
31	0.945125615669434	0.109748768661131	0.0548743843305657
32	0.930254460824958	0.139491078350083	0.0697455391750416
33	0.909895172403286	0.180209655193428	0.0901048275967141
34	0.969075677448379	0.061848645103243	0.0309243225516215
35	0.963251211290745	0.07349757741851	0.036748788709255
36	0.991361797850197	0.0172764042996054	0.0086382021498027
37	0.990112031383664	0.019775937232673	0.00988796861633649
38	0.986331783107547	0.0273364337849062	0.0136682168924531
39	0.984434838835687	0.0311303223286253	0.0155651611643126
40	0.980752715932267	0.0384945681354663	0.0192472840677331
41	0.984066915327378	0.0318661693452444	0.0159330846726222
42	0.979174883834253	0.0416502323314933	0.0208251161657466
43	0.973412202696383	0.0531755946072341	0.0265877973036171
44	0.97500478529893	0.0499904294021404	0.0249952147010702
45	0.977271259196731	0.0454574816065381	0.022728740803269
46	0.976946961714308	0.0461060765713839	0.0230530382856919
47	0.970336197678683	0.0593276046426345	0.0296638023213172
48	0.961644486260015	0.0767110274799693	0.0383555137399846
49	0.954458045698029	0.0910839086039417	0.0455419543019709
50	0.94272447687738	0.11455104624524	0.0572755231226202
51	0.938257517281429	0.123484965437142	0.0617424827185711
52	0.936978400588866	0.126043198822269	0.0630215994111344
53	0.935854704769173	0.128290590461654	0.064145295230827
54	0.920744332622613	0.158511334754773	0.0792556673773865
55	0.962996494094224	0.0740070118115513	0.0370035059057756
56	0.985926035201241	0.0281479295975189	0.0140739647987594
57	0.99334409470276	0.0133118105944802	0.00665590529724011
58	0.991116146983406	0.0177677060331889	0.00888385301659443
59	0.990405678007081	0.0191886439858384	0.00959432199291919
60	0.993362085791203	0.0132758284175937	0.00663791420879684
61	0.991826388430731	0.0163472231385382	0.0081736115692691
62	0.98919651235298	0.0216069752940404	0.0108034876470202
63	0.98705565000419	0.0258886999916208	0.0129443499958104
64	0.985943448347621	0.0281131033047573	0.0140565516523787
65	0.98395918469415	0.0320816306117001	0.0160408153058501
66	0.980278842775788	0.0394423144484236	0.0197211572242118
67	0.978407357093066	0.0431852858138675	0.0215926429069338
68	0.978418966947804	0.0431620661043929	0.0215810330521964
69	0.973727029175499	0.0525459416490019	0.026272970824501
70	0.967043360486754	0.065913279026492	0.032956639513246
71	0.971773807285287	0.0564523854294255	0.0282261927147128
72	0.973581328705542	0.0528373425889154	0.0264186712944577
73	0.984449854461802	0.0311002910763957	0.0155501455381979
74	0.983423313099956	0.0331533738000887	0.0165766869000444
75	0.97980863436467	0.0403827312706605	0.0201913656353302
76	0.974695046907716	0.050609906184567	0.0253049530922835
77	0.983529235156406	0.0329415296871882	0.0164707648435941
78	0.980897008760256	0.0382059824794873	0.0191029912397437
79	0.977949055265097	0.0441018894698065	0.0220509447349033
80	0.984065088110387	0.0318698237792269	0.0159349118896135
81	0.982153105912904	0.0356937881741927	0.0178468940870964
82	0.986311182816767	0.0273776343664668	0.0136888171832334
83	0.98540947043047	0.0291810591390595	0.0145905295695297
84	0.982376810532686	0.0352463789346289	0.0176231894673144
85	0.987151245578794	0.0256975088424122	0.0128487544212061
86	0.989409532281402	0.0211809354371959	0.010590467718598
87	0.98762619795466	0.0247476040906795	0.0123738020453397
88	0.984647613994726	0.0307047720105489	0.0153523860052745
89	0.985610212197681	0.0287795756046387	0.0143897878023194
90	0.98648157497065	0.0270368500586992	0.0135184250293496
91	0.984086561775488	0.0318268764490241	0.0159134382245121
92	0.981044384064277	0.0379112318714468	0.0189556159357234
93	0.98407285783746	0.031854284325081	0.0159271421625405
94	0.984104688387863	0.0317906232242735	0.0158953116121368
95	0.982393729133093	0.0352125417338148	0.0176062708669074
96	0.979859564833268	0.0402808703334634	0.0201404351667317
97	0.989059662489474	0.0218806750210524	0.0109403375105262
98	0.986824326642951	0.0263513467140974	0.0131756733570487
99	0.990600548126499	0.0187989037470017	0.00939945187350086
100	0.994522026030794	0.0109559479384126	0.00547797396920629
101	0.99332789803387	0.0133442039322595	0.00667210196612973
102	0.99445893890429	0.0110821221914191	0.00554106109570956
103	0.994229415177198	0.0115411696456049	0.00577058482280247
104	0.994045876479136	0.0119082470417284	0.00595412352086418
105	0.992816373945088	0.014367252109824	0.007183626054912
106	0.994682354444296	0.0106352911114075	0.00531764555570375
107	0.99576572965589	0.00846854068821937	0.00423427034410968
108	0.994796716784655	0.0104065664306899	0.00520328321534493
109	0.993662224504818	0.0126755509903646	0.00633777549518229
110	0.992983179952801	0.0140336400943971	0.00701682004719855
111	0.993653838981214	0.0126923220375723	0.00634616101878614
112	0.991944235586551	0.0161115288268972	0.00805576441344861
113	0.995302695206813	0.00939460958637371	0.00469730479318686
114	0.994142129165073	0.0117157416698537	0.00585787083492687
115	0.992730974136803	0.014538051726395	0.00726902586319748
116	0.994500670563835	0.0109986588723306	0.0054993294361653
117	0.992994572128848	0.0140108557423032	0.00700542787115162
118	0.995377581531457	0.0092448369370855	0.00462241846854275
119	0.997158608874324	0.00568278225135153	0.00284139112567577
120	0.997226203828336	0.00554759234332843	0.00277379617166421
121	0.996459870743252	0.00708025851349675	0.00354012925674838
122	0.996021271493094	0.00795745701381123	0.00397872850690561
123	0.994932407853885	0.0101351842922296	0.00506759214611481
124	0.993976181047391	0.0120476379052184	0.00602381895260921
125	0.992339516961456	0.0153209660770876	0.00766048303854379
126	0.991761007708675	0.0164779845826507	0.00823899229132535
127	0.989701823369049	0.0205963532619029	0.0102981766309514
128	0.988158871738052	0.0236822565238965	0.0118411282619482
129	0.985320272438825	0.0293594551223506	0.0146797275611753
130	0.981989517155818	0.0360209656883642	0.0180104828441821
131	0.981010726019399	0.037978547961203	0.0189892739806015
132	0.978209680297395	0.0435806394052105	0.0217903197026052
133	0.975769978490354	0.0484600430192916	0.0242300215096458
134	0.974451257421514	0.051097485156973	0.0255487425784865
135	0.974120391279537	0.0517592174409255	0.0258796087204628
136	0.972714792323433	0.0545704153531346	0.0272852076765673
137	0.97041440124345	0.0591711975131006	0.0295855987565503
138	0.965629320851694	0.0687413582966118	0.0343706791483059
139	0.96031545600152	0.0793690879969604	0.0396845439984802
140	0.972917836469011	0.0541643270619777	0.0270821635309888
141	0.967524276979813	0.0649514460403743	0.0324757230201872
142	0.962857872125492	0.0742842557490163	0.0371421278745081
143	0.9696502122042	0.0606995755916008	0.0303497877958004
144	0.976236155068325	0.04752768986335	0.023763844931675
145	0.971542759091015	0.0569144818179698	0.0284572409089849
146	0.966504550520258	0.0669908989594837	0.0334954494797418
147	0.960387289432451	0.0792254211350976	0.0396127105675488
148	0.955913590282174	0.0881728194356519	0.044086409717826
149	0.947785016330704	0.104429967338593	0.0522149836692963
150	0.941587525711247	0.116824948577505	0.0584124742887525
151	0.934444431394511	0.131111137210978	0.0655555686054892
152	0.95417429806696	0.0916514038660807	0.0458257019330403
153	0.948937407489947	0.102125185020105	0.0510625925100525
154	0.950615802805622	0.0987683943887554	0.0493841971943777
155	0.942651257627183	0.114697484745634	0.0573487423728171
156	0.932262799759035	0.135474400481931	0.0677372002409654
157	0.920497180985084	0.159005638029833	0.0795028190149163
158	0.920772584883008	0.158454830233984	0.0792274151169922
159	0.913154780464315	0.17369043907137	0.086845219535685
160	0.906112497838814	0.187775004322371	0.0938875021611856
161	0.907551209863146	0.184897580273709	0.0924487901368543
162	0.933337367160291	0.133325265679417	0.0666626328397087
163	0.931881288143157	0.136237423713686	0.0681187118568432
164	0.920342094263248	0.159315811473503	0.0796579057367516
165	0.912003593399302	0.175992813201396	0.087996406600698
166	0.907680466536457	0.184639066927087	0.0923195334635434
167	0.913000795559065	0.173998408881869	0.0869992044409346
168	0.909782923122163	0.180434153755673	0.0902170768778365
169	0.908953168687414	0.182093662625172	0.0910468313125859
170	0.909420145783891	0.181159708432218	0.0905798542161089
171	0.96761153532055	0.0647769293589004	0.0323884646794502
172	0.962225512581317	0.0755489748373655	0.0377744874186828
173	0.968396390386907	0.0632072192261861	0.031603609613093
174	0.962222808562575	0.0755543828748507	0.0377771914374253
175	0.974081093718703	0.0518378125625946	0.0259189062812973
176	0.971783253985829	0.056433492028342	0.028216746014171
177	0.981155885873416	0.0376882282531679	0.018844114126584
178	0.980593325651106	0.038813348697787	0.0194066743488935
179	0.979647424922308	0.0407051501553842	0.0203525750776921
180	0.97933215866689	0.0413356826662205	0.0206678413331103
181	0.975101234672268	0.0497975306554632	0.0248987653277316
182	0.970198703074881	0.0596025938502386	0.0298012969251193
183	0.972757766480249	0.0544844670395024	0.0272422335197512
184	0.967433669262153	0.0651326614756949	0.0325663307378475
185	0.962124367779501	0.0757512644409977	0.0378756322204988
186	0.954340105781112	0.0913197884377769	0.0456598942188884
187	0.947822859366634	0.104354281266732	0.0521771406333661
188	0.960757742488231	0.0784845150235384	0.0392422575117692
189	0.9537202533536	0.0925594932928008	0.0462797466464004
190	0.945258308826916	0.109483382346168	0.054741691173084
191	0.93625261724754	0.127494765504919	0.0637473827524596
192	0.941845899101629	0.116308201796742	0.0581541008983711
193	0.941808283103126	0.116383433793747	0.0581917168968736
194	0.951394553252005	0.0972108934959906	0.0486054467479953
195	0.941450137198754	0.117099725602492	0.0585498628012461
196	0.933374363464599	0.133251273070801	0.0666256365354006
197	0.953202584050418	0.0935948318991638	0.0467974159495819
198	0.944084782945746	0.111830434108509	0.0559152170542543
199	0.93609248476816	0.127815030463681	0.0639075152318405
200	0.924700996579397	0.150598006841205	0.0752990034206026
201	0.91067489802406	0.17865020395188	0.0893251019759402
202	0.899878086422117	0.200243827155766	0.100121913577883
203	0.885879251058306	0.228241497883387	0.114120748941694
204	0.872164362685432	0.255671274629137	0.127835637314569
205	0.851837541921252	0.296324916157496	0.148162458078748
206	0.832971939144063	0.334056121711874	0.167028060855937
207	0.815218765277562	0.369562469444876	0.184781234722438
208	0.804158076225641	0.391683847548718	0.195841923774359
209	0.776585321009084	0.446829357981833	0.223414678990916
210	0.81582510120461	0.36834979759078	0.18417489879539
211	0.78881828602486	0.422363427950279	0.21118171397514
212	0.75967772278397	0.48064455443206	0.24032227721603
213	0.737498047547517	0.525003904904966	0.262501952452483
214	0.725299663272659	0.549400673454681	0.274700336727341
215	0.691671691474253	0.616656617051494	0.308328308525747
216	0.698769670076144	0.602460659847712	0.301230329923856
217	0.781956116111405	0.436087767777189	0.218043883888595
218	0.795525258690447	0.408949482619107	0.204474741309553
219	0.836466380255337	0.327067239489327	0.163533619744663
220	0.898208005062524	0.203583989874953	0.101791994937476
221	0.967128323499285	0.0657433530014292	0.0328716765007146
222	0.975599629917605	0.0488007401647891	0.0244003700823946
223	0.970293914461634	0.0594121710767311	0.0297060855383656
224	0.973446016318462	0.0531079673630764	0.0265539836815382
225	0.96719348801722	0.0656130239655597	0.0328065119827798
226	0.968241376806485	0.0635172463870294	0.0317586231935147
227	0.971686972651483	0.0566260546970335	0.0283130273485167
228	0.967267997088131	0.0654640058237382	0.0327320029118691
229	0.974426959502452	0.0511460809950956	0.0255730404975478
230	0.978200346565964	0.0435993068680712	0.0217996534340356
231	0.972228991323852	0.0555420173522968	0.0277710086761484
232	0.975866643101656	0.048266713796687	0.0241333568983435
233	0.984392103980149	0.0312157920397026	0.0156078960198513
234	0.981644243202961	0.0367115135940777	0.0183557567970389
235	0.978656124349486	0.0426877513010279	0.021343875650514
236	0.97551979091019	0.0489604181796209	0.0244802090898105
237	0.972393436478353	0.0552131270432932	0.0276065635216466
238	0.965719110073626	0.0685617798527482	0.0342808899263741
239	0.955952267512448	0.0880954649751048	0.0440477324875524
240	0.96976532039093	0.0604693592181397	0.0302346796090699
241	0.966804794152837	0.0663904116943257	0.0331952058471628
242	0.966720608791079	0.0665587824178416	0.0332793912089208
243	0.986222603427102	0.0275547931457966	0.0137773965728983
244	0.998320029861858	0.00335994027628312	0.00167997013814156
245	0.997944518565109	0.0041109628697812	0.0020554814348906
246	0.99694903745985	0.00610192508029906	0.00305096254014953
247	0.996169915987876	0.00766016802424859	0.0038300840121243
248	0.995627804530487	0.0087443909390269	0.00437219546951345
249	0.994421274905474	0.0111574501890521	0.00557872509452604
250	0.992724697012811	0.0145506059743779	0.00727530298718895
251	0.999706235410662	0.000587529178676645	0.000293764589338322
252	0.99989702724863	0.000205945502740477	0.000102972751370238
253	0.999847846313636	0.00030430737272723	0.000152153686363615
254	0.999951229263736	9.75414725270179e-05	4.8770736263509e-05
255	0.999927526356643	0.000144947286714172	7.24736433570859e-05
256	0.999881687877757	0.000236624244485577	0.000118312122242789
257	0.999794671564484	0.000410656871031194	0.000205328435515597
258	0.999661971726309	0.000676056547382254	0.000338028273691127
259	0.999640181389486	0.000719637221028117	0.000359818610514059
260	0.999529109852031	0.000941780295938137	0.000470890147969068
261	0.999843147792385	0.000313704415230006	0.000156852207615003
262	0.999754990676361	0.000490018647278701	0.00024500932363935
263	0.999700608541383	0.000598782917234683	0.000299391458617342
264	0.999416391869586	0.00116721626082861	0.000583608130414303
265	0.998917704818238	0.00216459036352309	0.00108229518176155
266	0.998432021068407	0.00313595786318547	0.00156797893159274
267	0.997484276025708	0.00503144794858302	0.00251572397429151
268	0.995455917140985	0.00908816571802907	0.00454408285901454
269	0.992885510444902	0.0142289791101958	0.00711448955509792
270	0.987666302289221	0.0246673954215572	0.0123336977107786
271	0.982220696488092	0.0355586070238153	0.0177793035119076
272	0.975583296562291	0.048833406875417	0.0244167034377085
273	0.963485452653294	0.0730290946934118	0.0365145473467059
274	0.940935403701801	0.118129192596399	0.0590645962981995
275	0.90647740223755	0.187045195524901	0.0935225977624503
276	0.868039691722218	0.263920616555565	0.131960308277782
277	0.871372196845812	0.257255606308376	0.128627803154188
278	0.915013021830915	0.16997395633817	0.0849869781690851
279	0.887611159821998	0.224777680356004	0.112388840178002
280	0.95439227441222	0.0912154511755592	0.0456077255877796
281	0.91892073698233	0.162158526035339	0.0810792630176697
282	0.836034705297675	0.327930589404649	0.163965294702325
283	1	1.19909340196844e-46	5.9954670098422e-47

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
15 & 5.25595016926085e-40 & 1.05119003385217e-39 & 1 \tabularnewline
16 & 7.03172370631854e-55 & 1.40634474126371e-54 & 1 \tabularnewline
17 & 0.547557000086192 & 0.904885999827616 & 0.452442999913808 \tabularnewline
18 & 0.461663389715576 & 0.923326779431152 & 0.538336610284424 \tabularnewline
19 & 0.602898652720776 & 0.794202694558448 & 0.397101347279224 \tabularnewline
20 & 0.498878088536986 & 0.997756177073971 & 0.501121911463014 \tabularnewline
21 & 0.405727064076504 & 0.811454128153008 & 0.594272935923496 \tabularnewline
22 & 0.467187303288956 & 0.934374606577912 & 0.532812696711044 \tabularnewline
23 & 0.464745829704057 & 0.929491659408115 & 0.535254170295943 \tabularnewline
24 & 0.483195967417473 & 0.966391934834945 & 0.516804032582527 \tabularnewline
25 & 0.769025347086883 & 0.461949305826235 & 0.230974652913117 \tabularnewline
26 & 0.726805783329712 & 0.546388433340577 & 0.273194216670288 \tabularnewline
27 & 0.890371203031083 & 0.219257593937834 & 0.109628796968917 \tabularnewline
28 & 0.960258918309945 & 0.07948216338011 & 0.039741081690055 \tabularnewline
29 & 0.948218658166741 & 0.103562683666517 & 0.0517813418332585 \tabularnewline
30 & 0.93705210404215 & 0.1258957919157 & 0.0629478959578501 \tabularnewline
31 & 0.945125615669434 & 0.109748768661131 & 0.0548743843305657 \tabularnewline
32 & 0.930254460824958 & 0.139491078350083 & 0.0697455391750416 \tabularnewline
33 & 0.909895172403286 & 0.180209655193428 & 0.0901048275967141 \tabularnewline
34 & 0.969075677448379 & 0.061848645103243 & 0.0309243225516215 \tabularnewline
35 & 0.963251211290745 & 0.07349757741851 & 0.036748788709255 \tabularnewline
36 & 0.991361797850197 & 0.0172764042996054 & 0.0086382021498027 \tabularnewline
37 & 0.990112031383664 & 0.019775937232673 & 0.00988796861633649 \tabularnewline
38 & 0.986331783107547 & 0.0273364337849062 & 0.0136682168924531 \tabularnewline
39 & 0.984434838835687 & 0.0311303223286253 & 0.0155651611643126 \tabularnewline
40 & 0.980752715932267 & 0.0384945681354663 & 0.0192472840677331 \tabularnewline
41 & 0.984066915327378 & 0.0318661693452444 & 0.0159330846726222 \tabularnewline
42 & 0.979174883834253 & 0.0416502323314933 & 0.0208251161657466 \tabularnewline
43 & 0.973412202696383 & 0.0531755946072341 & 0.0265877973036171 \tabularnewline
44 & 0.97500478529893 & 0.0499904294021404 & 0.0249952147010702 \tabularnewline
45 & 0.977271259196731 & 0.0454574816065381 & 0.022728740803269 \tabularnewline
46 & 0.976946961714308 & 0.0461060765713839 & 0.0230530382856919 \tabularnewline
47 & 0.970336197678683 & 0.0593276046426345 & 0.0296638023213172 \tabularnewline
48 & 0.961644486260015 & 0.0767110274799693 & 0.0383555137399846 \tabularnewline
49 & 0.954458045698029 & 0.0910839086039417 & 0.0455419543019709 \tabularnewline
50 & 0.94272447687738 & 0.11455104624524 & 0.0572755231226202 \tabularnewline
51 & 0.938257517281429 & 0.123484965437142 & 0.0617424827185711 \tabularnewline
52 & 0.936978400588866 & 0.126043198822269 & 0.0630215994111344 \tabularnewline
53 & 0.935854704769173 & 0.128290590461654 & 0.064145295230827 \tabularnewline
54 & 0.920744332622613 & 0.158511334754773 & 0.0792556673773865 \tabularnewline
55 & 0.962996494094224 & 0.0740070118115513 & 0.0370035059057756 \tabularnewline
56 & 0.985926035201241 & 0.0281479295975189 & 0.0140739647987594 \tabularnewline
57 & 0.99334409470276 & 0.0133118105944802 & 0.00665590529724011 \tabularnewline
58 & 0.991116146983406 & 0.0177677060331889 & 0.00888385301659443 \tabularnewline
59 & 0.990405678007081 & 0.0191886439858384 & 0.00959432199291919 \tabularnewline
60 & 0.993362085791203 & 0.0132758284175937 & 0.00663791420879684 \tabularnewline
61 & 0.991826388430731 & 0.0163472231385382 & 0.0081736115692691 \tabularnewline
62 & 0.98919651235298 & 0.0216069752940404 & 0.0108034876470202 \tabularnewline
63 & 0.98705565000419 & 0.0258886999916208 & 0.0129443499958104 \tabularnewline
64 & 0.985943448347621 & 0.0281131033047573 & 0.0140565516523787 \tabularnewline
65 & 0.98395918469415 & 0.0320816306117001 & 0.0160408153058501 \tabularnewline
66 & 0.980278842775788 & 0.0394423144484236 & 0.0197211572242118 \tabularnewline
67 & 0.978407357093066 & 0.0431852858138675 & 0.0215926429069338 \tabularnewline
68 & 0.978418966947804 & 0.0431620661043929 & 0.0215810330521964 \tabularnewline
69 & 0.973727029175499 & 0.0525459416490019 & 0.026272970824501 \tabularnewline
70 & 0.967043360486754 & 0.065913279026492 & 0.032956639513246 \tabularnewline
71 & 0.971773807285287 & 0.0564523854294255 & 0.0282261927147128 \tabularnewline
72 & 0.973581328705542 & 0.0528373425889154 & 0.0264186712944577 \tabularnewline
73 & 0.984449854461802 & 0.0311002910763957 & 0.0155501455381979 \tabularnewline
74 & 0.983423313099956 & 0.0331533738000887 & 0.0165766869000444 \tabularnewline
75 & 0.97980863436467 & 0.0403827312706605 & 0.0201913656353302 \tabularnewline
76 & 0.974695046907716 & 0.050609906184567 & 0.0253049530922835 \tabularnewline
77 & 0.983529235156406 & 0.0329415296871882 & 0.0164707648435941 \tabularnewline
78 & 0.980897008760256 & 0.0382059824794873 & 0.0191029912397437 \tabularnewline
79 & 0.977949055265097 & 0.0441018894698065 & 0.0220509447349033 \tabularnewline
80 & 0.984065088110387 & 0.0318698237792269 & 0.0159349118896135 \tabularnewline
81 & 0.982153105912904 & 0.0356937881741927 & 0.0178468940870964 \tabularnewline
82 & 0.986311182816767 & 0.0273776343664668 & 0.0136888171832334 \tabularnewline
83 & 0.98540947043047 & 0.0291810591390595 & 0.0145905295695297 \tabularnewline
84 & 0.982376810532686 & 0.0352463789346289 & 0.0176231894673144 \tabularnewline
85 & 0.987151245578794 & 0.0256975088424122 & 0.0128487544212061 \tabularnewline
86 & 0.989409532281402 & 0.0211809354371959 & 0.010590467718598 \tabularnewline
87 & 0.98762619795466 & 0.0247476040906795 & 0.0123738020453397 \tabularnewline
88 & 0.984647613994726 & 0.0307047720105489 & 0.0153523860052745 \tabularnewline
89 & 0.985610212197681 & 0.0287795756046387 & 0.0143897878023194 \tabularnewline
90 & 0.98648157497065 & 0.0270368500586992 & 0.0135184250293496 \tabularnewline
91 & 0.984086561775488 & 0.0318268764490241 & 0.0159134382245121 \tabularnewline
92 & 0.981044384064277 & 0.0379112318714468 & 0.0189556159357234 \tabularnewline
93 & 0.98407285783746 & 0.031854284325081 & 0.0159271421625405 \tabularnewline
94 & 0.984104688387863 & 0.0317906232242735 & 0.0158953116121368 \tabularnewline
95 & 0.982393729133093 & 0.0352125417338148 & 0.0176062708669074 \tabularnewline
96 & 0.979859564833268 & 0.0402808703334634 & 0.0201404351667317 \tabularnewline
97 & 0.989059662489474 & 0.0218806750210524 & 0.0109403375105262 \tabularnewline
98 & 0.986824326642951 & 0.0263513467140974 & 0.0131756733570487 \tabularnewline
99 & 0.990600548126499 & 0.0187989037470017 & 0.00939945187350086 \tabularnewline
100 & 0.994522026030794 & 0.0109559479384126 & 0.00547797396920629 \tabularnewline
101 & 0.99332789803387 & 0.0133442039322595 & 0.00667210196612973 \tabularnewline
102 & 0.99445893890429 & 0.0110821221914191 & 0.00554106109570956 \tabularnewline
103 & 0.994229415177198 & 0.0115411696456049 & 0.00577058482280247 \tabularnewline
104 & 0.994045876479136 & 0.0119082470417284 & 0.00595412352086418 \tabularnewline
105 & 0.992816373945088 & 0.014367252109824 & 0.007183626054912 \tabularnewline
106 & 0.994682354444296 & 0.0106352911114075 & 0.00531764555570375 \tabularnewline
107 & 0.99576572965589 & 0.00846854068821937 & 0.00423427034410968 \tabularnewline
108 & 0.994796716784655 & 0.0104065664306899 & 0.00520328321534493 \tabularnewline
109 & 0.993662224504818 & 0.0126755509903646 & 0.00633777549518229 \tabularnewline
110 & 0.992983179952801 & 0.0140336400943971 & 0.00701682004719855 \tabularnewline
111 & 0.993653838981214 & 0.0126923220375723 & 0.00634616101878614 \tabularnewline
112 & 0.991944235586551 & 0.0161115288268972 & 0.00805576441344861 \tabularnewline
113 & 0.995302695206813 & 0.00939460958637371 & 0.00469730479318686 \tabularnewline
114 & 0.994142129165073 & 0.0117157416698537 & 0.00585787083492687 \tabularnewline
115 & 0.992730974136803 & 0.014538051726395 & 0.00726902586319748 \tabularnewline
116 & 0.994500670563835 & 0.0109986588723306 & 0.0054993294361653 \tabularnewline
117 & 0.992994572128848 & 0.0140108557423032 & 0.00700542787115162 \tabularnewline
118 & 0.995377581531457 & 0.0092448369370855 & 0.00462241846854275 \tabularnewline
119 & 0.997158608874324 & 0.00568278225135153 & 0.00284139112567577 \tabularnewline
120 & 0.997226203828336 & 0.00554759234332843 & 0.00277379617166421 \tabularnewline
121 & 0.996459870743252 & 0.00708025851349675 & 0.00354012925674838 \tabularnewline
122 & 0.996021271493094 & 0.00795745701381123 & 0.00397872850690561 \tabularnewline
123 & 0.994932407853885 & 0.0101351842922296 & 0.00506759214611481 \tabularnewline
124 & 0.993976181047391 & 0.0120476379052184 & 0.00602381895260921 \tabularnewline
125 & 0.992339516961456 & 0.0153209660770876 & 0.00766048303854379 \tabularnewline
126 & 0.991761007708675 & 0.0164779845826507 & 0.00823899229132535 \tabularnewline
127 & 0.989701823369049 & 0.0205963532619029 & 0.0102981766309514 \tabularnewline
128 & 0.988158871738052 & 0.0236822565238965 & 0.0118411282619482 \tabularnewline
129 & 0.985320272438825 & 0.0293594551223506 & 0.0146797275611753 \tabularnewline
130 & 0.981989517155818 & 0.0360209656883642 & 0.0180104828441821 \tabularnewline
131 & 0.981010726019399 & 0.037978547961203 & 0.0189892739806015 \tabularnewline
132 & 0.978209680297395 & 0.0435806394052105 & 0.0217903197026052 \tabularnewline
133 & 0.975769978490354 & 0.0484600430192916 & 0.0242300215096458 \tabularnewline
134 & 0.974451257421514 & 0.051097485156973 & 0.0255487425784865 \tabularnewline
135 & 0.974120391279537 & 0.0517592174409255 & 0.0258796087204628 \tabularnewline
136 & 0.972714792323433 & 0.0545704153531346 & 0.0272852076765673 \tabularnewline
137 & 0.97041440124345 & 0.0591711975131006 & 0.0295855987565503 \tabularnewline
138 & 0.965629320851694 & 0.0687413582966118 & 0.0343706791483059 \tabularnewline
139 & 0.96031545600152 & 0.0793690879969604 & 0.0396845439984802 \tabularnewline
140 & 0.972917836469011 & 0.0541643270619777 & 0.0270821635309888 \tabularnewline
141 & 0.967524276979813 & 0.0649514460403743 & 0.0324757230201872 \tabularnewline
142 & 0.962857872125492 & 0.0742842557490163 & 0.0371421278745081 \tabularnewline
143 & 0.9696502122042 & 0.0606995755916008 & 0.0303497877958004 \tabularnewline
144 & 0.976236155068325 & 0.04752768986335 & 0.023763844931675 \tabularnewline
145 & 0.971542759091015 & 0.0569144818179698 & 0.0284572409089849 \tabularnewline
146 & 0.966504550520258 & 0.0669908989594837 & 0.0334954494797418 \tabularnewline
147 & 0.960387289432451 & 0.0792254211350976 & 0.0396127105675488 \tabularnewline
148 & 0.955913590282174 & 0.0881728194356519 & 0.044086409717826 \tabularnewline
149 & 0.947785016330704 & 0.104429967338593 & 0.0522149836692963 \tabularnewline
150 & 0.941587525711247 & 0.116824948577505 & 0.0584124742887525 \tabularnewline
151 & 0.934444431394511 & 0.131111137210978 & 0.0655555686054892 \tabularnewline
152 & 0.95417429806696 & 0.0916514038660807 & 0.0458257019330403 \tabularnewline
153 & 0.948937407489947 & 0.102125185020105 & 0.0510625925100525 \tabularnewline
154 & 0.950615802805622 & 0.0987683943887554 & 0.0493841971943777 \tabularnewline
155 & 0.942651257627183 & 0.114697484745634 & 0.0573487423728171 \tabularnewline
156 & 0.932262799759035 & 0.135474400481931 & 0.0677372002409654 \tabularnewline
157 & 0.920497180985084 & 0.159005638029833 & 0.0795028190149163 \tabularnewline
158 & 0.920772584883008 & 0.158454830233984 & 0.0792274151169922 \tabularnewline
159 & 0.913154780464315 & 0.17369043907137 & 0.086845219535685 \tabularnewline
160 & 0.906112497838814 & 0.187775004322371 & 0.0938875021611856 \tabularnewline
161 & 0.907551209863146 & 0.184897580273709 & 0.0924487901368543 \tabularnewline
162 & 0.933337367160291 & 0.133325265679417 & 0.0666626328397087 \tabularnewline
163 & 0.931881288143157 & 0.136237423713686 & 0.0681187118568432 \tabularnewline
164 & 0.920342094263248 & 0.159315811473503 & 0.0796579057367516 \tabularnewline
165 & 0.912003593399302 & 0.175992813201396 & 0.087996406600698 \tabularnewline
166 & 0.907680466536457 & 0.184639066927087 & 0.0923195334635434 \tabularnewline
167 & 0.913000795559065 & 0.173998408881869 & 0.0869992044409346 \tabularnewline
168 & 0.909782923122163 & 0.180434153755673 & 0.0902170768778365 \tabularnewline
169 & 0.908953168687414 & 0.182093662625172 & 0.0910468313125859 \tabularnewline
170 & 0.909420145783891 & 0.181159708432218 & 0.0905798542161089 \tabularnewline
171 & 0.96761153532055 & 0.0647769293589004 & 0.0323884646794502 \tabularnewline
172 & 0.962225512581317 & 0.0755489748373655 & 0.0377744874186828 \tabularnewline
173 & 0.968396390386907 & 0.0632072192261861 & 0.031603609613093 \tabularnewline
174 & 0.962222808562575 & 0.0755543828748507 & 0.0377771914374253 \tabularnewline
175 & 0.974081093718703 & 0.0518378125625946 & 0.0259189062812973 \tabularnewline
176 & 0.971783253985829 & 0.056433492028342 & 0.028216746014171 \tabularnewline
177 & 0.981155885873416 & 0.0376882282531679 & 0.018844114126584 \tabularnewline
178 & 0.980593325651106 & 0.038813348697787 & 0.0194066743488935 \tabularnewline
179 & 0.979647424922308 & 0.0407051501553842 & 0.0203525750776921 \tabularnewline
180 & 0.97933215866689 & 0.0413356826662205 & 0.0206678413331103 \tabularnewline
181 & 0.975101234672268 & 0.0497975306554632 & 0.0248987653277316 \tabularnewline
182 & 0.970198703074881 & 0.0596025938502386 & 0.0298012969251193 \tabularnewline
183 & 0.972757766480249 & 0.0544844670395024 & 0.0272422335197512 \tabularnewline
184 & 0.967433669262153 & 0.0651326614756949 & 0.0325663307378475 \tabularnewline
185 & 0.962124367779501 & 0.0757512644409977 & 0.0378756322204988 \tabularnewline
186 & 0.954340105781112 & 0.0913197884377769 & 0.0456598942188884 \tabularnewline
187 & 0.947822859366634 & 0.104354281266732 & 0.0521771406333661 \tabularnewline
188 & 0.960757742488231 & 0.0784845150235384 & 0.0392422575117692 \tabularnewline
189 & 0.9537202533536 & 0.0925594932928008 & 0.0462797466464004 \tabularnewline
190 & 0.945258308826916 & 0.109483382346168 & 0.054741691173084 \tabularnewline
191 & 0.93625261724754 & 0.127494765504919 & 0.0637473827524596 \tabularnewline
192 & 0.941845899101629 & 0.116308201796742 & 0.0581541008983711 \tabularnewline
193 & 0.941808283103126 & 0.116383433793747 & 0.0581917168968736 \tabularnewline
194 & 0.951394553252005 & 0.0972108934959906 & 0.0486054467479953 \tabularnewline
195 & 0.941450137198754 & 0.117099725602492 & 0.0585498628012461 \tabularnewline
196 & 0.933374363464599 & 0.133251273070801 & 0.0666256365354006 \tabularnewline
197 & 0.953202584050418 & 0.0935948318991638 & 0.0467974159495819 \tabularnewline
198 & 0.944084782945746 & 0.111830434108509 & 0.0559152170542543 \tabularnewline
199 & 0.93609248476816 & 0.127815030463681 & 0.0639075152318405 \tabularnewline
200 & 0.924700996579397 & 0.150598006841205 & 0.0752990034206026 \tabularnewline
201 & 0.91067489802406 & 0.17865020395188 & 0.0893251019759402 \tabularnewline
202 & 0.899878086422117 & 0.200243827155766 & 0.100121913577883 \tabularnewline
203 & 0.885879251058306 & 0.228241497883387 & 0.114120748941694 \tabularnewline
204 & 0.872164362685432 & 0.255671274629137 & 0.127835637314569 \tabularnewline
205 & 0.851837541921252 & 0.296324916157496 & 0.148162458078748 \tabularnewline
206 & 0.832971939144063 & 0.334056121711874 & 0.167028060855937 \tabularnewline
207 & 0.815218765277562 & 0.369562469444876 & 0.184781234722438 \tabularnewline
208 & 0.804158076225641 & 0.391683847548718 & 0.195841923774359 \tabularnewline
209 & 0.776585321009084 & 0.446829357981833 & 0.223414678990916 \tabularnewline
210 & 0.81582510120461 & 0.36834979759078 & 0.18417489879539 \tabularnewline
211 & 0.78881828602486 & 0.422363427950279 & 0.21118171397514 \tabularnewline
212 & 0.75967772278397 & 0.48064455443206 & 0.24032227721603 \tabularnewline
213 & 0.737498047547517 & 0.525003904904966 & 0.262501952452483 \tabularnewline
214 & 0.725299663272659 & 0.549400673454681 & 0.274700336727341 \tabularnewline
215 & 0.691671691474253 & 0.616656617051494 & 0.308328308525747 \tabularnewline
216 & 0.698769670076144 & 0.602460659847712 & 0.301230329923856 \tabularnewline
217 & 0.781956116111405 & 0.436087767777189 & 0.218043883888595 \tabularnewline
218 & 0.795525258690447 & 0.408949482619107 & 0.204474741309553 \tabularnewline
219 & 0.836466380255337 & 0.327067239489327 & 0.163533619744663 \tabularnewline
220 & 0.898208005062524 & 0.203583989874953 & 0.101791994937476 \tabularnewline
221 & 0.967128323499285 & 0.0657433530014292 & 0.0328716765007146 \tabularnewline
222 & 0.975599629917605 & 0.0488007401647891 & 0.0244003700823946 \tabularnewline
223 & 0.970293914461634 & 0.0594121710767311 & 0.0297060855383656 \tabularnewline
224 & 0.973446016318462 & 0.0531079673630764 & 0.0265539836815382 \tabularnewline
225 & 0.96719348801722 & 0.0656130239655597 & 0.0328065119827798 \tabularnewline
226 & 0.968241376806485 & 0.0635172463870294 & 0.0317586231935147 \tabularnewline
227 & 0.971686972651483 & 0.0566260546970335 & 0.0283130273485167 \tabularnewline
228 & 0.967267997088131 & 0.0654640058237382 & 0.0327320029118691 \tabularnewline
229 & 0.974426959502452 & 0.0511460809950956 & 0.0255730404975478 \tabularnewline
230 & 0.978200346565964 & 0.0435993068680712 & 0.0217996534340356 \tabularnewline
231 & 0.972228991323852 & 0.0555420173522968 & 0.0277710086761484 \tabularnewline
232 & 0.975866643101656 & 0.048266713796687 & 0.0241333568983435 \tabularnewline
233 & 0.984392103980149 & 0.0312157920397026 & 0.0156078960198513 \tabularnewline
234 & 0.981644243202961 & 0.0367115135940777 & 0.0183557567970389 \tabularnewline
235 & 0.978656124349486 & 0.0426877513010279 & 0.021343875650514 \tabularnewline
236 & 0.97551979091019 & 0.0489604181796209 & 0.0244802090898105 \tabularnewline
237 & 0.972393436478353 & 0.0552131270432932 & 0.0276065635216466 \tabularnewline
238 & 0.965719110073626 & 0.0685617798527482 & 0.0342808899263741 \tabularnewline
239 & 0.955952267512448 & 0.0880954649751048 & 0.0440477324875524 \tabularnewline
240 & 0.96976532039093 & 0.0604693592181397 & 0.0302346796090699 \tabularnewline
241 & 0.966804794152837 & 0.0663904116943257 & 0.0331952058471628 \tabularnewline
242 & 0.966720608791079 & 0.0665587824178416 & 0.0332793912089208 \tabularnewline
243 & 0.986222603427102 & 0.0275547931457966 & 0.0137773965728983 \tabularnewline
244 & 0.998320029861858 & 0.00335994027628312 & 0.00167997013814156 \tabularnewline
245 & 0.997944518565109 & 0.0041109628697812 & 0.0020554814348906 \tabularnewline
246 & 0.99694903745985 & 0.00610192508029906 & 0.00305096254014953 \tabularnewline
247 & 0.996169915987876 & 0.00766016802424859 & 0.0038300840121243 \tabularnewline
248 & 0.995627804530487 & 0.0087443909390269 & 0.00437219546951345 \tabularnewline
249 & 0.994421274905474 & 0.0111574501890521 & 0.00557872509452604 \tabularnewline
250 & 0.992724697012811 & 0.0145506059743779 & 0.00727530298718895 \tabularnewline
251 & 0.999706235410662 & 0.000587529178676645 & 0.000293764589338322 \tabularnewline
252 & 0.99989702724863 & 0.000205945502740477 & 0.000102972751370238 \tabularnewline
253 & 0.999847846313636 & 0.00030430737272723 & 0.000152153686363615 \tabularnewline
254 & 0.999951229263736 & 9.75414725270179e-05 & 4.8770736263509e-05 \tabularnewline
255 & 0.999927526356643 & 0.000144947286714172 & 7.24736433570859e-05 \tabularnewline
256 & 0.999881687877757 & 0.000236624244485577 & 0.000118312122242789 \tabularnewline
257 & 0.999794671564484 & 0.000410656871031194 & 0.000205328435515597 \tabularnewline
258 & 0.999661971726309 & 0.000676056547382254 & 0.000338028273691127 \tabularnewline
259 & 0.999640181389486 & 0.000719637221028117 & 0.000359818610514059 \tabularnewline
260 & 0.999529109852031 & 0.000941780295938137 & 0.000470890147969068 \tabularnewline
261 & 0.999843147792385 & 0.000313704415230006 & 0.000156852207615003 \tabularnewline
262 & 0.999754990676361 & 0.000490018647278701 & 0.00024500932363935 \tabularnewline
263 & 0.999700608541383 & 0.000598782917234683 & 0.000299391458617342 \tabularnewline
264 & 0.999416391869586 & 0.00116721626082861 & 0.000583608130414303 \tabularnewline
265 & 0.998917704818238 & 0.00216459036352309 & 0.00108229518176155 \tabularnewline
266 & 0.998432021068407 & 0.00313595786318547 & 0.00156797893159274 \tabularnewline
267 & 0.997484276025708 & 0.00503144794858302 & 0.00251572397429151 \tabularnewline
268 & 0.995455917140985 & 0.00908816571802907 & 0.00454408285901454 \tabularnewline
269 & 0.992885510444902 & 0.0142289791101958 & 0.00711448955509792 \tabularnewline
270 & 0.987666302289221 & 0.0246673954215572 & 0.0123336977107786 \tabularnewline
271 & 0.982220696488092 & 0.0355586070238153 & 0.0177793035119076 \tabularnewline
272 & 0.975583296562291 & 0.048833406875417 & 0.0244167034377085 \tabularnewline
273 & 0.963485452653294 & 0.0730290946934118 & 0.0365145473467059 \tabularnewline
274 & 0.940935403701801 & 0.118129192596399 & 0.0590645962981995 \tabularnewline
275 & 0.90647740223755 & 0.187045195524901 & 0.0935225977624503 \tabularnewline
276 & 0.868039691722218 & 0.263920616555565 & 0.131960308277782 \tabularnewline
277 & 0.871372196845812 & 0.257255606308376 & 0.128627803154188 \tabularnewline
278 & 0.915013021830915 & 0.16997395633817 & 0.0849869781690851 \tabularnewline
279 & 0.887611159821998 & 0.224777680356004 & 0.112388840178002 \tabularnewline
280 & 0.95439227441222 & 0.0912154511755592 & 0.0456077255877796 \tabularnewline
281 & 0.91892073698233 & 0.162158526035339 & 0.0810792630176697 \tabularnewline
282 & 0.836034705297675 & 0.327930589404649 & 0.163965294702325 \tabularnewline
283 & 1 & 1.19909340196844e-46 & 5.9954670098422e-47 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154771&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]15[/C][C]5.25595016926085e-40[/C][C]1.05119003385217e-39[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]7.03172370631854e-55[/C][C]1.40634474126371e-54[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]0.547557000086192[/C][C]0.904885999827616[/C][C]0.452442999913808[/C][/ROW]
[ROW][C]18[/C][C]0.461663389715576[/C][C]0.923326779431152[/C][C]0.538336610284424[/C][/ROW]
[ROW][C]19[/C][C]0.602898652720776[/C][C]0.794202694558448[/C][C]0.397101347279224[/C][/ROW]
[ROW][C]20[/C][C]0.498878088536986[/C][C]0.997756177073971[/C][C]0.501121911463014[/C][/ROW]
[ROW][C]21[/C][C]0.405727064076504[/C][C]0.811454128153008[/C][C]0.594272935923496[/C][/ROW]
[ROW][C]22[/C][C]0.467187303288956[/C][C]0.934374606577912[/C][C]0.532812696711044[/C][/ROW]
[ROW][C]23[/C][C]0.464745829704057[/C][C]0.929491659408115[/C][C]0.535254170295943[/C][/ROW]
[ROW][C]24[/C][C]0.483195967417473[/C][C]0.966391934834945[/C][C]0.516804032582527[/C][/ROW]
[ROW][C]25[/C][C]0.769025347086883[/C][C]0.461949305826235[/C][C]0.230974652913117[/C][/ROW]
[ROW][C]26[/C][C]0.726805783329712[/C][C]0.546388433340577[/C][C]0.273194216670288[/C][/ROW]
[ROW][C]27[/C][C]0.890371203031083[/C][C]0.219257593937834[/C][C]0.109628796968917[/C][/ROW]
[ROW][C]28[/C][C]0.960258918309945[/C][C]0.07948216338011[/C][C]0.039741081690055[/C][/ROW]
[ROW][C]29[/C][C]0.948218658166741[/C][C]0.103562683666517[/C][C]0.0517813418332585[/C][/ROW]
[ROW][C]30[/C][C]0.93705210404215[/C][C]0.1258957919157[/C][C]0.0629478959578501[/C][/ROW]
[ROW][C]31[/C][C]0.945125615669434[/C][C]0.109748768661131[/C][C]0.0548743843305657[/C][/ROW]
[ROW][C]32[/C][C]0.930254460824958[/C][C]0.139491078350083[/C][C]0.0697455391750416[/C][/ROW]
[ROW][C]33[/C][C]0.909895172403286[/C][C]0.180209655193428[/C][C]0.0901048275967141[/C][/ROW]
[ROW][C]34[/C][C]0.969075677448379[/C][C]0.061848645103243[/C][C]0.0309243225516215[/C][/ROW]
[ROW][C]35[/C][C]0.963251211290745[/C][C]0.07349757741851[/C][C]0.036748788709255[/C][/ROW]
[ROW][C]36[/C][C]0.991361797850197[/C][C]0.0172764042996054[/C][C]0.0086382021498027[/C][/ROW]
[ROW][C]37[/C][C]0.990112031383664[/C][C]0.019775937232673[/C][C]0.00988796861633649[/C][/ROW]
[ROW][C]38[/C][C]0.986331783107547[/C][C]0.0273364337849062[/C][C]0.0136682168924531[/C][/ROW]
[ROW][C]39[/C][C]0.984434838835687[/C][C]0.0311303223286253[/C][C]0.0155651611643126[/C][/ROW]
[ROW][C]40[/C][C]0.980752715932267[/C][C]0.0384945681354663[/C][C]0.0192472840677331[/C][/ROW]
[ROW][C]41[/C][C]0.984066915327378[/C][C]0.0318661693452444[/C][C]0.0159330846726222[/C][/ROW]
[ROW][C]42[/C][C]0.979174883834253[/C][C]0.0416502323314933[/C][C]0.0208251161657466[/C][/ROW]
[ROW][C]43[/C][C]0.973412202696383[/C][C]0.0531755946072341[/C][C]0.0265877973036171[/C][/ROW]
[ROW][C]44[/C][C]0.97500478529893[/C][C]0.0499904294021404[/C][C]0.0249952147010702[/C][/ROW]
[ROW][C]45[/C][C]0.977271259196731[/C][C]0.0454574816065381[/C][C]0.022728740803269[/C][/ROW]
[ROW][C]46[/C][C]0.976946961714308[/C][C]0.0461060765713839[/C][C]0.0230530382856919[/C][/ROW]
[ROW][C]47[/C][C]0.970336197678683[/C][C]0.0593276046426345[/C][C]0.0296638023213172[/C][/ROW]
[ROW][C]48[/C][C]0.961644486260015[/C][C]0.0767110274799693[/C][C]0.0383555137399846[/C][/ROW]
[ROW][C]49[/C][C]0.954458045698029[/C][C]0.0910839086039417[/C][C]0.0455419543019709[/C][/ROW]
[ROW][C]50[/C][C]0.94272447687738[/C][C]0.11455104624524[/C][C]0.0572755231226202[/C][/ROW]
[ROW][C]51[/C][C]0.938257517281429[/C][C]0.123484965437142[/C][C]0.0617424827185711[/C][/ROW]
[ROW][C]52[/C][C]0.936978400588866[/C][C]0.126043198822269[/C][C]0.0630215994111344[/C][/ROW]
[ROW][C]53[/C][C]0.935854704769173[/C][C]0.128290590461654[/C][C]0.064145295230827[/C][/ROW]
[ROW][C]54[/C][C]0.920744332622613[/C][C]0.158511334754773[/C][C]0.0792556673773865[/C][/ROW]
[ROW][C]55[/C][C]0.962996494094224[/C][C]0.0740070118115513[/C][C]0.0370035059057756[/C][/ROW]
[ROW][C]56[/C][C]0.985926035201241[/C][C]0.0281479295975189[/C][C]0.0140739647987594[/C][/ROW]
[ROW][C]57[/C][C]0.99334409470276[/C][C]0.0133118105944802[/C][C]0.00665590529724011[/C][/ROW]
[ROW][C]58[/C][C]0.991116146983406[/C][C]0.0177677060331889[/C][C]0.00888385301659443[/C][/ROW]
[ROW][C]59[/C][C]0.990405678007081[/C][C]0.0191886439858384[/C][C]0.00959432199291919[/C][/ROW]
[ROW][C]60[/C][C]0.993362085791203[/C][C]0.0132758284175937[/C][C]0.00663791420879684[/C][/ROW]
[ROW][C]61[/C][C]0.991826388430731[/C][C]0.0163472231385382[/C][C]0.0081736115692691[/C][/ROW]
[ROW][C]62[/C][C]0.98919651235298[/C][C]0.0216069752940404[/C][C]0.0108034876470202[/C][/ROW]
[ROW][C]63[/C][C]0.98705565000419[/C][C]0.0258886999916208[/C][C]0.0129443499958104[/C][/ROW]
[ROW][C]64[/C][C]0.985943448347621[/C][C]0.0281131033047573[/C][C]0.0140565516523787[/C][/ROW]
[ROW][C]65[/C][C]0.98395918469415[/C][C]0.0320816306117001[/C][C]0.0160408153058501[/C][/ROW]
[ROW][C]66[/C][C]0.980278842775788[/C][C]0.0394423144484236[/C][C]0.0197211572242118[/C][/ROW]
[ROW][C]67[/C][C]0.978407357093066[/C][C]0.0431852858138675[/C][C]0.0215926429069338[/C][/ROW]
[ROW][C]68[/C][C]0.978418966947804[/C][C]0.0431620661043929[/C][C]0.0215810330521964[/C][/ROW]
[ROW][C]69[/C][C]0.973727029175499[/C][C]0.0525459416490019[/C][C]0.026272970824501[/C][/ROW]
[ROW][C]70[/C][C]0.967043360486754[/C][C]0.065913279026492[/C][C]0.032956639513246[/C][/ROW]
[ROW][C]71[/C][C]0.971773807285287[/C][C]0.0564523854294255[/C][C]0.0282261927147128[/C][/ROW]
[ROW][C]72[/C][C]0.973581328705542[/C][C]0.0528373425889154[/C][C]0.0264186712944577[/C][/ROW]
[ROW][C]73[/C][C]0.984449854461802[/C][C]0.0311002910763957[/C][C]0.0155501455381979[/C][/ROW]
[ROW][C]74[/C][C]0.983423313099956[/C][C]0.0331533738000887[/C][C]0.0165766869000444[/C][/ROW]
[ROW][C]75[/C][C]0.97980863436467[/C][C]0.0403827312706605[/C][C]0.0201913656353302[/C][/ROW]
[ROW][C]76[/C][C]0.974695046907716[/C][C]0.050609906184567[/C][C]0.0253049530922835[/C][/ROW]
[ROW][C]77[/C][C]0.983529235156406[/C][C]0.0329415296871882[/C][C]0.0164707648435941[/C][/ROW]
[ROW][C]78[/C][C]0.980897008760256[/C][C]0.0382059824794873[/C][C]0.0191029912397437[/C][/ROW]
[ROW][C]79[/C][C]0.977949055265097[/C][C]0.0441018894698065[/C][C]0.0220509447349033[/C][/ROW]
[ROW][C]80[/C][C]0.984065088110387[/C][C]0.0318698237792269[/C][C]0.0159349118896135[/C][/ROW]
[ROW][C]81[/C][C]0.982153105912904[/C][C]0.0356937881741927[/C][C]0.0178468940870964[/C][/ROW]
[ROW][C]82[/C][C]0.986311182816767[/C][C]0.0273776343664668[/C][C]0.0136888171832334[/C][/ROW]
[ROW][C]83[/C][C]0.98540947043047[/C][C]0.0291810591390595[/C][C]0.0145905295695297[/C][/ROW]
[ROW][C]84[/C][C]0.982376810532686[/C][C]0.0352463789346289[/C][C]0.0176231894673144[/C][/ROW]
[ROW][C]85[/C][C]0.987151245578794[/C][C]0.0256975088424122[/C][C]0.0128487544212061[/C][/ROW]
[ROW][C]86[/C][C]0.989409532281402[/C][C]0.0211809354371959[/C][C]0.010590467718598[/C][/ROW]
[ROW][C]87[/C][C]0.98762619795466[/C][C]0.0247476040906795[/C][C]0.0123738020453397[/C][/ROW]
[ROW][C]88[/C][C]0.984647613994726[/C][C]0.0307047720105489[/C][C]0.0153523860052745[/C][/ROW]
[ROW][C]89[/C][C]0.985610212197681[/C][C]0.0287795756046387[/C][C]0.0143897878023194[/C][/ROW]
[ROW][C]90[/C][C]0.98648157497065[/C][C]0.0270368500586992[/C][C]0.0135184250293496[/C][/ROW]
[ROW][C]91[/C][C]0.984086561775488[/C][C]0.0318268764490241[/C][C]0.0159134382245121[/C][/ROW]
[ROW][C]92[/C][C]0.981044384064277[/C][C]0.0379112318714468[/C][C]0.0189556159357234[/C][/ROW]
[ROW][C]93[/C][C]0.98407285783746[/C][C]0.031854284325081[/C][C]0.0159271421625405[/C][/ROW]
[ROW][C]94[/C][C]0.984104688387863[/C][C]0.0317906232242735[/C][C]0.0158953116121368[/C][/ROW]
[ROW][C]95[/C][C]0.982393729133093[/C][C]0.0352125417338148[/C][C]0.0176062708669074[/C][/ROW]
[ROW][C]96[/C][C]0.979859564833268[/C][C]0.0402808703334634[/C][C]0.0201404351667317[/C][/ROW]
[ROW][C]97[/C][C]0.989059662489474[/C][C]0.0218806750210524[/C][C]0.0109403375105262[/C][/ROW]
[ROW][C]98[/C][C]0.986824326642951[/C][C]0.0263513467140974[/C][C]0.0131756733570487[/C][/ROW]
[ROW][C]99[/C][C]0.990600548126499[/C][C]0.0187989037470017[/C][C]0.00939945187350086[/C][/ROW]
[ROW][C]100[/C][C]0.994522026030794[/C][C]0.0109559479384126[/C][C]0.00547797396920629[/C][/ROW]
[ROW][C]101[/C][C]0.99332789803387[/C][C]0.0133442039322595[/C][C]0.00667210196612973[/C][/ROW]
[ROW][C]102[/C][C]0.99445893890429[/C][C]0.0110821221914191[/C][C]0.00554106109570956[/C][/ROW]
[ROW][C]103[/C][C]0.994229415177198[/C][C]0.0115411696456049[/C][C]0.00577058482280247[/C][/ROW]
[ROW][C]104[/C][C]0.994045876479136[/C][C]0.0119082470417284[/C][C]0.00595412352086418[/C][/ROW]
[ROW][C]105[/C][C]0.992816373945088[/C][C]0.014367252109824[/C][C]0.007183626054912[/C][/ROW]
[ROW][C]106[/C][C]0.994682354444296[/C][C]0.0106352911114075[/C][C]0.00531764555570375[/C][/ROW]
[ROW][C]107[/C][C]0.99576572965589[/C][C]0.00846854068821937[/C][C]0.00423427034410968[/C][/ROW]
[ROW][C]108[/C][C]0.994796716784655[/C][C]0.0104065664306899[/C][C]0.00520328321534493[/C][/ROW]
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[ROW][C]254[/C][C]0.999951229263736[/C][C]9.75414725270179e-05[/C][C]4.8770736263509e-05[/C][/ROW]
[ROW][C]255[/C][C]0.999927526356643[/C][C]0.000144947286714172[/C][C]7.24736433570859e-05[/C][/ROW]
[ROW][C]256[/C][C]0.999881687877757[/C][C]0.000236624244485577[/C][C]0.000118312122242789[/C][/ROW]
[ROW][C]257[/C][C]0.999794671564484[/C][C]0.000410656871031194[/C][C]0.000205328435515597[/C][/ROW]
[ROW][C]258[/C][C]0.999661971726309[/C][C]0.000676056547382254[/C][C]0.000338028273691127[/C][/ROW]
[ROW][C]259[/C][C]0.999640181389486[/C][C]0.000719637221028117[/C][C]0.000359818610514059[/C][/ROW]
[ROW][C]260[/C][C]0.999529109852031[/C][C]0.000941780295938137[/C][C]0.000470890147969068[/C][/ROW]
[ROW][C]261[/C][C]0.999843147792385[/C][C]0.000313704415230006[/C][C]0.000156852207615003[/C][/ROW]
[ROW][C]262[/C][C]0.999754990676361[/C][C]0.000490018647278701[/C][C]0.00024500932363935[/C][/ROW]
[ROW][C]263[/C][C]0.999700608541383[/C][C]0.000598782917234683[/C][C]0.000299391458617342[/C][/ROW]
[ROW][C]264[/C][C]0.999416391869586[/C][C]0.00116721626082861[/C][C]0.000583608130414303[/C][/ROW]
[ROW][C]265[/C][C]0.998917704818238[/C][C]0.00216459036352309[/C][C]0.00108229518176155[/C][/ROW]
[ROW][C]266[/C][C]0.998432021068407[/C][C]0.00313595786318547[/C][C]0.00156797893159274[/C][/ROW]
[ROW][C]267[/C][C]0.997484276025708[/C][C]0.00503144794858302[/C][C]0.00251572397429151[/C][/ROW]
[ROW][C]268[/C][C]0.995455917140985[/C][C]0.00908816571802907[/C][C]0.00454408285901454[/C][/ROW]
[ROW][C]269[/C][C]0.992885510444902[/C][C]0.0142289791101958[/C][C]0.00711448955509792[/C][/ROW]
[ROW][C]270[/C][C]0.987666302289221[/C][C]0.0246673954215572[/C][C]0.0123336977107786[/C][/ROW]
[ROW][C]271[/C][C]0.982220696488092[/C][C]0.0355586070238153[/C][C]0.0177793035119076[/C][/ROW]
[ROW][C]272[/C][C]0.975583296562291[/C][C]0.048833406875417[/C][C]0.0244167034377085[/C][/ROW]
[ROW][C]273[/C][C]0.963485452653294[/C][C]0.0730290946934118[/C][C]0.0365145473467059[/C][/ROW]
[ROW][C]274[/C][C]0.940935403701801[/C][C]0.118129192596399[/C][C]0.0590645962981995[/C][/ROW]
[ROW][C]275[/C][C]0.90647740223755[/C][C]0.187045195524901[/C][C]0.0935225977624503[/C][/ROW]
[ROW][C]276[/C][C]0.868039691722218[/C][C]0.263920616555565[/C][C]0.131960308277782[/C][/ROW]
[ROW][C]277[/C][C]0.871372196845812[/C][C]0.257255606308376[/C][C]0.128627803154188[/C][/ROW]
[ROW][C]278[/C][C]0.915013021830915[/C][C]0.16997395633817[/C][C]0.0849869781690851[/C][/ROW]
[ROW][C]279[/C][C]0.887611159821998[/C][C]0.224777680356004[/C][C]0.112388840178002[/C][/ROW]
[ROW][C]280[/C][C]0.95439227441222[/C][C]0.0912154511755592[/C][C]0.0456077255877796[/C][/ROW]
[ROW][C]281[/C][C]0.91892073698233[/C][C]0.162158526035339[/C][C]0.0810792630176697[/C][/ROW]
[ROW][C]282[/C][C]0.836034705297675[/C][C]0.327930589404649[/C][C]0.163965294702325[/C][/ROW]
[ROW][C]283[/C][C]1[/C][C]1.19909340196844e-46[/C][C]5.9954670098422e-47[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154771&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154771&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
15	5.25595016926085e-40	1.05119003385217e-39	1
16	7.03172370631854e-55	1.40634474126371e-54	1
17	0.547557000086192	0.904885999827616	0.452442999913808
18	0.461663389715576	0.923326779431152	0.538336610284424
19	0.602898652720776	0.794202694558448	0.397101347279224
20	0.498878088536986	0.997756177073971	0.501121911463014
21	0.405727064076504	0.811454128153008	0.594272935923496
22	0.467187303288956	0.934374606577912	0.532812696711044
23	0.464745829704057	0.929491659408115	0.535254170295943
24	0.483195967417473	0.966391934834945	0.516804032582527
25	0.769025347086883	0.461949305826235	0.230974652913117
26	0.726805783329712	0.546388433340577	0.273194216670288
27	0.890371203031083	0.219257593937834	0.109628796968917
28	0.960258918309945	0.07948216338011	0.039741081690055
29	0.948218658166741	0.103562683666517	0.0517813418332585
30	0.93705210404215	0.1258957919157	0.0629478959578501
31	0.945125615669434	0.109748768661131	0.0548743843305657
32	0.930254460824958	0.139491078350083	0.0697455391750416
33	0.909895172403286	0.180209655193428	0.0901048275967141
34	0.969075677448379	0.061848645103243	0.0309243225516215
35	0.963251211290745	0.07349757741851	0.036748788709255
36	0.991361797850197	0.0172764042996054	0.0086382021498027
37	0.990112031383664	0.019775937232673	0.00988796861633649
38	0.986331783107547	0.0273364337849062	0.0136682168924531
39	0.984434838835687	0.0311303223286253	0.0155651611643126
40	0.980752715932267	0.0384945681354663	0.0192472840677331
41	0.984066915327378	0.0318661693452444	0.0159330846726222
42	0.979174883834253	0.0416502323314933	0.0208251161657466
43	0.973412202696383	0.0531755946072341	0.0265877973036171
44	0.97500478529893	0.0499904294021404	0.0249952147010702
45	0.977271259196731	0.0454574816065381	0.022728740803269
46	0.976946961714308	0.0461060765713839	0.0230530382856919
47	0.970336197678683	0.0593276046426345	0.0296638023213172
48	0.961644486260015	0.0767110274799693	0.0383555137399846
49	0.954458045698029	0.0910839086039417	0.0455419543019709
50	0.94272447687738	0.11455104624524	0.0572755231226202
51	0.938257517281429	0.123484965437142	0.0617424827185711
52	0.936978400588866	0.126043198822269	0.0630215994111344
53	0.935854704769173	0.128290590461654	0.064145295230827
54	0.920744332622613	0.158511334754773	0.0792556673773865
55	0.962996494094224	0.0740070118115513	0.0370035059057756
56	0.985926035201241	0.0281479295975189	0.0140739647987594
57	0.99334409470276	0.0133118105944802	0.00665590529724011
58	0.991116146983406	0.0177677060331889	0.00888385301659443
59	0.990405678007081	0.0191886439858384	0.00959432199291919
60	0.993362085791203	0.0132758284175937	0.00663791420879684
61	0.991826388430731	0.0163472231385382	0.0081736115692691
62	0.98919651235298	0.0216069752940404	0.0108034876470202
63	0.98705565000419	0.0258886999916208	0.0129443499958104
64	0.985943448347621	0.0281131033047573	0.0140565516523787
65	0.98395918469415	0.0320816306117001	0.0160408153058501
66	0.980278842775788	0.0394423144484236	0.0197211572242118
67	0.978407357093066	0.0431852858138675	0.0215926429069338
68	0.978418966947804	0.0431620661043929	0.0215810330521964
69	0.973727029175499	0.0525459416490019	0.026272970824501
70	0.967043360486754	0.065913279026492	0.032956639513246
71	0.971773807285287	0.0564523854294255	0.0282261927147128
72	0.973581328705542	0.0528373425889154	0.0264186712944577
73	0.984449854461802	0.0311002910763957	0.0155501455381979
74	0.983423313099956	0.0331533738000887	0.0165766869000444
75	0.97980863436467	0.0403827312706605	0.0201913656353302
76	0.974695046907716	0.050609906184567	0.0253049530922835
77	0.983529235156406	0.0329415296871882	0.0164707648435941
78	0.980897008760256	0.0382059824794873	0.0191029912397437
79	0.977949055265097	0.0441018894698065	0.0220509447349033
80	0.984065088110387	0.0318698237792269	0.0159349118896135
81	0.982153105912904	0.0356937881741927	0.0178468940870964
82	0.986311182816767	0.0273776343664668	0.0136888171832334
83	0.98540947043047	0.0291810591390595	0.0145905295695297
84	0.982376810532686	0.0352463789346289	0.0176231894673144
85	0.987151245578794	0.0256975088424122	0.0128487544212061
86	0.989409532281402	0.0211809354371959	0.010590467718598
87	0.98762619795466	0.0247476040906795	0.0123738020453397
88	0.984647613994726	0.0307047720105489	0.0153523860052745
89	0.985610212197681	0.0287795756046387	0.0143897878023194
90	0.98648157497065	0.0270368500586992	0.0135184250293496
91	0.984086561775488	0.0318268764490241	0.0159134382245121
92	0.981044384064277	0.0379112318714468	0.0189556159357234
93	0.98407285783746	0.031854284325081	0.0159271421625405
94	0.984104688387863	0.0317906232242735	0.0158953116121368
95	0.982393729133093	0.0352125417338148	0.0176062708669074
96	0.979859564833268	0.0402808703334634	0.0201404351667317
97	0.989059662489474	0.0218806750210524	0.0109403375105262
98	0.986824326642951	0.0263513467140974	0.0131756733570487
99	0.990600548126499	0.0187989037470017	0.00939945187350086
100	0.994522026030794	0.0109559479384126	0.00547797396920629
101	0.99332789803387	0.0133442039322595	0.00667210196612973
102	0.99445893890429	0.0110821221914191	0.00554106109570956
103	0.994229415177198	0.0115411696456049	0.00577058482280247
104	0.994045876479136	0.0119082470417284	0.00595412352086418
105	0.992816373945088	0.014367252109824	0.007183626054912
106	0.994682354444296	0.0106352911114075	0.00531764555570375
107	0.99576572965589	0.00846854068821937	0.00423427034410968
108	0.994796716784655	0.0104065664306899	0.00520328321534493
109	0.993662224504818	0.0126755509903646	0.00633777549518229
110	0.992983179952801	0.0140336400943971	0.00701682004719855
111	0.993653838981214	0.0126923220375723	0.00634616101878614
112	0.991944235586551	0.0161115288268972	0.00805576441344861
113	0.995302695206813	0.00939460958637371	0.00469730479318686
114	0.994142129165073	0.0117157416698537	0.00585787083492687
115	0.992730974136803	0.014538051726395	0.00726902586319748
116	0.994500670563835	0.0109986588723306	0.0054993294361653
117	0.992994572128848	0.0140108557423032	0.00700542787115162
118	0.995377581531457	0.0092448369370855	0.00462241846854275
119	0.997158608874324	0.00568278225135153	0.00284139112567577
120	0.997226203828336	0.00554759234332843	0.00277379617166421
121	0.996459870743252	0.00708025851349675	0.00354012925674838
122	0.996021271493094	0.00795745701381123	0.00397872850690561
123	0.994932407853885	0.0101351842922296	0.00506759214611481
124	0.993976181047391	0.0120476379052184	0.00602381895260921
125	0.992339516961456	0.0153209660770876	0.00766048303854379
126	0.991761007708675	0.0164779845826507	0.00823899229132535
127	0.989701823369049	0.0205963532619029	0.0102981766309514
128	0.988158871738052	0.0236822565238965	0.0118411282619482
129	0.985320272438825	0.0293594551223506	0.0146797275611753
130	0.981989517155818	0.0360209656883642	0.0180104828441821
131	0.981010726019399	0.037978547961203	0.0189892739806015
132	0.978209680297395	0.0435806394052105	0.0217903197026052
133	0.975769978490354	0.0484600430192916	0.0242300215096458
134	0.974451257421514	0.051097485156973	0.0255487425784865
135	0.974120391279537	0.0517592174409255	0.0258796087204628
136	0.972714792323433	0.0545704153531346	0.0272852076765673
137	0.97041440124345	0.0591711975131006	0.0295855987565503
138	0.965629320851694	0.0687413582966118	0.0343706791483059
139	0.96031545600152	0.0793690879969604	0.0396845439984802
140	0.972917836469011	0.0541643270619777	0.0270821635309888
141	0.967524276979813	0.0649514460403743	0.0324757230201872
142	0.962857872125492	0.0742842557490163	0.0371421278745081
143	0.9696502122042	0.0606995755916008	0.0303497877958004
144	0.976236155068325	0.04752768986335	0.023763844931675
145	0.971542759091015	0.0569144818179698	0.0284572409089849
146	0.966504550520258	0.0669908989594837	0.0334954494797418
147	0.960387289432451	0.0792254211350976	0.0396127105675488
148	0.955913590282174	0.0881728194356519	0.044086409717826
149	0.947785016330704	0.104429967338593	0.0522149836692963
150	0.941587525711247	0.116824948577505	0.0584124742887525
151	0.934444431394511	0.131111137210978	0.0655555686054892
152	0.95417429806696	0.0916514038660807	0.0458257019330403
153	0.948937407489947	0.102125185020105	0.0510625925100525
154	0.950615802805622	0.0987683943887554	0.0493841971943777
155	0.942651257627183	0.114697484745634	0.0573487423728171
156	0.932262799759035	0.135474400481931	0.0677372002409654
157	0.920497180985084	0.159005638029833	0.0795028190149163
158	0.920772584883008	0.158454830233984	0.0792274151169922
159	0.913154780464315	0.17369043907137	0.086845219535685
160	0.906112497838814	0.187775004322371	0.0938875021611856
161	0.907551209863146	0.184897580273709	0.0924487901368543
162	0.933337367160291	0.133325265679417	0.0666626328397087
163	0.931881288143157	0.136237423713686	0.0681187118568432
164	0.920342094263248	0.159315811473503	0.0796579057367516
165	0.912003593399302	0.175992813201396	0.087996406600698
166	0.907680466536457	0.184639066927087	0.0923195334635434
167	0.913000795559065	0.173998408881869	0.0869992044409346
168	0.909782923122163	0.180434153755673	0.0902170768778365
169	0.908953168687414	0.182093662625172	0.0910468313125859
170	0.909420145783891	0.181159708432218	0.0905798542161089
171	0.96761153532055	0.0647769293589004	0.0323884646794502
172	0.962225512581317	0.0755489748373655	0.0377744874186828
173	0.968396390386907	0.0632072192261861	0.031603609613093
174	0.962222808562575	0.0755543828748507	0.0377771914374253
175	0.974081093718703	0.0518378125625946	0.0259189062812973
176	0.971783253985829	0.056433492028342	0.028216746014171
177	0.981155885873416	0.0376882282531679	0.018844114126584
178	0.980593325651106	0.038813348697787	0.0194066743488935
179	0.979647424922308	0.0407051501553842	0.0203525750776921
180	0.97933215866689	0.0413356826662205	0.0206678413331103
181	0.975101234672268	0.0497975306554632	0.0248987653277316
182	0.970198703074881	0.0596025938502386	0.0298012969251193
183	0.972757766480249	0.0544844670395024	0.0272422335197512
184	0.967433669262153	0.0651326614756949	0.0325663307378475
185	0.962124367779501	0.0757512644409977	0.0378756322204988
186	0.954340105781112	0.0913197884377769	0.0456598942188884
187	0.947822859366634	0.104354281266732	0.0521771406333661
188	0.960757742488231	0.0784845150235384	0.0392422575117692
189	0.9537202533536	0.0925594932928008	0.0462797466464004
190	0.945258308826916	0.109483382346168	0.054741691173084
191	0.93625261724754	0.127494765504919	0.0637473827524596
192	0.941845899101629	0.116308201796742	0.0581541008983711
193	0.941808283103126	0.116383433793747	0.0581917168968736
194	0.951394553252005	0.0972108934959906	0.0486054467479953
195	0.941450137198754	0.117099725602492	0.0585498628012461
196	0.933374363464599	0.133251273070801	0.0666256365354006
197	0.953202584050418	0.0935948318991638	0.0467974159495819
198	0.944084782945746	0.111830434108509	0.0559152170542543
199	0.93609248476816	0.127815030463681	0.0639075152318405
200	0.924700996579397	0.150598006841205	0.0752990034206026
201	0.91067489802406	0.17865020395188	0.0893251019759402
202	0.899878086422117	0.200243827155766	0.100121913577883
203	0.885879251058306	0.228241497883387	0.114120748941694
204	0.872164362685432	0.255671274629137	0.127835637314569
205	0.851837541921252	0.296324916157496	0.148162458078748
206	0.832971939144063	0.334056121711874	0.167028060855937
207	0.815218765277562	0.369562469444876	0.184781234722438
208	0.804158076225641	0.391683847548718	0.195841923774359
209	0.776585321009084	0.446829357981833	0.223414678990916
210	0.81582510120461	0.36834979759078	0.18417489879539
211	0.78881828602486	0.422363427950279	0.21118171397514
212	0.75967772278397	0.48064455443206	0.24032227721603
213	0.737498047547517	0.525003904904966	0.262501952452483
214	0.725299663272659	0.549400673454681	0.274700336727341
215	0.691671691474253	0.616656617051494	0.308328308525747
216	0.698769670076144	0.602460659847712	0.301230329923856
217	0.781956116111405	0.436087767777189	0.218043883888595
218	0.795525258690447	0.408949482619107	0.204474741309553
219	0.836466380255337	0.327067239489327	0.163533619744663
220	0.898208005062524	0.203583989874953	0.101791994937476
221	0.967128323499285	0.0657433530014292	0.0328716765007146
222	0.975599629917605	0.0488007401647891	0.0244003700823946
223	0.970293914461634	0.0594121710767311	0.0297060855383656
224	0.973446016318462	0.0531079673630764	0.0265539836815382
225	0.96719348801722	0.0656130239655597	0.0328065119827798
226	0.968241376806485	0.0635172463870294	0.0317586231935147
227	0.971686972651483	0.0566260546970335	0.0283130273485167
228	0.967267997088131	0.0654640058237382	0.0327320029118691
229	0.974426959502452	0.0511460809950956	0.0255730404975478
230	0.978200346565964	0.0435993068680712	0.0217996534340356
231	0.972228991323852	0.0555420173522968	0.0277710086761484
232	0.975866643101656	0.048266713796687	0.0241333568983435
233	0.984392103980149	0.0312157920397026	0.0156078960198513
234	0.981644243202961	0.0367115135940777	0.0183557567970389
235	0.978656124349486	0.0426877513010279	0.021343875650514
236	0.97551979091019	0.0489604181796209	0.0244802090898105
237	0.972393436478353	0.0552131270432932	0.0276065635216466
238	0.965719110073626	0.0685617798527482	0.0342808899263741
239	0.955952267512448	0.0880954649751048	0.0440477324875524
240	0.96976532039093	0.0604693592181397	0.0302346796090699
241	0.966804794152837	0.0663904116943257	0.0331952058471628
242	0.966720608791079	0.0665587824178416	0.0332793912089208
243	0.986222603427102	0.0275547931457966	0.0137773965728983
244	0.998320029861858	0.00335994027628312	0.00167997013814156
245	0.997944518565109	0.0041109628697812	0.0020554814348906
246	0.99694903745985	0.00610192508029906	0.00305096254014953
247	0.996169915987876	0.00766016802424859	0.0038300840121243
248	0.995627804530487	0.0087443909390269	0.00437219546951345
249	0.994421274905474	0.0111574501890521	0.00557872509452604
250	0.992724697012811	0.0145506059743779	0.00727530298718895
251	0.999706235410662	0.000587529178676645	0.000293764589338322
252	0.99989702724863	0.000205945502740477	0.000102972751370238
253	0.999847846313636	0.00030430737272723	0.000152153686363615
254	0.999951229263736	9.75414725270179e-05	4.8770736263509e-05
255	0.999927526356643	0.000144947286714172	7.24736433570859e-05
256	0.999881687877757	0.000236624244485577	0.000118312122242789
257	0.999794671564484	0.000410656871031194	0.000205328435515597
258	0.999661971726309	0.000676056547382254	0.000338028273691127
259	0.999640181389486	0.000719637221028117	0.000359818610514059
260	0.999529109852031	0.000941780295938137	0.000470890147969068
261	0.999843147792385	0.000313704415230006	0.000156852207615003
262	0.999754990676361	0.000490018647278701	0.00024500932363935
263	0.999700608541383	0.000598782917234683	0.000299391458617342
264	0.999416391869586	0.00116721626082861	0.000583608130414303
265	0.998917704818238	0.00216459036352309	0.00108229518176155
266	0.998432021068407	0.00313595786318547	0.00156797893159274
267	0.997484276025708	0.00503144794858302	0.00251572397429151
268	0.995455917140985	0.00908816571802907	0.00454408285901454
269	0.992885510444902	0.0142289791101958	0.00711448955509792
270	0.987666302289221	0.0246673954215572	0.0123336977107786
271	0.982220696488092	0.0355586070238153	0.0177793035119076
272	0.975583296562291	0.048833406875417	0.0244167034377085
273	0.963485452653294	0.0730290946934118	0.0365145473467059
274	0.940935403701801	0.118129192596399	0.0590645962981995
275	0.90647740223755	0.187045195524901	0.0935225977624503
276	0.868039691722218	0.263920616555565	0.131960308277782
277	0.871372196845812	0.257255606308376	0.128627803154188
278	0.915013021830915	0.16997395633817	0.0849869781690851
279	0.887611159821998	0.224777680356004	0.112388840178002
280	0.95439227441222	0.0912154511755592	0.0456077255877796
281	0.91892073698233	0.162158526035339	0.0810792630176697
282	0.836034705297675	0.327930589404649	0.163965294702325
283	1	1.19909340196844e-46	5.9954670098422e-47

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	33	0.122676579925651	NOK
5% type I error level	129	0.479553903345725	NOK
10% type I error level	190	0.706319702602231	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 & 33 & 0.122676579925651 & NOK \tabularnewline
5% type I error level & 129 & 0.479553903345725 & NOK \tabularnewline
10% type I error level & 190 & 0.706319702602231 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154771&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]33[/C][C]0.122676579925651[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]129[/C][C]0.479553903345725[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]190[/C][C]0.706319702602231[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154771&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154771&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	33	0.122676579925651	NOK
5% type I error level	129	0.479553903345725	NOK
10% type I error level	190	0.706319702602231	NOK

Figure 1

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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 = 11 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 11 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

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

library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code