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R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Tue, 13 Dec 2011 09:01:28 -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/t1323784916v6hn8ls0ccrmnek.htm/, Retrieved Fri, 03 May 2024 02:17:41 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154396, Retrieved Fri, 03 May 2024 02:17:41 +0000

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Estimated Impact

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

-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [WS Multiple regre...] [2011-12-13 14:01:28] [c98b04636162cea751932dfe577607eb] [Current]

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Dataseries X:

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7.4	0.7	0	1.9	0.076	11	34	0.9978	3.51	0.56	9.4	5
7.8	0.88	0	2.6	0.098	25	67	0.9968	3.2	0.68	9.8	5
7.8	0.76	0.04	2.3	0.092	15	54	0.997	3.26	0.65	9.8	5
11.2	0.28	0.56	1.9	0.075	17	60	0.998	3.16	0.58	9.8	6
7.4	0.7	0	1.9	0.076	11	34	0.9978	3.51	0.56	9.4	5
7.4	0.66	0	1.8	0.075	13	40	0.9978	3.51	0.56	9.4	5
7.9	0.6	0.06	1.6	0.069	15	59	0.9964	3.3	0.46	9.4	5
7.3	0.65	0	1.2	0.065	15	21	0.9946	3.39	0.47	10	7
7.8	0.58	0.02	2	0.073	9	18	0.9968	3.36	0.57	9.5	7
7.5	0.5	0.36	6.1	0.071	17	102	0.9978	3.35	0.8	10.5	5
6.7	0.58	0.08	1.8	0.097	15	65	0.9959	3.28	0.54	9.2	5
7.5	0.5	0.36	6.1	0.071	17	102	0.9978	3.35	0.8	10.5	5
5.6	0.615	0	1.6	0.089	16	59	0.9943	3.58	0.52	9.9	5
7.8	0.61	0.29	1.6	0.114	9	29	0.9974	3.26	1.56	9.1	5
8.9	0.62	0.18	3.8	0.176	52	145	0.9986	3.16	0.88	9.2	5
8.9	0.62	0.19	3.9	0.17	51	148	0.9986	3.17	0.93	9.2	5
8.5	0.28	0.56	1.8	0.092	35	103	0.9969	3.3	0.75	10.5	7
8.1	0.56	0.28	1.7	0.368	16	56	0.9968	3.11	1.28	9.3	5
7.4	0.59	0.08	4.4	0.086	6	29	0.9974	3.38	0.5	9	4
7.9	0.32	0.51	1.8	0.341	17	56	0.9969	3.04	1.08	9.2	6
8.9	0.22	0.48	1.8	0.077	29	60	0.9968	3.39	0.53	9.4	6
7.6	0.39	0.31	2.3	0.082	23	71	0.9982	3.52	0.65	9.7	5
7.9	0.43	0.21	1.6	0.106	10	37	0.9966	3.17	0.91	9.5	5
8.5	0.49	0.11	2.3	0.084	9	67	0.9968	3.17	0.53	9.4	5
6.9	0.4	0.14	2.4	0.085	21	40	0.9968	3.43	0.63	9.7	6
6.3	0.39	0.16	1.4	0.08	11	23	0.9955	3.34	0.56	9.3	5
7.6	0.41	0.24	1.8	0.08	4	11	0.9962	3.28	0.59	9.5	5
7.9	0.43	0.21	1.6	0.106	10	37	0.9966	3.17	0.91	9.5	5
7.1	0.71	0	1.9	0.08	14	35	0.9972	3.47	0.55	9.4	5
7.8	0.645	0	2	0.082	8	16	0.9964	3.38	0.59	9.8	6
6.7	0.675	0.07	2.4	0.089	17	82	0.9958	3.35	0.54	10.1	5
6.9	0.685	0	2.5	0.105	22	37	0.9966	3.46	0.57	10.6	6
8.3	0.655	0.12	2.3	0.083	15	113	0.9966	3.17	0.66	9.8	5
6.9	0.605	0.12	10.7	0.073	40	83	0.9993	3.45	0.52	9.4	6
5.2	0.32	0.25	1.8	0.103	13	50	0.9957	3.38	0.55	9.2	5
7.8	0.645	0	5.5	0.086	5	18	0.9986	3.4	0.55	9.6	6
7.8	0.6	0.14	2.4	0.086	3	15	0.9975	3.42	0.6	10.8	6
8.1	0.38	0.28	2.1	0.066	13	30	0.9968	3.23	0.73	9.7	7
5.7	1.13	0.09	1.5	0.172	7	19	0.994	3.5	0.48	9.8	4
7.3	0.45	0.36	5.9	0.074	12	87	0.9978	3.33	0.83	10.5	5
7.3	0.45	0.36	5.9	0.074	12	87	0.9978	3.33	0.83	10.5	5
8.8	0.61	0.3	2.8	0.088	17	46	0.9976	3.26	0.51	9.3	4
7.5	0.49	0.2	2.6	0.332	8	14	0.9968	3.21	0.9	10.5	6
8.1	0.66	0.22	2.2	0.069	9	23	0.9968	3.3	1.2	10.3	5
6.8	0.67	0.02	1.8	0.05	5	11	0.9962	3.48	0.52	9.5	5
4.6	0.52	0.15	2.1	0.054	8	65	0.9934	3.9	0.56	13.1	4
7.7	0.935	0.43	2.2	0.114	22	114	0.997	3.25	0.73	9.2	5
8.7	0.29	0.52	1.6	0.113	12	37	0.9969	3.25	0.58	9.5	5
6.4	0.4	0.23	1.6	0.066	5	12	0.9958	3.34	0.56	9.2	5
5.6	0.31	0.37	1.4	0.074	12	96	0.9954	3.32	0.58	9.2	5
8.8	0.66	0.26	1.7	0.074	4	23	0.9971	3.15	0.74	9.2	5
6.6	0.52	0.04	2.2	0.069	8	15	0.9956	3.4	0.63	9.4	6
6.6	0.5	0.04	2.1	0.068	6	14	0.9955	3.39	0.64	9.4	6
8.6	0.38	0.36	3	0.081	30	119	0.997	3.2	0.56	9.4	5
7.6	0.51	0.15	2.8	0.11	33	73	0.9955	3.17	0.63	10.2	6
7.7	0.62	0.04	3.8	0.084	25	45	0.9978	3.34	0.53	9.5	5
10.2	0.42	0.57	3.4	0.07	4	10	0.9971	3.04	0.63	9.6	5
7.5	0.63	0.12	5.1	0.111	50	110	0.9983	3.26	0.77	9.4	5
7.8	0.59	0.18	2.3	0.076	17	54	0.9975	3.43	0.59	10	5
7.3	0.39	0.31	2.4	0.074	9	46	0.9962	3.41	0.54	9.4	6
8.8	0.4	0.4	2.2	0.079	19	52	0.998	3.44	0.64	9.2	5
7.7	0.69	0.49	1.8	0.115	20	112	0.9968	3.21	0.71	9.3	5
7.5	0.52	0.16	1.9	0.085	12	35	0.9968	3.38	0.62	9.5	7
7	0.735	0.05	2	0.081	13	54	0.9966	3.39	0.57	9.8	5
7.2	0.725	0.05	4.65	0.086	4	11	0.9962	3.41	0.39	10.9	5
7.2	0.725	0.05	4.65	0.086	4	11	0.9962	3.41	0.39	10.9	5
7.5	0.52	0.11	1.5	0.079	11	39	0.9968	3.42	0.58	9.6	5
6.6	0.705	0.07	1.6	0.076	6	15	0.9962	3.44	0.58	10.7	5
9.3	0.32	0.57	2	0.074	27	65	0.9969	3.28	0.79	10.7	5
8	0.705	0.05	1.9	0.074	8	19	0.9962	3.34	0.95	10.5	6
7.7	0.63	0.08	1.9	0.076	15	27	0.9967	3.32	0.54	9.5	6
7.7	0.67	0.23	2.1	0.088	17	96	0.9962	3.32	0.48	9.5	5
7.7	0.69	0.22	1.9	0.084	18	94	0.9961	3.31	0.48	9.5	5
8.3	0.675	0.26	2.1	0.084	11	43	0.9976	3.31	0.53	9.2	4
9.7	0.32	0.54	2.5	0.094	28	83	0.9984	3.28	0.82	9.6	5
8.8	0.41	0.64	2.2	0.093	9	42	0.9986	3.54	0.66	10.5	5
8.8	0.41	0.64	2.2	0.093	9	42	0.9986	3.54	0.66	10.5	5
6.8	0.785	0	2.4	0.104	14	30	0.9966	3.52	0.55	10.7	6
6.7	0.75	0.12	2	0.086	12	80	0.9958	3.38	0.52	10.1	5
8.3	0.625	0.2	1.5	0.08	27	119	0.9972	3.16	1.12	9.1	4
6.2	0.45	0.2	1.6	0.069	3	15	0.9958	3.41	0.56	9.2	5
7.8	0.43	0.7	1.9	0.464	22	67	0.9974	3.13	1.28	9.4	5
7.4	0.5	0.47	2	0.086	21	73	0.997	3.36	0.57	9.1	5
7.3	0.67	0.26	1.8	0.401	16	51	0.9969	3.16	1.14	9.4	5
6.3	0.3	0.48	1.8	0.069	18	61	0.9959	3.44	0.78	10.3	6
6.9	0.55	0.15	2.2	0.076	19	40	0.9961	3.41	0.59	10.1	5
8.6	0.49	0.28	1.9	0.11	20	136	0.9972	2.93	1.95	9.9	6
7.7	0.49	0.26	1.9	0.062	9	31	0.9966	3.39	0.64	9.6	5
9.3	0.39	0.44	2.1	0.107	34	125	0.9978	3.14	1.22	9.5	5
7	0.62	0.08	1.8	0.076	8	24	0.9978	3.48	0.53	9	5
7.9	0.52	0.26	1.9	0.079	42	140	0.9964	3.23	0.54	9.5	5
8.6	0.49	0.28	1.9	0.11	20	136	0.9972	2.93	1.95	9.9	6
8.6	0.49	0.29	2	0.11	19	133	0.9972	2.93	1.98	9.8	5
7.7	0.49	0.26	1.9	0.062	9	31	0.9966	3.39	0.64	9.6	5
5	1.02	0.04	1.4	0.045	41	85	0.9938	3.75	0.48	10.5	4
4.7	0.6	0.17	2.3	0.058	17	106	0.9932	3.85	0.6	12.9	6
6.8	0.775	0	3	0.102	8	23	0.9965	3.45	0.56	10.7	5
7	0.5	0.25	2	0.07	3	22	0.9963	3.25	0.63	9.2	5
7.6	0.9	0.06	2.5	0.079	5	10	0.9967	3.39	0.56	9.8	5
8.1	0.545	0.18	1.9	0.08	13	35	0.9972	3.3	0.59	9	6
8.3	0.61	0.3	2.1	0.084	11	50	0.9972	3.4	0.61	10.2	6
7.8	0.5	0.3	1.9	0.075	8	22	0.9959	3.31	0.56	10.4	6
8.1	0.545	0.18	1.9	0.08	13	35	0.9972	3.3	0.59	9	6
8.1	0.575	0.22	2.1	0.077	12	65	0.9967	3.29	0.51	9.2	5
7.2	0.49	0.24	2.2	0.07	5	36	0.996	3.33	0.48	9.4	5
8.1	0.575	0.22	2.1	0.077	12	65	0.9967	3.29	0.51	9.2	5
7.8	0.41	0.68	1.7	0.467	18	69	0.9973	3.08	1.31	9.3	5
6.2	0.63	0.31	1.7	0.088	15	64	0.9969	3.46	0.79	9.3	5
8	0.33	0.53	2.5	0.091	18	80	0.9976	3.37	0.8	9.6	6
8.1	0.785	0.52	2	0.122	37	153	0.9969	3.21	0.69	9.3	5
7.8	0.56	0.19	1.8	0.104	12	47	0.9964	3.19	0.93	9.5	5
8.4	0.62	0.09	2.2	0.084	11	108	0.9964	3.15	0.66	9.8	5
8.4	0.6	0.1	2.2	0.085	14	111	0.9964	3.15	0.66	9.8	5
10.1	0.31	0.44	2.3	0.08	22	46	0.9988	3.32	0.67	9.7	6
7.8	0.56	0.19	1.8	0.104	12	47	0.9964	3.19	0.93	9.5	5
9.4	0.4	0.31	2.2	0.09	13	62	0.9966	3.07	0.63	10.5	6
8.3	0.54	0.28	1.9	0.077	11	40	0.9978	3.39	0.61	10	6
7.8	0.56	0.12	2	0.082	7	28	0.997	3.37	0.5	9.4	6
8.8	0.55	0.04	2.2	0.119	14	56	0.9962	3.21	0.6	10.9	6
7	0.69	0.08	1.8	0.097	22	89	0.9959	3.34	0.54	9.2	6
7.3	1.07	0.09	1.7	0.178	10	89	0.9962	3.3	0.57	9	5
8.8	0.55	0.04	2.2	0.119	14	56	0.9962	3.21	0.6	10.9	6
7.3	0.695	0	2.5	0.075	3	13	0.998	3.49	0.52	9.2	5
8	0.71	0	2.6	0.08	11	34	0.9976	3.44	0.53	9.5	5
7.8	0.5	0.17	1.6	0.082	21	102	0.996	3.39	0.48	9.5	5
9	0.62	0.04	1.9	0.146	27	90	0.9984	3.16	0.7	9.4	5
8.2	1.33	0	1.7	0.081	3	12	0.9964	3.53	0.49	10.9	5
8.1	1.33	0	1.8	0.082	3	12	0.9964	3.54	0.48	10.9	5
8	0.59	0.16	1.8	0.065	3	16	0.9962	3.42	0.92	10.5	7
6.1	0.38	0.15	1.8	0.072	6	19	0.9955	3.42	0.57	9.4	5
8	0.745	0.56	2	0.118	30	134	0.9968	3.24	0.66	9.4	5
5.6	0.5	0.09	2.3	0.049	17	99	0.9937	3.63	0.63	13	5
5.6	0.5	0.09	2.3	0.049	17	99	0.9937	3.63	0.63	13	5
6.6	0.5	0.01	1.5	0.06	17	26	0.9952	3.4	0.58	9.8	6
7.9	1.04	0.05	2.2	0.084	13	29	0.9959	3.22	0.55	9.9	6
8.4	0.745	0.11	1.9	0.09	16	63	0.9965	3.19	0.82	9.6	5
8.3	0.715	0.15	1.8	0.089	10	52	0.9968	3.23	0.77	9.5	5
7.2	0.415	0.36	2	0.081	13	45	0.9972	3.48	0.64	9.2	5
7.8	0.56	0.19	2.1	0.081	15	105	0.9962	3.33	0.54	9.5	5
7.8	0.56	0.19	2	0.081	17	108	0.9962	3.32	0.54	9.5	5
8.4	0.745	0.11	1.9	0.09	16	63	0.9965	3.19	0.82	9.6	5
8.3	0.715	0.15	1.8	0.089	10	52	0.9968	3.23	0.77	9.5	5
5.2	0.34	0	1.8	0.05	27	63	0.9916	3.68	0.79	14	6
6.3	0.39	0.08	1.7	0.066	3	20	0.9954	3.34	0.58	9.4	5
5.2	0.34	0	1.8	0.05	27	63	0.9916	3.68	0.79	14	6
8.1	0.67	0.55	1.8	0.117	32	141	0.9968	3.17	0.62	9.4	5
5.8	0.68	0.02	1.8	0.087	21	94	0.9944	3.54	0.52	10	5
7.6	0.49	0.26	1.6	0.236	10	88	0.9968	3.11	0.8	9.3	5
6.9	0.49	0.1	2.3	0.074	12	30	0.9959	3.42	0.58	10.2	6
8.2	0.4	0.44	2.8	0.089	11	43	0.9975	3.53	0.61	10.5	6
7.3	0.33	0.47	2.1	0.077	5	11	0.9958	3.33	0.53	10.3	6
9.2	0.52	1	3.4	0.61	32	69	0.9996	2.74	2	9.4	4
7.5	0.6	0.03	1.8	0.095	25	99	0.995	3.35	0.54	10.1	5
7.5	0.6	0.03	1.8	0.095	25	99	0.995	3.35	0.54	10.1	5
7.1	0.43	0.42	5.5	0.07	29	129	0.9973	3.42	0.72	10.5	5
7.1	0.43	0.42	5.5	0.071	28	128	0.9973	3.42	0.71	10.5	5
7.1	0.43	0.42	5.5	0.07	29	129	0.9973	3.42	0.72	10.5	5
7.1	0.43	0.42	5.5	0.071	28	128	0.9973	3.42	0.71	10.5	5
7.1	0.68	0	2.2	0.073	12	22	0.9969	3.48	0.5	9.3	5
6.8	0.6	0.18	1.9	0.079	18	86	0.9968	3.59	0.57	9.3	6
7.6	0.95	0.03	2	0.09	7	20	0.9959	3.2	0.56	9.6	5
7.6	0.68	0.02	1.3	0.072	9	20	0.9965	3.17	1.08	9.2	4
7.8	0.53	0.04	1.7	0.076	17	31	0.9964	3.33	0.56	10	6
7.4	0.6	0.26	7.3	0.07	36	121	0.9982	3.37	0.49	9.4	5
7.3	0.59	0.26	7.2	0.07	35	121	0.9981	3.37	0.49	9.4	5
7.8	0.63	0.48	1.7	0.1	14	96	0.9961	3.19	0.62	9.5	5
6.8	0.64	0.1	2.1	0.085	18	101	0.9956	3.34	0.52	10.2	5
7.3	0.55	0.03	1.6	0.072	17	42	0.9956	3.37	0.48	9	4
6.8	0.63	0.07	2.1	0.089	11	44	0.9953	3.47	0.55	10.4	6
7.5	0.705	0.24	1.8	0.36	15	63	0.9964	3	1.59	9.5	5
7.9	0.885	0.03	1.8	0.058	4	8	0.9972	3.36	0.33	9.1	4
8	0.42	0.17	2	0.073	6	18	0.9972	3.29	0.61	9.2	6
8	0.42	0.17	2	0.073	6	18	0.9972	3.29	0.61	9.2	6
7.4	0.62	0.05	1.9	0.068	24	42	0.9961	3.42	0.57	11.5	6
7.3	0.38	0.21	2	0.08	7	35	0.9961	3.33	0.47	9.5	5
6.9	0.5	0.04	1.5	0.085	19	49	0.9958	3.35	0.78	9.5	5
7.3	0.38	0.21	2	0.08	7	35	0.9961	3.33	0.47	9.5	5
7.5	0.52	0.42	2.3	0.087	8	38	0.9972	3.58	0.61	10.5	6
7	0.805	0	2.5	0.068	7	20	0.9969	3.48	0.56	9.6	5
8.8	0.61	0.14	2.4	0.067	10	42	0.9969	3.19	0.59	9.5	5
8.8	0.61	0.14	2.4	0.067	10	42	0.9969	3.19	0.59	9.5	5
8.9	0.61	0.49	2	0.27	23	110	0.9972	3.12	1.02	9.3	5
7.2	0.73	0.02	2.5	0.076	16	42	0.9972	3.44	0.52	9.3	5
6.8	0.61	0.2	1.8	0.077	11	65	0.9971	3.54	0.58	9.3	5
6.7	0.62	0.21	1.9	0.079	8	62	0.997	3.52	0.58	9.3	6
8.9	0.31	0.57	2	0.111	26	85	0.9971	3.26	0.53	9.7	5
7.4	0.39	0.48	2	0.082	14	67	0.9972	3.34	0.55	9.2	5
7.7	0.705	0.1	2.6	0.084	9	26	0.9976	3.39	0.49	9.7	5
7.9	0.5	0.33	2	0.084	15	143	0.9968	3.2	0.55	9.5	5
7.9	0.49	0.32	1.9	0.082	17	144	0.9968	3.2	0.55	9.5	5
8.2	0.5	0.35	2.9	0.077	21	127	0.9976	3.23	0.62	9.4	5
6.4	0.37	0.25	1.9	0.074	21	49	0.9974	3.57	0.62	9.8	6
6.8	0.63	0.12	3.8	0.099	16	126	0.9969	3.28	0.61	9.5	5
7.6	0.55	0.21	2.2	0.071	7	28	0.9964	3.28	0.55	9.7	5
7.6	0.55	0.21	2.2	0.071	7	28	0.9964	3.28	0.55	9.7	5
7.8	0.59	0.33	2	0.074	24	120	0.9968	3.25	0.54	9.4	5
7.3	0.58	0.3	2.4	0.074	15	55	0.9968	3.46	0.59	10.2	5
11.5	0.3	0.6	2	0.067	12	27	0.9981	3.11	0.97	10.1	6
5.4	0.835	0.08	1.2	0.046	13	93	0.9924	3.57	0.85	13	7
6.9	1.09	0.06	2.1	0.061	12	31	0.9948	3.51	0.43	11.4	4

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	8 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154396&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154396&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154396&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	8 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Multiple Linear Regression - Estimated Regression Equation
chlorides[t] = -22.1204315363458 -0.0465280614058755fixedacidity[t] + 0.105401893258454volatileacidity[t] + 0.169620029655421citricacid[t] -0.0116640766840466residualsugar[t] + 0.00233433208445535freesulfurdioxide[t] -0.000757435419474768totalsulfurdioxide[t] + 23.4392153207321density[t] -0.318548434814975pH[t] + 0.0503830331892637sulphates[t] + 0.0199312796232007alcohol[t] -0.00298007201075349quality[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
chlorides[t] =  -22.1204315363458 -0.0465280614058755fixedacidity[t] +  0.105401893258454volatileacidity[t] +  0.169620029655421citricacid[t] -0.0116640766840466residualsugar[t] +  0.00233433208445535freesulfurdioxide[t] -0.000757435419474768totalsulfurdioxide[t] +  23.4392153207321density[t] -0.318548434814975pH[t] +  0.0503830331892637sulphates[t] +  0.0199312796232007alcohol[t] -0.00298007201075349quality[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154396&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]chlorides[t] =  -22.1204315363458 -0.0465280614058755fixedacidity[t] +  0.105401893258454volatileacidity[t] +  0.169620029655421citricacid[t] -0.0116640766840466residualsugar[t] +  0.00233433208445535freesulfurdioxide[t] -0.000757435419474768totalsulfurdioxide[t] +  23.4392153207321density[t] -0.318548434814975pH[t] +  0.0503830331892637sulphates[t] +  0.0199312796232007alcohol[t] -0.00298007201075349quality[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154396&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154396&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
chlorides[t] = -22.1204315363458 -0.0465280614058755fixedacidity[t] + 0.105401893258454volatileacidity[t] + 0.169620029655421citricacid[t] -0.0116640766840466residualsugar[t] + 0.00233433208445535freesulfurdioxide[t] -0.000757435419474768totalsulfurdioxide[t] + 23.4392153207321density[t] -0.318548434814975pH[t] + 0.0503830331892637sulphates[t] + 0.0199312796232007alcohol[t] -0.00298007201075349quality[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)	-22.1204315363458	7.250916	-3.0507	0.002613	0.001306
fixedacidity	-0.0465280614058755	0.007604	-6.1187	0	0
volatileacidity	0.105401893258454	0.024624	4.2804	3e-05	1.5e-05
citricacid	0.169620029655421	0.027936	6.0718	0	0
residualsugar	-0.0116640766840466	0.004362	-2.6741	0.008153	0.004076
freesulfurdioxide	0.00233433208445535	0.000565	4.1334	5.4e-05	2.7e-05
totalsulfurdioxide	-0.000757435419474768	0.000147	-5.1587	1e-06	0
density	23.4392153207321	7.360047	3.1847	0.001697	0.000848
pH	-0.318548434814975	0.049452	-6.4415	0	0
sulphates	0.0503830331892637	0.020444	2.4644	0.014621	0.00731
alcohol	0.0199312796232007	0.008105	2.4591	0.014834	0.007417
quality	-0.00298007201075349	0.006324	-0.4713	0.638006	0.319003

\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) & -22.1204315363458 & 7.250916 & -3.0507 & 0.002613 & 0.001306 \tabularnewline
fixedacidity & -0.0465280614058755 & 0.007604 & -6.1187 & 0 & 0 \tabularnewline
volatileacidity & 0.105401893258454 & 0.024624 & 4.2804 & 3e-05 & 1.5e-05 \tabularnewline
citricacid & 0.169620029655421 & 0.027936 & 6.0718 & 0 & 0 \tabularnewline
residualsugar & -0.0116640766840466 & 0.004362 & -2.6741 & 0.008153 & 0.004076 \tabularnewline
freesulfurdioxide & 0.00233433208445535 & 0.000565 & 4.1334 & 5.4e-05 & 2.7e-05 \tabularnewline
totalsulfurdioxide & -0.000757435419474768 & 0.000147 & -5.1587 & 1e-06 & 0 \tabularnewline
density & 23.4392153207321 & 7.360047 & 3.1847 & 0.001697 & 0.000848 \tabularnewline
pH & -0.318548434814975 & 0.049452 & -6.4415 & 0 & 0 \tabularnewline
sulphates & 0.0503830331892637 & 0.020444 & 2.4644 & 0.014621 & 0.00731 \tabularnewline
alcohol & 0.0199312796232007 & 0.008105 & 2.4591 & 0.014834 & 0.007417 \tabularnewline
quality & -0.00298007201075349 & 0.006324 & -0.4713 & 0.638006 & 0.319003 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154396&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]-22.1204315363458[/C][C]7.250916[/C][C]-3.0507[/C][C]0.002613[/C][C]0.001306[/C][/ROW]
[ROW][C]fixedacidity[/C][C]-0.0465280614058755[/C][C]0.007604[/C][C]-6.1187[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]volatileacidity[/C][C]0.105401893258454[/C][C]0.024624[/C][C]4.2804[/C][C]3e-05[/C][C]1.5e-05[/C][/ROW]
[ROW][C]citricacid[/C][C]0.169620029655421[/C][C]0.027936[/C][C]6.0718[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]residualsugar[/C][C]-0.0116640766840466[/C][C]0.004362[/C][C]-2.6741[/C][C]0.008153[/C][C]0.004076[/C][/ROW]
[ROW][C]freesulfurdioxide[/C][C]0.00233433208445535[/C][C]0.000565[/C][C]4.1334[/C][C]5.4e-05[/C][C]2.7e-05[/C][/ROW]
[ROW][C]totalsulfurdioxide[/C][C]-0.000757435419474768[/C][C]0.000147[/C][C]-5.1587[/C][C]1e-06[/C][C]0[/C][/ROW]
[ROW][C]density[/C][C]23.4392153207321[/C][C]7.360047[/C][C]3.1847[/C][C]0.001697[/C][C]0.000848[/C][/ROW]
[ROW][C]pH[/C][C]-0.318548434814975[/C][C]0.049452[/C][C]-6.4415[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]sulphates[/C][C]0.0503830331892637[/C][C]0.020444[/C][C]2.4644[/C][C]0.014621[/C][C]0.00731[/C][/ROW]
[ROW][C]alcohol[/C][C]0.0199312796232007[/C][C]0.008105[/C][C]2.4591[/C][C]0.014834[/C][C]0.007417[/C][/ROW]
[ROW][C]quality[/C][C]-0.00298007201075349[/C][C]0.006324[/C][C]-0.4713[/C][C]0.638006[/C][C]0.319003[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154396&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154396&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)	-22.1204315363458	7.250916	-3.0507	0.002613	0.001306
fixedacidity	-0.0465280614058755	0.007604	-6.1187	0	0
volatileacidity	0.105401893258454	0.024624	4.2804	3e-05	1.5e-05
citricacid	0.169620029655421	0.027936	6.0718	0	0
residualsugar	-0.0116640766840466	0.004362	-2.6741	0.008153	0.004076
freesulfurdioxide	0.00233433208445535	0.000565	4.1334	5.4e-05	2.7e-05
totalsulfurdioxide	-0.000757435419474768	0.000147	-5.1587	1e-06	0
density	23.4392153207321	7.360047	3.1847	0.001697	0.000848
pH	-0.318548434814975	0.049452	-6.4415	0	0
sulphates	0.0503830331892637	0.020444	2.4644	0.014621	0.00731
alcohol	0.0199312796232007	0.008105	2.4591	0.014834	0.007417
quality	-0.00298007201075349	0.006324	-0.4713	0.638006	0.319003

Multiple Linear Regression - Regression Statistics
Multiple R	0.750281730072112
R-squared	0.562922674480002
Adjusted R-squared	0.5373490011783
F-TEST (value)	22.011803616907
F-TEST (DF numerator)	11
F-TEST (DF denominator)	188
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.0493108573752403
Sum Squared Residuals	0.457133403155282

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.750281730072112 \tabularnewline
R-squared & 0.562922674480002 \tabularnewline
Adjusted R-squared & 0.5373490011783 \tabularnewline
F-TEST (value) & 22.011803616907 \tabularnewline
F-TEST (DF numerator) & 11 \tabularnewline
F-TEST (DF denominator) & 188 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.0493108573752403 \tabularnewline
Sum Squared Residuals & 0.457133403155282 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154396&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.750281730072112[/C][/ROW]
[ROW][C]R-squared[/C][C]0.562922674480002[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.5373490011783[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]22.011803616907[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]11[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]188[/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]0.0493108573752403[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]0.457133403155282[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154396&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154396&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	0.750281730072112
R-squared	0.562922674480002
Adjusted R-squared	0.5373490011783
F-TEST (value)	22.011803616907
F-TEST (DF numerator)	11
F-TEST (DF denominator)	188
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.0493108573752403
Sum Squared Residuals	0.457133403155282

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	0.076	0.0570174453149601	0.0189825546850399
2	0.098	0.14622826350395	-0.0482282635039496
3	0.092	0.114430846092554	-0.0224308460925539
4	0.075	0.047421800763246	0.027578199236754
5	0.076	0.0570174453150011	0.0189825546849989
6	0.075	0.0540918289051296	0.0209081710948704
7	0.069	0.056333059464901	0.012666940535099
8	0.065	0.0484334731793262	0.0165665268206738
9	0.073	0.0563141532032454	0.0166858467967546
10	0.071	0.0908428182294663	-0.0198428182294663
11	0.097	0.101269415792669	-0.00426941579266873
12	0.071	0.0908428182294663	-0.0198428182294663
13	0.089	0.0316584672836477	0.0573415327163523
14	0.114	0.195392666770892	-0.0813926667708918
15	0.176	0.14117498442252	0.0348250155774797
16	0.17	0.136431806019104	0.0335681939808963
17	0.092	0.132819250351056	-0.0408192503510562
18	0.368	0.192788856648071	0.175211143351929
19	0.086	0.045968352961755	0.040031647038245
20	0.341	0.226571051142209	0.114428948857791
21	0.077	0.0518361568096219	0.0251638431903781
22	0.082	0.0796447577903006	0.0023552422096994
23	0.106	0.139614293353029	-0.0336142933530289
24	0.084	0.0513864812818435	0.0326135187181565
25	0.085	0.0939451658417639	-0.0089451658417639
26	0.08	0.115076669370999	-0.0350766693709988
27	0.08	0.0993692032835817	-0.0193692032835817
28	0.106	0.139614293353029	-0.0336142933530289
29	0.08	0.0764500213715055	0.00354997862849453
30	0.082	0.0531738761633358	0.0288261238366642
31	0.089	0.0876760510748388	0.00132394892516123
32	0.105	0.104349005504069	0.000650994495930736
33	0.083	0.0687780325578491	0.0142219674421509
34	0.073	0.0678364555240392	0.00516354447596079
35	0.103	0.143146431605165	-0.0401464316051655
36	0.086	0.0430254684339599	0.0429745315660401
37	0.086	0.0900740488573457	-0.00407404885734567
38	0.066	0.11791709723679	-0.0519170972367898
39	0.172	0.124432007437291	0.0475679925627088
40	0.074	0.10478348174635	-0.0307834817463501
41	0.074	0.10478348174635	-0.0307834817463501
42	0.088	0.101114154336102	-0.0131141543361016
43	0.332	0.172334987961396	0.159665012038604
44	0.069	0.151351284457262	-0.0823512844572623
45	0.05	0.0617775709294996	-0.0117775709294996
46	0.054	0.0103097409468837	0.0436902590531163
47	0.114	0.170998761439461	-0.0569987614394613
48	0.113	0.1098079413928	0.00319205860720013
49	0.066	0.120382902643455	-0.054382902643455
50	0.074	0.12491749345056	-0.05091749345056
51	0.074	0.129440247544996	-0.0554402475449957
52	0.069	0.0699622029873691	-0.000962202987369103
53	0.068	0.0664547371891381	0.00154526281086189
54	0.081	0.0756568335940974	0.00534316640590257
55	0.11	0.135334169856356	-0.0253341698563564
56	0.084	0.0982336613724307	-0.0142336613724307
57	0.07	0.119075152506323	-0.0490751525063226
58	0.111	0.163426877563553	-0.0524268775635533
59	0.076	0.083457640234392	-0.00745764023439204
60	0.074	0.0523523124878031	0.0216476875121969
61	0.079	0.0566778195829853	0.0223221804170147
62	0.115	0.165903898341111	-0.0509038983411106
63	0.085	0.0791364469351231	0.00586355306487694
64	0.081	0.0947273817092706	-0.0137273817092706
65	0.086	0.0621274883469638	0.0238725116530361
66	0.086	0.0621274883469638	0.0238725116530361
67	0.079	0.0631530156272737	0.0158469843727263
68	0.076	0.124573111632653	-0.0485731116326529
69	0.074	0.127616841150854	-0.0536168411508543
70	0.074	0.0977113623832479	-0.0237113623832479
71	0.076	0.0966363340615464	-0.0206363340615464
72	0.088	0.0646057014875704	0.0233942985124296
73	0.084	0.0720411201324762	0.0119588798675238
74	0.084	0.103962785305863	-0.0199627853058632
75	0.094	0.101531378281982	-0.00753137828198184
76	0.093	0.0917986888679539	0.00120131113204607
77	0.093	0.0917986888679539	0.00120131113204607
78	0.104	0.0892083611092238	0.0147916388907762
79	0.086	0.0880069219340508	-0.00200692193405082
80	0.08	0.141437597058544	-0.0614375970585437
81	0.069	0.100630647833507	-0.0316306478335069
82	0.464	0.27731251741567	0.18668748258433
83	0.086	0.131850751828583	-0.0458507518285831
84	0.401	0.222189885974209	0.178810114025791
85	0.069	0.14831737400588	-0.0793173740058797
86	0.076	0.108016581799234	-0.0320165817992343
87	0.11	0.218006105255033	-0.108006105255033
88	0.062	0.080745131481586	-0.018745131481586
89	0.107	0.146111404964336	-0.0391114049643362
90	0.076	0.0825763365983858	-0.00657633659838584
91	0.079	0.108322549287442	-0.0293225492874424
92	0.11	0.218006105255033	-0.108006105255033
93	0.11	0.220972307101263	-0.110972307101263
94	0.062	0.080745131481586	-0.018745131481586
95	0.045	0.0970963455031059	-0.0520963455031059
96	0.058	0.00841130814293038	0.0495886918570696
97	0.102	0.0958903228434239	0.00610967715657608
98	0.07	0.133405785798567	-0.0634057857985675
99	0.079	0.0965586121893486	-0.0175586121893486
100	0.08	0.0859438922175879	-0.00594389221758793
101	0.084	0.0785511484891498	0.00544885151085018
102	0.075	0.106424465243968	-0.0314244652439681
103	0.08	0.0859438922175879	-0.00594389221758793
104	0.077	0.0629021021640881	0.0140978978359119
105	0.07	0.076994868812542	-0.00699486881254197
106	0.077	0.0629021021640881	0.0140978978359119
107	0.467	0.276394558359464	0.190605441640536
108	0.088	0.151429374380828	-0.063429374380828
109	0.091	0.107507422657401	-0.0165074226574011
110	0.122	0.17002669329673	-0.04802669329673
111	0.104	0.139287288564798	-0.0352872885647982
112	0.084	0.0526469413236611	0.0313530586763389
113	0.085	0.056965793749988	0.028034206250012
114	0.08	0.0693454148810211	0.0106545851189789
115	0.104	0.139287288564798	-0.0352872885647982
116	0.09	0.0993896139690238	-0.00938961396902385
117	0.077	0.0909505425154565	-0.0139505425154565
118	0.082	0.0578875903811411	0.0241124096188589
119	0.119	0.0566868252468692	0.0623131747531308
120	0.097	0.0749741020534771	0.0220258979465229
121	0.178	0.0961980350920309	0.0818019649079691
122	0.119	0.0566868252468692	0.0623131747531308
123	0.075	0.0564335176204303	0.0185664823795697
124	0.08	0.0400819580647721	0.0399180419352279
125	0.082	0.0154958923755222	0.0665041076244778
126	0.146	0.108467232676015	0.037532767323985
127	0.081	0.0737041637989649	0.00729583620103509
128	0.082	0.0735012475911053	0.00849875240889467
129	0.065	0.0660399636335447	-0.0010399636335447
130	0.072	0.0853375965140536	-0.0133375965140536
131	0.118	0.163880435662149	-0.0458804356621492
132	0.049	0.0360132634041001	0.0129867365958999
133	0.049	0.0360132634041001	0.0129867365958999
134	0.06	0.0796852911187684	-0.0196852911187684
135	0.084	0.137353952519685	-0.0533539525196849
136	0.09	0.11214706940305	-0.0221470694030503
137	0.089	0.105692372289833	-0.0166923722898326
138	0.081	0.0880545061622615	-0.00705450616226146
139	0.081	0.0299258006013584	0.0510741993986416
140	0.081	0.0366740505283993	0.0443259494716007
141	0.09	0.11214706940305	-0.0221470694030503
142	0.089	0.105692372289833	-0.0166923722898326
143	0.05	0.0388001356722215	0.0111998643277785
144	0.066	0.0822623606701625	-0.0162623606701625
145	0.05	0.0388001356722215	0.0111998643277785
146	0.117	0.171608787909498	-0.0546087879094978
147	0.087	0.0325039709482231	0.0544960290517769
148	0.236	0.144020980037442	0.091979019962558
149	0.074	0.07391498686349	8.50131365100393e-05
150	0.089	0.0535534074119467	0.0354465925880533
151	0.077	0.127382047972067	-0.0503820479720668
152	0.61	0.491933764907342	0.118066235092658
153	0.095	0.0298089870679509	0.0651910129320491
154	0.095	0.0298089870679509	0.0651910129320491
155	0.07	0.0887641459885667	-0.0187641459885667
156	0.071	0.0866834189916935	-0.0156834189916935
157	0.07	0.0887641459885667	-0.0187641459885667
158	0.071	0.0866834189916935	-0.0156834189916935
159	0.073	0.0602372092866474	0.0127627907133526
160	0.079	0.0284869212020451	0.0505130787979549
161	0.09	0.137453028712414	-0.0474530287124137
162	0.072	0.1649585547406	-0.0929585547406001
163	0.076	0.0793863267677319	-0.00338632676773193
164	0.07	0.0704995249019322	-0.000499524901932191
165	0.07	0.0705864661618116	-0.000586466161811566
166	0.1	0.141925461091123	-0.041925461091123
167	0.085	0.0753481702620554	0.00965182973794465
168	0.072	0.0464017251874493	0.0255982748125506
169	0.089	0.0501136585460789	0.0388863414539211
170	0.36	0.265671017053337	0.0943289829466633
171	0.058	0.0819920962581696	-0.0239920962581696
172	0.073	0.0792743322123685	-0.00627433221236848
173	0.073	0.0792743322123685	-0.00627433221236848
174	0.068	0.10955526769718	-0.04155526769718
175	0.08	0.067251387611557	0.012748612388443
176	0.085	0.0951313688024944	-0.0101313688024944
177	0.08	0.067251387611557	0.012748612388443
178	0.087	0.0750359098430264	0.0119640901569735
179	0.068	0.0734116053743165	-0.00541160537431653
180	0.067	0.0762577636331272	-0.00925776363312716
181	0.067	0.0762577636331272	-0.00925776363312716
182	0.27	0.161486910499201	0.108513089500799
183	0.076	0.0757176579978062	0.000282342002193847
184	0.077	0.0601086562935391	0.0168913437064609
185	0.079	0.062661559153392	0.016338440846608
186	0.111	0.105718949814705	0.00528105018529458
187	0.082	0.122201310851349	-0.0402013108513487
188	0.084	0.0897645455104902	-0.00576454551049024
189	0.084	0.0710582027956655	0.0129417972043345
190	0.082	0.0733856199843674	0.00861438001563265
191	0.077	0.0868480787427633	-0.00984807874276328
192	0.074	0.102676508524563	-0.0286765085245635
193	0.099	0.0744195351605629	0.0245804648394371
194	0.071	0.105156608559995	-0.0341566085599946
195	0.071	0.105156608559995	-0.0341566085599946
196	0.074	0.10520280270257	-0.0312028027025705
197	0.074	0.0974519004622833	-0.0234519004622833
198	0.067	0.0984136322484499	-0.0314136322484499
199	0.046	0.0807361276138575	-0.0347361276138575
200	0.061	0.0998144301544859	-0.0388144301544859

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 0.076 & 0.0570174453149601 & 0.0189825546850399 \tabularnewline
2 & 0.098 & 0.14622826350395 & -0.0482282635039496 \tabularnewline
3 & 0.092 & 0.114430846092554 & -0.0224308460925539 \tabularnewline
4 & 0.075 & 0.047421800763246 & 0.027578199236754 \tabularnewline
5 & 0.076 & 0.0570174453150011 & 0.0189825546849989 \tabularnewline
6 & 0.075 & 0.0540918289051296 & 0.0209081710948704 \tabularnewline
7 & 0.069 & 0.056333059464901 & 0.012666940535099 \tabularnewline
8 & 0.065 & 0.0484334731793262 & 0.0165665268206738 \tabularnewline
9 & 0.073 & 0.0563141532032454 & 0.0166858467967546 \tabularnewline
10 & 0.071 & 0.0908428182294663 & -0.0198428182294663 \tabularnewline
11 & 0.097 & 0.101269415792669 & -0.00426941579266873 \tabularnewline
12 & 0.071 & 0.0908428182294663 & -0.0198428182294663 \tabularnewline
13 & 0.089 & 0.0316584672836477 & 0.0573415327163523 \tabularnewline
14 & 0.114 & 0.195392666770892 & -0.0813926667708918 \tabularnewline
15 & 0.176 & 0.14117498442252 & 0.0348250155774797 \tabularnewline
16 & 0.17 & 0.136431806019104 & 0.0335681939808963 \tabularnewline
17 & 0.092 & 0.132819250351056 & -0.0408192503510562 \tabularnewline
18 & 0.368 & 0.192788856648071 & 0.175211143351929 \tabularnewline
19 & 0.086 & 0.045968352961755 & 0.040031647038245 \tabularnewline
20 & 0.341 & 0.226571051142209 & 0.114428948857791 \tabularnewline
21 & 0.077 & 0.0518361568096219 & 0.0251638431903781 \tabularnewline
22 & 0.082 & 0.0796447577903006 & 0.0023552422096994 \tabularnewline
23 & 0.106 & 0.139614293353029 & -0.0336142933530289 \tabularnewline
24 & 0.084 & 0.0513864812818435 & 0.0326135187181565 \tabularnewline
25 & 0.085 & 0.0939451658417639 & -0.0089451658417639 \tabularnewline
26 & 0.08 & 0.115076669370999 & -0.0350766693709988 \tabularnewline
27 & 0.08 & 0.0993692032835817 & -0.0193692032835817 \tabularnewline
28 & 0.106 & 0.139614293353029 & -0.0336142933530289 \tabularnewline
29 & 0.08 & 0.0764500213715055 & 0.00354997862849453 \tabularnewline
30 & 0.082 & 0.0531738761633358 & 0.0288261238366642 \tabularnewline
31 & 0.089 & 0.0876760510748388 & 0.00132394892516123 \tabularnewline
32 & 0.105 & 0.104349005504069 & 0.000650994495930736 \tabularnewline
33 & 0.083 & 0.0687780325578491 & 0.0142219674421509 \tabularnewline
34 & 0.073 & 0.0678364555240392 & 0.00516354447596079 \tabularnewline
35 & 0.103 & 0.143146431605165 & -0.0401464316051655 \tabularnewline
36 & 0.086 & 0.0430254684339599 & 0.0429745315660401 \tabularnewline
37 & 0.086 & 0.0900740488573457 & -0.00407404885734567 \tabularnewline
38 & 0.066 & 0.11791709723679 & -0.0519170972367898 \tabularnewline
39 & 0.172 & 0.124432007437291 & 0.0475679925627088 \tabularnewline
40 & 0.074 & 0.10478348174635 & -0.0307834817463501 \tabularnewline
41 & 0.074 & 0.10478348174635 & -0.0307834817463501 \tabularnewline
42 & 0.088 & 0.101114154336102 & -0.0131141543361016 \tabularnewline
43 & 0.332 & 0.172334987961396 & 0.159665012038604 \tabularnewline
44 & 0.069 & 0.151351284457262 & -0.0823512844572623 \tabularnewline
45 & 0.05 & 0.0617775709294996 & -0.0117775709294996 \tabularnewline
46 & 0.054 & 0.0103097409468837 & 0.0436902590531163 \tabularnewline
47 & 0.114 & 0.170998761439461 & -0.0569987614394613 \tabularnewline
48 & 0.113 & 0.1098079413928 & 0.00319205860720013 \tabularnewline
49 & 0.066 & 0.120382902643455 & -0.054382902643455 \tabularnewline
50 & 0.074 & 0.12491749345056 & -0.05091749345056 \tabularnewline
51 & 0.074 & 0.129440247544996 & -0.0554402475449957 \tabularnewline
52 & 0.069 & 0.0699622029873691 & -0.000962202987369103 \tabularnewline
53 & 0.068 & 0.0664547371891381 & 0.00154526281086189 \tabularnewline
54 & 0.081 & 0.0756568335940974 & 0.00534316640590257 \tabularnewline
55 & 0.11 & 0.135334169856356 & -0.0253341698563564 \tabularnewline
56 & 0.084 & 0.0982336613724307 & -0.0142336613724307 \tabularnewline
57 & 0.07 & 0.119075152506323 & -0.0490751525063226 \tabularnewline
58 & 0.111 & 0.163426877563553 & -0.0524268775635533 \tabularnewline
59 & 0.076 & 0.083457640234392 & -0.00745764023439204 \tabularnewline
60 & 0.074 & 0.0523523124878031 & 0.0216476875121969 \tabularnewline
61 & 0.079 & 0.0566778195829853 & 0.0223221804170147 \tabularnewline
62 & 0.115 & 0.165903898341111 & -0.0509038983411106 \tabularnewline
63 & 0.085 & 0.0791364469351231 & 0.00586355306487694 \tabularnewline
64 & 0.081 & 0.0947273817092706 & -0.0137273817092706 \tabularnewline
65 & 0.086 & 0.0621274883469638 & 0.0238725116530361 \tabularnewline
66 & 0.086 & 0.0621274883469638 & 0.0238725116530361 \tabularnewline
67 & 0.079 & 0.0631530156272737 & 0.0158469843727263 \tabularnewline
68 & 0.076 & 0.124573111632653 & -0.0485731116326529 \tabularnewline
69 & 0.074 & 0.127616841150854 & -0.0536168411508543 \tabularnewline
70 & 0.074 & 0.0977113623832479 & -0.0237113623832479 \tabularnewline
71 & 0.076 & 0.0966363340615464 & -0.0206363340615464 \tabularnewline
72 & 0.088 & 0.0646057014875704 & 0.0233942985124296 \tabularnewline
73 & 0.084 & 0.0720411201324762 & 0.0119588798675238 \tabularnewline
74 & 0.084 & 0.103962785305863 & -0.0199627853058632 \tabularnewline
75 & 0.094 & 0.101531378281982 & -0.00753137828198184 \tabularnewline
76 & 0.093 & 0.0917986888679539 & 0.00120131113204607 \tabularnewline
77 & 0.093 & 0.0917986888679539 & 0.00120131113204607 \tabularnewline
78 & 0.104 & 0.0892083611092238 & 0.0147916388907762 \tabularnewline
79 & 0.086 & 0.0880069219340508 & -0.00200692193405082 \tabularnewline
80 & 0.08 & 0.141437597058544 & -0.0614375970585437 \tabularnewline
81 & 0.069 & 0.100630647833507 & -0.0316306478335069 \tabularnewline
82 & 0.464 & 0.27731251741567 & 0.18668748258433 \tabularnewline
83 & 0.086 & 0.131850751828583 & -0.0458507518285831 \tabularnewline
84 & 0.401 & 0.222189885974209 & 0.178810114025791 \tabularnewline
85 & 0.069 & 0.14831737400588 & -0.0793173740058797 \tabularnewline
86 & 0.076 & 0.108016581799234 & -0.0320165817992343 \tabularnewline
87 & 0.11 & 0.218006105255033 & -0.108006105255033 \tabularnewline
88 & 0.062 & 0.080745131481586 & -0.018745131481586 \tabularnewline
89 & 0.107 & 0.146111404964336 & -0.0391114049643362 \tabularnewline
90 & 0.076 & 0.0825763365983858 & -0.00657633659838584 \tabularnewline
91 & 0.079 & 0.108322549287442 & -0.0293225492874424 \tabularnewline
92 & 0.11 & 0.218006105255033 & -0.108006105255033 \tabularnewline
93 & 0.11 & 0.220972307101263 & -0.110972307101263 \tabularnewline
94 & 0.062 & 0.080745131481586 & -0.018745131481586 \tabularnewline
95 & 0.045 & 0.0970963455031059 & -0.0520963455031059 \tabularnewline
96 & 0.058 & 0.00841130814293038 & 0.0495886918570696 \tabularnewline
97 & 0.102 & 0.0958903228434239 & 0.00610967715657608 \tabularnewline
98 & 0.07 & 0.133405785798567 & -0.0634057857985675 \tabularnewline
99 & 0.079 & 0.0965586121893486 & -0.0175586121893486 \tabularnewline
100 & 0.08 & 0.0859438922175879 & -0.00594389221758793 \tabularnewline
101 & 0.084 & 0.0785511484891498 & 0.00544885151085018 \tabularnewline
102 & 0.075 & 0.106424465243968 & -0.0314244652439681 \tabularnewline
103 & 0.08 & 0.0859438922175879 & -0.00594389221758793 \tabularnewline
104 & 0.077 & 0.0629021021640881 & 0.0140978978359119 \tabularnewline
105 & 0.07 & 0.076994868812542 & -0.00699486881254197 \tabularnewline
106 & 0.077 & 0.0629021021640881 & 0.0140978978359119 \tabularnewline
107 & 0.467 & 0.276394558359464 & 0.190605441640536 \tabularnewline
108 & 0.088 & 0.151429374380828 & -0.063429374380828 \tabularnewline
109 & 0.091 & 0.107507422657401 & -0.0165074226574011 \tabularnewline
110 & 0.122 & 0.17002669329673 & -0.04802669329673 \tabularnewline
111 & 0.104 & 0.139287288564798 & -0.0352872885647982 \tabularnewline
112 & 0.084 & 0.0526469413236611 & 0.0313530586763389 \tabularnewline
113 & 0.085 & 0.056965793749988 & 0.028034206250012 \tabularnewline
114 & 0.08 & 0.0693454148810211 & 0.0106545851189789 \tabularnewline
115 & 0.104 & 0.139287288564798 & -0.0352872885647982 \tabularnewline
116 & 0.09 & 0.0993896139690238 & -0.00938961396902385 \tabularnewline
117 & 0.077 & 0.0909505425154565 & -0.0139505425154565 \tabularnewline
118 & 0.082 & 0.0578875903811411 & 0.0241124096188589 \tabularnewline
119 & 0.119 & 0.0566868252468692 & 0.0623131747531308 \tabularnewline
120 & 0.097 & 0.0749741020534771 & 0.0220258979465229 \tabularnewline
121 & 0.178 & 0.0961980350920309 & 0.0818019649079691 \tabularnewline
122 & 0.119 & 0.0566868252468692 & 0.0623131747531308 \tabularnewline
123 & 0.075 & 0.0564335176204303 & 0.0185664823795697 \tabularnewline
124 & 0.08 & 0.0400819580647721 & 0.0399180419352279 \tabularnewline
125 & 0.082 & 0.0154958923755222 & 0.0665041076244778 \tabularnewline
126 & 0.146 & 0.108467232676015 & 0.037532767323985 \tabularnewline
127 & 0.081 & 0.0737041637989649 & 0.00729583620103509 \tabularnewline
128 & 0.082 & 0.0735012475911053 & 0.00849875240889467 \tabularnewline
129 & 0.065 & 0.0660399636335447 & -0.0010399636335447 \tabularnewline
130 & 0.072 & 0.0853375965140536 & -0.0133375965140536 \tabularnewline
131 & 0.118 & 0.163880435662149 & -0.0458804356621492 \tabularnewline
132 & 0.049 & 0.0360132634041001 & 0.0129867365958999 \tabularnewline
133 & 0.049 & 0.0360132634041001 & 0.0129867365958999 \tabularnewline
134 & 0.06 & 0.0796852911187684 & -0.0196852911187684 \tabularnewline
135 & 0.084 & 0.137353952519685 & -0.0533539525196849 \tabularnewline
136 & 0.09 & 0.11214706940305 & -0.0221470694030503 \tabularnewline
137 & 0.089 & 0.105692372289833 & -0.0166923722898326 \tabularnewline
138 & 0.081 & 0.0880545061622615 & -0.00705450616226146 \tabularnewline
139 & 0.081 & 0.0299258006013584 & 0.0510741993986416 \tabularnewline
140 & 0.081 & 0.0366740505283993 & 0.0443259494716007 \tabularnewline
141 & 0.09 & 0.11214706940305 & -0.0221470694030503 \tabularnewline
142 & 0.089 & 0.105692372289833 & -0.0166923722898326 \tabularnewline
143 & 0.05 & 0.0388001356722215 & 0.0111998643277785 \tabularnewline
144 & 0.066 & 0.0822623606701625 & -0.0162623606701625 \tabularnewline
145 & 0.05 & 0.0388001356722215 & 0.0111998643277785 \tabularnewline
146 & 0.117 & 0.171608787909498 & -0.0546087879094978 \tabularnewline
147 & 0.087 & 0.0325039709482231 & 0.0544960290517769 \tabularnewline
148 & 0.236 & 0.144020980037442 & 0.091979019962558 \tabularnewline
149 & 0.074 & 0.07391498686349 & 8.50131365100393e-05 \tabularnewline
150 & 0.089 & 0.0535534074119467 & 0.0354465925880533 \tabularnewline
151 & 0.077 & 0.127382047972067 & -0.0503820479720668 \tabularnewline
152 & 0.61 & 0.491933764907342 & 0.118066235092658 \tabularnewline
153 & 0.095 & 0.0298089870679509 & 0.0651910129320491 \tabularnewline
154 & 0.095 & 0.0298089870679509 & 0.0651910129320491 \tabularnewline
155 & 0.07 & 0.0887641459885667 & -0.0187641459885667 \tabularnewline
156 & 0.071 & 0.0866834189916935 & -0.0156834189916935 \tabularnewline
157 & 0.07 & 0.0887641459885667 & -0.0187641459885667 \tabularnewline
158 & 0.071 & 0.0866834189916935 & -0.0156834189916935 \tabularnewline
159 & 0.073 & 0.0602372092866474 & 0.0127627907133526 \tabularnewline
160 & 0.079 & 0.0284869212020451 & 0.0505130787979549 \tabularnewline
161 & 0.09 & 0.137453028712414 & -0.0474530287124137 \tabularnewline
162 & 0.072 & 0.1649585547406 & -0.0929585547406001 \tabularnewline
163 & 0.076 & 0.0793863267677319 & -0.00338632676773193 \tabularnewline
164 & 0.07 & 0.0704995249019322 & -0.000499524901932191 \tabularnewline
165 & 0.07 & 0.0705864661618116 & -0.000586466161811566 \tabularnewline
166 & 0.1 & 0.141925461091123 & -0.041925461091123 \tabularnewline
167 & 0.085 & 0.0753481702620554 & 0.00965182973794465 \tabularnewline
168 & 0.072 & 0.0464017251874493 & 0.0255982748125506 \tabularnewline
169 & 0.089 & 0.0501136585460789 & 0.0388863414539211 \tabularnewline
170 & 0.36 & 0.265671017053337 & 0.0943289829466633 \tabularnewline
171 & 0.058 & 0.0819920962581696 & -0.0239920962581696 \tabularnewline
172 & 0.073 & 0.0792743322123685 & -0.00627433221236848 \tabularnewline
173 & 0.073 & 0.0792743322123685 & -0.00627433221236848 \tabularnewline
174 & 0.068 & 0.10955526769718 & -0.04155526769718 \tabularnewline
175 & 0.08 & 0.067251387611557 & 0.012748612388443 \tabularnewline
176 & 0.085 & 0.0951313688024944 & -0.0101313688024944 \tabularnewline
177 & 0.08 & 0.067251387611557 & 0.012748612388443 \tabularnewline
178 & 0.087 & 0.0750359098430264 & 0.0119640901569735 \tabularnewline
179 & 0.068 & 0.0734116053743165 & -0.00541160537431653 \tabularnewline
180 & 0.067 & 0.0762577636331272 & -0.00925776363312716 \tabularnewline
181 & 0.067 & 0.0762577636331272 & -0.00925776363312716 \tabularnewline
182 & 0.27 & 0.161486910499201 & 0.108513089500799 \tabularnewline
183 & 0.076 & 0.0757176579978062 & 0.000282342002193847 \tabularnewline
184 & 0.077 & 0.0601086562935391 & 0.0168913437064609 \tabularnewline
185 & 0.079 & 0.062661559153392 & 0.016338440846608 \tabularnewline
186 & 0.111 & 0.105718949814705 & 0.00528105018529458 \tabularnewline
187 & 0.082 & 0.122201310851349 & -0.0402013108513487 \tabularnewline
188 & 0.084 & 0.0897645455104902 & -0.00576454551049024 \tabularnewline
189 & 0.084 & 0.0710582027956655 & 0.0129417972043345 \tabularnewline
190 & 0.082 & 0.0733856199843674 & 0.00861438001563265 \tabularnewline
191 & 0.077 & 0.0868480787427633 & -0.00984807874276328 \tabularnewline
192 & 0.074 & 0.102676508524563 & -0.0286765085245635 \tabularnewline
193 & 0.099 & 0.0744195351605629 & 0.0245804648394371 \tabularnewline
194 & 0.071 & 0.105156608559995 & -0.0341566085599946 \tabularnewline
195 & 0.071 & 0.105156608559995 & -0.0341566085599946 \tabularnewline
196 & 0.074 & 0.10520280270257 & -0.0312028027025705 \tabularnewline
197 & 0.074 & 0.0974519004622833 & -0.0234519004622833 \tabularnewline
198 & 0.067 & 0.0984136322484499 & -0.0314136322484499 \tabularnewline
199 & 0.046 & 0.0807361276138575 & -0.0347361276138575 \tabularnewline
200 & 0.061 & 0.0998144301544859 & -0.0388144301544859 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154396&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]0.076[/C][C]0.0570174453149601[/C][C]0.0189825546850399[/C][/ROW]
[ROW][C]2[/C][C]0.098[/C][C]0.14622826350395[/C][C]-0.0482282635039496[/C][/ROW]
[ROW][C]3[/C][C]0.092[/C][C]0.114430846092554[/C][C]-0.0224308460925539[/C][/ROW]
[ROW][C]4[/C][C]0.075[/C][C]0.047421800763246[/C][C]0.027578199236754[/C][/ROW]
[ROW][C]5[/C][C]0.076[/C][C]0.0570174453150011[/C][C]0.0189825546849989[/C][/ROW]
[ROW][C]6[/C][C]0.075[/C][C]0.0540918289051296[/C][C]0.0209081710948704[/C][/ROW]
[ROW][C]7[/C][C]0.069[/C][C]0.056333059464901[/C][C]0.012666940535099[/C][/ROW]
[ROW][C]8[/C][C]0.065[/C][C]0.0484334731793262[/C][C]0.0165665268206738[/C][/ROW]
[ROW][C]9[/C][C]0.073[/C][C]0.0563141532032454[/C][C]0.0166858467967546[/C][/ROW]
[ROW][C]10[/C][C]0.071[/C][C]0.0908428182294663[/C][C]-0.0198428182294663[/C][/ROW]
[ROW][C]11[/C][C]0.097[/C][C]0.101269415792669[/C][C]-0.00426941579266873[/C][/ROW]
[ROW][C]12[/C][C]0.071[/C][C]0.0908428182294663[/C][C]-0.0198428182294663[/C][/ROW]
[ROW][C]13[/C][C]0.089[/C][C]0.0316584672836477[/C][C]0.0573415327163523[/C][/ROW]
[ROW][C]14[/C][C]0.114[/C][C]0.195392666770892[/C][C]-0.0813926667708918[/C][/ROW]
[ROW][C]15[/C][C]0.176[/C][C]0.14117498442252[/C][C]0.0348250155774797[/C][/ROW]
[ROW][C]16[/C][C]0.17[/C][C]0.136431806019104[/C][C]0.0335681939808963[/C][/ROW]
[ROW][C]17[/C][C]0.092[/C][C]0.132819250351056[/C][C]-0.0408192503510562[/C][/ROW]
[ROW][C]18[/C][C]0.368[/C][C]0.192788856648071[/C][C]0.175211143351929[/C][/ROW]
[ROW][C]19[/C][C]0.086[/C][C]0.045968352961755[/C][C]0.040031647038245[/C][/ROW]
[ROW][C]20[/C][C]0.341[/C][C]0.226571051142209[/C][C]0.114428948857791[/C][/ROW]
[ROW][C]21[/C][C]0.077[/C][C]0.0518361568096219[/C][C]0.0251638431903781[/C][/ROW]
[ROW][C]22[/C][C]0.082[/C][C]0.0796447577903006[/C][C]0.0023552422096994[/C][/ROW]
[ROW][C]23[/C][C]0.106[/C][C]0.139614293353029[/C][C]-0.0336142933530289[/C][/ROW]
[ROW][C]24[/C][C]0.084[/C][C]0.0513864812818435[/C][C]0.0326135187181565[/C][/ROW]
[ROW][C]25[/C][C]0.085[/C][C]0.0939451658417639[/C][C]-0.0089451658417639[/C][/ROW]
[ROW][C]26[/C][C]0.08[/C][C]0.115076669370999[/C][C]-0.0350766693709988[/C][/ROW]
[ROW][C]27[/C][C]0.08[/C][C]0.0993692032835817[/C][C]-0.0193692032835817[/C][/ROW]
[ROW][C]28[/C][C]0.106[/C][C]0.139614293353029[/C][C]-0.0336142933530289[/C][/ROW]
[ROW][C]29[/C][C]0.08[/C][C]0.0764500213715055[/C][C]0.00354997862849453[/C][/ROW]
[ROW][C]30[/C][C]0.082[/C][C]0.0531738761633358[/C][C]0.0288261238366642[/C][/ROW]
[ROW][C]31[/C][C]0.089[/C][C]0.0876760510748388[/C][C]0.00132394892516123[/C][/ROW]
[ROW][C]32[/C][C]0.105[/C][C]0.104349005504069[/C][C]0.000650994495930736[/C][/ROW]
[ROW][C]33[/C][C]0.083[/C][C]0.0687780325578491[/C][C]0.0142219674421509[/C][/ROW]
[ROW][C]34[/C][C]0.073[/C][C]0.0678364555240392[/C][C]0.00516354447596079[/C][/ROW]
[ROW][C]35[/C][C]0.103[/C][C]0.143146431605165[/C][C]-0.0401464316051655[/C][/ROW]
[ROW][C]36[/C][C]0.086[/C][C]0.0430254684339599[/C][C]0.0429745315660401[/C][/ROW]
[ROW][C]37[/C][C]0.086[/C][C]0.0900740488573457[/C][C]-0.00407404885734567[/C][/ROW]
[ROW][C]38[/C][C]0.066[/C][C]0.11791709723679[/C][C]-0.0519170972367898[/C][/ROW]
[ROW][C]39[/C][C]0.172[/C][C]0.124432007437291[/C][C]0.0475679925627088[/C][/ROW]
[ROW][C]40[/C][C]0.074[/C][C]0.10478348174635[/C][C]-0.0307834817463501[/C][/ROW]
[ROW][C]41[/C][C]0.074[/C][C]0.10478348174635[/C][C]-0.0307834817463501[/C][/ROW]
[ROW][C]42[/C][C]0.088[/C][C]0.101114154336102[/C][C]-0.0131141543361016[/C][/ROW]
[ROW][C]43[/C][C]0.332[/C][C]0.172334987961396[/C][C]0.159665012038604[/C][/ROW]
[ROW][C]44[/C][C]0.069[/C][C]0.151351284457262[/C][C]-0.0823512844572623[/C][/ROW]
[ROW][C]45[/C][C]0.05[/C][C]0.0617775709294996[/C][C]-0.0117775709294996[/C][/ROW]
[ROW][C]46[/C][C]0.054[/C][C]0.0103097409468837[/C][C]0.0436902590531163[/C][/ROW]
[ROW][C]47[/C][C]0.114[/C][C]0.170998761439461[/C][C]-0.0569987614394613[/C][/ROW]
[ROW][C]48[/C][C]0.113[/C][C]0.1098079413928[/C][C]0.00319205860720013[/C][/ROW]
[ROW][C]49[/C][C]0.066[/C][C]0.120382902643455[/C][C]-0.054382902643455[/C][/ROW]
[ROW][C]50[/C][C]0.074[/C][C]0.12491749345056[/C][C]-0.05091749345056[/C][/ROW]
[ROW][C]51[/C][C]0.074[/C][C]0.129440247544996[/C][C]-0.0554402475449957[/C][/ROW]
[ROW][C]52[/C][C]0.069[/C][C]0.0699622029873691[/C][C]-0.000962202987369103[/C][/ROW]
[ROW][C]53[/C][C]0.068[/C][C]0.0664547371891381[/C][C]0.00154526281086189[/C][/ROW]
[ROW][C]54[/C][C]0.081[/C][C]0.0756568335940974[/C][C]0.00534316640590257[/C][/ROW]
[ROW][C]55[/C][C]0.11[/C][C]0.135334169856356[/C][C]-0.0253341698563564[/C][/ROW]
[ROW][C]56[/C][C]0.084[/C][C]0.0982336613724307[/C][C]-0.0142336613724307[/C][/ROW]
[ROW][C]57[/C][C]0.07[/C][C]0.119075152506323[/C][C]-0.0490751525063226[/C][/ROW]
[ROW][C]58[/C][C]0.111[/C][C]0.163426877563553[/C][C]-0.0524268775635533[/C][/ROW]
[ROW][C]59[/C][C]0.076[/C][C]0.083457640234392[/C][C]-0.00745764023439204[/C][/ROW]
[ROW][C]60[/C][C]0.074[/C][C]0.0523523124878031[/C][C]0.0216476875121969[/C][/ROW]
[ROW][C]61[/C][C]0.079[/C][C]0.0566778195829853[/C][C]0.0223221804170147[/C][/ROW]
[ROW][C]62[/C][C]0.115[/C][C]0.165903898341111[/C][C]-0.0509038983411106[/C][/ROW]
[ROW][C]63[/C][C]0.085[/C][C]0.0791364469351231[/C][C]0.00586355306487694[/C][/ROW]
[ROW][C]64[/C][C]0.081[/C][C]0.0947273817092706[/C][C]-0.0137273817092706[/C][/ROW]
[ROW][C]65[/C][C]0.086[/C][C]0.0621274883469638[/C][C]0.0238725116530361[/C][/ROW]
[ROW][C]66[/C][C]0.086[/C][C]0.0621274883469638[/C][C]0.0238725116530361[/C][/ROW]
[ROW][C]67[/C][C]0.079[/C][C]0.0631530156272737[/C][C]0.0158469843727263[/C][/ROW]
[ROW][C]68[/C][C]0.076[/C][C]0.124573111632653[/C][C]-0.0485731116326529[/C][/ROW]
[ROW][C]69[/C][C]0.074[/C][C]0.127616841150854[/C][C]-0.0536168411508543[/C][/ROW]
[ROW][C]70[/C][C]0.074[/C][C]0.0977113623832479[/C][C]-0.0237113623832479[/C][/ROW]
[ROW][C]71[/C][C]0.076[/C][C]0.0966363340615464[/C][C]-0.0206363340615464[/C][/ROW]
[ROW][C]72[/C][C]0.088[/C][C]0.0646057014875704[/C][C]0.0233942985124296[/C][/ROW]
[ROW][C]73[/C][C]0.084[/C][C]0.0720411201324762[/C][C]0.0119588798675238[/C][/ROW]
[ROW][C]74[/C][C]0.084[/C][C]0.103962785305863[/C][C]-0.0199627853058632[/C][/ROW]
[ROW][C]75[/C][C]0.094[/C][C]0.101531378281982[/C][C]-0.00753137828198184[/C][/ROW]
[ROW][C]76[/C][C]0.093[/C][C]0.0917986888679539[/C][C]0.00120131113204607[/C][/ROW]
[ROW][C]77[/C][C]0.093[/C][C]0.0917986888679539[/C][C]0.00120131113204607[/C][/ROW]
[ROW][C]78[/C][C]0.104[/C][C]0.0892083611092238[/C][C]0.0147916388907762[/C][/ROW]
[ROW][C]79[/C][C]0.086[/C][C]0.0880069219340508[/C][C]-0.00200692193405082[/C][/ROW]
[ROW][C]80[/C][C]0.08[/C][C]0.141437597058544[/C][C]-0.0614375970585437[/C][/ROW]
[ROW][C]81[/C][C]0.069[/C][C]0.100630647833507[/C][C]-0.0316306478335069[/C][/ROW]
[ROW][C]82[/C][C]0.464[/C][C]0.27731251741567[/C][C]0.18668748258433[/C][/ROW]
[ROW][C]83[/C][C]0.086[/C][C]0.131850751828583[/C][C]-0.0458507518285831[/C][/ROW]
[ROW][C]84[/C][C]0.401[/C][C]0.222189885974209[/C][C]0.178810114025791[/C][/ROW]
[ROW][C]85[/C][C]0.069[/C][C]0.14831737400588[/C][C]-0.0793173740058797[/C][/ROW]
[ROW][C]86[/C][C]0.076[/C][C]0.108016581799234[/C][C]-0.0320165817992343[/C][/ROW]
[ROW][C]87[/C][C]0.11[/C][C]0.218006105255033[/C][C]-0.108006105255033[/C][/ROW]
[ROW][C]88[/C][C]0.062[/C][C]0.080745131481586[/C][C]-0.018745131481586[/C][/ROW]
[ROW][C]89[/C][C]0.107[/C][C]0.146111404964336[/C][C]-0.0391114049643362[/C][/ROW]
[ROW][C]90[/C][C]0.076[/C][C]0.0825763365983858[/C][C]-0.00657633659838584[/C][/ROW]
[ROW][C]91[/C][C]0.079[/C][C]0.108322549287442[/C][C]-0.0293225492874424[/C][/ROW]
[ROW][C]92[/C][C]0.11[/C][C]0.218006105255033[/C][C]-0.108006105255033[/C][/ROW]
[ROW][C]93[/C][C]0.11[/C][C]0.220972307101263[/C][C]-0.110972307101263[/C][/ROW]
[ROW][C]94[/C][C]0.062[/C][C]0.080745131481586[/C][C]-0.018745131481586[/C][/ROW]
[ROW][C]95[/C][C]0.045[/C][C]0.0970963455031059[/C][C]-0.0520963455031059[/C][/ROW]
[ROW][C]96[/C][C]0.058[/C][C]0.00841130814293038[/C][C]0.0495886918570696[/C][/ROW]
[ROW][C]97[/C][C]0.102[/C][C]0.0958903228434239[/C][C]0.00610967715657608[/C][/ROW]
[ROW][C]98[/C][C]0.07[/C][C]0.133405785798567[/C][C]-0.0634057857985675[/C][/ROW]
[ROW][C]99[/C][C]0.079[/C][C]0.0965586121893486[/C][C]-0.0175586121893486[/C][/ROW]
[ROW][C]100[/C][C]0.08[/C][C]0.0859438922175879[/C][C]-0.00594389221758793[/C][/ROW]
[ROW][C]101[/C][C]0.084[/C][C]0.0785511484891498[/C][C]0.00544885151085018[/C][/ROW]
[ROW][C]102[/C][C]0.075[/C][C]0.106424465243968[/C][C]-0.0314244652439681[/C][/ROW]
[ROW][C]103[/C][C]0.08[/C][C]0.0859438922175879[/C][C]-0.00594389221758793[/C][/ROW]
[ROW][C]104[/C][C]0.077[/C][C]0.0629021021640881[/C][C]0.0140978978359119[/C][/ROW]
[ROW][C]105[/C][C]0.07[/C][C]0.076994868812542[/C][C]-0.00699486881254197[/C][/ROW]
[ROW][C]106[/C][C]0.077[/C][C]0.0629021021640881[/C][C]0.0140978978359119[/C][/ROW]
[ROW][C]107[/C][C]0.467[/C][C]0.276394558359464[/C][C]0.190605441640536[/C][/ROW]
[ROW][C]108[/C][C]0.088[/C][C]0.151429374380828[/C][C]-0.063429374380828[/C][/ROW]
[ROW][C]109[/C][C]0.091[/C][C]0.107507422657401[/C][C]-0.0165074226574011[/C][/ROW]
[ROW][C]110[/C][C]0.122[/C][C]0.17002669329673[/C][C]-0.04802669329673[/C][/ROW]
[ROW][C]111[/C][C]0.104[/C][C]0.139287288564798[/C][C]-0.0352872885647982[/C][/ROW]
[ROW][C]112[/C][C]0.084[/C][C]0.0526469413236611[/C][C]0.0313530586763389[/C][/ROW]
[ROW][C]113[/C][C]0.085[/C][C]0.056965793749988[/C][C]0.028034206250012[/C][/ROW]
[ROW][C]114[/C][C]0.08[/C][C]0.0693454148810211[/C][C]0.0106545851189789[/C][/ROW]
[ROW][C]115[/C][C]0.104[/C][C]0.139287288564798[/C][C]-0.0352872885647982[/C][/ROW]
[ROW][C]116[/C][C]0.09[/C][C]0.0993896139690238[/C][C]-0.00938961396902385[/C][/ROW]
[ROW][C]117[/C][C]0.077[/C][C]0.0909505425154565[/C][C]-0.0139505425154565[/C][/ROW]
[ROW][C]118[/C][C]0.082[/C][C]0.0578875903811411[/C][C]0.0241124096188589[/C][/ROW]
[ROW][C]119[/C][C]0.119[/C][C]0.0566868252468692[/C][C]0.0623131747531308[/C][/ROW]
[ROW][C]120[/C][C]0.097[/C][C]0.0749741020534771[/C][C]0.0220258979465229[/C][/ROW]
[ROW][C]121[/C][C]0.178[/C][C]0.0961980350920309[/C][C]0.0818019649079691[/C][/ROW]
[ROW][C]122[/C][C]0.119[/C][C]0.0566868252468692[/C][C]0.0623131747531308[/C][/ROW]
[ROW][C]123[/C][C]0.075[/C][C]0.0564335176204303[/C][C]0.0185664823795697[/C][/ROW]
[ROW][C]124[/C][C]0.08[/C][C]0.0400819580647721[/C][C]0.0399180419352279[/C][/ROW]
[ROW][C]125[/C][C]0.082[/C][C]0.0154958923755222[/C][C]0.0665041076244778[/C][/ROW]
[ROW][C]126[/C][C]0.146[/C][C]0.108467232676015[/C][C]0.037532767323985[/C][/ROW]
[ROW][C]127[/C][C]0.081[/C][C]0.0737041637989649[/C][C]0.00729583620103509[/C][/ROW]
[ROW][C]128[/C][C]0.082[/C][C]0.0735012475911053[/C][C]0.00849875240889467[/C][/ROW]
[ROW][C]129[/C][C]0.065[/C][C]0.0660399636335447[/C][C]-0.0010399636335447[/C][/ROW]
[ROW][C]130[/C][C]0.072[/C][C]0.0853375965140536[/C][C]-0.0133375965140536[/C][/ROW]
[ROW][C]131[/C][C]0.118[/C][C]0.163880435662149[/C][C]-0.0458804356621492[/C][/ROW]
[ROW][C]132[/C][C]0.049[/C][C]0.0360132634041001[/C][C]0.0129867365958999[/C][/ROW]
[ROW][C]133[/C][C]0.049[/C][C]0.0360132634041001[/C][C]0.0129867365958999[/C][/ROW]
[ROW][C]134[/C][C]0.06[/C][C]0.0796852911187684[/C][C]-0.0196852911187684[/C][/ROW]
[ROW][C]135[/C][C]0.084[/C][C]0.137353952519685[/C][C]-0.0533539525196849[/C][/ROW]
[ROW][C]136[/C][C]0.09[/C][C]0.11214706940305[/C][C]-0.0221470694030503[/C][/ROW]
[ROW][C]137[/C][C]0.089[/C][C]0.105692372289833[/C][C]-0.0166923722898326[/C][/ROW]
[ROW][C]138[/C][C]0.081[/C][C]0.0880545061622615[/C][C]-0.00705450616226146[/C][/ROW]
[ROW][C]139[/C][C]0.081[/C][C]0.0299258006013584[/C][C]0.0510741993986416[/C][/ROW]
[ROW][C]140[/C][C]0.081[/C][C]0.0366740505283993[/C][C]0.0443259494716007[/C][/ROW]
[ROW][C]141[/C][C]0.09[/C][C]0.11214706940305[/C][C]-0.0221470694030503[/C][/ROW]
[ROW][C]142[/C][C]0.089[/C][C]0.105692372289833[/C][C]-0.0166923722898326[/C][/ROW]
[ROW][C]143[/C][C]0.05[/C][C]0.0388001356722215[/C][C]0.0111998643277785[/C][/ROW]
[ROW][C]144[/C][C]0.066[/C][C]0.0822623606701625[/C][C]-0.0162623606701625[/C][/ROW]
[ROW][C]145[/C][C]0.05[/C][C]0.0388001356722215[/C][C]0.0111998643277785[/C][/ROW]
[ROW][C]146[/C][C]0.117[/C][C]0.171608787909498[/C][C]-0.0546087879094978[/C][/ROW]
[ROW][C]147[/C][C]0.087[/C][C]0.0325039709482231[/C][C]0.0544960290517769[/C][/ROW]
[ROW][C]148[/C][C]0.236[/C][C]0.144020980037442[/C][C]0.091979019962558[/C][/ROW]
[ROW][C]149[/C][C]0.074[/C][C]0.07391498686349[/C][C]8.50131365100393e-05[/C][/ROW]
[ROW][C]150[/C][C]0.089[/C][C]0.0535534074119467[/C][C]0.0354465925880533[/C][/ROW]
[ROW][C]151[/C][C]0.077[/C][C]0.127382047972067[/C][C]-0.0503820479720668[/C][/ROW]
[ROW][C]152[/C][C]0.61[/C][C]0.491933764907342[/C][C]0.118066235092658[/C][/ROW]
[ROW][C]153[/C][C]0.095[/C][C]0.0298089870679509[/C][C]0.0651910129320491[/C][/ROW]
[ROW][C]154[/C][C]0.095[/C][C]0.0298089870679509[/C][C]0.0651910129320491[/C][/ROW]
[ROW][C]155[/C][C]0.07[/C][C]0.0887641459885667[/C][C]-0.0187641459885667[/C][/ROW]
[ROW][C]156[/C][C]0.071[/C][C]0.0866834189916935[/C][C]-0.0156834189916935[/C][/ROW]
[ROW][C]157[/C][C]0.07[/C][C]0.0887641459885667[/C][C]-0.0187641459885667[/C][/ROW]
[ROW][C]158[/C][C]0.071[/C][C]0.0866834189916935[/C][C]-0.0156834189916935[/C][/ROW]
[ROW][C]159[/C][C]0.073[/C][C]0.0602372092866474[/C][C]0.0127627907133526[/C][/ROW]
[ROW][C]160[/C][C]0.079[/C][C]0.0284869212020451[/C][C]0.0505130787979549[/C][/ROW]
[ROW][C]161[/C][C]0.09[/C][C]0.137453028712414[/C][C]-0.0474530287124137[/C][/ROW]
[ROW][C]162[/C][C]0.072[/C][C]0.1649585547406[/C][C]-0.0929585547406001[/C][/ROW]
[ROW][C]163[/C][C]0.076[/C][C]0.0793863267677319[/C][C]-0.00338632676773193[/C][/ROW]
[ROW][C]164[/C][C]0.07[/C][C]0.0704995249019322[/C][C]-0.000499524901932191[/C][/ROW]
[ROW][C]165[/C][C]0.07[/C][C]0.0705864661618116[/C][C]-0.000586466161811566[/C][/ROW]
[ROW][C]166[/C][C]0.1[/C][C]0.141925461091123[/C][C]-0.041925461091123[/C][/ROW]
[ROW][C]167[/C][C]0.085[/C][C]0.0753481702620554[/C][C]0.00965182973794465[/C][/ROW]
[ROW][C]168[/C][C]0.072[/C][C]0.0464017251874493[/C][C]0.0255982748125506[/C][/ROW]
[ROW][C]169[/C][C]0.089[/C][C]0.0501136585460789[/C][C]0.0388863414539211[/C][/ROW]
[ROW][C]170[/C][C]0.36[/C][C]0.265671017053337[/C][C]0.0943289829466633[/C][/ROW]
[ROW][C]171[/C][C]0.058[/C][C]0.0819920962581696[/C][C]-0.0239920962581696[/C][/ROW]
[ROW][C]172[/C][C]0.073[/C][C]0.0792743322123685[/C][C]-0.00627433221236848[/C][/ROW]
[ROW][C]173[/C][C]0.073[/C][C]0.0792743322123685[/C][C]-0.00627433221236848[/C][/ROW]
[ROW][C]174[/C][C]0.068[/C][C]0.10955526769718[/C][C]-0.04155526769718[/C][/ROW]
[ROW][C]175[/C][C]0.08[/C][C]0.067251387611557[/C][C]0.012748612388443[/C][/ROW]
[ROW][C]176[/C][C]0.085[/C][C]0.0951313688024944[/C][C]-0.0101313688024944[/C][/ROW]
[ROW][C]177[/C][C]0.08[/C][C]0.067251387611557[/C][C]0.012748612388443[/C][/ROW]
[ROW][C]178[/C][C]0.087[/C][C]0.0750359098430264[/C][C]0.0119640901569735[/C][/ROW]
[ROW][C]179[/C][C]0.068[/C][C]0.0734116053743165[/C][C]-0.00541160537431653[/C][/ROW]
[ROW][C]180[/C][C]0.067[/C][C]0.0762577636331272[/C][C]-0.00925776363312716[/C][/ROW]
[ROW][C]181[/C][C]0.067[/C][C]0.0762577636331272[/C][C]-0.00925776363312716[/C][/ROW]
[ROW][C]182[/C][C]0.27[/C][C]0.161486910499201[/C][C]0.108513089500799[/C][/ROW]
[ROW][C]183[/C][C]0.076[/C][C]0.0757176579978062[/C][C]0.000282342002193847[/C][/ROW]
[ROW][C]184[/C][C]0.077[/C][C]0.0601086562935391[/C][C]0.0168913437064609[/C][/ROW]
[ROW][C]185[/C][C]0.079[/C][C]0.062661559153392[/C][C]0.016338440846608[/C][/ROW]
[ROW][C]186[/C][C]0.111[/C][C]0.105718949814705[/C][C]0.00528105018529458[/C][/ROW]
[ROW][C]187[/C][C]0.082[/C][C]0.122201310851349[/C][C]-0.0402013108513487[/C][/ROW]
[ROW][C]188[/C][C]0.084[/C][C]0.0897645455104902[/C][C]-0.00576454551049024[/C][/ROW]
[ROW][C]189[/C][C]0.084[/C][C]0.0710582027956655[/C][C]0.0129417972043345[/C][/ROW]
[ROW][C]190[/C][C]0.082[/C][C]0.0733856199843674[/C][C]0.00861438001563265[/C][/ROW]
[ROW][C]191[/C][C]0.077[/C][C]0.0868480787427633[/C][C]-0.00984807874276328[/C][/ROW]
[ROW][C]192[/C][C]0.074[/C][C]0.102676508524563[/C][C]-0.0286765085245635[/C][/ROW]
[ROW][C]193[/C][C]0.099[/C][C]0.0744195351605629[/C][C]0.0245804648394371[/C][/ROW]
[ROW][C]194[/C][C]0.071[/C][C]0.105156608559995[/C][C]-0.0341566085599946[/C][/ROW]
[ROW][C]195[/C][C]0.071[/C][C]0.105156608559995[/C][C]-0.0341566085599946[/C][/ROW]
[ROW][C]196[/C][C]0.074[/C][C]0.10520280270257[/C][C]-0.0312028027025705[/C][/ROW]
[ROW][C]197[/C][C]0.074[/C][C]0.0974519004622833[/C][C]-0.0234519004622833[/C][/ROW]
[ROW][C]198[/C][C]0.067[/C][C]0.0984136322484499[/C][C]-0.0314136322484499[/C][/ROW]
[ROW][C]199[/C][C]0.046[/C][C]0.0807361276138575[/C][C]-0.0347361276138575[/C][/ROW]
[ROW][C]200[/C][C]0.061[/C][C]0.0998144301544859[/C][C]-0.0388144301544859[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154396&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154396&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	0.076	0.0570174453149601	0.0189825546850399
2	0.098	0.14622826350395	-0.0482282635039496
3	0.092	0.114430846092554	-0.0224308460925539
4	0.075	0.047421800763246	0.027578199236754
5	0.076	0.0570174453150011	0.0189825546849989
6	0.075	0.0540918289051296	0.0209081710948704
7	0.069	0.056333059464901	0.012666940535099
8	0.065	0.0484334731793262	0.0165665268206738
9	0.073	0.0563141532032454	0.0166858467967546
10	0.071	0.0908428182294663	-0.0198428182294663
11	0.097	0.101269415792669	-0.00426941579266873
12	0.071	0.0908428182294663	-0.0198428182294663
13	0.089	0.0316584672836477	0.0573415327163523
14	0.114	0.195392666770892	-0.0813926667708918
15	0.176	0.14117498442252	0.0348250155774797
16	0.17	0.136431806019104	0.0335681939808963
17	0.092	0.132819250351056	-0.0408192503510562
18	0.368	0.192788856648071	0.175211143351929
19	0.086	0.045968352961755	0.040031647038245
20	0.341	0.226571051142209	0.114428948857791
21	0.077	0.0518361568096219	0.0251638431903781
22	0.082	0.0796447577903006	0.0023552422096994
23	0.106	0.139614293353029	-0.0336142933530289
24	0.084	0.0513864812818435	0.0326135187181565
25	0.085	0.0939451658417639	-0.0089451658417639
26	0.08	0.115076669370999	-0.0350766693709988
27	0.08	0.0993692032835817	-0.0193692032835817
28	0.106	0.139614293353029	-0.0336142933530289
29	0.08	0.0764500213715055	0.00354997862849453
30	0.082	0.0531738761633358	0.0288261238366642
31	0.089	0.0876760510748388	0.00132394892516123
32	0.105	0.104349005504069	0.000650994495930736
33	0.083	0.0687780325578491	0.0142219674421509
34	0.073	0.0678364555240392	0.00516354447596079
35	0.103	0.143146431605165	-0.0401464316051655
36	0.086	0.0430254684339599	0.0429745315660401
37	0.086	0.0900740488573457	-0.00407404885734567
38	0.066	0.11791709723679	-0.0519170972367898
39	0.172	0.124432007437291	0.0475679925627088
40	0.074	0.10478348174635	-0.0307834817463501
41	0.074	0.10478348174635	-0.0307834817463501
42	0.088	0.101114154336102	-0.0131141543361016
43	0.332	0.172334987961396	0.159665012038604
44	0.069	0.151351284457262	-0.0823512844572623
45	0.05	0.0617775709294996	-0.0117775709294996
46	0.054	0.0103097409468837	0.0436902590531163
47	0.114	0.170998761439461	-0.0569987614394613
48	0.113	0.1098079413928	0.00319205860720013
49	0.066	0.120382902643455	-0.054382902643455
50	0.074	0.12491749345056	-0.05091749345056
51	0.074	0.129440247544996	-0.0554402475449957
52	0.069	0.0699622029873691	-0.000962202987369103
53	0.068	0.0664547371891381	0.00154526281086189
54	0.081	0.0756568335940974	0.00534316640590257
55	0.11	0.135334169856356	-0.0253341698563564
56	0.084	0.0982336613724307	-0.0142336613724307
57	0.07	0.119075152506323	-0.0490751525063226
58	0.111	0.163426877563553	-0.0524268775635533
59	0.076	0.083457640234392	-0.00745764023439204
60	0.074	0.0523523124878031	0.0216476875121969
61	0.079	0.0566778195829853	0.0223221804170147
62	0.115	0.165903898341111	-0.0509038983411106
63	0.085	0.0791364469351231	0.00586355306487694
64	0.081	0.0947273817092706	-0.0137273817092706
65	0.086	0.0621274883469638	0.0238725116530361
66	0.086	0.0621274883469638	0.0238725116530361
67	0.079	0.0631530156272737	0.0158469843727263
68	0.076	0.124573111632653	-0.0485731116326529
69	0.074	0.127616841150854	-0.0536168411508543
70	0.074	0.0977113623832479	-0.0237113623832479
71	0.076	0.0966363340615464	-0.0206363340615464
72	0.088	0.0646057014875704	0.0233942985124296
73	0.084	0.0720411201324762	0.0119588798675238
74	0.084	0.103962785305863	-0.0199627853058632
75	0.094	0.101531378281982	-0.00753137828198184
76	0.093	0.0917986888679539	0.00120131113204607
77	0.093	0.0917986888679539	0.00120131113204607
78	0.104	0.0892083611092238	0.0147916388907762
79	0.086	0.0880069219340508	-0.00200692193405082
80	0.08	0.141437597058544	-0.0614375970585437
81	0.069	0.100630647833507	-0.0316306478335069
82	0.464	0.27731251741567	0.18668748258433
83	0.086	0.131850751828583	-0.0458507518285831
84	0.401	0.222189885974209	0.178810114025791
85	0.069	0.14831737400588	-0.0793173740058797
86	0.076	0.108016581799234	-0.0320165817992343
87	0.11	0.218006105255033	-0.108006105255033
88	0.062	0.080745131481586	-0.018745131481586
89	0.107	0.146111404964336	-0.0391114049643362
90	0.076	0.0825763365983858	-0.00657633659838584
91	0.079	0.108322549287442	-0.0293225492874424
92	0.11	0.218006105255033	-0.108006105255033
93	0.11	0.220972307101263	-0.110972307101263
94	0.062	0.080745131481586	-0.018745131481586
95	0.045	0.0970963455031059	-0.0520963455031059
96	0.058	0.00841130814293038	0.0495886918570696
97	0.102	0.0958903228434239	0.00610967715657608
98	0.07	0.133405785798567	-0.0634057857985675
99	0.079	0.0965586121893486	-0.0175586121893486
100	0.08	0.0859438922175879	-0.00594389221758793
101	0.084	0.0785511484891498	0.00544885151085018
102	0.075	0.106424465243968	-0.0314244652439681
103	0.08	0.0859438922175879	-0.00594389221758793
104	0.077	0.0629021021640881	0.0140978978359119
105	0.07	0.076994868812542	-0.00699486881254197
106	0.077	0.0629021021640881	0.0140978978359119
107	0.467	0.276394558359464	0.190605441640536
108	0.088	0.151429374380828	-0.063429374380828
109	0.091	0.107507422657401	-0.0165074226574011
110	0.122	0.17002669329673	-0.04802669329673
111	0.104	0.139287288564798	-0.0352872885647982
112	0.084	0.0526469413236611	0.0313530586763389
113	0.085	0.056965793749988	0.028034206250012
114	0.08	0.0693454148810211	0.0106545851189789
115	0.104	0.139287288564798	-0.0352872885647982
116	0.09	0.0993896139690238	-0.00938961396902385
117	0.077	0.0909505425154565	-0.0139505425154565
118	0.082	0.0578875903811411	0.0241124096188589
119	0.119	0.0566868252468692	0.0623131747531308
120	0.097	0.0749741020534771	0.0220258979465229
121	0.178	0.0961980350920309	0.0818019649079691
122	0.119	0.0566868252468692	0.0623131747531308
123	0.075	0.0564335176204303	0.0185664823795697
124	0.08	0.0400819580647721	0.0399180419352279
125	0.082	0.0154958923755222	0.0665041076244778
126	0.146	0.108467232676015	0.037532767323985
127	0.081	0.0737041637989649	0.00729583620103509
128	0.082	0.0735012475911053	0.00849875240889467
129	0.065	0.0660399636335447	-0.0010399636335447
130	0.072	0.0853375965140536	-0.0133375965140536
131	0.118	0.163880435662149	-0.0458804356621492
132	0.049	0.0360132634041001	0.0129867365958999
133	0.049	0.0360132634041001	0.0129867365958999
134	0.06	0.0796852911187684	-0.0196852911187684
135	0.084	0.137353952519685	-0.0533539525196849
136	0.09	0.11214706940305	-0.0221470694030503
137	0.089	0.105692372289833	-0.0166923722898326
138	0.081	0.0880545061622615	-0.00705450616226146
139	0.081	0.0299258006013584	0.0510741993986416
140	0.081	0.0366740505283993	0.0443259494716007
141	0.09	0.11214706940305	-0.0221470694030503
142	0.089	0.105692372289833	-0.0166923722898326
143	0.05	0.0388001356722215	0.0111998643277785
144	0.066	0.0822623606701625	-0.0162623606701625
145	0.05	0.0388001356722215	0.0111998643277785
146	0.117	0.171608787909498	-0.0546087879094978
147	0.087	0.0325039709482231	0.0544960290517769
148	0.236	0.144020980037442	0.091979019962558
149	0.074	0.07391498686349	8.50131365100393e-05
150	0.089	0.0535534074119467	0.0354465925880533
151	0.077	0.127382047972067	-0.0503820479720668
152	0.61	0.491933764907342	0.118066235092658
153	0.095	0.0298089870679509	0.0651910129320491
154	0.095	0.0298089870679509	0.0651910129320491
155	0.07	0.0887641459885667	-0.0187641459885667
156	0.071	0.0866834189916935	-0.0156834189916935
157	0.07	0.0887641459885667	-0.0187641459885667
158	0.071	0.0866834189916935	-0.0156834189916935
159	0.073	0.0602372092866474	0.0127627907133526
160	0.079	0.0284869212020451	0.0505130787979549
161	0.09	0.137453028712414	-0.0474530287124137
162	0.072	0.1649585547406	-0.0929585547406001
163	0.076	0.0793863267677319	-0.00338632676773193
164	0.07	0.0704995249019322	-0.000499524901932191
165	0.07	0.0705864661618116	-0.000586466161811566
166	0.1	0.141925461091123	-0.041925461091123
167	0.085	0.0753481702620554	0.00965182973794465
168	0.072	0.0464017251874493	0.0255982748125506
169	0.089	0.0501136585460789	0.0388863414539211
170	0.36	0.265671017053337	0.0943289829466633
171	0.058	0.0819920962581696	-0.0239920962581696
172	0.073	0.0792743322123685	-0.00627433221236848
173	0.073	0.0792743322123685	-0.00627433221236848
174	0.068	0.10955526769718	-0.04155526769718
175	0.08	0.067251387611557	0.012748612388443
176	0.085	0.0951313688024944	-0.0101313688024944
177	0.08	0.067251387611557	0.012748612388443
178	0.087	0.0750359098430264	0.0119640901569735
179	0.068	0.0734116053743165	-0.00541160537431653
180	0.067	0.0762577636331272	-0.00925776363312716
181	0.067	0.0762577636331272	-0.00925776363312716
182	0.27	0.161486910499201	0.108513089500799
183	0.076	0.0757176579978062	0.000282342002193847
184	0.077	0.0601086562935391	0.0168913437064609
185	0.079	0.062661559153392	0.016338440846608
186	0.111	0.105718949814705	0.00528105018529458
187	0.082	0.122201310851349	-0.0402013108513487
188	0.084	0.0897645455104902	-0.00576454551049024
189	0.084	0.0710582027956655	0.0129417972043345
190	0.082	0.0733856199843674	0.00861438001563265
191	0.077	0.0868480787427633	-0.00984807874276328
192	0.074	0.102676508524563	-0.0286765085245635
193	0.099	0.0744195351605629	0.0245804648394371
194	0.071	0.105156608559995	-0.0341566085599946
195	0.071	0.105156608559995	-0.0341566085599946
196	0.074	0.10520280270257	-0.0312028027025705
197	0.074	0.0974519004622833	-0.0234519004622833
198	0.067	0.0984136322484499	-0.0314136322484499
199	0.046	0.0807361276138575	-0.0347361276138575
200	0.061	0.0998144301544859	-0.0388144301544859

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
15	6.89134429335794e-05	0.000137826885867159	0.999931086557066
16	0.000886299562512693	0.00177259912502539	0.999113700437487
17	0.00107272263660939	0.00214544527321879	0.998927277363391
18	0.547567212677298	0.904865574645403	0.452432787322702
19	0.666493846181997	0.667012307636007	0.333506153818003
20	0.76826998664384	0.463460026712319	0.23173001335616
21	0.71433984055037	0.57132031889926	0.28566015944963
22	0.775377219995297	0.449245560009406	0.224622780004703
23	0.94762615700593	0.104747685988141	0.0523738429940704
24	0.92500194431139	0.149996111377219	0.0749980556886097
25	0.893158686479337	0.213682627041325	0.106841313520663
26	0.892582245255785	0.21483550948843	0.107417754744215
27	0.856721581390832	0.286556837218336	0.143278418609168
28	0.821036046043002	0.357927907913996	0.178963953956998
29	0.770590508028158	0.458818983943684	0.229409491971842
30	0.749192785649841	0.501614428700318	0.250807214350159
31	0.691314688495638	0.617370623008723	0.308685311504361
32	0.722256052070086	0.555487895859827	0.277743947929914
33	0.669045351959821	0.661909296080357	0.330954648040179
34	0.616034734273297	0.767930531453407	0.383965265726703
35	0.6000948816995	0.799810236601	0.3999051183005
36	0.568808853331994	0.862382293336011	0.431191146668006
37	0.528701027263604	0.942597945472792	0.471298972736396
38	0.565052028807148	0.869895942385703	0.434947971192852
39	0.519255900100335	0.96148819979933	0.480744099899665
40	0.46648922408989	0.932978448179781	0.53351077591011
41	0.415258482506799	0.830516965013598	0.584741517493201
42	0.376462033890732	0.752924067781464	0.623537966109268
43	0.848986530141191	0.302026939717618	0.151013469858809
44	0.903206234267304	0.193587531465392	0.096793765732696
45	0.880289944108641	0.239420111782719	0.119710055891359
46	0.895404982250123	0.209190035499754	0.104595017749877
47	0.885537567246688	0.228924865506624	0.114462432753312
48	0.85844855218328	0.283102895633441	0.14155144781672
49	0.860417401581652	0.279165196836695	0.139582598418347
50	0.843850468155214	0.312299063689573	0.156149531844786
51	0.847459018459266	0.305081963081469	0.152540981540735
52	0.817308369177079	0.365383261645842	0.182691630822921
53	0.783064383162696	0.433871233674609	0.216935616837304
54	0.745028676274364	0.509942647451271	0.254971323725636
55	0.742517143974693	0.514965712050614	0.257482856025307
56	0.709022706895452	0.581954586209095	0.290977293104548
57	0.697748987097786	0.604502025804428	0.302251012902214
58	0.700851729376335	0.598296541247329	0.299148270623665
59	0.658151018881342	0.683697962237316	0.341848981118658
60	0.622314079388542	0.755371841222917	0.377685920611458
61	0.587213513419918	0.825572973160164	0.412786486580082
62	0.563606414299199	0.872787171401603	0.436393585700801
63	0.517349623748863	0.965300752502274	0.482650376251137
64	0.472901221917702	0.945802443835405	0.527098778082298
65	0.434751381884177	0.869502763768355	0.565248618115823
66	0.39610739006625	0.792214780132501	0.60389260993375
67	0.354846112468669	0.709692224937338	0.645153887531331
68	0.34632831786163	0.69265663572326	0.65367168213837
69	0.346065246031905	0.692130492063809	0.653934753968095
70	0.330488751706147	0.660977503412294	0.669511248293853
71	0.296483109945992	0.592966219891984	0.703516890054008
72	0.266494924043883	0.532989848087765	0.733505075956117
73	0.232320224102976	0.464640448205952	0.767679775897024
74	0.201750734544727	0.403501469089454	0.798249265455273
75	0.171666596205113	0.343333192410225	0.828333403794887
76	0.151621190821177	0.303242381642353	0.848378809178823
77	0.130611597593748	0.261223195187496	0.869388402406252
78	0.110265854802046	0.220531709604092	0.889734145197954
79	0.0906693770296457	0.181338754059291	0.909330622970354
80	0.102139103090709	0.204278206181418	0.897860896909291
81	0.0892711827806702	0.17854236556134	0.91072881721933
82	0.579885446176531	0.840229107646937	0.420114553823469
83	0.567704200687047	0.864591598625907	0.432295799312953
84	0.909777385432416	0.180445229135169	0.0902226145675843
85	0.933333557308695	0.13333288538261	0.066666442691305
86	0.924119788609638	0.151760422780724	0.0758802113903621
87	0.96629279555575	0.0674144088885004	0.0337072044442502
88	0.958815719092929	0.0823685618141427	0.0411842809070713
89	0.955009756056187	0.0899804878876255	0.0449902439438128
90	0.944148869704526	0.111702260590948	0.0558511302954742
91	0.935585343305057	0.128829313389887	0.0644146566949434
92	0.974769040135982	0.0504619197280354	0.0252309598640177
93	0.999257426267195	0.00148514746560934	0.000742573732804669
94	0.998995046394312	0.00200990721137665	0.00100495360568832
95	0.998944992765335	0.00211001446933002	0.00105500723466501
96	0.99908324749265	0.00183350501470096	0.000916752507350482
97	0.998765782111929	0.00246843577614265	0.00123421788807133
98	0.998894898351908	0.00221020329618457	0.00110510164809229
99	0.998493478377128	0.00301304324574384	0.00150652162287192
100	0.997878196412379	0.00424360717524245	0.00212180358762122
101	0.997048562720285	0.00590287455942923	0.00295143727971462
102	0.996230005132597	0.00753998973480538	0.00376999486740269
103	0.994837707727104	0.0103245845457924	0.00516229227289619
104	0.99330310190537	0.0133937961892604	0.00669689809463021
105	0.991071732787633	0.0178565344247332	0.00892826721236662
106	0.98858708244389	0.0228258351122204	0.0114129175561102
107	0.999926764188188	0.000146471623623363	7.32358118116814e-05
108	0.999957172539642	8.56549207158309e-05	4.28274603579154e-05
109	0.999941327455116	0.00011734508976705	5.86725448835249e-05
110	0.999947562687314	0.000104874625372882	5.24373126864411e-05
111	0.99995364491588	9.2710168239233e-05	4.63550841196165e-05
112	0.999943483632373	0.000113032735254982	5.65163676274912e-05
113	0.999925653094986	0.000148693810028309	7.43469050141545e-05
114	0.999884752723912	0.000230494552175105	0.000115247276087552
115	0.999904342088258	0.000191315823484487	9.56579117422436e-05
116	0.999852041632849	0.000295916734301115	0.000147958367150557
117	0.999782225701477	0.000435548597045165	0.000217774298522582
118	0.999719876440771	0.000560247118458658	0.000280123559229329
119	0.999810463037283	0.000379073925433577	0.000189536962716789
120	0.999732547990214	0.000534904019571425	0.000267452009785712
121	0.999886123240104	0.000227753519791298	0.000113876759895649
122	0.999940623804105	0.0001187523917901	5.93761958950499e-05
123	0.999909905496763	0.00018018900647466	9.009450323733e-05
124	0.999889568226444	0.00022086354711185	0.000110431773555925
125	0.999910175837403	0.000179648325194706	8.98241625973531e-05
126	0.999877843221862	0.000244313556275187	0.000122156778137594
127	0.999845009736726	0.000309980526548848	0.000154990263274424
128	0.999852568111324	0.000294863777352906	0.000147431888676453
129	0.999780075340538	0.000439849318923818	0.000219924659461909
130	0.999672593848332	0.000654812303336718	0.000327406151668359
131	0.999690048463636	0.000619903072727536	0.000309951536363768
132	0.999540039123167	0.00091992175366604	0.00045996087683302
133	0.999338401953503	0.00132319609299378	0.000661598046496891
134	0.999092367400196	0.00181526519960765	0.000907632599803827
135	0.998860585898844	0.00227882820231212	0.00113941410115606
136	0.99870490604064	0.00259018791871953	0.00129509395935976
137	0.998311533077298	0.00337693384540375	0.00168846692270187
138	0.997715130591728	0.0045697388165433	0.00228486940827165
139	0.997413518582166	0.00517296283566886	0.00258648141783443
140	0.996833897979063	0.00633220404187486	0.00316610202093743
141	0.996554309832344	0.00689138033531123	0.00344569016765561
142	0.995698172258056	0.00860365548388881	0.0043018277419444
143	0.993897673030611	0.0122046539387773	0.00610232696938864
144	0.991599585804565	0.0168008283908706	0.00840041419543529
145	0.988816427200809	0.0223671455983824	0.0111835727991912
146	0.994101134821078	0.0117977303578449	0.00589886517892243
147	0.99303793630083	0.0139241273983393	0.00696206369916965
148	0.998042795751373	0.00391440849725314	0.00195720424862657
149	0.997142090875056	0.00571581824988747	0.00285790912494373
150	0.997691586870961	0.00461682625807849	0.00230841312903925
151	0.996731255095346	0.00653748980930863	0.00326874490465431
152	0.999657706166048	0.000684587667903136	0.000342293833951568
153	0.999590420002826	0.000819159994347366	0.000409579997173683
154	0.999592408303406	0.000815183393187769	0.000407591696593884
155	0.999318093911375	0.00136381217724996	0.000681906088624979
156	0.998860909629422	0.00227818074115567	0.00113909037057783
157	0.998183850458613	0.00363229908277358	0.00181614954138679
158	0.997140504835365	0.00571899032927103	0.00285949516463551
159	0.99562339812423	0.0087532037515406	0.0043766018757703
160	0.993588358596236	0.0128232828075277	0.00641164140376383
161	0.992374297903827	0.0152514041923459	0.00762570209617297
162	0.999912526383441	0.00017494723311745	8.7473616558725e-05
163	0.999852733675217	0.000294532649566308	0.000147266324783154
164	0.999710331060581	0.000579337878838322	0.000289668939419161
165	0.999534191741443	0.000931616517114911	0.000465808258557455
166	0.999611015253139	0.000777969493721601	0.000388984746860801
167	0.999335145172391	0.00132970965521723	0.000664854827608614
168	0.998775314655973	0.00244937068805415	0.00122468534402707
169	0.999273117356276	0.00145376528744772	0.00072688264372386
170	0.998757646910067	0.0024847061798656	0.0012423530899328
171	0.99758714350837	0.00482571298326068	0.00241285649163034
172	0.99540166837836	0.00919666324327919	0.00459833162163959
173	0.991563507571525	0.01687298485695	0.00843649242847499
174	0.993076119950016	0.0138477600999672	0.0069238800499836
175	0.991426777385157	0.0171464452296851	0.00857322261484255
176	0.987359200576402	0.0252815988471949	0.0126407994235975
177	0.990351935265712	0.0192961294685763	0.00964806473428815
178	0.992523198443851	0.0149536031122978	0.00747680155614888
179	0.984350125811953	0.0312997483760943	0.0156498741880471
180	0.967576406594017	0.0648471868119668	0.0324235934059834
181	0.936306131964765	0.127387736070469	0.0636938680352345
182	0.999964681030779	7.06379384419298e-05	3.53189692209649e-05
183	0.999744309892724	0.000511380214551594	0.000255690107275797
184	0.998970281888952	0.0020594362220953	0.00102971811104765
185	0.997523998637113	0.00495200272577468	0.00247600136288734

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
15 & 6.89134429335794e-05 & 0.000137826885867159 & 0.999931086557066 \tabularnewline
16 & 0.000886299562512693 & 0.00177259912502539 & 0.999113700437487 \tabularnewline
17 & 0.00107272263660939 & 0.00214544527321879 & 0.998927277363391 \tabularnewline
18 & 0.547567212677298 & 0.904865574645403 & 0.452432787322702 \tabularnewline
19 & 0.666493846181997 & 0.667012307636007 & 0.333506153818003 \tabularnewline
20 & 0.76826998664384 & 0.463460026712319 & 0.23173001335616 \tabularnewline
21 & 0.71433984055037 & 0.57132031889926 & 0.28566015944963 \tabularnewline
22 & 0.775377219995297 & 0.449245560009406 & 0.224622780004703 \tabularnewline
23 & 0.94762615700593 & 0.104747685988141 & 0.0523738429940704 \tabularnewline
24 & 0.92500194431139 & 0.149996111377219 & 0.0749980556886097 \tabularnewline
25 & 0.893158686479337 & 0.213682627041325 & 0.106841313520663 \tabularnewline
26 & 0.892582245255785 & 0.21483550948843 & 0.107417754744215 \tabularnewline
27 & 0.856721581390832 & 0.286556837218336 & 0.143278418609168 \tabularnewline
28 & 0.821036046043002 & 0.357927907913996 & 0.178963953956998 \tabularnewline
29 & 0.770590508028158 & 0.458818983943684 & 0.229409491971842 \tabularnewline
30 & 0.749192785649841 & 0.501614428700318 & 0.250807214350159 \tabularnewline
31 & 0.691314688495638 & 0.617370623008723 & 0.308685311504361 \tabularnewline
32 & 0.722256052070086 & 0.555487895859827 & 0.277743947929914 \tabularnewline
33 & 0.669045351959821 & 0.661909296080357 & 0.330954648040179 \tabularnewline
34 & 0.616034734273297 & 0.767930531453407 & 0.383965265726703 \tabularnewline
35 & 0.6000948816995 & 0.799810236601 & 0.3999051183005 \tabularnewline
36 & 0.568808853331994 & 0.862382293336011 & 0.431191146668006 \tabularnewline
37 & 0.528701027263604 & 0.942597945472792 & 0.471298972736396 \tabularnewline
38 & 0.565052028807148 & 0.869895942385703 & 0.434947971192852 \tabularnewline
39 & 0.519255900100335 & 0.96148819979933 & 0.480744099899665 \tabularnewline
40 & 0.46648922408989 & 0.932978448179781 & 0.53351077591011 \tabularnewline
41 & 0.415258482506799 & 0.830516965013598 & 0.584741517493201 \tabularnewline
42 & 0.376462033890732 & 0.752924067781464 & 0.623537966109268 \tabularnewline
43 & 0.848986530141191 & 0.302026939717618 & 0.151013469858809 \tabularnewline
44 & 0.903206234267304 & 0.193587531465392 & 0.096793765732696 \tabularnewline
45 & 0.880289944108641 & 0.239420111782719 & 0.119710055891359 \tabularnewline
46 & 0.895404982250123 & 0.209190035499754 & 0.104595017749877 \tabularnewline
47 & 0.885537567246688 & 0.228924865506624 & 0.114462432753312 \tabularnewline
48 & 0.85844855218328 & 0.283102895633441 & 0.14155144781672 \tabularnewline
49 & 0.860417401581652 & 0.279165196836695 & 0.139582598418347 \tabularnewline
50 & 0.843850468155214 & 0.312299063689573 & 0.156149531844786 \tabularnewline
51 & 0.847459018459266 & 0.305081963081469 & 0.152540981540735 \tabularnewline
52 & 0.817308369177079 & 0.365383261645842 & 0.182691630822921 \tabularnewline
53 & 0.783064383162696 & 0.433871233674609 & 0.216935616837304 \tabularnewline
54 & 0.745028676274364 & 0.509942647451271 & 0.254971323725636 \tabularnewline
55 & 0.742517143974693 & 0.514965712050614 & 0.257482856025307 \tabularnewline
56 & 0.709022706895452 & 0.581954586209095 & 0.290977293104548 \tabularnewline
57 & 0.697748987097786 & 0.604502025804428 & 0.302251012902214 \tabularnewline
58 & 0.700851729376335 & 0.598296541247329 & 0.299148270623665 \tabularnewline
59 & 0.658151018881342 & 0.683697962237316 & 0.341848981118658 \tabularnewline
60 & 0.622314079388542 & 0.755371841222917 & 0.377685920611458 \tabularnewline
61 & 0.587213513419918 & 0.825572973160164 & 0.412786486580082 \tabularnewline
62 & 0.563606414299199 & 0.872787171401603 & 0.436393585700801 \tabularnewline
63 & 0.517349623748863 & 0.965300752502274 & 0.482650376251137 \tabularnewline
64 & 0.472901221917702 & 0.945802443835405 & 0.527098778082298 \tabularnewline
65 & 0.434751381884177 & 0.869502763768355 & 0.565248618115823 \tabularnewline
66 & 0.39610739006625 & 0.792214780132501 & 0.60389260993375 \tabularnewline
67 & 0.354846112468669 & 0.709692224937338 & 0.645153887531331 \tabularnewline
68 & 0.34632831786163 & 0.69265663572326 & 0.65367168213837 \tabularnewline
69 & 0.346065246031905 & 0.692130492063809 & 0.653934753968095 \tabularnewline
70 & 0.330488751706147 & 0.660977503412294 & 0.669511248293853 \tabularnewline
71 & 0.296483109945992 & 0.592966219891984 & 0.703516890054008 \tabularnewline
72 & 0.266494924043883 & 0.532989848087765 & 0.733505075956117 \tabularnewline
73 & 0.232320224102976 & 0.464640448205952 & 0.767679775897024 \tabularnewline
74 & 0.201750734544727 & 0.403501469089454 & 0.798249265455273 \tabularnewline
75 & 0.171666596205113 & 0.343333192410225 & 0.828333403794887 \tabularnewline
76 & 0.151621190821177 & 0.303242381642353 & 0.848378809178823 \tabularnewline
77 & 0.130611597593748 & 0.261223195187496 & 0.869388402406252 \tabularnewline
78 & 0.110265854802046 & 0.220531709604092 & 0.889734145197954 \tabularnewline
79 & 0.0906693770296457 & 0.181338754059291 & 0.909330622970354 \tabularnewline
80 & 0.102139103090709 & 0.204278206181418 & 0.897860896909291 \tabularnewline
81 & 0.0892711827806702 & 0.17854236556134 & 0.91072881721933 \tabularnewline
82 & 0.579885446176531 & 0.840229107646937 & 0.420114553823469 \tabularnewline
83 & 0.567704200687047 & 0.864591598625907 & 0.432295799312953 \tabularnewline
84 & 0.909777385432416 & 0.180445229135169 & 0.0902226145675843 \tabularnewline
85 & 0.933333557308695 & 0.13333288538261 & 0.066666442691305 \tabularnewline
86 & 0.924119788609638 & 0.151760422780724 & 0.0758802113903621 \tabularnewline
87 & 0.96629279555575 & 0.0674144088885004 & 0.0337072044442502 \tabularnewline
88 & 0.958815719092929 & 0.0823685618141427 & 0.0411842809070713 \tabularnewline
89 & 0.955009756056187 & 0.0899804878876255 & 0.0449902439438128 \tabularnewline
90 & 0.944148869704526 & 0.111702260590948 & 0.0558511302954742 \tabularnewline
91 & 0.935585343305057 & 0.128829313389887 & 0.0644146566949434 \tabularnewline
92 & 0.974769040135982 & 0.0504619197280354 & 0.0252309598640177 \tabularnewline
93 & 0.999257426267195 & 0.00148514746560934 & 0.000742573732804669 \tabularnewline
94 & 0.998995046394312 & 0.00200990721137665 & 0.00100495360568832 \tabularnewline
95 & 0.998944992765335 & 0.00211001446933002 & 0.00105500723466501 \tabularnewline
96 & 0.99908324749265 & 0.00183350501470096 & 0.000916752507350482 \tabularnewline
97 & 0.998765782111929 & 0.00246843577614265 & 0.00123421788807133 \tabularnewline
98 & 0.998894898351908 & 0.00221020329618457 & 0.00110510164809229 \tabularnewline
99 & 0.998493478377128 & 0.00301304324574384 & 0.00150652162287192 \tabularnewline
100 & 0.997878196412379 & 0.00424360717524245 & 0.00212180358762122 \tabularnewline
101 & 0.997048562720285 & 0.00590287455942923 & 0.00295143727971462 \tabularnewline
102 & 0.996230005132597 & 0.00753998973480538 & 0.00376999486740269 \tabularnewline
103 & 0.994837707727104 & 0.0103245845457924 & 0.00516229227289619 \tabularnewline
104 & 0.99330310190537 & 0.0133937961892604 & 0.00669689809463021 \tabularnewline
105 & 0.991071732787633 & 0.0178565344247332 & 0.00892826721236662 \tabularnewline
106 & 0.98858708244389 & 0.0228258351122204 & 0.0114129175561102 \tabularnewline
107 & 0.999926764188188 & 0.000146471623623363 & 7.32358118116814e-05 \tabularnewline
108 & 0.999957172539642 & 8.56549207158309e-05 & 4.28274603579154e-05 \tabularnewline
109 & 0.999941327455116 & 0.00011734508976705 & 5.86725448835249e-05 \tabularnewline
110 & 0.999947562687314 & 0.000104874625372882 & 5.24373126864411e-05 \tabularnewline
111 & 0.99995364491588 & 9.2710168239233e-05 & 4.63550841196165e-05 \tabularnewline
112 & 0.999943483632373 & 0.000113032735254982 & 5.65163676274912e-05 \tabularnewline
113 & 0.999925653094986 & 0.000148693810028309 & 7.43469050141545e-05 \tabularnewline
114 & 0.999884752723912 & 0.000230494552175105 & 0.000115247276087552 \tabularnewline
115 & 0.999904342088258 & 0.000191315823484487 & 9.56579117422436e-05 \tabularnewline
116 & 0.999852041632849 & 0.000295916734301115 & 0.000147958367150557 \tabularnewline
117 & 0.999782225701477 & 0.000435548597045165 & 0.000217774298522582 \tabularnewline
118 & 0.999719876440771 & 0.000560247118458658 & 0.000280123559229329 \tabularnewline
119 & 0.999810463037283 & 0.000379073925433577 & 0.000189536962716789 \tabularnewline
120 & 0.999732547990214 & 0.000534904019571425 & 0.000267452009785712 \tabularnewline
121 & 0.999886123240104 & 0.000227753519791298 & 0.000113876759895649 \tabularnewline
122 & 0.999940623804105 & 0.0001187523917901 & 5.93761958950499e-05 \tabularnewline
123 & 0.999909905496763 & 0.00018018900647466 & 9.009450323733e-05 \tabularnewline
124 & 0.999889568226444 & 0.00022086354711185 & 0.000110431773555925 \tabularnewline
125 & 0.999910175837403 & 0.000179648325194706 & 8.98241625973531e-05 \tabularnewline
126 & 0.999877843221862 & 0.000244313556275187 & 0.000122156778137594 \tabularnewline
127 & 0.999845009736726 & 0.000309980526548848 & 0.000154990263274424 \tabularnewline
128 & 0.999852568111324 & 0.000294863777352906 & 0.000147431888676453 \tabularnewline
129 & 0.999780075340538 & 0.000439849318923818 & 0.000219924659461909 \tabularnewline
130 & 0.999672593848332 & 0.000654812303336718 & 0.000327406151668359 \tabularnewline
131 & 0.999690048463636 & 0.000619903072727536 & 0.000309951536363768 \tabularnewline
132 & 0.999540039123167 & 0.00091992175366604 & 0.00045996087683302 \tabularnewline
133 & 0.999338401953503 & 0.00132319609299378 & 0.000661598046496891 \tabularnewline
134 & 0.999092367400196 & 0.00181526519960765 & 0.000907632599803827 \tabularnewline
135 & 0.998860585898844 & 0.00227882820231212 & 0.00113941410115606 \tabularnewline
136 & 0.99870490604064 & 0.00259018791871953 & 0.00129509395935976 \tabularnewline
137 & 0.998311533077298 & 0.00337693384540375 & 0.00168846692270187 \tabularnewline
138 & 0.997715130591728 & 0.0045697388165433 & 0.00228486940827165 \tabularnewline
139 & 0.997413518582166 & 0.00517296283566886 & 0.00258648141783443 \tabularnewline
140 & 0.996833897979063 & 0.00633220404187486 & 0.00316610202093743 \tabularnewline
141 & 0.996554309832344 & 0.00689138033531123 & 0.00344569016765561 \tabularnewline
142 & 0.995698172258056 & 0.00860365548388881 & 0.0043018277419444 \tabularnewline
143 & 0.993897673030611 & 0.0122046539387773 & 0.00610232696938864 \tabularnewline
144 & 0.991599585804565 & 0.0168008283908706 & 0.00840041419543529 \tabularnewline
145 & 0.988816427200809 & 0.0223671455983824 & 0.0111835727991912 \tabularnewline
146 & 0.994101134821078 & 0.0117977303578449 & 0.00589886517892243 \tabularnewline
147 & 0.99303793630083 & 0.0139241273983393 & 0.00696206369916965 \tabularnewline
148 & 0.998042795751373 & 0.00391440849725314 & 0.00195720424862657 \tabularnewline
149 & 0.997142090875056 & 0.00571581824988747 & 0.00285790912494373 \tabularnewline
150 & 0.997691586870961 & 0.00461682625807849 & 0.00230841312903925 \tabularnewline
151 & 0.996731255095346 & 0.00653748980930863 & 0.00326874490465431 \tabularnewline
152 & 0.999657706166048 & 0.000684587667903136 & 0.000342293833951568 \tabularnewline
153 & 0.999590420002826 & 0.000819159994347366 & 0.000409579997173683 \tabularnewline
154 & 0.999592408303406 & 0.000815183393187769 & 0.000407591696593884 \tabularnewline
155 & 0.999318093911375 & 0.00136381217724996 & 0.000681906088624979 \tabularnewline
156 & 0.998860909629422 & 0.00227818074115567 & 0.00113909037057783 \tabularnewline
157 & 0.998183850458613 & 0.00363229908277358 & 0.00181614954138679 \tabularnewline
158 & 0.997140504835365 & 0.00571899032927103 & 0.00285949516463551 \tabularnewline
159 & 0.99562339812423 & 0.0087532037515406 & 0.0043766018757703 \tabularnewline
160 & 0.993588358596236 & 0.0128232828075277 & 0.00641164140376383 \tabularnewline
161 & 0.992374297903827 & 0.0152514041923459 & 0.00762570209617297 \tabularnewline
162 & 0.999912526383441 & 0.00017494723311745 & 8.7473616558725e-05 \tabularnewline
163 & 0.999852733675217 & 0.000294532649566308 & 0.000147266324783154 \tabularnewline
164 & 0.999710331060581 & 0.000579337878838322 & 0.000289668939419161 \tabularnewline
165 & 0.999534191741443 & 0.000931616517114911 & 0.000465808258557455 \tabularnewline
166 & 0.999611015253139 & 0.000777969493721601 & 0.000388984746860801 \tabularnewline
167 & 0.999335145172391 & 0.00132970965521723 & 0.000664854827608614 \tabularnewline
168 & 0.998775314655973 & 0.00244937068805415 & 0.00122468534402707 \tabularnewline
169 & 0.999273117356276 & 0.00145376528744772 & 0.00072688264372386 \tabularnewline
170 & 0.998757646910067 & 0.0024847061798656 & 0.0012423530899328 \tabularnewline
171 & 0.99758714350837 & 0.00482571298326068 & 0.00241285649163034 \tabularnewline
172 & 0.99540166837836 & 0.00919666324327919 & 0.00459833162163959 \tabularnewline
173 & 0.991563507571525 & 0.01687298485695 & 0.00843649242847499 \tabularnewline
174 & 0.993076119950016 & 0.0138477600999672 & 0.0069238800499836 \tabularnewline
175 & 0.991426777385157 & 0.0171464452296851 & 0.00857322261484255 \tabularnewline
176 & 0.987359200576402 & 0.0252815988471949 & 0.0126407994235975 \tabularnewline
177 & 0.990351935265712 & 0.0192961294685763 & 0.00964806473428815 \tabularnewline
178 & 0.992523198443851 & 0.0149536031122978 & 0.00747680155614888 \tabularnewline
179 & 0.984350125811953 & 0.0312997483760943 & 0.0156498741880471 \tabularnewline
180 & 0.967576406594017 & 0.0648471868119668 & 0.0324235934059834 \tabularnewline
181 & 0.936306131964765 & 0.127387736070469 & 0.0636938680352345 \tabularnewline
182 & 0.999964681030779 & 7.06379384419298e-05 & 3.53189692209649e-05 \tabularnewline
183 & 0.999744309892724 & 0.000511380214551594 & 0.000255690107275797 \tabularnewline
184 & 0.998970281888952 & 0.0020594362220953 & 0.00102971811104765 \tabularnewline
185 & 0.997523998637113 & 0.00495200272577468 & 0.00247600136288734 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154396&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]6.89134429335794e-05[/C][C]0.000137826885867159[/C][C]0.999931086557066[/C][/ROW]
[ROW][C]16[/C][C]0.000886299562512693[/C][C]0.00177259912502539[/C][C]0.999113700437487[/C][/ROW]
[ROW][C]17[/C][C]0.00107272263660939[/C][C]0.00214544527321879[/C][C]0.998927277363391[/C][/ROW]
[ROW][C]18[/C][C]0.547567212677298[/C][C]0.904865574645403[/C][C]0.452432787322702[/C][/ROW]
[ROW][C]19[/C][C]0.666493846181997[/C][C]0.667012307636007[/C][C]0.333506153818003[/C][/ROW]
[ROW][C]20[/C][C]0.76826998664384[/C][C]0.463460026712319[/C][C]0.23173001335616[/C][/ROW]
[ROW][C]21[/C][C]0.71433984055037[/C][C]0.57132031889926[/C][C]0.28566015944963[/C][/ROW]
[ROW][C]22[/C][C]0.775377219995297[/C][C]0.449245560009406[/C][C]0.224622780004703[/C][/ROW]
[ROW][C]23[/C][C]0.94762615700593[/C][C]0.104747685988141[/C][C]0.0523738429940704[/C][/ROW]
[ROW][C]24[/C][C]0.92500194431139[/C][C]0.149996111377219[/C][C]0.0749980556886097[/C][/ROW]
[ROW][C]25[/C][C]0.893158686479337[/C][C]0.213682627041325[/C][C]0.106841313520663[/C][/ROW]
[ROW][C]26[/C][C]0.892582245255785[/C][C]0.21483550948843[/C][C]0.107417754744215[/C][/ROW]
[ROW][C]27[/C][C]0.856721581390832[/C][C]0.286556837218336[/C][C]0.143278418609168[/C][/ROW]
[ROW][C]28[/C][C]0.821036046043002[/C][C]0.357927907913996[/C][C]0.178963953956998[/C][/ROW]
[ROW][C]29[/C][C]0.770590508028158[/C][C]0.458818983943684[/C][C]0.229409491971842[/C][/ROW]
[ROW][C]30[/C][C]0.749192785649841[/C][C]0.501614428700318[/C][C]0.250807214350159[/C][/ROW]
[ROW][C]31[/C][C]0.691314688495638[/C][C]0.617370623008723[/C][C]0.308685311504361[/C][/ROW]
[ROW][C]32[/C][C]0.722256052070086[/C][C]0.555487895859827[/C][C]0.277743947929914[/C][/ROW]
[ROW][C]33[/C][C]0.669045351959821[/C][C]0.661909296080357[/C][C]0.330954648040179[/C][/ROW]
[ROW][C]34[/C][C]0.616034734273297[/C][C]0.767930531453407[/C][C]0.383965265726703[/C][/ROW]
[ROW][C]35[/C][C]0.6000948816995[/C][C]0.799810236601[/C][C]0.3999051183005[/C][/ROW]
[ROW][C]36[/C][C]0.568808853331994[/C][C]0.862382293336011[/C][C]0.431191146668006[/C][/ROW]
[ROW][C]37[/C][C]0.528701027263604[/C][C]0.942597945472792[/C][C]0.471298972736396[/C][/ROW]
[ROW][C]38[/C][C]0.565052028807148[/C][C]0.869895942385703[/C][C]0.434947971192852[/C][/ROW]
[ROW][C]39[/C][C]0.519255900100335[/C][C]0.96148819979933[/C][C]0.480744099899665[/C][/ROW]
[ROW][C]40[/C][C]0.46648922408989[/C][C]0.932978448179781[/C][C]0.53351077591011[/C][/ROW]
[ROW][C]41[/C][C]0.415258482506799[/C][C]0.830516965013598[/C][C]0.584741517493201[/C][/ROW]
[ROW][C]42[/C][C]0.376462033890732[/C][C]0.752924067781464[/C][C]0.623537966109268[/C][/ROW]
[ROW][C]43[/C][C]0.848986530141191[/C][C]0.302026939717618[/C][C]0.151013469858809[/C][/ROW]
[ROW][C]44[/C][C]0.903206234267304[/C][C]0.193587531465392[/C][C]0.096793765732696[/C][/ROW]
[ROW][C]45[/C][C]0.880289944108641[/C][C]0.239420111782719[/C][C]0.119710055891359[/C][/ROW]
[ROW][C]46[/C][C]0.895404982250123[/C][C]0.209190035499754[/C][C]0.104595017749877[/C][/ROW]
[ROW][C]47[/C][C]0.885537567246688[/C][C]0.228924865506624[/C][C]0.114462432753312[/C][/ROW]
[ROW][C]48[/C][C]0.85844855218328[/C][C]0.283102895633441[/C][C]0.14155144781672[/C][/ROW]
[ROW][C]49[/C][C]0.860417401581652[/C][C]0.279165196836695[/C][C]0.139582598418347[/C][/ROW]
[ROW][C]50[/C][C]0.843850468155214[/C][C]0.312299063689573[/C][C]0.156149531844786[/C][/ROW]
[ROW][C]51[/C][C]0.847459018459266[/C][C]0.305081963081469[/C][C]0.152540981540735[/C][/ROW]
[ROW][C]52[/C][C]0.817308369177079[/C][C]0.365383261645842[/C][C]0.182691630822921[/C][/ROW]
[ROW][C]53[/C][C]0.783064383162696[/C][C]0.433871233674609[/C][C]0.216935616837304[/C][/ROW]
[ROW][C]54[/C][C]0.745028676274364[/C][C]0.509942647451271[/C][C]0.254971323725636[/C][/ROW]
[ROW][C]55[/C][C]0.742517143974693[/C][C]0.514965712050614[/C][C]0.257482856025307[/C][/ROW]
[ROW][C]56[/C][C]0.709022706895452[/C][C]0.581954586209095[/C][C]0.290977293104548[/C][/ROW]
[ROW][C]57[/C][C]0.697748987097786[/C][C]0.604502025804428[/C][C]0.302251012902214[/C][/ROW]
[ROW][C]58[/C][C]0.700851729376335[/C][C]0.598296541247329[/C][C]0.299148270623665[/C][/ROW]
[ROW][C]59[/C][C]0.658151018881342[/C][C]0.683697962237316[/C][C]0.341848981118658[/C][/ROW]
[ROW][C]60[/C][C]0.622314079388542[/C][C]0.755371841222917[/C][C]0.377685920611458[/C][/ROW]
[ROW][C]61[/C][C]0.587213513419918[/C][C]0.825572973160164[/C][C]0.412786486580082[/C][/ROW]
[ROW][C]62[/C][C]0.563606414299199[/C][C]0.872787171401603[/C][C]0.436393585700801[/C][/ROW]
[ROW][C]63[/C][C]0.517349623748863[/C][C]0.965300752502274[/C][C]0.482650376251137[/C][/ROW]
[ROW][C]64[/C][C]0.472901221917702[/C][C]0.945802443835405[/C][C]0.527098778082298[/C][/ROW]
[ROW][C]65[/C][C]0.434751381884177[/C][C]0.869502763768355[/C][C]0.565248618115823[/C][/ROW]
[ROW][C]66[/C][C]0.39610739006625[/C][C]0.792214780132501[/C][C]0.60389260993375[/C][/ROW]
[ROW][C]67[/C][C]0.354846112468669[/C][C]0.709692224937338[/C][C]0.645153887531331[/C][/ROW]
[ROW][C]68[/C][C]0.34632831786163[/C][C]0.69265663572326[/C][C]0.65367168213837[/C][/ROW]
[ROW][C]69[/C][C]0.346065246031905[/C][C]0.692130492063809[/C][C]0.653934753968095[/C][/ROW]
[ROW][C]70[/C][C]0.330488751706147[/C][C]0.660977503412294[/C][C]0.669511248293853[/C][/ROW]
[ROW][C]71[/C][C]0.296483109945992[/C][C]0.592966219891984[/C][C]0.703516890054008[/C][/ROW]
[ROW][C]72[/C][C]0.266494924043883[/C][C]0.532989848087765[/C][C]0.733505075956117[/C][/ROW]
[ROW][C]73[/C][C]0.232320224102976[/C][C]0.464640448205952[/C][C]0.767679775897024[/C][/ROW]
[ROW][C]74[/C][C]0.201750734544727[/C][C]0.403501469089454[/C][C]0.798249265455273[/C][/ROW]
[ROW][C]75[/C][C]0.171666596205113[/C][C]0.343333192410225[/C][C]0.828333403794887[/C][/ROW]
[ROW][C]76[/C][C]0.151621190821177[/C][C]0.303242381642353[/C][C]0.848378809178823[/C][/ROW]
[ROW][C]77[/C][C]0.130611597593748[/C][C]0.261223195187496[/C][C]0.869388402406252[/C][/ROW]
[ROW][C]78[/C][C]0.110265854802046[/C][C]0.220531709604092[/C][C]0.889734145197954[/C][/ROW]
[ROW][C]79[/C][C]0.0906693770296457[/C][C]0.181338754059291[/C][C]0.909330622970354[/C][/ROW]
[ROW][C]80[/C][C]0.102139103090709[/C][C]0.204278206181418[/C][C]0.897860896909291[/C][/ROW]
[ROW][C]81[/C][C]0.0892711827806702[/C][C]0.17854236556134[/C][C]0.91072881721933[/C][/ROW]
[ROW][C]82[/C][C]0.579885446176531[/C][C]0.840229107646937[/C][C]0.420114553823469[/C][/ROW]
[ROW][C]83[/C][C]0.567704200687047[/C][C]0.864591598625907[/C][C]0.432295799312953[/C][/ROW]
[ROW][C]84[/C][C]0.909777385432416[/C][C]0.180445229135169[/C][C]0.0902226145675843[/C][/ROW]
[ROW][C]85[/C][C]0.933333557308695[/C][C]0.13333288538261[/C][C]0.066666442691305[/C][/ROW]
[ROW][C]86[/C][C]0.924119788609638[/C][C]0.151760422780724[/C][C]0.0758802113903621[/C][/ROW]
[ROW][C]87[/C][C]0.96629279555575[/C][C]0.0674144088885004[/C][C]0.0337072044442502[/C][/ROW]
[ROW][C]88[/C][C]0.958815719092929[/C][C]0.0823685618141427[/C][C]0.0411842809070713[/C][/ROW]
[ROW][C]89[/C][C]0.955009756056187[/C][C]0.0899804878876255[/C][C]0.0449902439438128[/C][/ROW]
[ROW][C]90[/C][C]0.944148869704526[/C][C]0.111702260590948[/C][C]0.0558511302954742[/C][/ROW]
[ROW][C]91[/C][C]0.935585343305057[/C][C]0.128829313389887[/C][C]0.0644146566949434[/C][/ROW]
[ROW][C]92[/C][C]0.974769040135982[/C][C]0.0504619197280354[/C][C]0.0252309598640177[/C][/ROW]
[ROW][C]93[/C][C]0.999257426267195[/C][C]0.00148514746560934[/C][C]0.000742573732804669[/C][/ROW]
[ROW][C]94[/C][C]0.998995046394312[/C][C]0.00200990721137665[/C][C]0.00100495360568832[/C][/ROW]
[ROW][C]95[/C][C]0.998944992765335[/C][C]0.00211001446933002[/C][C]0.00105500723466501[/C][/ROW]
[ROW][C]96[/C][C]0.99908324749265[/C][C]0.00183350501470096[/C][C]0.000916752507350482[/C][/ROW]
[ROW][C]97[/C][C]0.998765782111929[/C][C]0.00246843577614265[/C][C]0.00123421788807133[/C][/ROW]
[ROW][C]98[/C][C]0.998894898351908[/C][C]0.00221020329618457[/C][C]0.00110510164809229[/C][/ROW]
[ROW][C]99[/C][C]0.998493478377128[/C][C]0.00301304324574384[/C][C]0.00150652162287192[/C][/ROW]
[ROW][C]100[/C][C]0.997878196412379[/C][C]0.00424360717524245[/C][C]0.00212180358762122[/C][/ROW]
[ROW][C]101[/C][C]0.997048562720285[/C][C]0.00590287455942923[/C][C]0.00295143727971462[/C][/ROW]
[ROW][C]102[/C][C]0.996230005132597[/C][C]0.00753998973480538[/C][C]0.00376999486740269[/C][/ROW]
[ROW][C]103[/C][C]0.994837707727104[/C][C]0.0103245845457924[/C][C]0.00516229227289619[/C][/ROW]
[ROW][C]104[/C][C]0.99330310190537[/C][C]0.0133937961892604[/C][C]0.00669689809463021[/C][/ROW]
[ROW][C]105[/C][C]0.991071732787633[/C][C]0.0178565344247332[/C][C]0.00892826721236662[/C][/ROW]
[ROW][C]106[/C][C]0.98858708244389[/C][C]0.0228258351122204[/C][C]0.0114129175561102[/C][/ROW]
[ROW][C]107[/C][C]0.999926764188188[/C][C]0.000146471623623363[/C][C]7.32358118116814e-05[/C][/ROW]
[ROW][C]108[/C][C]0.999957172539642[/C][C]8.56549207158309e-05[/C][C]4.28274603579154e-05[/C][/ROW]
[ROW][C]109[/C][C]0.999941327455116[/C][C]0.00011734508976705[/C][C]5.86725448835249e-05[/C][/ROW]
[ROW][C]110[/C][C]0.999947562687314[/C][C]0.000104874625372882[/C][C]5.24373126864411e-05[/C][/ROW]
[ROW][C]111[/C][C]0.99995364491588[/C][C]9.2710168239233e-05[/C][C]4.63550841196165e-05[/C][/ROW]
[ROW][C]112[/C][C]0.999943483632373[/C][C]0.000113032735254982[/C][C]5.65163676274912e-05[/C][/ROW]
[ROW][C]113[/C][C]0.999925653094986[/C][C]0.000148693810028309[/C][C]7.43469050141545e-05[/C][/ROW]
[ROW][C]114[/C][C]0.999884752723912[/C][C]0.000230494552175105[/C][C]0.000115247276087552[/C][/ROW]
[ROW][C]115[/C][C]0.999904342088258[/C][C]0.000191315823484487[/C][C]9.56579117422436e-05[/C][/ROW]
[ROW][C]116[/C][C]0.999852041632849[/C][C]0.000295916734301115[/C][C]0.000147958367150557[/C][/ROW]
[ROW][C]117[/C][C]0.999782225701477[/C][C]0.000435548597045165[/C][C]0.000217774298522582[/C][/ROW]
[ROW][C]118[/C][C]0.999719876440771[/C][C]0.000560247118458658[/C][C]0.000280123559229329[/C][/ROW]
[ROW][C]119[/C][C]0.999810463037283[/C][C]0.000379073925433577[/C][C]0.000189536962716789[/C][/ROW]
[ROW][C]120[/C][C]0.999732547990214[/C][C]0.000534904019571425[/C][C]0.000267452009785712[/C][/ROW]
[ROW][C]121[/C][C]0.999886123240104[/C][C]0.000227753519791298[/C][C]0.000113876759895649[/C][/ROW]
[ROW][C]122[/C][C]0.999940623804105[/C][C]0.0001187523917901[/C][C]5.93761958950499e-05[/C][/ROW]
[ROW][C]123[/C][C]0.999909905496763[/C][C]0.00018018900647466[/C][C]9.009450323733e-05[/C][/ROW]
[ROW][C]124[/C][C]0.999889568226444[/C][C]0.00022086354711185[/C][C]0.000110431773555925[/C][/ROW]
[ROW][C]125[/C][C]0.999910175837403[/C][C]0.000179648325194706[/C][C]8.98241625973531e-05[/C][/ROW]
[ROW][C]126[/C][C]0.999877843221862[/C][C]0.000244313556275187[/C][C]0.000122156778137594[/C][/ROW]
[ROW][C]127[/C][C]0.999845009736726[/C][C]0.000309980526548848[/C][C]0.000154990263274424[/C][/ROW]
[ROW][C]128[/C][C]0.999852568111324[/C][C]0.000294863777352906[/C][C]0.000147431888676453[/C][/ROW]
[ROW][C]129[/C][C]0.999780075340538[/C][C]0.000439849318923818[/C][C]0.000219924659461909[/C][/ROW]
[ROW][C]130[/C][C]0.999672593848332[/C][C]0.000654812303336718[/C][C]0.000327406151668359[/C][/ROW]
[ROW][C]131[/C][C]0.999690048463636[/C][C]0.000619903072727536[/C][C]0.000309951536363768[/C][/ROW]
[ROW][C]132[/C][C]0.999540039123167[/C][C]0.00091992175366604[/C][C]0.00045996087683302[/C][/ROW]
[ROW][C]133[/C][C]0.999338401953503[/C][C]0.00132319609299378[/C][C]0.000661598046496891[/C][/ROW]
[ROW][C]134[/C][C]0.999092367400196[/C][C]0.00181526519960765[/C][C]0.000907632599803827[/C][/ROW]
[ROW][C]135[/C][C]0.998860585898844[/C][C]0.00227882820231212[/C][C]0.00113941410115606[/C][/ROW]
[ROW][C]136[/C][C]0.99870490604064[/C][C]0.00259018791871953[/C][C]0.00129509395935976[/C][/ROW]
[ROW][C]137[/C][C]0.998311533077298[/C][C]0.00337693384540375[/C][C]0.00168846692270187[/C][/ROW]
[ROW][C]138[/C][C]0.997715130591728[/C][C]0.0045697388165433[/C][C]0.00228486940827165[/C][/ROW]
[ROW][C]139[/C][C]0.997413518582166[/C][C]0.00517296283566886[/C][C]0.00258648141783443[/C][/ROW]
[ROW][C]140[/C][C]0.996833897979063[/C][C]0.00633220404187486[/C][C]0.00316610202093743[/C][/ROW]
[ROW][C]141[/C][C]0.996554309832344[/C][C]0.00689138033531123[/C][C]0.00344569016765561[/C][/ROW]
[ROW][C]142[/C][C]0.995698172258056[/C][C]0.00860365548388881[/C][C]0.0043018277419444[/C][/ROW]
[ROW][C]143[/C][C]0.993897673030611[/C][C]0.0122046539387773[/C][C]0.00610232696938864[/C][/ROW]
[ROW][C]144[/C][C]0.991599585804565[/C][C]0.0168008283908706[/C][C]0.00840041419543529[/C][/ROW]
[ROW][C]145[/C][C]0.988816427200809[/C][C]0.0223671455983824[/C][C]0.0111835727991912[/C][/ROW]
[ROW][C]146[/C][C]0.994101134821078[/C][C]0.0117977303578449[/C][C]0.00589886517892243[/C][/ROW]
[ROW][C]147[/C][C]0.99303793630083[/C][C]0.0139241273983393[/C][C]0.00696206369916965[/C][/ROW]
[ROW][C]148[/C][C]0.998042795751373[/C][C]0.00391440849725314[/C][C]0.00195720424862657[/C][/ROW]
[ROW][C]149[/C][C]0.997142090875056[/C][C]0.00571581824988747[/C][C]0.00285790912494373[/C][/ROW]
[ROW][C]150[/C][C]0.997691586870961[/C][C]0.00461682625807849[/C][C]0.00230841312903925[/C][/ROW]
[ROW][C]151[/C][C]0.996731255095346[/C][C]0.00653748980930863[/C][C]0.00326874490465431[/C][/ROW]
[ROW][C]152[/C][C]0.999657706166048[/C][C]0.000684587667903136[/C][C]0.000342293833951568[/C][/ROW]
[ROW][C]153[/C][C]0.999590420002826[/C][C]0.000819159994347366[/C][C]0.000409579997173683[/C][/ROW]
[ROW][C]154[/C][C]0.999592408303406[/C][C]0.000815183393187769[/C][C]0.000407591696593884[/C][/ROW]
[ROW][C]155[/C][C]0.999318093911375[/C][C]0.00136381217724996[/C][C]0.000681906088624979[/C][/ROW]
[ROW][C]156[/C][C]0.998860909629422[/C][C]0.00227818074115567[/C][C]0.00113909037057783[/C][/ROW]
[ROW][C]157[/C][C]0.998183850458613[/C][C]0.00363229908277358[/C][C]0.00181614954138679[/C][/ROW]
[ROW][C]158[/C][C]0.997140504835365[/C][C]0.00571899032927103[/C][C]0.00285949516463551[/C][/ROW]
[ROW][C]159[/C][C]0.99562339812423[/C][C]0.0087532037515406[/C][C]0.0043766018757703[/C][/ROW]
[ROW][C]160[/C][C]0.993588358596236[/C][C]0.0128232828075277[/C][C]0.00641164140376383[/C][/ROW]
[ROW][C]161[/C][C]0.992374297903827[/C][C]0.0152514041923459[/C][C]0.00762570209617297[/C][/ROW]
[ROW][C]162[/C][C]0.999912526383441[/C][C]0.00017494723311745[/C][C]8.7473616558725e-05[/C][/ROW]
[ROW][C]163[/C][C]0.999852733675217[/C][C]0.000294532649566308[/C][C]0.000147266324783154[/C][/ROW]
[ROW][C]164[/C][C]0.999710331060581[/C][C]0.000579337878838322[/C][C]0.000289668939419161[/C][/ROW]
[ROW][C]165[/C][C]0.999534191741443[/C][C]0.000931616517114911[/C][C]0.000465808258557455[/C][/ROW]
[ROW][C]166[/C][C]0.999611015253139[/C][C]0.000777969493721601[/C][C]0.000388984746860801[/C][/ROW]
[ROW][C]167[/C][C]0.999335145172391[/C][C]0.00132970965521723[/C][C]0.000664854827608614[/C][/ROW]
[ROW][C]168[/C][C]0.998775314655973[/C][C]0.00244937068805415[/C][C]0.00122468534402707[/C][/ROW]
[ROW][C]169[/C][C]0.999273117356276[/C][C]0.00145376528744772[/C][C]0.00072688264372386[/C][/ROW]
[ROW][C]170[/C][C]0.998757646910067[/C][C]0.0024847061798656[/C][C]0.0012423530899328[/C][/ROW]
[ROW][C]171[/C][C]0.99758714350837[/C][C]0.00482571298326068[/C][C]0.00241285649163034[/C][/ROW]
[ROW][C]172[/C][C]0.99540166837836[/C][C]0.00919666324327919[/C][C]0.00459833162163959[/C][/ROW]
[ROW][C]173[/C][C]0.991563507571525[/C][C]0.01687298485695[/C][C]0.00843649242847499[/C][/ROW]
[ROW][C]174[/C][C]0.993076119950016[/C][C]0.0138477600999672[/C][C]0.0069238800499836[/C][/ROW]
[ROW][C]175[/C][C]0.991426777385157[/C][C]0.0171464452296851[/C][C]0.00857322261484255[/C][/ROW]
[ROW][C]176[/C][C]0.987359200576402[/C][C]0.0252815988471949[/C][C]0.0126407994235975[/C][/ROW]
[ROW][C]177[/C][C]0.990351935265712[/C][C]0.0192961294685763[/C][C]0.00964806473428815[/C][/ROW]
[ROW][C]178[/C][C]0.992523198443851[/C][C]0.0149536031122978[/C][C]0.00747680155614888[/C][/ROW]
[ROW][C]179[/C][C]0.984350125811953[/C][C]0.0312997483760943[/C][C]0.0156498741880471[/C][/ROW]
[ROW][C]180[/C][C]0.967576406594017[/C][C]0.0648471868119668[/C][C]0.0324235934059834[/C][/ROW]
[ROW][C]181[/C][C]0.936306131964765[/C][C]0.127387736070469[/C][C]0.0636938680352345[/C][/ROW]
[ROW][C]182[/C][C]0.999964681030779[/C][C]7.06379384419298e-05[/C][C]3.53189692209649e-05[/C][/ROW]
[ROW][C]183[/C][C]0.999744309892724[/C][C]0.000511380214551594[/C][C]0.000255690107275797[/C][/ROW]
[ROW][C]184[/C][C]0.998970281888952[/C][C]0.0020594362220953[/C][C]0.00102971811104765[/C][/ROW]
[ROW][C]185[/C][C]0.997523998637113[/C][C]0.00495200272577468[/C][C]0.00247600136288734[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154396&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154396&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	6.89134429335794e-05	0.000137826885867159	0.999931086557066
16	0.000886299562512693	0.00177259912502539	0.999113700437487
17	0.00107272263660939	0.00214544527321879	0.998927277363391
18	0.547567212677298	0.904865574645403	0.452432787322702
19	0.666493846181997	0.667012307636007	0.333506153818003
20	0.76826998664384	0.463460026712319	0.23173001335616
21	0.71433984055037	0.57132031889926	0.28566015944963
22	0.775377219995297	0.449245560009406	0.224622780004703
23	0.94762615700593	0.104747685988141	0.0523738429940704
24	0.92500194431139	0.149996111377219	0.0749980556886097
25	0.893158686479337	0.213682627041325	0.106841313520663
26	0.892582245255785	0.21483550948843	0.107417754744215
27	0.856721581390832	0.286556837218336	0.143278418609168
28	0.821036046043002	0.357927907913996	0.178963953956998
29	0.770590508028158	0.458818983943684	0.229409491971842
30	0.749192785649841	0.501614428700318	0.250807214350159
31	0.691314688495638	0.617370623008723	0.308685311504361
32	0.722256052070086	0.555487895859827	0.277743947929914
33	0.669045351959821	0.661909296080357	0.330954648040179
34	0.616034734273297	0.767930531453407	0.383965265726703
35	0.6000948816995	0.799810236601	0.3999051183005
36	0.568808853331994	0.862382293336011	0.431191146668006
37	0.528701027263604	0.942597945472792	0.471298972736396
38	0.565052028807148	0.869895942385703	0.434947971192852
39	0.519255900100335	0.96148819979933	0.480744099899665
40	0.46648922408989	0.932978448179781	0.53351077591011
41	0.415258482506799	0.830516965013598	0.584741517493201
42	0.376462033890732	0.752924067781464	0.623537966109268
43	0.848986530141191	0.302026939717618	0.151013469858809
44	0.903206234267304	0.193587531465392	0.096793765732696
45	0.880289944108641	0.239420111782719	0.119710055891359
46	0.895404982250123	0.209190035499754	0.104595017749877
47	0.885537567246688	0.228924865506624	0.114462432753312
48	0.85844855218328	0.283102895633441	0.14155144781672
49	0.860417401581652	0.279165196836695	0.139582598418347
50	0.843850468155214	0.312299063689573	0.156149531844786
51	0.847459018459266	0.305081963081469	0.152540981540735
52	0.817308369177079	0.365383261645842	0.182691630822921
53	0.783064383162696	0.433871233674609	0.216935616837304
54	0.745028676274364	0.509942647451271	0.254971323725636
55	0.742517143974693	0.514965712050614	0.257482856025307
56	0.709022706895452	0.581954586209095	0.290977293104548
57	0.697748987097786	0.604502025804428	0.302251012902214
58	0.700851729376335	0.598296541247329	0.299148270623665
59	0.658151018881342	0.683697962237316	0.341848981118658
60	0.622314079388542	0.755371841222917	0.377685920611458
61	0.587213513419918	0.825572973160164	0.412786486580082
62	0.563606414299199	0.872787171401603	0.436393585700801
63	0.517349623748863	0.965300752502274	0.482650376251137
64	0.472901221917702	0.945802443835405	0.527098778082298
65	0.434751381884177	0.869502763768355	0.565248618115823
66	0.39610739006625	0.792214780132501	0.60389260993375
67	0.354846112468669	0.709692224937338	0.645153887531331
68	0.34632831786163	0.69265663572326	0.65367168213837
69	0.346065246031905	0.692130492063809	0.653934753968095
70	0.330488751706147	0.660977503412294	0.669511248293853
71	0.296483109945992	0.592966219891984	0.703516890054008
72	0.266494924043883	0.532989848087765	0.733505075956117
73	0.232320224102976	0.464640448205952	0.767679775897024
74	0.201750734544727	0.403501469089454	0.798249265455273
75	0.171666596205113	0.343333192410225	0.828333403794887
76	0.151621190821177	0.303242381642353	0.848378809178823
77	0.130611597593748	0.261223195187496	0.869388402406252
78	0.110265854802046	0.220531709604092	0.889734145197954
79	0.0906693770296457	0.181338754059291	0.909330622970354
80	0.102139103090709	0.204278206181418	0.897860896909291
81	0.0892711827806702	0.17854236556134	0.91072881721933
82	0.579885446176531	0.840229107646937	0.420114553823469
83	0.567704200687047	0.864591598625907	0.432295799312953
84	0.909777385432416	0.180445229135169	0.0902226145675843
85	0.933333557308695	0.13333288538261	0.066666442691305
86	0.924119788609638	0.151760422780724	0.0758802113903621
87	0.96629279555575	0.0674144088885004	0.0337072044442502
88	0.958815719092929	0.0823685618141427	0.0411842809070713
89	0.955009756056187	0.0899804878876255	0.0449902439438128
90	0.944148869704526	0.111702260590948	0.0558511302954742
91	0.935585343305057	0.128829313389887	0.0644146566949434
92	0.974769040135982	0.0504619197280354	0.0252309598640177
93	0.999257426267195	0.00148514746560934	0.000742573732804669
94	0.998995046394312	0.00200990721137665	0.00100495360568832
95	0.998944992765335	0.00211001446933002	0.00105500723466501
96	0.99908324749265	0.00183350501470096	0.000916752507350482
97	0.998765782111929	0.00246843577614265	0.00123421788807133
98	0.998894898351908	0.00221020329618457	0.00110510164809229
99	0.998493478377128	0.00301304324574384	0.00150652162287192
100	0.997878196412379	0.00424360717524245	0.00212180358762122
101	0.997048562720285	0.00590287455942923	0.00295143727971462
102	0.996230005132597	0.00753998973480538	0.00376999486740269
103	0.994837707727104	0.0103245845457924	0.00516229227289619
104	0.99330310190537	0.0133937961892604	0.00669689809463021
105	0.991071732787633	0.0178565344247332	0.00892826721236662
106	0.98858708244389	0.0228258351122204	0.0114129175561102
107	0.999926764188188	0.000146471623623363	7.32358118116814e-05
108	0.999957172539642	8.56549207158309e-05	4.28274603579154e-05
109	0.999941327455116	0.00011734508976705	5.86725448835249e-05
110	0.999947562687314	0.000104874625372882	5.24373126864411e-05
111	0.99995364491588	9.2710168239233e-05	4.63550841196165e-05
112	0.999943483632373	0.000113032735254982	5.65163676274912e-05
113	0.999925653094986	0.000148693810028309	7.43469050141545e-05
114	0.999884752723912	0.000230494552175105	0.000115247276087552
115	0.999904342088258	0.000191315823484487	9.56579117422436e-05
116	0.999852041632849	0.000295916734301115	0.000147958367150557
117	0.999782225701477	0.000435548597045165	0.000217774298522582
118	0.999719876440771	0.000560247118458658	0.000280123559229329
119	0.999810463037283	0.000379073925433577	0.000189536962716789
120	0.999732547990214	0.000534904019571425	0.000267452009785712
121	0.999886123240104	0.000227753519791298	0.000113876759895649
122	0.999940623804105	0.0001187523917901	5.93761958950499e-05
123	0.999909905496763	0.00018018900647466	9.009450323733e-05
124	0.999889568226444	0.00022086354711185	0.000110431773555925
125	0.999910175837403	0.000179648325194706	8.98241625973531e-05
126	0.999877843221862	0.000244313556275187	0.000122156778137594
127	0.999845009736726	0.000309980526548848	0.000154990263274424
128	0.999852568111324	0.000294863777352906	0.000147431888676453
129	0.999780075340538	0.000439849318923818	0.000219924659461909
130	0.999672593848332	0.000654812303336718	0.000327406151668359
131	0.999690048463636	0.000619903072727536	0.000309951536363768
132	0.999540039123167	0.00091992175366604	0.00045996087683302
133	0.999338401953503	0.00132319609299378	0.000661598046496891
134	0.999092367400196	0.00181526519960765	0.000907632599803827
135	0.998860585898844	0.00227882820231212	0.00113941410115606
136	0.99870490604064	0.00259018791871953	0.00129509395935976
137	0.998311533077298	0.00337693384540375	0.00168846692270187
138	0.997715130591728	0.0045697388165433	0.00228486940827165
139	0.997413518582166	0.00517296283566886	0.00258648141783443
140	0.996833897979063	0.00633220404187486	0.00316610202093743
141	0.996554309832344	0.00689138033531123	0.00344569016765561
142	0.995698172258056	0.00860365548388881	0.0043018277419444
143	0.993897673030611	0.0122046539387773	0.00610232696938864
144	0.991599585804565	0.0168008283908706	0.00840041419543529
145	0.988816427200809	0.0223671455983824	0.0111835727991912
146	0.994101134821078	0.0117977303578449	0.00589886517892243
147	0.99303793630083	0.0139241273983393	0.00696206369916965
148	0.998042795751373	0.00391440849725314	0.00195720424862657
149	0.997142090875056	0.00571581824988747	0.00285790912494373
150	0.997691586870961	0.00461682625807849	0.00230841312903925
151	0.996731255095346	0.00653748980930863	0.00326874490465431
152	0.999657706166048	0.000684587667903136	0.000342293833951568
153	0.999590420002826	0.000819159994347366	0.000409579997173683
154	0.999592408303406	0.000815183393187769	0.000407591696593884
155	0.999318093911375	0.00136381217724996	0.000681906088624979
156	0.998860909629422	0.00227818074115567	0.00113909037057783
157	0.998183850458613	0.00363229908277358	0.00181614954138679
158	0.997140504835365	0.00571899032927103	0.00285949516463551
159	0.99562339812423	0.0087532037515406	0.0043766018757703
160	0.993588358596236	0.0128232828075277	0.00641164140376383
161	0.992374297903827	0.0152514041923459	0.00762570209617297
162	0.999912526383441	0.00017494723311745	8.7473616558725e-05
163	0.999852733675217	0.000294532649566308	0.000147266324783154
164	0.999710331060581	0.000579337878838322	0.000289668939419161
165	0.999534191741443	0.000931616517114911	0.000465808258557455
166	0.999611015253139	0.000777969493721601	0.000388984746860801
167	0.999335145172391	0.00132970965521723	0.000664854827608614
168	0.998775314655973	0.00244937068805415	0.00122468534402707
169	0.999273117356276	0.00145376528744772	0.00072688264372386
170	0.998757646910067	0.0024847061798656	0.0012423530899328
171	0.99758714350837	0.00482571298326068	0.00241285649163034
172	0.99540166837836	0.00919666324327919	0.00459833162163959
173	0.991563507571525	0.01687298485695	0.00843649242847499
174	0.993076119950016	0.0138477600999672	0.0069238800499836
175	0.991426777385157	0.0171464452296851	0.00857322261484255
176	0.987359200576402	0.0252815988471949	0.0126407994235975
177	0.990351935265712	0.0192961294685763	0.00964806473428815
178	0.992523198443851	0.0149536031122978	0.00747680155614888
179	0.984350125811953	0.0312997483760943	0.0156498741880471
180	0.967576406594017	0.0648471868119668	0.0324235934059834
181	0.936306131964765	0.127387736070469	0.0636938680352345
182	0.999964681030779	7.06379384419298e-05	3.53189692209649e-05
183	0.999744309892724	0.000511380214551594	0.000255690107275797
184	0.998970281888952	0.0020594362220953	0.00102971811104765
185	0.997523998637113	0.00495200272577468	0.00247600136288734

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	76	0.444444444444444	NOK
5% type I error level	94	0.549707602339181	NOK
10% type I error level	99	0.578947368421053	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 & 76 & 0.444444444444444 & NOK \tabularnewline
5% type I error level & 94 & 0.549707602339181 & NOK \tabularnewline
10% type I error level & 99 & 0.578947368421053 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154396&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]76[/C][C]0.444444444444444[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]94[/C][C]0.549707602339181[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]99[/C][C]0.578947368421053[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154396&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154396&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	76	0.444444444444444	NOK
5% type I error level	94	0.549707602339181	NOK
10% type I error level	99	0.578947368421053	NOK

Figure 1

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

Parameters (R input):

par1 = 5 ; 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