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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_regression_trees1.wasp
Title produced by softwareRecursive Partitioning (Regression Trees)
Date of computationTue, 13 Dec 2011 19:13:22 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/13/t1323821625679jl8kcl9gy9bv.htm/, Retrieved Thu, 02 May 2024 14:50:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154783, Retrieved Thu, 02 May 2024 14:50:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Recursive Partitioning (Regression Trees)] [] [2010-12-05 18:59:57] [b98453cac15ba1066b407e146608df68]
- R PD  [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2011-12-13 16:29:21] [7156a20ff7d97880b6dc50f7239ba03b]
-   P     [Recursive Partitioning (Regression Trees)] [kwhnm] [2011-12-13 23:57:18] [7156a20ff7d97880b6dc50f7239ba03b]
-   PD      [Recursive Partitioning (Regression Trees)] [kwhtnm] [2011-12-14 00:07:05] [7156a20ff7d97880b6dc50f7239ba03b]
-   P           [Recursive Partitioning (Regression Trees)] [kwhnm] [2011-12-14 00:13:22] [8aedcf735e397266388b06f47fe45218] [Current]
-    D            [Recursive Partitioning (Regression Trees)] [hjzed] [2011-12-14 00:15:51] [7156a20ff7d97880b6dc50f7239ba03b]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 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=154783&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=154783&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154783&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Goodness of Fit
Correlation0.8028
R-squared0.6444
RMSE0.6508

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.8028 \tabularnewline
R-squared & 0.6444 \tabularnewline
RMSE & 0.6508 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154783&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.8028[/C][/ROW]
[ROW][C]R-squared[/C][C]0.6444[/C][/ROW]
[ROW][C]RMSE[/C][C]0.6508[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154783&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154783&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Goodness of Fit
Correlation0.8028
R-squared0.6444
RMSE0.6508






Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
18.89.15-0.35
29.59.84722222222222-0.347222222222221
310.19.847222222222220.252777777777778
49.99.337931034482760.562068965517241
59.99.337931034482760.562068965517241
610.19.847222222222220.252777777777778
79.69.84722222222222-0.247222222222222
88.89.15-0.35
99.59.84722222222222-0.347222222222221
101111.0769230769231-0.0769230769230766
111211.07692307692310.923076923076923
129.711.0769230769231-1.37692307692308
1310.811.0769230769231-0.276923076923076
1412.411.40645161290320.993548387096775
159.79.150.549999999999999
1611.411.4064516129032-0.00645161290322527
179.69.84722222222222-0.247222222222222
1812.812.16923076923080.630769230769232
1911.311.07692307692310.223076923076924
209.59.94814814814815-0.448148148148148
2112.812.16923076923080.630769230769232
221111.4064516129032-0.406451612903226
2310.511.4064516129032-0.906451612903226
249.39.84722222222222-0.547222222222221
25109.847222222222220.152777777777779
2610.49.948148148148150.451851851851853
27109.847222222222220.152777777777779
2810.59.337931034482761.16206896551724
2911.69.847222222222221.75277777777778
3012.312.16923076923080.130769230769232
31109.948148148148150.0518518518518523
3210.210.24375-0.0437500000000011
3310.89.847222222222220.952777777777779
3499.84722222222222-0.847222222222221
3510.29.151.05
3612.89.847222222222222.95277777777778
37109.847222222222220.152777777777779
3811.29.847222222222221.35277777777778
398.69.15-0.550000000000001
408.69.15-0.550000000000001
419.49.84722222222222-0.447222222222221
429.49.84722222222222-0.447222222222221
439.89.337931034482760.462068965517242
449.59.84722222222222-0.347222222222221
459.59.84722222222222-0.347222222222221
461011.4064516129032-1.40645161290323
479.89.84722222222222-0.0472222222222207
489.89.84722222222222-0.0472222222222207
499.89.337931034482760.462068965517242
509.89.84722222222222-0.0472222222222207
5111.79.847222222222221.85277777777778
521111.4064516129032-0.406451612903226
5310.911.4064516129032-0.506451612903225
5410.99.847222222222221.05277777777778
559.19.84722222222222-0.747222222222222
561111.0769230769231-0.0769230769230766
579.69.150.449999999999999
588.99.15-0.25
5910.210.24375-0.0437500000000011
609.911.0769230769231-1.17692307692308
618.69.84722222222222-1.24722222222222
628.99.15-0.25
6310.510.243750.25625
6410.210.24375-0.0437500000000011
6510.310.243750.0562500000000004
669.19.84722222222222-0.747222222222222
6712.611.40645161290321.19354838709677
689.810.24375-0.44375
6910.711.4064516129032-0.706451612903226
709.59.337931034482760.162068965517241
7199.33793103448276-0.337931034482759
729.59.84722222222222-0.347222222222221
73109.847222222222220.152777777777779
749.19.84722222222222-0.747222222222222
7510.711.4064516129032-0.706451612903226
769.59.337931034482760.162068965517241
7712.711.40645161290321.29354838709677
781212.1692307692308-0.169230769230769
799.39.33793103448276-0.0379310344827584
8099.84722222222222-0.847222222222221
8110.69.847222222222220.752777777777778
829.29.150.0499999999999989
83109.847222222222220.152777777777779
849.59.337931034482760.162068965517241
858.79.15-0.450000000000001
868.79.15-0.450000000000001
878.79.15-0.450000000000001
889.79.150.549999999999999
898.79.15-0.450000000000001
908.79.15-0.450000000000001
918.79.15-0.450000000000001
9299.33793103448276-0.337931034482759
9312.611.40645161290321.19354838709677
9412.611.40645161290321.19354838709677
9511.511.40645161290320.0935483870967744
969.29.150.0499999999999989
978.89.15-0.35
9811.411.4064516129032-0.00645161290322527
9910.19.150.949999999999999
1008.89.15-0.35
1019.19.15-0.0500000000000007
1029.49.337931034482760.0620689655172413
1039.49.150.25
10499.15-0.15
1059.19.15-0.0500000000000007
1069.29.150.0499999999999989
1079.49.337931034482760.0620689655172413
1089.19.15-0.0500000000000007
1099.19.15-0.0500000000000007
11010.39.847222222222220.452777777777779
1118.89.33793103448276-0.537931034482758
1128.99.15-0.25
1139.29.150.0499999999999989
1149.19.33793103448276-0.237931034482759
1159.19.33793103448276-0.237931034482759
1169.79.84722222222222-0.147222222222222
11711.310.243751.05625
11811.811.07692307692310.723076923076924
1199.29.150.0499999999999989
1209.29.150.0499999999999989
12110.29.847222222222220.352777777777778
1228.89.15-0.35
1239.79.84722222222222-0.147222222222222
1249.19.84722222222222-0.747222222222222
1259.89.84722222222222-0.0472222222222207
1261111.0769230769231-0.0769230769230766
12710.510.243750.25625
1289.79.94814814814815-0.248148148148148
12910.911.4064516129032-0.506451612903225
13010.99.847222222222221.05277777777778
13110.69.948148148148150.651851851851852
1329.79.94814814814815-0.248148148148148
13399.15-0.15
1349.29.150.0499999999999989
1358.99.94814814814815-1.04814814814815
1369.69.150.449999999999999
13710.711.0769230769231-0.376923076923077
1388.79.15-0.450000000000001
13910.811.4064516129032-0.606451612903225
14011.811.07692307692310.723076923076924
14110.29.847222222222220.352777777777778
1428.79.15-0.450000000000001
14310.811.0769230769231-0.276923076923076
1449.711.0769230769231-1.37692307692308
14511.211.07692307692310.123076923076923
14610.911.0769230769231-0.176923076923076
14710.110.24375-0.143750000000001
14899.84722222222222-0.847222222222221
1491212.1692307692308-0.169230769230769
1509.49.84722222222222-0.447222222222221
15111.59.948148148148151.55185185185185
1529.99.337931034482760.562068965517241
1539.49.84722222222222-0.447222222222221
15410.49.847222222222220.552777777777779
1559.79.337931034482760.36206896551724
1568.99.15-0.25
1578.99.15-0.25
15812.412.16923076923080.230769230769232
15912.112.1692307692308-0.069230769230769
16012.112.1692307692308-0.069230769230769
16112.412.16923076923080.230769230769232
1629.19.15-0.0500000000000007
16310.69.847222222222220.752777777777778
1648.99.15-0.25
1659.59.150.35
1669.89.150.65
1679.69.337931034482760.262068965517241
16812.612.16923076923080.430769230769231
1699.39.33793103448276-0.0379310344827584
170109.948148148148150.0518518518518523
17112.79.847222222222222.85277777777778
172119.847222222222221.15277777777778
17311.411.07692307692310.323076923076924
17411.511.40645161290320.0935483870967744
17510.29.151.05
17611.49.948148148148151.45185185185185
17712.611.07692307692311.52307692307692
1789.49.150.25
1798.79.84722222222222-1.14722222222222
1809.29.84722222222222-0.647222222222222
1819.39.84722222222222-0.547222222222221
1829.29.84722222222222-0.647222222222222
1838.79.15-0.450000000000001
1849.69.150.449999999999999
1859.39.150.15
1869.39.150.15
1879.99.94814814814815-0.0481481481481474
1881110.243750.75625
18912.712.16923076923080.530769230769231
1908.99.33793103448276-0.437931034482759
1918.99.33793103448276-0.437931034482759
1928.79.15-0.450000000000001
19311.49.948148148148151.45185185185185
1949.69.84722222222222-0.247222222222222
1959.19.84722222222222-0.747222222222222
1969.19.84722222222222-0.747222222222222
1979.19.84722222222222-0.747222222222222
1988.99.33793103448276-0.437931034482759
1998.89.15-0.35
2008.99.33793103448276-0.437931034482759
2019.39.150.15
2028.89.15-0.35
2039.69.150.449999999999999
204129.152.85
20510.29.847222222222220.352777777777778
2068.89.15-0.35
2079.29.94814814814815-0.748148148148148
2089.99.847222222222220.0527777777777789
20910.210.24375-0.0437500000000011
2109.59.84722222222222-0.347222222222221
21110.59.948148148148150.551851851851852
21211.211.4064516129032-0.206451612903226
2139.29.94814814814815-0.748148148148148
2149.79.84722222222222-0.147222222222222
21511.111.4064516129032-0.306451612903226
2169.49.94814814814815-0.548148148148147
2171111.0769230769231-0.0769230769230766
2189.49.94814814814815-0.548148148148147
2199.49.150.25
2201111.0769230769231-0.0769230769230766
2211111.0769230769231-0.0769230769230766
2229.19.33793103448276-0.237931034482759
22311.111.4064516129032-0.306451612903226
2249.110.24375-1.14375
22510.49.847222222222220.552777777777779
2268.79.15-0.450000000000001
2279.79.84722222222222-0.147222222222222
2289.19.94814814814815-0.848148148148148
2299.79.84722222222222-0.147222222222222
2308.79.15-0.450000000000001
2318.99.33793103448276-0.437931034482759
2329.69.94814814814815-0.348148148148148
2339.59.94814814814815-0.448148148148148
23499.15-0.15
23599.15-0.15
23699.15-0.15
23799.15-0.15
2389.69.150.449999999999999
23911.111.4064516129032-0.306451612903226
2409.69.150.449999999999999
2418.79.15-0.450000000000001
24210.49.948148148148150.451851851851853
24311.411.4064516129032-0.00645161290322527
2449.79.84722222222222-0.147222222222222
2458.79.15-0.450000000000001
24611.311.07692307692310.223076923076924
24712.611.40645161290321.19354838709677
24810.911.4064516129032-0.506451612903225
24910.911.4064516129032-0.506451612903225
250109.948148148148150.0518518518518523
251109.847222222222220.152777777777779
2529.89.150.65
2538.79.15-0.450000000000001
25411.711.07692307692310.623076923076923
2559.39.84722222222222-0.547222222222221
2569.611.4064516129032-1.80645161290323
2571112.1692307692308-1.16923076923077
2581112.1692307692308-1.16923076923077
25911.811.07692307692310.723076923076924
26011.411.07692307692310.323076923076924
26110.29.847222222222220.352777777777778
2628.99.15-0.25
26310.29.948148148148150.251851851851852
2649.69.150.449999999999999
26510.611.0769230769231-0.476923076923077
2668.99.15-0.25
2679.29.33793103448276-0.13793103448276
2689.710.24375-0.543750000000001
2699.79.94814814814815-0.248148148148148
2709.79.84722222222222-0.147222222222222
2719.29.33793103448276-0.13793103448276
2729.710.24375-0.543750000000001
2739.39.150.15
27499.84722222222222-0.847222222222221
2759.59.150.35
2769.89.94814814814815-0.148148148148147
2779.89.94814814814815-0.148148148148147
27810.611.0769230769231-0.476923076923077
27910.610.243750.356249999999999
28012.411.40645161290320.993548387096775
28112.611.40645161290321.19354838709677
28212.311.40645161290320.893548387096775
28310.59.847222222222220.652777777777779
2849.39.150.15
2858.89.15-0.35
2868.89.33793103448276-0.537931034482758
2879.79.150.549999999999999
28899.15-0.15
28999.15-0.15
29099.15-0.15
29199.15-0.15
29210.510.243750.25625
2939.19.15-0.0500000000000007
2949.89.94814814814815-0.148148148148147
2958.59.84722222222222-1.34722222222222
2969.49.84722222222222-0.447222222222221
2979.49.150.25
29811.211.4064516129032-0.206451612903226

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 8.8 & 9.15 & -0.35 \tabularnewline
2 & 9.5 & 9.84722222222222 & -0.347222222222221 \tabularnewline
3 & 10.1 & 9.84722222222222 & 0.252777777777778 \tabularnewline
4 & 9.9 & 9.33793103448276 & 0.562068965517241 \tabularnewline
5 & 9.9 & 9.33793103448276 & 0.562068965517241 \tabularnewline
6 & 10.1 & 9.84722222222222 & 0.252777777777778 \tabularnewline
7 & 9.6 & 9.84722222222222 & -0.247222222222222 \tabularnewline
8 & 8.8 & 9.15 & -0.35 \tabularnewline
9 & 9.5 & 9.84722222222222 & -0.347222222222221 \tabularnewline
10 & 11 & 11.0769230769231 & -0.0769230769230766 \tabularnewline
11 & 12 & 11.0769230769231 & 0.923076923076923 \tabularnewline
12 & 9.7 & 11.0769230769231 & -1.37692307692308 \tabularnewline
13 & 10.8 & 11.0769230769231 & -0.276923076923076 \tabularnewline
14 & 12.4 & 11.4064516129032 & 0.993548387096775 \tabularnewline
15 & 9.7 & 9.15 & 0.549999999999999 \tabularnewline
16 & 11.4 & 11.4064516129032 & -0.00645161290322527 \tabularnewline
17 & 9.6 & 9.84722222222222 & -0.247222222222222 \tabularnewline
18 & 12.8 & 12.1692307692308 & 0.630769230769232 \tabularnewline
19 & 11.3 & 11.0769230769231 & 0.223076923076924 \tabularnewline
20 & 9.5 & 9.94814814814815 & -0.448148148148148 \tabularnewline
21 & 12.8 & 12.1692307692308 & 0.630769230769232 \tabularnewline
22 & 11 & 11.4064516129032 & -0.406451612903226 \tabularnewline
23 & 10.5 & 11.4064516129032 & -0.906451612903226 \tabularnewline
24 & 9.3 & 9.84722222222222 & -0.547222222222221 \tabularnewline
25 & 10 & 9.84722222222222 & 0.152777777777779 \tabularnewline
26 & 10.4 & 9.94814814814815 & 0.451851851851853 \tabularnewline
27 & 10 & 9.84722222222222 & 0.152777777777779 \tabularnewline
28 & 10.5 & 9.33793103448276 & 1.16206896551724 \tabularnewline
29 & 11.6 & 9.84722222222222 & 1.75277777777778 \tabularnewline
30 & 12.3 & 12.1692307692308 & 0.130769230769232 \tabularnewline
31 & 10 & 9.94814814814815 & 0.0518518518518523 \tabularnewline
32 & 10.2 & 10.24375 & -0.0437500000000011 \tabularnewline
33 & 10.8 & 9.84722222222222 & 0.952777777777779 \tabularnewline
34 & 9 & 9.84722222222222 & -0.847222222222221 \tabularnewline
35 & 10.2 & 9.15 & 1.05 \tabularnewline
36 & 12.8 & 9.84722222222222 & 2.95277777777778 \tabularnewline
37 & 10 & 9.84722222222222 & 0.152777777777779 \tabularnewline
38 & 11.2 & 9.84722222222222 & 1.35277777777778 \tabularnewline
39 & 8.6 & 9.15 & -0.550000000000001 \tabularnewline
40 & 8.6 & 9.15 & -0.550000000000001 \tabularnewline
41 & 9.4 & 9.84722222222222 & -0.447222222222221 \tabularnewline
42 & 9.4 & 9.84722222222222 & -0.447222222222221 \tabularnewline
43 & 9.8 & 9.33793103448276 & 0.462068965517242 \tabularnewline
44 & 9.5 & 9.84722222222222 & -0.347222222222221 \tabularnewline
45 & 9.5 & 9.84722222222222 & -0.347222222222221 \tabularnewline
46 & 10 & 11.4064516129032 & -1.40645161290323 \tabularnewline
47 & 9.8 & 9.84722222222222 & -0.0472222222222207 \tabularnewline
48 & 9.8 & 9.84722222222222 & -0.0472222222222207 \tabularnewline
49 & 9.8 & 9.33793103448276 & 0.462068965517242 \tabularnewline
50 & 9.8 & 9.84722222222222 & -0.0472222222222207 \tabularnewline
51 & 11.7 & 9.84722222222222 & 1.85277777777778 \tabularnewline
52 & 11 & 11.4064516129032 & -0.406451612903226 \tabularnewline
53 & 10.9 & 11.4064516129032 & -0.506451612903225 \tabularnewline
54 & 10.9 & 9.84722222222222 & 1.05277777777778 \tabularnewline
55 & 9.1 & 9.84722222222222 & -0.747222222222222 \tabularnewline
56 & 11 & 11.0769230769231 & -0.0769230769230766 \tabularnewline
57 & 9.6 & 9.15 & 0.449999999999999 \tabularnewline
58 & 8.9 & 9.15 & -0.25 \tabularnewline
59 & 10.2 & 10.24375 & -0.0437500000000011 \tabularnewline
60 & 9.9 & 11.0769230769231 & -1.17692307692308 \tabularnewline
61 & 8.6 & 9.84722222222222 & -1.24722222222222 \tabularnewline
62 & 8.9 & 9.15 & -0.25 \tabularnewline
63 & 10.5 & 10.24375 & 0.25625 \tabularnewline
64 & 10.2 & 10.24375 & -0.0437500000000011 \tabularnewline
65 & 10.3 & 10.24375 & 0.0562500000000004 \tabularnewline
66 & 9.1 & 9.84722222222222 & -0.747222222222222 \tabularnewline
67 & 12.6 & 11.4064516129032 & 1.19354838709677 \tabularnewline
68 & 9.8 & 10.24375 & -0.44375 \tabularnewline
69 & 10.7 & 11.4064516129032 & -0.706451612903226 \tabularnewline
70 & 9.5 & 9.33793103448276 & 0.162068965517241 \tabularnewline
71 & 9 & 9.33793103448276 & -0.337931034482759 \tabularnewline
72 & 9.5 & 9.84722222222222 & -0.347222222222221 \tabularnewline
73 & 10 & 9.84722222222222 & 0.152777777777779 \tabularnewline
74 & 9.1 & 9.84722222222222 & -0.747222222222222 \tabularnewline
75 & 10.7 & 11.4064516129032 & -0.706451612903226 \tabularnewline
76 & 9.5 & 9.33793103448276 & 0.162068965517241 \tabularnewline
77 & 12.7 & 11.4064516129032 & 1.29354838709677 \tabularnewline
78 & 12 & 12.1692307692308 & -0.169230769230769 \tabularnewline
79 & 9.3 & 9.33793103448276 & -0.0379310344827584 \tabularnewline
80 & 9 & 9.84722222222222 & -0.847222222222221 \tabularnewline
81 & 10.6 & 9.84722222222222 & 0.752777777777778 \tabularnewline
82 & 9.2 & 9.15 & 0.0499999999999989 \tabularnewline
83 & 10 & 9.84722222222222 & 0.152777777777779 \tabularnewline
84 & 9.5 & 9.33793103448276 & 0.162068965517241 \tabularnewline
85 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
86 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
87 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
88 & 9.7 & 9.15 & 0.549999999999999 \tabularnewline
89 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
90 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
91 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
92 & 9 & 9.33793103448276 & -0.337931034482759 \tabularnewline
93 & 12.6 & 11.4064516129032 & 1.19354838709677 \tabularnewline
94 & 12.6 & 11.4064516129032 & 1.19354838709677 \tabularnewline
95 & 11.5 & 11.4064516129032 & 0.0935483870967744 \tabularnewline
96 & 9.2 & 9.15 & 0.0499999999999989 \tabularnewline
97 & 8.8 & 9.15 & -0.35 \tabularnewline
98 & 11.4 & 11.4064516129032 & -0.00645161290322527 \tabularnewline
99 & 10.1 & 9.15 & 0.949999999999999 \tabularnewline
100 & 8.8 & 9.15 & -0.35 \tabularnewline
101 & 9.1 & 9.15 & -0.0500000000000007 \tabularnewline
102 & 9.4 & 9.33793103448276 & 0.0620689655172413 \tabularnewline
103 & 9.4 & 9.15 & 0.25 \tabularnewline
104 & 9 & 9.15 & -0.15 \tabularnewline
105 & 9.1 & 9.15 & -0.0500000000000007 \tabularnewline
106 & 9.2 & 9.15 & 0.0499999999999989 \tabularnewline
107 & 9.4 & 9.33793103448276 & 0.0620689655172413 \tabularnewline
108 & 9.1 & 9.15 & -0.0500000000000007 \tabularnewline
109 & 9.1 & 9.15 & -0.0500000000000007 \tabularnewline
110 & 10.3 & 9.84722222222222 & 0.452777777777779 \tabularnewline
111 & 8.8 & 9.33793103448276 & -0.537931034482758 \tabularnewline
112 & 8.9 & 9.15 & -0.25 \tabularnewline
113 & 9.2 & 9.15 & 0.0499999999999989 \tabularnewline
114 & 9.1 & 9.33793103448276 & -0.237931034482759 \tabularnewline
115 & 9.1 & 9.33793103448276 & -0.237931034482759 \tabularnewline
116 & 9.7 & 9.84722222222222 & -0.147222222222222 \tabularnewline
117 & 11.3 & 10.24375 & 1.05625 \tabularnewline
118 & 11.8 & 11.0769230769231 & 0.723076923076924 \tabularnewline
119 & 9.2 & 9.15 & 0.0499999999999989 \tabularnewline
120 & 9.2 & 9.15 & 0.0499999999999989 \tabularnewline
121 & 10.2 & 9.84722222222222 & 0.352777777777778 \tabularnewline
122 & 8.8 & 9.15 & -0.35 \tabularnewline
123 & 9.7 & 9.84722222222222 & -0.147222222222222 \tabularnewline
124 & 9.1 & 9.84722222222222 & -0.747222222222222 \tabularnewline
125 & 9.8 & 9.84722222222222 & -0.0472222222222207 \tabularnewline
126 & 11 & 11.0769230769231 & -0.0769230769230766 \tabularnewline
127 & 10.5 & 10.24375 & 0.25625 \tabularnewline
128 & 9.7 & 9.94814814814815 & -0.248148148148148 \tabularnewline
129 & 10.9 & 11.4064516129032 & -0.506451612903225 \tabularnewline
130 & 10.9 & 9.84722222222222 & 1.05277777777778 \tabularnewline
131 & 10.6 & 9.94814814814815 & 0.651851851851852 \tabularnewline
132 & 9.7 & 9.94814814814815 & -0.248148148148148 \tabularnewline
133 & 9 & 9.15 & -0.15 \tabularnewline
134 & 9.2 & 9.15 & 0.0499999999999989 \tabularnewline
135 & 8.9 & 9.94814814814815 & -1.04814814814815 \tabularnewline
136 & 9.6 & 9.15 & 0.449999999999999 \tabularnewline
137 & 10.7 & 11.0769230769231 & -0.376923076923077 \tabularnewline
138 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
139 & 10.8 & 11.4064516129032 & -0.606451612903225 \tabularnewline
140 & 11.8 & 11.0769230769231 & 0.723076923076924 \tabularnewline
141 & 10.2 & 9.84722222222222 & 0.352777777777778 \tabularnewline
142 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
143 & 10.8 & 11.0769230769231 & -0.276923076923076 \tabularnewline
144 & 9.7 & 11.0769230769231 & -1.37692307692308 \tabularnewline
145 & 11.2 & 11.0769230769231 & 0.123076923076923 \tabularnewline
146 & 10.9 & 11.0769230769231 & -0.176923076923076 \tabularnewline
147 & 10.1 & 10.24375 & -0.143750000000001 \tabularnewline
148 & 9 & 9.84722222222222 & -0.847222222222221 \tabularnewline
149 & 12 & 12.1692307692308 & -0.169230769230769 \tabularnewline
150 & 9.4 & 9.84722222222222 & -0.447222222222221 \tabularnewline
151 & 11.5 & 9.94814814814815 & 1.55185185185185 \tabularnewline
152 & 9.9 & 9.33793103448276 & 0.562068965517241 \tabularnewline
153 & 9.4 & 9.84722222222222 & -0.447222222222221 \tabularnewline
154 & 10.4 & 9.84722222222222 & 0.552777777777779 \tabularnewline
155 & 9.7 & 9.33793103448276 & 0.36206896551724 \tabularnewline
156 & 8.9 & 9.15 & -0.25 \tabularnewline
157 & 8.9 & 9.15 & -0.25 \tabularnewline
158 & 12.4 & 12.1692307692308 & 0.230769230769232 \tabularnewline
159 & 12.1 & 12.1692307692308 & -0.069230769230769 \tabularnewline
160 & 12.1 & 12.1692307692308 & -0.069230769230769 \tabularnewline
161 & 12.4 & 12.1692307692308 & 0.230769230769232 \tabularnewline
162 & 9.1 & 9.15 & -0.0500000000000007 \tabularnewline
163 & 10.6 & 9.84722222222222 & 0.752777777777778 \tabularnewline
164 & 8.9 & 9.15 & -0.25 \tabularnewline
165 & 9.5 & 9.15 & 0.35 \tabularnewline
166 & 9.8 & 9.15 & 0.65 \tabularnewline
167 & 9.6 & 9.33793103448276 & 0.262068965517241 \tabularnewline
168 & 12.6 & 12.1692307692308 & 0.430769230769231 \tabularnewline
169 & 9.3 & 9.33793103448276 & -0.0379310344827584 \tabularnewline
170 & 10 & 9.94814814814815 & 0.0518518518518523 \tabularnewline
171 & 12.7 & 9.84722222222222 & 2.85277777777778 \tabularnewline
172 & 11 & 9.84722222222222 & 1.15277777777778 \tabularnewline
173 & 11.4 & 11.0769230769231 & 0.323076923076924 \tabularnewline
174 & 11.5 & 11.4064516129032 & 0.0935483870967744 \tabularnewline
175 & 10.2 & 9.15 & 1.05 \tabularnewline
176 & 11.4 & 9.94814814814815 & 1.45185185185185 \tabularnewline
177 & 12.6 & 11.0769230769231 & 1.52307692307692 \tabularnewline
178 & 9.4 & 9.15 & 0.25 \tabularnewline
179 & 8.7 & 9.84722222222222 & -1.14722222222222 \tabularnewline
180 & 9.2 & 9.84722222222222 & -0.647222222222222 \tabularnewline
181 & 9.3 & 9.84722222222222 & -0.547222222222221 \tabularnewline
182 & 9.2 & 9.84722222222222 & -0.647222222222222 \tabularnewline
183 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
184 & 9.6 & 9.15 & 0.449999999999999 \tabularnewline
185 & 9.3 & 9.15 & 0.15 \tabularnewline
186 & 9.3 & 9.15 & 0.15 \tabularnewline
187 & 9.9 & 9.94814814814815 & -0.0481481481481474 \tabularnewline
188 & 11 & 10.24375 & 0.75625 \tabularnewline
189 & 12.7 & 12.1692307692308 & 0.530769230769231 \tabularnewline
190 & 8.9 & 9.33793103448276 & -0.437931034482759 \tabularnewline
191 & 8.9 & 9.33793103448276 & -0.437931034482759 \tabularnewline
192 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
193 & 11.4 & 9.94814814814815 & 1.45185185185185 \tabularnewline
194 & 9.6 & 9.84722222222222 & -0.247222222222222 \tabularnewline
195 & 9.1 & 9.84722222222222 & -0.747222222222222 \tabularnewline
196 & 9.1 & 9.84722222222222 & -0.747222222222222 \tabularnewline
197 & 9.1 & 9.84722222222222 & -0.747222222222222 \tabularnewline
198 & 8.9 & 9.33793103448276 & -0.437931034482759 \tabularnewline
199 & 8.8 & 9.15 & -0.35 \tabularnewline
200 & 8.9 & 9.33793103448276 & -0.437931034482759 \tabularnewline
201 & 9.3 & 9.15 & 0.15 \tabularnewline
202 & 8.8 & 9.15 & -0.35 \tabularnewline
203 & 9.6 & 9.15 & 0.449999999999999 \tabularnewline
204 & 12 & 9.15 & 2.85 \tabularnewline
205 & 10.2 & 9.84722222222222 & 0.352777777777778 \tabularnewline
206 & 8.8 & 9.15 & -0.35 \tabularnewline
207 & 9.2 & 9.94814814814815 & -0.748148148148148 \tabularnewline
208 & 9.9 & 9.84722222222222 & 0.0527777777777789 \tabularnewline
209 & 10.2 & 10.24375 & -0.0437500000000011 \tabularnewline
210 & 9.5 & 9.84722222222222 & -0.347222222222221 \tabularnewline
211 & 10.5 & 9.94814814814815 & 0.551851851851852 \tabularnewline
212 & 11.2 & 11.4064516129032 & -0.206451612903226 \tabularnewline
213 & 9.2 & 9.94814814814815 & -0.748148148148148 \tabularnewline
214 & 9.7 & 9.84722222222222 & -0.147222222222222 \tabularnewline
215 & 11.1 & 11.4064516129032 & -0.306451612903226 \tabularnewline
216 & 9.4 & 9.94814814814815 & -0.548148148148147 \tabularnewline
217 & 11 & 11.0769230769231 & -0.0769230769230766 \tabularnewline
218 & 9.4 & 9.94814814814815 & -0.548148148148147 \tabularnewline
219 & 9.4 & 9.15 & 0.25 \tabularnewline
220 & 11 & 11.0769230769231 & -0.0769230769230766 \tabularnewline
221 & 11 & 11.0769230769231 & -0.0769230769230766 \tabularnewline
222 & 9.1 & 9.33793103448276 & -0.237931034482759 \tabularnewline
223 & 11.1 & 11.4064516129032 & -0.306451612903226 \tabularnewline
224 & 9.1 & 10.24375 & -1.14375 \tabularnewline
225 & 10.4 & 9.84722222222222 & 0.552777777777779 \tabularnewline
226 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
227 & 9.7 & 9.84722222222222 & -0.147222222222222 \tabularnewline
228 & 9.1 & 9.94814814814815 & -0.848148148148148 \tabularnewline
229 & 9.7 & 9.84722222222222 & -0.147222222222222 \tabularnewline
230 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
231 & 8.9 & 9.33793103448276 & -0.437931034482759 \tabularnewline
232 & 9.6 & 9.94814814814815 & -0.348148148148148 \tabularnewline
233 & 9.5 & 9.94814814814815 & -0.448148148148148 \tabularnewline
234 & 9 & 9.15 & -0.15 \tabularnewline
235 & 9 & 9.15 & -0.15 \tabularnewline
236 & 9 & 9.15 & -0.15 \tabularnewline
237 & 9 & 9.15 & -0.15 \tabularnewline
238 & 9.6 & 9.15 & 0.449999999999999 \tabularnewline
239 & 11.1 & 11.4064516129032 & -0.306451612903226 \tabularnewline
240 & 9.6 & 9.15 & 0.449999999999999 \tabularnewline
241 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
242 & 10.4 & 9.94814814814815 & 0.451851851851853 \tabularnewline
243 & 11.4 & 11.4064516129032 & -0.00645161290322527 \tabularnewline
244 & 9.7 & 9.84722222222222 & -0.147222222222222 \tabularnewline
245 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
246 & 11.3 & 11.0769230769231 & 0.223076923076924 \tabularnewline
247 & 12.6 & 11.4064516129032 & 1.19354838709677 \tabularnewline
248 & 10.9 & 11.4064516129032 & -0.506451612903225 \tabularnewline
249 & 10.9 & 11.4064516129032 & -0.506451612903225 \tabularnewline
250 & 10 & 9.94814814814815 & 0.0518518518518523 \tabularnewline
251 & 10 & 9.84722222222222 & 0.152777777777779 \tabularnewline
252 & 9.8 & 9.15 & 0.65 \tabularnewline
253 & 8.7 & 9.15 & -0.450000000000001 \tabularnewline
254 & 11.7 & 11.0769230769231 & 0.623076923076923 \tabularnewline
255 & 9.3 & 9.84722222222222 & -0.547222222222221 \tabularnewline
256 & 9.6 & 11.4064516129032 & -1.80645161290323 \tabularnewline
257 & 11 & 12.1692307692308 & -1.16923076923077 \tabularnewline
258 & 11 & 12.1692307692308 & -1.16923076923077 \tabularnewline
259 & 11.8 & 11.0769230769231 & 0.723076923076924 \tabularnewline
260 & 11.4 & 11.0769230769231 & 0.323076923076924 \tabularnewline
261 & 10.2 & 9.84722222222222 & 0.352777777777778 \tabularnewline
262 & 8.9 & 9.15 & -0.25 \tabularnewline
263 & 10.2 & 9.94814814814815 & 0.251851851851852 \tabularnewline
264 & 9.6 & 9.15 & 0.449999999999999 \tabularnewline
265 & 10.6 & 11.0769230769231 & -0.476923076923077 \tabularnewline
266 & 8.9 & 9.15 & -0.25 \tabularnewline
267 & 9.2 & 9.33793103448276 & -0.13793103448276 \tabularnewline
268 & 9.7 & 10.24375 & -0.543750000000001 \tabularnewline
269 & 9.7 & 9.94814814814815 & -0.248148148148148 \tabularnewline
270 & 9.7 & 9.84722222222222 & -0.147222222222222 \tabularnewline
271 & 9.2 & 9.33793103448276 & -0.13793103448276 \tabularnewline
272 & 9.7 & 10.24375 & -0.543750000000001 \tabularnewline
273 & 9.3 & 9.15 & 0.15 \tabularnewline
274 & 9 & 9.84722222222222 & -0.847222222222221 \tabularnewline
275 & 9.5 & 9.15 & 0.35 \tabularnewline
276 & 9.8 & 9.94814814814815 & -0.148148148148147 \tabularnewline
277 & 9.8 & 9.94814814814815 & -0.148148148148147 \tabularnewline
278 & 10.6 & 11.0769230769231 & -0.476923076923077 \tabularnewline
279 & 10.6 & 10.24375 & 0.356249999999999 \tabularnewline
280 & 12.4 & 11.4064516129032 & 0.993548387096775 \tabularnewline
281 & 12.6 & 11.4064516129032 & 1.19354838709677 \tabularnewline
282 & 12.3 & 11.4064516129032 & 0.893548387096775 \tabularnewline
283 & 10.5 & 9.84722222222222 & 0.652777777777779 \tabularnewline
284 & 9.3 & 9.15 & 0.15 \tabularnewline
285 & 8.8 & 9.15 & -0.35 \tabularnewline
286 & 8.8 & 9.33793103448276 & -0.537931034482758 \tabularnewline
287 & 9.7 & 9.15 & 0.549999999999999 \tabularnewline
288 & 9 & 9.15 & -0.15 \tabularnewline
289 & 9 & 9.15 & -0.15 \tabularnewline
290 & 9 & 9.15 & -0.15 \tabularnewline
291 & 9 & 9.15 & -0.15 \tabularnewline
292 & 10.5 & 10.24375 & 0.25625 \tabularnewline
293 & 9.1 & 9.15 & -0.0500000000000007 \tabularnewline
294 & 9.8 & 9.94814814814815 & -0.148148148148147 \tabularnewline
295 & 8.5 & 9.84722222222222 & -1.34722222222222 \tabularnewline
296 & 9.4 & 9.84722222222222 & -0.447222222222221 \tabularnewline
297 & 9.4 & 9.15 & 0.25 \tabularnewline
298 & 11.2 & 11.4064516129032 & -0.206451612903226 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154783&T=2

[TABLE]
[ROW][C]Actuals, Predictions, and Residuals[/C][/ROW]
[ROW][C]#[/C][C]Actuals[/C][C]Forecasts[/C][C]Residuals[/C][/ROW]
[ROW][C]1[/C][C]8.8[/C][C]9.15[/C][C]-0.35[/C][/ROW]
[ROW][C]2[/C][C]9.5[/C][C]9.84722222222222[/C][C]-0.347222222222221[/C][/ROW]
[ROW][C]3[/C][C]10.1[/C][C]9.84722222222222[/C][C]0.252777777777778[/C][/ROW]
[ROW][C]4[/C][C]9.9[/C][C]9.33793103448276[/C][C]0.562068965517241[/C][/ROW]
[ROW][C]5[/C][C]9.9[/C][C]9.33793103448276[/C][C]0.562068965517241[/C][/ROW]
[ROW][C]6[/C][C]10.1[/C][C]9.84722222222222[/C][C]0.252777777777778[/C][/ROW]
[ROW][C]7[/C][C]9.6[/C][C]9.84722222222222[/C][C]-0.247222222222222[/C][/ROW]
[ROW][C]8[/C][C]8.8[/C][C]9.15[/C][C]-0.35[/C][/ROW]
[ROW][C]9[/C][C]9.5[/C][C]9.84722222222222[/C][C]-0.347222222222221[/C][/ROW]
[ROW][C]10[/C][C]11[/C][C]11.0769230769231[/C][C]-0.0769230769230766[/C][/ROW]
[ROW][C]11[/C][C]12[/C][C]11.0769230769231[/C][C]0.923076923076923[/C][/ROW]
[ROW][C]12[/C][C]9.7[/C][C]11.0769230769231[/C][C]-1.37692307692308[/C][/ROW]
[ROW][C]13[/C][C]10.8[/C][C]11.0769230769231[/C][C]-0.276923076923076[/C][/ROW]
[ROW][C]14[/C][C]12.4[/C][C]11.4064516129032[/C][C]0.993548387096775[/C][/ROW]
[ROW][C]15[/C][C]9.7[/C][C]9.15[/C][C]0.549999999999999[/C][/ROW]
[ROW][C]16[/C][C]11.4[/C][C]11.4064516129032[/C][C]-0.00645161290322527[/C][/ROW]
[ROW][C]17[/C][C]9.6[/C][C]9.84722222222222[/C][C]-0.247222222222222[/C][/ROW]
[ROW][C]18[/C][C]12.8[/C][C]12.1692307692308[/C][C]0.630769230769232[/C][/ROW]
[ROW][C]19[/C][C]11.3[/C][C]11.0769230769231[/C][C]0.223076923076924[/C][/ROW]
[ROW][C]20[/C][C]9.5[/C][C]9.94814814814815[/C][C]-0.448148148148148[/C][/ROW]
[ROW][C]21[/C][C]12.8[/C][C]12.1692307692308[/C][C]0.630769230769232[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]11.4064516129032[/C][C]-0.406451612903226[/C][/ROW]
[ROW][C]23[/C][C]10.5[/C][C]11.4064516129032[/C][C]-0.906451612903226[/C][/ROW]
[ROW][C]24[/C][C]9.3[/C][C]9.84722222222222[/C][C]-0.547222222222221[/C][/ROW]
[ROW][C]25[/C][C]10[/C][C]9.84722222222222[/C][C]0.152777777777779[/C][/ROW]
[ROW][C]26[/C][C]10.4[/C][C]9.94814814814815[/C][C]0.451851851851853[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]9.84722222222222[/C][C]0.152777777777779[/C][/ROW]
[ROW][C]28[/C][C]10.5[/C][C]9.33793103448276[/C][C]1.16206896551724[/C][/ROW]
[ROW][C]29[/C][C]11.6[/C][C]9.84722222222222[/C][C]1.75277777777778[/C][/ROW]
[ROW][C]30[/C][C]12.3[/C][C]12.1692307692308[/C][C]0.130769230769232[/C][/ROW]
[ROW][C]31[/C][C]10[/C][C]9.94814814814815[/C][C]0.0518518518518523[/C][/ROW]
[ROW][C]32[/C][C]10.2[/C][C]10.24375[/C][C]-0.0437500000000011[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]9.84722222222222[/C][C]0.952777777777779[/C][/ROW]
[ROW][C]34[/C][C]9[/C][C]9.84722222222222[/C][C]-0.847222222222221[/C][/ROW]
[ROW][C]35[/C][C]10.2[/C][C]9.15[/C][C]1.05[/C][/ROW]
[ROW][C]36[/C][C]12.8[/C][C]9.84722222222222[/C][C]2.95277777777778[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]9.84722222222222[/C][C]0.152777777777779[/C][/ROW]
[ROW][C]38[/C][C]11.2[/C][C]9.84722222222222[/C][C]1.35277777777778[/C][/ROW]
[ROW][C]39[/C][C]8.6[/C][C]9.15[/C][C]-0.550000000000001[/C][/ROW]
[ROW][C]40[/C][C]8.6[/C][C]9.15[/C][C]-0.550000000000001[/C][/ROW]
[ROW][C]41[/C][C]9.4[/C][C]9.84722222222222[/C][C]-0.447222222222221[/C][/ROW]
[ROW][C]42[/C][C]9.4[/C][C]9.84722222222222[/C][C]-0.447222222222221[/C][/ROW]
[ROW][C]43[/C][C]9.8[/C][C]9.33793103448276[/C][C]0.462068965517242[/C][/ROW]
[ROW][C]44[/C][C]9.5[/C][C]9.84722222222222[/C][C]-0.347222222222221[/C][/ROW]
[ROW][C]45[/C][C]9.5[/C][C]9.84722222222222[/C][C]-0.347222222222221[/C][/ROW]
[ROW][C]46[/C][C]10[/C][C]11.4064516129032[/C][C]-1.40645161290323[/C][/ROW]
[ROW][C]47[/C][C]9.8[/C][C]9.84722222222222[/C][C]-0.0472222222222207[/C][/ROW]
[ROW][C]48[/C][C]9.8[/C][C]9.84722222222222[/C][C]-0.0472222222222207[/C][/ROW]
[ROW][C]49[/C][C]9.8[/C][C]9.33793103448276[/C][C]0.462068965517242[/C][/ROW]
[ROW][C]50[/C][C]9.8[/C][C]9.84722222222222[/C][C]-0.0472222222222207[/C][/ROW]
[ROW][C]51[/C][C]11.7[/C][C]9.84722222222222[/C][C]1.85277777777778[/C][/ROW]
[ROW][C]52[/C][C]11[/C][C]11.4064516129032[/C][C]-0.406451612903226[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]11.4064516129032[/C][C]-0.506451612903225[/C][/ROW]
[ROW][C]54[/C][C]10.9[/C][C]9.84722222222222[/C][C]1.05277777777778[/C][/ROW]
[ROW][C]55[/C][C]9.1[/C][C]9.84722222222222[/C][C]-0.747222222222222[/C][/ROW]
[ROW][C]56[/C][C]11[/C][C]11.0769230769231[/C][C]-0.0769230769230766[/C][/ROW]
[ROW][C]57[/C][C]9.6[/C][C]9.15[/C][C]0.449999999999999[/C][/ROW]
[ROW][C]58[/C][C]8.9[/C][C]9.15[/C][C]-0.25[/C][/ROW]
[ROW][C]59[/C][C]10.2[/C][C]10.24375[/C][C]-0.0437500000000011[/C][/ROW]
[ROW][C]60[/C][C]9.9[/C][C]11.0769230769231[/C][C]-1.17692307692308[/C][/ROW]
[ROW][C]61[/C][C]8.6[/C][C]9.84722222222222[/C][C]-1.24722222222222[/C][/ROW]
[ROW][C]62[/C][C]8.9[/C][C]9.15[/C][C]-0.25[/C][/ROW]
[ROW][C]63[/C][C]10.5[/C][C]10.24375[/C][C]0.25625[/C][/ROW]
[ROW][C]64[/C][C]10.2[/C][C]10.24375[/C][C]-0.0437500000000011[/C][/ROW]
[ROW][C]65[/C][C]10.3[/C][C]10.24375[/C][C]0.0562500000000004[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]9.84722222222222[/C][C]-0.747222222222222[/C][/ROW]
[ROW][C]67[/C][C]12.6[/C][C]11.4064516129032[/C][C]1.19354838709677[/C][/ROW]
[ROW][C]68[/C][C]9.8[/C][C]10.24375[/C][C]-0.44375[/C][/ROW]
[ROW][C]69[/C][C]10.7[/C][C]11.4064516129032[/C][C]-0.706451612903226[/C][/ROW]
[ROW][C]70[/C][C]9.5[/C][C]9.33793103448276[/C][C]0.162068965517241[/C][/ROW]
[ROW][C]71[/C][C]9[/C][C]9.33793103448276[/C][C]-0.337931034482759[/C][/ROW]
[ROW][C]72[/C][C]9.5[/C][C]9.84722222222222[/C][C]-0.347222222222221[/C][/ROW]
[ROW][C]73[/C][C]10[/C][C]9.84722222222222[/C][C]0.152777777777779[/C][/ROW]
[ROW][C]74[/C][C]9.1[/C][C]9.84722222222222[/C][C]-0.747222222222222[/C][/ROW]
[ROW][C]75[/C][C]10.7[/C][C]11.4064516129032[/C][C]-0.706451612903226[/C][/ROW]
[ROW][C]76[/C][C]9.5[/C][C]9.33793103448276[/C][C]0.162068965517241[/C][/ROW]
[ROW][C]77[/C][C]12.7[/C][C]11.4064516129032[/C][C]1.29354838709677[/C][/ROW]
[ROW][C]78[/C][C]12[/C][C]12.1692307692308[/C][C]-0.169230769230769[/C][/ROW]
[ROW][C]79[/C][C]9.3[/C][C]9.33793103448276[/C][C]-0.0379310344827584[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]9.84722222222222[/C][C]-0.847222222222221[/C][/ROW]
[ROW][C]81[/C][C]10.6[/C][C]9.84722222222222[/C][C]0.752777777777778[/C][/ROW]
[ROW][C]82[/C][C]9.2[/C][C]9.15[/C][C]0.0499999999999989[/C][/ROW]
[ROW][C]83[/C][C]10[/C][C]9.84722222222222[/C][C]0.152777777777779[/C][/ROW]
[ROW][C]84[/C][C]9.5[/C][C]9.33793103448276[/C][C]0.162068965517241[/C][/ROW]
[ROW][C]85[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]86[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]87[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]88[/C][C]9.7[/C][C]9.15[/C][C]0.549999999999999[/C][/ROW]
[ROW][C]89[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]90[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]91[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]92[/C][C]9[/C][C]9.33793103448276[/C][C]-0.337931034482759[/C][/ROW]
[ROW][C]93[/C][C]12.6[/C][C]11.4064516129032[/C][C]1.19354838709677[/C][/ROW]
[ROW][C]94[/C][C]12.6[/C][C]11.4064516129032[/C][C]1.19354838709677[/C][/ROW]
[ROW][C]95[/C][C]11.5[/C][C]11.4064516129032[/C][C]0.0935483870967744[/C][/ROW]
[ROW][C]96[/C][C]9.2[/C][C]9.15[/C][C]0.0499999999999989[/C][/ROW]
[ROW][C]97[/C][C]8.8[/C][C]9.15[/C][C]-0.35[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]11.4064516129032[/C][C]-0.00645161290322527[/C][/ROW]
[ROW][C]99[/C][C]10.1[/C][C]9.15[/C][C]0.949999999999999[/C][/ROW]
[ROW][C]100[/C][C]8.8[/C][C]9.15[/C][C]-0.35[/C][/ROW]
[ROW][C]101[/C][C]9.1[/C][C]9.15[/C][C]-0.0500000000000007[/C][/ROW]
[ROW][C]102[/C][C]9.4[/C][C]9.33793103448276[/C][C]0.0620689655172413[/C][/ROW]
[ROW][C]103[/C][C]9.4[/C][C]9.15[/C][C]0.25[/C][/ROW]
[ROW][C]104[/C][C]9[/C][C]9.15[/C][C]-0.15[/C][/ROW]
[ROW][C]105[/C][C]9.1[/C][C]9.15[/C][C]-0.0500000000000007[/C][/ROW]
[ROW][C]106[/C][C]9.2[/C][C]9.15[/C][C]0.0499999999999989[/C][/ROW]
[ROW][C]107[/C][C]9.4[/C][C]9.33793103448276[/C][C]0.0620689655172413[/C][/ROW]
[ROW][C]108[/C][C]9.1[/C][C]9.15[/C][C]-0.0500000000000007[/C][/ROW]
[ROW][C]109[/C][C]9.1[/C][C]9.15[/C][C]-0.0500000000000007[/C][/ROW]
[ROW][C]110[/C][C]10.3[/C][C]9.84722222222222[/C][C]0.452777777777779[/C][/ROW]
[ROW][C]111[/C][C]8.8[/C][C]9.33793103448276[/C][C]-0.537931034482758[/C][/ROW]
[ROW][C]112[/C][C]8.9[/C][C]9.15[/C][C]-0.25[/C][/ROW]
[ROW][C]113[/C][C]9.2[/C][C]9.15[/C][C]0.0499999999999989[/C][/ROW]
[ROW][C]114[/C][C]9.1[/C][C]9.33793103448276[/C][C]-0.237931034482759[/C][/ROW]
[ROW][C]115[/C][C]9.1[/C][C]9.33793103448276[/C][C]-0.237931034482759[/C][/ROW]
[ROW][C]116[/C][C]9.7[/C][C]9.84722222222222[/C][C]-0.147222222222222[/C][/ROW]
[ROW][C]117[/C][C]11.3[/C][C]10.24375[/C][C]1.05625[/C][/ROW]
[ROW][C]118[/C][C]11.8[/C][C]11.0769230769231[/C][C]0.723076923076924[/C][/ROW]
[ROW][C]119[/C][C]9.2[/C][C]9.15[/C][C]0.0499999999999989[/C][/ROW]
[ROW][C]120[/C][C]9.2[/C][C]9.15[/C][C]0.0499999999999989[/C][/ROW]
[ROW][C]121[/C][C]10.2[/C][C]9.84722222222222[/C][C]0.352777777777778[/C][/ROW]
[ROW][C]122[/C][C]8.8[/C][C]9.15[/C][C]-0.35[/C][/ROW]
[ROW][C]123[/C][C]9.7[/C][C]9.84722222222222[/C][C]-0.147222222222222[/C][/ROW]
[ROW][C]124[/C][C]9.1[/C][C]9.84722222222222[/C][C]-0.747222222222222[/C][/ROW]
[ROW][C]125[/C][C]9.8[/C][C]9.84722222222222[/C][C]-0.0472222222222207[/C][/ROW]
[ROW][C]126[/C][C]11[/C][C]11.0769230769231[/C][C]-0.0769230769230766[/C][/ROW]
[ROW][C]127[/C][C]10.5[/C][C]10.24375[/C][C]0.25625[/C][/ROW]
[ROW][C]128[/C][C]9.7[/C][C]9.94814814814815[/C][C]-0.248148148148148[/C][/ROW]
[ROW][C]129[/C][C]10.9[/C][C]11.4064516129032[/C][C]-0.506451612903225[/C][/ROW]
[ROW][C]130[/C][C]10.9[/C][C]9.84722222222222[/C][C]1.05277777777778[/C][/ROW]
[ROW][C]131[/C][C]10.6[/C][C]9.94814814814815[/C][C]0.651851851851852[/C][/ROW]
[ROW][C]132[/C][C]9.7[/C][C]9.94814814814815[/C][C]-0.248148148148148[/C][/ROW]
[ROW][C]133[/C][C]9[/C][C]9.15[/C][C]-0.15[/C][/ROW]
[ROW][C]134[/C][C]9.2[/C][C]9.15[/C][C]0.0499999999999989[/C][/ROW]
[ROW][C]135[/C][C]8.9[/C][C]9.94814814814815[/C][C]-1.04814814814815[/C][/ROW]
[ROW][C]136[/C][C]9.6[/C][C]9.15[/C][C]0.449999999999999[/C][/ROW]
[ROW][C]137[/C][C]10.7[/C][C]11.0769230769231[/C][C]-0.376923076923077[/C][/ROW]
[ROW][C]138[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]139[/C][C]10.8[/C][C]11.4064516129032[/C][C]-0.606451612903225[/C][/ROW]
[ROW][C]140[/C][C]11.8[/C][C]11.0769230769231[/C][C]0.723076923076924[/C][/ROW]
[ROW][C]141[/C][C]10.2[/C][C]9.84722222222222[/C][C]0.352777777777778[/C][/ROW]
[ROW][C]142[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]143[/C][C]10.8[/C][C]11.0769230769231[/C][C]-0.276923076923076[/C][/ROW]
[ROW][C]144[/C][C]9.7[/C][C]11.0769230769231[/C][C]-1.37692307692308[/C][/ROW]
[ROW][C]145[/C][C]11.2[/C][C]11.0769230769231[/C][C]0.123076923076923[/C][/ROW]
[ROW][C]146[/C][C]10.9[/C][C]11.0769230769231[/C][C]-0.176923076923076[/C][/ROW]
[ROW][C]147[/C][C]10.1[/C][C]10.24375[/C][C]-0.143750000000001[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]9.84722222222222[/C][C]-0.847222222222221[/C][/ROW]
[ROW][C]149[/C][C]12[/C][C]12.1692307692308[/C][C]-0.169230769230769[/C][/ROW]
[ROW][C]150[/C][C]9.4[/C][C]9.84722222222222[/C][C]-0.447222222222221[/C][/ROW]
[ROW][C]151[/C][C]11.5[/C][C]9.94814814814815[/C][C]1.55185185185185[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]9.33793103448276[/C][C]0.562068965517241[/C][/ROW]
[ROW][C]153[/C][C]9.4[/C][C]9.84722222222222[/C][C]-0.447222222222221[/C][/ROW]
[ROW][C]154[/C][C]10.4[/C][C]9.84722222222222[/C][C]0.552777777777779[/C][/ROW]
[ROW][C]155[/C][C]9.7[/C][C]9.33793103448276[/C][C]0.36206896551724[/C][/ROW]
[ROW][C]156[/C][C]8.9[/C][C]9.15[/C][C]-0.25[/C][/ROW]
[ROW][C]157[/C][C]8.9[/C][C]9.15[/C][C]-0.25[/C][/ROW]
[ROW][C]158[/C][C]12.4[/C][C]12.1692307692308[/C][C]0.230769230769232[/C][/ROW]
[ROW][C]159[/C][C]12.1[/C][C]12.1692307692308[/C][C]-0.069230769230769[/C][/ROW]
[ROW][C]160[/C][C]12.1[/C][C]12.1692307692308[/C][C]-0.069230769230769[/C][/ROW]
[ROW][C]161[/C][C]12.4[/C][C]12.1692307692308[/C][C]0.230769230769232[/C][/ROW]
[ROW][C]162[/C][C]9.1[/C][C]9.15[/C][C]-0.0500000000000007[/C][/ROW]
[ROW][C]163[/C][C]10.6[/C][C]9.84722222222222[/C][C]0.752777777777778[/C][/ROW]
[ROW][C]164[/C][C]8.9[/C][C]9.15[/C][C]-0.25[/C][/ROW]
[ROW][C]165[/C][C]9.5[/C][C]9.15[/C][C]0.35[/C][/ROW]
[ROW][C]166[/C][C]9.8[/C][C]9.15[/C][C]0.65[/C][/ROW]
[ROW][C]167[/C][C]9.6[/C][C]9.33793103448276[/C][C]0.262068965517241[/C][/ROW]
[ROW][C]168[/C][C]12.6[/C][C]12.1692307692308[/C][C]0.430769230769231[/C][/ROW]
[ROW][C]169[/C][C]9.3[/C][C]9.33793103448276[/C][C]-0.0379310344827584[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]9.94814814814815[/C][C]0.0518518518518523[/C][/ROW]
[ROW][C]171[/C][C]12.7[/C][C]9.84722222222222[/C][C]2.85277777777778[/C][/ROW]
[ROW][C]172[/C][C]11[/C][C]9.84722222222222[/C][C]1.15277777777778[/C][/ROW]
[ROW][C]173[/C][C]11.4[/C][C]11.0769230769231[/C][C]0.323076923076924[/C][/ROW]
[ROW][C]174[/C][C]11.5[/C][C]11.4064516129032[/C][C]0.0935483870967744[/C][/ROW]
[ROW][C]175[/C][C]10.2[/C][C]9.15[/C][C]1.05[/C][/ROW]
[ROW][C]176[/C][C]11.4[/C][C]9.94814814814815[/C][C]1.45185185185185[/C][/ROW]
[ROW][C]177[/C][C]12.6[/C][C]11.0769230769231[/C][C]1.52307692307692[/C][/ROW]
[ROW][C]178[/C][C]9.4[/C][C]9.15[/C][C]0.25[/C][/ROW]
[ROW][C]179[/C][C]8.7[/C][C]9.84722222222222[/C][C]-1.14722222222222[/C][/ROW]
[ROW][C]180[/C][C]9.2[/C][C]9.84722222222222[/C][C]-0.647222222222222[/C][/ROW]
[ROW][C]181[/C][C]9.3[/C][C]9.84722222222222[/C][C]-0.547222222222221[/C][/ROW]
[ROW][C]182[/C][C]9.2[/C][C]9.84722222222222[/C][C]-0.647222222222222[/C][/ROW]
[ROW][C]183[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]184[/C][C]9.6[/C][C]9.15[/C][C]0.449999999999999[/C][/ROW]
[ROW][C]185[/C][C]9.3[/C][C]9.15[/C][C]0.15[/C][/ROW]
[ROW][C]186[/C][C]9.3[/C][C]9.15[/C][C]0.15[/C][/ROW]
[ROW][C]187[/C][C]9.9[/C][C]9.94814814814815[/C][C]-0.0481481481481474[/C][/ROW]
[ROW][C]188[/C][C]11[/C][C]10.24375[/C][C]0.75625[/C][/ROW]
[ROW][C]189[/C][C]12.7[/C][C]12.1692307692308[/C][C]0.530769230769231[/C][/ROW]
[ROW][C]190[/C][C]8.9[/C][C]9.33793103448276[/C][C]-0.437931034482759[/C][/ROW]
[ROW][C]191[/C][C]8.9[/C][C]9.33793103448276[/C][C]-0.437931034482759[/C][/ROW]
[ROW][C]192[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]193[/C][C]11.4[/C][C]9.94814814814815[/C][C]1.45185185185185[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]9.84722222222222[/C][C]-0.247222222222222[/C][/ROW]
[ROW][C]195[/C][C]9.1[/C][C]9.84722222222222[/C][C]-0.747222222222222[/C][/ROW]
[ROW][C]196[/C][C]9.1[/C][C]9.84722222222222[/C][C]-0.747222222222222[/C][/ROW]
[ROW][C]197[/C][C]9.1[/C][C]9.84722222222222[/C][C]-0.747222222222222[/C][/ROW]
[ROW][C]198[/C][C]8.9[/C][C]9.33793103448276[/C][C]-0.437931034482759[/C][/ROW]
[ROW][C]199[/C][C]8.8[/C][C]9.15[/C][C]-0.35[/C][/ROW]
[ROW][C]200[/C][C]8.9[/C][C]9.33793103448276[/C][C]-0.437931034482759[/C][/ROW]
[ROW][C]201[/C][C]9.3[/C][C]9.15[/C][C]0.15[/C][/ROW]
[ROW][C]202[/C][C]8.8[/C][C]9.15[/C][C]-0.35[/C][/ROW]
[ROW][C]203[/C][C]9.6[/C][C]9.15[/C][C]0.449999999999999[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]9.15[/C][C]2.85[/C][/ROW]
[ROW][C]205[/C][C]10.2[/C][C]9.84722222222222[/C][C]0.352777777777778[/C][/ROW]
[ROW][C]206[/C][C]8.8[/C][C]9.15[/C][C]-0.35[/C][/ROW]
[ROW][C]207[/C][C]9.2[/C][C]9.94814814814815[/C][C]-0.748148148148148[/C][/ROW]
[ROW][C]208[/C][C]9.9[/C][C]9.84722222222222[/C][C]0.0527777777777789[/C][/ROW]
[ROW][C]209[/C][C]10.2[/C][C]10.24375[/C][C]-0.0437500000000011[/C][/ROW]
[ROW][C]210[/C][C]9.5[/C][C]9.84722222222222[/C][C]-0.347222222222221[/C][/ROW]
[ROW][C]211[/C][C]10.5[/C][C]9.94814814814815[/C][C]0.551851851851852[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]11.4064516129032[/C][C]-0.206451612903226[/C][/ROW]
[ROW][C]213[/C][C]9.2[/C][C]9.94814814814815[/C][C]-0.748148148148148[/C][/ROW]
[ROW][C]214[/C][C]9.7[/C][C]9.84722222222222[/C][C]-0.147222222222222[/C][/ROW]
[ROW][C]215[/C][C]11.1[/C][C]11.4064516129032[/C][C]-0.306451612903226[/C][/ROW]
[ROW][C]216[/C][C]9.4[/C][C]9.94814814814815[/C][C]-0.548148148148147[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]11.0769230769231[/C][C]-0.0769230769230766[/C][/ROW]
[ROW][C]218[/C][C]9.4[/C][C]9.94814814814815[/C][C]-0.548148148148147[/C][/ROW]
[ROW][C]219[/C][C]9.4[/C][C]9.15[/C][C]0.25[/C][/ROW]
[ROW][C]220[/C][C]11[/C][C]11.0769230769231[/C][C]-0.0769230769230766[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]11.0769230769231[/C][C]-0.0769230769230766[/C][/ROW]
[ROW][C]222[/C][C]9.1[/C][C]9.33793103448276[/C][C]-0.237931034482759[/C][/ROW]
[ROW][C]223[/C][C]11.1[/C][C]11.4064516129032[/C][C]-0.306451612903226[/C][/ROW]
[ROW][C]224[/C][C]9.1[/C][C]10.24375[/C][C]-1.14375[/C][/ROW]
[ROW][C]225[/C][C]10.4[/C][C]9.84722222222222[/C][C]0.552777777777779[/C][/ROW]
[ROW][C]226[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]227[/C][C]9.7[/C][C]9.84722222222222[/C][C]-0.147222222222222[/C][/ROW]
[ROW][C]228[/C][C]9.1[/C][C]9.94814814814815[/C][C]-0.848148148148148[/C][/ROW]
[ROW][C]229[/C][C]9.7[/C][C]9.84722222222222[/C][C]-0.147222222222222[/C][/ROW]
[ROW][C]230[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]231[/C][C]8.9[/C][C]9.33793103448276[/C][C]-0.437931034482759[/C][/ROW]
[ROW][C]232[/C][C]9.6[/C][C]9.94814814814815[/C][C]-0.348148148148148[/C][/ROW]
[ROW][C]233[/C][C]9.5[/C][C]9.94814814814815[/C][C]-0.448148148148148[/C][/ROW]
[ROW][C]234[/C][C]9[/C][C]9.15[/C][C]-0.15[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]9.15[/C][C]-0.15[/C][/ROW]
[ROW][C]236[/C][C]9[/C][C]9.15[/C][C]-0.15[/C][/ROW]
[ROW][C]237[/C][C]9[/C][C]9.15[/C][C]-0.15[/C][/ROW]
[ROW][C]238[/C][C]9.6[/C][C]9.15[/C][C]0.449999999999999[/C][/ROW]
[ROW][C]239[/C][C]11.1[/C][C]11.4064516129032[/C][C]-0.306451612903226[/C][/ROW]
[ROW][C]240[/C][C]9.6[/C][C]9.15[/C][C]0.449999999999999[/C][/ROW]
[ROW][C]241[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]242[/C][C]10.4[/C][C]9.94814814814815[/C][C]0.451851851851853[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]11.4064516129032[/C][C]-0.00645161290322527[/C][/ROW]
[ROW][C]244[/C][C]9.7[/C][C]9.84722222222222[/C][C]-0.147222222222222[/C][/ROW]
[ROW][C]245[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]246[/C][C]11.3[/C][C]11.0769230769231[/C][C]0.223076923076924[/C][/ROW]
[ROW][C]247[/C][C]12.6[/C][C]11.4064516129032[/C][C]1.19354838709677[/C][/ROW]
[ROW][C]248[/C][C]10.9[/C][C]11.4064516129032[/C][C]-0.506451612903225[/C][/ROW]
[ROW][C]249[/C][C]10.9[/C][C]11.4064516129032[/C][C]-0.506451612903225[/C][/ROW]
[ROW][C]250[/C][C]10[/C][C]9.94814814814815[/C][C]0.0518518518518523[/C][/ROW]
[ROW][C]251[/C][C]10[/C][C]9.84722222222222[/C][C]0.152777777777779[/C][/ROW]
[ROW][C]252[/C][C]9.8[/C][C]9.15[/C][C]0.65[/C][/ROW]
[ROW][C]253[/C][C]8.7[/C][C]9.15[/C][C]-0.450000000000001[/C][/ROW]
[ROW][C]254[/C][C]11.7[/C][C]11.0769230769231[/C][C]0.623076923076923[/C][/ROW]
[ROW][C]255[/C][C]9.3[/C][C]9.84722222222222[/C][C]-0.547222222222221[/C][/ROW]
[ROW][C]256[/C][C]9.6[/C][C]11.4064516129032[/C][C]-1.80645161290323[/C][/ROW]
[ROW][C]257[/C][C]11[/C][C]12.1692307692308[/C][C]-1.16923076923077[/C][/ROW]
[ROW][C]258[/C][C]11[/C][C]12.1692307692308[/C][C]-1.16923076923077[/C][/ROW]
[ROW][C]259[/C][C]11.8[/C][C]11.0769230769231[/C][C]0.723076923076924[/C][/ROW]
[ROW][C]260[/C][C]11.4[/C][C]11.0769230769231[/C][C]0.323076923076924[/C][/ROW]
[ROW][C]261[/C][C]10.2[/C][C]9.84722222222222[/C][C]0.352777777777778[/C][/ROW]
[ROW][C]262[/C][C]8.9[/C][C]9.15[/C][C]-0.25[/C][/ROW]
[ROW][C]263[/C][C]10.2[/C][C]9.94814814814815[/C][C]0.251851851851852[/C][/ROW]
[ROW][C]264[/C][C]9.6[/C][C]9.15[/C][C]0.449999999999999[/C][/ROW]
[ROW][C]265[/C][C]10.6[/C][C]11.0769230769231[/C][C]-0.476923076923077[/C][/ROW]
[ROW][C]266[/C][C]8.9[/C][C]9.15[/C][C]-0.25[/C][/ROW]
[ROW][C]267[/C][C]9.2[/C][C]9.33793103448276[/C][C]-0.13793103448276[/C][/ROW]
[ROW][C]268[/C][C]9.7[/C][C]10.24375[/C][C]-0.543750000000001[/C][/ROW]
[ROW][C]269[/C][C]9.7[/C][C]9.94814814814815[/C][C]-0.248148148148148[/C][/ROW]
[ROW][C]270[/C][C]9.7[/C][C]9.84722222222222[/C][C]-0.147222222222222[/C][/ROW]
[ROW][C]271[/C][C]9.2[/C][C]9.33793103448276[/C][C]-0.13793103448276[/C][/ROW]
[ROW][C]272[/C][C]9.7[/C][C]10.24375[/C][C]-0.543750000000001[/C][/ROW]
[ROW][C]273[/C][C]9.3[/C][C]9.15[/C][C]0.15[/C][/ROW]
[ROW][C]274[/C][C]9[/C][C]9.84722222222222[/C][C]-0.847222222222221[/C][/ROW]
[ROW][C]275[/C][C]9.5[/C][C]9.15[/C][C]0.35[/C][/ROW]
[ROW][C]276[/C][C]9.8[/C][C]9.94814814814815[/C][C]-0.148148148148147[/C][/ROW]
[ROW][C]277[/C][C]9.8[/C][C]9.94814814814815[/C][C]-0.148148148148147[/C][/ROW]
[ROW][C]278[/C][C]10.6[/C][C]11.0769230769231[/C][C]-0.476923076923077[/C][/ROW]
[ROW][C]279[/C][C]10.6[/C][C]10.24375[/C][C]0.356249999999999[/C][/ROW]
[ROW][C]280[/C][C]12.4[/C][C]11.4064516129032[/C][C]0.993548387096775[/C][/ROW]
[ROW][C]281[/C][C]12.6[/C][C]11.4064516129032[/C][C]1.19354838709677[/C][/ROW]
[ROW][C]282[/C][C]12.3[/C][C]11.4064516129032[/C][C]0.893548387096775[/C][/ROW]
[ROW][C]283[/C][C]10.5[/C][C]9.84722222222222[/C][C]0.652777777777779[/C][/ROW]
[ROW][C]284[/C][C]9.3[/C][C]9.15[/C][C]0.15[/C][/ROW]
[ROW][C]285[/C][C]8.8[/C][C]9.15[/C][C]-0.35[/C][/ROW]
[ROW][C]286[/C][C]8.8[/C][C]9.33793103448276[/C][C]-0.537931034482758[/C][/ROW]
[ROW][C]287[/C][C]9.7[/C][C]9.15[/C][C]0.549999999999999[/C][/ROW]
[ROW][C]288[/C][C]9[/C][C]9.15[/C][C]-0.15[/C][/ROW]
[ROW][C]289[/C][C]9[/C][C]9.15[/C][C]-0.15[/C][/ROW]
[ROW][C]290[/C][C]9[/C][C]9.15[/C][C]-0.15[/C][/ROW]
[ROW][C]291[/C][C]9[/C][C]9.15[/C][C]-0.15[/C][/ROW]
[ROW][C]292[/C][C]10.5[/C][C]10.24375[/C][C]0.25625[/C][/ROW]
[ROW][C]293[/C][C]9.1[/C][C]9.15[/C][C]-0.0500000000000007[/C][/ROW]
[ROW][C]294[/C][C]9.8[/C][C]9.94814814814815[/C][C]-0.148148148148147[/C][/ROW]
[ROW][C]295[/C][C]8.5[/C][C]9.84722222222222[/C][C]-1.34722222222222[/C][/ROW]
[ROW][C]296[/C][C]9.4[/C][C]9.84722222222222[/C][C]-0.447222222222221[/C][/ROW]
[ROW][C]297[/C][C]9.4[/C][C]9.15[/C][C]0.25[/C][/ROW]
[ROW][C]298[/C][C]11.2[/C][C]11.4064516129032[/C][C]-0.206451612903226[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154783&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154783&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
18.89.15-0.35
29.59.84722222222222-0.347222222222221
310.19.847222222222220.252777777777778
49.99.337931034482760.562068965517241
59.99.337931034482760.562068965517241
610.19.847222222222220.252777777777778
79.69.84722222222222-0.247222222222222
88.89.15-0.35
99.59.84722222222222-0.347222222222221
101111.0769230769231-0.0769230769230766
111211.07692307692310.923076923076923
129.711.0769230769231-1.37692307692308
1310.811.0769230769231-0.276923076923076
1412.411.40645161290320.993548387096775
159.79.150.549999999999999
1611.411.4064516129032-0.00645161290322527
179.69.84722222222222-0.247222222222222
1812.812.16923076923080.630769230769232
1911.311.07692307692310.223076923076924
209.59.94814814814815-0.448148148148148
2112.812.16923076923080.630769230769232
221111.4064516129032-0.406451612903226
2310.511.4064516129032-0.906451612903226
249.39.84722222222222-0.547222222222221
25109.847222222222220.152777777777779
2610.49.948148148148150.451851851851853
27109.847222222222220.152777777777779
2810.59.337931034482761.16206896551724
2911.69.847222222222221.75277777777778
3012.312.16923076923080.130769230769232
31109.948148148148150.0518518518518523
3210.210.24375-0.0437500000000011
3310.89.847222222222220.952777777777779
3499.84722222222222-0.847222222222221
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15410.49.847222222222220.552777777777779
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1829.29.84722222222222-0.647222222222222
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1869.39.150.15
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1881110.243750.75625
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1918.99.33793103448276-0.437931034482759
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1949.69.84722222222222-0.247222222222222
1959.19.84722222222222-0.747222222222222
1969.19.84722222222222-0.747222222222222
1979.19.84722222222222-0.747222222222222
1988.99.33793103448276-0.437931034482759
1998.89.15-0.35
2008.99.33793103448276-0.437931034482759
2019.39.150.15
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24810.911.4064516129032-0.506451612903225
24910.911.4064516129032-0.506451612903225
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2571112.1692307692308-1.16923076923077
2581112.1692307692308-1.16923076923077
25911.811.07692307692310.723076923076924
26011.411.07692307692310.323076923076924
26110.29.847222222222220.352777777777778
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2709.79.84722222222222-0.147222222222222
2719.29.33793103448276-0.13793103448276
2729.710.24375-0.543750000000001
2739.39.150.15
27499.84722222222222-0.847222222222221
2759.59.150.35
2769.89.94814814814815-0.148148148148147
2779.89.94814814814815-0.148148148148147
27810.611.0769230769231-0.476923076923077
27910.610.243750.356249999999999
28012.411.40645161290320.993548387096775
28112.611.40645161290321.19354838709677
28212.311.40645161290320.893548387096775
28310.59.847222222222220.652777777777779
2849.39.150.15
2858.89.15-0.35
2868.89.33793103448276-0.537931034482758
2879.79.150.549999999999999
28899.15-0.15
28999.15-0.15
29099.15-0.15
29199.15-0.15
29210.510.243750.25625
2939.19.15-0.0500000000000007
2949.89.94814814814815-0.148148148148147
2958.59.84722222222222-1.34722222222222
2969.49.84722222222222-0.447222222222221
2979.49.150.25
29811.211.4064516129032-0.206451612903226


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 10 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 10 ; par2 = none ; par3 = 3 ; par4 = no ;
R code (references can be found in the software module):
library(party)
library(Hmisc)
par1 <- as.numeric(par1)
par3 <- as.numeric(par3)
x <- data.frame(t(y))
is.data.frame(x)
x <- x[!is.na(x[,par1]),]
k <- length(x[1,])
n <- length(x[,1])
colnames(x)[par1]
x[,par1]
if (par2 == 'kmeans') {
cl <- kmeans(x[,par1], par3)
print(cl)
clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
clm <- clm[sort.list(clm[,1]),]
for (i in 1:par3) {
cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
}
cl$cluster <- as.factor(cl$cluster)
print(cl$cluster)
x[,par1] <- cl$cluster
}
if (par2 == 'quantiles') {
x[,par1] <- cut2(x[,par1],g=par3)
}
if (par2 == 'hclust') {
hc <- hclust(dist(x[,par1])^2, 'cen')
print(hc)
memb <- cutree(hc, k = par3)
dum <- c(mean(x[memb==1,par1]))
for (i in 2:par3) {
dum <- c(dum, mean(x[memb==i,par1]))
}
hcm <- matrix(cbind(dum,1:par3),ncol=2)
hcm <- hcm[sort.list(hcm[,1]),]
for (i in 1:par3) {
memb[memb==hcm[i,2]] <- paste('C',i,sep='')
}
memb <- as.factor(memb)
print(memb)
x[,par1] <- memb
}
if (par2=='equal') {
ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
x[,par1] <- as.factor(ed)
}
table(x[,par1])
colnames(x)
colnames(x)[par1]
x[,par1]
if (par2 == 'none') {
m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
}
load(file='createtable')
if (par2 != 'none') {
m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
if (par4=='yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
a<-table.element(a,'Prediction (training)',par3+1,TRUE)
a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Actual',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
a<-table.row.end(a)
for (i in 1:10) {
ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
if (i==1) {
m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
m.ct.i.actu <- x[ind==1,par1]
m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
m.ct.x.actu <- x[ind==2,par1]
} else {
m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
}
}
print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
numer <- numer + m.ct.i.tab[i,i]
}
print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
numer <- numer + m.ct.x.tab[i,i]
}
print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'Overall',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.i.cp,4))
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.x.cp,4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
}
}
m
bitmap(file='test1.png')
plot(m)
dev.off()
bitmap(file='test1a.png')
plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
dev.off()
if (par2 == 'none') {
forec <- predict(m)
result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
colnames(result) <- c('Actuals','Forecasts','Residuals')
print(result)
}
if (par2 != 'none') {
print(cbind(as.factor(x[,par1]),predict(m)))
myt <- table(as.factor(x[,par1]),predict(m))
print(myt)
}
bitmap(file='test2.png')
if(par2=='none') {
op <- par(mfrow=c(2,2))
plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
par(op)
}
if(par2!='none') {
plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
}
dev.off()
if (par2 == 'none') {
detcoef <- cor(result$Forecasts,result$Actuals)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goodness of Fit',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',1,TRUE)
a<-table.element(a,round(detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'R-squared',1,TRUE)
a<-table.element(a,round(detcoef*detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'RMSE',1,TRUE)
a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#',header=TRUE)
a<-table.element(a,'Actuals',header=TRUE)
a<-table.element(a,'Forecasts',header=TRUE)
a<-table.element(a,'Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(result$Actuals)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,result$Actuals[i])
a<-table.element(a,result$Forecasts[i])
a<-table.element(a,result$Residuals[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
}
if (par2 != 'none') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
for (i in 1:par3) {
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (j in 1:par3) {
a<-table.element(a,myt[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}