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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 16 Dec 2014 15:14:22 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/16/t141874287780h5pujy8qop70i.htm/, Retrieved Thu, 16 May 2024 11:57:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269694, Retrieved Thu, 16 May 2024 11:57:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Paired and Unpaired Two Samples Tests about the Mean] [BS] [2014-12-11 09:49:38] [2568c9326b0361ae14a2b722dbd6de4e]
- RMPD    [Multiple Regression] [] [2014-12-16 15:14:22] [72ee53c6f28232e74174360ca89644de] [Current]
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Dataset

Dataseries X:
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Histogram
Boxplots 
1	0	11	8	7	18	12	20	4	1	0.5	0.67	0.67	0	149	96	86	12.9
1	1	19	18	20	23	20	19	4	0.89	0.5	0.83	0.33	0.5	139	70	70	12.2
1	0	16	12	9	22	14	18	5	0.89	0.4	1	0.67	0	148	88	71	12.8
1	1	24	24	19	22	25	24	4	0.89	0.5	0.83	0	0	158	114	108	7.4
1	1	15	16	12	19	15	20	4	0.89	0.7	0.67	0	1	128	69	64	6.7
1	1	17	19	16	25	20	20	9	0.78	0.3	0	0	0.5	224	176	119	12.6
1	0	19	16	17	28	21	24	8	0.89	0.4	0.83	0.67	0.5	159	114	97	14.8
1	1	19	15	9	16	15	21	11	1	0.4	0.5	0.67	1	105	121	129	13.3
1	1	28	28	28	28	28	28	4	0.89	0.7	0.83	0	0.5	159	110	153	11.1
1	1	26	21	20	21	11	10	4	0.78	0.6	0.33	0.67	0.5	167	158	78	8.2
1	1	15	18	16	22	22	22	6	1	0.6	0.5	1	0	165	116	80	11.4
1	1	26	22	22	24	22	19	4	0.78	0.2	0.67	0	0.5	159	181	99	6.4
1	1	16	19	17	24	27	27	8	0.89	0.4	1	0	0.5	119	77	68	10.6
1	0	24	22	12	26	24	23	4	0.89	0.4	0.5	0.67	0	176	141	147	12
1	0	25	25	18	28	23	24	4	0.89	0.5	0.67	0.33	0	54	35	40	6.3
0	0	22	20	20	24	24	24	11	0.89	0.3	0.17	0.67	0	91	80	57	11.3
1	1	15	16	12	20	21	25	4	0.89	0.4	0.83	0.33	0.5	163	152	120	11.9
1	0	21	19	16	26	20	24	4	0.67	0.7	0.67	0.33	0.5	124	97	71	9.3
0	1	22	18	16	21	19	21	6	1	0.5	0.67	0.33	0	137	99	84	9.6
1	0	27	26	21	28	25	28	6	0.78	0.2	0.67	0	0	121	84	68	10
1	1	26	24	15	27	16	28	4	0.78	0.3	0.5	0.67	0	153	68	55	6.4
1	1	26	20	17	23	24	22	8	0.89	0.6	1	0.33	0	148	101	137	13.8
1	0	22	19	17	24	21	26	5	0.78	0.6	0.83	0.33	0	221	107	79	10.8
1	1	21	19	17	24	22	26	4	0.89	0.2	0.83	0.33	0	188	88	116	13.8
1	1	22	23	18	22	25	21	9	0.89	0.7	1	0.67	1	149	112	101	11.7
1	1	20	18	15	21	23	26	4	0.33	0.2	0.67	0	0	244	171	111	10.9
0	1	21	16	20	25	20	23	7	1	1	1	0.33	1	148	137	189	16.1
0	0	20	18	13	20	21	20	10	0.89	0.4	0.83	0.67	0	92	77	66	13.4
1	1	22	21	21	21	22	24	4	0.89	0.4	1	1	0	150	66	81	9.9
1	0	21	20	12	26	25	25	4	0.67	0.2	0.83	0.67	0	153	93	63	11.5
1	0	8	15	6	23	23	24	7	0.56	0.4	0.67	0.33	0	94	105	69	8.3
1	0	22	19	13	21	19	20	12	0.89	0.4	0.67	0	0.5	156	131	71	11.7
1	1	20	19	19	27	21	24	7	0.89	0.7	1	0.67	0.5	132	102	64	9
1	1	24	7	12	25	19	25	5	1	0.2	0.67	0.67	0	161	161	143	9.7
1	1	17	20	14	23	25	23	8	0.78	0.6	1	1	0	105	120	85	10.8
1	1	20	20	13	25	16	21	5	0.78	0.3	1	1	0.5	97	127	86	10.3
1	0	23	19	12	23	24	23	4	0.33	0.3	0.5	0.33	0	151	77	55	10.4
0	1	20	19	17	19	24	21	9	0.78	0.2	0.67	0	0.5	131	108	69	12.7
1	1	22	20	19	22	18	18	7	0.89	0.5	0.83	0.67	0.5	166	85	120	9.3
1	0	19	18	10	24	28	24	4	0.89	0.7	1	0.67	0.5	157	168	96	11.8
1	1	15	14	10	19	15	18	4	0.78	0.6	1	0.67	0.5	111	48	60	5.9
1	1	20	17	11	21	17	21	4	0.89	0.4	1	0.67	0.5	145	152	95	11.4
1	1	22	17	11	27	18	23	4	0.89	0.6	1	0.33	0.5	162	75	100	13
1	1	17	8	10	25	26	25	4	1	0.4	1	1	0	163	107	68	10.8
0	1	14	9	7	25	18	22	7	0.67	0.3	0.83	0.67	0	59	62	57	12.3
1	0	24	22	22	23	22	22	4	1	0.5	0.83	0.67	0.5	187	121	105	11.3
1	1	17	20	12	17	19	23	7	0.89	0.2	0.5	0	0	109	124	85	11.8
0	1	23	20	18	28	17	24	4	0.89	0.3	0.83	0	0.5	90	72	103	7.9
1	0	25	22	20	25	26	25	4	0.89	0.5	0.17	0	0	105	40	57	12.7
0	1	16	22	9	20	21	22	4	0.78	0.7	0.83	1	0.5	83	58	51	12.3
0	1	18	22	16	25	26	24	4	0.89	0.4	1	0.67	1	116	97	69	11.6
0	1	20	16	14	21	21	21	8	0.78	0.3	1	0	0	42	88	41	6.7
1	1	18	14	11	24	12	24	4	0.78	0.2	0.67	0.67	1	148	126	49	10.9
0	1	23	24	20	28	20	25	4	1	0.5	1	0	0	155	104	50	12.1
1	1	24	21	17	20	20	23	4	0.78	0.4	1	0	0.5	125	148	93	13.3
1	1	23	20	14	19	24	27	4	1	0.6	1	0.67	1	116	146	58	10.1
0	0	13	20	8	24	24	27	7	0.78	0.4	0.83	1	0	128	80	54	5.7
1	1	20	18	16	21	22	23	12	0.67	0.4	0.33	0	0	138	97	74	14.3
0	0	20	14	11	24	21	18	4	0.33	0.2	0.33	0.33	0	49	25	15	8
0	1	19	19	10	23	20	20	4	1	0.9	1	0.67	0.5	96	99	69	13.3
1	1	22	24	15	18	23	23	4	1	0.8	1	0.67	1	164	118	107	9.3
1	0	22	19	15	27	19	24	5	0.78	0.8	0.83	0	0.5	162	58	65	12.5
1	0	15	16	10	25	24	26	15	0.67	0.3	1	1	0.5	99	63	58	7.6
1	1	17	16	10	20	21	20	5	1	0.2	0.83	0.67	0	202	139	107	15.9
1	0	19	16	18	21	16	23	10	0.89	0.4	0.67	0	0.5	186	50	70	9.2
0	1	20	14	10	23	17	22	9	0.89	0.2	0.83	1	0	66	60	53	9.1
1	0	22	22	22	27	23	23	8	0.78	0.2	0.67	0.67	0.5	183	152	136	11.1
1	1	21	21	16	24	20	17	4	1	0.1	0.83	0.67	0	214	142	126	13
1	1	21	15	10	27	19	20	5	0.56	0.4	0.67	1	0.5	188	94	95	14.5
0	0	16	14	7	24	18	22	4	0.67	0.5	1	0	0.5	104	66	69	12.2
1	0	20	15	16	23	18	18	9	0.89	0.8	0.83	0.33	0.5	177	127	136	12.3
1	0	21	14	16	24	21	19	4	0.89	0.4	0.67	0.67	0	126	67	58	11.4
0	0	20	20	16	21	20	19	10	0.89	0.6	0.83	0.33	0.5	76	90	59	8.8
0	1	23	21	22	23	17	16	4	0.89	0.5	0.83	0.67	0.5	99	75	118	14.6
1	0	18	14	5	27	25	26	4	0.78	0.3	0.67	0	0	139	128	82	12.6
1	1	22	19	18	24	15	14	6	0.89	0.8	1	1	0.5	78	41	50	NA
1	0	16	16	10	25	17	25	7	1	0.4	0.33	0	0.5	162	146	102	13
0	1	17	13	8	19	17	23	5	1	0.6	0.83	0.67	0.5	108	69	65	12.6
1	0	24	26	16	24	24	18	4	0.89	0.4	1	0.33	0	159	186	90	13.2
0	0	13	13	8	25	21	22	4	0.44	0.3	0.83	0	0	74	81	64	9.9
1	1	19	18	16	23	22	26	4	0.78	0.8	0.83	0	1	110	85	83	7.7
0	0	20	15	14	23	18	25	4	0.89	0.6	0.5	0.33	1	96	54	70	10.5
0	0	22	18	15	25	22	26	4	0.67	0.3	0.5	0	0	116	46	50	13.4
0	0	19	21	9	26	20	26	4	0.78	0.5	0.83	0.67	0.5	87	106	77	10.9
0	1	21	17	21	26	21	24	6	0.78	0.4	1	0.33	0	97	34	37	4.3
0	0	15	18	7	16	21	22	10	0.33	0.3	0.33	0.67	0	127	60	81	10.3
0	1	21	20	17	23	20	21	7	0.89	0.7	1	0.33	0	106	95	101	11.8
0	1	24	18	18	26	18	22	4	0.89	0.2	0.67	0.33	0.5	80	57	79	11.2
0	0	22	25	16	25	25	28	4	0.89	0.4	0.83	1	0	74	62	71	11.4
0	0	20	20	16	23	23	22	7	0.89	0.6	1	0.67	0.5	91	36	60	8.6
0	0	21	19	14	26	21	26	4	0.56	0.6	0.83	0	0	133	56	55	13.2
0	1	19	18	15	22	20	20	8	0.67	0.6	0.83	0.67	0.5	74	54	44	12.6
0	1	14	12	8	20	21	24	11	0.67	0.4	1	0.33	0.5	114	64	40	5.6
0	1	25	22	22	27	20	21	6	0.78	0.6	0.83	0	0	140	76	56	9.9
0	0	11	16	5	20	22	23	14	0.78	0.5	1	0.33	0.5	95	98	43	8.8
0	1	17	18	13	22	15	23	5	0.78	0.5	0.83	0	0	98	88	45	7.7
0	0	22	23	22	24	24	23	4	0.89	0.6	0.67	0	0	121	35	32	9
0	1	20	20	18	21	22	22	8	1	0.8	0.83	0.33	0.5	126	102	56	7.3
0	1	22	20	15	24	21	23	9	0.89	0.5	0.83	0.67	1	98	61	40	11.4
0	1	15	16	11	26	17	21	4	0.89	0.6	0.83	0.67	0.5	95	80	34	13.6
0	1	23	22	19	24	23	27	4	0.78	0.4	0.83	0.67	0.5	110	49	89	7.9
0	1	20	19	19	24	22	23	5	1	0.3	0.67	0.67	0.5	70	78	50	10.7
0	0	22	23	21	27	23	26	4	0.78	0.3	0.83	1	0	102	90	56	10.3
0	1	16	6	4	25	16	27	5	0.67	0.2	0	0	0	86	45	46	8.3
0	1	25	19	17	27	18	27	4	0.78	0.4	0.83	0	0	130	55	76	9.6
0	1	18	24	10	19	25	23	4	0.89	0.5	1	0	0	96	96	64	14.2
0	0	19	19	13	22	18	23	7	0.67	0.3	0.17	0	0.5	102	43	74	8.5
0	0	25	15	15	22	14	23	10	0.22	0.4	0.17	0	0.5	100	52	57	13.5
0	0	21	18	11	25	20	28	4	0.44	0.5	0.5	1	0	94	60	45	4.9
0	0	22	18	20	23	19	24	5	0.89	0.3	0.5	0.67	0	52	54	30	6.4
0	0	21	22	13	24	18	20	4	0.67	0.5	1	0	0	98	51	62	9.6
0	0	22	23	18	24	22	23	4	0.89	0.4	0.67	0.67	0	118	51	51	11.6
0	1	23	18	20	23	21	22	4	0.67	0.4	0.83	0.67	0	99	38	36	11.1
1	1	20	17	15	22	14	15	6	0.78	0.6	1	0	1	48	41	34	4.35
1	1	6	6	4	24	5	27	4	0.78	0.3	1	0.67	1	50	146	61	12.7
1	1	15	22	9	19	25	23	8	0.78	0.4	1	0.33	1	150	182	70	18.1
1	1	18	20	18	25	21	23	5	1	0.3	1	1	1	154	192	69	17.85
0	0	24	16	12	26	11	20	4	0.78	1	1	1	1	109	263	145	16.6
0	1	22	16	17	18	20	18	17	0.67	0.4	1	0	0	68	35	23	12.6
1	1	21	17	12	24	9	22	4	0.89	0.8	0.83	1	0.5	194	439	120	17.1
1	0	23	20	16	28	15	20	4	0.89	0.3	1	0.67	1	158	214	147	19.1
1	1	20	23	17	23	23	21	8	1	0.5	0.83	0.67	0	159	341	215	16.1
1	0	20	18	14	19	21	25	4	0.78	0.4	1	0	0	67	58	24	13.35
1	0	18	13	13	19	9	19	7	0.67	0.3	0.83	0.67	0	147	292	84	18.4
1	1	25	22	20	27	24	25	4	0.89	0.5	0.83	1	0	39	85	30	14.7
1	1	16	20	16	24	16	24	4	0.67	0.3	1	0.67	0	100	200	77	10.6
1	1	20	20	15	26	20	22	5	0.67	0.3	0.67	0	0	111	158	46	12.6
1	1	14	13	10	21	15	28	7	1	0.4	0.83	0	0	138	199	61	16.2
1	1	22	16	16	25	18	22	4	0.67	0.3	1	0	0	101	297	178	13.6
0	1	26	25	21	28	22	21	4	1	0.6	1	0.33	0.5	131	227	160	18.9
1	1	20	16	15	19	21	23	7	0.89	0.6	0.83	0.67	1	101	108	57	14.1
1	1	17	15	16	20	21	19	11	0.89	0.4	1	1	1	114	86	42	14.5
1	0	22	19	19	26	21	21	7	1	0.4	1	0	0	165	302	163	16.15
1	1	22	19	9	27	20	25	4	0.67	0.4	1	0.67	0	114	148	75	14.75
1	1	20	24	19	23	24	23	4	0.44	0.3	0.67	0.67	0.5	111	178	94	14.8
1	1	17	9	7	18	15	28	4	0.89	0.2	1	0.33	1	75	120	45	12.45
1	1	22	22	23	23	24	14	4	0.56	0.5	0.83	0.67	0	82	207	78	12.65
1	1	17	15	14	21	18	23	4	0.78	0.4	1	0.67	1	121	157	47	17.35
1	1	22	22	10	23	24	24	4	1	0.4	1	0.67	0	32	128	29	8.6
1	0	21	22	16	22	24	25	6	1	0.4	0.83	0.67	0	150	296	97	18.4
1	1	25	24	12	21	15	15	8	0.89	0.3	0.67	0.67	0.5	117	323	116	16.1
0	1	11	12	10	14	19	23	23	0.67	0.4	0.83	0.67	1	71	79	32	11.6
1	1	19	21	7	24	20	26	4	0.89	0.2	1	0.33	0.5	165	70	50	17.75
1	1	24	25	20	26	26	21	8	0.33	0	0	0	0	154	146	118	15.25
1	1	17	26	9	24	26	26	6	0.89	0.4	1	0.67	0.5	126	246	66	17.65
1	0	22	21	12	22	23	23	4	0.78	0.6	1	0	1	149	196	86	16.35
1	0	17	14	10	20	13	15	7	1	0.4	0.67	0.67	0	145	199	89	17.65
1	1	26	28	19	20	16	16	4	0.44	0.4	1	0	0	120	127	76	13.6
1	0	20	21	11	18	22	20	4	0.67	0.4	0.83	0	0.5	109	153	75	14.35
1	0	19	16	15	18	21	20	4	0.33	0.2	0.17	0	0.5	132	299	57	14.75
1	1	21	16	14	25	11	21	10	0.89	0.4	0.83	1	1	172	228	72	18.25
1	0	24	25	11	28	23	28	6	0.89	0.3	0.83	0	0	169	190	60	9.9
1	1	21	21	14	23	18	19	5	1	0.6	0.83	0.67	1	114	180	109	16
1	1	19	22	15	20	19	21	5	0.89	0.6	0.83	1	0	156	212	76	18.25
1	0	13	9	7	22	15	22	4	0.89	0.4	0.83	0	0	172	269	65	16.85
0	1	24	20	22	27	8	27	4	1	0.5	1	0.67	1	68	130	40	14.6
0	1	28	19	19	24	15	20	5	0.89	0.4	0.83	0	0.5	89	179	58	13.85
1	1	27	24	22	23	21	17	5	1	0.6	1	1	1	167	243	123	18.95
1	0	22	22	11	20	25	26	5	0.78	0.6	0.83	0.67	0.5	113	190	71	15.6
0	0	23	22	19	22	14	21	5	0.78	0.9	1	0.67	0.5	115	299	102	14.85
0	0	19	12	9	21	21	24	4	0.67	0.4	0.83	0.67	0.5	78	121	80	11.75
0	0	18	17	11	24	18	21	6	0.89	0.8	1	1	0.5	118	137	97	18.45
0	1	23	18	17	26	18	25	4	0.67	0.5	0.83	1	0	87	305	46	15.9
1	0	21	10	12	24	12	22	4	0.78	0.4	0.83	1	0	173	157	93	17.1
1	1	22	22	17	18	24	17	4	0.89	0.4	1	0.67	1	2	96	19	16.1
0	0	17	24	10	17	17	14	9	0.89	0.7	1	1	1	162	183	140	19.9
0	1	15	18	17	23	20	23	18	0.78	0.4	1	0.33	1	49	52	78	10.95
0	0	21	18	13	21	24	28	6	1	0.8	1	0.67	0.5	122	238	98	18.45
0	1	20	23	11	21	22	24	5	1	0.4	1	1	1	96	40	40	15.1
0	0	26	21	19	24	15	22	4	1	0.3	1	0.67	0	100	226	80	15
0	0	19	21	21	22	22	24	11	0.67	0.5	1	0.67	0.5	82	190	76	11.35
0	1	28	28	24	24	26	25	4	0.89	0.8	1	0.67	1	100	214	79	15.95
0	0	21	17	13	24	17	21	10	1	0.4	0.83	0.33	0	115	145	87	18.1
0	1	19	21	16	24	23	22	6	1	1	1	1	0.5	141	119	95	14.6
1	1	22	21	13	23	19	16	8	0.89	0.5	1	0.67	1	165	222	49	15.4
1	1	21	20	15	21	21	18	8	0.89	0.5	1	0.67	1	165	222	49	15.4
0	1	20	18	15	24	23	27	6	0.89	0.3	1	0.33	0	110	159	80	17.6
1	1	19	17	11	19	19	17	8	0.89	0.3	0.83	0.33	0.5	118	165	86	13.35
1	0	11	7	7	19	18	25	4	0.89	0.3	0.5	0	0	158	249	69	19.1
0	1	17	17	13	23	16	24	4	1	0.4	0.67	0.33	0.5	146	125	79	15.35
1	0	19	14	13	25	23	21	9	0.67	0.5	1	0.33	0	49	122	52	7.6
0	0	20	18	12	24	13	21	9	1	0.5	0.67	0.67	0.5	90	186	120	13.4
0	0	17	14	8	21	18	19	5	0.89	0.4	1	0	0	121	148	69	13.9
1	1	21	23	7	18	23	27	4	0.89	0.7	1	1	0.5	155	274	94	19.1
0	0	21	20	17	23	21	28	4	0.89	0.5	0.5	0.33	0	104	172	72	15.25
0	1	12	14	9	20	23	19	15	0.89	0.4	0.67	0.33	1	147	84	43	12.9
0	0	23	17	18	23	16	23	10	1	0.7	0.67	1	0	110	168	87	16.1
0	0	22	21	17	23	17	25	9	1	0.7	0.67	1	0	108	102	52	17.35
0	0	22	23	17	23	20	26	7	1	0.7	0.67	1	0	113	106	71	13.15
0	0	21	24	18	23	18	25	9	0.89	0.7	0.67	1	0	115	2	61	12.15
0	1	20	21	12	27	20	25	6	0.89	0.7	0.67	0	0	61	139	51	12.6
0	1	18	14	14	19	19	24	4	0.89	0.7	1	0.67	0.5	60	95	50	10.35
0	1	21	24	22	25	26	24	7	0.33	0.1	0.67	0.33	0.5	109	130	67	15.4
0	1	24	16	19	25	9	24	4	0.67	0.2	0.67	0.67	0.5	68	72	30	9.6
0	0	22	21	21	21	23	22	7	0.56	0.3	0.33	0.33	0	111	141	70	18.2
0	0	20	8	10	25	9	21	4	0.44	0.6	0.83	0.33	0	77	113	52	13.6
0	1	17	17	16	17	13	17	15	1	0.8	1	1	1	73	206	75	14.85
1	0	19	18	11	22	27	23	4	0.89	0.8	1	0.33	0.5	151	268	87	14.75
0	0	16	17	15	23	22	17	9	0.33	0	0.17	0	0	89	175	69	14.1
0	0	19	16	12	27	12	25	4	0.67	0.3	0.67	0.33	0	78	77	72	14.9
0	0	23	22	21	27	18	19	4	0.67	0.6	0.83	0.33	0.5	110	125	79	16.25
1	1	8	17	22	5	6	8	28	1	0.5	0.83	0.67	0	220	255	121	19.25
0	1	22	21	20	19	17	14	4	0.78	0.7	1	0.33	0	65	111	43	13.6
1	0	23	20	15	24	22	22	4	0.67	0.3	0.83	0	0.5	141	132	58	13.6
0	0	15	20	9	23	22	25	4	1	0.3	1	0.67	0	117	211	57	15.65
1	1	17	19	15	28	23	28	5	0.78	0.4	1	0.67	0	122	92	50	12.75
0	0	21	8	14	25	19	25	4	0.89	0.4	0.83	1	0	63	76	69	14.6
1	1	25	19	11	27	20	24	4	0.89	0.1	0.83	0	0	44	171	64	9.85
0	1	18	11	9	16	17	15	12	0.89	0.5	1	0.67	0	52	83	38	12.65
0	0	20	13	12	25	24	24	4	0	0	0	0	0	131	266	90	19.2
0	1	21	18	11	26	20	28	6	0.67	0.4	1	0.33	0.5	101	186	96	16.6
0	1	21	19	14	24	18	24	6	1	0.6	0.83	0.67	1	42	50	49	11.2
1	1	24	23	10	23	23	25	5	1	0.4	1	0.33	0.5	152	117	56	15.25
1	0	22	20	18	24	27	23	4	0.67	0.1	0.33	0	0.5	107	219	102	11.9
0	0	22	22	11	27	25	26	4	0.89	0.3	0.83	0	0	77	246	40	13.2
1	0	23	19	14	25	24	26	4	0.89	0.7	0.83	0.67	0	154	279	100	16.35
1	1	17	16	16	19	12	22	10	0.56	0.3	0.17	0	0	103	148	67	12.4
0	1	15	11	11	19	16	25	7	0.67	0.5	0.83	0.33	0.5	96	137	78	15.85
1	1	22	21	16	24	24	22	4	1	0.3	0.83	0.67	1	175	181	55	18.15
0	1	19	14	13	20	23	26	7	1	0.6	0.67	0.67	0.5	57	98	59	11.15
0	0	18	21	12	21	24	20	4	1	0.9	1	1	0	112	226	96	15.65
1	0	21	20	17	28	24	26	4	0.67	0.4	0.83	0	0.5	143	234	86	17.75
0	0	20	21	23	26	26	26	12	0.44	0.3	1	0	0.5	49	138	38	7.65
1	1	19	20	14	19	19	21	5	0.89	0.9	1	0.67	1	110	85	43	12.35
1	1	19	19	10	23	28	21	8	0.44	0.5	1	0	0.5	131	66	23	15.6
1	0	16	19	16	23	23	24	6	0.56	0.3	1	1	0.5	167	236	77	19.3
0	0	18	18	11	21	21	21	17	0.89	0.6	0.83	0.67	0	56	106	48	15.2
1	0	23	20	16	26	19	18	4	0.67	0.2	1	0.33	0	137	135	26	17.1
0	1	22	21	19	25	23	23	5	0.89	0.4	0.83	1	0.5	86	122	91	15.6
1	1	23	22	17	25	23	26	4	1	0.5	0.83	0.67	0.5	121	218	94	18.4
1	0	20	19	12	24	20	23	5	0.78	0.4	0.83	0.67	0	149	199	62	19.05
1	0	24	23	17	23	18	25	5	0.44	0	0	0	0	168	112	74	18.55
1	0	25	16	11	22	20	20	6	0.89	0.2	1	0.33	0.5	140	278	114	19.1
0	1	25	23	19	27	28	25	4	0.89	0.5	1	0.67	0.5	88	94	52	13.1
1	1	20	18	12	26	21	26	4	0.89	0.3	1	0.67	0	168	113	64	12.85
1	1	23	23	8	23	25	19	4	0.44	0	0	0	0	94	84	31	9.5
1	1	21	20	17	22	18	21	6	1	0.5	0.83	1	0	51	86	38	4.5
0	0	23	20	13	26	24	23	8	0.89	0.6	0.83	0.33	0	48	62	27	11.85
1	1	23	23	17	22	28	24	10	0.67	0.3	0.83	0	0.5	145	222	105	13.6
1	1	11	13	7	17	9	6	4	0.33	0	0	0	0	66	167	64	11.7
0	1	21	21	23	25	22	22	5	0.78	0.3	0.67	0	0.5	85	82	62	12.4
1	0	27	26	18	22	26	21	4	0.89	0.5	1	0.67	0.5	109	207	65	13.35
0	0	19	18	13	28	28	28	4	0.78	0.4	0.67	0	0	63	184	58	11.4
0	1	21	19	17	22	18	24	4	0.78	0.5	0.83	0.67	0	102	83	76	14.9
0	0	16	18	13	21	23	14	16	0.89	0.7	1	1	1	162	183	140	19.9
0	1	21	18	8	24	15	20	7	0.78	0.8	1	0.67	0.5	86	89	68	11.2
0	1	22	19	16	26	24	28	4	0.78	0.6	1	0.33	0.5	114	225	80	14.6
1	0	16	13	14	26	12	19	4	0.67	0.4	0.83	0.33	0	164	237	71	17.6
1	1	18	10	13	24	12	24	14	0.89	0.5	0.83	0.33	0.5	119	102	76	14.05
1	0	23	21	19	27	20	21	5	0.89	0.5	1	0	0.5	126	221	63	16.1
1	1	24	24	15	22	25	21	5	0.78	0.3	1	0.33	0	132	128	46	13.35
1	1	20	21	15	23	24	26	5	1	0.6	1	0	0.5	142	91	53	11.85
1	0	20	23	8	22	23	24	5	1	0.3	0.67	0.67	0	83	198	74	11.95
0	1	18	18	14	23	18	26	7	0.78	0.6	0.83	1	0.5	94	204	70	14.75
0	0	4	11	7	15	20	25	19	0.78	0.3	0.33	0.33	0	81	158	78	15.15
1	1	14	16	11	20	22	23	16	0.89	0.7	1	0.67	1	166	138	56	13.2
0	0	22	20	17	22	20	24	4	0.89	0.7	1	1	0	110	226	100	16.85
0	1	17	20	19	25	25	24	4	0.67	0.6	0.67	1	0.5	64	44	51	7.85
1	0	23	26	17	27	28	26	7	1	0.5	1	0.33	0.5	93	196	52	7.7
0	0	20	21	12	24	25	23	9	0.67	0.5	0.83	0.33	0	104	83	102	12.6
0	1	18	12	12	21	14	20	5	0.56	0.4	0.67	0	0	105	79	78	7.85
0	1	19	15	18	17	16	16	14	0.78	0.4	1	0.33	1	49	52	78	10.95
0	0	20	18	16	26	24	24	4	1	0.7	1	1	0	88	105	55	12.35
0	1	15	14	15	20	13	20	16	0.67	0.2	0.17	0	0.5	95	116	98	9.95
0	1	24	18	20	22	19	23	10	0.78	0.5	0.83	0.67	0	102	83	76	14.9
0	0	21	16	16	24	18	23	5	0.56	0.4	0.83	0.67	0.5	99	196	73	16.65
0	1	19	19	12	23	16	18	6	1	0.2	1	0.67	1	63	153	47	13.4
0	0	19	7	10	22	8	21	4	0.89	0.5	0.67	0.67	0	76	157	45	13.95
0	0	27	21	28	28	27	25	4	0.44	0.4	0.5	0	0	109	75	83	15.7
0	1	23	24	19	21	23	23	4	1	0.7	0.67	1	1	117	106	60	16.85
0	1	23	21	18	24	20	26	5	0.89	0.6	0.83	0.67	1	57	58	48	10.95
0	0	20	20	19	28	20	26	4	0.78	0.4	0.83	0	0	120	75	50	15.35
0	1	17	22	8	25	26	24	4	0.89	0.5	1	0.67	1	73	74	56	12.2
0	0	21	17	17	24	23	23	5	0.11	0	0.17	0	0	91	185	77	15.1
0	0	23	19	16	24	24	21	4	0.89	0.7	1	0.67	0.5	108	265	91	17.75
0	1	22	20	18	21	21	23	4	0.89	0.4	0.67	0.67	0	105	131	76	15.2
1	0	16	16	12	20	15	20	5	1	0.5	0.67	1	0	117	139	68	14.6
0	0	20	20	17	26	22	23	8	0.89	0.6	0.83	0.67	0	119	196	74	16.65
0	1	16	16	13	16	25	24	15	1	0.8	0.5	0.67	0.5	31	78	29	8.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 14 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269694&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]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269694&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269694&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 time14 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






Multiple Linear Regression - Estimated Regression Equation
TOTAL [t] = + 9.38677 -1.54264GroepN[t] -0.630482gender[t] + 0.0598483I1[t] -0.00995794I2[t] -0.0172786I3[t] -0.0785439E1[t] -0.00925136E2[t] -0.0263684E3[t] + 0.00050666AMOTIVATION[t] -0.0433568Calculation[t] -1.64572Algebraic_Reasoning[t] + 0.92Graphical_Interpretation[t] + 1.10317Proportionality_and_Ratio[t] + 0.826482Probability_and_Sampling[t] + 0.0217256LFM[t] + 0.0266816Blogs[t] -0.00386931Hours[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOTAL
[t] =  +  9.38677 -1.54264GroepN[t] -0.630482gender[t] +  0.0598483I1[t] -0.00995794I2[t] -0.0172786I3[t] -0.0785439E1[t] -0.00925136E2[t] -0.0263684E3[t] +  0.00050666AMOTIVATION[t] -0.0433568Calculation[t] -1.64572Algebraic_Reasoning[t] +  0.92Graphical_Interpretation[t] +  1.10317Proportionality_and_Ratio[t] +  0.826482Probability_and_Sampling[t] +  0.0217256LFM[t] +  0.0266816Blogs[t] -0.00386931Hours[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269694&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOTAL
[t] =  +  9.38677 -1.54264GroepN[t] -0.630482gender[t] +  0.0598483I1[t] -0.00995794I2[t] -0.0172786I3[t] -0.0785439E1[t] -0.00925136E2[t] -0.0263684E3[t] +  0.00050666AMOTIVATION[t] -0.0433568Calculation[t] -1.64572Algebraic_Reasoning[t] +  0.92Graphical_Interpretation[t] +  1.10317Proportionality_and_Ratio[t] +  0.826482Probability_and_Sampling[t] +  0.0217256LFM[t] +  0.0266816Blogs[t] -0.00386931Hours[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269694&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269694&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:

Multiple Linear Regression - Estimated Regression Equation
TOTAL [t] = + 9.38677 -1.54264GroepN[t] -0.630482gender[t] + 0.0598483I1[t] -0.00995794I2[t] -0.0172786I3[t] -0.0785439E1[t] -0.00925136E2[t] -0.0263684E3[t] + 0.00050666AMOTIVATION[t] -0.0433568Calculation[t] -1.64572Algebraic_Reasoning[t] + 0.92Graphical_Interpretation[t] + 1.10317Proportionality_and_Ratio[t] + 0.826482Probability_and_Sampling[t] + 0.0217256LFM[t] + 0.0266816Blogs[t] -0.00386931Hours[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.386772.073084.5289.07787e-064.53894e-06
GroepN-1.542640.403284-3.8250.0001636828.18408e-05
gender-0.6304820.358872-1.7570.08012140.0400607
I10.05984830.06600450.90670.3653890.182694
I2-0.009957940.0575459-0.1730.8627520.431376
I3-0.01727860.0497892-0.3470.7288460.364423
E1-0.07854390.0698861-1.1240.2620980.131049
E2-0.009251360.0470435-0.19670.8442510.422125
E3-0.02636840.0568881-0.46350.6433840.321692
AMOTIVATION0.000506660.05652570.0089630.9928550.496428
Calculation-0.04335681.0891-0.039810.9682750.484138
Algebraic_Reasoning-1.645721.03826-1.5850.1141630.0570813
Graphical_Interpretation0.920.8163721.1270.2608080.130404
Proportionality_and_Ratio1.103170.5013052.2010.02864480.0143224
Probability_and_Sampling0.8264820.482481.7130.08790680.0439534
LFM0.02172560.005380214.0387.09715e-053.54858e-05
Blogs0.02668160.002718419.8151.50768e-197.53841e-20
Hours-0.003869310.00688725-0.56180.5747310.287366

\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) & 9.38677 & 2.07308 & 4.528 & 9.07787e-06 & 4.53894e-06 \tabularnewline
GroepN & -1.54264 & 0.403284 & -3.825 & 0.000163682 & 8.18408e-05 \tabularnewline
gender & -0.630482 & 0.358872 & -1.757 & 0.0801214 & 0.0400607 \tabularnewline
I1 & 0.0598483 & 0.0660045 & 0.9067 & 0.365389 & 0.182694 \tabularnewline
I2 & -0.00995794 & 0.0575459 & -0.173 & 0.862752 & 0.431376 \tabularnewline
I3 & -0.0172786 & 0.0497892 & -0.347 & 0.728846 & 0.364423 \tabularnewline
E1 & -0.0785439 & 0.0698861 & -1.124 & 0.262098 & 0.131049 \tabularnewline
E2 & -0.00925136 & 0.0470435 & -0.1967 & 0.844251 & 0.422125 \tabularnewline
E3 & -0.0263684 & 0.0568881 & -0.4635 & 0.643384 & 0.321692 \tabularnewline
AMOTIVATION & 0.00050666 & 0.0565257 & 0.008963 & 0.992855 & 0.496428 \tabularnewline
Calculation & -0.0433568 & 1.0891 & -0.03981 & 0.968275 & 0.484138 \tabularnewline
Algebraic_Reasoning & -1.64572 & 1.03826 & -1.585 & 0.114163 & 0.0570813 \tabularnewline
Graphical_Interpretation & 0.92 & 0.816372 & 1.127 & 0.260808 & 0.130404 \tabularnewline
Proportionality_and_Ratio & 1.10317 & 0.501305 & 2.201 & 0.0286448 & 0.0143224 \tabularnewline
Probability_and_Sampling & 0.826482 & 0.48248 & 1.713 & 0.0879068 & 0.0439534 \tabularnewline
LFM & 0.0217256 & 0.00538021 & 4.038 & 7.09715e-05 & 3.54858e-05 \tabularnewline
Blogs & 0.0266816 & 0.00271841 & 9.815 & 1.50768e-19 & 7.53841e-20 \tabularnewline
Hours & -0.00386931 & 0.00688725 & -0.5618 & 0.574731 & 0.287366 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269694&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]9.38677[/C][C]2.07308[/C][C]4.528[/C][C]9.07787e-06[/C][C]4.53894e-06[/C][/ROW]
[ROW][C]GroepN[/C][C]-1.54264[/C][C]0.403284[/C][C]-3.825[/C][C]0.000163682[/C][C]8.18408e-05[/C][/ROW]
[ROW][C]gender[/C][C]-0.630482[/C][C]0.358872[/C][C]-1.757[/C][C]0.0801214[/C][C]0.0400607[/C][/ROW]
[ROW][C]I1[/C][C]0.0598483[/C][C]0.0660045[/C][C]0.9067[/C][C]0.365389[/C][C]0.182694[/C][/ROW]
[ROW][C]I2[/C][C]-0.00995794[/C][C]0.0575459[/C][C]-0.173[/C][C]0.862752[/C][C]0.431376[/C][/ROW]
[ROW][C]I3[/C][C]-0.0172786[/C][C]0.0497892[/C][C]-0.347[/C][C]0.728846[/C][C]0.364423[/C][/ROW]
[ROW][C]E1[/C][C]-0.0785439[/C][C]0.0698861[/C][C]-1.124[/C][C]0.262098[/C][C]0.131049[/C][/ROW]
[ROW][C]E2[/C][C]-0.00925136[/C][C]0.0470435[/C][C]-0.1967[/C][C]0.844251[/C][C]0.422125[/C][/ROW]
[ROW][C]E3[/C][C]-0.0263684[/C][C]0.0568881[/C][C]-0.4635[/C][C]0.643384[/C][C]0.321692[/C][/ROW]
[ROW][C]AMOTIVATION[/C][C]0.00050666[/C][C]0.0565257[/C][C]0.008963[/C][C]0.992855[/C][C]0.496428[/C][/ROW]
[ROW][C]Calculation[/C][C]-0.0433568[/C][C]1.0891[/C][C]-0.03981[/C][C]0.968275[/C][C]0.484138[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-1.64572[/C][C]1.03826[/C][C]-1.585[/C][C]0.114163[/C][C]0.0570813[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]0.92[/C][C]0.816372[/C][C]1.127[/C][C]0.260808[/C][C]0.130404[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.10317[/C][C]0.501305[/C][C]2.201[/C][C]0.0286448[/C][C]0.0143224[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.826482[/C][C]0.48248[/C][C]1.713[/C][C]0.0879068[/C][C]0.0439534[/C][/ROW]
[ROW][C]LFM[/C][C]0.0217256[/C][C]0.00538021[/C][C]4.038[/C][C]7.09715e-05[/C][C]3.54858e-05[/C][/ROW]
[ROW][C]Blogs[/C][C]0.0266816[/C][C]0.00271841[/C][C]9.815[/C][C]1.50768e-19[/C][C]7.53841e-20[/C][/ROW]
[ROW][C]Hours[/C][C]-0.00386931[/C][C]0.00688725[/C][C]-0.5618[/C][C]0.574731[/C][C]0.287366[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269694&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269694&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:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.386772.073084.5289.07787e-064.53894e-06
GroepN-1.542640.403284-3.8250.0001636828.18408e-05
gender-0.6304820.358872-1.7570.08012140.0400607
I10.05984830.06600450.90670.3653890.182694
I2-0.009957940.0575459-0.1730.8627520.431376
I3-0.01727860.0497892-0.3470.7288460.364423
E1-0.07854390.0698861-1.1240.2620980.131049
E2-0.009251360.0470435-0.19670.8442510.422125
E3-0.02636840.0568881-0.46350.6433840.321692
AMOTIVATION0.000506660.05652570.0089630.9928550.496428
Calculation-0.04335681.0891-0.039810.9682750.484138
Algebraic_Reasoning-1.645721.03826-1.5850.1141630.0570813
Graphical_Interpretation0.920.8163721.1270.2608080.130404
Proportionality_and_Ratio1.103170.5013052.2010.02864480.0143224
Probability_and_Sampling0.8264820.482481.7130.08790680.0439534
LFM0.02172560.005380214.0387.09715e-053.54858e-05
Blogs0.02668160.002718419.8151.50768e-197.53841e-20
Hours-0.003869310.00688725-0.56180.5747310.287366






Multiple Linear Regression - Regression Statistics
Multiple R0.658663
R-squared0.433836
Adjusted R-squared0.396818
F-TEST (value)11.7195
F-TEST (DF numerator)17
F-TEST (DF denominator)260
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.63622
Sum Squared Residuals1806.91

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.658663 \tabularnewline
R-squared & 0.433836 \tabularnewline
Adjusted R-squared & 0.396818 \tabularnewline
F-TEST (value) & 11.7195 \tabularnewline
F-TEST (DF numerator) & 17 \tabularnewline
F-TEST (DF denominator) & 260 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.63622 \tabularnewline
Sum Squared Residuals & 1806.91 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269694&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.658663[/C][/ROW]
[ROW][C]R-squared[/C][C]0.433836[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.396818[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]11.7195[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]17[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]260[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.63622[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1806.91[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269694&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269694&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.658663
R-squared0.433836
Adjusted R-squared0.396818
F-TEST (value)11.7195
F-TEST (DF numerator)17
F-TEST (DF denominator)260
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.63622
Sum Squared Residuals1806.91






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.20680.693216
212.210.63161.56841
312.812.4480.351995
47.411.4513-4.05127
56.710.2148-3.51481
612.614.0817-1.48172
714.812.84571.95428
813.312.43670.863274
911.110.71580.384195
108.214.1789-5.97893
1111.412.0497-0.649724
126.414.1503-7.75029
1310.69.858630.741373
141213.5047-1.50471
156.37.80881-1.50881
1611.311.6786-0.378564
1711.913.2989-1.39892
189.310.9973-1.6973
199.612.6484-3.04844
201010.5329-0.532861
216.410.8637-4.46367
2213.811.31042.48963
2310.813.3725-2.57248
2413.811.95891.84115
2511.712.6115-0.911494
2610.915.1335-4.23348
2716.113.31762.78244
2813.412.49610.903885
299.911.5073-1.60727
3011.512.47-0.969995
318.310.296-1.99595
3211.713.343-1.643
33911.1723-2.17229
349.713.8002-4.10017
3510.811.3058-0.505793
3610.312.3961-2.09606
3710.411.6294-1.22936
3812.713.3341-0.634127
399.312.1019-2.80186
4011.814.258-2.45805
415.910.2067-4.30667
4211.413.9066-2.50657
431311.08431.9157
4410.812.5719-1.77191
4512.310.37241.92762
4611.314.0278-2.72779
4711.811.15060.649401
487.910.7577-2.85768
4912.78.337234.36277
5012.311.24361.05636
5111.613.1331-1.5331
526.710.6529-3.95292
5310.913.5413-2.64126
5412.112.5095-0.409458
5513.312.73270.567339
5610.113.3709-3.27088
575.712.893-7.19304
5814.310.41773.88226
5989.70007-1.70007
6013.312.02251.27746
619.313.2242-3.9242
6212.510.42772.07234
637.611.0671-3.46713
6415.914.42251.47753
659.211.549-2.34901
669.111.4305-2.33047
6711.114.5367-3.43666
681314.7139-1.71389
6914.513.00211.49786
7012.211.68910.510885
7112.313.0656-0.765644
7211.411.06610.333916
738.812.1168-3.3168
7414.611.90982.69022
7512.611.86680.733248
76NANA0.271366
771312.47350.526466
7812.614.2215-1.6215
7913.214.2332-1.03323
809.911.9778-2.07775
817.78.64236-0.942361
8210.58.005622.49438
8313.415.2283-1.82826
8410.916.6781-5.77807
854.36.5396-2.2396
8610.310.01880.281211
8711.811.49480.305183
8811.211.204-0.00397209
8911.414.064-2.66401
908.66.615251.98475
9113.211.39641.8036
9212.618.9835-6.38352
935.67.09193-1.49193
949.913.8785-3.97854
958.812.2091-3.40905
967.79.11195-1.41195
97914.1373-5.13729
987.37.90303-0.603029
9911.49.310332.08967
10013.617.0544-3.45437
1017.98.58341-0.68341
10210.713.2344-2.53443
10310.311.2969-0.996852
1048.39.54166-1.24166
1059.66.951722.64828
10614.216.4365-2.23651
1078.56.25682.2432
10813.520.1796-6.67957
1094.99.18729-4.28729
1106.47.74103-1.34103
1119.69.85604-0.25604
11211.611.36990.230065
11311.115.2126-4.11263
1144.353.156471.19353
11512.79.27323.4268
11618.115.78312.31688
11717.8519.0316-1.1816
11816.614.10992.49009
11912.617.4359-4.83593
12017.114.40872.69131
12119.120.6763-1.57625
12216.112.16433.93567
12313.3513.08390.266115
12418.412.84985.55022
12514.717.479-2.779
12610.69.690410.90959
12712.69.760012.83999
12816.217.8135-1.61353
12913.610.39623.20376
13018.916.66112.23891
13114.111.90632.19375
13214.515.4369-0.936899
13316.1513.72992.42012
13414.7513.21351.53655
13514.814.48150.318468
13612.4512.9765-0.526511
13712.659.148853.50115
13817.3519.1848-1.83482
1398.67.781580.818424
14018.420.3315-1.93151
14116.116.9205-0.820532
14211.65.705595.89441
14317.7514.49353.25651
14415.2513.02972.22027
14517.6516.35831.29169
14616.3513.93562.41442
14717.6516.0181.63198
14813.612.39891.20107
14914.3516.8805-2.53053
15014.7513.49321.25682
15118.2522.7844-4.53445
1529.97.6042.296
1531612.9173.08299
15418.2518.09610.153869
15516.8515.36931.4807
15614.615.081-0.481006
15713.8512.11861.73136
15818.9517.76091.18908
15915.619.1962-3.59617
16014.8516.7165-1.86651
16111.757.727324.02268
16218.4520.2088-1.75884
16315.913.78222.11778
16417.111.25555.84447
16516.113.85492.24509
16619.919.11070.789251
16710.959.466951.48305
16818.4515.5472.90296
16915.116.9186-1.81861
1701518.8205-3.82053
17111.3511.06290.287069
17215.9511.96533.98468
17318.116.85111.24892
17414.615.839-1.23903
17515.416.6404-1.24043
17615.411.58253.81753
17717.617.771-0.170995
17813.359.982833.36717
17919.117.43791.66205
18015.3518.1923-2.8423
1817.69.19895-1.59895
18213.413.8459-0.445943
18313.912.14431.7557
18419.117.79631.3037
18515.2515.6311-0.381068
18612.911.58691.31307
18716.111.7234.37698
18817.3517.23980.11019
18913.1511.31061.83936
19012.1510.38741.76262
19112.613.9299-1.3299
19210.358.302812.04719
19315.417.5203-2.12025
1949.65.145144.45486
19518.216.94051.25947
19613.614.4637-0.863671
19714.8516.5665-1.71645
19814.7514.59010.159906
19914.110.39653.70351
20014.911.98892.91109
20116.2515.24981.00023
20219.2517.45721.79282
20313.613.11060.489429
20413.614.2858-0.685802
20515.6513.41372.23633
20612.759.974882.77512
20714.615.9753-1.37534
2089.858.960030.889973
20912.6510.47562.1744
21019.217.07692.1231
21116.615.6560.944012
21211.28.725212.47479
21315.2517.5578-2.30778
21411.914.2718-2.37183
21513.213.4855-0.28545
21616.3515.13271.21734
21712.49.736592.66341
21815.8513.27022.57977
21918.1518.4265-0.276513
22011.1511.7413-0.591283
22115.6512.91022.73978
22217.7522.5351-4.78506
2237.656.447631.20237
22412.357.132895.21711
22515.613.53242.06755
22619.316.14183.15824
22715.211.55823.64183
22817.114.60982.49021
22915.611.54884.05118
23018.414.4383.96201
23119.0512.96086.08916
23218.5517.35111.19887
23319.118.08791.01211
23413.112.89820.201848
23512.8513.1806-0.330562
2369.514.7885-5.28851
2374.52.817141.68286
23811.8513.0239-1.17393
23913.613.57470.0253497
24011.710.25861.44135
24112.414.2705-1.87048
24213.3514.8535-1.50346
24311.48.287413.11259
24414.912.23682.66316
24519.920.5499-0.649894
24611.212.0534-0.853384
24714.612.83031.76967
24817.614.58713.01287
24914.0512.63841.41161
25016.115.25290.847076
25113.3512.34121.00884
25211.8513.6211-1.77107
25311.9512.4305-0.480492
25414.7512.79671.95333
25515.1515.6462-0.496189
25613.212.88220.317785
25716.8518.904-2.05397
2587.8513.6362-5.78617
2597.76.904120.795882
26012.615.974-3.374
2617.858.00356-0.153559
26210.9511.1614-0.21145
26312.3514.4363-2.08626
2649.956.995232.95477
26514.914.13360.766369
26616.6517.703-1.05297
26713.413.5378-0.137809
26813.959.284244.66576
26915.712.43753.26247
27016.8516.66290.187117
27110.957.074693.87531
27215.3514.69930.650669
27312.211.34560.854403
27415.114.93550.164538
27517.7515.80571.94432
27615.213.64141.55859
27714.613.1981.40195
27816.6518.6616-2.01155
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.2068 & 0.693216 \tabularnewline
2 & 12.2 & 10.6316 & 1.56841 \tabularnewline
3 & 12.8 & 12.448 & 0.351995 \tabularnewline
4 & 7.4 & 11.4513 & -4.05127 \tabularnewline
5 & 6.7 & 10.2148 & -3.51481 \tabularnewline
6 & 12.6 & 14.0817 & -1.48172 \tabularnewline
7 & 14.8 & 12.8457 & 1.95428 \tabularnewline
8 & 13.3 & 12.4367 & 0.863274 \tabularnewline
9 & 11.1 & 10.7158 & 0.384195 \tabularnewline
10 & 8.2 & 14.1789 & -5.97893 \tabularnewline
11 & 11.4 & 12.0497 & -0.649724 \tabularnewline
12 & 6.4 & 14.1503 & -7.75029 \tabularnewline
13 & 10.6 & 9.85863 & 0.741373 \tabularnewline
14 & 12 & 13.5047 & -1.50471 \tabularnewline
15 & 6.3 & 7.80881 & -1.50881 \tabularnewline
16 & 11.3 & 11.6786 & -0.378564 \tabularnewline
17 & 11.9 & 13.2989 & -1.39892 \tabularnewline
18 & 9.3 & 10.9973 & -1.6973 \tabularnewline
19 & 9.6 & 12.6484 & -3.04844 \tabularnewline
20 & 10 & 10.5329 & -0.532861 \tabularnewline
21 & 6.4 & 10.8637 & -4.46367 \tabularnewline
22 & 13.8 & 11.3104 & 2.48963 \tabularnewline
23 & 10.8 & 13.3725 & -2.57248 \tabularnewline
24 & 13.8 & 11.9589 & 1.84115 \tabularnewline
25 & 11.7 & 12.6115 & -0.911494 \tabularnewline
26 & 10.9 & 15.1335 & -4.23348 \tabularnewline
27 & 16.1 & 13.3176 & 2.78244 \tabularnewline
28 & 13.4 & 12.4961 & 0.903885 \tabularnewline
29 & 9.9 & 11.5073 & -1.60727 \tabularnewline
30 & 11.5 & 12.47 & -0.969995 \tabularnewline
31 & 8.3 & 10.296 & -1.99595 \tabularnewline
32 & 11.7 & 13.343 & -1.643 \tabularnewline
33 & 9 & 11.1723 & -2.17229 \tabularnewline
34 & 9.7 & 13.8002 & -4.10017 \tabularnewline
35 & 10.8 & 11.3058 & -0.505793 \tabularnewline
36 & 10.3 & 12.3961 & -2.09606 \tabularnewline
37 & 10.4 & 11.6294 & -1.22936 \tabularnewline
38 & 12.7 & 13.3341 & -0.634127 \tabularnewline
39 & 9.3 & 12.1019 & -2.80186 \tabularnewline
40 & 11.8 & 14.258 & -2.45805 \tabularnewline
41 & 5.9 & 10.2067 & -4.30667 \tabularnewline
42 & 11.4 & 13.9066 & -2.50657 \tabularnewline
43 & 13 & 11.0843 & 1.9157 \tabularnewline
44 & 10.8 & 12.5719 & -1.77191 \tabularnewline
45 & 12.3 & 10.3724 & 1.92762 \tabularnewline
46 & 11.3 & 14.0278 & -2.72779 \tabularnewline
47 & 11.8 & 11.1506 & 0.649401 \tabularnewline
48 & 7.9 & 10.7577 & -2.85768 \tabularnewline
49 & 12.7 & 8.33723 & 4.36277 \tabularnewline
50 & 12.3 & 11.2436 & 1.05636 \tabularnewline
51 & 11.6 & 13.1331 & -1.5331 \tabularnewline
52 & 6.7 & 10.6529 & -3.95292 \tabularnewline
53 & 10.9 & 13.5413 & -2.64126 \tabularnewline
54 & 12.1 & 12.5095 & -0.409458 \tabularnewline
55 & 13.3 & 12.7327 & 0.567339 \tabularnewline
56 & 10.1 & 13.3709 & -3.27088 \tabularnewline
57 & 5.7 & 12.893 & -7.19304 \tabularnewline
58 & 14.3 & 10.4177 & 3.88226 \tabularnewline
59 & 8 & 9.70007 & -1.70007 \tabularnewline
60 & 13.3 & 12.0225 & 1.27746 \tabularnewline
61 & 9.3 & 13.2242 & -3.9242 \tabularnewline
62 & 12.5 & 10.4277 & 2.07234 \tabularnewline
63 & 7.6 & 11.0671 & -3.46713 \tabularnewline
64 & 15.9 & 14.4225 & 1.47753 \tabularnewline
65 & 9.2 & 11.549 & -2.34901 \tabularnewline
66 & 9.1 & 11.4305 & -2.33047 \tabularnewline
67 & 11.1 & 14.5367 & -3.43666 \tabularnewline
68 & 13 & 14.7139 & -1.71389 \tabularnewline
69 & 14.5 & 13.0021 & 1.49786 \tabularnewline
70 & 12.2 & 11.6891 & 0.510885 \tabularnewline
71 & 12.3 & 13.0656 & -0.765644 \tabularnewline
72 & 11.4 & 11.0661 & 0.333916 \tabularnewline
73 & 8.8 & 12.1168 & -3.3168 \tabularnewline
74 & 14.6 & 11.9098 & 2.69022 \tabularnewline
75 & 12.6 & 11.8668 & 0.733248 \tabularnewline
76 & NA & NA & 0.271366 \tabularnewline
77 & 13 & 12.4735 & 0.526466 \tabularnewline
78 & 12.6 & 14.2215 & -1.6215 \tabularnewline
79 & 13.2 & 14.2332 & -1.03323 \tabularnewline
80 & 9.9 & 11.9778 & -2.07775 \tabularnewline
81 & 7.7 & 8.64236 & -0.942361 \tabularnewline
82 & 10.5 & 8.00562 & 2.49438 \tabularnewline
83 & 13.4 & 15.2283 & -1.82826 \tabularnewline
84 & 10.9 & 16.6781 & -5.77807 \tabularnewline
85 & 4.3 & 6.5396 & -2.2396 \tabularnewline
86 & 10.3 & 10.0188 & 0.281211 \tabularnewline
87 & 11.8 & 11.4948 & 0.305183 \tabularnewline
88 & 11.2 & 11.204 & -0.00397209 \tabularnewline
89 & 11.4 & 14.064 & -2.66401 \tabularnewline
90 & 8.6 & 6.61525 & 1.98475 \tabularnewline
91 & 13.2 & 11.3964 & 1.8036 \tabularnewline
92 & 12.6 & 18.9835 & -6.38352 \tabularnewline
93 & 5.6 & 7.09193 & -1.49193 \tabularnewline
94 & 9.9 & 13.8785 & -3.97854 \tabularnewline
95 & 8.8 & 12.2091 & -3.40905 \tabularnewline
96 & 7.7 & 9.11195 & -1.41195 \tabularnewline
97 & 9 & 14.1373 & -5.13729 \tabularnewline
98 & 7.3 & 7.90303 & -0.603029 \tabularnewline
99 & 11.4 & 9.31033 & 2.08967 \tabularnewline
100 & 13.6 & 17.0544 & -3.45437 \tabularnewline
101 & 7.9 & 8.58341 & -0.68341 \tabularnewline
102 & 10.7 & 13.2344 & -2.53443 \tabularnewline
103 & 10.3 & 11.2969 & -0.996852 \tabularnewline
104 & 8.3 & 9.54166 & -1.24166 \tabularnewline
105 & 9.6 & 6.95172 & 2.64828 \tabularnewline
106 & 14.2 & 16.4365 & -2.23651 \tabularnewline
107 & 8.5 & 6.2568 & 2.2432 \tabularnewline
108 & 13.5 & 20.1796 & -6.67957 \tabularnewline
109 & 4.9 & 9.18729 & -4.28729 \tabularnewline
110 & 6.4 & 7.74103 & -1.34103 \tabularnewline
111 & 9.6 & 9.85604 & -0.25604 \tabularnewline
112 & 11.6 & 11.3699 & 0.230065 \tabularnewline
113 & 11.1 & 15.2126 & -4.11263 \tabularnewline
114 & 4.35 & 3.15647 & 1.19353 \tabularnewline
115 & 12.7 & 9.2732 & 3.4268 \tabularnewline
116 & 18.1 & 15.7831 & 2.31688 \tabularnewline
117 & 17.85 & 19.0316 & -1.1816 \tabularnewline
118 & 16.6 & 14.1099 & 2.49009 \tabularnewline
119 & 12.6 & 17.4359 & -4.83593 \tabularnewline
120 & 17.1 & 14.4087 & 2.69131 \tabularnewline
121 & 19.1 & 20.6763 & -1.57625 \tabularnewline
122 & 16.1 & 12.1643 & 3.93567 \tabularnewline
123 & 13.35 & 13.0839 & 0.266115 \tabularnewline
124 & 18.4 & 12.8498 & 5.55022 \tabularnewline
125 & 14.7 & 17.479 & -2.779 \tabularnewline
126 & 10.6 & 9.69041 & 0.90959 \tabularnewline
127 & 12.6 & 9.76001 & 2.83999 \tabularnewline
128 & 16.2 & 17.8135 & -1.61353 \tabularnewline
129 & 13.6 & 10.3962 & 3.20376 \tabularnewline
130 & 18.9 & 16.6611 & 2.23891 \tabularnewline
131 & 14.1 & 11.9063 & 2.19375 \tabularnewline
132 & 14.5 & 15.4369 & -0.936899 \tabularnewline
133 & 16.15 & 13.7299 & 2.42012 \tabularnewline
134 & 14.75 & 13.2135 & 1.53655 \tabularnewline
135 & 14.8 & 14.4815 & 0.318468 \tabularnewline
136 & 12.45 & 12.9765 & -0.526511 \tabularnewline
137 & 12.65 & 9.14885 & 3.50115 \tabularnewline
138 & 17.35 & 19.1848 & -1.83482 \tabularnewline
139 & 8.6 & 7.78158 & 0.818424 \tabularnewline
140 & 18.4 & 20.3315 & -1.93151 \tabularnewline
141 & 16.1 & 16.9205 & -0.820532 \tabularnewline
142 & 11.6 & 5.70559 & 5.89441 \tabularnewline
143 & 17.75 & 14.4935 & 3.25651 \tabularnewline
144 & 15.25 & 13.0297 & 2.22027 \tabularnewline
145 & 17.65 & 16.3583 & 1.29169 \tabularnewline
146 & 16.35 & 13.9356 & 2.41442 \tabularnewline
147 & 17.65 & 16.018 & 1.63198 \tabularnewline
148 & 13.6 & 12.3989 & 1.20107 \tabularnewline
149 & 14.35 & 16.8805 & -2.53053 \tabularnewline
150 & 14.75 & 13.4932 & 1.25682 \tabularnewline
151 & 18.25 & 22.7844 & -4.53445 \tabularnewline
152 & 9.9 & 7.604 & 2.296 \tabularnewline
153 & 16 & 12.917 & 3.08299 \tabularnewline
154 & 18.25 & 18.0961 & 0.153869 \tabularnewline
155 & 16.85 & 15.3693 & 1.4807 \tabularnewline
156 & 14.6 & 15.081 & -0.481006 \tabularnewline
157 & 13.85 & 12.1186 & 1.73136 \tabularnewline
158 & 18.95 & 17.7609 & 1.18908 \tabularnewline
159 & 15.6 & 19.1962 & -3.59617 \tabularnewline
160 & 14.85 & 16.7165 & -1.86651 \tabularnewline
161 & 11.75 & 7.72732 & 4.02268 \tabularnewline
162 & 18.45 & 20.2088 & -1.75884 \tabularnewline
163 & 15.9 & 13.7822 & 2.11778 \tabularnewline
164 & 17.1 & 11.2555 & 5.84447 \tabularnewline
165 & 16.1 & 13.8549 & 2.24509 \tabularnewline
166 & 19.9 & 19.1107 & 0.789251 \tabularnewline
167 & 10.95 & 9.46695 & 1.48305 \tabularnewline
168 & 18.45 & 15.547 & 2.90296 \tabularnewline
169 & 15.1 & 16.9186 & -1.81861 \tabularnewline
170 & 15 & 18.8205 & -3.82053 \tabularnewline
171 & 11.35 & 11.0629 & 0.287069 \tabularnewline
172 & 15.95 & 11.9653 & 3.98468 \tabularnewline
173 & 18.1 & 16.8511 & 1.24892 \tabularnewline
174 & 14.6 & 15.839 & -1.23903 \tabularnewline
175 & 15.4 & 16.6404 & -1.24043 \tabularnewline
176 & 15.4 & 11.5825 & 3.81753 \tabularnewline
177 & 17.6 & 17.771 & -0.170995 \tabularnewline
178 & 13.35 & 9.98283 & 3.36717 \tabularnewline
179 & 19.1 & 17.4379 & 1.66205 \tabularnewline
180 & 15.35 & 18.1923 & -2.8423 \tabularnewline
181 & 7.6 & 9.19895 & -1.59895 \tabularnewline
182 & 13.4 & 13.8459 & -0.445943 \tabularnewline
183 & 13.9 & 12.1443 & 1.7557 \tabularnewline
184 & 19.1 & 17.7963 & 1.3037 \tabularnewline
185 & 15.25 & 15.6311 & -0.381068 \tabularnewline
186 & 12.9 & 11.5869 & 1.31307 \tabularnewline
187 & 16.1 & 11.723 & 4.37698 \tabularnewline
188 & 17.35 & 17.2398 & 0.11019 \tabularnewline
189 & 13.15 & 11.3106 & 1.83936 \tabularnewline
190 & 12.15 & 10.3874 & 1.76262 \tabularnewline
191 & 12.6 & 13.9299 & -1.3299 \tabularnewline
192 & 10.35 & 8.30281 & 2.04719 \tabularnewline
193 & 15.4 & 17.5203 & -2.12025 \tabularnewline
194 & 9.6 & 5.14514 & 4.45486 \tabularnewline
195 & 18.2 & 16.9405 & 1.25947 \tabularnewline
196 & 13.6 & 14.4637 & -0.863671 \tabularnewline
197 & 14.85 & 16.5665 & -1.71645 \tabularnewline
198 & 14.75 & 14.5901 & 0.159906 \tabularnewline
199 & 14.1 & 10.3965 & 3.70351 \tabularnewline
200 & 14.9 & 11.9889 & 2.91109 \tabularnewline
201 & 16.25 & 15.2498 & 1.00023 \tabularnewline
202 & 19.25 & 17.4572 & 1.79282 \tabularnewline
203 & 13.6 & 13.1106 & 0.489429 \tabularnewline
204 & 13.6 & 14.2858 & -0.685802 \tabularnewline
205 & 15.65 & 13.4137 & 2.23633 \tabularnewline
206 & 12.75 & 9.97488 & 2.77512 \tabularnewline
207 & 14.6 & 15.9753 & -1.37534 \tabularnewline
208 & 9.85 & 8.96003 & 0.889973 \tabularnewline
209 & 12.65 & 10.4756 & 2.1744 \tabularnewline
210 & 19.2 & 17.0769 & 2.1231 \tabularnewline
211 & 16.6 & 15.656 & 0.944012 \tabularnewline
212 & 11.2 & 8.72521 & 2.47479 \tabularnewline
213 & 15.25 & 17.5578 & -2.30778 \tabularnewline
214 & 11.9 & 14.2718 & -2.37183 \tabularnewline
215 & 13.2 & 13.4855 & -0.28545 \tabularnewline
216 & 16.35 & 15.1327 & 1.21734 \tabularnewline
217 & 12.4 & 9.73659 & 2.66341 \tabularnewline
218 & 15.85 & 13.2702 & 2.57977 \tabularnewline
219 & 18.15 & 18.4265 & -0.276513 \tabularnewline
220 & 11.15 & 11.7413 & -0.591283 \tabularnewline
221 & 15.65 & 12.9102 & 2.73978 \tabularnewline
222 & 17.75 & 22.5351 & -4.78506 \tabularnewline
223 & 7.65 & 6.44763 & 1.20237 \tabularnewline
224 & 12.35 & 7.13289 & 5.21711 \tabularnewline
225 & 15.6 & 13.5324 & 2.06755 \tabularnewline
226 & 19.3 & 16.1418 & 3.15824 \tabularnewline
227 & 15.2 & 11.5582 & 3.64183 \tabularnewline
228 & 17.1 & 14.6098 & 2.49021 \tabularnewline
229 & 15.6 & 11.5488 & 4.05118 \tabularnewline
230 & 18.4 & 14.438 & 3.96201 \tabularnewline
231 & 19.05 & 12.9608 & 6.08916 \tabularnewline
232 & 18.55 & 17.3511 & 1.19887 \tabularnewline
233 & 19.1 & 18.0879 & 1.01211 \tabularnewline
234 & 13.1 & 12.8982 & 0.201848 \tabularnewline
235 & 12.85 & 13.1806 & -0.330562 \tabularnewline
236 & 9.5 & 14.7885 & -5.28851 \tabularnewline
237 & 4.5 & 2.81714 & 1.68286 \tabularnewline
238 & 11.85 & 13.0239 & -1.17393 \tabularnewline
239 & 13.6 & 13.5747 & 0.0253497 \tabularnewline
240 & 11.7 & 10.2586 & 1.44135 \tabularnewline
241 & 12.4 & 14.2705 & -1.87048 \tabularnewline
242 & 13.35 & 14.8535 & -1.50346 \tabularnewline
243 & 11.4 & 8.28741 & 3.11259 \tabularnewline
244 & 14.9 & 12.2368 & 2.66316 \tabularnewline
245 & 19.9 & 20.5499 & -0.649894 \tabularnewline
246 & 11.2 & 12.0534 & -0.853384 \tabularnewline
247 & 14.6 & 12.8303 & 1.76967 \tabularnewline
248 & 17.6 & 14.5871 & 3.01287 \tabularnewline
249 & 14.05 & 12.6384 & 1.41161 \tabularnewline
250 & 16.1 & 15.2529 & 0.847076 \tabularnewline
251 & 13.35 & 12.3412 & 1.00884 \tabularnewline
252 & 11.85 & 13.6211 & -1.77107 \tabularnewline
253 & 11.95 & 12.4305 & -0.480492 \tabularnewline
254 & 14.75 & 12.7967 & 1.95333 \tabularnewline
255 & 15.15 & 15.6462 & -0.496189 \tabularnewline
256 & 13.2 & 12.8822 & 0.317785 \tabularnewline
257 & 16.85 & 18.904 & -2.05397 \tabularnewline
258 & 7.85 & 13.6362 & -5.78617 \tabularnewline
259 & 7.7 & 6.90412 & 0.795882 \tabularnewline
260 & 12.6 & 15.974 & -3.374 \tabularnewline
261 & 7.85 & 8.00356 & -0.153559 \tabularnewline
262 & 10.95 & 11.1614 & -0.21145 \tabularnewline
263 & 12.35 & 14.4363 & -2.08626 \tabularnewline
264 & 9.95 & 6.99523 & 2.95477 \tabularnewline
265 & 14.9 & 14.1336 & 0.766369 \tabularnewline
266 & 16.65 & 17.703 & -1.05297 \tabularnewline
267 & 13.4 & 13.5378 & -0.137809 \tabularnewline
268 & 13.95 & 9.28424 & 4.66576 \tabularnewline
269 & 15.7 & 12.4375 & 3.26247 \tabularnewline
270 & 16.85 & 16.6629 & 0.187117 \tabularnewline
271 & 10.95 & 7.07469 & 3.87531 \tabularnewline
272 & 15.35 & 14.6993 & 0.650669 \tabularnewline
273 & 12.2 & 11.3456 & 0.854403 \tabularnewline
274 & 15.1 & 14.9355 & 0.164538 \tabularnewline
275 & 17.75 & 15.8057 & 1.94432 \tabularnewline
276 & 15.2 & 13.6414 & 1.55859 \tabularnewline
277 & 14.6 & 13.198 & 1.40195 \tabularnewline
278 & 16.65 & 18.6616 & -2.01155 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269694&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]12.9[/C][C]12.2068[/C][C]0.693216[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.6316[/C][C]1.56841[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]12.448[/C][C]0.351995[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.4513[/C][C]-4.05127[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.2148[/C][C]-3.51481[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]14.0817[/C][C]-1.48172[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.8457[/C][C]1.95428[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]12.4367[/C][C]0.863274[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]10.7158[/C][C]0.384195[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.1789[/C][C]-5.97893[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.0497[/C][C]-0.649724[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.1503[/C][C]-7.75029[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.85863[/C][C]0.741373[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.5047[/C][C]-1.50471[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]7.80881[/C][C]-1.50881[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.6786[/C][C]-0.378564[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]13.2989[/C][C]-1.39892[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.9973[/C][C]-1.6973[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.6484[/C][C]-3.04844[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]10.5329[/C][C]-0.532861[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]10.8637[/C][C]-4.46367[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]11.3104[/C][C]2.48963[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]13.3725[/C][C]-2.57248[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]11.9589[/C][C]1.84115[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]12.6115[/C][C]-0.911494[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]15.1335[/C][C]-4.23348[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.3176[/C][C]2.78244[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]12.4961[/C][C]0.903885[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.5073[/C][C]-1.60727[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.47[/C][C]-0.969995[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]10.296[/C][C]-1.99595[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.343[/C][C]-1.643[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]11.1723[/C][C]-2.17229[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]13.8002[/C][C]-4.10017[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]11.3058[/C][C]-0.505793[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.3961[/C][C]-2.09606[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.6294[/C][C]-1.22936[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]13.3341[/C][C]-0.634127[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]12.1019[/C][C]-2.80186[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.258[/C][C]-2.45805[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.2067[/C][C]-4.30667[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.9066[/C][C]-2.50657[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.0843[/C][C]1.9157[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.5719[/C][C]-1.77191[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]10.3724[/C][C]1.92762[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]14.0278[/C][C]-2.72779[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]11.1506[/C][C]0.649401[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]10.7577[/C][C]-2.85768[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]8.33723[/C][C]4.36277[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]11.2436[/C][C]1.05636[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]13.1331[/C][C]-1.5331[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.6529[/C][C]-3.95292[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.5413[/C][C]-2.64126[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.5095[/C][C]-0.409458[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]12.7327[/C][C]0.567339[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.3709[/C][C]-3.27088[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.893[/C][C]-7.19304[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]10.4177[/C][C]3.88226[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]9.70007[/C][C]-1.70007[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.0225[/C][C]1.27746[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.2242[/C][C]-3.9242[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]10.4277[/C][C]2.07234[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]11.0671[/C][C]-3.46713[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]14.4225[/C][C]1.47753[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.549[/C][C]-2.34901[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]11.4305[/C][C]-2.33047[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]14.5367[/C][C]-3.43666[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]14.7139[/C][C]-1.71389[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]13.0021[/C][C]1.49786[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.6891[/C][C]0.510885[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.0656[/C][C]-0.765644[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]11.0661[/C][C]0.333916[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]12.1168[/C][C]-3.3168[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.9098[/C][C]2.69022[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.8668[/C][C]0.733248[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.271366[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]12.4735[/C][C]0.526466[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]14.2215[/C][C]-1.6215[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]14.2332[/C][C]-1.03323[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]11.9778[/C][C]-2.07775[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]8.64236[/C][C]-0.942361[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]8.00562[/C][C]2.49438[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]15.2283[/C][C]-1.82826[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]16.6781[/C][C]-5.77807[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]6.5396[/C][C]-2.2396[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]10.0188[/C][C]0.281211[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]11.4948[/C][C]0.305183[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]11.204[/C][C]-0.00397209[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]14.064[/C][C]-2.66401[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]6.61525[/C][C]1.98475[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]11.3964[/C][C]1.8036[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]18.9835[/C][C]-6.38352[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]7.09193[/C][C]-1.49193[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]13.8785[/C][C]-3.97854[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]12.2091[/C][C]-3.40905[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]9.11195[/C][C]-1.41195[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]14.1373[/C][C]-5.13729[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]7.90303[/C][C]-0.603029[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]9.31033[/C][C]2.08967[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]17.0544[/C][C]-3.45437[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]8.58341[/C][C]-0.68341[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]13.2344[/C][C]-2.53443[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]11.2969[/C][C]-0.996852[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]9.54166[/C][C]-1.24166[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]6.95172[/C][C]2.64828[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]16.4365[/C][C]-2.23651[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]6.2568[/C][C]2.2432[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]20.1796[/C][C]-6.67957[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]9.18729[/C][C]-4.28729[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]7.74103[/C][C]-1.34103[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]9.85604[/C][C]-0.25604[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]11.3699[/C][C]0.230065[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]15.2126[/C][C]-4.11263[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]3.15647[/C][C]1.19353[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]9.2732[/C][C]3.4268[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]15.7831[/C][C]2.31688[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]19.0316[/C][C]-1.1816[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]14.1099[/C][C]2.49009[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]17.4359[/C][C]-4.83593[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]14.4087[/C][C]2.69131[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]20.6763[/C][C]-1.57625[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]12.1643[/C][C]3.93567[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]13.0839[/C][C]0.266115[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]12.8498[/C][C]5.55022[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.479[/C][C]-2.779[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]9.69041[/C][C]0.90959[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]9.76001[/C][C]2.83999[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]17.8135[/C][C]-1.61353[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]10.3962[/C][C]3.20376[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]16.6611[/C][C]2.23891[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]11.9063[/C][C]2.19375[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]15.4369[/C][C]-0.936899[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]13.7299[/C][C]2.42012[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.2135[/C][C]1.53655[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]14.4815[/C][C]0.318468[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.9765[/C][C]-0.526511[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.14885[/C][C]3.50115[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]19.1848[/C][C]-1.83482[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]7.78158[/C][C]0.818424[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]20.3315[/C][C]-1.93151[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]16.9205[/C][C]-0.820532[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]5.70559[/C][C]5.89441[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]14.4935[/C][C]3.25651[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]13.0297[/C][C]2.22027[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]16.3583[/C][C]1.29169[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]13.9356[/C][C]2.41442[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]16.018[/C][C]1.63198[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.3989[/C][C]1.20107[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]16.8805[/C][C]-2.53053[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]13.4932[/C][C]1.25682[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]22.7844[/C][C]-4.53445[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]7.604[/C][C]2.296[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]12.917[/C][C]3.08299[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]18.0961[/C][C]0.153869[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]15.3693[/C][C]1.4807[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]15.081[/C][C]-0.481006[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]12.1186[/C][C]1.73136[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]17.7609[/C][C]1.18908[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]19.1962[/C][C]-3.59617[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]16.7165[/C][C]-1.86651[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]7.72732[/C][C]4.02268[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]20.2088[/C][C]-1.75884[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]13.7822[/C][C]2.11778[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]11.2555[/C][C]5.84447[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]13.8549[/C][C]2.24509[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]19.1107[/C][C]0.789251[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]9.46695[/C][C]1.48305[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]15.547[/C][C]2.90296[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]16.9186[/C][C]-1.81861[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]18.8205[/C][C]-3.82053[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]11.0629[/C][C]0.287069[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]11.9653[/C][C]3.98468[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]16.8511[/C][C]1.24892[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]15.839[/C][C]-1.23903[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.6404[/C][C]-1.24043[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]11.5825[/C][C]3.81753[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]17.771[/C][C]-0.170995[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]9.98283[/C][C]3.36717[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]17.4379[/C][C]1.66205[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]18.1923[/C][C]-2.8423[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]9.19895[/C][C]-1.59895[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]13.8459[/C][C]-0.445943[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]12.1443[/C][C]1.7557[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]17.7963[/C][C]1.3037[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]15.6311[/C][C]-0.381068[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]11.5869[/C][C]1.31307[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]11.723[/C][C]4.37698[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]17.2398[/C][C]0.11019[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]11.3106[/C][C]1.83936[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]10.3874[/C][C]1.76262[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]13.9299[/C][C]-1.3299[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]8.30281[/C][C]2.04719[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]17.5203[/C][C]-2.12025[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]5.14514[/C][C]4.45486[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]16.9405[/C][C]1.25947[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]14.4637[/C][C]-0.863671[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]16.5665[/C][C]-1.71645[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]14.5901[/C][C]0.159906[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]10.3965[/C][C]3.70351[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.9889[/C][C]2.91109[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]15.2498[/C][C]1.00023[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]17.4572[/C][C]1.79282[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.1106[/C][C]0.489429[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]14.2858[/C][C]-0.685802[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]13.4137[/C][C]2.23633[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]9.97488[/C][C]2.77512[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]15.9753[/C][C]-1.37534[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]8.96003[/C][C]0.889973[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]10.4756[/C][C]2.1744[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]17.0769[/C][C]2.1231[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]15.656[/C][C]0.944012[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]8.72521[/C][C]2.47479[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]17.5578[/C][C]-2.30778[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]14.2718[/C][C]-2.37183[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]13.4855[/C][C]-0.28545[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]15.1327[/C][C]1.21734[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.73659[/C][C]2.66341[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]13.2702[/C][C]2.57977[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]18.4265[/C][C]-0.276513[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]11.7413[/C][C]-0.591283[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]12.9102[/C][C]2.73978[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]22.5351[/C][C]-4.78506[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]6.44763[/C][C]1.20237[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]7.13289[/C][C]5.21711[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]13.5324[/C][C]2.06755[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]16.1418[/C][C]3.15824[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]11.5582[/C][C]3.64183[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]14.6098[/C][C]2.49021[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]11.5488[/C][C]4.05118[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]14.438[/C][C]3.96201[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]12.9608[/C][C]6.08916[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]17.3511[/C][C]1.19887[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]18.0879[/C][C]1.01211[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]12.8982[/C][C]0.201848[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]13.1806[/C][C]-0.330562[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]14.7885[/C][C]-5.28851[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]2.81714[/C][C]1.68286[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]13.0239[/C][C]-1.17393[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]13.5747[/C][C]0.0253497[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]10.2586[/C][C]1.44135[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]14.2705[/C][C]-1.87048[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]14.8535[/C][C]-1.50346[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]8.28741[/C][C]3.11259[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]12.2368[/C][C]2.66316[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]20.5499[/C][C]-0.649894[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]12.0534[/C][C]-0.853384[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]12.8303[/C][C]1.76967[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]14.5871[/C][C]3.01287[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]12.6384[/C][C]1.41161[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]15.2529[/C][C]0.847076[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]12.3412[/C][C]1.00884[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]13.6211[/C][C]-1.77107[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]12.4305[/C][C]-0.480492[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]12.7967[/C][C]1.95333[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]15.6462[/C][C]-0.496189[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]12.8822[/C][C]0.317785[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]18.904[/C][C]-2.05397[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]13.6362[/C][C]-5.78617[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]6.90412[/C][C]0.795882[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]15.974[/C][C]-3.374[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]8.00356[/C][C]-0.153559[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]11.1614[/C][C]-0.21145[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]14.4363[/C][C]-2.08626[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]6.99523[/C][C]2.95477[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]14.1336[/C][C]0.766369[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]17.703[/C][C]-1.05297[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]13.5378[/C][C]-0.137809[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]9.28424[/C][C]4.66576[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]12.4375[/C][C]3.26247[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]16.6629[/C][C]0.187117[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]7.07469[/C][C]3.87531[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]14.6993[/C][C]0.650669[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]11.3456[/C][C]0.854403[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]14.9355[/C][C]0.164538[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.8057[/C][C]1.94432[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]13.6414[/C][C]1.55859[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]13.198[/C][C]1.40195[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]18.6616[/C][C]-2.01155[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269694&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269694&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.20680.693216
212.210.63161.56841
312.812.4480.351995
47.411.4513-4.05127
56.710.2148-3.51481
612.614.0817-1.48172
714.812.84571.95428
813.312.43670.863274
911.110.71580.384195
108.214.1789-5.97893
1111.412.0497-0.649724
126.414.1503-7.75029
1310.69.858630.741373
141213.5047-1.50471
156.37.80881-1.50881
1611.311.6786-0.378564
1711.913.2989-1.39892
189.310.9973-1.6973
199.612.6484-3.04844
201010.5329-0.532861
216.410.8637-4.46367
2213.811.31042.48963
2310.813.3725-2.57248
2413.811.95891.84115
2511.712.6115-0.911494
2610.915.1335-4.23348
2716.113.31762.78244
2813.412.49610.903885
299.911.5073-1.60727
3011.512.47-0.969995
318.310.296-1.99595
3211.713.343-1.643
33911.1723-2.17229
349.713.8002-4.10017
3510.811.3058-0.505793
3610.312.3961-2.09606
3710.411.6294-1.22936
3812.713.3341-0.634127
399.312.1019-2.80186
4011.814.258-2.45805
415.910.2067-4.30667
4211.413.9066-2.50657
431311.08431.9157
4410.812.5719-1.77191
4512.310.37241.92762
4611.314.0278-2.72779
4711.811.15060.649401
487.910.7577-2.85768
4912.78.337234.36277
5012.311.24361.05636
5111.613.1331-1.5331
526.710.6529-3.95292
5310.913.5413-2.64126
5412.112.5095-0.409458
5513.312.73270.567339
5610.113.3709-3.27088
575.712.893-7.19304
5814.310.41773.88226
5989.70007-1.70007
6013.312.02251.27746
619.313.2242-3.9242
6212.510.42772.07234
637.611.0671-3.46713
6415.914.42251.47753
659.211.549-2.34901
669.111.4305-2.33047
6711.114.5367-3.43666
681314.7139-1.71389
6914.513.00211.49786
7012.211.68910.510885
7112.313.0656-0.765644
7211.411.06610.333916
738.812.1168-3.3168
7414.611.90982.69022
7512.611.86680.733248
76NANA0.271366
771312.47350.526466
7812.614.2215-1.6215
7913.214.2332-1.03323
809.911.9778-2.07775
817.78.64236-0.942361
8210.58.005622.49438
8313.415.2283-1.82826
8410.916.6781-5.77807
854.36.5396-2.2396
8610.310.01880.281211
8711.811.49480.305183
8811.211.204-0.00397209
8911.414.064-2.66401
908.66.615251.98475
9113.211.39641.8036
9212.618.9835-6.38352
935.67.09193-1.49193
949.913.8785-3.97854
958.812.2091-3.40905
967.79.11195-1.41195
97914.1373-5.13729
987.37.90303-0.603029
9911.49.310332.08967
10013.617.0544-3.45437
1017.98.58341-0.68341
10210.713.2344-2.53443
10310.311.2969-0.996852
1048.39.54166-1.24166
1059.66.951722.64828
10614.216.4365-2.23651
1078.56.25682.2432
10813.520.1796-6.67957
1094.99.18729-4.28729
1106.47.74103-1.34103
1119.69.85604-0.25604
11211.611.36990.230065
11311.115.2126-4.11263
1144.353.156471.19353
11512.79.27323.4268
11618.115.78312.31688
11717.8519.0316-1.1816
11816.614.10992.49009
11912.617.4359-4.83593
12017.114.40872.69131
12119.120.6763-1.57625
12216.112.16433.93567
12313.3513.08390.266115
12418.412.84985.55022
12514.717.479-2.779
12610.69.690410.90959
12712.69.760012.83999
12816.217.8135-1.61353
12913.610.39623.20376
13018.916.66112.23891
13114.111.90632.19375
13214.515.4369-0.936899
13316.1513.72992.42012
13414.7513.21351.53655
13514.814.48150.318468
13612.4512.9765-0.526511
13712.659.148853.50115
13817.3519.1848-1.83482
1398.67.781580.818424
14018.420.3315-1.93151
14116.116.9205-0.820532
14211.65.705595.89441
14317.7514.49353.25651
14415.2513.02972.22027
14517.6516.35831.29169
14616.3513.93562.41442
14717.6516.0181.63198
14813.612.39891.20107
14914.3516.8805-2.53053
15014.7513.49321.25682
15118.2522.7844-4.53445
1529.97.6042.296
1531612.9173.08299
15418.2518.09610.153869
15516.8515.36931.4807
15614.615.081-0.481006
15713.8512.11861.73136
15818.9517.76091.18908
15915.619.1962-3.59617
16014.8516.7165-1.86651
16111.757.727324.02268
16218.4520.2088-1.75884
16315.913.78222.11778
16417.111.25555.84447
16516.113.85492.24509
16619.919.11070.789251
16710.959.466951.48305
16818.4515.5472.90296
16915.116.9186-1.81861
1701518.8205-3.82053
17111.3511.06290.287069
17215.9511.96533.98468
17318.116.85111.24892
17414.615.839-1.23903
17515.416.6404-1.24043
17615.411.58253.81753
17717.617.771-0.170995
17813.359.982833.36717
17919.117.43791.66205
18015.3518.1923-2.8423
1817.69.19895-1.59895
18213.413.8459-0.445943
18313.912.14431.7557
18419.117.79631.3037
18515.2515.6311-0.381068
18612.911.58691.31307
18716.111.7234.37698
18817.3517.23980.11019
18913.1511.31061.83936
19012.1510.38741.76262
19112.613.9299-1.3299
19210.358.302812.04719
19315.417.5203-2.12025
1949.65.145144.45486
19518.216.94051.25947
19613.614.4637-0.863671
19714.8516.5665-1.71645
19814.7514.59010.159906
19914.110.39653.70351
20014.911.98892.91109
20116.2515.24981.00023
20219.2517.45721.79282
20313.613.11060.489429
20413.614.2858-0.685802
20515.6513.41372.23633
20612.759.974882.77512
20714.615.9753-1.37534
2089.858.960030.889973
20912.6510.47562.1744
21019.217.07692.1231
21116.615.6560.944012
21211.28.725212.47479
21315.2517.5578-2.30778
21411.914.2718-2.37183
21513.213.4855-0.28545
21616.3515.13271.21734
21712.49.736592.66341
21815.8513.27022.57977
21918.1518.4265-0.276513
22011.1511.7413-0.591283
22115.6512.91022.73978
22217.7522.5351-4.78506
2237.656.447631.20237
22412.357.132895.21711
22515.613.53242.06755
22619.316.14183.15824
22715.211.55823.64183
22817.114.60982.49021
22915.611.54884.05118
23018.414.4383.96201
23119.0512.96086.08916
23218.5517.35111.19887
23319.118.08791.01211
23413.112.89820.201848
23512.8513.1806-0.330562
2369.514.7885-5.28851
2374.52.817141.68286
23811.8513.0239-1.17393
23913.613.57470.0253497
24011.710.25861.44135
24112.414.2705-1.87048
24213.3514.8535-1.50346
24311.48.287413.11259
24414.912.23682.66316
24519.920.5499-0.649894
24611.212.0534-0.853384
24714.612.83031.76967
24817.614.58713.01287
24914.0512.63841.41161
25016.115.25290.847076
25113.3512.34121.00884
25211.8513.6211-1.77107
25311.9512.4305-0.480492
25414.7512.79671.95333
25515.1515.6462-0.496189
25613.212.88220.317785
25716.8518.904-2.05397
2587.8513.6362-5.78617
2597.76.904120.795882
26012.615.974-3.374
2617.858.00356-0.153559
26210.9511.1614-0.21145
26312.3514.4363-2.08626
2649.956.995232.95477
26514.914.13360.766369
26616.6517.703-1.05297
26713.413.5378-0.137809
26813.959.284244.66576
26915.712.43753.26247
27016.8516.66290.187117
27110.957.074693.87531
27215.3514.69930.650669
27312.211.34560.854403
27415.114.93550.164538
27517.7515.80571.94432
27615.213.64141.55859
27714.613.1981.40195
27816.6518.6616-2.01155
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
210.2543690.5087370.745631
220.1374920.2749850.862508
230.07073640.1414730.929264
240.0313760.0627520.968624
250.01326940.02653880.986731
260.007717910.01543580.992282
270.003167490.006334980.996833
280.001251540.002503080.998748
290.002928830.005857660.997071
300.00169620.00339240.998304
310.003683890.007367770.996316
320.001794580.003589170.998205
330.000908430.001816860.999092
340.001596410.003192820.998404
350.00100830.002016610.998992
360.0005131510.00102630.999487
370.0003627430.0007254860.999637
380.0002543210.0005086420.999746
390.01164290.02328570.988357
400.007757010.0155140.992243
410.01587250.0317450.984127
420.01433310.02866620.985667
430.01544170.03088340.984558
440.01070050.0214010.9893
450.00833960.01667920.99166
460.006594010.0131880.993406
470.01167580.02335150.988324
480.01508550.0301710.984914
490.04083290.08166580.959167
500.0407380.08147610.959262
510.03011150.0602230.969888
520.02678480.05356960.973215
530.02757860.05515730.972421
540.03163350.0632670.968366
550.0726130.1452260.927387
560.0614160.1228320.938584
570.2798560.5597110.720144
580.3065410.6130820.693459
590.2680540.5361080.731946
600.2770720.5541440.722928
610.3000320.6000640.699968
620.2689010.5378030.731099
630.3431930.6863850.656807
640.3687790.7375580.631221
650.3880120.7760240.611988
660.3617360.7234730.638264
670.3565520.7131030.643448
680.3462580.6925160.653742
690.3553560.7107130.644644
700.3178840.6357680.682116
710.2934440.5868870.706556
720.2643970.5287940.735603
730.2517690.5035370.748231
740.2816250.5632510.718375
750.2476840.4953670.752316
760.2191280.4382550.780872
770.190890.3817790.80911
780.1914510.3829020.808549
790.1652670.3305350.834733
800.1629520.3259040.837048
810.1416740.2833480.858326
820.1478430.2956870.852157
830.1285820.2571630.871418
840.2274050.454810.772595
850.2218860.4437720.778114
860.1937370.3874750.806263
870.1692740.3385480.830726
880.1527190.3054380.847281
890.1608560.3217120.839144
900.1652430.3304860.834757
910.1799730.3599460.820027
920.3290710.6581430.670929
930.3058960.6117920.694104
940.3159980.6319960.684002
950.3175220.6350440.682478
960.301860.603720.69814
970.3891260.7782530.610874
980.3713640.7427270.628636
990.3994880.7989750.600512
1000.4700950.940190.529905
1010.4435890.8871770.556411
1020.453930.9078590.54607
1030.4595040.9190070.540496
1040.4625930.9251850.537407
1050.4731770.9463540.526823
1060.5030070.9939850.496993
1070.5745630.8508750.425437
1080.7927820.4144350.207218
1090.8387210.3225590.161279
1100.8381750.3236510.161825
1110.8439520.3120960.156048
1120.8534520.2930950.146548
1130.8967260.2065480.103274
1140.9262520.1474960.0737478
1150.9667720.06645550.0332277
1160.9801180.0397630.0198815
1170.9761070.04778560.0238928
1180.9811650.037670.018835
1190.9811640.03767150.0188357
1200.983440.03311970.0165598
1210.9810580.03788410.018942
1220.9887950.02240910.0112046
1230.9892110.02157730.0107887
1240.9971410.005717710.00285885
1250.9972480.005503360.00275168
1260.9965930.006814710.00340736
1270.9970730.005853380.00292669
1280.9966520.006695080.00334754
1290.99720.005600180.00280009
1300.9971320.005735810.00286791
1310.9970620.005875570.00293779
1320.9964110.007178590.0035893
1330.9961840.00763180.0038159
1340.9958710.008257230.00412861
1350.9946850.01062960.00531478
1360.9931270.01374650.00687323
1370.9949870.01002530.00501264
1380.9943320.01133620.00566808
1390.9933520.01329580.00664789
1400.9916070.01678580.0083929
1410.9893160.02136780.0106839
1420.9947420.01051580.00525789
1430.9946540.01069150.00534574
1440.9951930.009614510.00480726
1450.9940110.01197850.00598924
1460.9939090.0121810.0060905
1470.9928720.01425560.00712781
1480.9910370.01792580.00896292
1490.9902670.01946660.00973328
1500.9888990.02220270.0111013
1510.9959780.008043760.00402188
1520.9955780.008843710.00442186
1530.9962460.007508560.00375428
1540.9952090.009581730.00479086
1550.9949470.01010540.00505271
1560.9934510.01309720.00654862
1570.9923020.01539620.00769808
1580.9905830.01883460.00941732
1590.9909740.01805130.00902567
1600.9918140.01637180.00818591
1610.9941610.0116790.00583948
1620.9923960.01520870.00760437
1630.9920610.01587810.00793903
1640.9996530.0006935130.000346757
1650.9995920.0008152540.000407627
1660.9995230.0009539330.000476966
1670.9994170.001165610.000582805
1680.9993950.0012090.0006045
1690.9993380.001324610.000662304
1700.9994590.001081040.00054052
1710.9992730.001453790.000726895
1720.9994260.001147190.000573595
1730.9992710.001457280.000728638
1740.9991290.001741420.000870712
1750.9989990.002002190.00100109
1760.9993040.001392060.00069603
1770.9990310.001938750.000969375
1780.9992040.001592910.000796453
1790.9989920.002015370.00100769
1800.9988740.002251120.00112556
1810.9987750.002449350.00122467
1820.9985880.002823260.00141163
1830.9982870.00342530.00171265
1840.9977690.004462180.00223109
1850.9979770.00404560.0020228
1860.9974490.005102960.00255148
1870.997980.004039120.00201956
1880.9977450.004509810.0022549
1890.9977520.004495420.00224771
1900.9977370.004525390.00226269
1910.9970470.005905950.00295297
1920.9966790.006642620.00332131
1930.9980050.003989540.00199477
1940.9984920.003015860.00150793
1950.9981990.003602450.00180123
1960.9975470.004906520.00245326
1970.9970420.005916130.00295807
1980.9959420.008115240.00405762
1990.9956960.008608230.00430412
2000.9949240.01015220.00507609
2010.993630.0127390.00636951
2020.9936470.0127070.0063535
2030.9928780.01424350.00712177
2040.9909760.01804820.00902411
2050.9892750.02144940.0107247
2060.9870340.02593190.0129659
2070.9854190.02916190.014581
2080.982080.03583960.0179198
2090.9781590.04368220.0218411
2100.9772950.04540910.0227046
2110.9730230.05395440.0269772
2120.96630.06739960.0336998
2130.9655740.06885180.0344259
2140.9577310.08453790.0422689
2150.9489610.1020780.0510392
2160.937670.124660.0623301
2170.9370840.1258310.0629155
2180.9259710.1480570.0740285
2190.9069180.1861640.0930822
2200.8867370.2265260.113263
2210.8833330.2333340.116667
2220.9053580.1892830.0946417
2230.8863150.227370.113685
2240.9471510.1056990.0528495
2250.9338820.1322360.0661178
2260.9545390.09092280.0454614
2270.9538830.09223360.0461168
2280.9465560.1068890.0534443
2290.9830270.03394690.0169734
2300.9859060.02818720.0140936
2310.9840290.03194270.0159714
2320.9791170.04176610.0208831
2330.9719120.05617540.0280877
2340.964240.07152070.0357604
2350.9502240.09955270.0497764
2360.9643710.07125810.035629
2370.9630740.0738510.0369255
2380.9479870.1040270.0520133
2390.9654010.06919860.0345993
2400.950810.09838040.0491902
2410.9371710.1256580.0628289
2420.913210.1735790.0867897
2430.8943350.2113310.105665
2440.8571860.2856280.142814
2450.8540260.2919490.145974
2460.8040850.3918290.195915
2470.7783030.4433940.221697
2480.8548750.2902510.145125
2490.9420430.1159140.0579569
2500.9143930.1712140.0856072
2510.8977070.2045860.102293
2520.8495280.3009450.150472
2530.837130.3257410.16287
2540.746530.506940.25347
2550.6273170.7453670.372683
2560.4824210.9648430.517579
2570.344980.689960.65502
2580.663130.6737390.33687

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
21 & 0.254369 & 0.508737 & 0.745631 \tabularnewline
22 & 0.137492 & 0.274985 & 0.862508 \tabularnewline
23 & 0.0707364 & 0.141473 & 0.929264 \tabularnewline
24 & 0.031376 & 0.062752 & 0.968624 \tabularnewline
25 & 0.0132694 & 0.0265388 & 0.986731 \tabularnewline
26 & 0.00771791 & 0.0154358 & 0.992282 \tabularnewline
27 & 0.00316749 & 0.00633498 & 0.996833 \tabularnewline
28 & 0.00125154 & 0.00250308 & 0.998748 \tabularnewline
29 & 0.00292883 & 0.00585766 & 0.997071 \tabularnewline
30 & 0.0016962 & 0.0033924 & 0.998304 \tabularnewline
31 & 0.00368389 & 0.00736777 & 0.996316 \tabularnewline
32 & 0.00179458 & 0.00358917 & 0.998205 \tabularnewline
33 & 0.00090843 & 0.00181686 & 0.999092 \tabularnewline
34 & 0.00159641 & 0.00319282 & 0.998404 \tabularnewline
35 & 0.0010083 & 0.00201661 & 0.998992 \tabularnewline
36 & 0.000513151 & 0.0010263 & 0.999487 \tabularnewline
37 & 0.000362743 & 0.000725486 & 0.999637 \tabularnewline
38 & 0.000254321 & 0.000508642 & 0.999746 \tabularnewline
39 & 0.0116429 & 0.0232857 & 0.988357 \tabularnewline
40 & 0.00775701 & 0.015514 & 0.992243 \tabularnewline
41 & 0.0158725 & 0.031745 & 0.984127 \tabularnewline
42 & 0.0143331 & 0.0286662 & 0.985667 \tabularnewline
43 & 0.0154417 & 0.0308834 & 0.984558 \tabularnewline
44 & 0.0107005 & 0.021401 & 0.9893 \tabularnewline
45 & 0.0083396 & 0.0166792 & 0.99166 \tabularnewline
46 & 0.00659401 & 0.013188 & 0.993406 \tabularnewline
47 & 0.0116758 & 0.0233515 & 0.988324 \tabularnewline
48 & 0.0150855 & 0.030171 & 0.984914 \tabularnewline
49 & 0.0408329 & 0.0816658 & 0.959167 \tabularnewline
50 & 0.040738 & 0.0814761 & 0.959262 \tabularnewline
51 & 0.0301115 & 0.060223 & 0.969888 \tabularnewline
52 & 0.0267848 & 0.0535696 & 0.973215 \tabularnewline
53 & 0.0275786 & 0.0551573 & 0.972421 \tabularnewline
54 & 0.0316335 & 0.063267 & 0.968366 \tabularnewline
55 & 0.072613 & 0.145226 & 0.927387 \tabularnewline
56 & 0.061416 & 0.122832 & 0.938584 \tabularnewline
57 & 0.279856 & 0.559711 & 0.720144 \tabularnewline
58 & 0.306541 & 0.613082 & 0.693459 \tabularnewline
59 & 0.268054 & 0.536108 & 0.731946 \tabularnewline
60 & 0.277072 & 0.554144 & 0.722928 \tabularnewline
61 & 0.300032 & 0.600064 & 0.699968 \tabularnewline
62 & 0.268901 & 0.537803 & 0.731099 \tabularnewline
63 & 0.343193 & 0.686385 & 0.656807 \tabularnewline
64 & 0.368779 & 0.737558 & 0.631221 \tabularnewline
65 & 0.388012 & 0.776024 & 0.611988 \tabularnewline
66 & 0.361736 & 0.723473 & 0.638264 \tabularnewline
67 & 0.356552 & 0.713103 & 0.643448 \tabularnewline
68 & 0.346258 & 0.692516 & 0.653742 \tabularnewline
69 & 0.355356 & 0.710713 & 0.644644 \tabularnewline
70 & 0.317884 & 0.635768 & 0.682116 \tabularnewline
71 & 0.293444 & 0.586887 & 0.706556 \tabularnewline
72 & 0.264397 & 0.528794 & 0.735603 \tabularnewline
73 & 0.251769 & 0.503537 & 0.748231 \tabularnewline
74 & 0.281625 & 0.563251 & 0.718375 \tabularnewline
75 & 0.247684 & 0.495367 & 0.752316 \tabularnewline
76 & 0.219128 & 0.438255 & 0.780872 \tabularnewline
77 & 0.19089 & 0.381779 & 0.80911 \tabularnewline
78 & 0.191451 & 0.382902 & 0.808549 \tabularnewline
79 & 0.165267 & 0.330535 & 0.834733 \tabularnewline
80 & 0.162952 & 0.325904 & 0.837048 \tabularnewline
81 & 0.141674 & 0.283348 & 0.858326 \tabularnewline
82 & 0.147843 & 0.295687 & 0.852157 \tabularnewline
83 & 0.128582 & 0.257163 & 0.871418 \tabularnewline
84 & 0.227405 & 0.45481 & 0.772595 \tabularnewline
85 & 0.221886 & 0.443772 & 0.778114 \tabularnewline
86 & 0.193737 & 0.387475 & 0.806263 \tabularnewline
87 & 0.169274 & 0.338548 & 0.830726 \tabularnewline
88 & 0.152719 & 0.305438 & 0.847281 \tabularnewline
89 & 0.160856 & 0.321712 & 0.839144 \tabularnewline
90 & 0.165243 & 0.330486 & 0.834757 \tabularnewline
91 & 0.179973 & 0.359946 & 0.820027 \tabularnewline
92 & 0.329071 & 0.658143 & 0.670929 \tabularnewline
93 & 0.305896 & 0.611792 & 0.694104 \tabularnewline
94 & 0.315998 & 0.631996 & 0.684002 \tabularnewline
95 & 0.317522 & 0.635044 & 0.682478 \tabularnewline
96 & 0.30186 & 0.60372 & 0.69814 \tabularnewline
97 & 0.389126 & 0.778253 & 0.610874 \tabularnewline
98 & 0.371364 & 0.742727 & 0.628636 \tabularnewline
99 & 0.399488 & 0.798975 & 0.600512 \tabularnewline
100 & 0.470095 & 0.94019 & 0.529905 \tabularnewline
101 & 0.443589 & 0.887177 & 0.556411 \tabularnewline
102 & 0.45393 & 0.907859 & 0.54607 \tabularnewline
103 & 0.459504 & 0.919007 & 0.540496 \tabularnewline
104 & 0.462593 & 0.925185 & 0.537407 \tabularnewline
105 & 0.473177 & 0.946354 & 0.526823 \tabularnewline
106 & 0.503007 & 0.993985 & 0.496993 \tabularnewline
107 & 0.574563 & 0.850875 & 0.425437 \tabularnewline
108 & 0.792782 & 0.414435 & 0.207218 \tabularnewline
109 & 0.838721 & 0.322559 & 0.161279 \tabularnewline
110 & 0.838175 & 0.323651 & 0.161825 \tabularnewline
111 & 0.843952 & 0.312096 & 0.156048 \tabularnewline
112 & 0.853452 & 0.293095 & 0.146548 \tabularnewline
113 & 0.896726 & 0.206548 & 0.103274 \tabularnewline
114 & 0.926252 & 0.147496 & 0.0737478 \tabularnewline
115 & 0.966772 & 0.0664555 & 0.0332277 \tabularnewline
116 & 0.980118 & 0.039763 & 0.0198815 \tabularnewline
117 & 0.976107 & 0.0477856 & 0.0238928 \tabularnewline
118 & 0.981165 & 0.03767 & 0.018835 \tabularnewline
119 & 0.981164 & 0.0376715 & 0.0188357 \tabularnewline
120 & 0.98344 & 0.0331197 & 0.0165598 \tabularnewline
121 & 0.981058 & 0.0378841 & 0.018942 \tabularnewline
122 & 0.988795 & 0.0224091 & 0.0112046 \tabularnewline
123 & 0.989211 & 0.0215773 & 0.0107887 \tabularnewline
124 & 0.997141 & 0.00571771 & 0.00285885 \tabularnewline
125 & 0.997248 & 0.00550336 & 0.00275168 \tabularnewline
126 & 0.996593 & 0.00681471 & 0.00340736 \tabularnewline
127 & 0.997073 & 0.00585338 & 0.00292669 \tabularnewline
128 & 0.996652 & 0.00669508 & 0.00334754 \tabularnewline
129 & 0.9972 & 0.00560018 & 0.00280009 \tabularnewline
130 & 0.997132 & 0.00573581 & 0.00286791 \tabularnewline
131 & 0.997062 & 0.00587557 & 0.00293779 \tabularnewline
132 & 0.996411 & 0.00717859 & 0.0035893 \tabularnewline
133 & 0.996184 & 0.0076318 & 0.0038159 \tabularnewline
134 & 0.995871 & 0.00825723 & 0.00412861 \tabularnewline
135 & 0.994685 & 0.0106296 & 0.00531478 \tabularnewline
136 & 0.993127 & 0.0137465 & 0.00687323 \tabularnewline
137 & 0.994987 & 0.0100253 & 0.00501264 \tabularnewline
138 & 0.994332 & 0.0113362 & 0.00566808 \tabularnewline
139 & 0.993352 & 0.0132958 & 0.00664789 \tabularnewline
140 & 0.991607 & 0.0167858 & 0.0083929 \tabularnewline
141 & 0.989316 & 0.0213678 & 0.0106839 \tabularnewline
142 & 0.994742 & 0.0105158 & 0.00525789 \tabularnewline
143 & 0.994654 & 0.0106915 & 0.00534574 \tabularnewline
144 & 0.995193 & 0.00961451 & 0.00480726 \tabularnewline
145 & 0.994011 & 0.0119785 & 0.00598924 \tabularnewline
146 & 0.993909 & 0.012181 & 0.0060905 \tabularnewline
147 & 0.992872 & 0.0142556 & 0.00712781 \tabularnewline
148 & 0.991037 & 0.0179258 & 0.00896292 \tabularnewline
149 & 0.990267 & 0.0194666 & 0.00973328 \tabularnewline
150 & 0.988899 & 0.0222027 & 0.0111013 \tabularnewline
151 & 0.995978 & 0.00804376 & 0.00402188 \tabularnewline
152 & 0.995578 & 0.00884371 & 0.00442186 \tabularnewline
153 & 0.996246 & 0.00750856 & 0.00375428 \tabularnewline
154 & 0.995209 & 0.00958173 & 0.00479086 \tabularnewline
155 & 0.994947 & 0.0101054 & 0.00505271 \tabularnewline
156 & 0.993451 & 0.0130972 & 0.00654862 \tabularnewline
157 & 0.992302 & 0.0153962 & 0.00769808 \tabularnewline
158 & 0.990583 & 0.0188346 & 0.00941732 \tabularnewline
159 & 0.990974 & 0.0180513 & 0.00902567 \tabularnewline
160 & 0.991814 & 0.0163718 & 0.00818591 \tabularnewline
161 & 0.994161 & 0.011679 & 0.00583948 \tabularnewline
162 & 0.992396 & 0.0152087 & 0.00760437 \tabularnewline
163 & 0.992061 & 0.0158781 & 0.00793903 \tabularnewline
164 & 0.999653 & 0.000693513 & 0.000346757 \tabularnewline
165 & 0.999592 & 0.000815254 & 0.000407627 \tabularnewline
166 & 0.999523 & 0.000953933 & 0.000476966 \tabularnewline
167 & 0.999417 & 0.00116561 & 0.000582805 \tabularnewline
168 & 0.999395 & 0.001209 & 0.0006045 \tabularnewline
169 & 0.999338 & 0.00132461 & 0.000662304 \tabularnewline
170 & 0.999459 & 0.00108104 & 0.00054052 \tabularnewline
171 & 0.999273 & 0.00145379 & 0.000726895 \tabularnewline
172 & 0.999426 & 0.00114719 & 0.000573595 \tabularnewline
173 & 0.999271 & 0.00145728 & 0.000728638 \tabularnewline
174 & 0.999129 & 0.00174142 & 0.000870712 \tabularnewline
175 & 0.998999 & 0.00200219 & 0.00100109 \tabularnewline
176 & 0.999304 & 0.00139206 & 0.00069603 \tabularnewline
177 & 0.999031 & 0.00193875 & 0.000969375 \tabularnewline
178 & 0.999204 & 0.00159291 & 0.000796453 \tabularnewline
179 & 0.998992 & 0.00201537 & 0.00100769 \tabularnewline
180 & 0.998874 & 0.00225112 & 0.00112556 \tabularnewline
181 & 0.998775 & 0.00244935 & 0.00122467 \tabularnewline
182 & 0.998588 & 0.00282326 & 0.00141163 \tabularnewline
183 & 0.998287 & 0.0034253 & 0.00171265 \tabularnewline
184 & 0.997769 & 0.00446218 & 0.00223109 \tabularnewline
185 & 0.997977 & 0.0040456 & 0.0020228 \tabularnewline
186 & 0.997449 & 0.00510296 & 0.00255148 \tabularnewline
187 & 0.99798 & 0.00403912 & 0.00201956 \tabularnewline
188 & 0.997745 & 0.00450981 & 0.0022549 \tabularnewline
189 & 0.997752 & 0.00449542 & 0.00224771 \tabularnewline
190 & 0.997737 & 0.00452539 & 0.00226269 \tabularnewline
191 & 0.997047 & 0.00590595 & 0.00295297 \tabularnewline
192 & 0.996679 & 0.00664262 & 0.00332131 \tabularnewline
193 & 0.998005 & 0.00398954 & 0.00199477 \tabularnewline
194 & 0.998492 & 0.00301586 & 0.00150793 \tabularnewline
195 & 0.998199 & 0.00360245 & 0.00180123 \tabularnewline
196 & 0.997547 & 0.00490652 & 0.00245326 \tabularnewline
197 & 0.997042 & 0.00591613 & 0.00295807 \tabularnewline
198 & 0.995942 & 0.00811524 & 0.00405762 \tabularnewline
199 & 0.995696 & 0.00860823 & 0.00430412 \tabularnewline
200 & 0.994924 & 0.0101522 & 0.00507609 \tabularnewline
201 & 0.99363 & 0.012739 & 0.00636951 \tabularnewline
202 & 0.993647 & 0.012707 & 0.0063535 \tabularnewline
203 & 0.992878 & 0.0142435 & 0.00712177 \tabularnewline
204 & 0.990976 & 0.0180482 & 0.00902411 \tabularnewline
205 & 0.989275 & 0.0214494 & 0.0107247 \tabularnewline
206 & 0.987034 & 0.0259319 & 0.0129659 \tabularnewline
207 & 0.985419 & 0.0291619 & 0.014581 \tabularnewline
208 & 0.98208 & 0.0358396 & 0.0179198 \tabularnewline
209 & 0.978159 & 0.0436822 & 0.0218411 \tabularnewline
210 & 0.977295 & 0.0454091 & 0.0227046 \tabularnewline
211 & 0.973023 & 0.0539544 & 0.0269772 \tabularnewline
212 & 0.9663 & 0.0673996 & 0.0336998 \tabularnewline
213 & 0.965574 & 0.0688518 & 0.0344259 \tabularnewline
214 & 0.957731 & 0.0845379 & 0.0422689 \tabularnewline
215 & 0.948961 & 0.102078 & 0.0510392 \tabularnewline
216 & 0.93767 & 0.12466 & 0.0623301 \tabularnewline
217 & 0.937084 & 0.125831 & 0.0629155 \tabularnewline
218 & 0.925971 & 0.148057 & 0.0740285 \tabularnewline
219 & 0.906918 & 0.186164 & 0.0930822 \tabularnewline
220 & 0.886737 & 0.226526 & 0.113263 \tabularnewline
221 & 0.883333 & 0.233334 & 0.116667 \tabularnewline
222 & 0.905358 & 0.189283 & 0.0946417 \tabularnewline
223 & 0.886315 & 0.22737 & 0.113685 \tabularnewline
224 & 0.947151 & 0.105699 & 0.0528495 \tabularnewline
225 & 0.933882 & 0.132236 & 0.0661178 \tabularnewline
226 & 0.954539 & 0.0909228 & 0.0454614 \tabularnewline
227 & 0.953883 & 0.0922336 & 0.0461168 \tabularnewline
228 & 0.946556 & 0.106889 & 0.0534443 \tabularnewline
229 & 0.983027 & 0.0339469 & 0.0169734 \tabularnewline
230 & 0.985906 & 0.0281872 & 0.0140936 \tabularnewline
231 & 0.984029 & 0.0319427 & 0.0159714 \tabularnewline
232 & 0.979117 & 0.0417661 & 0.0208831 \tabularnewline
233 & 0.971912 & 0.0561754 & 0.0280877 \tabularnewline
234 & 0.96424 & 0.0715207 & 0.0357604 \tabularnewline
235 & 0.950224 & 0.0995527 & 0.0497764 \tabularnewline
236 & 0.964371 & 0.0712581 & 0.035629 \tabularnewline
237 & 0.963074 & 0.073851 & 0.0369255 \tabularnewline
238 & 0.947987 & 0.104027 & 0.0520133 \tabularnewline
239 & 0.965401 & 0.0691986 & 0.0345993 \tabularnewline
240 & 0.95081 & 0.0983804 & 0.0491902 \tabularnewline
241 & 0.937171 & 0.125658 & 0.0628289 \tabularnewline
242 & 0.91321 & 0.173579 & 0.0867897 \tabularnewline
243 & 0.894335 & 0.211331 & 0.105665 \tabularnewline
244 & 0.857186 & 0.285628 & 0.142814 \tabularnewline
245 & 0.854026 & 0.291949 & 0.145974 \tabularnewline
246 & 0.804085 & 0.391829 & 0.195915 \tabularnewline
247 & 0.778303 & 0.443394 & 0.221697 \tabularnewline
248 & 0.854875 & 0.290251 & 0.145125 \tabularnewline
249 & 0.942043 & 0.115914 & 0.0579569 \tabularnewline
250 & 0.914393 & 0.171214 & 0.0856072 \tabularnewline
251 & 0.897707 & 0.204586 & 0.102293 \tabularnewline
252 & 0.849528 & 0.300945 & 0.150472 \tabularnewline
253 & 0.83713 & 0.325741 & 0.16287 \tabularnewline
254 & 0.74653 & 0.50694 & 0.25347 \tabularnewline
255 & 0.627317 & 0.745367 & 0.372683 \tabularnewline
256 & 0.482421 & 0.964843 & 0.517579 \tabularnewline
257 & 0.34498 & 0.68996 & 0.65502 \tabularnewline
258 & 0.66313 & 0.673739 & 0.33687 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269694&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]21[/C][C]0.254369[/C][C]0.508737[/C][C]0.745631[/C][/ROW]
[ROW][C]22[/C][C]0.137492[/C][C]0.274985[/C][C]0.862508[/C][/ROW]
[ROW][C]23[/C][C]0.0707364[/C][C]0.141473[/C][C]0.929264[/C][/ROW]
[ROW][C]24[/C][C]0.031376[/C][C]0.062752[/C][C]0.968624[/C][/ROW]
[ROW][C]25[/C][C]0.0132694[/C][C]0.0265388[/C][C]0.986731[/C][/ROW]
[ROW][C]26[/C][C]0.00771791[/C][C]0.0154358[/C][C]0.992282[/C][/ROW]
[ROW][C]27[/C][C]0.00316749[/C][C]0.00633498[/C][C]0.996833[/C][/ROW]
[ROW][C]28[/C][C]0.00125154[/C][C]0.00250308[/C][C]0.998748[/C][/ROW]
[ROW][C]29[/C][C]0.00292883[/C][C]0.00585766[/C][C]0.997071[/C][/ROW]
[ROW][C]30[/C][C]0.0016962[/C][C]0.0033924[/C][C]0.998304[/C][/ROW]
[ROW][C]31[/C][C]0.00368389[/C][C]0.00736777[/C][C]0.996316[/C][/ROW]
[ROW][C]32[/C][C]0.00179458[/C][C]0.00358917[/C][C]0.998205[/C][/ROW]
[ROW][C]33[/C][C]0.00090843[/C][C]0.00181686[/C][C]0.999092[/C][/ROW]
[ROW][C]34[/C][C]0.00159641[/C][C]0.00319282[/C][C]0.998404[/C][/ROW]
[ROW][C]35[/C][C]0.0010083[/C][C]0.00201661[/C][C]0.998992[/C][/ROW]
[ROW][C]36[/C][C]0.000513151[/C][C]0.0010263[/C][C]0.999487[/C][/ROW]
[ROW][C]37[/C][C]0.000362743[/C][C]0.000725486[/C][C]0.999637[/C][/ROW]
[ROW][C]38[/C][C]0.000254321[/C][C]0.000508642[/C][C]0.999746[/C][/ROW]
[ROW][C]39[/C][C]0.0116429[/C][C]0.0232857[/C][C]0.988357[/C][/ROW]
[ROW][C]40[/C][C]0.00775701[/C][C]0.015514[/C][C]0.992243[/C][/ROW]
[ROW][C]41[/C][C]0.0158725[/C][C]0.031745[/C][C]0.984127[/C][/ROW]
[ROW][C]42[/C][C]0.0143331[/C][C]0.0286662[/C][C]0.985667[/C][/ROW]
[ROW][C]43[/C][C]0.0154417[/C][C]0.0308834[/C][C]0.984558[/C][/ROW]
[ROW][C]44[/C][C]0.0107005[/C][C]0.021401[/C][C]0.9893[/C][/ROW]
[ROW][C]45[/C][C]0.0083396[/C][C]0.0166792[/C][C]0.99166[/C][/ROW]
[ROW][C]46[/C][C]0.00659401[/C][C]0.013188[/C][C]0.993406[/C][/ROW]
[ROW][C]47[/C][C]0.0116758[/C][C]0.0233515[/C][C]0.988324[/C][/ROW]
[ROW][C]48[/C][C]0.0150855[/C][C]0.030171[/C][C]0.984914[/C][/ROW]
[ROW][C]49[/C][C]0.0408329[/C][C]0.0816658[/C][C]0.959167[/C][/ROW]
[ROW][C]50[/C][C]0.040738[/C][C]0.0814761[/C][C]0.959262[/C][/ROW]
[ROW][C]51[/C][C]0.0301115[/C][C]0.060223[/C][C]0.969888[/C][/ROW]
[ROW][C]52[/C][C]0.0267848[/C][C]0.0535696[/C][C]0.973215[/C][/ROW]
[ROW][C]53[/C][C]0.0275786[/C][C]0.0551573[/C][C]0.972421[/C][/ROW]
[ROW][C]54[/C][C]0.0316335[/C][C]0.063267[/C][C]0.968366[/C][/ROW]
[ROW][C]55[/C][C]0.072613[/C][C]0.145226[/C][C]0.927387[/C][/ROW]
[ROW][C]56[/C][C]0.061416[/C][C]0.122832[/C][C]0.938584[/C][/ROW]
[ROW][C]57[/C][C]0.279856[/C][C]0.559711[/C][C]0.720144[/C][/ROW]
[ROW][C]58[/C][C]0.306541[/C][C]0.613082[/C][C]0.693459[/C][/ROW]
[ROW][C]59[/C][C]0.268054[/C][C]0.536108[/C][C]0.731946[/C][/ROW]
[ROW][C]60[/C][C]0.277072[/C][C]0.554144[/C][C]0.722928[/C][/ROW]
[ROW][C]61[/C][C]0.300032[/C][C]0.600064[/C][C]0.699968[/C][/ROW]
[ROW][C]62[/C][C]0.268901[/C][C]0.537803[/C][C]0.731099[/C][/ROW]
[ROW][C]63[/C][C]0.343193[/C][C]0.686385[/C][C]0.656807[/C][/ROW]
[ROW][C]64[/C][C]0.368779[/C][C]0.737558[/C][C]0.631221[/C][/ROW]
[ROW][C]65[/C][C]0.388012[/C][C]0.776024[/C][C]0.611988[/C][/ROW]
[ROW][C]66[/C][C]0.361736[/C][C]0.723473[/C][C]0.638264[/C][/ROW]
[ROW][C]67[/C][C]0.356552[/C][C]0.713103[/C][C]0.643448[/C][/ROW]
[ROW][C]68[/C][C]0.346258[/C][C]0.692516[/C][C]0.653742[/C][/ROW]
[ROW][C]69[/C][C]0.355356[/C][C]0.710713[/C][C]0.644644[/C][/ROW]
[ROW][C]70[/C][C]0.317884[/C][C]0.635768[/C][C]0.682116[/C][/ROW]
[ROW][C]71[/C][C]0.293444[/C][C]0.586887[/C][C]0.706556[/C][/ROW]
[ROW][C]72[/C][C]0.264397[/C][C]0.528794[/C][C]0.735603[/C][/ROW]
[ROW][C]73[/C][C]0.251769[/C][C]0.503537[/C][C]0.748231[/C][/ROW]
[ROW][C]74[/C][C]0.281625[/C][C]0.563251[/C][C]0.718375[/C][/ROW]
[ROW][C]75[/C][C]0.247684[/C][C]0.495367[/C][C]0.752316[/C][/ROW]
[ROW][C]76[/C][C]0.219128[/C][C]0.438255[/C][C]0.780872[/C][/ROW]
[ROW][C]77[/C][C]0.19089[/C][C]0.381779[/C][C]0.80911[/C][/ROW]
[ROW][C]78[/C][C]0.191451[/C][C]0.382902[/C][C]0.808549[/C][/ROW]
[ROW][C]79[/C][C]0.165267[/C][C]0.330535[/C][C]0.834733[/C][/ROW]
[ROW][C]80[/C][C]0.162952[/C][C]0.325904[/C][C]0.837048[/C][/ROW]
[ROW][C]81[/C][C]0.141674[/C][C]0.283348[/C][C]0.858326[/C][/ROW]
[ROW][C]82[/C][C]0.147843[/C][C]0.295687[/C][C]0.852157[/C][/ROW]
[ROW][C]83[/C][C]0.128582[/C][C]0.257163[/C][C]0.871418[/C][/ROW]
[ROW][C]84[/C][C]0.227405[/C][C]0.45481[/C][C]0.772595[/C][/ROW]
[ROW][C]85[/C][C]0.221886[/C][C]0.443772[/C][C]0.778114[/C][/ROW]
[ROW][C]86[/C][C]0.193737[/C][C]0.387475[/C][C]0.806263[/C][/ROW]
[ROW][C]87[/C][C]0.169274[/C][C]0.338548[/C][C]0.830726[/C][/ROW]
[ROW][C]88[/C][C]0.152719[/C][C]0.305438[/C][C]0.847281[/C][/ROW]
[ROW][C]89[/C][C]0.160856[/C][C]0.321712[/C][C]0.839144[/C][/ROW]
[ROW][C]90[/C][C]0.165243[/C][C]0.330486[/C][C]0.834757[/C][/ROW]
[ROW][C]91[/C][C]0.179973[/C][C]0.359946[/C][C]0.820027[/C][/ROW]
[ROW][C]92[/C][C]0.329071[/C][C]0.658143[/C][C]0.670929[/C][/ROW]
[ROW][C]93[/C][C]0.305896[/C][C]0.611792[/C][C]0.694104[/C][/ROW]
[ROW][C]94[/C][C]0.315998[/C][C]0.631996[/C][C]0.684002[/C][/ROW]
[ROW][C]95[/C][C]0.317522[/C][C]0.635044[/C][C]0.682478[/C][/ROW]
[ROW][C]96[/C][C]0.30186[/C][C]0.60372[/C][C]0.69814[/C][/ROW]
[ROW][C]97[/C][C]0.389126[/C][C]0.778253[/C][C]0.610874[/C][/ROW]
[ROW][C]98[/C][C]0.371364[/C][C]0.742727[/C][C]0.628636[/C][/ROW]
[ROW][C]99[/C][C]0.399488[/C][C]0.798975[/C][C]0.600512[/C][/ROW]
[ROW][C]100[/C][C]0.470095[/C][C]0.94019[/C][C]0.529905[/C][/ROW]
[ROW][C]101[/C][C]0.443589[/C][C]0.887177[/C][C]0.556411[/C][/ROW]
[ROW][C]102[/C][C]0.45393[/C][C]0.907859[/C][C]0.54607[/C][/ROW]
[ROW][C]103[/C][C]0.459504[/C][C]0.919007[/C][C]0.540496[/C][/ROW]
[ROW][C]104[/C][C]0.462593[/C][C]0.925185[/C][C]0.537407[/C][/ROW]
[ROW][C]105[/C][C]0.473177[/C][C]0.946354[/C][C]0.526823[/C][/ROW]
[ROW][C]106[/C][C]0.503007[/C][C]0.993985[/C][C]0.496993[/C][/ROW]
[ROW][C]107[/C][C]0.574563[/C][C]0.850875[/C][C]0.425437[/C][/ROW]
[ROW][C]108[/C][C]0.792782[/C][C]0.414435[/C][C]0.207218[/C][/ROW]
[ROW][C]109[/C][C]0.838721[/C][C]0.322559[/C][C]0.161279[/C][/ROW]
[ROW][C]110[/C][C]0.838175[/C][C]0.323651[/C][C]0.161825[/C][/ROW]
[ROW][C]111[/C][C]0.843952[/C][C]0.312096[/C][C]0.156048[/C][/ROW]
[ROW][C]112[/C][C]0.853452[/C][C]0.293095[/C][C]0.146548[/C][/ROW]
[ROW][C]113[/C][C]0.896726[/C][C]0.206548[/C][C]0.103274[/C][/ROW]
[ROW][C]114[/C][C]0.926252[/C][C]0.147496[/C][C]0.0737478[/C][/ROW]
[ROW][C]115[/C][C]0.966772[/C][C]0.0664555[/C][C]0.0332277[/C][/ROW]
[ROW][C]116[/C][C]0.980118[/C][C]0.039763[/C][C]0.0198815[/C][/ROW]
[ROW][C]117[/C][C]0.976107[/C][C]0.0477856[/C][C]0.0238928[/C][/ROW]
[ROW][C]118[/C][C]0.981165[/C][C]0.03767[/C][C]0.018835[/C][/ROW]
[ROW][C]119[/C][C]0.981164[/C][C]0.0376715[/C][C]0.0188357[/C][/ROW]
[ROW][C]120[/C][C]0.98344[/C][C]0.0331197[/C][C]0.0165598[/C][/ROW]
[ROW][C]121[/C][C]0.981058[/C][C]0.0378841[/C][C]0.018942[/C][/ROW]
[ROW][C]122[/C][C]0.988795[/C][C]0.0224091[/C][C]0.0112046[/C][/ROW]
[ROW][C]123[/C][C]0.989211[/C][C]0.0215773[/C][C]0.0107887[/C][/ROW]
[ROW][C]124[/C][C]0.997141[/C][C]0.00571771[/C][C]0.00285885[/C][/ROW]
[ROW][C]125[/C][C]0.997248[/C][C]0.00550336[/C][C]0.00275168[/C][/ROW]
[ROW][C]126[/C][C]0.996593[/C][C]0.00681471[/C][C]0.00340736[/C][/ROW]
[ROW][C]127[/C][C]0.997073[/C][C]0.00585338[/C][C]0.00292669[/C][/ROW]
[ROW][C]128[/C][C]0.996652[/C][C]0.00669508[/C][C]0.00334754[/C][/ROW]
[ROW][C]129[/C][C]0.9972[/C][C]0.00560018[/C][C]0.00280009[/C][/ROW]
[ROW][C]130[/C][C]0.997132[/C][C]0.00573581[/C][C]0.00286791[/C][/ROW]
[ROW][C]131[/C][C]0.997062[/C][C]0.00587557[/C][C]0.00293779[/C][/ROW]
[ROW][C]132[/C][C]0.996411[/C][C]0.00717859[/C][C]0.0035893[/C][/ROW]
[ROW][C]133[/C][C]0.996184[/C][C]0.0076318[/C][C]0.0038159[/C][/ROW]
[ROW][C]134[/C][C]0.995871[/C][C]0.00825723[/C][C]0.00412861[/C][/ROW]
[ROW][C]135[/C][C]0.994685[/C][C]0.0106296[/C][C]0.00531478[/C][/ROW]
[ROW][C]136[/C][C]0.993127[/C][C]0.0137465[/C][C]0.00687323[/C][/ROW]
[ROW][C]137[/C][C]0.994987[/C][C]0.0100253[/C][C]0.00501264[/C][/ROW]
[ROW][C]138[/C][C]0.994332[/C][C]0.0113362[/C][C]0.00566808[/C][/ROW]
[ROW][C]139[/C][C]0.993352[/C][C]0.0132958[/C][C]0.00664789[/C][/ROW]
[ROW][C]140[/C][C]0.991607[/C][C]0.0167858[/C][C]0.0083929[/C][/ROW]
[ROW][C]141[/C][C]0.989316[/C][C]0.0213678[/C][C]0.0106839[/C][/ROW]
[ROW][C]142[/C][C]0.994742[/C][C]0.0105158[/C][C]0.00525789[/C][/ROW]
[ROW][C]143[/C][C]0.994654[/C][C]0.0106915[/C][C]0.00534574[/C][/ROW]
[ROW][C]144[/C][C]0.995193[/C][C]0.00961451[/C][C]0.00480726[/C][/ROW]
[ROW][C]145[/C][C]0.994011[/C][C]0.0119785[/C][C]0.00598924[/C][/ROW]
[ROW][C]146[/C][C]0.993909[/C][C]0.012181[/C][C]0.0060905[/C][/ROW]
[ROW][C]147[/C][C]0.992872[/C][C]0.0142556[/C][C]0.00712781[/C][/ROW]
[ROW][C]148[/C][C]0.991037[/C][C]0.0179258[/C][C]0.00896292[/C][/ROW]
[ROW][C]149[/C][C]0.990267[/C][C]0.0194666[/C][C]0.00973328[/C][/ROW]
[ROW][C]150[/C][C]0.988899[/C][C]0.0222027[/C][C]0.0111013[/C][/ROW]
[ROW][C]151[/C][C]0.995978[/C][C]0.00804376[/C][C]0.00402188[/C][/ROW]
[ROW][C]152[/C][C]0.995578[/C][C]0.00884371[/C][C]0.00442186[/C][/ROW]
[ROW][C]153[/C][C]0.996246[/C][C]0.00750856[/C][C]0.00375428[/C][/ROW]
[ROW][C]154[/C][C]0.995209[/C][C]0.00958173[/C][C]0.00479086[/C][/ROW]
[ROW][C]155[/C][C]0.994947[/C][C]0.0101054[/C][C]0.00505271[/C][/ROW]
[ROW][C]156[/C][C]0.993451[/C][C]0.0130972[/C][C]0.00654862[/C][/ROW]
[ROW][C]157[/C][C]0.992302[/C][C]0.0153962[/C][C]0.00769808[/C][/ROW]
[ROW][C]158[/C][C]0.990583[/C][C]0.0188346[/C][C]0.00941732[/C][/ROW]
[ROW][C]159[/C][C]0.990974[/C][C]0.0180513[/C][C]0.00902567[/C][/ROW]
[ROW][C]160[/C][C]0.991814[/C][C]0.0163718[/C][C]0.00818591[/C][/ROW]
[ROW][C]161[/C][C]0.994161[/C][C]0.011679[/C][C]0.00583948[/C][/ROW]
[ROW][C]162[/C][C]0.992396[/C][C]0.0152087[/C][C]0.00760437[/C][/ROW]
[ROW][C]163[/C][C]0.992061[/C][C]0.0158781[/C][C]0.00793903[/C][/ROW]
[ROW][C]164[/C][C]0.999653[/C][C]0.000693513[/C][C]0.000346757[/C][/ROW]
[ROW][C]165[/C][C]0.999592[/C][C]0.000815254[/C][C]0.000407627[/C][/ROW]
[ROW][C]166[/C][C]0.999523[/C][C]0.000953933[/C][C]0.000476966[/C][/ROW]
[ROW][C]167[/C][C]0.999417[/C][C]0.00116561[/C][C]0.000582805[/C][/ROW]
[ROW][C]168[/C][C]0.999395[/C][C]0.001209[/C][C]0.0006045[/C][/ROW]
[ROW][C]169[/C][C]0.999338[/C][C]0.00132461[/C][C]0.000662304[/C][/ROW]
[ROW][C]170[/C][C]0.999459[/C][C]0.00108104[/C][C]0.00054052[/C][/ROW]
[ROW][C]171[/C][C]0.999273[/C][C]0.00145379[/C][C]0.000726895[/C][/ROW]
[ROW][C]172[/C][C]0.999426[/C][C]0.00114719[/C][C]0.000573595[/C][/ROW]
[ROW][C]173[/C][C]0.999271[/C][C]0.00145728[/C][C]0.000728638[/C][/ROW]
[ROW][C]174[/C][C]0.999129[/C][C]0.00174142[/C][C]0.000870712[/C][/ROW]
[ROW][C]175[/C][C]0.998999[/C][C]0.00200219[/C][C]0.00100109[/C][/ROW]
[ROW][C]176[/C][C]0.999304[/C][C]0.00139206[/C][C]0.00069603[/C][/ROW]
[ROW][C]177[/C][C]0.999031[/C][C]0.00193875[/C][C]0.000969375[/C][/ROW]
[ROW][C]178[/C][C]0.999204[/C][C]0.00159291[/C][C]0.000796453[/C][/ROW]
[ROW][C]179[/C][C]0.998992[/C][C]0.00201537[/C][C]0.00100769[/C][/ROW]
[ROW][C]180[/C][C]0.998874[/C][C]0.00225112[/C][C]0.00112556[/C][/ROW]
[ROW][C]181[/C][C]0.998775[/C][C]0.00244935[/C][C]0.00122467[/C][/ROW]
[ROW][C]182[/C][C]0.998588[/C][C]0.00282326[/C][C]0.00141163[/C][/ROW]
[ROW][C]183[/C][C]0.998287[/C][C]0.0034253[/C][C]0.00171265[/C][/ROW]
[ROW][C]184[/C][C]0.997769[/C][C]0.00446218[/C][C]0.00223109[/C][/ROW]
[ROW][C]185[/C][C]0.997977[/C][C]0.0040456[/C][C]0.0020228[/C][/ROW]
[ROW][C]186[/C][C]0.997449[/C][C]0.00510296[/C][C]0.00255148[/C][/ROW]
[ROW][C]187[/C][C]0.99798[/C][C]0.00403912[/C][C]0.00201956[/C][/ROW]
[ROW][C]188[/C][C]0.997745[/C][C]0.00450981[/C][C]0.0022549[/C][/ROW]
[ROW][C]189[/C][C]0.997752[/C][C]0.00449542[/C][C]0.00224771[/C][/ROW]
[ROW][C]190[/C][C]0.997737[/C][C]0.00452539[/C][C]0.00226269[/C][/ROW]
[ROW][C]191[/C][C]0.997047[/C][C]0.00590595[/C][C]0.00295297[/C][/ROW]
[ROW][C]192[/C][C]0.996679[/C][C]0.00664262[/C][C]0.00332131[/C][/ROW]
[ROW][C]193[/C][C]0.998005[/C][C]0.00398954[/C][C]0.00199477[/C][/ROW]
[ROW][C]194[/C][C]0.998492[/C][C]0.00301586[/C][C]0.00150793[/C][/ROW]
[ROW][C]195[/C][C]0.998199[/C][C]0.00360245[/C][C]0.00180123[/C][/ROW]
[ROW][C]196[/C][C]0.997547[/C][C]0.00490652[/C][C]0.00245326[/C][/ROW]
[ROW][C]197[/C][C]0.997042[/C][C]0.00591613[/C][C]0.00295807[/C][/ROW]
[ROW][C]198[/C][C]0.995942[/C][C]0.00811524[/C][C]0.00405762[/C][/ROW]
[ROW][C]199[/C][C]0.995696[/C][C]0.00860823[/C][C]0.00430412[/C][/ROW]
[ROW][C]200[/C][C]0.994924[/C][C]0.0101522[/C][C]0.00507609[/C][/ROW]
[ROW][C]201[/C][C]0.99363[/C][C]0.012739[/C][C]0.00636951[/C][/ROW]
[ROW][C]202[/C][C]0.993647[/C][C]0.012707[/C][C]0.0063535[/C][/ROW]
[ROW][C]203[/C][C]0.992878[/C][C]0.0142435[/C][C]0.00712177[/C][/ROW]
[ROW][C]204[/C][C]0.990976[/C][C]0.0180482[/C][C]0.00902411[/C][/ROW]
[ROW][C]205[/C][C]0.989275[/C][C]0.0214494[/C][C]0.0107247[/C][/ROW]
[ROW][C]206[/C][C]0.987034[/C][C]0.0259319[/C][C]0.0129659[/C][/ROW]
[ROW][C]207[/C][C]0.985419[/C][C]0.0291619[/C][C]0.014581[/C][/ROW]
[ROW][C]208[/C][C]0.98208[/C][C]0.0358396[/C][C]0.0179198[/C][/ROW]
[ROW][C]209[/C][C]0.978159[/C][C]0.0436822[/C][C]0.0218411[/C][/ROW]
[ROW][C]210[/C][C]0.977295[/C][C]0.0454091[/C][C]0.0227046[/C][/ROW]
[ROW][C]211[/C][C]0.973023[/C][C]0.0539544[/C][C]0.0269772[/C][/ROW]
[ROW][C]212[/C][C]0.9663[/C][C]0.0673996[/C][C]0.0336998[/C][/ROW]
[ROW][C]213[/C][C]0.965574[/C][C]0.0688518[/C][C]0.0344259[/C][/ROW]
[ROW][C]214[/C][C]0.957731[/C][C]0.0845379[/C][C]0.0422689[/C][/ROW]
[ROW][C]215[/C][C]0.948961[/C][C]0.102078[/C][C]0.0510392[/C][/ROW]
[ROW][C]216[/C][C]0.93767[/C][C]0.12466[/C][C]0.0623301[/C][/ROW]
[ROW][C]217[/C][C]0.937084[/C][C]0.125831[/C][C]0.0629155[/C][/ROW]
[ROW][C]218[/C][C]0.925971[/C][C]0.148057[/C][C]0.0740285[/C][/ROW]
[ROW][C]219[/C][C]0.906918[/C][C]0.186164[/C][C]0.0930822[/C][/ROW]
[ROW][C]220[/C][C]0.886737[/C][C]0.226526[/C][C]0.113263[/C][/ROW]
[ROW][C]221[/C][C]0.883333[/C][C]0.233334[/C][C]0.116667[/C][/ROW]
[ROW][C]222[/C][C]0.905358[/C][C]0.189283[/C][C]0.0946417[/C][/ROW]
[ROW][C]223[/C][C]0.886315[/C][C]0.22737[/C][C]0.113685[/C][/ROW]
[ROW][C]224[/C][C]0.947151[/C][C]0.105699[/C][C]0.0528495[/C][/ROW]
[ROW][C]225[/C][C]0.933882[/C][C]0.132236[/C][C]0.0661178[/C][/ROW]
[ROW][C]226[/C][C]0.954539[/C][C]0.0909228[/C][C]0.0454614[/C][/ROW]
[ROW][C]227[/C][C]0.953883[/C][C]0.0922336[/C][C]0.0461168[/C][/ROW]
[ROW][C]228[/C][C]0.946556[/C][C]0.106889[/C][C]0.0534443[/C][/ROW]
[ROW][C]229[/C][C]0.983027[/C][C]0.0339469[/C][C]0.0169734[/C][/ROW]
[ROW][C]230[/C][C]0.985906[/C][C]0.0281872[/C][C]0.0140936[/C][/ROW]
[ROW][C]231[/C][C]0.984029[/C][C]0.0319427[/C][C]0.0159714[/C][/ROW]
[ROW][C]232[/C][C]0.979117[/C][C]0.0417661[/C][C]0.0208831[/C][/ROW]
[ROW][C]233[/C][C]0.971912[/C][C]0.0561754[/C][C]0.0280877[/C][/ROW]
[ROW][C]234[/C][C]0.96424[/C][C]0.0715207[/C][C]0.0357604[/C][/ROW]
[ROW][C]235[/C][C]0.950224[/C][C]0.0995527[/C][C]0.0497764[/C][/ROW]
[ROW][C]236[/C][C]0.964371[/C][C]0.0712581[/C][C]0.035629[/C][/ROW]
[ROW][C]237[/C][C]0.963074[/C][C]0.073851[/C][C]0.0369255[/C][/ROW]
[ROW][C]238[/C][C]0.947987[/C][C]0.104027[/C][C]0.0520133[/C][/ROW]
[ROW][C]239[/C][C]0.965401[/C][C]0.0691986[/C][C]0.0345993[/C][/ROW]
[ROW][C]240[/C][C]0.95081[/C][C]0.0983804[/C][C]0.0491902[/C][/ROW]
[ROW][C]241[/C][C]0.937171[/C][C]0.125658[/C][C]0.0628289[/C][/ROW]
[ROW][C]242[/C][C]0.91321[/C][C]0.173579[/C][C]0.0867897[/C][/ROW]
[ROW][C]243[/C][C]0.894335[/C][C]0.211331[/C][C]0.105665[/C][/ROW]
[ROW][C]244[/C][C]0.857186[/C][C]0.285628[/C][C]0.142814[/C][/ROW]
[ROW][C]245[/C][C]0.854026[/C][C]0.291949[/C][C]0.145974[/C][/ROW]
[ROW][C]246[/C][C]0.804085[/C][C]0.391829[/C][C]0.195915[/C][/ROW]
[ROW][C]247[/C][C]0.778303[/C][C]0.443394[/C][C]0.221697[/C][/ROW]
[ROW][C]248[/C][C]0.854875[/C][C]0.290251[/C][C]0.145125[/C][/ROW]
[ROW][C]249[/C][C]0.942043[/C][C]0.115914[/C][C]0.0579569[/C][/ROW]
[ROW][C]250[/C][C]0.914393[/C][C]0.171214[/C][C]0.0856072[/C][/ROW]
[ROW][C]251[/C][C]0.897707[/C][C]0.204586[/C][C]0.102293[/C][/ROW]
[ROW][C]252[/C][C]0.849528[/C][C]0.300945[/C][C]0.150472[/C][/ROW]
[ROW][C]253[/C][C]0.83713[/C][C]0.325741[/C][C]0.16287[/C][/ROW]
[ROW][C]254[/C][C]0.74653[/C][C]0.50694[/C][C]0.25347[/C][/ROW]
[ROW][C]255[/C][C]0.627317[/C][C]0.745367[/C][C]0.372683[/C][/ROW]
[ROW][C]256[/C][C]0.482421[/C][C]0.964843[/C][C]0.517579[/C][/ROW]
[ROW][C]257[/C][C]0.34498[/C][C]0.68996[/C][C]0.65502[/C][/ROW]
[ROW][C]258[/C][C]0.66313[/C][C]0.673739[/C][C]0.33687[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269694&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269694&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
210.2543690.5087370.745631
220.1374920.2749850.862508
230.07073640.1414730.929264
240.0313760.0627520.968624
250.01326940.02653880.986731
260.007717910.01543580.992282
270.003167490.006334980.996833
280.001251540.002503080.998748
290.002928830.005857660.997071
300.00169620.00339240.998304
310.003683890.007367770.996316
320.001794580.003589170.998205
330.000908430.001816860.999092
340.001596410.003192820.998404
350.00100830.002016610.998992
360.0005131510.00102630.999487
370.0003627430.0007254860.999637
380.0002543210.0005086420.999746
390.01164290.02328570.988357
400.007757010.0155140.992243
410.01587250.0317450.984127
420.01433310.02866620.985667
430.01544170.03088340.984558
440.01070050.0214010.9893
450.00833960.01667920.99166
460.006594010.0131880.993406
470.01167580.02335150.988324
480.01508550.0301710.984914
490.04083290.08166580.959167
500.0407380.08147610.959262
510.03011150.0602230.969888
520.02678480.05356960.973215
530.02757860.05515730.972421
540.03163350.0632670.968366
550.0726130.1452260.927387
560.0614160.1228320.938584
570.2798560.5597110.720144
580.3065410.6130820.693459
590.2680540.5361080.731946
600.2770720.5541440.722928
610.3000320.6000640.699968
620.2689010.5378030.731099
630.3431930.6863850.656807
640.3687790.7375580.631221
650.3880120.7760240.611988
660.3617360.7234730.638264
670.3565520.7131030.643448
680.3462580.6925160.653742
690.3553560.7107130.644644
700.3178840.6357680.682116
710.2934440.5868870.706556
720.2643970.5287940.735603
730.2517690.5035370.748231
740.2816250.5632510.718375
750.2476840.4953670.752316
760.2191280.4382550.780872
770.190890.3817790.80911
780.1914510.3829020.808549
790.1652670.3305350.834733
800.1629520.3259040.837048
810.1416740.2833480.858326
820.1478430.2956870.852157
830.1285820.2571630.871418
840.2274050.454810.772595
850.2218860.4437720.778114
860.1937370.3874750.806263
870.1692740.3385480.830726
880.1527190.3054380.847281
890.1608560.3217120.839144
900.1652430.3304860.834757
910.1799730.3599460.820027
920.3290710.6581430.670929
930.3058960.6117920.694104
940.3159980.6319960.684002
950.3175220.6350440.682478
960.301860.603720.69814
970.3891260.7782530.610874
980.3713640.7427270.628636
990.3994880.7989750.600512
1000.4700950.940190.529905
1010.4435890.8871770.556411
1020.453930.9078590.54607
1030.4595040.9190070.540496
1040.4625930.9251850.537407
1050.4731770.9463540.526823
1060.5030070.9939850.496993
1070.5745630.8508750.425437
1080.7927820.4144350.207218
1090.8387210.3225590.161279
1100.8381750.3236510.161825
1110.8439520.3120960.156048
1120.8534520.2930950.146548
1130.8967260.2065480.103274
1140.9262520.1474960.0737478
1150.9667720.06645550.0332277
1160.9801180.0397630.0198815
1170.9761070.04778560.0238928
1180.9811650.037670.018835
1190.9811640.03767150.0188357
1200.983440.03311970.0165598
1210.9810580.03788410.018942
1220.9887950.02240910.0112046
1230.9892110.02157730.0107887
1240.9971410.005717710.00285885
1250.9972480.005503360.00275168
1260.9965930.006814710.00340736
1270.9970730.005853380.00292669
1280.9966520.006695080.00334754
1290.99720.005600180.00280009
1300.9971320.005735810.00286791
1310.9970620.005875570.00293779
1320.9964110.007178590.0035893
1330.9961840.00763180.0038159
1340.9958710.008257230.00412861
1350.9946850.01062960.00531478
1360.9931270.01374650.00687323
1370.9949870.01002530.00501264
1380.9943320.01133620.00566808
1390.9933520.01329580.00664789
1400.9916070.01678580.0083929
1410.9893160.02136780.0106839
1420.9947420.01051580.00525789
1430.9946540.01069150.00534574
1440.9951930.009614510.00480726
1450.9940110.01197850.00598924
1460.9939090.0121810.0060905
1470.9928720.01425560.00712781
1480.9910370.01792580.00896292
1490.9902670.01946660.00973328
1500.9888990.02220270.0111013
1510.9959780.008043760.00402188
1520.9955780.008843710.00442186
1530.9962460.007508560.00375428
1540.9952090.009581730.00479086
1550.9949470.01010540.00505271
1560.9934510.01309720.00654862
1570.9923020.01539620.00769808
1580.9905830.01883460.00941732
1590.9909740.01805130.00902567
1600.9918140.01637180.00818591
1610.9941610.0116790.00583948
1620.9923960.01520870.00760437
1630.9920610.01587810.00793903
1640.9996530.0006935130.000346757
1650.9995920.0008152540.000407627
1660.9995230.0009539330.000476966
1670.9994170.001165610.000582805
1680.9993950.0012090.0006045
1690.9993380.001324610.000662304
1700.9994590.001081040.00054052
1710.9992730.001453790.000726895
1720.9994260.001147190.000573595
1730.9992710.001457280.000728638
1740.9991290.001741420.000870712
1750.9989990.002002190.00100109
1760.9993040.001392060.00069603
1770.9990310.001938750.000969375
1780.9992040.001592910.000796453
1790.9989920.002015370.00100769
1800.9988740.002251120.00112556
1810.9987750.002449350.00122467
1820.9985880.002823260.00141163
1830.9982870.00342530.00171265
1840.9977690.004462180.00223109
1850.9979770.00404560.0020228
1860.9974490.005102960.00255148
1870.997980.004039120.00201956
1880.9977450.004509810.0022549
1890.9977520.004495420.00224771
1900.9977370.004525390.00226269
1910.9970470.005905950.00295297
1920.9966790.006642620.00332131
1930.9980050.003989540.00199477
1940.9984920.003015860.00150793
1950.9981990.003602450.00180123
1960.9975470.004906520.00245326
1970.9970420.005916130.00295807
1980.9959420.008115240.00405762
1990.9956960.008608230.00430412
2000.9949240.01015220.00507609
2010.993630.0127390.00636951
2020.9936470.0127070.0063535
2030.9928780.01424350.00712177
2040.9909760.01804820.00902411
2050.9892750.02144940.0107247
2060.9870340.02593190.0129659
2070.9854190.02916190.014581
2080.982080.03583960.0179198
2090.9781590.04368220.0218411
2100.9772950.04540910.0227046
2110.9730230.05395440.0269772
2120.96630.06739960.0336998
2130.9655740.06885180.0344259
2140.9577310.08453790.0422689
2150.9489610.1020780.0510392
2160.937670.124660.0623301
2170.9370840.1258310.0629155
2180.9259710.1480570.0740285
2190.9069180.1861640.0930822
2200.8867370.2265260.113263
2210.8833330.2333340.116667
2220.9053580.1892830.0946417
2230.8863150.227370.113685
2240.9471510.1056990.0528495
2250.9338820.1322360.0661178
2260.9545390.09092280.0454614
2270.9538830.09223360.0461168
2280.9465560.1068890.0534443
2290.9830270.03394690.0169734
2300.9859060.02818720.0140936
2310.9840290.03194270.0159714
2320.9791170.04176610.0208831
2330.9719120.05617540.0280877
2340.964240.07152070.0357604
2350.9502240.09955270.0497764
2360.9643710.07125810.035629
2370.9630740.0738510.0369255
2380.9479870.1040270.0520133
2390.9654010.06919860.0345993
2400.950810.09838040.0491902
2410.9371710.1256580.0628289
2420.913210.1735790.0867897
2430.8943350.2113310.105665
2440.8571860.2856280.142814
2450.8540260.2919490.145974
2460.8040850.3918290.195915
2470.7783030.4433940.221697
2480.8548750.2902510.145125
2490.9420430.1159140.0579569
2500.9143930.1712140.0856072
2510.8977070.2045860.102293
2520.8495280.3009450.150472
2530.837130.3257410.16287
2540.746530.506940.25347
2550.6273170.7453670.372683
2560.4824210.9648430.517579
2570.344980.689960.65502
2580.663130.6737390.33687






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level640.268908NOK
5% type I error level1230.516807NOK
10% type I error level1440.605042NOK

\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 & 64 & 0.268908 & NOK \tabularnewline
5% type I error level & 123 & 0.516807 & NOK \tabularnewline
10% type I error level & 144 & 0.605042 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269694&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]64[/C][C]0.268908[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]123[/C][C]0.516807[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]144[/C][C]0.605042[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269694&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269694&T=6

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level640.268908NOK
5% type I error level1230.516807NOK
10% type I error level1440.605042NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 18 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '18'
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}