Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Sat, 06 Dec 2014 14:27:59 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/06/t14178761019o2n6ey02d2o34z.htm/, Retrieved Thu, 16 May 2024 23:07:19 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263629, Retrieved Thu, 16 May 2024 23:07:19 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

118

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

-       [Multiple Regression] [Multiple regression] [2014-12-06 14:27:59] [0e510e249d31411b3faa1a25774a526d] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

26	50	4	0	13	12	21	149	96	18	68	86	12.9
57	62	4	1	8	8	22	139	70	31	39	70	12.2
37	54	5	0	14	11	22	148	88	39	32	71	12.8
67	71	4	1	16	13	18	158	114	46	62	108	7.4
43	54	4	1	14	11	23	128	69	31	33	64	6.7
52	65	9	1	13	10	12	224	176	67	52	119	12.6
52	73	8	0	15	7	20	159	114	35	62	97	14.8
43	52	11	1	13	10	22	105	121	52	77	129	13.3
84	84	4	1	20	15	21	159	110	77	76	153	11.1
67	42	4	1	17	12	19	167	158	37	41	78	8.2
49	66	6	1	15	12	22	165	116	32	48	80	11.4
70	65	4	1	16	10	15	159	181	36	63	99	6.4
52	78	8	1	12	10	20	119	77	38	30	68	10.6
58	73	4	0	17	14	19	176	141	69	78	147	12
68	75	4	0	11	6	18	54	35	21	19	40	6.3
62	72	11	0	16	12	15	91	80	26	31	57	11.3
43	66	4	1	16	14	20	163	152	54	66	120	11.9
56	70	4	0	15	11	21	124	97	36	35	71	9.3
56	61	6	1	13	8	21	137	99	42	42	84	9.6
74	81	6	0	14	12	15	121	84	23	45	68	10
65	71	4	1	19	15	16	153	68	34	21	55	6.4
63	69	8	1	16	13	23	148	101	112	25	137	13.8
58	71	5	0	17	11	21	221	107	35	44	79	10.8
57	72	4	1	10	12	18	188	88	47	69	116	13.8
63	68	9	1	15	7	25	149	112	47	54	101	11.7
53	70	4	1	14	11	9	244	171	37	74	111	10.9
57	68	7	1	14	7	30	148	137	109	80	189	16.1
51	61	10	0	16	12	20	92	77	24	42	66	13.4
64	67	4	1	15	12	23	150	66	20	61	81	9.9
53	76	4	0	17	13	16	153	93	22	41	63	11.5
29	70	7	0	14	9	16	94	105	23	46	69	8.3
54	60	12	0	16	11	19	156	131	32	39	71	11.7
58	72	7	1	15	12	25	132	102	30	34	64	9
43	69	5	1	16	15	18	161	161	92	51	143	9.7
51	71	8	1	16	12	23	105	120	43	42	85	10.8
53	62	5	1	10	6	21	97	127	55	31	86	10.3
54	70	4	0	8	5	10	151	77	16	39	55	10.4
56	64	9	1	17	13	14	131	108	49	20	69	12.7
61	58	7	1	14	11	22	166	85	71	49	120	9.3
47	76	4	0	10	6	26	157	168	43	53	96	11.8
39	52	4	1	14	12	23	111	48	29	31	60	5.9
48	59	4	1	12	10	23	145	152	56	39	95	11.4
50	68	4	1	16	6	24	162	75	46	54	100	13
35	76	4	1	16	12	24	163	107	19	49	68	10.8
30	65	7	1	16	11	18	59	62	23	34	57	12.3
68	67	4	0	8	6	23	187	121	59	46	105	11.3
49	59	7	1	16	12	15	109	124	30	55	85	11.8
61	69	4	1	15	12	19	90	72	61	42	103	7.9
67	76	4	0	8	8	16	105	40	7	50	57	12.7
47	63	4	1	13	10	25	83	58	38	13	51	12.3
56	75	4	1	14	11	23	116	97	32	37	69	11.6
50	63	8	1	13	7	17	42	88	16	25	41	6.7
43	60	4	1	16	12	19	148	126	19	30	49	10.9
67	73	4	1	19	13	21	155	104	22	28	50	12.1
62	63	4	1	19	14	18	125	148	48	45	93	13.3
57	70	4	1	14	12	27	116	146	23	35	58	10.1
41	75	7	0	15	6	21	128	80	26	28	54	5.7
54	66	12	1	13	14	13	138	97	33	41	74	14.3
45	63	4	0	10	10	8	49	25	9	6	15	8
48	63	4	1	16	12	29	96	99	24	45	69	13.3
61	64	4	1	15	11	28	164	118	34	73	107	9.3
56	70	5	0	11	10	23	162	58	48	17	65	12.5
41	75	15	0	9	7	21	99	63	18	40	58	7.6
43	61	5	1	16	12	19	202	139	43	64	107	15.9
53	60	10	0	12	7	19	186	50	33	37	70	9.2
44	62	9	1	12	12	20	66	60	28	25	53	9.1
66	73	8	0	14	12	18	183	152	71	65	136	11.1
58	61	4	1	14	10	19	214	142	26	100	126	13
46	66	5	1	13	10	17	188	94	67	28	95	14.5
37	64	4	0	15	12	19	104	66	34	35	69	12.2
51	59	9	0	17	12	25	177	127	80	56	136	12.3
51	64	4	0	14	12	19	126	67	29	29	58	11.4
56	60	10	0	11	8	22	76	90	16	43	59	8.8
66	56	4	1	9	10	23	99	75	59	59	118	14.6
37	78	4	0	7	5	14	139	128	32	50	82	12.6
42	67	7	0	15	10	16	162	146	43	59	102	13
38	59	5	1	12	12	24	108	69	38	27	65	12.6
66	66	4	0	15	11	20	159	186	29	61	90	13.2
34	68	4	0	14	9	12	74	81	36	28	64	9.9
53	71	4	1	16	12	24	110	85	32	51	83	7.7
49	66	4	0	14	11	22	96	54	35	35	70	10.5
55	73	4	0	13	10	12	116	46	21	29	50	13.4
49	72	4	0	16	12	22	87	106	29	48	77	10.9
59	71	6	1	13	10	20	97	34	12	25	37	4.3
40	59	10	0	16	9	10	127	60	37	44	81	10.3
58	64	7	1	16	11	23	106	95	37	64	101	11.8
60	66	4	1	16	12	17	80	57	47	32	79	11.2
63	78	4	0	10	7	22	74	62	51	20	71	11.4
56	68	7	0	12	11	24	91	36	32	28	60	8.6
54	73	4	0	12	12	18	133	56	21	34	55	13.2
52	62	8	1	12	6	21	74	54	13	31	44	12.6
34	65	11	1	12	9	20	114	64	14	26	40	5.6
69	68	6	1	19	15	20	140	76	-2	58	56	9.9
32	65	14	0	14	10	22	95	98	20	23	43	8.8
48	60	5	1	13	11	19	98	88	24	21	45	7.7
67	71	4	0	16	12	20	121	35	11	21	32	9
58	65	8	1	15	12	26	126	102	23	33	56	7.3
57	68	9	1	12	12	23	98	61	24	16	40	11.4
42	64	4	1	8	11	24	95	80	14	20	34	13.6
64	74	4	1	10	9	21	110	49	52	37	89	7.9
58	69	5	1	16	11	21	70	78	15	35	50	10.7
66	76	4	0	16	12	19	102	90	23	33	56	10.3
26	68	5	1	10	12	8	86	45	19	27	46	8.3
61	72	4	1	18	14	17	130	55	35	41	76	9.6
52	67	4	1	12	8	20	96	96	24	40	64	14.2
51	63	7	0	16	10	11	102	43	39	35	74	8.5
55	59	10	0	10	9	8	100	52	29	28	57	13.5
50	73	4	0	14	10	15	94	60	13	32	45	4.9
60	66	5	0	12	9	18	52	54	8	22	30	6.4
56	62	4	0	11	10	18	98	51	18	44	62	9.6
63	69	4	0	15	12	19	118	51	24	27	51	11.6
61	66	4	1	7	11	19	99	38	19	17	36	11.1
52	51	6	1	16	9	23	48	41	23	12	34	4.35
16	56	4	1	16	11	22	50	146	16	45	61	12.7
46	67	8	1	16	12	21	150	182	33	37	70	18.1
56	69	5	1	16	12	25	154	192	32	37	69	17.85
52	57	4	0	12	7	30	109	263	37	108	145	16.6
55	56	17	1	15	12	17	68	35	14	10	23	12.6
50	55	4	1	14	12	27	194	439	52	68	120	17.1
59	63	4	0	15	12	23	158	214	75	72	147	19.1
60	67	8	1	16	10	23	159	341	72	143	215	16.1
52	65	4	0	13	15	18	67	58	15	9	24	13.35
44	47	7	0	10	10	18	147	292	29	55	84	18.4
67	76	4	1	17	15	23	39	85	13	17	30	14.7
52	64	4	1	15	10	19	100	200	40	37	77	10.6
55	68	5	1	18	15	15	111	158	19	27	46	12.6
37	64	7	1	16	9	20	138	199	24	37	61	16.2
54	65	4	1	20	15	16	101	297	121	58	178	13.6
72	71	4	1	16	12	24	131	227	93	66	160	18.9
51	63	7	1	17	13	25	101	108	36	21	57	14.1
48	60	11	1	16	12	25	114	86	23	19	42	14.5
60	68	7	0	15	12	19	165	302	85	78	163	16.15
50	72	4	1	13	8	19	114	148	41	35	75	14.75
63	70	4	1	16	9	16	111	178	46	48	94	14.8
33	61	4	1	16	15	19	75	120	18	27	45	12.45
67	61	4	1	16	12	19	82	207	35	43	78	12.65
46	62	4	1	17	12	23	121	157	17	30	47	17.35
54	71	4	1	20	15	21	32	128	4	25	29	8.6
59	71	6	0	14	11	22	150	296	28	69	97	18.4
61	51	8	1	17	12	19	117	323	44	72	116	16.1
33	56	23	1	6	6	20	71	79	10	23	32	11.6
47	70	4	1	16	14	20	165	70	38	13	50	17.75
69	73	8	1	15	12	3	154	146	57	61	118	15.25
52	76	6	1	16	12	23	126	246	23	43	66	17.65
55	68	4	0	16	12	23	149	196	36	51	86	16.35
41	48	7	0	14	11	20	145	199	22	67	89	17.65
73	52	4	1	16	12	15	120	127	40	36	76	13.6
52	60	4	0	16	12	16	109	153	31	44	75	14.35
50	59	4	0	16	12	7	132	299	11	45	57	14.75
51	57	10	1	14	12	24	172	228	38	34	72	18.25
60	79	6	0	14	8	17	169	190	24	36	60	9.9
56	60	5	1	16	8	24	114	180	37	72	109	16
56	60	5	1	16	12	24	156	212	37	39	76	18.25
29	59	4	0	15	12	19	172	269	22	43	65	16.85
66	62	4	1	16	11	25	68	130	15	25	40	14.6
66	59	5	1	16	10	20	89	179	2	56	58	13.85
73	61	5	1	18	11	28	167	243	43	80	123	18.95
55	71	5	0	15	12	23	113	190	31	40	71	15.6
64	57	5	0	16	13	27	115	299	29	73	102	14.85
40	66	4	0	16	12	18	78	121	45	34	80	11.75
46	63	6	0	16	12	28	118	137	25	72	97	18.45
58	69	4	1	17	10	21	87	305	4	42	46	15.9
43	58	4	0	14	10	19	173	157	31	61	93	17.1
61	59	4	1	18	11	23	2	96	-4	23	19	16.1
51	48	9	0	9	8	27	162	183	66	74	140	19.9
50	66	18	1	15	12	22	49	52	61	16	78	10.95
52	73	6	0	14	9	28	122	238	32	66	98	18.45
54	67	5	1	15	12	25	96	40	31	9	40	15.1
66	61	4	0	13	9	21	100	226	39	41	80	15
61	68	11	0	16	11	22	82	190	19	57	76	11.35
80	75	4	1	20	15	28	100	214	31	48	79	15.95
51	62	10	0	14	8	20	115	145	36	51	87	18.1
56	69	6	1	12	8	29	141	119	42	53	95	14.6
56	58	8	1	15	11	25	165	222	21	29	49	15.4
56	60	8	1	15	11	25	165	222	21	29	49	15.4
53	74	6	1	15	11	20	110	159	25	55	80	17.6
47	55	8	1	16	13	20	118	165	32	54	86	13.35
25	62	4	0	11	7	16	158	249	26	43	69	19.1
47	63	4	1	16	12	20	146	125	28	51	79	15.35
46	69	9	0	7	8	20	49	122	32	20	52	7.6
50	58	9	0	11	8	23	90	186	41	79	120	13.4
39	58	5	0	9	4	18	121	148	29	39	69	13.9
51	68	4	1	15	11	25	155	274	33	61	94	19.1
58	72	4	0	16	10	18	104	172	17	55	72	15.25
35	62	15	1	14	7	19	147	84	13	30	43	12.9
58	62	10	0	15	12	25	110	168	32	55	87	16.1
60	65	9	0	13	11	25	108	102	30	22	52	17.35
62	69	7	0	13	9	25	113	106	34	37	71	13.15
63	66	9	0	12	10	24	115	2	59	2	61	12.15
53	72	6	1	16	8	19	61	139	13	38	51	12.6
46	62	4	1	14	8	26	60	95	23	27	50	10.35
67	75	7	1	16	11	10	109	130	10	56	67	15.4
59	58	4	1	14	12	17	68	72	5	25	30	9.6
64	66	7	0	15	10	13	111	141	31	39	70	18.2
38	55	4	0	10	10	17	77	113	19	33	52	13.6
50	47	15	1	16	12	30	73	206	32	43	75	14.85
48	72	4	0	14	8	25	151	268	30	57	87	14.75
48	62	9	0	16	11	4	89	175	25	43	69	14.1
47	64	4	0	12	8	16	78	77	48	23	72	14.9
66	64	4	0	16	10	21	110	125	35	44	79	16.25
47	19	28	1	16	14	23	220	255	67	54	121	19.25
63	50	4	1	15	9	22	65	111	15	28	43	13.6
58	68	4	0	14	9	17	141	132	22	36	58	13.6
44	70	4	0	16	10	20	117	211	18	39	57	15.65
51	79	5	1	11	13	20	122	92	33	16	50	12.75
43	69	4	0	15	12	22	63	76	46	23	69	14.6
55	71	4	1	18	13	16	44	171	24	40	64	9.85
38	48	12	1	13	8	23	52	83	14	24	38	12.65
45	73	4	0	7	3	0	131	266	12	78	90	19.2
50	74	6	1	7	8	18	101	186	38	57	96	16.6
54	66	6	1	17	12	25	42	50	12	37	49	11.2
57	71	5	1	18	11	23	152	117	28	27	56	15.25
60	74	4	0	15	9	12	107	219	41	61	102	11.9
55	78	4	0	8	12	18	77	246	12	27	40	13.2
56	75	4	0	13	12	24	154	279	31	69	100	16.35
49	53	10	1	13	12	11	103	148	33	34	67	12.4
37	60	7	1	15	10	18	96	137	34	44	78	15.85
59	70	4	1	18	13	23	175	181	21	34	55	18.15
46	69	7	1	16	9	24	57	98	20	39	59	11.15
51	65	4	0	14	12	29	112	226	44	51	96	15.65
58	78	4	0	15	11	18	143	234	52	34	86	17.75
64	78	12	0	19	14	15	49	138	7	31	38	7.65
53	59	5	1	16	11	29	110	85	29	13	43	12.35
48	72	8	1	12	9	16	131	66	11	12	23	15.6
51	70	6	0	16	12	19	167	236	26	51	77	19.3
47	63	17	0	11	8	22	56	106	24	24	48	15.2
59	63	4	0	16	15	16	137	135	7	19	26	17.1
62	71	5	1	15	12	23	86	122	60	30	91	15.6
62	74	4	1	19	14	23	121	218	13	81	94	18.4
51	67	5	0	15	12	19	149	199	20	42	62	19.05
64	66	5	0	14	9	4	168	112	52	22	74	18.55
52	62	6	0	14	9	20	140	278	28	85	114	19.1
67	80	4	1	17	13	24	88	94	25	27	52	13.1
50	73	4	1	16	13	20	168	113	39	25	64	12.85
54	67	4	1	20	15	4	94	84	9	22	31	9.5
58	61	6	1	16	11	24	51	86	19	19	38	4.5
56	73	8	0	9	7	22	48	62	13	14	27	11.85
63	74	10	1	13	10	16	145	222	60	45	105	13.6
31	32	4	1	15	11	3	66	167	19	45	64	11.7
65	69	5	1	19	14	15	85	82	34	28	62	12.4
71	69	4	0	16	14	24	109	207	14	51	65	13.35
50	84	4	0	17	13	17	63	184	17	41	58	11.4
57	64	4	1	16	12	20	102	83	45	31	76	14.9
47	58	16	0	9	8	27	162	183	66	74	140	19.9
47	59	7	1	11	13	26	86	89	48	19	68	11.2
57	78	4	1	14	9	23	114	225	29	51	80	14.6
43	57	4	0	19	12	17	164	237	-2	73	71	17.6
41	60	14	1	13	13	20	119	102	51	24	76	14.05
63	68	5	0	14	11	22	126	221	2	61	63	16.1
63	68	5	1	15	11	19	132	128	24	23	46	13.35
56	73	5	1	15	13	24	142	91	40	14	53	11.85
51	69	5	0	14	12	19	83	198	20	54	74	11.95
50	67	7	1	16	12	23	94	204	19	51	70	14.75
22	60	19	0	17	10	15	81	158	16	62	78	15.15
41	65	16	1	12	9	27	166	138	20	36	56	13.2
59	66	4	0	15	10	26	110	226	40	59	100	16.85
56	74	4	1	17	13	22	64	44	27	24	51	7.85
66	81	7	0	15	13	22	93	196	25	26	52	7.7
53	72	9	0	10	9	18	104	83	49	54	102	12.6
42	55	5	1	16	11	15	105	79	39	39	78	7.85
52	49	14	1	15	12	22	49	52	61	16	78	10.95
54	74	4	0	11	8	27	88	105	19	36	55	12.35
44	53	16	1	16	12	10	95	116	67	31	98	9.95
62	64	10	1	16	12	20	102	83	45	31	76	14.9
53	65	5	0	16	12	17	99	196	30	42	73	16.65
50	57	6	1	14	9	23	63	153	8	39	47	13.4
36	51	4	0	14	12	19	76	157	19	25	45	13.95
76	80	4	0	16	12	13	109	75	52	31	83	15.7
66	67	4	1	16	11	27	117	106	22	38	60	16.85
62	70	5	1	18	12	23	57	58	17	31	48	10.95
59	74	4	0	14	6	16	120	75	33	17	50	15.35
47	75	4	1	20	7	25	73	74	34	22	56	12.2
55	70	5	0	15	10	2	91	185	22	55	77	15.1
58	69	4	0	16	12	26	108	265	30	62	91	17.75
60	65	4	1	16	10	20	105	131	25	51	76	15.2
44	55	5	0	16	12	23	117	139	38	30	68	14.6
57	71	8	0	12	9	22	119	196	26	49	74	16.65
45	65	15	1	8	3	24	31	78	13	16	29	8.1

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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 11 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263629&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263629&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263629&T=0

As an alternative you can also use a QR Code:

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

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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.96418 + 0.00604243AMSi[t] -0.0271607AMSE[t] + 0.0263081AMSA[t] -0.605303Gender[t] -0.0065626CONFSTAT[t] -0.00392901CONFSOFT[t] + 0.0583365NUMERACY[t] + 0.0118009LFM[t] + 0.0268136B[t] -0.364791PRH[t] -0.376729CH[t] + 0.366881H[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.96418 +  0.00604243AMSi[t] -0.0271607AMSE[t] +  0.0263081AMSA[t] -0.605303Gender[t] -0.0065626CONFSTAT[t] -0.00392901CONFSOFT[t] +  0.0583365NUMERACY[t] +  0.0118009LFM[t] +  0.0268136B[t] -0.364791PRH[t] -0.376729CH[t] +  0.366881H[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263629&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.96418 +  0.00604243AMSi[t] -0.0271607AMSE[t] +  0.0263081AMSA[t] -0.605303Gender[t] -0.0065626CONFSTAT[t] -0.00392901CONFSOFT[t] +  0.0583365NUMERACY[t] +  0.0118009LFM[t] +  0.0268136B[t] -0.364791PRH[t] -0.376729CH[t] +  0.366881H[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263629&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263629&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.96418 + 0.00604243AMSi[t] -0.0271607AMSE[t] + 0.0263081AMSA[t] -0.605303Gender[t] -0.0065626CONFSTAT[t] -0.00392901CONFSOFT[t] + 0.0583365NUMERACY[t] + 0.0118009LFM[t] + 0.0268136B[t] -0.364791PRH[t] -0.376729CH[t] + 0.366881H[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	8.96418	2.04691	4.379	1.71522e-05	8.57609e-06
AMSi	0.00604243	0.0179442	0.3367	0.736583	0.368292
AMSE	-0.0271607	0.0229565	-1.183	0.237814	0.118907
AMSA	0.0263081	0.0515283	0.5106	0.610086	0.305043
Gender	-0.605303	0.360434	-1.679	0.0942578	0.0471289
CONFSTAT	-0.0065626	0.0804246	-0.0816	0.935027	0.467513
CONFSOFT	-0.00392901	0.0948187	-0.04144	0.966979	0.483489
NUMERACY	0.0583365	0.0328902	1.774	0.0772651	0.0386325
LFM	0.0118009	0.00490071	2.408	0.0167239	0.00836196
B	0.0268136	0.00299826	8.943	6.67904e-17	3.33952e-17
PRH	-0.364791	0.453421	-0.8045	0.421812	0.210906
CH	-0.376729	0.452648	-0.8323	0.406002	0.203001
H	0.366881	0.452382	0.811	0.418094	0.209047

\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) & 8.96418 & 2.04691 & 4.379 & 1.71522e-05 & 8.57609e-06 \tabularnewline
AMSi & 0.00604243 & 0.0179442 & 0.3367 & 0.736583 & 0.368292 \tabularnewline
AMSE & -0.0271607 & 0.0229565 & -1.183 & 0.237814 & 0.118907 \tabularnewline
AMSA & 0.0263081 & 0.0515283 & 0.5106 & 0.610086 & 0.305043 \tabularnewline
Gender & -0.605303 & 0.360434 & -1.679 & 0.0942578 & 0.0471289 \tabularnewline
CONFSTAT & -0.0065626 & 0.0804246 & -0.0816 & 0.935027 & 0.467513 \tabularnewline
CONFSOFT & -0.00392901 & 0.0948187 & -0.04144 & 0.966979 & 0.483489 \tabularnewline
NUMERACY & 0.0583365 & 0.0328902 & 1.774 & 0.0772651 & 0.0386325 \tabularnewline
LFM & 0.0118009 & 0.00490071 & 2.408 & 0.0167239 & 0.00836196 \tabularnewline
B & 0.0268136 & 0.00299826 & 8.943 & 6.67904e-17 & 3.33952e-17 \tabularnewline
PRH & -0.364791 & 0.453421 & -0.8045 & 0.421812 & 0.210906 \tabularnewline
CH & -0.376729 & 0.452648 & -0.8323 & 0.406002 & 0.203001 \tabularnewline
H & 0.366881 & 0.452382 & 0.811 & 0.418094 & 0.209047 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263629&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]8.96418[/C][C]2.04691[/C][C]4.379[/C][C]1.71522e-05[/C][C]8.57609e-06[/C][/ROW]
[ROW][C]AMSi[/C][C]0.00604243[/C][C]0.0179442[/C][C]0.3367[/C][C]0.736583[/C][C]0.368292[/C][/ROW]
[ROW][C]AMSE[/C][C]-0.0271607[/C][C]0.0229565[/C][C]-1.183[/C][C]0.237814[/C][C]0.118907[/C][/ROW]
[ROW][C]AMSA[/C][C]0.0263081[/C][C]0.0515283[/C][C]0.5106[/C][C]0.610086[/C][C]0.305043[/C][/ROW]
[ROW][C]Gender[/C][C]-0.605303[/C][C]0.360434[/C][C]-1.679[/C][C]0.0942578[/C][C]0.0471289[/C][/ROW]
[ROW][C]CONFSTAT[/C][C]-0.0065626[/C][C]0.0804246[/C][C]-0.0816[/C][C]0.935027[/C][C]0.467513[/C][/ROW]
[ROW][C]CONFSOFT[/C][C]-0.00392901[/C][C]0.0948187[/C][C]-0.04144[/C][C]0.966979[/C][C]0.483489[/C][/ROW]
[ROW][C]NUMERACY[/C][C]0.0583365[/C][C]0.0328902[/C][C]1.774[/C][C]0.0772651[/C][C]0.0386325[/C][/ROW]
[ROW][C]LFM[/C][C]0.0118009[/C][C]0.00490071[/C][C]2.408[/C][C]0.0167239[/C][C]0.00836196[/C][/ROW]
[ROW][C]B[/C][C]0.0268136[/C][C]0.00299826[/C][C]8.943[/C][C]6.67904e-17[/C][C]3.33952e-17[/C][/ROW]
[ROW][C]PRH[/C][C]-0.364791[/C][C]0.453421[/C][C]-0.8045[/C][C]0.421812[/C][C]0.210906[/C][/ROW]
[ROW][C]CH[/C][C]-0.376729[/C][C]0.452648[/C][C]-0.8323[/C][C]0.406002[/C][C]0.203001[/C][/ROW]
[ROW][C]H[/C][C]0.366881[/C][C]0.452382[/C][C]0.811[/C][C]0.418094[/C][C]0.209047[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263629&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263629&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	8.96418	2.04691	4.379	1.71522e-05	8.57609e-06
AMSi	0.00604243	0.0179442	0.3367	0.736583	0.368292
AMSE	-0.0271607	0.0229565	-1.183	0.237814	0.118907
AMSA	0.0263081	0.0515283	0.5106	0.610086	0.305043
Gender	-0.605303	0.360434	-1.679	0.0942578	0.0471289
CONFSTAT	-0.0065626	0.0804246	-0.0816	0.935027	0.467513
CONFSOFT	-0.00392901	0.0948187	-0.04144	0.966979	0.483489
NUMERACY	0.0583365	0.0328902	1.774	0.0772651	0.0386325
LFM	0.0118009	0.00490071	2.408	0.0167239	0.00836196
B	0.0268136	0.00299826	8.943	6.67904e-17	3.33952e-17
PRH	-0.364791	0.453421	-0.8045	0.421812	0.210906
CH	-0.376729	0.452648	-0.8323	0.406002	0.203001
H	0.366881	0.452382	0.811	0.418094	0.209047

Multiple Linear Regression - Regression Statistics
Multiple R	0.622315
R-squared	0.387276
Adjusted R-squared	0.35953
F-TEST (value)	13.9579
F-TEST (DF numerator)	12
F-TEST (DF denominator)	265
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.71648
Sum Squared Residuals	1955.51

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.622315 \tabularnewline
R-squared & 0.387276 \tabularnewline
Adjusted R-squared & 0.35953 \tabularnewline
F-TEST (value) & 13.9579 \tabularnewline
F-TEST (DF numerator) & 12 \tabularnewline
F-TEST (DF denominator) & 265 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.71648 \tabularnewline
Sum Squared Residuals & 1955.51 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263629&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.622315[/C][/ROW]
[ROW][C]R-squared[/C][C]0.387276[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.35953[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]13.9579[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]12[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]265[/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]2.71648[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1955.51[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263629&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263629&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.622315
R-squared	0.387276
Adjusted R-squared	0.35953
F-TEST (value)	13.9579
F-TEST (DF numerator)	12
F-TEST (DF denominator)	265
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.71648
Sum Squared Residuals	1955.51

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	12.6615	0.238497
2	12.2	11.5221	0.677948
3	12.8	12.8735	-0.0734505
4	7.4	12.2414	-4.84141
5	6.7	11.5644	-4.86438
6	12.6	14.7104	-2.11042
7	14.8	12.9426	1.85739
8	13.3	12.4885	0.811498
9	11.1	11.9634	-0.863432
10	8.2	14.5588	-6.35877
11	11.4	12.8097	-1.40974
12	6.4	14.0368	-7.63684
13	10.6	11.0667	-0.466661
14	12	13.6128	-1.61276
15	6.3	9.83005	-3.53005
16	11.3	11.3636	-0.0635677
17	11.9	13.4002	-1.5002
18	9.3	12.3848	-3.08476
19	9.6	12.2521	-2.65208
20	10	11.3904	-1.39036
21	6.4	11.1714	-4.77135
22	13.8	12.7042	1.09576
23	10.8	13.705	-2.90497
24	13.8	11.7872	2.01284
25	11.7	12.7898	-1.0898
26	10.9	14.0862	-3.1862
27	16.1	13.5313	2.56872
28	13.4	11.6801	1.7199
29	9.9	11.2081	-1.30814
30	11.5	12.0376	-0.537623
31	8.3	11.7483	-3.44826
32	11.7	13.9731	-2.27305
33	9	12.2713	-3.27134
34	9.7	13.6693	-3.9693
35	10.8	12.2717	-1.4717
36	10.3	12.6223	-2.32228
37	10.4	11.5016	-1.10164
38	12.7	12.1971	0.502923
39	9.3	12.3886	-3.0886
40	11.8	14.6421	-2.84213
41	5.9	10.8424	-4.94242
42	11.4	13.8952	-2.49517
43	13	11.678	1.32205
44	10.8	12.2091	-1.40908
45	12.3	9.93265	2.36735
46	11.3	14.0478	-2.74775
47	11.8	12.0918	-0.291801
48	7.9	10.628	-2.72799
49	12.7	10.0934	2.60663
50	12.3	10.8569	1.44313
51	11.6	11.6444	-0.0444277
52	6.7	10.6817	-3.98173
53	10.9	12.9199	-2.01987
54	12.1	12.3235	-0.223526
55	13.3	13.0987	0.201302
56	10.1	13.3304	-3.23044
57	5.7	11.8963	-6.19629
58	14.3	11.721	2.57902
59	8	9.20028	-1.20028
60	13.3	11.9771	1.32292
61	9.3	13.0377	-3.73772
62	12.5	12.163	0.337026
63	7.6	11.2092	-3.60925
64	15.9	13.6202	2.27981
65	9.2	12.1603	-2.96027
66	9.1	10.4184	-1.3184
67	11.1	14.2453	-3.1453
68	13	13.5375	-0.537491
69	14.5	12.4463	2.05375
70	12.2	11.2409	0.959101
71	12.3	14.3162	-2.01619
72	11.4	11.6671	-0.267122
73	8.8	12.0359	-3.23586
74	14.6	11.3069	3.29307
75	12.6	12.5725	0.0274524
76	13	13.7134	-0.713411
77	12.6	11.3299	1.27009
78	13.2	15.0243	-1.82426
79	9.9	10.8454	-0.945416
80	7.7	11.2458	-3.54579
81	10.5	11.0305	-0.530508
82	13.4	10.3551	3.04491
83	10.9	11.998	-1.09802
84	4.3	9.82218	-5.52218
85	10.3	11.0611	-0.761055
86	11.8	11.594	0.205994
87	11.2	10.1292	1.07081
88	11.4	10.9672	0.432805
89	8.6	10.7482	-2.14822
90	13.2	11.1173	2.08272
91	12.6	10.3654	2.23458
92	5.6	10.9755	-5.37548
93	9.9	11.1844	-1.28443
94	8.8	12.4768	-3.67677
95	7.7	11.4901	-3.79013
96	9	10.743	-1.743
97	7.3	12.4705	-5.17052
98	11.4	10.9937	0.406295
99	13.6	11.3824	2.21755
100	7.9	10.3213	-2.42132
101	10.7	10.6478	0.052157
102	10.3	11.7003	-1.40026
103	8.3	9.14983	-0.849827
104	9.6	10.374	-0.773986
105	14.2	11.3783	2.82165
106	8.5	10.3363	-1.83632
107	13.5	10.6821	2.8179
108	4.9	10.5628	-5.66283
109	6.4	10.4633	-4.06326
110	9.6	10.7907	-1.19071
111	11.6	11.0831	0.516917
112	11.1	10.1188	0.981162
113	4.35	9.87594	-5.52594
114	12.7	12.2701	0.4299
115	18.1	14.4553	3.64473
116	17.85	14.929	2.92095
117	16.6	16.8314	-0.231366
118	12.6	9.76843	2.83157
119	17.1	22.2081	-5.10806
120	19.1	15.9613	3.13865
121	16.1	18.0716	-1.97164
122	13.35	10.8126	2.53744
123	18.4	18.1661	0.233905
124	14.7	10.5751	4.12487
125	10.6	14.2728	-3.67276
126	12.6	12.9941	-0.394087
127	16.2	14.7049	1.49508
128	13.6	16.2386	-2.63859
129	18.9	15.7626	3.13736
130	14.1	12.3921	1.70794
131	14.5	12.1272	2.37283
132	16.15	18.0812	-1.93119
133	14.75	12.4902	2.25982
134	14.8	13.4427	1.35725
135	12.45	11.8256	0.624398
136	12.65	14.3362	-1.6862
137	17.35	13.6189	3.73113
138	8.6	11.4688	-2.86881
139	18.4	17.7844	0.61557
140	16.1	17.9269	-1.82686
141	11.6	11.1298	0.470194
142	17.75	11.2622	6.48779
143	15.25	12.2835	2.96647
144	17.65	15.664	1.986
145	16.35	14.9643	1.38565
146	17.65	15.5572	2.09278
147	13.6	12.7663	0.833716
148	14.35	13.5555	0.794506
149	14.75	17.547	-2.79697
150	18.25	16.5309	1.71911
151	9.9	14.9919	-5.09188
152	16	14.0029	1.99715
153	18.25	15.6658	2.58421
154	16.85	17.4701	-0.620119
155	14.6	12.5625	2.03747
156	13.85	13.6118	0.238206
157	18.95	16.5353	2.41468
158	15.6	14.7948	0.805222
159	14.85	18.0694	-3.21939
160	11.75	12.7075	-0.957458
161	18.45	13.5793	4.87068
162	15.9	16.8143	-0.914278
163	17.1	14.8134	2.28659
164	16.1	10.7735	5.32655
165	19.9	15.9179	3.98213
166	10.95	10.7891	0.160855
167	18.45	16.198	2.25202
168	15.1	10.4914	4.60863
169	15	15.8335	-0.833539
170	11.35	14.4511	-3.10107
171	15.95	14.864	1.086
172	18.1	13.713	4.38702
173	14.6	12.9832	1.6168
174	15.4	15.9404	-0.540354
175	15.4	15.886	-0.486032
176	17.6	12.9243	4.67575
177	13.35	13.722	-0.372016
178	19.1	16.5422	2.55777
179	15.35	12.6825	2.66751
180	7.6	12.4136	-4.81362
181	13.4	14.523	-1.12302
182	13.9	14.1711	-0.271097
183	19.1	16.8864	2.21356
184	15.25	13.7032	1.54679
185	12.9	11.9888	0.911151
186	16.1	14.5346	1.56536
187	17.35	12.9835	4.36652
188	13.15	12.8691	0.280931
189	12.15	10.5854	1.56457
190	12.6	11.9533	0.646731
191	10.35	11.4891	-1.13908
192	15.4	11.9543	3.44566
193	9.6	10.5953	-0.995284
194	18.2	13.1345	5.06555
195	13.6	12.3453	1.25466
196	14.85	15.4055	-0.555524
197	14.75	17.2084	-2.45836
198	14.1	13.6305	0.469498
199	14.9	11.6642	3.23583
200	16.25	13.1004	3.14963
201	19.25	19.0871	0.162868
202	13.6	12.1353	1.46466
203	13.6	13.3322	0.267779
204	15.65	15.1484	0.50159
205	12.75	11.8812	0.868786
206	14.6	11.2439	3.35608
207	9.85	12.3928	-2.54284
208	12.65	11.4576	1.19244
209	19.2	15.2362	3.96384
210	16.6	13.8459	2.75414
211	11.2	9.84714	1.35286
212	15.25	13.1773	2.07273
213	11.9	14.6082	-2.70818
214	13.2	15.8645	-2.66451
215	16.35	17.322	-0.971994
216	12.4	12.9058	-0.505828
217	15.85	12.4934	3.35659
218	18.15	14.7194	3.43061
219	11.15	11.1647	-0.0147404
220	15.65	16.5031	-0.853069
221	17.75	15.9455	1.80447
222	7.65	12.2313	-4.58128
223	12.35	12.6285	-0.278462
224	15.6	10.9435	4.65649
225	19.3	16.3361	2.96394
226	15.2	12.481	2.71901
227	17.1	13.5483	3.55168
228	15.6	12.6158	2.98419
229	18.4	14.4937	3.90633
230	19.05	15.2694	3.78063
231	18.55	12.6737	5.87633
232	19.1	17.4864	1.61357
233	13.1	11.2789	1.82114
234	12.85	12.642	0.208027
235	9.5	10.1776	-0.67758
236	4.5	11.2227	-6.72267
237	11.85	10.8453	1.00468
238	13.6	15.1476	-1.54755
239	11.7	12.6689	-0.968935
240	12.4	10.7016	1.69843
241	13.35	15.2281	-1.87815
242	11.4	13.2281	-1.82805
243	14.9	11.3028	3.59716
244	19.9	15.8062	4.09375
245	11.2	12.2994	-1.09944
246	14.6	14.8412	-0.241247
247	17.6	16.1681	1.43194
248	14.05	12.7521	1.29793
249	16.1	15.594	0.506042
250	13.35	12.4375	0.912451
251	11.85	11.7913	0.058743
252	11.95	14.2978	-2.34776
253	14.75	14.3317	0.418279
254	15.15	13.3068	1.84317
255	13.2	14.0696	-0.869589
256	16.85	16.2398	0.610213
257	7.85	9.66851	-1.81851
258	7.7	14.9971	-7.29706
259	12.6	11.1713	1.4287
260	7.85	11.032	-3.18202
261	10.95	11.1577	-0.20773
262	12.35	12.3964	-0.046382
263	9.95	12.1036	-2.15362
264	14.9	11.4909	3.4091
265	16.65	14.9298	1.72016
266	13.4	12.9638	0.436213
267	13.95	14.1381	-0.188124
268	15.7	11.0627	4.63725
269	16.85	12.3647	4.48527
270	10.95	10.0984	0.851641
271	15.35	11.5627	3.78734
272	12.2	10.7108	1.48919
273	15.1	13.0445	2.05549
274	17.75	16.3758	1.37424
275	15.2	12.3853	2.81465
276	14.6	13.9491	0.650859
277	16.65	14.6246	2.02535
278	8.1	10.9227	-2.82265

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.6615 & 0.238497 \tabularnewline
2 & 12.2 & 11.5221 & 0.677948 \tabularnewline
3 & 12.8 & 12.8735 & -0.0734505 \tabularnewline
4 & 7.4 & 12.2414 & -4.84141 \tabularnewline
5 & 6.7 & 11.5644 & -4.86438 \tabularnewline
6 & 12.6 & 14.7104 & -2.11042 \tabularnewline
7 & 14.8 & 12.9426 & 1.85739 \tabularnewline
8 & 13.3 & 12.4885 & 0.811498 \tabularnewline
9 & 11.1 & 11.9634 & -0.863432 \tabularnewline
10 & 8.2 & 14.5588 & -6.35877 \tabularnewline
11 & 11.4 & 12.8097 & -1.40974 \tabularnewline
12 & 6.4 & 14.0368 & -7.63684 \tabularnewline
13 & 10.6 & 11.0667 & -0.466661 \tabularnewline
14 & 12 & 13.6128 & -1.61276 \tabularnewline
15 & 6.3 & 9.83005 & -3.53005 \tabularnewline
16 & 11.3 & 11.3636 & -0.0635677 \tabularnewline
17 & 11.9 & 13.4002 & -1.5002 \tabularnewline
18 & 9.3 & 12.3848 & -3.08476 \tabularnewline
19 & 9.6 & 12.2521 & -2.65208 \tabularnewline
20 & 10 & 11.3904 & -1.39036 \tabularnewline
21 & 6.4 & 11.1714 & -4.77135 \tabularnewline
22 & 13.8 & 12.7042 & 1.09576 \tabularnewline
23 & 10.8 & 13.705 & -2.90497 \tabularnewline
24 & 13.8 & 11.7872 & 2.01284 \tabularnewline
25 & 11.7 & 12.7898 & -1.0898 \tabularnewline
26 & 10.9 & 14.0862 & -3.1862 \tabularnewline
27 & 16.1 & 13.5313 & 2.56872 \tabularnewline
28 & 13.4 & 11.6801 & 1.7199 \tabularnewline
29 & 9.9 & 11.2081 & -1.30814 \tabularnewline
30 & 11.5 & 12.0376 & -0.537623 \tabularnewline
31 & 8.3 & 11.7483 & -3.44826 \tabularnewline
32 & 11.7 & 13.9731 & -2.27305 \tabularnewline
33 & 9 & 12.2713 & -3.27134 \tabularnewline
34 & 9.7 & 13.6693 & -3.9693 \tabularnewline
35 & 10.8 & 12.2717 & -1.4717 \tabularnewline
36 & 10.3 & 12.6223 & -2.32228 \tabularnewline
37 & 10.4 & 11.5016 & -1.10164 \tabularnewline
38 & 12.7 & 12.1971 & 0.502923 \tabularnewline
39 & 9.3 & 12.3886 & -3.0886 \tabularnewline
40 & 11.8 & 14.6421 & -2.84213 \tabularnewline
41 & 5.9 & 10.8424 & -4.94242 \tabularnewline
42 & 11.4 & 13.8952 & -2.49517 \tabularnewline
43 & 13 & 11.678 & 1.32205 \tabularnewline
44 & 10.8 & 12.2091 & -1.40908 \tabularnewline
45 & 12.3 & 9.93265 & 2.36735 \tabularnewline
46 & 11.3 & 14.0478 & -2.74775 \tabularnewline
47 & 11.8 & 12.0918 & -0.291801 \tabularnewline
48 & 7.9 & 10.628 & -2.72799 \tabularnewline
49 & 12.7 & 10.0934 & 2.60663 \tabularnewline
50 & 12.3 & 10.8569 & 1.44313 \tabularnewline
51 & 11.6 & 11.6444 & -0.0444277 \tabularnewline
52 & 6.7 & 10.6817 & -3.98173 \tabularnewline
53 & 10.9 & 12.9199 & -2.01987 \tabularnewline
54 & 12.1 & 12.3235 & -0.223526 \tabularnewline
55 & 13.3 & 13.0987 & 0.201302 \tabularnewline
56 & 10.1 & 13.3304 & -3.23044 \tabularnewline
57 & 5.7 & 11.8963 & -6.19629 \tabularnewline
58 & 14.3 & 11.721 & 2.57902 \tabularnewline
59 & 8 & 9.20028 & -1.20028 \tabularnewline
60 & 13.3 & 11.9771 & 1.32292 \tabularnewline
61 & 9.3 & 13.0377 & -3.73772 \tabularnewline
62 & 12.5 & 12.163 & 0.337026 \tabularnewline
63 & 7.6 & 11.2092 & -3.60925 \tabularnewline
64 & 15.9 & 13.6202 & 2.27981 \tabularnewline
65 & 9.2 & 12.1603 & -2.96027 \tabularnewline
66 & 9.1 & 10.4184 & -1.3184 \tabularnewline
67 & 11.1 & 14.2453 & -3.1453 \tabularnewline
68 & 13 & 13.5375 & -0.537491 \tabularnewline
69 & 14.5 & 12.4463 & 2.05375 \tabularnewline
70 & 12.2 & 11.2409 & 0.959101 \tabularnewline
71 & 12.3 & 14.3162 & -2.01619 \tabularnewline
72 & 11.4 & 11.6671 & -0.267122 \tabularnewline
73 & 8.8 & 12.0359 & -3.23586 \tabularnewline
74 & 14.6 & 11.3069 & 3.29307 \tabularnewline
75 & 12.6 & 12.5725 & 0.0274524 \tabularnewline
76 & 13 & 13.7134 & -0.713411 \tabularnewline
77 & 12.6 & 11.3299 & 1.27009 \tabularnewline
78 & 13.2 & 15.0243 & -1.82426 \tabularnewline
79 & 9.9 & 10.8454 & -0.945416 \tabularnewline
80 & 7.7 & 11.2458 & -3.54579 \tabularnewline
81 & 10.5 & 11.0305 & -0.530508 \tabularnewline
82 & 13.4 & 10.3551 & 3.04491 \tabularnewline
83 & 10.9 & 11.998 & -1.09802 \tabularnewline
84 & 4.3 & 9.82218 & -5.52218 \tabularnewline
85 & 10.3 & 11.0611 & -0.761055 \tabularnewline
86 & 11.8 & 11.594 & 0.205994 \tabularnewline
87 & 11.2 & 10.1292 & 1.07081 \tabularnewline
88 & 11.4 & 10.9672 & 0.432805 \tabularnewline
89 & 8.6 & 10.7482 & -2.14822 \tabularnewline
90 & 13.2 & 11.1173 & 2.08272 \tabularnewline
91 & 12.6 & 10.3654 & 2.23458 \tabularnewline
92 & 5.6 & 10.9755 & -5.37548 \tabularnewline
93 & 9.9 & 11.1844 & -1.28443 \tabularnewline
94 & 8.8 & 12.4768 & -3.67677 \tabularnewline
95 & 7.7 & 11.4901 & -3.79013 \tabularnewline
96 & 9 & 10.743 & -1.743 \tabularnewline
97 & 7.3 & 12.4705 & -5.17052 \tabularnewline
98 & 11.4 & 10.9937 & 0.406295 \tabularnewline
99 & 13.6 & 11.3824 & 2.21755 \tabularnewline
100 & 7.9 & 10.3213 & -2.42132 \tabularnewline
101 & 10.7 & 10.6478 & 0.052157 \tabularnewline
102 & 10.3 & 11.7003 & -1.40026 \tabularnewline
103 & 8.3 & 9.14983 & -0.849827 \tabularnewline
104 & 9.6 & 10.374 & -0.773986 \tabularnewline
105 & 14.2 & 11.3783 & 2.82165 \tabularnewline
106 & 8.5 & 10.3363 & -1.83632 \tabularnewline
107 & 13.5 & 10.6821 & 2.8179 \tabularnewline
108 & 4.9 & 10.5628 & -5.66283 \tabularnewline
109 & 6.4 & 10.4633 & -4.06326 \tabularnewline
110 & 9.6 & 10.7907 & -1.19071 \tabularnewline
111 & 11.6 & 11.0831 & 0.516917 \tabularnewline
112 & 11.1 & 10.1188 & 0.981162 \tabularnewline
113 & 4.35 & 9.87594 & -5.52594 \tabularnewline
114 & 12.7 & 12.2701 & 0.4299 \tabularnewline
115 & 18.1 & 14.4553 & 3.64473 \tabularnewline
116 & 17.85 & 14.929 & 2.92095 \tabularnewline
117 & 16.6 & 16.8314 & -0.231366 \tabularnewline
118 & 12.6 & 9.76843 & 2.83157 \tabularnewline
119 & 17.1 & 22.2081 & -5.10806 \tabularnewline
120 & 19.1 & 15.9613 & 3.13865 \tabularnewline
121 & 16.1 & 18.0716 & -1.97164 \tabularnewline
122 & 13.35 & 10.8126 & 2.53744 \tabularnewline
123 & 18.4 & 18.1661 & 0.233905 \tabularnewline
124 & 14.7 & 10.5751 & 4.12487 \tabularnewline
125 & 10.6 & 14.2728 & -3.67276 \tabularnewline
126 & 12.6 & 12.9941 & -0.394087 \tabularnewline
127 & 16.2 & 14.7049 & 1.49508 \tabularnewline
128 & 13.6 & 16.2386 & -2.63859 \tabularnewline
129 & 18.9 & 15.7626 & 3.13736 \tabularnewline
130 & 14.1 & 12.3921 & 1.70794 \tabularnewline
131 & 14.5 & 12.1272 & 2.37283 \tabularnewline
132 & 16.15 & 18.0812 & -1.93119 \tabularnewline
133 & 14.75 & 12.4902 & 2.25982 \tabularnewline
134 & 14.8 & 13.4427 & 1.35725 \tabularnewline
135 & 12.45 & 11.8256 & 0.624398 \tabularnewline
136 & 12.65 & 14.3362 & -1.6862 \tabularnewline
137 & 17.35 & 13.6189 & 3.73113 \tabularnewline
138 & 8.6 & 11.4688 & -2.86881 \tabularnewline
139 & 18.4 & 17.7844 & 0.61557 \tabularnewline
140 & 16.1 & 17.9269 & -1.82686 \tabularnewline
141 & 11.6 & 11.1298 & 0.470194 \tabularnewline
142 & 17.75 & 11.2622 & 6.48779 \tabularnewline
143 & 15.25 & 12.2835 & 2.96647 \tabularnewline
144 & 17.65 & 15.664 & 1.986 \tabularnewline
145 & 16.35 & 14.9643 & 1.38565 \tabularnewline
146 & 17.65 & 15.5572 & 2.09278 \tabularnewline
147 & 13.6 & 12.7663 & 0.833716 \tabularnewline
148 & 14.35 & 13.5555 & 0.794506 \tabularnewline
149 & 14.75 & 17.547 & -2.79697 \tabularnewline
150 & 18.25 & 16.5309 & 1.71911 \tabularnewline
151 & 9.9 & 14.9919 & -5.09188 \tabularnewline
152 & 16 & 14.0029 & 1.99715 \tabularnewline
153 & 18.25 & 15.6658 & 2.58421 \tabularnewline
154 & 16.85 & 17.4701 & -0.620119 \tabularnewline
155 & 14.6 & 12.5625 & 2.03747 \tabularnewline
156 & 13.85 & 13.6118 & 0.238206 \tabularnewline
157 & 18.95 & 16.5353 & 2.41468 \tabularnewline
158 & 15.6 & 14.7948 & 0.805222 \tabularnewline
159 & 14.85 & 18.0694 & -3.21939 \tabularnewline
160 & 11.75 & 12.7075 & -0.957458 \tabularnewline
161 & 18.45 & 13.5793 & 4.87068 \tabularnewline
162 & 15.9 & 16.8143 & -0.914278 \tabularnewline
163 & 17.1 & 14.8134 & 2.28659 \tabularnewline
164 & 16.1 & 10.7735 & 5.32655 \tabularnewline
165 & 19.9 & 15.9179 & 3.98213 \tabularnewline
166 & 10.95 & 10.7891 & 0.160855 \tabularnewline
167 & 18.45 & 16.198 & 2.25202 \tabularnewline
168 & 15.1 & 10.4914 & 4.60863 \tabularnewline
169 & 15 & 15.8335 & -0.833539 \tabularnewline
170 & 11.35 & 14.4511 & -3.10107 \tabularnewline
171 & 15.95 & 14.864 & 1.086 \tabularnewline
172 & 18.1 & 13.713 & 4.38702 \tabularnewline
173 & 14.6 & 12.9832 & 1.6168 \tabularnewline
174 & 15.4 & 15.9404 & -0.540354 \tabularnewline
175 & 15.4 & 15.886 & -0.486032 \tabularnewline
176 & 17.6 & 12.9243 & 4.67575 \tabularnewline
177 & 13.35 & 13.722 & -0.372016 \tabularnewline
178 & 19.1 & 16.5422 & 2.55777 \tabularnewline
179 & 15.35 & 12.6825 & 2.66751 \tabularnewline
180 & 7.6 & 12.4136 & -4.81362 \tabularnewline
181 & 13.4 & 14.523 & -1.12302 \tabularnewline
182 & 13.9 & 14.1711 & -0.271097 \tabularnewline
183 & 19.1 & 16.8864 & 2.21356 \tabularnewline
184 & 15.25 & 13.7032 & 1.54679 \tabularnewline
185 & 12.9 & 11.9888 & 0.911151 \tabularnewline
186 & 16.1 & 14.5346 & 1.56536 \tabularnewline
187 & 17.35 & 12.9835 & 4.36652 \tabularnewline
188 & 13.15 & 12.8691 & 0.280931 \tabularnewline
189 & 12.15 & 10.5854 & 1.56457 \tabularnewline
190 & 12.6 & 11.9533 & 0.646731 \tabularnewline
191 & 10.35 & 11.4891 & -1.13908 \tabularnewline
192 & 15.4 & 11.9543 & 3.44566 \tabularnewline
193 & 9.6 & 10.5953 & -0.995284 \tabularnewline
194 & 18.2 & 13.1345 & 5.06555 \tabularnewline
195 & 13.6 & 12.3453 & 1.25466 \tabularnewline
196 & 14.85 & 15.4055 & -0.555524 \tabularnewline
197 & 14.75 & 17.2084 & -2.45836 \tabularnewline
198 & 14.1 & 13.6305 & 0.469498 \tabularnewline
199 & 14.9 & 11.6642 & 3.23583 \tabularnewline
200 & 16.25 & 13.1004 & 3.14963 \tabularnewline
201 & 19.25 & 19.0871 & 0.162868 \tabularnewline
202 & 13.6 & 12.1353 & 1.46466 \tabularnewline
203 & 13.6 & 13.3322 & 0.267779 \tabularnewline
204 & 15.65 & 15.1484 & 0.50159 \tabularnewline
205 & 12.75 & 11.8812 & 0.868786 \tabularnewline
206 & 14.6 & 11.2439 & 3.35608 \tabularnewline
207 & 9.85 & 12.3928 & -2.54284 \tabularnewline
208 & 12.65 & 11.4576 & 1.19244 \tabularnewline
209 & 19.2 & 15.2362 & 3.96384 \tabularnewline
210 & 16.6 & 13.8459 & 2.75414 \tabularnewline
211 & 11.2 & 9.84714 & 1.35286 \tabularnewline
212 & 15.25 & 13.1773 & 2.07273 \tabularnewline
213 & 11.9 & 14.6082 & -2.70818 \tabularnewline
214 & 13.2 & 15.8645 & -2.66451 \tabularnewline
215 & 16.35 & 17.322 & -0.971994 \tabularnewline
216 & 12.4 & 12.9058 & -0.505828 \tabularnewline
217 & 15.85 & 12.4934 & 3.35659 \tabularnewline
218 & 18.15 & 14.7194 & 3.43061 \tabularnewline
219 & 11.15 & 11.1647 & -0.0147404 \tabularnewline
220 & 15.65 & 16.5031 & -0.853069 \tabularnewline
221 & 17.75 & 15.9455 & 1.80447 \tabularnewline
222 & 7.65 & 12.2313 & -4.58128 \tabularnewline
223 & 12.35 & 12.6285 & -0.278462 \tabularnewline
224 & 15.6 & 10.9435 & 4.65649 \tabularnewline
225 & 19.3 & 16.3361 & 2.96394 \tabularnewline
226 & 15.2 & 12.481 & 2.71901 \tabularnewline
227 & 17.1 & 13.5483 & 3.55168 \tabularnewline
228 & 15.6 & 12.6158 & 2.98419 \tabularnewline
229 & 18.4 & 14.4937 & 3.90633 \tabularnewline
230 & 19.05 & 15.2694 & 3.78063 \tabularnewline
231 & 18.55 & 12.6737 & 5.87633 \tabularnewline
232 & 19.1 & 17.4864 & 1.61357 \tabularnewline
233 & 13.1 & 11.2789 & 1.82114 \tabularnewline
234 & 12.85 & 12.642 & 0.208027 \tabularnewline
235 & 9.5 & 10.1776 & -0.67758 \tabularnewline
236 & 4.5 & 11.2227 & -6.72267 \tabularnewline
237 & 11.85 & 10.8453 & 1.00468 \tabularnewline
238 & 13.6 & 15.1476 & -1.54755 \tabularnewline
239 & 11.7 & 12.6689 & -0.968935 \tabularnewline
240 & 12.4 & 10.7016 & 1.69843 \tabularnewline
241 & 13.35 & 15.2281 & -1.87815 \tabularnewline
242 & 11.4 & 13.2281 & -1.82805 \tabularnewline
243 & 14.9 & 11.3028 & 3.59716 \tabularnewline
244 & 19.9 & 15.8062 & 4.09375 \tabularnewline
245 & 11.2 & 12.2994 & -1.09944 \tabularnewline
246 & 14.6 & 14.8412 & -0.241247 \tabularnewline
247 & 17.6 & 16.1681 & 1.43194 \tabularnewline
248 & 14.05 & 12.7521 & 1.29793 \tabularnewline
249 & 16.1 & 15.594 & 0.506042 \tabularnewline
250 & 13.35 & 12.4375 & 0.912451 \tabularnewline
251 & 11.85 & 11.7913 & 0.058743 \tabularnewline
252 & 11.95 & 14.2978 & -2.34776 \tabularnewline
253 & 14.75 & 14.3317 & 0.418279 \tabularnewline
254 & 15.15 & 13.3068 & 1.84317 \tabularnewline
255 & 13.2 & 14.0696 & -0.869589 \tabularnewline
256 & 16.85 & 16.2398 & 0.610213 \tabularnewline
257 & 7.85 & 9.66851 & -1.81851 \tabularnewline
258 & 7.7 & 14.9971 & -7.29706 \tabularnewline
259 & 12.6 & 11.1713 & 1.4287 \tabularnewline
260 & 7.85 & 11.032 & -3.18202 \tabularnewline
261 & 10.95 & 11.1577 & -0.20773 \tabularnewline
262 & 12.35 & 12.3964 & -0.046382 \tabularnewline
263 & 9.95 & 12.1036 & -2.15362 \tabularnewline
264 & 14.9 & 11.4909 & 3.4091 \tabularnewline
265 & 16.65 & 14.9298 & 1.72016 \tabularnewline
266 & 13.4 & 12.9638 & 0.436213 \tabularnewline
267 & 13.95 & 14.1381 & -0.188124 \tabularnewline
268 & 15.7 & 11.0627 & 4.63725 \tabularnewline
269 & 16.85 & 12.3647 & 4.48527 \tabularnewline
270 & 10.95 & 10.0984 & 0.851641 \tabularnewline
271 & 15.35 & 11.5627 & 3.78734 \tabularnewline
272 & 12.2 & 10.7108 & 1.48919 \tabularnewline
273 & 15.1 & 13.0445 & 2.05549 \tabularnewline
274 & 17.75 & 16.3758 & 1.37424 \tabularnewline
275 & 15.2 & 12.3853 & 2.81465 \tabularnewline
276 & 14.6 & 13.9491 & 0.650859 \tabularnewline
277 & 16.65 & 14.6246 & 2.02535 \tabularnewline
278 & 8.1 & 10.9227 & -2.82265 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263629&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]12.6615[/C][C]0.238497[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]11.5221[/C][C]0.677948[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]12.8735[/C][C]-0.0734505[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.2414[/C][C]-4.84141[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]11.5644[/C][C]-4.86438[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]14.7104[/C][C]-2.11042[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.9426[/C][C]1.85739[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]12.4885[/C][C]0.811498[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.9634[/C][C]-0.863432[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.5588[/C][C]-6.35877[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.8097[/C][C]-1.40974[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.0368[/C][C]-7.63684[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.0667[/C][C]-0.466661[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.6128[/C][C]-1.61276[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]9.83005[/C][C]-3.53005[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.3636[/C][C]-0.0635677[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]13.4002[/C][C]-1.5002[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.3848[/C][C]-3.08476[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.2521[/C][C]-2.65208[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]11.3904[/C][C]-1.39036[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]11.1714[/C][C]-4.77135[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.7042[/C][C]1.09576[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]13.705[/C][C]-2.90497[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]11.7872[/C][C]2.01284[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]12.7898[/C][C]-1.0898[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]14.0862[/C][C]-3.1862[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.5313[/C][C]2.56872[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]11.6801[/C][C]1.7199[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.2081[/C][C]-1.30814[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.0376[/C][C]-0.537623[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.7483[/C][C]-3.44826[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.9731[/C][C]-2.27305[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.2713[/C][C]-3.27134[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]13.6693[/C][C]-3.9693[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.2717[/C][C]-1.4717[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.6223[/C][C]-2.32228[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.5016[/C][C]-1.10164[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.1971[/C][C]0.502923[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]12.3886[/C][C]-3.0886[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.6421[/C][C]-2.84213[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.8424[/C][C]-4.94242[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.8952[/C][C]-2.49517[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.678[/C][C]1.32205[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.2091[/C][C]-1.40908[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]9.93265[/C][C]2.36735[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]14.0478[/C][C]-2.74775[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.0918[/C][C]-0.291801[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]10.628[/C][C]-2.72799[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.0934[/C][C]2.60663[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]10.8569[/C][C]1.44313[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]11.6444[/C][C]-0.0444277[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.6817[/C][C]-3.98173[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]12.9199[/C][C]-2.01987[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.3235[/C][C]-0.223526[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.0987[/C][C]0.201302[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.3304[/C][C]-3.23044[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.8963[/C][C]-6.19629[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]11.721[/C][C]2.57902[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]9.20028[/C][C]-1.20028[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]11.9771[/C][C]1.32292[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.0377[/C][C]-3.73772[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]12.163[/C][C]0.337026[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]11.2092[/C][C]-3.60925[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.6202[/C][C]2.27981[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]12.1603[/C][C]-2.96027[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]10.4184[/C][C]-1.3184[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]14.2453[/C][C]-3.1453[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.5375[/C][C]-0.537491[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.4463[/C][C]2.05375[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.2409[/C][C]0.959101[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]14.3162[/C][C]-2.01619[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]11.6671[/C][C]-0.267122[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]12.0359[/C][C]-3.23586[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.3069[/C][C]3.29307[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.5725[/C][C]0.0274524[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]13.7134[/C][C]-0.713411[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]11.3299[/C][C]1.27009[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]15.0243[/C][C]-1.82426[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]10.8454[/C][C]-0.945416[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]11.2458[/C][C]-3.54579[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]11.0305[/C][C]-0.530508[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]10.3551[/C][C]3.04491[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]11.998[/C][C]-1.09802[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]9.82218[/C][C]-5.52218[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]11.0611[/C][C]-0.761055[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]11.594[/C][C]0.205994[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]10.1292[/C][C]1.07081[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]10.9672[/C][C]0.432805[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.7482[/C][C]-2.14822[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]11.1173[/C][C]2.08272[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]10.3654[/C][C]2.23458[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]10.9755[/C][C]-5.37548[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]11.1844[/C][C]-1.28443[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]12.4768[/C][C]-3.67677[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]11.4901[/C][C]-3.79013[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]10.743[/C][C]-1.743[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]12.4705[/C][C]-5.17052[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]10.9937[/C][C]0.406295[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]11.3824[/C][C]2.21755[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]10.3213[/C][C]-2.42132[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]10.6478[/C][C]0.052157[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]11.7003[/C][C]-1.40026[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]9.14983[/C][C]-0.849827[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]10.374[/C][C]-0.773986[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]11.3783[/C][C]2.82165[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]10.3363[/C][C]-1.83632[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]10.6821[/C][C]2.8179[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]10.5628[/C][C]-5.66283[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]10.4633[/C][C]-4.06326[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]10.7907[/C][C]-1.19071[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]11.0831[/C][C]0.516917[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]10.1188[/C][C]0.981162[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]9.87594[/C][C]-5.52594[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.2701[/C][C]0.4299[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]14.4553[/C][C]3.64473[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]14.929[/C][C]2.92095[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]16.8314[/C][C]-0.231366[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]9.76843[/C][C]2.83157[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]22.2081[/C][C]-5.10806[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]15.9613[/C][C]3.13865[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]18.0716[/C][C]-1.97164[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]10.8126[/C][C]2.53744[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]18.1661[/C][C]0.233905[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]10.5751[/C][C]4.12487[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]14.2728[/C][C]-3.67276[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]12.9941[/C][C]-0.394087[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]14.7049[/C][C]1.49508[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]16.2386[/C][C]-2.63859[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]15.7626[/C][C]3.13736[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]12.3921[/C][C]1.70794[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]12.1272[/C][C]2.37283[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]18.0812[/C][C]-1.93119[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]12.4902[/C][C]2.25982[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]13.4427[/C][C]1.35725[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]11.8256[/C][C]0.624398[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]14.3362[/C][C]-1.6862[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]13.6189[/C][C]3.73113[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]11.4688[/C][C]-2.86881[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]17.7844[/C][C]0.61557[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]17.9269[/C][C]-1.82686[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]11.1298[/C][C]0.470194[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]11.2622[/C][C]6.48779[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]12.2835[/C][C]2.96647[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]15.664[/C][C]1.986[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]14.9643[/C][C]1.38565[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]15.5572[/C][C]2.09278[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]12.7663[/C][C]0.833716[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]13.5555[/C][C]0.794506[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]17.547[/C][C]-2.79697[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]16.5309[/C][C]1.71911[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]14.9919[/C][C]-5.09188[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.0029[/C][C]1.99715[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]15.6658[/C][C]2.58421[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]17.4701[/C][C]-0.620119[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]12.5625[/C][C]2.03747[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]13.6118[/C][C]0.238206[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]16.5353[/C][C]2.41468[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]14.7948[/C][C]0.805222[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]18.0694[/C][C]-3.21939[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]12.7075[/C][C]-0.957458[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]13.5793[/C][C]4.87068[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]16.8143[/C][C]-0.914278[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]14.8134[/C][C]2.28659[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]10.7735[/C][C]5.32655[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]15.9179[/C][C]3.98213[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]10.7891[/C][C]0.160855[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]16.198[/C][C]2.25202[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]10.4914[/C][C]4.60863[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]15.8335[/C][C]-0.833539[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]14.4511[/C][C]-3.10107[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]14.864[/C][C]1.086[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]13.713[/C][C]4.38702[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]12.9832[/C][C]1.6168[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]15.9404[/C][C]-0.540354[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]15.886[/C][C]-0.486032[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]12.9243[/C][C]4.67575[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]13.722[/C][C]-0.372016[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]16.5422[/C][C]2.55777[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]12.6825[/C][C]2.66751[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]12.4136[/C][C]-4.81362[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]14.523[/C][C]-1.12302[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]14.1711[/C][C]-0.271097[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]16.8864[/C][C]2.21356[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]13.7032[/C][C]1.54679[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]11.9888[/C][C]0.911151[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]14.5346[/C][C]1.56536[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]12.9835[/C][C]4.36652[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]12.8691[/C][C]0.280931[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]10.5854[/C][C]1.56457[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]11.9533[/C][C]0.646731[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]11.4891[/C][C]-1.13908[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]11.9543[/C][C]3.44566[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]10.5953[/C][C]-0.995284[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]13.1345[/C][C]5.06555[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]12.3453[/C][C]1.25466[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]15.4055[/C][C]-0.555524[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]17.2084[/C][C]-2.45836[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]13.6305[/C][C]0.469498[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]11.6642[/C][C]3.23583[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]13.1004[/C][C]3.14963[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]19.0871[/C][C]0.162868[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]12.1353[/C][C]1.46466[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.3322[/C][C]0.267779[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]15.1484[/C][C]0.50159[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]11.8812[/C][C]0.868786[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]11.2439[/C][C]3.35608[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]12.3928[/C][C]-2.54284[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]11.4576[/C][C]1.19244[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]15.2362[/C][C]3.96384[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]13.8459[/C][C]2.75414[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]9.84714[/C][C]1.35286[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]13.1773[/C][C]2.07273[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]14.6082[/C][C]-2.70818[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]15.8645[/C][C]-2.66451[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]17.322[/C][C]-0.971994[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]12.9058[/C][C]-0.505828[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]12.4934[/C][C]3.35659[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]14.7194[/C][C]3.43061[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]11.1647[/C][C]-0.0147404[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]16.5031[/C][C]-0.853069[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]15.9455[/C][C]1.80447[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]12.2313[/C][C]-4.58128[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]12.6285[/C][C]-0.278462[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]10.9435[/C][C]4.65649[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]16.3361[/C][C]2.96394[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]12.481[/C][C]2.71901[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]13.5483[/C][C]3.55168[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]12.6158[/C][C]2.98419[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]14.4937[/C][C]3.90633[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]15.2694[/C][C]3.78063[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]12.6737[/C][C]5.87633[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]17.4864[/C][C]1.61357[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]11.2789[/C][C]1.82114[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]12.642[/C][C]0.208027[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]10.1776[/C][C]-0.67758[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]11.2227[/C][C]-6.72267[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]10.8453[/C][C]1.00468[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]15.1476[/C][C]-1.54755[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]12.6689[/C][C]-0.968935[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]10.7016[/C][C]1.69843[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]15.2281[/C][C]-1.87815[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]13.2281[/C][C]-1.82805[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]11.3028[/C][C]3.59716[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]15.8062[/C][C]4.09375[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]12.2994[/C][C]-1.09944[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]14.8412[/C][C]-0.241247[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]16.1681[/C][C]1.43194[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]12.7521[/C][C]1.29793[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]15.594[/C][C]0.506042[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]12.4375[/C][C]0.912451[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]11.7913[/C][C]0.058743[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]14.2978[/C][C]-2.34776[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]14.3317[/C][C]0.418279[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]13.3068[/C][C]1.84317[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]14.0696[/C][C]-0.869589[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]16.2398[/C][C]0.610213[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]9.66851[/C][C]-1.81851[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]14.9971[/C][C]-7.29706[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]11.1713[/C][C]1.4287[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]11.032[/C][C]-3.18202[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]11.1577[/C][C]-0.20773[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]12.3964[/C][C]-0.046382[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]12.1036[/C][C]-2.15362[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]11.4909[/C][C]3.4091[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]14.9298[/C][C]1.72016[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]12.9638[/C][C]0.436213[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]14.1381[/C][C]-0.188124[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]11.0627[/C][C]4.63725[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]12.3647[/C][C]4.48527[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]10.0984[/C][C]0.851641[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]11.5627[/C][C]3.78734[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]10.7108[/C][C]1.48919[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]13.0445[/C][C]2.05549[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]16.3758[/C][C]1.37424[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]12.3853[/C][C]2.81465[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]13.9491[/C][C]0.650859[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]14.6246[/C][C]2.02535[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]10.9227[/C][C]-2.82265[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263629&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263629&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	12.6615	0.238497
2	12.2	11.5221	0.677948
3	12.8	12.8735	-0.0734505
4	7.4	12.2414	-4.84141
5	6.7	11.5644	-4.86438
6	12.6	14.7104	-2.11042
7	14.8	12.9426	1.85739
8	13.3	12.4885	0.811498
9	11.1	11.9634	-0.863432
10	8.2	14.5588	-6.35877
11	11.4	12.8097	-1.40974
12	6.4	14.0368	-7.63684
13	10.6	11.0667	-0.466661
14	12	13.6128	-1.61276
15	6.3	9.83005	-3.53005
16	11.3	11.3636	-0.0635677
17	11.9	13.4002	-1.5002
18	9.3	12.3848	-3.08476
19	9.6	12.2521	-2.65208
20	10	11.3904	-1.39036
21	6.4	11.1714	-4.77135
22	13.8	12.7042	1.09576
23	10.8	13.705	-2.90497
24	13.8	11.7872	2.01284
25	11.7	12.7898	-1.0898
26	10.9	14.0862	-3.1862
27	16.1	13.5313	2.56872
28	13.4	11.6801	1.7199
29	9.9	11.2081	-1.30814
30	11.5	12.0376	-0.537623
31	8.3	11.7483	-3.44826
32	11.7	13.9731	-2.27305
33	9	12.2713	-3.27134
34	9.7	13.6693	-3.9693
35	10.8	12.2717	-1.4717
36	10.3	12.6223	-2.32228
37	10.4	11.5016	-1.10164
38	12.7	12.1971	0.502923
39	9.3	12.3886	-3.0886
40	11.8	14.6421	-2.84213
41	5.9	10.8424	-4.94242
42	11.4	13.8952	-2.49517
43	13	11.678	1.32205
44	10.8	12.2091	-1.40908
45	12.3	9.93265	2.36735
46	11.3	14.0478	-2.74775
47	11.8	12.0918	-0.291801
48	7.9	10.628	-2.72799
49	12.7	10.0934	2.60663
50	12.3	10.8569	1.44313
51	11.6	11.6444	-0.0444277
52	6.7	10.6817	-3.98173
53	10.9	12.9199	-2.01987
54	12.1	12.3235	-0.223526
55	13.3	13.0987	0.201302
56	10.1	13.3304	-3.23044
57	5.7	11.8963	-6.19629
58	14.3	11.721	2.57902
59	8	9.20028	-1.20028
60	13.3	11.9771	1.32292
61	9.3	13.0377	-3.73772
62	12.5	12.163	0.337026
63	7.6	11.2092	-3.60925
64	15.9	13.6202	2.27981
65	9.2	12.1603	-2.96027
66	9.1	10.4184	-1.3184
67	11.1	14.2453	-3.1453
68	13	13.5375	-0.537491
69	14.5	12.4463	2.05375
70	12.2	11.2409	0.959101
71	12.3	14.3162	-2.01619
72	11.4	11.6671	-0.267122
73	8.8	12.0359	-3.23586
74	14.6	11.3069	3.29307
75	12.6	12.5725	0.0274524
76	13	13.7134	-0.713411
77	12.6	11.3299	1.27009
78	13.2	15.0243	-1.82426
79	9.9	10.8454	-0.945416
80	7.7	11.2458	-3.54579
81	10.5	11.0305	-0.530508
82	13.4	10.3551	3.04491
83	10.9	11.998	-1.09802
84	4.3	9.82218	-5.52218
85	10.3	11.0611	-0.761055
86	11.8	11.594	0.205994
87	11.2	10.1292	1.07081
88	11.4	10.9672	0.432805
89	8.6	10.7482	-2.14822
90	13.2	11.1173	2.08272
91	12.6	10.3654	2.23458
92	5.6	10.9755	-5.37548
93	9.9	11.1844	-1.28443
94	8.8	12.4768	-3.67677
95	7.7	11.4901	-3.79013
96	9	10.743	-1.743
97	7.3	12.4705	-5.17052
98	11.4	10.9937	0.406295
99	13.6	11.3824	2.21755
100	7.9	10.3213	-2.42132
101	10.7	10.6478	0.052157
102	10.3	11.7003	-1.40026
103	8.3	9.14983	-0.849827
104	9.6	10.374	-0.773986
105	14.2	11.3783	2.82165
106	8.5	10.3363	-1.83632
107	13.5	10.6821	2.8179
108	4.9	10.5628	-5.66283
109	6.4	10.4633	-4.06326
110	9.6	10.7907	-1.19071
111	11.6	11.0831	0.516917
112	11.1	10.1188	0.981162
113	4.35	9.87594	-5.52594
114	12.7	12.2701	0.4299
115	18.1	14.4553	3.64473
116	17.85	14.929	2.92095
117	16.6	16.8314	-0.231366
118	12.6	9.76843	2.83157
119	17.1	22.2081	-5.10806
120	19.1	15.9613	3.13865
121	16.1	18.0716	-1.97164
122	13.35	10.8126	2.53744
123	18.4	18.1661	0.233905
124	14.7	10.5751	4.12487
125	10.6	14.2728	-3.67276
126	12.6	12.9941	-0.394087
127	16.2	14.7049	1.49508
128	13.6	16.2386	-2.63859
129	18.9	15.7626	3.13736
130	14.1	12.3921	1.70794
131	14.5	12.1272	2.37283
132	16.15	18.0812	-1.93119
133	14.75	12.4902	2.25982
134	14.8	13.4427	1.35725
135	12.45	11.8256	0.624398
136	12.65	14.3362	-1.6862
137	17.35	13.6189	3.73113
138	8.6	11.4688	-2.86881
139	18.4	17.7844	0.61557
140	16.1	17.9269	-1.82686
141	11.6	11.1298	0.470194
142	17.75	11.2622	6.48779
143	15.25	12.2835	2.96647
144	17.65	15.664	1.986
145	16.35	14.9643	1.38565
146	17.65	15.5572	2.09278
147	13.6	12.7663	0.833716
148	14.35	13.5555	0.794506
149	14.75	17.547	-2.79697
150	18.25	16.5309	1.71911
151	9.9	14.9919	-5.09188
152	16	14.0029	1.99715
153	18.25	15.6658	2.58421
154	16.85	17.4701	-0.620119
155	14.6	12.5625	2.03747
156	13.85	13.6118	0.238206
157	18.95	16.5353	2.41468
158	15.6	14.7948	0.805222
159	14.85	18.0694	-3.21939
160	11.75	12.7075	-0.957458
161	18.45	13.5793	4.87068
162	15.9	16.8143	-0.914278
163	17.1	14.8134	2.28659
164	16.1	10.7735	5.32655
165	19.9	15.9179	3.98213
166	10.95	10.7891	0.160855
167	18.45	16.198	2.25202
168	15.1	10.4914	4.60863
169	15	15.8335	-0.833539
170	11.35	14.4511	-3.10107
171	15.95	14.864	1.086
172	18.1	13.713	4.38702
173	14.6	12.9832	1.6168
174	15.4	15.9404	-0.540354
175	15.4	15.886	-0.486032
176	17.6	12.9243	4.67575
177	13.35	13.722	-0.372016
178	19.1	16.5422	2.55777
179	15.35	12.6825	2.66751
180	7.6	12.4136	-4.81362
181	13.4	14.523	-1.12302
182	13.9	14.1711	-0.271097
183	19.1	16.8864	2.21356
184	15.25	13.7032	1.54679
185	12.9	11.9888	0.911151
186	16.1	14.5346	1.56536
187	17.35	12.9835	4.36652
188	13.15	12.8691	0.280931
189	12.15	10.5854	1.56457
190	12.6	11.9533	0.646731
191	10.35	11.4891	-1.13908
192	15.4	11.9543	3.44566
193	9.6	10.5953	-0.995284
194	18.2	13.1345	5.06555
195	13.6	12.3453	1.25466
196	14.85	15.4055	-0.555524
197	14.75	17.2084	-2.45836
198	14.1	13.6305	0.469498
199	14.9	11.6642	3.23583
200	16.25	13.1004	3.14963
201	19.25	19.0871	0.162868
202	13.6	12.1353	1.46466
203	13.6	13.3322	0.267779
204	15.65	15.1484	0.50159
205	12.75	11.8812	0.868786
206	14.6	11.2439	3.35608
207	9.85	12.3928	-2.54284
208	12.65	11.4576	1.19244
209	19.2	15.2362	3.96384
210	16.6	13.8459	2.75414
211	11.2	9.84714	1.35286
212	15.25	13.1773	2.07273
213	11.9	14.6082	-2.70818
214	13.2	15.8645	-2.66451
215	16.35	17.322	-0.971994
216	12.4	12.9058	-0.505828
217	15.85	12.4934	3.35659
218	18.15	14.7194	3.43061
219	11.15	11.1647	-0.0147404
220	15.65	16.5031	-0.853069
221	17.75	15.9455	1.80447
222	7.65	12.2313	-4.58128
223	12.35	12.6285	-0.278462
224	15.6	10.9435	4.65649
225	19.3	16.3361	2.96394
226	15.2	12.481	2.71901
227	17.1	13.5483	3.55168
228	15.6	12.6158	2.98419
229	18.4	14.4937	3.90633
230	19.05	15.2694	3.78063
231	18.55	12.6737	5.87633
232	19.1	17.4864	1.61357
233	13.1	11.2789	1.82114
234	12.85	12.642	0.208027
235	9.5	10.1776	-0.67758
236	4.5	11.2227	-6.72267
237	11.85	10.8453	1.00468
238	13.6	15.1476	-1.54755
239	11.7	12.6689	-0.968935
240	12.4	10.7016	1.69843
241	13.35	15.2281	-1.87815
242	11.4	13.2281	-1.82805
243	14.9	11.3028	3.59716
244	19.9	15.8062	4.09375
245	11.2	12.2994	-1.09944
246	14.6	14.8412	-0.241247
247	17.6	16.1681	1.43194
248	14.05	12.7521	1.29793
249	16.1	15.594	0.506042
250	13.35	12.4375	0.912451
251	11.85	11.7913	0.058743
252	11.95	14.2978	-2.34776
253	14.75	14.3317	0.418279
254	15.15	13.3068	1.84317
255	13.2	14.0696	-0.869589
256	16.85	16.2398	0.610213
257	7.85	9.66851	-1.81851
258	7.7	14.9971	-7.29706
259	12.6	11.1713	1.4287
260	7.85	11.032	-3.18202
261	10.95	11.1577	-0.20773
262	12.35	12.3964	-0.046382
263	9.95	12.1036	-2.15362
264	14.9	11.4909	3.4091
265	16.65	14.9298	1.72016
266	13.4	12.9638	0.436213
267	13.95	14.1381	-0.188124
268	15.7	11.0627	4.63725
269	16.85	12.3647	4.48527
270	10.95	10.0984	0.851641
271	15.35	11.5627	3.78734
272	12.2	10.7108	1.48919
273	15.1	13.0445	2.05549
274	17.75	16.3758	1.37424
275	15.2	12.3853	2.81465
276	14.6	13.9491	0.650859
277	16.65	14.6246	2.02535
278	8.1	10.9227	-2.82265

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
16	0.137714	0.275429	0.862286
17	0.219679	0.439357	0.780321
18	0.164406	0.328813	0.835594
19	0.090264	0.180528	0.909736
20	0.0476324	0.0952648	0.952368
21	0.0314499	0.0628998	0.96855
22	0.0162424	0.0324848	0.983758
23	0.0292331	0.0584662	0.970767
24	0.0175863	0.0351726	0.982414
25	0.00958879	0.0191776	0.990411
26	0.0061045	0.012209	0.993895
27	0.00314169	0.00628338	0.996858
28	0.00237978	0.00475956	0.99762
29	0.00117127	0.00234254	0.998829
30	0.00166209	0.00332418	0.998338
31	0.00142758	0.00285516	0.998572
32	0.00200909	0.00401819	0.997991
33	0.00132551	0.00265102	0.998674
34	0.00107521	0.00215042	0.998925
35	0.000793566	0.00158713	0.999206
36	0.000699927	0.00139985	0.9993
37	0.000378588	0.000757176	0.999621
38	0.00175182	0.00350364	0.998248
39	0.0057213	0.0114426	0.994279
40	0.0038641	0.00772819	0.996136
41	0.00574314	0.0114863	0.994257
42	0.00472668	0.00945336	0.995273
43	0.00660281	0.0132056	0.993397
44	0.00457141	0.00914282	0.995429
45	0.00755839	0.0151168	0.992442
46	0.0058059	0.0116118	0.994194
47	0.00564576	0.0112915	0.994354
48	0.00447886	0.00895771	0.995521
49	0.00526323	0.0105265	0.994737
50	0.0100869	0.0201738	0.989913
51	0.00960236	0.0192047	0.990398
52	0.00969289	0.0193858	0.990307
53	0.0108376	0.0216753	0.989162
54	0.0187547	0.0375094	0.981245
55	0.0433348	0.0866695	0.956665
56	0.0357278	0.0714556	0.964272
57	0.106995	0.213989	0.893005
58	0.0951757	0.190351	0.904824
59	0.0776807	0.155361	0.922319
60	0.0813116	0.162623	0.918688
61	0.0939777	0.187955	0.906022
62	0.0791253	0.158251	0.920875
63	0.187579	0.375158	0.812421
64	0.225434	0.450868	0.774566
65	0.238463	0.476925	0.761537
66	0.214751	0.429501	0.785249
67	0.217629	0.435258	0.782371
68	0.201283	0.402566	0.798717
69	0.211053	0.422106	0.788947
70	0.190394	0.380788	0.809606
71	0.179866	0.359733	0.820134
72	0.15979	0.319579	0.84021
73	0.148731	0.297463	0.851269
74	0.16214	0.324281	0.83786
75	0.14391	0.28782	0.85609
76	0.129907	0.259814	0.870093
77	0.112937	0.225874	0.887063
78	0.118086	0.236172	0.881914
79	0.0998854	0.199771	0.900115
80	0.120266	0.240532	0.879734
81	0.102833	0.205666	0.897167
82	0.122715	0.24543	0.877285
83	0.105445	0.21089	0.894555
84	0.18842	0.37684	0.81158
85	0.171896	0.343791	0.828104
86	0.154031	0.308063	0.845969
87	0.139334	0.278668	0.860666
88	0.122926	0.245852	0.877074
89	0.122181	0.244362	0.877819
90	0.117819	0.235639	0.882181
91	0.13711	0.274219	0.86289
92	0.228348	0.456696	0.771652
93	0.22423	0.44846	0.77577
94	0.226336	0.452672	0.773664
95	0.24246	0.48492	0.75754
96	0.239288	0.478576	0.760712
97	0.314277	0.628554	0.685723
98	0.301675	0.60335	0.698325
99	0.315069	0.630138	0.684931
100	0.364856	0.729711	0.635144
101	0.34665	0.6933	0.65335
102	0.331562	0.663125	0.668438
103	0.327809	0.655618	0.672191
104	0.332351	0.664701	0.667649
105	0.374945	0.749889	0.625055
106	0.390551	0.781103	0.609449
107	0.403823	0.807646	0.596177
108	0.61877	0.76246	0.38123
109	0.670593	0.658814	0.329407
110	0.688566	0.622869	0.311434
111	0.691367	0.617266	0.308633
112	0.669328	0.661345	0.330672
113	0.7498	0.5004	0.2502
114	0.736653	0.526694	0.263347
115	0.851811	0.296377	0.148189
116	0.900803	0.198394	0.0991972
117	0.889095	0.221811	0.110905
118	0.920208	0.159584	0.0797919
119	0.917618	0.164763	0.0823816
120	0.928394	0.143212	0.0716061
121	0.934282	0.131437	0.0657185
122	0.934773	0.130454	0.0652268
123	0.928728	0.142545	0.0712724
124	0.95978	0.0804406	0.0402203
125	0.962564	0.0748714	0.0374357
126	0.956022	0.0879551	0.0439775
127	0.961117	0.0777656	0.0388828
128	0.956006	0.0879887	0.0439943
129	0.957104	0.0857927	0.0428964
130	0.954781	0.090438	0.045219
131	0.955142	0.0897166	0.0448583
132	0.952508	0.0949835	0.0474917
133	0.960762	0.0784761	0.039238
134	0.959283	0.0814341	0.040717
135	0.951419	0.097162	0.048581
136	0.943046	0.113907	0.0569537
137	0.96088	0.0782408	0.0391204
138	0.958146	0.0837075	0.0418538
139	0.952577	0.0948462	0.0474231
140	0.94361	0.112779	0.0563895
141	0.933904	0.132191	0.0660956
142	0.96768	0.0646394	0.0323197
143	0.967246	0.0655089	0.0327544
144	0.969228	0.0615433	0.0307716
145	0.964281	0.0714381	0.0357191
146	0.963516	0.0729676	0.0364838
147	0.961023	0.0779548	0.0389774
148	0.955269	0.0894614	0.0447307
149	0.948944	0.102113	0.0510563
150	0.946127	0.107747	0.0538734
151	0.980808	0.0383839	0.0191919
152	0.980756	0.0384875	0.0192437
153	0.981505	0.036989	0.0184945
154	0.977165	0.0456698	0.0228349
155	0.977596	0.0448075	0.0224037
156	0.973661	0.0526773	0.0263386
157	0.972832	0.0543362	0.0271681
158	0.967651	0.0646981	0.0323491
159	0.969935	0.06013	0.030065
160	0.965016	0.069969	0.0349845
161	0.972309	0.0553816	0.0276908
162	0.967572	0.0648552	0.0324276
163	0.969449	0.0611024	0.0305512
164	0.993618	0.0127637	0.00638184
165	0.993482	0.0130353	0.00651763
166	0.991943	0.0161136	0.00805682
167	0.991196	0.0176074	0.00880369
168	0.994331	0.0113389	0.00566947
169	0.992691	0.0146186	0.00730932
170	0.993598	0.0128038	0.00640191
171	0.992608	0.0147838	0.00739189
172	0.994337	0.0113257	0.00566286
173	0.993494	0.0130112	0.00650558
174	0.991587	0.0168257	0.00841287
175	0.989201	0.0215988	0.0107994
176	0.992932	0.014136	0.00706802
177	0.991353	0.0172945	0.00864724
178	0.991378	0.0172435	0.00862174
179	0.989996	0.020008	0.010004
180	0.993182	0.0136366	0.00681828
181	0.993767	0.0124667	0.00623334
182	0.994217	0.0115663	0.00578315
183	0.993872	0.0122561	0.00612804
184	0.992443	0.0151134	0.00755668
185	0.991512	0.016976	0.00848801
186	0.989274	0.0214512	0.0107256
187	0.992457	0.0150859	0.00754295
188	0.991801	0.0163983	0.00819914
189	0.990636	0.0187277	0.00936386
190	0.988405	0.02319	0.011595
191	0.985961	0.0280789	0.0140395
192	0.985142	0.0297152	0.0148576
193	0.982877	0.0342452	0.0171226
194	0.988519	0.022963	0.0114815
195	0.985277	0.0294462	0.0147231
196	0.984646	0.0307086	0.0153543
197	0.987525	0.0249507	0.0124753
198	0.983904	0.0321922	0.0160961
199	0.9818	0.0363993	0.0181997
200	0.979111	0.0417775	0.0208887
201	0.973254	0.0534916	0.0267458
202	0.968426	0.0631479	0.0315739
203	0.971218	0.0575648	0.0287824
204	0.963689	0.0726218	0.0363109
205	0.954229	0.0915418	0.0457709
206	0.960323	0.0793542	0.0396771
207	0.95217	0.0956601	0.04783
208	0.946218	0.107564	0.0537819
209	0.942767	0.114467	0.0572334
210	0.938975	0.12205	0.0610252
211	0.928335	0.14333	0.0716649
212	0.915511	0.168978	0.0844888
213	0.940447	0.119107	0.0595533
214	0.935098	0.129803	0.0649017
215	0.927955	0.144089	0.0720446
216	0.910695	0.178609	0.0893047
217	0.918451	0.163097	0.0815485
218	0.912595	0.17481	0.0874049
219	0.892307	0.215386	0.107693
220	0.87119	0.257619	0.12881
221	0.855141	0.289719	0.144859
222	0.8749	0.250199	0.1251
223	0.852139	0.295723	0.147861
224	0.885961	0.228077	0.114039
225	0.873299	0.253402	0.126701
226	0.899566	0.200869	0.100434
227	0.915769	0.168462	0.0842311
228	0.922352	0.155295	0.0776475
229	0.92594	0.14812	0.07406
230	0.937493	0.125013	0.0625067
231	0.939464	0.121072	0.0605361
232	0.923368	0.153264	0.0766318
233	0.917442	0.165116	0.0825579
234	0.895266	0.209468	0.104734
235	0.866876	0.266248	0.133124
236	0.967632	0.064736	0.032368
237	0.962199	0.0756025	0.0378012
238	0.954748	0.0905049	0.0452524
239	0.939908	0.120184	0.0600918
240	0.921416	0.157169	0.0785843
241	0.919599	0.160803	0.0804015
242	0.897816	0.204368	0.102184
243	0.891214	0.217573	0.108786
244	0.86181	0.276379	0.13819
245	0.834747	0.330506	0.165253
246	0.792421	0.415159	0.207579
247	0.789565	0.420871	0.210435
248	0.90266	0.19468	0.09734
249	0.91666	0.166681	0.0833404
250	0.892567	0.214865	0.107433
251	0.887284	0.225432	0.112716
252	0.852794	0.294413	0.147206
253	0.897661	0.204678	0.102339
254	0.860093	0.279813	0.139907
255	0.82283	0.35434	0.17717
256	0.77833	0.44334	0.22167
257	0.790531	0.418938	0.209469
258	0.957068	0.0858636	0.0429318
259	0.984633	0.0307341	0.0153671
260	0.985038	0.0299232	0.0149616
261	0.981551	0.0368977	0.0184489
262	0.948743	0.102514	0.0512572

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
16 & 0.137714 & 0.275429 & 0.862286 \tabularnewline
17 & 0.219679 & 0.439357 & 0.780321 \tabularnewline
18 & 0.164406 & 0.328813 & 0.835594 \tabularnewline
19 & 0.090264 & 0.180528 & 0.909736 \tabularnewline
20 & 0.0476324 & 0.0952648 & 0.952368 \tabularnewline
21 & 0.0314499 & 0.0628998 & 0.96855 \tabularnewline
22 & 0.0162424 & 0.0324848 & 0.983758 \tabularnewline
23 & 0.0292331 & 0.0584662 & 0.970767 \tabularnewline
24 & 0.0175863 & 0.0351726 & 0.982414 \tabularnewline
25 & 0.00958879 & 0.0191776 & 0.990411 \tabularnewline
26 & 0.0061045 & 0.012209 & 0.993895 \tabularnewline
27 & 0.00314169 & 0.00628338 & 0.996858 \tabularnewline
28 & 0.00237978 & 0.00475956 & 0.99762 \tabularnewline
29 & 0.00117127 & 0.00234254 & 0.998829 \tabularnewline
30 & 0.00166209 & 0.00332418 & 0.998338 \tabularnewline
31 & 0.00142758 & 0.00285516 & 0.998572 \tabularnewline
32 & 0.00200909 & 0.00401819 & 0.997991 \tabularnewline
33 & 0.00132551 & 0.00265102 & 0.998674 \tabularnewline
34 & 0.00107521 & 0.00215042 & 0.998925 \tabularnewline
35 & 0.000793566 & 0.00158713 & 0.999206 \tabularnewline
36 & 0.000699927 & 0.00139985 & 0.9993 \tabularnewline
37 & 0.000378588 & 0.000757176 & 0.999621 \tabularnewline
38 & 0.00175182 & 0.00350364 & 0.998248 \tabularnewline
39 & 0.0057213 & 0.0114426 & 0.994279 \tabularnewline
40 & 0.0038641 & 0.00772819 & 0.996136 \tabularnewline
41 & 0.00574314 & 0.0114863 & 0.994257 \tabularnewline
42 & 0.00472668 & 0.00945336 & 0.995273 \tabularnewline
43 & 0.00660281 & 0.0132056 & 0.993397 \tabularnewline
44 & 0.00457141 & 0.00914282 & 0.995429 \tabularnewline
45 & 0.00755839 & 0.0151168 & 0.992442 \tabularnewline
46 & 0.0058059 & 0.0116118 & 0.994194 \tabularnewline
47 & 0.00564576 & 0.0112915 & 0.994354 \tabularnewline
48 & 0.00447886 & 0.00895771 & 0.995521 \tabularnewline
49 & 0.00526323 & 0.0105265 & 0.994737 \tabularnewline
50 & 0.0100869 & 0.0201738 & 0.989913 \tabularnewline
51 & 0.00960236 & 0.0192047 & 0.990398 \tabularnewline
52 & 0.00969289 & 0.0193858 & 0.990307 \tabularnewline
53 & 0.0108376 & 0.0216753 & 0.989162 \tabularnewline
54 & 0.0187547 & 0.0375094 & 0.981245 \tabularnewline
55 & 0.0433348 & 0.0866695 & 0.956665 \tabularnewline
56 & 0.0357278 & 0.0714556 & 0.964272 \tabularnewline
57 & 0.106995 & 0.213989 & 0.893005 \tabularnewline
58 & 0.0951757 & 0.190351 & 0.904824 \tabularnewline
59 & 0.0776807 & 0.155361 & 0.922319 \tabularnewline
60 & 0.0813116 & 0.162623 & 0.918688 \tabularnewline
61 & 0.0939777 & 0.187955 & 0.906022 \tabularnewline
62 & 0.0791253 & 0.158251 & 0.920875 \tabularnewline
63 & 0.187579 & 0.375158 & 0.812421 \tabularnewline
64 & 0.225434 & 0.450868 & 0.774566 \tabularnewline
65 & 0.238463 & 0.476925 & 0.761537 \tabularnewline
66 & 0.214751 & 0.429501 & 0.785249 \tabularnewline
67 & 0.217629 & 0.435258 & 0.782371 \tabularnewline
68 & 0.201283 & 0.402566 & 0.798717 \tabularnewline
69 & 0.211053 & 0.422106 & 0.788947 \tabularnewline
70 & 0.190394 & 0.380788 & 0.809606 \tabularnewline
71 & 0.179866 & 0.359733 & 0.820134 \tabularnewline
72 & 0.15979 & 0.319579 & 0.84021 \tabularnewline
73 & 0.148731 & 0.297463 & 0.851269 \tabularnewline
74 & 0.16214 & 0.324281 & 0.83786 \tabularnewline
75 & 0.14391 & 0.28782 & 0.85609 \tabularnewline
76 & 0.129907 & 0.259814 & 0.870093 \tabularnewline
77 & 0.112937 & 0.225874 & 0.887063 \tabularnewline
78 & 0.118086 & 0.236172 & 0.881914 \tabularnewline
79 & 0.0998854 & 0.199771 & 0.900115 \tabularnewline
80 & 0.120266 & 0.240532 & 0.879734 \tabularnewline
81 & 0.102833 & 0.205666 & 0.897167 \tabularnewline
82 & 0.122715 & 0.24543 & 0.877285 \tabularnewline
83 & 0.105445 & 0.21089 & 0.894555 \tabularnewline
84 & 0.18842 & 0.37684 & 0.81158 \tabularnewline
85 & 0.171896 & 0.343791 & 0.828104 \tabularnewline
86 & 0.154031 & 0.308063 & 0.845969 \tabularnewline
87 & 0.139334 & 0.278668 & 0.860666 \tabularnewline
88 & 0.122926 & 0.245852 & 0.877074 \tabularnewline
89 & 0.122181 & 0.244362 & 0.877819 \tabularnewline
90 & 0.117819 & 0.235639 & 0.882181 \tabularnewline
91 & 0.13711 & 0.274219 & 0.86289 \tabularnewline
92 & 0.228348 & 0.456696 & 0.771652 \tabularnewline
93 & 0.22423 & 0.44846 & 0.77577 \tabularnewline
94 & 0.226336 & 0.452672 & 0.773664 \tabularnewline
95 & 0.24246 & 0.48492 & 0.75754 \tabularnewline
96 & 0.239288 & 0.478576 & 0.760712 \tabularnewline
97 & 0.314277 & 0.628554 & 0.685723 \tabularnewline
98 & 0.301675 & 0.60335 & 0.698325 \tabularnewline
99 & 0.315069 & 0.630138 & 0.684931 \tabularnewline
100 & 0.364856 & 0.729711 & 0.635144 \tabularnewline
101 & 0.34665 & 0.6933 & 0.65335 \tabularnewline
102 & 0.331562 & 0.663125 & 0.668438 \tabularnewline
103 & 0.327809 & 0.655618 & 0.672191 \tabularnewline
104 & 0.332351 & 0.664701 & 0.667649 \tabularnewline
105 & 0.374945 & 0.749889 & 0.625055 \tabularnewline
106 & 0.390551 & 0.781103 & 0.609449 \tabularnewline
107 & 0.403823 & 0.807646 & 0.596177 \tabularnewline
108 & 0.61877 & 0.76246 & 0.38123 \tabularnewline
109 & 0.670593 & 0.658814 & 0.329407 \tabularnewline
110 & 0.688566 & 0.622869 & 0.311434 \tabularnewline
111 & 0.691367 & 0.617266 & 0.308633 \tabularnewline
112 & 0.669328 & 0.661345 & 0.330672 \tabularnewline
113 & 0.7498 & 0.5004 & 0.2502 \tabularnewline
114 & 0.736653 & 0.526694 & 0.263347 \tabularnewline
115 & 0.851811 & 0.296377 & 0.148189 \tabularnewline
116 & 0.900803 & 0.198394 & 0.0991972 \tabularnewline
117 & 0.889095 & 0.221811 & 0.110905 \tabularnewline
118 & 0.920208 & 0.159584 & 0.0797919 \tabularnewline
119 & 0.917618 & 0.164763 & 0.0823816 \tabularnewline
120 & 0.928394 & 0.143212 & 0.0716061 \tabularnewline
121 & 0.934282 & 0.131437 & 0.0657185 \tabularnewline
122 & 0.934773 & 0.130454 & 0.0652268 \tabularnewline
123 & 0.928728 & 0.142545 & 0.0712724 \tabularnewline
124 & 0.95978 & 0.0804406 & 0.0402203 \tabularnewline
125 & 0.962564 & 0.0748714 & 0.0374357 \tabularnewline
126 & 0.956022 & 0.0879551 & 0.0439775 \tabularnewline
127 & 0.961117 & 0.0777656 & 0.0388828 \tabularnewline
128 & 0.956006 & 0.0879887 & 0.0439943 \tabularnewline
129 & 0.957104 & 0.0857927 & 0.0428964 \tabularnewline
130 & 0.954781 & 0.090438 & 0.045219 \tabularnewline
131 & 0.955142 & 0.0897166 & 0.0448583 \tabularnewline
132 & 0.952508 & 0.0949835 & 0.0474917 \tabularnewline
133 & 0.960762 & 0.0784761 & 0.039238 \tabularnewline
134 & 0.959283 & 0.0814341 & 0.040717 \tabularnewline
135 & 0.951419 & 0.097162 & 0.048581 \tabularnewline
136 & 0.943046 & 0.113907 & 0.0569537 \tabularnewline
137 & 0.96088 & 0.0782408 & 0.0391204 \tabularnewline
138 & 0.958146 & 0.0837075 & 0.0418538 \tabularnewline
139 & 0.952577 & 0.0948462 & 0.0474231 \tabularnewline
140 & 0.94361 & 0.112779 & 0.0563895 \tabularnewline
141 & 0.933904 & 0.132191 & 0.0660956 \tabularnewline
142 & 0.96768 & 0.0646394 & 0.0323197 \tabularnewline
143 & 0.967246 & 0.0655089 & 0.0327544 \tabularnewline
144 & 0.969228 & 0.0615433 & 0.0307716 \tabularnewline
145 & 0.964281 & 0.0714381 & 0.0357191 \tabularnewline
146 & 0.963516 & 0.0729676 & 0.0364838 \tabularnewline
147 & 0.961023 & 0.0779548 & 0.0389774 \tabularnewline
148 & 0.955269 & 0.0894614 & 0.0447307 \tabularnewline
149 & 0.948944 & 0.102113 & 0.0510563 \tabularnewline
150 & 0.946127 & 0.107747 & 0.0538734 \tabularnewline
151 & 0.980808 & 0.0383839 & 0.0191919 \tabularnewline
152 & 0.980756 & 0.0384875 & 0.0192437 \tabularnewline
153 & 0.981505 & 0.036989 & 0.0184945 \tabularnewline
154 & 0.977165 & 0.0456698 & 0.0228349 \tabularnewline
155 & 0.977596 & 0.0448075 & 0.0224037 \tabularnewline
156 & 0.973661 & 0.0526773 & 0.0263386 \tabularnewline
157 & 0.972832 & 0.0543362 & 0.0271681 \tabularnewline
158 & 0.967651 & 0.0646981 & 0.0323491 \tabularnewline
159 & 0.969935 & 0.06013 & 0.030065 \tabularnewline
160 & 0.965016 & 0.069969 & 0.0349845 \tabularnewline
161 & 0.972309 & 0.0553816 & 0.0276908 \tabularnewline
162 & 0.967572 & 0.0648552 & 0.0324276 \tabularnewline
163 & 0.969449 & 0.0611024 & 0.0305512 \tabularnewline
164 & 0.993618 & 0.0127637 & 0.00638184 \tabularnewline
165 & 0.993482 & 0.0130353 & 0.00651763 \tabularnewline
166 & 0.991943 & 0.0161136 & 0.00805682 \tabularnewline
167 & 0.991196 & 0.0176074 & 0.00880369 \tabularnewline
168 & 0.994331 & 0.0113389 & 0.00566947 \tabularnewline
169 & 0.992691 & 0.0146186 & 0.00730932 \tabularnewline
170 & 0.993598 & 0.0128038 & 0.00640191 \tabularnewline
171 & 0.992608 & 0.0147838 & 0.00739189 \tabularnewline
172 & 0.994337 & 0.0113257 & 0.00566286 \tabularnewline
173 & 0.993494 & 0.0130112 & 0.00650558 \tabularnewline
174 & 0.991587 & 0.0168257 & 0.00841287 \tabularnewline
175 & 0.989201 & 0.0215988 & 0.0107994 \tabularnewline
176 & 0.992932 & 0.014136 & 0.00706802 \tabularnewline
177 & 0.991353 & 0.0172945 & 0.00864724 \tabularnewline
178 & 0.991378 & 0.0172435 & 0.00862174 \tabularnewline
179 & 0.989996 & 0.020008 & 0.010004 \tabularnewline
180 & 0.993182 & 0.0136366 & 0.00681828 \tabularnewline
181 & 0.993767 & 0.0124667 & 0.00623334 \tabularnewline
182 & 0.994217 & 0.0115663 & 0.00578315 \tabularnewline
183 & 0.993872 & 0.0122561 & 0.00612804 \tabularnewline
184 & 0.992443 & 0.0151134 & 0.00755668 \tabularnewline
185 & 0.991512 & 0.016976 & 0.00848801 \tabularnewline
186 & 0.989274 & 0.0214512 & 0.0107256 \tabularnewline
187 & 0.992457 & 0.0150859 & 0.00754295 \tabularnewline
188 & 0.991801 & 0.0163983 & 0.00819914 \tabularnewline
189 & 0.990636 & 0.0187277 & 0.00936386 \tabularnewline
190 & 0.988405 & 0.02319 & 0.011595 \tabularnewline
191 & 0.985961 & 0.0280789 & 0.0140395 \tabularnewline
192 & 0.985142 & 0.0297152 & 0.0148576 \tabularnewline
193 & 0.982877 & 0.0342452 & 0.0171226 \tabularnewline
194 & 0.988519 & 0.022963 & 0.0114815 \tabularnewline
195 & 0.985277 & 0.0294462 & 0.0147231 \tabularnewline
196 & 0.984646 & 0.0307086 & 0.0153543 \tabularnewline
197 & 0.987525 & 0.0249507 & 0.0124753 \tabularnewline
198 & 0.983904 & 0.0321922 & 0.0160961 \tabularnewline
199 & 0.9818 & 0.0363993 & 0.0181997 \tabularnewline
200 & 0.979111 & 0.0417775 & 0.0208887 \tabularnewline
201 & 0.973254 & 0.0534916 & 0.0267458 \tabularnewline
202 & 0.968426 & 0.0631479 & 0.0315739 \tabularnewline
203 & 0.971218 & 0.0575648 & 0.0287824 \tabularnewline
204 & 0.963689 & 0.0726218 & 0.0363109 \tabularnewline
205 & 0.954229 & 0.0915418 & 0.0457709 \tabularnewline
206 & 0.960323 & 0.0793542 & 0.0396771 \tabularnewline
207 & 0.95217 & 0.0956601 & 0.04783 \tabularnewline
208 & 0.946218 & 0.107564 & 0.0537819 \tabularnewline
209 & 0.942767 & 0.114467 & 0.0572334 \tabularnewline
210 & 0.938975 & 0.12205 & 0.0610252 \tabularnewline
211 & 0.928335 & 0.14333 & 0.0716649 \tabularnewline
212 & 0.915511 & 0.168978 & 0.0844888 \tabularnewline
213 & 0.940447 & 0.119107 & 0.0595533 \tabularnewline
214 & 0.935098 & 0.129803 & 0.0649017 \tabularnewline
215 & 0.927955 & 0.144089 & 0.0720446 \tabularnewline
216 & 0.910695 & 0.178609 & 0.0893047 \tabularnewline
217 & 0.918451 & 0.163097 & 0.0815485 \tabularnewline
218 & 0.912595 & 0.17481 & 0.0874049 \tabularnewline
219 & 0.892307 & 0.215386 & 0.107693 \tabularnewline
220 & 0.87119 & 0.257619 & 0.12881 \tabularnewline
221 & 0.855141 & 0.289719 & 0.144859 \tabularnewline
222 & 0.8749 & 0.250199 & 0.1251 \tabularnewline
223 & 0.852139 & 0.295723 & 0.147861 \tabularnewline
224 & 0.885961 & 0.228077 & 0.114039 \tabularnewline
225 & 0.873299 & 0.253402 & 0.126701 \tabularnewline
226 & 0.899566 & 0.200869 & 0.100434 \tabularnewline
227 & 0.915769 & 0.168462 & 0.0842311 \tabularnewline
228 & 0.922352 & 0.155295 & 0.0776475 \tabularnewline
229 & 0.92594 & 0.14812 & 0.07406 \tabularnewline
230 & 0.937493 & 0.125013 & 0.0625067 \tabularnewline
231 & 0.939464 & 0.121072 & 0.0605361 \tabularnewline
232 & 0.923368 & 0.153264 & 0.0766318 \tabularnewline
233 & 0.917442 & 0.165116 & 0.0825579 \tabularnewline
234 & 0.895266 & 0.209468 & 0.104734 \tabularnewline
235 & 0.866876 & 0.266248 & 0.133124 \tabularnewline
236 & 0.967632 & 0.064736 & 0.032368 \tabularnewline
237 & 0.962199 & 0.0756025 & 0.0378012 \tabularnewline
238 & 0.954748 & 0.0905049 & 0.0452524 \tabularnewline
239 & 0.939908 & 0.120184 & 0.0600918 \tabularnewline
240 & 0.921416 & 0.157169 & 0.0785843 \tabularnewline
241 & 0.919599 & 0.160803 & 0.0804015 \tabularnewline
242 & 0.897816 & 0.204368 & 0.102184 \tabularnewline
243 & 0.891214 & 0.217573 & 0.108786 \tabularnewline
244 & 0.86181 & 0.276379 & 0.13819 \tabularnewline
245 & 0.834747 & 0.330506 & 0.165253 \tabularnewline
246 & 0.792421 & 0.415159 & 0.207579 \tabularnewline
247 & 0.789565 & 0.420871 & 0.210435 \tabularnewline
248 & 0.90266 & 0.19468 & 0.09734 \tabularnewline
249 & 0.91666 & 0.166681 & 0.0833404 \tabularnewline
250 & 0.892567 & 0.214865 & 0.107433 \tabularnewline
251 & 0.887284 & 0.225432 & 0.112716 \tabularnewline
252 & 0.852794 & 0.294413 & 0.147206 \tabularnewline
253 & 0.897661 & 0.204678 & 0.102339 \tabularnewline
254 & 0.860093 & 0.279813 & 0.139907 \tabularnewline
255 & 0.82283 & 0.35434 & 0.17717 \tabularnewline
256 & 0.77833 & 0.44334 & 0.22167 \tabularnewline
257 & 0.790531 & 0.418938 & 0.209469 \tabularnewline
258 & 0.957068 & 0.0858636 & 0.0429318 \tabularnewline
259 & 0.984633 & 0.0307341 & 0.0153671 \tabularnewline
260 & 0.985038 & 0.0299232 & 0.0149616 \tabularnewline
261 & 0.981551 & 0.0368977 & 0.0184489 \tabularnewline
262 & 0.948743 & 0.102514 & 0.0512572 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263629&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]16[/C][C]0.137714[/C][C]0.275429[/C][C]0.862286[/C][/ROW]
[ROW][C]17[/C][C]0.219679[/C][C]0.439357[/C][C]0.780321[/C][/ROW]
[ROW][C]18[/C][C]0.164406[/C][C]0.328813[/C][C]0.835594[/C][/ROW]
[ROW][C]19[/C][C]0.090264[/C][C]0.180528[/C][C]0.909736[/C][/ROW]
[ROW][C]20[/C][C]0.0476324[/C][C]0.0952648[/C][C]0.952368[/C][/ROW]
[ROW][C]21[/C][C]0.0314499[/C][C]0.0628998[/C][C]0.96855[/C][/ROW]
[ROW][C]22[/C][C]0.0162424[/C][C]0.0324848[/C][C]0.983758[/C][/ROW]
[ROW][C]23[/C][C]0.0292331[/C][C]0.0584662[/C][C]0.970767[/C][/ROW]
[ROW][C]24[/C][C]0.0175863[/C][C]0.0351726[/C][C]0.982414[/C][/ROW]
[ROW][C]25[/C][C]0.00958879[/C][C]0.0191776[/C][C]0.990411[/C][/ROW]
[ROW][C]26[/C][C]0.0061045[/C][C]0.012209[/C][C]0.993895[/C][/ROW]
[ROW][C]27[/C][C]0.00314169[/C][C]0.00628338[/C][C]0.996858[/C][/ROW]
[ROW][C]28[/C][C]0.00237978[/C][C]0.00475956[/C][C]0.99762[/C][/ROW]
[ROW][C]29[/C][C]0.00117127[/C][C]0.00234254[/C][C]0.998829[/C][/ROW]
[ROW][C]30[/C][C]0.00166209[/C][C]0.00332418[/C][C]0.998338[/C][/ROW]
[ROW][C]31[/C][C]0.00142758[/C][C]0.00285516[/C][C]0.998572[/C][/ROW]
[ROW][C]32[/C][C]0.00200909[/C][C]0.00401819[/C][C]0.997991[/C][/ROW]
[ROW][C]33[/C][C]0.00132551[/C][C]0.00265102[/C][C]0.998674[/C][/ROW]
[ROW][C]34[/C][C]0.00107521[/C][C]0.00215042[/C][C]0.998925[/C][/ROW]
[ROW][C]35[/C][C]0.000793566[/C][C]0.00158713[/C][C]0.999206[/C][/ROW]
[ROW][C]36[/C][C]0.000699927[/C][C]0.00139985[/C][C]0.9993[/C][/ROW]
[ROW][C]37[/C][C]0.000378588[/C][C]0.000757176[/C][C]0.999621[/C][/ROW]
[ROW][C]38[/C][C]0.00175182[/C][C]0.00350364[/C][C]0.998248[/C][/ROW]
[ROW][C]39[/C][C]0.0057213[/C][C]0.0114426[/C][C]0.994279[/C][/ROW]
[ROW][C]40[/C][C]0.0038641[/C][C]0.00772819[/C][C]0.996136[/C][/ROW]
[ROW][C]41[/C][C]0.00574314[/C][C]0.0114863[/C][C]0.994257[/C][/ROW]
[ROW][C]42[/C][C]0.00472668[/C][C]0.00945336[/C][C]0.995273[/C][/ROW]
[ROW][C]43[/C][C]0.00660281[/C][C]0.0132056[/C][C]0.993397[/C][/ROW]
[ROW][C]44[/C][C]0.00457141[/C][C]0.00914282[/C][C]0.995429[/C][/ROW]
[ROW][C]45[/C][C]0.00755839[/C][C]0.0151168[/C][C]0.992442[/C][/ROW]
[ROW][C]46[/C][C]0.0058059[/C][C]0.0116118[/C][C]0.994194[/C][/ROW]
[ROW][C]47[/C][C]0.00564576[/C][C]0.0112915[/C][C]0.994354[/C][/ROW]
[ROW][C]48[/C][C]0.00447886[/C][C]0.00895771[/C][C]0.995521[/C][/ROW]
[ROW][C]49[/C][C]0.00526323[/C][C]0.0105265[/C][C]0.994737[/C][/ROW]
[ROW][C]50[/C][C]0.0100869[/C][C]0.0201738[/C][C]0.989913[/C][/ROW]
[ROW][C]51[/C][C]0.00960236[/C][C]0.0192047[/C][C]0.990398[/C][/ROW]
[ROW][C]52[/C][C]0.00969289[/C][C]0.0193858[/C][C]0.990307[/C][/ROW]
[ROW][C]53[/C][C]0.0108376[/C][C]0.0216753[/C][C]0.989162[/C][/ROW]
[ROW][C]54[/C][C]0.0187547[/C][C]0.0375094[/C][C]0.981245[/C][/ROW]
[ROW][C]55[/C][C]0.0433348[/C][C]0.0866695[/C][C]0.956665[/C][/ROW]
[ROW][C]56[/C][C]0.0357278[/C][C]0.0714556[/C][C]0.964272[/C][/ROW]
[ROW][C]57[/C][C]0.106995[/C][C]0.213989[/C][C]0.893005[/C][/ROW]
[ROW][C]58[/C][C]0.0951757[/C][C]0.190351[/C][C]0.904824[/C][/ROW]
[ROW][C]59[/C][C]0.0776807[/C][C]0.155361[/C][C]0.922319[/C][/ROW]
[ROW][C]60[/C][C]0.0813116[/C][C]0.162623[/C][C]0.918688[/C][/ROW]
[ROW][C]61[/C][C]0.0939777[/C][C]0.187955[/C][C]0.906022[/C][/ROW]
[ROW][C]62[/C][C]0.0791253[/C][C]0.158251[/C][C]0.920875[/C][/ROW]
[ROW][C]63[/C][C]0.187579[/C][C]0.375158[/C][C]0.812421[/C][/ROW]
[ROW][C]64[/C][C]0.225434[/C][C]0.450868[/C][C]0.774566[/C][/ROW]
[ROW][C]65[/C][C]0.238463[/C][C]0.476925[/C][C]0.761537[/C][/ROW]
[ROW][C]66[/C][C]0.214751[/C][C]0.429501[/C][C]0.785249[/C][/ROW]
[ROW][C]67[/C][C]0.217629[/C][C]0.435258[/C][C]0.782371[/C][/ROW]
[ROW][C]68[/C][C]0.201283[/C][C]0.402566[/C][C]0.798717[/C][/ROW]
[ROW][C]69[/C][C]0.211053[/C][C]0.422106[/C][C]0.788947[/C][/ROW]
[ROW][C]70[/C][C]0.190394[/C][C]0.380788[/C][C]0.809606[/C][/ROW]
[ROW][C]71[/C][C]0.179866[/C][C]0.359733[/C][C]0.820134[/C][/ROW]
[ROW][C]72[/C][C]0.15979[/C][C]0.319579[/C][C]0.84021[/C][/ROW]
[ROW][C]73[/C][C]0.148731[/C][C]0.297463[/C][C]0.851269[/C][/ROW]
[ROW][C]74[/C][C]0.16214[/C][C]0.324281[/C][C]0.83786[/C][/ROW]
[ROW][C]75[/C][C]0.14391[/C][C]0.28782[/C][C]0.85609[/C][/ROW]
[ROW][C]76[/C][C]0.129907[/C][C]0.259814[/C][C]0.870093[/C][/ROW]
[ROW][C]77[/C][C]0.112937[/C][C]0.225874[/C][C]0.887063[/C][/ROW]
[ROW][C]78[/C][C]0.118086[/C][C]0.236172[/C][C]0.881914[/C][/ROW]
[ROW][C]79[/C][C]0.0998854[/C][C]0.199771[/C][C]0.900115[/C][/ROW]
[ROW][C]80[/C][C]0.120266[/C][C]0.240532[/C][C]0.879734[/C][/ROW]
[ROW][C]81[/C][C]0.102833[/C][C]0.205666[/C][C]0.897167[/C][/ROW]
[ROW][C]82[/C][C]0.122715[/C][C]0.24543[/C][C]0.877285[/C][/ROW]
[ROW][C]83[/C][C]0.105445[/C][C]0.21089[/C][C]0.894555[/C][/ROW]
[ROW][C]84[/C][C]0.18842[/C][C]0.37684[/C][C]0.81158[/C][/ROW]
[ROW][C]85[/C][C]0.171896[/C][C]0.343791[/C][C]0.828104[/C][/ROW]
[ROW][C]86[/C][C]0.154031[/C][C]0.308063[/C][C]0.845969[/C][/ROW]
[ROW][C]87[/C][C]0.139334[/C][C]0.278668[/C][C]0.860666[/C][/ROW]
[ROW][C]88[/C][C]0.122926[/C][C]0.245852[/C][C]0.877074[/C][/ROW]
[ROW][C]89[/C][C]0.122181[/C][C]0.244362[/C][C]0.877819[/C][/ROW]
[ROW][C]90[/C][C]0.117819[/C][C]0.235639[/C][C]0.882181[/C][/ROW]
[ROW][C]91[/C][C]0.13711[/C][C]0.274219[/C][C]0.86289[/C][/ROW]
[ROW][C]92[/C][C]0.228348[/C][C]0.456696[/C][C]0.771652[/C][/ROW]
[ROW][C]93[/C][C]0.22423[/C][C]0.44846[/C][C]0.77577[/C][/ROW]
[ROW][C]94[/C][C]0.226336[/C][C]0.452672[/C][C]0.773664[/C][/ROW]
[ROW][C]95[/C][C]0.24246[/C][C]0.48492[/C][C]0.75754[/C][/ROW]
[ROW][C]96[/C][C]0.239288[/C][C]0.478576[/C][C]0.760712[/C][/ROW]
[ROW][C]97[/C][C]0.314277[/C][C]0.628554[/C][C]0.685723[/C][/ROW]
[ROW][C]98[/C][C]0.301675[/C][C]0.60335[/C][C]0.698325[/C][/ROW]
[ROW][C]99[/C][C]0.315069[/C][C]0.630138[/C][C]0.684931[/C][/ROW]
[ROW][C]100[/C][C]0.364856[/C][C]0.729711[/C][C]0.635144[/C][/ROW]
[ROW][C]101[/C][C]0.34665[/C][C]0.6933[/C][C]0.65335[/C][/ROW]
[ROW][C]102[/C][C]0.331562[/C][C]0.663125[/C][C]0.668438[/C][/ROW]
[ROW][C]103[/C][C]0.327809[/C][C]0.655618[/C][C]0.672191[/C][/ROW]
[ROW][C]104[/C][C]0.332351[/C][C]0.664701[/C][C]0.667649[/C][/ROW]
[ROW][C]105[/C][C]0.374945[/C][C]0.749889[/C][C]0.625055[/C][/ROW]
[ROW][C]106[/C][C]0.390551[/C][C]0.781103[/C][C]0.609449[/C][/ROW]
[ROW][C]107[/C][C]0.403823[/C][C]0.807646[/C][C]0.596177[/C][/ROW]
[ROW][C]108[/C][C]0.61877[/C][C]0.76246[/C][C]0.38123[/C][/ROW]
[ROW][C]109[/C][C]0.670593[/C][C]0.658814[/C][C]0.329407[/C][/ROW]
[ROW][C]110[/C][C]0.688566[/C][C]0.622869[/C][C]0.311434[/C][/ROW]
[ROW][C]111[/C][C]0.691367[/C][C]0.617266[/C][C]0.308633[/C][/ROW]
[ROW][C]112[/C][C]0.669328[/C][C]0.661345[/C][C]0.330672[/C][/ROW]
[ROW][C]113[/C][C]0.7498[/C][C]0.5004[/C][C]0.2502[/C][/ROW]
[ROW][C]114[/C][C]0.736653[/C][C]0.526694[/C][C]0.263347[/C][/ROW]
[ROW][C]115[/C][C]0.851811[/C][C]0.296377[/C][C]0.148189[/C][/ROW]
[ROW][C]116[/C][C]0.900803[/C][C]0.198394[/C][C]0.0991972[/C][/ROW]
[ROW][C]117[/C][C]0.889095[/C][C]0.221811[/C][C]0.110905[/C][/ROW]
[ROW][C]118[/C][C]0.920208[/C][C]0.159584[/C][C]0.0797919[/C][/ROW]
[ROW][C]119[/C][C]0.917618[/C][C]0.164763[/C][C]0.0823816[/C][/ROW]
[ROW][C]120[/C][C]0.928394[/C][C]0.143212[/C][C]0.0716061[/C][/ROW]
[ROW][C]121[/C][C]0.934282[/C][C]0.131437[/C][C]0.0657185[/C][/ROW]
[ROW][C]122[/C][C]0.934773[/C][C]0.130454[/C][C]0.0652268[/C][/ROW]
[ROW][C]123[/C][C]0.928728[/C][C]0.142545[/C][C]0.0712724[/C][/ROW]
[ROW][C]124[/C][C]0.95978[/C][C]0.0804406[/C][C]0.0402203[/C][/ROW]
[ROW][C]125[/C][C]0.962564[/C][C]0.0748714[/C][C]0.0374357[/C][/ROW]
[ROW][C]126[/C][C]0.956022[/C][C]0.0879551[/C][C]0.0439775[/C][/ROW]
[ROW][C]127[/C][C]0.961117[/C][C]0.0777656[/C][C]0.0388828[/C][/ROW]
[ROW][C]128[/C][C]0.956006[/C][C]0.0879887[/C][C]0.0439943[/C][/ROW]
[ROW][C]129[/C][C]0.957104[/C][C]0.0857927[/C][C]0.0428964[/C][/ROW]
[ROW][C]130[/C][C]0.954781[/C][C]0.090438[/C][C]0.045219[/C][/ROW]
[ROW][C]131[/C][C]0.955142[/C][C]0.0897166[/C][C]0.0448583[/C][/ROW]
[ROW][C]132[/C][C]0.952508[/C][C]0.0949835[/C][C]0.0474917[/C][/ROW]
[ROW][C]133[/C][C]0.960762[/C][C]0.0784761[/C][C]0.039238[/C][/ROW]
[ROW][C]134[/C][C]0.959283[/C][C]0.0814341[/C][C]0.040717[/C][/ROW]
[ROW][C]135[/C][C]0.951419[/C][C]0.097162[/C][C]0.048581[/C][/ROW]
[ROW][C]136[/C][C]0.943046[/C][C]0.113907[/C][C]0.0569537[/C][/ROW]
[ROW][C]137[/C][C]0.96088[/C][C]0.0782408[/C][C]0.0391204[/C][/ROW]
[ROW][C]138[/C][C]0.958146[/C][C]0.0837075[/C][C]0.0418538[/C][/ROW]
[ROW][C]139[/C][C]0.952577[/C][C]0.0948462[/C][C]0.0474231[/C][/ROW]
[ROW][C]140[/C][C]0.94361[/C][C]0.112779[/C][C]0.0563895[/C][/ROW]
[ROW][C]141[/C][C]0.933904[/C][C]0.132191[/C][C]0.0660956[/C][/ROW]
[ROW][C]142[/C][C]0.96768[/C][C]0.0646394[/C][C]0.0323197[/C][/ROW]
[ROW][C]143[/C][C]0.967246[/C][C]0.0655089[/C][C]0.0327544[/C][/ROW]
[ROW][C]144[/C][C]0.969228[/C][C]0.0615433[/C][C]0.0307716[/C][/ROW]
[ROW][C]145[/C][C]0.964281[/C][C]0.0714381[/C][C]0.0357191[/C][/ROW]
[ROW][C]146[/C][C]0.963516[/C][C]0.0729676[/C][C]0.0364838[/C][/ROW]
[ROW][C]147[/C][C]0.961023[/C][C]0.0779548[/C][C]0.0389774[/C][/ROW]
[ROW][C]148[/C][C]0.955269[/C][C]0.0894614[/C][C]0.0447307[/C][/ROW]
[ROW][C]149[/C][C]0.948944[/C][C]0.102113[/C][C]0.0510563[/C][/ROW]
[ROW][C]150[/C][C]0.946127[/C][C]0.107747[/C][C]0.0538734[/C][/ROW]
[ROW][C]151[/C][C]0.980808[/C][C]0.0383839[/C][C]0.0191919[/C][/ROW]
[ROW][C]152[/C][C]0.980756[/C][C]0.0384875[/C][C]0.0192437[/C][/ROW]
[ROW][C]153[/C][C]0.981505[/C][C]0.036989[/C][C]0.0184945[/C][/ROW]
[ROW][C]154[/C][C]0.977165[/C][C]0.0456698[/C][C]0.0228349[/C][/ROW]
[ROW][C]155[/C][C]0.977596[/C][C]0.0448075[/C][C]0.0224037[/C][/ROW]
[ROW][C]156[/C][C]0.973661[/C][C]0.0526773[/C][C]0.0263386[/C][/ROW]
[ROW][C]157[/C][C]0.972832[/C][C]0.0543362[/C][C]0.0271681[/C][/ROW]
[ROW][C]158[/C][C]0.967651[/C][C]0.0646981[/C][C]0.0323491[/C][/ROW]
[ROW][C]159[/C][C]0.969935[/C][C]0.06013[/C][C]0.030065[/C][/ROW]
[ROW][C]160[/C][C]0.965016[/C][C]0.069969[/C][C]0.0349845[/C][/ROW]
[ROW][C]161[/C][C]0.972309[/C][C]0.0553816[/C][C]0.0276908[/C][/ROW]
[ROW][C]162[/C][C]0.967572[/C][C]0.0648552[/C][C]0.0324276[/C][/ROW]
[ROW][C]163[/C][C]0.969449[/C][C]0.0611024[/C][C]0.0305512[/C][/ROW]
[ROW][C]164[/C][C]0.993618[/C][C]0.0127637[/C][C]0.00638184[/C][/ROW]
[ROW][C]165[/C][C]0.993482[/C][C]0.0130353[/C][C]0.00651763[/C][/ROW]
[ROW][C]166[/C][C]0.991943[/C][C]0.0161136[/C][C]0.00805682[/C][/ROW]
[ROW][C]167[/C][C]0.991196[/C][C]0.0176074[/C][C]0.00880369[/C][/ROW]
[ROW][C]168[/C][C]0.994331[/C][C]0.0113389[/C][C]0.00566947[/C][/ROW]
[ROW][C]169[/C][C]0.992691[/C][C]0.0146186[/C][C]0.00730932[/C][/ROW]
[ROW][C]170[/C][C]0.993598[/C][C]0.0128038[/C][C]0.00640191[/C][/ROW]
[ROW][C]171[/C][C]0.992608[/C][C]0.0147838[/C][C]0.00739189[/C][/ROW]
[ROW][C]172[/C][C]0.994337[/C][C]0.0113257[/C][C]0.00566286[/C][/ROW]
[ROW][C]173[/C][C]0.993494[/C][C]0.0130112[/C][C]0.00650558[/C][/ROW]
[ROW][C]174[/C][C]0.991587[/C][C]0.0168257[/C][C]0.00841287[/C][/ROW]
[ROW][C]175[/C][C]0.989201[/C][C]0.0215988[/C][C]0.0107994[/C][/ROW]
[ROW][C]176[/C][C]0.992932[/C][C]0.014136[/C][C]0.00706802[/C][/ROW]
[ROW][C]177[/C][C]0.991353[/C][C]0.0172945[/C][C]0.00864724[/C][/ROW]
[ROW][C]178[/C][C]0.991378[/C][C]0.0172435[/C][C]0.00862174[/C][/ROW]
[ROW][C]179[/C][C]0.989996[/C][C]0.020008[/C][C]0.010004[/C][/ROW]
[ROW][C]180[/C][C]0.993182[/C][C]0.0136366[/C][C]0.00681828[/C][/ROW]
[ROW][C]181[/C][C]0.993767[/C][C]0.0124667[/C][C]0.00623334[/C][/ROW]
[ROW][C]182[/C][C]0.994217[/C][C]0.0115663[/C][C]0.00578315[/C][/ROW]
[ROW][C]183[/C][C]0.993872[/C][C]0.0122561[/C][C]0.00612804[/C][/ROW]
[ROW][C]184[/C][C]0.992443[/C][C]0.0151134[/C][C]0.00755668[/C][/ROW]
[ROW][C]185[/C][C]0.991512[/C][C]0.016976[/C][C]0.00848801[/C][/ROW]
[ROW][C]186[/C][C]0.989274[/C][C]0.0214512[/C][C]0.0107256[/C][/ROW]
[ROW][C]187[/C][C]0.992457[/C][C]0.0150859[/C][C]0.00754295[/C][/ROW]
[ROW][C]188[/C][C]0.991801[/C][C]0.0163983[/C][C]0.00819914[/C][/ROW]
[ROW][C]189[/C][C]0.990636[/C][C]0.0187277[/C][C]0.00936386[/C][/ROW]
[ROW][C]190[/C][C]0.988405[/C][C]0.02319[/C][C]0.011595[/C][/ROW]
[ROW][C]191[/C][C]0.985961[/C][C]0.0280789[/C][C]0.0140395[/C][/ROW]
[ROW][C]192[/C][C]0.985142[/C][C]0.0297152[/C][C]0.0148576[/C][/ROW]
[ROW][C]193[/C][C]0.982877[/C][C]0.0342452[/C][C]0.0171226[/C][/ROW]
[ROW][C]194[/C][C]0.988519[/C][C]0.022963[/C][C]0.0114815[/C][/ROW]
[ROW][C]195[/C][C]0.985277[/C][C]0.0294462[/C][C]0.0147231[/C][/ROW]
[ROW][C]196[/C][C]0.984646[/C][C]0.0307086[/C][C]0.0153543[/C][/ROW]
[ROW][C]197[/C][C]0.987525[/C][C]0.0249507[/C][C]0.0124753[/C][/ROW]
[ROW][C]198[/C][C]0.983904[/C][C]0.0321922[/C][C]0.0160961[/C][/ROW]
[ROW][C]199[/C][C]0.9818[/C][C]0.0363993[/C][C]0.0181997[/C][/ROW]
[ROW][C]200[/C][C]0.979111[/C][C]0.0417775[/C][C]0.0208887[/C][/ROW]
[ROW][C]201[/C][C]0.973254[/C][C]0.0534916[/C][C]0.0267458[/C][/ROW]
[ROW][C]202[/C][C]0.968426[/C][C]0.0631479[/C][C]0.0315739[/C][/ROW]
[ROW][C]203[/C][C]0.971218[/C][C]0.0575648[/C][C]0.0287824[/C][/ROW]
[ROW][C]204[/C][C]0.963689[/C][C]0.0726218[/C][C]0.0363109[/C][/ROW]
[ROW][C]205[/C][C]0.954229[/C][C]0.0915418[/C][C]0.0457709[/C][/ROW]
[ROW][C]206[/C][C]0.960323[/C][C]0.0793542[/C][C]0.0396771[/C][/ROW]
[ROW][C]207[/C][C]0.95217[/C][C]0.0956601[/C][C]0.04783[/C][/ROW]
[ROW][C]208[/C][C]0.946218[/C][C]0.107564[/C][C]0.0537819[/C][/ROW]
[ROW][C]209[/C][C]0.942767[/C][C]0.114467[/C][C]0.0572334[/C][/ROW]
[ROW][C]210[/C][C]0.938975[/C][C]0.12205[/C][C]0.0610252[/C][/ROW]
[ROW][C]211[/C][C]0.928335[/C][C]0.14333[/C][C]0.0716649[/C][/ROW]
[ROW][C]212[/C][C]0.915511[/C][C]0.168978[/C][C]0.0844888[/C][/ROW]
[ROW][C]213[/C][C]0.940447[/C][C]0.119107[/C][C]0.0595533[/C][/ROW]
[ROW][C]214[/C][C]0.935098[/C][C]0.129803[/C][C]0.0649017[/C][/ROW]
[ROW][C]215[/C][C]0.927955[/C][C]0.144089[/C][C]0.0720446[/C][/ROW]
[ROW][C]216[/C][C]0.910695[/C][C]0.178609[/C][C]0.0893047[/C][/ROW]
[ROW][C]217[/C][C]0.918451[/C][C]0.163097[/C][C]0.0815485[/C][/ROW]
[ROW][C]218[/C][C]0.912595[/C][C]0.17481[/C][C]0.0874049[/C][/ROW]
[ROW][C]219[/C][C]0.892307[/C][C]0.215386[/C][C]0.107693[/C][/ROW]
[ROW][C]220[/C][C]0.87119[/C][C]0.257619[/C][C]0.12881[/C][/ROW]
[ROW][C]221[/C][C]0.855141[/C][C]0.289719[/C][C]0.144859[/C][/ROW]
[ROW][C]222[/C][C]0.8749[/C][C]0.250199[/C][C]0.1251[/C][/ROW]
[ROW][C]223[/C][C]0.852139[/C][C]0.295723[/C][C]0.147861[/C][/ROW]
[ROW][C]224[/C][C]0.885961[/C][C]0.228077[/C][C]0.114039[/C][/ROW]
[ROW][C]225[/C][C]0.873299[/C][C]0.253402[/C][C]0.126701[/C][/ROW]
[ROW][C]226[/C][C]0.899566[/C][C]0.200869[/C][C]0.100434[/C][/ROW]
[ROW][C]227[/C][C]0.915769[/C][C]0.168462[/C][C]0.0842311[/C][/ROW]
[ROW][C]228[/C][C]0.922352[/C][C]0.155295[/C][C]0.0776475[/C][/ROW]
[ROW][C]229[/C][C]0.92594[/C][C]0.14812[/C][C]0.07406[/C][/ROW]
[ROW][C]230[/C][C]0.937493[/C][C]0.125013[/C][C]0.0625067[/C][/ROW]
[ROW][C]231[/C][C]0.939464[/C][C]0.121072[/C][C]0.0605361[/C][/ROW]
[ROW][C]232[/C][C]0.923368[/C][C]0.153264[/C][C]0.0766318[/C][/ROW]
[ROW][C]233[/C][C]0.917442[/C][C]0.165116[/C][C]0.0825579[/C][/ROW]
[ROW][C]234[/C][C]0.895266[/C][C]0.209468[/C][C]0.104734[/C][/ROW]
[ROW][C]235[/C][C]0.866876[/C][C]0.266248[/C][C]0.133124[/C][/ROW]
[ROW][C]236[/C][C]0.967632[/C][C]0.064736[/C][C]0.032368[/C][/ROW]
[ROW][C]237[/C][C]0.962199[/C][C]0.0756025[/C][C]0.0378012[/C][/ROW]
[ROW][C]238[/C][C]0.954748[/C][C]0.0905049[/C][C]0.0452524[/C][/ROW]
[ROW][C]239[/C][C]0.939908[/C][C]0.120184[/C][C]0.0600918[/C][/ROW]
[ROW][C]240[/C][C]0.921416[/C][C]0.157169[/C][C]0.0785843[/C][/ROW]
[ROW][C]241[/C][C]0.919599[/C][C]0.160803[/C][C]0.0804015[/C][/ROW]
[ROW][C]242[/C][C]0.897816[/C][C]0.204368[/C][C]0.102184[/C][/ROW]
[ROW][C]243[/C][C]0.891214[/C][C]0.217573[/C][C]0.108786[/C][/ROW]
[ROW][C]244[/C][C]0.86181[/C][C]0.276379[/C][C]0.13819[/C][/ROW]
[ROW][C]245[/C][C]0.834747[/C][C]0.330506[/C][C]0.165253[/C][/ROW]
[ROW][C]246[/C][C]0.792421[/C][C]0.415159[/C][C]0.207579[/C][/ROW]
[ROW][C]247[/C][C]0.789565[/C][C]0.420871[/C][C]0.210435[/C][/ROW]
[ROW][C]248[/C][C]0.90266[/C][C]0.19468[/C][C]0.09734[/C][/ROW]
[ROW][C]249[/C][C]0.91666[/C][C]0.166681[/C][C]0.0833404[/C][/ROW]
[ROW][C]250[/C][C]0.892567[/C][C]0.214865[/C][C]0.107433[/C][/ROW]
[ROW][C]251[/C][C]0.887284[/C][C]0.225432[/C][C]0.112716[/C][/ROW]
[ROW][C]252[/C][C]0.852794[/C][C]0.294413[/C][C]0.147206[/C][/ROW]
[ROW][C]253[/C][C]0.897661[/C][C]0.204678[/C][C]0.102339[/C][/ROW]
[ROW][C]254[/C][C]0.860093[/C][C]0.279813[/C][C]0.139907[/C][/ROW]
[ROW][C]255[/C][C]0.82283[/C][C]0.35434[/C][C]0.17717[/C][/ROW]
[ROW][C]256[/C][C]0.77833[/C][C]0.44334[/C][C]0.22167[/C][/ROW]
[ROW][C]257[/C][C]0.790531[/C][C]0.418938[/C][C]0.209469[/C][/ROW]
[ROW][C]258[/C][C]0.957068[/C][C]0.0858636[/C][C]0.0429318[/C][/ROW]
[ROW][C]259[/C][C]0.984633[/C][C]0.0307341[/C][C]0.0153671[/C][/ROW]
[ROW][C]260[/C][C]0.985038[/C][C]0.0299232[/C][C]0.0149616[/C][/ROW]
[ROW][C]261[/C][C]0.981551[/C][C]0.0368977[/C][C]0.0184489[/C][/ROW]
[ROW][C]262[/C][C]0.948743[/C][C]0.102514[/C][C]0.0512572[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263629&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263629&T=5

As an alternative you can also use a QR Code:

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

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
16	0.137714	0.275429	0.862286
17	0.219679	0.439357	0.780321
18	0.164406	0.328813	0.835594
19	0.090264	0.180528	0.909736
20	0.0476324	0.0952648	0.952368
21	0.0314499	0.0628998	0.96855
22	0.0162424	0.0324848	0.983758
23	0.0292331	0.0584662	0.970767
24	0.0175863	0.0351726	0.982414
25	0.00958879	0.0191776	0.990411
26	0.0061045	0.012209	0.993895
27	0.00314169	0.00628338	0.996858
28	0.00237978	0.00475956	0.99762
29	0.00117127	0.00234254	0.998829
30	0.00166209	0.00332418	0.998338
31	0.00142758	0.00285516	0.998572
32	0.00200909	0.00401819	0.997991
33	0.00132551	0.00265102	0.998674
34	0.00107521	0.00215042	0.998925
35	0.000793566	0.00158713	0.999206
36	0.000699927	0.00139985	0.9993
37	0.000378588	0.000757176	0.999621
38	0.00175182	0.00350364	0.998248
39	0.0057213	0.0114426	0.994279
40	0.0038641	0.00772819	0.996136
41	0.00574314	0.0114863	0.994257
42	0.00472668	0.00945336	0.995273
43	0.00660281	0.0132056	0.993397
44	0.00457141	0.00914282	0.995429
45	0.00755839	0.0151168	0.992442
46	0.0058059	0.0116118	0.994194
47	0.00564576	0.0112915	0.994354
48	0.00447886	0.00895771	0.995521
49	0.00526323	0.0105265	0.994737
50	0.0100869	0.0201738	0.989913
51	0.00960236	0.0192047	0.990398
52	0.00969289	0.0193858	0.990307
53	0.0108376	0.0216753	0.989162
54	0.0187547	0.0375094	0.981245
55	0.0433348	0.0866695	0.956665
56	0.0357278	0.0714556	0.964272
57	0.106995	0.213989	0.893005
58	0.0951757	0.190351	0.904824
59	0.0776807	0.155361	0.922319
60	0.0813116	0.162623	0.918688
61	0.0939777	0.187955	0.906022
62	0.0791253	0.158251	0.920875
63	0.187579	0.375158	0.812421
64	0.225434	0.450868	0.774566
65	0.238463	0.476925	0.761537
66	0.214751	0.429501	0.785249
67	0.217629	0.435258	0.782371
68	0.201283	0.402566	0.798717
69	0.211053	0.422106	0.788947
70	0.190394	0.380788	0.809606
71	0.179866	0.359733	0.820134
72	0.15979	0.319579	0.84021
73	0.148731	0.297463	0.851269
74	0.16214	0.324281	0.83786
75	0.14391	0.28782	0.85609
76	0.129907	0.259814	0.870093
77	0.112937	0.225874	0.887063
78	0.118086	0.236172	0.881914
79	0.0998854	0.199771	0.900115
80	0.120266	0.240532	0.879734
81	0.102833	0.205666	0.897167
82	0.122715	0.24543	0.877285
83	0.105445	0.21089	0.894555
84	0.18842	0.37684	0.81158
85	0.171896	0.343791	0.828104
86	0.154031	0.308063	0.845969
87	0.139334	0.278668	0.860666
88	0.122926	0.245852	0.877074
89	0.122181	0.244362	0.877819
90	0.117819	0.235639	0.882181
91	0.13711	0.274219	0.86289
92	0.228348	0.456696	0.771652
93	0.22423	0.44846	0.77577
94	0.226336	0.452672	0.773664
95	0.24246	0.48492	0.75754
96	0.239288	0.478576	0.760712
97	0.314277	0.628554	0.685723
98	0.301675	0.60335	0.698325
99	0.315069	0.630138	0.684931
100	0.364856	0.729711	0.635144
101	0.34665	0.6933	0.65335
102	0.331562	0.663125	0.668438
103	0.327809	0.655618	0.672191
104	0.332351	0.664701	0.667649
105	0.374945	0.749889	0.625055
106	0.390551	0.781103	0.609449
107	0.403823	0.807646	0.596177
108	0.61877	0.76246	0.38123
109	0.670593	0.658814	0.329407
110	0.688566	0.622869	0.311434
111	0.691367	0.617266	0.308633
112	0.669328	0.661345	0.330672
113	0.7498	0.5004	0.2502
114	0.736653	0.526694	0.263347
115	0.851811	0.296377	0.148189
116	0.900803	0.198394	0.0991972
117	0.889095	0.221811	0.110905
118	0.920208	0.159584	0.0797919
119	0.917618	0.164763	0.0823816
120	0.928394	0.143212	0.0716061
121	0.934282	0.131437	0.0657185
122	0.934773	0.130454	0.0652268
123	0.928728	0.142545	0.0712724
124	0.95978	0.0804406	0.0402203
125	0.962564	0.0748714	0.0374357
126	0.956022	0.0879551	0.0439775
127	0.961117	0.0777656	0.0388828
128	0.956006	0.0879887	0.0439943
129	0.957104	0.0857927	0.0428964
130	0.954781	0.090438	0.045219
131	0.955142	0.0897166	0.0448583
132	0.952508	0.0949835	0.0474917
133	0.960762	0.0784761	0.039238
134	0.959283	0.0814341	0.040717
135	0.951419	0.097162	0.048581
136	0.943046	0.113907	0.0569537
137	0.96088	0.0782408	0.0391204
138	0.958146	0.0837075	0.0418538
139	0.952577	0.0948462	0.0474231
140	0.94361	0.112779	0.0563895
141	0.933904	0.132191	0.0660956
142	0.96768	0.0646394	0.0323197
143	0.967246	0.0655089	0.0327544
144	0.969228	0.0615433	0.0307716
145	0.964281	0.0714381	0.0357191
146	0.963516	0.0729676	0.0364838
147	0.961023	0.0779548	0.0389774
148	0.955269	0.0894614	0.0447307
149	0.948944	0.102113	0.0510563
150	0.946127	0.107747	0.0538734
151	0.980808	0.0383839	0.0191919
152	0.980756	0.0384875	0.0192437
153	0.981505	0.036989	0.0184945
154	0.977165	0.0456698	0.0228349
155	0.977596	0.0448075	0.0224037
156	0.973661	0.0526773	0.0263386
157	0.972832	0.0543362	0.0271681
158	0.967651	0.0646981	0.0323491
159	0.969935	0.06013	0.030065
160	0.965016	0.069969	0.0349845
161	0.972309	0.0553816	0.0276908
162	0.967572	0.0648552	0.0324276
163	0.969449	0.0611024	0.0305512
164	0.993618	0.0127637	0.00638184
165	0.993482	0.0130353	0.00651763
166	0.991943	0.0161136	0.00805682
167	0.991196	0.0176074	0.00880369
168	0.994331	0.0113389	0.00566947
169	0.992691	0.0146186	0.00730932
170	0.993598	0.0128038	0.00640191
171	0.992608	0.0147838	0.00739189
172	0.994337	0.0113257	0.00566286
173	0.993494	0.0130112	0.00650558
174	0.991587	0.0168257	0.00841287
175	0.989201	0.0215988	0.0107994
176	0.992932	0.014136	0.00706802
177	0.991353	0.0172945	0.00864724
178	0.991378	0.0172435	0.00862174
179	0.989996	0.020008	0.010004
180	0.993182	0.0136366	0.00681828
181	0.993767	0.0124667	0.00623334
182	0.994217	0.0115663	0.00578315
183	0.993872	0.0122561	0.00612804
184	0.992443	0.0151134	0.00755668
185	0.991512	0.016976	0.00848801
186	0.989274	0.0214512	0.0107256
187	0.992457	0.0150859	0.00754295
188	0.991801	0.0163983	0.00819914
189	0.990636	0.0187277	0.00936386
190	0.988405	0.02319	0.011595
191	0.985961	0.0280789	0.0140395
192	0.985142	0.0297152	0.0148576
193	0.982877	0.0342452	0.0171226
194	0.988519	0.022963	0.0114815
195	0.985277	0.0294462	0.0147231
196	0.984646	0.0307086	0.0153543
197	0.987525	0.0249507	0.0124753
198	0.983904	0.0321922	0.0160961
199	0.9818	0.0363993	0.0181997
200	0.979111	0.0417775	0.0208887
201	0.973254	0.0534916	0.0267458
202	0.968426	0.0631479	0.0315739
203	0.971218	0.0575648	0.0287824
204	0.963689	0.0726218	0.0363109
205	0.954229	0.0915418	0.0457709
206	0.960323	0.0793542	0.0396771
207	0.95217	0.0956601	0.04783
208	0.946218	0.107564	0.0537819
209	0.942767	0.114467	0.0572334
210	0.938975	0.12205	0.0610252
211	0.928335	0.14333	0.0716649
212	0.915511	0.168978	0.0844888
213	0.940447	0.119107	0.0595533
214	0.935098	0.129803	0.0649017
215	0.927955	0.144089	0.0720446
216	0.910695	0.178609	0.0893047
217	0.918451	0.163097	0.0815485
218	0.912595	0.17481	0.0874049
219	0.892307	0.215386	0.107693
220	0.87119	0.257619	0.12881
221	0.855141	0.289719	0.144859
222	0.8749	0.250199	0.1251
223	0.852139	0.295723	0.147861
224	0.885961	0.228077	0.114039
225	0.873299	0.253402	0.126701
226	0.899566	0.200869	0.100434
227	0.915769	0.168462	0.0842311
228	0.922352	0.155295	0.0776475
229	0.92594	0.14812	0.07406
230	0.937493	0.125013	0.0625067
231	0.939464	0.121072	0.0605361
232	0.923368	0.153264	0.0766318
233	0.917442	0.165116	0.0825579
234	0.895266	0.209468	0.104734
235	0.866876	0.266248	0.133124
236	0.967632	0.064736	0.032368
237	0.962199	0.0756025	0.0378012
238	0.954748	0.0905049	0.0452524
239	0.939908	0.120184	0.0600918
240	0.921416	0.157169	0.0785843
241	0.919599	0.160803	0.0804015
242	0.897816	0.204368	0.102184
243	0.891214	0.217573	0.108786
244	0.86181	0.276379	0.13819
245	0.834747	0.330506	0.165253
246	0.792421	0.415159	0.207579
247	0.789565	0.420871	0.210435
248	0.90266	0.19468	0.09734
249	0.91666	0.166681	0.0833404
250	0.892567	0.214865	0.107433
251	0.887284	0.225432	0.112716
252	0.852794	0.294413	0.147206
253	0.897661	0.204678	0.102339
254	0.860093	0.279813	0.139907
255	0.82283	0.35434	0.17717
256	0.77833	0.44334	0.22167
257	0.790531	0.418938	0.209469
258	0.957068	0.0858636	0.0429318
259	0.984633	0.0307341	0.0153671
260	0.985038	0.0299232	0.0149616
261	0.981551	0.0368977	0.0184489
262	0.948743	0.102514	0.0512572

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	16	0.0647773	NOK
5% type I error level	77	0.311741	NOK
10% type I error level	123	0.497976	NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 16 & 0.0647773 & NOK \tabularnewline
5% type I error level & 77 & 0.311741 & NOK \tabularnewline
10% type I error level & 123 & 0.497976 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263629&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]16[/C][C]0.0647773[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]77[/C][C]0.311741[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]123[/C][C]0.497976[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263629&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263629&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	16	0.0647773	NOK
5% type I error level	77	0.311741	NOK
10% type I error level	123	0.497976	NOK

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Figure 6

PNG link

Postscript link

PDF link

Figure 7

PNG link

Postscript link

PDF link

Figure 8

PNG link

Postscript link

PDF link

Figure 9

PNG link

Postscript link

PDF link

Figure 10

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 13 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 13 ; 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 <- '14'
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code