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Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Thu, 18 Dec 2014 16:03:42 +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/18/t1418918665a6xx1amvsvwafs6.htm/, Retrieved Fri, 17 May 2024 09:21:00 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=271106, Retrieved Fri, 17 May 2024 09:21:00 +0000

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Estimated Impact

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

-       [Multiple Regression] [Regression analysis ] [2014-12-18 16:03:42] [164fad6d182490e1bc62c0c9500aee6c] [Current]

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26	50	4	21	149	96	18	68	86	12,9
57	62	4	22	139	70	31	39	70	12,2
37	54	5	22	148	88	39	32	71	12,8
67	71	4	18	158	114	46	62	108	7,4
43	54	4	23	128	69	31	33	64	6,7
52	65	9	12	224	176	67	52	119	12,6
52	73	8	20	159	114	35	62	97	14,8
43	52	11	22	105	121	52	77	129	13,3
84	84	4	21	159	110	77	76	153	11,1
67	42	4	19	167	158	37	41	78	8,2
49	66	6	22	165	116	32	48	80	11,4
70	65	4	15	159	181	36	63	99	6,4
52	78	8	20	119	77	38	30	68	10,6
58	73	4	19	176	141	69	78	147	12
68	75	4	18	54	35	21	19	40	6,3
62	72	11	15	91	80	26	31	57	11,3
43	66	4	20	163	152	54	66	120	11,9
56	70	4	21	124	97	36	35	71	9,3
56	61	6	21	137	99	42	42	84	9,6
74	81	6	15	121	84	23	45	68	10
65	71	4	16	153	68	34	21	55	6,4
63	69	8	23	148	101	112	25	137	13,8
58	71	5	21	221	107	35	44	79	10,8
57	72	4	18	188	88	47	69	116	13,8
63	68	9	25	149	112	47	54	101	11,7
53	70	4	9	244	171	37	74	111	10,9
57	68	7	30	148	137	109	80	189	16,1
51	61	10	20	92	77	24	42	66	13,4
64	67	4	23	150	66	20	61	81	9,9
53	76	4	16	153	93	22	41	63	11,5
29	70	7	16	94	105	23	46	69	8,3
54	60	12	19	156	131	32	39	71	11,7
58	72	7	25	132	102	30	34	64	9
43	69	5	18	161	161	92	51	143	9,7
51	71	8	23	105	120	43	42	85	10,8
53	62	5	21	97	127	55	31	86	10,3
54	70	4	10	151	77	16	39	55	10,4
56	64	9	14	131	108	49	20	69	12,7
61	58	7	22	166	85	71	49	120	9,3
47	76	4	26	157	168	43	53	96	11,8
39	52	4	23	111	48	29	31	60	5,9
48	59	4	23	145	152	56	39	95	11,4
50	68	4	24	162	75	46	54	100	13
35	76	4	24	163	107	19	49	68	10,8
30	65	7	18	59	62	23	34	57	12,3
68	67	4	23	187	121	59	46	105	11,3
49	59	7	15	109	124	30	55	85	11,8
61	69	4	19	90	72	61	42	103	7,9
67	76	4	16	105	40	7	50	57	12,7
47	63	4	25	83	58	38	13	51	12,3
56	75	4	23	116	97	32	37	69	11,6
50	63	8	17	42	88	16	25	41	6,7
43	60	4	19	148	126	19	30	49	10,9
67	73	4	21	155	104	22	28	50	12,1
62	63	4	18	125	148	48	45	93	13,3
57	70	4	27	116	146	23	35	58	10,1
41	75	7	21	128	80	26	28	54	5,7
54	66	12	13	138	97	33	41	74	14,3
45	63	4	8	49	25	9	6	15	8
48	63	4	29	96	99	24	45	69	13,3
61	64	4	28	164	118	34	73	107	9,3
56	70	5	23	162	58	48	17	65	12,5
41	75	15	21	99	63	18	40	58	7,6
43	61	5	19	202	139	43	64	107	15,9
53	60	10	19	186	50	33	37	70	9,2
44	62	9	20	66	60	28	25	53	9,1
66	73	8	18	183	152	71	65	136	11,1
58	61	4	19	214	142	26	100	126	13
46	66	5	17	188	94	67	28	95	14,5
37	64	4	19	104	66	34	35	69	12,2
51	59	9	25	177	127	80	56	136	12,3
51	64	4	19	126	67	29	29	58	11,4
56	60	10	22	76	90	16	43	59	8,8
66	56	4	23	99	75	59	59	118	14,6
37	78	4	14	139	128	32	50	82	12,6
42	67	7	16	162	146	43	59	102	13
38	59	5	24	108	69	38	27	65	12,6
66	66	4	20	159	186	29	61	90	13,2
34	68	4	12	74	81	36	28	64	9,9
53	71	4	24	110	85	32	51	83	7,7
49	66	4	22	96	54	35	35	70	10,5
55	73	4	12	116	46	21	29	50	13,4
49	72	4	22	87	106	29	48	77	10,9
59	71	6	20	97	34	12	25	37	4,3
40	59	10	10	127	60	37	44	81	10,3
58	64	7	23	106	95	37	64	101	11,8
60	66	4	17	80	57	47	32	79	11,2
63	78	4	22	74	62	51	20	71	11,4
56	68	7	24	91	36	32	28	60	8,6
54	73	4	18	133	56	21	34	55	13,2
52	62	8	21	74	54	13	31	44	12,6
34	65	11	20	114	64	14	26	40	5,6
69	68	6	20	140	76	-2	58	56	9,9
32	65	14	22	95	98	20	23	43	8,8
48	60	5	19	98	88	24	21	45	7,7
67	71	4	20	121	35	11	21	32	9
58	65	8	26	126	102	23	33	56	7,3
57	68	9	23	98	61	24	16	40	11,4
42	64	4	24	95	80	14	20	34	13,6
64	74	4	21	110	49	52	37	89	7,9
58	69	5	21	70	78	15	35	50	10,7
66	76	4	19	102	90	23	33	56	10,3
26	68	5	8	86	45	19	27	46	8,3
61	72	4	17	130	55	35	41	76	9,6
52	67	4	20	96	96	24	40	64	14,2
51	63	7	11	102	43	39	35	74	8,5
55	59	10	8	100	52	29	28	57	13,5
50	73	4	15	94	60	13	32	45	4,9
60	66	5	18	52	54	8	22	30	6,4
56	62	4	18	98	51	18	44	62	9,6
63	69	4	19	118	51	24	27	51	11,6
61	66	4	19	99	38	19	17	36	11,1
52	51	6	23	48	41	23	12	34	4,35
16	56	4	22	50	146	16	45	61	12,7
46	67	8	21	150	182	33	37	70	18,1
56	69	5	25	154	192	32	37	69	17,85
52	57	4	30	109	263	37	108	145	16,6
55	56	17	17	68	35	14	10	23	12,6
50	55	4	27	194	439	52	68	120	17,1
59	63	4	23	158	214	75	72	147	19,1
60	67	8	23	159	341	72	143	215	16,1
52	65	4	18	67	58	15	9	24	13,35
44	47	7	18	147	292	29	55	84	18,4
67	76	4	23	39	85	13	17	30	14,7
52	64	4	19	100	200	40	37	77	10,6
55	68	5	15	111	158	19	27	46	12,6
37	64	7	20	138	199	24	37	61	16,2
54	65	4	16	101	297	121	58	178	13,6
72	71	4	24	131	227	93	66	160	18,9
51	63	7	25	101	108	36	21	57	14,1
48	60	11	25	114	86	23	19	42	14,5
60	68	7	19	165	302	85	78	163	16,15
50	72	4	19	114	148	41	35	75	14,75
63	70	4	16	111	178	46	48	94	14,8
33	61	4	19	75	120	18	27	45	12,45
67	61	4	19	82	207	35	43	78	12,65
46	62	4	23	121	157	17	30	47	17,35
54	71	4	21	32	128	4	25	29	8,6
59	71	6	22	150	296	28	69	97	18,4
61	51	8	19	117	323	44	72	116	16,1
33	56	23	20	71	79	10	23	32	11,6
47	70	4	20	165	70	38	13	50	17,75
69	73	8	3	154	146	57	61	118	15,25
52	76	6	23	126	246	23	43	66	17,65
55	68	4	23	149	196	36	51	86	16,35
41	48	7	20	145	199	22	67	89	17,65
73	52	4	15	120	127	40	36	76	13,6
52	60	4	16	109	153	31	44	75	14,35
50	59	4	7	132	299	11	45	57	14,75
51	57	10	24	172	228	38	34	72	18,25
60	79	6	17	169	190	24	36	60	9,9
56	60	5	24	114	180	37	72	109	16
56	60	5	24	156	212	37	39	76	18,25
29	59	4	19	172	269	22	43	65	16,85
66	62	4	25	68	130	15	25	40	14,6
66	59	5	20	89	179	2	56	58	13,85
73	61	5	28	167	243	43	80	123	18,95
55	71	5	23	113	190	31	40	71	15,6
64	57	5	27	115	299	29	73	102	14,85
40	66	4	18	78	121	45	34	80	11,75
46	63	6	28	118	137	25	72	97	18,45
58	69	4	21	87	305	4	42	46	15,9
43	58	4	19	173	157	31	61	93	17,1
61	59	4	23	2	96	-4	23	19	16,1
51	48	9	27	162	183	66	74	140	19,9
50	66	18	22	49	52	61	16	78	10,95
52	73	6	28	122	238	32	66	98	18,45
54	67	5	25	96	40	31	9	40	15,1
66	61	4	21	100	226	39	41	80	15
61	68	11	22	82	190	19	57	76	11,35
80	75	4	28	100	214	31	48	79	15,95
51	62	10	20	115	145	36	51	87	18,1
56	69	6	29	141	119	42	53	95	14,6
56	58	8	25	165	222	21	29	49	15,4
56	60	8	25	165	222	21	29	49	15,4
53	74	6	20	110	159	25	55	80	17,6
47	55	8	20	118	165	32	54	86	13,35
25	62	4	16	158	249	26	43	69	19,1
47	63	4	20	146	125	28	51	79	15,35
46	69	9	20	49	122	32	20	52	7,6
50	58	9	23	90	186	41	79	120	13,4
39	58	5	18	121	148	29	39	69	13,9
51	68	4	25	155	274	33	61	94	19,1
58	72	4	18	104	172	17	55	72	15,25
35	62	15	19	147	84	13	30	43	12,9
58	62	10	25	110	168	32	55	87	16,1
60	65	9	25	108	102	30	22	52	17,35
62	69	7	25	113	106	34	37	71	13,15
63	66	9	24	115	2	59	2	61	12,15
53	72	6	19	61	139	13	38	51	12,6
46	62	4	26	60	95	23	27	50	10,35
67	75	7	10	109	130	10	56	67	15,4
59	58	4	17	68	72	5	25	30	9,6
64	66	7	13	111	141	31	39	70	18,2
38	55	4	17	77	113	19	33	52	13,6
50	47	15	30	73	206	32	43	75	14,85
48	72	4	25	151	268	30	57	87	14,75
48	62	9	4	89	175	25	43	69	14,1
47	64	4	16	78	77	48	23	72	14,9
66	64	4	21	110	125	35	44	79	16,25
47	19	28	23	220	255	67	54	121	19,25
63	50	4	22	65	111	15	28	43	13,6
58	68	4	17	141	132	22	36	58	13,6
44	70	4	20	117	211	18	39	57	15,65
51	79	5	20	122	92	33	16	50	12,75
43	69	4	22	63	76	46	23	69	14,6
55	71	4	16	44	171	24	40	64	9,85
38	48	12	23	52	83	14	24	38	12,65
45	73	4	0	131	266	12	78	90	19,2
50	74	6	18	101	186	38	57	96	16,6
54	66	6	25	42	50	12	37	49	11,2
57	71	5	23	152	117	28	27	56	15,25
60	74	4	12	107	219	41	61	102	11,9
55	78	4	18	77	246	12	27	40	13,2
56	75	4	24	154	279	31	69	100	16,35
49	53	10	11	103	148	33	34	67	12,4
37	60	7	18	96	137	34	44	78	15,85
59	70	4	23	175	181	21	34	55	18,15
46	69	7	24	57	98	20	39	59	11,15
51	65	4	29	112	226	44	51	96	15,65
58	78	4	18	143	234	52	34	86	17,75
64	78	12	15	49	138	7	31	38	7,65
53	59	5	29	110	85	29	13	43	12,35
48	72	8	16	131	66	11	12	23	15,6
51	70	6	19	167	236	26	51	77	19,3
47	63	17	22	56	106	24	24	48	15,2
59	63	4	16	137	135	7	19	26	17,1
62	71	5	23	86	122	60	30	91	15,6
62	74	4	23	121	218	13	81	94	18,4
51	67	5	19	149	199	20	42	62	19,05
64	66	5	4	168	112	52	22	74	18,55
52	62	6	20	140	278	28	85	114	19,1
67	80	4	24	88	94	25	27	52	13,1
50	73	4	20	168	113	39	25	64	12,85
54	67	4	4	94	84	9	22	31	9,5
58	61	6	24	51	86	19	19	38	4,5
56	73	8	22	48	62	13	14	27	11,85
63	74	10	16	145	222	60	45	105	13,6
31	32	4	3	66	167	19	45	64	11,7
65	69	5	15	85	82	34	28	62	12,4
71	69	4	24	109	207	14	51	65	13,35
50	84	4	17	63	184	17	41	58	11,4
57	64	4	20	102	83	45	31	76	14,9
47	58	16	27	162	183	66	74	140	19,9
47	59	7	26	86	89	48	19	68	11,2
57	78	4	23	114	225	29	51	80	14,6
43	57	4	17	164	237	-2	73	71	17,6
41	60	14	20	119	102	51	24	76	14,05
63	68	5	22	126	221	2	61	63	16,1
63	68	5	19	132	128	24	23	46	13,35
56	73	5	24	142	91	40	14	53	11,85
51	69	5	19	83	198	20	54	74	11,95
50	67	7	23	94	204	19	51	70	14,75
22	60	19	15	81	158	16	62	78	15,15
41	65	16	27	166	138	20	36	56	13,2
59	66	4	26	110	226	40	59	100	16,85
56	74	4	22	64	44	27	24	51	7,85
66	81	7	22	93	196	25	26	52	7,7
53	72	9	18	104	83	49	54	102	12,6
42	55	5	15	105	79	39	39	78	7,85
52	49	14	22	49	52	61	16	78	10,95
54	74	4	27	88	105	19	36	55	12,35
44	53	16	10	95	116	67	31	98	9,95
62	64	10	20	102	83	45	31	76	14,9
53	65	5	17	99	196	30	42	73	16,65
50	57	6	23	63	153	8	39	47	13,4
36	51	4	19	76	157	19	25	45	13,95
76	80	4	13	109	75	52	31	83	15,7
66	67	4	27	117	106	22	38	60	16,85
62	70	5	23	57	58	17	31	48	10,95
59	74	4	16	120	75	33	17	50	15,35
47	75	4	25	73	74	34	22	56	12,2
55	70	5	2	91	185	22	55	77	15,1
58	69	4	26	108	265	30	62	91	17,75
60	65	4	20	105	131	25	51	76	15,2
44	55	5	23	117	139	38	30	68	14,6
57	71	8	22	119	196	26	49	74	16,65
45	65	15	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	'George Udny Yule' @ yule.wessa.net
R Framework error message	The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 11 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
R Framework error message & The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271106&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271106&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271106&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	'George Udny Yule' @ yule.wessa.net
R Framework error message	The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'.

Multiple Linear Regression - Estimated Regression Equation
TOT [t] = + 8.25603 + 0.00261901AMS.I[t] -0.01975AMS.E[t] + 0.029883AMS.A[t] + 0.0491566NUMERACYTOT[t] + 0.0119326LFM[t] + 0.0271545B[t] -0.434853PRH[t] -0.443113CH[t] + 0.435175H[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT
[t] =  +  8.25603 +  0.00261901AMS.I[t] -0.01975AMS.E[t] +  0.029883AMS.A[t] +  0.0491566NUMERACYTOT[t] +  0.0119326LFM[t] +  0.0271545B[t] -0.434853PRH[t] -0.443113CH[t] +  0.435175H[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271106&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT
[t] =  +  8.25603 +  0.00261901AMS.I[t] -0.01975AMS.E[t] +  0.029883AMS.A[t] +  0.0491566NUMERACYTOT[t] +  0.0119326LFM[t] +  0.0271545B[t] -0.434853PRH[t] -0.443113CH[t] +  0.435175H[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271106&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271106&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] = + 8.25603 + 0.00261901AMS.I[t] -0.01975AMS.E[t] + 0.029883AMS.A[t] + 0.0491566NUMERACYTOT[t] + 0.0119326LFM[t] + 0.0271545B[t] -0.434853PRH[t] -0.443113CH[t] + 0.435175H[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)	8.25603	1.83504	4.499	1.01776e-05	5.08881e-06
AMS.I	0.00261901	0.0174857	0.1498	0.881051	0.440525
AMS.E	-0.01975	0.0225404	-0.8762	0.381705	0.190852
AMS.A	0.029883	0.051071	0.5851	0.558954	0.279477
NUMERACYTOT	0.0491566	0.0324373	1.515	0.130842	0.0654208
LFM	0.0119326	0.00487827	2.446	0.015086	0.007543
B	0.0271545	0.00294355	9.225	8.76991e-18	4.38496e-18
PRH	-0.434853	0.450447	-0.9654	0.335224	0.167612
CH	-0.443113	0.449602	-0.9856	0.325235	0.162618
H	0.435175	0.449424	0.9683	0.333769	0.166885

\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) & 8.25603 & 1.83504 & 4.499 & 1.01776e-05 & 5.08881e-06 \tabularnewline
AMS.I & 0.00261901 & 0.0174857 & 0.1498 & 0.881051 & 0.440525 \tabularnewline
AMS.E & -0.01975 & 0.0225404 & -0.8762 & 0.381705 & 0.190852 \tabularnewline
AMS.A & 0.029883 & 0.051071 & 0.5851 & 0.558954 & 0.279477 \tabularnewline
NUMERACYTOT & 0.0491566 & 0.0324373 & 1.515 & 0.130842 & 0.0654208 \tabularnewline
LFM & 0.0119326 & 0.00487827 & 2.446 & 0.015086 & 0.007543 \tabularnewline
B & 0.0271545 & 0.00294355 & 9.225 & 8.76991e-18 & 4.38496e-18 \tabularnewline
PRH & -0.434853 & 0.450447 & -0.9654 & 0.335224 & 0.167612 \tabularnewline
CH & -0.443113 & 0.449602 & -0.9856 & 0.325235 & 0.162618 \tabularnewline
H & 0.435175 & 0.449424 & 0.9683 & 0.333769 & 0.166885 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271106&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]8.25603[/C][C]1.83504[/C][C]4.499[/C][C]1.01776e-05[/C][C]5.08881e-06[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.00261901[/C][C]0.0174857[/C][C]0.1498[/C][C]0.881051[/C][C]0.440525[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.01975[/C][C]0.0225404[/C][C]-0.8762[/C][C]0.381705[/C][C]0.190852[/C][/ROW]
[ROW][C]AMS.A[/C][C]0.029883[/C][C]0.051071[/C][C]0.5851[/C][C]0.558954[/C][C]0.279477[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0491566[/C][C]0.0324373[/C][C]1.515[/C][C]0.130842[/C][C]0.0654208[/C][/ROW]
[ROW][C]LFM[/C][C]0.0119326[/C][C]0.00487827[/C][C]2.446[/C][C]0.015086[/C][C]0.007543[/C][/ROW]
[ROW][C]B[/C][C]0.0271545[/C][C]0.00294355[/C][C]9.225[/C][C]8.76991e-18[/C][C]4.38496e-18[/C][/ROW]
[ROW][C]PRH[/C][C]-0.434853[/C][C]0.450447[/C][C]-0.9654[/C][C]0.335224[/C][C]0.167612[/C][/ROW]
[ROW][C]CH[/C][C]-0.443113[/C][C]0.449602[/C][C]-0.9856[/C][C]0.325235[/C][C]0.162618[/C][/ROW]
[ROW][C]H[/C][C]0.435175[/C][C]0.449424[/C][C]0.9683[/C][C]0.333769[/C][C]0.166885[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271106&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271106&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)	8.25603	1.83504	4.499	1.01776e-05	5.08881e-06
AMS.I	0.00261901	0.0174857	0.1498	0.881051	0.440525
AMS.E	-0.01975	0.0225404	-0.8762	0.381705	0.190852
AMS.A	0.029883	0.051071	0.5851	0.558954	0.279477
NUMERACYTOT	0.0491566	0.0324373	1.515	0.130842	0.0654208
LFM	0.0119326	0.00487827	2.446	0.015086	0.007543
B	0.0271545	0.00294355	9.225	8.76991e-18	4.38496e-18
PRH	-0.434853	0.450447	-0.9654	0.335224	0.167612
CH	-0.443113	0.449602	-0.9856	0.325235	0.162618
H	0.435175	0.449424	0.9683	0.333769	0.166885

Multiple Linear Regression - Regression Statistics
Multiple R	0.616343
R-squared	0.379878
Adjusted R-squared	0.359053
F-TEST (value)	18.2415
F-TEST (DF numerator)	9
F-TEST (DF denominator)	268
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.71749
Sum Squared Residuals	1979.12

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.616343 \tabularnewline
R-squared & 0.379878 \tabularnewline
Adjusted R-squared & 0.359053 \tabularnewline
F-TEST (value) & 18.2415 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 268 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.71749 \tabularnewline
Sum Squared Residuals & 1979.12 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271106&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.616343[/C][/ROW]
[ROW][C]R-squared[/C][C]0.379878[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.359053[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]18.2415[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]268[/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]2.71749[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1979.12[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271106&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271106&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	0.616343
R-squared	0.379878
Adjusted R-squared	0.359053
F-TEST (value)	18.2415
F-TEST (DF numerator)	9
F-TEST (DF denominator)	268
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.71749
Sum Squared Residuals	1979.12

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	12.3393	0.560716
2	12.2	11.6417	0.558339
3	12.8	12.4315	0.368524
4	7.4	12.5373	-5.13726
5	6.7	11.7014	-5.00136
6	12.6	15.0282	-2.42822
7	14.8	12.6847	2.11529
8	13.3	12.696	0.604007
9	11.1	12.2747	-1.17469
10	8.2	14.6251	-6.42514
11	11.4	13.0897	-1.68971
12	6.4	14.3363	-7.93627
13	10.6	11.3589	-0.758906
14	12	13.3517	-1.35172
15	6.3	9.40794	-3.10794
16	11.3	11.083	0.216989
17	11.9	13.7338	-1.83383
18	9.3	12.0194	-2.71943
19	9.6	12.4127	-2.81275
20	10	11.1418	-1.14178
21	6.4	11.4465	-5.04651
22	13.8	12.7742	1.02578
23	10.8	13.392	-2.59204
24	13.8	12.088	1.71196
25	11.7	12.9817	-1.28167
26	10.9	14.5538	-3.65379
27	16.1	13.6325	2.4675
28	13.4	11.3299	2.07013
29	9.9	11.4549	-1.55487
30	11.5	11.8326	-0.332579
31	8.3	11.5603	-3.26034
32	11.7	13.6245	-1.9245
33	9	12.5087	-3.50868
34	9.7	13.958	-4.25798
35	10.8	12.549	-1.74896
36	10.3	12.7298	-2.42978
37	10.4	11.2144	-0.814364
38	12.7	12.4487	0.251277
39	9.3	12.4838	-3.1838
40	11.8	14.3043	-2.50426
41	5.9	10.9725	-5.07252
42	11.4	14.0328	-2.63281
43	13	11.8991	1.10087
44	10.8	12.6137	-1.81371
45	12.3	10.27	2.03001
46	11.3	13.532	-2.23198
47	11.8	12.4066	-0.606556
48	7.9	10.8219	-2.92188
49	12.7	9.78103	2.91897
50	12.3	10.9577	1.34226
51	11.6	11.9064	-0.306367
52	6.7	10.9149	-4.21494
53	10.9	13.1926	-2.29264
54	12.1	12.6	-0.500028
55	13.3	13.3472	-0.0472252
56	10.1	13.5479	-3.44791
57	5.7	11.6095	-5.90949
58	14.3	12.0575	2.24253
59	8	8.86125	-0.861254
60	13.3	12.1669	1.13306
61	9.3	13.2404	-3.9404
62	12.5	11.6888	0.811224
63	7.6	10.9431	-3.34305
64	15.9	13.938	1.962
65	9.2	11.7368	-2.53677
66	9.1	10.6263	-1.52625
67	11.1	13.9291	-2.8291
68	13	13.8808	-0.880834
69	14.5	12.6533	1.84674
70	12.2	10.9088	1.29123
71	12.3	13.8642	-1.56418
72	11.4	11.2811	0.118881
73	8.8	11.6126	-2.8126
74	14.6	11.3416	3.25837
75	12.6	12.368	0.232001
76	13	13.4816	-0.481643
77	12.6	11.4798	1.12021
78	13.2	14.7012	-1.50122
79	9.9	10.5834	-0.683362
80	7.7	11.5181	-3.81809
81	10.5	10.6272	-0.127175
82	13.4	10.0776	3.3224
83	10.9	11.7082	-0.808196
84	4.3	10.0569	-5.75687
85	10.3	10.7933	-0.493318
86	11.8	11.8322	-0.0321717
87	11.2	10.3284	0.871578
88	11.4	10.5058	0.894224
89	8.6	10.3001	-1.70012
90	13.2	10.8046	2.39537
91	12.6	10.5466	2.05345
92	5.6	11.2695	-5.66951
93	9.9	11.5295	-1.62946
94	8.8	12.1745	-3.37451
95	7.7	11.6802	-3.98017
96	9	10.363	-1.36302
97	7.3	12.6601	-5.36005
98	11.4	11.1684	0.231589
99	13.6	11.553	2.04697
100	7.9	10.4802	-2.58019
101	10.7	10.9072	-0.20724
102	10.3	11.3879	-1.08789
103	8.3	9.56376	-1.26376
104	9.6	10.6796	-1.07956
105	14.2	11.6142	2.58577
106	8.5	10.0148	-1.51478
107	13.5	10.3193	3.1807
108	4.9	10.3032	-5.40323
109	6.4	10.0587	-3.65869
110	9.6	10.3934	-0.79337
111	11.6	10.6981	0.901871
112	11.1	10.2502	0.849823
113	4.35	9.85795	-5.50795
114	12.7	12.6021	0.0979341
115	18.1	14.7736	3.32645
116	17.85	15.1862	2.66383
117	16.6	16.4577	0.142341
118	12.6	9.88953	2.71047
119	17.1	22.4602	-5.36023
120	19.1	15.5655	3.53449
121	16.1	18.5047	-2.40469
122	13.35	10.4207	2.92934
123	18.4	17.793	0.607004
124	14.7	10.8234	3.87661
125	10.6	14.5251	-3.92508
126	12.6	13.3506	-0.750573
127	16.2	15.0457	1.15427
128	13.6	16.4333	-2.83325
129	18.9	16.0101	2.88986
130	14.1	12.5662	1.53377
131	14.5	12.3066	2.19343
132	16.15	17.7911	-1.64112
133	14.75	12.6979	2.05211
134	14.8	13.7364	1.0636
135	12.45	12.1362	0.313816
136	12.65	14.5497	-1.89968
137	17.35	13.8766	3.47341
138	8.6	11.8075	-3.2075
139	18.4	17.558	0.842004
140	16.1	18.1913	-2.09127
141	11.6	11.2848	0.315199
142	17.75	11.4429	6.30714
143	15.25	12.7179	2.53212
144	17.65	16.0507	1.59928
145	16.35	14.5791	1.77094
146	17.65	15.217	2.43303
147	13.6	12.8848	0.715234
148	14.35	13.2293	1.12072
149	14.75	17.4612	-2.71118
150	18.25	16.7284	1.52157
151	9.9	14.7658	-4.86582
152	16	14.2354	1.76458
153	18.25	15.8675	2.38254
154	16.85	17.243	-0.392973
155	14.6	12.7007	1.89927
156	13.85	13.875	-0.0249819
157	18.95	16.7384	2.21159
158	15.6	14.4781	1.12194
159	14.85	17.6959	-2.84589
160	11.75	12.4579	-0.707876
161	18.45	13.2527	5.19729
162	15.9	17.1852	-1.28517
163	17.1	14.5652	2.53478
164	16.1	10.9475	5.15248
165	19.9	15.374	4.52598
166	10.95	11.0274	-0.0773797
167	18.45	15.9111	2.53887
168	15.1	10.6228	4.47721
169	15	15.3933	-0.393255
170	11.35	14.1745	-2.82446
171	15.95	15.1135	0.836475
172	18.1	13.3635	4.7365
173	14.6	13.1515	1.44849
174	15.4	16.0637	-0.663746
175	15.4	16.0242	-0.624246
176	17.6	13.2974	4.30259
177	13.35	13.9853	-0.635292
178	19.1	16.3169	2.78308
179	15.35	12.9782	2.37178
180	7.6	12.0149	-4.41494
181	13.4	14.1518	-0.75185
182	13.9	13.8446	0.0554315
183	19.1	17.2114	1.88863
184	15.25	13.4708	1.77924
185	12.9	12.3065	0.593454
186	16.1	14.1595	1.94053
187	17.35	12.5208	4.8292
188	13.15	12.4378	0.71222
189	12.15	9.99592	2.15408
190	12.6	12.291	0.308962
191	10.35	11.6383	-1.28834
192	15.4	12.4756	2.92436
193	9.6	10.79	-1.18996
194	18.2	12.8221	5.37791
195	13.6	11.9559	1.64405
196	14.85	15.5156	-0.665575
197	14.75	16.9446	-2.19464
198	14.1	13.5388	0.56123
199	14.9	11.3109	3.58912
200	16.25	12.6856	3.56437
201	19.25	19.1137	0.136278
202	13.6	12.2069	1.39315
203	13.6	13.0084	0.591649
204	15.65	14.9134	0.736624
205	12.75	12.2347	0.51531
206	14.6	10.8546	3.74537
207	9.85	12.7625	-2.91255
208	12.65	11.5851	1.06492
209	19.2	15.2227	3.97733
210	16.6	14.2405	2.35949
211	11.2	10.0712	1.12876
212	15.25	13.5038	1.74621
213	11.9	14.4137	-2.51373
214	13.2	15.6875	-2.48747
215	16.35	17.0968	-0.746756
216	12.4	13.1658	-0.765842
217	15.85	12.7893	3.06067
218	18.15	15.0182	3.13176
219	11.15	11.4409	-0.290875
220	15.65	16.1688	-0.518826
221	17.75	15.6792	2.07083
222	7.65	12.0673	-4.4173
223	12.35	12.7666	-0.416589
224	15.6	11.249	4.35103
225	19.3	16.1251	3.17486
226	15.2	12.0882	3.11184
227	17.1	13.2244	3.8756
228	15.6	12.8516	2.74839
229	18.4	14.9318	3.46818
230	19.05	15.0045	4.04549
231	18.55	12.3543	6.19571
232	19.1	17.3192	1.78083
233	13.1	11.5471	1.55287
234	12.85	12.9352	-0.0851515
235	9.5	10.6213	-1.12128
236	4.5	11.3614	-6.8614
237	11.85	10.4309	1.41914
238	13.6	15.4655	-1.86553
239	11.7	12.9435	-1.24351
240	12.4	10.9799	1.42008
241	13.35	14.8998	-1.54985
242	11.4	13.1114	-1.71139
243	14.9	11.4834	3.41664
244	19.9	15.3752	4.52478
245	11.2	12.4439	-1.2439
246	14.6	15.1896	-0.589553
247	17.6	16.0106	1.58943
248	14.05	13.0307	1.01925
249	16.1	15.33	0.770006
250	13.35	12.6023	0.747714
251	11.85	11.9222	-0.0721879
252	11.95	14.0551	-2.10505
253	14.75	14.666	0.0839977
254	15.15	13.2038	1.94624
255	13.2	14.3338	-1.13384
256	16.85	15.9339	0.916094
257	7.85	9.91886	-2.06886
258	7.7	14.7886	-7.08862
259	12.6	10.7734	1.82659
260	7.85	11.2677	-3.41767
261	10.95	11.2488	-0.298835
262	12.35	12.0044	0.345622
263	9.95	12.3533	-2.40325
264	14.9	11.6758	3.22425
265	16.65	14.7112	1.93876
266	13.4	13.1705	0.229464
267	13.95	13.8096	0.140439
268	15.7	10.7416	4.95843
269	16.85	12.5323	4.31765
270	10.95	10.3305	0.61954
271	15.35	11.1993	4.15072
272	12.2	10.9632	1.23684
273	15.1	12.9453	2.15472
274	17.75	16.0098	1.74019
275	15.2	12.6455	2.55451
276	14.6	13.5097	1.09026
277	16.65	14.2501	2.39991
278	8.1	11.0833	-2.98329

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.3393 & 0.560716 \tabularnewline
2 & 12.2 & 11.6417 & 0.558339 \tabularnewline
3 & 12.8 & 12.4315 & 0.368524 \tabularnewline
4 & 7.4 & 12.5373 & -5.13726 \tabularnewline
5 & 6.7 & 11.7014 & -5.00136 \tabularnewline
6 & 12.6 & 15.0282 & -2.42822 \tabularnewline
7 & 14.8 & 12.6847 & 2.11529 \tabularnewline
8 & 13.3 & 12.696 & 0.604007 \tabularnewline
9 & 11.1 & 12.2747 & -1.17469 \tabularnewline
10 & 8.2 & 14.6251 & -6.42514 \tabularnewline
11 & 11.4 & 13.0897 & -1.68971 \tabularnewline
12 & 6.4 & 14.3363 & -7.93627 \tabularnewline
13 & 10.6 & 11.3589 & -0.758906 \tabularnewline
14 & 12 & 13.3517 & -1.35172 \tabularnewline
15 & 6.3 & 9.40794 & -3.10794 \tabularnewline
16 & 11.3 & 11.083 & 0.216989 \tabularnewline
17 & 11.9 & 13.7338 & -1.83383 \tabularnewline
18 & 9.3 & 12.0194 & -2.71943 \tabularnewline
19 & 9.6 & 12.4127 & -2.81275 \tabularnewline
20 & 10 & 11.1418 & -1.14178 \tabularnewline
21 & 6.4 & 11.4465 & -5.04651 \tabularnewline
22 & 13.8 & 12.7742 & 1.02578 \tabularnewline
23 & 10.8 & 13.392 & -2.59204 \tabularnewline
24 & 13.8 & 12.088 & 1.71196 \tabularnewline
25 & 11.7 & 12.9817 & -1.28167 \tabularnewline
26 & 10.9 & 14.5538 & -3.65379 \tabularnewline
27 & 16.1 & 13.6325 & 2.4675 \tabularnewline
28 & 13.4 & 11.3299 & 2.07013 \tabularnewline
29 & 9.9 & 11.4549 & -1.55487 \tabularnewline
30 & 11.5 & 11.8326 & -0.332579 \tabularnewline
31 & 8.3 & 11.5603 & -3.26034 \tabularnewline
32 & 11.7 & 13.6245 & -1.9245 \tabularnewline
33 & 9 & 12.5087 & -3.50868 \tabularnewline
34 & 9.7 & 13.958 & -4.25798 \tabularnewline
35 & 10.8 & 12.549 & -1.74896 \tabularnewline
36 & 10.3 & 12.7298 & -2.42978 \tabularnewline
37 & 10.4 & 11.2144 & -0.814364 \tabularnewline
38 & 12.7 & 12.4487 & 0.251277 \tabularnewline
39 & 9.3 & 12.4838 & -3.1838 \tabularnewline
40 & 11.8 & 14.3043 & -2.50426 \tabularnewline
41 & 5.9 & 10.9725 & -5.07252 \tabularnewline
42 & 11.4 & 14.0328 & -2.63281 \tabularnewline
43 & 13 & 11.8991 & 1.10087 \tabularnewline
44 & 10.8 & 12.6137 & -1.81371 \tabularnewline
45 & 12.3 & 10.27 & 2.03001 \tabularnewline
46 & 11.3 & 13.532 & -2.23198 \tabularnewline
47 & 11.8 & 12.4066 & -0.606556 \tabularnewline
48 & 7.9 & 10.8219 & -2.92188 \tabularnewline
49 & 12.7 & 9.78103 & 2.91897 \tabularnewline
50 & 12.3 & 10.9577 & 1.34226 \tabularnewline
51 & 11.6 & 11.9064 & -0.306367 \tabularnewline
52 & 6.7 & 10.9149 & -4.21494 \tabularnewline
53 & 10.9 & 13.1926 & -2.29264 \tabularnewline
54 & 12.1 & 12.6 & -0.500028 \tabularnewline
55 & 13.3 & 13.3472 & -0.0472252 \tabularnewline
56 & 10.1 & 13.5479 & -3.44791 \tabularnewline
57 & 5.7 & 11.6095 & -5.90949 \tabularnewline
58 & 14.3 & 12.0575 & 2.24253 \tabularnewline
59 & 8 & 8.86125 & -0.861254 \tabularnewline
60 & 13.3 & 12.1669 & 1.13306 \tabularnewline
61 & 9.3 & 13.2404 & -3.9404 \tabularnewline
62 & 12.5 & 11.6888 & 0.811224 \tabularnewline
63 & 7.6 & 10.9431 & -3.34305 \tabularnewline
64 & 15.9 & 13.938 & 1.962 \tabularnewline
65 & 9.2 & 11.7368 & -2.53677 \tabularnewline
66 & 9.1 & 10.6263 & -1.52625 \tabularnewline
67 & 11.1 & 13.9291 & -2.8291 \tabularnewline
68 & 13 & 13.8808 & -0.880834 \tabularnewline
69 & 14.5 & 12.6533 & 1.84674 \tabularnewline
70 & 12.2 & 10.9088 & 1.29123 \tabularnewline
71 & 12.3 & 13.8642 & -1.56418 \tabularnewline
72 & 11.4 & 11.2811 & 0.118881 \tabularnewline
73 & 8.8 & 11.6126 & -2.8126 \tabularnewline
74 & 14.6 & 11.3416 & 3.25837 \tabularnewline
75 & 12.6 & 12.368 & 0.232001 \tabularnewline
76 & 13 & 13.4816 & -0.481643 \tabularnewline
77 & 12.6 & 11.4798 & 1.12021 \tabularnewline
78 & 13.2 & 14.7012 & -1.50122 \tabularnewline
79 & 9.9 & 10.5834 & -0.683362 \tabularnewline
80 & 7.7 & 11.5181 & -3.81809 \tabularnewline
81 & 10.5 & 10.6272 & -0.127175 \tabularnewline
82 & 13.4 & 10.0776 & 3.3224 \tabularnewline
83 & 10.9 & 11.7082 & -0.808196 \tabularnewline
84 & 4.3 & 10.0569 & -5.75687 \tabularnewline
85 & 10.3 & 10.7933 & -0.493318 \tabularnewline
86 & 11.8 & 11.8322 & -0.0321717 \tabularnewline
87 & 11.2 & 10.3284 & 0.871578 \tabularnewline
88 & 11.4 & 10.5058 & 0.894224 \tabularnewline
89 & 8.6 & 10.3001 & -1.70012 \tabularnewline
90 & 13.2 & 10.8046 & 2.39537 \tabularnewline
91 & 12.6 & 10.5466 & 2.05345 \tabularnewline
92 & 5.6 & 11.2695 & -5.66951 \tabularnewline
93 & 9.9 & 11.5295 & -1.62946 \tabularnewline
94 & 8.8 & 12.1745 & -3.37451 \tabularnewline
95 & 7.7 & 11.6802 & -3.98017 \tabularnewline
96 & 9 & 10.363 & -1.36302 \tabularnewline
97 & 7.3 & 12.6601 & -5.36005 \tabularnewline
98 & 11.4 & 11.1684 & 0.231589 \tabularnewline
99 & 13.6 & 11.553 & 2.04697 \tabularnewline
100 & 7.9 & 10.4802 & -2.58019 \tabularnewline
101 & 10.7 & 10.9072 & -0.20724 \tabularnewline
102 & 10.3 & 11.3879 & -1.08789 \tabularnewline
103 & 8.3 & 9.56376 & -1.26376 \tabularnewline
104 & 9.6 & 10.6796 & -1.07956 \tabularnewline
105 & 14.2 & 11.6142 & 2.58577 \tabularnewline
106 & 8.5 & 10.0148 & -1.51478 \tabularnewline
107 & 13.5 & 10.3193 & 3.1807 \tabularnewline
108 & 4.9 & 10.3032 & -5.40323 \tabularnewline
109 & 6.4 & 10.0587 & -3.65869 \tabularnewline
110 & 9.6 & 10.3934 & -0.79337 \tabularnewline
111 & 11.6 & 10.6981 & 0.901871 \tabularnewline
112 & 11.1 & 10.2502 & 0.849823 \tabularnewline
113 & 4.35 & 9.85795 & -5.50795 \tabularnewline
114 & 12.7 & 12.6021 & 0.0979341 \tabularnewline
115 & 18.1 & 14.7736 & 3.32645 \tabularnewline
116 & 17.85 & 15.1862 & 2.66383 \tabularnewline
117 & 16.6 & 16.4577 & 0.142341 \tabularnewline
118 & 12.6 & 9.88953 & 2.71047 \tabularnewline
119 & 17.1 & 22.4602 & -5.36023 \tabularnewline
120 & 19.1 & 15.5655 & 3.53449 \tabularnewline
121 & 16.1 & 18.5047 & -2.40469 \tabularnewline
122 & 13.35 & 10.4207 & 2.92934 \tabularnewline
123 & 18.4 & 17.793 & 0.607004 \tabularnewline
124 & 14.7 & 10.8234 & 3.87661 \tabularnewline
125 & 10.6 & 14.5251 & -3.92508 \tabularnewline
126 & 12.6 & 13.3506 & -0.750573 \tabularnewline
127 & 16.2 & 15.0457 & 1.15427 \tabularnewline
128 & 13.6 & 16.4333 & -2.83325 \tabularnewline
129 & 18.9 & 16.0101 & 2.88986 \tabularnewline
130 & 14.1 & 12.5662 & 1.53377 \tabularnewline
131 & 14.5 & 12.3066 & 2.19343 \tabularnewline
132 & 16.15 & 17.7911 & -1.64112 \tabularnewline
133 & 14.75 & 12.6979 & 2.05211 \tabularnewline
134 & 14.8 & 13.7364 & 1.0636 \tabularnewline
135 & 12.45 & 12.1362 & 0.313816 \tabularnewline
136 & 12.65 & 14.5497 & -1.89968 \tabularnewline
137 & 17.35 & 13.8766 & 3.47341 \tabularnewline
138 & 8.6 & 11.8075 & -3.2075 \tabularnewline
139 & 18.4 & 17.558 & 0.842004 \tabularnewline
140 & 16.1 & 18.1913 & -2.09127 \tabularnewline
141 & 11.6 & 11.2848 & 0.315199 \tabularnewline
142 & 17.75 & 11.4429 & 6.30714 \tabularnewline
143 & 15.25 & 12.7179 & 2.53212 \tabularnewline
144 & 17.65 & 16.0507 & 1.59928 \tabularnewline
145 & 16.35 & 14.5791 & 1.77094 \tabularnewline
146 & 17.65 & 15.217 & 2.43303 \tabularnewline
147 & 13.6 & 12.8848 & 0.715234 \tabularnewline
148 & 14.35 & 13.2293 & 1.12072 \tabularnewline
149 & 14.75 & 17.4612 & -2.71118 \tabularnewline
150 & 18.25 & 16.7284 & 1.52157 \tabularnewline
151 & 9.9 & 14.7658 & -4.86582 \tabularnewline
152 & 16 & 14.2354 & 1.76458 \tabularnewline
153 & 18.25 & 15.8675 & 2.38254 \tabularnewline
154 & 16.85 & 17.243 & -0.392973 \tabularnewline
155 & 14.6 & 12.7007 & 1.89927 \tabularnewline
156 & 13.85 & 13.875 & -0.0249819 \tabularnewline
157 & 18.95 & 16.7384 & 2.21159 \tabularnewline
158 & 15.6 & 14.4781 & 1.12194 \tabularnewline
159 & 14.85 & 17.6959 & -2.84589 \tabularnewline
160 & 11.75 & 12.4579 & -0.707876 \tabularnewline
161 & 18.45 & 13.2527 & 5.19729 \tabularnewline
162 & 15.9 & 17.1852 & -1.28517 \tabularnewline
163 & 17.1 & 14.5652 & 2.53478 \tabularnewline
164 & 16.1 & 10.9475 & 5.15248 \tabularnewline
165 & 19.9 & 15.374 & 4.52598 \tabularnewline
166 & 10.95 & 11.0274 & -0.0773797 \tabularnewline
167 & 18.45 & 15.9111 & 2.53887 \tabularnewline
168 & 15.1 & 10.6228 & 4.47721 \tabularnewline
169 & 15 & 15.3933 & -0.393255 \tabularnewline
170 & 11.35 & 14.1745 & -2.82446 \tabularnewline
171 & 15.95 & 15.1135 & 0.836475 \tabularnewline
172 & 18.1 & 13.3635 & 4.7365 \tabularnewline
173 & 14.6 & 13.1515 & 1.44849 \tabularnewline
174 & 15.4 & 16.0637 & -0.663746 \tabularnewline
175 & 15.4 & 16.0242 & -0.624246 \tabularnewline
176 & 17.6 & 13.2974 & 4.30259 \tabularnewline
177 & 13.35 & 13.9853 & -0.635292 \tabularnewline
178 & 19.1 & 16.3169 & 2.78308 \tabularnewline
179 & 15.35 & 12.9782 & 2.37178 \tabularnewline
180 & 7.6 & 12.0149 & -4.41494 \tabularnewline
181 & 13.4 & 14.1518 & -0.75185 \tabularnewline
182 & 13.9 & 13.8446 & 0.0554315 \tabularnewline
183 & 19.1 & 17.2114 & 1.88863 \tabularnewline
184 & 15.25 & 13.4708 & 1.77924 \tabularnewline
185 & 12.9 & 12.3065 & 0.593454 \tabularnewline
186 & 16.1 & 14.1595 & 1.94053 \tabularnewline
187 & 17.35 & 12.5208 & 4.8292 \tabularnewline
188 & 13.15 & 12.4378 & 0.71222 \tabularnewline
189 & 12.15 & 9.99592 & 2.15408 \tabularnewline
190 & 12.6 & 12.291 & 0.308962 \tabularnewline
191 & 10.35 & 11.6383 & -1.28834 \tabularnewline
192 & 15.4 & 12.4756 & 2.92436 \tabularnewline
193 & 9.6 & 10.79 & -1.18996 \tabularnewline
194 & 18.2 & 12.8221 & 5.37791 \tabularnewline
195 & 13.6 & 11.9559 & 1.64405 \tabularnewline
196 & 14.85 & 15.5156 & -0.665575 \tabularnewline
197 & 14.75 & 16.9446 & -2.19464 \tabularnewline
198 & 14.1 & 13.5388 & 0.56123 \tabularnewline
199 & 14.9 & 11.3109 & 3.58912 \tabularnewline
200 & 16.25 & 12.6856 & 3.56437 \tabularnewline
201 & 19.25 & 19.1137 & 0.136278 \tabularnewline
202 & 13.6 & 12.2069 & 1.39315 \tabularnewline
203 & 13.6 & 13.0084 & 0.591649 \tabularnewline
204 & 15.65 & 14.9134 & 0.736624 \tabularnewline
205 & 12.75 & 12.2347 & 0.51531 \tabularnewline
206 & 14.6 & 10.8546 & 3.74537 \tabularnewline
207 & 9.85 & 12.7625 & -2.91255 \tabularnewline
208 & 12.65 & 11.5851 & 1.06492 \tabularnewline
209 & 19.2 & 15.2227 & 3.97733 \tabularnewline
210 & 16.6 & 14.2405 & 2.35949 \tabularnewline
211 & 11.2 & 10.0712 & 1.12876 \tabularnewline
212 & 15.25 & 13.5038 & 1.74621 \tabularnewline
213 & 11.9 & 14.4137 & -2.51373 \tabularnewline
214 & 13.2 & 15.6875 & -2.48747 \tabularnewline
215 & 16.35 & 17.0968 & -0.746756 \tabularnewline
216 & 12.4 & 13.1658 & -0.765842 \tabularnewline
217 & 15.85 & 12.7893 & 3.06067 \tabularnewline
218 & 18.15 & 15.0182 & 3.13176 \tabularnewline
219 & 11.15 & 11.4409 & -0.290875 \tabularnewline
220 & 15.65 & 16.1688 & -0.518826 \tabularnewline
221 & 17.75 & 15.6792 & 2.07083 \tabularnewline
222 & 7.65 & 12.0673 & -4.4173 \tabularnewline
223 & 12.35 & 12.7666 & -0.416589 \tabularnewline
224 & 15.6 & 11.249 & 4.35103 \tabularnewline
225 & 19.3 & 16.1251 & 3.17486 \tabularnewline
226 & 15.2 & 12.0882 & 3.11184 \tabularnewline
227 & 17.1 & 13.2244 & 3.8756 \tabularnewline
228 & 15.6 & 12.8516 & 2.74839 \tabularnewline
229 & 18.4 & 14.9318 & 3.46818 \tabularnewline
230 & 19.05 & 15.0045 & 4.04549 \tabularnewline
231 & 18.55 & 12.3543 & 6.19571 \tabularnewline
232 & 19.1 & 17.3192 & 1.78083 \tabularnewline
233 & 13.1 & 11.5471 & 1.55287 \tabularnewline
234 & 12.85 & 12.9352 & -0.0851515 \tabularnewline
235 & 9.5 & 10.6213 & -1.12128 \tabularnewline
236 & 4.5 & 11.3614 & -6.8614 \tabularnewline
237 & 11.85 & 10.4309 & 1.41914 \tabularnewline
238 & 13.6 & 15.4655 & -1.86553 \tabularnewline
239 & 11.7 & 12.9435 & -1.24351 \tabularnewline
240 & 12.4 & 10.9799 & 1.42008 \tabularnewline
241 & 13.35 & 14.8998 & -1.54985 \tabularnewline
242 & 11.4 & 13.1114 & -1.71139 \tabularnewline
243 & 14.9 & 11.4834 & 3.41664 \tabularnewline
244 & 19.9 & 15.3752 & 4.52478 \tabularnewline
245 & 11.2 & 12.4439 & -1.2439 \tabularnewline
246 & 14.6 & 15.1896 & -0.589553 \tabularnewline
247 & 17.6 & 16.0106 & 1.58943 \tabularnewline
248 & 14.05 & 13.0307 & 1.01925 \tabularnewline
249 & 16.1 & 15.33 & 0.770006 \tabularnewline
250 & 13.35 & 12.6023 & 0.747714 \tabularnewline
251 & 11.85 & 11.9222 & -0.0721879 \tabularnewline
252 & 11.95 & 14.0551 & -2.10505 \tabularnewline
253 & 14.75 & 14.666 & 0.0839977 \tabularnewline
254 & 15.15 & 13.2038 & 1.94624 \tabularnewline
255 & 13.2 & 14.3338 & -1.13384 \tabularnewline
256 & 16.85 & 15.9339 & 0.916094 \tabularnewline
257 & 7.85 & 9.91886 & -2.06886 \tabularnewline
258 & 7.7 & 14.7886 & -7.08862 \tabularnewline
259 & 12.6 & 10.7734 & 1.82659 \tabularnewline
260 & 7.85 & 11.2677 & -3.41767 \tabularnewline
261 & 10.95 & 11.2488 & -0.298835 \tabularnewline
262 & 12.35 & 12.0044 & 0.345622 \tabularnewline
263 & 9.95 & 12.3533 & -2.40325 \tabularnewline
264 & 14.9 & 11.6758 & 3.22425 \tabularnewline
265 & 16.65 & 14.7112 & 1.93876 \tabularnewline
266 & 13.4 & 13.1705 & 0.229464 \tabularnewline
267 & 13.95 & 13.8096 & 0.140439 \tabularnewline
268 & 15.7 & 10.7416 & 4.95843 \tabularnewline
269 & 16.85 & 12.5323 & 4.31765 \tabularnewline
270 & 10.95 & 10.3305 & 0.61954 \tabularnewline
271 & 15.35 & 11.1993 & 4.15072 \tabularnewline
272 & 12.2 & 10.9632 & 1.23684 \tabularnewline
273 & 15.1 & 12.9453 & 2.15472 \tabularnewline
274 & 17.75 & 16.0098 & 1.74019 \tabularnewline
275 & 15.2 & 12.6455 & 2.55451 \tabularnewline
276 & 14.6 & 13.5097 & 1.09026 \tabularnewline
277 & 16.65 & 14.2501 & 2.39991 \tabularnewline
278 & 8.1 & 11.0833 & -2.98329 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271106&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]12.3393[/C][C]0.560716[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]11.6417[/C][C]0.558339[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]12.4315[/C][C]0.368524[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.5373[/C][C]-5.13726[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]11.7014[/C][C]-5.00136[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]15.0282[/C][C]-2.42822[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.6847[/C][C]2.11529[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]12.696[/C][C]0.604007[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.2747[/C][C]-1.17469[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.6251[/C][C]-6.42514[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]13.0897[/C][C]-1.68971[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.3363[/C][C]-7.93627[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.3589[/C][C]-0.758906[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.3517[/C][C]-1.35172[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]9.40794[/C][C]-3.10794[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.083[/C][C]0.216989[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]13.7338[/C][C]-1.83383[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.0194[/C][C]-2.71943[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.4127[/C][C]-2.81275[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]11.1418[/C][C]-1.14178[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]11.4465[/C][C]-5.04651[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.7742[/C][C]1.02578[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]13.392[/C][C]-2.59204[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.088[/C][C]1.71196[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]12.9817[/C][C]-1.28167[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]14.5538[/C][C]-3.65379[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.6325[/C][C]2.4675[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]11.3299[/C][C]2.07013[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.4549[/C][C]-1.55487[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]11.8326[/C][C]-0.332579[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.5603[/C][C]-3.26034[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.6245[/C][C]-1.9245[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.5087[/C][C]-3.50868[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]13.958[/C][C]-4.25798[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.549[/C][C]-1.74896[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.7298[/C][C]-2.42978[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.2144[/C][C]-0.814364[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.4487[/C][C]0.251277[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]12.4838[/C][C]-3.1838[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.3043[/C][C]-2.50426[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.9725[/C][C]-5.07252[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]14.0328[/C][C]-2.63281[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.8991[/C][C]1.10087[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.6137[/C][C]-1.81371[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]10.27[/C][C]2.03001[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.532[/C][C]-2.23198[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.4066[/C][C]-0.606556[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]10.8219[/C][C]-2.92188[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]9.78103[/C][C]2.91897[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]10.9577[/C][C]1.34226[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]11.9064[/C][C]-0.306367[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.9149[/C][C]-4.21494[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.1926[/C][C]-2.29264[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.6[/C][C]-0.500028[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.3472[/C][C]-0.0472252[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.5479[/C][C]-3.44791[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.6095[/C][C]-5.90949[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.0575[/C][C]2.24253[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]8.86125[/C][C]-0.861254[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.1669[/C][C]1.13306[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.2404[/C][C]-3.9404[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.6888[/C][C]0.811224[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]10.9431[/C][C]-3.34305[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.938[/C][C]1.962[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.7368[/C][C]-2.53677[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]10.6263[/C][C]-1.52625[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]13.9291[/C][C]-2.8291[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.8808[/C][C]-0.880834[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.6533[/C][C]1.84674[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.9088[/C][C]1.29123[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.8642[/C][C]-1.56418[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]11.2811[/C][C]0.118881[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.6126[/C][C]-2.8126[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.3416[/C][C]3.25837[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.368[/C][C]0.232001[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]13.4816[/C][C]-0.481643[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]11.4798[/C][C]1.12021[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]14.7012[/C][C]-1.50122[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]10.5834[/C][C]-0.683362[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]11.5181[/C][C]-3.81809[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]10.6272[/C][C]-0.127175[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]10.0776[/C][C]3.3224[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]11.7082[/C][C]-0.808196[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]10.0569[/C][C]-5.75687[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]10.7933[/C][C]-0.493318[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]11.8322[/C][C]-0.0321717[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]10.3284[/C][C]0.871578[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]10.5058[/C][C]0.894224[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.3001[/C][C]-1.70012[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]10.8046[/C][C]2.39537[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]10.5466[/C][C]2.05345[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]11.2695[/C][C]-5.66951[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]11.5295[/C][C]-1.62946[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]12.1745[/C][C]-3.37451[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]11.6802[/C][C]-3.98017[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]10.363[/C][C]-1.36302[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]12.6601[/C][C]-5.36005[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]11.1684[/C][C]0.231589[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]11.553[/C][C]2.04697[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]10.4802[/C][C]-2.58019[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]10.9072[/C][C]-0.20724[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]11.3879[/C][C]-1.08789[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]9.56376[/C][C]-1.26376[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]10.6796[/C][C]-1.07956[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]11.6142[/C][C]2.58577[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]10.0148[/C][C]-1.51478[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]10.3193[/C][C]3.1807[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]10.3032[/C][C]-5.40323[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]10.0587[/C][C]-3.65869[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]10.3934[/C][C]-0.79337[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]10.6981[/C][C]0.901871[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]10.2502[/C][C]0.849823[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]9.85795[/C][C]-5.50795[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.6021[/C][C]0.0979341[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]14.7736[/C][C]3.32645[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]15.1862[/C][C]2.66383[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]16.4577[/C][C]0.142341[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]9.88953[/C][C]2.71047[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]22.4602[/C][C]-5.36023[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]15.5655[/C][C]3.53449[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]18.5047[/C][C]-2.40469[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]10.4207[/C][C]2.92934[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]17.793[/C][C]0.607004[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]10.8234[/C][C]3.87661[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]14.5251[/C][C]-3.92508[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]13.3506[/C][C]-0.750573[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]15.0457[/C][C]1.15427[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]16.4333[/C][C]-2.83325[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]16.0101[/C][C]2.88986[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]12.5662[/C][C]1.53377[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]12.3066[/C][C]2.19343[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]17.7911[/C][C]-1.64112[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]12.6979[/C][C]2.05211[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]13.7364[/C][C]1.0636[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]12.1362[/C][C]0.313816[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]14.5497[/C][C]-1.89968[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]13.8766[/C][C]3.47341[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]11.8075[/C][C]-3.2075[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]17.558[/C][C]0.842004[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]18.1913[/C][C]-2.09127[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]11.2848[/C][C]0.315199[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]11.4429[/C][C]6.30714[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]12.7179[/C][C]2.53212[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]16.0507[/C][C]1.59928[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]14.5791[/C][C]1.77094[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]15.217[/C][C]2.43303[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]12.8848[/C][C]0.715234[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]13.2293[/C][C]1.12072[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]17.4612[/C][C]-2.71118[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]16.7284[/C][C]1.52157[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]14.7658[/C][C]-4.86582[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.2354[/C][C]1.76458[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]15.8675[/C][C]2.38254[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]17.243[/C][C]-0.392973[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]12.7007[/C][C]1.89927[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]13.875[/C][C]-0.0249819[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]16.7384[/C][C]2.21159[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]14.4781[/C][C]1.12194[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]17.6959[/C][C]-2.84589[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]12.4579[/C][C]-0.707876[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]13.2527[/C][C]5.19729[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]17.1852[/C][C]-1.28517[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]14.5652[/C][C]2.53478[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]10.9475[/C][C]5.15248[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]15.374[/C][C]4.52598[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]11.0274[/C][C]-0.0773797[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]15.9111[/C][C]2.53887[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]10.6228[/C][C]4.47721[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]15.3933[/C][C]-0.393255[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]14.1745[/C][C]-2.82446[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]15.1135[/C][C]0.836475[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]13.3635[/C][C]4.7365[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]13.1515[/C][C]1.44849[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]16.0637[/C][C]-0.663746[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.0242[/C][C]-0.624246[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]13.2974[/C][C]4.30259[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]13.9853[/C][C]-0.635292[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]16.3169[/C][C]2.78308[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]12.9782[/C][C]2.37178[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]12.0149[/C][C]-4.41494[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]14.1518[/C][C]-0.75185[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]13.8446[/C][C]0.0554315[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]17.2114[/C][C]1.88863[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]13.4708[/C][C]1.77924[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]12.3065[/C][C]0.593454[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]14.1595[/C][C]1.94053[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]12.5208[/C][C]4.8292[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]12.4378[/C][C]0.71222[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]9.99592[/C][C]2.15408[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]12.291[/C][C]0.308962[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]11.6383[/C][C]-1.28834[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]12.4756[/C][C]2.92436[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]10.79[/C][C]-1.18996[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]12.8221[/C][C]5.37791[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]11.9559[/C][C]1.64405[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]15.5156[/C][C]-0.665575[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]16.9446[/C][C]-2.19464[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]13.5388[/C][C]0.56123[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]11.3109[/C][C]3.58912[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]12.6856[/C][C]3.56437[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]19.1137[/C][C]0.136278[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]12.2069[/C][C]1.39315[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.0084[/C][C]0.591649[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]14.9134[/C][C]0.736624[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]12.2347[/C][C]0.51531[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]10.8546[/C][C]3.74537[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]12.7625[/C][C]-2.91255[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]11.5851[/C][C]1.06492[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]15.2227[/C][C]3.97733[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]14.2405[/C][C]2.35949[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]10.0712[/C][C]1.12876[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]13.5038[/C][C]1.74621[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]14.4137[/C][C]-2.51373[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]15.6875[/C][C]-2.48747[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]17.0968[/C][C]-0.746756[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]13.1658[/C][C]-0.765842[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]12.7893[/C][C]3.06067[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]15.0182[/C][C]3.13176[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]11.4409[/C][C]-0.290875[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]16.1688[/C][C]-0.518826[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]15.6792[/C][C]2.07083[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]12.0673[/C][C]-4.4173[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]12.7666[/C][C]-0.416589[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]11.249[/C][C]4.35103[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]16.1251[/C][C]3.17486[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]12.0882[/C][C]3.11184[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]13.2244[/C][C]3.8756[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]12.8516[/C][C]2.74839[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]14.9318[/C][C]3.46818[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]15.0045[/C][C]4.04549[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]12.3543[/C][C]6.19571[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]17.3192[/C][C]1.78083[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]11.5471[/C][C]1.55287[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]12.9352[/C][C]-0.0851515[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]10.6213[/C][C]-1.12128[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]11.3614[/C][C]-6.8614[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]10.4309[/C][C]1.41914[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]15.4655[/C][C]-1.86553[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]12.9435[/C][C]-1.24351[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]10.9799[/C][C]1.42008[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]14.8998[/C][C]-1.54985[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]13.1114[/C][C]-1.71139[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]11.4834[/C][C]3.41664[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]15.3752[/C][C]4.52478[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]12.4439[/C][C]-1.2439[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]15.1896[/C][C]-0.589553[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]16.0106[/C][C]1.58943[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]13.0307[/C][C]1.01925[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]15.33[/C][C]0.770006[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]12.6023[/C][C]0.747714[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]11.9222[/C][C]-0.0721879[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]14.0551[/C][C]-2.10505[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]14.666[/C][C]0.0839977[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]13.2038[/C][C]1.94624[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]14.3338[/C][C]-1.13384[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]15.9339[/C][C]0.916094[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]9.91886[/C][C]-2.06886[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]14.7886[/C][C]-7.08862[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]10.7734[/C][C]1.82659[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]11.2677[/C][C]-3.41767[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]11.2488[/C][C]-0.298835[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]12.0044[/C][C]0.345622[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]12.3533[/C][C]-2.40325[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]11.6758[/C][C]3.22425[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]14.7112[/C][C]1.93876[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]13.1705[/C][C]0.229464[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]13.8096[/C][C]0.140439[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]10.7416[/C][C]4.95843[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]12.5323[/C][C]4.31765[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]10.3305[/C][C]0.61954[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]11.1993[/C][C]4.15072[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]10.9632[/C][C]1.23684[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]12.9453[/C][C]2.15472[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]16.0098[/C][C]1.74019[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]12.6455[/C][C]2.55451[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]13.5097[/C][C]1.09026[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]14.2501[/C][C]2.39991[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]11.0833[/C][C]-2.98329[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271106&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271106&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	12.3393	0.560716
2	12.2	11.6417	0.558339
3	12.8	12.4315	0.368524
4	7.4	12.5373	-5.13726
5	6.7	11.7014	-5.00136
6	12.6	15.0282	-2.42822
7	14.8	12.6847	2.11529
8	13.3	12.696	0.604007
9	11.1	12.2747	-1.17469
10	8.2	14.6251	-6.42514
11	11.4	13.0897	-1.68971
12	6.4	14.3363	-7.93627
13	10.6	11.3589	-0.758906
14	12	13.3517	-1.35172
15	6.3	9.40794	-3.10794
16	11.3	11.083	0.216989
17	11.9	13.7338	-1.83383
18	9.3	12.0194	-2.71943
19	9.6	12.4127	-2.81275
20	10	11.1418	-1.14178
21	6.4	11.4465	-5.04651
22	13.8	12.7742	1.02578
23	10.8	13.392	-2.59204
24	13.8	12.088	1.71196
25	11.7	12.9817	-1.28167
26	10.9	14.5538	-3.65379
27	16.1	13.6325	2.4675
28	13.4	11.3299	2.07013
29	9.9	11.4549	-1.55487
30	11.5	11.8326	-0.332579
31	8.3	11.5603	-3.26034
32	11.7	13.6245	-1.9245
33	9	12.5087	-3.50868
34	9.7	13.958	-4.25798
35	10.8	12.549	-1.74896
36	10.3	12.7298	-2.42978
37	10.4	11.2144	-0.814364
38	12.7	12.4487	0.251277
39	9.3	12.4838	-3.1838
40	11.8	14.3043	-2.50426
41	5.9	10.9725	-5.07252
42	11.4	14.0328	-2.63281
43	13	11.8991	1.10087
44	10.8	12.6137	-1.81371
45	12.3	10.27	2.03001
46	11.3	13.532	-2.23198
47	11.8	12.4066	-0.606556
48	7.9	10.8219	-2.92188
49	12.7	9.78103	2.91897
50	12.3	10.9577	1.34226
51	11.6	11.9064	-0.306367
52	6.7	10.9149	-4.21494
53	10.9	13.1926	-2.29264
54	12.1	12.6	-0.500028
55	13.3	13.3472	-0.0472252
56	10.1	13.5479	-3.44791
57	5.7	11.6095	-5.90949
58	14.3	12.0575	2.24253
59	8	8.86125	-0.861254
60	13.3	12.1669	1.13306
61	9.3	13.2404	-3.9404
62	12.5	11.6888	0.811224
63	7.6	10.9431	-3.34305
64	15.9	13.938	1.962
65	9.2	11.7368	-2.53677
66	9.1	10.6263	-1.52625
67	11.1	13.9291	-2.8291
68	13	13.8808	-0.880834
69	14.5	12.6533	1.84674
70	12.2	10.9088	1.29123
71	12.3	13.8642	-1.56418
72	11.4	11.2811	0.118881
73	8.8	11.6126	-2.8126
74	14.6	11.3416	3.25837
75	12.6	12.368	0.232001
76	13	13.4816	-0.481643
77	12.6	11.4798	1.12021
78	13.2	14.7012	-1.50122
79	9.9	10.5834	-0.683362
80	7.7	11.5181	-3.81809
81	10.5	10.6272	-0.127175
82	13.4	10.0776	3.3224
83	10.9	11.7082	-0.808196
84	4.3	10.0569	-5.75687
85	10.3	10.7933	-0.493318
86	11.8	11.8322	-0.0321717
87	11.2	10.3284	0.871578
88	11.4	10.5058	0.894224
89	8.6	10.3001	-1.70012
90	13.2	10.8046	2.39537
91	12.6	10.5466	2.05345
92	5.6	11.2695	-5.66951
93	9.9	11.5295	-1.62946
94	8.8	12.1745	-3.37451
95	7.7	11.6802	-3.98017
96	9	10.363	-1.36302
97	7.3	12.6601	-5.36005
98	11.4	11.1684	0.231589
99	13.6	11.553	2.04697
100	7.9	10.4802	-2.58019
101	10.7	10.9072	-0.20724
102	10.3	11.3879	-1.08789
103	8.3	9.56376	-1.26376
104	9.6	10.6796	-1.07956
105	14.2	11.6142	2.58577
106	8.5	10.0148	-1.51478
107	13.5	10.3193	3.1807
108	4.9	10.3032	-5.40323
109	6.4	10.0587	-3.65869
110	9.6	10.3934	-0.79337
111	11.6	10.6981	0.901871
112	11.1	10.2502	0.849823
113	4.35	9.85795	-5.50795
114	12.7	12.6021	0.0979341
115	18.1	14.7736	3.32645
116	17.85	15.1862	2.66383
117	16.6	16.4577	0.142341
118	12.6	9.88953	2.71047
119	17.1	22.4602	-5.36023
120	19.1	15.5655	3.53449
121	16.1	18.5047	-2.40469
122	13.35	10.4207	2.92934
123	18.4	17.793	0.607004
124	14.7	10.8234	3.87661
125	10.6	14.5251	-3.92508
126	12.6	13.3506	-0.750573
127	16.2	15.0457	1.15427
128	13.6	16.4333	-2.83325
129	18.9	16.0101	2.88986
130	14.1	12.5662	1.53377
131	14.5	12.3066	2.19343
132	16.15	17.7911	-1.64112
133	14.75	12.6979	2.05211
134	14.8	13.7364	1.0636
135	12.45	12.1362	0.313816
136	12.65	14.5497	-1.89968
137	17.35	13.8766	3.47341
138	8.6	11.8075	-3.2075
139	18.4	17.558	0.842004
140	16.1	18.1913	-2.09127
141	11.6	11.2848	0.315199
142	17.75	11.4429	6.30714
143	15.25	12.7179	2.53212
144	17.65	16.0507	1.59928
145	16.35	14.5791	1.77094
146	17.65	15.217	2.43303
147	13.6	12.8848	0.715234
148	14.35	13.2293	1.12072
149	14.75	17.4612	-2.71118
150	18.25	16.7284	1.52157
151	9.9	14.7658	-4.86582
152	16	14.2354	1.76458
153	18.25	15.8675	2.38254
154	16.85	17.243	-0.392973
155	14.6	12.7007	1.89927
156	13.85	13.875	-0.0249819
157	18.95	16.7384	2.21159
158	15.6	14.4781	1.12194
159	14.85	17.6959	-2.84589
160	11.75	12.4579	-0.707876
161	18.45	13.2527	5.19729
162	15.9	17.1852	-1.28517
163	17.1	14.5652	2.53478
164	16.1	10.9475	5.15248
165	19.9	15.374	4.52598
166	10.95	11.0274	-0.0773797
167	18.45	15.9111	2.53887
168	15.1	10.6228	4.47721
169	15	15.3933	-0.393255
170	11.35	14.1745	-2.82446
171	15.95	15.1135	0.836475
172	18.1	13.3635	4.7365
173	14.6	13.1515	1.44849
174	15.4	16.0637	-0.663746
175	15.4	16.0242	-0.624246
176	17.6	13.2974	4.30259
177	13.35	13.9853	-0.635292
178	19.1	16.3169	2.78308
179	15.35	12.9782	2.37178
180	7.6	12.0149	-4.41494
181	13.4	14.1518	-0.75185
182	13.9	13.8446	0.0554315
183	19.1	17.2114	1.88863
184	15.25	13.4708	1.77924
185	12.9	12.3065	0.593454
186	16.1	14.1595	1.94053
187	17.35	12.5208	4.8292
188	13.15	12.4378	0.71222
189	12.15	9.99592	2.15408
190	12.6	12.291	0.308962
191	10.35	11.6383	-1.28834
192	15.4	12.4756	2.92436
193	9.6	10.79	-1.18996
194	18.2	12.8221	5.37791
195	13.6	11.9559	1.64405
196	14.85	15.5156	-0.665575
197	14.75	16.9446	-2.19464
198	14.1	13.5388	0.56123
199	14.9	11.3109	3.58912
200	16.25	12.6856	3.56437
201	19.25	19.1137	0.136278
202	13.6	12.2069	1.39315
203	13.6	13.0084	0.591649
204	15.65	14.9134	0.736624
205	12.75	12.2347	0.51531
206	14.6	10.8546	3.74537
207	9.85	12.7625	-2.91255
208	12.65	11.5851	1.06492
209	19.2	15.2227	3.97733
210	16.6	14.2405	2.35949
211	11.2	10.0712	1.12876
212	15.25	13.5038	1.74621
213	11.9	14.4137	-2.51373
214	13.2	15.6875	-2.48747
215	16.35	17.0968	-0.746756
216	12.4	13.1658	-0.765842
217	15.85	12.7893	3.06067
218	18.15	15.0182	3.13176
219	11.15	11.4409	-0.290875
220	15.65	16.1688	-0.518826
221	17.75	15.6792	2.07083
222	7.65	12.0673	-4.4173
223	12.35	12.7666	-0.416589
224	15.6	11.249	4.35103
225	19.3	16.1251	3.17486
226	15.2	12.0882	3.11184
227	17.1	13.2244	3.8756
228	15.6	12.8516	2.74839
229	18.4	14.9318	3.46818
230	19.05	15.0045	4.04549
231	18.55	12.3543	6.19571
232	19.1	17.3192	1.78083
233	13.1	11.5471	1.55287
234	12.85	12.9352	-0.0851515
235	9.5	10.6213	-1.12128
236	4.5	11.3614	-6.8614
237	11.85	10.4309	1.41914
238	13.6	15.4655	-1.86553
239	11.7	12.9435	-1.24351
240	12.4	10.9799	1.42008
241	13.35	14.8998	-1.54985
242	11.4	13.1114	-1.71139
243	14.9	11.4834	3.41664
244	19.9	15.3752	4.52478
245	11.2	12.4439	-1.2439
246	14.6	15.1896	-0.589553
247	17.6	16.0106	1.58943
248	14.05	13.0307	1.01925
249	16.1	15.33	0.770006
250	13.35	12.6023	0.747714
251	11.85	11.9222	-0.0721879
252	11.95	14.0551	-2.10505
253	14.75	14.666	0.0839977
254	15.15	13.2038	1.94624
255	13.2	14.3338	-1.13384
256	16.85	15.9339	0.916094
257	7.85	9.91886	-2.06886
258	7.7	14.7886	-7.08862
259	12.6	10.7734	1.82659
260	7.85	11.2677	-3.41767
261	10.95	11.2488	-0.298835
262	12.35	12.0044	0.345622
263	9.95	12.3533	-2.40325
264	14.9	11.6758	3.22425
265	16.65	14.7112	1.93876
266	13.4	13.1705	0.229464
267	13.95	13.8096	0.140439
268	15.7	10.7416	4.95843
269	16.85	12.5323	4.31765
270	10.95	10.3305	0.61954
271	15.35	11.1993	4.15072
272	12.2	10.9632	1.23684
273	15.1	12.9453	2.15472
274	17.75	16.0098	1.74019
275	15.2	12.6455	2.55451
276	14.6	13.5097	1.09026
277	16.65	14.2501	2.39991
278	8.1	11.0833	-2.98329

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
13	0.675588	0.648825	0.324412
14	0.538871	0.922257	0.461129
15	0.484189	0.968378	0.515811
16	0.359679	0.719359	0.640321
17	0.297055	0.594111	0.702945
18	0.209613	0.419226	0.790387
19	0.150024	0.300048	0.849976
20	0.102705	0.20541	0.897295
21	0.0968817	0.193763	0.903118
22	0.0806714	0.161343	0.919329
23	0.0626475	0.125295	0.937352
24	0.0529773	0.105955	0.947023
25	0.0378934	0.0757869	0.962107
26	0.0252636	0.0505272	0.974736
27	0.0162378	0.0324757	0.983762
28	0.013289	0.0265779	0.986711
29	0.00844492	0.0168898	0.991555
30	0.00792825	0.0158565	0.992072
31	0.0121654	0.0243307	0.987835
32	0.00837248	0.016745	0.991628
33	0.00612945	0.0122589	0.993871
34	0.00530235	0.0106047	0.994698
35	0.00337522	0.00675045	0.996625
36	0.00413464	0.00826928	0.995865
37	0.00324999	0.00649997	0.99675
38	0.00337865	0.0067573	0.996621
39	0.00942599	0.018852	0.990574
40	0.00799467	0.0159893	0.992005
41	0.0178932	0.0357865	0.982107
42	0.017331	0.034662	0.982669
43	0.0137578	0.0275156	0.986242
44	0.0103885	0.0207771	0.989611
45	0.00917149	0.018343	0.990829
46	0.00750557	0.0150111	0.992494
47	0.0062263	0.0124526	0.993774
48	0.00529851	0.010597	0.994701
49	0.0100259	0.0200517	0.989974
50	0.0156638	0.0313276	0.984336
51	0.0135916	0.0271831	0.986408
52	0.0143032	0.0286064	0.985697
53	0.0134469	0.0268938	0.986553
54	0.016	0.0320001	0.984
55	0.0313226	0.0626453	0.968677
56	0.0259389	0.0518778	0.974061
57	0.0901712	0.180342	0.909829
58	0.0872827	0.174565	0.912717
59	0.073227	0.146454	0.926773
60	0.0772639	0.154528	0.922736
61	0.0898542	0.179708	0.910146
62	0.0819949	0.16399	0.918005
63	0.160227	0.320453	0.839773
64	0.188128	0.376256	0.811872
65	0.202369	0.404738	0.797631
66	0.178457	0.356915	0.821543
67	0.175803	0.351605	0.824197
68	0.163325	0.326649	0.836675
69	0.168733	0.337466	0.831267
70	0.15218	0.304361	0.84782
71	0.142134	0.284268	0.857866
72	0.127094	0.254188	0.872906
73	0.115493	0.230986	0.884507
74	0.135848	0.271696	0.864152
75	0.120883	0.241765	0.879117
76	0.10723	0.21446	0.89277
77	0.0959077	0.191815	0.904092
78	0.103926	0.207853	0.896074
79	0.0876104	0.175221	0.91239
80	0.11174	0.22348	0.88826
81	0.0951421	0.190284	0.904858
82	0.112962	0.225923	0.887038
83	0.0970748	0.19415	0.902925
84	0.187574	0.375148	0.812426
85	0.172942	0.345884	0.827058
86	0.153641	0.307283	0.846359
87	0.135641	0.271281	0.864359
88	0.122411	0.244822	0.877589
89	0.115401	0.230802	0.884599
90	0.120765	0.241531	0.879235
91	0.127695	0.255389	0.872305
92	0.225512	0.451023	0.774488
93	0.226695	0.453389	0.773305
94	0.222758	0.445516	0.777242
95	0.243048	0.486096	0.756952
96	0.23661	0.47322	0.76339
97	0.31748	0.634959	0.68252
98	0.310295	0.620589	0.689705
99	0.348339	0.696678	0.651661
100	0.402482	0.804964	0.597518
101	0.377194	0.754387	0.622806
102	0.360936	0.721872	0.639064
103	0.361603	0.723206	0.638397
104	0.374711	0.749423	0.625289
105	0.406136	0.812272	0.593864
106	0.421745	0.84349	0.578255
107	0.453223	0.906446	0.546777
108	0.659391	0.681219	0.340609
109	0.696648	0.606704	0.303352
110	0.706716	0.586568	0.293284
111	0.705512	0.588976	0.294488
112	0.697438	0.605124	0.302562
113	0.770197	0.459606	0.229803
114	0.751621	0.496758	0.248379
115	0.856121	0.287758	0.143879
116	0.902972	0.194056	0.0970282
117	0.894115	0.211769	0.105885
118	0.931819	0.136362	0.0681809
119	0.930125	0.139749	0.0698747
120	0.945507	0.108987	0.0544933
121	0.954646	0.090709	0.0453545
122	0.962493	0.0750137	0.0375069
123	0.963762	0.0724759	0.0362379
124	0.979351	0.0412971	0.0206485
125	0.982292	0.0354165	0.0177083
126	0.978995	0.0420092	0.0210046
127	0.977977	0.0440459	0.0220229
128	0.974699	0.0506026	0.0253013
129	0.973409	0.0531827	0.0265913
130	0.97104	0.0579195	0.0289598
131	0.970467	0.0590657	0.0295328
132	0.96828	0.0634406	0.0317203
133	0.972292	0.0554163	0.0277082
134	0.968395	0.06321	0.031605
135	0.962162	0.0756758	0.0378379
136	0.956002	0.0879956	0.0439978
137	0.966849	0.0663029	0.0331514
138	0.966573	0.0668549	0.0334274
139	0.963492	0.0730151	0.0365076
140	0.956904	0.0861919	0.0430959
141	0.950016	0.0999682	0.0499841
142	0.975972	0.0480559	0.024028
143	0.975617	0.0487658	0.0243829
144	0.975635	0.0487309	0.0243655
145	0.972124	0.0557515	0.0278757
146	0.972495	0.0550103	0.0275051
147	0.969949	0.0601014	0.0300507
148	0.965326	0.0693471	0.0346736
149	0.959996	0.0800088	0.0400044
150	0.957485	0.0850291	0.0425145
151	0.982079	0.0358426	0.0179213
152	0.979957	0.0400864	0.0200432
153	0.97983	0.0403398	0.0201699
154	0.975376	0.0492477	0.0246238
155	0.974945	0.0501104	0.0250552
156	0.97024	0.0595195	0.0297598
157	0.968304	0.0633925	0.0316963
158	0.96322	0.0735606	0.0367803
159	0.96395	0.0721009	0.0360504
160	0.9578	0.0844002	0.0422001
161	0.967799	0.0644023	0.0322012
162	0.962155	0.0756901	0.0378451
163	0.962677	0.0746462	0.0373231
164	0.990466	0.0190689	0.00953445
165	0.99107	0.0178608	0.00893041
166	0.988788	0.022424	0.011212
167	0.988396	0.0232083	0.0116041
168	0.991679	0.0166414	0.00832071
169	0.989353	0.0212939	0.010647
170	0.989521	0.0209585	0.0104792
171	0.987296	0.0254082	0.0127041
172	0.991109	0.0177811	0.00889053
173	0.989853	0.0202943	0.0101471
174	0.987233	0.0255349	0.0127674
175	0.984095	0.031809	0.0159045
176	0.987245	0.0255105	0.0127552
177	0.985946	0.0281072	0.0140536
178	0.986577	0.0268463	0.0134231
179	0.984885	0.030229	0.0151145
180	0.987221	0.0255577	0.0127789
181	0.986505	0.0269902	0.0134951
182	0.983798	0.0324038	0.0162019
183	0.981085	0.0378295	0.0189147
184	0.977381	0.0452382	0.0226191
185	0.974166	0.0516672	0.0258336
186	0.969467	0.0610656	0.0305328
187	0.98179	0.0364193	0.0182097
188	0.977858	0.0442833	0.0221417
189	0.973433	0.0531344	0.0265672
190	0.967375	0.06525	0.032625
191	0.961676	0.0766488	0.0383244
192	0.958094	0.0838121	0.041906
193	0.954247	0.0915067	0.0457534
194	0.972442	0.0551153	0.0275577
195	0.967035	0.0659295	0.0329648
196	0.963057	0.0738866	0.0369433
197	0.963904	0.0721915	0.0360957
198	0.955641	0.088719	0.0443595
199	0.957534	0.0849319	0.042466
200	0.955814	0.0883729	0.0441865
201	0.94732	0.105361	0.0526803
202	0.941529	0.116941	0.0584705
203	0.93492	0.13016	0.0650798
204	0.922233	0.155533	0.0777666
205	0.908206	0.183588	0.0917939
206	0.926578	0.146845	0.0734225
207	0.917257	0.165486	0.0827432
208	0.911894	0.176211	0.0881057
209	0.914321	0.171358	0.0856791
210	0.90437	0.19126	0.0956299
211	0.886748	0.226504	0.113252
212	0.8682	0.2636	0.1318
213	0.883364	0.233271	0.116636
214	0.866521	0.266958	0.133479
215	0.8601	0.279801	0.1399
216	0.838866	0.322267	0.161134
217	0.837314	0.325373	0.162686
218	0.819869	0.360262	0.180131
219	0.788419	0.423162	0.211581
220	0.754987	0.490027	0.245013
221	0.740106	0.519787	0.259894
222	0.76776	0.46448	0.23224
223	0.733417	0.533167	0.266583
224	0.751675	0.49665	0.248325
225	0.738193	0.523615	0.261807
226	0.826095	0.34781	0.173905
227	0.851827	0.296345	0.148173
228	0.84589	0.308219	0.15411
229	0.82337	0.35326	0.17663
230	0.851708	0.296584	0.148292
231	0.901978	0.196044	0.0980218
232	0.878945	0.242109	0.121055
233	0.855534	0.288932	0.144466
234	0.835331	0.329339	0.164669
235	0.809046	0.381907	0.190954
236	0.935438	0.129123	0.0645616
237	0.935587	0.128825	0.0644126
238	0.931609	0.136781	0.0683906
239	0.916916	0.166169	0.0830844
240	0.89255	0.2149	0.10745
241	0.892995	0.214011	0.107005
242	0.863086	0.273828	0.136914
243	0.844494	0.311011	0.155506
244	0.821056	0.357887	0.178944
245	0.780129	0.439742	0.219871
246	0.731319	0.537362	0.268681
247	0.690144	0.619712	0.309856
248	0.656171	0.687657	0.343829
249	0.614213	0.771575	0.385787
250	0.55553	0.88894	0.44447
251	0.492974	0.985948	0.507026
252	0.485952	0.971903	0.514048
253	0.41201	0.82402	0.58799
254	0.567588	0.864824	0.432412
255	0.494648	0.989295	0.505352
256	0.429356	0.858713	0.570644
257	0.45998	0.91996	0.54002
258	0.988884	0.0222313	0.0111156
259	0.997279	0.00544175	0.00272087
260	0.998959	0.00208205	0.00104102
261	0.998007	0.0039853	0.00199265
262	0.998063	0.00387361	0.00193681
263	0.99704	0.00592065	0.00296032
264	0.99741	0.00518059	0.00259029
265	0.991175	0.0176498	0.00882488

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.675588 & 0.648825 & 0.324412 \tabularnewline
14 & 0.538871 & 0.922257 & 0.461129 \tabularnewline
15 & 0.484189 & 0.968378 & 0.515811 \tabularnewline
16 & 0.359679 & 0.719359 & 0.640321 \tabularnewline
17 & 0.297055 & 0.594111 & 0.702945 \tabularnewline
18 & 0.209613 & 0.419226 & 0.790387 \tabularnewline
19 & 0.150024 & 0.300048 & 0.849976 \tabularnewline
20 & 0.102705 & 0.20541 & 0.897295 \tabularnewline
21 & 0.0968817 & 0.193763 & 0.903118 \tabularnewline
22 & 0.0806714 & 0.161343 & 0.919329 \tabularnewline
23 & 0.0626475 & 0.125295 & 0.937352 \tabularnewline
24 & 0.0529773 & 0.105955 & 0.947023 \tabularnewline
25 & 0.0378934 & 0.0757869 & 0.962107 \tabularnewline
26 & 0.0252636 & 0.0505272 & 0.974736 \tabularnewline
27 & 0.0162378 & 0.0324757 & 0.983762 \tabularnewline
28 & 0.013289 & 0.0265779 & 0.986711 \tabularnewline
29 & 0.00844492 & 0.0168898 & 0.991555 \tabularnewline
30 & 0.00792825 & 0.0158565 & 0.992072 \tabularnewline
31 & 0.0121654 & 0.0243307 & 0.987835 \tabularnewline
32 & 0.00837248 & 0.016745 & 0.991628 \tabularnewline
33 & 0.00612945 & 0.0122589 & 0.993871 \tabularnewline
34 & 0.00530235 & 0.0106047 & 0.994698 \tabularnewline
35 & 0.00337522 & 0.00675045 & 0.996625 \tabularnewline
36 & 0.00413464 & 0.00826928 & 0.995865 \tabularnewline
37 & 0.00324999 & 0.00649997 & 0.99675 \tabularnewline
38 & 0.00337865 & 0.0067573 & 0.996621 \tabularnewline
39 & 0.00942599 & 0.018852 & 0.990574 \tabularnewline
40 & 0.00799467 & 0.0159893 & 0.992005 \tabularnewline
41 & 0.0178932 & 0.0357865 & 0.982107 \tabularnewline
42 & 0.017331 & 0.034662 & 0.982669 \tabularnewline
43 & 0.0137578 & 0.0275156 & 0.986242 \tabularnewline
44 & 0.0103885 & 0.0207771 & 0.989611 \tabularnewline
45 & 0.00917149 & 0.018343 & 0.990829 \tabularnewline
46 & 0.00750557 & 0.0150111 & 0.992494 \tabularnewline
47 & 0.0062263 & 0.0124526 & 0.993774 \tabularnewline
48 & 0.00529851 & 0.010597 & 0.994701 \tabularnewline
49 & 0.0100259 & 0.0200517 & 0.989974 \tabularnewline
50 & 0.0156638 & 0.0313276 & 0.984336 \tabularnewline
51 & 0.0135916 & 0.0271831 & 0.986408 \tabularnewline
52 & 0.0143032 & 0.0286064 & 0.985697 \tabularnewline
53 & 0.0134469 & 0.0268938 & 0.986553 \tabularnewline
54 & 0.016 & 0.0320001 & 0.984 \tabularnewline
55 & 0.0313226 & 0.0626453 & 0.968677 \tabularnewline
56 & 0.0259389 & 0.0518778 & 0.974061 \tabularnewline
57 & 0.0901712 & 0.180342 & 0.909829 \tabularnewline
58 & 0.0872827 & 0.174565 & 0.912717 \tabularnewline
59 & 0.073227 & 0.146454 & 0.926773 \tabularnewline
60 & 0.0772639 & 0.154528 & 0.922736 \tabularnewline
61 & 0.0898542 & 0.179708 & 0.910146 \tabularnewline
62 & 0.0819949 & 0.16399 & 0.918005 \tabularnewline
63 & 0.160227 & 0.320453 & 0.839773 \tabularnewline
64 & 0.188128 & 0.376256 & 0.811872 \tabularnewline
65 & 0.202369 & 0.404738 & 0.797631 \tabularnewline
66 & 0.178457 & 0.356915 & 0.821543 \tabularnewline
67 & 0.175803 & 0.351605 & 0.824197 \tabularnewline
68 & 0.163325 & 0.326649 & 0.836675 \tabularnewline
69 & 0.168733 & 0.337466 & 0.831267 \tabularnewline
70 & 0.15218 & 0.304361 & 0.84782 \tabularnewline
71 & 0.142134 & 0.284268 & 0.857866 \tabularnewline
72 & 0.127094 & 0.254188 & 0.872906 \tabularnewline
73 & 0.115493 & 0.230986 & 0.884507 \tabularnewline
74 & 0.135848 & 0.271696 & 0.864152 \tabularnewline
75 & 0.120883 & 0.241765 & 0.879117 \tabularnewline
76 & 0.10723 & 0.21446 & 0.89277 \tabularnewline
77 & 0.0959077 & 0.191815 & 0.904092 \tabularnewline
78 & 0.103926 & 0.207853 & 0.896074 \tabularnewline
79 & 0.0876104 & 0.175221 & 0.91239 \tabularnewline
80 & 0.11174 & 0.22348 & 0.88826 \tabularnewline
81 & 0.0951421 & 0.190284 & 0.904858 \tabularnewline
82 & 0.112962 & 0.225923 & 0.887038 \tabularnewline
83 & 0.0970748 & 0.19415 & 0.902925 \tabularnewline
84 & 0.187574 & 0.375148 & 0.812426 \tabularnewline
85 & 0.172942 & 0.345884 & 0.827058 \tabularnewline
86 & 0.153641 & 0.307283 & 0.846359 \tabularnewline
87 & 0.135641 & 0.271281 & 0.864359 \tabularnewline
88 & 0.122411 & 0.244822 & 0.877589 \tabularnewline
89 & 0.115401 & 0.230802 & 0.884599 \tabularnewline
90 & 0.120765 & 0.241531 & 0.879235 \tabularnewline
91 & 0.127695 & 0.255389 & 0.872305 \tabularnewline
92 & 0.225512 & 0.451023 & 0.774488 \tabularnewline
93 & 0.226695 & 0.453389 & 0.773305 \tabularnewline
94 & 0.222758 & 0.445516 & 0.777242 \tabularnewline
95 & 0.243048 & 0.486096 & 0.756952 \tabularnewline
96 & 0.23661 & 0.47322 & 0.76339 \tabularnewline
97 & 0.31748 & 0.634959 & 0.68252 \tabularnewline
98 & 0.310295 & 0.620589 & 0.689705 \tabularnewline
99 & 0.348339 & 0.696678 & 0.651661 \tabularnewline
100 & 0.402482 & 0.804964 & 0.597518 \tabularnewline
101 & 0.377194 & 0.754387 & 0.622806 \tabularnewline
102 & 0.360936 & 0.721872 & 0.639064 \tabularnewline
103 & 0.361603 & 0.723206 & 0.638397 \tabularnewline
104 & 0.374711 & 0.749423 & 0.625289 \tabularnewline
105 & 0.406136 & 0.812272 & 0.593864 \tabularnewline
106 & 0.421745 & 0.84349 & 0.578255 \tabularnewline
107 & 0.453223 & 0.906446 & 0.546777 \tabularnewline
108 & 0.659391 & 0.681219 & 0.340609 \tabularnewline
109 & 0.696648 & 0.606704 & 0.303352 \tabularnewline
110 & 0.706716 & 0.586568 & 0.293284 \tabularnewline
111 & 0.705512 & 0.588976 & 0.294488 \tabularnewline
112 & 0.697438 & 0.605124 & 0.302562 \tabularnewline
113 & 0.770197 & 0.459606 & 0.229803 \tabularnewline
114 & 0.751621 & 0.496758 & 0.248379 \tabularnewline
115 & 0.856121 & 0.287758 & 0.143879 \tabularnewline
116 & 0.902972 & 0.194056 & 0.0970282 \tabularnewline
117 & 0.894115 & 0.211769 & 0.105885 \tabularnewline
118 & 0.931819 & 0.136362 & 0.0681809 \tabularnewline
119 & 0.930125 & 0.139749 & 0.0698747 \tabularnewline
120 & 0.945507 & 0.108987 & 0.0544933 \tabularnewline
121 & 0.954646 & 0.090709 & 0.0453545 \tabularnewline
122 & 0.962493 & 0.0750137 & 0.0375069 \tabularnewline
123 & 0.963762 & 0.0724759 & 0.0362379 \tabularnewline
124 & 0.979351 & 0.0412971 & 0.0206485 \tabularnewline
125 & 0.982292 & 0.0354165 & 0.0177083 \tabularnewline
126 & 0.978995 & 0.0420092 & 0.0210046 \tabularnewline
127 & 0.977977 & 0.0440459 & 0.0220229 \tabularnewline
128 & 0.974699 & 0.0506026 & 0.0253013 \tabularnewline
129 & 0.973409 & 0.0531827 & 0.0265913 \tabularnewline
130 & 0.97104 & 0.0579195 & 0.0289598 \tabularnewline
131 & 0.970467 & 0.0590657 & 0.0295328 \tabularnewline
132 & 0.96828 & 0.0634406 & 0.0317203 \tabularnewline
133 & 0.972292 & 0.0554163 & 0.0277082 \tabularnewline
134 & 0.968395 & 0.06321 & 0.031605 \tabularnewline
135 & 0.962162 & 0.0756758 & 0.0378379 \tabularnewline
136 & 0.956002 & 0.0879956 & 0.0439978 \tabularnewline
137 & 0.966849 & 0.0663029 & 0.0331514 \tabularnewline
138 & 0.966573 & 0.0668549 & 0.0334274 \tabularnewline
139 & 0.963492 & 0.0730151 & 0.0365076 \tabularnewline
140 & 0.956904 & 0.0861919 & 0.0430959 \tabularnewline
141 & 0.950016 & 0.0999682 & 0.0499841 \tabularnewline
142 & 0.975972 & 0.0480559 & 0.024028 \tabularnewline
143 & 0.975617 & 0.0487658 & 0.0243829 \tabularnewline
144 & 0.975635 & 0.0487309 & 0.0243655 \tabularnewline
145 & 0.972124 & 0.0557515 & 0.0278757 \tabularnewline
146 & 0.972495 & 0.0550103 & 0.0275051 \tabularnewline
147 & 0.969949 & 0.0601014 & 0.0300507 \tabularnewline
148 & 0.965326 & 0.0693471 & 0.0346736 \tabularnewline
149 & 0.959996 & 0.0800088 & 0.0400044 \tabularnewline
150 & 0.957485 & 0.0850291 & 0.0425145 \tabularnewline
151 & 0.982079 & 0.0358426 & 0.0179213 \tabularnewline
152 & 0.979957 & 0.0400864 & 0.0200432 \tabularnewline
153 & 0.97983 & 0.0403398 & 0.0201699 \tabularnewline
154 & 0.975376 & 0.0492477 & 0.0246238 \tabularnewline
155 & 0.974945 & 0.0501104 & 0.0250552 \tabularnewline
156 & 0.97024 & 0.0595195 & 0.0297598 \tabularnewline
157 & 0.968304 & 0.0633925 & 0.0316963 \tabularnewline
158 & 0.96322 & 0.0735606 & 0.0367803 \tabularnewline
159 & 0.96395 & 0.0721009 & 0.0360504 \tabularnewline
160 & 0.9578 & 0.0844002 & 0.0422001 \tabularnewline
161 & 0.967799 & 0.0644023 & 0.0322012 \tabularnewline
162 & 0.962155 & 0.0756901 & 0.0378451 \tabularnewline
163 & 0.962677 & 0.0746462 & 0.0373231 \tabularnewline
164 & 0.990466 & 0.0190689 & 0.00953445 \tabularnewline
165 & 0.99107 & 0.0178608 & 0.00893041 \tabularnewline
166 & 0.988788 & 0.022424 & 0.011212 \tabularnewline
167 & 0.988396 & 0.0232083 & 0.0116041 \tabularnewline
168 & 0.991679 & 0.0166414 & 0.00832071 \tabularnewline
169 & 0.989353 & 0.0212939 & 0.010647 \tabularnewline
170 & 0.989521 & 0.0209585 & 0.0104792 \tabularnewline
171 & 0.987296 & 0.0254082 & 0.0127041 \tabularnewline
172 & 0.991109 & 0.0177811 & 0.00889053 \tabularnewline
173 & 0.989853 & 0.0202943 & 0.0101471 \tabularnewline
174 & 0.987233 & 0.0255349 & 0.0127674 \tabularnewline
175 & 0.984095 & 0.031809 & 0.0159045 \tabularnewline
176 & 0.987245 & 0.0255105 & 0.0127552 \tabularnewline
177 & 0.985946 & 0.0281072 & 0.0140536 \tabularnewline
178 & 0.986577 & 0.0268463 & 0.0134231 \tabularnewline
179 & 0.984885 & 0.030229 & 0.0151145 \tabularnewline
180 & 0.987221 & 0.0255577 & 0.0127789 \tabularnewline
181 & 0.986505 & 0.0269902 & 0.0134951 \tabularnewline
182 & 0.983798 & 0.0324038 & 0.0162019 \tabularnewline
183 & 0.981085 & 0.0378295 & 0.0189147 \tabularnewline
184 & 0.977381 & 0.0452382 & 0.0226191 \tabularnewline
185 & 0.974166 & 0.0516672 & 0.0258336 \tabularnewline
186 & 0.969467 & 0.0610656 & 0.0305328 \tabularnewline
187 & 0.98179 & 0.0364193 & 0.0182097 \tabularnewline
188 & 0.977858 & 0.0442833 & 0.0221417 \tabularnewline
189 & 0.973433 & 0.0531344 & 0.0265672 \tabularnewline
190 & 0.967375 & 0.06525 & 0.032625 \tabularnewline
191 & 0.961676 & 0.0766488 & 0.0383244 \tabularnewline
192 & 0.958094 & 0.0838121 & 0.041906 \tabularnewline
193 & 0.954247 & 0.0915067 & 0.0457534 \tabularnewline
194 & 0.972442 & 0.0551153 & 0.0275577 \tabularnewline
195 & 0.967035 & 0.0659295 & 0.0329648 \tabularnewline
196 & 0.963057 & 0.0738866 & 0.0369433 \tabularnewline
197 & 0.963904 & 0.0721915 & 0.0360957 \tabularnewline
198 & 0.955641 & 0.088719 & 0.0443595 \tabularnewline
199 & 0.957534 & 0.0849319 & 0.042466 \tabularnewline
200 & 0.955814 & 0.0883729 & 0.0441865 \tabularnewline
201 & 0.94732 & 0.105361 & 0.0526803 \tabularnewline
202 & 0.941529 & 0.116941 & 0.0584705 \tabularnewline
203 & 0.93492 & 0.13016 & 0.0650798 \tabularnewline
204 & 0.922233 & 0.155533 & 0.0777666 \tabularnewline
205 & 0.908206 & 0.183588 & 0.0917939 \tabularnewline
206 & 0.926578 & 0.146845 & 0.0734225 \tabularnewline
207 & 0.917257 & 0.165486 & 0.0827432 \tabularnewline
208 & 0.911894 & 0.176211 & 0.0881057 \tabularnewline
209 & 0.914321 & 0.171358 & 0.0856791 \tabularnewline
210 & 0.90437 & 0.19126 & 0.0956299 \tabularnewline
211 & 0.886748 & 0.226504 & 0.113252 \tabularnewline
212 & 0.8682 & 0.2636 & 0.1318 \tabularnewline
213 & 0.883364 & 0.233271 & 0.116636 \tabularnewline
214 & 0.866521 & 0.266958 & 0.133479 \tabularnewline
215 & 0.8601 & 0.279801 & 0.1399 \tabularnewline
216 & 0.838866 & 0.322267 & 0.161134 \tabularnewline
217 & 0.837314 & 0.325373 & 0.162686 \tabularnewline
218 & 0.819869 & 0.360262 & 0.180131 \tabularnewline
219 & 0.788419 & 0.423162 & 0.211581 \tabularnewline
220 & 0.754987 & 0.490027 & 0.245013 \tabularnewline
221 & 0.740106 & 0.519787 & 0.259894 \tabularnewline
222 & 0.76776 & 0.46448 & 0.23224 \tabularnewline
223 & 0.733417 & 0.533167 & 0.266583 \tabularnewline
224 & 0.751675 & 0.49665 & 0.248325 \tabularnewline
225 & 0.738193 & 0.523615 & 0.261807 \tabularnewline
226 & 0.826095 & 0.34781 & 0.173905 \tabularnewline
227 & 0.851827 & 0.296345 & 0.148173 \tabularnewline
228 & 0.84589 & 0.308219 & 0.15411 \tabularnewline
229 & 0.82337 & 0.35326 & 0.17663 \tabularnewline
230 & 0.851708 & 0.296584 & 0.148292 \tabularnewline
231 & 0.901978 & 0.196044 & 0.0980218 \tabularnewline
232 & 0.878945 & 0.242109 & 0.121055 \tabularnewline
233 & 0.855534 & 0.288932 & 0.144466 \tabularnewline
234 & 0.835331 & 0.329339 & 0.164669 \tabularnewline
235 & 0.809046 & 0.381907 & 0.190954 \tabularnewline
236 & 0.935438 & 0.129123 & 0.0645616 \tabularnewline
237 & 0.935587 & 0.128825 & 0.0644126 \tabularnewline
238 & 0.931609 & 0.136781 & 0.0683906 \tabularnewline
239 & 0.916916 & 0.166169 & 0.0830844 \tabularnewline
240 & 0.89255 & 0.2149 & 0.10745 \tabularnewline
241 & 0.892995 & 0.214011 & 0.107005 \tabularnewline
242 & 0.863086 & 0.273828 & 0.136914 \tabularnewline
243 & 0.844494 & 0.311011 & 0.155506 \tabularnewline
244 & 0.821056 & 0.357887 & 0.178944 \tabularnewline
245 & 0.780129 & 0.439742 & 0.219871 \tabularnewline
246 & 0.731319 & 0.537362 & 0.268681 \tabularnewline
247 & 0.690144 & 0.619712 & 0.309856 \tabularnewline
248 & 0.656171 & 0.687657 & 0.343829 \tabularnewline
249 & 0.614213 & 0.771575 & 0.385787 \tabularnewline
250 & 0.55553 & 0.88894 & 0.44447 \tabularnewline
251 & 0.492974 & 0.985948 & 0.507026 \tabularnewline
252 & 0.485952 & 0.971903 & 0.514048 \tabularnewline
253 & 0.41201 & 0.82402 & 0.58799 \tabularnewline
254 & 0.567588 & 0.864824 & 0.432412 \tabularnewline
255 & 0.494648 & 0.989295 & 0.505352 \tabularnewline
256 & 0.429356 & 0.858713 & 0.570644 \tabularnewline
257 & 0.45998 & 0.91996 & 0.54002 \tabularnewline
258 & 0.988884 & 0.0222313 & 0.0111156 \tabularnewline
259 & 0.997279 & 0.00544175 & 0.00272087 \tabularnewline
260 & 0.998959 & 0.00208205 & 0.00104102 \tabularnewline
261 & 0.998007 & 0.0039853 & 0.00199265 \tabularnewline
262 & 0.998063 & 0.00387361 & 0.00193681 \tabularnewline
263 & 0.99704 & 0.00592065 & 0.00296032 \tabularnewline
264 & 0.99741 & 0.00518059 & 0.00259029 \tabularnewline
265 & 0.991175 & 0.0176498 & 0.00882488 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271106&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]13[/C][C]0.675588[/C][C]0.648825[/C][C]0.324412[/C][/ROW]
[ROW][C]14[/C][C]0.538871[/C][C]0.922257[/C][C]0.461129[/C][/ROW]
[ROW][C]15[/C][C]0.484189[/C][C]0.968378[/C][C]0.515811[/C][/ROW]
[ROW][C]16[/C][C]0.359679[/C][C]0.719359[/C][C]0.640321[/C][/ROW]
[ROW][C]17[/C][C]0.297055[/C][C]0.594111[/C][C]0.702945[/C][/ROW]
[ROW][C]18[/C][C]0.209613[/C][C]0.419226[/C][C]0.790387[/C][/ROW]
[ROW][C]19[/C][C]0.150024[/C][C]0.300048[/C][C]0.849976[/C][/ROW]
[ROW][C]20[/C][C]0.102705[/C][C]0.20541[/C][C]0.897295[/C][/ROW]
[ROW][C]21[/C][C]0.0968817[/C][C]0.193763[/C][C]0.903118[/C][/ROW]
[ROW][C]22[/C][C]0.0806714[/C][C]0.161343[/C][C]0.919329[/C][/ROW]
[ROW][C]23[/C][C]0.0626475[/C][C]0.125295[/C][C]0.937352[/C][/ROW]
[ROW][C]24[/C][C]0.0529773[/C][C]0.105955[/C][C]0.947023[/C][/ROW]
[ROW][C]25[/C][C]0.0378934[/C][C]0.0757869[/C][C]0.962107[/C][/ROW]
[ROW][C]26[/C][C]0.0252636[/C][C]0.0505272[/C][C]0.974736[/C][/ROW]
[ROW][C]27[/C][C]0.0162378[/C][C]0.0324757[/C][C]0.983762[/C][/ROW]
[ROW][C]28[/C][C]0.013289[/C][C]0.0265779[/C][C]0.986711[/C][/ROW]
[ROW][C]29[/C][C]0.00844492[/C][C]0.0168898[/C][C]0.991555[/C][/ROW]
[ROW][C]30[/C][C]0.00792825[/C][C]0.0158565[/C][C]0.992072[/C][/ROW]
[ROW][C]31[/C][C]0.0121654[/C][C]0.0243307[/C][C]0.987835[/C][/ROW]
[ROW][C]32[/C][C]0.00837248[/C][C]0.016745[/C][C]0.991628[/C][/ROW]
[ROW][C]33[/C][C]0.00612945[/C][C]0.0122589[/C][C]0.993871[/C][/ROW]
[ROW][C]34[/C][C]0.00530235[/C][C]0.0106047[/C][C]0.994698[/C][/ROW]
[ROW][C]35[/C][C]0.00337522[/C][C]0.00675045[/C][C]0.996625[/C][/ROW]
[ROW][C]36[/C][C]0.00413464[/C][C]0.00826928[/C][C]0.995865[/C][/ROW]
[ROW][C]37[/C][C]0.00324999[/C][C]0.00649997[/C][C]0.99675[/C][/ROW]
[ROW][C]38[/C][C]0.00337865[/C][C]0.0067573[/C][C]0.996621[/C][/ROW]
[ROW][C]39[/C][C]0.00942599[/C][C]0.018852[/C][C]0.990574[/C][/ROW]
[ROW][C]40[/C][C]0.00799467[/C][C]0.0159893[/C][C]0.992005[/C][/ROW]
[ROW][C]41[/C][C]0.0178932[/C][C]0.0357865[/C][C]0.982107[/C][/ROW]
[ROW][C]42[/C][C]0.017331[/C][C]0.034662[/C][C]0.982669[/C][/ROW]
[ROW][C]43[/C][C]0.0137578[/C][C]0.0275156[/C][C]0.986242[/C][/ROW]
[ROW][C]44[/C][C]0.0103885[/C][C]0.0207771[/C][C]0.989611[/C][/ROW]
[ROW][C]45[/C][C]0.00917149[/C][C]0.018343[/C][C]0.990829[/C][/ROW]
[ROW][C]46[/C][C]0.00750557[/C][C]0.0150111[/C][C]0.992494[/C][/ROW]
[ROW][C]47[/C][C]0.0062263[/C][C]0.0124526[/C][C]0.993774[/C][/ROW]
[ROW][C]48[/C][C]0.00529851[/C][C]0.010597[/C][C]0.994701[/C][/ROW]
[ROW][C]49[/C][C]0.0100259[/C][C]0.0200517[/C][C]0.989974[/C][/ROW]
[ROW][C]50[/C][C]0.0156638[/C][C]0.0313276[/C][C]0.984336[/C][/ROW]
[ROW][C]51[/C][C]0.0135916[/C][C]0.0271831[/C][C]0.986408[/C][/ROW]
[ROW][C]52[/C][C]0.0143032[/C][C]0.0286064[/C][C]0.985697[/C][/ROW]
[ROW][C]53[/C][C]0.0134469[/C][C]0.0268938[/C][C]0.986553[/C][/ROW]
[ROW][C]54[/C][C]0.016[/C][C]0.0320001[/C][C]0.984[/C][/ROW]
[ROW][C]55[/C][C]0.0313226[/C][C]0.0626453[/C][C]0.968677[/C][/ROW]
[ROW][C]56[/C][C]0.0259389[/C][C]0.0518778[/C][C]0.974061[/C][/ROW]
[ROW][C]57[/C][C]0.0901712[/C][C]0.180342[/C][C]0.909829[/C][/ROW]
[ROW][C]58[/C][C]0.0872827[/C][C]0.174565[/C][C]0.912717[/C][/ROW]
[ROW][C]59[/C][C]0.073227[/C][C]0.146454[/C][C]0.926773[/C][/ROW]
[ROW][C]60[/C][C]0.0772639[/C][C]0.154528[/C][C]0.922736[/C][/ROW]
[ROW][C]61[/C][C]0.0898542[/C][C]0.179708[/C][C]0.910146[/C][/ROW]
[ROW][C]62[/C][C]0.0819949[/C][C]0.16399[/C][C]0.918005[/C][/ROW]
[ROW][C]63[/C][C]0.160227[/C][C]0.320453[/C][C]0.839773[/C][/ROW]
[ROW][C]64[/C][C]0.188128[/C][C]0.376256[/C][C]0.811872[/C][/ROW]
[ROW][C]65[/C][C]0.202369[/C][C]0.404738[/C][C]0.797631[/C][/ROW]
[ROW][C]66[/C][C]0.178457[/C][C]0.356915[/C][C]0.821543[/C][/ROW]
[ROW][C]67[/C][C]0.175803[/C][C]0.351605[/C][C]0.824197[/C][/ROW]
[ROW][C]68[/C][C]0.163325[/C][C]0.326649[/C][C]0.836675[/C][/ROW]
[ROW][C]69[/C][C]0.168733[/C][C]0.337466[/C][C]0.831267[/C][/ROW]
[ROW][C]70[/C][C]0.15218[/C][C]0.304361[/C][C]0.84782[/C][/ROW]
[ROW][C]71[/C][C]0.142134[/C][C]0.284268[/C][C]0.857866[/C][/ROW]
[ROW][C]72[/C][C]0.127094[/C][C]0.254188[/C][C]0.872906[/C][/ROW]
[ROW][C]73[/C][C]0.115493[/C][C]0.230986[/C][C]0.884507[/C][/ROW]
[ROW][C]74[/C][C]0.135848[/C][C]0.271696[/C][C]0.864152[/C][/ROW]
[ROW][C]75[/C][C]0.120883[/C][C]0.241765[/C][C]0.879117[/C][/ROW]
[ROW][C]76[/C][C]0.10723[/C][C]0.21446[/C][C]0.89277[/C][/ROW]
[ROW][C]77[/C][C]0.0959077[/C][C]0.191815[/C][C]0.904092[/C][/ROW]
[ROW][C]78[/C][C]0.103926[/C][C]0.207853[/C][C]0.896074[/C][/ROW]
[ROW][C]79[/C][C]0.0876104[/C][C]0.175221[/C][C]0.91239[/C][/ROW]
[ROW][C]80[/C][C]0.11174[/C][C]0.22348[/C][C]0.88826[/C][/ROW]
[ROW][C]81[/C][C]0.0951421[/C][C]0.190284[/C][C]0.904858[/C][/ROW]
[ROW][C]82[/C][C]0.112962[/C][C]0.225923[/C][C]0.887038[/C][/ROW]
[ROW][C]83[/C][C]0.0970748[/C][C]0.19415[/C][C]0.902925[/C][/ROW]
[ROW][C]84[/C][C]0.187574[/C][C]0.375148[/C][C]0.812426[/C][/ROW]
[ROW][C]85[/C][C]0.172942[/C][C]0.345884[/C][C]0.827058[/C][/ROW]
[ROW][C]86[/C][C]0.153641[/C][C]0.307283[/C][C]0.846359[/C][/ROW]
[ROW][C]87[/C][C]0.135641[/C][C]0.271281[/C][C]0.864359[/C][/ROW]
[ROW][C]88[/C][C]0.122411[/C][C]0.244822[/C][C]0.877589[/C][/ROW]
[ROW][C]89[/C][C]0.115401[/C][C]0.230802[/C][C]0.884599[/C][/ROW]
[ROW][C]90[/C][C]0.120765[/C][C]0.241531[/C][C]0.879235[/C][/ROW]
[ROW][C]91[/C][C]0.127695[/C][C]0.255389[/C][C]0.872305[/C][/ROW]
[ROW][C]92[/C][C]0.225512[/C][C]0.451023[/C][C]0.774488[/C][/ROW]
[ROW][C]93[/C][C]0.226695[/C][C]0.453389[/C][C]0.773305[/C][/ROW]
[ROW][C]94[/C][C]0.222758[/C][C]0.445516[/C][C]0.777242[/C][/ROW]
[ROW][C]95[/C][C]0.243048[/C][C]0.486096[/C][C]0.756952[/C][/ROW]
[ROW][C]96[/C][C]0.23661[/C][C]0.47322[/C][C]0.76339[/C][/ROW]
[ROW][C]97[/C][C]0.31748[/C][C]0.634959[/C][C]0.68252[/C][/ROW]
[ROW][C]98[/C][C]0.310295[/C][C]0.620589[/C][C]0.689705[/C][/ROW]
[ROW][C]99[/C][C]0.348339[/C][C]0.696678[/C][C]0.651661[/C][/ROW]
[ROW][C]100[/C][C]0.402482[/C][C]0.804964[/C][C]0.597518[/C][/ROW]
[ROW][C]101[/C][C]0.377194[/C][C]0.754387[/C][C]0.622806[/C][/ROW]
[ROW][C]102[/C][C]0.360936[/C][C]0.721872[/C][C]0.639064[/C][/ROW]
[ROW][C]103[/C][C]0.361603[/C][C]0.723206[/C][C]0.638397[/C][/ROW]
[ROW][C]104[/C][C]0.374711[/C][C]0.749423[/C][C]0.625289[/C][/ROW]
[ROW][C]105[/C][C]0.406136[/C][C]0.812272[/C][C]0.593864[/C][/ROW]
[ROW][C]106[/C][C]0.421745[/C][C]0.84349[/C][C]0.578255[/C][/ROW]
[ROW][C]107[/C][C]0.453223[/C][C]0.906446[/C][C]0.546777[/C][/ROW]
[ROW][C]108[/C][C]0.659391[/C][C]0.681219[/C][C]0.340609[/C][/ROW]
[ROW][C]109[/C][C]0.696648[/C][C]0.606704[/C][C]0.303352[/C][/ROW]
[ROW][C]110[/C][C]0.706716[/C][C]0.586568[/C][C]0.293284[/C][/ROW]
[ROW][C]111[/C][C]0.705512[/C][C]0.588976[/C][C]0.294488[/C][/ROW]
[ROW][C]112[/C][C]0.697438[/C][C]0.605124[/C][C]0.302562[/C][/ROW]
[ROW][C]113[/C][C]0.770197[/C][C]0.459606[/C][C]0.229803[/C][/ROW]
[ROW][C]114[/C][C]0.751621[/C][C]0.496758[/C][C]0.248379[/C][/ROW]
[ROW][C]115[/C][C]0.856121[/C][C]0.287758[/C][C]0.143879[/C][/ROW]
[ROW][C]116[/C][C]0.902972[/C][C]0.194056[/C][C]0.0970282[/C][/ROW]
[ROW][C]117[/C][C]0.894115[/C][C]0.211769[/C][C]0.105885[/C][/ROW]
[ROW][C]118[/C][C]0.931819[/C][C]0.136362[/C][C]0.0681809[/C][/ROW]
[ROW][C]119[/C][C]0.930125[/C][C]0.139749[/C][C]0.0698747[/C][/ROW]
[ROW][C]120[/C][C]0.945507[/C][C]0.108987[/C][C]0.0544933[/C][/ROW]
[ROW][C]121[/C][C]0.954646[/C][C]0.090709[/C][C]0.0453545[/C][/ROW]
[ROW][C]122[/C][C]0.962493[/C][C]0.0750137[/C][C]0.0375069[/C][/ROW]
[ROW][C]123[/C][C]0.963762[/C][C]0.0724759[/C][C]0.0362379[/C][/ROW]
[ROW][C]124[/C][C]0.979351[/C][C]0.0412971[/C][C]0.0206485[/C][/ROW]
[ROW][C]125[/C][C]0.982292[/C][C]0.0354165[/C][C]0.0177083[/C][/ROW]
[ROW][C]126[/C][C]0.978995[/C][C]0.0420092[/C][C]0.0210046[/C][/ROW]
[ROW][C]127[/C][C]0.977977[/C][C]0.0440459[/C][C]0.0220229[/C][/ROW]
[ROW][C]128[/C][C]0.974699[/C][C]0.0506026[/C][C]0.0253013[/C][/ROW]
[ROW][C]129[/C][C]0.973409[/C][C]0.0531827[/C][C]0.0265913[/C][/ROW]
[ROW][C]130[/C][C]0.97104[/C][C]0.0579195[/C][C]0.0289598[/C][/ROW]
[ROW][C]131[/C][C]0.970467[/C][C]0.0590657[/C][C]0.0295328[/C][/ROW]
[ROW][C]132[/C][C]0.96828[/C][C]0.0634406[/C][C]0.0317203[/C][/ROW]
[ROW][C]133[/C][C]0.972292[/C][C]0.0554163[/C][C]0.0277082[/C][/ROW]
[ROW][C]134[/C][C]0.968395[/C][C]0.06321[/C][C]0.031605[/C][/ROW]
[ROW][C]135[/C][C]0.962162[/C][C]0.0756758[/C][C]0.0378379[/C][/ROW]
[ROW][C]136[/C][C]0.956002[/C][C]0.0879956[/C][C]0.0439978[/C][/ROW]
[ROW][C]137[/C][C]0.966849[/C][C]0.0663029[/C][C]0.0331514[/C][/ROW]
[ROW][C]138[/C][C]0.966573[/C][C]0.0668549[/C][C]0.0334274[/C][/ROW]
[ROW][C]139[/C][C]0.963492[/C][C]0.0730151[/C][C]0.0365076[/C][/ROW]
[ROW][C]140[/C][C]0.956904[/C][C]0.0861919[/C][C]0.0430959[/C][/ROW]
[ROW][C]141[/C][C]0.950016[/C][C]0.0999682[/C][C]0.0499841[/C][/ROW]
[ROW][C]142[/C][C]0.975972[/C][C]0.0480559[/C][C]0.024028[/C][/ROW]
[ROW][C]143[/C][C]0.975617[/C][C]0.0487658[/C][C]0.0243829[/C][/ROW]
[ROW][C]144[/C][C]0.975635[/C][C]0.0487309[/C][C]0.0243655[/C][/ROW]
[ROW][C]145[/C][C]0.972124[/C][C]0.0557515[/C][C]0.0278757[/C][/ROW]
[ROW][C]146[/C][C]0.972495[/C][C]0.0550103[/C][C]0.0275051[/C][/ROW]
[ROW][C]147[/C][C]0.969949[/C][C]0.0601014[/C][C]0.0300507[/C][/ROW]
[ROW][C]148[/C][C]0.965326[/C][C]0.0693471[/C][C]0.0346736[/C][/ROW]
[ROW][C]149[/C][C]0.959996[/C][C]0.0800088[/C][C]0.0400044[/C][/ROW]
[ROW][C]150[/C][C]0.957485[/C][C]0.0850291[/C][C]0.0425145[/C][/ROW]
[ROW][C]151[/C][C]0.982079[/C][C]0.0358426[/C][C]0.0179213[/C][/ROW]
[ROW][C]152[/C][C]0.979957[/C][C]0.0400864[/C][C]0.0200432[/C][/ROW]
[ROW][C]153[/C][C]0.97983[/C][C]0.0403398[/C][C]0.0201699[/C][/ROW]
[ROW][C]154[/C][C]0.975376[/C][C]0.0492477[/C][C]0.0246238[/C][/ROW]
[ROW][C]155[/C][C]0.974945[/C][C]0.0501104[/C][C]0.0250552[/C][/ROW]
[ROW][C]156[/C][C]0.97024[/C][C]0.0595195[/C][C]0.0297598[/C][/ROW]
[ROW][C]157[/C][C]0.968304[/C][C]0.0633925[/C][C]0.0316963[/C][/ROW]
[ROW][C]158[/C][C]0.96322[/C][C]0.0735606[/C][C]0.0367803[/C][/ROW]
[ROW][C]159[/C][C]0.96395[/C][C]0.0721009[/C][C]0.0360504[/C][/ROW]
[ROW][C]160[/C][C]0.9578[/C][C]0.0844002[/C][C]0.0422001[/C][/ROW]
[ROW][C]161[/C][C]0.967799[/C][C]0.0644023[/C][C]0.0322012[/C][/ROW]
[ROW][C]162[/C][C]0.962155[/C][C]0.0756901[/C][C]0.0378451[/C][/ROW]
[ROW][C]163[/C][C]0.962677[/C][C]0.0746462[/C][C]0.0373231[/C][/ROW]
[ROW][C]164[/C][C]0.990466[/C][C]0.0190689[/C][C]0.00953445[/C][/ROW]
[ROW][C]165[/C][C]0.99107[/C][C]0.0178608[/C][C]0.00893041[/C][/ROW]
[ROW][C]166[/C][C]0.988788[/C][C]0.022424[/C][C]0.011212[/C][/ROW]
[ROW][C]167[/C][C]0.988396[/C][C]0.0232083[/C][C]0.0116041[/C][/ROW]
[ROW][C]168[/C][C]0.991679[/C][C]0.0166414[/C][C]0.00832071[/C][/ROW]
[ROW][C]169[/C][C]0.989353[/C][C]0.0212939[/C][C]0.010647[/C][/ROW]
[ROW][C]170[/C][C]0.989521[/C][C]0.0209585[/C][C]0.0104792[/C][/ROW]
[ROW][C]171[/C][C]0.987296[/C][C]0.0254082[/C][C]0.0127041[/C][/ROW]
[ROW][C]172[/C][C]0.991109[/C][C]0.0177811[/C][C]0.00889053[/C][/ROW]
[ROW][C]173[/C][C]0.989853[/C][C]0.0202943[/C][C]0.0101471[/C][/ROW]
[ROW][C]174[/C][C]0.987233[/C][C]0.0255349[/C][C]0.0127674[/C][/ROW]
[ROW][C]175[/C][C]0.984095[/C][C]0.031809[/C][C]0.0159045[/C][/ROW]
[ROW][C]176[/C][C]0.987245[/C][C]0.0255105[/C][C]0.0127552[/C][/ROW]
[ROW][C]177[/C][C]0.985946[/C][C]0.0281072[/C][C]0.0140536[/C][/ROW]
[ROW][C]178[/C][C]0.986577[/C][C]0.0268463[/C][C]0.0134231[/C][/ROW]
[ROW][C]179[/C][C]0.984885[/C][C]0.030229[/C][C]0.0151145[/C][/ROW]
[ROW][C]180[/C][C]0.987221[/C][C]0.0255577[/C][C]0.0127789[/C][/ROW]
[ROW][C]181[/C][C]0.986505[/C][C]0.0269902[/C][C]0.0134951[/C][/ROW]
[ROW][C]182[/C][C]0.983798[/C][C]0.0324038[/C][C]0.0162019[/C][/ROW]
[ROW][C]183[/C][C]0.981085[/C][C]0.0378295[/C][C]0.0189147[/C][/ROW]
[ROW][C]184[/C][C]0.977381[/C][C]0.0452382[/C][C]0.0226191[/C][/ROW]
[ROW][C]185[/C][C]0.974166[/C][C]0.0516672[/C][C]0.0258336[/C][/ROW]
[ROW][C]186[/C][C]0.969467[/C][C]0.0610656[/C][C]0.0305328[/C][/ROW]
[ROW][C]187[/C][C]0.98179[/C][C]0.0364193[/C][C]0.0182097[/C][/ROW]
[ROW][C]188[/C][C]0.977858[/C][C]0.0442833[/C][C]0.0221417[/C][/ROW]
[ROW][C]189[/C][C]0.973433[/C][C]0.0531344[/C][C]0.0265672[/C][/ROW]
[ROW][C]190[/C][C]0.967375[/C][C]0.06525[/C][C]0.032625[/C][/ROW]
[ROW][C]191[/C][C]0.961676[/C][C]0.0766488[/C][C]0.0383244[/C][/ROW]
[ROW][C]192[/C][C]0.958094[/C][C]0.0838121[/C][C]0.041906[/C][/ROW]
[ROW][C]193[/C][C]0.954247[/C][C]0.0915067[/C][C]0.0457534[/C][/ROW]
[ROW][C]194[/C][C]0.972442[/C][C]0.0551153[/C][C]0.0275577[/C][/ROW]
[ROW][C]195[/C][C]0.967035[/C][C]0.0659295[/C][C]0.0329648[/C][/ROW]
[ROW][C]196[/C][C]0.963057[/C][C]0.0738866[/C][C]0.0369433[/C][/ROW]
[ROW][C]197[/C][C]0.963904[/C][C]0.0721915[/C][C]0.0360957[/C][/ROW]
[ROW][C]198[/C][C]0.955641[/C][C]0.088719[/C][C]0.0443595[/C][/ROW]
[ROW][C]199[/C][C]0.957534[/C][C]0.0849319[/C][C]0.042466[/C][/ROW]
[ROW][C]200[/C][C]0.955814[/C][C]0.0883729[/C][C]0.0441865[/C][/ROW]
[ROW][C]201[/C][C]0.94732[/C][C]0.105361[/C][C]0.0526803[/C][/ROW]
[ROW][C]202[/C][C]0.941529[/C][C]0.116941[/C][C]0.0584705[/C][/ROW]
[ROW][C]203[/C][C]0.93492[/C][C]0.13016[/C][C]0.0650798[/C][/ROW]
[ROW][C]204[/C][C]0.922233[/C][C]0.155533[/C][C]0.0777666[/C][/ROW]
[ROW][C]205[/C][C]0.908206[/C][C]0.183588[/C][C]0.0917939[/C][/ROW]
[ROW][C]206[/C][C]0.926578[/C][C]0.146845[/C][C]0.0734225[/C][/ROW]
[ROW][C]207[/C][C]0.917257[/C][C]0.165486[/C][C]0.0827432[/C][/ROW]
[ROW][C]208[/C][C]0.911894[/C][C]0.176211[/C][C]0.0881057[/C][/ROW]
[ROW][C]209[/C][C]0.914321[/C][C]0.171358[/C][C]0.0856791[/C][/ROW]
[ROW][C]210[/C][C]0.90437[/C][C]0.19126[/C][C]0.0956299[/C][/ROW]
[ROW][C]211[/C][C]0.886748[/C][C]0.226504[/C][C]0.113252[/C][/ROW]
[ROW][C]212[/C][C]0.8682[/C][C]0.2636[/C][C]0.1318[/C][/ROW]
[ROW][C]213[/C][C]0.883364[/C][C]0.233271[/C][C]0.116636[/C][/ROW]
[ROW][C]214[/C][C]0.866521[/C][C]0.266958[/C][C]0.133479[/C][/ROW]
[ROW][C]215[/C][C]0.8601[/C][C]0.279801[/C][C]0.1399[/C][/ROW]
[ROW][C]216[/C][C]0.838866[/C][C]0.322267[/C][C]0.161134[/C][/ROW]
[ROW][C]217[/C][C]0.837314[/C][C]0.325373[/C][C]0.162686[/C][/ROW]
[ROW][C]218[/C][C]0.819869[/C][C]0.360262[/C][C]0.180131[/C][/ROW]
[ROW][C]219[/C][C]0.788419[/C][C]0.423162[/C][C]0.211581[/C][/ROW]
[ROW][C]220[/C][C]0.754987[/C][C]0.490027[/C][C]0.245013[/C][/ROW]
[ROW][C]221[/C][C]0.740106[/C][C]0.519787[/C][C]0.259894[/C][/ROW]
[ROW][C]222[/C][C]0.76776[/C][C]0.46448[/C][C]0.23224[/C][/ROW]
[ROW][C]223[/C][C]0.733417[/C][C]0.533167[/C][C]0.266583[/C][/ROW]
[ROW][C]224[/C][C]0.751675[/C][C]0.49665[/C][C]0.248325[/C][/ROW]
[ROW][C]225[/C][C]0.738193[/C][C]0.523615[/C][C]0.261807[/C][/ROW]
[ROW][C]226[/C][C]0.826095[/C][C]0.34781[/C][C]0.173905[/C][/ROW]
[ROW][C]227[/C][C]0.851827[/C][C]0.296345[/C][C]0.148173[/C][/ROW]
[ROW][C]228[/C][C]0.84589[/C][C]0.308219[/C][C]0.15411[/C][/ROW]
[ROW][C]229[/C][C]0.82337[/C][C]0.35326[/C][C]0.17663[/C][/ROW]
[ROW][C]230[/C][C]0.851708[/C][C]0.296584[/C][C]0.148292[/C][/ROW]
[ROW][C]231[/C][C]0.901978[/C][C]0.196044[/C][C]0.0980218[/C][/ROW]
[ROW][C]232[/C][C]0.878945[/C][C]0.242109[/C][C]0.121055[/C][/ROW]
[ROW][C]233[/C][C]0.855534[/C][C]0.288932[/C][C]0.144466[/C][/ROW]
[ROW][C]234[/C][C]0.835331[/C][C]0.329339[/C][C]0.164669[/C][/ROW]
[ROW][C]235[/C][C]0.809046[/C][C]0.381907[/C][C]0.190954[/C][/ROW]
[ROW][C]236[/C][C]0.935438[/C][C]0.129123[/C][C]0.0645616[/C][/ROW]
[ROW][C]237[/C][C]0.935587[/C][C]0.128825[/C][C]0.0644126[/C][/ROW]
[ROW][C]238[/C][C]0.931609[/C][C]0.136781[/C][C]0.0683906[/C][/ROW]
[ROW][C]239[/C][C]0.916916[/C][C]0.166169[/C][C]0.0830844[/C][/ROW]
[ROW][C]240[/C][C]0.89255[/C][C]0.2149[/C][C]0.10745[/C][/ROW]
[ROW][C]241[/C][C]0.892995[/C][C]0.214011[/C][C]0.107005[/C][/ROW]
[ROW][C]242[/C][C]0.863086[/C][C]0.273828[/C][C]0.136914[/C][/ROW]
[ROW][C]243[/C][C]0.844494[/C][C]0.311011[/C][C]0.155506[/C][/ROW]
[ROW][C]244[/C][C]0.821056[/C][C]0.357887[/C][C]0.178944[/C][/ROW]
[ROW][C]245[/C][C]0.780129[/C][C]0.439742[/C][C]0.219871[/C][/ROW]
[ROW][C]246[/C][C]0.731319[/C][C]0.537362[/C][C]0.268681[/C][/ROW]
[ROW][C]247[/C][C]0.690144[/C][C]0.619712[/C][C]0.309856[/C][/ROW]
[ROW][C]248[/C][C]0.656171[/C][C]0.687657[/C][C]0.343829[/C][/ROW]
[ROW][C]249[/C][C]0.614213[/C][C]0.771575[/C][C]0.385787[/C][/ROW]
[ROW][C]250[/C][C]0.55553[/C][C]0.88894[/C][C]0.44447[/C][/ROW]
[ROW][C]251[/C][C]0.492974[/C][C]0.985948[/C][C]0.507026[/C][/ROW]
[ROW][C]252[/C][C]0.485952[/C][C]0.971903[/C][C]0.514048[/C][/ROW]
[ROW][C]253[/C][C]0.41201[/C][C]0.82402[/C][C]0.58799[/C][/ROW]
[ROW][C]254[/C][C]0.567588[/C][C]0.864824[/C][C]0.432412[/C][/ROW]
[ROW][C]255[/C][C]0.494648[/C][C]0.989295[/C][C]0.505352[/C][/ROW]
[ROW][C]256[/C][C]0.429356[/C][C]0.858713[/C][C]0.570644[/C][/ROW]
[ROW][C]257[/C][C]0.45998[/C][C]0.91996[/C][C]0.54002[/C][/ROW]
[ROW][C]258[/C][C]0.988884[/C][C]0.0222313[/C][C]0.0111156[/C][/ROW]
[ROW][C]259[/C][C]0.997279[/C][C]0.00544175[/C][C]0.00272087[/C][/ROW]
[ROW][C]260[/C][C]0.998959[/C][C]0.00208205[/C][C]0.00104102[/C][/ROW]
[ROW][C]261[/C][C]0.998007[/C][C]0.0039853[/C][C]0.00199265[/C][/ROW]
[ROW][C]262[/C][C]0.998063[/C][C]0.00387361[/C][C]0.00193681[/C][/ROW]
[ROW][C]263[/C][C]0.99704[/C][C]0.00592065[/C][C]0.00296032[/C][/ROW]
[ROW][C]264[/C][C]0.99741[/C][C]0.00518059[/C][C]0.00259029[/C][/ROW]
[ROW][C]265[/C][C]0.991175[/C][C]0.0176498[/C][C]0.00882488[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271106&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271106&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
13	0.675588	0.648825	0.324412
14	0.538871	0.922257	0.461129
15	0.484189	0.968378	0.515811
16	0.359679	0.719359	0.640321
17	0.297055	0.594111	0.702945
18	0.209613	0.419226	0.790387
19	0.150024	0.300048	0.849976
20	0.102705	0.20541	0.897295
21	0.0968817	0.193763	0.903118
22	0.0806714	0.161343	0.919329
23	0.0626475	0.125295	0.937352
24	0.0529773	0.105955	0.947023
25	0.0378934	0.0757869	0.962107
26	0.0252636	0.0505272	0.974736
27	0.0162378	0.0324757	0.983762
28	0.013289	0.0265779	0.986711
29	0.00844492	0.0168898	0.991555
30	0.00792825	0.0158565	0.992072
31	0.0121654	0.0243307	0.987835
32	0.00837248	0.016745	0.991628
33	0.00612945	0.0122589	0.993871
34	0.00530235	0.0106047	0.994698
35	0.00337522	0.00675045	0.996625
36	0.00413464	0.00826928	0.995865
37	0.00324999	0.00649997	0.99675
38	0.00337865	0.0067573	0.996621
39	0.00942599	0.018852	0.990574
40	0.00799467	0.0159893	0.992005
41	0.0178932	0.0357865	0.982107
42	0.017331	0.034662	0.982669
43	0.0137578	0.0275156	0.986242
44	0.0103885	0.0207771	0.989611
45	0.00917149	0.018343	0.990829
46	0.00750557	0.0150111	0.992494
47	0.0062263	0.0124526	0.993774
48	0.00529851	0.010597	0.994701
49	0.0100259	0.0200517	0.989974
50	0.0156638	0.0313276	0.984336
51	0.0135916	0.0271831	0.986408
52	0.0143032	0.0286064	0.985697
53	0.0134469	0.0268938	0.986553
54	0.016	0.0320001	0.984
55	0.0313226	0.0626453	0.968677
56	0.0259389	0.0518778	0.974061
57	0.0901712	0.180342	0.909829
58	0.0872827	0.174565	0.912717
59	0.073227	0.146454	0.926773
60	0.0772639	0.154528	0.922736
61	0.0898542	0.179708	0.910146
62	0.0819949	0.16399	0.918005
63	0.160227	0.320453	0.839773
64	0.188128	0.376256	0.811872
65	0.202369	0.404738	0.797631
66	0.178457	0.356915	0.821543
67	0.175803	0.351605	0.824197
68	0.163325	0.326649	0.836675
69	0.168733	0.337466	0.831267
70	0.15218	0.304361	0.84782
71	0.142134	0.284268	0.857866
72	0.127094	0.254188	0.872906
73	0.115493	0.230986	0.884507
74	0.135848	0.271696	0.864152
75	0.120883	0.241765	0.879117
76	0.10723	0.21446	0.89277
77	0.0959077	0.191815	0.904092
78	0.103926	0.207853	0.896074
79	0.0876104	0.175221	0.91239
80	0.11174	0.22348	0.88826
81	0.0951421	0.190284	0.904858
82	0.112962	0.225923	0.887038
83	0.0970748	0.19415	0.902925
84	0.187574	0.375148	0.812426
85	0.172942	0.345884	0.827058
86	0.153641	0.307283	0.846359
87	0.135641	0.271281	0.864359
88	0.122411	0.244822	0.877589
89	0.115401	0.230802	0.884599
90	0.120765	0.241531	0.879235
91	0.127695	0.255389	0.872305
92	0.225512	0.451023	0.774488
93	0.226695	0.453389	0.773305
94	0.222758	0.445516	0.777242
95	0.243048	0.486096	0.756952
96	0.23661	0.47322	0.76339
97	0.31748	0.634959	0.68252
98	0.310295	0.620589	0.689705
99	0.348339	0.696678	0.651661
100	0.402482	0.804964	0.597518
101	0.377194	0.754387	0.622806
102	0.360936	0.721872	0.639064
103	0.361603	0.723206	0.638397
104	0.374711	0.749423	0.625289
105	0.406136	0.812272	0.593864
106	0.421745	0.84349	0.578255
107	0.453223	0.906446	0.546777
108	0.659391	0.681219	0.340609
109	0.696648	0.606704	0.303352
110	0.706716	0.586568	0.293284
111	0.705512	0.588976	0.294488
112	0.697438	0.605124	0.302562
113	0.770197	0.459606	0.229803
114	0.751621	0.496758	0.248379
115	0.856121	0.287758	0.143879
116	0.902972	0.194056	0.0970282
117	0.894115	0.211769	0.105885
118	0.931819	0.136362	0.0681809
119	0.930125	0.139749	0.0698747
120	0.945507	0.108987	0.0544933
121	0.954646	0.090709	0.0453545
122	0.962493	0.0750137	0.0375069
123	0.963762	0.0724759	0.0362379
124	0.979351	0.0412971	0.0206485
125	0.982292	0.0354165	0.0177083
126	0.978995	0.0420092	0.0210046
127	0.977977	0.0440459	0.0220229
128	0.974699	0.0506026	0.0253013
129	0.973409	0.0531827	0.0265913
130	0.97104	0.0579195	0.0289598
131	0.970467	0.0590657	0.0295328
132	0.96828	0.0634406	0.0317203
133	0.972292	0.0554163	0.0277082
134	0.968395	0.06321	0.031605
135	0.962162	0.0756758	0.0378379
136	0.956002	0.0879956	0.0439978
137	0.966849	0.0663029	0.0331514
138	0.966573	0.0668549	0.0334274
139	0.963492	0.0730151	0.0365076
140	0.956904	0.0861919	0.0430959
141	0.950016	0.0999682	0.0499841
142	0.975972	0.0480559	0.024028
143	0.975617	0.0487658	0.0243829
144	0.975635	0.0487309	0.0243655
145	0.972124	0.0557515	0.0278757
146	0.972495	0.0550103	0.0275051
147	0.969949	0.0601014	0.0300507
148	0.965326	0.0693471	0.0346736
149	0.959996	0.0800088	0.0400044
150	0.957485	0.0850291	0.0425145
151	0.982079	0.0358426	0.0179213
152	0.979957	0.0400864	0.0200432
153	0.97983	0.0403398	0.0201699
154	0.975376	0.0492477	0.0246238
155	0.974945	0.0501104	0.0250552
156	0.97024	0.0595195	0.0297598
157	0.968304	0.0633925	0.0316963
158	0.96322	0.0735606	0.0367803
159	0.96395	0.0721009	0.0360504
160	0.9578	0.0844002	0.0422001
161	0.967799	0.0644023	0.0322012
162	0.962155	0.0756901	0.0378451
163	0.962677	0.0746462	0.0373231
164	0.990466	0.0190689	0.00953445
165	0.99107	0.0178608	0.00893041
166	0.988788	0.022424	0.011212
167	0.988396	0.0232083	0.0116041
168	0.991679	0.0166414	0.00832071
169	0.989353	0.0212939	0.010647
170	0.989521	0.0209585	0.0104792
171	0.987296	0.0254082	0.0127041
172	0.991109	0.0177811	0.00889053
173	0.989853	0.0202943	0.0101471
174	0.987233	0.0255349	0.0127674
175	0.984095	0.031809	0.0159045
176	0.987245	0.0255105	0.0127552
177	0.985946	0.0281072	0.0140536
178	0.986577	0.0268463	0.0134231
179	0.984885	0.030229	0.0151145
180	0.987221	0.0255577	0.0127789
181	0.986505	0.0269902	0.0134951
182	0.983798	0.0324038	0.0162019
183	0.981085	0.0378295	0.0189147
184	0.977381	0.0452382	0.0226191
185	0.974166	0.0516672	0.0258336
186	0.969467	0.0610656	0.0305328
187	0.98179	0.0364193	0.0182097
188	0.977858	0.0442833	0.0221417
189	0.973433	0.0531344	0.0265672
190	0.967375	0.06525	0.032625
191	0.961676	0.0766488	0.0383244
192	0.958094	0.0838121	0.041906
193	0.954247	0.0915067	0.0457534
194	0.972442	0.0551153	0.0275577
195	0.967035	0.0659295	0.0329648
196	0.963057	0.0738866	0.0369433
197	0.963904	0.0721915	0.0360957
198	0.955641	0.088719	0.0443595
199	0.957534	0.0849319	0.042466
200	0.955814	0.0883729	0.0441865
201	0.94732	0.105361	0.0526803
202	0.941529	0.116941	0.0584705
203	0.93492	0.13016	0.0650798
204	0.922233	0.155533	0.0777666
205	0.908206	0.183588	0.0917939
206	0.926578	0.146845	0.0734225
207	0.917257	0.165486	0.0827432
208	0.911894	0.176211	0.0881057
209	0.914321	0.171358	0.0856791
210	0.90437	0.19126	0.0956299
211	0.886748	0.226504	0.113252
212	0.8682	0.2636	0.1318
213	0.883364	0.233271	0.116636
214	0.866521	0.266958	0.133479
215	0.8601	0.279801	0.1399
216	0.838866	0.322267	0.161134
217	0.837314	0.325373	0.162686
218	0.819869	0.360262	0.180131
219	0.788419	0.423162	0.211581
220	0.754987	0.490027	0.245013
221	0.740106	0.519787	0.259894
222	0.76776	0.46448	0.23224
223	0.733417	0.533167	0.266583
224	0.751675	0.49665	0.248325
225	0.738193	0.523615	0.261807
226	0.826095	0.34781	0.173905
227	0.851827	0.296345	0.148173
228	0.84589	0.308219	0.15411
229	0.82337	0.35326	0.17663
230	0.851708	0.296584	0.148292
231	0.901978	0.196044	0.0980218
232	0.878945	0.242109	0.121055
233	0.855534	0.288932	0.144466
234	0.835331	0.329339	0.164669
235	0.809046	0.381907	0.190954
236	0.935438	0.129123	0.0645616
237	0.935587	0.128825	0.0644126
238	0.931609	0.136781	0.0683906
239	0.916916	0.166169	0.0830844
240	0.89255	0.2149	0.10745
241	0.892995	0.214011	0.107005
242	0.863086	0.273828	0.136914
243	0.844494	0.311011	0.155506
244	0.821056	0.357887	0.178944
245	0.780129	0.439742	0.219871
246	0.731319	0.537362	0.268681
247	0.690144	0.619712	0.309856
248	0.656171	0.687657	0.343829
249	0.614213	0.771575	0.385787
250	0.55553	0.88894	0.44447
251	0.492974	0.985948	0.507026
252	0.485952	0.971903	0.514048
253	0.41201	0.82402	0.58799
254	0.567588	0.864824	0.432412
255	0.494648	0.989295	0.505352
256	0.429356	0.858713	0.570644
257	0.45998	0.91996	0.54002
258	0.988884	0.0222313	0.0111156
259	0.997279	0.00544175	0.00272087
260	0.998959	0.00208205	0.00104102
261	0.998007	0.0039853	0.00199265
262	0.998063	0.00387361	0.00193681
263	0.99704	0.00592065	0.00296032
264	0.99741	0.00518059	0.00259029
265	0.991175	0.0176498	0.00882488

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	10	0.0395257	NOK
5% type I error level	70	0.27668	NOK
10% type I error level	120	0.474308	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 & 10 & 0.0395257 & NOK \tabularnewline
5% type I error level & 70 & 0.27668 & NOK \tabularnewline
10% type I error level & 120 & 0.474308 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271106&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]10[/C][C]0.0395257[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]70[/C][C]0.27668[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]120[/C][C]0.474308[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271106&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271106&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	10	0.0395257	NOK
5% type I error level	70	0.27668	NOK
10% type I error level	120	0.474308	NOK

Figure 1

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 10 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 10 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

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

library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$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