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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Sun, 14 Dec 2014 23:33:56 +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/14/t14186011480qhltkwvqe4uk8f.htm/, Retrieved Thu, 16 May 2024 22:09:37 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267934, Retrieved Thu, 16 May 2024 22:09:37 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

112

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

-     [Factor Analysis] [Sleep in Mammals ...] [2010-03-21 11:39:53] [b98453cac15ba1066b407e146608df68]
- RMPD  [Testing Mean with unknown Variance - Critical Value] [Hypothesis Test a...] [2010-10-19 11:45:26] [b98453cac15ba1066b407e146608df68]
- RM D    [Testing Mean with unknown Variance - Critical Value] [] [2014-10-14 18:43:28] [32b17a345b130fdf5cc88718ed94a974]
- RMPD      [Multiple Regression] [] [2014-12-11 21:39:03] [6b382800c0d3804662889dbce999b8c7]
- R PD          [Multiple Regression] [] [2014-12-14 23:33:56] [6993448de96b8662e47595bfdf466bf3] [Current]
- RM D            [Decomposition by Loess] [] [2014-12-15 02:12:41] [6b382800c0d3804662889dbce999b8c7] 

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Dataseries X:

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1	0	0	21	149	86	1,8	12,9
1	0	1	22	139	70	2,1	12,2
1	0	0	22	148	71	2,2	12,8
1	0	1	18	158	108	2,3	7,4
1	0	1	23	128	64	2,1	6,7
1	0	1	12	224	119	2,7	12,6
1	0	0	20	159	97	2,1	14,8
1	0	1	22	105	129	2,4	13,3
1	0	1	21	159	153	2,9	11,1
1	0	1	19	167	78	2,2	8,2
1	0	1	22	165	80	2,1	11,4
1	0	1	15	159	99	2,2	6,4
1	0	1	20	119	68	2,2	10,6
1	0	0	19	176	147	2,7	12,0
1	0	0	18	54	40	1,9	6,3
1	1	0	15	91	57	2,0	11,3
1	0	1	20	163	120	2,5	11,9
1	0	0	21	124	71	2,2	9,3
1	1	1	21	137	84	2,3	9,6
1	0	0	15	121	68	1,9	10,0
1	0	1	16	153	55	2,1	6,4
1	0	1	23	148	137	3,5	13,8
1	0	0	21	221	79	2,1	10,8
1	0	1	18	188	116	2,3	13,8
1	0	1	25	149	101	2,3	11,7
1	0	1	9	244	111	2,2	10,9
1	1	1	30	148	189	3,5	16,1
1	1	0	20	92	66	1,9	13,4
1	0	1	23	150	81	1,9	9,9
1	0	0	16	153	63	1,9	11,5
1	0	0	16	94	69	1,9	8,3
1	0	0	19	156	71	2,1	11,7
1	0	1	25	132	64	2,0	9,0
1	0	1	18	161	143	3,2	9,7
1	0	1	23	105	85	2,3	10,8
1	0	1	21	97	86	2,5	10,3
1	0	0	10	151	55	1,8	10,4
1	1	1	14	131	69	2,4	12,7
1	0	1	22	166	120	2,8	9,3
1	0	0	26	157	96	2,3	11,8
1	0	1	23	111	60	2,0	5,9
1	0	1	23	145	95	2,5	11,4
1	0	1	24	162	100	2,3	13,0
1	0	1	24	163	68	1,8	10,8
1	1	1	18	59	57	1,9	12,3
1	0	0	23	187	105	2,6	11,3
1	0	1	15	109	85	2,0	11,8
1	1	1	19	90	103	2,6	7,9
1	0	0	16	105	57	1,6	12,7
1	1	1	25	83	51	2,2	12,3
1	1	1	23	116	69	2,1	11,6
1	1	1	17	42	41	1,8	6,7
1	0	1	19	148	49	1,8	10,9
1	1	1	21	155	50	1,9	12,1
1	0	1	18	125	93	2,4	13,3
1	0	1	27	116	58	1,9	10,1
1	1	0	21	128	54	2,0	5,7
1	0	1	13	138	74	2,1	14,3
1	1	0	8	49	15	1,7	8,0
1	1	1	29	96	69	1,9	13,3
1	0	1	28	164	107	2,1	9,3
1	0	0	23	162	65	2,4	12,5
1	0	0	21	99	58	1,8	7,6
1	0	1	19	202	107	2,3	15,9
1	0	0	19	186	70	2,1	9,2
1	1	1	20	66	53	2,0	9,1
1	0	0	18	183	136	2,8	11,1
1	0	1	19	214	126	2,0	13,0
1	0	1	17	188	95	2,7	14,5
1	1	0	19	104	69	2,1	12,2
1	0	0	25	177	136	2,9	12,3
1	0	0	19	126	58	2,0	11,4
1	1	0	22	76	59	1,8	8,8
1	1	1	23	99	118	2,6	14,6
1	0	0	14	139	82	2,1	12,6
1	0	1	28	78	50	2,3	NA
1	0	0	16	162	102	2,3	13,0
1	1	1	24	108	65	2,2	12,6
1	0	0	20	159	90	2,0	13,2
1	1	0	12	74	64	2,2	9,9
1	0	1	24	110	83	2,1	7,7
1	1	0	22	96	70	2,1	10,5
1	1	0	12	116	50	1,9	13,4
1	1	0	22	87	77	2,0	10,9
1	1	1	20	97	37	1,7	4,3
1	1	0	10	127	81	2,2	10,3
1	1	1	23	106	101	2,2	11,8
1	1	1	17	80	79	2,3	11,2
1	1	0	22	74	71	2,4	11,4
1	1	0	24	91	60	2,1	8,6
1	1	0	18	133	55	1,9	13,2
1	1	1	21	74	44	1,7	12,6
1	1	1	20	114	40	1,8	5,6
1	1	1	20	140	56	1,5	9,9
1	1	0	22	95	43	1,9	8,8
1	1	1	19	98	45	1,9	7,7
1	1	0	20	121	32	1,7	9,0
1	1	1	26	126	56	1,9	7,3
1	1	1	23	98	40	1,9	11,4
1	1	1	24	95	34	1,8	13,6
1	1	1	21	110	89	2,4	7,9
1	1	1	21	70	50	1,8	10,7
1	1	0	19	102	56	1,9	10,3
1	1	1	8	86	46	1,8	8,3
1	1	1	17	130	76	2,1	9,6
1	1	1	20	96	64	1,9	14,2
1	1	0	11	102	74	2,2	8,5
1	1	0	8	100	57	2,0	13,5
1	1	0	15	94	45	1,7	4,9
1	1	0	18	52	30	1,7	6,4
1	1	0	18	98	62	1,8	9,6
1	1	0	19	118	51	1,9	11,6
1	1	1	19	99	36	1,8	11,1
0	0	1	23	48	34	1	4,35
0	0	1	22	50	61	1	12,7
0	0	1	21	150	70	4	18,1
0	0	1	25	154	69	4	17,85
0	1	0	30	109	145	3	16,6
0	1	1	17	68	23	2	12,6
0	0	1	27	194	120	4	17,1
0	0	0	23	158	147	4	19,1
0	0	1	23	159	215	4	16,1
0	0	0	18	67	24	2	13,35
0	0	0	18	147	84	4	18,4
0	0	1	23	39	30	1	14,7
0	0	1	19	100	77	3	10,6
0	0	1	15	111	46	3	12,6
0	0	1	20	138	61	4	16,2
0	0	1	16	101	178	3	13,6
0	1	1	24	131	160	4	18,9
0	0	1	25	101	57	3	14,1
0	0	1	25	114	42	3	14,5
0	0	0	19	165	163	4	16,15
0	0	1	19	114	75	3	14,75
0	0	1	16	111	94	3	14,8
0	0	1	19	75	45	2	12,45
0	0	1	19	82	78	2	12,65
0	0	1	23	121	47	3	17,35
0	0	1	21	32	29	1	8,6
0	0	0	22	150	97	4	18,4
0	0	1	19	117	116	3	16,1
0	1	1	20	71	32	2	11,6
0	0	1	20	165	50	4	17,75
0	0	1	3	154	118	4	15,25
0	0	1	23	126	66	4	17,65
0	0	0	23	149	86	4	16,35
0	0	0	20	145	89	4	17,65
0	0	1	15	120	76	3	13,6
0	0	0	16	109	75	3	14,35
0	0	0	7	132	57	4	14,75
0	0	1	24	172	72	4	18,25
0	0	0	17	169	60	4	9,9
0	0	1	24	114	109	3	16
0	0	1	24	156	76	4	18,25
0	0	0	19	172	65	4	16,85
0	1	1	25	68	40	2	14,6
0	1	1	20	89	58	2	13,85
0	0	1	28	167	123	4	18,95
0	0	0	23	113	71	3	15,6
0	1	0	27	115	102	3	14,85
0	1	0	18	78	80	2	11,75
0	1	0	28	118	97	3	18,45
0	1	1	21	87	46	2	15,9
0	0	0	19	173	93	4	17,1
0	0	1	23	2	19	1	16,1
0	1	0	27	162	140	4	19,9
0	1	1	22	49	78	1	10,95
0	1	0	28	122	98	4	18,45
0	1	1	25	96	40	3	15,1
0	1	0	21	100	80	3	15
0	1	0	22	82	76	2	11,35
0	1	1	28	100	79	3	15,95
0	1	0	20	115	87	3	18,1
0	1	1	29	141	95	4	14,6
0	0	1	25	165	49	4	15,4
0	0	1	25	165	49	4	15,4
0	1	1	20	110	80	3	17,6
0	0	1	20	118	86	3	13,35
0	0	0	16	158	69	4	19,1
0	1	1	20	146	79	4	15,35
0	0	0	20	49	52	1	7,6
0	1	0	23	90	120	2	13,4
0	1	0	18	121	69	3	13,9
0	0	1	25	155	94	4	19,1
0	1	0	18	104	72	3	15,25
0	1	1	19	147	43	4	12,9
0	1	0	25	110	87	3	16,1
0	1	0	25	108	52	3	17,35
0	1	0	25	113	71	3	13,15
0	1	0	24	115	61	3	12,15
0	1	1	19	61	51	1	12,6
0	1	1	26	60	50	1	10,35
0	1	1	10	109	67	3	15,4
0	1	1	17	68	30	2	9,6
0	1	0	13	111	70	3	18,2
0	1	0	17	77	52	2	13,6
0	1	1	30	73	75	2	14,85
0	0	0	25	151	87	4	14,75
0	1	0	4	89	69	2	14,1
0	1	0	16	78	72	2	14,9
0	1	0	21	110	79	3	16,25
0	0	1	23	220	121	4	19,25
0	1	1	22	65	43	2	13,6
0	0	0	17	141	58	4	13,6
0	1	0	20	117	57	3	15,65
0	0	1	20	122	50	4	12,75
0	1	0	22	63	69	2	14,6
0	0	1	16	44	64	1	9,85
0	1	1	23	52	38	1	12,65
0	1	0	0	131	90	4	19,2
0	1	1	18	101	96	3	16,6
0	1	1	25	42	49	1	11,2
0	0	1	23	152	56	4	15,25
0	0	0	12	107	102	3	11,9
0	1	0	18	77	40	2	13,2
0	0	0	24	154	100	4	16,35
0	0	1	11	103	67	3	12,4
0	1	1	18	96	78	3	15,85
0	0	1	23	175	55	4	18,15
0	1	1	24	57	59	1	11,15
0	1	0	29	112	96	3	15,65
0	0	0	18	143	86	4	17,75
0	1	0	15	49	38	1	7,65
0	0	1	29	110	43	3	12,35
0	0	1	16	131	23	4	15,6
0	0	0	19	167	77	4	19,3
0	1	0	22	56	48	1	15,2
0	0	0	16	137	26	4	17,1
0	1	1	23	86	91	2	15,6
0	0	1	23	121	94	3	18,4
0	0	0	19	149	62	4	19,05
0	0	0	4	168	74	4	18,55
0	0	0	20	140	114	4	19,1
0	1	1	24	88	52	2	13,1
0	0	1	20	168	64	4	12,85
0	0	1	4	94	31	2	9,5
0	0	1	24	51	38	1	4,5
0	1	0	22	48	27	1	11,85
0	0	1	16	145	105	4	13,6
0	0	1	3	66	64	2	11,7
0	1	1	15	85	62	2	12,4
0	0	0	24	109	65	3	13,35
0	1	0	17	63	58	2	11,4
0	1	1	20	102	76	3	14,9
0	1	0	27	162	140	4	19,9
0	1	1	26	86	68	2	11,2
0	1	1	23	114	80	3	14,6
0	0	0	17	164	71	4	17,6
0	0	1	20	119	76	3	14,05
0	0	0	22	126	63	4	16,1
0	0	1	19	132	46	4	13,35
0	0	1	24	142	53	4	11,85
0	0	0	19	83	74	2	11,95
0	1	1	23	94	70	2	14,75
0	1	0	15	81	78	2	15,15
0	0	1	27	166	56	4	13,2
0	1	0	26	110	100	3	16,85
0	1	1	22	64	51	2	7,85
0	0	0	22	93	52	2	7,7
0	1	0	18	104	102	3	12,6
0	1	1	15	105	78	3	7,85
0	1	1	22	49	78	1	10,95
0	1	0	27	88	55	2	12,35
0	1	1	10	95	98	2	9,95
0	1	1	20	102	76	3	14,9
0	1	0	17	99	73	3	16,65
0	1	1	23	63	47	2	13,4
0	1	0	19	76	45	2	13,95
0	1	0	13	109	83	3	15,7
0	1	1	27	117	60	3	16,85
0	1	1	23	57	48	1	10,95
0	1	0	16	120	50	3	15,35
0	1	1	25	73	56	2	12,2
0	1	0	2	91	77	2	15,1
0	1	0	26	108	91	3	17,75
0	1	1	20	105	76	3	15,2
0	0	0	23	117	68	3	14,6
0	1	0	22	119	74	3	16,65
0	1	1	24	31	29	1	8,1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267934&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267934&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267934&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	9 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 6.85783 -3.06893jaar_bin[t] + 0.92338group_bin[t] -0.571854gender_bin[t] + 0.0400841NUMERACYTOT[t] + 0.0153646LFM[t] + 0.0145006Hour[t] + 1.38702PR[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  6.85783 -3.06893jaar_bin[t] +  0.92338group_bin[t] -0.571854gender_bin[t] +  0.0400841NUMERACYTOT[t] +  0.0153646LFM[t] +  0.0145006Hour[t] +  1.38702PR[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267934&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  6.85783 -3.06893jaar_bin[t] +  0.92338group_bin[t] -0.571854gender_bin[t] +  0.0400841NUMERACYTOT[t] +  0.0153646LFM[t] +  0.0145006Hour[t] +  1.38702PR[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267934&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267934&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] = + 6.85783 -3.06893jaar_bin[t] + 0.92338group_bin[t] -0.571854gender_bin[t] + 0.0400841NUMERACYTOT[t] + 0.0153646LFM[t] + 0.0145006Hour[t] + 1.38702PR[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)	6.85783	0.79912	8.582	7.47699e-16	3.73849e-16
jaar_bin	-3.06893	0.376298	-8.156	1.31936e-14	6.59682e-15
group_bin	0.92338	0.313566	2.945	0.00351348	0.00175674
gender_bin	-0.571854	0.273791	-2.089	0.037676	0.018838
NUMERACYTOT	0.0400841	0.0265415	1.51	0.132151	0.0660755
LFM	0.0153646	0.0059954	2.563	0.0109279	0.00546394
Hour	0.0145006	0.00517687	2.801	0.00546232	0.00273116
PR	1.38702	0.255696	5.425	1.29186e-07	6.4593e-08

\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) & 6.85783 & 0.79912 & 8.582 & 7.47699e-16 & 3.73849e-16 \tabularnewline
jaar_bin & -3.06893 & 0.376298 & -8.156 & 1.31936e-14 & 6.59682e-15 \tabularnewline
group_bin & 0.92338 & 0.313566 & 2.945 & 0.00351348 & 0.00175674 \tabularnewline
gender_bin & -0.571854 & 0.273791 & -2.089 & 0.037676 & 0.018838 \tabularnewline
NUMERACYTOT & 0.0400841 & 0.0265415 & 1.51 & 0.132151 & 0.0660755 \tabularnewline
LFM & 0.0153646 & 0.0059954 & 2.563 & 0.0109279 & 0.00546394 \tabularnewline
Hour & 0.0145006 & 0.00517687 & 2.801 & 0.00546232 & 0.00273116 \tabularnewline
PR & 1.38702 & 0.255696 & 5.425 & 1.29186e-07 & 6.4593e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267934&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]6.85783[/C][C]0.79912[/C][C]8.582[/C][C]7.47699e-16[/C][C]3.73849e-16[/C][/ROW]
[ROW][C]jaar_bin[/C][C]-3.06893[/C][C]0.376298[/C][C]-8.156[/C][C]1.31936e-14[/C][C]6.59682e-15[/C][/ROW]
[ROW][C]group_bin[/C][C]0.92338[/C][C]0.313566[/C][C]2.945[/C][C]0.00351348[/C][C]0.00175674[/C][/ROW]
[ROW][C]gender_bin[/C][C]-0.571854[/C][C]0.273791[/C][C]-2.089[/C][C]0.037676[/C][C]0.018838[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0400841[/C][C]0.0265415[/C][C]1.51[/C][C]0.132151[/C][C]0.0660755[/C][/ROW]
[ROW][C]LFM[/C][C]0.0153646[/C][C]0.0059954[/C][C]2.563[/C][C]0.0109279[/C][C]0.00546394[/C][/ROW]
[ROW][C]Hour[/C][C]0.0145006[/C][C]0.00517687[/C][C]2.801[/C][C]0.00546232[/C][C]0.00273116[/C][/ROW]
[ROW][C]PR[/C][C]1.38702[/C][C]0.255696[/C][C]5.425[/C][C]1.29186e-07[/C][C]6.4593e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267934&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267934&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)	6.85783	0.79912	8.582	7.47699e-16	3.73849e-16
jaar_bin	-3.06893	0.376298	-8.156	1.31936e-14	6.59682e-15
group_bin	0.92338	0.313566	2.945	0.00351348	0.00175674
gender_bin	-0.571854	0.273791	-2.089	0.037676	0.018838
NUMERACYTOT	0.0400841	0.0265415	1.51	0.132151	0.0660755
LFM	0.0153646	0.0059954	2.563	0.0109279	0.00546394
Hour	0.0145006	0.00517687	2.801	0.00546232	0.00273116
PR	1.38702	0.255696	5.425	1.29186e-07	6.4593e-08

Multiple Linear Regression - Regression Statistics
Multiple R	0.769487
R-squared	0.59211
Adjusted R-squared	0.581536
F-TEST (value)	55.992
F-TEST (DF numerator)	7
F-TEST (DF denominator)	270
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.19577
Sum Squared Residuals	1301.78

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.769487 \tabularnewline
R-squared & 0.59211 \tabularnewline
Adjusted R-squared & 0.581536 \tabularnewline
F-TEST (value) & 55.992 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 270 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.19577 \tabularnewline
Sum Squared Residuals & 1301.78 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267934&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.769487[/C][/ROW]
[ROW][C]R-squared[/C][C]0.59211[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.581536[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]55.992[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]270[/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]2.19577[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1301.78[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267934&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267934&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	0.769487
R-squared	0.59211
Adjusted R-squared	0.581536
F-TEST (value)	55.992
F-TEST (DF numerator)	7
F-TEST (DF denominator)	270
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.19577
Sum Squared Residuals	1301.78

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	10.6637	2.23632
2	12.2	10.1624	2.03764
3	12.8	11.0257	1.7743
4	7.4	11.1224	-3.72238
5	6.7	9.94643	-3.24643
6	12.6	12.6102	-0.0102496
7	14.8	11.3529	3.44715
8	13.3	10.9116	2.3884
9	11.1	12.7427	-1.64273
10	8.2	10.727	-2.52702
11	11.4	10.7068	0.693156
12	6.4	10.7483	-4.34828
13	10.6	9.8846	0.7154
14	12	13.1312	-1.13121
15	6.3	8.55546	-2.25546
16	11.3	10.3123	0.987706
17	11.9	11.7308	0.169222
18	9.3	10.6169	-1.31686
19	9.6	11.4953	-1.89534
20	10	9.87066	0.129345
21	6.4	9.91945	-3.51945
22	13.8	13.2541	0.545908
23	10.8	12.0845	-1.28453
24	13.8	11.6993	2.10068
25	11.7	11.1632	0.536822
26	10.9	11.9878	-1.08777
27	16.1	15.2121	0.88791
28	13.4	10.5199	2.88012
29	9.9	10.2536	-0.353555
30	11.5	10.3299	1.1701
31	8.3	9.5104	-1.2104
32	11.7	10.8897	0.810341
33	9	9.94935	-0.949353
34	9.7	12.9243	-3.22431
35	10.8	10.175	0.625041
36	10.3	10.2638	0.0362209
37	10.4	9.80396	0.596036
38	12.7	11.0438	1.65624
39	9.3	12.2731	-2.97315
40	11.8	11.8255	-0.0255302
41	5.9	9.48853	-3.58853
42	11.4	11.212	0.188047
43	13	11.3083	1.69167
44	10.8	10.1662	0.63383
45	12.3	9.23032	3.06968
46	11.3	12.7128	-1.41283
47	11.8	9.49964	2.30036
48	7.9	11.3847	-3.48465
49	12.7	9.08929	3.61071
50	12.3	10.2088	2.09123
51	11.6	10.7579	0.842063
52	6.7	8.55833	-1.85833
53	10.9	9.45977	1.44023
54	12.1	10.7241	1.37593
55	13.3	10.5365	2.76346
56	10.1	9.55798	0.542018
57	5.7	11.0778	-5.37779
58	14.3	9.84424	4.45576
59	8	8.36126	-0.361262
60	13.3	10.4137	2.88626
61	9.3	11.3235	-2.0235
62	12.5	11.4713	1.02871
63	7.6	9.48943	-1.88943
64	15.9	11.824	4.076
65	9.2	11.3361	-2.1361
66	9.1	9.49874	-0.398743
67	11.1	13.1779	-2.07787
68	13	11.8678	1.13222
69	14.5	11.9095	2.59047
70	12.2	10.9851	1.21492
71	12.3	13.505	-1.20497
72	11.4	10.1015	1.29849
73	8.8	10.114	-1.31401
74	14.6	11.9008	2.69922
75	12.6	10.5875	2.01245
76	NA	NA	1.41148
77	13	11.1558	1.8442
78	12.6	10.5126	2.08735
79	13.2	13.6098	-0.409752
80	9.9	12.1855	-2.28546
81	7.7	8.19691	-0.496915
82	10.5	7.43595	3.06405
83	13.4	13.3214	0.0785652
84	10.9	15.9269	-5.02693
85	4.3	5.29042	-0.990417
86	10.3	9.70701	0.59299
87	11.8	10.9867	0.813283
88	11.2	10.8895	0.310499
89	11.4	13.6553	-2.25525
90	8.6	6.31016	2.28984
91	13.2	9.71513	3.48487
92	12.6	16.7703	-4.17033
93	5.6	5.68571	-0.0857143
94	9.9	11.4126	-1.51263
95	8.8	10.7956	-1.99562
96	7.7	8.89503	-1.19503
97	9	12.2659	-3.26592
98	7.3	5.68345	1.61655
99	11.4	7.35174	4.04826
100	13.6	16.9917	-3.3917
101	7.9	6.47938	1.42062
102	10.7	10.8884	-0.188438
103	10.3	10.9461	-0.646118
104	8.3	9.53404	-1.23404
105	9.6	5.38049	4.21951
106	14.2	16.5449	-2.34488
107	8.5	5.16999	3.33001
108	13.5	18.3683	-4.86827
109	4.9	7.5257	-2.6257
110	6.4	7.1352	-0.735196
111	9.6	8.66177	0.938231
112	11.6	9.94178	1.65822
113	11.1	16.5755	-5.47545
114	4.35	1.85761	2.49239
115	12.7	10.5956	2.10444
116	18.1	16.4529	1.64715
117	17.85	18.1721	-0.322121
118	16.6	16.0431	0.556863
119	12.6	13.1371	-0.537135
120	17.1	15.887	1.21296
121	19.1	21.3166	-2.21659
122	16.1	14.4808	1.61917
123	13.35	11.5541	1.79592
124	18.4	13.3292	5.07083
125	14.7	17.9616	-3.26164
126	10.6	11.4208	-0.820801
127	12.6	12.0406	0.559404
128	16.2	17.8213	-1.62131
129	13.6	12.7523	0.847685
130	18.9	18.6275	0.272498
131	14.1	13.4097	0.690267
132	14.5	16.4163	-1.91627
133	16.15	15.4477	0.702253
134	14.75	14.1069	0.643088
135	14.8	13.9765	0.823511
136	12.45	12.0126	0.437441
137	12.65	9.20962	3.44038
138	17.35	18.1769	-0.826948
139	8.6	7.19901	1.40099
140	18.4	16.9884	1.41164
141	16.1	16.84	-0.739988
142	11.6	9.74593	1.85407
143	17.75	18.5315	-0.781532
144	15.25	13.249	2.00102
145	17.65	18.1642	-0.514226
146	16.35	15.426	0.923983
147	17.65	18.0441	-0.394099
148	13.6	13.6725	-0.0725256
149	14.35	15.1412	-0.791167
150	14.75	12.9828	1.76716
151	18.25	24.904	-6.654
152	9.9	8.64119	1.25881
153	16	14.045	1.955
154	18.25	18.1528	0.0972356
155	16.85	14.8603	1.98968
156	14.6	13.7436	0.856435
157	13.85	12.2059	1.64412
158	18.95	18.0566	0.89343
159	15.6	17.0205	-1.42053
160	14.85	16.7353	-1.88525
161	11.75	9.58421	2.16579
162	18.45	15.3789	3.07109
163	15.9	15.9741	-0.0741445
164	17.1	9.90117	7.19883
165	16.1	15.1307	0.969288
166	19.9	20.3121	-0.412138
167	10.95	10.2472	0.702811
168	18.45	17.7775	0.67245
169	15.1	15.5805	-0.480547
170	15	17.449	-2.44904
171	11.35	10.5748	0.775218
172	15.95	13.6224	2.32756
173	18.1	20.9638	-2.86385
174	14.6	15.2819	-0.681854
175	15.4	16.0819	-0.681854
176	15.4	12.8223	2.57774
177	17.6	18.5588	-0.958796
178	13.35	10.7254	2.62459
179	19.1	20.6979	-1.5979
180	15.35	18.3034	-2.95343
181	7.6	8.80007	-1.20007
182	13.4	15.0234	-1.62345
183	13.9	11.3807	2.51927
184	19.1	19.1557	-0.0557493
185	15.25	18.7512	-3.50116
186	12.9	12.696	0.203966
187	16.1	14.1078	1.99221
188	17.35	19.9101	-2.56012
189	13.15	16.5558	-3.40576
190	12.15	10.5847	1.56525
191	12.6	13.5355	-0.935469
192	10.35	9.36754	0.982457
193	15.4	17.9446	-2.54464
194	9.6	6.58388	3.01612
195	18.2	17.7738	0.426212
196	13.6	12.1451	1.45492
197	14.85	17.0896	-2.23962
198	14.75	13.7336	1.01642
199	14.1	12.6391	1.46092
200	14.9	14.2697	0.630307
201	16.25	14.8908	1.35922
202	19.25	18.1375	1.11253
203	13.6	16.0948	-2.49479
204	13.6	13.3181	0.281851
205	15.65	18.1353	-2.48526
206	12.75	11.5556	1.19439
207	14.6	14.6684	-0.0684224
208	9.85	8.06829	1.78171
209	12.65	10.0971	2.55289
210	19.2	17.6358	1.56418
211	16.6	16.3543	0.245678
212	11.2	11.8535	-0.65345
213	15.25	17.973	-2.72298
214	11.9	11.7399	0.160135
215	13.2	14.0341	-0.834141
216	16.35	17.3921	-1.04206
217	12.4	11.248	1.15202
218	15.85	13.9423	1.90766
219	18.15	18.2897	-0.139712
220	11.15	11.7176	-0.567604
221	15.65	14.4716	1.17838
222	17.75	21.1734	-3.42338
223	7.65	9.22311	-1.57311
224	12.35	11.5717	0.778313
225	15.6	13.1499	2.45005
226	19.3	15.7065	3.59347
227	15.2	13.6292	1.57077
228	17.1	15.0462	2.05376
229	15.6	11.7911	3.80885
230	18.4	15.7059	2.69412
231	19.05	16.7205	2.32945
232	18.55	16.4617	2.08829
233	19.1	19.0515	0.0484668
234	13.1	16.395	-3.29504
235	12.85	14.4641	-1.61415
236	9.5	14.9696	-5.46963
237	4.5	3.8291	0.670901
238	11.85	14.4758	-2.62584
239	13.6	13.0224	0.577627
240	11.7	12.0897	-0.389688
241	12.4	13.6482	-1.24819
242	13.35	14.9957	-1.64569
243	11.4	11.3413	0.0586632
244	14.9	13.9307	0.969288
245	19.9	22.033	-2.13298
246	11.2	11.804	-0.603966
247	14.6	13.6367	0.963317
248	17.6	17.7292	-0.129155
249	14.05	14.0872	-0.0372438
250	16.1	18.0408	-1.94082
251	13.35	17.2464	-3.89639
252	11.85	12.6418	-0.791775
253	11.95	10.5646	1.38535
254	14.75	13.1321	1.61791
255	15.15	18.2289	-3.07889
256	13.2	12.4746	0.725375
257	16.85	21.5881	-4.73811
258	7.85	12.8467	-4.99666
259	7.7	10.8408	-3.14077
260	12.6	19.466	-6.86601
261	7.85	8.26214	-0.412138
262	10.95	12.3871	-1.43714
263	12.35	15.6649	-3.31493
264	9.95	9.89134	0.0586632
265	14.9	13.4533	1.44666
266	16.65	15.8048	0.845169
267	13.4	12.5871	0.812913
268	13.95	13.5917	0.358342
269	15.7	13.9704	1.72961
270	16.85	16.9901	-0.140122
271	10.95	10.7524	0.197597
272	15.35	16.0692	-0.71915
273	12.2	10.2501	1.94986
274	15.1	13.3134	1.78661
275	17.75	17.4374	0.312569
276	15.2	15.3245	-0.124527
277	14.6	13.6756	0.924444
278	16.65	19.0052	-2.35522
279	8.1	NA	NA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 10.6637 & 2.23632 \tabularnewline
2 & 12.2 & 10.1624 & 2.03764 \tabularnewline
3 & 12.8 & 11.0257 & 1.7743 \tabularnewline
4 & 7.4 & 11.1224 & -3.72238 \tabularnewline
5 & 6.7 & 9.94643 & -3.24643 \tabularnewline
6 & 12.6 & 12.6102 & -0.0102496 \tabularnewline
7 & 14.8 & 11.3529 & 3.44715 \tabularnewline
8 & 13.3 & 10.9116 & 2.3884 \tabularnewline
9 & 11.1 & 12.7427 & -1.64273 \tabularnewline
10 & 8.2 & 10.727 & -2.52702 \tabularnewline
11 & 11.4 & 10.7068 & 0.693156 \tabularnewline
12 & 6.4 & 10.7483 & -4.34828 \tabularnewline
13 & 10.6 & 9.8846 & 0.7154 \tabularnewline
14 & 12 & 13.1312 & -1.13121 \tabularnewline
15 & 6.3 & 8.55546 & -2.25546 \tabularnewline
16 & 11.3 & 10.3123 & 0.987706 \tabularnewline
17 & 11.9 & 11.7308 & 0.169222 \tabularnewline
18 & 9.3 & 10.6169 & -1.31686 \tabularnewline
19 & 9.6 & 11.4953 & -1.89534 \tabularnewline
20 & 10 & 9.87066 & 0.129345 \tabularnewline
21 & 6.4 & 9.91945 & -3.51945 \tabularnewline
22 & 13.8 & 13.2541 & 0.545908 \tabularnewline
23 & 10.8 & 12.0845 & -1.28453 \tabularnewline
24 & 13.8 & 11.6993 & 2.10068 \tabularnewline
25 & 11.7 & 11.1632 & 0.536822 \tabularnewline
26 & 10.9 & 11.9878 & -1.08777 \tabularnewline
27 & 16.1 & 15.2121 & 0.88791 \tabularnewline
28 & 13.4 & 10.5199 & 2.88012 \tabularnewline
29 & 9.9 & 10.2536 & -0.353555 \tabularnewline
30 & 11.5 & 10.3299 & 1.1701 \tabularnewline
31 & 8.3 & 9.5104 & -1.2104 \tabularnewline
32 & 11.7 & 10.8897 & 0.810341 \tabularnewline
33 & 9 & 9.94935 & -0.949353 \tabularnewline
34 & 9.7 & 12.9243 & -3.22431 \tabularnewline
35 & 10.8 & 10.175 & 0.625041 \tabularnewline
36 & 10.3 & 10.2638 & 0.0362209 \tabularnewline
37 & 10.4 & 9.80396 & 0.596036 \tabularnewline
38 & 12.7 & 11.0438 & 1.65624 \tabularnewline
39 & 9.3 & 12.2731 & -2.97315 \tabularnewline
40 & 11.8 & 11.8255 & -0.0255302 \tabularnewline
41 & 5.9 & 9.48853 & -3.58853 \tabularnewline
42 & 11.4 & 11.212 & 0.188047 \tabularnewline
43 & 13 & 11.3083 & 1.69167 \tabularnewline
44 & 10.8 & 10.1662 & 0.63383 \tabularnewline
45 & 12.3 & 9.23032 & 3.06968 \tabularnewline
46 & 11.3 & 12.7128 & -1.41283 \tabularnewline
47 & 11.8 & 9.49964 & 2.30036 \tabularnewline
48 & 7.9 & 11.3847 & -3.48465 \tabularnewline
49 & 12.7 & 9.08929 & 3.61071 \tabularnewline
50 & 12.3 & 10.2088 & 2.09123 \tabularnewline
51 & 11.6 & 10.7579 & 0.842063 \tabularnewline
52 & 6.7 & 8.55833 & -1.85833 \tabularnewline
53 & 10.9 & 9.45977 & 1.44023 \tabularnewline
54 & 12.1 & 10.7241 & 1.37593 \tabularnewline
55 & 13.3 & 10.5365 & 2.76346 \tabularnewline
56 & 10.1 & 9.55798 & 0.542018 \tabularnewline
57 & 5.7 & 11.0778 & -5.37779 \tabularnewline
58 & 14.3 & 9.84424 & 4.45576 \tabularnewline
59 & 8 & 8.36126 & -0.361262 \tabularnewline
60 & 13.3 & 10.4137 & 2.88626 \tabularnewline
61 & 9.3 & 11.3235 & -2.0235 \tabularnewline
62 & 12.5 & 11.4713 & 1.02871 \tabularnewline
63 & 7.6 & 9.48943 & -1.88943 \tabularnewline
64 & 15.9 & 11.824 & 4.076 \tabularnewline
65 & 9.2 & 11.3361 & -2.1361 \tabularnewline
66 & 9.1 & 9.49874 & -0.398743 \tabularnewline
67 & 11.1 & 13.1779 & -2.07787 \tabularnewline
68 & 13 & 11.8678 & 1.13222 \tabularnewline
69 & 14.5 & 11.9095 & 2.59047 \tabularnewline
70 & 12.2 & 10.9851 & 1.21492 \tabularnewline
71 & 12.3 & 13.505 & -1.20497 \tabularnewline
72 & 11.4 & 10.1015 & 1.29849 \tabularnewline
73 & 8.8 & 10.114 & -1.31401 \tabularnewline
74 & 14.6 & 11.9008 & 2.69922 \tabularnewline
75 & 12.6 & 10.5875 & 2.01245 \tabularnewline
76 & NA & NA & 1.41148 \tabularnewline
77 & 13 & 11.1558 & 1.8442 \tabularnewline
78 & 12.6 & 10.5126 & 2.08735 \tabularnewline
79 & 13.2 & 13.6098 & -0.409752 \tabularnewline
80 & 9.9 & 12.1855 & -2.28546 \tabularnewline
81 & 7.7 & 8.19691 & -0.496915 \tabularnewline
82 & 10.5 & 7.43595 & 3.06405 \tabularnewline
83 & 13.4 & 13.3214 & 0.0785652 \tabularnewline
84 & 10.9 & 15.9269 & -5.02693 \tabularnewline
85 & 4.3 & 5.29042 & -0.990417 \tabularnewline
86 & 10.3 & 9.70701 & 0.59299 \tabularnewline
87 & 11.8 & 10.9867 & 0.813283 \tabularnewline
88 & 11.2 & 10.8895 & 0.310499 \tabularnewline
89 & 11.4 & 13.6553 & -2.25525 \tabularnewline
90 & 8.6 & 6.31016 & 2.28984 \tabularnewline
91 & 13.2 & 9.71513 & 3.48487 \tabularnewline
92 & 12.6 & 16.7703 & -4.17033 \tabularnewline
93 & 5.6 & 5.68571 & -0.0857143 \tabularnewline
94 & 9.9 & 11.4126 & -1.51263 \tabularnewline
95 & 8.8 & 10.7956 & -1.99562 \tabularnewline
96 & 7.7 & 8.89503 & -1.19503 \tabularnewline
97 & 9 & 12.2659 & -3.26592 \tabularnewline
98 & 7.3 & 5.68345 & 1.61655 \tabularnewline
99 & 11.4 & 7.35174 & 4.04826 \tabularnewline
100 & 13.6 & 16.9917 & -3.3917 \tabularnewline
101 & 7.9 & 6.47938 & 1.42062 \tabularnewline
102 & 10.7 & 10.8884 & -0.188438 \tabularnewline
103 & 10.3 & 10.9461 & -0.646118 \tabularnewline
104 & 8.3 & 9.53404 & -1.23404 \tabularnewline
105 & 9.6 & 5.38049 & 4.21951 \tabularnewline
106 & 14.2 & 16.5449 & -2.34488 \tabularnewline
107 & 8.5 & 5.16999 & 3.33001 \tabularnewline
108 & 13.5 & 18.3683 & -4.86827 \tabularnewline
109 & 4.9 & 7.5257 & -2.6257 \tabularnewline
110 & 6.4 & 7.1352 & -0.735196 \tabularnewline
111 & 9.6 & 8.66177 & 0.938231 \tabularnewline
112 & 11.6 & 9.94178 & 1.65822 \tabularnewline
113 & 11.1 & 16.5755 & -5.47545 \tabularnewline
114 & 4.35 & 1.85761 & 2.49239 \tabularnewline
115 & 12.7 & 10.5956 & 2.10444 \tabularnewline
116 & 18.1 & 16.4529 & 1.64715 \tabularnewline
117 & 17.85 & 18.1721 & -0.322121 \tabularnewline
118 & 16.6 & 16.0431 & 0.556863 \tabularnewline
119 & 12.6 & 13.1371 & -0.537135 \tabularnewline
120 & 17.1 & 15.887 & 1.21296 \tabularnewline
121 & 19.1 & 21.3166 & -2.21659 \tabularnewline
122 & 16.1 & 14.4808 & 1.61917 \tabularnewline
123 & 13.35 & 11.5541 & 1.79592 \tabularnewline
124 & 18.4 & 13.3292 & 5.07083 \tabularnewline
125 & 14.7 & 17.9616 & -3.26164 \tabularnewline
126 & 10.6 & 11.4208 & -0.820801 \tabularnewline
127 & 12.6 & 12.0406 & 0.559404 \tabularnewline
128 & 16.2 & 17.8213 & -1.62131 \tabularnewline
129 & 13.6 & 12.7523 & 0.847685 \tabularnewline
130 & 18.9 & 18.6275 & 0.272498 \tabularnewline
131 & 14.1 & 13.4097 & 0.690267 \tabularnewline
132 & 14.5 & 16.4163 & -1.91627 \tabularnewline
133 & 16.15 & 15.4477 & 0.702253 \tabularnewline
134 & 14.75 & 14.1069 & 0.643088 \tabularnewline
135 & 14.8 & 13.9765 & 0.823511 \tabularnewline
136 & 12.45 & 12.0126 & 0.437441 \tabularnewline
137 & 12.65 & 9.20962 & 3.44038 \tabularnewline
138 & 17.35 & 18.1769 & -0.826948 \tabularnewline
139 & 8.6 & 7.19901 & 1.40099 \tabularnewline
140 & 18.4 & 16.9884 & 1.41164 \tabularnewline
141 & 16.1 & 16.84 & -0.739988 \tabularnewline
142 & 11.6 & 9.74593 & 1.85407 \tabularnewline
143 & 17.75 & 18.5315 & -0.781532 \tabularnewline
144 & 15.25 & 13.249 & 2.00102 \tabularnewline
145 & 17.65 & 18.1642 & -0.514226 \tabularnewline
146 & 16.35 & 15.426 & 0.923983 \tabularnewline
147 & 17.65 & 18.0441 & -0.394099 \tabularnewline
148 & 13.6 & 13.6725 & -0.0725256 \tabularnewline
149 & 14.35 & 15.1412 & -0.791167 \tabularnewline
150 & 14.75 & 12.9828 & 1.76716 \tabularnewline
151 & 18.25 & 24.904 & -6.654 \tabularnewline
152 & 9.9 & 8.64119 & 1.25881 \tabularnewline
153 & 16 & 14.045 & 1.955 \tabularnewline
154 & 18.25 & 18.1528 & 0.0972356 \tabularnewline
155 & 16.85 & 14.8603 & 1.98968 \tabularnewline
156 & 14.6 & 13.7436 & 0.856435 \tabularnewline
157 & 13.85 & 12.2059 & 1.64412 \tabularnewline
158 & 18.95 & 18.0566 & 0.89343 \tabularnewline
159 & 15.6 & 17.0205 & -1.42053 \tabularnewline
160 & 14.85 & 16.7353 & -1.88525 \tabularnewline
161 & 11.75 & 9.58421 & 2.16579 \tabularnewline
162 & 18.45 & 15.3789 & 3.07109 \tabularnewline
163 & 15.9 & 15.9741 & -0.0741445 \tabularnewline
164 & 17.1 & 9.90117 & 7.19883 \tabularnewline
165 & 16.1 & 15.1307 & 0.969288 \tabularnewline
166 & 19.9 & 20.3121 & -0.412138 \tabularnewline
167 & 10.95 & 10.2472 & 0.702811 \tabularnewline
168 & 18.45 & 17.7775 & 0.67245 \tabularnewline
169 & 15.1 & 15.5805 & -0.480547 \tabularnewline
170 & 15 & 17.449 & -2.44904 \tabularnewline
171 & 11.35 & 10.5748 & 0.775218 \tabularnewline
172 & 15.95 & 13.6224 & 2.32756 \tabularnewline
173 & 18.1 & 20.9638 & -2.86385 \tabularnewline
174 & 14.6 & 15.2819 & -0.681854 \tabularnewline
175 & 15.4 & 16.0819 & -0.681854 \tabularnewline
176 & 15.4 & 12.8223 & 2.57774 \tabularnewline
177 & 17.6 & 18.5588 & -0.958796 \tabularnewline
178 & 13.35 & 10.7254 & 2.62459 \tabularnewline
179 & 19.1 & 20.6979 & -1.5979 \tabularnewline
180 & 15.35 & 18.3034 & -2.95343 \tabularnewline
181 & 7.6 & 8.80007 & -1.20007 \tabularnewline
182 & 13.4 & 15.0234 & -1.62345 \tabularnewline
183 & 13.9 & 11.3807 & 2.51927 \tabularnewline
184 & 19.1 & 19.1557 & -0.0557493 \tabularnewline
185 & 15.25 & 18.7512 & -3.50116 \tabularnewline
186 & 12.9 & 12.696 & 0.203966 \tabularnewline
187 & 16.1 & 14.1078 & 1.99221 \tabularnewline
188 & 17.35 & 19.9101 & -2.56012 \tabularnewline
189 & 13.15 & 16.5558 & -3.40576 \tabularnewline
190 & 12.15 & 10.5847 & 1.56525 \tabularnewline
191 & 12.6 & 13.5355 & -0.935469 \tabularnewline
192 & 10.35 & 9.36754 & 0.982457 \tabularnewline
193 & 15.4 & 17.9446 & -2.54464 \tabularnewline
194 & 9.6 & 6.58388 & 3.01612 \tabularnewline
195 & 18.2 & 17.7738 & 0.426212 \tabularnewline
196 & 13.6 & 12.1451 & 1.45492 \tabularnewline
197 & 14.85 & 17.0896 & -2.23962 \tabularnewline
198 & 14.75 & 13.7336 & 1.01642 \tabularnewline
199 & 14.1 & 12.6391 & 1.46092 \tabularnewline
200 & 14.9 & 14.2697 & 0.630307 \tabularnewline
201 & 16.25 & 14.8908 & 1.35922 \tabularnewline
202 & 19.25 & 18.1375 & 1.11253 \tabularnewline
203 & 13.6 & 16.0948 & -2.49479 \tabularnewline
204 & 13.6 & 13.3181 & 0.281851 \tabularnewline
205 & 15.65 & 18.1353 & -2.48526 \tabularnewline
206 & 12.75 & 11.5556 & 1.19439 \tabularnewline
207 & 14.6 & 14.6684 & -0.0684224 \tabularnewline
208 & 9.85 & 8.06829 & 1.78171 \tabularnewline
209 & 12.65 & 10.0971 & 2.55289 \tabularnewline
210 & 19.2 & 17.6358 & 1.56418 \tabularnewline
211 & 16.6 & 16.3543 & 0.245678 \tabularnewline
212 & 11.2 & 11.8535 & -0.65345 \tabularnewline
213 & 15.25 & 17.973 & -2.72298 \tabularnewline
214 & 11.9 & 11.7399 & 0.160135 \tabularnewline
215 & 13.2 & 14.0341 & -0.834141 \tabularnewline
216 & 16.35 & 17.3921 & -1.04206 \tabularnewline
217 & 12.4 & 11.248 & 1.15202 \tabularnewline
218 & 15.85 & 13.9423 & 1.90766 \tabularnewline
219 & 18.15 & 18.2897 & -0.139712 \tabularnewline
220 & 11.15 & 11.7176 & -0.567604 \tabularnewline
221 & 15.65 & 14.4716 & 1.17838 \tabularnewline
222 & 17.75 & 21.1734 & -3.42338 \tabularnewline
223 & 7.65 & 9.22311 & -1.57311 \tabularnewline
224 & 12.35 & 11.5717 & 0.778313 \tabularnewline
225 & 15.6 & 13.1499 & 2.45005 \tabularnewline
226 & 19.3 & 15.7065 & 3.59347 \tabularnewline
227 & 15.2 & 13.6292 & 1.57077 \tabularnewline
228 & 17.1 & 15.0462 & 2.05376 \tabularnewline
229 & 15.6 & 11.7911 & 3.80885 \tabularnewline
230 & 18.4 & 15.7059 & 2.69412 \tabularnewline
231 & 19.05 & 16.7205 & 2.32945 \tabularnewline
232 & 18.55 & 16.4617 & 2.08829 \tabularnewline
233 & 19.1 & 19.0515 & 0.0484668 \tabularnewline
234 & 13.1 & 16.395 & -3.29504 \tabularnewline
235 & 12.85 & 14.4641 & -1.61415 \tabularnewline
236 & 9.5 & 14.9696 & -5.46963 \tabularnewline
237 & 4.5 & 3.8291 & 0.670901 \tabularnewline
238 & 11.85 & 14.4758 & -2.62584 \tabularnewline
239 & 13.6 & 13.0224 & 0.577627 \tabularnewline
240 & 11.7 & 12.0897 & -0.389688 \tabularnewline
241 & 12.4 & 13.6482 & -1.24819 \tabularnewline
242 & 13.35 & 14.9957 & -1.64569 \tabularnewline
243 & 11.4 & 11.3413 & 0.0586632 \tabularnewline
244 & 14.9 & 13.9307 & 0.969288 \tabularnewline
245 & 19.9 & 22.033 & -2.13298 \tabularnewline
246 & 11.2 & 11.804 & -0.603966 \tabularnewline
247 & 14.6 & 13.6367 & 0.963317 \tabularnewline
248 & 17.6 & 17.7292 & -0.129155 \tabularnewline
249 & 14.05 & 14.0872 & -0.0372438 \tabularnewline
250 & 16.1 & 18.0408 & -1.94082 \tabularnewline
251 & 13.35 & 17.2464 & -3.89639 \tabularnewline
252 & 11.85 & 12.6418 & -0.791775 \tabularnewline
253 & 11.95 & 10.5646 & 1.38535 \tabularnewline
254 & 14.75 & 13.1321 & 1.61791 \tabularnewline
255 & 15.15 & 18.2289 & -3.07889 \tabularnewline
256 & 13.2 & 12.4746 & 0.725375 \tabularnewline
257 & 16.85 & 21.5881 & -4.73811 \tabularnewline
258 & 7.85 & 12.8467 & -4.99666 \tabularnewline
259 & 7.7 & 10.8408 & -3.14077 \tabularnewline
260 & 12.6 & 19.466 & -6.86601 \tabularnewline
261 & 7.85 & 8.26214 & -0.412138 \tabularnewline
262 & 10.95 & 12.3871 & -1.43714 \tabularnewline
263 & 12.35 & 15.6649 & -3.31493 \tabularnewline
264 & 9.95 & 9.89134 & 0.0586632 \tabularnewline
265 & 14.9 & 13.4533 & 1.44666 \tabularnewline
266 & 16.65 & 15.8048 & 0.845169 \tabularnewline
267 & 13.4 & 12.5871 & 0.812913 \tabularnewline
268 & 13.95 & 13.5917 & 0.358342 \tabularnewline
269 & 15.7 & 13.9704 & 1.72961 \tabularnewline
270 & 16.85 & 16.9901 & -0.140122 \tabularnewline
271 & 10.95 & 10.7524 & 0.197597 \tabularnewline
272 & 15.35 & 16.0692 & -0.71915 \tabularnewline
273 & 12.2 & 10.2501 & 1.94986 \tabularnewline
274 & 15.1 & 13.3134 & 1.78661 \tabularnewline
275 & 17.75 & 17.4374 & 0.312569 \tabularnewline
276 & 15.2 & 15.3245 & -0.124527 \tabularnewline
277 & 14.6 & 13.6756 & 0.924444 \tabularnewline
278 & 16.65 & 19.0052 & -2.35522 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267934&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]10.6637[/C][C]2.23632[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.1624[/C][C]2.03764[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.0257[/C][C]1.7743[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.1224[/C][C]-3.72238[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]9.94643[/C][C]-3.24643[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]12.6102[/C][C]-0.0102496[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]11.3529[/C][C]3.44715[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]10.9116[/C][C]2.3884[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.7427[/C][C]-1.64273[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]10.727[/C][C]-2.52702[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]10.7068[/C][C]0.693156[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]10.7483[/C][C]-4.34828[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.8846[/C][C]0.7154[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.1312[/C][C]-1.13121[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]8.55546[/C][C]-2.25546[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]10.3123[/C][C]0.987706[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]11.7308[/C][C]0.169222[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.6169[/C][C]-1.31686[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.4953[/C][C]-1.89534[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]9.87066[/C][C]0.129345[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]9.91945[/C][C]-3.51945[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]13.2541[/C][C]0.545908[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.0845[/C][C]-1.28453[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]11.6993[/C][C]2.10068[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]11.1632[/C][C]0.536822[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]11.9878[/C][C]-1.08777[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]15.2121[/C][C]0.88791[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.5199[/C][C]2.88012[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]10.2536[/C][C]-0.353555[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]10.3299[/C][C]1.1701[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]9.5104[/C][C]-1.2104[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]10.8897[/C][C]0.810341[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]9.94935[/C][C]-0.949353[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.9243[/C][C]-3.22431[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]10.175[/C][C]0.625041[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]10.2638[/C][C]0.0362209[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]9.80396[/C][C]0.596036[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]11.0438[/C][C]1.65624[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]12.2731[/C][C]-2.97315[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]11.8255[/C][C]-0.0255302[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]9.48853[/C][C]-3.58853[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]11.212[/C][C]0.188047[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.3083[/C][C]1.69167[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]10.1662[/C][C]0.63383[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]9.23032[/C][C]3.06968[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.7128[/C][C]-1.41283[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]9.49964[/C][C]2.30036[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]11.3847[/C][C]-3.48465[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]9.08929[/C][C]3.61071[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]10.2088[/C][C]2.09123[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.7579[/C][C]0.842063[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]8.55833[/C][C]-1.85833[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]9.45977[/C][C]1.44023[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]10.7241[/C][C]1.37593[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.5365[/C][C]2.76346[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]9.55798[/C][C]0.542018[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.0778[/C][C]-5.37779[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]9.84424[/C][C]4.45576[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]8.36126[/C][C]-0.361262[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.4137[/C][C]2.88626[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]11.3235[/C][C]-2.0235[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.4713[/C][C]1.02871[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]9.48943[/C][C]-1.88943[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]11.824[/C][C]4.076[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.3361[/C][C]-2.1361[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]9.49874[/C][C]-0.398743[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]13.1779[/C][C]-2.07787[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]11.8678[/C][C]1.13222[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.9095[/C][C]2.59047[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.9851[/C][C]1.21492[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.505[/C][C]-1.20497[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.1015[/C][C]1.29849[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]10.114[/C][C]-1.31401[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.9008[/C][C]2.69922[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]10.5875[/C][C]2.01245[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]1.41148[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.1558[/C][C]1.8442[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]10.5126[/C][C]2.08735[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]13.6098[/C][C]-0.409752[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]12.1855[/C][C]-2.28546[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]8.19691[/C][C]-0.496915[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]7.43595[/C][C]3.06405[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]13.3214[/C][C]0.0785652[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]15.9269[/C][C]-5.02693[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]5.29042[/C][C]-0.990417[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]9.70701[/C][C]0.59299[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]10.9867[/C][C]0.813283[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]10.8895[/C][C]0.310499[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]13.6553[/C][C]-2.25525[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]6.31016[/C][C]2.28984[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]9.71513[/C][C]3.48487[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]16.7703[/C][C]-4.17033[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]5.68571[/C][C]-0.0857143[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]11.4126[/C][C]-1.51263[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]10.7956[/C][C]-1.99562[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]8.89503[/C][C]-1.19503[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]12.2659[/C][C]-3.26592[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]5.68345[/C][C]1.61655[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]7.35174[/C][C]4.04826[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]16.9917[/C][C]-3.3917[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]6.47938[/C][C]1.42062[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]10.8884[/C][C]-0.188438[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]10.9461[/C][C]-0.646118[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]9.53404[/C][C]-1.23404[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]5.38049[/C][C]4.21951[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]16.5449[/C][C]-2.34488[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]5.16999[/C][C]3.33001[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]18.3683[/C][C]-4.86827[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]7.5257[/C][C]-2.6257[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]7.1352[/C][C]-0.735196[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]8.66177[/C][C]0.938231[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]9.94178[/C][C]1.65822[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]16.5755[/C][C]-5.47545[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]1.85761[/C][C]2.49239[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]10.5956[/C][C]2.10444[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]16.4529[/C][C]1.64715[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]18.1721[/C][C]-0.322121[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]16.0431[/C][C]0.556863[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]13.1371[/C][C]-0.537135[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]15.887[/C][C]1.21296[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]21.3166[/C][C]-2.21659[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]14.4808[/C][C]1.61917[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]11.5541[/C][C]1.79592[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]13.3292[/C][C]5.07083[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.9616[/C][C]-3.26164[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.4208[/C][C]-0.820801[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]12.0406[/C][C]0.559404[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]17.8213[/C][C]-1.62131[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]12.7523[/C][C]0.847685[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]18.6275[/C][C]0.272498[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]13.4097[/C][C]0.690267[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]16.4163[/C][C]-1.91627[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]15.4477[/C][C]0.702253[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]14.1069[/C][C]0.643088[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]13.9765[/C][C]0.823511[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.0126[/C][C]0.437441[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.20962[/C][C]3.44038[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]18.1769[/C][C]-0.826948[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]7.19901[/C][C]1.40099[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]16.9884[/C][C]1.41164[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]16.84[/C][C]-0.739988[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]9.74593[/C][C]1.85407[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]18.5315[/C][C]-0.781532[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]13.249[/C][C]2.00102[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]18.1642[/C][C]-0.514226[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]15.426[/C][C]0.923983[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]18.0441[/C][C]-0.394099[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]13.6725[/C][C]-0.0725256[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]15.1412[/C][C]-0.791167[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]12.9828[/C][C]1.76716[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]24.904[/C][C]-6.654[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]8.64119[/C][C]1.25881[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]14.045[/C][C]1.955[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]18.1528[/C][C]0.0972356[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]14.8603[/C][C]1.98968[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]13.7436[/C][C]0.856435[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]12.2059[/C][C]1.64412[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]18.0566[/C][C]0.89343[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]17.0205[/C][C]-1.42053[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]16.7353[/C][C]-1.88525[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]9.58421[/C][C]2.16579[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.3789[/C][C]3.07109[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]15.9741[/C][C]-0.0741445[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]9.90117[/C][C]7.19883[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]15.1307[/C][C]0.969288[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]20.3121[/C][C]-0.412138[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]10.2472[/C][C]0.702811[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]17.7775[/C][C]0.67245[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]15.5805[/C][C]-0.480547[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]17.449[/C][C]-2.44904[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]10.5748[/C][C]0.775218[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]13.6224[/C][C]2.32756[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]20.9638[/C][C]-2.86385[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]15.2819[/C][C]-0.681854[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.0819[/C][C]-0.681854[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]12.8223[/C][C]2.57774[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]18.5588[/C][C]-0.958796[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]10.7254[/C][C]2.62459[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]20.6979[/C][C]-1.5979[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]18.3034[/C][C]-2.95343[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]8.80007[/C][C]-1.20007[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]15.0234[/C][C]-1.62345[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]11.3807[/C][C]2.51927[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]19.1557[/C][C]-0.0557493[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]18.7512[/C][C]-3.50116[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]12.696[/C][C]0.203966[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]14.1078[/C][C]1.99221[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]19.9101[/C][C]-2.56012[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]16.5558[/C][C]-3.40576[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]10.5847[/C][C]1.56525[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]13.5355[/C][C]-0.935469[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]9.36754[/C][C]0.982457[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]17.9446[/C][C]-2.54464[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]6.58388[/C][C]3.01612[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]17.7738[/C][C]0.426212[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.1451[/C][C]1.45492[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]17.0896[/C][C]-2.23962[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]13.7336[/C][C]1.01642[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]12.6391[/C][C]1.46092[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]14.2697[/C][C]0.630307[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]14.8908[/C][C]1.35922[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]18.1375[/C][C]1.11253[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]16.0948[/C][C]-2.49479[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]13.3181[/C][C]0.281851[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]18.1353[/C][C]-2.48526[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]11.5556[/C][C]1.19439[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]14.6684[/C][C]-0.0684224[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]8.06829[/C][C]1.78171[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]10.0971[/C][C]2.55289[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]17.6358[/C][C]1.56418[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]16.3543[/C][C]0.245678[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]11.8535[/C][C]-0.65345[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]17.973[/C][C]-2.72298[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]11.7399[/C][C]0.160135[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]14.0341[/C][C]-0.834141[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]17.3921[/C][C]-1.04206[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]11.248[/C][C]1.15202[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]13.9423[/C][C]1.90766[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]18.2897[/C][C]-0.139712[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]11.7176[/C][C]-0.567604[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]14.4716[/C][C]1.17838[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]21.1734[/C][C]-3.42338[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]9.22311[/C][C]-1.57311[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]11.5717[/C][C]0.778313[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]13.1499[/C][C]2.45005[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]15.7065[/C][C]3.59347[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]13.6292[/C][C]1.57077[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]15.0462[/C][C]2.05376[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]11.7911[/C][C]3.80885[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]15.7059[/C][C]2.69412[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]16.7205[/C][C]2.32945[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]16.4617[/C][C]2.08829[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]19.0515[/C][C]0.0484668[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]16.395[/C][C]-3.29504[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]14.4641[/C][C]-1.61415[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]14.9696[/C][C]-5.46963[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]3.8291[/C][C]0.670901[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]14.4758[/C][C]-2.62584[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]13.0224[/C][C]0.577627[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]12.0897[/C][C]-0.389688[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.6482[/C][C]-1.24819[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]14.9957[/C][C]-1.64569[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]11.3413[/C][C]0.0586632[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]13.9307[/C][C]0.969288[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]22.033[/C][C]-2.13298[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]11.804[/C][C]-0.603966[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]13.6367[/C][C]0.963317[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]17.7292[/C][C]-0.129155[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]14.0872[/C][C]-0.0372438[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]18.0408[/C][C]-1.94082[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]17.2464[/C][C]-3.89639[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]12.6418[/C][C]-0.791775[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]10.5646[/C][C]1.38535[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]13.1321[/C][C]1.61791[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]18.2289[/C][C]-3.07889[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]12.4746[/C][C]0.725375[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.5881[/C][C]-4.73811[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]12.8467[/C][C]-4.99666[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]10.8408[/C][C]-3.14077[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]19.466[/C][C]-6.86601[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]8.26214[/C][C]-0.412138[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]12.3871[/C][C]-1.43714[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]15.6649[/C][C]-3.31493[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]9.89134[/C][C]0.0586632[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]13.4533[/C][C]1.44666[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]15.8048[/C][C]0.845169[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]12.5871[/C][C]0.812913[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]13.5917[/C][C]0.358342[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]13.9704[/C][C]1.72961[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]16.9901[/C][C]-0.140122[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]10.7524[/C][C]0.197597[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]16.0692[/C][C]-0.71915[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]10.2501[/C][C]1.94986[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]13.3134[/C][C]1.78661[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]17.4374[/C][C]0.312569[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]15.3245[/C][C]-0.124527[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]13.6756[/C][C]0.924444[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]19.0052[/C][C]-2.35522[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267934&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267934&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	10.6637	2.23632
2	12.2	10.1624	2.03764
3	12.8	11.0257	1.7743
4	7.4	11.1224	-3.72238
5	6.7	9.94643	-3.24643
6	12.6	12.6102	-0.0102496
7	14.8	11.3529	3.44715
8	13.3	10.9116	2.3884
9	11.1	12.7427	-1.64273
10	8.2	10.727	-2.52702
11	11.4	10.7068	0.693156
12	6.4	10.7483	-4.34828
13	10.6	9.8846	0.7154
14	12	13.1312	-1.13121
15	6.3	8.55546	-2.25546
16	11.3	10.3123	0.987706
17	11.9	11.7308	0.169222
18	9.3	10.6169	-1.31686
19	9.6	11.4953	-1.89534
20	10	9.87066	0.129345
21	6.4	9.91945	-3.51945
22	13.8	13.2541	0.545908
23	10.8	12.0845	-1.28453
24	13.8	11.6993	2.10068
25	11.7	11.1632	0.536822
26	10.9	11.9878	-1.08777
27	16.1	15.2121	0.88791
28	13.4	10.5199	2.88012
29	9.9	10.2536	-0.353555
30	11.5	10.3299	1.1701
31	8.3	9.5104	-1.2104
32	11.7	10.8897	0.810341
33	9	9.94935	-0.949353
34	9.7	12.9243	-3.22431
35	10.8	10.175	0.625041
36	10.3	10.2638	0.0362209
37	10.4	9.80396	0.596036
38	12.7	11.0438	1.65624
39	9.3	12.2731	-2.97315
40	11.8	11.8255	-0.0255302
41	5.9	9.48853	-3.58853
42	11.4	11.212	0.188047
43	13	11.3083	1.69167
44	10.8	10.1662	0.63383
45	12.3	9.23032	3.06968
46	11.3	12.7128	-1.41283
47	11.8	9.49964	2.30036
48	7.9	11.3847	-3.48465
49	12.7	9.08929	3.61071
50	12.3	10.2088	2.09123
51	11.6	10.7579	0.842063
52	6.7	8.55833	-1.85833
53	10.9	9.45977	1.44023
54	12.1	10.7241	1.37593
55	13.3	10.5365	2.76346
56	10.1	9.55798	0.542018
57	5.7	11.0778	-5.37779
58	14.3	9.84424	4.45576
59	8	8.36126	-0.361262
60	13.3	10.4137	2.88626
61	9.3	11.3235	-2.0235
62	12.5	11.4713	1.02871
63	7.6	9.48943	-1.88943
64	15.9	11.824	4.076
65	9.2	11.3361	-2.1361
66	9.1	9.49874	-0.398743
67	11.1	13.1779	-2.07787
68	13	11.8678	1.13222
69	14.5	11.9095	2.59047
70	12.2	10.9851	1.21492
71	12.3	13.505	-1.20497
72	11.4	10.1015	1.29849
73	8.8	10.114	-1.31401
74	14.6	11.9008	2.69922
75	12.6	10.5875	2.01245
76	NA	NA	1.41148
77	13	11.1558	1.8442
78	12.6	10.5126	2.08735
79	13.2	13.6098	-0.409752
80	9.9	12.1855	-2.28546
81	7.7	8.19691	-0.496915
82	10.5	7.43595	3.06405
83	13.4	13.3214	0.0785652
84	10.9	15.9269	-5.02693
85	4.3	5.29042	-0.990417
86	10.3	9.70701	0.59299
87	11.8	10.9867	0.813283
88	11.2	10.8895	0.310499
89	11.4	13.6553	-2.25525
90	8.6	6.31016	2.28984
91	13.2	9.71513	3.48487
92	12.6	16.7703	-4.17033
93	5.6	5.68571	-0.0857143
94	9.9	11.4126	-1.51263
95	8.8	10.7956	-1.99562
96	7.7	8.89503	-1.19503
97	9	12.2659	-3.26592
98	7.3	5.68345	1.61655
99	11.4	7.35174	4.04826
100	13.6	16.9917	-3.3917
101	7.9	6.47938	1.42062
102	10.7	10.8884	-0.188438
103	10.3	10.9461	-0.646118
104	8.3	9.53404	-1.23404
105	9.6	5.38049	4.21951
106	14.2	16.5449	-2.34488
107	8.5	5.16999	3.33001
108	13.5	18.3683	-4.86827
109	4.9	7.5257	-2.6257
110	6.4	7.1352	-0.735196
111	9.6	8.66177	0.938231
112	11.6	9.94178	1.65822
113	11.1	16.5755	-5.47545
114	4.35	1.85761	2.49239
115	12.7	10.5956	2.10444
116	18.1	16.4529	1.64715
117	17.85	18.1721	-0.322121
118	16.6	16.0431	0.556863
119	12.6	13.1371	-0.537135
120	17.1	15.887	1.21296
121	19.1	21.3166	-2.21659
122	16.1	14.4808	1.61917
123	13.35	11.5541	1.79592
124	18.4	13.3292	5.07083
125	14.7	17.9616	-3.26164
126	10.6	11.4208	-0.820801
127	12.6	12.0406	0.559404
128	16.2	17.8213	-1.62131
129	13.6	12.7523	0.847685
130	18.9	18.6275	0.272498
131	14.1	13.4097	0.690267
132	14.5	16.4163	-1.91627
133	16.15	15.4477	0.702253
134	14.75	14.1069	0.643088
135	14.8	13.9765	0.823511
136	12.45	12.0126	0.437441
137	12.65	9.20962	3.44038
138	17.35	18.1769	-0.826948
139	8.6	7.19901	1.40099
140	18.4	16.9884	1.41164
141	16.1	16.84	-0.739988
142	11.6	9.74593	1.85407
143	17.75	18.5315	-0.781532
144	15.25	13.249	2.00102
145	17.65	18.1642	-0.514226
146	16.35	15.426	0.923983
147	17.65	18.0441	-0.394099
148	13.6	13.6725	-0.0725256
149	14.35	15.1412	-0.791167
150	14.75	12.9828	1.76716
151	18.25	24.904	-6.654
152	9.9	8.64119	1.25881
153	16	14.045	1.955
154	18.25	18.1528	0.0972356
155	16.85	14.8603	1.98968
156	14.6	13.7436	0.856435
157	13.85	12.2059	1.64412
158	18.95	18.0566	0.89343
159	15.6	17.0205	-1.42053
160	14.85	16.7353	-1.88525
161	11.75	9.58421	2.16579
162	18.45	15.3789	3.07109
163	15.9	15.9741	-0.0741445
164	17.1	9.90117	7.19883
165	16.1	15.1307	0.969288
166	19.9	20.3121	-0.412138
167	10.95	10.2472	0.702811
168	18.45	17.7775	0.67245
169	15.1	15.5805	-0.480547
170	15	17.449	-2.44904
171	11.35	10.5748	0.775218
172	15.95	13.6224	2.32756
173	18.1	20.9638	-2.86385
174	14.6	15.2819	-0.681854
175	15.4	16.0819	-0.681854
176	15.4	12.8223	2.57774
177	17.6	18.5588	-0.958796
178	13.35	10.7254	2.62459
179	19.1	20.6979	-1.5979
180	15.35	18.3034	-2.95343
181	7.6	8.80007	-1.20007
182	13.4	15.0234	-1.62345
183	13.9	11.3807	2.51927
184	19.1	19.1557	-0.0557493
185	15.25	18.7512	-3.50116
186	12.9	12.696	0.203966
187	16.1	14.1078	1.99221
188	17.35	19.9101	-2.56012
189	13.15	16.5558	-3.40576
190	12.15	10.5847	1.56525
191	12.6	13.5355	-0.935469
192	10.35	9.36754	0.982457
193	15.4	17.9446	-2.54464
194	9.6	6.58388	3.01612
195	18.2	17.7738	0.426212
196	13.6	12.1451	1.45492
197	14.85	17.0896	-2.23962
198	14.75	13.7336	1.01642
199	14.1	12.6391	1.46092
200	14.9	14.2697	0.630307
201	16.25	14.8908	1.35922
202	19.25	18.1375	1.11253
203	13.6	16.0948	-2.49479
204	13.6	13.3181	0.281851
205	15.65	18.1353	-2.48526
206	12.75	11.5556	1.19439
207	14.6	14.6684	-0.0684224
208	9.85	8.06829	1.78171
209	12.65	10.0971	2.55289
210	19.2	17.6358	1.56418
211	16.6	16.3543	0.245678
212	11.2	11.8535	-0.65345
213	15.25	17.973	-2.72298
214	11.9	11.7399	0.160135
215	13.2	14.0341	-0.834141
216	16.35	17.3921	-1.04206
217	12.4	11.248	1.15202
218	15.85	13.9423	1.90766
219	18.15	18.2897	-0.139712
220	11.15	11.7176	-0.567604
221	15.65	14.4716	1.17838
222	17.75	21.1734	-3.42338
223	7.65	9.22311	-1.57311
224	12.35	11.5717	0.778313
225	15.6	13.1499	2.45005
226	19.3	15.7065	3.59347
227	15.2	13.6292	1.57077
228	17.1	15.0462	2.05376
229	15.6	11.7911	3.80885
230	18.4	15.7059	2.69412
231	19.05	16.7205	2.32945
232	18.55	16.4617	2.08829
233	19.1	19.0515	0.0484668
234	13.1	16.395	-3.29504
235	12.85	14.4641	-1.61415
236	9.5	14.9696	-5.46963
237	4.5	3.8291	0.670901
238	11.85	14.4758	-2.62584
239	13.6	13.0224	0.577627
240	11.7	12.0897	-0.389688
241	12.4	13.6482	-1.24819
242	13.35	14.9957	-1.64569
243	11.4	11.3413	0.0586632
244	14.9	13.9307	0.969288
245	19.9	22.033	-2.13298
246	11.2	11.804	-0.603966
247	14.6	13.6367	0.963317
248	17.6	17.7292	-0.129155
249	14.05	14.0872	-0.0372438
250	16.1	18.0408	-1.94082
251	13.35	17.2464	-3.89639
252	11.85	12.6418	-0.791775
253	11.95	10.5646	1.38535
254	14.75	13.1321	1.61791
255	15.15	18.2289	-3.07889
256	13.2	12.4746	0.725375
257	16.85	21.5881	-4.73811
258	7.85	12.8467	-4.99666
259	7.7	10.8408	-3.14077
260	12.6	19.466	-6.86601
261	7.85	8.26214	-0.412138
262	10.95	12.3871	-1.43714
263	12.35	15.6649	-3.31493
264	9.95	9.89134	0.0586632
265	14.9	13.4533	1.44666
266	16.65	15.8048	0.845169
267	13.4	12.5871	0.812913
268	13.95	13.5917	0.358342
269	15.7	13.9704	1.72961
270	16.85	16.9901	-0.140122
271	10.95	10.7524	0.197597
272	15.35	16.0692	-0.71915
273	12.2	10.2501	1.94986
274	15.1	13.3134	1.78661
275	17.75	17.4374	0.312569
276	15.2	15.3245	-0.124527
277	14.6	13.6756	0.924444
278	16.65	19.0052	-2.35522
279	8.1	NA	NA

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
11	0.95047	0.09906	0.04953
12	0.943756	0.112489	0.0562444
13	0.934118	0.131763	0.0658817
14	0.937382	0.125237	0.0626184
15	0.914547	0.170906	0.085453
16	0.86892	0.26216	0.13108
17	0.816261	0.367478	0.183739
18	0.781366	0.437268	0.218634
19	0.792179	0.415642	0.207821
20	0.728558	0.542885	0.271442
21	0.686332	0.627335	0.313668
22	0.665767	0.668466	0.334233
23	0.660537	0.678925	0.339463
24	0.692714	0.614571	0.307286
25	0.626997	0.746006	0.373003
26	0.573879	0.852242	0.426121
27	0.517926	0.964147	0.482074
28	0.510115	0.979769	0.489885
29	0.44733	0.894661	0.55267
30	0.403781	0.807562	0.596219
31	0.363046	0.726093	0.636954
32	0.309678	0.619356	0.690322
33	0.261912	0.523824	0.738088
34	0.249877	0.499754	0.750123
35	0.221281	0.442562	0.778719
36	0.19491	0.389821	0.80509
37	0.174487	0.348974	0.825513
38	0.199333	0.398666	0.800667
39	0.20552	0.411039	0.79448
40	0.174661	0.349321	0.825339
41	0.210901	0.421801	0.789099
42	0.183827	0.367653	0.816173
43	0.179371	0.358742	0.820629
44	0.149243	0.298487	0.850757
45	0.158869	0.317738	0.841131
46	0.141362	0.282725	0.858638
47	0.152593	0.305186	0.847407
48	0.240784	0.481569	0.759216
49	0.263755	0.52751	0.736245
50	0.25527	0.51054	0.74473
51	0.218419	0.436837	0.781581
52	0.23259	0.465181	0.76741
53	0.223033	0.446065	0.776967
54	0.193727	0.387453	0.806273
55	0.252539	0.505078	0.747461
56	0.217303	0.434606	0.782697
57	0.480371	0.960741	0.519629
58	0.633099	0.733803	0.366901
59	0.591727	0.816547	0.408273
60	0.581656	0.836688	0.418344
61	0.60855	0.782899	0.39145
62	0.598498	0.803004	0.401502
63	0.604416	0.791167	0.395584
64	0.693782	0.612437	0.306218
65	0.682249	0.635502	0.317751
66	0.647554	0.704892	0.352446
67	0.631461	0.737078	0.368539
68	0.592979	0.814041	0.407021
69	0.645244	0.709512	0.354756
70	0.615749	0.768502	0.384251
71	0.580511	0.838977	0.419489
72	0.557392	0.885216	0.442608
73	0.543218	0.913564	0.456782
74	0.553408	0.893183	0.446592
75	0.546552	0.906896	0.453448
76	0.524039	0.951921	0.475961
77	0.510163	0.979675	0.489837
78	0.502454	0.995092	0.497546
79	0.464859	0.929718	0.535141
80	0.47204	0.94408	0.52796
81	0.437417	0.874835	0.562583
82	0.461991	0.923982	0.538009
83	0.426241	0.852483	0.573759
84	0.608281	0.783439	0.391719
85	0.582957	0.834086	0.417043
86	0.546583	0.906834	0.453417
87	0.512874	0.974252	0.487126
88	0.476886	0.953772	0.523114
89	0.475046	0.950091	0.524954
90	0.477922	0.955843	0.522078
91	0.518933	0.962135	0.481067
92	0.611579	0.776841	0.388421
93	0.580446	0.839108	0.419554
94	0.557124	0.885752	0.442876
95	0.546353	0.907294	0.453647
96	0.516499	0.967003	0.483501
97	0.548264	0.903473	0.451736
98	0.539578	0.920845	0.460422
99	0.636406	0.727188	0.363594
100	0.67488	0.650241	0.32512
101	0.652079	0.695841	0.347921
102	0.618266	0.763468	0.381734
103	0.58881	0.822381	0.41119
104	0.563914	0.872172	0.436086
105	0.650295	0.69941	0.349705
106	0.648626	0.702748	0.351374
107	0.700022	0.599955	0.299978
108	0.802904	0.394191	0.197096
109	0.815962	0.368077	0.184038
110	0.800174	0.399652	0.199826
111	0.779283	0.441434	0.220717
112	0.761752	0.476495	0.238248
113	0.80447	0.391061	0.19553
114	0.862247	0.275505	0.137753
115	0.897172	0.205656	0.102828
116	0.889818	0.220365	0.110182
117	0.872641	0.254718	0.127359
118	0.854073	0.291854	0.145927
119	0.834577	0.330846	0.165423
120	0.817765	0.364471	0.182235
121	0.817656	0.364688	0.182344
122	0.80533	0.38934	0.19467
123	0.792417	0.415166	0.207583
124	0.87457	0.25086	0.12543
125	0.900589	0.198822	0.0994109
126	0.887903	0.224194	0.112097
127	0.871144	0.257713	0.128856
128	0.865661	0.268678	0.134339
129	0.848338	0.303325	0.151662
130	0.82701	0.34598	0.17299
131	0.805866	0.388268	0.194134
132	0.803785	0.39243	0.196215
133	0.780382	0.439236	0.219618
134	0.754721	0.490558	0.245279
135	0.730134	0.539733	0.269866
136	0.701102	0.597796	0.298898
137	0.740968	0.518064	0.259032
138	0.718325	0.563349	0.281675
139	0.697059	0.605882	0.302941
140	0.675235	0.649531	0.324765
141	0.648592	0.702817	0.351408
142	0.638862	0.722276	0.361138
143	0.613005	0.773989	0.386995
144	0.601418	0.797164	0.398582
145	0.571584	0.856832	0.428416
146	0.540916	0.918169	0.459084
147	0.508379	0.983243	0.491621
148	0.473842	0.947685	0.526158
149	0.445636	0.891273	0.554364
150	0.434044	0.868089	0.565956
151	0.704802	0.590397	0.295198
152	0.683345	0.633311	0.316655
153	0.678409	0.643183	0.321591
154	0.646377	0.707245	0.353623
155	0.641764	0.716471	0.358236
156	0.613898	0.772204	0.386102
157	0.599859	0.800281	0.400141
158	0.57139	0.85722	0.42861
159	0.554263	0.891475	0.445737
160	0.5483	0.903399	0.4517
161	0.543293	0.913413	0.456707
162	0.579507	0.840986	0.420493
163	0.544438	0.911125	0.455562
164	0.888587	0.222825	0.111413
165	0.872724	0.254553	0.127276
166	0.855642	0.288716	0.144358
167	0.836185	0.32763	0.163815
168	0.821367	0.357266	0.178633
169	0.798687	0.402626	0.201313
170	0.81193	0.376141	0.18807
171	0.794614	0.410772	0.205386
172	0.79146	0.417081	0.20854
173	0.811762	0.376476	0.188238
174	0.789477	0.421046	0.210523
175	0.765178	0.469643	0.234822
176	0.777499	0.445002	0.222501
177	0.753779	0.492443	0.246221
178	0.765744	0.468512	0.234256
179	0.755329	0.489343	0.244671
180	0.769586	0.460828	0.230414
181	0.761097	0.477806	0.238903
182	0.758104	0.483793	0.241896
183	0.780732	0.438537	0.219268
184	0.752764	0.494472	0.247236
185	0.800472	0.399056	0.199528
186	0.773244	0.453512	0.226756
187	0.766727	0.466546	0.233273
188	0.787866	0.424268	0.212134
189	0.843508	0.312984	0.156492
190	0.835463	0.329074	0.164537
191	0.814364	0.371271	0.185636
192	0.792016	0.415967	0.207984
193	0.794107	0.411787	0.205893
194	0.804734	0.390533	0.195266
195	0.77698	0.446041	0.22302
196	0.773066	0.453869	0.226934
197	0.774137	0.451727	0.225863
198	0.746098	0.507804	0.253902
199	0.723003	0.553993	0.276997
200	0.689748	0.620505	0.310252
201	0.658148	0.683705	0.341852
202	0.646438	0.707123	0.353562
203	0.657238	0.685524	0.342762
204	0.621416	0.757168	0.378584
205	0.60652	0.786959	0.39348
206	0.579682	0.840635	0.420318
207	0.56975	0.860499	0.43025
208	0.587551	0.824898	0.412449
209	0.571702	0.856596	0.428298
210	0.561975	0.87605	0.438025
211	0.543686	0.912628	0.456314
212	0.503103	0.993794	0.496897
213	0.518468	0.963064	0.481532
214	0.475873	0.951747	0.524127
215	0.446973	0.893946	0.553027
216	0.40871	0.81742	0.59129
217	0.394177	0.788354	0.605823
218	0.390158	0.780316	0.609842
219	0.360202	0.720405	0.639798
220	0.329845	0.65969	0.670155
221	0.296771	0.593543	0.703229
222	0.358876	0.717751	0.641124
223	0.324856	0.649712	0.675144
224	0.32673	0.653461	0.67327
225	0.317388	0.634775	0.682612
226	0.379892	0.759785	0.620108
227	0.375314	0.750628	0.624686
228	0.392491	0.784982	0.607509
229	0.633022	0.733956	0.366978
230	0.670265	0.65947	0.329735
231	0.666866	0.666267	0.333134
232	0.696935	0.60613	0.303065
233	0.663939	0.672122	0.336061
234	0.65547	0.689061	0.34453
235	0.613639	0.772723	0.386361
236	0.677496	0.645008	0.322504
237	0.632719	0.734563	0.367281
238	0.600186	0.799628	0.399814
239	0.654558	0.690884	0.345442
240	0.608438	0.783123	0.391562
241	0.555889	0.888222	0.444111
242	0.526594	0.946811	0.473406
243	0.484946	0.969892	0.515054
244	0.428962	0.857924	0.571038
245	0.395102	0.790204	0.604898
246	0.33958	0.67916	0.66042
247	0.311324	0.622649	0.688676
248	0.340386	0.680772	0.659614
249	0.31558	0.631159	0.68442
250	0.309886	0.619772	0.690114
251	0.268905	0.537811	0.731095
252	0.260847	0.521694	0.739153
253	0.240024	0.480047	0.759976
254	0.214923	0.429845	0.785077
255	0.173147	0.346294	0.826853
256	0.13046	0.260919	0.86954
257	0.186345	0.372691	0.813655
258	0.270522	0.541043	0.729478
259	0.330186	0.660371	0.669814
260	0.925521	0.148958	0.0744788
261	0.903516	0.192968	0.0964838
262	0.907044	0.185911	0.0929557
263	0.977108	0.0457846	0.0228923
264	0.954879	0.0902421	0.045121
265	0.915521	0.168958	0.0844792
266	0.93432	0.131359	0.0656796
267	0.936295	0.12741	0.063705
268	0.842785	0.31443	0.157215

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.95047 & 0.09906 & 0.04953 \tabularnewline
12 & 0.943756 & 0.112489 & 0.0562444 \tabularnewline
13 & 0.934118 & 0.131763 & 0.0658817 \tabularnewline
14 & 0.937382 & 0.125237 & 0.0626184 \tabularnewline
15 & 0.914547 & 0.170906 & 0.085453 \tabularnewline
16 & 0.86892 & 0.26216 & 0.13108 \tabularnewline
17 & 0.816261 & 0.367478 & 0.183739 \tabularnewline
18 & 0.781366 & 0.437268 & 0.218634 \tabularnewline
19 & 0.792179 & 0.415642 & 0.207821 \tabularnewline
20 & 0.728558 & 0.542885 & 0.271442 \tabularnewline
21 & 0.686332 & 0.627335 & 0.313668 \tabularnewline
22 & 0.665767 & 0.668466 & 0.334233 \tabularnewline
23 & 0.660537 & 0.678925 & 0.339463 \tabularnewline
24 & 0.692714 & 0.614571 & 0.307286 \tabularnewline
25 & 0.626997 & 0.746006 & 0.373003 \tabularnewline
26 & 0.573879 & 0.852242 & 0.426121 \tabularnewline
27 & 0.517926 & 0.964147 & 0.482074 \tabularnewline
28 & 0.510115 & 0.979769 & 0.489885 \tabularnewline
29 & 0.44733 & 0.894661 & 0.55267 \tabularnewline
30 & 0.403781 & 0.807562 & 0.596219 \tabularnewline
31 & 0.363046 & 0.726093 & 0.636954 \tabularnewline
32 & 0.309678 & 0.619356 & 0.690322 \tabularnewline
33 & 0.261912 & 0.523824 & 0.738088 \tabularnewline
34 & 0.249877 & 0.499754 & 0.750123 \tabularnewline
35 & 0.221281 & 0.442562 & 0.778719 \tabularnewline
36 & 0.19491 & 0.389821 & 0.80509 \tabularnewline
37 & 0.174487 & 0.348974 & 0.825513 \tabularnewline
38 & 0.199333 & 0.398666 & 0.800667 \tabularnewline
39 & 0.20552 & 0.411039 & 0.79448 \tabularnewline
40 & 0.174661 & 0.349321 & 0.825339 \tabularnewline
41 & 0.210901 & 0.421801 & 0.789099 \tabularnewline
42 & 0.183827 & 0.367653 & 0.816173 \tabularnewline
43 & 0.179371 & 0.358742 & 0.820629 \tabularnewline
44 & 0.149243 & 0.298487 & 0.850757 \tabularnewline
45 & 0.158869 & 0.317738 & 0.841131 \tabularnewline
46 & 0.141362 & 0.282725 & 0.858638 \tabularnewline
47 & 0.152593 & 0.305186 & 0.847407 \tabularnewline
48 & 0.240784 & 0.481569 & 0.759216 \tabularnewline
49 & 0.263755 & 0.52751 & 0.736245 \tabularnewline
50 & 0.25527 & 0.51054 & 0.74473 \tabularnewline
51 & 0.218419 & 0.436837 & 0.781581 \tabularnewline
52 & 0.23259 & 0.465181 & 0.76741 \tabularnewline
53 & 0.223033 & 0.446065 & 0.776967 \tabularnewline
54 & 0.193727 & 0.387453 & 0.806273 \tabularnewline
55 & 0.252539 & 0.505078 & 0.747461 \tabularnewline
56 & 0.217303 & 0.434606 & 0.782697 \tabularnewline
57 & 0.480371 & 0.960741 & 0.519629 \tabularnewline
58 & 0.633099 & 0.733803 & 0.366901 \tabularnewline
59 & 0.591727 & 0.816547 & 0.408273 \tabularnewline
60 & 0.581656 & 0.836688 & 0.418344 \tabularnewline
61 & 0.60855 & 0.782899 & 0.39145 \tabularnewline
62 & 0.598498 & 0.803004 & 0.401502 \tabularnewline
63 & 0.604416 & 0.791167 & 0.395584 \tabularnewline
64 & 0.693782 & 0.612437 & 0.306218 \tabularnewline
65 & 0.682249 & 0.635502 & 0.317751 \tabularnewline
66 & 0.647554 & 0.704892 & 0.352446 \tabularnewline
67 & 0.631461 & 0.737078 & 0.368539 \tabularnewline
68 & 0.592979 & 0.814041 & 0.407021 \tabularnewline
69 & 0.645244 & 0.709512 & 0.354756 \tabularnewline
70 & 0.615749 & 0.768502 & 0.384251 \tabularnewline
71 & 0.580511 & 0.838977 & 0.419489 \tabularnewline
72 & 0.557392 & 0.885216 & 0.442608 \tabularnewline
73 & 0.543218 & 0.913564 & 0.456782 \tabularnewline
74 & 0.553408 & 0.893183 & 0.446592 \tabularnewline
75 & 0.546552 & 0.906896 & 0.453448 \tabularnewline
76 & 0.524039 & 0.951921 & 0.475961 \tabularnewline
77 & 0.510163 & 0.979675 & 0.489837 \tabularnewline
78 & 0.502454 & 0.995092 & 0.497546 \tabularnewline
79 & 0.464859 & 0.929718 & 0.535141 \tabularnewline
80 & 0.47204 & 0.94408 & 0.52796 \tabularnewline
81 & 0.437417 & 0.874835 & 0.562583 \tabularnewline
82 & 0.461991 & 0.923982 & 0.538009 \tabularnewline
83 & 0.426241 & 0.852483 & 0.573759 \tabularnewline
84 & 0.608281 & 0.783439 & 0.391719 \tabularnewline
85 & 0.582957 & 0.834086 & 0.417043 \tabularnewline
86 & 0.546583 & 0.906834 & 0.453417 \tabularnewline
87 & 0.512874 & 0.974252 & 0.487126 \tabularnewline
88 & 0.476886 & 0.953772 & 0.523114 \tabularnewline
89 & 0.475046 & 0.950091 & 0.524954 \tabularnewline
90 & 0.477922 & 0.955843 & 0.522078 \tabularnewline
91 & 0.518933 & 0.962135 & 0.481067 \tabularnewline
92 & 0.611579 & 0.776841 & 0.388421 \tabularnewline
93 & 0.580446 & 0.839108 & 0.419554 \tabularnewline
94 & 0.557124 & 0.885752 & 0.442876 \tabularnewline
95 & 0.546353 & 0.907294 & 0.453647 \tabularnewline
96 & 0.516499 & 0.967003 & 0.483501 \tabularnewline
97 & 0.548264 & 0.903473 & 0.451736 \tabularnewline
98 & 0.539578 & 0.920845 & 0.460422 \tabularnewline
99 & 0.636406 & 0.727188 & 0.363594 \tabularnewline
100 & 0.67488 & 0.650241 & 0.32512 \tabularnewline
101 & 0.652079 & 0.695841 & 0.347921 \tabularnewline
102 & 0.618266 & 0.763468 & 0.381734 \tabularnewline
103 & 0.58881 & 0.822381 & 0.41119 \tabularnewline
104 & 0.563914 & 0.872172 & 0.436086 \tabularnewline
105 & 0.650295 & 0.69941 & 0.349705 \tabularnewline
106 & 0.648626 & 0.702748 & 0.351374 \tabularnewline
107 & 0.700022 & 0.599955 & 0.299978 \tabularnewline
108 & 0.802904 & 0.394191 & 0.197096 \tabularnewline
109 & 0.815962 & 0.368077 & 0.184038 \tabularnewline
110 & 0.800174 & 0.399652 & 0.199826 \tabularnewline
111 & 0.779283 & 0.441434 & 0.220717 \tabularnewline
112 & 0.761752 & 0.476495 & 0.238248 \tabularnewline
113 & 0.80447 & 0.391061 & 0.19553 \tabularnewline
114 & 0.862247 & 0.275505 & 0.137753 \tabularnewline
115 & 0.897172 & 0.205656 & 0.102828 \tabularnewline
116 & 0.889818 & 0.220365 & 0.110182 \tabularnewline
117 & 0.872641 & 0.254718 & 0.127359 \tabularnewline
118 & 0.854073 & 0.291854 & 0.145927 \tabularnewline
119 & 0.834577 & 0.330846 & 0.165423 \tabularnewline
120 & 0.817765 & 0.364471 & 0.182235 \tabularnewline
121 & 0.817656 & 0.364688 & 0.182344 \tabularnewline
122 & 0.80533 & 0.38934 & 0.19467 \tabularnewline
123 & 0.792417 & 0.415166 & 0.207583 \tabularnewline
124 & 0.87457 & 0.25086 & 0.12543 \tabularnewline
125 & 0.900589 & 0.198822 & 0.0994109 \tabularnewline
126 & 0.887903 & 0.224194 & 0.112097 \tabularnewline
127 & 0.871144 & 0.257713 & 0.128856 \tabularnewline
128 & 0.865661 & 0.268678 & 0.134339 \tabularnewline
129 & 0.848338 & 0.303325 & 0.151662 \tabularnewline
130 & 0.82701 & 0.34598 & 0.17299 \tabularnewline
131 & 0.805866 & 0.388268 & 0.194134 \tabularnewline
132 & 0.803785 & 0.39243 & 0.196215 \tabularnewline
133 & 0.780382 & 0.439236 & 0.219618 \tabularnewline
134 & 0.754721 & 0.490558 & 0.245279 \tabularnewline
135 & 0.730134 & 0.539733 & 0.269866 \tabularnewline
136 & 0.701102 & 0.597796 & 0.298898 \tabularnewline
137 & 0.740968 & 0.518064 & 0.259032 \tabularnewline
138 & 0.718325 & 0.563349 & 0.281675 \tabularnewline
139 & 0.697059 & 0.605882 & 0.302941 \tabularnewline
140 & 0.675235 & 0.649531 & 0.324765 \tabularnewline
141 & 0.648592 & 0.702817 & 0.351408 \tabularnewline
142 & 0.638862 & 0.722276 & 0.361138 \tabularnewline
143 & 0.613005 & 0.773989 & 0.386995 \tabularnewline
144 & 0.601418 & 0.797164 & 0.398582 \tabularnewline
145 & 0.571584 & 0.856832 & 0.428416 \tabularnewline
146 & 0.540916 & 0.918169 & 0.459084 \tabularnewline
147 & 0.508379 & 0.983243 & 0.491621 \tabularnewline
148 & 0.473842 & 0.947685 & 0.526158 \tabularnewline
149 & 0.445636 & 0.891273 & 0.554364 \tabularnewline
150 & 0.434044 & 0.868089 & 0.565956 \tabularnewline
151 & 0.704802 & 0.590397 & 0.295198 \tabularnewline
152 & 0.683345 & 0.633311 & 0.316655 \tabularnewline
153 & 0.678409 & 0.643183 & 0.321591 \tabularnewline
154 & 0.646377 & 0.707245 & 0.353623 \tabularnewline
155 & 0.641764 & 0.716471 & 0.358236 \tabularnewline
156 & 0.613898 & 0.772204 & 0.386102 \tabularnewline
157 & 0.599859 & 0.800281 & 0.400141 \tabularnewline
158 & 0.57139 & 0.85722 & 0.42861 \tabularnewline
159 & 0.554263 & 0.891475 & 0.445737 \tabularnewline
160 & 0.5483 & 0.903399 & 0.4517 \tabularnewline
161 & 0.543293 & 0.913413 & 0.456707 \tabularnewline
162 & 0.579507 & 0.840986 & 0.420493 \tabularnewline
163 & 0.544438 & 0.911125 & 0.455562 \tabularnewline
164 & 0.888587 & 0.222825 & 0.111413 \tabularnewline
165 & 0.872724 & 0.254553 & 0.127276 \tabularnewline
166 & 0.855642 & 0.288716 & 0.144358 \tabularnewline
167 & 0.836185 & 0.32763 & 0.163815 \tabularnewline
168 & 0.821367 & 0.357266 & 0.178633 \tabularnewline
169 & 0.798687 & 0.402626 & 0.201313 \tabularnewline
170 & 0.81193 & 0.376141 & 0.18807 \tabularnewline
171 & 0.794614 & 0.410772 & 0.205386 \tabularnewline
172 & 0.79146 & 0.417081 & 0.20854 \tabularnewline
173 & 0.811762 & 0.376476 & 0.188238 \tabularnewline
174 & 0.789477 & 0.421046 & 0.210523 \tabularnewline
175 & 0.765178 & 0.469643 & 0.234822 \tabularnewline
176 & 0.777499 & 0.445002 & 0.222501 \tabularnewline
177 & 0.753779 & 0.492443 & 0.246221 \tabularnewline
178 & 0.765744 & 0.468512 & 0.234256 \tabularnewline
179 & 0.755329 & 0.489343 & 0.244671 \tabularnewline
180 & 0.769586 & 0.460828 & 0.230414 \tabularnewline
181 & 0.761097 & 0.477806 & 0.238903 \tabularnewline
182 & 0.758104 & 0.483793 & 0.241896 \tabularnewline
183 & 0.780732 & 0.438537 & 0.219268 \tabularnewline
184 & 0.752764 & 0.494472 & 0.247236 \tabularnewline
185 & 0.800472 & 0.399056 & 0.199528 \tabularnewline
186 & 0.773244 & 0.453512 & 0.226756 \tabularnewline
187 & 0.766727 & 0.466546 & 0.233273 \tabularnewline
188 & 0.787866 & 0.424268 & 0.212134 \tabularnewline
189 & 0.843508 & 0.312984 & 0.156492 \tabularnewline
190 & 0.835463 & 0.329074 & 0.164537 \tabularnewline
191 & 0.814364 & 0.371271 & 0.185636 \tabularnewline
192 & 0.792016 & 0.415967 & 0.207984 \tabularnewline
193 & 0.794107 & 0.411787 & 0.205893 \tabularnewline
194 & 0.804734 & 0.390533 & 0.195266 \tabularnewline
195 & 0.77698 & 0.446041 & 0.22302 \tabularnewline
196 & 0.773066 & 0.453869 & 0.226934 \tabularnewline
197 & 0.774137 & 0.451727 & 0.225863 \tabularnewline
198 & 0.746098 & 0.507804 & 0.253902 \tabularnewline
199 & 0.723003 & 0.553993 & 0.276997 \tabularnewline
200 & 0.689748 & 0.620505 & 0.310252 \tabularnewline
201 & 0.658148 & 0.683705 & 0.341852 \tabularnewline
202 & 0.646438 & 0.707123 & 0.353562 \tabularnewline
203 & 0.657238 & 0.685524 & 0.342762 \tabularnewline
204 & 0.621416 & 0.757168 & 0.378584 \tabularnewline
205 & 0.60652 & 0.786959 & 0.39348 \tabularnewline
206 & 0.579682 & 0.840635 & 0.420318 \tabularnewline
207 & 0.56975 & 0.860499 & 0.43025 \tabularnewline
208 & 0.587551 & 0.824898 & 0.412449 \tabularnewline
209 & 0.571702 & 0.856596 & 0.428298 \tabularnewline
210 & 0.561975 & 0.87605 & 0.438025 \tabularnewline
211 & 0.543686 & 0.912628 & 0.456314 \tabularnewline
212 & 0.503103 & 0.993794 & 0.496897 \tabularnewline
213 & 0.518468 & 0.963064 & 0.481532 \tabularnewline
214 & 0.475873 & 0.951747 & 0.524127 \tabularnewline
215 & 0.446973 & 0.893946 & 0.553027 \tabularnewline
216 & 0.40871 & 0.81742 & 0.59129 \tabularnewline
217 & 0.394177 & 0.788354 & 0.605823 \tabularnewline
218 & 0.390158 & 0.780316 & 0.609842 \tabularnewline
219 & 0.360202 & 0.720405 & 0.639798 \tabularnewline
220 & 0.329845 & 0.65969 & 0.670155 \tabularnewline
221 & 0.296771 & 0.593543 & 0.703229 \tabularnewline
222 & 0.358876 & 0.717751 & 0.641124 \tabularnewline
223 & 0.324856 & 0.649712 & 0.675144 \tabularnewline
224 & 0.32673 & 0.653461 & 0.67327 \tabularnewline
225 & 0.317388 & 0.634775 & 0.682612 \tabularnewline
226 & 0.379892 & 0.759785 & 0.620108 \tabularnewline
227 & 0.375314 & 0.750628 & 0.624686 \tabularnewline
228 & 0.392491 & 0.784982 & 0.607509 \tabularnewline
229 & 0.633022 & 0.733956 & 0.366978 \tabularnewline
230 & 0.670265 & 0.65947 & 0.329735 \tabularnewline
231 & 0.666866 & 0.666267 & 0.333134 \tabularnewline
232 & 0.696935 & 0.60613 & 0.303065 \tabularnewline
233 & 0.663939 & 0.672122 & 0.336061 \tabularnewline
234 & 0.65547 & 0.689061 & 0.34453 \tabularnewline
235 & 0.613639 & 0.772723 & 0.386361 \tabularnewline
236 & 0.677496 & 0.645008 & 0.322504 \tabularnewline
237 & 0.632719 & 0.734563 & 0.367281 \tabularnewline
238 & 0.600186 & 0.799628 & 0.399814 \tabularnewline
239 & 0.654558 & 0.690884 & 0.345442 \tabularnewline
240 & 0.608438 & 0.783123 & 0.391562 \tabularnewline
241 & 0.555889 & 0.888222 & 0.444111 \tabularnewline
242 & 0.526594 & 0.946811 & 0.473406 \tabularnewline
243 & 0.484946 & 0.969892 & 0.515054 \tabularnewline
244 & 0.428962 & 0.857924 & 0.571038 \tabularnewline
245 & 0.395102 & 0.790204 & 0.604898 \tabularnewline
246 & 0.33958 & 0.67916 & 0.66042 \tabularnewline
247 & 0.311324 & 0.622649 & 0.688676 \tabularnewline
248 & 0.340386 & 0.680772 & 0.659614 \tabularnewline
249 & 0.31558 & 0.631159 & 0.68442 \tabularnewline
250 & 0.309886 & 0.619772 & 0.690114 \tabularnewline
251 & 0.268905 & 0.537811 & 0.731095 \tabularnewline
252 & 0.260847 & 0.521694 & 0.739153 \tabularnewline
253 & 0.240024 & 0.480047 & 0.759976 \tabularnewline
254 & 0.214923 & 0.429845 & 0.785077 \tabularnewline
255 & 0.173147 & 0.346294 & 0.826853 \tabularnewline
256 & 0.13046 & 0.260919 & 0.86954 \tabularnewline
257 & 0.186345 & 0.372691 & 0.813655 \tabularnewline
258 & 0.270522 & 0.541043 & 0.729478 \tabularnewline
259 & 0.330186 & 0.660371 & 0.669814 \tabularnewline
260 & 0.925521 & 0.148958 & 0.0744788 \tabularnewline
261 & 0.903516 & 0.192968 & 0.0964838 \tabularnewline
262 & 0.907044 & 0.185911 & 0.0929557 \tabularnewline
263 & 0.977108 & 0.0457846 & 0.0228923 \tabularnewline
264 & 0.954879 & 0.0902421 & 0.045121 \tabularnewline
265 & 0.915521 & 0.168958 & 0.0844792 \tabularnewline
266 & 0.93432 & 0.131359 & 0.0656796 \tabularnewline
267 & 0.936295 & 0.12741 & 0.063705 \tabularnewline
268 & 0.842785 & 0.31443 & 0.157215 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267934&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]11[/C][C]0.95047[/C][C]0.09906[/C][C]0.04953[/C][/ROW]
[ROW][C]12[/C][C]0.943756[/C][C]0.112489[/C][C]0.0562444[/C][/ROW]
[ROW][C]13[/C][C]0.934118[/C][C]0.131763[/C][C]0.0658817[/C][/ROW]
[ROW][C]14[/C][C]0.937382[/C][C]0.125237[/C][C]0.0626184[/C][/ROW]
[ROW][C]15[/C][C]0.914547[/C][C]0.170906[/C][C]0.085453[/C][/ROW]
[ROW][C]16[/C][C]0.86892[/C][C]0.26216[/C][C]0.13108[/C][/ROW]
[ROW][C]17[/C][C]0.816261[/C][C]0.367478[/C][C]0.183739[/C][/ROW]
[ROW][C]18[/C][C]0.781366[/C][C]0.437268[/C][C]0.218634[/C][/ROW]
[ROW][C]19[/C][C]0.792179[/C][C]0.415642[/C][C]0.207821[/C][/ROW]
[ROW][C]20[/C][C]0.728558[/C][C]0.542885[/C][C]0.271442[/C][/ROW]
[ROW][C]21[/C][C]0.686332[/C][C]0.627335[/C][C]0.313668[/C][/ROW]
[ROW][C]22[/C][C]0.665767[/C][C]0.668466[/C][C]0.334233[/C][/ROW]
[ROW][C]23[/C][C]0.660537[/C][C]0.678925[/C][C]0.339463[/C][/ROW]
[ROW][C]24[/C][C]0.692714[/C][C]0.614571[/C][C]0.307286[/C][/ROW]
[ROW][C]25[/C][C]0.626997[/C][C]0.746006[/C][C]0.373003[/C][/ROW]
[ROW][C]26[/C][C]0.573879[/C][C]0.852242[/C][C]0.426121[/C][/ROW]
[ROW][C]27[/C][C]0.517926[/C][C]0.964147[/C][C]0.482074[/C][/ROW]
[ROW][C]28[/C][C]0.510115[/C][C]0.979769[/C][C]0.489885[/C][/ROW]
[ROW][C]29[/C][C]0.44733[/C][C]0.894661[/C][C]0.55267[/C][/ROW]
[ROW][C]30[/C][C]0.403781[/C][C]0.807562[/C][C]0.596219[/C][/ROW]
[ROW][C]31[/C][C]0.363046[/C][C]0.726093[/C][C]0.636954[/C][/ROW]
[ROW][C]32[/C][C]0.309678[/C][C]0.619356[/C][C]0.690322[/C][/ROW]
[ROW][C]33[/C][C]0.261912[/C][C]0.523824[/C][C]0.738088[/C][/ROW]
[ROW][C]34[/C][C]0.249877[/C][C]0.499754[/C][C]0.750123[/C][/ROW]
[ROW][C]35[/C][C]0.221281[/C][C]0.442562[/C][C]0.778719[/C][/ROW]
[ROW][C]36[/C][C]0.19491[/C][C]0.389821[/C][C]0.80509[/C][/ROW]
[ROW][C]37[/C][C]0.174487[/C][C]0.348974[/C][C]0.825513[/C][/ROW]
[ROW][C]38[/C][C]0.199333[/C][C]0.398666[/C][C]0.800667[/C][/ROW]
[ROW][C]39[/C][C]0.20552[/C][C]0.411039[/C][C]0.79448[/C][/ROW]
[ROW][C]40[/C][C]0.174661[/C][C]0.349321[/C][C]0.825339[/C][/ROW]
[ROW][C]41[/C][C]0.210901[/C][C]0.421801[/C][C]0.789099[/C][/ROW]
[ROW][C]42[/C][C]0.183827[/C][C]0.367653[/C][C]0.816173[/C][/ROW]
[ROW][C]43[/C][C]0.179371[/C][C]0.358742[/C][C]0.820629[/C][/ROW]
[ROW][C]44[/C][C]0.149243[/C][C]0.298487[/C][C]0.850757[/C][/ROW]
[ROW][C]45[/C][C]0.158869[/C][C]0.317738[/C][C]0.841131[/C][/ROW]
[ROW][C]46[/C][C]0.141362[/C][C]0.282725[/C][C]0.858638[/C][/ROW]
[ROW][C]47[/C][C]0.152593[/C][C]0.305186[/C][C]0.847407[/C][/ROW]
[ROW][C]48[/C][C]0.240784[/C][C]0.481569[/C][C]0.759216[/C][/ROW]
[ROW][C]49[/C][C]0.263755[/C][C]0.52751[/C][C]0.736245[/C][/ROW]
[ROW][C]50[/C][C]0.25527[/C][C]0.51054[/C][C]0.74473[/C][/ROW]
[ROW][C]51[/C][C]0.218419[/C][C]0.436837[/C][C]0.781581[/C][/ROW]
[ROW][C]52[/C][C]0.23259[/C][C]0.465181[/C][C]0.76741[/C][/ROW]
[ROW][C]53[/C][C]0.223033[/C][C]0.446065[/C][C]0.776967[/C][/ROW]
[ROW][C]54[/C][C]0.193727[/C][C]0.387453[/C][C]0.806273[/C][/ROW]
[ROW][C]55[/C][C]0.252539[/C][C]0.505078[/C][C]0.747461[/C][/ROW]
[ROW][C]56[/C][C]0.217303[/C][C]0.434606[/C][C]0.782697[/C][/ROW]
[ROW][C]57[/C][C]0.480371[/C][C]0.960741[/C][C]0.519629[/C][/ROW]
[ROW][C]58[/C][C]0.633099[/C][C]0.733803[/C][C]0.366901[/C][/ROW]
[ROW][C]59[/C][C]0.591727[/C][C]0.816547[/C][C]0.408273[/C][/ROW]
[ROW][C]60[/C][C]0.581656[/C][C]0.836688[/C][C]0.418344[/C][/ROW]
[ROW][C]61[/C][C]0.60855[/C][C]0.782899[/C][C]0.39145[/C][/ROW]
[ROW][C]62[/C][C]0.598498[/C][C]0.803004[/C][C]0.401502[/C][/ROW]
[ROW][C]63[/C][C]0.604416[/C][C]0.791167[/C][C]0.395584[/C][/ROW]
[ROW][C]64[/C][C]0.693782[/C][C]0.612437[/C][C]0.306218[/C][/ROW]
[ROW][C]65[/C][C]0.682249[/C][C]0.635502[/C][C]0.317751[/C][/ROW]
[ROW][C]66[/C][C]0.647554[/C][C]0.704892[/C][C]0.352446[/C][/ROW]
[ROW][C]67[/C][C]0.631461[/C][C]0.737078[/C][C]0.368539[/C][/ROW]
[ROW][C]68[/C][C]0.592979[/C][C]0.814041[/C][C]0.407021[/C][/ROW]
[ROW][C]69[/C][C]0.645244[/C][C]0.709512[/C][C]0.354756[/C][/ROW]
[ROW][C]70[/C][C]0.615749[/C][C]0.768502[/C][C]0.384251[/C][/ROW]
[ROW][C]71[/C][C]0.580511[/C][C]0.838977[/C][C]0.419489[/C][/ROW]
[ROW][C]72[/C][C]0.557392[/C][C]0.885216[/C][C]0.442608[/C][/ROW]
[ROW][C]73[/C][C]0.543218[/C][C]0.913564[/C][C]0.456782[/C][/ROW]
[ROW][C]74[/C][C]0.553408[/C][C]0.893183[/C][C]0.446592[/C][/ROW]
[ROW][C]75[/C][C]0.546552[/C][C]0.906896[/C][C]0.453448[/C][/ROW]
[ROW][C]76[/C][C]0.524039[/C][C]0.951921[/C][C]0.475961[/C][/ROW]
[ROW][C]77[/C][C]0.510163[/C][C]0.979675[/C][C]0.489837[/C][/ROW]
[ROW][C]78[/C][C]0.502454[/C][C]0.995092[/C][C]0.497546[/C][/ROW]
[ROW][C]79[/C][C]0.464859[/C][C]0.929718[/C][C]0.535141[/C][/ROW]
[ROW][C]80[/C][C]0.47204[/C][C]0.94408[/C][C]0.52796[/C][/ROW]
[ROW][C]81[/C][C]0.437417[/C][C]0.874835[/C][C]0.562583[/C][/ROW]
[ROW][C]82[/C][C]0.461991[/C][C]0.923982[/C][C]0.538009[/C][/ROW]
[ROW][C]83[/C][C]0.426241[/C][C]0.852483[/C][C]0.573759[/C][/ROW]
[ROW][C]84[/C][C]0.608281[/C][C]0.783439[/C][C]0.391719[/C][/ROW]
[ROW][C]85[/C][C]0.582957[/C][C]0.834086[/C][C]0.417043[/C][/ROW]
[ROW][C]86[/C][C]0.546583[/C][C]0.906834[/C][C]0.453417[/C][/ROW]
[ROW][C]87[/C][C]0.512874[/C][C]0.974252[/C][C]0.487126[/C][/ROW]
[ROW][C]88[/C][C]0.476886[/C][C]0.953772[/C][C]0.523114[/C][/ROW]
[ROW][C]89[/C][C]0.475046[/C][C]0.950091[/C][C]0.524954[/C][/ROW]
[ROW][C]90[/C][C]0.477922[/C][C]0.955843[/C][C]0.522078[/C][/ROW]
[ROW][C]91[/C][C]0.518933[/C][C]0.962135[/C][C]0.481067[/C][/ROW]
[ROW][C]92[/C][C]0.611579[/C][C]0.776841[/C][C]0.388421[/C][/ROW]
[ROW][C]93[/C][C]0.580446[/C][C]0.839108[/C][C]0.419554[/C][/ROW]
[ROW][C]94[/C][C]0.557124[/C][C]0.885752[/C][C]0.442876[/C][/ROW]
[ROW][C]95[/C][C]0.546353[/C][C]0.907294[/C][C]0.453647[/C][/ROW]
[ROW][C]96[/C][C]0.516499[/C][C]0.967003[/C][C]0.483501[/C][/ROW]
[ROW][C]97[/C][C]0.548264[/C][C]0.903473[/C][C]0.451736[/C][/ROW]
[ROW][C]98[/C][C]0.539578[/C][C]0.920845[/C][C]0.460422[/C][/ROW]
[ROW][C]99[/C][C]0.636406[/C][C]0.727188[/C][C]0.363594[/C][/ROW]
[ROW][C]100[/C][C]0.67488[/C][C]0.650241[/C][C]0.32512[/C][/ROW]
[ROW][C]101[/C][C]0.652079[/C][C]0.695841[/C][C]0.347921[/C][/ROW]
[ROW][C]102[/C][C]0.618266[/C][C]0.763468[/C][C]0.381734[/C][/ROW]
[ROW][C]103[/C][C]0.58881[/C][C]0.822381[/C][C]0.41119[/C][/ROW]
[ROW][C]104[/C][C]0.563914[/C][C]0.872172[/C][C]0.436086[/C][/ROW]
[ROW][C]105[/C][C]0.650295[/C][C]0.69941[/C][C]0.349705[/C][/ROW]
[ROW][C]106[/C][C]0.648626[/C][C]0.702748[/C][C]0.351374[/C][/ROW]
[ROW][C]107[/C][C]0.700022[/C][C]0.599955[/C][C]0.299978[/C][/ROW]
[ROW][C]108[/C][C]0.802904[/C][C]0.394191[/C][C]0.197096[/C][/ROW]
[ROW][C]109[/C][C]0.815962[/C][C]0.368077[/C][C]0.184038[/C][/ROW]
[ROW][C]110[/C][C]0.800174[/C][C]0.399652[/C][C]0.199826[/C][/ROW]
[ROW][C]111[/C][C]0.779283[/C][C]0.441434[/C][C]0.220717[/C][/ROW]
[ROW][C]112[/C][C]0.761752[/C][C]0.476495[/C][C]0.238248[/C][/ROW]
[ROW][C]113[/C][C]0.80447[/C][C]0.391061[/C][C]0.19553[/C][/ROW]
[ROW][C]114[/C][C]0.862247[/C][C]0.275505[/C][C]0.137753[/C][/ROW]
[ROW][C]115[/C][C]0.897172[/C][C]0.205656[/C][C]0.102828[/C][/ROW]
[ROW][C]116[/C][C]0.889818[/C][C]0.220365[/C][C]0.110182[/C][/ROW]
[ROW][C]117[/C][C]0.872641[/C][C]0.254718[/C][C]0.127359[/C][/ROW]
[ROW][C]118[/C][C]0.854073[/C][C]0.291854[/C][C]0.145927[/C][/ROW]
[ROW][C]119[/C][C]0.834577[/C][C]0.330846[/C][C]0.165423[/C][/ROW]
[ROW][C]120[/C][C]0.817765[/C][C]0.364471[/C][C]0.182235[/C][/ROW]
[ROW][C]121[/C][C]0.817656[/C][C]0.364688[/C][C]0.182344[/C][/ROW]
[ROW][C]122[/C][C]0.80533[/C][C]0.38934[/C][C]0.19467[/C][/ROW]
[ROW][C]123[/C][C]0.792417[/C][C]0.415166[/C][C]0.207583[/C][/ROW]
[ROW][C]124[/C][C]0.87457[/C][C]0.25086[/C][C]0.12543[/C][/ROW]
[ROW][C]125[/C][C]0.900589[/C][C]0.198822[/C][C]0.0994109[/C][/ROW]
[ROW][C]126[/C][C]0.887903[/C][C]0.224194[/C][C]0.112097[/C][/ROW]
[ROW][C]127[/C][C]0.871144[/C][C]0.257713[/C][C]0.128856[/C][/ROW]
[ROW][C]128[/C][C]0.865661[/C][C]0.268678[/C][C]0.134339[/C][/ROW]
[ROW][C]129[/C][C]0.848338[/C][C]0.303325[/C][C]0.151662[/C][/ROW]
[ROW][C]130[/C][C]0.82701[/C][C]0.34598[/C][C]0.17299[/C][/ROW]
[ROW][C]131[/C][C]0.805866[/C][C]0.388268[/C][C]0.194134[/C][/ROW]
[ROW][C]132[/C][C]0.803785[/C][C]0.39243[/C][C]0.196215[/C][/ROW]
[ROW][C]133[/C][C]0.780382[/C][C]0.439236[/C][C]0.219618[/C][/ROW]
[ROW][C]134[/C][C]0.754721[/C][C]0.490558[/C][C]0.245279[/C][/ROW]
[ROW][C]135[/C][C]0.730134[/C][C]0.539733[/C][C]0.269866[/C][/ROW]
[ROW][C]136[/C][C]0.701102[/C][C]0.597796[/C][C]0.298898[/C][/ROW]
[ROW][C]137[/C][C]0.740968[/C][C]0.518064[/C][C]0.259032[/C][/ROW]
[ROW][C]138[/C][C]0.718325[/C][C]0.563349[/C][C]0.281675[/C][/ROW]
[ROW][C]139[/C][C]0.697059[/C][C]0.605882[/C][C]0.302941[/C][/ROW]
[ROW][C]140[/C][C]0.675235[/C][C]0.649531[/C][C]0.324765[/C][/ROW]
[ROW][C]141[/C][C]0.648592[/C][C]0.702817[/C][C]0.351408[/C][/ROW]
[ROW][C]142[/C][C]0.638862[/C][C]0.722276[/C][C]0.361138[/C][/ROW]
[ROW][C]143[/C][C]0.613005[/C][C]0.773989[/C][C]0.386995[/C][/ROW]
[ROW][C]144[/C][C]0.601418[/C][C]0.797164[/C][C]0.398582[/C][/ROW]
[ROW][C]145[/C][C]0.571584[/C][C]0.856832[/C][C]0.428416[/C][/ROW]
[ROW][C]146[/C][C]0.540916[/C][C]0.918169[/C][C]0.459084[/C][/ROW]
[ROW][C]147[/C][C]0.508379[/C][C]0.983243[/C][C]0.491621[/C][/ROW]
[ROW][C]148[/C][C]0.473842[/C][C]0.947685[/C][C]0.526158[/C][/ROW]
[ROW][C]149[/C][C]0.445636[/C][C]0.891273[/C][C]0.554364[/C][/ROW]
[ROW][C]150[/C][C]0.434044[/C][C]0.868089[/C][C]0.565956[/C][/ROW]
[ROW][C]151[/C][C]0.704802[/C][C]0.590397[/C][C]0.295198[/C][/ROW]
[ROW][C]152[/C][C]0.683345[/C][C]0.633311[/C][C]0.316655[/C][/ROW]
[ROW][C]153[/C][C]0.678409[/C][C]0.643183[/C][C]0.321591[/C][/ROW]
[ROW][C]154[/C][C]0.646377[/C][C]0.707245[/C][C]0.353623[/C][/ROW]
[ROW][C]155[/C][C]0.641764[/C][C]0.716471[/C][C]0.358236[/C][/ROW]
[ROW][C]156[/C][C]0.613898[/C][C]0.772204[/C][C]0.386102[/C][/ROW]
[ROW][C]157[/C][C]0.599859[/C][C]0.800281[/C][C]0.400141[/C][/ROW]
[ROW][C]158[/C][C]0.57139[/C][C]0.85722[/C][C]0.42861[/C][/ROW]
[ROW][C]159[/C][C]0.554263[/C][C]0.891475[/C][C]0.445737[/C][/ROW]
[ROW][C]160[/C][C]0.5483[/C][C]0.903399[/C][C]0.4517[/C][/ROW]
[ROW][C]161[/C][C]0.543293[/C][C]0.913413[/C][C]0.456707[/C][/ROW]
[ROW][C]162[/C][C]0.579507[/C][C]0.840986[/C][C]0.420493[/C][/ROW]
[ROW][C]163[/C][C]0.544438[/C][C]0.911125[/C][C]0.455562[/C][/ROW]
[ROW][C]164[/C][C]0.888587[/C][C]0.222825[/C][C]0.111413[/C][/ROW]
[ROW][C]165[/C][C]0.872724[/C][C]0.254553[/C][C]0.127276[/C][/ROW]
[ROW][C]166[/C][C]0.855642[/C][C]0.288716[/C][C]0.144358[/C][/ROW]
[ROW][C]167[/C][C]0.836185[/C][C]0.32763[/C][C]0.163815[/C][/ROW]
[ROW][C]168[/C][C]0.821367[/C][C]0.357266[/C][C]0.178633[/C][/ROW]
[ROW][C]169[/C][C]0.798687[/C][C]0.402626[/C][C]0.201313[/C][/ROW]
[ROW][C]170[/C][C]0.81193[/C][C]0.376141[/C][C]0.18807[/C][/ROW]
[ROW][C]171[/C][C]0.794614[/C][C]0.410772[/C][C]0.205386[/C][/ROW]
[ROW][C]172[/C][C]0.79146[/C][C]0.417081[/C][C]0.20854[/C][/ROW]
[ROW][C]173[/C][C]0.811762[/C][C]0.376476[/C][C]0.188238[/C][/ROW]
[ROW][C]174[/C][C]0.789477[/C][C]0.421046[/C][C]0.210523[/C][/ROW]
[ROW][C]175[/C][C]0.765178[/C][C]0.469643[/C][C]0.234822[/C][/ROW]
[ROW][C]176[/C][C]0.777499[/C][C]0.445002[/C][C]0.222501[/C][/ROW]
[ROW][C]177[/C][C]0.753779[/C][C]0.492443[/C][C]0.246221[/C][/ROW]
[ROW][C]178[/C][C]0.765744[/C][C]0.468512[/C][C]0.234256[/C][/ROW]
[ROW][C]179[/C][C]0.755329[/C][C]0.489343[/C][C]0.244671[/C][/ROW]
[ROW][C]180[/C][C]0.769586[/C][C]0.460828[/C][C]0.230414[/C][/ROW]
[ROW][C]181[/C][C]0.761097[/C][C]0.477806[/C][C]0.238903[/C][/ROW]
[ROW][C]182[/C][C]0.758104[/C][C]0.483793[/C][C]0.241896[/C][/ROW]
[ROW][C]183[/C][C]0.780732[/C][C]0.438537[/C][C]0.219268[/C][/ROW]
[ROW][C]184[/C][C]0.752764[/C][C]0.494472[/C][C]0.247236[/C][/ROW]
[ROW][C]185[/C][C]0.800472[/C][C]0.399056[/C][C]0.199528[/C][/ROW]
[ROW][C]186[/C][C]0.773244[/C][C]0.453512[/C][C]0.226756[/C][/ROW]
[ROW][C]187[/C][C]0.766727[/C][C]0.466546[/C][C]0.233273[/C][/ROW]
[ROW][C]188[/C][C]0.787866[/C][C]0.424268[/C][C]0.212134[/C][/ROW]
[ROW][C]189[/C][C]0.843508[/C][C]0.312984[/C][C]0.156492[/C][/ROW]
[ROW][C]190[/C][C]0.835463[/C][C]0.329074[/C][C]0.164537[/C][/ROW]
[ROW][C]191[/C][C]0.814364[/C][C]0.371271[/C][C]0.185636[/C][/ROW]
[ROW][C]192[/C][C]0.792016[/C][C]0.415967[/C][C]0.207984[/C][/ROW]
[ROW][C]193[/C][C]0.794107[/C][C]0.411787[/C][C]0.205893[/C][/ROW]
[ROW][C]194[/C][C]0.804734[/C][C]0.390533[/C][C]0.195266[/C][/ROW]
[ROW][C]195[/C][C]0.77698[/C][C]0.446041[/C][C]0.22302[/C][/ROW]
[ROW][C]196[/C][C]0.773066[/C][C]0.453869[/C][C]0.226934[/C][/ROW]
[ROW][C]197[/C][C]0.774137[/C][C]0.451727[/C][C]0.225863[/C][/ROW]
[ROW][C]198[/C][C]0.746098[/C][C]0.507804[/C][C]0.253902[/C][/ROW]
[ROW][C]199[/C][C]0.723003[/C][C]0.553993[/C][C]0.276997[/C][/ROW]
[ROW][C]200[/C][C]0.689748[/C][C]0.620505[/C][C]0.310252[/C][/ROW]
[ROW][C]201[/C][C]0.658148[/C][C]0.683705[/C][C]0.341852[/C][/ROW]
[ROW][C]202[/C][C]0.646438[/C][C]0.707123[/C][C]0.353562[/C][/ROW]
[ROW][C]203[/C][C]0.657238[/C][C]0.685524[/C][C]0.342762[/C][/ROW]
[ROW][C]204[/C][C]0.621416[/C][C]0.757168[/C][C]0.378584[/C][/ROW]
[ROW][C]205[/C][C]0.60652[/C][C]0.786959[/C][C]0.39348[/C][/ROW]
[ROW][C]206[/C][C]0.579682[/C][C]0.840635[/C][C]0.420318[/C][/ROW]
[ROW][C]207[/C][C]0.56975[/C][C]0.860499[/C][C]0.43025[/C][/ROW]
[ROW][C]208[/C][C]0.587551[/C][C]0.824898[/C][C]0.412449[/C][/ROW]
[ROW][C]209[/C][C]0.571702[/C][C]0.856596[/C][C]0.428298[/C][/ROW]
[ROW][C]210[/C][C]0.561975[/C][C]0.87605[/C][C]0.438025[/C][/ROW]
[ROW][C]211[/C][C]0.543686[/C][C]0.912628[/C][C]0.456314[/C][/ROW]
[ROW][C]212[/C][C]0.503103[/C][C]0.993794[/C][C]0.496897[/C][/ROW]
[ROW][C]213[/C][C]0.518468[/C][C]0.963064[/C][C]0.481532[/C][/ROW]
[ROW][C]214[/C][C]0.475873[/C][C]0.951747[/C][C]0.524127[/C][/ROW]
[ROW][C]215[/C][C]0.446973[/C][C]0.893946[/C][C]0.553027[/C][/ROW]
[ROW][C]216[/C][C]0.40871[/C][C]0.81742[/C][C]0.59129[/C][/ROW]
[ROW][C]217[/C][C]0.394177[/C][C]0.788354[/C][C]0.605823[/C][/ROW]
[ROW][C]218[/C][C]0.390158[/C][C]0.780316[/C][C]0.609842[/C][/ROW]
[ROW][C]219[/C][C]0.360202[/C][C]0.720405[/C][C]0.639798[/C][/ROW]
[ROW][C]220[/C][C]0.329845[/C][C]0.65969[/C][C]0.670155[/C][/ROW]
[ROW][C]221[/C][C]0.296771[/C][C]0.593543[/C][C]0.703229[/C][/ROW]
[ROW][C]222[/C][C]0.358876[/C][C]0.717751[/C][C]0.641124[/C][/ROW]
[ROW][C]223[/C][C]0.324856[/C][C]0.649712[/C][C]0.675144[/C][/ROW]
[ROW][C]224[/C][C]0.32673[/C][C]0.653461[/C][C]0.67327[/C][/ROW]
[ROW][C]225[/C][C]0.317388[/C][C]0.634775[/C][C]0.682612[/C][/ROW]
[ROW][C]226[/C][C]0.379892[/C][C]0.759785[/C][C]0.620108[/C][/ROW]
[ROW][C]227[/C][C]0.375314[/C][C]0.750628[/C][C]0.624686[/C][/ROW]
[ROW][C]228[/C][C]0.392491[/C][C]0.784982[/C][C]0.607509[/C][/ROW]
[ROW][C]229[/C][C]0.633022[/C][C]0.733956[/C][C]0.366978[/C][/ROW]
[ROW][C]230[/C][C]0.670265[/C][C]0.65947[/C][C]0.329735[/C][/ROW]
[ROW][C]231[/C][C]0.666866[/C][C]0.666267[/C][C]0.333134[/C][/ROW]
[ROW][C]232[/C][C]0.696935[/C][C]0.60613[/C][C]0.303065[/C][/ROW]
[ROW][C]233[/C][C]0.663939[/C][C]0.672122[/C][C]0.336061[/C][/ROW]
[ROW][C]234[/C][C]0.65547[/C][C]0.689061[/C][C]0.34453[/C][/ROW]
[ROW][C]235[/C][C]0.613639[/C][C]0.772723[/C][C]0.386361[/C][/ROW]
[ROW][C]236[/C][C]0.677496[/C][C]0.645008[/C][C]0.322504[/C][/ROW]
[ROW][C]237[/C][C]0.632719[/C][C]0.734563[/C][C]0.367281[/C][/ROW]
[ROW][C]238[/C][C]0.600186[/C][C]0.799628[/C][C]0.399814[/C][/ROW]
[ROW][C]239[/C][C]0.654558[/C][C]0.690884[/C][C]0.345442[/C][/ROW]
[ROW][C]240[/C][C]0.608438[/C][C]0.783123[/C][C]0.391562[/C][/ROW]
[ROW][C]241[/C][C]0.555889[/C][C]0.888222[/C][C]0.444111[/C][/ROW]
[ROW][C]242[/C][C]0.526594[/C][C]0.946811[/C][C]0.473406[/C][/ROW]
[ROW][C]243[/C][C]0.484946[/C][C]0.969892[/C][C]0.515054[/C][/ROW]
[ROW][C]244[/C][C]0.428962[/C][C]0.857924[/C][C]0.571038[/C][/ROW]
[ROW][C]245[/C][C]0.395102[/C][C]0.790204[/C][C]0.604898[/C][/ROW]
[ROW][C]246[/C][C]0.33958[/C][C]0.67916[/C][C]0.66042[/C][/ROW]
[ROW][C]247[/C][C]0.311324[/C][C]0.622649[/C][C]0.688676[/C][/ROW]
[ROW][C]248[/C][C]0.340386[/C][C]0.680772[/C][C]0.659614[/C][/ROW]
[ROW][C]249[/C][C]0.31558[/C][C]0.631159[/C][C]0.68442[/C][/ROW]
[ROW][C]250[/C][C]0.309886[/C][C]0.619772[/C][C]0.690114[/C][/ROW]
[ROW][C]251[/C][C]0.268905[/C][C]0.537811[/C][C]0.731095[/C][/ROW]
[ROW][C]252[/C][C]0.260847[/C][C]0.521694[/C][C]0.739153[/C][/ROW]
[ROW][C]253[/C][C]0.240024[/C][C]0.480047[/C][C]0.759976[/C][/ROW]
[ROW][C]254[/C][C]0.214923[/C][C]0.429845[/C][C]0.785077[/C][/ROW]
[ROW][C]255[/C][C]0.173147[/C][C]0.346294[/C][C]0.826853[/C][/ROW]
[ROW][C]256[/C][C]0.13046[/C][C]0.260919[/C][C]0.86954[/C][/ROW]
[ROW][C]257[/C][C]0.186345[/C][C]0.372691[/C][C]0.813655[/C][/ROW]
[ROW][C]258[/C][C]0.270522[/C][C]0.541043[/C][C]0.729478[/C][/ROW]
[ROW][C]259[/C][C]0.330186[/C][C]0.660371[/C][C]0.669814[/C][/ROW]
[ROW][C]260[/C][C]0.925521[/C][C]0.148958[/C][C]0.0744788[/C][/ROW]
[ROW][C]261[/C][C]0.903516[/C][C]0.192968[/C][C]0.0964838[/C][/ROW]
[ROW][C]262[/C][C]0.907044[/C][C]0.185911[/C][C]0.0929557[/C][/ROW]
[ROW][C]263[/C][C]0.977108[/C][C]0.0457846[/C][C]0.0228923[/C][/ROW]
[ROW][C]264[/C][C]0.954879[/C][C]0.0902421[/C][C]0.045121[/C][/ROW]
[ROW][C]265[/C][C]0.915521[/C][C]0.168958[/C][C]0.0844792[/C][/ROW]
[ROW][C]266[/C][C]0.93432[/C][C]0.131359[/C][C]0.0656796[/C][/ROW]
[ROW][C]267[/C][C]0.936295[/C][C]0.12741[/C][C]0.063705[/C][/ROW]
[ROW][C]268[/C][C]0.842785[/C][C]0.31443[/C][C]0.157215[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267934&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267934&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
11	0.95047	0.09906	0.04953
12	0.943756	0.112489	0.0562444
13	0.934118	0.131763	0.0658817
14	0.937382	0.125237	0.0626184
15	0.914547	0.170906	0.085453
16	0.86892	0.26216	0.13108
17	0.816261	0.367478	0.183739
18	0.781366	0.437268	0.218634
19	0.792179	0.415642	0.207821
20	0.728558	0.542885	0.271442
21	0.686332	0.627335	0.313668
22	0.665767	0.668466	0.334233
23	0.660537	0.678925	0.339463
24	0.692714	0.614571	0.307286
25	0.626997	0.746006	0.373003
26	0.573879	0.852242	0.426121
27	0.517926	0.964147	0.482074
28	0.510115	0.979769	0.489885
29	0.44733	0.894661	0.55267
30	0.403781	0.807562	0.596219
31	0.363046	0.726093	0.636954
32	0.309678	0.619356	0.690322
33	0.261912	0.523824	0.738088
34	0.249877	0.499754	0.750123
35	0.221281	0.442562	0.778719
36	0.19491	0.389821	0.80509
37	0.174487	0.348974	0.825513
38	0.199333	0.398666	0.800667
39	0.20552	0.411039	0.79448
40	0.174661	0.349321	0.825339
41	0.210901	0.421801	0.789099
42	0.183827	0.367653	0.816173
43	0.179371	0.358742	0.820629
44	0.149243	0.298487	0.850757
45	0.158869	0.317738	0.841131
46	0.141362	0.282725	0.858638
47	0.152593	0.305186	0.847407
48	0.240784	0.481569	0.759216
49	0.263755	0.52751	0.736245
50	0.25527	0.51054	0.74473
51	0.218419	0.436837	0.781581
52	0.23259	0.465181	0.76741
53	0.223033	0.446065	0.776967
54	0.193727	0.387453	0.806273
55	0.252539	0.505078	0.747461
56	0.217303	0.434606	0.782697
57	0.480371	0.960741	0.519629
58	0.633099	0.733803	0.366901
59	0.591727	0.816547	0.408273
60	0.581656	0.836688	0.418344
61	0.60855	0.782899	0.39145
62	0.598498	0.803004	0.401502
63	0.604416	0.791167	0.395584
64	0.693782	0.612437	0.306218
65	0.682249	0.635502	0.317751
66	0.647554	0.704892	0.352446
67	0.631461	0.737078	0.368539
68	0.592979	0.814041	0.407021
69	0.645244	0.709512	0.354756
70	0.615749	0.768502	0.384251
71	0.580511	0.838977	0.419489
72	0.557392	0.885216	0.442608
73	0.543218	0.913564	0.456782
74	0.553408	0.893183	0.446592
75	0.546552	0.906896	0.453448
76	0.524039	0.951921	0.475961
77	0.510163	0.979675	0.489837
78	0.502454	0.995092	0.497546
79	0.464859	0.929718	0.535141
80	0.47204	0.94408	0.52796
81	0.437417	0.874835	0.562583
82	0.461991	0.923982	0.538009
83	0.426241	0.852483	0.573759
84	0.608281	0.783439	0.391719
85	0.582957	0.834086	0.417043
86	0.546583	0.906834	0.453417
87	0.512874	0.974252	0.487126
88	0.476886	0.953772	0.523114
89	0.475046	0.950091	0.524954
90	0.477922	0.955843	0.522078
91	0.518933	0.962135	0.481067
92	0.611579	0.776841	0.388421
93	0.580446	0.839108	0.419554
94	0.557124	0.885752	0.442876
95	0.546353	0.907294	0.453647
96	0.516499	0.967003	0.483501
97	0.548264	0.903473	0.451736
98	0.539578	0.920845	0.460422
99	0.636406	0.727188	0.363594
100	0.67488	0.650241	0.32512
101	0.652079	0.695841	0.347921
102	0.618266	0.763468	0.381734
103	0.58881	0.822381	0.41119
104	0.563914	0.872172	0.436086
105	0.650295	0.69941	0.349705
106	0.648626	0.702748	0.351374
107	0.700022	0.599955	0.299978
108	0.802904	0.394191	0.197096
109	0.815962	0.368077	0.184038
110	0.800174	0.399652	0.199826
111	0.779283	0.441434	0.220717
112	0.761752	0.476495	0.238248
113	0.80447	0.391061	0.19553
114	0.862247	0.275505	0.137753
115	0.897172	0.205656	0.102828
116	0.889818	0.220365	0.110182
117	0.872641	0.254718	0.127359
118	0.854073	0.291854	0.145927
119	0.834577	0.330846	0.165423
120	0.817765	0.364471	0.182235
121	0.817656	0.364688	0.182344
122	0.80533	0.38934	0.19467
123	0.792417	0.415166	0.207583
124	0.87457	0.25086	0.12543
125	0.900589	0.198822	0.0994109
126	0.887903	0.224194	0.112097
127	0.871144	0.257713	0.128856
128	0.865661	0.268678	0.134339
129	0.848338	0.303325	0.151662
130	0.82701	0.34598	0.17299
131	0.805866	0.388268	0.194134
132	0.803785	0.39243	0.196215
133	0.780382	0.439236	0.219618
134	0.754721	0.490558	0.245279
135	0.730134	0.539733	0.269866
136	0.701102	0.597796	0.298898
137	0.740968	0.518064	0.259032
138	0.718325	0.563349	0.281675
139	0.697059	0.605882	0.302941
140	0.675235	0.649531	0.324765
141	0.648592	0.702817	0.351408
142	0.638862	0.722276	0.361138
143	0.613005	0.773989	0.386995
144	0.601418	0.797164	0.398582
145	0.571584	0.856832	0.428416
146	0.540916	0.918169	0.459084
147	0.508379	0.983243	0.491621
148	0.473842	0.947685	0.526158
149	0.445636	0.891273	0.554364
150	0.434044	0.868089	0.565956
151	0.704802	0.590397	0.295198
152	0.683345	0.633311	0.316655
153	0.678409	0.643183	0.321591
154	0.646377	0.707245	0.353623
155	0.641764	0.716471	0.358236
156	0.613898	0.772204	0.386102
157	0.599859	0.800281	0.400141
158	0.57139	0.85722	0.42861
159	0.554263	0.891475	0.445737
160	0.5483	0.903399	0.4517
161	0.543293	0.913413	0.456707
162	0.579507	0.840986	0.420493
163	0.544438	0.911125	0.455562
164	0.888587	0.222825	0.111413
165	0.872724	0.254553	0.127276
166	0.855642	0.288716	0.144358
167	0.836185	0.32763	0.163815
168	0.821367	0.357266	0.178633
169	0.798687	0.402626	0.201313
170	0.81193	0.376141	0.18807
171	0.794614	0.410772	0.205386
172	0.79146	0.417081	0.20854
173	0.811762	0.376476	0.188238
174	0.789477	0.421046	0.210523
175	0.765178	0.469643	0.234822
176	0.777499	0.445002	0.222501
177	0.753779	0.492443	0.246221
178	0.765744	0.468512	0.234256
179	0.755329	0.489343	0.244671
180	0.769586	0.460828	0.230414
181	0.761097	0.477806	0.238903
182	0.758104	0.483793	0.241896
183	0.780732	0.438537	0.219268
184	0.752764	0.494472	0.247236
185	0.800472	0.399056	0.199528
186	0.773244	0.453512	0.226756
187	0.766727	0.466546	0.233273
188	0.787866	0.424268	0.212134
189	0.843508	0.312984	0.156492
190	0.835463	0.329074	0.164537
191	0.814364	0.371271	0.185636
192	0.792016	0.415967	0.207984
193	0.794107	0.411787	0.205893
194	0.804734	0.390533	0.195266
195	0.77698	0.446041	0.22302
196	0.773066	0.453869	0.226934
197	0.774137	0.451727	0.225863
198	0.746098	0.507804	0.253902
199	0.723003	0.553993	0.276997
200	0.689748	0.620505	0.310252
201	0.658148	0.683705	0.341852
202	0.646438	0.707123	0.353562
203	0.657238	0.685524	0.342762
204	0.621416	0.757168	0.378584
205	0.60652	0.786959	0.39348
206	0.579682	0.840635	0.420318
207	0.56975	0.860499	0.43025
208	0.587551	0.824898	0.412449
209	0.571702	0.856596	0.428298
210	0.561975	0.87605	0.438025
211	0.543686	0.912628	0.456314
212	0.503103	0.993794	0.496897
213	0.518468	0.963064	0.481532
214	0.475873	0.951747	0.524127
215	0.446973	0.893946	0.553027
216	0.40871	0.81742	0.59129
217	0.394177	0.788354	0.605823
218	0.390158	0.780316	0.609842
219	0.360202	0.720405	0.639798
220	0.329845	0.65969	0.670155
221	0.296771	0.593543	0.703229
222	0.358876	0.717751	0.641124
223	0.324856	0.649712	0.675144
224	0.32673	0.653461	0.67327
225	0.317388	0.634775	0.682612
226	0.379892	0.759785	0.620108
227	0.375314	0.750628	0.624686
228	0.392491	0.784982	0.607509
229	0.633022	0.733956	0.366978
230	0.670265	0.65947	0.329735
231	0.666866	0.666267	0.333134
232	0.696935	0.60613	0.303065
233	0.663939	0.672122	0.336061
234	0.65547	0.689061	0.34453
235	0.613639	0.772723	0.386361
236	0.677496	0.645008	0.322504
237	0.632719	0.734563	0.367281
238	0.600186	0.799628	0.399814
239	0.654558	0.690884	0.345442
240	0.608438	0.783123	0.391562
241	0.555889	0.888222	0.444111
242	0.526594	0.946811	0.473406
243	0.484946	0.969892	0.515054
244	0.428962	0.857924	0.571038
245	0.395102	0.790204	0.604898
246	0.33958	0.67916	0.66042
247	0.311324	0.622649	0.688676
248	0.340386	0.680772	0.659614
249	0.31558	0.631159	0.68442
250	0.309886	0.619772	0.690114
251	0.268905	0.537811	0.731095
252	0.260847	0.521694	0.739153
253	0.240024	0.480047	0.759976
254	0.214923	0.429845	0.785077
255	0.173147	0.346294	0.826853
256	0.13046	0.260919	0.86954
257	0.186345	0.372691	0.813655
258	0.270522	0.541043	0.729478
259	0.330186	0.660371	0.669814
260	0.925521	0.148958	0.0744788
261	0.903516	0.192968	0.0964838
262	0.907044	0.185911	0.0929557
263	0.977108	0.0457846	0.0228923
264	0.954879	0.0902421	0.045121
265	0.915521	0.168958	0.0844792
266	0.93432	0.131359	0.0656796
267	0.936295	0.12741	0.063705
268	0.842785	0.31443	0.157215

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	1	0.00387597	OK
10% type I error level	3	0.0116279	OK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 1 & 0.00387597 & OK \tabularnewline
10% type I error level & 3 & 0.0116279 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267934&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]1[/C][C]0.00387597[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]3[/C][C]0.0116279[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267934&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267934&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	0	0	OK
5% type I error level	1	0.00387597	OK
10% type I error level	3	0.0116279	OK

Figure 1

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Figure 2

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 5 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;

Parameters (R input):

par1 = 8 ; 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