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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

Thu, 11 Dec 2014 21:39:03 +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/11/t1418334919u69n1xkuqafps2c.htm/, Retrieved Thu, 16 May 2024 14:33:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266372, Retrieved Thu, 16 May 2024 14:33:45 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

111

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] [6993448de96b8662e47595bfdf466bf3] [Current]
- R PD          [Multiple Regression] [] [2014-12-14 23:33:56] [6b382800c0d3804662889dbce999b8c7] 
- 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	96	1,8	12,9
1	0	1	22	139	70	2,1	12,2
1	0	0	22	148	88,00	2,20	12,8
1	0	1	18	158	114,00	2,30	7,4
1	0	1	23	128	69,00	2,10	6,7
1	0	1	12	224	176,00	2,70	12,6
1	0	0	20	159	114	2,1	14,8
1	0	1	22	105	121	2,4	13,3
1	0	1	21	159	110	2,9	11,1
1	0	1	19	167	158	2,2	8,2
1	0	1	22	165	116,00	2,10	11,4
1	0	1	15	159	181,00	2,20	6,4
1	0	1	20	119	77,00	2,20	10,6
1	0	0	19	176	141,00	2,70	12
1	0	0	18	54	35	1,9	6,3
1	1	0	15	91	80	2	11,3
1	0	1	20	163	152	2,5	11,9
1	0	0	21	124	97	2,2	9,3
1	1	1	21	137	99	2,3	9,6
1	0	0	15	121	84	1,9	10
1	0	1	16	153	68	2,1	6,4
1	0	1	23	148	101	3,5	13,8
1	0	0	21	221	107	2,1	10,8
1	0	1	18	188	88	2,3	13,8
1	0	1	25	149	112	2,3	11,7
1	0	1	9	244	171	2,2	10,9
1	1	1	30	148	137	3,5	16,1
1	1	0	20	92	77	1,9	13,4
1	0	1	23	150	66	1,9	9,9
1	0	0	16	153	93	1,9	11,5
1	0	0	16	94	105	1,9	8,3
1	0	0	19	156	131	2,1	11,7
1	0	1	25	132	102	2	9
1	0	1	18	161	161	3,2	9,7
1	0	1	23	105	120	2,3	10,8
1	0	1	21	97	127	2,5	10,3
1	0	0	10	151	77	1,8	10,4
1	1	1	14	131	108	2,4	12,7
1	0	1	22	166	85	2,8	9,3
1	0	0	26	157	168	2,3	11,8
1	0	1	23	111	48	2	5,9
1	0	1	23	145	152	2,5	11,4
1	0	1	24	162	75	2,3	13
1	0	1	24	163	107	1,8	10,8
1	1	1	18	59	62	1,9	12,3
1	0	0	23	187	121	2,6	11,3
1	0	1	15	109	124	2	11,8
1	1	1	19	90	72	2,6	7,9
1	0	0	16	105	40	1,6	12,7
1	1	1	25	83	58	2,2	12,3
1	1	1	23	116	97	2,1	11,6
1	1	1	17	42	88	1,8	6,7
1	0	1	19	148	126	1,8	10,9
1	1	1	21	155	104	1,9	12,1
1	0	1	18	125	148	2,4	13,3
1	0	1	27	116	146	1,9	10,1
1	1	0	21	128	80	2	5,7
1	0	1	13	138	97	2,1	14,3
1	1	0	8	49	25	1,7	8
1	1	1	29	96	99	1,9	13,3
1	0	1	28	164	118	2,1	9,3
1	0	0	23	162	58	2,4	12,5
1	0	0	21	99	63	1,8	7,6
1	0	1	19	202	139	2,3	15,9
1	0	0	19	186	50	2,1	9,2
1	1	1	20	66	60	2	9,1
1	0	0	18	183	152	2,8	11,1
1	0	1	19	214	142	2	13
1	0	1	17	188	94	2,7	14,5
1	1	0	19	104	66	2,1	12,2
1	0	0	25	177	127	2,9	12,3
1	0	0	19	126	67	2	11,4
1	1	0	22	76	90	1,8	8,8
1	1	1	23	99	75	2,6	14,6
1	0	0	14	139	128	2,1	12,6
1	0	0	16	162	146	2,3	13
1	1	1	24	108	69	2,2	12,6
1	0	0	20	159	186	2	13,2
1	1	0	12	74	81	2,2	9,9
1	0	1	24	110	85	2,1	7,7
1	1	0	22	96	54	2,1	10,5
1	1	0	12	116	46	1,9	13,4
1	1	0	22	87	106	2	10,9
1	1	1	20	97	34	1,7	4,3
1	1	0	10	127	60	2,2	10,3
1	1	1	23	106	95	2,2	11,8
1	1	1	17	80	57	2,3	11,2
1	1	0	22	74	62	2,4	11,4
1	1	0	24	91	36	2,1	8,6
1	1	0	18	133	56	1,9	13,2
1	1	1	21	74	54	1,7	12,6
1	1	1	20	114	64	1,8	5,6
1	1	1	20	140	76	1,5	9,9
1	1	0	22	95	98	1,9	8,8
1	1	1	19	98	88	1,9	7,7
1	1	0	20	121	35	1,7	9
1	1	1	26	126	102	1,9	7,3
1	1	1	23	98	61	1,9	11,4
1	1	1	24	95	80	1,8	13,6
1	1	1	21	110	49	2,4	7,9
1	1	1	21	70	78	1,8	10,7
1	1	0	19	102	90	1,9	10,3
1	1	1	8	86	45	1,8	8,3
1	1	1	17	130	55	2,1	9,6
1	1	1	20	96	96	1,9	14,2
1	1	0	11	102	43	2,2	8,5
1	1	0	8	100	52	2	13,5
1	1	0	15	94	60	1,7	4,9
1	1	0	18	52	54	1,7	6,4
1	1	0	18	98	51	1,8	9,6
1	1	0	19	118	51	1,9	11,6
1	1	1	19	99	38	1,8	11,1
0	0	1	23	48	41	1	4,35
0	0	1	22	50	146	1	12,7
0	0	1	21	150	182	4	18,1
0	0	1	25	154	192	4	17,85
0	1	0	30	109	263	3	16,6
0	1	1	17	68	35	2	12,6
0	0	1	27	194	439	4	17,1
0	0	0	23	158	214	4	19,1
0	0	1	23	159	341	4	16,1
0	0	0	18	67	58	2	13,35
0	0	0	18	147	292	4	18,4
0	0	1	23	39	85	1	14,7
0	0	1	19	100	200	3	10,6
0	0	1	15	111	158	3	12,6
0	0	1	20	138	199	4	16,2
0	0	1	16	101	297	3	13,6
0	1	1	24	131	227	4	18,9
0	0	1	25	101	108	3	14,1
0	0	1	25	114	86	3	14,5
0	0	0	19	165	302	4	16,15
0	0	1	19	114	148	3	14,75
0	0	1	16	111	178	3	14,8
0	0	1	19	75	120	2	12,45
0	0	1	19	82	207	2	12,65
0	0	1	23	121	157	3	17,35
0	0	1	21	32	128	1	8,6
0	0	0	22	150	296	4	18,4
0	0	1	19	117	323	3	16,1
0	1	1	20	71	79	2	11,6
0	0	1	20	165	70	4	17,75
0	0	1	3	154	146	4	15,25
0	0	1	23	126	246	4	17,65
0	0	0	23	149	196	4	16,35
0	0	0	20	145	199	4	17,65
0	0	1	15	120	127	3	13,6
0	0	0	16	109	153	3	14,35
0	0	0	7	132	299	4	14,75
0	0	1	24	172	228	4	18,25
0	0	0	17	169	190	4	9,9
0	0	1	24	114	180	3	16
0	0	1	24	156	212	4	18,25
0	0	0	19	172	269	4	16,85
0	1	1	25	68	130	2	14,6
0	1	1	20	89	179	2	13,85
0	0	1	28	167	243	4	18,95
0	0	0	23	113	190	3	15,6
0	1	0	27	115	299	3	14,85
0	1	0	18	78	121	2	11,75
0	1	0	28	118	137	3	18,45
0	1	1	21	87	305	2	15,9
0	0	0	19	173	157	4	17,1
0	0	1	23	2	96	1	16,1
0	1	0	27	162	183	4	19,9
0	1	1	22	49	52	1	10,95
0	1	0	28	122	238	4	18,45
0	1	1	25	96	40	3	15,1
0	1	0	21	100	226	3	15
0	1	0	22	82	190	2	11,35
0	1	1	28	100	214	3	15,95
0	1	0	20	115	145	3	18,1
0	1	1	29	141	119	4	14,6
0	0	1	25	165	222	4	15,4
0	0	1	25	165	222	4	15,4
0	1	1	20	110	159	3	17,6
0	0	1	20	118	165	3	13,35
0	0	0	16	158	249	4	19,1
0	1	1	20	146	125	4	15,35
0	0	0	20	49	122	1	7,6
0	1	0	23	90	186	2	13,4
0	1	0	18	121	148	3	13,9
0	0	1	25	155	274	4	19,1
0	1	0	18	104	172	3	15,25
0	1	1	19	147	84	4	12,9
0	1	0	25	110	168	3	16,1
0	1	0	25	108	102	3	17,35
0	1	0	25	113	106	3	13,15
0	1	0	24	115	2	3	12,15
0	1	1	19	61	139	1	12,6
0	1	1	26	60	95	1	10,35
0	1	1	10	109	130	3	15,4
0	1	1	17	68	72	2	9,6
0	1	0	13	111	141	3	18,2
0	1	0	17	77	113	2	13,6
0	1	1	30	73	206	2	14,85
0	0	0	25	151	268	4	14,75
0	1	0	4	89	175	2	14,1
0	1	0	16	78	77	2	14,9
0	1	0	21	110	125	3	16,25
0	0	1	23	220	255	4	19,25
0	1	1	22	65	111	2	13,6
0	0	0	17	141	132	4	13,6
0	1	0	20	117	211	3	15,65
0	0	1	20	122	92	4	12,75
0	1	0	22	63	76	2	14,6
0	0	1	16	44	171	1	9,85
0	1	1	23	52	83	1	12,65
0	1	0	0	131	266	4	19,2
0	1	1	18	101	186	3	16,6
0	1	1	25	42	50	1	11,2
0	0	1	23	152	117	4	15,25
0	0	0	12	107	219	3	11,9
0	1	0	18	77	246	2	13,2
0	0	0	24	154	279	4	16,35
0	0	1	11	103	148	3	12,4
0	1	1	18	96	137	3	15,85
0	0	1	23	175	181	4	18,15
0	1	1	24	57	98	1	11,15
0	1	0	29	112	226	3	15,65
0	0	0	18	143	234	4	17,75
0	1	0	15	49	138	1	7,65
0	0	1	29	110	85	3	12,35
0	0	1	16	131	66	4	15,6
0	0	0	19	167	236	4	19,3
0	1	0	22	56	106	1	15,2
0	0	0	16	137	135	4	17,1
0	1	1	23	86	122	2	15,6
0	0	1	23	121	218	3	18,4
0	0	0	19	149	199	4	19,05
0	0	0	4	168	112	4	18,55
0	0	0	20	140	278	4	19,1
0	1	1	24	88	94	2	13,1
0	0	1	20	168	113	4	12,85
0	0	1	4	94	84	2	9,5
0	0	1	24	51	86	1	4,5
0	1	0	22	48	62	1	11,85
0	0	1	16	145	222	4	13,6
0	0	1	3	66	167	2	11,7
0	1	1	15	85	82	2	12,4
0	0	0	24	109	207	3	13,35
0	1	0	17	63	184	2	11,4
0	1	1	20	102	83	3	14,9
0	1	0	27	162	183	4	19,9
0	1	1	26	86	89	2	11,2
0	1	1	23	114	225	3	14,6
0	0	0	17	164	237	4	17,6
0	0	1	20	119	102	3	14,05
0	0	0	22	126	221	4	16,1
0	0	1	19	132	128	4	13,35
0	0	1	24	142	91	4	11,85
0	0	0	19	83	198	2	11,95
0	1	1	23	94	204	2	14,75
0	1	0	15	81	158	2	15,15
0	0	1	27	166	138	4	13,2
0	1	0	26	110	226	3	16,85
0	1	1	22	64	44	2	7,85
0	0	0	22	93	196	2	7,7
0	1	0	18	104	83	3	12,6
0	1	1	15	105	79	3	7,85
0	1	1	22	49	52	1	10,95
0	1	0	27	88	105	2	12,35
0	1	1	10	95	116	2	9,95
0	1	1	20	102	83	3	14,9
0	1	0	17	99	196	3	16,65
0	1	1	23	63	153	2	13,4
0	1	0	19	76	157	2	13,95
0	1	0	13	109	75	3	15,7
0	1	1	27	117	106	3	16,85
0	1	1	23	57	58	1	10,95
0	1	0	16	120	75	3	15,35
0	1	1	25	73	74	2	12,2
0	1	0	2	91	185	2	15,1
0	1	0	26	108	265	3	17,75
0	1	1	20	105	131	3	15,2
0	0	0	23	117	139	3	14,6
0	1	0	22	119	196	3	16,65
0	1	1	24	31	78	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	'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message	The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266372&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266372&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266372&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	'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message	The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'.

Multiple Linear Regression - Estimated Regression Equation
TOT [t] = + 6.2172 -2.35843jaar_bin[t] + 1.16728group_bin[t] -0.416118gender_bin[t] + 0.0397039NUMERACYTOT[t] + 0.0158343LFM[t] + 0.0100241B[t] + 1.3235PR[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT
[t] =  +  6.2172 -2.35843jaar_bin[t] +  1.16728group_bin[t] -0.416118gender_bin[t] +  0.0397039NUMERACYTOT[t] +  0.0158343LFM[t] +  0.0100241B[t] +  1.3235PR[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266372&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT
[t] =  +  6.2172 -2.35843jaar_bin[t] +  1.16728group_bin[t] -0.416118gender_bin[t] +  0.0397039NUMERACYTOT[t] +  0.0158343LFM[t] +  0.0100241B[t] +  1.3235PR[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266372&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266372&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] = + 6.2172 -2.35843jaar_bin[t] + 1.16728group_bin[t] -0.416118gender_bin[t] + 0.0397039NUMERACYTOT[t] + 0.0158343LFM[t] + 0.0100241B[t] + 1.3235PR[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)	6.2172	0.808179	7.693	2.7046e-13	1.3523e-13
jaar_bin	-2.35843	0.405583	-5.815	1.70957e-08	8.54783e-09
group_bin	1.16728	0.312417	3.736	0.000227897	0.000113949
gender_bin	-0.416118	0.272784	-1.525	0.128318	0.0641588
NUMERACYTOT	0.0397039	0.0260983	1.521	0.12935	0.0646748
LFM	0.0158343	0.00577794	2.74	0.00654437	0.00327218
B	0.0100241	0.0025255	3.969	9.25223e-05	4.62612e-05
PR	1.3235	0.253096	5.229	3.41534e-07	1.70767e-07

\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) & 6.2172 & 0.808179 & 7.693 & 2.7046e-13 & 1.3523e-13 \tabularnewline
jaar_bin & -2.35843 & 0.405583 & -5.815 & 1.70957e-08 & 8.54783e-09 \tabularnewline
group_bin & 1.16728 & 0.312417 & 3.736 & 0.000227897 & 0.000113949 \tabularnewline
gender_bin & -0.416118 & 0.272784 & -1.525 & 0.128318 & 0.0641588 \tabularnewline
NUMERACYTOT & 0.0397039 & 0.0260983 & 1.521 & 0.12935 & 0.0646748 \tabularnewline
LFM & 0.0158343 & 0.00577794 & 2.74 & 0.00654437 & 0.00327218 \tabularnewline
B & 0.0100241 & 0.0025255 & 3.969 & 9.25223e-05 & 4.62612e-05 \tabularnewline
PR & 1.3235 & 0.253096 & 5.229 & 3.41534e-07 & 1.70767e-07 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266372&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]6.2172[/C][C]0.808179[/C][C]7.693[/C][C]2.7046e-13[/C][C]1.3523e-13[/C][/ROW]
[ROW][C]jaar_bin[/C][C]-2.35843[/C][C]0.405583[/C][C]-5.815[/C][C]1.70957e-08[/C][C]8.54783e-09[/C][/ROW]
[ROW][C]group_bin[/C][C]1.16728[/C][C]0.312417[/C][C]3.736[/C][C]0.000227897[/C][C]0.000113949[/C][/ROW]
[ROW][C]gender_bin[/C][C]-0.416118[/C][C]0.272784[/C][C]-1.525[/C][C]0.128318[/C][C]0.0641588[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0397039[/C][C]0.0260983[/C][C]1.521[/C][C]0.12935[/C][C]0.0646748[/C][/ROW]
[ROW][C]LFM[/C][C]0.0158343[/C][C]0.00577794[/C][C]2.74[/C][C]0.00654437[/C][C]0.00327218[/C][/ROW]
[ROW][C]B[/C][C]0.0100241[/C][C]0.0025255[/C][C]3.969[/C][C]9.25223e-05[/C][C]4.62612e-05[/C][/ROW]
[ROW][C]PR[/C][C]1.3235[/C][C]0.253096[/C][C]5.229[/C][C]3.41534e-07[/C][C]1.70767e-07[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266372&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266372&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)	6.2172	0.808179	7.693	2.7046e-13	1.3523e-13
jaar_bin	-2.35843	0.405583	-5.815	1.70957e-08	8.54783e-09
group_bin	1.16728	0.312417	3.736	0.000227897	0.000113949
gender_bin	-0.416118	0.272784	-1.525	0.128318	0.0641588
NUMERACYTOT	0.0397039	0.0260983	1.521	0.12935	0.0646748
LFM	0.0158343	0.00577794	2.74	0.00654437	0.00327218
B	0.0100241	0.0025255	3.969	9.25223e-05	4.62612e-05
PR	1.3235	0.253096	5.229	3.41534e-07	1.70767e-07

Multiple Linear Regression - Regression Statistics
Multiple R	0.776788
R-squared	0.603399
Adjusted R-squared	0.593117
F-TEST (value)	58.6836
F-TEST (DF numerator)	7
F-TEST (DF denominator)	270
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.16517
Sum Squared Residuals	1265.75

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.776788 \tabularnewline
R-squared & 0.603399 \tabularnewline
Adjusted R-squared & 0.593117 \tabularnewline
F-TEST (value) & 58.6836 \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 & 2.16517 \tabularnewline
Sum Squared Residuals & 1265.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266372&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.776788[/C][/ROW]
[ROW][C]R-squared[/C][C]0.603399[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.593117[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]58.6836[/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]2.16517[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1265.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266372&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266372&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	0.776788
R-squared	0.603399
Adjusted R-squared	0.593117
F-TEST (value)	58.6836
F-TEST (DF numerator)	7
F-TEST (DF denominator)	270
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.16517
Sum Squared Residuals	1265.75

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	10.3965	2.50353
2	12.2	9.99813	2.20187
3	12.8	10.8695	1.93046
4	7.4	10.8459	-3.44593
5	6.7	9.85364	-3.15364
6	12.6	12.8037	-0.203663
7	14.8	11.0926	3.70741
8	13.3	10.368	2.93195
9	11.1	11.7349	-0.634881
10	8.2	11.3369	-3.13685
11	11.4	10.8709	0.529066
12	6.4	11.2819	-4.88192
13	10.6	9.80456	0.79544
14	12	12.3868	-0.38682
15	6.3	8.29398	-1.99398
16	11.3	10.5114	0.788551
17	11.9	11.6501	0.249875
18	9.3	10.54	-1.24003
19	9.6	11.6494	-2.04944
20	10	9.72695	0.273055
21	6.4	9.96154	-3.56154
22	13.8	12.344	1.456
23	10.8	12.0439	-1.24385
24	13.8	11.0603	2.73967
25	11.7	10.9613	0.738699
26	10.9	12.2894	-1.38937
27	16.1	14.1501	1.94993
28	13.4	10.5634	2.83662
29	9.9	9.90722	-0.00721885
30	11.5	10.3636	1.13644
31	8.3	9.54963	-1.24963
32	11.7	11.1758	0.524207
33	9	10.1948	-1.19483
34	9.7	12.5557	-2.85572
35	10.8	10.2654	0.534622
36	10.3	10.3942	-0.0941647
37	10.4	9.80093	0.599065
38	12.7	11.4991	1.20093
39	9.3	11.5025	-2.20247
40	11.8	12.1051	-0.305146
41	5.9	9.2416	-3.3416
42	11.4	11.4842	-0.08422
43	13	10.7566	2.24345
44	10.8	10.4314	0.368594
45	12.3	9.39496	2.90504
46	11.3	12.387	-1.08698
47	11.8	9.65413	2.14587
48	7.9	10.9522	-3.05222
49	12.7	8.67519	4.02481
50	12.3	10.4099	1.89013
51	11.6	11.1116	0.48842
52	6.7	9.21435	-2.51435
53	10.9	10.1858	0.71417
54	12.1	11.4552	0.644823
55	13.3	10.7966	2.50343
56	10.1	10.3296	-0.229596
57	5.7	11.3355	-5.63554
58	14.3	9.89562	4.40438
59	8	8.62011	-0.620107
60	13.3	10.7885	2.51153
61	9.3	11.1134	-1.81337
62	12.5	11.0949	1.40509
63	7.6	9.27396	-1.67396
64	15.9	11.8329	4.06706
65	9.2	10.8389	-1.63887
66	9.1	9.69751	-0.597513
67	11.1	12.7006	-1.60057
68	13	11.656	1.34402
69	14.5	11.6102	2.88983
70	12.2	10.8681	1.33188
71	12.3	12.7652	-0.465241
72	11.4	9.92687	1.47313
73	8.8	10.3874	-1.5874
74	14.6	11.2836	3.31638
75	12.6	10.678	1.92198
76	13	11.5667	1.43325
77	12.6	10.8763	1.72372
78	13.2	11.682	1.51803
79	9.9	10.3979	-0.497879
80	7.7	9.76871	-2.06871
81	10.5	10.7403	-0.240272
82	13.4	10.315	3.08497
83	10.9	10.9867	-0.0866662
84	4.3	9.5307	-5.2307
85	10.3	10.9472	-0.647182
86	11.8	11.0655	0.734461
87	11.2	10.1671	1.03294
88	11.4	10.8692	0.530839
89	8.6	10.5601	-1.96007
90	13.2	10.9227	2.27733
91	12.6	9.4067	3.1933
92	5.6	10.233	-4.63295
93	9.9	10.3679	-0.467884
94	8.8	10.9008	-2.1008
95	7.7	10.3128	-2.61283
96	9	10.3369	-1.33686
97	7.3	11.1745	-3.87445
98	11.4	10.201	1.199
99	13.6	10.2513	3.3487
100	7.9	10.8531	-2.95306
101	10.7	9.71629	0.983713
102	10.3	10.8123	-0.512333
103	8.3	9.12269	-0.822689
104	9.6	10.674	-1.07402
105	14.2	10.4011	3.79894
106	8.5	10.4206	-1.92062
107	13.5	10.0954	3.40464
108	4.9	9.96142	-5.06142
109	6.4	9.35535	-2.95535
110	9.6	10.186	-0.586002
111	11.6	10.6747	0.925258
112	11.1	9.69511	1.40489
113	4.35	9.2088	-4.8588
114	12.7	10.2533	2.4467
115	18.1	16.1284	1.97161
116	17.85	16.4508	1.39921
117	16.6	16.9084	-0.308369
118	12.6	11.7179	0.882099
119	17.1	19.6395	-2.53951
120	19.1	17.0714	2.02864
121	16.1	17.9441	-1.84414
122	13.35	11.2212	2.12884
123	18.4	17.4805	0.919455
124	14.7	9.50735	5.19265
125	10.6	14.1142	-3.5142
126	12.6	13.7086	-1.10855
127	16.2	16.0691	0.130914
128	13.6	14.9833	-1.38326
129	18.9	17.565	1.33498
130	14.1	13.446	0.653956
131	14.5	13.4314	1.06864
132	16.15	17.9055	-1.75551
133	14.75	13.8146	0.93537
134	14.8	13.9487	0.851262
135	12.45	11.5929	0.857083
136	12.65	12.5759	0.0741467
137	17.35	14.1745	3.1755
138	8.6	9.74814	-1.14814
139	18.4	17.727	0.67304
140	16.1	15.6163	0.483651
141	11.6	12.3256	-0.725576
142	17.75	15.2035	2.5465
143	15.25	15.1162	0.133809
144	17.65	16.4693	1.18068
145	16.35	16.7484	-0.398421
146	17.65	16.596	1.05396
147	13.6	13.5403	0.059686
148	14.35	14.0826	0.267415
149	14.75	16.8765	-2.12646
150	18.25	17.057	1.19303
151	9.9	16.7667	-6.86674
152	16	14.3339	1.66608
153	18.25	16.6432	1.60677
154	16.85	17.6856	-0.835552
155	14.6	12.9878	1.61218
156	13.85	13.613	0.236998
157	18.95	17.287	1.66303
158	15.6	14.7947	0.805259
159	14.85	17.2451	-2.39513
160	11.75	13.1941	-1.44414
161	18.45	15.7084	2.74157
162	15.9	14.8841	1.01593
163	17.1	16.5787	0.521312
164	16.1	9.03175	7.06825
165	19.9	18.15	1.74995
166	10.95	10.4625	0.487522
167	18.45	18.1077	0.342294
168	15.1	13.8525	1.24749
169	15	16.0376	-1.03763
170	11.35	14.108	-2.75795
171	15.95	15.7792	0.170846
172	18.1	15.4235	2.67651
173	14.6	16.8393	-2.23928
174	15.4	16.9257	-1.52569
175	15.4	16.9257	-1.52569
176	17.6	15.0685	2.53146
177	13.35	14.0881	-0.738081
178	19.1	17.1443	1.95572
179	15.35	16.6213	-1.27126
180	7.6	10.3336	-2.7336
181	13.4	14.2342	-0.834234
182	13.9	15.4692	-1.56916
183	19.1	17.2886	1.8114
184	15.25	15.4406	-0.190558
185	12.9	16.1864	-3.2864
186	16.1	15.7734	0.326605
187	17.35	15.0801	2.26986
188	13.15	15.1994	-2.0494
189	12.15	14.1489	-1.99886
190	12.6	11.4055	1.19453
191	10.35	11.2265	-0.876506
192	15.4	14.365	1.03503
193	9.6	12.0888	-2.48879
194	18.2	15.0421	3.15787
195	13.6	13.0584	0.541594
196	14.85	14.0273	0.822657
197	14.75	17.5812	-2.83123
198	14.1	13.3538	0.74624
199	14.9	12.6737	2.22633
200	16.25	15.1835	1.06646
201	19.25	18.048	1.20204
202	13.6	12.6307	0.969251
203	13.6	15.742	-2.14198
204	15.65	16.1168	-0.466751
205	12.75	14.7432	-1.99316
206	14.6	12.6644	1.93565
207	9.85	10.1707	-0.320671
208	12.65	10.8604	1.78957
209	19.2	17.4192	1.78082
210	16.6	15.1173	1.48273
211	11.2	10.4507	0.749299
212	15.25	15.5879	-0.337902
213	11.9	14.5537	-2.65369
214	13.2	14.4313	-1.23131
215	16.35	17.6993	-1.3493
216	12.4	13.3228	-0.922822
217	15.85	14.5469	1.30308
218	18.15	16.5936	1.55637
219	11.15	11.1297	0.0203321
220	15.65	16.5453	-0.895276
221	17.75	16.8358	0.914189
222	7.65	11.4627	-3.81274
223	12.35	13.5168	-1.16681
224	15.6	14.4662	1.13377
225	19.3	17.2756	2.02441
226	15.2	11.5307	3.66926
227	17.1	15.669	1.43099
228	15.6	13.1132	2.48676
229	18.4	14.786	3.61403
230	19.05	16.6197	2.43032
231	18.55	15.4529	3.09713
232	19.1	17.3088	1.79122
233	13.1	12.9039	0.196065
234	12.85	15.682	-2.83204
235	9.5	10.9373	-1.43734
236	4.5	9.74709	-5.24709
237	11.85	10.963	0.886998
238	13.6	16.2517	-2.65166
239	11.7	11.2863	0.413721
240	12.4	12.3788	0.021192
241	13.35	14.9415	-1.59152
242	11.4	13.5484	-2.14844
243	14.9	14.18	0.719964
244	19.9	18.15	1.74995
245	11.2	12.9016	-1.70155
246	14.6	15.9126	-1.31258
247	17.6	17.1587	0.441301
248	14.05	13.4724	0.577603
249	16.1	16.5951	-0.495131
250	13.35	15.2227	-1.87267
251	11.85	15.2086	-3.35864
252	11.95	12.9176	-0.967589
253	14.75	14.0619	0.688113
254	15.15	13.4934	1.65658
255	13.2	16.1789	-2.9789
256	16.85	16.3945	0.455504
257	7.85	11.9433	-4.0933
258	7.7	13.175	-5.47499
259	12.6	14.5484	-1.94841
260	7.85	13.9889	-6.13892
261	10.95	10.4625	0.487522
262	12.35	13.5494	-1.19943
263	9.95	12.6795	-2.72945
264	14.9	14.18	0.719964
265	16.65	15.5623	1.08774
266	13.4	13.0598	0.340204
267	13.95	13.563	0.38696
268	15.7	14.3489	1.35113
269	16.85	14.926	1.92397
270	10.95	10.689	0.261
271	15.35	14.6422	0.707838
272	12.2	12.5056	-0.305643
273	15.1	13.4063	1.69374
274	17.75	16.7538	0.996233
275	15.2	14.7087	0.491305
276	14.6	14.3468	0.253151
277	16.65	16.0775	0.572534
278	8.1	10.5175	-2.41749

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 10.3965 & 2.50353 \tabularnewline
2 & 12.2 & 9.99813 & 2.20187 \tabularnewline
3 & 12.8 & 10.8695 & 1.93046 \tabularnewline
4 & 7.4 & 10.8459 & -3.44593 \tabularnewline
5 & 6.7 & 9.85364 & -3.15364 \tabularnewline
6 & 12.6 & 12.8037 & -0.203663 \tabularnewline
7 & 14.8 & 11.0926 & 3.70741 \tabularnewline
8 & 13.3 & 10.368 & 2.93195 \tabularnewline
9 & 11.1 & 11.7349 & -0.634881 \tabularnewline
10 & 8.2 & 11.3369 & -3.13685 \tabularnewline
11 & 11.4 & 10.8709 & 0.529066 \tabularnewline
12 & 6.4 & 11.2819 & -4.88192 \tabularnewline
13 & 10.6 & 9.80456 & 0.79544 \tabularnewline
14 & 12 & 12.3868 & -0.38682 \tabularnewline
15 & 6.3 & 8.29398 & -1.99398 \tabularnewline
16 & 11.3 & 10.5114 & 0.788551 \tabularnewline
17 & 11.9 & 11.6501 & 0.249875 \tabularnewline
18 & 9.3 & 10.54 & -1.24003 \tabularnewline
19 & 9.6 & 11.6494 & -2.04944 \tabularnewline
20 & 10 & 9.72695 & 0.273055 \tabularnewline
21 & 6.4 & 9.96154 & -3.56154 \tabularnewline
22 & 13.8 & 12.344 & 1.456 \tabularnewline
23 & 10.8 & 12.0439 & -1.24385 \tabularnewline
24 & 13.8 & 11.0603 & 2.73967 \tabularnewline
25 & 11.7 & 10.9613 & 0.738699 \tabularnewline
26 & 10.9 & 12.2894 & -1.38937 \tabularnewline
27 & 16.1 & 14.1501 & 1.94993 \tabularnewline
28 & 13.4 & 10.5634 & 2.83662 \tabularnewline
29 & 9.9 & 9.90722 & -0.00721885 \tabularnewline
30 & 11.5 & 10.3636 & 1.13644 \tabularnewline
31 & 8.3 & 9.54963 & -1.24963 \tabularnewline
32 & 11.7 & 11.1758 & 0.524207 \tabularnewline
33 & 9 & 10.1948 & -1.19483 \tabularnewline
34 & 9.7 & 12.5557 & -2.85572 \tabularnewline
35 & 10.8 & 10.2654 & 0.534622 \tabularnewline
36 & 10.3 & 10.3942 & -0.0941647 \tabularnewline
37 & 10.4 & 9.80093 & 0.599065 \tabularnewline
38 & 12.7 & 11.4991 & 1.20093 \tabularnewline
39 & 9.3 & 11.5025 & -2.20247 \tabularnewline
40 & 11.8 & 12.1051 & -0.305146 \tabularnewline
41 & 5.9 & 9.2416 & -3.3416 \tabularnewline
42 & 11.4 & 11.4842 & -0.08422 \tabularnewline
43 & 13 & 10.7566 & 2.24345 \tabularnewline
44 & 10.8 & 10.4314 & 0.368594 \tabularnewline
45 & 12.3 & 9.39496 & 2.90504 \tabularnewline
46 & 11.3 & 12.387 & -1.08698 \tabularnewline
47 & 11.8 & 9.65413 & 2.14587 \tabularnewline
48 & 7.9 & 10.9522 & -3.05222 \tabularnewline
49 & 12.7 & 8.67519 & 4.02481 \tabularnewline
50 & 12.3 & 10.4099 & 1.89013 \tabularnewline
51 & 11.6 & 11.1116 & 0.48842 \tabularnewline
52 & 6.7 & 9.21435 & -2.51435 \tabularnewline
53 & 10.9 & 10.1858 & 0.71417 \tabularnewline
54 & 12.1 & 11.4552 & 0.644823 \tabularnewline
55 & 13.3 & 10.7966 & 2.50343 \tabularnewline
56 & 10.1 & 10.3296 & -0.229596 \tabularnewline
57 & 5.7 & 11.3355 & -5.63554 \tabularnewline
58 & 14.3 & 9.89562 & 4.40438 \tabularnewline
59 & 8 & 8.62011 & -0.620107 \tabularnewline
60 & 13.3 & 10.7885 & 2.51153 \tabularnewline
61 & 9.3 & 11.1134 & -1.81337 \tabularnewline
62 & 12.5 & 11.0949 & 1.40509 \tabularnewline
63 & 7.6 & 9.27396 & -1.67396 \tabularnewline
64 & 15.9 & 11.8329 & 4.06706 \tabularnewline
65 & 9.2 & 10.8389 & -1.63887 \tabularnewline
66 & 9.1 & 9.69751 & -0.597513 \tabularnewline
67 & 11.1 & 12.7006 & -1.60057 \tabularnewline
68 & 13 & 11.656 & 1.34402 \tabularnewline
69 & 14.5 & 11.6102 & 2.88983 \tabularnewline
70 & 12.2 & 10.8681 & 1.33188 \tabularnewline
71 & 12.3 & 12.7652 & -0.465241 \tabularnewline
72 & 11.4 & 9.92687 & 1.47313 \tabularnewline
73 & 8.8 & 10.3874 & -1.5874 \tabularnewline
74 & 14.6 & 11.2836 & 3.31638 \tabularnewline
75 & 12.6 & 10.678 & 1.92198 \tabularnewline
76 & 13 & 11.5667 & 1.43325 \tabularnewline
77 & 12.6 & 10.8763 & 1.72372 \tabularnewline
78 & 13.2 & 11.682 & 1.51803 \tabularnewline
79 & 9.9 & 10.3979 & -0.497879 \tabularnewline
80 & 7.7 & 9.76871 & -2.06871 \tabularnewline
81 & 10.5 & 10.7403 & -0.240272 \tabularnewline
82 & 13.4 & 10.315 & 3.08497 \tabularnewline
83 & 10.9 & 10.9867 & -0.0866662 \tabularnewline
84 & 4.3 & 9.5307 & -5.2307 \tabularnewline
85 & 10.3 & 10.9472 & -0.647182 \tabularnewline
86 & 11.8 & 11.0655 & 0.734461 \tabularnewline
87 & 11.2 & 10.1671 & 1.03294 \tabularnewline
88 & 11.4 & 10.8692 & 0.530839 \tabularnewline
89 & 8.6 & 10.5601 & -1.96007 \tabularnewline
90 & 13.2 & 10.9227 & 2.27733 \tabularnewline
91 & 12.6 & 9.4067 & 3.1933 \tabularnewline
92 & 5.6 & 10.233 & -4.63295 \tabularnewline
93 & 9.9 & 10.3679 & -0.467884 \tabularnewline
94 & 8.8 & 10.9008 & -2.1008 \tabularnewline
95 & 7.7 & 10.3128 & -2.61283 \tabularnewline
96 & 9 & 10.3369 & -1.33686 \tabularnewline
97 & 7.3 & 11.1745 & -3.87445 \tabularnewline
98 & 11.4 & 10.201 & 1.199 \tabularnewline
99 & 13.6 & 10.2513 & 3.3487 \tabularnewline
100 & 7.9 & 10.8531 & -2.95306 \tabularnewline
101 & 10.7 & 9.71629 & 0.983713 \tabularnewline
102 & 10.3 & 10.8123 & -0.512333 \tabularnewline
103 & 8.3 & 9.12269 & -0.822689 \tabularnewline
104 & 9.6 & 10.674 & -1.07402 \tabularnewline
105 & 14.2 & 10.4011 & 3.79894 \tabularnewline
106 & 8.5 & 10.4206 & -1.92062 \tabularnewline
107 & 13.5 & 10.0954 & 3.40464 \tabularnewline
108 & 4.9 & 9.96142 & -5.06142 \tabularnewline
109 & 6.4 & 9.35535 & -2.95535 \tabularnewline
110 & 9.6 & 10.186 & -0.586002 \tabularnewline
111 & 11.6 & 10.6747 & 0.925258 \tabularnewline
112 & 11.1 & 9.69511 & 1.40489 \tabularnewline
113 & 4.35 & 9.2088 & -4.8588 \tabularnewline
114 & 12.7 & 10.2533 & 2.4467 \tabularnewline
115 & 18.1 & 16.1284 & 1.97161 \tabularnewline
116 & 17.85 & 16.4508 & 1.39921 \tabularnewline
117 & 16.6 & 16.9084 & -0.308369 \tabularnewline
118 & 12.6 & 11.7179 & 0.882099 \tabularnewline
119 & 17.1 & 19.6395 & -2.53951 \tabularnewline
120 & 19.1 & 17.0714 & 2.02864 \tabularnewline
121 & 16.1 & 17.9441 & -1.84414 \tabularnewline
122 & 13.35 & 11.2212 & 2.12884 \tabularnewline
123 & 18.4 & 17.4805 & 0.919455 \tabularnewline
124 & 14.7 & 9.50735 & 5.19265 \tabularnewline
125 & 10.6 & 14.1142 & -3.5142 \tabularnewline
126 & 12.6 & 13.7086 & -1.10855 \tabularnewline
127 & 16.2 & 16.0691 & 0.130914 \tabularnewline
128 & 13.6 & 14.9833 & -1.38326 \tabularnewline
129 & 18.9 & 17.565 & 1.33498 \tabularnewline
130 & 14.1 & 13.446 & 0.653956 \tabularnewline
131 & 14.5 & 13.4314 & 1.06864 \tabularnewline
132 & 16.15 & 17.9055 & -1.75551 \tabularnewline
133 & 14.75 & 13.8146 & 0.93537 \tabularnewline
134 & 14.8 & 13.9487 & 0.851262 \tabularnewline
135 & 12.45 & 11.5929 & 0.857083 \tabularnewline
136 & 12.65 & 12.5759 & 0.0741467 \tabularnewline
137 & 17.35 & 14.1745 & 3.1755 \tabularnewline
138 & 8.6 & 9.74814 & -1.14814 \tabularnewline
139 & 18.4 & 17.727 & 0.67304 \tabularnewline
140 & 16.1 & 15.6163 & 0.483651 \tabularnewline
141 & 11.6 & 12.3256 & -0.725576 \tabularnewline
142 & 17.75 & 15.2035 & 2.5465 \tabularnewline
143 & 15.25 & 15.1162 & 0.133809 \tabularnewline
144 & 17.65 & 16.4693 & 1.18068 \tabularnewline
145 & 16.35 & 16.7484 & -0.398421 \tabularnewline
146 & 17.65 & 16.596 & 1.05396 \tabularnewline
147 & 13.6 & 13.5403 & 0.059686 \tabularnewline
148 & 14.35 & 14.0826 & 0.267415 \tabularnewline
149 & 14.75 & 16.8765 & -2.12646 \tabularnewline
150 & 18.25 & 17.057 & 1.19303 \tabularnewline
151 & 9.9 & 16.7667 & -6.86674 \tabularnewline
152 & 16 & 14.3339 & 1.66608 \tabularnewline
153 & 18.25 & 16.6432 & 1.60677 \tabularnewline
154 & 16.85 & 17.6856 & -0.835552 \tabularnewline
155 & 14.6 & 12.9878 & 1.61218 \tabularnewline
156 & 13.85 & 13.613 & 0.236998 \tabularnewline
157 & 18.95 & 17.287 & 1.66303 \tabularnewline
158 & 15.6 & 14.7947 & 0.805259 \tabularnewline
159 & 14.85 & 17.2451 & -2.39513 \tabularnewline
160 & 11.75 & 13.1941 & -1.44414 \tabularnewline
161 & 18.45 & 15.7084 & 2.74157 \tabularnewline
162 & 15.9 & 14.8841 & 1.01593 \tabularnewline
163 & 17.1 & 16.5787 & 0.521312 \tabularnewline
164 & 16.1 & 9.03175 & 7.06825 \tabularnewline
165 & 19.9 & 18.15 & 1.74995 \tabularnewline
166 & 10.95 & 10.4625 & 0.487522 \tabularnewline
167 & 18.45 & 18.1077 & 0.342294 \tabularnewline
168 & 15.1 & 13.8525 & 1.24749 \tabularnewline
169 & 15 & 16.0376 & -1.03763 \tabularnewline
170 & 11.35 & 14.108 & -2.75795 \tabularnewline
171 & 15.95 & 15.7792 & 0.170846 \tabularnewline
172 & 18.1 & 15.4235 & 2.67651 \tabularnewline
173 & 14.6 & 16.8393 & -2.23928 \tabularnewline
174 & 15.4 & 16.9257 & -1.52569 \tabularnewline
175 & 15.4 & 16.9257 & -1.52569 \tabularnewline
176 & 17.6 & 15.0685 & 2.53146 \tabularnewline
177 & 13.35 & 14.0881 & -0.738081 \tabularnewline
178 & 19.1 & 17.1443 & 1.95572 \tabularnewline
179 & 15.35 & 16.6213 & -1.27126 \tabularnewline
180 & 7.6 & 10.3336 & -2.7336 \tabularnewline
181 & 13.4 & 14.2342 & -0.834234 \tabularnewline
182 & 13.9 & 15.4692 & -1.56916 \tabularnewline
183 & 19.1 & 17.2886 & 1.8114 \tabularnewline
184 & 15.25 & 15.4406 & -0.190558 \tabularnewline
185 & 12.9 & 16.1864 & -3.2864 \tabularnewline
186 & 16.1 & 15.7734 & 0.326605 \tabularnewline
187 & 17.35 & 15.0801 & 2.26986 \tabularnewline
188 & 13.15 & 15.1994 & -2.0494 \tabularnewline
189 & 12.15 & 14.1489 & -1.99886 \tabularnewline
190 & 12.6 & 11.4055 & 1.19453 \tabularnewline
191 & 10.35 & 11.2265 & -0.876506 \tabularnewline
192 & 15.4 & 14.365 & 1.03503 \tabularnewline
193 & 9.6 & 12.0888 & -2.48879 \tabularnewline
194 & 18.2 & 15.0421 & 3.15787 \tabularnewline
195 & 13.6 & 13.0584 & 0.541594 \tabularnewline
196 & 14.85 & 14.0273 & 0.822657 \tabularnewline
197 & 14.75 & 17.5812 & -2.83123 \tabularnewline
198 & 14.1 & 13.3538 & 0.74624 \tabularnewline
199 & 14.9 & 12.6737 & 2.22633 \tabularnewline
200 & 16.25 & 15.1835 & 1.06646 \tabularnewline
201 & 19.25 & 18.048 & 1.20204 \tabularnewline
202 & 13.6 & 12.6307 & 0.969251 \tabularnewline
203 & 13.6 & 15.742 & -2.14198 \tabularnewline
204 & 15.65 & 16.1168 & -0.466751 \tabularnewline
205 & 12.75 & 14.7432 & -1.99316 \tabularnewline
206 & 14.6 & 12.6644 & 1.93565 \tabularnewline
207 & 9.85 & 10.1707 & -0.320671 \tabularnewline
208 & 12.65 & 10.8604 & 1.78957 \tabularnewline
209 & 19.2 & 17.4192 & 1.78082 \tabularnewline
210 & 16.6 & 15.1173 & 1.48273 \tabularnewline
211 & 11.2 & 10.4507 & 0.749299 \tabularnewline
212 & 15.25 & 15.5879 & -0.337902 \tabularnewline
213 & 11.9 & 14.5537 & -2.65369 \tabularnewline
214 & 13.2 & 14.4313 & -1.23131 \tabularnewline
215 & 16.35 & 17.6993 & -1.3493 \tabularnewline
216 & 12.4 & 13.3228 & -0.922822 \tabularnewline
217 & 15.85 & 14.5469 & 1.30308 \tabularnewline
218 & 18.15 & 16.5936 & 1.55637 \tabularnewline
219 & 11.15 & 11.1297 & 0.0203321 \tabularnewline
220 & 15.65 & 16.5453 & -0.895276 \tabularnewline
221 & 17.75 & 16.8358 & 0.914189 \tabularnewline
222 & 7.65 & 11.4627 & -3.81274 \tabularnewline
223 & 12.35 & 13.5168 & -1.16681 \tabularnewline
224 & 15.6 & 14.4662 & 1.13377 \tabularnewline
225 & 19.3 & 17.2756 & 2.02441 \tabularnewline
226 & 15.2 & 11.5307 & 3.66926 \tabularnewline
227 & 17.1 & 15.669 & 1.43099 \tabularnewline
228 & 15.6 & 13.1132 & 2.48676 \tabularnewline
229 & 18.4 & 14.786 & 3.61403 \tabularnewline
230 & 19.05 & 16.6197 & 2.43032 \tabularnewline
231 & 18.55 & 15.4529 & 3.09713 \tabularnewline
232 & 19.1 & 17.3088 & 1.79122 \tabularnewline
233 & 13.1 & 12.9039 & 0.196065 \tabularnewline
234 & 12.85 & 15.682 & -2.83204 \tabularnewline
235 & 9.5 & 10.9373 & -1.43734 \tabularnewline
236 & 4.5 & 9.74709 & -5.24709 \tabularnewline
237 & 11.85 & 10.963 & 0.886998 \tabularnewline
238 & 13.6 & 16.2517 & -2.65166 \tabularnewline
239 & 11.7 & 11.2863 & 0.413721 \tabularnewline
240 & 12.4 & 12.3788 & 0.021192 \tabularnewline
241 & 13.35 & 14.9415 & -1.59152 \tabularnewline
242 & 11.4 & 13.5484 & -2.14844 \tabularnewline
243 & 14.9 & 14.18 & 0.719964 \tabularnewline
244 & 19.9 & 18.15 & 1.74995 \tabularnewline
245 & 11.2 & 12.9016 & -1.70155 \tabularnewline
246 & 14.6 & 15.9126 & -1.31258 \tabularnewline
247 & 17.6 & 17.1587 & 0.441301 \tabularnewline
248 & 14.05 & 13.4724 & 0.577603 \tabularnewline
249 & 16.1 & 16.5951 & -0.495131 \tabularnewline
250 & 13.35 & 15.2227 & -1.87267 \tabularnewline
251 & 11.85 & 15.2086 & -3.35864 \tabularnewline
252 & 11.95 & 12.9176 & -0.967589 \tabularnewline
253 & 14.75 & 14.0619 & 0.688113 \tabularnewline
254 & 15.15 & 13.4934 & 1.65658 \tabularnewline
255 & 13.2 & 16.1789 & -2.9789 \tabularnewline
256 & 16.85 & 16.3945 & 0.455504 \tabularnewline
257 & 7.85 & 11.9433 & -4.0933 \tabularnewline
258 & 7.7 & 13.175 & -5.47499 \tabularnewline
259 & 12.6 & 14.5484 & -1.94841 \tabularnewline
260 & 7.85 & 13.9889 & -6.13892 \tabularnewline
261 & 10.95 & 10.4625 & 0.487522 \tabularnewline
262 & 12.35 & 13.5494 & -1.19943 \tabularnewline
263 & 9.95 & 12.6795 & -2.72945 \tabularnewline
264 & 14.9 & 14.18 & 0.719964 \tabularnewline
265 & 16.65 & 15.5623 & 1.08774 \tabularnewline
266 & 13.4 & 13.0598 & 0.340204 \tabularnewline
267 & 13.95 & 13.563 & 0.38696 \tabularnewline
268 & 15.7 & 14.3489 & 1.35113 \tabularnewline
269 & 16.85 & 14.926 & 1.92397 \tabularnewline
270 & 10.95 & 10.689 & 0.261 \tabularnewline
271 & 15.35 & 14.6422 & 0.707838 \tabularnewline
272 & 12.2 & 12.5056 & -0.305643 \tabularnewline
273 & 15.1 & 13.4063 & 1.69374 \tabularnewline
274 & 17.75 & 16.7538 & 0.996233 \tabularnewline
275 & 15.2 & 14.7087 & 0.491305 \tabularnewline
276 & 14.6 & 14.3468 & 0.253151 \tabularnewline
277 & 16.65 & 16.0775 & 0.572534 \tabularnewline
278 & 8.1 & 10.5175 & -2.41749 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266372&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]10.3965[/C][C]2.50353[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]9.99813[/C][C]2.20187[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]10.8695[/C][C]1.93046[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]10.8459[/C][C]-3.44593[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]9.85364[/C][C]-3.15364[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]12.8037[/C][C]-0.203663[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]11.0926[/C][C]3.70741[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]10.368[/C][C]2.93195[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.7349[/C][C]-0.634881[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]11.3369[/C][C]-3.13685[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]10.8709[/C][C]0.529066[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.2819[/C][C]-4.88192[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.80456[/C][C]0.79544[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.3868[/C][C]-0.38682[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]8.29398[/C][C]-1.99398[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]10.5114[/C][C]0.788551[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]11.6501[/C][C]0.249875[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.54[/C][C]-1.24003[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.6494[/C][C]-2.04944[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]9.72695[/C][C]0.273055[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]9.96154[/C][C]-3.56154[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.344[/C][C]1.456[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.0439[/C][C]-1.24385[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]11.0603[/C][C]2.73967[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]10.9613[/C][C]0.738699[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.2894[/C][C]-1.38937[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]14.1501[/C][C]1.94993[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.5634[/C][C]2.83662[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]9.90722[/C][C]-0.00721885[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]10.3636[/C][C]1.13644[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]9.54963[/C][C]-1.24963[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.1758[/C][C]0.524207[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]10.1948[/C][C]-1.19483[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.5557[/C][C]-2.85572[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]10.2654[/C][C]0.534622[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]10.3942[/C][C]-0.0941647[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]9.80093[/C][C]0.599065[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]11.4991[/C][C]1.20093[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]11.5025[/C][C]-2.20247[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.1051[/C][C]-0.305146[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]9.2416[/C][C]-3.3416[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]11.4842[/C][C]-0.08422[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]10.7566[/C][C]2.24345[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]10.4314[/C][C]0.368594[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]9.39496[/C][C]2.90504[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.387[/C][C]-1.08698[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]9.65413[/C][C]2.14587[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]10.9522[/C][C]-3.05222[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]8.67519[/C][C]4.02481[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]10.4099[/C][C]1.89013[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]11.1116[/C][C]0.48842[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]9.21435[/C][C]-2.51435[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.1858[/C][C]0.71417[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]11.4552[/C][C]0.644823[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.7966[/C][C]2.50343[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]10.3296[/C][C]-0.229596[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.3355[/C][C]-5.63554[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]9.89562[/C][C]4.40438[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]8.62011[/C][C]-0.620107[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.7885[/C][C]2.51153[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]11.1134[/C][C]-1.81337[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.0949[/C][C]1.40509[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]9.27396[/C][C]-1.67396[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]11.8329[/C][C]4.06706[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]10.8389[/C][C]-1.63887[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]9.69751[/C][C]-0.597513[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.7006[/C][C]-1.60057[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]11.656[/C][C]1.34402[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.6102[/C][C]2.88983[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.8681[/C][C]1.33188[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]12.7652[/C][C]-0.465241[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]9.92687[/C][C]1.47313[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]10.3874[/C][C]-1.5874[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.2836[/C][C]3.31638[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]10.678[/C][C]1.92198[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]11.5667[/C][C]1.43325[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]10.8763[/C][C]1.72372[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]11.682[/C][C]1.51803[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]10.3979[/C][C]-0.497879[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]9.76871[/C][C]-2.06871[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]10.7403[/C][C]-0.240272[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]10.315[/C][C]3.08497[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]10.9867[/C][C]-0.0866662[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]9.5307[/C][C]-5.2307[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]10.9472[/C][C]-0.647182[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]11.0655[/C][C]0.734461[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]10.1671[/C][C]1.03294[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]10.8692[/C][C]0.530839[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.5601[/C][C]-1.96007[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]10.9227[/C][C]2.27733[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]9.4067[/C][C]3.1933[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]10.233[/C][C]-4.63295[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]10.3679[/C][C]-0.467884[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]10.9008[/C][C]-2.1008[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]10.3128[/C][C]-2.61283[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]10.3369[/C][C]-1.33686[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]11.1745[/C][C]-3.87445[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]10.201[/C][C]1.199[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]10.2513[/C][C]3.3487[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]10.8531[/C][C]-2.95306[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]9.71629[/C][C]0.983713[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]10.8123[/C][C]-0.512333[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]9.12269[/C][C]-0.822689[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]10.674[/C][C]-1.07402[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]10.4011[/C][C]3.79894[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]10.4206[/C][C]-1.92062[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]10.0954[/C][C]3.40464[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]9.96142[/C][C]-5.06142[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]9.35535[/C][C]-2.95535[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]10.186[/C][C]-0.586002[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]10.6747[/C][C]0.925258[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]9.69511[/C][C]1.40489[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]9.2088[/C][C]-4.8588[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]10.2533[/C][C]2.4467[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]16.1284[/C][C]1.97161[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]16.4508[/C][C]1.39921[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]16.9084[/C][C]-0.308369[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]11.7179[/C][C]0.882099[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]19.6395[/C][C]-2.53951[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]17.0714[/C][C]2.02864[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]17.9441[/C][C]-1.84414[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]11.2212[/C][C]2.12884[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]17.4805[/C][C]0.919455[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]9.50735[/C][C]5.19265[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]14.1142[/C][C]-3.5142[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]13.7086[/C][C]-1.10855[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]16.0691[/C][C]0.130914[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]14.9833[/C][C]-1.38326[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]17.565[/C][C]1.33498[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]13.446[/C][C]0.653956[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]13.4314[/C][C]1.06864[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]17.9055[/C][C]-1.75551[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]13.8146[/C][C]0.93537[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]13.9487[/C][C]0.851262[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]11.5929[/C][C]0.857083[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]12.5759[/C][C]0.0741467[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]14.1745[/C][C]3.1755[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]9.74814[/C][C]-1.14814[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]17.727[/C][C]0.67304[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]15.6163[/C][C]0.483651[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]12.3256[/C][C]-0.725576[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]15.2035[/C][C]2.5465[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]15.1162[/C][C]0.133809[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]16.4693[/C][C]1.18068[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]16.7484[/C][C]-0.398421[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]16.596[/C][C]1.05396[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]13.5403[/C][C]0.059686[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]14.0826[/C][C]0.267415[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]16.8765[/C][C]-2.12646[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]17.057[/C][C]1.19303[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]16.7667[/C][C]-6.86674[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.3339[/C][C]1.66608[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]16.6432[/C][C]1.60677[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]17.6856[/C][C]-0.835552[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]12.9878[/C][C]1.61218[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]13.613[/C][C]0.236998[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]17.287[/C][C]1.66303[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]14.7947[/C][C]0.805259[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]17.2451[/C][C]-2.39513[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]13.1941[/C][C]-1.44414[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]15.7084[/C][C]2.74157[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]14.8841[/C][C]1.01593[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]16.5787[/C][C]0.521312[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]9.03175[/C][C]7.06825[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]18.15[/C][C]1.74995[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]10.4625[/C][C]0.487522[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]18.1077[/C][C]0.342294[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]13.8525[/C][C]1.24749[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]16.0376[/C][C]-1.03763[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]14.108[/C][C]-2.75795[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]15.7792[/C][C]0.170846[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]15.4235[/C][C]2.67651[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]16.8393[/C][C]-2.23928[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]16.9257[/C][C]-1.52569[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.9257[/C][C]-1.52569[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]15.0685[/C][C]2.53146[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]14.0881[/C][C]-0.738081[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]17.1443[/C][C]1.95572[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]16.6213[/C][C]-1.27126[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]10.3336[/C][C]-2.7336[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]14.2342[/C][C]-0.834234[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]15.4692[/C][C]-1.56916[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]17.2886[/C][C]1.8114[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]15.4406[/C][C]-0.190558[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]16.1864[/C][C]-3.2864[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]15.7734[/C][C]0.326605[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]15.0801[/C][C]2.26986[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]15.1994[/C][C]-2.0494[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]14.1489[/C][C]-1.99886[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]11.4055[/C][C]1.19453[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]11.2265[/C][C]-0.876506[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]14.365[/C][C]1.03503[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]12.0888[/C][C]-2.48879[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]15.0421[/C][C]3.15787[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]13.0584[/C][C]0.541594[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]14.0273[/C][C]0.822657[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]17.5812[/C][C]-2.83123[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]13.3538[/C][C]0.74624[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]12.6737[/C][C]2.22633[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]15.1835[/C][C]1.06646[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]18.048[/C][C]1.20204[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]12.6307[/C][C]0.969251[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]15.742[/C][C]-2.14198[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]16.1168[/C][C]-0.466751[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]14.7432[/C][C]-1.99316[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]12.6644[/C][C]1.93565[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]10.1707[/C][C]-0.320671[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]10.8604[/C][C]1.78957[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]17.4192[/C][C]1.78082[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]15.1173[/C][C]1.48273[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]10.4507[/C][C]0.749299[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]15.5879[/C][C]-0.337902[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]14.5537[/C][C]-2.65369[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]14.4313[/C][C]-1.23131[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]17.6993[/C][C]-1.3493[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]13.3228[/C][C]-0.922822[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]14.5469[/C][C]1.30308[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]16.5936[/C][C]1.55637[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]11.1297[/C][C]0.0203321[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]16.5453[/C][C]-0.895276[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]16.8358[/C][C]0.914189[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]11.4627[/C][C]-3.81274[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.5168[/C][C]-1.16681[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]14.4662[/C][C]1.13377[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]17.2756[/C][C]2.02441[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]11.5307[/C][C]3.66926[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]15.669[/C][C]1.43099[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]13.1132[/C][C]2.48676[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]14.786[/C][C]3.61403[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]16.6197[/C][C]2.43032[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]15.4529[/C][C]3.09713[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]17.3088[/C][C]1.79122[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]12.9039[/C][C]0.196065[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]15.682[/C][C]-2.83204[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]10.9373[/C][C]-1.43734[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]9.74709[/C][C]-5.24709[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]10.963[/C][C]0.886998[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]16.2517[/C][C]-2.65166[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]11.2863[/C][C]0.413721[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.3788[/C][C]0.021192[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]14.9415[/C][C]-1.59152[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]13.5484[/C][C]-2.14844[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]14.18[/C][C]0.719964[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]18.15[/C][C]1.74995[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]12.9016[/C][C]-1.70155[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]15.9126[/C][C]-1.31258[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]17.1587[/C][C]0.441301[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]13.4724[/C][C]0.577603[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]16.5951[/C][C]-0.495131[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]15.2227[/C][C]-1.87267[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]15.2086[/C][C]-3.35864[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]12.9176[/C][C]-0.967589[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]14.0619[/C][C]0.688113[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]13.4934[/C][C]1.65658[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]16.1789[/C][C]-2.9789[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]16.3945[/C][C]0.455504[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]11.9433[/C][C]-4.0933[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]13.175[/C][C]-5.47499[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]14.5484[/C][C]-1.94841[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]13.9889[/C][C]-6.13892[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]10.4625[/C][C]0.487522[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]13.5494[/C][C]-1.19943[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]12.6795[/C][C]-2.72945[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]14.18[/C][C]0.719964[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]15.5623[/C][C]1.08774[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]13.0598[/C][C]0.340204[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]13.563[/C][C]0.38696[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]14.3489[/C][C]1.35113[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]14.926[/C][C]1.92397[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]10.689[/C][C]0.261[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]14.6422[/C][C]0.707838[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]12.5056[/C][C]-0.305643[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]13.4063[/C][C]1.69374[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]16.7538[/C][C]0.996233[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]14.7087[/C][C]0.491305[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]14.3468[/C][C]0.253151[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]16.0775[/C][C]0.572534[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]10.5175[/C][C]-2.41749[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266372&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266372&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	10.3965	2.50353
2	12.2	9.99813	2.20187
3	12.8	10.8695	1.93046
4	7.4	10.8459	-3.44593
5	6.7	9.85364	-3.15364
6	12.6	12.8037	-0.203663
7	14.8	11.0926	3.70741
8	13.3	10.368	2.93195
9	11.1	11.7349	-0.634881
10	8.2	11.3369	-3.13685
11	11.4	10.8709	0.529066
12	6.4	11.2819	-4.88192
13	10.6	9.80456	0.79544
14	12	12.3868	-0.38682
15	6.3	8.29398	-1.99398
16	11.3	10.5114	0.788551
17	11.9	11.6501	0.249875
18	9.3	10.54	-1.24003
19	9.6	11.6494	-2.04944
20	10	9.72695	0.273055
21	6.4	9.96154	-3.56154
22	13.8	12.344	1.456
23	10.8	12.0439	-1.24385
24	13.8	11.0603	2.73967
25	11.7	10.9613	0.738699
26	10.9	12.2894	-1.38937
27	16.1	14.1501	1.94993
28	13.4	10.5634	2.83662
29	9.9	9.90722	-0.00721885
30	11.5	10.3636	1.13644
31	8.3	9.54963	-1.24963
32	11.7	11.1758	0.524207
33	9	10.1948	-1.19483
34	9.7	12.5557	-2.85572
35	10.8	10.2654	0.534622
36	10.3	10.3942	-0.0941647
37	10.4	9.80093	0.599065
38	12.7	11.4991	1.20093
39	9.3	11.5025	-2.20247
40	11.8	12.1051	-0.305146
41	5.9	9.2416	-3.3416
42	11.4	11.4842	-0.08422
43	13	10.7566	2.24345
44	10.8	10.4314	0.368594
45	12.3	9.39496	2.90504
46	11.3	12.387	-1.08698
47	11.8	9.65413	2.14587
48	7.9	10.9522	-3.05222
49	12.7	8.67519	4.02481
50	12.3	10.4099	1.89013
51	11.6	11.1116	0.48842
52	6.7	9.21435	-2.51435
53	10.9	10.1858	0.71417
54	12.1	11.4552	0.644823
55	13.3	10.7966	2.50343
56	10.1	10.3296	-0.229596
57	5.7	11.3355	-5.63554
58	14.3	9.89562	4.40438
59	8	8.62011	-0.620107
60	13.3	10.7885	2.51153
61	9.3	11.1134	-1.81337
62	12.5	11.0949	1.40509
63	7.6	9.27396	-1.67396
64	15.9	11.8329	4.06706
65	9.2	10.8389	-1.63887
66	9.1	9.69751	-0.597513
67	11.1	12.7006	-1.60057
68	13	11.656	1.34402
69	14.5	11.6102	2.88983
70	12.2	10.8681	1.33188
71	12.3	12.7652	-0.465241
72	11.4	9.92687	1.47313
73	8.8	10.3874	-1.5874
74	14.6	11.2836	3.31638
75	12.6	10.678	1.92198
76	13	11.5667	1.43325
77	12.6	10.8763	1.72372
78	13.2	11.682	1.51803
79	9.9	10.3979	-0.497879
80	7.7	9.76871	-2.06871
81	10.5	10.7403	-0.240272
82	13.4	10.315	3.08497
83	10.9	10.9867	-0.0866662
84	4.3	9.5307	-5.2307
85	10.3	10.9472	-0.647182
86	11.8	11.0655	0.734461
87	11.2	10.1671	1.03294
88	11.4	10.8692	0.530839
89	8.6	10.5601	-1.96007
90	13.2	10.9227	2.27733
91	12.6	9.4067	3.1933
92	5.6	10.233	-4.63295
93	9.9	10.3679	-0.467884
94	8.8	10.9008	-2.1008
95	7.7	10.3128	-2.61283
96	9	10.3369	-1.33686
97	7.3	11.1745	-3.87445
98	11.4	10.201	1.199
99	13.6	10.2513	3.3487
100	7.9	10.8531	-2.95306
101	10.7	9.71629	0.983713
102	10.3	10.8123	-0.512333
103	8.3	9.12269	-0.822689
104	9.6	10.674	-1.07402
105	14.2	10.4011	3.79894
106	8.5	10.4206	-1.92062
107	13.5	10.0954	3.40464
108	4.9	9.96142	-5.06142
109	6.4	9.35535	-2.95535
110	9.6	10.186	-0.586002
111	11.6	10.6747	0.925258
112	11.1	9.69511	1.40489
113	4.35	9.2088	-4.8588
114	12.7	10.2533	2.4467
115	18.1	16.1284	1.97161
116	17.85	16.4508	1.39921
117	16.6	16.9084	-0.308369
118	12.6	11.7179	0.882099
119	17.1	19.6395	-2.53951
120	19.1	17.0714	2.02864
121	16.1	17.9441	-1.84414
122	13.35	11.2212	2.12884
123	18.4	17.4805	0.919455
124	14.7	9.50735	5.19265
125	10.6	14.1142	-3.5142
126	12.6	13.7086	-1.10855
127	16.2	16.0691	0.130914
128	13.6	14.9833	-1.38326
129	18.9	17.565	1.33498
130	14.1	13.446	0.653956
131	14.5	13.4314	1.06864
132	16.15	17.9055	-1.75551
133	14.75	13.8146	0.93537
134	14.8	13.9487	0.851262
135	12.45	11.5929	0.857083
136	12.65	12.5759	0.0741467
137	17.35	14.1745	3.1755
138	8.6	9.74814	-1.14814
139	18.4	17.727	0.67304
140	16.1	15.6163	0.483651
141	11.6	12.3256	-0.725576
142	17.75	15.2035	2.5465
143	15.25	15.1162	0.133809
144	17.65	16.4693	1.18068
145	16.35	16.7484	-0.398421
146	17.65	16.596	1.05396
147	13.6	13.5403	0.059686
148	14.35	14.0826	0.267415
149	14.75	16.8765	-2.12646
150	18.25	17.057	1.19303
151	9.9	16.7667	-6.86674
152	16	14.3339	1.66608
153	18.25	16.6432	1.60677
154	16.85	17.6856	-0.835552
155	14.6	12.9878	1.61218
156	13.85	13.613	0.236998
157	18.95	17.287	1.66303
158	15.6	14.7947	0.805259
159	14.85	17.2451	-2.39513
160	11.75	13.1941	-1.44414
161	18.45	15.7084	2.74157
162	15.9	14.8841	1.01593
163	17.1	16.5787	0.521312
164	16.1	9.03175	7.06825
165	19.9	18.15	1.74995
166	10.95	10.4625	0.487522
167	18.45	18.1077	0.342294
168	15.1	13.8525	1.24749
169	15	16.0376	-1.03763
170	11.35	14.108	-2.75795
171	15.95	15.7792	0.170846
172	18.1	15.4235	2.67651
173	14.6	16.8393	-2.23928
174	15.4	16.9257	-1.52569
175	15.4	16.9257	-1.52569
176	17.6	15.0685	2.53146
177	13.35	14.0881	-0.738081
178	19.1	17.1443	1.95572
179	15.35	16.6213	-1.27126
180	7.6	10.3336	-2.7336
181	13.4	14.2342	-0.834234
182	13.9	15.4692	-1.56916
183	19.1	17.2886	1.8114
184	15.25	15.4406	-0.190558
185	12.9	16.1864	-3.2864
186	16.1	15.7734	0.326605
187	17.35	15.0801	2.26986
188	13.15	15.1994	-2.0494
189	12.15	14.1489	-1.99886
190	12.6	11.4055	1.19453
191	10.35	11.2265	-0.876506
192	15.4	14.365	1.03503
193	9.6	12.0888	-2.48879
194	18.2	15.0421	3.15787
195	13.6	13.0584	0.541594
196	14.85	14.0273	0.822657
197	14.75	17.5812	-2.83123
198	14.1	13.3538	0.74624
199	14.9	12.6737	2.22633
200	16.25	15.1835	1.06646
201	19.25	18.048	1.20204
202	13.6	12.6307	0.969251
203	13.6	15.742	-2.14198
204	15.65	16.1168	-0.466751
205	12.75	14.7432	-1.99316
206	14.6	12.6644	1.93565
207	9.85	10.1707	-0.320671
208	12.65	10.8604	1.78957
209	19.2	17.4192	1.78082
210	16.6	15.1173	1.48273
211	11.2	10.4507	0.749299
212	15.25	15.5879	-0.337902
213	11.9	14.5537	-2.65369
214	13.2	14.4313	-1.23131
215	16.35	17.6993	-1.3493
216	12.4	13.3228	-0.922822
217	15.85	14.5469	1.30308
218	18.15	16.5936	1.55637
219	11.15	11.1297	0.0203321
220	15.65	16.5453	-0.895276
221	17.75	16.8358	0.914189
222	7.65	11.4627	-3.81274
223	12.35	13.5168	-1.16681
224	15.6	14.4662	1.13377
225	19.3	17.2756	2.02441
226	15.2	11.5307	3.66926
227	17.1	15.669	1.43099
228	15.6	13.1132	2.48676
229	18.4	14.786	3.61403
230	19.05	16.6197	2.43032
231	18.55	15.4529	3.09713
232	19.1	17.3088	1.79122
233	13.1	12.9039	0.196065
234	12.85	15.682	-2.83204
235	9.5	10.9373	-1.43734
236	4.5	9.74709	-5.24709
237	11.85	10.963	0.886998
238	13.6	16.2517	-2.65166
239	11.7	11.2863	0.413721
240	12.4	12.3788	0.021192
241	13.35	14.9415	-1.59152
242	11.4	13.5484	-2.14844
243	14.9	14.18	0.719964
244	19.9	18.15	1.74995
245	11.2	12.9016	-1.70155
246	14.6	15.9126	-1.31258
247	17.6	17.1587	0.441301
248	14.05	13.4724	0.577603
249	16.1	16.5951	-0.495131
250	13.35	15.2227	-1.87267
251	11.85	15.2086	-3.35864
252	11.95	12.9176	-0.967589
253	14.75	14.0619	0.688113
254	15.15	13.4934	1.65658
255	13.2	16.1789	-2.9789
256	16.85	16.3945	0.455504
257	7.85	11.9433	-4.0933
258	7.7	13.175	-5.47499
259	12.6	14.5484	-1.94841
260	7.85	13.9889	-6.13892
261	10.95	10.4625	0.487522
262	12.35	13.5494	-1.19943
263	9.95	12.6795	-2.72945
264	14.9	14.18	0.719964
265	16.65	15.5623	1.08774
266	13.4	13.0598	0.340204
267	13.95	13.563	0.38696
268	15.7	14.3489	1.35113
269	16.85	14.926	1.92397
270	10.95	10.689	0.261
271	15.35	14.6422	0.707838
272	12.2	12.5056	-0.305643
273	15.1	13.4063	1.69374
274	17.75	16.7538	0.996233
275	15.2	14.7087	0.491305
276	14.6	14.3468	0.253151
277	16.65	16.0775	0.572534
278	8.1	10.5175	-2.41749

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
11	0.964458	0.0710834	0.0355417
12	0.967431	0.0651371	0.0325685
13	0.947332	0.105337	0.0526683
14	0.945837	0.108327	0.0541635
15	0.93998	0.12004	0.0600201
16	0.90482	0.190361	0.0951804
17	0.863664	0.272672	0.136336
18	0.857044	0.285912	0.142956
19	0.871453	0.257095	0.128547
20	0.827225	0.345549	0.172775
21	0.814014	0.371973	0.185986
22	0.763257	0.473487	0.236743
23	0.775263	0.449473	0.224737
24	0.854687	0.290627	0.145313
25	0.812196	0.375608	0.187804
26	0.78022	0.43956	0.21978
27	0.731052	0.537897	0.268948
28	0.73541	0.52918	0.26459
29	0.680036	0.639929	0.319964
30	0.63366	0.73268	0.36634
31	0.58056	0.838879	0.41944
32	0.519795	0.960409	0.480205
33	0.47266	0.945321	0.52734
34	0.466787	0.933573	0.533213
35	0.431069	0.862139	0.568931
36	0.385635	0.771269	0.614365
37	0.350807	0.701615	0.649193
38	0.338172	0.676345	0.661828
39	0.352458	0.704916	0.647542
40	0.316624	0.633248	0.683376
41	0.372934	0.745868	0.627066
42	0.327925	0.65585	0.672075
43	0.330712	0.661425	0.669288
44	0.288314	0.576628	0.711686
45	0.318655	0.63731	0.681345
46	0.308633	0.617266	0.691367
47	0.364565	0.72913	0.635435
48	0.450882	0.901763	0.549118
49	0.532121	0.935759	0.467879
50	0.495518	0.991036	0.504482
51	0.449154	0.898308	0.550846
52	0.469527	0.939055	0.530473
53	0.437084	0.874168	0.562916
54	0.391859	0.783718	0.608141
55	0.450084	0.900169	0.549916
56	0.406235	0.812469	0.593765
57	0.723072	0.553856	0.276928
58	0.827962	0.344076	0.172038
59	0.803474	0.393053	0.196526
60	0.803857	0.392285	0.196143
61	0.798155	0.40369	0.201845
62	0.77405	0.4519	0.22595
63	0.770619	0.458763	0.229381
64	0.842337	0.315326	0.157663
65	0.833887	0.332226	0.166113
66	0.809309	0.381383	0.190691
67	0.791127	0.417745	0.208873
68	0.770991	0.458019	0.229009
69	0.793739	0.412523	0.206261
70	0.773748	0.452504	0.226252
71	0.742744	0.514512	0.257256
72	0.722875	0.554251	0.277125
73	0.705745	0.588509	0.294255
74	0.740978	0.518043	0.259022
75	0.740357	0.519286	0.259643
76	0.727581	0.544838	0.272419
77	0.711142	0.577717	0.288858
78	0.703629	0.592741	0.296371
79	0.670845	0.65831	0.329155
80	0.666228	0.667545	0.333772
81	0.632058	0.735883	0.367942
82	0.661028	0.677943	0.338972
83	0.625691	0.748618	0.374309
84	0.781959	0.436082	0.218041
85	0.756583	0.486833	0.243417
86	0.73022	0.53956	0.26978
87	0.705071	0.589858	0.294929
88	0.673053	0.653894	0.326947
89	0.666747	0.666507	0.333253
90	0.674471	0.651058	0.325529
91	0.713492	0.573017	0.286508
92	0.803616	0.392769	0.196384
93	0.77785	0.4443	0.22215
94	0.772167	0.455666	0.227833
95	0.776845	0.44631	0.223155
96	0.756038	0.487925	0.243962
97	0.796457	0.407086	0.203543
98	0.781129	0.437742	0.218871
99	0.824001	0.351999	0.175999
100	0.838118	0.323763	0.161882
101	0.820946	0.358108	0.179054
102	0.796926	0.406148	0.203074
103	0.773252	0.453496	0.226748
104	0.749343	0.501314	0.250657
105	0.810671	0.378658	0.189329
106	0.80017	0.399659	0.19983
107	0.844068	0.311863	0.155932
108	0.907644	0.184712	0.0923558
109	0.91998	0.160039	0.0800196
110	0.908981	0.182038	0.0910189
111	0.896171	0.207658	0.103829
112	0.884403	0.231194	0.115597
113	0.90355	0.192899	0.0964496
114	0.934412	0.131177	0.0655883
115	0.931893	0.136213	0.0681067
116	0.922916	0.154167	0.0770837
117	0.910612	0.178777	0.0893885
118	0.898719	0.202563	0.101281
119	0.905653	0.188695	0.0943475
120	0.901135	0.197731	0.0988654
121	0.897193	0.205613	0.102807
122	0.895315	0.209371	0.104685
123	0.880649	0.238702	0.119351
124	0.942334	0.115332	0.0576662
125	0.959592	0.080816	0.040408
126	0.954448	0.0911039	0.045552
127	0.945434	0.109132	0.0545662
128	0.939484	0.121031	0.0605157
129	0.931762	0.136475	0.0682376
130	0.920463	0.159073	0.0795366
131	0.909939	0.180121	0.0900606
132	0.904301	0.191399	0.0956994
133	0.891171	0.217659	0.108829
134	0.876213	0.247573	0.123787
135	0.86076	0.278481	0.13924
136	0.840501	0.318998	0.159499
137	0.861556	0.276887	0.138444
138	0.846515	0.306969	0.153485
139	0.826968	0.346064	0.173032
140	0.805982	0.388035	0.194018
141	0.785402	0.429196	0.214598
142	0.792596	0.414808	0.207404
143	0.768464	0.463071	0.231536
144	0.74687	0.506259	0.25313
145	0.721403	0.557195	0.278597
146	0.69838	0.603241	0.30162
147	0.669484	0.661032	0.330516
148	0.639425	0.72115	0.360575
149	0.639412	0.721175	0.360588
150	0.617015	0.765969	0.382985
151	0.861338	0.277325	0.138662
152	0.854984	0.290033	0.145016
153	0.846884	0.306232	0.153116
154	0.827859	0.344282	0.172141
155	0.817607	0.364785	0.182393
156	0.79356	0.412879	0.20644
157	0.785959	0.428083	0.214041
158	0.76471	0.47058	0.23529
159	0.775006	0.449987	0.224994
160	0.761136	0.477728	0.238864
161	0.775334	0.449332	0.224666
162	0.756447	0.487106	0.243553
163	0.731337	0.537326	0.268663
164	0.961479	0.0770423	0.0385212
165	0.95647	0.0870591	0.0435296
166	0.949708	0.100583	0.0502917
167	0.93978	0.12044	0.0602199
168	0.936129	0.127742	0.0638711
169	0.928626	0.142747	0.0713736
170	0.940672	0.118656	0.0593279
171	0.929231	0.141538	0.0707692
172	0.932921	0.134159	0.0670794
173	0.936147	0.127706	0.0638532
174	0.930264	0.139473	0.0697363
175	0.924178	0.151645	0.0758225
176	0.927618	0.144764	0.0723821
177	0.915652	0.168696	0.084348
178	0.912415	0.17517	0.0875852
179	0.905843	0.188314	0.0941569
180	0.907369	0.185262	0.0926308
181	0.896081	0.207837	0.103919
182	0.895397	0.209207	0.104603
183	0.893984	0.212032	0.106016
184	0.877069	0.245863	0.122931
185	0.911678	0.176644	0.0883218
186	0.895614	0.208771	0.104386
187	0.896863	0.206274	0.103137
188	0.899755	0.200489	0.100245
189	0.902712	0.194576	0.0972878
190	0.891317	0.217365	0.108683
191	0.874917	0.250165	0.125083
192	0.85682	0.286359	0.14318
193	0.861684	0.276632	0.138316
194	0.87421	0.25158	0.12579
195	0.853439	0.293123	0.146561
196	0.837642	0.324716	0.162358
197	0.85186	0.29628	0.14814
198	0.83	0.34	0.17
199	0.828273	0.343454	0.171727
200	0.805044	0.389912	0.194956
201	0.778683	0.442634	0.221317
202	0.761972	0.476056	0.238028
203	0.757264	0.485472	0.242736
204	0.734741	0.530518	0.265259
205	0.713835	0.572329	0.286165
206	0.717944	0.564112	0.282056
207	0.699029	0.601943	0.300971
208	0.710164	0.579673	0.289836
209	0.684376	0.631248	0.315624
210	0.664506	0.670987	0.335494
211	0.659495	0.68101	0.340505
212	0.6209	0.7582	0.3791
213	0.63096	0.73808	0.36904
214	0.611594	0.776813	0.388406
215	0.597741	0.804517	0.402259
216	0.558077	0.883847	0.441923
217	0.538301	0.923398	0.461699
218	0.512061	0.975878	0.487939
219	0.478519	0.957039	0.521481
220	0.454324	0.908648	0.545676
221	0.41456	0.82912	0.58544
222	0.518866	0.962269	0.481134
223	0.48598	0.971959	0.51402
224	0.51224	0.975521	0.48776
225	0.483486	0.966971	0.516514
226	0.571332	0.857337	0.428668
227	0.56347	0.87306	0.43653
228	0.605791	0.788418	0.394209
229	0.78715	0.4257	0.21285
230	0.810662	0.378677	0.189338
231	0.84434	0.311319	0.15566
232	0.852726	0.294547	0.147274
233	0.828678	0.342645	0.171322
234	0.813828	0.372344	0.186172
235	0.782242	0.435515	0.217758
236	0.819456	0.361089	0.180544
237	0.797206	0.405588	0.202794
238	0.786239	0.427521	0.213761
239	0.799715	0.40057	0.200285
240	0.764258	0.471484	0.235742
241	0.721766	0.556468	0.278234
242	0.723608	0.552784	0.276392
243	0.700456	0.599088	0.299544
244	0.653134	0.693732	0.346866
245	0.608703	0.782594	0.391297
246	0.582389	0.835222	0.417611
247	0.528378	0.943243	0.471622
248	0.609802	0.780396	0.390198
249	0.558301	0.883398	0.441699
250	0.531219	0.937563	0.468781
251	0.47991	0.959821	0.52009
252	0.446468	0.892936	0.553532
253	0.379058	0.758115	0.620942
254	0.341114	0.682229	0.658886
255	0.286255	0.57251	0.713745
256	0.233908	0.467816	0.766092
257	0.260822	0.521644	0.739178
258	0.471829	0.943659	0.528171
259	0.442634	0.885267	0.557366
260	0.953272	0.0934557	0.0467279
261	0.949781	0.100439	0.0502193
262	0.940181	0.119637	0.0598185
263	0.997409	0.00518267	0.00259134
264	0.991986	0.0160281	0.00801404
265	0.980062	0.0398768	0.0199384
266	0.963705	0.0725896	0.0362948
267	0.9191	0.1618	0.0808999

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.964458 & 0.0710834 & 0.0355417 \tabularnewline
12 & 0.967431 & 0.0651371 & 0.0325685 \tabularnewline
13 & 0.947332 & 0.105337 & 0.0526683 \tabularnewline
14 & 0.945837 & 0.108327 & 0.0541635 \tabularnewline
15 & 0.93998 & 0.12004 & 0.0600201 \tabularnewline
16 & 0.90482 & 0.190361 & 0.0951804 \tabularnewline
17 & 0.863664 & 0.272672 & 0.136336 \tabularnewline
18 & 0.857044 & 0.285912 & 0.142956 \tabularnewline
19 & 0.871453 & 0.257095 & 0.128547 \tabularnewline
20 & 0.827225 & 0.345549 & 0.172775 \tabularnewline
21 & 0.814014 & 0.371973 & 0.185986 \tabularnewline
22 & 0.763257 & 0.473487 & 0.236743 \tabularnewline
23 & 0.775263 & 0.449473 & 0.224737 \tabularnewline
24 & 0.854687 & 0.290627 & 0.145313 \tabularnewline
25 & 0.812196 & 0.375608 & 0.187804 \tabularnewline
26 & 0.78022 & 0.43956 & 0.21978 \tabularnewline
27 & 0.731052 & 0.537897 & 0.268948 \tabularnewline
28 & 0.73541 & 0.52918 & 0.26459 \tabularnewline
29 & 0.680036 & 0.639929 & 0.319964 \tabularnewline
30 & 0.63366 & 0.73268 & 0.36634 \tabularnewline
31 & 0.58056 & 0.838879 & 0.41944 \tabularnewline
32 & 0.519795 & 0.960409 & 0.480205 \tabularnewline
33 & 0.47266 & 0.945321 & 0.52734 \tabularnewline
34 & 0.466787 & 0.933573 & 0.533213 \tabularnewline
35 & 0.431069 & 0.862139 & 0.568931 \tabularnewline
36 & 0.385635 & 0.771269 & 0.614365 \tabularnewline
37 & 0.350807 & 0.701615 & 0.649193 \tabularnewline
38 & 0.338172 & 0.676345 & 0.661828 \tabularnewline
39 & 0.352458 & 0.704916 & 0.647542 \tabularnewline
40 & 0.316624 & 0.633248 & 0.683376 \tabularnewline
41 & 0.372934 & 0.745868 & 0.627066 \tabularnewline
42 & 0.327925 & 0.65585 & 0.672075 \tabularnewline
43 & 0.330712 & 0.661425 & 0.669288 \tabularnewline
44 & 0.288314 & 0.576628 & 0.711686 \tabularnewline
45 & 0.318655 & 0.63731 & 0.681345 \tabularnewline
46 & 0.308633 & 0.617266 & 0.691367 \tabularnewline
47 & 0.364565 & 0.72913 & 0.635435 \tabularnewline
48 & 0.450882 & 0.901763 & 0.549118 \tabularnewline
49 & 0.532121 & 0.935759 & 0.467879 \tabularnewline
50 & 0.495518 & 0.991036 & 0.504482 \tabularnewline
51 & 0.449154 & 0.898308 & 0.550846 \tabularnewline
52 & 0.469527 & 0.939055 & 0.530473 \tabularnewline
53 & 0.437084 & 0.874168 & 0.562916 \tabularnewline
54 & 0.391859 & 0.783718 & 0.608141 \tabularnewline
55 & 0.450084 & 0.900169 & 0.549916 \tabularnewline
56 & 0.406235 & 0.812469 & 0.593765 \tabularnewline
57 & 0.723072 & 0.553856 & 0.276928 \tabularnewline
58 & 0.827962 & 0.344076 & 0.172038 \tabularnewline
59 & 0.803474 & 0.393053 & 0.196526 \tabularnewline
60 & 0.803857 & 0.392285 & 0.196143 \tabularnewline
61 & 0.798155 & 0.40369 & 0.201845 \tabularnewline
62 & 0.77405 & 0.4519 & 0.22595 \tabularnewline
63 & 0.770619 & 0.458763 & 0.229381 \tabularnewline
64 & 0.842337 & 0.315326 & 0.157663 \tabularnewline
65 & 0.833887 & 0.332226 & 0.166113 \tabularnewline
66 & 0.809309 & 0.381383 & 0.190691 \tabularnewline
67 & 0.791127 & 0.417745 & 0.208873 \tabularnewline
68 & 0.770991 & 0.458019 & 0.229009 \tabularnewline
69 & 0.793739 & 0.412523 & 0.206261 \tabularnewline
70 & 0.773748 & 0.452504 & 0.226252 \tabularnewline
71 & 0.742744 & 0.514512 & 0.257256 \tabularnewline
72 & 0.722875 & 0.554251 & 0.277125 \tabularnewline
73 & 0.705745 & 0.588509 & 0.294255 \tabularnewline
74 & 0.740978 & 0.518043 & 0.259022 \tabularnewline
75 & 0.740357 & 0.519286 & 0.259643 \tabularnewline
76 & 0.727581 & 0.544838 & 0.272419 \tabularnewline
77 & 0.711142 & 0.577717 & 0.288858 \tabularnewline
78 & 0.703629 & 0.592741 & 0.296371 \tabularnewline
79 & 0.670845 & 0.65831 & 0.329155 \tabularnewline
80 & 0.666228 & 0.667545 & 0.333772 \tabularnewline
81 & 0.632058 & 0.735883 & 0.367942 \tabularnewline
82 & 0.661028 & 0.677943 & 0.338972 \tabularnewline
83 & 0.625691 & 0.748618 & 0.374309 \tabularnewline
84 & 0.781959 & 0.436082 & 0.218041 \tabularnewline
85 & 0.756583 & 0.486833 & 0.243417 \tabularnewline
86 & 0.73022 & 0.53956 & 0.26978 \tabularnewline
87 & 0.705071 & 0.589858 & 0.294929 \tabularnewline
88 & 0.673053 & 0.653894 & 0.326947 \tabularnewline
89 & 0.666747 & 0.666507 & 0.333253 \tabularnewline
90 & 0.674471 & 0.651058 & 0.325529 \tabularnewline
91 & 0.713492 & 0.573017 & 0.286508 \tabularnewline
92 & 0.803616 & 0.392769 & 0.196384 \tabularnewline
93 & 0.77785 & 0.4443 & 0.22215 \tabularnewline
94 & 0.772167 & 0.455666 & 0.227833 \tabularnewline
95 & 0.776845 & 0.44631 & 0.223155 \tabularnewline
96 & 0.756038 & 0.487925 & 0.243962 \tabularnewline
97 & 0.796457 & 0.407086 & 0.203543 \tabularnewline
98 & 0.781129 & 0.437742 & 0.218871 \tabularnewline
99 & 0.824001 & 0.351999 & 0.175999 \tabularnewline
100 & 0.838118 & 0.323763 & 0.161882 \tabularnewline
101 & 0.820946 & 0.358108 & 0.179054 \tabularnewline
102 & 0.796926 & 0.406148 & 0.203074 \tabularnewline
103 & 0.773252 & 0.453496 & 0.226748 \tabularnewline
104 & 0.749343 & 0.501314 & 0.250657 \tabularnewline
105 & 0.810671 & 0.378658 & 0.189329 \tabularnewline
106 & 0.80017 & 0.399659 & 0.19983 \tabularnewline
107 & 0.844068 & 0.311863 & 0.155932 \tabularnewline
108 & 0.907644 & 0.184712 & 0.0923558 \tabularnewline
109 & 0.91998 & 0.160039 & 0.0800196 \tabularnewline
110 & 0.908981 & 0.182038 & 0.0910189 \tabularnewline
111 & 0.896171 & 0.207658 & 0.103829 \tabularnewline
112 & 0.884403 & 0.231194 & 0.115597 \tabularnewline
113 & 0.90355 & 0.192899 & 0.0964496 \tabularnewline
114 & 0.934412 & 0.131177 & 0.0655883 \tabularnewline
115 & 0.931893 & 0.136213 & 0.0681067 \tabularnewline
116 & 0.922916 & 0.154167 & 0.0770837 \tabularnewline
117 & 0.910612 & 0.178777 & 0.0893885 \tabularnewline
118 & 0.898719 & 0.202563 & 0.101281 \tabularnewline
119 & 0.905653 & 0.188695 & 0.0943475 \tabularnewline
120 & 0.901135 & 0.197731 & 0.0988654 \tabularnewline
121 & 0.897193 & 0.205613 & 0.102807 \tabularnewline
122 & 0.895315 & 0.209371 & 0.104685 \tabularnewline
123 & 0.880649 & 0.238702 & 0.119351 \tabularnewline
124 & 0.942334 & 0.115332 & 0.0576662 \tabularnewline
125 & 0.959592 & 0.080816 & 0.040408 \tabularnewline
126 & 0.954448 & 0.0911039 & 0.045552 \tabularnewline
127 & 0.945434 & 0.109132 & 0.0545662 \tabularnewline
128 & 0.939484 & 0.121031 & 0.0605157 \tabularnewline
129 & 0.931762 & 0.136475 & 0.0682376 \tabularnewline
130 & 0.920463 & 0.159073 & 0.0795366 \tabularnewline
131 & 0.909939 & 0.180121 & 0.0900606 \tabularnewline
132 & 0.904301 & 0.191399 & 0.0956994 \tabularnewline
133 & 0.891171 & 0.217659 & 0.108829 \tabularnewline
134 & 0.876213 & 0.247573 & 0.123787 \tabularnewline
135 & 0.86076 & 0.278481 & 0.13924 \tabularnewline
136 & 0.840501 & 0.318998 & 0.159499 \tabularnewline
137 & 0.861556 & 0.276887 & 0.138444 \tabularnewline
138 & 0.846515 & 0.306969 & 0.153485 \tabularnewline
139 & 0.826968 & 0.346064 & 0.173032 \tabularnewline
140 & 0.805982 & 0.388035 & 0.194018 \tabularnewline
141 & 0.785402 & 0.429196 & 0.214598 \tabularnewline
142 & 0.792596 & 0.414808 & 0.207404 \tabularnewline
143 & 0.768464 & 0.463071 & 0.231536 \tabularnewline
144 & 0.74687 & 0.506259 & 0.25313 \tabularnewline
145 & 0.721403 & 0.557195 & 0.278597 \tabularnewline
146 & 0.69838 & 0.603241 & 0.30162 \tabularnewline
147 & 0.669484 & 0.661032 & 0.330516 \tabularnewline
148 & 0.639425 & 0.72115 & 0.360575 \tabularnewline
149 & 0.639412 & 0.721175 & 0.360588 \tabularnewline
150 & 0.617015 & 0.765969 & 0.382985 \tabularnewline
151 & 0.861338 & 0.277325 & 0.138662 \tabularnewline
152 & 0.854984 & 0.290033 & 0.145016 \tabularnewline
153 & 0.846884 & 0.306232 & 0.153116 \tabularnewline
154 & 0.827859 & 0.344282 & 0.172141 \tabularnewline
155 & 0.817607 & 0.364785 & 0.182393 \tabularnewline
156 & 0.79356 & 0.412879 & 0.20644 \tabularnewline
157 & 0.785959 & 0.428083 & 0.214041 \tabularnewline
158 & 0.76471 & 0.47058 & 0.23529 \tabularnewline
159 & 0.775006 & 0.449987 & 0.224994 \tabularnewline
160 & 0.761136 & 0.477728 & 0.238864 \tabularnewline
161 & 0.775334 & 0.449332 & 0.224666 \tabularnewline
162 & 0.756447 & 0.487106 & 0.243553 \tabularnewline
163 & 0.731337 & 0.537326 & 0.268663 \tabularnewline
164 & 0.961479 & 0.0770423 & 0.0385212 \tabularnewline
165 & 0.95647 & 0.0870591 & 0.0435296 \tabularnewline
166 & 0.949708 & 0.100583 & 0.0502917 \tabularnewline
167 & 0.93978 & 0.12044 & 0.0602199 \tabularnewline
168 & 0.936129 & 0.127742 & 0.0638711 \tabularnewline
169 & 0.928626 & 0.142747 & 0.0713736 \tabularnewline
170 & 0.940672 & 0.118656 & 0.0593279 \tabularnewline
171 & 0.929231 & 0.141538 & 0.0707692 \tabularnewline
172 & 0.932921 & 0.134159 & 0.0670794 \tabularnewline
173 & 0.936147 & 0.127706 & 0.0638532 \tabularnewline
174 & 0.930264 & 0.139473 & 0.0697363 \tabularnewline
175 & 0.924178 & 0.151645 & 0.0758225 \tabularnewline
176 & 0.927618 & 0.144764 & 0.0723821 \tabularnewline
177 & 0.915652 & 0.168696 & 0.084348 \tabularnewline
178 & 0.912415 & 0.17517 & 0.0875852 \tabularnewline
179 & 0.905843 & 0.188314 & 0.0941569 \tabularnewline
180 & 0.907369 & 0.185262 & 0.0926308 \tabularnewline
181 & 0.896081 & 0.207837 & 0.103919 \tabularnewline
182 & 0.895397 & 0.209207 & 0.104603 \tabularnewline
183 & 0.893984 & 0.212032 & 0.106016 \tabularnewline
184 & 0.877069 & 0.245863 & 0.122931 \tabularnewline
185 & 0.911678 & 0.176644 & 0.0883218 \tabularnewline
186 & 0.895614 & 0.208771 & 0.104386 \tabularnewline
187 & 0.896863 & 0.206274 & 0.103137 \tabularnewline
188 & 0.899755 & 0.200489 & 0.100245 \tabularnewline
189 & 0.902712 & 0.194576 & 0.0972878 \tabularnewline
190 & 0.891317 & 0.217365 & 0.108683 \tabularnewline
191 & 0.874917 & 0.250165 & 0.125083 \tabularnewline
192 & 0.85682 & 0.286359 & 0.14318 \tabularnewline
193 & 0.861684 & 0.276632 & 0.138316 \tabularnewline
194 & 0.87421 & 0.25158 & 0.12579 \tabularnewline
195 & 0.853439 & 0.293123 & 0.146561 \tabularnewline
196 & 0.837642 & 0.324716 & 0.162358 \tabularnewline
197 & 0.85186 & 0.29628 & 0.14814 \tabularnewline
198 & 0.83 & 0.34 & 0.17 \tabularnewline
199 & 0.828273 & 0.343454 & 0.171727 \tabularnewline
200 & 0.805044 & 0.389912 & 0.194956 \tabularnewline
201 & 0.778683 & 0.442634 & 0.221317 \tabularnewline
202 & 0.761972 & 0.476056 & 0.238028 \tabularnewline
203 & 0.757264 & 0.485472 & 0.242736 \tabularnewline
204 & 0.734741 & 0.530518 & 0.265259 \tabularnewline
205 & 0.713835 & 0.572329 & 0.286165 \tabularnewline
206 & 0.717944 & 0.564112 & 0.282056 \tabularnewline
207 & 0.699029 & 0.601943 & 0.300971 \tabularnewline
208 & 0.710164 & 0.579673 & 0.289836 \tabularnewline
209 & 0.684376 & 0.631248 & 0.315624 \tabularnewline
210 & 0.664506 & 0.670987 & 0.335494 \tabularnewline
211 & 0.659495 & 0.68101 & 0.340505 \tabularnewline
212 & 0.6209 & 0.7582 & 0.3791 \tabularnewline
213 & 0.63096 & 0.73808 & 0.36904 \tabularnewline
214 & 0.611594 & 0.776813 & 0.388406 \tabularnewline
215 & 0.597741 & 0.804517 & 0.402259 \tabularnewline
216 & 0.558077 & 0.883847 & 0.441923 \tabularnewline
217 & 0.538301 & 0.923398 & 0.461699 \tabularnewline
218 & 0.512061 & 0.975878 & 0.487939 \tabularnewline
219 & 0.478519 & 0.957039 & 0.521481 \tabularnewline
220 & 0.454324 & 0.908648 & 0.545676 \tabularnewline
221 & 0.41456 & 0.82912 & 0.58544 \tabularnewline
222 & 0.518866 & 0.962269 & 0.481134 \tabularnewline
223 & 0.48598 & 0.971959 & 0.51402 \tabularnewline
224 & 0.51224 & 0.975521 & 0.48776 \tabularnewline
225 & 0.483486 & 0.966971 & 0.516514 \tabularnewline
226 & 0.571332 & 0.857337 & 0.428668 \tabularnewline
227 & 0.56347 & 0.87306 & 0.43653 \tabularnewline
228 & 0.605791 & 0.788418 & 0.394209 \tabularnewline
229 & 0.78715 & 0.4257 & 0.21285 \tabularnewline
230 & 0.810662 & 0.378677 & 0.189338 \tabularnewline
231 & 0.84434 & 0.311319 & 0.15566 \tabularnewline
232 & 0.852726 & 0.294547 & 0.147274 \tabularnewline
233 & 0.828678 & 0.342645 & 0.171322 \tabularnewline
234 & 0.813828 & 0.372344 & 0.186172 \tabularnewline
235 & 0.782242 & 0.435515 & 0.217758 \tabularnewline
236 & 0.819456 & 0.361089 & 0.180544 \tabularnewline
237 & 0.797206 & 0.405588 & 0.202794 \tabularnewline
238 & 0.786239 & 0.427521 & 0.213761 \tabularnewline
239 & 0.799715 & 0.40057 & 0.200285 \tabularnewline
240 & 0.764258 & 0.471484 & 0.235742 \tabularnewline
241 & 0.721766 & 0.556468 & 0.278234 \tabularnewline
242 & 0.723608 & 0.552784 & 0.276392 \tabularnewline
243 & 0.700456 & 0.599088 & 0.299544 \tabularnewline
244 & 0.653134 & 0.693732 & 0.346866 \tabularnewline
245 & 0.608703 & 0.782594 & 0.391297 \tabularnewline
246 & 0.582389 & 0.835222 & 0.417611 \tabularnewline
247 & 0.528378 & 0.943243 & 0.471622 \tabularnewline
248 & 0.609802 & 0.780396 & 0.390198 \tabularnewline
249 & 0.558301 & 0.883398 & 0.441699 \tabularnewline
250 & 0.531219 & 0.937563 & 0.468781 \tabularnewline
251 & 0.47991 & 0.959821 & 0.52009 \tabularnewline
252 & 0.446468 & 0.892936 & 0.553532 \tabularnewline
253 & 0.379058 & 0.758115 & 0.620942 \tabularnewline
254 & 0.341114 & 0.682229 & 0.658886 \tabularnewline
255 & 0.286255 & 0.57251 & 0.713745 \tabularnewline
256 & 0.233908 & 0.467816 & 0.766092 \tabularnewline
257 & 0.260822 & 0.521644 & 0.739178 \tabularnewline
258 & 0.471829 & 0.943659 & 0.528171 \tabularnewline
259 & 0.442634 & 0.885267 & 0.557366 \tabularnewline
260 & 0.953272 & 0.0934557 & 0.0467279 \tabularnewline
261 & 0.949781 & 0.100439 & 0.0502193 \tabularnewline
262 & 0.940181 & 0.119637 & 0.0598185 \tabularnewline
263 & 0.997409 & 0.00518267 & 0.00259134 \tabularnewline
264 & 0.991986 & 0.0160281 & 0.00801404 \tabularnewline
265 & 0.980062 & 0.0398768 & 0.0199384 \tabularnewline
266 & 0.963705 & 0.0725896 & 0.0362948 \tabularnewline
267 & 0.9191 & 0.1618 & 0.0808999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266372&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]0.964458[/C][C]0.0710834[/C][C]0.0355417[/C][/ROW]
[ROW][C]12[/C][C]0.967431[/C][C]0.0651371[/C][C]0.0325685[/C][/ROW]
[ROW][C]13[/C][C]0.947332[/C][C]0.105337[/C][C]0.0526683[/C][/ROW]
[ROW][C]14[/C][C]0.945837[/C][C]0.108327[/C][C]0.0541635[/C][/ROW]
[ROW][C]15[/C][C]0.93998[/C][C]0.12004[/C][C]0.0600201[/C][/ROW]
[ROW][C]16[/C][C]0.90482[/C][C]0.190361[/C][C]0.0951804[/C][/ROW]
[ROW][C]17[/C][C]0.863664[/C][C]0.272672[/C][C]0.136336[/C][/ROW]
[ROW][C]18[/C][C]0.857044[/C][C]0.285912[/C][C]0.142956[/C][/ROW]
[ROW][C]19[/C][C]0.871453[/C][C]0.257095[/C][C]0.128547[/C][/ROW]
[ROW][C]20[/C][C]0.827225[/C][C]0.345549[/C][C]0.172775[/C][/ROW]
[ROW][C]21[/C][C]0.814014[/C][C]0.371973[/C][C]0.185986[/C][/ROW]
[ROW][C]22[/C][C]0.763257[/C][C]0.473487[/C][C]0.236743[/C][/ROW]
[ROW][C]23[/C][C]0.775263[/C][C]0.449473[/C][C]0.224737[/C][/ROW]
[ROW][C]24[/C][C]0.854687[/C][C]0.290627[/C][C]0.145313[/C][/ROW]
[ROW][C]25[/C][C]0.812196[/C][C]0.375608[/C][C]0.187804[/C][/ROW]
[ROW][C]26[/C][C]0.78022[/C][C]0.43956[/C][C]0.21978[/C][/ROW]
[ROW][C]27[/C][C]0.731052[/C][C]0.537897[/C][C]0.268948[/C][/ROW]
[ROW][C]28[/C][C]0.73541[/C][C]0.52918[/C][C]0.26459[/C][/ROW]
[ROW][C]29[/C][C]0.680036[/C][C]0.639929[/C][C]0.319964[/C][/ROW]
[ROW][C]30[/C][C]0.63366[/C][C]0.73268[/C][C]0.36634[/C][/ROW]
[ROW][C]31[/C][C]0.58056[/C][C]0.838879[/C][C]0.41944[/C][/ROW]
[ROW][C]32[/C][C]0.519795[/C][C]0.960409[/C][C]0.480205[/C][/ROW]
[ROW][C]33[/C][C]0.47266[/C][C]0.945321[/C][C]0.52734[/C][/ROW]
[ROW][C]34[/C][C]0.466787[/C][C]0.933573[/C][C]0.533213[/C][/ROW]
[ROW][C]35[/C][C]0.431069[/C][C]0.862139[/C][C]0.568931[/C][/ROW]
[ROW][C]36[/C][C]0.385635[/C][C]0.771269[/C][C]0.614365[/C][/ROW]
[ROW][C]37[/C][C]0.350807[/C][C]0.701615[/C][C]0.649193[/C][/ROW]
[ROW][C]38[/C][C]0.338172[/C][C]0.676345[/C][C]0.661828[/C][/ROW]
[ROW][C]39[/C][C]0.352458[/C][C]0.704916[/C][C]0.647542[/C][/ROW]
[ROW][C]40[/C][C]0.316624[/C][C]0.633248[/C][C]0.683376[/C][/ROW]
[ROW][C]41[/C][C]0.372934[/C][C]0.745868[/C][C]0.627066[/C][/ROW]
[ROW][C]42[/C][C]0.327925[/C][C]0.65585[/C][C]0.672075[/C][/ROW]
[ROW][C]43[/C][C]0.330712[/C][C]0.661425[/C][C]0.669288[/C][/ROW]
[ROW][C]44[/C][C]0.288314[/C][C]0.576628[/C][C]0.711686[/C][/ROW]
[ROW][C]45[/C][C]0.318655[/C][C]0.63731[/C][C]0.681345[/C][/ROW]
[ROW][C]46[/C][C]0.308633[/C][C]0.617266[/C][C]0.691367[/C][/ROW]
[ROW][C]47[/C][C]0.364565[/C][C]0.72913[/C][C]0.635435[/C][/ROW]
[ROW][C]48[/C][C]0.450882[/C][C]0.901763[/C][C]0.549118[/C][/ROW]
[ROW][C]49[/C][C]0.532121[/C][C]0.935759[/C][C]0.467879[/C][/ROW]
[ROW][C]50[/C][C]0.495518[/C][C]0.991036[/C][C]0.504482[/C][/ROW]
[ROW][C]51[/C][C]0.449154[/C][C]0.898308[/C][C]0.550846[/C][/ROW]
[ROW][C]52[/C][C]0.469527[/C][C]0.939055[/C][C]0.530473[/C][/ROW]
[ROW][C]53[/C][C]0.437084[/C][C]0.874168[/C][C]0.562916[/C][/ROW]
[ROW][C]54[/C][C]0.391859[/C][C]0.783718[/C][C]0.608141[/C][/ROW]
[ROW][C]55[/C][C]0.450084[/C][C]0.900169[/C][C]0.549916[/C][/ROW]
[ROW][C]56[/C][C]0.406235[/C][C]0.812469[/C][C]0.593765[/C][/ROW]
[ROW][C]57[/C][C]0.723072[/C][C]0.553856[/C][C]0.276928[/C][/ROW]
[ROW][C]58[/C][C]0.827962[/C][C]0.344076[/C][C]0.172038[/C][/ROW]
[ROW][C]59[/C][C]0.803474[/C][C]0.393053[/C][C]0.196526[/C][/ROW]
[ROW][C]60[/C][C]0.803857[/C][C]0.392285[/C][C]0.196143[/C][/ROW]
[ROW][C]61[/C][C]0.798155[/C][C]0.40369[/C][C]0.201845[/C][/ROW]
[ROW][C]62[/C][C]0.77405[/C][C]0.4519[/C][C]0.22595[/C][/ROW]
[ROW][C]63[/C][C]0.770619[/C][C]0.458763[/C][C]0.229381[/C][/ROW]
[ROW][C]64[/C][C]0.842337[/C][C]0.315326[/C][C]0.157663[/C][/ROW]
[ROW][C]65[/C][C]0.833887[/C][C]0.332226[/C][C]0.166113[/C][/ROW]
[ROW][C]66[/C][C]0.809309[/C][C]0.381383[/C][C]0.190691[/C][/ROW]
[ROW][C]67[/C][C]0.791127[/C][C]0.417745[/C][C]0.208873[/C][/ROW]
[ROW][C]68[/C][C]0.770991[/C][C]0.458019[/C][C]0.229009[/C][/ROW]
[ROW][C]69[/C][C]0.793739[/C][C]0.412523[/C][C]0.206261[/C][/ROW]
[ROW][C]70[/C][C]0.773748[/C][C]0.452504[/C][C]0.226252[/C][/ROW]
[ROW][C]71[/C][C]0.742744[/C][C]0.514512[/C][C]0.257256[/C][/ROW]
[ROW][C]72[/C][C]0.722875[/C][C]0.554251[/C][C]0.277125[/C][/ROW]
[ROW][C]73[/C][C]0.705745[/C][C]0.588509[/C][C]0.294255[/C][/ROW]
[ROW][C]74[/C][C]0.740978[/C][C]0.518043[/C][C]0.259022[/C][/ROW]
[ROW][C]75[/C][C]0.740357[/C][C]0.519286[/C][C]0.259643[/C][/ROW]
[ROW][C]76[/C][C]0.727581[/C][C]0.544838[/C][C]0.272419[/C][/ROW]
[ROW][C]77[/C][C]0.711142[/C][C]0.577717[/C][C]0.288858[/C][/ROW]
[ROW][C]78[/C][C]0.703629[/C][C]0.592741[/C][C]0.296371[/C][/ROW]
[ROW][C]79[/C][C]0.670845[/C][C]0.65831[/C][C]0.329155[/C][/ROW]
[ROW][C]80[/C][C]0.666228[/C][C]0.667545[/C][C]0.333772[/C][/ROW]
[ROW][C]81[/C][C]0.632058[/C][C]0.735883[/C][C]0.367942[/C][/ROW]
[ROW][C]82[/C][C]0.661028[/C][C]0.677943[/C][C]0.338972[/C][/ROW]
[ROW][C]83[/C][C]0.625691[/C][C]0.748618[/C][C]0.374309[/C][/ROW]
[ROW][C]84[/C][C]0.781959[/C][C]0.436082[/C][C]0.218041[/C][/ROW]
[ROW][C]85[/C][C]0.756583[/C][C]0.486833[/C][C]0.243417[/C][/ROW]
[ROW][C]86[/C][C]0.73022[/C][C]0.53956[/C][C]0.26978[/C][/ROW]
[ROW][C]87[/C][C]0.705071[/C][C]0.589858[/C][C]0.294929[/C][/ROW]
[ROW][C]88[/C][C]0.673053[/C][C]0.653894[/C][C]0.326947[/C][/ROW]
[ROW][C]89[/C][C]0.666747[/C][C]0.666507[/C][C]0.333253[/C][/ROW]
[ROW][C]90[/C][C]0.674471[/C][C]0.651058[/C][C]0.325529[/C][/ROW]
[ROW][C]91[/C][C]0.713492[/C][C]0.573017[/C][C]0.286508[/C][/ROW]
[ROW][C]92[/C][C]0.803616[/C][C]0.392769[/C][C]0.196384[/C][/ROW]
[ROW][C]93[/C][C]0.77785[/C][C]0.4443[/C][C]0.22215[/C][/ROW]
[ROW][C]94[/C][C]0.772167[/C][C]0.455666[/C][C]0.227833[/C][/ROW]
[ROW][C]95[/C][C]0.776845[/C][C]0.44631[/C][C]0.223155[/C][/ROW]
[ROW][C]96[/C][C]0.756038[/C][C]0.487925[/C][C]0.243962[/C][/ROW]
[ROW][C]97[/C][C]0.796457[/C][C]0.407086[/C][C]0.203543[/C][/ROW]
[ROW][C]98[/C][C]0.781129[/C][C]0.437742[/C][C]0.218871[/C][/ROW]
[ROW][C]99[/C][C]0.824001[/C][C]0.351999[/C][C]0.175999[/C][/ROW]
[ROW][C]100[/C][C]0.838118[/C][C]0.323763[/C][C]0.161882[/C][/ROW]
[ROW][C]101[/C][C]0.820946[/C][C]0.358108[/C][C]0.179054[/C][/ROW]
[ROW][C]102[/C][C]0.796926[/C][C]0.406148[/C][C]0.203074[/C][/ROW]
[ROW][C]103[/C][C]0.773252[/C][C]0.453496[/C][C]0.226748[/C][/ROW]
[ROW][C]104[/C][C]0.749343[/C][C]0.501314[/C][C]0.250657[/C][/ROW]
[ROW][C]105[/C][C]0.810671[/C][C]0.378658[/C][C]0.189329[/C][/ROW]
[ROW][C]106[/C][C]0.80017[/C][C]0.399659[/C][C]0.19983[/C][/ROW]
[ROW][C]107[/C][C]0.844068[/C][C]0.311863[/C][C]0.155932[/C][/ROW]
[ROW][C]108[/C][C]0.907644[/C][C]0.184712[/C][C]0.0923558[/C][/ROW]
[ROW][C]109[/C][C]0.91998[/C][C]0.160039[/C][C]0.0800196[/C][/ROW]
[ROW][C]110[/C][C]0.908981[/C][C]0.182038[/C][C]0.0910189[/C][/ROW]
[ROW][C]111[/C][C]0.896171[/C][C]0.207658[/C][C]0.103829[/C][/ROW]
[ROW][C]112[/C][C]0.884403[/C][C]0.231194[/C][C]0.115597[/C][/ROW]
[ROW][C]113[/C][C]0.90355[/C][C]0.192899[/C][C]0.0964496[/C][/ROW]
[ROW][C]114[/C][C]0.934412[/C][C]0.131177[/C][C]0.0655883[/C][/ROW]
[ROW][C]115[/C][C]0.931893[/C][C]0.136213[/C][C]0.0681067[/C][/ROW]
[ROW][C]116[/C][C]0.922916[/C][C]0.154167[/C][C]0.0770837[/C][/ROW]
[ROW][C]117[/C][C]0.910612[/C][C]0.178777[/C][C]0.0893885[/C][/ROW]
[ROW][C]118[/C][C]0.898719[/C][C]0.202563[/C][C]0.101281[/C][/ROW]
[ROW][C]119[/C][C]0.905653[/C][C]0.188695[/C][C]0.0943475[/C][/ROW]
[ROW][C]120[/C][C]0.901135[/C][C]0.197731[/C][C]0.0988654[/C][/ROW]
[ROW][C]121[/C][C]0.897193[/C][C]0.205613[/C][C]0.102807[/C][/ROW]
[ROW][C]122[/C][C]0.895315[/C][C]0.209371[/C][C]0.104685[/C][/ROW]
[ROW][C]123[/C][C]0.880649[/C][C]0.238702[/C][C]0.119351[/C][/ROW]
[ROW][C]124[/C][C]0.942334[/C][C]0.115332[/C][C]0.0576662[/C][/ROW]
[ROW][C]125[/C][C]0.959592[/C][C]0.080816[/C][C]0.040408[/C][/ROW]
[ROW][C]126[/C][C]0.954448[/C][C]0.0911039[/C][C]0.045552[/C][/ROW]
[ROW][C]127[/C][C]0.945434[/C][C]0.109132[/C][C]0.0545662[/C][/ROW]
[ROW][C]128[/C][C]0.939484[/C][C]0.121031[/C][C]0.0605157[/C][/ROW]
[ROW][C]129[/C][C]0.931762[/C][C]0.136475[/C][C]0.0682376[/C][/ROW]
[ROW][C]130[/C][C]0.920463[/C][C]0.159073[/C][C]0.0795366[/C][/ROW]
[ROW][C]131[/C][C]0.909939[/C][C]0.180121[/C][C]0.0900606[/C][/ROW]
[ROW][C]132[/C][C]0.904301[/C][C]0.191399[/C][C]0.0956994[/C][/ROW]
[ROW][C]133[/C][C]0.891171[/C][C]0.217659[/C][C]0.108829[/C][/ROW]
[ROW][C]134[/C][C]0.876213[/C][C]0.247573[/C][C]0.123787[/C][/ROW]
[ROW][C]135[/C][C]0.86076[/C][C]0.278481[/C][C]0.13924[/C][/ROW]
[ROW][C]136[/C][C]0.840501[/C][C]0.318998[/C][C]0.159499[/C][/ROW]
[ROW][C]137[/C][C]0.861556[/C][C]0.276887[/C][C]0.138444[/C][/ROW]
[ROW][C]138[/C][C]0.846515[/C][C]0.306969[/C][C]0.153485[/C][/ROW]
[ROW][C]139[/C][C]0.826968[/C][C]0.346064[/C][C]0.173032[/C][/ROW]
[ROW][C]140[/C][C]0.805982[/C][C]0.388035[/C][C]0.194018[/C][/ROW]
[ROW][C]141[/C][C]0.785402[/C][C]0.429196[/C][C]0.214598[/C][/ROW]
[ROW][C]142[/C][C]0.792596[/C][C]0.414808[/C][C]0.207404[/C][/ROW]
[ROW][C]143[/C][C]0.768464[/C][C]0.463071[/C][C]0.231536[/C][/ROW]
[ROW][C]144[/C][C]0.74687[/C][C]0.506259[/C][C]0.25313[/C][/ROW]
[ROW][C]145[/C][C]0.721403[/C][C]0.557195[/C][C]0.278597[/C][/ROW]
[ROW][C]146[/C][C]0.69838[/C][C]0.603241[/C][C]0.30162[/C][/ROW]
[ROW][C]147[/C][C]0.669484[/C][C]0.661032[/C][C]0.330516[/C][/ROW]
[ROW][C]148[/C][C]0.639425[/C][C]0.72115[/C][C]0.360575[/C][/ROW]
[ROW][C]149[/C][C]0.639412[/C][C]0.721175[/C][C]0.360588[/C][/ROW]
[ROW][C]150[/C][C]0.617015[/C][C]0.765969[/C][C]0.382985[/C][/ROW]
[ROW][C]151[/C][C]0.861338[/C][C]0.277325[/C][C]0.138662[/C][/ROW]
[ROW][C]152[/C][C]0.854984[/C][C]0.290033[/C][C]0.145016[/C][/ROW]
[ROW][C]153[/C][C]0.846884[/C][C]0.306232[/C][C]0.153116[/C][/ROW]
[ROW][C]154[/C][C]0.827859[/C][C]0.344282[/C][C]0.172141[/C][/ROW]
[ROW][C]155[/C][C]0.817607[/C][C]0.364785[/C][C]0.182393[/C][/ROW]
[ROW][C]156[/C][C]0.79356[/C][C]0.412879[/C][C]0.20644[/C][/ROW]
[ROW][C]157[/C][C]0.785959[/C][C]0.428083[/C][C]0.214041[/C][/ROW]
[ROW][C]158[/C][C]0.76471[/C][C]0.47058[/C][C]0.23529[/C][/ROW]
[ROW][C]159[/C][C]0.775006[/C][C]0.449987[/C][C]0.224994[/C][/ROW]
[ROW][C]160[/C][C]0.761136[/C][C]0.477728[/C][C]0.238864[/C][/ROW]
[ROW][C]161[/C][C]0.775334[/C][C]0.449332[/C][C]0.224666[/C][/ROW]
[ROW][C]162[/C][C]0.756447[/C][C]0.487106[/C][C]0.243553[/C][/ROW]
[ROW][C]163[/C][C]0.731337[/C][C]0.537326[/C][C]0.268663[/C][/ROW]
[ROW][C]164[/C][C]0.961479[/C][C]0.0770423[/C][C]0.0385212[/C][/ROW]
[ROW][C]165[/C][C]0.95647[/C][C]0.0870591[/C][C]0.0435296[/C][/ROW]
[ROW][C]166[/C][C]0.949708[/C][C]0.100583[/C][C]0.0502917[/C][/ROW]
[ROW][C]167[/C][C]0.93978[/C][C]0.12044[/C][C]0.0602199[/C][/ROW]
[ROW][C]168[/C][C]0.936129[/C][C]0.127742[/C][C]0.0638711[/C][/ROW]
[ROW][C]169[/C][C]0.928626[/C][C]0.142747[/C][C]0.0713736[/C][/ROW]
[ROW][C]170[/C][C]0.940672[/C][C]0.118656[/C][C]0.0593279[/C][/ROW]
[ROW][C]171[/C][C]0.929231[/C][C]0.141538[/C][C]0.0707692[/C][/ROW]
[ROW][C]172[/C][C]0.932921[/C][C]0.134159[/C][C]0.0670794[/C][/ROW]
[ROW][C]173[/C][C]0.936147[/C][C]0.127706[/C][C]0.0638532[/C][/ROW]
[ROW][C]174[/C][C]0.930264[/C][C]0.139473[/C][C]0.0697363[/C][/ROW]
[ROW][C]175[/C][C]0.924178[/C][C]0.151645[/C][C]0.0758225[/C][/ROW]
[ROW][C]176[/C][C]0.927618[/C][C]0.144764[/C][C]0.0723821[/C][/ROW]
[ROW][C]177[/C][C]0.915652[/C][C]0.168696[/C][C]0.084348[/C][/ROW]
[ROW][C]178[/C][C]0.912415[/C][C]0.17517[/C][C]0.0875852[/C][/ROW]
[ROW][C]179[/C][C]0.905843[/C][C]0.188314[/C][C]0.0941569[/C][/ROW]
[ROW][C]180[/C][C]0.907369[/C][C]0.185262[/C][C]0.0926308[/C][/ROW]
[ROW][C]181[/C][C]0.896081[/C][C]0.207837[/C][C]0.103919[/C][/ROW]
[ROW][C]182[/C][C]0.895397[/C][C]0.209207[/C][C]0.104603[/C][/ROW]
[ROW][C]183[/C][C]0.893984[/C][C]0.212032[/C][C]0.106016[/C][/ROW]
[ROW][C]184[/C][C]0.877069[/C][C]0.245863[/C][C]0.122931[/C][/ROW]
[ROW][C]185[/C][C]0.911678[/C][C]0.176644[/C][C]0.0883218[/C][/ROW]
[ROW][C]186[/C][C]0.895614[/C][C]0.208771[/C][C]0.104386[/C][/ROW]
[ROW][C]187[/C][C]0.896863[/C][C]0.206274[/C][C]0.103137[/C][/ROW]
[ROW][C]188[/C][C]0.899755[/C][C]0.200489[/C][C]0.100245[/C][/ROW]
[ROW][C]189[/C][C]0.902712[/C][C]0.194576[/C][C]0.0972878[/C][/ROW]
[ROW][C]190[/C][C]0.891317[/C][C]0.217365[/C][C]0.108683[/C][/ROW]
[ROW][C]191[/C][C]0.874917[/C][C]0.250165[/C][C]0.125083[/C][/ROW]
[ROW][C]192[/C][C]0.85682[/C][C]0.286359[/C][C]0.14318[/C][/ROW]
[ROW][C]193[/C][C]0.861684[/C][C]0.276632[/C][C]0.138316[/C][/ROW]
[ROW][C]194[/C][C]0.87421[/C][C]0.25158[/C][C]0.12579[/C][/ROW]
[ROW][C]195[/C][C]0.853439[/C][C]0.293123[/C][C]0.146561[/C][/ROW]
[ROW][C]196[/C][C]0.837642[/C][C]0.324716[/C][C]0.162358[/C][/ROW]
[ROW][C]197[/C][C]0.85186[/C][C]0.29628[/C][C]0.14814[/C][/ROW]
[ROW][C]198[/C][C]0.83[/C][C]0.34[/C][C]0.17[/C][/ROW]
[ROW][C]199[/C][C]0.828273[/C][C]0.343454[/C][C]0.171727[/C][/ROW]
[ROW][C]200[/C][C]0.805044[/C][C]0.389912[/C][C]0.194956[/C][/ROW]
[ROW][C]201[/C][C]0.778683[/C][C]0.442634[/C][C]0.221317[/C][/ROW]
[ROW][C]202[/C][C]0.761972[/C][C]0.476056[/C][C]0.238028[/C][/ROW]
[ROW][C]203[/C][C]0.757264[/C][C]0.485472[/C][C]0.242736[/C][/ROW]
[ROW][C]204[/C][C]0.734741[/C][C]0.530518[/C][C]0.265259[/C][/ROW]
[ROW][C]205[/C][C]0.713835[/C][C]0.572329[/C][C]0.286165[/C][/ROW]
[ROW][C]206[/C][C]0.717944[/C][C]0.564112[/C][C]0.282056[/C][/ROW]
[ROW][C]207[/C][C]0.699029[/C][C]0.601943[/C][C]0.300971[/C][/ROW]
[ROW][C]208[/C][C]0.710164[/C][C]0.579673[/C][C]0.289836[/C][/ROW]
[ROW][C]209[/C][C]0.684376[/C][C]0.631248[/C][C]0.315624[/C][/ROW]
[ROW][C]210[/C][C]0.664506[/C][C]0.670987[/C][C]0.335494[/C][/ROW]
[ROW][C]211[/C][C]0.659495[/C][C]0.68101[/C][C]0.340505[/C][/ROW]
[ROW][C]212[/C][C]0.6209[/C][C]0.7582[/C][C]0.3791[/C][/ROW]
[ROW][C]213[/C][C]0.63096[/C][C]0.73808[/C][C]0.36904[/C][/ROW]
[ROW][C]214[/C][C]0.611594[/C][C]0.776813[/C][C]0.388406[/C][/ROW]
[ROW][C]215[/C][C]0.597741[/C][C]0.804517[/C][C]0.402259[/C][/ROW]
[ROW][C]216[/C][C]0.558077[/C][C]0.883847[/C][C]0.441923[/C][/ROW]
[ROW][C]217[/C][C]0.538301[/C][C]0.923398[/C][C]0.461699[/C][/ROW]
[ROW][C]218[/C][C]0.512061[/C][C]0.975878[/C][C]0.487939[/C][/ROW]
[ROW][C]219[/C][C]0.478519[/C][C]0.957039[/C][C]0.521481[/C][/ROW]
[ROW][C]220[/C][C]0.454324[/C][C]0.908648[/C][C]0.545676[/C][/ROW]
[ROW][C]221[/C][C]0.41456[/C][C]0.82912[/C][C]0.58544[/C][/ROW]
[ROW][C]222[/C][C]0.518866[/C][C]0.962269[/C][C]0.481134[/C][/ROW]
[ROW][C]223[/C][C]0.48598[/C][C]0.971959[/C][C]0.51402[/C][/ROW]
[ROW][C]224[/C][C]0.51224[/C][C]0.975521[/C][C]0.48776[/C][/ROW]
[ROW][C]225[/C][C]0.483486[/C][C]0.966971[/C][C]0.516514[/C][/ROW]
[ROW][C]226[/C][C]0.571332[/C][C]0.857337[/C][C]0.428668[/C][/ROW]
[ROW][C]227[/C][C]0.56347[/C][C]0.87306[/C][C]0.43653[/C][/ROW]
[ROW][C]228[/C][C]0.605791[/C][C]0.788418[/C][C]0.394209[/C][/ROW]
[ROW][C]229[/C][C]0.78715[/C][C]0.4257[/C][C]0.21285[/C][/ROW]
[ROW][C]230[/C][C]0.810662[/C][C]0.378677[/C][C]0.189338[/C][/ROW]
[ROW][C]231[/C][C]0.84434[/C][C]0.311319[/C][C]0.15566[/C][/ROW]
[ROW][C]232[/C][C]0.852726[/C][C]0.294547[/C][C]0.147274[/C][/ROW]
[ROW][C]233[/C][C]0.828678[/C][C]0.342645[/C][C]0.171322[/C][/ROW]
[ROW][C]234[/C][C]0.813828[/C][C]0.372344[/C][C]0.186172[/C][/ROW]
[ROW][C]235[/C][C]0.782242[/C][C]0.435515[/C][C]0.217758[/C][/ROW]
[ROW][C]236[/C][C]0.819456[/C][C]0.361089[/C][C]0.180544[/C][/ROW]
[ROW][C]237[/C][C]0.797206[/C][C]0.405588[/C][C]0.202794[/C][/ROW]
[ROW][C]238[/C][C]0.786239[/C][C]0.427521[/C][C]0.213761[/C][/ROW]
[ROW][C]239[/C][C]0.799715[/C][C]0.40057[/C][C]0.200285[/C][/ROW]
[ROW][C]240[/C][C]0.764258[/C][C]0.471484[/C][C]0.235742[/C][/ROW]
[ROW][C]241[/C][C]0.721766[/C][C]0.556468[/C][C]0.278234[/C][/ROW]
[ROW][C]242[/C][C]0.723608[/C][C]0.552784[/C][C]0.276392[/C][/ROW]
[ROW][C]243[/C][C]0.700456[/C][C]0.599088[/C][C]0.299544[/C][/ROW]
[ROW][C]244[/C][C]0.653134[/C][C]0.693732[/C][C]0.346866[/C][/ROW]
[ROW][C]245[/C][C]0.608703[/C][C]0.782594[/C][C]0.391297[/C][/ROW]
[ROW][C]246[/C][C]0.582389[/C][C]0.835222[/C][C]0.417611[/C][/ROW]
[ROW][C]247[/C][C]0.528378[/C][C]0.943243[/C][C]0.471622[/C][/ROW]
[ROW][C]248[/C][C]0.609802[/C][C]0.780396[/C][C]0.390198[/C][/ROW]
[ROW][C]249[/C][C]0.558301[/C][C]0.883398[/C][C]0.441699[/C][/ROW]
[ROW][C]250[/C][C]0.531219[/C][C]0.937563[/C][C]0.468781[/C][/ROW]
[ROW][C]251[/C][C]0.47991[/C][C]0.959821[/C][C]0.52009[/C][/ROW]
[ROW][C]252[/C][C]0.446468[/C][C]0.892936[/C][C]0.553532[/C][/ROW]
[ROW][C]253[/C][C]0.379058[/C][C]0.758115[/C][C]0.620942[/C][/ROW]
[ROW][C]254[/C][C]0.341114[/C][C]0.682229[/C][C]0.658886[/C][/ROW]
[ROW][C]255[/C][C]0.286255[/C][C]0.57251[/C][C]0.713745[/C][/ROW]
[ROW][C]256[/C][C]0.233908[/C][C]0.467816[/C][C]0.766092[/C][/ROW]
[ROW][C]257[/C][C]0.260822[/C][C]0.521644[/C][C]0.739178[/C][/ROW]
[ROW][C]258[/C][C]0.471829[/C][C]0.943659[/C][C]0.528171[/C][/ROW]
[ROW][C]259[/C][C]0.442634[/C][C]0.885267[/C][C]0.557366[/C][/ROW]
[ROW][C]260[/C][C]0.953272[/C][C]0.0934557[/C][C]0.0467279[/C][/ROW]
[ROW][C]261[/C][C]0.949781[/C][C]0.100439[/C][C]0.0502193[/C][/ROW]
[ROW][C]262[/C][C]0.940181[/C][C]0.119637[/C][C]0.0598185[/C][/ROW]
[ROW][C]263[/C][C]0.997409[/C][C]0.00518267[/C][C]0.00259134[/C][/ROW]
[ROW][C]264[/C][C]0.991986[/C][C]0.0160281[/C][C]0.00801404[/C][/ROW]
[ROW][C]265[/C][C]0.980062[/C][C]0.0398768[/C][C]0.0199384[/C][/ROW]
[ROW][C]266[/C][C]0.963705[/C][C]0.0725896[/C][C]0.0362948[/C][/ROW]
[ROW][C]267[/C][C]0.9191[/C][C]0.1618[/C][C]0.0808999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266372&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266372&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	0.964458	0.0710834	0.0355417
12	0.967431	0.0651371	0.0325685
13	0.947332	0.105337	0.0526683
14	0.945837	0.108327	0.0541635
15	0.93998	0.12004	0.0600201
16	0.90482	0.190361	0.0951804
17	0.863664	0.272672	0.136336
18	0.857044	0.285912	0.142956
19	0.871453	0.257095	0.128547
20	0.827225	0.345549	0.172775
21	0.814014	0.371973	0.185986
22	0.763257	0.473487	0.236743
23	0.775263	0.449473	0.224737
24	0.854687	0.290627	0.145313
25	0.812196	0.375608	0.187804
26	0.78022	0.43956	0.21978
27	0.731052	0.537897	0.268948
28	0.73541	0.52918	0.26459
29	0.680036	0.639929	0.319964
30	0.63366	0.73268	0.36634
31	0.58056	0.838879	0.41944
32	0.519795	0.960409	0.480205
33	0.47266	0.945321	0.52734
34	0.466787	0.933573	0.533213
35	0.431069	0.862139	0.568931
36	0.385635	0.771269	0.614365
37	0.350807	0.701615	0.649193
38	0.338172	0.676345	0.661828
39	0.352458	0.704916	0.647542
40	0.316624	0.633248	0.683376
41	0.372934	0.745868	0.627066
42	0.327925	0.65585	0.672075
43	0.330712	0.661425	0.669288
44	0.288314	0.576628	0.711686
45	0.318655	0.63731	0.681345
46	0.308633	0.617266	0.691367
47	0.364565	0.72913	0.635435
48	0.450882	0.901763	0.549118
49	0.532121	0.935759	0.467879
50	0.495518	0.991036	0.504482
51	0.449154	0.898308	0.550846
52	0.469527	0.939055	0.530473
53	0.437084	0.874168	0.562916
54	0.391859	0.783718	0.608141
55	0.450084	0.900169	0.549916
56	0.406235	0.812469	0.593765
57	0.723072	0.553856	0.276928
58	0.827962	0.344076	0.172038
59	0.803474	0.393053	0.196526
60	0.803857	0.392285	0.196143
61	0.798155	0.40369	0.201845
62	0.77405	0.4519	0.22595
63	0.770619	0.458763	0.229381
64	0.842337	0.315326	0.157663
65	0.833887	0.332226	0.166113
66	0.809309	0.381383	0.190691
67	0.791127	0.417745	0.208873
68	0.770991	0.458019	0.229009
69	0.793739	0.412523	0.206261
70	0.773748	0.452504	0.226252
71	0.742744	0.514512	0.257256
72	0.722875	0.554251	0.277125
73	0.705745	0.588509	0.294255
74	0.740978	0.518043	0.259022
75	0.740357	0.519286	0.259643
76	0.727581	0.544838	0.272419
77	0.711142	0.577717	0.288858
78	0.703629	0.592741	0.296371
79	0.670845	0.65831	0.329155
80	0.666228	0.667545	0.333772
81	0.632058	0.735883	0.367942
82	0.661028	0.677943	0.338972
83	0.625691	0.748618	0.374309
84	0.781959	0.436082	0.218041
85	0.756583	0.486833	0.243417
86	0.73022	0.53956	0.26978
87	0.705071	0.589858	0.294929
88	0.673053	0.653894	0.326947
89	0.666747	0.666507	0.333253
90	0.674471	0.651058	0.325529
91	0.713492	0.573017	0.286508
92	0.803616	0.392769	0.196384
93	0.77785	0.4443	0.22215
94	0.772167	0.455666	0.227833
95	0.776845	0.44631	0.223155
96	0.756038	0.487925	0.243962
97	0.796457	0.407086	0.203543
98	0.781129	0.437742	0.218871
99	0.824001	0.351999	0.175999
100	0.838118	0.323763	0.161882
101	0.820946	0.358108	0.179054
102	0.796926	0.406148	0.203074
103	0.773252	0.453496	0.226748
104	0.749343	0.501314	0.250657
105	0.810671	0.378658	0.189329
106	0.80017	0.399659	0.19983
107	0.844068	0.311863	0.155932
108	0.907644	0.184712	0.0923558
109	0.91998	0.160039	0.0800196
110	0.908981	0.182038	0.0910189
111	0.896171	0.207658	0.103829
112	0.884403	0.231194	0.115597
113	0.90355	0.192899	0.0964496
114	0.934412	0.131177	0.0655883
115	0.931893	0.136213	0.0681067
116	0.922916	0.154167	0.0770837
117	0.910612	0.178777	0.0893885
118	0.898719	0.202563	0.101281
119	0.905653	0.188695	0.0943475
120	0.901135	0.197731	0.0988654
121	0.897193	0.205613	0.102807
122	0.895315	0.209371	0.104685
123	0.880649	0.238702	0.119351
124	0.942334	0.115332	0.0576662
125	0.959592	0.080816	0.040408
126	0.954448	0.0911039	0.045552
127	0.945434	0.109132	0.0545662
128	0.939484	0.121031	0.0605157
129	0.931762	0.136475	0.0682376
130	0.920463	0.159073	0.0795366
131	0.909939	0.180121	0.0900606
132	0.904301	0.191399	0.0956994
133	0.891171	0.217659	0.108829
134	0.876213	0.247573	0.123787
135	0.86076	0.278481	0.13924
136	0.840501	0.318998	0.159499
137	0.861556	0.276887	0.138444
138	0.846515	0.306969	0.153485
139	0.826968	0.346064	0.173032
140	0.805982	0.388035	0.194018
141	0.785402	0.429196	0.214598
142	0.792596	0.414808	0.207404
143	0.768464	0.463071	0.231536
144	0.74687	0.506259	0.25313
145	0.721403	0.557195	0.278597
146	0.69838	0.603241	0.30162
147	0.669484	0.661032	0.330516
148	0.639425	0.72115	0.360575
149	0.639412	0.721175	0.360588
150	0.617015	0.765969	0.382985
151	0.861338	0.277325	0.138662
152	0.854984	0.290033	0.145016
153	0.846884	0.306232	0.153116
154	0.827859	0.344282	0.172141
155	0.817607	0.364785	0.182393
156	0.79356	0.412879	0.20644
157	0.785959	0.428083	0.214041
158	0.76471	0.47058	0.23529
159	0.775006	0.449987	0.224994
160	0.761136	0.477728	0.238864
161	0.775334	0.449332	0.224666
162	0.756447	0.487106	0.243553
163	0.731337	0.537326	0.268663
164	0.961479	0.0770423	0.0385212
165	0.95647	0.0870591	0.0435296
166	0.949708	0.100583	0.0502917
167	0.93978	0.12044	0.0602199
168	0.936129	0.127742	0.0638711
169	0.928626	0.142747	0.0713736
170	0.940672	0.118656	0.0593279
171	0.929231	0.141538	0.0707692
172	0.932921	0.134159	0.0670794
173	0.936147	0.127706	0.0638532
174	0.930264	0.139473	0.0697363
175	0.924178	0.151645	0.0758225
176	0.927618	0.144764	0.0723821
177	0.915652	0.168696	0.084348
178	0.912415	0.17517	0.0875852
179	0.905843	0.188314	0.0941569
180	0.907369	0.185262	0.0926308
181	0.896081	0.207837	0.103919
182	0.895397	0.209207	0.104603
183	0.893984	0.212032	0.106016
184	0.877069	0.245863	0.122931
185	0.911678	0.176644	0.0883218
186	0.895614	0.208771	0.104386
187	0.896863	0.206274	0.103137
188	0.899755	0.200489	0.100245
189	0.902712	0.194576	0.0972878
190	0.891317	0.217365	0.108683
191	0.874917	0.250165	0.125083
192	0.85682	0.286359	0.14318
193	0.861684	0.276632	0.138316
194	0.87421	0.25158	0.12579
195	0.853439	0.293123	0.146561
196	0.837642	0.324716	0.162358
197	0.85186	0.29628	0.14814
198	0.83	0.34	0.17
199	0.828273	0.343454	0.171727
200	0.805044	0.389912	0.194956
201	0.778683	0.442634	0.221317
202	0.761972	0.476056	0.238028
203	0.757264	0.485472	0.242736
204	0.734741	0.530518	0.265259
205	0.713835	0.572329	0.286165
206	0.717944	0.564112	0.282056
207	0.699029	0.601943	0.300971
208	0.710164	0.579673	0.289836
209	0.684376	0.631248	0.315624
210	0.664506	0.670987	0.335494
211	0.659495	0.68101	0.340505
212	0.6209	0.7582	0.3791
213	0.63096	0.73808	0.36904
214	0.611594	0.776813	0.388406
215	0.597741	0.804517	0.402259
216	0.558077	0.883847	0.441923
217	0.538301	0.923398	0.461699
218	0.512061	0.975878	0.487939
219	0.478519	0.957039	0.521481
220	0.454324	0.908648	0.545676
221	0.41456	0.82912	0.58544
222	0.518866	0.962269	0.481134
223	0.48598	0.971959	0.51402
224	0.51224	0.975521	0.48776
225	0.483486	0.966971	0.516514
226	0.571332	0.857337	0.428668
227	0.56347	0.87306	0.43653
228	0.605791	0.788418	0.394209
229	0.78715	0.4257	0.21285
230	0.810662	0.378677	0.189338
231	0.84434	0.311319	0.15566
232	0.852726	0.294547	0.147274
233	0.828678	0.342645	0.171322
234	0.813828	0.372344	0.186172
235	0.782242	0.435515	0.217758
236	0.819456	0.361089	0.180544
237	0.797206	0.405588	0.202794
238	0.786239	0.427521	0.213761
239	0.799715	0.40057	0.200285
240	0.764258	0.471484	0.235742
241	0.721766	0.556468	0.278234
242	0.723608	0.552784	0.276392
243	0.700456	0.599088	0.299544
244	0.653134	0.693732	0.346866
245	0.608703	0.782594	0.391297
246	0.582389	0.835222	0.417611
247	0.528378	0.943243	0.471622
248	0.609802	0.780396	0.390198
249	0.558301	0.883398	0.441699
250	0.531219	0.937563	0.468781
251	0.47991	0.959821	0.52009
252	0.446468	0.892936	0.553532
253	0.379058	0.758115	0.620942
254	0.341114	0.682229	0.658886
255	0.286255	0.57251	0.713745
256	0.233908	0.467816	0.766092
257	0.260822	0.521644	0.739178
258	0.471829	0.943659	0.528171
259	0.442634	0.885267	0.557366
260	0.953272	0.0934557	0.0467279
261	0.949781	0.100439	0.0502193
262	0.940181	0.119637	0.0598185
263	0.997409	0.00518267	0.00259134
264	0.991986	0.0160281	0.00801404
265	0.980062	0.0398768	0.0199384
266	0.963705	0.0725896	0.0362948
267	0.9191	0.1618	0.0808999

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	1	0.00389105	OK
5% type I error level	3	0.0116732	OK
10% type I error level	11	0.0428016	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 & 1 & 0.00389105 & OK \tabularnewline
5% type I error level & 3 & 0.0116732 & OK \tabularnewline
10% type I error level & 11 & 0.0428016 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266372&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]1[/C][C]0.00389105[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]3[/C][C]0.0116732[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]11[/C][C]0.0428016[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266372&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266372&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	1	0.00389105	OK
5% type I error level	3	0.0116732	OK
10% type I error level	11	0.0428016	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 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 = 9 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

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):

par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '9'
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