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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 07 Dec 2012 05:55:42 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/07/t1354877760eflbjtulrobprtp.htm/, Retrieved Fri, 19 Apr 2024 22:15:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197292, Retrieved Fri, 19 Apr 2024 22:15:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [Workshop 10 (2)] [2012-12-07 10:55:42] [de03d6ba395ecb425436b99f470cccc0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1418	210907	56	81	79	30
869	120982	56	55	58	28
1530	176508	54	50	60	38
2172	179321	89	125	108	30
901	123185	40	40	49	22
463	52746	25	37	0	26
3201	385534	92	63	121	25
371	33170	18	44	1	18
1192	101645	63	88	20	11
1583	149061	44	66	43	26
1439	165446	33	57	69	25
1764	237213	84	74	78	38
1495	173326	88	49	86	44
1373	133131	55	52	44	30
2187	258873	60	88	104	40
1491	180083	66	36	63	34
4041	324799	154	108	158	47
1706	230964	53	43	102	30
2152	236785	119	75	77	31
1036	135473	41	32	82	23
1882	202925	61	44	115	36
1929	215147	58	85	101	36
2242	344297	75	86	80	30
1220	153935	33	56	50	25
1289	132943	40	50	83	39
2515	174724	92	135	123	34
2147	174415	100	63	73	31
2352	225548	112	81	81	31
1638	223632	73	52	105	33
1222	124817	40	44	47	25
1812	221698	45	113	105	33
1677	210767	60	39	94	35
1579	170266	62	73	44	42
1731	260561	75	48	114	43
807	84853	31	33	38	30
2452	294424	77	59	107	33
829	101011	34	41	30	13
1940	215641	46	69	71	32
2662	325107	99	64	84	36
186	7176	17	1	0	0
1499	167542	66	59	59	28
865	106408	30	32	33	14
1793	96560	76	129	42	17
2527	265769	146	37	96	32
2747	269651	67	31	106	30
1324	149112	56	65	56	35
2702	175824	107	107	57	20
1383	152871	58	74	59	28
1179	111665	34	54	39	28
2099	116408	61	76	34	39
4308	362301	119	715	76	34
918	78800	42	57	20	26
1831	183167	66	66	91	39
3373	277965	89	106	115	39
1713	150629	44	54	85	33
1438	168809	66	32	76	28
496	24188	24	20	8	4
2253	329267	259	71	79	39
744	65029	17	21	21	18
1161	101097	64	70	30	14
2352	218946	41	112	76	29
2144	244052	68	66	101	44
4691	341570	168	190	94	21
1112	103597	43	66	27	16
2694	233328	132	165	92	28
1973	256462	105	56	123	35
1769	206161	71	61	75	28
3148	311473	112	53	128	38
2474	235800	94	127	105	23
2084	177939	82	63	55	36
1954	207176	70	38	56	32
1226	196553	57	50	41	29
1389	174184	53	52	72	25
1496	143246	103	42	67	27
2269	187559	121	76	75	36
1833	187681	62	67	114	28
1268	119016	52	50	118	23
1943	182192	52	53	77	40
893	73566	32	39	22	23
1762	194979	62	50	66	40
1403	167488	45	77	69	28
1425	143756	46	57	105	34
1857	275541	63	73	116	33
1840	243199	75	34	88	28
1502	182999	88	39	73	34
1441	135649	46	46	99	30
1420	152299	53	63	62	33
1416	120221	37	35	53	22
2970	346485	90	106	118	38
1317	145790	63	43	30	26
1644	193339	78	47	100	35
870	80953	25	31	49	8
1654	122774	45	162	24	24
1054	130585	46	57	67	29
937	112611	41	36	46	20
3004	286468	144	263	57	29
2008	241066	82	78	75	45
2547	148446	91	63	135	37
1885	204713	71	54	68	33
1626	182079	63	63	124	33
1468	140344	53	77	33	25
2445	220516	62	79	98	32
1964	243060	63	110	58	29
1381	162765	32	56	68	28
1369	182613	39	56	81	28
1659	232138	62	43	131	31
2888	265318	117	111	110	52
1290	85574	34	71	37	21
2845	310839	92	62	130	24
1982	225060	93	56	93	41
1904	232317	54	74	118	33
1391	144966	144	60	39	32
602	43287	14	43	13	19
1743	155754	61	68	74	20
1559	164709	109	53	81	31
2014	201940	38	87	109	31
2143	235454	73	46	151	32
2146	220801	75	105	51	18
874	99466	50	32	28	23
1590	92661	61	133	40	17
1590	133328	55	79	56	20
1210	61361	77	51	27	12
2072	125930	75	207	37	17
1281	100750	72	67	83	30
1401	224549	50	47	54	31
834	82316	32	34	27	10
1105	102010	53	66	28	13
1272	101523	42	76	59	22
1944	243511	71	65	133	42
391	22938	10	9	12	1
761	41566	35	42	0	9
1605	152474	65	45	106	32
530	61857	25	25	23	11
1988	99923	66	115	44	25
1386	132487	41	97	71	36
2395	317394	86	53	116	31
387	21054	16	2	4	0
1742	209641	42	52	62	24
620	22648	19	44	12	13
449	31414	19	22	18	8
800	46698	45	35	14	13
1684	131698	65	74	60	19
1050	91735	35	103	7	18
2699	244749	95	144	98	33
1606	184510	49	60	64	40
1502	79863	37	134	29	22
1204	128423	64	89	32	38
1138	97839	38	42	25	24
568	38214	34	52	16	8
1459	151101	32	98	48	35
2158	272458	65	99	100	43
1111	172494	52	52	46	43
1421	108043	62	29	45	14
2833	328107	65	125	129	41
1955	250579	83	106	130	38
2922	351067	95	95	136	45
1002	158015	29	40	59	31
1060	98866	18	140	25	13
956	85439	33	43	32	28
2186	229242	247	128	63	31
3604	351619	139	142	95	40
1035	84207	29	73	14	30
1417	120445	118	72	36	16
3261	324598	110	128	113	37
1587	131069	67	61	47	30
1424	204271	42	73	92	35
1701	165543	65	148	70	32
1249	141722	94	64	19	27
946	116048	64	45	50	20
1926	250047	81	58	41	18
3352	299775	95	97	91	31
1641	195838	67	50	111	31
2035	173260	63	37	41	21
2312	254488	83	50	120	39
1369	104389	45	105	135	41
1577	136084	30	69	27	13
2201	199476	70	46	87	32
961	92499	32	57	25	18
1900	224330	83	52	131	39
1254	135781	31	98	45	14
1335	74408	67	61	29	7
1597	81240	66	89	58	17
207	14688	10	0	4	0
1645	181633	70	48	47	30
2429	271856	103	91	109	37
151	7199	5	0	7	0
474	46660	20	7	12	5
141	17547	5	3	0	1
1639	133368	36	54	37	16
872	95227	34	70	37	32
1318	152601	48	36	46	24
1018	98146	40	37	15	17
1383	79619	43	123	42	11
1314	59194	31	247	7	24
1335	139942	42	46	54	22
1403	118612	46	72	54	12
910	72880	33	41	14	19
616	65475	18	24	16	13
1407	99643	55	45	33	17
771	71965	35	33	32	15
766	77272	59	27	21	16
473	49289	19	36	15	24
1376	135131	66	87	38	15
1232	108446	60	90	22	17
1521	89746	36	114	28	18
572	44296	25	31	10	20
1059	77648	47	45	31	16
1544	181528	54	69	32	16
1230	134019	53	51	32	18
1206	124064	40	34	43	22
1205	92630	40	60	27	8
1255	121848	39	45	37	17
613	52915	14	54	20	18
721	81872	45	25	32	16
1109	58981	36	38	0	23
740	53515	28	52	5	22
1126	60812	44	67	26	13
728	56375	30	74	10	13
689	65490	22	38	27	16
592	80949	17	30	11	16
995	76302	31	26	29	20
1613	104011	55	67	25	22
2048	98104	54	132	55	17
705	67989	21	42	23	18
301	30989	14	35	5	17
1803	135458	81	118	43	12
799	73504	35	68	23	7
861	63123	43	43	34	17
1186	61254	46	76	36	14
1451	74914	30	64	35	23
628	31774	23	48	0	17
1161	81437	38	64	37	14
1463	87186	54	56	28	15
742	50090	20	71	16	17
979	65745	53	75	26	21
675	56653	45	39	38	18
1241	158399	39	42	23	18
676	46455	20	39	22	17
1049	73624	24	93	30	17
620	38395	31	38	16	16
1081	91899	35	60	18	15
1688	139526	151	71	28	21
736	52164	52	52	32	16
617	51567	30	27	21	14
812	70551	31	59	23	15
1051	84856	29	40	29	17
1656	102538	57	79	50	15
705	86678	40	44	12	15
945	85709	44	65	21	10
554	34662	25	10	18	6
1597	150580	77	124	27	22
982	99611	35	81	41	21
222	19349	11	15	13	1
1212	99373	63	92	12	18
1143	86230	44	42	21	17
435	30837	19	10	8	4
532	31706	13	24	26	10
882	89806	42	64	27	16
608	62088	38	45	13	16
459	40151	29	22	16	9
578	27634	20	56	2	16
826	76990	27	94	42	17
509	37460	20	19	5	7
717	54157	19	35	37	15
637	49862	37	32	17	14
857	84337	26	35	38	14
830	64175	42	48	37	18
652	59382	49	49	29	12
707	119308	30	48	32	16
954	76702	49	62	35	21
1461	103425	67	96	17	19
672	70344	28	45	20	16
778	43410	19	63	7	1
1141	104838	49	71	46	16
680	62215	27	26	24	10
1090	69304	30	48	40	19
616	53117	22	29	3	12
285	19764	12	19	10	2
1145	86680	31	45	37	14
733	84105	20	45	17	17
888	77945	20	67	28	19
849	89113	39	30	19	14
1182	91005	29	36	29	11
528	40248	16	34	8	4
642	64187	27	36	10	16
947	50857	21	34	15	20
819	56613	19	37	15	12
757	62792	35	46	28	15
894	72535	14	44	17	16

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 13 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197292&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197292&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197292&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
bloggedcomputations[t] = -9.83880256155132 + 0.0183669981444719pageviews[t] + 0.000188255566367176RFC[t] -0.12300461942706logins[t] -0.125553624839805compendiumviews[t] + 1.07685696964723compendiumsreviewed[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
bloggedcomputations[t] =  -9.83880256155132 +  0.0183669981444719pageviews[t] +  0.000188255566367176RFC[t] -0.12300461942706logins[t] -0.125553624839805compendiumviews[t] +  1.07685696964723compendiumsreviewed[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197292&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]bloggedcomputations[t] =  -9.83880256155132 +  0.0183669981444719pageviews[t] +  0.000188255566367176RFC[t] -0.12300461942706logins[t] -0.125553624839805compendiumviews[t] +  1.07685696964723compendiumsreviewed[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197292&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197292&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
bloggedcomputations[t] = -9.83880256155132 + 0.0183669981444719pageviews[t] + 0.000188255566367176RFC[t] -0.12300461942706logins[t] -0.125553624839805compendiumviews[t] + 1.07685696964723compendiumsreviewed[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-9.838802561551322.840428-3.46380.0006150.000307
pageviews0.01836699814447190.0040524.53259e-064e-06
RFC0.0001882555663671763.5e-055.454300
logins-0.123004619427060.049333-2.49340.0132260.006613
compendiumviews-0.1255536248398050.026035-4.82252e-061e-06
compendiumsreviewed1.076856969647230.1562626.891400

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & -9.83880256155132 & 2.840428 & -3.4638 & 0.000615 & 0.000307 \tabularnewline
pageviews & 0.0183669981444719 & 0.004052 & 4.5325 & 9e-06 & 4e-06 \tabularnewline
RFC & 0.000188255566367176 & 3.5e-05 & 5.4543 & 0 & 0 \tabularnewline
logins & -0.12300461942706 & 0.049333 & -2.4934 & 0.013226 & 0.006613 \tabularnewline
compendiumviews & -0.125553624839805 & 0.026035 & -4.8225 & 2e-06 & 1e-06 \tabularnewline
compendiumsreviewed & 1.07685696964723 & 0.156262 & 6.8914 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197292&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]-9.83880256155132[/C][C]2.840428[/C][C]-3.4638[/C][C]0.000615[/C][C]0.000307[/C][/ROW]
[ROW][C]pageviews[/C][C]0.0183669981444719[/C][C]0.004052[/C][C]4.5325[/C][C]9e-06[/C][C]4e-06[/C][/ROW]
[ROW][C]RFC[/C][C]0.000188255566367176[/C][C]3.5e-05[/C][C]5.4543[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]logins[/C][C]-0.12300461942706[/C][C]0.049333[/C][C]-2.4934[/C][C]0.013226[/C][C]0.006613[/C][/ROW]
[ROW][C]compendiumviews[/C][C]-0.125553624839805[/C][C]0.026035[/C][C]-4.8225[/C][C]2e-06[/C][C]1e-06[/C][/ROW]
[ROW][C]compendiumsreviewed[/C][C]1.07685696964723[/C][C]0.156262[/C][C]6.8914[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197292&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197292&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-9.838802561551322.840428-3.46380.0006150.000307
pageviews0.01836699814447190.0040524.53259e-064e-06
RFC0.0001882555663671763.5e-055.454300
logins-0.123004619427060.049333-2.49340.0132260.006613
compendiumviews-0.1255536248398050.026035-4.82252e-061e-06
compendiumsreviewed1.076856969647230.1562626.891400






Multiple Linear Regression - Regression Statistics
Multiple R0.870951302133135
R-squared0.758556170687404
Adjusted R-squared0.754290378650079
F-TEST (value)177.823054675463
F-TEST (DF numerator)5
F-TEST (DF denominator)283
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation18.2908201470808
Sum Squared Residuals94678.810767758

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.870951302133135 \tabularnewline
R-squared & 0.758556170687404 \tabularnewline
Adjusted R-squared & 0.754290378650079 \tabularnewline
F-TEST (value) & 177.823054675463 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 283 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 18.2908201470808 \tabularnewline
Sum Squared Residuals & 94678.810767758 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197292&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.870951302133135[/C][/ROW]
[ROW][C]R-squared[/C][C]0.758556170687404[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.754290378650079[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]177.823054675463[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]283[/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]18.2908201470808[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]94678.810767758[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197292&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197292&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.870951302133135
R-squared0.758556170687404
Adjusted R-squared0.754290378650079
F-TEST (value)177.823054675463
F-TEST (DF numerator)5
F-TEST (DF denominator)283
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation18.2908201470808
Sum Squared Residuals94678.810767758






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17971.1576243325897.842375667411
25845.255940852246112.7440591477539
36079.4919522633712-19.4919522633712
410869.476588680202838.5234113197972
54943.64864827112285.35135172887722
6028.8725272890208-28.8725272890208
7121129.228000911689-8.2280009116893
8114.8647736974586-13.8647736974586
92024.2373129263626-4.23731292636262
104361.5972571960154-18.5972571960154
116963.44315338574635.55684661425373
127888.5144584065299-10.5144584065299
138680.65461649833755.34538350166252
144459.4534042260957-15.4534042260957
15104103.7093882469410.290611753058818
166375.4229204215431-12.4229204215431
17158143.63723133970514.3627686602947
1810285.363213295017116.6367867049829
197783.5915662118624-6.59156621186237
208250.399758769084931.6002412309151
2111588.668858380701926.331141619298
2210187.054282065480913.9457179345191
2380108.438584908038-28.4385849080382
245057.3793245924942-7.37932459249417
258369.663073603393613.3369263966064
2612377.593935977076445.4060640229236
277375.601962814011-2.60196281401105
288185.2572486284394-4.25724862843938
2910582.374463505431122.6255364945689
304752.5800441693919-5.58004416939193
3110580.991593145944724.0084068540553
329486.05383968651557.94616031348453
334479.6525014790433-35.6525014790433
34114102.05945910021811.9405408997822
353845.3067107814558-7.30671078145582
36107109.281294197709-2.28129419770942
373029.07260684099260.927393159007444
387186.5268028468282-15.5268028468282
3984118.81131050824-34.8113105082399
400-7.288251117528527.28825111752852
415963.8600681596893-4.86006815968927
423333.4486921367909-0.448692136790902
434234.03298240311277.9670175968873
449698.4623598406547-2.46235984065472
45106111.550880285558-5.55088028555803
465665.191016629022-9.19101662902199
475767.830080382144-10.830080382144
485958.06833154357710.931668456422896
493952.0273884174245-13.0273884174245
503475.5800450567313-41.5800450567313
517669.69615089095286.30384910904721
522037.5321709438298-17.5321709438298
539183.86595606038197.1340439396181
54115122.182867139218-7.18286713921848
558573.324793968468711.6752060315313
567666.36814894613849.63185105386158
5782.668998672939355.33100132706065
587994.7533078499718-15.7533078499718
592130.724036084981-9.72403608498098
603028.93230347014591.06769652985412
617686.7018370492762-10.7018370492761
62101106.215042247249-5.2150422472491
6394118.717271117485-24.7172711174852
642733.7419849236066-6.74198492360663
659276.766222516158915.2337774838411
6612392.423189745932930.5768102540671
677575.2232690294157-0.22326902941572
68128127.1067389745840.893261025416324
6910577.251779118339527.7482208816605
705582.7066225447105-27.7066225447105
715686.1304089553372-30.1304089553372
724167.6212410701756-26.6212410701756
737262.33745635309699.66254364690312
746755.737493658627211.2625063413728
757581.4861584693172-6.48615846931719
7611473.273513870001240.7264861299988
7711847.949764422083670.0502355779164
787790.1706294398983-13.1706294398983
792236.3471068882976-14.3471068882976
806688.4000413831348-22.4000413831348
816962.40980229808796.59019770191208
8210567.195404851492937.8045951485071
8311694.762414366258921.2375856337412
848886.39786495774721.60213504225283
857373.0911481307442-0.0911481307442444
869963.036750939914735.9632490600853
876266.0206261095698-4.02062610956982
885353.5464447992937-0.546444799293674
89118126.480376705401-8.48037670540091
903056.6464973342002-26.6464973342002
9110078.948298588695221.0517014113048
924923.027916589728525.9720834102715
932443.6227734478362-19.6227734478361
946752.517449627035614.4825503729644
954640.54474178619495.45525821380506
965779.7604390399185-22.7604390399185
9775101.003148178019-26.0031481780193
9813585.628136661537549.3718633384625
996883.3444069761895-15.3444069761896
10012474.180432299474949.8195677005251
1013354.2790402196498-21.2790402196498
1029893.49627263659554.50372736340452
1035881.6600421188834-23.6600421188834
1046865.35228347314512.64771652685495
1058168.007343640677712.9926563593223
10613184.690791811945646.3092081880543
107110120.821248028561-10.8212480285612
1083739.4819388195677-2.48193881956766
109130107.67629669765422.3237033023463
1109394.6140886851791-1.61408868517913
11111888.46999262839829.530007371602
1123952.2138886322194-13.2138886322194
1131322.7065609059635-9.70656090596354
1147456.992643807003417.0073561929966
1158163.123454051456317.8765459485437
11610982.953885933375226.0461140666248
11715193.551819653373757.4481803466263
1185168.1187411543652-17.1187411543652
1192839.538745316654-11.538745316654
1204030.9133281185669.08667188143402
1215649.31761160287346.68238839712659
1222720.9845080741696.01549192583104
1233735.01626275154661.9837372484534
1248347.693353999411735.3066460005883
1255479.4972757312769-25.4972757312769
1262723.53931772227163.46068227772836
1272828.8540372495583-0.854037249558343
1285941.61887277098917.381127229011
129133100.04262218421432.9573778157857
130120.37772804608584611.6222719539142
131012.0768127016159-12.0768127016159
13210669.158518334755936.8414816652441
1332317.1721015832415.82789841675897
1344449.8503032101832-5.8503032101832
1357162.10423198930438.89576801069567
136116110.0511718978295.94882810217061
1374-0.9864227458587474.98642274585875
1386275.7721781588268-13.7721781588268
1391211.95004169845340.0499583015465648
140187.8374282087629810.162571791237
1411417.7155102540436-3.71551025404363
1426049.058117815556510.9418821844435
143728.8624102860401-21.8624102860401
1449891.5802062190346.41979378096596
1456483.9074659524529-19.9074659524529
1462935.0985796331311-6.09857963313111
1473258.3254043964848-26.3254043964848
1482545.3787171746891-20.3787171746891
149165.6915608026518810.3084391973481
1504866.8538429465659-18.8538429465659
151100106.968655108418-6.9686551084181
1524676.4197090348503-30.4197090348503
1534540.40905400898114.59094599101892
154129124.4245046835744.5754953164258
15513090.64406757674139.355932423259
156136134.7654133631941.2345866368062
1575963.1054200008059-4.10542000080586
1582522.44984027420032.55015972579974
1593244.4984518403267-12.4984518403267
1606360.39709900849352.60290099150654
16195130.698114699861-35.6981146998607
1621444.5966375077841-30.5966375077841
1633632.53698093375643.46301906624361
164113121.4056944797-8.40569447969971
1654760.3897207944806-13.3897207944806
1669278.129340901976613.8706590980234
1677060.45003879497799.54996120502206
1681949.2588054621669-30.2588054621669
1695037.397990280718612.6020097192814
1704174.7467165074642-33.7467165074642
17191117.680113230471-26.6801132304707
17211176.032610315202734.9673896847973
1734170.37441931084-29.37441931084
174120106.04483688392313.9551631160769
17513560.390225488872974.6097745111271
1762746.3903259144472-19.3903259144472
1778788.213060637276-1.21306063727603
1782533.5160553047988-8.51605530479882
17913192.549115028219738.4508849717802
1804537.71354130703937.28645869296066
1812920.32677831425698.67322168574309
1825833.801166677913924.1988333220861
1834-4.501782381115158.50178238111515
1844772.2371444092861-25.2371444092861
185109101.7018933972247.29810660277626
1867-6.3251571165940613.3251571165941
187129.696476371437072.30352362856293
1880-3.860562402143433.86056240214343
1893751.3936252461276-14.3936252461276
1903745.5927448682801-8.59274486828006
1914658.5173037208616-12.5173037208616
1921536.0762319540415-21.0762319540415
1934221.664607986301420.3353920136986
194716.4587117296861-9.45871172968612
1955453.77519300354540.224806996454626
1965436.483675226742217.5163247732578
1971431.8486627905302-17.8486627905302
1981622.5730719629057-6.57307196290574
1993340.6533145249684-7.65331452496842
2003225.5743880864986.42561191350197
2012125.3596932389229-4.35969323892289
2021527.1152651796419-12.1152651796419
2033837.98473412546420.0152658745357799
2042232.8313673854896-10.8313673854896
2052835.6347315979171-7.63473159791712
2061023.5759504821211-13.5759504821211
2073130.02809797421540.971902025784561
2083254.6177609763618-22.6177609763618
2093244.4433736622975-12.4433736622975
2104350.1693810970623-7.16938109706226
2112725.89299680483591.1070031951641
2123744.0098195690248-7.0098195690248
2132022.2631756356508-2.26317563565083
2143227.37232584936914.62767415063089
215037.2022061991699-37.2022061991699
216527.5452081961087-22.5452081961087
2172622.46547933740113.53452066259892
2181015.1633134260303-5.16331342603033
2192724.89748834442392.10251165557614
2201127.645584420734-16.645584420734
2212937.2602387620172-8.26023876201718
2222547.8813215583819-22.8813215583819
2235541.336674277299913.6633257227001
2242327.4363150344493-4.43631503444928
225513.713642568718-8.71364256871797
2264336.92119933297426.07880066702576
2272313.36915672461149.63084327538865
2283425.47700293716198.52299706283814
2293623.351573293638512.6484267063615
2303543.9568289742349-8.95682897423487
231017.1281928837975-17.1281928837975
2323729.18264088950967.8173591104904
2332835.9249676377177-7.9249676377177
2341620.1514001128142-4.15140011281416
2352627.1975805026688-1.19758050266883
2363822.175789998046815.8242100019532
2372352.0871286454555-29.0871286454555
2382222.2725852464081-0.27258524640808
2393026.96627681786823.03372318213181
2401617.4223393268931-1.42233932689314
2411831.6308961005729-13.6308961005729
2422842.5572279247433-14.5572279247433
2433217.80415424923614.195845750764
2442119.19732120601861.80267879398138
2452323.2888658714515-0.288865871451511
2462935.1568163549676-6.1568163549676
2475039.10315050487310.896849495127
2481225.13585738655-13.13585738655
2492120.84858784983320.151412150166822
250188.992318935713969.00768106428604
2512746.4916648149591-19.4916648149591
2524135.08890590834135.91109409165873
25313-4.2782702364875817.2782702364876
2541231.2127205306372-19.2127205306372
2552135.009066791362-14.009066791362
25684.670882392435263.32911760756474
2572612.057494086310613.9425059136894
2582727.2954547037151-0.295454703715052
2591319.9223667732289-6.92236677322892
260169.512697848934346.48730215106566
261213.7181928217293-11.7181928217293
2624223.009536984921918.9904630150781
26359.25444053713236-4.25444053713236
2643722.947081721983214.0529182780168
2651717.7548849680636-0.75488496806358
2663829.2621251495348.73787485046599
2673725.677764315376811.3222356846232
2682914.058401937350314.9415980626497
2693233.1200591779585-1.12005917795849
2703530.92533739036794.07466260963213
2711736.6315386161103-19.6315386161103
2722023.8821388046731-3.88213880467312
27373.452786966472293.54721303352771
2744633.142457186896612.8575428131034
2752418.54612696433015.45387303566989
2764033.97165903560866.02834096439136
277318.0499661021857-15.0499661021857
27810-2.5913854424825212.5913854424825
2793733.12234406160693.87765593839314
2801729.6540044653283-12.6540044653283
2812830.7327690817184-2.7327690817184
2821929.0430058209951-10.0430058209951
2832932.761549270961-3.76154927096104
28485.506413217078512.49358678292149
2851023.4250265812016-13.4250265812016
2861531.8140771604219-16.8140771604219
2871521.8011930450959-6.80119304509586
2882821.95818467927196.04181532072814
2891730.219698635475-13.219698635475

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 79 & 71.157624332589 & 7.842375667411 \tabularnewline
2 & 58 & 45.2559408522461 & 12.7440591477539 \tabularnewline
3 & 60 & 79.4919522633712 & -19.4919522633712 \tabularnewline
4 & 108 & 69.4765886802028 & 38.5234113197972 \tabularnewline
5 & 49 & 43.6486482711228 & 5.35135172887722 \tabularnewline
6 & 0 & 28.8725272890208 & -28.8725272890208 \tabularnewline
7 & 121 & 129.228000911689 & -8.2280009116893 \tabularnewline
8 & 1 & 14.8647736974586 & -13.8647736974586 \tabularnewline
9 & 20 & 24.2373129263626 & -4.23731292636262 \tabularnewline
10 & 43 & 61.5972571960154 & -18.5972571960154 \tabularnewline
11 & 69 & 63.4431533857463 & 5.55684661425373 \tabularnewline
12 & 78 & 88.5144584065299 & -10.5144584065299 \tabularnewline
13 & 86 & 80.6546164983375 & 5.34538350166252 \tabularnewline
14 & 44 & 59.4534042260957 & -15.4534042260957 \tabularnewline
15 & 104 & 103.709388246941 & 0.290611753058818 \tabularnewline
16 & 63 & 75.4229204215431 & -12.4229204215431 \tabularnewline
17 & 158 & 143.637231339705 & 14.3627686602947 \tabularnewline
18 & 102 & 85.3632132950171 & 16.6367867049829 \tabularnewline
19 & 77 & 83.5915662118624 & -6.59156621186237 \tabularnewline
20 & 82 & 50.3997587690849 & 31.6002412309151 \tabularnewline
21 & 115 & 88.6688583807019 & 26.331141619298 \tabularnewline
22 & 101 & 87.0542820654809 & 13.9457179345191 \tabularnewline
23 & 80 & 108.438584908038 & -28.4385849080382 \tabularnewline
24 & 50 & 57.3793245924942 & -7.37932459249417 \tabularnewline
25 & 83 & 69.6630736033936 & 13.3369263966064 \tabularnewline
26 & 123 & 77.5939359770764 & 45.4060640229236 \tabularnewline
27 & 73 & 75.601962814011 & -2.60196281401105 \tabularnewline
28 & 81 & 85.2572486284394 & -4.25724862843938 \tabularnewline
29 & 105 & 82.3744635054311 & 22.6255364945689 \tabularnewline
30 & 47 & 52.5800441693919 & -5.58004416939193 \tabularnewline
31 & 105 & 80.9915931459447 & 24.0084068540553 \tabularnewline
32 & 94 & 86.0538396865155 & 7.94616031348453 \tabularnewline
33 & 44 & 79.6525014790433 & -35.6525014790433 \tabularnewline
34 & 114 & 102.059459100218 & 11.9405408997822 \tabularnewline
35 & 38 & 45.3067107814558 & -7.30671078145582 \tabularnewline
36 & 107 & 109.281294197709 & -2.28129419770942 \tabularnewline
37 & 30 & 29.0726068409926 & 0.927393159007444 \tabularnewline
38 & 71 & 86.5268028468282 & -15.5268028468282 \tabularnewline
39 & 84 & 118.81131050824 & -34.8113105082399 \tabularnewline
40 & 0 & -7.28825111752852 & 7.28825111752852 \tabularnewline
41 & 59 & 63.8600681596893 & -4.86006815968927 \tabularnewline
42 & 33 & 33.4486921367909 & -0.448692136790902 \tabularnewline
43 & 42 & 34.0329824031127 & 7.9670175968873 \tabularnewline
44 & 96 & 98.4623598406547 & -2.46235984065472 \tabularnewline
45 & 106 & 111.550880285558 & -5.55088028555803 \tabularnewline
46 & 56 & 65.191016629022 & -9.19101662902199 \tabularnewline
47 & 57 & 67.830080382144 & -10.830080382144 \tabularnewline
48 & 59 & 58.0683315435771 & 0.931668456422896 \tabularnewline
49 & 39 & 52.0273884174245 & -13.0273884174245 \tabularnewline
50 & 34 & 75.5800450567313 & -41.5800450567313 \tabularnewline
51 & 76 & 69.6961508909528 & 6.30384910904721 \tabularnewline
52 & 20 & 37.5321709438298 & -17.5321709438298 \tabularnewline
53 & 91 & 83.8659560603819 & 7.1340439396181 \tabularnewline
54 & 115 & 122.182867139218 & -7.18286713921848 \tabularnewline
55 & 85 & 73.3247939684687 & 11.6752060315313 \tabularnewline
56 & 76 & 66.3681489461384 & 9.63185105386158 \tabularnewline
57 & 8 & 2.66899867293935 & 5.33100132706065 \tabularnewline
58 & 79 & 94.7533078499718 & -15.7533078499718 \tabularnewline
59 & 21 & 30.724036084981 & -9.72403608498098 \tabularnewline
60 & 30 & 28.9323034701459 & 1.06769652985412 \tabularnewline
61 & 76 & 86.7018370492762 & -10.7018370492761 \tabularnewline
62 & 101 & 106.215042247249 & -5.2150422472491 \tabularnewline
63 & 94 & 118.717271117485 & -24.7172711174852 \tabularnewline
64 & 27 & 33.7419849236066 & -6.74198492360663 \tabularnewline
65 & 92 & 76.7662225161589 & 15.2337774838411 \tabularnewline
66 & 123 & 92.4231897459329 & 30.5768102540671 \tabularnewline
67 & 75 & 75.2232690294157 & -0.22326902941572 \tabularnewline
68 & 128 & 127.106738974584 & 0.893261025416324 \tabularnewline
69 & 105 & 77.2517791183395 & 27.7482208816605 \tabularnewline
70 & 55 & 82.7066225447105 & -27.7066225447105 \tabularnewline
71 & 56 & 86.1304089553372 & -30.1304089553372 \tabularnewline
72 & 41 & 67.6212410701756 & -26.6212410701756 \tabularnewline
73 & 72 & 62.3374563530969 & 9.66254364690312 \tabularnewline
74 & 67 & 55.7374936586272 & 11.2625063413728 \tabularnewline
75 & 75 & 81.4861584693172 & -6.48615846931719 \tabularnewline
76 & 114 & 73.2735138700012 & 40.7264861299988 \tabularnewline
77 & 118 & 47.9497644220836 & 70.0502355779164 \tabularnewline
78 & 77 & 90.1706294398983 & -13.1706294398983 \tabularnewline
79 & 22 & 36.3471068882976 & -14.3471068882976 \tabularnewline
80 & 66 & 88.4000413831348 & -22.4000413831348 \tabularnewline
81 & 69 & 62.4098022980879 & 6.59019770191208 \tabularnewline
82 & 105 & 67.1954048514929 & 37.8045951485071 \tabularnewline
83 & 116 & 94.7624143662589 & 21.2375856337412 \tabularnewline
84 & 88 & 86.3978649577472 & 1.60213504225283 \tabularnewline
85 & 73 & 73.0911481307442 & -0.0911481307442444 \tabularnewline
86 & 99 & 63.0367509399147 & 35.9632490600853 \tabularnewline
87 & 62 & 66.0206261095698 & -4.02062610956982 \tabularnewline
88 & 53 & 53.5464447992937 & -0.546444799293674 \tabularnewline
89 & 118 & 126.480376705401 & -8.48037670540091 \tabularnewline
90 & 30 & 56.6464973342002 & -26.6464973342002 \tabularnewline
91 & 100 & 78.9482985886952 & 21.0517014113048 \tabularnewline
92 & 49 & 23.0279165897285 & 25.9720834102715 \tabularnewline
93 & 24 & 43.6227734478362 & -19.6227734478361 \tabularnewline
94 & 67 & 52.5174496270356 & 14.4825503729644 \tabularnewline
95 & 46 & 40.5447417861949 & 5.45525821380506 \tabularnewline
96 & 57 & 79.7604390399185 & -22.7604390399185 \tabularnewline
97 & 75 & 101.003148178019 & -26.0031481780193 \tabularnewline
98 & 135 & 85.6281366615375 & 49.3718633384625 \tabularnewline
99 & 68 & 83.3444069761895 & -15.3444069761896 \tabularnewline
100 & 124 & 74.1804322994749 & 49.8195677005251 \tabularnewline
101 & 33 & 54.2790402196498 & -21.2790402196498 \tabularnewline
102 & 98 & 93.4962726365955 & 4.50372736340452 \tabularnewline
103 & 58 & 81.6600421188834 & -23.6600421188834 \tabularnewline
104 & 68 & 65.3522834731451 & 2.64771652685495 \tabularnewline
105 & 81 & 68.0073436406777 & 12.9926563593223 \tabularnewline
106 & 131 & 84.6907918119456 & 46.3092081880543 \tabularnewline
107 & 110 & 120.821248028561 & -10.8212480285612 \tabularnewline
108 & 37 & 39.4819388195677 & -2.48193881956766 \tabularnewline
109 & 130 & 107.676296697654 & 22.3237033023463 \tabularnewline
110 & 93 & 94.6140886851791 & -1.61408868517913 \tabularnewline
111 & 118 & 88.469992628398 & 29.530007371602 \tabularnewline
112 & 39 & 52.2138886322194 & -13.2138886322194 \tabularnewline
113 & 13 & 22.7065609059635 & -9.70656090596354 \tabularnewline
114 & 74 & 56.9926438070034 & 17.0073561929966 \tabularnewline
115 & 81 & 63.1234540514563 & 17.8765459485437 \tabularnewline
116 & 109 & 82.9538859333752 & 26.0461140666248 \tabularnewline
117 & 151 & 93.5518196533737 & 57.4481803466263 \tabularnewline
118 & 51 & 68.1187411543652 & -17.1187411543652 \tabularnewline
119 & 28 & 39.538745316654 & -11.538745316654 \tabularnewline
120 & 40 & 30.913328118566 & 9.08667188143402 \tabularnewline
121 & 56 & 49.3176116028734 & 6.68238839712659 \tabularnewline
122 & 27 & 20.984508074169 & 6.01549192583104 \tabularnewline
123 & 37 & 35.0162627515466 & 1.9837372484534 \tabularnewline
124 & 83 & 47.6933539994117 & 35.3066460005883 \tabularnewline
125 & 54 & 79.4972757312769 & -25.4972757312769 \tabularnewline
126 & 27 & 23.5393177222716 & 3.46068227772836 \tabularnewline
127 & 28 & 28.8540372495583 & -0.854037249558343 \tabularnewline
128 & 59 & 41.618872770989 & 17.381127229011 \tabularnewline
129 & 133 & 100.042622184214 & 32.9573778157857 \tabularnewline
130 & 12 & 0.377728046085846 & 11.6222719539142 \tabularnewline
131 & 0 & 12.0768127016159 & -12.0768127016159 \tabularnewline
132 & 106 & 69.1585183347559 & 36.8414816652441 \tabularnewline
133 & 23 & 17.172101583241 & 5.82789841675897 \tabularnewline
134 & 44 & 49.8503032101832 & -5.8503032101832 \tabularnewline
135 & 71 & 62.1042319893043 & 8.89576801069567 \tabularnewline
136 & 116 & 110.051171897829 & 5.94882810217061 \tabularnewline
137 & 4 & -0.986422745858747 & 4.98642274585875 \tabularnewline
138 & 62 & 75.7721781588268 & -13.7721781588268 \tabularnewline
139 & 12 & 11.9500416984534 & 0.0499583015465648 \tabularnewline
140 & 18 & 7.83742820876298 & 10.162571791237 \tabularnewline
141 & 14 & 17.7155102540436 & -3.71551025404363 \tabularnewline
142 & 60 & 49.0581178155565 & 10.9418821844435 \tabularnewline
143 & 7 & 28.8624102860401 & -21.8624102860401 \tabularnewline
144 & 98 & 91.580206219034 & 6.41979378096596 \tabularnewline
145 & 64 & 83.9074659524529 & -19.9074659524529 \tabularnewline
146 & 29 & 35.0985796331311 & -6.09857963313111 \tabularnewline
147 & 32 & 58.3254043964848 & -26.3254043964848 \tabularnewline
148 & 25 & 45.3787171746891 & -20.3787171746891 \tabularnewline
149 & 16 & 5.69156080265188 & 10.3084391973481 \tabularnewline
150 & 48 & 66.8538429465659 & -18.8538429465659 \tabularnewline
151 & 100 & 106.968655108418 & -6.9686551084181 \tabularnewline
152 & 46 & 76.4197090348503 & -30.4197090348503 \tabularnewline
153 & 45 & 40.4090540089811 & 4.59094599101892 \tabularnewline
154 & 129 & 124.424504683574 & 4.5754953164258 \tabularnewline
155 & 130 & 90.644067576741 & 39.355932423259 \tabularnewline
156 & 136 & 134.765413363194 & 1.2345866368062 \tabularnewline
157 & 59 & 63.1054200008059 & -4.10542000080586 \tabularnewline
158 & 25 & 22.4498402742003 & 2.55015972579974 \tabularnewline
159 & 32 & 44.4984518403267 & -12.4984518403267 \tabularnewline
160 & 63 & 60.3970990084935 & 2.60290099150654 \tabularnewline
161 & 95 & 130.698114699861 & -35.6981146998607 \tabularnewline
162 & 14 & 44.5966375077841 & -30.5966375077841 \tabularnewline
163 & 36 & 32.5369809337564 & 3.46301906624361 \tabularnewline
164 & 113 & 121.4056944797 & -8.40569447969971 \tabularnewline
165 & 47 & 60.3897207944806 & -13.3897207944806 \tabularnewline
166 & 92 & 78.1293409019766 & 13.8706590980234 \tabularnewline
167 & 70 & 60.4500387949779 & 9.54996120502206 \tabularnewline
168 & 19 & 49.2588054621669 & -30.2588054621669 \tabularnewline
169 & 50 & 37.3979902807186 & 12.6020097192814 \tabularnewline
170 & 41 & 74.7467165074642 & -33.7467165074642 \tabularnewline
171 & 91 & 117.680113230471 & -26.6801132304707 \tabularnewline
172 & 111 & 76.0326103152027 & 34.9673896847973 \tabularnewline
173 & 41 & 70.37441931084 & -29.37441931084 \tabularnewline
174 & 120 & 106.044836883923 & 13.9551631160769 \tabularnewline
175 & 135 & 60.3902254888729 & 74.6097745111271 \tabularnewline
176 & 27 & 46.3903259144472 & -19.3903259144472 \tabularnewline
177 & 87 & 88.213060637276 & -1.21306063727603 \tabularnewline
178 & 25 & 33.5160553047988 & -8.51605530479882 \tabularnewline
179 & 131 & 92.5491150282197 & 38.4508849717802 \tabularnewline
180 & 45 & 37.7135413070393 & 7.28645869296066 \tabularnewline
181 & 29 & 20.3267783142569 & 8.67322168574309 \tabularnewline
182 & 58 & 33.8011666779139 & 24.1988333220861 \tabularnewline
183 & 4 & -4.50178238111515 & 8.50178238111515 \tabularnewline
184 & 47 & 72.2371444092861 & -25.2371444092861 \tabularnewline
185 & 109 & 101.701893397224 & 7.29810660277626 \tabularnewline
186 & 7 & -6.32515711659406 & 13.3251571165941 \tabularnewline
187 & 12 & 9.69647637143707 & 2.30352362856293 \tabularnewline
188 & 0 & -3.86056240214343 & 3.86056240214343 \tabularnewline
189 & 37 & 51.3936252461276 & -14.3936252461276 \tabularnewline
190 & 37 & 45.5927448682801 & -8.59274486828006 \tabularnewline
191 & 46 & 58.5173037208616 & -12.5173037208616 \tabularnewline
192 & 15 & 36.0762319540415 & -21.0762319540415 \tabularnewline
193 & 42 & 21.6646079863014 & 20.3353920136986 \tabularnewline
194 & 7 & 16.4587117296861 & -9.45871172968612 \tabularnewline
195 & 54 & 53.7751930035454 & 0.224806996454626 \tabularnewline
196 & 54 & 36.4836752267422 & 17.5163247732578 \tabularnewline
197 & 14 & 31.8486627905302 & -17.8486627905302 \tabularnewline
198 & 16 & 22.5730719629057 & -6.57307196290574 \tabularnewline
199 & 33 & 40.6533145249684 & -7.65331452496842 \tabularnewline
200 & 32 & 25.574388086498 & 6.42561191350197 \tabularnewline
201 & 21 & 25.3596932389229 & -4.35969323892289 \tabularnewline
202 & 15 & 27.1152651796419 & -12.1152651796419 \tabularnewline
203 & 38 & 37.9847341254642 & 0.0152658745357799 \tabularnewline
204 & 22 & 32.8313673854896 & -10.8313673854896 \tabularnewline
205 & 28 & 35.6347315979171 & -7.63473159791712 \tabularnewline
206 & 10 & 23.5759504821211 & -13.5759504821211 \tabularnewline
207 & 31 & 30.0280979742154 & 0.971902025784561 \tabularnewline
208 & 32 & 54.6177609763618 & -22.6177609763618 \tabularnewline
209 & 32 & 44.4433736622975 & -12.4433736622975 \tabularnewline
210 & 43 & 50.1693810970623 & -7.16938109706226 \tabularnewline
211 & 27 & 25.8929968048359 & 1.1070031951641 \tabularnewline
212 & 37 & 44.0098195690248 & -7.0098195690248 \tabularnewline
213 & 20 & 22.2631756356508 & -2.26317563565083 \tabularnewline
214 & 32 & 27.3723258493691 & 4.62767415063089 \tabularnewline
215 & 0 & 37.2022061991699 & -37.2022061991699 \tabularnewline
216 & 5 & 27.5452081961087 & -22.5452081961087 \tabularnewline
217 & 26 & 22.4654793374011 & 3.53452066259892 \tabularnewline
218 & 10 & 15.1633134260303 & -5.16331342603033 \tabularnewline
219 & 27 & 24.8974883444239 & 2.10251165557614 \tabularnewline
220 & 11 & 27.645584420734 & -16.645584420734 \tabularnewline
221 & 29 & 37.2602387620172 & -8.26023876201718 \tabularnewline
222 & 25 & 47.8813215583819 & -22.8813215583819 \tabularnewline
223 & 55 & 41.3366742772999 & 13.6633257227001 \tabularnewline
224 & 23 & 27.4363150344493 & -4.43631503444928 \tabularnewline
225 & 5 & 13.713642568718 & -8.71364256871797 \tabularnewline
226 & 43 & 36.9211993329742 & 6.07880066702576 \tabularnewline
227 & 23 & 13.3691567246114 & 9.63084327538865 \tabularnewline
228 & 34 & 25.4770029371619 & 8.52299706283814 \tabularnewline
229 & 36 & 23.3515732936385 & 12.6484267063615 \tabularnewline
230 & 35 & 43.9568289742349 & -8.95682897423487 \tabularnewline
231 & 0 & 17.1281928837975 & -17.1281928837975 \tabularnewline
232 & 37 & 29.1826408895096 & 7.8173591104904 \tabularnewline
233 & 28 & 35.9249676377177 & -7.9249676377177 \tabularnewline
234 & 16 & 20.1514001128142 & -4.15140011281416 \tabularnewline
235 & 26 & 27.1975805026688 & -1.19758050266883 \tabularnewline
236 & 38 & 22.1757899980468 & 15.8242100019532 \tabularnewline
237 & 23 & 52.0871286454555 & -29.0871286454555 \tabularnewline
238 & 22 & 22.2725852464081 & -0.27258524640808 \tabularnewline
239 & 30 & 26.9662768178682 & 3.03372318213181 \tabularnewline
240 & 16 & 17.4223393268931 & -1.42233932689314 \tabularnewline
241 & 18 & 31.6308961005729 & -13.6308961005729 \tabularnewline
242 & 28 & 42.5572279247433 & -14.5572279247433 \tabularnewline
243 & 32 & 17.804154249236 & 14.195845750764 \tabularnewline
244 & 21 & 19.1973212060186 & 1.80267879398138 \tabularnewline
245 & 23 & 23.2888658714515 & -0.288865871451511 \tabularnewline
246 & 29 & 35.1568163549676 & -6.1568163549676 \tabularnewline
247 & 50 & 39.103150504873 & 10.896849495127 \tabularnewline
248 & 12 & 25.13585738655 & -13.13585738655 \tabularnewline
249 & 21 & 20.8485878498332 & 0.151412150166822 \tabularnewline
250 & 18 & 8.99231893571396 & 9.00768106428604 \tabularnewline
251 & 27 & 46.4916648149591 & -19.4916648149591 \tabularnewline
252 & 41 & 35.0889059083413 & 5.91109409165873 \tabularnewline
253 & 13 & -4.27827023648758 & 17.2782702364876 \tabularnewline
254 & 12 & 31.2127205306372 & -19.2127205306372 \tabularnewline
255 & 21 & 35.009066791362 & -14.009066791362 \tabularnewline
256 & 8 & 4.67088239243526 & 3.32911760756474 \tabularnewline
257 & 26 & 12.0574940863106 & 13.9425059136894 \tabularnewline
258 & 27 & 27.2954547037151 & -0.295454703715052 \tabularnewline
259 & 13 & 19.9223667732289 & -6.92236677322892 \tabularnewline
260 & 16 & 9.51269784893434 & 6.48730215106566 \tabularnewline
261 & 2 & 13.7181928217293 & -11.7181928217293 \tabularnewline
262 & 42 & 23.0095369849219 & 18.9904630150781 \tabularnewline
263 & 5 & 9.25444053713236 & -4.25444053713236 \tabularnewline
264 & 37 & 22.9470817219832 & 14.0529182780168 \tabularnewline
265 & 17 & 17.7548849680636 & -0.75488496806358 \tabularnewline
266 & 38 & 29.262125149534 & 8.73787485046599 \tabularnewline
267 & 37 & 25.6777643153768 & 11.3222356846232 \tabularnewline
268 & 29 & 14.0584019373503 & 14.9415980626497 \tabularnewline
269 & 32 & 33.1200591779585 & -1.12005917795849 \tabularnewline
270 & 35 & 30.9253373903679 & 4.07466260963213 \tabularnewline
271 & 17 & 36.6315386161103 & -19.6315386161103 \tabularnewline
272 & 20 & 23.8821388046731 & -3.88213880467312 \tabularnewline
273 & 7 & 3.45278696647229 & 3.54721303352771 \tabularnewline
274 & 46 & 33.1424571868966 & 12.8575428131034 \tabularnewline
275 & 24 & 18.5461269643301 & 5.45387303566989 \tabularnewline
276 & 40 & 33.9716590356086 & 6.02834096439136 \tabularnewline
277 & 3 & 18.0499661021857 & -15.0499661021857 \tabularnewline
278 & 10 & -2.59138544248252 & 12.5913854424825 \tabularnewline
279 & 37 & 33.1223440616069 & 3.87765593839314 \tabularnewline
280 & 17 & 29.6540044653283 & -12.6540044653283 \tabularnewline
281 & 28 & 30.7327690817184 & -2.7327690817184 \tabularnewline
282 & 19 & 29.0430058209951 & -10.0430058209951 \tabularnewline
283 & 29 & 32.761549270961 & -3.76154927096104 \tabularnewline
284 & 8 & 5.50641321707851 & 2.49358678292149 \tabularnewline
285 & 10 & 23.4250265812016 & -13.4250265812016 \tabularnewline
286 & 15 & 31.8140771604219 & -16.8140771604219 \tabularnewline
287 & 15 & 21.8011930450959 & -6.80119304509586 \tabularnewline
288 & 28 & 21.9581846792719 & 6.04181532072814 \tabularnewline
289 & 17 & 30.219698635475 & -13.219698635475 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197292&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]79[/C][C]71.157624332589[/C][C]7.842375667411[/C][/ROW]
[ROW][C]2[/C][C]58[/C][C]45.2559408522461[/C][C]12.7440591477539[/C][/ROW]
[ROW][C]3[/C][C]60[/C][C]79.4919522633712[/C][C]-19.4919522633712[/C][/ROW]
[ROW][C]4[/C][C]108[/C][C]69.4765886802028[/C][C]38.5234113197972[/C][/ROW]
[ROW][C]5[/C][C]49[/C][C]43.6486482711228[/C][C]5.35135172887722[/C][/ROW]
[ROW][C]6[/C][C]0[/C][C]28.8725272890208[/C][C]-28.8725272890208[/C][/ROW]
[ROW][C]7[/C][C]121[/C][C]129.228000911689[/C][C]-8.2280009116893[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]14.8647736974586[/C][C]-13.8647736974586[/C][/ROW]
[ROW][C]9[/C][C]20[/C][C]24.2373129263626[/C][C]-4.23731292636262[/C][/ROW]
[ROW][C]10[/C][C]43[/C][C]61.5972571960154[/C][C]-18.5972571960154[/C][/ROW]
[ROW][C]11[/C][C]69[/C][C]63.4431533857463[/C][C]5.55684661425373[/C][/ROW]
[ROW][C]12[/C][C]78[/C][C]88.5144584065299[/C][C]-10.5144584065299[/C][/ROW]
[ROW][C]13[/C][C]86[/C][C]80.6546164983375[/C][C]5.34538350166252[/C][/ROW]
[ROW][C]14[/C][C]44[/C][C]59.4534042260957[/C][C]-15.4534042260957[/C][/ROW]
[ROW][C]15[/C][C]104[/C][C]103.709388246941[/C][C]0.290611753058818[/C][/ROW]
[ROW][C]16[/C][C]63[/C][C]75.4229204215431[/C][C]-12.4229204215431[/C][/ROW]
[ROW][C]17[/C][C]158[/C][C]143.637231339705[/C][C]14.3627686602947[/C][/ROW]
[ROW][C]18[/C][C]102[/C][C]85.3632132950171[/C][C]16.6367867049829[/C][/ROW]
[ROW][C]19[/C][C]77[/C][C]83.5915662118624[/C][C]-6.59156621186237[/C][/ROW]
[ROW][C]20[/C][C]82[/C][C]50.3997587690849[/C][C]31.6002412309151[/C][/ROW]
[ROW][C]21[/C][C]115[/C][C]88.6688583807019[/C][C]26.331141619298[/C][/ROW]
[ROW][C]22[/C][C]101[/C][C]87.0542820654809[/C][C]13.9457179345191[/C][/ROW]
[ROW][C]23[/C][C]80[/C][C]108.438584908038[/C][C]-28.4385849080382[/C][/ROW]
[ROW][C]24[/C][C]50[/C][C]57.3793245924942[/C][C]-7.37932459249417[/C][/ROW]
[ROW][C]25[/C][C]83[/C][C]69.6630736033936[/C][C]13.3369263966064[/C][/ROW]
[ROW][C]26[/C][C]123[/C][C]77.5939359770764[/C][C]45.4060640229236[/C][/ROW]
[ROW][C]27[/C][C]73[/C][C]75.601962814011[/C][C]-2.60196281401105[/C][/ROW]
[ROW][C]28[/C][C]81[/C][C]85.2572486284394[/C][C]-4.25724862843938[/C][/ROW]
[ROW][C]29[/C][C]105[/C][C]82.3744635054311[/C][C]22.6255364945689[/C][/ROW]
[ROW][C]30[/C][C]47[/C][C]52.5800441693919[/C][C]-5.58004416939193[/C][/ROW]
[ROW][C]31[/C][C]105[/C][C]80.9915931459447[/C][C]24.0084068540553[/C][/ROW]
[ROW][C]32[/C][C]94[/C][C]86.0538396865155[/C][C]7.94616031348453[/C][/ROW]
[ROW][C]33[/C][C]44[/C][C]79.6525014790433[/C][C]-35.6525014790433[/C][/ROW]
[ROW][C]34[/C][C]114[/C][C]102.059459100218[/C][C]11.9405408997822[/C][/ROW]
[ROW][C]35[/C][C]38[/C][C]45.3067107814558[/C][C]-7.30671078145582[/C][/ROW]
[ROW][C]36[/C][C]107[/C][C]109.281294197709[/C][C]-2.28129419770942[/C][/ROW]
[ROW][C]37[/C][C]30[/C][C]29.0726068409926[/C][C]0.927393159007444[/C][/ROW]
[ROW][C]38[/C][C]71[/C][C]86.5268028468282[/C][C]-15.5268028468282[/C][/ROW]
[ROW][C]39[/C][C]84[/C][C]118.81131050824[/C][C]-34.8113105082399[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]-7.28825111752852[/C][C]7.28825111752852[/C][/ROW]
[ROW][C]41[/C][C]59[/C][C]63.8600681596893[/C][C]-4.86006815968927[/C][/ROW]
[ROW][C]42[/C][C]33[/C][C]33.4486921367909[/C][C]-0.448692136790902[/C][/ROW]
[ROW][C]43[/C][C]42[/C][C]34.0329824031127[/C][C]7.9670175968873[/C][/ROW]
[ROW][C]44[/C][C]96[/C][C]98.4623598406547[/C][C]-2.46235984065472[/C][/ROW]
[ROW][C]45[/C][C]106[/C][C]111.550880285558[/C][C]-5.55088028555803[/C][/ROW]
[ROW][C]46[/C][C]56[/C][C]65.191016629022[/C][C]-9.19101662902199[/C][/ROW]
[ROW][C]47[/C][C]57[/C][C]67.830080382144[/C][C]-10.830080382144[/C][/ROW]
[ROW][C]48[/C][C]59[/C][C]58.0683315435771[/C][C]0.931668456422896[/C][/ROW]
[ROW][C]49[/C][C]39[/C][C]52.0273884174245[/C][C]-13.0273884174245[/C][/ROW]
[ROW][C]50[/C][C]34[/C][C]75.5800450567313[/C][C]-41.5800450567313[/C][/ROW]
[ROW][C]51[/C][C]76[/C][C]69.6961508909528[/C][C]6.30384910904721[/C][/ROW]
[ROW][C]52[/C][C]20[/C][C]37.5321709438298[/C][C]-17.5321709438298[/C][/ROW]
[ROW][C]53[/C][C]91[/C][C]83.8659560603819[/C][C]7.1340439396181[/C][/ROW]
[ROW][C]54[/C][C]115[/C][C]122.182867139218[/C][C]-7.18286713921848[/C][/ROW]
[ROW][C]55[/C][C]85[/C][C]73.3247939684687[/C][C]11.6752060315313[/C][/ROW]
[ROW][C]56[/C][C]76[/C][C]66.3681489461384[/C][C]9.63185105386158[/C][/ROW]
[ROW][C]57[/C][C]8[/C][C]2.66899867293935[/C][C]5.33100132706065[/C][/ROW]
[ROW][C]58[/C][C]79[/C][C]94.7533078499718[/C][C]-15.7533078499718[/C][/ROW]
[ROW][C]59[/C][C]21[/C][C]30.724036084981[/C][C]-9.72403608498098[/C][/ROW]
[ROW][C]60[/C][C]30[/C][C]28.9323034701459[/C][C]1.06769652985412[/C][/ROW]
[ROW][C]61[/C][C]76[/C][C]86.7018370492762[/C][C]-10.7018370492761[/C][/ROW]
[ROW][C]62[/C][C]101[/C][C]106.215042247249[/C][C]-5.2150422472491[/C][/ROW]
[ROW][C]63[/C][C]94[/C][C]118.717271117485[/C][C]-24.7172711174852[/C][/ROW]
[ROW][C]64[/C][C]27[/C][C]33.7419849236066[/C][C]-6.74198492360663[/C][/ROW]
[ROW][C]65[/C][C]92[/C][C]76.7662225161589[/C][C]15.2337774838411[/C][/ROW]
[ROW][C]66[/C][C]123[/C][C]92.4231897459329[/C][C]30.5768102540671[/C][/ROW]
[ROW][C]67[/C][C]75[/C][C]75.2232690294157[/C][C]-0.22326902941572[/C][/ROW]
[ROW][C]68[/C][C]128[/C][C]127.106738974584[/C][C]0.893261025416324[/C][/ROW]
[ROW][C]69[/C][C]105[/C][C]77.2517791183395[/C][C]27.7482208816605[/C][/ROW]
[ROW][C]70[/C][C]55[/C][C]82.7066225447105[/C][C]-27.7066225447105[/C][/ROW]
[ROW][C]71[/C][C]56[/C][C]86.1304089553372[/C][C]-30.1304089553372[/C][/ROW]
[ROW][C]72[/C][C]41[/C][C]67.6212410701756[/C][C]-26.6212410701756[/C][/ROW]
[ROW][C]73[/C][C]72[/C][C]62.3374563530969[/C][C]9.66254364690312[/C][/ROW]
[ROW][C]74[/C][C]67[/C][C]55.7374936586272[/C][C]11.2625063413728[/C][/ROW]
[ROW][C]75[/C][C]75[/C][C]81.4861584693172[/C][C]-6.48615846931719[/C][/ROW]
[ROW][C]76[/C][C]114[/C][C]73.2735138700012[/C][C]40.7264861299988[/C][/ROW]
[ROW][C]77[/C][C]118[/C][C]47.9497644220836[/C][C]70.0502355779164[/C][/ROW]
[ROW][C]78[/C][C]77[/C][C]90.1706294398983[/C][C]-13.1706294398983[/C][/ROW]
[ROW][C]79[/C][C]22[/C][C]36.3471068882976[/C][C]-14.3471068882976[/C][/ROW]
[ROW][C]80[/C][C]66[/C][C]88.4000413831348[/C][C]-22.4000413831348[/C][/ROW]
[ROW][C]81[/C][C]69[/C][C]62.4098022980879[/C][C]6.59019770191208[/C][/ROW]
[ROW][C]82[/C][C]105[/C][C]67.1954048514929[/C][C]37.8045951485071[/C][/ROW]
[ROW][C]83[/C][C]116[/C][C]94.7624143662589[/C][C]21.2375856337412[/C][/ROW]
[ROW][C]84[/C][C]88[/C][C]86.3978649577472[/C][C]1.60213504225283[/C][/ROW]
[ROW][C]85[/C][C]73[/C][C]73.0911481307442[/C][C]-0.0911481307442444[/C][/ROW]
[ROW][C]86[/C][C]99[/C][C]63.0367509399147[/C][C]35.9632490600853[/C][/ROW]
[ROW][C]87[/C][C]62[/C][C]66.0206261095698[/C][C]-4.02062610956982[/C][/ROW]
[ROW][C]88[/C][C]53[/C][C]53.5464447992937[/C][C]-0.546444799293674[/C][/ROW]
[ROW][C]89[/C][C]118[/C][C]126.480376705401[/C][C]-8.48037670540091[/C][/ROW]
[ROW][C]90[/C][C]30[/C][C]56.6464973342002[/C][C]-26.6464973342002[/C][/ROW]
[ROW][C]91[/C][C]100[/C][C]78.9482985886952[/C][C]21.0517014113048[/C][/ROW]
[ROW][C]92[/C][C]49[/C][C]23.0279165897285[/C][C]25.9720834102715[/C][/ROW]
[ROW][C]93[/C][C]24[/C][C]43.6227734478362[/C][C]-19.6227734478361[/C][/ROW]
[ROW][C]94[/C][C]67[/C][C]52.5174496270356[/C][C]14.4825503729644[/C][/ROW]
[ROW][C]95[/C][C]46[/C][C]40.5447417861949[/C][C]5.45525821380506[/C][/ROW]
[ROW][C]96[/C][C]57[/C][C]79.7604390399185[/C][C]-22.7604390399185[/C][/ROW]
[ROW][C]97[/C][C]75[/C][C]101.003148178019[/C][C]-26.0031481780193[/C][/ROW]
[ROW][C]98[/C][C]135[/C][C]85.6281366615375[/C][C]49.3718633384625[/C][/ROW]
[ROW][C]99[/C][C]68[/C][C]83.3444069761895[/C][C]-15.3444069761896[/C][/ROW]
[ROW][C]100[/C][C]124[/C][C]74.1804322994749[/C][C]49.8195677005251[/C][/ROW]
[ROW][C]101[/C][C]33[/C][C]54.2790402196498[/C][C]-21.2790402196498[/C][/ROW]
[ROW][C]102[/C][C]98[/C][C]93.4962726365955[/C][C]4.50372736340452[/C][/ROW]
[ROW][C]103[/C][C]58[/C][C]81.6600421188834[/C][C]-23.6600421188834[/C][/ROW]
[ROW][C]104[/C][C]68[/C][C]65.3522834731451[/C][C]2.64771652685495[/C][/ROW]
[ROW][C]105[/C][C]81[/C][C]68.0073436406777[/C][C]12.9926563593223[/C][/ROW]
[ROW][C]106[/C][C]131[/C][C]84.6907918119456[/C][C]46.3092081880543[/C][/ROW]
[ROW][C]107[/C][C]110[/C][C]120.821248028561[/C][C]-10.8212480285612[/C][/ROW]
[ROW][C]108[/C][C]37[/C][C]39.4819388195677[/C][C]-2.48193881956766[/C][/ROW]
[ROW][C]109[/C][C]130[/C][C]107.676296697654[/C][C]22.3237033023463[/C][/ROW]
[ROW][C]110[/C][C]93[/C][C]94.6140886851791[/C][C]-1.61408868517913[/C][/ROW]
[ROW][C]111[/C][C]118[/C][C]88.469992628398[/C][C]29.530007371602[/C][/ROW]
[ROW][C]112[/C][C]39[/C][C]52.2138886322194[/C][C]-13.2138886322194[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]22.7065609059635[/C][C]-9.70656090596354[/C][/ROW]
[ROW][C]114[/C][C]74[/C][C]56.9926438070034[/C][C]17.0073561929966[/C][/ROW]
[ROW][C]115[/C][C]81[/C][C]63.1234540514563[/C][C]17.8765459485437[/C][/ROW]
[ROW][C]116[/C][C]109[/C][C]82.9538859333752[/C][C]26.0461140666248[/C][/ROW]
[ROW][C]117[/C][C]151[/C][C]93.5518196533737[/C][C]57.4481803466263[/C][/ROW]
[ROW][C]118[/C][C]51[/C][C]68.1187411543652[/C][C]-17.1187411543652[/C][/ROW]
[ROW][C]119[/C][C]28[/C][C]39.538745316654[/C][C]-11.538745316654[/C][/ROW]
[ROW][C]120[/C][C]40[/C][C]30.913328118566[/C][C]9.08667188143402[/C][/ROW]
[ROW][C]121[/C][C]56[/C][C]49.3176116028734[/C][C]6.68238839712659[/C][/ROW]
[ROW][C]122[/C][C]27[/C][C]20.984508074169[/C][C]6.01549192583104[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]35.0162627515466[/C][C]1.9837372484534[/C][/ROW]
[ROW][C]124[/C][C]83[/C][C]47.6933539994117[/C][C]35.3066460005883[/C][/ROW]
[ROW][C]125[/C][C]54[/C][C]79.4972757312769[/C][C]-25.4972757312769[/C][/ROW]
[ROW][C]126[/C][C]27[/C][C]23.5393177222716[/C][C]3.46068227772836[/C][/ROW]
[ROW][C]127[/C][C]28[/C][C]28.8540372495583[/C][C]-0.854037249558343[/C][/ROW]
[ROW][C]128[/C][C]59[/C][C]41.618872770989[/C][C]17.381127229011[/C][/ROW]
[ROW][C]129[/C][C]133[/C][C]100.042622184214[/C][C]32.9573778157857[/C][/ROW]
[ROW][C]130[/C][C]12[/C][C]0.377728046085846[/C][C]11.6222719539142[/C][/ROW]
[ROW][C]131[/C][C]0[/C][C]12.0768127016159[/C][C]-12.0768127016159[/C][/ROW]
[ROW][C]132[/C][C]106[/C][C]69.1585183347559[/C][C]36.8414816652441[/C][/ROW]
[ROW][C]133[/C][C]23[/C][C]17.172101583241[/C][C]5.82789841675897[/C][/ROW]
[ROW][C]134[/C][C]44[/C][C]49.8503032101832[/C][C]-5.8503032101832[/C][/ROW]
[ROW][C]135[/C][C]71[/C][C]62.1042319893043[/C][C]8.89576801069567[/C][/ROW]
[ROW][C]136[/C][C]116[/C][C]110.051171897829[/C][C]5.94882810217061[/C][/ROW]
[ROW][C]137[/C][C]4[/C][C]-0.986422745858747[/C][C]4.98642274585875[/C][/ROW]
[ROW][C]138[/C][C]62[/C][C]75.7721781588268[/C][C]-13.7721781588268[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]11.9500416984534[/C][C]0.0499583015465648[/C][/ROW]
[ROW][C]140[/C][C]18[/C][C]7.83742820876298[/C][C]10.162571791237[/C][/ROW]
[ROW][C]141[/C][C]14[/C][C]17.7155102540436[/C][C]-3.71551025404363[/C][/ROW]
[ROW][C]142[/C][C]60[/C][C]49.0581178155565[/C][C]10.9418821844435[/C][/ROW]
[ROW][C]143[/C][C]7[/C][C]28.8624102860401[/C][C]-21.8624102860401[/C][/ROW]
[ROW][C]144[/C][C]98[/C][C]91.580206219034[/C][C]6.41979378096596[/C][/ROW]
[ROW][C]145[/C][C]64[/C][C]83.9074659524529[/C][C]-19.9074659524529[/C][/ROW]
[ROW][C]146[/C][C]29[/C][C]35.0985796331311[/C][C]-6.09857963313111[/C][/ROW]
[ROW][C]147[/C][C]32[/C][C]58.3254043964848[/C][C]-26.3254043964848[/C][/ROW]
[ROW][C]148[/C][C]25[/C][C]45.3787171746891[/C][C]-20.3787171746891[/C][/ROW]
[ROW][C]149[/C][C]16[/C][C]5.69156080265188[/C][C]10.3084391973481[/C][/ROW]
[ROW][C]150[/C][C]48[/C][C]66.8538429465659[/C][C]-18.8538429465659[/C][/ROW]
[ROW][C]151[/C][C]100[/C][C]106.968655108418[/C][C]-6.9686551084181[/C][/ROW]
[ROW][C]152[/C][C]46[/C][C]76.4197090348503[/C][C]-30.4197090348503[/C][/ROW]
[ROW][C]153[/C][C]45[/C][C]40.4090540089811[/C][C]4.59094599101892[/C][/ROW]
[ROW][C]154[/C][C]129[/C][C]124.424504683574[/C][C]4.5754953164258[/C][/ROW]
[ROW][C]155[/C][C]130[/C][C]90.644067576741[/C][C]39.355932423259[/C][/ROW]
[ROW][C]156[/C][C]136[/C][C]134.765413363194[/C][C]1.2345866368062[/C][/ROW]
[ROW][C]157[/C][C]59[/C][C]63.1054200008059[/C][C]-4.10542000080586[/C][/ROW]
[ROW][C]158[/C][C]25[/C][C]22.4498402742003[/C][C]2.55015972579974[/C][/ROW]
[ROW][C]159[/C][C]32[/C][C]44.4984518403267[/C][C]-12.4984518403267[/C][/ROW]
[ROW][C]160[/C][C]63[/C][C]60.3970990084935[/C][C]2.60290099150654[/C][/ROW]
[ROW][C]161[/C][C]95[/C][C]130.698114699861[/C][C]-35.6981146998607[/C][/ROW]
[ROW][C]162[/C][C]14[/C][C]44.5966375077841[/C][C]-30.5966375077841[/C][/ROW]
[ROW][C]163[/C][C]36[/C][C]32.5369809337564[/C][C]3.46301906624361[/C][/ROW]
[ROW][C]164[/C][C]113[/C][C]121.4056944797[/C][C]-8.40569447969971[/C][/ROW]
[ROW][C]165[/C][C]47[/C][C]60.3897207944806[/C][C]-13.3897207944806[/C][/ROW]
[ROW][C]166[/C][C]92[/C][C]78.1293409019766[/C][C]13.8706590980234[/C][/ROW]
[ROW][C]167[/C][C]70[/C][C]60.4500387949779[/C][C]9.54996120502206[/C][/ROW]
[ROW][C]168[/C][C]19[/C][C]49.2588054621669[/C][C]-30.2588054621669[/C][/ROW]
[ROW][C]169[/C][C]50[/C][C]37.3979902807186[/C][C]12.6020097192814[/C][/ROW]
[ROW][C]170[/C][C]41[/C][C]74.7467165074642[/C][C]-33.7467165074642[/C][/ROW]
[ROW][C]171[/C][C]91[/C][C]117.680113230471[/C][C]-26.6801132304707[/C][/ROW]
[ROW][C]172[/C][C]111[/C][C]76.0326103152027[/C][C]34.9673896847973[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]70.37441931084[/C][C]-29.37441931084[/C][/ROW]
[ROW][C]174[/C][C]120[/C][C]106.044836883923[/C][C]13.9551631160769[/C][/ROW]
[ROW][C]175[/C][C]135[/C][C]60.3902254888729[/C][C]74.6097745111271[/C][/ROW]
[ROW][C]176[/C][C]27[/C][C]46.3903259144472[/C][C]-19.3903259144472[/C][/ROW]
[ROW][C]177[/C][C]87[/C][C]88.213060637276[/C][C]-1.21306063727603[/C][/ROW]
[ROW][C]178[/C][C]25[/C][C]33.5160553047988[/C][C]-8.51605530479882[/C][/ROW]
[ROW][C]179[/C][C]131[/C][C]92.5491150282197[/C][C]38.4508849717802[/C][/ROW]
[ROW][C]180[/C][C]45[/C][C]37.7135413070393[/C][C]7.28645869296066[/C][/ROW]
[ROW][C]181[/C][C]29[/C][C]20.3267783142569[/C][C]8.67322168574309[/C][/ROW]
[ROW][C]182[/C][C]58[/C][C]33.8011666779139[/C][C]24.1988333220861[/C][/ROW]
[ROW][C]183[/C][C]4[/C][C]-4.50178238111515[/C][C]8.50178238111515[/C][/ROW]
[ROW][C]184[/C][C]47[/C][C]72.2371444092861[/C][C]-25.2371444092861[/C][/ROW]
[ROW][C]185[/C][C]109[/C][C]101.701893397224[/C][C]7.29810660277626[/C][/ROW]
[ROW][C]186[/C][C]7[/C][C]-6.32515711659406[/C][C]13.3251571165941[/C][/ROW]
[ROW][C]187[/C][C]12[/C][C]9.69647637143707[/C][C]2.30352362856293[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]-3.86056240214343[/C][C]3.86056240214343[/C][/ROW]
[ROW][C]189[/C][C]37[/C][C]51.3936252461276[/C][C]-14.3936252461276[/C][/ROW]
[ROW][C]190[/C][C]37[/C][C]45.5927448682801[/C][C]-8.59274486828006[/C][/ROW]
[ROW][C]191[/C][C]46[/C][C]58.5173037208616[/C][C]-12.5173037208616[/C][/ROW]
[ROW][C]192[/C][C]15[/C][C]36.0762319540415[/C][C]-21.0762319540415[/C][/ROW]
[ROW][C]193[/C][C]42[/C][C]21.6646079863014[/C][C]20.3353920136986[/C][/ROW]
[ROW][C]194[/C][C]7[/C][C]16.4587117296861[/C][C]-9.45871172968612[/C][/ROW]
[ROW][C]195[/C][C]54[/C][C]53.7751930035454[/C][C]0.224806996454626[/C][/ROW]
[ROW][C]196[/C][C]54[/C][C]36.4836752267422[/C][C]17.5163247732578[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]31.8486627905302[/C][C]-17.8486627905302[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]22.5730719629057[/C][C]-6.57307196290574[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]40.6533145249684[/C][C]-7.65331452496842[/C][/ROW]
[ROW][C]200[/C][C]32[/C][C]25.574388086498[/C][C]6.42561191350197[/C][/ROW]
[ROW][C]201[/C][C]21[/C][C]25.3596932389229[/C][C]-4.35969323892289[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]27.1152651796419[/C][C]-12.1152651796419[/C][/ROW]
[ROW][C]203[/C][C]38[/C][C]37.9847341254642[/C][C]0.0152658745357799[/C][/ROW]
[ROW][C]204[/C][C]22[/C][C]32.8313673854896[/C][C]-10.8313673854896[/C][/ROW]
[ROW][C]205[/C][C]28[/C][C]35.6347315979171[/C][C]-7.63473159791712[/C][/ROW]
[ROW][C]206[/C][C]10[/C][C]23.5759504821211[/C][C]-13.5759504821211[/C][/ROW]
[ROW][C]207[/C][C]31[/C][C]30.0280979742154[/C][C]0.971902025784561[/C][/ROW]
[ROW][C]208[/C][C]32[/C][C]54.6177609763618[/C][C]-22.6177609763618[/C][/ROW]
[ROW][C]209[/C][C]32[/C][C]44.4433736622975[/C][C]-12.4433736622975[/C][/ROW]
[ROW][C]210[/C][C]43[/C][C]50.1693810970623[/C][C]-7.16938109706226[/C][/ROW]
[ROW][C]211[/C][C]27[/C][C]25.8929968048359[/C][C]1.1070031951641[/C][/ROW]
[ROW][C]212[/C][C]37[/C][C]44.0098195690248[/C][C]-7.0098195690248[/C][/ROW]
[ROW][C]213[/C][C]20[/C][C]22.2631756356508[/C][C]-2.26317563565083[/C][/ROW]
[ROW][C]214[/C][C]32[/C][C]27.3723258493691[/C][C]4.62767415063089[/C][/ROW]
[ROW][C]215[/C][C]0[/C][C]37.2022061991699[/C][C]-37.2022061991699[/C][/ROW]
[ROW][C]216[/C][C]5[/C][C]27.5452081961087[/C][C]-22.5452081961087[/C][/ROW]
[ROW][C]217[/C][C]26[/C][C]22.4654793374011[/C][C]3.53452066259892[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]15.1633134260303[/C][C]-5.16331342603033[/C][/ROW]
[ROW][C]219[/C][C]27[/C][C]24.8974883444239[/C][C]2.10251165557614[/C][/ROW]
[ROW][C]220[/C][C]11[/C][C]27.645584420734[/C][C]-16.645584420734[/C][/ROW]
[ROW][C]221[/C][C]29[/C][C]37.2602387620172[/C][C]-8.26023876201718[/C][/ROW]
[ROW][C]222[/C][C]25[/C][C]47.8813215583819[/C][C]-22.8813215583819[/C][/ROW]
[ROW][C]223[/C][C]55[/C][C]41.3366742772999[/C][C]13.6633257227001[/C][/ROW]
[ROW][C]224[/C][C]23[/C][C]27.4363150344493[/C][C]-4.43631503444928[/C][/ROW]
[ROW][C]225[/C][C]5[/C][C]13.713642568718[/C][C]-8.71364256871797[/C][/ROW]
[ROW][C]226[/C][C]43[/C][C]36.9211993329742[/C][C]6.07880066702576[/C][/ROW]
[ROW][C]227[/C][C]23[/C][C]13.3691567246114[/C][C]9.63084327538865[/C][/ROW]
[ROW][C]228[/C][C]34[/C][C]25.4770029371619[/C][C]8.52299706283814[/C][/ROW]
[ROW][C]229[/C][C]36[/C][C]23.3515732936385[/C][C]12.6484267063615[/C][/ROW]
[ROW][C]230[/C][C]35[/C][C]43.9568289742349[/C][C]-8.95682897423487[/C][/ROW]
[ROW][C]231[/C][C]0[/C][C]17.1281928837975[/C][C]-17.1281928837975[/C][/ROW]
[ROW][C]232[/C][C]37[/C][C]29.1826408895096[/C][C]7.8173591104904[/C][/ROW]
[ROW][C]233[/C][C]28[/C][C]35.9249676377177[/C][C]-7.9249676377177[/C][/ROW]
[ROW][C]234[/C][C]16[/C][C]20.1514001128142[/C][C]-4.15140011281416[/C][/ROW]
[ROW][C]235[/C][C]26[/C][C]27.1975805026688[/C][C]-1.19758050266883[/C][/ROW]
[ROW][C]236[/C][C]38[/C][C]22.1757899980468[/C][C]15.8242100019532[/C][/ROW]
[ROW][C]237[/C][C]23[/C][C]52.0871286454555[/C][C]-29.0871286454555[/C][/ROW]
[ROW][C]238[/C][C]22[/C][C]22.2725852464081[/C][C]-0.27258524640808[/C][/ROW]
[ROW][C]239[/C][C]30[/C][C]26.9662768178682[/C][C]3.03372318213181[/C][/ROW]
[ROW][C]240[/C][C]16[/C][C]17.4223393268931[/C][C]-1.42233932689314[/C][/ROW]
[ROW][C]241[/C][C]18[/C][C]31.6308961005729[/C][C]-13.6308961005729[/C][/ROW]
[ROW][C]242[/C][C]28[/C][C]42.5572279247433[/C][C]-14.5572279247433[/C][/ROW]
[ROW][C]243[/C][C]32[/C][C]17.804154249236[/C][C]14.195845750764[/C][/ROW]
[ROW][C]244[/C][C]21[/C][C]19.1973212060186[/C][C]1.80267879398138[/C][/ROW]
[ROW][C]245[/C][C]23[/C][C]23.2888658714515[/C][C]-0.288865871451511[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]35.1568163549676[/C][C]-6.1568163549676[/C][/ROW]
[ROW][C]247[/C][C]50[/C][C]39.103150504873[/C][C]10.896849495127[/C][/ROW]
[ROW][C]248[/C][C]12[/C][C]25.13585738655[/C][C]-13.13585738655[/C][/ROW]
[ROW][C]249[/C][C]21[/C][C]20.8485878498332[/C][C]0.151412150166822[/C][/ROW]
[ROW][C]250[/C][C]18[/C][C]8.99231893571396[/C][C]9.00768106428604[/C][/ROW]
[ROW][C]251[/C][C]27[/C][C]46.4916648149591[/C][C]-19.4916648149591[/C][/ROW]
[ROW][C]252[/C][C]41[/C][C]35.0889059083413[/C][C]5.91109409165873[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]-4.27827023648758[/C][C]17.2782702364876[/C][/ROW]
[ROW][C]254[/C][C]12[/C][C]31.2127205306372[/C][C]-19.2127205306372[/C][/ROW]
[ROW][C]255[/C][C]21[/C][C]35.009066791362[/C][C]-14.009066791362[/C][/ROW]
[ROW][C]256[/C][C]8[/C][C]4.67088239243526[/C][C]3.32911760756474[/C][/ROW]
[ROW][C]257[/C][C]26[/C][C]12.0574940863106[/C][C]13.9425059136894[/C][/ROW]
[ROW][C]258[/C][C]27[/C][C]27.2954547037151[/C][C]-0.295454703715052[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]19.9223667732289[/C][C]-6.92236677322892[/C][/ROW]
[ROW][C]260[/C][C]16[/C][C]9.51269784893434[/C][C]6.48730215106566[/C][/ROW]
[ROW][C]261[/C][C]2[/C][C]13.7181928217293[/C][C]-11.7181928217293[/C][/ROW]
[ROW][C]262[/C][C]42[/C][C]23.0095369849219[/C][C]18.9904630150781[/C][/ROW]
[ROW][C]263[/C][C]5[/C][C]9.25444053713236[/C][C]-4.25444053713236[/C][/ROW]
[ROW][C]264[/C][C]37[/C][C]22.9470817219832[/C][C]14.0529182780168[/C][/ROW]
[ROW][C]265[/C][C]17[/C][C]17.7548849680636[/C][C]-0.75488496806358[/C][/ROW]
[ROW][C]266[/C][C]38[/C][C]29.262125149534[/C][C]8.73787485046599[/C][/ROW]
[ROW][C]267[/C][C]37[/C][C]25.6777643153768[/C][C]11.3222356846232[/C][/ROW]
[ROW][C]268[/C][C]29[/C][C]14.0584019373503[/C][C]14.9415980626497[/C][/ROW]
[ROW][C]269[/C][C]32[/C][C]33.1200591779585[/C][C]-1.12005917795849[/C][/ROW]
[ROW][C]270[/C][C]35[/C][C]30.9253373903679[/C][C]4.07466260963213[/C][/ROW]
[ROW][C]271[/C][C]17[/C][C]36.6315386161103[/C][C]-19.6315386161103[/C][/ROW]
[ROW][C]272[/C][C]20[/C][C]23.8821388046731[/C][C]-3.88213880467312[/C][/ROW]
[ROW][C]273[/C][C]7[/C][C]3.45278696647229[/C][C]3.54721303352771[/C][/ROW]
[ROW][C]274[/C][C]46[/C][C]33.1424571868966[/C][C]12.8575428131034[/C][/ROW]
[ROW][C]275[/C][C]24[/C][C]18.5461269643301[/C][C]5.45387303566989[/C][/ROW]
[ROW][C]276[/C][C]40[/C][C]33.9716590356086[/C][C]6.02834096439136[/C][/ROW]
[ROW][C]277[/C][C]3[/C][C]18.0499661021857[/C][C]-15.0499661021857[/C][/ROW]
[ROW][C]278[/C][C]10[/C][C]-2.59138544248252[/C][C]12.5913854424825[/C][/ROW]
[ROW][C]279[/C][C]37[/C][C]33.1223440616069[/C][C]3.87765593839314[/C][/ROW]
[ROW][C]280[/C][C]17[/C][C]29.6540044653283[/C][C]-12.6540044653283[/C][/ROW]
[ROW][C]281[/C][C]28[/C][C]30.7327690817184[/C][C]-2.7327690817184[/C][/ROW]
[ROW][C]282[/C][C]19[/C][C]29.0430058209951[/C][C]-10.0430058209951[/C][/ROW]
[ROW][C]283[/C][C]29[/C][C]32.761549270961[/C][C]-3.76154927096104[/C][/ROW]
[ROW][C]284[/C][C]8[/C][C]5.50641321707851[/C][C]2.49358678292149[/C][/ROW]
[ROW][C]285[/C][C]10[/C][C]23.4250265812016[/C][C]-13.4250265812016[/C][/ROW]
[ROW][C]286[/C][C]15[/C][C]31.8140771604219[/C][C]-16.8140771604219[/C][/ROW]
[ROW][C]287[/C][C]15[/C][C]21.8011930450959[/C][C]-6.80119304509586[/C][/ROW]
[ROW][C]288[/C][C]28[/C][C]21.9581846792719[/C][C]6.04181532072814[/C][/ROW]
[ROW][C]289[/C][C]17[/C][C]30.219698635475[/C][C]-13.219698635475[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197292&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197292&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17971.1576243325897.842375667411
25845.255940852246112.7440591477539
36079.4919522633712-19.4919522633712
410869.476588680202838.5234113197972
54943.64864827112285.35135172887722
6028.8725272890208-28.8725272890208
7121129.228000911689-8.2280009116893
8114.8647736974586-13.8647736974586
92024.2373129263626-4.23731292636262
104361.5972571960154-18.5972571960154
116963.44315338574635.55684661425373
127888.5144584065299-10.5144584065299
138680.65461649833755.34538350166252
144459.4534042260957-15.4534042260957
15104103.7093882469410.290611753058818
166375.4229204215431-12.4229204215431
17158143.63723133970514.3627686602947
1810285.363213295017116.6367867049829
197783.5915662118624-6.59156621186237
208250.399758769084931.6002412309151
2111588.668858380701926.331141619298
2210187.054282065480913.9457179345191
2380108.438584908038-28.4385849080382
245057.3793245924942-7.37932459249417
258369.663073603393613.3369263966064
2612377.593935977076445.4060640229236
277375.601962814011-2.60196281401105
288185.2572486284394-4.25724862843938
2910582.374463505431122.6255364945689
304752.5800441693919-5.58004416939193
3110580.991593145944724.0084068540553
329486.05383968651557.94616031348453
334479.6525014790433-35.6525014790433
34114102.05945910021811.9405408997822
353845.3067107814558-7.30671078145582
36107109.281294197709-2.28129419770942
373029.07260684099260.927393159007444
387186.5268028468282-15.5268028468282
3984118.81131050824-34.8113105082399
400-7.288251117528527.28825111752852
415963.8600681596893-4.86006815968927
423333.4486921367909-0.448692136790902
434234.03298240311277.9670175968873
449698.4623598406547-2.46235984065472
45106111.550880285558-5.55088028555803
465665.191016629022-9.19101662902199
475767.830080382144-10.830080382144
485958.06833154357710.931668456422896
493952.0273884174245-13.0273884174245
503475.5800450567313-41.5800450567313
517669.69615089095286.30384910904721
522037.5321709438298-17.5321709438298
539183.86595606038197.1340439396181
54115122.182867139218-7.18286713921848
558573.324793968468711.6752060315313
567666.36814894613849.63185105386158
5782.668998672939355.33100132706065
587994.7533078499718-15.7533078499718
592130.724036084981-9.72403608498098
603028.93230347014591.06769652985412
617686.7018370492762-10.7018370492761
62101106.215042247249-5.2150422472491
6394118.717271117485-24.7172711174852
642733.7419849236066-6.74198492360663
659276.766222516158915.2337774838411
6612392.423189745932930.5768102540671
677575.2232690294157-0.22326902941572
68128127.1067389745840.893261025416324
6910577.251779118339527.7482208816605
705582.7066225447105-27.7066225447105
715686.1304089553372-30.1304089553372
724167.6212410701756-26.6212410701756
737262.33745635309699.66254364690312
746755.737493658627211.2625063413728
757581.4861584693172-6.48615846931719
7611473.273513870001240.7264861299988
7711847.949764422083670.0502355779164
787790.1706294398983-13.1706294398983
792236.3471068882976-14.3471068882976
806688.4000413831348-22.4000413831348
816962.40980229808796.59019770191208
8210567.195404851492937.8045951485071
8311694.762414366258921.2375856337412
848886.39786495774721.60213504225283
857373.0911481307442-0.0911481307442444
869963.036750939914735.9632490600853
876266.0206261095698-4.02062610956982
885353.5464447992937-0.546444799293674
89118126.480376705401-8.48037670540091
903056.6464973342002-26.6464973342002
9110078.948298588695221.0517014113048
924923.027916589728525.9720834102715
932443.6227734478362-19.6227734478361
946752.517449627035614.4825503729644
954640.54474178619495.45525821380506
965779.7604390399185-22.7604390399185
9775101.003148178019-26.0031481780193
9813585.628136661537549.3718633384625
996883.3444069761895-15.3444069761896
10012474.180432299474949.8195677005251
1013354.2790402196498-21.2790402196498
1029893.49627263659554.50372736340452
1035881.6600421188834-23.6600421188834
1046865.35228347314512.64771652685495
1058168.007343640677712.9926563593223
10613184.690791811945646.3092081880543
107110120.821248028561-10.8212480285612
1083739.4819388195677-2.48193881956766
109130107.67629669765422.3237033023463
1109394.6140886851791-1.61408868517913
11111888.46999262839829.530007371602
1123952.2138886322194-13.2138886322194
1131322.7065609059635-9.70656090596354
1147456.992643807003417.0073561929966
1158163.123454051456317.8765459485437
11610982.953885933375226.0461140666248
11715193.551819653373757.4481803466263
1185168.1187411543652-17.1187411543652
1192839.538745316654-11.538745316654
1204030.9133281185669.08667188143402
1215649.31761160287346.68238839712659
1222720.9845080741696.01549192583104
1233735.01626275154661.9837372484534
1248347.693353999411735.3066460005883
1255479.4972757312769-25.4972757312769
1262723.53931772227163.46068227772836
1272828.8540372495583-0.854037249558343
1285941.61887277098917.381127229011
129133100.04262218421432.9573778157857
130120.37772804608584611.6222719539142
131012.0768127016159-12.0768127016159
13210669.158518334755936.8414816652441
1332317.1721015832415.82789841675897
1344449.8503032101832-5.8503032101832
1357162.10423198930438.89576801069567
136116110.0511718978295.94882810217061
1374-0.9864227458587474.98642274585875
1386275.7721781588268-13.7721781588268
1391211.95004169845340.0499583015465648
140187.8374282087629810.162571791237
1411417.7155102540436-3.71551025404363
1426049.058117815556510.9418821844435
143728.8624102860401-21.8624102860401
1449891.5802062190346.41979378096596
1456483.9074659524529-19.9074659524529
1462935.0985796331311-6.09857963313111
1473258.3254043964848-26.3254043964848
1482545.3787171746891-20.3787171746891
149165.6915608026518810.3084391973481
1504866.8538429465659-18.8538429465659
151100106.968655108418-6.9686551084181
1524676.4197090348503-30.4197090348503
1534540.40905400898114.59094599101892
154129124.4245046835744.5754953164258
15513090.64406757674139.355932423259
156136134.7654133631941.2345866368062
1575963.1054200008059-4.10542000080586
1582522.44984027420032.55015972579974
1593244.4984518403267-12.4984518403267
1606360.39709900849352.60290099150654
16195130.698114699861-35.6981146998607
1621444.5966375077841-30.5966375077841
1633632.53698093375643.46301906624361
164113121.4056944797-8.40569447969971
1654760.3897207944806-13.3897207944806
1669278.129340901976613.8706590980234
1677060.45003879497799.54996120502206
1681949.2588054621669-30.2588054621669
1695037.397990280718612.6020097192814
1704174.7467165074642-33.7467165074642
17191117.680113230471-26.6801132304707
17211176.032610315202734.9673896847973
1734170.37441931084-29.37441931084
174120106.04483688392313.9551631160769
17513560.390225488872974.6097745111271
1762746.3903259144472-19.3903259144472
1778788.213060637276-1.21306063727603
1782533.5160553047988-8.51605530479882
17913192.549115028219738.4508849717802
1804537.71354130703937.28645869296066
1812920.32677831425698.67322168574309
1825833.801166677913924.1988333220861
1834-4.501782381115158.50178238111515
1844772.2371444092861-25.2371444092861
185109101.7018933972247.29810660277626
1867-6.3251571165940613.3251571165941
187129.696476371437072.30352362856293
1880-3.860562402143433.86056240214343
1893751.3936252461276-14.3936252461276
1903745.5927448682801-8.59274486828006
1914658.5173037208616-12.5173037208616
1921536.0762319540415-21.0762319540415
1934221.664607986301420.3353920136986
194716.4587117296861-9.45871172968612
1955453.77519300354540.224806996454626
1965436.483675226742217.5163247732578
1971431.8486627905302-17.8486627905302
1981622.5730719629057-6.57307196290574
1993340.6533145249684-7.65331452496842
2003225.5743880864986.42561191350197
2012125.3596932389229-4.35969323892289
2021527.1152651796419-12.1152651796419
2033837.98473412546420.0152658745357799
2042232.8313673854896-10.8313673854896
2052835.6347315979171-7.63473159791712
2061023.5759504821211-13.5759504821211
2073130.02809797421540.971902025784561
2083254.6177609763618-22.6177609763618
2093244.4433736622975-12.4433736622975
2104350.1693810970623-7.16938109706226
2112725.89299680483591.1070031951641
2123744.0098195690248-7.0098195690248
2132022.2631756356508-2.26317563565083
2143227.37232584936914.62767415063089
215037.2022061991699-37.2022061991699
216527.5452081961087-22.5452081961087
2172622.46547933740113.53452066259892
2181015.1633134260303-5.16331342603033
2192724.89748834442392.10251165557614
2201127.645584420734-16.645584420734
2212937.2602387620172-8.26023876201718
2222547.8813215583819-22.8813215583819
2235541.336674277299913.6633257227001
2242327.4363150344493-4.43631503444928
225513.713642568718-8.71364256871797
2264336.92119933297426.07880066702576
2272313.36915672461149.63084327538865
2283425.47700293716198.52299706283814
2293623.351573293638512.6484267063615
2303543.9568289742349-8.95682897423487
231017.1281928837975-17.1281928837975
2323729.18264088950967.8173591104904
2332835.9249676377177-7.9249676377177
2341620.1514001128142-4.15140011281416
2352627.1975805026688-1.19758050266883
2363822.175789998046815.8242100019532
2372352.0871286454555-29.0871286454555
2382222.2725852464081-0.27258524640808
2393026.96627681786823.03372318213181
2401617.4223393268931-1.42233932689314
2411831.6308961005729-13.6308961005729
2422842.5572279247433-14.5572279247433
2433217.80415424923614.195845750764
2442119.19732120601861.80267879398138
2452323.2888658714515-0.288865871451511
2462935.1568163549676-6.1568163549676
2475039.10315050487310.896849495127
2481225.13585738655-13.13585738655
2492120.84858784983320.151412150166822
250188.992318935713969.00768106428604
2512746.4916648149591-19.4916648149591
2524135.08890590834135.91109409165873
25313-4.2782702364875817.2782702364876
2541231.2127205306372-19.2127205306372
2552135.009066791362-14.009066791362
25684.670882392435263.32911760756474
2572612.057494086310613.9425059136894
2582727.2954547037151-0.295454703715052
2591319.9223667732289-6.92236677322892
260169.512697848934346.48730215106566
261213.7181928217293-11.7181928217293
2624223.009536984921918.9904630150781
26359.25444053713236-4.25444053713236
2643722.947081721983214.0529182780168
2651717.7548849680636-0.75488496806358
2663829.2621251495348.73787485046599
2673725.677764315376811.3222356846232
2682914.058401937350314.9415980626497
2693233.1200591779585-1.12005917795849
2703530.92533739036794.07466260963213
2711736.6315386161103-19.6315386161103
2722023.8821388046731-3.88213880467312
27373.452786966472293.54721303352771
2744633.142457186896612.8575428131034
2752418.54612696433015.45387303566989
2764033.97165903560866.02834096439136
277318.0499661021857-15.0499661021857
27810-2.5913854424825212.5913854424825
2793733.12234406160693.87765593839314
2801729.6540044653283-12.6540044653283
2812830.7327690817184-2.7327690817184
2821929.0430058209951-10.0430058209951
2832932.761549270961-3.76154927096104
28485.506413217078512.49358678292149
2851023.4250265812016-13.4250265812016
2861531.8140771604219-16.8140771604219
2871521.8011930450959-6.80119304509586
2882821.95818467927196.04181532072814
2891730.219698635475-13.219698635475






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.6076288279690670.7847423440618660.392371172030933
100.4431878921947830.8863757843895650.556812107805217
110.5073630829629290.9852738340741430.492636917037071
120.5147168060621460.9705663878757080.485283193937854
130.4564148232760280.9128296465520550.543585176723972
140.3615016952950310.7230033905900620.638498304704969
150.271238757189230.5424775143784610.72876124281077
160.1946438988656370.3892877977312740.805356101134363
170.1349973106549550.2699946213099090.865002689345045
180.2461525215641680.4923050431283370.753847478435832
190.2262561187278120.4525122374556240.773743881272188
200.5732527556672860.8534944886654280.426747244332714
210.6806828658771850.638634268245630.319317134122815
220.6242610354290930.7514779291418140.375738964570907
230.7058535913128970.5882928173742060.294146408687103
240.648661531132660.7026769377346810.35133846886734
250.602472758178810.7950544836423810.39752724182119
260.6424540184489490.7150919631021020.357545981551051
270.5949852168284030.8100295663431950.405014783171597
280.542846372991850.9143072540162990.45715362700815
290.6198772588793420.7602454822413150.380122741120658
300.5646127753008610.8707744493982770.435387224699139
310.5270335086053630.9459329827892750.472966491394637
320.4878372591648360.9756745183296720.512162740835164
330.7246337300951060.5507325398097880.275366269904894
340.71334811439280.5733037712143990.2866518856072
350.6676382691681080.6647234616637850.332361730831892
360.6174962305974880.7650075388050250.382503769402512
370.5703667183098230.8592665633803530.429633281690177
380.5730632183437310.8538735633125380.426936781656269
390.6773287198010670.6453425603978660.322671280198933
400.6584926382409320.6830147235181360.341507361759068
410.6140216696468670.7719566607062650.385978330353133
420.5654008358652530.8691983282694940.434599164134747
430.533990648329420.932018703341160.46600935167058
440.4854462303575440.9708924607150890.514553769642456
450.4374989736005460.8749979472010920.562501026399454
460.4056377045872250.8112754091744490.594362295412775
470.4195384111898520.8390768223797030.580461588810148
480.3731586261401750.7463172522803490.626841373859825
490.3545430494479890.7090860988959780.645456950552011
500.5524263961219860.8951472077560280.447573603878014
510.5816961271516720.8366077456966570.418303872848328
520.5719339625386370.8561320749227270.428066037461363
530.5373314755245370.9253370489509270.462668524475463
540.4959438699910070.9918877399820140.504056130008993
550.478279553313520.9565591066270390.52172044668648
560.4474151900650180.8948303801300370.552584809934982
570.4076552603509840.8153105207019690.592344739649016
580.3978758222388410.7957516444776810.602124177761159
590.3673587142081620.7347174284163240.632641285791838
600.327178841303240.6543576826064790.67282115869676
610.3030984637124280.6061969274248560.696901536287572
620.268028037422970.5360560748459410.73197196257703
630.2922918315201150.584583663040230.707708168479885
640.2605011929882920.5210023859765830.739498807011708
650.2551610301146520.5103220602293040.744838969885348
660.3281916559177580.6563833118355150.671808344082242
670.2914723574276490.5829447148552990.70852764257235
680.2586369889854420.5172739779708830.741363011014558
690.3084765051760350.6169530103520710.691523494823965
700.3506822222471380.7013644444942750.649317777752862
710.4098264520453170.8196529040906340.590173547954683
720.451532976116910.9030659522338210.54846702388309
730.424967487383220.849934974766440.57503251261678
740.4021826325766740.8043652651533480.597817367423326
750.3684625289629170.7369250579258340.631537471037083
760.5272565074234830.9454869851530350.472743492576517
770.9056867677660840.1886264644678310.0943132322339156
780.8963556832175880.2072886335648230.103644316782412
790.8901046060605330.2197907878789330.109895393939467
800.8954833944041290.2090332111917420.104516605595871
810.8796538846448910.2406922307102180.120346115355109
820.9282299563972280.1435400872055430.0717700436027716
830.9318518897531770.1362962204936450.0681481102468225
840.9187549357082770.1624901285834460.0812450642917228
850.9038765534375350.192246893124930.0961234465624651
860.9380777895712570.1238444208574870.0619222104287434
870.9267179548129280.1465640903741450.0732820451870724
880.9131760542722350.1736478914555310.0868239457277654
890.9004197600343550.199160479931290.099580239965645
900.9175945638154390.1648108723691220.082405436184561
910.9206504241048890.1586991517902230.0793495758951114
920.9283726626174060.1432546747651890.0716273373825944
930.9307452547452150.1385094905095710.0692547452547853
940.9250221320576920.1499557358846150.0749778679423076
950.9121370965173960.1757258069652080.0878629034826039
960.9178924961509090.1642150076981810.0821075038490906
970.9279398262978230.1441203474043540.0720601737021772
980.9761099501106610.04778009977867790.0238900498893389
990.9744268741414030.05114625171719350.0255731258585968
1000.9933269228644070.01334615427118610.00667307713559306
1010.9939597476021210.01208050479575790.00604025239787894
1020.9923790946615720.01524181067685680.00762090533842842
1030.9934415494984920.01311690100301580.00655845050150788
1040.9916680689998320.01666386200033690.00833193100016844
1050.9905013512886160.01899729742276820.00949864871138411
1060.9973789654840380.005242069031924020.00262103451596201
1070.9968029017619670.006394196476065840.00319709823803292
1080.9959111371134960.008177725773007470.00408886288650374
1090.9963171685319910.00736566293601880.0036828314680094
1100.9952453661491820.009509267701636710.00475463385081835
1110.9968143696976270.006371260604746330.00318563030237317
1120.9963820682767130.007235863446573220.00361793172328661
1130.9957399641397310.008520071720538940.00426003586026947
1140.995491462331620.009017075336759920.00450853766837996
1150.9954108863771210.009178227245758180.00458911362287909
1160.9964858177620990.007028364475801740.00351418223790087
1170.9997577133325760.0004845733348484860.000242286667424243
1180.9997515252088670.0004969495822654740.000248474791132737
1190.999700918895850.0005981622083000440.000299081104150022
1200.999612212855380.0007755742892398140.000387787144619907
1210.999495587622010.00100882475597920.0005044123779896
1220.9993327381853380.001334523629324110.000667261814662053
1230.999104421185610.001791157628779630.000895578814389813
1240.9996104389756270.0007791220487460290.000389561024373015
1250.9996997362617280.0006005274765433890.000300263738271694
1260.9995946129206810.0008107741586380060.000405387079319003
1270.9994541090606460.001091781878708540.000545890939354272
1280.9994378095428530.001124380914293130.000562190457146565
1290.9997726774858040.000454645028392740.00022732251419637
1300.9997171899110950.0005656201778104280.000282810088905214
1310.9996765337671510.0006469324656987470.000323466232849374
1320.9999092067181870.000181586563625889.07932818129398e-05
1330.9998765198318780.0002469603362437410.000123480168121871
1340.9998350189094220.0003299621811568770.000164981090578438
1350.9997986399491610.0004027201016781030.000201360050839051
1360.9997532111141680.000493577771663510.000246788885831755
1370.9996673358644060.0006653282711885850.000332664135594293
1380.9996084269845060.0007831460309884370.000391573015494218
1390.9994724353741120.001055129251775660.000527564625887832
1400.9993455319265390.001308936146922190.000654468073461094
1410.9991389591896880.001722081620624980.000861040810312492
1420.9989975167999180.002004966400164790.00100248320008239
1430.9991934018259910.001613196348018710.000806598174009354
1440.9989994918634230.002001016273154750.00100050813657737
1450.9989638763268840.002072247346231840.00103612367311592
1460.9986842958144930.002631408371014320.00131570418550716
1470.9990163360768240.001967327846351960.000983663923175979
1480.9990522952298060.001895409540388460.000947704770194232
1490.9988197317550330.002360536489934930.00118026824496746
1500.9988261041035050.002347791792990570.00117389589649528
1510.9984732038589710.003053592282058820.00152679614102941
1520.9990794568197890.001841086360422870.000920543180211433
1530.9988622226100970.00227555477980490.00113777738990245
1540.9985855272460880.002828945507823990.00141447275391199
1550.9996212281785250.000757543642949610.000378771821474805
1560.9995495814852030.0009008370295931510.000450418514796575
1570.9993920284603990.001215943079202340.000607971539601172
1580.9991789126019980.001642174796005020.000821087398002508
1590.9990301026453830.001939794709233030.000969897354616517
1600.998710011436860.002579977126280560.00128998856314028
1610.9992306445403230.001538710919353330.000769355459676667
1620.9996012688028060.0007974623943874710.000398731197193736
1630.9994614276451340.001077144709731160.000538572354865582
1640.9992912379600630.001417524079873340.000708762039936672
1650.9991731375127790.001653724974441350.000826862487220676
1660.9991493990671070.001701201865786680.000850600932893341
1670.998946745832460.002106508335079870.00105325416753993
1680.9994576826934580.001084634613084180.000542317306542089
1690.9993646265477970.001270746904406940.000635373452203471
1700.9996417424901930.0007165150196145090.000358257509807254
1710.9996924295364670.0006151409270663330.000307570463533167
1720.9999165494113620.0001669011772751358.34505886375674e-05
1730.9999474819968960.0001050360062084495.25180031042246e-05
1740.9999554379158118.91241683789848e-054.45620841894924e-05
1750.9999999993320351.3359294926309e-096.67964746315452e-10
1760.9999999994811651.03766924913225e-095.18834624566125e-10
1770.9999999992537021.4925950870236e-097.462975435118e-10
1780.9999999987790242.44195252259051e-091.22097626129526e-09
1790.9999999999997495.02304801044837e-132.51152400522418e-13
1800.9999999999995938.13468128715255e-134.06734064357628e-13
1810.9999999999992061.58712824825734e-127.93564124128671e-13
1820.9999999999997624.76522172356638e-132.38261086178319e-13
1830.9999999999995249.51570650076222e-134.75785325038111e-13
1840.9999999999993931.21479186694441e-126.07395933472206e-13
1850.9999999999999754.92260418361868e-142.46130209180934e-14
1860.999999999999959.94179659333554e-144.97089829666777e-14
1870.99999999999992.00012895411011e-131.00006447705505e-13
1880.9999999999998313.37383408861243e-131.68691704430621e-13
1890.9999999999997215.57776223829856e-132.78888111914928e-13
1900.9999999999996866.27836854947543e-133.13918427473772e-13
1910.9999999999994861.02874600270246e-125.14373001351231e-13
1920.9999999999995449.12651913298708e-134.56325956649354e-13
1930.9999999999995429.16435607299174e-134.58217803649587e-13
1940.999999999999529.59308319450672e-134.79654159725336e-13
1950.9999999999996536.95000128627134e-133.47500064313567e-13
1960.9999999999998263.48804398615414e-131.74402199307707e-13
1970.9999999999997764.47514668336693e-132.23757334168347e-13
1980.9999999999995538.94228793984164e-134.47114396992082e-13
1990.9999999999990791.84197061155544e-129.20985305777722e-13
2000.9999999999987072.5856972229277e-121.29284861146385e-12
2010.9999999999973115.37720679241187e-122.68860339620594e-12
2020.9999999999947961.04080729005405e-115.20403645027024e-12
2030.9999999999897532.04950176440955e-111.02475088220477e-11
2040.9999999999842073.15855955980697e-111.57927977990348e-11
2050.999999999973615.27803334557004e-112.63901667278502e-11
2060.9999999999577198.45616378568942e-114.22808189284471e-11
2070.9999999999216121.56775866531464e-107.8387933265732e-11
2080.9999999999020381.95923067057241e-109.79615335286204e-11
2090.999999999813623.72759118865885e-101.86379559432943e-10
2100.999999999748635.02740517174054e-102.51370258587027e-10
2110.9999999995102139.79574419963918e-104.89787209981959e-10
2120.999999999106511.78697958348634e-098.9348979174317e-10
2130.9999999982520423.49591687251491e-091.74795843625745e-09
2140.9999999978534334.29313312979634e-092.14656656489817e-09
2150.9999999997177795.64441802792232e-102.82220901396116e-10
2160.9999999998283883.43223831404168e-101.71611915702084e-10
2170.9999999996456817.08638720632131e-103.54319360316065e-10
2180.9999999995363959.27210654170561e-104.6360532708528e-10
2190.9999999991672231.66555318838708e-098.32776594193542e-10
2200.9999999988068912.38621850573336e-091.19310925286668e-09
2210.9999999976694584.66108422340396e-092.33054211170198e-09
2220.9999999978295974.34080688265009e-092.17040344132504e-09
2230.999999996932116.13578013849029e-093.06789006924514e-09
2240.9999999938021481.23957045849208e-086.1978522924604e-09
2250.9999999913823061.72353881547508e-088.61769407737539e-09
2260.9999999853010422.93979165979025e-081.46989582989513e-08
2270.9999999727513645.44972722206574e-082.72486361103287e-08
2280.9999999630312567.39374873450329e-083.69687436725165e-08
2290.9999999503565739.9286853794846e-084.9643426897423e-08
2300.9999999039787661.92042468514694e-079.60212342573468e-08
2310.9999999593961748.12076513496953e-084.06038256748477e-08
2320.9999999448030161.10393968957159e-075.51969844785797e-08
2330.9999998921758252.15648350441472e-071.07824175220736e-07
2340.9999998280468123.43906375583705e-071.71953187791853e-07
2350.9999996648171426.70365715463974e-073.35182857731987e-07
2360.9999997446414145.10717172994583e-072.55358586497291e-07
2370.9999997383911265.23217748755801e-072.616088743779e-07
2380.9999994781431261.04371374834569e-065.21856874172845e-07
2390.9999989959813712.00803725850632e-061.00401862925316e-06
2400.9999980963360973.80732780517687e-061.90366390258843e-06
2410.9999974886722055.02265558975242e-062.51132779487621e-06
2420.9999955325611088.93487778314743e-064.46743889157372e-06
2430.9999955409418678.91811626571795e-064.45905813285898e-06
2440.9999916202875821.67594248361344e-058.37971241806718e-06
2450.9999841520839163.16958321688062e-051.58479160844031e-05
2460.9999707441816955.8511636610511e-052.92558183052555e-05
2470.9999812678792863.74642414273396e-051.87321207136698e-05
2480.999979429699284.11406014403585e-052.05703007201792e-05
2490.9999609639795067.80720409873029e-053.90360204936515e-05
2500.9999344450860920.0001311098278157116.55549139078555e-05
2510.9999228540694290.0001542918611414167.7145930570708e-05
2520.9998836906842160.0002326186315672230.000116309315783612
2530.9998193726024830.0003612547950337670.000180627397516883
2540.9998925452742190.0002149094515615120.000107454725780756
2550.9998435022473220.0003129955053568650.000156497752678432
2560.9997068291146920.0005863417706151970.000293170885307598
2570.9997241073576540.0005517852846910840.000275892642345542
2580.9994954123837980.001009175232404590.000504587616202296
2590.9992841603249810.001431679350036980.000715839675018489
2600.998730977998080.002538044003839430.00126902200191971
2610.9986798029359080.002640394128183750.00132019706409187
2620.9988700626637430.002259874672513750.00112993733625687
2630.9983137171079060.00337256578418720.0016862828920936
2640.9988867832181790.002226433563642850.00111321678182142
2650.9979690168915010.004061966216999010.0020309831084995
2660.9976834676801570.004633064639686450.00231653231984323
2670.9973005023487560.005398995302487580.00269949765124379
2680.9962353319025130.007529336194973630.00376466809748681
2690.9928072962679010.01438540746419830.00719270373209913
2700.9908695292260140.01826094154797210.00913047077398606
2710.9992010812663790.001597837467241920.000798918733620962
2720.9980205090591680.003958981881664550.00197949094083227
2730.9995798421724320.0008403156551350860.000420157827567543
2740.9990200328959860.001959934208027560.000979967104013782
2750.9990897657859560.001820468428087680.000910234214043841
2760.9988584527357890.002283094528421250.00114154726421063
2770.9981518549456350.003696290108729350.00184814505436467
2780.9998018629497350.0003962741005296430.000198137050264821
2790.9993307343414660.00133853131706770.000669265658533849
2800.9982075400538530.003584919892294740.00179245994614737

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.607628827969067 & 0.784742344061866 & 0.392371172030933 \tabularnewline
10 & 0.443187892194783 & 0.886375784389565 & 0.556812107805217 \tabularnewline
11 & 0.507363082962929 & 0.985273834074143 & 0.492636917037071 \tabularnewline
12 & 0.514716806062146 & 0.970566387875708 & 0.485283193937854 \tabularnewline
13 & 0.456414823276028 & 0.912829646552055 & 0.543585176723972 \tabularnewline
14 & 0.361501695295031 & 0.723003390590062 & 0.638498304704969 \tabularnewline
15 & 0.27123875718923 & 0.542477514378461 & 0.72876124281077 \tabularnewline
16 & 0.194643898865637 & 0.389287797731274 & 0.805356101134363 \tabularnewline
17 & 0.134997310654955 & 0.269994621309909 & 0.865002689345045 \tabularnewline
18 & 0.246152521564168 & 0.492305043128337 & 0.753847478435832 \tabularnewline
19 & 0.226256118727812 & 0.452512237455624 & 0.773743881272188 \tabularnewline
20 & 0.573252755667286 & 0.853494488665428 & 0.426747244332714 \tabularnewline
21 & 0.680682865877185 & 0.63863426824563 & 0.319317134122815 \tabularnewline
22 & 0.624261035429093 & 0.751477929141814 & 0.375738964570907 \tabularnewline
23 & 0.705853591312897 & 0.588292817374206 & 0.294146408687103 \tabularnewline
24 & 0.64866153113266 & 0.702676937734681 & 0.35133846886734 \tabularnewline
25 & 0.60247275817881 & 0.795054483642381 & 0.39752724182119 \tabularnewline
26 & 0.642454018448949 & 0.715091963102102 & 0.357545981551051 \tabularnewline
27 & 0.594985216828403 & 0.810029566343195 & 0.405014783171597 \tabularnewline
28 & 0.54284637299185 & 0.914307254016299 & 0.45715362700815 \tabularnewline
29 & 0.619877258879342 & 0.760245482241315 & 0.380122741120658 \tabularnewline
30 & 0.564612775300861 & 0.870774449398277 & 0.435387224699139 \tabularnewline
31 & 0.527033508605363 & 0.945932982789275 & 0.472966491394637 \tabularnewline
32 & 0.487837259164836 & 0.975674518329672 & 0.512162740835164 \tabularnewline
33 & 0.724633730095106 & 0.550732539809788 & 0.275366269904894 \tabularnewline
34 & 0.7133481143928 & 0.573303771214399 & 0.2866518856072 \tabularnewline
35 & 0.667638269168108 & 0.664723461663785 & 0.332361730831892 \tabularnewline
36 & 0.617496230597488 & 0.765007538805025 & 0.382503769402512 \tabularnewline
37 & 0.570366718309823 & 0.859266563380353 & 0.429633281690177 \tabularnewline
38 & 0.573063218343731 & 0.853873563312538 & 0.426936781656269 \tabularnewline
39 & 0.677328719801067 & 0.645342560397866 & 0.322671280198933 \tabularnewline
40 & 0.658492638240932 & 0.683014723518136 & 0.341507361759068 \tabularnewline
41 & 0.614021669646867 & 0.771956660706265 & 0.385978330353133 \tabularnewline
42 & 0.565400835865253 & 0.869198328269494 & 0.434599164134747 \tabularnewline
43 & 0.53399064832942 & 0.93201870334116 & 0.46600935167058 \tabularnewline
44 & 0.485446230357544 & 0.970892460715089 & 0.514553769642456 \tabularnewline
45 & 0.437498973600546 & 0.874997947201092 & 0.562501026399454 \tabularnewline
46 & 0.405637704587225 & 0.811275409174449 & 0.594362295412775 \tabularnewline
47 & 0.419538411189852 & 0.839076822379703 & 0.580461588810148 \tabularnewline
48 & 0.373158626140175 & 0.746317252280349 & 0.626841373859825 \tabularnewline
49 & 0.354543049447989 & 0.709086098895978 & 0.645456950552011 \tabularnewline
50 & 0.552426396121986 & 0.895147207756028 & 0.447573603878014 \tabularnewline
51 & 0.581696127151672 & 0.836607745696657 & 0.418303872848328 \tabularnewline
52 & 0.571933962538637 & 0.856132074922727 & 0.428066037461363 \tabularnewline
53 & 0.537331475524537 & 0.925337048950927 & 0.462668524475463 \tabularnewline
54 & 0.495943869991007 & 0.991887739982014 & 0.504056130008993 \tabularnewline
55 & 0.47827955331352 & 0.956559106627039 & 0.52172044668648 \tabularnewline
56 & 0.447415190065018 & 0.894830380130037 & 0.552584809934982 \tabularnewline
57 & 0.407655260350984 & 0.815310520701969 & 0.592344739649016 \tabularnewline
58 & 0.397875822238841 & 0.795751644477681 & 0.602124177761159 \tabularnewline
59 & 0.367358714208162 & 0.734717428416324 & 0.632641285791838 \tabularnewline
60 & 0.32717884130324 & 0.654357682606479 & 0.67282115869676 \tabularnewline
61 & 0.303098463712428 & 0.606196927424856 & 0.696901536287572 \tabularnewline
62 & 0.26802803742297 & 0.536056074845941 & 0.73197196257703 \tabularnewline
63 & 0.292291831520115 & 0.58458366304023 & 0.707708168479885 \tabularnewline
64 & 0.260501192988292 & 0.521002385976583 & 0.739498807011708 \tabularnewline
65 & 0.255161030114652 & 0.510322060229304 & 0.744838969885348 \tabularnewline
66 & 0.328191655917758 & 0.656383311835515 & 0.671808344082242 \tabularnewline
67 & 0.291472357427649 & 0.582944714855299 & 0.70852764257235 \tabularnewline
68 & 0.258636988985442 & 0.517273977970883 & 0.741363011014558 \tabularnewline
69 & 0.308476505176035 & 0.616953010352071 & 0.691523494823965 \tabularnewline
70 & 0.350682222247138 & 0.701364444494275 & 0.649317777752862 \tabularnewline
71 & 0.409826452045317 & 0.819652904090634 & 0.590173547954683 \tabularnewline
72 & 0.45153297611691 & 0.903065952233821 & 0.54846702388309 \tabularnewline
73 & 0.42496748738322 & 0.84993497476644 & 0.57503251261678 \tabularnewline
74 & 0.402182632576674 & 0.804365265153348 & 0.597817367423326 \tabularnewline
75 & 0.368462528962917 & 0.736925057925834 & 0.631537471037083 \tabularnewline
76 & 0.527256507423483 & 0.945486985153035 & 0.472743492576517 \tabularnewline
77 & 0.905686767766084 & 0.188626464467831 & 0.0943132322339156 \tabularnewline
78 & 0.896355683217588 & 0.207288633564823 & 0.103644316782412 \tabularnewline
79 & 0.890104606060533 & 0.219790787878933 & 0.109895393939467 \tabularnewline
80 & 0.895483394404129 & 0.209033211191742 & 0.104516605595871 \tabularnewline
81 & 0.879653884644891 & 0.240692230710218 & 0.120346115355109 \tabularnewline
82 & 0.928229956397228 & 0.143540087205543 & 0.0717700436027716 \tabularnewline
83 & 0.931851889753177 & 0.136296220493645 & 0.0681481102468225 \tabularnewline
84 & 0.918754935708277 & 0.162490128583446 & 0.0812450642917228 \tabularnewline
85 & 0.903876553437535 & 0.19224689312493 & 0.0961234465624651 \tabularnewline
86 & 0.938077789571257 & 0.123844420857487 & 0.0619222104287434 \tabularnewline
87 & 0.926717954812928 & 0.146564090374145 & 0.0732820451870724 \tabularnewline
88 & 0.913176054272235 & 0.173647891455531 & 0.0868239457277654 \tabularnewline
89 & 0.900419760034355 & 0.19916047993129 & 0.099580239965645 \tabularnewline
90 & 0.917594563815439 & 0.164810872369122 & 0.082405436184561 \tabularnewline
91 & 0.920650424104889 & 0.158699151790223 & 0.0793495758951114 \tabularnewline
92 & 0.928372662617406 & 0.143254674765189 & 0.0716273373825944 \tabularnewline
93 & 0.930745254745215 & 0.138509490509571 & 0.0692547452547853 \tabularnewline
94 & 0.925022132057692 & 0.149955735884615 & 0.0749778679423076 \tabularnewline
95 & 0.912137096517396 & 0.175725806965208 & 0.0878629034826039 \tabularnewline
96 & 0.917892496150909 & 0.164215007698181 & 0.0821075038490906 \tabularnewline
97 & 0.927939826297823 & 0.144120347404354 & 0.0720601737021772 \tabularnewline
98 & 0.976109950110661 & 0.0477800997786779 & 0.0238900498893389 \tabularnewline
99 & 0.974426874141403 & 0.0511462517171935 & 0.0255731258585968 \tabularnewline
100 & 0.993326922864407 & 0.0133461542711861 & 0.00667307713559306 \tabularnewline
101 & 0.993959747602121 & 0.0120805047957579 & 0.00604025239787894 \tabularnewline
102 & 0.992379094661572 & 0.0152418106768568 & 0.00762090533842842 \tabularnewline
103 & 0.993441549498492 & 0.0131169010030158 & 0.00655845050150788 \tabularnewline
104 & 0.991668068999832 & 0.0166638620003369 & 0.00833193100016844 \tabularnewline
105 & 0.990501351288616 & 0.0189972974227682 & 0.00949864871138411 \tabularnewline
106 & 0.997378965484038 & 0.00524206903192402 & 0.00262103451596201 \tabularnewline
107 & 0.996802901761967 & 0.00639419647606584 & 0.00319709823803292 \tabularnewline
108 & 0.995911137113496 & 0.00817772577300747 & 0.00408886288650374 \tabularnewline
109 & 0.996317168531991 & 0.0073656629360188 & 0.0036828314680094 \tabularnewline
110 & 0.995245366149182 & 0.00950926770163671 & 0.00475463385081835 \tabularnewline
111 & 0.996814369697627 & 0.00637126060474633 & 0.00318563030237317 \tabularnewline
112 & 0.996382068276713 & 0.00723586344657322 & 0.00361793172328661 \tabularnewline
113 & 0.995739964139731 & 0.00852007172053894 & 0.00426003586026947 \tabularnewline
114 & 0.99549146233162 & 0.00901707533675992 & 0.00450853766837996 \tabularnewline
115 & 0.995410886377121 & 0.00917822724575818 & 0.00458911362287909 \tabularnewline
116 & 0.996485817762099 & 0.00702836447580174 & 0.00351418223790087 \tabularnewline
117 & 0.999757713332576 & 0.000484573334848486 & 0.000242286667424243 \tabularnewline
118 & 0.999751525208867 & 0.000496949582265474 & 0.000248474791132737 \tabularnewline
119 & 0.99970091889585 & 0.000598162208300044 & 0.000299081104150022 \tabularnewline
120 & 0.99961221285538 & 0.000775574289239814 & 0.000387787144619907 \tabularnewline
121 & 0.99949558762201 & 0.0010088247559792 & 0.0005044123779896 \tabularnewline
122 & 0.999332738185338 & 0.00133452362932411 & 0.000667261814662053 \tabularnewline
123 & 0.99910442118561 & 0.00179115762877963 & 0.000895578814389813 \tabularnewline
124 & 0.999610438975627 & 0.000779122048746029 & 0.000389561024373015 \tabularnewline
125 & 0.999699736261728 & 0.000600527476543389 & 0.000300263738271694 \tabularnewline
126 & 0.999594612920681 & 0.000810774158638006 & 0.000405387079319003 \tabularnewline
127 & 0.999454109060646 & 0.00109178187870854 & 0.000545890939354272 \tabularnewline
128 & 0.999437809542853 & 0.00112438091429313 & 0.000562190457146565 \tabularnewline
129 & 0.999772677485804 & 0.00045464502839274 & 0.00022732251419637 \tabularnewline
130 & 0.999717189911095 & 0.000565620177810428 & 0.000282810088905214 \tabularnewline
131 & 0.999676533767151 & 0.000646932465698747 & 0.000323466232849374 \tabularnewline
132 & 0.999909206718187 & 0.00018158656362588 & 9.07932818129398e-05 \tabularnewline
133 & 0.999876519831878 & 0.000246960336243741 & 0.000123480168121871 \tabularnewline
134 & 0.999835018909422 & 0.000329962181156877 & 0.000164981090578438 \tabularnewline
135 & 0.999798639949161 & 0.000402720101678103 & 0.000201360050839051 \tabularnewline
136 & 0.999753211114168 & 0.00049357777166351 & 0.000246788885831755 \tabularnewline
137 & 0.999667335864406 & 0.000665328271188585 & 0.000332664135594293 \tabularnewline
138 & 0.999608426984506 & 0.000783146030988437 & 0.000391573015494218 \tabularnewline
139 & 0.999472435374112 & 0.00105512925177566 & 0.000527564625887832 \tabularnewline
140 & 0.999345531926539 & 0.00130893614692219 & 0.000654468073461094 \tabularnewline
141 & 0.999138959189688 & 0.00172208162062498 & 0.000861040810312492 \tabularnewline
142 & 0.998997516799918 & 0.00200496640016479 & 0.00100248320008239 \tabularnewline
143 & 0.999193401825991 & 0.00161319634801871 & 0.000806598174009354 \tabularnewline
144 & 0.998999491863423 & 0.00200101627315475 & 0.00100050813657737 \tabularnewline
145 & 0.998963876326884 & 0.00207224734623184 & 0.00103612367311592 \tabularnewline
146 & 0.998684295814493 & 0.00263140837101432 & 0.00131570418550716 \tabularnewline
147 & 0.999016336076824 & 0.00196732784635196 & 0.000983663923175979 \tabularnewline
148 & 0.999052295229806 & 0.00189540954038846 & 0.000947704770194232 \tabularnewline
149 & 0.998819731755033 & 0.00236053648993493 & 0.00118026824496746 \tabularnewline
150 & 0.998826104103505 & 0.00234779179299057 & 0.00117389589649528 \tabularnewline
151 & 0.998473203858971 & 0.00305359228205882 & 0.00152679614102941 \tabularnewline
152 & 0.999079456819789 & 0.00184108636042287 & 0.000920543180211433 \tabularnewline
153 & 0.998862222610097 & 0.0022755547798049 & 0.00113777738990245 \tabularnewline
154 & 0.998585527246088 & 0.00282894550782399 & 0.00141447275391199 \tabularnewline
155 & 0.999621228178525 & 0.00075754364294961 & 0.000378771821474805 \tabularnewline
156 & 0.999549581485203 & 0.000900837029593151 & 0.000450418514796575 \tabularnewline
157 & 0.999392028460399 & 0.00121594307920234 & 0.000607971539601172 \tabularnewline
158 & 0.999178912601998 & 0.00164217479600502 & 0.000821087398002508 \tabularnewline
159 & 0.999030102645383 & 0.00193979470923303 & 0.000969897354616517 \tabularnewline
160 & 0.99871001143686 & 0.00257997712628056 & 0.00128998856314028 \tabularnewline
161 & 0.999230644540323 & 0.00153871091935333 & 0.000769355459676667 \tabularnewline
162 & 0.999601268802806 & 0.000797462394387471 & 0.000398731197193736 \tabularnewline
163 & 0.999461427645134 & 0.00107714470973116 & 0.000538572354865582 \tabularnewline
164 & 0.999291237960063 & 0.00141752407987334 & 0.000708762039936672 \tabularnewline
165 & 0.999173137512779 & 0.00165372497444135 & 0.000826862487220676 \tabularnewline
166 & 0.999149399067107 & 0.00170120186578668 & 0.000850600932893341 \tabularnewline
167 & 0.99894674583246 & 0.00210650833507987 & 0.00105325416753993 \tabularnewline
168 & 0.999457682693458 & 0.00108463461308418 & 0.000542317306542089 \tabularnewline
169 & 0.999364626547797 & 0.00127074690440694 & 0.000635373452203471 \tabularnewline
170 & 0.999641742490193 & 0.000716515019614509 & 0.000358257509807254 \tabularnewline
171 & 0.999692429536467 & 0.000615140927066333 & 0.000307570463533167 \tabularnewline
172 & 0.999916549411362 & 0.000166901177275135 & 8.34505886375674e-05 \tabularnewline
173 & 0.999947481996896 & 0.000105036006208449 & 5.25180031042246e-05 \tabularnewline
174 & 0.999955437915811 & 8.91241683789848e-05 & 4.45620841894924e-05 \tabularnewline
175 & 0.999999999332035 & 1.3359294926309e-09 & 6.67964746315452e-10 \tabularnewline
176 & 0.999999999481165 & 1.03766924913225e-09 & 5.18834624566125e-10 \tabularnewline
177 & 0.999999999253702 & 1.4925950870236e-09 & 7.462975435118e-10 \tabularnewline
178 & 0.999999998779024 & 2.44195252259051e-09 & 1.22097626129526e-09 \tabularnewline
179 & 0.999999999999749 & 5.02304801044837e-13 & 2.51152400522418e-13 \tabularnewline
180 & 0.999999999999593 & 8.13468128715255e-13 & 4.06734064357628e-13 \tabularnewline
181 & 0.999999999999206 & 1.58712824825734e-12 & 7.93564124128671e-13 \tabularnewline
182 & 0.999999999999762 & 4.76522172356638e-13 & 2.38261086178319e-13 \tabularnewline
183 & 0.999999999999524 & 9.51570650076222e-13 & 4.75785325038111e-13 \tabularnewline
184 & 0.999999999999393 & 1.21479186694441e-12 & 6.07395933472206e-13 \tabularnewline
185 & 0.999999999999975 & 4.92260418361868e-14 & 2.46130209180934e-14 \tabularnewline
186 & 0.99999999999995 & 9.94179659333554e-14 & 4.97089829666777e-14 \tabularnewline
187 & 0.9999999999999 & 2.00012895411011e-13 & 1.00006447705505e-13 \tabularnewline
188 & 0.999999999999831 & 3.37383408861243e-13 & 1.68691704430621e-13 \tabularnewline
189 & 0.999999999999721 & 5.57776223829856e-13 & 2.78888111914928e-13 \tabularnewline
190 & 0.999999999999686 & 6.27836854947543e-13 & 3.13918427473772e-13 \tabularnewline
191 & 0.999999999999486 & 1.02874600270246e-12 & 5.14373001351231e-13 \tabularnewline
192 & 0.999999999999544 & 9.12651913298708e-13 & 4.56325956649354e-13 \tabularnewline
193 & 0.999999999999542 & 9.16435607299174e-13 & 4.58217803649587e-13 \tabularnewline
194 & 0.99999999999952 & 9.59308319450672e-13 & 4.79654159725336e-13 \tabularnewline
195 & 0.999999999999653 & 6.95000128627134e-13 & 3.47500064313567e-13 \tabularnewline
196 & 0.999999999999826 & 3.48804398615414e-13 & 1.74402199307707e-13 \tabularnewline
197 & 0.999999999999776 & 4.47514668336693e-13 & 2.23757334168347e-13 \tabularnewline
198 & 0.999999999999553 & 8.94228793984164e-13 & 4.47114396992082e-13 \tabularnewline
199 & 0.999999999999079 & 1.84197061155544e-12 & 9.20985305777722e-13 \tabularnewline
200 & 0.999999999998707 & 2.5856972229277e-12 & 1.29284861146385e-12 \tabularnewline
201 & 0.999999999997311 & 5.37720679241187e-12 & 2.68860339620594e-12 \tabularnewline
202 & 0.999999999994796 & 1.04080729005405e-11 & 5.20403645027024e-12 \tabularnewline
203 & 0.999999999989753 & 2.04950176440955e-11 & 1.02475088220477e-11 \tabularnewline
204 & 0.999999999984207 & 3.15855955980697e-11 & 1.57927977990348e-11 \tabularnewline
205 & 0.99999999997361 & 5.27803334557004e-11 & 2.63901667278502e-11 \tabularnewline
206 & 0.999999999957719 & 8.45616378568942e-11 & 4.22808189284471e-11 \tabularnewline
207 & 0.999999999921612 & 1.56775866531464e-10 & 7.8387933265732e-11 \tabularnewline
208 & 0.999999999902038 & 1.95923067057241e-10 & 9.79615335286204e-11 \tabularnewline
209 & 0.99999999981362 & 3.72759118865885e-10 & 1.86379559432943e-10 \tabularnewline
210 & 0.99999999974863 & 5.02740517174054e-10 & 2.51370258587027e-10 \tabularnewline
211 & 0.999999999510213 & 9.79574419963918e-10 & 4.89787209981959e-10 \tabularnewline
212 & 0.99999999910651 & 1.78697958348634e-09 & 8.9348979174317e-10 \tabularnewline
213 & 0.999999998252042 & 3.49591687251491e-09 & 1.74795843625745e-09 \tabularnewline
214 & 0.999999997853433 & 4.29313312979634e-09 & 2.14656656489817e-09 \tabularnewline
215 & 0.999999999717779 & 5.64441802792232e-10 & 2.82220901396116e-10 \tabularnewline
216 & 0.999999999828388 & 3.43223831404168e-10 & 1.71611915702084e-10 \tabularnewline
217 & 0.999999999645681 & 7.08638720632131e-10 & 3.54319360316065e-10 \tabularnewline
218 & 0.999999999536395 & 9.27210654170561e-10 & 4.6360532708528e-10 \tabularnewline
219 & 0.999999999167223 & 1.66555318838708e-09 & 8.32776594193542e-10 \tabularnewline
220 & 0.999999998806891 & 2.38621850573336e-09 & 1.19310925286668e-09 \tabularnewline
221 & 0.999999997669458 & 4.66108422340396e-09 & 2.33054211170198e-09 \tabularnewline
222 & 0.999999997829597 & 4.34080688265009e-09 & 2.17040344132504e-09 \tabularnewline
223 & 0.99999999693211 & 6.13578013849029e-09 & 3.06789006924514e-09 \tabularnewline
224 & 0.999999993802148 & 1.23957045849208e-08 & 6.1978522924604e-09 \tabularnewline
225 & 0.999999991382306 & 1.72353881547508e-08 & 8.61769407737539e-09 \tabularnewline
226 & 0.999999985301042 & 2.93979165979025e-08 & 1.46989582989513e-08 \tabularnewline
227 & 0.999999972751364 & 5.44972722206574e-08 & 2.72486361103287e-08 \tabularnewline
228 & 0.999999963031256 & 7.39374873450329e-08 & 3.69687436725165e-08 \tabularnewline
229 & 0.999999950356573 & 9.9286853794846e-08 & 4.9643426897423e-08 \tabularnewline
230 & 0.999999903978766 & 1.92042468514694e-07 & 9.60212342573468e-08 \tabularnewline
231 & 0.999999959396174 & 8.12076513496953e-08 & 4.06038256748477e-08 \tabularnewline
232 & 0.999999944803016 & 1.10393968957159e-07 & 5.51969844785797e-08 \tabularnewline
233 & 0.999999892175825 & 2.15648350441472e-07 & 1.07824175220736e-07 \tabularnewline
234 & 0.999999828046812 & 3.43906375583705e-07 & 1.71953187791853e-07 \tabularnewline
235 & 0.999999664817142 & 6.70365715463974e-07 & 3.35182857731987e-07 \tabularnewline
236 & 0.999999744641414 & 5.10717172994583e-07 & 2.55358586497291e-07 \tabularnewline
237 & 0.999999738391126 & 5.23217748755801e-07 & 2.616088743779e-07 \tabularnewline
238 & 0.999999478143126 & 1.04371374834569e-06 & 5.21856874172845e-07 \tabularnewline
239 & 0.999998995981371 & 2.00803725850632e-06 & 1.00401862925316e-06 \tabularnewline
240 & 0.999998096336097 & 3.80732780517687e-06 & 1.90366390258843e-06 \tabularnewline
241 & 0.999997488672205 & 5.02265558975242e-06 & 2.51132779487621e-06 \tabularnewline
242 & 0.999995532561108 & 8.93487778314743e-06 & 4.46743889157372e-06 \tabularnewline
243 & 0.999995540941867 & 8.91811626571795e-06 & 4.45905813285898e-06 \tabularnewline
244 & 0.999991620287582 & 1.67594248361344e-05 & 8.37971241806718e-06 \tabularnewline
245 & 0.999984152083916 & 3.16958321688062e-05 & 1.58479160844031e-05 \tabularnewline
246 & 0.999970744181695 & 5.8511636610511e-05 & 2.92558183052555e-05 \tabularnewline
247 & 0.999981267879286 & 3.74642414273396e-05 & 1.87321207136698e-05 \tabularnewline
248 & 0.99997942969928 & 4.11406014403585e-05 & 2.05703007201792e-05 \tabularnewline
249 & 0.999960963979506 & 7.80720409873029e-05 & 3.90360204936515e-05 \tabularnewline
250 & 0.999934445086092 & 0.000131109827815711 & 6.55549139078555e-05 \tabularnewline
251 & 0.999922854069429 & 0.000154291861141416 & 7.7145930570708e-05 \tabularnewline
252 & 0.999883690684216 & 0.000232618631567223 & 0.000116309315783612 \tabularnewline
253 & 0.999819372602483 & 0.000361254795033767 & 0.000180627397516883 \tabularnewline
254 & 0.999892545274219 & 0.000214909451561512 & 0.000107454725780756 \tabularnewline
255 & 0.999843502247322 & 0.000312995505356865 & 0.000156497752678432 \tabularnewline
256 & 0.999706829114692 & 0.000586341770615197 & 0.000293170885307598 \tabularnewline
257 & 0.999724107357654 & 0.000551785284691084 & 0.000275892642345542 \tabularnewline
258 & 0.999495412383798 & 0.00100917523240459 & 0.000504587616202296 \tabularnewline
259 & 0.999284160324981 & 0.00143167935003698 & 0.000715839675018489 \tabularnewline
260 & 0.99873097799808 & 0.00253804400383943 & 0.00126902200191971 \tabularnewline
261 & 0.998679802935908 & 0.00264039412818375 & 0.00132019706409187 \tabularnewline
262 & 0.998870062663743 & 0.00225987467251375 & 0.00112993733625687 \tabularnewline
263 & 0.998313717107906 & 0.0033725657841872 & 0.0016862828920936 \tabularnewline
264 & 0.998886783218179 & 0.00222643356364285 & 0.00111321678182142 \tabularnewline
265 & 0.997969016891501 & 0.00406196621699901 & 0.0020309831084995 \tabularnewline
266 & 0.997683467680157 & 0.00463306463968645 & 0.00231653231984323 \tabularnewline
267 & 0.997300502348756 & 0.00539899530248758 & 0.00269949765124379 \tabularnewline
268 & 0.996235331902513 & 0.00752933619497363 & 0.00376466809748681 \tabularnewline
269 & 0.992807296267901 & 0.0143854074641983 & 0.00719270373209913 \tabularnewline
270 & 0.990869529226014 & 0.0182609415479721 & 0.00913047077398606 \tabularnewline
271 & 0.999201081266379 & 0.00159783746724192 & 0.000798918733620962 \tabularnewline
272 & 0.998020509059168 & 0.00395898188166455 & 0.00197949094083227 \tabularnewline
273 & 0.999579842172432 & 0.000840315655135086 & 0.000420157827567543 \tabularnewline
274 & 0.999020032895986 & 0.00195993420802756 & 0.000979967104013782 \tabularnewline
275 & 0.999089765785956 & 0.00182046842808768 & 0.000910234214043841 \tabularnewline
276 & 0.998858452735789 & 0.00228309452842125 & 0.00114154726421063 \tabularnewline
277 & 0.998151854945635 & 0.00369629010872935 & 0.00184814505436467 \tabularnewline
278 & 0.999801862949735 & 0.000396274100529643 & 0.000198137050264821 \tabularnewline
279 & 0.999330734341466 & 0.0013385313170677 & 0.000669265658533849 \tabularnewline
280 & 0.998207540053853 & 0.00358491989229474 & 0.00179245994614737 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197292&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]9[/C][C]0.607628827969067[/C][C]0.784742344061866[/C][C]0.392371172030933[/C][/ROW]
[ROW][C]10[/C][C]0.443187892194783[/C][C]0.886375784389565[/C][C]0.556812107805217[/C][/ROW]
[ROW][C]11[/C][C]0.507363082962929[/C][C]0.985273834074143[/C][C]0.492636917037071[/C][/ROW]
[ROW][C]12[/C][C]0.514716806062146[/C][C]0.970566387875708[/C][C]0.485283193937854[/C][/ROW]
[ROW][C]13[/C][C]0.456414823276028[/C][C]0.912829646552055[/C][C]0.543585176723972[/C][/ROW]
[ROW][C]14[/C][C]0.361501695295031[/C][C]0.723003390590062[/C][C]0.638498304704969[/C][/ROW]
[ROW][C]15[/C][C]0.27123875718923[/C][C]0.542477514378461[/C][C]0.72876124281077[/C][/ROW]
[ROW][C]16[/C][C]0.194643898865637[/C][C]0.389287797731274[/C][C]0.805356101134363[/C][/ROW]
[ROW][C]17[/C][C]0.134997310654955[/C][C]0.269994621309909[/C][C]0.865002689345045[/C][/ROW]
[ROW][C]18[/C][C]0.246152521564168[/C][C]0.492305043128337[/C][C]0.753847478435832[/C][/ROW]
[ROW][C]19[/C][C]0.226256118727812[/C][C]0.452512237455624[/C][C]0.773743881272188[/C][/ROW]
[ROW][C]20[/C][C]0.573252755667286[/C][C]0.853494488665428[/C][C]0.426747244332714[/C][/ROW]
[ROW][C]21[/C][C]0.680682865877185[/C][C]0.63863426824563[/C][C]0.319317134122815[/C][/ROW]
[ROW][C]22[/C][C]0.624261035429093[/C][C]0.751477929141814[/C][C]0.375738964570907[/C][/ROW]
[ROW][C]23[/C][C]0.705853591312897[/C][C]0.588292817374206[/C][C]0.294146408687103[/C][/ROW]
[ROW][C]24[/C][C]0.64866153113266[/C][C]0.702676937734681[/C][C]0.35133846886734[/C][/ROW]
[ROW][C]25[/C][C]0.60247275817881[/C][C]0.795054483642381[/C][C]0.39752724182119[/C][/ROW]
[ROW][C]26[/C][C]0.642454018448949[/C][C]0.715091963102102[/C][C]0.357545981551051[/C][/ROW]
[ROW][C]27[/C][C]0.594985216828403[/C][C]0.810029566343195[/C][C]0.405014783171597[/C][/ROW]
[ROW][C]28[/C][C]0.54284637299185[/C][C]0.914307254016299[/C][C]0.45715362700815[/C][/ROW]
[ROW][C]29[/C][C]0.619877258879342[/C][C]0.760245482241315[/C][C]0.380122741120658[/C][/ROW]
[ROW][C]30[/C][C]0.564612775300861[/C][C]0.870774449398277[/C][C]0.435387224699139[/C][/ROW]
[ROW][C]31[/C][C]0.527033508605363[/C][C]0.945932982789275[/C][C]0.472966491394637[/C][/ROW]
[ROW][C]32[/C][C]0.487837259164836[/C][C]0.975674518329672[/C][C]0.512162740835164[/C][/ROW]
[ROW][C]33[/C][C]0.724633730095106[/C][C]0.550732539809788[/C][C]0.275366269904894[/C][/ROW]
[ROW][C]34[/C][C]0.7133481143928[/C][C]0.573303771214399[/C][C]0.2866518856072[/C][/ROW]
[ROW][C]35[/C][C]0.667638269168108[/C][C]0.664723461663785[/C][C]0.332361730831892[/C][/ROW]
[ROW][C]36[/C][C]0.617496230597488[/C][C]0.765007538805025[/C][C]0.382503769402512[/C][/ROW]
[ROW][C]37[/C][C]0.570366718309823[/C][C]0.859266563380353[/C][C]0.429633281690177[/C][/ROW]
[ROW][C]38[/C][C]0.573063218343731[/C][C]0.853873563312538[/C][C]0.426936781656269[/C][/ROW]
[ROW][C]39[/C][C]0.677328719801067[/C][C]0.645342560397866[/C][C]0.322671280198933[/C][/ROW]
[ROW][C]40[/C][C]0.658492638240932[/C][C]0.683014723518136[/C][C]0.341507361759068[/C][/ROW]
[ROW][C]41[/C][C]0.614021669646867[/C][C]0.771956660706265[/C][C]0.385978330353133[/C][/ROW]
[ROW][C]42[/C][C]0.565400835865253[/C][C]0.869198328269494[/C][C]0.434599164134747[/C][/ROW]
[ROW][C]43[/C][C]0.53399064832942[/C][C]0.93201870334116[/C][C]0.46600935167058[/C][/ROW]
[ROW][C]44[/C][C]0.485446230357544[/C][C]0.970892460715089[/C][C]0.514553769642456[/C][/ROW]
[ROW][C]45[/C][C]0.437498973600546[/C][C]0.874997947201092[/C][C]0.562501026399454[/C][/ROW]
[ROW][C]46[/C][C]0.405637704587225[/C][C]0.811275409174449[/C][C]0.594362295412775[/C][/ROW]
[ROW][C]47[/C][C]0.419538411189852[/C][C]0.839076822379703[/C][C]0.580461588810148[/C][/ROW]
[ROW][C]48[/C][C]0.373158626140175[/C][C]0.746317252280349[/C][C]0.626841373859825[/C][/ROW]
[ROW][C]49[/C][C]0.354543049447989[/C][C]0.709086098895978[/C][C]0.645456950552011[/C][/ROW]
[ROW][C]50[/C][C]0.552426396121986[/C][C]0.895147207756028[/C][C]0.447573603878014[/C][/ROW]
[ROW][C]51[/C][C]0.581696127151672[/C][C]0.836607745696657[/C][C]0.418303872848328[/C][/ROW]
[ROW][C]52[/C][C]0.571933962538637[/C][C]0.856132074922727[/C][C]0.428066037461363[/C][/ROW]
[ROW][C]53[/C][C]0.537331475524537[/C][C]0.925337048950927[/C][C]0.462668524475463[/C][/ROW]
[ROW][C]54[/C][C]0.495943869991007[/C][C]0.991887739982014[/C][C]0.504056130008993[/C][/ROW]
[ROW][C]55[/C][C]0.47827955331352[/C][C]0.956559106627039[/C][C]0.52172044668648[/C][/ROW]
[ROW][C]56[/C][C]0.447415190065018[/C][C]0.894830380130037[/C][C]0.552584809934982[/C][/ROW]
[ROW][C]57[/C][C]0.407655260350984[/C][C]0.815310520701969[/C][C]0.592344739649016[/C][/ROW]
[ROW][C]58[/C][C]0.397875822238841[/C][C]0.795751644477681[/C][C]0.602124177761159[/C][/ROW]
[ROW][C]59[/C][C]0.367358714208162[/C][C]0.734717428416324[/C][C]0.632641285791838[/C][/ROW]
[ROW][C]60[/C][C]0.32717884130324[/C][C]0.654357682606479[/C][C]0.67282115869676[/C][/ROW]
[ROW][C]61[/C][C]0.303098463712428[/C][C]0.606196927424856[/C][C]0.696901536287572[/C][/ROW]
[ROW][C]62[/C][C]0.26802803742297[/C][C]0.536056074845941[/C][C]0.73197196257703[/C][/ROW]
[ROW][C]63[/C][C]0.292291831520115[/C][C]0.58458366304023[/C][C]0.707708168479885[/C][/ROW]
[ROW][C]64[/C][C]0.260501192988292[/C][C]0.521002385976583[/C][C]0.739498807011708[/C][/ROW]
[ROW][C]65[/C][C]0.255161030114652[/C][C]0.510322060229304[/C][C]0.744838969885348[/C][/ROW]
[ROW][C]66[/C][C]0.328191655917758[/C][C]0.656383311835515[/C][C]0.671808344082242[/C][/ROW]
[ROW][C]67[/C][C]0.291472357427649[/C][C]0.582944714855299[/C][C]0.70852764257235[/C][/ROW]
[ROW][C]68[/C][C]0.258636988985442[/C][C]0.517273977970883[/C][C]0.741363011014558[/C][/ROW]
[ROW][C]69[/C][C]0.308476505176035[/C][C]0.616953010352071[/C][C]0.691523494823965[/C][/ROW]
[ROW][C]70[/C][C]0.350682222247138[/C][C]0.701364444494275[/C][C]0.649317777752862[/C][/ROW]
[ROW][C]71[/C][C]0.409826452045317[/C][C]0.819652904090634[/C][C]0.590173547954683[/C][/ROW]
[ROW][C]72[/C][C]0.45153297611691[/C][C]0.903065952233821[/C][C]0.54846702388309[/C][/ROW]
[ROW][C]73[/C][C]0.42496748738322[/C][C]0.84993497476644[/C][C]0.57503251261678[/C][/ROW]
[ROW][C]74[/C][C]0.402182632576674[/C][C]0.804365265153348[/C][C]0.597817367423326[/C][/ROW]
[ROW][C]75[/C][C]0.368462528962917[/C][C]0.736925057925834[/C][C]0.631537471037083[/C][/ROW]
[ROW][C]76[/C][C]0.527256507423483[/C][C]0.945486985153035[/C][C]0.472743492576517[/C][/ROW]
[ROW][C]77[/C][C]0.905686767766084[/C][C]0.188626464467831[/C][C]0.0943132322339156[/C][/ROW]
[ROW][C]78[/C][C]0.896355683217588[/C][C]0.207288633564823[/C][C]0.103644316782412[/C][/ROW]
[ROW][C]79[/C][C]0.890104606060533[/C][C]0.219790787878933[/C][C]0.109895393939467[/C][/ROW]
[ROW][C]80[/C][C]0.895483394404129[/C][C]0.209033211191742[/C][C]0.104516605595871[/C][/ROW]
[ROW][C]81[/C][C]0.879653884644891[/C][C]0.240692230710218[/C][C]0.120346115355109[/C][/ROW]
[ROW][C]82[/C][C]0.928229956397228[/C][C]0.143540087205543[/C][C]0.0717700436027716[/C][/ROW]
[ROW][C]83[/C][C]0.931851889753177[/C][C]0.136296220493645[/C][C]0.0681481102468225[/C][/ROW]
[ROW][C]84[/C][C]0.918754935708277[/C][C]0.162490128583446[/C][C]0.0812450642917228[/C][/ROW]
[ROW][C]85[/C][C]0.903876553437535[/C][C]0.19224689312493[/C][C]0.0961234465624651[/C][/ROW]
[ROW][C]86[/C][C]0.938077789571257[/C][C]0.123844420857487[/C][C]0.0619222104287434[/C][/ROW]
[ROW][C]87[/C][C]0.926717954812928[/C][C]0.146564090374145[/C][C]0.0732820451870724[/C][/ROW]
[ROW][C]88[/C][C]0.913176054272235[/C][C]0.173647891455531[/C][C]0.0868239457277654[/C][/ROW]
[ROW][C]89[/C][C]0.900419760034355[/C][C]0.19916047993129[/C][C]0.099580239965645[/C][/ROW]
[ROW][C]90[/C][C]0.917594563815439[/C][C]0.164810872369122[/C][C]0.082405436184561[/C][/ROW]
[ROW][C]91[/C][C]0.920650424104889[/C][C]0.158699151790223[/C][C]0.0793495758951114[/C][/ROW]
[ROW][C]92[/C][C]0.928372662617406[/C][C]0.143254674765189[/C][C]0.0716273373825944[/C][/ROW]
[ROW][C]93[/C][C]0.930745254745215[/C][C]0.138509490509571[/C][C]0.0692547452547853[/C][/ROW]
[ROW][C]94[/C][C]0.925022132057692[/C][C]0.149955735884615[/C][C]0.0749778679423076[/C][/ROW]
[ROW][C]95[/C][C]0.912137096517396[/C][C]0.175725806965208[/C][C]0.0878629034826039[/C][/ROW]
[ROW][C]96[/C][C]0.917892496150909[/C][C]0.164215007698181[/C][C]0.0821075038490906[/C][/ROW]
[ROW][C]97[/C][C]0.927939826297823[/C][C]0.144120347404354[/C][C]0.0720601737021772[/C][/ROW]
[ROW][C]98[/C][C]0.976109950110661[/C][C]0.0477800997786779[/C][C]0.0238900498893389[/C][/ROW]
[ROW][C]99[/C][C]0.974426874141403[/C][C]0.0511462517171935[/C][C]0.0255731258585968[/C][/ROW]
[ROW][C]100[/C][C]0.993326922864407[/C][C]0.0133461542711861[/C][C]0.00667307713559306[/C][/ROW]
[ROW][C]101[/C][C]0.993959747602121[/C][C]0.0120805047957579[/C][C]0.00604025239787894[/C][/ROW]
[ROW][C]102[/C][C]0.992379094661572[/C][C]0.0152418106768568[/C][C]0.00762090533842842[/C][/ROW]
[ROW][C]103[/C][C]0.993441549498492[/C][C]0.0131169010030158[/C][C]0.00655845050150788[/C][/ROW]
[ROW][C]104[/C][C]0.991668068999832[/C][C]0.0166638620003369[/C][C]0.00833193100016844[/C][/ROW]
[ROW][C]105[/C][C]0.990501351288616[/C][C]0.0189972974227682[/C][C]0.00949864871138411[/C][/ROW]
[ROW][C]106[/C][C]0.997378965484038[/C][C]0.00524206903192402[/C][C]0.00262103451596201[/C][/ROW]
[ROW][C]107[/C][C]0.996802901761967[/C][C]0.00639419647606584[/C][C]0.00319709823803292[/C][/ROW]
[ROW][C]108[/C][C]0.995911137113496[/C][C]0.00817772577300747[/C][C]0.00408886288650374[/C][/ROW]
[ROW][C]109[/C][C]0.996317168531991[/C][C]0.0073656629360188[/C][C]0.0036828314680094[/C][/ROW]
[ROW][C]110[/C][C]0.995245366149182[/C][C]0.00950926770163671[/C][C]0.00475463385081835[/C][/ROW]
[ROW][C]111[/C][C]0.996814369697627[/C][C]0.00637126060474633[/C][C]0.00318563030237317[/C][/ROW]
[ROW][C]112[/C][C]0.996382068276713[/C][C]0.00723586344657322[/C][C]0.00361793172328661[/C][/ROW]
[ROW][C]113[/C][C]0.995739964139731[/C][C]0.00852007172053894[/C][C]0.00426003586026947[/C][/ROW]
[ROW][C]114[/C][C]0.99549146233162[/C][C]0.00901707533675992[/C][C]0.00450853766837996[/C][/ROW]
[ROW][C]115[/C][C]0.995410886377121[/C][C]0.00917822724575818[/C][C]0.00458911362287909[/C][/ROW]
[ROW][C]116[/C][C]0.996485817762099[/C][C]0.00702836447580174[/C][C]0.00351418223790087[/C][/ROW]
[ROW][C]117[/C][C]0.999757713332576[/C][C]0.000484573334848486[/C][C]0.000242286667424243[/C][/ROW]
[ROW][C]118[/C][C]0.999751525208867[/C][C]0.000496949582265474[/C][C]0.000248474791132737[/C][/ROW]
[ROW][C]119[/C][C]0.99970091889585[/C][C]0.000598162208300044[/C][C]0.000299081104150022[/C][/ROW]
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[ROW][C]186[/C][C]0.99999999999995[/C][C]9.94179659333554e-14[/C][C]4.97089829666777e-14[/C][/ROW]
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[ROW][C]190[/C][C]0.999999999999686[/C][C]6.27836854947543e-13[/C][C]3.13918427473772e-13[/C][/ROW]
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[ROW][C]217[/C][C]0.999999999645681[/C][C]7.08638720632131e-10[/C][C]3.54319360316065e-10[/C][/ROW]
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[ROW][C]219[/C][C]0.999999999167223[/C][C]1.66555318838708e-09[/C][C]8.32776594193542e-10[/C][/ROW]
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[ROW][C]221[/C][C]0.999999997669458[/C][C]4.66108422340396e-09[/C][C]2.33054211170198e-09[/C][/ROW]
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[ROW][C]261[/C][C]0.998679802935908[/C][C]0.00264039412818375[/C][C]0.00132019706409187[/C][/ROW]
[ROW][C]262[/C][C]0.998870062663743[/C][C]0.00225987467251375[/C][C]0.00112993733625687[/C][/ROW]
[ROW][C]263[/C][C]0.998313717107906[/C][C]0.0033725657841872[/C][C]0.0016862828920936[/C][/ROW]
[ROW][C]264[/C][C]0.998886783218179[/C][C]0.00222643356364285[/C][C]0.00111321678182142[/C][/ROW]
[ROW][C]265[/C][C]0.997969016891501[/C][C]0.00406196621699901[/C][C]0.0020309831084995[/C][/ROW]
[ROW][C]266[/C][C]0.997683467680157[/C][C]0.00463306463968645[/C][C]0.00231653231984323[/C][/ROW]
[ROW][C]267[/C][C]0.997300502348756[/C][C]0.00539899530248758[/C][C]0.00269949765124379[/C][/ROW]
[ROW][C]268[/C][C]0.996235331902513[/C][C]0.00752933619497363[/C][C]0.00376466809748681[/C][/ROW]
[ROW][C]269[/C][C]0.992807296267901[/C][C]0.0143854074641983[/C][C]0.00719270373209913[/C][/ROW]
[ROW][C]270[/C][C]0.990869529226014[/C][C]0.0182609415479721[/C][C]0.00913047077398606[/C][/ROW]
[ROW][C]271[/C][C]0.999201081266379[/C][C]0.00159783746724192[/C][C]0.000798918733620962[/C][/ROW]
[ROW][C]272[/C][C]0.998020509059168[/C][C]0.00395898188166455[/C][C]0.00197949094083227[/C][/ROW]
[ROW][C]273[/C][C]0.999579842172432[/C][C]0.000840315655135086[/C][C]0.000420157827567543[/C][/ROW]
[ROW][C]274[/C][C]0.999020032895986[/C][C]0.00195993420802756[/C][C]0.000979967104013782[/C][/ROW]
[ROW][C]275[/C][C]0.999089765785956[/C][C]0.00182046842808768[/C][C]0.000910234214043841[/C][/ROW]
[ROW][C]276[/C][C]0.998858452735789[/C][C]0.00228309452842125[/C][C]0.00114154726421063[/C][/ROW]
[ROW][C]277[/C][C]0.998151854945635[/C][C]0.00369629010872935[/C][C]0.00184814505436467[/C][/ROW]
[ROW][C]278[/C][C]0.999801862949735[/C][C]0.000396274100529643[/C][C]0.000198137050264821[/C][/ROW]
[ROW][C]279[/C][C]0.999330734341466[/C][C]0.0013385313170677[/C][C]0.000669265658533849[/C][/ROW]
[ROW][C]280[/C][C]0.998207540053853[/C][C]0.00358491989229474[/C][C]0.00179245994614737[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197292&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197292&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.6076288279690670.7847423440618660.392371172030933
100.4431878921947830.8863757843895650.556812107805217
110.5073630829629290.9852738340741430.492636917037071
120.5147168060621460.9705663878757080.485283193937854
130.4564148232760280.9128296465520550.543585176723972
140.3615016952950310.7230033905900620.638498304704969
150.271238757189230.5424775143784610.72876124281077
160.1946438988656370.3892877977312740.805356101134363
170.1349973106549550.2699946213099090.865002689345045
180.2461525215641680.4923050431283370.753847478435832
190.2262561187278120.4525122374556240.773743881272188
200.5732527556672860.8534944886654280.426747244332714
210.6806828658771850.638634268245630.319317134122815
220.6242610354290930.7514779291418140.375738964570907
230.7058535913128970.5882928173742060.294146408687103
240.648661531132660.7026769377346810.35133846886734
250.602472758178810.7950544836423810.39752724182119
260.6424540184489490.7150919631021020.357545981551051
270.5949852168284030.8100295663431950.405014783171597
280.542846372991850.9143072540162990.45715362700815
290.6198772588793420.7602454822413150.380122741120658
300.5646127753008610.8707744493982770.435387224699139
310.5270335086053630.9459329827892750.472966491394637
320.4878372591648360.9756745183296720.512162740835164
330.7246337300951060.5507325398097880.275366269904894
340.71334811439280.5733037712143990.2866518856072
350.6676382691681080.6647234616637850.332361730831892
360.6174962305974880.7650075388050250.382503769402512
370.5703667183098230.8592665633803530.429633281690177
380.5730632183437310.8538735633125380.426936781656269
390.6773287198010670.6453425603978660.322671280198933
400.6584926382409320.6830147235181360.341507361759068
410.6140216696468670.7719566607062650.385978330353133
420.5654008358652530.8691983282694940.434599164134747
430.533990648329420.932018703341160.46600935167058
440.4854462303575440.9708924607150890.514553769642456
450.4374989736005460.8749979472010920.562501026399454
460.4056377045872250.8112754091744490.594362295412775
470.4195384111898520.8390768223797030.580461588810148
480.3731586261401750.7463172522803490.626841373859825
490.3545430494479890.7090860988959780.645456950552011
500.5524263961219860.8951472077560280.447573603878014
510.5816961271516720.8366077456966570.418303872848328
520.5719339625386370.8561320749227270.428066037461363
530.5373314755245370.9253370489509270.462668524475463
540.4959438699910070.9918877399820140.504056130008993
550.478279553313520.9565591066270390.52172044668648
560.4474151900650180.8948303801300370.552584809934982
570.4076552603509840.8153105207019690.592344739649016
580.3978758222388410.7957516444776810.602124177761159
590.3673587142081620.7347174284163240.632641285791838
600.327178841303240.6543576826064790.67282115869676
610.3030984637124280.6061969274248560.696901536287572
620.268028037422970.5360560748459410.73197196257703
630.2922918315201150.584583663040230.707708168479885
640.2605011929882920.5210023859765830.739498807011708
650.2551610301146520.5103220602293040.744838969885348
660.3281916559177580.6563833118355150.671808344082242
670.2914723574276490.5829447148552990.70852764257235
680.2586369889854420.5172739779708830.741363011014558
690.3084765051760350.6169530103520710.691523494823965
700.3506822222471380.7013644444942750.649317777752862
710.4098264520453170.8196529040906340.590173547954683
720.451532976116910.9030659522338210.54846702388309
730.424967487383220.849934974766440.57503251261678
740.4021826325766740.8043652651533480.597817367423326
750.3684625289629170.7369250579258340.631537471037083
760.5272565074234830.9454869851530350.472743492576517
770.9056867677660840.1886264644678310.0943132322339156
780.8963556832175880.2072886335648230.103644316782412
790.8901046060605330.2197907878789330.109895393939467
800.8954833944041290.2090332111917420.104516605595871
810.8796538846448910.2406922307102180.120346115355109
820.9282299563972280.1435400872055430.0717700436027716
830.9318518897531770.1362962204936450.0681481102468225
840.9187549357082770.1624901285834460.0812450642917228
850.9038765534375350.192246893124930.0961234465624651
860.9380777895712570.1238444208574870.0619222104287434
870.9267179548129280.1465640903741450.0732820451870724
880.9131760542722350.1736478914555310.0868239457277654
890.9004197600343550.199160479931290.099580239965645
900.9175945638154390.1648108723691220.082405436184561
910.9206504241048890.1586991517902230.0793495758951114
920.9283726626174060.1432546747651890.0716273373825944
930.9307452547452150.1385094905095710.0692547452547853
940.9250221320576920.1499557358846150.0749778679423076
950.9121370965173960.1757258069652080.0878629034826039
960.9178924961509090.1642150076981810.0821075038490906
970.9279398262978230.1441203474043540.0720601737021772
980.9761099501106610.04778009977867790.0238900498893389
990.9744268741414030.05114625171719350.0255731258585968
1000.9933269228644070.01334615427118610.00667307713559306
1010.9939597476021210.01208050479575790.00604025239787894
1020.9923790946615720.01524181067685680.00762090533842842
1030.9934415494984920.01311690100301580.00655845050150788
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1050.9905013512886160.01899729742276820.00949864871138411
1060.9973789654840380.005242069031924020.00262103451596201
1070.9968029017619670.006394196476065840.00319709823803292
1080.9959111371134960.008177725773007470.00408886288650374
1090.9963171685319910.00736566293601880.0036828314680094
1100.9952453661491820.009509267701636710.00475463385081835
1110.9968143696976270.006371260604746330.00318563030237317
1120.9963820682767130.007235863446573220.00361793172328661
1130.9957399641397310.008520071720538940.00426003586026947
1140.995491462331620.009017075336759920.00450853766837996
1150.9954108863771210.009178227245758180.00458911362287909
1160.9964858177620990.007028364475801740.00351418223790087
1170.9997577133325760.0004845733348484860.000242286667424243
1180.9997515252088670.0004969495822654740.000248474791132737
1190.999700918895850.0005981622083000440.000299081104150022
1200.999612212855380.0007755742892398140.000387787144619907
1210.999495587622010.00100882475597920.0005044123779896
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1320.9999092067181870.000181586563625889.07932818129398e-05
1330.9998765198318780.0002469603362437410.000123480168121871
1340.9998350189094220.0003299621811568770.000164981090578438
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1400.9993455319265390.001308936146922190.000654468073461094
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1450.9989638763268840.002072247346231840.00103612367311592
1460.9986842958144930.002631408371014320.00131570418550716
1470.9990163360768240.001967327846351960.000983663923175979
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1490.9988197317550330.002360536489934930.00118026824496746
1500.9988261041035050.002347791792990570.00117389589649528
1510.9984732038589710.003053592282058820.00152679614102941
1520.9990794568197890.001841086360422870.000920543180211433
1530.9988622226100970.00227555477980490.00113777738990245
1540.9985855272460880.002828945507823990.00141447275391199
1550.9996212281785250.000757543642949610.000378771821474805
1560.9995495814852030.0009008370295931510.000450418514796575
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1590.9990301026453830.001939794709233030.000969897354616517
1600.998710011436860.002579977126280560.00128998856314028
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1630.9994614276451340.001077144709731160.000538572354865582
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1710.9996924295364670.0006151409270663330.000307570463533167
1720.9999165494113620.0001669011772751358.34505886375674e-05
1730.9999474819968960.0001050360062084495.25180031042246e-05
1740.9999554379158118.91241683789848e-054.45620841894924e-05
1750.9999999993320351.3359294926309e-096.67964746315452e-10
1760.9999999994811651.03766924913225e-095.18834624566125e-10
1770.9999999992537021.4925950870236e-097.462975435118e-10
1780.9999999987790242.44195252259051e-091.22097626129526e-09
1790.9999999999997495.02304801044837e-132.51152400522418e-13
1800.9999999999995938.13468128715255e-134.06734064357628e-13
1810.9999999999992061.58712824825734e-127.93564124128671e-13
1820.9999999999997624.76522172356638e-132.38261086178319e-13
1830.9999999999995249.51570650076222e-134.75785325038111e-13
1840.9999999999993931.21479186694441e-126.07395933472206e-13
1850.9999999999999754.92260418361868e-142.46130209180934e-14
1860.999999999999959.94179659333554e-144.97089829666777e-14
1870.99999999999992.00012895411011e-131.00006447705505e-13
1880.9999999999998313.37383408861243e-131.68691704430621e-13
1890.9999999999997215.57776223829856e-132.78888111914928e-13
1900.9999999999996866.27836854947543e-133.13918427473772e-13
1910.9999999999994861.02874600270246e-125.14373001351231e-13
1920.9999999999995449.12651913298708e-134.56325956649354e-13
1930.9999999999995429.16435607299174e-134.58217803649587e-13
1940.999999999999529.59308319450672e-134.79654159725336e-13
1950.9999999999996536.95000128627134e-133.47500064313567e-13
1960.9999999999998263.48804398615414e-131.74402199307707e-13
1970.9999999999997764.47514668336693e-132.23757334168347e-13
1980.9999999999995538.94228793984164e-134.47114396992082e-13
1990.9999999999990791.84197061155544e-129.20985305777722e-13
2000.9999999999987072.5856972229277e-121.29284861146385e-12
2010.9999999999973115.37720679241187e-122.68860339620594e-12
2020.9999999999947961.04080729005405e-115.20403645027024e-12
2030.9999999999897532.04950176440955e-111.02475088220477e-11
2040.9999999999842073.15855955980697e-111.57927977990348e-11
2050.999999999973615.27803334557004e-112.63901667278502e-11
2060.9999999999577198.45616378568942e-114.22808189284471e-11
2070.9999999999216121.56775866531464e-107.8387933265732e-11
2080.9999999999020381.95923067057241e-109.79615335286204e-11
2090.999999999813623.72759118865885e-101.86379559432943e-10
2100.999999999748635.02740517174054e-102.51370258587027e-10
2110.9999999995102139.79574419963918e-104.89787209981959e-10
2120.999999999106511.78697958348634e-098.9348979174317e-10
2130.9999999982520423.49591687251491e-091.74795843625745e-09
2140.9999999978534334.29313312979634e-092.14656656489817e-09
2150.9999999997177795.64441802792232e-102.82220901396116e-10
2160.9999999998283883.43223831404168e-101.71611915702084e-10
2170.9999999996456817.08638720632131e-103.54319360316065e-10
2180.9999999995363959.27210654170561e-104.6360532708528e-10
2190.9999999991672231.66555318838708e-098.32776594193542e-10
2200.9999999988068912.38621850573336e-091.19310925286668e-09
2210.9999999976694584.66108422340396e-092.33054211170198e-09
2220.9999999978295974.34080688265009e-092.17040344132504e-09
2230.999999996932116.13578013849029e-093.06789006924514e-09
2240.9999999938021481.23957045849208e-086.1978522924604e-09
2250.9999999913823061.72353881547508e-088.61769407737539e-09
2260.9999999853010422.93979165979025e-081.46989582989513e-08
2270.9999999727513645.44972722206574e-082.72486361103287e-08
2280.9999999630312567.39374873450329e-083.69687436725165e-08
2290.9999999503565739.9286853794846e-084.9643426897423e-08
2300.9999999039787661.92042468514694e-079.60212342573468e-08
2310.9999999593961748.12076513496953e-084.06038256748477e-08
2320.9999999448030161.10393968957159e-075.51969844785797e-08
2330.9999998921758252.15648350441472e-071.07824175220736e-07
2340.9999998280468123.43906375583705e-071.71953187791853e-07
2350.9999996648171426.70365715463974e-073.35182857731987e-07
2360.9999997446414145.10717172994583e-072.55358586497291e-07
2370.9999997383911265.23217748755801e-072.616088743779e-07
2380.9999994781431261.04371374834569e-065.21856874172845e-07
2390.9999989959813712.00803725850632e-061.00401862925316e-06
2400.9999980963360973.80732780517687e-061.90366390258843e-06
2410.9999974886722055.02265558975242e-062.51132779487621e-06
2420.9999955325611088.93487778314743e-064.46743889157372e-06
2430.9999955409418678.91811626571795e-064.45905813285898e-06
2440.9999916202875821.67594248361344e-058.37971241806718e-06
2450.9999841520839163.16958321688062e-051.58479160844031e-05
2460.9999707441816955.8511636610511e-052.92558183052555e-05
2470.9999812678792863.74642414273396e-051.87321207136698e-05
2480.999979429699284.11406014403585e-052.05703007201792e-05
2490.9999609639795067.80720409873029e-053.90360204936515e-05
2500.9999344450860920.0001311098278157116.55549139078555e-05
2510.9999228540694290.0001542918611414167.7145930570708e-05
2520.9998836906842160.0002326186315672230.000116309315783612
2530.9998193726024830.0003612547950337670.000180627397516883
2540.9998925452742190.0002149094515615120.000107454725780756
2550.9998435022473220.0003129955053568650.000156497752678432
2560.9997068291146920.0005863417706151970.000293170885307598
2570.9997241073576540.0005517852846910840.000275892642345542
2580.9994954123837980.001009175232404590.000504587616202296
2590.9992841603249810.001431679350036980.000715839675018489
2600.998730977998080.002538044003839430.00126902200191971
2610.9986798029359080.002640394128183750.00132019706409187
2620.9988700626637430.002259874672513750.00112993733625687
2630.9983137171079060.00337256578418720.0016862828920936
2640.9988867832181790.002226433563642850.00111321678182142
2650.9979690168915010.004061966216999010.0020309831084995
2660.9976834676801570.004633064639686450.00231653231984323
2670.9973005023487560.005398995302487580.00269949765124379
2680.9962353319025130.007529336194973630.00376466809748681
2690.9928072962679010.01438540746419830.00719270373209913
2700.9908695292260140.01826094154797210.00913047077398606
2710.9992010812663790.001597837467241920.000798918733620962
2720.9980205090591680.003958981881664550.00197949094083227
2730.9995798421724320.0008403156551350860.000420157827567543
2740.9990200328959860.001959934208027560.000979967104013782
2750.9990897657859560.001820468428087680.000910234214043841
2760.9988584527357890.002283094528421250.00114154726421063
2770.9981518549456350.003696290108729350.00184814505436467
2780.9998018629497350.0003962741005296430.000198137050264821
2790.9993307343414660.00133853131706770.000669265658533849
2800.9982075400538530.003584919892294740.00179245994614737






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1730.636029411764706NOK
5% type I error level1820.669117647058823NOK
10% type I error level1830.672794117647059NOK

\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 & 173 & 0.636029411764706 & NOK \tabularnewline
5% type I error level & 182 & 0.669117647058823 & NOK \tabularnewline
10% type I error level & 183 & 0.672794117647059 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197292&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]173[/C][C]0.636029411764706[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]182[/C][C]0.669117647058823[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]183[/C][C]0.672794117647059[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197292&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197292&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1730.636029411764706NOK
5% type I error level1820.669117647058823NOK
10% type I error level1830.672794117647059NOK


Figures (Output of Computation)

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Input Parameters & R Code

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