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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, 16 Dec 2011 08:33:43 -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/2011/Dec/16/t1324042479pgekbv36wkzcffx.htm/, Retrieved Sun, 05 May 2024 13:09:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155913, Retrieved Sun, 05 May 2024 13:09:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Multiple Regressi...] [2011-12-16 13:33:43] [10a6f28c51bb1cb94db47cee32729d66] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1418	396	79	30	94	146283	0.69
869	297	58	28	103	98364	0.81
1530	559	60	38	93	86146	0.49
2172	967	108	30	103	96933	0.54
901	270	49	22	51	79234	0.64
463	143	0	26	70	42551	0.81
3201	1562	121	25	91	195663	0.51
371	109	1	18	22	6853	0.21
1192	371	20	11	38	21529	0.21
1583	656	43	26	93	95757	0.64
1439	511	69	25	60	85584	0.52
1764	655	78	38	123	143983	0.61
1495	465	86	44	148	75851	0.44
1373	525	44	30	90	59238	0.44
2187	885	104	40	124	93163	0.36
1491	497	63	34	70	96037	0.53
4041	1436	158	47	168	151511	0.47
1706	612	102	30	115	136368	0.59
2152	865	77	31	71	112642	0.48
1036	385	82	23	66	94728	0.70
1882	567	115	36	134	105499	0.52
1929	639	101	36	117	121527	0.56
2242	963	80	30	108	127766	0.37
1220	398	50	25	84	98958	0.64
1289	410	83	39	156	77900	0.59
2515	966	123	34	120	85646	0.49
2147	801	73	31	114	98579	0.57
2352	892	81	31	94	130767	0.58
1638	513	105	33	120	131741	0.59
1222	469	47	25	81	53907	0.43
1812	683	105	33	110	178812	0.81
1677	643	94	35	133	146761	0.70
1579	535	44	42	122	82036	0.48
1731	625	114	43	158	163253	0.63
807	264	38	30	109	27032	0.32
2452	992	107	33	124	171975	0.58
829	238	30	13	39	65990	0.65
1940	818	71	32	92	86572	0.40
2662	937	84	36	126	159676	0.49
186	70	0	0	0	1929	0.27
1499	507	59	28	70	85371	0.51
865	260	33	14	37	58391	0.55
1793	503	42	17	38	31580	0.33
2527	927	96	32	120	136815	0.51
2747	1269	106	30	93	120642	0.45
1324	537	56	35	95	69107	0.46
2702	910	57	20	77	50495	0.29
1383	532	59	28	90	108016	0.71
1179	345	39	28	80	46341	0.42
2099	918	34	39	31	78348	0.67
4308	1635	76	34	110	79336	0.22
918	330	20	26	66	56968	0.72
1831	557	91	39	138	93176	0.51
3373	1178	115	39	133	161632	0.58
1713	740	85	33	113	87850	0.58
1438	452	76	28	100	127969	0.76
496	218	8	4	7	15049	0.62
2253	764	79	39	140	155135	0.47
744	255	21	18	61	25109	0.39
1161	454	30	14	41	45824	0.45
2352	866	76	29	96	102996	0.47
2144	574	101	44	164	160604	0.66
4691	1276	94	21	78	158051	0.46
1112	379	27	16	49	44547	0.43
2694	825	92	28	102	162647	0.70
1973	798	123	35	124	174141	0.68
1769	663	75	28	99	60622	0.29
3148	1069	128	38	129	179566	0.58
2474	921	105	23	62	184301	0.78
2084	858	55	36	73	75661	0.43
1954	711	56	32	114	96144	0.46
1226	503	41	29	99	129847	0.66
1389	382	72	25	70	117286	0.67
1496	464	67	27	104	71180	0.50
2269	717	75	36	116	109377	0.58
1833	690	114	28	91	85298	0.45
1268	462	118	23	74	73631	0.62
1943	657	77	40	138	86767	0.48
893	385	22	23	67	23824	0.32
1762	577	66	40	151	93487	0.48
1403	619	69	28	72	82981	0.50
1425	479	105	34	120	73815	0.51
1857	817	116	33	115	94552	0.34
1840	752	88	28	105	132190	0.54
1502	430	73	34	104	128754	0.70
1441	451	99	30	108	66363	0.49
1420	537	62	33	98	67808	0.45
1416	519	53	22	69	61724	0.51
2970	1000	118	38	111	131722	0.38
1317	637	30	26	99	68580	0.47
1644	465	100	35	71	106175	0.55
870	437	49	8	27	55792	0.69
1654	711	24	24	69	25157	0.20
1054	299	67	29	107	76669	0.59
937	248	46	20	73	57283	0.51
3004	1162	57	29	107	105805	0.37
2008	714	75	45	93	129484	0.54
2547	905	135	37	129	72413	0.49
1885	649	68	33	69	87831	0.43
1626	512	124	33	118	96971	0.53
1468	472	33	25	73	71299	0.51
2445	905	98	32	119	77494	0.35
1964	786	58	29	104	120336	0.50
1381	489	68	28	107	93913	0.58
1369	479	81	28	99	136048	0.75
1659	617	131	31	90	181248	0.78
2888	925	110	52	197	146123	0.55
1290	351	37	21	36	32036	0.37
2845	1144	130	24	85	186646	0.60
1982	669	93	41	139	102255	0.45
1904	707	118	33	106	168237	0.72
1391	458	39	32	50	64219	0.44
602	214	13	19	64	19630	0.45
1743	599	74	20	31	76825	0.49
1559	572	81	31	63	115338	0.70
2014	897	109	31	92	109427	0.54
2143	819	151	32	106	118168	0.50
2146	720	51	18	63	84845	0.38
874	273	28	23	69	153197	1.54
1590	508	40	17	41	29877	0.32
1590	506	56	20	56	63506	0.48
1210	451	27	12	25	22445	0.37
2072	699	37	17	65	47695	0.38
1281	407	83	30	93	68370	0.68
1401	465	54	31	114	146304	0.65
834	245	27	10	38	38233	0.46
1105	370	28	13	44	42071	0.41
1272	316	59	22	87	50517	0.50
1944	603	133	42	110	103950	0.43
391	154	12	1	0	5841	0.25
761	229	0	9	27	2341	0.06
1605	577	106	32	83	84396	0.55
530	192	23	11	30	24610	0.40
1988	617	44	25	80	35753	0.36
1386	411	71	36	98	55515	0.42
2395	975	116	31	82	209056	0.66
387	146	4	0	0	6622	0.31
1742	705	62	24	60	115814	0.55
620	184	12	13	28	11609	0.51
449	200	18	8	9	13155	0.42
800	274	14	13	33	18274	0.39
1684	502	60	19	59	72875	0.55
1050	382	7	18	49	10112	0.11
2699	964	98	33	115	142775	0.58
1606	537	64	40	140	68847	0.37
1502	438	29	22	49	17659	0.22
1204	369	32	38	120	20112	0.16
1138	417	25	24	66	61023	0.62
568	276	16	8	21	13983	0.37
1459	514	48	35	124	65176	0.43
2158	822	100	43	152	132432	0.49
1111	389	46	43	139	112494	0.65
1421	466	45	14	38	45109	0.42
2833	1255	129	41	144	170875	0.52
1955	694	130	38	120	180759	0.72
2922	1024	136	45	160	214921	0.61
1002	400	59	31	114	100226	0.63
1060	397	25	13	39	32043	0.32
956	350	32	28	78	54454	0.64
2186	719	63	31	119	78876	0.34
3604	1277	95	40	141	170745	0.49
1035	356	14	30	101	6940	0.08
1417	457	36	16	56	49025	0.41
3261	1402	113	37	133	122037	0.38
1587	600	47	30	83	53782	0.41
1424	480	92	35	116	127748	0.63
1701	595	70	32	90	86839	0.52
1249	436	19	27	36	44830	0.32
946	230	50	20	50	77395	0.67
1926	651	41	18	61	89324	0.36
3352	1367	91	31	97	103300	0.34
1641	564	111	31	98	112283	0.57
2035	716	41	21	78	10901	0.06
2312	747	120	39	117	120691	0.47
1369	467	135	41	148	58106	0.56
1577	671	27	13	41	57140	0.42
2201	861	87	32	105	122422	0.61
961	319	25	18	55	25899	0.28
1900	612	131	39	132	139296	0.62
1254	433	45	14	44	52678	0.39
1335	434	29	7	21	23853	0.32
1597	503	58	17	50	17306	0.21
207	85	4	0	0	7953	0.54
1645	564	47	30	73	89455	0.49
2429	824	109	37	86	147866	0.54
151	74	7	0	0	4245	0.59
474	259	12	5	13	21509	0.46
141	69	0	1	4	7670	0.44
1639	535	37	16	57	66675	0.50
872	239	37	32	48	14336	0.15
1318	438	46	24	46	53608	0.35
1018	459	15	17	48	30059	0.31
1383	426	42	11	32	29668	0.37
1314	288	7	24	68	22097	0.37
1335	498	54	22	87	96841	0.69
1403	454	54	12	43	41907	0.35
910	376	14	19	67	27080	0.37
616	225	16	13	46	35885	0.55
1407	555	33	17	46	41247	0.41
771	252	32	15	56	28313	0.39
766	208	21	16	48	36845	0.48
473	130	15	24	44	16548	0.34
1376	481	38	15	60	36134	0.27
1232	389	22	17	65	55764	0.51
1521	565	28	18	55	28910	0.32
572	173	10	20	38	13339	0.30
1059	278	31	16	52	25319	0.33
1544	609	32	16	60	66956	0.37
1230	422	32	18	54	47487	0.35
1206	445	43	22	86	52785	0.43
1205	387	27	8	24	44683	0.48
1255	339	37	17	52	35619	0.29
613	181	20	18	49	21920	0.41
721	245	32	16	61	45608	0.56
1109	384	0	23	61	7721	0.13
740	212	5	22	81	20634	0.39
1126	399	26	13	43	29788	0.49
728	229	10	13	40	31931	0.57
689	224	27	16	40	37754	0.58
592	203	11	16	56	32505	0.40
995	333	29	20	68	40557	0.53
1613	384	25	22	79	94238	0.91
2048	636	55	17	47	44197	0.45
705	185	23	18	57	43228	0.64
301	93	5	17	41	4103	0.13
1803	581	43	12	29	44144	0.33
799	248	23	7	3	32868	0.45
861	304	34	17	60	27640	0.44
1186	344	36	14	30	14063	0.23
1451	407	35	23	79	28990	0.39
628	170	0	17	47	4694	0.15
1161	312	37	14	40	42648	0.52
1463	507	28	15	48	64329	0.74
742	224	16	17	36	21928	0.44
979	340	26	21	42	25836	0.39
675	168	38	18	49	22779	0.40
1241	443	23	18	57	40820	0.26
676	204	22	17	12	27530	0.59
1049	367	30	17	40	32378	0.44
620	210	16	16	43	10824	0.28
1081	335	18	15	33	39613	0.43
1688	364	28	21	77	60865	0.44
736	178	32	16	43	19787	0.38
617	206	21	14	45	20107	0.39
812	279	23	15	47	36605	0.52
1051	387	29	17	43	40961	0.48
1656	490	50	15	45	48231	0.47
705	238	12	15	50	39725	0.46
945	343	21	10	35	21455	0.25
554	232	18	6	7	23430	0.68
1597	530	27	22	71	62991	0.42
982	291	41	21	67	49363	0.50
222	67	13	1	0	9604	0.50
1212	397	12	18	62	24552	0.25
1143	467	21	17	54	31493	0.37
435	178	8	4	4	3439	0.11
532	175	26	10	25	19555	0.62
882	299	27	16	40	21228	0.24
608	154	13	16	38	23177	0.37
459	106	16	9	19	22094	0.55
578	189	2	16	17	2342	0.08
826	194	42	17	67	38798	0.50
509	135	5	7	14	3255	0.09
717	201	37	15	30	24261	0.45
637	207	17	14	54	18511	0.37
857	280	38	14	35	40798	0.48
830	260	37	18	59	28893	0.45
652	227	29	12	24	21425	0.36
707	239	32	16	58	50276	0.42
954	333	35	21	42	37643	0.49
1461	428	17	19	46	30377	0.29
672	230	20	16	61	27126	0.39
778	292	7	1	3	13	0.00
1141	350	46	16	52	42097	0.40
680	186	24	10	25	24451	0.39
1090	326	40	19	40	14335	0.21
616	155	3	12	32	5084	0.10
285	75	10	2	4	9927	0.50
1145	361	37	14	49	43527	0.50
733	261	17	17	63	27184	0.32
888	299	28	19	67	21610	0.28
849	300	19	14	32	20484	0.23
1182	450	29	11	23	20156	0.22
528	183	8	4	7	6012	0.15
642	238	10	16	54	18475	0.29
947	165	15	20	37	12645	0.25
819	234	15	12	35	11017	0.19
757	176	28	15	51	37623	0.60
894	329	17	16	39	35873	0.49

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'AstonUniversity' @ aston.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 & 8 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155913&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155913&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155913&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 time8 seconds
R Server'AstonUniversity' @ aston.wessa.net






Multiple Linear Regression - Estimated Regression Equation
fdm120[t] = -3.80158515930054 + 0.0052385334882863page[t] -0.0127363627375444comp[t] + 0.124717318940338blogcomp[t] + 2.78730536903674review[t] + 7.6195298409881e-05totsec[t] -4.60089639868684prod[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
fdm120[t] =  -3.80158515930054 +  0.0052385334882863page[t] -0.0127363627375444comp[t] +  0.124717318940338blogcomp[t] +  2.78730536903674review[t] +  7.6195298409881e-05totsec[t] -4.60089639868684prod[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155913&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]fdm120[t] =  -3.80158515930054 +  0.0052385334882863page[t] -0.0127363627375444comp[t] +  0.124717318940338blogcomp[t] +  2.78730536903674review[t] +  7.6195298409881e-05totsec[t] -4.60089639868684prod[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155913&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155913&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
fdm120[t] = -3.80158515930054 + 0.0052385334882863page[t] -0.0127363627375444comp[t] + 0.124717318940338blogcomp[t] + 2.78730536903674review[t] + 7.6195298409881e-05totsec[t] -4.60089639868684prod[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-3.801585159300544.200245-0.90510.3661920.183096
page0.00523853348828630.0045651.14760.2521260.126063
comp-0.01273636273754440.011491-1.10840.2686350.134317
blogcomp0.1247173189403380.0499952.49460.0131820.006591
review2.787305369036740.13447820.726800
totsec7.6195298409881e-054.9e-051.56810.1179710.058985
prod-4.600896398686848.086394-0.5690.5698310.284915

\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) & -3.80158515930054 & 4.200245 & -0.9051 & 0.366192 & 0.183096 \tabularnewline
page & 0.0052385334882863 & 0.004565 & 1.1476 & 0.252126 & 0.126063 \tabularnewline
comp & -0.0127363627375444 & 0.011491 & -1.1084 & 0.268635 & 0.134317 \tabularnewline
blogcomp & 0.124717318940338 & 0.049995 & 2.4946 & 0.013182 & 0.006591 \tabularnewline
review & 2.78730536903674 & 0.134478 & 20.7268 & 0 & 0 \tabularnewline
totsec & 7.6195298409881e-05 & 4.9e-05 & 1.5681 & 0.117971 & 0.058985 \tabularnewline
prod & -4.60089639868684 & 8.086394 & -0.569 & 0.569831 & 0.284915 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155913&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]-3.80158515930054[/C][C]4.200245[/C][C]-0.9051[/C][C]0.366192[/C][C]0.183096[/C][/ROW]
[ROW][C]page[/C][C]0.0052385334882863[/C][C]0.004565[/C][C]1.1476[/C][C]0.252126[/C][C]0.126063[/C][/ROW]
[ROW][C]comp[/C][C]-0.0127363627375444[/C][C]0.011491[/C][C]-1.1084[/C][C]0.268635[/C][C]0.134317[/C][/ROW]
[ROW][C]blogcomp[/C][C]0.124717318940338[/C][C]0.049995[/C][C]2.4946[/C][C]0.013182[/C][C]0.006591[/C][/ROW]
[ROW][C]review[/C][C]2.78730536903674[/C][C]0.134478[/C][C]20.7268[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]totsec[/C][C]7.6195298409881e-05[/C][C]4.9e-05[/C][C]1.5681[/C][C]0.117971[/C][C]0.058985[/C][/ROW]
[ROW][C]prod[/C][C]-4.60089639868684[/C][C]8.086394[/C][C]-0.569[/C][C]0.569831[/C][C]0.284915[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155913&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155913&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)-3.801585159300544.200245-0.90510.3661920.183096
page0.00523853348828630.0045651.14760.2521260.126063
comp-0.01273636273754440.011491-1.10840.2686350.134317
blogcomp0.1247173189403380.0499952.49460.0131820.006591
review2.787305369036740.13447820.726800
totsec7.6195298409881e-054.9e-051.56810.1179710.058985
prod-4.600896398686848.086394-0.5690.5698310.284915






Multiple Linear Regression - Regression Statistics
Multiple R0.92657721509924
R-squared0.858545335541063
Adjusted R-squared0.855535661829171
F-TEST (value)285.261931268048
F-TEST (DF numerator)6
F-TEST (DF denominator)282
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation14.8098931900305
Sum Squared Residuals61851.8880366316

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.92657721509924 \tabularnewline
R-squared & 0.858545335541063 \tabularnewline
Adjusted R-squared & 0.855535661829171 \tabularnewline
F-TEST (value) & 285.261931268048 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 282 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 14.8098931900305 \tabularnewline
Sum Squared Residuals & 61851.8880366316 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155913&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.92657721509924[/C][/ROW]
[ROW][C]R-squared[/C][C]0.858545335541063[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.855535661829171[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]285.261931268048[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]282[/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]14.8098931900305[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]61851.8880366316[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155913&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155913&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 R0.92657721509924
R-squared0.858545335541063
Adjusted R-squared0.855535661829171
F-TEST (value)285.261931268048
F-TEST (DF numerator)6
F-TEST (DF denominator)282
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation14.8098931900305
Sum Squared Residuals61851.8880366316






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
194100.026343272609-6.0263432726094
210386.01430379039116.9856962096089
393114.803868408768-21.8038684087676
410397.25043313218465.74956686781537
55168.0040669004422-17.0040669004422
67068.78795562896481.21204437103516
79190.40833526780120.591664732198777
82246.6058393243416-24.6058393243416
93831.54648195706076.45351804293928
109378.320403200892714.6795967991073
116079.6451446960541-19.6451446960541
12123120.9067060694382.09329393056174
13148135.22983456348112.7701654365194
149088.3003166591651.69968334083492
15124126.288482370352-2.28848237035199
1670105.183762413751-35.1837624137509
17168159.1686050630478.83139493695256
18115101.35709815768913.6429018423112
197198.8388456701767-27.8388456701767
206675.0540802702526-9.0540802702526
21134119.16736381655514.8326361834451
22117117.787736695203-0.787736695202567
2310897.30747302063410.692526979366
248478.03441414468685.96558585531315
25156120.00650752009335.9934924799074
26120111.4499962284388.55000377156157
2711497.643295784756816.3567042152432
2894100.962489993492-6.96248999349206
29120110.6452902096919.3547097903091
308174.29997135553756.70002864446255
31110111.966005055011-1.96600505501059
32133114.03494086784418.9650591321561
33122124.252819916018-2.25281991601845
34158140.91854114587217.0814588541283
3510986.009355252905922.9906447470941
36124112.16982395596311.8301760440371
373939.5239392195626-0.523939219562573
389298.7475473570687-6.74754735706868
39126118.9407884112897.05921158871092
400-4.81402461912024.8140246191202
417087.1549244394339-17.1549244394339
423742.4748653380247-5.47486533802465
433852.6949853095481-14.6949853095481
44120106.87441772396113.125582276039
459398.3873687092119-5.38736870921188
4695103.98388030989-8.98388030988964
477764.131058432805412.8689415671946
489087.03410873910852.96589126089154
498082.4877162868019-2.48771628680186
5031111.334562528648-80.3345625286481
51110107.2217958060022.77820419399822
526672.7967232060782-6.79672320607815
53138123.50331699025214.4966830097482
54133131.5590326237811.44096737621895
55113102.35440062256210.6455993774382
5610091.75161149119158.24838850880848
5776.461267680358890.538732319641108
58140126.48596355847813.5140364415219
596149.757509750604911.2424902493951
604140.68300824740450.31699175259552
619693.48551706360782.51448293639221
62164144.55772196151319.4422780384874
637884.7039480768913-6.7039480768913
644946.57672262495112.42327737504894
6510298.49437769659953.50562230340046
66124119.4064580037634.59354199623663
679987.704372764624611.2956272353754
68129131.969132386179-2.96913238617944
696285.0858690872856-23.0858690872856
7073107.176792250071-34.1767922500708
7111498.76620546717515.233794532825
729989.01687150846749.9831284915326
737083.125769661991-13.1257696619911
7410484.862027103421719.1379728965783
75116114.3149606915891.68503930841114
769193.7037843124068-2.70378431240679
777478.539123091938-4.53912309193797
78138123.50735059550914.4926494044909
796763.16772003805423.83227996194585
80151122.71822695010328.2817730498965
817286.336627988144-14.3366279881441
82120108.70420713500311.2957928649967
83115107.6091624268627.39083757313752
8410592.867018521802612.1329814781974
85104109.05262496524-5.0526249652402
8610896.771327001901511.2286729980985
879899.607503971686-1.60750397168612
886967.29336345769471.70663654230532
89111127.943000687367-16.9430006873667
909974.259011801688924.7409881983111
9171114.475117822195-43.475117822195
922724.67620961336232.32379038663772
936966.69260567774082.30739432225923
9410790.226861208457416.7731387915426
957361.44964492778611.5503550722141
9610791.43557070089315.5644292991071
9793139.787755581764-46.7877555817644
98129121.244778977597.75522102240988
9969102.982929718811-33.9829297188111
100118110.5915364886457.40846351135491
1017374.7615159583282-1.76151595832821
102119103.19065472284515.8093452771545
10310491.410162930696912.5898370693031
10410788.217285378664118.7827146213359
1059992.3314482611286.66855173887194
10690109.996787565243-19.9967875652431
107197166.80834086625930.1916591337414
1083662.3722741826195-26.3722741826195
1098591.1012337900474-6.10123379004744
110139129.6597391945179.34026080548329
111106113.371917971654-7.37191797165358
1125094.578499490121-44.5784994901211
1136450.631867861112613.3681321388874
1143166.2745509782957-35.2745509782957
1156399.1562441862867-36.1562441862867
11692101.178296978974-9.17829697897365
117106111.72299581637-5.72299581637023
1186359.51865590623383.48134409376622
1196969.4874851768073-0.487485176807308
1204151.2346949306524-10.2346949306524
1215663.4437891327191-7.44378913271913
1222533.615844612019-8.61584461201899
1236552.034464875460512.9655351245395
1249393.7768381493404-0.776838149340361
12511498.913487527160315.0865124728397
1263829.48412670169748.51587329830261
1274438.3208397361125.67916026388805
1288769.064888439452317.9351115605477
129110138.298441948069-28.2984419480685
1300-0.1359725923012420.135972592301242
1312722.25637948937464.74362051062538
13283103.57127279201-20.5712727920099
1333030.093121073307-0.093121073306999
1348074.99236766616235.00763233383773
13598109.719905604196-11.7199056041962
13682110.0929169945-28.0929169945003
1370-4.056625000776574.05662500077657
1386077.2665963492723-17.2665963492723
1392833.3724865404005-5.37248654040046
140919.6165711857846-10.6165711857846
1413334.4785337915379-1.47853379153795
1425962.0905316411869-3.09053164118693
1434948.14249056656690.857509433433077
144115110.4730013001894.52699869981072
145140120.78968204858819.210317951412
1464963.759021196048-14.7590211960481
147120108.51074595775911.4892540422412
1486668.6591744468837-2.65917444688374
1492119.31569299197441.68430700802563
150124103.8247832961620.1752167038395
151152137.19599922443414.8040007755658
152139128.23603922129110.7639607787093
1533843.846497639211-5.846497639211
154144136.0505047396777.94949526032252
155120130.191908094301-10.1919080943005
156160154.4230941591175.57690584088317
15711494.855853805819419.1441461941806
1583937.01706620183191.98293379816812
1597879.9887955209322-1.98879552093219
16011997.201737353003321.7982626469967
161141132.9096413690798.09035863092068
16210182.612079061846518.3879209381535
1635648.73671539006627.26328460993385
164133120.19855268312712.801447316873
1658388.5625929209998-5.56259292099983
166116113.4095459228882.59045407711245
1679099.6792660017333-9.67926600173333
1683676.7587114179932-40.7587114179932
1695063.0212119520473-13.0212119520473
1706158.43111104784962.56888895215043
17197100.409783245109-3.4097832451088
17298103.794554297624-5.79455429762384
1737861.940968759650616.0590312403494
174117129.500494418949-12.5004944189492
175148130.38934600132217.610653998678
1764137.93724302739353.06275697260648
177105103.3280313071121.6719686928876
1785551.14430646772093.85569353227914
179132131.16099716680.839002833199702
1804444.1067116226312-0.106711622631155
1812121.1374150573855-0.137415057385474
1825053.1282057272292-3.12820572722917
1830-5.179433131192325.17943313119232
1847391.6749800901528-18.6749800901528
18586123.934746146251-37.9347461462511
1860-5.471116046040535.47111604604053
1871310.33836876769312.66163123230691
1884-2.594432073924446.59443207392444
1895749.96171719093027.03828280906983
1904891.9329392963812-43.9329392963812
1914672.6309644449701-26.6309644449701
1924845.80427908428132.19572091571865
1933234.474333029414-2.47433302941404
1946867.1634813068080.836518693192051
1958769.108812124068417.8911878759316
1964339.53097092406163.4690290759384
1976751.242489416011515.7575105839885
1984634.993892018220111.0061079817799
1994649.2566728880876-3.25667288808761
2005643.1912633803412.80873661966
2014845.37690314419482.62309685580519
2024465.483177688298-21.4831776882981
2036045.340283984203714.6597160157963
2046549.728312740873715.2716872591263
2055551.3642801321113.63571986788904
2063853.6208459784255-15.6208459784255
2075247.07932870436874.92067129563129
2086048.517506482945511.4824935170545
2095453.43748920084960.562510799150398
2108665.575551017738520.4244489822615
2112424.4438901258168-0.443890125816828
2125251.83361985333060.166380146669365
2134949.5540306526744-0.554030652674452
2146146.341441912347314.6585580876527
2156161.2153960430303-0.215396043030282
2168159.096989627083421.9030103729166
2174336.5080812198336.49191878016702
2184034.38806426642965.6119357335704
2194045.127230061824-5.12723006182399
2205643.319291058313412.6807089416866
2216857.184234126252110.8157658737479
2227967.189733967150211.8102660328498
2234754.3674487633872-7.36744876338715
2245750.92454548628746.0754545137126
2254144.3130223319547-3.31302233195469
2262938.8994425538809-9.89944255388088
227320.039004746541-17.039004746541
2286048.543161652123411.4568383478766
2293041.5554337342984-11.5554337342984
2307967.503509054193711.4964909458063
2314744.37474975051822.6252502494818
2324042.8005339730603-2.80053397306029
2334844.20362290838883.79637709161118
2343646.2585459005776-10.2585459005776
2354258.9468709714168-16.9468709714168
2364952.4007649107833-3.40076491078333
2375752.01128020265244.98871979734758
2381246.6525454606327-34.6525454606327
2394048.5877591435606-8.5877591435606
2404342.90051935454210.0994806454579105
2413342.689019205412-9.689019205412
2427765.043753434856711.9562465651433
2434346.1340787696092-3.13407876960921
2444538.1859474129396.814052587061
2454741.97340047156845.02659952843157
2464348.6887400271505-5.68874002715048
2474548.1906091686969-3.19060916869695
2485041.07696086717748.92303913282257
2493527.7569199839797.24308001602095
250713.7711164838827-6.77111648388273
2517165.36940785547985.63059214452015
2526762.74397631196014.25602368803992
2530-0.6520050664702640.652005066470264
2546249.879808758530412.1201912414696
2555446.93871905605747.06128094394264
25648.11300139586678-4.11300139586678
2572526.5095984534331-1.50959845343305
2584045.4881410937792-5.48814109377924
2593843.7039011545396-5.70390115453957
2601923.4870385898094-4.48703858980936
2611741.4758128589825-24.4758128589825
2626751.332684788422215.6673152115778
2631417.1140786150699-3.11407861506989
2643043.5967265332109-13.5967265332109
2655437.749522675917416.2504773240826
2663541.7833752730522-6.7833752730522
2675952.1520881452176.84791185478305
2682433.7634125762546-9.76341257625464
2695847.344325768730110.6556742312699
2704260.4670662922922-18.4670662922922
2714654.4600700732783-8.46007007327828
2726144.153102267765816.8468977322342
27330.2162931157216672.78370688427833
2745249.4189720862232.58102791377703
2752528.3266251344185-3.32662513441851
2764055.829928218785-15.829928218785
2773231.20031888767340.799681112326552
27842.013896134993541.98610386500646
2794942.25162925838416.74837074161594
2806346.817461053118916.1825389468811
2816753.851276468804613.1487235311954
2823238.719503498302-6.71950349830198
2832331.4597547276713-8.45975472767126
28478.54851784345082-1.54851784345082
2855442.447806285138211.5521937148618
2863756.4879388159728-19.4879388159728
2873532.79216238639762.20783761360237
2885143.33020818826787.66979181173225
2893943.88739546965-4.88739546964997

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 94 & 100.026343272609 & -6.0263432726094 \tabularnewline
2 & 103 & 86.014303790391 & 16.9856962096089 \tabularnewline
3 & 93 & 114.803868408768 & -21.8038684087676 \tabularnewline
4 & 103 & 97.2504331321846 & 5.74956686781537 \tabularnewline
5 & 51 & 68.0040669004422 & -17.0040669004422 \tabularnewline
6 & 70 & 68.7879556289648 & 1.21204437103516 \tabularnewline
7 & 91 & 90.4083352678012 & 0.591664732198777 \tabularnewline
8 & 22 & 46.6058393243416 & -24.6058393243416 \tabularnewline
9 & 38 & 31.5464819570607 & 6.45351804293928 \tabularnewline
10 & 93 & 78.3204032008927 & 14.6795967991073 \tabularnewline
11 & 60 & 79.6451446960541 & -19.6451446960541 \tabularnewline
12 & 123 & 120.906706069438 & 2.09329393056174 \tabularnewline
13 & 148 & 135.229834563481 & 12.7701654365194 \tabularnewline
14 & 90 & 88.300316659165 & 1.69968334083492 \tabularnewline
15 & 124 & 126.288482370352 & -2.28848237035199 \tabularnewline
16 & 70 & 105.183762413751 & -35.1837624137509 \tabularnewline
17 & 168 & 159.168605063047 & 8.83139493695256 \tabularnewline
18 & 115 & 101.357098157689 & 13.6429018423112 \tabularnewline
19 & 71 & 98.8388456701767 & -27.8388456701767 \tabularnewline
20 & 66 & 75.0540802702526 & -9.0540802702526 \tabularnewline
21 & 134 & 119.167363816555 & 14.8326361834451 \tabularnewline
22 & 117 & 117.787736695203 & -0.787736695202567 \tabularnewline
23 & 108 & 97.307473020634 & 10.692526979366 \tabularnewline
24 & 84 & 78.0344141446868 & 5.96558585531315 \tabularnewline
25 & 156 & 120.006507520093 & 35.9934924799074 \tabularnewline
26 & 120 & 111.449996228438 & 8.55000377156157 \tabularnewline
27 & 114 & 97.6432957847568 & 16.3567042152432 \tabularnewline
28 & 94 & 100.962489993492 & -6.96248999349206 \tabularnewline
29 & 120 & 110.645290209691 & 9.3547097903091 \tabularnewline
30 & 81 & 74.2999713555375 & 6.70002864446255 \tabularnewline
31 & 110 & 111.966005055011 & -1.96600505501059 \tabularnewline
32 & 133 & 114.034940867844 & 18.9650591321561 \tabularnewline
33 & 122 & 124.252819916018 & -2.25281991601845 \tabularnewline
34 & 158 & 140.918541145872 & 17.0814588541283 \tabularnewline
35 & 109 & 86.0093552529059 & 22.9906447470941 \tabularnewline
36 & 124 & 112.169823955963 & 11.8301760440371 \tabularnewline
37 & 39 & 39.5239392195626 & -0.523939219562573 \tabularnewline
38 & 92 & 98.7475473570687 & -6.74754735706868 \tabularnewline
39 & 126 & 118.940788411289 & 7.05921158871092 \tabularnewline
40 & 0 & -4.8140246191202 & 4.8140246191202 \tabularnewline
41 & 70 & 87.1549244394339 & -17.1549244394339 \tabularnewline
42 & 37 & 42.4748653380247 & -5.47486533802465 \tabularnewline
43 & 38 & 52.6949853095481 & -14.6949853095481 \tabularnewline
44 & 120 & 106.874417723961 & 13.125582276039 \tabularnewline
45 & 93 & 98.3873687092119 & -5.38736870921188 \tabularnewline
46 & 95 & 103.98388030989 & -8.98388030988964 \tabularnewline
47 & 77 & 64.1310584328054 & 12.8689415671946 \tabularnewline
48 & 90 & 87.0341087391085 & 2.96589126089154 \tabularnewline
49 & 80 & 82.4877162868019 & -2.48771628680186 \tabularnewline
50 & 31 & 111.334562528648 & -80.3345625286481 \tabularnewline
51 & 110 & 107.221795806002 & 2.77820419399822 \tabularnewline
52 & 66 & 72.7967232060782 & -6.79672320607815 \tabularnewline
53 & 138 & 123.503316990252 & 14.4966830097482 \tabularnewline
54 & 133 & 131.559032623781 & 1.44096737621895 \tabularnewline
55 & 113 & 102.354400622562 & 10.6455993774382 \tabularnewline
56 & 100 & 91.7516114911915 & 8.24838850880848 \tabularnewline
57 & 7 & 6.46126768035889 & 0.538732319641108 \tabularnewline
58 & 140 & 126.485963558478 & 13.5140364415219 \tabularnewline
59 & 61 & 49.7575097506049 & 11.2424902493951 \tabularnewline
60 & 41 & 40.6830082474045 & 0.31699175259552 \tabularnewline
61 & 96 & 93.4855170636078 & 2.51448293639221 \tabularnewline
62 & 164 & 144.557721961513 & 19.4422780384874 \tabularnewline
63 & 78 & 84.7039480768913 & -6.7039480768913 \tabularnewline
64 & 49 & 46.5767226249511 & 2.42327737504894 \tabularnewline
65 & 102 & 98.4943776965995 & 3.50562230340046 \tabularnewline
66 & 124 & 119.406458003763 & 4.59354199623663 \tabularnewline
67 & 99 & 87.7043727646246 & 11.2956272353754 \tabularnewline
68 & 129 & 131.969132386179 & -2.96913238617944 \tabularnewline
69 & 62 & 85.0858690872856 & -23.0858690872856 \tabularnewline
70 & 73 & 107.176792250071 & -34.1767922500708 \tabularnewline
71 & 114 & 98.766205467175 & 15.233794532825 \tabularnewline
72 & 99 & 89.0168715084674 & 9.9831284915326 \tabularnewline
73 & 70 & 83.125769661991 & -13.1257696619911 \tabularnewline
74 & 104 & 84.8620271034217 & 19.1379728965783 \tabularnewline
75 & 116 & 114.314960691589 & 1.68503930841114 \tabularnewline
76 & 91 & 93.7037843124068 & -2.70378431240679 \tabularnewline
77 & 74 & 78.539123091938 & -4.53912309193797 \tabularnewline
78 & 138 & 123.507350595509 & 14.4926494044909 \tabularnewline
79 & 67 & 63.1677200380542 & 3.83227996194585 \tabularnewline
80 & 151 & 122.718226950103 & 28.2817730498965 \tabularnewline
81 & 72 & 86.336627988144 & -14.3366279881441 \tabularnewline
82 & 120 & 108.704207135003 & 11.2957928649967 \tabularnewline
83 & 115 & 107.609162426862 & 7.39083757313752 \tabularnewline
84 & 105 & 92.8670185218026 & 12.1329814781974 \tabularnewline
85 & 104 & 109.05262496524 & -5.0526249652402 \tabularnewline
86 & 108 & 96.7713270019015 & 11.2286729980985 \tabularnewline
87 & 98 & 99.607503971686 & -1.60750397168612 \tabularnewline
88 & 69 & 67.2933634576947 & 1.70663654230532 \tabularnewline
89 & 111 & 127.943000687367 & -16.9430006873667 \tabularnewline
90 & 99 & 74.2590118016889 & 24.7409881983111 \tabularnewline
91 & 71 & 114.475117822195 & -43.475117822195 \tabularnewline
92 & 27 & 24.6762096133623 & 2.32379038663772 \tabularnewline
93 & 69 & 66.6926056777408 & 2.30739432225923 \tabularnewline
94 & 107 & 90.2268612084574 & 16.7731387915426 \tabularnewline
95 & 73 & 61.449644927786 & 11.5503550722141 \tabularnewline
96 & 107 & 91.435570700893 & 15.5644292991071 \tabularnewline
97 & 93 & 139.787755581764 & -46.7877555817644 \tabularnewline
98 & 129 & 121.24477897759 & 7.75522102240988 \tabularnewline
99 & 69 & 102.982929718811 & -33.9829297188111 \tabularnewline
100 & 118 & 110.591536488645 & 7.40846351135491 \tabularnewline
101 & 73 & 74.7615159583282 & -1.76151595832821 \tabularnewline
102 & 119 & 103.190654722845 & 15.8093452771545 \tabularnewline
103 & 104 & 91.4101629306969 & 12.5898370693031 \tabularnewline
104 & 107 & 88.2172853786641 & 18.7827146213359 \tabularnewline
105 & 99 & 92.331448261128 & 6.66855173887194 \tabularnewline
106 & 90 & 109.996787565243 & -19.9967875652431 \tabularnewline
107 & 197 & 166.808340866259 & 30.1916591337414 \tabularnewline
108 & 36 & 62.3722741826195 & -26.3722741826195 \tabularnewline
109 & 85 & 91.1012337900474 & -6.10123379004744 \tabularnewline
110 & 139 & 129.659739194517 & 9.34026080548329 \tabularnewline
111 & 106 & 113.371917971654 & -7.37191797165358 \tabularnewline
112 & 50 & 94.578499490121 & -44.5784994901211 \tabularnewline
113 & 64 & 50.6318678611126 & 13.3681321388874 \tabularnewline
114 & 31 & 66.2745509782957 & -35.2745509782957 \tabularnewline
115 & 63 & 99.1562441862867 & -36.1562441862867 \tabularnewline
116 & 92 & 101.178296978974 & -9.17829697897365 \tabularnewline
117 & 106 & 111.72299581637 & -5.72299581637023 \tabularnewline
118 & 63 & 59.5186559062338 & 3.48134409376622 \tabularnewline
119 & 69 & 69.4874851768073 & -0.487485176807308 \tabularnewline
120 & 41 & 51.2346949306524 & -10.2346949306524 \tabularnewline
121 & 56 & 63.4437891327191 & -7.44378913271913 \tabularnewline
122 & 25 & 33.615844612019 & -8.61584461201899 \tabularnewline
123 & 65 & 52.0344648754605 & 12.9655351245395 \tabularnewline
124 & 93 & 93.7768381493404 & -0.776838149340361 \tabularnewline
125 & 114 & 98.9134875271603 & 15.0865124728397 \tabularnewline
126 & 38 & 29.4841267016974 & 8.51587329830261 \tabularnewline
127 & 44 & 38.320839736112 & 5.67916026388805 \tabularnewline
128 & 87 & 69.0648884394523 & 17.9351115605477 \tabularnewline
129 & 110 & 138.298441948069 & -28.2984419480685 \tabularnewline
130 & 0 & -0.135972592301242 & 0.135972592301242 \tabularnewline
131 & 27 & 22.2563794893746 & 4.74362051062538 \tabularnewline
132 & 83 & 103.57127279201 & -20.5712727920099 \tabularnewline
133 & 30 & 30.093121073307 & -0.093121073306999 \tabularnewline
134 & 80 & 74.9923676661623 & 5.00763233383773 \tabularnewline
135 & 98 & 109.719905604196 & -11.7199056041962 \tabularnewline
136 & 82 & 110.0929169945 & -28.0929169945003 \tabularnewline
137 & 0 & -4.05662500077657 & 4.05662500077657 \tabularnewline
138 & 60 & 77.2665963492723 & -17.2665963492723 \tabularnewline
139 & 28 & 33.3724865404005 & -5.37248654040046 \tabularnewline
140 & 9 & 19.6165711857846 & -10.6165711857846 \tabularnewline
141 & 33 & 34.4785337915379 & -1.47853379153795 \tabularnewline
142 & 59 & 62.0905316411869 & -3.09053164118693 \tabularnewline
143 & 49 & 48.1424905665669 & 0.857509433433077 \tabularnewline
144 & 115 & 110.473001300189 & 4.52699869981072 \tabularnewline
145 & 140 & 120.789682048588 & 19.210317951412 \tabularnewline
146 & 49 & 63.759021196048 & -14.7590211960481 \tabularnewline
147 & 120 & 108.510745957759 & 11.4892540422412 \tabularnewline
148 & 66 & 68.6591744468837 & -2.65917444688374 \tabularnewline
149 & 21 & 19.3156929919744 & 1.68430700802563 \tabularnewline
150 & 124 & 103.82478329616 & 20.1752167038395 \tabularnewline
151 & 152 & 137.195999224434 & 14.8040007755658 \tabularnewline
152 & 139 & 128.236039221291 & 10.7639607787093 \tabularnewline
153 & 38 & 43.846497639211 & -5.846497639211 \tabularnewline
154 & 144 & 136.050504739677 & 7.94949526032252 \tabularnewline
155 & 120 & 130.191908094301 & -10.1919080943005 \tabularnewline
156 & 160 & 154.423094159117 & 5.57690584088317 \tabularnewline
157 & 114 & 94.8558538058194 & 19.1441461941806 \tabularnewline
158 & 39 & 37.0170662018319 & 1.98293379816812 \tabularnewline
159 & 78 & 79.9887955209322 & -1.98879552093219 \tabularnewline
160 & 119 & 97.2017373530033 & 21.7982626469967 \tabularnewline
161 & 141 & 132.909641369079 & 8.09035863092068 \tabularnewline
162 & 101 & 82.6120790618465 & 18.3879209381535 \tabularnewline
163 & 56 & 48.7367153900662 & 7.26328460993385 \tabularnewline
164 & 133 & 120.198552683127 & 12.801447316873 \tabularnewline
165 & 83 & 88.5625929209998 & -5.56259292099983 \tabularnewline
166 & 116 & 113.409545922888 & 2.59045407711245 \tabularnewline
167 & 90 & 99.6792660017333 & -9.67926600173333 \tabularnewline
168 & 36 & 76.7587114179932 & -40.7587114179932 \tabularnewline
169 & 50 & 63.0212119520473 & -13.0212119520473 \tabularnewline
170 & 61 & 58.4311110478496 & 2.56888895215043 \tabularnewline
171 & 97 & 100.409783245109 & -3.4097832451088 \tabularnewline
172 & 98 & 103.794554297624 & -5.79455429762384 \tabularnewline
173 & 78 & 61.9409687596506 & 16.0590312403494 \tabularnewline
174 & 117 & 129.500494418949 & -12.5004944189492 \tabularnewline
175 & 148 & 130.389346001322 & 17.610653998678 \tabularnewline
176 & 41 & 37.9372430273935 & 3.06275697260648 \tabularnewline
177 & 105 & 103.328031307112 & 1.6719686928876 \tabularnewline
178 & 55 & 51.1443064677209 & 3.85569353227914 \tabularnewline
179 & 132 & 131.1609971668 & 0.839002833199702 \tabularnewline
180 & 44 & 44.1067116226312 & -0.106711622631155 \tabularnewline
181 & 21 & 21.1374150573855 & -0.137415057385474 \tabularnewline
182 & 50 & 53.1282057272292 & -3.12820572722917 \tabularnewline
183 & 0 & -5.17943313119232 & 5.17943313119232 \tabularnewline
184 & 73 & 91.6749800901528 & -18.6749800901528 \tabularnewline
185 & 86 & 123.934746146251 & -37.9347461462511 \tabularnewline
186 & 0 & -5.47111604604053 & 5.47111604604053 \tabularnewline
187 & 13 & 10.3383687676931 & 2.66163123230691 \tabularnewline
188 & 4 & -2.59443207392444 & 6.59443207392444 \tabularnewline
189 & 57 & 49.9617171909302 & 7.03828280906983 \tabularnewline
190 & 48 & 91.9329392963812 & -43.9329392963812 \tabularnewline
191 & 46 & 72.6309644449701 & -26.6309644449701 \tabularnewline
192 & 48 & 45.8042790842813 & 2.19572091571865 \tabularnewline
193 & 32 & 34.474333029414 & -2.47433302941404 \tabularnewline
194 & 68 & 67.163481306808 & 0.836518693192051 \tabularnewline
195 & 87 & 69.1088121240684 & 17.8911878759316 \tabularnewline
196 & 43 & 39.5309709240616 & 3.4690290759384 \tabularnewline
197 & 67 & 51.2424894160115 & 15.7575105839885 \tabularnewline
198 & 46 & 34.9938920182201 & 11.0061079817799 \tabularnewline
199 & 46 & 49.2566728880876 & -3.25667288808761 \tabularnewline
200 & 56 & 43.19126338034 & 12.80873661966 \tabularnewline
201 & 48 & 45.3769031441948 & 2.62309685580519 \tabularnewline
202 & 44 & 65.483177688298 & -21.4831776882981 \tabularnewline
203 & 60 & 45.3402839842037 & 14.6597160157963 \tabularnewline
204 & 65 & 49.7283127408737 & 15.2716872591263 \tabularnewline
205 & 55 & 51.364280132111 & 3.63571986788904 \tabularnewline
206 & 38 & 53.6208459784255 & -15.6208459784255 \tabularnewline
207 & 52 & 47.0793287043687 & 4.92067129563129 \tabularnewline
208 & 60 & 48.5175064829455 & 11.4824935170545 \tabularnewline
209 & 54 & 53.4374892008496 & 0.562510799150398 \tabularnewline
210 & 86 & 65.5755510177385 & 20.4244489822615 \tabularnewline
211 & 24 & 24.4438901258168 & -0.443890125816828 \tabularnewline
212 & 52 & 51.8336198533306 & 0.166380146669365 \tabularnewline
213 & 49 & 49.5540306526744 & -0.554030652674452 \tabularnewline
214 & 61 & 46.3414419123473 & 14.6585580876527 \tabularnewline
215 & 61 & 61.2153960430303 & -0.215396043030282 \tabularnewline
216 & 81 & 59.0969896270834 & 21.9030103729166 \tabularnewline
217 & 43 & 36.508081219833 & 6.49191878016702 \tabularnewline
218 & 40 & 34.3880642664296 & 5.6119357335704 \tabularnewline
219 & 40 & 45.127230061824 & -5.12723006182399 \tabularnewline
220 & 56 & 43.3192910583134 & 12.6807089416866 \tabularnewline
221 & 68 & 57.1842341262521 & 10.8157658737479 \tabularnewline
222 & 79 & 67.1897339671502 & 11.8102660328498 \tabularnewline
223 & 47 & 54.3674487633872 & -7.36744876338715 \tabularnewline
224 & 57 & 50.9245454862874 & 6.0754545137126 \tabularnewline
225 & 41 & 44.3130223319547 & -3.31302233195469 \tabularnewline
226 & 29 & 38.8994425538809 & -9.89944255388088 \tabularnewline
227 & 3 & 20.039004746541 & -17.039004746541 \tabularnewline
228 & 60 & 48.5431616521234 & 11.4568383478766 \tabularnewline
229 & 30 & 41.5554337342984 & -11.5554337342984 \tabularnewline
230 & 79 & 67.5035090541937 & 11.4964909458063 \tabularnewline
231 & 47 & 44.3747497505182 & 2.6252502494818 \tabularnewline
232 & 40 & 42.8005339730603 & -2.80053397306029 \tabularnewline
233 & 48 & 44.2036229083888 & 3.79637709161118 \tabularnewline
234 & 36 & 46.2585459005776 & -10.2585459005776 \tabularnewline
235 & 42 & 58.9468709714168 & -16.9468709714168 \tabularnewline
236 & 49 & 52.4007649107833 & -3.40076491078333 \tabularnewline
237 & 57 & 52.0112802026524 & 4.98871979734758 \tabularnewline
238 & 12 & 46.6525454606327 & -34.6525454606327 \tabularnewline
239 & 40 & 48.5877591435606 & -8.5877591435606 \tabularnewline
240 & 43 & 42.9005193545421 & 0.0994806454579105 \tabularnewline
241 & 33 & 42.689019205412 & -9.689019205412 \tabularnewline
242 & 77 & 65.0437534348567 & 11.9562465651433 \tabularnewline
243 & 43 & 46.1340787696092 & -3.13407876960921 \tabularnewline
244 & 45 & 38.185947412939 & 6.814052587061 \tabularnewline
245 & 47 & 41.9734004715684 & 5.02659952843157 \tabularnewline
246 & 43 & 48.6887400271505 & -5.68874002715048 \tabularnewline
247 & 45 & 48.1906091686969 & -3.19060916869695 \tabularnewline
248 & 50 & 41.0769608671774 & 8.92303913282257 \tabularnewline
249 & 35 & 27.756919983979 & 7.24308001602095 \tabularnewline
250 & 7 & 13.7711164838827 & -6.77111648388273 \tabularnewline
251 & 71 & 65.3694078554798 & 5.63059214452015 \tabularnewline
252 & 67 & 62.7439763119601 & 4.25602368803992 \tabularnewline
253 & 0 & -0.652005066470264 & 0.652005066470264 \tabularnewline
254 & 62 & 49.8798087585304 & 12.1201912414696 \tabularnewline
255 & 54 & 46.9387190560574 & 7.06128094394264 \tabularnewline
256 & 4 & 8.11300139586678 & -4.11300139586678 \tabularnewline
257 & 25 & 26.5095984534331 & -1.50959845343305 \tabularnewline
258 & 40 & 45.4881410937792 & -5.48814109377924 \tabularnewline
259 & 38 & 43.7039011545396 & -5.70390115453957 \tabularnewline
260 & 19 & 23.4870385898094 & -4.48703858980936 \tabularnewline
261 & 17 & 41.4758128589825 & -24.4758128589825 \tabularnewline
262 & 67 & 51.3326847884222 & 15.6673152115778 \tabularnewline
263 & 14 & 17.1140786150699 & -3.11407861506989 \tabularnewline
264 & 30 & 43.5967265332109 & -13.5967265332109 \tabularnewline
265 & 54 & 37.7495226759174 & 16.2504773240826 \tabularnewline
266 & 35 & 41.7833752730522 & -6.7833752730522 \tabularnewline
267 & 59 & 52.152088145217 & 6.84791185478305 \tabularnewline
268 & 24 & 33.7634125762546 & -9.76341257625464 \tabularnewline
269 & 58 & 47.3443257687301 & 10.6556742312699 \tabularnewline
270 & 42 & 60.4670662922922 & -18.4670662922922 \tabularnewline
271 & 46 & 54.4600700732783 & -8.46007007327828 \tabularnewline
272 & 61 & 44.1531022677658 & 16.8468977322342 \tabularnewline
273 & 3 & 0.216293115721667 & 2.78370688427833 \tabularnewline
274 & 52 & 49.418972086223 & 2.58102791377703 \tabularnewline
275 & 25 & 28.3266251344185 & -3.32662513441851 \tabularnewline
276 & 40 & 55.829928218785 & -15.829928218785 \tabularnewline
277 & 32 & 31.2003188876734 & 0.799681112326552 \tabularnewline
278 & 4 & 2.01389613499354 & 1.98610386500646 \tabularnewline
279 & 49 & 42.2516292583841 & 6.74837074161594 \tabularnewline
280 & 63 & 46.8174610531189 & 16.1825389468811 \tabularnewline
281 & 67 & 53.8512764688046 & 13.1487235311954 \tabularnewline
282 & 32 & 38.719503498302 & -6.71950349830198 \tabularnewline
283 & 23 & 31.4597547276713 & -8.45975472767126 \tabularnewline
284 & 7 & 8.54851784345082 & -1.54851784345082 \tabularnewline
285 & 54 & 42.4478062851382 & 11.5521937148618 \tabularnewline
286 & 37 & 56.4879388159728 & -19.4879388159728 \tabularnewline
287 & 35 & 32.7921623863976 & 2.20783761360237 \tabularnewline
288 & 51 & 43.3302081882678 & 7.66979181173225 \tabularnewline
289 & 39 & 43.88739546965 & -4.88739546964997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155913&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]94[/C][C]100.026343272609[/C][C]-6.0263432726094[/C][/ROW]
[ROW][C]2[/C][C]103[/C][C]86.014303790391[/C][C]16.9856962096089[/C][/ROW]
[ROW][C]3[/C][C]93[/C][C]114.803868408768[/C][C]-21.8038684087676[/C][/ROW]
[ROW][C]4[/C][C]103[/C][C]97.2504331321846[/C][C]5.74956686781537[/C][/ROW]
[ROW][C]5[/C][C]51[/C][C]68.0040669004422[/C][C]-17.0040669004422[/C][/ROW]
[ROW][C]6[/C][C]70[/C][C]68.7879556289648[/C][C]1.21204437103516[/C][/ROW]
[ROW][C]7[/C][C]91[/C][C]90.4083352678012[/C][C]0.591664732198777[/C][/ROW]
[ROW][C]8[/C][C]22[/C][C]46.6058393243416[/C][C]-24.6058393243416[/C][/ROW]
[ROW][C]9[/C][C]38[/C][C]31.5464819570607[/C][C]6.45351804293928[/C][/ROW]
[ROW][C]10[/C][C]93[/C][C]78.3204032008927[/C][C]14.6795967991073[/C][/ROW]
[ROW][C]11[/C][C]60[/C][C]79.6451446960541[/C][C]-19.6451446960541[/C][/ROW]
[ROW][C]12[/C][C]123[/C][C]120.906706069438[/C][C]2.09329393056174[/C][/ROW]
[ROW][C]13[/C][C]148[/C][C]135.229834563481[/C][C]12.7701654365194[/C][/ROW]
[ROW][C]14[/C][C]90[/C][C]88.300316659165[/C][C]1.69968334083492[/C][/ROW]
[ROW][C]15[/C][C]124[/C][C]126.288482370352[/C][C]-2.28848237035199[/C][/ROW]
[ROW][C]16[/C][C]70[/C][C]105.183762413751[/C][C]-35.1837624137509[/C][/ROW]
[ROW][C]17[/C][C]168[/C][C]159.168605063047[/C][C]8.83139493695256[/C][/ROW]
[ROW][C]18[/C][C]115[/C][C]101.357098157689[/C][C]13.6429018423112[/C][/ROW]
[ROW][C]19[/C][C]71[/C][C]98.8388456701767[/C][C]-27.8388456701767[/C][/ROW]
[ROW][C]20[/C][C]66[/C][C]75.0540802702526[/C][C]-9.0540802702526[/C][/ROW]
[ROW][C]21[/C][C]134[/C][C]119.167363816555[/C][C]14.8326361834451[/C][/ROW]
[ROW][C]22[/C][C]117[/C][C]117.787736695203[/C][C]-0.787736695202567[/C][/ROW]
[ROW][C]23[/C][C]108[/C][C]97.307473020634[/C][C]10.692526979366[/C][/ROW]
[ROW][C]24[/C][C]84[/C][C]78.0344141446868[/C][C]5.96558585531315[/C][/ROW]
[ROW][C]25[/C][C]156[/C][C]120.006507520093[/C][C]35.9934924799074[/C][/ROW]
[ROW][C]26[/C][C]120[/C][C]111.449996228438[/C][C]8.55000377156157[/C][/ROW]
[ROW][C]27[/C][C]114[/C][C]97.6432957847568[/C][C]16.3567042152432[/C][/ROW]
[ROW][C]28[/C][C]94[/C][C]100.962489993492[/C][C]-6.96248999349206[/C][/ROW]
[ROW][C]29[/C][C]120[/C][C]110.645290209691[/C][C]9.3547097903091[/C][/ROW]
[ROW][C]30[/C][C]81[/C][C]74.2999713555375[/C][C]6.70002864446255[/C][/ROW]
[ROW][C]31[/C][C]110[/C][C]111.966005055011[/C][C]-1.96600505501059[/C][/ROW]
[ROW][C]32[/C][C]133[/C][C]114.034940867844[/C][C]18.9650591321561[/C][/ROW]
[ROW][C]33[/C][C]122[/C][C]124.252819916018[/C][C]-2.25281991601845[/C][/ROW]
[ROW][C]34[/C][C]158[/C][C]140.918541145872[/C][C]17.0814588541283[/C][/ROW]
[ROW][C]35[/C][C]109[/C][C]86.0093552529059[/C][C]22.9906447470941[/C][/ROW]
[ROW][C]36[/C][C]124[/C][C]112.169823955963[/C][C]11.8301760440371[/C][/ROW]
[ROW][C]37[/C][C]39[/C][C]39.5239392195626[/C][C]-0.523939219562573[/C][/ROW]
[ROW][C]38[/C][C]92[/C][C]98.7475473570687[/C][C]-6.74754735706868[/C][/ROW]
[ROW][C]39[/C][C]126[/C][C]118.940788411289[/C][C]7.05921158871092[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]-4.8140246191202[/C][C]4.8140246191202[/C][/ROW]
[ROW][C]41[/C][C]70[/C][C]87.1549244394339[/C][C]-17.1549244394339[/C][/ROW]
[ROW][C]42[/C][C]37[/C][C]42.4748653380247[/C][C]-5.47486533802465[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]52.6949853095481[/C][C]-14.6949853095481[/C][/ROW]
[ROW][C]44[/C][C]120[/C][C]106.874417723961[/C][C]13.125582276039[/C][/ROW]
[ROW][C]45[/C][C]93[/C][C]98.3873687092119[/C][C]-5.38736870921188[/C][/ROW]
[ROW][C]46[/C][C]95[/C][C]103.98388030989[/C][C]-8.98388030988964[/C][/ROW]
[ROW][C]47[/C][C]77[/C][C]64.1310584328054[/C][C]12.8689415671946[/C][/ROW]
[ROW][C]48[/C][C]90[/C][C]87.0341087391085[/C][C]2.96589126089154[/C][/ROW]
[ROW][C]49[/C][C]80[/C][C]82.4877162868019[/C][C]-2.48771628680186[/C][/ROW]
[ROW][C]50[/C][C]31[/C][C]111.334562528648[/C][C]-80.3345625286481[/C][/ROW]
[ROW][C]51[/C][C]110[/C][C]107.221795806002[/C][C]2.77820419399822[/C][/ROW]
[ROW][C]52[/C][C]66[/C][C]72.7967232060782[/C][C]-6.79672320607815[/C][/ROW]
[ROW][C]53[/C][C]138[/C][C]123.503316990252[/C][C]14.4966830097482[/C][/ROW]
[ROW][C]54[/C][C]133[/C][C]131.559032623781[/C][C]1.44096737621895[/C][/ROW]
[ROW][C]55[/C][C]113[/C][C]102.354400622562[/C][C]10.6455993774382[/C][/ROW]
[ROW][C]56[/C][C]100[/C][C]91.7516114911915[/C][C]8.24838850880848[/C][/ROW]
[ROW][C]57[/C][C]7[/C][C]6.46126768035889[/C][C]0.538732319641108[/C][/ROW]
[ROW][C]58[/C][C]140[/C][C]126.485963558478[/C][C]13.5140364415219[/C][/ROW]
[ROW][C]59[/C][C]61[/C][C]49.7575097506049[/C][C]11.2424902493951[/C][/ROW]
[ROW][C]60[/C][C]41[/C][C]40.6830082474045[/C][C]0.31699175259552[/C][/ROW]
[ROW][C]61[/C][C]96[/C][C]93.4855170636078[/C][C]2.51448293639221[/C][/ROW]
[ROW][C]62[/C][C]164[/C][C]144.557721961513[/C][C]19.4422780384874[/C][/ROW]
[ROW][C]63[/C][C]78[/C][C]84.7039480768913[/C][C]-6.7039480768913[/C][/ROW]
[ROW][C]64[/C][C]49[/C][C]46.5767226249511[/C][C]2.42327737504894[/C][/ROW]
[ROW][C]65[/C][C]102[/C][C]98.4943776965995[/C][C]3.50562230340046[/C][/ROW]
[ROW][C]66[/C][C]124[/C][C]119.406458003763[/C][C]4.59354199623663[/C][/ROW]
[ROW][C]67[/C][C]99[/C][C]87.7043727646246[/C][C]11.2956272353754[/C][/ROW]
[ROW][C]68[/C][C]129[/C][C]131.969132386179[/C][C]-2.96913238617944[/C][/ROW]
[ROW][C]69[/C][C]62[/C][C]85.0858690872856[/C][C]-23.0858690872856[/C][/ROW]
[ROW][C]70[/C][C]73[/C][C]107.176792250071[/C][C]-34.1767922500708[/C][/ROW]
[ROW][C]71[/C][C]114[/C][C]98.766205467175[/C][C]15.233794532825[/C][/ROW]
[ROW][C]72[/C][C]99[/C][C]89.0168715084674[/C][C]9.9831284915326[/C][/ROW]
[ROW][C]73[/C][C]70[/C][C]83.125769661991[/C][C]-13.1257696619911[/C][/ROW]
[ROW][C]74[/C][C]104[/C][C]84.8620271034217[/C][C]19.1379728965783[/C][/ROW]
[ROW][C]75[/C][C]116[/C][C]114.314960691589[/C][C]1.68503930841114[/C][/ROW]
[ROW][C]76[/C][C]91[/C][C]93.7037843124068[/C][C]-2.70378431240679[/C][/ROW]
[ROW][C]77[/C][C]74[/C][C]78.539123091938[/C][C]-4.53912309193797[/C][/ROW]
[ROW][C]78[/C][C]138[/C][C]123.507350595509[/C][C]14.4926494044909[/C][/ROW]
[ROW][C]79[/C][C]67[/C][C]63.1677200380542[/C][C]3.83227996194585[/C][/ROW]
[ROW][C]80[/C][C]151[/C][C]122.718226950103[/C][C]28.2817730498965[/C][/ROW]
[ROW][C]81[/C][C]72[/C][C]86.336627988144[/C][C]-14.3366279881441[/C][/ROW]
[ROW][C]82[/C][C]120[/C][C]108.704207135003[/C][C]11.2957928649967[/C][/ROW]
[ROW][C]83[/C][C]115[/C][C]107.609162426862[/C][C]7.39083757313752[/C][/ROW]
[ROW][C]84[/C][C]105[/C][C]92.8670185218026[/C][C]12.1329814781974[/C][/ROW]
[ROW][C]85[/C][C]104[/C][C]109.05262496524[/C][C]-5.0526249652402[/C][/ROW]
[ROW][C]86[/C][C]108[/C][C]96.7713270019015[/C][C]11.2286729980985[/C][/ROW]
[ROW][C]87[/C][C]98[/C][C]99.607503971686[/C][C]-1.60750397168612[/C][/ROW]
[ROW][C]88[/C][C]69[/C][C]67.2933634576947[/C][C]1.70663654230532[/C][/ROW]
[ROW][C]89[/C][C]111[/C][C]127.943000687367[/C][C]-16.9430006873667[/C][/ROW]
[ROW][C]90[/C][C]99[/C][C]74.2590118016889[/C][C]24.7409881983111[/C][/ROW]
[ROW][C]91[/C][C]71[/C][C]114.475117822195[/C][C]-43.475117822195[/C][/ROW]
[ROW][C]92[/C][C]27[/C][C]24.6762096133623[/C][C]2.32379038663772[/C][/ROW]
[ROW][C]93[/C][C]69[/C][C]66.6926056777408[/C][C]2.30739432225923[/C][/ROW]
[ROW][C]94[/C][C]107[/C][C]90.2268612084574[/C][C]16.7731387915426[/C][/ROW]
[ROW][C]95[/C][C]73[/C][C]61.449644927786[/C][C]11.5503550722141[/C][/ROW]
[ROW][C]96[/C][C]107[/C][C]91.435570700893[/C][C]15.5644292991071[/C][/ROW]
[ROW][C]97[/C][C]93[/C][C]139.787755581764[/C][C]-46.7877555817644[/C][/ROW]
[ROW][C]98[/C][C]129[/C][C]121.24477897759[/C][C]7.75522102240988[/C][/ROW]
[ROW][C]99[/C][C]69[/C][C]102.982929718811[/C][C]-33.9829297188111[/C][/ROW]
[ROW][C]100[/C][C]118[/C][C]110.591536488645[/C][C]7.40846351135491[/C][/ROW]
[ROW][C]101[/C][C]73[/C][C]74.7615159583282[/C][C]-1.76151595832821[/C][/ROW]
[ROW][C]102[/C][C]119[/C][C]103.190654722845[/C][C]15.8093452771545[/C][/ROW]
[ROW][C]103[/C][C]104[/C][C]91.4101629306969[/C][C]12.5898370693031[/C][/ROW]
[ROW][C]104[/C][C]107[/C][C]88.2172853786641[/C][C]18.7827146213359[/C][/ROW]
[ROW][C]105[/C][C]99[/C][C]92.331448261128[/C][C]6.66855173887194[/C][/ROW]
[ROW][C]106[/C][C]90[/C][C]109.996787565243[/C][C]-19.9967875652431[/C][/ROW]
[ROW][C]107[/C][C]197[/C][C]166.808340866259[/C][C]30.1916591337414[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]62.3722741826195[/C][C]-26.3722741826195[/C][/ROW]
[ROW][C]109[/C][C]85[/C][C]91.1012337900474[/C][C]-6.10123379004744[/C][/ROW]
[ROW][C]110[/C][C]139[/C][C]129.659739194517[/C][C]9.34026080548329[/C][/ROW]
[ROW][C]111[/C][C]106[/C][C]113.371917971654[/C][C]-7.37191797165358[/C][/ROW]
[ROW][C]112[/C][C]50[/C][C]94.578499490121[/C][C]-44.5784994901211[/C][/ROW]
[ROW][C]113[/C][C]64[/C][C]50.6318678611126[/C][C]13.3681321388874[/C][/ROW]
[ROW][C]114[/C][C]31[/C][C]66.2745509782957[/C][C]-35.2745509782957[/C][/ROW]
[ROW][C]115[/C][C]63[/C][C]99.1562441862867[/C][C]-36.1562441862867[/C][/ROW]
[ROW][C]116[/C][C]92[/C][C]101.178296978974[/C][C]-9.17829697897365[/C][/ROW]
[ROW][C]117[/C][C]106[/C][C]111.72299581637[/C][C]-5.72299581637023[/C][/ROW]
[ROW][C]118[/C][C]63[/C][C]59.5186559062338[/C][C]3.48134409376622[/C][/ROW]
[ROW][C]119[/C][C]69[/C][C]69.4874851768073[/C][C]-0.487485176807308[/C][/ROW]
[ROW][C]120[/C][C]41[/C][C]51.2346949306524[/C][C]-10.2346949306524[/C][/ROW]
[ROW][C]121[/C][C]56[/C][C]63.4437891327191[/C][C]-7.44378913271913[/C][/ROW]
[ROW][C]122[/C][C]25[/C][C]33.615844612019[/C][C]-8.61584461201899[/C][/ROW]
[ROW][C]123[/C][C]65[/C][C]52.0344648754605[/C][C]12.9655351245395[/C][/ROW]
[ROW][C]124[/C][C]93[/C][C]93.7768381493404[/C][C]-0.776838149340361[/C][/ROW]
[ROW][C]125[/C][C]114[/C][C]98.9134875271603[/C][C]15.0865124728397[/C][/ROW]
[ROW][C]126[/C][C]38[/C][C]29.4841267016974[/C][C]8.51587329830261[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]38.320839736112[/C][C]5.67916026388805[/C][/ROW]
[ROW][C]128[/C][C]87[/C][C]69.0648884394523[/C][C]17.9351115605477[/C][/ROW]
[ROW][C]129[/C][C]110[/C][C]138.298441948069[/C][C]-28.2984419480685[/C][/ROW]
[ROW][C]130[/C][C]0[/C][C]-0.135972592301242[/C][C]0.135972592301242[/C][/ROW]
[ROW][C]131[/C][C]27[/C][C]22.2563794893746[/C][C]4.74362051062538[/C][/ROW]
[ROW][C]132[/C][C]83[/C][C]103.57127279201[/C][C]-20.5712727920099[/C][/ROW]
[ROW][C]133[/C][C]30[/C][C]30.093121073307[/C][C]-0.093121073306999[/C][/ROW]
[ROW][C]134[/C][C]80[/C][C]74.9923676661623[/C][C]5.00763233383773[/C][/ROW]
[ROW][C]135[/C][C]98[/C][C]109.719905604196[/C][C]-11.7199056041962[/C][/ROW]
[ROW][C]136[/C][C]82[/C][C]110.0929169945[/C][C]-28.0929169945003[/C][/ROW]
[ROW][C]137[/C][C]0[/C][C]-4.05662500077657[/C][C]4.05662500077657[/C][/ROW]
[ROW][C]138[/C][C]60[/C][C]77.2665963492723[/C][C]-17.2665963492723[/C][/ROW]
[ROW][C]139[/C][C]28[/C][C]33.3724865404005[/C][C]-5.37248654040046[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]19.6165711857846[/C][C]-10.6165711857846[/C][/ROW]
[ROW][C]141[/C][C]33[/C][C]34.4785337915379[/C][C]-1.47853379153795[/C][/ROW]
[ROW][C]142[/C][C]59[/C][C]62.0905316411869[/C][C]-3.09053164118693[/C][/ROW]
[ROW][C]143[/C][C]49[/C][C]48.1424905665669[/C][C]0.857509433433077[/C][/ROW]
[ROW][C]144[/C][C]115[/C][C]110.473001300189[/C][C]4.52699869981072[/C][/ROW]
[ROW][C]145[/C][C]140[/C][C]120.789682048588[/C][C]19.210317951412[/C][/ROW]
[ROW][C]146[/C][C]49[/C][C]63.759021196048[/C][C]-14.7590211960481[/C][/ROW]
[ROW][C]147[/C][C]120[/C][C]108.510745957759[/C][C]11.4892540422412[/C][/ROW]
[ROW][C]148[/C][C]66[/C][C]68.6591744468837[/C][C]-2.65917444688374[/C][/ROW]
[ROW][C]149[/C][C]21[/C][C]19.3156929919744[/C][C]1.68430700802563[/C][/ROW]
[ROW][C]150[/C][C]124[/C][C]103.82478329616[/C][C]20.1752167038395[/C][/ROW]
[ROW][C]151[/C][C]152[/C][C]137.195999224434[/C][C]14.8040007755658[/C][/ROW]
[ROW][C]152[/C][C]139[/C][C]128.236039221291[/C][C]10.7639607787093[/C][/ROW]
[ROW][C]153[/C][C]38[/C][C]43.846497639211[/C][C]-5.846497639211[/C][/ROW]
[ROW][C]154[/C][C]144[/C][C]136.050504739677[/C][C]7.94949526032252[/C][/ROW]
[ROW][C]155[/C][C]120[/C][C]130.191908094301[/C][C]-10.1919080943005[/C][/ROW]
[ROW][C]156[/C][C]160[/C][C]154.423094159117[/C][C]5.57690584088317[/C][/ROW]
[ROW][C]157[/C][C]114[/C][C]94.8558538058194[/C][C]19.1441461941806[/C][/ROW]
[ROW][C]158[/C][C]39[/C][C]37.0170662018319[/C][C]1.98293379816812[/C][/ROW]
[ROW][C]159[/C][C]78[/C][C]79.9887955209322[/C][C]-1.98879552093219[/C][/ROW]
[ROW][C]160[/C][C]119[/C][C]97.2017373530033[/C][C]21.7982626469967[/C][/ROW]
[ROW][C]161[/C][C]141[/C][C]132.909641369079[/C][C]8.09035863092068[/C][/ROW]
[ROW][C]162[/C][C]101[/C][C]82.6120790618465[/C][C]18.3879209381535[/C][/ROW]
[ROW][C]163[/C][C]56[/C][C]48.7367153900662[/C][C]7.26328460993385[/C][/ROW]
[ROW][C]164[/C][C]133[/C][C]120.198552683127[/C][C]12.801447316873[/C][/ROW]
[ROW][C]165[/C][C]83[/C][C]88.5625929209998[/C][C]-5.56259292099983[/C][/ROW]
[ROW][C]166[/C][C]116[/C][C]113.409545922888[/C][C]2.59045407711245[/C][/ROW]
[ROW][C]167[/C][C]90[/C][C]99.6792660017333[/C][C]-9.67926600173333[/C][/ROW]
[ROW][C]168[/C][C]36[/C][C]76.7587114179932[/C][C]-40.7587114179932[/C][/ROW]
[ROW][C]169[/C][C]50[/C][C]63.0212119520473[/C][C]-13.0212119520473[/C][/ROW]
[ROW][C]170[/C][C]61[/C][C]58.4311110478496[/C][C]2.56888895215043[/C][/ROW]
[ROW][C]171[/C][C]97[/C][C]100.409783245109[/C][C]-3.4097832451088[/C][/ROW]
[ROW][C]172[/C][C]98[/C][C]103.794554297624[/C][C]-5.79455429762384[/C][/ROW]
[ROW][C]173[/C][C]78[/C][C]61.9409687596506[/C][C]16.0590312403494[/C][/ROW]
[ROW][C]174[/C][C]117[/C][C]129.500494418949[/C][C]-12.5004944189492[/C][/ROW]
[ROW][C]175[/C][C]148[/C][C]130.389346001322[/C][C]17.610653998678[/C][/ROW]
[ROW][C]176[/C][C]41[/C][C]37.9372430273935[/C][C]3.06275697260648[/C][/ROW]
[ROW][C]177[/C][C]105[/C][C]103.328031307112[/C][C]1.6719686928876[/C][/ROW]
[ROW][C]178[/C][C]55[/C][C]51.1443064677209[/C][C]3.85569353227914[/C][/ROW]
[ROW][C]179[/C][C]132[/C][C]131.1609971668[/C][C]0.839002833199702[/C][/ROW]
[ROW][C]180[/C][C]44[/C][C]44.1067116226312[/C][C]-0.106711622631155[/C][/ROW]
[ROW][C]181[/C][C]21[/C][C]21.1374150573855[/C][C]-0.137415057385474[/C][/ROW]
[ROW][C]182[/C][C]50[/C][C]53.1282057272292[/C][C]-3.12820572722917[/C][/ROW]
[ROW][C]183[/C][C]0[/C][C]-5.17943313119232[/C][C]5.17943313119232[/C][/ROW]
[ROW][C]184[/C][C]73[/C][C]91.6749800901528[/C][C]-18.6749800901528[/C][/ROW]
[ROW][C]185[/C][C]86[/C][C]123.934746146251[/C][C]-37.9347461462511[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]-5.47111604604053[/C][C]5.47111604604053[/C][/ROW]
[ROW][C]187[/C][C]13[/C][C]10.3383687676931[/C][C]2.66163123230691[/C][/ROW]
[ROW][C]188[/C][C]4[/C][C]-2.59443207392444[/C][C]6.59443207392444[/C][/ROW]
[ROW][C]189[/C][C]57[/C][C]49.9617171909302[/C][C]7.03828280906983[/C][/ROW]
[ROW][C]190[/C][C]48[/C][C]91.9329392963812[/C][C]-43.9329392963812[/C][/ROW]
[ROW][C]191[/C][C]46[/C][C]72.6309644449701[/C][C]-26.6309644449701[/C][/ROW]
[ROW][C]192[/C][C]48[/C][C]45.8042790842813[/C][C]2.19572091571865[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]34.474333029414[/C][C]-2.47433302941404[/C][/ROW]
[ROW][C]194[/C][C]68[/C][C]67.163481306808[/C][C]0.836518693192051[/C][/ROW]
[ROW][C]195[/C][C]87[/C][C]69.1088121240684[/C][C]17.8911878759316[/C][/ROW]
[ROW][C]196[/C][C]43[/C][C]39.5309709240616[/C][C]3.4690290759384[/C][/ROW]
[ROW][C]197[/C][C]67[/C][C]51.2424894160115[/C][C]15.7575105839885[/C][/ROW]
[ROW][C]198[/C][C]46[/C][C]34.9938920182201[/C][C]11.0061079817799[/C][/ROW]
[ROW][C]199[/C][C]46[/C][C]49.2566728880876[/C][C]-3.25667288808761[/C][/ROW]
[ROW][C]200[/C][C]56[/C][C]43.19126338034[/C][C]12.80873661966[/C][/ROW]
[ROW][C]201[/C][C]48[/C][C]45.3769031441948[/C][C]2.62309685580519[/C][/ROW]
[ROW][C]202[/C][C]44[/C][C]65.483177688298[/C][C]-21.4831776882981[/C][/ROW]
[ROW][C]203[/C][C]60[/C][C]45.3402839842037[/C][C]14.6597160157963[/C][/ROW]
[ROW][C]204[/C][C]65[/C][C]49.7283127408737[/C][C]15.2716872591263[/C][/ROW]
[ROW][C]205[/C][C]55[/C][C]51.364280132111[/C][C]3.63571986788904[/C][/ROW]
[ROW][C]206[/C][C]38[/C][C]53.6208459784255[/C][C]-15.6208459784255[/C][/ROW]
[ROW][C]207[/C][C]52[/C][C]47.0793287043687[/C][C]4.92067129563129[/C][/ROW]
[ROW][C]208[/C][C]60[/C][C]48.5175064829455[/C][C]11.4824935170545[/C][/ROW]
[ROW][C]209[/C][C]54[/C][C]53.4374892008496[/C][C]0.562510799150398[/C][/ROW]
[ROW][C]210[/C][C]86[/C][C]65.5755510177385[/C][C]20.4244489822615[/C][/ROW]
[ROW][C]211[/C][C]24[/C][C]24.4438901258168[/C][C]-0.443890125816828[/C][/ROW]
[ROW][C]212[/C][C]52[/C][C]51.8336198533306[/C][C]0.166380146669365[/C][/ROW]
[ROW][C]213[/C][C]49[/C][C]49.5540306526744[/C][C]-0.554030652674452[/C][/ROW]
[ROW][C]214[/C][C]61[/C][C]46.3414419123473[/C][C]14.6585580876527[/C][/ROW]
[ROW][C]215[/C][C]61[/C][C]61.2153960430303[/C][C]-0.215396043030282[/C][/ROW]
[ROW][C]216[/C][C]81[/C][C]59.0969896270834[/C][C]21.9030103729166[/C][/ROW]
[ROW][C]217[/C][C]43[/C][C]36.508081219833[/C][C]6.49191878016702[/C][/ROW]
[ROW][C]218[/C][C]40[/C][C]34.3880642664296[/C][C]5.6119357335704[/C][/ROW]
[ROW][C]219[/C][C]40[/C][C]45.127230061824[/C][C]-5.12723006182399[/C][/ROW]
[ROW][C]220[/C][C]56[/C][C]43.3192910583134[/C][C]12.6807089416866[/C][/ROW]
[ROW][C]221[/C][C]68[/C][C]57.1842341262521[/C][C]10.8157658737479[/C][/ROW]
[ROW][C]222[/C][C]79[/C][C]67.1897339671502[/C][C]11.8102660328498[/C][/ROW]
[ROW][C]223[/C][C]47[/C][C]54.3674487633872[/C][C]-7.36744876338715[/C][/ROW]
[ROW][C]224[/C][C]57[/C][C]50.9245454862874[/C][C]6.0754545137126[/C][/ROW]
[ROW][C]225[/C][C]41[/C][C]44.3130223319547[/C][C]-3.31302233195469[/C][/ROW]
[ROW][C]226[/C][C]29[/C][C]38.8994425538809[/C][C]-9.89944255388088[/C][/ROW]
[ROW][C]227[/C][C]3[/C][C]20.039004746541[/C][C]-17.039004746541[/C][/ROW]
[ROW][C]228[/C][C]60[/C][C]48.5431616521234[/C][C]11.4568383478766[/C][/ROW]
[ROW][C]229[/C][C]30[/C][C]41.5554337342984[/C][C]-11.5554337342984[/C][/ROW]
[ROW][C]230[/C][C]79[/C][C]67.5035090541937[/C][C]11.4964909458063[/C][/ROW]
[ROW][C]231[/C][C]47[/C][C]44.3747497505182[/C][C]2.6252502494818[/C][/ROW]
[ROW][C]232[/C][C]40[/C][C]42.8005339730603[/C][C]-2.80053397306029[/C][/ROW]
[ROW][C]233[/C][C]48[/C][C]44.2036229083888[/C][C]3.79637709161118[/C][/ROW]
[ROW][C]234[/C][C]36[/C][C]46.2585459005776[/C][C]-10.2585459005776[/C][/ROW]
[ROW][C]235[/C][C]42[/C][C]58.9468709714168[/C][C]-16.9468709714168[/C][/ROW]
[ROW][C]236[/C][C]49[/C][C]52.4007649107833[/C][C]-3.40076491078333[/C][/ROW]
[ROW][C]237[/C][C]57[/C][C]52.0112802026524[/C][C]4.98871979734758[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]46.6525454606327[/C][C]-34.6525454606327[/C][/ROW]
[ROW][C]239[/C][C]40[/C][C]48.5877591435606[/C][C]-8.5877591435606[/C][/ROW]
[ROW][C]240[/C][C]43[/C][C]42.9005193545421[/C][C]0.0994806454579105[/C][/ROW]
[ROW][C]241[/C][C]33[/C][C]42.689019205412[/C][C]-9.689019205412[/C][/ROW]
[ROW][C]242[/C][C]77[/C][C]65.0437534348567[/C][C]11.9562465651433[/C][/ROW]
[ROW][C]243[/C][C]43[/C][C]46.1340787696092[/C][C]-3.13407876960921[/C][/ROW]
[ROW][C]244[/C][C]45[/C][C]38.185947412939[/C][C]6.814052587061[/C][/ROW]
[ROW][C]245[/C][C]47[/C][C]41.9734004715684[/C][C]5.02659952843157[/C][/ROW]
[ROW][C]246[/C][C]43[/C][C]48.6887400271505[/C][C]-5.68874002715048[/C][/ROW]
[ROW][C]247[/C][C]45[/C][C]48.1906091686969[/C][C]-3.19060916869695[/C][/ROW]
[ROW][C]248[/C][C]50[/C][C]41.0769608671774[/C][C]8.92303913282257[/C][/ROW]
[ROW][C]249[/C][C]35[/C][C]27.756919983979[/C][C]7.24308001602095[/C][/ROW]
[ROW][C]250[/C][C]7[/C][C]13.7711164838827[/C][C]-6.77111648388273[/C][/ROW]
[ROW][C]251[/C][C]71[/C][C]65.3694078554798[/C][C]5.63059214452015[/C][/ROW]
[ROW][C]252[/C][C]67[/C][C]62.7439763119601[/C][C]4.25602368803992[/C][/ROW]
[ROW][C]253[/C][C]0[/C][C]-0.652005066470264[/C][C]0.652005066470264[/C][/ROW]
[ROW][C]254[/C][C]62[/C][C]49.8798087585304[/C][C]12.1201912414696[/C][/ROW]
[ROW][C]255[/C][C]54[/C][C]46.9387190560574[/C][C]7.06128094394264[/C][/ROW]
[ROW][C]256[/C][C]4[/C][C]8.11300139586678[/C][C]-4.11300139586678[/C][/ROW]
[ROW][C]257[/C][C]25[/C][C]26.5095984534331[/C][C]-1.50959845343305[/C][/ROW]
[ROW][C]258[/C][C]40[/C][C]45.4881410937792[/C][C]-5.48814109377924[/C][/ROW]
[ROW][C]259[/C][C]38[/C][C]43.7039011545396[/C][C]-5.70390115453957[/C][/ROW]
[ROW][C]260[/C][C]19[/C][C]23.4870385898094[/C][C]-4.48703858980936[/C][/ROW]
[ROW][C]261[/C][C]17[/C][C]41.4758128589825[/C][C]-24.4758128589825[/C][/ROW]
[ROW][C]262[/C][C]67[/C][C]51.3326847884222[/C][C]15.6673152115778[/C][/ROW]
[ROW][C]263[/C][C]14[/C][C]17.1140786150699[/C][C]-3.11407861506989[/C][/ROW]
[ROW][C]264[/C][C]30[/C][C]43.5967265332109[/C][C]-13.5967265332109[/C][/ROW]
[ROW][C]265[/C][C]54[/C][C]37.7495226759174[/C][C]16.2504773240826[/C][/ROW]
[ROW][C]266[/C][C]35[/C][C]41.7833752730522[/C][C]-6.7833752730522[/C][/ROW]
[ROW][C]267[/C][C]59[/C][C]52.152088145217[/C][C]6.84791185478305[/C][/ROW]
[ROW][C]268[/C][C]24[/C][C]33.7634125762546[/C][C]-9.76341257625464[/C][/ROW]
[ROW][C]269[/C][C]58[/C][C]47.3443257687301[/C][C]10.6556742312699[/C][/ROW]
[ROW][C]270[/C][C]42[/C][C]60.4670662922922[/C][C]-18.4670662922922[/C][/ROW]
[ROW][C]271[/C][C]46[/C][C]54.4600700732783[/C][C]-8.46007007327828[/C][/ROW]
[ROW][C]272[/C][C]61[/C][C]44.1531022677658[/C][C]16.8468977322342[/C][/ROW]
[ROW][C]273[/C][C]3[/C][C]0.216293115721667[/C][C]2.78370688427833[/C][/ROW]
[ROW][C]274[/C][C]52[/C][C]49.418972086223[/C][C]2.58102791377703[/C][/ROW]
[ROW][C]275[/C][C]25[/C][C]28.3266251344185[/C][C]-3.32662513441851[/C][/ROW]
[ROW][C]276[/C][C]40[/C][C]55.829928218785[/C][C]-15.829928218785[/C][/ROW]
[ROW][C]277[/C][C]32[/C][C]31.2003188876734[/C][C]0.799681112326552[/C][/ROW]
[ROW][C]278[/C][C]4[/C][C]2.01389613499354[/C][C]1.98610386500646[/C][/ROW]
[ROW][C]279[/C][C]49[/C][C]42.2516292583841[/C][C]6.74837074161594[/C][/ROW]
[ROW][C]280[/C][C]63[/C][C]46.8174610531189[/C][C]16.1825389468811[/C][/ROW]
[ROW][C]281[/C][C]67[/C][C]53.8512764688046[/C][C]13.1487235311954[/C][/ROW]
[ROW][C]282[/C][C]32[/C][C]38.719503498302[/C][C]-6.71950349830198[/C][/ROW]
[ROW][C]283[/C][C]23[/C][C]31.4597547276713[/C][C]-8.45975472767126[/C][/ROW]
[ROW][C]284[/C][C]7[/C][C]8.54851784345082[/C][C]-1.54851784345082[/C][/ROW]
[ROW][C]285[/C][C]54[/C][C]42.4478062851382[/C][C]11.5521937148618[/C][/ROW]
[ROW][C]286[/C][C]37[/C][C]56.4879388159728[/C][C]-19.4879388159728[/C][/ROW]
[ROW][C]287[/C][C]35[/C][C]32.7921623863976[/C][C]2.20783761360237[/C][/ROW]
[ROW][C]288[/C][C]51[/C][C]43.3302081882678[/C][C]7.66979181173225[/C][/ROW]
[ROW][C]289[/C][C]39[/C][C]43.88739546965[/C][C]-4.88739546964997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155913&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155913&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
194100.026343272609-6.0263432726094
210386.01430379039116.9856962096089
393114.803868408768-21.8038684087676
410397.25043313218465.74956686781537
55168.0040669004422-17.0040669004422
67068.78795562896481.21204437103516
79190.40833526780120.591664732198777
82246.6058393243416-24.6058393243416
93831.54648195706076.45351804293928
109378.320403200892714.6795967991073
116079.6451446960541-19.6451446960541
12123120.9067060694382.09329393056174
13148135.22983456348112.7701654365194
149088.3003166591651.69968334083492
15124126.288482370352-2.28848237035199
1670105.183762413751-35.1837624137509
17168159.1686050630478.83139493695256
18115101.35709815768913.6429018423112
197198.8388456701767-27.8388456701767
206675.0540802702526-9.0540802702526
21134119.16736381655514.8326361834451
22117117.787736695203-0.787736695202567
2310897.30747302063410.692526979366
248478.03441414468685.96558585531315
25156120.00650752009335.9934924799074
26120111.4499962284388.55000377156157
2711497.643295784756816.3567042152432
2894100.962489993492-6.96248999349206
29120110.6452902096919.3547097903091
308174.29997135553756.70002864446255
31110111.966005055011-1.96600505501059
32133114.03494086784418.9650591321561
33122124.252819916018-2.25281991601845
34158140.91854114587217.0814588541283
3510986.009355252905922.9906447470941
36124112.16982395596311.8301760440371
373939.5239392195626-0.523939219562573
389298.7475473570687-6.74754735706868
39126118.9407884112897.05921158871092
400-4.81402461912024.8140246191202
417087.1549244394339-17.1549244394339
423742.4748653380247-5.47486533802465
433852.6949853095481-14.6949853095481
44120106.87441772396113.125582276039
459398.3873687092119-5.38736870921188
4695103.98388030989-8.98388030988964
477764.131058432805412.8689415671946
489087.03410873910852.96589126089154
498082.4877162868019-2.48771628680186
5031111.334562528648-80.3345625286481
51110107.2217958060022.77820419399822
526672.7967232060782-6.79672320607815
53138123.50331699025214.4966830097482
54133131.5590326237811.44096737621895
55113102.35440062256210.6455993774382
5610091.75161149119158.24838850880848
5776.461267680358890.538732319641108
58140126.48596355847813.5140364415219
596149.757509750604911.2424902493951
604140.68300824740450.31699175259552
619693.48551706360782.51448293639221
62164144.55772196151319.4422780384874
637884.7039480768913-6.7039480768913
644946.57672262495112.42327737504894
6510298.49437769659953.50562230340046
66124119.4064580037634.59354199623663
679987.704372764624611.2956272353754
68129131.969132386179-2.96913238617944
696285.0858690872856-23.0858690872856
7073107.176792250071-34.1767922500708
7111498.76620546717515.233794532825
729989.01687150846749.9831284915326
737083.125769661991-13.1257696619911
7410484.862027103421719.1379728965783
75116114.3149606915891.68503930841114
769193.7037843124068-2.70378431240679
777478.539123091938-4.53912309193797
78138123.50735059550914.4926494044909
796763.16772003805423.83227996194585
80151122.71822695010328.2817730498965
817286.336627988144-14.3366279881441
82120108.70420713500311.2957928649967
83115107.6091624268627.39083757313752
8410592.867018521802612.1329814781974
85104109.05262496524-5.0526249652402
8610896.771327001901511.2286729980985
879899.607503971686-1.60750397168612
886967.29336345769471.70663654230532
89111127.943000687367-16.9430006873667
909974.259011801688924.7409881983111
9171114.475117822195-43.475117822195
922724.67620961336232.32379038663772
936966.69260567774082.30739432225923
9410790.226861208457416.7731387915426
957361.44964492778611.5503550722141
9610791.43557070089315.5644292991071
9793139.787755581764-46.7877555817644
98129121.244778977597.75522102240988
9969102.982929718811-33.9829297188111
100118110.5915364886457.40846351135491
1017374.7615159583282-1.76151595832821
102119103.19065472284515.8093452771545
10310491.410162930696912.5898370693031
10410788.217285378664118.7827146213359
1059992.3314482611286.66855173887194
10690109.996787565243-19.9967875652431
107197166.80834086625930.1916591337414
1083662.3722741826195-26.3722741826195
1098591.1012337900474-6.10123379004744
110139129.6597391945179.34026080548329
111106113.371917971654-7.37191797165358
1125094.578499490121-44.5784994901211
1136450.631867861112613.3681321388874
1143166.2745509782957-35.2745509782957
1156399.1562441862867-36.1562441862867
11692101.178296978974-9.17829697897365
117106111.72299581637-5.72299581637023
1186359.51865590623383.48134409376622
1196969.4874851768073-0.487485176807308
1204151.2346949306524-10.2346949306524
1215663.4437891327191-7.44378913271913
1222533.615844612019-8.61584461201899
1236552.034464875460512.9655351245395
1249393.7768381493404-0.776838149340361
12511498.913487527160315.0865124728397
1263829.48412670169748.51587329830261
1274438.3208397361125.67916026388805
1288769.064888439452317.9351115605477
129110138.298441948069-28.2984419480685
1300-0.1359725923012420.135972592301242
1312722.25637948937464.74362051062538
13283103.57127279201-20.5712727920099
1333030.093121073307-0.093121073306999
1348074.99236766616235.00763233383773
13598109.719905604196-11.7199056041962
13682110.0929169945-28.0929169945003
1370-4.056625000776574.05662500077657
1386077.2665963492723-17.2665963492723
1392833.3724865404005-5.37248654040046
140919.6165711857846-10.6165711857846
1413334.4785337915379-1.47853379153795
1425962.0905316411869-3.09053164118693
1434948.14249056656690.857509433433077
144115110.4730013001894.52699869981072
145140120.78968204858819.210317951412
1464963.759021196048-14.7590211960481
147120108.51074595775911.4892540422412
1486668.6591744468837-2.65917444688374
1492119.31569299197441.68430700802563
150124103.8247832961620.1752167038395
151152137.19599922443414.8040007755658
152139128.23603922129110.7639607787093
1533843.846497639211-5.846497639211
154144136.0505047396777.94949526032252
155120130.191908094301-10.1919080943005
156160154.4230941591175.57690584088317
15711494.855853805819419.1441461941806
1583937.01706620183191.98293379816812
1597879.9887955209322-1.98879552093219
16011997.201737353003321.7982626469967
161141132.9096413690798.09035863092068
16210182.612079061846518.3879209381535
1635648.73671539006627.26328460993385
164133120.19855268312712.801447316873
1658388.5625929209998-5.56259292099983
166116113.4095459228882.59045407711245
1679099.6792660017333-9.67926600173333
1683676.7587114179932-40.7587114179932
1695063.0212119520473-13.0212119520473
1706158.43111104784962.56888895215043
17197100.409783245109-3.4097832451088
17298103.794554297624-5.79455429762384
1737861.940968759650616.0590312403494
174117129.500494418949-12.5004944189492
175148130.38934600132217.610653998678
1764137.93724302739353.06275697260648
177105103.3280313071121.6719686928876
1785551.14430646772093.85569353227914
179132131.16099716680.839002833199702
1804444.1067116226312-0.106711622631155
1812121.1374150573855-0.137415057385474
1825053.1282057272292-3.12820572722917
1830-5.179433131192325.17943313119232
1847391.6749800901528-18.6749800901528
18586123.934746146251-37.9347461462511
1860-5.471116046040535.47111604604053
1871310.33836876769312.66163123230691
1884-2.594432073924446.59443207392444
1895749.96171719093027.03828280906983
1904891.9329392963812-43.9329392963812
1914672.6309644449701-26.6309644449701
1924845.80427908428132.19572091571865
1933234.474333029414-2.47433302941404
1946867.1634813068080.836518693192051
1958769.108812124068417.8911878759316
1964339.53097092406163.4690290759384
1976751.242489416011515.7575105839885
1984634.993892018220111.0061079817799
1994649.2566728880876-3.25667288808761
2005643.1912633803412.80873661966
2014845.37690314419482.62309685580519
2024465.483177688298-21.4831776882981
2036045.340283984203714.6597160157963
2046549.728312740873715.2716872591263
2055551.3642801321113.63571986788904
2063853.6208459784255-15.6208459784255
2075247.07932870436874.92067129563129
2086048.517506482945511.4824935170545
2095453.43748920084960.562510799150398
2108665.575551017738520.4244489822615
2112424.4438901258168-0.443890125816828
2125251.83361985333060.166380146669365
2134949.5540306526744-0.554030652674452
2146146.341441912347314.6585580876527
2156161.2153960430303-0.215396043030282
2168159.096989627083421.9030103729166
2174336.5080812198336.49191878016702
2184034.38806426642965.6119357335704
2194045.127230061824-5.12723006182399
2205643.319291058313412.6807089416866
2216857.184234126252110.8157658737479
2227967.189733967150211.8102660328498
2234754.3674487633872-7.36744876338715
2245750.92454548628746.0754545137126
2254144.3130223319547-3.31302233195469
2262938.8994425538809-9.89944255388088
227320.039004746541-17.039004746541
2286048.543161652123411.4568383478766
2293041.5554337342984-11.5554337342984
2307967.503509054193711.4964909458063
2314744.37474975051822.6252502494818
2324042.8005339730603-2.80053397306029
2334844.20362290838883.79637709161118
2343646.2585459005776-10.2585459005776
2354258.9468709714168-16.9468709714168
2364952.4007649107833-3.40076491078333
2375752.01128020265244.98871979734758
2381246.6525454606327-34.6525454606327
2394048.5877591435606-8.5877591435606
2404342.90051935454210.0994806454579105
2413342.689019205412-9.689019205412
2427765.043753434856711.9562465651433
2434346.1340787696092-3.13407876960921
2444538.1859474129396.814052587061
2454741.97340047156845.02659952843157
2464348.6887400271505-5.68874002715048
2474548.1906091686969-3.19060916869695
2485041.07696086717748.92303913282257
2493527.7569199839797.24308001602095
250713.7711164838827-6.77111648388273
2517165.36940785547985.63059214452015
2526762.74397631196014.25602368803992
2530-0.6520050664702640.652005066470264
2546249.879808758530412.1201912414696
2555446.93871905605747.06128094394264
25648.11300139586678-4.11300139586678
2572526.5095984534331-1.50959845343305
2584045.4881410937792-5.48814109377924
2593843.7039011545396-5.70390115453957
2601923.4870385898094-4.48703858980936
2611741.4758128589825-24.4758128589825
2626751.332684788422215.6673152115778
2631417.1140786150699-3.11407861506989
2643043.5967265332109-13.5967265332109
2655437.749522675917416.2504773240826
2663541.7833752730522-6.7833752730522
2675952.1520881452176.84791185478305
2682433.7634125762546-9.76341257625464
2695847.344325768730110.6556742312699
2704260.4670662922922-18.4670662922922
2714654.4600700732783-8.46007007327828
2726144.153102267765816.8468977322342
27330.2162931157216672.78370688427833
2745249.4189720862232.58102791377703
2752528.3266251344185-3.32662513441851
2764055.829928218785-15.829928218785
2773231.20031888767340.799681112326552
27842.013896134993541.98610386500646
2794942.25162925838416.74837074161594
2806346.817461053118916.1825389468811
2816753.851276468804613.1487235311954
2823238.719503498302-6.71950349830198
2832331.4597547276713-8.45975472767126
28478.54851784345082-1.54851784345082
2855442.447806285138211.5521937148618
2863756.4879388159728-19.4879388159728
2873532.79216238639762.20783761360237
2885143.33020818826787.66979181173225
2893943.88739546965-4.88739546964997






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.6649246795898170.6701506408203670.335075320410183
110.67391071372890.65217857254220.3260892862711
120.6618694228367020.6762611543265970.338130577163298
130.7555477988258730.4889044023482530.244452201174127
140.6611546867879070.6776906264241860.338845313212093
150.562352984704720.875294030590560.43764701529528
160.8227411010404720.3545177979190560.177258898959528
170.7691906916030930.4616186167938140.230809308396907
180.7755931931457270.4488136137085460.224406806854273
190.8427640607354080.3144718785291850.157235939264592
200.8307772391800840.3384455216398310.169222760819916
210.8129708050568160.3740583898863690.187029194943184
220.7586475861923180.4827048276153640.241352413807682
230.7833799841913540.4332400316172920.216620015808646
240.7468566494587490.5062867010825010.253143350541251
250.8906620339764010.2186759320471980.109337966023599
260.860044213482630.2799115730347380.139955786517369
270.8530076366349830.2939847267300350.146992363365017
280.8218309185731270.3563381628537470.178169081426873
290.7884440112313060.4231119775373880.211555988768694
300.7590139715842680.4819720568314640.240986028415732
310.7141830916646310.5716338166707370.285816908335369
320.722351466527630.555297066944740.27764853347237
330.672217002131870.6555659957362590.327782997868129
340.6561977731362860.6876044537274280.343802226863714
350.7272828935862170.5454342128275670.272717106413783
360.7085945164772220.5828109670455550.291405483522778
370.6631879208930240.6736241582139530.336812079106976
380.6246460517180850.750707896563830.375353948281915
390.6029120282125820.7941759435748360.397087971787418
400.587612994440180.824774011119640.41238700555982
410.6031949916819760.7936100166360480.396805008318024
420.5555016184378770.8889967631242460.444498381562123
430.5244948136075320.9510103727849350.475505186392468
440.5141861662028540.9716276675942930.485813833797146
450.4796360807051710.9592721614103410.520363919294829
460.452012581334870.9040251626697410.54798741866513
470.4646607739345630.9293215478691260.535339226065437
480.4177882945183780.8355765890367560.582211705481622
490.3716365616045470.7432731232090940.628363438395453
500.9641886879852470.0716226240295060.035811312014753
510.9664324293501270.06713514129974540.0335675706498727
520.9605649732365520.07887005352689650.0394350267634483
530.9544912384576010.0910175230847980.045508761542399
540.9433258593963680.1133482812072640.0566741406036319
550.9367341682422560.1265316635154890.0632658317577444
560.9244710169278210.1510579661443570.0755289830721787
570.910272136334940.1794557273301190.0897278636650593
580.9082524976926750.1834950046146490.0917475023073246
590.9046813019894750.1906373960210490.0953186980105246
600.886133429638350.2277331407233010.11386657036165
610.8648586282117940.2702827435764110.135141371788206
620.8635585938547220.2728828122905560.136441406145278
630.8572953469562220.2854093060875550.142704653043778
640.8347883702822730.3304232594354540.165211629717727
650.8095394312463370.3809211375073260.190460568753663
660.7879691727403340.4240616545193330.212030827259666
670.7643649719267150.4712700561465690.235635028073285
680.7480095330564480.5039809338871030.251990466943552
690.797126053617110.4057478927657810.20287394638289
700.8712105682742480.2575788634515040.128789431725752
710.884061928300280.231876143399440.11593807169972
720.8887321366535380.2225357266929250.111267863346462
730.8935049529614060.2129900940771880.106495047038594
740.8975111851924230.2049776296151530.102488814807577
750.8796631035035910.2406737929928170.120336896496409
760.8779077948252430.2441844103495140.122092205174757
770.8779480410401740.2441039179196520.122051958959826
780.8734539296291990.2530921407416020.126546070370801
790.8548645138323860.2902709723352270.145135486167614
800.8980462328417820.2039075343164360.101953767158218
810.8983178251894650.2033643496210690.101682174810535
820.8872869555418620.2254260889162760.112713044458138
830.871394885364750.25721022927050.12860511463525
840.8627873576243130.2744252847513740.137212642375687
850.8467190096569470.3065619806861060.153280990343053
860.8342917072568120.3314165854863760.165708292743188
870.8110892747580270.3778214504839450.188910725241973
880.7859617786488960.4280764427022070.214038221351104
890.8212251286142820.3575497427714350.178774871385718
900.8783242330953370.2433515338093260.121675766904663
910.9763847943468740.04723041130625240.0236152056531262
920.9716772523826450.056645495234710.028322747617355
930.9656956934465250.06860861310695020.0343043065534751
940.9671156242750170.06576875144996620.0328843757249831
950.9641726206874240.0716547586251520.035827379312576
960.9665443926733180.06691121465336390.0334556073266819
970.9954164176589040.009167164682191840.00458358234109592
980.9944360390696780.01112792186064440.00556396093032222
990.998252159545370.003495680909261110.00174784045463055
1000.9980187570425080.00396248591498310.00198124295749155
1010.9974168817555180.005166236488963630.00258311824448182
1020.997410923741060.00517815251787980.0025890762589399
1030.9971884899297580.005623020140484220.00281151007024211
1040.99761724840680.004765503186402380.00238275159320119
1050.9971023980710230.005795203857954750.00289760192897737
1060.9977727746740380.004454450651922980.00222722532596149
1070.9991528327021670.001694334595665440.000847167297832718
1080.9995684742547380.0008630514905237740.000431525745261887
1090.9994463049052050.001107390189590730.000553695094795364
1100.9993524303478420.001295139304315440.00064756965215772
1110.9991888928700240.001622214259951480.000811107129975742
1120.9999433517553870.0001132964892252845.66482446126421e-05
1130.9999394305883650.00012113882326966.05694116347998e-05
1140.9999884303190212.31393619571923e-051.15696809785962e-05
1150.999998260542473.47891506026122e-061.73945753013061e-06
1160.9999977810027184.43799456378852e-062.21899728189426e-06
1170.9999970988886085.80222278352281e-062.9011113917614e-06
1180.9999957445953928.51080921695537e-064.25540460847769e-06
1190.9999956685496858.66290063046153e-064.33145031523076e-06
1200.9999945988905741.08022188515113e-055.40110942575564e-06
1210.9999926405061221.47189877559588e-057.3594938779794e-06
1220.9999906531395361.86937209288548e-059.3468604644274e-06
1230.9999897791564282.04416871450244e-051.02208435725122e-05
1240.9999850766406672.98467186660902e-051.49233593330451e-05
1250.9999853245286662.93509426687699e-051.4675471334385e-05
1260.9999816629568063.66740863876239e-051.8337043193812e-05
1270.9999749435451415.01129097174216e-052.50564548587108e-05
1280.999981975251413.60494971807535e-051.80247485903768e-05
1290.9999919684169991.60631660027366e-058.0315830013683e-06
1300.9999883080832022.33838335956857e-051.16919167978428e-05
1310.9999839316023683.21367952648065e-051.60683976324032e-05
1320.9999881658367532.36683264941973e-051.18341632470987e-05
1330.9999827400858823.45198282364579e-051.72599141182289e-05
1340.9999758687883234.8262423354553e-052.41312116772765e-05
1350.9999721807682015.56384635973023e-052.78192317986512e-05
1360.999990545054351.89098912998687e-059.45494564993433e-06
1370.9999865944370672.68111258660723e-051.34055629330361e-05
1380.9999906549597951.86900804107405e-059.34504020537025e-06
1390.9999871812882562.56374234881839e-051.2818711744092e-05
1400.9999853011967842.93976064328988e-051.46988032164494e-05
1410.9999788268544824.23462910358321e-052.11731455179161e-05
1420.9999696972350526.06055298965676e-053.03027649482838e-05
1430.9999565034878438.69930243147445e-054.34965121573722e-05
1440.9999393621736220.0001212756527567246.0637826378362e-05
1450.9999543038095879.13923808267544e-054.56961904133772e-05
1460.9999527880508639.44238982736565e-054.72119491368282e-05
1470.9999499294118380.0001001411763238875.00705881619436e-05
1480.9999338382149440.0001323235701120836.61617850560416e-05
1490.9999071254471750.0001857491056499639.28745528249813e-05
1500.9999323732235960.0001352535528071396.76267764035694e-05
1510.999932517540150.0001349649197009856.74824598504925e-05
1520.9999197440292020.0001605119415962168.0255970798108e-05
1530.9998936786146370.0002126427707250990.00010632138536255
1540.9998580239113060.0002839521773889390.000141976088694469
1550.9998318342732750.0003363314534507040.000168165726725352
1560.9997771960421360.0004456079157289640.000222803957864482
1570.9998296238849550.0003407522300899710.000170376115044985
1580.9997635017838690.0004729964322617470.000236498216130874
1590.9996772411251620.0006455177496769350.000322758874838468
1600.9998146130083440.0003707739833111130.000185386991655557
1610.999771248632430.0004575027351408450.000228751367570422
1620.9998627101191560.0002745797616874540.000137289880843727
1630.9998232010285630.0003535979428737160.000176798971436858
1640.9998061273126340.00038774537473230.00019387268736615
1650.9997379313133920.0005241373732152560.000262068686607628
1660.999666398469370.0006672030612607990.000333601530630399
1670.9995802180100550.0008395639798894570.000419781989944729
1680.9999639565695757.20868608504408e-053.60434304252204e-05
1690.9999609454259577.81091480863846e-053.90545740431923e-05
1700.9999440757131440.0001118485737124315.59242868562157e-05
1710.9999254906035660.0001490187928685677.45093964342835e-05
1720.999895921200580.0002081575988392650.000104078799419633
1730.9999236685106530.0001526629786944257.63314893472124e-05
1740.9999053830192660.0001892339614673989.4616980733699e-05
1750.9999834193933723.31612132553481e-051.65806066276741e-05
1760.9999770608744634.58782510743698e-052.29391255371849e-05
1770.9999665141707976.69716584051698e-053.34858292025849e-05
1780.999954403175929.1193648158233e-054.55968240791165e-05
1790.9999639334657027.21330685950027e-053.60665342975013e-05
1800.999947264187340.0001054716253208015.27358126604004e-05
1810.9999241617327660.0001516765344674687.58382672337341e-05
1820.9999094394457170.0001811211085653889.05605542826938e-05
1830.9998782808535670.0002434382928663620.000121719146433181
1840.9999147063138540.0001705873722924268.52936861462131e-05
1850.9999959997580418.00048391708443e-064.00024195854222e-06
1860.9999942774367061.14451265888068e-055.72256329440342e-06
1870.999991500055911.69998881795368e-058.49994408976838e-06
1880.9999874532213772.50935572467877e-051.25467786233938e-05
1890.9999819151129453.61697741096179e-051.80848870548089e-05
1900.9999989501466682.09970666340385e-061.04985333170193e-06
1910.9999999164394831.67121034182296e-078.35605170911481e-08
1920.9999998629006982.74198604401483e-071.37099302200741e-07
1930.9999997735058784.52988244756592e-072.26494122378296e-07
1940.9999996620633246.75873351772038e-073.37936675886019e-07
1950.9999995533313168.93337368781268e-074.46668684390634e-07
1960.9999992871724181.42565516377909e-067.12827581889546e-07
1970.9999993415059271.31698814656531e-066.58494073282657e-07
1980.999999098263491.80347301902251e-069.01736509511255e-07
1990.9999986651015862.66979682902103e-061.33489841451052e-06
2000.9999986634664052.67306719052282e-061.33653359526141e-06
2010.9999978286257114.34274857791282e-062.17137428895641e-06
2020.9999991155052631.76898947411192e-068.84494737055962e-07
2030.9999992111072981.57778540315812e-067.8889270157906e-07
2040.9999989751205872.04975882510026e-061.02487941255013e-06
2050.9999985167488962.96650220854648e-061.48325110427324e-06
2060.9999989067877952.18642441015199e-061.09321220507599e-06
2070.9999985293567142.94128657168701e-061.4706432858435e-06
2080.999997703386544.59322692039994e-062.29661346019997e-06
2090.9999965836970366.83260592828421e-063.41630296414211e-06
2100.9999971014817665.7970364678063e-062.89851823390315e-06
2110.999995278808499.44238301858473e-064.72119150929236e-06
2120.9999923282433161.5343513369068e-057.67175668453399e-06
2130.9999876164192962.47671614077239e-051.2383580703862e-05
2140.9999854266657912.91466684173216e-051.45733342086608e-05
2150.9999767360596234.65278807544994e-052.32639403772497e-05
2160.9999908230272141.83539455719418e-059.1769727859709e-06
2170.9999892821645762.14356708475768e-051.07178354237884e-05
2180.9999841189678373.17620643264989e-051.58810321632495e-05
2190.9999776139295214.4772140958078e-052.2386070479039e-05
2200.9999699199011666.01601976680069e-053.00800988340034e-05
2210.9999650597203386.98805593244949e-053.49402796622475e-05
2220.999946770541270.0001064589174614635.32294587307316e-05
2230.9999182671856390.0001634656287223858.17328143611925e-05
2240.9998766508197650.0002466983604705330.000123349180235267
2250.9998165683121330.0003668633757337680.000183431687866884
2260.9997637395161920.000472520967615620.00023626048380781
2270.9998728036398580.0002543927202833980.000127196360141699
2280.9998943114677210.0002113770645576080.000105688532278804
2290.999844267736680.000311464526638680.00015573226331934
2300.999943514446180.0001129711076408385.64855538204192e-05
2310.9999235130042650.0001529739914699817.64869957349906e-05
2320.9998795831777680.0002408336444636690.000120416822231835
2330.9998070100125360.0003859799749283060.000192989987464153
2340.9997152992814950.0005694014370102030.000284700718505102
2350.999676583918380.0006468321632399420.000323416081619971
2360.9994948464640420.001010307071916370.000505153535958187
2370.9992192346716550.001561530656689640.00078076532834482
2380.9999427750845640.0001144498308717875.72249154358936e-05
2390.99991889402280.0001622119544012838.11059772006413e-05
2400.9998703024801570.0002593950396865540.000129697519843277
2410.9998962607313680.0002074785372645040.000103739268632252
2420.999851222487510.0002975550249809890.000148777512490495
2430.999753803189890.0004923936202193810.00024619681010969
2440.9996638030451240.0006723939097516830.000336196954875841
2450.9994482942072220.001103411585556780.00055170579277839
2460.9993303360417480.001339327916503870.000669663958251934
2470.9989102984491880.002179403101623550.00108970155081178
2480.998281216437510.003437567124981870.00171878356249093
2490.9976599047724240.004680190455152750.00234009522757638
2500.9970651331665540.005869733666891950.00293486683344598
2510.995901947766650.008196104466697990.004098052233349
2520.99369332384580.01261335230840180.0063066761542009
2530.9903870769979320.01922584600413650.00961292300206825
2540.9912268643485710.01754627130285790.00877313565142893
2550.988039531037110.02392093792578190.0119604689628909
2560.9832594260237050.03348114795259010.016740573976295
2570.9753001486598190.04939970268036270.0246998513401814
2580.9647830719712720.07043385605745660.0352169280287283
2590.95488728694460.09022542611079840.0451127130553992
2600.942992968066640.1140140638667210.0570070319333604
2610.9775865419297780.04482691614044380.0224134580702219
2620.9849172327462860.03016553450742890.0150827672537144
2630.9785332258738970.04293354825220690.0214667741261035
2640.9740257831319620.05194843373607680.0259742168680384
2650.9772265570079790.04554688598404260.0227734429920213
2660.9732393402003540.05352131959929250.0267606597996463
2670.9688120123264980.06237597534700360.0311879876735018
2680.9654887655883390.06902246882332260.0345112344116613
2690.9619637834559290.07607243308814160.0380362165440708
2700.991836313246370.01632737350725880.00816368675362941
2710.9884800626847440.02303987463051110.0115199373152556
2720.98143558985910.03712882028179870.0185644101408994
2730.977386519162530.04522696167493920.0226134808374696
2740.9572736909888140.08545261802237190.0427263090111859
2750.9511952583162180.09760948336756340.0488047416837817
2760.969318913597190.06136217280561850.0306810864028093
2770.9414223246296780.1171553507406430.0585776753703215
2780.8719155913231060.2561688173537870.128084408676894
2790.8137700367515820.3724599264968350.186229963248418

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.664924679589817 & 0.670150640820367 & 0.335075320410183 \tabularnewline
11 & 0.6739107137289 & 0.6521785725422 & 0.3260892862711 \tabularnewline
12 & 0.661869422836702 & 0.676261154326597 & 0.338130577163298 \tabularnewline
13 & 0.755547798825873 & 0.488904402348253 & 0.244452201174127 \tabularnewline
14 & 0.661154686787907 & 0.677690626424186 & 0.338845313212093 \tabularnewline
15 & 0.56235298470472 & 0.87529403059056 & 0.43764701529528 \tabularnewline
16 & 0.822741101040472 & 0.354517797919056 & 0.177258898959528 \tabularnewline
17 & 0.769190691603093 & 0.461618616793814 & 0.230809308396907 \tabularnewline
18 & 0.775593193145727 & 0.448813613708546 & 0.224406806854273 \tabularnewline
19 & 0.842764060735408 & 0.314471878529185 & 0.157235939264592 \tabularnewline
20 & 0.830777239180084 & 0.338445521639831 & 0.169222760819916 \tabularnewline
21 & 0.812970805056816 & 0.374058389886369 & 0.187029194943184 \tabularnewline
22 & 0.758647586192318 & 0.482704827615364 & 0.241352413807682 \tabularnewline
23 & 0.783379984191354 & 0.433240031617292 & 0.216620015808646 \tabularnewline
24 & 0.746856649458749 & 0.506286701082501 & 0.253143350541251 \tabularnewline
25 & 0.890662033976401 & 0.218675932047198 & 0.109337966023599 \tabularnewline
26 & 0.86004421348263 & 0.279911573034738 & 0.139955786517369 \tabularnewline
27 & 0.853007636634983 & 0.293984726730035 & 0.146992363365017 \tabularnewline
28 & 0.821830918573127 & 0.356338162853747 & 0.178169081426873 \tabularnewline
29 & 0.788444011231306 & 0.423111977537388 & 0.211555988768694 \tabularnewline
30 & 0.759013971584268 & 0.481972056831464 & 0.240986028415732 \tabularnewline
31 & 0.714183091664631 & 0.571633816670737 & 0.285816908335369 \tabularnewline
32 & 0.72235146652763 & 0.55529706694474 & 0.27764853347237 \tabularnewline
33 & 0.67221700213187 & 0.655565995736259 & 0.327782997868129 \tabularnewline
34 & 0.656197773136286 & 0.687604453727428 & 0.343802226863714 \tabularnewline
35 & 0.727282893586217 & 0.545434212827567 & 0.272717106413783 \tabularnewline
36 & 0.708594516477222 & 0.582810967045555 & 0.291405483522778 \tabularnewline
37 & 0.663187920893024 & 0.673624158213953 & 0.336812079106976 \tabularnewline
38 & 0.624646051718085 & 0.75070789656383 & 0.375353948281915 \tabularnewline
39 & 0.602912028212582 & 0.794175943574836 & 0.397087971787418 \tabularnewline
40 & 0.58761299444018 & 0.82477401111964 & 0.41238700555982 \tabularnewline
41 & 0.603194991681976 & 0.793610016636048 & 0.396805008318024 \tabularnewline
42 & 0.555501618437877 & 0.888996763124246 & 0.444498381562123 \tabularnewline
43 & 0.524494813607532 & 0.951010372784935 & 0.475505186392468 \tabularnewline
44 & 0.514186166202854 & 0.971627667594293 & 0.485813833797146 \tabularnewline
45 & 0.479636080705171 & 0.959272161410341 & 0.520363919294829 \tabularnewline
46 & 0.45201258133487 & 0.904025162669741 & 0.54798741866513 \tabularnewline
47 & 0.464660773934563 & 0.929321547869126 & 0.535339226065437 \tabularnewline
48 & 0.417788294518378 & 0.835576589036756 & 0.582211705481622 \tabularnewline
49 & 0.371636561604547 & 0.743273123209094 & 0.628363438395453 \tabularnewline
50 & 0.964188687985247 & 0.071622624029506 & 0.035811312014753 \tabularnewline
51 & 0.966432429350127 & 0.0671351412997454 & 0.0335675706498727 \tabularnewline
52 & 0.960564973236552 & 0.0788700535268965 & 0.0394350267634483 \tabularnewline
53 & 0.954491238457601 & 0.091017523084798 & 0.045508761542399 \tabularnewline
54 & 0.943325859396368 & 0.113348281207264 & 0.0566741406036319 \tabularnewline
55 & 0.936734168242256 & 0.126531663515489 & 0.0632658317577444 \tabularnewline
56 & 0.924471016927821 & 0.151057966144357 & 0.0755289830721787 \tabularnewline
57 & 0.91027213633494 & 0.179455727330119 & 0.0897278636650593 \tabularnewline
58 & 0.908252497692675 & 0.183495004614649 & 0.0917475023073246 \tabularnewline
59 & 0.904681301989475 & 0.190637396021049 & 0.0953186980105246 \tabularnewline
60 & 0.88613342963835 & 0.227733140723301 & 0.11386657036165 \tabularnewline
61 & 0.864858628211794 & 0.270282743576411 & 0.135141371788206 \tabularnewline
62 & 0.863558593854722 & 0.272882812290556 & 0.136441406145278 \tabularnewline
63 & 0.857295346956222 & 0.285409306087555 & 0.142704653043778 \tabularnewline
64 & 0.834788370282273 & 0.330423259435454 & 0.165211629717727 \tabularnewline
65 & 0.809539431246337 & 0.380921137507326 & 0.190460568753663 \tabularnewline
66 & 0.787969172740334 & 0.424061654519333 & 0.212030827259666 \tabularnewline
67 & 0.764364971926715 & 0.471270056146569 & 0.235635028073285 \tabularnewline
68 & 0.748009533056448 & 0.503980933887103 & 0.251990466943552 \tabularnewline
69 & 0.79712605361711 & 0.405747892765781 & 0.20287394638289 \tabularnewline
70 & 0.871210568274248 & 0.257578863451504 & 0.128789431725752 \tabularnewline
71 & 0.88406192830028 & 0.23187614339944 & 0.11593807169972 \tabularnewline
72 & 0.888732136653538 & 0.222535726692925 & 0.111267863346462 \tabularnewline
73 & 0.893504952961406 & 0.212990094077188 & 0.106495047038594 \tabularnewline
74 & 0.897511185192423 & 0.204977629615153 & 0.102488814807577 \tabularnewline
75 & 0.879663103503591 & 0.240673792992817 & 0.120336896496409 \tabularnewline
76 & 0.877907794825243 & 0.244184410349514 & 0.122092205174757 \tabularnewline
77 & 0.877948041040174 & 0.244103917919652 & 0.122051958959826 \tabularnewline
78 & 0.873453929629199 & 0.253092140741602 & 0.126546070370801 \tabularnewline
79 & 0.854864513832386 & 0.290270972335227 & 0.145135486167614 \tabularnewline
80 & 0.898046232841782 & 0.203907534316436 & 0.101953767158218 \tabularnewline
81 & 0.898317825189465 & 0.203364349621069 & 0.101682174810535 \tabularnewline
82 & 0.887286955541862 & 0.225426088916276 & 0.112713044458138 \tabularnewline
83 & 0.87139488536475 & 0.2572102292705 & 0.12860511463525 \tabularnewline
84 & 0.862787357624313 & 0.274425284751374 & 0.137212642375687 \tabularnewline
85 & 0.846719009656947 & 0.306561980686106 & 0.153280990343053 \tabularnewline
86 & 0.834291707256812 & 0.331416585486376 & 0.165708292743188 \tabularnewline
87 & 0.811089274758027 & 0.377821450483945 & 0.188910725241973 \tabularnewline
88 & 0.785961778648896 & 0.428076442702207 & 0.214038221351104 \tabularnewline
89 & 0.821225128614282 & 0.357549742771435 & 0.178774871385718 \tabularnewline
90 & 0.878324233095337 & 0.243351533809326 & 0.121675766904663 \tabularnewline
91 & 0.976384794346874 & 0.0472304113062524 & 0.0236152056531262 \tabularnewline
92 & 0.971677252382645 & 0.05664549523471 & 0.028322747617355 \tabularnewline
93 & 0.965695693446525 & 0.0686086131069502 & 0.0343043065534751 \tabularnewline
94 & 0.967115624275017 & 0.0657687514499662 & 0.0328843757249831 \tabularnewline
95 & 0.964172620687424 & 0.071654758625152 & 0.035827379312576 \tabularnewline
96 & 0.966544392673318 & 0.0669112146533639 & 0.0334556073266819 \tabularnewline
97 & 0.995416417658904 & 0.00916716468219184 & 0.00458358234109592 \tabularnewline
98 & 0.994436039069678 & 0.0111279218606444 & 0.00556396093032222 \tabularnewline
99 & 0.99825215954537 & 0.00349568090926111 & 0.00174784045463055 \tabularnewline
100 & 0.998018757042508 & 0.0039624859149831 & 0.00198124295749155 \tabularnewline
101 & 0.997416881755518 & 0.00516623648896363 & 0.00258311824448182 \tabularnewline
102 & 0.99741092374106 & 0.0051781525178798 & 0.0025890762589399 \tabularnewline
103 & 0.997188489929758 & 0.00562302014048422 & 0.00281151007024211 \tabularnewline
104 & 0.9976172484068 & 0.00476550318640238 & 0.00238275159320119 \tabularnewline
105 & 0.997102398071023 & 0.00579520385795475 & 0.00289760192897737 \tabularnewline
106 & 0.997772774674038 & 0.00445445065192298 & 0.00222722532596149 \tabularnewline
107 & 0.999152832702167 & 0.00169433459566544 & 0.000847167297832718 \tabularnewline
108 & 0.999568474254738 & 0.000863051490523774 & 0.000431525745261887 \tabularnewline
109 & 0.999446304905205 & 0.00110739018959073 & 0.000553695094795364 \tabularnewline
110 & 0.999352430347842 & 0.00129513930431544 & 0.00064756965215772 \tabularnewline
111 & 0.999188892870024 & 0.00162221425995148 & 0.000811107129975742 \tabularnewline
112 & 0.999943351755387 & 0.000113296489225284 & 5.66482446126421e-05 \tabularnewline
113 & 0.999939430588365 & 0.0001211388232696 & 6.05694116347998e-05 \tabularnewline
114 & 0.999988430319021 & 2.31393619571923e-05 & 1.15696809785962e-05 \tabularnewline
115 & 0.99999826054247 & 3.47891506026122e-06 & 1.73945753013061e-06 \tabularnewline
116 & 0.999997781002718 & 4.43799456378852e-06 & 2.21899728189426e-06 \tabularnewline
117 & 0.999997098888608 & 5.80222278352281e-06 & 2.9011113917614e-06 \tabularnewline
118 & 0.999995744595392 & 8.51080921695537e-06 & 4.25540460847769e-06 \tabularnewline
119 & 0.999995668549685 & 8.66290063046153e-06 & 4.33145031523076e-06 \tabularnewline
120 & 0.999994598890574 & 1.08022188515113e-05 & 5.40110942575564e-06 \tabularnewline
121 & 0.999992640506122 & 1.47189877559588e-05 & 7.3594938779794e-06 \tabularnewline
122 & 0.999990653139536 & 1.86937209288548e-05 & 9.3468604644274e-06 \tabularnewline
123 & 0.999989779156428 & 2.04416871450244e-05 & 1.02208435725122e-05 \tabularnewline
124 & 0.999985076640667 & 2.98467186660902e-05 & 1.49233593330451e-05 \tabularnewline
125 & 0.999985324528666 & 2.93509426687699e-05 & 1.4675471334385e-05 \tabularnewline
126 & 0.999981662956806 & 3.66740863876239e-05 & 1.8337043193812e-05 \tabularnewline
127 & 0.999974943545141 & 5.01129097174216e-05 & 2.50564548587108e-05 \tabularnewline
128 & 0.99998197525141 & 3.60494971807535e-05 & 1.80247485903768e-05 \tabularnewline
129 & 0.999991968416999 & 1.60631660027366e-05 & 8.0315830013683e-06 \tabularnewline
130 & 0.999988308083202 & 2.33838335956857e-05 & 1.16919167978428e-05 \tabularnewline
131 & 0.999983931602368 & 3.21367952648065e-05 & 1.60683976324032e-05 \tabularnewline
132 & 0.999988165836753 & 2.36683264941973e-05 & 1.18341632470987e-05 \tabularnewline
133 & 0.999982740085882 & 3.45198282364579e-05 & 1.72599141182289e-05 \tabularnewline
134 & 0.999975868788323 & 4.8262423354553e-05 & 2.41312116772765e-05 \tabularnewline
135 & 0.999972180768201 & 5.56384635973023e-05 & 2.78192317986512e-05 \tabularnewline
136 & 0.99999054505435 & 1.89098912998687e-05 & 9.45494564993433e-06 \tabularnewline
137 & 0.999986594437067 & 2.68111258660723e-05 & 1.34055629330361e-05 \tabularnewline
138 & 0.999990654959795 & 1.86900804107405e-05 & 9.34504020537025e-06 \tabularnewline
139 & 0.999987181288256 & 2.56374234881839e-05 & 1.2818711744092e-05 \tabularnewline
140 & 0.999985301196784 & 2.93976064328988e-05 & 1.46988032164494e-05 \tabularnewline
141 & 0.999978826854482 & 4.23462910358321e-05 & 2.11731455179161e-05 \tabularnewline
142 & 0.999969697235052 & 6.06055298965676e-05 & 3.03027649482838e-05 \tabularnewline
143 & 0.999956503487843 & 8.69930243147445e-05 & 4.34965121573722e-05 \tabularnewline
144 & 0.999939362173622 & 0.000121275652756724 & 6.0637826378362e-05 \tabularnewline
145 & 0.999954303809587 & 9.13923808267544e-05 & 4.56961904133772e-05 \tabularnewline
146 & 0.999952788050863 & 9.44238982736565e-05 & 4.72119491368282e-05 \tabularnewline
147 & 0.999949929411838 & 0.000100141176323887 & 5.00705881619436e-05 \tabularnewline
148 & 0.999933838214944 & 0.000132323570112083 & 6.61617850560416e-05 \tabularnewline
149 & 0.999907125447175 & 0.000185749105649963 & 9.28745528249813e-05 \tabularnewline
150 & 0.999932373223596 & 0.000135253552807139 & 6.76267764035694e-05 \tabularnewline
151 & 0.99993251754015 & 0.000134964919700985 & 6.74824598504925e-05 \tabularnewline
152 & 0.999919744029202 & 0.000160511941596216 & 8.0255970798108e-05 \tabularnewline
153 & 0.999893678614637 & 0.000212642770725099 & 0.00010632138536255 \tabularnewline
154 & 0.999858023911306 & 0.000283952177388939 & 0.000141976088694469 \tabularnewline
155 & 0.999831834273275 & 0.000336331453450704 & 0.000168165726725352 \tabularnewline
156 & 0.999777196042136 & 0.000445607915728964 & 0.000222803957864482 \tabularnewline
157 & 0.999829623884955 & 0.000340752230089971 & 0.000170376115044985 \tabularnewline
158 & 0.999763501783869 & 0.000472996432261747 & 0.000236498216130874 \tabularnewline
159 & 0.999677241125162 & 0.000645517749676935 & 0.000322758874838468 \tabularnewline
160 & 0.999814613008344 & 0.000370773983311113 & 0.000185386991655557 \tabularnewline
161 & 0.99977124863243 & 0.000457502735140845 & 0.000228751367570422 \tabularnewline
162 & 0.999862710119156 & 0.000274579761687454 & 0.000137289880843727 \tabularnewline
163 & 0.999823201028563 & 0.000353597942873716 & 0.000176798971436858 \tabularnewline
164 & 0.999806127312634 & 0.0003877453747323 & 0.00019387268736615 \tabularnewline
165 & 0.999737931313392 & 0.000524137373215256 & 0.000262068686607628 \tabularnewline
166 & 0.99966639846937 & 0.000667203061260799 & 0.000333601530630399 \tabularnewline
167 & 0.999580218010055 & 0.000839563979889457 & 0.000419781989944729 \tabularnewline
168 & 0.999963956569575 & 7.20868608504408e-05 & 3.60434304252204e-05 \tabularnewline
169 & 0.999960945425957 & 7.81091480863846e-05 & 3.90545740431923e-05 \tabularnewline
170 & 0.999944075713144 & 0.000111848573712431 & 5.59242868562157e-05 \tabularnewline
171 & 0.999925490603566 & 0.000149018792868567 & 7.45093964342835e-05 \tabularnewline
172 & 0.99989592120058 & 0.000208157598839265 & 0.000104078799419633 \tabularnewline
173 & 0.999923668510653 & 0.000152662978694425 & 7.63314893472124e-05 \tabularnewline
174 & 0.999905383019266 & 0.000189233961467398 & 9.4616980733699e-05 \tabularnewline
175 & 0.999983419393372 & 3.31612132553481e-05 & 1.65806066276741e-05 \tabularnewline
176 & 0.999977060874463 & 4.58782510743698e-05 & 2.29391255371849e-05 \tabularnewline
177 & 0.999966514170797 & 6.69716584051698e-05 & 3.34858292025849e-05 \tabularnewline
178 & 0.99995440317592 & 9.1193648158233e-05 & 4.55968240791165e-05 \tabularnewline
179 & 0.999963933465702 & 7.21330685950027e-05 & 3.60665342975013e-05 \tabularnewline
180 & 0.99994726418734 & 0.000105471625320801 & 5.27358126604004e-05 \tabularnewline
181 & 0.999924161732766 & 0.000151676534467468 & 7.58382672337341e-05 \tabularnewline
182 & 0.999909439445717 & 0.000181121108565388 & 9.05605542826938e-05 \tabularnewline
183 & 0.999878280853567 & 0.000243438292866362 & 0.000121719146433181 \tabularnewline
184 & 0.999914706313854 & 0.000170587372292426 & 8.52936861462131e-05 \tabularnewline
185 & 0.999995999758041 & 8.00048391708443e-06 & 4.00024195854222e-06 \tabularnewline
186 & 0.999994277436706 & 1.14451265888068e-05 & 5.72256329440342e-06 \tabularnewline
187 & 0.99999150005591 & 1.69998881795368e-05 & 8.49994408976838e-06 \tabularnewline
188 & 0.999987453221377 & 2.50935572467877e-05 & 1.25467786233938e-05 \tabularnewline
189 & 0.999981915112945 & 3.61697741096179e-05 & 1.80848870548089e-05 \tabularnewline
190 & 0.999998950146668 & 2.09970666340385e-06 & 1.04985333170193e-06 \tabularnewline
191 & 0.999999916439483 & 1.67121034182296e-07 & 8.35605170911481e-08 \tabularnewline
192 & 0.999999862900698 & 2.74198604401483e-07 & 1.37099302200741e-07 \tabularnewline
193 & 0.999999773505878 & 4.52988244756592e-07 & 2.26494122378296e-07 \tabularnewline
194 & 0.999999662063324 & 6.75873351772038e-07 & 3.37936675886019e-07 \tabularnewline
195 & 0.999999553331316 & 8.93337368781268e-07 & 4.46668684390634e-07 \tabularnewline
196 & 0.999999287172418 & 1.42565516377909e-06 & 7.12827581889546e-07 \tabularnewline
197 & 0.999999341505927 & 1.31698814656531e-06 & 6.58494073282657e-07 \tabularnewline
198 & 0.99999909826349 & 1.80347301902251e-06 & 9.01736509511255e-07 \tabularnewline
199 & 0.999998665101586 & 2.66979682902103e-06 & 1.33489841451052e-06 \tabularnewline
200 & 0.999998663466405 & 2.67306719052282e-06 & 1.33653359526141e-06 \tabularnewline
201 & 0.999997828625711 & 4.34274857791282e-06 & 2.17137428895641e-06 \tabularnewline
202 & 0.999999115505263 & 1.76898947411192e-06 & 8.84494737055962e-07 \tabularnewline
203 & 0.999999211107298 & 1.57778540315812e-06 & 7.8889270157906e-07 \tabularnewline
204 & 0.999998975120587 & 2.04975882510026e-06 & 1.02487941255013e-06 \tabularnewline
205 & 0.999998516748896 & 2.96650220854648e-06 & 1.48325110427324e-06 \tabularnewline
206 & 0.999998906787795 & 2.18642441015199e-06 & 1.09321220507599e-06 \tabularnewline
207 & 0.999998529356714 & 2.94128657168701e-06 & 1.4706432858435e-06 \tabularnewline
208 & 0.99999770338654 & 4.59322692039994e-06 & 2.29661346019997e-06 \tabularnewline
209 & 0.999996583697036 & 6.83260592828421e-06 & 3.41630296414211e-06 \tabularnewline
210 & 0.999997101481766 & 5.7970364678063e-06 & 2.89851823390315e-06 \tabularnewline
211 & 0.99999527880849 & 9.44238301858473e-06 & 4.72119150929236e-06 \tabularnewline
212 & 0.999992328243316 & 1.5343513369068e-05 & 7.67175668453399e-06 \tabularnewline
213 & 0.999987616419296 & 2.47671614077239e-05 & 1.2383580703862e-05 \tabularnewline
214 & 0.999985426665791 & 2.91466684173216e-05 & 1.45733342086608e-05 \tabularnewline
215 & 0.999976736059623 & 4.65278807544994e-05 & 2.32639403772497e-05 \tabularnewline
216 & 0.999990823027214 & 1.83539455719418e-05 & 9.1769727859709e-06 \tabularnewline
217 & 0.999989282164576 & 2.14356708475768e-05 & 1.07178354237884e-05 \tabularnewline
218 & 0.999984118967837 & 3.17620643264989e-05 & 1.58810321632495e-05 \tabularnewline
219 & 0.999977613929521 & 4.4772140958078e-05 & 2.2386070479039e-05 \tabularnewline
220 & 0.999969919901166 & 6.01601976680069e-05 & 3.00800988340034e-05 \tabularnewline
221 & 0.999965059720338 & 6.98805593244949e-05 & 3.49402796622475e-05 \tabularnewline
222 & 0.99994677054127 & 0.000106458917461463 & 5.32294587307316e-05 \tabularnewline
223 & 0.999918267185639 & 0.000163465628722385 & 8.17328143611925e-05 \tabularnewline
224 & 0.999876650819765 & 0.000246698360470533 & 0.000123349180235267 \tabularnewline
225 & 0.999816568312133 & 0.000366863375733768 & 0.000183431687866884 \tabularnewline
226 & 0.999763739516192 & 0.00047252096761562 & 0.00023626048380781 \tabularnewline
227 & 0.999872803639858 & 0.000254392720283398 & 0.000127196360141699 \tabularnewline
228 & 0.999894311467721 & 0.000211377064557608 & 0.000105688532278804 \tabularnewline
229 & 0.99984426773668 & 0.00031146452663868 & 0.00015573226331934 \tabularnewline
230 & 0.99994351444618 & 0.000112971107640838 & 5.64855538204192e-05 \tabularnewline
231 & 0.999923513004265 & 0.000152973991469981 & 7.64869957349906e-05 \tabularnewline
232 & 0.999879583177768 & 0.000240833644463669 & 0.000120416822231835 \tabularnewline
233 & 0.999807010012536 & 0.000385979974928306 & 0.000192989987464153 \tabularnewline
234 & 0.999715299281495 & 0.000569401437010203 & 0.000284700718505102 \tabularnewline
235 & 0.99967658391838 & 0.000646832163239942 & 0.000323416081619971 \tabularnewline
236 & 0.999494846464042 & 0.00101030707191637 & 0.000505153535958187 \tabularnewline
237 & 0.999219234671655 & 0.00156153065668964 & 0.00078076532834482 \tabularnewline
238 & 0.999942775084564 & 0.000114449830871787 & 5.72249154358936e-05 \tabularnewline
239 & 0.9999188940228 & 0.000162211954401283 & 8.11059772006413e-05 \tabularnewline
240 & 0.999870302480157 & 0.000259395039686554 & 0.000129697519843277 \tabularnewline
241 & 0.999896260731368 & 0.000207478537264504 & 0.000103739268632252 \tabularnewline
242 & 0.99985122248751 & 0.000297555024980989 & 0.000148777512490495 \tabularnewline
243 & 0.99975380318989 & 0.000492393620219381 & 0.00024619681010969 \tabularnewline
244 & 0.999663803045124 & 0.000672393909751683 & 0.000336196954875841 \tabularnewline
245 & 0.999448294207222 & 0.00110341158555678 & 0.00055170579277839 \tabularnewline
246 & 0.999330336041748 & 0.00133932791650387 & 0.000669663958251934 \tabularnewline
247 & 0.998910298449188 & 0.00217940310162355 & 0.00108970155081178 \tabularnewline
248 & 0.99828121643751 & 0.00343756712498187 & 0.00171878356249093 \tabularnewline
249 & 0.997659904772424 & 0.00468019045515275 & 0.00234009522757638 \tabularnewline
250 & 0.997065133166554 & 0.00586973366689195 & 0.00293486683344598 \tabularnewline
251 & 0.99590194776665 & 0.00819610446669799 & 0.004098052233349 \tabularnewline
252 & 0.9936933238458 & 0.0126133523084018 & 0.0063066761542009 \tabularnewline
253 & 0.990387076997932 & 0.0192258460041365 & 0.00961292300206825 \tabularnewline
254 & 0.991226864348571 & 0.0175462713028579 & 0.00877313565142893 \tabularnewline
255 & 0.98803953103711 & 0.0239209379257819 & 0.0119604689628909 \tabularnewline
256 & 0.983259426023705 & 0.0334811479525901 & 0.016740573976295 \tabularnewline
257 & 0.975300148659819 & 0.0493997026803627 & 0.0246998513401814 \tabularnewline
258 & 0.964783071971272 & 0.0704338560574566 & 0.0352169280287283 \tabularnewline
259 & 0.9548872869446 & 0.0902254261107984 & 0.0451127130553992 \tabularnewline
260 & 0.94299296806664 & 0.114014063866721 & 0.0570070319333604 \tabularnewline
261 & 0.977586541929778 & 0.0448269161404438 & 0.0224134580702219 \tabularnewline
262 & 0.984917232746286 & 0.0301655345074289 & 0.0150827672537144 \tabularnewline
263 & 0.978533225873897 & 0.0429335482522069 & 0.0214667741261035 \tabularnewline
264 & 0.974025783131962 & 0.0519484337360768 & 0.0259742168680384 \tabularnewline
265 & 0.977226557007979 & 0.0455468859840426 & 0.0227734429920213 \tabularnewline
266 & 0.973239340200354 & 0.0535213195992925 & 0.0267606597996463 \tabularnewline
267 & 0.968812012326498 & 0.0623759753470036 & 0.0311879876735018 \tabularnewline
268 & 0.965488765588339 & 0.0690224688233226 & 0.0345112344116613 \tabularnewline
269 & 0.961963783455929 & 0.0760724330881416 & 0.0380362165440708 \tabularnewline
270 & 0.99183631324637 & 0.0163273735072588 & 0.00816368675362941 \tabularnewline
271 & 0.988480062684744 & 0.0230398746305111 & 0.0115199373152556 \tabularnewline
272 & 0.9814355898591 & 0.0371288202817987 & 0.0185644101408994 \tabularnewline
273 & 0.97738651916253 & 0.0452269616749392 & 0.0226134808374696 \tabularnewline
274 & 0.957273690988814 & 0.0854526180223719 & 0.0427263090111859 \tabularnewline
275 & 0.951195258316218 & 0.0976094833675634 & 0.0488047416837817 \tabularnewline
276 & 0.96931891359719 & 0.0613621728056185 & 0.0306810864028093 \tabularnewline
277 & 0.941422324629678 & 0.117155350740643 & 0.0585776753703215 \tabularnewline
278 & 0.871915591323106 & 0.256168817353787 & 0.128084408676894 \tabularnewline
279 & 0.813770036751582 & 0.372459926496835 & 0.186229963248418 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155913&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]10[/C][C]0.664924679589817[/C][C]0.670150640820367[/C][C]0.335075320410183[/C][/ROW]
[ROW][C]11[/C][C]0.6739107137289[/C][C]0.6521785725422[/C][C]0.3260892862711[/C][/ROW]
[ROW][C]12[/C][C]0.661869422836702[/C][C]0.676261154326597[/C][C]0.338130577163298[/C][/ROW]
[ROW][C]13[/C][C]0.755547798825873[/C][C]0.488904402348253[/C][C]0.244452201174127[/C][/ROW]
[ROW][C]14[/C][C]0.661154686787907[/C][C]0.677690626424186[/C][C]0.338845313212093[/C][/ROW]
[ROW][C]15[/C][C]0.56235298470472[/C][C]0.87529403059056[/C][C]0.43764701529528[/C][/ROW]
[ROW][C]16[/C][C]0.822741101040472[/C][C]0.354517797919056[/C][C]0.177258898959528[/C][/ROW]
[ROW][C]17[/C][C]0.769190691603093[/C][C]0.461618616793814[/C][C]0.230809308396907[/C][/ROW]
[ROW][C]18[/C][C]0.775593193145727[/C][C]0.448813613708546[/C][C]0.224406806854273[/C][/ROW]
[ROW][C]19[/C][C]0.842764060735408[/C][C]0.314471878529185[/C][C]0.157235939264592[/C][/ROW]
[ROW][C]20[/C][C]0.830777239180084[/C][C]0.338445521639831[/C][C]0.169222760819916[/C][/ROW]
[ROW][C]21[/C][C]0.812970805056816[/C][C]0.374058389886369[/C][C]0.187029194943184[/C][/ROW]
[ROW][C]22[/C][C]0.758647586192318[/C][C]0.482704827615364[/C][C]0.241352413807682[/C][/ROW]
[ROW][C]23[/C][C]0.783379984191354[/C][C]0.433240031617292[/C][C]0.216620015808646[/C][/ROW]
[ROW][C]24[/C][C]0.746856649458749[/C][C]0.506286701082501[/C][C]0.253143350541251[/C][/ROW]
[ROW][C]25[/C][C]0.890662033976401[/C][C]0.218675932047198[/C][C]0.109337966023599[/C][/ROW]
[ROW][C]26[/C][C]0.86004421348263[/C][C]0.279911573034738[/C][C]0.139955786517369[/C][/ROW]
[ROW][C]27[/C][C]0.853007636634983[/C][C]0.293984726730035[/C][C]0.146992363365017[/C][/ROW]
[ROW][C]28[/C][C]0.821830918573127[/C][C]0.356338162853747[/C][C]0.178169081426873[/C][/ROW]
[ROW][C]29[/C][C]0.788444011231306[/C][C]0.423111977537388[/C][C]0.211555988768694[/C][/ROW]
[ROW][C]30[/C][C]0.759013971584268[/C][C]0.481972056831464[/C][C]0.240986028415732[/C][/ROW]
[ROW][C]31[/C][C]0.714183091664631[/C][C]0.571633816670737[/C][C]0.285816908335369[/C][/ROW]
[ROW][C]32[/C][C]0.72235146652763[/C][C]0.55529706694474[/C][C]0.27764853347237[/C][/ROW]
[ROW][C]33[/C][C]0.67221700213187[/C][C]0.655565995736259[/C][C]0.327782997868129[/C][/ROW]
[ROW][C]34[/C][C]0.656197773136286[/C][C]0.687604453727428[/C][C]0.343802226863714[/C][/ROW]
[ROW][C]35[/C][C]0.727282893586217[/C][C]0.545434212827567[/C][C]0.272717106413783[/C][/ROW]
[ROW][C]36[/C][C]0.708594516477222[/C][C]0.582810967045555[/C][C]0.291405483522778[/C][/ROW]
[ROW][C]37[/C][C]0.663187920893024[/C][C]0.673624158213953[/C][C]0.336812079106976[/C][/ROW]
[ROW][C]38[/C][C]0.624646051718085[/C][C]0.75070789656383[/C][C]0.375353948281915[/C][/ROW]
[ROW][C]39[/C][C]0.602912028212582[/C][C]0.794175943574836[/C][C]0.397087971787418[/C][/ROW]
[ROW][C]40[/C][C]0.58761299444018[/C][C]0.82477401111964[/C][C]0.41238700555982[/C][/ROW]
[ROW][C]41[/C][C]0.603194991681976[/C][C]0.793610016636048[/C][C]0.396805008318024[/C][/ROW]
[ROW][C]42[/C][C]0.555501618437877[/C][C]0.888996763124246[/C][C]0.444498381562123[/C][/ROW]
[ROW][C]43[/C][C]0.524494813607532[/C][C]0.951010372784935[/C][C]0.475505186392468[/C][/ROW]
[ROW][C]44[/C][C]0.514186166202854[/C][C]0.971627667594293[/C][C]0.485813833797146[/C][/ROW]
[ROW][C]45[/C][C]0.479636080705171[/C][C]0.959272161410341[/C][C]0.520363919294829[/C][/ROW]
[ROW][C]46[/C][C]0.45201258133487[/C][C]0.904025162669741[/C][C]0.54798741866513[/C][/ROW]
[ROW][C]47[/C][C]0.464660773934563[/C][C]0.929321547869126[/C][C]0.535339226065437[/C][/ROW]
[ROW][C]48[/C][C]0.417788294518378[/C][C]0.835576589036756[/C][C]0.582211705481622[/C][/ROW]
[ROW][C]49[/C][C]0.371636561604547[/C][C]0.743273123209094[/C][C]0.628363438395453[/C][/ROW]
[ROW][C]50[/C][C]0.964188687985247[/C][C]0.071622624029506[/C][C]0.035811312014753[/C][/ROW]
[ROW][C]51[/C][C]0.966432429350127[/C][C]0.0671351412997454[/C][C]0.0335675706498727[/C][/ROW]
[ROW][C]52[/C][C]0.960564973236552[/C][C]0.0788700535268965[/C][C]0.0394350267634483[/C][/ROW]
[ROW][C]53[/C][C]0.954491238457601[/C][C]0.091017523084798[/C][C]0.045508761542399[/C][/ROW]
[ROW][C]54[/C][C]0.943325859396368[/C][C]0.113348281207264[/C][C]0.0566741406036319[/C][/ROW]
[ROW][C]55[/C][C]0.936734168242256[/C][C]0.126531663515489[/C][C]0.0632658317577444[/C][/ROW]
[ROW][C]56[/C][C]0.924471016927821[/C][C]0.151057966144357[/C][C]0.0755289830721787[/C][/ROW]
[ROW][C]57[/C][C]0.91027213633494[/C][C]0.179455727330119[/C][C]0.0897278636650593[/C][/ROW]
[ROW][C]58[/C][C]0.908252497692675[/C][C]0.183495004614649[/C][C]0.0917475023073246[/C][/ROW]
[ROW][C]59[/C][C]0.904681301989475[/C][C]0.190637396021049[/C][C]0.0953186980105246[/C][/ROW]
[ROW][C]60[/C][C]0.88613342963835[/C][C]0.227733140723301[/C][C]0.11386657036165[/C][/ROW]
[ROW][C]61[/C][C]0.864858628211794[/C][C]0.270282743576411[/C][C]0.135141371788206[/C][/ROW]
[ROW][C]62[/C][C]0.863558593854722[/C][C]0.272882812290556[/C][C]0.136441406145278[/C][/ROW]
[ROW][C]63[/C][C]0.857295346956222[/C][C]0.285409306087555[/C][C]0.142704653043778[/C][/ROW]
[ROW][C]64[/C][C]0.834788370282273[/C][C]0.330423259435454[/C][C]0.165211629717727[/C][/ROW]
[ROW][C]65[/C][C]0.809539431246337[/C][C]0.380921137507326[/C][C]0.190460568753663[/C][/ROW]
[ROW][C]66[/C][C]0.787969172740334[/C][C]0.424061654519333[/C][C]0.212030827259666[/C][/ROW]
[ROW][C]67[/C][C]0.764364971926715[/C][C]0.471270056146569[/C][C]0.235635028073285[/C][/ROW]
[ROW][C]68[/C][C]0.748009533056448[/C][C]0.503980933887103[/C][C]0.251990466943552[/C][/ROW]
[ROW][C]69[/C][C]0.79712605361711[/C][C]0.405747892765781[/C][C]0.20287394638289[/C][/ROW]
[ROW][C]70[/C][C]0.871210568274248[/C][C]0.257578863451504[/C][C]0.128789431725752[/C][/ROW]
[ROW][C]71[/C][C]0.88406192830028[/C][C]0.23187614339944[/C][C]0.11593807169972[/C][/ROW]
[ROW][C]72[/C][C]0.888732136653538[/C][C]0.222535726692925[/C][C]0.111267863346462[/C][/ROW]
[ROW][C]73[/C][C]0.893504952961406[/C][C]0.212990094077188[/C][C]0.106495047038594[/C][/ROW]
[ROW][C]74[/C][C]0.897511185192423[/C][C]0.204977629615153[/C][C]0.102488814807577[/C][/ROW]
[ROW][C]75[/C][C]0.879663103503591[/C][C]0.240673792992817[/C][C]0.120336896496409[/C][/ROW]
[ROW][C]76[/C][C]0.877907794825243[/C][C]0.244184410349514[/C][C]0.122092205174757[/C][/ROW]
[ROW][C]77[/C][C]0.877948041040174[/C][C]0.244103917919652[/C][C]0.122051958959826[/C][/ROW]
[ROW][C]78[/C][C]0.873453929629199[/C][C]0.253092140741602[/C][C]0.126546070370801[/C][/ROW]
[ROW][C]79[/C][C]0.854864513832386[/C][C]0.290270972335227[/C][C]0.145135486167614[/C][/ROW]
[ROW][C]80[/C][C]0.898046232841782[/C][C]0.203907534316436[/C][C]0.101953767158218[/C][/ROW]
[ROW][C]81[/C][C]0.898317825189465[/C][C]0.203364349621069[/C][C]0.101682174810535[/C][/ROW]
[ROW][C]82[/C][C]0.887286955541862[/C][C]0.225426088916276[/C][C]0.112713044458138[/C][/ROW]
[ROW][C]83[/C][C]0.87139488536475[/C][C]0.2572102292705[/C][C]0.12860511463525[/C][/ROW]
[ROW][C]84[/C][C]0.862787357624313[/C][C]0.274425284751374[/C][C]0.137212642375687[/C][/ROW]
[ROW][C]85[/C][C]0.846719009656947[/C][C]0.306561980686106[/C][C]0.153280990343053[/C][/ROW]
[ROW][C]86[/C][C]0.834291707256812[/C][C]0.331416585486376[/C][C]0.165708292743188[/C][/ROW]
[ROW][C]87[/C][C]0.811089274758027[/C][C]0.377821450483945[/C][C]0.188910725241973[/C][/ROW]
[ROW][C]88[/C][C]0.785961778648896[/C][C]0.428076442702207[/C][C]0.214038221351104[/C][/ROW]
[ROW][C]89[/C][C]0.821225128614282[/C][C]0.357549742771435[/C][C]0.178774871385718[/C][/ROW]
[ROW][C]90[/C][C]0.878324233095337[/C][C]0.243351533809326[/C][C]0.121675766904663[/C][/ROW]
[ROW][C]91[/C][C]0.976384794346874[/C][C]0.0472304113062524[/C][C]0.0236152056531262[/C][/ROW]
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[ROW][C]116[/C][C]0.999997781002718[/C][C]4.43799456378852e-06[/C][C]2.21899728189426e-06[/C][/ROW]
[ROW][C]117[/C][C]0.999997098888608[/C][C]5.80222278352281e-06[/C][C]2.9011113917614e-06[/C][/ROW]
[ROW][C]118[/C][C]0.999995744595392[/C][C]8.51080921695537e-06[/C][C]4.25540460847769e-06[/C][/ROW]
[ROW][C]119[/C][C]0.999995668549685[/C][C]8.66290063046153e-06[/C][C]4.33145031523076e-06[/C][/ROW]
[ROW][C]120[/C][C]0.999994598890574[/C][C]1.08022188515113e-05[/C][C]5.40110942575564e-06[/C][/ROW]
[ROW][C]121[/C][C]0.999992640506122[/C][C]1.47189877559588e-05[/C][C]7.3594938779794e-06[/C][/ROW]
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[ROW][C]124[/C][C]0.999985076640667[/C][C]2.98467186660902e-05[/C][C]1.49233593330451e-05[/C][/ROW]
[ROW][C]125[/C][C]0.999985324528666[/C][C]2.93509426687699e-05[/C][C]1.4675471334385e-05[/C][/ROW]
[ROW][C]126[/C][C]0.999981662956806[/C][C]3.66740863876239e-05[/C][C]1.8337043193812e-05[/C][/ROW]
[ROW][C]127[/C][C]0.999974943545141[/C][C]5.01129097174216e-05[/C][C]2.50564548587108e-05[/C][/ROW]
[ROW][C]128[/C][C]0.99998197525141[/C][C]3.60494971807535e-05[/C][C]1.80247485903768e-05[/C][/ROW]
[ROW][C]129[/C][C]0.999991968416999[/C][C]1.60631660027366e-05[/C][C]8.0315830013683e-06[/C][/ROW]
[ROW][C]130[/C][C]0.999988308083202[/C][C]2.33838335956857e-05[/C][C]1.16919167978428e-05[/C][/ROW]
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[ROW][C]176[/C][C]0.999977060874463[/C][C]4.58782510743698e-05[/C][C]2.29391255371849e-05[/C][/ROW]
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[ROW][C]189[/C][C]0.999981915112945[/C][C]3.61697741096179e-05[/C][C]1.80848870548089e-05[/C][/ROW]
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[ROW][C]217[/C][C]0.999989282164576[/C][C]2.14356708475768e-05[/C][C]1.07178354237884e-05[/C][/ROW]
[ROW][C]218[/C][C]0.999984118967837[/C][C]3.17620643264989e-05[/C][C]1.58810321632495e-05[/C][/ROW]
[ROW][C]219[/C][C]0.999977613929521[/C][C]4.4772140958078e-05[/C][C]2.2386070479039e-05[/C][/ROW]
[ROW][C]220[/C][C]0.999969919901166[/C][C]6.01601976680069e-05[/C][C]3.00800988340034e-05[/C][/ROW]
[ROW][C]221[/C][C]0.999965059720338[/C][C]6.98805593244949e-05[/C][C]3.49402796622475e-05[/C][/ROW]
[ROW][C]222[/C][C]0.99994677054127[/C][C]0.000106458917461463[/C][C]5.32294587307316e-05[/C][/ROW]
[ROW][C]223[/C][C]0.999918267185639[/C][C]0.000163465628722385[/C][C]8.17328143611925e-05[/C][/ROW]
[ROW][C]224[/C][C]0.999876650819765[/C][C]0.000246698360470533[/C][C]0.000123349180235267[/C][/ROW]
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[ROW][C]228[/C][C]0.999894311467721[/C][C]0.000211377064557608[/C][C]0.000105688532278804[/C][/ROW]
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[ROW][C]230[/C][C]0.99994351444618[/C][C]0.000112971107640838[/C][C]5.64855538204192e-05[/C][/ROW]
[ROW][C]231[/C][C]0.999923513004265[/C][C]0.000152973991469981[/C][C]7.64869957349906e-05[/C][/ROW]
[ROW][C]232[/C][C]0.999879583177768[/C][C]0.000240833644463669[/C][C]0.000120416822231835[/C][/ROW]
[ROW][C]233[/C][C]0.999807010012536[/C][C]0.000385979974928306[/C][C]0.000192989987464153[/C][/ROW]
[ROW][C]234[/C][C]0.999715299281495[/C][C]0.000569401437010203[/C][C]0.000284700718505102[/C][/ROW]
[ROW][C]235[/C][C]0.99967658391838[/C][C]0.000646832163239942[/C][C]0.000323416081619971[/C][/ROW]
[ROW][C]236[/C][C]0.999494846464042[/C][C]0.00101030707191637[/C][C]0.000505153535958187[/C][/ROW]
[ROW][C]237[/C][C]0.999219234671655[/C][C]0.00156153065668964[/C][C]0.00078076532834482[/C][/ROW]
[ROW][C]238[/C][C]0.999942775084564[/C][C]0.000114449830871787[/C][C]5.72249154358936e-05[/C][/ROW]
[ROW][C]239[/C][C]0.9999188940228[/C][C]0.000162211954401283[/C][C]8.11059772006413e-05[/C][/ROW]
[ROW][C]240[/C][C]0.999870302480157[/C][C]0.000259395039686554[/C][C]0.000129697519843277[/C][/ROW]
[ROW][C]241[/C][C]0.999896260731368[/C][C]0.000207478537264504[/C][C]0.000103739268632252[/C][/ROW]
[ROW][C]242[/C][C]0.99985122248751[/C][C]0.000297555024980989[/C][C]0.000148777512490495[/C][/ROW]
[ROW][C]243[/C][C]0.99975380318989[/C][C]0.000492393620219381[/C][C]0.00024619681010969[/C][/ROW]
[ROW][C]244[/C][C]0.999663803045124[/C][C]0.000672393909751683[/C][C]0.000336196954875841[/C][/ROW]
[ROW][C]245[/C][C]0.999448294207222[/C][C]0.00110341158555678[/C][C]0.00055170579277839[/C][/ROW]
[ROW][C]246[/C][C]0.999330336041748[/C][C]0.00133932791650387[/C][C]0.000669663958251934[/C][/ROW]
[ROW][C]247[/C][C]0.998910298449188[/C][C]0.00217940310162355[/C][C]0.00108970155081178[/C][/ROW]
[ROW][C]248[/C][C]0.99828121643751[/C][C]0.00343756712498187[/C][C]0.00171878356249093[/C][/ROW]
[ROW][C]249[/C][C]0.997659904772424[/C][C]0.00468019045515275[/C][C]0.00234009522757638[/C][/ROW]
[ROW][C]250[/C][C]0.997065133166554[/C][C]0.00586973366689195[/C][C]0.00293486683344598[/C][/ROW]
[ROW][C]251[/C][C]0.99590194776665[/C][C]0.00819610446669799[/C][C]0.004098052233349[/C][/ROW]
[ROW][C]252[/C][C]0.9936933238458[/C][C]0.0126133523084018[/C][C]0.0063066761542009[/C][/ROW]
[ROW][C]253[/C][C]0.990387076997932[/C][C]0.0192258460041365[/C][C]0.00961292300206825[/C][/ROW]
[ROW][C]254[/C][C]0.991226864348571[/C][C]0.0175462713028579[/C][C]0.00877313565142893[/C][/ROW]
[ROW][C]255[/C][C]0.98803953103711[/C][C]0.0239209379257819[/C][C]0.0119604689628909[/C][/ROW]
[ROW][C]256[/C][C]0.983259426023705[/C][C]0.0334811479525901[/C][C]0.016740573976295[/C][/ROW]
[ROW][C]257[/C][C]0.975300148659819[/C][C]0.0493997026803627[/C][C]0.0246998513401814[/C][/ROW]
[ROW][C]258[/C][C]0.964783071971272[/C][C]0.0704338560574566[/C][C]0.0352169280287283[/C][/ROW]
[ROW][C]259[/C][C]0.9548872869446[/C][C]0.0902254261107984[/C][C]0.0451127130553992[/C][/ROW]
[ROW][C]260[/C][C]0.94299296806664[/C][C]0.114014063866721[/C][C]0.0570070319333604[/C][/ROW]
[ROW][C]261[/C][C]0.977586541929778[/C][C]0.0448269161404438[/C][C]0.0224134580702219[/C][/ROW]
[ROW][C]262[/C][C]0.984917232746286[/C][C]0.0301655345074289[/C][C]0.0150827672537144[/C][/ROW]
[ROW][C]263[/C][C]0.978533225873897[/C][C]0.0429335482522069[/C][C]0.0214667741261035[/C][/ROW]
[ROW][C]264[/C][C]0.974025783131962[/C][C]0.0519484337360768[/C][C]0.0259742168680384[/C][/ROW]
[ROW][C]265[/C][C]0.977226557007979[/C][C]0.0455468859840426[/C][C]0.0227734429920213[/C][/ROW]
[ROW][C]266[/C][C]0.973239340200354[/C][C]0.0535213195992925[/C][C]0.0267606597996463[/C][/ROW]
[ROW][C]267[/C][C]0.968812012326498[/C][C]0.0623759753470036[/C][C]0.0311879876735018[/C][/ROW]
[ROW][C]268[/C][C]0.965488765588339[/C][C]0.0690224688233226[/C][C]0.0345112344116613[/C][/ROW]
[ROW][C]269[/C][C]0.961963783455929[/C][C]0.0760724330881416[/C][C]0.0380362165440708[/C][/ROW]
[ROW][C]270[/C][C]0.99183631324637[/C][C]0.0163273735072588[/C][C]0.00816368675362941[/C][/ROW]
[ROW][C]271[/C][C]0.988480062684744[/C][C]0.0230398746305111[/C][C]0.0115199373152556[/C][/ROW]
[ROW][C]272[/C][C]0.9814355898591[/C][C]0.0371288202817987[/C][C]0.0185644101408994[/C][/ROW]
[ROW][C]273[/C][C]0.97738651916253[/C][C]0.0452269616749392[/C][C]0.0226134808374696[/C][/ROW]
[ROW][C]274[/C][C]0.957273690988814[/C][C]0.0854526180223719[/C][C]0.0427263090111859[/C][/ROW]
[ROW][C]275[/C][C]0.951195258316218[/C][C]0.0976094833675634[/C][C]0.0488047416837817[/C][/ROW]
[ROW][C]276[/C][C]0.96931891359719[/C][C]0.0613621728056185[/C][C]0.0306810864028093[/C][/ROW]
[ROW][C]277[/C][C]0.941422324629678[/C][C]0.117155350740643[/C][C]0.0585776753703215[/C][/ROW]
[ROW][C]278[/C][C]0.871915591323106[/C][C]0.256168817353787[/C][C]0.128084408676894[/C][/ROW]
[ROW][C]279[/C][C]0.813770036751582[/C][C]0.372459926496835[/C][C]0.186229963248418[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155913&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155913&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
100.6649246795898170.6701506408203670.335075320410183
110.67391071372890.65217857254220.3260892862711
120.6618694228367020.6762611543265970.338130577163298
130.7555477988258730.4889044023482530.244452201174127
140.6611546867879070.6776906264241860.338845313212093
150.562352984704720.875294030590560.43764701529528
160.8227411010404720.3545177979190560.177258898959528
170.7691906916030930.4616186167938140.230809308396907
180.7755931931457270.4488136137085460.224406806854273
190.8427640607354080.3144718785291850.157235939264592
200.8307772391800840.3384455216398310.169222760819916
210.8129708050568160.3740583898863690.187029194943184
220.7586475861923180.4827048276153640.241352413807682
230.7833799841913540.4332400316172920.216620015808646
240.7468566494587490.5062867010825010.253143350541251
250.8906620339764010.2186759320471980.109337966023599
260.860044213482630.2799115730347380.139955786517369
270.8530076366349830.2939847267300350.146992363365017
280.8218309185731270.3563381628537470.178169081426873
290.7884440112313060.4231119775373880.211555988768694
300.7590139715842680.4819720568314640.240986028415732
310.7141830916646310.5716338166707370.285816908335369
320.722351466527630.555297066944740.27764853347237
330.672217002131870.6555659957362590.327782997868129
340.6561977731362860.6876044537274280.343802226863714
350.7272828935862170.5454342128275670.272717106413783
360.7085945164772220.5828109670455550.291405483522778
370.6631879208930240.6736241582139530.336812079106976
380.6246460517180850.750707896563830.375353948281915
390.6029120282125820.7941759435748360.397087971787418
400.587612994440180.824774011119640.41238700555982
410.6031949916819760.7936100166360480.396805008318024
420.5555016184378770.8889967631242460.444498381562123
430.5244948136075320.9510103727849350.475505186392468
440.5141861662028540.9716276675942930.485813833797146
450.4796360807051710.9592721614103410.520363919294829
460.452012581334870.9040251626697410.54798741866513
470.4646607739345630.9293215478691260.535339226065437
480.4177882945183780.8355765890367560.582211705481622
490.3716365616045470.7432731232090940.628363438395453
500.9641886879852470.0716226240295060.035811312014753
510.9664324293501270.06713514129974540.0335675706498727
520.9605649732365520.07887005352689650.0394350267634483
530.9544912384576010.0910175230847980.045508761542399
540.9433258593963680.1133482812072640.0566741406036319
550.9367341682422560.1265316635154890.0632658317577444
560.9244710169278210.1510579661443570.0755289830721787
570.910272136334940.1794557273301190.0897278636650593
580.9082524976926750.1834950046146490.0917475023073246
590.9046813019894750.1906373960210490.0953186980105246
600.886133429638350.2277331407233010.11386657036165
610.8648586282117940.2702827435764110.135141371788206
620.8635585938547220.2728828122905560.136441406145278
630.8572953469562220.2854093060875550.142704653043778
640.8347883702822730.3304232594354540.165211629717727
650.8095394312463370.3809211375073260.190460568753663
660.7879691727403340.4240616545193330.212030827259666
670.7643649719267150.4712700561465690.235635028073285
680.7480095330564480.5039809338871030.251990466943552
690.797126053617110.4057478927657810.20287394638289
700.8712105682742480.2575788634515040.128789431725752
710.884061928300280.231876143399440.11593807169972
720.8887321366535380.2225357266929250.111267863346462
730.8935049529614060.2129900940771880.106495047038594
740.8975111851924230.2049776296151530.102488814807577
750.8796631035035910.2406737929928170.120336896496409
760.8779077948252430.2441844103495140.122092205174757
770.8779480410401740.2441039179196520.122051958959826
780.8734539296291990.2530921407416020.126546070370801
790.8548645138323860.2902709723352270.145135486167614
800.8980462328417820.2039075343164360.101953767158218
810.8983178251894650.2033643496210690.101682174810535
820.8872869555418620.2254260889162760.112713044458138
830.871394885364750.25721022927050.12860511463525
840.8627873576243130.2744252847513740.137212642375687
850.8467190096569470.3065619806861060.153280990343053
860.8342917072568120.3314165854863760.165708292743188
870.8110892747580270.3778214504839450.188910725241973
880.7859617786488960.4280764427022070.214038221351104
890.8212251286142820.3575497427714350.178774871385718
900.8783242330953370.2433515338093260.121675766904663
910.9763847943468740.04723041130625240.0236152056531262
920.9716772523826450.056645495234710.028322747617355
930.9656956934465250.06860861310695020.0343043065534751
940.9671156242750170.06576875144996620.0328843757249831
950.9641726206874240.0716547586251520.035827379312576
960.9665443926733180.06691121465336390.0334556073266819
970.9954164176589040.009167164682191840.00458358234109592
980.9944360390696780.01112792186064440.00556396093032222
990.998252159545370.003495680909261110.00174784045463055
1000.9980187570425080.00396248591498310.00198124295749155
1010.9974168817555180.005166236488963630.00258311824448182
1020.997410923741060.00517815251787980.0025890762589399
1030.9971884899297580.005623020140484220.00281151007024211
1040.99761724840680.004765503186402380.00238275159320119
1050.9971023980710230.005795203857954750.00289760192897737
1060.9977727746740380.004454450651922980.00222722532596149
1070.9991528327021670.001694334595665440.000847167297832718
1080.9995684742547380.0008630514905237740.000431525745261887
1090.9994463049052050.001107390189590730.000553695094795364
1100.9993524303478420.001295139304315440.00064756965215772
1110.9991888928700240.001622214259951480.000811107129975742
1120.9999433517553870.0001132964892252845.66482446126421e-05
1130.9999394305883650.00012113882326966.05694116347998e-05
1140.9999884303190212.31393619571923e-051.15696809785962e-05
1150.999998260542473.47891506026122e-061.73945753013061e-06
1160.9999977810027184.43799456378852e-062.21899728189426e-06
1170.9999970988886085.80222278352281e-062.9011113917614e-06
1180.9999957445953928.51080921695537e-064.25540460847769e-06
1190.9999956685496858.66290063046153e-064.33145031523076e-06
1200.9999945988905741.08022188515113e-055.40110942575564e-06
1210.9999926405061221.47189877559588e-057.3594938779794e-06
1220.9999906531395361.86937209288548e-059.3468604644274e-06
1230.9999897791564282.04416871450244e-051.02208435725122e-05
1240.9999850766406672.98467186660902e-051.49233593330451e-05
1250.9999853245286662.93509426687699e-051.4675471334385e-05
1260.9999816629568063.66740863876239e-051.8337043193812e-05
1270.9999749435451415.01129097174216e-052.50564548587108e-05
1280.999981975251413.60494971807535e-051.80247485903768e-05
1290.9999919684169991.60631660027366e-058.0315830013683e-06
1300.9999883080832022.33838335956857e-051.16919167978428e-05
1310.9999839316023683.21367952648065e-051.60683976324032e-05
1320.9999881658367532.36683264941973e-051.18341632470987e-05
1330.9999827400858823.45198282364579e-051.72599141182289e-05
1340.9999758687883234.8262423354553e-052.41312116772765e-05
1350.9999721807682015.56384635973023e-052.78192317986512e-05
1360.999990545054351.89098912998687e-059.45494564993433e-06
1370.9999865944370672.68111258660723e-051.34055629330361e-05
1380.9999906549597951.86900804107405e-059.34504020537025e-06
1390.9999871812882562.56374234881839e-051.2818711744092e-05
1400.9999853011967842.93976064328988e-051.46988032164494e-05
1410.9999788268544824.23462910358321e-052.11731455179161e-05
1420.9999696972350526.06055298965676e-053.03027649482838e-05
1430.9999565034878438.69930243147445e-054.34965121573722e-05
1440.9999393621736220.0001212756527567246.0637826378362e-05
1450.9999543038095879.13923808267544e-054.56961904133772e-05
1460.9999527880508639.44238982736565e-054.72119491368282e-05
1470.9999499294118380.0001001411763238875.00705881619436e-05
1480.9999338382149440.0001323235701120836.61617850560416e-05
1490.9999071254471750.0001857491056499639.28745528249813e-05
1500.9999323732235960.0001352535528071396.76267764035694e-05
1510.999932517540150.0001349649197009856.74824598504925e-05
1520.9999197440292020.0001605119415962168.0255970798108e-05
1530.9998936786146370.0002126427707250990.00010632138536255
1540.9998580239113060.0002839521773889390.000141976088694469
1550.9998318342732750.0003363314534507040.000168165726725352
1560.9997771960421360.0004456079157289640.000222803957864482
1570.9998296238849550.0003407522300899710.000170376115044985
1580.9997635017838690.0004729964322617470.000236498216130874
1590.9996772411251620.0006455177496769350.000322758874838468
1600.9998146130083440.0003707739833111130.000185386991655557
1610.999771248632430.0004575027351408450.000228751367570422
1620.9998627101191560.0002745797616874540.000137289880843727
1630.9998232010285630.0003535979428737160.000176798971436858
1640.9998061273126340.00038774537473230.00019387268736615
1650.9997379313133920.0005241373732152560.000262068686607628
1660.999666398469370.0006672030612607990.000333601530630399
1670.9995802180100550.0008395639798894570.000419781989944729
1680.9999639565695757.20868608504408e-053.60434304252204e-05
1690.9999609454259577.81091480863846e-053.90545740431923e-05
1700.9999440757131440.0001118485737124315.59242868562157e-05
1710.9999254906035660.0001490187928685677.45093964342835e-05
1720.999895921200580.0002081575988392650.000104078799419633
1730.9999236685106530.0001526629786944257.63314893472124e-05
1740.9999053830192660.0001892339614673989.4616980733699e-05
1750.9999834193933723.31612132553481e-051.65806066276741e-05
1760.9999770608744634.58782510743698e-052.29391255371849e-05
1770.9999665141707976.69716584051698e-053.34858292025849e-05
1780.999954403175929.1193648158233e-054.55968240791165e-05
1790.9999639334657027.21330685950027e-053.60665342975013e-05
1800.999947264187340.0001054716253208015.27358126604004e-05
1810.9999241617327660.0001516765344674687.58382672337341e-05
1820.9999094394457170.0001811211085653889.05605542826938e-05
1830.9998782808535670.0002434382928663620.000121719146433181
1840.9999147063138540.0001705873722924268.52936861462131e-05
1850.9999959997580418.00048391708443e-064.00024195854222e-06
1860.9999942774367061.14451265888068e-055.72256329440342e-06
1870.999991500055911.69998881795368e-058.49994408976838e-06
1880.9999874532213772.50935572467877e-051.25467786233938e-05
1890.9999819151129453.61697741096179e-051.80848870548089e-05
1900.9999989501466682.09970666340385e-061.04985333170193e-06
1910.9999999164394831.67121034182296e-078.35605170911481e-08
1920.9999998629006982.74198604401483e-071.37099302200741e-07
1930.9999997735058784.52988244756592e-072.26494122378296e-07
1940.9999996620633246.75873351772038e-073.37936675886019e-07
1950.9999995533313168.93337368781268e-074.46668684390634e-07
1960.9999992871724181.42565516377909e-067.12827581889546e-07
1970.9999993415059271.31698814656531e-066.58494073282657e-07
1980.999999098263491.80347301902251e-069.01736509511255e-07
1990.9999986651015862.66979682902103e-061.33489841451052e-06
2000.9999986634664052.67306719052282e-061.33653359526141e-06
2010.9999978286257114.34274857791282e-062.17137428895641e-06
2020.9999991155052631.76898947411192e-068.84494737055962e-07
2030.9999992111072981.57778540315812e-067.8889270157906e-07
2040.9999989751205872.04975882510026e-061.02487941255013e-06
2050.9999985167488962.96650220854648e-061.48325110427324e-06
2060.9999989067877952.18642441015199e-061.09321220507599e-06
2070.9999985293567142.94128657168701e-061.4706432858435e-06
2080.999997703386544.59322692039994e-062.29661346019997e-06
2090.9999965836970366.83260592828421e-063.41630296414211e-06
2100.9999971014817665.7970364678063e-062.89851823390315e-06
2110.999995278808499.44238301858473e-064.72119150929236e-06
2120.9999923282433161.5343513369068e-057.67175668453399e-06
2130.9999876164192962.47671614077239e-051.2383580703862e-05
2140.9999854266657912.91466684173216e-051.45733342086608e-05
2150.9999767360596234.65278807544994e-052.32639403772497e-05
2160.9999908230272141.83539455719418e-059.1769727859709e-06
2170.9999892821645762.14356708475768e-051.07178354237884e-05
2180.9999841189678373.17620643264989e-051.58810321632495e-05
2190.9999776139295214.4772140958078e-052.2386070479039e-05
2200.9999699199011666.01601976680069e-053.00800988340034e-05
2210.9999650597203386.98805593244949e-053.49402796622475e-05
2220.999946770541270.0001064589174614635.32294587307316e-05
2230.9999182671856390.0001634656287223858.17328143611925e-05
2240.9998766508197650.0002466983604705330.000123349180235267
2250.9998165683121330.0003668633757337680.000183431687866884
2260.9997637395161920.000472520967615620.00023626048380781
2270.9998728036398580.0002543927202833980.000127196360141699
2280.9998943114677210.0002113770645576080.000105688532278804
2290.999844267736680.000311464526638680.00015573226331934
2300.999943514446180.0001129711076408385.64855538204192e-05
2310.9999235130042650.0001529739914699817.64869957349906e-05
2320.9998795831777680.0002408336444636690.000120416822231835
2330.9998070100125360.0003859799749283060.000192989987464153
2340.9997152992814950.0005694014370102030.000284700718505102
2350.999676583918380.0006468321632399420.000323416081619971
2360.9994948464640420.001010307071916370.000505153535958187
2370.9992192346716550.001561530656689640.00078076532834482
2380.9999427750845640.0001144498308717875.72249154358936e-05
2390.99991889402280.0001622119544012838.11059772006413e-05
2400.9998703024801570.0002593950396865540.000129697519843277
2410.9998962607313680.0002074785372645040.000103739268632252
2420.999851222487510.0002975550249809890.000148777512490495
2430.999753803189890.0004923936202193810.00024619681010969
2440.9996638030451240.0006723939097516830.000336196954875841
2450.9994482942072220.001103411585556780.00055170579277839
2460.9993303360417480.001339327916503870.000669663958251934
2470.9989102984491880.002179403101623550.00108970155081178
2480.998281216437510.003437567124981870.00171878356249093
2490.9976599047724240.004680190455152750.00234009522757638
2500.9970651331665540.005869733666891950.00293486683344598
2510.995901947766650.008196104466697990.004098052233349
2520.99369332384580.01261335230840180.0063066761542009
2530.9903870769979320.01922584600413650.00961292300206825
2540.9912268643485710.01754627130285790.00877313565142893
2550.988039531037110.02392093792578190.0119604689628909
2560.9832594260237050.03348114795259010.016740573976295
2570.9753001486598190.04939970268036270.0246998513401814
2580.9647830719712720.07043385605745660.0352169280287283
2590.95488728694460.09022542611079840.0451127130553992
2600.942992968066640.1140140638667210.0570070319333604
2610.9775865419297780.04482691614044380.0224134580702219
2620.9849172327462860.03016553450742890.0150827672537144
2630.9785332258738970.04293354825220690.0214667741261035
2640.9740257831319620.05194843373607680.0259742168680384
2650.9772265570079790.04554688598404260.0227734429920213
2660.9732393402003540.05352131959929250.0267606597996463
2670.9688120123264980.06237597534700360.0311879876735018
2680.9654887655883390.06902246882332260.0345112344116613
2690.9619637834559290.07607243308814160.0380362165440708
2700.991836313246370.01632737350725880.00816368675362941
2710.9884800626847440.02303987463051110.0115199373152556
2720.98143558985910.03712882028179870.0185644101408994
2730.977386519162530.04522696167493920.0226134808374696
2740.9572736909888140.08545261802237190.0427263090111859
2750.9511952583162180.09760948336756340.0488047416837817
2760.969318913597190.06136217280561850.0306810864028093
2770.9414223246296780.1171553507406430.0585776753703215
2780.8719155913231060.2561688173537870.128084408676894
2790.8137700367515820.3724599264968350.186229963248418






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1540.57037037037037NOK
5% type I error level1700.62962962962963NOK
10% type I error level1890.7NOK

\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 & 154 & 0.57037037037037 & NOK \tabularnewline
5% type I error level & 170 & 0.62962962962963 & NOK \tabularnewline
10% type I error level & 189 & 0.7 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155913&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]154[/C][C]0.57037037037037[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]170[/C][C]0.62962962962963[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]189[/C][C]0.7[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155913&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155913&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 level1540.57037037037037NOK
5% type I error level1700.62962962962963NOK
10% type I error level1890.7NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 4 ; 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')
}