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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, 23 Dec 2011 07:25:40 -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/23/t1324643406we0i63j3j4hz14v.htm/, Retrieved Mon, 29 Apr 2024 18:25:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160348, Retrieved Mon, 29 Apr 2024 18:25:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2008-12-08 19:22:39] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMPD  [(Partial) Autocorrelation Function] [] [2011-12-01 17:46:48] [86f7284edee3dbb8ea5c7e2dec87d892]
- R P     [(Partial) Autocorrelation Function] [] [2011-12-05 14:45:05] [86f7284edee3dbb8ea5c7e2dec87d892]
- RMP       [ARIMA Forecasting] [] [2011-12-05 16:06:32] [86f7284edee3dbb8ea5c7e2dec87d892]
- R P         [ARIMA Forecasting] [] [2011-12-16 07:39:11] [86f7284edee3dbb8ea5c7e2dec87d892]
- RMPD            [Multiple Regression] [] [2011-12-23 12:25:40] [daf26cf00f2f7a7ee0a1368c8ac8117e] [Current]
- R                 [Multiple Regression] [] [2011-12-23 12:45:24] [ad2d4c5ace9fa07b356a7b5098237581]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1418	210907	56	396	81	3	79	30	115	94	112285	24188	146283	144	145
869	120982	56	297	55	4	58	28	109	103	84786	18273	98364	103	101
1530	176508	54	559	50	12	60	38	146	93	83123	14130	86146	98	98
2172	179321	89	967	125	2	108	30	116	103	101193	32287	96933	135	132
901	123185	40	270	40	1	49	22	68	51	38361	8654	79234	61	60
463	52746	25	143	37	3	0	26	101	70	68504	9245	42551	39	38
3201	385534	92	1562	63	0	121	25	96	91	119182	33251	195663	150	144
371	33170	18	109	44	0	1	18	67	22	22807	1271	6853	5	5
1192	101645	63	371	88	0	20	11	44	38	17140	5279	21529	28	28
1583	149061	44	656	66	5	43	26	100	93	116174	27101	95757	84	84
1439	165446	33	511	57	0	69	25	93	60	57635	16373	85584	80	79
1764	237213	84	655	74	0	78	38	140	123	66198	19716	143983	130	127
1495	173326	88	465	49	7	86	44	166	148	71701	17753	75851	82	78
1373	133131	55	525	52	7	44	30	99	90	57793	9028	59238	60	60
2187	258873	60	885	88	3	104	40	139	124	80444	18653	93163	131	131
1491	180083	66	497	36	9	63	34	130	70	53855	8828	96037	84	84
4041	324799	154	1436	108	0	158	47	181	168	97668	29498	151511	140	133
1706	230964	53	612	43	4	102	30	116	115	133824	27563	136368	151	150
2152	236785	119	865	75	3	77	31	116	71	101481	18293	112642	91	91
1036	135473	41	385	32	0	82	23	88	66	99645	22530	94728	138	132
1882	202925	61	567	44	7	115	36	139	134	114789	15977	105499	150	136
1929	215147	58	639	85	0	101	36	135	117	99052	35082	121527	124	124
2242	344297	75	963	86	1	80	30	108	108	67654	16116	127766	119	118
1220	153935	33	398	56	5	50	25	89	84	65553	15849	98958	73	70
1289	132943	40	410	50	7	83	39	156	156	97500	16026	77900	110	107
2515	174724	92	966	135	0	123	34	129	120	69112	26569	85646	123	119
2147	174415	100	801	63	0	73	31	118	114	82753	24785	98579	90	89
2352	225548	112	892	81	5	81	31	118	94	85323	17569	130767	116	112
1638	223632	73	513	52	0	105	33	125	120	72654	23825	131741	113	108
1222	124817	40	469	44	0	47	25	95	81	30727	7869	53907	56	52
1812	221698	45	683	113	0	105	33	126	110	77873	14975	178812	115	112
1677	210767	60	643	39	3	94	35	135	133	117478	37791	146761	119	116
1579	170266	62	535	73	4	44	42	154	122	74007	9605	82036	129	123
1731	260561	75	625	48	1	114	43	165	158	90183	27295	163253	127	125
807	84853	31	264	33	4	38	30	113	109	61542	2746	27032	27	27
2452	294424	77	992	59	2	107	33	127	124	101494	34461	171975	175	162
829	101011	34	238	41	0	30	13	52	39	27570	8098	65990	35	32
1940	215641	46	818	69	0	71	32	121	92	55813	4787	86572	64	64
2662	325107	99	937	64	0	84	36	136	126	79215	24919	159676	96	92
186	7176	17	70	1	0	0	0	0	0	1423	603	1929	0	0
1499	167542	66	507	59	2	59	28	108	70	55461	16329	85371	84	83
865	106408	30	260	32	1	33	14	46	37	31081	12558	58391	41	41
1793	96560	76	503	129	0	42	17	54	38	22996	7784	31580	47	47
2527	265769	146	927	37	2	96	32	124	120	83122	28522	136815	126	120
2747	269651	67	1269	31	10	106	30	115	93	70106	22265	120642	105	105
1324	149112	56	537	65	6	56	35	128	95	60578	14459	69107	80	79
2702	175824	107	910	107	0	57	20	80	77	39992	14526	50495	70	65
1383	152871	58	532	74	5	59	28	97	90	79892	22240	108016	73	70
1179	111665	34	345	54	4	39	28	104	80	49810	11802	46341	57	55
2099	116408	61	918	76	1	34	39	59	31	71570	7623	78348	40	39
4308	362301	119	1635	715	2	76	34	125	110	100708	11912	79336	68	67
918	78800	42	330	57	2	20	26	82	66	33032	7935	56968	21	21
1831	183167	66	557	66	0	91	39	149	138	82875	18220	93176	127	127
3373	277965	89	1178	106	8	115	39	149	133	139077	19199	161632	154	152
1713	150629	44	740	54	3	85	33	122	113	71595	19918	87850	116	113
1438	168809	66	452	32	0	76	28	118	100	72260	21884	127969	102	99
496	24188	24	218	20	0	8	4	12	7	5950	2694	15049	7	7
2253	329267	259	764	71	8	79	39	144	140	115762	15808	155135	148	141
744	65029	17	255	21	5	21	18	67	61	32551	3597	25109	21	21
1161	101097	64	454	70	3	30	14	52	41	31701	5296	45824	35	35
2352	218946	41	866	112	1	76	29	108	96	80670	25239	102996	112	109
2144	244052	68	574	66	5	101	44	166	164	143558	29801	160604	137	133
4691	341570	168	1276	190	1	94	21	80	78	117105	18450	158051	135	123
1112	103597	43	379	66	1	27	16	60	49	23789	7132	44547	26	26
2694	233328	132	825	165	5	92	28	107	102	120733	34861	162647	230	230
1973	256462	105	798	56	0	123	35	127	124	105195	35940	174141	181	166
1769	206161	71	663	61	12	75	28	107	99	73107	16688	60622	71	68
3148	311473	112	1069	53	8	128	38	146	129	132068	24683	179566	147	147
2474	235800	94	921	127	8	105	23	84	62	149193	46230	184301	190	179
2084	177939	82	858	63	8	55	36	141	73	46821	10387	75661	64	61
1954	207176	70	711	38	8	56	32	123	114	87011	21436	96144	105	101
1226	196553	57	503	50	2	41	29	111	99	95260	30546	129847	107	108
1389	174184	53	382	52	0	72	25	98	70	55183	19746	117286	94	90
1496	143246	103	464	42	5	67	27	105	104	106671	15977	71180	116	114
2269	187559	121	717	76	8	75	36	135	116	73511	22583	109377	106	103
1833	187681	62	690	67	2	114	28	107	91	92945	17274	85298	143	142
1268	119016	52	462	50	5	118	23	85	74	78664	16469	73631	81	79
1943	182192	52	657	53	12	77	40	155	138	70054	14251	86767	89	88
893	73566	32	385	39	6	22	23	88	67	22618	3007	23824	26	25
1762	194979	62	577	50	7	66	40	155	151	74011	16851	93487	84	83
1403	167488	45	619	77	2	69	28	104	72	83737	21113	82981	113	113
1425	143756	46	479	57	0	105	34	132	120	69094	17401	73815	120	118
1857	275541	63	817	73	4	116	33	127	115	93133	23958	94552	110	110
1840	243199	75	752	34	3	88	28	108	105	95536	23567	132190	134	129
1502	182999	88	430	39	6	73	34	129	104	225920	13065	128754	54	51
1441	135649	46	451	46	2	99	30	116	108	62133	15358	66363	96	93
1420	152299	53	537	63	0	62	33	122	98	61370	14587	67808	78	76
1416	120221	37	519	35	1	53	22	85	69	43836	12770	61724	51	49
2970	346485	90	1000	106	0	118	38	147	111	106117	24021	131722	121	118
1317	145790	63	637	43	5	30	26	99	99	38692	9648	68580	38	38
1644	193339	78	465	47	2	100	35	87	71	84651	20537	106175	145	141
870	80953	25	437	31	0	49	8	28	27	56622	7905	55792	59	58
1654	122774	45	711	162	0	24	24	90	69	15986	4527	25157	27	27
1054	130585	46	299	57	5	67	29	109	107	95364	30495	76669	91	91
937	112611	41	248	36	0	46	20	78	73	26706	7117	57283	48	48
3004	286468	144	1162	263	1	57	29	111	107	89691	17719	105805	68	63
2008	241066	82	714	78	0	75	45	158	93	67267	27056	129484	58	56
2547	148446	91	905	63	1	135	37	141	129	126846	33473	72413	150	144
1885	204713	71	649	54	1	68	33	122	69	41140	9758	87831	74	73
1626	182079	63	512	63	2	124	33	124	118	102860	21115	96971	181	168
1468	140344	53	472	77	6	33	25	93	73	51715	7236	71299	65	64
2445	220516	62	905	79	1	98	32	124	119	55801	13790	77494	97	97
1964	243060	63	786	110	4	58	29	112	104	111813	32902	120336	121	117
1381	162765	32	489	56	2	68	28	108	107	120293	25131	93913	99	100
1369	182613	39	479	56	3	81	28	99	99	138599	30910	136048	152	149
1659	232138	62	617	43	0	131	31	117	90	161647	35947	181248	188	187
2888	265318	117	925	111	10	110	52	199	197	115929	29848	146123	138	127
1290	85574	34	351	71	0	37	21	78	36	24266	6943	32036	40	37
2845	310839	92	1144	62	9	130	24	91	85	162901	42705	186646	254	245
1982	225060	93	669	56	7	93	41	158	139	109825	31808	102255	87	87
1904	232317	54	707	74	0	118	33	126	106	129838	26675	168237	178	177
1391	144966	144	458	60	0	39	32	122	50	37510	8435	64219	51	49
602	43287	14	214	43	4	13	19	71	64	43750	7409	19630	49	49
1743	155754	61	599	68	4	74	20	75	31	40652	14993	76825	73	73
1559	164709	109	572	53	0	81	31	115	63	87771	36867	115338	176	177
2014	201940	38	897	87	0	109	31	119	92	85872	33835	109427	94	94
2143	235454	73	819	46	0	151	32	124	106	89275	24164	118168	120	117
2146	220801	75	720	105	1	51	18	72	63	44418	12607	84845	66	60
874	99466	50	273	32	0	28	23	91	69	192565	22609	153197	56	55
1590	92661	61	508	133	1	40	17	45	41	35232	5892	29877	39	39
1590	133328	55	506	79	0	56	20	78	56	40909	17014	63506	66	64
1210	61361	77	451	51	0	27	12	39	25	13294	5394	22445	27	26
2072	125930	75	699	207	4	37	17	68	65	32387	9178	47695	65	64
1281	100750	72	407	67	0	83	30	119	93	140867	6440	68370	58	58
1401	224549	50	465	47	4	54	31	117	114	120662	21916	146304	98	95
834	82316	32	245	34	4	27	10	39	38	21233	4011	38233	25	25
1105	102010	53	370	66	3	28	13	50	44	44332	5818	42071	26	26
1272	101523	42	316	76	0	59	22	88	87	61056	18647	50517	77	76
1944	243511	71	603	65	0	133	42	155	110	101338	20556	103950	130	129
391	22938	10	154	9	0	12	1	0	0	1168	238	5841	11	11
761	41566	35	229	42	5	0	9	36	27	13497	70	2341	2	2
1605	152474	65	577	45	0	106	32	123	83	65567	22392	84396	101	101
530	61857	25	192	25	4	23	11	32	30	25162	3913	24610	31	28
1988	99923	66	617	115	0	44	25	99	80	32334	12237	35753	36	36
1386	132487	41	411	97	0	71	36	136	98	40735	8388	55515	120	89
2395	317394	86	975	53	1	116	31	117	82	91413	22120	209056	195	193
387	21054	16	146	2	0	4	0	0	0	855	338	6622	4	4
1742	209641	42	705	52	5	62	24	88	60	97068	11727	115814	89	84
620	22648	19	184	44	0	12	13	39	28	44339	3704	11609	24	23
449	31414	19	200	22	0	18	8	25	9	14116	3988	13155	39	39
800	46698	45	274	35	0	14	13	52	33	10288	3030	18274	14	14
1684	131698	65	502	74	0	60	19	75	59	65622	13520	72875	78	78
1050	91735	35	382	103	0	7	18	71	49	16563	1421	10112	15	14
2699	244749	95	964	144	2	98	33	124	115	76643	20923	142775	106	101
1606	184510	49	537	60	7	64	40	151	140	110681	20237	68847	83	82
1502	79863	37	438	134	1	29	22	71	49	29011	3219	17659	24	24
1204	128423	64	369	89	8	32	38	145	120	92696	3769	20112	37	36
1138	97839	38	417	42	2	25	24	87	66	94785	12252	61023	77	75
568	38214	34	276	52	0	16	8	27	21	8773	1888	13983	16	16
1459	151101	32	514	98	2	48	35	131	124	83209	14497	65176	56	55
2158	272458	65	822	99	0	100	43	162	152	93815	28864	132432	132	131
1111	172494	52	389	52	0	46	43	165	139	86687	21721	112494	144	131
1421	108043	62	466	29	1	45	14	54	38	34553	4821	45109	40	39
2833	328107	65	1255	125	3	129	41	159	144	105547	33644	170875	153	144
1955	250579	83	694	106	0	130	38	147	120	103487	15923	180759	143	139
2922	351067	95	1024	95	3	136	45	170	160	213688	42935	214921	220	211
1002	158015	29	400	40	0	59	31	119	114	71220	18864	100226	79	78
1060	98866	18	397	140	0	25	13	49	39	23517	4977	32043	50	50
956	85439	33	350	43	0	32	28	104	78	56926	7785	54454	39	39
2186	229242	247	719	128	4	63	31	120	119	91721	17939	78876	95	90
3604	351619	139	1277	142	4	95	40	150	141	115168	23436	170745	169	166
1035	84207	29	356	73	11	14	30	112	101	111194	325	6940	12	12
1417	120445	118	457	72	0	36	16	59	56	51009	13539	49025	63	57
3261	324598	110	1402	128	0	113	37	136	133	135777	34538	122037	134	133
1587	131069	67	600	61	4	47	30	107	83	51513	12198	53782	69	69
1424	204271	42	480	73	0	92	35	130	116	74163	26924	127748	119	119
1701	165543	65	595	148	1	70	32	115	90	51633	12716	86839	119	119
1249	141722	94	436	64	0	19	27	107	36	75345	8172	44830	75	65
946	116048	64	230	45	0	50	20	75	50	33416	10855	77395	63	61
1926	250047	81	651	58	0	41	18	71	61	83305	11932	89324	55	49
3352	299775	95	1367	97	9	91	31	120	97	98952	14300	103300	103	101
1641	195838	67	564	50	1	111	31	116	98	102372	25515	112283	197	196
2035	173260	63	716	37	3	41	21	79	78	37238	2805	10901	16	15
2312	254488	83	747	50	10	120	39	150	117	103772	29402	120691	140	136
1369	104389	45	467	105	5	135	41	156	148	123969	16440	58106	89	89
1577	136084	30	671	69	0	27	13	51	41	27142	11221	57140	40	40
2201	199476	70	861	46	2	87	32	118	105	135400	28732	122422	125	123
961	92499	32	319	57	0	25	18	71	55	21399	5250	25899	21	21
1900	224330	83	612	52	1	131	39	144	132	130115	28608	139296	167	163
1254	135781	31	433	98	2	45	14	47	44	24874	8092	52678	32	29
1335	74408	67	434	61	4	29	7	28	21	34988	4473	23853	36	35
1597	81240	66	503	89	0	58	17	68	50	45549	1572	17306	13	13
207	14688	10	85	0	0	4	0	0	0	6023	2065	7953	5	5
1645	181633	70	564	48	2	47	30	110	73	64466	14817	89455	96	96
2429	271856	103	824	91	1	109	37	147	86	54990	16714	147866	151	151
151	7199	5	74	0	0	7	0	0	0	1644	556	4245	6	6
474	46660	20	259	7	0	12	5	15	13	6179	2089	21509	13	13
141	17547	5	69	3	0	0	1	4	4	3926	2658	7670	3	3
1639	133368	36	535	54	1	37	16	64	57	32755	10695	66675	57	56
872	95227	34	239	70	0	37	32	111	48	34777	1669	14336	23	23
1318	152601	48	438	36	2	46	24	85	46	73224	16267	53608	61	57
1018	98146	40	459	37	0	15	17	68	48	27114	7768	30059	21	14
1383	79619	43	426	123	3	42	11	40	32	20760	7252	29668	43	43
1314	59194	31	288	247	6	7	24	80	68	37636	6387	22097	20	20
1335	139942	42	498	46	0	54	22	88	87	65461	18715	96841	82	72
1403	118612	46	454	72	2	54	12	48	43	30080	7936	41907	90	87
910	72880	33	376	41	0	14	19	76	67	24094	8643	27080	25	21

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160348&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160348&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160348&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 time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






Multiple Linear Regression - Estimated Regression Equation
time_in_rfc[t] = -7939.46567245173 + 12.1104834900291pageviews[t] + 137.626173048037logins[t] + 102.36393085263compendium_views_info[t] + 16.392625052739compendium_views_pr[t] + 36.1220890032628shared_compendiums[t] -6.16309612954041blogged_computations[t] -1191.39119203464compendiums_reviewed[t] + 514.862280288374feedback_messages_p1[t] + 126.734887887954feedback_messages_p120[t] -0.117178054693074totsize[t] -0.741453487536829totrevisions[t] + 0.851540731668338totseconds[t] -3.86199005445029tothyperlinks[t] + 38.2951277357944`totblogs `[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
time_in_rfc[t] =  -7939.46567245173 +  12.1104834900291pageviews[t] +  137.626173048037logins[t] +  102.36393085263compendium_views_info[t] +  16.392625052739compendium_views_pr[t] +  36.1220890032628shared_compendiums[t] -6.16309612954041blogged_computations[t] -1191.39119203464compendiums_reviewed[t] +  514.862280288374feedback_messages_p1[t] +  126.734887887954feedback_messages_p120[t] -0.117178054693074totsize[t] -0.741453487536829totrevisions[t] +  0.851540731668338totseconds[t] -3.86199005445029tothyperlinks[t] +  38.2951277357944`totblogs
`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160348&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]time_in_rfc[t] =  -7939.46567245173 +  12.1104834900291pageviews[t] +  137.626173048037logins[t] +  102.36393085263compendium_views_info[t] +  16.392625052739compendium_views_pr[t] +  36.1220890032628shared_compendiums[t] -6.16309612954041blogged_computations[t] -1191.39119203464compendiums_reviewed[t] +  514.862280288374feedback_messages_p1[t] +  126.734887887954feedback_messages_p120[t] -0.117178054693074totsize[t] -0.741453487536829totrevisions[t] +  0.851540731668338totseconds[t] -3.86199005445029tothyperlinks[t] +  38.2951277357944`totblogs
`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160348&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160348&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
time_in_rfc[t] = -7939.46567245173 + 12.1104834900291pageviews[t] + 137.626173048037logins[t] + 102.36393085263compendium_views_info[t] + 16.392625052739compendium_views_pr[t] + 36.1220890032628shared_compendiums[t] -6.16309612954041blogged_computations[t] -1191.39119203464compendiums_reviewed[t] + 514.862280288374feedback_messages_p1[t] + 126.734887887954feedback_messages_p120[t] -0.117178054693074totsize[t] -0.741453487536829totrevisions[t] + 0.851540731668338totseconds[t] -3.86199005445029tothyperlinks[t] + 38.2951277357944`totblogs `[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-7939.465672451735137.227629-1.54550.1239680.061984
pageviews12.11048349002919.8176311.23350.2189630.109482
logins137.62617304803772.5829671.89610.0595280.029764
compendium_views_info102.3639308526321.0427934.86462e-061e-06
compendium_views_pr16.39262505273938.4880840.42590.6706740.335337
shared_compendiums36.1220890032628667.9093310.05410.9569290.478464
blogged_computations-6.16309612954041110.298719-0.05590.9555020.477751
compendiums_reviewed-1191.39119203464807.47576-1.47550.1418190.07091
feedback_messages_p1514.862280288374245.6275482.09610.0374550.018728
feedback_messages_p120126.734887887954127.7646510.99190.3225440.161272
totsize-0.1171780546930740.077622-1.50960.132880.06644
totrevisions-0.7414534875368290.371969-1.99330.047720.02386
totseconds0.8515407316683380.08383710.157100
tothyperlinks-3.86199005445029506.286677-0.00760.9939220.496961
`totblogs `38.2951277357944524.3850610.0730.9418640.470932

\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) & -7939.46567245173 & 5137.227629 & -1.5455 & 0.123968 & 0.061984 \tabularnewline
pageviews & 12.1104834900291 & 9.817631 & 1.2335 & 0.218963 & 0.109482 \tabularnewline
logins & 137.626173048037 & 72.582967 & 1.8961 & 0.059528 & 0.029764 \tabularnewline
compendium_views_info & 102.36393085263 & 21.042793 & 4.8646 & 2e-06 & 1e-06 \tabularnewline
compendium_views_pr & 16.392625052739 & 38.488084 & 0.4259 & 0.670674 & 0.335337 \tabularnewline
shared_compendiums & 36.1220890032628 & 667.909331 & 0.0541 & 0.956929 & 0.478464 \tabularnewline
blogged_computations & -6.16309612954041 & 110.298719 & -0.0559 & 0.955502 & 0.477751 \tabularnewline
compendiums_reviewed & -1191.39119203464 & 807.47576 & -1.4755 & 0.141819 & 0.07091 \tabularnewline
feedback_messages_p1 & 514.862280288374 & 245.627548 & 2.0961 & 0.037455 & 0.018728 \tabularnewline
feedback_messages_p120 & 126.734887887954 & 127.764651 & 0.9919 & 0.322544 & 0.161272 \tabularnewline
totsize & -0.117178054693074 & 0.077622 & -1.5096 & 0.13288 & 0.06644 \tabularnewline
totrevisions & -0.741453487536829 & 0.371969 & -1.9933 & 0.04772 & 0.02386 \tabularnewline
totseconds & 0.851540731668338 & 0.083837 & 10.1571 & 0 & 0 \tabularnewline
tothyperlinks & -3.86199005445029 & 506.286677 & -0.0076 & 0.993922 & 0.496961 \tabularnewline
`totblogs
` & 38.2951277357944 & 524.385061 & 0.073 & 0.941864 & 0.470932 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160348&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]-7939.46567245173[/C][C]5137.227629[/C][C]-1.5455[/C][C]0.123968[/C][C]0.061984[/C][/ROW]
[ROW][C]pageviews[/C][C]12.1104834900291[/C][C]9.817631[/C][C]1.2335[/C][C]0.218963[/C][C]0.109482[/C][/ROW]
[ROW][C]logins[/C][C]137.626173048037[/C][C]72.582967[/C][C]1.8961[/C][C]0.059528[/C][C]0.029764[/C][/ROW]
[ROW][C]compendium_views_info[/C][C]102.36393085263[/C][C]21.042793[/C][C]4.8646[/C][C]2e-06[/C][C]1e-06[/C][/ROW]
[ROW][C]compendium_views_pr[/C][C]16.392625052739[/C][C]38.488084[/C][C]0.4259[/C][C]0.670674[/C][C]0.335337[/C][/ROW]
[ROW][C]shared_compendiums[/C][C]36.1220890032628[/C][C]667.909331[/C][C]0.0541[/C][C]0.956929[/C][C]0.478464[/C][/ROW]
[ROW][C]blogged_computations[/C][C]-6.16309612954041[/C][C]110.298719[/C][C]-0.0559[/C][C]0.955502[/C][C]0.477751[/C][/ROW]
[ROW][C]compendiums_reviewed[/C][C]-1191.39119203464[/C][C]807.47576[/C][C]-1.4755[/C][C]0.141819[/C][C]0.07091[/C][/ROW]
[ROW][C]feedback_messages_p1[/C][C]514.862280288374[/C][C]245.627548[/C][C]2.0961[/C][C]0.037455[/C][C]0.018728[/C][/ROW]
[ROW][C]feedback_messages_p120[/C][C]126.734887887954[/C][C]127.764651[/C][C]0.9919[/C][C]0.322544[/C][C]0.161272[/C][/ROW]
[ROW][C]totsize[/C][C]-0.117178054693074[/C][C]0.077622[/C][C]-1.5096[/C][C]0.13288[/C][C]0.06644[/C][/ROW]
[ROW][C]totrevisions[/C][C]-0.741453487536829[/C][C]0.371969[/C][C]-1.9933[/C][C]0.04772[/C][C]0.02386[/C][/ROW]
[ROW][C]totseconds[/C][C]0.851540731668338[/C][C]0.083837[/C][C]10.1571[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]tothyperlinks[/C][C]-3.86199005445029[/C][C]506.286677[/C][C]-0.0076[/C][C]0.993922[/C][C]0.496961[/C][/ROW]
[ROW][C]`totblogs
`[/C][C]38.2951277357944[/C][C]524.385061[/C][C]0.073[/C][C]0.941864[/C][C]0.470932[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160348&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160348&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)-7939.465672451735137.227629-1.54550.1239680.061984
pageviews12.11048349002919.8176311.23350.2189630.109482
logins137.62617304803772.5829671.89610.0595280.029764
compendium_views_info102.3639308526321.0427934.86462e-061e-06
compendium_views_pr16.39262505273938.4880840.42590.6706740.335337
shared_compendiums36.1220890032628667.9093310.05410.9569290.478464
blogged_computations-6.16309612954041110.298719-0.05590.9555020.477751
compendiums_reviewed-1191.39119203464807.47576-1.47550.1418190.07091
feedback_messages_p1514.862280288374245.6275482.09610.0374550.018728
feedback_messages_p120126.734887887954127.7646510.99190.3225440.161272
totsize-0.1171780546930740.077622-1.50960.132880.06644
totrevisions-0.7414534875368290.371969-1.99330.047720.02386
totseconds0.8515407316683380.08383710.157100
tothyperlinks-3.86199005445029506.286677-0.00760.9939220.496961
`totblogs `38.2951277357944524.3850610.0730.9418640.470932






Multiple Linear Regression - Regression Statistics
Multiple R0.959954795862855
R-squared0.921513210100095
Adjusted R-squared0.915475764723179
F-TEST (value)152.632968510739
F-TEST (DF numerator)14
F-TEST (DF denominator)182
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation23952.7360386102
Sum Squared Residuals104419508599.831

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.959954795862855 \tabularnewline
R-squared & 0.921513210100095 \tabularnewline
Adjusted R-squared & 0.915475764723179 \tabularnewline
F-TEST (value) & 152.632968510739 \tabularnewline
F-TEST (DF numerator) & 14 \tabularnewline
F-TEST (DF denominator) & 182 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 23952.7360386102 \tabularnewline
Sum Squared Residuals & 104419508599.831 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160348&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.959954795862855[/C][/ROW]
[ROW][C]R-squared[/C][C]0.921513210100095[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.915475764723179[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]152.632968510739[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]14[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]182[/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]23952.7360386102[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]104419508599.831[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160348&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160348&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 R0.959954795862855
R-squared0.921513210100095
Adjusted R-squared0.915475764723179
F-TEST (value)152.632968510739
F-TEST (DF numerator)14
F-TEST (DF denominator)182
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation23952.7360386102
Sum Squared Residuals104419508599.831






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1210907192277.15743711718629.8425628831
2120982140944.386752191-19962.3867521911
3176508174323.8536537012184.14634629857
4179321219369.923442063-40048.9234420634
5123185110390.23046870512794.769531295
65274669014.2434479856-16268.2434479856
7385534367772.76378032117761.2362196791
83317029135.38158905954034.61841094046
910164582201.933387134119443.0666128659
10149061168457.827236096-19396.8272360959
11165446149249.02671247616196.9732875238
12237213239754.340215862-2541.34021586187
13173326167900.5400419855425.45995801545
14133131136512.240891213-3381.24089121268
15258873218517.32844460540355.6715553954
16180083177714.2878623382368.71213766161
17324799368725.235609418-43926.2356094176
18230964206605.5649925624358.4350074403
19236785229294.8507325137490.14926748649
20135473132754.9559936942718.04400630601
21202925196380.2131230636544.78687693705
22215147201166.24170712413980.758292876
23344297255594.63811839188702.3618816087
24153935146824.8007928967110.19920710422
25132943156031.445595624-23088.4455956239
26174724225851.69466381-51127.6946638098
27174415211600.05780155-37185.0578015505
28225548256179.963903295-30631.963903295
29223632204615.97982251719016.0201774834
30124817128441.602215131-3624.60221513064
31221698266697.644287462-44999.6442874621
32210767218448.711940669-7681.71194066857
33170266178537.947086049-8271.94708604892
34260561253697.6992678486863.30073215157
358485384528.3762919078324.623708092219
36294424290591.9403487583832.05965124157
3710101195905.20702526515105.79297473494
38215641207980.2188769587660.78112304179
39325107288834.32624492136272.6737550788
4071764863.378229822422312.62177017758
41167542159934.3570247967607.64297520429
4210640883511.082227977222896.9177720229
4396560109987.828085183-13427.8280851832
44265769268386.755656895-2617.75565689489
45269651281542.399247657-11891.3992476569
46149112151696.618367831-2584.61836783132
47175824190943.552782012-15119.5527820117
48152871168795.374623898-15924.3746238981
49111665104208.5592283857456.4407716147
50116408162776.550462953-46368.5504629534
51362301326318.9689454435982.0310545597
5278800102708.364462317-23908.3644623171
53183167189091.329685574-5924.32968557433
54277965326496.844029228-48531.8440292281
55150629188428.267503635-37799.2675036351
56168809192626.543132243-23817.5431322434
572418836625.3570739833-12437.3570739833
58329267291227.58748615438039.4125138456
596502966313.3324594178-1284.33245941781
60101097110347.317893369-9250.31789336923
61218946212739.8774298756206.12257012459
62244052243018.490150781033.50984921979
63341570342608.706972928-1038.70697292841
6410359799985.61773805573611.38226194432
65233328270704.831502794-37376.8315027944
66256462266627.295148587-10165.2951485866
67206161159384.02934735346776.9706526467
68311473325832.914016412-14359.9140164121
69235800265964.941139187-30164.9411391868
70177939209681.65566205-31742.6556620503
71207176197600.3430223929575.65697760785
72196553182508.87762639614044.1223736041
73174184167081.4075819427102.5924180579
74143246147564.376563619-4318.37656361919
75187559223292.960384694-35733.9603846937
76187681180976.511144916704.48885508952
77119016131861.596440678-12845.5964406781
78182192198602.647099275-16410.6470992752
797356690071.1134984182-16505.1134984182
80194979194242.091528032736.908471968104
81167488157915.0517884459572.94821155507
82143756153544.594416102-9788.59441610229
83275541203749.46376110471791.5362388959
84243199225639.33926671617559.6607332837
85182999181098.3983723021900.60162769771
86135649140928.119545418-5279.11954541758
87152299150432.6393895731866.36061042668
88120221133643.663846127-13422.6638461266
89346485274241.92677189572243.0732281046
90145790163148.589103788-17358.5891037881
91193339152728.62203219840610.3779678016
928095396289.757888627-15336.757888627
93122774137183.958059838-14409.9580598381
94130585112229.94260506418355.0573949362
95112611102352.01496311710258.9850368828
96286468275961.18443545510506.8155645455
97241066225328.4018217815737.5981782201
98148446200084.601162585-51638.6011625854
99204713189084.29730575915628.7026942414
100182079173256.0402618678822.95973813287
101140344145562.169111981-5218.16911198111
102220516216935.8745200053580.1254799953
103243060211845.80131230831214.1986876922
104162765150311.81145696412453.188543036
105182613175536.1151128417076.8848871594
106232138233633.29130376-1495.29130375953
107265318297844.369864197-32526.3698641966
1088557489481.4730228988-3907.4730228988
109310839302438.4268494468400.57315055378
110225060201675.98905994523384.010940055
111232317248757.477763845-16440.4777638447
112144966153090.772324559-8124.77232455945
1134328753765.7656009764-10478.7656009764
114155754154452.1459819361301.85401806443
115164709181817.662462106-17108.6624621059
116201940211519.63353841-9579.63353840976
117235454227136.2098239048317.79017609614
118220801186865.46631588233935.5336841176
11999466159034.4653869-59568.4653869001
12092661100080.690271505-7419.69027150497
121133328133925.479205641-597.479205641425
1226136187545.5607370334-26184.5607370334
123125930157546.27470887-31616.2747088698
124100750135980.737380889-35230.7373808892
125224549199298.27404567925250.7259543208
1268231673116.72857971619199.27142028393
12710201094672.45437554237337.54562445767
128101523101247.830389524275.169610476321
129243511196891.87694429846619.1230557024
1302293817857.50976407495080.49023592515
1314156642067.2016975481-501.201697548127
132152474166373.20613255-13899.2061325501
1336185745217.726474360616639.2735256394
13499923140140.128081486-40217.1280814864
135132487136489.175513177-4002.17551317701
136317394324138.880596937-6744.88059693743
1372105419328.41373731251725.58626268748
138209641197497.51485495712143.4851450433
1392264832538.0683462696-9890.06834626957
1403141433250.4771220875-1836.47712208752
1414669864535.2662343609-17837.2662343609
142131698144113.754408298-12415.7544082976
1439173577756.524582794413978.4754172056
144244749277973.225293188-33224.2252931879
145184510155368.00063433929141.9993656608
1467986388864.2416501389-9001.24165013889
147128423104068.41817529724354.5818247027
14897839113275.929055623-15436.9290556235
1493821449686.5723861978-11472.5723861978
150151101146485.9729967754615.02700322453
151272458248615.69004068823842.309959312
152172494178389.763076323-5895.76307632338
153108043113804.907606837-5761.90760683666
154328107329527.644235234-1420.64423523393
155250579279518.402200702-28939.4022007019
156351067333732.33945352717334.6605464728
157158015153903.5585720844111.44142791553
1589886687398.801689021111467.1983109789
15985439109856.902912334-24417.9029123337
160229242214110.82663415215131.1733658478
161351619355114.326090212-3495.32609021185
1628420774310.80904463549896.19095536456
163120445119282.0880995091162.9119004911
164324598301380.10963391723217.8903660828
165131069145734.487980901-14665.4879809006
166204271189012.15639544415258.8436045563
167165543179600.216651177-14057.2166511773
168141722118657.41589009223064.5841099082
169116048113455.5286396122592.47136038762
170250047175829.59371016774217.4062898327
171299775293395.2201585356379.77984146522
172195838185715.2579943110122.7420056903
173173260128022.85159811245237.1484018876
174254488227463.89358837927024.1064116212
175104389139763.211488396-35374.2114883963
176136084139438.524890337-3354.52489033686
177199476224016.915988544-24540.9159885442
1789249979994.767242289712504.2327577103
179224330221381.4883580322948.51164196776
180135781107263.75083904428517.2491609562
1817440885675.2278908735-11267.2278908735
18281240102850.060941254-21610.0609412539
183146889327.552130605135360.44786939487
184181633171003.59590196810629.4040980323
185271856275635.879317991-3779.87931799079
18671995325.637781004961873.36221899504
1874666047010.4889140233-350.488914023342
188175477147.322361885210399.6776381148
189133368140367.826537575-6999.82653757496
1909522765480.127087795429746.8729122046
191152601107797.36257592544803.6374240751
1929814695348.15418656942797.84581343061
1937961990679.3048415578-11060.3048415578
1945919477516.4501332279-18322.4501332279
195139942158887.757218153-18945.7572181529
196118612107902.29623865810709.7037613415
1977288086217.4288398622-13337.4288398622

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 210907 & 192277.157437117 & 18629.8425628831 \tabularnewline
2 & 120982 & 140944.386752191 & -19962.3867521911 \tabularnewline
3 & 176508 & 174323.853653701 & 2184.14634629857 \tabularnewline
4 & 179321 & 219369.923442063 & -40048.9234420634 \tabularnewline
5 & 123185 & 110390.230468705 & 12794.769531295 \tabularnewline
6 & 52746 & 69014.2434479856 & -16268.2434479856 \tabularnewline
7 & 385534 & 367772.763780321 & 17761.2362196791 \tabularnewline
8 & 33170 & 29135.3815890595 & 4034.61841094046 \tabularnewline
9 & 101645 & 82201.9333871341 & 19443.0666128659 \tabularnewline
10 & 149061 & 168457.827236096 & -19396.8272360959 \tabularnewline
11 & 165446 & 149249.026712476 & 16196.9732875238 \tabularnewline
12 & 237213 & 239754.340215862 & -2541.34021586187 \tabularnewline
13 & 173326 & 167900.540041985 & 5425.45995801545 \tabularnewline
14 & 133131 & 136512.240891213 & -3381.24089121268 \tabularnewline
15 & 258873 & 218517.328444605 & 40355.6715553954 \tabularnewline
16 & 180083 & 177714.287862338 & 2368.71213766161 \tabularnewline
17 & 324799 & 368725.235609418 & -43926.2356094176 \tabularnewline
18 & 230964 & 206605.56499256 & 24358.4350074403 \tabularnewline
19 & 236785 & 229294.850732513 & 7490.14926748649 \tabularnewline
20 & 135473 & 132754.955993694 & 2718.04400630601 \tabularnewline
21 & 202925 & 196380.213123063 & 6544.78687693705 \tabularnewline
22 & 215147 & 201166.241707124 & 13980.758292876 \tabularnewline
23 & 344297 & 255594.638118391 & 88702.3618816087 \tabularnewline
24 & 153935 & 146824.800792896 & 7110.19920710422 \tabularnewline
25 & 132943 & 156031.445595624 & -23088.4455956239 \tabularnewline
26 & 174724 & 225851.69466381 & -51127.6946638098 \tabularnewline
27 & 174415 & 211600.05780155 & -37185.0578015505 \tabularnewline
28 & 225548 & 256179.963903295 & -30631.963903295 \tabularnewline
29 & 223632 & 204615.979822517 & 19016.0201774834 \tabularnewline
30 & 124817 & 128441.602215131 & -3624.60221513064 \tabularnewline
31 & 221698 & 266697.644287462 & -44999.6442874621 \tabularnewline
32 & 210767 & 218448.711940669 & -7681.71194066857 \tabularnewline
33 & 170266 & 178537.947086049 & -8271.94708604892 \tabularnewline
34 & 260561 & 253697.699267848 & 6863.30073215157 \tabularnewline
35 & 84853 & 84528.3762919078 & 324.623708092219 \tabularnewline
36 & 294424 & 290591.940348758 & 3832.05965124157 \tabularnewline
37 & 101011 & 95905.2070252651 & 5105.79297473494 \tabularnewline
38 & 215641 & 207980.218876958 & 7660.78112304179 \tabularnewline
39 & 325107 & 288834.326244921 & 36272.6737550788 \tabularnewline
40 & 7176 & 4863.37822982242 & 2312.62177017758 \tabularnewline
41 & 167542 & 159934.357024796 & 7607.64297520429 \tabularnewline
42 & 106408 & 83511.0822279772 & 22896.9177720229 \tabularnewline
43 & 96560 & 109987.828085183 & -13427.8280851832 \tabularnewline
44 & 265769 & 268386.755656895 & -2617.75565689489 \tabularnewline
45 & 269651 & 281542.399247657 & -11891.3992476569 \tabularnewline
46 & 149112 & 151696.618367831 & -2584.61836783132 \tabularnewline
47 & 175824 & 190943.552782012 & -15119.5527820117 \tabularnewline
48 & 152871 & 168795.374623898 & -15924.3746238981 \tabularnewline
49 & 111665 & 104208.559228385 & 7456.4407716147 \tabularnewline
50 & 116408 & 162776.550462953 & -46368.5504629534 \tabularnewline
51 & 362301 & 326318.96894544 & 35982.0310545597 \tabularnewline
52 & 78800 & 102708.364462317 & -23908.3644623171 \tabularnewline
53 & 183167 & 189091.329685574 & -5924.32968557433 \tabularnewline
54 & 277965 & 326496.844029228 & -48531.8440292281 \tabularnewline
55 & 150629 & 188428.267503635 & -37799.2675036351 \tabularnewline
56 & 168809 & 192626.543132243 & -23817.5431322434 \tabularnewline
57 & 24188 & 36625.3570739833 & -12437.3570739833 \tabularnewline
58 & 329267 & 291227.587486154 & 38039.4125138456 \tabularnewline
59 & 65029 & 66313.3324594178 & -1284.33245941781 \tabularnewline
60 & 101097 & 110347.317893369 & -9250.31789336923 \tabularnewline
61 & 218946 & 212739.877429875 & 6206.12257012459 \tabularnewline
62 & 244052 & 243018.49015078 & 1033.50984921979 \tabularnewline
63 & 341570 & 342608.706972928 & -1038.70697292841 \tabularnewline
64 & 103597 & 99985.6177380557 & 3611.38226194432 \tabularnewline
65 & 233328 & 270704.831502794 & -37376.8315027944 \tabularnewline
66 & 256462 & 266627.295148587 & -10165.2951485866 \tabularnewline
67 & 206161 & 159384.029347353 & 46776.9706526467 \tabularnewline
68 & 311473 & 325832.914016412 & -14359.9140164121 \tabularnewline
69 & 235800 & 265964.941139187 & -30164.9411391868 \tabularnewline
70 & 177939 & 209681.65566205 & -31742.6556620503 \tabularnewline
71 & 207176 & 197600.343022392 & 9575.65697760785 \tabularnewline
72 & 196553 & 182508.877626396 & 14044.1223736041 \tabularnewline
73 & 174184 & 167081.407581942 & 7102.5924180579 \tabularnewline
74 & 143246 & 147564.376563619 & -4318.37656361919 \tabularnewline
75 & 187559 & 223292.960384694 & -35733.9603846937 \tabularnewline
76 & 187681 & 180976.51114491 & 6704.48885508952 \tabularnewline
77 & 119016 & 131861.596440678 & -12845.5964406781 \tabularnewline
78 & 182192 & 198602.647099275 & -16410.6470992752 \tabularnewline
79 & 73566 & 90071.1134984182 & -16505.1134984182 \tabularnewline
80 & 194979 & 194242.091528032 & 736.908471968104 \tabularnewline
81 & 167488 & 157915.051788445 & 9572.94821155507 \tabularnewline
82 & 143756 & 153544.594416102 & -9788.59441610229 \tabularnewline
83 & 275541 & 203749.463761104 & 71791.5362388959 \tabularnewline
84 & 243199 & 225639.339266716 & 17559.6607332837 \tabularnewline
85 & 182999 & 181098.398372302 & 1900.60162769771 \tabularnewline
86 & 135649 & 140928.119545418 & -5279.11954541758 \tabularnewline
87 & 152299 & 150432.639389573 & 1866.36061042668 \tabularnewline
88 & 120221 & 133643.663846127 & -13422.6638461266 \tabularnewline
89 & 346485 & 274241.926771895 & 72243.0732281046 \tabularnewline
90 & 145790 & 163148.589103788 & -17358.5891037881 \tabularnewline
91 & 193339 & 152728.622032198 & 40610.3779678016 \tabularnewline
92 & 80953 & 96289.757888627 & -15336.757888627 \tabularnewline
93 & 122774 & 137183.958059838 & -14409.9580598381 \tabularnewline
94 & 130585 & 112229.942605064 & 18355.0573949362 \tabularnewline
95 & 112611 & 102352.014963117 & 10258.9850368828 \tabularnewline
96 & 286468 & 275961.184435455 & 10506.8155645455 \tabularnewline
97 & 241066 & 225328.40182178 & 15737.5981782201 \tabularnewline
98 & 148446 & 200084.601162585 & -51638.6011625854 \tabularnewline
99 & 204713 & 189084.297305759 & 15628.7026942414 \tabularnewline
100 & 182079 & 173256.040261867 & 8822.95973813287 \tabularnewline
101 & 140344 & 145562.169111981 & -5218.16911198111 \tabularnewline
102 & 220516 & 216935.874520005 & 3580.1254799953 \tabularnewline
103 & 243060 & 211845.801312308 & 31214.1986876922 \tabularnewline
104 & 162765 & 150311.811456964 & 12453.188543036 \tabularnewline
105 & 182613 & 175536.115112841 & 7076.8848871594 \tabularnewline
106 & 232138 & 233633.29130376 & -1495.29130375953 \tabularnewline
107 & 265318 & 297844.369864197 & -32526.3698641966 \tabularnewline
108 & 85574 & 89481.4730228988 & -3907.4730228988 \tabularnewline
109 & 310839 & 302438.426849446 & 8400.57315055378 \tabularnewline
110 & 225060 & 201675.989059945 & 23384.010940055 \tabularnewline
111 & 232317 & 248757.477763845 & -16440.4777638447 \tabularnewline
112 & 144966 & 153090.772324559 & -8124.77232455945 \tabularnewline
113 & 43287 & 53765.7656009764 & -10478.7656009764 \tabularnewline
114 & 155754 & 154452.145981936 & 1301.85401806443 \tabularnewline
115 & 164709 & 181817.662462106 & -17108.6624621059 \tabularnewline
116 & 201940 & 211519.63353841 & -9579.63353840976 \tabularnewline
117 & 235454 & 227136.209823904 & 8317.79017609614 \tabularnewline
118 & 220801 & 186865.466315882 & 33935.5336841176 \tabularnewline
119 & 99466 & 159034.4653869 & -59568.4653869001 \tabularnewline
120 & 92661 & 100080.690271505 & -7419.69027150497 \tabularnewline
121 & 133328 & 133925.479205641 & -597.479205641425 \tabularnewline
122 & 61361 & 87545.5607370334 & -26184.5607370334 \tabularnewline
123 & 125930 & 157546.27470887 & -31616.2747088698 \tabularnewline
124 & 100750 & 135980.737380889 & -35230.7373808892 \tabularnewline
125 & 224549 & 199298.274045679 & 25250.7259543208 \tabularnewline
126 & 82316 & 73116.7285797161 & 9199.27142028393 \tabularnewline
127 & 102010 & 94672.4543755423 & 7337.54562445767 \tabularnewline
128 & 101523 & 101247.830389524 & 275.169610476321 \tabularnewline
129 & 243511 & 196891.876944298 & 46619.1230557024 \tabularnewline
130 & 22938 & 17857.5097640749 & 5080.49023592515 \tabularnewline
131 & 41566 & 42067.2016975481 & -501.201697548127 \tabularnewline
132 & 152474 & 166373.20613255 & -13899.2061325501 \tabularnewline
133 & 61857 & 45217.7264743606 & 16639.2735256394 \tabularnewline
134 & 99923 & 140140.128081486 & -40217.1280814864 \tabularnewline
135 & 132487 & 136489.175513177 & -4002.17551317701 \tabularnewline
136 & 317394 & 324138.880596937 & -6744.88059693743 \tabularnewline
137 & 21054 & 19328.4137373125 & 1725.58626268748 \tabularnewline
138 & 209641 & 197497.514854957 & 12143.4851450433 \tabularnewline
139 & 22648 & 32538.0683462696 & -9890.06834626957 \tabularnewline
140 & 31414 & 33250.4771220875 & -1836.47712208752 \tabularnewline
141 & 46698 & 64535.2662343609 & -17837.2662343609 \tabularnewline
142 & 131698 & 144113.754408298 & -12415.7544082976 \tabularnewline
143 & 91735 & 77756.5245827944 & 13978.4754172056 \tabularnewline
144 & 244749 & 277973.225293188 & -33224.2252931879 \tabularnewline
145 & 184510 & 155368.000634339 & 29141.9993656608 \tabularnewline
146 & 79863 & 88864.2416501389 & -9001.24165013889 \tabularnewline
147 & 128423 & 104068.418175297 & 24354.5818247027 \tabularnewline
148 & 97839 & 113275.929055623 & -15436.9290556235 \tabularnewline
149 & 38214 & 49686.5723861978 & -11472.5723861978 \tabularnewline
150 & 151101 & 146485.972996775 & 4615.02700322453 \tabularnewline
151 & 272458 & 248615.690040688 & 23842.309959312 \tabularnewline
152 & 172494 & 178389.763076323 & -5895.76307632338 \tabularnewline
153 & 108043 & 113804.907606837 & -5761.90760683666 \tabularnewline
154 & 328107 & 329527.644235234 & -1420.64423523393 \tabularnewline
155 & 250579 & 279518.402200702 & -28939.4022007019 \tabularnewline
156 & 351067 & 333732.339453527 & 17334.6605464728 \tabularnewline
157 & 158015 & 153903.558572084 & 4111.44142791553 \tabularnewline
158 & 98866 & 87398.8016890211 & 11467.1983109789 \tabularnewline
159 & 85439 & 109856.902912334 & -24417.9029123337 \tabularnewline
160 & 229242 & 214110.826634152 & 15131.1733658478 \tabularnewline
161 & 351619 & 355114.326090212 & -3495.32609021185 \tabularnewline
162 & 84207 & 74310.8090446354 & 9896.19095536456 \tabularnewline
163 & 120445 & 119282.088099509 & 1162.9119004911 \tabularnewline
164 & 324598 & 301380.109633917 & 23217.8903660828 \tabularnewline
165 & 131069 & 145734.487980901 & -14665.4879809006 \tabularnewline
166 & 204271 & 189012.156395444 & 15258.8436045563 \tabularnewline
167 & 165543 & 179600.216651177 & -14057.2166511773 \tabularnewline
168 & 141722 & 118657.415890092 & 23064.5841099082 \tabularnewline
169 & 116048 & 113455.528639612 & 2592.47136038762 \tabularnewline
170 & 250047 & 175829.593710167 & 74217.4062898327 \tabularnewline
171 & 299775 & 293395.220158535 & 6379.77984146522 \tabularnewline
172 & 195838 & 185715.25799431 & 10122.7420056903 \tabularnewline
173 & 173260 & 128022.851598112 & 45237.1484018876 \tabularnewline
174 & 254488 & 227463.893588379 & 27024.1064116212 \tabularnewline
175 & 104389 & 139763.211488396 & -35374.2114883963 \tabularnewline
176 & 136084 & 139438.524890337 & -3354.52489033686 \tabularnewline
177 & 199476 & 224016.915988544 & -24540.9159885442 \tabularnewline
178 & 92499 & 79994.7672422897 & 12504.2327577103 \tabularnewline
179 & 224330 & 221381.488358032 & 2948.51164196776 \tabularnewline
180 & 135781 & 107263.750839044 & 28517.2491609562 \tabularnewline
181 & 74408 & 85675.2278908735 & -11267.2278908735 \tabularnewline
182 & 81240 & 102850.060941254 & -21610.0609412539 \tabularnewline
183 & 14688 & 9327.55213060513 & 5360.44786939487 \tabularnewline
184 & 181633 & 171003.595901968 & 10629.4040980323 \tabularnewline
185 & 271856 & 275635.879317991 & -3779.87931799079 \tabularnewline
186 & 7199 & 5325.63778100496 & 1873.36221899504 \tabularnewline
187 & 46660 & 47010.4889140233 & -350.488914023342 \tabularnewline
188 & 17547 & 7147.3223618852 & 10399.6776381148 \tabularnewline
189 & 133368 & 140367.826537575 & -6999.82653757496 \tabularnewline
190 & 95227 & 65480.1270877954 & 29746.8729122046 \tabularnewline
191 & 152601 & 107797.362575925 & 44803.6374240751 \tabularnewline
192 & 98146 & 95348.1541865694 & 2797.84581343061 \tabularnewline
193 & 79619 & 90679.3048415578 & -11060.3048415578 \tabularnewline
194 & 59194 & 77516.4501332279 & -18322.4501332279 \tabularnewline
195 & 139942 & 158887.757218153 & -18945.7572181529 \tabularnewline
196 & 118612 & 107902.296238658 & 10709.7037613415 \tabularnewline
197 & 72880 & 86217.4288398622 & -13337.4288398622 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160348&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]210907[/C][C]192277.157437117[/C][C]18629.8425628831[/C][/ROW]
[ROW][C]2[/C][C]120982[/C][C]140944.386752191[/C][C]-19962.3867521911[/C][/ROW]
[ROW][C]3[/C][C]176508[/C][C]174323.853653701[/C][C]2184.14634629857[/C][/ROW]
[ROW][C]4[/C][C]179321[/C][C]219369.923442063[/C][C]-40048.9234420634[/C][/ROW]
[ROW][C]5[/C][C]123185[/C][C]110390.230468705[/C][C]12794.769531295[/C][/ROW]
[ROW][C]6[/C][C]52746[/C][C]69014.2434479856[/C][C]-16268.2434479856[/C][/ROW]
[ROW][C]7[/C][C]385534[/C][C]367772.763780321[/C][C]17761.2362196791[/C][/ROW]
[ROW][C]8[/C][C]33170[/C][C]29135.3815890595[/C][C]4034.61841094046[/C][/ROW]
[ROW][C]9[/C][C]101645[/C][C]82201.9333871341[/C][C]19443.0666128659[/C][/ROW]
[ROW][C]10[/C][C]149061[/C][C]168457.827236096[/C][C]-19396.8272360959[/C][/ROW]
[ROW][C]11[/C][C]165446[/C][C]149249.026712476[/C][C]16196.9732875238[/C][/ROW]
[ROW][C]12[/C][C]237213[/C][C]239754.340215862[/C][C]-2541.34021586187[/C][/ROW]
[ROW][C]13[/C][C]173326[/C][C]167900.540041985[/C][C]5425.45995801545[/C][/ROW]
[ROW][C]14[/C][C]133131[/C][C]136512.240891213[/C][C]-3381.24089121268[/C][/ROW]
[ROW][C]15[/C][C]258873[/C][C]218517.328444605[/C][C]40355.6715553954[/C][/ROW]
[ROW][C]16[/C][C]180083[/C][C]177714.287862338[/C][C]2368.71213766161[/C][/ROW]
[ROW][C]17[/C][C]324799[/C][C]368725.235609418[/C][C]-43926.2356094176[/C][/ROW]
[ROW][C]18[/C][C]230964[/C][C]206605.56499256[/C][C]24358.4350074403[/C][/ROW]
[ROW][C]19[/C][C]236785[/C][C]229294.850732513[/C][C]7490.14926748649[/C][/ROW]
[ROW][C]20[/C][C]135473[/C][C]132754.955993694[/C][C]2718.04400630601[/C][/ROW]
[ROW][C]21[/C][C]202925[/C][C]196380.213123063[/C][C]6544.78687693705[/C][/ROW]
[ROW][C]22[/C][C]215147[/C][C]201166.241707124[/C][C]13980.758292876[/C][/ROW]
[ROW][C]23[/C][C]344297[/C][C]255594.638118391[/C][C]88702.3618816087[/C][/ROW]
[ROW][C]24[/C][C]153935[/C][C]146824.800792896[/C][C]7110.19920710422[/C][/ROW]
[ROW][C]25[/C][C]132943[/C][C]156031.445595624[/C][C]-23088.4455956239[/C][/ROW]
[ROW][C]26[/C][C]174724[/C][C]225851.69466381[/C][C]-51127.6946638098[/C][/ROW]
[ROW][C]27[/C][C]174415[/C][C]211600.05780155[/C][C]-37185.0578015505[/C][/ROW]
[ROW][C]28[/C][C]225548[/C][C]256179.963903295[/C][C]-30631.963903295[/C][/ROW]
[ROW][C]29[/C][C]223632[/C][C]204615.979822517[/C][C]19016.0201774834[/C][/ROW]
[ROW][C]30[/C][C]124817[/C][C]128441.602215131[/C][C]-3624.60221513064[/C][/ROW]
[ROW][C]31[/C][C]221698[/C][C]266697.644287462[/C][C]-44999.6442874621[/C][/ROW]
[ROW][C]32[/C][C]210767[/C][C]218448.711940669[/C][C]-7681.71194066857[/C][/ROW]
[ROW][C]33[/C][C]170266[/C][C]178537.947086049[/C][C]-8271.94708604892[/C][/ROW]
[ROW][C]34[/C][C]260561[/C][C]253697.699267848[/C][C]6863.30073215157[/C][/ROW]
[ROW][C]35[/C][C]84853[/C][C]84528.3762919078[/C][C]324.623708092219[/C][/ROW]
[ROW][C]36[/C][C]294424[/C][C]290591.940348758[/C][C]3832.05965124157[/C][/ROW]
[ROW][C]37[/C][C]101011[/C][C]95905.2070252651[/C][C]5105.79297473494[/C][/ROW]
[ROW][C]38[/C][C]215641[/C][C]207980.218876958[/C][C]7660.78112304179[/C][/ROW]
[ROW][C]39[/C][C]325107[/C][C]288834.326244921[/C][C]36272.6737550788[/C][/ROW]
[ROW][C]40[/C][C]7176[/C][C]4863.37822982242[/C][C]2312.62177017758[/C][/ROW]
[ROW][C]41[/C][C]167542[/C][C]159934.357024796[/C][C]7607.64297520429[/C][/ROW]
[ROW][C]42[/C][C]106408[/C][C]83511.0822279772[/C][C]22896.9177720229[/C][/ROW]
[ROW][C]43[/C][C]96560[/C][C]109987.828085183[/C][C]-13427.8280851832[/C][/ROW]
[ROW][C]44[/C][C]265769[/C][C]268386.755656895[/C][C]-2617.75565689489[/C][/ROW]
[ROW][C]45[/C][C]269651[/C][C]281542.399247657[/C][C]-11891.3992476569[/C][/ROW]
[ROW][C]46[/C][C]149112[/C][C]151696.618367831[/C][C]-2584.61836783132[/C][/ROW]
[ROW][C]47[/C][C]175824[/C][C]190943.552782012[/C][C]-15119.5527820117[/C][/ROW]
[ROW][C]48[/C][C]152871[/C][C]168795.374623898[/C][C]-15924.3746238981[/C][/ROW]
[ROW][C]49[/C][C]111665[/C][C]104208.559228385[/C][C]7456.4407716147[/C][/ROW]
[ROW][C]50[/C][C]116408[/C][C]162776.550462953[/C][C]-46368.5504629534[/C][/ROW]
[ROW][C]51[/C][C]362301[/C][C]326318.96894544[/C][C]35982.0310545597[/C][/ROW]
[ROW][C]52[/C][C]78800[/C][C]102708.364462317[/C][C]-23908.3644623171[/C][/ROW]
[ROW][C]53[/C][C]183167[/C][C]189091.329685574[/C][C]-5924.32968557433[/C][/ROW]
[ROW][C]54[/C][C]277965[/C][C]326496.844029228[/C][C]-48531.8440292281[/C][/ROW]
[ROW][C]55[/C][C]150629[/C][C]188428.267503635[/C][C]-37799.2675036351[/C][/ROW]
[ROW][C]56[/C][C]168809[/C][C]192626.543132243[/C][C]-23817.5431322434[/C][/ROW]
[ROW][C]57[/C][C]24188[/C][C]36625.3570739833[/C][C]-12437.3570739833[/C][/ROW]
[ROW][C]58[/C][C]329267[/C][C]291227.587486154[/C][C]38039.4125138456[/C][/ROW]
[ROW][C]59[/C][C]65029[/C][C]66313.3324594178[/C][C]-1284.33245941781[/C][/ROW]
[ROW][C]60[/C][C]101097[/C][C]110347.317893369[/C][C]-9250.31789336923[/C][/ROW]
[ROW][C]61[/C][C]218946[/C][C]212739.877429875[/C][C]6206.12257012459[/C][/ROW]
[ROW][C]62[/C][C]244052[/C][C]243018.49015078[/C][C]1033.50984921979[/C][/ROW]
[ROW][C]63[/C][C]341570[/C][C]342608.706972928[/C][C]-1038.70697292841[/C][/ROW]
[ROW][C]64[/C][C]103597[/C][C]99985.6177380557[/C][C]3611.38226194432[/C][/ROW]
[ROW][C]65[/C][C]233328[/C][C]270704.831502794[/C][C]-37376.8315027944[/C][/ROW]
[ROW][C]66[/C][C]256462[/C][C]266627.295148587[/C][C]-10165.2951485866[/C][/ROW]
[ROW][C]67[/C][C]206161[/C][C]159384.029347353[/C][C]46776.9706526467[/C][/ROW]
[ROW][C]68[/C][C]311473[/C][C]325832.914016412[/C][C]-14359.9140164121[/C][/ROW]
[ROW][C]69[/C][C]235800[/C][C]265964.941139187[/C][C]-30164.9411391868[/C][/ROW]
[ROW][C]70[/C][C]177939[/C][C]209681.65566205[/C][C]-31742.6556620503[/C][/ROW]
[ROW][C]71[/C][C]207176[/C][C]197600.343022392[/C][C]9575.65697760785[/C][/ROW]
[ROW][C]72[/C][C]196553[/C][C]182508.877626396[/C][C]14044.1223736041[/C][/ROW]
[ROW][C]73[/C][C]174184[/C][C]167081.407581942[/C][C]7102.5924180579[/C][/ROW]
[ROW][C]74[/C][C]143246[/C][C]147564.376563619[/C][C]-4318.37656361919[/C][/ROW]
[ROW][C]75[/C][C]187559[/C][C]223292.960384694[/C][C]-35733.9603846937[/C][/ROW]
[ROW][C]76[/C][C]187681[/C][C]180976.51114491[/C][C]6704.48885508952[/C][/ROW]
[ROW][C]77[/C][C]119016[/C][C]131861.596440678[/C][C]-12845.5964406781[/C][/ROW]
[ROW][C]78[/C][C]182192[/C][C]198602.647099275[/C][C]-16410.6470992752[/C][/ROW]
[ROW][C]79[/C][C]73566[/C][C]90071.1134984182[/C][C]-16505.1134984182[/C][/ROW]
[ROW][C]80[/C][C]194979[/C][C]194242.091528032[/C][C]736.908471968104[/C][/ROW]
[ROW][C]81[/C][C]167488[/C][C]157915.051788445[/C][C]9572.94821155507[/C][/ROW]
[ROW][C]82[/C][C]143756[/C][C]153544.594416102[/C][C]-9788.59441610229[/C][/ROW]
[ROW][C]83[/C][C]275541[/C][C]203749.463761104[/C][C]71791.5362388959[/C][/ROW]
[ROW][C]84[/C][C]243199[/C][C]225639.339266716[/C][C]17559.6607332837[/C][/ROW]
[ROW][C]85[/C][C]182999[/C][C]181098.398372302[/C][C]1900.60162769771[/C][/ROW]
[ROW][C]86[/C][C]135649[/C][C]140928.119545418[/C][C]-5279.11954541758[/C][/ROW]
[ROW][C]87[/C][C]152299[/C][C]150432.639389573[/C][C]1866.36061042668[/C][/ROW]
[ROW][C]88[/C][C]120221[/C][C]133643.663846127[/C][C]-13422.6638461266[/C][/ROW]
[ROW][C]89[/C][C]346485[/C][C]274241.926771895[/C][C]72243.0732281046[/C][/ROW]
[ROW][C]90[/C][C]145790[/C][C]163148.589103788[/C][C]-17358.5891037881[/C][/ROW]
[ROW][C]91[/C][C]193339[/C][C]152728.622032198[/C][C]40610.3779678016[/C][/ROW]
[ROW][C]92[/C][C]80953[/C][C]96289.757888627[/C][C]-15336.757888627[/C][/ROW]
[ROW][C]93[/C][C]122774[/C][C]137183.958059838[/C][C]-14409.9580598381[/C][/ROW]
[ROW][C]94[/C][C]130585[/C][C]112229.942605064[/C][C]18355.0573949362[/C][/ROW]
[ROW][C]95[/C][C]112611[/C][C]102352.014963117[/C][C]10258.9850368828[/C][/ROW]
[ROW][C]96[/C][C]286468[/C][C]275961.184435455[/C][C]10506.8155645455[/C][/ROW]
[ROW][C]97[/C][C]241066[/C][C]225328.40182178[/C][C]15737.5981782201[/C][/ROW]
[ROW][C]98[/C][C]148446[/C][C]200084.601162585[/C][C]-51638.6011625854[/C][/ROW]
[ROW][C]99[/C][C]204713[/C][C]189084.297305759[/C][C]15628.7026942414[/C][/ROW]
[ROW][C]100[/C][C]182079[/C][C]173256.040261867[/C][C]8822.95973813287[/C][/ROW]
[ROW][C]101[/C][C]140344[/C][C]145562.169111981[/C][C]-5218.16911198111[/C][/ROW]
[ROW][C]102[/C][C]220516[/C][C]216935.874520005[/C][C]3580.1254799953[/C][/ROW]
[ROW][C]103[/C][C]243060[/C][C]211845.801312308[/C][C]31214.1986876922[/C][/ROW]
[ROW][C]104[/C][C]162765[/C][C]150311.811456964[/C][C]12453.188543036[/C][/ROW]
[ROW][C]105[/C][C]182613[/C][C]175536.115112841[/C][C]7076.8848871594[/C][/ROW]
[ROW][C]106[/C][C]232138[/C][C]233633.29130376[/C][C]-1495.29130375953[/C][/ROW]
[ROW][C]107[/C][C]265318[/C][C]297844.369864197[/C][C]-32526.3698641966[/C][/ROW]
[ROW][C]108[/C][C]85574[/C][C]89481.4730228988[/C][C]-3907.4730228988[/C][/ROW]
[ROW][C]109[/C][C]310839[/C][C]302438.426849446[/C][C]8400.57315055378[/C][/ROW]
[ROW][C]110[/C][C]225060[/C][C]201675.989059945[/C][C]23384.010940055[/C][/ROW]
[ROW][C]111[/C][C]232317[/C][C]248757.477763845[/C][C]-16440.4777638447[/C][/ROW]
[ROW][C]112[/C][C]144966[/C][C]153090.772324559[/C][C]-8124.77232455945[/C][/ROW]
[ROW][C]113[/C][C]43287[/C][C]53765.7656009764[/C][C]-10478.7656009764[/C][/ROW]
[ROW][C]114[/C][C]155754[/C][C]154452.145981936[/C][C]1301.85401806443[/C][/ROW]
[ROW][C]115[/C][C]164709[/C][C]181817.662462106[/C][C]-17108.6624621059[/C][/ROW]
[ROW][C]116[/C][C]201940[/C][C]211519.63353841[/C][C]-9579.63353840976[/C][/ROW]
[ROW][C]117[/C][C]235454[/C][C]227136.209823904[/C][C]8317.79017609614[/C][/ROW]
[ROW][C]118[/C][C]220801[/C][C]186865.466315882[/C][C]33935.5336841176[/C][/ROW]
[ROW][C]119[/C][C]99466[/C][C]159034.4653869[/C][C]-59568.4653869001[/C][/ROW]
[ROW][C]120[/C][C]92661[/C][C]100080.690271505[/C][C]-7419.69027150497[/C][/ROW]
[ROW][C]121[/C][C]133328[/C][C]133925.479205641[/C][C]-597.479205641425[/C][/ROW]
[ROW][C]122[/C][C]61361[/C][C]87545.5607370334[/C][C]-26184.5607370334[/C][/ROW]
[ROW][C]123[/C][C]125930[/C][C]157546.27470887[/C][C]-31616.2747088698[/C][/ROW]
[ROW][C]124[/C][C]100750[/C][C]135980.737380889[/C][C]-35230.7373808892[/C][/ROW]
[ROW][C]125[/C][C]224549[/C][C]199298.274045679[/C][C]25250.7259543208[/C][/ROW]
[ROW][C]126[/C][C]82316[/C][C]73116.7285797161[/C][C]9199.27142028393[/C][/ROW]
[ROW][C]127[/C][C]102010[/C][C]94672.4543755423[/C][C]7337.54562445767[/C][/ROW]
[ROW][C]128[/C][C]101523[/C][C]101247.830389524[/C][C]275.169610476321[/C][/ROW]
[ROW][C]129[/C][C]243511[/C][C]196891.876944298[/C][C]46619.1230557024[/C][/ROW]
[ROW][C]130[/C][C]22938[/C][C]17857.5097640749[/C][C]5080.49023592515[/C][/ROW]
[ROW][C]131[/C][C]41566[/C][C]42067.2016975481[/C][C]-501.201697548127[/C][/ROW]
[ROW][C]132[/C][C]152474[/C][C]166373.20613255[/C][C]-13899.2061325501[/C][/ROW]
[ROW][C]133[/C][C]61857[/C][C]45217.7264743606[/C][C]16639.2735256394[/C][/ROW]
[ROW][C]134[/C][C]99923[/C][C]140140.128081486[/C][C]-40217.1280814864[/C][/ROW]
[ROW][C]135[/C][C]132487[/C][C]136489.175513177[/C][C]-4002.17551317701[/C][/ROW]
[ROW][C]136[/C][C]317394[/C][C]324138.880596937[/C][C]-6744.88059693743[/C][/ROW]
[ROW][C]137[/C][C]21054[/C][C]19328.4137373125[/C][C]1725.58626268748[/C][/ROW]
[ROW][C]138[/C][C]209641[/C][C]197497.514854957[/C][C]12143.4851450433[/C][/ROW]
[ROW][C]139[/C][C]22648[/C][C]32538.0683462696[/C][C]-9890.06834626957[/C][/ROW]
[ROW][C]140[/C][C]31414[/C][C]33250.4771220875[/C][C]-1836.47712208752[/C][/ROW]
[ROW][C]141[/C][C]46698[/C][C]64535.2662343609[/C][C]-17837.2662343609[/C][/ROW]
[ROW][C]142[/C][C]131698[/C][C]144113.754408298[/C][C]-12415.7544082976[/C][/ROW]
[ROW][C]143[/C][C]91735[/C][C]77756.5245827944[/C][C]13978.4754172056[/C][/ROW]
[ROW][C]144[/C][C]244749[/C][C]277973.225293188[/C][C]-33224.2252931879[/C][/ROW]
[ROW][C]145[/C][C]184510[/C][C]155368.000634339[/C][C]29141.9993656608[/C][/ROW]
[ROW][C]146[/C][C]79863[/C][C]88864.2416501389[/C][C]-9001.24165013889[/C][/ROW]
[ROW][C]147[/C][C]128423[/C][C]104068.418175297[/C][C]24354.5818247027[/C][/ROW]
[ROW][C]148[/C][C]97839[/C][C]113275.929055623[/C][C]-15436.9290556235[/C][/ROW]
[ROW][C]149[/C][C]38214[/C][C]49686.5723861978[/C][C]-11472.5723861978[/C][/ROW]
[ROW][C]150[/C][C]151101[/C][C]146485.972996775[/C][C]4615.02700322453[/C][/ROW]
[ROW][C]151[/C][C]272458[/C][C]248615.690040688[/C][C]23842.309959312[/C][/ROW]
[ROW][C]152[/C][C]172494[/C][C]178389.763076323[/C][C]-5895.76307632338[/C][/ROW]
[ROW][C]153[/C][C]108043[/C][C]113804.907606837[/C][C]-5761.90760683666[/C][/ROW]
[ROW][C]154[/C][C]328107[/C][C]329527.644235234[/C][C]-1420.64423523393[/C][/ROW]
[ROW][C]155[/C][C]250579[/C][C]279518.402200702[/C][C]-28939.4022007019[/C][/ROW]
[ROW][C]156[/C][C]351067[/C][C]333732.339453527[/C][C]17334.6605464728[/C][/ROW]
[ROW][C]157[/C][C]158015[/C][C]153903.558572084[/C][C]4111.44142791553[/C][/ROW]
[ROW][C]158[/C][C]98866[/C][C]87398.8016890211[/C][C]11467.1983109789[/C][/ROW]
[ROW][C]159[/C][C]85439[/C][C]109856.902912334[/C][C]-24417.9029123337[/C][/ROW]
[ROW][C]160[/C][C]229242[/C][C]214110.826634152[/C][C]15131.1733658478[/C][/ROW]
[ROW][C]161[/C][C]351619[/C][C]355114.326090212[/C][C]-3495.32609021185[/C][/ROW]
[ROW][C]162[/C][C]84207[/C][C]74310.8090446354[/C][C]9896.19095536456[/C][/ROW]
[ROW][C]163[/C][C]120445[/C][C]119282.088099509[/C][C]1162.9119004911[/C][/ROW]
[ROW][C]164[/C][C]324598[/C][C]301380.109633917[/C][C]23217.8903660828[/C][/ROW]
[ROW][C]165[/C][C]131069[/C][C]145734.487980901[/C][C]-14665.4879809006[/C][/ROW]
[ROW][C]166[/C][C]204271[/C][C]189012.156395444[/C][C]15258.8436045563[/C][/ROW]
[ROW][C]167[/C][C]165543[/C][C]179600.216651177[/C][C]-14057.2166511773[/C][/ROW]
[ROW][C]168[/C][C]141722[/C][C]118657.415890092[/C][C]23064.5841099082[/C][/ROW]
[ROW][C]169[/C][C]116048[/C][C]113455.528639612[/C][C]2592.47136038762[/C][/ROW]
[ROW][C]170[/C][C]250047[/C][C]175829.593710167[/C][C]74217.4062898327[/C][/ROW]
[ROW][C]171[/C][C]299775[/C][C]293395.220158535[/C][C]6379.77984146522[/C][/ROW]
[ROW][C]172[/C][C]195838[/C][C]185715.25799431[/C][C]10122.7420056903[/C][/ROW]
[ROW][C]173[/C][C]173260[/C][C]128022.851598112[/C][C]45237.1484018876[/C][/ROW]
[ROW][C]174[/C][C]254488[/C][C]227463.893588379[/C][C]27024.1064116212[/C][/ROW]
[ROW][C]175[/C][C]104389[/C][C]139763.211488396[/C][C]-35374.2114883963[/C][/ROW]
[ROW][C]176[/C][C]136084[/C][C]139438.524890337[/C][C]-3354.52489033686[/C][/ROW]
[ROW][C]177[/C][C]199476[/C][C]224016.915988544[/C][C]-24540.9159885442[/C][/ROW]
[ROW][C]178[/C][C]92499[/C][C]79994.7672422897[/C][C]12504.2327577103[/C][/ROW]
[ROW][C]179[/C][C]224330[/C][C]221381.488358032[/C][C]2948.51164196776[/C][/ROW]
[ROW][C]180[/C][C]135781[/C][C]107263.750839044[/C][C]28517.2491609562[/C][/ROW]
[ROW][C]181[/C][C]74408[/C][C]85675.2278908735[/C][C]-11267.2278908735[/C][/ROW]
[ROW][C]182[/C][C]81240[/C][C]102850.060941254[/C][C]-21610.0609412539[/C][/ROW]
[ROW][C]183[/C][C]14688[/C][C]9327.55213060513[/C][C]5360.44786939487[/C][/ROW]
[ROW][C]184[/C][C]181633[/C][C]171003.595901968[/C][C]10629.4040980323[/C][/ROW]
[ROW][C]185[/C][C]271856[/C][C]275635.879317991[/C][C]-3779.87931799079[/C][/ROW]
[ROW][C]186[/C][C]7199[/C][C]5325.63778100496[/C][C]1873.36221899504[/C][/ROW]
[ROW][C]187[/C][C]46660[/C][C]47010.4889140233[/C][C]-350.488914023342[/C][/ROW]
[ROW][C]188[/C][C]17547[/C][C]7147.3223618852[/C][C]10399.6776381148[/C][/ROW]
[ROW][C]189[/C][C]133368[/C][C]140367.826537575[/C][C]-6999.82653757496[/C][/ROW]
[ROW][C]190[/C][C]95227[/C][C]65480.1270877954[/C][C]29746.8729122046[/C][/ROW]
[ROW][C]191[/C][C]152601[/C][C]107797.362575925[/C][C]44803.6374240751[/C][/ROW]
[ROW][C]192[/C][C]98146[/C][C]95348.1541865694[/C][C]2797.84581343061[/C][/ROW]
[ROW][C]193[/C][C]79619[/C][C]90679.3048415578[/C][C]-11060.3048415578[/C][/ROW]
[ROW][C]194[/C][C]59194[/C][C]77516.4501332279[/C][C]-18322.4501332279[/C][/ROW]
[ROW][C]195[/C][C]139942[/C][C]158887.757218153[/C][C]-18945.7572181529[/C][/ROW]
[ROW][C]196[/C][C]118612[/C][C]107902.296238658[/C][C]10709.7037613415[/C][/ROW]
[ROW][C]197[/C][C]72880[/C][C]86217.4288398622[/C][C]-13337.4288398622[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160348&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160348&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
1210907192277.15743711718629.8425628831
2120982140944.386752191-19962.3867521911
3176508174323.8536537012184.14634629857
4179321219369.923442063-40048.9234420634
5123185110390.23046870512794.769531295
65274669014.2434479856-16268.2434479856
7385534367772.76378032117761.2362196791
83317029135.38158905954034.61841094046
910164582201.933387134119443.0666128659
10149061168457.827236096-19396.8272360959
11165446149249.02671247616196.9732875238
12237213239754.340215862-2541.34021586187
13173326167900.5400419855425.45995801545
14133131136512.240891213-3381.24089121268
15258873218517.32844460540355.6715553954
16180083177714.2878623382368.71213766161
17324799368725.235609418-43926.2356094176
18230964206605.5649925624358.4350074403
19236785229294.8507325137490.14926748649
20135473132754.9559936942718.04400630601
21202925196380.2131230636544.78687693705
22215147201166.24170712413980.758292876
23344297255594.63811839188702.3618816087
24153935146824.8007928967110.19920710422
25132943156031.445595624-23088.4455956239
26174724225851.69466381-51127.6946638098
27174415211600.05780155-37185.0578015505
28225548256179.963903295-30631.963903295
29223632204615.97982251719016.0201774834
30124817128441.602215131-3624.60221513064
31221698266697.644287462-44999.6442874621
32210767218448.711940669-7681.71194066857
33170266178537.947086049-8271.94708604892
34260561253697.6992678486863.30073215157
358485384528.3762919078324.623708092219
36294424290591.9403487583832.05965124157
3710101195905.20702526515105.79297473494
38215641207980.2188769587660.78112304179
39325107288834.32624492136272.6737550788
4071764863.378229822422312.62177017758
41167542159934.3570247967607.64297520429
4210640883511.082227977222896.9177720229
4396560109987.828085183-13427.8280851832
44265769268386.755656895-2617.75565689489
45269651281542.399247657-11891.3992476569
46149112151696.618367831-2584.61836783132
47175824190943.552782012-15119.5527820117
48152871168795.374623898-15924.3746238981
49111665104208.5592283857456.4407716147
50116408162776.550462953-46368.5504629534
51362301326318.9689454435982.0310545597
5278800102708.364462317-23908.3644623171
53183167189091.329685574-5924.32968557433
54277965326496.844029228-48531.8440292281
55150629188428.267503635-37799.2675036351
56168809192626.543132243-23817.5431322434
572418836625.3570739833-12437.3570739833
58329267291227.58748615438039.4125138456
596502966313.3324594178-1284.33245941781
60101097110347.317893369-9250.31789336923
61218946212739.8774298756206.12257012459
62244052243018.490150781033.50984921979
63341570342608.706972928-1038.70697292841
6410359799985.61773805573611.38226194432
65233328270704.831502794-37376.8315027944
66256462266627.295148587-10165.2951485866
67206161159384.02934735346776.9706526467
68311473325832.914016412-14359.9140164121
69235800265964.941139187-30164.9411391868
70177939209681.65566205-31742.6556620503
71207176197600.3430223929575.65697760785
72196553182508.87762639614044.1223736041
73174184167081.4075819427102.5924180579
74143246147564.376563619-4318.37656361919
75187559223292.960384694-35733.9603846937
76187681180976.511144916704.48885508952
77119016131861.596440678-12845.5964406781
78182192198602.647099275-16410.6470992752
797356690071.1134984182-16505.1134984182
80194979194242.091528032736.908471968104
81167488157915.0517884459572.94821155507
82143756153544.594416102-9788.59441610229
83275541203749.46376110471791.5362388959
84243199225639.33926671617559.6607332837
85182999181098.3983723021900.60162769771
86135649140928.119545418-5279.11954541758
87152299150432.6393895731866.36061042668
88120221133643.663846127-13422.6638461266
89346485274241.92677189572243.0732281046
90145790163148.589103788-17358.5891037881
91193339152728.62203219840610.3779678016
928095396289.757888627-15336.757888627
93122774137183.958059838-14409.9580598381
94130585112229.94260506418355.0573949362
95112611102352.01496311710258.9850368828
96286468275961.18443545510506.8155645455
97241066225328.4018217815737.5981782201
98148446200084.601162585-51638.6011625854
99204713189084.29730575915628.7026942414
100182079173256.0402618678822.95973813287
101140344145562.169111981-5218.16911198111
102220516216935.8745200053580.1254799953
103243060211845.80131230831214.1986876922
104162765150311.81145696412453.188543036
105182613175536.1151128417076.8848871594
106232138233633.29130376-1495.29130375953
107265318297844.369864197-32526.3698641966
1088557489481.4730228988-3907.4730228988
109310839302438.4268494468400.57315055378
110225060201675.98905994523384.010940055
111232317248757.477763845-16440.4777638447
112144966153090.772324559-8124.77232455945
1134328753765.7656009764-10478.7656009764
114155754154452.1459819361301.85401806443
115164709181817.662462106-17108.6624621059
116201940211519.63353841-9579.63353840976
117235454227136.2098239048317.79017609614
118220801186865.46631588233935.5336841176
11999466159034.4653869-59568.4653869001
12092661100080.690271505-7419.69027150497
121133328133925.479205641-597.479205641425
1226136187545.5607370334-26184.5607370334
123125930157546.27470887-31616.2747088698
124100750135980.737380889-35230.7373808892
125224549199298.27404567925250.7259543208
1268231673116.72857971619199.27142028393
12710201094672.45437554237337.54562445767
128101523101247.830389524275.169610476321
129243511196891.87694429846619.1230557024
1302293817857.50976407495080.49023592515
1314156642067.2016975481-501.201697548127
132152474166373.20613255-13899.2061325501
1336185745217.726474360616639.2735256394
13499923140140.128081486-40217.1280814864
135132487136489.175513177-4002.17551317701
136317394324138.880596937-6744.88059693743
1372105419328.41373731251725.58626268748
138209641197497.51485495712143.4851450433
1392264832538.0683462696-9890.06834626957
1403141433250.4771220875-1836.47712208752
1414669864535.2662343609-17837.2662343609
142131698144113.754408298-12415.7544082976
1439173577756.524582794413978.4754172056
144244749277973.225293188-33224.2252931879
145184510155368.00063433929141.9993656608
1467986388864.2416501389-9001.24165013889
147128423104068.41817529724354.5818247027
14897839113275.929055623-15436.9290556235
1493821449686.5723861978-11472.5723861978
150151101146485.9729967754615.02700322453
151272458248615.69004068823842.309959312
152172494178389.763076323-5895.76307632338
153108043113804.907606837-5761.90760683666
154328107329527.644235234-1420.64423523393
155250579279518.402200702-28939.4022007019
156351067333732.33945352717334.6605464728
157158015153903.5585720844111.44142791553
1589886687398.801689021111467.1983109789
15985439109856.902912334-24417.9029123337
160229242214110.82663415215131.1733658478
161351619355114.326090212-3495.32609021185
1628420774310.80904463549896.19095536456
163120445119282.0880995091162.9119004911
164324598301380.10963391723217.8903660828
165131069145734.487980901-14665.4879809006
166204271189012.15639544415258.8436045563
167165543179600.216651177-14057.2166511773
168141722118657.41589009223064.5841099082
169116048113455.5286396122592.47136038762
170250047175829.59371016774217.4062898327
171299775293395.2201585356379.77984146522
172195838185715.2579943110122.7420056903
173173260128022.85159811245237.1484018876
174254488227463.89358837927024.1064116212
175104389139763.211488396-35374.2114883963
176136084139438.524890337-3354.52489033686
177199476224016.915988544-24540.9159885442
1789249979994.767242289712504.2327577103
179224330221381.4883580322948.51164196776
180135781107263.75083904428517.2491609562
1817440885675.2278908735-11267.2278908735
18281240102850.060941254-21610.0609412539
183146889327.552130605135360.44786939487
184181633171003.59590196810629.4040980323
185271856275635.879317991-3779.87931799079
18671995325.637781004961873.36221899504
1874666047010.4889140233-350.488914023342
188175477147.322361885210399.6776381148
189133368140367.826537575-6999.82653757496
1909522765480.127087795429746.8729122046
191152601107797.36257592544803.6374240751
1929814695348.15418656942797.84581343061
1937961990679.3048415578-11060.3048415578
1945919477516.4501332279-18322.4501332279
195139942158887.757218153-18945.7572181529
196118612107902.29623865810709.7037613415
1977288086217.4288398622-13337.4288398622






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
180.639604333601640.720791332796720.36039566639836
190.4962176317954610.9924352635909220.503782368204539
200.4634834700435260.9269669400870520.536516529956474
210.4279532058267380.8559064116534770.572046794173262
220.4985760179163460.9971520358326920.501423982083654
230.8309479960967850.338104007806430.169052003903215
240.765075294675270.4698494106494590.23492470532473
250.8364381011691240.3271237976617520.163561898830876
260.8671994815088170.2656010369823650.132800518491183
270.8703068836431290.2593862327137430.129693116356871
280.8688771356143670.2622457287712660.131122864385633
290.8513318820160410.2973362359679180.148668117983959
300.8153571765040410.3692856469919180.184642823495959
310.8984873211765240.2030253576469530.101512678823476
320.8673095372899850.2653809254200290.132690462710015
330.8304573729858030.3390852540283950.169542627014197
340.7869548487457510.4260903025084980.213045151254249
350.7352704346467780.5294591307064450.264729565353222
360.6894657276366330.6210685447267340.310534272363367
370.6302081680580330.7395836638839340.369791831941967
380.5698416469952710.8603167060094580.430158353004729
390.6495865201958350.700826959608330.350413479804165
400.6808024515874150.638395096825170.319197548412585
410.6288683999575830.7422632000848340.371131600042417
420.5835047881217350.832990423756530.416495211878265
430.5300534198098810.9398931603802380.469946580190119
440.4767479403752990.9534958807505980.523252059624701
450.5125579640562690.9748840718874610.487442035943731
460.4598070337196050.9196140674392090.540192966280395
470.4122922845241340.8245845690482690.587707715475866
480.362607691723390.725215383446780.63739230827661
490.3175698454295730.6351396908591450.682430154570427
500.5319543877065740.9360912245868520.468045612293426
510.8392446788795190.3215106422409610.160755321120481
520.8366083808691130.3267832382617740.163391619130887
530.8156620461631360.3686759076737270.184337953836864
540.9107622601214830.1784754797570340.089237739878517
550.9417017102835930.1165965794328150.0582982897164074
560.9425742298433430.1148515403133140.0574257701566568
570.9355042315686190.1289915368627630.0644957684313814
580.9435059923175060.1129880153649880.0564940076824939
590.9285740232094960.1428519535810080.071425976790504
600.9166462339354680.1667075321290640.0833537660645321
610.9003718588966750.1992562822066490.0996281411033246
620.8813819110479160.2372361779041680.118618088952084
630.8567825152545540.2864349694908920.143217484745446
640.8284745161096750.343050967780650.171525483890325
650.8921307527746460.2157384944507090.107869247225354
660.873219526288920.253560947422160.12678047371108
670.9354290286829080.1291419426341840.0645709713170921
680.9263860171664480.1472279656671050.0736139828335525
690.925381403117290.1492371937654190.0746185968827095
700.9304088135991650.139182372801670.0695911864008351
710.9175314726795050.164937054640990.0824685273204952
720.9049488896020670.1901022207958660.0950511103979329
730.8878939851772170.2242120296455660.112106014822783
740.8648294869243820.2703410261512370.135170513075618
750.8942002712016950.211599457596610.105799728798305
760.8773731464114160.2452537071771680.122626853588584
770.8579668270570130.2840663458859730.142033172942987
780.8489347384698590.3021305230602830.151065261530141
790.8390905070140650.3218189859718710.160909492985935
800.8115056194902920.3769887610194170.188494380509708
810.791066352701630.417867294596740.20893364729837
820.7593955211848180.4812089576303630.240604478815182
830.9514609880774990.09707802384500280.0485390119225014
840.9442973084963630.1114053830072750.0557026915036374
850.9309787719984410.1380424560031180.069021228001559
860.9155268332461990.1689463335076020.084473166753801
870.8977376785515630.2045246428968740.102262321448437
880.8859263783299550.228147243340090.114073621670045
890.9841733046770680.03165339064586340.0158266953229317
900.9837780539209710.03244389215805880.0162219460790294
910.9872543129670420.02549137406591630.0127456870329581
920.9853202069026360.0293595861947290.0146797930973645
930.9815136015382970.03697279692340540.0184863984617027
940.9791882247025830.04162355059483420.0208117752974171
950.9741885698503620.05162286029927520.0258114301496376
960.9739776538725790.05204469225484170.0260223461274209
970.9684984352129110.06300312957417860.0315015647870893
980.9907665521266310.01846689574673740.00923344787336869
990.9884246186300930.02315076273981330.0115753813699066
1000.9853246083116350.02935078337673080.0146753916883654
1010.9810873228793560.03782535424128910.0189126771206445
1020.9755217322638620.04895653547227650.0244782677361382
1030.9827386218082630.0345227563834750.0172613781917375
1040.9792782391635370.04144352167292660.0207217608364633
1050.9734532398616050.05309352027678990.0265467601383949
1060.9674741770243910.06505164595121870.0325258229756094
1070.985983446802650.02803310639470090.0140165531973504
1080.9820715375857820.03585692482843520.0179284624142176
1090.9777420521098290.04451589578034220.0222579478901711
1100.9747007052064110.05059858958717910.0252992947935895
1110.9707532990405880.05849340191882290.0292467009594115
1120.9635682401876940.07286351962461270.0364317598123064
1130.9564375667796190.08712486644076130.0435624332203806
1140.9452206493881880.1095587012236240.0547793506118122
1150.9417136767430760.1165726465138470.0582863232569236
1160.9288176036154420.1423647927691150.0711823963845577
1170.9133420678031810.1733158643936380.0866579321968189
1180.9354184102110590.1291631795778810.0645815897889405
1190.9779451747625810.04410965047483870.0220548252374194
1200.9724839620482340.05503207590353220.0275160379517661
1210.9644005046172660.07119899076546780.0355994953827339
1220.9724881565066520.05502368698669610.0275118434933481
1230.9706236287918460.05875274241630690.0293763712081535
1240.973687744778610.0526245104427810.0263122552213905
1250.9712188927720660.05756221445586810.0287811072279341
1260.9636783070293120.07264338594137540.0363216929706877
1270.9543643426721620.09127131465567550.0456356573278378
1280.9418315634308240.1163368731383520.0581684365691758
1290.9699935773552030.06001284528959420.0300064226447971
1300.9610652896491050.07786942070179090.0389347103508954
1310.9505455508639410.09890889827211820.0494544491360591
1320.9436855584015920.1126288831968150.0563144415984076
1330.9319795440861810.1360409118276390.0680204559138193
1340.966362296269710.06727540746058070.0336377037302904
1350.956718989705730.08656202058853920.0432810102942696
1360.9464211607526360.1071576784947280.0535788392473642
1370.9311360266440380.1377279467119230.0688639733559617
1380.9192855918999280.1614288162001440.0807144081000718
1390.9061295500508380.1877408998983240.093870449949162
1400.8825585260234140.2348829479531720.117441473976586
1410.8797396062414330.2405207875171330.120260393758567
1420.8713148744613560.2573702510772880.128685125538644
1430.8549396390964650.290120721807070.145060360903535
1440.8831307060518720.2337385878962560.116869293948128
1450.8777741515984830.2444516968030340.122225848401517
1460.8678095810819680.2643808378360640.132190418918032
1470.8828235542050170.2343528915899670.117176445794983
1480.8795582739945150.240883452010970.120441726005485
1490.8517717539852780.2964564920294440.148228246014722
1500.8184118914332590.3631762171334830.181588108566741
1510.8351282177070.3297435645860.164871782293
1520.8004461936981890.3991076126036220.199553806301811
1530.7817647930064060.4364704139871880.218235206993594
1540.7416725002242320.5166549995515360.258327499775768
1550.716312875043760.567374249912480.28368712495624
1560.6682144540031350.6635710919937290.331785545996865
1570.646234291990220.707531416019560.35376570800978
1580.6891197955004590.6217604089990810.310880204499541
1590.6989146505759180.6021706988481630.301085349424082
1600.7135172021539010.5729655956921990.286482797846099
1610.6742469585216110.6515060829567780.325753041478389
1620.6840275284816410.6319449430367180.315972471518359
1630.6327578120790380.7344843758419230.367242187920961
1640.7054042578877850.589191484224430.294595742112215
1650.6837320664497070.6325358671005870.316267933550293
1660.7546363394708990.4907273210582030.245363660529101
1670.6940490527815160.6119018944369680.305950947218484
1680.6319082343057940.7361835313884110.368091765694206
1690.5657086536305380.8685826927389240.434291346369462
1700.9928024071386160.01439518572276870.00719759286138436
1710.9896305416444110.02073891671117750.0103694583555888
1720.9813828477178270.03723430456434520.0186171522821726
1730.9824644452277830.03507110954443380.0175355547722169
1740.9694694861218830.06106102775623320.0305305138781166
1750.9418167330063470.1163665339873070.0581832669936533
1760.9056211840158040.1887576319683910.0943788159841956
1770.8412856909901520.3174286180196960.158714309009848
1780.8568520013782560.2862959972434870.143147998621744
1790.722397037624940.555205924750120.27760296237506

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
18 & 0.63960433360164 & 0.72079133279672 & 0.36039566639836 \tabularnewline
19 & 0.496217631795461 & 0.992435263590922 & 0.503782368204539 \tabularnewline
20 & 0.463483470043526 & 0.926966940087052 & 0.536516529956474 \tabularnewline
21 & 0.427953205826738 & 0.855906411653477 & 0.572046794173262 \tabularnewline
22 & 0.498576017916346 & 0.997152035832692 & 0.501423982083654 \tabularnewline
23 & 0.830947996096785 & 0.33810400780643 & 0.169052003903215 \tabularnewline
24 & 0.76507529467527 & 0.469849410649459 & 0.23492470532473 \tabularnewline
25 & 0.836438101169124 & 0.327123797661752 & 0.163561898830876 \tabularnewline
26 & 0.867199481508817 & 0.265601036982365 & 0.132800518491183 \tabularnewline
27 & 0.870306883643129 & 0.259386232713743 & 0.129693116356871 \tabularnewline
28 & 0.868877135614367 & 0.262245728771266 & 0.131122864385633 \tabularnewline
29 & 0.851331882016041 & 0.297336235967918 & 0.148668117983959 \tabularnewline
30 & 0.815357176504041 & 0.369285646991918 & 0.184642823495959 \tabularnewline
31 & 0.898487321176524 & 0.203025357646953 & 0.101512678823476 \tabularnewline
32 & 0.867309537289985 & 0.265380925420029 & 0.132690462710015 \tabularnewline
33 & 0.830457372985803 & 0.339085254028395 & 0.169542627014197 \tabularnewline
34 & 0.786954848745751 & 0.426090302508498 & 0.213045151254249 \tabularnewline
35 & 0.735270434646778 & 0.529459130706445 & 0.264729565353222 \tabularnewline
36 & 0.689465727636633 & 0.621068544726734 & 0.310534272363367 \tabularnewline
37 & 0.630208168058033 & 0.739583663883934 & 0.369791831941967 \tabularnewline
38 & 0.569841646995271 & 0.860316706009458 & 0.430158353004729 \tabularnewline
39 & 0.649586520195835 & 0.70082695960833 & 0.350413479804165 \tabularnewline
40 & 0.680802451587415 & 0.63839509682517 & 0.319197548412585 \tabularnewline
41 & 0.628868399957583 & 0.742263200084834 & 0.371131600042417 \tabularnewline
42 & 0.583504788121735 & 0.83299042375653 & 0.416495211878265 \tabularnewline
43 & 0.530053419809881 & 0.939893160380238 & 0.469946580190119 \tabularnewline
44 & 0.476747940375299 & 0.953495880750598 & 0.523252059624701 \tabularnewline
45 & 0.512557964056269 & 0.974884071887461 & 0.487442035943731 \tabularnewline
46 & 0.459807033719605 & 0.919614067439209 & 0.540192966280395 \tabularnewline
47 & 0.412292284524134 & 0.824584569048269 & 0.587707715475866 \tabularnewline
48 & 0.36260769172339 & 0.72521538344678 & 0.63739230827661 \tabularnewline
49 & 0.317569845429573 & 0.635139690859145 & 0.682430154570427 \tabularnewline
50 & 0.531954387706574 & 0.936091224586852 & 0.468045612293426 \tabularnewline
51 & 0.839244678879519 & 0.321510642240961 & 0.160755321120481 \tabularnewline
52 & 0.836608380869113 & 0.326783238261774 & 0.163391619130887 \tabularnewline
53 & 0.815662046163136 & 0.368675907673727 & 0.184337953836864 \tabularnewline
54 & 0.910762260121483 & 0.178475479757034 & 0.089237739878517 \tabularnewline
55 & 0.941701710283593 & 0.116596579432815 & 0.0582982897164074 \tabularnewline
56 & 0.942574229843343 & 0.114851540313314 & 0.0574257701566568 \tabularnewline
57 & 0.935504231568619 & 0.128991536862763 & 0.0644957684313814 \tabularnewline
58 & 0.943505992317506 & 0.112988015364988 & 0.0564940076824939 \tabularnewline
59 & 0.928574023209496 & 0.142851953581008 & 0.071425976790504 \tabularnewline
60 & 0.916646233935468 & 0.166707532129064 & 0.0833537660645321 \tabularnewline
61 & 0.900371858896675 & 0.199256282206649 & 0.0996281411033246 \tabularnewline
62 & 0.881381911047916 & 0.237236177904168 & 0.118618088952084 \tabularnewline
63 & 0.856782515254554 & 0.286434969490892 & 0.143217484745446 \tabularnewline
64 & 0.828474516109675 & 0.34305096778065 & 0.171525483890325 \tabularnewline
65 & 0.892130752774646 & 0.215738494450709 & 0.107869247225354 \tabularnewline
66 & 0.87321952628892 & 0.25356094742216 & 0.12678047371108 \tabularnewline
67 & 0.935429028682908 & 0.129141942634184 & 0.0645709713170921 \tabularnewline
68 & 0.926386017166448 & 0.147227965667105 & 0.0736139828335525 \tabularnewline
69 & 0.92538140311729 & 0.149237193765419 & 0.0746185968827095 \tabularnewline
70 & 0.930408813599165 & 0.13918237280167 & 0.0695911864008351 \tabularnewline
71 & 0.917531472679505 & 0.16493705464099 & 0.0824685273204952 \tabularnewline
72 & 0.904948889602067 & 0.190102220795866 & 0.0950511103979329 \tabularnewline
73 & 0.887893985177217 & 0.224212029645566 & 0.112106014822783 \tabularnewline
74 & 0.864829486924382 & 0.270341026151237 & 0.135170513075618 \tabularnewline
75 & 0.894200271201695 & 0.21159945759661 & 0.105799728798305 \tabularnewline
76 & 0.877373146411416 & 0.245253707177168 & 0.122626853588584 \tabularnewline
77 & 0.857966827057013 & 0.284066345885973 & 0.142033172942987 \tabularnewline
78 & 0.848934738469859 & 0.302130523060283 & 0.151065261530141 \tabularnewline
79 & 0.839090507014065 & 0.321818985971871 & 0.160909492985935 \tabularnewline
80 & 0.811505619490292 & 0.376988761019417 & 0.188494380509708 \tabularnewline
81 & 0.79106635270163 & 0.41786729459674 & 0.20893364729837 \tabularnewline
82 & 0.759395521184818 & 0.481208957630363 & 0.240604478815182 \tabularnewline
83 & 0.951460988077499 & 0.0970780238450028 & 0.0485390119225014 \tabularnewline
84 & 0.944297308496363 & 0.111405383007275 & 0.0557026915036374 \tabularnewline
85 & 0.930978771998441 & 0.138042456003118 & 0.069021228001559 \tabularnewline
86 & 0.915526833246199 & 0.168946333507602 & 0.084473166753801 \tabularnewline
87 & 0.897737678551563 & 0.204524642896874 & 0.102262321448437 \tabularnewline
88 & 0.885926378329955 & 0.22814724334009 & 0.114073621670045 \tabularnewline
89 & 0.984173304677068 & 0.0316533906458634 & 0.0158266953229317 \tabularnewline
90 & 0.983778053920971 & 0.0324438921580588 & 0.0162219460790294 \tabularnewline
91 & 0.987254312967042 & 0.0254913740659163 & 0.0127456870329581 \tabularnewline
92 & 0.985320206902636 & 0.029359586194729 & 0.0146797930973645 \tabularnewline
93 & 0.981513601538297 & 0.0369727969234054 & 0.0184863984617027 \tabularnewline
94 & 0.979188224702583 & 0.0416235505948342 & 0.0208117752974171 \tabularnewline
95 & 0.974188569850362 & 0.0516228602992752 & 0.0258114301496376 \tabularnewline
96 & 0.973977653872579 & 0.0520446922548417 & 0.0260223461274209 \tabularnewline
97 & 0.968498435212911 & 0.0630031295741786 & 0.0315015647870893 \tabularnewline
98 & 0.990766552126631 & 0.0184668957467374 & 0.00923344787336869 \tabularnewline
99 & 0.988424618630093 & 0.0231507627398133 & 0.0115753813699066 \tabularnewline
100 & 0.985324608311635 & 0.0293507833767308 & 0.0146753916883654 \tabularnewline
101 & 0.981087322879356 & 0.0378253542412891 & 0.0189126771206445 \tabularnewline
102 & 0.975521732263862 & 0.0489565354722765 & 0.0244782677361382 \tabularnewline
103 & 0.982738621808263 & 0.034522756383475 & 0.0172613781917375 \tabularnewline
104 & 0.979278239163537 & 0.0414435216729266 & 0.0207217608364633 \tabularnewline
105 & 0.973453239861605 & 0.0530935202767899 & 0.0265467601383949 \tabularnewline
106 & 0.967474177024391 & 0.0650516459512187 & 0.0325258229756094 \tabularnewline
107 & 0.98598344680265 & 0.0280331063947009 & 0.0140165531973504 \tabularnewline
108 & 0.982071537585782 & 0.0358569248284352 & 0.0179284624142176 \tabularnewline
109 & 0.977742052109829 & 0.0445158957803422 & 0.0222579478901711 \tabularnewline
110 & 0.974700705206411 & 0.0505985895871791 & 0.0252992947935895 \tabularnewline
111 & 0.970753299040588 & 0.0584934019188229 & 0.0292467009594115 \tabularnewline
112 & 0.963568240187694 & 0.0728635196246127 & 0.0364317598123064 \tabularnewline
113 & 0.956437566779619 & 0.0871248664407613 & 0.0435624332203806 \tabularnewline
114 & 0.945220649388188 & 0.109558701223624 & 0.0547793506118122 \tabularnewline
115 & 0.941713676743076 & 0.116572646513847 & 0.0582863232569236 \tabularnewline
116 & 0.928817603615442 & 0.142364792769115 & 0.0711823963845577 \tabularnewline
117 & 0.913342067803181 & 0.173315864393638 & 0.0866579321968189 \tabularnewline
118 & 0.935418410211059 & 0.129163179577881 & 0.0645815897889405 \tabularnewline
119 & 0.977945174762581 & 0.0441096504748387 & 0.0220548252374194 \tabularnewline
120 & 0.972483962048234 & 0.0550320759035322 & 0.0275160379517661 \tabularnewline
121 & 0.964400504617266 & 0.0711989907654678 & 0.0355994953827339 \tabularnewline
122 & 0.972488156506652 & 0.0550236869866961 & 0.0275118434933481 \tabularnewline
123 & 0.970623628791846 & 0.0587527424163069 & 0.0293763712081535 \tabularnewline
124 & 0.97368774477861 & 0.052624510442781 & 0.0263122552213905 \tabularnewline
125 & 0.971218892772066 & 0.0575622144558681 & 0.0287811072279341 \tabularnewline
126 & 0.963678307029312 & 0.0726433859413754 & 0.0363216929706877 \tabularnewline
127 & 0.954364342672162 & 0.0912713146556755 & 0.0456356573278378 \tabularnewline
128 & 0.941831563430824 & 0.116336873138352 & 0.0581684365691758 \tabularnewline
129 & 0.969993577355203 & 0.0600128452895942 & 0.0300064226447971 \tabularnewline
130 & 0.961065289649105 & 0.0778694207017909 & 0.0389347103508954 \tabularnewline
131 & 0.950545550863941 & 0.0989088982721182 & 0.0494544491360591 \tabularnewline
132 & 0.943685558401592 & 0.112628883196815 & 0.0563144415984076 \tabularnewline
133 & 0.931979544086181 & 0.136040911827639 & 0.0680204559138193 \tabularnewline
134 & 0.96636229626971 & 0.0672754074605807 & 0.0336377037302904 \tabularnewline
135 & 0.95671898970573 & 0.0865620205885392 & 0.0432810102942696 \tabularnewline
136 & 0.946421160752636 & 0.107157678494728 & 0.0535788392473642 \tabularnewline
137 & 0.931136026644038 & 0.137727946711923 & 0.0688639733559617 \tabularnewline
138 & 0.919285591899928 & 0.161428816200144 & 0.0807144081000718 \tabularnewline
139 & 0.906129550050838 & 0.187740899898324 & 0.093870449949162 \tabularnewline
140 & 0.882558526023414 & 0.234882947953172 & 0.117441473976586 \tabularnewline
141 & 0.879739606241433 & 0.240520787517133 & 0.120260393758567 \tabularnewline
142 & 0.871314874461356 & 0.257370251077288 & 0.128685125538644 \tabularnewline
143 & 0.854939639096465 & 0.29012072180707 & 0.145060360903535 \tabularnewline
144 & 0.883130706051872 & 0.233738587896256 & 0.116869293948128 \tabularnewline
145 & 0.877774151598483 & 0.244451696803034 & 0.122225848401517 \tabularnewline
146 & 0.867809581081968 & 0.264380837836064 & 0.132190418918032 \tabularnewline
147 & 0.882823554205017 & 0.234352891589967 & 0.117176445794983 \tabularnewline
148 & 0.879558273994515 & 0.24088345201097 & 0.120441726005485 \tabularnewline
149 & 0.851771753985278 & 0.296456492029444 & 0.148228246014722 \tabularnewline
150 & 0.818411891433259 & 0.363176217133483 & 0.181588108566741 \tabularnewline
151 & 0.835128217707 & 0.329743564586 & 0.164871782293 \tabularnewline
152 & 0.800446193698189 & 0.399107612603622 & 0.199553806301811 \tabularnewline
153 & 0.781764793006406 & 0.436470413987188 & 0.218235206993594 \tabularnewline
154 & 0.741672500224232 & 0.516654999551536 & 0.258327499775768 \tabularnewline
155 & 0.71631287504376 & 0.56737424991248 & 0.28368712495624 \tabularnewline
156 & 0.668214454003135 & 0.663571091993729 & 0.331785545996865 \tabularnewline
157 & 0.64623429199022 & 0.70753141601956 & 0.35376570800978 \tabularnewline
158 & 0.689119795500459 & 0.621760408999081 & 0.310880204499541 \tabularnewline
159 & 0.698914650575918 & 0.602170698848163 & 0.301085349424082 \tabularnewline
160 & 0.713517202153901 & 0.572965595692199 & 0.286482797846099 \tabularnewline
161 & 0.674246958521611 & 0.651506082956778 & 0.325753041478389 \tabularnewline
162 & 0.684027528481641 & 0.631944943036718 & 0.315972471518359 \tabularnewline
163 & 0.632757812079038 & 0.734484375841923 & 0.367242187920961 \tabularnewline
164 & 0.705404257887785 & 0.58919148422443 & 0.294595742112215 \tabularnewline
165 & 0.683732066449707 & 0.632535867100587 & 0.316267933550293 \tabularnewline
166 & 0.754636339470899 & 0.490727321058203 & 0.245363660529101 \tabularnewline
167 & 0.694049052781516 & 0.611901894436968 & 0.305950947218484 \tabularnewline
168 & 0.631908234305794 & 0.736183531388411 & 0.368091765694206 \tabularnewline
169 & 0.565708653630538 & 0.868582692738924 & 0.434291346369462 \tabularnewline
170 & 0.992802407138616 & 0.0143951857227687 & 0.00719759286138436 \tabularnewline
171 & 0.989630541644411 & 0.0207389167111775 & 0.0103694583555888 \tabularnewline
172 & 0.981382847717827 & 0.0372343045643452 & 0.0186171522821726 \tabularnewline
173 & 0.982464445227783 & 0.0350711095444338 & 0.0175355547722169 \tabularnewline
174 & 0.969469486121883 & 0.0610610277562332 & 0.0305305138781166 \tabularnewline
175 & 0.941816733006347 & 0.116366533987307 & 0.0581832669936533 \tabularnewline
176 & 0.905621184015804 & 0.188757631968391 & 0.0943788159841956 \tabularnewline
177 & 0.841285690990152 & 0.317428618019696 & 0.158714309009848 \tabularnewline
178 & 0.856852001378256 & 0.286295997243487 & 0.143147998621744 \tabularnewline
179 & 0.72239703762494 & 0.55520592475012 & 0.27760296237506 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160348&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]18[/C][C]0.63960433360164[/C][C]0.72079133279672[/C][C]0.36039566639836[/C][/ROW]
[ROW][C]19[/C][C]0.496217631795461[/C][C]0.992435263590922[/C][C]0.503782368204539[/C][/ROW]
[ROW][C]20[/C][C]0.463483470043526[/C][C]0.926966940087052[/C][C]0.536516529956474[/C][/ROW]
[ROW][C]21[/C][C]0.427953205826738[/C][C]0.855906411653477[/C][C]0.572046794173262[/C][/ROW]
[ROW][C]22[/C][C]0.498576017916346[/C][C]0.997152035832692[/C][C]0.501423982083654[/C][/ROW]
[ROW][C]23[/C][C]0.830947996096785[/C][C]0.33810400780643[/C][C]0.169052003903215[/C][/ROW]
[ROW][C]24[/C][C]0.76507529467527[/C][C]0.469849410649459[/C][C]0.23492470532473[/C][/ROW]
[ROW][C]25[/C][C]0.836438101169124[/C][C]0.327123797661752[/C][C]0.163561898830876[/C][/ROW]
[ROW][C]26[/C][C]0.867199481508817[/C][C]0.265601036982365[/C][C]0.132800518491183[/C][/ROW]
[ROW][C]27[/C][C]0.870306883643129[/C][C]0.259386232713743[/C][C]0.129693116356871[/C][/ROW]
[ROW][C]28[/C][C]0.868877135614367[/C][C]0.262245728771266[/C][C]0.131122864385633[/C][/ROW]
[ROW][C]29[/C][C]0.851331882016041[/C][C]0.297336235967918[/C][C]0.148668117983959[/C][/ROW]
[ROW][C]30[/C][C]0.815357176504041[/C][C]0.369285646991918[/C][C]0.184642823495959[/C][/ROW]
[ROW][C]31[/C][C]0.898487321176524[/C][C]0.203025357646953[/C][C]0.101512678823476[/C][/ROW]
[ROW][C]32[/C][C]0.867309537289985[/C][C]0.265380925420029[/C][C]0.132690462710015[/C][/ROW]
[ROW][C]33[/C][C]0.830457372985803[/C][C]0.339085254028395[/C][C]0.169542627014197[/C][/ROW]
[ROW][C]34[/C][C]0.786954848745751[/C][C]0.426090302508498[/C][C]0.213045151254249[/C][/ROW]
[ROW][C]35[/C][C]0.735270434646778[/C][C]0.529459130706445[/C][C]0.264729565353222[/C][/ROW]
[ROW][C]36[/C][C]0.689465727636633[/C][C]0.621068544726734[/C][C]0.310534272363367[/C][/ROW]
[ROW][C]37[/C][C]0.630208168058033[/C][C]0.739583663883934[/C][C]0.369791831941967[/C][/ROW]
[ROW][C]38[/C][C]0.569841646995271[/C][C]0.860316706009458[/C][C]0.430158353004729[/C][/ROW]
[ROW][C]39[/C][C]0.649586520195835[/C][C]0.70082695960833[/C][C]0.350413479804165[/C][/ROW]
[ROW][C]40[/C][C]0.680802451587415[/C][C]0.63839509682517[/C][C]0.319197548412585[/C][/ROW]
[ROW][C]41[/C][C]0.628868399957583[/C][C]0.742263200084834[/C][C]0.371131600042417[/C][/ROW]
[ROW][C]42[/C][C]0.583504788121735[/C][C]0.83299042375653[/C][C]0.416495211878265[/C][/ROW]
[ROW][C]43[/C][C]0.530053419809881[/C][C]0.939893160380238[/C][C]0.469946580190119[/C][/ROW]
[ROW][C]44[/C][C]0.476747940375299[/C][C]0.953495880750598[/C][C]0.523252059624701[/C][/ROW]
[ROW][C]45[/C][C]0.512557964056269[/C][C]0.974884071887461[/C][C]0.487442035943731[/C][/ROW]
[ROW][C]46[/C][C]0.459807033719605[/C][C]0.919614067439209[/C][C]0.540192966280395[/C][/ROW]
[ROW][C]47[/C][C]0.412292284524134[/C][C]0.824584569048269[/C][C]0.587707715475866[/C][/ROW]
[ROW][C]48[/C][C]0.36260769172339[/C][C]0.72521538344678[/C][C]0.63739230827661[/C][/ROW]
[ROW][C]49[/C][C]0.317569845429573[/C][C]0.635139690859145[/C][C]0.682430154570427[/C][/ROW]
[ROW][C]50[/C][C]0.531954387706574[/C][C]0.936091224586852[/C][C]0.468045612293426[/C][/ROW]
[ROW][C]51[/C][C]0.839244678879519[/C][C]0.321510642240961[/C][C]0.160755321120481[/C][/ROW]
[ROW][C]52[/C][C]0.836608380869113[/C][C]0.326783238261774[/C][C]0.163391619130887[/C][/ROW]
[ROW][C]53[/C][C]0.815662046163136[/C][C]0.368675907673727[/C][C]0.184337953836864[/C][/ROW]
[ROW][C]54[/C][C]0.910762260121483[/C][C]0.178475479757034[/C][C]0.089237739878517[/C][/ROW]
[ROW][C]55[/C][C]0.941701710283593[/C][C]0.116596579432815[/C][C]0.0582982897164074[/C][/ROW]
[ROW][C]56[/C][C]0.942574229843343[/C][C]0.114851540313314[/C][C]0.0574257701566568[/C][/ROW]
[ROW][C]57[/C][C]0.935504231568619[/C][C]0.128991536862763[/C][C]0.0644957684313814[/C][/ROW]
[ROW][C]58[/C][C]0.943505992317506[/C][C]0.112988015364988[/C][C]0.0564940076824939[/C][/ROW]
[ROW][C]59[/C][C]0.928574023209496[/C][C]0.142851953581008[/C][C]0.071425976790504[/C][/ROW]
[ROW][C]60[/C][C]0.916646233935468[/C][C]0.166707532129064[/C][C]0.0833537660645321[/C][/ROW]
[ROW][C]61[/C][C]0.900371858896675[/C][C]0.199256282206649[/C][C]0.0996281411033246[/C][/ROW]
[ROW][C]62[/C][C]0.881381911047916[/C][C]0.237236177904168[/C][C]0.118618088952084[/C][/ROW]
[ROW][C]63[/C][C]0.856782515254554[/C][C]0.286434969490892[/C][C]0.143217484745446[/C][/ROW]
[ROW][C]64[/C][C]0.828474516109675[/C][C]0.34305096778065[/C][C]0.171525483890325[/C][/ROW]
[ROW][C]65[/C][C]0.892130752774646[/C][C]0.215738494450709[/C][C]0.107869247225354[/C][/ROW]
[ROW][C]66[/C][C]0.87321952628892[/C][C]0.25356094742216[/C][C]0.12678047371108[/C][/ROW]
[ROW][C]67[/C][C]0.935429028682908[/C][C]0.129141942634184[/C][C]0.0645709713170921[/C][/ROW]
[ROW][C]68[/C][C]0.926386017166448[/C][C]0.147227965667105[/C][C]0.0736139828335525[/C][/ROW]
[ROW][C]69[/C][C]0.92538140311729[/C][C]0.149237193765419[/C][C]0.0746185968827095[/C][/ROW]
[ROW][C]70[/C][C]0.930408813599165[/C][C]0.13918237280167[/C][C]0.0695911864008351[/C][/ROW]
[ROW][C]71[/C][C]0.917531472679505[/C][C]0.16493705464099[/C][C]0.0824685273204952[/C][/ROW]
[ROW][C]72[/C][C]0.904948889602067[/C][C]0.190102220795866[/C][C]0.0950511103979329[/C][/ROW]
[ROW][C]73[/C][C]0.887893985177217[/C][C]0.224212029645566[/C][C]0.112106014822783[/C][/ROW]
[ROW][C]74[/C][C]0.864829486924382[/C][C]0.270341026151237[/C][C]0.135170513075618[/C][/ROW]
[ROW][C]75[/C][C]0.894200271201695[/C][C]0.21159945759661[/C][C]0.105799728798305[/C][/ROW]
[ROW][C]76[/C][C]0.877373146411416[/C][C]0.245253707177168[/C][C]0.122626853588584[/C][/ROW]
[ROW][C]77[/C][C]0.857966827057013[/C][C]0.284066345885973[/C][C]0.142033172942987[/C][/ROW]
[ROW][C]78[/C][C]0.848934738469859[/C][C]0.302130523060283[/C][C]0.151065261530141[/C][/ROW]
[ROW][C]79[/C][C]0.839090507014065[/C][C]0.321818985971871[/C][C]0.160909492985935[/C][/ROW]
[ROW][C]80[/C][C]0.811505619490292[/C][C]0.376988761019417[/C][C]0.188494380509708[/C][/ROW]
[ROW][C]81[/C][C]0.79106635270163[/C][C]0.41786729459674[/C][C]0.20893364729837[/C][/ROW]
[ROW][C]82[/C][C]0.759395521184818[/C][C]0.481208957630363[/C][C]0.240604478815182[/C][/ROW]
[ROW][C]83[/C][C]0.951460988077499[/C][C]0.0970780238450028[/C][C]0.0485390119225014[/C][/ROW]
[ROW][C]84[/C][C]0.944297308496363[/C][C]0.111405383007275[/C][C]0.0557026915036374[/C][/ROW]
[ROW][C]85[/C][C]0.930978771998441[/C][C]0.138042456003118[/C][C]0.069021228001559[/C][/ROW]
[ROW][C]86[/C][C]0.915526833246199[/C][C]0.168946333507602[/C][C]0.084473166753801[/C][/ROW]
[ROW][C]87[/C][C]0.897737678551563[/C][C]0.204524642896874[/C][C]0.102262321448437[/C][/ROW]
[ROW][C]88[/C][C]0.885926378329955[/C][C]0.22814724334009[/C][C]0.114073621670045[/C][/ROW]
[ROW][C]89[/C][C]0.984173304677068[/C][C]0.0316533906458634[/C][C]0.0158266953229317[/C][/ROW]
[ROW][C]90[/C][C]0.983778053920971[/C][C]0.0324438921580588[/C][C]0.0162219460790294[/C][/ROW]
[ROW][C]91[/C][C]0.987254312967042[/C][C]0.0254913740659163[/C][C]0.0127456870329581[/C][/ROW]
[ROW][C]92[/C][C]0.985320206902636[/C][C]0.029359586194729[/C][C]0.0146797930973645[/C][/ROW]
[ROW][C]93[/C][C]0.981513601538297[/C][C]0.0369727969234054[/C][C]0.0184863984617027[/C][/ROW]
[ROW][C]94[/C][C]0.979188224702583[/C][C]0.0416235505948342[/C][C]0.0208117752974171[/C][/ROW]
[ROW][C]95[/C][C]0.974188569850362[/C][C]0.0516228602992752[/C][C]0.0258114301496376[/C][/ROW]
[ROW][C]96[/C][C]0.973977653872579[/C][C]0.0520446922548417[/C][C]0.0260223461274209[/C][/ROW]
[ROW][C]97[/C][C]0.968498435212911[/C][C]0.0630031295741786[/C][C]0.0315015647870893[/C][/ROW]
[ROW][C]98[/C][C]0.990766552126631[/C][C]0.0184668957467374[/C][C]0.00923344787336869[/C][/ROW]
[ROW][C]99[/C][C]0.988424618630093[/C][C]0.0231507627398133[/C][C]0.0115753813699066[/C][/ROW]
[ROW][C]100[/C][C]0.985324608311635[/C][C]0.0293507833767308[/C][C]0.0146753916883654[/C][/ROW]
[ROW][C]101[/C][C]0.981087322879356[/C][C]0.0378253542412891[/C][C]0.0189126771206445[/C][/ROW]
[ROW][C]102[/C][C]0.975521732263862[/C][C]0.0489565354722765[/C][C]0.0244782677361382[/C][/ROW]
[ROW][C]103[/C][C]0.982738621808263[/C][C]0.034522756383475[/C][C]0.0172613781917375[/C][/ROW]
[ROW][C]104[/C][C]0.979278239163537[/C][C]0.0414435216729266[/C][C]0.0207217608364633[/C][/ROW]
[ROW][C]105[/C][C]0.973453239861605[/C][C]0.0530935202767899[/C][C]0.0265467601383949[/C][/ROW]
[ROW][C]106[/C][C]0.967474177024391[/C][C]0.0650516459512187[/C][C]0.0325258229756094[/C][/ROW]
[ROW][C]107[/C][C]0.98598344680265[/C][C]0.0280331063947009[/C][C]0.0140165531973504[/C][/ROW]
[ROW][C]108[/C][C]0.982071537585782[/C][C]0.0358569248284352[/C][C]0.0179284624142176[/C][/ROW]
[ROW][C]109[/C][C]0.977742052109829[/C][C]0.0445158957803422[/C][C]0.0222579478901711[/C][/ROW]
[ROW][C]110[/C][C]0.974700705206411[/C][C]0.0505985895871791[/C][C]0.0252992947935895[/C][/ROW]
[ROW][C]111[/C][C]0.970753299040588[/C][C]0.0584934019188229[/C][C]0.0292467009594115[/C][/ROW]
[ROW][C]112[/C][C]0.963568240187694[/C][C]0.0728635196246127[/C][C]0.0364317598123064[/C][/ROW]
[ROW][C]113[/C][C]0.956437566779619[/C][C]0.0871248664407613[/C][C]0.0435624332203806[/C][/ROW]
[ROW][C]114[/C][C]0.945220649388188[/C][C]0.109558701223624[/C][C]0.0547793506118122[/C][/ROW]
[ROW][C]115[/C][C]0.941713676743076[/C][C]0.116572646513847[/C][C]0.0582863232569236[/C][/ROW]
[ROW][C]116[/C][C]0.928817603615442[/C][C]0.142364792769115[/C][C]0.0711823963845577[/C][/ROW]
[ROW][C]117[/C][C]0.913342067803181[/C][C]0.173315864393638[/C][C]0.0866579321968189[/C][/ROW]
[ROW][C]118[/C][C]0.935418410211059[/C][C]0.129163179577881[/C][C]0.0645815897889405[/C][/ROW]
[ROW][C]119[/C][C]0.977945174762581[/C][C]0.0441096504748387[/C][C]0.0220548252374194[/C][/ROW]
[ROW][C]120[/C][C]0.972483962048234[/C][C]0.0550320759035322[/C][C]0.0275160379517661[/C][/ROW]
[ROW][C]121[/C][C]0.964400504617266[/C][C]0.0711989907654678[/C][C]0.0355994953827339[/C][/ROW]
[ROW][C]122[/C][C]0.972488156506652[/C][C]0.0550236869866961[/C][C]0.0275118434933481[/C][/ROW]
[ROW][C]123[/C][C]0.970623628791846[/C][C]0.0587527424163069[/C][C]0.0293763712081535[/C][/ROW]
[ROW][C]124[/C][C]0.97368774477861[/C][C]0.052624510442781[/C][C]0.0263122552213905[/C][/ROW]
[ROW][C]125[/C][C]0.971218892772066[/C][C]0.0575622144558681[/C][C]0.0287811072279341[/C][/ROW]
[ROW][C]126[/C][C]0.963678307029312[/C][C]0.0726433859413754[/C][C]0.0363216929706877[/C][/ROW]
[ROW][C]127[/C][C]0.954364342672162[/C][C]0.0912713146556755[/C][C]0.0456356573278378[/C][/ROW]
[ROW][C]128[/C][C]0.941831563430824[/C][C]0.116336873138352[/C][C]0.0581684365691758[/C][/ROW]
[ROW][C]129[/C][C]0.969993577355203[/C][C]0.0600128452895942[/C][C]0.0300064226447971[/C][/ROW]
[ROW][C]130[/C][C]0.961065289649105[/C][C]0.0778694207017909[/C][C]0.0389347103508954[/C][/ROW]
[ROW][C]131[/C][C]0.950545550863941[/C][C]0.0989088982721182[/C][C]0.0494544491360591[/C][/ROW]
[ROW][C]132[/C][C]0.943685558401592[/C][C]0.112628883196815[/C][C]0.0563144415984076[/C][/ROW]
[ROW][C]133[/C][C]0.931979544086181[/C][C]0.136040911827639[/C][C]0.0680204559138193[/C][/ROW]
[ROW][C]134[/C][C]0.96636229626971[/C][C]0.0672754074605807[/C][C]0.0336377037302904[/C][/ROW]
[ROW][C]135[/C][C]0.95671898970573[/C][C]0.0865620205885392[/C][C]0.0432810102942696[/C][/ROW]
[ROW][C]136[/C][C]0.946421160752636[/C][C]0.107157678494728[/C][C]0.0535788392473642[/C][/ROW]
[ROW][C]137[/C][C]0.931136026644038[/C][C]0.137727946711923[/C][C]0.0688639733559617[/C][/ROW]
[ROW][C]138[/C][C]0.919285591899928[/C][C]0.161428816200144[/C][C]0.0807144081000718[/C][/ROW]
[ROW][C]139[/C][C]0.906129550050838[/C][C]0.187740899898324[/C][C]0.093870449949162[/C][/ROW]
[ROW][C]140[/C][C]0.882558526023414[/C][C]0.234882947953172[/C][C]0.117441473976586[/C][/ROW]
[ROW][C]141[/C][C]0.879739606241433[/C][C]0.240520787517133[/C][C]0.120260393758567[/C][/ROW]
[ROW][C]142[/C][C]0.871314874461356[/C][C]0.257370251077288[/C][C]0.128685125538644[/C][/ROW]
[ROW][C]143[/C][C]0.854939639096465[/C][C]0.29012072180707[/C][C]0.145060360903535[/C][/ROW]
[ROW][C]144[/C][C]0.883130706051872[/C][C]0.233738587896256[/C][C]0.116869293948128[/C][/ROW]
[ROW][C]145[/C][C]0.877774151598483[/C][C]0.244451696803034[/C][C]0.122225848401517[/C][/ROW]
[ROW][C]146[/C][C]0.867809581081968[/C][C]0.264380837836064[/C][C]0.132190418918032[/C][/ROW]
[ROW][C]147[/C][C]0.882823554205017[/C][C]0.234352891589967[/C][C]0.117176445794983[/C][/ROW]
[ROW][C]148[/C][C]0.879558273994515[/C][C]0.24088345201097[/C][C]0.120441726005485[/C][/ROW]
[ROW][C]149[/C][C]0.851771753985278[/C][C]0.296456492029444[/C][C]0.148228246014722[/C][/ROW]
[ROW][C]150[/C][C]0.818411891433259[/C][C]0.363176217133483[/C][C]0.181588108566741[/C][/ROW]
[ROW][C]151[/C][C]0.835128217707[/C][C]0.329743564586[/C][C]0.164871782293[/C][/ROW]
[ROW][C]152[/C][C]0.800446193698189[/C][C]0.399107612603622[/C][C]0.199553806301811[/C][/ROW]
[ROW][C]153[/C][C]0.781764793006406[/C][C]0.436470413987188[/C][C]0.218235206993594[/C][/ROW]
[ROW][C]154[/C][C]0.741672500224232[/C][C]0.516654999551536[/C][C]0.258327499775768[/C][/ROW]
[ROW][C]155[/C][C]0.71631287504376[/C][C]0.56737424991248[/C][C]0.28368712495624[/C][/ROW]
[ROW][C]156[/C][C]0.668214454003135[/C][C]0.663571091993729[/C][C]0.331785545996865[/C][/ROW]
[ROW][C]157[/C][C]0.64623429199022[/C][C]0.70753141601956[/C][C]0.35376570800978[/C][/ROW]
[ROW][C]158[/C][C]0.689119795500459[/C][C]0.621760408999081[/C][C]0.310880204499541[/C][/ROW]
[ROW][C]159[/C][C]0.698914650575918[/C][C]0.602170698848163[/C][C]0.301085349424082[/C][/ROW]
[ROW][C]160[/C][C]0.713517202153901[/C][C]0.572965595692199[/C][C]0.286482797846099[/C][/ROW]
[ROW][C]161[/C][C]0.674246958521611[/C][C]0.651506082956778[/C][C]0.325753041478389[/C][/ROW]
[ROW][C]162[/C][C]0.684027528481641[/C][C]0.631944943036718[/C][C]0.315972471518359[/C][/ROW]
[ROW][C]163[/C][C]0.632757812079038[/C][C]0.734484375841923[/C][C]0.367242187920961[/C][/ROW]
[ROW][C]164[/C][C]0.705404257887785[/C][C]0.58919148422443[/C][C]0.294595742112215[/C][/ROW]
[ROW][C]165[/C][C]0.683732066449707[/C][C]0.632535867100587[/C][C]0.316267933550293[/C][/ROW]
[ROW][C]166[/C][C]0.754636339470899[/C][C]0.490727321058203[/C][C]0.245363660529101[/C][/ROW]
[ROW][C]167[/C][C]0.694049052781516[/C][C]0.611901894436968[/C][C]0.305950947218484[/C][/ROW]
[ROW][C]168[/C][C]0.631908234305794[/C][C]0.736183531388411[/C][C]0.368091765694206[/C][/ROW]
[ROW][C]169[/C][C]0.565708653630538[/C][C]0.868582692738924[/C][C]0.434291346369462[/C][/ROW]
[ROW][C]170[/C][C]0.992802407138616[/C][C]0.0143951857227687[/C][C]0.00719759286138436[/C][/ROW]
[ROW][C]171[/C][C]0.989630541644411[/C][C]0.0207389167111775[/C][C]0.0103694583555888[/C][/ROW]
[ROW][C]172[/C][C]0.981382847717827[/C][C]0.0372343045643452[/C][C]0.0186171522821726[/C][/ROW]
[ROW][C]173[/C][C]0.982464445227783[/C][C]0.0350711095444338[/C][C]0.0175355547722169[/C][/ROW]
[ROW][C]174[/C][C]0.969469486121883[/C][C]0.0610610277562332[/C][C]0.0305305138781166[/C][/ROW]
[ROW][C]175[/C][C]0.941816733006347[/C][C]0.116366533987307[/C][C]0.0581832669936533[/C][/ROW]
[ROW][C]176[/C][C]0.905621184015804[/C][C]0.188757631968391[/C][C]0.0943788159841956[/C][/ROW]
[ROW][C]177[/C][C]0.841285690990152[/C][C]0.317428618019696[/C][C]0.158714309009848[/C][/ROW]
[ROW][C]178[/C][C]0.856852001378256[/C][C]0.286295997243487[/C][C]0.143147998621744[/C][/ROW]
[ROW][C]179[/C][C]0.72239703762494[/C][C]0.55520592475012[/C][C]0.27760296237506[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160348&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160348&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
180.639604333601640.720791332796720.36039566639836
190.4962176317954610.9924352635909220.503782368204539
200.4634834700435260.9269669400870520.536516529956474
210.4279532058267380.8559064116534770.572046794173262
220.4985760179163460.9971520358326920.501423982083654
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600.9166462339354680.1667075321290640.0833537660645321
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730.8878939851772170.2242120296455660.112106014822783
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750.8942002712016950.211599457596610.105799728798305
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850.9309787719984410.1380424560031180.069021228001559
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1200.9724839620482340.05503207590353220.0275160379517661
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1390.9061295500508380.1877408998983240.093870449949162
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Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level210.12962962962963NOK
10% type I error level450.277777777777778NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 21 & 0.12962962962963 & NOK \tabularnewline
10% type I error level & 45 & 0.277777777777778 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160348&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]21[/C][C]0.12962962962963[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]45[/C][C]0.277777777777778[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160348&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160348&T=6

As an alternative you can also use a QR Code:  
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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 level00OK
5% type I error level210.12962962962963NOK
10% type I error level450.277777777777778NOK


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 2 ; 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')
}