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Author's title

Author*Unverified author*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSat, 17 Dec 2011 13:08:25 -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/17/t1324145321jmbrmgnpfgc5b0e.htm/, Retrieved Fri, 26 Apr 2024 19:19:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156535, Retrieved Fri, 26 Apr 2024 19:19:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101
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]
- RMPD        [Multiple Regression] [] [2011-12-16 11:27:07] [86f7284edee3dbb8ea5c7e2dec87d892]
- R               [Multiple Regression] [] [2011-12-17 18:08:25] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
56	3	30	112285	24188	146283	144	145	1
56	4	28	84786	18273	98364	103	101	1
54	12	38	83123	14130	86146	98	98	1
89	2	30	101193	32287	96933	135	132	1
40	1	22	38361	8654	79234	61	60	1
25	3	26	68504	9245	42551	39	38	1
92	0	25	119182	33251	195663	150	144	1
18	0	18	22807	1271	6853	5	5	1
63	0	11	17140	5279	21529	28	28	0
44	5	26	116174	27101	95757	84	84	1
33	0	25	57635	16373	85584	80	79	1
84	0	38	66198	19716	143983	130	127	1
88	7	44	71701	17753	75851	82	78	1
55	7	30	57793	9028	59238	60	60	1
60	3	40	80444	18653	93163	131	131	1
66	9	34	53855	8828	96037	84	84	1
154	0	47	97668	29498	151511	140	133	1
53	4	30	133824	27563	136368	151	150	1
119	3	31	101481	18293	112642	91	91	1
41	0	23	99645	22530	94728	138	132	1
61	7	36	114789	15977	105499	150	136	1
58	0	36	99052	35082	121527	124	124	1
75	1	30	67654	16116	127766	119	118	1
33	5	25	65553	15849	98958	73	70	1
40	7	39	97500	16026	77900	110	107	1
92	0	34	69112	26569	85646	123	119	1
100	0	31	82753	24785	98579	90	89	1
112	5	31	85323	17569	130767	116	112	1
73	0	33	72654	23825	131741	113	108	1
40	0	25	30727	7869	53907	56	52	1
45	0	33	77873	14975	178812	115	112	1
60	3	35	117478	37791	146761	119	116	1
62	4	42	74007	9605	82036	129	123	1
75	1	43	90183	27295	163253	127	125	1
31	4	30	61542	2746	27032	27	27	1
77	2	33	101494	34461	171975	175	162	1
34	0	13	27570	8098	65990	35	32	0
46	0	32	55813	4787	86572	64	64	1
99	0	36	79215	24919	159676	96	92	1
17	0	0	1423	603	1929	0	0	0
66	2	28	55461	16329	85371	84	83	1
30	1	14	31081	12558	58391	41	41	1
76	0	17	22996	7784	31580	47	47	0
146	2	32	83122	28522	136815	126	120	1
67	10	30	70106	22265	120642	105	105	1
56	6	35	60578	14459	69107	80	79	1
107	0	20	39992	14526	50495	70	65	0
58	5	28	79892	22240	108016	73	70	1
34	4	28	49810	11802	46341	57	55	1
61	1	39	71570	7623	78348	40	39	1
119	2	34	100708	11912	79336	68	67	1
42	2	26	33032	7935	56968	21	21	1
66	0	39	82875	18220	93176	127	127	1
89	8	39	139077	19199	161632	154	152	1
44	3	33	71595	19918	87850	116	113	1
66	0	28	72260	21884	127969	102	99	1
24	0	4	5950	2694	15049	7	7	1
259	8	39	115762	15808	155135	148	141	1
17	5	18	32551	3597	25109	21	21	1
64	3	14	31701	5296	45824	35	35	1
41	1	29	80670	25239	102996	112	109	1
68	5	44	143558	29801	160604	137	133	1
168	1	21	117105	18450	158051	135	123	0
43	1	16	23789	7132	44547	26	26	0
132	5	28	120733	34861	162647	230	230	1
105	0	35	105195	35940	174141	181	166	1
71	12	28	73107	16688	60622	71	68	1
112	8	38	132068	24683	179566	147	147	1
94	8	23	149193	46230	184301	190	179	1
82	8	36	46821	10387	75661	64	61	1
70	8	32	87011	21436	96144	105	101	1
57	2	29	95260	30546	129847	107	108	1
53	0	25	55183	19746	117286	94	90	1
103	5	27	106671	15977	71180	116	114	1
121	8	36	73511	22583	109377	106	103	1
62	2	28	92945	17274	85298	143	142	1
52	5	23	78664	16469	73631	81	79	1
52	12	40	70054	14251	86767	89	88	1
32	6	23	22618	3007	23824	26	25	1
62	7	40	74011	16851	93487	84	83	1
45	2	28	83737	21113	82981	113	113	1
46	0	34	69094	17401	73815	120	118	1
63	4	33	93133	23958	94552	110	110	1
75	3	28	95536	23567	132190	134	129	1
88	6	34	225920	13065	128754	54	51	1
46	2	30	62133	15358	66363	96	93	1
53	0	33	61370	14587	67808	78	76	1
37	1	22	43836	12770	61724	51	49	1
90	0	38	106117	24021	131722	121	118	1
63	5	26	38692	9648	68580	38	38	1
78	2	35	84651	20537	106175	145	141	1
25	0	8	56622	7905	55792	59	58	1
45	0	24	15986	4527	25157	27	27	1
46	5	29	95364	30495	76669	91	91	1
41	0	20	26706	7117	57283	48	48	0
144	1	29	89691	17719	105805	68	63	1
82	0	45	67267	27056	129484	58	56	1
91	1	37	126846	33473	72413	150	144	1
71	1	33	41140	9758	87831	74	73	1
63	2	33	102860	21115	96971	181	168	1
53	6	25	51715	7236	71299	65	64	1
62	1	32	55801	13790	77494	97	97	1
63	4	29	111813	32902	120336	121	117	1
32	2	28	120293	25131	93913	99	100	1
39	3	28	138599	30910	136048	152	149	1
62	0	31	161647	35947	181248	188	187	1
117	10	52	115929	29848	146123	138	127	1
34	0	21	24266	6943	32036	40	37	0
92	9	24	162901	42705	186646	254	245	1
93	7	41	109825	31808	102255	87	87	1
54	0	33	129838	26675	168237	178	177	1
144	0	32	37510	8435	64219	51	49	1
14	4	19	43750	7409	19630	49	49	1
61	4	20	40652	14993	76825	73	73	1
109	0	31	87771	36867	115338	176	177	1
38	0	31	85872	33835	109427	94	94	1
73	0	32	89275	24164	118168	120	117	1
75	1	18	44418	12607	84845	66	60	0
50	0	23	192565	22609	153197	56	55	1
61	1	17	35232	5892	29877	39	39	0
55	0	20	40909	17014	63506	66	64	0
77	0	12	13294	5394	22445	27	26	0
75	4	17	32387	9178	47695	65	64	0
72	0	30	140867	6440	68370	58	58	1
50	4	31	120662	21916	146304	98	95	1
32	4	10	21233	4011	38233	25	25	0
53	3	13	44332	5818	42071	26	26	0
42	0	22	61056	18647	50517	77	76	0
71	0	42	101338	20556	103950	130	129	1
10	0	1	1168	238	5841	11	11	1
35	5	9	13497	70	2341	2	2	0
65	0	32	65567	22392	84396	101	101	1
25	4	11	25162	3913	24610	31	28	1
66	0	25	32334	12237	35753	36	36	0
41	0	36	40735	8388	55515	120	89	1
86	1	31	91413	22120	209056	195	193	1
16	0	0	855	338	6622	4	4	1
42	5	24	97068	11727	115814	89	84	1
19	0	13	44339	3704	11609	24	23	0
19	0	8	14116	3988	13155	39	39	1
45	0	13	10288	3030	18274	14	14	0
65	0	19	65622	13520	72875	78	78	0
35	0	18	16563	1421	10112	15	14	0
95	2	33	76643	20923	142775	106	101	1
49	7	40	110681	20237	68847	83	82	1
37	1	22	29011	3219	17659	24	24	0
64	8	38	92696	3769	20112	37	36	1
38	2	24	94785	12252	61023	77	75	1
34	0	8	8773	1888	13983	16	16	1
32	2	35	83209	14497	65176	56	55	1
65	0	43	93815	28864	132432	132	131	1
52	0	43	86687	21721	112494	144	131	1
62	1	14	34553	4821	45109	40	39	0
65	3	41	105547	33644	170875	153	144	1
83	0	38	103487	15923	180759	143	139	1
95	3	45	213688	42935	214921	220	211	1
29	0	31	71220	18864	100226	79	78	1
18	0	13	23517	4977	32043	50	50	0
33	0	28	56926	7785	54454	39	39	1
247	4	31	91721	17939	78876	95	90	1
139	4	40	115168	23436	170745	169	166	1
29	11	30	111194	325	6940	12	12	1
118	0	16	51009	13539	49025	63	57	0
110	0	37	135777	34538	122037	134	133	1
67	4	30	51513	12198	53782	69	69	1
42	0	35	74163	26924	127748	119	119	1
65	1	32	51633	12716	86839	119	119	1
94	0	27	75345	8172	44830	75	65	1
64	0	20	33416	10855	77395	63	61	0
81	0	18	83305	11932	89324	55	49	0
95	9	31	98952	14300	103300	103	101	1
67	1	31	102372	25515	112283	197	196	1
63	3	21	37238	2805	10901	16	15	1
83	10	39	103772	29402	120691	140	136	1
45	5	41	123969	16440	58106	89	89	1
30	0	13	27142	11221	57140	40	40	0
70	2	32	135400	28732	122422	125	123	1
32	0	18	21399	5250	25899	21	21	0
83	1	39	130115	28608	139296	167	163	1
31	2	14	24874	8092	52678	32	29	0
67	4	7	34988	4473	23853	36	35	0
66	0	17	45549	1572	17306	13	13	0
10	0	0	6023	2065	7953	5	5	1
70	2	30	64466	14817	89455	96	96	1
103	1	37	54990	16714	147866	151	151	1
5	0	0	1644	556	4245	6	6	1
20	0	5	6179	2089	21509	13	13	1
5	0	1	3926	2658	7670	3	3	1
36	1	16	32755	10695	66675	57	56	0
34	0	32	34777	1669	14336	23	23	1
48	2	24	73224	16267	53608	61	57	1
40	0	17	27114	7768	30059	21	14	0
43	3	11	20760	7252	29668	43	43	0
31	6	24	37636	6387	22097	20	20	0
42	0	22	65461	18715	96841	82	72	0
46	2	12	30080	7936	41907	90	87	0
33	0	19	24094	8643	27080	25	21	0
18	2	13	69008	7294	35885	60	56	0
55	1	17	54968	4570	41247	61	59	0
35	1	15	46090	7185	28313	85	82	0
59	2	16	27507	10058	36845	43	43	0
19	1	24	10672	2342	16548	25	25	0
66	0	15	34029	8509	36134	41	38	0
60	1	17	46300	13275	55764	26	25	0
36	3	18	24760	6816	28910	38	38	0
25	0	20	18779	1930	13339	12	12	0
47	0	16	21280	8086	25319	29	29	0
54	0	16	40662	10737	66956	49	47	0
53	0	18	28987	8033	47487	46	45	0
40	1	22	22827	7058	52785	41	40	0
40	4	8	18513	6782	44683	31	30	0
39	0	17	30594	5401	35619	41	41	0
14	0	18	24006	6521	21920	26	25	0
45	0	16	27913	10856	45608	23	23	0
36	7	23	42744	2154	7721	14	14	0
28	2	22	12934	6117	20634	16	16	0
44	0	13	22574	5238	29788	25	26	0
30	7	13	41385	4820	31931	21	21	0
22	3	16	18653	5615	37754	32	27	0
17	0	16	18472	4272	32505	9	9	0
31	0	20	30976	8702	40557	35	33	0
55	6	22	63339	15340	94238	42	42	0
54	2	17	25568	8030	44197	68	68	0
21	0	18	33747	9526	43228	32	32	0
14	0	17	4154	1278	4103	6	6	0
81	3	12	19474	4236	44144	68	67	0
35	0	7	35130	3023	32868	33	33	0
43	1	17	39067	7196	27640	84	77	0
46	1	14	13310	3394	14063	46	46	0
30	0	23	65892	6371	28990	30	30	0
23	1	17	4143	1574	4694	0	0	0
38	0	14	28579	9620	42648	36	36	0
54	0	15	51776	6978	64329	47	46	0
20	0	17	21152	4911	21928	20	18	0
53	0	21	38084	8645	25836	50	48	0
45	0	18	27717	8987	22779	30	29	0
39	0	18	32928	5544	40820	30	28	0
20	0	17	11342	3083	27530	34	34	0
24	0	17	19499	6909	32378	33	33	0
31	0	16	16380	3189	10824	34	34	0
35	0	15	36874	6745	39613	37	33	0
151	0	21	48259	16724	60865	83	80	0
52	0	16	16734	4850	19787	32	32	0
30	2	14	28207	7025	20107	30	30	0
31	0	15	30143	6047	36605	43	41	0
29	1	17	41369	7377	40961	41	41	0
57	1	15	45833	9078	48231	51	51	0
40	0	15	29156	4605	39725	19	18	0
44	0	10	35944	3238	21455	37	34	0
25	0	6	36278	8100	23430	33	31	0
77	0	22	45588	9653	62991	41	39	0
35	0	21	45097	8914	49363	54	54	0
11	0	1	3895	786	9604	14	14	0
63	1	18	28394	6700	24552	25	24	0
44	0	17	18632	5788	31493	25	24	0
19	0	4	2325	593	3439	8	8	0
13	0	10	25139	4506	19555	26	26	0
42	0	16	27975	6382	21228	20	19	0
38	1	16	14483	5621	23177	11	11	0
29	0	9	13127	3997	22094	14	14	0
20	0	16	5839	520	2342	3	1	0
27	0	17	24069	8891	38798	40	39	0
20	0	7	3738	999	3255	5	5	0
19	0	15	18625	7067	24261	38	37	0
37	0	14	36341	4639	18511	32	32	0
26	0	14	24548	5654	40798	41	38	0
42	0	18	21792	6928	28893	46	47	0
49	0	12	26263	1514	21425	47	47	0
30	0	16	23686	9238	50276	37	37	0
49	0	21	49303	8204	37643	51	51	0
67	1	19	25659	5926	30377	49	45	0
28	0	16	28904	5785	27126	21	21	0
19	0	1	2781	4	13	1	1	0
49	1	16	29236	5930	42097	44	42	0
27	0	10	19546	3710	24451	26	26	0
30	6	19	22818	705	14335	21	21	0
22	3	12	32689	443	5084	4	4	0
12	1	2	5752	2416	9927	10	10	0
31	2	14	22197	7747	43527	43	43	0
20	0	17	20055	5432	27184	34	34	0
20	0	19	25272	4913	21610	32	31	0
39	0	14	82206	2650	20484	20	19	0
29	3	11	32073	2370	20156	34	34	0
16	1	4	5444	775	6012	6	6	0
27	0	16	20154	5576	18475	12	11	0
21	0	20	36944	1352	12645	24	24	0
19	1	12	8019	3080	11017	16	16	0
35	0	15	30884	10205	37623	72	72	0
14	0	16	19540	6095	35873	27	21	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156535&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]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156535&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156535&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Multiple Linear Regression - Estimated Regression Equation
totsize[t] = + 528.279951966106 + 9.5829773538428logins[t] + 2014.61748089442shared_compendiums[t] + 539.619440965055compendiums_reviewed[t] + 1.14707552171977totrevisions[t] + 0.252763603144547totseconds[t] + 72.9180606729002tothyperlinks[t] + 4.36169994355521totblogs[t] + 5358.7323750144course_cid[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
totsize[t] =  +  528.279951966106 +  9.5829773538428logins[t] +  2014.61748089442shared_compendiums[t] +  539.619440965055compendiums_reviewed[t] +  1.14707552171977totrevisions[t] +  0.252763603144547totseconds[t] +  72.9180606729002tothyperlinks[t] +  4.36169994355521totblogs[t] +  5358.7323750144course_cid[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156535&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]totsize[t] =  +  528.279951966106 +  9.5829773538428logins[t] +  2014.61748089442shared_compendiums[t] +  539.619440965055compendiums_reviewed[t] +  1.14707552171977totrevisions[t] +  0.252763603144547totseconds[t] +  72.9180606729002tothyperlinks[t] +  4.36169994355521totblogs[t] +  5358.7323750144course_cid[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156535&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156535&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
totsize[t] = + 528.279951966106 + 9.5829773538428logins[t] + 2014.61748089442shared_compendiums[t] + 539.619440965055compendiums_reviewed[t] + 1.14707552171977totrevisions[t] + 0.252763603144547totseconds[t] + 72.9180606729002tothyperlinks[t] + 4.36169994355521totblogs[t] + 5358.7323750144course_cid[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)528.2799519661063045.4655030.17350.8624120.431206
logins9.582977353842845.9263870.20870.8348660.417433
shared_compendiums2014.61748089442482.3503324.17674e-052e-05
compendiums_reviewed539.619440965055191.864242.81250.0052630.002632
totrevisions1.147075521719770.2781824.12354.9e-052.5e-05
totseconds0.2527636031445470.0611134.1364.7e-052.3e-05
tothyperlinks72.9180606729002405.1389140.180.8572960.428648
totblogs4.36169994355521417.1296390.01050.9916650.495832
course_cid5358.73237501443453.8215591.55150.1219030.060951

\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) & 528.279951966106 & 3045.465503 & 0.1735 & 0.862412 & 0.431206 \tabularnewline
logins & 9.5829773538428 & 45.926387 & 0.2087 & 0.834866 & 0.417433 \tabularnewline
shared_compendiums & 2014.61748089442 & 482.350332 & 4.1767 & 4e-05 & 2e-05 \tabularnewline
compendiums_reviewed & 539.619440965055 & 191.86424 & 2.8125 & 0.005263 & 0.002632 \tabularnewline
totrevisions & 1.14707552171977 & 0.278182 & 4.1235 & 4.9e-05 & 2.5e-05 \tabularnewline
totseconds & 0.252763603144547 & 0.061113 & 4.136 & 4.7e-05 & 2.3e-05 \tabularnewline
tothyperlinks & 72.9180606729002 & 405.138914 & 0.18 & 0.857296 & 0.428648 \tabularnewline
totblogs & 4.36169994355521 & 417.129639 & 0.0105 & 0.991665 & 0.495832 \tabularnewline
course_cid & 5358.7323750144 & 3453.821559 & 1.5515 & 0.121903 & 0.060951 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156535&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]528.279951966106[/C][C]3045.465503[/C][C]0.1735[/C][C]0.862412[/C][C]0.431206[/C][/ROW]
[ROW][C]logins[/C][C]9.5829773538428[/C][C]45.926387[/C][C]0.2087[/C][C]0.834866[/C][C]0.417433[/C][/ROW]
[ROW][C]shared_compendiums[/C][C]2014.61748089442[/C][C]482.350332[/C][C]4.1767[/C][C]4e-05[/C][C]2e-05[/C][/ROW]
[ROW][C]compendiums_reviewed[/C][C]539.619440965055[/C][C]191.86424[/C][C]2.8125[/C][C]0.005263[/C][C]0.002632[/C][/ROW]
[ROW][C]totrevisions[/C][C]1.14707552171977[/C][C]0.278182[/C][C]4.1235[/C][C]4.9e-05[/C][C]2.5e-05[/C][/ROW]
[ROW][C]totseconds[/C][C]0.252763603144547[/C][C]0.061113[/C][C]4.136[/C][C]4.7e-05[/C][C]2.3e-05[/C][/ROW]
[ROW][C]tothyperlinks[/C][C]72.9180606729002[/C][C]405.138914[/C][C]0.18[/C][C]0.857296[/C][C]0.428648[/C][/ROW]
[ROW][C]totblogs[/C][C]4.36169994355521[/C][C]417.129639[/C][C]0.0105[/C][C]0.991665[/C][C]0.495832[/C][/ROW]
[ROW][C]course_cid[/C][C]5358.7323750144[/C][C]3453.821559[/C][C]1.5515[/C][C]0.121903[/C][C]0.060951[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156535&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156535&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)528.2799519661063045.4655030.17350.8624120.431206
logins9.582977353842845.9263870.20870.8348660.417433
shared_compendiums2014.61748089442482.3503324.17674e-052e-05
compendiums_reviewed539.619440965055191.864242.81250.0052630.002632
totrevisions1.147075521719770.2781824.12354.9e-052.5e-05
totseconds0.2527636031445470.0611134.1364.7e-052.3e-05
tothyperlinks72.9180606729002405.1389140.180.8572960.428648
totblogs4.36169994355521417.1296390.01050.9916650.495832
course_cid5358.73237501443453.8215591.55150.1219030.060951







Multiple Linear Regression - Regression Statistics
Multiple R0.871654572253717
R-squared0.75978169333081
Adjusted R-squared0.752918313140261
F-TEST (value)110.700802263165
F-TEST (DF numerator)8
F-TEST (DF denominator)280
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation20093.8967637112
Sum Squared Residuals113054112402.191

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.871654572253717 \tabularnewline
R-squared & 0.75978169333081 \tabularnewline
Adjusted R-squared & 0.752918313140261 \tabularnewline
F-TEST (value) & 110.700802263165 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 280 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 20093.8967637112 \tabularnewline
Sum Squared Residuals & 113054112402.191 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156535&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.871654572253717[/C][/ROW]
[ROW][C]R-squared[/C][C]0.75978169333081[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.752918313140261[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]110.700802263165[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]280[/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]20093.8967637112[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]113054112402.191[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156535&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156535&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.871654572253717
R-squared0.75978169333081
Adjusted R-squared0.752918313140261
F-TEST (value)110.700802263165
F-TEST (DF numerator)8
F-TEST (DF denominator)280
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation20093.8967637112
Sum Squared Residuals113054112402.191







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1112285104509.2228372957775.77716270472
28478683365.91534109821420.08465890178
38312396641.6086502963-13518.6086502963
410119398914.15979898042278.84020101963
53836154820.543197438-16459.543197438
66850450570.150908402417933.8490915976
7119182119422.819215243-240.819215242889
82280719349.17662025833457.82337974165
91714020728.8139643922-3588.81396439215
1011617492194.134152335223979.8658476648
115763566285.3434817972-8650.34348179724
126619896240.2078194722-30042.2078194722
137170190431.7894728253-18730.7894728253
145779366670.7754468045-8877.77544680454
158044489158.8849566465-8714.88495664647
165385583890.647905913-30035.647905913
1797668115646.439167252-17978.4391672519
18133824108392.55507118225431.4449288177
1910148186287.15026501315193.849734987
209964579117.000409116920527.9995908831
2111478996524.229458489718264.7705415103
2299052106411.121057006-7359.12105700612
236765484781.7297791814-17127.7297791814
246555378588.1420171411-13035.1420171411
259750087978.8175490539521.18245094702
266911286728.5120838861-17616.5120838861
278275383871.7795280297-1118.77952802967
288532395914.7092302319-10591.7092302319
297265493733.2198224388-21079.2198224388
303072746723.1020751338-15996.1020751338
317787395374.3965740482-17501.3965740482
32117478121020.700460607-3542.70046060743
337400778899.9376205746-4892.9376205746
3490183114203.638138811-24020.638138811
356154242500.266416969119041.7335830309
36101494124927.224310244-23433.2243102439
372757036529.7481826831-8959.74818268308
385581355914.8572494944-101.857249494411
3979215102607.693200602-23392.693200602
4014231870.45809704428-447.458097044282
415546172454.4840911984-16993.4840911984
423108148076.3554402458-16995.3554402457
432299630973.375924609-7977.37592460895
4483122105593.004126037-22471.0041260366
4570106107011.747813967-36905.7478139667
466057877629.3628183684-17051.3628183684
473999247159.5392608477-7167.53926084773
487989290067.0671504767-10175.0671504767
494981059027.9742235194-9217.9742235194
507157061165.857830049910404.1421699501
5110070868371.561442465632336.4385575344
523303249473.1939844527-16441.1939844527
538287581830.39412059161044.60587940841
54139077118671.74473626920405.2552637307
557159584164.0572346206-12569.0572346206
567226086946.7899105234-14686.7899105234
57595015710.5007908835-9760.50079088348
58115762114283.4255992241478.57440077582
593255137931.7072197669-5380.70721976694
603170140461.19042892-8760.19042892002
618067087570.4229187424-6900.42291874241
62143558125703.72134085417854.2786591459
6311710586978.356788799630126.6432112004
642378933038.95314073-9249.95314073001
65120733131208.18355429-10475.1835542901
66105195124944.517421139-19749.517421139
677310785791.3671970839-12684.3671970839
68132068128643.923469923424.07653007994
69149193149565.061197589-372.061197588837
704682178187.8961931383-31366.8961931383
718701196929.9255090545-9918.92550905453
7295260102243.901335791-6983.90133579131
735518379428.032059323-24245.032059323
7410667176791.139018922229879.8609810778
7573511104319.292962345-30808.2929623451
769294578041.192683149514903.8073168505
777866472623.02253643356040.97746356651
787005497297.5643677079-27243.5643677079
792261842168.6278810776-19550.6278810776
807401191614.8757032947-17603.8757032947
818373779382.22060898044354.7793910196
826909472557.7446717171-3463.7446717171
839313392238.3645973926894.635402607378
849553698538.5613611582-3002.5613611582
8522592088855.9688362968137064.031163703
866213368342.3562534006-6209.35625340059
876137064093.2346441291-2723.2346441291
884383654310.1071156059-10474.1071156059
8910611797441.21342089548675.78657910456
903869261932.0762104668-23240.0762104668
918465191133.183999189-6482.18399918897
925662238168.505410809718453.4945891904
931598632907.2512788418-16921.2512788418
949536493441.5394181471922.46058185295
952670638065.7933193733-11359.7933193733
968969177232.441757077412458.5582429226
976726799193.311734509-31926.311734509
9812684697004.823688620529841.1763113795
994114065497.4463062489-24357.4463062489
10010286090989.589987863211870.4100121368
1015171563313.9543921204-11598.9543921204
1025580168665.5674010902-12864.5674010902
103111813107689.217610284123.78238972021
10412029385552.248110539934740.7518894601
105138599108991.47080432329607.5291956769
106161647124780.41421078936866.5857892111
107115929137003.720836781-21074.7208367812
1082426631325.8949047295-7059.89490472953
109162901153604.0496793939296.95032060735
110109825112060.808274756-2235.80827475578
111129838111085.80018982418752.1998101757
1123751054375.1354244136-16865.1354244136
1134375041579.55365220362170.44634779641
1144065267580.5223221693-26928.5223221693
11587771108707.840815634-20936.8408156342
1168587296714.1287129768-10842.1287129768
1178927590701.3803220581-1426.38032205807
1184441853955.9736839146-9537.97368391464
11919256587757.5694129443104807.430587056
1203523229625.28735701515606.71264298486
1214090952507.8216343652-11598.8216343652
1221329421684.3987732292-8390.39877322918
1233238746081.2456039372-13694.2456039372
12414086751916.409948031288950.5900519688
125120662100832.79855721919829.2014427808
1262123330486.4243325722-9253.42433257215
1274433233412.059636236410919.9403637636
1286105652906.94876314388149.05123685617
12910133889127.488391178512210.5116088215
13011689121.9350884016-7953.9350884016
1311349716619.9209352229-3122.9209352229
1326556778600.5359214603-13033.5359214603
1332516233212.4768041761-8050.47680417608
1343233440507.1341261503-8173.1341261503
1354073558498.4137537094-17763.4137537094
13691413118729.856809971-27316.8568099715
1378558410.97111347228-7555.97111347228
1389706878894.860136412418173.1398635876
1394433916758.862210441327580.1377895587
1401411621299.5974684507-7183.59746845067
1411028817151.1242287395-6863.12422873947
1426562251360.372819195614261.6271808044
1431656315917.6086773863645.391322613681
1447664396892.5023947631-20249.5023947631
14511068189068.919772139821612.0802278602
1462901124779.79812332434231.20187667566
1479269655384.700152124137311.2998478759
1489478558651.447825756936133.5521742431
149877317466.337302372-8693.337302372
1508320966536.162329367716672.8376706323
15193815106493.285868464-12678.2858684642
1528668794010.5627197988-7323.5627197988
1533455330710.50739148263842.49260851743
154105547128245.892992121-22698.8929921208
155103487102175.6768455491311.32315445055
156213688157660.30837430256027.6916256981
1577122075965.7782594021-4745.77825940215
1582351725388.1133148638-1871.11331486377
1595692647020.47777294229905.52222705783
1609172180874.818831479710846.1811685203
161115168119950.471531635-4782.47153163498
16211119447568.630266811863625.3697331882
1635100943057.42818706117951.57181293886
164135777107722.3915803828054.6084196199
1655151363694.5877630105-12181.5877630105
1667416397546.3754442696-23383.3754442696
1675163371524.5878277725-19891.5878277725
1687534547815.195643560827529.8043564392
1693341648808.024694503-15392.024694503
1708330551506.628901685831798.3710983141
1719895292121.90728259436830.09271740575
17210237298140.33069055634231.66930944369
1733723831071.63794944446166.36205055559
174103772122908.058657184-19136.0586571835
17512396978938.632988197445030.3670118026
1762714238236.2591426823-11094.2591426823
177135400101407.72420580433992.275794196
1782139924739.431184475-3340.43118447503
179130115110654.94373803719460.0562619632
1802487437466.3428333356-12592.3428333356
1813498826943.89416171498044.1058382851
1824554917516.453477902628032.5465220974
183602310748.1807917611-4725.18079176111
1846446673801.682076287-9335.68207628696
1855499097071.2028567083-42081.2028567083
18616448109.36126287324-6465.36126287324
187617917614.3390718052-11435.3390718052
188392611694.009509414-7768.00950941396
1893275545043.3662726897-12288.3662726897
1903477730796.17822250193980.82177749808
1917322460233.34413193312990.655868067
1922711428185.7764155075-1071.77641550753
1932076032060.626239592-11300.626239592
1943763640321.2076267014-2685.20762670143
1956546165041.114554279419.885445720963
1963008038111.6141766093-8031.61417660931
1972409429770.8469059944-5676.84690599442
1986900833801.59083014935206.409169851
1995496832616.709154606922351.2908453931
2004609032926.52132667713163.478673323
2012750737930.2118948984-10423.2118948984
2021067224477.0175778599-13805.0175778599
2033402931304.25880757812724.74119242188
2044630043618.85576316382681.14423683624
2052476034692.7629431348-9932.76294313481
2061877918073.069791775705.930208224993
2072128027528.6783375576-6248.67833755763
2084066242697.8463436851-2035.84634368513
2092898735517.2778660042-6530.27786600415
2102282739400.1385378596-16573.1385378596
2111851334752.0376441958-16239.0376441958
2123059428442.55842366072151.44157633933
2132400625401.1613064383-1395.16130643827
2142791335351.5537585147-7438.55375851469
2154274432891.14174745559852.85825254451
2161293430166.1273044015-17232.1273044015
2172257423439.0431966738-865.043196673751
2184138537155.91797103144229.08202896856
2191865333851.6789194593-15198.6789194593
2201847223137.0070169708-4665.00701697076
2213097634546.993933664-3570.99393366398
2226333969676.5011752334-6337.5011752334
2232556839885.9593167766-14317.9593167766
2243374734769.1312101294-1022.13121012936
225415412802.7022754845-8648.70227548452
2261947435091.4572810845-15617.4572810845
2273513018966.695756762816163.3042432372
2283906733830.20539286985236.7946071302
2291331021541.0444247437-8231.04442474367
2306589230181.044237308435710.9557626916
231414314928.8056327523-10785.8056327523
2322857933043.9053129681-4464.90531296811
2335177637032.162209825414743.8377901746
2342115222606.2299848103-1454.22998481031
2353808432670.31897903155413.6810209685
2362771729053.1648185353-1336.16481853533
2373292829602.03239751833325.96760248168
2381134223015.9976844398-11673.9976844398
2391949928591.1587273833-9092.15872738332
2401638018480.7122455365-2100.71224553652
2413687429549.62912222587324.37087777417
2424825954276.6005546319-6017.60055463188
2431673422698.2078652954-5964.2078652954
2442820727858.5925348835348.407465116548
2453014328422.72754397711720.27245602289
2464136933978.23052993317390.7694700669
2474583337728.87947738138104.12052261869
2482915625793.16132480143362.8386751986
2493594418329.665052958817614.3349470412
2503627821760.642679665314517.3573203347
2514558843292.09583166982295.90416833016
2524509739071.00043553966025.99956446037
25338955584.37179712577-1689.37179712577
2542839428678.6652389188-284.665238918804
2551863226650.6510409542-8018.65104095419
25623255036.5421860749-2711.5421860749
2572513918169.84140360536969.15859639465
2582797523792.21131582194182.78868417806
2591448324697.0525321964-10214.0525321964
2601312716914.0978207329-3787.09782073295
261583910765.4180663049-4926.41806630491
2622406933052.750300053-8983.75030005305
26337386852.34836331417-3114.34836331417
2641862525975.5978275302-7350.59782753015
2653634120910.665030362315430.3349696377
2662454828285.3091030156-3737.30910301559
2672179229453.1836266289-7661.18362662895
2682626318257.56042011418005.4395798859
2692368635613.6580521736-11927.6580521736
2704930335196.509787368914106.4902126311
2712565931682.7572787694-6023.75727876938
2722890424545.6867383084358.31326169201
27327811335.129952198391445.87004780161
2742923632480.7076912508-3244.70769125085
2751954618628.4615722659917.538427734096
2762281829211.1730031191-6393.17300311906
2773268915360.714844989117328.2851550109
27857529790.44839809219-4038.44839809219
2792219735620.7245125782-13423.7245125782
2802005525623.0218782715-5568.02187827153
2812527224539.1030193249732.896980675089
2828220618215.281534032663990.7184659674
2833207323226.63662094328846.36337905676
28454447726.97970951881-2282.97970951881
2852015421409.8275006196-1255.82750061959
2863694418123.667417620818820.3325823792
287801916754.5726867679-8735.57268676785
2883088435737.7492784687-4853.74927846875
2891954027415.5500678301-7875.55006783007

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 112285 & 104509.222837295 & 7775.77716270472 \tabularnewline
2 & 84786 & 83365.9153410982 & 1420.08465890178 \tabularnewline
3 & 83123 & 96641.6086502963 & -13518.6086502963 \tabularnewline
4 & 101193 & 98914.1597989804 & 2278.84020101963 \tabularnewline
5 & 38361 & 54820.543197438 & -16459.543197438 \tabularnewline
6 & 68504 & 50570.1509084024 & 17933.8490915976 \tabularnewline
7 & 119182 & 119422.819215243 & -240.819215242889 \tabularnewline
8 & 22807 & 19349.1766202583 & 3457.82337974165 \tabularnewline
9 & 17140 & 20728.8139643922 & -3588.81396439215 \tabularnewline
10 & 116174 & 92194.1341523352 & 23979.8658476648 \tabularnewline
11 & 57635 & 66285.3434817972 & -8650.34348179724 \tabularnewline
12 & 66198 & 96240.2078194722 & -30042.2078194722 \tabularnewline
13 & 71701 & 90431.7894728253 & -18730.7894728253 \tabularnewline
14 & 57793 & 66670.7754468045 & -8877.77544680454 \tabularnewline
15 & 80444 & 89158.8849566465 & -8714.88495664647 \tabularnewline
16 & 53855 & 83890.647905913 & -30035.647905913 \tabularnewline
17 & 97668 & 115646.439167252 & -17978.4391672519 \tabularnewline
18 & 133824 & 108392.555071182 & 25431.4449288177 \tabularnewline
19 & 101481 & 86287.150265013 & 15193.849734987 \tabularnewline
20 & 99645 & 79117.0004091169 & 20527.9995908831 \tabularnewline
21 & 114789 & 96524.2294584897 & 18264.7705415103 \tabularnewline
22 & 99052 & 106411.121057006 & -7359.12105700612 \tabularnewline
23 & 67654 & 84781.7297791814 & -17127.7297791814 \tabularnewline
24 & 65553 & 78588.1420171411 & -13035.1420171411 \tabularnewline
25 & 97500 & 87978.817549053 & 9521.18245094702 \tabularnewline
26 & 69112 & 86728.5120838861 & -17616.5120838861 \tabularnewline
27 & 82753 & 83871.7795280297 & -1118.77952802967 \tabularnewline
28 & 85323 & 95914.7092302319 & -10591.7092302319 \tabularnewline
29 & 72654 & 93733.2198224388 & -21079.2198224388 \tabularnewline
30 & 30727 & 46723.1020751338 & -15996.1020751338 \tabularnewline
31 & 77873 & 95374.3965740482 & -17501.3965740482 \tabularnewline
32 & 117478 & 121020.700460607 & -3542.70046060743 \tabularnewline
33 & 74007 & 78899.9376205746 & -4892.9376205746 \tabularnewline
34 & 90183 & 114203.638138811 & -24020.638138811 \tabularnewline
35 & 61542 & 42500.2664169691 & 19041.7335830309 \tabularnewline
36 & 101494 & 124927.224310244 & -23433.2243102439 \tabularnewline
37 & 27570 & 36529.7481826831 & -8959.74818268308 \tabularnewline
38 & 55813 & 55914.8572494944 & -101.857249494411 \tabularnewline
39 & 79215 & 102607.693200602 & -23392.693200602 \tabularnewline
40 & 1423 & 1870.45809704428 & -447.458097044282 \tabularnewline
41 & 55461 & 72454.4840911984 & -16993.4840911984 \tabularnewline
42 & 31081 & 48076.3554402458 & -16995.3554402457 \tabularnewline
43 & 22996 & 30973.375924609 & -7977.37592460895 \tabularnewline
44 & 83122 & 105593.004126037 & -22471.0041260366 \tabularnewline
45 & 70106 & 107011.747813967 & -36905.7478139667 \tabularnewline
46 & 60578 & 77629.3628183684 & -17051.3628183684 \tabularnewline
47 & 39992 & 47159.5392608477 & -7167.53926084773 \tabularnewline
48 & 79892 & 90067.0671504767 & -10175.0671504767 \tabularnewline
49 & 49810 & 59027.9742235194 & -9217.9742235194 \tabularnewline
50 & 71570 & 61165.8578300499 & 10404.1421699501 \tabularnewline
51 & 100708 & 68371.5614424656 & 32336.4385575344 \tabularnewline
52 & 33032 & 49473.1939844527 & -16441.1939844527 \tabularnewline
53 & 82875 & 81830.3941205916 & 1044.60587940841 \tabularnewline
54 & 139077 & 118671.744736269 & 20405.2552637307 \tabularnewline
55 & 71595 & 84164.0572346206 & -12569.0572346206 \tabularnewline
56 & 72260 & 86946.7899105234 & -14686.7899105234 \tabularnewline
57 & 5950 & 15710.5007908835 & -9760.50079088348 \tabularnewline
58 & 115762 & 114283.425599224 & 1478.57440077582 \tabularnewline
59 & 32551 & 37931.7072197669 & -5380.70721976694 \tabularnewline
60 & 31701 & 40461.19042892 & -8760.19042892002 \tabularnewline
61 & 80670 & 87570.4229187424 & -6900.42291874241 \tabularnewline
62 & 143558 & 125703.721340854 & 17854.2786591459 \tabularnewline
63 & 117105 & 86978.3567887996 & 30126.6432112004 \tabularnewline
64 & 23789 & 33038.95314073 & -9249.95314073001 \tabularnewline
65 & 120733 & 131208.18355429 & -10475.1835542901 \tabularnewline
66 & 105195 & 124944.517421139 & -19749.517421139 \tabularnewline
67 & 73107 & 85791.3671970839 & -12684.3671970839 \tabularnewline
68 & 132068 & 128643.92346992 & 3424.07653007994 \tabularnewline
69 & 149193 & 149565.061197589 & -372.061197588837 \tabularnewline
70 & 46821 & 78187.8961931383 & -31366.8961931383 \tabularnewline
71 & 87011 & 96929.9255090545 & -9918.92550905453 \tabularnewline
72 & 95260 & 102243.901335791 & -6983.90133579131 \tabularnewline
73 & 55183 & 79428.032059323 & -24245.032059323 \tabularnewline
74 & 106671 & 76791.1390189222 & 29879.8609810778 \tabularnewline
75 & 73511 & 104319.292962345 & -30808.2929623451 \tabularnewline
76 & 92945 & 78041.1926831495 & 14903.8073168505 \tabularnewline
77 & 78664 & 72623.0225364335 & 6040.97746356651 \tabularnewline
78 & 70054 & 97297.5643677079 & -27243.5643677079 \tabularnewline
79 & 22618 & 42168.6278810776 & -19550.6278810776 \tabularnewline
80 & 74011 & 91614.8757032947 & -17603.8757032947 \tabularnewline
81 & 83737 & 79382.2206089804 & 4354.7793910196 \tabularnewline
82 & 69094 & 72557.7446717171 & -3463.7446717171 \tabularnewline
83 & 93133 & 92238.3645973926 & 894.635402607378 \tabularnewline
84 & 95536 & 98538.5613611582 & -3002.5613611582 \tabularnewline
85 & 225920 & 88855.9688362968 & 137064.031163703 \tabularnewline
86 & 62133 & 68342.3562534006 & -6209.35625340059 \tabularnewline
87 & 61370 & 64093.2346441291 & -2723.2346441291 \tabularnewline
88 & 43836 & 54310.1071156059 & -10474.1071156059 \tabularnewline
89 & 106117 & 97441.2134208954 & 8675.78657910456 \tabularnewline
90 & 38692 & 61932.0762104668 & -23240.0762104668 \tabularnewline
91 & 84651 & 91133.183999189 & -6482.18399918897 \tabularnewline
92 & 56622 & 38168.5054108097 & 18453.4945891904 \tabularnewline
93 & 15986 & 32907.2512788418 & -16921.2512788418 \tabularnewline
94 & 95364 & 93441.539418147 & 1922.46058185295 \tabularnewline
95 & 26706 & 38065.7933193733 & -11359.7933193733 \tabularnewline
96 & 89691 & 77232.4417570774 & 12458.5582429226 \tabularnewline
97 & 67267 & 99193.311734509 & -31926.311734509 \tabularnewline
98 & 126846 & 97004.8236886205 & 29841.1763113795 \tabularnewline
99 & 41140 & 65497.4463062489 & -24357.4463062489 \tabularnewline
100 & 102860 & 90989.5899878632 & 11870.4100121368 \tabularnewline
101 & 51715 & 63313.9543921204 & -11598.9543921204 \tabularnewline
102 & 55801 & 68665.5674010902 & -12864.5674010902 \tabularnewline
103 & 111813 & 107689.21761028 & 4123.78238972021 \tabularnewline
104 & 120293 & 85552.2481105399 & 34740.7518894601 \tabularnewline
105 & 138599 & 108991.470804323 & 29607.5291956769 \tabularnewline
106 & 161647 & 124780.414210789 & 36866.5857892111 \tabularnewline
107 & 115929 & 137003.720836781 & -21074.7208367812 \tabularnewline
108 & 24266 & 31325.8949047295 & -7059.89490472953 \tabularnewline
109 & 162901 & 153604.049679393 & 9296.95032060735 \tabularnewline
110 & 109825 & 112060.808274756 & -2235.80827475578 \tabularnewline
111 & 129838 & 111085.800189824 & 18752.1998101757 \tabularnewline
112 & 37510 & 54375.1354244136 & -16865.1354244136 \tabularnewline
113 & 43750 & 41579.5536522036 & 2170.44634779641 \tabularnewline
114 & 40652 & 67580.5223221693 & -26928.5223221693 \tabularnewline
115 & 87771 & 108707.840815634 & -20936.8408156342 \tabularnewline
116 & 85872 & 96714.1287129768 & -10842.1287129768 \tabularnewline
117 & 89275 & 90701.3803220581 & -1426.38032205807 \tabularnewline
118 & 44418 & 53955.9736839146 & -9537.97368391464 \tabularnewline
119 & 192565 & 87757.5694129443 & 104807.430587056 \tabularnewline
120 & 35232 & 29625.2873570151 & 5606.71264298486 \tabularnewline
121 & 40909 & 52507.8216343652 & -11598.8216343652 \tabularnewline
122 & 13294 & 21684.3987732292 & -8390.39877322918 \tabularnewline
123 & 32387 & 46081.2456039372 & -13694.2456039372 \tabularnewline
124 & 140867 & 51916.4099480312 & 88950.5900519688 \tabularnewline
125 & 120662 & 100832.798557219 & 19829.2014427808 \tabularnewline
126 & 21233 & 30486.4243325722 & -9253.42433257215 \tabularnewline
127 & 44332 & 33412.0596362364 & 10919.9403637636 \tabularnewline
128 & 61056 & 52906.9487631438 & 8149.05123685617 \tabularnewline
129 & 101338 & 89127.4883911785 & 12210.5116088215 \tabularnewline
130 & 1168 & 9121.9350884016 & -7953.9350884016 \tabularnewline
131 & 13497 & 16619.9209352229 & -3122.9209352229 \tabularnewline
132 & 65567 & 78600.5359214603 & -13033.5359214603 \tabularnewline
133 & 25162 & 33212.4768041761 & -8050.47680417608 \tabularnewline
134 & 32334 & 40507.1341261503 & -8173.1341261503 \tabularnewline
135 & 40735 & 58498.4137537094 & -17763.4137537094 \tabularnewline
136 & 91413 & 118729.856809971 & -27316.8568099715 \tabularnewline
137 & 855 & 8410.97111347228 & -7555.97111347228 \tabularnewline
138 & 97068 & 78894.8601364124 & 18173.1398635876 \tabularnewline
139 & 44339 & 16758.8622104413 & 27580.1377895587 \tabularnewline
140 & 14116 & 21299.5974684507 & -7183.59746845067 \tabularnewline
141 & 10288 & 17151.1242287395 & -6863.12422873947 \tabularnewline
142 & 65622 & 51360.3728191956 & 14261.6271808044 \tabularnewline
143 & 16563 & 15917.6086773863 & 645.391322613681 \tabularnewline
144 & 76643 & 96892.5023947631 & -20249.5023947631 \tabularnewline
145 & 110681 & 89068.9197721398 & 21612.0802278602 \tabularnewline
146 & 29011 & 24779.7981233243 & 4231.20187667566 \tabularnewline
147 & 92696 & 55384.7001521241 & 37311.2998478759 \tabularnewline
148 & 94785 & 58651.4478257569 & 36133.5521742431 \tabularnewline
149 & 8773 & 17466.337302372 & -8693.337302372 \tabularnewline
150 & 83209 & 66536.1623293677 & 16672.8376706323 \tabularnewline
151 & 93815 & 106493.285868464 & -12678.2858684642 \tabularnewline
152 & 86687 & 94010.5627197988 & -7323.5627197988 \tabularnewline
153 & 34553 & 30710.5073914826 & 3842.49260851743 \tabularnewline
154 & 105547 & 128245.892992121 & -22698.8929921208 \tabularnewline
155 & 103487 & 102175.676845549 & 1311.32315445055 \tabularnewline
156 & 213688 & 157660.308374302 & 56027.6916256981 \tabularnewline
157 & 71220 & 75965.7782594021 & -4745.77825940215 \tabularnewline
158 & 23517 & 25388.1133148638 & -1871.11331486377 \tabularnewline
159 & 56926 & 47020.4777729422 & 9905.52222705783 \tabularnewline
160 & 91721 & 80874.8188314797 & 10846.1811685203 \tabularnewline
161 & 115168 & 119950.471531635 & -4782.47153163498 \tabularnewline
162 & 111194 & 47568.6302668118 & 63625.3697331882 \tabularnewline
163 & 51009 & 43057.4281870611 & 7951.57181293886 \tabularnewline
164 & 135777 & 107722.39158038 & 28054.6084196199 \tabularnewline
165 & 51513 & 63694.5877630105 & -12181.5877630105 \tabularnewline
166 & 74163 & 97546.3754442696 & -23383.3754442696 \tabularnewline
167 & 51633 & 71524.5878277725 & -19891.5878277725 \tabularnewline
168 & 75345 & 47815.1956435608 & 27529.8043564392 \tabularnewline
169 & 33416 & 48808.024694503 & -15392.024694503 \tabularnewline
170 & 83305 & 51506.6289016858 & 31798.3710983141 \tabularnewline
171 & 98952 & 92121.9072825943 & 6830.09271740575 \tabularnewline
172 & 102372 & 98140.3306905563 & 4231.66930944369 \tabularnewline
173 & 37238 & 31071.6379494444 & 6166.36205055559 \tabularnewline
174 & 103772 & 122908.058657184 & -19136.0586571835 \tabularnewline
175 & 123969 & 78938.6329881974 & 45030.3670118026 \tabularnewline
176 & 27142 & 38236.2591426823 & -11094.2591426823 \tabularnewline
177 & 135400 & 101407.724205804 & 33992.275794196 \tabularnewline
178 & 21399 & 24739.431184475 & -3340.43118447503 \tabularnewline
179 & 130115 & 110654.943738037 & 19460.0562619632 \tabularnewline
180 & 24874 & 37466.3428333356 & -12592.3428333356 \tabularnewline
181 & 34988 & 26943.8941617149 & 8044.1058382851 \tabularnewline
182 & 45549 & 17516.4534779026 & 28032.5465220974 \tabularnewline
183 & 6023 & 10748.1807917611 & -4725.18079176111 \tabularnewline
184 & 64466 & 73801.682076287 & -9335.68207628696 \tabularnewline
185 & 54990 & 97071.2028567083 & -42081.2028567083 \tabularnewline
186 & 1644 & 8109.36126287324 & -6465.36126287324 \tabularnewline
187 & 6179 & 17614.3390718052 & -11435.3390718052 \tabularnewline
188 & 3926 & 11694.009509414 & -7768.00950941396 \tabularnewline
189 & 32755 & 45043.3662726897 & -12288.3662726897 \tabularnewline
190 & 34777 & 30796.1782225019 & 3980.82177749808 \tabularnewline
191 & 73224 & 60233.344131933 & 12990.655868067 \tabularnewline
192 & 27114 & 28185.7764155075 & -1071.77641550753 \tabularnewline
193 & 20760 & 32060.626239592 & -11300.626239592 \tabularnewline
194 & 37636 & 40321.2076267014 & -2685.20762670143 \tabularnewline
195 & 65461 & 65041.114554279 & 419.885445720963 \tabularnewline
196 & 30080 & 38111.6141766093 & -8031.61417660931 \tabularnewline
197 & 24094 & 29770.8469059944 & -5676.84690599442 \tabularnewline
198 & 69008 & 33801.590830149 & 35206.409169851 \tabularnewline
199 & 54968 & 32616.7091546069 & 22351.2908453931 \tabularnewline
200 & 46090 & 32926.521326677 & 13163.478673323 \tabularnewline
201 & 27507 & 37930.2118948984 & -10423.2118948984 \tabularnewline
202 & 10672 & 24477.0175778599 & -13805.0175778599 \tabularnewline
203 & 34029 & 31304.2588075781 & 2724.74119242188 \tabularnewline
204 & 46300 & 43618.8557631638 & 2681.14423683624 \tabularnewline
205 & 24760 & 34692.7629431348 & -9932.76294313481 \tabularnewline
206 & 18779 & 18073.069791775 & 705.930208224993 \tabularnewline
207 & 21280 & 27528.6783375576 & -6248.67833755763 \tabularnewline
208 & 40662 & 42697.8463436851 & -2035.84634368513 \tabularnewline
209 & 28987 & 35517.2778660042 & -6530.27786600415 \tabularnewline
210 & 22827 & 39400.1385378596 & -16573.1385378596 \tabularnewline
211 & 18513 & 34752.0376441958 & -16239.0376441958 \tabularnewline
212 & 30594 & 28442.5584236607 & 2151.44157633933 \tabularnewline
213 & 24006 & 25401.1613064383 & -1395.16130643827 \tabularnewline
214 & 27913 & 35351.5537585147 & -7438.55375851469 \tabularnewline
215 & 42744 & 32891.1417474555 & 9852.85825254451 \tabularnewline
216 & 12934 & 30166.1273044015 & -17232.1273044015 \tabularnewline
217 & 22574 & 23439.0431966738 & -865.043196673751 \tabularnewline
218 & 41385 & 37155.9179710314 & 4229.08202896856 \tabularnewline
219 & 18653 & 33851.6789194593 & -15198.6789194593 \tabularnewline
220 & 18472 & 23137.0070169708 & -4665.00701697076 \tabularnewline
221 & 30976 & 34546.993933664 & -3570.99393366398 \tabularnewline
222 & 63339 & 69676.5011752334 & -6337.5011752334 \tabularnewline
223 & 25568 & 39885.9593167766 & -14317.9593167766 \tabularnewline
224 & 33747 & 34769.1312101294 & -1022.13121012936 \tabularnewline
225 & 4154 & 12802.7022754845 & -8648.70227548452 \tabularnewline
226 & 19474 & 35091.4572810845 & -15617.4572810845 \tabularnewline
227 & 35130 & 18966.6957567628 & 16163.3042432372 \tabularnewline
228 & 39067 & 33830.2053928698 & 5236.7946071302 \tabularnewline
229 & 13310 & 21541.0444247437 & -8231.04442474367 \tabularnewline
230 & 65892 & 30181.0442373084 & 35710.9557626916 \tabularnewline
231 & 4143 & 14928.8056327523 & -10785.8056327523 \tabularnewline
232 & 28579 & 33043.9053129681 & -4464.90531296811 \tabularnewline
233 & 51776 & 37032.1622098254 & 14743.8377901746 \tabularnewline
234 & 21152 & 22606.2299848103 & -1454.22998481031 \tabularnewline
235 & 38084 & 32670.3189790315 & 5413.6810209685 \tabularnewline
236 & 27717 & 29053.1648185353 & -1336.16481853533 \tabularnewline
237 & 32928 & 29602.0323975183 & 3325.96760248168 \tabularnewline
238 & 11342 & 23015.9976844398 & -11673.9976844398 \tabularnewline
239 & 19499 & 28591.1587273833 & -9092.15872738332 \tabularnewline
240 & 16380 & 18480.7122455365 & -2100.71224553652 \tabularnewline
241 & 36874 & 29549.6291222258 & 7324.37087777417 \tabularnewline
242 & 48259 & 54276.6005546319 & -6017.60055463188 \tabularnewline
243 & 16734 & 22698.2078652954 & -5964.2078652954 \tabularnewline
244 & 28207 & 27858.5925348835 & 348.407465116548 \tabularnewline
245 & 30143 & 28422.7275439771 & 1720.27245602289 \tabularnewline
246 & 41369 & 33978.2305299331 & 7390.7694700669 \tabularnewline
247 & 45833 & 37728.8794773813 & 8104.12052261869 \tabularnewline
248 & 29156 & 25793.1613248014 & 3362.8386751986 \tabularnewline
249 & 35944 & 18329.6650529588 & 17614.3349470412 \tabularnewline
250 & 36278 & 21760.6426796653 & 14517.3573203347 \tabularnewline
251 & 45588 & 43292.0958316698 & 2295.90416833016 \tabularnewline
252 & 45097 & 39071.0004355396 & 6025.99956446037 \tabularnewline
253 & 3895 & 5584.37179712577 & -1689.37179712577 \tabularnewline
254 & 28394 & 28678.6652389188 & -284.665238918804 \tabularnewline
255 & 18632 & 26650.6510409542 & -8018.65104095419 \tabularnewline
256 & 2325 & 5036.5421860749 & -2711.5421860749 \tabularnewline
257 & 25139 & 18169.8414036053 & 6969.15859639465 \tabularnewline
258 & 27975 & 23792.2113158219 & 4182.78868417806 \tabularnewline
259 & 14483 & 24697.0525321964 & -10214.0525321964 \tabularnewline
260 & 13127 & 16914.0978207329 & -3787.09782073295 \tabularnewline
261 & 5839 & 10765.4180663049 & -4926.41806630491 \tabularnewline
262 & 24069 & 33052.750300053 & -8983.75030005305 \tabularnewline
263 & 3738 & 6852.34836331417 & -3114.34836331417 \tabularnewline
264 & 18625 & 25975.5978275302 & -7350.59782753015 \tabularnewline
265 & 36341 & 20910.6650303623 & 15430.3349696377 \tabularnewline
266 & 24548 & 28285.3091030156 & -3737.30910301559 \tabularnewline
267 & 21792 & 29453.1836266289 & -7661.18362662895 \tabularnewline
268 & 26263 & 18257.5604201141 & 8005.4395798859 \tabularnewline
269 & 23686 & 35613.6580521736 & -11927.6580521736 \tabularnewline
270 & 49303 & 35196.5097873689 & 14106.4902126311 \tabularnewline
271 & 25659 & 31682.7572787694 & -6023.75727876938 \tabularnewline
272 & 28904 & 24545.686738308 & 4358.31326169201 \tabularnewline
273 & 2781 & 1335.12995219839 & 1445.87004780161 \tabularnewline
274 & 29236 & 32480.7076912508 & -3244.70769125085 \tabularnewline
275 & 19546 & 18628.4615722659 & 917.538427734096 \tabularnewline
276 & 22818 & 29211.1730031191 & -6393.17300311906 \tabularnewline
277 & 32689 & 15360.7148449891 & 17328.2851550109 \tabularnewline
278 & 5752 & 9790.44839809219 & -4038.44839809219 \tabularnewline
279 & 22197 & 35620.7245125782 & -13423.7245125782 \tabularnewline
280 & 20055 & 25623.0218782715 & -5568.02187827153 \tabularnewline
281 & 25272 & 24539.1030193249 & 732.896980675089 \tabularnewline
282 & 82206 & 18215.2815340326 & 63990.7184659674 \tabularnewline
283 & 32073 & 23226.6366209432 & 8846.36337905676 \tabularnewline
284 & 5444 & 7726.97970951881 & -2282.97970951881 \tabularnewline
285 & 20154 & 21409.8275006196 & -1255.82750061959 \tabularnewline
286 & 36944 & 18123.6674176208 & 18820.3325823792 \tabularnewline
287 & 8019 & 16754.5726867679 & -8735.57268676785 \tabularnewline
288 & 30884 & 35737.7492784687 & -4853.74927846875 \tabularnewline
289 & 19540 & 27415.5500678301 & -7875.55006783007 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156535&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]112285[/C][C]104509.222837295[/C][C]7775.77716270472[/C][/ROW]
[ROW][C]2[/C][C]84786[/C][C]83365.9153410982[/C][C]1420.08465890178[/C][/ROW]
[ROW][C]3[/C][C]83123[/C][C]96641.6086502963[/C][C]-13518.6086502963[/C][/ROW]
[ROW][C]4[/C][C]101193[/C][C]98914.1597989804[/C][C]2278.84020101963[/C][/ROW]
[ROW][C]5[/C][C]38361[/C][C]54820.543197438[/C][C]-16459.543197438[/C][/ROW]
[ROW][C]6[/C][C]68504[/C][C]50570.1509084024[/C][C]17933.8490915976[/C][/ROW]
[ROW][C]7[/C][C]119182[/C][C]119422.819215243[/C][C]-240.819215242889[/C][/ROW]
[ROW][C]8[/C][C]22807[/C][C]19349.1766202583[/C][C]3457.82337974165[/C][/ROW]
[ROW][C]9[/C][C]17140[/C][C]20728.8139643922[/C][C]-3588.81396439215[/C][/ROW]
[ROW][C]10[/C][C]116174[/C][C]92194.1341523352[/C][C]23979.8658476648[/C][/ROW]
[ROW][C]11[/C][C]57635[/C][C]66285.3434817972[/C][C]-8650.34348179724[/C][/ROW]
[ROW][C]12[/C][C]66198[/C][C]96240.2078194722[/C][C]-30042.2078194722[/C][/ROW]
[ROW][C]13[/C][C]71701[/C][C]90431.7894728253[/C][C]-18730.7894728253[/C][/ROW]
[ROW][C]14[/C][C]57793[/C][C]66670.7754468045[/C][C]-8877.77544680454[/C][/ROW]
[ROW][C]15[/C][C]80444[/C][C]89158.8849566465[/C][C]-8714.88495664647[/C][/ROW]
[ROW][C]16[/C][C]53855[/C][C]83890.647905913[/C][C]-30035.647905913[/C][/ROW]
[ROW][C]17[/C][C]97668[/C][C]115646.439167252[/C][C]-17978.4391672519[/C][/ROW]
[ROW][C]18[/C][C]133824[/C][C]108392.555071182[/C][C]25431.4449288177[/C][/ROW]
[ROW][C]19[/C][C]101481[/C][C]86287.150265013[/C][C]15193.849734987[/C][/ROW]
[ROW][C]20[/C][C]99645[/C][C]79117.0004091169[/C][C]20527.9995908831[/C][/ROW]
[ROW][C]21[/C][C]114789[/C][C]96524.2294584897[/C][C]18264.7705415103[/C][/ROW]
[ROW][C]22[/C][C]99052[/C][C]106411.121057006[/C][C]-7359.12105700612[/C][/ROW]
[ROW][C]23[/C][C]67654[/C][C]84781.7297791814[/C][C]-17127.7297791814[/C][/ROW]
[ROW][C]24[/C][C]65553[/C][C]78588.1420171411[/C][C]-13035.1420171411[/C][/ROW]
[ROW][C]25[/C][C]97500[/C][C]87978.817549053[/C][C]9521.18245094702[/C][/ROW]
[ROW][C]26[/C][C]69112[/C][C]86728.5120838861[/C][C]-17616.5120838861[/C][/ROW]
[ROW][C]27[/C][C]82753[/C][C]83871.7795280297[/C][C]-1118.77952802967[/C][/ROW]
[ROW][C]28[/C][C]85323[/C][C]95914.7092302319[/C][C]-10591.7092302319[/C][/ROW]
[ROW][C]29[/C][C]72654[/C][C]93733.2198224388[/C][C]-21079.2198224388[/C][/ROW]
[ROW][C]30[/C][C]30727[/C][C]46723.1020751338[/C][C]-15996.1020751338[/C][/ROW]
[ROW][C]31[/C][C]77873[/C][C]95374.3965740482[/C][C]-17501.3965740482[/C][/ROW]
[ROW][C]32[/C][C]117478[/C][C]121020.700460607[/C][C]-3542.70046060743[/C][/ROW]
[ROW][C]33[/C][C]74007[/C][C]78899.9376205746[/C][C]-4892.9376205746[/C][/ROW]
[ROW][C]34[/C][C]90183[/C][C]114203.638138811[/C][C]-24020.638138811[/C][/ROW]
[ROW][C]35[/C][C]61542[/C][C]42500.2664169691[/C][C]19041.7335830309[/C][/ROW]
[ROW][C]36[/C][C]101494[/C][C]124927.224310244[/C][C]-23433.2243102439[/C][/ROW]
[ROW][C]37[/C][C]27570[/C][C]36529.7481826831[/C][C]-8959.74818268308[/C][/ROW]
[ROW][C]38[/C][C]55813[/C][C]55914.8572494944[/C][C]-101.857249494411[/C][/ROW]
[ROW][C]39[/C][C]79215[/C][C]102607.693200602[/C][C]-23392.693200602[/C][/ROW]
[ROW][C]40[/C][C]1423[/C][C]1870.45809704428[/C][C]-447.458097044282[/C][/ROW]
[ROW][C]41[/C][C]55461[/C][C]72454.4840911984[/C][C]-16993.4840911984[/C][/ROW]
[ROW][C]42[/C][C]31081[/C][C]48076.3554402458[/C][C]-16995.3554402457[/C][/ROW]
[ROW][C]43[/C][C]22996[/C][C]30973.375924609[/C][C]-7977.37592460895[/C][/ROW]
[ROW][C]44[/C][C]83122[/C][C]105593.004126037[/C][C]-22471.0041260366[/C][/ROW]
[ROW][C]45[/C][C]70106[/C][C]107011.747813967[/C][C]-36905.7478139667[/C][/ROW]
[ROW][C]46[/C][C]60578[/C][C]77629.3628183684[/C][C]-17051.3628183684[/C][/ROW]
[ROW][C]47[/C][C]39992[/C][C]47159.5392608477[/C][C]-7167.53926084773[/C][/ROW]
[ROW][C]48[/C][C]79892[/C][C]90067.0671504767[/C][C]-10175.0671504767[/C][/ROW]
[ROW][C]49[/C][C]49810[/C][C]59027.9742235194[/C][C]-9217.9742235194[/C][/ROW]
[ROW][C]50[/C][C]71570[/C][C]61165.8578300499[/C][C]10404.1421699501[/C][/ROW]
[ROW][C]51[/C][C]100708[/C][C]68371.5614424656[/C][C]32336.4385575344[/C][/ROW]
[ROW][C]52[/C][C]33032[/C][C]49473.1939844527[/C][C]-16441.1939844527[/C][/ROW]
[ROW][C]53[/C][C]82875[/C][C]81830.3941205916[/C][C]1044.60587940841[/C][/ROW]
[ROW][C]54[/C][C]139077[/C][C]118671.744736269[/C][C]20405.2552637307[/C][/ROW]
[ROW][C]55[/C][C]71595[/C][C]84164.0572346206[/C][C]-12569.0572346206[/C][/ROW]
[ROW][C]56[/C][C]72260[/C][C]86946.7899105234[/C][C]-14686.7899105234[/C][/ROW]
[ROW][C]57[/C][C]5950[/C][C]15710.5007908835[/C][C]-9760.50079088348[/C][/ROW]
[ROW][C]58[/C][C]115762[/C][C]114283.425599224[/C][C]1478.57440077582[/C][/ROW]
[ROW][C]59[/C][C]32551[/C][C]37931.7072197669[/C][C]-5380.70721976694[/C][/ROW]
[ROW][C]60[/C][C]31701[/C][C]40461.19042892[/C][C]-8760.19042892002[/C][/ROW]
[ROW][C]61[/C][C]80670[/C][C]87570.4229187424[/C][C]-6900.42291874241[/C][/ROW]
[ROW][C]62[/C][C]143558[/C][C]125703.721340854[/C][C]17854.2786591459[/C][/ROW]
[ROW][C]63[/C][C]117105[/C][C]86978.3567887996[/C][C]30126.6432112004[/C][/ROW]
[ROW][C]64[/C][C]23789[/C][C]33038.95314073[/C][C]-9249.95314073001[/C][/ROW]
[ROW][C]65[/C][C]120733[/C][C]131208.18355429[/C][C]-10475.1835542901[/C][/ROW]
[ROW][C]66[/C][C]105195[/C][C]124944.517421139[/C][C]-19749.517421139[/C][/ROW]
[ROW][C]67[/C][C]73107[/C][C]85791.3671970839[/C][C]-12684.3671970839[/C][/ROW]
[ROW][C]68[/C][C]132068[/C][C]128643.92346992[/C][C]3424.07653007994[/C][/ROW]
[ROW][C]69[/C][C]149193[/C][C]149565.061197589[/C][C]-372.061197588837[/C][/ROW]
[ROW][C]70[/C][C]46821[/C][C]78187.8961931383[/C][C]-31366.8961931383[/C][/ROW]
[ROW][C]71[/C][C]87011[/C][C]96929.9255090545[/C][C]-9918.92550905453[/C][/ROW]
[ROW][C]72[/C][C]95260[/C][C]102243.901335791[/C][C]-6983.90133579131[/C][/ROW]
[ROW][C]73[/C][C]55183[/C][C]79428.032059323[/C][C]-24245.032059323[/C][/ROW]
[ROW][C]74[/C][C]106671[/C][C]76791.1390189222[/C][C]29879.8609810778[/C][/ROW]
[ROW][C]75[/C][C]73511[/C][C]104319.292962345[/C][C]-30808.2929623451[/C][/ROW]
[ROW][C]76[/C][C]92945[/C][C]78041.1926831495[/C][C]14903.8073168505[/C][/ROW]
[ROW][C]77[/C][C]78664[/C][C]72623.0225364335[/C][C]6040.97746356651[/C][/ROW]
[ROW][C]78[/C][C]70054[/C][C]97297.5643677079[/C][C]-27243.5643677079[/C][/ROW]
[ROW][C]79[/C][C]22618[/C][C]42168.6278810776[/C][C]-19550.6278810776[/C][/ROW]
[ROW][C]80[/C][C]74011[/C][C]91614.8757032947[/C][C]-17603.8757032947[/C][/ROW]
[ROW][C]81[/C][C]83737[/C][C]79382.2206089804[/C][C]4354.7793910196[/C][/ROW]
[ROW][C]82[/C][C]69094[/C][C]72557.7446717171[/C][C]-3463.7446717171[/C][/ROW]
[ROW][C]83[/C][C]93133[/C][C]92238.3645973926[/C][C]894.635402607378[/C][/ROW]
[ROW][C]84[/C][C]95536[/C][C]98538.5613611582[/C][C]-3002.5613611582[/C][/ROW]
[ROW][C]85[/C][C]225920[/C][C]88855.9688362968[/C][C]137064.031163703[/C][/ROW]
[ROW][C]86[/C][C]62133[/C][C]68342.3562534006[/C][C]-6209.35625340059[/C][/ROW]
[ROW][C]87[/C][C]61370[/C][C]64093.2346441291[/C][C]-2723.2346441291[/C][/ROW]
[ROW][C]88[/C][C]43836[/C][C]54310.1071156059[/C][C]-10474.1071156059[/C][/ROW]
[ROW][C]89[/C][C]106117[/C][C]97441.2134208954[/C][C]8675.78657910456[/C][/ROW]
[ROW][C]90[/C][C]38692[/C][C]61932.0762104668[/C][C]-23240.0762104668[/C][/ROW]
[ROW][C]91[/C][C]84651[/C][C]91133.183999189[/C][C]-6482.18399918897[/C][/ROW]
[ROW][C]92[/C][C]56622[/C][C]38168.5054108097[/C][C]18453.4945891904[/C][/ROW]
[ROW][C]93[/C][C]15986[/C][C]32907.2512788418[/C][C]-16921.2512788418[/C][/ROW]
[ROW][C]94[/C][C]95364[/C][C]93441.539418147[/C][C]1922.46058185295[/C][/ROW]
[ROW][C]95[/C][C]26706[/C][C]38065.7933193733[/C][C]-11359.7933193733[/C][/ROW]
[ROW][C]96[/C][C]89691[/C][C]77232.4417570774[/C][C]12458.5582429226[/C][/ROW]
[ROW][C]97[/C][C]67267[/C][C]99193.311734509[/C][C]-31926.311734509[/C][/ROW]
[ROW][C]98[/C][C]126846[/C][C]97004.8236886205[/C][C]29841.1763113795[/C][/ROW]
[ROW][C]99[/C][C]41140[/C][C]65497.4463062489[/C][C]-24357.4463062489[/C][/ROW]
[ROW][C]100[/C][C]102860[/C][C]90989.5899878632[/C][C]11870.4100121368[/C][/ROW]
[ROW][C]101[/C][C]51715[/C][C]63313.9543921204[/C][C]-11598.9543921204[/C][/ROW]
[ROW][C]102[/C][C]55801[/C][C]68665.5674010902[/C][C]-12864.5674010902[/C][/ROW]
[ROW][C]103[/C][C]111813[/C][C]107689.21761028[/C][C]4123.78238972021[/C][/ROW]
[ROW][C]104[/C][C]120293[/C][C]85552.2481105399[/C][C]34740.7518894601[/C][/ROW]
[ROW][C]105[/C][C]138599[/C][C]108991.470804323[/C][C]29607.5291956769[/C][/ROW]
[ROW][C]106[/C][C]161647[/C][C]124780.414210789[/C][C]36866.5857892111[/C][/ROW]
[ROW][C]107[/C][C]115929[/C][C]137003.720836781[/C][C]-21074.7208367812[/C][/ROW]
[ROW][C]108[/C][C]24266[/C][C]31325.8949047295[/C][C]-7059.89490472953[/C][/ROW]
[ROW][C]109[/C][C]162901[/C][C]153604.049679393[/C][C]9296.95032060735[/C][/ROW]
[ROW][C]110[/C][C]109825[/C][C]112060.808274756[/C][C]-2235.80827475578[/C][/ROW]
[ROW][C]111[/C][C]129838[/C][C]111085.800189824[/C][C]18752.1998101757[/C][/ROW]
[ROW][C]112[/C][C]37510[/C][C]54375.1354244136[/C][C]-16865.1354244136[/C][/ROW]
[ROW][C]113[/C][C]43750[/C][C]41579.5536522036[/C][C]2170.44634779641[/C][/ROW]
[ROW][C]114[/C][C]40652[/C][C]67580.5223221693[/C][C]-26928.5223221693[/C][/ROW]
[ROW][C]115[/C][C]87771[/C][C]108707.840815634[/C][C]-20936.8408156342[/C][/ROW]
[ROW][C]116[/C][C]85872[/C][C]96714.1287129768[/C][C]-10842.1287129768[/C][/ROW]
[ROW][C]117[/C][C]89275[/C][C]90701.3803220581[/C][C]-1426.38032205807[/C][/ROW]
[ROW][C]118[/C][C]44418[/C][C]53955.9736839146[/C][C]-9537.97368391464[/C][/ROW]
[ROW][C]119[/C][C]192565[/C][C]87757.5694129443[/C][C]104807.430587056[/C][/ROW]
[ROW][C]120[/C][C]35232[/C][C]29625.2873570151[/C][C]5606.71264298486[/C][/ROW]
[ROW][C]121[/C][C]40909[/C][C]52507.8216343652[/C][C]-11598.8216343652[/C][/ROW]
[ROW][C]122[/C][C]13294[/C][C]21684.3987732292[/C][C]-8390.39877322918[/C][/ROW]
[ROW][C]123[/C][C]32387[/C][C]46081.2456039372[/C][C]-13694.2456039372[/C][/ROW]
[ROW][C]124[/C][C]140867[/C][C]51916.4099480312[/C][C]88950.5900519688[/C][/ROW]
[ROW][C]125[/C][C]120662[/C][C]100832.798557219[/C][C]19829.2014427808[/C][/ROW]
[ROW][C]126[/C][C]21233[/C][C]30486.4243325722[/C][C]-9253.42433257215[/C][/ROW]
[ROW][C]127[/C][C]44332[/C][C]33412.0596362364[/C][C]10919.9403637636[/C][/ROW]
[ROW][C]128[/C][C]61056[/C][C]52906.9487631438[/C][C]8149.05123685617[/C][/ROW]
[ROW][C]129[/C][C]101338[/C][C]89127.4883911785[/C][C]12210.5116088215[/C][/ROW]
[ROW][C]130[/C][C]1168[/C][C]9121.9350884016[/C][C]-7953.9350884016[/C][/ROW]
[ROW][C]131[/C][C]13497[/C][C]16619.9209352229[/C][C]-3122.9209352229[/C][/ROW]
[ROW][C]132[/C][C]65567[/C][C]78600.5359214603[/C][C]-13033.5359214603[/C][/ROW]
[ROW][C]133[/C][C]25162[/C][C]33212.4768041761[/C][C]-8050.47680417608[/C][/ROW]
[ROW][C]134[/C][C]32334[/C][C]40507.1341261503[/C][C]-8173.1341261503[/C][/ROW]
[ROW][C]135[/C][C]40735[/C][C]58498.4137537094[/C][C]-17763.4137537094[/C][/ROW]
[ROW][C]136[/C][C]91413[/C][C]118729.856809971[/C][C]-27316.8568099715[/C][/ROW]
[ROW][C]137[/C][C]855[/C][C]8410.97111347228[/C][C]-7555.97111347228[/C][/ROW]
[ROW][C]138[/C][C]97068[/C][C]78894.8601364124[/C][C]18173.1398635876[/C][/ROW]
[ROW][C]139[/C][C]44339[/C][C]16758.8622104413[/C][C]27580.1377895587[/C][/ROW]
[ROW][C]140[/C][C]14116[/C][C]21299.5974684507[/C][C]-7183.59746845067[/C][/ROW]
[ROW][C]141[/C][C]10288[/C][C]17151.1242287395[/C][C]-6863.12422873947[/C][/ROW]
[ROW][C]142[/C][C]65622[/C][C]51360.3728191956[/C][C]14261.6271808044[/C][/ROW]
[ROW][C]143[/C][C]16563[/C][C]15917.6086773863[/C][C]645.391322613681[/C][/ROW]
[ROW][C]144[/C][C]76643[/C][C]96892.5023947631[/C][C]-20249.5023947631[/C][/ROW]
[ROW][C]145[/C][C]110681[/C][C]89068.9197721398[/C][C]21612.0802278602[/C][/ROW]
[ROW][C]146[/C][C]29011[/C][C]24779.7981233243[/C][C]4231.20187667566[/C][/ROW]
[ROW][C]147[/C][C]92696[/C][C]55384.7001521241[/C][C]37311.2998478759[/C][/ROW]
[ROW][C]148[/C][C]94785[/C][C]58651.4478257569[/C][C]36133.5521742431[/C][/ROW]
[ROW][C]149[/C][C]8773[/C][C]17466.337302372[/C][C]-8693.337302372[/C][/ROW]
[ROW][C]150[/C][C]83209[/C][C]66536.1623293677[/C][C]16672.8376706323[/C][/ROW]
[ROW][C]151[/C][C]93815[/C][C]106493.285868464[/C][C]-12678.2858684642[/C][/ROW]
[ROW][C]152[/C][C]86687[/C][C]94010.5627197988[/C][C]-7323.5627197988[/C][/ROW]
[ROW][C]153[/C][C]34553[/C][C]30710.5073914826[/C][C]3842.49260851743[/C][/ROW]
[ROW][C]154[/C][C]105547[/C][C]128245.892992121[/C][C]-22698.8929921208[/C][/ROW]
[ROW][C]155[/C][C]103487[/C][C]102175.676845549[/C][C]1311.32315445055[/C][/ROW]
[ROW][C]156[/C][C]213688[/C][C]157660.308374302[/C][C]56027.6916256981[/C][/ROW]
[ROW][C]157[/C][C]71220[/C][C]75965.7782594021[/C][C]-4745.77825940215[/C][/ROW]
[ROW][C]158[/C][C]23517[/C][C]25388.1133148638[/C][C]-1871.11331486377[/C][/ROW]
[ROW][C]159[/C][C]56926[/C][C]47020.4777729422[/C][C]9905.52222705783[/C][/ROW]
[ROW][C]160[/C][C]91721[/C][C]80874.8188314797[/C][C]10846.1811685203[/C][/ROW]
[ROW][C]161[/C][C]115168[/C][C]119950.471531635[/C][C]-4782.47153163498[/C][/ROW]
[ROW][C]162[/C][C]111194[/C][C]47568.6302668118[/C][C]63625.3697331882[/C][/ROW]
[ROW][C]163[/C][C]51009[/C][C]43057.4281870611[/C][C]7951.57181293886[/C][/ROW]
[ROW][C]164[/C][C]135777[/C][C]107722.39158038[/C][C]28054.6084196199[/C][/ROW]
[ROW][C]165[/C][C]51513[/C][C]63694.5877630105[/C][C]-12181.5877630105[/C][/ROW]
[ROW][C]166[/C][C]74163[/C][C]97546.3754442696[/C][C]-23383.3754442696[/C][/ROW]
[ROW][C]167[/C][C]51633[/C][C]71524.5878277725[/C][C]-19891.5878277725[/C][/ROW]
[ROW][C]168[/C][C]75345[/C][C]47815.1956435608[/C][C]27529.8043564392[/C][/ROW]
[ROW][C]169[/C][C]33416[/C][C]48808.024694503[/C][C]-15392.024694503[/C][/ROW]
[ROW][C]170[/C][C]83305[/C][C]51506.6289016858[/C][C]31798.3710983141[/C][/ROW]
[ROW][C]171[/C][C]98952[/C][C]92121.9072825943[/C][C]6830.09271740575[/C][/ROW]
[ROW][C]172[/C][C]102372[/C][C]98140.3306905563[/C][C]4231.66930944369[/C][/ROW]
[ROW][C]173[/C][C]37238[/C][C]31071.6379494444[/C][C]6166.36205055559[/C][/ROW]
[ROW][C]174[/C][C]103772[/C][C]122908.058657184[/C][C]-19136.0586571835[/C][/ROW]
[ROW][C]175[/C][C]123969[/C][C]78938.6329881974[/C][C]45030.3670118026[/C][/ROW]
[ROW][C]176[/C][C]27142[/C][C]38236.2591426823[/C][C]-11094.2591426823[/C][/ROW]
[ROW][C]177[/C][C]135400[/C][C]101407.724205804[/C][C]33992.275794196[/C][/ROW]
[ROW][C]178[/C][C]21399[/C][C]24739.431184475[/C][C]-3340.43118447503[/C][/ROW]
[ROW][C]179[/C][C]130115[/C][C]110654.943738037[/C][C]19460.0562619632[/C][/ROW]
[ROW][C]180[/C][C]24874[/C][C]37466.3428333356[/C][C]-12592.3428333356[/C][/ROW]
[ROW][C]181[/C][C]34988[/C][C]26943.8941617149[/C][C]8044.1058382851[/C][/ROW]
[ROW][C]182[/C][C]45549[/C][C]17516.4534779026[/C][C]28032.5465220974[/C][/ROW]
[ROW][C]183[/C][C]6023[/C][C]10748.1807917611[/C][C]-4725.18079176111[/C][/ROW]
[ROW][C]184[/C][C]64466[/C][C]73801.682076287[/C][C]-9335.68207628696[/C][/ROW]
[ROW][C]185[/C][C]54990[/C][C]97071.2028567083[/C][C]-42081.2028567083[/C][/ROW]
[ROW][C]186[/C][C]1644[/C][C]8109.36126287324[/C][C]-6465.36126287324[/C][/ROW]
[ROW][C]187[/C][C]6179[/C][C]17614.3390718052[/C][C]-11435.3390718052[/C][/ROW]
[ROW][C]188[/C][C]3926[/C][C]11694.009509414[/C][C]-7768.00950941396[/C][/ROW]
[ROW][C]189[/C][C]32755[/C][C]45043.3662726897[/C][C]-12288.3662726897[/C][/ROW]
[ROW][C]190[/C][C]34777[/C][C]30796.1782225019[/C][C]3980.82177749808[/C][/ROW]
[ROW][C]191[/C][C]73224[/C][C]60233.344131933[/C][C]12990.655868067[/C][/ROW]
[ROW][C]192[/C][C]27114[/C][C]28185.7764155075[/C][C]-1071.77641550753[/C][/ROW]
[ROW][C]193[/C][C]20760[/C][C]32060.626239592[/C][C]-11300.626239592[/C][/ROW]
[ROW][C]194[/C][C]37636[/C][C]40321.2076267014[/C][C]-2685.20762670143[/C][/ROW]
[ROW][C]195[/C][C]65461[/C][C]65041.114554279[/C][C]419.885445720963[/C][/ROW]
[ROW][C]196[/C][C]30080[/C][C]38111.6141766093[/C][C]-8031.61417660931[/C][/ROW]
[ROW][C]197[/C][C]24094[/C][C]29770.8469059944[/C][C]-5676.84690599442[/C][/ROW]
[ROW][C]198[/C][C]69008[/C][C]33801.590830149[/C][C]35206.409169851[/C][/ROW]
[ROW][C]199[/C][C]54968[/C][C]32616.7091546069[/C][C]22351.2908453931[/C][/ROW]
[ROW][C]200[/C][C]46090[/C][C]32926.521326677[/C][C]13163.478673323[/C][/ROW]
[ROW][C]201[/C][C]27507[/C][C]37930.2118948984[/C][C]-10423.2118948984[/C][/ROW]
[ROW][C]202[/C][C]10672[/C][C]24477.0175778599[/C][C]-13805.0175778599[/C][/ROW]
[ROW][C]203[/C][C]34029[/C][C]31304.2588075781[/C][C]2724.74119242188[/C][/ROW]
[ROW][C]204[/C][C]46300[/C][C]43618.8557631638[/C][C]2681.14423683624[/C][/ROW]
[ROW][C]205[/C][C]24760[/C][C]34692.7629431348[/C][C]-9932.76294313481[/C][/ROW]
[ROW][C]206[/C][C]18779[/C][C]18073.069791775[/C][C]705.930208224993[/C][/ROW]
[ROW][C]207[/C][C]21280[/C][C]27528.6783375576[/C][C]-6248.67833755763[/C][/ROW]
[ROW][C]208[/C][C]40662[/C][C]42697.8463436851[/C][C]-2035.84634368513[/C][/ROW]
[ROW][C]209[/C][C]28987[/C][C]35517.2778660042[/C][C]-6530.27786600415[/C][/ROW]
[ROW][C]210[/C][C]22827[/C][C]39400.1385378596[/C][C]-16573.1385378596[/C][/ROW]
[ROW][C]211[/C][C]18513[/C][C]34752.0376441958[/C][C]-16239.0376441958[/C][/ROW]
[ROW][C]212[/C][C]30594[/C][C]28442.5584236607[/C][C]2151.44157633933[/C][/ROW]
[ROW][C]213[/C][C]24006[/C][C]25401.1613064383[/C][C]-1395.16130643827[/C][/ROW]
[ROW][C]214[/C][C]27913[/C][C]35351.5537585147[/C][C]-7438.55375851469[/C][/ROW]
[ROW][C]215[/C][C]42744[/C][C]32891.1417474555[/C][C]9852.85825254451[/C][/ROW]
[ROW][C]216[/C][C]12934[/C][C]30166.1273044015[/C][C]-17232.1273044015[/C][/ROW]
[ROW][C]217[/C][C]22574[/C][C]23439.0431966738[/C][C]-865.043196673751[/C][/ROW]
[ROW][C]218[/C][C]41385[/C][C]37155.9179710314[/C][C]4229.08202896856[/C][/ROW]
[ROW][C]219[/C][C]18653[/C][C]33851.6789194593[/C][C]-15198.6789194593[/C][/ROW]
[ROW][C]220[/C][C]18472[/C][C]23137.0070169708[/C][C]-4665.00701697076[/C][/ROW]
[ROW][C]221[/C][C]30976[/C][C]34546.993933664[/C][C]-3570.99393366398[/C][/ROW]
[ROW][C]222[/C][C]63339[/C][C]69676.5011752334[/C][C]-6337.5011752334[/C][/ROW]
[ROW][C]223[/C][C]25568[/C][C]39885.9593167766[/C][C]-14317.9593167766[/C][/ROW]
[ROW][C]224[/C][C]33747[/C][C]34769.1312101294[/C][C]-1022.13121012936[/C][/ROW]
[ROW][C]225[/C][C]4154[/C][C]12802.7022754845[/C][C]-8648.70227548452[/C][/ROW]
[ROW][C]226[/C][C]19474[/C][C]35091.4572810845[/C][C]-15617.4572810845[/C][/ROW]
[ROW][C]227[/C][C]35130[/C][C]18966.6957567628[/C][C]16163.3042432372[/C][/ROW]
[ROW][C]228[/C][C]39067[/C][C]33830.2053928698[/C][C]5236.7946071302[/C][/ROW]
[ROW][C]229[/C][C]13310[/C][C]21541.0444247437[/C][C]-8231.04442474367[/C][/ROW]
[ROW][C]230[/C][C]65892[/C][C]30181.0442373084[/C][C]35710.9557626916[/C][/ROW]
[ROW][C]231[/C][C]4143[/C][C]14928.8056327523[/C][C]-10785.8056327523[/C][/ROW]
[ROW][C]232[/C][C]28579[/C][C]33043.9053129681[/C][C]-4464.90531296811[/C][/ROW]
[ROW][C]233[/C][C]51776[/C][C]37032.1622098254[/C][C]14743.8377901746[/C][/ROW]
[ROW][C]234[/C][C]21152[/C][C]22606.2299848103[/C][C]-1454.22998481031[/C][/ROW]
[ROW][C]235[/C][C]38084[/C][C]32670.3189790315[/C][C]5413.6810209685[/C][/ROW]
[ROW][C]236[/C][C]27717[/C][C]29053.1648185353[/C][C]-1336.16481853533[/C][/ROW]
[ROW][C]237[/C][C]32928[/C][C]29602.0323975183[/C][C]3325.96760248168[/C][/ROW]
[ROW][C]238[/C][C]11342[/C][C]23015.9976844398[/C][C]-11673.9976844398[/C][/ROW]
[ROW][C]239[/C][C]19499[/C][C]28591.1587273833[/C][C]-9092.15872738332[/C][/ROW]
[ROW][C]240[/C][C]16380[/C][C]18480.7122455365[/C][C]-2100.71224553652[/C][/ROW]
[ROW][C]241[/C][C]36874[/C][C]29549.6291222258[/C][C]7324.37087777417[/C][/ROW]
[ROW][C]242[/C][C]48259[/C][C]54276.6005546319[/C][C]-6017.60055463188[/C][/ROW]
[ROW][C]243[/C][C]16734[/C][C]22698.2078652954[/C][C]-5964.2078652954[/C][/ROW]
[ROW][C]244[/C][C]28207[/C][C]27858.5925348835[/C][C]348.407465116548[/C][/ROW]
[ROW][C]245[/C][C]30143[/C][C]28422.7275439771[/C][C]1720.27245602289[/C][/ROW]
[ROW][C]246[/C][C]41369[/C][C]33978.2305299331[/C][C]7390.7694700669[/C][/ROW]
[ROW][C]247[/C][C]45833[/C][C]37728.8794773813[/C][C]8104.12052261869[/C][/ROW]
[ROW][C]248[/C][C]29156[/C][C]25793.1613248014[/C][C]3362.8386751986[/C][/ROW]
[ROW][C]249[/C][C]35944[/C][C]18329.6650529588[/C][C]17614.3349470412[/C][/ROW]
[ROW][C]250[/C][C]36278[/C][C]21760.6426796653[/C][C]14517.3573203347[/C][/ROW]
[ROW][C]251[/C][C]45588[/C][C]43292.0958316698[/C][C]2295.90416833016[/C][/ROW]
[ROW][C]252[/C][C]45097[/C][C]39071.0004355396[/C][C]6025.99956446037[/C][/ROW]
[ROW][C]253[/C][C]3895[/C][C]5584.37179712577[/C][C]-1689.37179712577[/C][/ROW]
[ROW][C]254[/C][C]28394[/C][C]28678.6652389188[/C][C]-284.665238918804[/C][/ROW]
[ROW][C]255[/C][C]18632[/C][C]26650.6510409542[/C][C]-8018.65104095419[/C][/ROW]
[ROW][C]256[/C][C]2325[/C][C]5036.5421860749[/C][C]-2711.5421860749[/C][/ROW]
[ROW][C]257[/C][C]25139[/C][C]18169.8414036053[/C][C]6969.15859639465[/C][/ROW]
[ROW][C]258[/C][C]27975[/C][C]23792.2113158219[/C][C]4182.78868417806[/C][/ROW]
[ROW][C]259[/C][C]14483[/C][C]24697.0525321964[/C][C]-10214.0525321964[/C][/ROW]
[ROW][C]260[/C][C]13127[/C][C]16914.0978207329[/C][C]-3787.09782073295[/C][/ROW]
[ROW][C]261[/C][C]5839[/C][C]10765.4180663049[/C][C]-4926.41806630491[/C][/ROW]
[ROW][C]262[/C][C]24069[/C][C]33052.750300053[/C][C]-8983.75030005305[/C][/ROW]
[ROW][C]263[/C][C]3738[/C][C]6852.34836331417[/C][C]-3114.34836331417[/C][/ROW]
[ROW][C]264[/C][C]18625[/C][C]25975.5978275302[/C][C]-7350.59782753015[/C][/ROW]
[ROW][C]265[/C][C]36341[/C][C]20910.6650303623[/C][C]15430.3349696377[/C][/ROW]
[ROW][C]266[/C][C]24548[/C][C]28285.3091030156[/C][C]-3737.30910301559[/C][/ROW]
[ROW][C]267[/C][C]21792[/C][C]29453.1836266289[/C][C]-7661.18362662895[/C][/ROW]
[ROW][C]268[/C][C]26263[/C][C]18257.5604201141[/C][C]8005.4395798859[/C][/ROW]
[ROW][C]269[/C][C]23686[/C][C]35613.6580521736[/C][C]-11927.6580521736[/C][/ROW]
[ROW][C]270[/C][C]49303[/C][C]35196.5097873689[/C][C]14106.4902126311[/C][/ROW]
[ROW][C]271[/C][C]25659[/C][C]31682.7572787694[/C][C]-6023.75727876938[/C][/ROW]
[ROW][C]272[/C][C]28904[/C][C]24545.686738308[/C][C]4358.31326169201[/C][/ROW]
[ROW][C]273[/C][C]2781[/C][C]1335.12995219839[/C][C]1445.87004780161[/C][/ROW]
[ROW][C]274[/C][C]29236[/C][C]32480.7076912508[/C][C]-3244.70769125085[/C][/ROW]
[ROW][C]275[/C][C]19546[/C][C]18628.4615722659[/C][C]917.538427734096[/C][/ROW]
[ROW][C]276[/C][C]22818[/C][C]29211.1730031191[/C][C]-6393.17300311906[/C][/ROW]
[ROW][C]277[/C][C]32689[/C][C]15360.7148449891[/C][C]17328.2851550109[/C][/ROW]
[ROW][C]278[/C][C]5752[/C][C]9790.44839809219[/C][C]-4038.44839809219[/C][/ROW]
[ROW][C]279[/C][C]22197[/C][C]35620.7245125782[/C][C]-13423.7245125782[/C][/ROW]
[ROW][C]280[/C][C]20055[/C][C]25623.0218782715[/C][C]-5568.02187827153[/C][/ROW]
[ROW][C]281[/C][C]25272[/C][C]24539.1030193249[/C][C]732.896980675089[/C][/ROW]
[ROW][C]282[/C][C]82206[/C][C]18215.2815340326[/C][C]63990.7184659674[/C][/ROW]
[ROW][C]283[/C][C]32073[/C][C]23226.6366209432[/C][C]8846.36337905676[/C][/ROW]
[ROW][C]284[/C][C]5444[/C][C]7726.97970951881[/C][C]-2282.97970951881[/C][/ROW]
[ROW][C]285[/C][C]20154[/C][C]21409.8275006196[/C][C]-1255.82750061959[/C][/ROW]
[ROW][C]286[/C][C]36944[/C][C]18123.6674176208[/C][C]18820.3325823792[/C][/ROW]
[ROW][C]287[/C][C]8019[/C][C]16754.5726867679[/C][C]-8735.57268676785[/C][/ROW]
[ROW][C]288[/C][C]30884[/C][C]35737.7492784687[/C][C]-4853.74927846875[/C][/ROW]
[ROW][C]289[/C][C]19540[/C][C]27415.5500678301[/C][C]-7875.55006783007[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156535&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156535&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1112285104509.2228372957775.77716270472
28478683365.91534109821420.08465890178
38312396641.6086502963-13518.6086502963
410119398914.15979898042278.84020101963
53836154820.543197438-16459.543197438
66850450570.150908402417933.8490915976
7119182119422.819215243-240.819215242889
82280719349.17662025833457.82337974165
91714020728.8139643922-3588.81396439215
1011617492194.134152335223979.8658476648
115763566285.3434817972-8650.34348179724
126619896240.2078194722-30042.2078194722
137170190431.7894728253-18730.7894728253
145779366670.7754468045-8877.77544680454
158044489158.8849566465-8714.88495664647
165385583890.647905913-30035.647905913
1797668115646.439167252-17978.4391672519
18133824108392.55507118225431.4449288177
1910148186287.15026501315193.849734987
209964579117.000409116920527.9995908831
2111478996524.229458489718264.7705415103
2299052106411.121057006-7359.12105700612
236765484781.7297791814-17127.7297791814
246555378588.1420171411-13035.1420171411
259750087978.8175490539521.18245094702
266911286728.5120838861-17616.5120838861
278275383871.7795280297-1118.77952802967
288532395914.7092302319-10591.7092302319
297265493733.2198224388-21079.2198224388
303072746723.1020751338-15996.1020751338
317787395374.3965740482-17501.3965740482
32117478121020.700460607-3542.70046060743
337400778899.9376205746-4892.9376205746
3490183114203.638138811-24020.638138811
356154242500.266416969119041.7335830309
36101494124927.224310244-23433.2243102439
372757036529.7481826831-8959.74818268308
385581355914.8572494944-101.857249494411
3979215102607.693200602-23392.693200602
4014231870.45809704428-447.458097044282
415546172454.4840911984-16993.4840911984
423108148076.3554402458-16995.3554402457
432299630973.375924609-7977.37592460895
4483122105593.004126037-22471.0041260366
4570106107011.747813967-36905.7478139667
466057877629.3628183684-17051.3628183684
473999247159.5392608477-7167.53926084773
487989290067.0671504767-10175.0671504767
494981059027.9742235194-9217.9742235194
507157061165.857830049910404.1421699501
5110070868371.561442465632336.4385575344
523303249473.1939844527-16441.1939844527
538287581830.39412059161044.60587940841
54139077118671.74473626920405.2552637307
557159584164.0572346206-12569.0572346206
567226086946.7899105234-14686.7899105234
57595015710.5007908835-9760.50079088348
58115762114283.4255992241478.57440077582
593255137931.7072197669-5380.70721976694
603170140461.19042892-8760.19042892002
618067087570.4229187424-6900.42291874241
62143558125703.72134085417854.2786591459
6311710586978.356788799630126.6432112004
642378933038.95314073-9249.95314073001
65120733131208.18355429-10475.1835542901
66105195124944.517421139-19749.517421139
677310785791.3671970839-12684.3671970839
68132068128643.923469923424.07653007994
69149193149565.061197589-372.061197588837
704682178187.8961931383-31366.8961931383
718701196929.9255090545-9918.92550905453
7295260102243.901335791-6983.90133579131
735518379428.032059323-24245.032059323
7410667176791.139018922229879.8609810778
7573511104319.292962345-30808.2929623451
769294578041.192683149514903.8073168505
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2243374734769.1312101294-1022.13121012936
225415412802.7022754845-8648.70227548452
2261947435091.4572810845-15617.4572810845
2273513018966.695756762816163.3042432372
2283906733830.20539286985236.7946071302
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2306589230181.044237308435710.9557626916
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2322857933043.9053129681-4464.90531296811
2335177637032.162209825414743.8377901746
2342115222606.2299848103-1454.22998481031
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2401638018480.7122455365-2100.71224553652
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2503627821760.642679665314517.3573203347
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25623255036.5421860749-2711.5421860749
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2601312716914.0978207329-3787.09782073295
261583910765.4180663049-4926.41806630491
2622406933052.750300053-8983.75030005305
26337386852.34836331417-3114.34836331417
2641862525975.5978275302-7350.59782753015
2653634120910.665030362315430.3349696377
2662454828285.3091030156-3737.30910301559
2672179229453.1836266289-7661.18362662895
2682626318257.56042011418005.4395798859
2692368635613.6580521736-11927.6580521736
2704930335196.509787368914106.4902126311
2712565931682.7572787694-6023.75727876938
2722890424545.6867383084358.31326169201
27327811335.129952198391445.87004780161
2742923632480.7076912508-3244.70769125085
2751954618628.4615722659917.538427734096
2762281829211.1730031191-6393.17300311906
2773268915360.714844989117328.2851550109
27857529790.44839809219-4038.44839809219
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2802005525623.0218782715-5568.02187827153
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2828220618215.281534032663990.7184659674
2833207323226.63662094328846.36337905676
28454447726.97970951881-2282.97970951881
2852015421409.8275006196-1255.82750061959
2863694418123.667417620818820.3325823792
287801916754.5726867679-8735.57268676785
2883088435737.7492784687-4853.74927846875
2891954027415.5500678301-7875.55006783007







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.3071627377100870.6143254754201730.692837262289913
130.1680590140934590.3361180281869190.831940985906541
140.08383517875407810.1676703575081560.916164821245922
150.04341497134967090.08682994269934180.956585028650329
160.02247357147529520.04494714295059030.977526428524705
170.02339347052162350.04678694104324690.976606529478377
180.03738745861825740.07477491723651480.962612541381743
190.05098892960178510.101977859203570.949011070398215
200.06759830069492340.1351966013898470.932401699305077
210.101840232682230.203680465364460.89815976731777
220.07192524855360080.1438504971072020.928074751446399
230.04929340973290.09858681946580010.9507065902671
240.04148675568767240.08297351137534470.958513244312328
250.03742342759574310.07484685519148620.962576572404257
260.05603528551243520.112070571024870.943964714487565
270.03823846711808720.07647693423617440.961761532881913
280.02578028581810820.05156057163621650.974219714181892
290.02004128427852370.04008256855704740.979958715721476
300.01471941354340670.02943882708681330.985280586456593
310.01201366259950370.02402732519900740.987986337400496
320.007785766597850890.01557153319570180.992214233402149
330.005370678225294680.01074135645058940.994629321774705
340.003445684089053190.006891368178106390.996554315910947
350.00915117241939970.01830234483879940.9908488275806
360.01328634587166990.02657269174333980.98671365412833
370.008937157099735560.01787431419947110.991062842900264
380.00830768905295530.01661537810591060.991692310947045
390.005828222048115170.01165644409623030.994171777951885
400.004057219360433010.008114438720866010.995942780639567
410.003798831220389030.007597662440778060.996201168779611
420.005377917925315990.0107558358506320.994622082074684
430.003538663897342020.007077327794684040.996461336102658
440.002736755357874590.005473510715749170.997263244642125
450.008298208231189390.01659641646237880.991701791768811
460.006915766875489510.0138315337509790.99308423312451
470.004756638456633980.009513276913267950.995243361543366
480.003255439193641680.006510878387283360.996744560806358
490.002411605827411290.004823211654822580.997588394172589
500.004319437337008930.008638874674017850.995680562662991
510.02154420192144860.04308840384289720.978455798078551
520.01807135978117030.03614271956234070.98192864021883
530.01318195042592120.02636390085184230.986818049574079
540.02280678884062830.04561357768125670.977193211159372
550.0195821980174460.03916439603489190.980417801982554
560.01555628309149780.03111256618299550.984443716908502
570.01320348970517440.02640697941034880.986796510294826
580.01025046383671270.02050092767342550.989749536163287
590.007550919878549810.01510183975709960.99244908012145
600.005802149799557880.01160429959911580.994197850200442
610.004195665316293680.008391330632587350.995804334683706
620.006780204075762380.01356040815152480.993219795924238
630.0146917035483170.0293834070966340.985308296451683
640.01134477864490030.02268955728980070.9886552213551
650.0103334436286730.0206668872573460.989666556371327
660.009761509551664760.01952301910332950.990238490448335
670.007870388731396690.01574077746279340.992129611268603
680.006238687998284280.01247737599656860.993761312001716
690.004707050924784610.009414101849569220.995292949075215
700.006766971340364570.01353394268072910.993233028659635
710.005193656179720870.01038731235944170.994806343820279
720.003889172576737880.007778345153475760.996110827423262
730.004024208542948240.008048417085896470.995975791457052
740.006293944526431560.01258788905286310.993706055473568
750.008771260911308840.01754252182261770.991228739088691
760.007218921736756790.01443784347351360.992781078263243
770.005826154893751070.01165230978750210.994173845106249
780.006802753817841020.0136055076356820.993197246182159
790.006349926985874230.01269985397174850.993650073014126
800.005527758274342380.01105551654868480.994472241725658
810.004173140471987380.008346280943974760.995826859528013
820.003145073452640940.006290146905281880.996854926547359
830.002369561171494450.004739122342988890.997630438828506
840.001748531574014350.003497063148028690.998251468425986
850.9782008426473670.04359831470526510.0217991573526325
860.9734246231788040.05315075364239240.0265753768211962
870.967597075054290.06480584989142040.0324029249457102
880.9620952568970060.07580948620598780.0379047431029939
890.9563521979392240.08729560412155290.0436478020607764
900.9589577923569130.08208441528617380.0410422076430869
910.9511660366944050.09766792661118940.0488339633055947
920.9489903276318120.1020193447363760.0510096723681878
930.9452187639999090.1095624720001810.0547812360000906
940.9378890896236030.1242218207527930.0621109103763966
950.9285876509795370.1428246980409250.0714123490204627
960.9202344633838760.1595310732322480.0797655366161241
970.9361533698217120.1276932603565760.0638466301782882
980.9528708584103190.09425828317936220.0471291415896811
990.9571872581272660.08562548374546730.0428127418727336
1000.9513128517214670.0973742965570660.048687148278533
1010.9462274063905280.1075451872189430.0537725936094715
1020.9407486348558990.1185027302882030.0592513651441015
1030.9310645760156340.1378708479687310.0689354239843657
1040.9529314181507640.09413716369847120.0470685818492356
1050.9612639312553270.07747213748934510.0387360687446726
1060.97385394112050.05229211775900020.0261460588795001
1070.9761159599097050.04776808018059080.0238840400902954
1080.971118130955260.05776373808948010.0288818690447401
1090.9674919900621180.06501601987576350.0325080099378817
1100.9629434691751630.07411306164967480.0370565308248374
1110.9614334029281730.07713319414365480.0385665970718274
1120.9633930568799160.07321388624016830.0366069431200842
1130.9560609436632550.08787811267349060.0439390563367453
1140.9645343380068780.07093132398624470.0354656619931224
1150.9653248113879050.06935037722418930.0346751886120946
1160.9619861921732310.07602761565353770.0380138078267689
1170.954783016242080.09043396751583940.0452169837579197
1180.9475221308165790.1049557383668420.0524778691834211
1190.9999284345100880.0001431309798234547.15654899117272e-05
1200.999904581872320.0001908362553597119.54181276798557e-05
1210.9998759477794340.0002481044411318190.00012405222056591
1220.9998353185579910.0003293628840169770.000164681442008489
1230.9998041109736710.0003917780526589340.000195889026329467
1240.9999999111395971.77720806666458e-078.88604033332291e-08
1250.999999916646031.66707939718016e-078.33539698590079e-08
1260.9999998769958472.46008305862999e-071.230041529315e-07
1270.9999998393089053.21382190098605e-071.60691095049303e-07
1280.9999997747746584.50450684529841e-072.2522534226492e-07
1290.9999996963323526.07335295098377e-073.03667647549188e-07
1300.999999560618948.78762119673757e-074.39381059836879e-07
1310.9999993567218161.28655636828307e-066.43278184141537e-07
1320.999999272483221.45503355982845e-067.27516779914225e-07
1330.9999990192566331.96148673352157e-069.80743366760785e-07
1340.9999987129987852.57400242934988e-061.28700121467494e-06
1350.9999994494100621.10117987551046e-065.5058993775523e-07
1360.9999995897028128.20594375908474e-074.10297187954237e-07
1370.9999994032130331.19357393348075e-065.96786966740377e-07
1380.9999993739728691.25205426154746e-066.26027130773731e-07
1390.9999996233257297.53348541593027e-073.76674270796514e-07
1400.999999466834491.06633102056118e-065.3316551028059e-07
1410.9999992050395411.58992091758255e-067.94960458791276e-07
1420.9999991674789881.66504202458715e-068.32521012293573e-07
1430.9999987345078922.5309842159664e-061.2654921079832e-06
1440.9999988115851632.37682967463274e-061.18841483731637e-06
1450.9999987050999532.58980009375314e-061.29490004687657e-06
1460.9999980615123053.87697539036247e-061.93848769518123e-06
1470.9999989483396572.10332068689618e-061.05166034344809e-06
1480.9999995834837978.33032405218933e-074.16516202609467e-07
1490.9999994160956061.16780878858001e-065.83904394290005e-07
1500.9999992812575771.43748484617728e-067.18742423088642e-07
1510.9999991020101151.79597977072082e-068.97989885360412e-07
1520.9999992763918251.44721635045561e-067.23608175227805e-07
1530.9999989293366562.14132668789349e-061.07066334394675e-06
1540.9999995725503498.54899302293573e-074.27449651146787e-07
1550.9999993788562611.24228747700896e-066.2114373850448e-07
1560.9999999739329285.21341431284134e-082.60670715642067e-08
1570.9999999579044048.41911913609392e-084.20955956804696e-08
1580.9999999317381191.36523761249427e-076.82618806247137e-08
1590.9999999012284451.97543109783902e-079.87715548919508e-08
1600.9999998754615592.4907688144522e-071.2453844072261e-07
1610.9999998025568933.9488621314868e-071.9744310657434e-07
1620.9999999980094883.98102306165787e-091.99051153082894e-09
1630.9999999969514626.09707646715513e-093.04853823357757e-09
1640.9999999980146663.97066731353787e-091.98533365676893e-09
1650.9999999975409284.91814399276968e-092.45907199638484e-09
1660.9999999976594194.68116133994393e-092.34058066997196e-09
1670.999999997994884.01023958254643e-092.00511979127322e-09
1680.9999999977027294.59454135488216e-092.29727067744108e-09
1690.999999997061795.87642093866312e-092.93821046933156e-09
1700.9999999993776491.24470142946287e-096.22350714731437e-10
1710.9999999991560881.68782477167915e-098.43912385839575e-10
1720.9999999985692112.86157902206393e-091.43078951103197e-09
1730.9999999975353344.92933157426769e-092.46466578713384e-09
1740.9999999986251962.74960820504887e-091.37480410252443e-09
1750.999999999843483.13040129675393e-101.56520064837697e-10
1760.9999999997517964.96407919863099e-102.48203959931549e-10
1770.9999999999778524.42961579196668e-112.21480789598334e-11
1780.9999999999588248.23514443618291e-114.11757221809146e-11
1790.9999999999920881.58249446146442e-117.91247230732209e-12
1800.9999999999879582.40843373730135e-111.20421686865068e-11
1810.999999999979264.14790235956326e-112.07395117978163e-11
1820.9999999999911291.77412809682686e-118.87064048413431e-12
1830.9999999999828693.42628362921815e-111.71314181460908e-11
1840.9999999999707955.84096269885334e-112.92048134942667e-11
1850.9999999999944931.10131672992983e-115.50658364964913e-12
1860.999999999989872.0259302616477e-111.01296513082385e-11
1870.9999999999868592.62818484295829e-111.31409242147914e-11
1880.9999999999831963.36083925519769e-111.68041962759885e-11
1890.9999999999752094.95821831589318e-112.47910915794659e-11
1900.9999999999662876.74255032667512e-113.37127516333756e-11
1910.9999999999374461.25107125148557e-106.25535625742784e-11
1920.9999999998813772.37246021025944e-101.18623010512972e-10
1930.9999999998096943.80612864972096e-101.90306432486048e-10
1940.9999999996531336.93733302859819e-103.46866651429909e-10
1950.9999999993432211.31355788367327e-096.56778941836635e-10
1960.999999999122611.75477961202497e-098.77389806012484e-10
1970.9999999984332623.13347537625957e-091.56673768812978e-09
1980.9999999998438973.12205761931961e-101.5610288096598e-10
1990.999999999876312.47380509835023e-101.23690254917511e-10
2000.999999999856372.87260972715906e-101.43630486357953e-10
2010.9999999997511084.97783057918126e-102.48891528959063e-10
2020.999999999737435.25139437405184e-102.62569718702592e-10
2030.9999999994927741.01445131820526e-095.07225659102631e-10
2040.9999999991853521.62929589988809e-098.14647949944047e-10
2050.9999999985969592.80608133552928e-091.40304066776464e-09
2060.999999997391455.21709996752506e-092.60854998376253e-09
2070.9999999953367859.32643088462096e-094.66321544231048e-09
2080.9999999911998091.76003811604249e-088.80019058021244e-09
2090.9999999853433922.93132153749986e-081.46566076874993e-08
2100.9999999871164732.57670541237205e-081.28835270618603e-08
2110.9999999827028313.45943386583315e-081.72971693291658e-08
2120.9999999677647046.44705911833049e-083.22352955916525e-08
2130.9999999403116681.19376664695083e-075.96883323475415e-08
2140.9999998950954612.09809077936178e-071.04904538968089e-07
2150.9999998801739642.39652072867532e-071.19826036433766e-07
2160.9999998658015882.68396824368603e-071.34198412184301e-07
2170.9999997619218214.76156357728992e-072.38078178864496e-07
2180.9999997255551735.48889654739034e-072.74444827369517e-07
2190.9999996297201387.40559723779237e-073.70279861889618e-07
2200.9999994221636631.15567267482372e-065.77836337411859e-07
2210.9999990001845021.99963099551612e-069.99815497758058e-07
2220.9999984674712313.06505753872601e-061.532528769363e-06
2230.999997980300114.03939978019043e-062.01969989009522e-06
2240.9999964564735657.0870528704232e-063.5435264352116e-06
2250.9999957672948778.46541024639583e-064.23270512319791e-06
2260.9999966771017356.64579652901047e-063.32289826450523e-06
2270.9999953885591639.22288167412519e-064.61144083706259e-06
2280.9999922600973661.54798052677302e-057.73990263386508e-06
2290.9999905205960851.89588078291943e-059.47940391459716e-06
2300.9999989994288992.00114220120964e-061.00057110060482e-06
2310.9999986836927882.63261442407452e-061.31630721203726e-06
2320.999997552668724.89466255990367e-062.44733127995184e-06
2330.9999965166655846.96666883145548e-063.48333441572774e-06
2340.9999936523168211.26953663582564e-056.34768317912821e-06
2350.9999891802468272.16395063458681e-051.08197531729341e-05
2360.9999809119891613.81760216776045e-051.90880108388023e-05
2370.9999663109485866.73781028279105e-053.36890514139553e-05
2380.9999688366659926.23266680157371e-053.11633340078685e-05
2390.9999520537824979.58924350055201e-054.794621750276e-05
2400.9999286947106540.0001426105786916767.13052893458378e-05
2410.9998907133978580.0002185732042846620.000109286602142331
2420.9998309217680830.0003381564638343370.000169078231917169
2430.9998082238958580.0003835522082849340.000191776104142467
2440.9996928172858850.0006143654282302490.000307182714115124
2450.9994821745351070.00103565092978540.000517825464892698
2460.9993046064124480.001390787175103060.000695393587551532
2470.9990137596423320.001972480715335740.000986240357667872
2480.9983871881086290.003225623782741440.00161281189137072
2490.9978115815814220.004376836837155740.00218841841857787
2500.9991440489291550.001711902141690970.000855951070845484
2510.9985680575470690.002863884905861840.00143194245293092
2520.9977397139387860.004520572122428820.00226028606121441
2530.9963582730880980.007283453823803410.00364172691190171
2540.9941294138951610.01174117220967860.00587058610483932
2550.9928561074112340.01428778517753220.00714389258876609
2560.9897800836703790.02043983265924220.0102199163296211
2570.9864737262857990.02705254742840260.0135262737142013
2580.9797665217288240.04046695654235160.0202334782711758
2590.9745343054705720.05093138905885580.0254656945294279
2600.9651333316611380.06973333667772420.0348666683388621
2610.9672352604530440.06552947909391120.0327647395469556
2620.9508043419100010.09839131617999870.0491956580899993
2630.9419332609829030.1161334780341930.0580667390170967
2640.9156187488136370.1687625023727250.0843812511863625
2650.8886909026830710.2226181946338580.111309097316929
2660.8440069629548680.3119860740902640.155993037045132
2670.8164703304704340.3670593390591320.183529669529566
2680.8108572977297990.3782854045404010.189142702270201
2690.7544532796590810.4910934406818390.245546720340919
2700.6824227426181630.6351545147636730.317577257381837
2710.7653882421891840.4692235156216320.234611757810816
2720.6765643936020410.6468712127959180.323435606397959
2730.6555668097047670.6888663805904660.344433190295233
2740.9140713251555430.1718573496889150.0859286748444573
2750.9442958501262730.1114082997474540.0557041498737272
2760.8908385467714270.2183229064571460.109161453228573
2770.9058514600343670.1882970799312650.0941485399656325

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.307162737710087 & 0.614325475420173 & 0.692837262289913 \tabularnewline
13 & 0.168059014093459 & 0.336118028186919 & 0.831940985906541 \tabularnewline
14 & 0.0838351787540781 & 0.167670357508156 & 0.916164821245922 \tabularnewline
15 & 0.0434149713496709 & 0.0868299426993418 & 0.956585028650329 \tabularnewline
16 & 0.0224735714752952 & 0.0449471429505903 & 0.977526428524705 \tabularnewline
17 & 0.0233934705216235 & 0.0467869410432469 & 0.976606529478377 \tabularnewline
18 & 0.0373874586182574 & 0.0747749172365148 & 0.962612541381743 \tabularnewline
19 & 0.0509889296017851 & 0.10197785920357 & 0.949011070398215 \tabularnewline
20 & 0.0675983006949234 & 0.135196601389847 & 0.932401699305077 \tabularnewline
21 & 0.10184023268223 & 0.20368046536446 & 0.89815976731777 \tabularnewline
22 & 0.0719252485536008 & 0.143850497107202 & 0.928074751446399 \tabularnewline
23 & 0.0492934097329 & 0.0985868194658001 & 0.9507065902671 \tabularnewline
24 & 0.0414867556876724 & 0.0829735113753447 & 0.958513244312328 \tabularnewline
25 & 0.0374234275957431 & 0.0748468551914862 & 0.962576572404257 \tabularnewline
26 & 0.0560352855124352 & 0.11207057102487 & 0.943964714487565 \tabularnewline
27 & 0.0382384671180872 & 0.0764769342361744 & 0.961761532881913 \tabularnewline
28 & 0.0257802858181082 & 0.0515605716362165 & 0.974219714181892 \tabularnewline
29 & 0.0200412842785237 & 0.0400825685570474 & 0.979958715721476 \tabularnewline
30 & 0.0147194135434067 & 0.0294388270868133 & 0.985280586456593 \tabularnewline
31 & 0.0120136625995037 & 0.0240273251990074 & 0.987986337400496 \tabularnewline
32 & 0.00778576659785089 & 0.0155715331957018 & 0.992214233402149 \tabularnewline
33 & 0.00537067822529468 & 0.0107413564505894 & 0.994629321774705 \tabularnewline
34 & 0.00344568408905319 & 0.00689136817810639 & 0.996554315910947 \tabularnewline
35 & 0.0091511724193997 & 0.0183023448387994 & 0.9908488275806 \tabularnewline
36 & 0.0132863458716699 & 0.0265726917433398 & 0.98671365412833 \tabularnewline
37 & 0.00893715709973556 & 0.0178743141994711 & 0.991062842900264 \tabularnewline
38 & 0.0083076890529553 & 0.0166153781059106 & 0.991692310947045 \tabularnewline
39 & 0.00582822204811517 & 0.0116564440962303 & 0.994171777951885 \tabularnewline
40 & 0.00405721936043301 & 0.00811443872086601 & 0.995942780639567 \tabularnewline
41 & 0.00379883122038903 & 0.00759766244077806 & 0.996201168779611 \tabularnewline
42 & 0.00537791792531599 & 0.010755835850632 & 0.994622082074684 \tabularnewline
43 & 0.00353866389734202 & 0.00707732779468404 & 0.996461336102658 \tabularnewline
44 & 0.00273675535787459 & 0.00547351071574917 & 0.997263244642125 \tabularnewline
45 & 0.00829820823118939 & 0.0165964164623788 & 0.991701791768811 \tabularnewline
46 & 0.00691576687548951 & 0.013831533750979 & 0.99308423312451 \tabularnewline
47 & 0.00475663845663398 & 0.00951327691326795 & 0.995243361543366 \tabularnewline
48 & 0.00325543919364168 & 0.00651087838728336 & 0.996744560806358 \tabularnewline
49 & 0.00241160582741129 & 0.00482321165482258 & 0.997588394172589 \tabularnewline
50 & 0.00431943733700893 & 0.00863887467401785 & 0.995680562662991 \tabularnewline
51 & 0.0215442019214486 & 0.0430884038428972 & 0.978455798078551 \tabularnewline
52 & 0.0180713597811703 & 0.0361427195623407 & 0.98192864021883 \tabularnewline
53 & 0.0131819504259212 & 0.0263639008518423 & 0.986818049574079 \tabularnewline
54 & 0.0228067888406283 & 0.0456135776812567 & 0.977193211159372 \tabularnewline
55 & 0.019582198017446 & 0.0391643960348919 & 0.980417801982554 \tabularnewline
56 & 0.0155562830914978 & 0.0311125661829955 & 0.984443716908502 \tabularnewline
57 & 0.0132034897051744 & 0.0264069794103488 & 0.986796510294826 \tabularnewline
58 & 0.0102504638367127 & 0.0205009276734255 & 0.989749536163287 \tabularnewline
59 & 0.00755091987854981 & 0.0151018397570996 & 0.99244908012145 \tabularnewline
60 & 0.00580214979955788 & 0.0116042995991158 & 0.994197850200442 \tabularnewline
61 & 0.00419566531629368 & 0.00839133063258735 & 0.995804334683706 \tabularnewline
62 & 0.00678020407576238 & 0.0135604081515248 & 0.993219795924238 \tabularnewline
63 & 0.014691703548317 & 0.029383407096634 & 0.985308296451683 \tabularnewline
64 & 0.0113447786449003 & 0.0226895572898007 & 0.9886552213551 \tabularnewline
65 & 0.010333443628673 & 0.020666887257346 & 0.989666556371327 \tabularnewline
66 & 0.00976150955166476 & 0.0195230191033295 & 0.990238490448335 \tabularnewline
67 & 0.00787038873139669 & 0.0157407774627934 & 0.992129611268603 \tabularnewline
68 & 0.00623868799828428 & 0.0124773759965686 & 0.993761312001716 \tabularnewline
69 & 0.00470705092478461 & 0.00941410184956922 & 0.995292949075215 \tabularnewline
70 & 0.00676697134036457 & 0.0135339426807291 & 0.993233028659635 \tabularnewline
71 & 0.00519365617972087 & 0.0103873123594417 & 0.994806343820279 \tabularnewline
72 & 0.00388917257673788 & 0.00777834515347576 & 0.996110827423262 \tabularnewline
73 & 0.00402420854294824 & 0.00804841708589647 & 0.995975791457052 \tabularnewline
74 & 0.00629394452643156 & 0.0125878890528631 & 0.993706055473568 \tabularnewline
75 & 0.00877126091130884 & 0.0175425218226177 & 0.991228739088691 \tabularnewline
76 & 0.00721892173675679 & 0.0144378434735136 & 0.992781078263243 \tabularnewline
77 & 0.00582615489375107 & 0.0116523097875021 & 0.994173845106249 \tabularnewline
78 & 0.00680275381784102 & 0.013605507635682 & 0.993197246182159 \tabularnewline
79 & 0.00634992698587423 & 0.0126998539717485 & 0.993650073014126 \tabularnewline
80 & 0.00552775827434238 & 0.0110555165486848 & 0.994472241725658 \tabularnewline
81 & 0.00417314047198738 & 0.00834628094397476 & 0.995826859528013 \tabularnewline
82 & 0.00314507345264094 & 0.00629014690528188 & 0.996854926547359 \tabularnewline
83 & 0.00236956117149445 & 0.00473912234298889 & 0.997630438828506 \tabularnewline
84 & 0.00174853157401435 & 0.00349706314802869 & 0.998251468425986 \tabularnewline
85 & 0.978200842647367 & 0.0435983147052651 & 0.0217991573526325 \tabularnewline
86 & 0.973424623178804 & 0.0531507536423924 & 0.0265753768211962 \tabularnewline
87 & 0.96759707505429 & 0.0648058498914204 & 0.0324029249457102 \tabularnewline
88 & 0.962095256897006 & 0.0758094862059878 & 0.0379047431029939 \tabularnewline
89 & 0.956352197939224 & 0.0872956041215529 & 0.0436478020607764 \tabularnewline
90 & 0.958957792356913 & 0.0820844152861738 & 0.0410422076430869 \tabularnewline
91 & 0.951166036694405 & 0.0976679266111894 & 0.0488339633055947 \tabularnewline
92 & 0.948990327631812 & 0.102019344736376 & 0.0510096723681878 \tabularnewline
93 & 0.945218763999909 & 0.109562472000181 & 0.0547812360000906 \tabularnewline
94 & 0.937889089623603 & 0.124221820752793 & 0.0621109103763966 \tabularnewline
95 & 0.928587650979537 & 0.142824698040925 & 0.0714123490204627 \tabularnewline
96 & 0.920234463383876 & 0.159531073232248 & 0.0797655366161241 \tabularnewline
97 & 0.936153369821712 & 0.127693260356576 & 0.0638466301782882 \tabularnewline
98 & 0.952870858410319 & 0.0942582831793622 & 0.0471291415896811 \tabularnewline
99 & 0.957187258127266 & 0.0856254837454673 & 0.0428127418727336 \tabularnewline
100 & 0.951312851721467 & 0.097374296557066 & 0.048687148278533 \tabularnewline
101 & 0.946227406390528 & 0.107545187218943 & 0.0537725936094715 \tabularnewline
102 & 0.940748634855899 & 0.118502730288203 & 0.0592513651441015 \tabularnewline
103 & 0.931064576015634 & 0.137870847968731 & 0.0689354239843657 \tabularnewline
104 & 0.952931418150764 & 0.0941371636984712 & 0.0470685818492356 \tabularnewline
105 & 0.961263931255327 & 0.0774721374893451 & 0.0387360687446726 \tabularnewline
106 & 0.9738539411205 & 0.0522921177590002 & 0.0261460588795001 \tabularnewline
107 & 0.976115959909705 & 0.0477680801805908 & 0.0238840400902954 \tabularnewline
108 & 0.97111813095526 & 0.0577637380894801 & 0.0288818690447401 \tabularnewline
109 & 0.967491990062118 & 0.0650160198757635 & 0.0325080099378817 \tabularnewline
110 & 0.962943469175163 & 0.0741130616496748 & 0.0370565308248374 \tabularnewline
111 & 0.961433402928173 & 0.0771331941436548 & 0.0385665970718274 \tabularnewline
112 & 0.963393056879916 & 0.0732138862401683 & 0.0366069431200842 \tabularnewline
113 & 0.956060943663255 & 0.0878781126734906 & 0.0439390563367453 \tabularnewline
114 & 0.964534338006878 & 0.0709313239862447 & 0.0354656619931224 \tabularnewline
115 & 0.965324811387905 & 0.0693503772241893 & 0.0346751886120946 \tabularnewline
116 & 0.961986192173231 & 0.0760276156535377 & 0.0380138078267689 \tabularnewline
117 & 0.95478301624208 & 0.0904339675158394 & 0.0452169837579197 \tabularnewline
118 & 0.947522130816579 & 0.104955738366842 & 0.0524778691834211 \tabularnewline
119 & 0.999928434510088 & 0.000143130979823454 & 7.15654899117272e-05 \tabularnewline
120 & 0.99990458187232 & 0.000190836255359711 & 9.54181276798557e-05 \tabularnewline
121 & 0.999875947779434 & 0.000248104441131819 & 0.00012405222056591 \tabularnewline
122 & 0.999835318557991 & 0.000329362884016977 & 0.000164681442008489 \tabularnewline
123 & 0.999804110973671 & 0.000391778052658934 & 0.000195889026329467 \tabularnewline
124 & 0.999999911139597 & 1.77720806666458e-07 & 8.88604033332291e-08 \tabularnewline
125 & 0.99999991664603 & 1.66707939718016e-07 & 8.33539698590079e-08 \tabularnewline
126 & 0.999999876995847 & 2.46008305862999e-07 & 1.230041529315e-07 \tabularnewline
127 & 0.999999839308905 & 3.21382190098605e-07 & 1.60691095049303e-07 \tabularnewline
128 & 0.999999774774658 & 4.50450684529841e-07 & 2.2522534226492e-07 \tabularnewline
129 & 0.999999696332352 & 6.07335295098377e-07 & 3.03667647549188e-07 \tabularnewline
130 & 0.99999956061894 & 8.78762119673757e-07 & 4.39381059836879e-07 \tabularnewline
131 & 0.999999356721816 & 1.28655636828307e-06 & 6.43278184141537e-07 \tabularnewline
132 & 0.99999927248322 & 1.45503355982845e-06 & 7.27516779914225e-07 \tabularnewline
133 & 0.999999019256633 & 1.96148673352157e-06 & 9.80743366760785e-07 \tabularnewline
134 & 0.999998712998785 & 2.57400242934988e-06 & 1.28700121467494e-06 \tabularnewline
135 & 0.999999449410062 & 1.10117987551046e-06 & 5.5058993775523e-07 \tabularnewline
136 & 0.999999589702812 & 8.20594375908474e-07 & 4.10297187954237e-07 \tabularnewline
137 & 0.999999403213033 & 1.19357393348075e-06 & 5.96786966740377e-07 \tabularnewline
138 & 0.999999373972869 & 1.25205426154746e-06 & 6.26027130773731e-07 \tabularnewline
139 & 0.999999623325729 & 7.53348541593027e-07 & 3.76674270796514e-07 \tabularnewline
140 & 0.99999946683449 & 1.06633102056118e-06 & 5.3316551028059e-07 \tabularnewline
141 & 0.999999205039541 & 1.58992091758255e-06 & 7.94960458791276e-07 \tabularnewline
142 & 0.999999167478988 & 1.66504202458715e-06 & 8.32521012293573e-07 \tabularnewline
143 & 0.999998734507892 & 2.5309842159664e-06 & 1.2654921079832e-06 \tabularnewline
144 & 0.999998811585163 & 2.37682967463274e-06 & 1.18841483731637e-06 \tabularnewline
145 & 0.999998705099953 & 2.58980009375314e-06 & 1.29490004687657e-06 \tabularnewline
146 & 0.999998061512305 & 3.87697539036247e-06 & 1.93848769518123e-06 \tabularnewline
147 & 0.999998948339657 & 2.10332068689618e-06 & 1.05166034344809e-06 \tabularnewline
148 & 0.999999583483797 & 8.33032405218933e-07 & 4.16516202609467e-07 \tabularnewline
149 & 0.999999416095606 & 1.16780878858001e-06 & 5.83904394290005e-07 \tabularnewline
150 & 0.999999281257577 & 1.43748484617728e-06 & 7.18742423088642e-07 \tabularnewline
151 & 0.999999102010115 & 1.79597977072082e-06 & 8.97989885360412e-07 \tabularnewline
152 & 0.999999276391825 & 1.44721635045561e-06 & 7.23608175227805e-07 \tabularnewline
153 & 0.999998929336656 & 2.14132668789349e-06 & 1.07066334394675e-06 \tabularnewline
154 & 0.999999572550349 & 8.54899302293573e-07 & 4.27449651146787e-07 \tabularnewline
155 & 0.999999378856261 & 1.24228747700896e-06 & 6.2114373850448e-07 \tabularnewline
156 & 0.999999973932928 & 5.21341431284134e-08 & 2.60670715642067e-08 \tabularnewline
157 & 0.999999957904404 & 8.41911913609392e-08 & 4.20955956804696e-08 \tabularnewline
158 & 0.999999931738119 & 1.36523761249427e-07 & 6.82618806247137e-08 \tabularnewline
159 & 0.999999901228445 & 1.97543109783902e-07 & 9.87715548919508e-08 \tabularnewline
160 & 0.999999875461559 & 2.4907688144522e-07 & 1.2453844072261e-07 \tabularnewline
161 & 0.999999802556893 & 3.9488621314868e-07 & 1.9744310657434e-07 \tabularnewline
162 & 0.999999998009488 & 3.98102306165787e-09 & 1.99051153082894e-09 \tabularnewline
163 & 0.999999996951462 & 6.09707646715513e-09 & 3.04853823357757e-09 \tabularnewline
164 & 0.999999998014666 & 3.97066731353787e-09 & 1.98533365676893e-09 \tabularnewline
165 & 0.999999997540928 & 4.91814399276968e-09 & 2.45907199638484e-09 \tabularnewline
166 & 0.999999997659419 & 4.68116133994393e-09 & 2.34058066997196e-09 \tabularnewline
167 & 0.99999999799488 & 4.01023958254643e-09 & 2.00511979127322e-09 \tabularnewline
168 & 0.999999997702729 & 4.59454135488216e-09 & 2.29727067744108e-09 \tabularnewline
169 & 0.99999999706179 & 5.87642093866312e-09 & 2.93821046933156e-09 \tabularnewline
170 & 0.999999999377649 & 1.24470142946287e-09 & 6.22350714731437e-10 \tabularnewline
171 & 0.999999999156088 & 1.68782477167915e-09 & 8.43912385839575e-10 \tabularnewline
172 & 0.999999998569211 & 2.86157902206393e-09 & 1.43078951103197e-09 \tabularnewline
173 & 0.999999997535334 & 4.92933157426769e-09 & 2.46466578713384e-09 \tabularnewline
174 & 0.999999998625196 & 2.74960820504887e-09 & 1.37480410252443e-09 \tabularnewline
175 & 0.99999999984348 & 3.13040129675393e-10 & 1.56520064837697e-10 \tabularnewline
176 & 0.999999999751796 & 4.96407919863099e-10 & 2.48203959931549e-10 \tabularnewline
177 & 0.999999999977852 & 4.42961579196668e-11 & 2.21480789598334e-11 \tabularnewline
178 & 0.999999999958824 & 8.23514443618291e-11 & 4.11757221809146e-11 \tabularnewline
179 & 0.999999999992088 & 1.58249446146442e-11 & 7.91247230732209e-12 \tabularnewline
180 & 0.999999999987958 & 2.40843373730135e-11 & 1.20421686865068e-11 \tabularnewline
181 & 0.99999999997926 & 4.14790235956326e-11 & 2.07395117978163e-11 \tabularnewline
182 & 0.999999999991129 & 1.77412809682686e-11 & 8.87064048413431e-12 \tabularnewline
183 & 0.999999999982869 & 3.42628362921815e-11 & 1.71314181460908e-11 \tabularnewline
184 & 0.999999999970795 & 5.84096269885334e-11 & 2.92048134942667e-11 \tabularnewline
185 & 0.999999999994493 & 1.10131672992983e-11 & 5.50658364964913e-12 \tabularnewline
186 & 0.99999999998987 & 2.0259302616477e-11 & 1.01296513082385e-11 \tabularnewline
187 & 0.999999999986859 & 2.62818484295829e-11 & 1.31409242147914e-11 \tabularnewline
188 & 0.999999999983196 & 3.36083925519769e-11 & 1.68041962759885e-11 \tabularnewline
189 & 0.999999999975209 & 4.95821831589318e-11 & 2.47910915794659e-11 \tabularnewline
190 & 0.999999999966287 & 6.74255032667512e-11 & 3.37127516333756e-11 \tabularnewline
191 & 0.999999999937446 & 1.25107125148557e-10 & 6.25535625742784e-11 \tabularnewline
192 & 0.999999999881377 & 2.37246021025944e-10 & 1.18623010512972e-10 \tabularnewline
193 & 0.999999999809694 & 3.80612864972096e-10 & 1.90306432486048e-10 \tabularnewline
194 & 0.999999999653133 & 6.93733302859819e-10 & 3.46866651429909e-10 \tabularnewline
195 & 0.999999999343221 & 1.31355788367327e-09 & 6.56778941836635e-10 \tabularnewline
196 & 0.99999999912261 & 1.75477961202497e-09 & 8.77389806012484e-10 \tabularnewline
197 & 0.999999998433262 & 3.13347537625957e-09 & 1.56673768812978e-09 \tabularnewline
198 & 0.999999999843897 & 3.12205761931961e-10 & 1.5610288096598e-10 \tabularnewline
199 & 0.99999999987631 & 2.47380509835023e-10 & 1.23690254917511e-10 \tabularnewline
200 & 0.99999999985637 & 2.87260972715906e-10 & 1.43630486357953e-10 \tabularnewline
201 & 0.999999999751108 & 4.97783057918126e-10 & 2.48891528959063e-10 \tabularnewline
202 & 0.99999999973743 & 5.25139437405184e-10 & 2.62569718702592e-10 \tabularnewline
203 & 0.999999999492774 & 1.01445131820526e-09 & 5.07225659102631e-10 \tabularnewline
204 & 0.999999999185352 & 1.62929589988809e-09 & 8.14647949944047e-10 \tabularnewline
205 & 0.999999998596959 & 2.80608133552928e-09 & 1.40304066776464e-09 \tabularnewline
206 & 0.99999999739145 & 5.21709996752506e-09 & 2.60854998376253e-09 \tabularnewline
207 & 0.999999995336785 & 9.32643088462096e-09 & 4.66321544231048e-09 \tabularnewline
208 & 0.999999991199809 & 1.76003811604249e-08 & 8.80019058021244e-09 \tabularnewline
209 & 0.999999985343392 & 2.93132153749986e-08 & 1.46566076874993e-08 \tabularnewline
210 & 0.999999987116473 & 2.57670541237205e-08 & 1.28835270618603e-08 \tabularnewline
211 & 0.999999982702831 & 3.45943386583315e-08 & 1.72971693291658e-08 \tabularnewline
212 & 0.999999967764704 & 6.44705911833049e-08 & 3.22352955916525e-08 \tabularnewline
213 & 0.999999940311668 & 1.19376664695083e-07 & 5.96883323475415e-08 \tabularnewline
214 & 0.999999895095461 & 2.09809077936178e-07 & 1.04904538968089e-07 \tabularnewline
215 & 0.999999880173964 & 2.39652072867532e-07 & 1.19826036433766e-07 \tabularnewline
216 & 0.999999865801588 & 2.68396824368603e-07 & 1.34198412184301e-07 \tabularnewline
217 & 0.999999761921821 & 4.76156357728992e-07 & 2.38078178864496e-07 \tabularnewline
218 & 0.999999725555173 & 5.48889654739034e-07 & 2.74444827369517e-07 \tabularnewline
219 & 0.999999629720138 & 7.40559723779237e-07 & 3.70279861889618e-07 \tabularnewline
220 & 0.999999422163663 & 1.15567267482372e-06 & 5.77836337411859e-07 \tabularnewline
221 & 0.999999000184502 & 1.99963099551612e-06 & 9.99815497758058e-07 \tabularnewline
222 & 0.999998467471231 & 3.06505753872601e-06 & 1.532528769363e-06 \tabularnewline
223 & 0.99999798030011 & 4.03939978019043e-06 & 2.01969989009522e-06 \tabularnewline
224 & 0.999996456473565 & 7.0870528704232e-06 & 3.5435264352116e-06 \tabularnewline
225 & 0.999995767294877 & 8.46541024639583e-06 & 4.23270512319791e-06 \tabularnewline
226 & 0.999996677101735 & 6.64579652901047e-06 & 3.32289826450523e-06 \tabularnewline
227 & 0.999995388559163 & 9.22288167412519e-06 & 4.61144083706259e-06 \tabularnewline
228 & 0.999992260097366 & 1.54798052677302e-05 & 7.73990263386508e-06 \tabularnewline
229 & 0.999990520596085 & 1.89588078291943e-05 & 9.47940391459716e-06 \tabularnewline
230 & 0.999998999428899 & 2.00114220120964e-06 & 1.00057110060482e-06 \tabularnewline
231 & 0.999998683692788 & 2.63261442407452e-06 & 1.31630721203726e-06 \tabularnewline
232 & 0.99999755266872 & 4.89466255990367e-06 & 2.44733127995184e-06 \tabularnewline
233 & 0.999996516665584 & 6.96666883145548e-06 & 3.48333441572774e-06 \tabularnewline
234 & 0.999993652316821 & 1.26953663582564e-05 & 6.34768317912821e-06 \tabularnewline
235 & 0.999989180246827 & 2.16395063458681e-05 & 1.08197531729341e-05 \tabularnewline
236 & 0.999980911989161 & 3.81760216776045e-05 & 1.90880108388023e-05 \tabularnewline
237 & 0.999966310948586 & 6.73781028279105e-05 & 3.36890514139553e-05 \tabularnewline
238 & 0.999968836665992 & 6.23266680157371e-05 & 3.11633340078685e-05 \tabularnewline
239 & 0.999952053782497 & 9.58924350055201e-05 & 4.794621750276e-05 \tabularnewline
240 & 0.999928694710654 & 0.000142610578691676 & 7.13052893458378e-05 \tabularnewline
241 & 0.999890713397858 & 0.000218573204284662 & 0.000109286602142331 \tabularnewline
242 & 0.999830921768083 & 0.000338156463834337 & 0.000169078231917169 \tabularnewline
243 & 0.999808223895858 & 0.000383552208284934 & 0.000191776104142467 \tabularnewline
244 & 0.999692817285885 & 0.000614365428230249 & 0.000307182714115124 \tabularnewline
245 & 0.999482174535107 & 0.0010356509297854 & 0.000517825464892698 \tabularnewline
246 & 0.999304606412448 & 0.00139078717510306 & 0.000695393587551532 \tabularnewline
247 & 0.999013759642332 & 0.00197248071533574 & 0.000986240357667872 \tabularnewline
248 & 0.998387188108629 & 0.00322562378274144 & 0.00161281189137072 \tabularnewline
249 & 0.997811581581422 & 0.00437683683715574 & 0.00218841841857787 \tabularnewline
250 & 0.999144048929155 & 0.00171190214169097 & 0.000855951070845484 \tabularnewline
251 & 0.998568057547069 & 0.00286388490586184 & 0.00143194245293092 \tabularnewline
252 & 0.997739713938786 & 0.00452057212242882 & 0.00226028606121441 \tabularnewline
253 & 0.996358273088098 & 0.00728345382380341 & 0.00364172691190171 \tabularnewline
254 & 0.994129413895161 & 0.0117411722096786 & 0.00587058610483932 \tabularnewline
255 & 0.992856107411234 & 0.0142877851775322 & 0.00714389258876609 \tabularnewline
256 & 0.989780083670379 & 0.0204398326592422 & 0.0102199163296211 \tabularnewline
257 & 0.986473726285799 & 0.0270525474284026 & 0.0135262737142013 \tabularnewline
258 & 0.979766521728824 & 0.0404669565423516 & 0.0202334782711758 \tabularnewline
259 & 0.974534305470572 & 0.0509313890588558 & 0.0254656945294279 \tabularnewline
260 & 0.965133331661138 & 0.0697333366777242 & 0.0348666683388621 \tabularnewline
261 & 0.967235260453044 & 0.0655294790939112 & 0.0327647395469556 \tabularnewline
262 & 0.950804341910001 & 0.0983913161799987 & 0.0491956580899993 \tabularnewline
263 & 0.941933260982903 & 0.116133478034193 & 0.0580667390170967 \tabularnewline
264 & 0.915618748813637 & 0.168762502372725 & 0.0843812511863625 \tabularnewline
265 & 0.888690902683071 & 0.222618194633858 & 0.111309097316929 \tabularnewline
266 & 0.844006962954868 & 0.311986074090264 & 0.155993037045132 \tabularnewline
267 & 0.816470330470434 & 0.367059339059132 & 0.183529669529566 \tabularnewline
268 & 0.810857297729799 & 0.378285404540401 & 0.189142702270201 \tabularnewline
269 & 0.754453279659081 & 0.491093440681839 & 0.245546720340919 \tabularnewline
270 & 0.682422742618163 & 0.635154514763673 & 0.317577257381837 \tabularnewline
271 & 0.765388242189184 & 0.469223515621632 & 0.234611757810816 \tabularnewline
272 & 0.676564393602041 & 0.646871212795918 & 0.323435606397959 \tabularnewline
273 & 0.655566809704767 & 0.688866380590466 & 0.344433190295233 \tabularnewline
274 & 0.914071325155543 & 0.171857349688915 & 0.0859286748444573 \tabularnewline
275 & 0.944295850126273 & 0.111408299747454 & 0.0557041498737272 \tabularnewline
276 & 0.890838546771427 & 0.218322906457146 & 0.109161453228573 \tabularnewline
277 & 0.905851460034367 & 0.188297079931265 & 0.0941485399656325 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156535&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]12[/C][C]0.307162737710087[/C][C]0.614325475420173[/C][C]0.692837262289913[/C][/ROW]
[ROW][C]13[/C][C]0.168059014093459[/C][C]0.336118028186919[/C][C]0.831940985906541[/C][/ROW]
[ROW][C]14[/C][C]0.0838351787540781[/C][C]0.167670357508156[/C][C]0.916164821245922[/C][/ROW]
[ROW][C]15[/C][C]0.0434149713496709[/C][C]0.0868299426993418[/C][C]0.956585028650329[/C][/ROW]
[ROW][C]16[/C][C]0.0224735714752952[/C][C]0.0449471429505903[/C][C]0.977526428524705[/C][/ROW]
[ROW][C]17[/C][C]0.0233934705216235[/C][C]0.0467869410432469[/C][C]0.976606529478377[/C][/ROW]
[ROW][C]18[/C][C]0.0373874586182574[/C][C]0.0747749172365148[/C][C]0.962612541381743[/C][/ROW]
[ROW][C]19[/C][C]0.0509889296017851[/C][C]0.10197785920357[/C][C]0.949011070398215[/C][/ROW]
[ROW][C]20[/C][C]0.0675983006949234[/C][C]0.135196601389847[/C][C]0.932401699305077[/C][/ROW]
[ROW][C]21[/C][C]0.10184023268223[/C][C]0.20368046536446[/C][C]0.89815976731777[/C][/ROW]
[ROW][C]22[/C][C]0.0719252485536008[/C][C]0.143850497107202[/C][C]0.928074751446399[/C][/ROW]
[ROW][C]23[/C][C]0.0492934097329[/C][C]0.0985868194658001[/C][C]0.9507065902671[/C][/ROW]
[ROW][C]24[/C][C]0.0414867556876724[/C][C]0.0829735113753447[/C][C]0.958513244312328[/C][/ROW]
[ROW][C]25[/C][C]0.0374234275957431[/C][C]0.0748468551914862[/C][C]0.962576572404257[/C][/ROW]
[ROW][C]26[/C][C]0.0560352855124352[/C][C]0.11207057102487[/C][C]0.943964714487565[/C][/ROW]
[ROW][C]27[/C][C]0.0382384671180872[/C][C]0.0764769342361744[/C][C]0.961761532881913[/C][/ROW]
[ROW][C]28[/C][C]0.0257802858181082[/C][C]0.0515605716362165[/C][C]0.974219714181892[/C][/ROW]
[ROW][C]29[/C][C]0.0200412842785237[/C][C]0.0400825685570474[/C][C]0.979958715721476[/C][/ROW]
[ROW][C]30[/C][C]0.0147194135434067[/C][C]0.0294388270868133[/C][C]0.985280586456593[/C][/ROW]
[ROW][C]31[/C][C]0.0120136625995037[/C][C]0.0240273251990074[/C][C]0.987986337400496[/C][/ROW]
[ROW][C]32[/C][C]0.00778576659785089[/C][C]0.0155715331957018[/C][C]0.992214233402149[/C][/ROW]
[ROW][C]33[/C][C]0.00537067822529468[/C][C]0.0107413564505894[/C][C]0.994629321774705[/C][/ROW]
[ROW][C]34[/C][C]0.00344568408905319[/C][C]0.00689136817810639[/C][C]0.996554315910947[/C][/ROW]
[ROW][C]35[/C][C]0.0091511724193997[/C][C]0.0183023448387994[/C][C]0.9908488275806[/C][/ROW]
[ROW][C]36[/C][C]0.0132863458716699[/C][C]0.0265726917433398[/C][C]0.98671365412833[/C][/ROW]
[ROW][C]37[/C][C]0.00893715709973556[/C][C]0.0178743141994711[/C][C]0.991062842900264[/C][/ROW]
[ROW][C]38[/C][C]0.0083076890529553[/C][C]0.0166153781059106[/C][C]0.991692310947045[/C][/ROW]
[ROW][C]39[/C][C]0.00582822204811517[/C][C]0.0116564440962303[/C][C]0.994171777951885[/C][/ROW]
[ROW][C]40[/C][C]0.00405721936043301[/C][C]0.00811443872086601[/C][C]0.995942780639567[/C][/ROW]
[ROW][C]41[/C][C]0.00379883122038903[/C][C]0.00759766244077806[/C][C]0.996201168779611[/C][/ROW]
[ROW][C]42[/C][C]0.00537791792531599[/C][C]0.010755835850632[/C][C]0.994622082074684[/C][/ROW]
[ROW][C]43[/C][C]0.00353866389734202[/C][C]0.00707732779468404[/C][C]0.996461336102658[/C][/ROW]
[ROW][C]44[/C][C]0.00273675535787459[/C][C]0.00547351071574917[/C][C]0.997263244642125[/C][/ROW]
[ROW][C]45[/C][C]0.00829820823118939[/C][C]0.0165964164623788[/C][C]0.991701791768811[/C][/ROW]
[ROW][C]46[/C][C]0.00691576687548951[/C][C]0.013831533750979[/C][C]0.99308423312451[/C][/ROW]
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[ROW][C]126[/C][C]0.999999876995847[/C][C]2.46008305862999e-07[/C][C]1.230041529315e-07[/C][/ROW]
[ROW][C]127[/C][C]0.999999839308905[/C][C]3.21382190098605e-07[/C][C]1.60691095049303e-07[/C][/ROW]
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[ROW][C]129[/C][C]0.999999696332352[/C][C]6.07335295098377e-07[/C][C]3.03667647549188e-07[/C][/ROW]
[ROW][C]130[/C][C]0.99999956061894[/C][C]8.78762119673757e-07[/C][C]4.39381059836879e-07[/C][/ROW]
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[ROW][C]185[/C][C]0.999999999994493[/C][C]1.10131672992983e-11[/C][C]5.50658364964913e-12[/C][/ROW]
[ROW][C]186[/C][C]0.99999999998987[/C][C]2.0259302616477e-11[/C][C]1.01296513082385e-11[/C][/ROW]
[ROW][C]187[/C][C]0.999999999986859[/C][C]2.62818484295829e-11[/C][C]1.31409242147914e-11[/C][/ROW]
[ROW][C]188[/C][C]0.999999999983196[/C][C]3.36083925519769e-11[/C][C]1.68041962759885e-11[/C][/ROW]
[ROW][C]189[/C][C]0.999999999975209[/C][C]4.95821831589318e-11[/C][C]2.47910915794659e-11[/C][/ROW]
[ROW][C]190[/C][C]0.999999999966287[/C][C]6.74255032667512e-11[/C][C]3.37127516333756e-11[/C][/ROW]
[ROW][C]191[/C][C]0.999999999937446[/C][C]1.25107125148557e-10[/C][C]6.25535625742784e-11[/C][/ROW]
[ROW][C]192[/C][C]0.999999999881377[/C][C]2.37246021025944e-10[/C][C]1.18623010512972e-10[/C][/ROW]
[ROW][C]193[/C][C]0.999999999809694[/C][C]3.80612864972096e-10[/C][C]1.90306432486048e-10[/C][/ROW]
[ROW][C]194[/C][C]0.999999999653133[/C][C]6.93733302859819e-10[/C][C]3.46866651429909e-10[/C][/ROW]
[ROW][C]195[/C][C]0.999999999343221[/C][C]1.31355788367327e-09[/C][C]6.56778941836635e-10[/C][/ROW]
[ROW][C]196[/C][C]0.99999999912261[/C][C]1.75477961202497e-09[/C][C]8.77389806012484e-10[/C][/ROW]
[ROW][C]197[/C][C]0.999999998433262[/C][C]3.13347537625957e-09[/C][C]1.56673768812978e-09[/C][/ROW]
[ROW][C]198[/C][C]0.999999999843897[/C][C]3.12205761931961e-10[/C][C]1.5610288096598e-10[/C][/ROW]
[ROW][C]199[/C][C]0.99999999987631[/C][C]2.47380509835023e-10[/C][C]1.23690254917511e-10[/C][/ROW]
[ROW][C]200[/C][C]0.99999999985637[/C][C]2.87260972715906e-10[/C][C]1.43630486357953e-10[/C][/ROW]
[ROW][C]201[/C][C]0.999999999751108[/C][C]4.97783057918126e-10[/C][C]2.48891528959063e-10[/C][/ROW]
[ROW][C]202[/C][C]0.99999999973743[/C][C]5.25139437405184e-10[/C][C]2.62569718702592e-10[/C][/ROW]
[ROW][C]203[/C][C]0.999999999492774[/C][C]1.01445131820526e-09[/C][C]5.07225659102631e-10[/C][/ROW]
[ROW][C]204[/C][C]0.999999999185352[/C][C]1.62929589988809e-09[/C][C]8.14647949944047e-10[/C][/ROW]
[ROW][C]205[/C][C]0.999999998596959[/C][C]2.80608133552928e-09[/C][C]1.40304066776464e-09[/C][/ROW]
[ROW][C]206[/C][C]0.99999999739145[/C][C]5.21709996752506e-09[/C][C]2.60854998376253e-09[/C][/ROW]
[ROW][C]207[/C][C]0.999999995336785[/C][C]9.32643088462096e-09[/C][C]4.66321544231048e-09[/C][/ROW]
[ROW][C]208[/C][C]0.999999991199809[/C][C]1.76003811604249e-08[/C][C]8.80019058021244e-09[/C][/ROW]
[ROW][C]209[/C][C]0.999999985343392[/C][C]2.93132153749986e-08[/C][C]1.46566076874993e-08[/C][/ROW]
[ROW][C]210[/C][C]0.999999987116473[/C][C]2.57670541237205e-08[/C][C]1.28835270618603e-08[/C][/ROW]
[ROW][C]211[/C][C]0.999999982702831[/C][C]3.45943386583315e-08[/C][C]1.72971693291658e-08[/C][/ROW]
[ROW][C]212[/C][C]0.999999967764704[/C][C]6.44705911833049e-08[/C][C]3.22352955916525e-08[/C][/ROW]
[ROW][C]213[/C][C]0.999999940311668[/C][C]1.19376664695083e-07[/C][C]5.96883323475415e-08[/C][/ROW]
[ROW][C]214[/C][C]0.999999895095461[/C][C]2.09809077936178e-07[/C][C]1.04904538968089e-07[/C][/ROW]
[ROW][C]215[/C][C]0.999999880173964[/C][C]2.39652072867532e-07[/C][C]1.19826036433766e-07[/C][/ROW]
[ROW][C]216[/C][C]0.999999865801588[/C][C]2.68396824368603e-07[/C][C]1.34198412184301e-07[/C][/ROW]
[ROW][C]217[/C][C]0.999999761921821[/C][C]4.76156357728992e-07[/C][C]2.38078178864496e-07[/C][/ROW]
[ROW][C]218[/C][C]0.999999725555173[/C][C]5.48889654739034e-07[/C][C]2.74444827369517e-07[/C][/ROW]
[ROW][C]219[/C][C]0.999999629720138[/C][C]7.40559723779237e-07[/C][C]3.70279861889618e-07[/C][/ROW]
[ROW][C]220[/C][C]0.999999422163663[/C][C]1.15567267482372e-06[/C][C]5.77836337411859e-07[/C][/ROW]
[ROW][C]221[/C][C]0.999999000184502[/C][C]1.99963099551612e-06[/C][C]9.99815497758058e-07[/C][/ROW]
[ROW][C]222[/C][C]0.999998467471231[/C][C]3.06505753872601e-06[/C][C]1.532528769363e-06[/C][/ROW]
[ROW][C]223[/C][C]0.99999798030011[/C][C]4.03939978019043e-06[/C][C]2.01969989009522e-06[/C][/ROW]
[ROW][C]224[/C][C]0.999996456473565[/C][C]7.0870528704232e-06[/C][C]3.5435264352116e-06[/C][/ROW]
[ROW][C]225[/C][C]0.999995767294877[/C][C]8.46541024639583e-06[/C][C]4.23270512319791e-06[/C][/ROW]
[ROW][C]226[/C][C]0.999996677101735[/C][C]6.64579652901047e-06[/C][C]3.32289826450523e-06[/C][/ROW]
[ROW][C]227[/C][C]0.999995388559163[/C][C]9.22288167412519e-06[/C][C]4.61144083706259e-06[/C][/ROW]
[ROW][C]228[/C][C]0.999992260097366[/C][C]1.54798052677302e-05[/C][C]7.73990263386508e-06[/C][/ROW]
[ROW][C]229[/C][C]0.999990520596085[/C][C]1.89588078291943e-05[/C][C]9.47940391459716e-06[/C][/ROW]
[ROW][C]230[/C][C]0.999998999428899[/C][C]2.00114220120964e-06[/C][C]1.00057110060482e-06[/C][/ROW]
[ROW][C]231[/C][C]0.999998683692788[/C][C]2.63261442407452e-06[/C][C]1.31630721203726e-06[/C][/ROW]
[ROW][C]232[/C][C]0.99999755266872[/C][C]4.89466255990367e-06[/C][C]2.44733127995184e-06[/C][/ROW]
[ROW][C]233[/C][C]0.999996516665584[/C][C]6.96666883145548e-06[/C][C]3.48333441572774e-06[/C][/ROW]
[ROW][C]234[/C][C]0.999993652316821[/C][C]1.26953663582564e-05[/C][C]6.34768317912821e-06[/C][/ROW]
[ROW][C]235[/C][C]0.999989180246827[/C][C]2.16395063458681e-05[/C][C]1.08197531729341e-05[/C][/ROW]
[ROW][C]236[/C][C]0.999980911989161[/C][C]3.81760216776045e-05[/C][C]1.90880108388023e-05[/C][/ROW]
[ROW][C]237[/C][C]0.999966310948586[/C][C]6.73781028279105e-05[/C][C]3.36890514139553e-05[/C][/ROW]
[ROW][C]238[/C][C]0.999968836665992[/C][C]6.23266680157371e-05[/C][C]3.11633340078685e-05[/C][/ROW]
[ROW][C]239[/C][C]0.999952053782497[/C][C]9.58924350055201e-05[/C][C]4.794621750276e-05[/C][/ROW]
[ROW][C]240[/C][C]0.999928694710654[/C][C]0.000142610578691676[/C][C]7.13052893458378e-05[/C][/ROW]
[ROW][C]241[/C][C]0.999890713397858[/C][C]0.000218573204284662[/C][C]0.000109286602142331[/C][/ROW]
[ROW][C]242[/C][C]0.999830921768083[/C][C]0.000338156463834337[/C][C]0.000169078231917169[/C][/ROW]
[ROW][C]243[/C][C]0.999808223895858[/C][C]0.000383552208284934[/C][C]0.000191776104142467[/C][/ROW]
[ROW][C]244[/C][C]0.999692817285885[/C][C]0.000614365428230249[/C][C]0.000307182714115124[/C][/ROW]
[ROW][C]245[/C][C]0.999482174535107[/C][C]0.0010356509297854[/C][C]0.000517825464892698[/C][/ROW]
[ROW][C]246[/C][C]0.999304606412448[/C][C]0.00139078717510306[/C][C]0.000695393587551532[/C][/ROW]
[ROW][C]247[/C][C]0.999013759642332[/C][C]0.00197248071533574[/C][C]0.000986240357667872[/C][/ROW]
[ROW][C]248[/C][C]0.998387188108629[/C][C]0.00322562378274144[/C][C]0.00161281189137072[/C][/ROW]
[ROW][C]249[/C][C]0.997811581581422[/C][C]0.00437683683715574[/C][C]0.00218841841857787[/C][/ROW]
[ROW][C]250[/C][C]0.999144048929155[/C][C]0.00171190214169097[/C][C]0.000855951070845484[/C][/ROW]
[ROW][C]251[/C][C]0.998568057547069[/C][C]0.00286388490586184[/C][C]0.00143194245293092[/C][/ROW]
[ROW][C]252[/C][C]0.997739713938786[/C][C]0.00452057212242882[/C][C]0.00226028606121441[/C][/ROW]
[ROW][C]253[/C][C]0.996358273088098[/C][C]0.00728345382380341[/C][C]0.00364172691190171[/C][/ROW]
[ROW][C]254[/C][C]0.994129413895161[/C][C]0.0117411722096786[/C][C]0.00587058610483932[/C][/ROW]
[ROW][C]255[/C][C]0.992856107411234[/C][C]0.0142877851775322[/C][C]0.00714389258876609[/C][/ROW]
[ROW][C]256[/C][C]0.989780083670379[/C][C]0.0204398326592422[/C][C]0.0102199163296211[/C][/ROW]
[ROW][C]257[/C][C]0.986473726285799[/C][C]0.0270525474284026[/C][C]0.0135262737142013[/C][/ROW]
[ROW][C]258[/C][C]0.979766521728824[/C][C]0.0404669565423516[/C][C]0.0202334782711758[/C][/ROW]
[ROW][C]259[/C][C]0.974534305470572[/C][C]0.0509313890588558[/C][C]0.0254656945294279[/C][/ROW]
[ROW][C]260[/C][C]0.965133331661138[/C][C]0.0697333366777242[/C][C]0.0348666683388621[/C][/ROW]
[ROW][C]261[/C][C]0.967235260453044[/C][C]0.0655294790939112[/C][C]0.0327647395469556[/C][/ROW]
[ROW][C]262[/C][C]0.950804341910001[/C][C]0.0983913161799987[/C][C]0.0491956580899993[/C][/ROW]
[ROW][C]263[/C][C]0.941933260982903[/C][C]0.116133478034193[/C][C]0.0580667390170967[/C][/ROW]
[ROW][C]264[/C][C]0.915618748813637[/C][C]0.168762502372725[/C][C]0.0843812511863625[/C][/ROW]
[ROW][C]265[/C][C]0.888690902683071[/C][C]0.222618194633858[/C][C]0.111309097316929[/C][/ROW]
[ROW][C]266[/C][C]0.844006962954868[/C][C]0.311986074090264[/C][C]0.155993037045132[/C][/ROW]
[ROW][C]267[/C][C]0.816470330470434[/C][C]0.367059339059132[/C][C]0.183529669529566[/C][/ROW]
[ROW][C]268[/C][C]0.810857297729799[/C][C]0.378285404540401[/C][C]0.189142702270201[/C][/ROW]
[ROW][C]269[/C][C]0.754453279659081[/C][C]0.491093440681839[/C][C]0.245546720340919[/C][/ROW]
[ROW][C]270[/C][C]0.682422742618163[/C][C]0.635154514763673[/C][C]0.317577257381837[/C][/ROW]
[ROW][C]271[/C][C]0.765388242189184[/C][C]0.469223515621632[/C][C]0.234611757810816[/C][/ROW]
[ROW][C]272[/C][C]0.676564393602041[/C][C]0.646871212795918[/C][C]0.323435606397959[/C][/ROW]
[ROW][C]273[/C][C]0.655566809704767[/C][C]0.688866380590466[/C][C]0.344433190295233[/C][/ROW]
[ROW][C]274[/C][C]0.914071325155543[/C][C]0.171857349688915[/C][C]0.0859286748444573[/C][/ROW]
[ROW][C]275[/C][C]0.944295850126273[/C][C]0.111408299747454[/C][C]0.0557041498737272[/C][/ROW]
[ROW][C]276[/C][C]0.890838546771427[/C][C]0.218322906457146[/C][C]0.109161453228573[/C][/ROW]
[ROW][C]277[/C][C]0.905851460034367[/C][C]0.188297079931265[/C][C]0.0941485399656325[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156535&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156535&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.3071627377100870.6143254754201730.692837262289913
130.1680590140934590.3361180281869190.831940985906541
140.08383517875407810.1676703575081560.916164821245922
150.04341497134967090.08682994269934180.956585028650329
160.02247357147529520.04494714295059030.977526428524705
170.02339347052162350.04678694104324690.976606529478377
180.03738745861825740.07477491723651480.962612541381743
190.05098892960178510.101977859203570.949011070398215
200.06759830069492340.1351966013898470.932401699305077
210.101840232682230.203680465364460.89815976731777
220.07192524855360080.1438504971072020.928074751446399
230.04929340973290.09858681946580010.9507065902671
240.04148675568767240.08297351137534470.958513244312328
250.03742342759574310.07484685519148620.962576572404257
260.05603528551243520.112070571024870.943964714487565
270.03823846711808720.07647693423617440.961761532881913
280.02578028581810820.05156057163621650.974219714181892
290.02004128427852370.04008256855704740.979958715721476
300.01471941354340670.02943882708681330.985280586456593
310.01201366259950370.02402732519900740.987986337400496
320.007785766597850890.01557153319570180.992214233402149
330.005370678225294680.01074135645058940.994629321774705
340.003445684089053190.006891368178106390.996554315910947
350.00915117241939970.01830234483879940.9908488275806
360.01328634587166990.02657269174333980.98671365412833
370.008937157099735560.01787431419947110.991062842900264
380.00830768905295530.01661537810591060.991692310947045
390.005828222048115170.01165644409623030.994171777951885
400.004057219360433010.008114438720866010.995942780639567
410.003798831220389030.007597662440778060.996201168779611
420.005377917925315990.0107558358506320.994622082074684
430.003538663897342020.007077327794684040.996461336102658
440.002736755357874590.005473510715749170.997263244642125
450.008298208231189390.01659641646237880.991701791768811
460.006915766875489510.0138315337509790.99308423312451
470.004756638456633980.009513276913267950.995243361543366
480.003255439193641680.006510878387283360.996744560806358
490.002411605827411290.004823211654822580.997588394172589
500.004319437337008930.008638874674017850.995680562662991
510.02154420192144860.04308840384289720.978455798078551
520.01807135978117030.03614271956234070.98192864021883
530.01318195042592120.02636390085184230.986818049574079
540.02280678884062830.04561357768125670.977193211159372
550.0195821980174460.03916439603489190.980417801982554
560.01555628309149780.03111256618299550.984443716908502
570.01320348970517440.02640697941034880.986796510294826
580.01025046383671270.02050092767342550.989749536163287
590.007550919878549810.01510183975709960.99244908012145
600.005802149799557880.01160429959911580.994197850200442
610.004195665316293680.008391330632587350.995804334683706
620.006780204075762380.01356040815152480.993219795924238
630.0146917035483170.0293834070966340.985308296451683
640.01134477864490030.02268955728980070.9886552213551
650.0103334436286730.0206668872573460.989666556371327
660.009761509551664760.01952301910332950.990238490448335
670.007870388731396690.01574077746279340.992129611268603
680.006238687998284280.01247737599656860.993761312001716
690.004707050924784610.009414101849569220.995292949075215
700.006766971340364570.01353394268072910.993233028659635
710.005193656179720870.01038731235944170.994806343820279
720.003889172576737880.007778345153475760.996110827423262
730.004024208542948240.008048417085896470.995975791457052
740.006293944526431560.01258788905286310.993706055473568
750.008771260911308840.01754252182261770.991228739088691
760.007218921736756790.01443784347351360.992781078263243
770.005826154893751070.01165230978750210.994173845106249
780.006802753817841020.0136055076356820.993197246182159
790.006349926985874230.01269985397174850.993650073014126
800.005527758274342380.01105551654868480.994472241725658
810.004173140471987380.008346280943974760.995826859528013
820.003145073452640940.006290146905281880.996854926547359
830.002369561171494450.004739122342988890.997630438828506
840.001748531574014350.003497063148028690.998251468425986
850.9782008426473670.04359831470526510.0217991573526325
860.9734246231788040.05315075364239240.0265753768211962
870.967597075054290.06480584989142040.0324029249457102
880.9620952568970060.07580948620598780.0379047431029939
890.9563521979392240.08729560412155290.0436478020607764
900.9589577923569130.08208441528617380.0410422076430869
910.9511660366944050.09766792661118940.0488339633055947
920.9489903276318120.1020193447363760.0510096723681878
930.9452187639999090.1095624720001810.0547812360000906
940.9378890896236030.1242218207527930.0621109103763966
950.9285876509795370.1428246980409250.0714123490204627
960.9202344633838760.1595310732322480.0797655366161241
970.9361533698217120.1276932603565760.0638466301782882
980.9528708584103190.09425828317936220.0471291415896811
990.9571872581272660.08562548374546730.0428127418727336
1000.9513128517214670.0973742965570660.048687148278533
1010.9462274063905280.1075451872189430.0537725936094715
1020.9407486348558990.1185027302882030.0592513651441015
1030.9310645760156340.1378708479687310.0689354239843657
1040.9529314181507640.09413716369847120.0470685818492356
1050.9612639312553270.07747213748934510.0387360687446726
1060.97385394112050.05229211775900020.0261460588795001
1070.9761159599097050.04776808018059080.0238840400902954
1080.971118130955260.05776373808948010.0288818690447401
1090.9674919900621180.06501601987576350.0325080099378817
1100.9629434691751630.07411306164967480.0370565308248374
1110.9614334029281730.07713319414365480.0385665970718274
1120.9633930568799160.07321388624016830.0366069431200842
1130.9560609436632550.08787811267349060.0439390563367453
1140.9645343380068780.07093132398624470.0354656619931224
1150.9653248113879050.06935037722418930.0346751886120946
1160.9619861921732310.07602761565353770.0380138078267689
1170.954783016242080.09043396751583940.0452169837579197
1180.9475221308165790.1049557383668420.0524778691834211
1190.9999284345100880.0001431309798234547.15654899117272e-05
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1600.9999998754615592.4907688144522e-071.2453844072261e-07
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1780.9999999999588248.23514443618291e-114.11757221809146e-11
1790.9999999999920881.58249446146442e-117.91247230732209e-12
1800.9999999999879582.40843373730135e-111.20421686865068e-11
1810.999999999979264.14790235956326e-112.07395117978163e-11
1820.9999999999911291.77412809682686e-118.87064048413431e-12
1830.9999999999828693.42628362921815e-111.71314181460908e-11
1840.9999999999707955.84096269885334e-112.92048134942667e-11
1850.9999999999944931.10131672992983e-115.50658364964913e-12
1860.999999999989872.0259302616477e-111.01296513082385e-11
1870.9999999999868592.62818484295829e-111.31409242147914e-11
1880.9999999999831963.36083925519769e-111.68041962759885e-11
1890.9999999999752094.95821831589318e-112.47910915794659e-11
1900.9999999999662876.74255032667512e-113.37127516333756e-11
1910.9999999999374461.25107125148557e-106.25535625742784e-11
1920.9999999998813772.37246021025944e-101.18623010512972e-10
1930.9999999998096943.80612864972096e-101.90306432486048e-10
1940.9999999996531336.93733302859819e-103.46866651429909e-10
1950.9999999993432211.31355788367327e-096.56778941836635e-10
1960.999999999122611.75477961202497e-098.77389806012484e-10
1970.9999999984332623.13347537625957e-091.56673768812978e-09
1980.9999999998438973.12205761931961e-101.5610288096598e-10
1990.999999999876312.47380509835023e-101.23690254917511e-10
2000.999999999856372.87260972715906e-101.43630486357953e-10
2010.9999999997511084.97783057918126e-102.48891528959063e-10
2020.999999999737435.25139437405184e-102.62569718702592e-10
2030.9999999994927741.01445131820526e-095.07225659102631e-10
2040.9999999991853521.62929589988809e-098.14647949944047e-10
2050.9999999985969592.80608133552928e-091.40304066776464e-09
2060.999999997391455.21709996752506e-092.60854998376253e-09
2070.9999999953367859.32643088462096e-094.66321544231048e-09
2080.9999999911998091.76003811604249e-088.80019058021244e-09
2090.9999999853433922.93132153749986e-081.46566076874993e-08
2100.9999999871164732.57670541237205e-081.28835270618603e-08
2110.9999999827028313.45943386583315e-081.72971693291658e-08
2120.9999999677647046.44705911833049e-083.22352955916525e-08
2130.9999999403116681.19376664695083e-075.96883323475415e-08
2140.9999998950954612.09809077936178e-071.04904538968089e-07
2150.9999998801739642.39652072867532e-071.19826036433766e-07
2160.9999998658015882.68396824368603e-071.34198412184301e-07
2170.9999997619218214.76156357728992e-072.38078178864496e-07
2180.9999997255551735.48889654739034e-072.74444827369517e-07
2190.9999996297201387.40559723779237e-073.70279861889618e-07
2200.9999994221636631.15567267482372e-065.77836337411859e-07
2210.9999990001845021.99963099551612e-069.99815497758058e-07
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2230.999997980300114.03939978019043e-062.01969989009522e-06
2240.9999964564735657.0870528704232e-063.5435264352116e-06
2250.9999957672948778.46541024639583e-064.23270512319791e-06
2260.9999966771017356.64579652901047e-063.32289826450523e-06
2270.9999953885591639.22288167412519e-064.61144083706259e-06
2280.9999922600973661.54798052677302e-057.73990263386508e-06
2290.9999905205960851.89588078291943e-059.47940391459716e-06
2300.9999989994288992.00114220120964e-061.00057110060482e-06
2310.9999986836927882.63261442407452e-061.31630721203726e-06
2320.999997552668724.89466255990367e-062.44733127995184e-06
2330.9999965166655846.96666883145548e-063.48333441572774e-06
2340.9999936523168211.26953663582564e-056.34768317912821e-06
2350.9999891802468272.16395063458681e-051.08197531729341e-05
2360.9999809119891613.81760216776045e-051.90880108388023e-05
2370.9999663109485866.73781028279105e-053.36890514139553e-05
2380.9999688366659926.23266680157371e-053.11633340078685e-05
2390.9999520537824979.58924350055201e-054.794621750276e-05
2400.9999286947106540.0001426105786916767.13052893458378e-05
2410.9998907133978580.0002185732042846620.000109286602142331
2420.9998309217680830.0003381564638343370.000169078231917169
2430.9998082238958580.0003835522082849340.000191776104142467
2440.9996928172858850.0006143654282302490.000307182714115124
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2460.9993046064124480.001390787175103060.000695393587551532
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2770.9058514600343670.1882970799312650.0941485399656325







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1520.571428571428571NOK
5% type I error level2000.75187969924812NOK
10% type I error level2330.87593984962406NOK

\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 & 152 & 0.571428571428571 & NOK \tabularnewline
5% type I error level & 200 & 0.75187969924812 & NOK \tabularnewline
10% type I error level & 233 & 0.87593984962406 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156535&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]152[/C][C]0.571428571428571[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]200[/C][C]0.75187969924812[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]233[/C][C]0.87593984962406[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156535&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156535&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1520.571428571428571NOK
5% type I error level2000.75187969924812NOK
10% type I error level2330.87593984962406NOK



Parameters (Session):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 4 ; 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')
}