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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 23 Dec 2011 17:09:04 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/23/t1324678182vztid3dsj9oxrrm.htm/, Retrieved Fri, 01 Nov 2024 00:14:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160728, Retrieved Fri, 01 Nov 2024 00:14:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
- R PD  [Multiple Regression] [] [2011-12-15 18:32:07] [0cacbd6f25ea662f229a505efea21410]
-   P       [Multiple Regression] [MR] [2011-12-23 22:09:04] [85205d4a623eda481b08e88585a15826] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
210907	1418	56	79	30	112285	144
120982	869	56	58	28	84786	103
176508	1530	54	60	38	83123	98
179321	2172	89	108	30	101193	135
123185	901	40	49	22	38361	61
52746	463	25	0	26	68504	39
385534	3201	92	121	25	119182	150
33170	371	18	1	18	22807	5
101645	1192	63	20	11	17140	28
149061	1583	44	43	26	116174	84
165446	1439	33	69	25	57635	80
237213	1764	84	78	38	66198	130
173326	1495	88	86	44	71701	82
133131	1373	55	44	30	57793	60
258873	2187	60	104	40	80444	131
180083	1491	66	63	34	53855	84
324799	4041	154	158	47	97668	140
230964	1706	53	102	30	133824	151
236785	2152	119	77	31	101481	91
135473	1036	41	82	23	99645	138
202925	1882	61	115	36	114789	150
215147	1929	58	101	36	99052	124
344297	2242	75	80	30	67654	119
153935	1220	33	50	25	65553	73
132943	1289	40	83	39	97500	110
174724	2515	92	123	34	69112	123
174415	2147	100	73	31	82753	90
225548	2352	112	81	31	85323	116
223632	1638	73	105	33	72654	113
124817	1222	40	47	25	30727	56
221698	1812	45	105	33	77873	115
210767	1677	60	94	35	117478	119
170266	1579	62	44	42	74007	129
260561	1731	75	114	43	90183	127
84853	807	31	38	30	61542	27
294424	2452	77	107	33	101494	175
101011	829	34	30	13	27570	35
215641	1940	46	71	32	55813	64
325107	2662	99	84	36	79215	96
7176	186	17	0	0	1423	0
167542	1499	66	59	28	55461	84
106408	865	30	33	14	31081	41
96560	1793	76	42	17	22996	47
265769	2527	146	96	32	83122	126
269651	2747	67	106	30	70106	105
149112	1324	56	56	35	60578	80
175824	2702	107	57	20	39992	70
152871	1383	58	59	28	79892	73
111665	1179	34	39	28	49810	57
116408	2099	61	34	39	71570	40
362301	4308	119	76	34	100708	68
78800	918	42	20	26	33032	21
183167	1831	66	91	39	82875	127
277965	3373	89	115	39	139077	154
150629	1713	44	85	33	71595	116
168809	1438	66	76	28	72260	102
24188	496	24	8	4	5950	7
329267	2253	259	79	39	115762	148
65029	744	17	21	18	32551	21
101097	1161	64	30	14	31701	35
218946	2352	41	76	29	80670	112
244052	2144	68	101	44	143558	137
341570	4691	168	94	21	117105	135
103597	1112	43	27	16	23789	26
233328	2694	132	92	28	120733	230
256462	1973	105	123	35	105195	181
206161	1769	71	75	28	73107	71
311473	3148	112	128	38	132068	147
235800	2474	94	105	23	149193	190
177939	2084	82	55	36	46821	64
207176	1954	70	56	32	87011	105
196553	1226	57	41	29	95260	107
174184	1389	53	72	25	55183	94
143246	1496	103	67	27	106671	116
187559	2269	121	75	36	73511	106
187681	1833	62	114	28	92945	143
119016	1268	52	118	23	78664	81
182192	1943	52	77	40	70054	89
73566	893	32	22	23	22618	26
194979	1762	62	66	40	74011	84
167488	1403	45	69	28	83737	113
143756	1425	46	105	34	69094	120
275541	1857	63	116	33	93133	110
243199	1840	75	88	28	95536	134
182999	1502	88	73	34	225920	54
135649	1441	46	99	30	62133	96
152299	1420	53	62	33	61370	78
120221	1416	37	53	22	43836	51
346485	2970	90	118	38	106117	121
145790	1317	63	30	26	38692	38
193339	1644	78	100	35	84651	145
80953	870	25	49	8	56622	59
122774	1654	45	24	24	15986	27
130585	1054	46	67	29	95364	91
112611	937	41	46	20	26706	48
286468	3004	144	57	29	89691	68
241066	2008	82	75	45	67267	58
148446	2547	91	135	37	126846	150
204713	1885	71	68	33	41140	74
182079	1626	63	124	33	102860	181
140344	1468	53	33	25	51715	65
220516	2445	62	98	32	55801	97
243060	1964	63	58	29	111813	121
162765	1381	32	68	28	120293	99
182613	1369	39	81	28	138599	152
232138	1659	62	131	31	161647	188
265318	2888	117	110	52	115929	138
85574	1290	34	37	21	24266	40
310839	2845	92	130	24	162901	254
225060	1982	93	93	41	109825	87
232317	1904	54	118	33	129838	178
144966	1391	144	39	32	37510	51
43287	602	14	13	19	43750	49
155754	1743	61	74	20	40652	73
164709	1559	109	81	31	87771	176
201940	2014	38	109	31	85872	94
235454	2143	73	151	32	89275	120
220801	2146	75	51	18	44418	66
99466	874	50	28	23	192565	56
92661	1590	61	40	17	35232	39
133328	1590	55	56	20	40909	66
61361	1210	77	27	12	13294	27
125930	2072	75	37	17	32387	65
100750	1281	72	83	30	140867	58
224549	1401	50	54	31	120662	98
82316	834	32	27	10	21233	25
102010	1105	53	28	13	44332	26
101523	1272	42	59	22	61056	77
243511	1944	71	133	42	101338	130
22938	391	10	12	1	1168	11
41566	761	35	0	9	13497	2
152474	1605	65	106	32	65567	101
61857	530	25	23	11	25162	31
99923	1988	66	44	25	32334	36
132487	1386	41	71	36	40735	120
317394	2395	86	116	31	91413	195
21054	387	16	4	0	855	4
209641	1742	42	62	24	97068	89
22648	620	19	12	13	44339	24
31414	449	19	18	8	14116	39
46698	800	45	14	13	10288	14
131698	1684	65	60	19	65622	78
91735	1050	35	7	18	16563	15
244749	2699	95	98	33	76643	106
184510	1606	49	64	40	110681	83
79863	1502	37	29	22	29011	24
128423	1204	64	32	38	92696	37
97839	1138	38	25	24	94785	77
38214	568	34	16	8	8773	16
151101	1459	32	48	35	83209	56
272458	2158	65	100	43	93815	132
172494	1111	52	46	43	86687	144
108043	1421	62	45	14	34553	40
328107	2833	65	129	41	105547	153
250579	1955	83	130	38	103487	143
351067	2922	95	136	45	213688	220
158015	1002	29	59	31	71220	79
98866	1060	18	25	13	23517	50
85439	956	33	32	28	56926	39
229242	2186	247	63	31	91721	95
351619	3604	139	95	40	115168	169
84207	1035	29	14	30	111194	12
120445	1417	118	36	16	51009	63
324598	3261	110	113	37	135777	134
131069	1587	67	47	30	51513	69
204271	1424	42	92	35	74163	119
165543	1701	65	70	32	51633	119
141722	1249	94	19	27	75345	75
116048	946	64	50	20	33416	63
250047	1926	81	41	18	83305	55
299775	3352	95	91	31	98952	103
195838	1641	67	111	31	102372	197
173260	2035	63	41	21	37238	16
254488	2312	83	120	39	103772	140
104389	1369	45	135	41	123969	89
136084	1577	30	27	13	27142	40
199476	2201	70	87	32	135400	125
92499	961	32	25	18	21399	21
224330	1900	83	131	39	130115	167
135781	1254	31	45	14	24874	32
74408	1335	67	29	7	34988	36
81240	1597	66	58	17	45549	13
14688	207	10	4	0	6023	5
181633	1645	70	47	30	64466	96
271856	2429	103	109	37	54990	151
7199	151	5	7	0	1644	6
46660	474	20	12	5	6179	13
17547	141	5	0	1	3926	3
133368	1639	36	37	16	32755	57
95227	872	34	37	32	34777	23
152601	1318	48	46	24	73224	61
98146	1018	40	15	17	27114	21
79619	1383	43	42	11	20760	43
59194	1314	31	7	24	37636	20
139942	1335	42	54	22	65461	82
118612	1403	46	54	12	30080	90
72880	910	33	14	19	24094	25
65475	616	18	16	13	69008	60
99643	1407	55	33	17	54968	61
71965	771	35	32	15	46090	85
77272	766	59	21	16	27507	43
49289	473	19	15	24	10672	25
135131	1376	66	38	15	34029	41
108446	1232	60	22	17	46300	26
89746	1521	36	28	18	24760	38
44296	572	25	10	20	18779	12
77648	1059	47	31	16	21280	29
181528	1544	54	32	16	40662	49
134019	1230	53	32	18	28987	46
124064	1206	40	43	22	22827	41
92630	1205	40	27	8	18513	31
121848	1255	39	37	17	30594	41
52915	613	14	20	18	24006	26
81872	721	45	32	16	27913	23
58981	1109	36	0	23	42744	14
53515	740	28	5	22	12934	16
60812	1126	44	26	13	22574	25
56375	728	30	10	13	41385	21
65490	689	22	27	16	18653	32
80949	592	17	11	16	18472	9
76302	995	31	29	20	30976	35
104011	1613	55	25	22	63339	42
98104	2048	54	55	17	25568	68
67989	705	21	23	18	33747	32
30989	301	14	5	17	4154	6
135458	1803	81	43	12	19474	68
73504	799	35	23	7	35130	33
63123	861	43	34	17	39067	84
61254	1186	46	36	14	13310	46
74914	1451	30	35	23	65892	30
31774	628	23	0	17	4143	0
81437	1161	38	37	14	28579	36
87186	1463	54	28	15	51776	47
50090	742	20	16	17	21152	20
65745	979	53	26	21	38084	50
56653	675	45	38	18	27717	30
158399	1241	39	23	18	32928	30
46455	676	20	22	17	11342	34
73624	1049	24	30	17	19499	33
38395	620	31	16	16	16380	34
91899	1081	35	18	15	36874	37
139526	1688	151	28	21	48259	83
52164	736	52	32	16	16734	32
51567	617	30	21	14	28207	30
70551	812	31	23	15	30143	43
84856	1051	29	29	17	41369	41
102538	1656	57	50	15	45833	51
86678	705	40	12	15	29156	19
85709	945	44	21	10	35944	37
34662	554	25	18	6	36278	33
150580	1597	77	27	22	45588	41
99611	982	35	41	21	45097	54
19349	222	11	13	1	3895	14
99373	1212	63	12	18	28394	25
86230	1143	44	21	17	18632	25
30837	435	19	8	4	2325	8
31706	532	13	26	10	25139	26
89806	882	42	27	16	27975	20
62088	608	38	13	16	14483	11
40151	459	29	16	9	13127	14
27634	578	20	2	16	5839	3
76990	826	27	42	17	24069	40
37460	509	20	5	7	3738	5
54157	717	19	37	15	18625	38
49862	637	37	17	14	36341	32
84337	857	26	38	14	24548	41
64175	830	42	37	18	21792	46
59382	652	49	29	12	26263	47
119308	707	30	32	16	23686	37
76702	954	49	35	21	49303	51
103425	1461	67	17	19	25659	49
70344	672	28	20	16	28904	21
43410	778	19	7	1	2781	1
104838	1141	49	46	16	29236	44
62215	680	27	24	10	19546	26
69304	1090	30	40	19	22818	21
53117	616	22	3	12	32689	4
19764	285	12	10	2	5752	10
86680	1145	31	37	14	22197	43
84105	733	20	17	17	20055	34
77945	888	20	28	19	25272	32
89113	849	39	19	14	82206	20
91005	1182	29	29	11	32073	34
40248	528	16	8	4	5444	6
64187	642	27	10	16	20154	12
50857	947	21	15	20	36944	24
56613	819	19	15	12	8019	16
62792	757	35	28	15	30884	72
72535	894	14	17	16	19540	27

Tables (Output of Computation)





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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160728&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160728&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160728&T=0

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


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

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






Multiple Linear Regression - Estimated Regression Equation
compendiums_reviewed[t] = + 9.39979282070841 + 4.62296653534767e-05time_in_rfc[t] -0.00150497411259796pageviews[t] + 0.0185109938352304logins[t] + 0.106385236628769blogged_computations[t] + 7.89900172469073e-05totsize[t] -0.0214513220866374`tothyperlinks `[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
compendiums_reviewed[t] =  +  9.39979282070841 +  4.62296653534767e-05time_in_rfc[t] -0.00150497411259796pageviews[t] +  0.0185109938352304logins[t] +  0.106385236628769blogged_computations[t] +  7.89900172469073e-05totsize[t] -0.0214513220866374`tothyperlinks
`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160728&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]compendiums_reviewed[t] =  +  9.39979282070841 +  4.62296653534767e-05time_in_rfc[t] -0.00150497411259796pageviews[t] +  0.0185109938352304logins[t] +  0.106385236628769blogged_computations[t] +  7.89900172469073e-05totsize[t] -0.0214513220866374`tothyperlinks
`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160728&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160728&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
compendiums_reviewed[t] = + 9.39979282070841 + 4.62296653534767e-05time_in_rfc[t] -0.00150497411259796pageviews[t] + 0.0185109938352304logins[t] + 0.106385236628769blogged_computations[t] + 7.89900172469073e-05totsize[t] -0.0214513220866374`tothyperlinks `[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.399792820708410.80754211.6400
time_in_rfc4.62296653534767e-051.3e-053.68780.0002710.000136
pageviews-0.001504974112597960.001231-1.22250.2225410.11127
logins0.01851099383523040.0169991.0890.2770940.138547
blogged_computations0.1063852366287690.0240294.42731.4e-057e-06
totsize7.89900172469073e-051.6e-055.04321e-060
`tothyperlinks `-0.02145132208663740.017831-1.2030.2299790.11499

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 9.39979282070841 & 0.807542 & 11.64 & 0 & 0 \tabularnewline
time_in_rfc & 4.62296653534767e-05 & 1.3e-05 & 3.6878 & 0.000271 & 0.000136 \tabularnewline
pageviews & -0.00150497411259796 & 0.001231 & -1.2225 & 0.222541 & 0.11127 \tabularnewline
logins & 0.0185109938352304 & 0.016999 & 1.089 & 0.277094 & 0.138547 \tabularnewline
blogged_computations & 0.106385236628769 & 0.024029 & 4.4273 & 1.4e-05 & 7e-06 \tabularnewline
totsize & 7.89900172469073e-05 & 1.6e-05 & 5.0432 & 1e-06 & 0 \tabularnewline
`tothyperlinks
` & -0.0214513220866374 & 0.017831 & -1.203 & 0.229979 & 0.11499 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160728&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]9.39979282070841[/C][C]0.807542[/C][C]11.64[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]time_in_rfc[/C][C]4.62296653534767e-05[/C][C]1.3e-05[/C][C]3.6878[/C][C]0.000271[/C][C]0.000136[/C][/ROW]
[ROW][C]pageviews[/C][C]-0.00150497411259796[/C][C]0.001231[/C][C]-1.2225[/C][C]0.222541[/C][C]0.11127[/C][/ROW]
[ROW][C]logins[/C][C]0.0185109938352304[/C][C]0.016999[/C][C]1.089[/C][C]0.277094[/C][C]0.138547[/C][/ROW]
[ROW][C]blogged_computations[/C][C]0.106385236628769[/C][C]0.024029[/C][C]4.4273[/C][C]1.4e-05[/C][C]7e-06[/C][/ROW]
[ROW][C]totsize[/C][C]7.89900172469073e-05[/C][C]1.6e-05[/C][C]5.0432[/C][C]1e-06[/C][C]0[/C][/ROW]
[ROW][C]`tothyperlinks
`[/C][C]-0.0214513220866374[/C][C]0.017831[/C][C]-1.203[/C][C]0.229979[/C][C]0.11499[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160728&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160728&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.399792820708410.80754211.6400
time_in_rfc4.62296653534767e-051.3e-053.68780.0002710.000136
pageviews-0.001504974112597960.001231-1.22250.2225410.11127
logins0.01851099383523040.0169991.0890.2770940.138547
blogged_computations0.1063852366287690.0240294.42731.4e-057e-06
totsize7.89900172469073e-051.6e-055.04321e-060
`tothyperlinks `-0.02145132208663740.017831-1.2030.2299790.11499






Multiple Linear Regression - Regression Statistics
Multiple R0.815928384921015
R-squared0.665739129319815
Adjusted R-squared0.658627195901088
F-TEST (value)93.6087404258839
F-TEST (DF numerator)6
F-TEST (DF denominator)282
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation6.19051109735342
Sum Squared Residuals10806.9245963005

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.815928384921015 \tabularnewline
R-squared & 0.665739129319815 \tabularnewline
Adjusted R-squared & 0.658627195901088 \tabularnewline
F-TEST (value) & 93.6087404258839 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 282 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 6.19051109735342 \tabularnewline
Sum Squared Residuals & 10806.9245963005 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160728&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.815928384921015[/C][/ROW]
[ROW][C]R-squared[/C][C]0.665739129319815[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.658627195901088[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]93.6087404258839[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]282[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]6.19051109735342[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]10806.9245963005[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160728&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160728&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.815928384921015
R-squared0.665739129319815
Adjusted R-squared0.658627195901088
F-TEST (value)93.6087404258839
F-TEST (DF numerator)6
F-TEST (DF denominator)282
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation6.19051109735342
Sum Squared Residuals10806.9245963005






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
13032.2373526142891-2.23735261428907
22825.37964849726922.62035150273076
33827.103453704597810.8965462954022
43032.6553312098093-2.65533120980926
52221.41353422436830.586465775631692
62616.17872516129419.82127483870593
72543.1775934761172-18.1775934761172
81812.50873726328935.49126273671067
91116.3520272347268-5.35202723472683
102626.6721830598723-0.672183059872311
112525.6705762877934-0.670576287793439
123830.00457732323117.99542267676886
134429.845412122521814.1545878774782
143022.46511075644097.5348892435591
154033.79490058907386.20509941092622
163425.85714506896738.14285493103269
174742.70471385915674.29528614084335
183036.6736826556862-6.67368265568623
193133.5659669582776-2.56596695827763
202328.4967290659041-5.49672906590411
213635.16154599567050.838454004329548
223633.42557336085812.57442663914193
233034.632802718926-4.63280271892598
242524.22229865578940.777701344210618
253928.518087236297310.4819127637027
263431.30125597023712.69874402976293
273128.45502405044642.54497594955362
283131.228849625008-0.228849625008016
293333.109771459861-0.109771459861014
302520.2973606935944.702639306406
313332.60953621992720.390463780072772
323534.45739290247830.542607097521692
334223.802004584657118.1979954153429
344336.75581079966546.24418920033456
353021.00650225193578.99349774806426
363336.3923175785373-3.39231757853735
371318.0697634001106-5.06976340011057
383227.88979704487754.11020295512251
393635.38995510944640.610044890553615
4009.878701404083-9.878701404083
412824.9666560640523.03334393594796
421418.6588235885492-4.65882358854921
431717.8485684917757-0.848568491775719
443234.6616646164881-2.66166461648812
453033.5338614252569-3.53386142525689
463524.363745359652510.6362546403475
472023.1636485014616-3.16364850146161
482826.48067934434291.5193206556571
492820.27782934270137.72217065729865
503921.163886363055717.8361136369443
513436.4497413360554-2.44974133605544
522616.7250111747339.27498882526704
533929.83669623501959.16330376498049
543938.73771575984460.262284240155427
553326.80946619329496.19053380670514
562827.86641099578380.133589004216236
57411.386705899518-7.38670589951804
583940.39901717168-1.39901717168001
591815.95586414119452.04413585880547
601418.4557253222523-4.45572532225234
612928.79569936699580.204300633004153
624437.86004486250866.13995513749137
632137.5948827487245-16.5948827487245
641617.5052495190494-1.50524951904939
652832.965858547407-4.96585854740696
663537.7423353570808-2.74233535708083
672829.8131002866382-1.81310028663817
683842.0306777199506-4.0306777199506
692337.19693166968-14.19693166968
703624.184083686430411.8159163135696
713227.91070494521484.08929505478518
722927.28749290294311.71250709705692
732526.3451533643706-1.34515336437059
742728.7426001783372-1.74260017833716
753628.40731438113087.59268561886921
762832.8673917836108-4.86739178361083
772330.9856987269634-7.98569872696341
784027.676937212362512.3230627876375
792315.61847134395067.38152865604943
804027.975168701732712.0248312982673
812827.39519205984130.604807940158729
823428.80652964651345.1934703534866
833337.8470360220592-4.84703602205917
842833.2957873268934-5.29578732689344
853441.6814472687505-7.68144726875046
863027.73433696394222.26566303605784
873325.05484296442437.94515703557566
882221.51843935857520.481560641424766
893840.9539263613643-2.95392636136428
902620.7564460448085.24355395519203
913531.52213607880363.47786392119639
92820.7154916362414-12.7154916362414
932416.65615569362487.34384430637519
942927.41050122161211.58949877838789
952019.92811649492960.0718835050703734
962932.4777156960579-3.47771569605795
974531.088244361482213.9117556385178
983735.2776094575791.72239054242099
993326.23745823015186.76254176984821
1003333.9703419814422-0.970341981442222
1012520.86097526609194.13902473390808
1023229.81489051788822.18510948211182
1032931.2536432864155-2.25364328641552
1042830.0508082040581-2.05080820405806
1052832.8080905094958-4.80809050949575
1063141.4545012055098-10.4545012055098
1075237.384103505126614.6158964948734
1082117.03878001912573.96121998087429
1092442.4401336032903-18.4401336032903
1104135.24554566974885.75445433025118
1113337.2648813934252-4.26488139342524
1123222.69160895902499.30839104097508
1131914.54180239125464.45819760874543
1142024.6239120431903-4.6239120431903
1153128.46048274137452.53951725862548
1163132.7704086225743-1.77040862257431
1173238.9527413437856-6.95274134378561
1181825.2844376488508-7.28443764885077
1192330.5965002920128-7.59650029201277
1201718.6215258183602-1.62152581836016
1212021.9618860739104-1.96188607391041
1221215.1841281474503-3.18412814745025
1231718.5916802632197-1.59168026321966
1243032.1752360416528-2.17523604165275
1253131.7713655806874-0.771365580687428
1261016.5557507197803-6.55575071978029
1271319.3566049582059-6.3566049582059
1282222.404093459698-0.404093459697972
1294238.41109071614033.58890928385967
130111.1897925816496-10.1897925816496
131911.8472001939453-2.84720019394528
1323229.52573597711182.4742640228882
1331115.6939760684249-4.69397606842487
1342518.71180276331276.28819723668727
1353622.39453062437713.605469375623
1363137.438737784702-6.43873778470197
137010.4941352377634-10.4941352377634
1382429.6013429314064-5.60134293140641
1391314.1295566988692-1.12955669886915
140812.7213828158318-4.72138281583175
1411313.1893652669181-0.189365266918095
1421924.0503794688506-5.05037946885058
1431814.43957161867723.56042838132285
1443332.6170214110420.382978588957992
1454030.19056815812769.80943184187237
1462216.37818776211955.62181223788045
1473824.642147201919113.3578527980809
1482421.40856217462582.59143782537424
149812.9928838009496-4.99288380094959
1503525.25963372415829.74036627584182
1514335.16831306334897.83168693665107
1524325.316816286056917.6831837139431
1531420.0623227890382-6.06232278903818
1544140.28649516535660.713504834643427
1553838.5151458516939-0.515145851693901
1564549.6188329326026-4.61883293260257
1573125.94135169651435.05864830348568
1581316.1529332922084-3.15293329220843
1592819.58602847630238.41397152369774
1603133.1893535141184-2.18935351411838
1614038.38256931730971.61743068269031
1623022.28701829132717.71298170867285
1631621.5273108361388-5.52731083613882
1643741.4064206269845-4.40642062698448
1653021.89988915520488.10011084479517
1663530.57042248748794.42957751251207
1673224.66879474229347.33120525770659
1682722.17584739672774.82415260327232
1692021.1330100768887-1.13301007688871
1701829.3224276869073-11.3224276869073
1713135.2599524858757-4.25995248587573
1723132.893108952716-1.89310895271597
1732122.4731187429681-1.47311874296812
1743937.18159561025081.81840438974924
1754135.24349924698625.75650075301379
1761318.0311917937877-5.03119179378769
1773233.874171754501-1.87417175450104
1781816.72152284772681.2784771522732
1793939.0793366278235-0.0793366278235007
1801420.4291973142849-6.42919731428492
181717.1473728975222-10.1473728975222
1821721.4631656022528-4.46316560225283
183010.7464356524248-10.7464356524248
1843024.6496624341735.35033756582698
1853732.91915717643254.08084282356751
186010.3437523719974-10.3437523719974
187512.6995661224224-7.69956612242239
188110.3370992194172-9.33709921941715
1891619.0659404483397-3.06594044833971
1903219.309050704603812.6909492953962
1912424.7286130675273-0.728613067527299
1921716.432461776520.567538223479975
1931116.9807519304075-5.9807519304075
1942414.02115496035389.97884503964623
1952223.7941458362151-1.79414583621512
1961219.8134164330038-7.81341643300379
1971914.86664292195214.13335707804793
1981317.6988415664377-4.69884156643775
1991719.4509668795297-2.45096687952974
2001517.4358755209578-2.43587552095779
2011616.3958515118202-0.395851511820244
2022413.220739885251110.7792601147489
2031520.6488210270156-5.64882102701559
2041719.1097252631368-2.10972526313684
2051816.04547973367511.95452026632493
2062013.33930176580856.66069823419154
2071616.6224445630833-0.622444563083307
2081622.0327900214146-6.03279002141465
2091819.4326612425591-1.43266124255912
2102219.55883708991832.44116291008168
211816.2787452637126-8.27874526371264
2121719.3393414703266-2.3393414703266
2131814.64884505791043.35115494208963
2141618.0484118854714-2.04841188547137
2152314.19987498810798.80012501189214
2162212.48876225899289.51123774100718
2171315.3438478576626-2.34384785766262
2181315.3480753323278-2.34807533232782
2191615.45704817941360.542951820586392
2201615.00205952466950.997940475330484
2212016.78477067680883.21522932319124
2222219.56059205158842.43940794841164
2231718.2646294687076-1.2646294687076
2241816.29671990730491.70328009269511
2251711.36990340841625.63009659158379
2261219.1020198748112-7.10201987481121
227716.7571547306042-9.75715473060417
2281716.71922800466950.280771995330476
2291415.1926159933564-1.1926159933564
2302319.51940818451713.48059181548295
2311710.67657896460256.3234210353975
2321417.5422027621569-3.54220276215689
2331518.2885505850977-3.28855058509771
2341713.91290003255513.08709996744488
2352116.64858105125394.35141894874611
2361817.42444488588730.575555114112692
2371819.9810855366424-1.98108553664242
2381713.40728433179423.59271566820577
2391715.69284152692451.30715847307546
2401613.08221299865552.91778700134447
2411516.703173843617-1.70317384361696
2422121.1151030106052-0.115103010605174
2431615.7059320307250.294067969274983
2441415.2291004846637-1.22910048466366
2451515.918593453134-0.918593453133956
2461717.7511540129937-0.751154012993737
2471520.5485736303666-5.54857363036657
2481516.2584014209947-1.25840142099467
2491017.033982632756-7.03398263275602
250614.7038651448342-8.70386514483423
2512220.97685278680541.02314721319462
2522119.94041233878031.05958766121966
253111.5541629789614-10.5541629789614
2541816.31911968011821.68088031988178
2551715.6500241005721.34997589942803
256411.385545261539-7.38554526153895
2571014.4995591040271-4.49955910402705
2581617.6546894009373-1.65468940093727
2591614.34954974146221.65045025853779
260913.5407430511026-4.54074305110261
2611610.78728745041175.21271254958831
2621717.7270407528765-0.727040752876508
263711.4556783954215-4.45567839542149
2641515.7683878385892-0.768387838589177
2651415.4238175894286-1.42381758942863
2661417.5923688625623-3.59236886256229
2671816.56575821751491.43424178248511
2681216.2222729323589-4.22227293235886
2691618.8882610555764-2.88826105557644
2702118.94090468307132.0590953169287
2711916.00680446132882.9931955386712
2721616.1190920513146-0.119092051314604
273111.5303781892494-10.5303781892494
2741619.6954965698301-3.69549656983014
2751015.2918360696055-5.29183606960551
2761917.12592749556221.87407250443779
2771214.1510068616277-2.15100686162767
278211.4103799553124-9.4103799553124
2791417.0248139818839-3.0248139818839
2801715.2183615450631.781638454937
2811916.32554698609982.67445301390025
2821421.0494091393442-7.04940913934423
2831117.2541366707811-6.25413667078115
284411.9143895761696-7.9143895761696
2851614.29914111285761.70085888714244
2862014.71356931402175.28643068597827
2871213.0221062943647-1.02210629436472
2881515.6850844766015-0.68508447660146
2891614.43959691750791.56040308249207

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 30 & 32.2373526142891 & -2.23735261428907 \tabularnewline
2 & 28 & 25.3796484972692 & 2.62035150273076 \tabularnewline
3 & 38 & 27.1034537045978 & 10.8965462954022 \tabularnewline
4 & 30 & 32.6553312098093 & -2.65533120980926 \tabularnewline
5 & 22 & 21.4135342243683 & 0.586465775631692 \tabularnewline
6 & 26 & 16.1787251612941 & 9.82127483870593 \tabularnewline
7 & 25 & 43.1775934761172 & -18.1775934761172 \tabularnewline
8 & 18 & 12.5087372632893 & 5.49126273671067 \tabularnewline
9 & 11 & 16.3520272347268 & -5.35202723472683 \tabularnewline
10 & 26 & 26.6721830598723 & -0.672183059872311 \tabularnewline
11 & 25 & 25.6705762877934 & -0.670576287793439 \tabularnewline
12 & 38 & 30.0045773232311 & 7.99542267676886 \tabularnewline
13 & 44 & 29.8454121225218 & 14.1545878774782 \tabularnewline
14 & 30 & 22.4651107564409 & 7.5348892435591 \tabularnewline
15 & 40 & 33.7949005890738 & 6.20509941092622 \tabularnewline
16 & 34 & 25.8571450689673 & 8.14285493103269 \tabularnewline
17 & 47 & 42.7047138591567 & 4.29528614084335 \tabularnewline
18 & 30 & 36.6736826556862 & -6.67368265568623 \tabularnewline
19 & 31 & 33.5659669582776 & -2.56596695827763 \tabularnewline
20 & 23 & 28.4967290659041 & -5.49672906590411 \tabularnewline
21 & 36 & 35.1615459956705 & 0.838454004329548 \tabularnewline
22 & 36 & 33.4255733608581 & 2.57442663914193 \tabularnewline
23 & 30 & 34.632802718926 & -4.63280271892598 \tabularnewline
24 & 25 & 24.2222986557894 & 0.777701344210618 \tabularnewline
25 & 39 & 28.5180872362973 & 10.4819127637027 \tabularnewline
26 & 34 & 31.3012559702371 & 2.69874402976293 \tabularnewline
27 & 31 & 28.4550240504464 & 2.54497594955362 \tabularnewline
28 & 31 & 31.228849625008 & -0.228849625008016 \tabularnewline
29 & 33 & 33.109771459861 & -0.109771459861014 \tabularnewline
30 & 25 & 20.297360693594 & 4.702639306406 \tabularnewline
31 & 33 & 32.6095362199272 & 0.390463780072772 \tabularnewline
32 & 35 & 34.4573929024783 & 0.542607097521692 \tabularnewline
33 & 42 & 23.8020045846571 & 18.1979954153429 \tabularnewline
34 & 43 & 36.7558107996654 & 6.24418920033456 \tabularnewline
35 & 30 & 21.0065022519357 & 8.99349774806426 \tabularnewline
36 & 33 & 36.3923175785373 & -3.39231757853735 \tabularnewline
37 & 13 & 18.0697634001106 & -5.06976340011057 \tabularnewline
38 & 32 & 27.8897970448775 & 4.11020295512251 \tabularnewline
39 & 36 & 35.3899551094464 & 0.610044890553615 \tabularnewline
40 & 0 & 9.878701404083 & -9.878701404083 \tabularnewline
41 & 28 & 24.966656064052 & 3.03334393594796 \tabularnewline
42 & 14 & 18.6588235885492 & -4.65882358854921 \tabularnewline
43 & 17 & 17.8485684917757 & -0.848568491775719 \tabularnewline
44 & 32 & 34.6616646164881 & -2.66166461648812 \tabularnewline
45 & 30 & 33.5338614252569 & -3.53386142525689 \tabularnewline
46 & 35 & 24.3637453596525 & 10.6362546403475 \tabularnewline
47 & 20 & 23.1636485014616 & -3.16364850146161 \tabularnewline
48 & 28 & 26.4806793443429 & 1.5193206556571 \tabularnewline
49 & 28 & 20.2778293427013 & 7.72217065729865 \tabularnewline
50 & 39 & 21.1638863630557 & 17.8361136369443 \tabularnewline
51 & 34 & 36.4497413360554 & -2.44974133605544 \tabularnewline
52 & 26 & 16.725011174733 & 9.27498882526704 \tabularnewline
53 & 39 & 29.8366962350195 & 9.16330376498049 \tabularnewline
54 & 39 & 38.7377157598446 & 0.262284240155427 \tabularnewline
55 & 33 & 26.8094661932949 & 6.19053380670514 \tabularnewline
56 & 28 & 27.8664109957838 & 0.133589004216236 \tabularnewline
57 & 4 & 11.386705899518 & -7.38670589951804 \tabularnewline
58 & 39 & 40.39901717168 & -1.39901717168001 \tabularnewline
59 & 18 & 15.9558641411945 & 2.04413585880547 \tabularnewline
60 & 14 & 18.4557253222523 & -4.45572532225234 \tabularnewline
61 & 29 & 28.7956993669958 & 0.204300633004153 \tabularnewline
62 & 44 & 37.8600448625086 & 6.13995513749137 \tabularnewline
63 & 21 & 37.5948827487245 & -16.5948827487245 \tabularnewline
64 & 16 & 17.5052495190494 & -1.50524951904939 \tabularnewline
65 & 28 & 32.965858547407 & -4.96585854740696 \tabularnewline
66 & 35 & 37.7423353570808 & -2.74233535708083 \tabularnewline
67 & 28 & 29.8131002866382 & -1.81310028663817 \tabularnewline
68 & 38 & 42.0306777199506 & -4.0306777199506 \tabularnewline
69 & 23 & 37.19693166968 & -14.19693166968 \tabularnewline
70 & 36 & 24.1840836864304 & 11.8159163135696 \tabularnewline
71 & 32 & 27.9107049452148 & 4.08929505478518 \tabularnewline
72 & 29 & 27.2874929029431 & 1.71250709705692 \tabularnewline
73 & 25 & 26.3451533643706 & -1.34515336437059 \tabularnewline
74 & 27 & 28.7426001783372 & -1.74260017833716 \tabularnewline
75 & 36 & 28.4073143811308 & 7.59268561886921 \tabularnewline
76 & 28 & 32.8673917836108 & -4.86739178361083 \tabularnewline
77 & 23 & 30.9856987269634 & -7.98569872696341 \tabularnewline
78 & 40 & 27.6769372123625 & 12.3230627876375 \tabularnewline
79 & 23 & 15.6184713439506 & 7.38152865604943 \tabularnewline
80 & 40 & 27.9751687017327 & 12.0248312982673 \tabularnewline
81 & 28 & 27.3951920598413 & 0.604807940158729 \tabularnewline
82 & 34 & 28.8065296465134 & 5.1934703534866 \tabularnewline
83 & 33 & 37.8470360220592 & -4.84703602205917 \tabularnewline
84 & 28 & 33.2957873268934 & -5.29578732689344 \tabularnewline
85 & 34 & 41.6814472687505 & -7.68144726875046 \tabularnewline
86 & 30 & 27.7343369639422 & 2.26566303605784 \tabularnewline
87 & 33 & 25.0548429644243 & 7.94515703557566 \tabularnewline
88 & 22 & 21.5184393585752 & 0.481560641424766 \tabularnewline
89 & 38 & 40.9539263613643 & -2.95392636136428 \tabularnewline
90 & 26 & 20.756446044808 & 5.24355395519203 \tabularnewline
91 & 35 & 31.5221360788036 & 3.47786392119639 \tabularnewline
92 & 8 & 20.7154916362414 & -12.7154916362414 \tabularnewline
93 & 24 & 16.6561556936248 & 7.34384430637519 \tabularnewline
94 & 29 & 27.4105012216121 & 1.58949877838789 \tabularnewline
95 & 20 & 19.9281164949296 & 0.0718835050703734 \tabularnewline
96 & 29 & 32.4777156960579 & -3.47771569605795 \tabularnewline
97 & 45 & 31.0882443614822 & 13.9117556385178 \tabularnewline
98 & 37 & 35.277609457579 & 1.72239054242099 \tabularnewline
99 & 33 & 26.2374582301518 & 6.76254176984821 \tabularnewline
100 & 33 & 33.9703419814422 & -0.970341981442222 \tabularnewline
101 & 25 & 20.8609752660919 & 4.13902473390808 \tabularnewline
102 & 32 & 29.8148905178882 & 2.18510948211182 \tabularnewline
103 & 29 & 31.2536432864155 & -2.25364328641552 \tabularnewline
104 & 28 & 30.0508082040581 & -2.05080820405806 \tabularnewline
105 & 28 & 32.8080905094958 & -4.80809050949575 \tabularnewline
106 & 31 & 41.4545012055098 & -10.4545012055098 \tabularnewline
107 & 52 & 37.3841035051266 & 14.6158964948734 \tabularnewline
108 & 21 & 17.0387800191257 & 3.96121998087429 \tabularnewline
109 & 24 & 42.4401336032903 & -18.4401336032903 \tabularnewline
110 & 41 & 35.2455456697488 & 5.75445433025118 \tabularnewline
111 & 33 & 37.2648813934252 & -4.26488139342524 \tabularnewline
112 & 32 & 22.6916089590249 & 9.30839104097508 \tabularnewline
113 & 19 & 14.5418023912546 & 4.45819760874543 \tabularnewline
114 & 20 & 24.6239120431903 & -4.6239120431903 \tabularnewline
115 & 31 & 28.4604827413745 & 2.53951725862548 \tabularnewline
116 & 31 & 32.7704086225743 & -1.77040862257431 \tabularnewline
117 & 32 & 38.9527413437856 & -6.95274134378561 \tabularnewline
118 & 18 & 25.2844376488508 & -7.28443764885077 \tabularnewline
119 & 23 & 30.5965002920128 & -7.59650029201277 \tabularnewline
120 & 17 & 18.6215258183602 & -1.62152581836016 \tabularnewline
121 & 20 & 21.9618860739104 & -1.96188607391041 \tabularnewline
122 & 12 & 15.1841281474503 & -3.18412814745025 \tabularnewline
123 & 17 & 18.5916802632197 & -1.59168026321966 \tabularnewline
124 & 30 & 32.1752360416528 & -2.17523604165275 \tabularnewline
125 & 31 & 31.7713655806874 & -0.771365580687428 \tabularnewline
126 & 10 & 16.5557507197803 & -6.55575071978029 \tabularnewline
127 & 13 & 19.3566049582059 & -6.3566049582059 \tabularnewline
128 & 22 & 22.404093459698 & -0.404093459697972 \tabularnewline
129 & 42 & 38.4110907161403 & 3.58890928385967 \tabularnewline
130 & 1 & 11.1897925816496 & -10.1897925816496 \tabularnewline
131 & 9 & 11.8472001939453 & -2.84720019394528 \tabularnewline
132 & 32 & 29.5257359771118 & 2.4742640228882 \tabularnewline
133 & 11 & 15.6939760684249 & -4.69397606842487 \tabularnewline
134 & 25 & 18.7118027633127 & 6.28819723668727 \tabularnewline
135 & 36 & 22.394530624377 & 13.605469375623 \tabularnewline
136 & 31 & 37.438737784702 & -6.43873778470197 \tabularnewline
137 & 0 & 10.4941352377634 & -10.4941352377634 \tabularnewline
138 & 24 & 29.6013429314064 & -5.60134293140641 \tabularnewline
139 & 13 & 14.1295566988692 & -1.12955669886915 \tabularnewline
140 & 8 & 12.7213828158318 & -4.72138281583175 \tabularnewline
141 & 13 & 13.1893652669181 & -0.189365266918095 \tabularnewline
142 & 19 & 24.0503794688506 & -5.05037946885058 \tabularnewline
143 & 18 & 14.4395716186772 & 3.56042838132285 \tabularnewline
144 & 33 & 32.617021411042 & 0.382978588957992 \tabularnewline
145 & 40 & 30.1905681581276 & 9.80943184187237 \tabularnewline
146 & 22 & 16.3781877621195 & 5.62181223788045 \tabularnewline
147 & 38 & 24.6421472019191 & 13.3578527980809 \tabularnewline
148 & 24 & 21.4085621746258 & 2.59143782537424 \tabularnewline
149 & 8 & 12.9928838009496 & -4.99288380094959 \tabularnewline
150 & 35 & 25.2596337241582 & 9.74036627584182 \tabularnewline
151 & 43 & 35.1683130633489 & 7.83168693665107 \tabularnewline
152 & 43 & 25.3168162860569 & 17.6831837139431 \tabularnewline
153 & 14 & 20.0623227890382 & -6.06232278903818 \tabularnewline
154 & 41 & 40.2864951653566 & 0.713504834643427 \tabularnewline
155 & 38 & 38.5151458516939 & -0.515145851693901 \tabularnewline
156 & 45 & 49.6188329326026 & -4.61883293260257 \tabularnewline
157 & 31 & 25.9413516965143 & 5.05864830348568 \tabularnewline
158 & 13 & 16.1529332922084 & -3.15293329220843 \tabularnewline
159 & 28 & 19.5860284763023 & 8.41397152369774 \tabularnewline
160 & 31 & 33.1893535141184 & -2.18935351411838 \tabularnewline
161 & 40 & 38.3825693173097 & 1.61743068269031 \tabularnewline
162 & 30 & 22.2870182913271 & 7.71298170867285 \tabularnewline
163 & 16 & 21.5273108361388 & -5.52731083613882 \tabularnewline
164 & 37 & 41.4064206269845 & -4.40642062698448 \tabularnewline
165 & 30 & 21.8998891552048 & 8.10011084479517 \tabularnewline
166 & 35 & 30.5704224874879 & 4.42957751251207 \tabularnewline
167 & 32 & 24.6687947422934 & 7.33120525770659 \tabularnewline
168 & 27 & 22.1758473967277 & 4.82415260327232 \tabularnewline
169 & 20 & 21.1330100768887 & -1.13301007688871 \tabularnewline
170 & 18 & 29.3224276869073 & -11.3224276869073 \tabularnewline
171 & 31 & 35.2599524858757 & -4.25995248587573 \tabularnewline
172 & 31 & 32.893108952716 & -1.89310895271597 \tabularnewline
173 & 21 & 22.4731187429681 & -1.47311874296812 \tabularnewline
174 & 39 & 37.1815956102508 & 1.81840438974924 \tabularnewline
175 & 41 & 35.2434992469862 & 5.75650075301379 \tabularnewline
176 & 13 & 18.0311917937877 & -5.03119179378769 \tabularnewline
177 & 32 & 33.874171754501 & -1.87417175450104 \tabularnewline
178 & 18 & 16.7215228477268 & 1.2784771522732 \tabularnewline
179 & 39 & 39.0793366278235 & -0.0793366278235007 \tabularnewline
180 & 14 & 20.4291973142849 & -6.42919731428492 \tabularnewline
181 & 7 & 17.1473728975222 & -10.1473728975222 \tabularnewline
182 & 17 & 21.4631656022528 & -4.46316560225283 \tabularnewline
183 & 0 & 10.7464356524248 & -10.7464356524248 \tabularnewline
184 & 30 & 24.649662434173 & 5.35033756582698 \tabularnewline
185 & 37 & 32.9191571764325 & 4.08084282356751 \tabularnewline
186 & 0 & 10.3437523719974 & -10.3437523719974 \tabularnewline
187 & 5 & 12.6995661224224 & -7.69956612242239 \tabularnewline
188 & 1 & 10.3370992194172 & -9.33709921941715 \tabularnewline
189 & 16 & 19.0659404483397 & -3.06594044833971 \tabularnewline
190 & 32 & 19.3090507046038 & 12.6909492953962 \tabularnewline
191 & 24 & 24.7286130675273 & -0.728613067527299 \tabularnewline
192 & 17 & 16.43246177652 & 0.567538223479975 \tabularnewline
193 & 11 & 16.9807519304075 & -5.9807519304075 \tabularnewline
194 & 24 & 14.0211549603538 & 9.97884503964623 \tabularnewline
195 & 22 & 23.7941458362151 & -1.79414583621512 \tabularnewline
196 & 12 & 19.8134164330038 & -7.81341643300379 \tabularnewline
197 & 19 & 14.8666429219521 & 4.13335707804793 \tabularnewline
198 & 13 & 17.6988415664377 & -4.69884156643775 \tabularnewline
199 & 17 & 19.4509668795297 & -2.45096687952974 \tabularnewline
200 & 15 & 17.4358755209578 & -2.43587552095779 \tabularnewline
201 & 16 & 16.3958515118202 & -0.395851511820244 \tabularnewline
202 & 24 & 13.2207398852511 & 10.7792601147489 \tabularnewline
203 & 15 & 20.6488210270156 & -5.64882102701559 \tabularnewline
204 & 17 & 19.1097252631368 & -2.10972526313684 \tabularnewline
205 & 18 & 16.0454797336751 & 1.95452026632493 \tabularnewline
206 & 20 & 13.3393017658085 & 6.66069823419154 \tabularnewline
207 & 16 & 16.6224445630833 & -0.622444563083307 \tabularnewline
208 & 16 & 22.0327900214146 & -6.03279002141465 \tabularnewline
209 & 18 & 19.4326612425591 & -1.43266124255912 \tabularnewline
210 & 22 & 19.5588370899183 & 2.44116291008168 \tabularnewline
211 & 8 & 16.2787452637126 & -8.27874526371264 \tabularnewline
212 & 17 & 19.3393414703266 & -2.3393414703266 \tabularnewline
213 & 18 & 14.6488450579104 & 3.35115494208963 \tabularnewline
214 & 16 & 18.0484118854714 & -2.04841188547137 \tabularnewline
215 & 23 & 14.1998749881079 & 8.80012501189214 \tabularnewline
216 & 22 & 12.4887622589928 & 9.51123774100718 \tabularnewline
217 & 13 & 15.3438478576626 & -2.34384785766262 \tabularnewline
218 & 13 & 15.3480753323278 & -2.34807533232782 \tabularnewline
219 & 16 & 15.4570481794136 & 0.542951820586392 \tabularnewline
220 & 16 & 15.0020595246695 & 0.997940475330484 \tabularnewline
221 & 20 & 16.7847706768088 & 3.21522932319124 \tabularnewline
222 & 22 & 19.5605920515884 & 2.43940794841164 \tabularnewline
223 & 17 & 18.2646294687076 & -1.2646294687076 \tabularnewline
224 & 18 & 16.2967199073049 & 1.70328009269511 \tabularnewline
225 & 17 & 11.3699034084162 & 5.63009659158379 \tabularnewline
226 & 12 & 19.1020198748112 & -7.10201987481121 \tabularnewline
227 & 7 & 16.7571547306042 & -9.75715473060417 \tabularnewline
228 & 17 & 16.7192280046695 & 0.280771995330476 \tabularnewline
229 & 14 & 15.1926159933564 & -1.1926159933564 \tabularnewline
230 & 23 & 19.5194081845171 & 3.48059181548295 \tabularnewline
231 & 17 & 10.6765789646025 & 6.3234210353975 \tabularnewline
232 & 14 & 17.5422027621569 & -3.54220276215689 \tabularnewline
233 & 15 & 18.2885505850977 & -3.28855058509771 \tabularnewline
234 & 17 & 13.9129000325551 & 3.08709996744488 \tabularnewline
235 & 21 & 16.6485810512539 & 4.35141894874611 \tabularnewline
236 & 18 & 17.4244448858873 & 0.575555114112692 \tabularnewline
237 & 18 & 19.9810855366424 & -1.98108553664242 \tabularnewline
238 & 17 & 13.4072843317942 & 3.59271566820577 \tabularnewline
239 & 17 & 15.6928415269245 & 1.30715847307546 \tabularnewline
240 & 16 & 13.0822129986555 & 2.91778700134447 \tabularnewline
241 & 15 & 16.703173843617 & -1.70317384361696 \tabularnewline
242 & 21 & 21.1151030106052 & -0.115103010605174 \tabularnewline
243 & 16 & 15.705932030725 & 0.294067969274983 \tabularnewline
244 & 14 & 15.2291004846637 & -1.22910048466366 \tabularnewline
245 & 15 & 15.918593453134 & -0.918593453133956 \tabularnewline
246 & 17 & 17.7511540129937 & -0.751154012993737 \tabularnewline
247 & 15 & 20.5485736303666 & -5.54857363036657 \tabularnewline
248 & 15 & 16.2584014209947 & -1.25840142099467 \tabularnewline
249 & 10 & 17.033982632756 & -7.03398263275602 \tabularnewline
250 & 6 & 14.7038651448342 & -8.70386514483423 \tabularnewline
251 & 22 & 20.9768527868054 & 1.02314721319462 \tabularnewline
252 & 21 & 19.9404123387803 & 1.05958766121966 \tabularnewline
253 & 1 & 11.5541629789614 & -10.5541629789614 \tabularnewline
254 & 18 & 16.3191196801182 & 1.68088031988178 \tabularnewline
255 & 17 & 15.650024100572 & 1.34997589942803 \tabularnewline
256 & 4 & 11.385545261539 & -7.38554526153895 \tabularnewline
257 & 10 & 14.4995591040271 & -4.49955910402705 \tabularnewline
258 & 16 & 17.6546894009373 & -1.65468940093727 \tabularnewline
259 & 16 & 14.3495497414622 & 1.65045025853779 \tabularnewline
260 & 9 & 13.5407430511026 & -4.54074305110261 \tabularnewline
261 & 16 & 10.7872874504117 & 5.21271254958831 \tabularnewline
262 & 17 & 17.7270407528765 & -0.727040752876508 \tabularnewline
263 & 7 & 11.4556783954215 & -4.45567839542149 \tabularnewline
264 & 15 & 15.7683878385892 & -0.768387838589177 \tabularnewline
265 & 14 & 15.4238175894286 & -1.42381758942863 \tabularnewline
266 & 14 & 17.5923688625623 & -3.59236886256229 \tabularnewline
267 & 18 & 16.5657582175149 & 1.43424178248511 \tabularnewline
268 & 12 & 16.2222729323589 & -4.22227293235886 \tabularnewline
269 & 16 & 18.8882610555764 & -2.88826105557644 \tabularnewline
270 & 21 & 18.9409046830713 & 2.0590953169287 \tabularnewline
271 & 19 & 16.0068044613288 & 2.9931955386712 \tabularnewline
272 & 16 & 16.1190920513146 & -0.119092051314604 \tabularnewline
273 & 1 & 11.5303781892494 & -10.5303781892494 \tabularnewline
274 & 16 & 19.6954965698301 & -3.69549656983014 \tabularnewline
275 & 10 & 15.2918360696055 & -5.29183606960551 \tabularnewline
276 & 19 & 17.1259274955622 & 1.87407250443779 \tabularnewline
277 & 12 & 14.1510068616277 & -2.15100686162767 \tabularnewline
278 & 2 & 11.4103799553124 & -9.4103799553124 \tabularnewline
279 & 14 & 17.0248139818839 & -3.0248139818839 \tabularnewline
280 & 17 & 15.218361545063 & 1.781638454937 \tabularnewline
281 & 19 & 16.3255469860998 & 2.67445301390025 \tabularnewline
282 & 14 & 21.0494091393442 & -7.04940913934423 \tabularnewline
283 & 11 & 17.2541366707811 & -6.25413667078115 \tabularnewline
284 & 4 & 11.9143895761696 & -7.9143895761696 \tabularnewline
285 & 16 & 14.2991411128576 & 1.70085888714244 \tabularnewline
286 & 20 & 14.7135693140217 & 5.28643068597827 \tabularnewline
287 & 12 & 13.0221062943647 & -1.02210629436472 \tabularnewline
288 & 15 & 15.6850844766015 & -0.68508447660146 \tabularnewline
289 & 16 & 14.4395969175079 & 1.56040308249207 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160728&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]30[/C][C]32.2373526142891[/C][C]-2.23735261428907[/C][/ROW]
[ROW][C]2[/C][C]28[/C][C]25.3796484972692[/C][C]2.62035150273076[/C][/ROW]
[ROW][C]3[/C][C]38[/C][C]27.1034537045978[/C][C]10.8965462954022[/C][/ROW]
[ROW][C]4[/C][C]30[/C][C]32.6553312098093[/C][C]-2.65533120980926[/C][/ROW]
[ROW][C]5[/C][C]22[/C][C]21.4135342243683[/C][C]0.586465775631692[/C][/ROW]
[ROW][C]6[/C][C]26[/C][C]16.1787251612941[/C][C]9.82127483870593[/C][/ROW]
[ROW][C]7[/C][C]25[/C][C]43.1775934761172[/C][C]-18.1775934761172[/C][/ROW]
[ROW][C]8[/C][C]18[/C][C]12.5087372632893[/C][C]5.49126273671067[/C][/ROW]
[ROW][C]9[/C][C]11[/C][C]16.3520272347268[/C][C]-5.35202723472683[/C][/ROW]
[ROW][C]10[/C][C]26[/C][C]26.6721830598723[/C][C]-0.672183059872311[/C][/ROW]
[ROW][C]11[/C][C]25[/C][C]25.6705762877934[/C][C]-0.670576287793439[/C][/ROW]
[ROW][C]12[/C][C]38[/C][C]30.0045773232311[/C][C]7.99542267676886[/C][/ROW]
[ROW][C]13[/C][C]44[/C][C]29.8454121225218[/C][C]14.1545878774782[/C][/ROW]
[ROW][C]14[/C][C]30[/C][C]22.4651107564409[/C][C]7.5348892435591[/C][/ROW]
[ROW][C]15[/C][C]40[/C][C]33.7949005890738[/C][C]6.20509941092622[/C][/ROW]
[ROW][C]16[/C][C]34[/C][C]25.8571450689673[/C][C]8.14285493103269[/C][/ROW]
[ROW][C]17[/C][C]47[/C][C]42.7047138591567[/C][C]4.29528614084335[/C][/ROW]
[ROW][C]18[/C][C]30[/C][C]36.6736826556862[/C][C]-6.67368265568623[/C][/ROW]
[ROW][C]19[/C][C]31[/C][C]33.5659669582776[/C][C]-2.56596695827763[/C][/ROW]
[ROW][C]20[/C][C]23[/C][C]28.4967290659041[/C][C]-5.49672906590411[/C][/ROW]
[ROW][C]21[/C][C]36[/C][C]35.1615459956705[/C][C]0.838454004329548[/C][/ROW]
[ROW][C]22[/C][C]36[/C][C]33.4255733608581[/C][C]2.57442663914193[/C][/ROW]
[ROW][C]23[/C][C]30[/C][C]34.632802718926[/C][C]-4.63280271892598[/C][/ROW]
[ROW][C]24[/C][C]25[/C][C]24.2222986557894[/C][C]0.777701344210618[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]28.5180872362973[/C][C]10.4819127637027[/C][/ROW]
[ROW][C]26[/C][C]34[/C][C]31.3012559702371[/C][C]2.69874402976293[/C][/ROW]
[ROW][C]27[/C][C]31[/C][C]28.4550240504464[/C][C]2.54497594955362[/C][/ROW]
[ROW][C]28[/C][C]31[/C][C]31.228849625008[/C][C]-0.228849625008016[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]33.109771459861[/C][C]-0.109771459861014[/C][/ROW]
[ROW][C]30[/C][C]25[/C][C]20.297360693594[/C][C]4.702639306406[/C][/ROW]
[ROW][C]31[/C][C]33[/C][C]32.6095362199272[/C][C]0.390463780072772[/C][/ROW]
[ROW][C]32[/C][C]35[/C][C]34.4573929024783[/C][C]0.542607097521692[/C][/ROW]
[ROW][C]33[/C][C]42[/C][C]23.8020045846571[/C][C]18.1979954153429[/C][/ROW]
[ROW][C]34[/C][C]43[/C][C]36.7558107996654[/C][C]6.24418920033456[/C][/ROW]
[ROW][C]35[/C][C]30[/C][C]21.0065022519357[/C][C]8.99349774806426[/C][/ROW]
[ROW][C]36[/C][C]33[/C][C]36.3923175785373[/C][C]-3.39231757853735[/C][/ROW]
[ROW][C]37[/C][C]13[/C][C]18.0697634001106[/C][C]-5.06976340011057[/C][/ROW]
[ROW][C]38[/C][C]32[/C][C]27.8897970448775[/C][C]4.11020295512251[/C][/ROW]
[ROW][C]39[/C][C]36[/C][C]35.3899551094464[/C][C]0.610044890553615[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]9.878701404083[/C][C]-9.878701404083[/C][/ROW]
[ROW][C]41[/C][C]28[/C][C]24.966656064052[/C][C]3.03334393594796[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]18.6588235885492[/C][C]-4.65882358854921[/C][/ROW]
[ROW][C]43[/C][C]17[/C][C]17.8485684917757[/C][C]-0.848568491775719[/C][/ROW]
[ROW][C]44[/C][C]32[/C][C]34.6616646164881[/C][C]-2.66166461648812[/C][/ROW]
[ROW][C]45[/C][C]30[/C][C]33.5338614252569[/C][C]-3.53386142525689[/C][/ROW]
[ROW][C]46[/C][C]35[/C][C]24.3637453596525[/C][C]10.6362546403475[/C][/ROW]
[ROW][C]47[/C][C]20[/C][C]23.1636485014616[/C][C]-3.16364850146161[/C][/ROW]
[ROW][C]48[/C][C]28[/C][C]26.4806793443429[/C][C]1.5193206556571[/C][/ROW]
[ROW][C]49[/C][C]28[/C][C]20.2778293427013[/C][C]7.72217065729865[/C][/ROW]
[ROW][C]50[/C][C]39[/C][C]21.1638863630557[/C][C]17.8361136369443[/C][/ROW]
[ROW][C]51[/C][C]34[/C][C]36.4497413360554[/C][C]-2.44974133605544[/C][/ROW]
[ROW][C]52[/C][C]26[/C][C]16.725011174733[/C][C]9.27498882526704[/C][/ROW]
[ROW][C]53[/C][C]39[/C][C]29.8366962350195[/C][C]9.16330376498049[/C][/ROW]
[ROW][C]54[/C][C]39[/C][C]38.7377157598446[/C][C]0.262284240155427[/C][/ROW]
[ROW][C]55[/C][C]33[/C][C]26.8094661932949[/C][C]6.19053380670514[/C][/ROW]
[ROW][C]56[/C][C]28[/C][C]27.8664109957838[/C][C]0.133589004216236[/C][/ROW]
[ROW][C]57[/C][C]4[/C][C]11.386705899518[/C][C]-7.38670589951804[/C][/ROW]
[ROW][C]58[/C][C]39[/C][C]40.39901717168[/C][C]-1.39901717168001[/C][/ROW]
[ROW][C]59[/C][C]18[/C][C]15.9558641411945[/C][C]2.04413585880547[/C][/ROW]
[ROW][C]60[/C][C]14[/C][C]18.4557253222523[/C][C]-4.45572532225234[/C][/ROW]
[ROW][C]61[/C][C]29[/C][C]28.7956993669958[/C][C]0.204300633004153[/C][/ROW]
[ROW][C]62[/C][C]44[/C][C]37.8600448625086[/C][C]6.13995513749137[/C][/ROW]
[ROW][C]63[/C][C]21[/C][C]37.5948827487245[/C][C]-16.5948827487245[/C][/ROW]
[ROW][C]64[/C][C]16[/C][C]17.5052495190494[/C][C]-1.50524951904939[/C][/ROW]
[ROW][C]65[/C][C]28[/C][C]32.965858547407[/C][C]-4.96585854740696[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]37.7423353570808[/C][C]-2.74233535708083[/C][/ROW]
[ROW][C]67[/C][C]28[/C][C]29.8131002866382[/C][C]-1.81310028663817[/C][/ROW]
[ROW][C]68[/C][C]38[/C][C]42.0306777199506[/C][C]-4.0306777199506[/C][/ROW]
[ROW][C]69[/C][C]23[/C][C]37.19693166968[/C][C]-14.19693166968[/C][/ROW]
[ROW][C]70[/C][C]36[/C][C]24.1840836864304[/C][C]11.8159163135696[/C][/ROW]
[ROW][C]71[/C][C]32[/C][C]27.9107049452148[/C][C]4.08929505478518[/C][/ROW]
[ROW][C]72[/C][C]29[/C][C]27.2874929029431[/C][C]1.71250709705692[/C][/ROW]
[ROW][C]73[/C][C]25[/C][C]26.3451533643706[/C][C]-1.34515336437059[/C][/ROW]
[ROW][C]74[/C][C]27[/C][C]28.7426001783372[/C][C]-1.74260017833716[/C][/ROW]
[ROW][C]75[/C][C]36[/C][C]28.4073143811308[/C][C]7.59268561886921[/C][/ROW]
[ROW][C]76[/C][C]28[/C][C]32.8673917836108[/C][C]-4.86739178361083[/C][/ROW]
[ROW][C]77[/C][C]23[/C][C]30.9856987269634[/C][C]-7.98569872696341[/C][/ROW]
[ROW][C]78[/C][C]40[/C][C]27.6769372123625[/C][C]12.3230627876375[/C][/ROW]
[ROW][C]79[/C][C]23[/C][C]15.6184713439506[/C][C]7.38152865604943[/C][/ROW]
[ROW][C]80[/C][C]40[/C][C]27.9751687017327[/C][C]12.0248312982673[/C][/ROW]
[ROW][C]81[/C][C]28[/C][C]27.3951920598413[/C][C]0.604807940158729[/C][/ROW]
[ROW][C]82[/C][C]34[/C][C]28.8065296465134[/C][C]5.1934703534866[/C][/ROW]
[ROW][C]83[/C][C]33[/C][C]37.8470360220592[/C][C]-4.84703602205917[/C][/ROW]
[ROW][C]84[/C][C]28[/C][C]33.2957873268934[/C][C]-5.29578732689344[/C][/ROW]
[ROW][C]85[/C][C]34[/C][C]41.6814472687505[/C][C]-7.68144726875046[/C][/ROW]
[ROW][C]86[/C][C]30[/C][C]27.7343369639422[/C][C]2.26566303605784[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]25.0548429644243[/C][C]7.94515703557566[/C][/ROW]
[ROW][C]88[/C][C]22[/C][C]21.5184393585752[/C][C]0.481560641424766[/C][/ROW]
[ROW][C]89[/C][C]38[/C][C]40.9539263613643[/C][C]-2.95392636136428[/C][/ROW]
[ROW][C]90[/C][C]26[/C][C]20.756446044808[/C][C]5.24355395519203[/C][/ROW]
[ROW][C]91[/C][C]35[/C][C]31.5221360788036[/C][C]3.47786392119639[/C][/ROW]
[ROW][C]92[/C][C]8[/C][C]20.7154916362414[/C][C]-12.7154916362414[/C][/ROW]
[ROW][C]93[/C][C]24[/C][C]16.6561556936248[/C][C]7.34384430637519[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]27.4105012216121[/C][C]1.58949877838789[/C][/ROW]
[ROW][C]95[/C][C]20[/C][C]19.9281164949296[/C][C]0.0718835050703734[/C][/ROW]
[ROW][C]96[/C][C]29[/C][C]32.4777156960579[/C][C]-3.47771569605795[/C][/ROW]
[ROW][C]97[/C][C]45[/C][C]31.0882443614822[/C][C]13.9117556385178[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]35.277609457579[/C][C]1.72239054242099[/C][/ROW]
[ROW][C]99[/C][C]33[/C][C]26.2374582301518[/C][C]6.76254176984821[/C][/ROW]
[ROW][C]100[/C][C]33[/C][C]33.9703419814422[/C][C]-0.970341981442222[/C][/ROW]
[ROW][C]101[/C][C]25[/C][C]20.8609752660919[/C][C]4.13902473390808[/C][/ROW]
[ROW][C]102[/C][C]32[/C][C]29.8148905178882[/C][C]2.18510948211182[/C][/ROW]
[ROW][C]103[/C][C]29[/C][C]31.2536432864155[/C][C]-2.25364328641552[/C][/ROW]
[ROW][C]104[/C][C]28[/C][C]30.0508082040581[/C][C]-2.05080820405806[/C][/ROW]
[ROW][C]105[/C][C]28[/C][C]32.8080905094958[/C][C]-4.80809050949575[/C][/ROW]
[ROW][C]106[/C][C]31[/C][C]41.4545012055098[/C][C]-10.4545012055098[/C][/ROW]
[ROW][C]107[/C][C]52[/C][C]37.3841035051266[/C][C]14.6158964948734[/C][/ROW]
[ROW][C]108[/C][C]21[/C][C]17.0387800191257[/C][C]3.96121998087429[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]42.4401336032903[/C][C]-18.4401336032903[/C][/ROW]
[ROW][C]110[/C][C]41[/C][C]35.2455456697488[/C][C]5.75445433025118[/C][/ROW]
[ROW][C]111[/C][C]33[/C][C]37.2648813934252[/C][C]-4.26488139342524[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]22.6916089590249[/C][C]9.30839104097508[/C][/ROW]
[ROW][C]113[/C][C]19[/C][C]14.5418023912546[/C][C]4.45819760874543[/C][/ROW]
[ROW][C]114[/C][C]20[/C][C]24.6239120431903[/C][C]-4.6239120431903[/C][/ROW]
[ROW][C]115[/C][C]31[/C][C]28.4604827413745[/C][C]2.53951725862548[/C][/ROW]
[ROW][C]116[/C][C]31[/C][C]32.7704086225743[/C][C]-1.77040862257431[/C][/ROW]
[ROW][C]117[/C][C]32[/C][C]38.9527413437856[/C][C]-6.95274134378561[/C][/ROW]
[ROW][C]118[/C][C]18[/C][C]25.2844376488508[/C][C]-7.28443764885077[/C][/ROW]
[ROW][C]119[/C][C]23[/C][C]30.5965002920128[/C][C]-7.59650029201277[/C][/ROW]
[ROW][C]120[/C][C]17[/C][C]18.6215258183602[/C][C]-1.62152581836016[/C][/ROW]
[ROW][C]121[/C][C]20[/C][C]21.9618860739104[/C][C]-1.96188607391041[/C][/ROW]
[ROW][C]122[/C][C]12[/C][C]15.1841281474503[/C][C]-3.18412814745025[/C][/ROW]
[ROW][C]123[/C][C]17[/C][C]18.5916802632197[/C][C]-1.59168026321966[/C][/ROW]
[ROW][C]124[/C][C]30[/C][C]32.1752360416528[/C][C]-2.17523604165275[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]31.7713655806874[/C][C]-0.771365580687428[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]16.5557507197803[/C][C]-6.55575071978029[/C][/ROW]
[ROW][C]127[/C][C]13[/C][C]19.3566049582059[/C][C]-6.3566049582059[/C][/ROW]
[ROW][C]128[/C][C]22[/C][C]22.404093459698[/C][C]-0.404093459697972[/C][/ROW]
[ROW][C]129[/C][C]42[/C][C]38.4110907161403[/C][C]3.58890928385967[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]11.1897925816496[/C][C]-10.1897925816496[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]11.8472001939453[/C][C]-2.84720019394528[/C][/ROW]
[ROW][C]132[/C][C]32[/C][C]29.5257359771118[/C][C]2.4742640228882[/C][/ROW]
[ROW][C]133[/C][C]11[/C][C]15.6939760684249[/C][C]-4.69397606842487[/C][/ROW]
[ROW][C]134[/C][C]25[/C][C]18.7118027633127[/C][C]6.28819723668727[/C][/ROW]
[ROW][C]135[/C][C]36[/C][C]22.394530624377[/C][C]13.605469375623[/C][/ROW]
[ROW][C]136[/C][C]31[/C][C]37.438737784702[/C][C]-6.43873778470197[/C][/ROW]
[ROW][C]137[/C][C]0[/C][C]10.4941352377634[/C][C]-10.4941352377634[/C][/ROW]
[ROW][C]138[/C][C]24[/C][C]29.6013429314064[/C][C]-5.60134293140641[/C][/ROW]
[ROW][C]139[/C][C]13[/C][C]14.1295566988692[/C][C]-1.12955669886915[/C][/ROW]
[ROW][C]140[/C][C]8[/C][C]12.7213828158318[/C][C]-4.72138281583175[/C][/ROW]
[ROW][C]141[/C][C]13[/C][C]13.1893652669181[/C][C]-0.189365266918095[/C][/ROW]
[ROW][C]142[/C][C]19[/C][C]24.0503794688506[/C][C]-5.05037946885058[/C][/ROW]
[ROW][C]143[/C][C]18[/C][C]14.4395716186772[/C][C]3.56042838132285[/C][/ROW]
[ROW][C]144[/C][C]33[/C][C]32.617021411042[/C][C]0.382978588957992[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]30.1905681581276[/C][C]9.80943184187237[/C][/ROW]
[ROW][C]146[/C][C]22[/C][C]16.3781877621195[/C][C]5.62181223788045[/C][/ROW]
[ROW][C]147[/C][C]38[/C][C]24.6421472019191[/C][C]13.3578527980809[/C][/ROW]
[ROW][C]148[/C][C]24[/C][C]21.4085621746258[/C][C]2.59143782537424[/C][/ROW]
[ROW][C]149[/C][C]8[/C][C]12.9928838009496[/C][C]-4.99288380094959[/C][/ROW]
[ROW][C]150[/C][C]35[/C][C]25.2596337241582[/C][C]9.74036627584182[/C][/ROW]
[ROW][C]151[/C][C]43[/C][C]35.1683130633489[/C][C]7.83168693665107[/C][/ROW]
[ROW][C]152[/C][C]43[/C][C]25.3168162860569[/C][C]17.6831837139431[/C][/ROW]
[ROW][C]153[/C][C]14[/C][C]20.0623227890382[/C][C]-6.06232278903818[/C][/ROW]
[ROW][C]154[/C][C]41[/C][C]40.2864951653566[/C][C]0.713504834643427[/C][/ROW]
[ROW][C]155[/C][C]38[/C][C]38.5151458516939[/C][C]-0.515145851693901[/C][/ROW]
[ROW][C]156[/C][C]45[/C][C]49.6188329326026[/C][C]-4.61883293260257[/C][/ROW]
[ROW][C]157[/C][C]31[/C][C]25.9413516965143[/C][C]5.05864830348568[/C][/ROW]
[ROW][C]158[/C][C]13[/C][C]16.1529332922084[/C][C]-3.15293329220843[/C][/ROW]
[ROW][C]159[/C][C]28[/C][C]19.5860284763023[/C][C]8.41397152369774[/C][/ROW]
[ROW][C]160[/C][C]31[/C][C]33.1893535141184[/C][C]-2.18935351411838[/C][/ROW]
[ROW][C]161[/C][C]40[/C][C]38.3825693173097[/C][C]1.61743068269031[/C][/ROW]
[ROW][C]162[/C][C]30[/C][C]22.2870182913271[/C][C]7.71298170867285[/C][/ROW]
[ROW][C]163[/C][C]16[/C][C]21.5273108361388[/C][C]-5.52731083613882[/C][/ROW]
[ROW][C]164[/C][C]37[/C][C]41.4064206269845[/C][C]-4.40642062698448[/C][/ROW]
[ROW][C]165[/C][C]30[/C][C]21.8998891552048[/C][C]8.10011084479517[/C][/ROW]
[ROW][C]166[/C][C]35[/C][C]30.5704224874879[/C][C]4.42957751251207[/C][/ROW]
[ROW][C]167[/C][C]32[/C][C]24.6687947422934[/C][C]7.33120525770659[/C][/ROW]
[ROW][C]168[/C][C]27[/C][C]22.1758473967277[/C][C]4.82415260327232[/C][/ROW]
[ROW][C]169[/C][C]20[/C][C]21.1330100768887[/C][C]-1.13301007688871[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]29.3224276869073[/C][C]-11.3224276869073[/C][/ROW]
[ROW][C]171[/C][C]31[/C][C]35.2599524858757[/C][C]-4.25995248587573[/C][/ROW]
[ROW][C]172[/C][C]31[/C][C]32.893108952716[/C][C]-1.89310895271597[/C][/ROW]
[ROW][C]173[/C][C]21[/C][C]22.4731187429681[/C][C]-1.47311874296812[/C][/ROW]
[ROW][C]174[/C][C]39[/C][C]37.1815956102508[/C][C]1.81840438974924[/C][/ROW]
[ROW][C]175[/C][C]41[/C][C]35.2434992469862[/C][C]5.75650075301379[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]18.0311917937877[/C][C]-5.03119179378769[/C][/ROW]
[ROW][C]177[/C][C]32[/C][C]33.874171754501[/C][C]-1.87417175450104[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]16.7215228477268[/C][C]1.2784771522732[/C][/ROW]
[ROW][C]179[/C][C]39[/C][C]39.0793366278235[/C][C]-0.0793366278235007[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]20.4291973142849[/C][C]-6.42919731428492[/C][/ROW]
[ROW][C]181[/C][C]7[/C][C]17.1473728975222[/C][C]-10.1473728975222[/C][/ROW]
[ROW][C]182[/C][C]17[/C][C]21.4631656022528[/C][C]-4.46316560225283[/C][/ROW]
[ROW][C]183[/C][C]0[/C][C]10.7464356524248[/C][C]-10.7464356524248[/C][/ROW]
[ROW][C]184[/C][C]30[/C][C]24.649662434173[/C][C]5.35033756582698[/C][/ROW]
[ROW][C]185[/C][C]37[/C][C]32.9191571764325[/C][C]4.08084282356751[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]10.3437523719974[/C][C]-10.3437523719974[/C][/ROW]
[ROW][C]187[/C][C]5[/C][C]12.6995661224224[/C][C]-7.69956612242239[/C][/ROW]
[ROW][C]188[/C][C]1[/C][C]10.3370992194172[/C][C]-9.33709921941715[/C][/ROW]
[ROW][C]189[/C][C]16[/C][C]19.0659404483397[/C][C]-3.06594044833971[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]19.3090507046038[/C][C]12.6909492953962[/C][/ROW]
[ROW][C]191[/C][C]24[/C][C]24.7286130675273[/C][C]-0.728613067527299[/C][/ROW]
[ROW][C]192[/C][C]17[/C][C]16.43246177652[/C][C]0.567538223479975[/C][/ROW]
[ROW][C]193[/C][C]11[/C][C]16.9807519304075[/C][C]-5.9807519304075[/C][/ROW]
[ROW][C]194[/C][C]24[/C][C]14.0211549603538[/C][C]9.97884503964623[/C][/ROW]
[ROW][C]195[/C][C]22[/C][C]23.7941458362151[/C][C]-1.79414583621512[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]19.8134164330038[/C][C]-7.81341643300379[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]14.8666429219521[/C][C]4.13335707804793[/C][/ROW]
[ROW][C]198[/C][C]13[/C][C]17.6988415664377[/C][C]-4.69884156643775[/C][/ROW]
[ROW][C]199[/C][C]17[/C][C]19.4509668795297[/C][C]-2.45096687952974[/C][/ROW]
[ROW][C]200[/C][C]15[/C][C]17.4358755209578[/C][C]-2.43587552095779[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]16.3958515118202[/C][C]-0.395851511820244[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]13.2207398852511[/C][C]10.7792601147489[/C][/ROW]
[ROW][C]203[/C][C]15[/C][C]20.6488210270156[/C][C]-5.64882102701559[/C][/ROW]
[ROW][C]204[/C][C]17[/C][C]19.1097252631368[/C][C]-2.10972526313684[/C][/ROW]
[ROW][C]205[/C][C]18[/C][C]16.0454797336751[/C][C]1.95452026632493[/C][/ROW]
[ROW][C]206[/C][C]20[/C][C]13.3393017658085[/C][C]6.66069823419154[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]16.6224445630833[/C][C]-0.622444563083307[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]22.0327900214146[/C][C]-6.03279002141465[/C][/ROW]
[ROW][C]209[/C][C]18[/C][C]19.4326612425591[/C][C]-1.43266124255912[/C][/ROW]
[ROW][C]210[/C][C]22[/C][C]19.5588370899183[/C][C]2.44116291008168[/C][/ROW]
[ROW][C]211[/C][C]8[/C][C]16.2787452637126[/C][C]-8.27874526371264[/C][/ROW]
[ROW][C]212[/C][C]17[/C][C]19.3393414703266[/C][C]-2.3393414703266[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]14.6488450579104[/C][C]3.35115494208963[/C][/ROW]
[ROW][C]214[/C][C]16[/C][C]18.0484118854714[/C][C]-2.04841188547137[/C][/ROW]
[ROW][C]215[/C][C]23[/C][C]14.1998749881079[/C][C]8.80012501189214[/C][/ROW]
[ROW][C]216[/C][C]22[/C][C]12.4887622589928[/C][C]9.51123774100718[/C][/ROW]
[ROW][C]217[/C][C]13[/C][C]15.3438478576626[/C][C]-2.34384785766262[/C][/ROW]
[ROW][C]218[/C][C]13[/C][C]15.3480753323278[/C][C]-2.34807533232782[/C][/ROW]
[ROW][C]219[/C][C]16[/C][C]15.4570481794136[/C][C]0.542951820586392[/C][/ROW]
[ROW][C]220[/C][C]16[/C][C]15.0020595246695[/C][C]0.997940475330484[/C][/ROW]
[ROW][C]221[/C][C]20[/C][C]16.7847706768088[/C][C]3.21522932319124[/C][/ROW]
[ROW][C]222[/C][C]22[/C][C]19.5605920515884[/C][C]2.43940794841164[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]18.2646294687076[/C][C]-1.2646294687076[/C][/ROW]
[ROW][C]224[/C][C]18[/C][C]16.2967199073049[/C][C]1.70328009269511[/C][/ROW]
[ROW][C]225[/C][C]17[/C][C]11.3699034084162[/C][C]5.63009659158379[/C][/ROW]
[ROW][C]226[/C][C]12[/C][C]19.1020198748112[/C][C]-7.10201987481121[/C][/ROW]
[ROW][C]227[/C][C]7[/C][C]16.7571547306042[/C][C]-9.75715473060417[/C][/ROW]
[ROW][C]228[/C][C]17[/C][C]16.7192280046695[/C][C]0.280771995330476[/C][/ROW]
[ROW][C]229[/C][C]14[/C][C]15.1926159933564[/C][C]-1.1926159933564[/C][/ROW]
[ROW][C]230[/C][C]23[/C][C]19.5194081845171[/C][C]3.48059181548295[/C][/ROW]
[ROW][C]231[/C][C]17[/C][C]10.6765789646025[/C][C]6.3234210353975[/C][/ROW]
[ROW][C]232[/C][C]14[/C][C]17.5422027621569[/C][C]-3.54220276215689[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]18.2885505850977[/C][C]-3.28855058509771[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]13.9129000325551[/C][C]3.08709996744488[/C][/ROW]
[ROW][C]235[/C][C]21[/C][C]16.6485810512539[/C][C]4.35141894874611[/C][/ROW]
[ROW][C]236[/C][C]18[/C][C]17.4244448858873[/C][C]0.575555114112692[/C][/ROW]
[ROW][C]237[/C][C]18[/C][C]19.9810855366424[/C][C]-1.98108553664242[/C][/ROW]
[ROW][C]238[/C][C]17[/C][C]13.4072843317942[/C][C]3.59271566820577[/C][/ROW]
[ROW][C]239[/C][C]17[/C][C]15.6928415269245[/C][C]1.30715847307546[/C][/ROW]
[ROW][C]240[/C][C]16[/C][C]13.0822129986555[/C][C]2.91778700134447[/C][/ROW]
[ROW][C]241[/C][C]15[/C][C]16.703173843617[/C][C]-1.70317384361696[/C][/ROW]
[ROW][C]242[/C][C]21[/C][C]21.1151030106052[/C][C]-0.115103010605174[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]15.705932030725[/C][C]0.294067969274983[/C][/ROW]
[ROW][C]244[/C][C]14[/C][C]15.2291004846637[/C][C]-1.22910048466366[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]15.918593453134[/C][C]-0.918593453133956[/C][/ROW]
[ROW][C]246[/C][C]17[/C][C]17.7511540129937[/C][C]-0.751154012993737[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]20.5485736303666[/C][C]-5.54857363036657[/C][/ROW]
[ROW][C]248[/C][C]15[/C][C]16.2584014209947[/C][C]-1.25840142099467[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]17.033982632756[/C][C]-7.03398263275602[/C][/ROW]
[ROW][C]250[/C][C]6[/C][C]14.7038651448342[/C][C]-8.70386514483423[/C][/ROW]
[ROW][C]251[/C][C]22[/C][C]20.9768527868054[/C][C]1.02314721319462[/C][/ROW]
[ROW][C]252[/C][C]21[/C][C]19.9404123387803[/C][C]1.05958766121966[/C][/ROW]
[ROW][C]253[/C][C]1[/C][C]11.5541629789614[/C][C]-10.5541629789614[/C][/ROW]
[ROW][C]254[/C][C]18[/C][C]16.3191196801182[/C][C]1.68088031988178[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]15.650024100572[/C][C]1.34997589942803[/C][/ROW]
[ROW][C]256[/C][C]4[/C][C]11.385545261539[/C][C]-7.38554526153895[/C][/ROW]
[ROW][C]257[/C][C]10[/C][C]14.4995591040271[/C][C]-4.49955910402705[/C][/ROW]
[ROW][C]258[/C][C]16[/C][C]17.6546894009373[/C][C]-1.65468940093727[/C][/ROW]
[ROW][C]259[/C][C]16[/C][C]14.3495497414622[/C][C]1.65045025853779[/C][/ROW]
[ROW][C]260[/C][C]9[/C][C]13.5407430511026[/C][C]-4.54074305110261[/C][/ROW]
[ROW][C]261[/C][C]16[/C][C]10.7872874504117[/C][C]5.21271254958831[/C][/ROW]
[ROW][C]262[/C][C]17[/C][C]17.7270407528765[/C][C]-0.727040752876508[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]11.4556783954215[/C][C]-4.45567839542149[/C][/ROW]
[ROW][C]264[/C][C]15[/C][C]15.7683878385892[/C][C]-0.768387838589177[/C][/ROW]
[ROW][C]265[/C][C]14[/C][C]15.4238175894286[/C][C]-1.42381758942863[/C][/ROW]
[ROW][C]266[/C][C]14[/C][C]17.5923688625623[/C][C]-3.59236886256229[/C][/ROW]
[ROW][C]267[/C][C]18[/C][C]16.5657582175149[/C][C]1.43424178248511[/C][/ROW]
[ROW][C]268[/C][C]12[/C][C]16.2222729323589[/C][C]-4.22227293235886[/C][/ROW]
[ROW][C]269[/C][C]16[/C][C]18.8882610555764[/C][C]-2.88826105557644[/C][/ROW]
[ROW][C]270[/C][C]21[/C][C]18.9409046830713[/C][C]2.0590953169287[/C][/ROW]
[ROW][C]271[/C][C]19[/C][C]16.0068044613288[/C][C]2.9931955386712[/C][/ROW]
[ROW][C]272[/C][C]16[/C][C]16.1190920513146[/C][C]-0.119092051314604[/C][/ROW]
[ROW][C]273[/C][C]1[/C][C]11.5303781892494[/C][C]-10.5303781892494[/C][/ROW]
[ROW][C]274[/C][C]16[/C][C]19.6954965698301[/C][C]-3.69549656983014[/C][/ROW]
[ROW][C]275[/C][C]10[/C][C]15.2918360696055[/C][C]-5.29183606960551[/C][/ROW]
[ROW][C]276[/C][C]19[/C][C]17.1259274955622[/C][C]1.87407250443779[/C][/ROW]
[ROW][C]277[/C][C]12[/C][C]14.1510068616277[/C][C]-2.15100686162767[/C][/ROW]
[ROW][C]278[/C][C]2[/C][C]11.4103799553124[/C][C]-9.4103799553124[/C][/ROW]
[ROW][C]279[/C][C]14[/C][C]17.0248139818839[/C][C]-3.0248139818839[/C][/ROW]
[ROW][C]280[/C][C]17[/C][C]15.218361545063[/C][C]1.781638454937[/C][/ROW]
[ROW][C]281[/C][C]19[/C][C]16.3255469860998[/C][C]2.67445301390025[/C][/ROW]
[ROW][C]282[/C][C]14[/C][C]21.0494091393442[/C][C]-7.04940913934423[/C][/ROW]
[ROW][C]283[/C][C]11[/C][C]17.2541366707811[/C][C]-6.25413667078115[/C][/ROW]
[ROW][C]284[/C][C]4[/C][C]11.9143895761696[/C][C]-7.9143895761696[/C][/ROW]
[ROW][C]285[/C][C]16[/C][C]14.2991411128576[/C][C]1.70085888714244[/C][/ROW]
[ROW][C]286[/C][C]20[/C][C]14.7135693140217[/C][C]5.28643068597827[/C][/ROW]
[ROW][C]287[/C][C]12[/C][C]13.0221062943647[/C][C]-1.02210629436472[/C][/ROW]
[ROW][C]288[/C][C]15[/C][C]15.6850844766015[/C][C]-0.68508447660146[/C][/ROW]
[ROW][C]289[/C][C]16[/C][C]14.4395969175079[/C][C]1.56040308249207[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160728&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160728&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
13032.2373526142891-2.23735261428907
22825.37964849726922.62035150273076
33827.103453704597810.8965462954022
43032.6553312098093-2.65533120980926
52221.41353422436830.586465775631692
62616.17872516129419.82127483870593
72543.1775934761172-18.1775934761172
81812.50873726328935.49126273671067
91116.3520272347268-5.35202723472683
102626.6721830598723-0.672183059872311
112525.6705762877934-0.670576287793439
123830.00457732323117.99542267676886
134429.845412122521814.1545878774782
143022.46511075644097.5348892435591
154033.79490058907386.20509941092622
163425.85714506896738.14285493103269
174742.70471385915674.29528614084335
183036.6736826556862-6.67368265568623
193133.5659669582776-2.56596695827763
202328.4967290659041-5.49672906590411
213635.16154599567050.838454004329548
223633.42557336085812.57442663914193
233034.632802718926-4.63280271892598
242524.22229865578940.777701344210618
253928.518087236297310.4819127637027
263431.30125597023712.69874402976293
273128.45502405044642.54497594955362
283131.228849625008-0.228849625008016
293333.109771459861-0.109771459861014
302520.2973606935944.702639306406
313332.60953621992720.390463780072772
323534.45739290247830.542607097521692
334223.802004584657118.1979954153429
344336.75581079966546.24418920033456
353021.00650225193578.99349774806426
363336.3923175785373-3.39231757853735
371318.0697634001106-5.06976340011057
383227.88979704487754.11020295512251
393635.38995510944640.610044890553615
4009.878701404083-9.878701404083
412824.9666560640523.03334393594796
421418.6588235885492-4.65882358854921
431717.8485684917757-0.848568491775719
443234.6616646164881-2.66166461648812
453033.5338614252569-3.53386142525689
463524.363745359652510.6362546403475
472023.1636485014616-3.16364850146161
482826.48067934434291.5193206556571
492820.27782934270137.72217065729865
503921.163886363055717.8361136369443
513436.4497413360554-2.44974133605544
522616.7250111747339.27498882526704
533929.83669623501959.16330376498049
543938.73771575984460.262284240155427
553326.80946619329496.19053380670514
562827.86641099578380.133589004216236
57411.386705899518-7.38670589951804
583940.39901717168-1.39901717168001
591815.95586414119452.04413585880547
601418.4557253222523-4.45572532225234
612928.79569936699580.204300633004153
624437.86004486250866.13995513749137
632137.5948827487245-16.5948827487245
641617.5052495190494-1.50524951904939
652832.965858547407-4.96585854740696
663537.7423353570808-2.74233535708083
672829.8131002866382-1.81310028663817
683842.0306777199506-4.0306777199506
692337.19693166968-14.19693166968
703624.184083686430411.8159163135696
713227.91070494521484.08929505478518
722927.28749290294311.71250709705692
732526.3451533643706-1.34515336437059
742728.7426001783372-1.74260017833716
753628.40731438113087.59268561886921
762832.8673917836108-4.86739178361083
772330.9856987269634-7.98569872696341
784027.676937212362512.3230627876375
792315.61847134395067.38152865604943
804027.975168701732712.0248312982673
812827.39519205984130.604807940158729
823428.80652964651345.1934703534866
833337.8470360220592-4.84703602205917
842833.2957873268934-5.29578732689344
853441.6814472687505-7.68144726875046
863027.73433696394222.26566303605784
873325.05484296442437.94515703557566
882221.51843935857520.481560641424766
893840.9539263613643-2.95392636136428
902620.7564460448085.24355395519203
913531.52213607880363.47786392119639
92820.7154916362414-12.7154916362414
932416.65615569362487.34384430637519
942927.41050122161211.58949877838789
952019.92811649492960.0718835050703734
962932.4777156960579-3.47771569605795
974531.088244361482213.9117556385178
983735.2776094575791.72239054242099
993326.23745823015186.76254176984821
1003333.9703419814422-0.970341981442222
1012520.86097526609194.13902473390808
1023229.81489051788822.18510948211182
1032931.2536432864155-2.25364328641552
1042830.0508082040581-2.05080820405806
1052832.8080905094958-4.80809050949575
1063141.4545012055098-10.4545012055098
1075237.384103505126614.6158964948734
1082117.03878001912573.96121998087429
1092442.4401336032903-18.4401336032903
1104135.24554566974885.75445433025118
1113337.2648813934252-4.26488139342524
1123222.69160895902499.30839104097508
1131914.54180239125464.45819760874543
1142024.6239120431903-4.6239120431903
1153128.46048274137452.53951725862548
1163132.7704086225743-1.77040862257431
1173238.9527413437856-6.95274134378561
1181825.2844376488508-7.28443764885077
1192330.5965002920128-7.59650029201277
1201718.6215258183602-1.62152581836016
1212021.9618860739104-1.96188607391041
1221215.1841281474503-3.18412814745025
1231718.5916802632197-1.59168026321966
1243032.1752360416528-2.17523604165275
1253131.7713655806874-0.771365580687428
1261016.5557507197803-6.55575071978029
1271319.3566049582059-6.3566049582059
1282222.404093459698-0.404093459697972
1294238.41109071614033.58890928385967
130111.1897925816496-10.1897925816496
131911.8472001939453-2.84720019394528
1323229.52573597711182.4742640228882
1331115.6939760684249-4.69397606842487
1342518.71180276331276.28819723668727
1353622.39453062437713.605469375623
1363137.438737784702-6.43873778470197
137010.4941352377634-10.4941352377634
1382429.6013429314064-5.60134293140641
1391314.1295566988692-1.12955669886915
140812.7213828158318-4.72138281583175
1411313.1893652669181-0.189365266918095
1421924.0503794688506-5.05037946885058
1431814.43957161867723.56042838132285
1443332.6170214110420.382978588957992
1454030.19056815812769.80943184187237
1462216.37818776211955.62181223788045
1473824.642147201919113.3578527980809
1482421.40856217462582.59143782537424
149812.9928838009496-4.99288380094959
1503525.25963372415829.74036627584182
1514335.16831306334897.83168693665107
1524325.316816286056917.6831837139431
1531420.0623227890382-6.06232278903818
1544140.28649516535660.713504834643427
1553838.5151458516939-0.515145851693901
1564549.6188329326026-4.61883293260257
1573125.94135169651435.05864830348568
1581316.1529332922084-3.15293329220843
1592819.58602847630238.41397152369774
1603133.1893535141184-2.18935351411838
1614038.38256931730971.61743068269031
1623022.28701829132717.71298170867285
1631621.5273108361388-5.52731083613882
1643741.4064206269845-4.40642062698448
1653021.89988915520488.10011084479517
1663530.57042248748794.42957751251207
1673224.66879474229347.33120525770659
1682722.17584739672774.82415260327232
1692021.1330100768887-1.13301007688871
1701829.3224276869073-11.3224276869073
1713135.2599524858757-4.25995248587573
1723132.893108952716-1.89310895271597
1732122.4731187429681-1.47311874296812
1743937.18159561025081.81840438974924
1754135.24349924698625.75650075301379
1761318.0311917937877-5.03119179378769
1773233.874171754501-1.87417175450104
1781816.72152284772681.2784771522732
1793939.0793366278235-0.0793366278235007
1801420.4291973142849-6.42919731428492
181717.1473728975222-10.1473728975222
1821721.4631656022528-4.46316560225283
183010.7464356524248-10.7464356524248
1843024.6496624341735.35033756582698
1853732.91915717643254.08084282356751
186010.3437523719974-10.3437523719974
187512.6995661224224-7.69956612242239
188110.3370992194172-9.33709921941715
1891619.0659404483397-3.06594044833971
1903219.309050704603812.6909492953962
1912424.7286130675273-0.728613067527299
1921716.432461776520.567538223479975
1931116.9807519304075-5.9807519304075
1942414.02115496035389.97884503964623
1952223.7941458362151-1.79414583621512
1961219.8134164330038-7.81341643300379
1971914.86664292195214.13335707804793
1981317.6988415664377-4.69884156643775
1991719.4509668795297-2.45096687952974
2001517.4358755209578-2.43587552095779
2011616.3958515118202-0.395851511820244
2022413.220739885251110.7792601147489
2031520.6488210270156-5.64882102701559
2041719.1097252631368-2.10972526313684
2051816.04547973367511.95452026632493
2062013.33930176580856.66069823419154
2071616.6224445630833-0.622444563083307
2081622.0327900214146-6.03279002141465
2091819.4326612425591-1.43266124255912
2102219.55883708991832.44116291008168
211816.2787452637126-8.27874526371264
2121719.3393414703266-2.3393414703266
2131814.64884505791043.35115494208963
2141618.0484118854714-2.04841188547137
2152314.19987498810798.80012501189214
2162212.48876225899289.51123774100718
2171315.3438478576626-2.34384785766262
2181315.3480753323278-2.34807533232782
2191615.45704817941360.542951820586392
2201615.00205952466950.997940475330484
2212016.78477067680883.21522932319124
2222219.56059205158842.43940794841164
2231718.2646294687076-1.2646294687076
2241816.29671990730491.70328009269511
2251711.36990340841625.63009659158379
2261219.1020198748112-7.10201987481121
227716.7571547306042-9.75715473060417
2281716.71922800466950.280771995330476
2291415.1926159933564-1.1926159933564
2302319.51940818451713.48059181548295
2311710.67657896460256.3234210353975
2321417.5422027621569-3.54220276215689
2331518.2885505850977-3.28855058509771
2341713.91290003255513.08709996744488
2352116.64858105125394.35141894874611
2361817.42444488588730.575555114112692
2371819.9810855366424-1.98108553664242
2381713.40728433179423.59271566820577
2391715.69284152692451.30715847307546
2401613.08221299865552.91778700134447
2411516.703173843617-1.70317384361696
2422121.1151030106052-0.115103010605174
2431615.7059320307250.294067969274983
2441415.2291004846637-1.22910048466366
2451515.918593453134-0.918593453133956
2461717.7511540129937-0.751154012993737
2471520.5485736303666-5.54857363036657
2481516.2584014209947-1.25840142099467
2491017.033982632756-7.03398263275602
250614.7038651448342-8.70386514483423
2512220.97685278680541.02314721319462
2522119.94041233878031.05958766121966
253111.5541629789614-10.5541629789614
2541816.31911968011821.68088031988178
2551715.6500241005721.34997589942803
256411.385545261539-7.38554526153895
2571014.4995591040271-4.49955910402705
2581617.6546894009373-1.65468940093727
2591614.34954974146221.65045025853779
260913.5407430511026-4.54074305110261
2611610.78728745041175.21271254958831
2621717.7270407528765-0.727040752876508
263711.4556783954215-4.45567839542149
2641515.7683878385892-0.768387838589177
2651415.4238175894286-1.42381758942863
2661417.5923688625623-3.59236886256229
2671816.56575821751491.43424178248511
2681216.2222729323589-4.22227293235886
2691618.8882610555764-2.88826105557644
2702118.94090468307132.0590953169287
2711916.00680446132882.9931955386712
2721616.1190920513146-0.119092051314604
273111.5303781892494-10.5303781892494
2741619.6954965698301-3.69549656983014
2751015.2918360696055-5.29183606960551
2761917.12592749556221.87407250443779
2771214.1510068616277-2.15100686162767
278211.4103799553124-9.4103799553124
2791417.0248139818839-3.0248139818839
2801715.2183615450631.781638454937
2811916.32554698609982.67445301390025
2821421.0494091393442-7.04940913934423
2831117.2541366707811-6.25413667078115
284411.9143895761696-7.9143895761696
2851614.29914111285761.70085888714244
2862014.71356931402175.28643068597827
2871213.0221062943647-1.02210629436472
2881515.6850844766015-0.68508447660146
2891614.43959691750791.56040308249207






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.6928182632428280.6143634735143440.307181736757172
110.6014157147730510.7971685704538990.398584285226949
120.5909105354413310.8181789291173380.409089464558669
130.9019650593154420.1960698813691150.0980349406845575
140.8930983850869020.2138032298261950.106901614913098
150.9402468428923810.1195063142152370.0597531571076187
160.9264583919072550.147083216185490.0735416080927451
170.9279260676513080.1441478646973840.0720739323486922
180.9213574077966250.157285184406750.0786425922033751
190.9043993526543980.1912012946912050.0956006473456024
200.9255134584719910.1489730830560190.0744865415280095
210.8962558640648230.2074882718703550.103744135935177
220.8675287569674350.264942486065130.132471243032565
230.8273892847604480.3452214304791040.172610715239552
240.7789735025850080.4420529948299840.221026497414992
250.798708198159130.4025836036817410.20129180184087
260.7612298262369810.4775403475260380.238770173763019
270.7085310696936370.5829378606127250.291468930306363
280.6514144804078110.6971710391843780.348585519592189
290.6154343584814870.7691312830370270.384565641518513
300.5575615745021860.8848768509956280.442438425497814
310.4963839599933340.9927679199866670.503616040006666
320.4361283702757340.8722567405514680.563871629724266
330.6948789196524820.6102421606950360.305121080347518
340.7092360860090010.5815278279819980.290763913990999
350.7138009377562940.5723981244874110.286199062243706
360.6739713868901480.6520572262197050.326028613109852
370.7461475428563240.5077049142873510.253852457143676
380.7355834445481380.5288331109037250.264416555451862
390.7053685180661110.5892629638677790.294631481933889
400.8894492331835480.2211015336329040.110550766816452
410.8647187699566670.2705624600866660.135281230043333
420.8649444587630510.2701110824738980.135055541236949
430.8508847742773470.2982304514453060.149115225722653
440.8430571684411350.3138856631177290.156942831558865
450.8153442065690090.3693115868619830.184655793430991
460.8418847103813420.3162305792373160.158115289618658
470.8238756570603640.3522486858792730.176124342939636
480.7922543733299590.4154912533400820.207745626670041
490.7903107350886390.4193785298227220.209689264911361
500.9136994138993560.1726011722012880.0863005861006441
510.8957824564995280.2084350870009430.104217543500471
520.8956737973555810.2086524052888390.10432620264442
530.9016191106044040.1967617787911910.0983808893955957
540.8824132458470970.2351735083058050.117586754152903
550.8688774616918550.2622450766162890.131122538308145
560.8473786685038710.3052426629922570.152621331496129
570.8941148428628440.2117703142743120.105885157137156
580.8750119072704820.2499761854590360.124988092729518
590.8532725466579040.2934549066841920.146727453342096
600.8548457051907870.2903085896184260.145154294809213
610.8304270013902190.3391459972195610.169572998609781
620.8164341309656350.3671317380687310.183565869034365
630.9270183644780050.145963271043990.0729816355219948
640.9149088263585520.1701823472828960.085091173641448
650.9079060277284310.1841879445431380.092093972271569
660.8950994332109480.2098011335781050.104900566789053
670.8803148623798150.239370275240370.119685137620185
680.868885796322350.2622284073553010.13111420367765
690.9414608031608360.1170783936783290.0585391968391643
700.9628085731592770.07438285368144580.0371914268407229
710.9579349381248170.08413012375036620.0420650618751831
720.9489475331352890.1021049337294230.0510524668647114
730.9397359788676430.1205280422647140.0602640211323568
740.9313857819923360.1372284360153290.0686142180076645
750.9347404324717760.1305191350564480.0652595675282239
760.9336217821758070.1327564356483870.0663782178241933
770.9529523892176750.09409522156464980.0470476107823249
780.9707907793827130.05841844123457340.0292092206172867
790.9690742179008930.06185156419821410.030925782099107
800.9806652413696540.03866951726069170.0193347586303458
810.9760132088731930.04797358225361420.0239867911268071
820.9732823232647610.05343535347047690.0267176767352385
830.9705466020817220.05890679583655540.0294533979182777
840.9684688582426060.06306228351478750.0315311417573937
850.970600578415980.05879884316804090.0293994215840204
860.9645124333567750.07097513328645010.0354875666432251
870.9658822802978780.06823543940424380.0341177197021219
880.9593708456520180.08125830869596470.0406291543479823
890.9519505843982780.09609883120344380.0480494156017219
900.9460217269996680.1079565460006630.0539782730003315
910.9383056403828890.1233887192342210.0616943596171106
920.9745860702117540.05082785957649210.025413929788246
930.9733236018050150.05335279638996920.0266763981949846
940.9675938657012830.06481226859743470.0324061342987174
950.9619365059864140.07612698802717230.0380634940135862
960.9569127107277720.08617457854445560.0430872892722278
970.9802892529375690.0394214941248620.019710747062431
980.976010516986090.04797896602782040.0239894830139102
990.975711761605830.04857647678834040.0242882383941702
1000.9703899556582260.05922008868354840.0296100443417742
1010.9656398276377560.06872034472448730.0343601723622436
1020.9590783626441310.0818432747117380.040921637355869
1030.951703450726480.09659309854703950.0482965492735198
1040.943383766260570.113232467478860.0566162337394301
1050.9380674914405670.1238650171188670.0619325085594333
1060.9497097311780120.1005805376439750.0502902688219877
1070.9814581963140940.03708360737181150.0185418036859057
1080.978503219298980.04299356140204010.0214967807010201
1090.9960278875483860.007944224903228170.00397211245161408
1100.9960224308646790.007955138270641920.00397756913532096
1110.9955626182091940.008874763581612360.00443738179080618
1120.9968377408265610.006324518346877940.00316225917343897
1130.9960762104337270.007847579132545670.00392378956627284
1140.9960913409973120.007817318005375130.00390865900268757
1150.995083015110350.009833969779300610.00491698488965031
1160.9938585449308760.01228291013824770.00614145506912386
1170.9940060363830720.01198792723385580.00599396361692789
1180.9950104025499540.009979194900091850.00498959745004592
1190.9964686847032550.007062630593490010.00353131529674501
1200.9959289291593350.008142141681330060.00407107084066503
1210.9951938299713880.009612340057223530.00480617002861176
1220.9951539269580880.009692146083824350.00484607304191218
1230.99421381222740.01157237554519980.00578618777259992
1240.9931651883389670.01366962332206530.00683481166103265
1250.9916064940143080.01678701197138410.00839350598569203
1260.9930475689780890.01390486204382170.00695243102191086
1270.99387671860870.01224656278259980.00612328139129988
1280.9923495999451750.01530080010965080.0076504000548254
1290.9912869466508390.01742610669832250.00871305334916124
1300.9954408581289030.009118283742194420.00455914187109721
1310.9948494289411790.01030114211764250.00515057105882124
1320.9937799093184090.01244018136318160.00622009068159079
1330.993584628743110.01283074251378070.00641537125689037
1340.9937302130671030.01253957386579330.00626978693289664
1350.9976358751833480.004728249633304220.00236412481665211
1360.9976836901395480.004632619720903210.00231630986045161
1370.9988569086818390.002286182636322080.00114309131816104
1380.9989390465852420.002121906829515820.00106095341475791
1390.9986507249569580.002698550086083320.00134927504304166
1400.9985931340959230.002813731808154780.00140686590407739
1410.9982169178035420.003566164392916530.00178308219645827
1420.9981171467426110.003765706514777590.0018828532573888
1430.9977739620967840.004452075806432790.0022260379032164
1440.9971402424414850.005719515117028970.00285975755851448
1450.997894650576230.004210698847540090.00210534942377004
1460.9978835765976790.004232846804641420.00211642340232071
1470.9992002993337570.001599401332486620.000799700666243309
1480.9989567980148960.002086403970207750.00104320198510388
1490.9988992129097620.002201574180476110.00110078709023805
1500.9992651570614850.00146968587702920.0007348429385146
1510.9994237167977650.001152566404469580.000576283202234789
1520.9999325987670210.0001348024659586156.74012329793073e-05
1530.9999327571283570.0001344857432850896.72428716425446e-05
1540.9999074236425210.0001851527149586639.25763574793314e-05
1550.9998702929501870.0002594140996260850.000129707049813042
1560.9998846390889720.000230721822055960.00011536091102798
1570.9998735338931230.0002529322137533230.000126466106876662
1580.9998422848589230.000315430282153360.00015771514107668
1590.9998836265317480.0002327469365039730.000116373468251987
1600.9998413341602420.0003173316795164730.000158665839758236
1610.999784476133110.0004310477337807640.000215523866890382
1620.9998046890453190.000390621909361060.00019531095468053
1630.9997938704442440.0004122591115114620.000206129555755731
1640.9997590279488540.0004819441022925540.000240972051146277
1650.9998222356425070.0003555287149865710.000177764357493286
1660.9998096097962990.0003807804074018520.000190390203700926
1670.9998516953144340.0002966093711325780.000148304685566289
1680.9998353929230890.0003292141538222910.000164607076911145
1690.9997767248936420.0004465502127161660.000223275106358083
1700.9999034607866230.0001930784267550749.6539213377537e-05
1710.9998952651645980.0002094696708033130.000104734835401656
1720.9998553980237960.0002892039524083350.000144601976204167
1730.9998026943846240.0003946112307529490.000197305615376474
1740.9997329502691020.000534099461795820.00026704973089791
1750.9997889186111310.0004221627777371660.000211081388868583
1760.9997943028871740.0004113942256519390.00020569711282597
1770.9997340542983390.0005318914033215280.000265945701660764
1780.9996482942611430.000703411477714930.000351705738857465
1790.9995332427038540.0009335145922918540.000466757296145927
1800.9995409311197620.0009181377604751160.000459068880237558
1810.999769358297360.0004612834052804420.000230641702640221
1820.9997180822680550.0005638354638895560.000281917731944778
1830.9998592888127820.0002814223744354930.000140711187217747
1840.9998528635873590.0002942728252825050.000147136412641252
1850.9998979554810390.0002040890379227550.000102044518961377
1860.9999539603202439.20793595147002e-054.60396797573501e-05
1870.9999648245702057.03508595904458e-053.51754297952229e-05
1880.9999844023451883.11953096246625e-051.55976548123313e-05
1890.99997836080024.32783995997014e-052.16391997998507e-05
1900.9999986529404012.69411919741256e-061.34705959870628e-06
1910.9999980824098453.83518030992237e-061.91759015496118e-06
1920.999996976412376.04717525921036e-063.02358762960518e-06
1930.9999968460220276.30795594551494e-063.15397797275747e-06
1940.9999978509496894.29810062131667e-062.14905031065833e-06
1950.9999968293479476.34130410634405e-063.17065205317203e-06
1960.9999971082277135.78354457416182e-062.89177228708091e-06
1970.999996379900797.2401984192352e-063.6200992096176e-06
1980.9999960665143057.8669713892654e-063.9334856946327e-06
1990.9999943080902891.13838194215151e-055.69190971075757e-06
2000.9999920532855711.58934288571164e-057.9467144285582e-06
2010.9999876890206112.46219587784152e-051.23109793892076e-05
2020.9999974605493635.07890127460008e-062.53945063730004e-06
2030.9999967088692436.58226151419045e-063.29113075709522e-06
2040.9999948992406451.02015187099686e-055.10075935498429e-06
2050.999992047928491.59041430194113e-057.95207150970565e-06
2060.9999944115082451.1176983509311e-055.58849175465552e-06
2070.9999912862720731.74274558535588e-058.71372792677938e-06
2080.9999911727823311.76544353388087e-058.82721766940434e-06
2090.9999860827468442.7834506311145e-051.39172531555725e-05
2100.9999851435965442.97128069117309e-051.48564034558654e-05
2110.9999911531601461.76936797086652e-058.8468398543326e-06
2120.9999861708188072.76583623857939e-051.38291811928969e-05
2130.9999835261249643.29477500710473e-051.64738750355236e-05
2140.9999753457906554.93084186897709e-052.46542093448855e-05
2150.9999822702551113.54594897776385e-051.77297448888192e-05
2160.9999943503002911.12993994182218e-055.64969970911092e-06
2170.99999108713791.7825724200979e-058.9128621004895e-06
2180.9999863408071232.73183857547798e-051.36591928773899e-05
2190.9999796768428934.06463142145335e-052.03231571072668e-05
2200.9999709925341485.8014931703595e-052.90074658517975e-05
2210.9999660733701666.78532596688907e-053.39266298344454e-05
2220.999948778191290.0001024436174201725.12218087100862e-05
2230.9999235806266480.0001528387467032117.64193733516057e-05
2240.9998982932371210.0002034135257577380.000101706762878869
2250.9999396430269440.0001207139461122466.03569730561231e-05
2260.9999734687199175.30625601659609e-052.65312800829804e-05
2270.9999880675234332.38649531336195e-051.19324765668097e-05
2280.9999798536095994.02927808029483e-052.01463904014741e-05
2290.9999682895181766.3420963648639e-053.17104818243195e-05
2300.9999616188948087.67622103847949e-053.83811051923975e-05
2310.9999819803820243.60392359514065e-051.80196179757033e-05
2320.9999737856624815.2428675037796e-052.6214337518898e-05
2330.9999688111165696.23777668625661e-053.11888834312831e-05
2340.9999670505873066.58988253879375e-053.29494126939688e-05
2350.9999657017266536.85965466936171e-053.42982733468085e-05
2360.9999604285951117.91428097770599e-053.957140488853e-05
2370.999939960151660.0001200796966807156.00398483403573e-05
2380.9999403788985280.0001192422029439145.9621101471957e-05
2390.9999069695009520.0001860609980955399.30304990477695e-05
2400.9999115059213440.0001769881573110188.84940786555088e-05
2410.9998591084773730.0002817830452535830.000140891522626791
2420.9998006168762620.0003987662474766660.000199383123738333
2430.9997511566340510.0004976867318989240.000248843365949462
2440.9996205421495380.0007589157009240740.000379457850462037
2450.9993780112746480.001243977450704410.000621988725352204
2460.9989918011824490.002016397635101830.00100819881755091
2470.9993199009960490.00136019800790210.000680099003951048
2480.998941268416520.002117463166960650.00105873158348033
2490.99922541666030.001549166679399750.000774583339699874
2500.9994078552074790.001184289585041530.000592144792520767
2510.9991232933688810.001753413262237430.000876706631118717
2520.9985896172669430.002820765466114450.00141038273305723
2530.9987372722956720.002525455408656480.00126272770432824
2540.9978943193456160.004211361308767120.00210568065438356
2550.9966304267786320.006739146442735840.00336957322136792
2560.9960148953096660.007970209380667810.00398510469033391
2570.9939135495954780.01217290080904320.00608645040452162
2580.9905148039746820.01897039205063690.00948519602531843
2590.9911725989123270.01765480217534630.00882740108767313
2600.986204432283960.02759113543208090.0137955677160404
2610.9945791734450170.01084165310996680.00542082655498338
2620.9911617018384890.01767659632302160.0088382981615108
2630.9857418703090850.02851625938182930.0142581296909146
2640.9776803213527250.04463935729455020.0223196786472751
2650.9657179430607020.06856411387859620.0342820569392981
2660.9513328196630980.09733436067380450.0486671803369022
2670.9410461818565360.1179076362869270.0589538181434637
2680.9121448335644460.1757103328711080.0878551664355539
2690.8723673120169180.2552653759661630.127632687983082
2700.8468615496545760.3062769006908480.153138450345424
2710.8176347759708380.3647304480583230.182365224029162
2720.778916094663430.4421678106731410.22108390533657
2730.8312896063043350.3374207873913310.168710393695665
2740.7545380871940870.4909238256118270.245461912805913
2750.6593337157321050.6813325685357890.340666284267895
2760.7559967191447560.4880065617104870.244003280855244
2770.6382689224522010.7234621550955970.361731077547799
2780.5458556083027220.9082887833945560.454144391697278
2790.3897285723608360.7794571447216720.610271427639164

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.692818263242828 & 0.614363473514344 & 0.307181736757172 \tabularnewline
11 & 0.601415714773051 & 0.797168570453899 & 0.398584285226949 \tabularnewline
12 & 0.590910535441331 & 0.818178929117338 & 0.409089464558669 \tabularnewline
13 & 0.901965059315442 & 0.196069881369115 & 0.0980349406845575 \tabularnewline
14 & 0.893098385086902 & 0.213803229826195 & 0.106901614913098 \tabularnewline
15 & 0.940246842892381 & 0.119506314215237 & 0.0597531571076187 \tabularnewline
16 & 0.926458391907255 & 0.14708321618549 & 0.0735416080927451 \tabularnewline
17 & 0.927926067651308 & 0.144147864697384 & 0.0720739323486922 \tabularnewline
18 & 0.921357407796625 & 0.15728518440675 & 0.0786425922033751 \tabularnewline
19 & 0.904399352654398 & 0.191201294691205 & 0.0956006473456024 \tabularnewline
20 & 0.925513458471991 & 0.148973083056019 & 0.0744865415280095 \tabularnewline
21 & 0.896255864064823 & 0.207488271870355 & 0.103744135935177 \tabularnewline
22 & 0.867528756967435 & 0.26494248606513 & 0.132471243032565 \tabularnewline
23 & 0.827389284760448 & 0.345221430479104 & 0.172610715239552 \tabularnewline
24 & 0.778973502585008 & 0.442052994829984 & 0.221026497414992 \tabularnewline
25 & 0.79870819815913 & 0.402583603681741 & 0.20129180184087 \tabularnewline
26 & 0.761229826236981 & 0.477540347526038 & 0.238770173763019 \tabularnewline
27 & 0.708531069693637 & 0.582937860612725 & 0.291468930306363 \tabularnewline
28 & 0.651414480407811 & 0.697171039184378 & 0.348585519592189 \tabularnewline
29 & 0.615434358481487 & 0.769131283037027 & 0.384565641518513 \tabularnewline
30 & 0.557561574502186 & 0.884876850995628 & 0.442438425497814 \tabularnewline
31 & 0.496383959993334 & 0.992767919986667 & 0.503616040006666 \tabularnewline
32 & 0.436128370275734 & 0.872256740551468 & 0.563871629724266 \tabularnewline
33 & 0.694878919652482 & 0.610242160695036 & 0.305121080347518 \tabularnewline
34 & 0.709236086009001 & 0.581527827981998 & 0.290763913990999 \tabularnewline
35 & 0.713800937756294 & 0.572398124487411 & 0.286199062243706 \tabularnewline
36 & 0.673971386890148 & 0.652057226219705 & 0.326028613109852 \tabularnewline
37 & 0.746147542856324 & 0.507704914287351 & 0.253852457143676 \tabularnewline
38 & 0.735583444548138 & 0.528833110903725 & 0.264416555451862 \tabularnewline
39 & 0.705368518066111 & 0.589262963867779 & 0.294631481933889 \tabularnewline
40 & 0.889449233183548 & 0.221101533632904 & 0.110550766816452 \tabularnewline
41 & 0.864718769956667 & 0.270562460086666 & 0.135281230043333 \tabularnewline
42 & 0.864944458763051 & 0.270111082473898 & 0.135055541236949 \tabularnewline
43 & 0.850884774277347 & 0.298230451445306 & 0.149115225722653 \tabularnewline
44 & 0.843057168441135 & 0.313885663117729 & 0.156942831558865 \tabularnewline
45 & 0.815344206569009 & 0.369311586861983 & 0.184655793430991 \tabularnewline
46 & 0.841884710381342 & 0.316230579237316 & 0.158115289618658 \tabularnewline
47 & 0.823875657060364 & 0.352248685879273 & 0.176124342939636 \tabularnewline
48 & 0.792254373329959 & 0.415491253340082 & 0.207745626670041 \tabularnewline
49 & 0.790310735088639 & 0.419378529822722 & 0.209689264911361 \tabularnewline
50 & 0.913699413899356 & 0.172601172201288 & 0.0863005861006441 \tabularnewline
51 & 0.895782456499528 & 0.208435087000943 & 0.104217543500471 \tabularnewline
52 & 0.895673797355581 & 0.208652405288839 & 0.10432620264442 \tabularnewline
53 & 0.901619110604404 & 0.196761778791191 & 0.0983808893955957 \tabularnewline
54 & 0.882413245847097 & 0.235173508305805 & 0.117586754152903 \tabularnewline
55 & 0.868877461691855 & 0.262245076616289 & 0.131122538308145 \tabularnewline
56 & 0.847378668503871 & 0.305242662992257 & 0.152621331496129 \tabularnewline
57 & 0.894114842862844 & 0.211770314274312 & 0.105885157137156 \tabularnewline
58 & 0.875011907270482 & 0.249976185459036 & 0.124988092729518 \tabularnewline
59 & 0.853272546657904 & 0.293454906684192 & 0.146727453342096 \tabularnewline
60 & 0.854845705190787 & 0.290308589618426 & 0.145154294809213 \tabularnewline
61 & 0.830427001390219 & 0.339145997219561 & 0.169572998609781 \tabularnewline
62 & 0.816434130965635 & 0.367131738068731 & 0.183565869034365 \tabularnewline
63 & 0.927018364478005 & 0.14596327104399 & 0.0729816355219948 \tabularnewline
64 & 0.914908826358552 & 0.170182347282896 & 0.085091173641448 \tabularnewline
65 & 0.907906027728431 & 0.184187944543138 & 0.092093972271569 \tabularnewline
66 & 0.895099433210948 & 0.209801133578105 & 0.104900566789053 \tabularnewline
67 & 0.880314862379815 & 0.23937027524037 & 0.119685137620185 \tabularnewline
68 & 0.86888579632235 & 0.262228407355301 & 0.13111420367765 \tabularnewline
69 & 0.941460803160836 & 0.117078393678329 & 0.0585391968391643 \tabularnewline
70 & 0.962808573159277 & 0.0743828536814458 & 0.0371914268407229 \tabularnewline
71 & 0.957934938124817 & 0.0841301237503662 & 0.0420650618751831 \tabularnewline
72 & 0.948947533135289 & 0.102104933729423 & 0.0510524668647114 \tabularnewline
73 & 0.939735978867643 & 0.120528042264714 & 0.0602640211323568 \tabularnewline
74 & 0.931385781992336 & 0.137228436015329 & 0.0686142180076645 \tabularnewline
75 & 0.934740432471776 & 0.130519135056448 & 0.0652595675282239 \tabularnewline
76 & 0.933621782175807 & 0.132756435648387 & 0.0663782178241933 \tabularnewline
77 & 0.952952389217675 & 0.0940952215646498 & 0.0470476107823249 \tabularnewline
78 & 0.970790779382713 & 0.0584184412345734 & 0.0292092206172867 \tabularnewline
79 & 0.969074217900893 & 0.0618515641982141 & 0.030925782099107 \tabularnewline
80 & 0.980665241369654 & 0.0386695172606917 & 0.0193347586303458 \tabularnewline
81 & 0.976013208873193 & 0.0479735822536142 & 0.0239867911268071 \tabularnewline
82 & 0.973282323264761 & 0.0534353534704769 & 0.0267176767352385 \tabularnewline
83 & 0.970546602081722 & 0.0589067958365554 & 0.0294533979182777 \tabularnewline
84 & 0.968468858242606 & 0.0630622835147875 & 0.0315311417573937 \tabularnewline
85 & 0.97060057841598 & 0.0587988431680409 & 0.0293994215840204 \tabularnewline
86 & 0.964512433356775 & 0.0709751332864501 & 0.0354875666432251 \tabularnewline
87 & 0.965882280297878 & 0.0682354394042438 & 0.0341177197021219 \tabularnewline
88 & 0.959370845652018 & 0.0812583086959647 & 0.0406291543479823 \tabularnewline
89 & 0.951950584398278 & 0.0960988312034438 & 0.0480494156017219 \tabularnewline
90 & 0.946021726999668 & 0.107956546000663 & 0.0539782730003315 \tabularnewline
91 & 0.938305640382889 & 0.123388719234221 & 0.0616943596171106 \tabularnewline
92 & 0.974586070211754 & 0.0508278595764921 & 0.025413929788246 \tabularnewline
93 & 0.973323601805015 & 0.0533527963899692 & 0.0266763981949846 \tabularnewline
94 & 0.967593865701283 & 0.0648122685974347 & 0.0324061342987174 \tabularnewline
95 & 0.961936505986414 & 0.0761269880271723 & 0.0380634940135862 \tabularnewline
96 & 0.956912710727772 & 0.0861745785444556 & 0.0430872892722278 \tabularnewline
97 & 0.980289252937569 & 0.039421494124862 & 0.019710747062431 \tabularnewline
98 & 0.97601051698609 & 0.0479789660278204 & 0.0239894830139102 \tabularnewline
99 & 0.97571176160583 & 0.0485764767883404 & 0.0242882383941702 \tabularnewline
100 & 0.970389955658226 & 0.0592200886835484 & 0.0296100443417742 \tabularnewline
101 & 0.965639827637756 & 0.0687203447244873 & 0.0343601723622436 \tabularnewline
102 & 0.959078362644131 & 0.081843274711738 & 0.040921637355869 \tabularnewline
103 & 0.95170345072648 & 0.0965930985470395 & 0.0482965492735198 \tabularnewline
104 & 0.94338376626057 & 0.11323246747886 & 0.0566162337394301 \tabularnewline
105 & 0.938067491440567 & 0.123865017118867 & 0.0619325085594333 \tabularnewline
106 & 0.949709731178012 & 0.100580537643975 & 0.0502902688219877 \tabularnewline
107 & 0.981458196314094 & 0.0370836073718115 & 0.0185418036859057 \tabularnewline
108 & 0.97850321929898 & 0.0429935614020401 & 0.0214967807010201 \tabularnewline
109 & 0.996027887548386 & 0.00794422490322817 & 0.00397211245161408 \tabularnewline
110 & 0.996022430864679 & 0.00795513827064192 & 0.00397756913532096 \tabularnewline
111 & 0.995562618209194 & 0.00887476358161236 & 0.00443738179080618 \tabularnewline
112 & 0.996837740826561 & 0.00632451834687794 & 0.00316225917343897 \tabularnewline
113 & 0.996076210433727 & 0.00784757913254567 & 0.00392378956627284 \tabularnewline
114 & 0.996091340997312 & 0.00781731800537513 & 0.00390865900268757 \tabularnewline
115 & 0.99508301511035 & 0.00983396977930061 & 0.00491698488965031 \tabularnewline
116 & 0.993858544930876 & 0.0122829101382477 & 0.00614145506912386 \tabularnewline
117 & 0.994006036383072 & 0.0119879272338558 & 0.00599396361692789 \tabularnewline
118 & 0.995010402549954 & 0.00997919490009185 & 0.00498959745004592 \tabularnewline
119 & 0.996468684703255 & 0.00706263059349001 & 0.00353131529674501 \tabularnewline
120 & 0.995928929159335 & 0.00814214168133006 & 0.00407107084066503 \tabularnewline
121 & 0.995193829971388 & 0.00961234005722353 & 0.00480617002861176 \tabularnewline
122 & 0.995153926958088 & 0.00969214608382435 & 0.00484607304191218 \tabularnewline
123 & 0.9942138122274 & 0.0115723755451998 & 0.00578618777259992 \tabularnewline
124 & 0.993165188338967 & 0.0136696233220653 & 0.00683481166103265 \tabularnewline
125 & 0.991606494014308 & 0.0167870119713841 & 0.00839350598569203 \tabularnewline
126 & 0.993047568978089 & 0.0139048620438217 & 0.00695243102191086 \tabularnewline
127 & 0.9938767186087 & 0.0122465627825998 & 0.00612328139129988 \tabularnewline
128 & 0.992349599945175 & 0.0153008001096508 & 0.0076504000548254 \tabularnewline
129 & 0.991286946650839 & 0.0174261066983225 & 0.00871305334916124 \tabularnewline
130 & 0.995440858128903 & 0.00911828374219442 & 0.00455914187109721 \tabularnewline
131 & 0.994849428941179 & 0.0103011421176425 & 0.00515057105882124 \tabularnewline
132 & 0.993779909318409 & 0.0124401813631816 & 0.00622009068159079 \tabularnewline
133 & 0.99358462874311 & 0.0128307425137807 & 0.00641537125689037 \tabularnewline
134 & 0.993730213067103 & 0.0125395738657933 & 0.00626978693289664 \tabularnewline
135 & 0.997635875183348 & 0.00472824963330422 & 0.00236412481665211 \tabularnewline
136 & 0.997683690139548 & 0.00463261972090321 & 0.00231630986045161 \tabularnewline
137 & 0.998856908681839 & 0.00228618263632208 & 0.00114309131816104 \tabularnewline
138 & 0.998939046585242 & 0.00212190682951582 & 0.00106095341475791 \tabularnewline
139 & 0.998650724956958 & 0.00269855008608332 & 0.00134927504304166 \tabularnewline
140 & 0.998593134095923 & 0.00281373180815478 & 0.00140686590407739 \tabularnewline
141 & 0.998216917803542 & 0.00356616439291653 & 0.00178308219645827 \tabularnewline
142 & 0.998117146742611 & 0.00376570651477759 & 0.0018828532573888 \tabularnewline
143 & 0.997773962096784 & 0.00445207580643279 & 0.0022260379032164 \tabularnewline
144 & 0.997140242441485 & 0.00571951511702897 & 0.00285975755851448 \tabularnewline
145 & 0.99789465057623 & 0.00421069884754009 & 0.00210534942377004 \tabularnewline
146 & 0.997883576597679 & 0.00423284680464142 & 0.00211642340232071 \tabularnewline
147 & 0.999200299333757 & 0.00159940133248662 & 0.000799700666243309 \tabularnewline
148 & 0.998956798014896 & 0.00208640397020775 & 0.00104320198510388 \tabularnewline
149 & 0.998899212909762 & 0.00220157418047611 & 0.00110078709023805 \tabularnewline
150 & 0.999265157061485 & 0.0014696858770292 & 0.0007348429385146 \tabularnewline
151 & 0.999423716797765 & 0.00115256640446958 & 0.000576283202234789 \tabularnewline
152 & 0.999932598767021 & 0.000134802465958615 & 6.74012329793073e-05 \tabularnewline
153 & 0.999932757128357 & 0.000134485743285089 & 6.72428716425446e-05 \tabularnewline
154 & 0.999907423642521 & 0.000185152714958663 & 9.25763574793314e-05 \tabularnewline
155 & 0.999870292950187 & 0.000259414099626085 & 0.000129707049813042 \tabularnewline
156 & 0.999884639088972 & 0.00023072182205596 & 0.00011536091102798 \tabularnewline
157 & 0.999873533893123 & 0.000252932213753323 & 0.000126466106876662 \tabularnewline
158 & 0.999842284858923 & 0.00031543028215336 & 0.00015771514107668 \tabularnewline
159 & 0.999883626531748 & 0.000232746936503973 & 0.000116373468251987 \tabularnewline
160 & 0.999841334160242 & 0.000317331679516473 & 0.000158665839758236 \tabularnewline
161 & 0.99978447613311 & 0.000431047733780764 & 0.000215523866890382 \tabularnewline
162 & 0.999804689045319 & 0.00039062190936106 & 0.00019531095468053 \tabularnewline
163 & 0.999793870444244 & 0.000412259111511462 & 0.000206129555755731 \tabularnewline
164 & 0.999759027948854 & 0.000481944102292554 & 0.000240972051146277 \tabularnewline
165 & 0.999822235642507 & 0.000355528714986571 & 0.000177764357493286 \tabularnewline
166 & 0.999809609796299 & 0.000380780407401852 & 0.000190390203700926 \tabularnewline
167 & 0.999851695314434 & 0.000296609371132578 & 0.000148304685566289 \tabularnewline
168 & 0.999835392923089 & 0.000329214153822291 & 0.000164607076911145 \tabularnewline
169 & 0.999776724893642 & 0.000446550212716166 & 0.000223275106358083 \tabularnewline
170 & 0.999903460786623 & 0.000193078426755074 & 9.6539213377537e-05 \tabularnewline
171 & 0.999895265164598 & 0.000209469670803313 & 0.000104734835401656 \tabularnewline
172 & 0.999855398023796 & 0.000289203952408335 & 0.000144601976204167 \tabularnewline
173 & 0.999802694384624 & 0.000394611230752949 & 0.000197305615376474 \tabularnewline
174 & 0.999732950269102 & 0.00053409946179582 & 0.00026704973089791 \tabularnewline
175 & 0.999788918611131 & 0.000422162777737166 & 0.000211081388868583 \tabularnewline
176 & 0.999794302887174 & 0.000411394225651939 & 0.00020569711282597 \tabularnewline
177 & 0.999734054298339 & 0.000531891403321528 & 0.000265945701660764 \tabularnewline
178 & 0.999648294261143 & 0.00070341147771493 & 0.000351705738857465 \tabularnewline
179 & 0.999533242703854 & 0.000933514592291854 & 0.000466757296145927 \tabularnewline
180 & 0.999540931119762 & 0.000918137760475116 & 0.000459068880237558 \tabularnewline
181 & 0.99976935829736 & 0.000461283405280442 & 0.000230641702640221 \tabularnewline
182 & 0.999718082268055 & 0.000563835463889556 & 0.000281917731944778 \tabularnewline
183 & 0.999859288812782 & 0.000281422374435493 & 0.000140711187217747 \tabularnewline
184 & 0.999852863587359 & 0.000294272825282505 & 0.000147136412641252 \tabularnewline
185 & 0.999897955481039 & 0.000204089037922755 & 0.000102044518961377 \tabularnewline
186 & 0.999953960320243 & 9.20793595147002e-05 & 4.60396797573501e-05 \tabularnewline
187 & 0.999964824570205 & 7.03508595904458e-05 & 3.51754297952229e-05 \tabularnewline
188 & 0.999984402345188 & 3.11953096246625e-05 & 1.55976548123313e-05 \tabularnewline
189 & 0.9999783608002 & 4.32783995997014e-05 & 2.16391997998507e-05 \tabularnewline
190 & 0.999998652940401 & 2.69411919741256e-06 & 1.34705959870628e-06 \tabularnewline
191 & 0.999998082409845 & 3.83518030992237e-06 & 1.91759015496118e-06 \tabularnewline
192 & 0.99999697641237 & 6.04717525921036e-06 & 3.02358762960518e-06 \tabularnewline
193 & 0.999996846022027 & 6.30795594551494e-06 & 3.15397797275747e-06 \tabularnewline
194 & 0.999997850949689 & 4.29810062131667e-06 & 2.14905031065833e-06 \tabularnewline
195 & 0.999996829347947 & 6.34130410634405e-06 & 3.17065205317203e-06 \tabularnewline
196 & 0.999997108227713 & 5.78354457416182e-06 & 2.89177228708091e-06 \tabularnewline
197 & 0.99999637990079 & 7.2401984192352e-06 & 3.6200992096176e-06 \tabularnewline
198 & 0.999996066514305 & 7.8669713892654e-06 & 3.9334856946327e-06 \tabularnewline
199 & 0.999994308090289 & 1.13838194215151e-05 & 5.69190971075757e-06 \tabularnewline
200 & 0.999992053285571 & 1.58934288571164e-05 & 7.9467144285582e-06 \tabularnewline
201 & 0.999987689020611 & 2.46219587784152e-05 & 1.23109793892076e-05 \tabularnewline
202 & 0.999997460549363 & 5.07890127460008e-06 & 2.53945063730004e-06 \tabularnewline
203 & 0.999996708869243 & 6.58226151419045e-06 & 3.29113075709522e-06 \tabularnewline
204 & 0.999994899240645 & 1.02015187099686e-05 & 5.10075935498429e-06 \tabularnewline
205 & 0.99999204792849 & 1.59041430194113e-05 & 7.95207150970565e-06 \tabularnewline
206 & 0.999994411508245 & 1.1176983509311e-05 & 5.58849175465552e-06 \tabularnewline
207 & 0.999991286272073 & 1.74274558535588e-05 & 8.71372792677938e-06 \tabularnewline
208 & 0.999991172782331 & 1.76544353388087e-05 & 8.82721766940434e-06 \tabularnewline
209 & 0.999986082746844 & 2.7834506311145e-05 & 1.39172531555725e-05 \tabularnewline
210 & 0.999985143596544 & 2.97128069117309e-05 & 1.48564034558654e-05 \tabularnewline
211 & 0.999991153160146 & 1.76936797086652e-05 & 8.8468398543326e-06 \tabularnewline
212 & 0.999986170818807 & 2.76583623857939e-05 & 1.38291811928969e-05 \tabularnewline
213 & 0.999983526124964 & 3.29477500710473e-05 & 1.64738750355236e-05 \tabularnewline
214 & 0.999975345790655 & 4.93084186897709e-05 & 2.46542093448855e-05 \tabularnewline
215 & 0.999982270255111 & 3.54594897776385e-05 & 1.77297448888192e-05 \tabularnewline
216 & 0.999994350300291 & 1.12993994182218e-05 & 5.64969970911092e-06 \tabularnewline
217 & 0.9999910871379 & 1.7825724200979e-05 & 8.9128621004895e-06 \tabularnewline
218 & 0.999986340807123 & 2.73183857547798e-05 & 1.36591928773899e-05 \tabularnewline
219 & 0.999979676842893 & 4.06463142145335e-05 & 2.03231571072668e-05 \tabularnewline
220 & 0.999970992534148 & 5.8014931703595e-05 & 2.90074658517975e-05 \tabularnewline
221 & 0.999966073370166 & 6.78532596688907e-05 & 3.39266298344454e-05 \tabularnewline
222 & 0.99994877819129 & 0.000102443617420172 & 5.12218087100862e-05 \tabularnewline
223 & 0.999923580626648 & 0.000152838746703211 & 7.64193733516057e-05 \tabularnewline
224 & 0.999898293237121 & 0.000203413525757738 & 0.000101706762878869 \tabularnewline
225 & 0.999939643026944 & 0.000120713946112246 & 6.03569730561231e-05 \tabularnewline
226 & 0.999973468719917 & 5.30625601659609e-05 & 2.65312800829804e-05 \tabularnewline
227 & 0.999988067523433 & 2.38649531336195e-05 & 1.19324765668097e-05 \tabularnewline
228 & 0.999979853609599 & 4.02927808029483e-05 & 2.01463904014741e-05 \tabularnewline
229 & 0.999968289518176 & 6.3420963648639e-05 & 3.17104818243195e-05 \tabularnewline
230 & 0.999961618894808 & 7.67622103847949e-05 & 3.83811051923975e-05 \tabularnewline
231 & 0.999981980382024 & 3.60392359514065e-05 & 1.80196179757033e-05 \tabularnewline
232 & 0.999973785662481 & 5.2428675037796e-05 & 2.6214337518898e-05 \tabularnewline
233 & 0.999968811116569 & 6.23777668625661e-05 & 3.11888834312831e-05 \tabularnewline
234 & 0.999967050587306 & 6.58988253879375e-05 & 3.29494126939688e-05 \tabularnewline
235 & 0.999965701726653 & 6.85965466936171e-05 & 3.42982733468085e-05 \tabularnewline
236 & 0.999960428595111 & 7.91428097770599e-05 & 3.957140488853e-05 \tabularnewline
237 & 0.99993996015166 & 0.000120079696680715 & 6.00398483403573e-05 \tabularnewline
238 & 0.999940378898528 & 0.000119242202943914 & 5.9621101471957e-05 \tabularnewline
239 & 0.999906969500952 & 0.000186060998095539 & 9.30304990477695e-05 \tabularnewline
240 & 0.999911505921344 & 0.000176988157311018 & 8.84940786555088e-05 \tabularnewline
241 & 0.999859108477373 & 0.000281783045253583 & 0.000140891522626791 \tabularnewline
242 & 0.999800616876262 & 0.000398766247476666 & 0.000199383123738333 \tabularnewline
243 & 0.999751156634051 & 0.000497686731898924 & 0.000248843365949462 \tabularnewline
244 & 0.999620542149538 & 0.000758915700924074 & 0.000379457850462037 \tabularnewline
245 & 0.999378011274648 & 0.00124397745070441 & 0.000621988725352204 \tabularnewline
246 & 0.998991801182449 & 0.00201639763510183 & 0.00100819881755091 \tabularnewline
247 & 0.999319900996049 & 0.0013601980079021 & 0.000680099003951048 \tabularnewline
248 & 0.99894126841652 & 0.00211746316696065 & 0.00105873158348033 \tabularnewline
249 & 0.9992254166603 & 0.00154916667939975 & 0.000774583339699874 \tabularnewline
250 & 0.999407855207479 & 0.00118428958504153 & 0.000592144792520767 \tabularnewline
251 & 0.999123293368881 & 0.00175341326223743 & 0.000876706631118717 \tabularnewline
252 & 0.998589617266943 & 0.00282076546611445 & 0.00141038273305723 \tabularnewline
253 & 0.998737272295672 & 0.00252545540865648 & 0.00126272770432824 \tabularnewline
254 & 0.997894319345616 & 0.00421136130876712 & 0.00210568065438356 \tabularnewline
255 & 0.996630426778632 & 0.00673914644273584 & 0.00336957322136792 \tabularnewline
256 & 0.996014895309666 & 0.00797020938066781 & 0.00398510469033391 \tabularnewline
257 & 0.993913549595478 & 0.0121729008090432 & 0.00608645040452162 \tabularnewline
258 & 0.990514803974682 & 0.0189703920506369 & 0.00948519602531843 \tabularnewline
259 & 0.991172598912327 & 0.0176548021753463 & 0.00882740108767313 \tabularnewline
260 & 0.98620443228396 & 0.0275911354320809 & 0.0137955677160404 \tabularnewline
261 & 0.994579173445017 & 0.0108416531099668 & 0.00542082655498338 \tabularnewline
262 & 0.991161701838489 & 0.0176765963230216 & 0.0088382981615108 \tabularnewline
263 & 0.985741870309085 & 0.0285162593818293 & 0.0142581296909146 \tabularnewline
264 & 0.977680321352725 & 0.0446393572945502 & 0.0223196786472751 \tabularnewline
265 & 0.965717943060702 & 0.0685641138785962 & 0.0342820569392981 \tabularnewline
266 & 0.951332819663098 & 0.0973343606738045 & 0.0486671803369022 \tabularnewline
267 & 0.941046181856536 & 0.117907636286927 & 0.0589538181434637 \tabularnewline
268 & 0.912144833564446 & 0.175710332871108 & 0.0878551664355539 \tabularnewline
269 & 0.872367312016918 & 0.255265375966163 & 0.127632687983082 \tabularnewline
270 & 0.846861549654576 & 0.306276900690848 & 0.153138450345424 \tabularnewline
271 & 0.817634775970838 & 0.364730448058323 & 0.182365224029162 \tabularnewline
272 & 0.77891609466343 & 0.442167810673141 & 0.22108390533657 \tabularnewline
273 & 0.831289606304335 & 0.337420787391331 & 0.168710393695665 \tabularnewline
274 & 0.754538087194087 & 0.490923825611827 & 0.245461912805913 \tabularnewline
275 & 0.659333715732105 & 0.681332568535789 & 0.340666284267895 \tabularnewline
276 & 0.755996719144756 & 0.488006561710487 & 0.244003280855244 \tabularnewline
277 & 0.638268922452201 & 0.723462155095597 & 0.361731077547799 \tabularnewline
278 & 0.545855608302722 & 0.908288783394556 & 0.454144391697278 \tabularnewline
279 & 0.389728572360836 & 0.779457144721672 & 0.610271427639164 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160728&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]10[/C][C]0.692818263242828[/C][C]0.614363473514344[/C][C]0.307181736757172[/C][/ROW]
[ROW][C]11[/C][C]0.601415714773051[/C][C]0.797168570453899[/C][C]0.398584285226949[/C][/ROW]
[ROW][C]12[/C][C]0.590910535441331[/C][C]0.818178929117338[/C][C]0.409089464558669[/C][/ROW]
[ROW][C]13[/C][C]0.901965059315442[/C][C]0.196069881369115[/C][C]0.0980349406845575[/C][/ROW]
[ROW][C]14[/C][C]0.893098385086902[/C][C]0.213803229826195[/C][C]0.106901614913098[/C][/ROW]
[ROW][C]15[/C][C]0.940246842892381[/C][C]0.119506314215237[/C][C]0.0597531571076187[/C][/ROW]
[ROW][C]16[/C][C]0.926458391907255[/C][C]0.14708321618549[/C][C]0.0735416080927451[/C][/ROW]
[ROW][C]17[/C][C]0.927926067651308[/C][C]0.144147864697384[/C][C]0.0720739323486922[/C][/ROW]
[ROW][C]18[/C][C]0.921357407796625[/C][C]0.15728518440675[/C][C]0.0786425922033751[/C][/ROW]
[ROW][C]19[/C][C]0.904399352654398[/C][C]0.191201294691205[/C][C]0.0956006473456024[/C][/ROW]
[ROW][C]20[/C][C]0.925513458471991[/C][C]0.148973083056019[/C][C]0.0744865415280095[/C][/ROW]
[ROW][C]21[/C][C]0.896255864064823[/C][C]0.207488271870355[/C][C]0.103744135935177[/C][/ROW]
[ROW][C]22[/C][C]0.867528756967435[/C][C]0.26494248606513[/C][C]0.132471243032565[/C][/ROW]
[ROW][C]23[/C][C]0.827389284760448[/C][C]0.345221430479104[/C][C]0.172610715239552[/C][/ROW]
[ROW][C]24[/C][C]0.778973502585008[/C][C]0.442052994829984[/C][C]0.221026497414992[/C][/ROW]
[ROW][C]25[/C][C]0.79870819815913[/C][C]0.402583603681741[/C][C]0.20129180184087[/C][/ROW]
[ROW][C]26[/C][C]0.761229826236981[/C][C]0.477540347526038[/C][C]0.238770173763019[/C][/ROW]
[ROW][C]27[/C][C]0.708531069693637[/C][C]0.582937860612725[/C][C]0.291468930306363[/C][/ROW]
[ROW][C]28[/C][C]0.651414480407811[/C][C]0.697171039184378[/C][C]0.348585519592189[/C][/ROW]
[ROW][C]29[/C][C]0.615434358481487[/C][C]0.769131283037027[/C][C]0.384565641518513[/C][/ROW]
[ROW][C]30[/C][C]0.557561574502186[/C][C]0.884876850995628[/C][C]0.442438425497814[/C][/ROW]
[ROW][C]31[/C][C]0.496383959993334[/C][C]0.992767919986667[/C][C]0.503616040006666[/C][/ROW]
[ROW][C]32[/C][C]0.436128370275734[/C][C]0.872256740551468[/C][C]0.563871629724266[/C][/ROW]
[ROW][C]33[/C][C]0.694878919652482[/C][C]0.610242160695036[/C][C]0.305121080347518[/C][/ROW]
[ROW][C]34[/C][C]0.709236086009001[/C][C]0.581527827981998[/C][C]0.290763913990999[/C][/ROW]
[ROW][C]35[/C][C]0.713800937756294[/C][C]0.572398124487411[/C][C]0.286199062243706[/C][/ROW]
[ROW][C]36[/C][C]0.673971386890148[/C][C]0.652057226219705[/C][C]0.326028613109852[/C][/ROW]
[ROW][C]37[/C][C]0.746147542856324[/C][C]0.507704914287351[/C][C]0.253852457143676[/C][/ROW]
[ROW][C]38[/C][C]0.735583444548138[/C][C]0.528833110903725[/C][C]0.264416555451862[/C][/ROW]
[ROW][C]39[/C][C]0.705368518066111[/C][C]0.589262963867779[/C][C]0.294631481933889[/C][/ROW]
[ROW][C]40[/C][C]0.889449233183548[/C][C]0.221101533632904[/C][C]0.110550766816452[/C][/ROW]
[ROW][C]41[/C][C]0.864718769956667[/C][C]0.270562460086666[/C][C]0.135281230043333[/C][/ROW]
[ROW][C]42[/C][C]0.864944458763051[/C][C]0.270111082473898[/C][C]0.135055541236949[/C][/ROW]
[ROW][C]43[/C][C]0.850884774277347[/C][C]0.298230451445306[/C][C]0.149115225722653[/C][/ROW]
[ROW][C]44[/C][C]0.843057168441135[/C][C]0.313885663117729[/C][C]0.156942831558865[/C][/ROW]
[ROW][C]45[/C][C]0.815344206569009[/C][C]0.369311586861983[/C][C]0.184655793430991[/C][/ROW]
[ROW][C]46[/C][C]0.841884710381342[/C][C]0.316230579237316[/C][C]0.158115289618658[/C][/ROW]
[ROW][C]47[/C][C]0.823875657060364[/C][C]0.352248685879273[/C][C]0.176124342939636[/C][/ROW]
[ROW][C]48[/C][C]0.792254373329959[/C][C]0.415491253340082[/C][C]0.207745626670041[/C][/ROW]
[ROW][C]49[/C][C]0.790310735088639[/C][C]0.419378529822722[/C][C]0.209689264911361[/C][/ROW]
[ROW][C]50[/C][C]0.913699413899356[/C][C]0.172601172201288[/C][C]0.0863005861006441[/C][/ROW]
[ROW][C]51[/C][C]0.895782456499528[/C][C]0.208435087000943[/C][C]0.104217543500471[/C][/ROW]
[ROW][C]52[/C][C]0.895673797355581[/C][C]0.208652405288839[/C][C]0.10432620264442[/C][/ROW]
[ROW][C]53[/C][C]0.901619110604404[/C][C]0.196761778791191[/C][C]0.0983808893955957[/C][/ROW]
[ROW][C]54[/C][C]0.882413245847097[/C][C]0.235173508305805[/C][C]0.117586754152903[/C][/ROW]
[ROW][C]55[/C][C]0.868877461691855[/C][C]0.262245076616289[/C][C]0.131122538308145[/C][/ROW]
[ROW][C]56[/C][C]0.847378668503871[/C][C]0.305242662992257[/C][C]0.152621331496129[/C][/ROW]
[ROW][C]57[/C][C]0.894114842862844[/C][C]0.211770314274312[/C][C]0.105885157137156[/C][/ROW]
[ROW][C]58[/C][C]0.875011907270482[/C][C]0.249976185459036[/C][C]0.124988092729518[/C][/ROW]
[ROW][C]59[/C][C]0.853272546657904[/C][C]0.293454906684192[/C][C]0.146727453342096[/C][/ROW]
[ROW][C]60[/C][C]0.854845705190787[/C][C]0.290308589618426[/C][C]0.145154294809213[/C][/ROW]
[ROW][C]61[/C][C]0.830427001390219[/C][C]0.339145997219561[/C][C]0.169572998609781[/C][/ROW]
[ROW][C]62[/C][C]0.816434130965635[/C][C]0.367131738068731[/C][C]0.183565869034365[/C][/ROW]
[ROW][C]63[/C][C]0.927018364478005[/C][C]0.14596327104399[/C][C]0.0729816355219948[/C][/ROW]
[ROW][C]64[/C][C]0.914908826358552[/C][C]0.170182347282896[/C][C]0.085091173641448[/C][/ROW]
[ROW][C]65[/C][C]0.907906027728431[/C][C]0.184187944543138[/C][C]0.092093972271569[/C][/ROW]
[ROW][C]66[/C][C]0.895099433210948[/C][C]0.209801133578105[/C][C]0.104900566789053[/C][/ROW]
[ROW][C]67[/C][C]0.880314862379815[/C][C]0.23937027524037[/C][C]0.119685137620185[/C][/ROW]
[ROW][C]68[/C][C]0.86888579632235[/C][C]0.262228407355301[/C][C]0.13111420367765[/C][/ROW]
[ROW][C]69[/C][C]0.941460803160836[/C][C]0.117078393678329[/C][C]0.0585391968391643[/C][/ROW]
[ROW][C]70[/C][C]0.962808573159277[/C][C]0.0743828536814458[/C][C]0.0371914268407229[/C][/ROW]
[ROW][C]71[/C][C]0.957934938124817[/C][C]0.0841301237503662[/C][C]0.0420650618751831[/C][/ROW]
[ROW][C]72[/C][C]0.948947533135289[/C][C]0.102104933729423[/C][C]0.0510524668647114[/C][/ROW]
[ROW][C]73[/C][C]0.939735978867643[/C][C]0.120528042264714[/C][C]0.0602640211323568[/C][/ROW]
[ROW][C]74[/C][C]0.931385781992336[/C][C]0.137228436015329[/C][C]0.0686142180076645[/C][/ROW]
[ROW][C]75[/C][C]0.934740432471776[/C][C]0.130519135056448[/C][C]0.0652595675282239[/C][/ROW]
[ROW][C]76[/C][C]0.933621782175807[/C][C]0.132756435648387[/C][C]0.0663782178241933[/C][/ROW]
[ROW][C]77[/C][C]0.952952389217675[/C][C]0.0940952215646498[/C][C]0.0470476107823249[/C][/ROW]
[ROW][C]78[/C][C]0.970790779382713[/C][C]0.0584184412345734[/C][C]0.0292092206172867[/C][/ROW]
[ROW][C]79[/C][C]0.969074217900893[/C][C]0.0618515641982141[/C][C]0.030925782099107[/C][/ROW]
[ROW][C]80[/C][C]0.980665241369654[/C][C]0.0386695172606917[/C][C]0.0193347586303458[/C][/ROW]
[ROW][C]81[/C][C]0.976013208873193[/C][C]0.0479735822536142[/C][C]0.0239867911268071[/C][/ROW]
[ROW][C]82[/C][C]0.973282323264761[/C][C]0.0534353534704769[/C][C]0.0267176767352385[/C][/ROW]
[ROW][C]83[/C][C]0.970546602081722[/C][C]0.0589067958365554[/C][C]0.0294533979182777[/C][/ROW]
[ROW][C]84[/C][C]0.968468858242606[/C][C]0.0630622835147875[/C][C]0.0315311417573937[/C][/ROW]
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[ROW][C]191[/C][C]0.999998082409845[/C][C]3.83518030992237e-06[/C][C]1.91759015496118e-06[/C][/ROW]
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[ROW][C]218[/C][C]0.999986340807123[/C][C]2.73183857547798e-05[/C][C]1.36591928773899e-05[/C][/ROW]
[ROW][C]219[/C][C]0.999979676842893[/C][C]4.06463142145335e-05[/C][C]2.03231571072668e-05[/C][/ROW]
[ROW][C]220[/C][C]0.999970992534148[/C][C]5.8014931703595e-05[/C][C]2.90074658517975e-05[/C][/ROW]
[ROW][C]221[/C][C]0.999966073370166[/C][C]6.78532596688907e-05[/C][C]3.39266298344454e-05[/C][/ROW]
[ROW][C]222[/C][C]0.99994877819129[/C][C]0.000102443617420172[/C][C]5.12218087100862e-05[/C][/ROW]
[ROW][C]223[/C][C]0.999923580626648[/C][C]0.000152838746703211[/C][C]7.64193733516057e-05[/C][/ROW]
[ROW][C]224[/C][C]0.999898293237121[/C][C]0.000203413525757738[/C][C]0.000101706762878869[/C][/ROW]
[ROW][C]225[/C][C]0.999939643026944[/C][C]0.000120713946112246[/C][C]6.03569730561231e-05[/C][/ROW]
[ROW][C]226[/C][C]0.999973468719917[/C][C]5.30625601659609e-05[/C][C]2.65312800829804e-05[/C][/ROW]
[ROW][C]227[/C][C]0.999988067523433[/C][C]2.38649531336195e-05[/C][C]1.19324765668097e-05[/C][/ROW]
[ROW][C]228[/C][C]0.999979853609599[/C][C]4.02927808029483e-05[/C][C]2.01463904014741e-05[/C][/ROW]
[ROW][C]229[/C][C]0.999968289518176[/C][C]6.3420963648639e-05[/C][C]3.17104818243195e-05[/C][/ROW]
[ROW][C]230[/C][C]0.999961618894808[/C][C]7.67622103847949e-05[/C][C]3.83811051923975e-05[/C][/ROW]
[ROW][C]231[/C][C]0.999981980382024[/C][C]3.60392359514065e-05[/C][C]1.80196179757033e-05[/C][/ROW]
[ROW][C]232[/C][C]0.999973785662481[/C][C]5.2428675037796e-05[/C][C]2.6214337518898e-05[/C][/ROW]
[ROW][C]233[/C][C]0.999968811116569[/C][C]6.23777668625661e-05[/C][C]3.11888834312831e-05[/C][/ROW]
[ROW][C]234[/C][C]0.999967050587306[/C][C]6.58988253879375e-05[/C][C]3.29494126939688e-05[/C][/ROW]
[ROW][C]235[/C][C]0.999965701726653[/C][C]6.85965466936171e-05[/C][C]3.42982733468085e-05[/C][/ROW]
[ROW][C]236[/C][C]0.999960428595111[/C][C]7.91428097770599e-05[/C][C]3.957140488853e-05[/C][/ROW]
[ROW][C]237[/C][C]0.99993996015166[/C][C]0.000120079696680715[/C][C]6.00398483403573e-05[/C][/ROW]
[ROW][C]238[/C][C]0.999940378898528[/C][C]0.000119242202943914[/C][C]5.9621101471957e-05[/C][/ROW]
[ROW][C]239[/C][C]0.999906969500952[/C][C]0.000186060998095539[/C][C]9.30304990477695e-05[/C][/ROW]
[ROW][C]240[/C][C]0.999911505921344[/C][C]0.000176988157311018[/C][C]8.84940786555088e-05[/C][/ROW]
[ROW][C]241[/C][C]0.999859108477373[/C][C]0.000281783045253583[/C][C]0.000140891522626791[/C][/ROW]
[ROW][C]242[/C][C]0.999800616876262[/C][C]0.000398766247476666[/C][C]0.000199383123738333[/C][/ROW]
[ROW][C]243[/C][C]0.999751156634051[/C][C]0.000497686731898924[/C][C]0.000248843365949462[/C][/ROW]
[ROW][C]244[/C][C]0.999620542149538[/C][C]0.000758915700924074[/C][C]0.000379457850462037[/C][/ROW]
[ROW][C]245[/C][C]0.999378011274648[/C][C]0.00124397745070441[/C][C]0.000621988725352204[/C][/ROW]
[ROW][C]246[/C][C]0.998991801182449[/C][C]0.00201639763510183[/C][C]0.00100819881755091[/C][/ROW]
[ROW][C]247[/C][C]0.999319900996049[/C][C]0.0013601980079021[/C][C]0.000680099003951048[/C][/ROW]
[ROW][C]248[/C][C]0.99894126841652[/C][C]0.00211746316696065[/C][C]0.00105873158348033[/C][/ROW]
[ROW][C]249[/C][C]0.9992254166603[/C][C]0.00154916667939975[/C][C]0.000774583339699874[/C][/ROW]
[ROW][C]250[/C][C]0.999407855207479[/C][C]0.00118428958504153[/C][C]0.000592144792520767[/C][/ROW]
[ROW][C]251[/C][C]0.999123293368881[/C][C]0.00175341326223743[/C][C]0.000876706631118717[/C][/ROW]
[ROW][C]252[/C][C]0.998589617266943[/C][C]0.00282076546611445[/C][C]0.00141038273305723[/C][/ROW]
[ROW][C]253[/C][C]0.998737272295672[/C][C]0.00252545540865648[/C][C]0.00126272770432824[/C][/ROW]
[ROW][C]254[/C][C]0.997894319345616[/C][C]0.00421136130876712[/C][C]0.00210568065438356[/C][/ROW]
[ROW][C]255[/C][C]0.996630426778632[/C][C]0.00673914644273584[/C][C]0.00336957322136792[/C][/ROW]
[ROW][C]256[/C][C]0.996014895309666[/C][C]0.00797020938066781[/C][C]0.00398510469033391[/C][/ROW]
[ROW][C]257[/C][C]0.993913549595478[/C][C]0.0121729008090432[/C][C]0.00608645040452162[/C][/ROW]
[ROW][C]258[/C][C]0.990514803974682[/C][C]0.0189703920506369[/C][C]0.00948519602531843[/C][/ROW]
[ROW][C]259[/C][C]0.991172598912327[/C][C]0.0176548021753463[/C][C]0.00882740108767313[/C][/ROW]
[ROW][C]260[/C][C]0.98620443228396[/C][C]0.0275911354320809[/C][C]0.0137955677160404[/C][/ROW]
[ROW][C]261[/C][C]0.994579173445017[/C][C]0.0108416531099668[/C][C]0.00542082655498338[/C][/ROW]
[ROW][C]262[/C][C]0.991161701838489[/C][C]0.0176765963230216[/C][C]0.0088382981615108[/C][/ROW]
[ROW][C]263[/C][C]0.985741870309085[/C][C]0.0285162593818293[/C][C]0.0142581296909146[/C][/ROW]
[ROW][C]264[/C][C]0.977680321352725[/C][C]0.0446393572945502[/C][C]0.0223196786472751[/C][/ROW]
[ROW][C]265[/C][C]0.965717943060702[/C][C]0.0685641138785962[/C][C]0.0342820569392981[/C][/ROW]
[ROW][C]266[/C][C]0.951332819663098[/C][C]0.0973343606738045[/C][C]0.0486671803369022[/C][/ROW]
[ROW][C]267[/C][C]0.941046181856536[/C][C]0.117907636286927[/C][C]0.0589538181434637[/C][/ROW]
[ROW][C]268[/C][C]0.912144833564446[/C][C]0.175710332871108[/C][C]0.0878551664355539[/C][/ROW]
[ROW][C]269[/C][C]0.872367312016918[/C][C]0.255265375966163[/C][C]0.127632687983082[/C][/ROW]
[ROW][C]270[/C][C]0.846861549654576[/C][C]0.306276900690848[/C][C]0.153138450345424[/C][/ROW]
[ROW][C]271[/C][C]0.817634775970838[/C][C]0.364730448058323[/C][C]0.182365224029162[/C][/ROW]
[ROW][C]272[/C][C]0.77891609466343[/C][C]0.442167810673141[/C][C]0.22108390533657[/C][/ROW]
[ROW][C]273[/C][C]0.831289606304335[/C][C]0.337420787391331[/C][C]0.168710393695665[/C][/ROW]
[ROW][C]274[/C][C]0.754538087194087[/C][C]0.490923825611827[/C][C]0.245461912805913[/C][/ROW]
[ROW][C]275[/C][C]0.659333715732105[/C][C]0.681332568535789[/C][C]0.340666284267895[/C][/ROW]
[ROW][C]276[/C][C]0.755996719144756[/C][C]0.488006561710487[/C][C]0.244003280855244[/C][/ROW]
[ROW][C]277[/C][C]0.638268922452201[/C][C]0.723462155095597[/C][C]0.361731077547799[/C][/ROW]
[ROW][C]278[/C][C]0.545855608302722[/C][C]0.908288783394556[/C][C]0.454144391697278[/C][/ROW]
[ROW][C]279[/C][C]0.389728572360836[/C][C]0.779457144721672[/C][C]0.610271427639164[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160728&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160728&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.6928182632428280.6143634735143440.307181736757172
110.6014157147730510.7971685704538990.398584285226949
120.5909105354413310.8181789291173380.409089464558669
130.9019650593154420.1960698813691150.0980349406845575
140.8930983850869020.2138032298261950.106901614913098
150.9402468428923810.1195063142152370.0597531571076187
160.9264583919072550.147083216185490.0735416080927451
170.9279260676513080.1441478646973840.0720739323486922
180.9213574077966250.157285184406750.0786425922033751
190.9043993526543980.1912012946912050.0956006473456024
200.9255134584719910.1489730830560190.0744865415280095
210.8962558640648230.2074882718703550.103744135935177
220.8675287569674350.264942486065130.132471243032565
230.8273892847604480.3452214304791040.172610715239552
240.7789735025850080.4420529948299840.221026497414992
250.798708198159130.4025836036817410.20129180184087
260.7612298262369810.4775403475260380.238770173763019
270.7085310696936370.5829378606127250.291468930306363
280.6514144804078110.6971710391843780.348585519592189
290.6154343584814870.7691312830370270.384565641518513
300.5575615745021860.8848768509956280.442438425497814
310.4963839599933340.9927679199866670.503616040006666
320.4361283702757340.8722567405514680.563871629724266
330.6948789196524820.6102421606950360.305121080347518
340.7092360860090010.5815278279819980.290763913990999
350.7138009377562940.5723981244874110.286199062243706
360.6739713868901480.6520572262197050.326028613109852
370.7461475428563240.5077049142873510.253852457143676
380.7355834445481380.5288331109037250.264416555451862
390.7053685180661110.5892629638677790.294631481933889
400.8894492331835480.2211015336329040.110550766816452
410.8647187699566670.2705624600866660.135281230043333
420.8649444587630510.2701110824738980.135055541236949
430.8508847742773470.2982304514453060.149115225722653
440.8430571684411350.3138856631177290.156942831558865
450.8153442065690090.3693115868619830.184655793430991
460.8418847103813420.3162305792373160.158115289618658
470.8238756570603640.3522486858792730.176124342939636
480.7922543733299590.4154912533400820.207745626670041
490.7903107350886390.4193785298227220.209689264911361
500.9136994138993560.1726011722012880.0863005861006441
510.8957824564995280.2084350870009430.104217543500471
520.8956737973555810.2086524052888390.10432620264442
530.9016191106044040.1967617787911910.0983808893955957
540.8824132458470970.2351735083058050.117586754152903
550.8688774616918550.2622450766162890.131122538308145
560.8473786685038710.3052426629922570.152621331496129
570.8941148428628440.2117703142743120.105885157137156
580.8750119072704820.2499761854590360.124988092729518
590.8532725466579040.2934549066841920.146727453342096
600.8548457051907870.2903085896184260.145154294809213
610.8304270013902190.3391459972195610.169572998609781
620.8164341309656350.3671317380687310.183565869034365
630.9270183644780050.145963271043990.0729816355219948
640.9149088263585520.1701823472828960.085091173641448
650.9079060277284310.1841879445431380.092093972271569
660.8950994332109480.2098011335781050.104900566789053
670.8803148623798150.239370275240370.119685137620185
680.868885796322350.2622284073553010.13111420367765
690.9414608031608360.1170783936783290.0585391968391643
700.9628085731592770.07438285368144580.0371914268407229
710.9579349381248170.08413012375036620.0420650618751831
720.9489475331352890.1021049337294230.0510524668647114
730.9397359788676430.1205280422647140.0602640211323568
740.9313857819923360.1372284360153290.0686142180076645
750.9347404324717760.1305191350564480.0652595675282239
760.9336217821758070.1327564356483870.0663782178241933
770.9529523892176750.09409522156464980.0470476107823249
780.9707907793827130.05841844123457340.0292092206172867
790.9690742179008930.06185156419821410.030925782099107
800.9806652413696540.03866951726069170.0193347586303458
810.9760132088731930.04797358225361420.0239867911268071
820.9732823232647610.05343535347047690.0267176767352385
830.9705466020817220.05890679583655540.0294533979182777
840.9684688582426060.06306228351478750.0315311417573937
850.970600578415980.05879884316804090.0293994215840204
860.9645124333567750.07097513328645010.0354875666432251
870.9658822802978780.06823543940424380.0341177197021219
880.9593708456520180.08125830869596470.0406291543479823
890.9519505843982780.09609883120344380.0480494156017219
900.9460217269996680.1079565460006630.0539782730003315
910.9383056403828890.1233887192342210.0616943596171106
920.9745860702117540.05082785957649210.025413929788246
930.9733236018050150.05335279638996920.0266763981949846
940.9675938657012830.06481226859743470.0324061342987174
950.9619365059864140.07612698802717230.0380634940135862
960.9569127107277720.08617457854445560.0430872892722278
970.9802892529375690.0394214941248620.019710747062431
980.976010516986090.04797896602782040.0239894830139102
990.975711761605830.04857647678834040.0242882383941702
1000.9703899556582260.05922008868354840.0296100443417742
1010.9656398276377560.06872034472448730.0343601723622436
1020.9590783626441310.0818432747117380.040921637355869
1030.951703450726480.09659309854703950.0482965492735198
1040.943383766260570.113232467478860.0566162337394301
1050.9380674914405670.1238650171188670.0619325085594333
1060.9497097311780120.1005805376439750.0502902688219877
1070.9814581963140940.03708360737181150.0185418036859057
1080.978503219298980.04299356140204010.0214967807010201
1090.9960278875483860.007944224903228170.00397211245161408
1100.9960224308646790.007955138270641920.00397756913532096
1110.9955626182091940.008874763581612360.00443738179080618
1120.9968377408265610.006324518346877940.00316225917343897
1130.9960762104337270.007847579132545670.00392378956627284
1140.9960913409973120.007817318005375130.00390865900268757
1150.995083015110350.009833969779300610.00491698488965031
1160.9938585449308760.01228291013824770.00614145506912386
1170.9940060363830720.01198792723385580.00599396361692789
1180.9950104025499540.009979194900091850.00498959745004592
1190.9964686847032550.007062630593490010.00353131529674501
1200.9959289291593350.008142141681330060.00407107084066503
1210.9951938299713880.009612340057223530.00480617002861176
1220.9951539269580880.009692146083824350.00484607304191218
1230.99421381222740.01157237554519980.00578618777259992
1240.9931651883389670.01366962332206530.00683481166103265
1250.9916064940143080.01678701197138410.00839350598569203
1260.9930475689780890.01390486204382170.00695243102191086
1270.99387671860870.01224656278259980.00612328139129988
1280.9923495999451750.01530080010965080.0076504000548254
1290.9912869466508390.01742610669832250.00871305334916124
1300.9954408581289030.009118283742194420.00455914187109721
1310.9948494289411790.01030114211764250.00515057105882124
1320.9937799093184090.01244018136318160.00622009068159079
1330.993584628743110.01283074251378070.00641537125689037
1340.9937302130671030.01253957386579330.00626978693289664
1350.9976358751833480.004728249633304220.00236412481665211
1360.9976836901395480.004632619720903210.00231630986045161
1370.9988569086818390.002286182636322080.00114309131816104
1380.9989390465852420.002121906829515820.00106095341475791
1390.9986507249569580.002698550086083320.00134927504304166
1400.9985931340959230.002813731808154780.00140686590407739
1410.9982169178035420.003566164392916530.00178308219645827
1420.9981171467426110.003765706514777590.0018828532573888
1430.9977739620967840.004452075806432790.0022260379032164
1440.9971402424414850.005719515117028970.00285975755851448
1450.997894650576230.004210698847540090.00210534942377004
1460.9978835765976790.004232846804641420.00211642340232071
1470.9992002993337570.001599401332486620.000799700666243309
1480.9989567980148960.002086403970207750.00104320198510388
1490.9988992129097620.002201574180476110.00110078709023805
1500.9992651570614850.00146968587702920.0007348429385146
1510.9994237167977650.001152566404469580.000576283202234789
1520.9999325987670210.0001348024659586156.74012329793073e-05
1530.9999327571283570.0001344857432850896.72428716425446e-05
1540.9999074236425210.0001851527149586639.25763574793314e-05
1550.9998702929501870.0002594140996260850.000129707049813042
1560.9998846390889720.000230721822055960.00011536091102798
1570.9998735338931230.0002529322137533230.000126466106876662
1580.9998422848589230.000315430282153360.00015771514107668
1590.9998836265317480.0002327469365039730.000116373468251987
1600.9998413341602420.0003173316795164730.000158665839758236
1610.999784476133110.0004310477337807640.000215523866890382
1620.9998046890453190.000390621909361060.00019531095468053
1630.9997938704442440.0004122591115114620.000206129555755731
1640.9997590279488540.0004819441022925540.000240972051146277
1650.9998222356425070.0003555287149865710.000177764357493286
1660.9998096097962990.0003807804074018520.000190390203700926
1670.9998516953144340.0002966093711325780.000148304685566289
1680.9998353929230890.0003292141538222910.000164607076911145
1690.9997767248936420.0004465502127161660.000223275106358083
1700.9999034607866230.0001930784267550749.6539213377537e-05
1710.9998952651645980.0002094696708033130.000104734835401656
1720.9998553980237960.0002892039524083350.000144601976204167
1730.9998026943846240.0003946112307529490.000197305615376474
1740.9997329502691020.000534099461795820.00026704973089791
1750.9997889186111310.0004221627777371660.000211081388868583
1760.9997943028871740.0004113942256519390.00020569711282597
1770.9997340542983390.0005318914033215280.000265945701660764
1780.9996482942611430.000703411477714930.000351705738857465
1790.9995332427038540.0009335145922918540.000466757296145927
1800.9995409311197620.0009181377604751160.000459068880237558
1810.999769358297360.0004612834052804420.000230641702640221
1820.9997180822680550.0005638354638895560.000281917731944778
1830.9998592888127820.0002814223744354930.000140711187217747
1840.9998528635873590.0002942728252825050.000147136412641252
1850.9998979554810390.0002040890379227550.000102044518961377
1860.9999539603202439.20793595147002e-054.60396797573501e-05
1870.9999648245702057.03508595904458e-053.51754297952229e-05
1880.9999844023451883.11953096246625e-051.55976548123313e-05
1890.99997836080024.32783995997014e-052.16391997998507e-05
1900.9999986529404012.69411919741256e-061.34705959870628e-06
1910.9999980824098453.83518030992237e-061.91759015496118e-06
1920.999996976412376.04717525921036e-063.02358762960518e-06
1930.9999968460220276.30795594551494e-063.15397797275747e-06
1940.9999978509496894.29810062131667e-062.14905031065833e-06
1950.9999968293479476.34130410634405e-063.17065205317203e-06
1960.9999971082277135.78354457416182e-062.89177228708091e-06
1970.999996379900797.2401984192352e-063.6200992096176e-06
1980.9999960665143057.8669713892654e-063.9334856946327e-06
1990.9999943080902891.13838194215151e-055.69190971075757e-06
2000.9999920532855711.58934288571164e-057.9467144285582e-06
2010.9999876890206112.46219587784152e-051.23109793892076e-05
2020.9999974605493635.07890127460008e-062.53945063730004e-06
2030.9999967088692436.58226151419045e-063.29113075709522e-06
2040.9999948992406451.02015187099686e-055.10075935498429e-06
2050.999992047928491.59041430194113e-057.95207150970565e-06
2060.9999944115082451.1176983509311e-055.58849175465552e-06
2070.9999912862720731.74274558535588e-058.71372792677938e-06
2080.9999911727823311.76544353388087e-058.82721766940434e-06
2090.9999860827468442.7834506311145e-051.39172531555725e-05
2100.9999851435965442.97128069117309e-051.48564034558654e-05
2110.9999911531601461.76936797086652e-058.8468398543326e-06
2120.9999861708188072.76583623857939e-051.38291811928969e-05
2130.9999835261249643.29477500710473e-051.64738750355236e-05
2140.9999753457906554.93084186897709e-052.46542093448855e-05
2150.9999822702551113.54594897776385e-051.77297448888192e-05
2160.9999943503002911.12993994182218e-055.64969970911092e-06
2170.99999108713791.7825724200979e-058.9128621004895e-06
2180.9999863408071232.73183857547798e-051.36591928773899e-05
2190.9999796768428934.06463142145335e-052.03231571072668e-05
2200.9999709925341485.8014931703595e-052.90074658517975e-05
2210.9999660733701666.78532596688907e-053.39266298344454e-05
2220.999948778191290.0001024436174201725.12218087100862e-05
2230.9999235806266480.0001528387467032117.64193733516057e-05
2240.9998982932371210.0002034135257577380.000101706762878869
2250.9999396430269440.0001207139461122466.03569730561231e-05
2260.9999734687199175.30625601659609e-052.65312800829804e-05
2270.9999880675234332.38649531336195e-051.19324765668097e-05
2280.9999798536095994.02927808029483e-052.01463904014741e-05
2290.9999682895181766.3420963648639e-053.17104818243195e-05
2300.9999616188948087.67622103847949e-053.83811051923975e-05
2310.9999819803820243.60392359514065e-051.80196179757033e-05
2320.9999737856624815.2428675037796e-052.6214337518898e-05
2330.9999688111165696.23777668625661e-053.11888834312831e-05
2340.9999670505873066.58988253879375e-053.29494126939688e-05
2350.9999657017266536.85965466936171e-053.42982733468085e-05
2360.9999604285951117.91428097770599e-053.957140488853e-05
2370.999939960151660.0001200796966807156.00398483403573e-05
2380.9999403788985280.0001192422029439145.9621101471957e-05
2390.9999069695009520.0001860609980955399.30304990477695e-05
2400.9999115059213440.0001769881573110188.84940786555088e-05
2410.9998591084773730.0002817830452535830.000140891522626791
2420.9998006168762620.0003987662474766660.000199383123738333
2430.9997511566340510.0004976867318989240.000248843365949462
2440.9996205421495380.0007589157009240740.000379457850462037
2450.9993780112746480.001243977450704410.000621988725352204
2460.9989918011824490.002016397635101830.00100819881755091
2470.9993199009960490.00136019800790210.000680099003951048
2480.998941268416520.002117463166960650.00105873158348033
2490.99922541666030.001549166679399750.000774583339699874
2500.9994078552074790.001184289585041530.000592144792520767
2510.9991232933688810.001753413262237430.000876706631118717
2520.9985896172669430.002820765466114450.00141038273305723
2530.9987372722956720.002525455408656480.00126272770432824
2540.9978943193456160.004211361308767120.00210568065438356
2550.9966304267786320.006739146442735840.00336957322136792
2560.9960148953096660.007970209380667810.00398510469033391
2570.9939135495954780.01217290080904320.00608645040452162
2580.9905148039746820.01897039205063690.00948519602531843
2590.9911725989123270.01765480217534630.00882740108767313
2600.986204432283960.02759113543208090.0137955677160404
2610.9945791734450170.01084165310996680.00542082655498338
2620.9911617018384890.01767659632302160.0088382981615108
2630.9857418703090850.02851625938182930.0142581296909146
2640.9776803213527250.04463935729455020.0223196786472751
2650.9657179430607020.06856411387859620.0342820569392981
2660.9513328196630980.09733436067380450.0486671803369022
2670.9410461818565360.1179076362869270.0589538181434637
2680.9121448335644460.1757103328711080.0878551664355539
2690.8723673120169180.2552653759661630.127632687983082
2700.8468615496545760.3062769006908480.153138450345424
2710.8176347759708380.3647304480583230.182365224029162
2720.778916094663430.4421678106731410.22108390533657
2730.8312896063043350.3374207873913310.168710393695665
2740.7545380871940870.4909238256118270.245461912805913
2750.6593337157321050.6813325685357890.340666284267895
2760.7559967191447560.4880065617104870.244003280855244
2770.6382689224522010.7234621550955970.361731077547799
2780.5458556083027220.9082887833945560.454144391697278
2790.3897285723608360.7794571447216720.610271427639164






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1350.5NOK
5% type I error level1630.603703703703704NOK
10% type I error level1870.692592592592593NOK

\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 & 135 & 0.5 & NOK \tabularnewline
5% type I error level & 163 & 0.603703703703704 & NOK \tabularnewline
10% type I error level & 187 & 0.692592592592593 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160728&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]135[/C][C]0.5[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]163[/C][C]0.603703703703704[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]187[/C][C]0.692592592592593[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160728&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160728&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1350.5NOK
5% type I error level1630.603703703703704NOK
10% type I error level1870.692592592592593NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 6 ; par2 = 1 ; par3 = Exact Pearson Chi-Squared by Simulation ;
Parameters (R input):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}