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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 computationWed, 14 Dec 2011 09:44:54 -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/14/t1323873963ir3zo6yzofz7n44.htm/, Retrieved Wed, 01 May 2024 20:43:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155012, Retrieved Wed, 01 May 2024 20:43:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [Pearson Correlati...] [2011-12-14 13:13:32] [246430c28552f7bc561843533d7ec653]
- R     [Kendall tau Correlation Matrix] [Pearson Correlati...] [2011-12-14 13:25:26] [246430c28552f7bc561843533d7ec653]
-         [Kendall tau Correlation Matrix] [Pearson Correlati...] [2011-12-14 13:55:42] [246430c28552f7bc561843533d7ec653]
- RMPD        [Multiple Regression] [Multiple Regression] [2011-12-14 14:44:54] [7c363341293f6644b8647ab9153ed4f7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1713	269966	66	473	90	96	38	144	140824	32033	186099	165	165
1028	146082	61	352	63	64	34	133	110459	20654	113854	135	132
1807	214542	67	660	59	69	42	162	105079	16346	99776	121	121
2613	212452	100	1126	135	126	38	148	112098	35926	106194	148	145
1117	157206	49	333	48	59	27	88	43929	10621	100792	73	71
631	70849	28	179	46	8	35	129	76173	10024	47552	49	47
4294	476347	111	2091	109	145	33	128	187326	43068	250931	185	177
381	33186	19	111	46	1	18	67	22807	1271	6853	5	5
1937	201983	56	726	75	69	34	132	144408	34416	115466	125	124
1734	211698	43	585	72	82	33	120	66485	20318	110896	93	92
2010	292874	102	754	78	92	42	155	79089	24409	169351	154	149
1988	223814	107	619	61	106	55	210	81625	20648	94853	98	93
1600	156623	65	615	58	50	35	115	68788	12347	72591	70	70
2664	327332	73	1060	109	113	51	175	103297	21857	101345	148	148
1812	205898	78	588	45	70	42	158	69446	11034	113713	100	100
4698	369527	172	1626	127	168	59	223	114948	33433	165354	150	142
2043	290571	66	717	58	111	36	140	167949	35902	164263	197	194
2690	292903	146	1053	90	92	39	144	125081	22355	135213	114	113
1381	168639	52	491	41	102	29	111	125818	31219	111669	169	162
2249	253641	79	669	54	135	46	179	136588	21983	134163	200	186
2446	269240	68	819	99	122	45	171	112431	40085	140303	148	147
2681	414808	101	1150	101	86	39	144	103037	18507	150773	140	137
1306	161910	38	421	62	50	25	89	82317	16278	111848	74	71
1649	178722	53	583	65	94	52	208	118906	24662	102509	128	123
2975	200181	109	1146	150	127	41	153	83515	31452	96785	140	134
2507	203700	111	922	71	86	38	146	104581	32580	116136	116	115
2817	267099	126	1058	91	99	41	158	103129	22883	158376	147	138
1879	262716	83	593	59	117	39	142	83243	27652	153990	132	125
1495	155915	51	559	53	57	32	117	37110	9845	64057	70	66
2661	324641	59	1001	140	125	41	158	113344	20190	230054	144	137
2154	261785	72	848	49	120	45	175	139165	46201	184531	155	152
1741	192626	71	590	77	44	46	170	86652	10971	114198	165	159
2090	318563	83	779	53	133	48	185	112302	34811	198299	161	159
940	97615	35	308	40	43	37	141	69652	3029	33750	31	31
2804	343613	88	1108	72	117	39	151	119442	38941	189723	199	185
2751	272026	55	1183	87	83	42	159	69867	4958	100826	78	78
3509	408580	115	1261	71	105	41	151	101629	32344	188355	121	117
1771	206904	78	581	67	79	36	139	70168	19433	104470	112	109
934	115469	32	276	36	33	17	55	31081	12558	58391	41	41
3000	310587	176	1061	45	111	39	151	103925	36524	164808	158	149
3178	315746	76	1471	38	121	37	139	92622	26041	134097	123	123
1489	157897	62	590	70	67	38	138	79011	16637	80238	104	103
1723	192883	72	632	82	73	36	115	93487	28395	133252	94	87
1655	165876	56	450	83	68	42	157	64520	16747	54518	73	71
2496	153778	82	1022	82	50	45	73	93473	9105	121850	52	51
4948	414493	139	1864	780	98	38	138	114360	11941	79367	71	70
918	78800	42	330	57	20	26	82	33032	7935	56968	21	21
2219	207958	74	648	79	101	52	201	96125	19499	106314	155	155
3832	323118	113	1303	116	137	47	181	151911	22938	191889	174	172
2081	175523	54	868	68	99	45	164	89256	25314	104864	136	133
1805	213050	72	554	48	94	40	158	95671	28524	160791	128	125
496	24188	24	218	20	8	4	12	5950	2694	15049	7	7
2464	364968	300	816	76	83	44	163	149695	20867	191179	165	158
744	65029	17	255	21	21	18	67	32551	3597	25109	21	21
1161	101097	64	454	70	30	14	52	31701	5296	45824	35	35
2803	263096	54	1009	124	96	37	134	100087	32982	129711	137	133
2421	302012	81	639	80	122	56	210	169707	38975	210012	174	169
3449	315753	170	1048	206	115	36	134	150491	42721	194679	257	256
2323	300531	130	934	62	139	41	150	120192	41455	197680	207	190
2084	240445	79	784	77	89	36	139	95893	23923	81180	103	100
3866	360325	135	1282	65	147	46	178	151715	26719	197765	171	171
3104	296186	113	1128	146	135	28	101	176225	53405	214738	279	267
2372	210104	97	958	71	63	42	165	59900	12526	96252	83	80
2331	247076	85	847	48	72	38	147	104767	26584	124527	130	126
1363	220722	64	540	58	47	37	139	114799	37062	153242	131	132
1646	216027	65	436	58	96	30	116	72128	25696	145707	126	121
1841	187773	124	557	54	79	35	137	143592	24634	113963	158	156
2587	227055	137	794	89	85	44	167	89626	27269	134904	138	133
2254	229181	76	826	78	135	36	135	131072	25270	114268	200	199
1580	159082	63	580	62	142	28	102	126817	24634	94333	104	98
2449	232624	65	838	59	97	45	173	81351	17828	102204	111	109
893	73566	32	385	39	22	23	88	22618	3007	23824	26	25
2113	231827	76	698	55	75	45	175	88977	20065	111563	115	113
1593	181728	50	667	94	77	38	133	92059	24648	91313	127	126
1644	162366	57	548	61	110	38	148	81897	21588	89770	140	137
2153	329583	75	932	87	132	42	157	108146	25217	100125	121	121
2350	303317	87	941	48	111	36	140	126372	30927	165278	183	178
1770	205630	104	512	50	78	41	154	249771	18487	181712	68	63
2110	184970	60	648	58	126	38	148	71154	18050	80906	112	109
1601	168990	60	588	67	73	37	134	71571	17696	75881	103	101
1643	151231	45	608	41	62	28	109	55918	17326	83963	63	61
3559	421615	108	1165	114	141	45	175	160141	39361	175721	166	157
1358	145916	67	649	45	30	26	99	38692	9648	68580	38	38
2204	270487	99	623	57	116	44	122	102812	26759	136323	163	159
870	80953	25	437	31	49	8	28	56622	7905	55792	59	58
1773	139193	53	752	175	26	27	101	15986	4527	25157	27	27
1202	146777	53	342	63	71	35	129	123534	41517	100922	108	108
3422	335969	174	1351	276	59	37	143	108535	21261	118845	88	83
2417	297676	105	835	91	114	57	206	93879	36099	170492	92	88
3016	175232	101	1027	67	161	41	155	144551	39039	81716	170	164
2233	238938	87	770	58	74	37	138	56750	13841	115750	98	96
1992	228459	71	614	71	151	38	141	127654	23841	105590	205	192
1689	175244	61	545	86	41	31	114	65594	8589	92795	96	94
2916	256299	71	1046	89	121	36	140	59938	15049	82390	107	107
2342	288728	75	907	134	66	36	140	146975	39038	135599	150	144
1624	189252	36	555	64	83	36	140	143372	30391	111542	123	123
1579	222324	49	540	72	94	35	127	168553	39932	162519	176	170
1997	277755	74	736	61	154	39	141	183500	43840	211381	213	210
3760	364710	141	1247	121	151	58	223	165986	43146	189944	208	193
3611	392346	105	1389	73	164	30	114	184923	50099	226168	307	297
2355	260478	112	777	60	115	45	174	140358	40312	117495	125	125
2192	273240	62	802	85	140	41	155	149959	32616	195894	208	204
1984	186310	173	636	116	73	36	138	57224	11338	80684	73	70
602	43287	14	214	43	13	19	71	43750	7409	19630	49	49
2133	185181	78	711	85	89	23	84	48029	18213	88634	82	82
1927	202989	130	685	72	90	40	151	104978	45873	139292	206	205
2535	259498	46	1135	110	128	40	155	100046	39844	128602	112	111
2586	295230	86	999	54	169	40	150	101047	28317	135848	139	135
1072	114156	61	343	44	28	30	112	197426	24797	178377	60	59
3031	151624	82	880	79	116	41	161	160902	7471	106330	70	70
1855	306941	66	604	58	76	40	149	147172	27259	178303	112	108
2237	289398	84	660	70	145	45	164	109432	23201	116938	142	141
398	23623	11	156	9	12	1	0	1168	238	5841	11	11
1821	174970	69	648	49	120	36	139	83248	28830	106020	130	130
530	61857	25	192	25	23	11	32	25162	3913	24610	31	28
1596	163766	48	457	107	83	45	169	45724	9935	74151	132	101
2796	364027	108	1110	63	130	38	140	110529	27738	232241	219	216
387	21054	16	146	2	4	0	0	855	338	6622	4	4
2137	252805	52	866	67	81	30	111	101382	13326	127097	102	97
484	31929	22	200	22	18	8	25	14116	3988	13155	39	39
3223	294609	110	1163	152	103	39	146	89506	24347	160501	125	119
1878	217893	59	639	70	75	44	167	135356	27111	91502	121	118
1521	167612	81	463	95	55	44	165	116066	3938	24469	42	41
1652	149905	51	654	47	43	29	107	144244	17416	88229	111	107
568	38214	34	276	52	16	8	27	8773	1888	13983	16	16
1853	189451	39	646	108	66	39	147	102153	18700	80716	70	69
2627	339683	78	976	105	137	47	178	117440	36809	157384	162	160
1239	186627	57	434	58	50	48	185	104128	24959	122975	173	158
3411	386918	77	1517	131	134	46	179	134238	37343	191469	171	161
2311	302392	95	795	120	152	48	187	134047	21849	231257	172	165
3200	384345	118	1108	107	136	50	186	279488	49809	258287	254	246
1250	187992	35	473	49	71	40	151	79756	21654	122531	90	89
1121	102424	42	401	55	42	36	131	66089	8728	61394	50	49
2793	281117	310	922	149	83	40	155	102070	20920	86480	113	107
4014	399991	163	1426	155	103	46	172	146760	27195	195791	187	182
1628	131692	48	509	100	55	39	148	154771	1037	18284	16	16
3921	371090	127	1652	139	127	42	156	165933	42570	147581	175	173
1830	157429	76	689	76	55	39	143	64593	17672	72558	90	90
1627	236370	46	528	83	104	41	151	92280	34245	147341	140	140
2209	227299	84	775	185	92	42	145	67150	16786	114651	145	142
1738	209904	110	585	69	35	32	125	128692	20954	100187	141	126
3748	355457	111	1516	106	95	39	145	124089	16378	130332	125	123
2103	230883	83	743	61	121	35	129	125386	31852	134218	241	239
2035	173260	63	716	37	41	21	79	37238	2805	10901	16	15
2763	306577	96	891	56	136	45	174	140015	38086	145758	175	170
1705	141789	54	611	122	147	50	192	150047	21166	75767	132	123
2319	210565	78	901	52	88	36	132	154451	34672	134969	154	151
2393	273544	99	750	60	170	44	159	156349	36171	169216	198	194
2	1	0	0	0	0	0	0	0	0	0	0	0
207	14688	10	85	0	4	0	0	6023	2065	7953	5	5
5	98	1	0	0	0	0	0	0	0	0	0	0
8	455	2	0	0	0	0	0	0	0	0	0	0
0	0	0	0	0	0	0	0	0	0	0	0	0
0	0	0	0	0	0	0	0	0	0	0	0	0
1931	216803	82	662	58	61	37	133	84601	19354	105406	125	122
2965	347930	136	981	108	125	47	185	68946	22124	174586	174	173
0	0	0	0	0	0	0	0	0	0	0	0	0
4	203	4	0	0	0	0	0	0	0	0	0	0
151	7199	5	74	0	7	0	0	1644	556	4245	6	6
474	46660	20	259	7	12	5	15	6179	2089	21509	13	13
141	17547	5	69	3	0	1	4	3926	2658	7670	3	3
1031	112892	42	277	88	37	43	152	52789	1813	15673	35	35
29	969	2	0	0	0	0	0	0	0	0	0	0
1650	189334	62	544	46	47	31	113	100350	17372	75882	80	72

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155012&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155012&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155012&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 time7 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Total_Time_spent_in_rfc[t] = -4852.51917912818 + 12.6879977904084Pageviews[t] + 145.815465743711Logins[t] + 93.3145805510891Course_Compendium_Views[t] + 75.5303015798112Compendium_Views_pr_only[t] + 58.3793813764566Blogged_Computations[t] -1112.78069397914Reviewed_Compendiums[t] + 544.41356353873submitted_Feedback_Messages_in_Peer_Reviews[t] -0.153642989977112Number_of_characters[t] -0.27847238853901Total_number_of_revisions[t] + 0.752914871159385Total_Time[t] -221.355435199758Hyperlinks[t] + 308.826985567258Blogs[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Total_Time_spent_in_rfc[t] =  -4852.51917912818 +  12.6879977904084Pageviews[t] +  145.815465743711Logins[t] +  93.3145805510891Course_Compendium_Views[t] +  75.5303015798112Compendium_Views_pr_only[t] +  58.3793813764566Blogged_Computations[t] -1112.78069397914Reviewed_Compendiums[t] +  544.41356353873submitted_Feedback_Messages_in_Peer_Reviews[t] -0.153642989977112Number_of_characters[t] -0.27847238853901Total_number_of_revisions[t] +  0.752914871159385Total_Time[t] -221.355435199758Hyperlinks[t] +  308.826985567258Blogs[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155012&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Total_Time_spent_in_rfc[t] =  -4852.51917912818 +  12.6879977904084Pageviews[t] +  145.815465743711Logins[t] +  93.3145805510891Course_Compendium_Views[t] +  75.5303015798112Compendium_Views_pr_only[t] +  58.3793813764566Blogged_Computations[t] -1112.78069397914Reviewed_Compendiums[t] +  544.41356353873submitted_Feedback_Messages_in_Peer_Reviews[t] -0.153642989977112Number_of_characters[t] -0.27847238853901Total_number_of_revisions[t] +  0.752914871159385Total_Time[t] -221.355435199758Hyperlinks[t] +  308.826985567258Blogs[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155012&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155012&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
Total_Time_spent_in_rfc[t] = -4852.51917912818 + 12.6879977904084Pageviews[t] + 145.815465743711Logins[t] + 93.3145805510891Course_Compendium_Views[t] + 75.5303015798112Compendium_Views_pr_only[t] + 58.3793813764566Blogged_Computations[t] -1112.78069397914Reviewed_Compendiums[t] + 544.41356353873submitted_Feedback_Messages_in_Peer_Reviews[t] -0.153642989977112Number_of_characters[t] -0.27847238853901Total_number_of_revisions[t] + 0.752914871159385Total_Time[t] -221.355435199758Hyperlinks[t] + 308.826985567258Blogs[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-4852.519179128186538.138606-0.74220.4591270.229564
Pageviews12.687997790408413.9238330.91120.363620.18181
Logins145.81546574371183.2179491.75220.0817670.040884
Course_Compendium_Views93.314580551089127.8441723.35130.0010160.000508
Compendium_Views_pr_only75.530301579811246.959771.60840.1098350.054918
Blogged_Computations58.3793813764566126.2214280.46250.6443770.322189
Reviewed_Compendiums-1112.78069397914980.84681-1.13450.2583780.129189
submitted_Feedback_Messages_in_Peer_Reviews544.41356353873257.944482.11060.0364560.018228
Number_of_characters-0.1536429899771120.085777-1.79120.0752670.037633
Total_number_of_revisions-0.278472388539010.403009-0.6910.4906370.245319
Total_Time0.7529148711593850.0902388.343600
Hyperlinks-221.355435199758642.249984-0.34470.7308320.365416
Blogs308.826985567258664.3009850.46490.642680.32134

\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) & -4852.51917912818 & 6538.138606 & -0.7422 & 0.459127 & 0.229564 \tabularnewline
Pageviews & 12.6879977904084 & 13.923833 & 0.9112 & 0.36362 & 0.18181 \tabularnewline
Logins & 145.815465743711 & 83.217949 & 1.7522 & 0.081767 & 0.040884 \tabularnewline
Course_Compendium_Views & 93.3145805510891 & 27.844172 & 3.3513 & 0.001016 & 0.000508 \tabularnewline
Compendium_Views_pr_only & 75.5303015798112 & 46.95977 & 1.6084 & 0.109835 & 0.054918 \tabularnewline
Blogged_Computations & 58.3793813764566 & 126.221428 & 0.4625 & 0.644377 & 0.322189 \tabularnewline
Reviewed_Compendiums & -1112.78069397914 & 980.84681 & -1.1345 & 0.258378 & 0.129189 \tabularnewline
submitted_Feedback_Messages_in_Peer_Reviews & 544.41356353873 & 257.94448 & 2.1106 & 0.036456 & 0.018228 \tabularnewline
Number_of_characters & -0.153642989977112 & 0.085777 & -1.7912 & 0.075267 & 0.037633 \tabularnewline
Total_number_of_revisions & -0.27847238853901 & 0.403009 & -0.691 & 0.490637 & 0.245319 \tabularnewline
Total_Time & 0.752914871159385 & 0.090238 & 8.3436 & 0 & 0 \tabularnewline
Hyperlinks & -221.355435199758 & 642.249984 & -0.3447 & 0.730832 & 0.365416 \tabularnewline
Blogs & 308.826985567258 & 664.300985 & 0.4649 & 0.64268 & 0.32134 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155012&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]-4852.51917912818[/C][C]6538.138606[/C][C]-0.7422[/C][C]0.459127[/C][C]0.229564[/C][/ROW]
[ROW][C]Pageviews[/C][C]12.6879977904084[/C][C]13.923833[/C][C]0.9112[/C][C]0.36362[/C][C]0.18181[/C][/ROW]
[ROW][C]Logins[/C][C]145.815465743711[/C][C]83.217949[/C][C]1.7522[/C][C]0.081767[/C][C]0.040884[/C][/ROW]
[ROW][C]Course_Compendium_Views[/C][C]93.3145805510891[/C][C]27.844172[/C][C]3.3513[/C][C]0.001016[/C][C]0.000508[/C][/ROW]
[ROW][C]Compendium_Views_pr_only[/C][C]75.5303015798112[/C][C]46.95977[/C][C]1.6084[/C][C]0.109835[/C][C]0.054918[/C][/ROW]
[ROW][C]Blogged_Computations[/C][C]58.3793813764566[/C][C]126.221428[/C][C]0.4625[/C][C]0.644377[/C][C]0.322189[/C][/ROW]
[ROW][C]Reviewed_Compendiums[/C][C]-1112.78069397914[/C][C]980.84681[/C][C]-1.1345[/C][C]0.258378[/C][C]0.129189[/C][/ROW]
[ROW][C]submitted_Feedback_Messages_in_Peer_Reviews[/C][C]544.41356353873[/C][C]257.94448[/C][C]2.1106[/C][C]0.036456[/C][C]0.018228[/C][/ROW]
[ROW][C]Number_of_characters[/C][C]-0.153642989977112[/C][C]0.085777[/C][C]-1.7912[/C][C]0.075267[/C][C]0.037633[/C][/ROW]
[ROW][C]Total_number_of_revisions[/C][C]-0.27847238853901[/C][C]0.403009[/C][C]-0.691[/C][C]0.490637[/C][C]0.245319[/C][/ROW]
[ROW][C]Total_Time[/C][C]0.752914871159385[/C][C]0.090238[/C][C]8.3436[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Hyperlinks[/C][C]-221.355435199758[/C][C]642.249984[/C][C]-0.3447[/C][C]0.730832[/C][C]0.365416[/C][/ROW]
[ROW][C]Blogs[/C][C]308.826985567258[/C][C]664.300985[/C][C]0.4649[/C][C]0.64268[/C][C]0.32134[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155012&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155012&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)-4852.519179128186538.138606-0.74220.4591270.229564
Pageviews12.687997790408413.9238330.91120.363620.18181
Logins145.81546574371183.2179491.75220.0817670.040884
Course_Compendium_Views93.314580551089127.8441723.35130.0010160.000508
Compendium_Views_pr_only75.530301579811246.959771.60840.1098350.054918
Blogged_Computations58.3793813764566126.2214280.46250.6443770.322189
Reviewed_Compendiums-1112.78069397914980.84681-1.13450.2583780.129189
submitted_Feedback_Messages_in_Peer_Reviews544.41356353873257.944482.11060.0364560.018228
Number_of_characters-0.1536429899771120.085777-1.79120.0752670.037633
Total_number_of_revisions-0.278472388539010.403009-0.6910.4906370.245319
Total_Time0.7529148711593850.0902388.343600
Hyperlinks-221.355435199758642.249984-0.34470.7308320.365416
Blogs308.826985567258664.3009850.46490.642680.32134






Multiple Linear Regression - Regression Statistics
Multiple R0.96121587830119
R-squared0.923935964698328
Adjusted R-squared0.917891140700844
F-TEST (value)152.847455125726
F-TEST (DF numerator)12
F-TEST (DF denominator)151
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation30656.8510288178
Sum Squared Residuals141916219765.472

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.96121587830119 \tabularnewline
R-squared & 0.923935964698328 \tabularnewline
Adjusted R-squared & 0.917891140700844 \tabularnewline
F-TEST (value) & 152.847455125726 \tabularnewline
F-TEST (DF numerator) & 12 \tabularnewline
F-TEST (DF denominator) & 151 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 30656.8510288178 \tabularnewline
Sum Squared Residuals & 141916219765.472 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155012&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.96121587830119[/C][/ROW]
[ROW][C]R-squared[/C][C]0.923935964698328[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.917891140700844[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]152.847455125726[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]12[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]151[/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]30656.8510288178[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]141916219765.472[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155012&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155012&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 R0.96121587830119
R-squared0.923935964698328
Adjusted R-squared0.917891140700844
F-TEST (value)152.847455125726
F-TEST (DF numerator)12
F-TEST (DF denominator)151
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation30656.8510288178
Sum Squared Residuals141916219765.472






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1269966243148.25688420526817.7431157953
2146082166881.096417868-20799.0964178678
3214542204384.95582342510157.0441765754
4212452268541.79652582-56089.7965258202
5157206144420.36708293812785.6329170619
67084984139.409969-13290.409969
7476347472463.761264493883.23873550955
83318634827.4590744886-1641.45907448861
9201983205147.183531001-3164.18353100065
10211698192289.03792049619408.9620795041
11292874275276.97464053417597.025359466
12223814217807.9779672836006.02203271706
13156623160045.471038141-3422.47103814128
14327332259149.03865212168182.9613478794
15205898211767.495032388-5869.49503238769
16369527414892.19111881-45365.1911188099
17290571248797.66576743741773.334232563
18292903282016.98166444210886.0183355585
19168639171953.644381153-3314.64438115263
20253641242928.23565812410712.7643418763
21269240259978.1660149119261.83398508946
22414808302703.59462425112104.40537575
23161910157357.6023509984552.39764900163
24178722205667.180538686-26945.1805386855
25200181273815.575835952-73634.575835952
26203700248897.469743703-45197.4697437025
27267099308140.485377587-41041.4853775868
28262716236457.20782096826258.7921790321
29155915153807.5287095032107.47129049718
30324641349794.573573955-25153.5735739547
31261785285330.972752202-23545.9727522017
32192626214585.328859407-21959.3288594072
33318563301349.95205554317213.0479444566
349761598617.0436589851-1002.04365898507
35343613324758.62276040318854.3772395972
36272026270325.6893424251700.31065757476
37408580348725.59164689859854.4083531023
38206904199828.1582463867075.84175361434
3911546992367.426312477223101.5736875228
40310587315557.924982361-4970.92498236096
41315746318492.523132661-2746.52313266118
42157897172606.182267524-14709.1822675236
43192883203602.167420061-10719.1674200607
44165876147516.8571341918359.1428658101
45153778212006.013912097-58228.0139120973
46414493394375.03832220720117.9616777934
4778800102339.696209803-23539.6962098028
48207958231390.698511854-23432.6985118542
49323118374182.404662141-51064.4046621411
50175523229707.113931866-54184.1139318665
51213050239553.027230721-26503.0272307209
522418839620.8948756191-15432.8948756191
53364968324064.95507406240903.0449259381
546502964858.1356519971170.864348002872
55101097112561.982897417-11464.9828974175
56263096263336.488452994-240.488452994399
57302012297349.3518181314662.64818186923
58315753350384.447854534-34631.4478545344
59300531311251.200040333-10720.2000403332
60240445200701.8354576539743.16454235
61360325375829.996106295-15504.996106295
62296186339434.089965544-43248.0899655441
63210104247026.740864619-36922.7408646189
64247076242121.4640477414954.53595225905
65220722212975.4486848637746.55131513731
66216027206893.4777059099133.52229409097
67187773202976.86061458-15203.8606145804
68227055266413.082321605-39358.0823216046
69229181235158.621220613-5977.62122061281
70159082167772.789280839-8690.78928083945
71232624236702.49722573-4078.49722573017
727356689204.950640307-15638.950640307
73231827226083.4106505815743.58934941909
74181728185150.426203957-3422.42620395713
75162366185085.184462785-22719.1844627854
76329583235714.99002905593868.0099709451
77303317282597.53654256320719.4634574366
78205630224786.813016346-19156.8130163459
79184970194986.956206468-10016.956206468
80168990169779.242707194-789.242707194012
81151231168884.128840266-17653.1288402665
82421615335281.10596635986333.8940336406
83145916159150.83516725-13234.8351672505
84270487216630.06540750153856.9345924991
858095398110.9838745723-17157.9838745723
86139193152806.47296732-13613.4729673202
87146777145116.7616703451660.23832965464
88335969324011.98526717211957.0147328276
89297676291993.48349175682.51650830007
90175232238657.484766018-63425.4847660178
91238938233205.8485261085732.15147389172
92228459203889.60283428824569.3971657116
93175244177961.296905602-2717.29690560216
94256299248041.8552170458257.14478295458
95288728250476.74033172938251.2596682707
96189252182878.4342076256373.56579237499
97222324212723.7590827159600.24091728477
98277755283372.066158838-5617.06615883809
99364710373650.797597412-8940.79759741169
100392346381343.50897426711002.4910257328
101260478236369.62751735224108.3724826484
102273240292519.183124378-19279.1831243781
103186310207244.533135076-20934.5331350758
1044328756594.3991511967-13307.3991511967
105185181193139.264202573-7958.26420257256
106202989244543.130102381-41554.1301023808
107259498275432.408640791-15934.4086407906
108295230274610.14878253720619.8512174629
109114156184203.274488053-70047.2744880526
110151624241822.493728637-90198.4937286373
111306941242699.18880949364241.8111905067
112289398227209.67357025462188.3264297458
1132362321740.12460308061882.87539691942
114174970205477.836618746-30507.8366187459
1156185747204.280183578614652.7198164214
116163766167909.626347595-4143.62634759516
117364027364611.556471798-584.556471797736
1182105421509.4903613145-455.490361314475
119252805231273.93583551821531.0641644816
1203192940616.5304065998-8687.53040659978
121294609323577.706359293-28968.706359293
122217893189031.58711355928861.412886441
123167612123572.4616265944039.5383734101
124149905164505.232101647-14600.2321016466
1253821453779.2677097674-15565.2677097674
126189451178950.95370282710500.0462971734
127339683295216.43494778144466.5650522193
128186627194421.632198882-7794.63219888224
129386918380197.1740334426720.82596655829
130302392339156.596757111-36764.5967571107
131384345375394.5582665168950.44173348386
132187992187324.990366399667.009633600899
133102424128482.882712169-26058.8827121687
134281117269431.693457911685.3065421001
135399991395188.409480614802.59051939017
136131692109336.04679358722355.9532064135
137371090362132.7766040098957.22339599135
138157429184803.110642969-27374.1106429689
139236370220158.1585388716211.8414611301
140227299242377.525883242-15078.5258832421
141209904185051.16614656224852.8338534384
142355457334265.25524846421191.7447515357
143230883239602.171514122-8719.17151412236
144173260124591.39320187348668.6067981265
145306577275556.64582591631020.3541740842
146141789185219.682804574-43430.6828045745
147210565241667.234693536-31102.234693536
148273544271381.9943144522162.00568554817
1491-4827.143183547424828.14318354742
1501468812322.16040447472365.83959552529
15198-4643.263724432484741.26372443248
152455-4459.384265317554914.38426531755
1530-4852.519179128244852.51917912824
1540-4852.519179128244852.51917912824
155216803203536.44564479613266.5543552044
156347930337616.03877512910313.9612248711
1570-4852.519179128244852.51917912824
158203-4218.505324991764421.50532499176
15971998419.9136530843-1220.9136530843
1604666047878.4293857112-1218.42938571118
1611754710089.62608648647457.37391351359
16211289290155.599183627122736.4008163729
163969-4192.936311718975161.93631171897
164189334150531.22185511238802.7781448884

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 269966 & 243148.256884205 & 26817.7431157953 \tabularnewline
2 & 146082 & 166881.096417868 & -20799.0964178678 \tabularnewline
3 & 214542 & 204384.955823425 & 10157.0441765754 \tabularnewline
4 & 212452 & 268541.79652582 & -56089.7965258202 \tabularnewline
5 & 157206 & 144420.367082938 & 12785.6329170619 \tabularnewline
6 & 70849 & 84139.409969 & -13290.409969 \tabularnewline
7 & 476347 & 472463.76126449 & 3883.23873550955 \tabularnewline
8 & 33186 & 34827.4590744886 & -1641.45907448861 \tabularnewline
9 & 201983 & 205147.183531001 & -3164.18353100065 \tabularnewline
10 & 211698 & 192289.037920496 & 19408.9620795041 \tabularnewline
11 & 292874 & 275276.974640534 & 17597.025359466 \tabularnewline
12 & 223814 & 217807.977967283 & 6006.02203271706 \tabularnewline
13 & 156623 & 160045.471038141 & -3422.47103814128 \tabularnewline
14 & 327332 & 259149.038652121 & 68182.9613478794 \tabularnewline
15 & 205898 & 211767.495032388 & -5869.49503238769 \tabularnewline
16 & 369527 & 414892.19111881 & -45365.1911188099 \tabularnewline
17 & 290571 & 248797.665767437 & 41773.334232563 \tabularnewline
18 & 292903 & 282016.981664442 & 10886.0183355585 \tabularnewline
19 & 168639 & 171953.644381153 & -3314.64438115263 \tabularnewline
20 & 253641 & 242928.235658124 & 10712.7643418763 \tabularnewline
21 & 269240 & 259978.166014911 & 9261.83398508946 \tabularnewline
22 & 414808 & 302703.59462425 & 112104.40537575 \tabularnewline
23 & 161910 & 157357.602350998 & 4552.39764900163 \tabularnewline
24 & 178722 & 205667.180538686 & -26945.1805386855 \tabularnewline
25 & 200181 & 273815.575835952 & -73634.575835952 \tabularnewline
26 & 203700 & 248897.469743703 & -45197.4697437025 \tabularnewline
27 & 267099 & 308140.485377587 & -41041.4853775868 \tabularnewline
28 & 262716 & 236457.207820968 & 26258.7921790321 \tabularnewline
29 & 155915 & 153807.528709503 & 2107.47129049718 \tabularnewline
30 & 324641 & 349794.573573955 & -25153.5735739547 \tabularnewline
31 & 261785 & 285330.972752202 & -23545.9727522017 \tabularnewline
32 & 192626 & 214585.328859407 & -21959.3288594072 \tabularnewline
33 & 318563 & 301349.952055543 & 17213.0479444566 \tabularnewline
34 & 97615 & 98617.0436589851 & -1002.04365898507 \tabularnewline
35 & 343613 & 324758.622760403 & 18854.3772395972 \tabularnewline
36 & 272026 & 270325.689342425 & 1700.31065757476 \tabularnewline
37 & 408580 & 348725.591646898 & 59854.4083531023 \tabularnewline
38 & 206904 & 199828.158246386 & 7075.84175361434 \tabularnewline
39 & 115469 & 92367.4263124772 & 23101.5736875228 \tabularnewline
40 & 310587 & 315557.924982361 & -4970.92498236096 \tabularnewline
41 & 315746 & 318492.523132661 & -2746.52313266118 \tabularnewline
42 & 157897 & 172606.182267524 & -14709.1822675236 \tabularnewline
43 & 192883 & 203602.167420061 & -10719.1674200607 \tabularnewline
44 & 165876 & 147516.85713419 & 18359.1428658101 \tabularnewline
45 & 153778 & 212006.013912097 & -58228.0139120973 \tabularnewline
46 & 414493 & 394375.038322207 & 20117.9616777934 \tabularnewline
47 & 78800 & 102339.696209803 & -23539.6962098028 \tabularnewline
48 & 207958 & 231390.698511854 & -23432.6985118542 \tabularnewline
49 & 323118 & 374182.404662141 & -51064.4046621411 \tabularnewline
50 & 175523 & 229707.113931866 & -54184.1139318665 \tabularnewline
51 & 213050 & 239553.027230721 & -26503.0272307209 \tabularnewline
52 & 24188 & 39620.8948756191 & -15432.8948756191 \tabularnewline
53 & 364968 & 324064.955074062 & 40903.0449259381 \tabularnewline
54 & 65029 & 64858.1356519971 & 170.864348002872 \tabularnewline
55 & 101097 & 112561.982897417 & -11464.9828974175 \tabularnewline
56 & 263096 & 263336.488452994 & -240.488452994399 \tabularnewline
57 & 302012 & 297349.351818131 & 4662.64818186923 \tabularnewline
58 & 315753 & 350384.447854534 & -34631.4478545344 \tabularnewline
59 & 300531 & 311251.200040333 & -10720.2000403332 \tabularnewline
60 & 240445 & 200701.83545765 & 39743.16454235 \tabularnewline
61 & 360325 & 375829.996106295 & -15504.996106295 \tabularnewline
62 & 296186 & 339434.089965544 & -43248.0899655441 \tabularnewline
63 & 210104 & 247026.740864619 & -36922.7408646189 \tabularnewline
64 & 247076 & 242121.464047741 & 4954.53595225905 \tabularnewline
65 & 220722 & 212975.448684863 & 7746.55131513731 \tabularnewline
66 & 216027 & 206893.477705909 & 9133.52229409097 \tabularnewline
67 & 187773 & 202976.86061458 & -15203.8606145804 \tabularnewline
68 & 227055 & 266413.082321605 & -39358.0823216046 \tabularnewline
69 & 229181 & 235158.621220613 & -5977.62122061281 \tabularnewline
70 & 159082 & 167772.789280839 & -8690.78928083945 \tabularnewline
71 & 232624 & 236702.49722573 & -4078.49722573017 \tabularnewline
72 & 73566 & 89204.950640307 & -15638.950640307 \tabularnewline
73 & 231827 & 226083.410650581 & 5743.58934941909 \tabularnewline
74 & 181728 & 185150.426203957 & -3422.42620395713 \tabularnewline
75 & 162366 & 185085.184462785 & -22719.1844627854 \tabularnewline
76 & 329583 & 235714.990029055 & 93868.0099709451 \tabularnewline
77 & 303317 & 282597.536542563 & 20719.4634574366 \tabularnewline
78 & 205630 & 224786.813016346 & -19156.8130163459 \tabularnewline
79 & 184970 & 194986.956206468 & -10016.956206468 \tabularnewline
80 & 168990 & 169779.242707194 & -789.242707194012 \tabularnewline
81 & 151231 & 168884.128840266 & -17653.1288402665 \tabularnewline
82 & 421615 & 335281.105966359 & 86333.8940336406 \tabularnewline
83 & 145916 & 159150.83516725 & -13234.8351672505 \tabularnewline
84 & 270487 & 216630.065407501 & 53856.9345924991 \tabularnewline
85 & 80953 & 98110.9838745723 & -17157.9838745723 \tabularnewline
86 & 139193 & 152806.47296732 & -13613.4729673202 \tabularnewline
87 & 146777 & 145116.761670345 & 1660.23832965464 \tabularnewline
88 & 335969 & 324011.985267172 & 11957.0147328276 \tabularnewline
89 & 297676 & 291993.4834917 & 5682.51650830007 \tabularnewline
90 & 175232 & 238657.484766018 & -63425.4847660178 \tabularnewline
91 & 238938 & 233205.848526108 & 5732.15147389172 \tabularnewline
92 & 228459 & 203889.602834288 & 24569.3971657116 \tabularnewline
93 & 175244 & 177961.296905602 & -2717.29690560216 \tabularnewline
94 & 256299 & 248041.855217045 & 8257.14478295458 \tabularnewline
95 & 288728 & 250476.740331729 & 38251.2596682707 \tabularnewline
96 & 189252 & 182878.434207625 & 6373.56579237499 \tabularnewline
97 & 222324 & 212723.759082715 & 9600.24091728477 \tabularnewline
98 & 277755 & 283372.066158838 & -5617.06615883809 \tabularnewline
99 & 364710 & 373650.797597412 & -8940.79759741169 \tabularnewline
100 & 392346 & 381343.508974267 & 11002.4910257328 \tabularnewline
101 & 260478 & 236369.627517352 & 24108.3724826484 \tabularnewline
102 & 273240 & 292519.183124378 & -19279.1831243781 \tabularnewline
103 & 186310 & 207244.533135076 & -20934.5331350758 \tabularnewline
104 & 43287 & 56594.3991511967 & -13307.3991511967 \tabularnewline
105 & 185181 & 193139.264202573 & -7958.26420257256 \tabularnewline
106 & 202989 & 244543.130102381 & -41554.1301023808 \tabularnewline
107 & 259498 & 275432.408640791 & -15934.4086407906 \tabularnewline
108 & 295230 & 274610.148782537 & 20619.8512174629 \tabularnewline
109 & 114156 & 184203.274488053 & -70047.2744880526 \tabularnewline
110 & 151624 & 241822.493728637 & -90198.4937286373 \tabularnewline
111 & 306941 & 242699.188809493 & 64241.8111905067 \tabularnewline
112 & 289398 & 227209.673570254 & 62188.3264297458 \tabularnewline
113 & 23623 & 21740.1246030806 & 1882.87539691942 \tabularnewline
114 & 174970 & 205477.836618746 & -30507.8366187459 \tabularnewline
115 & 61857 & 47204.2801835786 & 14652.7198164214 \tabularnewline
116 & 163766 & 167909.626347595 & -4143.62634759516 \tabularnewline
117 & 364027 & 364611.556471798 & -584.556471797736 \tabularnewline
118 & 21054 & 21509.4903613145 & -455.490361314475 \tabularnewline
119 & 252805 & 231273.935835518 & 21531.0641644816 \tabularnewline
120 & 31929 & 40616.5304065998 & -8687.53040659978 \tabularnewline
121 & 294609 & 323577.706359293 & -28968.706359293 \tabularnewline
122 & 217893 & 189031.587113559 & 28861.412886441 \tabularnewline
123 & 167612 & 123572.46162659 & 44039.5383734101 \tabularnewline
124 & 149905 & 164505.232101647 & -14600.2321016466 \tabularnewline
125 & 38214 & 53779.2677097674 & -15565.2677097674 \tabularnewline
126 & 189451 & 178950.953702827 & 10500.0462971734 \tabularnewline
127 & 339683 & 295216.434947781 & 44466.5650522193 \tabularnewline
128 & 186627 & 194421.632198882 & -7794.63219888224 \tabularnewline
129 & 386918 & 380197.174033442 & 6720.82596655829 \tabularnewline
130 & 302392 & 339156.596757111 & -36764.5967571107 \tabularnewline
131 & 384345 & 375394.558266516 & 8950.44173348386 \tabularnewline
132 & 187992 & 187324.990366399 & 667.009633600899 \tabularnewline
133 & 102424 & 128482.882712169 & -26058.8827121687 \tabularnewline
134 & 281117 & 269431.6934579 & 11685.3065421001 \tabularnewline
135 & 399991 & 395188.40948061 & 4802.59051939017 \tabularnewline
136 & 131692 & 109336.046793587 & 22355.9532064135 \tabularnewline
137 & 371090 & 362132.776604009 & 8957.22339599135 \tabularnewline
138 & 157429 & 184803.110642969 & -27374.1106429689 \tabularnewline
139 & 236370 & 220158.15853887 & 16211.8414611301 \tabularnewline
140 & 227299 & 242377.525883242 & -15078.5258832421 \tabularnewline
141 & 209904 & 185051.166146562 & 24852.8338534384 \tabularnewline
142 & 355457 & 334265.255248464 & 21191.7447515357 \tabularnewline
143 & 230883 & 239602.171514122 & -8719.17151412236 \tabularnewline
144 & 173260 & 124591.393201873 & 48668.6067981265 \tabularnewline
145 & 306577 & 275556.645825916 & 31020.3541740842 \tabularnewline
146 & 141789 & 185219.682804574 & -43430.6828045745 \tabularnewline
147 & 210565 & 241667.234693536 & -31102.234693536 \tabularnewline
148 & 273544 & 271381.994314452 & 2162.00568554817 \tabularnewline
149 & 1 & -4827.14318354742 & 4828.14318354742 \tabularnewline
150 & 14688 & 12322.1604044747 & 2365.83959552529 \tabularnewline
151 & 98 & -4643.26372443248 & 4741.26372443248 \tabularnewline
152 & 455 & -4459.38426531755 & 4914.38426531755 \tabularnewline
153 & 0 & -4852.51917912824 & 4852.51917912824 \tabularnewline
154 & 0 & -4852.51917912824 & 4852.51917912824 \tabularnewline
155 & 216803 & 203536.445644796 & 13266.5543552044 \tabularnewline
156 & 347930 & 337616.038775129 & 10313.9612248711 \tabularnewline
157 & 0 & -4852.51917912824 & 4852.51917912824 \tabularnewline
158 & 203 & -4218.50532499176 & 4421.50532499176 \tabularnewline
159 & 7199 & 8419.9136530843 & -1220.9136530843 \tabularnewline
160 & 46660 & 47878.4293857112 & -1218.42938571118 \tabularnewline
161 & 17547 & 10089.6260864864 & 7457.37391351359 \tabularnewline
162 & 112892 & 90155.5991836271 & 22736.4008163729 \tabularnewline
163 & 969 & -4192.93631171897 & 5161.93631171897 \tabularnewline
164 & 189334 & 150531.221855112 & 38802.7781448884 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155012&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]269966[/C][C]243148.256884205[/C][C]26817.7431157953[/C][/ROW]
[ROW][C]2[/C][C]146082[/C][C]166881.096417868[/C][C]-20799.0964178678[/C][/ROW]
[ROW][C]3[/C][C]214542[/C][C]204384.955823425[/C][C]10157.0441765754[/C][/ROW]
[ROW][C]4[/C][C]212452[/C][C]268541.79652582[/C][C]-56089.7965258202[/C][/ROW]
[ROW][C]5[/C][C]157206[/C][C]144420.367082938[/C][C]12785.6329170619[/C][/ROW]
[ROW][C]6[/C][C]70849[/C][C]84139.409969[/C][C]-13290.409969[/C][/ROW]
[ROW][C]7[/C][C]476347[/C][C]472463.76126449[/C][C]3883.23873550955[/C][/ROW]
[ROW][C]8[/C][C]33186[/C][C]34827.4590744886[/C][C]-1641.45907448861[/C][/ROW]
[ROW][C]9[/C][C]201983[/C][C]205147.183531001[/C][C]-3164.18353100065[/C][/ROW]
[ROW][C]10[/C][C]211698[/C][C]192289.037920496[/C][C]19408.9620795041[/C][/ROW]
[ROW][C]11[/C][C]292874[/C][C]275276.974640534[/C][C]17597.025359466[/C][/ROW]
[ROW][C]12[/C][C]223814[/C][C]217807.977967283[/C][C]6006.02203271706[/C][/ROW]
[ROW][C]13[/C][C]156623[/C][C]160045.471038141[/C][C]-3422.47103814128[/C][/ROW]
[ROW][C]14[/C][C]327332[/C][C]259149.038652121[/C][C]68182.9613478794[/C][/ROW]
[ROW][C]15[/C][C]205898[/C][C]211767.495032388[/C][C]-5869.49503238769[/C][/ROW]
[ROW][C]16[/C][C]369527[/C][C]414892.19111881[/C][C]-45365.1911188099[/C][/ROW]
[ROW][C]17[/C][C]290571[/C][C]248797.665767437[/C][C]41773.334232563[/C][/ROW]
[ROW][C]18[/C][C]292903[/C][C]282016.981664442[/C][C]10886.0183355585[/C][/ROW]
[ROW][C]19[/C][C]168639[/C][C]171953.644381153[/C][C]-3314.64438115263[/C][/ROW]
[ROW][C]20[/C][C]253641[/C][C]242928.235658124[/C][C]10712.7643418763[/C][/ROW]
[ROW][C]21[/C][C]269240[/C][C]259978.166014911[/C][C]9261.83398508946[/C][/ROW]
[ROW][C]22[/C][C]414808[/C][C]302703.59462425[/C][C]112104.40537575[/C][/ROW]
[ROW][C]23[/C][C]161910[/C][C]157357.602350998[/C][C]4552.39764900163[/C][/ROW]
[ROW][C]24[/C][C]178722[/C][C]205667.180538686[/C][C]-26945.1805386855[/C][/ROW]
[ROW][C]25[/C][C]200181[/C][C]273815.575835952[/C][C]-73634.575835952[/C][/ROW]
[ROW][C]26[/C][C]203700[/C][C]248897.469743703[/C][C]-45197.4697437025[/C][/ROW]
[ROW][C]27[/C][C]267099[/C][C]308140.485377587[/C][C]-41041.4853775868[/C][/ROW]
[ROW][C]28[/C][C]262716[/C][C]236457.207820968[/C][C]26258.7921790321[/C][/ROW]
[ROW][C]29[/C][C]155915[/C][C]153807.528709503[/C][C]2107.47129049718[/C][/ROW]
[ROW][C]30[/C][C]324641[/C][C]349794.573573955[/C][C]-25153.5735739547[/C][/ROW]
[ROW][C]31[/C][C]261785[/C][C]285330.972752202[/C][C]-23545.9727522017[/C][/ROW]
[ROW][C]32[/C][C]192626[/C][C]214585.328859407[/C][C]-21959.3288594072[/C][/ROW]
[ROW][C]33[/C][C]318563[/C][C]301349.952055543[/C][C]17213.0479444566[/C][/ROW]
[ROW][C]34[/C][C]97615[/C][C]98617.0436589851[/C][C]-1002.04365898507[/C][/ROW]
[ROW][C]35[/C][C]343613[/C][C]324758.622760403[/C][C]18854.3772395972[/C][/ROW]
[ROW][C]36[/C][C]272026[/C][C]270325.689342425[/C][C]1700.31065757476[/C][/ROW]
[ROW][C]37[/C][C]408580[/C][C]348725.591646898[/C][C]59854.4083531023[/C][/ROW]
[ROW][C]38[/C][C]206904[/C][C]199828.158246386[/C][C]7075.84175361434[/C][/ROW]
[ROW][C]39[/C][C]115469[/C][C]92367.4263124772[/C][C]23101.5736875228[/C][/ROW]
[ROW][C]40[/C][C]310587[/C][C]315557.924982361[/C][C]-4970.92498236096[/C][/ROW]
[ROW][C]41[/C][C]315746[/C][C]318492.523132661[/C][C]-2746.52313266118[/C][/ROW]
[ROW][C]42[/C][C]157897[/C][C]172606.182267524[/C][C]-14709.1822675236[/C][/ROW]
[ROW][C]43[/C][C]192883[/C][C]203602.167420061[/C][C]-10719.1674200607[/C][/ROW]
[ROW][C]44[/C][C]165876[/C][C]147516.85713419[/C][C]18359.1428658101[/C][/ROW]
[ROW][C]45[/C][C]153778[/C][C]212006.013912097[/C][C]-58228.0139120973[/C][/ROW]
[ROW][C]46[/C][C]414493[/C][C]394375.038322207[/C][C]20117.9616777934[/C][/ROW]
[ROW][C]47[/C][C]78800[/C][C]102339.696209803[/C][C]-23539.6962098028[/C][/ROW]
[ROW][C]48[/C][C]207958[/C][C]231390.698511854[/C][C]-23432.6985118542[/C][/ROW]
[ROW][C]49[/C][C]323118[/C][C]374182.404662141[/C][C]-51064.4046621411[/C][/ROW]
[ROW][C]50[/C][C]175523[/C][C]229707.113931866[/C][C]-54184.1139318665[/C][/ROW]
[ROW][C]51[/C][C]213050[/C][C]239553.027230721[/C][C]-26503.0272307209[/C][/ROW]
[ROW][C]52[/C][C]24188[/C][C]39620.8948756191[/C][C]-15432.8948756191[/C][/ROW]
[ROW][C]53[/C][C]364968[/C][C]324064.955074062[/C][C]40903.0449259381[/C][/ROW]
[ROW][C]54[/C][C]65029[/C][C]64858.1356519971[/C][C]170.864348002872[/C][/ROW]
[ROW][C]55[/C][C]101097[/C][C]112561.982897417[/C][C]-11464.9828974175[/C][/ROW]
[ROW][C]56[/C][C]263096[/C][C]263336.488452994[/C][C]-240.488452994399[/C][/ROW]
[ROW][C]57[/C][C]302012[/C][C]297349.351818131[/C][C]4662.64818186923[/C][/ROW]
[ROW][C]58[/C][C]315753[/C][C]350384.447854534[/C][C]-34631.4478545344[/C][/ROW]
[ROW][C]59[/C][C]300531[/C][C]311251.200040333[/C][C]-10720.2000403332[/C][/ROW]
[ROW][C]60[/C][C]240445[/C][C]200701.83545765[/C][C]39743.16454235[/C][/ROW]
[ROW][C]61[/C][C]360325[/C][C]375829.996106295[/C][C]-15504.996106295[/C][/ROW]
[ROW][C]62[/C][C]296186[/C][C]339434.089965544[/C][C]-43248.0899655441[/C][/ROW]
[ROW][C]63[/C][C]210104[/C][C]247026.740864619[/C][C]-36922.7408646189[/C][/ROW]
[ROW][C]64[/C][C]247076[/C][C]242121.464047741[/C][C]4954.53595225905[/C][/ROW]
[ROW][C]65[/C][C]220722[/C][C]212975.448684863[/C][C]7746.55131513731[/C][/ROW]
[ROW][C]66[/C][C]216027[/C][C]206893.477705909[/C][C]9133.52229409097[/C][/ROW]
[ROW][C]67[/C][C]187773[/C][C]202976.86061458[/C][C]-15203.8606145804[/C][/ROW]
[ROW][C]68[/C][C]227055[/C][C]266413.082321605[/C][C]-39358.0823216046[/C][/ROW]
[ROW][C]69[/C][C]229181[/C][C]235158.621220613[/C][C]-5977.62122061281[/C][/ROW]
[ROW][C]70[/C][C]159082[/C][C]167772.789280839[/C][C]-8690.78928083945[/C][/ROW]
[ROW][C]71[/C][C]232624[/C][C]236702.49722573[/C][C]-4078.49722573017[/C][/ROW]
[ROW][C]72[/C][C]73566[/C][C]89204.950640307[/C][C]-15638.950640307[/C][/ROW]
[ROW][C]73[/C][C]231827[/C][C]226083.410650581[/C][C]5743.58934941909[/C][/ROW]
[ROW][C]74[/C][C]181728[/C][C]185150.426203957[/C][C]-3422.42620395713[/C][/ROW]
[ROW][C]75[/C][C]162366[/C][C]185085.184462785[/C][C]-22719.1844627854[/C][/ROW]
[ROW][C]76[/C][C]329583[/C][C]235714.990029055[/C][C]93868.0099709451[/C][/ROW]
[ROW][C]77[/C][C]303317[/C][C]282597.536542563[/C][C]20719.4634574366[/C][/ROW]
[ROW][C]78[/C][C]205630[/C][C]224786.813016346[/C][C]-19156.8130163459[/C][/ROW]
[ROW][C]79[/C][C]184970[/C][C]194986.956206468[/C][C]-10016.956206468[/C][/ROW]
[ROW][C]80[/C][C]168990[/C][C]169779.242707194[/C][C]-789.242707194012[/C][/ROW]
[ROW][C]81[/C][C]151231[/C][C]168884.128840266[/C][C]-17653.1288402665[/C][/ROW]
[ROW][C]82[/C][C]421615[/C][C]335281.105966359[/C][C]86333.8940336406[/C][/ROW]
[ROW][C]83[/C][C]145916[/C][C]159150.83516725[/C][C]-13234.8351672505[/C][/ROW]
[ROW][C]84[/C][C]270487[/C][C]216630.065407501[/C][C]53856.9345924991[/C][/ROW]
[ROW][C]85[/C][C]80953[/C][C]98110.9838745723[/C][C]-17157.9838745723[/C][/ROW]
[ROW][C]86[/C][C]139193[/C][C]152806.47296732[/C][C]-13613.4729673202[/C][/ROW]
[ROW][C]87[/C][C]146777[/C][C]145116.761670345[/C][C]1660.23832965464[/C][/ROW]
[ROW][C]88[/C][C]335969[/C][C]324011.985267172[/C][C]11957.0147328276[/C][/ROW]
[ROW][C]89[/C][C]297676[/C][C]291993.4834917[/C][C]5682.51650830007[/C][/ROW]
[ROW][C]90[/C][C]175232[/C][C]238657.484766018[/C][C]-63425.4847660178[/C][/ROW]
[ROW][C]91[/C][C]238938[/C][C]233205.848526108[/C][C]5732.15147389172[/C][/ROW]
[ROW][C]92[/C][C]228459[/C][C]203889.602834288[/C][C]24569.3971657116[/C][/ROW]
[ROW][C]93[/C][C]175244[/C][C]177961.296905602[/C][C]-2717.29690560216[/C][/ROW]
[ROW][C]94[/C][C]256299[/C][C]248041.855217045[/C][C]8257.14478295458[/C][/ROW]
[ROW][C]95[/C][C]288728[/C][C]250476.740331729[/C][C]38251.2596682707[/C][/ROW]
[ROW][C]96[/C][C]189252[/C][C]182878.434207625[/C][C]6373.56579237499[/C][/ROW]
[ROW][C]97[/C][C]222324[/C][C]212723.759082715[/C][C]9600.24091728477[/C][/ROW]
[ROW][C]98[/C][C]277755[/C][C]283372.066158838[/C][C]-5617.06615883809[/C][/ROW]
[ROW][C]99[/C][C]364710[/C][C]373650.797597412[/C][C]-8940.79759741169[/C][/ROW]
[ROW][C]100[/C][C]392346[/C][C]381343.508974267[/C][C]11002.4910257328[/C][/ROW]
[ROW][C]101[/C][C]260478[/C][C]236369.627517352[/C][C]24108.3724826484[/C][/ROW]
[ROW][C]102[/C][C]273240[/C][C]292519.183124378[/C][C]-19279.1831243781[/C][/ROW]
[ROW][C]103[/C][C]186310[/C][C]207244.533135076[/C][C]-20934.5331350758[/C][/ROW]
[ROW][C]104[/C][C]43287[/C][C]56594.3991511967[/C][C]-13307.3991511967[/C][/ROW]
[ROW][C]105[/C][C]185181[/C][C]193139.264202573[/C][C]-7958.26420257256[/C][/ROW]
[ROW][C]106[/C][C]202989[/C][C]244543.130102381[/C][C]-41554.1301023808[/C][/ROW]
[ROW][C]107[/C][C]259498[/C][C]275432.408640791[/C][C]-15934.4086407906[/C][/ROW]
[ROW][C]108[/C][C]295230[/C][C]274610.148782537[/C][C]20619.8512174629[/C][/ROW]
[ROW][C]109[/C][C]114156[/C][C]184203.274488053[/C][C]-70047.2744880526[/C][/ROW]
[ROW][C]110[/C][C]151624[/C][C]241822.493728637[/C][C]-90198.4937286373[/C][/ROW]
[ROW][C]111[/C][C]306941[/C][C]242699.188809493[/C][C]64241.8111905067[/C][/ROW]
[ROW][C]112[/C][C]289398[/C][C]227209.673570254[/C][C]62188.3264297458[/C][/ROW]
[ROW][C]113[/C][C]23623[/C][C]21740.1246030806[/C][C]1882.87539691942[/C][/ROW]
[ROW][C]114[/C][C]174970[/C][C]205477.836618746[/C][C]-30507.8366187459[/C][/ROW]
[ROW][C]115[/C][C]61857[/C][C]47204.2801835786[/C][C]14652.7198164214[/C][/ROW]
[ROW][C]116[/C][C]163766[/C][C]167909.626347595[/C][C]-4143.62634759516[/C][/ROW]
[ROW][C]117[/C][C]364027[/C][C]364611.556471798[/C][C]-584.556471797736[/C][/ROW]
[ROW][C]118[/C][C]21054[/C][C]21509.4903613145[/C][C]-455.490361314475[/C][/ROW]
[ROW][C]119[/C][C]252805[/C][C]231273.935835518[/C][C]21531.0641644816[/C][/ROW]
[ROW][C]120[/C][C]31929[/C][C]40616.5304065998[/C][C]-8687.53040659978[/C][/ROW]
[ROW][C]121[/C][C]294609[/C][C]323577.706359293[/C][C]-28968.706359293[/C][/ROW]
[ROW][C]122[/C][C]217893[/C][C]189031.587113559[/C][C]28861.412886441[/C][/ROW]
[ROW][C]123[/C][C]167612[/C][C]123572.46162659[/C][C]44039.5383734101[/C][/ROW]
[ROW][C]124[/C][C]149905[/C][C]164505.232101647[/C][C]-14600.2321016466[/C][/ROW]
[ROW][C]125[/C][C]38214[/C][C]53779.2677097674[/C][C]-15565.2677097674[/C][/ROW]
[ROW][C]126[/C][C]189451[/C][C]178950.953702827[/C][C]10500.0462971734[/C][/ROW]
[ROW][C]127[/C][C]339683[/C][C]295216.434947781[/C][C]44466.5650522193[/C][/ROW]
[ROW][C]128[/C][C]186627[/C][C]194421.632198882[/C][C]-7794.63219888224[/C][/ROW]
[ROW][C]129[/C][C]386918[/C][C]380197.174033442[/C][C]6720.82596655829[/C][/ROW]
[ROW][C]130[/C][C]302392[/C][C]339156.596757111[/C][C]-36764.5967571107[/C][/ROW]
[ROW][C]131[/C][C]384345[/C][C]375394.558266516[/C][C]8950.44173348386[/C][/ROW]
[ROW][C]132[/C][C]187992[/C][C]187324.990366399[/C][C]667.009633600899[/C][/ROW]
[ROW][C]133[/C][C]102424[/C][C]128482.882712169[/C][C]-26058.8827121687[/C][/ROW]
[ROW][C]134[/C][C]281117[/C][C]269431.6934579[/C][C]11685.3065421001[/C][/ROW]
[ROW][C]135[/C][C]399991[/C][C]395188.40948061[/C][C]4802.59051939017[/C][/ROW]
[ROW][C]136[/C][C]131692[/C][C]109336.046793587[/C][C]22355.9532064135[/C][/ROW]
[ROW][C]137[/C][C]371090[/C][C]362132.776604009[/C][C]8957.22339599135[/C][/ROW]
[ROW][C]138[/C][C]157429[/C][C]184803.110642969[/C][C]-27374.1106429689[/C][/ROW]
[ROW][C]139[/C][C]236370[/C][C]220158.15853887[/C][C]16211.8414611301[/C][/ROW]
[ROW][C]140[/C][C]227299[/C][C]242377.525883242[/C][C]-15078.5258832421[/C][/ROW]
[ROW][C]141[/C][C]209904[/C][C]185051.166146562[/C][C]24852.8338534384[/C][/ROW]
[ROW][C]142[/C][C]355457[/C][C]334265.255248464[/C][C]21191.7447515357[/C][/ROW]
[ROW][C]143[/C][C]230883[/C][C]239602.171514122[/C][C]-8719.17151412236[/C][/ROW]
[ROW][C]144[/C][C]173260[/C][C]124591.393201873[/C][C]48668.6067981265[/C][/ROW]
[ROW][C]145[/C][C]306577[/C][C]275556.645825916[/C][C]31020.3541740842[/C][/ROW]
[ROW][C]146[/C][C]141789[/C][C]185219.682804574[/C][C]-43430.6828045745[/C][/ROW]
[ROW][C]147[/C][C]210565[/C][C]241667.234693536[/C][C]-31102.234693536[/C][/ROW]
[ROW][C]148[/C][C]273544[/C][C]271381.994314452[/C][C]2162.00568554817[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]-4827.14318354742[/C][C]4828.14318354742[/C][/ROW]
[ROW][C]150[/C][C]14688[/C][C]12322.1604044747[/C][C]2365.83959552529[/C][/ROW]
[ROW][C]151[/C][C]98[/C][C]-4643.26372443248[/C][C]4741.26372443248[/C][/ROW]
[ROW][C]152[/C][C]455[/C][C]-4459.38426531755[/C][C]4914.38426531755[/C][/ROW]
[ROW][C]153[/C][C]0[/C][C]-4852.51917912824[/C][C]4852.51917912824[/C][/ROW]
[ROW][C]154[/C][C]0[/C][C]-4852.51917912824[/C][C]4852.51917912824[/C][/ROW]
[ROW][C]155[/C][C]216803[/C][C]203536.445644796[/C][C]13266.5543552044[/C][/ROW]
[ROW][C]156[/C][C]347930[/C][C]337616.038775129[/C][C]10313.9612248711[/C][/ROW]
[ROW][C]157[/C][C]0[/C][C]-4852.51917912824[/C][C]4852.51917912824[/C][/ROW]
[ROW][C]158[/C][C]203[/C][C]-4218.50532499176[/C][C]4421.50532499176[/C][/ROW]
[ROW][C]159[/C][C]7199[/C][C]8419.9136530843[/C][C]-1220.9136530843[/C][/ROW]
[ROW][C]160[/C][C]46660[/C][C]47878.4293857112[/C][C]-1218.42938571118[/C][/ROW]
[ROW][C]161[/C][C]17547[/C][C]10089.6260864864[/C][C]7457.37391351359[/C][/ROW]
[ROW][C]162[/C][C]112892[/C][C]90155.5991836271[/C][C]22736.4008163729[/C][/ROW]
[ROW][C]163[/C][C]969[/C][C]-4192.93631171897[/C][C]5161.93631171897[/C][/ROW]
[ROW][C]164[/C][C]189334[/C][C]150531.221855112[/C][C]38802.7781448884[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155012&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155012&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
1269966243148.25688420526817.7431157953
2146082166881.096417868-20799.0964178678
3214542204384.95582342510157.0441765754
4212452268541.79652582-56089.7965258202
5157206144420.36708293812785.6329170619
67084984139.409969-13290.409969
7476347472463.761264493883.23873550955
83318634827.4590744886-1641.45907448861
9201983205147.183531001-3164.18353100065
10211698192289.03792049619408.9620795041
11292874275276.97464053417597.025359466
12223814217807.9779672836006.02203271706
13156623160045.471038141-3422.47103814128
14327332259149.03865212168182.9613478794
15205898211767.495032388-5869.49503238769
16369527414892.19111881-45365.1911188099
17290571248797.66576743741773.334232563
18292903282016.98166444210886.0183355585
19168639171953.644381153-3314.64438115263
20253641242928.23565812410712.7643418763
21269240259978.1660149119261.83398508946
22414808302703.59462425112104.40537575
23161910157357.6023509984552.39764900163
24178722205667.180538686-26945.1805386855
25200181273815.575835952-73634.575835952
26203700248897.469743703-45197.4697437025
27267099308140.485377587-41041.4853775868
28262716236457.20782096826258.7921790321
29155915153807.5287095032107.47129049718
30324641349794.573573955-25153.5735739547
31261785285330.972752202-23545.9727522017
32192626214585.328859407-21959.3288594072
33318563301349.95205554317213.0479444566
349761598617.0436589851-1002.04365898507
35343613324758.62276040318854.3772395972
36272026270325.6893424251700.31065757476
37408580348725.59164689859854.4083531023
38206904199828.1582463867075.84175361434
3911546992367.426312477223101.5736875228
40310587315557.924982361-4970.92498236096
41315746318492.523132661-2746.52313266118
42157897172606.182267524-14709.1822675236
43192883203602.167420061-10719.1674200607
44165876147516.8571341918359.1428658101
45153778212006.013912097-58228.0139120973
46414493394375.03832220720117.9616777934
4778800102339.696209803-23539.6962098028
48207958231390.698511854-23432.6985118542
49323118374182.404662141-51064.4046621411
50175523229707.113931866-54184.1139318665
51213050239553.027230721-26503.0272307209
522418839620.8948756191-15432.8948756191
53364968324064.95507406240903.0449259381
546502964858.1356519971170.864348002872
55101097112561.982897417-11464.9828974175
56263096263336.488452994-240.488452994399
57302012297349.3518181314662.64818186923
58315753350384.447854534-34631.4478545344
59300531311251.200040333-10720.2000403332
60240445200701.8354576539743.16454235
61360325375829.996106295-15504.996106295
62296186339434.089965544-43248.0899655441
63210104247026.740864619-36922.7408646189
64247076242121.4640477414954.53595225905
65220722212975.4486848637746.55131513731
66216027206893.4777059099133.52229409097
67187773202976.86061458-15203.8606145804
68227055266413.082321605-39358.0823216046
69229181235158.621220613-5977.62122061281
70159082167772.789280839-8690.78928083945
71232624236702.49722573-4078.49722573017
727356689204.950640307-15638.950640307
73231827226083.4106505815743.58934941909
74181728185150.426203957-3422.42620395713
75162366185085.184462785-22719.1844627854
76329583235714.99002905593868.0099709451
77303317282597.53654256320719.4634574366
78205630224786.813016346-19156.8130163459
79184970194986.956206468-10016.956206468
80168990169779.242707194-789.242707194012
81151231168884.128840266-17653.1288402665
82421615335281.10596635986333.8940336406
83145916159150.83516725-13234.8351672505
84270487216630.06540750153856.9345924991
858095398110.9838745723-17157.9838745723
86139193152806.47296732-13613.4729673202
87146777145116.7616703451660.23832965464
88335969324011.98526717211957.0147328276
89297676291993.48349175682.51650830007
90175232238657.484766018-63425.4847660178
91238938233205.8485261085732.15147389172
92228459203889.60283428824569.3971657116
93175244177961.296905602-2717.29690560216
94256299248041.8552170458257.14478295458
95288728250476.74033172938251.2596682707
96189252182878.4342076256373.56579237499
97222324212723.7590827159600.24091728477
98277755283372.066158838-5617.06615883809
99364710373650.797597412-8940.79759741169
100392346381343.50897426711002.4910257328
101260478236369.62751735224108.3724826484
102273240292519.183124378-19279.1831243781
103186310207244.533135076-20934.5331350758
1044328756594.3991511967-13307.3991511967
105185181193139.264202573-7958.26420257256
106202989244543.130102381-41554.1301023808
107259498275432.408640791-15934.4086407906
108295230274610.14878253720619.8512174629
109114156184203.274488053-70047.2744880526
110151624241822.493728637-90198.4937286373
111306941242699.18880949364241.8111905067
112289398227209.67357025462188.3264297458
1132362321740.12460308061882.87539691942
114174970205477.836618746-30507.8366187459
1156185747204.280183578614652.7198164214
116163766167909.626347595-4143.62634759516
117364027364611.556471798-584.556471797736
1182105421509.4903613145-455.490361314475
119252805231273.93583551821531.0641644816
1203192940616.5304065998-8687.53040659978
121294609323577.706359293-28968.706359293
122217893189031.58711355928861.412886441
123167612123572.4616265944039.5383734101
124149905164505.232101647-14600.2321016466
1253821453779.2677097674-15565.2677097674
126189451178950.95370282710500.0462971734
127339683295216.43494778144466.5650522193
128186627194421.632198882-7794.63219888224
129386918380197.1740334426720.82596655829
130302392339156.596757111-36764.5967571107
131384345375394.5582665168950.44173348386
132187992187324.990366399667.009633600899
133102424128482.882712169-26058.8827121687
134281117269431.693457911685.3065421001
135399991395188.409480614802.59051939017
136131692109336.04679358722355.9532064135
137371090362132.7766040098957.22339599135
138157429184803.110642969-27374.1106429689
139236370220158.1585388716211.8414611301
140227299242377.525883242-15078.5258832421
141209904185051.16614656224852.8338534384
142355457334265.25524846421191.7447515357
143230883239602.171514122-8719.17151412236
144173260124591.39320187348668.6067981265
145306577275556.64582591631020.3541740842
146141789185219.682804574-43430.6828045745
147210565241667.234693536-31102.234693536
148273544271381.9943144522162.00568554817
1491-4827.143183547424828.14318354742
1501468812322.16040447472365.83959552529
15198-4643.263724432484741.26372443248
152455-4459.384265317554914.38426531755
1530-4852.519179128244852.51917912824
1540-4852.519179128244852.51917912824
155216803203536.44564479613266.5543552044
156347930337616.03877512910313.9612248711
1570-4852.519179128244852.51917912824
158203-4218.505324991764421.50532499176
15971998419.9136530843-1220.9136530843
1604666047878.4293857112-1218.42938571118
1611754710089.62608648647457.37391351359
16211289290155.599183627122736.4008163729
163969-4192.936311718975161.93631171897
164189334150531.22185511238802.7781448884






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
160.5884017607248520.8231964785502960.411598239275148
170.4592567987453840.9185135974907680.540743201254616
180.5720650429907160.8558699140185670.427934957009284
190.4486145644755520.8972291289511050.551385435524448
200.335334918542380.670669837084760.66466508145762
210.2438938499706170.4877876999412330.756106150029383
220.878680216394930.2426395672101410.12131978360507
230.8260464574630810.3479070850738390.173953542536919
240.7794349221288290.4411301557423430.220565077871171
250.830647457653570.338705084692860.16935254234643
260.7975051156726140.4049897686547720.202494884327386
270.7807310117308470.4385379765383050.219268988269153
280.7705212883381730.4589574233236540.229478711661827
290.7156434626792480.5687130746415030.284356537320751
300.7554090294875570.4891819410248860.244590970512443
310.727299487612920.545401024774160.27270051238708
320.7460793132655150.5078413734689690.253920686734485
330.6985293611299470.6029412777401070.301470638870053
340.6451387625200840.7097224749598310.354861237479916
350.7046779355581370.5906441288837270.295322064441863
360.661320512698030.677358974603940.33867948730197
370.7490270904748970.5019458190502070.250972909525103
380.71376378241340.5724724351731990.2862362175866
390.6679681125442290.6640637749115420.332031887455771
400.613580026464270.7728399470714610.38641997353573
410.6422097343127240.7155805313745520.357790265687276
420.606259082313440.7874818353731210.39374091768656
430.5816009638999110.8367980722001780.418399036100089
440.6013327626961450.7973344746077110.398667237303855
450.8572331735861490.2855336528277010.142766826413851
460.8978578774107430.2042842451785150.102142122589257
470.888242192224790.223515615550420.11175780777521
480.8995166833702840.2009666332594320.100483316629716
490.9530045395526860.09399092089462870.0469954604473144
500.973260972090150.05347805581970060.0267390279098503
510.971781527553980.05643694489203960.0282184724460198
520.9675527743601010.06489445127979740.0324472256398987
530.9672385276551320.0655229446897360.032761472344868
540.9566837624535970.08663247509280670.0433162375464033
550.9472717647353220.1054564705293560.0527282352646782
560.9340291653198390.1319416693603230.0659708346801613
570.9166936866483950.1666126267032090.0833063133516045
580.9280814846748610.1438370306502770.0719185153251387
590.9119261587310650.176147682537870.088073841268935
600.9308750668192490.1382498663615020.0691249331807509
610.9174071316034870.1651857367930260.0825928683965131
620.9258880352992010.1482239294015990.0741119647007993
630.9317902664571630.1364194670856740.0682097335428369
640.9161666131311610.1676667737376780.083833386868839
650.8963434472443090.2073131055113810.103656552755691
660.8757981333720380.2484037332559230.124201866627962
670.8525423279328150.2949153441343710.147457672067185
680.8640059143724730.2719881712550550.135994085627527
690.8354856951929310.3290286096141370.164514304807068
700.80629522592010.38740954815980.1937047740799
710.7733395216153960.4533209567692080.226660478384604
720.7448871783739110.5102256432521770.255112821626088
730.707453827825380.585092344349240.29254617217462
740.6682814858487540.6634370283024920.331718514151246
750.6380118563936780.7239762872126450.361988143606323
760.911760281930540.1764794361389190.0882397180694597
770.9037089716232850.192582056753430.096291028376715
780.8910997292386230.2178005415227540.108900270761377
790.8689269903926390.2621460192147210.131073009607361
800.8419890543248180.3160218913503640.158010945675182
810.8231241656943320.3537516686113350.176875834305668
820.968544026391130.06291194721773990.03145597360887
830.9615347087154510.07693058256909730.0384652912845487
840.9672546644740270.06549067105194660.0327453355259733
850.9598835656630010.08023286867399730.0401164343369987
860.9503600918148980.09927981637020460.0496399081851023
870.9367259866748530.1265480266502950.0632740133251474
880.9280232745957850.143953450808430.071976725404215
890.9113541225196490.1772917549607020.0886458774803511
900.9727321233598770.05453575328024590.027267876640123
910.9642158829640580.07156823407188310.0357841170359416
920.9608663411751920.07826731764961630.0391336588248081
930.949157723954780.101684552090440.0508422760452202
940.9356414724989210.1287170550021580.0643585275010792
950.9570041699929020.08599166001419520.0429958300070976
960.9473492094124050.1053015811751910.0526507905875954
970.9355819048841560.1288361902316880.0644180951158439
980.9209290689940330.1581418620119340.0790709310059672
990.9107558001744450.1784883996511090.0892441998255546
1000.893211574457390.2135768510852190.10678842554261
1010.877160536423940.245678927152120.12283946357606
1020.8581303737587660.2837392524824670.141869626241234
1030.8398056031260910.3203887937478190.160194396873909
1040.8093587987659730.3812824024680530.190641201234027
1050.7788250109010760.4423499781978480.221174989098924
1060.8367180799061340.3265638401877320.163281920093866
1070.8160562278464460.3678875443071080.183943772153554
1080.7836964041647610.4326071916704790.216303595835239
1090.9170254497683890.1659491004632220.0829745502316108
1100.9994551375056110.001089724988778840.000544862494389418
1110.9998207440694390.0003585118611217970.000179255930560898
1120.9999534887191889.30225616241531e-054.65112808120765e-05
1130.9999163094827060.0001673810345881288.36905172940638e-05
1140.9999583246213728.33507572550776e-054.16753786275388e-05
1150.9999416666096770.0001166667806458795.83333903229393e-05
1160.9998932506132460.0002134987735081020.000106749386754051
1170.9998705108554170.0002589782891667720.000129489144583386
1180.9997821720821820.0004356558356351080.000217827917817554
1190.999837453967590.0003250920648200870.000162546032410044
1200.999705878641590.0005882427168208770.000294121358410439
1210.9999583421554968.33156890081439e-054.16578445040719e-05
1220.9999317813734650.0001364372530691646.82186265345822e-05
1230.9999842446358033.15107283948708e-051.57553641974354e-05
1240.9999673005983076.53988033858123e-053.26994016929062e-05
1250.9999348809757130.0001302380485736276.51190242868136e-05
1260.9998894248423870.0002211503152255530.000110575157612777
1270.9999749978427645.00043144711734e-052.50021572355867e-05
1280.9999445486506040.0001109026987927375.54513493963683e-05
1290.9999555612078198.88775843628287e-054.44387921814144e-05
1300.9999166539995840.0001666920008317318.33460004158656e-05
1310.9998340936459650.0003318127080693550.000165906354034678
1320.9998495003678540.0003009992642926230.000150499632146311
1330.9997993886638880.0004012226722244860.000200611336112243
1340.9996474264192060.0007051471615880060.000352573580794003
1350.9998425318894090.0003149362211815950.000157468110590798
1360.9996451345712930.0007097308574143390.00035486542870717
1370.9999972658211685.46835766349262e-062.73417883174631e-06
1380.999993459382521.30812349589905e-056.54061747949524e-06
1390.999999687695796.24608419170216e-073.12304209585108e-07
1400.9999990615761021.87684779553758e-069.38423897768788e-07
1410.9999999413334321.17333136674868e-075.8666568337434e-08
1420.9999997710227184.57954564946809e-072.28977282473405e-07
1430.999999999692256.15500648214938e-103.07750324107469e-10
1440.9999999999936881.26239861491385e-116.31199307456923e-12
1450.9999999999552178.95667492935264e-114.47833746467632e-11
1460.9999999999996866.285910476511e-133.1429552382555e-13
1470.9999999998707912.58417436284558e-101.29208718142279e-10
1480.9999999512457449.75085127215963e-084.87542563607981e-08

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
16 & 0.588401760724852 & 0.823196478550296 & 0.411598239275148 \tabularnewline
17 & 0.459256798745384 & 0.918513597490768 & 0.540743201254616 \tabularnewline
18 & 0.572065042990716 & 0.855869914018567 & 0.427934957009284 \tabularnewline
19 & 0.448614564475552 & 0.897229128951105 & 0.551385435524448 \tabularnewline
20 & 0.33533491854238 & 0.67066983708476 & 0.66466508145762 \tabularnewline
21 & 0.243893849970617 & 0.487787699941233 & 0.756106150029383 \tabularnewline
22 & 0.87868021639493 & 0.242639567210141 & 0.12131978360507 \tabularnewline
23 & 0.826046457463081 & 0.347907085073839 & 0.173953542536919 \tabularnewline
24 & 0.779434922128829 & 0.441130155742343 & 0.220565077871171 \tabularnewline
25 & 0.83064745765357 & 0.33870508469286 & 0.16935254234643 \tabularnewline
26 & 0.797505115672614 & 0.404989768654772 & 0.202494884327386 \tabularnewline
27 & 0.780731011730847 & 0.438537976538305 & 0.219268988269153 \tabularnewline
28 & 0.770521288338173 & 0.458957423323654 & 0.229478711661827 \tabularnewline
29 & 0.715643462679248 & 0.568713074641503 & 0.284356537320751 \tabularnewline
30 & 0.755409029487557 & 0.489181941024886 & 0.244590970512443 \tabularnewline
31 & 0.72729948761292 & 0.54540102477416 & 0.27270051238708 \tabularnewline
32 & 0.746079313265515 & 0.507841373468969 & 0.253920686734485 \tabularnewline
33 & 0.698529361129947 & 0.602941277740107 & 0.301470638870053 \tabularnewline
34 & 0.645138762520084 & 0.709722474959831 & 0.354861237479916 \tabularnewline
35 & 0.704677935558137 & 0.590644128883727 & 0.295322064441863 \tabularnewline
36 & 0.66132051269803 & 0.67735897460394 & 0.33867948730197 \tabularnewline
37 & 0.749027090474897 & 0.501945819050207 & 0.250972909525103 \tabularnewline
38 & 0.7137637824134 & 0.572472435173199 & 0.2862362175866 \tabularnewline
39 & 0.667968112544229 & 0.664063774911542 & 0.332031887455771 \tabularnewline
40 & 0.61358002646427 & 0.772839947071461 & 0.38641997353573 \tabularnewline
41 & 0.642209734312724 & 0.715580531374552 & 0.357790265687276 \tabularnewline
42 & 0.60625908231344 & 0.787481835373121 & 0.39374091768656 \tabularnewline
43 & 0.581600963899911 & 0.836798072200178 & 0.418399036100089 \tabularnewline
44 & 0.601332762696145 & 0.797334474607711 & 0.398667237303855 \tabularnewline
45 & 0.857233173586149 & 0.285533652827701 & 0.142766826413851 \tabularnewline
46 & 0.897857877410743 & 0.204284245178515 & 0.102142122589257 \tabularnewline
47 & 0.88824219222479 & 0.22351561555042 & 0.11175780777521 \tabularnewline
48 & 0.899516683370284 & 0.200966633259432 & 0.100483316629716 \tabularnewline
49 & 0.953004539552686 & 0.0939909208946287 & 0.0469954604473144 \tabularnewline
50 & 0.97326097209015 & 0.0534780558197006 & 0.0267390279098503 \tabularnewline
51 & 0.97178152755398 & 0.0564369448920396 & 0.0282184724460198 \tabularnewline
52 & 0.967552774360101 & 0.0648944512797974 & 0.0324472256398987 \tabularnewline
53 & 0.967238527655132 & 0.065522944689736 & 0.032761472344868 \tabularnewline
54 & 0.956683762453597 & 0.0866324750928067 & 0.0433162375464033 \tabularnewline
55 & 0.947271764735322 & 0.105456470529356 & 0.0527282352646782 \tabularnewline
56 & 0.934029165319839 & 0.131941669360323 & 0.0659708346801613 \tabularnewline
57 & 0.916693686648395 & 0.166612626703209 & 0.0833063133516045 \tabularnewline
58 & 0.928081484674861 & 0.143837030650277 & 0.0719185153251387 \tabularnewline
59 & 0.911926158731065 & 0.17614768253787 & 0.088073841268935 \tabularnewline
60 & 0.930875066819249 & 0.138249866361502 & 0.0691249331807509 \tabularnewline
61 & 0.917407131603487 & 0.165185736793026 & 0.0825928683965131 \tabularnewline
62 & 0.925888035299201 & 0.148223929401599 & 0.0741119647007993 \tabularnewline
63 & 0.931790266457163 & 0.136419467085674 & 0.0682097335428369 \tabularnewline
64 & 0.916166613131161 & 0.167666773737678 & 0.083833386868839 \tabularnewline
65 & 0.896343447244309 & 0.207313105511381 & 0.103656552755691 \tabularnewline
66 & 0.875798133372038 & 0.248403733255923 & 0.124201866627962 \tabularnewline
67 & 0.852542327932815 & 0.294915344134371 & 0.147457672067185 \tabularnewline
68 & 0.864005914372473 & 0.271988171255055 & 0.135994085627527 \tabularnewline
69 & 0.835485695192931 & 0.329028609614137 & 0.164514304807068 \tabularnewline
70 & 0.8062952259201 & 0.3874095481598 & 0.1937047740799 \tabularnewline
71 & 0.773339521615396 & 0.453320956769208 & 0.226660478384604 \tabularnewline
72 & 0.744887178373911 & 0.510225643252177 & 0.255112821626088 \tabularnewline
73 & 0.70745382782538 & 0.58509234434924 & 0.29254617217462 \tabularnewline
74 & 0.668281485848754 & 0.663437028302492 & 0.331718514151246 \tabularnewline
75 & 0.638011856393678 & 0.723976287212645 & 0.361988143606323 \tabularnewline
76 & 0.91176028193054 & 0.176479436138919 & 0.0882397180694597 \tabularnewline
77 & 0.903708971623285 & 0.19258205675343 & 0.096291028376715 \tabularnewline
78 & 0.891099729238623 & 0.217800541522754 & 0.108900270761377 \tabularnewline
79 & 0.868926990392639 & 0.262146019214721 & 0.131073009607361 \tabularnewline
80 & 0.841989054324818 & 0.316021891350364 & 0.158010945675182 \tabularnewline
81 & 0.823124165694332 & 0.353751668611335 & 0.176875834305668 \tabularnewline
82 & 0.96854402639113 & 0.0629119472177399 & 0.03145597360887 \tabularnewline
83 & 0.961534708715451 & 0.0769305825690973 & 0.0384652912845487 \tabularnewline
84 & 0.967254664474027 & 0.0654906710519466 & 0.0327453355259733 \tabularnewline
85 & 0.959883565663001 & 0.0802328686739973 & 0.0401164343369987 \tabularnewline
86 & 0.950360091814898 & 0.0992798163702046 & 0.0496399081851023 \tabularnewline
87 & 0.936725986674853 & 0.126548026650295 & 0.0632740133251474 \tabularnewline
88 & 0.928023274595785 & 0.14395345080843 & 0.071976725404215 \tabularnewline
89 & 0.911354122519649 & 0.177291754960702 & 0.0886458774803511 \tabularnewline
90 & 0.972732123359877 & 0.0545357532802459 & 0.027267876640123 \tabularnewline
91 & 0.964215882964058 & 0.0715682340718831 & 0.0357841170359416 \tabularnewline
92 & 0.960866341175192 & 0.0782673176496163 & 0.0391336588248081 \tabularnewline
93 & 0.94915772395478 & 0.10168455209044 & 0.0508422760452202 \tabularnewline
94 & 0.935641472498921 & 0.128717055002158 & 0.0643585275010792 \tabularnewline
95 & 0.957004169992902 & 0.0859916600141952 & 0.0429958300070976 \tabularnewline
96 & 0.947349209412405 & 0.105301581175191 & 0.0526507905875954 \tabularnewline
97 & 0.935581904884156 & 0.128836190231688 & 0.0644180951158439 \tabularnewline
98 & 0.920929068994033 & 0.158141862011934 & 0.0790709310059672 \tabularnewline
99 & 0.910755800174445 & 0.178488399651109 & 0.0892441998255546 \tabularnewline
100 & 0.89321157445739 & 0.213576851085219 & 0.10678842554261 \tabularnewline
101 & 0.87716053642394 & 0.24567892715212 & 0.12283946357606 \tabularnewline
102 & 0.858130373758766 & 0.283739252482467 & 0.141869626241234 \tabularnewline
103 & 0.839805603126091 & 0.320388793747819 & 0.160194396873909 \tabularnewline
104 & 0.809358798765973 & 0.381282402468053 & 0.190641201234027 \tabularnewline
105 & 0.778825010901076 & 0.442349978197848 & 0.221174989098924 \tabularnewline
106 & 0.836718079906134 & 0.326563840187732 & 0.163281920093866 \tabularnewline
107 & 0.816056227846446 & 0.367887544307108 & 0.183943772153554 \tabularnewline
108 & 0.783696404164761 & 0.432607191670479 & 0.216303595835239 \tabularnewline
109 & 0.917025449768389 & 0.165949100463222 & 0.0829745502316108 \tabularnewline
110 & 0.999455137505611 & 0.00108972498877884 & 0.000544862494389418 \tabularnewline
111 & 0.999820744069439 & 0.000358511861121797 & 0.000179255930560898 \tabularnewline
112 & 0.999953488719188 & 9.30225616241531e-05 & 4.65112808120765e-05 \tabularnewline
113 & 0.999916309482706 & 0.000167381034588128 & 8.36905172940638e-05 \tabularnewline
114 & 0.999958324621372 & 8.33507572550776e-05 & 4.16753786275388e-05 \tabularnewline
115 & 0.999941666609677 & 0.000116666780645879 & 5.83333903229393e-05 \tabularnewline
116 & 0.999893250613246 & 0.000213498773508102 & 0.000106749386754051 \tabularnewline
117 & 0.999870510855417 & 0.000258978289166772 & 0.000129489144583386 \tabularnewline
118 & 0.999782172082182 & 0.000435655835635108 & 0.000217827917817554 \tabularnewline
119 & 0.99983745396759 & 0.000325092064820087 & 0.000162546032410044 \tabularnewline
120 & 0.99970587864159 & 0.000588242716820877 & 0.000294121358410439 \tabularnewline
121 & 0.999958342155496 & 8.33156890081439e-05 & 4.16578445040719e-05 \tabularnewline
122 & 0.999931781373465 & 0.000136437253069164 & 6.82186265345822e-05 \tabularnewline
123 & 0.999984244635803 & 3.15107283948708e-05 & 1.57553641974354e-05 \tabularnewline
124 & 0.999967300598307 & 6.53988033858123e-05 & 3.26994016929062e-05 \tabularnewline
125 & 0.999934880975713 & 0.000130238048573627 & 6.51190242868136e-05 \tabularnewline
126 & 0.999889424842387 & 0.000221150315225553 & 0.000110575157612777 \tabularnewline
127 & 0.999974997842764 & 5.00043144711734e-05 & 2.50021572355867e-05 \tabularnewline
128 & 0.999944548650604 & 0.000110902698792737 & 5.54513493963683e-05 \tabularnewline
129 & 0.999955561207819 & 8.88775843628287e-05 & 4.44387921814144e-05 \tabularnewline
130 & 0.999916653999584 & 0.000166692000831731 & 8.33460004158656e-05 \tabularnewline
131 & 0.999834093645965 & 0.000331812708069355 & 0.000165906354034678 \tabularnewline
132 & 0.999849500367854 & 0.000300999264292623 & 0.000150499632146311 \tabularnewline
133 & 0.999799388663888 & 0.000401222672224486 & 0.000200611336112243 \tabularnewline
134 & 0.999647426419206 & 0.000705147161588006 & 0.000352573580794003 \tabularnewline
135 & 0.999842531889409 & 0.000314936221181595 & 0.000157468110590798 \tabularnewline
136 & 0.999645134571293 & 0.000709730857414339 & 0.00035486542870717 \tabularnewline
137 & 0.999997265821168 & 5.46835766349262e-06 & 2.73417883174631e-06 \tabularnewline
138 & 0.99999345938252 & 1.30812349589905e-05 & 6.54061747949524e-06 \tabularnewline
139 & 0.99999968769579 & 6.24608419170216e-07 & 3.12304209585108e-07 \tabularnewline
140 & 0.999999061576102 & 1.87684779553758e-06 & 9.38423897768788e-07 \tabularnewline
141 & 0.999999941333432 & 1.17333136674868e-07 & 5.8666568337434e-08 \tabularnewline
142 & 0.999999771022718 & 4.57954564946809e-07 & 2.28977282473405e-07 \tabularnewline
143 & 0.99999999969225 & 6.15500648214938e-10 & 3.07750324107469e-10 \tabularnewline
144 & 0.999999999993688 & 1.26239861491385e-11 & 6.31199307456923e-12 \tabularnewline
145 & 0.999999999955217 & 8.95667492935264e-11 & 4.47833746467632e-11 \tabularnewline
146 & 0.999999999999686 & 6.285910476511e-13 & 3.1429552382555e-13 \tabularnewline
147 & 0.999999999870791 & 2.58417436284558e-10 & 1.29208718142279e-10 \tabularnewline
148 & 0.999999951245744 & 9.75085127215963e-08 & 4.87542563607981e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155012&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]16[/C][C]0.588401760724852[/C][C]0.823196478550296[/C][C]0.411598239275148[/C][/ROW]
[ROW][C]17[/C][C]0.459256798745384[/C][C]0.918513597490768[/C][C]0.540743201254616[/C][/ROW]
[ROW][C]18[/C][C]0.572065042990716[/C][C]0.855869914018567[/C][C]0.427934957009284[/C][/ROW]
[ROW][C]19[/C][C]0.448614564475552[/C][C]0.897229128951105[/C][C]0.551385435524448[/C][/ROW]
[ROW][C]20[/C][C]0.33533491854238[/C][C]0.67066983708476[/C][C]0.66466508145762[/C][/ROW]
[ROW][C]21[/C][C]0.243893849970617[/C][C]0.487787699941233[/C][C]0.756106150029383[/C][/ROW]
[ROW][C]22[/C][C]0.87868021639493[/C][C]0.242639567210141[/C][C]0.12131978360507[/C][/ROW]
[ROW][C]23[/C][C]0.826046457463081[/C][C]0.347907085073839[/C][C]0.173953542536919[/C][/ROW]
[ROW][C]24[/C][C]0.779434922128829[/C][C]0.441130155742343[/C][C]0.220565077871171[/C][/ROW]
[ROW][C]25[/C][C]0.83064745765357[/C][C]0.33870508469286[/C][C]0.16935254234643[/C][/ROW]
[ROW][C]26[/C][C]0.797505115672614[/C][C]0.404989768654772[/C][C]0.202494884327386[/C][/ROW]
[ROW][C]27[/C][C]0.780731011730847[/C][C]0.438537976538305[/C][C]0.219268988269153[/C][/ROW]
[ROW][C]28[/C][C]0.770521288338173[/C][C]0.458957423323654[/C][C]0.229478711661827[/C][/ROW]
[ROW][C]29[/C][C]0.715643462679248[/C][C]0.568713074641503[/C][C]0.284356537320751[/C][/ROW]
[ROW][C]30[/C][C]0.755409029487557[/C][C]0.489181941024886[/C][C]0.244590970512443[/C][/ROW]
[ROW][C]31[/C][C]0.72729948761292[/C][C]0.54540102477416[/C][C]0.27270051238708[/C][/ROW]
[ROW][C]32[/C][C]0.746079313265515[/C][C]0.507841373468969[/C][C]0.253920686734485[/C][/ROW]
[ROW][C]33[/C][C]0.698529361129947[/C][C]0.602941277740107[/C][C]0.301470638870053[/C][/ROW]
[ROW][C]34[/C][C]0.645138762520084[/C][C]0.709722474959831[/C][C]0.354861237479916[/C][/ROW]
[ROW][C]35[/C][C]0.704677935558137[/C][C]0.590644128883727[/C][C]0.295322064441863[/C][/ROW]
[ROW][C]36[/C][C]0.66132051269803[/C][C]0.67735897460394[/C][C]0.33867948730197[/C][/ROW]
[ROW][C]37[/C][C]0.749027090474897[/C][C]0.501945819050207[/C][C]0.250972909525103[/C][/ROW]
[ROW][C]38[/C][C]0.7137637824134[/C][C]0.572472435173199[/C][C]0.2862362175866[/C][/ROW]
[ROW][C]39[/C][C]0.667968112544229[/C][C]0.664063774911542[/C][C]0.332031887455771[/C][/ROW]
[ROW][C]40[/C][C]0.61358002646427[/C][C]0.772839947071461[/C][C]0.38641997353573[/C][/ROW]
[ROW][C]41[/C][C]0.642209734312724[/C][C]0.715580531374552[/C][C]0.357790265687276[/C][/ROW]
[ROW][C]42[/C][C]0.60625908231344[/C][C]0.787481835373121[/C][C]0.39374091768656[/C][/ROW]
[ROW][C]43[/C][C]0.581600963899911[/C][C]0.836798072200178[/C][C]0.418399036100089[/C][/ROW]
[ROW][C]44[/C][C]0.601332762696145[/C][C]0.797334474607711[/C][C]0.398667237303855[/C][/ROW]
[ROW][C]45[/C][C]0.857233173586149[/C][C]0.285533652827701[/C][C]0.142766826413851[/C][/ROW]
[ROW][C]46[/C][C]0.897857877410743[/C][C]0.204284245178515[/C][C]0.102142122589257[/C][/ROW]
[ROW][C]47[/C][C]0.88824219222479[/C][C]0.22351561555042[/C][C]0.11175780777521[/C][/ROW]
[ROW][C]48[/C][C]0.899516683370284[/C][C]0.200966633259432[/C][C]0.100483316629716[/C][/ROW]
[ROW][C]49[/C][C]0.953004539552686[/C][C]0.0939909208946287[/C][C]0.0469954604473144[/C][/ROW]
[ROW][C]50[/C][C]0.97326097209015[/C][C]0.0534780558197006[/C][C]0.0267390279098503[/C][/ROW]
[ROW][C]51[/C][C]0.97178152755398[/C][C]0.0564369448920396[/C][C]0.0282184724460198[/C][/ROW]
[ROW][C]52[/C][C]0.967552774360101[/C][C]0.0648944512797974[/C][C]0.0324472256398987[/C][/ROW]
[ROW][C]53[/C][C]0.967238527655132[/C][C]0.065522944689736[/C][C]0.032761472344868[/C][/ROW]
[ROW][C]54[/C][C]0.956683762453597[/C][C]0.0866324750928067[/C][C]0.0433162375464033[/C][/ROW]
[ROW][C]55[/C][C]0.947271764735322[/C][C]0.105456470529356[/C][C]0.0527282352646782[/C][/ROW]
[ROW][C]56[/C][C]0.934029165319839[/C][C]0.131941669360323[/C][C]0.0659708346801613[/C][/ROW]
[ROW][C]57[/C][C]0.916693686648395[/C][C]0.166612626703209[/C][C]0.0833063133516045[/C][/ROW]
[ROW][C]58[/C][C]0.928081484674861[/C][C]0.143837030650277[/C][C]0.0719185153251387[/C][/ROW]
[ROW][C]59[/C][C]0.911926158731065[/C][C]0.17614768253787[/C][C]0.088073841268935[/C][/ROW]
[ROW][C]60[/C][C]0.930875066819249[/C][C]0.138249866361502[/C][C]0.0691249331807509[/C][/ROW]
[ROW][C]61[/C][C]0.917407131603487[/C][C]0.165185736793026[/C][C]0.0825928683965131[/C][/ROW]
[ROW][C]62[/C][C]0.925888035299201[/C][C]0.148223929401599[/C][C]0.0741119647007993[/C][/ROW]
[ROW][C]63[/C][C]0.931790266457163[/C][C]0.136419467085674[/C][C]0.0682097335428369[/C][/ROW]
[ROW][C]64[/C][C]0.916166613131161[/C][C]0.167666773737678[/C][C]0.083833386868839[/C][/ROW]
[ROW][C]65[/C][C]0.896343447244309[/C][C]0.207313105511381[/C][C]0.103656552755691[/C][/ROW]
[ROW][C]66[/C][C]0.875798133372038[/C][C]0.248403733255923[/C][C]0.124201866627962[/C][/ROW]
[ROW][C]67[/C][C]0.852542327932815[/C][C]0.294915344134371[/C][C]0.147457672067185[/C][/ROW]
[ROW][C]68[/C][C]0.864005914372473[/C][C]0.271988171255055[/C][C]0.135994085627527[/C][/ROW]
[ROW][C]69[/C][C]0.835485695192931[/C][C]0.329028609614137[/C][C]0.164514304807068[/C][/ROW]
[ROW][C]70[/C][C]0.8062952259201[/C][C]0.3874095481598[/C][C]0.1937047740799[/C][/ROW]
[ROW][C]71[/C][C]0.773339521615396[/C][C]0.453320956769208[/C][C]0.226660478384604[/C][/ROW]
[ROW][C]72[/C][C]0.744887178373911[/C][C]0.510225643252177[/C][C]0.255112821626088[/C][/ROW]
[ROW][C]73[/C][C]0.70745382782538[/C][C]0.58509234434924[/C][C]0.29254617217462[/C][/ROW]
[ROW][C]74[/C][C]0.668281485848754[/C][C]0.663437028302492[/C][C]0.331718514151246[/C][/ROW]
[ROW][C]75[/C][C]0.638011856393678[/C][C]0.723976287212645[/C][C]0.361988143606323[/C][/ROW]
[ROW][C]76[/C][C]0.91176028193054[/C][C]0.176479436138919[/C][C]0.0882397180694597[/C][/ROW]
[ROW][C]77[/C][C]0.903708971623285[/C][C]0.19258205675343[/C][C]0.096291028376715[/C][/ROW]
[ROW][C]78[/C][C]0.891099729238623[/C][C]0.217800541522754[/C][C]0.108900270761377[/C][/ROW]
[ROW][C]79[/C][C]0.868926990392639[/C][C]0.262146019214721[/C][C]0.131073009607361[/C][/ROW]
[ROW][C]80[/C][C]0.841989054324818[/C][C]0.316021891350364[/C][C]0.158010945675182[/C][/ROW]
[ROW][C]81[/C][C]0.823124165694332[/C][C]0.353751668611335[/C][C]0.176875834305668[/C][/ROW]
[ROW][C]82[/C][C]0.96854402639113[/C][C]0.0629119472177399[/C][C]0.03145597360887[/C][/ROW]
[ROW][C]83[/C][C]0.961534708715451[/C][C]0.0769305825690973[/C][C]0.0384652912845487[/C][/ROW]
[ROW][C]84[/C][C]0.967254664474027[/C][C]0.0654906710519466[/C][C]0.0327453355259733[/C][/ROW]
[ROW][C]85[/C][C]0.959883565663001[/C][C]0.0802328686739973[/C][C]0.0401164343369987[/C][/ROW]
[ROW][C]86[/C][C]0.950360091814898[/C][C]0.0992798163702046[/C][C]0.0496399081851023[/C][/ROW]
[ROW][C]87[/C][C]0.936725986674853[/C][C]0.126548026650295[/C][C]0.0632740133251474[/C][/ROW]
[ROW][C]88[/C][C]0.928023274595785[/C][C]0.14395345080843[/C][C]0.071976725404215[/C][/ROW]
[ROW][C]89[/C][C]0.911354122519649[/C][C]0.177291754960702[/C][C]0.0886458774803511[/C][/ROW]
[ROW][C]90[/C][C]0.972732123359877[/C][C]0.0545357532802459[/C][C]0.027267876640123[/C][/ROW]
[ROW][C]91[/C][C]0.964215882964058[/C][C]0.0715682340718831[/C][C]0.0357841170359416[/C][/ROW]
[ROW][C]92[/C][C]0.960866341175192[/C][C]0.0782673176496163[/C][C]0.0391336588248081[/C][/ROW]
[ROW][C]93[/C][C]0.94915772395478[/C][C]0.10168455209044[/C][C]0.0508422760452202[/C][/ROW]
[ROW][C]94[/C][C]0.935641472498921[/C][C]0.128717055002158[/C][C]0.0643585275010792[/C][/ROW]
[ROW][C]95[/C][C]0.957004169992902[/C][C]0.0859916600141952[/C][C]0.0429958300070976[/C][/ROW]
[ROW][C]96[/C][C]0.947349209412405[/C][C]0.105301581175191[/C][C]0.0526507905875954[/C][/ROW]
[ROW][C]97[/C][C]0.935581904884156[/C][C]0.128836190231688[/C][C]0.0644180951158439[/C][/ROW]
[ROW][C]98[/C][C]0.920929068994033[/C][C]0.158141862011934[/C][C]0.0790709310059672[/C][/ROW]
[ROW][C]99[/C][C]0.910755800174445[/C][C]0.178488399651109[/C][C]0.0892441998255546[/C][/ROW]
[ROW][C]100[/C][C]0.89321157445739[/C][C]0.213576851085219[/C][C]0.10678842554261[/C][/ROW]
[ROW][C]101[/C][C]0.87716053642394[/C][C]0.24567892715212[/C][C]0.12283946357606[/C][/ROW]
[ROW][C]102[/C][C]0.858130373758766[/C][C]0.283739252482467[/C][C]0.141869626241234[/C][/ROW]
[ROW][C]103[/C][C]0.839805603126091[/C][C]0.320388793747819[/C][C]0.160194396873909[/C][/ROW]
[ROW][C]104[/C][C]0.809358798765973[/C][C]0.381282402468053[/C][C]0.190641201234027[/C][/ROW]
[ROW][C]105[/C][C]0.778825010901076[/C][C]0.442349978197848[/C][C]0.221174989098924[/C][/ROW]
[ROW][C]106[/C][C]0.836718079906134[/C][C]0.326563840187732[/C][C]0.163281920093866[/C][/ROW]
[ROW][C]107[/C][C]0.816056227846446[/C][C]0.367887544307108[/C][C]0.183943772153554[/C][/ROW]
[ROW][C]108[/C][C]0.783696404164761[/C][C]0.432607191670479[/C][C]0.216303595835239[/C][/ROW]
[ROW][C]109[/C][C]0.917025449768389[/C][C]0.165949100463222[/C][C]0.0829745502316108[/C][/ROW]
[ROW][C]110[/C][C]0.999455137505611[/C][C]0.00108972498877884[/C][C]0.000544862494389418[/C][/ROW]
[ROW][C]111[/C][C]0.999820744069439[/C][C]0.000358511861121797[/C][C]0.000179255930560898[/C][/ROW]
[ROW][C]112[/C][C]0.999953488719188[/C][C]9.30225616241531e-05[/C][C]4.65112808120765e-05[/C][/ROW]
[ROW][C]113[/C][C]0.999916309482706[/C][C]0.000167381034588128[/C][C]8.36905172940638e-05[/C][/ROW]
[ROW][C]114[/C][C]0.999958324621372[/C][C]8.33507572550776e-05[/C][C]4.16753786275388e-05[/C][/ROW]
[ROW][C]115[/C][C]0.999941666609677[/C][C]0.000116666780645879[/C][C]5.83333903229393e-05[/C][/ROW]
[ROW][C]116[/C][C]0.999893250613246[/C][C]0.000213498773508102[/C][C]0.000106749386754051[/C][/ROW]
[ROW][C]117[/C][C]0.999870510855417[/C][C]0.000258978289166772[/C][C]0.000129489144583386[/C][/ROW]
[ROW][C]118[/C][C]0.999782172082182[/C][C]0.000435655835635108[/C][C]0.000217827917817554[/C][/ROW]
[ROW][C]119[/C][C]0.99983745396759[/C][C]0.000325092064820087[/C][C]0.000162546032410044[/C][/ROW]
[ROW][C]120[/C][C]0.99970587864159[/C][C]0.000588242716820877[/C][C]0.000294121358410439[/C][/ROW]
[ROW][C]121[/C][C]0.999958342155496[/C][C]8.33156890081439e-05[/C][C]4.16578445040719e-05[/C][/ROW]
[ROW][C]122[/C][C]0.999931781373465[/C][C]0.000136437253069164[/C][C]6.82186265345822e-05[/C][/ROW]
[ROW][C]123[/C][C]0.999984244635803[/C][C]3.15107283948708e-05[/C][C]1.57553641974354e-05[/C][/ROW]
[ROW][C]124[/C][C]0.999967300598307[/C][C]6.53988033858123e-05[/C][C]3.26994016929062e-05[/C][/ROW]
[ROW][C]125[/C][C]0.999934880975713[/C][C]0.000130238048573627[/C][C]6.51190242868136e-05[/C][/ROW]
[ROW][C]126[/C][C]0.999889424842387[/C][C]0.000221150315225553[/C][C]0.000110575157612777[/C][/ROW]
[ROW][C]127[/C][C]0.999974997842764[/C][C]5.00043144711734e-05[/C][C]2.50021572355867e-05[/C][/ROW]
[ROW][C]128[/C][C]0.999944548650604[/C][C]0.000110902698792737[/C][C]5.54513493963683e-05[/C][/ROW]
[ROW][C]129[/C][C]0.999955561207819[/C][C]8.88775843628287e-05[/C][C]4.44387921814144e-05[/C][/ROW]
[ROW][C]130[/C][C]0.999916653999584[/C][C]0.000166692000831731[/C][C]8.33460004158656e-05[/C][/ROW]
[ROW][C]131[/C][C]0.999834093645965[/C][C]0.000331812708069355[/C][C]0.000165906354034678[/C][/ROW]
[ROW][C]132[/C][C]0.999849500367854[/C][C]0.000300999264292623[/C][C]0.000150499632146311[/C][/ROW]
[ROW][C]133[/C][C]0.999799388663888[/C][C]0.000401222672224486[/C][C]0.000200611336112243[/C][/ROW]
[ROW][C]134[/C][C]0.999647426419206[/C][C]0.000705147161588006[/C][C]0.000352573580794003[/C][/ROW]
[ROW][C]135[/C][C]0.999842531889409[/C][C]0.000314936221181595[/C][C]0.000157468110590798[/C][/ROW]
[ROW][C]136[/C][C]0.999645134571293[/C][C]0.000709730857414339[/C][C]0.00035486542870717[/C][/ROW]
[ROW][C]137[/C][C]0.999997265821168[/C][C]5.46835766349262e-06[/C][C]2.73417883174631e-06[/C][/ROW]
[ROW][C]138[/C][C]0.99999345938252[/C][C]1.30812349589905e-05[/C][C]6.54061747949524e-06[/C][/ROW]
[ROW][C]139[/C][C]0.99999968769579[/C][C]6.24608419170216e-07[/C][C]3.12304209585108e-07[/C][/ROW]
[ROW][C]140[/C][C]0.999999061576102[/C][C]1.87684779553758e-06[/C][C]9.38423897768788e-07[/C][/ROW]
[ROW][C]141[/C][C]0.999999941333432[/C][C]1.17333136674868e-07[/C][C]5.8666568337434e-08[/C][/ROW]
[ROW][C]142[/C][C]0.999999771022718[/C][C]4.57954564946809e-07[/C][C]2.28977282473405e-07[/C][/ROW]
[ROW][C]143[/C][C]0.99999999969225[/C][C]6.15500648214938e-10[/C][C]3.07750324107469e-10[/C][/ROW]
[ROW][C]144[/C][C]0.999999999993688[/C][C]1.26239861491385e-11[/C][C]6.31199307456923e-12[/C][/ROW]
[ROW][C]145[/C][C]0.999999999955217[/C][C]8.95667492935264e-11[/C][C]4.47833746467632e-11[/C][/ROW]
[ROW][C]146[/C][C]0.999999999999686[/C][C]6.285910476511e-13[/C][C]3.1429552382555e-13[/C][/ROW]
[ROW][C]147[/C][C]0.999999999870791[/C][C]2.58417436284558e-10[/C][C]1.29208718142279e-10[/C][/ROW]
[ROW][C]148[/C][C]0.999999951245744[/C][C]9.75085127215963e-08[/C][C]4.87542563607981e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155012&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155012&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
160.5884017607248520.8231964785502960.411598239275148
170.4592567987453840.9185135974907680.540743201254616
180.5720650429907160.8558699140185670.427934957009284
190.4486145644755520.8972291289511050.551385435524448
200.335334918542380.670669837084760.66466508145762
210.2438938499706170.4877876999412330.756106150029383
220.878680216394930.2426395672101410.12131978360507
230.8260464574630810.3479070850738390.173953542536919
240.7794349221288290.4411301557423430.220565077871171
250.830647457653570.338705084692860.16935254234643
260.7975051156726140.4049897686547720.202494884327386
270.7807310117308470.4385379765383050.219268988269153
280.7705212883381730.4589574233236540.229478711661827
290.7156434626792480.5687130746415030.284356537320751
300.7554090294875570.4891819410248860.244590970512443
310.727299487612920.545401024774160.27270051238708
320.7460793132655150.5078413734689690.253920686734485
330.6985293611299470.6029412777401070.301470638870053
340.6451387625200840.7097224749598310.354861237479916
350.7046779355581370.5906441288837270.295322064441863
360.661320512698030.677358974603940.33867948730197
370.7490270904748970.5019458190502070.250972909525103
380.71376378241340.5724724351731990.2862362175866
390.6679681125442290.6640637749115420.332031887455771
400.613580026464270.7728399470714610.38641997353573
410.6422097343127240.7155805313745520.357790265687276
420.606259082313440.7874818353731210.39374091768656
430.5816009638999110.8367980722001780.418399036100089
440.6013327626961450.7973344746077110.398667237303855
450.8572331735861490.2855336528277010.142766826413851
460.8978578774107430.2042842451785150.102142122589257
470.888242192224790.223515615550420.11175780777521
480.8995166833702840.2009666332594320.100483316629716
490.9530045395526860.09399092089462870.0469954604473144
500.973260972090150.05347805581970060.0267390279098503
510.971781527553980.05643694489203960.0282184724460198
520.9675527743601010.06489445127979740.0324472256398987
530.9672385276551320.0655229446897360.032761472344868
540.9566837624535970.08663247509280670.0433162375464033
550.9472717647353220.1054564705293560.0527282352646782
560.9340291653198390.1319416693603230.0659708346801613
570.9166936866483950.1666126267032090.0833063133516045
580.9280814846748610.1438370306502770.0719185153251387
590.9119261587310650.176147682537870.088073841268935
600.9308750668192490.1382498663615020.0691249331807509
610.9174071316034870.1651857367930260.0825928683965131
620.9258880352992010.1482239294015990.0741119647007993
630.9317902664571630.1364194670856740.0682097335428369
640.9161666131311610.1676667737376780.083833386868839
650.8963434472443090.2073131055113810.103656552755691
660.8757981333720380.2484037332559230.124201866627962
670.8525423279328150.2949153441343710.147457672067185
680.8640059143724730.2719881712550550.135994085627527
690.8354856951929310.3290286096141370.164514304807068
700.80629522592010.38740954815980.1937047740799
710.7733395216153960.4533209567692080.226660478384604
720.7448871783739110.5102256432521770.255112821626088
730.707453827825380.585092344349240.29254617217462
740.6682814858487540.6634370283024920.331718514151246
750.6380118563936780.7239762872126450.361988143606323
760.911760281930540.1764794361389190.0882397180694597
770.9037089716232850.192582056753430.096291028376715
780.8910997292386230.2178005415227540.108900270761377
790.8689269903926390.2621460192147210.131073009607361
800.8419890543248180.3160218913503640.158010945675182
810.8231241656943320.3537516686113350.176875834305668
820.968544026391130.06291194721773990.03145597360887
830.9615347087154510.07693058256909730.0384652912845487
840.9672546644740270.06549067105194660.0327453355259733
850.9598835656630010.08023286867399730.0401164343369987
860.9503600918148980.09927981637020460.0496399081851023
870.9367259866748530.1265480266502950.0632740133251474
880.9280232745957850.143953450808430.071976725404215
890.9113541225196490.1772917549607020.0886458774803511
900.9727321233598770.05453575328024590.027267876640123
910.9642158829640580.07156823407188310.0357841170359416
920.9608663411751920.07826731764961630.0391336588248081
930.949157723954780.101684552090440.0508422760452202
940.9356414724989210.1287170550021580.0643585275010792
950.9570041699929020.08599166001419520.0429958300070976
960.9473492094124050.1053015811751910.0526507905875954
970.9355819048841560.1288361902316880.0644180951158439
980.9209290689940330.1581418620119340.0790709310059672
990.9107558001744450.1784883996511090.0892441998255546
1000.893211574457390.2135768510852190.10678842554261
1010.877160536423940.245678927152120.12283946357606
1020.8581303737587660.2837392524824670.141869626241234
1030.8398056031260910.3203887937478190.160194396873909
1040.8093587987659730.3812824024680530.190641201234027
1050.7788250109010760.4423499781978480.221174989098924
1060.8367180799061340.3265638401877320.163281920093866
1070.8160562278464460.3678875443071080.183943772153554
1080.7836964041647610.4326071916704790.216303595835239
1090.9170254497683890.1659491004632220.0829745502316108
1100.9994551375056110.001089724988778840.000544862494389418
1110.9998207440694390.0003585118611217970.000179255930560898
1120.9999534887191889.30225616241531e-054.65112808120765e-05
1130.9999163094827060.0001673810345881288.36905172940638e-05
1140.9999583246213728.33507572550776e-054.16753786275388e-05
1150.9999416666096770.0001166667806458795.83333903229393e-05
1160.9998932506132460.0002134987735081020.000106749386754051
1170.9998705108554170.0002589782891667720.000129489144583386
1180.9997821720821820.0004356558356351080.000217827917817554
1190.999837453967590.0003250920648200870.000162546032410044
1200.999705878641590.0005882427168208770.000294121358410439
1210.9999583421554968.33156890081439e-054.16578445040719e-05
1220.9999317813734650.0001364372530691646.82186265345822e-05
1230.9999842446358033.15107283948708e-051.57553641974354e-05
1240.9999673005983076.53988033858123e-053.26994016929062e-05
1250.9999348809757130.0001302380485736276.51190242868136e-05
1260.9998894248423870.0002211503152255530.000110575157612777
1270.9999749978427645.00043144711734e-052.50021572355867e-05
1280.9999445486506040.0001109026987927375.54513493963683e-05
1290.9999555612078198.88775843628287e-054.44387921814144e-05
1300.9999166539995840.0001666920008317318.33460004158656e-05
1310.9998340936459650.0003318127080693550.000165906354034678
1320.9998495003678540.0003009992642926230.000150499632146311
1330.9997993886638880.0004012226722244860.000200611336112243
1340.9996474264192060.0007051471615880060.000352573580794003
1350.9998425318894090.0003149362211815950.000157468110590798
1360.9996451345712930.0007097308574143390.00035486542870717
1370.9999972658211685.46835766349262e-062.73417883174631e-06
1380.999993459382521.30812349589905e-056.54061747949524e-06
1390.999999687695796.24608419170216e-073.12304209585108e-07
1400.9999990615761021.87684779553758e-069.38423897768788e-07
1410.9999999413334321.17333136674868e-075.8666568337434e-08
1420.9999997710227184.57954564946809e-072.28977282473405e-07
1430.999999999692256.15500648214938e-103.07750324107469e-10
1440.9999999999936881.26239861491385e-116.31199307456923e-12
1450.9999999999552178.95667492935264e-114.47833746467632e-11
1460.9999999999996866.285910476511e-133.1429552382555e-13
1470.9999999998707912.58417436284558e-101.29208718142279e-10
1480.9999999512457449.75085127215963e-084.87542563607981e-08






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level390.293233082706767NOK
5% type I error level390.293233082706767NOK
10% type I error level540.406015037593985NOK

\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 & 39 & 0.293233082706767 & NOK \tabularnewline
5% type I error level & 39 & 0.293233082706767 & NOK \tabularnewline
10% type I error level & 54 & 0.406015037593985 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155012&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]39[/C][C]0.293233082706767[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]39[/C][C]0.293233082706767[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]54[/C][C]0.406015037593985[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155012&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155012&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 level390.293233082706767NOK
5% type I error level390.293233082706767NOK
10% type I error level540.406015037593985NOK


Figures (Output of Computation)

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Input Parameters & R Code

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