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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Thu, 14 Dec 2017 15:16:15 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/14/t1513282258zqlvgwlgv0l6rru.htm/, Retrieved Mon, 13 May 2024 22:50:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309586, Retrieved Mon, 13 May 2024 22:50:32 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Multiple Regression] [lnTotDamg 2 limieten] [2017-12-14 14:16:15] [52cce9dbcec2927ac392287242c803b1] [Current]

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Dataseries X:

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Boxplots

NA	0	1	0
NA	1	0	0
NA	1	0	0
11,08214255	1	0	0
9,279306576	0	1	0
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9,680344001	1	0	0
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10,49127422	1	0	0
NA	0	1	0
10,45843532	0	0	1
NA	0	0	1
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11,42894585	1	0	0
NA	1	0	0
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11,51292546	0	1	0
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9,6721228	1	0	0
NA	1	0	0
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NA	0	0	1
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NA	0	1	0
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NA	1	0	0
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9,850297724	1	0	0
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9,945396956	1	0	0
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10,3843693	1	0	0
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9,445570584	1	0	0
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10,98065487	1	0	0
9,494616651	1	0	0
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NA	1	0	0
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10,29262001	1	0	0
9,244935017	1	0	0
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9,924857578	1	0	0
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11,27466828	0	0	1
9,61580548	0	0	1
10,46310334	0	1	0
10,13074264	0	1	0
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10,16203686	1	0	0
NA	1	0	0
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9,552084403	1	0	0
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9,611663581	1	0	0
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10,87064249	1	0	0
10,14199251	1	0	0
9,37160852	0	0	1
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10,08460005	0	1	0
10,37838544	0	1	0
10,57362196	0	1	0
10,44540478	1	0	0
10,40589787	0	0	1
NA	0	1	0
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NA	1	0	0
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10,67359577	1	0	0
9,529230372	0	0	1
9,491299899	0	0	1
10,53006749	1	0	0
9,314700387	1	0	0
NA	0	1	0
NA	1	0	0
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9,587200223	1	0	0
NA	1	0	0
NA	1	0	0
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10,62789112	1	0	0
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NA	1	0	0
9,747418367	1	0	0
9,903487553	0	1	0
9,774915272	0	1	0
NA	1	0	0
NA	1	0	0
10,91508846	0	1	0
11,04224961	0	1	0
9,921081861	1	0	0
NA	1	0	0
NA	1	0	0
10,82978802	1	0	0
9,368710708	1	0	0
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10,12954685	0	0	1
9,990719738	1	0	0
10,35774282	1	0	0
10,74710006	0	0	1
9,354267541	1	0	0
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9,754059039	1	0	0
10,00297083	1	0	0
11,2515607	1	0	0
10,23016195	1	0	0
10,24124468	0	1	0
11,17448329	1	0	0
9,454540666	0	0	1
NA	1	0	0
9,219894585	1	0	0
11,61865391	1	0	0
11,2441829	1	0	0
NA	0	1	0
9,825526011	1	0	0
9,61580548	0	0	0
10,48849257	1	0	0
11,68237284	0	1	0
9,565564264	0	1	0
11,5885801	1	0	0
9,235032985	0	1	0
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9,844586445	1	0	0
9,819507939	1	0	0
9,812084729	1	0	0
10,46310334	0	1	0
9,898324246	1	0	0
NA	1	0	0
10,1662748	1	0	0
NA	1	0	0
9,847287503	1	0	0
11,61110425	1	0	0
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9,319374133	0	0	1
9,56254534	0	0	1
11,22243947	1	0	0
10,78903038	0	1	0
11,30480598	0	1	0
9,85828096	1	0	0
NA	1	0	0
10,18236851	1	0	0
9,486152272	1	0	0
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10,1266311	1	0	0
9,635608107	1	0	0
11,29464507	0	1	0
9,754059039	0	1	0
9,829410349	1	0	0
10,2267298	0	1	0
10,08618404	1	0	0
NA	1	0	0
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10,04324949	0	1	0
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11,30871406	0	0	0
9,790206866	1	0	0
10,44138345	1	0	0
9,637566972	0	1	0
9,739202358	1	0	0
9,397566548	1	0	0
NA	0	1	0
NA	1	0	0
9,216521231	1	0	0
11,65354791	1	0	0
10,29890232	1	0	0
NA	1	0	0
10,71441777	1	0	0
9,469468637	0	1	0
10,03245228	1	0	0
11,2218376	0	1	0
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9,824336114	1	0	0
10,37258452	0	1	0
10,59663473	1	0	0
10,50506754	0	1	0
10,17309475	0	0	1
9,387649387	0	0	1
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9,226508953	1	0	0
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NA	1	0	0
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10,9000302	0	0	1
9,546812609	1	0	0
NA	0	1	0
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9,739496952	0	1	0
10,01806546	1	0	0
9,686698767	1	0	0
9,562404703	1	0	0
10,49127422	0	1	0
9,798127037	1	0	0
NA	1	0	0
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10,87776413	0	1	0
NA	0	1	0
NA	1	0	0
10,30895266	1	0	0
10,60698103	1	0	0
NA	1	0	0
9,393827915	1	0	0
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9,37627845	1	0	0
10,22194128	0	1	0
10,88187006	0	1	0
9,699656312	0	1	0
11,4145185	0	1	0
11,10476172	1	0	0
NA	1	0	0
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9,6374365	1	0	0
9,392661929	1	0	0
10,90778916	1	0	0
9,425854896	0	1	0
NA	1	0	0
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10,13459927	1	0	0
NA	1	0	0
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9,923584254	1	0	0
10,6454249	1	0	0
10,1266311	0	1	0
10,4367887	1	0	0
11,19553991	1	0	0
9,752664663	1	0	0
NA	1	0	0
9,61580548	0	1	0
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10,48592661	0	1	0
11,16400608	0	1	0
10,85821023	0	1	0
9,71111566	1	0	0
9,367344121	0	1	0
10,31890299	1	0	0
NA	1	0	0
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9,305650552	1	0	0
9,472704636	0	1	0
10,46310334	0	1	0
9,998797732	1	0	0
9,634627234	1	0	0
NA	0	1	0
NA	0	0	1
NA	0	1	0
10,30705085	1	0	0
10,404899	0	1	0
9,245031612	1	0	0
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10,64120171	0	1	0
9,287301413	0	1	0
10,90963727	0	1	0
9,903487553	0	1	0
NA	0	1	0
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9,904387148	0	1	0
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9,413281216	0	0	1
11,11253745	1	0	0
9,839109019	0	0	1
10,51867319	0	1	0
NA	0	1	0
10,1266311	0	1	0
NA	0	1	0
11,65542279	1	0	0
10,36577398	0	0	1
10,98019501	0	1	0
9,772239266	0	1	0
11,39357871	1	0	0
10,59663473	0	1	0
9,998297607	0	0	1
10,48570317	0	1	0
10,14423524	0	0	1
10,59795886	0	1	0
11,12388965	1	0	0
NA	0	1	0
NA	0	1	0
9,786785183	0	1	0
10,01444736	1	0	0
9,367344121	1	0	0
NA	0	1	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
NA	0	1	0
9,58548372	1	0	0
NA	1	0	0
11,52485404	1	0	0
10,01153446	0	0	1
NA	0	0	1
9,45915167	1	0	0
10,1266311	0	0	1
10,07162566	1	0	0
9,575261225	1	0	0
9,749986662	1	0	0
10,49305042	1	0	0
10,57479804	1	0	0
11,00376512	1	0	0
10,1266311	1	0	0
NA	0	1	0
10,90527685	0	1	0
9,597505723	1	0	0
10,1266311	0	1	0
9,400464741	0	1	0
9,76995616	0	1	0
9,713234625	0	0	1
NA	0	1	0
NA	1	0	0
9,963453134	1	0	0
NA	1	0	0
10,87799059	0	1	0
NA	0	1	0
9,760252084	1	0	0
NA	0	0	0
11,65268741	0	1	0
9,928180165	0	0	1
9,641927964	1	0	0
NA	1	0	0
NA	0	1	0
9,952277717	0	1	0
NA	0	1	0
11,33154746	0	1	0
NA	0	1	0
9,612332791	1	0	0
NA	0	1	0
NA	0	1	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
10,66865302	1	0	0
NA	1	0	0
NA	1	0	0
10,29876764	0	0	1
9,392661929	0	0	1
10,31144954	1	0	0
9,392661929	0	0	1
NA	0	0	1
9,71111566	0	0	1
NA	0	1	0
9,787122261	1	0	0
9,433483923	0	1	0
9,919902094	0	1	0
9,948843254	0	1	0
9,576371411	0	1	0
9,693506988	0	0	1
9,400960732	0	0	1
NA	0	1	0
9,469082701	1	0	0
11,51546224	0	1	0
9,629050707	0	1	0
10,55602105	1	0	0
9,579141496	0	1	0
NA	0	1	0
10,82396949	0	0	0
NA	0	1	0
NA	1	0	0
11,19680276	1	0	0
9,71111566	0	1	0
9,581076	0	1	0
11,61005218	0	1	0
10,01717332	0	1	0
10,12262308	0	1	0
NA	1	0	0
11,04509547	1	0	0
10,60323788	0	1	0
NA	1	0	0
NA	1	0	0
9,674388804	1	0	0
NA	1	0	0
NA	1	0	0
9,920836191	0	1	0
10,1266311	0	0	1
NA	0	0	1
10,78931908	0	1	0
NA	1	0	0
NA	1	0	0
10,04081174	0	1	0
NA	0	1	0
9,740968623	0	1	0
9,525151112	1	0	0
11,46643116	0	1	0
NA	0	0	1
11,20525835	0	0	1
11,24373798	0	1	0
10,23935246	1	0	0
11,40275339	0	1	0
11,19643231	1	0	0
NA	1	0	0
NA	1	0	0
11,04469626	1	0	0
10,4487146	0	1	0
NA	1	0	0
10,54534144	0	1	0
NA	0	1	0
11,65789124	0	1	0
11,22632281	1	0	0
11,24127421	0	0	0
NA	0	1	0
11,0656535	1	0	0
9,450773592	0	1	0
NA	0	1	0
9,915910073	0	0	1
10,85096683	0	0	1
10,2561846	1	0	0
9,949511991	1	0	0
9,809176873	0	0	1
9,270494295	1	0	0
9,382190629	1	0	0
NA	1	0	0
11,22791981	0	1	0
9,903487553	0	1	0
11,00209984	1	0	0
9,38806806	1	0	0
10,39479391	1	0	0
9,528503152	0	1	0
NA	1	0	0
10,15225986	1	0	0
9,524055621	0	1	0
9,549808118	1	0	0
10,21178075	0	1	0
NA	0	1	0
9,709720748	0	0	1
NA	0	0	1
10,10389458	1	0	0
9,754465366	0	0	1
9,487972109	1	0	0
NA	1	0	0
NA	0	1	0
10,89942091	0	0	1
NA	0	1	0
NA	1	0	0
9,825526011	0	1	0
9,405084449	0	0	1
NA	1	0	0
NA	1	0	0
NA	0	1	0
NA	0	1	0
10,56035968	0	1	0
10,13658143	0	1	0
10,98613982	1	0	0
10,4421715	1	0	0
9,752664663	1	0	0
11,19353254	1	0	0
10,84933709	0	1	0
9,875396672	1	0	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
NA	0	1	0
10,53539742	1	0	0
9,305650552	1	0	0
9,839748712	1	0	0
9,868999622	1	0	0
9,692766521	1	0	0
11,57803882	1	0	0
9,743084031	1	0	0
NA	1	0	0
NA	1	0	0
NA	0	1	0
NA	1	0	0
11,62500337	0	1	0
NA	0	1	0
10,24558679	1	0	0
NA	0	1	0
NA	0	1	0
10,81977828	0	1	0
10,49127422	1	0	0
9,913437883	1	0	0
10,58405595	1	0	0
9,846070282	0	1	0
NA	0	1	0
10,81679384	0	1	0
NA	1	0	0
10,30011371	1	0	0
NA	0	1	0
11,53517607	0	1	0
10,06556388	1	0	0
9,510444964	1	0	0
NA	1	0	0
10,51254635	0	1	0
10,20032756	1	0	0
9,910959567	0	1	0
NA	0	0	0
NA	0	1	0
NA	0	1	0
NA	0	1	0
9,259130536	1	0	0
NA	0	1	0
9,975808214	0	1	0
9,620859354	1	0	0
10,37464676	0	1	0
9,36777138	1	0	0
NA	1	0	0
9,98681716	0	1	0
NA	0	1	0
11,29009436	0	1	0
9,630759772	0	1	0
11,08374127	0	1	0
9,903487553	0	0	1
NA	0	0	1
9,68427377	1	0	0
NA	1	0	0
NA	0	1	0
9,49912184	0	0	1
10,93310697	1	0	0
9,249561085	1	0	0
9,883284845	0	0	1
10,62132735	0	0	1
NA	1	0	0
NA	1	0	0
NA	0	1	0
11,01246263	0	1	0
NA	0	1	0
9,948317504	1	0	0
NA	1	0	0
9,417354541	1	0	0
NA	0	1	0
NA	0	1	0
9,568014816	0	1	0
9,928180165	0	1	0
9,563669726	1	0	0
10,59663473	0	1	0
10,57041909	1	0	0
11,6022633	1	0	0
10,31015194	1	0	0
10,20359214	1	0	0
9,398975291	1	0	0
NA	1	0	0
10,73203937	0	0	0
10,98359637	0	1	0
NA	0	1	0
NA	0	1	0
NA	0	1	0
9,313708905	1	0	0
NA	0	1	0
11,17557684	0	1	0
10,96888771	0	0	1
NA	0	0	0
10,80413659	0	1	0
9,562475024	0	1	0
10,81977828	1	0	0
10,67398922	1	0	0
NA	1	0	0
10,00595388	1	0	0
NA	0	1	0
NA	0	1	0
11,20854474	1	0	0
9,618867454	0	1	0
11,05830688	0	1	0
NA	0	1	0
NA	1	0	0
NA	1	0	0
10,04324949	1	0	0
NA	0	1	0
11,16574813	1	0	0
NA	1	0	0
11,39928633	1	0	0
11,34651663	1	0	0
10,74926998	1	0	0
NA	0	1	0
10,5118935	0	0	1
NA	1	0	0
9,742085646	1	0	0
11,34030866	0	1	0
10,54534144	0	1	0
NA	0	1	0
11,47553508	1	0	0
NA	1	0	0
NA	1	0	0
NA	0	1	0
11,22524339	0	1	0
10,70539945	1	0	0
10,39830574	1	0	0
NA	1	0	0
10,00333289	0	1	0
9,433483923	1	0	0
NA	0	1	0
NA	1	0	0
11,14759892	1	0	0
NA	1	0	0
10,1266311	0	0	1
10,20905866	1	0	0
9,775654181	0	1	0
NA	1	0	0
NA	0	1	0
9,384629757	0	0	1
9,733232897	1	0	0
9,392078425	1	0	0
11,46163217	1	0	0
9,928180165	0	1	0
NA	0	1	0
10,59663473	1	0	0
NA	1	0	0
10,30985226	1	0	0
11,34918226	1	0	0
10,51737505	1	0	0
10,06598898	0	0	1
9,279213236	1	0	0
11,00209984	1	0	0
9,287301413	1	0	0
NA	1	0	0
10,4487146	1	0	0
10,61189274	0	1	0
10,30895266	0	1	0
10,81977828	0	1	0
9,29679326	1	0	0
10,96950778	1	0	0
9,82978719	0	1	0
10,46310334	0	1	0
NA	0	1	0
10,98796711	0	1	0
9,604407435	1	0	0
11,23321156	1	0	0
11,47221805	0	1	0
9,546669741	0	1	0
NA	0	1	0
9,46109909	1	0	0
NA	0	1	0
10,77726736	0	1	0
10,81500692	1	0	0
11,66650455	1	0	0
NA	0	1	0
10,9511749	0	1	0
NA	0	0	0
9,588708312	1	0	0
11,25508694	1	0	0
NA	0	1	0
10,45036541	1	0	0
NA	0	1	0
10,30895266	0	1	0
9,431241411	0	1	0
9,519000851	1	0	0
NA	1	0	0
9,957028319	0	1	0
11,62973024	1	0	0
9,69879768	0	0	1
9,693877016	1	0	0
9,585827257	1	0	0
10,00278975	0	1	0
11,00209984	0	1	0
NA	0	1	0
10,42942836	1	0	0
NA	1	0	0
NA	1	0	0
9,215327913	0	1	0
9,878169745	0	1	0
NA	0	1	0
10,36407196	1	0	0
NA	1	0	0
10,30895266	1	0	0
10,08647555	0	1	0
9,223552703	0	0	0
NA	0	0	0
NA	1	0	0
11,65054599	1	0	0
11,44862158	1	0	0
9,305650552	0	0	1
NA	0	0	1
10,08580911	1	0	0
9,903487553	1	0	0
NA	1	0	0
11,09843979	0	1	0
10,70398577	0	0	1
9,651301316	1	0	0
10,0647557	1	0	0
11,19862559	1	0	0
10,2065138	1	0	0
NA	0	1	0
10,0895521	0	0	1
NA	0	0	1
11,05515076	0	0	1
9,590487672	1	0	0
9,416541203	1	0	0
10,59663473	0	1	0
11,65572626	1	0	0
9,449357272	1	0	0
NA	1	0	0
10,98063784	1	0	0
10,5971596	1	0	0
NA	1	0	0
11,18163976	1	0	0
11,51292546	0	1	0
9,463508636	0	1	0
10,46310334	0	1	0
9,25598273	0	1	0
11,31491345	1	0	0
9,971379819	0	1	0
NA	0	1	0
9,853456619	1	0	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
NA	0	0	1
9,409191231	0	0	1
10,58405595	0	1	0
NA	1	0	0
9,904487053	0	1	0
11,46163217	0	1	0
9,492507264	0	1	0
10,86666187	1	0	0
10,04450957	1	0	0
11,21187442	0	1	0
11,33881014	0	1	0
10,33624352	0	0	1
NA	0	0	1
NA	1	0	0
NA	1	0	0
11,16083997	0	1	0
10,00784757	0	0	0
10,41631118	0	1	0
NA	1	0	0
NA	1	0	0
9,702961291	0	1	0
NA	1	0	0
9,453286551	0	0	1
NA	0	1	0
9,986126886	0	1	0
NA	0	1	0
10,66082945	0	1	0
9,807196892	1	0	0
9,451716692	1	0	0
NA	1	0	0
9,798127037	1	0	0
9,774687805	0	1	0
10,28236909	1	0	0
NA	1	0	0
9,945684601	1	0	0
11,13657246	0	0	1
9,305650552	0	1	0
9,84686429	0	0	1
9,717157974	1	0	0
9,305650552	0	0	1
NA	0	0	1
NA	0	0	1
NA	1	0	0
10,98529272	0	1	0
10,73072847	0	0	1
9,667765219	0	0	1
NA	1	0	0
10,4115995	0	1	0
10,66807128	0	0	1
10,00802773	1	0	0
10,55059079	0	0	1
10,57681461	1	0	0
10,21603295	1	0	0
NA	0	1	0
9,216819338	0	1	0
NA	0	1	0
9,338293736	1	0	0
11,23425599	1	0	0
10,77895629	0	1	0
10,39249692	1	0	0
NA	1	0	0
10,23995979	1	0	0
NA	0	0	1
11,49740565	1	0	0
10,40426284	1	0	0
NA	1	0	0
9,594036922	1	0	0
NA	1	0	0
NA	0	1	0
9,509333236	0	1	0
9,314880551	1	0	0
9,541512876	1	0	0
10,30169304	0	1	0
9,694308542	1	0	0
NA	1	0	0
9,68059397	0	0	1
NA	0	1	0
NA	0	1	0
NA	0	1	0
NA	1	0	0
9,275191344	1	0	0
10,33064892	1	0	0
NA	0	0	0
NA	0	1	0
9,546812609	0	1	0
11,46163217	0	1	0
11,00209984	0	1	0
9,58342002	1	0	0
11,22524339	0	1	0
11,54659232	1	0	0
NA	0	1	0
NA	0	1	0
NA	0	1	0
NA	0	1	0
9,755045547	0	1	0
NA	0	1	0
9,61580548	1	0	0
10,19046938	1	0	0
NA	0	1	0
10,16819522	0	1	0
10,08776553	0	1	0
NA	0	1	0
9,652651581	1	0	0
9,305650552	1	0	0
10,30895266	0	0	1
9,900783901	0	1	0
11,60423675	0	0	1
9,61580548	1	0	0
NA	1	0	0
11,01287491	1	0	0
11,56264853	0	1	0
9,37160852	0	0	1
NA	1	0	0
NA	1	0	0
9,496946866	1	0	0
10,29214554	1	0	0
NA	0	1	0
11,22984612	0	1	0
NA	1	0	0
9,70454869	1	0	0
11,23630202	0	1	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
10,43429226	1	0	0
NA	0	1	0
9,433483923	1	0	0
NA	1	0	0
10,31201463	0	1	0
NA	1	0	0
NA	1	0	0
9,521861034	1	0	0
9,49912184	1	0	0
10,75930615	0	1	0
9,502114062	1	0	0
11,51782345	1	0	0
10,07314594	1	0	0
9,850877602	0	0	1
9,217812387	1	0	0
9,296518068	1	0	0
9,477156252	0	1	0
NA	1	0	0
NA	1	0	0
10,05212305	1	0	0
NA	0	1	0
NA	1	0	0
10,64823048	1	0	0
NA	1	0	0
9,375346207	1	0	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
9,573315428	1	0	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
10,75864728	1	0	0
11,51292546	0	1	0
NA	1	0	0
NA	0	1	0
10,47956707	1	0	0
10,01023211	1	0	0
NA	1	0	0
10,30895266	1	0	0
10,29741974	1	0	0
10,21533771	1	0	0
NA	1	0	0
9,461799234	0	1	0
9,668714136	1	0	0
NA	0	0	1
NA	0	1	0
10,30895266	0	1	0
10,68230771	1	0	0
9,392661929	1	0	0
10,66592756	1	0	0
9,510444964	1	0	0
10,02428825	1	0	0
NA	1	0	0
10,71014197	1	0	0
NA	0	1	0
NA	1	0	0
10,97671365	1	0	0
9,449357272	0	1	0
NA	0	1	0
10,47294051	0	0	0
NA	1	0	0
NA	1	0	0
10,34174248	0	0	1
9,643420647	0	1	0
10,6038834	0	1	0
NA	0	1	0
10,40976284	1	0	0
9,940012327	0	1	0
10,3609124	1	0	0
NA	1	0	0
9,52434787	1	0	0
11,23733005	1	0	0
9,521494801	1	0	0
9,263312257	1	0	0
NA	1	0	0
NA	1	0	0
NA	0	1	0
10,66024313	1	0	0
9,969696553	1	0	0
9,903487553	0	1	0
9,679093219	1	0	0
11,5972758	1	0	0
9,622450023	0	1	0
NA	0	1	0
NA	1	0	0
9,76995616	0	0	1
11,04404121	1	0	0
10,0961719	0	1	0
NA	1	0	0
10,95778216	1	0	0
9,903487553	1	0	0
NA	1	0	0
9,903487553	0	1	0
11,14764215	0	1	0
9,82119231	0	1	0
9,350015354	0	1	0
9,98994044	1	0	0
11,53092254	1	0	0
NA	1	0	0
NA	0	1	0
NA	0	1	0
9,226705726	1	0	0
NA	1	0	0
NA	1	0	0
11,62029895	0	1	0
9,588845299	0	1	0
9,45273738	1	0	0
11,27754485	0	1	0
10,35271433	1	0	0
10,66634735	0	1	0
10,88177608	1	0	0
9,964441532	1	0	0
10,95168336	1	0	0
NA	1	0	0
11,27357631	1	0	0
9,659056522	0	1	0
10,13277221	0	0	1
11,50720916	0	1	0
9,789870826	1	0	0
9,61580548	0	1	0
NA	0	1	0
9,627799925	1	0	0
11,57105285	0	1	0
NA	1	0	0
11,58907136	1	0	0
9,778151061	1	0	0
10,37648669	0	1	0
NA	1	0	0
9,825526011	0	1	0
11,04368954	0	1	0
11,44398259	0	1	0
10,49562585	0	1	0
9,903487553	0	1	0
NA	1	0	0
9,512369038	0	1	0
10,1266311	0	1	0
NA	0	1	0
9,546812609	0	0	1
9,908873025	1	0	0
9,820920829	0	1	0
10,46310334	0	1	0
10,40728856	0	1	0
11,08214255	0	1	0
NA	0	0	1
NA	0	0	1
11,16261593	0	0	1
9,61580548	0	1	0
10,7831143	1	0	0
10,67148707	1	0	0
NA	1	0	0
10,98569942	1	0	0
11,04775812	1	0	0
10,28636616	1	0	0
11,68435458	0	1	0
9,903487553	0	1	0
11,15988676	0	1	0
NA	0	1	0
10,54402478	0	1	0
11,34864027	1	0	0
11,62789566	0	1	0
NA	0	1	0
9,468851067	1	0	0
9,46498259	1	0	0
10,30895266	0	0	1
NA	0	0	1
9,715711145	0	0	1
9,752664663	0	1	0
10,35894845	0	0	1
NA	1	0	0
10,55968544	0	1	0
11,06352414	1	0	0
9,322418275	1	0	0
9,61580548	0	1	0
NA	0	1	0
10,80012645	0	1	0
NA	0	0	0
10,79133766	1	0	0
NA	1	0	0
10,17473532	0	1	0
NA	0	1	0
9,504873919	1	0	0
9,71111566	0	1	0
10,45042329	1	0	0
NA	0	1	0
10,98529272	0	1	0
10,56134429	1	0	0
NA	0	1	0
NA	0	1	0
9,897268253	1	0	0
9,488199355	1	0	0
9,29118276	1	0	0
NA	1	0	0
9,703388916	0	0	1
11,65268741	1	0	0
9,798127037	0	1	0
9,546812609	0	1	0
NA	0	1	0
9,392661929	1	0	0
NA	1	0	0
NA	0	1	0
9,328123408	0	1	0
9,579003174	0	1	0
9,396819939	1	0	0
NA	0	1	0
NA	0	0	1
9,779736745	0	0	1
9,221577004	0	0	1
10,89094479	1	0	0
NA	0	1	0
10,56359488	0	1	0
11,23056255	0	1	0
9,772125234	0	0	1
NA	0	0	1
9,392661929	1	0	0
NA	1	0	0
11,66514857	1	0	0
9,280052984	1	0	0
11,15806316	0	1	0
NA	0	1	0
9,37585481	1	0	0
NA	1	0	0
9,680344001	0	1	0
9,951467865	0	1	0
NA	0	1	0
10,40728856	1	0	0
11,23848862	1	0	0
10,23458825	1	0	0
10,14435314	0	1	0
9,823578169	1	0	0
9,736369829	1	0	0
9,297251744	1	0	0
9,86526634	1	0	0
9,809176873	0	1	0
9,380336279	0	1	0
10,59663473	1	0	0
NA	1	0	0
10,56553099	1	0	0
NA	0	1	0
NA	0	1	0
9,656947423	1	0	0
NA	0	1	0
10,81977828	0	1	0
10,59663473	0	1	0
9,740968623	0	0	1
NA	1	0	0
10,25878154	1	0	0
9,392661929	0	1	0
NA	0	1	0
NA	0	1	0
9,37160852	0	1	0
NA	0	1	0
9,433483923	1	0	0
NA	1	0	0
11,08572075	1	0	0
9,574636203	0	1	0
9,585277542	1	0	0
9,520395295	1	0	0
NA	1	0	0
10,49819466	0	1	0
10,01873404	0	1	0
9,60238246	0	0	1
NA	0	0	0
NA	1	0	0
10,3205518	1	0	0
NA	1	0	0
NA	0	1	0
NA	1	0	0
NA	1	0	0
11,2185544	1	0	0
NA	1	0	0
NA	1	0	0
11,08214255	1	0	0
NA	1	0	0
NA	0	1	0
11,41254143	0	0	0
9,369734424	0	1	0
NA	0	1	0
11,28978191	0	1	0
NA	1	0	0
9,729134165	0	1	0
9,875448096	1	0	0
NA	0	1	0
NA	0	1	0
9,903487553	1	0	0
NA	1	0	0
9,739673667	1	0	0
9,758692968	0	0	1
9,414504957	1	0	0
10,22918769	0	1	0
9,860057995	1	0	0
NA	1	0	0
NA	1	0	0
10,02127059	1	0	0
10,62132735	0	1	0
NA	0	1	0
10,18338944	0	1	0
10,858999	0	1	0
9,553930076	1	0	0
9,909071931	1	0	0
9,5965547	1	0	0
NA	1	0	0
9,903487553	0	0	1
9,825526011	1	0	0
9,215327913	1	0	0
9,238247325	1	0	0
NA	1	0	0
11,49786259	1	0	0
10,76983145	0	0	1
9,480367509	1	0	0
10,71007502	1	0	0
NA	1	0	0
11,17234882	1	0	0
10,69686461	1	0	0
10,81452451	1	0	0
9,76995616	0	1	0
10,30209587	0	0	1
10,74656222	0	1	0
11,09331072	1	0	0
9,487972109	0	0	1
9,472704636	0	1	0
NA	0	1	0
9,80642584	1	0	0
10,08580911	1	0	0
10,89942091	0	0	1
10,14643373	1	0	0
11,52936952	1	0	0
NA	1	0	0
NA	0	1	0
9,339436945	0	0	1
11,00209984	0	1	0
NA	1	0	0
NA	0	1	0
10,45558947	0	0	0
9,771212513	0	0	1
9,251866119	0	0	1
9,409191231	0	1	0
NA	1	0	0
NA	1	0	0
10,03889219	1	0	0
10,6454249	0	1	0
NA	1	0	0
NA	1	0	0
9,991544216	0	0	1
10,00056889	1	0	0
9,277064004	1	0	0
9,277064004	1	0	0
NA	0	0	1
11,53607542	1	0	0
10,65242415	0	1	0
11,22524339	1	0	0
10,46310334	0	1	0
NA	0	1	0
NA	1	0	0
NA	1	0	0
9,409191231	0	1	0
11,52832626	0	0	1
NA	1	0	0
NA	0	1	0
11,19747472	1	0	0
NA	1	0	0
10,83958091	1	0	0
NA	0	1	0
9,494616651	1	0	0
9,848450417	0	1	0
9,704426672	0	1	0
9,794174793	0	1	0
11,51292546	1	0	0
9,586376669	1	0	0
11,03438954	1	0	0
9,653614941	1	0	0
9,937599082	1	0	0
NA	1	0	0
10,50386133	1	0	0
NA	1	0	0
10,09481014	1	0	0
NA	1	0	0
10,69507637	1	0	0
NA	1	0	0
NA	0	0	1
10,50916871	0	1	0
9,396902923	0	1	0
10,05190756	0	1	0
NA	0	1	0
NA	0	1	0
9,798127037	0	0	0
NA	0	0	0
NA	1	0	0
11,31447453	1	0	0
NA	0	1	0
NA	1	0	0
10,13197679	1	0	0
11,00209984	1	0	0
9,309914177	0	0	1
10,73639668	1	0	0
9,994241916	0	1	0
NA	0	1	0
10,46310334	0	1	0
10,38899537	0	1	0
NA	0	1	0
NA	1	0	0
10,21950195	1	0	0
NA	1	0	0
10,46027076	0	1	0
9,660013735	0	0	0
10,3829773	1	0	0
10,24288408	1	0	0
9,59096619	1	0	0
NA	1	0	0
9,722025626	1	0	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
9,358760377	0	1	0
10,81404186	0	1	0
10,04706828	0	0	1
10,60164715	0	0	1
10,59663473	0	1	0
NA	0	1	0
10,36407196	1	0	0
9,798127037	0	0	1
NA	1	0	0
9,225031921	1	0	0
9,323669057	1	0	0
NA	1	0	0
10,1266311	1	0	0
NA	1	0	0
NA	0	0	1
NA	0	0	1
11,4870947	1	0	0
NA	0	0	1
NA	0	0	1
9,328834266	1	0	0
9,70320567	1	0	0
NA	1	0	0
10,85185818	0	0	1
11,01862914	0	1	0
9,466763949	0	0	0
11,61728548	1	0	0
NA	0	1	0
11,30116686	1	0	0
11,21188794	1	0	0
9,732817848	0	1	0
9,410092464	1	0	0
NA	1	0	0
11,50967017	0	1	0
9,220290703	1	0	0
10,66352206	1	0	0
9,667765219	1	0	0
NA	1	0	0
NA	0	1	0
10,29194213	1	0	0
NA	1	0	0
10,9252188	0	1	0
10,57339169	1	0	0
9,975808214	0	0	1
10,30895266	0	1	0
9,710751957	0	0	1
9,358760377	1	0	0
9,83397669	1	0	0
9,643939319	1	0	0
11,26735735	0	1	0
NA	0	1	0
10,50089446	1	0	0
10,6454249	0	1	0
NA	0	1	0
9,502636782	0	1	0
11,6324847	1	0	0
11,29266525	1	0	0
10,48570317	1	0	0
NA	1	0	0
NA	0	1	0
11,07168809	1	0	0
9,628392596	1	0	0
10,92649588	0	1	0
10,1266311	1	0	0
10,54428825	1	0	0
NA	0	1	0
9,463586267	1	0	0
NA	1	0	0
10,86856845	0	1	0
NA	0	1	0
11,35040654	0	0	1
10,85166447	1	0	0
NA	0	1	0
9,917143879	0	0	1
11,33377488	0	0	1
NA	0	1	0
NA	1	0	0
11,58603651	0	0	0
10,858999	1	0	0
NA	1	0	0
NA	0	1	0
10,23995979	1	0	0
9,648595303	1	0	0
10,81142348	1	0	0
9,726034127	1	0	0
11,55469101	0	1	0
10,05625156	1	0	0
NA	1	0	0
NA	0	1	0
NA	1	0	0
NA	1	0	0
NA	1	0	0
NA	0	1	0
10,63103616	1	0	0
9,28126471	0	0	1
9,893437217	0	1	0
10,1064284	1	0	0
10,1064284	1	0	0
9,27799902	0	1	0
11,31630212	0	1	0
10,94876939	1	0	0
9,517236663	0	0	1
NA	0	1	0
10,1266311	1	0	0
NA	0	1	0
9,827685839	0	0	1
NA	1	0	0
NA	1	0	0
10,32744724	0	1	0
NA	0	1	0
10,60539624	0	1	0
NA	0	1	0
NA	0	1	0
NA	0	1	0
10,30895266	0	1	0
NA	0	1	0
11,48408351	0	1	0
NA	0	1	0
9,392661929	0	1	0
NA	0	1	0
9,635608107	0	1	0
10,46021345	1	0	0
11,02100337	1	0	0
NA	0	1	0
9,581903928	1	0	0
10,80567936	1	0	0
NA	1	0	0
9,46498259	1	0	0
9,753594463	0	0	1
9,717398909	0	1	0
9,61580548	0	1	0
9,694431801	0	1	0
NA	0	1	0
NA	0	1	0
9,230142999	0	1	0
NA	0	1	0
9,436997743	0	1	0
NA	0	0	1
9,61580548	1	0	0
9,392661929	1	0	0
10,49548755	1	0	0
11,47525475	1	0	0
10,20894815	0	1	0
10,1266311	1	0	0
NA	1	0	0
9,667765219	0	1	0
10,27832162	1	0	0
NA	1	0	0
NA	0	1	0
10,49703537	0	0	1
9,66516691	0	1	0
NA	0	1	0
NA	1	0	0
10,73761333	1	0	0
11,38625051	0	1	0
9,540938245	0	0	0
NA	0	0	0
9,29468152	1	0	0
10,04324949	0	1	0
10,76553327	0	1	0
10,25590344	1	0	0
10,19854238	1	0	0
9,715711145	1	0	0
9,784140795	0	1	0
10,6454249	1	0	0
9,903487553	1	0	0
NA	1	0	0
9,61580548	1	0	0
NA	0	1	0
NA	0	1	0
9,798127037	0	1	0
9,852194258	0	1	0
NA	0	1	0
10,63648025	0	1	0
9,392661929	0	1	0
9,687195476	1	0	0
NA	1	0	0
11,00589264	0	0	1
NA	0	0	1
9,372033961	0	1	0
9,546812609	0	1	0
NA	0	1	0
9,305650552	1	0	0
NA	1	0	0
9,851615143	0	0	1
10,46626975	0	1	0
NA	1	0	0
9,935325309	1	0	0
NA	1	0	0
NA	0	1	0
10,29458325	0	1	0
10,54534144	0	1	0
10,66888562	1	0	0
9,61580548	1	0	0
10,77128108	0	1	0
9,621456152	1	0	0
NA	1	0	0
11,1861976	0	1	0
9,239899174	1	0	0
11,46268425	0	0	0
NA	0	1	0
NA	0	1	0
NA	0	1	0
9,38890488	1	0	0
9,665674427	1	0	0
NA	0	1	0
11,51292546	0	1	0
9,514879561	0	1	0
NA	0	1	0
10,82637647	1	0	0
9,998706819	1	0	0
9,510444964	1	0	0
11,58742979	0	1	0
10,37349118	0	1	0
10,80035079	1	0	0
NA	1	0	0
NA	0	1	0
10,13400386	1	0	0
NA	1	0	0
NA	0	1	0
NA	0	1	0
9,323669057	1	0	0
NA	0	1	0
9,354094336	1	0	0
NA	1	0	0
9,435721418	1	0	0
9,732402628	0	1	0
NA	0	1	0
NA	0	1	0
10,91412436	1	0	0
9,862665558	1	0	0
9,639326675	0	1	0
NA	0	1	0
11,06866755	0	1	0
9,724001971	0	1	0
11,32653564	1	0	0
NA	1	0	0
NA	0	1	0
10,01663765	1	0	0
NA	1	0	0
11,30936393	1	0	0
NA	1	0	0
9,86526634	1	0	0
NA	1	0	0
10,13559085	0	0	0
9,648595303	0	1	0
11,67717639	1	0	0
11,00209984	1	0	0
10,06734808	1	0	0
NA	0	1	0
11,20638672	0	0	0
10,30895266	0	1	0
9,259130536	0	0	0
11,66540618	1	0	0
10,29231502	1	0	0
NA	1	0	0
10,37349118	1	0	0
NA	1	0	0
10,6454249	0	0	0
NA	1	0	0
NA	1	0	0
9,629182277	1	0	0
NA	1	0	0
9,312535884	0	1	0
9,910860307	1	0	0
9,699472382	1	0	0
11,62204889	1	0	0
10,49182962	0	1	0
9,798127037	0	0	1
11,47626148	0	1	0
9,259130536	0	0	1
10,46310334	0	1	0
9,220290703	1	0	0
10,16761948	0	0	1
NA	0	1	0
9,778547718	1	0	0
10,43373338	0	1	0
10,90595598	1	0	0
NA	0	0	1
NA	1	0	0
9,236008119	0	1	0
9,343033914	1	0	0
NA	0	1	0
NA	0	1	0
NA	0	0	1
NA	0	1	0
NA	0	1	0
NA	0	1	0
11,53105021	0	1	0
9,942323576	0	1	0
NA	0	0	0
9,72853875	0	0	1
11,01039864	0	0	1
10,04102964	0	1	0
9,358070484	1	0	0
9,258368341	0	1	0
NA	1	0	0
10,24835304	1	0	0
NA	1	0	0
NA	1	0	0
11,30913101	1	0	0
9,835529859	1	0	0
11,60823564	0	1	0
9,385889044	1	0	0
9,61580548	1	0	0
NA	1	0	0
11,28978191	0	1	0
11,08214255	1	0	0
NA	1	0	0
11,13377117	0	0	1
10,85849887	1	0	0
9,96697865	1	0	0
9,754813515	0	0	1
NA	0	0	1
10,22201401	1	0	0
10,04324949	0	1	0
11,39196614	1	0	0
10,22012145	1	0	0
NA	1	0	0
10,8406	1	0	0
9,211939093	0	1	0
NA	0	1	0
11,68813848	0	1	0

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	22 seconds
R Server	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time22 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309586&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

22 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309586&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309586&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	22 seconds
R Server	Big Analytics Cloud Computing Center

Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 10.2928 -0.0872558Yard[t] + 0.0122649Main[t] -0.161998Industry[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Y[t] =  +  10.2928 -0.0872558Yard[t] +  0.0122649Main[t] -0.161998Industry[t]  + e[t] \tabularnewline
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309586&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Y[t] =  +  10.2928 -0.0872558Yard[t] +  0.0122649Main[t] -0.161998Industry[t]  + e[t][/C][/ROW]
[ROW][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309586&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309586&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 10.2928 -0.0872558Yard[t] + 0.0122649Main[t] -0.161998Industry[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	+10.29	0.1119	+9.1950e+01	0	0
Yard	-0.08726	0.1142	-7.6420e-01	0.4449	0.2224
Main	+0.01226	0.1155	+1.0620e-01	0.9155	0.4577
Industry	-0.162	0.122	-1.3280e+00	0.1842	0.09212

\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) & +10.29 &  0.1119 & +9.1950e+01 &  0 &  0 \tabularnewline
Yard & -0.08726 &  0.1142 & -7.6420e-01 &  0.4449 &  0.2224 \tabularnewline
Main & +0.01226 &  0.1155 & +1.0620e-01 &  0.9155 &  0.4577 \tabularnewline
Industry & -0.162 &  0.122 & -1.3280e+00 &  0.1842 &  0.09212 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309586&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]+10.29[/C][C] 0.1119[/C][C]+9.1950e+01[/C][C] 0[/C][C] 0[/C][/ROW]
[ROW][C]Yard[/C][C]-0.08726[/C][C] 0.1142[/C][C]-7.6420e-01[/C][C] 0.4449[/C][C] 0.2224[/C][/ROW]
[ROW][C]Main[/C][C]+0.01226[/C][C] 0.1155[/C][C]+1.0620e-01[/C][C] 0.9155[/C][C] 0.4577[/C][/ROW]
[ROW][C]Industry[/C][C]-0.162[/C][C] 0.122[/C][C]-1.3280e+00[/C][C] 0.1842[/C][C] 0.09212[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309586&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309586&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	+10.29	0.1119	+9.1950e+01	0	0
Yard	-0.08726	0.1142	-7.6420e-01	0.4449	0.2224
Main	+0.01226	0.1155	+1.0620e-01	0.9155	0.4577
Industry	-0.162	0.122	-1.3280e+00	0.1842	0.09212

Multiple Linear Regression - Regression Statistics
Multiple R	0.08543
R-squared	0.007299
Adjusted R-squared	0.005564
F-TEST (value)	4.208
F-TEST (DF numerator)	3
F-TEST (DF denominator)	1717
p-value	0.005636
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.6809
Sum Squared Residuals	796.1

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R &  0.08543 \tabularnewline
R-squared &  0.007299 \tabularnewline
Adjusted R-squared &  0.005564 \tabularnewline
F-TEST (value) &  4.208 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 1717 \tabularnewline
p-value &  0.005636 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation &  0.6809 \tabularnewline
Sum Squared Residuals &  796.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309586&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C] 0.08543[/C][/ROW]
[ROW][C]R-squared[/C][C] 0.007299[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C] 0.005564[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C] 4.208[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]1717[/C][/ROW]
[ROW][C]p-value[/C][C] 0.005636[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C] 0.6809[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C] 796.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309586&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309586&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.08543
R-squared	0.007299
Adjusted R-squared	0.005564
F-TEST (value)	4.208
F-TEST (DF numerator)	3
F-TEST (DF denominator)	1717
p-value	0.005636
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.6809
Sum Squared Residuals	796.1

Menu of Residual Diagnostics
Description	Link
Histogram	Compute
Central Tendency	Compute
QQ Plot	Compute
Kernel Density Plot	Compute
Skewness/Kurtosis Test	Compute
Skewness-Kurtosis Plot	Compute
Harrell-Davis Plot	Compute
Bootstrap Plot -- Central Tendency	Compute
Blocked Bootstrap Plot -- Central Tendency	Compute
(Partial) Autocorrelation Plot	Compute
Spectral Analysis	Compute
Tukey lambda PPCC Plot	Compute
Box-Cox Normality Plot	Compute
Summary Statistics	Compute

\begin{tabular}{lllllllll}
\hline
Menu of Residual Diagnostics \tabularnewline
Description & Link \tabularnewline
Histogram & Compute \tabularnewline
Central Tendency & Compute \tabularnewline
QQ Plot & Compute \tabularnewline
Kernel Density Plot & Compute \tabularnewline
Skewness/Kurtosis Test & Compute \tabularnewline
Skewness-Kurtosis Plot & Compute \tabularnewline
Harrell-Davis Plot & Compute \tabularnewline
Bootstrap Plot -- Central Tendency & Compute \tabularnewline
Blocked Bootstrap Plot -- Central Tendency & Compute \tabularnewline
(Partial) Autocorrelation Plot & Compute \tabularnewline
Spectral Analysis & Compute \tabularnewline
Tukey lambda PPCC Plot & Compute \tabularnewline
Box-Cox Normality Plot & Compute \tabularnewline
Summary Statistics & Compute \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309586&T=4

[TABLE]
[ROW][C]Menu of Residual Diagnostics[/C][/ROW]
[ROW][C]Description[/C][C]Link[/C][/ROW]
[ROW][C]Histogram[/C][C]Compute[/C][/ROW]
[ROW][C]Central Tendency[/C][C]Compute[/C][/ROW]
[ROW][C]QQ Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Kernel Density Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Skewness/Kurtosis Test[/C][C]Compute[/C][/ROW]
[ROW][C]Skewness-Kurtosis Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Harrell-Davis Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Bootstrap Plot -- Central Tendency[/C][C]Compute[/C][/ROW]
[ROW][C]Blocked Bootstrap Plot -- Central Tendency[/C][C]Compute[/C][/ROW]
[ROW][C](Partial) Autocorrelation Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Spectral Analysis[/C][C]Compute[/C][/ROW]
[ROW][C]Tukey lambda PPCC Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Box-Cox Normality Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Summary Statistics[/C][C]Compute[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309586&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309586&T=4

As an alternative you can also use a QR Code:

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

Menu of Residual Diagnostics
Description	Link
Histogram	Compute
Central Tendency	Compute
QQ Plot	Compute
Kernel Density Plot	Compute
Skewness/Kurtosis Test	Compute
Skewness-Kurtosis Plot	Compute
Harrell-Davis Plot	Compute
Bootstrap Plot -- Central Tendency	Compute
Blocked Bootstrap Plot -- Central Tendency	Compute
(Partial) Autocorrelation Plot	Compute
Spectral Analysis	Compute
Tukey lambda PPCC Plot	Compute
Box-Cox Normality Plot	Compute
Summary Statistics	Compute

Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted RESET test data: mylm RESET = 0, df1 = 2, df2 = 1715, p-value = 1
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors RESET test data: mylm RESET = 0, df1 = 6, df2 = 1711, p-value = 1
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components RESET test data: mylm RESET = 0, df1 = 2, df2 = 1715, p-value = 1

\begin{tabular}{lllllllll}
\hline
Ramsey RESET F-Test for powers (2 and 3) of fitted values \tabularnewline
> reset_test_fitted
	RESET test
data:  mylm
RESET = 0, df1 = 2, df2 = 1715, p-value = 1
 \tabularnewline
Ramsey RESET F-Test for powers (2 and 3) of regressors \tabularnewline
> reset_test_regressors
	RESET test
data:  mylm
RESET = 0, df1 = 6, df2 = 1711, p-value = 1
 \tabularnewline
Ramsey RESET F-Test for powers (2 and 3) of principal components \tabularnewline
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 0, df1 = 2, df2 = 1715, p-value = 1
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309586&T=5

[TABLE]
[ROW][C]Ramsey RESET F-Test for powers (2 and 3) of fitted values[/C][/ROW]
[ROW][C]> reset_test_fitted
	RESET test
data:  mylm
RESET = 0, df1 = 2, df2 = 1715, p-value = 1
[/C][/ROW]
[ROW][C]Ramsey RESET F-Test for powers (2 and 3) of regressors[/C][/ROW]
[ROW][C]> reset_test_regressors
	RESET test
data:  mylm
RESET = 0, df1 = 6, df2 = 1711, p-value = 1
[/C][/ROW]
[ROW][C]Ramsey RESET F-Test for powers (2 and 3) of principal components[/C][/ROW]
[ROW][C]> reset_test_principal_components
	RESET test
data:  mylm
RESET = 0, df1 = 2, df2 = 1715, p-value = 1
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309586&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309586&T=5

As an alternative you can also use a QR Code:

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

Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted RESET test data: mylm RESET = 0, df1 = 2, df2 = 1715, p-value = 1
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors RESET test data: mylm RESET = 0, df1 = 6, df2 = 1711, p-value = 1
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components RESET test data: mylm RESET = 0, df1 = 2, df2 = 1715, p-value = 1

Variance Inflation Factors (Multicollinearity)
> vif Yard Main Industry 12.050065 10.980417 5.620632

\begin{tabular}{lllllllll}
\hline
Variance Inflation Factors (Multicollinearity) \tabularnewline
> vif
     Yard      Main  Industry 
12.050065 10.980417  5.620632 
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309586&T=6

[TABLE]
[ROW][C]Variance Inflation Factors (Multicollinearity)[/C][/ROW]
[ROW][C]> vif
     Yard      Main  Industry 
12.050065 10.980417  5.620632 
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309586&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309586&T=6

As an alternative you can also use a QR Code:

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

Variance Inflation Factors (Multicollinearity)
> vif Yard Main Industry 12.050065 10.980417 5.620632

Figure 1

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Figure 2

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = 0 ; par5 = 0 ; par6 = 12 ;

Parameters (R input):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = 0 ; par5 = 0 ; par6 = 12 ;

R code (references can be found in the software module):

library(lattice)
library(lmtest)
library(car)
library(MASS)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
mywarning <- ''
par6 <- as.numeric(par6)
if(is.na(par6)) {
par6 <- 12
mywarning = 'Warning: you did not specify the seasonality. The seasonal period was set to s = 12.'
}
par1 <- as.numeric(par1)
if(is.na(par1)) {
par1 <- 1
mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.'
}
if (par4=='') par4 <- 0
par4 <- as.numeric(par4)
if (!is.numeric(par4)) par4 <- 0
if (par5=='') par5 <- 0
par5 <- as.numeric(par5)
if (!is.numeric(par5)) par5 <- 0
x <- na.omit(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'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'Seasonal Differences (s)'){
(n <- n - par6)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-Bs)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+par6,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'First and Seasonal Differences (s)'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
(n <- n - par6)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-Bs)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+par6,j] - x[i,j]
}
}
x <- x2
}
if(par4 > 0) {
x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep='')))
for (i in 1:(n-par4)) {
for (j in 1:par4) {
x2[i,j] <- x[i+par4-j,par1]
}
}
x <- cbind(x[(par4+1):n,], x2)
n <- n - par4
}
if(par5 > 0) {
x2 <- array(0, dim=c(n-par5*par6,par5), dimnames=list(1:(n-par5*par6), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep='')))
for (i in 1:(n-par5*par6)) {
for (j in 1:par5) {
x2[i,j] <- x[i+par5*par6-j*par6,par1]
}
}
x <- cbind(x[(par5*par6+1):n,], x2)
n <- n - par5*par6
}
if (par2 == 'Include Seasonal Dummies'){
x2 <- array(0, dim=c(n,par6-1), dimnames=list(1:n, paste('M', seq(1:(par6-1)), sep ='')))
for (i in 1:(par6-1)){
x2[seq(i,n,par6),i] <- 1
}
x <- cbind(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[n,]))
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
print(x)
(k <- length(x[n,]))
head(x)
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$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
sresid <- studres(mylm)
hist(sresid, freq=FALSE, main='Distribution of Studentized Residuals')
xfit<-seq(min(sresid),max(sresid),length=40)
yfit<-dnorm(xfit)
lines(xfit, yfit)
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqPlot(mylm, main='QQ Plot')
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
print(z)
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$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, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$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.row.start(a)
a<-table.element(a, mywarning)
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,'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$coefficients)[i],header=TRUE)
a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' '))
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,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a,formatC(signif(mysum$sigma,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
myr <- as.numeric(mysum$resid)
myr
a <-table.start()
a <- table.row.start(a)
a <- table.element(a,'Menu of Residual Diagnostics',2,TRUE)
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'Description',1,TRUE)
a <- table.element(a,'Link',1,TRUE)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Histogram',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_histogram.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Central Tendency',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_centraltendency.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'QQ Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_fitdistrnorm.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Kernel Density Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_density.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Skewness/Kurtosis Test',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_skewness_kurtosis.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Skewness-Kurtosis Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_skewness_kurtosis_plot.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Harrell-Davis Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_harrell_davis.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Bootstrap Plot -- Central Tendency',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_bootstrapplot1.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Blocked Bootstrap Plot -- Central Tendency',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_bootstrapplot.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'(Partial) Autocorrelation Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_autocorrelation.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Spectral Analysis',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_spectrum.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Tukey lambda PPCC Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_tukeylambda.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Box-Cox Normality Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_boxcoxnorm.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'Summary Statistics',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_summary1.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable7.tab')
if(n < 200) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,formatC(signif(x[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' '))
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,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' '))
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,signif(numsignificant1,6))
a<-table.element(a,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' '))
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,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
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,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
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')
}
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of fitted values',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
reset_test_fitted <- resettest(mylm,power=2:3,type='fitted')
a<-table.element(a,paste('',RC.texteval('reset_test_fitted'),'
',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of regressors',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
reset_test_regressors <- resettest(mylm,power=2:3,type='regressor')
a<-table.element(a,paste('',RC.texteval('reset_test_regressors'),'
',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of principal components',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
reset_test_principal_components <- resettest(mylm,power=2:3,type='princomp')
a<-table.element(a,paste('',RC.texteval('reset_test_principal_components'),'
',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable8.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Variance Inflation Factors (Multicollinearity)',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
vif <- vif(mylm)
a<-table.element(a,paste('',RC.texteval('vif'),'
',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable9.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code