000			03551nam a2200661 i 4500
001			11206360
003			CaPaEBR
005			20241023114845.0
006			m eo d
007			cr cn |||m|||a
008			160512s2016 nyu foab 001 0 eng d
020			_a9781631574443 _qe-book
035			_a(EBC)4518807
035			_a(OCoLC)949862466
035			_a(CaBNVSL)swl00406484
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050		4	_aHB137
100	1		_aNaghshpour, Shahdad., _eauthor.
245	1	0	_aRegression for economics / _cShahdad Naghshpour.
250			_aSecond edition.
264		1	_aNew York, New York (222 East 46th Street, New York, NY 10017) : _bBusiness Expert Press, _c[(c)2016.]
300			_a1 online resource (xix, 166 pages)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_adata file _2rda
490	1		_aEconomics collection, _x2163-7628
504			_aIncludes bibliographical references (page [161.) and index.
505	0		_a1. The concept of regression -- _t2. The method of least squares -- _t3. Simple linear regression using software packages -- _t4. Multiple regression -- _t5. Goodness of fit -- _t6. Regression coefficients -- _t7. Causality: correlation is not causality -- _t8. Qualitative variables in regression -- _t9. Pitfalls of regression analysis -- _tAppendix -- _tGlossary of terms -- _tNotes -- _tReferences -- _tIndex.
506			_aAccess restricted to authorized users and institutions.
520	3		_aThe concept of regression was introduced by Legendre in 1805 and advanced by Gauss in 1809. The term was popularized after Galton's 1886 article. Contribution of R. A. Fisher in the early 20th century was instrumental to the spread of the method to every scientific branch. Regression analysis, used in economics and many other fields, is now the most commonly used statistical method. Although few would characterize this technique as simple, regression is in fact both simple and elegant. The complexity that many attribute to regression analysis is often a reflection of their lack of familiarity with the language of mathematics. But regression analysis can be understood even without the mastery of sophisticated mathematical concepts. This book provides the foundation of regression analysis in a way that is easy to comprehend. All the examples are from economics and in almost all the examples real data are used to show the application of the method.
530			_a2 _ub
530			_aAlso available in printing.
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat reader.
588			_aTitle from PDF title page (viewed on May 12, 2016).
650		0	_aEconomics _xStatistical methods.
650		0	_aRegression analysis.
653			_aanalysis
653			_acausality
653			_aceteris paribus
653			_acoefficient of determination
653			_acontrol variables
653			_aerror
653			_agoodness of fit
653			_ainference
653			_amisspecification
653			_amodel
653			_aproxy variables
653			_aregression
653			_aspurious regression
653			_aStata
655		0	_a[genre]
776	0	8	_iPrint version: _z9781631574436
830		0	_aEconomics collection. _x2163-7628
856	4	0	_uhttps://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000489.html
942			_2lcc _bCIU _cOB _eBEP _QOL _zBEP11206360
999			_c74202 _d74202
902			_c1 _dCynthia Snell