000848630 000__ 03542nam\a2200673\i\4500
000848630 001__ 848630
000848630 003__ MiAaPQ
000848630 005__ 20211106003429.0
000848630 006__ m\\\\\o\\d\\\\\\\\
000848630 007__ cr\cn\nnnunnun
000848630 008__ 160512s2016\\\\nyu\\\\\oab\\\001\0\eng\d
000848630 020__ $$z9781631574436$$qpaperback
000848630 020__ $$a9781631574443$$q(electronic bk.)
000848630 035__ $$a(MiAaPQ)EBC4518807
000848630 035__ $$a(Au-PeEL)EBL4518807
000848630 035__ $$a(CaPaEBR)ebr11206360
000848630 035__ $$a(CaONFJC)MIL919738
000848630 035__ $$a(OCoLC)950465369
000848630 040__ $$aMiAaPQ$$beng$$erda$$epn$$cMiAaPQ$$dMiAaPQ
000848630 050_4 $$aHB137$$b.N247 2016
000848630 0820_ $$a519.536$$223
000848630 1001_ $$aNaghshpour, Shahdad.,$$eauthor.
000848630 24510 $$aRegression for economics /$$cShahdad Naghshpour.
000848630 250__ $$aSecond edition.
000848630 264_1 $$aNew York, New York (222 East 46th Street, New York, NY 10017) :$$bBusiness Expert Press,$$c2016.
000848630 300__ $$a1 online resource (xix, 166 pages)
000848630 336__ $$atext$$2rdacontent
000848630 337__ $$acomputer$$2rdamedia
000848630 338__ $$aonline resource$$2rdacarrier
000848630 4901_ $$aEconomics collection,$$x2163-7628
000848630 504__ $$aIncludes bibliographical references (page [161]) and index.
000848630 5050_ $$a1. The concept of regression -- 2. The method of least squares -- 3. Simple linear regression using software packages -- 4. Multiple regression -- 5. Goodness of fit -- 6. Regression coefficients -- 7. Causality: correlation is not causality -- 8. Qualitative variables in regression -- 9. Pitfalls of regression analysis -- Appendix -- Glossary of terms -- Notes -- References -- Index.
000848630 506__ $$aAccess limited to authorized users.
000848630 5203_ $$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.
000848630 588__ $$aTitle from PDF title page (viewed on May 12, 2016).
000848630 650_0 $$aEconomics$$xStatistical methods.
000848630 650_0 $$aRegression analysis.
000848630 653__ $$aanalysis
000848630 653__ $$acausality
000848630 653__ $$aceteris paribus
000848630 653__ $$acoefficient of determination
000848630 653__ $$acontrol variables
000848630 653__ $$aerror
000848630 653__ $$agoodness of fit
000848630 653__ $$ainference
000848630 653__ $$amisspecification
000848630 653__ $$amodel
000848630 653__ $$aproxy variables
000848630 653__ $$aregression
000848630 653__ $$aspurious regression
000848630 653__ $$aStata
000848630 655_0 $$aElectronic books
000848630 77608 $$iPrint version:$$z9781631574436
000848630 830_0 $$aEconomics collection.$$x2163-7628
000848630 852__ $$bebk
000848630 85640 $$3ProQuest Ebook Central Academic Complete $$uhttps://univsouthin.idm.oclc.org/login?url=https://ebookcentral.proquest.com/lib/usiricelib-ebooks/detail.action?docID=4518807$$zOnline Access
000848630 909CO $$ooai:library.usi.edu:848630$$pGLOBAL_SET
000848630 980__ $$aBIB
000848630 980__ $$aEBOOK
000848630 982__ $$aEbook
000848630 983__ $$aOnline