000			04146nam a2200841 i 4500
001			10594649
003			CaPaEBR
005			20241023114827.0
006			m eo d
007			cr cn |||m|||a
008			120829s2012 nyu foa 001 0 eng d
020			_a9781606494356 _qelectronic bk.
024	7		_a10.4128/9781606494356 _2doi
035			_a(OCoLC)808991413
035			_a(CaBNVSL)swl00401166
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050		4	_aQA278.2
100	1		_aWilson, J. Holton, _d1942-, _eauthor
245	1	0	_aRegression analysis : _bunderstanding and building business and economic models using Excel / _cJ. Holton Wilson, Barry P. Keating, and Mary Beal-Hodges.
250			_a1st ed.
264		1	_a[New York, N.Y.] (222 East 46th Street, New York, NY 10017) : _bBusiness Expert Press, _c[(c)2012.]
300			_a1 electronic text (179 pages) : _bdigital file.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_adata file _2rda
490	1		_aQuantitative approaches to decision making collection, _x2163-9582
500			_aPart of: 2012 digital library.
500			_aIncludes index.
505	0		_a1. Background issues for regression analysis -- _t2. Introduction to regression analysis -- _t3. The ordinary least squares (OLS) regression model -- _t4. Evaluation of ordinary least squares (OLS) regression models -- _t5. Point and interval estimates from a regression model -- _t6. Multiple linear regression -- _t7. A market share multiple regression model -- _t8. Qualitative events and seasonality in multiple regression models -- _t9. Nonlinear regression models -- _t10. Abercrombie and Fitch Company regression case study -- _t11. The formal ordinary least squares (OLS) regression model -- _tAppendix. Some statistical background -- _tIndex.
506			_aAccess restricted to authorized users and institutions.
520	3		_aThis book covers essential elements of building and understanding regression models in a business/economic context in an intuitive manner. The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for almost everyone engaged in the field. It is especially useful for those engaged in working with numbers - preparing forecasts, budgeting, estimating the effects of business decisions, and any of the forms of analytics that have recently become so useful.
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 t.p. (viewed on August 29, 2012).
630	0	0	_aMicrosoft Excel (Computer file)
650		0	_aRegression analysis.
650		0	_aEconometric models.
653			_aRegression analysis
653			_aordinary least squares (OLS)
653			_atime-series data
653			_across-sectional data,
653			_adependent variables
653			_aindependent variables
653			_apoint estimates
653			_ainterval estimates
653			_ahypothesis testing
653			_astatistical significance
653			_aconfidence level
653			_asignificance level
653			_ap-value
653			_aR-squared
653			_acoefficient of determination
653			_amulticollinearity
653			_acorrelation
653			_aserial correlation
653			_aseasonality
653			_aqualitative events
653			_adummy variables
653			_anon-linear regression models
653			_amarket share regression model
653			_aAbercrombie & Fitch Co.
655		0	_a[genre]
700	1		_aKeating, Barry P.
700	1		_aBeal-Hodges, Mary.
776	0	8	_iPrint version: _z9781606494349
830		0	_a2012 digital library.
830		0	_aQuantitative approaches to decision making collection. _x2163-9582
856	4	0	_uhttps://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000138.html
942			_2lcc _bCIU _cOB _eBEP _QOL _zBEP10594649
999			_c74201 _d74201
902			_c1 _dCynthia Snell