000			05103nam a2200697 i 4500
001			11129159
003			CaPaEBR
005			20240726104649.0
008			160124s2016 nyu foa 001 0 eng d
020			_a9781631573866 _q((electronic)l(electronic)ctronic)-book
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050	0	4	_aQA278 _b.R447 2016
100	1		_aWilson, J. Holton, _d1942-, _e1
245	1	0	_aRegression analysis : _bunderstanding and building business and economic models using Excel / _cJ. Holton Wilson, Barry P. Keating, and Mary Beal.
250			_aSecond edition.
260			_aNew York, New York (222 East 46th Street, New York, NY 10017) : _bBusiness Expert Press, _c(c)2016.
300			_a1 online resource (vi, 194 pages)
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,
505	0	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 and jewelry sales regression case studies -- _t11. The formal ordinary least squares (OLS) regression model -- _tAppendix. Some statistical background -- _tIndex.
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. This book is a nontheoretical treatment that is accessible to readers with even a limited statistical background. This book specifically does not cover the theory of regression; it is designed to teach the correct use of regression, while advising the reader of its limitations and teaching about common pitfalls. It is useful for business professionals, MBA students, and others with a desire to understand regression analysis without having to work through tedious mathematical/statistical theory. This book describes exactly how regression models are developed and evaluated. Real data are used, instead of contrived textbook-like problems. The data used in the book are the kind of data managers are faced with in the real world. Included are instructions for using Microsoft Excel to build business/economic models using regression analysis with an appendix using screen shots and step-by-step instructions. Completing this book will allow you to understand and build basic business/economic models using regression analysis. You will be able to interpret the output of those models and you will be able to evaluate the models for accuracy and shortcomings. Even if you never build a model yourself, at some point in your career it is likely that you will find it necessary to interpret one; this book will make that possible.
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 January 24, 2016).
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			_anonlinear regression models
653			_amarket share regression model
653			_aAbercrombie & Fitch Co.
700	1		_aKeating, Barry P., _e1
700	1		_aBeal-Hodges, Mary., _e1
856	4	1	_uhttps://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000445.html _zClick here to access this RESOURCE ONLINE | Login using your my.ciu username & password
942			_c1 _D _eBEP _hQA278.2 _m(c)2016 _QOB _R _x _8NFIC _dCynthia Snell
999			_c74200 _d74200
902			_a1 _bCynthia Snell _c1 _dCynthia Snell