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Regression analysis : understanding and building business and economic models using Excel / J. Holton Wilson, Barry P. Keating, and Mary Beal.

By: Contributor(s): Material type: TextTextSeries: Publication details: New York, New York (222 East 46th Street, New York, NY 10017) : Business Expert Press, (c)2016.Edition: Second editionDescription: 1 online resource (vi, 194 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781631573866
Subject(s): LOC classification:
  • QA278 .R447 2016
Online resources: Available additional physical forms:
Contents:
2. Introduction to regression analysis -- 3. The ordinary least squares (OLS) regression model -- 4. Evaluation of ordinary least squares (OLS) regression models -- 5. Point and interval estimates from a regression model -- 6. Multiple linear regression -- 7. A market share multiple regression model -- 8. Qualitative events and seasonality in multiple regression models -- 9. Nonlinear regression models -- 10. Abercrombie and Fitch and jewelry sales regression case studies -- 11. The formal ordinary least squares (OLS) regression model -- Appendix. Some statistical background -- Index.
Abstract: This 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.
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Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD) Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD) G. Allen Fleece Library Non-fiction QA278.2 (Browse shelf(Opens below)) Link to resource Available 11129159

1. Background issues for regression analysis -- 2. Introduction to regression analysis -- 3. The ordinary least squares (OLS) regression model -- 4. Evaluation of ordinary least squares (OLS) regression models -- 5. Point and interval estimates from a regression model -- 6. Multiple linear regression -- 7. A market share multiple regression model -- 8. Qualitative events and seasonality in multiple regression models -- 9. Nonlinear regression models -- 10. Abercrombie and Fitch and jewelry sales regression case studies -- 11. The formal ordinary least squares (OLS) regression model -- Appendix. Some statistical background -- Index.

This 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.

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