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Applied Regression Analysis

A Research Tool

  • Textbook
  • © 1998
  • Latest edition


Part of the book series: Springer Texts in Statistics (STS)

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About this book

Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool.
Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to statistical methods and a thoeretical linear models course.
Applied Regression Analysis emphasizes the concepts and the analysis of data sets. It provides a review of the key concepts in simple linear regression, matrix operations, and multiple regression. Methods and criteria for selecting regression variables and geometric interpretations are discussed. Polynomial, trigonometric, analysis of variance, nonlinear, time series, logistic, random effects, and mixed effects models are also discussed. Detailed case studies and exercises based on real data sets are used to reinforce the concepts. The data sets used in the book are available on the Internet.

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Table of contents (19 chapters)


From the reviews:


"Virtually all data taken require some form of modeling and curve fitting. This excellent book will give the reader a very clear understanding of the techniques used for fitting most types of data; and, because it covers all the significant areas, it can serve as a reference source. Students and especially researchers involved with data taking and modeling will greatly benefit from this book."

Editors and Affiliations

  • Department of Statistics, North Carolina State University, Raleigh, USA

    John O. Rawlings, Sastry G. Pantula, David A. Dickey

Bibliographic Information

  • Book Title: Applied Regression Analysis

  • Book Subtitle: A Research Tool

  • Editors: John O. Rawlings, Sastry G. Pantula, David A. Dickey

  • Series Title: Springer Texts in Statistics

  • DOI:

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 1998

  • Hardcover ISBN: 978-0-387-98454-4Published: 23 April 1998

  • Softcover ISBN: 978-1-4757-7155-8Published: 23 March 2013

  • eBook ISBN: 978-0-387-22753-5Published: 31 March 2006

  • Series ISSN: 1431-875X

  • Series E-ISSN: 2197-4136

  • Edition Number: 2

  • Number of Pages: XVIII, 660

  • Additional Information: Originally published by Wadsworth, 1989

  • Topics: Probability Theory and Stochastic Processes, Applications of Mathematics, Statistical Theory and Methods

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