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© 1998

Applied Regression Analysis

A Research Tool

  • John O. Rawlings
  • Sastry G. Pantula
  • David A. Dickey
Textbook

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

Table of contents

About this book

Introduction

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.

Keywords

Analysis of variance Excel Regression analysis SAS STATISTICA Time series linear regression

Editors and affiliations

  • John O. Rawlings
    • 1
  • Sastry G. Pantula
    • 1
  • David A. Dickey
    • 1
  1. 1.Department of StatisticsNorth Carolina State UniversityRaleighUSA

Bibliographic information

  • Book Title Applied Regression Analysis
  • Book Subtitle A Research Tool
  • Authors John O. Rawlings
    Sastry G. Pantula
    David A. Dickey
  • Series Title Springer Texts in Statistics
  • DOI https://doi.org/10.1007/b98890
  • Copyright Information Springer-Verlag New York, Inc. 1998
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Hardcover ISBN 978-0-387-98454-4
  • Softcover ISBN 978-1-4757-7155-8
  • eBook ISBN 978-0-387-22753-5
  • Series ISSN 1431-875X
  • Edition Number 2
  • Number of Pages XVIII, 660
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Additional Information Originally published by Wadsworth, 1989
  • Topics Probability Theory and Stochastic Processes
    Applications of Mathematics
    Statistical Theory and Methods
  • Buy this book on publisher's site
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Reviews

From the reviews:

IEEE ELECTRICAL INSULATION MAGAZINE

"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."