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The Statistical Analysis of Discrete Data

  • Thomas J. Santner
  • Diane E. Duffy

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

Table of contents

  1. Front Matter
    Pages i-xii
  2. Thomas J. Santner, Diane E. Duffy
    Pages 1-20
  3. Thomas J. Santner, Diane E. Duffy
    Pages 21-112
  4. Thomas J. Santner, Diane E. Duffy
    Pages 113-141
  5. Thomas J. Santner, Diane E. Duffy
    Pages 142-203
  6. Thomas J. Santner, Diane E. Duffy
    Pages 204-286
  7. Back Matter
    Pages 287-372

About this book

Introduction

The Statistical Analysis of Discrete Data provides an introduction to cur­ rent statistical methods for analyzing discrete response data. The book can be used as a course text for graduate students and as a reference for researchers who analyze discrete data. The book's mathematical prereq­ uisites are linear algebra and elementary advanced calculus. It assumes a basic statistics course which includes some decision theory, and knowledge of classical linear model theory for continuous response data. Problems are provided at the end of each chapter to give the reader an opportunity to ap­ ply the methods in the text, to explore extensions of the material covered, and to analyze data with discrete responses. In the text examples, and in the problems, we have sought to include interesting data sets from a wide variety of fields including political science, medicine, nuclear engineering, sociology, ecology, cancer research, library science, and biology. Although there are several texts available on discrete data analysis, we felt there was a need for a book which incorporated some of the myriad recent research advances. Our motivation was to introduce the subject by emphasizing its ties to the well-known theories of linear models, experi­ mental design, and regression diagnostics, as well as to describe alterna­ tive methodologies (Bayesian, smoothing, etc. ); the latter are based on the premise that external information is available. These overriding goals, to­ gether with our own experiences and biases, have governed our choice of topics.

Keywords

Logistic Regression calculus linear algebra statistical analysis statistics

Authors and affiliations

  • Thomas J. Santner
    • 1
  • Diane E. Duffy
    • 2
  1. 1.School of Operations Research and Industrial EngineeringCornell UniversityIthacaUSA
  2. 2.Bell Communications ResearchMorristownUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-1017-7
  • Copyright Information Springer-Verlag New York Inc. 1989
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-6986-1
  • Online ISBN 978-1-4612-1017-7
  • Series Print ISSN 1431-875X
  • Buy this book on publisher's site