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Statistical Methods: The Geometric Approach

  • Textbook
  • © 1991

Overview

Authors:
  1. David J. Saville

    1. AgResearch, Biometrics Unit, Lincoln, New Zealand

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  2. Graham R. Wood

    1. Department of Mathematics, University of Canterbury, Christchurch, New Zealand

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    You can also search for this author in PubMed   Google Scholar

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

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Table of contents (18 chapters)

  1. Front Matter

    Pages i-xv
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  2. Basic Ideas

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • David J. Saville, Graham R. Wood
      Pages 3-9

    3. The Geometric Tool Kit

      • David J. Saville, Graham R. Wood
      Pages 10-38

    4. The Statistical Tool Kit

      • David J. Saville, Graham R. Wood
      Pages 39-54

    5. Tool Kits At Work

      • David J. Saville, Graham R. Wood
      Pages 55-64

  3. Introduction to Analysis of Variance

    1. Front Matter

      Pages 65-65
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    2. Single Population Questions

      • David J. Saville, Graham R. Wood
      Pages 67-96

    3. Questions About Two Populations

      • David J. Saville, Graham R. Wood
      Pages 97-132

    4. Questions About Several Populations

      • David J. Saville, Graham R. Wood
      Pages 133-151

  4. Orthogonal Contrasts

    1. Front Matter

      Pages 153-153
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    2. Class Comparisons

      • David J. Saville, Graham R. Wood
      Pages 155-186

    3. Factorial Contrasts

      • David J. Saville, Graham R. Wood
      Pages 187-223

    4. Polynomial Contrasts

      • David J. Saville, Graham R. Wood
      Pages 224-270

    5. Pairwise Comparisons

      • David J. Saville, Graham R. Wood
      Pages 271-295

  5. Introducing Blocking

    1. Front Matter

      Pages 297-297
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    2. Randomized Block Design

      • David J. Saville, Graham R. Wood
      Pages 299-339

    3. Latin Square Design

      • David J. Saville, Graham R. Wood
      Pages 340-353

    4. Split Plot Design

      • David J. Saville, Graham R. Wood
      Pages 354-379

  6. Fundamentals of Regression

    1. Front Matter

      Pages 381-381
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Keywords

About this book

This book is a novel exposition of the traditional workhorses of statistics: analysis of variance and regression. The key feature is that these tools are viewed in their natural mathematical setting, the geometry of finite dimensions. The Authors To introduce ourselves, Dave Saville is a practicing statistician working in agricultural research; Graham Wood is a university lecturer involved in the teaching of statistical methods. Each of us has worked for sixteen years in our current field. Features of the Book People like pictures. One picture can present a set of ideas at a glance, while a series of pictures, each building on the last, can unify a wealth of ideas. Such a series we present in this text by means of a systematic geometric approach to the presentation of the theory of basic statistical methods. This approach fills the void between the traditional extremes of the "cookbook" approach and the "matrix algebra" approach, providing an elementary but at the same time rigorous view of the subject. It combines the virtues of the traditional methods, while avoiding their vices.

Reviews

"This is an interesting attempt to present analysis of variance and related topics in an informative way."
(Biometrics)

Authors and Affiliations

  • AgResearch, Biometrics Unit, Lincoln, New Zealand

    David J. Saville

  • Department of Mathematics, University of Canterbury, Christchurch, New Zealand

    Graham R. Wood

Bibliographic Information

  • Book Title: Statistical Methods: The Geometric Approach

  • Authors: David J. Saville, Graham R. Wood

  • Series Title: Springer Texts in Statistics

  • DOI: https://doi.org/10.1007/978-1-4612-0971-3

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 1991

  • Hardcover ISBN: 978-0-387-97517-7Published: 28 May 1991

  • Softcover ISBN: 978-1-4612-6965-6Published: 27 September 2012

  • eBook ISBN: 978-1-4612-0971-3Published: 06 December 2012

  • Series ISSN: 1431-875X

  • Series E-ISSN: 2197-4136

  • Edition Number: 1

  • Number of Pages: XV, 561

  • Topics: Applications of Mathematics

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