Synopses & Reviews
A novel exposition of the analysis of variance and regression. The key feature here is that these tools are viewed in their natural mathematical setting - the geometry of finite dimensions. This is because geometry clarifies the basic statistics and unifies the many aspects of analysing variance and regression.
Review
"This is an interesting attempt to present analysis of variance and related topics in an informative way." (Biometrics)
Synopsis
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.
Description
Includes bibliographical references (p. [550]-551) and index.
Table of Contents
Basic Ideas: Introduction: The Geometric Tool Kit. The Statistical Tool Kit. Tool Kits At Work.- Introduction to Analysis of Variance: Single Population Questions. Questions About Two Populations. Questions About Several Populations. Orthogonal Contrasts: Class Comparisons. Factorial Contrasts. Polynomial Contrasts. Pairwise Comparisons.- Introducing Blocking: Randomized Block Design. Latin Square Design. Split Plot Design.- Fundamentals of Regression: Simple Regression.- Polynomial Regression.- Analysis of Covariance.- General Summary. Appendices: A: Unequal Replications. Two Populations. B: Unequal Replications. Several Populations. C: Alternative Factorial Notation. D: Regression Through the Origin. E: Confidence Intervals. T: Statistical Tables. References. Index.