Beyond ANOVA: Basics of Applied Statistics, 1st Edition (Hardback) book cover

Beyond ANOVA

Basics of Applied Statistics, 1st Edition

By Rupert G. Miller, Jr.

Chapman and Hall/CRC

336 pages

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pub: 1997-01-01
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Description

Renowned statistician R.G. Miller set the pace for statistics students with Beyond ANOVA: Basics of Applied Statistics. Designed to show students how to work with a set of "real world data," Miller's text goes beyond any specific discipline, and considers a whole variety of techniques from ANOVA to empirical Bayes methods; the jackknife, bootstrap methods; and the James-Stein estimator.

This reissue of Miller's classic book has been revised by professors at Stanford University, California. As before, one of the main strengths of Beyond ANOVA is its promotion of the use of the most straightforward data analysis methods-giving students a viable option, instead of resorting to complicated and unnecessary tests.

Assuming a basic background in statistics, Beyond ANOVA is written for undergraduates and graduate statistics students. Its approach will also be valued by biologists, social scientists, engineers, and anyone who may wish to handle their own data analysis.

Table of Contents

One Sample

Normal Theory

Nonnormality

Effect

Dependence

Exercises

Two Samples

Normal Theory

Nonnormality

Unequal Variances

Dependence

Exercises

One-Way Classification

Fixed Effects

Normal Theory

Nonnormality

Unequal Variances

Dependence

Random Effects

Normal Theory

Nonnormality

Unequal Variances

Dependence

Exercises

Two-Way Classification

Fixed Effects

Normal Theory

Nonnormality

Unequal Variances

Dependence

Mixed Effects

Normal Theory

Departures from assumptions

Random Effects

Normal Theory

Departures from Assumptions

Exercises

Regression

Regression Model

Normal Linear Model

Nonlinearity

Nonnormality

Unequal Variances

Dependence

Errors-in-Variables Model

Normal Theory

Departures from Assumptions

Exercises

Ratios

Normal Theory

Departures from Assumptions

Exercises

Variances

Normal Theory

Nonnormality

Dependence

Exercises

About the Series

Chapman & Hall/CRC Texts in Statistical Science

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General