2nd Edition

Sample Size Choice Charts for Experiments with Linear Models, Second Edition

By Robert E. Odeh, Martin Fox Copyright 1991
    216 Pages
    by CRC Press

    216 Pages
    by CRC Press

    A guide to testing statistical hypotheses for readers familiar with the Neyman-Pearson theory of hypothesis testing including the notion of power, the general linear hypothesis (multiple regression) problem, and the special case of analysis of variance. The second edition (date of first not mentione

    1. INTRODUCTION, 2. EXAMPLES, 3. BACKGROUND, 4. LITERATURE SURVEY

    Biography

    Robert E. Odeh is Professor of Statistics at the University of Victoria, British Columbia, Canada. He is the coauthor (with Donald B. Owen, Z. W. Birnbaum, and Lloyd Fisher) of Pocketbook of Statistical Tables and (with Donald B. Owen) of Tables for Normal Tolerance Limits, Sampling Plans, and Screening; Attribute Sampling Plans, Tables of Tests and Confidence Limits for Proportions; and Parts per Million Values for Estimating Quality Levels (all titles, Marcel Dekker, Inc.). An editorial board member of Communications in Statistics: Theory and Methods (Marcel Dekker, Inc.) and coeditor of Selected Tables in Mathematical Statistics, he is a Fellow of the Royal Statistical Society, American Statistical Association, and Institute of Mathematical Statistics, and a member of the Statistical Society of Canada and International Statistical Institute . Dr. Odeh received the Ph.D. degree (1962) in mathematics from the Carnegie Institute of Technology (now Carnegie-Mellon University) in Pittsburgh, Pennsylvania. Martin Fox is Professor of Statistics at Michigan State University, East Lansing. The author or coauthor of over 15 journal articles, he is a Fellow of the Institute of Mathematical Statistics, and a member of the American Mathematical Society, Mathematical Association of America, and American Statistical Association, among others. Dr. Fox received the AB. degree (1951) in mathematics and  Ph.D. degree (1959) in statistics from the University of California, Berkeley.