A First Course in Design and Analysis of Experiments
Covers the basic topics in experimental design and analysis and is intended for graduate students and advanced undergraduates.
Tag(s): Statistics
Publication date: 01 Jan 2010
ISBN-10: 0716735105
ISBN-13: 9780716735106
Paperback: 679 pages
Views: 10,641
Type: N/A
Publisher: W. H. Freeman and Company
License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported
Post time: 26 Jun 2016 12:00:00
A First Course in Design and Analysis of Experiments
Gary W. Oehlert wrote:This text covers the basic topics in experimental design and analysis and is intended for graduate students and advanced undergraduates. Students should have had an introductory statistical methods course at about the level of Moore and McCabe’s Introduction to the Practice of Statistics (Moore and McCabe 1999) and be familiar with t-tests, p-values, confidence intervals, and the basics of regression and ANOVA. Most of the text soft-pedals theory and mathematics, but Chapter 19 on response surfaces is a little tougher sledding (eigenvectors and eigenvalues creep in through canonical analysis), and Appendix A is an introduction to the theory of linear models. I use the text in a service course for non-statisticians and in a course for first-year Masters students in statistics. The non-statisticians come from departments scattered all around the university including agronomy, ecology, educational psychology, engineering, food science, pharmacy, sociology, and wildlife.
About The Author(s)
Gary W. Oehlert, Ph.D. is a statistical consultant for Stat-Ease, Inc. He has a long list of achievements in the field of statistics, and in particular, design of experiments (DOE). Gary teaches courses in DOE in the School of Statistics at the University of Minnesota, where he is a professor of applied statistics. He has also taught at Princeton University and the University of California, Berkeley.
Gary W. Oehlert, Ph.D. is a statistical consultant for Stat-Ease, Inc. He has a long list of achievements in the field of statistics, and in particular, design of experiments (DOE). Gary teaches courses in DOE in the School of Statistics at the University of Minnesota, where he is a professor of applied statistics. He has also taught at Princeton University and the University of California, Berkeley.