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Design of Experiments: Statistical Principles of Research Design and Analysis

Design of Experiments: Statistical Principles of Research Design and Analysis
Author: Robert O. Kuehl
ISBN 13: 9780534368340
ISBN 10: 534368344
Edition: 2
Publisher: Duxbury Press
Publication Date: 1999-08-13
Format: Hardcover
Pages: 688
List Price: $354.95

The success of comparative scientific studies, according to Dr. Robert Kuehl, depends upon effective research design that clearly defines objectives and chooses the appropriate statistical design and analysis to meet those objectives. This research design process includes development of the research hypothesis, choice of the treatment design to answer it, and choice of the experiment design that facilitates efficient data collection. To further this philosophy, Kuehl has written Statistical Principles of Research Design and Analysis. Throughout the book, worked examples (almost all of which are taken from actual research studies performed in the agricultural, biological, industrial, engineering, manufacturing, and medical sciences) are illustrated with printouts of analysis of variance tables from popular computer programs such as SAS, SPSS, MINITAB, or BMPD. The book is divided into three parts: first, it traces the role statistical science plays in the planning stages of a research study; then, it delineates treatment designs, their analyses, and interpretations in the simplest setting of completely randomized designs; and lastly, it presents development of experiments and designs from the simplest to the most complex and specialized blocking structures.


Presents principles of statistical design and analysis for comparative scientific studies to graduate students in the experimental sciences and applied statistics. Material is applications-oriented, using the results of established theory, and does not include theoretical development. Early chapters emphasize the connection between research hypotheses and treatment designs in randomized designs, and later chapters present developments of experiment designs and their analyses. Examples and exercises are based on actual research studies when possible, demonstrating applications in life and agricultural sciences and in engineering, industrial, and chemistry research. Assumes previous courses in college algebra and an introduction to statistical methods. The author is affiliated with the University of Arizona. Annotation c. Book News, Inc., Portland, OR (booknews.com)