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Statistics, Mathematical Modeling - Science
A First Course in the Design of Experiments by Donald Weber β€” book cover

A First Course in the Design of Experiments

by Donald Weber, John H. Skillings
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Overview

Most texts on experimental design fall into one of two distinct categories. There are theoretical works with few applications and minimal discussion on design, and there are methods books with limited or no discussion of the underlying theory. Furthermore, most of these tend to either treat the analysis of each design separately with little attempt to unify procedures, or they will integrate the analysis for the designs into one general technique.

A First Course in the Design of Experiments: A Linear Models Approach stands apart. It presents theory and methods, emphasizes both the design selection for an experiment and the analysis of data, and integrates the analysis for the various designs with the general theory for linear models.

The authors begin with a general introduction then lead students through the theoretical results, the various design models, and the analytical concepts that will enable them to analyze virtually any design. Rife with examples and exercises, the text also encourages using computers to analyze data. The authors use the SAS software package throughout the book, but also demonstrate how any regression program can be used for analysis.

With its balanced presentation of theory, methods, and applications and its highly readable style, A First Course in the Design of Experiments proves ideal as a text for a beginning graduate or upper-level undergraduate course in the design and analysis of experiments.

"...ideal as a reference or text this book offers a balanced treatment of theory, methods & applications, emphasizing both design selection & data analysis & including numerous examples & exercises."

Synopsis

Most texts on experimental design fall into one of two distinct categories. There are theoretical works with few applications and minimal discussion on design, and there are methods books with limited or no discussion of the underlying theory. Furthermore, most of these tend to either treat the analysis of each design separately with little attempt to unify procedures, or they will integrate the analysis for the designs into one general technique.

A First Course in the Design of Experiments: A Linear Models Approach stands apart. It presents theory and methods, emphasizes both the design selection for an experiment and the analysis of data, and integrates the analysis for the various designs with the general theory for linear models.

The authors begin with a general introduction then lead students through the theoretical results, the various design models, and the analytical concepts that will enable them to analyze virtually any design. Rife with examples and exercises, the text also encourages using computers to analyze data. The authors use the SAS software package throughout the book, but also demonstrate how any regression program can be used for analysis.

With its balanced presentation of theory, methods, and applications and its highly readable style, A First Course in the Design of Experiments proves ideal as a text for a beginning graduate or upper-level undergraduate course in the design and analysis of experiments.

Booknews

A textbook for a one-semester undergraduate course for students who have completed a course in mathematical statistics and have had at least some exposure to matrix algebra, though the basics of that are appended. Weber and Skillings (both Miami U., Oxford, Ohio) find that most texts and courses either totally emphasize method, which neglects the distribution theory so central to the statistics course, or totally emphasize theory, and so neglect important applications in regression and design of experiments. So they use the linear models approach to include both, which also allows them to obtain the traditional analysis of variance, adjusted and unadjusted sum of squares, and the f-test; and unlike the analysis of variance approach, uses essentially the same procedures whether the data are from designed, undesigned, unbalanced, or missing cells experiments. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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Editorials

Booknews

A textbook for a one-semester undergraduate course for students who have completed a course in mathematical statistics and have had at least some exposure to matrix algebra, though the basics of that are appended. Weber and Skillings (both Miami U., Oxford, Ohio) find that most texts and courses either totally emphasize method, which neglects the distribution theory so central to the statistics course, or totally emphasize theory, and so neglect important applications in regression and design of experiments. So they use the linear models approach to include both, which also allows them to obtain the traditional analysis of variance, adjusted and unadjusted sum of squares, and the f-test; and unlike the analysis of variance approach, uses essentially the same procedures whether the data are from designed, undesigned, unbalanced, or missing cells experiments. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Book Details

Published
January 1, 2000
Publisher
Taylor & Francis, Inc.
Pages
696
Format
Hardcover
ISBN
9780849396717

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