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A indispensable guide to understanding and designing modernexperiments
The tools and techniques of Design of Experiments (DOE) allowresearchers to successfully collect, analyze, and interpret dataacross a wide array of disciplines. Statistical Analysis ofDesigned Experiments provides a modern and balanced treatment ofDOE methodology with thorough coverage of the underlying theory andstandard designs of experiments, guiding the reader throughapplications to research in various fields such as engineering, medicine, business, and the social sciences.
The book supplies a foundation for the subject, beginning withbasic concepts of DOE and a review of elementary normal theorystatistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in acomprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for itsanalysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesistests.
Numerous theoretical and applied exercises are provided in eachchapter, and answers to selected exercises are included at the endof the book. An appendix features three case studies thatillustrate the challenges often encountered in real-worldexperiments, such as randomization, unbalanced data, and outliers. Minitab® software is used to perform analyses throughout thebook, and an accompanying FTP site houses additional exercises anddata sets.
With its breadth of real-world examples and accessible treatmentof both theory and applications, Statistical Analysis of DesignedExperiments is a valuable book for experimental design courses atthe upper-undergraduate and graduate levels. It is also anindispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge ofDOE.
The tools and techniques of Design of Experiments (DOE) allowresearchers to successfully collect, analyze, and interpret dataacross a wide array of disciplines. Statistical Analysis ofDesigned Experiments provides a modern and balanced treatment ofDOE methodology with thorough coverage of the underlying theory andstandard designs of experiments, guiding the reader throughapplications to research in various fields such as engineering, medicine, business, and the social sciences.
The book supplies a foundation for the subject, beginning withbasic concepts of DOE and a review of elementary normal theorystatistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in acomprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for itsanalysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesistests.
Numerous theoretical and applied exercises are provided in eachchapter, and answers to selected exercises are included at the endof the book. An appendix features three case studies thatillustrate the challenges often encountered in real-worldexperiments, such as randomization, unbalanced data, and outliers. Minitab® software is used to perform analyses throughout thebook, and an accompanying FTP site houses additional exercises anddata sets.
With its breadth of real-world examples and accessible treatmentof both theory and applications, Statistical Analysis of DesignedExperiments is a valuable book for experimental design courses atthe upper-undergraduate and graduate levels. It is also anindispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge ofDOE.
