Statistics for Experimenters

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The classic adapted to modern times For many years, the First Edition of Statistics for Experimenters has been a premier guide and reference for the application of statistical methods, especially as applied to experimental design. Rewritten and updated, this new edition of Statistics for Experimenters adopts the same approach as the landmark First Edition by demonstrating thoroughly worked examples, readily understood graphics, and the appropriate use of computers. Catalyzing innovation, problem solving, and discovery, the Second Edition provides experimenters with the scientific and statistical tools needed to maximize the knowledge gained from research data. The authors' practical approach starts with a problem that needs to be solved and then illustrates the statistical methods best utilized in all stages of design and analysis. Providing even greater accessibility for its users, the Second Edition reflects the changes in techniques and technologies since the publication of the classic First Edition. Among the new topics included are: * Graphical analysis of variance * Computer analysis of complex designs * Simplification by transformation * Hands-on experimentation using response surface methods * Further development of robust product and process design using split-plot arrangements and minimization of error transmission * Introduction to process control, forecasting, and time series * Illustrations demonstrating how multiresponse problems can be solved using the concepts of active and inert factor spaces and canonical spaces * Bayesian approaches to model selection and sequential experimentation * Applications for Six Sigma initiatives in a variety of disciplines * An appendix featuring quaquaversal quotes from a variety of sources ranging from noted statisticians and scientists to famous philosophers that embellish key concepts and enliven the learning process Computations in the Second Edition can be done utilizing the statistical language R-functions for displaying ANOVA and lambda plots, Bayesian screening, and model building are all included, and R packages are available on a related FTP site. These topics can also be applied utilizing easy-to-use commercial software packages. Complete with applications covering the physical, engineering, biological, and social sciences, Statistics for Experimenters is designed for all individuals who must use statistical approaches to conduct an experiment. Experimenters need only a basic understanding of mathematics to master all the statistical methods presented. This text is an essential reference for all researchers and an invaluable course book for undergraduate and graduate students.