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Statistics for Experimenters: Design, Innovation, and Discovery, 2nd… (original 1978; édition 2005)
par George E. P. Box (Auteur)
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Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building par George E. P. Box (1978)
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A Classic adapted to modern times Rewritten and updated, this new edition of Statistics forExperimenters adopts the same approaches as the landmark FirstEdition by teaching with examples, readily understood graphics, andthe appropriate use of computers. Catalyzing innovation, problemsolving, and discovery, the Second Edition provides experimenterswith the scientific and statistical tools needed to maximize theknowledge gained from research data, illustrating how these toolsmay best be utilized during all stages of the investigativeprocess. The authors? practical approach starts with aproblem that needs to be solved and then examines the appropriatestatistical methods of design and analysis. Providing even greater accessibility for its users, the SecondEdition is thoroughly revised and updated to reflect the changes intechniques and technologies since the publication of the classicFirst Edition. Among the new topics included are: Graphical Analysis of Variance Computer Analysis of Complex Designs Simplification by transformation Hands-on experimentation using Response Service Methods Further development of robust product and process design usingsplit plot arrangements and minimization of error transmission Introduction to Process Control, Forecasting and TimeSeries Illustrations demonstrating how multi-response problems can besolved using the concepts of active and inert factor spaces andcanonical spaces Bayesian approaches to model selection and sequentialexperimentation An appendix featuring Quaquaversal quotes from a variety ofsources including noted statisticians and scientists to famousphilosophers is provided to illustrate key concepts and enliven thelearning process. All the computations in the Second Edition can be done utilizingthe statistical language R. Functions for displaying ANOVA andlamba plots, Bayesian screening, and model building are allincluded and R packages are available online. All theses topics canalso be applied utilizing easy-to-use commercial softwarepackages. Complete with applications covering the physical, engineering,biological, and social sciences, Statistics for Experimenters isdesigned for individuals who must use statistical approaches toconduct an experiment, but do not necessarily have formal trainingin statistics. Experimenters need only a basic understanding ofmathematics to master all the statistical methods presented. Thistext is an essential reference for all researchers and is a highlyrecommended course book for undergraduate and graduatestudents.
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Classification décimale de Melvil (CDD)001.424 — Information Computing and Information Knowledge Research Research methods [formerly : Operations research]
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