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Modern Industrial Statistics: With Applications R, MINITAB, and JMP

Current price: $118.95
Modern Industrial Statistics: With Applications R, MINITAB, and JMP
Modern Industrial Statistics: With Applications R, MINITAB, and JMP

Barnes and Noble

Modern Industrial Statistics: With Applications R, MINITAB, and JMP

Current price: $118.95

Size: Hardcover

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is a leading reference and guide to the statistics tools widely used in industry and services. Designed to help professionals and students easily access relevant theoretical and practical information in a single volume, this standard resource employs a computer-intensive approach to industrial statistics and provides numerous examples and procedures in the popular R language and for MINITAB and JMP statistical analysis software. Divided into two parts, the text covers the principles of statistical thinking and analysis, bootstrapping, predictive analytics, Bayesian inference, time series analysis, acceptance sampling, statistical process control, design and analysis of experiments, simulation and computer experiments, and reliability and survival analysis. Part A, on computer age statistical analysis, can be used in general courses on analytics and statistics. Part B is focused on industrial statistics applications. The fully revised third edition covers the latest techniques in R, MINITAB and JMP, and features brand-new coverage of time series analysis, predictive analytics and Bayesian inference. New and expanded simulation activities, examples, and case studies—drawn from the electronics, metal work, pharmaceutical, and financial industries—are complemented by additional computer and modeling methods. Helping readers develop skills for modeling data and designing experiments, this comprehensive volume: Part of the acclaimed series, , is the perfect textbook for advanced undergraduate and postgraduate courses in the areas of industrial statistics, quality and reliability engineering, and an important reference for industrial statisticians, researchers, and practitioners in related fields. The R-package is available from the R CRAN repository.

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