Modern Industrial Statistics The new edition of the prime reference
on the tools of statistics used in industry and services,
integrating theoretical, practical, and computer-based approaches
Modern Industrial Statistics 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: Explains the use of computer-based methods
such as bootstrapping and data visualization Covers nonstandard
techniques and applications of industrial statistical process
control (SPC) charts Contains numerous problems, exercises, and
data sets representing real-life case studies of statistical work
in various business and industry settings Includes access to a
companion website that contains an introduction to R, sample R
code, csv files of all data sets, JMP add-ins, and downloadable
appendices Provides an author-created R package, mistat, that
includes all data sets and statistical analysis applications used
in the book Part of the acclaimed Statistics in Practice series,
Modern Industrial Statistics with Applications in R, MINITAB, and
JMP, Third Edition, 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 mistat R-package is available
from the R CRAN repository.
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