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.
With its full integration of MINITAB™ and S-PLUS throughout, this book presents the most modern methods available in industrial statistics today. The authors show how to utilize the computer as...
Modern Industrial Statistics: Design and Control of Quality and Reliability
This book covers all the latest advances, as well as more established methods, in the application of statistical and optimisation methods within modern industry.
This volume presents an exposition of topics in industrial statistics. It serves as a reference for researchers in industrial statistics/industrial engineering and a source of information for practicing statisticians/industrial engineers.
This book is on Industrial Statistics, an area in which the authors are recognized as major experts.
A unique and comprehensive source of information, this book is the only international publication providing economists, planners, policymakers and business people with worldwide statistics on current performance and trends in the ...
Statistical Methods for Industrial Process Control provides the practical statistics foundation engineers can immediately apply to the work they do every day, regardless of their industry or specialty.
This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of America, and possibly other nations.
Industrial Statistics: Statistical Technique Applied to Problems in Industrial Research and Quality Control