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Modern Industrial Statistics
With Applications in R, MINITAB, and JMP
Ron S. Kenett (Author), Shelemyahu Zacks (Author)
9781119714903, Wiley
Hardback, published 3 June 2021
880 pages
24.4 x 17 x 5.2 cm, 1.616 kg
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: 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.
Preface to the third edition Preface to the second edition (abbreviated) Preface to the first edition (abbreviated) List of abbreviations Part A: Modern Statistics: A Computer Based Approach 1 Statistics and Analytics in Modern Industry 2 Analyzing Variability: Descriptive Statistics 3 Probability Models and Distribution Functions 4 Statistical Inference and Bootstrapping 5 Variability in Several Dimensions and Regression Models 6 Sampling for Estimation of Finite Population Quantities 7. Time Series Analysis and Prediction 8 Modern analytic methods Part B: Modern Industrial Statistics: Design and Control of Quality and Reliability 9 The Role of Industrial Analytics in Modern Industry 10 Basic Tools and Principles of Process Control 11 Advanced Methods of Statistical Process Control 12 Multivariate Statistical Process Control 13 Classical Design and Analysis of Experiments 14 Quality by Design 15 Computer Experiments 16 Reliability Analysis 17 Bayesian Reliability Estimation and Prediction 18 Sampling Plans for Batch and Sequential Inspection List of R packages References Author index Subject index Solution manual Appendices (available on book�s website) Appendix I Intro to R Appendix II Intro to MINITAB and Matrix Algebra Appendix III R scripts Appendix IV mistat Appendix V csv Files Appendix VI MINITAB macros Appendix VII JMP scripts
Subject Areas: Mathematics [PB]
