Kenett / Zacks / Amberti Modern Industrial Statistics

with applications in R, MINITAB and JMP
2. Auflage 2013
ISBN: 978-1-118-76368-1
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 592 Seiten, E-Book

Reihe: Statistics in Practice

Fully revised and updated, this book combines a theoretical background with examples and references to R, MINITAB and JMP, enabling practitioners to find state-of-the-art material on both foundation and implementation tools to support their work. Topics addressed include computer-intensive data analysis, acceptance sampling, univariate and multivariate statistical process control, design of experiments, quality by design, and reliability using classical and Bayesian methods. The book can be used for workshops or courses on acceptance sampling, statistical process control, design of experiments, and reliability.
Graduate and post-graduate students in the areas of statistical quality and engineering, as well as industrial statisticians, researchers and practitioners in these fields will all benefit from the comprehensive combination of theoretical and practical information provided in this single volume.
Modern Industrial Statistics: With applications in R, MINITAB and JMP:
* Combines a practical approach with theoretical foundations and computational support.
* Provides examples in R using a dedicated package called MISTAT, and also refers to MINITAB and JMP.
* Includes exercises at the end of each chapter to aid learning and test knowledge.
* Provides over 40 data sets representing real-life case studies.
* Is complemented by a comprehensive website providing an introduction to R, and installations of JMP scripts and MINITAB macros, including effective tutorials with introductory material: www.wiley.com/go/modern_industrial_statistics.

Autoren/Hrsg.

Kenett, Ron S.

Zacks, Shelemyahu

Amberti, Daniele

Inhaltsverzeichnis

Preface to first edition
Preface to second edition
List of Abbreviations
Part I: Principles of Statistical Thinking and Analysis
1. The Role of Statistical Methods in Modern Industry and Services
2. Analyzing Variability: Descriptive Statistics
3. Probability Models and Distribution Functions
4. Statistical Inference and Bootstrapping
5. Variability in Several Dimensions and Regression Models
Part II: Acceptance Sampling
6. Estimation in Finite Populations
7. Sampling Plans for Product Inspection
Part III: Statistical Process Control
8. Basic Tools and Principles of Process Control
9. Advanced methods of Statistical Process Control
10. Multivariate Statistical Process Control
Part IV: Design and Analysis of Experiments
11. Classical Design and Analysis of experiments
12. Quality by Design
13. Computer Experiments
Part V: Reliability
14. Reliability Analysis
15. Bayesian Reliability Estimation and Prediction
References
Subject Index
Author Index
Also available on book's website: www.wiley.com/go/modern_industrial_statistics
Appendix I: Introduction to R, by Stefano Iacus
Appendix II: Basic MINITAB commands and a review of matrix algebra for Statistics
Appendix III: R code included in the book, also available on the R CRAN website as MistatMain.R
Appendix IV: Source version of MistatMain.R (mistat_1.0.tar.gz)
Appendix V: Data sets as csv files (DatFiles.zip)
Appendix VI: MINITAB macros
Appendix VII: JMP scripts, by Ian Cox
Appendix VIII: Solution manual

Über Autor(innen)

RON S. KENETT, The KPA Group, Israel, University of Turin, Italy and NYU Center for Risk Engineering, New York, USA
SHELEMYAHU ZACKS, Binghamton University, Binghamton, USA
With contributions from DANIELE AMBERTI, Turin, Italy