Overview
- Concise presentation
- Emphasis on measurement issues critical to quality assurance
- Coverage that gives insight to correct implementation of quality improvement methods
- Online access to robust supporting materials, including R code for examples in the text and two sets of slides: one full set for lecture presentation and another with audio from a long-running and highly successful junior-level university course
- Includes supplementary material: sn.pub/extras
- Request lecturer material: sn.pub/lecturer-material
Part of the book series: Springer Texts in Statistics (STS)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (6 chapters)
Keywords
About this book
Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding.
Second Edition Improvements
- Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies)
- New end-of-section exercises and revised-end-of-chapter exercises
- Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures
- Substantial supporting material
Supporting Material
- Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses
- Documentation for the R programs
- Excel data files associated with theend-of-chapter problem sets, most from real engineering settings
Reviews
“This is a well-written book and provides a good number of worked examples to validate how the methods are actually used in real life situation using real datasets. … The main strength of the book is that it still offers a good number of applications that are based on real datasets emerging from an industrial sector. … I think this book can be successfully adopted for an undergraduate course on quality control and related topics.” (S. Ejaz Ahmed, Technometrics, Vol. 59 (1), January, 2017)
Authors and Affiliations
About the authors
J. Marcus Jobe is Professor of Information Systems and Analytics in the Farmer School of Business at Miami University (Ohio). His current research interests focus on measurement quality, multivariate process monitoring, pattern recognition, and oil exploration applications. Professor Jobe has taught and conducted research in Ukraine, and he has won numerous teaching awards at Miami University, including the all-university Outstanding Teaching award and the Richard T. Farmer Teaching Excellence award for senior professors in the school of business. The U.S. Dept. of State twice awarded him the Senior Fulbright Scholar award (1996-1997 and 2005-2006). Marcus Jobe also works as a consultant and has co-authored two statistics texts with Stephen Vardeman.
Bibliographic Information
Book Title: Statistical Methods for Quality Assurance
Book Subtitle: Basics, Measurement, Control, Capability, and Improvement
Authors: Stephen B. Vardeman, J. Marcus Jobe
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/978-0-387-79106-7
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag New York 2016
Softcover ISBN: 978-0-387-79105-0Published: 30 August 2016
eBook ISBN: 978-0-387-79106-7Published: 26 August 2016
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 2
Number of Pages: XIV, 437
Number of Illustrations: 5 b/w illustrations, 99 illustrations in colour
Topics: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences