This book is a desk reference and instructional aid for those individuals currently involved with, or preparing for involvement with, Six Sigma project teams. As Six Sigma team members, Green Belts help select, collect data for, and assist with the interpretation of a variety of statistical or quantitative tools within the context of the Six Sigma methodology. The second in a four-book series geared specifically for these Green Belt activities, this book provides a thorough discussion of statistical quality control (SQC) tools. These tools are introduced and discussed from the perspective of application rather than theoretical development. From this perspective, readers are taught to consider the SQC tools as statistical “alarm bells” that send signals when there are one or more problems with a particular process. Guidance is also given on the use of Minitab and JMP in doing these various SQC applications. In addition, examples and sample problems from all industries appear throughout the book to aid a Green Belt's comprehension of the material.

The only book on the market that provides a simple nonmathematical presentation of the statistics needed by Six Sigma Green Belts. Every concept is explained in plain English with a minimum of mathematical symbols. Includes real-world examples, step by step instructions and sample output for Minitab and JMP software as well as downloadble, ready to use data sets and templates. Includes applications to service industries to help managers understand the role of Six Sigma in nonmanufacturing industries. Acknowledgments xvii About the Author xix Preface xxi Chapter 1: Fundamentals of Six Sigma 1 Chapter 2: Introduction to Statistics 7 Chapter 3: Presenting Data in Charts and Tables 23 Chapter 4: Descriptive Statistics 39 Chapter 5: Probability and Probability Distributions 59 Chapter 6: Sampling Distributions and Confidence Intervals 95 Chapter 7: Hypothesis Testing 113 Chapter 8: Design of Experiments 157 Chapter 9: Simple Linear Regression 211 Chapter 10: Multiple Regression 241 Chapter 11: Control Charts for Six Sigma Management 279 Appendix A: Review of Arithmetic and Algebra 321 Appendix B: Summation Notation 329 Appendix C: Statistical Tables 333 Appendix D: Documentation of Data Files 347 Glossary 349 Index 359

In this volume of the Six Sigma and Beyond series, quality engineering expert D.H. Stamatis focuses on how Statistical Process Control (SPC) relates to Six Sigma. He emphasizes the "why we do" and "how to do" SPC in many different environments. The book provides readers with an overview of SPC in easy-to-follow, easy-to-understand terms. The author reviews and explains traditional SPC tools and how they relate to Six Sigma and goes on to cover the use of advanced techniques. In addition, he addresses issues that concern service SPC and short run processes, explores the issue of capability for both the short run and the long run, and discusses topics in measurement.

To make Six Sigma work, executive and managerial "greenbelts" and "champions" need to understand core statistical concepts and techniques--but they don't need to become professional statisticians. Now, there's a concise, non-mathematical guide to all the statistics they need--and none of the statistics they don't need. The author shows them exactly how to capture the right information, make sense of it, and use it to improve quality throughout the entire Six Sigma DMAIC process. Levine illuminates topics ranging from statistical process control and experimental design to regression analysis and hypothesis testing. Drawing on the experience that has made him one of the world's most honored statistics educators, Levine presents statistical topics with the least possible mathematics. Throughout, he teaches through realistic examples--including many examples from the service industries, among the fastest-growing areas of Six Sigma implementation.

"The process by which a company identifies, frames, acts and reviews progress on problems, projects and proposals can be found in the structure of the A3 process ... follow the story of a manager ... and his report ... which will reveal how the A3 can be used as a management process to create a standard method for innovating, planning, problem-solving, and building structures for a broader and deeper form of thinking - a practical and repeatable approach to organizational learning"--Publisher's description.

This reference manual is designed to help those interested in passing the ASQ's certification exam for Six Sigma Green Belts and others who want a handy reference to the appropriate materials needed to conduct successful Green Belt projects. It is a reference handbook on running projects for those who are already knowledgeable about process improvement and variation reduction. The primary layout of the handbook follows the ASQ Body of Knowledge (BoK) for the Certified Six Sigma Green Belt (CSSGB) updated in 2015. The authors were involved with the first edition handbook, and have utilized first edition user comments, numerous Six Sigma practitioners, and their own personal knowledge gained through helping others prepare for exams to bring together a handbook that they hope will be very beneficial to anyone seeking to pass the ASQ or other Green Belt exams. In addition to the primary text, the authors have added a number of new appendixes, an expanded acronym list, new practice exam questions, and other additional materials

"Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines.Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences.A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, provides students with a solid base of conceptual and practical knowledge."--