Statistics for Quality Control

Includes many easy to understand industrial examples of skills needed on the job.; Includes Basic Inferential statistics for hypothesis testing on the job.; Minitab & Excel data sets are used in many of the examples and home work problems.; Uses informal language to explain key concepts and processes used in Industry.

Offers a basic level study of statistics used in a production operations setting. The book covers introductory topics such as a brief background, measurements, and graphing techniques. It then moves on to the beginning statistics necessary to understand these practices commonly found in industry and ends with coverage of quality assurance issues.Statistics for Quality Control is a basic level study of statistics used in a production operations setting. It is primarily intended for students entering quality control or other industrial and operations careers. It covers introductory topics such as a brief background, measurements, and graphing techniques. It then moves on to the beginning statistics necessary to understand these practices commonly found in industry and ends with coverage of quality assurance issues along with some pertinent managerial practices associated with this topic.Daniel Jackson is an Associate Professor of Architectural and Manufacturing Sciences at Western Kentucky University. He has more than 30 years of teaching and research experience in manufacturing operations and design, quality assurance and control, six sigma, lean concepts, and graduate courses. He works extensively with students by teaching, advising, and directing their career interests. He has traveled throughout the world teaching and conducting research.   Preface. The Industrial Age. CH 1- Numbers, Measurements & Scales. CH 2- Sampling & Organization of Data. CH 3- Basic Statistics for Discrete Distributions. CH 4- Statistics for Continuous Distributions. CH 5- Statistical Process Control for Attributes. CH 6- Process Control for Variables. CH 7- Control Chart Analysis. CH 8- Acceptance Sampling. CH 9- Inferential Applications. CH 10- Additional Uses of Statistics in Industry. CH 11- Quality Management. Appendices.