This book is designed for an introductory course in probability and statistics for students of engineering and physical sciences. It is rich in exercises and examples. Each chapter begins with an introductory statement and checklist of key terms and concludes with a set of statistical guidelines for correctly applying statistical procedures. FEATURES :
Clear, concise presentation helps students quickly gain an understanding of the concepts.
Rich problem sets give students the practice they need to learn the material.
Do’s and Don’ts at the end of each chapter help students to apply statistics correctly to avoid misuses.
Computer exercises for MINITAB® help students learn and become familiar with this software.
Many data sets are drawn from author Richard Johnson’s own consulting activities as well as discussions with scientists and engineers about their statistical problems. This helps illustrate the statistical methods and reasoning required in order to draw generalizations from data collected in actual experiments.
Case studies in the first two chapters illustrate the power of even simple statistical methods to suggest changes that make major improvements in production processes.
Graphs of the sampling distribution show the critical region and P value, and accompany the examples of testing hypotheses. These graphs help reinforce student understanding of the critical region, significance level, and P value.
Summary tables of testing procedures provide a convenient reference for students.
A section on graphic presentation of 22 and 23 designs includes coverage of blocking. This serves as a stand-alone introduction to the design of experiments for those instructors who can only devote two or three lectures to the subject.
Solid treatment of confidence interval techniques and hypothesis testing procedures, which clearly and consistently delineates the steps for hypothesis testing in each application.
Clear, current coverage of two-level factorial design. To explore interactions, engineers have to know about experiments where more than one variable has been changed at the same time in design.
A full chapter on modern ideas of quality improvement provides up-to-date coverage of this popular significant trend in the field.
Accessible discussion on joint distributions and the properties of expectation—this is a difficult topic not always covered in the course, but if so desired, here is a nice, quick treatment of it.About the AuthorUniversity of Wisconsin, Madison
