Statistics and Probability with Applications for Engineers and Scientists Using MINITAB, R and JMP. Bhisham C. Gupta

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      In Chapter 17, we introduce the design and analysis of experiments using one, two, or more factors. Designs for eliminating the effects of one or two nuisance variables along with a method of estimating one or more missing observations are given. We include two nonparametric tests, the Kruskal–Wallis and the Friedman test, for analyzing one‐way and randomized complete block designs. Finally, models with fixed effects, mixed effects, and random effects are also discussed.

Chapter 18 introduces a special class of designs, the so‐called factorial designs. These designs are widely used in various industrial and scientific applications. An extensive discussion of unreplicated factorial designs, blocking of factorial designs, confounding in the factorial designs, and Yates's algorithm for the factorial designs is also included. We also devote a section to fractional factorial designs, discussing one‐half and one‐quarter replications of factorial designs.

      In Chapter 19, we introduce the topic of response surface methodology (RSM). First‐order and second‐order designs used in RSM are discussed. Methods of determining optimum or near optimum points using the “method of steepest ascent” and the analysis of a fitted second‐order response surface are also presented.

      Chapters 20 and 21 are devoted to control charts for variables and attributes used in phase I and phase II of a process. “Phase I” refers to the initial stage of a new process, and “phase II” refers to a matured process. Control charts are used to determine whether a process involving manufacturing or service is “under statistical control” on the basis of information contained in a sequence of small samples of items of interest. Due to lack of space, these two chapters are not included in the text but is available for download from the book website: www.wiley.com/college/gupta/statistics2e.

      All the chapters are supported by three popular statistical software packages, MINITAB, R, and JMP. The MINITAB and R are fully integrated into the text of each chapter, whereas JMP is given in an independent section, which is not included in the text but is available for download from the book website: www.wiley.com/college/gupta/statistics2e. Frequently, we use the same examples for the discussion of JMP as are used in the discussion of MINITAB and R. For the use of each of these software packages, no prior knowledge is assumed, since we give each step, from entering the data to the final analysis of such data under investigation. Finally, a section of case studies is included in almost all the chapters.