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Traditional textbooks fail to provide an overall approach for the analysis of data, while typical training classes focus on techniques without telling you how to choose between those techniques for a particular analysis. Dr. Wheeler's Guide to Data Analysis is the remedy for both of these problems. Here, the various techniques are organized according to the type of analysis problem. This makes it easy to select an appropriate analysis technique. Moreover, this is the first text to integrate the techniques of SPC with the traditional techniques of statistical inference. By placing these various analysis techniques side by side and using them on the same data sets, the reader can see how to gain the maximum insight with the least effort. Part One presents the foundations of data analysis. These foundations provide a distinction between the textbook approach to statistics and the perspective needed for data analysis. Beginning with eight axioms of data analysis, the fundamental problem of data analysis is laid out and discussed in general terms that will help the reader avoid much of the confusion that is commonly associated with statstics. A discussion of what descriptive statistics will do, and what they will not do, provides insight into the basis of all modern analysis. A brief overview of the role of process behavior charts in examining data for homogeneity shows how to address the fundamental question of data analysis. Next, an introduction to the elements of statistical inference is provided and a simplified approach to the problem of inference is presented. Part Two consists of the techniques for data analysis. Eleven different problems are addressed. These problems are characterized by how the data were obtained and what type of response variable you have. Data collected under one, two, or three or more conditions are considered, along with data collected at three or more values of a single variable. Also considered are responses that consist of measurements, counts, or categories. For each of these different problems the appropriate analysis techniques are presented and illustrated. Then, summaries are given to list the advantages and disadvantages of each analysis technique. Part Three provides the reader with the keys to effective data analysis. Here is a coherent approach to making sense of data. A systematic way of characterizing a process, with guidelines on what improvement activity is appropriate, is presented. Methodologies and tables for converting the statistical measures of performance into the Effective Costs of Production are presented. Then, ways to use these Effective Costs of Production to choose an appropriate improvement strategy are shown. Using Effective Costs of Production, this book provides the first rigorous explanation of why you want to operate in the Six Sigma Zone, and it also shows you how to accomplish this objective. Problems commonly encountered are addressed in the book, along with pitfalls for the unwary, and ways to avoid these pitfalls. Finally, two models for process improvement are presented. So, while this book won't tell you how to do Six Sigma, it will tell you how to do Six Sigma better! Includes 178 Figures, 41 Data Tables, and Index. Expert Advice Donald J. Wheeler, Ph.D., is a consulting statistician who had the good fortune to work with W. Edwards Deming and David S. Chambers. Dr. Wheeler graduated from the University of Texas at Austin with bachelor's degrees in physics and mathematics, and has master's and doctorate degrees in statistics from Southern Methodist University. From 1970 to 1982 he taught in the statistics department at the University of Tennessee, Knoxville, where he was an associate professor. Between 1981 and 1993, he periodically assisted Dr. Deming with his four-day seminars. He is the author of more than 15 books and more than 60 articles. Dr. Wheeler is a fellow of the American Statistical Association.
Price: $79.00 |
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