Handbook of Parametric and Nonparametric Statistical Procedures

described and related to one another and to the different resampling methods is also notable. This is especially useful for the book’s target audience, for whom such concepts may not yet have taken root. On the computational side, the book may be a little less satisfying. Stepby-step computational algorithms are at some times inefŽ cient and at other times cryptic so that an individual with little programming experience might have difŽ culty applying them. This problem is substantially offset by the presence of numerous detailed examples solved using existing software, providing readers roughly equal exposure to S-PLUS, SC, and Resampling Stats. Unfortunately, these examples often require large, complex programs, demonstrating as much as anything a need for better resampling software. On the whole, Data Analysis by Resampling is a useful and clear introduction to resampling. It would make an ambitious second course in statistics or a good third or later course. It is quite well suited for self-study by an individual with just a few previous statistics courses. Although it would be miscast as a graduate-level textbook or as a research reference—for one thing it lacks a thorough bibliography to make up for its surface treatment of many of the topics it covers—it is a very nice book for any reader seeking an introductory book on resampling.