Nonparametric Statistics with Applications to Science and Engineering

W HEN thinking of nonparametric statistics, most statisticians will think of tests such as the Wilcoxon Signed Rank Test or other such traditional tests based on the ranks of data. Books that will spring to mind when thinking of nonparametric statistics might be Practical Nonparametric Statistics by Conover (1971) or Nonparametric Statistical Methods by Hollander & Wolfe (1973). This book, although using “nonparametric” in the title, is certainly not a traditional book on nonparametric statistics. It does include coverage of the traditional methods, but the majority of the book focuses on methods not emphasized in a more traditional book. It includes several chapters on some of the new, more computationally intensive nonparametric methods such as wavelets, bootstrapping, machine learning, and nonparametric Bayes techniques.