Chapman and Hall/CRC
Distribution-free resampling methods—permutation tests, decision trees, and the bootstrap—are used today in virtually every research area. A Practitioner’s Guide to Resampling for Data Analysis, Data Mining, and Modeling explains how to use the bootstrap to estimate the precision of sample-based estimates and to determine sample size, data permutations to test hypotheses, and the readily-interpreted decision tree to replace arcane regression methods.
Statistics practitioners will find the methods described in the text easy to learn and to apply in a broad range of subject areas from A for Accounting, Agriculture, Anthropology, Aquatic science, Archaeology, Astronomy, and Atmospheric science to V for Virology and Vocational Guidance, and Z for Zoology.
Practitioners and research workers and in the biomedical, engineering and social sciences, as well as advanced students in biology, business, dentistry, medicine, psychology, public health, sociology, and statistics will find an easily-grasped guide to estimation, testing hypotheses and model building.
Wide Range of Applications. Estimation and the Bootstrap. Software for Use with the Bootstrap and Permutation Tests. Comparing Two Populations. Multiple Variables. Experimental Design and Analysis. Categorical Data. Multiple Hypotheses. Model Building. Classification. Restricted Permutations. References. Appendix A: Basic Concepts in Statistics. Appendix B: Proof of Theorems. Author Index. Subject Index.