Resampling methods techniques for repeatedly resampling data to obtain results are being used in virtually every research area. This practical guide discusses the applications of these methods, especially in the areas of microarrays and data mining. Each chapter contains a wealth of exercises along with R and Stata code. Written by a leading authority in the field, the text covers such topics as estimation, the bootstrap method, multivariate tests, decision trees, categorical data, multiple hypotheses, and model building.
Resampling methods techniques for repeatedly resampling data to obtain results are being used in virtually every research area. This practical guide discusses the applications of these methods, especially in the areas of microarrays and data mining. Each chapter contains a wealth of exercises along with R and Stata code. Written by a leading authority in the field, the text covers such topics as estimation, the bootstrap method, multivariate tests, decision trees, categorical data, multiple hypotheses, and model building.
Phillip Good is the author of 18 novels, 625 popular articles in magazines and newspapers, scholarly articles in the fields of astrophysics, biology, biostatistics, computer science, probability, and statistics, and nine statistical texts including Applying Statistics in the Courtroom: A New Approach for Attorneys and Expert Witnesses, Chapman Hall, London, 2001. ISBN 1-58488-271-9, and Managers' Guide to the Design and Conduct of Clinical Trials, Wiley, NY, 2002 (2nd edition, 2006).
Inhaltsangabe
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.
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.
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