000			05167cam a22003374a 4500
001			16936209
003			OSt
005			20210921105016.0
008			110826s2012 flua b 001 0 eng
010			_a 2011030498
016	7		_a015804580 _2Uk
020			_a9781439855508
035			_a(OCoLC)ocn651914252
038			_akhadija
040			_aDLC _cDLC _dYDX _dBTCTA _dYDXCP _dBWX _dZ@L _dCDX _dUKMGB _dDLC
042			_apcc
050	0	0	_aQA278.8 _b.G64 2012
082	0	0	_a519.54 _223 _bGOO
100	1		_aGood, Phillip I. _982556
245	1	2	_aA practitioner's guide to resampling for data analysis, data mining, and modeling / _cPhillip I. Good.
260			_aBoca Raton, FL : _bCRC Press, _cc2012.
300			_ax, 214 p. : _bill. ; _c25 cm.
504			_aIncludes bibliographical references (p. 193-209) and index.
505	0		_a1. Wide Range of Applications: Resampling Methods ; Fields of Application -- 2. Estimation and the Bootstrap: Precision of an Estimate ; Confidence Intervals ; Improved Confidence Intervals ; Estimating Bias ; Determining Sample Size -- 3. Software for Use with the Bootstrap and Permutation Tests : AFNI ; Blossom Statistical Analysis Package ; Eviews ; HaploView ; MatLab® ; NCSS ; PAUP ; R ; SAS ; S-Plus ; SPSS Exact Tests ; Stata ; Statistical Calculator ; StatXact ; Testimate -- 4. Comparing Two Populations: A Distribution-Free Test ; Some Statistical Considerations ; Computing the p-Value ; Other Two-Sample Comparisons ; Two-Sided Test ; Rank Tests ; Matched Pairs ; R Code ; Stata ; Test for Nonequivalence ; Underlying Assumptions ; Comparing Variances -- 5. Multiple Variables: Single-Valued Test Statistic ; Combining Univariate Tests -- 6. Experimental Design and Analysis: Separating Signal from Noise ; k-Sample Comparison ; Multiple Factors ; Eliminating the Effects of Multiple Covariates ; Crossover Designs ; Which Sets of Labels Should We Rearrange? ; Determining Sample Size ; Missing Combinations -- 7. Categorical Data: Fisher's Exact Test. ; Odds Ratio.4 ; Unordered r x c Contingency Tables ; Ordered Statistical Tables ; Multidimensional Arrays -- 8. Multiple Hypotheses: Controlling the Family-Wise Error Rate ; Controlling the False Discovery Rate ; Software for Performing Multiple Simultaneous Tests ; Testing for Trend -- 9. Model Building: Regression Models ; Applying the Permutation Test ; Applying the Bootstrap ; Prediction Error ; Validation -- 10. Classification: Cluster Analysis ; Classification ; Decision Trees ; Decision Trees vs. Regression ; Which Decision Tree Algorithm Is Best for Your Application? ; Reducing the Rate of Misclassification ; Comparison of Classification Tree Algorithms ; Validation vs. Cross-Validation --11. Restricted Permutations: Quasi Independence ; Complete Factorials ; Synchronized Permutations ; Model Validation -- Appendix A: Basic Concepts in Statistics: Additive vs. Multiplicative Models ; Central Values ; Combinations and Rearrangements ; Dispersion ; Frequency Distribution and Percentiles ; Linear vs. Nonlinear Regression ; Regression Methods -- Appendix B: Proof of Theorems.
520			_a"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. Highlights Each chapter contains dozens of thought provoking questions, along with applicable R and Stata code Methods are illustrated with examples from agriculture, audits, bird migration, clinical trials, epidemiology, image processing, immunology, medicine, microarrays and gene selection Lists of commercially available software for the bootstrap, decision trees, and permutation tests are incorporated in the text Access to APL, MATLAB, and SC code for many of the routines is provided on the author's website The text covers estimation, two-sample and k-sample univariate, and multivariate comparisons of means and variances, sample size determination, categorical data, multiple hypotheses, and model building 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"--Back cover.
563			_ahardcover
650		0	_aResampling (Statistics) _982557
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c32803 _d32803