Applied Nonparametric Statistical Methods, Fourth Edition
While preserving the clear, accessible style of previous editions, Applied Nonparametric Statistical Methods, Fourth Edition reflects the latest developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets.
Reorganized and with additional material, this edition begins with a brief summary of some relevant general statistical concepts and an introduction to basic ideas of nonparametric or distribution-free methods. Designed experiments, including those with factorial treatment structures, are now the focus of an entire chapter. The text also expands coverage on the analysis of survival data and the bootstrap method. The new final chapter focuses on important modern developments, such as large sample methods and computer-intensive applications.
Keeping mathematics to a minimum, this text introduces nonparametric methods to undergraduate students who are taking either mainstream statistics courses or statistics courses within other disciplines. By giving the proper attention to data collection and the interpretation of analyses, it provides a full introduction to nonparametric methods.
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FUNDAMENTALS OF NONPARAMETRIC METHODS
LOCATION INFERENCE FOR SINGLE SAMPLES
OTHER SINGLESAMPLE INFERENCES
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95 percent confidence alternative applied appropriate association asymptotic result asymptotic test binomial bootstrap bootstrap samples calculate cell censored Chapter chi-squared distribution Computational aspects Conclusion contingency table corresponding data in Example data set degrees of freedom deviations drug effect equal error estimate exact P-values exact permutation expected number factor Fisher exact test Formulation and assumptions Friedman test function given gives implies independent indicate inferences interaction Kendall's tau Kolmogorov test Kruskal-Wallis test least squares marginal totals median test mid-ranks Minitab normal distribution null hypothesis observations obtained odds ratio one-tail test outliers parametric patients percent confidence interval permutation test probability problem procedure random sample ranks regression relevant row and column sample median sample sizes sample values Section side-effects sign test significance level situation StatXact strong evidence symmetric t-test test statistic treatment two-tail test Walsh averages Wilcoxon signed-rank test Wilcoxon test WMW test zero