Practical Nonparametric Statistics
Wiley, 1980 M09 17 - 512 páginas
A self-contained introduction to the theory and methods of non-parametric statistics. Presents a review of probability theory and statistical inference and covers tests based on binomial and multinomial distributions and methods based on ranks and empirical distributions. Includes a thorough collection of statistics tables, hundreds of problems and references, detailed numerical examples for each procedure, and an instant consultant chart to guide the student to the appropriate procedure.
SOME TESTS BASED ON
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95 quantile American Statistical Association Annals of Mathematical approximation assigned assumption asymptotic binomial distribution binomial test Biometrika block chi-square distribution chi-square random variable coefficient column computed confidence interval considered contingency table correlation corresponds to values critical level critical region DECISION RULE Definition degrees of freedom denoted empirical distribution function estimate event exact distribution Example experiment Friedman test given by Equation graph H₁ identically distributed independent Journal Kolmogorov test Kruskal-Wallis test level of significance Mann-Whitney test Mathematical Statistics mean method n₁ n₂ normal distribution normal scores null hypothesis number of observations obtained from Table One-Sided Test One-Tailed Test pairs parameters points population probability function procedure R₁ random sample rank tests regression rejected sample space selected sign test smallest Spearman's standard normal T₁ T₂ Table A1 test statistic Theorem total number treatment two-sample two-tailed test variance Wilcoxon X₁ Y₁ zero