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Eudey, T. Lynn; Kerr, Joshua D.; Trumbo, Bruce E. – Journal of Statistics Education, 2010
Null distributions of permutation tests for two-sample, paired, and block designs are simulated using the R statistical programming language. For each design and type of data, permutation tests are compared with standard normal-theory and nonparametric tests. These examples (often using real data) provide for classroom discussion use of metrics…
Descriptors: Statistical Distributions, Hypothesis Testing, Relationship, Statistical Significance
Ryden, Jesper – International Journal of Mathematical Education in Science and Technology, 2008
Extreme-value statistics is often used to estimate so-called return values (actually related to quantiles) for environmental quantities like wind speed or wave height. A basic method for estimation is the method of block maxima which consists in partitioning observations in blocks, where maxima from each block could be considered independent.…
Descriptors: Simulation, Probability, Computation, Nonparametric Statistics

Morse, David T. – Educational and Psychological Measurement, 1999
Describes the MINISIZE 2 computer program, which permits the user to determine the effect size and the minimum sample size needed so that results of a given analysis will be statistically significant. Explains the program's operation and provides examples. (SLD)
Descriptors: Computer Software, Effect Size, Nonparametric Statistics, Sample Size
Ciechalski, Joseph C.; Pinkney, James W.; Weaver, Florence S. – 2002
This paper illustrates the use of the McNemar Test, using a hypothetical problem. The McNemar Test is a nonparametric statistical test that is a type of chi square test using dependent, rather than independent, samples to assess before-after designs in which each subject is used as his or her own control. Results of the McNemar test make it…
Descriptors: Attitude Change, Chi Square, Evaluation Methods, Nonparametric Statistics
McDermott, Paul A.; Watkins, Marley W. – 1979
A computer program named Program STANDARD is presented and demonstrated. This program calculates the statistical significance of the overall agreement of the categorical assignments. The program is based on Light's statistic, G, for describing the conjoint agreement of many observers with correct or standard set of classifications on nominal…
Descriptors: Classification, Computer Programs, Goodness of Fit, Nonparametric Statistics