This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 196
Type: Contributed
Date/Time: Monday, August 2, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract - #308497
Title: Classroom Derivation and Simulation: An Asymptotic Two-Sample Test for Comparing Population Medians
Author(s): Vadim Y. Bichutskiy*+ and Joshua D. Kerr and Eric A. Suess
Companies: California State University, East Bay and California State University, East Bay and California State University, East Bay
Address: Department of Statistics and Biostatistics, Hayward, CA, 94542,
Keywords: sample median ; two-sample hypothesis test ; computer simulations ; R statistical software ; convergence in law/distribution ; teaching

In the 21st century, the computer revolution is affecting statistical practice to such an extent that it seems appropriate to consider how computation and simulation can be better integrated into the teaching of statistical theory and methodology. We illustrate the interplay between theory, methodology and computation for statistical instruction by deriving and simulating in R the properties of an asymptotic two-sample test for comparing population medians. Further pedagogical goals are to reinforce concepts related to convergence in law and hypothesis testing, and to introduce ROC curves. Results show the proposed test is able to control the probability of Type I error, is as powerful as the permutation test and the bootstrap, and is more powerful than the Mann-Whitney-Wilcoxon rank sum test for heavy-tailed populations. Methods appropriate for courses at upper-division BS or MS level.

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