JSM 2012 Online Program

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Activity Details


CE_26C	Tue, 7/31/2012, 1:00 PM - 5:00 PM	HQ-Indigo E
Simulation and Sampling of Data — Continuing Education Course
ASA , Section for Statistical Programmers and Analysts
Instructor(s): Rick Wicklin, SAS Institute
Sampling and simulation are fundamental techniques in statistical programming. To assess statistical methods, you often need to create data with known properties, both random and nonrandom. This workshop presents techniques for simulating data with particular properties. The student will learn to sample data from: common discrete and continuous distributions heavy-tailed, skewed, and mixture distributions multivariate distributions distributions with known properties such as a specific covariance structure or a known regression structure The student will learn to use simulated data to estimate the probability of an event estimate the sampling distribution of a statistic estimate the coverage probabilities of approximate confidence intervals evaluate the robustness of a statistical test when assumptions of the test are not satisfied This workshop is intended for practicing statisticians who need to simulate data. Pre-requisites include standard statistical concepts such as distributions, variance, correlation, and regression. Examples are presented using the SAS system. To follow the programming examples, it will be helpful if participants are familiar with basic SAS programming and procedures. Participants who are unfamiliar with SAS/IML software can refer to the book, Statistical Programming with SAS/IML Software (Wicklin 2010).

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