JSM 2005 - Toronto

JSM Activity #CE_12C

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

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CE_12C Sun, 8/7/05, 1:00 PM - 5:00 PM MCC-L100 E
Bootstrap Methods and Permutation Tests for Doing and Teaching Statistics - Continuing Education - Course
ASA, Section on Statistical Computing, Section on Statistical Education
Instructor(s): Tim C. Hesterberg, Insightful Corp.
Early in Stat 101 we teach that robustness is important. Yet later in the course, and too often in statistical practice, we ignore those lessons, and use simple methods like means and least-squares regression, and the usual normal-based inferences, even if the assumptions behind those methods are violated. Bootstrapping and permutation tests (B&PT) let us check the accuracy of common procedures, and the result are surprising. We'll see how inaccurate Normal-based methods are in the presence of even moderate skewness. The old rule of trusting the CLT if n > 30 is just that-old. B&PT let us more easily do inferences for a wider variety of statistics (e.g. trimmed mean instead of mean, robust regression instead of least-squares) for data collected in a variety ways (e.g. stratification, finite-population). B&PT provide output we may graph in familiar ways (histograms, scatterplots, normal probability plots) to communicate to students and clients ideas of sampling variability, standard errors, p-values, and the Central Limit Theorem (CLT)-not just in the abstract, but for this data set, and this statistic. We'll look at applications from a variety of fields. One striking example is the wild variability and severe bias of a common portfolio optimization method. Class participants should be either (a) practicing statisticians (graduate study not required), or (b) statistical educators who have taught introductory statistics at the level of Moore & McCabe (including confidence intervals and significance tests) at least once. OPTIONAL TEXTBOOK AVAILABLE
 

JSM 2005 For information, contact jsm@amstat.org or phone (888) 231-3473. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2005