JSM 2011 Online Program

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Activity Details

CE_11C Mon, 8/1/2011, 8:00 AM - 12:00 PM HQ-Poinciana Salon 1
Bootstrap Methods and Permutation Tests for Doing and Teaching Statistics — Continuing Education Course
ASA , Section on Statistical Education , Section on Statistical Computing
Instructor(s): Tim Hesterberg, Google Inc.
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 means and least-squares regression together with Normal-based inferences, even though the corresponding assumptions are violated. Bootstrapping and permutation tests (BPT) let us check the accuracy of common procedures, and the results 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 old. BPT let us more easily do inferences for a wider variety of statistics (e.g. trimmed means, robust regression) for data collected in a variety of ways (e.g. stratification). BPT provide output we may graph in familiar ways (like histograms) to help students and clients understand sampling variability, standard errors, p-values, and the Central Limit Theorem (CLT)-not just in the abstract, but for the data set and statistic at hand. We'll look at applications from a variety of fields, including telecommunications, finance, and biopharm.

2011 JSM Online Program Home

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