We begin with a graphical approach to bootstrapping and permutation testing, illuminating basic statistical concepts of standard errors, confidence intervals, p-values and significance tests. We show graphical and numerical diagnostic checks for the validity of traditional Gaussian-based inferences.
We consider a variety of statistics (mean, trimmed mean, regression, etc.), and a number of sampling situations (one-sample, two-sample, stratified, finite-population), stressing the common techniques that apply in these situations.
Course sessions will be a combination of PowerPoint-style presentation, live demonstrations, and hands-on work using statistical software.
The demonstrations will use the free student version of S-PLUS with a resampling library that provides an easy-to-use graphical interface for BPT. However, the focus of this course is on the concepts to be taught, not the software. We use the graphical interface so that participants with no experience with S-PLUS will have no trouble following. The teaching ideas can also be implemented with other software.
Course participants will receive handouts and a copy of Bootstrap Methods and Permutation Tests, Hesterberg, et al., W. H. Freeman, 2003, a supplemental chapter for using BPT for teaching introductory statistics.
Participants will learn how to use resampling methods:
Participants will also gain an appreciation for the benefits of these methods in teaching statistical concepts.