Title: Introduction to Bootstrap
Speaker: Tejasvi Channagiri
Date/Time/Location: Friday, April 21st at 1:00pm, CMC 109
Abstract: A central problem of statistics is estimating a parameter (e.g., mean) of an unknown distribution given a sample. We usually also want to know the uncertainty of the estimate, such as its standard error. For simple cases like the sample mean there are closed-forms for the standard error. However, in more complex situations, closed-forms may be unavailable. The bootstrap is a computational method for determining standard errors of estimates that is widely applicable and easy to implement. Here we introduce the bootstrap, and present examples of its applications and limitations. No background is required aside from some elementary probability.