Instructor: Michael Minnotte
Office: Lund 201-C
Phone: 797-2844 (office)
E-mail: minnotte@math.usu.edu
Office Hours: TR 9:30 - 10:20, W 10:30 - 11:20, or by appointment.
Apparently, Geology 405 is actually available during our time slot after all, so we will meet there at the scheduled time, TR 1:30-2:45, starting Tuesday, September 2. Thank you, and sorry about the confusion.
One of the great revolutions in statistics in the last quarter century has been the introduction and widespread use of resampling methods such as the bootstrap. These methods allow us to estimate biases and calculate measures such as standard errors and confidence intervals when traditional methods are inappropriate or unavailable. They were not possible (or at least practical) before the advent of computers, but today's computing capabilities make them a valuable part of a statistician's toolkit.
This class constitutes an introduction to the bootstrap and other resampling plans, including the jackknife, subsampling methods, and some forms of cross-validation. There will be a mixture of theory and applied work. By the end of the class, you will know what the parametric and nonparametric bootstrap and other resampling plans are, what their properties and limitations are, when it is appropriate to use each, and how to implement them for many of the most commonly used families of models in statistics.
Prerequisites: Some probability and mathematical statistics, such as Math 5710 and 5720 is essential. We will be bootstrapping regression models, so some familiarity with multiple linear regression (such as Stat 5100) would be helpful. Some programming experience would also be desirable, especially with S-plus or R.
Assignments: There will be a variety of assignments throughout the semester. Each assignment will include a value (typically 20-100 points) that it will be scored out of. Your final grade will be determined by the sum of your points in all assignments. Assignments will include combinations of theoretical work, computer simulations, applied data-driven computational examples, discussion and summary of outside readings, and short oral presentations. The value of each assignment should be roughly proportional to its importance and the amount of work involved. Assignments will be handed out in class and posted to the web site.
Text: Efron, Bradley, and Tibshirani, Robert J., (1993), An Introduction to the Bootstrap, Chapman and Hall.
Brad Efron discovered and popularized the bootstrap starting with a paper in 1979.
Other Sources: Beyond the required text, additional material will be drawn from a number of sources. Some additional useful references are:
More theoretical than E&T, this book has the most comprehensive bibliography of resampling papers.
Another more theoretical work, also with a lot of S-plus examples.
The most theoretical work on the asymptotic properties of bootstraps.
Another introductory and applied book, with a slightly broader scope than the others, with introductions to subsampling and rerandomization as well as bootstrapping.
The most comprehensive text on the resampling variant of subsampling. Highly advanced and theoretical.
We will use the R computer package. R is a Gnu-license (freeware) clone of the S-Plus package, and is available for free download (Windows and Unix) from the Comprehensive R Archive Network (below). We will use the base package, and probably the libraries boot and bootstrap. I will spend some time in class going over the use of R, and you will have the opportunity to do some work in class to gain experience while I can help you.
R Sites
The Comprehensive R Archive Network
Windows R Setup Executable Download - click on rwXXXX.exe, where XXXX gives the version number
R Frequently Asked Questions (FAQ) List
R for Beginners (58 page pdf file)
An Introduction to R (100 page pdf file)
Data Analysis and Graphics Using R -- An Introduction (112 page pdf file)
Disability Statement: If a student has a disability that will likely require some accomodation by the instructor, the student must contact the instructor and document the disability through the Disability Resource Center, preferably during the first week of the course. Any requests for special considerations relating to attendance, pedagogy, taking of examinations, etc. must be discussed with and approved by the instructor. In cooperation with the Disability Resource Center, course materials can be provided in alternative formats - large print, audio, diskette or Braille.
Disclaimer: The instructor reserves the right to alter anything about this course, pretty much on whim (but he probably won't).