Resource Library

These slides address point estimation including unbiasedness and efficiency and the Cramer-Rao lower bound.

This file applies the Cramer-Rao inequality to a binomial random variable to prove that the usual estimator of p is a minimum variance unbiased estimator.

This page introduces the Cramer-Rao lower bound, discusses it's usefulness, and proves the inequality.

This page introduces the definition of sufficient statistics and gives two examples of the use of factorization to prove sufficiency.

This set of pages is an introduction to Maximum Likelihood Estimation. It discusses the likelihood and log-likelihood functions and the process of optimizing.

This set of pages describes software the author wrote to implement bootstrap and resampling procedures. It also contains an introduction to resampling and the bootstrap; and examples applying these procedures to the mean, the median, correlation between two groups, and analysis of variance.

This online, interactive lesson on point estimation provides examples, exercises, and applets concerning estimators, method of moments, maximum likelihood, Bayes estimators, best unbiased estimators, and sufficient, complete and ancillary statistics.

This online, interactive lesson on distributions provides examples, exercises, and applets which explore the basic types of probability distributions and the ways distributions can be defined using density functions, distribution functions, and quantile functions.

This site gives an explanation of, a definition for and an example of confidence intervals. It covers topics including inference about population mean and z and t critical values.

This is the description and instructions as well as a link for the Forest Fires and Percolation applet. It builds a background with a "hands-on" activity for the students which then leads to the applet itself. The applet is a game where the object is to save as many trees from the forest fire as possible. It shows the spread of a fire with the variable of density and the probabilty of the number of surviving trees.