Sorry, you need to enable JavaScript to visit this website.

Estimation Principles

  • Tips for helping students to take more effective notes during lecture.
    View Resource
    0
    No votes yet
  • This section of ARTIST contains suggestions for implementing student journals, writing assignments, and minute papers in statistics classes. Links to general references for writing assessments are included.
    View Resource
    0
    No votes yet
  • 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.
    View Resource
    0
    No votes yet

  • This online, interactive lesson on set estimation provides examples, exercises, and applets concerning estimation of the normal model, estimation in the Bernoulli Model, estimation in the two-sample normal model, and Bayesian set estimation.

    View Resource
    0
    No votes yet
  • 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.
    View Resource
    0
    No votes yet
  • This set of pages is an introduction to Maximum Likelihood Estimation. It discusses the likelihood and log-likelihood functions and the process of optimizing.
    View Resource
    0
    No votes yet
  • This page introduces the definition of sufficient statistics and gives two examples of the use of factorization to prove sufficiency.
    View Resource
    0
    No votes yet
  • This page introduces the Cramer-Rao lower bound, discusses it's usefulness, and proves the inequality.
    View Resource
    0
    No votes yet
  • 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.
    View Resource
    0
    No votes yet
  • These slides address point estimation including unbiasedness and efficiency and the Cramer-Rao lower bound.
    View Resource
    0
    No votes yet

Pages

list