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  • This journal article gives examples of erroneous beliefs about probability. It specifically examines the belief that a random sample must be representative of the true population.
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  • This journal article describes a set of experiments in which different methods of teaching Bayes' Theorem were compared to each other. The frequency representation of the rule was found to be easier to learn than the probability representation.
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  • This page introduces the definition of sufficient statistics and gives two examples of the use of factorization to prove sufficiency.
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  • This page introduces the Cramer-Rao lower bound, discusses it's usefulness, and proves the inequality.
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  • 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.
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  • This page contains course notes and homework assignments with solutions for a mathematical statistics class. The course covers statistical inference, probability, and estimation principles.
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  • These slides address point estimation including unbiasedness and efficiency and the Cramer-Rao lower bound.
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  • This page discusses the theory behind the bootstrap. It discusses the empirical distribution function as an approximation of the distribution function. It also introduces the parametric bootstrap.
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  • This site provides links to lecture outlines for an upper-level statistics class. Topics include hypothesis testing, ANOVA and regression.
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  • 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.
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