Discrete

  • This dataset comes from a study on drug treatments of reflux disease patients. Twelve patients were assigned to a four period crossover design, and data on their disease symptoms were collected after treatment. Questions this study focused on refer to dosage of the drug. A text file version of the data is found in the relation link.
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  • This dataset comes from a study on pregnant rats. Forty rats were given 4 doses of a drug, and data on their fetuses were collected. Questions this study focused on refer to the relationship between dosage of the drug and gender of the fetus. A text file version of the data is found in the relation link.
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  • This page calculates probabilities for a Poisson distribution.

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  • In this handout, students are asked to compare the ages of terminated employees to the ages of retained employees. Students will use the comparison to decide if the data supports the conclusion of age discrimination.
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  • This simulation illustrates types of sums of squares in a 2 x 3 ANOVA.
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  • This demonstration allows you to view the binomial distribution and the normal approximation to it as a function of the probability of a success on a given trial and the number of trials. It can be used to compute binomial probabilities and normal approximations of those probabilities.
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  • This online, interactive lesson on geometric models provides examples, exercises, and applets which include Buffon's Problems, Bertrand's Paradox, and Random Triangles.

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  • This online, interactive lesson on finite sampling models provides examples, exercises, and applets that include hypergeometric distribution, multivariate hypergeometric distribution, order statistics, the matching problem, the birthday problem, and the coupon collector problem.

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