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Theory Of Probability

Axioms of Probability, conditional probability, distribution functions, density functions, transformations, expectations (expected values, moments, and MGFs), discrete and continuous distributions, multiple random variables (joint marginal, and conditional distributions), bivariate transformations, covariance and correlation, inequalities.

Design And Analysis Of Experiments

Review of one-way analysis of variance; planned and unplanned individual comparisons, including contrasts and orthogonal polynomials; factorial experiments; completely randomized, randomized block, Latin square, and split-plot designs: relative efficiency, expected mean squares; multiple regression analysis for balanced and unbalanced experiments, analysis of covariance. Lecture, three hours per week; laboratory, two hours per week for seven and a half weeks. Offered the first or second half of each semester.

Biostatistics II

Students will learn statistical methods used in public health studies. This includes receiver operator curves, multiple regression, logistic regression, confounding and stratification, the Mantel-Haenzel procedure, and the Cox proportional hazards model.

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