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Practicum in Applied Statistics: Applied Probability

This course will first cover Kolgomorov's axioms of probabilities, basics of set theory, discrete combinatorial probability, Bayes' theorem, probability distributions and their properties and assumptions of dependence and independence, followed by the foundational topics of statistics: sampling distributions, the law of large numbers and the central limit theorem. This course will mix theoretical approaches with simulation-based illustrations of these main topics. The student will solve via analytical and simulation based approaches in statistical programming language R.

Course #
APSTA-GE 2351
Credits
3
Department
Applied Statistics, Social Science, and Humanities

Professors

Daphna Harel

Associate Professor of Applied Statistics; Director of A3SR MS Program