MATH 310 Probability and Statistics I
Introductory probability covering the design of experiments, axioms of probability, sample spaces, probability rules, independence, conditional probability, Bayes' Theorem, discrete and continuous random variables, expectation, moment generating functions, and central limit theorem. Also covered are various distributions, including joint, binomial, Poisson, geometric, normal, exponential, and uniform. Prerequisites: MATH 261, Analytical Geometry II with a grade of "C" or better.