Fall

Introduction to probability theory. Random variables, expectation, variance and moment generating functions. Distributions: Bernoulli, binomial, uniform, Gaussian, exponential, Poisson, gamma. Introduction to statistical concepts. Sampling and sample statistics. Point and interval estimation. Hypothesis testing. Regression. Numerical and computational aspects of random variable generation, sampling, and estimation.