EE 322 (STAT 322): Probabilistic Methods for Electrical Engineers
Fall 2012

The course will cover descriptions of discrete and continuous random variables (probability mass function, cumulative distribution function and probability density function); mean and variance computation; conditioning and Bayes rule; statistical independence; and joint, conditional and marginal pdf and cdf. Bernoulli, Binomial, Geometric, Poisson, Uniform, Exponential, Gaussian and other distributions of interest to EE students will be discussed. Moment generating functions, PMF, PDF of sums or random variables will also be covered. Covariance, correlation and Bayesian least squares (and linear least squares) estimation will be covered. Markov and Chebyshev inequality, law of large numbers, central limit theorem.