Probability and Statistics for Engineering and Computer Science.

Catalog description

Basic axioms of probability models, conditional probabilities and independence, discrete and continuous random variables, multiple random variables and their expected values and variances, models of stochastic processes, noise, stationarity and ergodicity, power spectral densities. Prerequisites: MATH 037 or MATH 039 or MATH 131 or ECPE 127 with a “C“ or better and Graduate or blended students in the School of Engineering and Computer Science.