Provides a one-semester course in probability and statistics with applications in the engineering sciences. Probability of events, discrete and continuous random variables cumulative distribution, ...

Addresses the topics of probability, random variables, discrete and continuous densities, expectation and variance, special distributions (binomial, Poisson, normal, etc.), moment generating functions ...

Julie Young is an experienced financial writer and editor. She specializes in financial analysis in capital planning and investment management. Suzanne is a content marketer, writer, and fact-checker.

This is a graduate-level course focused on techniques and models in modern discrete probability. Topics include: the first and second moment methods, Chernoff bounds and large deviations, martingales, ...

The Computer Science Department plans to debut a new course—Computer Science 20: “Discrete Mathematics in Computer Science”— next spring that will better prepare students for the required ...

In this paper we introduce discrete-time semi-Markov random evolutions (DTSMREs) and study asymptotic properties, namely, averaging, diffusion approximation, and diffusion approximation with ...

We adapt the expectation-maximization algorithm to incorporate unobserved heterogeneity into conditional choice probability (CCP) estimators of dynamic discrete choice problems. The unobserved ...

Majors usually begin by taking the calculus sequence. By the end of their first year, it is highly suggested for students to take either of the introductory proof classes (Discrete Math or Number ...