STAT 410 - Probability Models

An introduction to discrete and continuous probability and probability models, including conditional probability, expectation, common discrete and continuous distributions, Poisson processes and discrete Markov chains. Additional topics may come from continuous-time Markov chains, queueing theory, and other applications.

Prerequisites: Completion of Essential Skills in Statistics, MATH 263 - Analytic Geometry and Calculus II or STAT 290 - Statistics, and MATH 285 - Matrix Algebra or MATH 357 - Linear Algebra.
Credits: 3
NOTE:
* This course counts toward the 63-hour Liberal Arts and Sciences (LAS) graduation requirement.