3 credits
Spring 2026 Lecture Distance Learning Upper Division
A first course in probability, intended to serve as a background for statistics and other applications. Sample spaces and axioms of probability, discrete and continuous random variables, conditional probability and Bayes' theorem, joint and conditional probability distributions, expectations, moments and moment generating functions, law of large numbers, and central limit theorem. (The probability material in course one of the Society of Actuaries and the Casualty Actuarial Society is covered by this course.)
Learning Outcomes1Identify which discrete and continuous distributions are applicable in a given setting.
2Use conditional probabilities, Bayes theorem, and conditional distributions.
3Utilize joint distributions in the context of several random variables.
4Apply the law of large numbers and the central limit theorem in asymptotic settings.
5Derive moments and moment generating functions for discrete and continuous random variables.
Prerequisites
Restrictions
made by Purdue students.