STAT 461 - A First Course in Probability

(3 units)

Experiments, counting techniques, probability axioms; random variables, expectation, univariate and multivariate distribution theory, measures of association, conditional probability, Bayes theorem, sequences of random variables, Tchebychev inequality, Law of Large Numbers, and Central Limit Theorem.

Prerequisite(s): MATH 283 with a “C” or better.

Grading Basis: Graded
Units of Lecture: 3
Offered: Every Fall and Spring

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. demonstrate understanding of randomness and be able to use probability models to explain simple random phenomena. In addition, students will be able to compute summaries of probability distributions (univariate and multivariate).
2. compute measures of location, dispersion, and association, as well as probability of interest for many univariate and multivariate distributions.
3. assess and make use of the asymptotic results provided by the Law of Large Numbers and the Central Limit Theorem and their connection to the estimates of quantities from data.

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