STSCI 5080 - Probability Models and Inference

(crosslisted)
(also BTRY 5080, ILRST 5080)

Fall, spring. 4 credits.

F. Bunea.

This course provides an introduction to probability and parametric inference. Topics include: random variables, standard distributions, the law of large numbers, the central limit theorem, likelihood-based estimation, sampling distributions and hypothesis testing, as well as an introduction to Bayesian methods. Some assignments may involve computation using the R programming language.

Outcome 1: Students will be able to manipulate random variables and their distributions using differential and integral calculus.

Outcome 2: Students will be able to derive properties of standard probability.

Outcome 3: Students will be able to derive maximum likelihood estimators for standard probability distributions and discuss their properties.