STSCI 3080 - Probability Models and Inference

(crosslisted) BTRY 3080, ILRST 3080
(MQR-AS, SDS-AS)

Fall, Spring. 4 credits. Student option grading.

Forbidden Overlap: due to an overlap in content, students will receive credit for only one course in the following group: BTRY 3080, ECON 3110, ECON 3130, ILRST 3080, ILRST 3110, MATH 4710, STSCI 3110, STSCI 3080.
Prerequisite: STSCI 2150 or STSCI 2200/BTRY 3010 or equivalent, MATH 2130 or equivalent.

Staff.

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.