STSCI 3080

Probability Models and Inference

Course Description

Course information provided by the 2019-2020 Catalog.

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.

Prerequisites/Corequisites Prerequisite: STSCI 2150 or STSCI 2200/BTRY 3010 or equivalent, MATH 2130 or equivalent.

Forbidden Overlaps 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.

Outcomes

• Students will be able to manipulate random variables and their distributions using differential and integral calculus.
• Students will be able to derive properties of standard probability.
• Students will be able to derive maximum likelihood estimators for standard probability distributions and discuss their properties.

Distribution Category (MQR-AS)

When Offered Fall, Spring.

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