ILRST 3080

Probability Models and Inference

Course Description

Course information provided by the Courses of Study 2020-2021.

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.

When Offered Fall, Spring.

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

• 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.

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