SDS 4030
Statistics for Data Science II
This builds on the foundation from the first course (SDS 3030) and further develops the theory of statistical hypotheses testing. It also covers advanced computer intensive statistical methods, such as the Bootstrap, that will make extensive use of R. The emphasis of the course is to expose students to modern statistical modeling tools beyond linear models that allow for flexible and tractable interaction among response variables and covariates/feature sets. Statistical modeling and analysis of real datasets is a key component of the course. Prerequisites: Please see eligibility rules.
Prerequisites & course information
Credit 3 units. ArtSci IQ: AN, NSM Typical periods offered: Fall, Spring
Sources
- Course catalogue โ2026โ2027