STATS 762 - Regression for Data Science
Faculty
Science
Department
Statistics
Points:
15
Available Semesters:
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Course Components
Labs
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Description: Application of the generalised linear model to fit data arising from a wide range of sources, including multiple linear regression models, Poisson regression, and logistic regression models. The graphical exploration of data. Model building for prediction and for causal inference. Other regression models such as quantile regression. A basic understanding of vector spaces, matrix algebra and calculus will be assumed.
Prerequisites / Restrictions
Prerequisite: 15 points from STATS 210, 225, 707, and 15 points from ENGSCI 314, STATS 201, 207, 208 Restriction: STATS 330
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