STAT 4120
Applied Linear Models
Course Description
Pre-Requisite(s):
A prior course in statistics and a prior course in linear algebra
This course includes linear regression models, inferences in regression analysis, model validation, selection of independent variables, multicollinearity, influential observations, and other topics. Conceptual discussion is supplemented with hands-on practice in applied data-analysis tasks. Highly recommended: A prior course in applied regression such as STAT 3220.
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