Course Description
Pre-Requisite(s):
A prior course in statistics and a prior course in linear algebra
Discipline(s):
Quantification, Computation & Data Analysis
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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