HSE 731 Foundations of Regression for Health Data Science

The two courses in the regression for health data science series cover the theory and applications of regression-based statistical modeling as practiced within the health data sciences. Both courses emphasize the dual goals of modeling which are (i) prediction and (ii) causal inference. This first course presents the foundations of linear regression. Topics including model fitting, statistical testing and inference, diagnostic procedures, covariate selection, and missing data. The course requires the R Language for Statistical Computing.

0.75 Dartmouth units; (HP, P, LP, NC)

*Core Requirement for MS in Health Data Science Online

Prerequisites: HSE 712

Offered: Spring

Instructor

Keith Drake

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