Rigorous introduction to health data science using current applications in biomedical research, epidemiology, and health policy. Use modern statistical software to conduct reproducible data exploration, visualization, and analysis. Interpret and translate results for interdisciplinary researchers. Critically evaluate data-based claims, decisions, and policies. Includes exploratory data analysis, visualization, basics of probability and inference, predictive modeling, and classification. This course focuses on the R computing language. No statistics or computing background is necessary. Carries the Arts & Sciences 2025 QC code.
Reserved for first-year students in the Natural Systems constellation. Students may enroll in one constellation course per semester.