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How can we tell if the water we drink is making us sick? What’s the best way to estimate the prevalence of a new infectious disease? How do we know when an intervention is effective in reducing mortality? New and challenging data analysis problems require skills in quantitative research and computing. This course uses data from fields including environmental health and infectious disease to build research skills in exploratory data analysis, data visualization, statistical modeling and analysis, and scientific communication. The statistical software R is used. Students will develop skills in data visualization, multivariable regression modeling, generalized linear models, model diagnostics, and critical interpretation of results. Students will use these skills in a final data analysis project and report.

College/Department: Dornsife School of Public Health
Repeat Status: Not repeatable for credit
Prerequisites: PBHL 312 [Min Grade: C] or PBHL 210 [Min Grade: C] or STAT 201 [Min Grade: C]