Teaching

Statistical Methods in Epidemiology

Graduate course, Boston University, School of Public Health, 2024

I was a teaching assistant for this course. It contained about 60 MPH, MA, and PhD students, most of which were concentrating in biostatistics. This is the description of the course: “This course covers study design and intermediate-level data analysis techniques for handling confounding in epidemiologic studies. Confounding is carefully defined and distinguished from interaction. Course content covers stratification and multivariable techniques for controlling confounding in both matched and independent sample study designs, including analysis of covariance, logistic regression, and proportional hazards models. Model fit and prediction are discussed. Students are required to apply these methods with the aid of computerized statistical packages.” I held office hours and held exam review sessions. The course was taught in R and SAS.

Statistical Computing with SAS

Graduate course, Boston University, School of Public Health, 2024

I was a teaching assistant for this course. It contained about 35 MPH students, most of which were concentrating in biostatistics. This is the description of the course: “Emphasis is placed on the use of intermediate-level programming with the SAS statistical computer package to perform analyses using statistical models with emphasis on linear models. Computing topics include advanced data file manipulation, concatenating and merging data sets, working with date variables, array and do-loop programming, and macro construction. Statistical topics include analysis of variance and covariance, multiple linear regression, principal component and factor analysis, linear models for correlated data, and statistical power.” I held office hours and gave 2 guest lectures on introductory SAS coding and topics in multiple linear regression.