Teaching

DSC 241: Statistical Models (Winter 2023)

Graduate course, Teaching assistant

DSC 241 is a graduate course that covers statistical learning techniques, focusing on how to perform analysis with a computer and interpreting results based on the backing theory. Topics include: multiple regression; diagnostics (checking assumptions and looking for outliers); polynomial regression and other ways to enrich a model; robust regression methods; penalized regression for high-dimensional models; generalized linear models to allow for a categorical response (classification); and a short overview of other regression methods such as classification trees, random forests, boosting, and neural networks from a statistical point of view.

DSC 291： Large-Scale Statistical Analysis (Spring 2022)

Graduate course, Teaching assistant

DSC 291 is a graduate course on statistical analysis of high-dimensional data, focusing on large-scale multiple hypothesis testing and inference. Topics include: Family-wise error rate (FWER) and false discovery rate (FDR) control and estimation, empirical null distribution, empirical Bayes methods, smooth Gaussian random fields.

FMPH 221： Biostatistical Methods I (Fall 2021)

Graduate course, Teaching assistant

FMPH 221 is an introductory graduate course on applied statistical data analysis. Topics include: model interpretation, model assumptions, confounding, interactions, testing of coefficients and ANOVA, adjusting for multiple comparisons, heteroscedasticity, model diagnostics, variable selection, prediction error and inference, cross-validation and resampling via the bootstrap.

FMPH 102： Biostatistics in Public Health (Fall 2019)

Undergraduate course, Teaching assistant

FMPH 102 is an introductory undergraduate course on the fundamentals of Biostatistics,. Topics include: methods summarizing and displaying data; probability; statistical distributions; central limit theorem, confidence intervals, and hypothesis testing; methods for comparing means of continuous variables between two groups; methods for comparing proportions between two groups; simple and multiple linear regression.