TEACHING
AMS 311: Probability Theory
Objectives: To introduce students to probability spaces, random variables, moment generating functions, algebra of expectations, conditional and marginal distributions, multivariate distributions, order statistics, law of large numbers.
Prerequisites: AMS 301 and 310 or permission of instructor. Corequisites: MAT 203 or 205 or AMS 261.
Semester & year taught: Spring 2014, Fall 2014, Spring 2015, Fall 2015, Spring 2016, Spring 2017, Spring 2018
AMS 572: Data analysis I
Objectives: To introduce students to statistical procedures in data analysis, including sampling distributions, inferences on population means, variances, proportions, correlations, etc. Both parametric and non-parametric statistical procedures are introduced.
Semester & year taught: Fall 2015, Fall 2016, Fall 2017, Fall 2018, Fall 2019, Fall 2020, Fall 2021, Fall 2022, Fall 2023
AMS 597: Statistical Computing
Objectives: To introduce students to some basic elements of statistical computing and computational statistics. Students are expected to know statistical concepts including ANOVA, regression analysis, etc before taking the course. This course is divided into two main parts. The first part covers R and SAS implementation of important statistical models. The second part covers computational statistics including numerical analysis, Monte Carlo methods, bootstrap, permutation, etc.
Semester & year taught: Spring 2017, Spring 2018, Spring 2019, Spring 2021, Spring 2022, Spring 2023
BIOS 667: Applied Longitudinal Data Analysis
Objectives: To introduce students to statistical models and methods for the analysis of longitudinal data, i.e. data collected repeatedly on individuals (humans, animals, plants, samples, etc) over time (or other conditions).
Semester & year taught: Fall 2013 (UNC-Chapel Hill)