I am committed to providing an ear and a voice to all students with respect to Inclusion, Diversity, Belonging, and Equity and to achieving a culture that lives up to the definition of these words.
I have served as a teaching assistant for a variety of statistics courses at Indiana University, within the Department of Statistics. My experience spans from large undergraduate courses with over one hundred students to graduate-level courses with a strong focus on statistical theory. In total, I have contributed to the preparation and teaching of nine distinct courses.
Courses at Indiana University
Graduate Courses
- S620 Introduction to Statistical Theory (3 credits):
- Maximum likelihood, least squares, and Bayesian inference
- Assisted with lectures and problem sets, guiding master’s and first-year Ph.D. students in learning core statistical concepts.
- S625 Nonparametric Theory and Data Analysis (3 credits):
- Bootstrapping, empirical likelihood, and rank and permutation tests
- Provided guidance on nonparametric methods, helping students apply techniques like bootstrapping and permutation tests to real data.
- S626 Bayesian Theory and Data Analysis (3 credits):
- Prior and posterior probability distributions, Bayesian computation
- Supported students in understanding Bayesian inference and applying Bayesian methods to their own research projects.
- S630 Multivariate Data Analysis (3 credits):
- Classical inferential techniques for multivariate normal data
- Assisted in preparing course materials and helped students with projects involving multivariate methods like MANOVA.
- S650 Time Series Analysis (3 credits):
- Probability models, forecasting methods
- Helped students with time series projects, offering support with forecasting techniques and model analysis.
- S670 Exploratory Data Analysis (3 credits):
- Numerical and graphical techniques for summarizing and displaying data
- Provided assistance in data visualization exercises, helping students use exploratory techniques on large datasets.
Undergraduate Courses
- S320/520 Introduction to Statistics (3 credits):
- Basic concepts of data analysis and statistical inference
- Assisted with course for undergraduate statistics major students in understanding basic statistical concepts through review sessions.
- S301 Statistical Methods for Business (3 credits):
- Introduction to statistical methods for analyzing data arising in business
- Supported active learning for 100 business students by helping with case studies and group activities.
- S303 Statistical Methods for the Life Sciences (3 credits):
- Introduction to methods for analyzing data arising in the life sciences
- Assisted biology students with statistical methods applied to life science data, helping with assignments and in-class exercises.