Ciaran Evans

Assistant Professor, Department of Statistical Sciences

Wake Forest University

At Wake Forest, I have taught the following courses:

  • Statistical Computing (STA 279) (Fall 2023, Spring 2024). Course on fundamental statistical computing, including functions, iteration, objects, and data wrangling. Covers R and Python, with some SQL and C++. I created this course in response to student interest in additional computing instruction.
  • Advanced Statistical Inference (STA 711) (Spring 2023, Spring 2024). Graduate course on the theory of statistical inference, including estimation, asymptotics, hypothesis testing, and confidence intervals. Emphasizes multivariate thinking and analysis and motivates inference through logistic regression models.
  • Competitions: DataFest (STA 175) (Springs 2022, 2023, 2024). Preparation for participation in the annual DataFest statistics competition. Co-taught with Dr. Nicole Dalzell. We collaborated on a series of modules for the course which are freely available for other DataFest instructors to use.
  • Generalized Linear Models (STA 712) (Fall 2022, Fall 2023). Graduate course in the theory and application of generalized linear models, including logistic regression, multinomial regression, Poisson regression, and exponential dispersion models. Emphasizes model diagnostics and adapting to assumption violations like overdispersion, zero inflation, and correlated data.
  • Applied Generalized Linear Models (STA 214) (Spring 2022, Fall 2022, Spring 2023). Course in applied generalized linear models, covering logistic regression, multinomial regression, Poisson regression, and mixed effects models. (Previously numbered STA 279).
  • Introduction to Regression and Data Science (STA 112) (Fall 2021, Spring 2022). Second semester course covering data wrangling and visualization, simple and multiple linear regression, and logistic regression.

Outside of courses, I have also supervised a variety of independent student research projects and theses, and I have helped organize Wake Forest’s annual DataFest with Nicole Dalzell.

Beyond Wake Forest, I am an Associate Editor for the Journal of Statistics and Data Science Education, and I am involved in organizing the JSDSE/CAUSE webinar series, the Undergraduate Statistics Research Project Competition (USPROC), and the ASA Section on Statistics and Data Science Education (SSDSE) Mentoring Program.

Carnegie Mellon University

At Carnegie Mellon, I taught summer sections of Reasoning with Data (36-200) and Introduction to Statistical Inference (36-226). From Spring 2019 to Fall 2020, I was also the head TA for Reasoning with Data.

As a graduate student, I worked on designing new labs and projects for life science students, and in collaboration with the Teaching Statistics Group I developed new material for teaching about correlation, causation, and randomization.

In summer 2017, I advised an undergraduate research project for CMU’s Summer Undergraduate Research Experience in Statistics, and helped teach labs on programming and data analysis for the program participants.