ED 288A: Educational, Social, and Behavioral Statistics (Graduate)

This course introduces our first-year School of Education Ph.D. students to key statistical concepts and techniques for exploring and analyzing education data. These concepts include understanding estimation and uncertainty in data, sampling distributions, sampling error, hypothesis testing, descriptive statistics, statistical tests of association (e.g., correlation, independent tests), linear models (eg., regression), and statistical assumptions.

I teaching using a collaborative, step-by-step approach. I do this by working alongside students in constructing and solving equations, interpreting results, and asking students to consider strengths and limitations of specific inferential tests.

There is also a lab component to this course, where students learn how to use Stata to process, explore, and analyze data. This is led by a graduate student. Elham Zargar led this lab for two years (2019-2020), followed by Joseph Aubele (2021-2022), and Youngsun Moon (2023).

I use a stylus pen to work through equations and concepts. This helps me control the pace of the lecture while also soliciting advice about what I should do next.

Elham Zargar provides step-by-step walkthroughs for working with Stata.

Our wonderful Fall 2020 class. In addition to the incoming SOE grad student cohort, we also had students from the School of Nursing and the School of Business.

Our 2023 class. Joining us are students from Informatics, Biological Sciences, and the School of Nursing.