**Courses Taught or Assisted**

- Instructor,
*U.S. Air Force Academy* - Introduction to Economics (Fall 2022)
- Instructor,
*University of Colorado Boulder* - Math Tools for Economists II (Summer 2018, Summer 2019)
- Introduction to Statistics (Fall 2018)
- Teaching Assistant,
*University of Colorado Boulder* - Intermediate Microeconomics (Fall 2019)
- Principles of Macroeconomics (Spring 2017, Spring 2021)
- Principles of Microeconomics (Fall 2016, Fall 2020)

**Shiny Apps**

These are web applications I created using R and the Shiny API to illustrate various statistical concepts as part of teaching Intro to Statisics (source code).

Students often struggle with the idea of statistical power. The left panel shows the rejection region and how it changes with the size of the test, the population variance and the extremity of the alternative hypothesis. The right panel shows the power curve and how it scales with the same inputs. Additionally, I've found that animating these inputs (especially the alternative hypothesis) helps students better understand these concepts.

In my class, I stressed what a confidence interval *is* and what it *is not*. This app Matt Butner and I developed shows that we can't assume any single confidence interval "contains the true mean," rather 95% of confidence intervals constructed *in the same way* contain the true mean. I also stress how confidence intervals shrink when you increase the sample size or decrease the confidence level.