**Courses Taught**

*U.S. Air Force Academy*- Introduction to Economics
*University of Colorado Boulder*- Math Tools for Economists II, Introduction to Statistics

**Courses Assisted**

*University of Colorado Boulder*- Environmental Economics, Intermediate Microeconomics, Principles of Macroeconomics, Principles of Microeconomics

**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.