Resources

Below is a Shiny app I created to help undergraduate econometrics students who are working with R for the first time. R is an increasingly popular program used for econometric analysis (and countless other applications). However, many students struggle to master the program while simultaneously learning the basics of regression analysis. Even when students do understand the theory behind their exercises, loading all the necessary packages, troubleshooting errors, and aggregating output from different tests can be frustrating. The app below is meant to streamline this process.

App features:

• Uses the data library that corresponds to the Wooldridge econometrics textbook (one of the most popular undergraduate econometrics textbooks in the country), and serves as a companion resource (Wooldridge, Jeffrey M. 2013. Introductory econometrics: a modern approach. Mason, OH: South-Western Cengage Learning).

• Presents descriptions of datasets and variables automatically in the "Dataset Overview" tab.

• Allows students to select regression variables from a menu of options, avoiding typos and confusion when typing variable names.

• Shows regression output and corresponding R code at the click of a button.

• Visually represents the tests underlying statistical significance, to provide a better sense of what regression output actually means.

• Outputs collinearity and heteroskedasticity tests, so students can determine whether Gauss-Markov assumptions are violated (this tells us whether regression output is credible).

• Allows students to inspect, summarize, and print the data underlying their regressions.