Duke ShinyEd is a program where students develop interactive apps to explore concepts for introductory and intermediate level statistics courses. It was inspired and modeled after the ShinyEd project and the Book of Apps for Statistics Teaching (BOAST) at Penn State.

The program was originally held over six weeks in Summer 2020 and continued in Spring 2021.

For further information or questions please e-mail maria.tackett@duke.edu.

Check out our poster at USCOTS 2021!



Analysis of Variance

Learn more about the ANOVA test process including which assumptions the test makes and the meaning behind the test conclusion.

Hypothesis Testing

Explore the crucial aspects of hypothesis testing, including setting the hypotheses, calculating the test statistic and p-value, making conclusions, and navigating errors.

Logistic Regression

Learn the basics of logistic regression, with a focus on using the model for prediction. Explore the ROC curve, decision-making thresholds, and corresponding confusion matrices.

Model Diagnostics

Explore diagnostics for linear regression models and the impact of influential points on the model.