Shiny App Showcase of 36 Apps developed by Statistics Students
These students work full time in the summer developing web apps for teaching and then field-test them in classes during the academic year. Shiny is an R package that allows you to build interactive apps with R as the computational engine. In the first two years of the program, these Penn State students have created 36 different apps and compiled them into an eBook laid out in nine chapters covering both introductory topics in Data Gathering, Data Description, Probability, Estimation and Testing , and Multivariable Topics along with Upper Division topics in Regression, ANOVA, Time Series, and Data Science. The apps span a variety of styles including games, simulation-based explorations, and real data illustrations. The book is called BOAST for Book Of Apps for Statistics Teaching and because the students completing the program have created something to boast about on their resumes! Besides gaining expertise in R and R Shiny, the students in the program also gain a deeper understanding of their selected statistical concepts and learn crucial skills in the team-based reproducible development of software and have been able to present their work at a variety of events.
https://shinyapps.science.psu.edu/
People:
- Program supervisor and principal mentor: Dennis Pearl
- Faculty mentors: Matthew Beckman and Priyangi Bulathsinhala
- I.T. support: Bob Carey and Kathleen Smith
- 2017 BOAST students: Alex Chen, Qichao Chen, Jinglin Feng, Zibin Gao, Sitong Liu, Ryan Manigly-Haney, David Robinson, Yingjie Wang, Caihui Xiao, Yuxin Zhang
- 2018 BOAST students: Jiajun Gao, Stephen Li, Thomas Mclntyre, Samuel Messer, Angela Ting, Ryan J Voyack, Luxin Wang, Zhiliang Zhang, Yinqi Zhang, Yubaihe Zhou