Introduction to the Book Of Apps for Statistics Teaching

 

About the BOAST

The apps in this collection are the work of undergraduate students majoring in Statistics and Data Science at Penn State University. These students took part in the BOAST program between 2017 and 2024. (BOAST = Book Of Apps for Statistics Teaching). The program includes training in developing R Shiny applications focused on enhancing teaching and learning of statistical and data science objectives. This is followed by a full-time summer research experience developing the apps in this collection throughout the months of June and July. Finally, the BOAST students take part in a one-credit research class in Fall semester to showcase their work to statistics instructors, prepare a survey and IRB application to get student feedback in a human subjects research setting, and then formally test their apps in a live class. Besides gaining expertise in R and R Shiny, the students gained a deeper understanding of selected statistical concepts and learned crucial skills in the team-based reproducible development of software (e.g., though the use of the GitHub platform). This book is laid out in twelve chapters with four at the introductory level covering topics in Data GatheringData DescriptionBasic Probability, and Statistical Inference and with eight chapters at the upper division level covering ProbabilityRegressionANOVATime SeriesSamplingCategorical Data, Data Science, and Stochastic Processes, and a further chapter on statistical issues in Biology.

 

Using the Book

Icon/Attribute Description
Jump to the homepage of the PSU Statistics Department from within an app or back to this page from outside the apps.

Question Mark Icon

Information Icon

Home Icon

Timer Icon

Comment Icon

Hints for the app

Instructions for the app

Return to homepage

View/Hide timer

Give a review or comment on the app

Play slider animation

Searchable Tags
Tag Explanation
Explore with simulation
Multilevel app
Real data usage
Game
New entry in BOAST
A forthcoming entry
A lesson plan is available for this entry
5

Median 5-point mobile friendliness rating reported by multiple users:

1 = Not functional

2 = Functional – Very awkward

3 = Functional – Okay if no big screen available (multiple issues)

4 = Usable in a small class setting (single issue)

5 = Readily usable

 

Who We Are

  • Program Co-Supervisors and Principal Mentors: Dennis Pearl (2017-2024) and Neil Hatfield (2019-2024)
  • Faculty Mentors: Matthew Beckman (2017 – 2021), Priyangi Bulathsinhala (2017), and Jacopo Di Iorio (2022)
  • I.T. Support: Bob Carey
  • 2017 BOAST Students: Alex Chen, Qichao Chen, Jinglin Feng, Zibin Gao, Sitong Liu, Ryan Manigly-Haney, David Robinson, Yingjie Wang (2018 Peer Mentor), Caihui Xiao, Yuxin Zhang (2017 Website Coordinator)
  • 2018 BOAST Students: Jiajun Gao, Stephen Li, Thomas Mclntyre, Samuel Messer, Angela Ting, Ryan J Voyack, Luxin Wang, Zhiliang Zhang, Yinqi Zhang (2019 Peer Mentor), Yubaihe Zhou (2018 Website Coordinator)
  • 2019 BOAST Students: Oluwafunke Alliyu (2019 Website Coordinator), Yiyun Gong, Sean Klavans, Yuqing Lei, Shubo Sun, Jingjun Wang, Ruisi Wang, Yiyang  Wang, Zhiruo Wang, Yutong Wu, and Shunqi Zhang (2020 Peer Mentor)
  • 2020 BOAST Students: Leah Hunt (2020 Website Coordinator), Ethan Wright (2020 Website Coordinator), Hogeun Choi, Chenese Gray, Dae Hoon Gwak, Zhuolin Luo, Gonghao Liu, Zeyuan Wang, Jiawei Wu, Xigang Zhang (2021 Peer Mentor), and Xuefei Wang
  • 2021 BOAST Students: Kellien Peritz (2021 Website Coordinator), Adam Poleski (2021 Website Coordinator), Lydia Bednarczyk, Jiayue He, Paridhi Khandelwal, Shravani Samala, Qiaojuan (Tina) Tu, Yudan Zhang, and Ahmed Al Ali
  • 2022 BOAST Students: Jing Fu, Nurul Syafiqah Mohammad Hamdi, Junjie He, Peter Phillips, Wanyi Su, Phichchaya Sutaporn, Xinyue Tang, Stuart Vas, Hongyi Xia, and Yijun Yao
  • 2023 BOAST Students: Sean Burke, Rob Chappell, Aisiri Cherrimane Narendra, Luqi Jiao Emanuele, and Taryn McHugh
  • 2024 BOAST Students: Davis Im, Nathan Pechulis, Yusrat Sanni, and Michael Yun

Disclaimer: Because of time constraints, some apps have not yet been thoroughly tested on multiple platforms and by large groups of users. Please send lists of bugs and suggestions for improvement to Dennis Pearl (dkp13@psu.edu) and Neil Hatfield (njh5464@psu.edu).

Instructors: email Dennis Pearl and Neil Hatfield to request instructor resources for specific apps in the collection you would like to use in class (lesson plans and multiple choice assessment items).

 

Technical Info

To cite the entire book, please use:

Pearl, D. K., Hatfield, N. J., and Beckman, M. D. (2021). The Book Of Apps for Statistics Teaching (BOAST). Available from https://shinyapps.science.psu.edu.

To cite an individual app, please see the Overview page within the specific app.

To view the references used, please see the References page within the specific app.

BOAST Style Guide:

https://educationshinyappteam.github.io/Style_Guide/

GitHub:
https://github.com/EducationShinyAppTeam/BOAST