The deadline for Undergraduate Statistics Project Competition projects completed in winter/spring 2023 courses and year-long projects is June 23. USPROC encourages students to develop data analysis skills and enhance presentation skills. It is also a way to recognize outstanding work by undergraduate statistics students.

The submission categories are the following:

Undergraduate Statistics Class Project Competition (USCLAP)

This competition is for undergraduate students who are taking a statistics/data science course at the introductory or intermediate level in which a class project is part of the course work (either required or optional). Project submissions are a short report/paper (up to three pages). When submitting, a project needs to be entered with one of the following two levels:

• Introductory Level: A data-focused project that was completed as part of their first course in statistics or data science (with no statistics or data science prerequisite course), with or without a calculus prerequisite.
• Intermediate Level: A data-focused project that was completed as part of a second (or third) course in applied statistics OR as part of a Datafest competition.

Undergraduate Statistics Research Project Competition (USRESP)

This competition is for undergraduate students who conduct research projects related to statistics or data science, either methodological or applied. The types of research projects may include research work from summer Research Experiences for Undergraduates projects, senior-level research projects (part of coursework), or independent research projects (e.g., honors, capstone) not based on a specific course. Project submissions are a paper (up to 20 pages).

Winners will be announced in 2–3 months, and cash prizes will be awarded in all three categories.

For more information, email a USPROC committee member: Jennifer Ward; Maria Tackett, or Juanjuan Fan. 

USPROC 2022 Winners

USCLAP Introductory Statistics Competition
1st Place: Yijia Sun for “State-Level Abortion Restrictions and Its Association with Abortion Rates and Cross-State Movement in the United States, 2017–2019”
Faculty Sponsor: Marcela Alfaro Córdoba

2nd Place: Drake Gorecki and, Benjamin Zhao for “Examining Feature Rank and Dependency in the Q-Chat-10 ASD Questionnaire”
Faculty Sponsor: Tural Sadigov

3rd Place: James Mancini, Matthew Dolan, and Jack O’Sullivan for “Predicting Academic Performance of High-School Students”
Faculty Sponsor: Victoria Woodard

Honorable Mention: Aino Boley, Ruben Escobar, Mina Linsenmayer, and Michelle Dong for “Do Black Students Have a Significantly Higher Graduation Rate at HBCUs as Opposed to Other Colleges/Universities?”
Faculty Sponsor: James Normington

Honorable Mention: Hoang Nguyen Le, Evan Lee, Will Chen, and Ashley Kim for “Multivariate Logistic Regression for the Prediction of Coronary Heart Disease”
Faculty Sponsor: Xizhen Cai

USCLAP Intermediate Statistics Competition
1st Place: Zachary Swayne and Nathan Rethwisch for “Analysis of Vehicular Crashes in Iowa”
Faculty Sponsor: Heike Hofmann

2nd Place: Anh Vu, Quang Le, and Duy Nguyen for “Identification of Effective Biomarkers in Predicting the Survival of Patients with Severe Sepsis and Septic Shock”
Faculty Sponsor: Ryan Miller

3rd Place: Jinglin Xiong and Maya Gardner for “Predicting Forest Fires in Portugal and Northern Algeria”
Faculty Sponsor: Shonda Kuiper

Honorable Mention: Sam Magid, Payton Ahola, Spencer Huang, and Divij Jain for “Is There an Association Between Sleep and Memory?”
Faculty Sponsor: Xizhen Cai

USRESP Competition
1st Place: Irene Foster, Sunshine Schneider, Caitlin Timmons, and Katelyn Diaz for “Storm Chasers: Synthesizing New England Weather Data on a Dashboard for Emergency Response Workers”
Faculty Sponsor: Albert Kim 

2nd Place: Masahiro Nishikawa for “Performance of LDA and QDA on Non-Normally Distributed Predictors”
Faculty Sponsor: Amy Wagaman

3rd Place: Che Hoon Jeong for “Investigation of NCAA Basketball’s Three-Point Strategy Using Logistic Mixed-Effects Regression Model”
Faculty Sponsor: Sarah Supp

Honorable Mention: Nolan Alexander and Izabella Rivera for “Bayesian Data Synthesis for Protecting Sensitive Salary Data Information”
Faculty Sponsor: Monika Hu