Projects

This project analyzes COVID-19 cases and deaths across Pennsylvania counties (Apr 2020–Dec 2022). We explored how population size relates to per-capita rates and whether more cases lead to more deaths, using EDA methods and k-means clustering to identify county-level patterns. [Read More]

This project investigates how graduating during different phases of the COVID-19 pandemic (peak vs. decline) affects depression and hope levels among students. Using publicly available data, I applied PCA and logistic regression models to analyze mental health outcomes. Results indicate that students who graduated during the pandemic’s decline in 2021... [Read More]

Using real data from 2022 and 2023, this project predicts 2024 flight delays from Pittsburgh International Airport. We trained a ranodm forest classifier and achieved 78% prediction accuracy. [Read More]

This project investigates relational rule learning by exploring how the degree of understanding of a relational rule affects participants’ mastery rates across tasks of varying difficulty, whether prior training on a specific relational rule (rule matching) improves task accuracy, and whether interleaved pretraining—mixing different relational rules during training—enhances task performance.... [Read More]

This project examines patterns in medical incidents, analyzing how needs levels, and time-to-report vary across different incident types and time. We applied statistical techniques such as Fisher’s exact tests, time series, survival analysis, and Kruskal-Wallis tests to uncover insights. I was specifically responsible for analyzing medication errors. Below, you’ll find... [Read More]

This project investigates how gender stereotype threats affect academic outcomes using meta-analysis tehcniques in R. Results showed that both affirmative and non-affirmative interventions improved performance compared to no intervention, despite limited data for subgroup analysis. [Read More]

This project investigates the impact of gender stereotype threat on memory performance through a heading recall task. Conducted in Gorilla, with data cleaned in Excel and analyzed in Jamovi, the results revealed non-significant but suggestive trends in how stereotype threat may influence memory processing. [Read More]

This project explores the effects of incentives on visual search performance. The task was developed using Gorilla, and data were analyzed in Jamovi. Findings indicate that while incentives may affect search efficiency, their overall impact on performance was modest and not statistically significant. [Read More]