PROJECTS

Utah State University Analytics Solutions Center

Cache County School District Dual Language Immersion Analysis

September 2025 - January 2026

I worked on this project with the Analytics Solutions Center, a consulting arm of Utah State University's Department of Data Analytics and Information Systems. We used causal inference statistics to assess the efficacy of Cache County School District's Dual Language Immersion program on student academic outcomes. Our best model was a Coarsened Exact Match using 21 predictor variables.

Cache County School District Attendance Analysis

This, like the Dual Language Immersion project, was at the request of Cache County School District. The project focused on answering administrator questions around attendance, specifically the effects of chronic attendance on student performance and what groups are most impacted by chronic attendance. I did minor data engineering to include all grades and accurately merge teacher information, but most of the project focused on making charts and turning them into a coherent narrative.

Utah State University, Advanced Machine Learning for Analytics

YouTube Comment Sentiment Prediction

April 2026

My group and I built an LSTM Natural Language Processing model in Python using tensorflow.keras to predict YouTube comment sentiment as positive, neutral, or negative. We tested several methods to improve performance and class balance, including bi-directional layers, class weighting, and pre-trained embeddings. The pre-trained embeddings model was slightly more accurate and delivered better class balance than the original model.

Utah State University, Introduction to Regression and Machine Learning for Analytics

Wine Quality Linear Regression Analysis and Flight Delay Classification Analysis

September - December 2025

This class was my first real introduction to generalized linear regression. The first project, Wine Quality Linear Regression Analysis, used a dataset from [Cortez et al. 2009] and a linear regression model to predict wine quality The second project, Flight Delay Classification Analysis, used datasets from the US Bureau of Transportation Statistics and the Iowa Environmental Mesonet. We created a logit model to predict if a flight would be delayed based on weather patterns, utilizing interaction terms and principal component analysis.

We also did two projects for homework. The first project, Peanut Butter Sales Analysis, used a linear regression model to predict the sales of peanut butter based on price, size, texture, coupons, etc. The second project, Qualified Leads Classification Analysis, used a logit model to predict whether a sales lead will be qualified.

Utah State University, Introduction to Modern Data Analytics

Nashville Airbnb Insights

January - April 2025

This class covered a variety of statistical techniques, which are all incorporated in this final project. Nashville Airbnb Insights assesses the viability of Airbnb listings using an association rule analysis, a Spearman coefficient correlation matrix, and k-means clustering for customer segmentation.

Utah State University, Data Visualization with Tableau

Utah Department of Transportation Traffic Analysis

July - August 2024

I completed this as a final project for a Tableau class. I chose a collection of datasets from the Utah Department of Transportation, consisting of six monitors that collected traffic numbers every hour. This Tableau dashboard allows the user to see traffic trends from these six monitors by hour, day, month, and year. Using this dashboard, UDOT workers could optimally time road construction from when there is the lowest level of traffic.