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This study investigates the relationship between graduate student stress, commuting habits, and finances, a topic that has not been fully explored compared to the extensive research on undergraduate student housing. Data collected via an internet survey in Spring 2024 provides insights into how commuting time and distances influence stress levels among graduate students. Similarly, financial variables were found to predict these commuting habits. The analysis employed includes Rasch analysis for generating person scores, regression trees for machine learning, and quantile regression to uncover patterns at the highest levels of the outcome distribution. This research addresses a critical gap in the literature and aims to inform administrators and education researchers of necessary interventions and avenues of future research on graduate students.