In this study, we investigated the relationship between student performance and learning styles for students enrolled in a basic business statistics course. This course used a learner-centered approach that incorporated multiple teaching styles. To assess our success in designing a course that facilitates learning for all learning styles, we evaluated the impact of students' learning style on their performance in the course. To accomplish this analysis, we utilized quantile regression, a statistical technique from the economics literature developed by Koenker and Bassett (1978) that is an alternative to the classical ordinary least squares (OLS) regression. Quantile regression allowed investigation of a more complete picture of student performance over the entire population as opposed to the mean effect from OLS regression. Learning style was not significant in determining a student's overall course score for the entire cohort of students. For small cohorts of students, learning styles were significant for exam average. That is, some students experienced either a disadvantage or advantage due to their learning style for the exam course component. However, for the overall course performance, a student with a particular learning style was neither advantaged nor disadvantaged
