The dataset was analyzed using IBM SPSS. A series of analyses were conducted to understand how attitudes toward omics data analysis and involvement with research changed for students while taking the course. Non-parametric analysis was required on this dataset, as the data was determined to be not normally distributed. Change over the course for primary and secondary cohorts was measured by the pre-test/post-test design and was analyzed using a Wilcoxon Signed Rank test, with effect sizes calculated using Cohen's d approach. Differences within students' experiences for the primary cohort were measured using Mann Whitney U Tests (gender, racial identity, and previous programming experience) and Kruskal-Wallis H tests (socioeconomic status). Due to sample size, similar analysis was not able to be conducted on the secondary cohort. Differences in attitudes toward omics, involvement with research and overall course grades were examined. Effect size for Wilcoxon Signed Rank tests and Mann Whitney U Tests were determined using Cohen d's approach (small (0.2) medium (0.5), large (0.8). Type 1 errors for significance between groups in Kruskal-Wallis H tests were mitigated using the Dunn-Bonferroni approach, and effect size was calculated using eta-squared (small 0.06, medium (1.4), large (>1.4)).