Analyzing Disparities in Special Education Programs in California Schools

My undergraduate Statistics capstone project, in collaboration with some other classmates in the UC Davis Statistics major, was focused on analyzing the disparities in K-12 special education program enrollment.

We wanted to look at it from a machine learning perspective, as well as a traditional statistical testing perspective, which led to us implementing a K-means clustering algorithm and pairwise comparisons to identify factors which experience the most disparities in program enrollment.

A fair amount of work also went into literature review, which was used to provide context for our research problem, corroborate our findings, as well as motivate the methods that we used.

Slides can be accessed here.