Increasing accessibility and student readiness for statistical competitions


Ciaran Evans, Nicole Dalzell (Wake Forest University)


Abstract

Statistical competitions, such as DataFest, are popular and valuable opportunities for students to analyze complex and interesting data for real clients. Participation in such competitions requires skills in data wrangling, visualization, modeling, communication, and teamwork, all of which are crucial for a future career in statistics or data science. While advanced students may already have acquired these skills over the course of their undergraduate program, students with less experience often need additional preparation to participate. In this breakout session, we discuss the skills needed to succeed in a competition like DataFest, and how we can fill in the gaps for less-prepared students with targeted activities. We will also discuss our experiences running a DataFest preparation course at our institution.


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