Description: Building on a strong foundation in quantitative biology, fundamental statistical methods and basic R programming, students will learn an array of advanced biostatistical methods for data analysis. Topics covered include: data wrangling, methods for the analysis of designed experiments, regression analysis, including mixed effect models, and the analysis of multivariate data, including advanced supervised and unsupervised learning techniques. Requires students to apply their knowledge across a myriad of complex biological datasets.