DATA2020: Statistical Learning is one of the Data Science Master’s program required courses, currently taught by Roberta DeVito. The students spent the semester learning a variety of statistical methods and applying them to research projects on adolescent well-being, education, and achievement.
Statistical Learning is a modern introduction to inferential methods for regression analysis and statistical learning, with an emphasis on application in practical settings in the context of learning relationships from observed data. Topics covered include the basics of linear regression, variable selection and dimension reduction, and approaches to nonlinear regression. Extensions to other data structures such as longitudinal data and the fundamentals of causal inference are also introduced.