Advanced Methods for Data Analysis

Catalog description

This course introduces modern methods of data analysis, building on the theory and application of linear models from 36-401 . Topics include nonlinear regression, nonparametric smoothing, density estimation, generalized linear and generalized additive models, simulation and predictive model-checking, cross-validation, bootstrap uncertainty estimation, multivariate methods including factor analysis and mixture models, and graphical models and causal inference. Students will analyze real-world data from a range of fields, coding small programs and writing reports. Prerequisite: 36-401 Min. grade C