36-402 Advanced Methods for Data Analysis

9 units, Carnegie Mellon University

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.

Prerequisites: 36-401 (min C)

Offered: Spring 2027, Spring 2026

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