36-311 Statistical Analysis of Networks

9 units, Carnegie Mellon University

Networks are omnipresent in modern data science,arising in social systems, biology, technology, and beyond. In this course,students will get an introduction to network science, mainly focusing on social and biological networks. We will begin with some empirical examples, an overview of concepts for measuring and describing networks, and discuss network visualization. Traditional statistical models are often inadequate for network data due to complex dependence structure. We will introduce random graph models and statistical network models developed to characterize network structure and growth. We will also cover methods for statistical inference and prediction on network-linked data and, if time permits, special topics such as dynamic networks and multilayer networks.

Prerequisites: 36-226 or 36-236

Offered: Spring 2026

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