Social Networks: Statistical Approaches

Statistical Horizons presents Social Networks: Statistical Approaches, a 3-day livestream seminar taught by John Skvoretz on February 24-26.

This advanced seminar is a survey of statistical methods for analyzing social network data. We will focus on testing hypotheses about network structure, local structural effects, and the formation and dissolution of ties based on attributes.

Seminar participants will learn to:

• Propose and evaluate hypotheses about tie structure in dyads, in triads, and in complete networks.
• Build and assess biased net models for realized tie counts and complete networks.
• Understand the framework of exponential random graph models, formulate specific models for static and dynamic networks and for binary and weighted graphs, and estimate and assess goodness-of-fit with the statnet R package.
• Specify, estimate, and evaluate stochastic actor‐oriented models for longitudinal network and attribute data with the RSiena R package.

The seminar will be held live via Zoom, but you can also join asynchronously by viewing the recorded videos of each session. Lectures are held each day from 10am-2pm ET (New York time), with lab sessions Thursday and Friday from 4-5pm ET.

Please share this information with any colleagues, grad students, or others who may be interested. Email ashley@statisticalhorizons.com with any questions.