SOC 3740

Analyzing Complex Data Structures: Network, Spatial, Multilevel, and Text Data

Course Description

Course information provided by the Courses of Study 2023-2024.

Not only the world but also data about the world is becoming increasingly complex. This course provides students with a comprehensive understanding and set of tools to analyze network, spatial, multilevel, and text data. Students will gain experience in how to prepare, analyze, and visualize data in R and the tidyverse. Examples of complex data structures include network data that represent connections among individuals (e.g., friends on social media platforms), spatial data that represents geolocations (e.g., smartphone location data), data collected at multiple levels (e.g., employees in organizations), and text data (e.g., online comments).

When Offered Summer.

Prerequisites/Corequisites Prerequisite: An introductory course on quantitative data analysis (e.g., elementary probability theory, hypothesis testing, linear regression) and some exposure to programming.

Distribution Category (SDS-AS, SSC-AS)

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