This course will provide an introduction to descriptive and inferential network analysis. In the morning we will cover descriptive network analysis, including: terminology, data collection/management, position (e.g., centrality) analysis, visualization, and community detection. In the afternoon we will cover statistical network analysis. Do actor attributes such as gender, race, or political preferences salary predict tie formation in a network? Does the network exhibit a tendency towards reciprocal tie formation? Statistical network models can be used to empirically study network structure and answer questions such as these. We will cover both empirical analysis and network simulation using statistical network models. Real-world network data and R code will be presented through interactive workshop sessions in both the morning and afternoon. There are no formal prerequisites for the course, but a background in basic statistical analysis (e.g., regression) will be useful.