Statistical Analysis of Network Data

This lecture covers the basics of network data structures, including graphs, cycles, regular graphs, trees, and bipartite graphs. It also delves into network models such as Chung-Lu, Random Geometric Graphs, and Stochastic Block Models. The importance of permutation invariance and exchangeable sequences in network data analysis is discussed, along with Erdős-Rényi networks and degree distributions.