Daniel K. Sewell (University of Iowa) - An introduction to the statistical analysis of network data

9 e 10 Settembre 2019 - Aula VII (ex Castellano) ore 10-16 (con pausa)

Networks surround us in a wide range of contexts and can describe protein-protein interactions, interpersonal contacts, patient sharing amongst hospitals, transportation networks, world trade patterns, and other such phenomena. Network analysis is unique in its ability to understand such connected systems of interactions and flows. This short course of two 4-hour days is meant as a brief introduction to statistical techniques for analyzing network data. The goal of this course is to provide students with a basic knowledge of the fundamentals of analyzing network data, including (1) knowledge of salient structural properties of networks, (2) an understanding of some statistical models used to analyze network data, and (3) knowledge of and familiarity with available software implementing network analytic tools. Day one will focus on the basic concepts/nomenclature of networks, visualization techniques, data summarization, and centrality measures of the actors of the network. Day two will concentrate on statistical models, focusing on community detection methods and latent space models. Throughout the two days, periodic practicums will be available to learn how to implement network analysis in R.

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