# 401-3620-21L  Student Seminar in Statistics: Statistical Network Modeling

 Semester Frühjahrssemester 2021 Dozierende P. L. Bühlmann, M. Azadkia Periodizität jedes Semester wiederkehrende Veranstaltung Lehrsprache Englisch Kommentar Maximale Teilnehmerzahl: 48Hauptsächlich für Studierende der Bachelor- und Master-Studiengänge Mathematik, welche nach der einführenden Lerneinheit 401-2604-00L Wahrscheinlichkeit und Statistik (Probability and Statistics) mindestens ein Kernfach oder Wahlfach in Statistik besucht haben. Das Seminar wird auch für Studierende der Master-Studiengänge Statistik bzw. Data Science angeboten.

 Kurzbeschreibung Network models can be used to analyze non-iid data because their structure incorporates interconnectedness between the individuals. We introduce networks, describe them mathematically, and consider applications. Lernziel Network models can be used to analyze non-iid data because their structure incorporates interconnectedness between the individuals. The participants of the seminar acquire knowledge to formulate and analyze network models and to apply them in examples. Literatur E. D. Kolaczyk and G. Csárdi. Statistical analysis of network data with R. Springer, Cham, Switzerland, second edition, 2020.Tianxi Li, Elizaveta Levina, and Ji Zhu. Network cross-validation by edge sampling, 2020. Preprint arXiv:1612.04717.Tianxi Li, Elizaveta Levina, and Ji Zhu. Community models for partially observed networks from surveys, 2020. Preprint arXiv:2008.03652.Tianxi Li, Elizaveta Levina, and Ji Zhu. Prediction Models for Network-Linked Data, 2018. Preprint arXiv:1602.01192. Voraussetzungen / Besonderes Every class will consist of an oral presentation highlighting key ideas of selected book chapters by a pair of students. Another two students will be responsible for asking questions during the presentation and providing a discussion of the the presented concepts and ideas, including pros+cons, at the end. Finally, an additional two students are responsible for giving an evaluation on the quality of the presentations/discussions and provide constructive feedback for improvement.