Viviana Amati: Katalogdaten im Herbstsemester 2019

NameFrau Dr. Viviana Amati
DepartementGeistes-, Sozial- und Staatswissenschaften

851-0252-13LNetwork Modeling
Particularly suitable for students of D-INFK

Students are required to have basic knowledge in inferential statistics, such as regression models.
3 KP2VC. Stadtfeld, V. Amati
KurzbeschreibungNetwork Science is a distinct domain of data science that focuses on relational systems. Various models have been proposed to describe structures and dynamics of networks. Statistical and numerical methods have been developed to fit these models to empirical data. Emphasis is placed on the statistical analysis of (social) systems and their connection to social theories and data sources.
LernzielStudents will be able to develop hypotheses that relate to the structures and dynamics of (social) networks, and tests those by applying advanced statistical network methods such as stochastic actor-oriented models (SAOMs) and exponential random graph models (ERGMs). Students will be able to explain and compare various network models, and develop an understanding how those can be fit to empirical data. This will enable them to independently address research questions from various social science fields.
Voraussetzungen / BesonderesStudents are required to have basic knowledge in inferential statistics and should be familiar with linear and logistic regression models.