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Epidemiology is the study of the distribution and determinants of health-related states and events (e.g., diseases) in specified populations. Epidemiology provides public health scientists and researchers with tools and methods to investigate the outbreak and spread of diseases at various scales. In this course, graduate students in Public Health and Epidemiology who have already gained an appropriate understanding of the principles of epidemiology and general statistics will take on more advanced topics, focusing on quantitative techniques and regression models in order to manipulate and analyse complicated public health data collected through research studies and surveys. A range of practical modelling techniques, such as multivariable regression models, addressing continuous, binary, count, and survival (time-to-event) outcomes/data, as well as quantitative bias analysis will be covered. In Public Health, clustering of diseases in certain locations and points in time is very common. Thus, general techniques to handle and analyse such aggregate-level data will also be introduced; e.g., multilevel (mixed-effects) regression modelling as well as systemic reviews and meta-analyses.