College of Graduate Studies

This workshop will re-visit random and fixed effects with Hierachical GAMs (HGAMs) and expand the concepts of random slopes by introducing random smooths. The workshop will also cover smooth, nonlinear interaction terms via the ti() and te() functions.

By the end of this session, participants should be able to fit HGAMs with smooth interaction terms, plot and interpret the models.

Join our online workshop, where we'll unveil strategies for crafting the methods and results sections of your thesis.

This session will address the concepts of correlation, causation, and association in data. Participants will learn to differentiate between these concepts and to recognize and interpret various types of correlations.

By the end of the session, participants should be able to distinguish between correlation and causation, recognize the impact of confounding variables on associations, evaluate correlation reliability, and understand the significance of correlation results.

This workshop will introduce key ideas using clear mathematical notation while relating the concepts to the larger picture of Bayesian statistical inference and the Bayesian perspective of randomness, states of knowledge, and epistemology.

Ever found it challenging to answer the critical “So what” question in your research? Struggle no more!