I am planning to present a simple introduction to variational Bayesian inference during a lab research meet (45 mins). My audience is mainly from a psychometrics, psychology, educational sciences background who have a basic idea of Bayesian inference and mainly work with SPSS. Computational methods are relatively rare here and not discussed.
I was wondering how do I structure the presentation, I would lose the audience if I make it math heavy, yet, it is hard to talk about variational methods hiding the math.
I do not want to present it as a look, a cool method, but more to make people aware that there are alternatives to MCMC if they want to do Bayesian inference (in a large dataset and complex model context). Any suggestions would be highly appreciated!