STAT6050 - Statistics For Data Science

This course aims to provide students with a solid background in applications of Bayesian methods as well as regression and time series analysis at an advanced graduate level. The course covers the Bayesian methods for inference as well as basic techniques of both the linear model, generalized linear model, non-linear models, as well as various time series methods. Emphasis is placed on appropriate model selection, usage of statistical software, and interpretation of results. categorical data techniques, and bayesian methods for inference
Prerequisite: (STAT4230 and STAT4250) or approval from program director.
3 Credits