Bayesian Statistics: Time Series Analysis

This course for practicing and aspiring data scientists and statisticians. It is the fourth of a four-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, Techniques and Models, and Mixture models. Time series analysis is concerned with modeling the dependency among elements of a sequence of temporally related variables. To succeed in this course, you should be familiar with calculus-based probability,

• Build models describing temporal dependencies
• Use R for time series analysis and forecasting
• Explain stationary time series processes

• Knowledge of calculus-based probability
• Prior experience with Bayesian statistics
• Familiarity with basic R programming