Workflow & Model Building
This week we will cover a principled approach to Bayesian inference: explicitly detailing what you should be doing at every step of any problem. Then we will move on to the craft of building models, starting with linear models (which is where you should always start).
Practial Guide to Principled Bayesian Inference
Bayesian inference is not a single algorithm. It is a framework for learning from data—one that has been applied across astronomy for decades, but inconsistently, and with widely varying notation and terminology. This lecture will step you through how you should approach any problem, with a Bayesian view.
Linear Models
Linear models are the simplest type in data analysis. But they are more flexible than you think, because what you think is linear is different from a linear model! Linear models are always the first place you should start for any data analysis problem!