Explain 'Bayesian Linear Regression'.

Explain 'Bayesian Linear Regression'.

Approach: Describe linear regression where coefficients are treated as random variables with prior distributions.

An approach to linear regression in which the statistical analysis is undertaken within the context of Bayesian inference. Instead of finding a single best value for weights, it estimates a posterior distribution over them.

Follow-up: What is the advantage over frequentist OLS?

Key concepts: prior, posterior, uncertainty estimation.