Prior Distributions: Informative, Weakly Informative & Jeffreys' Prior – Practice Quiz

Prior distributions for Bayesian analysis: evaluate informative and weakly informative regularization, distinguish proper from improper densities and investigate the consequences of flat priors. Derive Jeffreys priors from Fisher information and check their invariance under reparameterization, boundary behavior and posterior propriety. Includes original single-select and multiselect scenarios, worked reasoning and explanations of each distractor. Prerequisites: prior-to-posterior normalization and Fisher information. Authored from the saved Statistics & Probability syllabus; intended for progressive independent practice.

Further reading: Bayesian Data Analysis, 3rd edition.