MML-09-07: Conjugate Prior Distributions & Bayesian Updating Mechanics – Practice Quiz

35 worked single-select and multiselect questions on Conjugate Prior Distributions & Bayesian Updating Mechanics. Intended level: Tier 2–3. Prerequisites: QS 9.6.

The sequence develops conceptual interpretation, explicit calculations, ML diagnostics and, where assigned, derivations with carefully stated assumptions. Feedback explains each answer and misconception by content.

Learning objectives: Recognize conjugacy relative to a likelihood and its parameter. Update Beta-Binomial probabilities and predictive probabilities. Update Dirichlet category counts without violating the simplex. Use Gamma shape-rate updates with correct exposure units. Combine Gaussian means using precision weights. Diagnose sequential updating, pseudo-count strength and prior-data conflict. Apply the general exponential-family conjugate update.

Study references: Deisenroth, Faisal & Ong, Mathematics for Machine Learning; Geyer, Minnesota Stat 5421.