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Apply Bayes theorem with conjugate priors

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's ability to apply Bayesian inference with a conjugate Beta prior to a binomial likelihood, derive the posterior distribution, compute posterior summaries (mean, credible interval, tail probabilities), and contrast Bayesian credible intervals with frequentist Wald and Clopper–Pearson intervals.

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Apply Bayes theorem with conjugate priors

Company: Other

Role: Data Scientist

Category: Statistics & Math

Difficulty: Medium

Interview Round: Onsite

A website’s true daily purchase conversion p is unknown. Prior: p ~ Beta(2, 8). Day 1: 10 purchases out of 120 visits; Day 2: 18 purchases out of 150 visits. (a) Derive the posterior after both days. (b) Compute the posterior mean and a 95% equal-tailed credible interval. (c) Compute P(p > 0.12 | data). (d) Compare your Bayesian 95% interval to a frequentist Wald interval and an exact Clopper–Pearson interval; explain differences and when each is appropriate.

Quick Answer: This question evaluates a candidate's ability to apply Bayesian inference with a conjugate Beta prior to a binomial likelihood, derive the posterior distribution, compute posterior summaries (mean, credible interval, tail probabilities), and contrast Bayesian credible intervals with frequentist Wald and Clopper–Pearson intervals.

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Other
Oct 13, 2025, 9:49 PM
Data Scientist
Onsite
Statistics & Math
1
0

A website’s true daily purchase conversion p is unknown. Prior: p ~ Beta(2, 8). Day 1: 10 purchases out of 120 visits; Day 2: 18 purchases out of 150 visits. (a) Derive the posterior after both days. (b) Compute the posterior mean and a 95% equal-tailed credible interval. (c) Compute P(p > 0.12 | data). (d) Compare your Bayesian 95% interval to a frequentist Wald interval and an exact Clopper–Pearson interval; explain differences and when each is appropriate.

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