Posterior Probability using Bayes' Theorem
Probability Theory DS practice problem on Onlearn.
Difficulty: medium.
Topics: Understanding Bayesian Inference and Conditional Probability, Bayes' Theorem Formula, Complementary Events, Normalization Constant, Hypothesis Testing, Sensitivity and Specificity, Probability Theory, Statistical Inference, Mathematics, Data Analysis, Machine Learning Foundations, Bayesian Statistics, Conditional Probability, Law of Total Probability, Prior and Posterior Distributions, Evidence Likelihood.
Implement a function that computes the posterior probability of a hypothesis H given evidence E. The function should accept the prior probability P(H), the conditional probability of the evidence given the hypothesis P(E|H), and the conditional probability of the evidence given the complement of the hypothesis P(E|not H).