Bayesian Reasoning
StatisticsDecision MakingProbability
Bayesian Reasoning updates probabilities based on new evidence using Bayes' Theorem.
Introduction
Bayesian Reasoning updates probabilities based on new evidence using Bayes' Theorem.
Core Concepts
- Prior Probability: Initial belief or probability.
- Likelihood: Probability of observing evidence given the prior.
- Posterior Probability: Updated belief after considering evidence.
Applications
- Medical diagnostics for refining probabilities of conditions.
- Machine learning for probabilistic modeling.
Related Resources
- Tools: Bayesian inference libraries like PyMC3.
- Book: "Bayesian Data Analysis" by Andrew Gelman.