.. _chapter5:

     Chapter 5: Bayesian Inference
     ===============================

     .. contents:: Chapter Contents
        :local:
        :depth: 2

     Overview
     --------

     This chapter covers bayesian inference. 

     Learning Objectives
     -------------------

     Upon completion of this chapter, students will be able to:

     * Understand the fundamental concepts
     * Apply computational techniques
     * Implement methods in Python

     .. toctree::
        :maxdepth: 2
        :caption: Sections

        bayesian_philosophy
prior_distributions
likelihood_posterior
bayesian_updating
credible_intervals
multiparameter_models
numerical_integration
mcmc_introduction
metropolis_hastings
gibbs_sampling
convergence_diagnostics
posterior_predictive_checks
model_comparison