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A student's guide to Bayesian statistics

A student's guide to Bayesian statistics

Lambert, Ben

Paperback, Book. English.
Published Thousand Oaks, CA: SAGE Publications, 2018.
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Statement of responsibility: Ben Lambert
ISBN: 1473916364, 9781473916364
Note: Includes bibliographical references and indexes.
Physical Description: xx, 498 p. : ill. ; 25 cm.
Subject: Bayesian statistical decision theory.


  1. How best to use this book
  2. I: An introduction to Bayesian inference
  3. The subjective worlds of Frequentist and Bayesian statistics
  4. Probability - the nuts and bolts of Bayesian inference
  5. II: Understanding the Bayesian formula
  6. Likelihoods
  7. Priors
  8. The devil is in the denominator
  9. The posterior - the goal of Bayesian inference
  10. III: Analytic Bayesian methods
  11. An introduction to distributions for the mathematically uninclined
  12. Conjugate priors
  13. Evaluation of model fit and hypothesis testing
  14. Making Bayesian analysis objective?
  15. IV: A practical guide to doing real-life Bayesian analysis: computational Bayes
  16. Leaving conjugates behind: Markov chain Monte Carolo
  17. Random walk metropolis
  18. Gibbs sampling
  19. Hamiltonian Monte Carlo
  20. Stan
  21. V: Hierarchical models and regression
  22. Hierarchical models
  23. Linear regression models
  24. Generalised linear models and other animals.