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Foreword
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1. Do we understand classical statistics?
2. The Bayesian choice
3. Posterior distributions
4. MCMC
5. The "baby" model
6. The linear model. I. The "fixed" effects model
7. The linear model. II. The "mixed" model
8. A scope of the possibilities of Bayesian inference + MCMC
9. Prior information
10. Model choice
Appendix
References.

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