Bayesian Data Analysis for Animal Scientists

Beschreibung

In this book, we provide an easy introduction to Bayesian inference using MCMC techniques, making most topics intuitively reasonable and deriving to appendixes the more complicated matters. The biologist or the agricultural researcher does not normally have a background in Bayesian statistics, having difficulties in following the technical books introducing Bayesian techniques. The difficulties arise from the way of making inferences, which is completely different in the Bayesian school, and from the difficulties in understanding complicated matters such as the MCMC numerical methods. We compare both schools, classic and Bayesian, underlying the advantages of Bayesian solutions, and proposing inferences based in relevant differences, guaranteed values, probabilities of similitude or the use of ratios. We also give a scope of complex problems that can be solved using Bayesian statistics, and we end the book explaining the difficulties associated to model choice and the use of small samples. The book has a practical orientation and uses simple models to introduce the reader in this increasingly popular school of inference.

An easy and intuitive introduction to Bayesian methods with Monte-Carlo Markov Chain methods (MCMC)

The author uses colours to help the understanding of the formulae and numerous graphs to make the inferences more intuitive

Examples are taken from published papers and common problems in the field of biology and agriculture

New ways of expressing uncertainty are proposed, to help researchers derive conclusions from their experiments

Autor*in

Agustín Blasco

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Bayesian statistics Animal production Animal breeding MCMC, Monte-Carlo Markov Chain methods

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