2.0-PART-II.Rmd

# (PART) BAYESIAN DATA ANALYSIS {-}

# Introduction to PART II {#PART-II}

```{r fig.align='center', echo=FALSE, fig.link=''}
knitr::include_graphics('images/part_II.jpg', dpi = 150)
```

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## Further reading {-} 
A really good introductory book to Bayesian data analyses is [@McElreath2016]. This book starts with a thorough introduction to applying the Bayes theorem for drawing inference from data. In addition, it carefully discusses what can and what cannot be concluded from statistical results. We like this very much.

The developer of the `brms` package, Paul Bürkner, is writing a [book](http://paulbuerkner.com/software/brms-book/) that is already partly available online. It is a helpful cookbook with understandable explanations. We very much look forward to the finished book, that may bundle all the helpful vignettes and help-files to the functions of the `brms`package. 

We like looking up statistical methods in papers and books written by Andrew Gelman [e.g. @Gelman2014] and Trevor Hastie (e.g. [@Hastie2009, @Efron2016]) because both explain complicated things in a concise and understandable way.