In this chapter, we present several Bayesian techniques in R, using either STAN or JAGS (both are the most important software packages that can be used in R). Bayesian statistics is fundamentally different from classical statistics. In the latter, parameters are fixed quantities that need to be found. In the Bayesian framework, parameters are random variables themselves that can be learned. Furthermore, Bayesian statistics allows us to incorporate prior knowledge about a distribution that we want to learn, and update it accordingly.