Bayesian inference is being increasingly used as an alternative approach to null hypothesis testing. The main tool in BI are Monte Carlo simulations, used to randomly sample posterior distributions of guessed parameters. The number of iterations grows exponentially with the number of parameters, making common laptops and desktop struggle with computation capacity. Our goal is use NAISS Small Compute / Uppmax resources to help us understand better and develop our BI skills. In other words, we need Uppmax to put in practice Bayesian Inference tools.