# Using predicted probabilities and bayesian inference to update beliefs

I'm currently working on a project to predict the likelihood of an outcome. I'd like to implement a system where the belief the event will happen is updated after running the model on new data. However, I'm having trouble figuring out exactly how to implement that. Any explanations of updating beliefs using Bayes theorem would be helpful.

• Bayesian data analysis is a huge field. There's a textbook of that name that I think you should find a copy of in order to figure out the next step forward. – Alex L Jun 6 '19 at 0:24

If you are interested in Bayesian statistical models I suggest you to take a look at an R package called JAGS, that you can use to implement pretty much any Bayesian model, and with ready-to-go MCMC algorithms.