Learning Data Mining with Python - Second Edition

Understanding Bayes' theorem

For most of us, when we were taught statistics, we started from a frequentist approach. In this approach, we assume the data comes from some distribution and we aim to determine what the parameters are for that distribution. However, those parameters are (perhaps incorrectly) assumed to be fixed. We use our model to describe the data, even testing to ensure the data fits our model.

Bayesian statistics instead model how people (at least, non-frequentist statisticians) actually reason. We have some data, and we use that data to update our model about how likely something is to occur. In Bayesian statistics, we use the data to describe the model rather than using a model and confirming it with data (as per the frequentist ...