Mastering pandas - Second Edition

Applications of Bayesian statistics

Bayesian statistics can be applied to many problems that we encounter in classical statistics, such as the following:

• Parameter estimation
• Prediction
• Hypothesis testing
• Linear regression

There are many compelling reasons for studying Bayesian statistics, such as using prior information to better inform a current model. The Bayesian approach works with probability distributions rather than point estimates, thus producing more realistic predictions. Bayesian inference bases a hypothesis on the available data—P(hypothesis|data). The frequentist approach tries to fit the data based on a hypothesis. It can be argued that the Bayesian approach is the more logical and empirical one as it tries to base its belief ...