Bayesian statistics

Bayesian statistics is an approach to data analysis and parameter estimation based on Bayes' theorem. Unique for Bayesian statistics is that all observed and unobserved parameters in a statistical model are given a joint probability distribution, termed the prior and data distributions.

1. What is Bayesian statistics used for?
2. What is Bayesian statistics simple?
3. What makes Bayesian statistics different?

What is Bayesian statistics used for?

Bayesian statistics is a particular approach to applying probability to statistical problems. It provides us with mathematical tools to update our beliefs about random events in light of seeing new data or evidence about those events.

What is Bayesian statistics simple?

“Bayesian statistics is a mathematical procedure that applies probabilities to statistical problems. It provides people the tools to update their beliefs in the evidence of new data.”

What makes Bayesian statistics different?

Frequentist statistics never uses or calculates the probability of the hypothesis, while Bayesian uses probabilities of data and probabilities of both hypothesis. Frequentist methods do not demand construction of a prior and depend on the probabilities of observed and unobserved data.