How does Bayesian inference work?

Can you explain how Bayesian inference works?

Sure! Bayesian inference is a statistical method that updates the probability for a hypothesis as more evidence or information becomes available.

What are the key components of Bayesian inference?

The key components are the prior probability, the likelihood of the evidence, and the posterior probability, which is the updated belief after considering the evidence.

Can you give me an example of how it's used in real life?

Absolutely! One common example is in medical diagnosis, where doctors update the probability of a disease based on test results.

How does it differ from frequentist statistics?

Bayesian statistics incorporates prior beliefs and updates them with new evidence, while frequentist statistics relies solely on the data at hand without prior beliefs.