What are the limitations of Bayesian statistics?

What are the limitations of Bayesian statistics?

Bayesian statistics has several limitations, including reliance on prior distributions, computational complexity, and potential for subjective bias.

Can you explain how prior distributions affect the results?

Certainly! The choice of prior distribution can significantly influence the posterior results, especially with limited data.

What are some common misconceptions about Bayesian statistics?

A common misconception is that Bayesian methods are purely subjective; in reality, they can be very data-driven.

How does Bayesian statistics compare to frequentist statistics?

Bayesian statistics incorporates prior beliefs and updates them with data, while frequentist statistics relies solely on the data at hand.

Are there specific fields where Bayesian statistics is particularly useful?

Yes, Bayesian statistics is particularly useful in fields like medicine, finance, and machine learning, where prior knowledge is valuable.