Bayesian Model and Hypothesis Testing

Question 1

How does Bayesian hypothesis testing differ from traditional hypothesis testing?

Answer 1

Bayesian hypothesis testing involves comparing the probability of different hypotheses, considering prior beliefs and likelihoods. It provides a continuous measure of evidence.

Question 2

What is a Bayesian model, and how does it help in hypothesis testing?

Answer 2

A Bayesian model represents the researcher’s beliefs about possible outcomes. It incorporates prior information, likelihood, and allows continuous updating of beliefs based on new data.

Question 3

How does the choice of prior in Bayesian modeling impact results?

Answer 3

The choice of prior influences the Bayesian model’s outcome. Sensible priors, based on existing knowledge, contribute to accurate representations of hypotheses and their likelihoods.