Bayesian updating definition
Lesson 5 introduces the fundamentals of Bayesian inference.Beginning with a binomial likelihood and prior probabilities for simple hypotheses, you will learn how to use Bayes’ theorem to update the prior with data to obtain posterior probabilities.UC Santa Cruz is an outstanding public research university with a deep commitment to undergraduate education.
Applications of the theorem are widespread and not limited to the financial realm.
This module introduces concepts of statistical inference from both frequentist and Bayesian perspectives.
Lesson 4 takes the frequentist view, demonstrating maximum likelihood estimation and confidence intervals for binomial data.
In Lesson 2, we review the rules of conditional probability and introduce Bayes’ theorem.
Lesson 3 reviews common probability distributions for discrete and continuous random variables.
In this module, we review the basics of probability and Bayes’ theorem.