Master Bayesian Statistics: Thinking in Probabilities
Master Bayesian Statistics — Learn to Think in Probabilities, Not Just P-Values
9
students
1 hour
content
Apr 2025
last update
FREE
regular price
What you will learn
Students will be able to explain Bayesian thinking, contrast it with frequentist methods, and understand why Bayes’ Theorem is useful for updating beliefs with
Students will break down Bayes’ Theorem, define priors, likelihoods, and posteriors, and apply them in basic examples like medical testing and coin tosses.
Students will compare credible and confidence intervals and apply Bayesian decision-making using posterior probabilities, risk, and utility.
Students will apply Bayesian thinking to regression, hierarchical models, and model checking using visual tools like PPCs and trace plots.
Students will apply Bayesian logic to A/B testing, networks, and machine learning, and address common misconceptions about Bayesian statistics.
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udemy ID
12/04/2025
course created date
20/04/2025
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