What is Bayesian statistics and how does it work?
Bayesian statistics is a statistical paradigm that uses Bayes' theorem to update the probability of a hypothesis as more evidence becomes available.
Can you explain Bayes' theorem in simple terms?
Sure! Bayes' theorem relates the conditional and marginal probabilities of random events. It shows how to update the probability of a hypothesis based on new evidence.
What are some practical applications of Bayesian statistics?
Bayesian statistics is used in various fields, including medicine for diagnostic testing, finance for risk assessment, and machine learning for predictive modeling.
How does Bayesian statistics differ from frequentist statistics?
The main difference is that Bayesian statistics incorporates prior beliefs and evidence, while frequentist statistics relies solely on the data at hand.
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