# Develop an Intuition for Bayes Theorem With Worked Examples

Last Updated on August 19, 2020

Bayes Theorem provides a principled way for calculating a conditional probability.

It is a deceptively simple calculation, providing a method that is easy to use for scenarios where our intuition often fails.

The best way to develop an intuition for Bayes Theorem is to think about the meaning of the terms in the equation and to apply the calculation many times in a range of different real-world scenarios. This will provide the context for what is being calculated and examples that can be used as a starting point when applying the calculation in new scenarios in the future.

In this tutorial, you will discover an intuition for calculating Bayes Theorem by working through multiple realistic scenarios.

After completing this tutorial, you will know:

- Bayes Theorem is a technique for calculating a conditional probability.
- The common and helpful names used for the terms in the Bayes Theorem equation.
- How to work through three realistic scenarios using Bayes Theorem to find a solution.

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