The formula for Bayes’ Theorem is shown below. As you can see, there are three components to it. We find it helpful to call these components ingredients and think of the answer as all of the ingredients combined. For every question you come across, you’ll need to find each ingredient and plug it into the formula.

### Simple Bayes’ Theorem Definitions To Get You Started

- The vertical bar | stands for given that.
- P stands for Probability.
- A & B are Events.
- P(A) and P(B) are the probabilities of events A and B. Each event is separate from the other and does not impact the other.
- P(A|B) is the probability of event A being true given that event B is true.
- P(B|A) is the probability of event B being true given that event A is true.

Using the above definitions, the entire formula can be read as follows:

The formula as a whole is built using basic algebra. It might look complicated but it is actually quite user-friendly. Every time you use the formula all you need to do is remember the three ingredients, find them, plug them into the formula, and voila. You will then have an updated probability based on new information; you’ll have P(A|B), which is technically called the Posterior Probability and is a normalized weighted average.

Continue on to Chapter 3: Bayes’ Theorem Examples to Get You Started.

- Home: BayesTheorem.net
- Chapter 1: Bayes’ Theorem for Dummies
- Chapter 2: Bayes’ Theorem Formula: A Simple Overview
- Chapter 3: Bayes’ Theorem Examples to Get You Started
- Chapter 4: Bayes’ Theorem Flu Example
- Chapter 5: Bayes’ Theorem Breathalyzer Example
- Chapter 6: Bayes’ Theorem Peacekeeping Example
- Chapter 7: No P(B) Provided and What Are You Looking For?
- Chapter 8: No P(B) Provided – Bayes’ Theorem Flu Example
- Chapter 9: Bayes’ Theorem in Real Life Use: Search and Rescue
- Chapter 10: Bayes’ Theorem in Real Life Uses: Spam Filtering
- Chapter 11: Bayes’ Theorem History
- Chapter 12: Books on Bayes’ Theorem
- Chapter 13: Articles on Bayes’ Theorem
- Chapter 14: Videos on Bayes’ Theorem