# Sampling from a Normal Distribution

One of the most common probability distributions is the normal (or Gaussian) distribution. Many natural phenomena can be modeled using a normal distribution. It's also of great importance due to its relation to the Central Limit Theorem.

In this post, we'll be reviewing the normal distribution and looking at how to draw samples from it using two methods. The first method using the central limit theorem, and the second method using the Box-Muller transform. As usual, some brief coverage of the mathematics and code will be included to help drive intuition.