# Normal distribution

The normal (or Gaussian) distribution is a stochastic model commonly used for estimating sensor uncertainty. The law is given by:

$y(x)=\frac{1}{\sigma.\sqrt{2.\pi}} e^ {-\frac{(x-c)^2}{2\sigma^2} }$

Where:

• $\sigma$ is the standard deviation (square root of the variance)
• $c$ is the center of the gaussian

$variance=\sigma^2$

Here are some examples of normal distributions:

As the sum of probabilities must be equal to one thus the following surface is equal to one:

68, 95 and 99.7% of the surface is included in respectively $\sigma$, $2.\sigma$ and $3.\sigma$:

## One thought on “Normal distribution”

1. What’s up, just wanted to tell you, I enjoyed this post.
It was practical. Keep on posting!