Normal - Gaussian Distribution

We expect most of our measurements to be close to the mean and symmetrical around it

Probability density function of a gaussian:

f (x) = \frac{1}{\sqrt{2 π σ^{2}}} \exp (- \frac{(x - μ)^{2}}{2 σ^{2}}) .

The parameter ⁠μ⁠ is the mean or expectation of the distribution (and also its median and mode), while the parameter $σ^{2}$ is the variance. The standard deviation of the distribution is the positive value ⁠σ⁠ (sigma).