Standard Gaussian Random Variable as Transformation of Gaussian Random Variable

Theorem
Let $\mu$ be a real number.

Let $\sigma$ be a positive real number.

Let $X \sim \Gaussian \mu {\sigma^2}$ where $\Gaussian \mu {\sigma^2}$ is the Gaussian distribution with parameters $\mu$ and $\sigma^2$.

Then:


 * $\dfrac {X - \mu} \sigma \sim \Gaussian 0 1$

where $\Gaussian 0 1$ is the standard Gaussian distribution.