## Definition of Normal Distribution

A continuous random variable $X$ is said to have an normal distribution with parameter $\mu$ and $\sigma$ if its p.d.f. is given by
```
$$
\begin{equation*}
f(x)=\left\{
\begin{array}{ll}
\frac{1}{\sigma\sqrt{2\pi}}e^{-\frac{1}{2}\big(\frac{x-\mu}{\sigma}\big)^2}, & \hbox{$-\infty< x<\infty ;-\infty < \mu < \infty; \sigma^2>0$;} \\
0, & \hbox{Otherwise.}
\end{array}
\right.
\end{equation*}
$$
```

Normal Probability Calculator | |
---|---|

Mean ($\mu$) | |

Standard deviation ($\sigma$) | |

P(X< A) | |

P(X > B) | |

P(A< X < B) | and |

Outside A and B | and |

Results | |

Required Probability : |