Normal Distribution |
(continuous probab dist for equations) |
Usage: |
NormalDist (x, m, s) |
Definition: |
[1/(s sqrt(2p))] exp (-[(x-m)/s]^2 / 2) |
Required: |
s > 0 |
Support |
- ¥ < x < ¥ |
Moments: |
mean = m standard deviation = s g1 = 0 b2 = 3 |
The normal distribution, or approximations of it, arise frequently in nature (this is partly explained by the = 4 && typeof(BSPSPopupOnMouseOver) == 'function') BSPSPopupOnMouseOver(event);" class="BSSCPopup" onclick="BSSCPopup('X_PU_central_limit_theorem.htm');return false;">central limit theorem). Since it also has many convenient mathematical properties it is the most commonly used continuous distribution.
For this distribution, 68.2% of the probability is within 1 standard deviation of the mean, 95.4% is within 2 standard deviations, and 99.74% is within 3 standard deviations.
If m = 0, s = 1 it is known as a “standard normal” distribution.