| Definition |
-
The random variable x can have any value
between -inf to +inf
-
The distribution is symmetric about the first
moment (=mean)
-
The term "normal distribution" is often used
for any distribution looking like a normal distribution. In order to
avoid any mistakes the term "standard normal distribution", or "standard
normal probability density function" should be used for normal
distributions which have a standard deviation of 1.0 and a mean of 0.0.
|
| Graphical View |
 You may
test the shape of the normal distribution for various standard deviations by
starting the following interactive example . |
| Applications |
One of the most important distributions in statistical theory, but
frequently not occurring as often expected. The importance of the normal
distribution in statistics is caused by the central limit theorem. Examples
-
body-height of adult women between 40 and
50
-
blood pressure
-
results of analytical measurements
|
| First Moment |
Mean: m |
| Second Moment |
Variance: s2 |