Normal distribution, sometimes called the bell curve, is a common way to describe a continuous distribution in probability theory and statistics. In the natural sciences, scientists typically assume that a series of measurements of a population will be normally distributed, even though the actual distribution may be unknown. But even if you assume that measurements of a population should be normally distributed, a sample taken from that population will not necessarily be normally distributed. Why is that?
In this Click & Learn, you will explore what sample distribution looks like when samples are taken from an idealized population of a defined mean and standard deviation. You can also explore graphically the standard error of the mean and how it is determined.
The following browsers are supported and recommended for this Click & Learn. Please be sure that JavaScript is enabled and your pop-up blocker is disabled.
Google Chrome version 9 or greater.
Mozilla Firefox version 9 or greater.
Apple Safari version 5 or greater.
Microsoft Internet Explorer version 9 or greater.
(The calculations may take minutes on slower devices/older browsers.)
Date created:
11/20/2015
Date modified:
11/20/2015
