That's incorrect... - Edit 1
Before modification by Shannow at 29/10/2012 10:31:11 AM
A Bell Curve by definition means that the distance from the weakest to the strongest channeler is intersected at exactly the 50% mark by the mean (the average channeler). Any skewing of the distribution would mean that the term “Bell Curve” cannot be applied to the distribution. Instead, it would then be either a positively or negatively skewed distribution. But not a Bell Curve.
This is simply wrong. First of all, when people say bell curve, or Gaussian distribution or whatever, they never mean it literally. Nothing can ever have a perfect Gaussian distribution, as you would need an infinite sample size. However, loads of things are described to an excellent approximation by a bell curve. That is what people mean when they say something is described by a bell curve.
Secondly, there is no reason to assume the average is at half the maximum value. You can very well have a distribution which is symmetric, aside from being truncated at zero. In that case, the average strength would be slightly shifted away from the most likely strength (the top of the curve). However, it could still be perfectly reasonable to call it a bell curve.
A Bell Curve is a perfectly normal distribution. Perfectly symmetrical. Otherwises it's not a Bell Curve.
EDIT:
Copied from statistics.com
There are several features of bell curves that are important and distinguishes them from other curves in statistics:
•A bell curve has one mode, which coincides with the mean and median. This is the center of the curve where it is at its highest.
•A bell curve is symmetric. If it were folded along a vertical line at the mean, both halves would match perfectly because they are mirror images of each other.
•A bell curve follows the 68-95-99.7 rule, which provides a convenient way to carry out estimated calculations:
•Approximately 68% of all of the data lies within one standard deviation of the mean.
•Approximately 95% of all the data is within two standard deviations of the mean.
•Approximately 99.7% of the data is within three standard deviations of the mean.