For many things that can be measured in the real world, such as heights, baby weights, IQ scores, etc., the distribution of those measures tends to follow a specific pattern. That pattern is that about two-thirds of the measures that you take will bunch evenly on either side of the average for all the measures, and then fewer and fewer of the measures will fall further away. This pattern of distribution is called the normal distribution, and it is represented graphically by the bell curve, which is produced using a histogram.
In statistics speak, normally distributed data share a central tendency, such that approximately two thirds (68%) of all the measures taken fall within one standard deviation of the mean (average), and that they are distributed symmetrically — 34% above the mean and 34% below the mean. Ninety-five percent of measures fall within two standard deviations, again evenly split above and below the mean. At three standard deviations, you get 99.7% of the measures.
Measures that fall outside of three standard deviations are generally regarded as outliers and not included in many analyses.
Distributions that are not normal are asymmetrical around the mean and are referred to as skewed.
