A very useful distribution in statistics and in psychology is the normal distribution . Normal distributions are unimodal, symmetric, and bell-shaped. They are characterized by having many cases close to the mean and increasingly fewer as one moves further away from the mean.
Normal distributions provide good approximations to chance processes like tossing a coin many times.
Many of the most important procedures for statistical inference rely on the assumption that the raw data are normally distributed. The normal distribution provides a degree of statistical precision we wouldn t otherwise have. If we know the data are normally distributed we can figure out the exact percentage of cases that lie between any 2 points on the dimension of interest. These numbers are worth memorizing. The rule can easily be used to compute percentile ranks if the data are normally distributed.