Although no data set is exactly normally distributed, most statistical analyses require that the data be approximately normally distributed for their findings to be valid. One way of testing for normality is through a quantile-quantile (q-q) plot, a technique for determining if data sets originate from populations with a common distribution.
In this tutorial, you will determine if a data set is normally distributed by comparing its quantiles against those of a theoretical normal distribution. You will also learn how to make a data set nearly normally distributed.
Oct 3, 2012 Update: I’ve added a new figure to the article and reworked few lines.