QQ plots – Quantile-Quantile plots are a graphical technique for determining if two data sets come from populations with a common distribution. A q-q plot is a plot of the quantiles of the first data set against the quantiles of the second data set. By a quantile, we mean the fraction (or percent) of points below the given value. The 0.3 (or 30%) quantile is the point at which 30% percent of the data fall below and 70% fall above that value. A 45-degree reference line is also plotted. If the two sets come from a population with the same distribution, the points should fall approximately along this reference line. The greater the departure from this reference line, the greater the evidence for the conclusion that the two data sets have come from populations with different distributions. The advantages of the q-q plot are:

Sample sizes do not need to be equal

Many distributional aspects can be simultaneously tested.

For example, shifts in location, shifts in scale, changes in symmetry. The q-q plot is similar to a probability plot. For a probability plot, the quantiles for one of the data samples are replaced with the quantiles of a theoretical distribution.

If you find above information useful please share this post on social media, for more detailed information, please refer to below books: