Other Distributions
Probability plots for distributions other than the normal are computed in exactly the same way. The normal quantile function G is simply replaced by the quantile function of the desired distribution. That is, a probability plot can easily be generated for any distribution for which one has the quantile function.
One advantage of this method of computing probability plots is that the intercept and slope estimates of the fitted line are in fact estimates for the location and scale parameters of the distribution. Although this is not too important for the normal distribution since the location and scale are estimated by the mean and standard deviation, respectively, it can be useful for many other distributions.
The correlation coefficient of the points on the normal probability plot can be compared to a table of critical values to provide a formal test of the hypothesis that the data come from a normal distribution.
Read more about this topic: Normal Probability Plot