  The QQ plot is a commonly used technique for informally deciding whether a
univariate random sample of size n comes from a specified distribution F. The
QQ plot graphs the sample quantiles against the theoretical quantiles of F and
then a visual check is made to see whether or not the points are close to a
straight line. For a location and scale family of distributions, the intercept
and slope of the straight line provide estimates for the shift and scale
parameters of the distribution respectively. Here we consider the set S_n of
points forming the QQ plot as a random closed set in R^2. We show that under
certain regularity conditions on the distribution F, S_n converges in
probability to a closed, non-random set. In the heavy tailed case where 1-F is
a regularly varying function, a similar result can be shown but a modification
is necessary to provide a statistically sensible result since typically F is
not completely known.
