  Exploratory data analysis is often used to test the goodness-of-fit of sample
observations to specific target distributions. A few such graphical tools have
been extensively used to detect subexponential or heavy-tailed behavior in
observed data. In this paper we discuss asymptotic limit behavior of two such
plotting tools: the quantile-quantile plot and the mean excess plot. The weak
consistency of these plots to fixed limit sets in an appropriate topology of
$\mathbb{R}^2$ has been shown in Das and Resnick (Stoch. Models 24 (2008)
103-132) and Ghosh and Resnick (Stochastic Process. Appl. 120 (2010)
1492-1517). In this paper we find asymptotic distributional limits for these
plots when the underlying distributions have regularly varying right-tails. As
an application we construct confidence bounds around the plots which enable us
to statistically test whether the underlying distribution is heavy-tailed or
not.
