I think it's helpful to show the sampling variability in a QQ plot under repeated sampling. An example is given in Venables, Ripley pg 86. The variance is higher at the tails. Even when the distributions are the same, the QQ plot does not have to resemble a straight line because of sampling. I don't think you can think of any one of these as the "correct" plot.
Also, if the two data sets have an equal number of points, the empirical qq plot is simply a plot of one sorted data set against the other. (Kundu, Statistical Computing, pg 42). On Sun, Sep 27, 2009 at 9:06 AM, Duncan Murdoch <murd...@stats.uwo.ca> wrote: > Eric Thompson wrote: >> >> The supposed example of a Q-Q plot is most certainly not how to make a >> Q-Q plot. I don't even know where to start.... >> >> First off, the two "Q:s in the title of the plot stand for "quantile", >> not "random". The "answer" supplied simply plots two sorted samples of >> a distribution against each other. While this may resemble the general >> shape of a QQ plot, that is where the similarities end. >> > > The empirical quantiles of a sample are simply the sorted values. You can > plot empirical quantiles of one sample versus some version of quantiles from > a distribution (what qqnorm does) or versus empirical quantiles of another > sample (what Sunil did). The randomness in his demonstration did two > things: it generated some data, and it showed the variability of the plot > under repeated sampling. >> ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.