Assessing credibility of a q-q plot by presence of outliers

What proportion of a data set should significantly betray a particular
distribution in order to reject the hypothesis that this is the correct
distribution (i.e. how many points in a data set of n=100, say, should
lie significantly away from the diagonal line in a q-q plot)?

I have a q-q plot that seems to have all the hallmarks of a correct
fit, but there are data points in upper quantiles that don't fit the
line. Are there any web references on this topic?

Thanks for any help you can give.

.

Relevant Pages

  • How to perform Least-Squares fit to gaussian integral?
    ... least-squares fitting method to determine sigma and mu for a gaussian ... distribution using a data set that is known to be of the integral of ... a simple function and a gaussian, but the expression to fit is not ...
    (sci.stat.math)
  • Re: Excel - trend line generators
    ... the fit points. ... You can generate trend lines for the motions of the planets ... using a model based on cycles and epicycles. ... a good fit to your data set. ...
    (sci.crypt)
  • Re: Computing derivative using finite differnce method
    ... Inorder to compute the asympotic covariance of the MLE of Weibull ... I took the data set: ... and the loglikehood function for the Weibull distribution fuction: ...
    (comp.soft-sys.matlab)
  • Re: Distribution Fitting and GoF Tests
    ... Regarding the p-value, I'm assuming the higher the p-value, the ... to be significant if you use the entire data set. ... from the theoretical distribution might be statistically ... It's true that the K-S test and some others require that the ...
    (comp.soft-sys.matlab)
  • Re: small data set
    ... The problem is the very small data set (25 ... distribution function, you can use the 25 observations to ... the tasks are:to produce two classifiers ... I tried to use SVM, Linear regresion, Backpropagation and ...
    (comp.soft-sys.matlab)