Tom is correct....those are all "descriptive statistics". But so are
the folks that talk about the normality requirement when handling
outliers based on standard deviations. I still don't fully understand
what Zone is trying to accomplish. The original post spoke to
determining the quartile points, which doesn't require normality. But
there was also talk of truncating the data set to those points lying
within 2.5 standard deviations of the mean, which does require
normality. There are other methods of handling outlying data. You
might look into methods for accommodating outlying data (as opposed to
eliminating them from the data set). One such method is known as the
Winsorized Mean method.

If you are looking to understand the dataset, then why not plot it?
Create 2 plots, a probability density function (PDF) and a cumulative
density function (CDF). These are easy to make, even for very large
datasets. A histogram is very similar to a PDF and can be created
using the Analysis ToolPak add-in. Google these terms and develop
the necessary albeit brief understanding of the concepts. Then you
will likely be in a better position to help your friend.

John