Literature on discriminant analysis Can anyone suggest a good book on discriminant analysis - comprehensible and detailed? (Kendall and Stuart write about the subject too concisely.) 
Thanks in advance. 
 A: Extended comment:
Linear discriminant analysis is a topic in 'multivariate analysis'.
If you google that topic for 'books' you will see, among other
things, a couple of pages on our associated site 'crossvalidated'
dealing with recommendations of books in the field. Take a look
to see which ones contain chapters on 'discriminant analysis'.
Modern books on multivariate statistics do not seem to focus
as much on discriminant analysis as older ones did. 'Cluster analysis' is not
exactly the same thing, but a related topic. Maybe your first
task is to find out if there is a related topic in multivariate
analysis that is of equal or greater interest to you. Perhaps
with online datasets and modern software to match.
Discriminant analysis was invented by R.A. Fisher. He illustrated
the key ideas with his now-famous dataset on iris flowers: 
petal and sepal lengths and widths for three species of
irises. The question is whether it is possible to DISCRIMINATE
among the three species using only these four measurements.
That is NOT just asking whether, for example, data indicate that
sepal widths have different species population means. It is asking whether the
sepal widths differ enough that you can identify which of the three species
a particular flower belongs to just knowing its sepal width. (The answer
is NO, but if you consider all four measurements in 4-space,
you can almost make an ID without error.)
Given the computational limitation of his time (1920s, I believe),
Fisher took some shortcuts. It might be a worthwhile (although
certainly not original) senior project to do a modern discriminant
analysis of the iris data using R or some other statistical
package. The iris dataset is of moderate size and has no
missing data--as you specified.
Some years ago I published a book 'Learning Statistics with Real
Data' in which one chapter used an older version of Minitab
to do a somewhat more modern discriminant analysis of the iris
data than Fisher's. (I say 'somewhat', because the Minitab procedure
available then made some assumptions that aren't quite true.)
The book is out of print (used copies on Amazon for \$5-\$10), but if you google my faculty profile
to get my contact info, I can email you a .pdf of the chapter.
There is an inexpensive Google-Sage book on discriminant
analysis by Klecka (1980) with editorial collaborators I know.
But I have not looked at it. Given the date, I do not suppose
you will get much help there with computation or large datasets,
but it might be a good orientation.
I also noticed there is a You Tube demo on discriminant analysis
using R. At least the price is right.
The modern computationally oriented books I have seen on
discriminant analysis seem to assume you already know what it
is and just want to know how to run a particular computer
program.
Your faculty adviser should give you some guidance as to the
subject and level of your project. Statistics, linear algebra,
graphics, and computation all play roles in discriminant
analysis. I won't make specific recommendations because I
don't know enough of your background, requirements of such
a project, or your enthusiasm for getting into unfamiliar
territory. 
