Newsgroups: bit.listserv.psycgrad
Date:         Sun, 11 Oct 1992 21:32:29 -0800
              <PSYCGRAD@UOTTAWA.BITNET>
From:         "(Tor Neilands)" <tbn@UTXVM.CC.UTEXAS.EDU>
Subject:      more on MR texts (computer info)

Michael Wexler  (Michael Wexler@unc.bitnet or  Wexler@unc.oit.unc.edu)
writes:

=== Date:         Fri, 9 Oct 1992 11:10:00 EDT
=== From:         Michael Wexler <WEXLER@UNC.BITNET>
=== Subject:      Mult Regr, etc. but on a computer?

  Ok , you guys, you have mentioned many of the books I have
referenced in the past (or have been told to and skipped) and so
they are all very good suggestions.

However, I am looking for a  personal list (to be forwarded to the
world) of good books with some explanation, but lots of COMPUTER
examples.  I have one, for instance, with program code for SAS and
SPSSx, but never of the same technique in both.  So, I can do, for
example, multivar contrasts in SAS, but I only have program code
for dummy-variable coding in SPSS (useless technique, good
example).  You see?  And this is more than most books!

 As a grad, we don't have time to sit around figuring out how to
make th e package use the error term from the big model, or how to
set up contrasts in some oddball syntax.  SAS and SPSS manuals are
not for humans, only experienced stat gods wiht lots of time.
Systat is a bit better, but give a very non standard ouput (you
estimate the model, then choose an effect, then re-run
everything...  If you forget to do one step, you get 3 pages of
junk...)

  So, hit me or the list with your recc of a good, grad level stats
book with computer help.  The more recent, the better, but your
call.  Mainframe or micro, Mac or pc...

  I will compile and send to either the list or an editor....

  Thanks, and remember, a thesis is only a big, big book report...

 Michael Wexler@unc.bitnet or  Wexler@unc.oit.unc.edu

        A couple of suggestions. First, I'd recommend taking as much time
as you possibly
can to determine "what the elves in the computer are doing with your data"
as
one of my stats profs here is fond of saying. If you can't translate a
manual, that's okay. However, you might check and see if your university
has a statistical consulting group located somewhere. Here at UT, for
example, there are two groups, our group at the comp center, and then
another group in the Business School. One of our primary jobs is
translating manual language into real English for users. Usually
departments have at least one or two profs who are into stats, too...
        Having said that, I'll now jump down off of my soapbox and fire a
couple of references that may be handy:

1.      Sas applications and programming: A gentle introduction.
         Frank C. DiIorio. Pws-kent publishers, ISBN: 0-534-92390-9.
         It cost me about 23 bucks, but boy has it been worth it. Clear,
         version 6 updated, lots of examples, and it even has a chapter on
         regression. What more could one ask for? (never mind, that was a
         rhetorical question, and having just watched the prez debates
earlier
         this evening, I probably shouldn't be asking that question right
         about now...).

2.      A guide to SPSS for the analysis of variance. Gustav Levine.
         Lawrence Erlbaum and Associates. ISBN: 0-8058-0941-4.
         Lots of good examples of both code and output. Levine's no fool
         statistically, either.

I'm looking forward to hearing what texts others on the net have had good
experiences with....

cheers,

Tor



Tor Neilands, Systems Analyst
Statistical Support Services
                                          													              	
Internet: TBN@Utxvm.cc.utexas.edu
Address:
        Com 1
        Mail Code 12700
        UT Austin
        Austin, TX  78712
        Phone:  (512)-471-3241
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___________________________________________

" Two roads diverged in a yellow wood, and
  I...I took the road less traveled, and
  that has made all the difference ".
                                         --- Robert Frost
____________________________________________

"Life is too short to self-verify".
                                         --- Shawn McNulty
____________________________________________

Disclaimer: All views expressed above and herein are only those of
the author and do not necessarily represent the views of the University
of Texas, the UT Comp Center, and anyone else I've forgotten to include
in this disclaimer.
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