Gosh, everyone's going to have a different opinion on this, especially
on the relative value of preparing tables and graphs for publication
submissions.

From an analysis standpoint, and as someone who learned all these
programs over the last two years, I would list the pros and cons thus:

SPSS --         pro:    Good point and click features
                        Relatively easy to work with data
                con:    Expensive on a students' budget
                        Program coding is not intuitively based

STATA --        pro:    Intuitive and simple program coding
                        Decent point and click
                        Simple, logical command structure
                        You can create "do-file" programs that process
data and                                run analytical programs; these
can be assembled into                           master do-files that
allow you to work off the                                       original
data set each session, rather than saving
modified data sets (which can quickly become
confusing, especially when several team members are
working with the data)
                        Decent graphics.
                        Relatively inexpensive for students

                con:  Inevitably you will need to deal with a data or
graphics                                issue that will send you to the
seven-volume manual.                            Someone in the
department better have one you can                              use,
because it's real expensive. The good news is
that you will probably find the instructions there
and understand them.
                        In-program help files are incomplete and often
not                                     helpful. Example: The STATA
typeface makes the                                      percent sign,
which is used in graphics commands,
                                look like a capital N on screen. I spent
four hours                              using the on-screen help in
trying unsuccessfully                           to format a graph
before going to the manual and                          discovering this
annoying little problem.
                        The program for time-series analysis is not
fully                                   developed, but the alternative
software is far more                            expensive.


R --            pro:    Price: freeware.
                        Exceptionally versatile: you do the programming,
so your                                 abilities are the limits of its
capabilities.                           Library of add-on components for
specialized analysis.
                        Easy access to outside modules (such as WinBugs
for                                     Bayesian analysis)
                        Excellent graphic capabilities.

                con:    Non-intuitive, object-based programming
structure                                       (however, if you are
familiar with computer                                  programming
structures, this is not too much of a
problem).
                        Importing data sets (major pain in the butt).

Personally, although I learned SPSS first, I prefer Stata for most
projects, although time series analysis is easier in E-Views and RATS
(both very expensive). The trick is learning how to format data in sets
in Stata using do-files. Once you learn that, Stata is a cheap, quick
and easy way to conduct most basic analysis. For advanced analysis and
Baysian, R is really the only choice.

Walt Borges
Doctoral candidate
University of Texas-Dallas


-----Original Message-----
From: Political Methodology Society [mailto:[log in to unmask]] On
Behalf Of Michael Plenty
Sent: Wednesday, October 04, 2006 4:42 PM
To: [log in to unmask]
Subject: [POLMETH] R vs. Stata vs. SPSS

My name is Mike and I work as an intern for a major consulting firm in
Washington,DC.

My company uses SPSS, as most undergraduate programs and companies,
however,
now that I'm beginning the thinking process for graduate school, most
schools, in particular Northwestern, UChicago, and Yale, all recommend I
become familiar with Stata and R.

Are there any major differences between the three programs?

If so, what? and what resources are out there to help me adjust?

Michael Plenty

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