Hey, I didn't mean to stomp on you, and I'm sure you're actually
right-thinking and not muddleheaded.  This is the same advice I
generally offer grad students.  I end up wording it strongly primarily
because I have been That Guy that lost an interesting result from
point-and-click stacks when I was in grad school, so I offer the advice
in terms that are strong enough that I hope even I would have paid some
attention to when I was a strong-willed grad student.  Sorry if I gave
offense.

Walt Borges wrote:
>
> While Jim and I agree (apparently) that R is the best program to learn,

Actually, my point was that it doesn't really matter which is the best
to learn.  To get through a program and dissertation as a
normal-to-quantish Americanist, you can expect that you're going to have
to learn some Stata and some R (or some boutique software) no matter
what you use to run OLS, completely irrespective of their actual worth
over a career-long period.

> I'll even defend "point and click," -- to a point. It's helpful
> especially when you use it to set up graphics. I really don't see value
> in spending a whole lot of time programming the graphics. Grad students
> don't have a lot of time, and frankly, the graphic artists are better
> with the graphs and tables.

Sure, and with Stata it's not too bad because all the point and click
does is generate a command to pass to the CLI, so you can copy the
command to a text file if you remember to do so.

But using point and click interfaces to statistical software, at least
for analysis, really is leading yourself into temptation.  It's easy to
acquire bad habits that then come back and bite at inopportune moments.
  It also makes it exceedingly, annoyingly difficult to help students
deal with their actual data problems because there's no program or
command stack to look at and see just what part of their analysis went
blooey.

> Finally, a lot of the secondary data sets we students use must be
> converted into CSV format for use in R. Sometimes its easy to do,
> sometimes it's not. Just depends on how much I can afford to spend this
> semester on programs to do the conversion. Comprendo?

If you have the usual full range of statistical software, the usual
answer would be to load it into whatever it's native to and then export
it to a csv.  Even SPSS and SAS seem to be able to do this, though SAS
probably wants to charge you $38000 for the relevant package.

--
James S. Coleman Battista
Dept. of Political Science, Univ. of North Texas
[log in to unmask]    (940)565-4960

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