We have been talking about R (well, actually pushing R)
as a good replacement for proprietary statistical software for some time, but
we thought we’d take this opportunity to share with you WHY we think this is.
By the way, we have developed this thinking more clearly
recently because of conversations we’ve had with our esteemed editor, Dana
Bliss, at Oxford University Press, and our colleagues, Dr. John Orme and
Matthew Cuellar, down in the relative warmth of Knoxville, Tennessee.
1) As educators, we
should be teaching our students to use software that they have access to once
they go out into the field. From our own
little anecdotal survey, very few social service agencies have SPSS, which is
what most schools teach, so what good is it to teach students skills that they
can’t apply later?
Can we convince agencies to use SPSS? Wouldn’t that be easier? The answer to that is most likely not. SPSS is expensive. Really, really expensive. SPSS is sold in different versions and with
different modules. If you’d like to
purchase the high-end networked version, it will set you back tens of thousands
of dollars. Per year. You’ve got it – licenses are only good for
one year.
2) R is cutting edge. We have only talked about using R for statistical analysis, but it can
be used for much, much more.
Think social service agency again. You may be producing similar reports
regularly. You might, for instance, have
to report to your board how many clients you served in a quarter, how many
terminated, etc. You may have to show
graphs. Or you may need to do more
sophisticated analysis, such as determining how successful your programs are.
You can actually create dynamic documents in R with some user-contributed packages
that will run your analysis and insert your findings, tables and graphics
AUTOMATICALLY in your documents. Way cool.
3) R has statistical capabilities that that
really expensive software can’t do. For
all that money you just spent, you still can’t do it all! How disheartening is
that?
4) We are pretty
certain that the steep learning curve that people write about is not quite as
steep as you may think. Sure, if you
want to run diagnostics on your logistic regression, you may have some learning
to do, but you can easily solve that problem by purchasing a REALLY GOOD BOOK
THAT IS GOING TO BE AVAILABLE FROM OXFORD UNIVERSITY PRESS IN JUNE FOR A GREAT
PRICE. Or you can spend thousands and
thousand per year for SPSS. But then
you’ll still have some learning to do.
Bottom line – we have been teaching R to our students for a
couple of years now (yes, we converted from SPSS) and we have seen NO
difference in our students’ abilities to learn statistical methods. If anything, our students are learning more
now because they install R on their home computers and can practice skills we
teach in class at home.
5) All the cool kids
are doing it! R is growing in popularity across all sectors. This includes academia, science, and
business. Microsoft, for example, just
purchased Revolution Analytics, a firm that focuses on using R for analyzing Big Data. R
is powerful and everyone knows it, including the “big boys.”
6) Resources
abound. You can learn about R, in large part, for FREE! A good starting point is http://cran.r-project.org/, the home of
all things R. Here, you can find, downloadable manuals, a
refereed journal, and a list of recommended books. Or go to YouTube and enter “R + statistics.” The last time we did that, we got 381,000
results. And in the spirit of things
being freely available, top-notch universities including Harvard, UC Berkley,
and Johns Hopkins are offering classes on R
via massive open online courses such as Coursera and edX.
R is just good for
the planet.
And did we mention R
and all of its packages are FREE?
Yup. We love R.
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