[R] Using R in a university course: dealing with proposal comments

Mon Feb 11 07:06:17 CET 2008

      R is "just a tool", but so is English.  R is the platform of 
choice for an increasing portion of people involved in new statistical 
algorithm development.  R is not yet the de facto standard for nearly 
all serious research internationally, to the extent that English is.  
However, I believe that is only a matter of time. 

      There will always be a place for software with a nicer graphical 
user interface, etc., than R.  For an undergraduate course, it may be 
wise to stick with SPSS, SAS, Minitab, etc. 

      Are you teaching graduate students to solve yesterday's problems 
or tomorrow's? 

      Much of my work in 2007 was in Matlab, because I am working with 
colleagues who use only Matlab.  Matlab has better debugging tools.  
However, R now has well over 1,000 contributed packages, and r-help and 
r-sig-x provide better support and extensibility than you will likely 
get from commercial software.  Twice in the past year, an executive said 
I should get some Matlab toolbox.  In the first case, after thinking 
about it for a few days, I finally requested and received official 
permission from a Vice President.  From that point, it took roughly a 
week to get a quote from Mathsoft, then close to two weeks to get 
approval from our Chief Financial Officer, then a few more days to 
actually get the software.  With R, that month long process is reduced 
to seconds:  I download the package and try it.  This has allowed me to 
do things today that I only dreamed of doing a few years ago. 

      Moreover, R makes it much easier for me to learn new statistical 
techniques.  When I'm not sure I understand the math, I can trace 
through a worked example in R, and the uncertainties almost always 
disappear.  For that, 'debug(fun)' helps a lot.  If I want to try 
something different, I don't have to start from scratch to develop code 
to perform an existing analysis.  I now look for companion R code before 
I decide to buy a book or when I prioritize how much time I will spend 
with different books or articles:  If something has companion R code, I 
know I can learn much quicker how to use, modify and extend the 
statistical tools discussed. 

      Spencer Graves

Bill.Venables at csiro.au wrote:
> Comment 1 raises a real issue.  R is just a tool.  Too often people do
> confuse the tool with the real skill that the people who use it should
> have.  There are plenty of questions on R-help that demonstrate this
> confusion.  It's well worth keeping in mind and acting upon if you can
> see a problem emerging, but I would not take it quite at face value and
> abandon R on those grounds.
>
> Comment 2 is one of those comments that belongs to a very particular
> period of time, one that passes as we look on.  It reminds me of the
> time I tried to introduce some new software into my courses, (back in
> the days when I was a teacher, long, long ago...).  The students took to
> it like ducks to water, but my colleagues on the staff were very slow to
> adapt, and some never did.  Also, R wins every time on price!
>
>
> Bill Venables
> CSIRO Laboratories
> PO Box 120, Cleveland, 4163
> AUSTRALIA
> Office Phone (email preferred): +61 7 3826 7251
> Fax (if absolutely necessary):  +61 7 3826 7304
> Mobile:                         +61 4 8819 4402
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> mailto:Bill.Venables at csiro.au
> http://www.cmis.csiro.au/bill.venables/ 
>
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
> On Behalf Of Arin Basu
> Sent: Monday, 11 February 2008 1:41 PM
> To: r-help at r-project.org
> Subject: [R] Using R in a university course: dealing with proposal
> comments
>
> Hi All,
>
> I am scheduled to teach a graduate course on research methods in
> health sciences at a university. While drafting the course proposal, I
> decided to include a brief introduction to R, primarily with an
> objective to enable the students to do data analysis using R. It is
> expected that enrolled students of this course have all at least a
> formal first level introduction to quantitative methods in health
> sciences and following completion of the course, they are all expected
> to either evaluate, interpret, or conduct primary research studies in
> health. The course would be delivered over 5 months, and R was
> proposed to be taught as several laboratory based hands-on sessions
> along with required readings within the coursework.
>
> The course proposal went to a few colleagues in the university for
> review. I received review feedbacks from them; two of them commented
> about inclusion of R in the proposal.
>
> In quoting parts these mails, I have masked the names/identities of
> the referees, and have included just part of the relevant text with
> their comments. Here are the comments:
>
> Comment 1:
>
> "In my quick glance, I did not see that statistics would be taught,
> but I did see that R would be taught.  Of course, R is a statistics
> programme. I worry that teaching R could overwhelm the class.  Or
> teaching R would be worthless, because the students do not understand
> statistics. " (Prof LR)
>
> Comment 2:
>
> Finally, on a minor point, why is "R" the statistical software being
> used? SPSS is probably more widely available in the workplace -
> certainly in areas of social policy etc. " (Prof NB)
>
> I am interested to know if any of you have faced similar questions
> from colleagues about inclusion of R in non-statistics based
> university graduate courses. If you did and were required to address
> these concerns, how you would respond?
>
> TIA,
> Arin Basu
>
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