[R-SIG-Mac] learning R

Rolf Turner r.turner at auckland.ac.nz
Fri Dec 10 22:25:50 CET 2010

I agree with you completely about ``begging the question''.  The
nearly universal misuse of this expression drives me crazy.  I'm
not so sure about ``steep learning curve'' however.  My impression
is that this phrase has *always* been used to convey the idea that
a subject area is difficult to learn, whence to use it (as you suggest)
in the sense that the subject area can be learned quickly would be to
change the original meaning of the phrase.  That would be undesirable,
even given that the original meaning is counter-intuitive.

I recall having heard/read a ``justification'' for the original meaning
to the effect that what is envisaged is plotting effort expended on
the *y* axis and knowledge level on the *x* axis.  Thus a steep learning
curve would entail expending a great deal of effort for a small increase
in knowledge.

I agree that this is a silly choice of axes --- I certainly wouldn't make
such a choice.  But I don't suppose that there's any law against it.


		Rolf Turner

On 11/12/2010, at 4:22 AM, Carl Witthoft wrote:

> Next to "begging the question,"  the phrase "steep learning curve" is
> probably the most misused cliche out there.
> A 'learning curve' represents knowledge (or understanding) as a function 
> of time.  THerefore,  the steeper the better.
> Please help save the English language from descent into Humpty-Dumpty 
> land, and train your colleagues in the correct usage of both these terms.
> Carl
>> Message: 2 Date: Thu, 9 Dec 2010 09:51:27 -0800 From: Payam
>> Minoofar<payam.minoofar at meissner.com> To:
>> "r-sig-mac at r-project.org"<r-sig-mac at r-project.org> Cc:
>> "deniz.kellecioglu at gmail.com"<deniz.kellecioglu at gmail.com> Subject:
>> [R-SIG-Mac] R for Mac, good enough?
>> Message-ID:<53DF393B-2037-4B0D-890F-8DBAA1BA1F55 at meissner.com>
>> Content-Type: text/plain; charset="us-ascii"
>> The power of R is virtually unmatched, and R for Mac works extremely
>> well.
>> The learning curve is steep, however, and documentation is difficult
>> to grasp, even though it is abundantly available. I am more partial
>> to a commercial data analysis package with which I grew up, but I
>> have done enough work with R on the mac platform to recommend it
>> highly.
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