To revive the topic:

I'm teaching a summer class at Columbia (3 hours/2x per week/6 weeks),
which is titled "Social Statistics", but into which I plan to integrate
SWC material. This happened partly for fortuitous reasons: I don't have
a separate lab session, so I get a computer lab for every class (why not
live code); the existing syllabus uses Stata (why not rewrite the whole
thing as R in jupyter notebooks); I have the same latitude over the
"lab" content as I would if I was a TA.

Any advice on putting together a syllabus like this would be
appreciated! In particular, I'm trying to work out how much time to
spend on basic R concepts vs. cookbook recipes for particular analyses.
I don't think I'll have time for anything outside of the R and
Reproducible R lessons, except for a bare minimum shell stuff (paths,
etc.). I also anticipate that it might be a challenge to separate out
the stats and programming concepts, so that the students understand that
the R way of doing something is an implementation rather than a
definition.

Also, any heads-up on whether there is funding available somewhere to
support developing this?


Cheers,

Adam



On Sat, Oct 4, 2014, at 08:59 PM, Daniel Chen wrote:
> Is anyone writing about this? otherwise I will since I asked the
> question :p
>
> On Tue, Sep 30, 2014 at 7:54 AM, Greg Wilson <gvwilson@software-
> carpentry.org> wrote:
>> Would someone like to summarize this thread in a blog post?  I've
>> learned a lot, and I'm sure other people would too...
>>
>>
-- 
>> 
Greg Wilson
>> 
Software Carpentry | http://www.software-carpentry.__org/
>> 
>> 
>> _________________________________________________
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