Excuses for illness made, I would like to write today on my experience of concurrent enrollment with Phd.
My advice would generally be that is you are in the third year of your Phd, don't do it.
However, back when I did undergrad there was no talk of R. You used excel or Ostats, or far off in the distance there was this Matlab thing, that I thought was some sort of engineering software. Excel for mac no longer even has a statspak, and my work has suffered a random walk towards palaeoclimatology: a far cry from the 'sample size of one' I was so pleased with when I studied Pterosaurs. The result? This is a gap in my skills I will have to rectify, or change my Phd topic.
Two years in, I attended a half-day course run by the UQ School of Biology stats advisor. It wasn't bad, but grossly insufficient for my needs. I have been banging my head against R for a year now, with the patient assistance of an R expert in my lab. Three years in, I enrolled in some more R courses.
I am currently enrolled in "Computing for Data Analysis" run on coursera.org by John Hopkins Bloomberg School of Public Health. I am impressed with the energy Roger Peng, the course organiser, is putting into the course, but with tens of thousands of students enrolled, getting the help you need is definitely part of the skills you are learning.
With no programming background, a history of frustration with statistics, and possible dyscalcula, I am swinging between mysterious highs when I finally get something to work, and mostly wallowing in the lows of frustration, sometimes as low as pondering if this is the career for me, and maybe I would be better off applying for one of those brewing jobs I saw advertised in Melbourne.
It is now less the 2 weeks until I go to SVP in Raleigh to present some work I haven't finished yet, let along written up, and part 1 of assignment 1 just took me two and a half days to complete. If this wasn't so damn important, I would not still be enrolled.
So as I said, my advice is that is you are in the third year of your Phd, if it isn't make or break, don't do it.
My subject reading for this week has largely been R-help and The R Book. While I think R-Help is an invaluable resource, it contains many R-sholes. It is certainly off-putting for those starting out. While searching previous answers is very handy, I don't think I will be asking questions there any time soon.
