GTDA Poll: What software are you itching to learn?

I have two. I have gone as far as buying phone-book sized manuals. They stand on my desk, mocking me, exuding their “new, unused book smell”.

R

Yes, I know it is high-end, extraordinarily flexible, and doesn’t suffer from the bloat and baroque passive-agressive coding of SAS. But I know SAS. I learned SAS using punch cards. And I don’t want to sound like a pirate.

Dreamweaver CS3

Gawd I hate web design programs. It used to be MS Frontpage. An abomination. Currently I use Adobe’s Go Live! CS2. That program!, and the people behind hit!, are personally responsible for the collective loss of about 4 cm! of my stomach lining!. Now Adobe has bought Dreamweaver.  Do I have any reasonable expectation for things to be better? No. But it is integrated with all the other Adobe stuff that I do use.

So have at it. What software do you feel compelled to learn, through some combination of peer-pressure (yeah, Aaron, I’m talkin’ bout you), slick marketing (Oh! A piece of candy! Oh! Another piece of candy!), and serious issues with procrastination? Leave your approach-avoidance conflicts in the comments.

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5 Responses to GTDA Poll: What software are you itching to learn?

  1. Scott says:

    I finally dove into the world of R about a month ago. I am sorry I did not do it earlier. It is worth if for the graphs alone. No other software (even the dedicated graphing apps) gets close.

    The biggest barrier for me was simply where to start (the reason I did not get to it earlier). What finally worked for me was picking my simplest-to-analyse dataset and sticking with R throughout. My advice is don’t start with a giant book that mocks you. Start by figuring out how to import a simple data set from excel, and how to run a simple test (say, a linear regression) on it. For me, everything followed from that.

  2. Geoff says:

    I’ve spent the past few days trying to determine where to begin learning Processing, a data visualization programming language. I think I’m going to start by picking up Ben Fry’s Visualizing Data book from O’Reilly.

    I’ve heard a few people say that R is worth a shot, so maybe I’ll make that a summer project, too.

  3. Winawer says:

    I use R all the time; when I write simulation software, I usually use R as a backend graphing tool, and I use it for all of my data analysis. Having said that, everything I do in R just seems to be *hard*. It’s never easy to get something done in R; I’ve written non-trivial amounts of code in about 10-12 languages, and of them all R is the most frustrating to me (with the possible exception of C++…). Added to that, my experiences with the R mailing lists when I needed help were disappointing, and frankly the responses made me sorry that I had ever asked. All told, I usually cringe when I have to write new R code, but I can’t deny that it’s probably the best choice out there.

    As for things I’m learning, or itching to learn: I’m learning LISP right now (which is a *real* mindjob, I’ll tell ya), and I’m looking forward to maybe getting up to speed on SQL to store the data I’m starting to accumulate….

  4. Scott says:

    See, that’s the problem with R. It is so powerful as a programming language that it is seems terrifying to those that want to use it instead of a point and click stats package.

    Winawer is clearly and advanced user with detailed knowledge of many programming languages. That’s great. But for the average biologist that wants to free themselves from the clutches of SPSS (etc), the R world is populated by people that are using R for really advanced purposes. In other words, I think there is a big difference between ‘learning R’ and ‘using R for statistical analysis’. The latter is actually quite easy, but it is hard to figure out how to get going when looking around in R forums, etc.

    Eventually ‘using R for stats’ will teach you the R programming language in the broader sense, but in the meantime, the figures in your publications will look way better and you won’t have to worry about your site license expiring, and if you will need an expensive upgrade if you upgrade your OS (or, MK, your dependency on Windows for running SAS after finally switching to Mac :o).

    Any biologists out there thinking of using R for stats should start tinkering with the analyses they use on a regular basis. The more complicated stuff will come once you start to launch R as your default app for simple stats. Just my 2 pence.

  5. Peter says:

    The best way to learn R as a non-statistician is probably, as Scott says, to do some of your regular analyses in it. Start with one of the free manuals to get the basics (http://cran.r-project.org/other-docs.html), then have a look at the task views to see what other people in your field are using (http://cran.at.r-project.org/web/views/).
    The R-help mailing list can be intimidating, but most of the specialized ones are very friendly.

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