Catching the wave

Recently, we were down in New Orleans for The Society for Social Work and Research annual meeting.  While we enjoyed all that that city has to offer, we also enjoyed something else.  We've noticed that R seems to be growing in popularity among social work researchers!

Two years ago, we did a workshop at SSWR on analyzing single-system data using our package, SSDforR.  We believe it may have been the first workshop at SSWR ever focusing on the use of R. Last year, we discovered that Joe Mienko, Richard Smith and Gregor Passolt had a workshop in addition to another one that we did.  And then there were two.

THIS year, there were three R-based workshops - we did one on effect sizes, Joe and his colleagues, David Rothwell, Richard Smith and Gregor Thomas, did one on visualizing data, and Kaipeng Wang, from Boston College, did a third on basic statistics using R.  And we jointly hosted a special interest group - which is basically a collection of like-minded people who sit down and chat about a particular topic.

So our question is - are we catching a wave?

We think so!

As we arrived back in New York, we got inspired to see how popular R really is becoming, and this is what we found (purely anecdotal folks) -

LinkedIn has a pretty active group for social science researchers called "Research, Methodology, and Statistics in the Social Sciences."  One recent poster wanted recommendations for basic books about R.  He got 42 replies in less than a week.  Another wanted volunteers to beta test an R package he wrote for educational purposes.  He got 76 replies!

This is sort of the buzz we've been hearing on the academic and popular fronts:

1)  R is free.  As in no cost.  Ever.  Big highlight.

2)  SPSS, probably the most widely used statistical package in the social sciences, is getting more expensive.  So expensive that they have basically priced themselves out in many cases.

3)  Most social service agencies have little to no budget for statistical software so....  why teach students to use something that they will likely never have access to once they leave school.  Why not give them tools that they can bring into the field and build research capacity in the agencies in which they work?

4)  The learning curve for learning R is less steep than rumors might suggest.  We are successfully using it in all our research classes and, it seems, other schools are picking it up, too.  Including some of the biggies.

5)  This week, Microsoft announced its purchase of Revolution Analytics, a firm that leverages the power of R to analyze "big data."

So.....

We come back from New Orleans INVIGORATED and ready to do more work with R!