Over the last decade, there has been a dramatic shift in the statistical tools ecologists use. Historically, many scientists have been able to get by with using just a few software packages for analyzing ecological data. Some of the most popular are those with slick easy to use 'point and click' interfaces (Excel, Systat, Minitab). More advanced tools like Matlab have also become popular - Matlab offers flexible models to be built from the command line (or code) and is widely used in other disciplines (finance, engineering, etc). The big downside to Matlab is the price of a license. In the last decade, a new programming environment known as 'R' has emerged - recently the NY Times highlighted the utility of R for data analysis.

So why should you use R?
1. Cost: R is free.  You get what you pay for, of course, so the support is somewhat limited and can be unhelpful.
2. Platform independence: you can use R in Windows, Mac, Linux
3. Scientists being trained at universities are being taught to almost exclusively use R. At SAFS for example, the quantitative curriculum has shifted from Excel/VB to R in the last 2 years. The learning curve can be a bit steep initially, but there's a large community of people using R at the NWFSC.
4. Development: Packages with cutting edge methods are updated constantly by some of the world's best statisticians.
5. Plots: Making a plot in R can be tricky, and often requires experimentation; at the same time, it's possible to make great, publication-quality plots.

Northwest Fisheries Science Center Short Course
With the shift to R occurring at universities and government labs, a number of biologists have approached us in the last year emphasizing the need for a course designed specifically for the analysis of ecological data. Following the model adopted at USGS, our goal is to develop a course that exists in an online format - rather than teach it annually and cap enrollment, employees can pursue this valuable training on their own schedule.