Some ResouRces for getting started with the open source statistical programming language R. If you’re new to the program, here’s a few starters. The general R list nabble and R-help. If you don’t use an RSS reader service, now’s the time to subscribe to R-bloggers RSS which brings everything conveniently together in one handy feed.

Using R for ecological data analysis has improved my understanding of statistical analysis and forced me to learn basic computer programming skills. I can’t emphasize how important it is to continue learning these two skills throughout your academic and scientific career. Despite having taken statistics courses both as an undergraduate and graduate student, when you have your own dataset to analyze, there is nothing in the world that prepares you more than a deep grasp of statistical tools.  Although I am nowhere fluent in any programming language, I enjoy using R. In bioinformatics, C, C++, C#, Java, Perl and Python are all commonly used languages (Reference), but R is increasingly being used. Within the field of ecological analysis or eco-informatics R enables ecologists to visually and quantitatively represent and apply new models and dynamic plots.



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