Open source refers to programs that are publicly accessible and publicly modifiable – and this also means that learning to code in R also comes with a huge community of people interested in making it more practical, useful and accessible in the widest range of contexts possible. The best part about R is that it is all free and open source. It’s not hard to see why! Before you learn R: Get R and R Studio The neuroscience lab that I work in is particularly obsessed with R as a platform for statistical analyses of experiments and creating beautiful graphs for theses and scientific journal article submissions. Using code also helps to be open about data analysis, and sharing it can lead to more reproducible research and greater scientific integrity! Research techniques can be shared, discussed and tweaked by multiple scientists across different disciplines to produce better quality research outcomes.įor someone like me (who spent an entire undergraduate degree working with SPSS), it didn’t take long to get hooked on programming in R. If you ever get six months down the track and wonder why a certain participants’ data looks like this and not that, you’ll likely have written exactly what transformations you did to it in your code (aka script). You can also see exactly what you did at every step of your analyses. Compared to working with data in excel – if your spreadsheet is suddenly deleted – there’s no way you’d be able to create means, delete columns and add rows from the raw data again, simply with one keyboard shortcut. If at some stage some sorted or edited data files go missing, you can easily re-run your code to create everything again from scratch. Having all your data processes written in code from the very first step, means if anything goes wrong at any stage, you’ll always have the script of exactly what you did. Some people can be totally freaked by the idea of coding, but programs such as R help science become more transparent and actually help you to keep track of your analysis process. I’m thinking you’ve come to this page because your time to learn R is now! These programming languages are emerging as some of the most popular tools in data science for data exploration (with graphics) and statistical computing.

If you are in the world of research, there is no doubt that you haven’t yet heard of R and R Studio.

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