Like with any language, there is a learning curve (trust me, I’m learning German at the moment), but we will take it step by step, and in no time you will be coding your own analyses and graphs! Thanks for joining us on your learning journey. This may seem a little daunting, but it also means a whole lot more flexibility, as you are not relying on a pre-determined toolkit for your analyses. R can be run entirely by typing commands into a text interface (welcome to the Matrix!). If you already know your way around statistical softwares like Minitab or SPSS, the main difference is that R has no graphical user interface, which means there are no buttons to click and no dropdown menus. With a huge online support community and dedicated packages that provide extra functionality for virtually any application and field of study, there’s hardly anything you can’t do in R. (Next time you need a fun fact, you can say “Did you know that S came before R?”) R is also the name of the software that uses this language for statistical computing. It was developed by Ross Ihaka and Robert Gentleman as an open source implementation of the “S” programming language. R is a statistical programming language that has rapidly gained popularity in many scientific fields.

In our first tutorial we will begin to explore “R” as a tool to analyse and visualise data.

Learn to manipulate R objects like vectors and data frames.

Develop the good habit of working with scripts.

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