You can start with our page with useful links!Īs we said before, R itself does not have a graphical interface, but most people interact with R through graphical platforms that provide extra functionality.

R has a very active and helpful online community - normally a quick search is all it takes to find that somebody has already solved the problem you’re having.

Because R is a programming language rather than a graphical interface, the user can easily save scripts as small text files for use in the future, or share them with collaborators.

R is free and open source, and always will be! Anybody can use the code and see exactly how it works.

If you need any more convincing, why are we using R and not one of the many other statistical packages like MATLAB, Minitab, or even Microsoft Excel? Well, R is great because: 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.

How to run r studio abline