An introduction to R

Overview

We live in a data intensive world and it is becoming increasingly important to learn and understand software tools for handling data. The volume of data being produced is increasing rapidly and researchers frequently need to collate, analyse and visualise their data in order to prepare it for publication.

This course will introduce you to R, one of the most powerful statistical software tools available today. The R software is completely free to use and it has an active global community, it is also one of the most widely used programs for statistics and graphics in scientific research, with tens of thousands of published papers citing R every year.

This suite of three short courses is designed to introduce beginners to the R software. We encourage you to complete all courses in the series but you are also welcome to finish only the courses that are of interest to you.

Why choose R?

There are a variety of statistical software tools available so why choose to learn R?

• It’s free
• There are loads of examples online
• It works on all platforms (Mac, Windows, Linux…)
• You can create many different graph types
• There are thousands of packages available
• There is a large global R community

There are several different software programs available for statistics but R is one of the most popular, especially among researchers, due to its flexibilty and comprehensive set of packages. Knowledge of R is also a useful transferable skill that is highly valued by employers from a range of sectors, from data science to marketing.

Who is this course for?

This course is designed for anyone who would like to learn R from scratch. No previous knowledge of the R software is required and we think it may be of particular interest to PhD students and postdoctoral researchers.

Please note that this is not a course on statistics: the focus of the course is on learning the R software, not learning statistical methods (though we do provide a statistics textbook for reference.) A background in statistics is not required but a knowledge of basic statistical concepts will be helpful.

Testimonials

"Easy to follow, instructions are written clearly, nice use of multiple choice sections to test learning (and a nice introduction to further courses using Swirl). Nice "code-as-you-go" format.

"Extremely helpful, easy to follow each step and written in a non complicated manner."

"Enjoyed the course as it was interactive and got me started using R. Course was easy to navigate."

"This is a nice introductory course for R which teaches the basic commands/ functions etc. clearly."