This beginners R training course will introduce you to the basic skills needed to use work with R.
It covers all of the key skills that you will need to use R independently. These include importing and exporting data, some basic data analysis and testing techniques and then finally regression modelling and data visualisation.
Our highly experienced R trainers have many years of experience and will quickly get you using R confidently. Our courses are hands-on which means that you will leave the course with plenty of practical R experience.
Once you have completed this course you will be ready to move onto our Advanced R training course.
This is a two day course for a group but could be reduced to 1 day for 1-2 people.
This beginners R training course will introduce you to the basic skills needed to use and work with R.
The course covers the key skills that you will need to use R independently. These skills include importing and exporting data, working with R data objects, summary statistics, basic data analysis and hypothesis testing techniques as well as data visualisation.
This course does not assume any prior familiarity with R. A general working knowledge of basic statistical hypothesis testing would be helpful but is not essential.
Our courses run from 9.30 am to approximately 4.30 pm.
When you book a course with use you get the following:
The first session gives you an introduction to R and gets you using it. We carry out some simple mathematics and also look at finding help and how to access additional command packages.
This section covers more introductory material (for example, how to import and export data) and also introduces the concept of objects. It then moves on to how to handle and manipulate objects.
During this session you see how to gather summary statistics from different types of data.
Tables and frequency data
In this session you’ll find out how to make frequency tables from data tables. You’ll also learn about cross tabulation and how to change data from one form to another.
Here you will look at basic hypothesis testing as well as presenting the results in a graphical format. The session will cover simple differences tests, correlation and tests of association. You’ll also look at random number generation and different kinds of data distribution.
The final session of the course will look at some methods of statistical modelling. You’ll focus on analysis of variance (ANOVA), a widely used analytical tool. The step-up from basic hypothesis testing to more advanced techniques is an important one and will give you a good foundation to explore more modelling methods (e.g. machine learning) in the future.
You’ll see how to use the powerful formula notation to describe analytical situations. You will also learn how to present the results graphically.