Introduction

Master the basics of working in R on this 2-day course.

Our highly experienced R trainer has many years of experience and has written a number of books on R.

This course is very hands-on. This means that there is plenty of time to experiment with what you are being taught, try things out for yourself and ask questions.

By the time you finish, you’ll be comfortable using a wide range of R’s core features.

✔ A complete beginner’s R course that covers all of the basics.
✔ Plenty of one to one attention and time to ask questions.
✔ Friendly expert trainers, small groups and a comfortable place to learn.
✔ All the materials and extras that you’ll ever need.
✔ Ongoing support and help with issues you have after the course.

What Will I Learn?

By the end of this course you will have covered all of the key skills that you will need to use R independently.

You will have learned how to:

  • Import and export data.
  • Basic data analysis and testing techniques.
  • Regression modelling and data visualisation.

Am I Ready for this Course?

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.

The Training Day

Our courses run from 9.30am to roughly 4.15pm with refreshments throughout the day and a break for a tasty, freshly prepared lunch.

We offer a relaxed, supportive learning environment, fully air-conditioned facilities and some of the nicest instructors on the planet.

Also, you’ll receive:

✔ A full-colour manual covering everything in the course so that you can recap.
✔ A USB stick for the course exercises to let you practice more in your own time.
✔ A Certificate of Attendance.

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.

  • Simple maths
  • Object names
  • Joining Items
  • Getting help
  • 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.

  • Disk Directories
  • Importing data
  • Managing data items
  • Types of data object
  • Exporting data
  • Object properties
  • Subsetting
  • Re-aranging

During this session you see how to gather summary statistics from different types of data.

  • Summary statistics
  • Manipulating 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.

  • Tabulation
  • Cross tabulation

Statistical testing

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.

  • Data distribution
  • Random numbers
  • Tests of distribution type

Statistical tests 

  • Stats tests (t, U, cor, chi)

Graphics

  • R Graphics (basics)

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.

  • Formula notation
  • ANOVA
  • ANOVA summary