R Programming Course (Introduction)

Welcome to the fascinating and exciting world of R programming. R is an elegant programming language specifically designed for data science, analytics, and statistics. This ‘R for Beginners’ course takes you through the fundamental skills and techniques required to use R.

By the time you leave this focused R tutorial, you will be equipped with the required skills to embark on your own data science adventures. Even the most inexperienced participants will walk away from the course with newfound confidence using R for statistics and data analysis.

Bringing a combination of private, public, and academic professional experience, your instructor will guide you through this R tutorial, showing you step by step how to utilise R.

You’ll set up R and the excellent development environment RStudio, import external data, utilise add-in packages, process data for specific use, derive elementary summary statistics, and produce basic statistical visualisations.

We encourage you to use the CCE R Programming level self-assessment tool if you are unsure which course level to enrol in.

Aims

This course aims to provide a practical introduction to the R programming language. By the end of the day-long course, the user will be comfortable operating in the R environment, including importing external data, manipulating data for specific needs, and running summary statistics and visualisations.

Outcomes

By the end of this course, you should be able to:

• download and install R and RStudio

• navigate and optimise the R integrated development environment (IDE) RStudio

• install and load add-in packages

• import external data into R for data processing and statistical analysis

• learn the main R data structures – vector and data frame

• compute basic summary statistics

• produce data visualisations with the ggplot package

• solve fundamental error problems.

Content

• The R Statistical Programming Language

• The RStudio Integrated Development Environment (IDE)

• Data importation methods

• Basic R Data Types

• Data processing and manipulation techniques

• External add-in packages for R

• Summary statistic functions

• Data visualisations using ggplot

• Error types

Intended Audience

• Business professionals

• Managers

• IT knowledge workers

• Lifelong learners looking to use and understand the basics of R

Prerequisites

This course is designed with the beginner in mind. While some participants may have experience in other computer programming languages, no prior programming skills are required.

Delivery Modes

• Face-to-face, presenter-taught training using your own device

• Online training via the platform Zoom

Face-to-face classes

These classes run in a classroom and you need to bring your own device with R and RStudio installed. You should ensure it is fully charged as access to power is limited. Please note that the University does not carry any responsibility for your lost, stolen, or damaged devices whilst on the University premises.

Online classes

You will need your own device with R and RStudio installed.

Delivery Style

This course is taught through a series of concepts, examples, problem exercises, and in-class knowledge challenges. The material is presented so that participants of varying backgrounds, skills and abilities can all move together in a brisk, but comfortable learning pace.

Utilising principles of productivity, efficiency, and time management, the course material and timeline is structured to optimise learning and value add.

Materials

A link to access and download the following online course materials is provided:

• PowerPoint notes with examples

• all code and script files used throughout the course

• ancillary hand-outs and learning aids.

Before The Course

You will need your own device with R and RStudio installed. Both pieces of software are free to download.

Recommended Reading

• DeVries, A 2015, R for Dummies, 2nd edition, For Dummies.

• Jones, O, Maillardet, R, and Robinson, A 2014, Introduction to Scientific Programming and Simulation Using R, 2nd edition, Chapman and Hall/CRC.

• Wickham, H 2019, Advanced R, 2nd edition, Chapman and Hall/CRC.

• Wickham, H 2017, R for Data Science, O’Reilly Media.