Introduction to R

Version 1.1

Designed for statistical analysis and reporting, R is a powerful tool for data analysis. This course focuses on the application of key data skills, providing opportunities to build confidence, independence, and resilience.

This 1 day course will introduce you to the building blocks of R including objects, vectors, and data frames and will examine common data types (e.g. character, factor). During the course we will also cover data manipulation using dplyr and data visualisation using ggplot with examples from the gapminder dataset.

Course objectives

The aim of this course is to equip you with a toolbox to get started with data in R and Rstudio and to provide a sound foundation from which to continue your learning beyond the classroom.

Learning objectives

  • Familiarise themselves with RStudio and R Notebooks, which is what we’ll use to interact with R;
  • Learn about the simple data structures in R: object, vector, and data frame;
  • Explore R’s basic data types = integer, character, numeric, etc;
  • Learn to read data into R;
  • Introduction to data wrangling using the tidyverse set of metapackages;
  • Use the tidyverse verbs to explore the gapminder data set which includes statistics for countries around the world including life expectancy, population, and GDP per capita;
  • Learn to merge datasets using left_join;
  • Create meaningful visualisations of the data using ggplot2;
  • Learn where to go for help.

Course type

E learning – Available

Self learning – Available

Face to face – Not available

Skill level

This courses is aimed at complete beginners with no prior programming experience.

Course materials

All course materials can be found on the Data Science Campus Github page

Booking

To discuss booking this course for remote delivery, please contact the Data Science Campus Faculty.