Online: Data Analysis with R

R is a language that has become one of the most popular tools for manipulating, visualizing and analyzing data. While there are many R courses, learning these skills can involve a steep learning curve, especially for people with no experience in programming or data analysis. This two-day remote course (delivered via Zoom) aims to help with this initial difficulty by equipping learners with essential skills in using R, including data wrangling and plotting.

The course topics include data importing and exporting, handling real-life data sets and creating publication-ready plots with R. The topics will be covered using both hands-on teaching and independent exercises.

Learning outcomes

After attending this course, participants will be able to:

– Navigate RStudio
– Understand R syntax and how to write R code
– Import and export data using R
– Use tidyverse for data wrangling
– Use ggplot2 for creating high-quality plots

Before the course

You need a Haka account to access the course environment. If you do not have one, please contact us (jesse.harrison@csc.fi) as soon as possible after registering. You do not have to install R or RStudio on your own computer, as the course will run on an RStudio environment available on the CSC Notebooks service. Instructions for logging into Notebooks using your Haka login details will be supplied in advance (please also make sure that you are able to log in before the course).

Note that the RStudio teaching environment used for the course comes complete with data sets that are not part of a standard R installation. For this reason and to ensure that all participants are using the same R package versions, please do not use your own R / RStudio installation during the course.

Prerequisites

– No prior experience of programming or using R is expected
– No data analysis or statistical experience is required
– A Haka account is required to access CSC Notebooks

Program

Day 1

09:00 – 14:30
Hands-on teaching via Zoom
Basic features of R
Starting with data
Data manipulation (introduction)

14:30 onward
Independent exercises:
Data manipulation (continued)

Day 2

09:00 – 14:30
Hands-on teaching via Zoom
Feedback and solutions to independent exercises
Data visualization (introduction)

14:30 onward
Independent exercises
Data visualization (continued)

Breaks

10:30 – 10:45 (short coffee break)
12:00 – 13:00 (lunch break)