A short Q&A about our course called R 4 – Visualisation and data exploration.
Here we have Måns Thulin, the course developer, answering a few common questions.

Next course date is on Zoom March 31

What is visualisation and data exploration?
Exploratory data analysis is used to summarize and visually explore a dataset. It can be used for presentation purposes but is also a vital part of any statistical analysis. Data exploration is used to generate hypotheses, for outlier detection, and much more. It also includes unsupervised learning techniques like clustering, where the aim is to find interesting subgroups and patterns in the data.

What is covered in the course?
Topics covered include outlier detection, visualisation of trends, and multivariate data. We’ll also cover cluster analysis as well as dimension-reduction of complex data using principal component analysis (PCA). In addition, you’ll learn how to create interactive plots, select colours for your figures, and much more.

Why should you attend the course?
Being able to create plots that are both relevant and good-looking is an incredibly useful skill for anyone working with data. Not only does it help you present your findings to others, but it can also guide your analyses and help you discover things that you otherwise would have missed. Doing analyses without good visualisations and without proper data exploration is a bit like driving with your eyes closed: you might end up in the right place, but you might also end up somewhere completely different, where you shouldn’t have gone. If you do any kind of data analysis and haven’t had a course like this, I highly recommend attending our R4 course.