Understanding Data with R

About

Which companies are committing fraud? Which scientific hypothesis is correct? Do movie critics differ from regular consumers in their ratings? Whether it’s a fun or serious question, each of these questions require data to answer them. In this course, you will learn the two vital skills for using data to answer questions of interest: 1) data manipulation; 2) data analysis.

In this interactive two-week course, you will learn through interactive workshop-sessions how to manipulate datasets so that you can produce informative analyses and insightful data visualizations. Importantly, you will not only learn data analysis techniques, but also how to use these techniques to answer questions.

We will use the popular programming language called R to manipulate data, run statistical tests, and produce data visualizations. No prior programming knowledge is required, although some knowledge of statistics is preferred.

Course leader

Dr. Willem Sleegers

Target group

Bachelor’s and Master’s students with a basic understanding of statistics who want to gain experience in coding and data analysis.

Course aim

This course about understanding data. Data is used to answer all kinds of questions, by both academics and companies. Academics use data to support scientific hypotheses, while companies rely on data to determine such things as insurance rates, fraud, or marketing success. In this course, you will learn the two vital skills for using data to answer questions of interest: 1) data manipulation and 2) data analysis. Through interactive workshop-sessions, you will learn how to manipulate datasets in order to produce informative analyses and insightful data visualizations. Importantly, you will not only learn how to analyze data, but also to answer questions.

The course makes use of interactive teaching methods aimed at developing all the necessary skills to become a data analyst, in a way that does not require substantial prior knowledge. While many courses are aimed at a singular aspect of data analysis (e.g., just statistical analysis, or just learning how to program), this course will cover all the basics of data analysis.

This course will have a broad appeal as the learned skills can be applied to multiple fields (e.g., both academics and industry), thereby preparing the student for a variety of different follow-up educational tracks.

Fee info