Understanding Data with R: a hands-on workshop towards becoming a data-analyst
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 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.
In this dynamic two-week course, you will discover the importance of data analysis in multiple disciplines. You will learn how to use data to answer a wide range of interesting questions, using the popular programming language called R. From gathering data to creating appealing and insightful data visualizations, you will master the basics of truly understanding data.
By completing this course, you will:
- Acquire an understanding of the role of data in answering research questions, both in academics and in the industry;
- Gain a basic understanding of the statistical programming language R, using RStudio;
- Learn how to manipulate data (e.g., renaming variables, removing cases, combining datasets);
- Learn how to create beautiful and insightful data visualizations that are relevant for answering the research question;
- Learn how to conduct statistical analyses (e.g., descriptives, correlations, regression);
- Learn how to write a report that answers a research question using the data.
6 Jul 2020 - 17 Jul 2020
Bachelor / Undergraduate
Master / Graduate
|Program fee||750 EUR|
|Extra information about the
Course fee online (reduced prices): €750
|Application deadline||31 May 2020|
Applications must contain a CV, a motivation letter and a Transcript or other document in which it is stated that you have successfully completed an introductory Statistics course.
Admission to this course will be based on your CV, a Transcript and motivation letter.
- English proficiency (spoken and written) is required