Admission requirements
Students should be very familiar with R, RStudio and be able to generate reproducible reports with RMarkdown. Within this master this pre-knowledge can be acquired from the course ‘Statistical Computing with R' and it is recommended that students pass this course first.
Description
Data visualizations give viewers insight in data patterns and are therefore an integral part of data analysis and the communication of statistical results. Hence, applied statisticians should learn how to visualize their data in an effective and perceptually accurate manner such that the plots correctly convey the data message. Additionally, statisticians should be able to visualize the statistical models fitted on data and these models’ uncertainty, so that they can easily be interpreted by users.
In this course you will learn about the principles of effective data visualizations and how to apply them. Furthermore, you will learn how to make explorative data visualizations and visualizations of statistical models, and how to visualize model uncertainty. In this course all plots are made in R (mainly with the ggplot2 package) in a reproducible way (R Markdown).
Course Objectives
By the end of the course, students can:
apply the principles of effective data visualizations to make perceptually accurate plots;
evaluate data visualizations and describe improvements;
create reproducible explorative data visualizations for data explorations, statistical models, and model or data uncertainty;
create reproducible visualizations that convey a data story.
Timetable
You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have sucessfully registered for in MyStudyMap will automatically be displayed in MyTimeTable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.
MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).
For more information, watch the video or go the the 'help-page' in MyTimetable. Please note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.
Mode of Instruction
The course consists of one course-day per week in the form of a computer practical in which students learn how to make data visualizations with R. Students are expected to prepare for each practical, for example, by reading literature, watching lecture videos, and making preparatory exercises.
Additionally, there are three interactive workgroups in which students work on a visualization assignment, share it with the group, and give each other feedback. Active participation in these workgroups is mandatory (see assessment method).
Make sure you have a laptop available during each meeting with the latest version of R and R-Studio (for details see Brightspace).
Assessment method
The final grade is based on three components:
20%: Active participation in interactive workgroups
In each interactive workgroup students work on a group assignment which is discussed at the end of the class.
Graded as pass/fail. Students fail if they do not actively participate in more than one workgroup.
Students need to pass this part in order to pass the course.
Resit: there is no resit opportunity for this part. However, students may miss at most one meeting (see previous point).
40%: Theoretical exam
Covers the topics presented in the whole course
Graded on a 0-10 scale, minimum grade = 5.0
Resit: a resit exam can replace the original grade of the exam
40%: Assignment
Assignment is done on campus within a set time (like an exam)
Graded on a 0-10 scale, minimum grade = 5.0
Resit: a resit assignment can replace the original grade of the assignment
To pass the course, the unrounded final grade should be a 5.5 or higher.
Reading list
Book: Fundamentals of Data Visualization by Claus O. Wilke, available online via clauswilke.com/dataviz.
Various scientific articles that will be announced at the start of the course via Brightspace and are available online via the Leiden University Library.
Registration
It is the responsibility of every student to register for courses with the new enrollment tool MyStudyMap. There are two registration periods per year: registration for the fall semester opens in July and registration for the spring semester opens in December. Please see this page for more information.
Please note that it is compulsory to both preregister and confirm your participation for every exam and retake. Not being registered for a course means that you are not allowed to participate in the final exam of the course. Confirming your exam participation is possible until ten days before the exam.
Extensive FAQ's on MyStudymap can be found here.
Contact
Dr. S.J.W. Willems: s.j.w.willems[at]fsw.leidenuniv.nl