Scientific Data Presentation

PhD-level course   —   2 hp   —   May 2015 Akademiska Sjukhuset, Uppsala

Schedule

All sessions will be held in the lecture hall of the Radiology Department at Akademiska Sjukhuset, entrace 70, 1st floor (Föreläsningssalen, Röntgenavdelningen, Akademiska Sjukhuset, Ingång 70, 1 trappa upp).

The start times below are sharp: no academic quarter. Please come on time!

Monday, 4 May 2015, 9:00-16:00
Exercises to do before this session:
  • Find two or three difficult to understand graphs in the literature. What is the main goal of each graph?
Activities:
  • Lecture: Introduction: purpose of graphing, when to use tables instead, simplicity, story. (slides)
  • Lecture: “Proper” formatting of tables. (slides)
  • Lecture: How good are we at percieving quantities when represented in different ways? (slides)
  • Lecture: Basic graph types: line plots, scatter plots, box/jitter/violin plots, dot plots, bar charts, pie charts, bubbles, etc. (slides)
  • Discussion: we'll look at the difficult graphs you found, discuss them, and think of ways to make them simpler.
Wednesday, 6 May 2015, 9:00-16:00
Exercises to do before this session:
  • In one issue of a journal, find the three best graphs and three worst graphs. Discuss why they are good/bad. How would you improve them?
  • Take one of the difficult graphs you found, and produce what you think is the best presentation for that data.
Activities:
  • Lecture: Data transformations: logarithmic axis, smoothing, aspect ratio, scale breaks, projections. (slides)
  • Discussion: present the graphs you created, we discuss good and bad aspects, think about how to improve them.
  • Lecture: Labels, legends, decorations. (slides)
  • Demo: Overview of most common graphing software. (slides)
  • Discussion: we discuss the good and bad graphs you found in the literature, and propose various ways of making them better.
  • Demo: Using Inkscape to prepare your graphs for publication.
Friday, 8 May 2015, 9:00-16:00
Exercises to do before this session:
  • Read Edward Tufte, The Visual Display of Quantitative Information, 2nd Ed.
  • Take some of your own data and create a journal-ready graph from it. Use Inkscape to make it prettier.
Activities:
  • Discussion: present the graphs you created, we discuss good and bad aspects, think about how to improve them.
  • Lecture: Colour perception (by Gunilla Borgefors). (shortened slides)
  • Lecture: Plotting multiple data sets and multidimensional data: small multiples, scatter plot matrix, images, surfaces, parallel coordinates, etc. (slides)

Note: Links to slides in the schedule above require a password. Students to this course have received this password by email. Please don't share the slides, they contain copyrighted material that I have collected from many sources (example graphs mostly). It is legal for me to show this material in class and make a copy for each of my students, but it would be illegal to distribute this material outside of the classroom. Thanks for your understanding!

Signing up for the course

Note that this instance of the course is only for MedFarm students!

Sign up for the course though the course database.

The course is limited to 20 participants. I am looking to fill this with participants from many different backgrounds, and therefore will try to limit the number of participants from the same division. In principle people will be accepted on a “first come, first served” basis, but you might be put on the wait list if too many people from your division are already accepted.

If you are registered for the course, but cannot participate for whatever reason, please let me know as soon as possible so that someone else can take your place!

Information

See here for the course description and goals.

To sign up for the course, read at the bottom of this page.

The course is limited to 20 participants, and taught in English. All sessions will be held in the lecture hall of the Radiology Department at Akademiska Sjukhuset.


Teachers:


Prerequisites:

No specific knowledge is required, besides that expected of any PhD student.


Literature:

Mandatory reading:

Suggested reading:


Software:

Besides the graphing software you are used to, you will learn to use Inkscape, an open-source drawing program, to make your graphs publication-ready. You will have to install this on your computer to do some of the homework. If you have access to a program such as Adobe Illustrator or CorelDRAW, feel free to use that instead.


Other resources:

Additional reading:

Additional software:


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Last modified January 8, 2015.