Please be advised: the information contained on this page is a general overview of the course. As course information is subject to change from one semester to another, please check DukeHub for the most accurate and up-to-date information about EGRMGMT courses.
At a Glance
- Instructor(s): (Louis) Daniel Egger
- Semester(s) typically taught: Spring
- Last taught: Spring 2022
- Units: 3.0
- Grading scale: Graded (A-F)
- Required or elective for MEM degree? Elective
- If elective, applicable elective track(s): Customer Experience and Product Design, Data Analytics and Machine Learning
- Pre-requisites: n/a
- Recommended previous courses: n/a
Course Description/Synopsis (from DukeHub)
Students learn best practices for presenting discoveries and “calls to action” that are the primary aims of business data analysis. Learning about human visual perception, in particular the science of how choice of color, form, and other design elements can assist pre attentive information processing. Origins of modern data visualization in the precomputer age are considered, starting with the use of overlay maps, and Galton’s Quincunx and Correlation Diagram. Students learn to recognize the most commonly utilized types of data-visualization metaphor, as well as rules of thumb for various types of data analysis. No prior software experience required.
Course Syllabus (Previous)
EGRMGMT 587.01 Syllabus, Spring 2022
A Word From the Faculty/TA
Please check back for this at a later time.
Student Testimonials (from Course Evaluations)
- “The course provided many insights of making presentations and storytelling. The book Storytelling with Data was very useful and a good guideline for the course.”
- “Prof. Egger has encouraged me to try different data visualization skills that I have never tried. Those experiences have encouraged me to jump out of my comfort zone. What I learned will equip me with professional skills.”
- “I really like professor Egger. I have learned many data visualization skills from him. His teaching quality is very high and always uses a positive attitude to appreciate students works.”
Previous Course Evaluations
- Spring 2021
