Insight into Experimental Data


  • Type: Elective
  • Goal: Learn the basics of statistics (challenge 1) and apply them in a design experiment (challenge 2).
  • Final grade: 9
  • Competencies: MDC | US | DRP

Key learning points

1. Understanding and applying statistics.
2. The role of statistics in any phase of the design process.
3. Quantitative data to compliment the qualitative.


Designers use a multitude of media to present and evaluate their ideas towards clients, potential users and colleagues. The media varies from plain sketches to high fidelity prototypes. For challenge 2 we wanted to find out possible differences between the experiences of looking at a sketch versus a low fidelity prototype. This is interesting as it might provide leverage for designers to use certain media under certain conditions. For instance, prototyping is more expensive than sketching, so depending on the impact of a certain kind of media it might be better to use a sketch over a prototype and vice versa.


First of all, the elective taught me what statistics are and how to apply them. Working with the Illmo program provided me of new ways to analyze data coming from design related challenges and to extract information from a dataset I was first not able to unravel.

Especially challenge 2, for which we used my M1.2 project as foundation, was educational as it made me able to apply the theory to a real design problem. This gave me more insights in how to apply it myself in the future as well. I experienced how the understanding of the theory helped in making more conscious decisions on what outcomes we were looking for which made the process of analyzing and interpreting easier. Moreover, this elective made me realize that statistics can play a role in any phase of the design process, whether it is for idea generation or evaluation of the concept. It provided me of new ways to involve the user in the design process and to analyze the outcomes.

As I’m an advocate of qualitative research, I wondered if this elective could change my perspective on using quantitative data. And indeed, once I had a grasp of the theory I also started to appreciate it more. After a steep learning curve I realized how statistics can be very powerful if used strategically in the design process. Together with supporting qualitative data it can help you in decision making in any phase.