Here come the science…

First, a warn­ing: The maths may well be crucially flawed (I consul­ted with stat­ist­i­cians but you know what those guys are like), and my profess­ors did not under­stand the results well enough to mark it with any degree of confid­ence. The anonymised data is avail­able at the end of the post, as I would sincerely like stat­ist­i­cians with more resources and brain power than me to take a proper look at them. The results apply to the UK only.

Methodology

I didn’t want to fall into the trap most graphic design disser­ta­tions fall into of taking a sample of 5 graphic design­ers as my subjects and expect­ing them to be repres­ent­at­ive of a whole popu­la­tion — a deeply flawed and far too commonly repeated approach in both design and pyscho­logy stud­ies. So I asked the inter­net instead. More than 300 of you obli­ging little blight­ers replied. I love you guys!

I displayed two things on a screen and asked people to tell me which one repres­en­ted more people.

Those things were a mixture of graph­ics, writ­ten ratios, and writ­ten percent­ages. Like was compared with like, and like was compared with both of the other options. The ques­tions were random­ised so parti­cipants never saw the ques­tions in the same order. There were a lot of ques­tions and it got a little dull. I only analysed the results of people who got to the end of the survey, which gave me 223 parti­cipants, and for the ques­tions alone over 7,000 data­points. With demo­graphic inform­a­tion it comes to more like 11,000 datapoints.

The results

You can down­load the data in Excel format.

I have edited them to take out any identi­fy­ing data, to merge the demo­graph­ics columns, and to add in which answers were correct and which were incorrect.

The final dissertation

Download the whole thing, includ­ing some analysis of char­ity commu­nic­a­tions and the current state of psycho­lo­gical models of risk-perception: The percep­tion of risk in char­ity health commu­nic­a­tions. This includes the survey ques­tions (in the appendix at the end) so you can see how the survey was run. It also includes the partic­u­lar pitfalls of this kind of meth­od­o­logy (and no doubt misses a few out).

Above all, I don’t care if I was right or not — but I would love it if you guys with the power and math­em­at­ical skills can look at this and tell me if there’s anything useful there.

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Corinne Pritchard

Information Designer at Simply Understand

I believe design and design­ers can and should make the world a better place. I love design­ing things that help people under­stand complex ideas.

Latest posts by Corinne Pritchard (see all)

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