Florence Nightingale: Saving lives with statistics

I love the emphasis in the OP, both in the content and in the headline, on her mathematical background. The rose diagram of military deaths is so frequently as image associated with her that she's sometimes more remembered as an infographic designer (the rose diagram, to be honest, is much less decipherable than a standard bar histogram) than the insightful statistician that she was.

I'd argue the same for John Snow, who is legendary for his map, even though it was, according to biographers, an afterthought for him when doing the actual research (and the map itself also wasn't particularly effective to make his case, nor was he the first to do it).

Amazing presentation! As a nursing informaticist myself, Florence Nightingale represents the core of what we strive to do.

["Nursing Informatics is the "science and practice (that) integrates nursing, its information and knowledge, with management of information and communication technologies to promote the health of people, families, and communities worldwide." (IMIA Special Interest Group on Nursing Informatics 2009).]

I've always thought that the rose diagram is an interesting example for discussing the purpose of visualisations. The positive result of this work is undeniable, but is it a good visualisation?

That depends on whether you believe the goal of a visualisation is to convince people of something, or if you believe the goal is to accurately communicate information. It excelled in the former, but failed in the latter.

Quantity of deaths in the diagram is represented as the distance from the edge of the wedge to the centre of the circle. Because of this, larger quantities have proportionally much larger areas displayed, which the brain interprets as a measure of quantity. The other way this diagram is designed to convince people at the expense of accuracy is the placement of preventable deaths furthest from the centre, meaning those wedges are much larger in area for the same quantity as the inner ones, further distorting the reality.

We've all seen bad representations of data by the media, politicians, and businesses criticised, but this work often seems to get a pass because of its undeniably positive outcome