Professor of Mathematics at Temple University, John Allen Paulos describes the differences between statistics and stories:
[T]here is a tension between stories and statistics, and one under-appreciated contrast between them is simply the mindset with which we approach them. In listening to stories we tend to suspend disbelief in order to be entertained, whereas in evaluating statistics we generally have an opposite inclination to suspend belief in order not to be beguiled.
And he concludes:
The focus of stories is on individual people rather than averages, on motives rather than movements, on point of view rather than the view from nowhere, context rather than raw data. Moreover, stories are open-ended and metaphorical rather than determinate and literal.
Which way do we go when we start telling stories with data?
[New York Times via @joandimicco]
There’s some danger in telling stories, at least with scientific topics. There’s hardly anything that’s straight forward and as simple as a round story will make us to believe. And where would be the place to have a look at the more complicated story than in academia?
However, I heard so many talks that were purely statistical where most of the audience simply didn’t understand well enough what the presentation was about. Obviously, nothing is won with that and that’s where storytelling can jump in. Give people an intuition about what you want to say, make them interested and then be as explicit about your data as possible.
I agree that stories are a needed but can be dangerous. They have their place just like visualization has it’s place but both can cover up the truth and one should always have the data available to support the story and/or let others draw their own conclusions.
Always be suspicious if the story is too good.