Stories, and Statistics

I’ve been wondering about the two ways of exploring the world recently. Stories, and statistics. Stories are causal interpretations of chains of events, one leading to another with barely a break. And statistics are analyses of the level of randomness of an event, trying to distill actual occurences from randomness. We use both, in varying ways, to try and make sense of everything, and we make a right mess of things when we try and combine the two.

One is an abductive process, where we craft the stories of how something came to be, based on pattern recognition, knowhow, and general leaps of faith. And the other is a deductive process, where we gather all the data and then assess outcomes against all possible explanations, coming with one that explains the deviations best. With any sufficiently complex phenomena, we are better off thinking statistically, because that would reduce the chance that we jump to poorly formed conclusions. Stories have to be formed through sufficient repetition.

In things like climate science, economics, or medicine, we seem to rely more on stories, despite statistics being a better approach as we have more data, because stories bring us comfort and the premium we put on comfort is rather high. And in things like entertainment, which should ideally be based on stories, we rely on statistics to predict the next box office hit or the next popstar, which is a reductive approach to a complex problem.

Applying different modes of thought at will is what helps us be better, and knowing when to do what is a far stronger ability than to think about the mind in terms of biases against a platonic template. If folks knew how to apply these different modes of thought, we would be able to solve most of the debates we keep having, and actually move forward.