Everything Is Predictable

Bayesian model lets you calculate just how likely it is that a particular hypothesis is true, given the data.

‘Necessarily,’ wrote David Howie, a historian of statistics, ‘these inferences were tentative. They were advanced not with certainty but with degrees of confidence that were updated or modified to account for new information.’95 That is: they were done in a Bayesian fashion. Each time Jeffreys got new information, he updated his prior confidence in

Imagine that I’m visiting a distant city, and a local friend volunteers to drive me to the airport. I don’t know the neighborhood. Each time my friend approaches a street intersection, I don’t know whether my friend will turn left, turn right, or continue straight ahead. I can’t predict my friend’s move even as we approach each individual intersect

The argument made by Bayes and Price is not that the world is intrinsically probabilistic or uncertain. Bayes was a believer in divine perfection; he was also an advocate of Isaac Newton’s work, which had seemed to suggest that nature follows regular and predictable laws. It is, rather, a statement—expressed both mathematically and philosophically—

A good model can be useful even when it fails. “It should be a given that whatever forecast we make on average will be wrong,” Ozonoff told me. “So usually it’s about understanding how it’s wrong, and what to do when it’s wrong, and minimizing the cost to us when it’s wrong.” The key is in remembering that a model is a tool to help us understand th

As an empirical matter, we all have beliefs and biases, forged from some combination of our experiences, our values, our knowledge, and perhaps our political or professional agenda. One of the nice characteristics of the Bayesian perspective is that, in explicitly acknowledging that we have prior beliefs that affect how we interpret new evidence, i