We are often wrong, in other words, about how the world works when we rely just on what we hear or personally experience. While the methodology of good data science is often intuitive, the results are frequently counterintuitive.

There are three important aspects of probability that we need to explain so you can integrate them into your thinking to get into the ballpark and improve your chances of catching the ball: Bayesian thinking Fat-tailed curves Asymmetries

When making uncertain decisions, it’s nearly always a mistake not to ask: What are the relevant priors? What might I already know that I can use to better understand the reality of the situation? —

In the Bayesian worldview, prediction is the yardstick by which we measure progress. We can perhaps never know the truth with 100 percent certainty, but making correct predictions is the way to tell if we’re getting closer.