Nate Silver
In a world overflowing with data, why do so many predictions fail while a few succeed? Discover how to cut through the noise and make better forecasts by changing how you process information.
Overconfidence is the leading cause of failed predictions because people underestimate the uncertainty intrinsic to complex problems.
You should approach forecasting like a fox by synthesizing many different pieces of data rather than relying on one grand theory.
Embracing Bayesian thinking allows you to incrementally adjust your probabilities and beliefs every time you encounter new information.