Moneyball: Data Decisions and Bias

Explore how human biases affect data-driven decisions, using a "Moneyball" baseball example to illustrate the importance of statistical parsimony.

Overview

We tend to believe that data-driven decision-making is the epitome of objectiveness, but as humans we are subject to several types of biases which tend to accommodate the narrative. And these biases tend to be replicated in the data we store and the models we create with it. We’ll illustrate this with a baseball example taken from Michael Lewis’ classic “Moneyball”.

Tech stack