Understanding Risk and Averages

This chapter explores the misconceptions surrounding risk assessment and the limitations of traditional averages in the context of extreme events like pandemics. The discussion emphasizes the significance of fat-tailed distributions, highlighting how outlier events can heavily influence average predictions and lead to poor decision-making. By focusing on the importance of understanding extremes rather than relying solely on means, the chapter seeks to reshape how we approach forecasting and risk analysis.