Mental Model

Base Rates,  Base Rate Fallacy, and Bayes Theorem

Summary

A Base Rate is a type of probability that describes the likelihood of an event when no new or more specific information is available. 

Another way to think about it is that Base Rates cover the general or usual chance that something will (or will not) happen, as opposed to recent or more specific information that may alter the probability for the event.

The key idea is that Base Rates cover what usually happens if nothing new or interesting occurs to impact the outcome.​

Base Rate Neglect or Base Rate Fallacy refers to our tendency to ignore data about what usually happens and instead focus just on new, recent, or interesting information.

Bayes Theorem is a mathematical equation where you can input the Base Rate for an event along with the probabilities associated with new information to get the actual overall probability for the event.​

Mental Model

Checklists

Summary

A checklist is a tool that can be used to outline a set of 'things' that need to be completed.

Since humans have limited memory and attention, checklists help us accomplish tasks that would otherwise be too complex or error-prone.

The key idea is that checklists are a tool to help us increase accuracy and consistency.

Mental Model

Pareto Principle (or 80/20 Principle)

Summary

The 80/20 principle is a type of power law which states that roughly 20% of a set of causes result in 80% of the effects.

​The numbers don't have to be exactly 80/20 though, and they don't have to add up to 100%: both '25/95' and '5/70' are also valid.

The key idea is that in most cases cause and effect are not linear: a small subset of causes usual generate most of the effects.​