The 37% rule, also known as the optimal stopping problem, is a mathematical strategy derived from probability theory. It suggests that when searching for a partner, you should date and reject the first 37% of candidates to gather information, then choose the next person who is better than all previous ones. This maximizes the probability of selecting the best option, though it does not guarantee success.
Research by mathematicians like Thomas Ferguson and others has shown that this rule applies to various scenarios, including hiring, apartment hunting, and dating. The rule assumes you can only evaluate candidates sequentially and cannot go back to a rejected one. The optimal stopping point is 1/e (approximately 0.37) of the total pool.
In practice, if you expect to date 10 people, you should date and reject the first 3-4, then choose the next one who is better than all previous. This gives about a 37% chance of selecting the best partner, which is the highest possible under these constraints.
Critics note that real-life dating involves complex emotions and preferences, and the rule may oversimplify human relationships. However, it remains a popular concept in decision theory and behavioral economics.
