The Tinder Problem
Explore probabilistic analysis and expected values through the Tinder Problem example. Understand how to model costs using indicator variables and calculate the expected number of break-ups and dating expenses across random matches. This lesson helps you grasp probability applied in algorithmic complexity contexts.
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Meet Neha. She's a millennial and an avid Tinder user. She swipes Tinder daily and dumps her latest boyfriend if she finds a better match than her current boyfriend (don't judge). In her world, there's never a tie between two potential boyfriends (i.e. she can always decide that one is better than the other). However, dating isn't easy or cheap. When Neha finds a mutual match, she'll go out on a date with the new guy and pay for it herself - which usually costs her about $30. If she finds she prefers the new match she'll immediately break-up with her current boyfriend over text while also sending him a $100 gift card at the same time to smooth out any grudges.
There are two costs in Neha's approach: one when she goes out on a date, and one when she breaks-up with someone. Let's see what the costs look like in ...