Expected Value with Signals Interview Questions
Expected value with signals interview questions covering signal accuracy, posterior probabilities, false positives, and action rules.
Candidates working on noisy indicator, forecast, or information prompts.
A signal changes probabilities, not payoffs by magic
A useful signal changes the probability you assign to each state. The expected value changes because those updated probabilities are multiplied by the same payoff map.
Define signal accuracy
State how often the signal is positive when the event is true and how often it is positive when the event is false. These rates determine the posterior.
Concrete example
A signal that is right 70 percent of the time can still produce a weak posterior when the base rate is low. Base rates and signal accuracy both matter.
Turn posterior into action
After updating, compare the posterior probability with the break-even probability from the payoff. The signal matters only through the decision it supports.
Watch false positives
High sensitivity is not enough if false positives are common. A signal can look impressive and still fail to create positive expected value.
Common mistakes
Candidates often treat signal accuracy as the probability the event is true. The posterior requires the base rate and both error rates.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.