Exponential Distribution Interview Questions
Exponential distribution interview prep for continuous waiting times, rates, survival probabilities, memorylessness, and modeling cautions.
Candidates moving from discrete geometric waiting times to continuous waiting times.
Continuous waiting time
The exponential distribution models the waiting time until an event in a simple constant-rate setting. It is the continuous analogue of a memoryless waiting-time pattern.
Rate and mean
If the rate is lambda, the mean waiting time is 1/lambda. Always check whether the prompt gives a rate per minute, per hour, or per another interval.
Survival probability
A useful form is P(T > t), the probability the wait exceeds t. For an exponential model, this survival probability decays with the rate and time.
Concrete example
If arrivals follow a simple exponential waiting-time model with mean 5 minutes, then the rate is 1/5 per minute. The exact probability calculation depends on the interval asked.
Memoryless intuition
Memorylessness means that after waiting without an event, the remaining waiting-time distribution looks like a fresh start under the same model.
Common mistakes
Candidates often apply exponential assumptions to any arrival problem. State that the model requires a stable rate and a memoryless assumption.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.