This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Compute probability with colored balls draws states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
##### Question
You have 5 red, 5 blue, and 5 green balls in a bag. You draw balls one at a time without replacement, but each time you draw a green ball you return it to the bag. You keep any red or blue balls drawn. When you have three balls in hand, what is the probability that at least two of them are red? Follow-up: If instead the bag initially contains 10 red balls (with the same 5 blue and 5 green), what is the probability that at least two of the three balls held are red?
Quick Answer: This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Compute probability with colored balls draws states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
mediumData ScientistTechnical ScreenStatistics & Math
4
0
Compute probability with colored balls draws
Probability with Replacement-on-Green Draws
Context
You have a bag with colored balls. You draw balls one at a time. Any time you draw a green ball, you put it back (it does not count toward the balls you hold). Any red or blue ball you draw is kept and removed from the bag. You stop once you are holding 3 balls (i.e., 3 kept balls, all of which are red or blue).
Questions
The bag starts with 5 red, 5 blue, and 5 green balls. What is the probability that at least two of the three held balls are red?
Follow-up: If instead the bag starts with 10 red, 5 blue, and 5 green balls, what is the probability that at least two of the three held balls are red?
Clarifying Questions to Ask Guidance
Clarify the random variables, distributional assumptions, independence assumptions, and desired output.
Show enough derivation for the interviewer to follow the reasoning.
Explain how you would validate the result with simulation or sensitivity checks.
What a Strong Answer Covers Guidance
A correct setup with definitions, formulas, and boundary conditions.
A step-by-step derivation or estimation plan.
Interpretation of the result, including uncertainty and practical limitations.
Checks for assumptions, edge cases, and numerical stability.
Follow-up Questions Guidance
How would the result change if the assumptions were relaxed?
Can you verify the answer with a simulation?
What is the most likely source of estimation error?