Calculate Expected Flips for Two Heads Coin Toss

Quick Overview

This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Calculate Expected Flips for Two Heads Coin Toss states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Calculate Expected Flips for Two Heads Coin Toss

Company: Experian

Role: Data Scientist

Category: Statistics & Math

Difficulty: easy

Interview Round: Technical Screen

##### Scenario Experian DataLabs online assessment – core probability section. Several short probability problems are asked back to back, covering coin-flip distributions and conditional probability. ##### Question Answer the following: 1. You repeatedly flip a fair coin until you obtain two heads (not necessarily consecutive). What is the expected number of flips? 2. If you flip a fair coin three times, what is the probability of getting exactly two heads? 3. Given two events A and B with P(A) = 0.3, P(B) = 0.5, and P(A ∩ B) = 0.15, compute P(A | B). 4. Given two events A and B with P(A) = 0.3, P(B) = 0.4, and P(A ∩ B) = 0.12, compute P(A | B). ##### Hints - For waiting-time problems, use the geometric / negative-binomial expectation E[T] = r / p. - For a fixed number of flips, use the binomial PMF P(X = k) = C(n, k) p^k (1 − p)^(n − k). - For conditional probability, apply P(A | B) = P(A ∩ B) / P(B), and check whether the events are independent.

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 Calculate Expected Flips for Two Heads Coin Toss states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

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Aug 4, 2025, 10:55 AM
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Calculate Expected Flips for Two Heads Coin Toss

Scenario

Experian DataLabs online assessment – core probability section. Several short probability problems are asked back to back, covering coin-flip distributions and conditional probability.

Question

Answer the following:

  1. You repeatedly flip a fair coin until you obtain two heads (not necessarily consecutive). What is the expected number of flips?
  2. If you flip a fair coin three times, what is the probability of getting exactly two heads?
  3. Given two events A and B with P(A) = 0.3, P(B) = 0.5, and P(A ∩ B) = 0.15, compute P(A | B).
  4. Given two events A and B with P(A) = 0.3, P(B) = 0.4, and P(A ∩ B) = 0.12, compute P(A | B).
Hints
  • For waiting-time problems, use the geometric / negative-binomial expectation E[T] = r / p.
  • For a fixed number of flips, use the binomial PMF P(X = k) = C(n, k) p^k (1 − p)^(n − k).
  • For conditional probability, apply P(A | B) = P(A ∩ B) / P(B), and check whether the events are independent.

Constraints & Assumptions

  • Preserve the scope, facts, inputs, and requested outputs from the prompt above.
  • If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
  • Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

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?
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