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Amazon·Data Scientist·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Amazon data scientist screen with a classic conditional probability puzzle. Three parts, each hinging on how you interpret the information you're given. The math isn't hard but the reasoning is easy to fumble if you're not careful about assumptions.

Questions Asked (3)

Q1

A family has two children and you know at least one is a boy. What is the probability both children are boys? State your assumptions.

Product Analytics & MetricsAlgorithms & Data Structures
Author's notes

I jumped to 1/2 immediately and had to backtrack.

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AI HintsAI Generated

Suggested Approach

Clarify the assumptions about how the information 'at least one is a boy' was obtained, then compute the probability under the standard assumption that all gender combinations are equally likely and the statement is a random observation. Present the answer as 1/3, but also discuss how different assumptions (e.g., a specific child is known to be a boy) lead to 1/2.

Pro tip: Explicitly state that the answer depends on the selection mechanism—this demonstrates the kind of rigorous thinking valued in data science and avoids the common pitfall of assuming the answer is always 1/2.

1. Clarify the assumptions

Ask or state how the information 'at least one is a boy' was obtained. Assume that the family was randomly selected from all two-child families and that you are told at least one is a boy, with no other information.

2. Define the sample space

List all equally likely gender combinations for two children: BB, BG, GB, GG. Since at least one is a boy, eliminate GG, leaving BB, BG, GB.

3. Compute the probability

Under the assumption, the remaining outcomes are equally likely. Only BB satisfies 'both are boys', so the probability is 1/3.

4. Discuss alternative interpretations

Explain that if instead you know a specific child (e.g., the older) is a boy, the probability is 1/2. This highlights the importance of the selection mechanism.

5. Relate to data science

Connect to how assumptions and data collection methods affect probabilistic models and decision-making, emphasizing the need to question how data is generated.

Key Points to Mention

  • The standard assumption: all four gender combinations are equally likely.
  • Conditional probability and the reduction of the sample space.
  • The answer 1/3 under the assumption that 'at least one is a boy' is a random observation.
  • The alternative answer 1/2 if a specific child is known to be a boy.
  • The importance of the selection mechanism (how the information was obtained).
  • Relevance to data science: assumptions drive model outcomes and must be validated.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

Same two-child family, but now you're told specifically that the older child is a boy. Does the probability that both are boys change?

Product Analytics & MetricsAlgorithms & Data Structures
Author's notes

This one I got right but probably for the wrong reasons.

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AI HintsAI Generated

Suggested Approach

Clarify that the probability changes from 1/3 to 1/2 because specifying the older child is a boy eliminates the girl-boy and girl-girl outcomes, leaving only boy-boy and boy-girl. Then explain the key distinction: this is different from merely knowing at least one child is a boy, which leaves three equally likely outcomes.

Pro tip: Emphasize that the answer hinges on how the information is obtained—if you simply know 'at least one is a boy,' the probability is 1/3, but if you know the older child is a boy, it's 1/2. This shows you understand conditional probability beyond memorized puzzles.

1. Define the sample space

List all equally likely gender combinations for two children: BB, BG, GB, GG, where the first letter represents the older child.

2. Apply the condition

Restrict the sample space to outcomes where the older child is a boy: BB and BG.

3. Compute the probability

Since both remaining outcomes are equally likely, the probability that both are boys is 1 out of 2, or 50%.

4. Contrast with the 'at least one boy' case

Explain that if you only knew at least one child is a boy, the sample space would be BB, BG, GB, giving a probability of 1/3. This highlights the importance of the specific information.

Key Points to Mention

  • Sample space for two children: BB, BG, GB, GG (order matters for older/younger).
  • Conditioning on 'older child is a boy' eliminates GB and GG.
  • Remaining outcomes: BB and BG, each equally likely.
  • Probability both are boys = 1/2.
  • Contrast with 'at least one boy' condition, which gives 1/3.
  • Assumption of independent 50/50 gender probabilities.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q3

Now a child is picked at random from the family and that child happens to be a boy. What is the probability the other child is also a boy?

Product Analytics & MetricsAlgorithms & Data Structures
Author's notes

Weirdest part of the whole question.

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AI HintsAI Generated

Suggested Approach

Clarify the assumptions about how the child was selected: if the family has two children and a randomly chosen child is a boy, the probability the other is a boy is 1/2. If instead we are told that at least one child is a boy, the probability both are boys is 1/3. State the assumption explicitly and compute accordingly.

Pro tip: Amazon interviewers value candidates who proactively state assumptions and avoid ambiguity. Mention the classic 'boy or girl paradox' and explain why the answer depends on the selection mechanism.

1. Clarify the selection process

Ask whether the child was randomly selected from all children in the family, or whether the information 'at least one boy' was given without random selection. This distinction changes the probability.

2. Define the sample space

For two children, the possible gender combinations are BB, BG, GB, GG, each with probability 1/4 under usual assumptions. If a child is randomly picked and is a boy, we condition on that event.

3. Compute conditional probability

If a random child is a boy, the probability the other is a boy is 1/2. If we only know at least one is a boy, the probability both are boys is 1/3. Show the calculation using Bayes' theorem or counting.

4. Address the ambiguity

Explain that the answer depends on the exact wording. The phrase 'a child is picked at random and happens to be a boy' implies random selection, so the answer is 1/2. If the problem meant 'at least one is a boy', the answer is 1/3.

5. Conclude with the answer

State the final probability clearly, referencing the assumption made. For the given wording, the probability is 1/2.

Key Points to Mention

  • Conditional probability and Bayes' theorem
  • The boy or girl paradox (also known as the two-child problem)
  • Importance of clarifying assumptions in probability problems
  • Difference between random selection and 'at least one' condition
  • Sample space enumeration: BB, BG, GB, GG
  • Real-world implications for data science: ambiguity in data collection affects conclusions

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.