Calculate conditional probability for A/B test results
Last updated: February 7, 2026
Quick Overview
Given the following scenario about user conversion, calculate the the sample size needed.
DoorDash
Statistics & Math
Data Scientist
DoorDash
February 7, 2026Data Scientist
Take-home Project
Statistics & Math
Medium
98
3
949 solved
Given the following scenario about user conversion, calculate the the sample size needed.
Statistics questions at DoorDash test your ability to reason quantitatively and design rigorous experiments. This Take-home Project question evaluates your understanding of statistical inference and its application to business decisions.
What the Interviewer Expects
- Set up the problem formally with proper notation
- Apply the correct statistical test with clear justification
- Interpret results with appropriate caveats and confidence levels
- Discuss practical significance vs statistical significance
- Identify potential confounders and how to address them
Key Topics to Cover
Hypothesis testing (H0, H1, p-values)
Central Limit Theorem
Multiple testing correction (Bonferroni, FDR)
Probability distributions
How to Approach This
- Define your hypotheses (H0 and H1) clearly before performing any test.
- Calculate required sample size BEFORE running an experiment, using power analysis.
- Remember the Central Limit Theorem: sample means become approximately normal with large n.
- Watch for Simpson's paradox. Always segment data by key dimensions.
- Distinguish between statistical significance and practical significance.
Possible Follow-up Questions
- How would you design a follow-up experiment based on these results?
- How would you handle multiple comparisons?
- How would you explain this result to a non-technical audience?
- What if the sample size is very small?
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Browse Statistics QuestionsSample Answer
Problem Formulation
To calculate the sample size needed for an A/B test assessing user conversion rates, we need to define our hypotheses clearly:
- Null Hypothesis (H0): There is no difference in conversion rates b...
Solution Approach
- Define Inputs: Assume the following values:
- (10% conversion rate of control group)
- (12% conversion rate of treatment group)
- ...
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