Calculate conditional probability for A/B test results
Last updated: March 3, 2026
Quick Overview
Given the following scenario about user conversion, calculate the the p-value.
Palantir
March 3, 202610
5
1,376 solved
Given the following scenario about user conversion, calculate the the p-value.
Palantir values data-driven decision making. This Phone Screen question assesses whether you can design experiments, interpret results correctly, and avoid common statistical pitfalls like p-hacking or Simpson's paradox.
What the Interviewer Expects
- Derive results from first principles when needed
- Handle complex scenarios with multiple interacting variables
- Design experiments that account for real-world complications
- Discuss advanced topics: Bayesian methods, causal inference, resampling
- Connect statistical concepts to business decision-making
- Identify subtle errors in reasoning (Simpson's paradox, survivorship bias)
Key Topics to Cover
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
- What alternative statistical method could you use here?
- What assumptions does this test make, and how would you validate them?
- How would you handle multiple comparisons?
- What if the sample size is very small?
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Problem Formulation
In this scenario, we have an A/B test where we want to assess the impact of a new feature on user conversion rates. Let's denote:
- : the group exposed to the new feature
- : the control...
Solution Approach
To compute the p-value for the A/B test, follow these steps:
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Calculate the conversion rates for both groups:
- p_A = rac{x_A}{n_A}
- p_B = rac{x_B}{n_B}
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**Compute the po...
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