Calculate probability for A/B test results
Last updated: October 18, 2025
Quick Overview
Given the following scenario about user conversion, calculate the the p-value.
Google
Statistics & Math
Data Scientist
Data Scientist
Technical Screen
Statistics & Math
Easy
279
5
167 solved
Given the following scenario about user conversion, calculate the the p-value.
Statistics questions at Google test your ability to reason quantitatively and design rigorous experiments. This Technical Screen question evaluates your understanding of statistical inference and its application to business decisions.
What the Interviewer Expects
- State the correct formula or theorem with clear definitions
- Apply the concept to the given scenario step by step
- Interpret the result in plain language
- Identify assumptions and when they might be violated
Key Topics to Cover
Power analysis and sample size calculation
Conditional probability and Bayes theorem
Confidence intervals and significance levels
Multiple testing correction (Bonferroni, FDR)
Causal inference basics
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 assumptions does this test make, and how would you validate them?
- What alternative statistical method could you use here?
- What if the sample size is very small?
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Browse Statistics QuestionsSample Answer
Problem Formulation
We are given the results of an A/B test to evaluate user conversion rates between two groups: Group A (control) and Group B (treatment). Let's denote the number of users in Group A as , the n...
Solution Approach
- Calculate the conversion rates: First, compute and .
- Calculate the pooled proportion: Under the null hypothesis, the pooled conversion rate is given by: [ p_{poole...
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