Design an A/B test for a pricing model
Last updated: August 31, 2025
Quick Overview
Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.
Zscaler
August 31, 20253
6
2,641 solved
Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.
Statistics questions at Zscaler test your ability to reason quantitatively and design rigorous experiments. This Phone Screen 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
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 handle multiple comparisons?
- What alternative statistical method could you use here?
- What if the sample size is very small?
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Problem Formulation
To design an A/B test for Zscaler's redesigned homepage, we need to define the objectives and the metrics for success. Our primary goal is to assess the impact of the new homepage layout on conversion...
Solution Approach
- Sample Size Calculation: To determine how many users we need for each group, we use the formula for sample size in A/B testing: [ n = \frac{(Z_{\alpha/2} + Z_{\beta})^2 (p_A(1 - p_A) + p_B(...
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