Calculate probability for click-through rates
Last updated: May 18, 2026
Quick Overview
Given the following scenario about user conversion, calculate the the p-value.
Redfin
Statistics & Math
Data Scientist
Redfin
May 18, 2026Data Scientist
Technical Screen
Statistics & Math
Hard
101
4
469 solved
Given the following scenario about user conversion, calculate the the p-value.
Redfin values data-driven decision making. This Technical 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
Regression analysis
Probability distributions
Central Limit Theorem
Hypothesis testing (H0, H1, p-values)
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 assumptions does this test make, and how would you validate them?
- How would you design a follow-up experiment based on these results?
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Browse Statistics QuestionsSample Answer
Problem Formulation
To calculate the p-value for user conversion rates in the context of Redfin, we first need to establish the null hypothesis (H0) and the alternative hypothesis (H1). Let’s denote the click-through rat...
Solution Approach
- Collect Data: Assume from the experiment, we have the following data:
- Number of users in the control group (n0): 1000
- Number of conversions in the control group (k0): 100 (CTR = 10%) ...
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