Calculate probability for user retention

Last updated: October 12, 2025

Quick Overview

Given the following scenario about user conversion, calculate the the p-value.

Workday
Statistics & Math
Data Scientist
Workday
October 12, 2025
Data Scientist
Phone Screen
Statistics & Math
Hard

28

4

3,953 solved


Given the following scenario about user conversion, calculate the the p-value.

Statistics questions at Workday 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
  • 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
Central Limit Theorem
Bayesian vs frequentist inference
Power analysis and sample size calculation
Multiple testing correction (Bonferroni, FDR)
Regression analysis
How to Approach This
  1. Define your hypotheses (H0 and H1) clearly before performing any test.
  2. Calculate required sample size BEFORE running an experiment, using power analysis.
  3. Remember the Central Limit Theorem: sample means become approximately normal with large n.
  4. Watch for Simpson's paradox. Always segment data by key dimensions.
  5. 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 design a follow-up experiment based on these results?
  • How would you handle multiple comparisons?
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Sample Answer
Problem Formulation

To calculate the p-value for user retention at Workday, we start by defining our variables and setting up the hypotheses. Let's assume we have a sample of users who were part of a new feature rollout....

Solution Approach
  1. Collect Data: Gather data on the number of users retained after the feature launch. Let’s say:
    • Total users in the sample (n) = 1000
    • Users retained (x) = 300
    • Baseline retention ra...

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