Calculate conditional probability for user retention
Last updated: April 6, 2026
Quick Overview
Given the following scenario about revenue per session, calculate the the p-value.
Waymo
April 6, 20262
6
1,694 solved
Given the following scenario about revenue per session, calculate the the p-value.
This analytics question from Waymo's Technical Screen tests your ability to think critically about data. The interviewer expects you to consider confounding variables, selection bias, and the difference between correlation and causation.
What the Interviewer Expects
- Define clear success metrics aligned with business goals
- Propose a basic experimental design with control and treatment groups
- Interpret results correctly and draw reasonable conclusions
- Identify obvious confounding variables
Key Topics to Cover
How to Approach This
- Define success metrics carefully. A good metric is measurable, actionable, and aligned with business goals.
- Run experiments long enough to account for novelty effects and weekly seasonality.
- Use funnel analysis to identify where users drop off for maximum optimization impact.
- Segment results by key dimensions (platform, country, user cohort) to catch hidden patterns.
- Consider network effects and interference between treatment and control groups.
Possible Follow-up Questions
- What if you discover a bug in the logging during the experiment?
- What would you do if a stakeholder wants to end the experiment early because initial results look good?
- What if the experiment shows a positive short-term effect but you suspect a negative long-term impact?
- How would you handle an experiment where the control and treatment groups are different sizes?
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Browse Analytics QuestionsSample Answer
Problem Setup
To evaluate user retention effectively, we need to calculate the conditional probability of a user returning after their first session, defined as the number of users returning for at least one more s...
Methodology
We will use the definition of conditional probability to calculate the probability of user retention:
P(Return | Session) = Number of users who returned / Total number of users who had at least one ...
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