Calculate conditional probability for coin flips
Last updated: January 19, 2026
Quick Overview
Given the following scenario about user conversion, calculate the the sample size needed.
Salesforce
January 19, 202626
8
243 solved
Given the following scenario about user conversion, calculate the the sample size needed.
Salesforce asks this during the Technical Screen to assess your experimentation skills. They want to see how you define success metrics, design controlled experiments, and interpret results with appropriate statistical rigor.
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?
- How would you handle an experiment where the control and treatment groups are different sizes?
- How would you handle interference between treatment and control?
- What would you do if a stakeholder wants to end the experiment early because initial results look good?
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Browse Analytics QuestionsSample Answer
Problem Setup
In this scenario, we want to determine the sample size needed for an A/B test to evaluate user conversion rates after implementing a new feature on Salesforce. The analytical question is: "What sample...
Methodology
To calculate the required sample size for detecting a difference in conversion rates, we can use the formula for sample size in an A/B test for proportions:
[ n = \frac{(Z_{\alpha/2} + Z_{\beta})^2 ...
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