Interpret no significant difference from an experiment
Last updated: November 27, 2025
Quick Overview
An experiment shows a 3% lift with p=0.08. What conclusions can you draw? What are the caveats?
Brex
November 27, 20257
5
4,583 solved
An experiment shows a 3% lift with p=0.08. What conclusions can you draw? What are the caveats?
This analytics question from Brex's Take-home Project 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
- Design a rigorous experiment with proper randomization and sample size calculation
- Define primary and guardrail metrics with clear rationale
- Address novelty effects, network effects, and interference
- Segment results appropriately and identify heterogeneous treatment effects
- Propose follow-up analyses when results are ambiguous
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 would you do if a stakeholder wants to end the experiment early because initial results look good?
- How would you handle interference between treatment and control?
- What if the experiment shows a positive short-term effect but you suspect a negative long-term impact?
- How would you handle seasonality in your experiment?
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Browse Analytics QuestionsSample Answer
Problem Setup
In this experiment, we observed a 3% lift in the primary metric (e.g., conversion rate) with a p-value of 0.08. The key analytical question is whether this lift is statistically significant and action...
Methodology
For this analysis, we will employ a hypothesis testing framework. Specifically, we will:
- Set Hypotheses:
- Null Hypothesis (H0): There is no difference in conversion rates (lift = 0). -...
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