Calculate probability for A/B test results

Last updated: January 11, 2026

Quick Overview

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

Tesla
Analytics & Experimentation
Data Scientist
Tesla
January 11, 2026
Data Scientist
Phone Screen
Analytics & Experimentation
Easy

52

5

424 solved


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

Analytics questions at Tesla evaluate your ability to define metrics, design experiments, and derive actionable insights from data. This Phone Screen question tests your end-to-end analytical thinking.

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
Funnel analysis and cohort analysis
Guardrail metrics
Network effects and interference
Sample size and power calculation
Simpson's paradox and ecological fallacy
How to Approach This
  1. Define success metrics carefully. A good metric is measurable, actionable, and aligned with business goals.
  2. Run experiments long enough to account for novelty effects and weekly seasonality.
  3. Use funnel analysis to identify where users drop off for maximum optimization impact.
  4. Segment results by key dimensions (platform, country, user cohort) to catch hidden patterns.
  5. 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 seasonality in your experiment?
  • 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 Questions
Sample Answer
Problem Setup

The analytical question here is to calculate the p-value for the A/B test results regarding user conversion rates at Tesla. To do this, we need data on the conversion rates of two groups: a control gr...

Methodology

For this problem, we will use a two-proportion z-test to compare the conversion rates of the two groups. The null hypothesis (H0) states that there is no difference in conversion rates between the con...


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