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Calculate Expected Users Adopting Wallet Feature

Last updated: Mar 29, 2026

Quick Overview

This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Calculate Expected Users Adopting Wallet Feature states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  • easy
  • Coinbase
  • Statistics & Math
  • Data Scientist

Calculate Expected Users Adopting Wallet Feature

Company: Coinbase

Role: Data Scientist

Category: Statistics & Math

Difficulty: easy

Interview Round: Technical Screen

##### Scenario For N users, each independently adopts the wallet feature with probability p. ##### Question Derive the expected number of users who adopt the wallet feature. 2) Compute the probability that at least one user adopts it. 3) State the core statistical assumption used in these calculations. 4) Given that at least one of two specific users adopted the feature, what is the probability both of them did? ##### Hints Apply linearity of expectation, Bernoulli independence, complement rule, and conditional probability.

Quick Answer: This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Calculate Expected Users Adopting Wallet Feature states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

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|Home/Statistics & Math/Coinbase

Calculate Expected Users Adopting Wallet Feature

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Coinbase
Aug 4, 2025, 10:55 AM
easyData ScientistTechnical ScreenStatistics & Math
2
0

Calculate Expected Users Adopting Wallet Feature

Wallet Feature Adoption – Probability and Expectation

Setup

  • You are analyzing adoption of a new wallet feature.
  • There are N users. Each user independently adopts the feature with probability p.

Questions

  1. What is the expected number of users who adopt the feature?
  2. What is the probability that at least one user adopts it?
  3. What core statistical assumption underlies these calculations?
  4. Given that at least one of two specific users adopted the feature, what is the probability both of them did?

Constraints & Assumptions

  • Preserve the scope, facts, inputs, and requested outputs from the prompt above.
  • If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
  • Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask

  • Clarify the random variables, distributional assumptions, independence assumptions, and desired output.
  • Show enough derivation for the interviewer to follow the reasoning.
  • Explain how you would validate the result with simulation or sensitivity checks.

What a Strong Answer Covers

  • A correct setup with definitions, formulas, and boundary conditions.
  • A step-by-step derivation or estimation plan.
  • Interpretation of the result, including uncertainty and practical limitations.
  • Checks for assumptions, edge cases, and numerical stability.

Follow-up Questions

  • How would the result change if the assumptions were relaxed?
  • Can you verify the answer with a simulation?
  • What is the most likely source of estimation error?
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