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Calculate Expected Users Linking Coinbase Wallets

Last updated: Jun 15, 2026

Quick Overview

Coinbase probability question covering Bernoulli indicators, expected wallet links, complement rule for at least one success, and conditional probability for two users linking wallets.

  • easy
  • Coinbase
  • Statistics & Math
  • Data Scientist

Calculate Expected Users Linking Coinbase Wallets

Company: Coinbase

Role: Data Scientist

Category: Statistics & Math

Difficulty: easy

Interview Round: Technical Screen

##### Scenario When users sign up for Coinbase, each of the `n` users is independently prompted to link a crypto wallet. Each user links their wallet with probability `p` (and fails to link with probability `1 − p`), independently of every other user. ##### Question Using this model, answer the following: 1. What is the expected number of users who link their wallet? 2. What is the probability that at least one of the `n` users links a wallet? 3. For two specific users A and B, given that at least one of A or B links a wallet, what is the probability that **both** A and B link their wallets? ##### Hints - Part 1: Use linearity of expectation with indicator variables — you do not even need independence here. - Part 2: Use the complement rule; it is easier to compute the probability that *no one* links. - Part 3: Use the definition of conditional probability, `P(A ∩ B | A ∪ B) = P(A ∩ B) / P(A ∪ B)`.

Quick Answer: Coinbase probability question covering Bernoulli indicators, expected wallet links, complement rule for at least one success, and conditional probability for two users linking wallets.

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|Home/Statistics & Math/Coinbase

Calculate Expected Users Linking Coinbase Wallets

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Coinbase
Jul 12, 2025, 6:59 PM
easyData ScientistTechnical ScreenStatistics & Math
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0

Expected Coinbase Wallet Linking

When users sign up for Coinbase, each of the n users is independently prompted to link a crypto wallet. Each user links their wallet with probability p and fails to link with probability 1 - p, independently of every other user.

Constraints & Assumptions

  • Use the Bernoulli/binomial model described above.
  • State where independence is required and where it is not.
  • Keep answers symbolic in terms of n and p .
  • For the two-user conditional probability, let A be "user A links" and B be "user B links."

Clarifying Questions to Ask

  • Are all users assumed to have the same wallet-linking probability p ?
  • Are linking decisions independent across users?
  • Is the interviewer asking for expected value, probability, or conditional probability?

Part 1 - Expected Number of Linked Wallets

What is the expected number of users who link their wallet?

What This Part Should Cover

  • Define indicator variables for each user.
  • Use linearity of expectation.
  • Show that the expected count is n * p .
  • Note that independence is not required for this expectation if each user has success probability p .

Part 2 - Probability at Least One User Links

What is the probability that at least one of the n users links a wallet?

What This Part Should Cover

  • Use the complement rule.
  • Compute the probability that no users link as (1 - p)^n .
  • Conclude that the probability at least one links is 1 - (1 - p)^n .
  • State that independence is needed for the product form.

Part 3 - Conditional Probability for Two Users

For two specific users A and B, given that at least one of A or B links a wallet, what is the probability that both A and B link their wallets?

What This Part Should Cover

  • Use P(A and B | A or B) = P(A and B) / P(A or B) .
  • Compute P(A and B) = p^2 .
  • Compute P(A or B) = 2p - p^2 .
  • Simplify to p / (2 - p) for p > 0 .

What a Strong Answer Covers

A strong answer distinguishes expected counts from probabilities, applies complement and conditional-probability rules correctly, and states when independence matters.

Follow-up Questions

  • What changes if each user has their own probability p_i ?
  • What is the variance of the number of users who link?
  • What happens to P(at least one) as n gets large?
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