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This question is commonly asked for Data Scientist candidates at Coinbase during technical interviews.

Model Feature Adoption Probability for Users

Last updated: Mar 29, 2026

Quick Overview

This question evaluates understanding of basic probability concepts such as the binomial distribution, expectation, and conditional probability in the Statistics & Math domain, assessing a candidate's ability to model and reason about discrete random variables.

Coinbase

Aug 4, 2025, 10:55 AM

Data Scientist

Technical Screen

Statistics & Math

Feature Adoption Probability Modeling

Context

You are analyzing adoption of a new wallet feature. Each of n users independently adopts the feature with identical probability p. Let X be the number of adopters among the n users.

Tasks

(a) Compute the expected number of adopters.

(b) Compute the probability that at least one user adopts.

Hints

Model X with a Binomial(n, p) distribution.
Use the complement rule for "at least one": P(X ≥ 1) = 1 − P(X = 0).
Use conditional probability: P(A | B) = P(A ∩ B) / P(B).

Solution

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