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Assess Probability of Heads in Coin Tosses

Last updated: Mar 29, 2026

Quick Overview

This question evaluates understanding of discrete and continuous probability concepts, specifically the binomial model for repeated Bernoulli trials and the normal distribution with standardization, testing core statistical reasoning and sensitivity to distribution parameters.

  • easy
  • Upstart
  • Statistics & Math
  • Data Scientist

Assess Probability of Heads in Coin Tosses

Company: Upstart

Role: Data Scientist

Category: Statistics & Math

Difficulty: easy

Interview Round: Onsite

##### Scenario HR screening for data-science role; assessing basic probability knowledge ##### Question A coin is tossed N times into a cup. Assuming each toss is independent and fair, what is the probability of observing exactly k heads? How would your answer change if the coin is biased with probability p of heads? For a variable X~N(μ,σ²), derive P(a<X<b) and explain how to standardise a normal variable. ##### Hints Use binomial pmf and standard normal Z-score transformation.

Quick Answer: This question evaluates understanding of discrete and continuous probability concepts, specifically the binomial model for repeated Bernoulli trials and the normal distribution with standardization, testing core statistical reasoning and sensitivity to distribution parameters.

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Upstart
Aug 4, 2025, 10:55 AM
Data Scientist
Onsite
Statistics & Math
24
0

Probability with Coin Tosses and the Normal Distribution

Context

Onsite data scientist screening question assessing basic probability and distribution knowledge.

Questions

  1. A fair coin is tossed N times, with independent tosses. What is the probability of observing exactly k heads?
  2. How does your answer change if the coin is biased, with probability p of heads on each toss?
  3. Let X ~ N(μ, σ²). Derive P(a < X < b) and explain how to standardize a normal variable.

Hint

  • Use the binomial probability mass function (pmf) for parts (1) and (2).
  • Use the Z-score transformation to standardize a normal variable.

Solution

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