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Calculate Particle Survival Probability After Time t

Last updated: Mar 29, 2026

Quick Overview

This question evaluates proficiency in probability theory and statistical modeling, focusing on exponential survival functions, independence of events, and discrete counting distributions for multiple identical components.

  • easy
  • Upstart
  • Statistics & Math
  • Data Scientist

Calculate Particle Survival Probability After Time t

Company: Upstart

Role: Data Scientist

Category: Statistics & Math

Difficulty: easy

Interview Round: Technical Screen

##### Scenario Radioactive-decay style process: 100 independent particles, each has a known half-life. Interviewer wants theoretical probability of how many survive after a given time. ##### Question Given 100 identical particles with half-life H (each decays independently with exponential distribution), derive the probability that exactly k (or at least one) particles remain undecayed after time t. ##### Hints Recall exponential survival function P(T>t)=e^{-λt} where λ=ln2/H; use Binomial distribution on independent survival events.

Quick Answer: This question evaluates proficiency in probability theory and statistical modeling, focusing on exponential survival functions, independence of events, and discrete counting distributions for multiple identical components.

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Upstart
Aug 4, 2025, 10:55 AM
Data Scientist
Technical Screen
Statistics & Math
4
0

Radioactive-Decay Style Probability

Context

You have 100 identical, independent particles. Each particle's lifetime is exponentially distributed with rate parameter λ corresponding to a known half-life H. For an exponential lifetime, the survival function is:

  • P(T > t) = e^{-λ t}, where λ = (ln 2) / H.

Task

  1. Derive the probability that exactly k particles (out of 100) remain undecayed after time t.
  2. Derive the probability that at least one particle remains undecayed after time t.

Assumptions

  • Particles decay independently.
  • All particles share the same half-life H (i.e., the same exponential rate λ).
  • Time t ≥ 0 and k ∈ {0, 1, ..., 100}.

Solution

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