---
title: "Using Information Entropy To Make Choices / Choose Experiments"
url: https://daily.dev/posts/using-information-entropy-to-make-choices-choose-experiments-c8selwyds
source_url: https://blog.demofox.org/2025/10/05/using-information-entropy-to-make-choices-choose-experiments/
type: article
source: "Bottom of the sea"
published: 2025-10-06T03:56:43.120Z
updated: 2025-10-06T03:57:07.437Z
tags: ["data-science", "algorithms", "statistics"]
reading_time: 13
upvotes: 1
comments: 0
language: en
---

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# Using Information Entropy To Make Choices / Choose Experiments

**[Bottom of the sea](https://daily.dev/sources/demofox)** · 13 min read · 1 upvotes · 0 comments

## Summary

Information entropy can guide experimental design by quantifying how much information different choices provide. Using probability theory, you can calculate expected bits of information from various outcomes and select experiments that maximize information gain. The classic 12-ball weighing problem demonstrates this: weighing 4 balls per side yields the highest expected entropy (1.58 bits) because it creates three equally probable outcomes. The key heuristic is choosing experiments where all possible outcomes have similar probabilities, as uniform distributions maximize information entropy.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.demofox.org/2025/10/05/using-information-entropy-to-make-choices-choose-experiments/>

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---

Tags: [#data-science](https://daily.dev/tags/data-science), [#algorithms](https://daily.dev/tags/algorithms), [#statistics](https://daily.dev/tags/statistics)

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