Bite-Size Data Science: Falling for the Gambler’s Fallacy | by Jarom Hulet | Jan, 2025

Where the gambler’s fallacy shows up in data science and what to do about it

Image generated by DALL-E using prompt by author

The “bite size” format of articles is meant to deliver concise, focused insights on a single, small-scope topic. My goal is to write an article that gives you a few key takeaways that you could read during a quick break at work. You’ll understand these key points after reading this article:

1. The definition of the gambler’s fallacy
2. Why we fall for it
3. The problems it can cause in you work as a data scientist and how to avoid those problems

1 — What is the gambler’s fallacy?

The gambler’s fallacy is the incorrect assumption that prior random events will impact other random events. It is a cognitive bias that causes us to believe that what randomly happened before will influence future random outcomes. The opposite of this fallacy is understanding that randomness is random and no number of peculiar independent events…

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