Bite-Size Data Science: Falling for the Gambler’s Fallacy

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

The “bite size” format of articles is supposed to deliver concise, focused insights on a single, small-scope topic. My goal is to write down an article that offers you a number of key takeaways that you can read during a fast break at work. You’ll understand these key points after reading this text:

1. The definition of the gambler’s fallacy
2. Why we fall for it
3. The issues it could cause in you’re employed as an information scientist and find out how to avoid those problems

Bite Size Data Science

1 — What’s the gambler’s fallacy?

The gambler’s fallacy is the wrong assumption that prior random events will impact other random events. It’s a cognitive bias that causes us to consider that what randomly happened before will influence future random outcomes. The alternative of this fallacy is knowing that randomness is random and no number of strange independent events…