Clustering illusion

The tendency to erroneously consider the inevitable streaks or clusters arising in small samples from random distributions to be non-random From Wikipedia, the free encyclopedia

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The clustering illusion refers to the cognitive bias where people tend to see patterns in random data or events, even when those patterns don't actually exist. Essentially, it's the tendency to assume that clusters or groupings appear where there are just random occurrences.[1]

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Examples of Clustering Illusion:

  1. Coin Tosses: If you toss a coin multiple times and get a streak of heads (or tails), you might think that the next toss is more likely to be tails, even though the probability of heads or tails on each toss is always 50%. You might also think that the heads are "clustering" when it's actually just random.
  2. Sports or Games: If a player has a series of good or bad performances in a row, you might start to think that they're "on a streak" or that there's some underlying reason, when it could just be a coincidence.
  3. Gambling: When someone plays slots, for example, they might think the machine is "due" for a win after several losses because they're seeing patterns where there are none.
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Why does it happen?

Humans are wired to seek patterns, as it's an evolutionary survival trait. In the past, spotting patterns in nature (like identifying a predator or prey) was essential for survival. However, in random events, our brains tend to "see" clusters where there are none, leading to incorrect conclusions.

In Summary:

The clustering illusion is essentially about our brains seeing patterns in random data—and it can affect everything from gambling to interpreting everyday events.

If you'd like to dive deeper into how this bias affects decision-making, feel free to ask!

References

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