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Clustering Illusion: Definition, Examples and Effects

Clustering illusion is a cognitive bias that causes people to perceive patterns in random data. It is a phenomenon in which people tend to see patterns in random data, even when there is none. This phenomenon is also known as “illusory correlation” or “illusory pattern recognition”.


Definition: Clustering illusion is a cognitive bias that causes people to perceive patterns in random data. It is a phenomenon in which people tend to see patterns in random data, even when there is none. This phenomenon is also known as “illusory correlation” or “illusory pattern recognition”.


Examples: One example of clustering illusion is when people see patterns in the stock market. People may think that a certain stock is going to go up or down based on past performance, even though the stock market is largely unpredictable. Another example is when people see patterns in the weather. People may think that a certain type of weather is more likely to occur based on past experience, even though the weather is largely unpredictable.


Effects: The effects of clustering illusion can be both positive and negative. On the positive side, it can lead to creative thinking and problem solving. On the negative side, it can lead to false assumptions and incorrect conclusions. It can also lead to overconfidence in one’s own predictions and decisions. Additionally, it can lead to a lack of objectivity when evaluating data.


Do you want to expand your knowledge on this topic? Read our full in-depth article on cognitive biases.


Do you have extra 15 minutes today? Takeour fun and interactive quiz to learn which of 16 reasoning styles you use, your overall level of rationality, and what you can do now to improve your rationality skills.

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