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Causation involves direct cause-and-effect relationships, while correlation is necessary before inferring causation, and coincidental biases should be avoided in event interpretation.
Causation refers to the direct relationship where one event leads to another as a result. This concept involves understanding cause-and-effect connections and is crucial in various fields, including social sciences and research.
Correlation, on the other hand, signifies a connection between two variables, which is essential before establishing a causal relationship. It helps differentiate between mere coincidence and actual causation.
When interpreting events, it's important to avoid coincidence biases, where unrelated occurrences are perceived to directly influence each other due to their timing or proximity in sequence.
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