🔬Correlation vs Causation

A relationship between two variables does not prove that one causes the other: hidden factors, reverse causation, or random coincidence may be behind the correlation.

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📖3 min read📊Level 6🗺️3 subtopics📅April 16, 2026

Author: Бессмертный А.П.

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Latent variable as a spurious effect
Two variables may appear related simply because both are influenced by a third factor that was not accounted for in the design or analysis.
How to move from correlation to cause
To talk about causation seriously requires an experiment, a natural experiment, or a strong causal strategy, not just a high coefficient of association.
Reverse causation
Sometimes the relationship is read in the wrong direction: it seems that A influences B, although in reality it is B that changes A, or both variables feed each other cyclically.

# Корреляция против причинности Связь между двумя переменными ещё не доказывает, что одна вызывает другую: за корреляцией могут стоять скрытые факторы, обратная причинность или случайное совпадение. Эта тема раскрывает узел "Анализ данных" и нужна для того, чтобы карта не заканчивалась общим названием без внутренней структуры.

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What is Correlation vs Causation?Correlation vs Causation: lecture Correlation vs Causation: overview

🔬Correlation vs Causation

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