Correlation CAN Imply Causation! | Statistics Misconceptions

The video explains the common misconception that correlation implies causation, using examples to illustrate that correlation alone cannot determine causality. It discusses how causality can be inferred from correlations with additional information and causal networks. The video uses an example involving islands, height, and cat ownership to demonstrate narrowing down possible causal relationships. It concludes by noting that while correlations can imply causation, quantum mechanics presents exceptions where correlations do not fit traditional cause and effect models.

What are causal networks and how do they relate to understanding correlations?

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In what scenarios might correlation imply causation, according to the text?

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