Misconceptions Footnote †: Randomness and Feedback

The video discusses the concept of correlations and causation, highlighting Reichenbach's principle, which suggests that finding a correlation naturally leads to seeking explanations or causes. It warns against spurious correlations that occur by chance, using examples like coin flips. The video also clarifies that feedback loops, such as the relationship between grass and sheep, are not true loops but causal chains affecting future states.

What happens to the correlation when larger samples are considered in the context of random correlations?

Describe the feedback loop involving grass and sheep. How is it different from a causal loop?