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Re:ChatGPT Fails to Understand Causation by audessuscest on Friday June 21, 2024 @01:52PM (#40752004)
another:

Here's another example of three events A, B, and C that follow the correlation pattern you described:

A: Coffee consumption B: Work productivity C: Typing speed

Explanation:

1. A and B are correlated: Coffee consumption (A) and work productivity (B) often show a positive correlation. Many people drink coffee to increase alertness and focus, which can lead to improved productivity at work.

2. B and C are correlated: Work productivity (B) and typing speed (C) are generally positively correlated. As people become more productive, they often type faster to keep up with their increased output.

3. A and C are uncorrelated: However, coffee consumption (A) and typing speed (C) are not directly correlated. While coffee might indirectly influence typing speed through increased productivity, there's no direct causal relationship between drinking coffee and typing faster.

This example shows how work productivity acts as an intermediary factor, connecting coffee consumption and typing speed without them being directly correlated.

Would you like me to provide another example or explain any part of this in more detail?

Re:ChatGPT Fails to Understand Causation by user_7832 on Friday June 21, 2024 @02:12PM (#40752168)
> 3. A and C are uncorrelated: However, coffee consumption (A) and typing speed (C) are not directly correlated. While coffee might indirectly influence typing speed through increased productivity, there's no direct causal relationship between drinking coffee and typing faster.

Hmm, not too sure how much I buy that... ;)

Re:ChatGPT Fails to Understand Causation by card_zero on Friday June 21, 2024 @02:29PM (#40752291)
Seems wrong, per hnlandfr's comment. How about: a) insomnia, b) coffee consumption, c) typing speed.

Edit: also it's wrong in a basic way because coffee does make you type faster. I somehow overlooked that.