Correlation vs causality implied by a graph

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Discussion Overview

The discussion revolves around the relationship between correlation and causality as suggested by a graph depicting two variables, referred to as the red line and the blue line. Participants explore the implications of correlation in the context of causation, questioning whether a correlation can imply causality under certain conditions.

Discussion Character

  • Debate/contested
  • Conceptual clarification
  • Exploratory

Main Points Raised

  • Some participants argue that correlation does not imply causation, emphasizing that the lack of exact correlation between the red and blue lines suggests that causality is not definitively established.
  • Others propose that if the blue events cannot cause the red events, and there is a reasonable possibility that the red events could cause the blue events, this suggests a potential causal relationship, though not a definitive one.
  • A participant raises the possibility that both variables could be influenced by a common source, which would lead to correlation without direct causation between the two.
  • There are suggestions to analyze the raw data for further insights, but some participants indicate that they are limited to the graph and the stated relationship regarding causality.
  • One participant mentions the importance of physical models and experiments to establish causation, noting that correlation alone is insufficient to draw conclusions about causal relationships.
  • Another participant uses the example of the correlation between the lengths of left and right arms to illustrate that correlation does not imply causation, highlighting the need for subject matter knowledge to support any causal claims.
  • Some participants express uncertainty about the implications of the graph and the relationship between the variables, indicating that they are not fully confident in their interpretations.

Areas of Agreement / Disagreement

Participants generally do not reach a consensus on whether correlation can imply causation in this context. Multiple competing views remain, with some arguing for the possibility of causation under certain conditions while others maintain that correlation alone is insufficient to establish causality.

Contextual Notes

Participants note limitations in their analysis due to the lack of raw data and the constraints of relying solely on the graph and the stated relationship. There are unresolved questions about underlying causes and the nature of the correlation presented.

  • #31
phinds said:
I think he just isn't a native speaker.
Yes you're right
Just wanted to mention about that phenomenon in which an event is connected by cause and effect. Sorry for the inconvenience
 
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  • #32
Justina said:
that phenomenon in which an event is connected by cause and effect.
Yes, that is causality, or you can say it is a causal relationship.
 
  • #33
phinds said:
Yes, that is causality, or you can say it is a causal relationship.
Thank you,
Well my doubt is ,that once i read on Google.
That correlation always don't end up on causality . Is it wrong?
 
  • #34
Justina said:
Thank you,
Well my doubt is ,that once i read on Google.
That correlation always don't end up on causality . Is it wrong?
It is RIGHT, not wrong, to say that correlation does not imply causality.
 
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  • #35
phinds said:
It is RIGHT, not wrong, to say that correlation does not imply causality.
Well than what results in causality?
 
  • #36
Justina said:
Well than what results in causality?
A cause. If I hit you in the jaw, your jaw will hurt. The cause would be my having hit you in the jaw.
 
  • #37
phinds said:
A cause. If I hit you in the jaw, your jaw will hurt. The cause would be my having hit you in the jaw.
Is it a joke? Or you're just trying to state something similar to Newton third law
 
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  • #38
No, I'm beginning to think you are a troll and I would like to hit you in the jaw. That would cause your jaw to hurt. :smile:
 
  • #39
phinds said:
No, I'm beginning to think you are a troll and I would like to hit you in the jaw. That would cause your jaw to hurt. :smile:
No I'm not a troll
I'm a high school student
I just wanted to join physics forum to learn something new, and i feel you guys are so advanced in knowledge, may be that's the reason why you found me as as troll, sorry if I just inturpted you by asking silly question.
 
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  • #40
phinds said:
My thoughts exactly. Thanks.

I agree w/ you that one should be VERY leery of making such a statement, BUT ... it's a given in the scenario I am trying to understand.

I think the discussion in this thread has confirmed my point of view that in the scenario I presented, causality is a possibility but absolutely is not guaranteed or even implied, just suggest as a possibility.
Maybe it would help if you tell us what the possibilities are. For what I got so far either:
  • Red causes Blue
  • Red and Blue are unrelated, if the two match is pure chance
  • Red and Blue have a common cause (unlikely)
With the requirement also that "Blue causes Red" is not possible. Is there any other possibility or sub-possibilities?
 
  • #41
Justina said:
No I'm not a troll
I'm a high school student
I just wanted to join physics forum to learn something new, and i feel u guys are so advanced in knowledge, may be that's the reason why u found me as as troll, sorry if I just inturpted you by asking silly question.
Your question is very good and not silly at all. And I think that people often make mistakes in it. There are a few ways to logically support the claim of one factor causing another.
1) Knowledge of the subject. You may know enough about the subject to know causality without relying on statistical evidence.
2) A designed experiment. You may be able to control and manipulate one factor in a well-designed experiment and show statistically that the controlled factor causes the result in the other factor.
3) There appear to be other statistical ways to support causality that I am not familiar with. See this.
 
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  • #42
FactChecker said:
Your question is very good and not silly at all. And I think that people often make mistakes in it. There are a few ways to logically support the claim of one factor causing another.
1) Knowledge of the subject. You may know enough about the subject to know causality without relying on statistical evidence.
2) A designed experiment. You may be able to control and manipulate one factor in a well-designed experiment and show statistically that the controlled factor causes the result in the other factor.
3) There appear to be other statistical ways to support causality that I am not familiar with. See this.
Thank you sir, that means a lot to me
 
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  • #43
pines-demon said:
Maybe it would help if you tell us what the possibilities are. For what I got so far either:
  • Red causes Blue
  • Red and Blue are unrelated, if the two match is pure chance
If there is enough data, this is unlikely in the long run. One important exception is when a person tries so many possible variables that one is bound to match. That is a danger when there is a lot of detailed data that is all included in a statistical regression.
pines-demon said:
  • Red and Blue have a common cause (unlikely)
Maybe not as unlikely as you might assume. For instance, a lot of variables have a time trend that makes them appear related. Other trends can exist that might lead you to the wrong conclusion.
pines-demon said:
  • With the requirement also that "Blue causes Red" is not possible.
This is often overlooked. People often infer causality in one direction and do not rule out or account for cases of causation in the opposite direction.
Example: Does exercise make people healthier, as is often claimed? Isn't it also true that healthy people might be able to exercise more? How is that accounted for?
 
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  • #44
Justina said:
No I'm not a troll
I'm a high school student
Then I apologize.
 
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  • #45
pines-demon said:
Maybe it would help if you tell us what the possibilities are. For what I got so far either:
  • Red causes Blue
  • Red and Blue are unrelated, if the two match is pure chance
  • Red and Blue have a common cause (unlikely)
With the requirement also that "Blue causes Red" is not possible. Is there any other possibility or sub-possibilities?
There is an obvious correlation between red and blue but red does not appear to lead blue. Blue definitely does not lead red.
It is possible that red causes blue.
It is not possible that blue causes red.
It is not possible that both have a separate common cause.

Given exactly those conditions, my question is, does the obvious correlation between the two necessarily mean that red causes blue. My answer is, and was ( that no, red MAY cause blue but causality is definitely not implied. I asked the question here because I am not always the best at logic and I wanted to be sure I was not overlooking something.

My thanks to all who participated.

Paul
 
  • #46
FactChecker said:
That is a danger when there is a lot of detailed data that is all included in a statistical regression.
FactChecker said:
Maybe not as unlikely as you might assume.
FactChecker said:
This is often overlooked.
Just to be clear. I was trying to narrow down the assumptions of the author of the thread, not making some myself.
 
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