Correlation vs causality implied by a graph

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SUMMARY

The discussion centers on the distinction between correlation and causation as illustrated by a graph showing a correlation between two variables, referred to as the red and blue lines. Participants argue that while a correlation exists, it does not definitively imply causation, particularly given the constraints that the blue cannot cause the red, and the red could potentially cause the blue. The consensus is that causality can only be established through controlled experiments, and correlation alone is insufficient to draw definitive conclusions about causal relationships.

PREREQUISITES
  • Understanding of correlation and causation concepts
  • Familiarity with statistical analysis methods
  • Knowledge of experimental design principles
  • Basic grasp of Bayes' theorem and its applications
NEXT STEPS
  • Research statistical methods for establishing causality, such as causal inference techniques
  • Study experimental design to understand how to control variables effectively
  • Explore the application of Bayes' theorem in causal analysis
  • Examine case studies where correlation was misinterpreted as causation
USEFUL FOR

Researchers, data analysts, statisticians, and anyone involved in interpreting data relationships and establishing causal links in their work.

  • #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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