# causation and correlation

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#1
im doing a data research project, and i have proved that there is no correlation between two variables.
can i therefore say that this does not necessairly mean that there is no causal link between one variable to the other, or does that not make sense?
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1 month ago
#2
(Original post by YouAreAYute)
im doing a data research project, and i have proved that there is no correlation between two variables.
can i therefore say that this does not necessairly mean that there is no causal link between one variable to the other, or does that not make sense?
It sounds plausible, but isn't correct. As a simple example zero correlation can occur between two variables which have a quadratic relationship. So zero correlation for a "causal" quadratic equation. A quick google gives more interesting examples. To read causality into statistics, you really have to do a very carefully controlled design - causal analysis.
Last edited by mqb2766; 1 month ago
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#3
(Original post by mqb2766)
It sounds plausible, but isn't correct. As a simple example zero correlation can occur between two variables which have a quadratic relationship. So zero correlation for a "causal" quadratic equation. A quick google gives more interesting examples. To read causality into statistics, you really have to do a very carefully controlled design - causal analysis.
I think this makes sense - so is there anyway I can verbally justify doing a casual test even if my correlation coefficient is like -0.008?
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1 month ago
#4
(Original post by YouAreAYute)
I think this makes sense - so is there anyway I can verbally justify doing a casual test even if my correlation coefficient is like -0.008?
What do you mean by the bold bit?
The value of the correlation coefficient (close to 1 or 0) is pretty irrelevant for trying to justify causality (existance or absence).
Last edited by mqb2766; 1 month ago
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#5
(Original post by mqb2766)
What do you mean by the bold bit?
The value of the correlation coefficient (close to 1 or 0) is pretty irrelevant for trying to justify causality (existance or absence).
Okay so
As I am doing a data research project, hypothetically if I found a positive correlation between A and B I would say that this may suggest a causal relationship between A ANS B which I would therefore go on to formulate a hypothesis for ANS investigate.

However, since there is no correlation, how do I justify doing a casual test like that - if that makes Sense?
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1 month ago
#6
(Original post by YouAreAYute)
Okay so
As I am doing a data research project, hypothetically if I found a positive correlation between A and B I would say that this may suggest a causal relationship between A ANS B which I would therefore go on to formulate a hypothesis for ANS investigate.

However, since there is no correlation, how do I justify doing a casual test like that - if that makes Sense?
Its not totally my area, but there are a number of causal analysis / inference tutorials online. It may be worth having a read of some of them. Similarly, Im not really sure about the type of analysis (area, data collection, goal, ...) of your project.

Tbh, it really depends on what the output of your project is / how much multivariable analysis / data design you're expected to do. In a simple sense, high/low correlations may indicate causal/non-causal relationships, but there are a lot of other possibilities which can be tested using designed/controlled data and multivariable/joint analysis.

(Unexpected) High/low correlations may provide a starting point for further analysis, but thats about it really.
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