Correlation vs Causation: What Can Be Inferred?

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In summary, in order to establish causality, it is not enough to solely rely on correlations in observational studies. One would need to conduct randomized, controlled experiments and assess conditional probabilities in a well ordered stochastic process.
  • #1
gl0Wyrm
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If variable X is positively correlated with variable Y, under what circumstances am I allowed to infer that X does not causally prevent Y with reasonable probability?

I don't know much about statistics and I'm trying to motivate myself to learn by doing. For example: https://drive.google.com/open?id=0B9wG-PC9QbVEUTBIVmgxeElCQnc (https://drive.google.com/open?id=0B9wG-PC9QbVEZ2NEU3BvYzkwM0U)
 
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In general, you can't infer causality solely from correlations in observational studies. You would need to perform some randomized, controlled experiments in order to establish causality.
 
  • #3
Hey gl0Wyrm.

If you want to assess causality then you should assess conditional probabilities in terms of a well ordered stochastic process.
 

Related to Correlation vs Causation: What Can Be Inferred?

What is the difference between correlation and causation?

Correlation refers to a relationship between two variables where a change in one variable is associated with a change in the other variable. Causation, on the other hand, refers to a relationship where one variable directly causes a change in the other variable.

How can I determine if a correlation is also a causation?

In order to determine if a correlation is also a causation, you need to establish a causal link between the two variables. This can be done through further research and experiments to eliminate other potential factors and establish a cause-and-effect relationship.

Can a correlation be used to make predictions?

Yes, a correlation can be used to make predictions about the relationship between two variables. However, it is important to note that correlation does not imply causation, so the predictions may not always be accurate.

Why is it important to understand the difference between correlation and causation?

Understanding the difference between correlation and causation is important because it helps us avoid making incorrect assumptions or conclusions. Just because two variables are correlated, it does not necessarily mean that one causes the other.

What are some examples of correlation and causation?

An example of correlation is the relationship between ice cream sales and sunglasses sales. As ice cream sales increase, so do sunglasses sales. However, this does not mean that ice cream causes people to buy sunglasses. An example of causation is the relationship between smoking and lung cancer. Smoking directly causes an increased risk of developing lung cancer.

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