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What i mean is you've got the data that shows a correlation between the two variables but you can't infer from the data the direction of 'causality'. You'd need time relevant data for that.


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Hey no time series isn't always a necessary factor to calculate the relation between two factors .

you can't infer from the data the direction of 'causality'

Any two independent variable can be taken for finding the coefficient of determination . Coefficient of determination is used to measure the direction and magnitude of causality . It is there to show us how much one factor is affecting other factor .

How can it do that ? It does by taking the whole data into picture ( like training and testing the dataset in Machine Learning ) .

Coefficient of determination comes under Machine Learning itself .

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Gotcha cheers!


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