Why do we need to distinguish between strong and weak correlation of data sets using best-fit lines? When a correlation has been established between the two data sets, how is it linked to causality? Please provide examples to support your answer.
A strong correlation leads to more exact predictability.
If two variables are correlated, A might cause B, B might cause A, or a third variable might cause changes in both A and B.
I'll leave the rest to you.