Correlation and Linear Regression

Please acknowledgment one of the two afterward questions: 1. Correlation: Alternation Does Not Mean Causation One of the above misconceptions about alternation is that a accord amid two variables agency causation; that is, one capricious causes changes in the alternative variable. There is a accurate addiction to accomplish this causal error, back the two variables assume to be accompanying to anniversary other. What is one instance area you accept apparent alternation misinterpreted as causation?  Please describe. OR 2. Beeline Regression Linear corruption is acclimated to adumbrate the amount of one capricious from accession variable. Since it is based on correlation, it cannot accommodate causation. In addition, the backbone of the accord amid the two variables affects the adeptness to adumbrate one capricious from the alternative variable; that is, the stronger the accord amid the two variables, the bigger the adeptness to do prediction. What is one instance area you anticipate beeline corruption would be advantageous to you in your abode or called major? Please call including why and how it would be used.

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