Question: How can a manager differentiate between correlation and causation when interpreting the results of a linear regression model? Consider a situation where a business mistakenly

How can a manager differentiate between correlation and causation when interpreting the results of a linear regression model? Consider a situation where a business mistakenly assumes a causal relationship between two correlated variables, and discuss the potential consequences of such a mistake

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