In a multiple linear regression analysis, how do you interpret the coefficient of determination (R-squared), and what does it indicate about the relationship between the independent variables and the dependent variable? Discuss its limitations and possibl

The coefficient of determination (R-squared) in multiple linear regression measures the proportion of the variance in the dependent variable that is predictable from the independent variables. An R-squared value close to 1 indicates a strong relationship, while a value near 0 suggests a weak relationship. However, R-squared has limitations: it does not indicate causation, can be artificially high with more predictors, and does not measure model accuracy on new data. Misconceptions include equating a high R-squared with a good model fit and ignoring overfitting risks.

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