A major car magazine has recently collected data on 30 leading cars in the U.S.market.It is interested in building a multiple regression model to explain the variation in highway miles.The following correlation matrix has been computed from the data collected: If the independent variables,curb weight,cylinders,and horsepower are used together in a multiple regression model,there may be a potential problem with multicollinearity since horsepower and cylinders are highly correlated.

Question

A major car magazine has recently collected data on 30 leading cars in the U.S.market.It is interested in building a multiple regression model to explain the variation in highway miles.The following correlation matrix has been computed from the data collected:  If the independent variables,curb weight,cylinders,and horsepower are used together in a multiple regression model,there may be a potential problem with multicollinearity since horsepower and cylinders are highly correlated.

Quizplus · Accepted Answer

The correlation matrix shows that horsepower and cylinders have a high correlation coefficient of 0.91, indicating strong multicollinearity. Therefore, using these variables together in a multiple regression model may result in unstable and unreliable estimates of the regression coefficients, making it difficult to interpret the individual effects of each variable on the dependent variable.

A Major Car Magazine Has Recently Collected Data on 30