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 correlation coefficient of 0.90, which indicates a high degree of correlation between the two variables. This can lead to multicollinearity, which is a problem in multiple regression when two or more independent variables are highly correlated with each other. Therefore, the statement is true.

A Major Car Magazine Has Recently Collected Data on 30