Answer
I do not agree with the statement. Multicollinearity typically occurs when two or more independent variables in a regression model are highly correlated with each other, not with the dependent variable. This high correlation between independent variables can create problems in regression analysis, such as making it difficult to identify the individual effects of each independent variable on the dependent variable. Therefore, it's essential to assess the correlation between independent variables rather than their correlation with the dependent variable.
Work Step by Step
I do not agree with the statement. Multicollinearity typically occurs when two or more independent variables in a regression model are highly correlated with each other, not with the dependent variable. This high correlation between independent variables can create problems in regression analysis, such as making it difficult to identify the individual effects of each independent variable on the dependent variable. Therefore, it's essential to assess the correlation between independent variables rather than their correlation with the dependent variable.