The given statement is true, multicollinearity exists when a variable is correlated to other variables.
What is multicollinearity ?
Correlations between two or more independent variables in a multiple regression model can be referred to as multicollinearity. When a researcher or analyst tries to figure out how well each independent variable can be utilized to predict or comprehend the dependent variable in a statistical model, multicollinearity can result in skewed or misleading conclusions.
When two or more explanatory variables in a multiple regression model have strong linear relationships with one another but not with the dependent variable, this is referred to as multicollinearity.
Since a variable is multicollinear when it is correlated with other variables, the offered statement in the question is true.
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