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In a regression analysis with multiple independent variables, multicollinearity can be caused by: A strong nonlinear relationship between the dependent variable and one or more independent variables A strong heteroskedastic relationship between the dependent variable and one or more independent variable A strong linear relationship between two or more independent variables None of the above

Respuesta :

Answer:

A strong linear relationship between two or more independent variables

Step-by-step explanation:

Multicolinearity underestimates the statistical significance of the independent variables. It exists when an independent variable is highly correlated with one or many other independent variables giving rise to a large standard error.