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n multiple regression models, correlation among independent variables can potentially distort the standard error of estimate and may therefore lead to incorrect conclusions as to

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n multiple regression models, correlation among independent variables can potentially distort the standard error of estimate and may therefore lead to incorrect conclusions as to which independent variables are statistically significant. Such correlation is called heteroscedasticity. multicollinearity homoscedasticity. autocorrelation. None of the above. Next

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