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In multiple regression analysis, when the independent variables are highly correlated, this situation is called __________________. Homoscedasticity Curvilinearity Autocorrelation Multicollinearity

User Sushilprj
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Answer:

Multi collinearity

Step-by-step explanation:

In multiple regression analysis, when the independent variables are highly correlated, this situation is called Multicollinearity.

Multicollinearity by defination only means that in one predictor variable in multiple regression model can be linearly predicted from the others with substantial degree of accuracy. Which means there is moderate or high correlation between two or more predictors in multiple regression.

User John Frazer
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