If the independent variables in a regression model are perfectly correlated,it will be impossible to estimate the regression coefficients.

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Perfect correlation between independent variables, known as multicollinearity, leads to unstable and unreliable coefficients. Due to the high correlation, it becomes difficult to determine which variable is truly responsible for the changes in the dependent variable, thus making it impossible to estimate the regression coefficients accurately.

If the Independent Variables in a Regression Model Are Perfectly