Various statistical techniques are used to detect multicollinearity. Common methods include examining the correlation matrix of predictor variables, calculating the Variance Inflation Factor (VIF), and analyzing the tolerance values. A VIF value greater than 10 often indicates significant multicollinearity, while a tolerance value less than 0.1 suggests the same.
