Multicollinearity refers to a situation in statistical modeling where two or more independent variables are highly correlated. This can cause issues in the interpretation of the model, leading to unreliable estimates of the regression coefficients. In the context of Nanotechnology, where data can be highly complex and interrelated, addressing multicollinearity is crucial for accurate analysis and predictions.
