What is multicollinearity in regression analysis?

Описание: Multicollinearity occurs in regression analysis when two or more independent variables are highly correlated 📊. This high correlation means that the variables share a significant amount of the same information, which can make it difficult to determine the individual effect of each variable on the dependent variable. Multicollinearity can lead to unreliable and unstable estimates of regression coefficients, making it challenging to interpret the results of the analysis accurately. It does not involve the relationship between the dependent variable and independent variables, outliers, or whether the regression line passes through the origin.