MULTICOLLINEARITY

Occurrence of different independent variables in a multiple regression model are closely connected to one another. It can lead to erratic results when aiming to study how individual independent variables contribute to comprehending the dependent variable. Generally speaking, it can result to wide confidence intervals and odd P values for independent variables.