Multicollinearity exists when there is a correlation between the independent variables being used to explain the movement in a dependent variable. When this correlation exists, the coefficients calculated for each independent variable may not be valid, because the variables are linked in some way. In particular, the calculated confidence intervals may be quite wide. When multicollinearity is present, it may be possible to eliminate one of the independent variables and then run the correlation analysis again.