Definition: Multi-Collinearity refers to predictor variables that are correlated with other predictors. It occurs when our model includes multiple factors that are correlated to each other.

In other words, it results when we have redundant factors.

The danger of multi-Collinearity is that it increases the standard errors of the coefficients and is also able to make some variables statistically insignificant when they should be significant.