Robust estimates are statistical procedures used to reduce uncertainty in the results of analyses. They are used to minimize the risk that a coincident estimate will be applied. Robust estimates are often less sensitive to outliers than are concordant estimates, meaning that they are less prone to failure when a small number of data are unusual.