The breakdown point of an estimator is the proportion of observations that must be moved toward infinity in order for the estimator to also become infinite. The higher the breakdown point, the more robust the estimator. For estimating the center of a symmetric distribution, explain why the breakdown point is 1∕n for the sample mean but 0.50 for the sample median. (However, even robust regression methods, such as using ????(ei) = |ei|, can have small breakdown points or other unsatisfactory behavior; see Seber and Lee 2003, Sections 3.13.2 and 3.13.3)