This paper deals with practical measures for performance evaluation of estimators and filters. Several new measures useful for evaluating various aspects of the performance of an estimator or filter are proposed and justified, including measurement error reduction factors, and success and failure rates. Pros and cons of some widely used measures are explained. In particular, the merits of a measure called average Euclidean error (AEE) over the widely used RMS error is presented and it is advocated that RMS error should be replaced by the AEE in many cases.