The jack-knife is a resampling method that is increasingly used for assessing the uncertainty in regression coefficient estimates, even when the predictor variables (X) are designed. Application of the jack-knife to designed data, however, violates a basic assumption underlying all resampling methods, namely that the resampled units should constitute a random sample from some distribution; the idea is to 'resample the sample.' This paper advances the view that the jack-knife should not be applied to estimate the uncertainty in regression coefficient estimates obtained from designed data, since a sound alternative is available. A literature data set is re-analyzed to lend support to this view.