Timing jitter generally causes a bias (systematic error) in the amplitude estimates of sampled waveforms. Equations are developed for computing the bias in both the time and frequency domains. Two principle estimators are considered: the sample mean and the so-called Markov estimator used in some equivalent-time sampling systems. Examples are given using both real and simulated data. It is shown that the bias that results from using the sample mean as an estimator can be approximated in the frequency domain by a simple filter function. The Markov estimator is shown to asymptotically converge to the population median. It is therefore an unbiased estimator for monotonic waveforms sampled with jitter distributions having a median of zero. >