Control chart methodology has important applications in the analytical chemistry laboratory. This paper explores application of statistical process control (SPC) techniques to chemical measuring systems and highlights problems when data are correlated. Instrumental methods of chemical analysis typically generate correlated quality-control (QC) sample data owing to the effect of calibration. That is, QC sample measurements stemming from the same calibration curve will tend to be more closely related than measurements derived from different calibration curves. Data correlation will bias the estimated sample variance and essentially invalidate the control limits if not accounted for. A way of calculating statistically valid control limits in the presence of intraclass correlation is examined and an illustrative example given.