What type of statistic is used to measure process variation?

The most appropriate choice for measuring process variation is control charts. Control charts are vital tools in quality control that visualize how a process varies over time. They display data points in relation to predetermined control limits, which helps identify whether a process is in a state of statistical control.

By plotting individual data points along with the upper and lower control limits, practitioners can effectively observe trends, shifts, and anomalies in the process. This visualization allows teams to monitor the stability and variability of processes, making control charts an essential tool in quality improvement efforts.

While standard deviation is a statistical measure that quantifies how much values in a dataset deviate from the mean, its purpose is more focused on summarizing variation rather than monitoring it continuously over time. Confidence intervals provide a range of values that likely contain a population parameter, helping to understand precision rather than direct process control. The mean and median offer central tendency measures but do not specifically address the aspect of variation in a process context. Thus, control charts stand out as the most effective method for assessing process variation.