Which chart type is best for demonstrating non-random process variation over time?

The control chart is particularly effective for demonstrating non-random process variation over time because it not only plots data points over time but also includes control limits that help identify whether variation is due to common causes or special causes. This distinction is essential in quality improvement processes. Control charts enable practitioners to monitor the stability of a process and discern patterns or trends that might indicate issues requiring intervention.

When assessing non-random variation, it is crucial to identify instances where the process deviates from its expected performance, which control charts are designed to highlight through their statistical control limits. This allows for a proactive approach in managing processes by determining if a change is significant or if it falls within the expected variation of the process.

Other chart types, like run charts, while also useful, do not include the same level of statistical analysis as control charts, making them less effective for identifying specific causes of variation over time. Bar and pie charts serve primarily to compare discrete categories or show proportions, rather than monitoring variations over a continuous timeline, which fundamentally differs from the purpose of control charts.