Six Sigma Black Belt Practice Exam 2025 – Complete Prep Resource

Control charts are a statistical method specifically designed to monitor the variation in a process over time. They provide a way to visualize data, making it easier to identify trends, shifts, or any unusual variation that might indicate issues within the process. By plotting data points over time and establishing control limits based on statistical calculations, control charts help practitioners determine whether a process is behaving consistently (in control) or if changes have occurred (out of control).

In the context of process improvement, control charts are crucial because they not only highlight the presence of variation but also help differentiate between common cause variation, which is inherent to the process, and special cause variation, which is due to specific, identifiable factors. This allows organizations to take appropriate action when necessary, ensuring that processes remain stable and under control.

While ANOVA is used to compare means across different groups, it does not specifically track changes over time within a single process. Regression analysis focuses on the relationship between variables but does not inherently monitor process variation. Hypothesis testing is a technique used to make inferences about populations based on sample data, but it does not provide a continuous view of process performance over time. Thus, control charts are the most suitable tool for analyzing variation over time in a given process.