Six Sigma Green Belt Certification Practice Exam

Control charts are a fundamental tool in Six Sigma for monitoring and analyzing the stability of a process over time. They are designed to distinguish between common cause variation, which is inherent to the process, and special cause variation, which arises from external factors. By plotting data points over time and establishing control limits, control charts help identify trends, shifts, or any abnormal patterns in the process. This allows teams to take corrective actions when necessary, ensuring the process operates consistently and within desired parameters.

The other statistical methods listed serve different purposes. Regression analysis is focused on understanding relationships between variables, rather than monitoring variation over time. Hypothesis testing is used to make inferences about populations based on sample data, and while it may involve variations, it does not specifically track changes in a process over time. Sampling techniques involve selecting a subset of data from a larger population to make estimates or inferences, but they do not inherently provide a continuous view of variation like control charts do.