How is a Six Sigma process statistically defined?

A Six Sigma process is statistically defined as a statistical representation of a near-perfect process, where the goal is to minimize defects and variability. Specifically, in Six Sigma terminology, a process is considered to be operating at Six Sigma quality level when it produces fewer than 3.4 defects per million opportunities.

This definition aligns with the underlying philosophy of Six Sigma, which seeks to improve quality by identifying and removing causes of defects and minimizing variability in manufacturing and business processes. The concept emphasizes measuring performance through statistical metrics, thus enabling organizations to progress toward optimal operation and efficiency.

Other options do not accurately convey the statistical nature associated with Six Sigma. The notion of a system with no variations or errors suggests an unrealistic perfection that is not attainable in practice. Continuous supervision implies a management style rather than a statistical characterization of process capability. Lastly, suggesting that a process is driven by random occurrences undermines the systematic approach of Six Sigma, which focuses on identifying and controlling variations rather than accepting randomness.