Certified Quality Auditor (CQA) Practice Exam 2025 - Free CQA Practice Questions and Study Guide

Determining that a sample does not meet statistical significance indicates that the observed results may have occurred by chance rather than reflecting a true effect or finding in the population being studied. This means that the conclusions drawn from the audit findings cannot be considered valid, as they lack the necessary statistical reliability to support a definitive conclusion about quality or compliance.

When an audit's findings are not statistically significant, it raises doubts about the reliability of those findings. For example, if a quality auditor identifies certain defects but the sample is not statistically significant, it will be challenging to argue that those defects are representative of a broader trend within the entire population of products or processes inspected. Consequently, the overall assessment of quality could be called into question, leading to potentially flawed decisions based on unreliable data.

In contrast, other options present implications that do not directly address the core issue of validity related to statistical significance. While further audits may sometimes be needed, this is not a direct consequence of the lack of significance but rather a potential next step based on the findings. Similarly, documenting samples can be a good practice, but it does not overcome the validity issue inherent in statistically insignificant results. Adjusting reports after an audit does not address the fundamental problem of interpreting nonsignificant data accurately.