The Analyze phase in Six Sigma closely examines the many process inputs identified in the Measure phase to determine if they are related to outputs, and if a relationship does exist, if it is statistically significant. An important tool for this analysis is hypothesis testing. Hypothesis testing uses statistical analysis to determine if the observed relationship between two or more samples is real or due to random chance. A variety of tests are used to find statistical evidence to reject or "not to reject" a hypothesis. Once this is accomplished, the Six Sigma team is ready to move forward with identifying, testing, and implementing solutions to address the root causes of failure. This course covers the key hypothesis testing concepts and the tests used in Six Sigma. The course will explore the steps for testing hypotheses for one-sample t-tests and two-sample t-tests with the help of real-life examples and case studies. The key terms and the common procedures used to test hypotheses are also introduced. This course is aligned with the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level