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The One-Sample T-Test is a hypothesis test that determines whether a statistically significant difference exists between the average of a normally distributed continuous data set and a standard. It provides a way to determine if there is truly a difference between the standard and a particular data set mean or whether the difference is due to random chance.

An example would be testing whether a supplier, that has guaranteed an average 12-ounce fill rate on their beverages, is performing as promised.

For a better understanding of the One-Sample T-Test, check out our Black Belt Training & Certification Course!

Elisabeth Swan

Elisabeth is a Managing Partner at For over 25 years, she's helped leading organizations like Amazon, Charles Schwab and Starwood Hotels & Resorts build problem-solving muscles with Lean Six Sigma to achieve their goals.

Tracy O'Rourke

Tracy is a Managing Partner at She is also a Lean Six Sigma Green Belt Instructor at UC San Diego and teaches in San Diego State University’s Lean Enterprise Program. For almost 20 years, she has helped leading organizations like Washington State, Charles Schwab and GE build problem-solving muscles.