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What’s A One-Sample T-Test?

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.

Learn more about One-Sample T-Tests in Analyze Phase, Module 4.3.3 of Black Belt Training.

How To Run A One-Sample T-Test In SigmaXL

Download the GoLeanSixSigma.com One-Sample T-Test Data Set for SigmaXL here.

1. Select Raw Data:

OneSampleT-SigmaXL-RawData

2. In The Menu Click Statistical Tools > 1 Sample t Test & Confidence Intervals:

OneSampleT-SigmaXL-SelectData

3. Since data is pre-selected, click Next:

OneSampleT-SigmaXL-Settings

4. Click in the “Numeric Data Variable Column, Select “Packaging” Click OK:

OneSampleT-SigmaXL

To learn more about One-Sample T-Tests, register for Black Belt Training and review Analyze Phase, Module 4.3.3.