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The Two-Sample T-Test is a hypothesis test that determines whether a statistically significant difference exists between the averages of two independent sets of normally distributed continuous data. It is useful for determining if a particular strata or group could provide insight into the root cause of process issues.

An example would be if Location A has average sales of $3,567 per month whereas Location B has average sales of $3,843 per month and you want to determine if Location B truly has greater averages sales or the difference is just due to random chance.

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

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