GAQM CLSSYB-001 Exam - Topic 4 Question 79 Discussion

Actual exam question for GAQM's CLSSYB-001 exam

Question #: 79
Topic #: 4

[All CLSSYB-001 Questions]

Six Sigma refers to a process whose output has 100% of its data points within 8 Standard Deviations from the Mean.

ATrue

BFalse

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Suggested Answer: A

by Merissa at Jan 05, 2026, 05:16 AM

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Gwen

3 days ago

False, everyone knows Six Sigma is about 6 standard deviations, not 8!

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Casandra

8 days ago

I'm pretty sure it's False, but I'll double-check my notes just in case.

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Adelaide

13 days ago

That's a trick question if I ever saw one!

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Dominga

18 days ago

I'm pretty confident that Six Sigma doesn't mean 100% within 8 standard deviations; it sounds too broad to be true.

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Delila

24 days ago

I practiced a question like this before, and I think it was about the definition of Six Sigma being related to 3.4 defects per million opportunities.

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Virgie

29 days ago

I remember something about the 1.5 sigma shift, but I can't recall if it relates to this question.

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Lettie

1 month ago

I think Six Sigma means having very few defects, but I'm not sure about the exact standard deviations.

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Timothy

1 month ago

I'm a bit confused on this one. I know Six Sigma is a quality management approach, but I'm not sure about the specifics of the standard deviation requirement. I'll have to think it through carefully.

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Huey

1 month ago

Easy peasy, Six Sigma is all about minimizing variability, so the output has to be within a tight range. I'm confident B) False is the right answer here.

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Cherri

2 months ago

Wait, I thought Six Sigma was about having 99.99966% of data within 6 standard deviations. This 8 standard deviation thing is throwing me off. I'll have to review my notes.

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Roosevelt

2 months ago

Okay, I'm pretty sure Six Sigma is about reducing defects, not having 100% of data within 8 standard deviations. I'll go with B) False on this one.

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Rene

2 months ago

Hmm, this seems like a tricky one. I'll need to think carefully about the definition of Six Sigma and how it relates to standard deviations.

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