IASSC Exam ICBB Topic 1 Question 63 Discussion

Actual exam question for IASSC's IASSC Certified Lean Six Sigma Black Belt exam

Question #: 63
Topic #: 1

[All IASSC Certified Lean Six Sigma Black Belt Questions]

The _____________ Distribution would be the most desirable for modeling the number of stitch defects in a portion of fabric.

AExponential

BExtended

CPoisson

DWeibull

Show Suggested Answer

Suggested Answer: C

by Jennie at Apr 09, 2024, 01:19 PM

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Penney

7 days ago

Ooh, the exponential, that's a good point! I was kind of dismissing that one, but it does make sense if the defects are truly random and uncorrelated. Though I still think the Poisson might be a better fit overall.

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Iluminada

9 days ago

Guys, I hate to be that person, but have you considered the exponential distribution? I mean, if the stitch defects are independent and the rate of defects is constant over time, then an exponential model might work well. Just a thought!

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Brandon

10 days ago

Hmm, the Weibull is an interesting thought. I think it really depends on the specific characteristics of the stitch defects and the fabric manufacturing process. If the defects are more consistently distributed, then Poisson might be better. But if there's more variation in the defect rates, Weibull could be the way to go.

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Julie

11 days ago

I was leaning more towards the Weibull distribution, actually. It's often used for modeling failure or defect rates, and it can handle skewed data better than the Poisson. But I'm open to hearing other perspectives on this.

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Oren

13 days ago

Yeah, I agree with you on the Poisson distribution. It's designed to handle discrete, countable events like this, and it's a good way to model the randomness of stitch defects. Plus, it's a pretty common distribution in quality control and manufacturing applications.

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Jame

15 days ago

Hmm, this seems like a tricky one. I'm thinking the Poisson distribution might be the best fit here, since it's commonly used to model the number of events occurring in a fixed interval of time or space, and stitch defects in fabric could be considered a similar kind of event.

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