GAQM Exam CLSSGB-001 Topic 6 Question 46 Discussion

Actual exam question for GAQM's CLSSGB-001 exam

Question #: 46
Topic #: 6

Conducting a viable Capability Analysis using Attribute Data one must obtain a fairly large sample set to be statistically sound.

ATrue

BFalse

Show Suggested Answer

Suggested Answer: A

by Glen at Apr 13, 2024, 02:19 AM

Limited Time Offer

25%

Off

Get Premium CLSSGB-001 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Merissa

5 months ago

Candidate 6: That's true, the size of the sample needed for a viable Capability Analysis using Attribute Data can vary based on the context.

upvoted 0 times

...

Carolynn

5 months ago

Candidate 5: I think it really depends on the specific situation and the level of precision required for the analysis.

upvoted 0 times

...

Amalia

6 months ago

Candidate 4: True, in some cases a smaller sample size might be sufficient for conducting a credible Capability Analysis with attribute data.

upvoted 0 times

...

Rashad

6 months ago

Candidate 3: I believe the answer is B) False because sometimes a smaller sample size can still provide valid results.

upvoted 0 times

...

Omer

6 months ago

Candidate 2: I agree, conducting a Capability Analysis with attribute data requires a large sample size to ensure reliability.

upvoted 0 times

...

Kattie

7 months ago

Candidate 1: I think the answer is A) True because larger sample size gives more accurate results.

upvoted 0 times

...

Yvonne

7 months ago

I think the answer is False because sometimes a smaller sample set can still provide valuable insights.

upvoted 0 times

...

Louisa

7 months ago

I'm not sure, but it makes sense that a larger sample size would provide more reliable results.

upvoted 0 times

...

Chantell

7 months ago

I agree with User1, a large sample set is necessary for statistical accuracy.

upvoted 0 times

...

Leota

7 months ago

I think the answer is True because a large sample set is needed for accurate analysis.

upvoted 0 times

...

Hmm, I'm not so sure. Aren't there ways to do statistical analyses with smaller sample sizes? I feel like there must be some nuance here that the question is missing. Maybe we need to dig into the details of capability analysis a bit more.

upvoted 0 times

...

Glennis

8 months ago

I'm going to go with 'False' on this one. Sure, a larger sample is generally better, but I don't think you necessarily need a 'fairly large' sample to do a capable analysis with attribute data. It depends on the specific situation and the level of precision you're aiming for.

upvoted 0 times

...

Novella

8 months ago

You know, I'm reminded of that old statistics joke - 'How do you make a small fortune in statistical consulting? Start with a large one!' But in all seriousness, I agree that a large sample is probably needed here to get meaningful results.

upvoted 0 times

Beatriz

7 months ago

Agree, a large sample size is crucial for accurate results.

upvoted 0 times

...

Lorriane

7 months ago

A) True

upvoted 0 times

...

Virgilio

8 months ago

Hmm, I'm leaning towards 'True' on this one. Attribute data can be tricky to work with, and if you don't have a big enough sample, your results might not be reliable. Better to err on the side of caution and get a large sample set, in my opinion.

upvoted 0 times

...

Dallas

8 months ago

Well, I think the key here is the phrase 'statistically sound.' In my experience, you generally do need a fairly large sample size to draw valid statistical conclusions. But I'm not an expert, so I'd have to double-check the specifics for this kind of analysis.

upvoted 0 times

...

Ivette

8 months ago

I'm not too sure about this question. Conducting a capability analysis seems like a pretty advanced topic, and I'm not sure how large the sample set needs to be to be statistically sound. I'd have to do some more research on the methodology to feel confident in answering this.

upvoted 0 times

...

GAQM Exam CLSSGB-001 Topic 6 Question 46 Discussion

Contribute your Thoughts:

Merissa

Carolynn

Amalia

Rashad

Omer

Kattie

Yvonne

Louisa

Chantell

Leota

Lauran

Glennis

Novella

Beatriz

Lorriane

Virgilio

Dallas

Ivette