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SAS A00-240 Exam - Topic 7 Question 99 Discussion

Actual exam question for SAS's A00-240 exam
Question #: 99
Topic #: 7
[All A00-240 Questions]

Refer to the exhibit.

Output from a multiple linear regression analysis is shown.

What is the most appropriate statement concerning collinearity between the input variables?

Show Suggested Answer Hide Answer
Suggested Answer: C

by Alba at Sep 16, 2024, 06:10 AM

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Janna
5 months ago
I’m surprised that people think collinearity is an issue here!
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Moira
5 months ago
I think A is misleading; those VIFs look fine to me.
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Ulysses
5 months ago
Wait, how can collinearity be a problem if the Pr>|t| values are low?
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Selma
6 months ago
Totally agree, B is the right choice!
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Sharen
6 months ago
Collinearity is not a problem since all variance inflation values are less than 10.
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Thora
6 months ago
I feel like I might be mixing things up, but I thought if the Pr>|t| values are low, it could indicate some kind of relationship, not collinearity?
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Tom
6 months ago
I practiced a similar question where the VIF values were the key to determining collinearity, and I think that’s what we need to focus on here too.
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Charlene
6 months ago
I’m not entirely sure, but I think the Pr>|t| values being less than 0.05 means the variables are significant, not necessarily about collinearity.
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Grover
7 months ago
I remember that variance inflation factors over 10 indicate collinearity issues, so if they're all under 10, it should be fine, right?
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Tamesha
7 months ago
Alright, I've got this. The VIF values are all less than 10, so that means collinearity is not a problem. The answer has to be option B.
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Estrella
7 months ago
I think the key here is to understand what the VIF values and Pr>|t| values are telling us about collinearity. I'll need to review my notes on interpreting those statistics.
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Maynard
7 months ago
Wait, I'm a bit confused. The question is asking about the "most appropriate statement" concerning collinearity, not just whether it's a problem or not. I'll need to read the answer choices carefully.
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Dana
7 months ago
Okay, the question is asking about collinearity, so I need to focus on the VIF values. If they're all less than 10, that means collinearity is not a problem, right?
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Glenn
7 months ago
Hmm, this looks like a tricky one. I'll need to carefully review the variance inflation values to determine if there's a collinearity issue.
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Pearlene
2 years ago
Collinearity, schmolinearity. As long as I can spell 'regression' correctly, I'm good to go! B seems legit, though.
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Arletta
2 years ago
Haha, these questions always try to trip you up. But I'm no rookie, I know the VIF values are the key here. B is the way to go, my dudes.
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Annita
1 year ago
Thanks for the tip, I'll go with B as well. VIF values are crucial in multiple linear regression analysis.
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Katina
2 years ago
Yeah, VIF values less than 10 indicate that collinearity is not a problem.
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Margurite
2 years ago
I agree, B is the correct answer. VIF values are important in determining collinearity.
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Emeline
2 years ago
Ah, tricky question. I was going to say D, but then I saw the part about the VIF values. Gotta pay attention to those details, you know? B it is.
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Nickie
2 years ago
Hmm, I think B is the right answer. If all the VIF values are less than 10, then collinearity is not an issue. Looks pretty straightforward to me.
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Janae
1 year ago
Christiane: Exactly, it's a good sign when all VIF values are below the threshold.
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Jose
1 year ago
User 4: That makes sense, thanks for clarifying.
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Jamey
1 year ago
User 3: So, we can conclude that collinearity is not an issue in this case.
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Christiane
1 year ago
User 2: Yeah, that makes sense. It's a clear indicator of no multicollinearity.
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Leah
1 year ago
Yeah, if VIF values are less than 10, collinearity is not a problem.
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Pete
2 years ago
I agree, B is the correct answer. VIF values less than 10 means no collinearity issue.
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Eladia
2 years ago
I agree, B is the correct answer.
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Shanda
2 years ago
But what about the Pr>|t| values? Maybe that's a better indicator of collinearity.
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Rima
2 years ago
I disagree, I believe collinearity is not a problem since all variance inflation values are less than 10.
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Shanda
2 years ago
I think collinearity is a problem since all variance inflation values are less than 10.
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