MENU
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?
Suggested Answer: C
Get Premium A00-240 Questions
as Interactive Web-Based Practice Test or PDF
Real Exam Format
Detailed Explanations
Instant Access
Get Your Practice Test
31 comments · newest first
JA
Janna
11 months ago
I’m surprised that people think collinearity is an issue here!
MO
Moira
11 months ago
I think A is misleading; those VIFs look fine to me.
UL
Ulysses
11 months ago
Wait, how can collinearity be a problem if the Pr>|t| values are low?
SE
Selma
12 months ago
Totally agree, B is the right choice!
SH
Sharen
12 months ago
Collinearity is not a problem since all variance inflation values are less than 10.
TH
Thora
1 year 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?
TO
Tom
1 year 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.
CH
Charlene
1 year 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.
GR
Grover
1 year ago
I remember that variance inflation factors over 10 indicate collinearity issues, so if they're all under 10, it should be fine, right?
TA
Tamesha
1 year 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.
ES
Estrella
1 year 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.
MA
Maynard
1 year 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.
DA
Dana
1 year 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?
GL
Glenn
1 year 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.
PE
Pearlene
2 years ago
Collinearity, schmolinearity. As long as I can spell 'regression' correctly, I'm good to go! B seems legit, though.
AR
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.
AN
Annita
2 years ago
Thanks for the tip, I'll go with B as well. VIF values are crucial in multiple linear regression analysis.
KA
Katina
2 years ago
Yeah, VIF values less than 10 indicate that collinearity is not a problem.
MA
Margurite
2 years ago
I agree, B is the correct answer. VIF values are important in determining collinearity.
EM
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.
NI
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.
JA
Janae
2 years ago
Christiane: Exactly, it's a good sign when all VIF values are below the threshold.
JO
Jose
2 years ago
User 4: That makes sense, thanks for clarifying.
JA
Jamey
2 years ago
User 3: So, we can conclude that collinearity is not an issue in this case.
CH
Christiane
2 years ago
User 2: Yeah, that makes sense. It's a clear indicator of no multicollinearity.
LE
Leah
2 years ago
Yeah, if VIF values are less than 10, collinearity is not a problem.
PE
Pete
2 years ago
I agree, B is the correct answer. VIF values less than 10 means no collinearity issue.
EL
Eladia
2 years ago
I agree, B is the correct answer.
SH
Shanda
2 years ago
But what about the Pr>|t| values? Maybe that's a better indicator of collinearity.
RI
Rima
2 years ago
I disagree, I believe collinearity is not a problem since all variance inflation values are less than 10.
SH
Shanda
2 years ago
I think collinearity is a problem since all variance inflation values are less than 10.