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SAS A00-240 Exam - Topic 4 Question 80 Discussion

Actual exam question for SAS's A00-240 exam
Question #: 80
Topic #: 4
[All A00-240 Questions]

An analyst knows that the categorical predictor, zip_code, is an important predictor of a binary target. However, zip_code has too many levels to be a feasible predictor in a model. The analyst uses PROC CLUSTER to implement Greenacre's method to reduce the number of categorical levels.

What is the correct application of Greenacre's method in this situation?

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Suggested Answer: D

by Alecia at Jan 26, 2024, 10:49 PM

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Brandon
5 months ago
D sounds complicated, but could work if done right!
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Abel
5 months ago
C is interesting, but I think A is more relevant here.
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Willow
6 months ago
Wait, can you really cluster using just zip_code values?
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Frederica
6 months ago
I disagree, B seems more straightforward.
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Solange
6 months ago
A is the way to go! Target proportions matter.
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Arlette
6 months ago
I vaguely recall that using dummy variables could complicate the clustering process, so I'm leaning towards option A for this one.
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Linn
6 months ago
I practiced a similar question where we clustered based on case counts, but I think that might not be the best approach here either.
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Leoma
6 months ago
I'm not entirely sure, but I feel like clustering based on the zip_code values themselves might not capture the target's influence effectively.
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Johnson
7 months ago
I remember discussing how Greenacre's method focuses on the relationships between categories, so I think using the target proportion for each zip_code makes sense.
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Reuben
7 months ago
I'm pretty confident that the correct answer is A. Clustering the levels using the target proportion for each zip_code makes the most sense to reduce the number of levels while preserving the predictive power of the variable.
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Essie
7 months ago
I'm a bit confused on this one. Clustering the levels using the zip_code values or the number of cases doesn't seem quite right. Dummy coding the zip_code levels also doesn't seem relevant here.
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Jamal
7 months ago
Okay, the key here is that we're trying to reduce the number of levels in the zip_code predictor. I think using the target proportion for each zip_code as the input to the clustering makes the most sense.
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Dell
7 months ago
This looks like a tricky question. I'll need to think carefully about the different options and how Greenacre's method works.
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Olene
7 months ago
Hmm, this seems like a tricky one. I'll need to carefully review the options and think through the implications of each setting.
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Dick
7 months ago
This seems straightforward - I think the answer is to assign the existing service appointment to the crew.
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Johnetta
7 months ago
I remember calculating probabilities before, but I'm not completely sure how to approach this one with different ball colors.
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Matthew
11 months ago
I don't know, guys. Greenacre's method sounds a bit like rocket science to me. Maybe we should just ask the professor for the answer key.
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Carrol
10 months ago
D) Clustering the levels using dummy coded zip_code levels as inputs.
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Curt
10 months ago
C) Clustering the levels using the number of cases in each zip_code as input.
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Marion
10 months ago
B) Clustering the levels using the zip_code values as input.
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Rana
11 months ago
A) Clustering the levels using the target proportion for each zip_code as input.
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Isaac
12 months ago
Ah, the number of cases in each zip_code, the classic approach. I like it, nice and straightforward.
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Ashlee
10 months ago
C) Clustering the levels using the number of cases in each zip_code as input.
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Olive
10 months ago
B) Clustering the levels using the zip_code values as input.
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Tish
10 months ago
A) Clustering the levels using the target proportion for each zip_code as input.
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Sage
12 months ago
I'm not sure about using dummy coded zip_code levels as inputs. Doesn't that seem a bit like overkill for this problem?
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Margo
10 months ago
C) Clustering the levels using the number of cases in each zip_code as input.
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Shenika
10 months ago
I agree, using dummy coded zip_code levels might be too complex for this situation.
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Leah
10 months ago
I think using the target proportion for each zip_code makes more sense.
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Vincent
10 months ago
B) Clustering the levels using the zip_code values as input.
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Alishia
11 months ago
B) Clustering the levels using the zip_code values as input.
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Youlanda
11 months ago
A) Clustering the levels using the target proportion for each zip_code as input.
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Ligia
12 months ago
A) Clustering the levels using the target proportion for each zip_code as input.
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Willetta
1 year ago
Clustering the levels using the zip_code values as input? That's a bold move, Cotton. Let's see if it pays off.
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Sena
10 months ago
D) Clustering the levels using dummy coded zip_code levels as inputs.
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Caitlin
11 months ago
C) Clustering the levels using the number of cases in each zip_code as input.
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Maricela
11 months ago
B) Clustering the levels using the zip_code values as input.
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Lenna
11 months ago
A) Clustering the levels using the target proportion for each zip_code as input.
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William
1 year ago
I'm not sure, but I think C) Clustering the levels using the number of cases in each zip_code as input could also be a valid approach.
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Tabetha
1 year ago
Hmm, I think option A is the way to go. Using the target proportion for each zip_code as input seems like the most logical approach to cluster the levels.
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Oneida
11 months ago
I think so too. It's important to consider the target proportion when clustering the levels.
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Alesia
12 months ago
I think so too. It's important to consider the target proportion when clustering the levels.
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Bernadine
12 months ago
I agree, option A makes the most sense. It takes into account the target proportion for each zip_code.
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Ena
12 months ago
I agree, option A makes the most sense. It takes into account the target proportion for each zip_code.
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Malinda
1 year ago
I disagree, I believe it should be D) Clustering the levels using dummy coded zip_code levels as inputs.
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Rolande
1 year ago
I think the correct application is A) Clustering the levels using the target proportion for each zip_code as input.
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Ty
1 year ago
I agree with Layla, A) makes more sense because we want to reduce the number of levels based on the target variable.
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Emily
1 year ago
I disagree, I believe it should be D) Clustering the levels using dummy coded zip_code levels as inputs.
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Layla
1 year ago
I think the correct application is A) Clustering the levels using the target proportion for each zip_code as input.
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