SAS A00-240 Exam - Topic 4 Question 80 Discussion

Actual exam question for SAS's A00-240 exam

Question #: 80
Topic #: 4

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?

AClustering the levels using the target proportion for each zip_code as input.

BClustering the levels using the zip_code values as input.

CClustering the levels using the number of cases in each zip_code as input.

DClustering the levels using dummy coded zip_code levels as inputs.

Show Suggested Answer

Suggested Answer: D

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

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Brandon

3 months ago

D sounds complicated, but could work if done right!

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Abel

4 months ago

C is interesting, but I think A is more relevant here.

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Willow

4 months ago

Wait, can you really cluster using just zip_code values?

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Frederica

4 months ago

I disagree, B seems more straightforward.

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Solange

4 months ago

A is the way to go! Target proportions matter.

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Arlette

4 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

4 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

5 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

5 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

5 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

5 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

5 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

5 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

5 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

5 months ago

This seems straightforward - I think the answer is to assign the existing service appointment to the crew.

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Johnetta

5 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

10 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

8 months ago

D) Clustering the levels using dummy coded zip_code levels as inputs.

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Curt

9 months ago

C) Clustering the levels using the number of cases in each zip_code as input.

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Marion

9 months ago

B) Clustering the levels using the zip_code values as input.

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Rana

9 months ago

A) Clustering the levels using the target proportion for each zip_code as input.

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Isaac

10 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

8 months ago

C) Clustering the levels using the number of cases in each zip_code as input.

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Olive

8 months ago

B) Clustering the levels using the zip_code values as input.

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Tish

9 months ago

A) Clustering the levels using the target proportion for each zip_code as input.

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Sage

10 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

9 months ago

C) Clustering the levels using the number of cases in each zip_code as input.

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Shenika

9 months ago

I agree, using dummy coded zip_code levels might be too complex for this situation.

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Leah

9 months ago

I think using the target proportion for each zip_code makes more sense.

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Vincent

9 months ago

B) Clustering the levels using the zip_code values as input.

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Alishia

9 months ago

B) Clustering the levels using the zip_code values as input.

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Youlanda

10 months ago

A) Clustering the levels using the target proportion for each zip_code as input.

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Ligia

10 months ago

A) Clustering the levels using the target proportion for each zip_code as input.

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Willetta

10 months 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

9 months ago

D) Clustering the levels using dummy coded zip_code levels as inputs.

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Caitlin

9 months ago

C) Clustering the levels using the number of cases in each zip_code as input.

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Maricela

9 months ago

B) Clustering the levels using the zip_code values as input.

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Lenna

9 months ago

A) Clustering the levels using the target proportion for each zip_code as input.

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William

11 months 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

11 months 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

9 months ago

I think so too. It's important to consider the target proportion when clustering the levels.

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Alesia

10 months ago

I think so too. It's important to consider the target proportion when clustering the levels.

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Bernadine

10 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

10 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

11 months 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

11 months 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

11 months 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

11 months 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

11 months 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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