SAS Exam A00-240 Topic 10 Question 104 Discussion

Actual exam question for SAS's A00-240 exam

Question #: 104
Topic #: 10

A marketing manager attempts to determine those customers most likely to purchase additional products as the result of a nation-wide marketing campaign.

The manager possesses a historical dataset (CAMPAIGN) of a similar campaign from last year.

It has the following characteristics:

Target variable Respond (0, 1)

Continuous predictor Income

Categorical predictor Homeowner(Y, N)

Which SAS program performs this analysis?

AOption A

BOption B

COption C

DOption D

Show Suggested Answer

Suggested Answer: C

by Shizue at Dec 04, 2024, 07:38 PM

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Jacquline

4 months ago

Wait, is this a trick question? I mean, who wouldn't want to use logistic regression for a binary target variable like Respond? Option C all the way, baby!

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Anjelica

2 months ago

Option C it is then, thanks for the input!

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Edmond

2 months ago

Definitely, Option C is the best choice for this scenario.

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Jose

2 months ago

Yeah, I agree. It's perfect for a binary target variable like Respond.

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Lorenza

2 months ago

I think logistic regression is the way to go for this analysis.

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Frederic

4 months ago

I'm just imagining the marketing manager trying to wrangle that CAMPAIGN dataset, like a rodeo clown tackling a wild bull. Option C is the way to go, no doubt about it.

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Bernadine

3 months ago

I agree, Option C is the way to go when dealing with historical datasets like CAMPAIGN.

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Sophia

3 months ago

Option C is definitely the best choice for this analysis.

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Mayra

4 months ago

Oh man, I bet the marketing manager is really hoping to find those high-income homeowners who'll buy anything. Option C is definitely the way to go here.

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Dorothy

4 months ago

Option A seems tempting, but I doubt a simple t-test would be enough to capture the complexity of this marketing campaign analysis. I'd have to go with Option C for this one.

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Stephen

4 months ago

Hmm, this seems like a classic case of predictive modeling. I'd go with Option C - it looks like it has the right components to tackle this problem using logistic regression.

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