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IIBA Exam CBDA Topic 3 Question 31 Discussion

Actual exam question for IIBA's CBDA exam
Question #: 31
Topic #: 3
[All CBDA Questions]

An analyst is performing regression analysis and reviewing the results. They would like to rescale the variables in the model to more clearly reflect the relationship between the regression coefficients. Which technique could be used to rescale the variables?

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Suggested Answer: C

by Meghan at Feb 10, 2025, 04:56 AM

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Gerardo
29 days ago
I'm not sure, but I think Mean Centering could also be used to rescale the variables.
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Izetta
1 months ago
I agree with Regenia. Normalization rescales the variables to a common range.
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Blondell
1 months ago
I'm going with C) Normalization. Rescaling the variables is key, and normalization is just the ticket. Plus, it's like the explanation says, it makes the coefficients easier to interpret. And who doesn't love a good interpretation, am I right?
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Amina
2 days ago
User1: It's definitely a useful technique to improve the performance of algorithms.
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Wilda
3 days ago
User3: I always use normalization for rescaling variables in regression analysis.
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Kattie
12 days ago
User2: Absolutely, normalization helps make the interpretation of regression coefficients easier.
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Jesusita
21 days ago
User1: I agree, C) Normalization is the way to go for rescaling the variables.
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Regenia
1 months ago
I think the answer is C) Normalization.
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Ashley
1 months ago
B) Mean centering, for sure. That's the way to go if you want to really understand the relationships between the regression coefficients. Normalization's cool and all, but mean centering is where it's at, my friend.
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Lorrine
8 days ago
C) Normalization
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Fausto
18 days ago
B) Mean Centering
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Doug
23 days ago
A) Dimension Reduction
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Odette
1 months ago
Hmm, I think normalization is the way to go here. It just makes sense to rescale those variables to a common range, you know? Plus, it helps with the whole outlier thing. Gotta keep those pesky outliers in check!
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Martina
25 days ago
User 2: Absolutely, normalization is key for rescaling variables in regression analysis. It's all about that common range.
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Adela
1 months ago
User 1: I agree, normalization is definitely the way to go. It helps with outliers and makes interpreting coefficients easier.
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