GAQM CLSSBB-001 Exam - Topic 4 Question 34 Discussion

Actual exam question for GAQM's CLSSBB-001 exam

Question #: 34
Topic #: 4

[All CLSSBB-001 Questions]

A valid Multiple Linear Regression (MLR) is characterized by all of these except _______________________.

AIt is an assumption that the X's (inputs) are not correlated to each other

BThe X's (inputs) are assumed to be independent of each other

CMLR is conducted based on a deliberate form of experimentation

DThe Residuals from MLR analysis have to be Normally Distributed

Show Suggested Answer

Suggested Answer: B

by Bok at Oct 03, 2023, 07:19 AM

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Cruz

3 months ago

B is correct, independence of inputs is key!

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Adria

3 months ago

Wait, are the residuals really supposed to be normally distributed?

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Sabra

4 months ago

C seems off to me, MLR doesn't always need experimentation.

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Elli

4 months ago

I agree, the inputs can't be correlated.

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Kattie

4 months ago

A is definitely a requirement for MLR.

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Thora

4 months ago

I feel like I saw something about the X's needing to be independent in a practice test, but I might be mixing it up with correlation.

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Mari

4 months ago

I practiced a question about residuals needing to be normally distributed, but I can't recall if that's a strict requirement for MLR validity.

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Delsie

4 months ago

I think option C sounds off because MLR can be used in observational studies too, not just experiments.

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Janey

5 months ago

I remember that MLR assumes the inputs should be independent, but I'm not sure if that's the same as saying they're not correlated.

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Paz

5 months ago

Wait, I'm not sure about this. Aren't the inputs supposed to be uncorrelated? I'm going to have to review my notes on the MLR assumptions again before answering this.

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Ozell

5 months ago

Okay, I've got it. The key is that MLR doesn't require a deliberate form of experimentation, unlike some other regression techniques. I'm confident that's the right answer.

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Alise

5 months ago

Hmm, I'm a bit confused on this one. I thought the residuals had to be normally distributed, but the options say that's not the case. Let me think this through again.

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Raylene

5 months ago

This one seems straightforward. I'm pretty sure the answer is that MLR doesn't require the inputs to be independent of each other.

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Ryann

5 months ago

I've got a good handle on the main advantages of low-code automation. I'll make sure to select the most relevant options that align with the question.

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Verona

5 months ago

I'm a little confused about the gastroesophageal reflux disease and how that might impact the primidone. I'll need to research that interaction more before deciding on the best course of action.

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Carmela

5 months ago

No problem, this is a classic inflation adjustment question. I'll just need to be careful with the calculations to make sure I get the right answer.

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Howard

5 months ago

Hmm, I'm a bit confused on the differences between these two models. I'll need to review my notes to make sure I understand the concepts before attempting to answer this.

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Maile

5 months ago

I remember we discussed that the Runtime Resource needs to be started for it to process anything, but I'm not entirely sure about the network connectivity part.

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Huey

5 months ago

I'm pretty sure the answer is B, Truth in Lending, since that's the regulation that covers disclosure requirements for adjustable-rate mortgages.

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Theresia

10 months ago

Wait, you're telling me that MLR doesn't require the inputs to be independent? That's news to me! Option B must be the right answer then.

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Pearlene

8 months ago

MLR is all about making sure the inputs are not correlated to each other.

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An

8 months ago

That's right. It's one of the key assumptions in Multiple Linear Regression analysis.

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Margot

8 months ago

Yes, you're correct. MLR assumes that the X's are independent of each other.

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Olive

10 months ago

Haha, this question is a piece of cake! Everyone knows that the inputs in MLR can't be correlated. Option A is clearly the correct answer.

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Stephen

9 months ago

Exactly, having correlated inputs can lead to multicollinearity issues in the regression analysis.

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Georgene

9 months ago

That's right, if the inputs are correlated, it violates one of the assumptions of MLR.

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Ollie

9 months ago

I agree, option A is the correct answer. The inputs in MLR should not be correlated.

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Corinne

10 months ago

Hmm, I thought MLR was all about the deliberate manipulation of the inputs to see their effect on the output. Option C seems like the answer to me.

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Elvera

10 months ago

User 2: Yeah, MLR is more about analyzing the relationship between inputs and output, not necessarily through deliberate experimentation.

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Altha

10 months ago

User 1: I think you're right, option C does seem like the odd one out.

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Dahlia

11 months ago

I'm not sure about the answer, but I know that the residuals should be normally distributed for the model to be valid. Option D looks like the odd one out.

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