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GAQM CLSSBB-001 Exam - Topic 4 Question 34 Discussion

A valid Multiple Linear Regression (MLR) is characterized by all of these except _______________________.
B) The X's (inputs) are assumed to be independent of each other
A) It is an assumption that the X's (inputs) are not correlated to each other
C) MLR is conducted based on a deliberate form of experimentation
D) The Residuals from MLR analysis have to be Normally Distributed

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 _______________________.

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Suggested Answer: B

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

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Cruz
9 months ago
B is correct, independence of inputs is key!
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Adria
10 months ago
Wait, are the residuals really supposed to be normally distributed?
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Sabra
10 months ago
C seems off to me, MLR doesn't always need experimentation.
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Elli
10 months ago
I agree, the inputs can't be correlated.
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Kattie
10 months ago
A is definitely a requirement for MLR.
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Thora
10 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
10 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
11 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
11 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
11 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
11 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
11 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
11 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
11 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
11 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
11 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
11 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
11 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
11 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
1 year 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
1 year ago
MLR is all about making sure the inputs are not correlated to each other.
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An
1 year ago
That's right. It's one of the key assumptions in Multiple Linear Regression analysis.
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Margot
1 year ago
Yes, you're correct. MLR assumes that the X's are independent of each other.
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Olive
1 year 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
1 year ago
Exactly, having correlated inputs can lead to multicollinearity issues in the regression analysis.
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Georgene
1 year ago
That's right, if the inputs are correlated, it violates one of the assumptions of MLR.
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Ollie
1 year ago
I agree, option A is the correct answer. The inputs in MLR should not be correlated.
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Corinne
1 year 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
1 year 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
1 year ago
User 1: I think you're right, option C does seem like the odd one out.
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Dahlia
1 year 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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Delisa
1 year ago
Thanks for clarifying that, now I understand the concept better.
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Tequila
1 year ago
So, the correct answer is D, the Residuals from MLR analysis have to be Normally Distributed.
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Blondell
1 year ago
I agree, the residuals being normally distributed is a key aspect of MLR.
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Lacresha
1 year ago
I think you're right, option D does seem out of place.
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Aleta
1 year ago
Option B seems like the correct answer here. The inputs in a valid MLR model should be independent of each other, not correlated.
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Juan
1 year ago
But doesn't MLR assume that the residuals are Normally Distributed?
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Matt
1 year ago
I disagree, I believe the answer is D.
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Juan
1 year ago
I think the answer is C.
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