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PRMIA Exam 8002 Topic 3 Question 88 Discussion

Actual exam question for PRMIA's 8002 exam
Question #: 88
Topic #: 3
[All 8002 Questions]

Which of the following is not a direct cause of autocorrelation or heteroskedasticity in the residuals of a regression model?

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Suggested Answer: B

by Melissia at Sep 12, 2024, 07:03 PM

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Chandra
7 months ago
I think C) The omission of a relevant explanatory variable can also cause issues with autocorrelation or heteroskedasticity.
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Jess
7 months ago
I agree with Erick, D) makes more sense because it can lead to misspecification of the model.
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Ligia
7 months ago
Using an inappropriate functional form? That's like trying to fit a square peg into a round hole. Rookie move.
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Rashad
7 months ago
The omission of a relevant explanatory variable is a classic cause of heteroskedasticity. Rookie mistake, really.
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Marleen
5 months ago
D) Using an inappropriate functional form in the model
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Bev
6 months ago
C) The omission of a relevant explanatory variable
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Zack
6 months ago
C) The omission of a relevant explanatory variable
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Keshia
6 months ago
B) A high positive correlation between two explanatory variables
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Terry
6 months ago
B) A high positive correlation between two explanatory variables
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Shawnna
6 months ago
A) A structural break in the dependent variable
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Tu
6 months ago
A) A structural break in the dependent variable
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Erick
7 months ago
I disagree, I believe it's D) Using an inappropriate functional form in the model.
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Phil
7 months ago
I think the answer is B) A high positive correlation between two explanatory variables.
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Chan
8 months ago
Wait, isn't autocorrelation and heteroskedasticity like the regression model's way of saying 'I don't feel so good'?
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Willodean
8 months ago
A structural break in the dependent variable? Sounds like a plot twist in a crime novel, not a regression issue!
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Jeff
7 months ago
B) A high positive correlation between two explanatory variables
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Nakisha
7 months ago
A) A structural break in the dependent variable
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Daniel
7 months ago
B) A high positive correlation between two explanatory variables
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Aileen
7 months ago
A) A structural break in the dependent variable
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