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Databricks Certified Professional Data Scientist Exam - Topic 3 Question 90 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam
Question #: 90
Topic #: 3
[All Databricks Certified Professional Data Scientist Questions]

RMSE is a good measure of accuracy, but only to compare forecasting errors of different models for a______, as it is scale-dependent.

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Suggested Answer: B

by Fidelia at Nov 24, 2025, 11:04 AM

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Mammie
9 hours ago
I think it’s best for a particular variable.
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Dean
6 days ago
RMSE is definitely scale-dependent!
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Toshia
11 days ago
RMSE? More like ARGH-MSE, am I right? Statistics can be such a headache sometimes.
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Louis
16 days ago
Option D is clearly the right answer. RMSE can be used to compare models for any variable, not just a particular one. Duh!
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Mabelle
21 days ago
All of the above are correct? Really? That's like saying "all of the above" is the right answer to every multiple-choice question.
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Owen
26 days ago
I feel like the answer is B, but I also recall something about it being scale-dependent for comparisons among variables.
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Sharika
1 month ago
I’m a bit confused; I thought RMSE could be used across all variables, but now I’m not so sure.
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Veronika
1 month ago
I remember practicing a question where RMSE was discussed in the context of different models, so I feel like "Particular Variable" might be the right choice.
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Brandee
1 month ago
I think RMSE is used to compare models for a specific variable, but I'm not entirely sure if it's just that.
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Nettie
2 months ago
Wait, I'm a little confused now. The question says RMSE is good for comparing forecasting errors, but then it mentions the scale-dependence. Does that mean you can only use it to compare models within the same variable, or is it more broad than that? I'll have to think this through carefully.
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Ernestine
2 months ago
I'm pretty confident on this one. The question is specifically asking about the limitations of RMSE, and it states that it's scale-dependent. That means you can only use it to compare models for the same variable, not across different ones. The answer is B.
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Adrianna
2 months ago
Okay, I've got this. RMSE can only be used to compare models for a single variable, not across different variables, since the scale matters. So the answer has to be B) Particular Variable.
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Jolene
2 months ago
I thought RMSE was a measure of accuracy, not a way to compare models. Guess I need to brush up on my stats!
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Elizabeth
2 months ago
I think it's B) Particular Variable. RMSE is specific.
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Ligia
3 months ago
Wait, can RMSE really be used for all variables? Sounds off.
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Shantell
3 months ago
Option B is correct. RMSE is scale-dependent, so it can only be used to compare forecasting errors for a particular variable.
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Cherilyn
3 months ago
Hmm, this one has me a bit stumped. I know RMSE is about measuring accuracy, but I'm not sure about the scale-dependence part and how that affects the comparison. I'll have to review my notes on that.
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Jolene
3 months ago
I think the key here is understanding that RMSE is scale-dependent, so it can only be used to compare models for a particular variable. I'll need to think through the implications of that.
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Lauran
2 months ago
RMSE really shines when comparing models for a specific variable.
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