Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

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.

Show Suggested Answer Hide Answer
Suggested Answer: B

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

Limited Time Offer

25%

Off

Get Premium Databricks Certified Professional Data Scientist Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Timothy
1 day ago
I feel B is best. RMSE needs a clear target.
upvoted 0 times
...
Flo
6 days ago
D) All of the above could work too. Depends on the scenario.
upvoted 0 times
...
Marylou
11 days ago
I lean towards A) Between Variables. Different contexts matter.
upvoted 0 times
...
Annice
17 days ago
Agreed, B makes sense. Comparisons need focus.
upvoted 0 times
...
Han
22 days ago
D) All of the above are correct! RMSE is versatile!
upvoted 0 times
...
Rosalind
27 days ago
Totally agree, it’s not useful for comparing across different scales.
upvoted 0 times
...
Mammie
2 months ago
I think it’s best for a particular variable.
upvoted 0 times
...
Dean
2 months ago
RMSE is definitely scale-dependent!
upvoted 0 times
...
Toshia
2 months ago
RMSE? More like ARGH-MSE, am I right? Statistics can be such a headache sometimes.
upvoted 0 times
...
Louis
2 months ago
Option D is clearly the right answer. RMSE can be used to compare models for any variable, not just a particular one. Duh!
upvoted 0 times
...
Mabelle
2 months 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.
upvoted 0 times
...
Owen
2 months ago
I feel like the answer is B, but I also recall something about it being scale-dependent for comparisons among variables.
upvoted 0 times
...
Sharika
3 months ago
I’m a bit confused; I thought RMSE could be used across all variables, but now I’m not so sure.
upvoted 0 times
...
Veronika
3 months 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.
upvoted 0 times
...
Brandee
3 months ago
I think RMSE is used to compare models for a specific variable, but I'm not entirely sure if it's just that.
upvoted 0 times
...
Nettie
3 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.
upvoted 0 times
...
Ernestine
3 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.
upvoted 0 times
...
Adrianna
3 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.
upvoted 0 times
...
Jolene
4 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!
upvoted 0 times
...
Elizabeth
4 months ago
I think it's B) Particular Variable. RMSE is specific.
upvoted 0 times
...
Ligia
4 months ago
Wait, can RMSE really be used for all variables? Sounds off.
upvoted 0 times
...
Shantell
4 months ago
Option B is correct. RMSE is scale-dependent, so it can only be used to compare forecasting errors for a particular variable.
upvoted 0 times
...
Cherilyn
5 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.
upvoted 0 times
...
Jolene
5 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.
upvoted 0 times
Lauran
4 months ago
RMSE really shines when comparing models for a specific variable.
upvoted 0 times
...
...

Save Cancel