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

CompTIA DA0-002 Exam - Topic 4 Question 6 Discussion

[Data Analysis]A data analyst must combine service calls into low-, medium-, and high-priority levels in order to analyze organizational responses. Which of the following techniques should the analyst use for this task?
D) Binning
A) Augmentation
B) Imputation
C) Scaling

CompTIA DA0-002 Exam - Topic 4 Question 6 Discussion

Actual exam question for CompTIA's DA0-002 exam
Question #: 6
Topic #: 4
[All DA0-002 Questions]

[Data Analysis]

A data analyst must combine service calls into low-, medium-, and high-priority levels in order to analyze organizational responses. Which of the following techniques should the analyst use for this task?

Show Suggested Answer Hide Answer
Suggested Answer: D

by Isreal at Jun 13, 2025, 10:53 PM

Limited Time Offer

25%

Off

Get Premium DA0-002 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Enola
9 months ago
Totally agree, binning makes the most sense for this task!
upvoted 0 times
...
Lottie
9 months ago
I think scaling could work too, but not as effective.
upvoted 0 times
...
Reiko
9 months ago
Imputation is more for missing data, not prioritization.
upvoted 0 times
...
Micaela
10 months ago
Wait, is binning really the best option here?
upvoted 0 times
...
Sherron
10 months ago
Binning is definitely the way to go for prioritizing!
upvoted 0 times
...
Onita
10 months ago
I keep mixing up imputation and binning. Imputation is for filling in missing values, right? So that can't be it.
upvoted 0 times
...
Elin
10 months ago
This question feels familiar; I think we practiced something similar where we had to classify data points. Binning seems to ring a bell.
upvoted 0 times
...
Rima
11 months ago
I'm not entirely sure, but I remember something about scaling being more about adjusting ranges rather than categorizing.
upvoted 0 times
...
Arthur
11 months ago
I think binning might be the right choice here since it involves categorizing data into different groups, which fits the priority levels.
upvoted 0 times
...
Benton
11 months ago
I'm a little confused by the options here. Augmentation, imputation, scaling - those all sound like they could be relevant, but I'm not sure which one is the best fit for this particular problem. Guess I'll have to weigh the pros and cons of each approach.
upvoted 0 times
...
Diego
11 months ago
Okay, I've got this. Binning is definitely the way to go here. I'll use a technique like equal-width or equal-frequency binning to group the service calls into the three priority levels. Simple but effective!
upvoted 0 times
...
Colton
11 months ago
Hmm, I'm a bit unsure about this one. Is binning the right approach, or should I be considering something like imputation to fill in any missing data first? I'll need to think this through carefully.
upvoted 0 times
...
Santos
11 months ago
This seems like a straightforward data binning problem. I'd start by looking at the distribution of the service call data and determining appropriate thresholds for the low, medium, and high priority levels.
upvoted 0 times
...
Rene
1 year ago
D) Binning all the way! It's like sorting service calls into nice little priority buckets. Easy peasy lemon squeezy.
upvoted 0 times
...
Lisha
1 year ago
C) Scaling? Hmm, maybe if we were trying to prioritize the service calls based on their magnitude, but that's not the question here. D) Binning is the clear winner.
upvoted 0 times
Maddie
1 year ago
A: Definitely, Binning helps in categorizing the data into specific groups based on certain criteria.
upvoted 0 times
...
Dorsey
1 year ago
B: I agree, Binning would be the most appropriate technique for this task.
upvoted 0 times
...
Nan
1 year ago
A: I think D) Binning is the best option for combining service calls into different priority levels.
upvoted 0 times
...
...
Clay
1 year ago
I'm not sure, but I think Scaling could also be a good option for this task.
upvoted 0 times
...
Genevieve
1 year ago
I agree with Meghan, Binning would be the best technique to combine service calls into priority levels.
upvoted 0 times
...
Catalina
1 year ago
A) Augmentation? What, are we trying to create some sort of super-service call or something? Nah, D) Binning is the way to go.
upvoted 0 times
...
Nathalie
1 year ago
B) Imputation? Really? How's that gonna help classify service calls into priorities? I think you're way off the mark there.
upvoted 0 times
Alfreda
1 year ago
B) Imputation is not the right choice for this task, it's more about filling missing values in data.
upvoted 0 times
...
Carma
1 year ago
D) Binning could be the technique to group service calls into low, medium, and high priorities.
upvoted 0 times
...
Wilford
1 year ago
C) Scaling might be useful to standardize the data before categorizing service calls.
upvoted 0 times
...
Carmela
1 year ago
A) Augmentation could help in combining service calls into different priority levels.
upvoted 0 times
...
...
Meghan
1 year ago
I think the analyst should use Binning for this task.
upvoted 0 times
...
Breana
1 year ago
Definitely going with D) Binning. Grouping service calls into priority levels is exactly what binning is all about.
upvoted 0 times
Paris
1 year ago
I think D) Binning is the most suitable technique for combining service calls into different priority levels.
upvoted 0 times
...
Gianna
1 year ago
Binning makes sense for this task, it helps organize the data effectively.
upvoted 0 times
...
Lezlie
1 year ago
I agree, D) Binning is the way to go for grouping service calls into priority levels.
upvoted 0 times
...
...

Save Cancel