Free COMPTIA Data+ DA0-001 Actual Exam Questions - Question 12 Discussion
scale of 0 to 1.
What term describes this action?
B. Another way to think about it is that normalization adjusts the data to a common scale without distorting differences in the ranges of values. Filtering would be cutting out data points, which isn’t what’s happening here, and transposition is just flipping data orientation. Aggregation combines data points, so that doesn’t fit either. So, scaling variables to 0-1 is definitely normalization.
I get why normalization (B) is a strong pick since it’s about adjusting values to a standard scale. Another angle: filtering (A) usually means selecting or removing data, not changing values. Transposition (C) flips rows and columns, so definitely not about scaling. Aggregation (D) combines multiple data points, which isn’t what’s happening here either. So, does anyone think there’s a reason to question normalization given these definitions?
D imo, since aggregation usually means combining data, not scaling it. Normalization for rescaling to 0-1 fits better than filtering or transposition too.
It’s B because only normalization rescales data values between 0 and 1.
This definitely sounds like B. Normalization is the go-to term when you're adjusting data values to fit within a specific range like 0 to 1. Filtering and aggregation don’t deal with changing value scales, and transposition is just about switching rows and columns, so those don’t apply here.
Probably B. Scaling variables to a 0-1 range is classic normalization; filtering (A) and aggregation (D) don’t really fit here. Transposition (C) is about rearranging data, not scaling.
Maybe B here. Normalization covers rescaling data to a common range like 0 to 1, while filtering is more about cutting out unwanted data, so B fits better.
Option B makes sense since normalization is the general term for scaling data, and scaling to 0-1 is a typical method. Filtering (A) is more about selecting data, not scaling.
I think it’s B, Normalization. Scaling data between 0 and 1 is a common normalization method to standardize values.