DA0-002 Data Analysis Practice Question
A data analyst is performing data cleaning on a dataset and identifies several outliers in the 'age' column. Which TWO methods are appropriate for handling these outliers? (Select two.)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Capping
Capping limits extreme values to a threshold, and removal deletes outlier records. Transformation (e.g., log) can reduce impact but is more for skewness. Imputation and binning are for missing data or discretization, not directly for outliers.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Capping
Why this is correct
Capping limits outliers to a specified percentile.
- ✗
Mean imputation
Why it's wrong here
Imputation is for missing values, not outliers.
- ✗
Transformation
Why it's wrong here
Transformation can reduce skewness but is not specifically for outlier handling.
- ✓
Removal
Why this is correct
Deleting outlier records is a common approach.
- ✗
Binning
Why it's wrong here
Binning groups values into categories, not outlier treatment.
Go deeper
Related to this question
About these practice questions
This DA0-002 question is part of Courseiva's 986-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DA0-002 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DA0-002 exam.