DA0-002 Data Analysis Practice Question
A data scientist is analyzing a dataset with 100 variables and 5,000 records. The dataset has several missing values and a few extreme outliers. The goal is to build a regression model to predict a continuous target. Which combination of preprocessing steps is most likely to improve model performance?
⚠ Common exam trap
CompTIA often tests the misconception that mean imputation and standard scaling are universally safe, but the trap here is that outliers and skewness require robust methods like median imputation and robust scaling to avoid distorting the model.
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
✓
Impute missing values with median, apply robust scaling, and then log transform skewed variables
Imputing missing values with the median is robust to outliers, robust scaling handles extreme values by using median and IQR, and log transformation reduces skewness in predictors. This combination preserves data integrity and stabilizes variance, which is critical for regression models on a dataset with 100 variables and 5,000 records.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Impute missing values with median, apply robust scaling, and then log transform skewed variables
Why this is correct
Median imputation is robust, robust scaling handles outliers, log transform handles skewness.
- ✗
Impute missing values with mean, then use PCA for dimensionality reduction
Why it's wrong here
Mean imputation is sensitive to outliers, PCA may not be needed initially.
- ✗
Drop all rows with missing values, then apply min-max scaling
Why it's wrong here
Dropping rows reduces sample size and min-max scaling is sensitive to outliers.
- ✗
Remove outliers using Z-score, then apply standard scaling
Why it's wrong here
Z-score removes data points and standard scaling is still sensitive to remaining outliers.
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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.