DA0-002 Data Analysis Practice Question
A data analyst wants to segment customers into groups based on their purchasing behavior. The dataset includes numerical features such as annual income and purchase frequency. Which algorithm is most appropriate for this task?
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
✓
K-means clustering
K-means clustering is a common algorithm for customer segmentation based on numerical features.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Linear regression
Why it's wrong here
Linear regression predicts a continuous outcome, not segments.
- ✓
K-means clustering
Why this is correct
Correct: K-means is unsupervised clustering for segmentation.
- ✗
Logistic regression
Why it's wrong here
Logistic regression is for binary classification.
- ✗
Chi-square test
Why it's wrong here
Chi-square tests independence, not segmentation.
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