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DA0-002 Data Analysis Practice Question

A data analyst is building a binary classification model to predict customer churn. The dataset is imbalanced, with only 10% churners. The analyst wants to evaluate model performance with a focus on correctly identifying churners. Which metric is most appropriate?

⚠ Common exam trap

Many exam-takers default to accuracy as the default metric, failing to recognize that class imbalance renders accuracy misleading, and that the question's explicit focus on 'correctly identifying churners' points directly to recall, not precision or F1-score.

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

Recall (sensitivity)

Recall (sensitivity) is the most appropriate metric because it measures the proportion of actual churners correctly identified by the model. Since the dataset is imbalanced (only 10% churners) and the analyst's focus is on correctly identifying churners, recall directly addresses the cost of missing positive cases (false negatives). Accuracy would be misleading due to class imbalance, while precision and F1-score prioritize different trade-offs.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Recall (sensitivity)

    Why this is correct

    Recall measures how many actual churners were correctly found, directly addressing the focus.

  • F1-score

    Why it's wrong here

    F1 is harmonic mean of precision and recall; recall is more directly aligned with the goal.

  • Precision

    Why it's wrong here

    Precision measures how many predicted churners are actually churners, not directly about finding churners.

  • Accuracy

    Why it's wrong here

    Accuracy is high even if model predicts all non-churners, not useful for imbalanced data.

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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.