DA0-002 Data Analysis Practice Question
After building a binary classification model, the data analyst obtains the following confusion matrix: True Positives=80, True Negatives=100, False Positives=20, False Negatives=30. What is the F1 score?
⚠ Common exam trap
CompTIA often tests the distinction between precision, recall, and F1, and the trap here is that candidates mistakenly use accuracy or a simple average instead of the harmonic mean, or they confuse recall with F1.
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
✓
0.76
The F1 score is the harmonic mean of precision and recall. Precision = TP/(TP+FP) = 80/(80+20) = 0.80. Recall = TP/(TP+FN) = 80/(80+30) ≈ 0.7273. F1 = 2 * (0.80 * 0.7273) / (0.80 + 0.7273) ≈ 0.7619, which rounds to 0.76. Option A is correct.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
0.76
Why this is correct
Precision=0.8, Recall≈0.727, F1≈0.76.
- ✗
0.73
Why it's wrong here
This is recall, not F1.
- ✗
0.80
Why it's wrong here
This is precision, not F1.
- ✗
0.69
Why it's wrong here
This value might come from miscalculation. The correct F1 is approximately 0.76.
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