Quick Answer
The answer is 0.76. This F1 score is derived from the confusion matrix by calculating the harmonic mean of precision and recall, where precision equals true positives divided by all predicted positives (80/100 = 0.80) and recall equals true positives divided by all actual positives (80/110 ≈ 0.7273); plugging these into the formula 2 × (precision × recall) / (precision + recall) yields approximately 0.7619, which rounds to 0.76. On the CompTIA Data+ DA0-001 exam, this F1 score calculation from a confusion matrix tests your ability to evaluate model performance beyond simple accuracy, especially when class imbalance is present—a common trap is forgetting to compute both precision and recall separately before applying the harmonic mean. A helpful memory tip: think of F1 as the "balanced score" that punishes extreme values, so if either precision or recall is low, the F1 score drops significantly.
This DA0-001 practice question tests your understanding of analyzing and modeling data. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
0.76
Precision=0.8, Recall≈0.727, F1≈0.76.
0.73
Why wrong: This is recall, not F1.
0.80
Why wrong: This is precision, not F1.
0.69
Why wrong: This value might come from miscalculation. The correct F1 is approximately 0.76.
Answer choices
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
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.
Related concept
Read the scenario before looking for a memorised answer.
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.
Common exam traps
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.
Detailed technical explanation
The F1 score is particularly useful when class distribution is imbalanced, as it balances precision and recall without favoring the majority class. In binary classification, the confusion matrix directly feeds into these metrics; for example, in a fraud detection model with 1% fraud cases, accuracy could be high while F1 reveals poor minority class performance. The harmonic mean penalizes extreme values more than the arithmetic mean, ensuring both precision and recall must be high for a good F1 score.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A practitioner preparing for the DA0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
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FAQ
Analyzing and Modeling Data — This question tests Analyzing and Modeling Data — Read the scenario before looking for a memorised answer..
The correct answer is: 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.
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Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
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