Confusion Matrix Calculator
Enter true positives, false positives, true negatives, and false negatives to calculate every standard classification and diagnostic test metric at once.
Last updated: September 1, 2026
Frequently asked questions
What's the difference between precision and recall?
Precision asks: of everything flagged positive, how much was actually positive? (TP/(TP+FP)). Recall asks: of everything actually positive, how much did you catch? (TP/(TP+FN)). There's usually a tradeoff between the two.
What is the F1 score?
The harmonic mean of precision and recall, giving a single balanced score: F1 = 2×(precision×recall)/(precision+recall). It's low if either precision or recall is low, unlike a simple average.
How is specificity different from recall (sensitivity)?
Recall (sensitivity) measures how well you catch actual positives; specificity measures how well you correctly identify actual negatives (TN/(TN+FP)). A test can have high sensitivity but low specificity, or vice versa.
What's the difference between PPV and NPV?
PPV (positive predictive value, same as precision) is the chance a positive result is truly positive. NPV (negative predictive value) is the chance a negative result is truly negative - both depend heavily on prevalence, not just the test's inherent accuracy.
Why does prevalence matter for interpreting these numbers?
A test's sensitivity and specificity are fixed properties of the test itself, but PPV and NPV shift with how common the condition actually is - the same test gives a much lower PPV when screening a low-prevalence population than a high-prevalence one, even with identical sensitivity/specificity.