Sensitivity & Specificity Calculator

About this calculator

Every diagnostic test is judged against a 2×2 table of true positives, false positives, true negatives, and false negatives, and from those four counts come the metrics that define how good the test actually is: Sensitivity = TP / (TP + FN), the fraction of people who truly have the condition that the test correctly flags, and Specificity = TN / (TN + FP), the fraction of people without the condition the test correctly clears — with overall accuracy = (TP + TN) / total tested.

These two numbers matter for different reasons: high sensitivity is prioritized for screening tests where missing a real case (a false negative) is dangerous, while high specificity is prioritized when a false positive would trigger unnecessary invasive follow-up, which is why the same underlying test math is applied differently to a cancer screen versus a confirmatory diagnostic assay.

Epidemiologists and biostatisticians evaluating new diagnostic tools, laboratory professionals validating assay performance, and medical and public health students learning test-characteristic statistics all use this calculation as the standard first step in judging any diagnostic test's real-world usefulness.