False Positive Rate (FPR) is a testing accuracy measure that describes the likelihood of incorrectly identifying a condition when it is not actually present. It is the proportion of people who do not have the condition but test positive anyway. In other words, it is the rate of false alarms generated by the test. A low FPR indicates that the test rarely produces misleading positives, which is especially important when false positives can lead to unnecessary treatments, anxiety, or follow-up tests. This statistic assesses a test’s inherent accuracy and does not incorporate real-world disease prevalence.
False Positive Rate is a measure derived from a confusion matrix, which records the number of true positives, false positives, true negatives, and false negatives. FPR is calculated using the number of false positives and true negatives.
The false positive rate formula is the following:
FPR = False Positives / (False Positives + True Negatives)
FPR expresses false alarms as a proportion. The numerator is the number of false positives—people who don’t have the condition but receive a positive result. The denominator includes all people without the condition: those correctly identified as negative (TN) and those falsely identified as positive (FP).
Because it reflects how the test behaves across all people without the condition, the false positive rate is not affected by disease prevalence—making it useful for assessing the inherent tendency of a test to produce false alarms. If you want to understand the meaning of an individual’s test result that incorporates disease prevalence, use measures such a positive predictive value (PPV) and negative predictive value (NPV) instead.
Additionally, the false positive rate is the complement of specificity, meaning:
FPR = 1 – Specificity
Suppose a test evaluates 1,000 people who do not have a disease. If 950 are correctly identified as negative and 50 are incorrectly flagged as positive, then:
FPR = 50 / (50 + 950) = 0.05 or 5%
This result indicates 5% of healthy individuals received a false positive result.
« Back to Glossary Index