False Positive Paradox Calculator

Calculates the statistical implications of testing accuracy when both a test's sensitivity and specificity are imperfect. Users input various metrics, such as the prevalence of a condition, the true positive rate (sensitivity), and the true negative rate (specificity). The tool then demonstrates how these independent probabilities interact to determine the actual probability of having a condition given a positive test result or a negative test result. This calculation helps illuminate why high test accuracy numbers may not translate into strong clinical evidence when applied in real-world populations. Assists students, researchers, and clinicians who analyze diagnostic testing data. Individuals studying biostatistics or epidemiology find this calculator useful for understanding the limitations inherent in screening tests.