false negative

A false positive is an error in data reporting in which a test result incorrectly indicates the presence of a condition such as a disease when the disease is not present, while a false negative is the opposite error where the test result incorrectly fails to indicate the presence of a condition when it is present. These are the two kinds of errors in a binary test, in contrast to the two kinds of correct result, a true positive and a true negative.) They are also known in medicine as a false positive (respectively negative) diagnosis, and in statistical classification as a false positive (respectively negative) error.

In statistical hypothesis testing the analogous concepts are known as type I and type II errors, where a positive result corresponds to rejecting the null hypothesis, and a negative result corresponds to not rejecting the null hypothesis. The terms are often used interchangeably, but there are differences in detail and interpretation due to the differences between medical testing and statistical hypothesis testing.