False positives and false negatives
types of error in data reporting, where false positive is an error in which a test result incorrectly indicates the presence of a condition, while a false negative is the opposite error where the test fails to indicate the actual presence
False positives and negatives are words related with practical testing. When performing a practical test, there is the possibility that the result of the test does not show the real situation.
In a test, a false positive is when a test result shows that a condition is present – but it is not. A false negative is when a test result shows a condition is not present when in fact it is present.
Related pages
change- Type I and type II errors describe the same condition when it occurs in a statistical test
