# All Science Fair Projects

## Science Fair Project Encyclopedia for Schools!

 Search    Browse    Forum  Coach    Links    Editor    Help    Tell-a-Friend    Encyclopedia    Dictionary

# Science Fair Project Encyclopedia

For information on any area of science that interests you,
enter a keyword (eg. scientific method, molecule, cloud, carbohydrate etc.).
Or else, you can start by choosing any of the categories below.

# Specificity

In binary testing, e.g. a medical diagnostic test for a certain disease, specificity is the proportion of true negatives of all the negative samples tested, that is

${\rm specificity}=\frac{\rm number\ of\ true\ negatives}{{\rm number\ of\ true\ negatives}+{\rm number\ of\ false\ positives}}$

In Information Retrieval, specificity is called precision.

For a test to determine who has a certain disease, a specificity of 100% means that all people labeled as sick are actually sick.

Specificity alone does not tell us all about the test, because a 100% specificity can be trivially achieved by labeling all test cases negative. Therefore, we also need to know the sensitivity of the test.

F-measure can be used as a single measure of performance of the test. The F-measure is the geometric mean of sensitivity and specificity:

F = 2 * precision * recall / (precision + recall).

A test with a high specificity has a low Type I error.

Sensitivity is not the same as the positive predictive value defined as

$\frac{\rm number\ of\ true\ positives}{{\rm number\ of\ true\ positives}+{\rm number\ of\ false\ positives}}$

which is as much a statement about the proportion of actual positives in the population being tested as it is about the test.