## **Core Concept**
The specificity of a diagnostic test is a measure of its accuracy in identifying individuals without the disease. It is calculated as the number of true negatives (those correctly identified as not having the disease) divided by the sum of true negatives and false positives (those incorrectly identified as having the disease). The formula for specificity is: Specificity = TN / (TN + FP), where TN is the number of true negatives and FP is the number of false positives.

## **Why the Correct Answer is Right**
To calculate the specificity of the test, we look at the data provided:
- True negatives (TN) = 95 (those with no disease and a negative test result)
- False positives (FP) = 5 (those with no disease but a positive test result)
Using the formula for specificity: Specificity = 95 / (95 + 5) = 95 / 100 = 0.95 or 95%. This matches option B, which is 95%.

## **Why Each Wrong Option is Incorrect**
- **Option A:** 80% is incorrect because it does not match the calculated specificity of 95%.
- **Option C:** 90% is incorrect because it underestimates the calculated specificity of 95%.
- **Option D:** 90.9% is close but incorrect because the precise calculation yields 95%, not 90.9%.

## **Clinical Pearl / High-Yield Fact**
A key point to remember is that specificity and sensitivity are complementary but distinct measures of a test's accuracy. Sensitivity (or true positive rate) measures the test's ability to correctly identify those with the disease, while specificity (or true negative rate) measures its ability to correctly identify those without the disease. A highly specific test is useful for confirming a diagnosis, as it minimizes the number of false positives.

## **Correct Answer:** B. 95%