In this article, we will learn about different test parameters that are required after performing medical tests on patients to analyse statistical data.

We may define terms for test results

**1. True positive (TP): **

A true positive test result is one that detects the condition when the condition is present. TP denotes the number of true positives.

**2. True negative (TN):**

A true negative test result is one that does not detect the condition when the condition is absent. TN denotes the number of true positives.

**3. False positive (FP):**

A false positive test result is one that detects the condition when the condition is absent. FP denotes the number of true positives.

**4. False negative (FN):**

A false negative test result is one that does not detect the condition when the condition is present. FN denotes the number of true positives.

**5. Sensitivity**

It measures the ability of a test to detect the condition when the condition is present. Thus,

Sensitivity = TP/(TP+FN)

**6. Specificity**

It measures the ability of a test to correctly exclude the condition (not detect the condition) when the condition is absent. Thus,

Specificity = TN/(TN+FP)

**7. Predictive value positive**

It is the proportion of positives that correspond to the presence of the condition. Thus,

Predictive value positive = TP/(TP+FP)

**8. Predictive value negative**

It is the proportion of negatives that correspond to the absence of the condition. Thus,

Predictive value negative = TN/(TN+FN)

**9. Parallel combination of tests**

It is a test that is positive if at least one of the combining tests is positive; otherwise, it is negative.

**OR**

It is a test that is negative only if all the combining tests are negative; otherwise, it is positive.

**10. Series combination of tests**

It is a test that is negative if at least one of the combining tests is negative; otherwise, it is positive.

**OR**

It is a test that is positive only if all the combining tests are positive; otherwise, it is negative.

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