True Positive (TP)
- A true positive is when a test or measurement indicates a condition and that condition is actually present.
- Appears in contexts such as medical tests, criminal investigations, and marketing research.
- TP must be considered alongside false positives, false negatives, and true negatives to assess overall accuracy.
Definition
Section titled “Definition”True Positive (TP) refers to a situation where a positive result is accurately identified. In other words, the test correctly identifies the presence of a specific condition or trait.
Explanation
Section titled “Explanation”TP denotes correct identification of a positive outcome. It is used across contexts (for example, medical testing, criminal investigations, and marketing research) to indicate that a test or survey has correctly detected the presence of the targeted condition or attribute.
TP is one of four possible outcomes for a binary decision process:
- False Positive (FP): a positive result that is incorrect.
- False Negative (FN): a negative result that is incorrect.
- True Negative (TN): a negative result that is correct.
These outcomes are commonly organized in a confusion matrix, which shows how many times each outcome occurred. From the confusion matrix one can compute metrics such as sensitivity (the ability to correctly identify positives) and specificity (the ability to correctly identify negatives).
Examples
Section titled “Examples”Medical test for a specific disease
Section titled “Medical test for a specific disease”A person goes to the doctor and gets tested for a particular disease. The test comes back positive, indicating that the person has the disease. This is a true positive result because the test accurately identified the presence of the disease.
Marketing research survey
Section titled “Marketing research survey”A company is conducting a survey to determine which product features are most appealing to consumers. One of the questions asks respondents if they would be interested in purchasing a product with a certain feature. A respondent answers “yes,” indicating that they would be interested in purchasing the product with that feature. This is a true positive result because the respondent’s answer accurately reflects their interest in the product.
Use cases
Section titled “Use cases”- Medical tests
- Criminal investigations
- Marketing research
Notes or pitfalls
Section titled “Notes or pitfalls”- TP alone does not fully describe a test’s accuracy; FP, FN, and TN must also be considered.
- The confusion matrix summarizes these four outcomes and is used to calculate performance metrics such as sensitivity and specificity.
Related terms
Section titled “Related terms”- False Positive (FP)
- False Negative (FN)
- True Negative (TN)
- Confusion matrix
- Sensitivity
- Specificity