False Positive

A false positive is a result that is incorrectly identified as positive when it is actually negative. It refers to a situation where a test or a system wrongly indicates the presence or occurrence of something, leading to a false or incorrect conclusion. False positives are observed in various domains such as medical testing, cybersecurity, quality control, and statistical analysis.

In medical testing, a false positive occurs when a healthy individual is mistakenly identified as having a disease or condition. This may lead to unnecessary follow-up tests, treatments, and unnecessary anxiety for the patient. In cybersecurity, false positives can arise when a security system or software mistakenly identifies legitimate activities or files as malicious, resulting in unnecessary alarms and wasted resources. False positives are also of concern in quality control processes, where they may lead to the rejection of acceptable products if the system identifies defects incorrectly. In statistical analysis, a false positive represents a Type I error, where a null hypothesis is incorrectly rejected when it is actually true. Managing and minimizing false positives is essential to ensure accurate and reliable results across various fields.