Controls in an experiment are elements that are held constant and not affected by independent variables. Controls are essential for unbiased and accurate measurement of the dependent variables in response to the treatment. For example, patients reporting in a hospital with high-grade fever, breathing difficulty, cough, cold, and severe body pain are suspected of COVID infection. But it is also possible that other respiratory infection causes the same symptoms. So, the doctor recommends a COVID test. The patient's nasal swabs are collected, and the COVID test is performed. In addition, a control sample is maintained that does not have COVID viral RNA. This type of control is also called negative control. It helps to prevent false positive reports in patients' samples. A positive control is another commonly used type of control in an experiment. Unlike the negative control, the positive control contains an actual sample – the viral RNA. This helps to match the presence of viral RNA in the test samples, and it validates the procedure and accuracy of the test.