What is the importance of a positive control in experiment?

Although not all experiments need to include them, they are very useful in experiments involving long, multistage processes where the experimental material is not always reliable whether human error can spread out. Experiments involving DNA amplification are both examples.

Positive control guarantees that the protocol is not disturbed or that the reagents are not degraded. If your positive control gets a negative result, you know that all other negative results in your treatment group should be tested more carefully, and fresh reagents I might use it

If the positive control does not produce the expected results, the experimental procedure may be problematic and the experiment repeated. For difficult experiments and complicated experiments, the results of positive control are also useful compared to previous experimental results. For example, if it is determined that a well-established disease test has the same effectiveness as the previous experimenter, it indicates that the experiment was performed in the same way as the previous experimenter.

While this is the most overlooked aspect of many experiments, it is often the most important. You can see that the experiment is functioning properly. Positive control is the condition you know to get positive results, and negative control is the opposite. Many scientists seem to think that all experiments always function as expected, it is not the case. Sometimes the machine breaks, the enzyme breaks down, someone is destroying your experiment. Therefore, a good way to calm the mind is to control, at least actively control

The simplest type of control is a negative control and a positive control, both of which exist in different kinds of experiments. If both are successful, these two controls are usually sufficient to eliminate most of the potential confounding variables. In other words, if a negative result is expected, negative results will be obtained in the experiment. There are only two possible consequences, such as positive or negative. If negative results are obtained with both treatment and negative control, it can be inferred that treatment is ineffective. If both the treatment group and the negative control produce positive results, it can be inferred that the phenomenon in the study involves confounding variables and that the positive outcome is not due to treatment alone