Scientific control

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The scientific control, while heavily disputed among scholars, is used in scientific experiments as a constant to show the effect a given environment has on certain variables.

A scientific control augments integrity in experiments by isolating variables as dictated by the scientific method in order to make a conclusion about such variables. In a controlled experiment, two virtually identical experiments are conducted, but the factor being tested is varied in only one of them. This serves to further isolate any causal phenomena. For example, in testing a drug, it is important to carefully test that the supposed effect of the drug is produced only by the drug itself. Doctors achieve this with a double-blind study in a clinical trial: two virtually identical groups of patients are compared, one of which receives the drug and one of which receives a placebo. Neither the patients nor the doctor know which group receives the real drug, which serves both to curb researchers' bias and isolates the effects of the drug.

[edit] Necessity of Controls

Controls are needed to eliminate alternate explanations of experimental results. For example, suppose a researcher feeds an experimental artificial sweetener to thirty laboratory rats and observes that eight of them subsequently die of dehydration. The underlying cause of death could be the sweetener itself or something unrelated. Perhaps the rats were simply not supplied with enough water; or the water was contaminated and undrinkable; or the rats were under some psychological or physiological stress that caused them not to drink enough; or a disease dehydrated them; or their cage was kept too hot. Eliminating each of these possible explanations individually would be time-consuming and difficult. Instead, the researcher can use an experimental control, separating the rats into two groups: one group that receives the sweetener and one that doesn't. The two groups are kept in otherwise identical conditions, and both groups are observed in the same ways. Now, any difference in morbidity between the two groups can be ascribed to the sweetener itself--and no other factor--with much greater confidence.

In other cases, an experimental control is used to prevent the effects of one variable from being drowned out by the known, greater effects of other variables. For example, suppose a program that gives out free books to children in subway stations wants to measure the effect of the program on standardized test scores. However, the researchers understand that many other factors probably have a much greater effect on standardized test scores than the free books: household income, for example, and the extent of parents' education. In scientific parlance, these are called confounding variables. In this case, the researchers can either use a control group or use statistical techniques to control for the other variables.

[edit] Types of Controls

Negative control: A control sample where a negative result is expected, to help correlate a positive result with the variable being tested. Example: a measurement of background radiation when trying to test the effects of a certain substance on local radiation levels.

Positive control: A control sample that is known to produce a positive result if the test is working as expected. Example: printing a test page on a printer with its own driver software to test that it has been installed correctly, before testing the printing behaviour of another piece of software.