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Information about Experimental Control

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. In one of them, the treatment, the factor being tested is applied. In the other, the control, the factor being tested is not applied. For example, in testing a drug, it is important to carefully verify that the supposed effects of the drug are produced only by the drug itself. Doctors achieve this with a double-blind study in a clinical trial: two (statistically) 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 to isolate the effects of the drug.

Necessity of controls

Controls are needed to eliminate alternate explanations of experimental results. For example, suppose a researcher feeds an experimental artificial sweetener to sixty laboratory rats and observes that ten of them subsequently die of dehydration and vomit. The underlying cause of death could be the sweetener itself or something unrelated. Perhaps the rats were simply supplied with a lot of 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. Variables such as independent and dependent.

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. Contrasting this with negative control, where you expose the subject (or experiment) to a substance or condition that is not known to have an effect.

See also

In the scientific method, an experiment (Latin: ex- periri, "of (or from) trying") is a set of observations performed in the context of solving a particular problem or question, to support or falsify a hypothesis or research concerning phenomena.
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variable (IPA pronunciation: [ˈvæɹiəbl]) (sometimes called a pronumeral) is a symbolic representation denoting a quantity or expression.
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Scientific method is a body of techniques for investigating phenomena, acquiring new knowledge, or correcting and integrating previous knowledge. It is based on gathering observable, empirical and measurable evidence subject to specific principles of reasoning,[1]
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A medication, medicine or drug is any substance or combination of substances administered to human beings or animals to treat or prevent disease; alternatively to assist in medical diagnosis.
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physician applies to a person who practices some type of medicine. Such medical practitioners are concerned with maintaining or restoring human health through the study, diagnosis and treatment of disease and injury, through both an area of knowledge
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For the communication paradox, see .


The double blind method is an important part of the scientific method, used to prevent research outcomes from being 'influenced' by either the placebo effect or the observer bias.
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In health care, a clinical trial is a comparison test of a medication or other medical treatment (such as a medical device), versus a placebo (inactive look-a-like), other medications/devices, or the standard medical treatment for a patient's condition.
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patient is any person who receives medical attention, care, or treatment. The person is most often ill or injured and in need of treatment by a physician or other medical professional.
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Placebo effect is the term applied by medical science to the therapeutical and healing effects of inert medicines and/or ritualistic or faith healing manipulations.[1] [2].
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bias is a prejudice in a general or specific sense, usually in the sense for having a preference to one particular point of view or ideological perspective. However, one is generally only said to be biased
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sugar substitute, or artificial sweetener, is a food additive which attempts to duplicate the effect of sugar or corn syrup in taste, but usually with less food energy.

An important class of sugar substitutes are known as high intensity sweeteners.
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RATS may refer to:
  • Regression Analysis of Time Series, a statistical package.
  • Rough Auditing Tool for Security, a computer program.
  • Reverse Add Then Sort, an integer sequence (1, 2, 4, 8, 16, 77, 145, 668, 1345, 6677, 13444, 55778...)

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A confounding variable (also confounding factor, lurking variable, a confound, or confounder) is an extraneous variable in a statistical or research model that should have been experimentally controlled, but was not.
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Background radiation is the ionizing radiation emitted from a variety of natural and artificial radiation sources. Primary contributions come from:
  • Sources in the Earth.

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Controlling for a variable means to deliberately vary the experimental conditions in order to take that variable into account in the prediction of the response variable. Controlling tends to reduce the experimental error.
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