The Definition Of An Uncontrolled Variable

In statistics and scientific studies, using variables is an important aspect of structuring and completing a test or survey. While most people are familiar with the independent and dependent variables, another type of variable can change the outcome of the results. That third variable is the uncontrolled variable, also known as the confounding variable.

An uncontrolled variable, or mediator variable, is the variable in an experiment that has the potential to negatively impact the relationship between the independent and dependent variables. This can cause false correlations, improper analysis of results and incorrect rejections of a null hypothesis.

You can reduce or eliminate the effects of uncontrolled variables by having a clearly planned design for the experiment along with consistent checks for uncontrolled variables. Some methods of reducing uncontrolled variables are randomizing experiment groups, strict controls on the independent variables and strictly defining variables into factors that are measurable to get rid of "fuzzy" factors.

An example of how an uncontrolled variable can alter the results of an experiment is when a person gets angry, he gets a severe headache. It would be easy to state that his headaches are a result of his anger until you consider the fact that he drinks more beverages containing caffeine and sleeps less than six hours a night on average when he is angry. These confounding variables alter the relationship between the anger and the headaches, because you don't have a way to determine which of the three variables cause the pain in his head.

The issue of uncontrolled variables often occurs in relation to problems with correlation and causation. Because correlation does not necessarily mean causation, analysis based on findings from uncontrolled variables can create an incorrect reading of a link between two variables. You must always use human judgment when analyzing test results to determine whether an uncontrolled variable caused underlying issues that led to incorrect findings.