Extraneous variable

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Extraneous variables are variables other than the independent variable that may bear any effect on the behavior of the subject being studied. This only affects the people in the experiment, not the place the experiment is taking place in. Some examples are gender, ethnicity, social class, genetics, intelligence, age.

A variable is extraneous only when it can be assumed to influence the dependent variable. It introduces noise but doesn't systematically bias the results.



Extraneous variables are often classified into three types:

  1. Subject variables, which are the characteristics of the individuals being studied that might affect their actions. These variables include age, gender, health status, mood, background, etc.
  2. Experimental variables are characteristics of the persons conducting the experiment which might influence how a person behaves. Gender, the presence of racial discrimination, language, or other factors may qualify as such variables.
  3. Situational variables are features of the environment in which the study or research was conducted, which have a bearing on the outcome of the experiment in a negative way. Included are the air temperature, level of activity, lighting, and the time of day.

Controlling extraneous variables

There are two strategies of controlling extraneous variables. Either a potentially influential variable is kept the same for all subjects in the research, or they balance the variables in a group.


According to Campbell and Stanley[citation needed], there are at least eight kinds of extraneous variables:all of the above


These are the occurrence of events during the course of the experiment, but may affect the results of the dependent variable. This is a concern in longitudinal designs, wherein there is a long time span for the duration of the experiment.

These are changes that occur within the subjects during the passage of time. Variables such as physical growth, aging, hunger,religion etc. change over time and tend to be confounding variables to the experiment. For example, if you put a long span between the pre-testing and the post-testing of infants during your study of memory, it will not be internally valid for the reason that infants brain development is high, and its brain may have developed enough to have an effect on the post-test, thus showing that there is an increase in the memory capabilities of the infant, notwithstanding the fact that it has grown over time.


This is a threat to internal validity when a pre-test has had an effect on the post-test. This variable occurs in experiments using repeated testing, wherein the subject being tested becomes 'knowledgeable' about the experiment by putting his/her thoughts about the experiment, these are called demand characteristics.


This is a threat to validity due to some misdemeanors on the part of the experimenter or checker, it has nothing to do with participants.


Improper assignment of test units to treatment conditions. This problem can be solved by random assignment of test units to treatment conditions.

Statistical regression

Similar to testing carryover, except that regression is the phenomenon that extreme scores change more from pretest to posttest than do average scores.

Attrition or experimental mortality

A subject quits the experiment while the experiment is in progress.