Extraneous Variables In Research: Types & Examples

When we conduct experiments, there are other variables that can affect our results if we do not control them.

Anything that is not the independent variable that has the potential to affect the results is called an extraneous variable.

It can be a natural characteristic of the participant, such as intelligence level, gender, or age, for example, or it could be a feature of the environment, such as lighting or noise.

Purpose

The researcher wants to make sure that it is the manipulation of the independent variable that has an effect on the dependent variable.

Hence, all the other variables that could affect the dependent variable to change must be controlled. These other variables are called extraneous or confounding variables.

Extraneous variables should be controlled where possible, as they might be important enough to provide alternative explanations for the effects.

Independent, Dependent and Extraneous Variables

Types

1. Situational Variables

Situational variables are factors, conditions, or characteristics related to the external environment that can influence a situation’s behavior, decision-making, or outcome.

They are called “situational” because they are specific to a certain situation or context, as opposed to more stable, personal characteristics (like personality traits) that are relatively constant across situations.

Examples of situational variables can range from physical aspects of the environment (like weather, location, time of day, or noise level) to social aspects (like the presence of others, group dynamics, or societal norms) to more abstract aspects (like time pressure, level of risk, or the clarity of instructions).

Situational variables should be controlled so they are the same for all participants.

Standardized procedures ensure that conditions are the same for all participants. This includes the use of standardized instructions

2. Participant  Variable

This refers to the ways in which each participant varies from the other and how this could affect the results, e.g., mood, intelligence, anxiety, nerves, concentration, etc.

For example, if a participant that has performed a memory test was tired, dyslexic, or had poor eyesight, this could affect their performance and the results of the experiment. The experimental design chosen can have an effect on participant variables.

Situational variables also include order effects that can be controlled using counterbalancing, such as giving half the participants condition “A” first while the other half gets condition “B” first. This prevents improvement due to practice or poorer performance due to boredom.

Participant variables can be controlled using random allocation to the conditions of the independent variable.

3. Experimenter / Investigator Effects

The experimenter unconsciously conveys to participants how they should behave – this is called experimenter bias.

The experiment might do this by giving unintentional clues to the participants about the experiment and how they expect them to behave. This affects the participants’ behavior.

The experimenter is often totally unaware of the influence that s/he is exerting, and the cues may be very subtle, but they may have an influence nevertheless.

Also, the personal attributes (e.g., age, gender, accent, manner, etc.) of the experiment can affect the behavior of the participants.

4. Demand Characteristics

Demand characteristics are all the clues in an experiment that convey to the participant the purpose of the research. Demand characteristics can change the results of an experiment if participants change their behavior to conform to expectations.

Participants will be affected by: (i) their surroundings; (ii) the researcher’s characteristics; (iii) the researcher’s behavior (e.g., non-verbal communication), and (iv) their interpretation of what is going on in the situation.

Experimenters should attempt to minimize these factors by keeping the environment as natural as possible and carefully following standardized procedures. Finally, perhaps different experimenters should be used to see if they obtain similar results.

Suppose we wanted to measure the effects of Alcohol (IV) on driving ability (DV). We would have to ensure that extraneous variables did not affect the results. These variables could include the following:

  • Familiarity with the car: Some people may drive better because they have driven this make of car before.
  • Familiarity with the test: Some people may do better than others because they know what to expect on the test.
  • Used to drinking: The effects of alcohol on some people may be less than on others because they are used to drinking.
  • Full stomach: The effect of alcohol on some subjects may be less than on others because they have just had a big meal.

If these extraneous variables are not controlled, they may become confounding variables because they could go on to affect the results of the experiment.

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Olivia Guy-Evans, MSc

BSc (Hons) Psychology, MSc Psychology of Education

Associate Editor for Simply Psychology

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.


Saul Mcleod, PhD

Educator, Researcher

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.