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What is an extraneous variable?

Last updated

6 February 2023


Dovetail Editorial Team

Reviewed by

Cathy Heath

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A variable in research is a characteristic, number, or quantity that may assume different values. Variables may be:

  • Dependent

  • Independent

  • Intervening

  • Moderating

  • Quantitative

  • Qualitative

  • Composite

  • Confounding

  • Extraneous

An extraneous variable is any variable not being investigated that has the potential to affect the outcome of a research study. In other words, it is any factor not considered an independent variable that can affect the dependent variables or controlled conditions.

For example, in a study of physical performance (independent variable), the effect of a specific athletic shoe (dependent variable) may be tested. Extraneous variables in this example might include:

  • Demographics such as age and gender

  • Testing environment

  • Time of day of testing

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Why do extraneous variables matter?

Extraneous variables provide alternative explanations for test results. Because of this, they can affect and threaten the internal validity of a study.

When not accounted for, extraneous variables often introduce selection biases to research, such as:

  • Attrition bias: the unequal loss of participants from a study group when those participants who drop out of the study are systematically different from those who stay.

  • Nonresponsive bias: when participants who do not respond to a survey are significantly different from those who do respond.

  • Ascertainment, or sampling, bias: when certain members of the intended population are less likely to be included than others.

  • Undercoverage bias: when some members of the population are not represented in the sample.

  • Survivorship bias: when conclusions are drawn by focusing only on examples of successful individuals (survivors) rather than the entire group. 

Extraneous variables matter because of the effect they can have on the outcome of a study.

Extraneous vs. confounding variables

An extraneous variable is anything that could influence the dependent variable. A confounding variable is an extraneous variable associated with both independent and dependent variables. The confounding variable influences the dependent variable and correlates with the independent variable.

In a conceptual framework diagram, the confounding variable is connected by an arrow to both the independent and dependent variables. Extraneous variables are only connected to a dependent variable.

How extraneous variables work

Uncontrolled extraneous variables make it hard to determine the exact effects of the independent variable on the dependent variable, because they may mask them. They can also make it seem as though there is a true effect of the independent variable in the experiment when there is none.

Types of extraneous variables

Extraneous variables are categorized into four major types. These categories help researchers to select the best methods of control for their research.

Experimenter effects

Unintentional actions by researchers that influence study outcomes are called experimenter effects. These include experimenters' interactions with study participants that can unintentionally affect their behaviors and cause errors in measurement, analysis, observation, or interpretation that might change the study results. Examples include:

  • Speaking in a positive or negative tone while providing experiment instructions

  • Using certain phrasing to hint at how experimenters want participants to behave

The experimenter must maintain an unbiased presence for test results to be valid.

Situational variables

Variables that can alter participants' behaviors in study environments, such as temperature or lighting, are called situational variables. Factors such as these are the sources of random variation, or random errors, in measurements.

The effect of situational variables must be eliminated or reduced to understand the true relationship between independent and dependent variables.

Participant variables

Participant variables are characteristics or aspects of a study participant's background that could affect study results. Examples of participant variables are:

  • Gender identity

  • Sex

  • Age

  • Marital status

  • Religious affiliation

  • Education

Because these differences can lead to different outcomes, it's important to measure and analyze these variables.

Demand characteristics

Demand characteristics are cues that encourage participants to conform to researchers' behavioral expectations. These occur when study subjects infer the intentions of a research study from the materials or research setting and use these hints to act in ways consistent with research hypotheses.

Demand characteristics can bias study outcomes and reduce the external validity of the results.

How to control extraneous variables

An important aspect of experimental design is the control of extraneous variables.

Standardized procedures

  • One way to avoid experimenter effects is to implement masking to hide the hypothesis from the participants and the researchers. In such a double-blind study, researchers cannot bias participants towards acting in expected ways or selectively interpret results to suit the hypothesis.

  • Keeping the variables constant throughout the study or statistically accounting for them in analyses is the best way to avoid situational variables from influencing study outcomes.

  • To avoid demand characteristics, researchers might try making it difficult for participants to guess the aim of the study. Asking participants to perform unrelated filler tasks or fill out plausibly relevant surveys can lead them away from the true nature of the study.

Random assignment

Randomly assigning the participants to control and experimental groups will prevent participant variables. This makes groups comparable by evenly distributing participant characteristics between them.

Controlling an extraneous variable turns it into a control variable.


Extraneous variables introduce research bias to a study. When left uncontrolled, they might lead to inaccurate conclusions about the relationship between independent and dependent variables.


What are some examples of extraneous variables?

In a study researching whether memory capacity is related to test performance, extraneous variables might include:

  • The time of day the test is taken

  • Test anxiety experienced by participants

  • The level of stress caused by the test

Researching whether sleep deprivation affects driving ability could have extraneous variables such as:

  • Years of driving experience

  • Road conditions

  • Noise levels in the vehicle

What is the difference between independent and extraneous variables?

Independent variables are controllable variables. They are changed or varied during a study to influence the dependent variable. The independent variable is the feature, attribute, or factor manipulated by the researcher so that its effect on the dependent variables can be measured.

Extraneous variables also affect the dependent variable, but the researcher cannot manipulate these. They are uncontrolled variables that present themselves during a study and provide alternative explanations for the test results.

What extraneous variables can arise from a telephone survey method?

In the telephone survey method of conducting research, extraneous variables might include:

  • Background noise

  • Distractions, such as a television or other people in the room

  • Integrity of the telephone connection

  • The interviewee's ability to hear and understand questions

These extraneous variables can influence the validity of study results.

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