What Is an Extraneous Variable? Definition and Challenges

An extraneous variable is anything in a psychology experiment other than the independent and dependent variables. The variables can present challenges and introduce errors, so it is important for experiments to control these extraneous factors.

Extraneous variables are the hidden influencers in psychological research – any factors besides the independent and dependent variables that could affect an experiment’s results. When a researcher studies how background music impacts test performance (independent variable) by measuring test scores (dependent variable), factors like room temperature, time of day, or participants’ caffeine intake are all extraneous variables that could secretly sway the outcomes.

These unplanned variables can make it difficult to determine whether changes in test scores are truly due to the music or other factors. That’s why researchers carefully control extraneous variables, typically by keeping them constant across all experimental conditions. For instance, all participants would take the test at the same time of day, in the same room, with the same amount of pre-test preparation time.

In this article, we’ll explore the types of extraneous variables that can impact psychological research and examine proven strategies for controlling them.

How Extraneous Variables Work

Let’s look at a real-world example of extraneous variables in action:

A Test Anxiety Study

Suppose researchers want to study whether extra study time reduces test anxiety. In this experiment:

• Independent Variable: Amount of study time (what researchers control)
• Dependent Variable: Level of test anxiety (what researchers measure)

Potential Extraneous Variables

Several uncontrolled factors could affect students’ anxiety levels:

• Room temperature (too hot or cold could increase stress)
• Time of day (morning vs. afternoon alertness)
• Noise levels in the testing area
• Amount of sleep students got the night before
• Recent caffeine consumption

Controlling These Variables

To ensure valid results, researchers would need to:

1. Test all students at the same time of day
2. Use rooms with consistent temperature
3. Maintain identical noise conditions
4. Screen for sleep patterns and caffeine use

Without controlling these variables, researchers couldn’t be certain whether changes in anxiety levels were due to study time or these other factors.

Examples of Extraneous Variables

Let’s explore three real research scenarios and their potential extraneous variables:

Testing a New Math Teaching Method

Research Goal: Determine if a new teaching method improves math exam scores

Key Extraneous Variables:

• Students’ prior math knowledge
• Individual learning styles
• Math anxiety levels
• Time of day when lessons are taught
• Class size differences
• Teacher experience with the new method

Music’s Impact on Marathon Performance

Research Goal: Study whether fast-paced music improves marathon times

Key Extraneous Variables:

• Runners’ fitness levels
• Previous marathon experience
• Weather conditions
• Course difficulty
• Sleep quality before the race
• Nutrition and hydration status
• Running gear/shoes used
• Motivation levels

Sleep Deprivation and Driving

Research Goal: Measure how sleep deprivation affects driving ability

Key Extraneous Variables:

• Driving experience
• Individual sleep patterns
• Caffeine consumption
• Road conditions
• Time of day
• Vehicle type/familiarity
• Natural tolerance to sleep deprivation
• Stress levels

Each scenario shows how multiple external factors could influence the research outcomes, highlighting why careful experimental control is essential.

Controlling for an Extraneous Variable

There are two key methods that social scientists utilize to control for an extraneous variable:

Standardized Procedures

Standardized procedures involve making all aspects of an experiment identical with the exception of the independent variable. As much as possible, researchers will:

• Recruit participants the same way
• Conduct the experiments in the same setting
• Offer the same rewards for participation in the study
• Give participants the same explanations and give similar feedback once the experiment is over

Other standardized procedures might involve performing the experiment at the same time of day for each condition and ensuring the conditions in the lab are the same for participants in all conditions (same temperature, brightness, and noise levels).

Random Assignment

Random assignment means that all participants have an equal chance of being assigned to any of the experimental conditions. Using random assignment in an experiment helps reduce the likelihood that the personal characteristics of the participants themselves will have an influence over the independent variables.

For example, in our previous example looking at study time and test anxiety, the researcher would use random assignment to assign students to either the experimental condition or the control condition. This reduces the likelihood that students who are simply less anxious in general will be assigned to one group while more anxious students are assigned to another group.

Randomizing the assignment process ensures that all students have an equal chance of being assigned to either group.

Challenges With Extraneous Variables

Breckler, Olson, and Wiggins (2006) note that while the control of extraneous variables is fairly simple in many fields, but is much more difficult when it comes to the social sciences. Why? Fields such as the physical sciences allow a great deal of control over the materials that are being studied.

When it comes to social science, researchers often have very little control over extraneous variables that may ultimately have an impact on the outcome.

A social psychologist, for example, might be interested in looking at human behaviors as they naturally occur. This makes it very difficult to construct a setting that allows complete control over all extraneous variables yet still permits the participants to behave as freely and spontaneously as they would in a more naturalistic setting.

Kantowitz, Roediger, and Elmes (2009) also note that exercising control over extraneous variables becomes particularly important in cases where the independent variable produces a small effect on the dependent variable.

Holding these variables constant can be very challenging in research that occurs outside of the lab.

Because controlling for extraneous variables is more challenging in real-world settings, researchers also utilize statistical techniques to help control for these extraneous factors.

For example, analysis of covariance (ANOVA) is one statistical technique that can be utilized to reduce the impact of an extraneous variable.

Extraneous vs. Confounding Variables

A confounding variable is one type of extraneous variable. An extraneous variable is any variable that is not being studied but could still potentially impact the dependent variable. Confounding variables are things that are not measured but can affect both the independent and dependent variables.

Examples of confounding variables can include participant characteristics (such as age, gender, or personality traits), environmental variables (like the lighting, temperature, or distractions), and demand characteristics (which are clues about the purpose of an experiment).

Final Thoughts

Understanding and controlling extraneous variables is crucial for conducting reliable psychological research. While it’s impossible to eliminate every outside influence, researchers can significantly strengthen their findings by identifying potential extraneous variables early and implementing proper controls.

Whether it’s standardizing test conditions, randomly assigning participants to groups, or carefully screening for confounding factors, these methodological steps help ensure that any observed effects are truly due to the variables being studied rather than unwanted external influences.

By staying vigilant about extraneous variables, researchers can design more robust experiments and draw more confident conclusions about human behavior and mental processes. This attention to experimental control ultimately leads to more reliable and useful psychological research that can be applied in real-world settings.

Sources:

Breckler, S., Olson, J., & Wiggins, E. (2006). Social Psychology Alive. Belmont, CA: Wadsworth.

Kantowitz, B. H., Roediger, H. L., & Elmes, D. G. (2009). Experimental psychology. Belmont, CA: Wadsworth.

Pourhoseingholi, M. A., Baghestani, A. R., & Vahedi, M. (2012). How to control confounding effects by statistical analysis. Gastroenterology and hepatology from bed to bench, 5(2), 79–83. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017459/