In the methodology of academic research, addressing extraneous variables is crucial to maintain the integrity and validity of your study. These are variables that you do not intentionally study but may inadvertently affect the outcome of your experiment or research. Mastering the identification and control of extraneous variables ensures a more accurate and reliable result in your academic work. Check our guide to deepen your understanding of extraneous variables and their impact on your research findings.
Definition: Extraneous variable
An extraneous variable in an experiment is any variable that is not being investigated but has the potential to influence the results of the experiment.
Uncontrolled extraneous variables can result in erroneous conclusions on the link between the independent and dependent variables.
Use of extraneous variables
Extraneous variables might compromise the internal validity of a study by presenting alternative interpretations of the outcomes.
In an experiment, one manipulates an independent variable to examine its influence on a dependent variable.
In an experiment, uncontrolled extraneous variables might also make it appear as if the independent variable has a fundamental influence when, in fact, none exists.
If these variables consistently differ between groups, you cannot be sure whether your results are due to the manipulation of the independent variable or to the extraneous variables.
Controlling extraneous variables is a crucial component of experimental design. When an extraneous variable is controlled, it becomes a control variable.
Extraneous variables vs. confounding variables
Confounding variables are extraneous variables that are connected to both the independent and dependent variables:
- Extraneous variables may be any variable that potentially affects the dependent variable.
- Confounding variables affect the dependent variable and correlate with or have a causal effect on the independent variable.
Extraneous Variables – Types and controls
There are four known types of extraneous variables:
Demand characteristics serve as cues that urge participants to comply with the researcher’s behavioral expectations. Experiment settings and study materials can often give away the research study’s purpose to participants.
The participants can then use these cues to engage in behavior that is relevant to and consistent with the study’s hypothesis. This may introduce bias into the research’s findings and reduce the generalizability of those findings to the population.
Experimenter effects are unintended behaviors performed by researchers that can alter the results of a study.
There are two categories of experimenter effects:
- Interactions between experimenters and subjects can unintentionally influence their behaviors.
- The study results may be affected by measurement, observation, analytical, or interpretation errors.
Situational variables, like lighting and temperature, can affect the behavior of participants in a study. These variables are causes of random error or fluctuation in your measurements.
You must limit or remove the influence of situational factors on your study outcomes to ascertain the actual relationship between independent and dependent variables.
This is an attribute or aspect of the participant’s background that can influence the research outcomes, even when not in the experiment’s best interest.
These variables consist of gender, religion, age, level of education, and marital status. Since these variances can result in varied outcomes for the research participants, it is necessary first to assess them.
An extraneous variable is a variable that isn’t part of your investigation, but may have an impact on your study’s dependent variable.
A confounding variable is an extraneous variable that not only impacts the dependent variable, but is also associated with the independent variable.
There are four primary categories of extraneous variables:
- Demand characteristics: contextual cues that motivate participants to comply with researchers’ expectations.
- Experimenter effects: unintended researcher behaviors that alter study outcomes.
- Situational variables: environmental characteristics that impact participants’ behaviors.
- Participant variables: any attribute or aspect of a participant’s background that may influence study outcomes.
Control factors assist in establishing a correlational or causal relationship between variables by bolstering internal validity.
Suppose you do not control relevant extraneous variables. In that case, they may impact the results of your study, and you may be unable to establish that the results are indeed the result of your independent variable.