A between-subjects experiment is an experimental design approach wherein each participant is exposed to only a single level of the independent variable. This method differs fundamentally from within-subjects designs, as individuals are tested in just one specific condition rather than across all experimental variations.

Between-Subjects Experiment

In an experiment testing the effect of expressive writing on physical health, researchers must manage multiple extraneous variables. Participant variables (individual differences) like baseline writing ability, gender, and diet can independently affect health. Furthermore, situational and task variables, such as the weather, the time of day, and whether participants type or write by hand, can introduce unintended variability. Holding these factors constant is necessary to separate the actual impact of expressive writing from the influence of these outside variables.

Example of Extraneous Variables: Expressive Writing Experiment

A non-manipulated independent variable is a factor in an empirical study that the researcher measures but does not actively manipulate or alter. These are frequently participant variables—such as gender, self-esteem, or hypochondriasis—which naturally function as between-subjects factors because an individual can only be tested in one condition of their pre-existing trait. A study incorporating these factors is still classified as an experiment provided that at least one other independent variable is actively manipulated.

Non-Manipulated Independent Variable

Private body consciousness is a participant variable representing a heightened awareness of one's own physical body. In empirical research, it is typically treated as a non-manipulated independent variable because it is a pre-existing characteristic that researchers simply measure, rather than actively manipulate or assign to conditions.

Private Body Consciousness

What is a participant variable in the context of an experiment?

A participant variable, also known as an individual difference, is a type of extraneous variable derived from the pre-existing characteristics of the individuals involved in an experiment. Examples of these variables include demographic factors such as gender, as well as personal attributes or habits like diet and writing ability. Because these individual differences are likely to have their own independent effect on the dependent variable, they must be controlled to prevent them from obscuring the effect of the experimental manipulation.

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In experimental research, an extraneous variable is any factor that varies within the context of a study other than the specific independent and dependent variables being investigated. These variables pose a significant problem because many of them are likely to influence the dependent variable. If these outside factors fluctuate, they introduce competing influences that make it difficult to separate the true effect of the independent variable from the effects of the extraneous variables.

Extraneous Variable

A variable is any quantity, quality, or characteristic that can change or vary across different individuals, situations, or over time. In psychological research, some variables are straightforward and simple to measure, such as age or height, while others are more complex and require careful operational definition to be studied empirically.

Variable

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Participant Variable

A situational variable is a type of extraneous variable that involves the broader environmental or contextual conditions present during an experiment, such as the time of day, weather, or physical setting. Since these external factors can unintentionally influence participants' behavior and the dependent variable, researchers must rigorously control them to isolate the true effect of the independent variable.

Situational Variable

A task variable is a specific type of extraneous variable relating to the mechanics, materials, or procedures of the activity participants are asked to complete during a study. For example, whether a participant completes a task by hand or on a computer is a task variable. Because variations in how a task is administered can independently affect the dependent variable, they must be held constant.

Task Variable

Experimental control is the fundamental process by which researchers hold extraneous variables constant throughout a study. Because extraneous factors—such as individual participant differences or situational contexts—are likely to have an unintended effect on the dependent variable, they make it difficult to separate their impact from the true effect of the manipulated independent variable. By actively controlling these outside variables and preventing them from fluctuating across conditions, researchers can isolate the independent variable and confidently attribute any changes in the dependent variable to the experimental manipulation.

Experimental Control

The biological sex of a researcher can act as an extraneous variable by unintentionally influencing participant behavior. Because male and female experimenters often interact differently with subjects—and subjects respond differently to them—this variation can confound study results. For instance, in a pain perception study by Ibolya, Brake, and Voss (2004), participants immersed their hands in icy water longer when the experimenter was of the opposite sex, demonstrating that researcher characteristics must be controlled to prevent noise in the data.

Experimenter's Sex as an Extraneous Variable

Standardizing the procedure is the process of minimizing unintended variation by conducting an experiment in the exact same way for all participants, regardless of their assigned condition. This consistency prevents extraneous variables, such as experimenter demeanor, from systematically affecting the results and creating confounds. Common standardization techniques include using written protocols, delivering standard or automated instructions, anticipating participant questions in advance, training multiple experimenters together, and ensuring each experimenter tests participants in all conditions.

Standardizing the Procedure

The experimenter expectancy effect occurs when a researcher's own expectations or beliefs about a study's outcome inadvertently bias the participants' behaviors in unintended ways. These subtle influences during the administration of a measure can systematically alter participant responses and compromise the study's validity.

Experimenter Expectancy Effect

A confounding variable is an extraneous variable that differs on average across levels of the independent variable, meaning it varies systematically alongside it. Because this variable differs systematically across conditions just like the independent variable, it provides a plausible alternative explanation for any observed difference in the dependent variable, making it difficult to establish a clear cause-and-effect relationship. For instance, if an extraneous variable like intelligence is substantially lower in one group than another, it becomes a confounder that confuses the results.

Confounding Variable

Internal validity indicates the degree to which an empirical study's design justifies the conclusion that changes in the independent variable directly caused the observed differences in the dependent variable. Experimental research designs typically achieve high internal validity because they involve deliberately manipulating an independent variable while rigorously controlling for extraneous variables, thereby eliminating alternative causal explanations. For instance, in the Darley and Latané experiment, the rigorous manipulation of the number of perceived bystanders isolated this independent variable as the direct cause of differences in helping behavior. In contrast, non-experimental correlational designs exhibit low internal validity; for example, a statistical relationship between regular exercise and happiness cannot confirm that exercise causes happiness, as other factors or reverse causation might explain the link.

Internal Validity

In the context of an experiment, what is an extraneous variable?

A constant is a property or quantity that does not vary across individuals or situations, such as the speed of light. Because constants do not change, they are not the focus of psychological research questions, which instead seek to understand phenomena that vary.

Constant

A quantitative variable is a type of variable that represents a measurable quantity, typically assessed by assigning a numerical value to each individual. Common examples in psychological research include a person's height, level of talkativeness, number of siblings, or score on a depression scale.

Quantitative Variable

A categorical variable is a type of variable that represents a characteristic or quality, typically assessed by assigning a descriptive category label to each individual rather than a number. Examples include a person's chosen major, nationality, occupation, or whether they are receiving psychotherapy.

Categorical Variable

An abstract construct, also referred to as an intangible variable, is a psychological characteristic or internal state that cannot be directly observed, such as self-esteem, mood, or a behavioral intention. Because psychological research relies on empirical data, researchers must develop specific methods to transform these intangible concepts into quantifiable variables so they can be measured and studied.

Abstract Construct

In experimental research, an independent variable is the presumed cause in a cause-and-effect relationship. It is the specific factor that a researcher systematically manipulates or varies to observe its impact on another variable. While experiments require manipulation, in some non-experimental or factorial designs, an independent variable may simply be measured.

Independent Variable

A dependent variable is the factor in an experiment that represents the presumed effect within a causal relationship. It is the variable that researchers measure to evaluate if it changes as a direct result of the manipulation of the independent variable.

Dependent Variable

In research, a population is the entire group of individuals that the researchers seek to draw conclusions about based on their findings from the sample. 

Population

In research, a population is the entire, often very large, group of individuals that researchers are interested in studying and drawing conclusions about. Depending on the researcher's goals, a population could be as broad as all human beings or as specific as all American teenagers, children with autism, or professional athletes.

To illustrate how quantities and qualities can vary across individuals or situations, consider the students enrolled in a university course. The physical height of these students serves as a clear example of a variable because it differs from one individual to another. Similarly, their chosen major is also a variable, provided that the class consists of students who have declared different fields of study. These illustrations demonstrate how commonly variations occur in the world.

Example of a Variable: Height and Chosen Major

Non-experimental research is a broad category of research methodologies defined by the lack of manipulation of an independent variable. Instead of controlling factors, researchers simply measure variables as they naturally occur in real-world or laboratory settings. Although experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, non-experimental research generally cannot. Despite this inability to draw causal conclusions, non-experimental research is still considered extremely important and is utilized in cases where experimental research cannot be carried out.

Non-Experimental Research

The distribution of a variable describes how individual scores or values are spread across the different levels or categories of that specific variable within a dataset.

Variable Distribution

In psychology, a construct is a complex variable that defies direct observation or straightforward measurement—such as an attitude, ability, personality trait, or emotional state. These variables cannot be seen directly because they represent broad behavioral tendencies rather than isolated actions, and they involve hidden internal processes like specific feelings, thoughts, and nervous system activities. Ultimately, a construct acts as a theoretical summary that encapsulates these intricate sets of internal and external processes.

Psychological Construct

Measurement is the process of systematically assigning scores to individuals or objects so that these scores accurately represent a specific characteristic of interest. Crucially, this broad concept does not limit measurement to the use of specific physical instruments or tools; rather, it requires any methodical procedure that yields a representative score.

Measurement

An operational definition defines a psychological variable in terms of the exact procedures used to measure or observe it. Because most variables are abstract constructs that cannot be directly observed (e.g., stress), researchers must transform these conceptual definitions into concrete, quantifiable forms. For instance, stress could be operationally defined as a score on a standardized questionnaire, the concentration of cortisol in saliva, or the number of recent stressful life events experienced.

Operational Definition

Psychological measurement is the systematic empirical process of quantifying abstract variables and constructs—such as moods, self-esteem, or behavioral intentions—to facilitate scientific analysis. By utilizing standardized tools and methodologies, researchers can translate intangible psychological characteristics into objective, numerical data that can be rigorously evaluated and studied.

Psychological Measurement

The distribution of a variable describes how scores or values are spread out across the different levels or categories of that specific variable.

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