Dependent and independent variable: what they are, with examples - psychology - 2023



The independent variable and the dependent variable They form two of the best known categories in the world of science and research in fields such as medicine, psychology, sociology, and other areas of knowledge.

They are not only fundamental concepts in conducting experiments; in addition, they help to understand how reality works from the analysis of isolated phenomena. In short, they allow us to reduce the complexity of what we study and focus on simple elements that can reveal scientific knowledge.

In this article we will see what the dependent and independent variables are, with several examples that help to understand its role in science and in the use of statistical tools.

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Dependent and independent variable: what are they?

In psychology, as in any other scientific discipline, research is essential to achieve the development of new techniques, methods, explanatory models and practical applications, or to improve or guarantee the safety and veracity of pre-existing ones.

And to investigate something we must bear in mind that in any experiment we must assess and manipulate different variables. Variables are traits or characteristics that can vary by adopting different values ​​or categories, and whose variation can provide us with clues about how it occurs or why a phenomenon appears that we are interested in studying.

The variables are thus elements of reality that we can define in a specific and predictable way to the point that we find what it refers to repeatedly in nature or in society. For example, sex is a variable, and what it indicates is reflected in most human beings we observe, with very few situations that present ambiguity.

At the operational level, whenever we work experimentally we will do so with two main types of them: dependent and independent variable. Let's look at each one of them throughout this article.

Basic definition of independent variable

An independent variable is defined as any variable that is tested at an experimental level, being manipulated by researchers in order to test a hypothesis. Is about a property, quality, characteristic or aptitude with the power to affect the rest of the variables, being able to alter or mark the behavior of the rest of variables.

Thus, the different values ​​of this variable will be essential to design and interpret the results of the experiment, since it can explain them.

For example, you can mark the different situations that the participants will go through during the experiment (if more than one pass) or the groups that will go through different experimental conditions. In these cases we could speak of independent variables within subjects or between subjects respectively.

The independent variable sIt is called this precisely because its values ​​are not going to be altered by the rest of the variables in the experiment itself. Sex or age are some variables that as a general rule tend to be independent, since they do not change depending on a few variables. Of course, we can use them to study other variables.

In any case, the variables are dependent or independent depending on the context in which we find ourselves. In one investigation, the favorite musical genre may be the dependent variable, and in another it may be the independent variable.

Dependent variable: concept

Regarding the dependent variable, we are talking about that quality or characteristic whose behavior is affected by the independent variable. It is the variable or variables that are measured in order to be able to interpret the results. In other words, it is what is being observed to see if it changes, or how it changes, if certain conditions are met (controlled by using the dependent variables).

In this way we are faced with the type of variable that we analyze in the experiment or investigation, assessing how it behaves based on the values ​​of the independent one. If the independent variable is the cause, we could consider that the dependent variable is the effect that we measure from having manipulated the first one.

Of course, you have to consider that not all investigations in which dependent and independent variables are used express causal relationships. In other words, the fact that by changing the value of the independent variable the value of the dependent also changes following a more or less predictable pattern, does not mean that the cause of this last change was the manipulation of the independent variable. Especially in Social Sciences, this type of phenomenon can express a simple correlation effect.

For example, if asking those with a lower educational level about the intention to vote gives a different result than asking those who have university studies about the intention to vote, this does not have to mean that the independent variable "level of studies "is the one that generates this variation; It is possible that there is another hidden variable that explains both the different intention to vote and the low level of education, such as the lack of financial resources.

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Details on its use in research

The division between dependent and independent variable is a basic element that is part of any investigation that is carried out. But the number of variables to take into account, as well as the type of experimental design and what is actually intended to be analyzed, can vary enormously.

For example, a simple design may require only the use of an independent variable and an independent variable. In general, it is recommended that at least with regard to the independent variable we only use one at a time, since the greater the number of independent variables, the greater the complexity of the experiment and the possibility of causing some measurement error.

However, if for example we want to assess the effects of a drug, it is more appropriate to assess different elements in the same experiment. We could have an intergroup independent variable, which would be the type of group (group of subjects with drug and group of control subjects, in order to see if there are significant differences) and an intra-group variable that would be the time of treatment (pre-treatment, post-treatment and follow-up).

Likewise, as dependent variables we could assess different aspects such as levels of depression, suicidal thoughts, eating patterns, libido, quantity and quality of sleep.

In any case, the relationship between the dependent and independent variables will be the same and it should always be checked whether there is an effect of each of the independent variables on the dependent variables (and not only of each of the independent variables, but also of whether the interaction between them has effect on dependents). This can be assessed through different types of design, such as ANOVA.

Another aspect to take into account is that depending on what is to be investigated and how the investigation is to be carried out, the same reality can be a dependent or independent variable.

For example, the Body Mass Index of a person can be an independent variable if it is used to assess whether it affects some other variable, or it can be a dependent variable if we assess that the same BMI may depend on another variable. Thus, it is rather the position from which we analyze the variable rather than the variable itself that makes it dependent or independent.

Examples of its use in science

By way of conclusion, let's look at a few examples of situations or investigations in which we can see a dependent and an independent variable.

A first case could be a study aimed at analyze the level of alteration of the heart rhythm generated by being exposed to different levels of altitude in people with acrophobia. In this case, the height to which the subject is exposed would be the independent variable, while the heart rate would be the dependent variable.

Another study could be to analyze the effects that the type of language used in self-esteem assessment instruments can have on the self-assessment of patients. The type of language could be an independent variable, and the results in the self-esteem questionnaires the dependent one.

A third example could be an investigation that analyzes the effect of sedentary / physical activity levels on body mass index, with BMI being the dependent variable and levels of physical activity the independent one.

A fourth and final example can be found in a study that assesses how positive affect affects levels of life satisfaction. The levels of positive affect would be the independent variable, and the dependent variable would be the levels of life satisfaction.