Dependent and independent variable: what they are, with examples

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 security and veracity of the pre-existing

And to investigate something we must take into account that in any experiment it is necessary to 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 a phenomenon that interests us occurs or why it appears study.

So the variables are elements of reality that we can define in a specific and predictable way to the point that we find repeated several times in nature or in society what it refers to. For example, sex is a variable, and what it indicates is reflected in the majority of human beings we observe, with very few situations presenting 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 see each of them throughout this article.

Basic definition of independent variable

An independent variable is defined as any variable that is put to the test at an experimental level, being manipulated by the 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 the 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 they go through more than one) or the groups that will go through different experimental conditions. In these cases we could speak of intrasubjects or intersubjects independent variables respectively.

The independent variable sIt is named like this precisely because its values ​​will not 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 music 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. These are the 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, given certain conditions (controlled by using the dependent variables).

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

Of course, it must be considered that not all investigations in which dependent and independent variables are used express causal relationships. That is, 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, it does not mean that the cause of this last change was the manipulation of the variable independent. 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 their intention to vote yields a different result than asking about their intention vote to those who have university studies, this does not have to mean that the independent variable "education level" 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 studies, such as the lack of financial resources.

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Details about 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 one independent variable and one independent. In general, it is usually recommended that at least with regard to the independent variable we only use one at a time, since the greater the number of independents, 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 independent intergroup variable, which would be type of group (group of subjects with drug and group of control subjects, of face to see if there are significant differences) and an intra-group 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 variable is going to be the same and it should always be checked if there is an effect of each one of the variables. independent on the dependent ones (and not only of each of the independent ones but also of whether the interaction between them has an effect on the dependent ones). This can be assessed through different types of design, such as the ANOVA.

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

For example, a person's Body Mass Index can be an independent variable if it is used to assess whether this 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 variable and an independent variable.

A first case could be a study aimed at analyze the level of alteration of the heart rate generated by exposure 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 lifestyle/physical activity levels on body mass index, being the BMI the dependent variable and the levels of physical activity the independent.

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.