Dependent and independent variable: what are they, with examples?
What is a dependent variable and an independent variable? Let's see how they are used in science.
The independent variable and the dependent variable form two of the most well-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; they also help us 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 their role in science and in the use of statistical tools. and in the use of statistical tools.
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 features or characteristics that can vary by adopting different values or categories, and whose variation can provide us with clues about how a phenomenon we are interested in studying occurs or why it appears.
Variables are, then, 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 most of the human beings we observe, with very few situations presenting ambiguity.
At the operational level, whenever we work experimentally, we work with two main types of variables: dependent and independent variables.. Let us look at each of them throughout this article.
Basic definition of independent variable
An independent variable is defined as any variable that is tested experimentally, being manipulated by researchers in order to test a hypothesis. It is a property, quality, characteristic or aptitude with the power to affect the rest of the variables, being able to alter or mark the experimental results.and can alter or mark the behavior of the rest of the variables.
Thus, the different values of this variable will be fundamental for designing and interpreting the results of the experiment, since it can explain them.
For example, it 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 intrasubject or intersubject independent variables respectively.
The independent variable isis so called precisely because its values will not be altered by the other variables in the experiment itself.. Sex or age are some variables that are usually independent, since they do not change depending on a few variables. However, 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 research, the favorite musical genre may be the dependent variable, and in another it may be the independent variable.
Dependent variable: concept
With regard to the dependent variable, we are talking about the quality or characteristic whose behavior is affected by the independent variable. 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 or how it changes under certain conditions (controlled by the use of the dependent variables).
In this way we are dealing with the type of variable that we analyze in the experiment or investigation, assessing how it behaves according to the values of the independent variable. If the independent variable is the cause, we could consider that the dependent variable is the effect that we measure of the fact of having manipulated the first one.
However, it is important to consider that not all research using dependent and independent variables expresses causal relationships.. That is, the fact that by changing the value of the independent variable the value of the dependent variable also changes following a more or less predictable pattern does not mean that the cause of the latter change was the manipulation of the independent variable. Especially in the social sciences, this type of phenomena can express a simple correlation effect.
For example, if asking about voting intention to those who have less education yields a different result than asking about voting intention to those who have university studies, this does not necessarily 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 voting intention and the low level of studies, such as, for example, the lack of economic resources.
Details on their use in research
The division between dependent and independent variable is a basic element that is part of any research to be carried out. But the number of variables to be taken into account, as well as the type of experimental design and what you intend to actually analyze, can vary greatly.
For example, a simple design may only require the use of one independent variable and one independent variable.. In general, it is usually advisable to use at least one independent variable at a time, since the greater the number of independent variables, the greater the complexity of the experiment and the possibility of causing a 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 intragroup one, which would be the time of treatment (pretreatment, 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 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 ones (and not only of each of the independent variables but also whether the interaction between them has an effect on the dependent ones). This can be assessed by means of different types of design, such as ANOVA, for example..
Another aspect to bear in mind is that depending on what is to be investigated and how the research is 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 it affects some other variable, or it can be a dependent variable if we assess that the BMI itself may depend on another variable. Thus, it is 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 us 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 the level of alteration in Heart rate generated by exposure to different levels of altitude in people with acrophobia. 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 may have on patients' self-evaluation. The type of language could be an independent variable, and the results in the self-esteem questionnaires could be the dependent variable.
A third example could be an investigation that analyzes the effect of levels of sedentariness on self-esteem. the effect of sedentary/physical activity levels on body mass index (BMI), with BMI as the dependent variable.with BMI as the dependent variable and physical activity levels as the independent variable.
A fourth and final example can be found in a study that assesses how positive affect affects levels of life satisfaction. Levels of positive affect would be the independent variable, and the dependent variable would be levels of life satisfaction.
(Updated at Mar 28 / 2023)