The 11 types of variables used in research

April 6, 2024

Age. Sex. Weight. Height. Occupation. Socioeconomic status Level of anxiety These and other elements must be taken into account when trying to explain some type of hypothesis with respect to the human being or some type of problem.

And is that in all that exists and happens around us involved innumerable types of variables that may have a more or less relevant role in the different phenomena that occur. It will be necessary to analyze and take into account which variables influence and how they do it if we want to obtain a generalizable explanation. It is something that all those dedicated to scientific research take into account, both in psychology and in the rest of sciences. In this article we are going to review what they are the main types of variables that exist .

Related article: "The 15 types of research (and features)"

What is a variable?

Before moving on to observe the different variable types, it may be convenient to make a brief review of what we consider as such in order to facilitate their identification and take into account their importance.

A variable is understood as an abstract construct that refers to a property, characteristic or element studied that may or may not have a specific role on what is being analyzed and that is presented in such a way that it may have different values. These values, then, can vary in different measures depending on the variable as well as the situation being analyzed or the limits that the researchers want to take into account. We are therefore faced with a concept that brings together the different options or modalities that can be taken into account with respect to a characteristic in question, said values being inconstant and different at different times and / or subjects .

The concept in question may seem complex to understand theoretically, but it is much more understandable if we think that some variables may be those cited in the introduction: the weight or sex of a person would be simple examples of variables that may or may not affect in different conditions (for example, in diabetes or heart disease).

The variables can be classified in very different ways and on the basis of numerous differentiated criteria, such as their level of operability, their relationship with other variables or even the scale at which they are measured. It is important to bear in mind that the same element can have different roles and be classified as different types of variable depending on its role in a given situation or experimental context.

Types of variables according to their operation

As we have mentioned, one of the most known and classic ways to divide and classify the different variables is in relation to their operability, that is, to the possibility of numeralizing their values and operating with them . Taking this aspect into account, we can find three major types of variables.

1. Qualitative variables

Qualitative variable is considered to be any variable that allows the expression and identification of a specific characteristic, but that does not allow to quantify them. This type of variable would only inform us of the existence or non-existence of said characteristic or the presence of alternatives. They are merely nominal, expressing equality and / or inequality. Sex or nationality would be examples of this. However, this does not mean that they can not be observed or that there are not highly relevant elements in the investigation.

Within the qualitative variables we can find different types.

Dichotomous qualitative variables

These are variables in which there are only two possible options . Being alive or dead is an example of this: it is not possible to be at the same time, in such a way that the presence of one of the values denies the other.

Qualitative polytomic variables

Those variables that admit the existence of multiple values, which as in the previous case they only allow an identification of a value and this excludes the rest without being able to be ordered or operate with said value. The color is an example.

2. Quasi-quantitative variables

These are variables with which it is not possible to perform mathematical operations, but which are more advanced than merely qualitative ones. They express a quality and at the same time allow to organize it and establish an order or hierarchy . An example of this is the level of studies, being able to determine if someone has more or less of said quality.

3. Quantitative variables

The quantitative variables are all those that, this time, allow the operationalization of their values. It is possible to assign different numbers to the values of the variable , being able to perform different mathematical procedures with them in such a way that different relationships can be established between their values.

In this type of variables we can find two large groups of great relevance, the continuous and discrete variables.

Discrete quantitative variables

This is the set of quantitative variables whose values do not admit intermediate values, it is not possible to obtain decimals in their measurement (although then means can be made that do include them). For example, it is not possible to have 2.5 children. They usually refer to variables that use ratio scales .

Continuous quantitative variables

We talk about this type of variable when its values are part of a continuum in which between two concrete values we can find different intermediate values. More often, we talk about variables that are measured on an interval scale .

According to its relation with other variables

It is also possible to determine different types of variables depending on how their values relate to those of others. In this sense, several types stand out, with the first two being particularly relevant. It is important to bear in mind that the same element can be a variable type and another depending on the type of relationship that is being measured and what is being modified. In addition, we must bear in mind that the role and type of variable in question is a function of what we are analyzing, regardless of the role that the variable actually occupies in the situation studied .

For example, if we are investigating the role of age in Alzheimer's, the age of the subject will be an independent variable while the presence or absence of tau protein and beta-amyloid plaques will be a dependent variable in our research (regardless of the role that have each variable in the disease).

1. Independent variables

Independent variables are understood as those variables that are taken into account at the time of the investigation and that may or may not be modified by the experimenter. It is the variable from which one starts to observe the effects that determines quality , characteristic or situation can have on different elements. Sex, age or level of anxiety base are examples of independent variable.

2. Dependent variables

The dependent variable refers to the element that is modified by the variation in the independent variable. On the research, the dependent variable will be chosen and generated from the independent . For example, if we measure the level of anxiety according to sex, gender will be independent variable whose modification will generate alterations in the dependent, in this case anxiety.

3. Moderating variables

We understand by moderating variables the set of variables that alter the existing relationship between dependent and independent variable . Example of this is given if we relate study hours with academic results, being moderating variables the emotional state or the intellectual capacity.

4. Strange variables

This label refers to all those variables that they have not been taken into account but they have an effect on the results obtained . They would be all that set of variables not controlled and taken into account in the studied situation, although it is possible to identify them after it or even during an experiment or invesigado context. They differ from the moderators in the fact that strangers are not taken into account, this not being the case of the moderators.

Types of variables according to scale

Another possible classification of variables can be made according to the scales and measures used. However, we must bear in mind that more than the variable we would be talking about the scale in question as a distinctive element. It is also necessary to take into account that as the level of operation of the scales used increases, new possibilities are added, in addition to those of the previous scales. Thus, a variable of reason also has the properties of the nominal, the ordinal and the interval. In this sense we can find the following types.

1. Nominal variable

We speak of nominal variables when the values that said variable can reach only allow us to distinguish the existence of a specific quality, without allowing these values to perform an ordering or mathematical operations with them. It is a type of qualitative variable.

2. Ordinal variable

Although it is not possible to operate with them, it is possible to establish an ordering among the different values. But nevertheless, This order does not allow the establishment of mathematical relationships between their values . These are basically qualitative variables. Examples of this are socioeconomic status or educational level.

3. Interval variable

In addition to the previous characteristics, the variables in interval scale allow establish numerical relationships among the variables, although generally these relations are limited to proportionality. There is no absolute zero or completely identifiable zero point, something that does not allow direct transformations of values in others. They measure ranges, more than concrete values, something that complicates their operation but helps to cover a large number of values.

4. Reason variable

The reason variables are measured in such a scale that it is possible to fully operationalize them, being able to carry out various transformations to the obtained results and establishing complex numerical relationships among them. There is a point of origin that supposes the total absence of what is measured .

Different ways of analyzing reality

Do not forget that the different types of variables are always a simplification of reality, a way to divide it into simple and easy to measure parameters isolating them from the rest of the components of nature or society.

Therefore, we can not limit ourselves to believe that knowing these variables is to fully understand what is happening. Taking a critical look at the results obtained from the studies of variables is necessary in order not to reach erroneous conclusions and not to close ourselves to more complete and realistic explanations of what is happening around us.

Bibliographic references:

Barnes, B. (1985): On science, Barcelona: Labor.
Latour, B. and Woolgar S. (1979/1986): Life in the laboratory. The construction of scientific facts, Madrid: Alianza Universidad.