Correlational Research

We explain what correlational research is and what it consists of, with its characteristics and the different types of variables. Also, how to do it and examples.

diagram that relates two variables
Correlational research allows us to make predictions and evaluate relationships between variables.

What is correlational research?

Correlational research is one that aims to measure the degree of relationship that exists between two or more variables in a particular case. It is a type of study based on observation and non-experimental analysis, and seeks to establish whether there is an association between the variables. If there is one, also analyze the direction and strength of said relationship.

This type of research is especially important for study relationships in situations where manipulation of variables is not possible or ethical. It allows projecting the behavior of a phenomenon based on the behavior of one or other related variables. For this reason, it is widely used in fields such as medicine, psychology, natural sciences, economics and education, where it is not appropriate to experiment with real subjects.

Unlike descriptive research, which is dedicated to characterizing in detail each of the individual variables of a phenomenon, correlational studies evaluate the relationship between the different aspects of the object analyzed. In this way, they provide fundamental knowledge that can serve as a starting point for deeper investigations, aimed at demonstrating the causes and consequences of a phenomenon.

Furthermore, in many fields, correlational research allows useful predictions to be made and the relationship between factors in complex settings to be evaluated, providing a solid basis for informed decision-making and policy development.

Characteristics of correlational research

Among the main characteristics of correlational research are:

  • Observation of variables Study a phenomenon by observing the variables as they occur in reality. The researcher does not interfere or manipulate the variables analyzed.
  • Relationship measurement. It is dedicated to identifying and measuring the relationships that may exist between two or more variables of a phenomenon.
  • Mathematical tools The analyzes use correlation coefficients, which indicate the direction (positive or negative) and strength of the relationship between variables.
  • Non-experimental scenarios. It is especially useful in situations where conducting experiments is not feasible.
  • Versatility of contexts. It can be applied in a wide variety of contexts and disciplines, from social sciences to natural sciences and economics.

Types of variables in correlational research

Correlational research can find different relationships between the variables studied. Among them, the most important types are:

  • Positive correlation. As one variable increases, the other does too. For example, a positive correlation could be found between the number of hours of study and academic grades: generally, the more hours of study, the better the grades.
  • Negative correlation As one variable increases, the other decreases. An example could be the relationship between the amount of time spent watching television and academic performance: the more hours spent watching television, the more academic performance decreases.
  • Null correlation. There is no significant relationship between the variables studied, that is, changes in one variable are not associated with changes in the other. An example might be the relationship between a person's height and their preference for a certain type of music: these variables are not expected to be related.
  • Linear correlation It refers to the relationship between two variables that can be represented graphically as a straight line. Both positive and negative correlations can be linear, if the change in one variable is proportional to the change in the other. An example could be the relationship between the outside temperature and the sale of ice cream: as the temperature increases, the sales of ice cream also increase proportionally.
  • Curvilinear correlation. It refers to the relationship between two variables that does not follow a straight line. This indicates that the change in one variable is not proportional to the change in the other. For example, there could be a curvilinear correlation between stress and performance: a moderate level of stress could improve performance, but a very high or very low level could reduce it.
  • Partial correlation It measures the relationship between two variables while controlling or keeping a third variable constant, to avoid possible distortions. For example, the relationship between the level of education and the income of a population could be investigated by controlling the variable “age”. By holding age constant, a better understanding can be obtained of how education level affects income without the influence of this variable.
  • Multiple correlation It measures how a variable is related to a set of other variables simultaneously, that is, it investigates the relationship between more than two variables. This approach is common in complex investigations, where multiple factors may be interacting with each other. For example, one could analyze how academic performance (a variable) is related to the number of hours of study, the quality of sleep, and the level of family support. This research could show how these combined factors affect academic performance.
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See also: Types of hypotheses

How to do correlational research?

To do correlational research, a series of steps can be followed:

  1. Define the problem. Choose the topic, select the variables to be studied and formulate a specific question to answer through the research.
  2. Review the bibliography Search previous studies on the topic to understand the context and fundamental concepts, and identify what has not been studied or requires further research.
  3. Formulate hypotheses Pose a hypothesis that proposes a relationship between the variables to be analyzed.
  4. Design the investigation. Define the sample to be studied and the methodology to measure its variables.
  5. Collect data Carry out data collection through the instruments and methodology designed.
  6. Analyze the data. Sort the information and measure the data based on a correlation coefficient, which will define the direction, strength and type of relationship that exists between the different variables.
  7. Interpret the results Relate the results to the information from previous studies and reflect on the scope of the research itself.
  8. Document the investigation. Write a detailed report that describes the steps of the study, findings, limitations, and proposals for future research.

Advantages and disadvantages of correlational research

Among the main advantages and disadvantages of correlational research are:

Advantages Disadvantages
Aim Identify relationships and associations between variables without the need to carry out experiments. It does not establish causality, it only indicates how the variables are related.
Approach It allows exploring links between variables in natural and social contexts. It may lack depth in explaining the observed relationships.
Theoretical framework It builds on previous research and allows for a deeper understanding of the phenomena studied. It depends on prior knowledge, which can limit its ability to innovate analysis perspectives.
Applicability It allows developing knowledge about phenomena on which experiments cannot be done. It may require deeper research to apply this knowledge to reality.
Collaboration of external actors Many institutions make investments to study phenomena of social or commercial interest. External collaborations may affect the interpretation of the results.
Social and economic relevance It can reveal important relationships for taking political, economic or social measures. The observed correlations may not always have practical or immediate application.

Examples of correlational research

Correlational research is a fundamental tool for science, since it allows us to explore and understand the relationships between variables without intervening in them. This approach is used across multiple disciplines to identify meaningful patterns and associations that help formulate hypotheses and guide future studies.

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Some examples of correlational research are:

  • The use of social networks and psychological well-being. One study found a correlation between the time people spend on social media and levels of psychological well-being. The results suggest that excessive use of social networks may be associated with higher levels of depression and anxiety.
  • Age and creativity. Research detected a curvilinear correlation between age and creativity levels. The results showed that creativity tends to be high in youth, decreases in middle age, and can increase again in old age.
  • Exposure to violence in the media and aggression in adolescents. One analysis examined the correlation between the violence that adolescents are exposed to in the media and their aggressive behavior. The study maintains that greater exposure to media violence is correlated with higher levels of aggressiveness in adolescents.
  • Performance at work and multiple variables. An analysis investigated the influence on job performance of variables such as satisfaction, support from managers, and work-life balance. The multiple correlation showed how these combined variables affect job performance.
  • Physical activity and psychological well-being One study looked at how physical activity is related to psychological well-being, controlling for the impact of diet and level of social support. The partial correlation revealed that physical activity has a positive correlation with psychological well-being, independently of the other two variables.

See also:

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References

  • Creswell, J. W. (2014). The Process of Conducting Research Using Quantitative and Qualitative Approaches. In Educational Research. Planning, Conducting and Evaluating Quantitative and Qualitative Research. Pearson.
  • Hernández Sampieri, R., Fernández Collado, C and Baptista Lucio, P. (1991). Definition of the type of research to be carried out. In Research methodology. McGraw-Hill.
  • Mora Ledesma, M and Sepúlveda, P. (1999). What is research? In Research methodology (pp. 97-108). Limusa.
  • Price, P.C., Jhangiani, R., and Chiang, I. (2015). Research Methods in Psychology. Open Educational Resources.
  • Sabino, C. (1992). The research process. Panapo.