Key Difference – Causal vs Correlational Research
Causal and correlational research are two types of research, and while some may consider them similar in nature, they have a clear difference between them. Causal research is aimed at identifying the causal relationships among variables, whereas correlational research is aimed at identifying whether an association exists or not. The key difference between causal and correlational research is that while causal research can predict causality, correlational research cannot.
Key Takeaways
- Causal research aims at identifying causality among variables, allowing the researcher to find the cause of a certain variable.
- Correlational research attempts to identify associations among variables, but cannot predict causality.
- In causal research, the researcher manipulates the environment, while in correlational research, the researcher does not manipulate the environment.
What is Causal Research?
Causal research aims at identifying causality among variables. This highlights that it allows the researcher to find the cause of a certain variable. For instance, a researcher who studies why there is less participation of women in politics will attempt to find variables that cause this situation, such as family responsibilities, the image of the woman, dangers associated, etc. In causal research, the researcher usually measures the impact each variable has before predicting the causality. It is essential to pay attention to the variables because, in most cases, the lack of control over variables can lead to false predictions. This is why most researchers manipulate the research environment. In the social sciences especially, it is very difficult to conduct causal research because the environment can consist of many variables that influence the causality that can go unnoticed.
What is Correlational Research?
The correlational research attempts to identify associations among variables. The key difference between correlational research and causal research is that correlational research cannot predict causality, although it can identify associations. However, it is essential to stress that the researcher tries to comprehend the variables as separate entities and the association of variables. Another difference that can be highlighted between the two research methods is that, in correlational research, the researcher does not attempt to manipulate the variables. He merely observes. For example, a researcher studying aggressive child behavior will notice that the family plays a key role in shaping the child’s behavior. He will also identify from the data gathered that children from broken families display a higher level of aggression compared to others. In this case, the researcher notices an association between variables (level of aggression and broken families). Although he notices this connection, he cannot predict that broken homes act as a cause for the higher level of aggression.
What is the Difference Between Causal and Correlational Research?
Definitions of Causal and Correlational Research:
Causal research: Causal research aims at identifying causality among variables.
Correlational research: Correlational research attempts to identify associations among variables.
Characteristics of Causal and Correlational Research:
Nature:
Causal research: In causal research, the researcher identifies the cause and effect.
Correlational research: In correlational research, the researcher identifies an association.
Manipulation:
Causal research: In causal research, the researcher manipulates the environment.
Correlational research: In correlational research, the researcher does not manipulate the environment.
Causality:
Causal research: Causal research can identify causality.
Correlational research: Correlational research cannot identify causality among variables.
