The purpose of correlational studies is to describe the association between variables and establish how strong a relationship is. Although they do not establish causality, they are essential in research. Researchers use them as a preliminary means of gathering information about a specific topic. This approach is vital in situations where researchers cannot conduct experiments. For example, a researcher can use a correlational study when it is impossible to influence or alter the independent variable due to various reasons, such as ethical matters. Also, correlations are used to identify if any relationship exists between multiple variables. However, researchers cannot influence the variables involved. Although correlation studies can show a relationship exists between variables, they do not provide evidence that a change in one variable leads to change in the other.
Despite the many problems experienced in analyzing correlation data, researchers use the study design if they doubt that an identified statistical relationship is causal or not. Also, they apply it when they do not need to determine a causal relationship. The primary aims of science are to make a prediction and describe. Correlational studies help researchers to achieve these two aims. If a relationship exists between variables, the scores of one can be used to predict the scores for the other one. Also, correlation is vital in determining if measurements are reliable and valid. For example, the validity of an extraversion test can be determined by administering it to a group of individuals alongside an already validated test. The researchers involved can determine if the scores on the short test have a solid correlation with the ones recorded on the valid one. In this case, an independent variable to alter does not exist. Therefore, although correlations are regarded as less valuable because they cannot determine causality, they are vital in research.
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