Question

Discuss correlational and experimental research. Provide an example of each. In your discussion, include an explanation of why correlational research is sometimes preferred over experimental research. Then, explain what the value of a correlation indicates.

Answer 1

Correlational research attempts to determine the nature and extent of the relationship between two variables. In other words, it measures whether and how two variables are associated with each other. For instance, a study may examine if students who attend class regularly perform well in their examinations by comparing their attendance records to their examination marks. This is an example of a correlational research because the main question is find if class attendance is positively linked to examination performance.

On the other hand, an experimental research aims to establish a causal relationship, that is, to find if one particular variable causes the occurrence of another variable. For instance, a researcher may attempt to understand if the practice of yoga leads to better performance in examinations. This may be carried out by forming two groups, those who are made to attend yoga sessions and those who are not and then comparing their academic performance. If a significant difference is found between the two groups, the researcher can conclude that yoga leads to improved exam performance.

Correlational research is sometimes preferred over experimental research because experiments are often resource-extensive and time-consuming. Also, experiments tend to have lower levels of external validity (the generalizability of the results) as they take place under very controlled settings.

The value of a correlation is expressed from -1 to 1, wherein -1 indicates a negative correction (the increase of 1 variable is associated with the corresponding decrease of the other variable) while 1 indicates a positive correlation (wherein if 1 variable increases or decreases, the other variable also increases or decreases, respectively). A value of 0 indicates no relationship betwen the variables.