Which research design is best suited for examining the relationships among multiple variables?

Correlational design is particularly well-suited for examining the relationships among multiple variables because it allows researchers to assess the degree and direction of association between these variables without manipulating them. This type of design is valuable in situations where experimentation may not be ethical or feasible, enabling a better understanding of how variables interact in natural settings.

In a correlational study, researchers can analyze data from surveys or observational studies to explore patterns and correlations. This can help identify potential relationships, such as whether increased stress levels are associated with sleep disturbances, or how various demographic factors influence mental health outcomes.

The other research designs have different focuses and limitations. For instance, experimental design is primarily concerned with establishing cause-and-effect relationships by manipulating an independent variable and observing its effects on a dependent variable. Case study design involves an in-depth analysis of a single individual or group, which limits its ability to generalize findings across multiple variables. Qualitative design emphasizes understanding experiences and perspectives, often through interviews or focus groups, but does not typically focus on quantifying relationships among multiple variables in the way that correlational design does.