What type of research focuses on collecting data to model cause-effect relationships?

Causal research is specifically designed to identify and understand the cause-effect relationships between variables. It focuses on determining whether a change in one variable (the independent variable) directly impacts another variable (the dependent variable). This type of research often involves controlled experiments or other methods that allow researchers to isolate variables and manipulate them in a way to observe the outcomes, thereby establishing a cause-and-effect link.

In contrast, exploratory research aims at gathering preliminary insights and understanding an issue or problem when there is little existing knowledge. It’s about exploring and generating ideas rather than determining specific relationships between variables.

In census studies, the goal is to collect comprehensive data from a whole population, which does not directly focus on establishing cause-effect relationships.

Descriptive research, while it can involve observational studies that lay groundwork for causal inquiries, primarily aims to describe characteristics or functions of a phenomenon without necessarily determining if one variable influences another.

Therefore, causal research is the most suitable choice when it comes to modeling cause-effect relationships, as it is structured to prove or disprove hypotheses related to these dynamics.