What is the term for examining relationships among variables based on past data in research?

The term for examining relationships among variables based on past data in research is correlational study. In a correlational study, researchers investigate the associations between two or more variables to determine whether a relationship exists and to what extent. This type of research is often used to identify patterns, trends, and potential predictions based on historical data without manipulating any variables.

For instance, researchers might collect data on variables such as physical activity levels and the incidence of heart disease to see if a correlation exists between these factors. While correlation does not imply causation, this method provides valuable insights into how different factors may be related in real-world scenarios.

Other research designs mentioned in the choices, such as experimental studies, focus on manipulating variables to establish cause-and-effect relationships. Cross-sectional studies typically assess data at a single point in time rather than analyzing the relationships over time, and descriptive studies primarily aim to describe characteristics of a population without exploring relationships between variables. Thus, the correlational study is the most appropriate choice for examining relationships among variables based on past data.