Final answer:
Observational studies can measure associations but cannot determine cause and effect relationships because they do not involve randomization and control of variables. They can be prospective or retrospective, as opposed to always being retrospective.
Step-by-step explanation:
Among the options provided, the statement that applies to observational studies is: They can measure associations between exposures and effects. Observational studies are valuable in research for exploring potential associations, but they cannot definitively prove causation due to the lack of randomization and potential for confounding variables.
To clarify why observational studies cannot establish causation, consider the inherent design of these studies. Unlike randomized controlled trials, observational studies do not manipulate the independent variable or assign subjects to different treatment groups randomly. Instead, they observe exposures and outcomes as they naturally occur. For instance, if a correlation between smoking and lung cancer is observed, it could be due to smoking, but it may also be due to other factors that are not controlled in the study.
Correlation in observational studies indicates that two variables may change together, but this does not mean one causes the other. For example, an observational study may find that as the number of firefighters at a scene increases, so does the damage to a building (positive correlation). This does not mean that firefighters cause more damage, but that larger fires may require more firefighters.