Final answer:
Pre-experimental designs are insufficient for drawing causal inferences due to their lack of controls, such as random assignment and the use of control groups, which are necessary to determine the effect of the independent variable on the dependent variable.
Step-by-step explanation:
Pre-experimental designs are insufficient for drawing causal inferences because they do not thoroughly control for confounding variables. Unlike true experiments, where subjects are randomly assigned to different treatment groups and where one of the groups serves as a control group, pre-experimental designs often lack a random assignment and may not include a control group at all.
To draw a causal inference, an experiment must be designed so that the only difference between the experimental and control groups is the one imposed by the researcher; which is the presence or absence of experimental manipulation. By doing so, any observed differences can be confidently attributed to the manipulation of the independent variable.
In contrast, pre-experimental designs often fail to implement these rigorous controls, such as random assignment, and as a result, cannot eliminate the possibility that observed effects are due to extraneous factors rather than the treatment itself. Therefore, pre-experimental designs do not provide a solid basis for establishing causality.