In a true experimental design, the subject matter are assigned at random to a group for various levels of treatment. It implies that any potential difference in the group might be due to chance. Randomization of subjects controls for potential participant difference that is believed to be a fundamental threat to the study’s internal validity (Gliner & Morgan, 2000). Therefore, random assignment is critical in controlling for any extraneous variables. True experimental has been shown to be excellent design when it comes to showing cause and effect relationship. Based on this, they are believed to have a higher internal validity and what is being measured is very clear. However, there is some significant bias present within a true experimental design.
In a quasi-experimental design, the subject matter under analysis are not assigned at random to a specific treatment implying that there exists no randomization (Chilton & Colburn, 1935). Membership within the treatment level is precisely determined by various factors that are beyond the researcher’s control. This study can be enhanced through the use of control group or even assess moderators and then integrating them into the study (Gliner & Morgan, 2000). Therefore, all experiments that will take advantage of the natural occurrence belong to quasi-experiments.
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A correlation design, on the other hand, is a relationship between two distinct variables, and the primary purpose is to figure out the variables that are connected (Gliner & Morgan, 2000). Correlation research aims at identifying those variables that seem to interact closely with one another, such that, when one changes, one can have an idea on how the other variable will change (Chilton & Colburn, 1935). It is worth noting that correlation does not necessarily imply causation and that there is no clear or accurate way to prove causation from the correlation research.
References
Chilton, T. H., & Colburn, A. P. (1935). Distillation and absorption in packed columns A convenient design and correlation method. Industrial & Engineering Chemistry , 27 (3), 255-260.
Gliner, J. A., & Morgan, G. A. (2000). Research Methods in Applied Settings: An Integrated Approach to Design and Analysis . Mahwah, N.J: Lawrence Erlbaum.
