Research studies often compare variables, conditions, times, and/or groups of participants to evaluate relationships between variables or differences between groups or times. For example, if researchers are interested in knowing whether an intervention produces change in the desired direction, they will want to know whether the change is due to chance (statistical significance) or possibly due to the intervention. In this case, researchers could use a pre and post measurement of the same participants on the condition being treated, or they could compare a group of individuals who receive the intervention to a group that does not receive the intervention. Researchers could also compare two groups of individuals who receive different interventions. The rigor of the research design helps control for other factors that might account for the changes (e.g., time, conditions, group differences in other factors, etc.).
To prepare for this Discussion, consider the concept of statistical significance.
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Reference
Bauer, S., Lambert, M. J., & Nielsen, S. L. (2004). Clinical significance methods: A comparison of statistical techniques. Journal of Personality Assessment, 82, 60–70. Retrieved from Walden Library databases.
Yegidis, B. L., Weinbach, R. W., & Myers, L. L. (2018). Research methods for social workers (8th ed.). New York, NY: Pearson. Chapter 13, “Analyzing Data” (pp. 295–297, “The Data in Perspective”)
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