Your explanatory research design depends on the research method you choose to collect your data. Step-by-step example of explanatory research In order to get conclusive causal results, you’ll need to conduct a full experimental design. Non-spurious: Be careful that there are no mitigating factors or hidden third variables that confound your results.Ĭorrelation doesn’t imply causation, but causation always implies correlation.Variation: Intervention must be systematic between your independent variable and dependent variable.Temporal: What you define as the “cause” must precede what you define as the “effect.”.In other words, there is a direct cause-and-effect relationship between variables.Ĭausal evidence must meet three criteria: However, this isn’t necessarily due to a direct or indirect causal link.Ĭausation means that changes in the independent variable bring about changes in the dependent variable. In order to ensure you are conducting your explanatory research correctly, be sure your analysis is definitively causal in nature, and not just correlated.Īlways remember the phrase “correlation doesn’t mean causation.” Correlated variables are merely associated with one another: when one variable changes, so does the other. If you have more time or funding available, an experiment or pilot study may be a good fit for you. If you are interested in opinions and behavior, consider an interview or focus group format. If there is already a body of research on your topic, a literature review is a great place to start. The method you choose depends on several factors, including your timeline, budget, and the structure of your question.
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