Every dissertation methodology requires a data analysis plan. The plan is critical because it tells the reader what analysis will be conducted to examine each of the research hypotheses. In the data plan, data cleaning, transformations, and assumptions of the analyses should be addressed, in addition to the actual analytic strategy selected.
Statistics Solutions can assist with the development of your quantitative data analysis plan. We offer the following services:
Aligning theoretical framework, gathering articles, synthesizing gaps, articulating a clear methodology and data plan, and writing about the theoretical and practical implications of your research are part of our comprehensive dissertation editing services.
Data analysis plans are presented in the methodology and used in the IRB process. They describe the procedures to analyze quantitative data. It is important in the scientific process, as it facilitates the ability for other researchers to replicate the study. The procedures, or selection of statistical tests, are driven by two factors: the way the research questions is phrased and the level of measurement of the data.
Research questions with variables that have the same level of measurement, but different phraseology, lead to different test selections. For example, here are some possible research questions using a dependent variable of Engagement Life Scores (ranging from 0-100) and an independent variable of Meditation condition (yes vs. no).
Fortunately, there are decision trees that can help in the selection of statistical tests. But we are not done yet…the selection of the test is the first step. The second step is to describe the assumptions of the test.
To learn more about data analysis plan assistance, call 727-442-4290, fill out our contact form, or email [email protected].
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