Scientific Data Analytics with R

The use of R to summarize and analyze data is only one aspect of the statistical problem-solving process. Decisions about appropriate summaries and procedures relate to many parts of the study. So, our instructional videos model the scientific inquiry process by highlighting important statistical considerations at each of stage of the PPDAC process (MacKay & Oldford, 1994, 2000) for published research studies.

	PROBLEM: Define the research question. What are the goals of the study? Who/what/where/when is the question about?
	PLAN: Decide how to carry out the study. Who and/or what should be selected and how should they be studied? What should be measured and how should measurements be taken and recorded? How will decisions made at this stage impact the Data, Analysis and Conclusion stages?
	DATA: Collect and record information on the individuals being studied and create preliminary summaries. How should the data be stored and organized to facilitate its management and analysis? Are there issues with data quality? What graphs, numbers and tables should be created?
	ANALYSIS: Extract meaning from the data. What patterns are emerging in the graphs, numbers, and tables? Which statistical procedures are appropriate to address research question? What are the statistical findings?
	CONCLUSION: Interpret and communicate statistical findings in the context of the research question. Are there limitations to the results? Do the results generate follow-up research questions?