Improving Statistical Competencies for Healthcare Undergraduate Students Using RStudio

Abstract

Many undergraduate biological science courses offered at the University of Minnesota Rochester (UMR) utilize Excel for necessary data analysis. The courses always analyze at a parametric level even when the data are non-normally distributed. Each experiment typically employs a ubiquitous test, a derivative of a T-test. This often violates the foundational rules of statistics, since the students do not analyze or even visualize their data. They get the data, test it, and come out with a reported p-value. To properly shape an evidence based medicine mindset for their future, students must be encouraged to analyze the data and from there decide what level of test, if any, is appropriate. RStudio is an easily accessible integrated development environment (IDE) that incorporates the coding language R across all platforms. This presentation will describe the development of an R package. The package “Data Analysis for You-UMR” (DAY-UMR) will include tools to visualize data, test for normality, create figures, and get the most accurate p-value. DAY-UMR will make analyzing data straightforward for undergraduates and allow them easy access to multiple levels of testing. In this way it will provide more accurate and realistic experiences regarding research and data analysis. Overall, DAY-UMR will require more interaction with the data that will foster the desired evidence based medicine thinking in undergraduate students.