Undergraduate students are increasingly in need of basic skills in data analysis. As a complement, analyzing data provides an opportunity for active learning. Having students utilize data visualization and statistical analysis skills in introductory classes (with their own data) allows students to quickly develop an appreciation for digital skills. Here we introduce these skills to freshmen, giving all students an equal footing in basic data analysis in the context of learning biological concepts. We developed a simple, step-wise introduction beginning with the free, spreadsheet program Google Sheets for storing data and continuing with importing data to the free, data analysis language R in the R-Studio environment. Our approach through the semester provides students with code that they can use to create boxplots, scatterplots, and line graphs in R. Students also use code to produce error bars, t-tests, and best-fit linear regressions. Students responded that this approach was effective in making them feel that they can use a coding language program to analyze and graphically display their data. Importantly, students can build on these skills in future classes as R can handle a wide range of analyses. Here we demonstrate how these skills can be taught in the context of learning introductory biology.
Keywords: species diversity, data analysis, R, coding
University of Ottawa (2019)
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