Presented by:Jo Hardin, Pomona College
There has been a recent push to change the way we - as statisticians - engage pedagogically with complex real-world data analysis problems. Two parallel forces have directed us toward embracing more complex data in real-world problems. The first force is a call from educators to make data in the classroom relevant to students’ experiences. The second force is from the students themselves and has likely been experienced by most statistical educators. Previously and for many years there has been a call for using real data in the classroom. We have seen the benefit of using real data sets (as opposed to made up numbers) in textbooks and in the classroom. Indeed, there are virtually no textbooks of any kind (AP Statistics, Introductory Statistics, second course in statistics) being written today without the vast majority of examples taken from actual studies or databases. Additionally, there has been a push to infuse R with datasets that are relevant, recent, and sophisticated. Unfortunately, by nature, however, all of the data given in a textbook or an R package is static. Currently, there do not exist mechanisms to continually update any dataset provided by the course materials. The most comprehensive baseball dataset compiled and provided to the students will be out of date (and possibly uninteresting) by next fall. The good news, however, is that data of all kinds are being updated in real time publicly and accessibly. And even better news is that R developers are continually improving interfaces to the vast amounts of public data. We provide examples (including full R Markdown files) for downloading and using dynamic data in the classroom. Additionally, we discuss helpful hints for using the files in a classroom.
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(Tip: right-click and choose "Save As...")Teaching with R Teaching Data Science