In this two-day course, participants will be introduced to core data management concepts and techniques using the R programming language, focusing on reading data into R (and writing data from R) from a wide variety of sources, and manipulating and cleaning it for use in statistical and descriptive analyses. Emphasis will be placed on providing participants with the skills to deal with poorly formatted source data, and multiple datasets at once. The workshop will also include a mini-unit on social network data management, as well as a mini-unit on producing publication-quality plots and graphics. By the end of the workshop participants should possess the basic skills necessary to perform most data management tasks they are likely to encounter over the course of a research project intended for publication as a scholarly journal article. No previous experience with R is required, and a number of tutorial resources will be provided before the beginning of the course. However, participants are expected to have some very basic experience working with data using software such as R, Stata, SAS, SPSS, or Excel.
Matt Denny is a PhD student in political science and social data analytics, and an NSF Big Data Social Science IGERT fellow at Penn State. He holds master's degrees in political science and resource economics from UMass-Amherst, where he was a statistical methods consultant for ISSR from 2013-15. He has taught a number of workshops on topics ranging from social network theory to big data analytics, and his research focuses primarily on developing statistical models for text, networks, and text-valued networks. You can check out more of his work at www.mjdenny.com.
Registration for this workshop is now closed.