Description:

Please join the R Workshop Series as they host a session on using R to clean data, led by Ph.D. candidate Jennifer Lin.

You've likely experienced times in your life where you meet someone who is ostensibly a stranger but after a brief conversation, you realize you have a mutual friend. You might have remarked "What a small world!" Our daily interactions are full of things that can be represented by networks, which can help us better understand how the world works. Network analyses help us get a bird's eye view of a phenomenon that we wish to study. In this workshop, we will explore tools to help us visualize networks and understand its properties. By the end of the workshop, students will be able to create a network visualization and understand how it can help them answer their own research questions.

This workshop serves to introduce the R programming language and promote best practices in its use. For many years, R has been favored by a passionate user-base of social scientists and statisticians. These users have contributed many packages to simplify the task of analyzing data and reporting results. Today, R stands apart in the statistical software ecosystem because of the extensiveness and quality of these open-source libraries. In previous eras, finding such high-quality software would require using expensive, proprietary systems such as STATA or SAS. While non-academic researchers often favor other languages (notably Python), R is still regarded as very useful outside academia. While each programming language has its wrinkles, familiarity with R will make learning other languages favored by data scientists considerably easier.