UPDATED with schedule adjustments for weather delays
The 2017 Paideia schedule is out; here we’ve highlighted a handful of data-related offerings including sessions on mapping, data visualization, and digital humanities as well as working with Stata, R, and multimedia materials.
This course will introduce participants to the theory and methodology of Digital Humanities, the use of digital tools in research in disciplines such as literature, languages, philosophy, religion, and history. Thinking of humanities research as data-based is the first step in working in the Digital Humanities, and so the class will address the question of what data in the humanities looks like for a variety of research projects, considering, for instance, what’s appropriate for a semester paper, versus a thesis or a longer professional research project. We’ll look at a variety of Digital Humanities projects as examples, and, given time, we’ll explore a few simple tools. | 1/18/2017, 9am-10:30am, ETC 205| Beth Platte and Angie Beiriger
No matter your discipline, maps can be very useful for visualizing data and putting questions into spatial context. Join this class to learn how maps might relate to your work, discover some new tools, and build maps of your own. This is an introductory workshop and will be an interactive blend of demonstration, lecture, and hands-on learning. | 1/18/2017, 11-noon, ETC 205 | Kristin Bott
The Internet is full of images, audio, or video just waiting for your tweaks and personality. Learn how to find existing open resources and re-mix them without worrying about copyright. This session will demo resources for finding open images, audio, video, and the software you will need to edit them. There will be time for hands-on participation as we re-use, re-make, and re-define digital objects. | 1/18/2017, 3-4pm, L17 | David Isaak + Angie Beiriger + Laura Buchholz
Your visuals shouldn’t be deceiving (though people often do that too), but should be clear as to their purpose. We’ll discuss strategies and some ideas as to what makes a good data visualization, what makes a bad one, and why it’s hard to always have a clear guide. Data visualization is in many ways an art as much as it is a science. Come explore with us how to better tell stories about your data! | 1/19/2017, 9am-10am, Eliot 314 | Chester Ismay
Whether you are getting ready to dive into your thesis data analysis, prepping for a methods course, or looking to build additional analytical skills – join me to build your familiarity with Stata, a statistical package used by the Economics, Political Science, Psychology, and Sociology departments at Reed. In this workshop you will work with data in Stata, including creating and importing datasets, conducting analyses, and visualizing data. All students will work hands-on in Stata during our session. All levels are welcome; I will provide basics for beginners and additional exercises and options for advanced students. | 1/19/2017, 10am-11am, ETC 211 | Kristin Bott
To better assist with reproducible research pairing with senior theses, I’ve put together an updated template (from last year) for senior theses using R Markdown. R Markdown allows for the use of simple text editing commands and also interfaces with LaTeX without all of the overhead of actually typing a LaTeX document. I’ll demo the template and also show how to easily add your data analysis and output into your thesis using R. | 1/19/2017, 2-3pm, ETC 205 | Chester Ismay
This course covers the various kinds of textual, literary, and linguistic analysis that are possible using digital methods. We will look at Digital Humanities projects to understand the sorts of research questions that computer-assisted text analysis can help to answer. This hands-on course will also introduce basic text encoding using the Text Encoding Initiative (TEI) schema and present various ways of digitizing texts. Finally, we’ll explore some applications that allow simple text analysis. | 1/19/2017, 3pm-4:30pm, ETC 205 | Beth Platte and Angie Beiriger
You can view the full Paideia schedule here; be sure to log in with your Reed credentials (“school ID”).