Upcoming Events

In this one day (6 hours, with a 1 hour break) workshop, participants will be introduced to R as a data management tool. 

Network analysis is increasingly used by social scientists to capture properties of complex relationships. It is both a descriptive device and an inferential tool, and is often used alongside other methods. Unlike many other quantitative techniques, the heart of network analysis presumes that actors are interconnected, rather than independent observations.

This 3-day (12-hour) intensive beginners workshop covers all the necessary elements to get started with network analysis in your own research. It will allow you to read, interpret and critique other scholars’ network analysis results, and to build up a range of specific skills and tools that can grow over time.

Inferring causality is central to many quantitative studies in social science. A large number of analytical methods have been developed to infer causal dependence from observational data, including propensity score matching, instrumental variable designs, interrupted time-series designs, and many others. Unfortunately, the assumptions and limitations of these methods can be difficult to explain and reason about.

This 2-day (12-hour) tutorial introduces participants to causal graphical models, a powerful formalism developed within computer science and statistics that simultaneously provides: 1) a unifying formal framework for understanding and explaining specific methods for causal inference; 2) a practical tool for representing and reasoning about the implications of particular causal models; and 3) powerful algorithmic methods for learning complex causal models from data and reasoning about their implications. This tutorial assumes only a basic understanding of probability and statistics and no knowledge of programming. Participants familiar with experimental and quasi-experimental designs will gain a new understanding of the benefits and assumptions of these methods, and participants without that knowledge will learn about multiple methods for inferring causality within a single unifying framework.

This three day (12-hour) workshop will get you up and running with coding and analyzing your qualitative data in NVivo 14 for Mac and Windows. The first day will focus on the basics: importing, organizing, and beginning to code your data (text documents, surveys, web pages, videos and audio). The second day, we'll discuss linking categorical data (e.g. demographic information) and how to effectively integrate it into your project/analyses. The third day will focus on analysis -- we will discuss the various types of queries and when to implement them.

In this one day (6 hours, with a 1 hour break) workshop, participants will learn how to efficiently automate the process of collecting data from large numbers of websites and text files using R. Practical and computational issues associated with scraping large amounts of data in a timely manner will be among the topics covered.

This three-day (15-hour) in-person workshop (with lunch break) will introduce you to the basics of Geospatial Information Systems (GIS) using QGIS, a free and open-source software platform. GIS is a spatial analysis tool with wide-ranging applications, including navigation, unmanned aerial vehicle surveys, satellite remote sensing, data visualization, and location analytics. The content of this workshop is geared towards beginners with little to no experience with GIS, but people with an intermediate skill level are welcome to attend for a refresher on the core concepts or to learn how to use QGIS.

With the rapid explosion in availability of digitized text, social scientists are increasingly turning to computational tools for the analysis of text-as-data. In this two-day course, participants will first learn how to convert text to formats suitable for analysis.