Computational & Quantitative Social Sciences (CQSS)
Methods Training Days DSI@UTSC 

Please note: the event has ended. The info is being left up for reference.
Stay tuned for next year’s event.

The CQSS Methods Training Days consist of focused workshops designed to improve and innovate research practices in the social sciences, humanities, and related fields. Training Days are led by experienced methodologists from a variety of disciplines. The workshops serve as an interdisciplinary platform that enables researchers to enrich their methodological skills while fostering valuable relationships with colleagues from different fields.  

The Training Days are open only to University of Toronto and external funding partner members, faculty, scientists, graduate students, and trainees. Each Training Day is capped with 25 learners. Learners commit to attending the full day.  

September 26, 2023
8:30 a.m. to 5:00 p.m.
In-person
10th floor, 700 University Ave
Toronto, ON

Schedule
8:30-8:55 am
Coffee/Light Breakfast
8:55 am
Welcome & Introduction (Ethan Fosse, Department of Sociology, University of Toronto Scarborough and Andrew Miles, Department of Sociology, University of Toronto Mississauga)
9:00-12:00 pm
Introduction to R (Aida Parnia, Department of Sociology, University of Toronto)

This workshop provides an overview of R, a powerful statistical programming language that can make your research more reproducible and efficient. No prior experience with R is required, but participants should have the latest versions of R and RStudio installed.

Download and Install R here.
Download and Install RStudio here.
12:00-1:00 pm
Networking Lunch 
1:00-3:00 pm
Data Visualization and Exploration (Alicia Eads, Department of Sociology, University of Toronto)

There are three main reasons to visualize data: to explore, to understand, and to explain. This course is for anyone who works with data, whether a little or a lot. We will use the R programming language and the ggplot package. We will learn about different types of plots and what each is good for. We will learn how to include more variables in the same plot and how to use grids of multiple plots. We will focus on exploring data, but we will also talk about visually presenting results from statistical analyses. Familiarity with the R statistical language is helpful, but not required. 
3:00-5:00 am
Introduction to Social Network Analysis (Chris Smith, Department of Sociology, University of Toronto Mississauga)

Social network analysis (SNA) is an approach to studying social structures using network and graph theory. It is used in a wide range of disciplines, from biology to sociology. The techniques covered in this workshop are applicable to any number of data types and disciplines. This primer begins with relational data organization and then introduces basic visualization and analysis in R. No background in social network analysis is required. Familiarity with the R statistical language is helpful, but not required

The CQSS Social Methods Training Days are an outgrowth of the Social Science Methods Week, which has been supported by the Department of Sociology, Faculty of Arts & Science, as well as the Milestones and Pathways program. 

Instructors

Alicia Eads

Department of Sociology, University of Toronto

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Alicia Eads is an Assistant Professor in the Department of Sociology and is cross-appointed with the Centre for Industrial Relations and Human Resources, Faculty of Arts & Science, University of Toronto. She received her PhD in Sociology from Cornell University and her BA in Sociology and Psychology from the University of Iowa. Her research uses computational and qualitative methods to understand how cultural meaning affects economic and political processes, particularly in the context of organizations. Her most recent work has focused on the political response to the housing market collapse in the United States. 

Aida Parnia (she/they)

Department of Sociology, University of Toronto

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Aida Parnia (she/they) is a Ph.D. candidate in Sociology at the University of Toronto and a Fellow with the Consortium on Analytics for Data-Driven Decision-Making (CAnD3). Her research focuses on health inequalities in Canada and measuring the impact of structural oppression, particularly as it relates to migration and racialization. Prior to studying sociology, Aida received a Master of Public Health and has worked in the public health sector in areas related to environmental and social epidemiology. 

Chris Smith

Department of Sociology, University of Toronto Mississauga

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Chris Smith is an Assistant Professor of Sociology, University of Toronto Mississauga. She uses social network analysis to understand the structures of criminal groups and organizations. Her work on criminal networks includes training materials for practitioners, articles, chapters, and her book, Syndicate Women: Gender and Networks in Chicago Organized Crime (University of California Press). She teaches social network analysis at the undergraduate and graduate level.