College of Education and Human Ecology
Join our Data Visualization Specialist, Brian Wisniewski, for a virtual workshop on the basics of Data Visualization. Hosted by the Research Commons, this workshop will break down what data visualization is and why it is important. Examples, tips, tools (Overviewing R, Tableau, Excel), and resources will be shared, with the aim of enabling participants to […]
Friday, March 3, 2023, 12:00pm – 1:00pm: Dr. Kalee Burns, U.S. Census Bureau Title: By the Numbers: Childhood Poverty & Inflation By the Numbers Please join Dr. Kalee Burns, who is an Economist for the U.S. Census, for a discussion of recent findings published by the Census regarding childhood poverty. Please read the following Census […]
This presentation will discuss causal inference and directed acyclic graphs. Participants will learn the difference between description, prediction, and causal inference as three distinct scientific tasks requiring distinct scientific methods. Additionally, participants will understand the main features of causal directed acyclic graphs and how they can be used to plan and interpret causal analysis and […]
Friday, March 10, 12:00pm – 1:00pm: Dr. Stephen Gavazzi, Director, Center for Human Resource Research (CHRR) Title: Data and Samples Available Through CHRR at The Ohio State University: The National Longitudinal Studies, Ohio Longitudinal Data Archive, and the American Population Panel Dr. Stephen Gavazzi Stephen M. Gavazzi, Ph.D. is Director of CHRR at The Ohio […]
With so many types of charts or graphs to choose from, how do you determine the most effective one to use to share your data? We will explore various families of charts – beyond the simple bar or line chart – that will allow you to compare categories, explore change over time, and examine distribution. […]
As data are increasingly mobilized in the service of governments and corporations, their unequal conditions of production, their asymmetrical methods of application, and their unequal effects on both individuals and groups have become increasingly difficult for data scientists--and others who rely on data in their work--to ignore. But it is precisely this power that makes […]
