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Two talks on Statistical graphics for visualizing data
Date
2010-01-29 (Creation date: 2010-01-29)
Main contributor
William Jacoby
Summary
These lectures cover methods for obtaining visual displays of quantitative information. They discuss ways to, quite literally, look at data. This is important because graphical representations avoid some of the restrictive assumptions and simplistic models that are often encountered in empirical analyses. These methods are very useful in the social sciences, where the robustness characteristics of traditional statistical techniques often are pushed to their limits. The lectures focus primarily on introductory concepts and graphical displays for univariate data, then move on to graphs for bivariate, multivariate, and categorical data. The main objective is to help you learn to construct a pictorial abstraction that highlights the salient aspects of your data without distorting any features or imposing undue assumptions.
Collection
Workshop in Methods
Unit
Social Science Research Commons
Notes

Performers

Dr. Jacoby is Professor of Political Science at Michigan State University. He is also a Research Scientist at the University of Michigan and Director of the Inter-University Consortium for Political and Social Research (ICPSR) Summer Program in Quantitative Methods. He received his PhD from the University of North Carolina, and he recently served as Editor of the Journal of Politics (2001-2004). Professor Jacoby’s research interests include mass political behavior (public opinion and voting behavior) and quantitative methodology (measurement theory, scaling methods, and statistical graphics).