- Date:
- 2010-10-22
- Main contributors:
- William G. 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.
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