Understanding data and effectively presenting results are challenges that applied quantitative researchers face most every day. There is seldom a more effective solution than a well thought out visualization. Problems in the data are easily identified; complex effects are quickly summarized; effect sizes and variability are immediately clear. In this workshop, we will cover best practices for accurately representing data as well as many specific approaches to data exploration, model diagnostics, and model presentation. The focus is on the applied analyst’s “bread and butter” types of visualizations: those I suspect will be useful in most every quantitative research project. Topics covered will range from exploratory data analysis techniques to methods for presenting complex model results. Template Stata code will be provided to workshop participants allowing participants to reproduce all workshop examples.

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Presenter: Trenton D. Mize, Assistant Professor of Sociology & Advanced Methodologies, Purdue University