SP&E 487 - Visualizing Data

Visual displays of data and models are an integral part of most social science presentations and can make or break a paper or presentation. Good visuals help researchers uncover patterns and relationships they would otherwise miss. Sophisticated statistical models cry out for clear, easy-to-understand visual representations of model findings. Yet social scientists seldom put as much care into designing visual displays as they devote to causal identification, running statistical models, or crafting effective prose. This course takes the design of graphics and tables seriously and explores a variety of visual techniques for investigating patterns in data, summarizing statistical results, and efficiently representing the robustness of such results to alternative modeling assumptions. Emphasis is placed on the principles of effective visualization, examples from the social sciences, novel visual displays, and the implementation of recommended techniques using the R statistical environment and the R package ggplot2. There are no specific prerequisite courses but some familiarity with the basics of research design and quantitative inference (linear regression & elementary maximum likelihood) and the R programming language is required.
Units: 4
Course Type: Seminar