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Visualizing Model Inference and Robustness
This is a 9-hour short course version of the full Data Visualization course; the lectures for the full term course are below. Students taking the short course will also need these additional resources:
Principles for the Visual Display of Scientific Information
Cognitive Issues in Visualization
Graphical Programming in R
We will examine two R scripts: a script using the base R graphics to show confidence intervals around a regression line, and another script using grid R graphics to accomplish the same task. A third, more advanced grid graphics script replaces ticks with gridlines. All three scripts require this dataset. Interested students can find detailed instructions for downloading, installing, and learning my recommended software for quantitative social science here. Focus on steps 1.1 and 1.3 for now, and then, optionally, step 1.2.
Exploratory Data Analysis: Between Data & Model
Download instructions for the tile package can be found under the Software tab at left. We will discuss three examples in detail:
Scales and Storytelling
Maps as Visual Displays of Information
Time Series as Narrative
Grayscale Images of Continuous Data
Turning Tables into Graphs
Heatmaps for Visualizing Continuous Dyadic Data
Ternary Plots for Compositional Data Analysis
Problem Set 1
Due in class 19 January 2016
Supplementary material: You will need these data.
Problem Set 2
Due in class 9 February 2016
Problem Set 3
Due in class 11 March 2016
Individual memo due before group meets; Group memo due by 22 February
Students will join a small group to discuss a visual display problem of common interest; creation and organization of these groups to be coordinated through the web. Students will write a 1-2 page memo before the first group meeting, and each group will write a 5+ page essay for the class on what they have learned, to be distributed by 22 February. Groups will answer questions from the class during the week of 22 February. See the syllabus for further details.
Presented during the final five classes
On an assigned day during the last two or three weeks of the course, each student will present a poster applying the tools learned in class to their own research. Alternatively, students can take an article published in their field and show how better visuals would either more clearly convey the findings or cast doubt on them. The final presentation may address problems raised in the breakout session or problem sets, but it is usually more fruitful for students to tackle a new problem.