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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:
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.
Download instructions for the tile package can be found under the Software tab at left. We will discuss three examples in detail:
Interactive Visual Displays with R + Shiny
The Shiny package makes it easy to convert your R code and graphics, including those made with the tile package, into interactive displays for the web. We’ll work through the written Shiny tutorial at the bottom of this page. We’ll then discuss several other examples in class, including this incomplete example from your instructor using tile and Shiny to show who got the most medals in the Olympics using different medal aggregation formulas. To run the example, unzip it to your R working directory, and in R run the commands library(Shiny) and runApp("olympics"). (If you haven't already, you will first need to install the tile package, available from my Software page.)
Advanced Latex for Scientific Typesetting
Time permitting, we will consider the use of modern Latex typesetting tools, especially Xetex and the fontspec package. We’ll discuss my caxetexFree stylesheet (manual; .sty file). Students new to Latex should read the Not So Short Introduction to Latex first.
Due in class 17 January 2017
You will need these data.
Due in class 7 February 2017
Due in class 9 March 2017
Individual memo due before group meets; Group memo due by 21 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 21 February. Groups will answer questions from the class during the week of 21 February. See the syllabus for further details.
Presented during the final three classes
On an assigned day during the last two 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.