I’m teaching a workshop at Penn’s Master’s of Urban Spatial Analytics on April 22nd.
I’ve posted all of the materials on github, including RMarkdown walkthroughs. Want to learn how I predicted the 2018 election and only made one bad mistake? Check it out!
Note: As an early tester, by reading the posts you commit to sending me feedback. Preferably before April 22nd. thx.
Post 1: The Relational Database. How I’ve organized the election data.
Post 2: Geographies. How I crosswalked geographies across moving boundaries.
Post 3: Creating the rectangular data.frame. Final steps to get ready to model.
Post 4: Predicting the election. The good stuff! (You can skip the others. This is what I’ll be teaching.)
any chance you’ll predict the 2019 election? and perhaps post the predictions after election day to see how close they were?
I don’t think so. It’s hard without polls, and basically only possible in aggregate (like I did for the State House). But I will be doing some simulations for the Court of Common Please and Council at Large to understand the role of ballot position. Stay tuned!
Great! Looking forward to the common pleas one (that’s the one I’m most interested in anyways)!