Democracy’s Data: Analytics and Insights into American Elections

Assessment

The course grade will be a weighted average of the following components:

Category	Percent of Final Grade
Participation & Attendance	15%
Discussion Board	20%
Weekly Data Contributions	10%
Three Tests (10% each)	30%
Data Journalism Project	25%

What each one is:

• Participation & Attendance — Being here, prepared, and in the conversation — on both days.
• Discussion Board — By Friday night each week, one post about any of the data we talked about: the lab, a classmate’s data slide, a figure in the reading. Something that surprised you, something we missed, something you do not understand, or an answer to somebody else’s question. A few sentences to a paragraph — enough to show you engaged with what we did. One post is full credit.
• Weekly Data Contributions — Find data bearing on the question Tuesday ended with, name the source, and post it as a slide before Thursday. Each week two slides are drawn at random and worked through in class, and nobody presents the data they found themselves. If your name is drawn and you are absent or have no slide, it costs 25% of your attendance grade for the semester — expect your own data to come up once or twice all term. At the end of term you hand in a newsletter: every piece of data you found, each with a short write-up. Build it as you go — it is a paragraph a week, and an evening’s work if you leave it all to December.
• Three Tests — In class, on paper, and on the textbook only. Test 1 on Tue, Oct 20 (Sides et al., Chapters 1–5), Test 2 on Tue, Nov 10 (Chapters 6–9), Test 3 on Thu, Dec 3 (Chapters 10–13). We read the book straight through in its own order, so each test is a block of consecutive chapters: each covers the chapters read since the last one, none is cumulative, and every chapter appears on exactly one test. There is no final exam.
• Data Journalism Project — A data-driven news story about a trend or issue in electoral processes. Runs in three parts — draft, peer review, final — and most of the marks are on the first two. It is the only substantial piece of writing this term.

Due Dates

Assignment	Due
Data slide	before each Thursday
Discussion board post	Friday, 11:59 p.m., each week
Data Session 4 board post (no Thursday session)	Tue, Sep 22 — no session to follow that week, so you get the weekend
Week 14 board post (Thanksgiving)	Mon, Nov 30 — Tuesday is the lab, and there is no Thursday
Data journalism: pitch	Thu, Oct 8, in class
Test 1 — Ch. 1–5	Tue, Oct 20, in class
Test 2 — Ch. 6–9	Tue, Nov 10, in class
Data journalism: draft	Thu, Nov 19 — the last session before the break
Data journalism: peer reviews (two)	Tue, Dec 1
Test 3 — Ch. 10–13	Thu, Dec 3, in class
Data newsletter	Fri, Dec 4 — the last day of classes
Data journalism: final	Fri, Dec 11 — after the last session

There is no final exam.

The Essentials

• Required text: Sides, Shaw, Grossmann & Lipsitz, Campaigns and Elections (W. W. Norton). Everything else is posted on Canvas — there is nothing else to buy.
• No coding, and nothing to install. Every lab arrives as a prepared data brief with the results already in front of you; what you do is work out what they show.
• Tests are on the textbook only — in class, on paper.
• First day, in class: the Cervas Election Study — link in Canvas, under Assignments; screenshot the confirmation screen for credit.

The Full Syllabus

The session-by-session schedule, every reading and lab, assignment details, and all policies:

https://jcervas.github.io/teaching/2026-2027/class-cmu-2026-84-355/readme.html