Quantitative Methods
  • Syllabus
  • Schedule
  • Classes and readings
  • Assignments
  • Resources

Schedule

Why and how do we measure things?

Date Topic Reading (before class!) Class
Sun, Aug 23 Why use data in political science?

Nothing!

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Tue, Aug 25 What even is data analysis?
  • The syllabus and assignments page
  • Install R and Positron on your laptop (instructions here)
  • Paul Musgrave, “Knowing What Counts,” Systematic Hatreds, January 6, 2025, https://musgrave.substack.com/p/knowing-what-counts
  • Dan Honig, “What South Sudanese Data Can Teach Us All, and Why We Should Care,” In Development 2 (August 2026), https://indevelopmentmag.com/what-south-sudanese-data-can-teach-us-all-and-why-we-should-care/
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Sun, Aug 30 Measurement and research design I
  • Yoon Soo Park, Lars Konge, and Anthony R. Artino, “The Positivism Paradigm of Research,” Academic Medicine 95, no. 5 (2020): 690–94, https://doi.org/10.1097/ACM.0000000000003093
  • Gerardo L. Munck, Jørgen Møller, and Svend-Erik Skaaning, “Conceptualization and Measurement: Basic Distinctions and Guidelines,” in The SAGE Handbook of Research Methods in Political Science and International Relations, ed. Luigi Curini and Robert Franzese (SAGE Publications Ltd, 2020), https://doi.org/10.4135/9781526486387.n22
  • Anna Lührmann, Marcus Tannenberg, and Staffan I. Lindberg, “Regimes of the World (RoW): Opening New Avenues for the Comparative Study of Political Regimes,” Politics and Governance 6, no. 1 (2018): 60–77, https://doi.org/10.17645/pag.v6i1.1214
  • Explore the Arab Barometer website (https://www.arabbarometer.org/) and see what kind of data they have
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Tue, Sep 1 Measurement and research design II
  • Research Paradigms Explained: Positivism, Interpretivism & Critical Realism 2024, https://www.youtube.com/watch?v=rLK-Vnc5gjg
  • Margit Van Wessel, Rita Manchanda, and Nandini Deo, “How Civil Society in India Is Marginalized. Civic Space as Relational Process,” Journal of Civil Society 21, no. 3 (2025): 237–55, https://doi.org/10.1080/17448689.2025.2515038
  • Suparna Chaudhry, Marc Dotson, and Andrew Heiss, “Navigating Hostility: The Effect of Nonprofit Transparency and Accountability on Donor Preferences in the Face of Shrinking Civic Space,” Nonprofit and Voluntary Sector Quarterly, 2025, 1–27, https://doi.org/10.1177/08997640251348654
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Sun, Sep 6  Problem set 1 due (submit by 23:59)

Problem set 1 instructions

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How do we work with data?

Date Topic Reading (before class!) Class
Sun, Sep 6 Data visualization I
  • 1.1–1.4 in Chester Ismay, Albert Y. Kim, and Arturo Valdivia, Statistical Inference via Data Science: A ModernDive into R and the Tidyverse, 2nd ed. (Chapman and Hall/CRC, 2025), https://doi.org/10.1201/9781032724546
  • Ismay, et al. ModernDive, 2.1–2.4
  • “Data visualization basics” interactive primer, https://r-primers.andrewheiss.com/basics/01-visualization-basics/
  • 99% Invisible, Florence Nightingale: Data Viz Pioneer, 433, March 2, 2021, https://99percentinvisible.org/episode/433-florence-nightingale-data-viz-pioneer/
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Tue, Sep 8 Data visualization II
  • Ismay, et al. ModernDive, 2.5–2.9
  • Robert Kosara, “Understanding Pie Charts,” EagerEyes, January 12, 2010, https://eagereyes.org/blog/2010/pie-charts
  • Nick Desbarats, “I’ve Stopped Using Box Plots. Should You?” Nightingale, November 4, 2021, https://nightingaledvs.com/ive-stopped-using-box-plots-should-you/
  • Stephen Few, Dual-Scaled Axes in Graphs: Are They Ever the Best Solution?, Visual Business Intelligence Newsletter (Perceptual Edge, 2008), https://www.perceptualedge.com/articles/visual_business_intelligence/dual-scaled_axes.pdf
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Mon, Sep 14  Problem set 2 due (submit by 23:59)

Problem set 2 instructions

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Sun, Sep 13 Data wrangling I
  • Ismay, et al. ModernDive, 3.1–3.4
  • “Working with tibbles” interactive primer, https://r-primers.andrewheiss.com/transform-data/01-tibbles/
  • Andrew Heiss, “Visualizing {dplyr}’s mutate(), summarize(), group_by(), and ungroup() with Animations,” April 4, 2024, https://doi.org/10.59350/d2sz4-w4e25
  • Recommended: “Data transformation” in Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund, R for Data Science, 2nd ed. (O’Reilly Media, 2023)
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Tue, Sep 15 Data wrangling II
  • Ismay, et al. ModernDive, 3.5–3.9
  • “Isolating data with {dplyr}” interactive primer, https://r-primers.andrewheiss.com/transform-data/02-isolating/
  • “Deriving information with {dplyr}” interactive primer, https://r-primers.andrewheiss.com/transform-data/03-deriving/
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Sun, Sep 20 Data importing and tidy data I
  • Ismay, et al. ModernDive, 4.1–4.2
  • Recommended: “Data tidying” in Wickham, et al. R for Data Science
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Tue, Sep 22 Data importing and tidy data II
  • Ismay, et al. ModernDive, 4.3–4.5
  • “Reshape data” interactive primer, https://r-primers.andrewheiss.com/tidy-data/01-reshape-data/
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Sat, Sep 26  Problem set 3 due (submit by 23:59)

Problem set 3 instructions

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Sun, Sep 27  Quiz 1 (in-class) 

How do we model things in the world?

Date Topic Reading (before class!) Class
Sun, Sep 27 Simple linear regression I
  • Ismay, et al. ModernDive, 5.1
  • David Diez, Mine Çetinkaya-Rundel, and Christopher D. Barr, OpenIntro Statistics, 4th ed. (OpenIntro, 2019), https://www.openintro.org/book/os/, 8.1–8.3. This one is more mathy than ModernDive—don’t worry about reading it as carefully or deeply.
  • OpenIntro, “Line Fitting, Residuals, and Correlation”, https://www.youtube.com/watch?v=mPvtZhdPBhQ
  • OpenIntro, “Fitting a Line with Least Squares Regression”, https://www.youtube.com/watch?v=z8DmwG2G4Qc
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Tue, Sep 29 Simple linear regression II
  • Ismay, et al. ModernDive, 5.2–5.4
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Sat, Oct 3  Problem set 4 due (submit by 23:59)

Problem set 4 instructions

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Sun, Oct 4 Multiple regression I
  • Ismay, et al. ModernDive, 6.1
  • Diez, et al. OpenIntro Statistics, 9.1–9.2. This one is more mathy than ModernDive—skim it!
  • OpenIntro, “Introduction to Multiple Regression”, https://www.youtube.com/watch?v=sQpAuyfEYZg
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Tue, Oct 6 Multiple regression II
  • Ismay, et al. ModernDive, 6.2–6.3
  • Diez, et al. OpenIntro Statistics, 9.3–9.4. This one is more mathy than ModernDive—again, skim it!
  • OpenIntro, “Model Selection in Multiple Regression”, https://www.youtube.com/watch?v=VB1qSwoF-l0
  • OpenIntro, “Checking Multiple Regression Diagnostics Using Graphs”, https://www.youtube.com/watch?v=3KSUeYMKt5A
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Sun, Oct 11 Fall break

Nothing!

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Tue, Oct 13 Fall break

Nothing!

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Sun, Oct 18  Problem set 5 due (submit by 23:59)

Problem set 5 instructions

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Sun, Oct 18  Quiz 2 (in-class) 

How do we infer things about the world?

Date Topic Reading (before class!) Class
Sun, Oct 18 Sampling I
  • Ismay, et al. ModernDive, 7.1–7.3
  • Other readings TBA
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Tue, Oct 20 Sampling II
  • Ismay, et al. ModernDive, 7.4–7.6
  • Other readings TBA
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Sun, Oct 25 Estimation, confidence intervals, and bootstrapping I
  • Ismay, et al. ModernDive, 8.1–8.2
  • Other readings TBA
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Tue, Oct 27 Estimation, confidence intervals, and bootstrapping II
  • Ismay, et al. ModernDive, 8.3–8.5
  • Other readings TBA
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Sun, Nov 1  Problem set 6 due (submit by 23:59)

Problem set 6 instructions

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Sun, Nov 1 Hypothesis testing I
  • Ismay, et al. ModernDive, 9.1–9.4
  • Other readings TBA
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Tue, Nov 3 Hypothesis testing II
  • Ismay, et al. ModernDive, 9.5–9.7
  • Other readings TBA
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Sun, Nov 8 Inference for regression I
  • Ismay, et al. ModernDive, 10.1–10.3
  • Diez, et al. OpenIntro Statistics, 8.4
  • OpenIntro, “Inference for Linear Regression”, https://www.youtube.com/watch?v=depiT-hTaGA
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Tue, Nov 10 Inference for regression II
  • Ismay, et al. ModernDive, 10.4–10.7
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Sat, Nov 14  Problem set 7 due (submit by 23:59)

Problem set 7 instructions

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Sun, Nov 15  Quiz 3 (in-class) 

Can we do slightly fancier analyses?

Date Topic Reading (before class!) Class
Sun, Nov 15 Marginal effects
  • Vincent Arel-Bundock, Noah Greifer, and Andrew Heiss, “How to Interpret Statistical Models Using Marginaleffects for R and Python,” Journal of Statistical Software 111, no. 9 (2024): 1–32, https://doi.org/10.18637/jss.v111.i09
  • “Conceptual framework,” chapter 3 in Vincent Arel-Bundock, Model to Meaning: How to Interpret Statistical Models with R and Python (CRC Press, 2026), https://doi.org/10.1201/9781003560333
  • Andrew Heiss, “Marginalia: A Guide to Figuring Out What the Heck Marginal Effects, Marginal Slopes, Average Marginal Effects, Marginal Effects at the Mean, and All These Other Marginal Things Are,” May 20, 2022, https://doi.org/10.59350/40xaj-4e562
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Tue, Nov 17 Logistic regression
  • Diez, et al. OpenIntro Statistics, 9.5
  • Robert Kubinec, “Lost in Transformation: The Horror and Wonder of Logit,” April 25, 2024, https://www.robertkubinec.com/post/flat_earth/
  • Steven V. Miller, “Get Comfortable with Logistic Regression and What It Can Tell You,” December 4, 2024, http://svmiller.com/blog/2024/12/just-use-logistic-regression-already/
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Sun, Nov 22 Causation
  • Andrew Heiss, “Statistical Methods in Public Policy Research,” pre-published September 26, 2025, https://doi.org/10.31235/osf.io/cwymb_v2
  • Other readings TBA
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Tue, Nov 24 Prediction
  • Readings TBA
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Sun, Nov 29  Problem set 8 due (submit by 23:59)

Problem set 8 instructions

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How can we communicate these results to regular people?

Date Topic Reading (before class!) Class
Sun, Nov 29 Tell your story with data I
  • Ismay, et al. ModernDive, 11.1–11.3
  • Other readings TBA
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Tue, Dec 1 Tell your story with data II
  • Readings TBA
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