Quantitative Methods in Urban Design and Planning
URBAN 520, Department of Urban Design and Planning, University of Washington, Autumn 2026
Tuesday & Thursday, 1:30 - 4:20 pm, Gould Hall 110, the 2nd lab room: Gould Hall 007
Instructor: Haoyu Yue, [email protected]. Office Hours: Monday 9:20-10:20 AM at Gould Hall 012C; or book online
Teaching Assistant: Sun Ho Hwang, [email protected]. Office Hours: Friday 10:00-11:00 AM at Gould Hall 432
Planning has always been built on the facts we observed, the future we anticipated, the good scenarios we wished for, and the correct interventions we relied on. But are the facts really facts? Will that future actually arrive? Is a number a good way to define the good? And are the correct interventions actually correct?
Quantitative Methods is a core course for Master of Urban Planning students at the University of Washington. It intends to serve as a foundation for taking on these questions with data, and a stepping stone toward advanced quantitative methods in the broader social sciences. We will work together this quarter, 6 hours per week, starting from where every number begins and spending the quarter making numbers, doubting them, connecting them, and deciding with them. You may not leave with an answer, but you will certainly carry away questions worth asking.
October 16, 2026
Hello everyone, as we discussed this Tuesday, we will slow down the pace a little bit so that we can reduce the number of assignments from 4 to 3. Accordingly, the deadline for assignment 1 will be extended to Oct 27.
Yesterday, we did a quick look at Tableau. Next Tuesday, we will do some exploratory visualization with Tableau. But we still have many functions in Tableau that we cannot cover. You can refer to some resources online:
- Learning Tableau Desktop by Tableau
- Tableau Tutorial by GeeksforGeeks
- Tableau: An Introduction. Princeton University
- Tableau Viz Gallery
- Tableau Dashboard Showcase
Also, Mik mentioned the new rule on accessibility of web content and mobile apps, which could impact how we do visualization, and Digital Accessibility Resource from WA Office of Equity. A few rules related to data visualization summarized by Google:
- No color-only data: You cannot use color as the single way to distinguish lines, bars, or slices.
- Add textures and markers: You must use symbols, distinct line styles, or high-contrast patterns alongside colors.
- Enforce strict text contrast: Text on charts must hit a minimum 4.5:1 contrast ratio against its background.
- Enforce strict graphical contrast: Visual elements like bars, lines, and borders must hit a minimum 3:1 contrast ratio against neighboring colors.
- Provide alt-text descriptions: Every chart must include text summaries that explain the main data trends and conclusions.
- Include raw data tables: Complex graphs must be paired with accessible data tables that screen readers can easily scan.
- Enable 100% keyboard control: Users must be able to navigate filters, tooltips, and interactive fields using only a keyboard.
- Design for 400% zoom: Layouts must dynamically scale up to 400% without overlapping text or requiring horizontal scrolling.
At thing, because of a medical appointment, Haoyu’s office hours on Oct 19 (next Monday) will be changed to 12:30 - 1:30 PM on the same day.
Schedules
Go to the recent section. This schedule is subject to change, and please check back regularly for updates. All readings and materials can be directly accessed via the links below, although some may require a UW NetID login. Some readings and links about R/coding are on each lab session page. Please give us any anonymous suggestions about the lectures, labs, or anything using the anonymous suggestions box.
I - Planning Concepts to Numbers
- Oct 01
- Introduction
- Pre-class Survey / Notes / PDF
- RequiredPage 4-6 and Chapter 3 Types of Research: Basic Quantitative Research Methods for Urban Planners. 2020.
OptionalChapter 5: Market, Place, Interface, All Data Are Local. Yanni Alexander Loukissas. 2019.
OptionalChapter 1 What is Science? Philosophy of Science: A Very Short Introduction. Samir Okasha. 2016.- Oct 06
- Assignment 1 Release
- Assignment 1
- RequiredChapter 4 Planning Data and Analysis: Basic Quantitative Research Methods for Urban Planners. 2020.
OptionalChapter 7 Descriptive Statistics (P107-114): Basic Quantitative Research Methods for Urban Planners. 2020.
OptionalTED Talk: 3 Ways to Spot a Bad Statistic. Mona Chalabi. 2017.
OptionalSection 1.2 and 2.1-2.2: OpenIntro Statistics. David Diez, et al. 2024.- Oct 08
- RequiredWhen Planners Lie with Numbers. Journal of the American Planning Association. Martin Wachs. 1989.
RequiredChapter 8 Numbers: Policy Paradox. Deborah Stone. 1988.
OptionalChapter 3 Indicators and Urban Planning: The Big Data Opportunities: Applied Data Analysis for Urban Planning and Management. Alasdair Rae and Cecilia Wong. 2021.
OptionalHandbook on Constructing Composite Indicators: Methodology and User Guide. OECD and European Union. 2008.
OptionalUnderstanding and Using American Community Survey Data. United States Census Bureau. 2020.- Oct 13
- Workflow and Data Visualization
- Notes / PDF / Class Survey
- Quiz 1
- REQUIREDVisual and Statistical Thinking: Displays of Evidence for Making Decisions. Edward Tufte. 1997.
SuggestedUrban Informatics in the Science and Practice of Planning, Journal of Planning Education and Research. Constantine E. Kontokosta. 2021.
OptionalChapter 5 Design and Narrative Techniques for Urban Data: Applied Data Analysis for Urban Planning and Management. Alasdair Rae and Cecilia Wong. 2021.- Oct 15
- LAB 4 Visualization in Tableau
- Page / Data & Packaged Tableau
- REQUIREDChapter 1 What’s Vis, and Why Do It?: Visualization Analysis & Design. Tamara Munzner. 2014.
REQUIREDDefense Against Dishonest Charts. Nathan Yau.
OptionalData Viz Project by ferdio.
OptionalFrom Data to Viz.
OptionalAutomating the Design of Graphical Presentations of Relational Information. Jock Mackinlay. 1986.
OptionalChapter 9 Designing with Purpose, Visualize This. Nathan Yau. 2024.
OptionalHow to Lie with Maps. Mark Monmonier. 1991.
OptionalHow to Lie with Charts. Gerald Everett Jones. 2018.- Oct 20
- LAB 5B Getting Started with SPSS
- Files
- RequiredExploratory Data Analysis. United States Environmental Protection Agency.
OptionalChapter 7 Visualizing Data (P114-117): Basic Quantitative Research Methods for Urban Planners. 2020.
OptionalSection 2.1-2.2: OpenIntro Statistics. David Diez, et al. 2024.
II - Trusting the Numbers
- Oct 22
- LAB 6B Summarizing and Merging Data in SPSS
- Slides
- RequiredChapter 1-2, Seeing Theory - A Visual Introduction to Probability and Statistics. Daniel Kunin.
OptionalBayes Theorem, the Geometry of Changing Beliefs. 3Blue1Brown. 2019.
OptionalSection 3.1-3.2: OpenIntro Statistics. David Diez, et al. 2024.- Oct 27
- Probability Distributions
- LAB 7A Visualizing in ggplot2
- LAB 7B Visualizing in SPSS
- Assignment 1 DUE 11:59 PM
- Assignment 2 Release
- RequiredChapter 3, Seeing Theory - A Visual Introduction to Probability and Statistics. Daniel Kunin.
OptionalSection 3.4-4.5: OpenIntro Statistics. David Diez, et al. 2024. - LAB 7A Visualizing in ggplot2
- Oct 29
- Sampling and Sampling Distributions
- OptionalSection 1.3: OpenIntro Statistics. David Diez, et al. 2024.
OptionalThe Most Dangerous Equation. American Scientist. Howard Wainer. 2007.
OptionalBut What is the Central Limit Theorem? 3Blue1Brown. 2023. - OptionalSection 1.3: OpenIntro Statistics. David Diez, et al. 2024.
- Nov 03
- Estimates and Confidence Intervals
- Quiz 2 Oct 22 – Oct 29
- RequiredChapter 4, Seeing Theory - A Visual Introduction to Probability and Statistics. Daniel Kunin.
OptionalNavigating Statistical Uncertainty: How Urban and Regional Planners Understand and Work With American Community Survey (ACS) Data for Guiding Policy. JAPA. Jason R. Jurjevich et al. 2018.
OptionalPatterns and causes of uncertainty in the American Community Survey. Seth E Spielman et al. 2014.
OptionalSection 5.1-5.2: OpenIntro Statistics. David Diez, et al. 2024. - Quiz 2 Oct 22 – Oct 29
- Nov 05
- Scientific Methods and Hypothesis Testing
- LAB 8A Simulation and Inference in R
- LAB 8B Simulation and Inference in SPSS
- OptionalChapter 6 Validity and Reliability: Basic Quantitative Research Methods for Urban Planners. 2020.
OptionalSection 5.3 and 6.3-6.4: OpenIntro Statistics. David Diez, et al. 2024. - LAB 8A Simulation and Inference in R
- Nov 10
- Statistical Testing
- Quiz 3 Oct 29 – Nov 05
- LAB 9A Hypothesis Test in R
- LAB 9B Hypothesis Test in SPSS
- OptionalSection 6.1-7.5: OpenIntro Statistics. David Diez, et al. 2024.
OptionalChapter 8, 10, and 11: Basic Quantitative Research Methods for Urban Planners. 2020. - Quiz 3 Oct 29 – Nov 05
III - Connecting the Numbers
- Nov 12
- Correlation and Regression
- Nov 17
- Linear Regression
- LAB 10A Linear Regression in R
- LAB 10B Linear Regression in SPSS
- Assignment 2 DUE 11:59 PM
- Assignment 3 Release
- LAB 10A Linear Regression in R
- Nov 19
- Logistic Regression
- LAB 11A Logistic Regression in R
- LAB 11B Logistic Regression in SPSS
- LAB 11A Logistic Regression in R
- Nov 24
- Regression with Correlated Data
- Quiz 4 Nov 12 – Nov 19
- Nov 26
- Thanksgiving Holiday
- Dec 01
- Spatial Analysis
- LAB 13A Spatial Analysis in R
- LAB 13B Spatial Analysis in GeoDa
- LAB 13A Spatial Analysis in R
IV - More Topics
- Dec 03
- Money, Time, and Decisions Making
LAB 14 TBD
- Dec 08
- Survey of Machine Learning
- Dec 10
- Introduction to Artificial Intelligence
- Assignment 3 DUE 11:59 PM
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Built on Just the Class developed by Kevin Lin at Allen School