Quantitative Methods in Urban Design and Planning
URBAN 520, Department of Urban Design and Planning, University of Washington, Autumn 2025
Tuesday & Thursday, 1:30 - 4:20pm, Gould Hall 114
The primary objective of this course is to familiarize planning students with methods and techniques they are likely to encounter and use in planning departments and organizations. Planners must be quite versatile, in that they must be knowledgeable of a variety of analytical methods, including statistical analysis and techniques, demographic techniques; economic analysis, project planning techniques, geographical and spatial analysis techniques and analysis, and various forms of transportation analysis.
We will use two wonderful textbooks. Even reading the textbooks is optional for most classes, but I highly recommend it.
Statistics (4th Edition). David A. Freedman, Robert L. Pisani, and Roger Purves. 2007. A gateway to statistical thinking with narratives and barely a formula in sight.
OpenIntro Statistics (4th Edition). David Diez, Mine Cetinkaya-Rundel, Christopher Barr, and OpenIntro. 2024. A free, open, and modern intro text with clear explanations of core statistical ideas.
Schedules
Go to the recent section. This schedule is subject to change and please check back regularly for updates. All readings can be directly accessed via the links below, although some may require a UW NetID login.
Module 1 - Introduction, Descriptive Statistics, and Visualization
- Sep 25
- Class Overview and Math Review
- Slides
- HWHomework 0 Release
- OptionalMath Review Note. Harvard Statistics. Joe Blitzstein.
- OptionalComputers and Decision Making. Journal of the American Planning Association. Richard Langendorf. 1985.
- Sep 30
- Data, Statistics and Research Design
- Slides
- LABBasic of Excel or R
- HWHomework 1 Release
- OptionalChapter 1, OpenIntro Statistics. David Diez et al. 2024
- Oct 02
- Descriptive Statistics
- Slides
- Quantitative Data in Urban Planning
- Slides
- LABDownload Data & Descriptive Statistics
- HW 0 DUE
- OptionalChapter 2, OpenIntro Statistics. David Diez et al. 2024
- OptionalVisual and Statistical Thinking: Displays of Evidence for Making Decisions. Edward Tufte. 1997.
- Oct 07
- Data Visualization
- Slides
- LABVisualization using Tableau
- HWHomework 2 Release
- HW 1 DUE
- OptionalDesign and Redesign in Data Visualization. Martin Wattenberg and Fernanda Viégas. 2015.
- OptionalExploratory Data Analysis. United States Environmental Protection Agency.
- OptionalData Viz Project by ferdio.
Module 2 - Sampling, Probability, and Distributions
- Oct 09
- Probability
- Slides
- IN-CLASS QUIZ
- OptionalChapter 3, OpenIntro Statistics. David Diez et al. 2024
- OptionalBayes Theorem, the Geometry of Changing Beliefs. 3Blue1Brown. 2019
- OptionalSeeing Theory - A Visual Introduction to Probability and Statistics. Daniel Kunin.
- Oct 14
- Random Variables
- Slides
- LabDistribution Simulations
- HWHomework 3 Release
- HW 2 DUE
- OptionalChapter 4, OpenIntro Statistics. David Diez et al. 2024
- OptionalBut What is the Central Limit Theorem? 3Blue1Brown. 2023
- Oct 16
- Sampling and Distributions
- Slides
- IN-CLASS QUIZ
- OptionalChapter 4, OpenIntro Statistics. David Diez et al. 2024
Module 3 - Estimation and Hypothesis Testing
- Oct 21
- Estimation
- Slides
- HWHomework 4 Release
- HW 3 DUE
- OptionalChapter 5.1, OpenIntro Statistics. David Diez et al. 2024
- Oct 23
- Instructor leave due to ACSP 2025
- IN-CLASS QUIZ
- LabLab
- IN-CLASS QUIZ
- Oct 28
- Confience Intervals
- Slides
- DEBATE Session 1
- HWHomework 5 Release
- HW 4 DUE
- OptionalChapter 5.2, OpenIntro Statistics. David Diez et al. 2024
- Oct 30
- Hypothesis Testing
- Slides
- LabLab
- OptionalChapter 5.3, OpenIntro Statistics. David Diez et al. 2024
- Nov 04
- Inference
- Slides
- DEBATE Session 2
- HWHomework 6 Release
- HW 5 DUE
- OptionalChapter 6-7, OpenIntro Statistics. David Diez et al. 2024
Module 4 - Regression
- Nov 06
- Correlation and Linear Regression
- Slides
- IN-CLASS QUIZ
- OptionalChapter 8.1-8.2, OpenIntro Statistics / Chapter 8-10, Statistics Fouth Edition
- Nov 11
- No Class due to Veterans
- HWHomework 7 Release
- HW 6 DUE
- HWHomework 7 Release
- Nov 13
- Linear Regression
- Slides
- DEBATE Session 3
- OptionalChapter 8.3-8.4, OpenIntro Statistics / Chapter 10-12, Statistics Fouth Edition
- Nov 18
- Mutliple and Logisic Regression
- Slides
- LabLab
- HWHomework 8 Release
- HW 7 DUE
- OptionalChapter 9, OpenIntro Statistics
- Nov 20
- Data Science Pipeline / Workflow
- Slides
- LabLab
- DEBATE Session 4
Module 5 - Advanced Topics (Not in the final exam)
- Nov 25
- Introduction to Advanced Regression
- Slides
- Introduction to Causal Inference
- Slides
- IN-CLASS QUIZ
- Nov 27
- No Class due to Thanksgiving
- Dec 02
- Introduction to Machine Learning and Artificial Intelligence
- Slides
- DEBATE Session 5
- HW 8 DUE
- Required(Skim) AI in Planning: Opportunities and Challenges and How to Prepare. American Planning Association. 2022.
- OptionalAI for Social Good. Nature Communications. Nenad Tomašev et al. 2020.
- OptionalA Golden Decade of Deep Learning: Computing Systems & Applications. Jeffrey Dean (UW Alumni, Google). 2022.
- OptionalStatistical Modeling: The Two Cultures. Leo Breiman. 2001.
- OptionalWhat is a Neural Network. 3Blue1Brown. 2017.
- OptionalAtlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Kate Crawford. 2022.
- Dec 04
- Data and Research Ethics
- Slides
- Review of Key Topics
- Notes; Final Exam Example
- RequiredWhen Planners Lie with Numbers. Journal of the American Planning Association. Martin Wachs. 1989.
- Dec 11
- Final Exam
- Solutions (Available after the Exam)
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Built on Just the Class developed by Kevin Lin at Allen School