- Overview
- Learning Objectives
- Pre-requisites
- Textbooks, Readings and Class Materials
- Computing
- Generative AI Policy
- Course Requirements
- Communication and Community Forum
- Course Evaluation
- Statistics and Data Science @ UW
- Campus Safety
- Religious Accommodation Policy
- Academic Integrity
- Disability Resources for Students (DRS)
- Use of AI
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
Syllabus
Overview
Learning Objectives
Pre-requisites
- Basic knowledge of arithmetic and algebra (e.g., MATH 120, MATH 124/125/126).
- Basic knowledge of R, Python, or other programming languages (e.g., CS&SS 508, CSE 160) is recommended but not required.
Textbooks, Readings and Class Materials
Required
- Class slides for every lecture will be posted on the course website before the lectures.
- Required readings are identified for each class and should be completed as preparation before coming to class.
Optional
- Class notes will be posted on the course website before the lectures as well. We encourage you to read and understand them, but the notes are prepared in a more formal statistical way. The notes also include some advanced topics, which are optional for this class.
Computing
No previous programming experience is required, but appreciated. All required analytics applications will be in Microsoft Excel. R or Python is encouraged but not required; students who use R or Python to complete at least six assignments will be awarded extra credit. We will have an installation session during the first and second computing workshops.
Bring your computer (Windows, MacBook, or Linux is acceptable) to the assigned lab session in the calendar. If you have any trouble with having a computer, you may check the computing resources from the college (https://be.uw.edu/spaces/computing/), Student Technology Loan Program (https://stlp.uw.edu), or UW libraries computer service (https://www.lib.washington.edu/services/computers/computers). Students are also welcome to conduct any needed computer-based work in the Digital Commons in the basement of Gould Hall or other computer labs on campus.
Generative AI Policy
According to the academic integrity requirements, we prohibit the use of AI-based tools to complete assignments and exams, as well as conducting discussions and reflections in any section during class. However, we encourage students to use generative AI tools, such as ChatGPT, to assist with coding, debugging, and understanding class content.
You may use generative AI tools such as ChatGPT, as you would use a human collaborator. This means that you may NOT directly ask generative AI tools for answers or copy solutions. You’re required to acknowledge generative AI tools as collaborators and include a paragraph describing how you used the tool. The use of generative AI tools to substantially complete an assignment or exam (e.g., by directly copying) is prohibited and will result in honor code violations. We will be checking students’ assignments to enforce this policy.
Course Requirements
| In-class Quizzes | 15% |
| Weekly Assignments | 40% |
| Critical Thinking Activity | 15% |
| Final Exam | 30% |
| Extra Credits | 5% |
It is highly recommended that students attend the course regularly, as the sessions will be offered synchronously and will not be recorded. We will use class time to do necessary activities, like quizzes. Class attendance and participation are integral parts of this course; much of the key material will be introduced and discussed in lectures. Good note-taking skills are essential, since the instructor often discusses material and provides examples that may not be directly quoted on the slides. Students are expected to keep track of the schedule and assignment due dates.
According to the estimates for UW courses, it should take about 15 hours of work to complete a five-credit class each week. If you spend more than 8 hours beyond the classroom, please let us know, and we will adjust the study plans for you.
The total scores will be curved and transformed into the UW numerical grading system for graduate courses, ranging from 4.0 to 1.7 in 0.1 increments as the final grade.
In-class Quizzes (15%)
There will be at least 5 in-class quiz sessions throughout the quarter, each one will take 25 minutes. Those quizzes are intended to review and help you understand basic statistics concepts. The quizzes are open-book and notes, but no electronic devices are allowed. If you cannot attend the class with a quiz, please let us know in advance.
Assignments (40%)
There will be a total of 9 assignments. HW 0 is intended for reviewing mathematical concepts and will not be added to the total grade; 5% each for the other 8 assignments. Each assignment will take approximately one week, and the expected finish time is around 2-3 hours. Each student is expected to submit their own assignments, but study groups are allowed. But you’re expected to acknowledge the names of collaborators along with a short description of the types of collaborations being done at the beginning of each assignment submission. You may use generative AI tools such as Co-Pilot and ChatGPT, but please check the AI policy section.
Details for each homework will be released after the previous homework is due. All homework will be due at 11:59 pm Pacific Time and should be submitted on Canvas. You can typeset or scan your assignment, but you should upload a PDF rather than submitting as images.
Late days: You will have 6 penalty-free late days in total (max 3 late days per assignment). Any delayed submission after the first 3 days will be penalized 10% per day for that specific assignment (but will not count towards your used late days).
Critical Thinking Activity (15%)
Final Exam (30%)
There will be a final exam in the final week (based on UW’s arrangement). The exam will cover all the content in modules 1-4, including topics like descriptive statistics, probability distributions, hypothesis testing, and regression. The exam is closed-book; however, each student is permitted to bring a letter-size double-sided cheat sheet. Calculators will be provided if computation is needed, but you are allowed to bring your own calculators.
Extra Credits (5%)
There will be two opportunities to receive extra credit. For the winning team in each debate session, all team members will be awarded 2% extra credit. For students who use R or Python for at least six of their assignments, they will be awarded 3% extra credit.
Communication and Community Forum
You can reach us via Ed Discussion, email, and in person during class and office hours. Please use the Ed Discussion as the first place to ask general questions. If you have a question about the course material or assignment, other students may have the same question. If you email me with a question like this, I will ask you to post it on the discussion board. I will review the discussion board at least once a day (weekdays). I also encourage students to answer each other’s questions on the discussion board. For emails, we try to reply to emails within 24 hours, 48 hours over a weekend, and the workday following a holiday unless otherwise noted. Simple questions will be answered by Ed Discussion or email, but students may be asked to schedule a meeting for more complex discussions.
Course Evaluation
Formal course evaluation occurs at the end of the quarter, university-widely. If you are experiencing a problem with the class, please let me know as soon as possible, as I might be able to correct for changes if needed within the course of the class.
Statistics and Data Science @ UW
The University of Washington is the leading institution in statistics and data science in the Pacific Northwest, in the United States, and in the world. We are lucky to be here and have the chance to enjoy the invaluable resources from the university and the Seattle region. Here are some resources if you hope to learn more about statistics and data science at UW. Be free to reach out to me if you have further thoughts or any questions.
- Coursework
- Institutes and Centers
Campus Safety
Call SafeCampus at 206-685-7233 to anonymously discuss safety and well-being concerns for yourself or others. SafeCampus’s team of caring professionals will provide individualized support, while discussing short- and long-term solutions and connecting you with additional resources when requested.
Religious Accommodation Policy
Washington state law requires that UW develop a policy for the accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy. Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form.
Academic Integrity
The University of Washington expects students to know their responsibilities and maintain the highest academic conduct standards (WAC 478-121). Students are held responsible for any violation of the University of Washington Student Code, irrespective of whether the violation was intentional or not. Students suspected of cheating or otherwise violating the misconduct code will be referred to the College disciplinary process. Behaving with integrity is part of our responsibility to our shared learning community. If you’re uncertain about whether something is academic misconduct, ask me. I am willing to discuss questions you might have. Acts of academic misconduct may include, but are not limited to:
- Cheating (working collaboratively on quizzes and exams, sharing answers, etc.).
- Plagiarism (using another person’s words or ideas without proper citation).
- Unauthorized collaboration (working with others on assignments without acknowledgment).
- Concerns about these or other behaviors prohibited by the Student Conduct Code will be referred for investigation and adjudication.
Disability Resources for Students (DRS)
Your experience in this class is important to me. It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law. If you have already established accommodations with Disability Resources for Students (DRS), please activate your accommodations via myDRS so we can discuss how they will be implemented in this course.
If you have not yet established services through DRS but have a temporary health condition or permanent disability that requires accommodations (conditions include but are not limited to mental health, attention-related, learning, vision, hearing, physical, or health impacts), contact DRS directly to set up an Access Plan. DRS facilitates the interactive process that establishes reasonable accommodations. Contact DRS at their website.
Use of AI
In this course, students are permitted to use AI-based tools (such as ChatGPT) on some assignments. The instructions for each assignment will include information about whether and how you may use AI-based tools to complete the assignment. All sources, including AI tools, must be properly cited. Detailed citation guidelines can be found at the UW Law Library, MIT Libraries, and the UMD Libraries. Using AI in ways inconsistent with the parameters above will be considered academic misconduct and subject to investigation.
Please note that AI results can be biased and inaccurate. It is your responsibility to ensure that the information you use from AI is accurate. Additionally, pay attention to the privacy of your data. Many AI tools will incorporate and use any content you share, so be careful not to unintentionally share copyrighted materials, original work, or personal information.
Learning how to thoughtfully and strategically use AI-based tools may help you develop your skills, refine your work, and prepare you for your future career. If you have any questions about citations or about what constitutes academic integrity in this course or at the University of Washington, please feel free to contact me to discuss your concerns.
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