Name: Just the Class
Author: Haoyu Yue

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Data Analytics and Visualization

RE 519, Runstad Department of Real Estate, University of Washington, Autumn 2025
Monday & Wednesday, 2:30 - 3:50pm, Mechanical Engineering Building 245
Haoyu Yue (Pre-doctoral Instructor), [email protected], Schedule Office Hours

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Real estate decision-making requires the assessment of interdisciplinary datasets, which include socioeconomic, financial, and environmental data. Determining evolving patterns, analyzing and visualizing them, is critical in holistically assessing an area and a real estate decision to be made. This course aims to provide you with an opportunity to improve your coding ability and demonstrate that using R is more replicable and efficient than Excel.

We will work in groups to solve tricky data analytics & visualization problems. Of course, we will encounter a lot of new commands and new ways of thinking about how data is organized. However, we will most importantly learn how to understand the process of data analysis and how to best inform our audience and honestly describe the underlying data. The course is developed based on materials from Dr. Feiyang Sun at UC San Diego, Siman Ning, and Christian Phillips.

December 04, 2025

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Final Announcements

Dear all, as the quarter ends, I would like to appreciate your effort during the class! We saw lots of great projects and positive feedback in terms of the class. There are some final announcements about the class and maybe future study in data science.

Project Final Delivery and All Submissions: the final deadline for all submissions is December 12 (the last day of this quarter). For the project delivery, please check the details on class website.

Peer Review (within-group): I would like you to report how working with your group members went over the course of the quarter. The expectation is that you worked equally with your partner on the final project. If this was not the case, let me know, and I will adjust grades accordingly. Canvas Assignment Page.

Course Evaluation: this is a formal university-wide course evaluation. The system will be closed on December 5 (this Friday). Course evaluation is always important to any instructor, and I appreciate your input so we can develop and adjust the course going forward. The link to the Course Evaluation.

Future Study in Data Science: this class intends to be an introduction to data science and we briefly cover lots of aspects: programming in R, geospatial data, visualization, regression, machine learning, and large language models. If you are into any of those topics, I recommend studying online and taking classes at UW. This section lists some UW courses for reference.

I hope you will have a wonderful winter break, and please feel free to contact me if you have any questions in the future. Happy new year and holiday in advance!

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.