A bank is entering the Hong Kong retail banking market. To drive traffic to the bank’s website and help establish its residential mortgage business, the bank plans to develop an online property valuation tool. In this case study, students will help the bank to provide property valuation services by building simple linear regression models to predict the property price as accurately as possible. More specifically, students will learn to make simple exploratory data analysis, and data visualization and to use simple linear regression methods to build prediction models for properties with multiple variables.
Students will need access to the ACRC’s cloud-based Data Analytics Platform to access the dataset and do the analysis. The platform is currently in development. Please contact us at firstname.lastname@example.org if you are an educator who wishes to use the case for teaching purposes and needs access to the platform.
- Identify key variables influencing property prices and explore their distribution and correlation.
- Build simple linear regression models and explore fixed effect and interaction effect using R coding.
- Evaluate and compare the accuracy of various models.