1. Prepare a choropleth map showing the distribution of GDP per capita, 2016 at municipality level. 2. Calibrate an explanatory model to explain factors affecting the GDP per capita at the municipality level by using multiple linear regression method. 3. Prepare a choropleth map showing the distribution of the residual of the GDP per capita. 4. Calibrate an explanatory model to explain factors affecting the GDP per capita at the municipality level by using geographically weighted regression method.SMU Classification: Restricted 5. Prepare a series of choropleth maps showing the outputs of the geographically weighted regression model

1. To delineate social areas using hierarchical clustering technique and describe the analysis result 2. To delineate social areas using spatially constrained clustering technique and describe the analysis result

1st and 2nd order spatial point pattern analysis of airbnb listings in Singapore

1. Calibrating a simple linear regression to reveal the relation between public bus commuters’ flows (i.e. tap-in or tap-out) data and residential population at the planning sub-zone level. 2. Performing spatial autocorrelation analysis on the residual of the regression model to test if the model conforms to the randomization assumption. 3. Performing localized geospatial statistics analysis by using commuters’ tap-in and tap-out data to identify geographical clustering