Spss in real estate research: choosing suitable analytical tasks
SPSS supports tabular statistics, group comparisons, survey scales and regression, while spatial questions may require GIS.
TECHNOLOGY · SPSS
Choose the question before the software
SPSS is useful for statistical analysis of well-structured real estate datasets. It does not replace research design, data validation or professional interpretation.
SPSS can summarize prices and sizes, compare groups, test hypotheses, analyze survey scales, estimate regression models and cluster observations. Method choice depends on measurement levels and research design.
- Descriptive analysis and outlier screening
- Group comparisons and statistical tests
- Scales, regression and clustering
Consider apartments with asking prices, area, location, room counts and distance to the center. Begin by checking summaries and distributions, then explore associations without treating correlation as proof of causation.
- Give each row a clear observational meaning
- Use consistent units and variable types
- Keep raw data and transformation records
GIS is more suitable for buffers, network travel and spatial overlay; databases organize operational records; 3D tools visualize buildings. SPSS contributes statistical analysis where appropriate.
- GIS for geographic relationships
- Spreadsheets and databases for data management
- SPSS for statistical models and interpretation
Note: This is an introductory article. Detailed examples and software workflows are available in the BDSNL SPSS series.
Introductory learning resource – Lecturer website of Nguyễn Mạnh Hùng.