Introduction
This dashboard explores the relationship between theft from motor vehicles and local unemployment across Victorian LGAs. Data are combined from CSA (crime) and ABS (unemployment) and aggregated to the year level.
Slide 1: Total incidents (all years)
Total incidents (all years)
282,950Slide 2: Victoria trend: crime vs unemployment
Victoria trend: crime vs unemployment
Slide 3: LGAs with biggest single-year unemployment jumps
LGAs with biggest single-year unemployment jumps
Slide 4: Change in crime vs change in unemployment (LGA level)
Change in crime vs change in unemployment (LGA level)
Slide 5: Conclusion and Next Steps
5. Story Summary and References
- Insight: The correlation plot in the previous frame suggests a moderate, but not universal, connection. While many LGAs saw both metrics rise (top-right quadrant), many others showed little change, proving that local socio-economic factors are more complex than just a simple jobless rate.
- Future Work: Further analysis should include other factors like population density, average income, and police resource allocation.
Assignment Details:
- Student Name: Kushagra Saluja
- Student Number: S4141640
Appendix / Data notes
- Crime data: local CSA extract; Offence subgroup = B42 Steal from
a motor vehicle.
- Economic data: ABS smoothed unemployment by LGA.
- Cleaning: LGA names normalised aggressively to allow joins.
- Limitations: inner join removes LGAs/years not present in both datasets.