from the police interventions in the area under study in the years from 2014 - 2017, coming from the event journals of the

- Grid

- Sum number of foreigners per cell (also depending on their nationalities)

- Sum number of interventions per cell (also depending on their nationalities)

- Calculate the ratio between Foreigner/Inhabitants and Interventions/Inhabitants for each cell

- Linear Regression (Foreigner/Interventions, Foreigner(nonEU)/Interventions etc.)

- Queen 2 Weightfile

- Rates Calculated Map - Spatial Rate Smoothed Method to include spatial correlation using Geoda

- Describe method

- represent results using QGIS

- Morans I 

 Regarding the hotspots, a simple representation of the variables over the area has been applied. To observe existing neighbouring effects and to include a smoothening filter, the SRS was applied for both parameters using a Queen 2 weightsfile. 

[IIIIIIIIIIMMMMMMMMMMMAAAAAAAAAAAAGGGGGGGGGEEEEEEEEEEE  OOOOOOOOOOOFFFFFFFFF TTTTTTTTTTTTTHHHHHHHHEEEEEEEEE TTTTTTTTTTWWWWWWWWWWOOOOOOOOOOOO PPPPPPPPPAAAAAARRRRRRRAMMMMMMMM (smoothed, raw) OOOOOOON    TTTTTTTTTTTHHHHHHHHHHHEEEEEE  RRRRRRRREEEEEEEEEGGGGGGGIIIIIIIIIIOOOOOOOOONNNNNNNNNN]

To research the relation between the two parameters, we first used common statistical methods such as a regression of the data. In the following, the two scatterplots for the two parameters are presented. The first shows the regression and its statistics for the raw data, while the second shows the variable interventions with the percentage of Swiss inhabitants for the smoothed data according to the SRS and the Queens 2 weightfile. in FIGURE the points with a 100% foreign population are selected and the blue line shows the regression without those ten points. In the second scatterplot, the cells with < 50% Swiss citizens are selected and the blue line shows the regression when ignoring those.