Based on five categories that I have chosen in the previous section,I partitioned those factors.

Part A: socio-economic factors
Part B: health related factors

In part A and B I build models and create result A and B.

In the end of the analysis, I will combine (WLC) the result of A and B to get a result of my project.







Part A: Socio-economic Factors

Converting a vector image to a raster one.

Creating 15 layers of social factors.

Creating a layer that shows the area where major minorities are not clustered.

Creating a layer shows the area where the ratio of people who spend more than 30% of income for their house (mortgage) and rent is high and also the average income is low.

The result of image shows the area that the ratio of people who work full year full time and part year or part time is low.

Creating a result of 7 socio-economic factors by WLC. From the background research the relationship between the income and the ratio of suicide is not straightforward, so I weighted less on the income related factors.







Part B: Health Related Factors

Converting a vector image to a raster image

Creating 8 layers of the health related factors.

Creating a result of the health related factors by WLC. I weighted less on the data 1996 than 2001 since they are old data.

Creating the final result of my project with the result of part A and B.