# How should I normalize my data - based on population of an area /neighbourhood or population of the entire city? [closed]

I am studying the driving's forces of crime in a particular city.

I have some independent values, e.g. percentage of the head of the household with low education per zone, the percentage of unemployed people per zone [...]

The percentage is related to the total population in each zone, and not from the total population of the whole city. I think if I use the absolute values it will give me some correlation (multicollinearity) among independent variable since that zone with more population tends to have also a higher number of people with low education, unemployed people and so on.

For example, instead of using the absolute value of the number of people with low education in a particular zone, maybe I should divide that value to the total population of that specific zone. This might help to avoid that such zones with higher population will not necessarily have a higher number of people with low level of education. Because a have difference in the size of zones and consequently the difference in their population.

## closed as too broad by PolyGeo♦Mar 27 '18 at 11:35

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

• Welcome to GIS SE! As a new user be sure to take its 2-minute Tour where you will see that there should only be one question asked per question. – PolyGeo Mar 27 '18 at 11:37
• Is this question asking: How should I normalize my data - based on population of an area /neighbourhood or population of the entire city? – GISKid Mar 28 '18 at 1:46
• Yes, that is the right question. I am sorry my English is not that good, I am learning. However, I meant normalize in the sense of scaling by ratio like population/area = Pop. Density. Thank you for your cooperation. – Patrik Silva Mar 28 '18 at 12:19