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#1
benbakelaar

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I have a polygon layer displaying povery rate by census tract (yes, the hated choropleth :D) and a point layer displaying fast food locations. Can I do a "correlation" function between the two to find out how related the poverty rate is to location? I know that doesn't exactly make sense... I've done statistical correlation before, which just gives you a variable with the relationship, but adding in "spatial", I'm confused about what the outcome is, as well as how to do it. Most of the information I see on the net on spatial correlation is using raster layers.

A. Can I do spatial correlation with vector layers? If so, how?
B. Can someone point me to an intro/tutorial to understand spatial correlation better?

#2
paul

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I'm not a stat guy, but...

You could use Hawth's Tools to get a count of fast food points in each census tract, and then plot number of fast food locations vs. poverty rate. Would that work?

http://www.spatialec...ls/tooldesc.php

#3
peanut

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As Paul says you can get a count of fast food points in each census tract. This can be done straight from the Spatial Join functionality in ArcMap.

In the ArcMap Table of Contents:

Right Click on your Census Tracts layer
Select Joins and Relates>>Join...
Where it says 'What do you want to join to this layer?' Select 'Join data from another layer based on spatial location
Where it says 'Choose the layer to join to this layer' Select your fast food locations
Then select the radio button 'Each Polygon will be given a summary of the numeric attibutes of the points that fall inside it...'

This will give you a table of the Census Tracts and fast food restraunt counts. Hope this helps.

Rich

#4
frax

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if you have spatial analyst, you could do a distance grid. that way you could calculate for each cell, what the distance is to the closest fast food place, then you could do an average for each census tract. That would also include fast food places that are close by, but outside the census tract (since people don't care about the census tract boundaries when they are hungry).

I have to raise some scepticism to doing this by census tract, and in vector though, I doubt that you will come up with something relevant.

I think you should go all raster with this, and try to distribute the poor in the tracts by cell. For distance, maybe it would be useful to use cost/distance as well, and try to model how and where people can move (not across water, for instance).
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#5
benbakelaar

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I have to raise some scepticism to doing this by census tract, and in vector though, I doubt that you will come up with something relevant.


Frax thanks for the tips! I too was skeptical of whether it would produce anything valuable. In general, the report I am helping my client produce will mention any "significant" statistics but both of us prefer not to draw sweeping conclusions based on weak stats :)

#6
frax

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I actually doubt that there would be any relevant relation between poverty and fast food outlets at all... :)
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