It's to help me double check my interpretation of a large dataset.

I have a collection of millions of traffic tickets. Each ticket has route
name, milepost, and lat/long. I want to see how well the tickets of a
particular route/milepost are to each other.

E.g., all tickets written for US 71, milepost 204--if they have a very large
dispersion, then either I have an error in my analysis or the data is not
good.

Aren

On Sat, May 28, 2011 at 2:32 AM, Ben Madin
<li...@remoteinformation.com.au>wrote:

> I'm not quite clear to me what you are trying to demonstrate - do you want
> to know the density of the points... relative to their total size (area /
> number?), or relative to some defined area?
>
> cheers
>
> Ben
>
>
> On 28/05/2011, at 6:19 AM, Aren Cambre wrote:
>
> Did anyone have thoughts on this? :-)
>
> Aren
>
> On Wed, May 4, 2011 at 2:12 PM, Aren Cambre <a...@arencambre.com> wrote:
>
>> The more I think about it, is this a job for R? I know I need to start
>> using R at some point, just haven't begun yet.
>>
>> Aren
>>
>>
>> On Wed, May 4, 2011 at 1:42 PM, Aren Cambre <a...@arencambre.com> wrote:
>>
>>> Suppose you have a geometry type with a multipoint. How would you
>>> calculate the variance of the points in that multipoint?
>>>
>>> I looked through the PostGIS 1.5 function reference and am not coming up
>>> with any easy way.
>>>
>>> A hard way seems to be using st_centroid(multipoint) to find the
>>> multipoint's  center. From there, I can calculate the distance of each point
>>> from its center, and use that towards calculating the variance (each
>>> distance is squared, all squared distances are added together, then divide
>>> by number of points).
>>>
>>> I guess my ultimate need is to measure relative dispersion of
>>> multipoints. The multipoints that have the most dispersion are suspect, but
>>> I need a way of identifying which ones are like this.
>>>
>>> Aren
>>>
>>
>>
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