Show Navigation
|
Hide Navigation
How Mean Center (Spatial Statistics) works |
|
|
Release 9.2
Last modified January 9, 2009 |
|
The mean center is the average x and y coordinate of all the features in the study area. It's useful for tracking changes in the distribution or for comparing the distributions of different types of features.
Potential applications
- A crime analyst might want to see if the mean center for burglaries shifts if evaluating daytime versus nighttime incidents. This can help police departments better allocate resources.
- A wildlife biologist can calculate the mean center of elk observations within a park over several years to see where elk congregate in summer and winter to provide better information to park visitors.
- Analyze level of service—Compare the mean center for 911 emergency calls to the location of emergency response stations. Or, evaluate the mean center weighted by individuals over the age of 65 to determine ideal locations for senior services.
Output
The Mean Center tool creates a new point feature class where each feature represents a mean center (one for each case when a case field is specified). The x and y mean center values, case, and mean dimension field are included as output feature attributes. The following identifies the possible origin of a disease epidemic.