The Greenwood statistic is a spacing statistic and can be used to evaluate clustering of events in time or locations in space.[1]
In general, for a given sequence of events in time or space the statistic is given by:.[1]
n+1 | |
G(n)=\sum | |
i=1 |
2 | |
D | |
i |
,
where
Di
Di=1
Where intervals are given by numbers that do not represent a fraction of the time period or distance, the Greenwood statistic is modified [2] and is given by:
G(n)= |
| |||||||||||||||
|
,
where:
n+1 | |
T | |
i=1 |
Xi,
and
Xi
A reformulation of the statistic yields
G(n)=\tfrac{1}{n+1}
2+1) | |
(\tfrac{n}{n+1}C | |
v |
,
where
Cv
The Greenwood statistic is a comparative measure that has a range of values between 0 and 1. For example, applying the Greenwood statistic to the arrival of 11 buses in a given time period of say 1 hour, where in the first example all eleven buses arrived at a given point each 6 minutes apart, would give a result of roughly 0.10. However, in the second example if the buses became bunched up or clustered so that 6 buses arrived 10 minutes apart and then 5 buses arrived 2 minutes apart in the last 10 minutes, the result is roughly 0.17. The result for a random distribution of 11 bus arrival times in an hour will fall somewhere between 0.10 and 0.17. So this can be used to tell how well a bus system is running and in a similar way, the Greenwood statistic was also used to determine how and where genes are placed in the chromosomes of living organisms.[3] This research showed that there is a definite order to where genes are placed, particularly with regard to what function the genes perform, and this is important in the science of genetics.