This blog entry is dedicated to my colleagues in CASA, especially Andy Hudson-Smith, Ollie O'Brien and Fabian Nuehaus.
Yesterday I collected data from CASA's weather station for the 2009 calendar year. I have collated it for analysis and these are my first results.
The reason why I have written a blog entry for three weeks is that I have been writing a paper entitled `A Geographical and Temporal Analysis of Violent Crime in London in 2009' which hope to submit to a journal for publication. This has switched me on to the characteristics of violent crime that are different to other crimes. One of things I noticed was the affect of events such as New Year's Day had on violent incidents but also the weather.
I thought I would look into the weather aspect a bit further and I am able to thanks Andy and Ollie. The graph above does not look to promising. It shows the maximum temperature for each day in 2009 on the y-axis and the number of incidents that were allocated a code 1 class 'violence against person` and graded as an 'I` or emergency call on the x-axis. The result shows a very weak positive correlation. Nothing to get too excited about there then.
This where I thank Fabian for helping me to regard everything in police data as monitoring a machine (or a body) that has rhythms and cycles. Police incident data has rhythms and cycles that you can set your watch and calendar by.
An R squared of 0.4417 means that temperature is not the only influence on violent incidents, holidays, celebrations, special events all play their part. These in some cases may be a contributory mechanism by which temperature is an influence, (eg hot May Bank Holiday weekends) and in others may be a negative influence (eg colder New Year's day( not on a Saturday in 2009) or Halloween). In any case the R squared value represents a correlation of 0.6646 which is generally regarded as significant in social sciences.