For example, the United States Census combines their population data with crime data compiled from the FBI’s Uniform Crime Reporting system (UCR) to produce crime rates. These rates are calculated with a constant of 100,000 and are broken down by type of crime. As decribed by Sacco and Kennedy in The Criminal Event, the constant in the above equation is designed so the crime rate can be expressed per c (the constant) units of exposure. The selection of the constant is largely arbitrary, but rates are traditionally expressed per 1,000 or per 100,000 units of exposure. It is, although, most important to choose a value of c so the resulting rates will be meaningful to the reader. For example, if you are calculating crime rates for a town of 10,000 people, and you choose a value of c * 10,000, the results will be expressed in terms of a population greater than the town.
Consequently, the results will not be meaningful to the town residents. On the other hand, if a value of 100 were chosen, a resident reading the rates would see how many people in a group of 100 would be likely to be a victim of a given crime. In contrast to the constant, which is arbitrary, and the numerator which is provided by observations and reports, the denominator must be carefully determined for each type of crime. To determine this denominator the target population must be established. The target poplulation can be defined as “the population we want to talk about” (Mosteller, Fienberg, and Rourke, 1983).
The Essay on Hypothesis on the correlation between per capita income and violent crime rate
I am investigating a hypothesis that there is a direct correlation between a state’s income level and their violent crime rate, specifically the higher the income, the lower the occurrence of violent crime. I believe this is an important topic to study because if we can find a way to automatically increase one poor situation in a country (such as a high crime rate) by increasing another poor ...
“The usual practice is to use the total population residing within the jurisdiction in which the count of events has taken place” (Sacco and Kennedy, 1996).
Although, this method does not take into account “the demographic characteristics of the population or the empirical fact that different segments of the population are involved in criminal events with different levels of frequency” (Sacco and Kennedy, 1996).
Segments of the population can be created by looking at cross sections of age, sex and potential for victimization. Members of these segments may have a higher probability to being exposed to a particular crime then members of other segments. For example, people who spend a large amount of time outside their homes in the evening may have a higher potential of being a victim of a crime such as aggravated assault. If the entire population were used in the denominator, the calculated rate of aggravated assalts would be artificially high for the general population and artificially low for the segment of people who go out in the evening. In summary, when reviewing crime rates, the value of the denominator should be considered when drawing conclusions. If the denominator reflects the size of the total population residing within the measured jurisdiction, conclusions should reflect the possibility that subsets of the popluation may be incorrectly included in the calculated crime rate.
If a subset such as males aged 16 – 30, were used in the calculations, conclusions should consider the subset of the population which may be excluded.
