Statistical Data Benefits
Abstract
Criminal justice professionals rely on statistical data.
Research using inferential and descriptive research methods enable governments,
law enforcement personnel, policy makers, crime prevention experts and
corrections specialists to identify and implement anti-crime programs and
assess theories of the measurement of crime. Samples are chosen from population
groups and methods such as mean, median and mode are utilized. The focus for
criminal justice is to utilize statistical data for the safety of the general
public and for implementing future anti-crime programs and future policies.
How does statistical data benefit criminal justice? Society
is constantly evolving and changing. Statistical data allows criminal justice
systems to catch criminals, prevent repeat offending, implement cost-saving
programs, and shield society communities from harm. The first step for criminal justice
researchers is to formulate a question or attempt to solve a problem. For
instance, research was conducted during an eight-year period, from 2004- 2011,
wherein data was collected from over 908,000 calls taken from police data
collected in Brisbane, Australia. Based on the type of calls received, the hypothesis
is that a full moon phenomenon causes people’s behavior to be unusual or that
more chaos ensued when people acted as lunatics (Sheldon & Prunckun, 2017).
The Research Process
Once the researcher has acknowledged the problem or
formulated a question, the research process begins. In research, a sample is a subset
of the population. A population is a set of characteristics. These two are
necessary in the research process. Testing the hypothesis by taking a sample of
the population helps to prove or disprove theories. Once the sample is chosen
and research begun, data is then collected.
According to Rose, Hutchinson,
Willner, and Bastik (2018) a recent study shows that half of all inmates in a
Trinidad prison suffer from some type of mental illness which results in the
need for anger management referral of the inmate to a suitable program. Of the
Trinidad inmates, a sample of 132 men and women were involved in a research
study, participating in anger management intervention. Prisoners were assessed
after completing questionnaires to determine his or her suitability. One can
see how research is important in criminal justice. Research helps criminal
justice professionals solve issues and formulate hypotheses.
When to use
Descriptive and Inferential Statistics
When are descriptive and inferential statistics
appropriate in criminal justice? Graphs, pie charts, tables and numerical sums
compiled during the research process, enables descriptive data to be utilized
more readily. Inferential statistics taken from a population enables criminal
justice researchers to make assumptions, inferences, and predictions based on
compiled data. Inferential statistics are often generalized to the larger
population.
As previously stated, studying data and processing
information is a major part of criminal justice work. Inferential statistics
allow criminal justice professionals to predict outcomes, show probability of criminal
activity in a certain area, or make an inference as to what type of offender or
criminal may be in a neighborhood. Inferential statistics are appropriate when
known facts are being utilized, for instance, when one concludes that some
burglaries peak on a certain night of the week. Riley, Cohen, Knight, Decker,
Marson, & Shumway (2014) explain that descriptive statistics may show data
such as age, race, or psychiatric characteristics. These descriptions are
appropriate when using the data to capture trends of domestic violence victims
or a homeless population. Descriptive statistics are beneficial to criminal
justice researchers in that a single number summarizes a characteristic of an
entire sample or population through the process of tendency using mean, mode,
median.
Mean.
The first tendency process is mean. A mean gives the
mathematical average of a data set, such as the average age at which one
committed a first crime. Mean also includes numerical categories (social
status, race, gender, education status) or values measured numerically from a
scale beginning with zero (number of births, disposable income).
Mode.
The next measure of central tendency is mode. This is the
most common score the highest amount of times in a distribution set. Mode might
be the most common age when one first burglarized a home.
Median.
Another measure of central tendency is median. Median
represents the middle of the data results, for instance, the age in the middle
of a range at which one was first incarcerated. Median is rather simple to
calculate. Simply arrange all the numbers in order from lowest to highest. The
number exactly in the middle is the median.
Conclusion
Statistical data is a vital tool in
the work of criminal justice professionals. Solving a problem, collecting, and
analyzing data are important responsibilities. Reporting those research results
in the form of charts, graphs, and tables allows one to see descriptive
statistics. Law enforcement, administrators, public officials, policy makers,
court systems, and many others rely on the criminal justice system to protect
and guide the public on crime statistics. Choosing a sample from the population
and collecting data helps differentiate and break down descriptive and
inferential statistics. Taking these known facts helps one to predict future
outcomes.
Furthermore, analyzing and
predicting trends in crime and the ability to make predictions are crucial for helping
implement programs to deter crime, rehabilitate offenders, and protect society.
Computing data results with the use of mean, median, and mode allows for
validity and unbiased research results. Determining factors such as
characteristics of populations, the amount of times and locations of crime
occurrences, and finding the middle range of a set of characteristics all play
a role in the research of criminal justice.
References
Riley, E. D., Cohen, J., Knight, K. R., Decker,
A., Marson, K., & Shumway, M. (2014, September). Recent Violence
in a Community-Based Sample of Homeless and Unhoused Women with High Levels of
Psychiatric Comorbidity. American
Journal of Public Health, 104(9), 1657-1663.
Retrieved from http://eds.a.ebscohost.com/eds/detail/detail?vid=7&sid=f7a6b667-26c7-443b-a16e-58bbb0b682cb%40sessionmgr4008&bdata=JkF1dGhUeXBlPXNoaWImc2l0ZT1lZHMtbGl2ZSZzY29wZT1zaXRl#AN=97657673&db=eue
Rose, J., Hutchinson, G., Willner, P., Bastik,
T. (2018, November). The prevalence of mental health difficulties in a
sample of prisoners in Trinidadian prisons referred for anger management. Journal of Forensic practice, 120(4),
249-256.
Retrieved from http://eds.a.ebscohost.com/eds/detail/detail?vid=1&sid=c3f031a2-9fa2-45fc-b331-116a8f3821a8%40sdc-v-sessmgr01&bdata=JkF1dGhUeXBlPXNoaWImc2l0ZT1lZHMtbGl2ZSZzY29wZT1zaXRl#AN=edsemr.10.1108.JFP.03.2018.0011&db=edsemr
Sheldon, G., & Prunkun, H. (2017, January - June). When the full moon rises over the
sunshine state: a quantitative evaluation of Queensland police calls, 12(1),
129-130.
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