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Statistics Assignment: Data Analysis In Police Force Of Colorado


Task: Primary Task Response: Within the Discussion Board area, write 400-600 words that respond to the following questions with your thoughts, ideas, and comments. This will be the foundation discussion by your classmates. Be substantive and clear, and use examples to reinforce your ideas.

In the following statistics assignment, choose a large municipal police department such as Chicago, New York, Los Angeles or your state police department and discuss the following:

• Summarize its history of the use of data analysis.
• How are the statistical variables such as mean, mode and median utilized in analysing criminal data?
• Explain how crime rates are calculated and utilized to address specific issues or problems with the data sets. Responses to Other Students: Response to at least 2 of your fellow classmates with at least a 100-word reply about their Primary Task Response regarding items you found to be compelling and enlightening. To help you with your discussion, please consider the following questions:
• What did you learn from your classmate’s posting?
• What additional questions do you have after reading the posting?
• What clarification do you need regarding the posting?
• What differences or similarities do you see between your posting and other classmates’ postings?


Data Analysis in Police Force: Colorado
The State Police Force of Colorado, selected to build this statistics assignment, has been utilizing advanced data analytics for the past two decades. Initially, the analysis process was very complicated and confusing due to disintegrated database systems. The recent advancements have helped the police forces of Colorado to solve the problem of integration and made data analysis more beneficial for the prevention and detection of crime. Cloud computing services and relational databases are the driving factors behind these benefits in Colorado Law and Order enforcement. The past applications of data analysis were confined to tracking location through digital signals for crime detection. The transition of data analysis in policing has gone from undefined analytics to predictive conclusionsthrough the Early Intervention Systems (EIS)(Lon?arski, 2016).

Mean, median, and mode of statistical analysis help the police departments narrow down the huge possible dataset while solving a crime or delivering criminal justice. For instance, if a particular crime occurs a certain number of times at the same place, the crime rate can be calculated under the percentage of a hundred. Thus, by analyzing different places, the probability of the crime can be explained. The results will help the force to further progress with a more particular direction in criminal justice. Mean, in this regard, provides the statistical average of a dataset (Lon?arski, 2016). Numerical categories like social status, gender identities, racial identity, birth specifications, etc., are also revealed through statistical analysis. This information helps the personnel involved in criminal justice find out the potential chance of a crime among specific groups. Median refers to the central tendency of a crime or criminal scenario. It helps eliminate the improbabilities from a set of intuition-based data systems and supports a faster solution to the problem.

Using the analytical results of predictive analysis, the police departments can create or detect a pattern of the criminal tendency among certain groups of people. For example, the young adult between the age of 15 to 17 can be the most criminally motivated in the juvenile crime of substance abuse. This probability data results from calculating the mode of a vast data set relating to juvenile crime under substance influence (Sax & Andersen, 2018). Again, the probability of theft or robbery in residential areas can be identified by predicting the statistical trend of a similar crime in different areas like urban, suburban, or rural places.In some cases of police investigation with data analysis, the average age of criminals and the target victims' age can be detected by calculating the median of an extensive database related to a similar crime. This information helps the police or law enforcement personnel to solve common categories of crime quickly without investing a lot of time and effort (Lin, 2018). Predictive analysis is also helping the police forces in preventing major criminal conspiracies, including threats to border security and terrorism. The ascending and descending arrangement of numbers also allows the police force to rate the probabilities of crime, thus helping crime prevention.

Response 1
The past systems included manual analysis of data with rudimentary analysis, digital signalling calculations, simple analytics for reading signals and predicting manually, and finally, predictive analysis. In the predictive analytical environment, the police departments used to apply the Early Intervention Systems (EIS) (Sax, & Andersen, 2018). This method identified inaccuracy in the results projected after analyzing data. This error trial system helped the police personnel in rejecting false directions. The Mode in this analytical system represents the highest possible probability of crime or the cause and effect relationship in any crime scene. For instance, the most common age of juvenile crime of sexual violence can be identified by mode of statistical analysis.

Response 2
After the EIS, the Personnel Management Software (PMS) appeared. This system records and analyzes location-based information, suspicious and unusual activities, and specific suggestions from hints of crime. An example of this method is the Benchmark Management System (BMS) (Van et al., 2017). It helped in capturing the critical sets of data in an integrated database. Automated dashboard of BMS reporting helped the police department further in utilizing data analytics. Another major invention is the Training Management Systems (TMS). This system allows the police forces to communicate across departments easily without any need to be physically meet with each individual in case of emergency advice and training. Integrated training management systems also help in the quick arrangement of forces for balancing disastrous situations.

Abkowitz, M., & Camp, J. (2017). Structuring an Enterprise Risk Assessment Protocol: Traditional Practice and New Methods. Risk Management And Insurance Review, 20(1), 79-97. DOI: 10.1111/rmir.12068
Lin, L. (2018). Integrating a national risk assessment into a disaster risk management system: Process and practice. International Journal Of Disaster Risk Reduction, 27, 625-631. DOI: 10.1016/j.ijdrr.2017.08.004
Lon?arski, I. (2016). Risk Management (2016). Statistics assignmentRisk Management, 18(1), 1-3. DOI: 10.1057/rm.2016.2 Sax, J., & Andersen, T. (2018). Making Risk Management Strategic: Integrating Enterprise Risk Management with Strategic Planning. European Management Review, 16(3), 719-740. DOI: 10.1111/emre.12185
Van der Kleij, R., Kleinhuis, G., & Young, H. (2017). Computer Security Incident Response Team Effectiveness: A Needs Assessment. Frontiers In Psychology, 8. doi: 10.3389/fpsyg.2017.02179


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