The course will employ a variety of instructional methods to accomplish its objectives, including some of the following: lectures, computer labs as well as practical exercises, and may include guest speakers, audio-visual presentations, and projects/presentations by students.
- The role of the crime and intelligence analyst in operational policing and public safety.
- Transforming raw data into actionable intelligence end-product for criminal justice purposes.
- Role of the crime analyst in addressing the following areas:
- preventing crime at problem places;
- controlling high-activity offenders;
- protecting repeat victims;
- facilitating crime reduction strategies and models; and
- addressing displacement.
- Role of the criminal intelligence analyst in addressing the following areas:
- applying models in intelligence analysis;
- leveraging information sharing systems
- ensuring data integrity and analyzing evidence;
- mining data and recognizing criminal patterns; and
- displaying quantitative information.
At the conclusion of the course the successful student will be able to:
- Describe the history of crime and intelligence analysis and its function
- Explain the difference between crime analysis, criminal intelligence analysis, and competitive analysis
- Explain and apply the different techniques utilized in strategic analysis, administrative analysis and tactical analysis
- Explain the relationship between crime analysis and intelligence analysis in the public safety domain
- Identify the role of analysis in addressing local, national, and trans-national crime
- Apply the intelligence cycle to the work of crime and intelligence analysis
- Explain the relevance and application of information systems to crime and intelligence analysis
- Articulate the relevance of a variety of policing models (e.g. traditional, community-based, intelligence-led, and problem-oriented)
- Comprehend current issues associated with crime and intelligence analysis (e.g. resistance to change and changing paradigms)
- Utilize computer software for statistical and geographic analysis of crime patterns
- Analyze and interpret crime patterns by synthesizing and applying all theoretical and practical knowledge gained in the course
Evaluation will be carried out in accordance with Douglas College policy. Evaluation will be based on the course objectives. The instructor will provide a written course outline with specific evaluation criteria at the beginning of the semester.
| Mid-term | 30% |
| Mini-Labs (4) | 20% |
| Final Project | 40% |
| Final Quiz | 10% |
| Total | 100% |
Texts and materials will be updated periodically as needed. An example of materials used are:
Boba, Rachel. Crime Analysis with Crime Mapping. Newbury Park, CA: Sage Publications, Inc. 2012, (3rd Ed).
Westphal, Christopher. Data Mining for Intelligence, Fraud & Criminal Detection: Advanced Analytics & Information Sharing Technologies. Boca Raton, FL: CRC Press (Taylor Francis Group), 2009.
Heuer, Richard J. Psychology of Intelligence Analysis. New York, NY: Novinka Books, 2006.
Courses listed here must be completed either prior to or simultaneously with this course:
- No corequisite courses
Courses listed here are equivalent to this course and cannot be taken for further credit:
- No equivalency courses