RPA307 - Statistical and Computer Applications in Valuation

Outline information
Semester
Schools offering this subject
Last revision date 2023-05-29 00:10:13.585
Last review date 2023-07-31 00:15:02.558

Subject Title
Statistical and Computer Applications in Valuation

Subject Description
This course will cover the theory and principles of computer assisted mass appraisal (CAMA) through illustrations and examples of practical applications, including case studies requiring hands-on computer work (using the SPSS software package). The material is meant to provide the student with a solid foundation in statistical analysis model building.

Students will explore creative, practical uses of statistical and computer applications in determining and analyzing real estate values and learn the fundamentals of exploratory data analysis and appraisal valuation modeling.

Credit Status
This is a credit subject applicable towards the Real Property Administration diploma program offered through the School of Legal, Public & Office Administration.
 
This is a credit subject applicable towards the Real Property Assessment certificate program offered through the University of British Columbia.
 
This is a credit subject applicable towards the AIMA and MIMA Designations with the Institute of Municipal Assessors.
 
This is a credit subject applicable towards the CRA and AACI Designations with the Appraisal Institute of Canada.

Learning Outcomes
Upon successful completion of this subject the student will be able to:

  1. Explain statistics, regression analysis, and key principles underlying application and testing. 
  2. Emphasize how statistics can be useful in a variety of areas of real estate practice, including appraisal and property tax assessment.   
  3. Pursue novel and creative solutions to vexing problems, using statistical and computer tools.            
  4. Use Computer tools (SPSS) for statistical analysis, with the understanding that software is simply a tool for applying the underlying methods, theory, and techniques. 
  5. Explore data for relationships of interest and to analyze data integrity.          
  6. Describe mass appraisal modeling principles and their applications in varying real estate contexts.   
  7. Test and evaluate model results in terms of quality, finding and repairing common errors, and assessing the reasonableness for practical application.      
  8. Evaluate results using sensitivity analysis to examine the impact of assumptions and inputs on outcomes.   
  9. Avoid common modelling pitfalls through effective quality control, data screening, consistent procedures, and accurate interpretation.       
  10. Explain how statistical analysis can benefit single-property appraisal applications, including benchmarking and adjustment support.             
  11. Describe the basis for automated valuation models (AVMs) and their advantages and disadvantages for real estate.         
  12. Describe the benefits of geographical information systems (GIS) and the potential they offer in real estate.
  13. Discuss issues surrounding statistical and computer applications in real estate, including incorporating these into culture of practice, professional standards, communicating results to clients and peers, and managing their expectations.

Essential Employability Skills

    •  Communicate clearly, concisely and correctly in the written, spoken and visual form that fulfils the purpose and meets the needs of the audience.

    •  Respond to written, spoken, or visual messages in a manner that ensures effective communication.

    •  Execute mathematical operations accurately.

    •  Apply a systematic approach to solve problems.

    •  Use a variety of thinking skills to anticipate and solve problems.

    •  Locate, select, organize, and document information using appropriate technology and information systems.

    •  Analyze, evaluate, and apply relevant information from a variety of sources.

    •  Show respect for diverse opinions, values, belief systems, and contributions of others.

    •  Interact with others in groups or teams in ways that contribute to effective working relationships and the achievement of goals.

    •  Manage the use of time and other resources to complete projects.

    •  Take responsibility for one's own actions, decisions, and consequences.

Academic Integrity
Seneca upholds a learning community that values academic integrity, honesty, fairness, trust, respect, responsibility and courage. These values enhance Seneca's commitment to deliver high-quality education and teaching excellence, while supporting a positive learning environment. Ensure that you are aware of Seneca's Academic Integrity Policy which can be found at: http://www.senecapolytechnic.ca/about/policies/academic-integrity-policy.html Review section 2 of the policy for details regarding approaches to supporting integrity. Section 2.3 and Appendix B of the policy describe various sanctions that can be applied, if there is suspected academic misconduct (e.g., contract cheating, cheating, falsification, impersonation or plagiarism).

Please visit the Academic Integrity website http://open2.senecac.on.ca/sites/academic-integrity/for-students to understand and learn more about how to prepare and submit work so that it supports academic integrity, and to avoid academic misconduct.

Discrimination/Harassment
All students and employees have the right to study and work in an environment that is free from discrimination and/or harassment. Language or activities that defeat this objective violate the College Policy on Discrimination/Harassment and shall not be tolerated. Information and assistance are available from the Student Conduct Office at student.conduct@senecapolytechnic.ca.

Accommodation for Students with Disabilities
The College will provide reasonable accommodation to students with disabilities in order to promote academic success. If you require accommodation, contact the Counselling and Accessibility Services Office at ext. 22900 to initiate the process for documenting, assessing and implementing your individual accommodation needs.

Camera Use and Recordings - Synchronous (Live) Classes
Synchronous (live) classes may be delivered in person, in a Flexible Learning space, or online through a Seneca web conferencing platform such as MS Teams or Zoom. Flexible Learning spaces are equipped with cameras, microphones, monitors and speakers that capture and stream instructor and student interactions, providing an in-person experience for students choosing to study online.

Students joining a live class online may be required to have a working camera in order to participate, or for certain activities (e.g. group work, assessments), and high-speed broadband access (e.g. Cable, DSL) is highly recommended. In the event students encounter circumstances that impact their ability to join the platform with their camera on, they should reach out to the professor to discuss. Live classes may be recorded and made available to students to support access to course content and promote student learning and success.

By attending live classes, students are consenting to the collection and use of their personal information for the purposes of administering the class and associated coursework. To learn more about Seneca's privacy practices, visit Privacy Notice.