AIC344 - Statistical and Computer App. in Valuation

Outline info
Last revision date 2018-07-20 13:29:38.856
Last review date 2018-07-20 13:29:47.167

Subject Title
Statistical and Computer App. in Valuation

Subject Description
This subject is intended to give students a working knowledge of how statistics and computer applications can be applied in real estate, with a particular focus on valuation.The subjects covers theory and principles, illustrations and examples of practical application, plus case studies requiring hands-on computer work (e.g., using the software packages SPSS, NCSS, and Excel). The material is intended to be introductory in nature; it is important to keep in mind that study of this subject by itself does not certify students as qualified mass appraisal model builders. However, the subject should give students a solid foundation in statistical analysis and model building which can be further enriched by real-world practice. Note that this subject has been recognized by many employers and professional groups as meeting entry level employment requirements and educational course requirements for professional accreditation.

Credit Status
This is a credit subject applicable towards the Appraisal Institute of Canada's CRA and AACI designations, as well as University of British Columbia's(UBC) Diploma in Urban Land Economics. Successful completion of the AIC course components of the program also earn students 50-60 degree credits toward the Bachelor of Business in Real Estate Program (BBRE) offered by the University of British Columbia (UBC) and Thompson Rivers University (TRU).

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

1. Explain regression and the statistics underlying its 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 (such as Microsoft Excel, SPSS, and NCSS) for statistical analysis, with the understanding that software is simply a tool for applying the underlying methods, theory, and techniques which are applicable to any software package.

5. Explore data for relationships of interest and to analyze data integrity.

6. Explain how statistical analysis can benefit single-property appraisal applications, including market identification and choosing a unit of comparison.

7. Describe mass appraisal modelling principles and their applications in varying real estate contexts.

8. Test and evaluate model results in terms of quality, finding and repairing common errors, and assessing the reasonableness for practical application.

9. Evaluate results using sensitivity analysis, to examine the impact of assumptions and inputs on outcomes.

10. Avoid common modelling pitfalls through effective quality control, data screening, consistent procedures, and accurate interpretation.

11. Describe the basis for automated valuation models (AVMs) and their advantages and disadvantages for real estate.

12. Describe the benefits of geographic 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 the culture of practice, professional standards, communicating results to clients and peers, and managing their expectations.

Cheating and Plagiarism
Each student should be aware of the College's policy regarding Cheating and Plagiarism. Seneca's Academic Policy will be strictly enforced.

To support academic honesty at Seneca College, all work submitted by students may be reviewed for authenticity and originality, utilizing software tools and third party services. Please visit the Academic Honesty site on for further information regarding cheating and plagiarism policies and procedures.

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

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 Disabilities Services Office at ext. 22900 to initiate the process for documenting, assessing and implementing your individual accommodation needs.



There are no formal pre-requisites for this course and it is designed to be an introduction to statistics and computer applications in real estate. However, it may be helpful if students have completed AIC(BUSI) 121 and 330 prior to taking this course. While AIC(BUSI) 344 is introductory in nature, a background in real estate statistics and valuation will serve as a solid foundation on which to build upon in this course.

Topic Outline
LESSON NO. 1 - Statistical Foundations for Real Estate Analysis

LESSON NO. 2 – Statistical Software Applications for Real Estate Analysis

LESSON NO. 3 - Exploratory Data Analysis

LESSON NO. 4 - Market Identification and Characterization

LESSON NO. 5 - Valuation Case Studies

LESSON NO. 6 - Basics of Model Building

LESSON NO. 7 - Model Building Using Multiple Regression Analysis

LESSON NO. 8 - Comprehensive Model Building – Data Screening and Testing

LESSON NO. 9 - Number Nine Automated Valuation Models (AVMs)

LESSON NO. 10 - Geographic Information Systems (GIS)

Mode of Instruction
Students learn through classroom lectures and hands-on assignments during classroom hours. There are homework assignments. Students must have ready access to a computer with SPSS or NCSS for Windows in order to complete assignments and project work.

Prescribed Texts
Statistical And Computer Applications In Valuation, Course Workbook, University of British Columbia. Latest edition.

Note: Photocopied texts are not permitted.


Reference Material

Required Supplies

There are no financial calculations in this course, so a business calculator is unnecessary – a simple mathematical calculator will suffice.

Use of statistical software. Several lessons in this course requires the use of a statistical software program. SPSS version 15.0 was used in producing the examples in this workbook (other versions produce similar results). Please note that this software is not included as part of the course materials and must be purchased separately. While the use of this program is introduced as a part of the course, a working familiarity with the SPSS is required before starting the lessons.

All students must have access to a personal computer when taking any Appraisal Institute course. You will find that a computer is a necessary tool in preparing and submitting your assignments, viewing your assignment answer guides, and for creating effective study notes to help you prepare for your examination. Students should also ensure that they have a high-quality printer (e.g., an inkjet or a laser) which will provide clear printouts of information from the Real Estate Division website.

All students must arrange for some form of Internet access. All of the Appraisal Institute’s courses offer numerous online course resources. Students should ensure they have Internet access prior to beginning their course work.

Promotion Policy

Grading Policy
A+ 90%  to  100%
A 80%  to  89%
B+ 75%  to  79%
B 70%  to  74%
C+ 65%  to  69%
C 60%  to  64%
D+ 55%  to  59%
D 50%  to  54%
F 0%    to  49% (Not a Pass)
EXC Excellent
SAT Satisfactory
UNSAT Unsatisfactory

For further information, see a copy of the Academic Policy, available online ( or at Seneca's Registrar's Offices.

Modes of Evaluation
Since this is a professional credit course, marking standards reinforce professional practice by demanding legible, neat documents. Material should be grammatically correct as a result of accurate proofreading, proper spelling and punctuation. Late assignments are penalized at the discretion of the instructor.

Students should be aware that absenteeism will almost guarantee their inability to achieve satisfactory grades. There is no formal provision for make-up tests to replace tests missed due to absenteeism.

Students must pass final examination to pass the course.

Students who are absent for more than three classes may be asked to withdraw, at the discretion of a Promotion Committee.


  • A minimum grade of 50% on the final examination and 50% overall in the course is required to obtain a Seneca credit.           
  • Requirements for the UBC Certificate in Real Property Assessment require a minimum grade of 50% on the final examination and a minimum overall grade of 60% in the course.  
  • Requirements for credits with the Institute of Municipal Assessors and the Appraisal Institute of Canada require a minimum grade of 50% on the final examination and a minimum overall grade of 60% in the course.
Grading is based on the following marking scheme:
Assignments (multiple choice) 10%
Project No. 1 15%
Project No. 2 25%
Final Exam 50%

Project 1: Statistical And Computer Valuation Applications (15%)

In this project, students are expected to apply the statistical methods illustrated and Lessons 1-5 to provide market analysis and support for determination of selling prices for strata condominium units in a proposed residential project.  This assignment reflects a common scenario for real estate consultants: provide a client with market intelligence to correctly position a residential project for the target market segment.

Project 2: Valuation Modelling Case Study (25%)

This project requires students to create a valuation model based on a database of property sales. Students write a report describing their conclusion and the procedures used to obtain these results.

Final exam: Multiple choice and short-answer written questions: 50% of final grade.

Please keep this document for future reference.  It will be required if you apply to another educational institution and seek advanced standing.

Academic Program Manager:
Emiliano Introcaso

Approved by: Academic Program Manager Emiliano Introcaso