Course Structure
This is a scheduled online course that is completed over 15 weeks. The weekly work typically includes reading one or more chapters, watching an instructional video, and completing a multiple choice assignment. There are three term projects required and the course ends with a take-home final examination.
Course Details/Syllabus
- Course Description for BUSI 444
- Learning Objectives for BUSI 444 - detailed competencies to be achieved from this course.
Lesson No. 1: Review of Statistical Software and Valuation Modeling Basics
Lesson No. 2: Data Screening – Preparing Data for Modeling
Lesson No. 3: Land Value Modeling
Lesson No. 4: Cost-Based Modeling
Lesson No. 5: Sales-Based Modeling
Lesson No. 6: Advanced Sales-Based Modeling – Non-Linear Regression
Lesson No. 7: Income-Based Modeling
Lesson No. 8: Integrating Geographic Information Systems and CAMA
Lesson No. 9: Neural Network Applications in Real Estate Analysis
Lesson No. 10: The Canadian CAMA Experience
Prerequisites : BUSI 121 and 344. Recommend BUSI 330 and BUSI 443.
Software: IBM SPSS. See the Statistical Software webpage for more information.
Weekly multiple choice assignments: 10% of final grade
Project 1: Modeling Land Value and Cost Case Study: 20% of final grade
Project 2: Sales-Based Modeling Case Study: 20% of final grade
Project 3: Income Modeling Case Study: 10% of final grade
Comprehensive Case Study final examination (take-home) (40%): Completes BUSI 444 course requirement. Also eligible for credit towards IAAO's demonstration report requirement for its CAE, MAS, and RES designations or AIC's guided case study requirement for its CRA designation. Please note: students who complete BUSI 444 with a partner institution (e.g., Lakeland College, Seneca College) will receive course credit for their final examination, but in order to receive demonstration report credit, students must submit their examination to the UBC Real Estate Division for review along with a $100 review fee.
Additional Resources
See Table of Contents for the textbook for this course:
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