Lectures and a weekly seminar, which will be devoted to problems.
- Properties of models.
- Nature of modeling processes.
- Deductive logic and syllogisms.
- Probability.
- Source of data.
- Data quality.
- Decision trees and utility.
- Indifference curve models.
- Linear programming models.
- Exchange models.
- Learning models.
- Diffusion models.
At the end of the course, the student will be able to:
- demonstrate the ability to think analytically about human behaviour;
- develop models relevant to economic analysis;
- evaluate a model’s implications and quantitatively confirm or refute the model’s consequences.
| Final examination | 30% - 40% |
| Mid-term examination | 30% - 70% |
| Assignments (3 or more) | 0% - 30% |
| Participation | 0% - 15% |
| Total | 100% |
THERE WILL BE A MINIMUM OF THREE (3) EVALUATIONS.
Students may conduct research as part of their coursework in this class. Instructors for the course are responsible for ensuring that student research projects comply with College policies on ethical conduct for research involving humans, which can require obtaining Informed Consent from participants and getting the approval of the Douglas College Research Ethics Board prior to conducting the research.
Textbooks and Materials to be Purchased by Students
Love, Charles A., and James G. March, An Introduction to Models in the Social Sciences, Latest Edition. Harper and Row, New York.
Courses listed here are equivalent to this course and cannot be taken for further credit:
- No equivalency courses