Syllabus
Registration via LPIS
Day | Date | Time | Room |
---|---|---|---|
Tuesday | 03/05/19 | 11:00 AM - 01:00 PM | TC.3.01 |
Wednesday | 03/06/19 | 01:30 PM - 03:30 PM | TC.4.01 |
Tuesday | 03/12/19 | 11:00 AM - 01:00 PM | TC.3.01 |
Wednesday | 03/13/19 | 01:30 PM - 03:30 PM | TC.4.01 |
Tuesday | 03/19/19 | 11:00 AM - 01:00 PM | D4.0.022 |
Wednesday | 03/20/19 | 01:30 PM - 03:30 PM | TC.4.01 |
Tuesday | 03/26/19 | 08:00 AM - 10:00 AM | D5.0.002 |
Wednesday | 03/27/19 | 12:30 PM - 01:30 PM | TC.4.03 |
Tuesday | 04/02/19 | 11:00 AM - 01:00 PM | TC.3.01 |
Wednesday | 04/03/19 | 01:30 PM - 03:30 PM | TC.4.01 |
Tuesday | 04/09/19 | 11:00 AM - 01:00 PM | D4.0.022 |
Wednesday | 04/10/19 | 01:30 PM - 03:30 PM | TC.4.01 |
This is an undergraduate course which aims to provide students of Business Mathematics Specialization with the basic ideas of probability required for the study of Economics and related subjects.
After completing this class successfully the student will have the ability to:
- Define, describe and work with the basic concepts in probability,
- Understanding and modeling of random phenomenon,
- Use methods and ideas from probability to solve simple real-world problems.
Full attendance is compulsory. This means that students should attend at least 80% of all lectures, at most one lecture can be missed.
The course consists of lectures and accompanying weekly tutorials The lecture part presents the theoretical concepts and gives examples. Students can work out a project in applied probability related to the taught material.
- 20% weekly tutorials
- 45% final exam
- 35% project in applied probability
There will be no opportunity to retake the final exam. The exam is a closed-book exam!
Successful completion of Analysis and Linear Algebra course is necessary.
Unit | Date | Contents |
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1 | Sample spaces, probability measures, computing probabilities. Reference: Handout |
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2 | Univariate probability distributions. Reference: Handout chapter 2. |
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3 | Univariate probability distributions. Reference: Handout chapter 2. |
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4 | Applications. Reference: Handout chapter 3. |
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5 | Multivariate probability distributions. Reference: Handout chapter 4. |
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6 | Multivariate probability distributions. Reference: Handout chapter 5. |
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7 | Limit laws, CRR model. Reference: Handout chapter 6. |
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8 | Limit laws, CRR model. Reference: Handout chapter 6. |
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9 | Monte Carlo simulation. Reference: Handout chapter 7. |
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10 | Projects. |
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11 | Projects |
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12 | Final Exam |
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