About this paper
| Paper title | Probability and Random Processes |
|---|---|
| Subject | Statistics |
| EFTS | 0.1667 |
| Points | 20 points |
| Teaching period | Semester 1 (On campus) |
| Domestic Tuition Fees ( NZD ) | $1,240.75 |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Prerequisite
- STAT 370, MATH 202 and MATH 203
- Contact
- Teaching staff
- Textbooks
Recommended reading:
- Grimmett, G.R and Stirzaker, D.R. (2001) Probability and Random Processes. Oxford University Press (3rd edition)
- Guttorp, P. (2018) Stochastic modeling of scientific data. CRC press
- Billingsley, P. Statistical Inference for Markov Processes
- Jones, P.W. and Smith, P. (2017) Stochastic Processes: An Introduction. CRC press
- Graduate Attributes Emphasised
interdisciplinary perspective, lifelong learning, scholarship, communication, critical thinking, ethics, information literacy, research, self-motivation, teamwork
View more information about Otago's graduate attributes.- Learning Outcomes
Students successfully completing this course will:
- Have knowledge of the mathematical foundations of probability theory
- Have understanding of the properties of common types of stochastic process models
- Apply probability and stochastic processes to model random phenomena
- Demonstrate autonomy and judgement in communicating technical results to others, including non-specialists
Timetable
About this paper
| Paper title | Probability and Random Processes |
|---|---|
| Subject | Statistics |
| EFTS | 0.1667 |
| Points | 20 points |
| Teaching period | Semester 1 (On campus) |
| Domestic Tuition Fees | Tuition Fees for 2025 have not yet been set |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Prerequisite
- STAT 370, MATH 202 and MATH 203
- Contact
- Teaching staff
- Textbooks
Recommended reading:
- Grimmett, G.R and Stirzaker, D.R. (2001) Probability and Random Processes. Oxford University Press (3rd edition).
- Guttorp, P. (2018) Stochastic modeling of scientific data. CRC press.
- Billingsley, P. Statistical Inference for Markov Processes.
- Jones, P.W. and Smith, P. (2017) Stochastic Processes: An Introduction. CRC press.
- Graduate Attributes Emphasised
interdisciplinary perspective, lifelong learning, scholarship, communication, critical thinking, ethics, information literacy, research, self-motivation, teamwork
View more information about Otago's graduate attributes.- Learning Outcomes
Students successfully completing this course will:
- Have knowledge of the mathematical foundations of probability theory
- Have understanding of the properties of common types of stochastic process models
- Apply probability and stochastic processes to model random phenomena
- Demonstrate autonomy and judgement in communicating technical results to others, including non-specialists