LEARNING OUTCOMES
Upon completing the course, the student
1. is familiar with the most common types of stochastic processes used in the modeling of random phenomena, and is aware of their underlying assumptions,
2. can apply stochastic processes to modeling and analyzing random phenomena,
3. is prepared to extend his/her knowledge to more sophisticated models, for example using the scientific literature in the field.
Credits: 5
Schedule: 01.11.2021 - 15.12.2021
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Jukka Kohonen, Anton Vavilov, Sari Salmisuo
Contact information for the course (applies in this implementation):
Lecturer: University Lecturer Jukka Kohonen
Head assistant: Anton Vavilov
Course assistants: Kristian Jakobsson, Oskari Honkasaari, Jerry Aunula
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
Random vectors and random processes. Markov chains. Branching processes. Random point patterns and Poisson processes. Population models, queues, and gambling.
Assessment Methods and Criteria
valid for whole curriculum period:
Exam and voluntary homework
applies in this implementation
The course grade g is determined by the exam and bonus points obtained from voluntary homeworks, online quizzes, and active participation according to formula:
g = f(e+b2/3),
where f is a monotone deterministic function, e = exam points (max 24), and b = bonus points (max 6). No bonus points are necessary for obtaining grade five. The bonus points are computed by
b = (h + q/3 + 4a) / 12,
where h = points from weekly homework problems (max 44), q = points from weekly online quizzes (max 48), and a = activity points (max 3). Activity points can be gathered from helping other students by asking helpful questions, answering others' questions (e.g. in Zulip forum), pointing out corrections to study materials etc. Attendance to lectures or exercise classes is voluntary and does not yield bonus points. Bonus points obtained during Autumn 2021 are valid in the exams of the academic year 2021–2022 which are held on:
- 15.12.2021
- 1.6.2022
Workload
valid for whole curriculum period:
Attending lectures 24 h (4)
Attending exercise classes 24 h (4)
Attending and preparing for the exam 2-32 h
DETAILS
Study Material
valid for whole curriculum period:
- L Leskelä. Stochastic processes. Lectures notes 2019.
- DA Levin, Y Peres. Markov Chains and Mixing Times. American Mathematical Society 2017.
- P Brémaud: Markov Chains, Springer 1999.
- VG Kulkarni. Modeling and Analysis of Stochastic Systems. Chapman and Hall/CRC 2016.
applies in this implementation
The primary reading material for the course is
- L Leskelä: Stochastic processes, lecture notes (will be updated during the course)
which is also available in Finnish. See Materials for more details and information about alternative study material.
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Period:
2020-2021 Autumn II
2021-2022 Autumn II
Course Homepage: https://mycourses.aalto.fi/course/search.php?search=MS-C2111
Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.
Details on the schedule
applies in this implementation
Lectures: Mon 10–12 and Wed 10–12 in Zoom. Before each lecture you are advised to do a short Preparatory quiz (see the Lectures and quizzes section).
Exercise classes: Twice per week, five exercise groups, see Sisu for details (time and place).
Remember to register to the course and to an exercise group in Sisu. For questions on practical matters concerning registering and exercises, contact the head assistant.