STATS 720 : Stochastic Processes

Science

2024 Semester One (1243) (15 POINTS)

Course Prescription

Stochastic models and their applications. Discrete and continuous-time jump Markov processes. A selection of topics from point processes, renewal theory, Markov decision processes, stochastic networks, inference for stochastic processes, simulation of stochastic processes, and computational methods using R.

Course Overview

The course will cover both theory and applications.  Students will also have the opportunity to simulate stochastic processes and solve numerically for equilibrium distributions, etc., using R. The models studied in this course are used in a wide range of applications, including, for instance, biology, finance, engineering, telecommunications, and health delivery. Since 2020,  simple models of epidemic growth have been included in the applications.

Course Requirements

Prerequisite: STATS 320 or 325

Capabilities Developed in this Course

Capability 3: Knowledge and Practice
Capability 4: Critical Thinking
Capability 5: Solution Seeking
Capability 6: Communication
Capability 7: Collaboration
Graduate Profile: Master of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Understand stochastic models and their analysis, and demonstrate that understanding by solving problems related to stochastic models. (Capability 3, 4, 5, 6 and 7)
  2. Construct and apply appropriate models in a variety of settings. (Capability 3, 4, 5, 6 and 7)
  3. Describe and explain key concepts in the mathematics of stochastic processes, and be able to construct sound mathematical arguments relating to them. (Capability 3, 4 and 6)
  4. Share and communicate mathematical ideas and models. (Capability 6 and 7)

Assessments

Assessment Type Percentage Classification
Assignments 60% Individual Coursework
Tests 40% Individual Test
Assessment Type Learning Outcome Addressed
1 2 3 4
Assignments
Tests

Tuākana

Tuākana Science is a multi-faceted programme for Māori and Pacific students providing topic specific tutorials, one-on-one sessions, test and exam preparation and more. Explore your options at
https://www.auckland.ac.nz/en/science/study-with-us/pacific-in-our-faculty.html
https://www.auckland.ac.nz/en/science/study-with-us/maori-in-our-faculty.html

Key Topics

  • Markov processes in discrete and continuous time
  • Markov decision processes
  • Renewal theory
  • Stochastic networks

Special Requirements

Both tests will be held during class hours. There are no evening tests.

Workload Expectations

This course is a standard 15 point course and students are expected to spend 150 hours per semester involved in each 15 point course that they are enrolled in. 

For this course, a typical weekly workload includes:

  • 3 hours of lectures
  • 3 hours of reviewing the course content
  • 4 hours of work on assignments and/or test preparation

Delivery Mode

Campus Experience

Attendance is expected at scheduled activities including tutorials to complete components of the course.
Some lectures might be available as recordings. Other learning activities including tutorials will not be available as recordings.
Attendance on campus is required for the tests.
The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Course Notes:
  • Course notes will be posted to Canvas and distributed in lectures
Coursebook:
  • There is no coursebook, but a reading list will be available for students who wish to consult it

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

Based on student feedback, additional material will be published prior to lectures.
Interactive components of the course in the tutorial sections were very well received, and will be continued as in previous years.  Students who participate in these group activities have found them to be very valuable.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed for potential plagiarism or other forms of academic misconduct, using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Copyright

The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

The delivery mode may change depending on COVID restrictions. Any changes will be communicated through Canvas.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 06/11/2023 08:40 a.m.