STAT 580: Stochastic Processes

Ivan Mizera (contact). Office hours: Tuesday and Thursday 12:30 - 13:30, and also after 15:20, if there is interest; otherwise by appointment
TR 14:00-15:20 CAB 457 (Sec A1)
Elements of stochastic processes. Discrete and continuous time Markov Chains; Birth and Death processes. Branching processes. Brownian Motion. General Stationary and Markov processes. Examples. Prerequisite: STAT 471 or consent of Instructor.
Teach working knowledge of several types of stochastic processes: in particular, discrete and continuous Markov chains; certain point processes; and finally Gaussian processes with special emphasis on the Wiener process (Brownian motion) and stochastic integration.
There is no single followed or required text. Useful sources for the technical details like statements and proofs of theorems, and also for additional exercises, are: The summaries of the results appearing in the lectures will be provided online; these documents sometimes serve as lecture notes, but more often constitute rather a handy study review.
The cumulative score will be computed from the performance in assignments (40%) (7-9 almost weekly assignments) midterm exam (20%) and the final exam (40%). This score will determine the final grade in the following manner: those who achieve 90% or more will get A; 76% or more qualifies for B; 60% or more guarantees C. Fine distinctions (+ and -) will be determined from the relative position of the student's score in class; also, one or several of the above cutpoints may be lowered if class circumstances render it necessary.
Grades are unofficial until approved by the Department and/or Faculty offering the course. Samples of past or representative evaluative course material will be made available through the course web page.
Students are supposed to attend all classes and actively participate in discussions and other class activities.
Students may use any notes written by their own hand; no other paper materials are allowed, especially no printed ones (books, photocopies, computer printouts). No access to the internet is allowed either; to prevent misunderstandings, cellphones, laptops and similar electronic devices are not to be brought to the exams. The exams will concentrate on the correct understanding of the material, testing it on suitable problems; therefore it is highly recommended that students work independently on the homework assignments and complement those by other exercises if necessary (starting from working out easy details in the lectures and summaries of results). The examinations will not involve any computational problems; however, computational assignments are deemed to be very helpful for gaining the proper understanding of the course material, and therefore are highly recommended.
Some part of the homework will involve exercises in computer generation of various stochastic processes, in a hope to bring deeper understanding of their underlying mechanism in this way. Students will thus have to do some, albeit simple, nevertheless programming, and possibly graphing of the result, in a computer language that facilitates such tasks, and the generation of (pseudo-)random numbers. The choice of software is not prescribed: R, Matlab, in past Mathematica and Maple, and recently also Python were successfully used by students in this course. The instructor is capable of providing the support in R and Matlab; the examples in the lectures will be mostly in R.
There are no deferred term exams. A student who cannot write a term examination or complete a term assignment because of an incapacitating illness, severe domestic affliction or other compelling reasons can apply for a deferral of the weight of the missed work to the final exam. To apply for an excused absence, a student must inform the instructor within two working days following the scheduled date of the term work or term exam missed, or as soon as the student is able, having regard to the circumstances underlying the absence. In all cases, instructors may request adequate documentation to substantiate the reason for the absence at their discretion. An excused absence is a privilege and not a right; there is no guarantee that an absence will be granted. Misrepresentation of Facts to gain a deferral is a serious breach of the Code of Student Behaviour.
A student who cannot write the final examination due to incapacitating illness, severe domestic affliction or other compelling reasons can apply for a deferred final examination. Students who failed at the start of term to request exam accommodations for religious beliefs are expected to follow the normal deferred final examination process. Such an application must be made to the student's Faculty office within two working days of the missed examination and must be supported by a Statutory Declaration (in lieu of a medical statement form) or other appropriate documentation (Calendar section 23.5.6). Deferred examinations are a privilege and not a right; there is no guarantee that a deferred examination will be granted. Misrepresentation of Facts to gain a deferred examination is a serious breach of the Code of Student Behaviour. If granted, the deferred final exam will be held from 9:00 to 12:00 (registration 8:30) on Saturday, January 13, 2018, CAB 357.
A student who writes the final examination and fails the course may apply for a re-examination. Re-examinations are rarely granted in the Faculty of Science. These exams are governed by University (Calendar section 23.5.5) and Faculty of Science Regulations (Calendar section 192.5.3). Misrepresentation of Facts to gain a re-examination is a serious breach of the Code of Student Behaviour.
The University of Alberta is committed to the highest standards of academic integrity and honesty. Students are expected to be familiar with these standards regarding academic honesty and to uphold the policies of the University in this respect. Students are particularly urged to familiarize themselves with the provisions of the Code of Student Behaviour and avoid any behaviour which could potentially result in suspicions of cheating, plagiarism, misrepresentation of facts and/or participation in an offence. Academic dishonesty is a serious offence and can result in suspension or expulsion from the University. All forms of dishonesty are unacceptable at the University. All forms of dishonesty are unacceptable at the University. Any offense will be reported to the Senior Associate Dean of Science who will determine the disciplinary action to be taken. Cheating, plagiarism and misrepresentation of facts are serious offenses. Anyone who engages in these practices will receive at minimum a grade of zero for the exam or paper in question and no opportunity will be given to replace the grade or redistribute the weights. As well, in the Faculty of Science the sanction for cheating on any examination will include a disciplinary failing grade (NO EXCEPTIONS) and senior students should expect a period of suspension or expulsion from the University of Alberta.
Electronic equipment cannot be brought to the examination rooms. Cell phones are to be turned off during lectures, labs and seminars. Cell phones are not to be brought to exams. Audio or video recording, digital or otherwise, of lectures, labs, seminars or any other teaching environment by students is allowed only with the prior written consent of the instructor or as a part of an approved accommodation plan. Student or instructor content, digital or otherwise, created and/or used within the context of the course is to be used solely for personal study, and is not to be used or distributed for any other purpose without prior written consent from the content author(s). updated