419: Models of randomness in a variety of fields: actuarial studies, economics, biology, engineering, and others as appropriate for student population. Discrete time Markov chains, Poisson processes and generalizations, time series, Brownian motion, and dynamic programming. An important part of the course is an opportunity for a student to become involved in an actual modeling problem.
519: Models of randomness in a variety of applications. Discrete and Continuous Time Markov chains, Renewal processes and generalizations, queueing theory, time series, Brownian motion, and dynamic programming. Completion of basic linear algebra and probability is assumed.
419: Math 122 and at least one of Math 223, 311, 319, 360, 370
519: Linear algebra at the level of Math 122 and probability at the level of Math 360 is assumed.
Some experience using Excel, VBA, Mathematica, Maple, or Matlab will also be VERY helpful, but it is not strictly a prerequisite.
419 Follow-up courses: Math 436 Numerical Analysis, various statistics classes
519 Follow-up courses: various statistics classes
Tue, Thu 5:30pm-6:45pm in Pray-Harrold 3XX or 503 (PC Lab)
"Final Exam" schedule: Tue Apr XXnd, regular class time
Math 419: CRN xxxx, 3 credit hours.
Math 519: CRN xxxx, 3 credit hours.
Class meetings will be mostly interactive lectures, with some time to discuss homework.
Professor Andrew Ross
Pray-Harrold 515b
andrew.ross@emich.edu
http://people.emich.edu/aross15/
(734) 487-1064, but I strongly prefer e-mail instead of phone contact.
Math department main office: Pray-Harrold 515, (734) 487-1444
Office Hours: TBA
I am also happy to make appointments if you cannot come to the general office hours. Please send me e-mail to arrange an appointment.
The Mathematics Student Services Center (or "Math Lab") is also here to help you, in Pray-Harrold 220. Please give them a call at 734-487-0983 to find out their hours.
Many assignments in this course will be in the form of papers, which I want to be well written. I will be providing you with as much discipline-specific writing help as I can. You may also find it helpful to consult with the Academic Project Center for help in tuning up your writing.
Our required textbook is "Introduction to Probability Models", by Sheldon Ross (no relation to your instructor), published by Academic Press, 10 th edition.
The textbook might not be available at all the usual bookstores on and around campus, since the class is fairly small. The library has a page about class textbooks that includes bookstore addresses, and also information about the student government's Bookswap.
Also, please purchase a pack of 3-by-5-inch notecards. At the end of many class sessions, I will ask you to write out your thoughts on the class, to provide me feedback on how things are going. For example, you might write a one-sentence summary of the class session, then something about what the high point was (most important, coolest, or most clear) and what the low point was (least important, boring, or most-unclear-but-important-so-please-explain-it-better-tomorrow!) A pack of 100 notecards costs roughly $1.00
We will use the Blackboard system. You are expected to keep an eye on your scores using the system, and get extra help if your scores indicate the need.
Here is a list of books that I have found interesting and related to math modeling. Perhaps some of them will strike your fancy, too. I own the ones that are starred (*) and can lend them to you. Others you will have to find at the library or on the usual Internet booksellers. Links are given to Amazon, but I do not specifically endorse them or any particular bookseller. Of course, if you like a book you can see what similar books the online bookseller recommends.
Our primary goal is to teach you to be a good (or great!) stochastic math modeler. To be a good modeler, you need:
We have a few secondary goals, which may be more or less applicable to your personal situation:
We will start by reviewing basic probability ideas. We will also learn how to simulate a variety of random variables using Excel or Matlab (your choice)--doing little simulations will help understand a fair amount of the theory we will learn.
Time Series are used for a variety of things in economics and the various sciences. This will be the most statistics-oriented part of the class.
Dynamic Programming is a method of optimizing one's decisions as they unfold in time. It often includes some model of randomness, because we don't know what the future will hold. It is also used in some pattern recognition problems, such as speech recognition and genomic searches/ DNA alignment.
After that, we will talk about Discrete Time Markov Chains (DTMCs), which are used to model a wide variety of phenomena, from people moving between socio-economic classes to babies learning where one word ends and the next begins. Then, we will talk about Poisson Processes, which are useful for modeling the arrival of demands (like phone calls or customers) or other time-based phenomena (radiation particles, asteroids, etc.)
We will also study Renewal Theory, in which many of the results are completely intuitive, but there is one important result (called the Inspection Paradox) that takes some getting used to.
Queueing Theory is the study of how long people (or items) have to wait to be served.
Reliability Theory is in the book, but we will not cover it in this course unless there is a demand for it and some extra time.
Brownian Motion is the basis of a lot of stock market models. It is essentially a random walk. We will also look at some generalizations.
Course Topic Outline (the schedule is approximate, and the order may change based on the interests of people in the class)
|
Week(s) |
Topic |
Chapter |
|
1 |
Queueing |
none |
|
2 |
Preliminaries |
1,2,3 |
|
3 |
Time Series |
none |
|
4 |
Dynamic Programming |
none |
|
5-6 |
Markov Chains |
4 |
|
7-8 |
Poisson Processes, etc. |
5 ; final version of midterm project due at the end of week 8. |
|
9-10 |
Renewal Theory |
7 |
|
11-12 |
Queueing Theory |
8 |
|
13-14 |
Brownian Motion |
10; final version of final project due on the scheduled "final exam" day. |
By the end of the course, students will be able to:
Regular attendance is strongly recommended. There will be material presented in class that is not in the textbook, yet will be very useful. Similarly, there are things in the textbook that are might not be covered in class, but are still very useful. If you must miss a class, arrange to get a copy of the notes from someone, and arrange for someone to ask your questions for you.
My lectures and discussions mostly use the chalkboard, along with demonstrations in Excel and other mathematical software. I do not usually have PowerPoint-like presentations, and thus cannot hand out copies of slides.
Homework will be assigned about once a week. It will sometimes be a small problem set designed to help you understand the behavior of math models. Other times, it will involve writing up a little paper on an assigned topic. All homework should be typed.
Homework papers should be submitted on-line, where they may be checked by TurnItIn.com or a similar service. This is partly to help keep you honest, and partly to help you learn acceptable ways to cite the work of others. A side benefit is that sometimes TurnItIn finds papers relevant to your work that you would not have found otherwise!
Non-Project Assignments
There will be no exams. If you would like an interesting project, you could create a final exam for this course, along with a writeup justifying why each question is appropriate, and of course a solution key.
Instead of a mid-term and a final exam, you will do a mid-term and a final project. Your results will be reported in a paper and a presentation to the class. The grade for each project is split into:
The final presentations will be made during the time slot reserved for the final exam. If there will not be enough time to do all final presentations, then random selection or point-auction may be used.
No scores will be dropped, unless a valid medical excuse with evidence is given. In the unfortunate event of a medical need, the appropriate grade or grades may be dropped entirely, rather than giving a make-up, at the instructor's discretion. You are highly encouraged to still complete the relevant assignments and consult with me during office hours to ensure you know the material.
Your final score will be computed as follows:
Once final scores are computed, {Policy depends on the individual instructor. What follows is an example.}
We will use the following grading scale:
A 90-100,B 80-89, C 70-79,D 60-69,E Below 60
Whether you go into industry or academics, you will need to be able to write reports on the mathematical work you have done. Math 419 is designed to enable students to apply math modeling techniques to formulate and solve problems in applied mathematics/operations research. In this class, students learn how to present their findings in the format of a peer-reviewed scientific journal or technical report, and how to present their findings in the format of PowerPoint-type presentations. Of the final grade in Math 419, over 50 percent is based on the writing assignments. Students are provided with the tools to enable them to communicate successfully their modeling findings. They receive written and oral feedback on smaller, staged writing assignments, as well as opportunities for revision, providing them with the skills to improve their writing and excel at writing complete papers. Students will individually write two full-length math modeling papers and presentations (those with an interest in secondary education may substitute one lesson plan for a modeling paper). Students who successfully complete Math 419 have the ability to read critically and evaluate peer-reviewed journal articles and present their own research in the same format. As such, Math 419 meets the requirements of a Writing Intensive Course in the Major of the General Education program.
Side note:
Math 419W is distinct from Math 311W, Mathematical Problem Solving, because 419W projects focus more on applied work where a substantial part of the difficulty is figuring out what problem we want to solve-do we optimize today's operations, or our tactics for the next few months, or our long-term corporate strategy? Also, Math 419W projects often start with real-world data that students obtain from their workplaces. Formal mathematical proofs are only rarely a part of Math 419W, whereas they are a mainstay of 311W. Computer simulations, computations, and sensitivity analysis are important parts of most 419W projects, while they are not usually important in 311W. Math 419W tends to consider stochastic (random) phenomena, while 311W considers deterministic formulas.
In the last few semesters, I've asked my math modeling students to give advice to you, future math modeling students, based on their experiences in my course. Here are some of the highlights:
See any common themes?
Current University policy recognizes the rights of students to observe religious holidays without penalty to the student. Students will provide advance notice to the instructor in order to make up work, including examinations, they miss as a result of their absence from class due to observance of religious holidays. If satisfactory arrangements cannot be made with the instructor, the student may appeal to the school director or head(s) of department(s) in which the course(s) is / are offered.
Academic dishonesty, including all forms of cheating, falsification, and/or plagiarism, will not be tolerated in this course. Penalties for an act of academic dishonesty may range from receiving a failing grade for a particular assignment to receiving a failing grade for the entire course. In addition, you may be referred to the Office of Student Conduct and Community Standards for discipline that can result in either a suspension or permanent dismissal. The Student Conduct Code contains detailed definitions of what constitutes academic dishonesty but if you are not sure about whether something you are doing would be considered academic dishonesty, consult with the course instructor. You may access the Code online at: www.emich.edu/studentconduct/
Students are expected to abide by the Student Conduct Code and assist in creating an environment that is conducive to learning and protects the rights of all members of the University Community. Incivility and disruptive behavior will not be tolerated and may result in a request to leave class and referral to the Office of Student Conduct and Community Standards (SJS) for discipline. Examples of inappropriate classroom conduct include repeatedly arriving late to class, using a mobile/cellular phone while in the class session, or talking while others are speaking. You may access the Code online at www.emich.edu/studentconduct/
If you wish to be accommodated for your disability, EMU Board of Regents Policy 8.3 requires that you first register with the Students with Disabilities Office (SDO) in 240 EMU Student Center. You may contact SDO by telephone (734.487.2470). Students with disabilities are encouraged to register with the SDO promptly as you will only be accommodated from the date you register with them forward. No retroactive accommodations are possible.
The Family Educational Rights and Privacy Act (FERPA) is a Federal law designated to protect the privacy of a student’s education records and academic work. The law applies to all schools and universities which receive funds under an applicable program of the U.S. Department of Education and is applicable to students at EMU. All files, records, and academic work completed within this course are considered educational records and are protected under FERPA. It is your right, as a student in this course, to expect that any materials you submit in this course, as well as your name and other identifying information, will not be viewable by guests or other individuals permitted access to the course. The exception will be only when you have given explicit, written, signed consent. Verbal consent or email is insufficient.
The Student Exchange Visitor Information System (SEVIS) requires F and J students to report the following to the Office of International Students, 244 EMU Student Center within ten (10) days of the event:
Prior permission from OIS is needed for the following:
Failure to report may result in the termination of your SEVIS record and even arrest and deportation. If you have questions or concerns, contact the
OIS at 487-3116, not your instructor. Also, see the EMU SEVIS page.