Math 419W/519: (Intro to) Stochastic Math Modeling
Winter Semester 2021
Eastern Michigan University Creed
We believe the INTEGRITY of our work and the RESPECT we show for our fellow students, faculty, alumni and staff are an integral part of our ongoing EDUCATION.
We believe that the RELATIONSHIPS we have and those we continue to develop will support us as we learn and grow together as a community.
INTEGRITY adds value to our educational experience.
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EDUCATION allows us to develop socially, intellectually, and emotionally.
RELATIONSHIPS are the foundation of our growth.
Land Acknowledgement
The campus of Eastern Michigan University is located on the traditional territory (ceded in the 1807 Treaty of Detroit) of the Anishinaabeg, which refers collectively to the Ojibwe, Odawa, and Potawatomi (also known as the People of the Three Fires), and was also home to the Wendat/Wyandot people. This acknowledgement is included here to honor the elders and stewards of these heritages.
Official Course Catalog Entry
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.
Prerequisites
419: Math 122 and at least one of Math/Stat 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, R, or Python will also be VERY helpful (or Matlab, or to a lesser extent Maple or Mathematica), 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
Class Format and Meetings
Format: Synchronous Online, with recordings available if needed.
Meetings:
Tue, Thu 2:00pm-3:15pm in Zoom
"Final Exam" (actually, presentations) schedule: Tue Apr 27, 1:30-3:00 A HALF HOUR EARLY
Math 419W: CRN 24290, 3 credit hours.
Math 519: CRN 24288, 3 credit hours.
Class meetings will be mostly interactive lectures, with some time to discuss homework.
Instructor information
Professor Andrew Ross
Pray-Harrold 515m
andrew.ross@emich.edu
My homepage
(734) 487-1658, but I strongly prefer e-mail instead of phone contact.
Math department main office:
Pray-Harrold 515
(734) 487-1444
Office Hours and other help
Here is my complete schedule.
Mon/Wed: various meetings for research and with students
Tue/Thu:
1:30 2:00 office hours
2:00 3:15 Math 419W/519
3:15 4:00 office hours
Fri
11:00-12:00 once/month: department Colloquium (students invited!)
12:30- 2:30 once/month: department meeting
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 411.
Their hours are posted here.
Please give them a call at 734-487-0983 or just drop by.
However, very few tutors have taken Math 419W/519, so while it's a good place to work (meet with classmates, etc.) the tutoring might not be as good as it usually is for 100, 200, and 300-level classes.
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.
Required materials
Heavy use of a computer is required in this class. We will mostly use Excel and R/Rstudio, but Python is also acceptable. Many days, it will be best to have a laptop in class, but if you can't bring one, you can probably buddy up with someone.
We will use files from this webpage sometimes in class.
Recommended materials
Our recommended (not required) textbook is "Introduction to Probability Models", by Sheldon Ross (no relation to your instructor), published by Academic Press, any edition
Course Web Page
We will use the Canvas system. You are expected to keep an eye on your scores using the system, and get extra help if your scores indicate the need.
Supplementary Materials
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.
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*Sheldon Ross, Stochastic Processes (2nd ed.)
- The Flaw of Averages by Sam Savage/Probability Management (in EMU Halle Library, electronically)
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Stochastic simulation [electronic resource] : algorithms and analysis / Søren Asmussen, Peter W. Glynn
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Informal Introduction to Stochastic Processes with Maple, Jan Vrbik, Paul Vrbik
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Probability and Stochastic Processes with Applications, free online!, Oliver Knill (more advanced than our class)
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Applied Stochastic Processes in science and engineering, free online!, M. Scott (more advanced than our class)
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Stochastic process in physics and chemistry, N. G. van Kampen
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*Bhat and Miller, Elements of Applied Stochastic Processes (3rd ed.)
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*Yates and Goodman, Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers (2nd ed.)
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James Solberg, Modeling Random Processes for Engineers and Managers
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*Marcel Neuts, Probability
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*Sidney Resnick, Adventures in Stochastic Processes
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*Linda Allen, An Introduction to Stochastic Processes with applications to Biology
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*Edward Kao, An Introduction to Stochastic Processes
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The Nature of Code
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Guide to Excel statistical functions
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Simulation (uses ExtendSim)
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An Elementary Introduction to Queueing Systems by Wah Chun Chan
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Performance Modeling and Design of Computer Systems: Queueing Theory in Action by Mor Harchol-Balter
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http://www.math.vu.nl/~koole/obp/obp.pdf
http://www.win.tue.nl/~iadan/queueing.pdf
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Probabilistic Search for Tracking Targets: Theory and Modern Applications
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Stationary Stochastic Processes for Scientists and Engineers;
Georg Lindgren, Holger Rootzen, and Maria Sandsten
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An Introduction to Statistical Learning, with Applications in R by James, Witten, Hastie and Tibshirani (Springer, 2013). As of January 5, 2014, the pdf for this book will be available for free, with the consent of the publisher, on the book website.
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It's sort of like the NIST data analysis handbook:
http://www.epa.gov/caddis/index.html
CADDIS: The Causal Analysis/Diagnosis Decision Information System
Especially volume 4.
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Systems Biology: Mathematical Modeling and Model Analysis
Course Content
Course Goals
Our primary goal is to teach you to be a good (or great!) stochastic math modeler. To be a good modeler, you need:
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Good habits and procedures, just like a scientist,
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Knowledge of common math models, and
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Communication skills (writing and presenting), to publicize and get feedback on your models.
We have a few secondary goals, which may be more or less applicable to your personal situation:
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Get enough people together to form a few teams for the
Math Contest in Modeling (MCM),
usually in Jan or Feb.
I participated in this 3 times as an undergrad and had a lot of fun. It is also a good resume-booster.
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Give future teachers some great ideas to show your kids how high-power math is used in the real world. You may enjoy reading
Meaningful Math.
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Give computer-science students lots of interesting things to program. You may like reading this blog entry about
math for programmers.
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Get everyone using the appropriate software for each problem: Excel, Matlab/Octave, or perhaps R, Sage, Python, Mathematica or Maple.
Outline/schedule
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.
Schedule
See the schedule in our Coursepack (readings, Homeworks).
Also, here is the link for our Class Logbook where I paste in various stuff from "lecture" and we do our end-of-class writing/questions.
Detailed Learning Outcomes
By the end of the course, students will be able to:
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(General modeling skills):
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evaluate models by constructing simple test cases
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select the most important variables to start modeling with
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Sketch sensitivity-analysis graphs before commencing modeling
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(Communications skills):
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Write a technical report
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Differentiate between literature of varying quality, e.g. peer-reviewed vs. working paper vs. white paper vs. web site,
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Design appropriate figures to communicate models and results
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(Applied Time Series Analysis):
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Extract a trend from a data set
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Extract seasonality from a data set
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Examine residuals for autocorrelation
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(Discrete Time Markov Chains):
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Formulate a DTMC from the description of a situation.
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Find the steady-state distribution of a DTMC.
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Apply the steady-state distribution to compute performance measures.
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Compute transient distributions.
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519 (Continuous Time Markov Chains): similar to DTMCs, above.
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(Queueing):
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Apply basic queueing formulas (Little's Law, VUT) when approximating real-life situations
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Describe queueing situations in standard notation, so they can look up appropriate solution methods
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Describe the difference between single- and multi-server systems
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(Poisson Processes):
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Graphically test a data set to determine if it is a Poisson process
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Use the memoryless property when appropriate in analyzing Poisson processes and exponential random variables.
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(Renewal Processes):
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Graphically test a data set to determine if it is a renewal process
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Describe the effects of the Inspection Paradox
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(Dynamic Programming):
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Formulate deterministic DPs (value function and end conditions) according to a described situation.
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Formulate stochastic DPs (value function and end conditions) according to a described situation.
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(Brownian Motion):
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Simulate Brownian motion using a computer.
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Simulate some variants of Brownian Motion using a computer.
Grading Policies
Attendance
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.
If you are stuck on occasion without your usual child care, you may bring your child to class, and need not even get advanced permission (this is my personal policy--I don't know if EMU has a policy). Please be considerate to your classmates if your child becomes disruptive.
My lectures and discussions mostly use the document camera, along with demonstrations in Excel and other mathematical software. I sometimes have
PowerPoint-like presentations, and I distribute electronic copies.
Homework
Homework will be assigned about once or twice 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 via Canvas, 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!
Exams
There will be no exams unless the class has trouble being otherwise motivated.
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 along with rubric for grading incorrect answers.
Projects
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:
- 10 percent for the project proposal (due 3 weeks before the project paper),
- 10 percent for an annotated bibliography (due 2 weeks before the project paper)
- 30 percent for a mandatory complete draft (due 1 week before the project paper)
- 10 percent for doing a peer review of someone else's complete draft (due 2 days after complete draft)
- 30 percent for final version of project paper
- 10 percent for PowerPoint-style slides (and presentating them, for midterm project)
Project Guides
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 posters, random selection, or point-auction may be used.
Overall Grades
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:
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50 percent for all the homework together,
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20 percent for the mid-term project, and
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30 percent for the final project.
Once final scores are computed, we will use the following grading scale:
92.0 and above : A
88.0 to 92.0: A-
84.0 to 88.0: B+
80.0 to 84.0: B
76.0 to 80.0: B-
72.0 to 76.0: C+, etc.
Writing-Intensive Rationale
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.
Unofficial additional rationale thinking:
On the other hand, who says the current system of writing expectations in academia or industry is the best possible system?
The paragraph above is about learning to "play the game". If you are more interested in "changing the game" instead,
let me know (well in advance of due dates) and we can work together to try new things.
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.
Advice from Other Math Modelling Students
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:
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* work in groups * start the first day assignment is given * don't take too many credits w/ this class * ask a lot of questions * utilize Dr. Ross
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Do go to his office hours more than you normally would; if you have a question ask don't wait.
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See Prof. Ross in office hours and don't be afraid to email him. He is usually very helpful and approachable.
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Plan on visiting Prof. Ross during office hours in order to do well in the class. You will learn a lot in the end, but be ready to work.
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[prof ross:] add a note to the syllabus stating something to the effect of, "This class will not be like other math classes. Instead of straight-up
problems or proofs, the biggest amount of work will be setting up the models, exercises, etc. and in analysing what your results mean. It will not
be the mathematical work done to obtain the results that is the tricky part." But word the note better.
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attend the office hours Prof Ross is really good at explaining & helping out with the homework
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WORK TOGETHER!
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Go to class. Go to office hours and pick project that you're energized about and interested in even if they're harder. It will make this math class
the best one you've ever taken.
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If your project isn't working out, contact him ASAP and he'll work with you to find a new project. Don't drop the class!
See any common themes?
Standard University Policies
In addition to the articulated course specific policies and expectations, students are responsible for understanding all applicable University guidelines, policies, and procedures. The EMU Student Handbook is the primary resource provided to students to ensure that they have access to all university policies, support resources, and student's rights and responsibilities. Changes may be made to the EMU Student Handbook whenever necessary, and shall be effective immediately, and/or as of the date on which a policy is formally adopted, and/or on the date specified in the amendment. Please note: Electing not to access the link provided below does not absolve a student of responsibility. For questions about any university policy, procedure, practice, or resource, please contact the Office of the Ombuds: 248 Student Center, 734.487.0074, emu_ombuds@emich.edu, or visit the website: www.emich.edu/ombuds .
University Course Policies: https://www.emich.edu/studenthandbook/policies/academic.php
Student Handbook Link: https://www.emich.edu/studenthandbook/index.php
Graduate School Policies: http://www.emich.edu/graduate/policies/index.php
University Writing Center
The University Writing Center (115 Halle Library; 487-0694) offers one-to-one writing consulting for both undergraduate and graduate students. Hours are 10 a.m. to 6 p.m. Mondays through Thursdays and 11 a.m. to 4 p.m. Fridays. The UWC opens Monday, September 10, and closes Thursday, December 13.
The UWC also has several college and program satellite locations across campus. The locations and hours for the other satellites can be found on the UWC web site: http://www.emich.edu/ccw/writing-center/contact.php
Students seeking writing support at any UWC location should bring a draft of their writing (along with any relevant instructions or rubrics) to work on during the consultation.
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Hand hygiene practices, as well as appropriate cough etiquette, help reduce the spread of COVID-19. All individuals should regularly wash their hands with soap and water for at least 20 seconds. At a minimum, individuals should wash their hands before eating and after using the restroom, touching anything in a public area, or blowing their nose. Use hand sanitizer when needed (but not in place of handwashing when soap and water are available). Hand sanitizer stations are in all buildings.
Wellness and Community Responsibility
We expect every member of the campus community to follow these standards as part of our community commitment to safety. Students who do not comply with the University’s policy requiring face coverings and physical distancing are subject to the University’s Code of Community Responsibility. Questions regarding enforcement involving students should be directed to the Office of Wellness and Community Responsibility at emu_owcr@emich.edu or 734-487-2157.
In addition to the articulated course specific policies and expectation, students are responsible for understanding all applicable university guidelines, policies, and procedures. The EMU Student Handbook is the primary resource provided to students to ensure that they have access to all university policies, support resources, and student's rights and responsibilities. Changes may be made to the EMU Student Handbook whenever necessary, and shall be effective immediately, and/or as of the date on which a policy is formally adopted, and/or the date specified in the amendment. Electing not to access the link provided below does not absolve a student of responsibility. For questions about any university policy, procedure, practice, or resource, please contact the Office of the Ombuds: 248 Student Center, 734.487.0074, emu_ombuds@emich.edu, or visit the website at www.emich.edu/ombuds .
CLICK HERE to access the University Course Policies
Mental Health Support
EMU's Counseling and Psychological Services is here to help you with anxiety, depression, and many other difficulties. They are operating online rather than being shut down by the coronavirus.
Food Pantry
Swoop's Pantry (104 Pierce Hall, emich.edu/swoopspantry, 734 487 4173) offers food assistance to all EMU students who could benefit. Students are able to visit twice per month to receive perishable and non-perishable food items, personal hygiene items, baby items, and more. Students can visit our website for hours of operation and more information.
If you are in a position to donate to Swoop's, I encourage you to do so!