Important COVID-19 Modifications: Though this will operate as a normal "in-person" class, due to the novel coronavirus I will fully accommodate any and all students that, for any reason, choose to work remotely. It will be possible to participate in classes, as well as complete, turn in, and receive feedback on all work without being physically in the classroom. Students who do this will not be viewed, treated, or graded differently whatsoever.
Mask and Social Distancing Policy: Students must wear a mask throughout the entire time they are physically in the classroom. This means no eating or drinking in the classroom. Masks must fit properly and cover both the nose and mouth. If a student is unable to wear a mask for any reason, he or she should use the online accommodations being provided and not attend in-person. Students and the instructor should all maintain at least 6 feet of separation before, during, and after class while leaving. Failure to comply with the mask policy and/or social distancing policy may result in a lower course grade and/or being reported to the Dean.
Virtual Instruction Option: All students enrolled in this course may choose to attend it remotely, even if they have not registered with the university as a Remote Student. So long as they follow the other protocols described here, students may freely switch between in-person/remote learning in this course. Though I am already giving you permission to work remotely, please communicate with me and keep me updated about your situation. I want to make sure students don't disappear, and I want to help anyone experiencing health (or other) problems to avoid falling too far behind.
For those who exercise their right to attend class virtually, I will provide a robust virtual classroom experience. Consistent with the technology provided by the University, I will make class available contemporaneously and will include you in classroom participation. To the best of my ability, I will ensure that your experience is positive and that you are integrated fully into the academic experience. You are very welcome to give me feedback during the semester on how I can enhance your learning experience. I will live-stream all lectures on Zoom (links posted in Blackboard). I will also post recordings and materials from the lectures for students who need to view them asynchronously. In addition, I will provide links to a number of external resources that can potentially supplement/complement/replace the lectures. All assignments will be submitted electronically, regardless of whether you participate remotely or in-person.
Illness: You must stay home if you are feeling at all ill, have tested positive for COVID-19, or believe you may have been exposed to COVID-19. I will not penalize you in any way for being cautious. In an ordinary year, students might choose to come into the classroom when they feel like they have a cold coming on. This year is different, and I am trusting you to be vigilant, be cautious, and to stay home. In such a case, you can still participate fully through the remote instruction option. Note that this paragraph applies to me too as the Instructor. I will not come to campus if I am feeling at all sick, even if I think it's only a minor cold. Instead, I will send an email to the entire class with instructions/information on how to proceed. Should you need, you can contact the department chair Dr. Rothman (Sheldon.Rothman@liu.edu), or the Dean of Liberal Arts & Science Dr. Bowditch (Nathaniel.Bowditch@liu.edu).
Class Time: Monday 3:30p - 6:10p, Humanities 119.
Instructor: Dr. Corbett Redden. Corbett.Redden [att] liu.edu. Phone 516-299-3487 (voicemail only).
Office Hours: Tuesday and Thursday 12:30p - 1:50p, or by appointment. Office hours will be held on Zoom at the link posted in Blackboard. If you plan to attend Office Hours, please tell me beforehand. I won't be hanging out in an empty Zoom session if no one is coming.
Course webpage: http://myweb.liu.edu/~dredden/568f20/ and also Blackboard
Homework/Schedule: Coming Soon!
Textbook: "Introduction to Probability" (2nd edition) by Joseph K. Blitzstein and Jessica Hwang. Chapman & Hall/CRC Texts in Statistical Science, 2019. ISBN-13: 978-1138369917.
A free online version of the book based is available at http://probabilitybook.net. Print copies of the text may be purchased from CRC Press or Amazon.
Important Resources: Students are encouraged to utilize the existing resources for Harvard's Statistics 110: Probability course, for which the above textbook was written. The site contains the textbook, handouts, and more. Complete lecture videos are available on YouTube, and an online version of the course is freely available (in audit mode) on EdX. While none of these resources will be required for this MTH 568 course, they will provide students with extra layers of support and make it easier for me to differentiate instruction for certain subsets of students. I will include links to specific material as the course progresses.
Description from Catalog: Topics include classification of data, experimental design, hypothesis testing, unbiased and maximum likelihood estimators, nonparametric statistics, regression and correlation. (3 credits)
Linked Course: This course will be taught concurrently with MTH 51: Probability. Though the lectures will be same, I will make some distinctions within assignments and may require additional work for those enrolled in MTH 568. Because we will also cover many of the probability topics from Math 51, some topics listed in Math 568's course description may be emphasized less or even omitted. If you are particularly interested in any of these topics, please tell me in advance and I will ensure you learn them.
Software: An optional part of the course will involve RStudio, a user-friendly coding language designed for statistical analysis. An open-source desktop version can be freely downloaded here. For those students taking MTH 672, RStudio can also be downloaded through the Anaconda Navigator.
Grading Scheme:
Homework | 30% |
Tests | 40% |
Final Project | 30% |
Homework: I will assign homework every week based off the current lecture. Students should attempt to complete the assignment before next week's class, but the assignment will be due by Wednesday of the following week. For example, the first homework will be assigned on Monday 9/14 and due on Wed 9/23. While you may work with other students on homework, the writing and final document you turn in must be entirely your own. It should be written clearly and neatly as a final draft, not a hastily done rough draft. Homeworks will be photographed/scanned and uploaded into Blackboard. Assignments will be graded on some combination of effort, completeness, and correctness; the relative weighting may vary from week to week. Late assignments will not be accepted, but the lowest 3 homework scores will be dropped.
Tests: There will be two (possibly three, but probably two) Tests during the semester. The exact dates have not yet been determined, but they will be announced at least two weeks ahead of time. They will most likely be untimed take-home tests, possibly with an additional short "in-class" component that can be done physically in the classroom or remotely while on camera. You may not consult with anyone else on tests. Test problems will be adopted from problems appearing in lectures or homeworks.
Final Project: There will be a Final Project at the end of the semester. Details will be announced later in the course, but there will be varying ideas that each focus on particular topics such as: statistical software (e.g. R), probability/stats in Adolescent Education, the P1 Probability actuarial exam, and statistical analysis of experiments. Students may be required to give short presentations on their project during the final class meeting (12/7) and the Final Exam period (12/21 ? 1:50p-4:30p).
Attendance: You will not be graded on your attendance. However, your final grade is far more likely to receive a beneficial bump if you actively participate and/or attend regularly (in-person or remote).
Help: Help is available from a number of places and people. The resources at Stat110 are extremely valuable. You are welcome to ask Prof. Redden questions during class, Zoom office hours, or via email. Finally, you are encouraged to work with others on homework. Explaining concepts and techniques to fellow classmates is an excellent way for you to better understand them yourself.
Students with Disabilities: In compliance with the Americans with Disabilities Act of 1990 and to facilitate learning for all students, I will make accommodations for students with disabilities. It is necessary for those students to inform me of these accommodations by the end of the second week of classes. Please contact the Academic Resource Center (299-2937) so that steps can be taken to develop an appropriate educational plan. If you are a student with a documented disability, medical condition, or think you may have a disability, and will need accommodations, academic adjustments, auxiliary aids, or other services, please contact Marie Fatscher in Disability Support Services (Post Hall, Lower Level, C10) at 516-299-3057 or marie.fatscher@liu.edu to request services, accommodations or for additional information. Additional information is also available on the DSS website: www.liu.edu/post/dss
Technology: If you have problems, please contact IT (Library 236A, M-Th 8am-8pm and F 9am-5pm; it@liu.edu; 516-299-3300). You can access online tutorials for Blackboard as needed: http://www.liu.edu/Information-Technology/Info-Tech/Tutorials (Step by Step Guides and Videos)