MA4710
Regression Analysis
College of Science and Arts
Summer 2020

Course Website(s)

• Canvas - www.courses.mtu.edu

Required Course Text

• Chatterjee, S. & Hadi, A. S. (2012). Regression analysis by example (5^th edition). John Wiley & Sons, Inc.

You should have already downloaded and installed the R programming language and RStudio from these sites:

• R Programming Language
• RStudio

Piazza: Your instructor will also make use of Piazza to provide supporting discussions each week and group collaboration for your final project. Be sure to review the Weekly Collaborative Discussion Space: Piazza in Week 1. Review the Welcome to Piazza page and review the discussion topics for each week.

Please also read the Meet Your Instructor & Course Introduction page in Week 0 of the course for further materials suggestions.

Milana Tarbuk, Student Success Advisor

Email: Milana.Tarbuk@onlinedegrees.mtu.edu

• Phone: 906.275.2035 (9 a.m. to 6 p.m. EST)
• Text: 906.214.2734 (9 a.m. to 6 p.m. EST)

Upon successful completion of this course, students will be able to:

• Fit a multiple regression model using the R programming language.
• Effectively communicate a summary of a linear regression analysis.
• Assess the linear regression model assumptions from a given set of data.
• Implement corrective measures to address any violated assumptions in a linear regression model.

I - Incomplete; given only when a student is unable to complete a segment of the course because of circumstances beyond the student’s control.

X - Conditional, with no grade points per credit; given only when the student is at fault in failing to complete a minor segment of a course, but in the judgment of the instructor does not need to repeat the course. It must be made up by the close of the next semester or the grade becomes a failure (F). A (X) grade is computed into the grade point average as a (F) grade.

Grading Policy

Please read the Meet Your Instructor & Course Introduction page in Week 0 of the course for further explanation of graded work in this course.

Grades will be based on the following:

Late Assignments

Homework assignments can be accepted up to two days past their deadlines, with a penalty of 20% for each day past day 7 that they are submitted.

You might be able to submit assignments past their due date without a late penalty upon prior approval by your instructor, but such approvals will be a rare exception to the rule.

We are all members of an academic community where it is our shared responsibility to cultivate a climate where all students/individuals are valued and where both they and their ideas are treated with respect.

Students may discuss homework assignments (if authorized), but are expected to individually work/write/solve any and all submitted work. All authorized resources used, including but not limited to internet sites (i.e. Chegg, Study Soup, Course Hero, etc.), should be appropriately cited. Please restrict all use of cell phones and/or other electronic devices during class to course-related activities. The focus of class time should be interaction between students, and with the instructor. Any other unauthorized activities are likely to be distracting to other students and the instructor. Please make sure to bring a calculator with you to class, so you can be appropriately prepared for assignments and/or exams. Calculators on other devices (computers, phones, etc.) are not allowed to ensure students do not communicate with others during exams. Because it’s important to everyone at Michigan Tech that academic standards be maintained, academic misconduct may result in an appropriate conduct sanction/educational condition(s) imposed by the Office of Academic and Community Conduct and/or in an academic penalty (lower grade/failing grade) imposed by the faculty.

For more details on academic integrity, please check the Academic Integrity Policy of Michigan Tech.

Student work products (exams, essays, projects, etc.) may be used for purposes of university, program, or course assessment. All work used for assessment purposes will not include any individual student identification.

Michigan Tech has standard policies on academic misconduct and complies with all federal and state laws and regulations regarding discrimination, including the Americans with Disabilities Act of 1990. For more information about reasonable accommodation for or equal access to education or services at Michigan Tech, please call the Dean of Students Office (906) 487- 2212) or go to University Policies for Course Syllabi.

Many useful resources are available at the J. Robert Van Pelt and John and Ruanne Opie Library.

Michigan Tech IT is available Monday - Friday from 8:00 am - 5:00 pm.

Additionally, support can be obtained from Michigan Tech's Support Channels.