Syllabus

Click here to download a PDF copy of the syllabus.

Teaching team & office hours

Instructor

Teaching Assistants

Course info

Textbooks

All books are freely available online. Print copies are also available for purchase.

Course Learning Objectives

By the end of the semester, you will be able to …

• describe generalized linear models (GLMs) as a unified framework.
• explain how specific models fit into the GLM framework, including extensions for correlated data.
• identify the appropriate model given the data and analysis objective.
• analyze real-world data by fitting and interpreting GLMs.
• use R Markdown to write reproducible reports and GitHub for version control and collaboration.
• effectively communicate results from statistical analyses to a general audience.

Course community

Duke Community Standard

As a student in this course, you have agreed to uphold the Duke Community Standard as well as the practices specific to this course.

Inclusive community

It is my intent that students from all diverse backgrounds and perspectives be well-served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that the students bring to this class be viewed as a resource, strength, and benefit. It is my intent to present materials and activities that are respectful of diversity and in alignment with Duke’s Commitment to Diversity and Inclusion. Your suggestions are encouraged and appreciated. Please let me know ways to improve the effectiveness of the course for you personally, or for other students or student groups.

Furthermore, I would like to create a learning environment for my students that supports a diversity of thoughts, perspectives and experiences, and honors your identities. To help accomplish this:

• If you feel like your performance in the class is being impacted by your experiences outside of class, please don’t hesitate to come and talk with me. If you prefer to speak with someone outside of the course, your academic dean is an excellent resource.
• I (like many people) am still in the process of learning about diverse perspectives and identities. If something was said in class (by anyone) that made you feel uncomfortable, please let me or a member of the teaching team know.

Accessibility

If there is any portion of the course that is not accessible to you due to challenges with technology or the course format, please let me know so we can make appropriate accommodations.

The Student Disability Access Office (SDAO) is available to ensure that students are able to engage with their courses and related assignments. Students should be in touch with the Student Disability Access Office to request or update accommodations under these circumstances.

Communication

All lecture notes, assignment instructions, an up-to-date schedule, and other course materials may be found on the course website, sta310-sp22.netlify.app

Announcements will be emailed through Sakai Announcements periodically. Please check your email regularly to ensure you have the latest announcements for the course.

Class support & resources

• If you have a question during lecture or lab, feel free to ask it! There are likely other students with the same question, so by asking you will create a learning opportunity for everyone.
• The teaching team is here to help you be successful in the course. You are encouraged to attend office hours to ask questions about the course content and assignments. Many questions are most effectively answered as you discuss them with others, so office hours are a valuable resource. Please use them!
• Outside of class and office hours, any general questions about course content or assignments should be posted on the class GitHub Discussion Forum. There is a chance another student has already asked a similar question, so please check the other posts before adding a new question. If you know the answer to a question posted in the discussion forum, I encourage you to respond!

Check out the Support tab for more resources.

Email

If there is a question that’s not appropriate for the public forum, you are welcome to email me directly with “STA 310” in the subject line. Barring extenuating circumstances, I will respond to STA 310 emails within 48 hours Monday - Thursday. Response time may be slower for emails received Friday - Sunday.

Activities & Assessment

The activities and assessments in this course are designed to help you successfully achieve the course learning objectives. Each activity and assessment is part of the prepare, practice, perform cycle for each topic.

• Prepare: Includes reading assignments and occasional videos to introduce new concepts and ensure a basic comprehension of the material.

• Practice: Includes in-class activities and application exercises to explore the topics new topics in more depth. These activities will be completed during lecture. As they are intended for practice, they will not be graded.

• Perform: Includes homework, quizzes, and the projects. These assignments are an opportunity for you to demonstrate your understanding of the course material and how it is applied to the analysis of real-world data.

Readings

There will be reading assignments to accompany each topic. Readings will primarily come from the course textbook Beyond Multiple Linear Regression, but they may periodically include articles and other resources. It is strongly recommended that you complete the readings before lectures, so you have an introduction to the topic before class.

Lectures

Lectures will be interactive with a mix of presenting lecture notes, short in-class activities, and application exercises. The activities and application exercises will give you an opportunity to explore concepts in more depth and get practice applying them to real-world data.

Homework

There will be about 5 homework assignments during the semester. In these assignments, you will apply what you’ve learned as you answer conceptual questions and complete guided and unguided analyses. You may discuss homework assignments with other students; however, homework should be completed and submitted individually.

The lowest homework grade will be dropped

Quizzes

There will be periodic short quizzes during the semester. These quizzes will cover the readings, lecture notes and activities, and any assignments since the previous quiz. More details about the format and content for each quiz will be available as they are assigned.

The lowest quiz grade will be dropped at the end of the semester.

Projects

There will be 2 mini group projects and 1 final individual project in this course. Teams will be randomly assigned for each of the mini projects. More details about each project will be available under the projects tab as they are assigned.

Grading

The final course grade will be calculated as follows:

The final letter grade will be determined based on the following thresholds:

Course policies

Academic honesty

By participating in this course, you agree to abide by the following when completing assignments:

• You may discuss individual homework and lab assignments with other students; however, you may not directly share (or copy) code or write up with other students. For team assignments, you may collaborate freely within your team. You may discuss the assignment with other teams; however, you may not directly share (or copy) code or write up with another team. Unauthorized sharing (or copying) of the code or write up will be considered a violation for all students involved.
• You may not discuss or otherwise work with others on the quizzes. Unauthorized collaboration or using unauthorized materials will be considered a violation for all students involved. More details will be given closer to the exam date.
• Reusing code: Unless explicitly stated otherwise, you may make use of online resources (e.g. StackOverflow) for coding examples on assignments. If you directly use code from an outside source (or use it as inspiration), you must explicitly cite where you obtained the code. Any recycled code that is discovered and is not explicitly cited will be treated as plagiarism.

Any violations in academic honesty standards as outlined in the Duke Community Standard and those specific to this course will automatically result in a 0 for the assignment and will be reported to the Office of Student Conduct for further action.

Late work & extensions

The due dates for assignments are there to help you keep up with the course material and to ensure the teaching team can provide feedback within a timely manner. We understand that things come up periodically that could make it difficult to submit an assignment by the deadline. Note that the lowest homework assignment will be dropped to accommodate such circumstances.

Late work policy

• Homework will be accepted up to 72 hours (3 days) after the due date. There will be a 5% deduction for each 24-hour period the assignment is late. A late waiver may be used for one homework assignment. See late waiver policy for more information.

• No late work is accepted on quizzes, and there are no makeups for missed quizzes.

• The late work policy for the project will be provided with the project instructions.

Late waiver for extenuating circumstances

If there are circumstances that prevent you from completing a homework assignment by the stated due date, you may email Professor Tackett before the deadline to waive the late penalty. In your email, you only need to request the waiver; you do not need to provide explanation. This waiver may only be used for once in the semester, so only use it for a truly extenuating circumstance.

If there are circumstances that are having a longer-term impact on your academic performance, please let your academic dean know, as they can be a resource. Please let Professor Tackett know if you need help contacting your academic dean.

Regrade requests

Regrade requests must be submitted on Gradescope within a week of when an assignment is returned. Regrade requests should only be submitted if a correct answer was mistakenly marked as incorrect. Requests to dispute the number of points deducted for an incorrect response will not be considered. Note that by submitting a regrade request, the entire question will be graded which could potentially result in losing points.

Attendance

You are expected to attend all lectures and labs with a fully-charged laptop or tablet with access to RStudio to participate. We understand there may be times when you are unable to attend a class meeting; in such instances it is your responsibility to make up the missed material. Labs will primarily be used to work on homework and the projects. If you miss a lab meeting dedicated to group work, please communicate with your teammates to make a plan to contribute to the assignment. Click here for more information on the Trinity attendance policies.

Attendance Policy Related to COVID Symptoms, Exposure, or Infection

Student health, safety, and well-being are the university’s top priorities. To help ensure your well-being and the well-being of those around you, please do not come to class if you have symptoms related to COVID-19, have had a known exposure to COVID-19, or have tested positive for COVID-19. If any of these situations apply to you, you must follow university guidance related to the ongoing COVID-19 pandemic and current health and safety protocols.

If you are experiencing any COVID-19 symptoms, contact student health at 919-681-9355. To keep the university community as safe and healthy as possible, you will be expected to follow these guidelines. Please reach out to me and your academic dean as soon as possible if you need to quarantine or isolate so that we can discuss arrangements for your continued participation in class.

Additional support

Academic Resource Center

The Academic Resource Center (the ARC) offers services to support students academically during their undergraduate careers at Duke. The ARC can provide support with time management, academic skills and strategies, unique learning styles, peer tutoring, learning consultations, learning communities, and more. ARC services are available free to any Duke undergraduate student, in any year, studying in any discipline.

Contact ARC@duke.edu, 919-684-5917.

Mental health and wellness resources

Student mental health and wellness is of primary importance at Duke, and the university offers resources to support students in managing daily stress and self-care. Duke offers several resources for students to seek assistance on coursework and to nurture daily habits that support overall well-being, some of which are listed below

• DuWell: (919) 681-8421, provides Moments of Mindfulness (stress management and resilience building) and Koru (meditation) programming to assist students in developing a daily emotional well-being practice. Click here to see schedules for programs please see. All are welcome and no experience necessary. duwell@studentaffairs.duke.edu, or studentaffairs.duke.edu/duwell

If your mental health concerns and/or stressful events negatively affect your daily emotional state, academic performance, or ability to participate in your daily activities, many resources are available to help you through difficult times. Duke encourages all students to access these resources.

• DukeReach: Provides comprehensive outreach services to identify and support students in managing all aspects of well-being. If you have concerns about a student’s behavior or health visit the website for resources and assistance. studentaffairs.duke.edu/dukereach
• Counseling and Psychological Services (CAPS): CAPS services include individual, group, and couples counseling services, health coaching, psychiatric services, and workshops and discussions. CAPS also provides referral to off-campus resources for specialized care. (919) 660-1000. studentaffairs.duke.edu/caps
• Blue Devils Care: A convenient, confidential, and free way for Duke students to receive 24/7 mental health support through TalkNow and scheduled counseling. bluedevilscare.duke.edu
• Two-Click Support: Duke Student Government and DukeReach partnership that connects students to help in just two clicks. bit.ly/TwoClickSupport

Technology Accommodations

Students with demonstrated high financial need who have limited access to computers may request assistance in the form of loaner laptops. For new Spring 2022 technology assistance requests, please go here. Please note that supplies are limited.

See the Support page for a more comprehensive list of academic and mental health wellness resources.

Important dates

• Jan 05: Classes begin
• Jan 17: Martin Luther King, Jr. Holiday - No classes
• Jan 19: Drop/add ends
• Mar 07 - 11: Spring break
• Mar 23: Last day to withdraw with W
• Apr 20: LDOC
• Apr 21 - 24: Reading period
• Apr 25 - 30: Final exams

Click here for the full academic calendar.