Course Policies
Assessments
It is my intent to design assessments that are a source of intellectual curiosity, joy, and learning rather than a source of stress. Assessments serve the purpose of measuring how much you have learned (i.e. how much you have achieved of the course goals). I would recommend you to first focus on your learning, then grades will follow.
In-Class Quizzes
In-Class quizzes provide an opportunity to practice as you are learning during the lectures. The questions will be asked sporadically throughout the lectures. You are encouraged to discuss quiz questions with your neighbors in class. You can check notes, use internet etc. You will be graded for participation, not for correctness of your answers. You need to be attending the lecture and respond to all questions in order to receive the full participation points. If you are not participating in lecture or have someone else participate for quizzes on your behalf, this will be considered academic misconduct. Note that during week zero we will have online quizzes for onboarding purposes which will be graded for correctness. In other words, these online quizzes will get you ready for the first day of class.
Section Activities
During sections, you will be working on a set of problems. You will be able to work on these problems with your classmates under the guidance of course assistants. You will submit this work by the end of the section. This work will be graded by completion and not correctness. While mistakes are considered part of the learning process for these activities, problems that have been solved by the course assistants are expected to be shown with a correct solution. Section activities need to be submitted by the end of each section.
Homework Assignments
You will be assigned a weekly homework on the topics that are covered each week. The homework assignments are best to be started after Wednesday’s lecture and you will have until the following lecture to finish the homework assignments. In other words, homework assignments will be due at 1:25 pm on Mondays. For homework assignments, you can use books and notes, talk to other people in your class, use online resources including generative AI however there are some limitations. See Section 4.1.
Midterm Exam
Midterm exam will be held in-person on Oct 7th at 1:30 - 2:45 pm at location TBD. You will work individually on the exam. It will be a closed-book exam. You will not need a calculator and thus you will not be allowed to use one.
Final Exam
Final exam will be held in-person on date and time TBD at location TBD. You will work individually on the exam. It will be a closed-book exam. You will not need a calculator and thus you will not be allowed to use one.
Team Project
You will complete a project with a team mostly in the second half of the semester. The team project will consist of hands-on data analysis. You will apply the methods learned in this course to answer a question(s) that interests you. The project will have multiple components starting in the second half of the semester. Two of the many components of the project is the proposal and the presentation. You are expected to submit a proposal by Nov 4th at 5 pm and submit a final paper along with the final state of data analysis that produced the paper by Dec 4th at 5 pm. If we notice a big discrepancy in the amount of team members amount of work, then we hold the right to assign different grades to different team members.
Grading
The following weights will be adopted in calculating the final grade.
| Component | Weight |
|---|---|
| In-Class Quizzes | 10% |
| Section Activities | 10% |
| Homework Assignments | 10% |
| Midterm Exam | 25% |
| Final Exam | 25% |
| Project | 20% |
Late Work Policy
Late work is not accepted on any assignments except for homework assignments. Each student has 48 hour late work submission allowance that they can use throughout the semester. This means that a student can submit one homework 24 hours late, another one 12 hours late, and another one 12 hours late and still have their work graded with maximum points possible. You do not need to notify us in order to use your late work submission allowance. We will be able to tally the amount of late hours you have used. But, for your own reference, please also keep track so that you know how much of your allowance remains.
It is recommended that you start working on the homework early and not leave it until the last minute to avoid any technological or personal issues. Starting early would also give you ample opportunity to attend office hours.
Excused Absences
You are expected to attend the lectures and the section you signed up for. Attendance is important, not only for your learning experience but also socializing with your classmates. Who would want to be elsewhere but be surrounded by their STAT 100 peers in their sections? If there is any physical, mental, personal, religious, cultural, and other reasons that prevent you from attending the lectures or the section, please email the course instructor. When possible please do so in a timely manner.
Re-grade Policy
While we will try our best to make sure that your grade is correct, it is possible for us to make minor mistakes in grading unfortunately. Thus, we strongly encourage you to go over your assignments to check for the correctness of your grade. You should immediately notify us if there are any errors. For all assignments other than the final exam, you have one-week after receiving feedback and grade from us to ask for regrading to correct any errors. For the final exam, you have 48 hours to request a regrade after receiving feedback. We will use Canvas Gradebook for keeping track of grades and you should check for its correctness. For assignments on Gradescope you can send regrade requests directly within Gradescope. For others, you can fill out this form. A regrade request should never be used for the argument of “I need a certain grade”, “I think I deserve more simply because”. You should only request a regrade if there is an error in our grading with a clear evidence. Note that a regrade request may result with 1) a higher grade, 2) the same grade or 3) a lower grade.
Getting Help
Office Hours
The teaching team, including the instructor, preceptor, and the course assistants have several office hours that you can attend. You can attend office hours for several reasons for asking questions about the course content, assignments, statistics careers, or simply to say hi because we love seeing our students during office hours.
You can find the schedule for office hours under the People tab and on the Google calendar on the Home page.
Online Discussion
We will have an online forum where you can ask questions. While communicating online, please note the following:
Before posting a question, please make sure that the same question has not been posted before.
Respect opinions of others.
If you choose to post memes or any jokes, be mindful. Any joke about a person, or a group of people, or cultures is not funny. However, statistics and data science jokes are always welcome.
There are absolutely no stupid questions. Do not feel shy about asking questions. Do not judge anyone about any question that they ask.
If somebody asks a question about homework etc. do not reveal answers for them. Instead, help them learn and show them in which lecture we have covered the topic.
Be generous with likes. That means when you read something useful like the post, so that we all know that we are not talking to ourselves but to each other.
Answer each other’s questions.
ARC Peer Tutoring
The Academic Resource Center (ARC) aims to create conditions for optimizing student learning by providing a range of resources, including academic coaching, peer tutoring, and group programming. Peer tutoring is a friendly, interactive learning opportunity with another student who has already been there. Meet with a peer tutor to get questions answered, clear up areas of confusion, work through practice problems, or just talk through course material. You can also book a small group tutoring session with classmates, teammates, or friends for a collaborative opportunity to reinforce course concepts. Peer tutors have experience with the course content and have been trained to facilitate learning in inclusive, active sessions. To get started, go to the ARC Scheduler to see the availability of peer tutors for your courses. Harvard College students can receive peer tutoring services free of charge up to a maximum of 6 total hours per week.
Please use email for only course logistics that are only about you. For instance, if you are sick with a stomachache, this only applies to you and does not apply to another student. In this instance, you should email me. For anything else, everything should be posted on the online forum Ed Discussion. If for instance, you don’t understand why I wrote “x+y” on the board. If you ask this on Ed Discussion then others who might have the same confusion would benefit from the answer. You can always make an anonymous post if you are feeling shy.
Getting Help From Peers and Artificial Intelligence (AI) Tools
Collaborative learning and AI tools can be incredible assets for mastering course material when used intentionally. Working with peers offers vital social benefits alongside academic support, a meaningful advantage as social isolation becomes a growing challenge. Engaging with AI tools can possibly save time later in the term, though navigating them effectively as a novice learner can be tricky. For this reason, avoiding AI during the early weeks of the semester is strongly recommended so you can build a solid foundation first.
Because your midterm and final exams are in-person and closed-book, developing true personal mastery during weekly assignments is your best path to success. While peer collaboration is encouraged and AI tool usage is not prohibited, both should strictly serve as study partners to deepen your understanding, never as shortcuts.
Attempt First, Consult Second: Try tackling problems independently before turning to peers or AI. Use outside help to clarify concepts, troubleshoot errors, or deepen your understanding—not to generate quick answers.
Reflect Your Own Mastery: Everything you submit should represent your authentic understanding. You should be prepared to walk through, explain, and discuss your logic, code, or answers with the teaching team if asked.
Match Course Conventions: Keep your work aligned with the specific notation, terminology, and tools (e.g., specific R functions) taught in class to ensure you build relevant skills.
Maintain Academic Integrity: Submitting work completed by someone else, paying for solutions, or copying directly from external sources harms your own learning process and violates academic integrity.
Course Climate
My goal is to make everyone (yes, that includes you too) feel welcome, not only in my classroom but also in the field of statistics and data science. If there is any reason you do not feel welcome in this class, please talk to me. If anything is said to you that makes you feel uncomfortable, please talk to me. If there is any life event that is interfering with your learning in this class, please talk to me. I may not be able to solve all your problems, but I may be able to direct you to the right resources on campus.
Disability Accommodations
Harvard University values inclusive excellence and providing equal educational opportunities for all students. Our goal is to remove barriers for disabled students related to inaccessible elements of instruction or design in this course. If reasonable accommodations are necessary to provide access, please contact the Disability Access Office (DAO). Accommodations do not alter fundamental requirements of the course and are not retroactive. Students should request accommodations as early as possible, since they may take time to implement. Students should notify DAO at any time during the semester if adjustments to their communicated accommodation plan are needed.
Audio/Video Recording Prohibited
Recording, photographing, or broadcasting any part of class lectures, section discussions, or course activities without explicit, advance permission from the instructor is strictly prohibited. Unauthorized distribution, posting, or sharing of course materials or recordings (including uploading to commercial websites) violates course policy.
If you have an approved accommodation through the Disability Access Office (DAO) that includes audio recording or assistive note-taking technology, I will be notified by DAO directly.
Technology Use Policy
A laptop (with Windows, Mac or Linux) is required to complete the tasks for this course.
To support a distraction-free learning environment, cell phones, tablets, and laptops are not permitted during lecture unless we are in a designated tech time (e.g., in-class quizzes or code-together sessions).
If you have an urgent personal reason to monitor your phone during a specific class, please check in with me before lecture begins. Students with an approved accommodation through the Disability Access Office (DAO) regarding technology use are fully permitted to use their devices as needed. Using technology during “no-tech” lecture time will result in the loss of all participation points (i.e., that day’s in-class quiz credit) for the session.
Laptops are required and actively used during section discussions; please have them open and ready for work at the start of section.
Subject to Change
Everything on the syllabus is subject to change depending on any unexpected circumstances that might arise during the semester (e.g., historical example of COVID-19 lockdowns). I hold the right to make modifications in a way to improve the learning process of student(s).