Stats 110
This syllabus and everything else you need will be posted on the course website: stats110.stanford.edu.
Learning Objectives
The theme of this class is the ubiquity of uncertainty in statistics and in everyday life.
By the end of this class, you should be able to:
- Carry out and interpret a hypothesis test to determine when a signal is real, not just noise.
- Construct and interpret a confidence interval to quantify uncertainty in a statistic.
- Design, implement, and analyze a survey.
- Design, implement, and analyze a randomized experiment.
- Write code in R to perform basic statistical analyses.
Course Staff
|
Professor | Dennis Sun |
| Lectures | Mon, Wed 1:30 - 2:50 PM in Turing Auditorium | |
| Office Hours | Fri 1 - 3 PM in Sequoia 124 | |
|
TA | Reese Feldmeier |
| Sections | Tues, Thurs 9:30 - 10:20 AM in 160-326 | |
| Office Hours | Mon 4 - 5 PM in Sequoia 220 (Fishbowl) | |
|
TA | Joon Lee |
| Sections | Tues, Thurs 10:30 - 11:20 AM in 160-315 | |
| Office Hours | Mon 10 - 11 AM in Sequoia 220 (Fishbowl) | |
|
TA | Tim Sudijono |
| Sections | Tues, Thurs 1:30 - 2:20 PM in 200-105 | |
| Office Hours | Wed 4 - 5 PM in Sequoia 220 (Fishbowl) | |
|
TA | Etaash Katiyar |
| Sections | Tues, Thurs 4:30 - 5:20 PM in Thornton 210 | |
| Office Hours | Tues 3:30 - 4:30 PM in Sequoia 220 (Fishbowl) | |
| CA | Simran Nayak | |
| Office Hours | Tues 12 - 1 PM in Sequoia 207 (Bowker) |
Contact Outside Class and Office Hours
We prefer to talk to you in person, during class or office hours! But if you need to reach us outside of these times, there are several options:
- If you have a question about class logistics or course material, please post it on the Ed Discussion forum so that everyone can benefit from your question.
- If you have a private concern, pleaes e-mail the staff list
stats110-aut2425-staff@lists.stanford.edu
Please use this list instead of our individual e-mail addresses for a timely response. You can expect a response within 1 business day.
Grading
Your final grade in the course will be determined from the following components.
| Component | Weight |
|---|---|
|
Participation This class is highly interactive, taught through hands-on activities and discussions. You have to be present to fully experience this class. For this reason, attendance is a substantial part of the final grade. Do not take this class if you are unwilling or unable to come to every lecture and section on time. We understand that other events may occasionally conflict with class. On section days, you may attend another section after e-mailing that TA for permission. But if you have to miss class altogether, you should review the slides and ask a classmate for their notes. To earn attendance credit, you need to prepare 3 - 5 pages of notes summarizing the material in your own words and upload it to this form. Besides attendance, a small part of the participation grade will be reserved for students who participate actively in class and/or answer questions on the Ed Discussion forum. |
15% |
|
Case Studies (posted on the Schedule page) A case study is a self-contained investigation of a statistics or data science question. One case study will be assigned after each lecture, due at noon 1 week later. A case study is shorter than a problem set, typically equivalent to 2-3 questions on a problem set. We will peer review each case study during lecture. So no extensions are possible, for any reason. However, there will be two optional case studies due Week 10 that will replace your lowest scores. |
15% |
|
Peer Reviews |
5% |
|
Instead of paper-and-pencil exams, there will be two short interviews, where you will demonstrate your understanding of statistics concepts to an instructor. We will provide example questions, as well as opportunities to practice interviews during class time. Although interviews might sound intimidating, we have found that interviews give students more chances to succeed, and they are more useful preparation for your future careers! |
25% |
|
To help you achieve the learning objectives, you will collect your own data and analyze it in two projects. For each project, you will submit a report. Then, you will present one of the projects in a poster session during finals week (instead of a final exam). |
40% |
| Total | 100% |
We are committed to following the syllabus as written here, including through short- or long-term disruptions, such as public health emergencies, natural disasters, or protests and demonstrations. However, there may be extenuating circumstances that necessitate some changes. Should adjustments be necessary, we will communicate clearly and promptly to ensure you understand the expectations and are positioned for successful learning.
Regrade Policy
If you believe that we have made a mistake in grading, please fill out this form within 1 week of getting the assignment back. Note that Professor Sun will regrade your entire assignment, so your grade could go up or down.
Collaboration and AI Policy
You are encouraged to work together with other students in the class on case studies. You are also encouraged to ask AI for hints if you get stuck or to check your work. However, under no circumstances should you submit a work that another human or AI produced as your own. We reserve the right to quiz you on any work that you submit in this class. If you are unable to explain it, it will be treated as a serious violation of the Honor Code.
In short, any collaboration in this class (with another human or AI) should further your learning, not replace it.
Accommodations
Students who may need an academic accommodation based on the impact of a disability must initiate the request with the Office of Accessible Education (OAE). Professional staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter for faculty dated in the current quarter in which the request is being made.
Once you have your letter, please send it to the staff list: stats110-aut2425-staff@lists.stanford.edu. (Please don't email it to the professor or your TA; they will just tell you to e-mail it to this list.)
We need time to prepare for any accommodations, so we must receive your letter by Monday, September 30.