Assignments, quizzes, and project
Assignment 1 📊
Exploring and visualizing data with dplyr and ggplot2.
Due date: Friday, April 12, 5pm PT
Solutions posted on Canvas.
Assignment 2 🤔
Statistical estimators and confidence intervals.
Due date: Friday, April 19, 5pm PT
Solutions posted on Canvas.
Assignment 3 🥾
The bootstrap, MLEs, and the method of moments.
Due date: Friday, April 26, 5pm midnight PT (i.e., 1 minute after 11:59pm)
Solutions posted on Canvas.
Project proposal 👥
Due date: Tuesday, April 30 Extended to Friday, May 3, midnight PT
Note: HW4 is now due at the same time as the project proposal. See below for HW4 details.
In teams of 3 people (no more, no fewer), please complete the project proposal form.
To help assess the feasibility and suitability of your project, please discuss your idea with the teaching staff before submitting your proposal. Your group should sign up for a 15-minute meeting slot. It is ideal if all members of your group can attend the meeting but, at a minimum, two members should be present. Your proposal does not have to be completed, or even started, when you meet with a member of the teaching staff. But, you should have started thinking about potential topics and ideas. This meeting is a required part of the assignment.
You are free to pursue any topic related to applied statistics. In previous years, teams have considered athletic performance, gender inequality, farming practices, restaurant quality, music success, gentrification, and standardized testing, just to name a few. Any data-driven investigation is fair game.
More specific instructions on final deliverables will be provided later in the quarter. In a previous iteration of the course, teams submitted either a 10-page report or a 10-minute presentation. You can see past examples of successful final projects here. The final deliverables will likely change for this iteration of the course.
For more project details, see the project page.
Upon completing the project, we’ll ask each student to evaluate the contributions of their team members, and we’ll consider these peer reviews when determining final grades.
Assignment 4 🔮
Linear Regression.
Due date: Friday, May 3, midnight PT
Solutions posted on Canvas.
Quiz 1 📝
Tuesday, May 7 in Shriram 104 during regular class time.
Quiz 1 tests the conceptual ideas presented during weeks 1-4 (through linear regression).
The quiz is designed to take 45 minutes, but you will have the full class period to complete it.
Reach out to the teaching team ASAP if you cannot attend class on Tuesday, May 7 due to an extenuating circumstance.
This Ed post has more details about the quiz.
Assignment 5 🪙
Logistic regression.
Due date: Friday, May 10 17, midnight PT
Solutions posted on Canvas.
Assignment 6 ⚖️ 🚬
Bias-variance trade-offs, cross-validation, and regularization, causal inference.
Note: We have collapsed the Assignment 6 and Assignment 7 from the original course schedule into a single assignment
Due date: Friday, May 17 Wednesday, May 29, midnight PT
Final project 👥
Due date: Thursday, May 30 Sunday, June 2, midnight PT
Only one team member needs to submit the project via Gradescope. Please add all team members to your submission group.
Peer evaluations for final project 👥
Due date: Friday, May 31 Monday, June 3, midnight PT
Confidential peer evaluations should be submitted separately by each team member.
Quiz 2 📝
Tuesday, June 4 in Shriram 104 during regular class time.
Quiz 2 tests the material from the entire course, with a heavier emphasis on material from weeks 5-9.
The quiz is designed to take 45 minutes, but you will have the full class period to complete it.
Reach out to the teaching team ASAP if you cannot attend class on June 4 due to an extenuating circumstance.