Assignments, quizzes, and project
Assignment 0
Due Date: Tuesday, April 5, 11:30am PT
In preparation for the first discussion section, first install R, and then install RStudio (you’ll get an error if you install RStudio first!). Section 1.4 of R for Data Science has some tips for installation. Feel free to post on Ed with any installation problems, and be sure to follow the Ed posting norms.
Take a screenshot of RStudio installed on your machine with your full name written in the R console. Submit via Canvas.
Assignment 1
Exploring and visualizing data with dplyr and ggplot2.
Due date: Friday, April 8, 5pm PT
Solutions posted on Canvas.
Assignment 2
Statistical estimators and confidence intervals.
Due date: Friday, April 15, 5pm PT
Solutions posted on Canvas.
Assignment 3
The bootstrap, MLEs, and the method of moments.
Due date: Friday, April 22, 5pm PT
Solutions posted on Canvas.
Project proposal
Due date: Tuesday, April 26, 9pm PT
In teams of 3-5 people, please complete the project proposal form.
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. At the end of the quarter, each team will prepare either a 10-page written report or a 10-minute video presentation.
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. (This meeting is a required part of the assignment.)
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, April 29, 5pm PT
Solutions posted on Canvas.
Quiz 1
Thursday, May 5, 12:01am PT to 11:59pm PT
You will have 24 hours to complete the quiz. The quiz is open book/computer. It consists of 5 true/false and 15 multiple-choice questions. The quiz is designed to take approximately 1 hour. Instructions to access the quiz will be posted on Canvas at 12:01 am.
You must complete the quiz on your own. Giving or receiving any form of aid on the quiz is a violation of the honor code.
The first quiz tests the conceptual ideas presented during weeks 1-4 (through linear regression).
Assignment 5
Logistic regression.
Due date: Friday, May 13, 5pm PT
Solutions posted on Canvas.
Assignment 6
Bias-variance trade-offs, cross-validation, and regularization.
Due date: Friday, May 20, 5pm PT
Solutions posted on Canvas.
Assignment 7
Causal inference.
Due date: Friday, May 27, 5pm PT
Final project
Due date: Tuesday, May 31, 9pm PT
Submit a 10-page written report or a 10-minute video presentation via Canvas.
Only one team member needs to submit the project, though please list your team members in the submission comment box.
Confidential peer evaluations are due at the same time, and should be submitted separately by each team member. Please use the form linked below.
Peer evaluations for final project
Due date: Tuesday, May 31, 9pm PT
Form link is here.
Quiz 2
Thursday, June 2, 12:01am PT to 11:59pm PT
You will have 24 hours to complete the quiz. The quiz is open book/computer. It consists of 5 true/false and 15 multiple-choice questions. The quiz is designed to take approximately 1 hour. Instructions to access the quiz will be posted on Canvas at 12:01 am.
You must complete the quiz on your own. Giving or receiving any form of aid on the quiz is a violation of the honor code.
The second quiz tests the material presented in weeks 5-9. Note that some of the concepts presented in weeks 5–9 draw on material from weeks 1–4, so you should be familiar with the week 1–4 material to the extent needed to understand the material from weeks 5–9.