Week 6 - Linear Models Contd
Linear models for predicting numerical data from single and multiple variables 📈
Light patterns. Photo by Ryan Stone on Unsplash
Tasks
- Complete the assignments
- Complete the readings
Topic Intro
No. |
Title |
Slides |
|
|---|---|---|---|
| 1 | Models with multiple predictors | ||
| 2 | More models with multiple predictors |
Class Activities
Activity |
Title |
Date |
|---|---|---|
| Topic Intro | Model Fitting and Interpreting | Tue, 13 Feb |
| Topic Intro | Models with Multiple Predictors | Wed, 14 Feb |
| Lab 05 | Lab - Grade the Professor Part 2 | Fri, 16 Feb |
Assignments
Assignment |
Title |
Due |
|---|---|---|
| Due this week | ||
| Lab 04 | Course Evaluations | Thu, 15 Feb 23:59 EST |
| Q 03 | Multiple regression | Sun, 18 Feb 23:59 EST |
| Due next week | ||
| Lab 05 | Grade the Professor Part 2 | Thu, 22 Feb 23:59 EST |
| HW 03 Optional | Bike rentals DC | Fri, 23 Feb 23:59 EST |
Readings
| 📖 | IMS: Chp 8 - Regression with multiple predictors | Required |
| 📄 | MLU-Explain Linear Regression | Optional |
| 📄 | Faculty Salaries Visualization by Michael Freeman | Optional |
Interactive R tutorials
The following are interactive R tutorials, designed to give you more practice with R. These are optional, but they will show up in your next homework assignment, so you should gain familiarity with it. If you’re struggling with any of the topics covered this week, we strongly recommend you work through the interactive tutorials.
| Bike Rentals in D.C. | Related to HW 03 |
