# Week 8 — Regression (Oct. 11–15)¶

In this week, we are learning about linear regression with StatsModels. All the examples will use the StatsModels OLS (ordinary least squares) model, generally with the formula interface.

## 🧐 Content Overview¶

Element Length

🎥 Introducing Regression

5m6s

🎥 Modeling

8m6s

🎥 Single Regression

10m14s

🎥 Prediction and Inference

8m33s

🎥 Categorical Predictors

3m41s

🎥 Testing Assumptions

9m46s

📃 Regression Model Assumptions

964 words

🎥 Multiple Regression

19m8s

🎥 Prediction Accuracy

9m12s

🎥 Instances and Sampling

9m40s

📃 Bootstrapping for Linear Regression

1950 words

This week has 1h23m of video and 2914 words of assigned readings. This week’s videos are available in a Panopto folder and as a podcast.

• Week 8 Quiz Thursday Oct. 14 at 8AM

## 🎥 Single Regression¶

In this video, I introduce single-variable regression.

Slide Clarification

On slide 6, where I show the slope, intercept, and variance in a model, I have extended the plot to include 0 at the left end of the x-axis. This is to highlight the meaning of the intercept. It is important to note that the intercept is where the line crosses zero, not where it crosses the left Y-axis.

Also, when discussing this slide, I am imprecise but make it sound like the unexplained variance is the remainder after projecting the data onto the line. It is the variance remaining after subtracting the line. A video in Week 9 provides more clarity on this relationship.

## 📃 Regression Model Assumptions¶

Read Regression Model Assumptions from JMP.

## 🚩 Week 8 Quiz¶

Complete the Week 8 quiz in Canvas.

## 📃 StatsModels Examples and User Guide¶

The following StatsModels pages document its OLS model:

## 📩 Assignment 4¶

Assignment 4 is due October 24, 2020.