Week 8 — Regression (10/10–14)#

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#

📅 Deadlines#

  • Week 8 Quiz Thursday Oct. 14 at 8AM

🎥 Introducing Regression#

🎥 Statistical Modeling#


🎥 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.

🎥 Prediction and Inference#

🎥 Categorical Predictors#

🎥 Testing Assumptions#

📃 Regression Model Assumptions#

Read Regression Model Assumptions from JMP.

🎥 Multiple Regression#

🎥 Measuring Prediction Accuracy#

🎥 Instances and Sampling#

📓 Supporting Notebooks#

🚩 Week 8 Quiz#

Complete the Week 8 quiz in Canvas.

📃 StatsModels Examples and User Guide#

The following StatsModels pages document its OLS model:

📃 Bootstrapping Linear Regression#

Read Bootstrapping for Linear Regression.

📩 Assignment 4#

Assignment 4 is due October 24, 2020.