Module 7: Lesson 4¶

Introduction to Ordinary Linear Regression¶

This lesson introduces ordinary linear regression, which can compute a best-fit linear model between two dimensions. This linear model can be used (with certain caveats) for predictive analytics and also to visually understand relationships between different dimensions of a data set.

Objectives¶

By the end of this lesson, you will be able to

understand the concepts behind ordinary linear regression,
articulate the benefits of a linear model that has been coimputed from a data set, and
compute an ordinary linear regression model from a data set by using Python.

Time Estimate¶

Approximately 2 hours.

Activities¶

Reading: Explore ordinary linear regression by using the Explained Visually website from Setosa.

Video: Watch the Introduction to Ordinary Linear Regression video, which will demonstrate how to compute and display a linear regression model.

Notebook: Read and complete the student exercises in the Introduction to Ordinary Linear Regression notebook.

This notebook is released under the Creative Commons license CC BY-NC-SA 4.0. Any reproduction, adaptation, distribution, dissemination or making available of this notebook for commercial use is not allowed unless authorized in writing by the copyright holder.