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Curriculum Module

Created with R2024b. Compatible with R2024b and later releases.

This curriculum module contains an interactiveMATLAB® live script that illustrates some basic concepts of regression analysis.

You can use this live script as a demonstration in lectures, a class activity, or an interactive assignment outside class. This module covers topics including solving for linear regression parameters, assessing and improving performance of regression models, and applying the gradient descent algorithm. It also includes an example of using a linear regression model to perform short-term forecasting.

The instructions inside the live script will guide you through the exercises and activities. Get started with the live script by running it one section at a time. To stop running the script or a section midway (for example, when an animation is in progress), use the Stop button in theRUN section of theLive Editor tab in the MATLAB Toolstrip.

Contact theMathWorks Educator Content Development Team if you would like to provide feedback, or if you have a question.

This module assumes knowledge of plotting and working with linear data.

Use the link to download the module. You will be prompted to log in or create a MathWorks account. The project will be loaded, and you will see an app with several navigation options to get you started.

Download or clone this repository. Open MATLAB, navigate to the folder containing these scripts and double-click onRegressionBasics.prj. It will add the appropriate files to your MATLAB path and open an app that asks you where you would like to start.

Ensure you have all the required products (listed below) installed. If you need to include a product, add it using the Add-On Explorer. To install an add-on, go to theHome tab and selectAdd-Ons >Get Add-Ons.

MATLAB® is used throughout. Tools from Statistics and Machine Learning Toolbox™ are used frequently as well. Parallel Computing Toolbox™ is used specifically for theparpool function.

	In this script, students will... $\bullet$ use least squares to solve for linear regression paramaters. $\bullet$ use a goodness-of-fit measure to assess model performance. $\bullet$ apply a basic linear regression to model real-world electricity load data.

	Available on: GitHub

	Available on: GitHub

Or feel free to explore our othermodular courseware content.

• Educator Page

Looking for more? Find an issue? Have a suggestion? Please contact theMathWorks Educator Content Development Team. If you want to contribute directly to this project, you can find information about how to do so in theCONTRIBUTING.md page on GitHub.

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