Basic linear regression  using R

This course presents the basic concepts of linear regression. This is an online course which was developed by Marc Lavielle within his initiative statistics in action with R (http://sia.webpopix.org/). All R code for the examples presented in the course is available online. Slides which cover most of the materials presented in the course are available.

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The course structure:

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• Introduction

• Fitting polynomial models

  • Fitting a polynomial of degree 0

  • Fitting a polynomial of degree 1

  • Numerical results

  • Some diagnostic plots

  • The predictive performance of the model

  • Confidence interval and prediction interval

  • Fitting a polynomial of degree 2

  • Fitting a polynomial without intercept

  • Using orthogonal polynomials

• Model comparison

  • t-test

  • Analysis-of-variance (anova)

  • Likelihood ratio test (LRT)

  • Information criteria

• Data transformation

  • log based tranformations

  • Diagnostic plots

  • Confidence interval and prediction interval

• Model comparison

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General information about the course

 

Course materials include:

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• Slides for classes (in PDF format).

• PowerPoint file for the slides.

• R programs for the example of the course.

• Online materials.

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As a student in the course, you can use the slides, R programs and online materials:

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• Click on the button Topics. This will take you to a page with slides & online book.

• Online tutorials and YouTube tutorials clink on the button Online Tutorials.

 

As a teacher, you can modify the PowerPoint file and create your own version of the course.

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