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About the course

The GLM course consists of 5-6 classes, each of three hours, and combines theory and application using R. The course is organised in two part with cover the following topics:

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Part 1:

 

  • Analysis of Variance

  • Linear regression models with normal error.

  • Generalized linear models.

  • Exponential Family

  • Generalized linear model function in R

  • Models for Binary data.

  • Estimation and confidence intervals.

  • Inference.

  • Model Selection.

  • Model diagnostic.

 

Part 2:

 

  • Poisson Regression.

  • Beyond Poisson and binomial distributions: models with different link functions and/or distributions.

  • Poisson regression and log linear models.

  • Over dispersion.

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Course developers: 

 

Tadesse Awokem Fetene Tekle, Said Musa and  Ziv Shkedy

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General information about the course

 

Course materials include:

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  • Slides for classes (in PDF format).

  • R programs for the 14 chapters of the course.

  • Online materails.

 

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 14 chapters (organised in two parts) that cover all topics in the course. Each part  has its own slides presentation.

  • Online books, online tutorials and YouTube tutorials clink on the button Online Tutorials.

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