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About the course

This group of courses is focused on statistical modelling and developed at an undergraduate level in statistics. Only basic level knowledge of statistics and R is required at the beginning of each course.  The courses were developed for both non statisticians and statisticians. The courses within this cluster can also be used as courses to support R usage in undergraduate program in biostatistic/statistics. We provide two sets of courses, each consist of three courses. The first set  was developed by the >eR-BioStat team while the second set was developed by Vu & Harrington (https://www.openintro.org/book/biostat/).

 

The following topics are included:

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Simple linear regression using R

 

This course covers the topic of simple linear regression using the R function lm(). Topics (all presented at a basic level) covered in the course include: (1) introduction and model formulation, (2) fitting a simple linear regression model using the lm() function in R, (3) model diagnostic and (4) model diagnostic in R.

 

One-way ANOVA using R

 

This course covers the topic of one way ANOVA models using the R function aov(). Topics (all presented at a basic level) covered in the course include: (1) the one-way ANOVA model, (2) sources of Variability, (4) One-way ANOVA using R: the aov() function, (5) model formulation and hypotheses testing, (6) model diagnostic in R: normal probability plot and (7) multiple testing.

 

Logistic Regression using R

  

This course covers the topic of simple logistic regression using the R function glm(). Topics (all presented at a basic level) covered in the course include: (1) Introduction and example tour, (2) fitting a simple linear logistic regression model using the glm() function in R, (3) model formulation and (4) interpretation of the model parameters.

General information about the course materials

 

Course materials include

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  • Slides (in PDF) and source files to produce the slides (PP & Rmd).

  • R program for the examples presented in the course.

  • Datasets that are used for illustrations (either R datasets or external datasets). 

  • Online interactive books for regression and ANOVA.

  • YouTube tutorials and online tutorials. Note that these tutorials were not developed especially for this course but they cover the same topics, usually with different examples.

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As a student in the course, you can choose between two study methods:

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  • If you prefer the traditional slides approach, you can click on the button Topics. This will take you to a page with 3 chapters that cover all topics in the course. Each chapter has its own slides presentation and an R program contains all the examples used in the course and presented in the slides is available as well.

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  • If you prefer a more interactive study style, clink on the button Online materails that will take you to the page with online interactive books YouTube tutorials and online tutorials.

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