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Advanced statistics: Statistical modelling

Teachers

Rachel Marcone

Mauro Delorenzi

Material

General learning outcomes

At the end of this course, participants will be able to:

  • identify the appropriate model to analyze a dataset;
  • fit the chosen model using R;
  • assess the fit of the model, as well as its limitations.

Learning outcomes explained

To reach the general learning outcomes above, we have set a number of smaller learning outcomes. Each chapter starts with these smaller learning outcomes. Use these at the start of a chapter to get an idea what you will learn. Use them also at the end of a chapter to evaluate whether you have learned what you were expected to learn.

Learning experiences

To reach the learning outcomes we will use lectures, exercises and group work. During exercises, you are free to discuss with other participants. During lectures, focus on the lecture only.

Exercises

Each block has practical work involved. Some more than others. The practicals are subdivided into chapters, and we’ll have a (short) discussion after each chapter. Some answers to the practicals are incorporated, but they are hidden. Do the exercise first by yourself, before checking out the answer. If your answer is different from the answer in the practicals, try to figure out why they are different.

Asking questions

During lectures, you are encouraged to raise your hand if you have questions.