Introduction to Linear models in R

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• Lecturer(s) or Responsable(s): Guilherme Oyarzabal
• Department Responsible: Azorean Biodiversity Group
• Data: January 19^th, 2026 to January 23^rd, 2026
• Deadline for Applications: December 10^th, 2025
• Duration: 35 hours
• Schedule: 9h-12:30h and 14h-17h30 Monday to Friday
• Nº (min, max) Students: 10
• Location: University of the Azores – Campus of Angra do Heroísmo. Rua Capitão João d’Ávlia, 9700-042. Terceira Island, Azores, Portugal

Objectives

This course presents theory and practice statistical principles such as sample design, data collection, precision, and accuracy. The program begins with the distinction between theoretical and empirical work, addresses the importance of uncertainty, and exemplifies the fitting of statistical models to data from a Maximum Likelihood perspective. Statistical modeling and parameter estimation will be based on real and simulated data. Based on these principles, we present different data distributions to perform linear models, generalized linear models, and mixed models. Most of the morning session will consist of theoretical lectures and the afternoon sessions will consist of practice lectures, with breaks in both sessions. The practical component will be entirely developed in the R environment

General Plan

Theory vs empiricism, determinism vs stochastic. How math and statistics fit these parameters?

Simpson paradox, prudent empiricism, types of uncertainty,

Why sampling?, types of sampling, Maximum Likelihood, precision and accuracy.

Types of distributions, statistical tests, Anova.

Linear models, Generalized Linear Models.

Linear mixed models and Generalized Linear Mixed Models.

Student’s case studies.

Funding

FCT-UID/00329/2025 - Centre for Ecology, Evolution and Environmental Changes (CE3C)

Partners

Fee

This course is free of charge.

Contacts for Inscription

Candidates should send a short CV and motivation letter, no mora than one page, explaining why they are interested in the course, including a brief description of their research projects. Send all information and requests to Guilherme Oyarzabal (guilhermeoyarzabal@gmail.com).

Include also in the email the following information:

Full Name:

E-mail:

Phone:

Professional activity: Professional/Postdoc, BTI, BI (or other non-post-doc research grant), PhD student (with/ without scholarship), Lic. (Bachelor)/Master student

PhD student of the 1st year of a Doctoral program at University of Azores?

If yes to the above question, PhD student doing the Course to count credits for 1st year?:

Name of the PhD program:

guilhermeoyarzabal@gmail.com