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Workshop
24 May
| 10:00 am
| CIIMAR

Advanced Statistics with R for Biological Sciences

ADVANCED STATISTICS WITH R FOR BIOLOGICAL SCIENCES CIIMAR

24-28 May 2021

ADVANCED STATISTICS WITH R FOR BIOLOGICAL SCIENCES CIIMAR

24-28 May 2021

Session 1. 10:00 – 14:00 h, 24 May 2021

  • 1.1 Reminder of linear regression
  • 1.2 Exercise
  • 1.3 Reminder of ANOVA
  • 1.4 Exercise

Session 2. 10:00 – 14:00 h 25 May 2021

  • 2.1 General linear model (GLM). Introduction and example 1
  • 2.2 GLM, Example 2
  • 2.3 Exercise
  • 2.4 GLM with random factors (mixed effects models). Example.

Session 3. 10:00 – 14:00 h 26 May 2021

  • 3.1 GLM with random factors. Hierarchical (nested) designs
  • 3.2 GLM with random factors. Random slope designs
  • 3.3 Exercise
  • 3.4 Exercise

Session 4. 10:00 – 14:00 h 27 May 2021

  • 4.1 Generalized linear models (GLZ). Introduction and example 1
  • 4.2 GLZ, example 2
  • 4.3 GLZ, example 3
  • 4.4 GLZ with random factors. Example

Session 5. 10:00 – 14:00 h 28 May 2021

  • 5.1 Exercise
  • 5.2 Generalized additive models (GAM). Introduction and example
  • 5.3 GAM models with random factors. Example
  • 5.4 Exercise

Docent: Aldo Barreiro Felpeto. CIIMAR.

Price: 200 € (150 € for CIIMAR/UP members)

Registration: after announcement, up to fill 25 available positions.
Registration, together with the payment information, is available in the LINK. Proof of payment required to book the place (send proof to abarreiro@ciimar.up.pt).
After sending the proof of payment, a confirmatory e-mail for the registration will be sent.

Important information:

  • All the course will be taught through a zoom platform.
  • The course will be taught in English.
  • At least a beginner’s background in R and basic statistics is recommended.
  • All the information and materials necessary for the development of the course (instructions to install R and R packages, pdf with lessons content, scripts with examples and exercises, data fo examples and exercises) will be made available for all the participants in the course through a link to the Open Science Framework platform.

More information about the course available HERE.