• Advanced Courses in Life Sciences

    Header of Statistics at Transmitting Science

Live Online Course – 5th Edition

Statistical Analyses with R

February 5th-16th, 2024

Live sessions will be recorded

Course Statistical Computing for Environmental Science with R and Rstudio


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Course overview & Programme

The course is given in four modules covering exploratory data analysis, univariate and multivariate statistical techniques and a final discussion session where students will work and discuss their projects:

  • Module I. Programming in R and Rstudio
  • Module II. Exploratory Data Analysis (EDA)
  • Module III. Univariate Statistical Analysis (UniStat)
  • Module IV. Multivariate Statistical Analysis (MultiStat)

This course will cover some advanced issues in most statistical computing workflows for the Life Sciences. Together with the statistical analyses, we will cover several aspects of data structure and workspace management, and visualization techniques using R and Rstudio.

This course is of intermediate level.

Module I. Programming in R and Rstudio

  • Along with this model, we will review the most commonly used files in any statistical programming workflow like the scripts (.R) the allocated memory (.RData) and the novel Rstudio projects (.Rproj) for establishing dedicated working directories, workspace, history, and source documents.

Module II. Exploratory Data Analysis (EDA)

  • During any statistical programming workflow, almost half of the time must be given to data exploration. However, not every exploration is a valid exercise. Here we will review the most common assumption in a classical statistical analysis like normality, heterogeneity and independence in the data.

Module III. Univariate Statistical Analysis (UniStat)

  • In module III we will review the classic univariate approach for statistics like te linear models and their extensions. The most common analysis like ANOVA, ANCOVA or Regression analysis will be covered. For those common cases in ecology, where the linear models fail (e.g. non-negative data in count/abundance data) we will present some extensions covering the Generalized Linear Models (GLM) for count and presence/absence data and we will review some insights in Generalized Additive Models (GAM).

Module IV. Multivariate Statistical Analysis (MultiStat)

  • Along with this fourth module, we will cover the analysis of multivariate data. We will review two different approaches to understand community (multivariate) data based on different ordination techniques. Thus, two approaches from unconstrained ordination, like Principal Component Analysis (PCA) and non-Metric Multidimensional Scaling (nMDS) will help us to reveal patterns along with our community data. Finally, we will use two approaches from constrained ordination like Redundancy Analysis (RDA) and Canonical Correspondence Analysis (CCA) to understand the role of some environmental (explanatory) variables over the community structure in our community Data.

Basic knowledge of Statistics and R.

All participants must have a computer (Windows, Macintosh, Linux), with access to a good internet connection. The use of webcam and headphones is strongly recommended.


Antonio Canepa instructor for Transmitting Science

Dr. Antonio Canepa
University of Burgos

Dates & Schedule

Online live sessions on February 5th, 6th, 12th, 14th and 16th

15:00-19:00 (Madrid time zone)

Total course hours: 26

20 hours of live lessons, plus 6 hours of participants working on their own, with tutored exercises.

This course is equivalent to 1 ECTS (European Credit Transfer System) at the Life Science Zurich Graduate School.

The recognition of ECTS by other institutions depends on each university or school.



This course will be delivered live online

This course will be taught using a combination of live (synchronous) sessions on Zoom and tasks to be completed in between live sessions on the Slack platform.

Live sessions will be recorded. Recordings will be made available to participants for a limited period of time. However, attendance to the live sessions is required.


Places are limited to 18 participants and will be occupied by strict registration order.

Participants who have completed the course will receive a certificate at the end.

Haris Saslis instructor for Transmitting Science

Dr. Haris Saslis
Transmitting Science

Fees & Discounts

  • Course Fee
  • Early bird (until December 31st, 2023):
  • 470 €
    (376 € for Ambassador Institutions)
  • Regular (after December 31st, 2023):
  • 540 €
    (432 € for Ambassador Institutions)
  • Prices include VAT.
    After registration you will receive confirmation of your acceptance on the course.
    Payment is not required during registration.

We offer discounts on the Course Fee.

Discounts are not cumulative. Participants receive the highest appropriate discount.

We also offer the possibility of paying in two instalments. Please contact us to request this.

Former participants of Transmitting Science courses receive a 5% discount on the Course Fee.

20% discount on the Course Fee is offered to members of certain organisations (Ambassador Institutions). If you wish to apply for this discount, please indicate it in the Registration form (proof will be asked later). If you would like your institution to become a Transmitting Science Ambassador Institution, please contact us at communication@transmittingscience.com

Unemployed scientists, as well as PhD students without any grant or scholarship to develop their PhD, can benefit from a 40% discount on the Course Fee. This applies only to participants based in Spain. If you wish to ask for this discount, please contact us. The discount may apply for a maximum of 2 places, which will be covered by strict registration order.