General information

Course type AMUPIE
Module title Basic R Programming For Scientists
Language English
Module lecturer dr hab. Łukasz Grewling, dr Paweł Bogawski, dr Bartosz Łabiszak
Lecturer's email
Lecturer position Assistant Professor
Faculty Faculty of Biology
Semester 2024/2025 (winter)
Duration 30


Lectures: 4 hours

Computer workshops: 26 hours

The schedule of classes will be given later

Module aim (aims)

Pre-requisites in terms of knowledge, skills and social competences (where relevant)

No programming knowledge required – this course aims to start from the basics


Week 1: Introduction to R environment (lecture, 2h)


Week 2: How R can enhance the research: examples in biology and geography (lecture, 2h)


Week 3:  Basics of manipulating data in R environment (R syntax, importing, managing, cleaning data) (computer workshop, 2h)


Week 4: Basics of manipulating data in R environment (export from R, format conversions, data types, functions and additional packages) (computer workshops, 3h)


Week 5: Downloading data from servers directly from R (for example, climatic and biological station/point data) (computer workshop, 3h)


Week 6: Statistical testing of hypotheses, preparing simple statistical models and performing their assessment (computer workshop, 3h)


Week 7: Visualisation of the results, creating boxplots, barplots and scatterplots and others using base and ggplot2 R package, preparing R Markdown reports directly from R (computer workshop, 3h)


Week 8: R software for maps, satellite and aerial images (for example mapping in ggplot2) (computer workshop, 3h)


Week 9: Laser scanning data as a valuable source of environmental/biotic information (computer workshop, 3h)


Week 10: Environmental niche modelling (computer workshop, 3h) 


Week 11: Machine learning, loops, animations, summary, reviewing the acquired knowledge (computer workshop, 3h)



Reading list

R software tutorials, e.g.

Lovelace R. et al. 2019. Geocomputation with R. 

Paradis E. 2005. R for beginners:

Quick-R tutorial:

Statistical tools for high-throughput data analysis:

Other R tutorials, Videos freely available in the Internet, YouTube

Wang K. et al 2010. Remote Sensing of Ecology, Biodiversity and Conservation: A Review from the Perspective of Remote Sensing Specialists. Sensors 10, 9647-9667; doi:10.3390/s101109647

United Nations 2000. Handbook on geographic information systems and digital mapping. New York