Advanced Strategies for Ecological Data Analysis

Advances in nearly all fields of ecological data collection have made available unprecedented amounts of data about our world. This means new challenges for ecologists in screening, processing and analysing multiple and large sources of ecological information.

This hands-on course with six whole day instalments explores strategies for efficiently analysing ecological data sets, documenting your workflow and making it reproducible, speeding up your computations, and creating nice and interactive visualisations. The focus is on the R language and environment for statistical computing, with excursions to the Unix shell, C++, and the Julia language. Topics covered include functional and object-oriented programming in R, the “Hadleyverse” packages for modern and efficient R, parallel computing, foreign language interfaces in R, version control with Git, and Shiny. We will explore these strategies using real-world data.

Recommended prerequesite

Basic working knowledge of R. Benchmark: you are able to write and use functions you wrote yourself.

More information: Flyer (pdf)