M.INC.1006: Data analysis for field biologists

(6 C / 4 SWS)

Learning outcome

In this module, we provide a basic introduction to data analysis in the R programming environment. We cover data collection and organisation, sampling designs in observational studies and basic statistics. We visualize our data throughout. The course participants will learn how to use classical hypothesis testing, linear regression and generalized linear models. If progress allows, we will introduce more advanced methods such as mixed effect models, models that can be used to correct for varying detection probability during data collection and approaches to extract, analyse and visualize spatial data.

Core skills acquired:
Ability to organize, transform and process data in R, ability to critically judge sources of bias resulting from data collection and analysis, ability to choose appropriate tools for the analysis of different types of data (e.g., categorical vs. continuous variables), skills to graphically present key messages, ability to report statistical results.


  • Statistics for Field Biologists (Lecture) (Lecture, 2 SWS)
  • Statistics for Field Biologists (Exercise, 2 SWS)


  • Assignments (max. 25 pages)
  • Examination requirements: Participants understand data structures and are able to organize, transform and summarize data. Particpants can judge on the quality of sampling designs, can apply basic statistical tests and statistical models, and have a basic command of the R language. They can visualize data and models, and are able report results of statistical tests.

Further details

  • Work load: 180 h (56/124 h, attendance / self-study)
  • Admission requirements: None
  • Recommended previous knowledge: No previous knowledge of R and R Studio is required. Basic skills of organizing and processing data in spreadsheet programs such as Excel are useful.
  • Language: English
  • Person responsible for module: Prof. Dr. Johannes Kamp
  • Course frequency: Each winter semester
  • Duration: One semester
  • Number of repeat examinations permitted: Twice
  • Recommended Semester: 1st semester
  • Maximum number of students: 25