12954 - Biostatistics Modulübersicht

Module Number: 12954 - Phase-out Module
Module Title:Biostatistics
  Biostatistik
Department: Faculty 2 - Environment and Natural Sciences
Responsible Staff Member:
  • Prof. Dr. rer. nat. Birkhofer, Klaus
Language of Teaching / Examination:English
Duration:1 semester
Frequency of Offer: Every summer semester
Credits: 6
Learning Outcome:The Module Biostatistics provides comprehensive introduction to data analysis for the applied sciences, especially for ecology, with a particular focus on R programming (R software).
Contents:Part "Experimental design”
Correct experimental design is the basis for high-quality research. Students learn about basic types of experimental designs and their advantages and limitations:
  • Random sampling
  • Non-random sampling (block design, longitudinal data, latin square, split plot)
  • Pseudoreplication
Part "Descriptive statistic" 
The application of descriptive statistics allows to gain quantitative insights into large data sets. Students learn about:
  • Data classification: discrete (binary, nominal, ordinal) and continuous (interval, ratio)  
  • Basic concepts of data distribution
  • Measures of central tendency: mean, median, or mode
  • Measures of variability: range, quartiles, absolute deviation, variance and standard deviation
  • Inferential statistics, normal and non-normal distributions and calculation of probabilities
Part "Univariate analysis" 
Students will gain substantial theoretical knowledge of basic statistical analyses and associated inference and evaluation methods. Students learn about:
  • Summary of assumptions
  • Difference between models and statistical tests
  • T-test and ANOVA (Analysis of variance)
  • Correlation and regression analysis
  • Non parametric analysis (Wilcoxon, Mann-Witney-U, Kruskal-Wallis)
  • General and generalized linear models
  • Introduction to mixed models
Part "Multivariate analysis" 
Students can learn the statistical technique for analysing data that resulting from more than one variable. Students learn about:
  • Principal component analysis (PCA)
  • Non-metric multidimensional scaling (NMDS)
  • Redundancy analysis (RDA)
  • Canonical correspondence analysis (CCA)
Part "Representation of results: graphs and tables" 
Basics for a proper presentation of the results for publication in journals.

Part "Introduction to R" 
The course will be taught using the R program. R is a powerful software system developed for analysing and graphically displaying data. R is an integrated programming environment, allowing users to script their own functions. Students learn about:
  • Comprehensive introduction to the essentials of R
  • Programing in R language: syntax parsing, evaluation, object-oriented programming, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code presenting the content of scientific studies
Recommended Prerequisites:None
Mandatory Prerequisites:None
Forms of Teaching and Proportion:
  • Lecture / 2 Hours per Week per Semester
  • Exercise / 2 Hours per Week per Semester
  • Self organised studies / 120 Hours
Teaching Materials and Literature:
  • Gotelli, N. J. & Ellison A. M. 2013 A primer of ecological statistics. Sunderland
  • Dytham, C. 2011 Choosing and using statistics: a biologist's guide. Chichester
  • Quinn, G. P. & Keough, M. J. 2003 Experimental design and data analysis for biologists. Cambridge
  • Zuur, A. F., Ieno, E. N. & Smith, G. M. 2007 Analysing ecological data. New York
  • Dormann, C. 2020 Environmental Data Analysis: An Introduction with Examples in R. Cham
  • Lakicevic, M., Povak, N. & Reynolds, K. M. 2020 Introduction to R for terrestrial ecology: basics of numerical analysis, mapping, statistical tests and advanced application of R, Cham
  • Crawley, M. 2013 The R book. Chichester Crawley, M. 2012 Statistik mit R. Weinheim
Module Examination:Final Module Examination (MAP)
Assessment Mode for Module Examination:Written examination, 90 min.

In case of regular (documented) attendance in the exercises, additional 10 % as a bonus is possible.
Evaluation of Module Examination:Performance Verification – graded
Limited Number of Participants:None
Part of the Study Programme:
  • Abschluss im Ausland / Environmental and Resource Management / keine PO
Remarks:No offer in SS 2026!


All students have to bring their own laptop!
Module Components:
  • 240782 Lecture/Exercise Biostatistics 
  • 240784 Examination Biostatistics
Components to be offered in the Current Semester:
  • no assignment
Follow-up Module/s: Phase-out module since: 10.12.2025
  • without Follow-up Module/s