14496 - Applied Biostatistics for environmental data Modulübersicht
| Module Number: | 14496 |
| Module Title: | Applied Biostatistics for environmental data |
| Angewandte Biostatistik für Umweltdaten | |
| Department: | Faculty 2 - Environment and Natural Sciences |
| Responsible Staff Member: |
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| Language of Teaching / Examination: | English |
| Duration: | 1 semester |
| Frequency of Offer: | Every summer semester |
| Credits: | 6 |
| Learning Outcome: | This module will provides a theoretical introduction to data analysis and results interpretation, statistical methods and tools for environmental and biological sciences, as well as applied tools with a particular focus on R programming (R software). |
| Contents: | Part 1. Introduction to experimental design Design principles Random sampling, block design, nested design, split-plot… Replication and Pseudoreplication Part 2. Introduction to R Introduction to the essentials of R Basics: Syntax, packages, writing codes & functions Data handling, analysis and visualisation (graphs and tables) Exercises Part 3. Distributions, Parameters and Estimators Data classification & distribution Measures of central tendency: mean, median … Measures of variability: variance and standard deviation Likelihood and Akaike Information Criterion Exercises Part 4. Univariate analysis T-test and ANOVA (Analysis of variance) Correlation and regression analysis Non parametric analysis (Wilcoxon, Mann-Witney-U, Kruskal-Wallis) linear models & introduction to mixed models Exercises Part 5. Multivariate analysis Principal component analysis (PCA) Non-metric multidimensional scaling (NMDS) Redundancy analysis (RDA) & Canonical correspondence analysis (CCA) Exercises |
| Recommended Prerequisites: | none |
| Mandatory Prerequisites: | none |
| Forms of Teaching and Proportion: |
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| Teaching Materials and Literature: | Zuur, A. F., Ieno, E. N. & Smith, G. M. 2007 Analysing ecological data. New York Gotelli, N. J. & Ellison A. M. 2013 A primer of ecological statistics. Sunderland 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 Wilke C.O. 2019 Fundamentals of Data Visualization, O’Reilly Wickham H& Grolemund G, 2017 R for Data Science, O’Reilly |
| Module Examination: | Continuous Assessment (MCA) |
| Assessment Mode for Module Examination: | - 10 Exercises during the courses (50%)) - Individual project presentation, 15 min. (50%) |
| Evaluation of Module Examination: | Performance Verification – graded |
| Limited Number of Participants: | 25 |
| Part of the Study Programme: |
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| Remarks: | Please bring your laptop! |
| Module Components: | 240740 Lecture/Exercise: Applied Biostatistics for environmental data |
| Components to be offered in the Current Semester: |