The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 15 student(s).
Current registration and enrollment status: enrolled: 1/15, only registered: 0/15, only registered with preference (fields directly associated with the programme): 0/15
Fields of study the course is directly associated with
In this course you can learn main statistical methods (mainly those multidimensional) needed by you biosystematical, taxonomical and phylogenetical research. The main objective is learn you (without redundant mathematics) to understand and to actively use these methods by designing of your experiments, analyses, and sampling. You will train each method yourself in practicals following the theoretical lectures.
You should learn how to correctly and effectively form hypotheses, ask research questions; how many, why, from where, and which one samples to collect; how many times and what to measure. You will learn to inspect multidimensional data by ordination diagrams (PCA, PCoA, CVA, NMDS), to test mutually various multidimensional data sets (Mantel test, Procrustes analysis), to construct and to test classifications of your samples, and to find out the most proper identification characters, e.g. useful for identification keys (discriminant analysis). You will get knowledge how to build phenetic and evolutionary trees from morphological and molecular/sequence data (UPGMA, NJ trees, LS trees, minimum evolution trees, maximum parsimony), how to understand and interpret trees, and how to test character evolution.
1. Basic classification of methods and data types; basic descriptive statistics
2. Simple statistical tests I, probability, significance
3. Simple statistical tests II, correlation, regression, experimental design, pseudoreplication, hypotheses formulation
4. Similarity coefficients, similarity matrices, testing of matrix data
5. Ordination methods I – basic classification of methods, construction of ordination diagrams
6. Ordination methods II – understanding of ordination diagrams, group testing, comparison of different ordinations
7. Cluster analysis I – classification of methods, agglomerative algorithms, tree building
8. Cluster analysis II – understanding dendrograms, testing of dendrograms reliability, comparison of different dendrograms
9. Discriminant analysis, selection of proper determination characters
10. Evolutionary trees I – phylogenetic approach, phylogenetic terms and the tree description, alignment
11. Evolutionary trees II – tree building methods and criteria (maximum likelihood, parsimony), testing or tree quality and reliability, understanding of trees
12. Evolutionary trees III – testing of character evolution, molecular clocks
13. Statistics on web, graphic presentation of results
To get credits, students should prepare an analysis of own or literature data.
Language in which the course is taught
The course is taught annually.
The course is taught: every week.