In order to pass the course, the student must have active participation in lectures and practical teaching. The prerequisite for passing the examination is the preparation and defence of a seminar paper on the topic assigned by the supervisor (in the range A-E), which is the result of self-study. The examination is awarded on the basis of an assessment of the knowledge acquired (in the A-E range).

After completing the course, the student will be able to set up an experimental design to objectively evaluate the obtained results using properly selected statistical methods, will be able to properly document, control and process the obtained data. The course focuses on the statistical methods most commonly used in the evaluation of biological experiments (biostatistics), i.e., in addition to basic descriptive statistics (mean, mode, median, variance, etc.), tests of normality of the data sets and the subsequent use of parametric or non-parametric analyses. Within parametric analyses, in particular the most commonly used analyses of variance (T-test, univariate and multivariate ANOVA), including complementary tests. Furthermore, students will be introduced to the use of regression and correlation analysis and the analysis of contingency tables and number series dynamics in the evaluation of experiments. This will result in the proper interpretation and presentation of the results obtained.

planning and proper design of an experiment; determination of hypotheses and selection of the correct statistical method; data collection and processing; descriptive statistics; normality tests, log transformation; analysis of variance; parametric and non-parametric tests; regression analysis; correlation analysis; contingency tables and their analysis; characterization of the dynamics of numerical series; interpretation and presentation of results.

planning and proper design of an experiment; determination of hypotheses and selection of the correct statistical method; data collection and processing; descriptive statistics; normality tests, log transformation; analysis of variance; parametric and non-parametric tests; regression analysis; correlation analysis; contingency tables and their analysis; characterization of the dynamics of numerical series; interpretation and presentation of results.

Zar, J.H.: Biostatistical analysis, 5th edition, Pearson Education, 2010, ISBN: 978-0-13-100846-5

Löster, T., Danko, J., Radváková, V.: Methods of scientific work, Melandrium, 2020, ISBN: 978-80-87990-23-0

Lepš, J. , Šmilauer P. : Biostatistics, 2016, ISBN: 978-80-7394-587-9.

Continuous assessment:

no

Conditions for completion of course:

In order to pass the course, the student must have active participation in lectures and practical teaching. The prerequisite for passing the examination is the preparation and defence of a seminar paper on the topic assigned by the supervisor (in the range A-E), which is the result of self-study. The examination is awarded on the basis of an assessment of the knowledge acquired (in the A-E range).

Final assessment:

The final assessment is given on the basis of the assessment of the exam and the seminar work (in the range of A-E).

no