| Course Unit Code | 546-0169/01 |
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| Number of ECTS Credits Allocated | 3 ECTS credits |
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| Type of Course Unit * | Compulsory |
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| Level of Course Unit * | First Cycle |
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| Year of Study * | Second Year |
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| Semester when the Course Unit is delivered | Winter Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | Czech |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| MOT127 | Mgr. Oldřich Motyka, Ph.D. |
| Summary |
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| Students will be acquainted with the basic methods of preparation of a sampling plan, collection, standartization/tranformation and evaluation of biological data. They will learn to use and interpret basic statistical methods with regard to the specifics of biological data. They will also get acquainted with the basics of biostatistical models and statistical evaluation of diversity. Working with data will be using MS Excel tools and R program and its libraries. |
| Learning Outcomes of the Course Unit |
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| Students will be able to analyze and evaluate quantitative, semi-quantitative and qualitative biological data. They will be able to correctly describe and visualize these data using the basic characteristics of descriptive statistics, identify and verify erroneous and outliers and the distribution from which the biological data come. They will also be able to formulate a statistical hypothesis, use appropriate test statistics and correctly interpret the results. They will also gain basic skills in correlation and regression analysis of biological data. |
| Course Contents |
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1. Preparation of sampling plan, storage of biological data.
2. Types of biological data - quantitative and qualitative data, description, measures of location and variability, visualization, identification of outliers.
3. Random variable and probability distribution (normal, standardized normal) and their applications in biology and ecology.
4. Other types of distributions (binomial, Poisson) and their applications in biology and ecology).
5. Introduction to hypothesis testing - null and alternative hypothesis, type I. and II. errors, statistical test and its strength, p - value.
6. The problem of multiple hypothesis testing in biology and ecology and correction procedures.
7. One-sample tests - parametric and nonparametric methods.
8. Comparison of parameters of two sample populations - parametric and nonparametric methods.
9. Analysis of variance (ANOVA) - evaluation of variance of biological and ecological data, evaluation of normality, Kruskal - Wallis test - nonparametric alternative ANOVA.
10. Correlation analysis - Pearson's and Spearman's correlation coefficient, similarity measures in ecology (similarity coefficients, correlation coefficients, covariance).
11. Regression analysis - linear regression, assumptions of linear model, estimation of regression model parameters, detemination coefficient, basic statistical tests.
12. Regression analysis - polynomial regression, basic statistical tests, residue analysis.
13. Introduction to multiple linear regression - types of variable interactions, multicollinearity, the problem of missing data, applications to biological and ecological data. |
| Recommended or Required Reading |
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| Required Reading: |
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SOKAL, R., R.,ROHLF, F.J. Biometry : the principles and practice of statistics in biological research. 4th ed. New York, N.Y.: W.H. Freeman and Company, 2012. xix, 937. ISBN 9780716786047
ZAR, J., H. Biostatistical analysis. Fifth edition. Uttar Pradesh, India: Pearson India Education Services, 2014. 756 stran. ISBN 9789332536678 |
HENDL, Jan. Přehled statistických metod zpracování dat. Praha: Portál, 2012. ISBN 978-80-262-0200-4
ZVÁRA K. Biostatistika. Praha: Nakladatelství Karolinum, 2006
LEPŠ, J. a P. ŠMILAUER. Biostatistika. České Budějovice: Episteme, 2016. ISBN 978-80-7394-587-9
SOKAL, R. a F. J. ROHLF. Biometry: The Principles and Practice of Statistics in Biological Research. New York: W.H. Freeman and Company, 2012. ISBN 978-0-7167-8604-7
ZAR, J. H. Biostatistical Analysis. Uttar Pradesh, India: Pearson India Education Services, 2014. ISBN 978-9-3325-3667-8 |
| Recommended Reading: |
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CRAWLEY, M., J. Statistics : an introduction using R. Chichester: John Wiley & Sons, 2005. xiii, 327. ISBN 0470022973
PETRIE, A., WATSON, P. Statistics for Veterinary and Animal Science. Wiley-Blackwell; 2nd ed, 2006
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ZVÁRA, K. Základy statistiky v prostředí R. Praha: Karolinum, 2013. 259 s. ISBN 978-80-246-2245-3
PEKÁR, S. a M. BRABEC. Moderní analýza biologických dat. Praha: Scientia, 2009. ISBN 978-80-8696-044-9
CRAWLEY, M. J. Statistics: An introduction using R. Chichester: John Wiley & Sons, 2005. xiii, 327 s. ISBN 0470022973
PETRIE, A. a P. WATSON. Statistics for Veterinary and Animal Science. Wiley-Blackwell, 2006 |
| Planned learning activities and teaching methods |
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| Tutorials |
| Assesment methods and criteria |
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| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
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| Graded credit | Graded credit | 100 | 51 |