PřF:Bi9127 Data evaluation in HUBI - Course Information
Bi9127 Data evaluation in Human BiologyFaculty of Science
- Extent and Intensity
- 0/2/0. 2 credit(s). Type of Completion: zk (examination).
- doc. Mgr. Tomáš Zeman, Ph.D. (seminar tutor)
- Guaranteed by
- doc. RNDr. Eva Drozdová, Ph.D.
Department of Experimental Biology - Biology Section - Faculty of Science
Contact Person: doc. RNDr. Eva Drozdová, Ph.D.
Supplier department: Department of Experimental Biology - Biology Section - Faculty of Science
- Course Enrolment Limitations
- The course is only offered to the students of the study fields the course is directly associated with.
- fields of study / plans the course is directly associated with
- Human Biology (programme PřF, N-BCL)
- Special Biology (programme PřF, N-EXB, specialization Antropobiology and Antropogenetics)
- Course objectives
- Students will get acquainted with basic statistical methods for evaluation of experimental data in human biology and will learn to use them on real data. After completing the course, they will be able to perform basic statistical analysis of experimental data in R software.
- Learning outcomes
- Student will be able to:
- to choose appropriate statistical methods for evaluating specific experimental data in human biology;
- statistically evaluate the data in the statistical program R with the use of basic statistical methods
- interpret the results of statistical evaluation of the data
- use statistical software R
- Basics of R software: installation, R language
- Types of data: nominal scale, ordinal scale, interval scale, and ratio scale
- Descriptive statistics: modus, median, arithmetic mean, geometric mean, standard deviation
- Hypothesis testing: null hypothesis, alternative hypothesis
- Parametric statistics: T-test, ANOVA
- Non-parametric statistics: Sign test, Wilcoxon test, Kolmogorov-Smirnov test
- Normality tests: Kolmogorov-Smirnov test, Lilliefors test, Shapiro–Wilk test
- Contingency table analysis: Fisher's exact test, Chi-squared test
- Correlation: Pearson' correlation coefficient, Spearman's rank correlation coefficient, basics of linear regression
- KONEČNÁ, Kateřina and Jan KOLÁČEK. Jak pracovat s jazykem R (How to work with R language). 2011. 84 pp. info
- BUDÍKOVÁ, Marie, Maria KRÁLOVÁ and Bohumil MAROŠ. Průvodce základními statistickými metodami (Guide to basic statistical methods). vydání první. Praha: Grada Publishing, a.s., 2010. 272 pp. edice Expert. ISBN 978-80-247-3243-5. URL info
- Teaching methods
- theoretical lectures, statistical data analysis using R software, class discussion
- Assessment methods
- final project presentation
- Language of instruction
- Further Comments
- Study Materials
The course is taught annually.
The course is taught: every other week.
- Enrolment Statistics (Autumn 2019, recent)
- Permalink: https://is.muni.cz/course/sci/autumn2019/Bi9127