LF:ASTAc Biostatistics - practice - Course Information
ASTAc Biostatistics - practice
Faculty of Medicineautumn 2025
- Extent and Intensity
- 0/1/0. 2 credit(s). Type of Completion: z (credit).
In-person direct teaching - Teacher(s)
- prof. RNDr. Ladislav Dušek, Ph.D. (seminar tutor)
RNDr. Jiří Jarkovský, Ph.D. (seminar tutor)
RNDr. Danka Haruštiaková, Ph.D. (seminar tutor)
RNDr. Michaela Cvanová, Ph.D. (seminar tutor)
Mgr. Renata Chloupková (seminar tutor)
Mgr. Ondřej Ngo, Ph.D. (seminar tutor)
RNDr. Michal Svoboda (seminar tutor) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
Institute of Biostatistics and Analyses – Other Departments for Educational and Scientific Research Activities – Faculty of Medicine
Supplier department: Institute of Biostatistics and Analyses – Other Departments for Educational and Scientific Research Activities – Faculty of Medicine - Timetable of Seminar Groups
- ASTAc/1: Thu 25. 9. 16:00–17:40 D29/347-RCX2, Thu 9. 10. 16:00–17:40 D29/347-RCX2, Thu 23. 10. 16:00–17:40 D29/347-RCX2, Thu 6. 11. 16:00–17:40 D29/347-RCX2, Thu 20. 11. 16:00–17:40 D29/347-RCX2, Thu 4. 12. 16:00–17:40 D29/347-RCX2, Thu 18. 12. 16:00–17:40 D29/347-RCX2, D. Haruštiaková
ASTAc/2: Thu 18. 9. 16:00–17:40 D29/347-RCX2, Thu 2. 10. 16:00–17:40 D29/347-RCX2, Thu 16. 10. 16:00–17:40 D29/347-RCX2, Thu 30. 10. 16:00–17:40 D29/347-RCX2, Thu 13. 11. 16:00–17:40 D29/347-RCX2, Thu 27. 11. 16:00–17:40 D29/347-RCX2, Thu 11. 12. 16:00–17:40 D29/347-RCX2, D. Haruštiaková
ASTAc/3: Thu 25. 9. 14:00–15:40 D29/347-RCX2, Thu 9. 10. 14:00–15:40 D29/347-RCX2, Thu 23. 10. 14:00–15:40 D29/347-RCX2, Thu 6. 11. 14:00–15:40 D29/347-RCX2, Thu 20. 11. 14:00–15:40 D29/347-RCX2, Thu 4. 12. 14:00–15:40 D29/347-RCX2, Thu 18. 12. 14:00–15:40 D29/347-RCX2, D. Haruštiaková
ASTAc/4: Thu 18. 9. 14:00–15:40 D29/347-RCX2, Thu 2. 10. 14:00–15:40 D29/347-RCX2, Thu 16. 10. 14:00–15:40 D29/347-RCX2, Thu 30. 10. 14:00–15:40 D29/347-RCX2, Thu 13. 11. 14:00–15:40 D29/347-RCX2, Thu 27. 11. 14:00–15:40 D29/347-RCX2, Thu 11. 12. 14:00–15:40 D29/347-RCX2, D. Haruštiaková - Prerequisites
- None - basic course.
- 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
- Biomedicínská technika a bioinformatika (programme LF, C-CV)
- Course objectives
- The course is basic introduction into practical data analysis for students of biology and clinical study specialisations. The course accompanies lectures of Bi5040 Biostatistics and shows the computation of presented methods on PC using statistical software (descriptive statistics, one sample and two sample tests, categorical data analysis, ANOVA, correlation and regression analysis, data visualisation, basics of experimental design).
- Learning outcomes
- The students will be able after the course to use the folowing data analysis methods:
Descriptive statistics, data visualisation.
Tables of distribution functions.
Introduction to sampling design and experimental design.
Distribution of continuous and bivariate variables.
Application of binomial distribution in biology.
One sample testing.
Two sample testing.
Application of goodness-of-fit test in biology.
Analysis of variance (ANOVA), non - parametric ANOVA.
Corelation, linear regression. - Syllabus
- 1. Data processing – principles of correct data manipulation. MS Office Excel – appropriate tool for storing, organizing, and manipulating data. • 2. Introduction to statistics. Data types in medicine and biology; nominal, ordinal, continuous variable. Visualization of quantitative and qualitative (categorical) variables. • 3. Descriptive statistics. Mean, median, quantiles, variance. Frequency table. • 4. Distribution of continuous variables. Normal distribution, log-normal distribution. • 5. Principles of hypotheses testing. Definition of null and alternative hypothesis. Significance level. Type I and type II error. • 6. Graphical examining of normal distribution (histogram, normal-probability plot). Shapiro-Wilk test – a test of normality. • 7. Parametrical tests: t-tests. One-sample t-test, two-sample t-test, t-test for dependent samples. • 8. Analysis of variance ANOVA. • 9. Nonparametrical tests: one-sample Wilcoxon test, Mann-Whitney U test, Wilcoxon test for dependent samples, Kruskal-Wallis test. • 10. Definition of contingency table and its analysis: Pearson chi-square test, Fisher exact test, McNemar test. • 11. Correlation. Pearson correlation coefficient, Spearman correlation coefficient. • 12. Introduction to regression analysis. Linear regression.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Practical training using computers
- Assessment methods
- Exam on computers based on correct application of statistical methods on example data.
- Language of instruction
- Czech
- Further Comments
- Study Materials
- Teacher's information
- http://www.iba.muni.cz/vyuka/
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/med/autumn2025/ASTAc