LF:MNBS081p Biostatistics - Course Information
MNBS081p Biostatistics - lecture
Faculty of Medicinespring 2025
- Extent and Intensity
- 1/0/0. 2 credit(s). Type of Completion: k (colloquium).
In-person direct teaching - Teacher(s)
- prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Michal Svoboda (lecturer)
RNDr. Danka Haruštiaková, Ph.D. (lecturer)
MVDr. Halina Matějová (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
Institute of Biostatistics and Analyses – Other Departments for Educational and Scientific Research Activities – Faculty of Medicine
Contact Person: MVDr. Halina Matějová
Supplier department: Institute of Biostatistics and Analyses – Other Departments for Educational and Scientific Research Activities – Faculty of Medicine - 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
- Nutrition therapist for child nutrition and Nutrition therapist for adult nutrition (programme LF, N-SZ)
- Dietetian (programme LF, N-VDD)
- Course objectives
- The course is aimed on applied data analysis for students of biological and clinical sciences. The presented topics range from theoretical background (statistical estimates, statistical distributions, statistical hypothesis testing) and simple applications (one sample and two sample tests, correlation analysis) to stochastic modelling (experimental design, regression analysis, analysis of variance).
- Learning outcomes
- At the end of the course the students are able to:
- define structure of dataset for statistical analysis;
- visualize the data and interpret data visualisation;
- identify correct methods of descriptive statistics;
- formulate hypothesis for statistical testing;
- select the correct statistical tests for hypotheses confirmation/refusal;
- interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature;
- assess the applicability of statistical methods on various types of data. - 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
- Teaching methods
- lectures supplemented by examples of practical exercises
- Assessment methods
- The course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further comments (probably available only in Czech)
- The course is taught annually.
Note related to how often the course is taught: samostudium.
Information on the extent and intensity of the course: 15.
- Enrolment Statistics (spring 2025, recent)
- Permalink: https://is.muni.cz/course/med/spring2025/MNBS081p