BLKBS051p Biostatistics - lecture

Faculty of Medicine
autumn 2019
Extent and Intensity
0/0. 1 credit(s). Type of Completion: zk (examination).
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Danka Haruštiaková, Ph.D. (seminar tutor)
Mgr. et Mgr. Jiří Kalina, Ph.D. (seminar tutor)
RNDr. Denisa Krejčí (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
Mon 9. 9. 11:00–12:40 A1/609 - IBA (A1,6.p, Kamenice 3), Tue 10. 9. 11:00–12:40 A1/609 - IBA (A1,6.p, Kamenice 3), Wed 11. 9. 10:00–11:40 A1/609 - IBA (A1,6.p, Kamenice 3), Thu 12. 9. 12:00–13:40 A1/609 - IBA (A1,6.p, Kamenice 3), Fri 13. 9. 11:00–12:40 A1/609 - IBA (A1,6.p, Kamenice 3)
BLKZI0211 Computer Science - p.
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
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, 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.
  • 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.
  • Zar, J.H. (1994) Biostatistical methods. Prentice Hall, London. 2nd ed.
  • W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
  • J. Benedík, L. Duąek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
  • HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993. 476 s. ISBN 8020000801. info
Teaching methods
Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.
Assessment methods
Biostatistics course is finished by written exam aimed on principles, assumptions and correct selection of methods for solution of practical examples.
Language of instruction
Further comments (probably available only in Czech)
Study Materials
Information on the extent and intensity of the course: 10.
The course is also listed under the following terms Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, autumn 2018.
  • Enrolment Statistics (recent)
  • Permalink: