BMAM041 Analysis and Data Management for Healthcare Specialisation

Faculty of Medicine
spring 2025
Extent and Intensity
2/0/0. 2 credit(s). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
RNDr. Danka Haruštiaková, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
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
Prerequisites (in Czech)
Předpokladem je pouze základní zkušenosti s prací na PC.
Course Enrolment Limitations
The course is offered to students of any study field.
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
  • ALTMAN, Douglas G. Practical statistics for medical research. 1st ed. Boca Raton: Chapmann & Hall/CRC, 1991, xii, 611. ISBN 0412276305. info
  • HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
  • MELOUN, Milan and Jiří MILITKÝ. Statistické zpracování experimentálních dat. [1. vyd.]. Praha: Plus, 1994, 839 s. ISBN 80-85297-56-6. info
  • ZAR, Jerrold H. Biostatistical analysis. 4th ed. Upper Saddle River, N.J.: Prentice Hall, 1999, [941] s. ISBN 013081542X. info
Teaching methods
Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.
Assessment methods
Course is finished by written exam (colloquium) aimed on principles, prerequisties and correct selection of methods for solution of practical examples.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught: every week.
Information on the extent and intensity of the course: 30.
The course is also listed under the following terms Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, spring 2019, spring 2020, spring 2021, spring 2022, spring 2023, spring 2024.
  • Enrolment Statistics (spring 2025, recent)
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