MFST081c Statistics - practice

Faculty of Medicine
spring 2021
Extent and Intensity
0/1/0. 1 credit(s). Type of Completion: z (credit).
Taught online.
RNDr. Danka Haruštiaková, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
Mgr. et Mgr. Filip Zlámal (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
Contact Person: Mgr. Leona Dunklerová
Supplier department: Institute of Biostatistics and Analyses - Other Departments for Educational and Scientific Research Activities - Faculty of Medicine
Thu 4. 3. 15:00–16:40 D29/347-RCX2, Thu 11. 3. 15:00–16:40 D29/347-RCX2, Thu 18. 3. 15:00–16:40 D29/347-RCX2, Thu 25. 3. 15:00–16:40 D29/347-RCX2, Thu 1. 4. 15:00–16:40 D29/347-RCX2, Thu 8. 4. 15:00–16:40 D29/347-RCX2, Thu 15. 4. 15:00–16:40 D29/347-RCX2, Thu 22. 4. 15:00–16:40 D29/347-RCX2, Thu 29. 4. 15:00–16:40 D29/347-RCX2, Thu 6. 5. 15:00–16:40 D29/347-RCX2, Thu 13. 5. 15:00–16:40 D29/347-RCX2, Thu 20. 5. 15:00–16:40 D29/347-RCX2, Thu 27. 5. 15:00–16:40 D29/347-RCX2, Thu 3. 6. 15:00–16:40 D29/347-RCX2, Thu 10. 6. 15:00–16:40 D29/347-RCX2
no - 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 introduces practical data analysis to students of clinical study specialisations. The course accompanies lectures of MFST081p and shows the computation of presented methods on PC using statistical software. Students will be trained in all aspects of data processing and its statistical analysis (descriptive statistics, one sample and two sample tests, categorical data analysis, ANOVA, correlation analysis, data visualisation).
Learning outcomes
Students will be able after the course to use the folowing data analysis methods:
- Descriptive statistics, data visualisation.
- Distribution of continuous variables.
- One sample tests - parametrical and nonparametrical.
- Two sample tests - parametrical and nonparametrical.
- Analysis of variance (ANOVA), Kruskal-Wallis test.
- Analysis of contingency table.
- Corelation, linear regression.
  • 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, Jerrold H. Biostatistical analysis. Fifth edition. Uttar Pradesh, India: Pearson India Education Services, 2014. 756 stran. ISBN 9789332536678. info
  • GERYLOVOVÁ, Anna and Jan HOLČÍK. Úvod do statistiky. Text pro semináře. 2. vyd. Brno: Masarykova univerzita, 2000. 31 pp. ISBN 80-210-2301-5. info
Teaching methods
Practical training using computers
Assessment methods
Exam based on correct application of statistical methods.
Language of instruction
Further comments (probably available only in Czech)
Information on the extent and intensity of the course: 15.
The course is also listed under the following terms Spring 2000, Spring 2001, Spring 2002, Spring 2003, Spring 2004, Spring 2005, 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.
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