ASTAc Biostatistics - practice

Faculty of Medicine
autumn 2022
Extent and Intensity
0/1/0. 2 credit(s). Type of Completion: z (credit).
Taught in person.
prof. RNDr. Ladislav Dušek, Ph.D. (seminar tutor)
RNDr. Jiří Jarkovský, Ph.D. (seminar tutor)
RNDr. Danka Haruštiaková, Ph.D. (seminar tutor)
Mgr. Renata Chloupková (seminar tutor)
Mgr. Ondřej Ngo (seminar tutor)
RNDr. Michal Svoboda (seminar tutor)
Mgr. Jan Švancara (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/A: Thu 15. 9. 14:00–15:40 D29/347-RCX2, Thu 29. 9. 14:00–15:40 D29/347-RCX2, Thu 13. 10. 14:00–15:40 D29/347-RCX2, Thu 27. 10. 14:00–15:40 D29/347-RCX2, Thu 10. 11. 14:00–15:40 D29/347-RCX2, Thu 24. 11. 14:00–15:40 D29/347-RCX2, Thu 8. 12. 14:00–15:40 D29/347-RCX2
ASTAc/B: Thu 22. 9. to Thu 15. 12. each even Thursday 14:00–15:40 D29/347-RCX2
ASTAc/C: Thu 22. 9. 16:00–17:40 D29/347-RCX2, Thu 6. 10. 16:00–17:40 D29/347-RCX2, Thu 20. 10. 16:00–17:40 D29/347-RCX2, Thu 3. 11. 16:00–17:40 D29/347-RCX2, Thu 1. 12. 16:00–17:40 D29/347-RCX2, Thu 15. 12. 16:00–17:40 D29/347-RCX2
None - basic course.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
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.
  • Introduction to statistics, testing of hypotheses.
  • Tables of distribution functions. Sampling from biological populations, data processing.
  • Introduction to sampling design. Continuous, ordinal and nominal data in biology.
  • Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
  • Application of binomial and Poisson distribution in biology.
  • One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
  • Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
  • Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
  • Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
  • Analysis of variance (ANOVA): one-way and two-way model.
  • Simple linear regression. Linear regression. Introduction to multivariate linear regression.
  • Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
  • 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
Further comments (probably available only in Czech)
Study Materials
Information on the extent and intensity of the course: 15.
Teacher's information
The course is also listed under the following terms Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, autumn 2018, autumn 2019, autumn 2020, autumn 2021, autumn 2023.
  • Enrolment Statistics (autumn 2022, recent)
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