Information package & Course catalogue

JAN EVANGELISTA PURKYNĚ UNIVERSITY IN ÚSTÍ NAD LABEM

for academic year 2025/2026
JAN EVANGELISTA PURKYNĚ UNIVERSITY IN ÚSTÍ NAD LABEM

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Course: Statistic methods of medical research

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Course title	Statistic methods of medical research
Course code	KSZD/SMUK2
Organizational form of instruction	Lecture + Seminary
Level of course	Master
Year of study	2
Semester	Summer
Number of ECTS credits	2
Language of instruction	Czech
Status of course	Compulsory
Form of instruction	Face-to-face
Work placements	This is not an internship
Recommended optional programme components	None

Lecturer(s)
Hrach Karel, RNDr. Ph.D.
Course content
Lecture topics: 1st consultation: 1. Continuous probability model, law of large numbers, central limit theorem, confidence intervals. 2. Principle of hypothesis testing. Chi-square tests (goodness-of-fit test, pivot table and independence test). 3. Paired and two-choice test (parametric and non-parametric version). 4. One-factor ANOVA (parametric and non-parametric version). 5. Simple linear regression and correlation. Seminar topics: 2nd consultation: 1. Frequency tables, graphs (R-project: read.table, hist, table, pie), calculations of moments and quantiles (R-project: mean, sd, median, boxplot, ecdf). 2. Normality test, goodness-of-fit test, independence test (R-project: shapiro.test, chisq.test), paired and two-sample test (R-project: t.test, wilcox.test). 3. ANOVA in case of one factor (R-project: aov, kruskal.test), simple linear regression model (R-project: lm). Self-study: 1. Statistical terminology, types of quantities, computerized data recording. 2. Description of categorical quantity, description of quantitative quantity (moments, quantiles) - definition, interpretation. 3. Selection distribution function - examples, interpretation. 4. Random phenomenon, random variable, discrete probability model (binomial, hypergeometric, Poisson). 5. Calculations of probabilities of random events (R-project: pbinom, qbinom, phyper, ppois). 6. Calculations with the Gaussian curve (R-project: dnorm, pnorm).
Learning activities and teaching methods
unspecified
Learning outcomes
The aim of the subject is to repeat and expand the basic knowledge of statistical description of data and to become familiar with the principles of statistical analysis, with an emphasis on biostatistical applications. During seminars in the computer room, students will learn to process statistical data using specialized SW (R-project). Expertise: The graduate of the course knows statistical terminology, knows selected types of statistical tests and understands the general principles of statistical induction. Professional skills: Graduates of the subject can use statistical SW. Graduate is able to choose the right descriptive methods (characteristics, graphs) and is familiar with statistical testing methods. General qualifications: The graduate of the subject is able to independently apply statistical methods in an adequate manner and can correctly interpret statistical results.
Prerequisites
unspecified
Assessment methods and criteria
unspecified min. 80% active attendance on seminars, summarized verification of knowledge and skilld (independently working with statistical SW and interpretation of results)
Recommended literature
HRACH, K. Sbírka úloh ze statistiky. Ústí nad Labem: UJEP, 2010. ISBN 978-80-7044-845-8.. HRACH, K. Základy biostatistiky s využitím Excelu. Ústí nad Labem: UJEP, 2011. ISBN 978-80-7414-398-4.. PEACOCK, J. L., PEACOCK., P. J. Oxford Handbook of Medical Statistics. Oxford: University Press, 517 s. ISBN 978-0-19-955128-6. ZVÁRA, K. Základy statistiky v prostředí R. Praha: Karolinum, 2013. ISBN 978-80-246-2245-3..

Study plans that include the course

Faculty	Study plan (Version)	Category of Branch/Specialization	Recommended year of study	Recommended semester

JAN EVANGELISTA PURKYNĚ UNIVERSITY IN ÚSTÍ NAD LABEM, date of update: 01.04.2025 23:50. Data created for academic year 2025/2026