Biostatistics - MS710P65

• Title: Biostatistics
• Czech title: Biostatistika
• Guaranteed by: Institute of Applied Mathematics and Information Technologies (31-710)
• Faculty: Faculty of Science
• Actual: from 2024
• Semester: summer
• E-Credits: 5
• Examination process: summer s.:
• Hours per week, examination: summer s.:2/2, C+Ex [HT]
• Capacity: 25
• Min. number of students: unlimited
• 4EU+: no
• Virtual mobility / capacity: no
• State of the course: taught
• Language: English
• Note: enabled for web enrollment; priority enrollment if the course is part of the study plan
• Guarantor: RNDr. Monika Pecková, Ph.D.
• Teacher(s): RNDr. Monika Pecková, Ph.D.
• Incompatibility : MS710P09
• Is incompatible with: MS710P09

Annotation

English

This is an introductory course of biostatistics. The students will learn the principles of estimation and statistical testing. Statistical methods will be applied on the types of data commonly encountered in medicine and biology. The students will learn to analyse the data independently, using statistical package R.

Last update: Pecková Monika, RNDr., Ph.D. (14.03.2019)

Czech

Předmět je úvodem do biostatistiky. Studenti se naučí základy pravděpodobnosti a principy statistického uvažování, zejména odhadování a testování statistických hypotéz. Statistické metody budou aplikovány na typy dat běžně se vyskytující v medicíně a biologii. Důraz bude kladen nejenom na schopnost správně používat statistické metody, ale především na schopnost správně interpretovat výsledky. Cvičení budou probíhat v počítačové laboratoři, kde se studenti se naučí samostatně analyzovat data s použitím statistického programu R.

Last update: Pecková Monika, RNDr., Ph.D. (14.03.2019)

Literature

English

 

Robert F. Woolson, William R. Clarke: Statistical Methods for the Analysis of Biomedical Data.

Marcello Pagano, Kimberlee Gauvreau: Principles of Biostatistics

 

Last update: Pecková Monika, RNDr., Ph.D. (14.02.2025)

Czech

Robert F. Woolson, William R. Clarke: Statistical Methods for the Analysis of Biomedical Data

Marcello Pagano, Kimberlee Gauvreau: Principes of Biostatistics

Last update: Pecková Monika, RNDr., Ph.D. (14.02.2025)

Requirements to the exam

English

Several homeworks will be reqiuired. The course exam will be practical (in class analysis of data and discusssion).

Last update: Rubešová Jana, RNDr., Ph.D. (05.03.2019)

Czech

Zápočet: několik domácích úkolů.

Zkouška bude praktická, půjde o analýzu dat a diskusi o výsledku.

Last update: Rubešová Jana, RNDr., Ph.D. (05.03.2019)

Syllabus

English

1. Types of data; samples and populations; descriptive statistics.
2. Introduction to probability; independence; Bayes theorem.
3. Random variables; probability distributions; quantiles; mean; variance.

4. Discrete distributions: binomial, Poisson; continuous distributions: normal,

Student's t, chi-square; central limit theorem.
5. Introduction to estimation and hypothesis testing; confidence intervals.
6. Testing the hypotheses about the mean of one sample, one sample t-test; confidence interval for the mean.

7. Testing the hypotheses about the means of two samples; paired t-test; two-sample t-test; nonparametric tests.
8. Introduction to analysis of variance.
9. Correlation; simple regression; least squares method; assumptions of regression.

10. Multiple regression models, confounding, choice of the model.
11. Multinomial distribution, goodness-of-fit tests, tests of independence for discrete variables.

12. Contingency tables, Fisher exact test, McNemar test of symmetry.

13. Designs of epidemiological studies; disease frequency; estimation of risk in epidemiology.

 

Last update: Rubešová Jana, RNDr., Ph.D. (05.03.2019)