Course detail
Biostatistics
FEKT-BPC-STAAcad. year: 2023/2024
The course is an introduction to applied data analysis for students of biological and possibly clinical disciplines. The substance is discussed from theoretical principles (principles for statistical estimates, the existence of stochastic distribution, basic statistical tests), simple applications (one-sample and two-sample tests, correlation analysis) to the basics of stochastic modeling and experimental design (design of experiments, regression analysis, analysis of variance). Theory is always discussed in direct connection with practical examples. This course enables students to acquire the basic principles of biostatistical data analysis and prepares candidates for its sole use in their scientific work. The course will also focus on pratical training with the use of all available software tools (Statistica for Windows, SPSS).
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
Rules for evaluation and completion of the course
Written exam for more than 40% of the points.
The final exam is focused on understanding of statistical data analysis and their applications.
Participation in seminar is mandatory, two absences are permitted. In the case of multiple absences, it is possible to substitute the seminar after the agreement with teacher (ideally in another parallel group).
Aims
After completing the course the student is able to:
• apply descriptive statistics on the given data
• select and use tools to test hypotheses
• graphically present statistical data
• clinical studies suggest
• work with databases and statistical programs
Study aids
Prerequisites and corequisites
Basic literature
HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993. ISBN 80-200-0080-1. (CS)
Recommended reading
Classification of course in study plans
- Programme BPC-BTB Bachelor's 2 year of study, winter semester, compulsory
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
1. Statistics for clinical investigation and practice
2. Model distributions and their practical applications
3. The theory of hypotheses testing
4. Statistical tests and modelling
5. Fundamentals of multi-dimensional analyses
6. Statistical tests for evaluation of diagnostic trials
7. Fundamentals of epidemiological data analysis and population hazard evaluation
BLOCK B: Medical data management, information technology in healthcare
8. User’s approach to the computer, his profile, local data
9. Networks, internet
10. Principles of database construction and data management with the view of quality assurance (QA/QC)
BLOCK C. Planning, management and evaluation of clinical studies
11. Basic terminology, ethical and legal aspects
12. Data analysis in healthcare
13. Randomisation and continuous monitoring of the planned experiment
Laboratory exercise
Teacher / Lecturer
Syllabus
1. Statistics for clinical investigation and practice
2. Model distributions and their practical applications
3. The theory of testing statistical hypotheses
4. Statistical tests and modelling
5. Fundamentals of multi-dimensional analysis
6. Statistical tests for evaluation of diagnostic trials
7. Fundamentals of epidemiological data analysis and population hazards evaluation
BLOCK B: Data management in healthcare, information technology application
8. User’s approach to the computer, his profile, local data
9. Networks, internet
10. Principles of database construction and data management with the view of data quality assurance (QA/QC).
BLOCK C. Planning, management and evaluation of clinical studies
11. Basic terminology, ethical and legal aspects
12. Data analysis in healthcare
13. Randomisation and continuous monitoring of the planned experiment