Course detail
Biostatistics
FCH-MC_BSTAcad. year: 2021/2022
Biostatistics consist of both theoretical and practical education which is aimed on the statistical field of descriptive data analysis, hypothesis testing, probability theory, correlation and regression analysis and multivariate data analysis. Theoretical knowledge from lectures are transferred to practice through practical lectures on computers. Student will become familiar with advanced statistical software such as Statistica. During the exercises, scientific-research problems are solved on model data, but also on current datasets of students, derived from theirs doploma theses.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Learning outcomes of the course unit
a) theoretical knowledge of basic statistical apparatus for evaluation of results in chemical, biological and biochemical field,
b) the ability to apply statistical principles to solve practical problems,
c) skills to process data using advanced software Statistica,
d) gain of overview to apply bio-statistics outputs in other subjects of the discipline, science, research and work life,
e) competence to process the final student's work statistically correctly.
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Seminars (2 lessons per 2 weeks): workshop, individual work, discussion methods.
Electronic Support: The Biostatistics course developed in the Moodle e-learning system, video database of lectures
Assesment methods and criteria linked to learning outcomes
Solve all the given test during semester.
At the end of the semester, full-time credit test for 50 points, minimum for success: 25 points.
Presentation of essential results from the statistical evaluation of a given research problem
Course curriculum
1. Introduction to biostatistics, basic statistical terms and methods
2. Estimation of the mean value, interval estimation of the mean value, assessment of correctness and conformity of results
3. Data distribution analysis, testing for outliers
4. Parametric and nonparametric hypothesis testing - T-Test, U-Test, ANOVA, MANOVA, Kruskal-wallis ANOVA
5. Correlation and regression analysis of data, application of linear regression in biotechnological and chemical practice, polynomial regression, determination of polynomial degree
6. Multivariate data analysis 1 - Cluster analysis, Principal component analysis
7. Multivariate data analysis 2 - Canonical and linear discrimination analysis
All topics are further practically taught in exercises on PC, using software Statistica and Excel.
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Lepš J., Šmilauer P.: Biostatistika. Nakladatelství Jihočeské univerzity, České Budějovice, Česká republika, 2016. (CS)
Meloun M., Militký J.: Statistická analýza experimentálních dat. Academia, Praha 2004. (CS)
Meloun M.: Počítačová analýza vícerozměrných dat, Academia, Praha, Česká republika, 2005. (CS)
Meloun M.: Statistická analýza vícerozměrnýcg dat v příkladech, Karolinium, Praha, Česká republika, 2017. (CS)
Recommended reading
Elearning
Classification of course in study plans
- Programme NPCP_CHMA Master's
specialization BF , 2 year of study, winter semester, compulsory-optional
specialization CHBL , 2 year of study, winter semester, compulsory-optional - Programme NPCP_CHTPO Master's
specialization PCH , 2 year of study, winter semester, compulsory-optional
specialization CHPL , 2 year of study, winter semester, compulsory-optional - Programme NKCP_CHTPO Master's
specialization PCH , 2 year of study, winter semester, compulsory-optional
specialization CHPL , 2 year of study, winter semester, compulsory-optional
specialization BCH , 2 year of study, winter semester, compulsory-optional - Programme NPCP_CHTP Master's
branch NPCO_CHTP , 2 year of study, winter semester, compulsory
- Programme NKCP_CHTP Master's
branch NKCO_CHTP , 2 year of study, winter semester, compulsory
- Programme NPCP_MA Master's
branch NPCO_MA , 2 year of study, winter semester, compulsory-optional
Type of course unit
Guided consultation in combined form of studies
Teacher / Lecturer
Elearning