Course: Biostatistics

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Course title Biostatistics
Course code KBE/012
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study not specified
Frequency of the course In each academic year, in the summer semester.
Semester Summer
Number of ECTS credits 7
Language of instruction Czech
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Šmilauer Petr, doc. RNDr. Ph.D.
  • Lepš Jan, prof. RNDr. CSc.
  • Koutecký Petr, Mgr. Ph.D.
  • Lisner Aleš, Mgr.
Course content
Content of lectures: Basic concepts, deductive and inductive thinking, general scientific method, hypothesis testing, confirmatory and exploratory data analysis. Statistical population and random sample, statistical interference. Statistical distributions, normal distribution, descriptive statistics. Statistical hypothesis testing, categorical data analysis. Contingency tables. Comparison of means (t-tests, ANOVA - various models). Relationship of two quantitative variables (regression and correlation). Discrete distributions (Poisson, binomial) and their use. Multivariate methods . Nonparametric methods are introduced together with corresponding parametric methods. Content of practicals: In practicals, students learn the correct use of statistical methods using the R (and RStudio) software.

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Written action (comprehensive tests, clauses), Demonstration, Projection, Skills training
  • Class attendance - 56 hours per semester
  • Preparation for classes - 28 hours per semester
  • Preparation for credit - 40 hours per semester
  • Semestral paper - 16 hours per semester
  • Preparation for exam - 40 hours per semester
Learning outcomes
This introductory statistical course is devoted to basic principles of statistical reasoning and applications of data analysis in the field of biological sciences. Students acquire the ability to properly apply the usual statistical methods in biology. This includes correct sampling and experimental design, as well as correct interpretation of results of statistical analyses. The program of the course is designed according to the needs of students analyzing data in their own projects, particularly in preparation of their theses. Practical skills of data analysis are learned with the statistical software R.
Students will be able to: (1) transform research questions into verifiable research hypotheses and corresponding statistical null hypotheses, as well as propose the design of an experiment or observation that will lead to high-quality data (2) identify data types corresponding to particular problem and determine the types of statistical models appropriate for those data types (3) choose and apply appropriate kinds of statistical methods and models, including e.g. goodness-of-fit test, analysis of contingency tables, single-sample, pairwise and two-sample t-value tests (plus corresponding non-parametric tests), analysis of variance (and corresponding non-parametric tests) including the analysis of data with a block structure, methods of simple and multiple regression. They will be also able to verify basic assumptions of those methods (4) summarize analysed data using sample statistics and appropriate graphs, as well as to visualize the main conclusions of their analyses
Prerequisites
Understanding of mathematics in the extent covered by secondary school curriculum (linear algebra, probability theory).

Assessment methods and criteria
Essay, Combined exam, Test, Interim evaluation

Participation in practicals is checked. In the mid of the term, abilities obtained in practicals are checked in a test, with its results combined with a final test at the end of the term. Before oral exam, student needs to submit an essay representing a fictional research paper, with a focus on the data analysis. This essay is discussed and scored during the oral exam, together with student's presentation of two randomly selected topics out of the course' contents.
Recommended literature
  • Lepš J., Šmilauer P. Biostatistika. Episteme, České Budějovice, 2016. ISBN 978-80-7394-587-9.
  • Sokal R.R., Rohlf F.J. Biometry. 4th edition. Freeman, San Francisco, 2012.
  • Zar J.H. Biostatistical analysis, 5th edition. Pearson, San Francisco, 2010.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Secondary Schools Teacher Training in Mathematics (1) Category: Pedagogy, teacher training and social care - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Environmental Management (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Biomedical Laboratory Techniques (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Experimental Biology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Arts Study plan (Version): Archeology (2016) Category: History courses 2 Recommended year of study:2, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Environmental Management (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Mathematics for future teachers (1) Category: Mathematics courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Biology (1) Category: Biology courses 2 Recommended year of study:2, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Environmental Management (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Mathematics for future teachers (1) Category: Mathematics courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Environmental Management (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Applied Mathematics (2010) Category: Mathematics courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Mathematics for future teachers (1) Category: Mathematics courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Secondary Schools Teacher Training in Mathematics (1) Category: Pedagogy, teacher training and social care - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Mathematics for future teachers (1) Category: Mathematics courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Experimental Biology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Secondary Schools Teacher Training in Mathematics (2012) Category: Pedagogy, teacher training and social care - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Secondary Schools Teacher Training in Mathematics (1) Category: Pedagogy, teacher training and social care - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Mathematics for future teachers (1) Category: Mathematics courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Chemistry (1) Category: Chemistry courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Arts Study plan (Version): Archeology (2016) Category: History courses 2 Recommended year of study:2, Recommended semester: Summer