| 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) |
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| Course content |
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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.
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| Learning activities and teaching methods |
Monologic (reading, lecture, briefing), Written action (comprehensive tests, clauses), Demonstration, Projection, Skills training
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| Learning outcomes |
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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 |
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Understanding of mathematics in the extent covered by secondary school curriculum (linear algebra, probability theory).
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| Assessment methods and criteria |
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Essay, Combined exam, Test, Interim evaluation
Participation in practicals is checked (at most 2 unexplained absences allowed). In the mid of the term, abilities obtained in practicals are checked in a test (0-5 pts), with its results combined with a final test at the end of the term (0-45 pts). Minimum count of points for pre-exam credit is 27. 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 (0-5 pts), together with student's presentation of two randomly selected topics (0-5 pts each). To pass the exam, minimum sum of points is 8. |
| Recommended literature |
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| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester | |
|---|---|---|---|---|
| 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): 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 Arts | Study plan (Version): Archaeology (2016) | Category: History courses | 2 | Recommended year of study:2, 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): Environmental Management (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): Applied Mathematics (2010) | 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): 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 Arts | Study plan (Version): Archaeology (2016) | Category: History courses | 2 | Recommended year of study:2, 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): 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 |