| Course title | Advanced regression methods |
|---|---|
| Course code | KBE/051E |
| Organizational form of instruction | Lecture + Lesson |
| Level of course | Doctoral |
| Year of study | not specified |
| Frequency of the course | In academic years starting with an even year (e.g. 2020/2021), in the winter semester. |
| Semester | Winter |
| Number of ECTS credits | 5 |
| Language of instruction | English |
| 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: Linear, generalized linear and generalized additive models; mixed-effect models - nested and (partially) crossed random effects, modelling correlation structure, GLMM, GAMM; survival analysis with random effects, zero-inflated and zero-truncated models, advanced regression trees and random forests, analysis of phylogenetic data, point pattern analysis; model selection using parsimony, model averaging; bootstrap methods Content of practicals: Practicals are inter-mixed with lectures, complementing the theory
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| Learning activities and teaching methods |
Monologic (reading, lecture, briefing), E-learning
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| Learning outcomes |
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Students will learn advanced ways of modelling data in natural sciences, with a focus on models with a combination of random and fixed effects and also on the selection of model complexity. Students should be enabled to work with such statistical models independently in their research. An important component are the homeworks evaluated by teacher.
Students will be able to choose correctly - for datasets produced in the field of natural sciences - the type of regression models: coding of explanatory variables, choice of fixed and random effects, scale transformation for explanatory and response variables, testing significances of individual effects, methods of selection of explanatory variables. They will be also able to effectively apply advanced types of tree models (e.g. boosted regression trees, regression forests). They will manage the use of methods modelling phylogenetic correlations among taxa in the field of comparative ecology and to correctly use the non-parametric generalized additive models (GAM and GAMM). |
| Prerequisites |
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Basic knowledge of working with R software, namely fitting and interpreting linear regression, ANOVA, and GLMs, is assumed and checked by an introductory test. Minimum of B+C students: 5
KBE/050 ----- or ----- KBE/785E |
| Assessment methods and criteria |
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Written examination, Interim evaluation
Students should study the materials provided by lecturer before the corresponding topic is discussed in the lecture-practicals. Students are provided with homeworks (5-7 times) during the term, and their solutions are scored by the lecturer. The credit before exam is based on introductory test (0-10 points) and points for the correctly solved homeworks (1 pt per fully correct solution): their sum must be at least 12. Exam is written - two examples to be analysed, scored with 0-10 points. To successfully pass, at least 4 points must be gained. |
| 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): Zoology (1) | Category: Biology courses | - | Recommended year of study:-, Recommended semester: Winter |
| Faculty: Faculty of Science | Study plan (Version): Hydrobiology (1) | Category: Biology courses | - | Recommended year of study:-, Recommended semester: Winter |
| Faculty: Faculty of Science | Study plan (Version): Botany (1) | Category: Biology courses | - | Recommended year of study:-, Recommended semester: Winter |
| Faculty: Faculty of Science | Study plan (Version): Botany (1) | Category: Biology courses | - | Recommended year of study:-, Recommended semester: Winter |
| Faculty: Faculty of Science | Study plan (Version): Entomology (1) | Category: Biology courses | - | Recommended year of study:-, Recommended semester: Winter |
| Faculty: Faculty of Science | Study plan (Version): Ecosystem Biology (1) | Category: Ecology and environmental protection | - | Recommended year of study:-, Recommended semester: Winter |
| Faculty: Faculty of Science | Study plan (Version): Zoology (1) | Category: Biology courses | - | Recommended year of study:-, Recommended semester: Winter |