BB852: Data handling, visualization and statistics
Students taking the course are expected to:
- Have basic knowledge of statistics and mathematics
- Have a Bachelor’s degree in a field with some level or focus on quantitative methods
- Develop skills in data exploration, visualisation and interpretation.
- Develop the students’ competence to undertake appropriate quantitative analysis of the student’s own data (e.g. masters project).
- Develop skills to critically evaluate statistical analyses (e.g. in scientific papers/presentations).
- Develop skills to use the R statistical software for analysis and graphing.
- Structure personal learning
Expected learning outcome
- formulate appropriate scientific questions in biological disciplines, e.g. ecology, physiology, neurobiology, and evolutionary biology.
- design appropriate laboratory or field studies in order to address scientific questions.
- manipulate and explore visually data from experimental and field studies.
- select appropriate statistical approaches for a variety of different data types.
- fit and interpret appropriate regression models (ordinary least squares, generalised linear models), randomisation tests, and “classical tests” (t-tests, chi-squared tests etc.).
- understand and commonly used model selection approaches.
- present quantitative the results from biological studies, including graphically.
- Questions and hypotheses in research
- Designing data collection for biological studies
- Manipulating data with R (dplyr, tidyr, magrittr)
- Visualising data with R (ggplot2)
- Regression models, randomisation tests and “classical” tests
- Model selection
- Presenting results of statistical analyses
Beckerman, Childs & Petchey (2017) Getting Started With R. 2nd Edition. Oxford University Press.
Other literature uploaded to, or linked to, on Blackboard.
See itslearning for syllabus lists and additional literature references.
Exam element a)
The portfolio exam consists of multiple choice tests at the end of the semester (weighs 30% of the total assessment) and a take-home exam / report (weighs 70% of the total assessment).
Reexam in the same exam period or immediately thereafter.
The mode of exam at the re-examination may differ from the mode of exam at the ordinary exam.
Indicative number of lessons
At the faculty of science, teaching is organized after the three-phase model ie. intro, training and study phase.
Intro phase: 22 hours
Skills training phase: 22 hours, hereof exercise class: 22 hours
Activities during the study phase:
- Computer-based exercises
- Research oriented learning (guided exploration of data)
- Reading relevant literature, or other written material (e.g. blog posts)
|Owen Jonesfirstname.lastname@example.org||Biologisk Institut, Biodemography Unit, Interdisciplinary Centre on Population Dynamics – Four Faculties Affiliates|
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