| Ansvarligt institut | Institut for Grundvidenskab og Miljø | ||||||||||||||||||
| English Title | Applied Statistics | ||||||||||||||||||
| Tidligst mulig placering | Bachelor 2. år til Kandidat 2. år | ||||||||||||||||||
| Varighed | En blok | ||||||||||||||||||
| Pointværdi | 7.5 (ECTS) | ||||||||||||||||||
| Kursustype | Fælleskursus | ||||||||||||||||||
| Eksamen | Sluteksamen mundtlig eksamen Alle hjælpemidler tilladt Beskrivelse af eksamen: Each group writes a report in a journal paper format about their project and presents it orally in class. At the end of the course each student is examined individually. Vægtning: Oral exam in report and curriculum 100%. bestået/ikke bestået, intern censur | ||||||||||||||||||
| Forudsætninger for indstilling til eksamen | The student should make a presentation in class of an exercise. | ||||||||||||||||||
| Rammer for Undervisning | Lectures, (computer) exercises and supervised project work. Preferably the project is about the student's own data. Report writing in journal article style and oral presentations. | ||||||||||||||||||
| Blokplacering | Block 2 Ugestruktur: A | ||||||||||||||||||
| Undervisningssprog | Engelsk | ||||||||||||||||||
| Anbefalede forudsætninger | 210005 Statistisk dataanalyse 1 The student should have at least one statistics course. Moreover, the student should have experience with SAS or R. | ||||||||||||||||||
| Begrænset deltagerantal | 30. | ||||||||||||||||||
| Kursusindhold | |||||||||||||||||||
| Each student carries out a statistical project (in a group) related to an experiment or a numerical investigation preferably delivered by one of the students in the group. A report is written in journal style and presented orally. Besides, a small number of statistical themes are taught. Examples of such themes are multi-way ANOVA, random effects, analysis of repeated measures and cross-over trials, analysis of count data or ordinal data, analysis of data with detection limit, simulation methods, non-linear regression models, analysis of time series data, Markov models. There is also some discussion of statistical methods used in specific application areas such as bacterial counting, plant competition and human nutrition. The statistical themes as well as the application areas may vary somewhat from year to year and to some extent adapt to the interests of the students. | |||||||||||||||||||
| Undervisningsform | |||||||||||||||||||
| During the first half of the course lectures and practical (computer) exercises will run parallel with the initial part of the project work, while the second half will concentrate on the projects. In the last week the students will present their projects orally and give critique to one of the other projects. | |||||||||||||||||||
| Målbeskrivelse | |||||||||||||||||||
| The course aims at giving the student experience of carrying out statistical analyses. The topics (methods) taught may vary from year to year. After completing the course the student should be able to: Knowledge: - recognize certain data types, identify and specify appropriate statistical models, and argue for the appropriateness - explain the prerequisities, prospects and limitations of the methods Skills: - formulate relevant problems and choose an appropriate statistical model addressing these problems - carry out the actual analysis (computations). This includes model fitting, model validation and hypothesis testing. - extract relevant estimates, draw conclusions and communicate the results from the analysis - use a statistical programming language such as R or SAS to carry out the analyses Competences: - independently formulate biological questions - motivated by data of similar types as those presented in the course - and answer them by the use of statistical methods. | |||||||||||||||||||
| Litteraturhenvisninger | |||||||||||||||||||
| Anders Tolver Jensen and Helle Sørensen: "Lecture notes for Applied Statistics", 2007. Possibly, supplementary material as handouts. | |||||||||||||||||||
| Kursusansvarlig | |||||||||||||||||||
| Christian Bressen Pipper, pipper@life.ku.dk, Institut for Grundvidenskab og Miljø/Statistics, Tlf: 353-32344 | |||||||||||||||||||
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