| Responsible Department | Department of Basic Science and Environment | ||||||||||||
| Course Dates | February to April 2012 | ||||||||||||
| Course Abstract | The course will cover basic theory and applications of mixed models, ie. fixed and random effects models The course aims at giving the student a variety of flexible statistical analysis tools based on the statistical programming environment R . | ||||||||||||
| Course Home Page | http://www.matfys.kvl.dk/stat/phdcourses/mixed/ | ||||||||||||
| Course Registration | Register by email to Christian B. Pipper (pipper@life.ku.dk) | ||||||||||||
| Deadline for Registration | January 1st 2012 | ||||||||||||
| Credits | 6 (ECTS) | ||||||||||||
| Level of Course | PhD course | ||||||||||||
| Organisation of Teaching | First part: Seminar course with presentations by students. Second part: project work | ||||||||||||
| Language of Instruction | English | ||||||||||||
| Restrictions | Limited number of participants. | ||||||||||||
| Course Content | |||||||||||||
| Statistical programming with R. Analysis of correlated data structures by mixed linear models. Reporting of statistical methods and results. | |||||||||||||
| Teaching and learning Methods | |||||||||||||
| The teaching sessions of the course take place on 5 whole days and are followed by a one month supervised project period. The project period is completed by a final whole day session where the students in turn present and discuss their projects. Specific Teaching and Learning Activities; Summaries from previous day: Student teacher discussion of concepts from the previous day. The product is a white-board overview of important concepts Student presentation of exercises: Students present a computer exercise and report their findings. Followed by questions from other students and student teacher discussion. Student seminar sessions: Based on a subject specific teacher written essay the students in pairs of two lecture over a subject. Each essay contains a number of open questions that form the basis of a classroom discussion. Lectures: Power-point presentations of general theory and concepts accompanied by student teacher discussion. Computer exercises: Analysis of data-examples by means of the statistical programming language R as well as interpretation and reporting of results. Supervised by teacher. Self-reflection exercises: The students relate course contents to their own data and discuss their findings with other students and teacher. Project supervision: Each student is entitled to two 1 hour supervision sessions with the teacher during the project period. Before each session the student sends an email with concrete questions to deal with at the session. Project presentation: 15 min oral student presentation of project followed by 5-10 min discussion with teacher and other students. | |||||||||||||
| Learning Outcome | |||||||||||||
| The course is intended to give students the competencies to justify, generate, and report statistical statements and conclusions so that they can answer relevant research questions on their own data. | |||||||||||||
| Course Literature | |||||||||||||
| None | |||||||||||||
| Course Material | |||||||||||||
| Web-based lecture notes, summaries and exercises. | |||||||||||||
| Course Coordinator | |||||||||||||
| Christian Bressen Pipper, pipper@life.ku.dk, Department of Basic Sciences and Environment/Statistik, Phone: 353-32344 | |||||||||||||
| Other Lecturers | |||||||||||||
| Chrstian Ritz, Dept. of Natural Science and Environment. | |||||||||||||
| Course Costs | |||||||||||||
| Free of charge for Ph.D. students under the Open Market for Postgraduate Courses in Denmark and for Ph.D. students from NOVA- and BOVA-partners. Otherwise: DKR 13000 | |||||||||||||
| Type of Evaluation | |||||||||||||
| The student analyzes a data material from his/her own research (preferably), submits a report and gives a short oral presentation. | |||||||||||||
| Work Load | |||||||||||||
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