| Responsible Department | Department of Basic Science and Environment |
| Earliest Possible Year | Post experience Master´s Programme |
| Duration | Outside schedule |
| Credits | 6 (ECTS) |
| Level of Course | Post experience masters programme |
| Examination | Continuous Assessment written examination Portfolio Examination All aids allowed Description of Examination: For passing the course and getting a diploma you are expected to submit practical assignments, typically with analysis of data, participate actively in discussions and time-synchronized group work, answer some multiple choice questionnaires, all together with sufficient degree of skill to document your learning. Thus, diplomas are not given for participation alone. pass/fail, internal examiner |
| Organisation of Teaching | The course is internet-based and is organized in 6 modules February-May 2011. Each module lasts 2 weeks. The expected work load per module is up to 25 hours. |
| Block Placement | Outside schedule Week Structure: Outside schedule Outside schedule Week Structure: Outside schedule Outside schedule Week Structure: Outside schedule Outside schedule Week Structure: Outside schedule |
| Language of Instruction | English |
| Optional Prerequisites | A previous introductory course in statistics and application of statistical procedures during your work with assessments such as p-values, confidence intervals, t-tests and standard errors. |
| Restrictions | 32 |
| Course Content | |
| The topics of the 6 course modules are: . Introduction to R and descriptive statistics . Populations, samples and statistical fundamentals; comparing groups . Curve fitting and regression . Factorial experiments . Analysis of count data and binary data . Models with random effects and repeated measures A quick basic review of statistical concepts is included in the first two modules, but the course then quickly progresses to a more advanced and realistic complexity. With the help of the statistical software R, you try the various methods during examples, exercises and discussions. Examples are mainly from bio-sciences. This angle of applications also affects the content of the course. | |
| Teaching and learning Methods | |
| The course is based on internet communication only including collaboration in groups with course mates and supervision by a teacher. Modules typically run from Monday one week till Tuesday the next, with feedback, non-mandatory follow-up discussions and time to "recover" the remaining part of second week. Over the six modules there is a considerable work load, but it is taken into consideration that you may be prevented from activities for some unspecified days, due to work or for other reasons. Stepping off for an entire week may be problematic. You need to have a PC with facilities to read common formats like pdf and PowerPoint, and to have a reasonable connection to the Internet. A webcam may be an advantage for interactive sessions, but this is not currently expected or demanded. | |
| Learning Outcome | |
| The goals of the course are to understand and train the application of tools for gaining knowledge from experimental and observational data. At the end of the course it is expected that the participant can do the following: Knowledge: Define, identify and describe statistical problems and tools relevant for analysing the data Skills: Apply the relevant statistical methods on the identified problem Competences: Collaborate scientifically and administratively with statisticians on relevant problems for disease control - Participate in the planning of statistical approaches to gain and analyse data - Take responsibility and participate in choosing among alternative design and analytic strategies from a statistical point of view. | |
| Course Coordinator | |
| Ib Skovgaard, ims@life.ku.dk, Department of Basic Sciences and Environment/Statistik, Phone: 353-32340 | |
| Course Fee | |
| 10000 DKK | |
| Study Board | |
| Study Committee MSN | |