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| Responsible Department | LIFE Graduate School
1 %
Dept. Mathematical Sciences, UCPH SCIENCE
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| Course Dates | 2 course days in spring 2013: May 8, May 15. Project writing until June 5. Project presentations June 10-12. |
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| Course Abstract | This is a follow-up to SmB I. The principal course content is the project work where the students analyze their own datasets and write an article style report. The two course days are used to introduce statistical methods which are needed for the projects but not taught on SmB I. The participants must bring their own datasets and hand in a project synopsis no later than 2 weeks prior to the first course day. Prerequisites for participation is SmB I or a similar course on applied statistics. |
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| Course Home Page | http://www.math.ku.dk/~pdq668/SmB/SmB_II.html |
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| Course Registration | Please register at bomar@life.ku.dk. |
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| Deadline for Registration | April 12, 2013. |
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| Credits | 4 (ECTS) |
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| Level of Course | PhD course |
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| Organisation of Teaching | UCPH SCIENCE. |
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| Language of Instruction | English |
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| Restrictions | The number of participants is limited at 30, and priority will be given to students who follow SmB I (LPhD014) in the same year. |
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| Course Content |
| The principal course content is the project work where the students under supervision analyze their own datasets; suitable datasets should be of moderate size and moderately complicated from a statistical point of view. The two course days are used to introduce statistical methods which are needed for the projects but not taught on SmB I. Examples of such methods are: analysis of longitudinal data and of repeated measurements, discriminant analysis as a supplement to logistic regression, multivariate methods like PCA, survival analysis. In order to identify the topics to be taught on SmB II the participants must hand in a project synopsis no later than 2 weeks prior to the first course day. Details on this are given on the course home page. |
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| Teaching and learning Methods |
| The course days will be a mixture of lectures and exercises including use of computers, and participants must bring their own laptops with R and RStudio installed. During the project period the participants are entitled to two individual supervision meetings with the course lecturer. The projects must result in an article style report and presented before the entire class at the concluding examination seminar. The teaching will be based on the software package R, but the projects may be done using statistical software of the participants own choice. The lecturer has concrete experience with the software packages R, SAS and JMP. |
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| Learning Outcome |
| This course trains the students' ability to perform a statistical analysis of their own datasets, and to report a statistical analysis in the style of a scientific paper. |
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| Course Literature |
| 'A First Guide to Statistical Computations in R', by Torben Martinussen, Ib Michael Skovgaard, and Helle Sørensen, Biofolia 2012. |
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| Course Material |
| R and RStudio is free and open source, and may be downloaded from the internet. |
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| Course Coordinator |
| Bo Markussen, bomar@life.ku.dk, Department of Basic Sciences and Environment, Phone: 353-20778 |
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| Course Fee |
| Free for PhD students from UCPH SCIENCE. Please contact the course responsible at bomar@life.ku.dk if you are not from UCPH SCIENCE. |
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| Course Costs |
| None. |
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| Type of Evaluation |
| An evaluation in form of passed/failed is based on the written report and the oral presentation. |
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| Work Load |
| preparation | 10 | | lectures | 10 | | theoretical exercises | 5 | | project work | 65 | | examination | 10 |
| | 100 |
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