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Statistical methods for the Biosciences II - SmB II
Provider: Faculty of Science

Activity no.: 5543-19-07-21 
Enrollment deadline: 30/01/2019
PlaceDepartment of Mathematical Sciences
Universitetsparken 5, 2100 København Ø
Date and time04.02.2019, at: 08:00 - 07.04.2019, at: 16:00
Regular seats20
Activity Prices:
  - Deltager/Participant from SCIENCE0.00 kr.
  - Deltager/Participant Others3,600.00 kr.
ECTS credits3.00
Contact personNina Weisse    E-mail address: weisse@math.ku.dk
Enrolment Handling/Course OrganiserBo Markussen    E-mail address: bomar@math.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 3
Scheme groupA (Tues 8-12 + Thurs 8-17)
Scheme group notePlenum teaching will only be done on Thursdays.
Exam formSkriftlig aflevering/Written examination
Exam formOral examination
Exam detailsAn evaluation in form of passed/failed is based on the written report and the oral presentation.
Grading scalePassed / Not passed
Exam re-examinationIf the student didn't pass based on the written report and the oral defense, then the student has the possibility of resubmitting the report based on the feedback from the examination. The resubmitted report then has to be sufficiently elaborate by itself in order to pass the reevaluation.
Course workload
Course workload categoryHours
Course Preparation7.00
Lectures8.00
Theory exercises4.00
Project work56.00
Exam5.00

Sum80.00


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. In addition up to 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 functional data, discriminant analysis as a supplement to logistic regression, multivariate methods like PCA, survival analysis.

No later than 2 weeks prior to the course, the participants should submit a synopsis with a description of their dataset and the desired outcome. This will allows us to consider whether to plan plenum lectures on some specific analysis method.

Formel requirements
The number of participants is limited at 20, and priority will be given to students who follow SmB I in the same year.

Learning outcome
After course completion the students are expected to be able to:

Knowledge:
- Describe the elements of frequentist statistics including estimation, confidence intervals, hypothesis tests, model validation.
- Describe the statistical models most commonly used in their own field of research.

Skills:
- Use a statistical software package like R or SAS to perform statistical analysis of their own datasets.

Competences:
- Formulate scientific questions from their PhD project in terms of statistical hypothesis.
- Interpret the results of a statistical analysis in relation to their PhD project.

Literature
R and RStudio is free and open source, and may be downloaded from the internet. If required, other resources and literature will be provided.

Teaching and learning methods
The possible course days can be traditional lectures and/or exercises, but will likely to a large degree be a workshop setting where the students can work with their projects with the lecturer available for help, feedback, and suggestions. Peer-feedback among the course participants is also a possibility. 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 projects may be done using statistical software of the participants own choice. The lecturer has experience with the software packages R, SAS and JMP.

Remarks
Course homepage: http://www.math.ku.dk/~pdq668/SmB/SmB_II.html

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