Faculty of Science

Statistical methods for the Biosciences II - SmB II (generic course) - LPhD015
Provider: Faculty of Science

Activity no.: 5543-22-07-21
	Enrollment deadline: 02/02/2022

Place

Department of Mathematical Sciences

Date and time

07.02.2022, at: 08:00 - 22.04.2022, at: 16:00

Regular seats

Activity Prices:

- Deltager/Participant from SCIENCE

0.00 kr.

- Deltager/Participant Others

3,600.00 kr.

ECTS credits

3.00

Contact person

Nina Weisse E-mail address: weisse@math.ku.dk

Enrolment Handling/Course Organiser

Bo Markussen E-mail address: bomar@math.ku.dk

Written language

English

Teaching language

English

Semester/Block

Block 3

Scheme group note

There will be no plenum teaching on this course.

Exam form

Skriftlig aflevering/Written examination

Exam form

Oral examination

Exam details

An evaluation in form of passed/failed is based on the written report and the oral presentation.

Grading scale

Passed / Not passed

Exam re-examination

If 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 category	Hours
Project work	75.00
Exam	5.00

Sum	80.00

Content

The course participants conduct a statistical analysis of their own dataset, report the results in a written project, and make an oral presentation of the project. The statistical analysis is done under the supervision of a statistician, and each course participant is entitled to two individual supervision meetings. Furthermore, short answers and aid on specific problems is also given via email. The used datasets should be provided by the course participants and usually comes from their PhD work. The project should be written in a paper like style, and may hence later be used as a paper draft. Similarly, the oral presentation should be given in a conference like style.

No later than 2 weeks prior to the course, the participants should submit a synopsis with a description of their dataset and the scientific questions to be investigated. If the dataset or the scientific investigation suggested in the synopsis is too ambitious an adequate subanalysis might be suggested by the statistical supervisor.

Formal 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 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

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 and SAS.

Remarks

Course homepage for the 2020 course:http://www.math.ku.dk/~pdq668/SmB/SmB_II.html

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