ST811: Multivariate Statistical Analysis (5 ECTS)

STADS: 25002401

Level
Master's level course approved as PhD course

Teaching period
The course is offered in the spring semester.

Teacher responsible
Email: hcpetersen@sdu.dk

Timetable
Show entire timetable
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Comment:
Ubegrænset deltagerantal. Fælles undervisning med ST514

Prerequisites:
A Bachelor’s degree in Science or an equivalent study programme.

Academic preconditions:
Students taking the course are expected to:

• have skills in statistics corresponding to ST520 Applied statistics or ST521 Mathematical statistics, and calculus corresponding to one of the calculus courses on the first year on the study programmes at the Faculty of Science, SDU
• be able to use the statistical software R

Course introduction
The aim of the course is to enable the student to work systematically with data sets with several variables, which is important in regard to performing statistical analyses in a broad range of research areas, such as biology and epidemiology

The course builds on the knowledge acquired in the courses such as ST520 Applied statistics or ST521 Mathematical statistics, and the calculus course in the respective study programme, and gives an academic basis for studying topics such as biometry, that are part of the degree, as well as master projects where multivariate methods are employed.

In relation to the competence profile of the degree it is the explicit focus of the course to:

• Give the competence to evaluate and choose between different methods for the analysis of multivariate data sets 
• Give skills to perform analyses of multivariate data sets using the statistical software R
• Give knowledge and understanding of  the fundamental ideas and methods for analyzing measurements on several variables

Expected learning outcome
The learning objective of the course is that the student demonstrates the ability to:

• reproduce key theoretical results concerning elementary operations on random variables and random vectors, and to apply these to simple theoretical assignments  
• work with the concepts and models, both in scalar and matrix/vector representation  
• understand and identify problems that can be solved using multivariate techniques  
• perform a practical data analysis with the techniques from the course  
• perform programming relevant to the content of the course in the statistical package used in the course  
• identify and interpret relevant information in the output of the statistical package used in the course  
• summarize the results of an analysis in a statistical report

Subject overview


Literature

Meddeles ved kursets start

Website
This course uses e-learn (blackboard).

Prerequisites for participating in the exam
None

Assessment and marking:

1. Oral exam based on written project reports, handed in during the course Internal marking, pass/fail. (5 ECTS). (25002402).

Expected working hours
The teaching method is based on three phase model.
Intro phase: 24 hours
Skills training phase: 24 hours

Educational activities

• Work on problems not covered in the training phase
• Discussion of the concepts and terms of the topic

Educational form
In the intro phase a modified version of the classical lecture is employed, where the terms and concepts of the topic are presented, from theory as well as from examples based on actual data. In these hours there is room for questions and discussions. In the training phase the students work with data-based problems and discussion topics, related to the content of the previous lectures in the intro phase. In these hours there is a possibility of working specifically with selected difficult concepts. In the study phase the students work independently with problems and the understanding of the terms and concepts of the topic. Questions from the study phase can afterwards be presented in either the intro phase hours aor the study phase hours.

Language
This course is taught in Danish or English, depending on the lecturer. However, if international students participate, the teaching language will always be English.

Remarks
The course is co-read with: ST514 Multivariate statistical analysis
The course cannot be chosen by students who have passed ST514

Course enrollment
See deadline of enrolment.

Tuition fees for single courses
See fees for single courses.