Statistical methods - an overview

The course is built on lectures and computer exercises with assignments. The main topics are:

- Design of experiments.

- Analysis of variance.

- Regression.

- Generalized linear models.

- Non-parametric methods.

- Multivariate statistical methods.

The content of the final project in the course depends on what specific methods and type of data the participants have in their research project.

Syllabus and other information

PLS0067 Statistical methods - an overview, 4.5 Credits

Subjects

Mathematical Statistics

Education cycle

Postgraduate level

Grading scale

Pass / Failed

Prior knowledge

A basic course in statistics is required. The course is primarily for students at the PhD level who already have collected some data in their research project.

Objectives

The aim of the course is that the student becomes better at handling and analyzing quantitative data using different statistical methods. After the course the student is expected to be more confident about which methods are appropriate for hers/his research and how to apply these.

Content

The course is built on lectures and computer exercises with assignments. The main topics are: - Design of experiments. - Analysis of variance. - Regression. - Generalized linear models. - Non-parametric methods. - Multivariate statistical methods. The content of the final project in the course depends on what specific methods and type of data the participants have in their research project.

Additional information

Examination Approved assignments during the course and written paper and oral presentation related to the students’ research project.

The course is given during January-February in Alnarp. The total time for the course is approximatetly 120 h.

Responsible department

Department of Biosystems and Technology

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