Course content

- Research process and planning- Analyses of variance and cross-table analysis- Linear multiple regression analysis- Cluster analysis- Factor analysis- Logistic regression- Conjoint analysis- Structural equation models using PLS- Communicating research results

Learning outcome

Learning Outcome - Knowledge- Master the terminology of the subject- Acquire comprehensive knowledge of basic statistical methods- Acquire good knowledge of advanced statistical methods- Have good knowledge of presentation and reporting techniques Learning Outcome - Skills- Be able to carry through an independent, small-scale research project in accordance with prevailing scientific ethical norms- Be able to select and master relevant statistical tools according to research questions and the formulated hypotheses.- Be able to communicate research problems, analyses, and conclusions, as well as acquire a basis for communicating more comprehensive scientific workLearning Outcome - General Competence- Be able to view the topics of this course in a larger business/economic professional perspective- Be able to view the topics of this course in a larger social perspective- Be able acquire updated knowledge within the above mentioned areas of knowledge and skills

Learning methods and activities

Lectures, discussions in groups and in plenary, laboratory exercises (statistical analyses).Mandatory Assignmenys: Two approved individual statistical exercises must be completed and passed. If the candidate does not pass all exercises, new exercises must be completed and passed before the the next ordinary exam (the following year year).

Compulsory assignments

• Individual statistical exercises

Further on evaluation

Both exams must be passed in order to be awarded a final mark.

Specific conditions

Required previous knowledge

As for the study programme.

Course materials

To be announced at the start of the term.