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Statistical Applications

Learning objectives

• ability to apply descriptive and advanced inferential statistical methods (also multivariate methods) in case studies
• ability to use a statistical software package for data analysis
• ability to recognize and to justify which method is to apply in the situations presented in the case studies
• ability to autonomously perform small adaptations appropriate for the data situation of the case studies
• ability to present the analysis results in oral presentations as well as written project reports
• ability to perform statistical projects in self-organized teams

Contents

• various case studies
• development of appropriate data analysis strategies
• performing the analyses by means of statistical software
• presenting results in written and oral form

Prerequisites

There are no formal prerequisites for participation in the course. However, knowledge of statistics and mathematics at bachelor level is desirable.

Lecture and exercise documents

Project descriptions, data sets and a template for the preparation of project reports are available for download in Stud.IP in the respective semester. Examinations with sample solutions from previous semesters can be found at the end of this page.

Scope and evaluation

• 3 WCH (instructed practical work on the PC as well as oral presentations)
• written exam
• 5 credit points

Dates

Dates are announced via Stud.IP. The course takes places every second winter semester.

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