Modul

 The module will be completed by an oral exam (ca. 20 min).

At the end of the course, students will 

• be familiar with the most important regression models and their properties, 
• be able to evaluate and interpret the results obtained using these models,
• be able to use the models to analyze more complex data sets.

None

This course covers basic models of statistics that allow us to capture relationships between variables. Topics include

• Linear regression models:
  Model diagnostics
  Multicollinearity
  Variable selection
  Generalized least squares
• Nonlinear regression models:
  Parameter estimation
  Asymptotic normality of maximum likelihood estimators
• Regression models for count data
• Generalized linear models:
  Parameter estimation
  Model diagnostics
  Overdispersion and quasi-likelihood

The contents of the course "Statistics" are strongly recommended.

Total workload: 120 hours

Attendance: 45 hours

• lectures, problem classes, and examination 

Self-studies: 75 hours

• follow-up and deepening of the course content,
• work on problem sheets,
• literature study and internet research relating to the course content,
• preparation for the module examination