Data Analysis in Transport Planning

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The course teaches the application of explorative, descriptive and inductive statistical methods. The cases of application considered originate from the field of transport planning. The course is divided into a lecture and an exercise. The lecture covers the theoretical background of handling quantitative data and gives an overview of relevant sources for mobility data. In the exercise, the students carry out statistical evaluations themselves on the basis of the traffic survey Mobility in Germany. In doing so, they learn how to use the programming language R from reading in the data to creating complex models. At the end of the semester there is an oral examination.

 

Teaching Aims

After completing the course, students should be able to apply common statistical methods independently. Furthermore, they should be able to understand and classify statistical evaluations and their key figures in scientific publications.

The course content includes the following topics:

  • Presentation of data
  • Design of surveys
  • Sample sizes
  • Weighting and extrapolation
  • Probability distributions, central limit theorem
  • Test distributions, confidence intervals, significance
  • Statistical tests (t-test, chi-square test, ANOVA)
  • Iterative proportional fitting
  • Regression methods (linear, non-linear, simple, multiple)
  • Discrete choice modelling