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Angewandte Statistik für Verkehrssysteme

BGU70009Areas of Specialization6 ECTSEnglishwinter semesterLehrstuhl für Vernetzte Verkehrssysteme (Prof. Antoniou)
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You learn probabilistic models and statistical methods to model and analyze questions in transportation systems. In the end you can describe traffic datasets, estimate parameters, test hypotheses, and assess and apply the results of studies in the field of transportation.

What you will be able to do

  • Understand mathematical foundations of probability models
  • Apply probabilistic and inference procedures to traffic problems
  • Represent and summarize traffic data meaningfully
  • Estimate parameters and construct confidence intervals
  • Conduct hypothesis tests
  • Use regression and analysis of variance for traffic analyses
  • Apply Bayesian methods to traffic questions
  • Assess results of scientific studies in the field of transportation

What the module consists of

  • VorlesungConveying concepts of probabilistic modeling and statistical inference with examples from urban traffic planning
  • ÜbungenComputational and application tasks on each major topic; solutions are discussed afterwards

Teaching method

  • Vortrag mit Folien und TafelIntroduction and derivation of methods as well as illustration with examples
  • Diskussion und aktive TeilnahmePromotes understanding and application of the concepts
  • Praktische Beispiele zu den MethodenIllustrate use cases in transportation systems
  • Übungsaufgaben mit MusterlösungenPractise computations and method application

Dates

Lecture with exerciseApplied Statistics for Transportation Systems

  • Tue08:00–11:15N 1090 ZG, Hörsaal mit exp. Bühne (0101.Z1.090)
    14× · 13.10.–02.02.
    • 13.10.
    • 20.10.
    • 27.10.
    • 03.11.
    • 17.11.
    • 24.11.
    • 01.12.
    • 08.12.
    • 15.12.
    • 22.12.
    • 12.01.
    • 19.01.
    • 26.01.
    • 02.02.

From the current semester, not binding.

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Official page in TUMonline · Details are not binding.