Subject Datasheet

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Budapest University of Technology and Economics
Faculty of Transportation Engineering and Vehicle Engineering
1. Subject name Statistics in Transport (PhD)
2. Subject name in Hungarian Közlekedésstatisztika (PhD)
3. Code BMEKOKKD013 4. Evaluation type exam grade 5. Credits 3
6. Weekly contact hours 2 (0) Lecture 0 (0) Practice 0 (0) Lab
7. Curriculum
PhD Programme
8. Role
Specific course
9. Working hours for fulfilling the requirements of the subject 102
Contact hours 70 Preparation for seminars 5 Homework 6
Reading written materials 8 Midterm preparation 5 Exam preparation 8
10. Department Department of Transport Technology and Economics
11. Responsible lecturer Dr. Török Ádám
12. Lecturers Dr. Sipos Tibor, Dr. Török Ádám
13. Prerequisites  
14. Description of lectures
Transport is an integral part of advanced societies. He is responsible for passenger transport, including access to services and goods and leisure mobility. He is also responsible for transporting consumer goods. Regional, national and global economies rely on efficient and safe transport. The aim of the course is the statistical analysis of data generated during transport processes. Descriptive statistics. Class interval estimation, hypothesis test, sample comparison. Linear regression. Time series analysis. Principal Component Analysis. Spatial Statistics.
15. Description of practices
16. Description of labortory practices
17. Learning outcomes
A. Knowledge   B. Skills
  • The student repeats the material of the descriptive statistics and the hypothesis test. 
  • It learns the evolution of predictions, and thus opens up its thinking to accommodate novel solutions. 
  • The student will be able to specialize the general statistical problems in time and space.
C. Attitudes   D. Autonomy and Responsibility  
18. Requirements, way to determine a grade (obtain a signature)
It is required to fulfill in time the individual student work.
19. Opportunity for repeat/retake and delayed completion
The attendance requirements cannot be delayed completed. The individual case study report can be delayed submitted in the delayed completion period.
20. Learning materials
Simon P Washington; Methew G Karlaftis; Fred L. Mannering: Statsictical and Econometric Methods for Transportation Data Analysis, Taylor a& Francis; 2011
Effective date 27 November 2019 This Subject Datasheet is valid for 2023/2024 semester I