| Quantitative Methods - Statistics and Operations Research (VL) |
| Untertitel: |
| This course is part of the module: Quantitative Methods - Statistics and Operations Research |
| DozentIn: |
| Prof. Dr. Kathrin Fischer, Kai Uwe Hoth, Tizian Schug, Tobias Klein, M. Sc, Lorenz Kolley, Heike Scheel |
| Semester: |
| WiSe 23/24 |
| Ort: |
| (D-2.022): Mo. 11:30 - 14:00 (13x),
(D-1.021): Di. 11:30 - 13:00 (7x),
(A-0.13): Di. 11:30 - 13:00 (1x),
(H-0.08): Mi. 11:30 - 13:00 (13x),
(K-1520): Do. 09:45 - 11:15 (13x),
(D-0.011): Fr. 09:45 - 11:15 (13x) |
| Zeiten: |
Mo. 11:30 - 14:00 (wöchentlich),
Di. 11:30 - 13:00 (wöchentlich) - Tutor session,
Mi. 11:30 - 13:00 (wöchentlich),
Do. 09:45 - 11:15 (wöchentlich),
Fr. 09:45 - 11:15 (wöchentlich)
Erster Termin:Montag, 23.10.2023 11:30 - 14:00, Ort: (D-2.022) |
| Leistungsnachweis: |
| 611 - Quantitative Methods - Statistics and Operations Research<ul><li>611 - Quantitative Methods - Statistics and Operations Research: Klausur schriftlich</li></ul><br>613 - Quantitative Methods - Statistics and Operations Research<ul><li>611 - Quantitative Methods - Statistics and Operations Research: Klausur schriftlich</li><li>811 - Quantitative Methods - Statistics and Operations Research - Midterm: Midterm</li><li>813 - Quantitative Methods - Statistics and Operations Research - Exercises: Excercises</li></ul> |
| Leistungspunkte: |
| 4 |
| Beschreibung: |
Statistics - Descriptive Statistics: Graphical representations, calculation of relevant measures of central tendency etc., also by using a computer; application of methods for large data sets, analysis and comparison of results, critical discussion and evaluation of methods and their use in scientific projects and business practice
- Probability theory: important laws, dependent probabilities, Bayes Rule; application to practical problems
- Use and application of probability distributions , as e.g. Binomial and Normal distribution to Management and Engineering problems
- Methods of inferential statistics: confidence intervals: theoretical background and applications; hypothesis testing: theoretical background and application to business problems; regression analysis: theoretical background and application in research practice.
Operations Research
- Linear Programming: Modelling business decision situations, solving problems by Simplex method and by using software, theoretical background of Simplex procedure, Dual Simplex procedure and blocked variables, special cases (degeneracy etc.); sensitivity analysis and interpretation
- Transportation planning: Modellung transportation and transshipment problems in global networks; Solving transportation problems using software
- Network Optimization problems: modelling production and transportation networks, solving planning problems in networks, Network Planning as a research topic
- Integer Programming: Models using integer variables, e.g. in location decisions, branch and bound procedure
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