040100 VO Mathematics 2 (2020S)
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Um Zugriff zu den Unterlagen in Moodle zu erhalten, melden Sie sich bitte via U:Space für die VO an.Es findet ein freiwilliges Tutorium (Georgi Atanasov) statt: MI wtl von 04.03.2020 bis 24.06.2020 18.30-20.00 Ort: Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
Details
Language: German
Examination dates
-
Thursday
02.07.2020
09:45 - 13:00
Auditorium Maximum Tiefparterre Hauptgebäude Stiege 10
Studierendenzone Tiefparterre Hauptgebäude Stiege 12 Hof 8 -
Tuesday
22.09.2020
09:45 - 13:00
Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock - Wednesday 27.01.2021 09:45 - 13:00 Digital
- Monday 22.02.2021 09:45 - 13:00 Digital
Lecturers
Classes (iCal) - next class is marked with N
- Monday 02.03. 13:15 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Monday 09.03. 13:15 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Monday 30.03. 13:15 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Monday 20.04. 13:15 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Monday 27.04. 13:15 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Monday 11.05. 13:15 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Monday 18.05. 13:15 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Monday 25.05. 13:15 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Monday 08.06. 13:15 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Monday 15.06. 13:15 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Information
Aims, contents and method of the course
Assessment and permitted materials
written exam about the topics discussed in the lecturePermitted materials for the exam:
No documents (neither notes nor formularies) are allowed. A simple, non-programmable calculator, without matrix operations, which does not plot graphs, solve equations, and does not compute derivatives or integrals is allowed.Please note that mobile phones, smart watches etc. must be out of reach during the exam.For more information please visit
http://homepage.univie.ac.at/andrea.gaunersdorfer/teaching/mathe2.html
No documents (neither notes nor formularies) are allowed. A simple, non-programmable calculator, without matrix operations, which does not plot graphs, solve equations, and does not compute derivatives or integrals is allowed.Please note that mobile phones, smart watches etc. must be out of reach during the exam.For more information please visit
http://homepage.univie.ac.at/andrea.gaunersdorfer/teaching/mathe2.html
Minimum requirements and assessment criteria
see German webpage
Examination topics
see German webpage
Reading list
A. Gaunersdorfer, Mathematik 2 - Optimierung in den Wirtschaftswissenschaften, Skriptum, Februar 2020.
Association in the course directory
Last modified: Fr 12.05.2023 00:12
as well as their application in business and economics.Contents:
1. Introduction: optimization problems in business and economics
2. Differential calculus for functions of several variables
(real valued functions of several variables, some basics terms of topoloy, partial derivatives, derivative, tangent plane, gradient, vector functions, Jacobian, chain rule, directional derivatives, total differential, geometric interpretation of the gradient, second derivatives, Hessian, second directional derivative)
3. Convexity
(convex sets, convex and concave functions in several variables)
4. Optimization of scalar valued functions
(stationary points, second order conditions, comparative statics, envelope theorem)
Inverse and implicit functions
5. Optimization with equality constraints: Lagrange's method
(first and second order conditions, interpretation of the Lagrange multipliers, conditions for global optima, quasiconcavity and quasiconvexity, economic applications)
6. Nonlinear programming
(convex programs, Kuhn-Tucker conditions, constraint qualifications, saddle point condition)
7. Linear programming
(model formulation, assumptions underlying a linear planning model, graphic solution of two-variable programs, basic solutions, characterization of the sets of feasible and optimal solutions, simplex method, formal structure of the simplex tabelaus, alternative optimal solutions, duality, complementary slackness, economic interpretation of the dual programme, interpretation of a computer solution)