Calculus II
Objectives
The course develops the fundamental tools of differential calculus in R, that enable the mathematical formulation and study of models in Economics, Business and Finance.
General characterization
Code
1302
Credits
7.5
Responsible teacher
Patrícia Xufre; Pedro Chaves
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese and English
Prerequisites
Mandatory Precedence:
- 1301. Calculus I
- 1303. Linear Algebra (highly recommended)
Bibliography
Main references:
• Pires, C., Cálculo para Economia e Gestão, Escolar Editora, 2011. (PT)
• Simon, C.P., Blume, L., Mathematics for Economists, W.W. Norton & Company, Inc, 1994. (EN)
• Xufre, P., Silva, P., Mendes, D., Análise em ???, 1ª edição, Escolar Editora, 2017.
Other references:
• Dias Agudo, F.R., Análise Real, Livraria Escolar Editora, 2ª edição, 1994.
Excepto tópicos 6.5 e 6.6
• Azenha, A., Jerónimo, M.A., Elementos de Cálculo Diferencial e Integral em ? e
???, McGraw-Hill, 1995.
Excepto tópicos 6.5 e 6.6
• Campos Ferreira, J., Introdução à Análise em , Publicação electrónica (https://math.tecnico.ulisboa.pt/textos/iarn.pdf), DM, IST, 2003.
Excepto tópicos 6.5 e 6.6
• Sydsæter, K. et al., Further Mathematics for Economic Analysis, Prentice Hall, 2005.
Teaching method
Theoretical classes; practical classes; resolution and proposal of problems and exercises; mini-tests, midterm test and final exam.
Evaluation method
The final grade in normal season is calculated as follows:
Final Score = 0.4 × Average of the 2 best TI + 0.6 × EF
- Three Intermediate Tests (IT) - during the semester students will perform 3 intermediate tests of which only the grade of the 2 best will be considered for the calculation of the final grade*
- Final Exam (EF)- minimum score of 8.5 out of 20 values
In The Appeal/Special Season the final grade may correspond exclusively to the exam grade if the student expresses this interest in writing on the day of the exam. By default, it will be calculated identically to that used for Normal Season.
Improvements:
Situation 1 - Obtained approval of the discipline in another semester and regardless of the time of examination in which he takes the final exam:
- If the student performs any of the intermediate Tests, his final grade will be obtained through the following formula:
Final Score = 0.4 × Average of the 2 best TI + 0.6 × EF
- Otherwise, your final grade will match the grade obtained in the final exam:
Final Score = EF
Situation 2 - Obtains approval of the discipline in the normal season of this semester:
* For a student who does not justifiably take at least two of the three intermediate tests, the weighting assigned to the final exam grade will be 100%. The exam that these students will take will obviously be different from that of the other students, as it will include subjects not yet evaluated.
The final grade may correspond exclusively to the exam grade if the student expresses this interest in writing on the day of the exam. Otherwise, it will be calculated according to the formula:
Final Score = 0.4 × Average of the 2 best TI + 0.6 × EF
Subject matter
a) The ??? Space
Notion of norm
Notion of distance
Short notions of topology
b) Functions from ?? ? ??? to ???
Examples in Economics/Management Domain
Particular case: ??: ?? ? ?2 ? ?; Grahical representation through level sets Limit of a function
Definition of limit
Limit of a function following a specific trajectory Some important properties
Continuity: main results
c) Derivation in ???
1st order partial derivatives (gradient vector and jacobian matrix) Higher order derivatives (hessean matrix)
Directional derivative Differentiability
Main properties of differentiable functions Symmetry of 2nd order derivatives
Derivative of the composite function Homogeneous function
Economic examples
Euler's theorem
Homogeneity of the partial derivatives
d) Taylor's Formula
Finite increment's theorem
Taylor's theorem and MacLaurin's formula
e) Inverse Function Theorem and Implicit Function Theorem
Functions invertibility in ???
Implicit functions; Economic examples
f) Optimization
Some basic concepts
Convex sets; Convex functions Unconstrained optimization
Optimization with equality constraints; Method of Lagrange multipliers Envelope's theorem
Optimization with inequality constraints; Karush-Kuhn-Tucker conditions