Credit hours
In-class work per week |
Practice per week |
Credits |
Duration |
Total |
6 |
2 |
8 |
10 weeks |
120 hours |
Instructor
Adriano Júlio de Barros Vicente de Azevedo Filho
Mirian Rumenos Piedade Bacchi
Vitor Augusto Ozaki
Objective
The objective is to introduce mathematical knowledge within the context of quantitative and
computational methods, focusing on their applications in theories and methodologies used in studies in
economics. Specifically, the course include training the student in understanding, modeling and solving
problems involving mathematics and mathematical models in order to improve their ability to analyze,
model and solve problems within the field of economics.
Content
1. Mathematical models: fundamental ideas and applications. 2. Review of fundamentals and
applications: set theory, functions, polynomials, equations, series, limits, derivatives and integrals. 3.
Equations and systems of linear and non-linear equations: theory, solution methods, computational
implementation and applications. 4. Linear and matrix algebra: fundamentals, computational
implementation and applications. 5. Differential and integral calculus in the multivariate context:
fundamentals and applications. 6. Linear and non-linear optimization: introduction to theory, algebraic
and computational solutions, and applications. 7. Differential equations and difference equations:
introduction and applications. 8. Optimal control theory and dynamic programming: introduction and
applications.
Bibliography
Amemiya, T. 1994. Introduction to Statistics and Econometrics. Harvard University Press, Cambridge.
Azevedo-Filho, A. 2010. Principios de Inferência Dedutiva e Indutiva: Noções de Lógica e Métodos de
Prova. CreateSpace (EUA). Azevedo-Filho, A. 2011. Introdução à Estatística Matemática Aplicada - Vol I:
Fundamentos. CreateSpace (EUA). Azevedo-Filho, A. 2011. Introdução à Estatistica Matemática Aplicada
- Vol II: Distribuições Paramétricas e Simulação. CreateSpace (EUA). Azevedo-Filho, A. 2007.
Probabilidades III - Distribuições Paramétricas Discretas e Contínuas. USP/DEAS - Série Didática, No. D-
133, 150p, Berger, J. 1993. Statistical Decision Theory and Decision Analysis, 2nd Edition, Springer,
617p, Berger, J. 2003. Could Fisher, Jeffreys and Neyman have agreed on testing? Statistical Science,
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Wesley, 702p. DeGroot, M. 1986. Probability and Statistics. Addison-Wesley. Drake, A. 1967.
Fundamentals of Applied Probabilistic Analysis. McGraw-Hill, New York. Greene, W. H. 2007.
Econometric Analysis. 6th Edition, Prentice Hall, Englewood Cliffs. Hoffmann, R. 2006. Estatística para
Economistas. 4ª. Edição, Editora Thomson Learning, São Paulo. Hoffmann, R. e Vieira, S. 1977. Análise
de Regressão: uma Introdução à Econometria. Hucitec-Edusp Hubbard, R. e Amstrong, J. 2006. Why we
don't really know what statistical significance means: Implications for educators. Journal of Marketing
Education, Volume 28, no. 2, 2006, Pages 114-120. Intriligator, Bodkin e Hsiao 1996. Econometric
Models, Techniques and Applications. 2nd Edition, Prentice-Hall. Mood, A., Graybill, F. A and Boes, D.
1989. Introduction to the Theory of Statistics. McGraw-Hill, New York. O'Haggan, A. e Luce, B. 2003. A
Primer on Bayesian Statistics. Centre for Bayesian Statistics in Health Economics, MEDTAP International,
2003. Spanos 1999. Statistical Foundations for Econometric Modelling with Observational Data.
Cambridge University Press.