Linear Algebra
Objectives
In this curricular unit it is intended that students develop algebraic skills, namely algorithmic conception, computional efficiency and inference of abstract structures of real models. Closely connected to the efficient organization of large amounts of numerical data, Linear Algebra will be a fundamental knowledge to other curricular units of the academic studies in Information Management.
General characterization
Code
100001
Credits
4.0
Responsible teacher
José António da Silva Carvalho
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Prerequisites
There are no requirements
Bibliography
Lay, D., Linear Algebra and its applications, 3rd ed., Pearson Education, 2006.; Sydsæter, K, Hammond, P., Essential Mathematics for Economic Analysis, 2nd ed., Prentice Hall, 2006.; Giraldes, E., Fernandes, V. H. e Smith, M. P. M, Curso de Álgebra Linear e Geometria Analítica, Editora McGraw-Hill de Portugal, 1995. ; Cabral, I., Perdigão, C., Saiago, C., Álgebra Linear, Escolar Editora, 2008.; Monteiro, A., Pinto, G. e Marques, C., Álgebra Linear e Geometria Analítica (Problemas e Exercícios), McGraw-Hill, 1997.
Teaching method
Lectures and practical classes in order to solve exercises
Evaluation method
Continue evaluation:
2 tests during the semester (minimum grade: 9,5 points)Final classification: average of the two tests.
Exam Evaluation (only in 2nd season):
Final Exam (100%) (minimum grade: 9,5 points)
Subject matter
1. Vector Spaces
1.1. Dependence and linear combination of vectors.
1.2. Vector Subspaces.
1.3. Base and dimension of a vector space.
2. Matrices
2.1. Definition and classification of matrices.
2.2. Operations between matrices.
2.3. Caracteristic of a matrix; Inverse of a matrix.
3. Determinants
3.1. Calculation and proprieties of determinants.
3.2. Minors and algebric complements.
3.3. Adjoint matrix.
4. Sistems of linear equations
4.1.Definition, matrix representation and resolution of a sistem linear equation
4.2. Calculation of the adjoint matrix using the condensation method
5. Eigenvalues and Eigenvectors
5.1. Definition.
5.2. Caracteristic polynomial and Caracteristic equation.
5.3. Main Results.
6. Introduction to quadratic forms
Programs
Programs where the course is taught: