The general objectives are to provide students with fundamental tools of Linear Algebra, in view of its future use as an auxiliary instrument in different disciplines of Information Management.
José António da Silva Carvalho
Weekly - Available soon
Total - Available soon
Portuguese. If there are Erasmus students, classes will be taught in English
The student must have successfully completed an high-school course in calculus, with the usual requirements considered within the European Union.
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.
The teaching method relies on weekly theoretical lectures and practical classes, supported by an attending schedule. Practical examples are provided in the theoretical lectures. Exercises are solved under teacher supervision in the practical classes.
The continuous evaluation method consists in two tests. The student is approved if the average of the two grades is upper or equal to 9.5.
Note: The student may optionally improve the grade of the first test at the date of the second test.
The non-approved student in continuous evaluation must attend the final exam, being aproved if the grade is upper or equal to 9.5.
1. Vector Spaces.
1.1. Dependence and linear combination of vectors.
1.2. Vector Subspaces.
1.3. Base and dimension of a vector space.
2.1. Definition and classification of matrices.
2.2. Operations between matrices.
2.3. Characteristic of a matrix; Inverse of a matrix.
3.1. Calculation and proprieties of determinants.
3.2. Minors and algebraic complements.
3.3. Adjoint matrix.
4. Systems of linear equations.
4.1. Definition, matrix representation and resolution of a system linear equation.
4.2. Calculation of the adjoint matrix using the condensation method.
5. Eigenvalues and Eigenvectors.
5.2. Characteristic polynomial and characteristic equation.
5.3. Main results.
6. Introduction to quadratic forms.
Programs where the course is taught: