MM533: Mathematical and Numerical Analysis
Study Board of Science
Teaching language: Danish or English depending on the teacher, but English if international students are enrolled
EKA: N300033102
Assessment: Second examiner: External
Grading: 7-point grading scale
Offered in: Odense
Offered in: Spring
Level: Bachelor
STADS ID (UVA): N300033101
ECTS value: 10
Date of Approval: 08-11-2018
Duration: 1 semester
Version: Archive
Comment
Entry requirements
Academic preconditions
Students taking the course are expected to:
- Have knowledge of the contents of MM536
- Have knowledge of the contents of MM540 or MM505 or acquire this knowledge in parallel to the lecture
Course introduction
The aim of the course is to enable the student to solve problems
concerning the course topics by means of mathematical and numerical
analysis. Formulate the answers (including proofs) in a correct
mathematical language. Implement algorithms as computer programs and
compute numerical approximations to mathematical problems that don't
allow a closed form solution.
The course builds on the knowledge
acquired in the courses MM536: Calculus for mathematics and MM505:
Linear Algebra or MM540: Mathematical methods for economics and gives an
academic basis for further studies in applied mathematics and
mathematics that are part of the respective degree programs. More
precisely, this includes MM545, MM546, MM547, MM548, MM549.
concerning the course topics by means of mathematical and numerical
analysis. Formulate the answers (including proofs) in a correct
mathematical language. Implement algorithms as computer programs and
compute numerical approximations to mathematical problems that don't
allow a closed form solution.
The course builds on the knowledge
acquired in the courses MM536: Calculus for mathematics and MM505:
Linear Algebra or MM540: Mathematical methods for economics and gives an
academic basis for further studies in applied mathematics and
mathematics that are part of the respective degree programs. More
precisely, this includes MM545, MM546, MM547, MM548, MM549.
In relation to the competence profile of the degree it is the explicit focus of the course to:
- Give the competence to analyse the qualitative and quantitative characteristics of a mathematical model
- Give basic understanding on how to perform computer based calculations in science, technology and economy
- Give knowledge and understanding of basic algorithms
Expected learning outcome
The learning objective of the course is that the student demonstrates the ability to:
- understand the abstract concepts of topological and metric spaces
- understand and work with the notions of compactness, continuity and convergence in the settings of topological and metric spaces
- understand the quantitative aspects of convergence in metric spaces
- analyse and conduct basic numerical methods for
- root finding
- interpolation
- integration
Content
The following main topics are contained in the course:
- Euclidian-, metric-, and topological spaces.
- Continuity of functions.
- Convergence of sequences and series.
- Bisection and secant methods and their convergence.
- Compact sets, Heine-Borel theorem.
- Completeness of Euclidian spaces.
- Banach fixed point theorem, norms and contractions.
- Linear convergence of fixed point iteration.
- Quadratic convergence of Newton iteration.
- Uniform continuity and the Riemann integral.
- Interpolation.
- Adaptive Newton-Cotes quadrature.
- Gaussian quadrature.
Literature
Examination regulations
Exam element a)
Timing
June
Tests
Written exam
EKA
N300033102
Assessment
Second examiner: External
Grading
7-point grading scale
Identification
Student Identification Card
Language
Normally, the same as teaching language
Examination aids
To be announced during the course
ECTS value
10
Additional information
The examination form for re-examination may be different from the exam form at the regular exam.
Indicative number of lessons
Teaching Method
Teaching is centred on interaction and dialogue. In the intro phase, concepts, theories and models are introduced and put into perspective. In the training phase, students train their skills through exercises and dig deeper into the subject matter. In the study phase, students gain academic, personal and social experiences that consolidate and further develop their scientific proficiency. Focus is on immersion, understanding, and development of collaborative skills.
Educational activities
- Reading of suggested literature
- Preparation of exercises in study groups
- Contributing to online learning activities related to the course