Elementary Calculus II
- ECTS credits10
- Teaching semesterSpring
- Course codeMAT102
- Number of semesters1
- LanguageNorwegian
- Resources
Main content
Teaching semester
Spring
Objectives and Content
Objectives:
The course contains theory of linear algebra for use in solving differential equations, data analysis and optimization.
Content:
In this course, systems of linear equations, determinants, matrix algebra, eigenvalues and vectors are studied. Furthermore, introduction to differential equations, systems of homogeneous linear differential equations, population dynamic models and functions of several variables are given. An introduction to the programs MATLAB and NumPy will be given, which will be used in exercises. Numerical solution of algebraic and differential equations will be a central theme.
Learning Outcomes
On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge
The student¿
¿ Knows basic definitions regarding matrixes and linear systems of equation.
¿ Knows the concept of the vector spaces and theyer dimension.
¿ Understands the use of digital tools in natural science.
¿ Understands population models.
Skills
The student¿
¿ Can use MATLAB or NumPy to analyze data.
¿ Can use MATLAB or NumPy to numerically solve systems of differential equations.
¿ Can apply the rules of matrix algebra and solve linear systems of equation.
¿ Can set up simple population models.
¿ Can use flow graphs to get a qualitative understanding of the solution curves for differential equations.
¿ Can find the partial derivative of functions of several variables and use this to determine extreme pounts
¿ Can, by hand, calculate determinants in specific cases.
¿ Can write and understand MATLAB / NumPy programs.
General competence
The student¿
¿ Has insight into the use of mathematics in natural science.
¿ Has experience with using a computer to solve mathematical problems.
¿ Understands how mathematical theory is useful for displaying models in natural science.
¿ Knows how mathematics can be used in data analysis
Recommended Previous Knowledge
Forms of Assessment
Written examination: 4 hours
Examination Support Material
Non- programmable calculator, according to model listed in faculty regulations
Grading Scale
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.
Exam information
For written exams, please note that the start time may change from 09:00 to 15:00 or vice versa until 14 days prior to the exam.
Type of assessment: Written examination
- Date
- 02.06.2023, 15:00
- Duration
- 4 hours
- Withdrawal deadline
- 19.05.2023
- Examination system
- Inspera
- Digital exam
- Location
- Solheimsgt. 18 (Administrasjonsbygget), SOL 2. etg.