# Mathematics 2 (ME)

## Code

ME-MAT2

## Version

2.2

## Offered by

Mechanical Engineering

## ECTS

5### Prerequisites

Admission requirements

### Main purpose

### Knowledge

The student will acquire knowledge in the following:

- Matrix arithmetic
- Analyse linear systems of differential equations (ODEs)
- Probability, mean and variance
- Account for the binomial, Poisson and normal distributions
- Discuss data analysis in Matlab
- Describe the use of logical expressions
- Use branches and loops
- Solve ODEs numerically

### Skills

The student will acquire the following skills:

- Perform matrix arithmetic
- Calculate eigenvalues and -vectors for small matrices
- Solve linear systems of ODEs
- Calculate simple descriptive statistics
- Use Matlab to solve the above
- Solve simple numerical problems in Matlab

### Competences

The student will be able to:

- Formulate and solve linear engineering problems analytically and numerically
- Read and write simple scripts in Matlab
- Apply the acquired skills in more advanced courses

### Topics

### Teaching methods and study activities

The course lasts for 12 weeks with 4 lessons per week. The total work load for the student is 138 hours.

Classroom teaching combined with solving exercises.

The student is expected to prepare for lessons by reading the required literature and solving exercises.

### Resources

- S. Leon: Linear Algebra with Applications, Pearson, Latest edition
- Matlab documentation
- Matlab to be installed (VIA license) on the student's PC

### Evaluation

### Examination

Exam type:

Individual oral exam - 20 minutes - based on a question drawn by lottery.

No preparation.

The exam accounts for 100% of the final grade.

Tools allowed:

None

Re-exam:

As ordinary

### Grading criteria

Grading based on the Danish 7-point scale.

### Additional information

### Responsible

Karl Woldum Tordrup

### Valid from

8/1/2022 12:00:00 AM

### Course type

### Keywords

Matrices and vectors, Eigenvalues and -vectors, Linear differential, quations, Descriptive statistics, Probability, Probability distributions, Matlab