Recommended prerequisite for participation in the module

The module builds on knowledge obtained by the modules in Mathematical Analysis, Probability Theory, Statistical Inference for Linear Models from the BSc programmes.

Content, progress and pedagogy of the module

Learning objectives

Knowledge

Students completing the module know about

• quantitative software development and computational statistics
• manufacturing planning and control including inventory management and material requirements planning
• optimization of discrete problems
• heuristics and meta-heuristics
• relational databases and their usage

Skills

Students completing the module are able to

• implement numerical algorithms
• formulate discrete optimization problems
• chose the appropriate solution strategy to a number of discrete optimization problems
• perform basic database operations

Competences

Students completing the module are able to

• understand the principles of inventory management
• understand differences in solutions strategies
• apply heuristics and meta-heuristic methods to solve complex problems
• understand relational data structures

understand the limitations, advantages and disadvantages of relational data structu

Type of instruction

Cf. §17.

Extent and expected workload

This is a 5 ECTS course module and the work load is expected to be 150 hours for the student.
 

Exam

Exams

Name of exam	Computational Statistics and Operations Research
Type of exam	Written or oral exam Individual oral or written exam, or individual ongoing during the course. In order to participate in the course evaluation, students must have actively participated in course progress by way of one or several independent oral and/or written contributions.
ECTS	5
Assessment	Passed/Not Passed
Type of grading	Internal examination
Criteria of assessment	The criteria of assessment are stated in the Examination Policies and Procedures