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Detailed information about the module

Module title:

Computational Statistics with R

Module title (english):

Computational Statistics with R

Module number:

82-021-IFM08-H-0507

Level:

Bachelor (UNI)

Course of study:

Type:

Modul

Organising faculty/Language Center:

Wirtschaftswissenschaftliche Fakultät

Instructors responsible:

Küsters, Ulrich

Examiners:

Ulrich Küsters und Eren Selman

Credit points (ECTS):

competencies/skills:

- Students acquire both baseline information and knowledge of selected programming techniques by using the statistical software environment R.
- The statistical analysis of data using R enables students to appropriately treat, prepare and graphically display empirical data.
- By addressing problems in the broad field of business and economics (i.e. statistical hypothesis testing, linear regression etc.), students gain decision making skills enabling them to conduct an analysis using R in a self-directed and aim-oriented manner.

course content/topics:

- Basics
- Objects and data structures in R und how to manage them
- Vectors
- Matrizes
- Arrays
- Lists
- Data Frames
- Logic and missing values
- Constructs for program control
- Conditional statements (if … else and the like)
- Loops
- Character strings
- Data input and output
- Working with Excel-Data
- Read and write R objects
- Details of the R language
- Functions
- S3-class objects
- Lazy Evaluation
- Graphics with R
- Statistics mit R
- Basic functions
- Random numbers
- Distributions and samples
- Linear models

formal requirements of admission:

recommended qualifications:

- Mathematics for Business
- Descriptive Statistics and Probability Theory
- Statistical Inference and Multivariate Statistics

Lehr- und Lernformen/Lehrveranstaltungstypen:

- Integrated Lecture and Exercise
- Programming projects

requirements for the attainment of ECTS points:

Final exam: assessment of theoretical and technical aspects of the programming language respectively of the statistical topics covered in class.

workload/distribution of ECTS points within the module:

28 h = Time of attendance
28 h = Preparation and post-processing
66 h = Homework assignment/ Programming project
28 h = Exam preparation
150 h = Total workload

calculation of module marks:

Final exam (100 %)

teaching/learning method:

compatibility with other courses of study:

Turnus des Angebots:

WS , SS

Beteiligte Fachgebiete:

Bemerkung:

*Limit due to capacity restriction in computer pools (special admission procedure).