107.106 Statistical Computing
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2020S, VO, 2.0h, 3.0EC
This course is evaluated following the new mode. Learn more

Course evaluation

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VO Lecture

Learning outcomes

After successful completion of the course, students are able to

  • outline the scheme and the structure of programing in the software environment R,
  • efficiently work with bigger and more complex data sets in R, including visualization.

Subject of course

This lecture gives an introduction into statistical data analysis using modern computer methods with an emphasis on applied practical work. The topics include the statistical language R application of statistical models and tests using R graphical data visualization regression writing code in R development, packaging and documentation of software.

Teaching methods

Exercises based on real data

Mode of examination

Immanent

Additional information

The content will be practiced with excercices from the learning platform www.datacamp.com. For the duration of this course, every participant will receive unlimited access to learning material from this platform.

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue14:00 - 16:0010.03.2020Hörsaal 6 Vorlesung Posekany

Examination modalities

Active attendance and work on exercises in the active attendance period.

Working through online modules pn DataCamp

Course registration

Begin End Deregistration end
25.02.2020 12:00 06.03.2020 12:00 06.03.2020 12:00

Curricula

Study CodeSemesterPrecon.Info
033 203 Statistics and Mathematics in Economics
033 531 Data Engineering & Statistics 3. Semester
033 533 Medical Informatics STEOP
Course requires the completion of the introductory and orientation phase
033 534 Software & Information Engineering STEOP
Course requires the completion of the introductory and orientation phase
066 421 Geodesy and Geoinformation 2. Semester
066 645 Data Science 2. Semester
860 GW Optional Courses - Technical Mathematics

Literature

All related documents will be available at the online lecture.

Miscellaneous

Language

English