Menü
Positionsanzeige
Inhalt

[ 551DATADSSP19 ] PR Data Analysis with Statistical Software
Versionsauswahl
(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
4 ECTS B2 - Bachelor's programme 2. year Statistics Markus Hainy 2 hpw Johannes Kepler University Linz
Detailed information
Pre-requisites (*)keine
Original study plan Bachelor's programme Statistics and Data Science 2025W
Learning Outcomes
Competences
Students can perform sophisticated data analyses using the programming language R, insert the results of the analyses into dynamically generated reports and present them as interactive web pages.
Skills Knowledge
  • Creating complex graphics in R to display and analyze multivariate data (k4, k6)
  • Applying efficient methods for extracting, transforming, combining, summarizing and analyzing data in R (k3, k4)
  • Creating simple documents using LaTeX (k6)
  • Creating documents in which text, R code and results are dynamically linked (k6)
  • Creating interactive web apps with R back end (k6)
  • Conducting linear regression analyses in R and evaluating the results (k3, k4, k5)
  • Packages for creating complex graphics
  • Packages and functions for efficient data manipulation
  • Basics of LaTeX
  • Principles of literate programming and packages for creating dynamical documents in R
  • Packages for creating interactive web apps with R back end
  • Fitting linear models in R
Criteria for evaluation Home work assignments and written project report
Methods Lecture by instructor; Discussion of the homework assignments by the students; Independent programming of statistical analysis methods
Language German
Study material Ligges, U. (2009) Programmieren mit R, Springer, Berlin / Heidelberg, 3. Auflage.

Wickham, H, Grolemund, G. (2016) R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O’Reilly.

Supplementary reading will be announced each semester.

Changing subject? No
Corresponding lecture (*)4MSSS2PR: PR Statistische Simulationen II (4 ECTS) und 551STSOSIMU14: Statistische Simulationen (4 ECTS)
On-site course
Maximum number of participants 20
Assignment procedure Assignment according to priority