Students have knowledge of the basics of the R language. They can use the R language and RStudio as an advanced calculator, know basic commands, work with basic data types, can use operations with vectors, arrays, and data frames. Students also have knowledge of extensions of the R language. They can create statistical analysis of data, its graphical display and an interactive web application in the R language.
Prerequisites for registration:
none
Course contents:
Recommended or required reading:
Recommended:
TEETOR, P. R Cookbook, O'Reilly Media, 2011, 438 s. ISBN 978-0-596-80915-7.
WICKHAM, H. – GROLEMUND, G. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, O'Reilly Media, 2017, 518 s. ISBN 978-1491910399.
Planned learning activities and teaching methods:
Contact teaching:
exercises – 26 h
Contactless teaching:
preparation for exercises – 24 h
Assesment methods and criteria:
The final grade consists of an evaluation of two assignments or tests, 50 points each. The final grade is given by the Study rules of the STU. To obtain credits for the subject, the student has to reach at least 56% of the maximum number of points.