Stud.IP Uni Oldenburg
University of Oldenburg
07.12.2021 03:21:29
neu725 - Multivariate Statistics and Applications in R
 Module label Multivariate Statistics and Applications in R Module code neu725 Credit points 6.0 KP Workload 180 h (1,5 SWS Lecture (VO)Total workload 68h: 28h contact / 20h background reading / 20h exam preparation2,5 SWS Supervised exercise (UE):Total workload 113h: 28h contact / 20h background reading / 65h exercise solving) Institute directory Department of Neurosciences Applicability of the module Master's Programme Neuroscience (Master) > Skills Modules Responsible persons Otto-Sobotka, Fabian (Module responsibility) Otto-Sobotka, Fabian (Authorized examiners) Prerequisites Skills to be acquired in this module + Social skills+ Interdiscipl. knowlg.++ Maths/Stats/Progr.+ Scientific Englishstudents learn the use of the software R in application scenariosstudents learn to actively "speak" the programming language Rstudents practice statistical data analysis with R Module contents The lecture gives an intuitive introduction into the use of the statistics software R. We start by introducing the basic handling of R and the syntax of its programming language. We use those to obtain the first statistical analyses from R. The next important step is to create informative graphics to represent the statistical results. Finally, we look into programming concepts that allow for more complex statistical analyses. Reader's advisory Uwe Ligges - Programmieren mit R (2008) Springer.R Core Team - R: A language and environment for statistical computing (Reference Manual)Simon N. Wood - Generalized Additive Models: An Introduction with R (2006) Chapman & Hall Links Language of instruction English Duration (semesters) 1 Semester Module frequency annually , summer term Module capacity 24 Reference text Recommended previous knowledge / skills: basic statistical knowledge including regression analysis Modullevel / module level Modulart / typ of module Wahlpflicht / Elective Lehr-/Lernform / Teaching/Learning method Vorkenntnisse / Previous knowledge
Course type Comment SWS Frequency Workload of compulsory attendance
Lecture
2 SuSe 28
Exercises
2 SuSe 28
Total time of attendance for the module 56 h
Examination Time of examination Type of examination
Final exam of module
after the course
practical exercise