neu725 - Multivariate Statistics and Applications in R (Complete module description)
| Module label | Multivariate Statistics and Applications in R |
| Modulkürzel | neu725 |
| Credit points | 6.0 KP |
| Workload | 180 h
( 1,5 SWS Lecture (VO) )
Total workload 68h: 28h contact / 20h background reading / 20h exam preparation 2,5 SWS Supervised exercise (UE): Total workload 113h: 28h contact / 20h background reading / 65h exercise solving |
| Institute directory | Department of Neurosciences |
| Verwendbarkeit des Moduls |
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| Zuständige Personen |
Otto-Sobotka, Fabian (Module responsibility)
Otto-Sobotka, Fabian (Prüfungsberechtigt)
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| Prerequisites | |
| Skills to be acquired in this module | + Social skills + Interdiscipl. knowlg. ++ Maths/Stats/Progr. + Scientific English students learn the use of the software R in application scenarios students learn to actively "speak" the programming language R students 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. |
| Literaturempfehlungen | 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 |
| Form of instruction | Comment | SWS | Frequency | Workload of compulsory attendance |
|---|---|---|---|---|
| Lecture | 2 | SoSe | 28 | |
| Exercises | 2 | SoSe | 28 | |
| Präsenzzeit Modul insgesamt | 56 h | |||
| Examination | Prüfungszeiten | Type of examination |
|---|---|---|
| Final exam of module | after the course |
practical exercise |
