Stud.IP Uni Oldenburg
University of Oldenburg
29.11.2021 01:46:10
neu725 - Multivariate Statistics and Applications in R
Department of Neurosciences 6 KP
Module components Semester courses Wintersemester 2021/2022 Examination
Lecture
  • Limited access 6.02.111_1L - Multivariate statistics I Show lecturers
    • Prof. Dr. Andrea Hildebrandt

    Wednesday: 08:15 - 09:45, weekly (from 20/10/21)
    Dates on Monday. 21.02.22 08:00 - 10:00

    hybrid 59 students can attend in presence, the others can watch the recoreded lectures online. For participation in presence, you need to register for each session you want to attend by signing up to the respective group. The class in only open for Neurocognitive Psychology, Neuroscience and PhD students, NOT for Biology students.

Exercises
  • Limited access 6.02.111_1T - Multivariate statistics I (Tutorial) Show lecturers
    • Prof. Dr. Andrea Hildebrandt
    • Maira Keller

    Tuesday: 16:15 - 17:45, weekly (from 19/10/21)

    34 students can attend in presence, the others can attend online. For participation in presence, you need to register for each session you want to attend by signing up to the respective group. Additonal voluntary tutorial for the multivariate statistics lecture. If you are from another study program, please contact the teacher.

  • Limited access 6.02.111_2_Gr2 - analysis methods with R - group 2 online Show lecturers
    • Juan Felipe Quinones Sanchez

    Wednesday: 16:15 - 17:45, weekly (from 20/10/21)

    The first 3 classes will take place as BBB sessions, the other classes online with R markdown tutorials and BBB Q&A sessions from 16-17h. The course is open for Neurocognitive Psychology and Neuroscience students.

Notes for the module
Prerequisites
recommended in semester 1/3
weeks 11-13 of summer semester
Time of examination
End of winter semester
Module examination
written exam
attendance of at least 70% in the seminars (in addition, mandatory but ungraded)
Skills to be acquired in this module
Students will acquire basic knowledge in planning empirical investigations, managing and understanding quantitative data and conducting a wide variety of multivariate statistical analyses. They will learn how to use the statistical methodology in terms of good scientific practice and how to interpret, evaluate and synthesize empirical results from the perspective of statistical modeling in basic and applied research context. The courses in this module will additionally point out statistical misconceptions and help students to overcome them.

+ Independent research
+ Scient. Literature
+ Social skills
++ Interdiscipl. knowledge
++ Maths/Stats/Progr.
++ Data preset./disc.
+ Scient. English
++ Ethics


 

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