Stud.IP Uni Oldenburg
University of Oldenburg
14.08.2020 22:18:16
neu770 - Basics of Statistical Data Analysis (Complete module description)
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Module label Basics of Statistical Data Analysis
Module code neu770
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 Seminar (SE)
Total workload 113h: 28h contact / 20h background reading / 65h exercise solving
Faculty/Institute Department of Neurosciences
Used in course of study
  • Bachelor's Programme Physics, Engineering and Medicine (Bachelor) >
  • Master's Programme Biology (Master) >
  • Master's Programme Biology (Master) >
  • Master's Programme Neuroscience (Master) >
Contact person
Module responsibility
Authorized examiners
Entry requirements
Skills to be acquired in this module
+ Social skills
+ Interdiscipl. knowl.
++ Maths/Stats/Progr.
+ Scientific English

Upon successful completion of this course, students
have basic statistical competencies for understanding data
understand the main statistical methods and their practical use through application
can evaluate statistical methods regarding the qualities and their limits
Module contents
  • populations and samples; exploratory data analysis through describing statistics
  • elementary probabilities and random variables
  • important discrete and continuous distributions
  • estimating parameters through the method of maximum likelihood
  • confidence intervals and classical significance testing
  • pairs of random variables; distribution and dependence
  • classical regression analysis
  • basic use of the software R to apply those methods
Reader's advisory
Will be available in Stud.IP
Language of instruction English
Duration (semesters) 1 Semester
Module frequency annually, winter term
Module capacity unlimited
Modullevel ---
Modulart Wahlpflicht / Elective
Lern-/Lehrform / Type of program
Vorkenntnisse / Previous knowledge basic mathematical knowledge; une of probabilities
recommended in combination with neu720 Statistical programming with R
Course type Comment SWS Frequency Workload attendance
Lecture 2.00 28 h
Seminar 2.00 28 h
Total time of attendance for the module 56 h
Examination Time of examination Type of examination
Final exam of module
after the course
written exam, 2h