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290254 PS Multivariat Regression Analysis (2013W)
Theoretical background and empirical application for geographers and spatial planners
Continuous assessment of course work
Labels
Termine Kursraum A (ZID) 18.45-20.15
DO 31.10. / DO 07.11.2013 / DO 14.11.2013 / DO 28.11.2013 / DO 05.12.2013Termine GIS-Labor (Computerkartographie) 18.45-20.15
DO 12.12.2013 / DO 09.01.2014 / DO 16.01.2014 / DO 23.01.2014 / DO 30.01.2014
DO 31.10. / DO 07.11.2013 / DO 14.11.2013 / DO 28.11.2013 / DO 05.12.2013Termine GIS-Labor (Computerkartographie) 18.45-20.15
DO 12.12.2013 / DO 09.01.2014 / DO 16.01.2014 / DO 23.01.2014 / DO 30.01.2014
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from We 11.09.2013 08:00 to We 25.09.2013 23:00
- Registration is open from Mo 30.09.2013 08:00 to Su 20.10.2013 23:00
- Deregistration possible until Fr 15.11.2013 23:00
Details
max. 30 participants
Language: German
Lecturers
Classes (iCal) - next class is marked with N
- Thursday 03.10. 18:45 - 20:15 Hörsaal 4C Geographie NIG 4.OG C0409
- Thursday 10.10. 18:45 - 20:15 Hörsaal 4C Geographie NIG 4.OG C0409
- Thursday 17.10. 18:45 - 20:15 Hörsaal 4C Geographie NIG 4.OG C0409
- Thursday 21.11. 18:45 - 20:15 Hörsaal 4C Geographie NIG 4.OG C0409
Information
Aims, contents and method of the course
Assessment and permitted materials
Minimum requirements and assessment criteria
Examination topics
Reading list
Association in the course directory
(B11-8.1) (MG-W5-PI) (MR1-a-PI) (L2-FW)
Last modified: Mo 07.09.2020 15:42
The aim of the lecture is to provide the students with a solid understanding of the basic principles and theoretical underpinnings of multivariate regression analysis with a special focus on geographical applications. The alternation of theoretically and more applied lectures builds the basic organizational principle of the course. An emphasis is placed upon intuitive understanding without neglect of basic mathematical and statistical derivations. We will use standard software packages such as Excel, R or Stata.