290026 UE Key Methods in Analysing Migration and Population Dynamics (2023W)
Quantitative Methods
Continuous assessment of course work
Labels
Note! Modules "290026 UE Key Methods in Analysing Migration and Population Dynamics (2023W)" and "290027 SE Migration and Population Dynamics in the Context of Global Change and Development (2023W)" work together and have been developed jointly. They cannot be taken individually, but only paired.
Therefore, registration for this UE is not possible. If you are registered for 290027 after the registration period, you will also be registered for 290026.
Therefore, registration for this UE is not possible. If you are registered for 290027 after the registration period, you will also be registered for 290026.
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 Mo 04.09.2023 09:00 to Mo 18.09.2023 09:00
- Deregistration possible until Tu 31.10.2023 23:59
Details
max. 23 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 03.10. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 10.10. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 24.10. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 07.11. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 21.11. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 28.11. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 05.12. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 12.12. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 09.01. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 16.01. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 23.01. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Tuesday 30.01. 15:00 - 17:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
Information
Aims, contents and method of the course
Assessment and permitted materials
• Tutorial Video on one data analysis/EDA chosen from a list of possibilities (50%)
• Short oral interview based on the topics covered during the class (30%)
• Presence, participation & session preparation (20%)Participants will work in groups to develop the tutorial video and individually (with the short oral interview).
• Short oral interview based on the topics covered during the class (30%)
• Presence, participation & session preparation (20%)Participants will work in groups to develop the tutorial video and individually (with the short oral interview).
Minimum requirements and assessment criteria
Attendance in at least 80% of the course sessions. In the case of illnesses that are confirmed by a doctor's note, additional absenteeism can be compensated by additional written assignments.
The tutorial video (50%) and interview (30%) will be marked as well as active participation and session preparation (20%). Assignments must be passed individually. An assignment is passed with a minimum grade of 4.
Grading scheme:
100 - 87 % - grade 1
86- 75 % - grade 2
74 - 62 % - grade 3
61 - 50 % - grade 4
less than 50% - grade 5
The tutorial video (50%) and interview (30%) will be marked as well as active participation and session preparation (20%). Assignments must be passed individually. An assignment is passed with a minimum grade of 4.
Grading scheme:
100 - 87 % - grade 1
86- 75 % - grade 2
74 - 62 % - grade 3
61 - 50 % - grade 4
less than 50% - grade 5
Examination topics
The examination will encompass the work items as outlined in the course requirements. The examination material includes the documents used to create the tutorial video, the video itself and the portfolio.
The ability to acquire the reasoning necessary to manipulate and analyse cross-sectional data with R is the focus of the course and its assessment.
AI-related applications can be used. The interests and implications of these tools will be discussed during the semester.
The ability to acquire the reasoning necessary to manipulate and analyse cross-sectional data with R is the focus of the course and its assessment.
AI-related applications can be used. The interests and implications of these tools will be discussed during the semester.
Reading list
In Clifford, Cope, Gillespie - Key Methods in Geography 2010 [Chapter 5 Paul White Making Use of Secondary Data; Chapter 6 Sara L. McLafferty Conducting Questionnaire Surveys; Chapter 21 Richard Field Data Handling and Representation; Chapter 23 Danny Dorling Using Statistics to Describe and Explore Data]
Vartanian, T. P. (2010). Secondary data analysis. Oxford University Press.Website:
R for Data Science https://r4ds.had.co.nz/index.html
R Cookbook https://rc2e.com/
Vartanian, T. P. (2010). Secondary data analysis. Oxford University Press.Website:
R for Data Science https://r4ds.had.co.nz/index.html
R Cookbook https://rc2e.com/
Association in the course directory
(MG21 APF MIGSPEC) (MR1)
Last modified: Mo 02.10.2023 12:28
• the ability to immerse oneself in a particular topic (that of migration and population dynamics
• the ability to use exploratory data analysis methods (involving a basic understanding of multivariate statistics)
• the motivation and ability to get started with programming with R.Note! Modules "290027 SE Migration and Population Dynamics in the Context of Global Change and Development (2023W)" and "290026 UE Key Methods in Analysing Migration and Population Dynamics (2023W)" work together and have been developed jointly. They cannot be taken individually, but only paired.