240090 UE MM1 - Methods of Quantitative Research in Development Studies (2023W)
Continuous assessment of course work
Labels
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 20.09.2023 10:00 to Mo 02.10.2023 09:00
- Deregistration possible until Tu 31.10.2023 09:00
Details
max. 30 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Monday
09.10.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
16.10.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
23.10.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
30.10.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
06.11.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
13.11.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
20.11.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
27.11.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
04.12.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
11.12.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
08.01.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
15.01.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
22.01.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Monday
29.01.
09:45 - 11:15
Seminarraum 7, Kolingasse 14-16, OG01
Information
Aims, contents and method of the course
This is a course in applied statistics. The main goal is for students to develop the foundations necessary to implement quantitative empirical research independently. For this purpose, they are required to carry out a number of "hands-on" applications. The course is taught at an introductory level.
Assessment and permitted materials
Students are graded according to three homeworks (20% each) and a final project (40%). Failure to hand in any of these implies a negative evaluation of the course.
Minimum requirements and assessment criteria
Students should prove a good command (at least 50%) of the course’s topics; 50% - 59% implies a 4; 60% - 69%, a 3; 70% - 84%, a 2; 85% - 100%, a 1.
Examination topics
Descriptive statistics, probability, random variables, statistical inference, regression analysis, causal inference
Reading list
The course has been prepared with three textbooks:Newbold, Carlson and Thorne (2013): Statistics for Business and Economics, Pearson, 8th edition, (NCT)Larsen and Marx (2012): An Introduction to Mathematical Statistics and its Applications, Prentice HallShafer and Zhang (2012): Beginning Statistics (legally available online for free), (SZ)Other introductory statistics textbooks are likely to provide very similar treatments.
Association in the course directory
MM1
Last modified: We 19.07.2023 13:47