Universität Wien

240090 UE MM1 - Methods of Quantitative Research in Development Studies (2024S)

5.00 ECTS (2.00 SWS), SPL 24 - Kultur- und Sozialanthropologie
Continuous assessment of course work
ON-SITE
Moodle
Mo 06.05. 09:45-11:15 Seminarraum 7, Kolingasse 14-16, OG01

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).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Monday 11.03. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 18.03. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 08.04. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 15.04. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 22.04. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 29.04. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 13.05. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 27.05. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 03.06. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 10.06. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 17.06. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
Monday 24.06. 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. Its 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.

The course is taught on site.

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

Topics: descriptive statistics, probability, random variables, statistical inference, regression analysis, causal inference

Reading list

The course is strongly (but not exclusively) based on Newbold, Carlson and Thorne (2013): Statistics for Business and Economics, Pearson, 8th edition. Other introductory statistics textbooks (two examples below) provide similar treatments. Eventual additional materials will be listed in the course's syllabus.
- Larsen and Marx (2012): An Introduction to Mathematical Statistics and its Applications, Prentice Hall
- Shafer and Zhang (2012): Beginning Statistics (legally available online for free).

Association in the course directory

MM1

Last modified: Sa 17.02.2024 14:46