Universität Wien

150009 UE Quantitative methods in research on Japan (2018S)

secondary data analysis

4.00 ECTS (2.00 SWS), SPL 15 - Ostasienwissenschaften
Continuous assessment of course work
Moodle

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. 25 participants
Language: German, English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 06.03. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 13.03. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 20.03. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 10.04. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 17.04. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 24.04. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 08.05. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 15.05. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 29.05. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 05.06. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 12.06. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 19.06. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
  • Tuesday 26.06. 13:00 - 14:30 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33

Information

Aims, contents and method of the course

This course offers an introduction into the methodology of quantitative research, with a focus on multivariate and descriptive statistics. Additionally, a small selection of more experimental methods, such as text mining and quantitative text analysis, may be introduced as well.

Participants will get the opportunity to explore the power of quantitative research methods using existing datasets from various international sources. The opportunity to collect and analyze their own datasets will be given to interested students as well.

This course also serves as a practical introduction into the most relevant data analysis software tools, specifically SPSS, RStudio and MS Excel.

SPSS can be acquired in the university's u:soft shop for ca. 25 € or used for free in the university's computer rooms.

RStudio is an open-source project and as such available free of charge from https://www.rstudio.com/products/rstudio/download/. Please also download R from the link at the bottom of the RStudio download page.

A free copy of MS Excel is available to students as part of the Office for Students package offered by the ZID.

Assessment and permitted materials

Regular attendance of the course is mandatory for a passing grade.

Assessment is based on reports, tests and active contribution in class or to online discussions.

Upon enrollment for this course, participants agree to perform all mandatory coursework by themselves and to use formally correct citations to denote the resources that were used for completion. Failure to do so will be considered plagiarism.

Minimum requirements and assessment criteria

As an introductory course, this course does not require any specific mathematical skills. However, a general curiosity for data and related topics will be an advantage when attending this course. Students who are not interested in data topics have the option to attend a second course on qualitative methods, provided that its topics are not identical to their first course on qualitative methods.

In order to receive a passing grade for this course as a whole, more than 50% of the following criteria must be assessed as "positive":

• Attendance and contributions to in-class and online discussions: 20%
• Homework assignments throughout the course: 30%
• Intermediate exam: 20%
• Final report: 30%

Examination topics

Students will learn:
• Fundamentals of quantitative research
• Searching for, obtaining and generating datasets
• Basic data processing in SPSS, R and Excel
• Interpreting and producing descriptive statistics
• Interpreting and producing basic test statistics
• Basics of regression analysis

Reading list

Pallant, Julie (2013).
SPSS survival manual. Maidenhead: McGraw-Hill Education.

Association in the course directory

JMA M4.2, M9

Last modified: Th 14.11.2024 00:13